tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 2 • 2022 309 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(2), 309-314. trade openness, industrialization, urbanization and pollution emissions in gcc countries: a way towards green and circular economies haider mahmood* department of finance, college of business administration, prince sattam bin abdulaziz university, 173 alkharj 11942, saudi arabia.*email: h.farooqi@psau.edu.sa received: 15 december 2021 accepted: 01 march 2022 doi: https://doi.org/10.32479/ijeep.12716 abstract the gcc countries are moving toward circular and green economies in their long-run visions. this transformation is accelerating the industrialization, urbanization, economic growth, and trade openness (to) in the region. this present study examines the effects of these economic indicators on pollution emissions in the gcc panel from 1980 to 2019 using panel techniques. we found the environmental kuznets curve. moreover, to is helping reduce co2 emissions. hence, economic growth and to are helping the gcc region to follow the track of green and circular economies. in short run, to also reduces emissions. industrialization and urbanization accelerate emissions in long run. thus, both indicators have environmental consequences in the gcc region in the long run. however, these indicators could not harm the in short run. to follow the track of green and circular economies, the study recommends increasing trade openness in the region and imposing carbon taxes on industrialization and urbanization to reduce their environmental consequences. keywords: trade openness, industrialization, urbanization, co2 emissions jel classifications: f18, l16, p25 1. introduction while framing the determinants of pollution emissions, after trade agreements of north america, grossman’s and krueger (1991) study is among the pioneers in working on determinants of pollution emissions, which hightligted the role of economic growth. because the increasing economic activities with rising economic growth and trade would boost energy usage and pollution emissions, termed as scale effect. conversely, these variables would help transfer cleaner technologies in the economies and shift the production from dirty to cleaner processes, which are termed as technique and composition effects. hence, growth and trade could help the economies follow the track of green and circular economies. claessens and feijen (2007) claimed that the financial sector could play an influential role in supporting government policies to promote cleaner technologies. but, fossil fuels are significant sources of energy demand in gcc countries. hence, it is vital to test the role of growth and trade policies on pollution emissions in the gcc region to test whether both have scale or technique effects at large in the region. another stream of literature focused on the population’s role in pollution emissions and economic growth. for instance, raskin (1995) suggested methods of estimating the contribution that pollution has on environmental change. using the specification of i = pat, the model indicated that impact (i) is equal to the production of the population (p), affluence (a), and technology (t), based on theoretical concepts of ehrlich and holdren (1971). york et al. (2002; 2003) used this framework and reported a significant this journal is licensed under a creative commons attribution 4.0 international license mahmood: trade openness, industrialization, urbanization and pollution emissions in gcc countries: a way towards green and circular economies international journal of energy economics and policy | vol 12 • issue 2 • 2022310 role of urbanization in emissions. the same is the case with industrialization, and more focus on the industry can result in higher co2 emissions. it is mentioned that even when a country is able to achieve a certain level of development, there are still possibilities that the environmentally degrading impacts will keep on increasing. hence, both urbanization and industrialization could have environmental consequences in the economies. due to intensive urbanization and other factors, climate change is an alarming issue in today’s life. the fossil fuels is pouring oil on the fire, so a need to avoid using fossil fuels arises but whether we can afford to abandon it or not is a question, especially when we see that energy consumption is still heavily based on coal, gas, and oil in the world. there is a need to balance energy use to spur economic growth and avoid environmental damage. finding a balance between environment and growth is very difficult to address, but we can avoid this situation if we shift the debate to energy origins. renewable energy is supposed to impact the environment positively, and it may contribute to economic growth as well. however, the energy production in gcc countries is rising and causing economic growth with carbon emission. global emissions from the energy sector hit a new high, but cleaner energy may help tackle climate change and pollution. decarbonized power can also reduce co2 emissions in other sectors using energybased liquids, including hydrogen or synthetic liquid fuels. as the atmosphere shifts, we need to be more aware of how we use it. it would be exacerbated if industrialized countries settled on a method to price carbon, allowing us to be more conscious of a basic need we have largely taken for granted due to oil costs and shift our perspective on a fundamental need we have primarily embraced as natural. as the selected gcc sample, economic growth seemed to increase environmental degradation due to excessive reliance on fossil fuels. with time, the contribution of this environmentally degrading energy is declining, but these gcc countries still rely on them primarily. the region needs to develop efficient ways of sustainable energy consumption further so that the economy and environment can go hand in hand. excessive reliance on nonrenewable energy can ruin the environment and not be sustainable for the energy and power market. for instance, how much trade a country has, how much energy, including renewable and nonrenewable, is being consumed in the country, how much urbanization is accelerating over time, how the industrial sector is structured, and many more aspects can help determine the co2 emissions profile of an economy. as per these discussions, some research has been conducted to test the effect of urbanization, industrialization, oil sector, financial sector, and foreign investment on emissions in some gcc nations (alsamara et al., 2018; al-mulali and lee, 2013; mahmood et al., 2020; rafindadi et al., 2018). in this domain, we cannot ignore the role of economic growth, which may have a deep impact on the environment. the environemt is also greatly affected by urbanization, trade, and industrialization, which eventually increase energy demand and would pollute the economy. the testing of the effects of economic growth, urbanization, trade, and industrialization on co2 emissions is well motivated in gcc region. hence, there is a still need to conduct comprehensive research to have deep inside of these variables in a panel analysis of the whole gcc region, which is targeted by this present research. 2. literature review wang et al. (2019) talked about how urbanization can lead to co2 emissions and indicated that many sectors, including agriculture, forestry, fishery, water conservancy, animal husbandry, and many more, get influenced by these higher co2 emissions. industrial areas and urbanization usually have to depend on fuel consumption, which primarily has to be oil in the middle eastern region. therefore, the more significant effect of urbanization is on the oil segment, which eventually worsens the environment because of resource depletion. the same findings are reported in the case of vietnam (fan et al., 2019), in pakistan (ali et al., 2019), and china (liang and yang, 2019). 2018 et al. (2019) found that urbanization and development of the cities are responsible for increasing temperature during heatwaves. mahmood et al. (2019) considered and validated the environmental kuznets curve (ekc) in egypt during 1990-2014. moreover, foreign investments reduce co2 emissions, and energy usage increases emissions. however, trade could not affect the emissions in egypt. plakolb et al. (2019) argued that traffic in an urban area is responsible for increasing co2 emissions and nox emissions, which may contribute to global warming. talking about environmental technologies and how they can reduce co2 emissions, alatas (2021) mentioned that environmental technologies do not affect the transport industry. however, energy consumption can help determine the emissions of a country while the effect of urbanization is insignificant. the results are contradictory to a few studies that argue that environmental technologies help to control emissions (alvarez-herranz et al., 2017a; li et al., 2021; alvarezherranz et al., 2017b). some literature also focuses an impact of financial development (fd) in determining emissions (jalil and feridun, 2011; dasgupta et al., 2001; chousa et al., 2009; zhang, 2011; sadorsky, 2010). chousa et al. (2009) investigated the us and japan and found that economin growth and fd helped reduce emissions. dasgupta et al. (2001) argued that capital markets re-act for any environmental regulations and could perform well to support the environment if a proper financial incentive is provided. sadorsky (2010) investigated some emerging economies from 1990-2006 and found that capital markets have strong ties with energy usage and, hence, affect emissions in economies. in china, zhang (2011) described an effect of fd on emissions, and the capital market has a greater impact on emissions than that of the banking sector. moreover, foreign investments reduced the emissions in china. conversely, jalil and feridun (2011) reported a negative effect of fd. however, trade, income, and energy usage have contributed to emissions in china. in the trade and emissions relationship, jiang et al. (2019) argued that developing countries could reduce their emissions by involving sustainable trade deals. but, the effect of trade was found positive on carbon emissions in the empirical exercise. moreover, aller et al. (2015) displayed the same results in the case of developing countries. alam and murad (2020) argued that trade openness promoted technological development in countries, mahmood: trade openness, industrialization, urbanization and pollution emissions in gcc countries: a way towards green and circular economies international journal of energy economics and policy | vol 12 • issue 2 • 2022 311 which fostered the use of renewable energy mix and could reduce pollution emissions. mutascu (2018) investigated and found a positive link between trade openness (to) and emissions. moreover, bi-directional association between both has also been reported. hence, increasing pollution also fosters more trading activities. shahbaz et al. (2017) found that to increased pollution emissions through scale effects. le and ozturk (2020) tested the cross-dependence in a panel of 47 economies to test the ekc from 1990-2014 and confirmed a positive effect of globalization, and fd also accelerated the emissions in the target economies. moreover, energy use also contributed to emissions significantly. sarkodie and ozturk (2020) tested the ekc for kenya during 1971-2013 and validated this hypothesis. moreover, urbanization accelerated pollution emissions in kenya. al-mulali et al. (2016) provided confirmation of the ekc with higher use of renewables in the economies. hence, renewable use helped reduce emissions. al-mulali et al. (2015) inquired vietnam from 1981-2011. the authors reported that imports and fossil fuels accelerated the emissions. however, exports and renewables could not affect the emissions in vietnam. solarin et al. (2017) explored the ekc from 1965 to 2013 in china and india and validated the hypothesis. the authors also reported the positive impact of urbanization and hydropower reduced emissions in the economies. alsamara et al. (2018) explored the gcc region and corroborated the positive impacts of income and exports. however, fd was found helpful in reducing emissions. on the other hand, al-mulali and lee (2013) corroborated the positive effect of fd and economic growth on emissions in gcc region. rafindadi et al. (2018) also probed the gcc region and a negative impact of foreign investment on emissions was reported. in saudi arabia, mahmood et al. (2020) investigated and observed positive effects of oil price and urban population on co2. mahmood and alanzi (2020) scrutinized and corroborated the positive role of the rule of law in saudi arabia to reduce co2 emissions. however, the effect of income growth could not be validated. in gcc, al-mulali and ozturk (2014) investigated and corroborated electricity and growth relationship, which may also have environmental consequences because of the heavy reliance of electricity on fossil fuels in gcc economies. literature has highlighted the role of urbanization, industry, trade, and economic growth on pollution emissions. however, the gcc region is still under-investigated in this context, and this present research motivates this issue in deep panel data analyses. 3. methods increasing trade would have a scale effect on pollution emissions. on the other hand, it may also have technique and composition effects and create pleasant environmental effects. the net impact of trade in any economy or group is an empirical question. the same description may be provided for economic growth and to test the ekc. moreover, urbanization and industrialization would also accelerate due to economic growth. hence, we test the effect of all these variables on emissions in gcc economies in the following way: lcoit = f (lyit, lyit 2, ltoit, lupit, liit) (1) lcoit is co2 emissions per capita. lyit and lyit 2 are economic growth and its square and are regressed to test the ekc in 6 gcc economies. t is the period of 1980-2019. ltoit is trade openness and is a share of trade in total income. lupit is urban population share of aggregate population. liit is industrialization and measured by industry’s share in income. all series are transformed in a natural log. data on emissions is from global carbon atlas (2021), and rest is from world bank (2021). after hypothesizing the model, the integration level will be tested by im-pesaran-shin (ips) of im et al. (2003) and fisher-augmented dickey fuller (adf) and fisher-phillip and perron (pp) tests of maddala and wu (1999). then, johansen (1988) cointegration will be tested using maddala and wu (1999) aggregation procedure: y ln pii n � � ��2 1 ( )( ) (2) afterward, the robustness of cointegration can be verified using the residual base procedure of kao (1999) and seven statistics of pedroni (2004). then, we may proceed to pesaran et al. (1999) for long and short-run analyses in the following way: � � � � � � � � � � � �� � � �lco lco ly ly it i j p j i t j i tj q j i t � � � � 1 1 1 1 1 1 0 1 2 , , , ��� � �� � �� � � � � � �� � � � �120 1 3 1 0 1 4 1 0 1 0 1 j q j i tj q j i tj q j q lto lup� �, , �� � � � � �� � � � � �5 1 1 1 21 1 22 1 2 23 j i t i t i t i t i t li µ lco µ ly µ ly µ lto , , , , , 11 24 1 25 1 1� � ��� �µ lup µ ii t i t it,� , (3) � � � � � � � � � � � �� � � �lco lco ly ly it i j p j i t j i tj q j i t � � � � 2 1 1 1 1 1 0 1 2 , , , ��� � �� � �� � � � � � � � � � � � 1 2 0 1 3 1 0 1 4 1 0 1 0 1 j q j i tj q j i tj q j q lto lup � � , , �� � � ��� ��5 1 3 1 2j i t i t itli µ ect, , (4) above equations are pooled mean group (pmg). a statistically negative may be verified the convergence. long and short runs results can be produced from equations 3 and 4. afterward, we use pedroni’s (2000) fully modified ordinary least square (fmols) and kao and chiang’s (2000) dynamic ordinary least square (dols), which may modify the estimated parameters in the following way: ( )  ( )'1 1 1 1ˆ ˆ / ( )εµβ χ ++ = = = =   = σ σ − + ∆ σ σ −     n t n t fmols n t it i it i t it iy y t y y (5) ' 1 1 . 1 /β̂ + = = =  =    ∑ ∑ ∑ t n t dols it it it itt i t t x x x x (6) the results from equations 5 and 6 can be utilized to check the robustness of pmg results. mahmood: trade openness, industrialization, urbanization and pollution emissions in gcc countries: a way towards green and circular economies international journal of energy economics and policy | vol 12 • issue 2 • 2022312 4. data analyses at first, we test the unit root and find that lcoit and lyit are nonstationary and δlcoit and δlyit are stationary. moreover, most results support stationarity in the level and first differences of the rest of the variables. hence, mixed order is confirmed in the analyses table 1. in table 2, cointegration is confirmed with fisher-johansen test. moreover, the pedroni test also validates it with 2 statistics and 1 weighted statistics. hence, we may claim cointegration in the model and proceed with further analyses. table 3 reflects long and short-run results from 3 techniques to test the robustness of findings. lyit has, and lyit 2 has negative parameters and corroborate the ekc in all estimations of gcc economies. the effect of ltoit is negative in 3 estimates. it affirms that the trade openness of the whole gcc region is helping reduce co2 emissions. it may be because high-income gcc economies are importing cleaner technologies, which help clean the environment in the economies to support the concept of green economies. moreover, the openness of economies helps to transfer cleaner technologies. it would help transform from oil to other relatively cleaner sectors in gcc economies, which reduce the co2 emissions and promote the green economies in the gcc region. hence, trade openness has greater composition and technique effects, which are larger than scale effects of trade. contrarily, literature corroborated positive impact of to on pollution (alam and murad, 2020; aller et al., 2015; jiang et al., 2019; mutascu, 2018; shahbaz et al., 2017). the parameter of lupit is positive in table 1: unit root tests series ips fisher-adf fisher-pp constant constant and trend constant constant and trend constant constant and trend lcoit −0.6604 (0.2057) −0.8871 (0.1875) 13.9498 (0.3039) 15.7985 (0.2006) 16.4233 (0.1726) 19.2199 (0.0834) lyit 1.5538 (0.9399) −0.3881 (0.2985) 4.3099 (0.9772) 15.8655 (0.1912) 3.5852 (0.9898) 13.4388 (0.3380) ltoit −2.1080 (0.0175) −2.1993 (0.0139) 25.3165 (0.0134) 23.2635 (0.0256) 21.3963 (0.0449) 14.9533 (0.2440) lupit −0.2492 (0.4016) −3.7995 (0.0001) 11.9507 (0.4496) 38.2207 (0.0001) 72.1514 (0.0000) 103.6020 (0.0000) liit −2.7001 (0.0035) −1.7062 (0.0440) 28.7905 (0.0042) 19.9373 (0.0683) 22.7920 (0.0295) 12.1716 (0.4320) δlcoit −10.1545 (0.0000) −9.1399 (0.0000) 110.3270 (0.0000) 90.9006 (0.0000) 168.7660 (0.0000) 207.0790 (0.0000) δlyit −6.9172 (0.0000) −5.6417 (0.0000) 69.6576 (0.0000) 52.2182 (0.0000) 110.0770 (0.0000) 93.4694 (0.0000) δltoit −9.9312 (0.0000) −8.8646 (0.0000) 107.0890 (0.0000) 86.8083 (0.0000) 138.5440 (0.0000) 345.4870 (0.0000) δlupit −2.5140 (0.0060) −0.1607 (0.4362) 26.1117 (0.0103) 12.4333 (0.4115) 29.0031 (0.0039) 10.7798 (0.5479) δliit −9.5594 (0.0000) −8.7243 (0.0000) 102.8090 (0.0000) 85.0609 (0.0000) 121.4800 (0.0000) 115.4350 (0.0000) table 2: cointegration analyses stat. p-value weighed stat. p-value pedroni (2004) v −0.2825 0.6112 −0.4537 0.6750 rho 0.0631 0.5251 −0.1556 0.4382 pp −1.3456 0.0892 −1.6398 0.0505 adf −0.7948 0.2134 −0.8203 0.2060 grouped-rho 0.4547 0.6753 grouped-pp −1.6423 0.0503 grouped-adf −0.8581 0.1954 kao (1999) stat −2.6770 0.0037 variance 0.0177 maddala and wu (1999) cointegrating vectors trace statistics max-eigen statistics 0 81.67 0.0000 37.58 0.0002 1 49.10 0.0000 24.57 0.0170 2 29.99 0.0028 11.64 0.4749 3 24.92 0.0152 12.53 0.4042 4 22.69 0.0305 18.92 0.0906 5 22.17 0.0356 22.17 0.0356 mahmood: trade openness, industrialization, urbanization and pollution emissions in gcc countries: a way towards green and circular economies international journal of energy economics and policy | vol 12 • issue 2 • 2022 313 all estimates. so, the increasing urban population is enhancing co2 emissions in the gcc region. hence, urbanization is damaging the environment of the gcc region by releasing emissions. many studies reported positive impact of urbanization on pollution (plakolb et al., 2019; sarkodie and ozturk, 2020; wang et al., 2019; solarin et al., 2017). the coefficient of liit is also positive in all estimates. therefore, increasing industrialization is augmenting co2 emissions in the gcc region. hence, industrialization is not healthy for the environment of the gcc region and promotes co2 emissions. ectt−1 has negative parameter as per expectations and confirms the convergence in case of disequilibrium. hence, equilibrium relationships are corroborated in pmg estimates. the lag of trade openness reduced emissions, and it also helps reduce co2 emissions. however, most of the effects are insignificant in the short run. therefore, we conclude that trade and urbanization take a long time to affect the environment in the gcc region. 5. conclusions trade, industrialization, and urbanization could have environmental consequences and affect circular economies. the effects of these variables on emissions in gcc region from 1980-2019 were investigated. we substantiated ekc hypothesis in whole region and income growth would help support green economies in the gcc region. moreover, to has a negative effect. so, trade openness is also helping in clean technology transfers in the gcc region. moreover, it also promotes cleaner production processes in the region and is changing the composition of production in the region. hence, trade openness fosters the concept of green and circular economies in the gcc region. increasing urbanization augmenting co2 emissions. thus, the urban population is destructive for the environment in the gcc region by releasing co2 emissions. further, industrialization puts fuel on the fire and increases co2 emissions in the region. hence, industrialization and urbanization have an environmental hazard in the gcc region and de-tracking the gcc region from green economies. most short-run effects are found insignificant. hence, urbanization and industrialization require a long time to have adverse environmental effects. moreover, to is also promoting the green economies in the gcc region. based on the results, we recommend further enhancing trade openness in gcc economies to enjoy its pleasant environmental effects in the region. conversely, the urban population and industries should be penalized with carbon taxes to reduce their environmental effects, and the carbon revenue could invest in clean technologies to follow the track of circular and green economies in the gcc region. 6. funding and acknowledgement this project was supported by the deanship of scientific research at prince sattam bin abdulaziz university under the research project # 2021/02/18338. references alam, m., murad, w. (2020), the impacts of economic growth, trade openness and technological progress on renewable energy use in organization for economic co-operation and development countries. renewable energy, 145(1), 382-390. alatas, s. (2021), do environmental technologies help to reduce transport sector co2 emissions? evidence from the eu15 countries. research in transportation economics. ali, r., bakhsh, k., yasin, m. (2019), impact of urbanization on co2 emissions in emerging economy: evidence from pakistan. sustainable cities and society, 48, 101553. aller, c., ductor, l., herrerias, m. (2015), the world trade network and the environment. energy economics, 52, 55-68. al-mulali, u., lee, j.y.m. (2013), estimating the impact of the financial development on energy use: evidence from the gulf cooperation council (gcc) countries. energy, 60, 215-221. al-mulali, u., ozturk, i. (2014), are energy conservation policies effective without harming economic growth in the gulf cooperation council countries? renewable and sustainable energy reviews, 38, 639-650. al-mulali, u., ozturk, i., solarin, s.a. (2016), investigating the environmental kuznets curve hypothesis in seven regions: the role of renewable energy. ecological indicators, 67, 267-282. al-mulali, u., saboori, b, ozturk, i. (2015), investigating the environmental kuznets curve hypothesis in vietnam. energy policy, 76, 123-131. alsamara, m., mrabet, z., saleh, a.s., anwar, s. (2018), the environmental kuznets curve relationship: a case study of the gulf table 3: regression results variable parameter standard error t-stat. p-value fmols lyit 2.7140 0.9084 2.9876 0.0031 lyit 2 −0.1332 0.0458 −2.9074 0.0040 ltoit −0.4773 0.1456 −3.2789 0.0012 lupit 1.5173 0.4094 3.7061 0.0003 liit 0.6360 0.2082 3.0544 0.0025 dols lyit 5.2971 1.3195 4.0145 0.0001 lyit 2 −0.2662 0.0670 −3.9736 0.0001 ltoit −0.4661 0.2249 −2.0726 0.0403 lupit 1.6782 0.7458 2.2502 0.0262 liit 0.6245 0.3517 1.7753 0.0784 pmg lyit 3.2255 1.2459 2.5889 0.0105 lyit 2 −0.1752 0.0636 −2.7563 0.0065 ltoit −0.6157 0.2382 −2.5848 0.0107 lupit 2.4961 0.4237 5.8910 0.0000 liit 1.2270 0.3129 3.9208 0.0001 ectt−1 −0.2797 0.0782 −3.5776 0.0005 δlcoit−1 0.0244 0.0723 0.3370 0.7366 δlyit 0.0985 2.1510 0.0458 0.9636 δlyit−1 1.4686 1.7461 0.8411 0.4016 δlyit 2 0.0147 0.1106 0.1334 0.8941 δlyit−1 2 −0.0809 0.0908 −0.8909 0.3743 δltoit −0.4102 0.3389 −1.2102 0.2280 δltoit−1 −0.6374 0.2148 −2.9675 0.0035 δlupit −3.3750 2.5454 −1.3260 0.1868 δlupit−1 1.2396 1.5861 0.7816 0.4356 δliit −0.2295 0.1466 −1.5651 0.1196 δliit−1 0.3597 0.2712 1.3262 0.1867 intercept −8.5059 2.3794 −3.5748 0.0005 mahmood: trade openness, industrialization, urbanization and pollution emissions in gcc countries: a way towards green and circular economies international journal of energy economics and policy | vol 12 • issue 2 • 2022314 cooperation council region. environmental sciences and pollution research, 25, 33183-33195. alvarez-herranz, a., balsalobre, d., lorente, j., cantos, m., shahbaz, m. (2017a), energy innovations-ghg emissions nexus: fresh empirical evidence from oecd countries. energy policy, 101, 90-100. alvarez-herranz, a., lorente, d., shahbaz, m., cantos, j. (2017b), energy innovation and renewable energy consumption in the correction of air pollution levels. energy policy, 105, 386-297. chousa, p.j., tamazian, a., vadlamannati, c. (2009), does higher economic and financial development lead to environmental degradation: evidence from bric countries. energy policy, 37, 246-253. claessens, s., feijen, e. (2007), financial sector development and the millennium development goals. world bank working paper no. 89. dasgupta, s., laplante, b., mamingi, n. (2001), pollution and capital markets in developing countries. journal of environmental economics and management, 42, 310-335. ehrlich, p., holdren, j. (1971), impact of population growth. science, 171, 1212-1217. fan, p., ouyan, z., nguyen, d., nguyen, t., park, h., chen, j. (2019), urbanization, economic development, environmental and social changes in transitional economies: vietnam after daimio. landscape and urban planning, 187, 145-155. g l o b a l c a r b o n a t l a s . ( 2 0 2 1 ) , av a i l a b l e f r o m : h t t p : / / w w w. globalcarbonatlas.org/en/co2-emissions grossman, g.m., krueger, a.b. (1991), environmental impacts of the north american free trade agreement, nber working paper no. 3914. han, l., zhuo, w., li, w., qian, y. (2018), urbanization strategy and environmental changes: an insight with relationship between population change and fine particulate pollution. science of the total environment, 642, 789-799. huang, b., ni, g.h., grimmond, c.s.b. (2019), impacts of urban expansion on relatively smaller surrounding cities during heat waves. atmosphere, 10(7), 00364. im, k.s., pesaran, m.h., shin, y. (2003), testing for unit roots in heterogeneous panels. journal of econometrics, 115, 53-74. jalil, a., feridun, m. (2011), the impact of growth, energy and financial development on the environment in china: a co-integration analysis. energy economics, 33, 284-291. jiang, m., an, h., gao, x., liu, s., xi, x. (2019), factors driving global carbon emissions: a complex network perspective. resources conservation and recycling, 146, 431-440. johansen, s. (1988), statistical analysis of co-integration vectors. journal of economic dynamics and control, 12, 231-254. kao, c. (1999), spurious regression and residual-based tests for cointegration in panel data. journal of econometrics, 90, 1-44. kao, c., chiang, m.h. (2000), on the estimation and inference of a co-integrated regression in panel data. advance econometrics, 15, 179-222. le, h.p., ozturk, i. (2020), the impacts of globalization, financial development, government expenditures, institutional quality on co2 emissions in the presence of environmental kuznets curve. environmental science and pollution research, 27, 22680-22697. li, w., elheddad, m., doytch, n. (2021), the impact of innovation on environmental quality: evidence for the non-linear relationship of patents and co2 emissions in china. journal of environmental management, 292, 112781. liang, w., yang, m. (2019), urbanization, economic growth and environmental pollution: evidence from china. sustainable computing: informatics and systems, 21, 1-9. maddala, g.s., wu, s. (1999), a comparative study of unit root tests with panel data and a new simple test. oxford bulletin of economics and statistics, 61, 631-652. mahmood, h., alanzi, a.a. (2020), rule of law and environment nexus in saudi arabia. international journal of energy economics and policy, 10(5), 7-12. mahmood, h., alkhateeb, t.t.y., al-qahtani, m.m.z., allam, z., ahmad, n., furqan, m. (2020), urbanization, oil price and pollution in saudi arabia. international journal of energy economics and policy, 10(2), 477-482. mahmood, h., furqan, m., alkhateeb, t.t.y., fawaz, m.m. (2019), testing the environmental kuznets curve in egypt: role of foreign investment and trade. international journal of energy economics and policy, 9(2), 225-228. mutascu, m. (2018), a time-frequency analysis of trade openness and co2 emissions in france. energy policy, 115, 443-455. pedroni, p. (2000), fully modified ols for heterogeneous co-integrated panels. advance econometrics, 15, 93-130. pedroni, p. (2004), panel co-integration: asymptotic and finite sample properties of pooled time series tests with an application to the ppp hypothesis. economic theory, 20, 579-625. pesaran, m.h., shin, y., smith, r. (1999), pooled mean group estimator of dynamic heterogeneous panels. journal of american statistical association, 94, 621-634. plakolb, s., jager, g., hofer, c., fullsack, m. (2019), mesoscopic urban-traffic simulation based on mobility behavior to calculate nox emissions caused by private motorist transport. atmosphere, 10(6), 00293. rafindadi, a.a., muye, i.m., kaita, r.a. (2018), the effects of fdi and energy use on environmental pollution in predominantly resourcebased economies of the gcc. sustainable energy technologies and assessment, 25, 126-137. raskin, p. (1995), methods for estimating the pollution contribution to environmental change. ecological economics, 15, 225-233. sadorsky, p. (2010), the impact of financial development on energy consumption in emerging economies. energy policy, 38, 2528-2535. sarkodie, s.a., ozturk, i. (2020), investigating the environmental kuznets curve hypothesis in kenya: a multivariate analysis. renewable and sustainable energy reviews, 117, 109481. shahbaz, m., nasreen, s., ahmed, k., hammoudeh, s. (2017), trade openness-carbon emissions nexus: the importance of turning points of trade openness for country panels. energy economics, 41, 221-232. solarin, s.a., al-mulali, u., ozturk, i. (2017), validating the environmental kuznets curve hypothesis in india and china: the role of hydroelectricity consumption. renewable and sustainable energy reviews, 80, 1578-1587. wang, y., luo, x., zhao, m., wang, b. (2019), exploring the spatial effect of urbanization on multi-sectoral co2 emissions china. atmospheric pollution research, 10(5), 1610-1620. world bank. (2021), world development indicators. washington, dc, usa: the world bank. york, r., rosa, e., dietz, t. (2002), bridging environmental science with environmental policy: plasticity of population, affluence and technology. social science quarterly, 83(1), 18-34. york, r., rosa, e., dietz, t. (2003), stripat, ipat and impact: analytic tools for unpacking the driving forces of environmental impacts. ecological economics, 46, 351-365. zhang, y.j. (2011), the impact of financial development on carbon emissions: an empirical analysis in china. energy policy, 39(4), 2197-2203. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 5 • 2022332 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(5), 332-341. climate change, poverty and income inequality linkage: empirical evidence from nigeria evelyn nwamaka ogbeide-osaretin1*, bright orhewere2, oseremen ebhote3, sadiq oshoke akhor4, israel o. imide5 1department of economics, faculty of arts, mgt. a social sciences, edo state university uzairue, edo state, nigeria, 2department of economics, western delta university, oghara, delta state, nigeria, 3department of business administration, faculty of arts, mgt. a social sciences, edo state university uzairue, edo state, nigeria, 4department of accounting, faculty of arts, mgt. & social sciences, edo state university uzairue, edo state, nigeria, 5department of economics, university of delta, agbor, delta state nigeria. *email: osaretin.evelyn@edouniversity.edu.ng received: 02 july 2022 accepted: 05 september 2022 doi: https://doi.org/10.32479/ijeep.13556 abstract there seems to be a vicious cycle between climate change and income inequality. hence, this study examined the existence of a feedback relationship between climate change and income inequality in nigeria. the study employed an annual data series for the period from 1980 to 2020 which was estimated with the dynamic ordinary least square. income inequality was measured by gini while climate change was captured by temperature. the upshot of the study revealed that there is a feedback substantial connectivity between climate change and income inequality. the impact of climate change on income inequality conformed to the u-shaped hypothesis. other factors of climate change were population growth, economic development, and emission of carbon dioxide. hence, the study pertinently advocates and recommends effective population control, reduction of income inequality through the provision of employment and education, and the supply of modern and efficient energy in the purse of economic growth and development. keywords: climatic change, economic development, gini coefficient, poverty; nigeria jel classifications: c32, i32, o15, q0 1. introduction in the last decades, the growth in global output has increased the welfare of many, lifting millions out of poverty. however, this drive is being threatened by global and regional poverty, and inequality beginning to rise again. an understanding of the causes of these is crucial for effective policy implications and achieving global equitable economic development. suspected among these causes is climate change. world bank reported that about 132 million people will transition into poverty by 2030 due to the rising climate change (internal displacement monitoring center, 2018; world bank, 2020). this is also expected to increase the inequality between and within countries. in a report by united nations, an estimate of us$ 383 million/day was recorded for global economic loss resulting from the disaster of climate change between 2010 and 2019 which is almost seven times the record of 1970-1979, us$ 49 million (world meteorological organization, 2021). it is of recent decades becoming clear that climate change, poverty, and income are inextricably linked and not independent. unmitigated climate change is suspected to exacerbate the existing inequality between and within countries’ inequalities and poverty rates. higher temperatures reduce productivity, income, and health. hurricanes from climate change also destroy homes and hamper employment opportunities, making the economic situation of the poor more precarious. on the other hand, poor people and countries do not have enough resources to meet up with the requirement of clean energy to mitigate climate change hence, contributing this journal is licensed under a creative commons attribution 4.0 international license ogbeide-osaretin, et al.: climate change, poverty and income inequality linkage: empirical evidence from nigeria international journal of energy economics and policy | vol 12 • issue 5 • 2022 333 to rising climate change (albu and albu, 2020). it has been suggested that the total damages from natural disasters and higher temperatures are higher in developing countries. as confirmed by sarkodie and strezov (2019) in a study on 192 united nations, africa has been noted to be among the most venerable to climate change. for instance, near-surface air temperature in 2020 was between 0.5°c and 0.88°c more than what was recorded between 1981 and 2010, and africa was found to be warmer than the global average temperature in the combination of overland and ocean (world meteorological organization, 2020). for the period 2015-2019, each year was warmer than all the years before 2014 (world meteorological organization, 2020). sub-saharan africa has also been found to be among the regions with the highest level of poverty and inequality. about 41% of the population is still living below the $1.90 poverty line, while it was estimated that about 87% of the world’s poor will be in ssa by 2030. africa is also the second most unequal continent in the world (seery et al., 2019). nigeria in sub-saharan africa has been of particular interest in terms of the level of climate change, poverty, and inequality. temperature as a measure of climate change was found by data to have risen from 26.85°c to in 1970 to 27.37°c in 2020. this is an average of 0.03°c per decade and in the last 30 years, it increased by 0.19°c per decade. average rainfall increased from 1295 to 2018 (world meteorological organization, 2020). it was estimated that about 83 million of the total population of nigeria’s population are still absolutely poor. inequality measured by the gini index was found to be 44% in 2019 which grew marginally from 43% in 2009 and is the lowest among other countries in ssa and the world. nigeria ranked the least of the 45 countries in africa and had 157 positions in the global ranking on the assessment of the government’s commitment to reducing inequality (seery et al., 2019; world bank, 2020). an overview of figure 1 showed that changes in poverty and inequality seem to be moving in the same direction as climate change captured by temperature in figure 2. although, the temperature seems to be more dynamic. thus, we may argue that climate changes are a foremost contributor to the wider inequality gap given the high negative effect on agricultural productivity, health, and income thereby increasing the poverty rate (poverty tends to be highest in the agricultural sector). on the other hand, it may also be argued that the high level of income inequality and poverty are contributing to the effect of climate change as the unequal income distribution and poverty reduces the ability to mitigate climate change as well as engage in clean energy uses that reduces the degree of climate change. for instance, in 2016, about 74% of the country’s population relied on firewood for cooking (monyei et al., 2018), while only about 55.4% have access to electricity as of 2019 (world bank, 2021). in the same period, poverty increased from 48.2% in 2015 to 72% in 2016. temperature also increased from 27.32°c to 27.77°c. hence, climate change may be a root or a corollary of some levels of inequality and poverty. hence, it has become paramount to analyze this nexus concerning nigeria and the outcome may be extended to other countries for effectiveness in the policy formulation for poverty and income inequality reduction as well as climate change mitigation. analysis of the impacts and causes of climate change has substantially increased over the decades with controversial findings. some empirical evidence concluded that countries with lower income inequality tend to contribute less to climate change, hence suggesting across countries lower inequality for the mitigation of climate change and adoption of a green economy (albu and albu, 2020). climate change has also been found to increase inequality both within counties and across countries (diffenbaugh and burke, 2019; hsiang et al., 2019; dasgupta et al., 2020). others noted that climate change negatively impacts welfare and falls heavily on the poor increasing the poverty level (skoufias, 2012). in sub-saharan africa and nigeria in particular, there are very few studies (skoufias, 2012) that found that the impact of climate change varies with the pattern of income inequality on the impact of climate change on inequality. however, rather than just focusing solely on climate-specific policies given their impact on the global economy, inequality, and poverty, it is also imperative to ask how efforts of the global economy and developing countries to improve economic opportunity and reduce poverty and inequality can increase climate change and its vulnerability. it is also crucial to ask if the level of poverty and income inequality is increasing the risk of climate change. this is based on the assumption that with poverty and a wide income gap, the poor tend to carry out activities that cause harm to the climate (deforestation for wood fuel, burning of charcoal, dumping of refuse in rivers, among others). hence, it can be argued that while climate change can impact inequality and poverty, poverty and inequality can impact climate change. this is a gap that has not been covered particularly in nigeria. hence, the current study is out to fill this gap. therefore, the objective of this study is to determine if there exists a feedback impact between climate change, poverty, and inequality in nigeria. this study, therefore, contributes to current literature in the following ways: first, it evaluates the possibility of a feedback effect between climate change and income inequality. second, it made use of the efficient measures of climate change (temperature) which has not been considered in nigeria studies. third, it explored the existence of a non-linear relationship between income inequality and climate. it is expected that there will be feedback connectivity between climate change and income inequality. figure 1: trend of temperature in nigeria source: authors’ chart ogbeide-osaretin, et al.: climate change, poverty and income inequality linkage: empirical evidence from nigeria international journal of energy economics and policy | vol 12 • issue 5 • 2022334 2. review of literature the impact of climate change on inequality and poverty is a particular area of active research and policy interest, as a result of the inconclusive outcome on the nature and causes of observed inequality. this is a result of the relevance of climate change in achieving sustainable development. climate change according to yue and gao (2018) is the increasing patterns of temperatures and weather that bring about environmental degradation and impact economic and social lives. climate change is mainly caused by the emission of greenhouse gas which causes heat to be trapped by the atmosphere earth’s atmosphere resulting in global warming. poverty is often defined with various measures. defining poverty in terms of income, we have income poverty which is the lack of enough income to live up to the acceptable standard of living or pleasurable well-being. in terms of lack of basic needs of life, we have basic needs poverty which defines a person to be poor when he/she lacks needed food, education, health care, and other necessities of life. poverty can also be defined in comparison to a universally acceptable income level which is absolute poverty. one is called poor if they are living below this level called the poverty line. poverty can also be defined as relative poverty, chronic poverty, and transitory poverty (todaro and smith, 2011). climate change is theoretically linked with poverty and inequality through the pursuit of development and resulting in a vicious cycle. climate change can be exogenous to inequality or endogenous to inequality, hence suggesting a feedback relationship. given the existence of income inequality, this will make some people poor. climate change is exogenous and three ways have been identified by which climate change can affect poverty and inequality. poverty and inequality increase the possibility of exposure of disadvantaged groups to the adverse effect of climate change. a major outcome of climate change is flooding. given that poor and disadvantaged groups can only afford to live in slums, these areas are often flooded. hence the flooding effect of climate change affects the poor group more. climate change also aggravates the susceptibility of the poor group to the effect of climate change as a result of the poor quality of life. finally, the poor and disadvantaged have a lower ability to manage and come out of the effect of climate change. they do not have enough resources to protect their health status or take care of health effects, easily get a new job/start a new investment if their current job/investment is negatively affected by climate change, or afford an insurance policy to compensate for the damage from climate change. all these aggravate the inequality gap and poverty status of the group. climate change is also endogenous, the poor and disadvantaged groups are forced to engage in activities that cause harm to the climate resulting in climate change. as observed by islam and winkel (2017), and evidenced by studies on oecd, inequality and poverty aggregate environmental degradation contributing substantially to climate change. countries with higher inequality tend to have higher levels of per capita waste generation. in line with the above, it may be expected that countries with higher inequality will tend to have higher levels of per capita ghg emissions change in climate in turn relatively affect the poor and the unequally treated group of the society. inequality thus aggravates climate change (islam and winkel, 2017). thus, given this possible endogeneity as presented in figure 3a and 3b, it has become important and urgent to tackle the task of breaking the vicious cycle between climate change and inequality. some earlier studies have been carried out to investigate this analytical framework. however, the outcome of these studies has been mixed results. analyzing the existence of a feedback relationship between climate change and income inequality, the diverse impact of income inequality was found on climate change. farmers are often believed to be the most vulnerable to climate change as a result of their direct and indirect dependency on climatic variables. hence, alam et al. (2017) analyzed the socioeconomic impacts of climatic changes on the farmers in malaysia they employed a primary data analysis method on a survey of 198 paddy farmers in the integrated agricultural development area in northwest selangor of malaysia in 2009. the outcome showed that climate change adversely affects agricultural productivity, health, and profitability thereby increasing income inequality. government spending through subsidies was found not to be adequate to support the farmers and reduce the effects of climate change on the farmers. this was contrary to boyce (2007) who found that inequality brings about a reduction in carbon emission and hence climate change. abaje and oladipo (2019) investigated the impact of the recent changes in temperature and rainfall in the kaduna state of nigeria for the period 1971-2016. linear regression, secondorder polynomial, standard deviation, and cramer’s test were employed in the analysis. the result showed an increasing trend in temperature which was on an average of 1.03°c and a mean increase of rainfall of 303.32 mm. this increase was found to be associated with the increase in greenhouse gases emission. uzar and eyuboglu (2019) examined the effect of co2 emissions on income distribution in turkey for the period 1984-2014. the autoregressive distributed lag model (ardl) bound testing was employed to determine the existence of long-run connectivity among the variables. the study found that there is a positive impact of income inequality on the emission of co2. income inequality granger causes co2 emission using the toda-yamamoto causality test. dasgupta et al. (2020) carried out a quantitative study on climate change’s impacts on inequality and poverty on a south african sub-national panel study. in conformity to alam et al. (2017), the outcome revealed that a substantial relationship exists between inequality/poverty and mean temperature which was a measure of climate change. climate change was found to reduce average growth, hence increasing inequality and poverty. in a similar study to that of uzar and eyuboglu (2019), kusumawardani and dewi (2020) investigated the effect of income inequality on climate change captured by carbon dioxide emissions in indonesia. they employed an autoregressive distributed lag (ardl) model for the period 1975-2017. income inequality was found to harm carbon dioxide which was found to be a function of the level of gdp per capita. thus, the existence of the environmental kuznets curve (ekc) was confirmed in indonesia and the relationship between gdp per capita and co2 emission was found to be an inverted “u” shape. urbanization and dependency were found to negatively affect co2 emissions. ogbeide-osaretin, et al.: climate change, poverty and income inequality linkage: empirical evidence from nigeria international journal of energy economics and policy | vol 12 • issue 5 • 2022 335 albu and albu (2020) explored the connectivity between income inequality and climate change in european union countries. they accounted for the consequences of the increase in carbon emissions on the increase in inequalities. the two-stage ols estimation method was applied to two groups of european union countries, (15 old member states and 13 new member states). the relationship between income inequality and carbon emission was different for the two groups. in the analysis of the effect of income inequality, poverty, and growth on the quality of the environment captured by carbon emission rate, yameogo, and dauda (2020), employed the ardl model on data for nigeria and burkina faso for the period 1980-2016. the result showed inverted u-shaped connectivity between environmental degradation and growth of income for nigeria while u-shaped connectivity was found for burkina faso. there was a positive relationship between income inequality and environmental degradation in both countries. government expenditure and poverty were found to increase the level of carbon emission in nigeria in the long run. in the short run, income inequality was found to reduce carbon emissions in nigeria and it had an adverse effect in burkina faso. following this is the study of sam et al. (2021) who adopted the micro econometric empirical analysis to analyze the effect of climate change on household welfare through the rising prices of cereal. data on five food groups were gathered from the 2009/2010 swaziland household income expenditure survey and was analyzed by the ideal demand system (aids). also, the food price projections of the international food policy research institute (ifpri) were employed to estimate the proportional increase in income that is needed to keep the households on the required welfare level. results showed that an increase in food prices as a result of climate change has led to an increase in the poverty rate of about 71-75 % as compared to 63% before the increase in prices. hence, an income transfer of 17.5 and 25.4% of the former income level is needed to keep welfare at the level before the price increase. hundie (2021) explored income inequality, economic growth, and carbon dioxide emission linkage in ethiopia. the study made use of the ardl bond testing and the dynamic ordinary least square method of estimation over the period 1979-2014. the result revealed that in the long run, the emission of co2 increases with the increase in economic growth and the square of economic growth confirming the kuznets u curve hypothesis of environment. income inequality was found not to have a substantial effect on co2and a positive relationship with it. population size and urbanization were other factors accounting for the increase in the emission of co2. yang et al. (2022) examined the impact of the channel between income inequality and climate change (carbon emissions) to clarify the nonlinear relationship between income inequality, and the different degrees of carbon emissions in the united states and france from 1915 to 2019. they made use of wavelet decomposition and quantile-on-quantile regression and the results revealed that for france, income inequality impacts carbon emissions negatively when there is low-income inequality. however, when income inequality increases, its impact changes from negative to positive which is amplified by the increase in the emission of carbon emissions. on the other hand, as income inequality becomes deeper, the emission-enhancing effect is reversed gradually for the united states. however, the impact of carbon emissions on income inequality are same for both countries. in the short run, the income inequality and carbon emissions relationship in the two countries are randomly volatile while in the medium run, it is a three-dimensional inverted “v” shaped relationship for the us and a three-dimensional “v” shaped relationship for france. also, in the long run, it exhibits a “v” shaped relationship with the us. in a more recent study by cevik and jalles (2022) on the linkage between climate change and income inequality, a panel of 158 countries was explored spanning the period 1955-2019. the researchers found that the increase in climate change vulnerability leads to an increase in income inequality. on segmentation of the sample size, it was revealed that there was no statistical impact of climate change vulnerability on income inequality for the developed countries while the reverse was the case for developing countries. this was accounted to the weak capacity of adaptation and mitigation by the developing countries. 2.1. summary of reviewed literature and contribution to knowledge the analysis of connectivity between climate change and inequality has been examined by some studies. in summary, the studies tend to conclude that climate change increases income inequality. this was for within the countries and, across countries. most of the studies investigated a one-way relationship between climate change and income inequity/poverty. the majority of the study found climate change increasing poverty rather than inequality d poverty increasing climate change. however, needed attention has not been drawn to the fact that there is a two-way relationship between climate change and inequality/poverty. while it is well recognized that climate change causes and aggravates inequality, it is also important to note that inequality can also aggravate climate change. this is the major contribution of this current study to existing literature. 3. methodology two major determinants of climate change are rainfall and temperature. however, we focused only on temperature. 3.1. conceptual framework the study adopted the approach of burke et al. (2015b), and dasgupta et al. (2020) to determine the non-linear relationship between climate change mean temperatures and our economic outcome variables (yit). this current study made use of normal levels of dependent variables rather than the first difference as in burke et al. (2015b) and dasgupta et al. (2020). a country responds to changes in temperature based on the country’s current level of temperature at a particular time, tt. taking the quadratic state can be given as: htt = α1tt + α2t 2t (1) we can then add the warming impact h(tt) to the reference scenarios without the climate impacts of the variable yit. we look ogbeide-osaretin, et al.: climate change, poverty and income inequality linkage: empirical evidence from nigeria international journal of energy economics and policy | vol 12 • issue 5 • 2022336 at the distribution within a country, and, we considered income inequality indices such as the gini index or the atkinson measure a(ω) of inequality or the class of generalized entropy indices. the poverty headcount ratio p0 can also be used which measures the proportion of the population that is counted as poor dasgupta et al. (2020). however, this study made use of the gini index as a measure of income inequality as a result of its simplicity and general acceptability. thus, the impact of climate on income inequality can be computed and simulated using this formula; ( ) ( )( ) g gnit 1 (1 gt h tt h t0 | gnit e − + + − = (2) where eg is the growth factor including climate impacts or g is its growth rate. the equation 2 result shows the effect of temperature on gni in a given country at a particular time t. 3.2. econometric model based on the theoretical under pinning that there could be a feedback relationship between climate change and inequality given the poverty level, thus study adopts a two equation model. gnit = α1tt + α2t 2 t + α3pov+ α4xt +µ1 (3) tt =β1gnit + β2povt+ β3zt + µ2 (4) we control for annual temperature tit and its squared term to capture the potential non-linear effects of climate change on income inequality. this was to test if an inverted u-shaped relationship exists between climate change and income inequality, taking into account the possibility that these relations are not linear. inequality may decrease due to initial increases in temperature, but, beyond a threshold, the incremental increases in temperature may lead to increased inequality. thus, it is expected that for some set of coefficients of temperature, t1 < 0; t2 > 0. in this case, the results indicate a non-linear relationship. the term xt and xt are the matrix of other relevant control variables of the income inequality (unemployment rate and population growth) and relevant control variables of the climate change (carbon dioxide (metric tons per capita), real gdp per capita, unemployment rate, population growth). from the above, equation 3 and 4, introducing the control variables is transformed to: 0 1 2 3 4 5 α α α α α α ε = + + + + + + tgini t tsq pov unmpr popg t (5) 0 1 2 3 4 5 6 β β β β β β β = + + + + + + + tt gini pov unmpr popg cadiox rgdppc ut (6) where gini = gini index a measure of income inequality t = temperature a measure of climate change pov = national poverty level captured by headcount unmpr = unemployment rate popg = population growth rate rgdppc = real gross domestic product per capita. this was used to captured the level of development cadiox = consumption of coal in a thousand short tons εt and ut are the error term for the income inequality and climate change equations respectively. εt and ut are the error term for the income inequality and climate change equations respectively. a priori, 1 2 3 4 5 6 1, 2 3, 4, 5 6, , , , , 0; , 0 0α α α α α α β β β β β β> > < 3.3. data and estimation method the study employed secondary data spanning from 1980 to 2020. the data for gini, pov, and unmpr were obtained from the world bank (2021) and sasu (2022). data for temperature was acquired from climate change knowledge portal (2021), while the rgdppc, popg, and cadiox were obtained from the world development indicators (2021). the variables were subjected to various pre-estimation tests to determine their diagnostic properties. the ardl bounds testing was employed to determine the presence of a long-run relationship given that the variables were stationary at orders one and zero. from the outcome of the ardl result, the dynamic ordinary least square method of estimation was used in carrying out the long-run analysis. the e-views 9 econometric package was used for the analysis. 4. empirical presentation and interpretation of results 4.1. correlation result the intensity of multi-collinearity among the variables was determined using the correction matrix. the result from table 1 showed that there is no multi-collinearity among the variables used in the result. this is proved by the correction coefficients of less than 0.8 for the variables. however, the correlation coefficient between temperature and temperature square of 0.9999 is not surprising as the latter was derived from the former hence, they tend to move together. the result further revealed that there is a positive correlation between inequality and temperature. this tends to suggest that climate change leads to inequality and vice-versa. however, the correlation does not indicate causation hence a further empirical analysis was carried out. 4.2. descriptive statistics as presented in table 2, the mean, maximum, minimum, and jargue-bera (j.b) of the variables showed good performance in the statistics of the variables. the result of the skewness showed that result that all of the variables are positively skewed. the jargue-bera test, on the other hand, confirmed distributional ogbeide-osaretin, et al.: climate change, poverty and income inequality linkage: empirical evidence from nigeria international journal of energy economics and policy | vol 12 • issue 5 • 2022 337 normality in all the variables. this means that all of the variables are distributed regularly 4.3. stationarity test to determine the level of stationary of the variables, the augmented dickey-fuller test was employed. as presented in table 3 while income inequality and population growth were stationary at levels, other variables were stationary at first difference. hence, we proceed to run a cointegration analysis using the ardl bound testing techniques. 4.4. cointegration test from the result of the unit root where some of the variables were integrated of order one and zero. the bound testing method was thus employed to determine the existence of cointegration between climate change and income inequality. from the income inequality model, the result showed that there is the existence of cointegration between the variables at the lower bound only at a 5% level of significance. this is as shown from the f sat of 2.717687 which is higher than the tabulated value of 2.62 lower bound but lower than 3.79 upper bound. hence, we conclude that there is cointegration between the variables (table a1 of the appendix). also, from the climate change model, the existence of cointegration was also found at a lower bound of 5% significance levels. the fsat of 2.661207 which is more than the tabulated values of 2.45 but lower than 3.61 uppers bound respectively allowed us to reject the null hypothesis of no cointegration between the variables (table a2 of the appendix). 4.5. estimation of the models 4.5.1. estimation of income inequality model from the outcome of the cointegration test carried out where the null hypothesis of cointegration was rejected, we proceed to the estimation of the model using the dynamic ols. table 4 shows the dols o the inequality model. examining the diagnostic statistics of the result the r2 of 0.675073 showed that about 68% of the variation in the dependent variable is explained by the independent variables which is not bad. on the performance of the variables of the model, the outcome of the estimation showed that there is a negative relationship between temperature (t) and income inequality (gini) and a positive relationship table 3: summary of the unit-root tests output employing the adf variable levels 5% critical 1st difference 5% critical remark gini −3.139398 −2.936942 i (0) t −1.948335 −2.941145 −8.101568 −2.941145 i (1) t2 −1.958416 −2.941145 −8.075350 −2.941145 i (1) pov −1.712944 −2.938987 −10.99401 −2.938987 i (1) popg −5.311883 −2.960411 i (0) rgdppc −0.580213 −2.938987 −4.569165 −2.938987 i (1) unmpr −0.124458 −2.938987 −7.205141 −2.938987 i (1) cadiox −2.303747 −2.936942 −6.876319 −2.938987 i (1) gini: gini index a measure of income inequality, t: temperature a measure of climate change, pov: national poverty level captured by headcount, unmpr: unemployment rate, popg: population growth rate, rgdppc: real gross domestic product per capita, cadiox: consumption of coal in a thousand short tons table 1: correlation matrix result variables gini t tsq pov popg rgdppc unmpr cadiox gini 1.000000 t 0.077048 1.000000 tsq 0.077078 0.999965 1.000000 pov 0.638624 0.425834 0.424772 1.000000 popg −0.226438 0.184657 0.185821 −0.216889 1.000000 rgdppc 0.099989 0.543493 0.543516 0.315193 0.578165 1.000000 unmpr 0.200912 0.401293 0.401862 0.422842 0.285371 0.711676 1.000000 cadiox −0.597379 0.080869 0.079646 −0.449570 0.448070 0.095579 0.014362 1.000000 source: author’s computation. gini: gini index a measure of income inequality, t: temperature a measure of climate change, pov: national poverty level captured by headcount, unmpr: unemployment rate, popg: population growth rate, rgdppc: real gross domestic product per capita, cadiox: consumption of coal in a thousand short tons, tsq: temperature square table 2: descriptive statistics statistics gini t tsq pov popg rgdppc unmpr cadiox mean 43.06195 27.17659 738.6741 54.52902 2.587127 1799.386 11.43598 0.610519 median 43.00000 27.21000 740.3841 59.30000 2.586546 1607.238 11.90000 0.610000 maximum 56.00000 27.83000 774.5089 72.90000 2.849252 2563.900 33.28000 0.928241 minimum 35.08000 26.32000 692.7424 35.20000 2.488785 1324.297 3.600000 0.325560 sd 4.470221 0.331577 18.00321 12.23253 0.078620 450.5880 6.328673 0.169989 skewness 0.667670 −0.181138 −0.145911 −0.247856 0.823394 0.473706 1.021092 −0.075513 kurtosis 3.623020 2.983925 2.954869 1.616939 4.077668 1.590788 4.690907 2.064996 jarque-bera 3.709285 0.224649 0.148962 3.687588 6.616846 4.925921 12.00904 1.532446 probability 0.156509 0.893754 0.928225 0.158216 0.036574 0.085182 0.002468 0.464765 sum 1765.540 1114.240 30285.64 2235.690 106.0722 73774.82 468.8750 25.03129 sum square deviation 799.3150 4.397722 12964.62 5985.394 0.247245 8121182. 1602.084 1.155851 observations 41 41 41 41 41 41 41 41 source: authors’ computation from eviews 9. gini: gini index a measure of income inequality, t: temperature a measure of climate change, pov: national poverty level captured by headcount, unmpr: unemployment rate, popg: population growth rate, rgdppc: real gross domestic product per capita, cadiox: consumption of coal in a thousand short tons, sd: standard deviation, tsq: temperature square ogbeide-osaretin, et al.: climate change, poverty and income inequality linkage: empirical evidence from nigeria international journal of energy economics and policy | vol 12 • issue 5 • 2022338 the result also divulged that population growth and household size were found to have a positive relationship with gini as expected which was however insignificant. the result revealed a 1% increase in population growth by 19% in gini in nigeria. this upshot is in agreement with the outcome of onwuka (2006), and ogbeideosaretin and orehwereh (2020) who found that population is harmful to development and will increase the income gap. 4.5.2. estimation of the climate change model following the outcome of the cointegration test which confirmed the existence of cointegration among the variables, the dols was employed in the estimation of the model the upshot of the dols estimation as presented in table 5 revealed that in conformity to expectation, income inequality had a substantial positive impact on climate change (t). a 1 unit increase in gini leads to a 0.09 increase in temperature. this is in line with some studies (yameogo and dauda, 2020; hundie, 2021). on the other hand, it was found by some other studies by kusumawardani and dewi (2020) that gini has a negative relationship and impact on climate change. contrary to our expectations, poverty and unemployment were found to have a negative relationship with climate change. while poverty had an insignificant impact on climate change, unemployment was found to have a significant impact on climate change. this is also contrary to the findings of yameogo and dauda (2020) who found that poverty increases climate change. the result further revealed that following some other studies, (hundie, 2021), population growth was found to have a substantial positive impact on climate change. population growth was also found to have the highest magnitude in terms of its impact on climate change. however, it is expected that population growth reduces the consumption of energy and the efficiency in the use of energy. hence, the release of greenhouse gasses will increase climate change and temperature will reduce. other important contributors to climate change are the emission of co2 and the level of development. the result revealed that these had substantial positive impacts on climate change at a 5% level of significance in agreement with our expectations. 1 unit increase in cadiox and rgdppc results in the 2.471865 and 1.89616 unit increases in temperature in nigeria respectively. this is in line with the findings of kusumawardani and dewi (2020) and hundie (2021). between temperature square (tsq) and income (gini). this tends to confirm the existence of the non-linear relationship between climate change and income inequality which showed a u-shaped relationship. climate change is found to substantially impact gini in nigeria at a 5% level of significance. one unit increase in t initially reduces gini by 1279 units and later increases inequality by 23 units. this outcome conforms with the studies of alam et al. (2017), dasgupta et al. (2020), and sam et al. (2021). in line with expectations, poverty was found to have a positive substantial impact on gini. a 1% increment in poverty leads to a 37% increase in income inequality. as revealed by ogbeideosaretin et al. (2016), poverty widens the income inequality gap. as the poor do not often have access to quality and higher levels of education which will create room for employment or increase their income-earning ability. the cycle continues, and the inequality gap widens unless it is broken by effective government policies such as increasing the welfare of the poor (increased access to education and health). however, contrary to expectation, the unemployment rate (unmpr) was found to have a negative relationship with gini which was however not significant. the results revealed that an increase in unemployment reduced income inequality. nevertheless, the unemployment rate in nigeria is more under-employment, and in most cases, the recorded data often underestimates the unemployment rate in nigeria. figure 2: trends of inequality and poverty source: authors’ chart table 4: dynamic ordinary least square estimation of the income inequality model dependent variable=income inequality method=dols diagnostics: r2=0.675073 independent variable coefficient t-sat probability t −1279.193 −2.519587 0.0220* tsq 23.50179 2.504725 0.0227* pov 0.377314 4.543038 0.0003* unmpr −0.318333 −1.556236 0.1381 popg 19.06347 1.020289 0.3219 c 17380.76 2.525623 0.0218 *source: authors’ computation, **significant at 5% and 10% level respectively. dols: dynamic ordinary least square, tsq: temperature square, t: temperature a measure of climate change, pov: national poverty level captured by headcount, unmpr: unemployment rate, popg: population growth rate table 5: dynamic ordinary least square estimation of climate change model dependent variable=income inequality method=dols diagnostics: r2=0.850496 independent variable coefficient t-sat probability gini 0.093341 2.829523 0.0142* pov −0.008594 −0.955033 0.3570 popg 2.889689 2.201680 0.0464* unmpr −0.052672 −2.155823 0.0504* cadiox 2.471865 3.672075 0.0028* log (rgdppc) 1.896167 3.417267 0.0046* c 16.07390 5.325664 0.0001 *source: author’s computation, **significant at 5% and 10% level respectively. dols: dynamic ordinary least square, gini: gini index a measure of income inequality, pov: national poverty level captured by headcount, unmpr: unemployment rate, popg: population growth rate, rgdppc: real gross domestic product per capita, cadiox: consumption of coal in a thousand short tons ogbeide-osaretin, et al.: climate change, poverty and income inequality linkage: empirical evidence from nigeria international journal of energy economics and policy | vol 12 • issue 5 • 2022 339 5. policy recommendations and conclusion 5.1. policy implications the connectivity between climate change and income inequality was examined to determine if there is a feedback relationship between them. time series annual data was employed where climate change was measured by temperature and income inequality by gini. based on the empirical estimates, the following policy colloraries were drawn and recommendations made: 1. temperature was found to have a negative substantial impact on gini while temperature square had a positive substantial impact on gini. this implication of the above is that at the initial level of temperature, income inequality falls as everyone tends to be on the same level with the effect of temperature as a result of climate change. however, as temperature increases with the increases in climate change, the poor not being able to afford means of reducing the effect and are exposed more to climate change, and their sources of income are also affected thereby increasing the income inequality gap. this study thus advocates for control measures for reducing climate change such as reduction of greenhouse gas emissions and putting in place emission fees. 2. income inequality was also found to have a positive significant impact on climate change. this reveals that the increase in income gap will lead to an increase in activities that are harmful to the environment thereby increasing climate change. therefore, we advocate for the reduction of income inequality through a transfer of income from the rich to the poor is effective in reducing energy inequality. also, there is the need to, provide access to commercialized energy to households, increase access to education by the low-income group, and the availability of efficient energy infrastructures to reduce income inequality which will lead to effective climate change adaptation. 3. poverty was found to have a positive substantial impact on income inequality. thus, as poverty increases, the gap between the poor and the rich increases. we, thus, counsel for the reduction in poverty through the provision of employment, and an increase in access to education and health. 4. as divulged by the result, population growth negatively and significantly impacts climate change. hence, we recommend the zealous pursuit of a population growth reduction policy. this can be done by employing practically fertility reduction and birth control. 5. the emission of carbon dioxide substantially impacts climate change. as the emission of co2 increases, the rate of climate change increases which is often seen with the increase in temperature and rainfall. we, therefore, advocate for the use of efficient sources and modern energy. this will help to mitigate climate change and hence. 6. development captured by real gdp per capita was revealed to have a positive substantial impact on climate change. as the quest for development increases, industrialization and household usage of energy increase which is a significant contributor to climate change. hence, this current study counsels that policy measures for modern sources of energy should be pursued. 5.2. conclusion climate change and income inequality are current priorities for the achievement of sustainable development. while there is a current pursuit of development by developing countries, which have increased economic growth and national income through advancements in technology, the increase in income has not been evenly distributed. therefore, the objective of this study is to investigate the interaction between climate change and income inequality. the upshot of the result revealed that there is a significant feedback impact between climate change and income inequality in nigeria. the impact of climate change on income inequality shows a u-shaped hypothesis. other contributors to climate change were population growth, economic development, and the emission of carbon dioxide. effective population control and reduction of income inequality through the provision of employment and education are pertinently recommended. also, efficient and modern energy uses in the purse of development are strongly recommended to reduce climate change and reduction of income inequality. we however suggest that further studies be cried out to investigate the dynamic feedback connectivity between income inequality and climate change. inequality ad climate change is expected to have a spillover effect from previous years. hence, the spillover effect can influence the linkage between them inequality. references abaje, i.b., oladipo, e.o. (2019), recent changes in the temperature and rainfall conditions over kaduna state, nigeria. ghana journal of geography, 11(2), 127-157. alam, m.m., taufique, k., sayal, a. (2017), do climate changes lead figure 3: the climate change income inequality flow source: adopted from islam and winkel (2017) ogbeide-osaretin, et al.: climate change, poverty and income inequality linkage: empirical evidence from nigeria international journal of energy economics and policy | vol 12 • issue 5 • 2022340 to income inequality? empirical study on the farming community in malaysia. international journal of environment and sustainable development, 16(1), 43-59. albu, a., albu, l. (2020), the impact of climate change on income inequality. evidence from european union countries. studies in business and economics, 15(3), 223-235. boyce, j.k. (2007), is inequality bad for the environment? equity and the environment. vol. 15. bingley, united kingdom: emerald group publishing limited, p.267-288. burke, m., hsiang, s.m., miguel, e. (2015), global non-linear effect of temperature on economic production. nature, 527, 235-239. cevik, s., jalles, j.t. (2022), for whom the bell tolls: climate change and inequality. international monetary fund working paper, wp/22/103 imf. climate change knowledge portal. (2021), nigeria current climate. united states: the world bank group. avialble from: https://www. climateknowledgeportal.worldbank.org/country/nigeria/climatedata-historical dasgupta, s., emmerling, j. shayegh, s (2020), inequality and growth impacts from climate change-insights from south africa. european institute of economics and environment, working paper 20-10. diffenbaugh, n.s., burke, m. (2019), global warming has increased global economic inequality. proceedings of the national academy of sciences, 116(20), 9808-9813. hsiang, s., oliva, p., walker, r. (2019), the distribution of environmental damages. review of environmental economics and policy, 13(1), 83-103. hundie, s.k. (2021), income inequality, economic growth and carbon dioxide emissions nexus: empirical evidence from ethiopia. environmental science and pollution research international, 28(32), 43579-43598. internal displacemet monitoring center. (2018), 2018 global report on internal displacement. geneva: internal displacemet monitoring center. available from: https://www.internal-displacement.org/ publications/2018-global-report-on-internal-displacement islam, s.n., winkel, j. (2017), climate change and social inequality. desa working paper no. 152 st/esa/2017/dwp/152. kusumawardani, d., dewi, a.k. (2020), the effect of income inequality on carbon dioxide emissions: a case study of indonesia. heliyon, 6(8), e04772. monyei, c., adewumi, a., obolo, m., sajou, b. (2018), nigeria’s energy poverty: insights and implications for smart policies and framework towards a smart nigeria electricity network. renewable and sustainable energy reviews, 18(1), 1582-1601. ogbeide-osaretin, e.n., orhewere, b. (2020), population growth, gender inequality and economic development in nigeria. izvestiya journal of varna university of economics, 64(1), 47-64. ogbeide-osaretin, n.e., edeme, r.k., ifelunini, i.a. (2016), can income inequality reduction be used as an instrument for poverty reduction? dynamic evidence from nigeria. journal of academic research in economics, 8(2), 307-319. onwuka, e.c. (2006), another look at the impact of nigeria’s growing population on the country’s development. african population studies, 21(1), 1-18. sam, a.g., abidoye, b.o., mashaba, s. (2021), climate change and household welfare in sub-saharan africa: empirical evidence from swaziland. food security, 13(2), 439-455. sarkodie, s.a., strezov, v. (2019), effect of foreign direct investments, economic development and energy consumption on greenhouse gas emissions in developing countries. science of the total environment, 646(1), 862-871. sasu, d.d. (2022), unemployment rate in nigeria in selected quarter between the 1st quarter of 2015 and the 4th quarter of 2020. hamburg: statista. available from: https://www.statista.com/statistics/1119375/ unemployment-rate-in-nigeria-by-quarter seery, e., okanda, j., lawson, m. (2019), a tale of two continents fighting inequality in africa. kenya: oxfam briefing paper. available from: https://www-cdn.oxfam.org/s3fs-public/file_ attachments/bp-tale-of-two-continents-fighting-inequality-africa030919-en.pdf skoufias, e. (2012), the poverty and welfare impacts of climate change quantifying the effects, identifying the adaptation strategies. directions in development; poverty. washington, dc: world bank. world bank. available from: https://www.openknowledge. worldbank.org/handle/10986/9384 todaro, m.p., smith, s.c. (2011), economic development. 11th ed. harlow: addison-wesley. uzar, u., eyuboglu, k (2019), the nexus between income inequality and co2 emission in turkey. journal of cleaner production, 227(1), 149-157. world bank. (2021), nigeria: gini inequality index. the globaleconomy. com. united states: world bank. available from: https://www. theglobaleconomy.com/nigeria/gini_inequality_index world bank. (2021), access to electricity (% of population)-nigeria. united states: world bank. available from: https://www.data. worldbank.org/indicator/eg.elc.accs.zs?locations=ng world bank. (2020), nigeria releases new report on poverty and inequality in the country. united states: world bank: available from: https://www.worldbank.org/en/programs/lsms/brief/nigeriareleases-new-report-on-poverty-and-inequality-in-country world meteorological organization. (2020), state of the climate in africa 2019. geneva: world meteorological organization. available from: https://www.library.wmo.int/doc_num.php?explnum_id=10421 world meteorological organization. (2021), weather-climate-water. geneva: world meteorological organization. available from: https://www.public.wmo.int/en/media/press-release/weather-relateddisasters-increase-over-past-50-years-causing-more-damage-fewer yameogo, c.e.w., dauda, r.o.s. (2020), the effect of income inequality and economic growth on environmental quality: a comparative analysis between burkina faso and nigeria. journal of public affairs, 7(2), 148-163. yang, z., ren, j., ma, s., chen, x., cui, s., xiang, l. (2022), the emission inequality nexus: empirical evidence from a wavelet-based quantile-on quantile regression approach. frontiers in environment science, 10, 871846. yue, x.l., gao, q.x. (2018), contributions of natural systems and human activity to greenhouse gas emissions. advances in climate change research, 9(4), 243-252. ogbeide-osaretin, et al.: climate change, poverty and income inequality linkage: empirical evidence from nigeria international journal of energy economics and policy | vol 12 • issue 5 • 2022 341 appendix table a1: autoregressive distributed lag model bounds test for income inequality equation ardl bounds test date: 04/29/22 time: 01:14 sample: 1981 2020 included observations: 40 null hypothesis: no long-run relationships exist test statistic value k f-statistic 2.717687 5 critical value bounds significance (%) i0 bound i1 bound 10 2.26 3.35 5 2.62 3.79 2.5 2.96 4.18 1 3.41 4.68 ardl: autoregressive distributed lag model table a2: autoregressive distributed lag model bounds test for climate change equation ardl bounds test date: 04/29/22 time: 01:03 sample: 1981 2020 included observations: 40 null hypothesis: no long-run relationships exist test statistic value k f-statistic 2.661207 6 critical value bounds significance (%) i0 bound i1 bound 10 2.12 3.23 5 2.45 3.61 2.5 2.75 3.99 1 3.15 4.43 ardl: autoregressive distributed lag model tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020 347 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 347-353. debt finance, inventory management and economic value of energy industry in saudi arabia: empirical investigation khaled salmen aljaaidi*, omar ali bagais department of accounting, college of business administration, prince sattam bin abdulaziz university, saudia arabia. *email: k.aljaaidi@psau.edu.sa received: 13 june 2020 accepted: 08 september 2020 doi: https://doi.org/10.32479/ijeep.10085 abstract the purpose of this paper is to identify the relationships of debt finance and inventory management with firm economic value of energy industry in saudi arabia, from 2012 to 2019. the sample comprises of 32 firm-year observations throughout the 8 years’ time frame until 2019. pearson’s correlation, pooled ols regression are used in this study. the findings of this study indicate to a negative association between debt finance and firm economic value. furthermore, a positive association is reported between inventory management and firm economic value. the results of this study are important for energy industry in saudi arabia in making decisions related to debt financing. in addition, energy industry can use the results of this study in controlling their inventory practices. further, the results of this study can be used in future research to gain a deeper understanding of the issues of debt finance, inventory management and firm economic value. keywords: debt finance, inventory management, economic value, energy industry, saudi arabia jel classifications: l25, g51, h68, o13, p18, p28, p48 1. introduction debt is employed by companies as a means of financing their activities (damadoran, 2001). choosing to employ debt financing is regarded as a crucial financial decision for all companies. every company wants to achieve the maximum possible return and choosing to take on debt can negatively affect profit. companies employ debt for financing what they presume will be successful projects. if the projects succeed as hoped, the firm will get a good return on its investments and therefore be able not only to pay their debt but also to use the funds left over for further investment. however, should projects not succeed, company performance can be adversely impacted for a considerable period (stiglitz and weiss, 1981). by the same way of token, it is widely agreed that the way in which inventory is managed can have a crucial influence on company profits, as good management can reduce the expense of retaining stock and make sure that production runs smoothly (cheung et al, 2004; shin, 2015). economic value ratios operate as indicators of how well a company is performing financially and how effectively it is generating profits (brigham and erhardt, 2013). bourne and walter (2005) state that there is a direct correlation between inventory management and company performance. inadequate management will inevitably result in a significant wastage related to the cost of storing inventory and greater risks of inventory being damaged or lost (lwiki et al., 2013). for effective performance, companies must create the maximum possible revenue for the minimum possible cost (mohamad et al., 2016). managing inventory will directly influence outlay and therefore company profit and performance (return on investment) (fullerton et al., 2003; swamidass, 2007; koumanakos, 2008; steven and britto, 2016; lin et al., 2018). this means that inventory management and roa are directly linked (eroglu and hofer, 2011; sahari et al., 2012). keeping the optimal level of inventory will lead to significant improvements in company financial performance (abd karim et al., 2018). this journal is licensed under a creative commons attribution 4.0 international license aljaaidi and bagais: debt finance, inventory management and economic value of energy industry in saudi arabia: empirical investigation international journal of energy economics and policy | vol 10 • issue 6 • 2020348 this paper aims to offer greater insight into the links between debt financing/inventory management and company performance related to saudi arabia’s energy businesses. as far as the researchers are aware, there is no empirical research available linking debt financing/inventory management and company performance. the energy industry has been chosen for examination as it is highly influential economically for the nation in which it employs labor and capital for its output. saudi arabia’s energy sector is crucial in helping to alleviate economic hardship and address social inequality in the country. development goals mandate that the energy sector must be developed in a manner that ensures that it benefits wider society. in this way, it can alleviate the poverty gap that exists in developing countries (ruti and felice, 2013; yergin and gross, 2012). saudi arabia has taken steps to implement a market economy through regulation and other means. the outcomes of this research should be a useful reference for the nation’s politicians and regulators. on a wider level, it should be useful for all those involved in emerging middle eastern markets as many countries in the region have similar institutions and economic structures (la porta and lopezde-silanes, 1999). it is likely that this research will raise new questions regarding debt financing and inventory management; numerous stakeholders will have an interest in seeing the influence that debt financing/inventory management has on a company’s profits. the following sections of the paper are organized as follows. the literature is reviewed and the hypotheses are developed in section 2. the data collection and research design is highlighted in section 3. section 4 displays the results and discussions. conclusions and implications were discussed in the final section, section 5. 2. literature review and development of hypotheses debt represents the monies borrowed by a company from outside agencies. it is recognized that management is frequently concerned about the impact that debt will have on company value (grossman and hart, 1982). this may occur if executives do not exercise effective control over a firm’s activity. excessive debt can damage a company’s reputation in the marketplace and thereby lead to a loss of custom. companies take on debt to have sufficient funds for large projects with an assumption of success. should these projects succeed and provide the desired results, a company will make significant profits and therefore will be able to pay off their debt and employ the remaining funds to reinvest. however, if such projects should fail, company performance may be negatively impacted for significant periods (stiglitz and weiss, 1981). berezinets et al. (2017) noted that if organizations have higher debt levels, this may be an indicator that they are expanding through engagement with new initiatives. this is why the organization will have to borrow some capital to be used in funding these projects, (berezinets et al., 2017; black et al., 2006). kinsman and newman (1998) reported that high levels of debt are correlated with lower firm performance. empirically, fernandez-temprano and tejerina-gaite (2020) assenga et al. (2018), mishra and kapil (2018), yasser et al. (2017), plalniappan (2017), kumar and singh (2013), mcconnell and servaes (1995), short and keasey (1999), weir et al. (2002), haniffa and hudaib (2006), majumdar and chhibber (1999), gleason (2000), cheng (2009), johnny jermias (2008). in the setting of saudi arabia, aljifri and moustafa (2007) find a negative association between firm performance and debts. accordingly, the expected signs for the relationships of debt finance with firm economic value is negative. h1a: there is a negative relationship between debt finance and firm economic value-roa. h1b: there is a negative relationship between debt finance and firm economic value-roe. inventory is an essential part of business and it requires effective management by senior executives, no matter what the company size (elsayed and wahba, 2013; abd karim et al., 2018). inventory management covers everything related to the maintenance and management of inventory, including raw materials, products during manufacture, and the finished article. companies holding inventory must make sure they maintain the correct level of stock, as over or under stocking can lead to wastage during manufacturing (chase et al., 2006; heizer and render, 2014; ahmad and zabri, 2018; kotler, 2002; abd karim et al., 2018). a primary reason for the importance of inventory is that storage and handling of inventory can be a costly and complicated process. this is especially true with modern systems (dennis and meredith, 2000). if inventory is not managed efficiently, delays may ensue and the company may not be able to satisfy the requirements of consumers (baron et al., 2010; ahmad and zabri, 2018). it is essential that companies should have rigorous systems established for managing inventory and make sure that such systems are subject to continuous monitoring and management by suitably qualified employees (coyle et al., 2003; mohamad et al., 2016). the chief aim of managing inventory is making sure that the ideal level of stock is maintained to accord with the demands of customers and the manufacturing processes (mohamad et al., 2016; toomey, 2000). in any firm producing products, inventory management is essential as problems with inventory can cause loss of sales or additional cost. managing inventory effectively maintains a robust supply chain and can help a company to take a lead over its rivals. inventory management may have a crucial effect on company profits, as it can lead to reductions in storage costs and assist in the smooth flow of production (cheung et al., 2004; shin et al., 2015). economic value ratios offer indicators of how a company is performing financially and how effectively it is creating profits (brigham and ehrhardt, 2013). bourne and walter (2005) state that inventory management directly influences how a firm performs. poor management of inventory will cause significant wastage in terms of the costs of storing inventory and greater risks of goods being damaged or lost (lwiki et al., 2013). for effective performance, companies must create the greatest possible level of revenue for the least outlay (mohamad et al, 2016). inventory management directly influences cost and therefore the profits and asset returns of a company (fullerton et al., 2003; swamidass, 2007; aljaaidi and bagais: debt finance, inventory management and economic value of energy industry in saudi arabia: empirical investigation international journal of energy economics and policy | vol 10 • issue 6 • 2020 349 koumanakos, 2008; steven and britto, 2016; lin et al., 2018). this creates a direct linkage of inventory management and roa (eroglu and hofer, 2011; sahari et al., 2012). the maintenance of the ideal level of inventory can lead to significant improvements in a company’s financial performance (abd karim et al., 2018). little clear evidence is available directly supporting the correlation between company performance and inventory management (vastag and whybark, 2005; cannon, 2008; keramidou et al., 2012; obermaier and donhauser, 2012; folinas and shen, 2014). a certain amount of empirical research has been undertaken to investigate this correlation, and what there is has found the two elements to be positively related (jonsson and mattsson, 2008; capkun et al., 2009; gaur and kesavan, 2009; pong and mitchell, 2012; sahari et al., 2012; ahmad and zabri,2018; lin et al., 2018). researchers have demonstrated that the lower a company’s inventory ratio is the greater likelihood of their having high levels of sales, improved roi, and remaining competitive. overall, based on the above empirical evidences reported by the extant literature, the following hypotheses are suggested: h2a: there is a positive relationship between inventory management and firm economic value-roa. h2b: there is a positive relationship between inventory management and firm economic value-roe. 3. data collection and research design 3.1. sample selection and data collection the sample of this study consists of energy listed companies on saudi stock exchange (tadawul) for the years ranging from 2012 to 2019. we conduct a cross-sectional review of financial reports of the sample companies as depicted in table 1. 3.2. regression model and definition of variables ordinary-least square ols regression is used to estimate the associations of debt finance and inventory management with firm economic value of energy listed companies in saudi arabia for the period ranging from 2012 to 2019. the utilizing of the ols regression is because the dependent variable in this study is a continuous measure. the functional equation of the ols model is as follows: fev-roa = β0 + β1 dfa + β2 im + e (1) fev-roa = β0 + β1 dfo + β2 im + e (2) fev-roe = β0 + β1 dfa + β2 im + e (3) fev-roe = β0 + β1 dfo + β2 im + e (4) where the dependent variable is: where the independent variables are: test variable dfa = total debts divided by total assets dfo = total debts divided by total owner’s equity im = sales/inventory e = error 4. results and discussions 4.1. summary statistics table 2 predicts the mean, standard deviation, minimum and maximum of each variable in the sample data set. table 2; panel a shows that the mean of the debt finance dfa is 0.486, and the range is between 0.01 and 0.86 and a standard deviation of 0.299. further, the average of the debt finance dfo is 1.805 and it ranges from 0.01 to 6.37 and a standard deviation 1.961. the mean of the inventory management im is 38.479 and it ranges from 10.01 to 88.63 and a standard deviation of 32.058. in addition, table 2; panel b illustrates that the mean of firm economic value fev-roa, the dependent variable, is .0417 and it ranges from 0.000 to 0.11 with a standard deviation of 0.0336. as for the firm economic value fev-roe, the average is .091 and it ranges from .000 to 0.33 with a standard deviation of 0.082. 4.2. correlation matrix tables 3 and 4 display the pearson correlations among the hypothesized variables. the coefficients of correlation are small and the highest correlation was between dfo and im (-.427), indicating that the sample has no multicollinearity, since none of the correlation is equal or above 0.80 or 0.90. all variables have a correlation of equal or less than -.427 (myers, 1990). as for the variance inflation factor (vif), tables 5 and 6 report the results as follows: table 1: sample selection from 2012 to 2019 totals total listed companies 5 firms number of years observed 8 years total observation 40 missing data (8) final sample 32 table 2: descriptive statistics panel a: independent variables continuous variables mean std. deviation minimum maximum dfa 0.486 0.299 0.01 0.86 dfo 1.805 1.961 0.01 6.37 im 38.479 32.058 10.01 88.63 panel b: dependent variable fev-roa 0.0417 0.0336 0.000 0.11 fev-roe 0.091 0.082 0.000 0.33 aljaaidi and bagais: debt finance, inventory management and economic value of energy industry in saudi arabia: empirical investigation international journal of energy economics and policy | vol 10 • issue 6 • 2020350 tables 5 and 6 illustrate that the largest vif value is 1.223, implying that the sample has no multicollinearity, since none of the vif values is up to 10 (hair et al., 2006) 4.3. regression results and discussions ordinary-least square (ols) was used to evaluate the level of associations of debt finance and inventory management with firm economic value. as shown by tables 7 and 8, the r2s for the models 1a and 1b are .836 and .740, respectively. this implies that model 1a has explained 83.6% and model 1b has explained 74% of the total variance in the firm economic value. tables 9 and 10 depict that the f-values for the models 1a and 1b are statistically significant at the 1% level which means that the overall models can be interpreted. tables 11, 12, 17 and 18 illustrate the pooled ols regression results. tables 11 and 12 show that there is a significantly negative association between dfa and fev-roa (β = −0.628, t = −6.574, p = 0.000, one-tailed significance) in the model 1a, and the same direction of association is reported between dfo and fev-roa (β = −0.543, t = −4.419, p = 0.000, one-tailed significance) in the model 1b. these findings are consistent with kinsman and newman (1998), fernandez-temprano and tejerina-gaite (2020) assenga et al. (2018), mishra and kapil (2018), yasser et al. (2017), plalniappan (2017), kumar and singh (2013), mcconnell and servaes (1995), short and keasey (1999), weir et al. (2002), haniffa and hudaib (2006), majumdar and chhibber (1999), gleason (2000), cheng (2009), johnny jermias (2008), and aljifri and moustafa (2007). thus, hypothesis h1a is accepted. tables 11 and 12 show that there is a significantly positive association between im and fev-roa (β = .463, t = 4.899, p = 0.000, one-tailed significance) in the model 1a, and the same direction of association is reported between im and fev-roa (β = 0.474, t = 3.858, p = 0.001, one-tailed significance) in the model 1b. these findings are consistent with several extant research (jonsson and mattsson, 2008; capkun et al., 2009; gaur and kesavan, 2009; pong and mitchell, 2012; sahari et al., 2012; ahmad and zabri,2018; lin et al., 2018). therefore, hypothesis h2a is accepted. as shown by tables 13 and 14, the r2s for the models 2a and 2b are 0.628 and 0.559, respectively. this implies that model 2a has table 4: pearson correlation analysis results dfo im dfo 1 im −0.427 1 **significant at 1% level (2-tailed). *significant at 5% level (2-tailed) table 6: variance inflation factor ‑ roe models variables tolerance vif dfa 0.855 1.169 im 0.855 1.169 table 3: pearson correlation analysis results dfa im dfa 1 im −0.380 1 **significant at 1% level (2-tailed). *significant at 5 per cent level (2-tailed) table 5: variance inflation factor ‑ roa models variables tolerance vif dfo 0.818 1.223 im 0.818 1.223 table 8: model summary – model 1b model r r square adjusted r square standard error of the estimate 1 0.860 0.740 0.716 5.417 table 9: anova analysis – model 1a 1 model sum of squares df mean square f sig. regression 1984.809 2 992.405 53.600 0.000 residual 388.816 21 18.515 total 2373.625 23 table 7: model summary – model 1a model r r square adjusted r square std. error of the estimate 1 0.914 0.836 0.821 4.303 table 10: anova analysis – model 1b 1 model sum of squares df mean square f sig. regression 1757.452 2 878.726 29.948 0.000 residual 616.173 21 29.342 total 2373.625 23 table 11: pooled ols regression – model 1a (roa) variables expected sign coeff. t p-value tolerance vif (constant) 2.551 0.061 test variable dfa −0.628 −6.574 0.000 0.855 1.169 im + 0.463 4.899 0.000 0.855 1.169 aljaaidi and bagais: debt finance, inventory management and economic value of energy industry in saudi arabia: empirical investigation international journal of energy economics and policy | vol 10 • issue 6 • 2020 351 explained 62.8% and model 1b has explained 55.9% of the total variance in the firm economic value. tables 15 and 16 depict that the f-values for the models 2a and 2b are statistically significant at the 1% level which means that the overall models can be interpreted. tables 17 and 18 show that there is a significantly negative association between dfa and fev-roe (β = .445, t = 3.092, p = .002, one-tailed significance) in the model 2a, and the same direction of association is reported between dfo and fev-roe (β = .350, t = 2.187, p = .040, one-tailed significance) in the model 2b. these findings are consistent with kinsman and newman (1998), fernandez-temprano and tejerina-gaite (2020) assenga et al. (2018), mishra and kapil (2018), yasser et al. (2017), plalniappan (2017), kumar and singh (2013), mcconnell and servaes (1995), short and keasey (1999), weir et al. (2002), haniffa and hudaib (2006), majumdar and chhibber (1999), gleason (2000), cheng (2009), johnny jermias (2008), and aljifri and moustafa (2007). thus, hypothesis h1b is accepted. tables 17 and 18 show that there is a significantly positive association between im and fev-roe (β = 0.508, t = 3.535, p = 0.002, onetailed significance) in the model 2a, and the same direction of association is reported between im and fev-roe (β = 0.528, t = 3.295, p = 0.003, one-tailed significance) in the model 2b. these findings are consistent with several extant research (jonsson and mattsson, 2008; capkun et al., 2009; gaur and kesavan, 2009; pong and mitchell, 2012; sahari et al., 2012; ahmad and zabri,2018; lin et al., 2018). therefore, hypothesis h2b is accepted. table 12: pooled ols regression – model 1b (roa) variables expected sign coeff. t p-value tolerance vif (constant) 2.551 0.061 test variable dfo −0.543 −4.419 0.000 0.818 1.223 im + 0.474 3.858 0.001 0.818 1.223 table 13: model summary – model 2a model r r square adjusted r square std. error of the estimate 1 0.793 0.628 0.593 5.854 table 16: anova analysis – model 2b 1 model sum of squares df mean square f sig. regression 1083.071 2 541.536 13.334 0.000 residual 852.887 21 40.614 total 1935.958 23 table 18: pooled ols regression – model 2b (roe) variables expected sign coeff. t p-value tolerance vif (constant) 14.666 0.000 test variable dfo −0.350 −2.187 0.040 0.818 1.223 im + 0.528 3.295 0.003 0.818 1.223 table 14: model summary – model 2b model r r square adjusted r square std. error of the estimate 1 0.748 0.559 0.517 6.373 table 15: anova analysis – model 2a 1 model sum of squares df mean square f sig. regression 1216.291 2 608.146 17.746 0.000 residual 719.667 21 34.270 total 1935.958 23 table 17: pooled ols regression – model 2a (roe) variables expected sign coeff. t p-value tolerance vif (constant) 12.977 0.000 test variable dfa −0.445 −3.092 0.002 0.855 1.169 im + 0.508 3.535 0.002 0.855 1.169 aljaaidi and bagais: debt finance, inventory management and economic value of energy industry in saudi arabia: empirical investigation international journal of energy economics and policy | vol 10 • issue 6 • 2020352 5. conclusions and implications this paper has examined the influence of debt financing and inventory management on company economic value for saudi arabia’s energy companies between 2012 and 2019. the selected sample for this research comprises 32 firm-year observations. employing pooled ols regression, this research has demonstrated that debt financing has a negative impact on company profits. additionally, it has also demonstrated that there is a positive correlation between company economic value and inventory management. this research makes it clear that saudi arabia’s energy companies must have an awareness about the influence that debt financing can have on their profits. they may have to consider the positives and negatives of equity financing. furthermore, these companies must make their inventory control systems more robust as more effective inventory management leads to greater profit. a number of factors influencing debt financing/inventory management could be researched in future, e.g. corporate governance (ownership structures, quality of audits, audit committee, and board of directors). this research model could be reproduced for other gcc nations and in other middle eastern (arab) markets to check for validity. this research can offer financial analysts, investors, auditors, banks, account/audit regulators, companies, stock markets, researchers, and academics fresh understanding of the correlations of debt financing/inventory management and company profits. refrences adams, r.b., mehran, h. (2005), firm value, board structure and its determinants in the banking industry. moscow: efa 2005 moscow meetings. alnasser, z. (2019), the effect of royal family members on the board on firm performance in saudi arabia. journal of accounting in emerging economies, forthcoming, 10(6), 2042-1168. al-abbas, m.a. (2008), do saudi companies underestimate us in the application of governance? aleqtisadia magazine. available from: http://www.aleqt.com/2008/02/29/article_11668.save. alexander, j.a., fennell, m.l., halpern, m.t. (1993), leadership instability in hospitals: the influence of board-ceo relations and organizational growth and decline. administrative science quarterly, 38(1), 74-99. al-ghamdi, s.a. (2012), investigation into earnings management practices and the role of corporate governance and external audit in emerging markets: empirical evidence from saudi listed companies, doctoral dissertation. england: durham university. al-hamidy, a. (2010), the global financial crisis: impact on saudi arabia. this volume bis papers, 54, 347-357. al-hussain, a.h. (2009), corporate governance structure efficiency and bank performance in saudi arabia, doctoral dissertation. university of phoenix. aljifri, k., moustafa, m. (2007), the impact of corporate governance mechanisms on the performance of uae firms: an empirical analysis. journal of economic and administrative sciences, 23(2), 71-93. al-moataz, e., basfar, a. (2010), the role of audit committees in corporate governance: an empirical investigation on saudi corporations. journal of king abdulaziz university: economics and administration, 24(2), 193-239. assenga, m.p., aly, d., hussainey, k. (2018), the impact of board characteristics on the financial performance of tanzanian firms. corporate governance: the international journal of business in society, 18(6), 1089-1106. aydin, n., sayim, m., yalama, a. (2007), foreign ownership and firm performance: evidence from turkey. international research journal of finance and economics, 11(1), 103-111. berezinets, i., ilina, y., cherkasskaya, a. (2017), board structure, board committees and corporate performance in russia. managerial finance, 43(10), 1073-1092. bhatt, r.r., bhattacharya, s. (2017), family firms, board structure and firm performance: evidence from top indian firms. international journal of law and management, 59(5), 699-717. black, b.s., jang, h., kim, w. (2006), does corporate governance predict firms’ market values? evidence from korea. the journal of law, economics, and organization, 22(2), 366-413. boone, a.l., field, l.c., karpoff, j.m., raheja, c.g. (2007), the determinants of corporate board size and composition: an empirical analysis. journal of financial economics, 85(1), 66-101. brick, i.e., chidambaran, n.k. (2010), board meetings, committee structure, and firm value. journal of corporate finance, 16(4), 533-553. brown-liburd, h., cohen, j., zamora, v.l. (2011), the effect of corporate social responsibility investment, assurance, and perceived fairness on investors’ judgments. usa: milgard school of business. cheng, m.t. (2009), relative effects of debt and equity on corporate operating performance: a quantile regression study. international journal of management, 26(1), 142.‏ coles, j., daniel, n., naveen, l. (2008), boards: does one size fit all? journal of financial economics, 87(2), 329-356. cubbin, j., leech, d. (1983), the effect of shareholding dispersion on the degree of control in british companies: theory and measurement. the economic journal, 93(370), 351-369. dalton, c., dalton, d. (2005), boards of directors: utilizing empirical evidence in developing practical prescriptions. british journal of management, 16(1), 91-97. dalton, d., daily, c., johnson, j., ellstrand, a. (1999), number of directors and financial performance: a meta-analysis. academy of management journal, 42(6), 674-686. damodaran, a. (2016), damodaran on valuation: security analysis for investment and corporate finance. vol. 324. united states: john wiley & sons. eisenberg, t., sundgren, s., wells, m. (1998), larger board size and decreasing firm value in small firms. journal of financial economics, 48(4), 35-54. fama, e.f., jensen, m.c. (1983), agency problems and residual claims. journal of law and economics, 26, 327-349. fernández-temprano, m.a., tejerina-gaite, f. (2020), types of director, board diversity and firm performance. corporate governance, 20(2), 324-342. gleason, k.c., mathur, l.k., mathur, i. (2000), the interrelationship between culture, capital structure, and performance: evidence from european retailers. journal of business research, 50(2), 185-191.‏ goodstein, j., gautam, k., boeker, w. (1994), the effects of board size and diversity on strategic change. strategic management journal, ‏.241-250 ,(3)15 grossman, s.j., hart, o.d. (1982), corporate financial structure and managerial incentives. in: the economics of information and uncertainty. united states: university of chicago press. p107-140. hair, j.f., black, w.c., babin, b.j., anderson, r.e., tatham, r.l. (2006), multivariate data analysis. vol. 6. upper saddle river, nj: pearson prentice hall. aljaaidi and bagais: debt finance, inventory management and economic value of energy industry in saudi arabia: empirical investigation international journal of energy economics and policy | vol 10 • issue 6 • 2020 353 haniffa, r., hudaib, m. (2006), corporate governance structure and performance of malaysian listed companies. journal of business finance and accounting, 33(7-8), 1034-1062.‏ hannan, m.t., freeman, j. (1989), organizational ecology. cambridge, massachusetts: harvard university press. hawkamah, the institute for corporate governance and ifc, international finance corporation. (2008), corporate governance survey of listed companies and banks across the middle east and north africa. available from: http://www.hawkamah.org. helmich, d. (1977), executive succession in the corporate organization: a current integration. the academy of management review, 2(2), 252-266. hurdle, g.j. (1974), leverage, risk, market structure and economic value. the review of economics and statistics, 56(4), 478-485. jensen, m.c. (1993), the modern industrial revolution, exit, and the failure of internal control systems. the journal of finance, 48(3), 831-880. jensen, m., meckling, w. (1976), theory of the firm: managerial behavior, agency costs, and capital structure. journal of financial economics, 3(4), 305-360. jermias, j. (2008), the relative influence of competitive intensity and business strategy on the relationship between financial leverage and performance. the british accounting review, 40(1), 71-86.‏ kao, m.f., hodgkinson, l., jaafar, a. (2019), ownership structure, board of directors and firm performance: evidence from taiwan. corporate governance: the international journal of business in society, 19(1), 189-216. karamanou, i., vafeas, n. (2005), the association between corporate boards, audit committees, and management earnings forecasts: an empirical analysis. journal of accounting research, 43(3), 453-486. kawaura, a. (2004), deregulation and governance: plight of japanese banks in the 1990s. applied economics, 36(5), 479-484. kinsman, m.d., newman, j.a. (1998), debt associated with lower firm performance finding calls for review of rise in debt use. california: graziadio business report.‏ kumar, j. (2004), does ownership structure influence firm value? evidence from india. the journal of entrepreneurial finance and business ventures, 9(2), 61-93. kumar, n., singh, j.p. (2013), effect of board size and promoter ownership on firm value: some empirical findings from india. corporate governance: the international journal of business in society, 13(1), 1472. kyereboah-coleman, a., biekpe, n. (2005), the relationship between board size, board composition ceo duality and firm performance experience from ghana. corporate ownership and control, 4(2), 1-19. la porta, r., lopez-de-silanes, f., shleifer, a., vishny, r. (1999), corporate ownership around the world. journal of finance, 54(2), 471-517. larmou, s., vafeas, n. (2008), the relation between board size and firm performance in firms with a history of poor operating performance. journal of management and governance, 14(1), 61-85. letendre, l. (2004), the dynamics of the boardroom. academy of management perspectives, 18(1), 101-104. lipton, m., lorsch, j. (1992), a modest proposal for improved corporate governance. business lawer, 48(1), 59-77. majumdar, s.k., chhibber, p. (1999), capital structure and performance: evidence from a transition economy on an aspect of corporate governance. public choice, 98(3-4), 287-305.‏ mcconnell, j.j., servaes, h. (1990), additional evidence on equity ownership and corporate value. journal of financial economics, ‏.595-612 ,(2)27 mishra, r., kapil, s. (2017), effect of ownership structure and board structure on firm value: evidence from india. corporate governance: the international journal of business in society, 17(4), 700-726. muller-kahle, m.i., wang, l., wu, j. (2014), board structure: an empirical study of firms in anglo-american governance environments. managerial finance, 40(7), 681-699. palaniappan, g. (2017), determinants of corporate financial performance relating to board characteristics of corporate governance in indian manufacturing industry: an empirical study. european journal of management and business economics, 26(1), 67-85. pearce, j.a., zahra, s.a. (1992), board composition from a strategic contingency perspective. journal of management studies, 29(4), 411-438. pfeffer, j. (1972), size and composition of corporate board of directors: the organization and its environment. administrative science quarterly, 17, 218-229. pfeffer, j.s., salancik, g. (1978), the external control of organizations: a resource dependence perspective. new york: stanford university press. porwal, h., kumar, s. (2003), ethical culture in corporate accounting. akauntan nasional, 16, 18-23. rodriguez-fernandez, m., fernandez-alonso, s., rodriguezrodriguez, j. (2014), board characteristics and firm performance in spain. corporate governance, 14(4), 485-503. ruti, p.m., de felice, m. (2013), climate and energy production-a climate services perspective. in: climate vulnerability: understanding and addressing threats to essential resources. netherlands: elsevier inc. sheikh, a.n., wang, z. (2012), effects of corporate governance on capital structure: empirical evidence from pakistan. corporate governance: the international journal of business in society, 12(5), 629-641. short, h., keasey, k. (1999), managerial ownership and the performance of firms: evidence from the uk. journal of corporate finance, 5(1), 79-101. stiglitz, j.e., weiss, a. (1981), credit rationing in markets with imperfect information. the american economic review, 71(3), 393-410. teng, l.l., aun, l.k., fook, o.s. (2011), corporate governance assessment in company board structure. african journal of business management, 5(4), 1175-1183. vafeas, n. (1999), board meeting frequency and firm performance. journal of financial economics, 53(1), 113-142. weir, c., laing, d., mcknight, p.j. (2002), internal and external governance mechanisms: their impact on the performance of large uk public companies. journal of business finance and accounting, ‏.579-611 ,(5-6)29 yasser, q.r., mamun, a.a., rodrigs, m. (2017), impact of board structure on firm performance: evidence from an emerging economy. journal of asia business studies, 11(2), 210-228. yergin, d., gross, s. (2012), energy for economic growth: energy vision update 2012, industry agenda. switzerland: world economic forum. yermack, d. (1996), higher market valuation of companies with a small board of directors. journal of financial economics, 40(2), 185-211. zahra, s.a., pearce j.a. (1989), boards of directors and corporate financial performance: a review and integrative model. journal of management, 15, 291-334. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020594 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 594-601. study of factors affecting micro-barriers that hinders the development of private enterprises: mediating role of intention to use of renewable energy phan the cong*, pham thi minh uyen thuongmai university, hanoi, vietnam. *email: congpt@tmu.edu.vn received: 19 june 2020 accepted: 10 september 2020 doi: https://doi.org/10.32479/ijeep.10588 abstract private enterprises in vietnam as well as in other countries play an important role in the economy, but they have encountered several barriers in their development at both micro and macro levels. inquires of these barriers is meaningful in making policy recommendations to remove barriers to private enterprise development in countries where the state/government is considered a major factor. this study focuses on evaluating factors affecting the micro-barrier system that hinder the development of private enterprises in vietnam to answer two research questions: which factors influence microbarriers that hinder the development of private enterprises in vietnam and what is the degree of influence of those factors along with the mediating impact of intention to use of renewable energy? the study applies quantitative research methods to measure the impact of factors on the micro-barriers system that hinder private enterprise development based on the survey sample of 392 private enterprises in vietnam, which are mainly small and medium-sized private enterprises (most affected by micro barriers). research findings indicate that state management policies; legal and tax systems, expanding scientific research and technological innovation activities are the main factors affecting the micro barriers that hinder the development of private enterprises in vietnam. intention to use of renewable energy significantly mediates between competitiveness in production and business, support for scientific research and technological innovation activities, expanding cooperation and international integration, state management policy, law and tax and barriers restricting enterprise development. these results could become experiences for other countries like vietnam. keywords: tectonic government, tectonic state, innovative government, remove barriers, private enterprises, renewable energy jel classifications: l2, o2, q2 1. introduction both economists with a free-market perspective and economists with modern perspectives agree that the role of the state as a regulatory actor is a natural need of the market. therefore, creating a healthy development environment for economic sectors is both a task and a goal of the state/government when intervening in a market economy. how the state/government (depending on the political institutions of each country) intervenes in the economy is usually a topical question; especially in recent years, when economies are increasingly dependent on each other in bilateral and multilateral trade relations, these questions become even more important. in vietnam, despite significant achievements in socio-economic development since the introduction of the “doi moi” (renovation) strategy and policy in 1986, vietnam continues to face many development challenges. per capita income is below the national expectation, leading to a high risk of falling into the middle-income trap. productivity growth has slowed down in recent years, and social and environmental problems in economic development are emerging, such as environmental pollution, social evils and increasingly extensive inequalities, weak economic and governance institutions were honestly admitted by the party and government of vietnam (congress, 2016). to achieve the objectives, set out in the 5-year socio-economic development plan 2020-2025 with a vision to 2035, vietnam needs to accelerate its institutional this journal is licensed under a creative commons attribution 4.0 international license cong and uyen.: study of factors affecting micro-barriers that hinders the development of private enterprises: mediating role of intention to use of renewable energy international journal of energy economics and policy | vol 10 • issue 6 • 2020 595 improvement and more effective access to opportunities, and actively participate in solving global challenges if they do not want to lag behind other economies in the region and the world. renewable energy endorses various roles between a variety of variables signifying strengthens and weakness of relationships or impacts. although, renewable energy is based on human exercise the wide benefits enumerated through renewable energy establishes in eliminating various barriers (rezaei and ghofranfarid, 2018). states strive for the deployment of various renewable energy measures to retain the competitive structure while performing varieties of instances pertain to the measures that restrict the development of businesses. the intention of using renewable energy has become the open end for the users individually for the means of different innovation activities that are important for technological and research (bozorgparvar et al., 2018). over the time, renewable energy counted as significant measure through which businesses are inserting robust impacts; therefore, using renewable energy has become dominant source between the supports that are needed for activities of research and technology to induce dominant impact on the barriers of enterprise development (nawaz et al., 2019; shakeel and rahman, 2018). renewable energy could insert its usage between the independent factors of this study to induce its influence upon the dependent factors, although, use of renewable energy could dominantly play a significant role among them the effectiveness of renewable energy helps to elaborate the various benefiting measures exist between them (wojuola and alant, 2017). in addition, vietnam has acknowledged that the market economy can only mature when it is led by the private sector, competition and deeper integration into the global economy. this is a significant stage that all economic models must go through. the way the government intervenes in a market economy to promote the development of the private sector, especially private enterprises, is a topical issue not only for vietnam but also of many other developing countries. it is a strong development of private enterprises that can drive the national economy to break from a developing economy to a developed one. therefore, the case study of vietnam is not only meant to be a typical representative for a developing country desiring to become a developed country, choosing to encourage the development of private enterprises economy with small and medium-sized enterprises as key players; but also marks a great transformation of the role of the state/ government in the economic development of a specific economic model (socialist-oriented market economy). many researchers studying vietnam’s economy think that this is a dynamic and emerging developing economy in southeast asia and asia with an increasingly important role in the international arena, but there are significant barriers that hinder the development of private enterprises at both micro and macro levels. at the microlevel, (wang, 2016) identifies possible barriers as the banking system and financial/credit market; competitive pressures under market mechanism slow growth of the input market; limited confidence among workers; the lack of governance capacity and poor cooperation in application research limited trust in entrepreneurs and poor establishment of entrepreneurship culture, as well as uniformity in organizational structure, are micro barriers to the development of private enterprises (bassey and ekong, 2019; chung, 2017; kazemi, 2013). the study of these barriers for each economy is important in making policy recommendations to remove barriers to private enterprise development in countries where the role of the state/government is considered as a key factor. therefore, the purpose of the study is to assess the factors affecting the micro-barrier system that hinders the development of private enterprises in vietnam. to achieve the purpose of the research, the research needs to answer two research questions: which factors influence micro-barriers that hinder the development of private enterprises in vietnam and what is the degree of influence of those factors? the study used the method of measuring the level of the impact of micro-barrier factors on the development of private enterprises based on the survey sample of 392 vietnamese private enterprises nationwide, mainly private small and medium enterprises (the type of enterprise most affected by micro barriers). 2. theoretical framework many studies address the barriers to private enterprise development in developing countries, especially small and medium-sized private enterprises. the most extensive study, wang (2016) used the cross-country data obtained from the world bank’s enterprise survey of 130,000 businesses in 135 countries and the multivariable regression model investigating barriers to small and medium-sized enterprises in developing countries. the study found five main factors affecting businesses including access to finance, tax rates, competitive pressure, electricity prices, and political factors. the two most influential factors are access to finance and competition. the egyptian economy analyzed and identified major barriers affecting private sector development in the country as difficult access to finance; policy instability and vulnerability in macroeconomic shocks; limited support for private enterprise development by the legal system; lack of market-driven competitiveness in the real estate and energy sectors; weakness of domestic value chains; and financial institutions. the study also identifies barriers by sectors such as energy, banking and finance, industry, and agribusiness. in addition, the research of amentie et al. (2016) using ethiopian interdisciplinary data and the sampling method combined with descriptive statistics identified nine major and moderate factors influencing the development of small and medium enterprises in ethiopia, including micro barriers such as competitive pressure, high-interest rate, debt payment problem of customers, unavailability of raw materials, weaknesses of the banking system and unavailability of corporate credit systems; and the market’s low demand for enterprise products. agreeing with the above study, the poor infrastructure and limited finance, weak management ability and the absence of supporting information as well as low entrepreneurial spirit greatly hinder the development of enterprises in the industry. even if credit is available to small and medium-sized businesses, it is still difficult to access and use this credit flow (salami., 2003). renewable energy widely became a dominant element in various countries which not only helps for businesses but also for various cong and uyen.: study of factors affecting micro-barriers that hinders the development of private enterprises: mediating role of intention to use of renewable energy international journal of energy economics and policy | vol 10 • issue 6 • 2020596 definite means. the importance of renewable energy has gained a dominant place in the literature which has a significant role between varieties of elements existing in studies (ari and yikmaz, 2019). the base of renewable energy eminently discussed in literature helps various countries to establish links between them and insert procedures of cooperation for international integration. the intention of using renewable energy enumerates vast varieties inserts role in the thoughts of business and production while remaining in competitiveness to counter the terminologies that restrict the development of enterprises (kahia et al., 2017). wide studies significant elaborated the using intentions of renewable energy among the development of enterprise where competitiveness in businesses are also eminent. the element of competitiveness in business and production is eminent in the process of eliminating barriers that exist in the development of business whereas the intentions of using renewable energy employs eminent role among them (dogan and ozturk, 2017). the use of renewable energy is eminent in the competitiveness of business and production while renewable energy also asserts dominant measures in the restricting elements of enterprise development (demirbag and yilmaz, 2020). literature induced the various measures for support of technological innovation activities and scientific research among the elements restraining developments of business where renewable energy usage intentions significantly insert possible role between them (uyar and beşikci, 2017). continuing to explore in-depth the internal factors of the enterprise itself as a barrier to private enterprise development, kazemi (2013) surveyed iranian biotechnology product manufacturers and found five main groups of barriers related businesses themselves: limited trust and encouragement for employees, the absence of corporate culture with poor cooperation, solidarity and cultural differences; lack of confidence in entrepreneurs; weak business skills and coordination in the organizational structure as well as poor corporate governance. the research also emphasized the importance of building a startup culture that significantly affects the development of private enterprises. levy (1992) in his study of the furniture industry in tanzania shows that the lack of credit financing in the market makes it difficult for both large and small enterprises to develop. meanwhile, in sri lanka, small and medium enterprises have difficulty accessing the inputs that are the advantages of state-owned corporations. with the ambition to find out if access to finance is a major constraint for small and medium enterprises in most countries. research findings show that in countries with underdeveloped capital markets, the central bank tends to prioritize loans for state-owned enterprises or large enterprises designated by the government instead of promoting capital for small and medium enterprises. agreeing with the above conclusion, chavis et al. (2011) use world bank business survey data to conduct research and find that 31% of businesses consider credit access as the main concern; even the financial barrier causes more serious effectors on small and medium-sized private enterprises than larger firms and this barrier is more impactful than other factors. renewable energy depends on various elements which are positively important for scientific research whereas the dominance of innovation activities are also significantly important technologically to induce influence upon the restraining barriers (higueras-castillo et al., 2019). for enumeration of renewable energy various scientific measures are used however, the existence of renewable energy intentions better enumerates the significance between the technological innovation activities and restricting barriers in the development of enterprises. the source of renewable energy is variant in studies, while literature placed dominant measures for expanding of cooperation between various countries and for the integrations internationally to eliminate the barriers in businesses growth (hai et al., 2017). the overall dependence of renewable energy is based on the state policies for its effective usage among various elements. the effective management policies are efficient for influencing the barriers that restrict the development of enterprise while the positive role of using renewable energy could elaborate positive results from them (irfan et al., 2020). law and tax are also dominant in the intentions of using renewable energy due to the company’s involvement which is using renewable energy for various measures in countering eminent barriers of developing businesses (husin and alrazi, 2017). for cooperation’s that must exist between the states of various countries for renewable energy intentions could enhance its significance between the expansions and international limelight’s on the restricting barriers of developing enterprises. role of renewable energy countered as a dominant place in the literature influencing various factors (komendantova and yazdanpanah, 2017). the intentions of using renewable energy have widely stated by literature through various modes for various purposes. studies into the development of private enterprises and the private sector in vietnam in recent decades generally conclude that private enterprises are facing many development barriers. there are many points of disagreement between the perception of private economic thinking and the development prospect of this economic sector. there is not even a clear definition of private enterprises, which makes it difficult for statistical and research activities. the difficulties in accessing private credit are still seen. only 40% of operating enterprises can access bank loans. many private businesses find it difficult to meet the lending regulations of credit institutions because they are not transparent and fully aware of their financial situation. the private enterprises have high average business costs that reduce competitiveness such as transportation and personnel costs, or the slow and inconsistent development of the input market and the production auxiliary market has caused significant obstacles for the development of vietnamese private enterprises. the barriers to corporate governance are also the reason why the private sector has not yet reached its full potential. to sum up, studied micro-barriers that can impede the development of private enterprises in vietnam are shown in the following table 1: 3. research methodology 3.1. samples samples of the study were selected based on the convenient method, one of the non-probability sampling approaches. according to the convenient sampling method, selected subjects were accessible objects. the survey subjects of this study are cong and uyen.: study of factors affecting micro-barriers that hinders the development of private enterprises: mediating role of intention to use of renewable energy international journal of energy economics and policy | vol 10 • issue 6 • 2020 597 managers and employees in enterprises. in efa, sampling is usually based on (congress, 2016) minimum size and the number of measurement variables in the analysis. hair et al. (1998) suggests that to use efa, the sample size should be at least 50, preferably 100 and the observed/measurement ratio should be 5:1, meaning that a measurement variable needs at least 5 observations. in this study, the total number of observed variables is 42, so the minimum number of samples to achieve is 210. for multivariable regression analysis: the minimum sample size to achieve is calculated by the formula of 50 + 8*m (m: number of independent variables) (tabachnick and fidell, 1996). thus, to identify the factors affecting business development barriers, the study conducted in-depth interviews and used 400 structured questionnaires for management leaders and workers in private enterprises in vietnam. the findings were from 400 questionnaire samples collected. of which 392 were valid, 3 were invalid, 4 were incomplete, and 1 was rated at the same score. 3.2. data analysis method in this study, the authors applied the structural equation modelling (sem) with smart-pls: analysing cronbach’s alpha, confirmatory factor analysis (cfa), and structural equation modelling (sem), specifically as follows: step 1: evaluation of the reliability of the scale. cronbach’s alpha (ca) was used to evaluate the reliability of the scale for each observed variable belonging to the factor groups. peterson peterson (1994) (peterson) suggests that any factor with ca less than 0.6 should be excluded from the research model. step 2: confirmation factor analysis (cfa). the affirmative factor analysis (cfa) is appropriate when researchers have some knowledge of the underlying variable structure. in which the relationship or hypothesis (derived from theory or experiment) between the observed variable and the base factor is accepted by the researchers before conducting statistical testing. in cfa development, the observed variables are also indicator variables in the measurement model, because they “upload” the conceptual basis theory. the factor analysis asserts that cfa accepts the hypotheses of the researchers, determined by the relationship between each variable and one or more factors. indicators for measuring the suitability of the model with data include chi-squared (cmin); chi-square adjusted according to degrees of freedom (cmin / df); comparability index (cfi); tucker and lewis index (tli); and root mean square error of approximation (rmsea). according to hair et al. (1998), if 1 <cmin/df <3, the model is considered to be a good fit. if the model receives cfi values, tli ≥0.9; rmsea ≤0.08, and p > 0.5, the model is suitable for the data. step 3: structural equation modelling (sem). structural equation modelling (sem) helps test a set of regression equations at the same time. in this study, the sem model was implemented to identify the influencing factors and the degree of influence of each factor on the micro-barriers that limit the development of private enterprises. the variables that have been adopted by the present study includes the intention to use of renewable energy (iure) has four items, competitiveness in production and business (cpb) has four items, support for scientific research and technological innovation activities (ssrtia) has three items, expanding cooperation and international integration (ecii) has three items, state management policy (smp) also has three items, law and tax (lt) also has three items and barriers restricting enterprise development (bred) has seven items. these are shown in figure 1. 4. results the findings show the convergent validity that exposes the correlation among the items and the statistics show that the figures of alpha and cr are larger than 0.70 while the figures of loadings and ave are more than 0.50. these statistics proved that convergent validity has valid and high linkage among the items. these statistics are shown in table 2. in addition, the management model assessment reported in figure 2 and structural model assessment reported in figure 3. the findings also show the discriminant validity that exposes the correlation among the variables and fornell larcker along with crossloadings has been conducted for the checking of discriminant validity. the statistics show that the figures of the relationship of variables with itself are more than with other variables. these statistics proved that discriminant validity has valid and no high linkage among the variables. these statistics are shown in tables 3 and 4. table 1: micro barriers restricting the development of vietnamese private enterprises abbreviation barriers restricting enterprise development (micro-level) literature bred 1 the banking system and the financial/credit market amentie et al. (2016); levy (1992); chavis et al. (2011) bred 2 competitive pressure in the market mechanism wang (2016) bred 3 input levy (1992) bred 4 absence of workers’ confidence kazemi, 2013) bred 5 lack of cooperation, governance capacity kazemi (2013) bred 6 lack of confidence in entrepreneurs and entrepreneurship culture kazemi, 2013) bred 7 lack of uniformity in the organizational structure of enterprises (kazemi, 2013) figure 1: theoretical framework cong and uyen.: study of factors affecting micro-barriers that hinders the development of private enterprises: mediating role of intention to use of renewable energy international journal of energy economics and policy | vol 10 • issue 6 • 2020598 table 2: convergent validity constructs items loadings alpha cr ave barriers restricting enterprise development bred1 0.697 0.827 0.868 0.587 bred2 0.762 bred3 0.665 bred4 0.637 bred5 0.625 bred6 0.697 bred7 0.785 competitiveness in production and business cpb1 0.858 0.833 0.900 0.749 cpb2 0.871 cpb3 0.867 expanding cooperation and international integration ecii1 0.689 0.751 0.810 0.588 ecii2 0.843 ecii3 0.761 intention to use of renewable energy iure1 0.877 0.858 0.907 0.713 iure2 0.655 iure3 0.904 iure4 0.914 law and tax lt1 0.862 0.931 0.956 0.880 lt2 0.975 lt3 0.972 state management policy smp1 0.898 0.710 0.790 0.562 smp2 0.657 smp3 0.671 support for scientific research and technological innovation activities ssrtia1 0.922 0.785 0.873 0.699 ssrtia2 0.851 ssrtia3 0.722 figure 2: measurement model assessment table 3: fornell larcker bred cpb ecii iure lt smp ssrtia bred 0.698 cpb 0.569 0.865 ecii 0.356 0.163 0.767 iure 0.685 0.497 0.328 0.844 lt −0.354 −0.254 −0.207 −0.261 0.938 smp 0.582 0.422 0.279 0.517 −0.294 0.750 ssrtia 0.702 0.475 0.243 0.570 −0.511 0.404 0.836 the heterotrait monotrait (htmt) ratio has also been conducted for the checking of discriminant validity. the statistics show that the figures for ratios are not more than 0.90. these statistics proved that discriminant validity has valid and no high linkage among the variables. these statistics are shown in table 5. the path analysis shows that support for competitiveness in production and business (cpb), scientific research and cong and uyen.: study of factors affecting micro-barriers that hinders the development of private enterprises: mediating role of intention to use of renewable energy international journal of energy economics and policy | vol 10 • issue 6 • 2020 599 figure 3: structural model assessment table 4: cross-loadings bred cpb ecii iure lt smp ssrtia bred1 0.697 0.323 0.217 0.375 −0.254 0.300 0.374 bred2 0.762 0.388 0.271 0.466 −0.200 0.295 0.461 bred3 0.665 0.502 0.219 0.548 −0.169 0.766 0.356 bred4 0.637 0.354 0.383 0.290 −0.262 0.280 0.334 bred5 0.625 0.386 0.173 0.417 −0.266 0.274 0.327 bred6 0.697 0.391 0.247 0.549 −0.276 0.427 0.642 bred7 0.785 0.408 0.255 0.583 −0.308 0.381 0.764 cpb1 0.472 0.858 0.189 0.454 −0.239 0.412 0.375 cpb2 0.467 0.871 0.136 0.435 −0.168 0.307 0.376 cpb3 0.538 0.867 0.100 0.401 −0.249 0.376 0.480 ecii1 0.307 0.160 0.689 0.223 −0.050 0.189 0.170 ecii2 0.287 0.100 0.843 0.322 −0.301 0.265 0.222 ecii3 0.205 0.118 0.761 0.182 −0.088 0.168 0.155 iure1 0.533 0.364 0.245 0.877 −0.141 0.451 0.396 iure2 0.608 0.478 0.354 0.655 −0.347 0.272 0.658 iure3 0.568 0.429 0.245 0.904 −0.165 0.538 0.382 iure4 0.564 0.373 0.238 0.914 −0.198 0.475 0.440 lt1 −0.269 −0.223 −0.182 −0.221 0.862 −0.260 −0.455 lt2 −0.364 −0.247 −0.206 −0.257 0.975 −0.286 −0.499 lt3 −0.354 −0.244 −0.194 −0.253 0.972 −0.281 −0.486 smp1 0.568 0.446 0.227 0.513 −0.193 0.898 0.352 smp2 0.301 0.195 0.205 0.248 −0.142 0.657 0.197 smp3 0.383 0.247 0.206 0.342 −0.341 0.671 0.340 ssrtia1 0.685 0.446 0.195 0.564 −0.440 0.391 0.922 ssrtia2 0.640 0.424 0.189 0.472 −0.363 0.281 0.851 ssrtia3 0.377 0.300 0.251 0.366 −0.532 0.357 0.722 technological innovation activities (ssrtia), expanding cooperation and international integration (ecii), and state management policy (smp) has a positive and significant association with barriers restricting enterprise development (bred). however, law and tax (lt) have an insignificant association with barriers restricting enterprise development (bred). in addition, intention to use of renewable energy has positively mediating among the links of competitiveness in production and business table 5: heterotrait monotrait ratio bred cpb ecii iure lt smp ssrtia bred cpb 0.676 ecii 0.479 0.223 iure 0.774 0.581 0.416 lt 0.400 0.288 0.247 0.284 smp 0.751 0.553 0.436 0.680 0.400 ssrtia 0.797 0.576 0.347 0.668 0.625 0.584 cong and uyen.: study of factors affecting micro-barriers that hinders the development of private enterprises: mediating role of intention to use of renewable energy international journal of energy economics and policy | vol 10 • issue 6 • 2020600 (cpb), scientific research and technological innovation activities (ssrtia), expanding cooperation and international integration (ecii), state management policy (smp), law and tax (lt) and barriers restricting enterprise development (bred). these links are shown in table 6. 5. conclusions and policy implications the research has synthesized and analyzed micro-barriers that limit the development of private enterprises, including banking system and financial/credit market; competitive pressure under the market mechanism; source of inputs; lack of confidence among workers; lack of cooperation, governance capacity; lack of confidence in entrepreneurs and entrepreneurship culture; and lack of uniformity in the organizational structure of enterprises. the analysis results show that the factors affecting the micro barriers that limit the development of private enterprises such as state management policies, legal system and taxation, expanding international cooperation and integration, increasing support for scientific research and technological innovation activities and competitiveness in production business areas all have a counter or negative impacts on the factor “micro barriers limit the development of private enterprises.” in other words, when the government creates and supports the development of private enterprises, including good state management policies; transparent and consistent legal and tax system; strengthened international cooperation and integration; increased support for scientific research and technological innovation activities; and increased support for businesses to improve competitiveness in production and business areas, barriers will be removed, thereby promoting the development of private enterprises better. positive results for the role of renewable energy generated from the study. the significance of using renewable energy helps through various channels to interpret the circumstance existing in this study. these findings are same as the output of gabriel (2016) who also examined that enterprze development has inflence on the use of renewable energy. dominant intentions of using renewable energy are where significant in retaining the competitiveness of business and production, renewable energy also dominantly insert significant role among various factors that influences the restricting barriers. results significantly enumerated the benefits of using renewable energy between the elements existing in states for positive implications and different barriers in the development of business and enterprises. a study by munro et al. (2016) examined that positive association among the enerprise development and the use of energy ressources in the country. therefore, the intention of using renewable energy countered as eminent factor inserts role between the factors affecting barriers in the development of enterprises. for the private sector to grow, the government of each country needs to continue its administrative reform, creating a favorable business environment for businesses to develop. at the same time, the government needs to improve its mechanisms and policies to encourage and facilitate strong development of the private economy; develop policies to support the development of small and medium-sized enterprises and start-ups; and develop legal regulations related to business investment, avoiding overlapping, causing difficulties for private enterprises. in doing so, microbarriers that limit the development of enterprises will be gradually removed, paving the way for more sustainable development of private enterprises in the future. this study was conducted in vietnam, a strongly growing economy in southeast asia thanks to drastic reforms of the vietnamese government in managing and operating the economy for a favorable environment for the private sector. therefore, the study can be considered as a meaningful lesson of experience of vietnam for other countries in the region and the world with similar conditions. changing the factors of micro barriers to the development of private enterprises requires a strong innovation of the government role, and the tectonic government is a direction with a lot of advantages. the study also provided similar findings to previous studies on the tectonic government in the countries. references amentie, c., negash, e., kumera, l. (2016), barriers to growth of medium and small enterprises in developing country: case study ethiopia. table 6: a path analysis relationships beta s.d. t-statistics p-values l.l. u.l. cpb -> bred 0.165 0.049 3.355 0.001 0.083 0.234 cpb -> iure 0.206 0.057 3.602 0.000 0.110 0.296 ecii -> bred 0.102 0.039 2.618 0.005 0.037 0.166 ecii -> iure 0.148 0.035 4.206 0.000 0.081 0.203 iure -> bred 0.248 0.042 5.966 0.000 0.181 0.311 lt -> bred 0.035 0.046 0.762 0.224 −0.051 0.110 lt -> iure 0.092 0.053 1.730 0.043 0.005 0.162 smp -> bred 0.208 0.062 3.371 0.001 0.098 0.308 smp -> iure 0.263 0.061 4.284 0.000 0.163 0.377 ssrtia -> bred 0.391 0.051 7.687 0.000 0.307 0.478 ssrtia -> iure 0.377 0.066 5.678 0.000 0.260 0.471 cpb -> iure -> bred 0.051 0.019 2.746 0.004 0.023 0.079 ecii -> iure -> bred 0.037 0.010 3.520 0.000 0.019 0.055 lt -> iure -> bred 0.023 0.014 1.668 0.049 0.001 0.044 smp -> iure -> bred 0.065 0.015 4.452 0.000 0.041 0.086 ssrtia -> iure -> bred 0.094 0.024 3.933 0.000 0.052 0.130 cong and uyen.: study of factors affecting micro-barriers that hinders the development of private enterprises: mediating role of intention to use of renewable energy international journal of energy economics and policy | vol 10 • issue 6 • 2020 601 journal of entrepreneurship and organization management, 5, 190-194. ari, i., yikmaz, r.f. (2019), the role of renewable energy in achieving turkey’s indc. renewable and sustainable energy reviews, 105(2), 244-251. bassey, g.e., ekong, u.m. (2019), energy consumption and inflation dynamics in nigeria: an ardl cointegration approach. energy economics letters, 6(2), 66-83. bozorgparvar, e., yazdanpanah, m., forouzani, m., khosravipour, b. (2018), cleaner and greener livestock production: appraising producers’ perceptions regarding renewable energy in iran. journal of cleaner production, 203(1), 769-776. chavis, l.w., klapper, l.f., love, i. (2011), the impact of the business environment on young firm financing. world bank economic review, 25, 486-507. chung, t.k. (2017), the private sector’s role in vietnam’s economic development model for the period 2016-2020 with a vision to 2035. international journal of economics and management, 80, 4-13. congress, v.c.p. (2016), evaluation of the implemention of the 2011-2015 economic development and socio-economic development directions and missions for 2016-2020. in: proceedings of the 12th vietnam communist party congress. demirbag, m., yilmaz, s. (2020), preservice teachers’ knowledge levels, risk perceptions and intentions to use renewable energy: a structural equation model. journal of education in science environment and health, 6(3), 193-206. dogan, e., ozturk, i. (2017), the influence of renewable and nonrenewable energy consumption and real income on co2 emissions in the usa: evidence from structural break tests. environmental science and pollution research, 24(11), 10846-10854. gabriel, c.a. (2016), what is challenging renewable energy entrepreneurs in developing countries? renewable and sustainable energy reviews, 64, 362-371. hai, m.a., moula, m.m.e., seppälä, u. (2017), results of intentionbehaviour gap for solar energy in regular residential buildings in finland. international journal of sustainable built environment, 6(2), 317-329. hair, j.f., anderson, r.e., tatham, r.l., black, w.c. (1998), multivariate data analysis. upper saddle river, nj: prentice hall. higueras-castillo, e., liébana-cabanillas, f., muñoz-leiva, f., molinillo, s. (2019), the role of collectivism in modeling the adoption of renewable energies: a cross-cultural approach. international journal of environmental science and technology, 16(4), 2143-2160. husin, n., alrazi, b. (2017), renewable energy investment in malaysia: an integrated model in evaluating public decision making process. journal of clean energy technologies, 5(4), 343-346. irfan, m., zhao, z.y., li, h., rehman, a. (2020), the influence of consumers’ intention factors on willingness to pay for renewable energy: a structural equation modeling approach. environmental science and pollution research, 10(2), 1-15. kahia, m., aïssa, m.s.b., lanouar, c. (2017), renewable and nonrenewable energy use-economic growth nexus: the case of mena net oil importing countries. renewable and sustainable energy reviews, 71(3), 127-140. kazemi, a. (2013), studied barriers to entrepreneurship in industrial companies (case study: iranian companies producing biotechnology products. european journal of experimental biology, 3, 484-489. komendantova, n., yazdanpanah, m. (2017), impacts of human factors on willingness to use renewable energy sources in iran and morocco. environmental energy and economic research, 1(2), 141-152. levy, b. (1992), obstacles to developing indigenous small and medium enterprises: an empirical assessment. the world bank economic review, 7, 65-83. munro, p., van der horst, g., willans, s., kemeny, p., christiansen, a., schiavone, n. (2016), social enterprise development and renewable energy dissemination in africa: the experience of the community charging station model in sierra leone. progress in development studies, 16(1), 24-38. nawaz, m.a., azam, m.a., bhatti, m.a. (2019), are natural resources, mineral and energy depletions damaging economic growth? evidence from asean countries. pakistan journal of economic studies, 2(2), 45-53. peterson, r.a. (1994), a meta-analysis of cronbach’s coefficient alpha. journal of consumer research, 21, 381-391. rezaei, r., ghofranfarid, m. (2018), rural households’ renewable energy usage intention in iran: extending the unified theory of acceptance and use of technology. renewable energy, 122(3), 382-391. salami., c.a.t. (2003), guidelines and stackholders responsibilities in smieis. seminar on small and medium industries equity investments scheme (smieis). p50-65. shakeel, s.r., rahman, s.u. (2018), towards the establishment of renewable energy technologies’ market: an assessment of public acceptance and use in pakistan. journal of renewable and sustainable energy, 10(4), 45907. tabachnick, b.g., fidell, l.s. (1996), using multivariate statistics. 3rd ed. united states: harpercollins college. uyar, t.s., beşikci, d. (2017), integration of hydrogen energy systems into renewable energy systems for better design of 100% renewable energy communities. international journal of hydrogen energy, 42(4), 2453-2456. wang, y. (2016), what are the biggest obstacles to growth of smes in developing countries? an empirical evidence from an enterprise survey. borsa istanbul review, 16, 167-176. wojuola, r.n., alant, b.p. (2017), public perceptions about renewable energy technologies in nigeria. african journal of science technology innovation and development, 9(4), 399-409. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 6 • 2021 243 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(6), 243-249. determinants of household electricity demand in rural india: a case study of the impacts of government subsidies and surcharges sijousa basumatary*, mridula devi, konita basumatary department of economics, bodoland university, india. *email: sbbasu6@gmail.com received: 08 june 2021 accepted: 16 september 2021 doi: https://doi.org/10.32479/ijeep.11716 abstract this paper analyses the determinants of household electricity consumption with the focus to find the impact of government subsidies and surcharges on the demand for electricity services in the rural areas. using surveyed household data of 332 samples, quantile regression has been employed for checking heterogeneity in electricity demand across different quantile of households. we find government subsidy has enhanced the household demand for electricity consumption with the elasticity ranging from 45 to 65%. skeptically, electricity consumers of higher quantile tend to consume more even in the presence of outstanding bill while it is the opposite for low quantile group. surprisingly, income and other socioeconomics variables don’t necessarily affect the households demand for electricity. this implies demand for electricity is inelastic to income and selected socioeconomic variables in rural regions. however, electricity demand decreases for households with dwelling characteristics categorized as poorer quantile. based on our empirical findings implications are drawn for policy makers. keywords: electricity, determinants, heterogeneity, quantile, subsidies, surcharges jel classifications: q4, q48, r2, r48 1. introduction in india, providing electricity service to every household started as mission in april 2005 naming it as rggvy (rajiv gandhi grameen vidyutikiran yojana) which was later subsumed and renamed as deendayal upadhayaya gram jyoti yojana (ddugjy) in august 2013 (ddugjy, 2014). infact in 2018 india had declared that all the villages are electrified which attracted criticisms as some of the remote villages were yet to be electrified. but, quickly in 2019 it was once again declared that all the households in india have access to electricity services barring a few remote areas of chhattisgarh (saubhagya, 2019). today the average hours of electricity supplied to the rural areas in india is around 18 h in a day (pib, 2019). while india still struggles to provide 24 h of electricity supply to both rural and urban region households along with major disruptions that arises due to weather conditions, load-shedding and often blackouts in peak evening hours due to demand being always higher than the total supply. assam is no exception, in which some of the households of the region have had the electricity connectivity for just above 5 years or more. practically, the households in assam receive around 19 h (pib, 2019) of electricity supply per day. while it is a wellestablished fact that the socio-economic benefits of electricity services are profoundly effective; it enables a child to read for longer time for a better educational outcome; increase in business hours, productivity and profit for a firm; and empowerment of women by accessibility to television, radios and cell-phones by cultivating better decision making abilities. rural electrification also increases labor supply of men and women, schooling of boys and girls, household per capita income and expenditure (khandker et al., 2014). electricity service in rural areas is a boon that creates avenues and opportunities for the empowerment of this journal is licensed under a creative commons attribution 4.0 international license basumatary, et al.: determinants of household electricity demand in rural india: a case study of the impacts of government subsidies and surcharges international journal of energy economics and policy | vol 11 • issue 6 • 2021244 the households. overall, access to electricity by the households should be an enhancer to their abilities creating better quality of life. however, the electricity bills have become a burden to many of the rural households in assam due to inefficient and faulty billing mechanism which is adversely affecting the economic condition of the households. the present study is undertaken in remote rural areas of assam, india, with the objective of exploring the factors that determine a household’s electricity consumption level. the recent personal survey in those regions reveal uniquely high amount of electricity bills per month. ironically the high average bills for different households in rural areas which are endowed with limited electric appliances and equipments raises an alarm for thorough inspection. along with the socio-economic factors of a household the structure of energy bills has been included to assess all the factors combined. needless to say, presently the households of the rural areas are not only energy poor but they are overburdened with energy bills. there is enormous literature on the determinants of residential electricity demand made at aggregate micro and macro level of the households. most of the earlier studies were done using time series and panel data sets for different countries and regions of the world. they have either used error correction model or panel data econometric analysis technique for identifying the determinants of electricity demand. at the macro level determinants of electricity consumption have been investigated by many researchers such as (narayan et al., 2007), (zhou and teng, 2013) (cialani and mortazavi, 2018) (al-bajjali and shamayleh, 2018) by using time series and panel data sets for identifying the factors that determine household electricity demand. at the micro level, associations between socio-economic and dwelling and demographic characteristics were assessed. studies at micro level such as (santamouris et al., 2007), (wassie et al., 2021), (huebner et al., 2016) have been done for identifying socio-economic, demographic and dwelling characteristics affecting electricity consumption. specifically for india (filippini and pachauri, 2004), (ramachandra et al., 2000), (tewathia, 2014) and (pachauri, 2004) made studies for different parts of india using survey data wherein these studies found that socio-economic, demographic, geographic, family and dwelling attributes influence the total household energy requirements with wide variations in the demand for electricity according to various income groups. specifically (pachauri, 2004) using nsso’s household level survey data had found that “total household expenditure or income level is the most important explanatory variable causing variation in energy requirements across households.” additionally, dwelling size of household and age of the head of the household are related to higher energy consumption. amongst the literature survey made, we find very limited papers that are related to the factors that are core variables for our study i.e. subsidy and surcharges as independent variables affecting the household demand for energy and electricity consumption. but studies related specifically to surcharges to bill defaults is almost nil. studies done on impact of government subsidies on consumer’s electricity demand are also focused mostly on developed countries. a few of them are studies done by (banfi et al., 2005) on the impact of fuel subsidies, (rivers and jaccard, 2011) on the impact of direct subsidy on energy prices, (mirnezami, 2014) studied the impact of electricity subsidization on electricity consumption in canada by using household expenditure data. in the most recent comprehensive study done by (athukorala et al., 2019) found that major determinants of demand for residential electricity are the subsidies, socioeconomic variables and energy saving technology wherein elasticities with respect to subsidy variables are found to be higher than the price variable. as stated earlier there is hardly any study made which is directly or indirectly related to surcharges that are charged by the billing agency due to payment defaults. for us it has become clear that different authors at different points of time have used different tools and techniques, analysed various aspects of household electricity demand for different countries and regions of the world using different forms of data at both micro and macro levels using mostly secondary data or indirect primary data sets. above all the basic objective remains the same i.e. to identify the important determinants of residential demand for electricity consumption. we also find there is still a huge vacuum of analysis related to subsidies of different forms for developing countries both at micro and macro level and considerably void in terms of surcharges incurred by consumers. particularly, our study is focused to identify the impact of government subsidies and surcharges on the electricity consumption at the household level using primary survey data of the households in rural areas of india. our paper is different and would be a bridge for literature gap, which takes into account of the issue of surcharges incurred recurrently in determining electricity consumption by households across different income groups in the rural areas. 2. materials and methods 2.1. data and variables the study uses both primary and secondary data. secondary data on the household’s monthly electricity consumption bill was obtained from the assam power distribution corporation limited (apdcl) website1. the electricity bills accessed also contain information of government subsidy and surcharges amount in it. notably, apdcl is the sole authority for distribution, trading and supply of electricity in the state of assam or outside it. within assam, primary data was collected from the rural areas of 4 districts of btr (bodoland territorial region) using stratified random sampling. a total of 332 sample households were selected for collecting primary information related to socioeconomic and dwelling characteristics of the household. description and type of variables used in our study are given in details in table 1. we have used current demand as the dependent variable and the independent variables are categorized into 3 different types: category 1: subsidies and surcharges; category 2: socioeconomic characteristics; category 3: dwelling characteristics. 2.2. statistical analysis for this study we have used the modified cobb-douglas model for estimating the household electricity demand. cobb-douglas 1 official website of assam power distribution corporation limited: https:// www.apdcl.org/website/viewbill. monthly household electricity bill are available in the website for maximum of five months including the current month’s bill. https://www.apdcl.org/website/viewbill https://www.apdcl.org/website/viewbill basumatary, et al.: determinants of household electricity demand in rural india: a case study of the impacts of government subsidies and surcharges international journal of energy economics and policy | vol 11 • issue 6 • 2021 245 table 1: description of variables variables dependent variable variable definition current demand amount of bill for previous month electricity consumption (in. rs)2 independent variables variable definition related literatures 1. subsidies and surcharges government subsidy amount the government bears as a subsidy for a consumer’s bill in a month (in rs) few close studies related to government subsidies in fuel subsidies and pricing dynamics with government intervention were done by (banfi et al., 2005), (rivers and jaccard, 2011), (mirnezami, 2014) and (athukorala et al., 2019). outstanding bill3 total bill accumulated over a period of time due to payment defaults including surcharges on outstanding bill (in rs). relatively none 2. socioeconomic variables family income amount of money a household earns per month taking all sources of income combined (in rs) several studies done by (brounen et al., 2102), (jones and lomas, 2015), (weismann et al., 2011), (yohanis et al., 2008), (tiwari, 2000), (bedir et al., 2013), (cramer et al., 1985) and (mansouri et al., 1996) found that households with higher income were found to higher consumers of electricity. education level highest level of education obtained by a member resident of the household(in years) (kostakis, 2020), found that level of education of the household has a positive effect on household electricity consumption. family size total family members residing in the household (number). households with more members likely to consume more electricity (jones and lomas, 2015), (bartusch et al., 2012), (ndiaye and gabriel, 2011), (bedir et al., 2013), (cramer et al., 1985) school/college going school and college going students in the household (number). households with teenagers more likely to consume more electricity (brounen et al., 2102) retired total retired persons in the household(number) (jones and lomas, 2015), (tiwari, 2000) found households with persons 65+ are likely to consume more electricity. minimum watt minimum watt required to run a electric appliance present in the household (watts)4 studies done by (huebner et al., 2016), (ndiaye and gabriel, 2011), (kavousian et al., 2013), (weismann et al., 2011), (yohanis et al., 2008), (tiwari, 2000), (bedir et al., 2013), (cramer et al., 1985) and (mcloughlin et al., 2012) found that households with more number of electric appliances have higher electricity bills. area housing area (in bigha5) (brounen et al., 2102), (kavousian et al., , 2013), (weismann et al., 2011), (jones and lomas, 2015), (yohanis et al., 2008) found that larger floor area is associated with more electricity consumption living rooms living rooms in the household (number) almost identical and similar to studies done by (huebner, david, hamilton, chalabi, & oreszczyn, 2016), (brounen, kok, & quigly, 2102), (kavousian, rajagopal, & fischer, 2013), (weismann, azevedo, ferrao, & fernandez, 2011), (jones & lomas, 2015), (yohanis, mondol, wright, & norton, 2008). 3. dwelling characteristics (dummy) floor of the house roof of the house floor of the house categorized into 3 parts; pukka(concrete), kutcha(non-concrete) and mixed roof of the house categorized into 2 parts; tin and terrace. studies have found that building characteristics have a sizeable impact on electricity consumption (huebner, david, hamilton, chalabi, & oreszczyn, 2016), (santin, itard, & visscher, 2009), (steemers & yun, 2009), (weismann, azevedo, ferrao, & fernandez, 2011), (yohanis, mondol, wright, & norton, 2008). equation for capturing electricity consumption of a household is given as2345 5 6 7 8 9 101 4 32 12 0 11 ββ β β β β ββ β ββ β == ∑ ji i i i i i i i jij i i i y r c el aa fm wt lr d ec gs ost (1) 2 current demand = number of units consumed * price per unit + electricity duty + current surcharge + fixed charge– government subsidy. 3 outstanding bill = arrear principle + arrear surcharge 4 watts are calculated as minimum watts required for running electric appliance multiplied by the number of appliances. standard minimum watts consumed by a appliance accessed from https://letsavelectricity.com/ wattagepower-consumption-of-household-appliances/ 5 unit of measurement for land area, 1 bigha = 14,400 sq ft. (nredc, 2020). where eci is the electricity consumed by a household in units, β0 is the constant term, yi refers to average monthly income of the household, gsi is the amount of subsidy (in rs) given by the government per month for a household, osti is the outstanding bill that is accumulated for a household due to non-payment previous months electricity bills (here we have assumed both these variables inversely affects the current electricity consumption for a household i.e., current consumption reduces/increases when the gsi and osti are high/low respectively), ri is the number of retired personnel (65 years) living in the house; ci is the number of school college going students in the household, eli is the highest level of education obtained in the household (in years)6; aaiis the housing area of the 6 according to the standard years required for school, colleges and university basumatary, et al.: determinants of household electricity demand in rural india: a case study of the impacts of government subsidies and surcharges international journal of energy economics and policy | vol 11 • issue 6 • 2021246 household; fmi is the total family members in the household, wti is the minimum amount of required watts to power up the appliances present in the household, lri is the number of living rooms in the household and dji are set of dummy variables which captures the heterogeneity of household electricity consumption. the parameters β1, β2 and β3 are interpreted as elasticities of electricity consumption for a household’s income, government subsidy and outstanding bill respectively. taking log of eq. 1 and adding error term εi we can estimate it using ols which yields the marginal effects of the independent variables on electricity demand. but our aim is to find out the heterogeneity that underlies in determinants of electricity consumption i.e. whether the explanatory variables has different impacts across a conditional quantile of electricity consumer households. so, we adopt the quantile regression developed by (koenker nd bassett, 1978). it produces more unbiased (olsen et al., 2012) and robust estimates than the linear regression model when the data sets are large and it contains outliers (tilov et al., 2020) and (yeh et al., 2009). quantile regression approach has been extensively used by (tilov et al., 2020), (romero et al., 2016), (kostakis, 2020), (athukorala et al., 2019), (huebner et al., 2016) for detecting and quantification of the effects of determinants on selected quantile for the study concerned. additionally, the box-plot of the units of electricity consumption of the households in figure 1 illustrates that its distribution does not follow normal distribution. as stated above the main objective of this study is to investigate how the effects of socio-economic predictors vary across different levels of electricity consumption of the households. infact, (tilov et al., 2020) had stated that qr addresses namely the question of whether an explanatory variable has different impacts across conditional quantiles. taking logarithms of eq. 1, quantile regression for analyzing the determinants of electricity consumption across the conditional distribution of dependent variable eci is given as 0 1 2 3 4 6 7 8 9 12 10 11 θ θ θ θ θ θ θ θ θ θ θ θ θ β β β β β β β β β β β β = = + + + + + + + + + + + +∈∑ i i i i i i i i i i i j ji i j lec l l y l gs l ost l r l c l el l aa l fm l wt l lr d (2) level studies in assam, india. in eq. 2, “θ” is the quantile in the distribution of household electricity current demand and can take values between zero to unity. “βθi”, measures the impact of respective independent variable on the current demand for electricity consumption in different quantiles “θ” chosen. with this we can ascertain whether the households of different electricity consumption levels quantiles will react same or differently according to the exogenous variables chosen for the study. technically, for 0 <θ <1, with quantile quantile y x xi� �� � � � � � � � � where y is the dependent variable and x is the set of independent variables and θ is the set of conditional distribution with θ quantiles. the parameters ˆ iθβ is obtained by minimizing the asymmetric weighted sum of absolute deviations given as i lnec n i i lnec n i i xi i xi lnec x lnec x : : | | | | � � � �� � �� � � � � � � � �� �1 now, ˆ iθβ can be interpreted as marginal effects for the respective quantile chosen (angrist and pischke, 2009) 3. results and discussion to analyse the association between the current demand for electricity and the three categories of exogenous variables viz. government subsidies and surcharges, socioeconomic variables and dwelling characteristics, we have used the classical ols and quantile regression analysis techniques. the descriptive statistics of the variables are given in table 2. the combined results are given in table 3. we find that there are variations in the coefficients obtained using ols and quantile regression. surprisingly we do not find any coefficients for income which is statistically significant in ols and in all the percentiles though a negative effect is seen for ols, 10th and 50th quantile while an insignificant positive effect is observed for 25th, 75th and 90th quantile respectively. results from table 3 indicate that rural household’s current demand for electricity is inelastic to their monthly income. this is partially attributable specifically to the rural areas where the households consume electricity only upto a certain free unit. thus our study contradicts the findings of (cramer et al., 1985), (santamouris et al., 2007) (zhou and teng, 2013) and (haas et al., 1998), (kostakis, 2020), (weismann et al., 2011), (yohanis et al., 2008) and (tewathia, 2014). however, our result is in line with (filippini and pachauri, 2004) and (athukorala et al., 2019). figure 1: box plot of current demand table 2: descriptive statistics of quantitative variables variable mean std. dev. min max current demand 2.353338 0.3649755 1.1461 3.5099 income 4.216323 0.3848518 3.4771 5 govt. subsidy 1.55006 0.4379701 0 2.3729 outstanding 1.712554 1.54235 0 4.8064 members 4.46729 1.50614 2 12 retired 0.9595016 0.8338044 0 4 living rooms 3.647975 1.195331 1 8 school/college 1.103125 0.9527997 0 4 area 0.7076324 0.4157403 0.25 2 min. watt 2.8033 0.56169 1.0414 3.772 education 13.86293 2.594447 10 16 basumatary, et al.: determinants of household electricity demand in rural india: a case study of the impacts of government subsidies and surcharges international journal of energy economics and policy | vol 11 • issue 6 • 2021 247 table 3: ols and quantile regression result variables ols percentiles 10 25 50 75 90 income −0.021 (0.081) −0.153 (0.148) 0.010 (0.037) −0.015 (0.036) 0.011 (0.050) 0.071 (0.110) govt. subsidy 0.310* (0.039) 0.459* (0.119) 0.624* (0.017) 0.634* (0.018) 0.564* (0.032) 0.444* (0.081) outstanding 0.023** (0.011) −0.000 (0.019) 0.007 (0.005) 0.016* (.005) 0.027* (0.008) 0.054* (0.019) members −0.012 (0.016) −0.015 (0.036) −0.001 (0.008) (0.003) (0.007) −0.002 (0.009) 0.001 (0.017) retired 0.010 (0.023) 0.003 (0.051) −0.019** (0.010) −0.013 (0.010) 0.009 (0.014) 0.008 (0.031) living rooms 0.002 (0.018) (0.040) (0.040) 0.003 (0.008) 0.004 (0.008) 0.004 (0.012) 0.008 (0.022) school/college −0.012 (0.023) −0.009 (0.047) −0.007 (0.011) −0.016 (0.010) 0.001 (0.015) −0.007 (0.022) area −0.067 (0.042) −0.027 (0.069) −0.012 (0.017) −0.008 (0.020) −0.028 (0.030) −0.045 (0.058) min watt 0.159* (0.051) 0.163*** (0.100) 0.037 (0.023) 0.038*** (0.023) 0.059** (0.031) 0.071 (0.047) education 0.010 (0.009) 0.004 (0.017) 0.004 (0.004) 0.006 (0.004) 0.008 (0.005) 0.014 (0.011) kutcha(dum_11) −0.103*** (0.056) −0.521* (0.105) −0.007 (0.026) −0.014 (0.025) ref ref mix(dum_21) 0.045 (0.069) (−0.188) (0.148) −0.060** (0.033) 0.017 (0.032) 0.043 (0.044) 0.087 (0.086) pukka(dum_31) 0.103*** (0.056) ref ref 0.014 (0.025) 0.016 (0.035) 0.076 (0.056) terrace(dum_21) 0.217** (0.103) ref ref 0.131* (0.046) 0.280* (0.064) 0.229 (0.146) tin(dum_22) −0.217** (0.103) (0.050) (0.108) −0.018 (0.047) −0.131* (0.046) −0.280* (0.064) ref _cons 1.561* (0.287) 1.516* (0.614) 1.174* (0.141) 1.220* (0.115) 1.172* (0.168) 1.023* (0.350) r2 0.352 mean vif 1.79 breusch-pagan (h0:constant variance) chi2 = 0.71 pseudo r2 0.227 0.381 0.435 0.418 0.358 signs (*), (**) and (***) indicates significance level at 1, 5 and 10% respectively. standard errors are given in parentheses. the primary variable of our study, government subsidy is statistically significant and positive at 1% level of significance for both ols and all the percentiles. the impact of subsidy is found to be the highest (63%) among the median electricity consumers followed by 25th and 75th quantiles with 62% and 56% respectively. evidently, elasticity of current demand for electricity increases from the 25th quantile upto the median quantile and decreases up the higher quantiles. it implies that government subsidy has increased the current demand for electricity consumption in the rural areas (table 3). our results are in line with (athukorala et al., 2019), (banfi et al., 2005), (rivers and jaccard, 2011) and (mirnezami, 2014) which shows that government subsidy plays a significant role in household’s demand for energy consumption. skeptically, we find the outstanding bills has a significant positive impact on the current demand for households of higher quantiles i.e., 50th, 75th and 90th while it is negative though not statistically significant for lowest 10th quantile. it indicates electricity consumer of lower quantile tend to consume less electricity as the outstanding bill accumulate whereas the electricity consumers of higher quantile tend to consume more even in the presence of outstanding bills. this is attributable to the increase in current demand of electricity by the households of higher quantile from their previous demand due to addition of appliances stock (table 3). next we find the minimum watt consumed by a household has a positive and statistically significant effect on the current demand for electricity (except for 25th and 90th quartile). overall, the coefficient value increases in ascending order as we proceed to higher quantiles. for the 5 quantiles of our study this is attributable to increase in addition of more electricity consuming appliances in the households resulting in higher electricity demand. as for the 25th and 90th quartile, one is not in the capacity to add more appliances on the other hand the richer households have almost reached a saturation point for addition of appliances in the household. intuitively, it implies that households with more number of electric equipments tend to consume more electricity in rural areas. our results are similar in terms of the positive impact of stock of electric appliances used by a household. studies done by (kavousian et al., 2013), (huebner et al., 2016), (athukorala et al., 2019) have proven this. dwelling characteristics of the household in terms of the floor and roof of a house are important determinants for electricity basumatary, et al.: determinants of household electricity demand in rural india: a case study of the impacts of government subsidies and surcharges international journal of energy economics and policy | vol 11 • issue 6 • 2021248 consumption. with the ols regression we find that houses with kutcha floors and tin roofs have a significant and negative impact on the current demand for electricity (table 3). this indicates that poorer households in the rural areas tend to consume lesser electricity than the richer counterparts as synonymously affluent households are assumed to have concrete floor and roof of a house. on the contrary we find households with terrace as roof has a positive and significant impact on the household’s current demand for electricity. overall, dwelling characteristics have a positive impact higher up the quantile while negative effect is observed for households of lower quantiles. interestingly we do not find the remaining socioeconomic variables statistically significant viz. total family members in a household, retired persons in a household, number of living rooms in the house, number of school/college going students and the housing area of a household (table 3). our study contradicts studies made by (athukorala et al., 2019), (huebner et al., 2016), (kostakis, 2020), (romero et al., 2016), (weismann et al., 2011), (weismann et al., 2011), (yohanis et al., 2008) and (kavousian et al., 2013) with exact or similar degree of the variables defined by them. 4. conclusion and implications our study was conceived with the primary aim to check the impact of subsidies, surcharges and outstanding bills on the current demand for electricity consumption in the rural areas. based on the results obtained we can draw three main conclusions. firstly, the government subsidy has enabled the rural households for higher electricity consumption in rural areas which is consistent with studies done by (athukorala et al., 2019), (banfi et al., 2005), (rivers and jaccard, 2011) and (mirnezami, 2014). while this increase in demand rises from the lowest to the middle consumer groups (45-63%) and decreases for the higher consumer groups. in case of the outstanding variable it is observed that current demand for electricity also increases due to accumulation of past electricity bills for a household. usually a well informed household would want to consume less units of electricity when their outstanding bills are high but we do not find it to be so. we are skeptical about this result as it has been found in the survey that the households accumulation of bills (outstanding) is not due to past 2-3 month’s bill but it was due to the bill that was produced before them 4-5 months back which was for a whole period from initial connection till the recent month. secondly, results suggest that the rural households are less sensitive to electricity bills as the elasticity of income is found to be insignificant for all the quantile groups. additionally, socioeconomic variables in our study are also found to be practically insignificant. thirdly, the dwelling characteristics of lower quantile have a negative impact on the electricity demand with the floor and roof type which is typically assigned to poorer segments of the population i.e., kutcha floors and tin roofs. overall our study reveals that subsidy provided by the government has played a significant role in reducing the burden of electricity bills in rural areas. for policy implications some decisions can be made based on the results for the households residing in rural areas. we find the demand for electricity is income inelastic along with the socioeconomic characteristics but responsive to the government subsidies in line with (athukorala et al., 2019). therefore, the government’s efforts to achieve energy sufficiency and also compensate its transmission and distribution losses by increasing the cost price per unit of electricity will prove to be ineffective as demand for electricity is dependent on the amount of subsidies the households receive in the rural areas. so raising the price will reduce the demand which will indirectly affect the well-being of a household. therefore, the government is encouraged to continue the electricity subsidy for the rural households. on the contrary, for the demand and supply side management, government can distribute basic electricity efficient appliances at a lower cost, stronghold and regulate the electricity saving technological products and industries to bring the cost down and finally spread awareness for electricity conservation at the grassroots level. lastly, the government can find a way out for amicable solution to the outstanding bills that have been accumulated for the rural households over the years inaudibly. references al-bajjali, s.k., shamayleh, a.y. (2018), estimating the determinants of electricity consumption in jordan. energy, 147, 1311-1320. angrist, j.d., pischke, j.s. (2009), most harmless econometrics: an empiricist’s companion. london: princeton university press. athukorala, w., wilson, c., managi, s., karunarathna, m. (2019), household demand for electricity: the role of market distortions and prices in competition policy. energy policy, 134, 110932. banfi, s., filippini, m., hunt, l.c. (2005), fuel tourism in border regions: the case of switzerland. energy economics, 27(5), 689-707. bartusch, c., odlare, m., wallin, f., wester, l. (2012), exploring variance in residential electricity consumption: household features and building properties. applied energy, 92, 637-643. bedir, m., hasselaar, e., itard, l. (2013), determinants of electricity consumption in dutch dwellings. energy and buildings, 58, 194-207. brounen, d., kok, n., quigly, j.m. (2102), residential energy use and conservation: economics and demographics. european economic review, 56 (5), 931-945. cialani, c., mortazavi, r. (2018), household and industrial electricity demand in europe. energy policy, 122, 592-600. cramer, j.c., miller, n., craig, p., hackett, b.m., dietz, t.m., vine, e.l., levine, m.d., kowalczyk, d.j. (1985), social and engineering determinants and their equity implications in residential electricity use. energy, 10 (12), 1283-1291. ddugjy. (2014), ministry of power, government of india. available from: https://powermin.gov.in/sites/default/files/uploads/deendayal_ upadhyaya_gram_jyoti_yojana.pdf filippini, m., pachauri, s. (2004), elasticities of electricity demand in urban indian households. energy policy, 32, 429-436. huebner, g., david, s., hamilton, i., chalabi, z., oreszczyn, t. (2016), understanding electricity consumption: a comparative contributionn of building factors, socio-demographics, appliances, behaviours and attitudes. applied energy, 177, 692-702. jones, r.v., lomas, k.j. (2015), determinants of high electrical energy demand in uk homes: socio-economic and dwelling characteristics. energy and buildings, 101(15), 24-34. kavousian, a., rajagopal, r., fischer, m. (2013), determinants of residential electricity consumption: using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants’ behavior. energy, 55(15), 184-194. khandker, s.r., samad, h.a., ali, r., barnes, d.f. (2014), who benefits basumatary, et al.: determinants of household electricity demand in rural india: a case study of the impacts of government subsidies and surcharges international journal of energy economics and policy | vol 11 • issue 6 • 2021 249 most from rural electrification? evidence in india. the energy journal, 35(2), 75-96. koenker, r., bassett, g. (1978), regression quantiles. econometrica, 46(1), 33-50. kostakis, i. (2020), socio-demographic determinants of household electricity consumption: evidence from greece using quantile regression analysis. current research in environmental sustainability, 1, 23-30. mansouri, i., newborough, m., probert, d. (1996), energy consumption in uk households: impact of domestic electrical appliances. applied energy, 54(3), 211-285. mcloughlin, f., duffy, a., conlon, m. (2012), characterising domestic electricity consumption patterns by dwelling and occupant socioeconomic variables: an irish case study. energy and buildings, 48, 240-248. mirnezami, s.r. (2014), electricity inequality in canada: should pricing reforms eliminate subsidies to encourage efficient usage? utilities policy, 31, 36-43. narayan, p.k., smyth, r., prasad, a. (2007), electricity consumption in g7 countries: a panel cointegration analysis of residential demand elasticities. energy policy, 35, 4485-4494. ndiaye, d., gabriel, k. (2011), principal component analysis of the electricity consumption in residential dwellings. energy and buildings, 43(2-3), 446-453. olsen, c.s., clark, a.e., thomas, a.m., cook, l.j. (2012), comparing least-squares and quantile regression approaches to analyzing median hospital charges. academic emergency medicine, 19(7), 866-875. pachauri, s. (2004), an analysis of cross-sectional variations in total household energy requirements in india using micro survey data. energy policy, 32(15), 1723-1735. pib. (2019), ministry of power, government of india. available from https://pib.gov.in/pressrelesedetailm.aspx?prid=1592833 ramachandra, t.v., subramanian, d.k., joshi, n.v., gunaga, s.v., harikantra, r.b. (2000), domestic energy consumption patterns in uttara kannada district, karnataka state, india. energy conversion and management, 41, 775-831. rivers, n., jaccard, m. (2011), retrospective evaluation of electric utility demand-side management programs in canada. energy, 32(4-5), 93-116. romero, j.d., rio, p.d., penasco, c. (2016), an analysis of the welfare and distributive implications of factors influencing house hold electricity consumption. energy policy, 88, 361-370. santamouris, m., kapsis, k., korres, d., livada, i., pavlou, c., assimakopoulus, m.n. (2007), on the relation between the energy and social characteristics of the residential sector. energy and buildings, 39(8), 893-905. santin, o.g., itard, l., visscher, h. (2009), the effect of occupancy and building characteristics on energy use for space and water heating in dutch residential stock. energy and buildings, 41(11), 1223-1232. saubhagya. (2019), ministry of power, government of india. available from https://saubhagya.gov.in steemers, k., yun, g.y. (2009), household energy consumption: a study of the role of occupants. research on building stocks, 37(5-6), 625-637. tewathia, n. (2014), determinants of the household electricity consumption: a case study of delhi. international journal of energy economics and policy, 4(3), 337-348. tilov, i., farsi, m., volland, b. (2020), from frugal jane to wasteful john: a quantile regression analysis of swiss households’ electricity demand. energy policy, 138, 1-11. tiwari, p. (2000), architectural, demographic, and economic causes of electricity consumption in bombay. journal of policy modelling, 22(1), 81-98. wassie, y.t., rannestad, m.m., adaramola, m.s. (2021), determinants of household energy choices in rural sub-saharan africa: an example from southern ethiopia. energy, 221, 119785. weismann, d., azevedo, i. l., ferrao, p., fernandez, j.e. (2011), residential electricity consumption in portugal: findings from top-down and bottom-up models. energy policy, 39(5), 2772-2779. yeh, c.c., wang, k.m., suen, y.b. (2009), quantile analyzing the dynamic linkage between inflation uncertainty and inflation. problems and perspectives in management, 7(1), 21-28. yohanis, y.g., mondol, j.d., wright, a., norton, b. (2008), real-life energy use in the uk: how occupancy and dwelling characteristics affect domestic electricity use. energy and building, 40(6), 1053-1059. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 3 • 2021388 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(3), 388-394. energy consumption, governance quality and sustainable development nexus: empirical evidence from mena countries mongi lassoued* department of economics, higher institute of finance and fiscality, university of sousse, sousse, tunisia. *email: lassouedmongi4@gmail.com received: 30 december 2020 accepted: 01 march 2021 doi: https://doi.org/10.32479/ijeep.11259 abstract the objective of this paper is to empirically examine whether energy consumption and governance quality affect sustainable development in 17 middle east and north africa (mena) countries over the period 1984-2018 using a simultaneous equation model (sem). empirical results provide evidence that control of corruption and the institutional or governance quality of are complementary and essential for energy consumption to have an indirect positive impact on sustainable development. the results also show that sustainable development reacts negatively to energy consumption because the poor governance quality in mena countries. these empirical insights are of particular interest to policymakers to improve the governance quality and implement sound economic policies to support economic development. keywords: governance quality, energy consumption, economic growth, simultaneous equation model jel classifications: h11, q01, q43, c30 1. introduction achievement of the sustainable development goals (sdgs) varies considerably across countries in the middle east and north africa (mena). certain problems in the region such as conflicts in some mena countries have not allowed remarkable progress in terms of the sustainable development goals (sdgs), in particular for poverty reduction and in terms of peace, justice and institution building (cuaresma et al., 2019). mena countries face major challenges in achieving sustainable development goals, due to stunting and sustainable use of energy resources. access to infrastructure, which is mainly covered by the affordable and clean energy goal, has improved rapidly. on the other hand, the high carbon dioxide (co2) emissions contained in fossil fuel exports have a negative effect and slow down the achievement of the climate action target iea (2019). however, further efforts should be made to tackle the higher levels of corruption perceived under the 16th sustainable development goal (sdg) (peace, justice and strong institutions) (transparency international, 2020). achieving this goal will allow the transition to more circular and green economies. but such a goal of sustainable development is not easy to achieve, as governance and the quality of public services are major challenges in the mena countries (sachs et al., 2019). according to the indicators of governance in the world which are determined by the world bank in 2016, the region has achieved poor results in terms of corruption control and government efficiency (praia city group, 2020). as a result, public services are inefficient, and there is a decline in trust in public authorities. in the middle east and north africa (mena), citizens aspire to achieve the goals of sustainable development through greater influence over government decisions (sachs et al., 2019). this could also be achieved through a more efficient and responsive public sector and through the eradication of corruption. on the other hand, tackling them through initiatives promoting sustainable and inclusive governance and development represents a global public good that could defuse problems and contribute to the achievement of peace and stability (oecd, 2020). by examining the relationship between corruption, oil rents and state stability, this journal is licensed under a creative commons attribution 4.0 international license lassoued: energy consumption, governance quality and sustainable development nexus: empirical evidence from mena countries international journal of energy economics and policy | vol 11 • issue 3 • 2021 389 lópez and mitra (2000) concluded that an increase in oil rents significantly increases the level of corruption. several studies have shown that corruption raises a set of challenges. some economists have opted for the analysis of the effects of corruption. this has led to the emergence of several currents in the literature relating to corruption. most traditional economic research has tended to determine the direct effect of corruption on certain macroeconomic variables. some researchers such as svensson (2005) have focused on the impact of corruption on economic growth. thus, corruption and other governance quality are taken into account in the literature as being factors that could affect the overall factor productivity of the country. referring to lópez and mitra (2000), actual and polluting emissions are significantly higher than levels which are socially optimal in relation to per capita gdp. this reflects ineffectiveness of public authorities due to government decisions. indeed, it has been noticed that when the degree of corruption is higher, the difference of polluting emissions compared to the social optimum will also be greater. according to sachs et al. (2019), the impact of financial liberalization on environmental policy remains dependent on the degree of corruption. a higher level of corruption normally results in a greater impact of trade liberalization on the quality of the environment. the impact of corruption on the quality of the environment materializes through indirect effects on natural resources. indeed, wendling et al. (2018) have shown that the decisions taken by public authorities for the use of natural resources are strongly influenced by major lobbies which defend their personal interests. while, the most empirical works analyze the direct impact of corruption on the degree of pollution (ahmad et al., 2020), the investigation of the indirect effects of corruption on sustainable development through the channel of energy consumption are very limited or even non-existent (cole, 2007). in this paper, we attempt to examine the effects of corruption on sustainable development taking into account the close relationship between environmental degradation and energy consumption. the analytical framework that we have adopted in this work incorporates an approach that is developed by eren et al. (2019). in this regard, we have decomposed the effects of corruption in our model into direct effects and indirect effects. corruption could have a direct impact on the quality of the environment through tax laws and regulations. however, corruption affects sustainable development through its effect on the quality of the environment and therefore on economic growth. in fact, corruption could negatively impact economic growth; because any increase in the degree of corruption lead to a significant drop in the gdp growth rate. in turn, this drop in gdp could affect the quality of the environment by resorting to the theory of the kuznets curve (goh and ang, 2018). the main objective in this paper is to examine the effect of corruption on sustainable development through the effect on energy consumption for a panel of 17 mena countries for the period 1984-2018, using a simultaneous equations model. our contribution is to explore (i) the direct interdependent relationships between the control of corruption and economic growth, degradation of environmental quality and energy consumption, and (ii) the indirect relationship between corruption and sustainable development through the mediating effect of energy consumption. the rest of the paper is organized as follows. section 2 presents an overview of the literature review on the subject area. section 3 describes the data and methodology used. section 4 interprets the empirical results. section 5 concludes and draws some policy recommendations. 2. literature review 2.1. relationship between corruption and sustainable development more recent literature has demonstrated the multiple economic and environmental implications of controlling corruption (wendling et al., 2018). however, the empirical studies have yielded mixed results (halliru et al., 2020). some authors have found that corruption has a negative impact on the quality of the environment. corruption could lead to dysfunctional governance systems in a country (raza and shah, 2018). this could contribute to the disappearance of species, the misuse of natural resources, pollution and environmental degradation and the spread of invasive diseases (wiebe et al., 2018). in fact, corruption leads to social underoptimization of environmental governance. thus, wendling et al. (2018) showed that this could be done by restraining environmental regulations through corrupt decisions. in a context of corruption, some actors pay the biggest bribes at the expense of optimal results (fredriksson et al., 2004). however, tougher and more stringent environmental policies appear in a context of weaker corruption. some other empirical work has shown that corruption affects the environment through the development of the informal sector. indeed, cole (2007) pointed out that strict environmental regulations and laws could encourage companies to resort more to the informal economy in order to achieve maximum profits. in this regard, corruption allows polluting industries to evade environmental regulations and laws. therefore, welsch (2004) showed that productive activities in the context of the informal economy are capable of increasing pollution levels and causing degradation of environmental quality. in the same context, cole (2007) justified a positive impact of corruption on the quality of the environment. the latter showed that corruption could in particular improve the quality of the environment through its negative impact on the rate of economic growth. this could be explained by the decrease in the quantities of pollutants emitted following the decline in economic growth. welsch (2004) showed that there is an indirect and implicit effect of corruption on the quality of the environment through the effect of corruption on income. 2.1.1. how corruption affects growth? many studies have examined the impact of corruption on economic growth, but this has not led to a consensus among economists on the importance of controlling corruption. according to the world bank (2020), asian countries experienced a high level of corruption during the period 1986-1996, but this did not prevent these countries from achieving an average annual rate of economic growth of about 7% while it was 2.5% in the rest of the world for the same period. this report could challenge most of the results found in previous empirical studies. several researchers drawing on the pioneering lassoued: energy consumption, governance quality and sustainable development nexus: empirical evidence from mena countries international journal of energy economics and policy | vol 11 • issue 3 • 2021390 work of mauro (1995) have shown that corruption could hold back growth and development. however, some other studies showed that corruption could have a positive impact on economic growth in the slowness of bureaucratic formalities and the rigid regulations dictated by governments, allow escaping the inefficiencies of imposed policies (leff, 1964). thus, corruption could increase economic efficiency and positively influence economic growth. on the other hand, various empirical works reveal that corruption is a destabilizing factor of economic growth. these results are also confirmed by fredriksson et al. (2004) who found that corrupt officials can waste public funds by diverting collected taxes or by granting advantages to private actors who pay the biggest bribes. working on a sample of 109 countries, takuma et al. (2014) found that the interaction between corruption and financial openness could have a significant and negative effect on economic growth. this result showed that financial openness further amplifies the negative impact of public authorities’ corruption on economic growth. dong et al. (2017) showed that the positive impact of corruption on economic efficiency remains conditioned by a real and optimal size of government. this implies the possibility that economic growth can increase the level of corruption. in addition, he found that the level of corruption declines with economic development. this contradiction in terms of the results found leads us to push further studies on the question. 2.1.2. how corruption affects energy? although energy is a diversified sector made up of a mixture of public and private actors generally situated in a context of monopoly competition, it is not immune to corruption. according to transparency international (2020), only nine out of 32 miners where coal, oil, natural gas and uranium mining takes place have a corruption perception index (cpi) score that is greater than 5.0. the other 23 have a score below 4.8. this finding is consistent with the result found by takuma et al. (2014) who showed that economies heavily dependent on oil are often characterized by a high level of corruption and poor governance. referring to the work of fredriksson et al. (2004), corruption can influence energy policy through three channels. first, a higher level of corruption could hamper the stringency of energy policies. second, according to takuma et al. (2014), the increased costs arising from the coordination of corruption lead to more rigid energy policies. third, the weight of lobbying lobbies from owners of capital depends on the distribution of income between these pressure groups. using dynamic panel data applied on energy intensity (energy consumption per unit of value added) in oecd countries for the period 1982-1996. fredriksson et al. (2004) found conclusive results. they found that there is a strong correlation between a higher level of corruption and low energy efficiency in oecd countries. second, increased coordination costs seem to limit the impact of pressure exerted by pressure groups made up of capital owners and workers. by focusing exclusively on energy-intensive sectors, they showed that the costs of coordination have perverse effects in terms of the political influence of these two lobbies. 2.2. relationship between energy consumption and sustainable development several works have focused on the relationship between economic growth and environmental quality, following an acceleration of the noticeable degradation of air quality. according to the environmental kuznets curve (ekc), an increase in economic growth could lead to an increase in co2 (carbon dioxide) emissions (world bank, 2019). these emitted quantities of co2 begin to decrease when production reaches an optimum level (dong et al., 2017). the literature relating to the environmental kuznets curve (ekc) is subdivided into two categories of researches. we find empirical work that is qualified as cross-sectional studies (shahbaz et al., 2013). the second group of empirical work consists of panel studies (al-mulali and ozturk, 2015). using a sample of 12 mena countries to determine the relationship between co2 emissions, energy use (ec), and economic growth rate, ozcan (2013) concluded that the inverted u-shaped ekc assumption is verified for the following countries: egypt, the united arab emirates and lebanon. referring to the literature, we can see that energy consumption has negative effects on the quality of the environment (alola et al., 2019). however, increased co2 emissions have caused catastrophic damage to the quality of the environment (qiao et al., 2019). some work showed that the consumption of non-renewable energies, although it stimulates economic growth, it could also increase co2 emissions. al-mulali and ozturk (2015) tried to determine the nature of the relationship between urbanization (ur), energy consumption (ec), industrial production (ip), trade openness (ot) and political stability (ps) on the deterioration of environmental quality, using a sample of mena countries and adopting the fully modified ordinary least squares (fmols) technique. they concluded that all of these exogenous variables (ur, ec, ip, ot and ps) increase environmental damage in these countries. in addition, a two-way causality has been observed between ec and environmental quality in the short and long term. this causal relationship between ec and environmental quality has not been confirmed in the work of omri et al. (2015) who found unidirectional causal links running from ec to co2 emissions, without any feedback effect. according to schwab (2019) the relationship between ec and economic growth (gdp growth) has been widely discussed in the context of energy economics. a large number of empirical works such as begum et al. (2015) and le quere et al. (2020) found a strong correlation between ec and gdp growth. al-mulali and ozturk (2015) showed a one-way causality ranging from ec to gdp. narayan and popp (2012) found unidirectional causal relationship running from gdp to ec for g6 countries. a long-term, positive, two-way causal links between ec, gdp, and co2 emissions has been found by al-mulali and ozturk (2015) in latin america and the caribbean countries. dong et al. (2017) found no causality links between ec and gdp. 3. data and methodology 3.1. model specification the purpose of this paper is to investigate the impact of control of corruption (cc) on the energy consumption (ec) and sustainable development (sd) through the governance quality indicator (iqg) in 17 mena countries over the period 1984-2018. to this end, we estimate the following simultaneous equations model: 4 , 0 1 , 2 , , , 3 i t i t i t i i t i t i y g e x ε = =∝ + ∝ + ∝ + ∝ +∑ (1) lassoued: energy consumption, governance quality and sustainable development nexus: empirical evidence from mena countries international journal of energy economics and policy | vol 11 • issue 3 • 2021 391 z y e vi t i t i t i i i t i t, , , , ,� � � � � � �� � � � �0 1 2 3 4 (2) e y c ri t i t i t i i i t i t, , , , ,� � � � � � �� � � � �0 1 2 3 4 (3) where eq. (1) represents the sustainable development equation, eq. (2) represents the corruption equation and eq. (3) represents the energy consumption equation. by introducing all the control and exogenous variables, the three above equations take the following forms: , 0 1 , 2 , 3 , 4 , 5 , 6 , 7 , , i t i t i t i t i t i t i t i t i t sd iqg ec trade inv hk fdi pop α α α α α α α α ε = + + + + + + + + (4) cc sd ec iqgi t i t i t i t i t, , , , ,� � � � �� � � � �0 1 2 3 (5) ec sd cc cgi t i t i t i t i t, , , , ,� � � � �� � � � �0 1 2 3 (6) where sdi,t represents the supported sustainable development variable, which is determined by the sustainable development indicator used by the world bank and is calculated as follows: sd gni c cg nct k k kp p h n� � � �� �� � �� � � �� � � (7) where gni is the gross national income; cp is the fixed capital consumption of poor households; cg is consumption for the public sector; nct is the net current transfer; kp is produced capital which consists mainly of fixed assets which are used on a permanent basis in production processes for a period of more than 1 year. we obtained the value of produced capital from the balance sheet accounts of the national accounts. it is accepted that the observed market prices for produced capital reliably express their impacts on well-being. kh represents investments in human capital which are measured by all expenditure on education; kn corresponds to the depreciation of material capital measured by the sum of depreciation of the depreciated resources plus environmental pollution. eq. (4) states that the sustainable development (sd) is a function of indicator quality of governance iqg, energy consumption ec and a set of control and exogenous variables such as trade openness (trade), investment (inv), human capital (hk), foreign direct investment (fdi) and population growth rate (pop). eq. (5) states that the control of corruption (cc) is regressed on sustainable development (sd), energy consumption (ec) and the quality of governance indicator (iqg), which reflects the quality of public services and its degree of autonomy in the face of political pressure and interference, the quality of the execution of policies and the government’s credibility towards these policies. eq. (6) states that the energy consumption (ec) is regressed on sustainable development (sd), control of corruption indicator (cc) and the consumption of government (cg). in our models, we assume that all the equations are over-identified. indeed, there are three endogenous variables in the model, that is, sd, cc and ec, and exogenous variables, that is, pop, inv, trade, hk, fdi, iqg and cg. in the total we have 10 variables (k=10). eq. (4) has 6 exclusion restrictions and no constraint restrictions. by applying the identification requirements, the variables in eq. (4) give: w' = 1, k’ = 6 and r = 0 (no correlation between variables) with w' is the number of endogenous variables and k' is the number of exogenous variables. therefore: w w '+ k k' = 3 1 + 11-6 = 7 > w 1 = 3 1 = 2, eq. (4) is on-identified. eq. (5) presents 7exclusion restrictions but no constraint restrictions. we consequently w = 3, k = 11, w’ = 1, k’ = 3 and r = 0, which gives: w w' + k k' = 3 1 + 11 3 = 10> w 1 = 2, eq. (5) is over-identified. eq. (6) has 6 restrictions of exclusion but no constraint restrictions. we therefore w = 3, k = 11, w’ = 1, k’ = 3 and r = 0. this implies w-w '+ k – k’ = 3 1 + 11-3 = 10> w 1 = 2, eq. (6) is over-identified. since in our model all equations are over-identified, the model will be on-identified. if order conditions (necessary conditions) are satisfied, it is also important to check the rank conditions (sufficient conditions). however, in practice these steps are difficult to implement. this is what prompts us to limit our analysis to the level of checking the order conditions. in our work, the presented model is econometrically over-identified. the method sur (seemingly unrelated regression) seems to be the most suitable for dealing with this kind of model. however, we note that our model is characterized by the presence of a problem of endogeneity of order two, which is why the estimate by the twostage least squares (2sls) regressions would be recommended. 3.2. data description the sample data used in this study covering 17 mena countries namely; algeria, bahrain, egypt, mauritania, iraq, kuwait, morocco, qatar, lebanon, libya, oman, saudi arabia, syria, tunisia, jordan, uae and yemen over the period 1984-2018. the data are gathered from the world bank world development indicators (wdi). the data on governance quality indicators are from the world bank worldwide governance indicators (wgi). table 1 provides the data sources and definitions of the variables. table 2 presents the descriptive statistics of the variables used. it is shown that the arithmetic means are very low for the variables except for ec and sd. the standard deviation is very low for the different variables except for sd, it is equal to 6.5239. overall, we can retain that the quality of precision of these variables is very good table 1: definitions of variables variables definitions source sustainable development (sd) the sustainable development wdi control of corruption (cc) control of corruption wgi human capital (hk) tertiary enrollment rate wdi domestic investment (inv) gross fixed capital formation to gdp growth wdi demographic variable (pop) the population growth rate wdi foreign direct investment (fdi) net flows of foreign direct investment wdi trade openness (trade) the sum of exports and imports to gdp wdi government consumption (gc) the level of government consumption as a percentage of gdp wdi quality of governance (iqg) the indicator quality of governance wgi energy consumption (ec) public spending in energy consumption as a percentage of gdp wdi lassoued: energy consumption, governance quality and sustainable development nexus: empirical evidence from mena countries international journal of energy economics and policy | vol 11 • issue 3 • 2021392 table 2: descriptive statistics variable obs. mean sd min. max. ec 595 9.7864 1.0696 7.5775 12.2710 sd 595 0.6825 6.52396 0.4511 0.8501 cc 595 −0.2609 1.1339 −14.5747 2.6021 gc 595 0.5446 0.1324 0.1666 0.8733 iqg 595 −0.1623 0.7350 −1.9470 1.9165 trade 595 −0.3006 1.1810 −4.6705 1.7633 hk 595 1.1830 0.3073 −1.1006 1.7830 pop 595 2.9142 2.5036 −2.9623 17.4832 fdi 595 2.0238 3.4072 −5.2881 33.5660 inv 595 1.4560 5.0049 0.0002 26.6156 source: author’s calculations based on data from wdi and wgi table 3: correlation matrix ec sd cc gc iqg trade hk pop fdi inv ec 1.0000 sd −0.0742 1.0000 cc −0.0834 0.1050 1.0000 gc −0.2330 0.0435 0.3225 1.0000 iqg −0.2789 0.0944 0.4032 0.5160 1.0000 trade −0.1937 0.0122 0.2690 0.6466 0.4098 1.0000 hk 0.0673 −0.0341 −0.0515 −0.0377 −0.2196 0.1199 1.0000 pop 0.1592 0.0720 0.2254 0.1317 0.3563 −0.0019 −0.2527 1.0000 fdi −0.2149 0.0783 0.0683 0.0612 0.1178 0.1175 0.2523 0.0938 1.0000 inv −0.2364 0.0014 0.0054 0.0525 0.0769 0.4123 0.1274 −0.1325 0.0746 1.0000 because the variance of each variable in our model is very low. the exception is noted only for the sd since the variance of this variable is very high. hence, the linear adjustment of development expressed by the sd could be bad. the minimum values of these variables are located around 10 except for sd which takes a minimum figure equal to 0.4511. the maximum values of these variables do not exceed 27 with the exception of fdi which has very high maximum figures. table 3 presents the correlation matrix of the endogenous and exogenous variables. the results of the matrix of correlation coefficients indicate that sd positively affects the different variables except hk variable which shows a negative relationship with the sd. also, the cc variable has a positive impact on the various variables except for hk which is negatively correlated with the cc. trade has a positive effect on all variables except for the pop. fdi increases the sd and positively affects the various components of gross domestic product. the results confirm the absence of a multi-collinearity problem since the coefficients of the total correlations between the explanatory variables are low. hence, we find a total absence of the correlation between the explanatory variables. we adopt the structural model which allows us to determine the direct impact of each indicator on the endogenous variable. this will allow us to detect the feedback effects exerted between the endogenous variables. we then opt for a transformation of this structural model into a “reduced” one in order to explain how these variables are substituted in the equations of the other endogenous variables. 4. empirical results the crucial objective of this work is to identify which of the institutional or governance indicators that could better promote the sd and ec. the iqg, in this case, can play a key role in the management of public expenditure, in particular ec and its importance in stimulating the sd. in each equation, we analyze each time the effect of iqg on the other variables. indeed, we started by primarily determining the direct effect of the iqg on the sd. the regression will be repeated in eqs. (5) and (6). table 4 reports the 2sls regression results of the effects of ec and iqg on the sd. indeed, regarding eq. (4), the regression results show that iqg is positively but statistically insignificant correlated with the sd. this brings us back to remember that the quality of governance does not explain the sustainable development. this result that we have found brings us back to remember that the quality of governance in the mena region is ineffective. this ineffectiveness stems from the poor institutional quality that accompanies poor governance, which reinforces the ineffectiveness of government power to stimulate the sustainable development in the mena region. in this context, the capacity of the state to control corruption remains dependent on its credibility with regard to its people and it also depends on the establishment of institutions that should be credible and powerful. from eq. (5), it shows that the effect of the iqg remains significant at the 1% level and positively correlated with cc. regarding the effect of the iqg and gc on ec, the regression results show a negative and significant effect of the cc on ec. the empirical evidence also shows a significant negative impact of the sd and gc on ec. therefore, we can retain that the institutional indicator remains effective since the iqg has a positive indirect effect and could contribute to the creation of wealth in a context of economic and social development. a good orientation of public expenditure towards the energy sector translates into effective action of good governance. this makes it possible to deduce that when gc has a negative effect on ec this comes from a misallocation of resources. in addition, filmer et al. (2000) draw on certain research results which assume that a homogeneous distribution of public health expenditure is beneficial for different social groups. they have also shown that the effects of gc on ec will be even greater for poor populations. but it could be argued that before opting for an increase in gc, strategies should be put in place for good governance of gc through a good allocation of financial resources. finally, we find that the direct impact of gc appears in a clear way on spending that is intended for ec, since the regression results indicate a negative and significant effect at the 1% level. so this brings us back to remember that gc is more essential to improve lassoued: energy consumption, governance quality and sustainable development nexus: empirical evidence from mena countries international journal of energy economics and policy | vol 11 • issue 3 • 2021 393 basic social sectors and in particular the energy sector and therefore this gc could stimulate ec. this can only be achieved through good and efficient government management. however, energy resources did not have a significant positive effect on the mena economies; by default this impact is by no means positive. the revenues that are generated by energy exports from these countries have been intended to fuel the development of some industrial sectors more than others. several research studies have shown that oil and gas reserves are also likely to emerge differences between various economies in the world, and even be a source of tension and conflict nationally and bilaterally. some researchers working on the energy issue have suggested that in countries like sudan, iraq and yemen, the wealth that comes from energy sources in those countries does not automatically translate into prosperity and human development. they have shown that this can only be achieved through good and efficient government management and a local modus operandi that allows a large number of citizens, rather than a few, to benefit and prosper from the energy resources of their country. all of these conditions are essential ingredients for turning energy resources into an engine for growth and development rather than economic decline and recession. 5. conclusion and policy implications in this paper, we focused on the impact of the cc on sd through ec. we also tried to know to what extent the iqg in mena countries is effective in the decisions taken in terms of resources allocation, particularly energy. using a panel data set of 17 mena countries over the period 1984-2018, and 2sls approach, the results suggest that iqg plays a crucial role in the sd. the iqg seems to have a positive and significant effect on the cc, which maintains their role as a catalyst for the sd. the results also show that the iqg alone does not largely explain the sd. this allows us to remember that the quality of governance in the mena region remains a sterile and ineffective factor. this could be explained as being the result of poor iqg which is accompanied by ineffectiveness of public power in order to avoid wasting gc especially in ec. this ineffectiveness of public authorities could translate into the absence of a will to direct and guide public resources towards the right model of the sd in the mena region. energy resources have undoubtedly played a crucial role in the economic development of mena region in recent years. the region’s energy sources have influenced choices for economic development. they have also shaped economic structures, encouraged certain models of industrial activity and brought about the integration of most of the mena countries into the world economy. in addition, the industrial oil and gas sectors represent the most important source of income and wealth for many oil and gas producing and exporting countries. this allowed for these countries the creation of modern welfare states among the gc states. thanks to this, we have also seen the emergence of development programs in a number of medium-sized producing countries. despite the efforts made by some mena countries, progress towards the achievement of the sustainable development goals (sdgs) in most mena countries is still limited. the arab forum for environment and development (afed) report concludes that achieving the sdgs remains a major challenge facing mena countries. according to the 9th annual report of this forum, these goals cannot be achieved without the resolution of the several violent conflicts in the region (un–united nations, 2018). saab and abdul-karim (2016) pointed out that governments in the mena region will not be able to achieve the sdgs by 2030 by still adopting the same traditional methods. the afed report argued that a change in the design of anti-corruption strategies is essential if mena countries are to achieve the sdgs through beneficial energy consumption. a wide range of strategies for good governance are urgently needed to ensure that programs for achieving the sdgs are economically equitable and environmentally acceptable. in addition, the adoption of anti-corruption strategies is a prerequisite for making a qualitative transition towards sustainable development. it is recommended to reform the current institutional qualities at regional and national level, for example by creating councils for sustainable development (sachs et al., 2018). these institutions help ensure better coordination between government entities and non-state stakeholders. we can see that in all the countries where these new institutions have been put in place, sustainable development is more advanced. finally, in order to fight against corruption through the quality of governance, the government authorities are called upon to opt for an update of the standards and legal texts. they must also create new laws likely to affect the socio-economic reality of the citizens of this region. this could be one of the primary objectives of current economic policies in order to improve the wealth of the country while limiting corruption. table 4: two-stage least squares (2sls) regressions variables sd (4) cc (5) ec (6) sd 0.0127* (1.62) −0.0256** (−2.67) ec −0.7390*** (−2.12) 0.0039 (0.12) cc −0.0318*** (−3.80) iqg 0.5247 (0.103) 0.6109*** (8.39) hk −0.3775 (−0.31) fdi 0.1246 (1.31) trade −0.2422 (−0.79) inv 0.0202 (0.3) -pop 0.1234 (0.91) gc −1.7649*** (−4.6) _cons r2 12.6351*** (3.24) −0.2629 (−0.57) 10.8272 (3.71)*** 0.155 0.213 0.521 no. observations 595 595 595 no. groups 17 17 17 the t-statistics are in parentheses. ***,**,*denote significance at the 1%, 5% and 10% levels, respectively lassoued: energy consumption, governance quality and sustainable development nexus: empirical evidence from mena countries international journal of energy economics and policy | vol 11 • issue 3 • 2021394 references ahmad, m., jabeen, g., irfan, m., mukeshimana, m.c., ahmed, n., maria, j. (2020), modeling causal interactions between energy investment, pollutant emissions, and economic growth: china study. biophysical economics and sustainability, 5(1), 1-12. al-mulali, u., ozturk, i. (2015), the effect of energy consumption, urbanization, trade openness, industrial output, and the political stability on the environmental degradation in the mena region. energy, 84, 382-389. alola, a.a., bekun, f.v., sarkodie, s.a. (2019), dynamic impact of trade policy, economic growth, fertility rate, renewable and non-renewable energy consumption on ecological footprint in europe. science of the total environment, 685, 702-709. begum, r.a., sohag, k., abdullah, s.m.s., jaafar, m. (2015), co2 emissions, energy consumption, economic and population growth in malaysia. renewable and sustainable energy reviews, 41, 594-601. cole, m.a. (2007), corruption, income and the environment: an empirical analysis. ecological economics, 62(3-4), 637-647. cuaresma, j.c., fengler, w., kharas, h., bekhtiar, k., brottrager, m., hofer, m. (2019), will the sustainable development goals be fulfilled? assessing present and future global poverty. palgrave communications, 4(29), 1-8. dong, k., sun, r., hochman, g. (2017), do natural gas and renewable energy consumption lead to less co2 emission? empirical evidence from a panel of brics countries. energy, 141, 1466-1478. eren, b.m., taspinar, n., gokmenoglu, k.k. (2019), the impact of financial development and economic growth on renewable energy consumption: empirical analysis of india. science of the total environment, 663, 189-197. filmer, d., hammer, j., pritchett, l. (1998), health policy in poor countries: weak links in the chain, policy research working paper, no. 1874. washington, dc: the world bank. fredriksson, p.g., vollebergh, h.r.j., dijkgraaf, e. (2004), corruption and energy efficiency in oecd countries: theory and evidence. journal of environmental economics and management, 47(2), 207-231. goh, t., ang, b.w. (2018), quantifying co2 emission reductions from renewables and nuclear energy-some paradoxes. energy policy, 113, 651-662. gpsdd, world bank group, united nations, and sdsn. (2019), data 4 now: accelerating sdg progress through timely information (concept note). washington, dc: world bank group. halliru, a.m., loganathan, n., hassan, g.a.a., mardani, a., kamyab, h. (2020), reexamining the environmental kuznets curve hypothesis in the economic community of west african states: a panel quantile regression approach. journal of cleaner production, 276, 124247. iea. (2019), co2 emissions from fuel combustion 2019. paris: international energy agency. available from: https://www.iea.org/ reports/co2-emissions-from-fuel-combustion-2019. le quéré, c., jackson, r.b., jones, m.w., smith a.j.p., abernethy, s., andrew, r.m., de-gol, a.j., willis, d.r., shan, y., canadell, j.g., friedlingstein, p., creutzig, f., peters, g.p. (2020), temporary reduction in daily global co2 emissions during the covid-19 forced confinement. nature climate change, 10, 647-653. leff, n.h. (1964), economic development through bureaucratic corruption. american behavioral scientist, 8(3), 8-14. lópez, r., mitra, s. (2000), corruption, pollution, and the kuznets environment curve. journal of environmental economics and management, 40(2), 137-150. mauro, p. (1995), corruption and growth quarterly. journal of economics, 60(3), 681-712. narayan, p.k., popp, s. (2012), the energy consumption-real gdp nexus revisited: empirical evidence from countries. economic modelling, 29(2), 303-308. oecd. (2020), a territorial approach to the sustainable development goals: synthesis report. oecd urban policy reviews. paris: oecd publishing. omri, a., daly, s., chaibi, a., rault, c. (2015), financial development, environmental quality, trade and economic growth: what causes what in mena countries. energy economics, 48, 242-252. ozcan, b. (2013), the nexus between carbon emissions, energy consumption and economic growth in middle east countries: a panel data analysis. energy policy, 62, 1138-1147. praia city group. (2020), handbook on governance statistics. praia group on governance statistics. qiao, h.., zheng, f., jiang, h., dong, k. (2019), the greenhouse effect of the agriculture-economic growth-renewable energy nexus: evidence from g20 countries. science of the total environment, 671, 722-731. raza, s.a., shah, n. (2018), testing environmental kuznets curve hypothesis in g7 countries: the role of renewable energy consumption and trade. environmental science and pollution research, 25, 26965-26977. saab, n., abdul-karim, s., editors. (2016), sustainable development in a changing arab climate. how can arab countries achieve sustainable development goals by 2030. beirut, lebanon: arab forum for environment and development. sachs, j., schmidt-traub, g., kroll, c., lafortune, g., fuller, g. (2018), global responsibilities: implementing the goals-sdg index and dashboard report 2018. new york, usa: bertelsmann stiftung and sustainable development solutions network. sachs, j.d., schmidt-traub, g., mazzucato, m., messner, d., nakienovic, n., rockström, j. (2019), six transformations to achieve the sustainable development goals. nature sustainability, 2(9), 805-814. sachs, j., schmidt-traub, g., pulselli, r.m., gigliotti, m., cresti, s., riccaboni, a. (2019), sustainable development report 2019-mediterranean countries edition. siena, italy: sustainable development solutions network for the mediterranean area (sdsn-mediterranean). schwab, k. (2019), the global competitiveness report 2019. geneva: world economic forum. available from: https://www.reports. weforum.org/global-competitiveness-report-2019. shahbaz, m., ozturk, i., afza, t., ali, a. (2013), revisiting the environmental kuznets curve in a global economy. renewable and sustainable energy reviews, 25, 494-502. svensson, j. (2005), eight questions about corruption. journal of economic perspectives, 19(3), 19-42. takuma, k., okada, k., shibata, a. (2014), corruption, capital account liberalization, and economic growth: theory and evidence. international economics, 139, 80-108. transparency international. (2020), corruption perceptions index 2019. berlin : transparency international. available from: https://www. transparency.org/cpi2019?/news/feature/cpi-2019. un-united nations. (2018), the sustainable development goals report 2018. new york, united nations. welsch, h. (2004), corruption, growth, and the environment: a cross-country analysis. environment and development economics, 9(5), 663-693. wendling, z.a., emerson, j.w., esty, d.c., levy, m.a., de sherbinin, a. (2018), 2018 environmental performance index. new haven, ct: yale center for environmental law and policy. available from: https://www.epi.yale.edu. wiebe, k.s., bjelle, e.l., többen, j., wood, r. (2018), implementing exogenous scenarios in a global mrio model for the estimation of future environmental footprints. journal of economic structures, 7(20), 1-18. world bank. (2020), gdp per capita, ppp (current international dollars). washington, dc: world bank. available from: https://www.data. worldbank.org/indicator/ny.gdp.pcap.pp.cd. world bank. (2019), tracking sdg7: the energy progress report 2019. washington, dc: world bank. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 3 • 2021176 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(3), 176-183. advantages and disadvantages of renewable energy sources utilization dario maradin* university of rijeka, faculty of economics and business, rijeka, croatia. *email: dario.maradin@efri.hr received: 09 december 2020 accepted: 15 febraury 2021 doi: https://doi.org/10.32479/ijeep.11027 abstract renewable energy sources are still not the predominant energy resource in the energy sector, although in certain developed countries they participate in a significant share in electricity generation. it is estimated that world energy consumption from renewable energy sources exceeds 20% at the present and continues to grow. renewable energy sources appear as an additional source of energy in the conventional electro-industry. the main reason for the increasing investment and exploitation of renewables is certainly environment preservation and environmental aspect of sustainability. this study seeks to expand the existing literature and contribute to a comprehensive understanding of the characteristics of renewable energy sources as a whole. therefore, the purpose of this paper is to determine the advantages and disadvantages of renewable energy sources utilization in general, without considering the individual type of renewables, such as wind or solar energy. thereby, the paper presents numerous advantages of using renewable energy in the electricity generation, such as environment preservation in terms of reduced greenhouse gas emissions or improvement of innovations and technical/technological development. there are also presented certain disadvantages of renewables in the production of electricity, such as dependence on weather conditions or low energy efficiency and low ability to produce electricity. keywords: renewable energy sources, boosting the economy, environment preservation, renewables limitations jel classifications: q42, q56 1. introduction alternative or renewable forms of energy appear as a supplement to conventional forms of energy, and, although in certain developed countries they participate in a significant share in energy production, they are still not the predominant energy resource in the energy sector. it should be noted that, in addition to the production of electricity, alternative forms of energy provide a significant role in the production of thermal energy. renewable sources in electricity / heat generation do not pollute the environment with greenhouse gas emissions and enable the use of limited fossil resources in the future. this is the main reason for the increasing investment and exploitation of renewable energy sources. the increase in use of alternative forms of energy is a consequence of growing economic development of individual national economies (the classification of the international monetary fund, the world bank or the united nations development program can serve as a criterion for economic development). on the other hand, the production and use of alternative energy plants encourages the development of new technologies in energy, the development of entrepreneurship and, ultimately, the entire economy, confirming the mutual impact on each other. in analysing renewable energy sources, the existing literature presents a number of advantages and disadvantages of their overall utilization. thus, mohtasham (2015) pointed out that application of any renewable energy requires a sustainability analysis, which has dependency on three main components, which are environmental effects, externalities costs, and economics and financing. ellabban et al. (2014) indicated global benefits of renewable energies production where they categorized it to environmental, economic, this journal is licensed under a creative commons attribution 4.0 international license maradin: advantages and disadvantages of renewable energy sources utilization international journal of energy economics and policy | vol 11 • issue 3 • 2021 177 technological, social and political aspects. in addition, they proposed renewable energy market development process and depicted barriers to renewable energy technology deployment. moreover, peidong et al. (2009) presented disadvantages of renewable energy development policy in china, which could be lack of coordination and consistence in policy, weakness and incompleteness in encouragement system, lack of innovation in regional policy, incomplete financing system for renewable energy projects or inadequate investment in the technical research and development for renewable energy. on the other hand, liu (2017) explored the influence of renewable energy policy in china and strategy for its development. maradin et al. (2017) analysed positive and negative economic effects of renewable energy technologies. they have shown that renewable energy technologies have a multiplier effect in stimulating the economy and the development of not only the energy sector but also all the supporting activities related to such industry. in addition, the advancement of technology enables the costs of renewable energy technologies to decrease (akinci, 2019). decreasing investment costs also stimulate competition in the renewable energy sector (tokic et al., 2020). furthermore, competitive activity in the renewable energy sector has again an impact on cost reduction and efficient operation of energy companies. it is necessary to emphasize that the majority of studies analyse an individual renewable energy source as a separate category, without considering them as a whole. to the best of authors’ knowledge, afore-mentioned represents a notable lack of researches in the field of renewable energy sources, their advantages and disadvantages. therefore, this study seeks to expand the existing literature and contribute to a comprehensive understanding of the characteristics of renewable energy sources. given the mentioned above, the purpose of this paper is to determine the advantages and disadvantages of renewable energy sources utilization in general, without considering the individual type of renewables, such as wind or solar energy. thereby, the paper presents numerous advantages of using renewable energy in the electricity generation, such as environment preservation in terms of reduced greenhouse gas emissions or improvement of innovations and technical/technological development. there are also presented certain disadvantages of renewables in the production of electricity, such as dependence on weather conditions or low energy efficiency and low ability to produce electricity. in analysing alternative forms of energy, this paper first defines the concept of alternative, namely renewable forms of energy, after which numerous advantages and disadvantages of using renewable energy sources in electricity generation are explained. finally, the conclusions of the research are presented. 2. defining renewable energy sources at the current stage of technical-technological development, fossil fuels supply most of the world’s energy requirements. although there are questions about the availability of energy resources, environmental pollution and related limitations in their use, fossil fuels are expected to be an important resource in providing energy in the coming decades, especially electricity (dresselhaus and thomas, 2001). however, in order to meet the growing global energy needs while preserving the environment, and to leave the possibility of using fossil fuels in the future, alternative “clean” energy sources are being developed that do not depend on fossil resources and have an acceptable impact on the environment. precise definition of alternative energy sources is “challenging,”s primarily due to the existence of diverse energy resources and choices, as well as various goals that promote their operation. however, in less words, alternative energy sources are all those energy sources that are an alternative to fossil resources. although certain authors (michaelides, 2012; kowalski, 2011) state nuclear energy as one of the sources of alternative forms of energy and there are conflicting views in this regard, this paper does not analyse the justification or challenge of such inclusion nor does nuclear energy be viewed in the context of alternative forms of energy. the expression alternative forms of energy are commonly used for renewable energy sources. renewable energy sources are defined as any energy resource that can be naturally renewable at a rate comparable to or faster than the energy consumption rate of that resource or as a durable resource that is abundantly available in nature (van vliet, 2012). renewable energy sources are inexhaustible sources, namely even though energy conversion processes consume them, their quantities are only temporarily depleted and they can always be compensated or renewed (labudović and barbir, 2002). strielkowski et al. (2013) stated that the renewable energy sources are able to endorse independence, employment and inherently improve environment, as it will be presented in this study. apart from the fact it leaves the option of using fossil fuels in the future, the use of renewable energy sources has an impact on the preservation of the environment as well as it contributes to the ecological aspect of sustainability as the direct use of renewable sources, in principle, does not pollute the environment (denona et al., 2012). this is one of the main advantages in encouraging the production of electricity from renewable sources. more specifically, nezhnikova et al. (2018) argued that the use of renewable energy sources has increased significantly in recent years due to a number of advantages: (i) first, from the point of view of energy security, renewable energy sources can provide opportunities for diversification of fuel mixtures; (ii) secondly, the widespread use of renewable sources reduce the impact on the environment (reduce co2 emissions and air pollution); (iii) thirdly, renewable energy sources are actively used in packages of measures to restore the economy in response to the global economic downturn; (iv) fourth, renewable energy sources can be one of the most effective tools for solving the problem of access to energy. renewable energy sources can be divided into wind energy, solar energy, hydropower, energy obtained from biomass (plant maradin: advantages and disadvantages of renewable energy sources utilization international journal of energy economics and policy | vol 11 • issue 3 • 2021178 matter), geothermal energy (earth’s heat) and ocean energy, which can include wave energy, tidal energy and sea current energy (armstrong and hamrin, 2000). it is estimated that world energy consumption from renewable energy sources has increased by about 4 times in the last decade, and at present exceeds 20% and continues to grow (chubraeva and sergey, 2018). in this regard, the next part of the paper analyses the ecological dimension of renewable energy sources, and namely the resulting greenhouse gas emissions of individual renewable sources during the overall life cycle of a renewable plant, and other benefits achieved through the use of renewable energy sources. 3. advantages of renewable energy sources utilization alongside with the growing interest in the availability and availability of fossil energy resources and the exponential growth of energy demand over the last decades, renewable energy sources are becoming an important additional energy resource in meeting the needs, especially for electricity. utilization of natural, unlimited energy resources from the environment with the aim of converting them into electricity, while ensuring the environmental aspect, gives renewable energy sources numerous advantages in their use, primarily the protection of environment. this is especially evident by the fact that renewable energy sources account for zero or almost zero percent of greenhouse gas emissions and other air pollution (united nations development programme, 2000). a comprehensive indicator of environmental pollution caused by a certain type of power plant in the activity of electricity production can be determined by the overall lifetime of an individual power plant. the assessment of the overall life cycle of different types of power plants understandably shows the highest level of greenhouse gas emissions in thermal power plants that use fossil fuels in electricity production. greenhouse gases, as a by-product of electricity generation, do not occur in the application of nuclear energy. since this is unlike fossil resources, this is also one of the reasons for observing nuclear energy in the context of “renewable sources”. however, in this case, the radioactive nuclear waste, which has a high impact on the environment and human health, is being forgotten. if the overall life cycle of a plant using a renewable energy source is observed, the emission of greenhouse gases expressed in carbon dioxide (co2) equivalent is still extremely small or negligible. the following graph 1 shows the range of greenhouse gas emissions (expressed in kilograms of carbon dioxide [co2] equivalent per kilowatt-hour [kwh]) over the life cycle of different types of power plants. in their overall life cycle, power plants using conventional renewable energy sources, such as wind or hydropower, have insignificant amounts of greenhouse gas emissions, which confirms their environmental acceptability. it is precisely the negative externalities caused by pollution from the combustion of conventional, fossil fuels that are one of the main arguments for promoting the production of electricity from renewable energy sources. as environmentally friendly energy resources, renewable energy sources appear primarily in the electricity system as additional support to already existing conventional energy plants in providing additional amounts of electricity. this directly affects the reduction of fossil fuel energy that would otherwise be consumed in a conventional power plant to produce an equal amount of electricity. also, renewable energy sources reduce dependence on imports, primarily electricity, but also the import of the necessary fossil energy resources – fuels that produce electricity. another advantage in the use of renewable energy sources is manifested in the encouragement of economic development, namely the development of the energy sector and all related activities related to this industry. renewable sources have a significant multiplier effect on those countries whose industry is capable and able to produce energy machinery and equipment based on technological innovations, especially in their exports (granić, 2010). the innovation that promotes technical/technological changes in new market structures has been indentified as the most important benefit of renewable energy sources utilization (fankhauser et al., 2008). in fact, innovations are related to new technological processes in the renewable energy sector that lead to the improvement of business processes and economic growth. also, technological changes and innovation, as well as the gradual development of renewable energy technologies, increase demand for qualified workforce, thus directly boosting employment. in addition to the above, policy measures that contribute to environmental preservation and sustainable development are highlighted. one such measure is the so-called energy-based economic development, which integrates economic development and energy policy and planning into a new field of managing national economies. energy-based economic development is defined as the process in which decision makers in economic and energy planning and development, government officials and other public authorities, energy regulators, industry representatives, and other market participants tend to increase energy efficiency and/or diversification of energy resources in a way that creates new jobs, 0 0.5 1 1.5 2 2.5 li gn ite h ar d co al o il in du st ria l g as n at ur al g as n uc le ar p ow er h yd ro po w er w in d po w er p ho to vo lta ic w oo d (c og en er at io n) minimum (kg co2-equiv./kwh) maximum (kg co2-equiv./kwh) 1,1.690 1.280 1.190 2.410 0.991 0.011 0.027 0.021 0.148 0.156 graph 1: greenhouse gas emissions during the entire life cycle of a power plant source: dones et al., 2004 maradin: advantages and disadvantages of renewable energy sources utilization international journal of energy economics and policy | vol 11 • issue 3 • 2021 179 maintains employment, and encourages the prosperity of the region (carley et al., 2011). the essence of the concept of energy-based economic development lies in fulfilling economic and energy development needs. thus, the fundamental objectives relate to the increase of energy efficiency, diversification of resources and selfsufficiency, improvement of industry and economic growth and development, development of entrepreneurship, encouragement of technological innovation, increase in the level of employment and specialization, and so on. the pioneers in the development of clean “green” technologies have an opportunity to become regional or even global leaders in the industry. the example of germany must be pointed out here, as this country is the leader in the export of renewable energy technologies (fankhauser et al., 2008; simas and pacca, 2013). renewable energy sources are generally considered to have a strong effect on increasing employment, especially on the employment of the local population where a particular renewable source is located. research has shown that this is not entirely correct, but differs significantly depending on the degree of activity of the life cycle of the plant that exploits the renewable energy source. although each segment of renewable energy has specific characteristics, they all have a common life cycle that includes five phases (llera-sastresa et al., 2010): 1. research and design 2. development and manufacture 3. construction and installation 4. operation and maintenance or service 5. updating and/or dismantling. in order to adequately present the impact of a power plant life cycle on the quantity and quality of employment, the place and duration of employment, and the indirect development of the “green” economy, the abovementioned five phases are modified into three main phases: (1) technological development, (2) installation/ uninstallation of a power plant and (3) operation or managing and maintenance of technological plants. the first two phases (i.e., research and design, and development and manufacture) are commonly seen as a separate whole, due to their complementary work areas and identical generated employment. this creates a new starting phase of a life cycle, called technological development. despite the third and the fifth phase being distant in time (i.e., construction and installation, and updating or dismantling), they create a single phase of installation/ uninstallation, since there is no difference in terms of the types of activities and characteristics of engaged employment. activities related to the maintenance of power plant operations comprise the third and the last phase of the life cycle. for example, some of these activities include management and maintenance of a wind power plant; the collection, supply and logistics of work of a biomass power plant; and other activities related to the normal functioning of renewable energy power plants (maradin et al., 2017). the impact of the three aforementioned life cycle phases of renewable energy technology on the previously mentioned elements of employment is shown in table 1. this division of power plants’ life cycle into phases could be useful for determining the need for a strategy that generates employment opportunities in one of the three phases, such as encouraging technological innovation (which increases the impact on local employment in the first phase) or professional specialization (which reduces the need for foreign engineers and technology installers). the amount of employment is particularly high in the installation/uninstallation phase, due to the workforce needed in the process of construction and installation, modernization and/or dismantling of the power plant. the adverse economic effect in this phase is temporary employment, because once the plant is built or dismantled, there is no more need for such specialized workforce. on the other hand, the management and maintenance of renewable energy power plants does not require much workforce, particularly in the case of the wind power industry (maradin et al., 2017). studies show that 20 mw of installed wind farm capacity requires only one or two full-time workers to operate and maintain a wind farm during its 20 to 30-year life expectancy (e.g. maradin, 2015). the level of expertise and specialization in the maintenance and repair of faulty components does not need to be particularly high, since the case is of mid-level complexity, so this job permanently employs mainly local workforce, which is certainly an advantage in exploiting renewable resources. every national economy aspires to achieve the phase of technological development, which ensures the greatest economic effects of renewable energy sources. although the quantity of employment in this phase is of mid-level complexity, the quality of employment is very high, because many technical and technological achievements and improvements are applied; research and development influence the innovation. the substantial benefit of this phase is permanent employment (maradin et al., 2017). in addition to the many benefits of using renewable energy sources in terms of environmental benefits, reducing fossil fuel consumption and import dependence, stimulating economic development and the impact on increasing employment, the presence of renewable energy sources in rural areas, especially those underdeveloped, can contribute their economic development and in general the civilizational need for electricity. this environment is particularly suitable for investments in renewable energy sources, mostly due to the lack of alternative development projects in that area. in this way, renewable energy sources provide much-needed electricity in areas where the electrical grid is underdeveloped or does not exist, such as remote villages or islands (sreeraj et al., 2010). the extension of the power grid table 1: phases of the life cycle of the exploitation of renewable energy sources and influence on employment phase volume of employment location of employment duration of employment level of specialisation technological development medium from foreign to local stable very high installation/uninstallation high from local to foreign temporary high operation and maintenance low local stable medium source: llera-sastresa et al., 2010 maradin: advantages and disadvantages of renewable energy sources utilization international journal of energy economics and policy | vol 11 • issue 3 • 2021180 in rural areas is not economically viable due to the high costs of electricity distribution. therefore, electricity off the grid which is produced in the hybrid system of renewable energy resources enables the process of rural electrification and brings benefits for the community (borhanazad et al., 2013). however, it should be noted that renewable energy sources are not always the best solution in providing additional quantities of electricity and in their delivery to the electricity network there are certain shortcomings and difficulties that are presented in the following part of the paper. 4. disadvantages of renewable energy sources utilization in addition to the multiple advantages of using renewable energy sources, there are certain disadvantages and limitations in their daily use. it is primarily due to their natural features that renewable sources depend entirely on geographical location and weather conditions, namely the volatility and unpredictability of the renewable source is a significant limitation and difficulty in electricity generation. this limitation can be alleviated by quality planning and careful site selection for a particular renewable energy source, as well as by conducting measurements and making environmental studies. also, due to the large daily oscillations in the availability of a renewable source on the basis of which electricity is generated, it is necessary to consider the possibilities of accepting renewable electricity into the electricity system. there must always be a sufficient reserve in the electricity system network in the form of available installed power of the power plant that can eliminate the deficiency that occurs when a particular renewable energy source is not available. furthermore, the electricity network at a certain location can receive only a certain amount of electricity without the risk of overloading and / or disturbing the stability of the power system. it is pointed out that the biggest difficulties in accepting electricity into the grid are posed by wind companies, primarily due to the relatively high installed capacity of wind farms, and therefore their power must be limited in each power system to ensure stable and safe operation of the entire electricity sector (http://www.hep.hr/oie/ oie/nestalnostizvora.aspx). when comparing renewable energy sources with traditional fossil energy resources; renewable sources have a lack of capacity (capacity) to produce electricity, they are not able to produce as large amounts of electricity as power plants with fossil fuels. in order to try to reduce this shortcoming, it is necessary to further invest in the development of renewable energy technologies, but also simply to build more renewable energy plants (agboola, 2014). in addition to this, renewable energy sources also have a lower ratio of installed plant power (in mw) or electricity production (in gwh) to the area of the location (in m2) occupied by the power plant, compared to fossil fuel power plants. this means that renewable energy plants should have a much larger area than thermal power plants in the production of the same amount of electricity. in addition to the required surface area, renewable energy sources also achieve relatively lower energy efficiency, with the exception of water resources and wind farms. efficiency in electricity generation can be defined as the ratio between the usable electricity output generated in a generating entity in a given unit of time and the energy value of energy resources delivered to the generating entity at the same time (honorio et al., 2003). the efficiency of different technologies, i.e. certain types of energy resources in power plants is shown in the following graph 2. the presented values of energy efficiency of different production technologies represent the minimum and maximum level of efficiency of a certain power plant. renewable energy sources, such as “clean” energy, are shown in green; large hydropower plants, as plants that significantly affect the ecosystem, are pointed out in blue; while thermal and nuclear power plants are shown in brown. it is stated that the energy efficiency of oil-fired thermal power plants can be from 38 to 44%, coal-fired power plants from 39 to 47%, gas thermal power plants up to 39%, but if we consider gas thermal power plants in a combined process (consisting of gas-turbine and steam-turbine part), then increases the efficiency of the energy process itself, which reaches up to 58%, because almost simultaneously produces thermal energy and electricity. it is also pointed out that the nuclear power plant has a relatively low energy efficiency of 33 to 36%. renewable energy sources achieve relatively lower energy efficiency, apart from the already mentioned hydro power plants. in addition, biomass and biogas power plants have an efficiency of 30 to 40%, waste power plants from 22 to 28%, while photovoltaic and geothermal power plants have the lowest energy efficiency of 15% (honorio et al., 2003). on the other hand, large hydropower plants have the highest energy efficiency of 95%, which, although they contain renewable water resources, are not classified as renewable energy sources. thus, large hydropower plants have the most efficient technology for electricity production. likewise, extremely high efficiency of as much as 90% are possessed by renewable power plants “on water resources,” namely small hydro power plants and tidal power plants. although it is stated that the average wind power plant has an energy efficiency of about 35%, in the most modern wind turbines it can reach 45%. moreover, theoretically the highest possible level of wind energy utilization in a wind turbine is defined by the so-called betz law or betz limit and it 0 10 20 30 40 50 60 70 80 90 100 la rg e hy dr o po w er p la nt s m al l h yd ro p ow er p la nt t id al p ow er p la nt s te am tu rb in e co al -f ire d po w er p la nt la rg e ga s / g as fi re d c c g t s te am tu rb in e fu el -o il po w er p la nt w in d tu rb in e n uc le ar p ow er p la nt b io m as s an d bi og as w as te -to -e le ct ric ity po w er p la nt g eo th er m al p ow er p la nt p ho to vo lta ic c el ls 45 graph 2: efficiency of different technologies in electricity generation (%) source: honorio et al., 2003 maradin: advantages and disadvantages of renewable energy sources utilization international journal of energy economics and policy | vol 11 • issue 3 • 2021 181 is 59.3%. no currently available sophisticated wind turbine can have an energy efficiency higher than the stated 59.3% (http:// www.vjetroelektrane.com/moderni-vjetroagregati-i-pretvorbaenergije?showall=1). this means that, in reality, less than half of the kinetic energy of wind can be used as useful electricity in wind power plants. similarly, due to their natural characteristics and availability of energy, renewable sources generally operate for a shorter time period in hours in 1 year at full power (at maximum utilized capacity) compared to fossil power plants. for example, noting that one calendar year contains 8760 h, coal-fired or gas-fired power plants and nuclear power plants can operate on average up to 7500 h/year at installed (full) power, while renewable energy sources (wind or solar energy) on average operate at only about 2000 h/year at maximum power (blesl et al., 2008). it is stated that onshore wind power plants typically operate from 2000 to 2500 h/ year, while offshore wind power plants operate as much as 4000 h/ year at maximum capacity, primarily due to less wind turbulence and higher wind speed. this indicates the operation of the power plant only at the installed (full) power during 1 year. it is normal to expect the operation of the power plant for a larger number of hours per year, but not with the maximum utilized production capacity. similar to this indicator, it is necessary to point out the capacity factor indicator which represents the ratio of the actual amount of energy delivered to the electricity network during the year and the potential amount of energy that could be produced if the power plant operates at maximum installed capacity during all 8760 h/ year. equivalent to the number of hours of operation of a power plant at full power during 1 year, renewable energy sources have a significantly lower capacity factor than fossil fuel power plants. thus, e.g. wind power plants have a capacity factor of only about 20 to 35% depending on the natural characteristics, namely wind characteristics and geographical location and technical capabilities of wind turbines, compared to about 60% of the capacity factor of other forms of power plants in electricity generation. a significant disadvantage of even greater use of renewable energy sources is certainly their relatively high cost of electricity production. the literature suggests a higher cost of building a renewable energy plant compared to fossil power plants. this is especially true for power plants that use marine energy, whose technology is extremely expensive, and due to the specificity of the location, this energy source participates in a negligible share in electricity production. the construction of photovoltaic systems is also a high cost, also due to the high cost of technology and the complexity of making solar panels (http://www.hep.hr/oie/ oie/visokacijena.aspx). depending on the factors involved in the formation of the price of electricity production by comparing renewable and non-renewable sources, different projections appear. this is illustrated by the following example. assessing the economic competitiveness of power plants using different types of fuel, a study was conducted in finland (tarjanne and kivistö, 2008) which analyses and compares the cost of electricity production from nuclear power plants, gas-fired combined heat and power plants, coal-fired power plants, biomass power plants (peat and wood), and a wind power plant. this seeks to explore an economic alternative for additional electricity generation in non-performing (basic) power plants. looking at the price level (for example, the price of building a power plant, fuel prices, etc.) from the beginning of 2008, the calculations are shown in the following graph 3. observing three types of costs; capital costs, management and maintenance costs of the power plant and fuel costs, the higher costs of electricity production of the plant (expressed in €/mwh) on renewable energy sources are evident, with the exception of biomass plants that use fuel peat, relative to fossil fuel plants. this is due to high capital costs, especially in the construction of wind farms, which capital costs (41.9%) are by far the highest in the structure of the observed entities, and almost the same fuel costs in the form of timber in biomass plants (40.6%). out of the observed power plants, wind power plants, which use (basically) unlimited wind energy resources, are the only ones that do not have fuel costs. in the observed period, gas plants also have a significant amount of fuel costs (as well as wood biomass plants), but with a very low level of other costs. if the costs of electricity generation of electricity plants include the costs of trading carbon dioxide (co2) emissions, renewable energy sources become competitive with fossil, conventional energy plants. this is shown in the following graph 4. taking into account the ecological component of electricity production, due to exhaust gases into the atmosphere, namely harmful emissions that occur as a by-product of electricity production and which should be limited, gas, coal and peat plants (the earliest form of coal generation) have an additional cost of electricity production. energy. limiting greenhouse gas emissions is carried out through the cost of emission rights; the market price of certificates of emissions into the environment, which at the time of publication of the results of the survey (2008) by graph 4 amounted to about 23 €/t co2. it should be noted that today’s price (14 december 2020) of the environmental certificate (emissions trading) is higher and amounts 30.92 €/t co2 (https://www.eex.com/en/market-data/environmentalmarkets/auction-market). 20.0 6.2 11.5 13.3 23.9 41.9 10.0 5.0 8.0 8.0 9.0 11.0 5.0 40.0 26.2 22.3 40.6 52.9 0 10 20 30 40 50 60 70 80 nuclear gas coal peat wood wind capital costs operation and maintenance costs fuel costs 73.5 43.6 51.2 45.7 35.0 graph 3: electricity generation costs of different power plants and their structure, without emission trading (€/mwh) source: tarjanne and kivistö, 2008 maradin: advantages and disadvantages of renewable energy sources utilization international journal of energy economics and policy | vol 11 • issue 3 • 2021182 with the aim of reducing greenhouse gas emissions, trade in environmental emission certificates for eu member states began on 1 january 2005. the purchase of the certificate was conceived as an alternative to the failed project of introducing a single tax on emissions into the environment. the certification system covers greenhouse gas emissions into the atmosphere and other gases that have a detrimental effect on the ozone layer. all gases are denominated in carbon dioxide equivalents (mance and škalamera-alilović, 2013). including the trading of environmental emission certificates, thus the newly incurred cost of producing electricity from fossil fuels is higher than the cost of producing a wind farm. this suggests that in the process of electricity production it is necessary to consider and include the overall operating costs of the power plant, in order to qualitatively and adequately assess the efficiency of operations. 5. conclusion from all the above, it can be stated that renewable energy sources have numerous advantages and disadvantages in providing additional quantities of electricity, and their application should be seen primarily in the context of improving the electricity sector and the development of the national economy. in order to highlight the advantages and disadvantages of using renewable energy sources, which are presented in this paper, the following table 2 is given. renewable energy sources, as environmentally friendly energy resources, will become even more important in the future, because they are unlimited and provide additional energy forms along with the existing conventional power plants (cerović et al., 2014). despite of some disadvantages of using renewables, and taking into consideration this literature overview, it can be perceived that the advantages outweigh the disadvantages of renewable energy sources utilization for the overall society. this study could be further widened in order to analyse the use of specific, individual renewable energy source in a particular national economy. starting from the assumption that each country has its own specifics, it could be useful to consider which renewable energy source can be utilized to the greatest extent in fostering the sustainability and progress of the economy. 6. acknowledgment this work has been fully supported by/supported in part by the university of rijeka, croatia under the project “new energy paradigm – how to reconciliate sustainability and feasibility”, faculty of economics and business, rijeka. references agboola, a. (2014), public sensitization on the adoption of renewable energy in nigeria: communicating the way forward. iosr journal of humanities and social science, 19(5), 74-81. akinci, t.c. (2019), intelligent systems in renewable energy sources. in: bostancı, s.h., yıldırım, d.ç., nişancı, e., editor. i̇ktisadi teknik ve strateji boyutları ile türkiye’de enerji sorunsalı. turkish: ekin pub. p229-262. armstrong, a.j., hamrin, j. (2000), the renewable energy policy manual. washington, usa: united states export council for renewable energy. available from: http://www.hep.hr/oie/oie/nestalnostizvora.aspx. [last accessed on 2015 feb 23]. available from: http://www.hep.hr/oie/oie/visokacijena.aspx. [last accessed on 2015 feb 25]. available from: http://www.vjetroelektrane.com/moderni-vjetroagregatii-pretvorba-energije?showall=1. [last accessed on 2015 mar 09]. available from: https://www.eex.com/en/market-data/environmentalmarkets/auction-market. [last accessed on 2020 dec 28]. blesl, m., wissel, s., mayer-spohn, o. (2008), private costs of electricity and heat generation. cost assessment of sustainable energy systems, 1, 1-47. borhanazad, h., mekhilef, s., saidur, r., boroumandjazi, g. (2013), potential application of renewable energy for rural electrification in malaysia. renewable energy, 59, 210-219. carley, s., lawrence, s., brown, a., nourafshan, a., benami, e. (2011), energy-based economic development. renewable and sustainable table 2: advantages and disadvantages of using renewable energy sources advantages disadvantages environmental protection (reduced greenhouse gas emissions) weather conditions dependence reduced fossil fuel consumption non-continuity and unpredictability reduced energy imports dependence acceptance of renewable electricity in the power system stimulating the development of innovation and the economy low ability to produce electricity increasing employment low energy efficiency rural development low maximum capacity utilization/low capacity factor reduction of energy scarcity (expansion of rural electrification capacities) relatively high cost of electricity production source: author 20.0 6.2 11.5 13.3 23.9 41.9 10.0 5.0 8.0 8.0 9.0 11.0 5.0 40.0 26.2 22.3 40.6 52.98.0 18.6 21.9 0 10 20 30 40 50 60 70 80 nuclear gas coal peat wood wind capital costs operation and maintenance costs fuel costs emission trade (23 €/t co2) 73.5 65.564.3 59.2 35.0 graph 4: electricity generation costs of different power plants and their structure, with carbon trading costs (€/mwh) source: tarjanne and kivistö, 2008 maradin: advantages and disadvantages of renewable energy sources utilization international journal of energy economics and policy | vol 11 • issue 3 • 2021 183 energy reviews, 15(1), 282-295. cerović, l.j., maradin, d., čegar, s. (2014), from the restructuring of the power sector to diversification of renewable energy sources: preconditions for efficient and sustainable electricity market. international journal of energy economics and policy, 4(4), 599-609. chubraeva, l., sergey, t. (2018), project of autonomous power plant with high-temperature superconductive devices. in: 2018 international multi-conference on industrial engineering and modern technologies (fareastcon), institute of electrical and electronics engineers. p1-5. denona, b.n., cerović, l.j., maradin, d. (2012), the security of electricity supply as the determinant of sustainable development. marketing and management of innovations, 3(2), 254-265. dones, r., heck, t., hirschberg, s. (2004), greenhouse gas emissions from energy systems, comparison and overview. in: encyclopaedia of energy. vol. 3. san diego, usa: academic press/elsevier. p77-95. dresselhaus, m., thomas, i. (2001), alternative energy technologies. nature, 414, 332-337. ellabban, o., abu-rub, h., blaabjerg, f. (2014), renewable energy resources: current status, future prospects and their enabling technology. renewable and sustainable energy reviews, 39, 748-764. fankhauser, s., sehlleier, f., stern, n. (2008), climate change, innovation and jobs. climate policy, 8(4), 421-429. granić, g. (2010), kako promišljati energetsku budućnost? [how to rethink energy future?]. zagreb, croatia: poslovna biblioteka, energy institute hrvoje pozar. honorio, l., bartaire, j.g., bauerschmidt, r., ohman, t., tihanyi, z., zeinhofer, h., scowcroft, j.f., de janeiro, v., kruger, h., meier, h.j., offermann, d., langnickel, u. (2003), efficiency in electricity generation. brussels, belgium: eurelectric union of the electricity industry. kowalski, k.m. (2011), alternative energy sources. new york, usa: marshall cavendish benchmark. labudović, b., barbir, f. (2002), obnovljivi izvori energije. [renewable energy sources]. zagreb, croatia: energetika marketing. liu, z. (2017), china’s strategy for the development of renewable energies. energy sources, part b: economics, planning, and policy, 12(11), 971-975. llera-sastresa, e., aranda-usón, a., bribián, i.z., scarpellini, s. (2010), local impact of renewables on employment: assessment methodology and case study. renewable and sustainable energy reviews, 14(2), 679-690. mance, d., škalamera-alilović, d. (2013), certifikati emisija u okoliš priznavanje u financijskim izvještajima [european union emmission allowances and their recognition in financial reports]. tim4pin magazin specijalizirani časopis centra za razvoj javnog i neprofitnog sektora. tim4pin magazine specialized journal of the center for public and nonprofit sector development, 11, 27-35. maradin, d. (2015), the efficiency of wind power companies in electricity generation. doctoral dissertation. rijeka, croatia: university of rijeka faculty of economics and business. maradin, d., cerović, l.j., mjeda, t. (2017), economic effects of renewable energy technologies. naše gospodarstvo/our economy, 63(2), 49-59. michaelides, e.e.s. (2012), alternative energy sources. in: part of the green energy and technology book series (green). berlin, heidelberg, germany: springer-verlag. mohtasham, j. (2015), review article-renewable energies. energy procedia, 74, 1289-1297. nezhnikova, e.v., okhremenko, i.v., papelniuk, o.v. (2018), investigation of the features of investment in the development of renewable energy sources: main consumers, legal regulation, equipment, rates and delivery. international journal of energy economics and policy, 8(4), 178-186. peidong, z., yanli, y., yonghong, z., lisheng, w., xinrong, l. (2009), opportunities and challenges for renewable energy policy in china. renewable and sustainable energy reviews, 13(2), 439-449. simas, m., pacca, s. (2013), socio-economic benefits of wind power in brazil. journal of sustainable development of energy, water and environment systems, 1, 27-40. sreeraj, e.s., chatterjee, k., bandyopadhyay, s. (2010), design of isolated renewable hybrid power systems. solar energy, 84(7), 1124-1136. strielkowski, w., krška, š., lisin, e. (2013), energy economics and policy of renewable energy sources in the european union. international journal of energy economics and policy, 3(4), 333-340. tarjanne, r., kivistö, a. (2008), comparison of electricity generation costs. lappeenranta university of technology, faculty of technology, department of energy and environmental technology, research report en a-56. tokic, a., akinci, t.c., zengin, a.t. (2020), bosnia and herzegovina’s renewable energy policy and perspective. international journal of energy economics and policy, 10(5), 524-530. united nations development programme. (2000), world energy assessment: energy and the challenge of sustainability. united nations: united nations development programme. van vliet, b. (2012), renewable resources. in: southerton, d., editors. encyclopedia of consumer culture. thousand oaks, california, usa: sage publications, inc., p1212-1214. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020502 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 502-509. basic stages of energy development program implementation in the chechen republic i. a. kerimov*, m. sh. mintsaev, m. v. debiev, m. ya. pashaev grozny state oil technical university named after acad. m.d. millionshchikov, grozny, russia. *email: i.akerimov@yahoo.com received: 24 june 2020 accepted: 11 september 2020 doi: https://doi.org/10.32479/ijeep.10492 abstract the article discusses the issues of energy complex development of the chechen republic, which requires the creation of a stable multi-vector energy that can satisfy the growing needs of the population and economy of the region. the main emphasis is made on the development of the renewable energy sources, which need to be paid close attention, drawing on the experience of other entities and countries developing innovative technologies in this direction. the analysis of the energy development program implementation in the chechen republic (2011-2030) over the past 8 years has been carried out, which includes four subprograms describing the potential of resources and the prospects for the energy development in the chechen republic,. the estimation of power consumption indicators and maximum loads in the chechen republic until 2018 and for the long term (“calculated,” “optimistic” and “actual” options) is given. the analysis of the state and potential for the water energy development in the chechen republic is carried out. the analysis of natural resources potential of the republic is carried out in order to implement effectively and develop each of the considered renewable energy sources, taking into account the development of modern innovative technologies to reduce electrical energy consumption. the state estimation of the existing integrated power grid of the chechen republic is given, where the initial tasks of work coordination to improve the efficiency of the republic’s energy system are outlined. the results of total indicators of electric grid construction and facilities reconstruction for 2011-2019 are derived. possible directions (calculated and optimistic options) of the electrical energy industry development are considered. in order to develop successfully the energy sector of the chechen republic, taking into account the electrical energy load growth, the development of modern program for the of alternative and renewable energy sources development was proposed that will allow to create additional electrical energy sources in combination with traditional ones. at the same time, the implementation of fundamental and applied research in the field of renewable energy was proposed. keywords: electric energy industry, power system, power center, electric energy, power balance, alternative and renewable energy sources jel classifications: o13, p28, p48, q42, q43, q47, r11 1. introduction the energy sector is one of the foundations for the development of the economy of both the region and the country as a whole. after a sharp decline in energy production in the early nineties, the level of energy sources production and consumption began to increase. however, there are a number of serious problems which if are not solved, the level of developed countries is impossible to reach. the irrational structure of the energy complex, where the use of gas and oil predominates, the considerable depreciation of equipment and electric transmission lines, the backwardness of technologies and low efficiency compared to today and high costs associated with this, lack of available funds for the retrofit and development of energy sector are аmong these problems. that’s why, raising of efficiency of energy sources use, adoption of new advantageous alternative sources, the need to find new solutions that take into account regional characteristics, is one of the most important tasks in the energy sector development. the search for ways out of the described difficult situation requires a comprehensive analysis of all factors affecting the regional energy development process (burmistrov, 2009; al-falahi monaaf, 2017; palival, 2014.). the development of the region’s energy capacities is a detailed study of the object of research on factors that affect the energetic state of this journal is licensed under a creative commons attribution 4.0 international license kerimov, et al.: basic stages of energy development program implementation in the chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020 503 the region as a whole. to perform an analysis of energy development schemes, first of all, it is necessary to identify all the base entities that affect the region’s energy sector formation and development, that is, the main “global participants” in the region’s energy sources production process. those are: directly existing power system; the economy, primarily industry, which is the main consumer of energy sources and a supplier of material resources (equipment, raw materials) to the energy system; the population, which is also one of the important consumers of energy resources; personnel in the energy production system, the environment, and the state, including regional authorities. based on the analysis of the factors, it is necessary to develop schemes of possible ways of the region’s energy system formation and functioning (guardian, 2017; sibikin and sibikin, 2010). 2. methods in order to ensure a stable economy of the chechen republic with energy resources, a scientifically based state energy policy is required. first of all, the chechen republic energy development program for 2011-2030 was developed for this in 2010, in which the principal directions and critical parameters, the list and terms of the electric power facilities planned for construction and commissioning were considered (debiev and popov, 2012). this program is reviewed annually and appropriate adjustments are introduced. the program is a document that defines the goals, main objectives and directions of the longstanding program for the development of the energy complex of the chechen republic, taking into account emerging internal and external issues in the fuel and energy sector, as well as in the economy of both the chechen republic and the russian federation as a whole. the energy development program of the chechen republic, taking into account the development of the electrical energy complex for the period until 2030, includes 4 subprograms: • subprogram “electrical energy.” • subprogram “water energy.” • subprogram “use of alternative and renewable energy sources.” • subprogram “use of geothermal waters.” • moreover, two programs have been developed additionally to increase the reliability of the functioning of the integrated power grid of the chechen republic: • the chechen republic electric grid complex modernization and reliability improvement program for 2020-2024 (long-term), which covers modernization, technical reequipment, renovation and new construction of power lines with a length of 5,188 km and the transformer fleet with capacity of 577 mva; • the program to reduce electrical energy losses for 20192023, for the retrofitting and reconstruction of 10-6/0.4 kv transformer substations with outgoing 0.4 kv overhead lines, as well as with the construction of 6.10 kv branch lines from overhead lines. 2.1. subprogram “electrical energy” currently, the management and operation of the energy complex of the chechen republic is carried out by the distribution company jsc chechenenergo. this complex territorially includes electric power systems with voltage of 330 kv, as well as electric power systems with voltage of 0.4; 6; 10; 35; 110 kv (kerimov and debiev, 2012). today the most important and primary main substation for the 110 kv electric power system on the territory of the chechen energy system is the substation “substation 330 kv grozny.” in 2011, the third autotransformer “at-3 330/110 kv” was installed on the substation “ps 330 kv grozny” with subsequent commissioning with a total capacity of 125 mva and the total power of the substation is 375 mva. the electric power systems with voltage of 330 kv are owned by jsc “fgc ues” and are serviced by its regional branch main power transmission lines of the south. the electric power systems with voltage of 0.4; 10; 35 and 110 kv are mainly owned and operated by jsc “chechenenergo.” jsc “chechenenergo” is the electricity wholesale market entity, as well as a guaranteeing electrical energy supplier serving consumers in six cities (grozny, gudermes, kurchaloy, argun, shali, urus-martan) and 16 rural areas of the chechen republic. jsc “chechenenergo” serves 200 thousand individuals and 16 thousand legal entities. jsc “chechenenergo” has the following technical potential on the books the number of substations is 4928 pcs., including: • 30 substations of 110 kv; • 59 substations of 35 kv; • 4842 substations of 6-10 kv. the total transformer capacity of all substations is 2258.96 mva. the length of electric transmission lines is 14678.31 km, including: • overhead line 110 kv 52 pcs. (1,150.54 km); • overhead line 35 kv 88 pcs. (980.65 km); • overhead line 6-20 355 pcs. (4,798.85 km); • overhead line 0.4 7408 pcs. (7,748.27 km); • cable line 6-20 kv 441 pcs. (459.62 km); • cable line 0.4 kv 449 pcs. (644.95 km). jsc chechenenergo pursues a uniform technological policy aimed at technical development, improving the reliability and efficiency of permanent assets. for the successful development of the electrical energy industry in the chechen republic, the following tasks are primary (ellabban et al., 2014; farkhutdinov and cherkasov, 2017; palival, 2014): • ensuring a reliable supply of electrical and thermal energy to consumers in the chechen republic; • maintaining full process management of the energy system in conjunction with the unified energy system of the russian federation in accordance with market conditions; • coordination of work to increase the efficiency of functioning and ensure stable development of the energy industry based on modern innovative technologies; • reduction of the level of negative impact on the environment. 3. results and discussions the evaluation of energy consumption indicators and maximum loads in the chechen republic until 2019 and for the long term is shown in 2 diagrams (figures 1 and 2). kerimov, et al.: basic stages of energy development program implementation in the chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020504 system are a prime consideration (kerimov and debiev, 2012). the development of generating sources in the chechen republic was provided by enhancement of the argun tpp to 50 mw and the construction of the grozny tpp with a capacity of 400 mw. the commissioning of the argun tpp capacity was planned in 2019, but due to the construction of the grozny tpp with a capacity of 358 mw, implementation of measures for the restoration of the argun tpp was completely stopped due to the lack of an investor and the advisability of restoring the station in its current form. in 2018, the grozny tpp (gtp-1 and gtp-2, with a capacity of 176 mw each) was commissioned in the chechen republic with a total capacity of 352 mw. taking into account the commissioning of the second 200 mw block at the grozny tpp and the hydroelectric power chain on the argun river the chechen energy system can self-balance (deficit in capacity is 50-60 mw, in electrical energy 140150 million kw/h). with the commissioning of the 1st and 2nd stage of the hydroelectric power chain of argun hpps, electrical energy excesses increase to 400 million kwh. in the period 2021-2030 taking into account the commissioning of the third stage of the argun cascade of hydroelectric power stations in the energy system of the chechen republic, there will be insignificant surpluses in both capacity and electricity (up to 130 mw and 470480 million kw/h, respectively). in 2015 a small hpp on the argun river (shpp kokadoy) with a capacity of 1.3 mw was commissioned. the construction of a small hpp on the sunzha river with a capacity of 0.5 mw (kirov shpp) is being completed. projects for the construction of small hpps on the argun river have been developed: shpp “satellite” – 1.2 mw; shpp “gukhoi” – 2.1 mw; shpp “ushkaloy” – 4.9 mw. llc “yug-stroy” began investing in construction project of shpp with capacity of 1 mw on the aksay river with a preliminary cost of 294 million rubles. preliminary surveys of the llc “stroyproject-tm” on the construction of the bashennaya shpp in the itum-kali district of the chechen republic with an installed capacity of 8 mw and an estimated value of 1.3 billion rubles have begun. according to the energy development program of the chechen republic for 2011-2030 on the terek ridge of the republic, it was planned to build a wind farm consisting of 24 wdpps with an installed capacity of 1.5 mw each, with the total installed capacity of 36 mw. unfortunately, this project is currently not taken into account in the program (debiev and popov, 2012). the government of the chechen republic signed an agreement with llc “avelar solar technology” on the construction of a solar power plant in the chechen republic with a capacity of up to 5 mw with an estimated construction cost of 525 million rubles. 3.2. electrical power systems development analyzing the state of the energy complex of the chechen republic, it is necessary to outline the following initial tasks for the development of electrical power systems: 350 400 450 500 550 600 650 700 750 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18 20 19 20 20 20 30 estimated optimistic actual m w figure 1: maximum power diagram 1900 2100 2300 2500 2700 2900 3100 3300 3500 3700 3900 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18 20 19 20 20 20 30 estimated optimistic actual m ill io n kw h figure 2: electrical energy consumption diagram in 2019, the chechen energy system’s own maximum load amounted to 492 mw (figure 1), as a result the rate of electricity consumption has a dynamic of a certain growth in electricity consumption. in the chechen republic, as a result of infrastructure development, as well as continued construction and repairing works, compared to 2018, the level of energy consumption increased by 5% and reached the value of 3015.9 million kw/h. (figure 2). at the same time, due to the fact that the existing electric networks are overage and have not undergone renewal, the losses of electrical energy occur, which must be minimized by renewal of the electric power systems. the main goal of electricity losses reduction is the implementation in the territory of the chechen republic of the comprehensive program to reduce excess losses. moreover, the active work of energy supplying enterprises in relation to consumers is required to obtain the effect of electricity losses reduction and increasing the level of payments for electricity consumed. 3.1. development of power-supply sources, capacity and electrical energy the shortage of capacity and electrical energy will increase in the coming years and may amount to 500-510 mw in capacity and 3120-3210 million kw/h in electrical energy in 2020. to achieve the goals of power-supply sources development in the energy system of the chechen republic, the creation of new generating capacities and the corresponding modernization of fixed assets of the energy kerimov, et al.: basic stages of energy development program implementation in the chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020 505 • increasing the stability of electrical connections of the energy system of the chechen republic with energy systems of other regions and constituent entities of the russian federation; • the formation and strengthening of the internal electric network of the energy system, if necessary, with the possibility of electric grid facilities redundancy, the purpose of which is to increase the reliability and uninterruptedness of power supply to consumers; • deloading of the 35 kv electric network, which has been significantly loaded in recent years and has led to an increase in the loss of electric energy in the electric network, additionally ensuring the maximum redundancy level with the minimum total length of electrical energy transmission lines; • increase in the transformers’ rated capacitance at some substations with a voltage of 35 and 110 kv, the load of which in recent years has increased and reached 70-90% of their rated capacitance, as a result they are overloaded at load-peaks; • making decisions on the construction, reconstruction and retrofitting of some overhead transmission lines and substations that have exhausted performance potential; • improving the flexibility of substation circuits and overhead transmission lines, replacing primary switching equipment in order to increase the reliability of both the energy system itself and the electric power supply to consumers. over the past 4 years, six new substations with voltage of 110 kv and total capacity of 285 mva have been constructed and commissioned on the territory of the republic. the “110 kv city” substation, built in the center of grozny and put into operation in 2019, with two transformers of 40 mva each, with a total capacity of 80 mva, is one of the first digital substations in the north caucasus. this substation will allow removing electrical loads from overloaded substations in the city of grozny and thereby will act to raise the uninterruptibility, reliability and quality of electric power supply to the population and infrastructure of the capital of the chechen republic. replacement of one of the two transformers from 16 mva to 40 mva was performed at the substation “110 kv shali” substation, which also contributes to the uninterrupted operation, reliability and quality of electric power supply to the population and infrastructure completely of the shali and vedeno regions of the republic. the block transformers with a capacity of 250 mva (total 500 mva) are installed at the commissioned grozny tpp. an increase in the capacity of the transformer fleet of the existing substations of the chechen energy system by 245 mva was performed. five overhead transmission lines with a voltage of 110 kv were commissioned, the total length of which is about 120 km. the reconstruction and retrofit of some substations of jsc “chechenenergo” was carried out, with the replacement of switching equipment, as well as the installation and commissioning of relay protection and automation devices on a modern elemental base. in view of the fact that the limited possibilities for innovative development of the energy complex are observed in the regions, it is necessary to analyze the effectiveness of the introduction and development of renewable energy sources, taking into account the development of modern innovative technologies that reduce energy consumption (burmistrov, 2009; ellabban et al., 2014; palival, 2014). 4. subprogram “water energy” today the state of russia’s water energy complex consists of over 80 hydropower plants with a total installed capacity of about 46 thousand mw. the long-term annual average generation reaches 180 billion kw/h/year, which is 22% and 18.6% respectively, of capacity and generation from all the existing power plants of the russian energy system. this list does not include small hydropower plants (hpps). the advisability of using the water energy resources of mountain rivers has been justified repeatedly on the practical activities of the energy development in the republics of the north caucasus, where 36 hydropower plants are operating currently. works on the design and construction of about 30 more hydroelectric power stations are under way (guardian, 2017; kerimov and debiev, 2012). in the “layout of hydroelectric power chain and social sphere facilities” presented by “riko group,” the construction of a hydroelectric power chain on the argun river which plans to ensure in the chechen republic: the further development of the economy, agricultural facilities, the production of ecologically-green electrical energy, the improvement of services and recreation, reduce losses in electric networks, improve the social situation. in august 2015 a small hydroelectric power station with capacity of 1.3 mw was commissioned on the river argun. the government of the chechen republic and rao “ues of russia” earlier came to a mutual decision on the necessity to develop water energy. by the resolution of the chechen republic government in 2009, the construction project of hydroelectric power chain on the argun river was included in the list of priority investment projects and proposals of the chechen republic. in general, the investment project of the argun hydroelectric power chain is also of great social importance, associated with the creation of more than 20,000 new jobs during construction (12-15 years). the territory of the chechen republic is characterized by a high supply of water resources (both surface and underground), concentrated in rivers, lakes, water storage reservoirs, glaciers and in the earth interior. the whole territory of the republic is characterized by an arterial drainage. the number of all rivers is about 3198, the total length of which is 6508.8 km. heavy autumn rains in the mountains also contribute to water level rise in the rivers of the republic. the value of the water level in mountain rivers is minimum in winter. the flow of mountain rivers by the seasons of the year is characterized by approximately the following distribution coefficient: 55% for the summer period (june-august), 35% for the spring and autumn, and 10% for the winter (december-february). the hydrological regime of rivers of this nature contributes to favorable conditions for irrigation of the soil, but is adverse for the regular operation of hydroelectric power plants. it should be noted that the hydrological regime of the rivers of the republic has changed significantly in recent decades, and therefore it is necessary to conduct regular hydrological observations on the most of rivers of the republic (kougias and patsialis, 2014; morales and corredor, 2014). kerimov, et al.: basic stages of energy development program implementation in the chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020506 5. subprogram “alternatives and res” 5.1. wind energy wind power continues to be the largest segment of the renewable energy market over the past few years. the total capacity of all wind turbines in the world amounted to about 530 gw at the end of 2017, which was almost one and a half times higher than the total capacity of 439 nuclear power reactors registered in 32 countries of the world with a total capacity of 340 gw. so, in 2017, 52 gw capacity from wind turbines was commissioned in the world, which was absolutely unprecedented (al-falahi, 2017; barinova and lanshina, 2017). concrete calculations for the research and study of wind energy resources in the chechen republic were not carried out. the chechen republic belongs to the region, where the territory is characterized by the medium speed of wind energy. a certain feature of the republic’s wind potential is the irregularity in the distribution of wind speed over different districts and intensity in different periods of the year. one of the most common types of winds in the territory of the chechen republic are mountain and valley breezes arising due to different air temperatures of particular areas of valleys or hollows, as well as flanks. the directions of the mountain and valley breezes are characterized by a day shift. also, the mountain and valley circulation is expressed especially strong and reaches its maximum value in the summer season (farkhutdinov and cherkasov, 2017; kerimov and debiev, 2012). the certain calculations of the wind potential have been performed for some different climatic zones of the republic, namely, the mountainous terrain, the midland and the zaterechny plain, with the recalculation of wind speeds and frequencies and intensities from the height of weather vanes to a height of 75 m (the level of the upper point of a wind power plant with a capacity of 500750 kw). from the analysis of the calculations, it follows that the wind energy gross potential of the above territories is 1406.0 billion kwh/year, and the technological capacity, in turn, reaches ≈ 14.0 billion kwh/year. therefore, in some areas of the republic where the wind speed is quite high, the use of wind energy is an innovative solution. the use of modern wind-driven power plants (wdpps) is economically feasible and profitable with an average annual wind speed of 5 m/s (kerimov and gaisumov, 2011; morales and corredor, 2014). data on wind speeds testify to the development of wind energy in the north of the republic. it seems optimal to create a wind power plant on the terek ridge with altitudes of 400-600 m above sea level (kerimov and debiev, 2012). according to the studies on windpower engineering, wind energy at such altitudes is 5-10% higher than wind energy at altitudes of 0-100 m. nevertheless, wind measurements are necessary for this region. it is necessary to install masts for a wind speed measurement cycle at the site of the future wdpp. in recent years, the construction of wdpps, in particular in the rostov region, has been actively conducted in several regions of southern russia. within design basis 78 wind turbines of the danish company vestas with a capacity of 3.8 mw each will be placed in total (kerimov and debiev, 2012). 5.2. solar energy geographically, the chechen republic is located between 42° and 46° north latitude, causing the heavy influx of solar radiation. the capacity of solar energy, expressed by the value of the radiation balance, in the plain and submontane districts amounts for 5055 kcal/cm2/year. the higher the terrain elevation, the lower the radiation balance and at an altitude of 2500 m its values do not exceed 30-35 kcal/cm2, and in the high mountain zone it decreases to negative values and at an altitude of more than 3000 m is –3 ÷ 4 kcal/cm2 on average. on the plain part of the territory of the chechen republic, the radiation balance is positive for almost the entire year. with territory height increase in the winter season, the expenditure side of the balance begins to exceed the incoming one. the wide scale of the physical and geographical states variety of the republic determines the vast diversity in the distribution of the sunshine duration (kerimov and debiev, 2012). the sunshine duration averages 330 days a year and the density of solar radiation reaches about 0.33 kw/m2 in the entire territory of the chechen republic, and reaches 0.46 kw/m2 on the plain and in mountainous districts. at the same time, there are sunless days, which range from 34 to 40 days in the valley and submontane districts of the republic and from 10 to 12 days in the mountainous areas. the largest number of sunless days is observed on the flat part of the territory of the republic and is 61 days. the least of “sunless” days in the annual cycle can be seen in the winter, from 6 to 12 days. from 1 to 5 “sunless” days are observed from the end of may to the end of september. in general, over the year cloudy weather decreases direct beam radiation by 20 ÷ 25% of the potentially probable. the value of the total solar radiation is determined by the total influx of direct and diffuse radiation to the horizontal surface of the entire territory of the chechen republic. the total solar radiation on the republic territory reaches the maximum intensity in may-july, varies from 280 to 300 mj/m2 for submontane districts, and ranges from 360 to 400 mj/m2 in high-mountain districts. the total volume for the entire territory of the chechen republic is estimated at 1.365 kwh/(m2∙year). recently, in view of technological upgrade, the efficiency factor of solar panels is becoming higher and the energy conversion efficiency of silicon photovoltaic sources series-produced by the industry is 12-17%. it can be said that given the current level of technology development and the lack of state support, it is economically feasible to install solar stations only in areas where technical means do not allow this to be done with the help of other power plants (barinova, 2017; kerimov and gaisumov, 2011). 5.3. expander-generator sets for the purposes of energy saving during the production of electrical energy, in addition to the recovery of waste-heat from gas turbine engines, the utilization of the excess pressure of natural gas supplied through gas pipelines to the gas distribution station or kerimov, et al.: basic stages of energy development program implementation in the chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020 507 gas distribution point of compressor stations and large enterprises has recently become very relevant. as well as a thermal power plant and combined heat and power plant. developing technologies for small energy, as well as the creation of own generating, autonomous energy sources on the basis of high-performance turbo-expander units with electric capacity of 0.5-10 mw, in different districts, human settlements and industrial facilities contribute to the economically sound and prospective development of the energy complex (aldo and hansen, 2020; kaja and slabe-erker, 2020). gas is supplied and distributed in the chechen republic by the gas supplying organization oao chechengazprom. the total length of high-pressure gas pipelines is currently 698 km. from 2000 to 2008, more than thirty gas control stations (gds) were restored and built. gas consumption in 2009 amounted to 3.1 billion m3. the energy resource potential of pressurized gas consists of the following parameters: gas pressure at the inlet and outlet of the pipeline; efficiency factor of a turbo-expander; value of gas flow rate and thermodynamic characteristics. the total value of the potential of the available gas capacity at the gas distribution station of the chechen republic is estimated at 27.2 mw. with this value of gas it becomes possible to generate electrical energy in the amount of 220 to 250 million kwh/year and will largely depend on the mode and specific character of design of the applied diagrams and operation algorithm. the employees of the company zao “ion exchange technologies” (moscow) performed an analysis of the possibilities of introducing an energy-saving complex based on an etda expander-generator set of russian production. studies have determined that expander-generator sets can be effectively used at 11 gas distribution stations of the chechen republic. in 2011-2018 it was planned to introduce the technology of expander-generator sets at five gas-regulating stations, which would affect the use of irretrievably lost energy of compressed gas, with an installed total capacity of 11.3 mw and generation of electrical energy up to 100 million kw/h in year. estimated project cost 500 million rubles. the first project was supposed to be implemented in 2011-2012 at gds-1, with a rated capacity of 1.5 mw and electrical energy generation up to 13.1 million kw/h/year. the estimated cost of the project is 62.1 million rubles. currently, the team of the scientific and technical center (stc) “green energy” has developed proposals for the introduction of expander-generator set at the chir-yurt cement plant, which will significantly increase the energy supply of technological production. 5.4. bioenergy the issues of solid municipal waste (smw) utilisation in bioenergy in the chechen republic have not been raised before, however, it is known from international experience that the level of profitability of biogas production increases significantly when waste utilisation from cities with a population of more than 100 thousand people and preparation for production is carried out in advance at the stage of filling of the municipal solid waste landfills. the implementation of such production is possible in some cities of the chechen republic; grozny, gudermes, argun, shali, urus-martan, etc. (kerimov and debiev, 2012; morales and corredor, 2014). the evaluation of initial biogas utilization, at the municipal solid waste landfill of grozny, is given below. 5.4.1. engineering factors • the value of biogas obtained is 13-15, 0 thousand m3/day. (5.0 million m3/year); • reduction of ghg emissions: about 40 thousand tons of co2 equivalent/year; • the design capacity of the engine generator, which can be used to generate electrical energy from biogas is 1000 kw; • tariff of electricity sold 1.74 rubles./kwh; • discount rate 10%; • the cost of a unified social tax (ust) is 8 euro/t со2 eq. the cost of construction of the biogas collection and utilization system in developed countries is usually in the range of $ 1,5502,250/1 kw of installed electric capacity. in accordance with the kyoto protocol, as a result of biogas collection and utilization, the so-called “carbon credits” or “emission reduction units” can be carried out as part of joint implementation projects. as a result, one can get additional investment of approximately $ 0.02/kwh (0.62 rubles kwh). this possibility increases significantly the attractiveness of biogas utilization even at the landfills that were previously considered prospect less. the average payback period of the project for landfill gas utilization for electricity production without taking into account the sale of emission reduction units is 7-8 years, and taking into account the sale of emission reduction units is <3 years. for the domestic waste recovery with biogas production at existing landfills in large cities and the human settlements of the chechen republic, it is necessary to conduct research on the domestic waste potential assessment, determine the direction of utilization and develop the project feasibility study for the implementation of technology. to solve these problems, in 2011 it was planned to allocate 10.0 million rubles for the research works. 6. subprogram “multiple use of geothermal waters” more than 70% of the geothermal water reserves of the russian federation are located on the territory of the north-caucasian federal district. among the constituent entities of the russian federation the chechen republic ranks third in terms of explored geothermal water reserves, trailing only to dagestan and the kamchatka region. on the territory of the chechen republic there are the most favorable conditions for the creation of geothermal circulation systems, which is confirmed by the long-term operation of the first geothermal circulation system in the ussr created in the khankala valley in 1985 (kerimov and gaisumov, 2017, april 7). on the territory of the chechen republic there are 14 thermal intakes, according to which the total explored reserves amount kerimov, et al.: basic stages of energy development program implementation in the chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020508 to 64,680 m3/day in spouting mode. the reserves for commercial categories in the amount of 10,650 m3/day are approved for two thermal water intakes (khankala, goity). in explored fields, the commercial reserves of geothermal waters cannot satisfy the ever increasing demand for heat. for example, in 1985 only in grozny the declared demand for thermal water amounted to 78 thousand m3/day. that’s why to satisfy the needs of the republic in thermal water, an increase in the raw material base is required due to the construction of new thermal intakes and expansion of old ones. at present, the main consumer of thermal water is municipal infrastructure 12.8 thousand m3/day (48%) and agriculture 11.4 thousand m3/day (43%). according to calculations, the creation of a geothermal heat supply system in the territory of grozny city on the basis of explored resources of the fields will ensure annual savings of fossil fuel at 150 thousand tonns of fuel oil equivalent and reducing the harmful substances emissions into the atmosphere in the amount of 250 thousand tons. from the available 14 geothermal water deposits, the khankala field is the largest and most promising in terms of commercial development, which is characterized by a shallow bedding of deposits, large flow rates, high enthalpy, low salinity, and high content of valuable components. within the decree of the government of the russian federation no. 218 of april 9, 2010, by efforts of gsotu named after acad. m.d. millionschikov the comprehensive project was implemented to create a experimental-industrial geothermal station based on the implementation of the circulation scheme for using the deep heat of the earth (kerimov and gaisumov, 2017, april 7). this field has several advantages over others: • bedding of deposits at shallow depths (up to 1000 m); • large flow rates (up to 1 l/cm); • high temperatures (up to 1000с and more); • the waters of the xiii bed are practically fresh, with salinity of 0.81-1.7 g/l, which conditions their low corrosion activity; • the ability to extract valuable components. the area assigned for the khankala geothermal station is 4900 m2, while the area of the station itself, including the wells, is 406 m2. at the same time, the heat survey of the village. gikalo and the adjacent territory of the khankala deposit revealed 13 abnormalities with various sources (bonfires, heating systems, etc.). to reduce the formation of solid deposits in the form of carbonates, corrosion inhibitors (5 g/ton of treated water) are used in the field (kerimov and mintsaev, 2019). 7. conclusion the development of the energy complex of the chechen republic requires the creation of a stable multi-vector energy that can satisfy the growing needs of the population and the economy of the region, and renewable energy sources need to be given close attention, drawing on the experience of other entities and countries developing innovative technologies in this direction. the primary tasks of the development of the republic’s energy sector are as follows: 1. development of the modern program for the development of alternative and renewable energy sources in the chechen republic. 2. organization of hydrological monitoring on the mountain rivers of the republic in order to select the optimal locations for shpp. 3. organization of integrated meteorological observations (solar radiation, wind speed and direction at different heights, etc.) in various districts of the republic in order to select the optimal locations for solar and wind power plants. 4. implementation of fundamental and applied research and development in the field of renewable energy. 5. development of recommendations and investment proposals for industrial enterprises and housing and communal services of the republic. references aldo, j.g.p., hansen, t. (2020), technology characteristics and catchingup policies: solar energy technologies in mexico. energy for sustainable development, 56, 51-66. al-falahi, m.d.a., jayasinghe, s. (2017), a review on recent size optimization methodologies for standalone solar and wind hybrid renewable energy system. energy conversion and management, 143, 252-274. barinova, v.a., lanshina, t.a. (2017), features of the renewable energy sources development in russia and in the world. russian entrepreneurship, 17(2), 259-267. burmistrov, a.a., vissarionov, v.i. (2009), methods for calculation the resources of renewable energy sources. moscow, russia: moscow power engineering institute. p144. debiev, m.v., popov, g.a. (2012), analysis of the development schemes of energy capacities in the region on the basis of the scenario approach: bulletin of astu. management, computer engineering and informatic, 1, 35-40. ellabban, o., abu-rub, h., blaabjerg, f. (2014), renewable energy resources: current status. future prospects and their enabling technology. renewable and sustainable energy reviews, 39, 748-764. farkhutdinov, a.m., cherkasov, s.v. (2017), thermal groundwaters of the chechen republic. nature, 3(1219), 28-35. guardian, t. (2017), electric cars and cheap solar could halt fossil fuel growth by 2020. the guardian. kaja, p., slabe-erker, r. (2020), social policy or energy policy? time to reconsider energy poverty policies. energy for sustainable development., 55, 32-36. kerimov, i.a., debiev, m.v. (2012), the use of pumped storage sets in the energy system of the chechen republic. electronic journal engineering bulletin of the don, 1. available from: http://ivdon.ru/ magazine/archive/n1y 2012/673. kerimov, i.a., gaisumov, m.ya. (2017), energy development program of the chechen republic for 2011-2030. science and education in the chechen republic: state and development prospects. proceedings of the all-russian research-to-practice conference dedicated to the 10th anniversary of the fou. russian academy of sciences. p38-63. kerimov, i.a., debiev, m.v. (2012), solar and wind energy resources of the chechen republic. engineering bulletin of the don, 1. available from: http://www.ivdon.ru/magazine/archive/n1y 2012/677. kerimov, i.a., gaisumov, m.ya. (2011), prospects for the use of expandergenerator sets in the gas network system of the chechen republic. bulletin of the academy of sciences of the chechen republic, 1(14), 80-89. kerimov, i.a., mintsaev, m.sh. (2019), the main stages of the chechen republic energy development program implementation in the kerimov, et al.: basic stages of energy development program implementation in the chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020 509 collection: geoenergy-2019. proceedings of the iv all-russian research-to-practice conference. p38-56. kougias, i., patsialis, t. (2014), exploging the potential of energy recovery using micro hydropower systems in water supply systems. water utility journal, 7, 25-33. morales, s., corredor, l. (2014), stages in the development of a small hydropower project: context and implementation basic criteria. dyna, 81(184), 178. national renewable energy laboratory. (2017) solar has the most potential of any renewable energy source. united states: national renewable energy laboratory. palival. p., patidar, p.n. (2014), determination of reliability constrained optimal resource mix for an autonomous hybrid power system using particle swarm optimization. renewable energy, 63, 194-204. sibikin, y.d., sibikin, m.yu. (2010), alternative renewable energy sources. m. knorus. p232. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 2 • 2022 11 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(2), 11-19. determining the offshore wind power potential in the mix-electric power of vietnam: the role of feed-in tariff policy xuan hoi bui*, phuong thao nguyen hanoi university of science and technology, vietnam. *email: hoi.buixuan@hust.edu.vn received: 04 september 2021 accepted: 30 december 2021 doi: https://doi.org/10.32479/ijeep.11877 abstract the purpose of the research is to examine the offshore wind power potential in the mix-electric power of vietnam. by using net present value method, the paper also aims to explore how economic factors influence the offshore wind power feasibility in the conditions that the technical factors are ensured. the result indicates that offshore wind power will have a low proportion in the mix-electric power of vietnam before 2030 and may be accelerated in the period 2035-2040. electricity supply from offshore wind is not economically viable without improvements in investment, operating costs, and capacity factor. in particular, the feed-in-tariff (fit) policy designed to support the development of renewable energy sources by providing a guaranteed, above-market price for producers, will be a decisive factor in developing offshore wind power of vietnam. additionally, the differences between characteristics of site’s condition leading to the disparities in capital and operational expenditure and capacity factor. thus, the electricity price and the subsidies for bottom-fixed sites and floating sites should be disparate and the location of offshore wind farms should be considered to ensure the harmonization of the profits derived from different types of offshore wind farms. keywords: offshore wind power development, fit policy, capacity factor, power development plan 8 jel classifications: d4, q21, q28, q41, q43, q48 1. introduction currently, vietnam is accelerating the development of electricity from renewable resources to meet the country’s increasing electricity demand and diversify mix-electric power that ensures energy security. however, the most important characteristic of renewable energy is the intermittent in supply, thus, the power system must have a suffering backup source leading to the increases in the production cost of electricity. over the last 3 years, the proportion of renewable energy has increased too quickly with a capacity exceeding the planning, while low electricity consumption demand during covid-19 period and the overloaded local grid has led to an excess of that source. according to national load dispatch center (nldc, 2021), over 3000 mw capacity of renewable energy was cut off on december 27, 2020, and the situation of reducing renewable power capacity is still happens regularly in the first half of 2021. hence, the development of renewable energy in the following phase needs more careful study. offshore wind power is another renewable energy source, which has great technical potential in vietnam. in addition, offshore wind farms have some advantages in comparison with onshore wind farms including high power rating, high yield energy, high offshore wind and unlimited space which make the installation of bigger offshore wind turbines possible etc. according to offshore wind road map for vietnam launched by the world bank group (tran, 2021), this energy source could play a significant role in sustainably meeting vietnam’s rapidly growing electricity demand and has the potential to supply 12% of vietnam’s electricity by 2035. to stimulate the growth of offshore wind energy, many policies which might include energy payment, international treaties, legislation, and incentives for investment are proposed. according to the government’s decision no. 39/2018/qd-ttg this journal is licensed under a creative commons attribution 4.0 international license bui and nguyen: determining the offshore wind power potential in the mix-electric power of vietnam: the role of feed-in tariff policy international journal of energy economics and policy | vol 12 • issue 2 • 202212 enacted by the vietnamese prime minister (2018), evn will buy wind power from investors at a tariff of 9.8 us cents/kwh for offshore wind power projects commissioned before november 01, 2021. recently, the new fit policy with the proposed tariff of 8.47 us cents/kwh for offshore wind applied to commissioned projects will be put into commercial operation from november 2021 to december 2022 and the rates of 8.21 us cents/kwh for projects commissioned in 2023 and after 2023, fit will be replaced with an auction system which is being mulled over (phan and doan, 2020). changing in fit policy or the emerge of the auction mechanism will affect the feasibility of offshore wind projects if there is no innovation in technology to reduce costs for offshore wind power projects. until now, there has been currently no research focusing on the economic potential of offshore wind in vietnam. the economic potential can change over time along with the development of technology, thereby leading a reduction in investing cost, operating cost, and policy shift. the purpose of the research is to determine the economic potential of the different regions of vietnam that has been assessed as having technical potential and its fluctuation when the economic factors such as investment cost, operating cost, fit policy, and capacity factor change. aside from determining the potential, we also compare it against the required capacity in pdp 8 (table 1) for evaluation and policy recommendation. the structure of this study is as follow: after introducing the background, the first part starts traditionally with a literature review of assessing offshore wind potential and then identifying the data and methodology that will be used in this paper to estimate the wind power potential in vietnam, before showing a result of the research. finally, it comes to conclusion and policy suggestions. 2. literature review theoretical potential of offshore wind power is defined as pure potential in terms of energy which is estimated via analyzing statistics meteorological data (du et al, 2020). the region has theoretical potential and is suitable for planning the construction of wind farms is supposed to be an area of technical potential. the region which has technical potential and wind farms in this area bring economic benefits to investors is considered as an economic potential area. in this paper, we focused on evaluating the economic potential of the areas having technical potential of offshore wind power. many economic studies on offshore wind potential have been conducted globally and the levelized cost of energy (lcoe) and net present value (npv) are the two commonly used methods. there may be some different points in the calculation steps or the selection of the input factors among these papers, but the core method remained the same. shin (2012) investigated the economic feasibility of offshore wind power in china and south korea. this paper focused on the offshore wind power project which either has already constructed or being constructed. it was also an analysis of feasibility with npv method conducted with the consideration of the status of technology, market and policy in korea and china. shin argued that npv method can be employed to economically evaluate large-scale infrastructure constructions, such as wind power generation farms. this research demonstrated the policy’s impact on the viability of wind power projects but showed the limitations in using the same discount rate of 7.5% for both korea and china, which may lead to some non-objective judgments due to the distinct economic characteristics. on the issue of estimating the operating cost of a unit production by the wind energy system, diaf et al. (2013) used the lcoe method which is described as the ratio of the total annualized cost of the wind system to the annual electricity produced by this system. because the economic viability of wind energy project depends on its ability to generate electricity at a low operating cost per unit energy, lcoe is an essential key to determine the economic potential of an individual site. the determination of the unit cost of energy involves two main steps: the first step is to calculate the present value of cost by taking into consideration the initial investment cost of the system and the present value of operation and maintenance cost throughout the lifetime-system, and the second step is to determine the unit cost of energy. caglayan (2019) concerned on both economic aspect and sufficient detail. this research applied a high spatial resolution to the three aspects of offshore wind potential analysis including ocean suitability, the simulation of wind turbines and cost estimation. a set of constraints is determined, then turbine designs specific to each location are selected by identifying turbines with the cheapest lcoe, restricted to capacities, hub height and rotor diameters. thus, lcoe is a powerful screening tool, and lcoe method demonstrates its strength in assessing the change of production costs when technology changes. however, according to eia (2013), there are unaccounted factors that which need to be involved when analyzing systems. lcoe works best when combined with other methods to give a more accurate, encompassing comparison of generation systems. to overcome this limitation, in the report conducted by musial et al. (2016), lcoe and levelized avoided cost of energy (lace) were computed to estimate the economic potential of offshore wind energy resources in maine (united state). lace is defined as a metric used to represent the electricity generation costs of a technology over its expected life cycle and is usually calculated per 1 mwh (beiter et al., 2016). eia (2013) considered lace particularly useful in assessing the economic competitiveness of non-conventional energy sources such as wind and solar. lace is determined based on the marginal cost of electricity generation and capacity value which are expressed as the average (avoidable) cost per mwh. the marginal power generation cost is determined table 1: offshore wind power installed capacity in draft pdp 8 2020 2025 2030 2035 2040 2045 offshore wind power installed capacity (gw) 0 0 0.5 6.4 14 19 total installed capacity (gw) 69.2 97.3 132.8 183.8 227 270 percentage 0 0 0.38 3.48 6.17 7.04 source: ievn (2020) bui and nguyen: determining the offshore wind power potential in the mix-electric power of vietnam: the role of feed-in tariff policy international journal of energy economics and policy | vol 12 • issue 2 • 2022 13 by the production cost of the highest-cost power generating unit dispatched to meet the load demand. the difference between the lcoe and the lace in each region is defined as the “net value” of that area, and this net value is used to determine the economic potential on the principle that an area having technical potential with net worth greater than 0 is considered as an area with economic potential. this method evaluates the economic efficiency of wind power projects taking into account the power generation costs of other sources. however, this method still shows limitations in analyzing the impact of the electricity price policy on the viability of the project, for example, the profit change is not shown/indicated, and the amount of computation as well as the required data is also larger. effiom et al. (2016) use an economic cost which was presented to evaluate the feasibility of offshore wind turbine farms in nigeria. the methodology adopted in this study includes the cost breakdown structural approach and the simple lcoe method. the later was used in evaluating the life cycle cost (lcc) of each phase of offshore wind turbine farm project. lcc is used to identify all the critical components of the project life cycle from pre-planning to decommissioning. lcc also takes into account the risks or expenses in different phases of the project and their impact on life cycle costs considering the value of money over time. another study evaluated the economic potential of offshore wind energy in the gulf of bothnia which was analyzed using lcoe and lcc analysis by lappalainen (2019). in both studies, life cycle phases are divided to pre-development and consenting (p&d), production and acquisition (p&a), installation and commissioning (i&c), operation and maintenance (o&m) and decommissioning and disposal (d&d). the combination of the lcoe and lcc method helps brings the more precise. in short, lcoe focuses on the assessment of power production cost and output and while ignoring the calculation of revenue from electricity sales. the lcoe is a good indicator of the impact investment cost fluctuation caused by technological developments, and the final result is the change in production cost per unit of power. lcoe can be combined with other methods such as lcc to obtain more accurate outcome. however, lcoe is not suitable in comparing the feasibility of different projects with different types of technology, and lace can be used in conjunction with lcoe to address this limitation. nevertheless, even with such combination, lcoe is still not suitable in assessing the policy impact. npv is used to calculate the project’s net value in present value of currency, and the calculation using npv requires both cost and revenue data. npv is concerned with determining the trajectory of future market prices and the financial consequences of policies, and it is appropriate for studying policy impact. the limitation of this method is that it is difficult to determine the specific impact of each factor on the outcome in scenarios where many factors change. 3. methodology and data the purpose of this study is to explore the impact of fit policy, capital expenditure (capex), operational expenditure (opex), and cf on the volatility of offshore wind power economic potential in vietnam. fit policy has always been a hot topic in vietnam and the remaining factors are considered as the cost drivers in several previous studies (ryan, 2016; irena, 2019). as the impact of fit policy is accounted for in the assessment, npv method is selected. each area with technical potential is regarded a project. if the project’s npv is positive, the area has economic potential. the total national’s economic potential is the sum of the capacity of all sites with positive npv. when calculating the economic potential, this paper focuses on the issue of determining the impact of economic factors, for example, investment costs and electricity price. thus, we assume that the technical factors, such as the demand of power transmissions from the potential site to the onshore substations and the inter-regional power transmissions, are ensured. therefore, the entire estimate power production from the potential farm is purchased. in addition, the average construction period of a wind power project usually takes 3-5 years, so this period is assumed 4 years. this study is conducted in three main steps. the first step is to determine the cash flow after tax (cfat) in each project, which is divided into 2 phases. cash outflows in the initial investment and financing phase are determined by the financing activity or fundraising to provide the main capital source, including funds from banks and investments. the investment activity concerning the use of mobilized capital, is invested mainly into capital expenditure (capex). this phase is equal to the project construction time (4 years) and the first year of this phase is equivalent to a financial year of −3. cash inflows (benefits) during the long-term operational phase are characterized by the main cash inflows from revenues, determined by two main value drivers: price per unit or tariff per unit produced (in kwh) and the quantity sold, or output measured in kwh as annual energy production (aep). there are two main types of cash outflows (costs) in the operational phase: opex, especially operation and maintenance of wind turbine generator and cost of capital (coc), which mainly consists of debt service. to determine the cfat in the operating phase, the interest payment is first calculated to determine taxable income. until now, the equity in offshore wind power projects in vietnam has usually accounted for 20-30% of total investment, the rest is either domestic or foreign loan. since interest payments will be deducted from taxable income, investors usually set the highest possible loan. in this paper, the weightage of equity will be 20% so that the weightage of debt will reach 80% (the highest possible level), thus bringing the highest interest payment. data on the grace period, repayment period and cost of debt are shown in table 2. the interest payment of each project can be estimated from those data. after calculating the interest payment, the taxable income of the projects is established by formula (1). tit=cfbtt-dt-it (1) where: tit is the taxable income at time t, cfbtt is the cash flow before tax at time t and cfbtt = revenuet – opext, dt is bui and nguyen: determining the offshore wind power potential in the mix-electric power of vietnam: the role of feed-in tariff policy international journal of energy economics and policy | vol 12 • issue 2 • 202214 the depreciation at time t (for the convenience of calculation, the straight-line depreciation method will be and the depreciation period is assumed to be 20 years which is equal to the operating period and has no salvage value), it is the interest payment at time t. income tax (it) can be calculated by multiplying ti by the tax rate. the tax rate is not fixed, and its determining principle is shown in table 3. profit after taxes (pat) can then be determined and cfat can be calculated by formula (2). cfatt=patt+dt-gt (2) where: cfatt is the cash flow after tax of investors at time t, patt is the profit after taxes at time t, gt is the principal payment at time t. the second step is to calculate the npv of each potential site, then calculating the total economic potential. the npv of each project can be established by formula (3). npv cfat rt t t t � ��� � 3 1( ) (3) where: cfatt is the cash flow after tax of investors at time t, r is the discount rate, t is the time period (in this case, it is the lifetime of the project and is assumed to be 20 years which is equal to the average lifetime of the current turbine). the weighted average cost of capital (wacc) serves as the discount rate. due to the difference in project’s tax rate, each site will have its distinct discount rate. as shown below, the wacc formula is: wacc=wd*kd*(1-tr)+we*ke (4) where: we is the weightage of equity in total capital, wd is the weightage of debt in total capital, ke is the cost of equity, kd is the cost of debt, tr is the tax rate of the project and its formula is tr t t t t � � �5 10 20 where t5, t10 and t20 are the total number of years when the tax rate is 5%, 10% and 20%, respectively. in the last step, the analysis scenarios are proposed. the first scenario is the baseline scenario (bau), presenting the impact opex, capex, cf and fit policy in 2020. taking account of the recent announcement of the fit application extension to the end of 2023, two alternate 1-changing-factor scenarios (sc2 and sc3) with lower fit prices compared to the base scenario. these scenarios can be used to estimate the offshore wind power potential in vietnam when fit 2 and fit 3 prices come into effect after november 01, 2021 and january 01, 2023 respectively. the remaining (sc4 to sc12) are scenarios with four factors changed. in each phase, two types of scenarios are proposed, the normal scenario and the low scenario. the normal cases are based on the projections of the change of cost and cf. in the low cases, both fit and cf costs will be lower than those in the ordinary ones. these scenarios are based on the forecast of the likely variation in costs and cfs of the offshore wind technology (irena, 2019), along with the adjustments to suit the situation in vietnam (brown and vu, 2020; authors). since irena’s forecast are made up to 2050, analysis scenarios to 2050 will be developed. the improvements in capex and opex are based on the status that vietnam is well-positioned to capture economic benefits from supply chain development. for industry players, in addition to the capacity in civil construction, the greater use of local sources will be the basis for reducing costs and increasing the competitiveness of offshore wind energy compared to other energy sources. currently, vietnam has one of cswind’s major facilities located in phu my serving the global market with a capacity of more than 900 towers annually. moreover, ge vietnam supplied turbines for offshore wind projects in vietnam such as bac lieu offshore wind power plant and helukabel manufactures turbine cable components, including medium voltage applications. according to the dea’s statistics (dea, 2020), vietnam will have a production localization of 30% by 2030, 60% by 2040, and 100% by 2050. moreover, in the feasibility analysis of some offshore wind projects in vietnam, it is proposed to use turbines from such major turbine producers in the world as vesta, ge energy or siemens. the expense for those turbines tends to decrease thanks to the development of technology, especially from 2020 to 2025. however, vietnam is still in the early stages of development, so the capital and operation costs are likely to be set at a high point compared to the world average cost before 2030. the resolution passed at the congress sets the target that vietnam will have become a high-income country by the year 2045, so we assume that vietnam will catch up with other developed countries’ cost reduction rate in the period 2040 2050. in addition, vietnam has a good wind regime, so the cf will be set equal to the world’s forecasted cf growth rate. moit proposes to change the application route of the competitive wind auction mechanism and this route will table 2: cost of capital and yield expectation of investors index remarks weightage of equity 20% common use weightage of debt 80% common use cost of equity 10% common use cost of debt 6% state bank of vietnam (2021) grace period 4 years equal to the assumed construction time repayment period 10 years common use in feasibility studies of some projects. starting from the first year of operational phase source: elaborated by authors table 3: income tax rate for power projects in vietnam tax rate index profitable first 4 years 0% the next 9 years 5% the next 2 years 10% other years 20% source: moit (2014) bui and nguyen: determining the offshore wind power potential in the mix-electric power of vietnam: the role of feed-in tariff policy international journal of energy economics and policy | vol 12 • issue 2 • 2022 15 be implemented after 2023. however, according to some assessments, vietnam government should develop a new fit tariff for offshore wind power that can support the auction mechanism in the early stages or can be applied in parallel with the auction mechanism (stephenson, 2021; li et al, 2021). therefore, we assume fit policy is still implemented after 2023 and the change in fit can be suggested by the authors. the national power plan 8 reflects vietnam’s reticence in promoting offshore wind power development before 2030. in addition, fit rates are often adjusted downward over time thanks to tariff degression to encourage technology cost reduction. therefore, we assume that fit price will continue to decline in the period before 2035. from 2040 to 2045, offshore wind power will develop rapidly according to the power plan. furthermore, some areas with technical potential haven’t been exploited due to significantly higher costs and complex terrain. to attract investment and ensure that the proposed capacity is met, we assume the fit price in this period should be increased compared to that in the previous period. scenarios are shown in table 4 with the factors as the percentage change in comparison to the bau scenario. regarding data collection, all secondary data on technical potential including park size, number of turbines, annual energy production (aep), as well as cf and estimated costs data including capex, and opex are based on the research conducted by the danish energy agency (dea, 2020). the capex includes not only the development and construction costs of the offshore wind farms but also the expenses for the substations and cables from the wind farm sites to the shore. the dea’s research identified 25 potentially feasible sites for fixed bottom foundation projects (the left-hand side of figure 1) and 17 sites for floating foundation projects (the right-hand side of figure 1) – along the coast of vietnam. both fixed bottom and floating projects with 500mw nameplate capacity have been considered for each site. all the sites have a total area of about 37,400 km2, are 5-100 km from the shore, and have wind speed of 6.5-9.5 m/s. 4. results and discussions if the points representing the economic potential of the scenarios are connected (figure 2), an upward sloping curve is obtained. the association of the curve shows the difference in economic potential at different times or at the same time under different conditions. intuitively, it can be seen that the potential before 2035 is relatively low and gradually increases over time. there will be a sharp increase in the potential from 2035 to 2040 and this increase will slow down after 2040. in the bau scenario, there are two fixed bottom projects having positive npv, indicating an economic potential of 1000 mw for offshore wind power in vietnam’s mix-electricity. in case that the table 4: the offshore wind power development scenarios bau_sc sc1_fit2 sc2_fit3 sc3_low_2030 sc4_ord_2030 sc5_low_2035 fixed floating fixed floating fixed floating capex (real 2020) set value 0% 0% -15% -15% -20% -20% -25% -25% opex (real 2020) set value 0% 0% -10% -10% -15% -15% -20% -20% fit (uscent/kwh) 9.8 -13% -16% -20% -20% -20% -20% -22% -22% cf (%) set value 0% 0% 15% 17% 15% 17% 16% 18% bau_sc sc6_ord_2035 sc7_low_2040 sc8_ord_2040 sc9_low_2045 fixed floating fixed floating fixed floating fixed floating capex (real 2020) set value -30% -30% -35% -35% -40% -40% -40% -45% opex (real 2020) set value -25% -25% -25% -25% -30% -30% -30% -35% fit (uscent/kwh) 9.8 -22% -22% -16% -16% -16% -16% -12% -12% cf (%) set value 16% 18% 17% 19% 17% 19% 20% 22% bau_sc sc10_ord_2045 sc11_low_2050 sc12_ord_2050 fixed floating fixed floating fixed floating capex (real 2020) -45% -50% -45% -50% -50% -55% opex (real 2020) set value -35% -40% -35% -40% -40% -45% fit (uscent/kwh) set value -12% -12% -8% -8% -8% -8% cf (%) 9.8 20% 22% 22% 23% 22% 23% source: elaborated by authors figure 1: vietnam offshore wind technical potential map site screened source: dea (2020) bui and nguyen: determining the offshore wind power potential in the mix-electric power of vietnam: the role of feed-in tariff policy international journal of energy economics and policy | vol 12 • issue 2 • 202216 fit follows the proposal of fit extension and is reduced by a sliding scale up to 2023 (sc2_fit2 and sc3_fit3), the economic potential of offshore wind power in vietnam will reach zero. however, it is unclear whether this proposal will be adopted. it is worth noting that in 2020, evn had a surplus of electricity due to the large uptake in solar. as a result, a reluctance can be seen in the suggestion of fit extension. assuming that the proposal will be approved, and the tariffs would be much lower than the current one, the sharp fall in electricity prices has made wind power investors worried and divert their investment to new planned wind power projects. moreover, the covid-19 pandemic has been slowing down wind power projects, making it difficult for many offshore wind power projects to come into commercial operation before november 2021 to be eligible for fit and so they had to incur lower prices. the development of offshore wind power projects in current time, therefore, has faced many difficulties. by 2030, the economic potential of offshore wind power will range from 2500 mw to 3500 mw. these estimates partly reflect the relatively low economic potential of offshore wind power before 2030. in addition, the npvs of some potential areas with a capacity of 500mw each do not appeal to investors (table 5). besides, all economic potential areas are located in the southcentral region. in fact, the overloading of the 500kv line in this area is one of the toughest problems in operating vietnam’s power system which could not be solved in a short time. therefore, continuing to promote offshore wind power development before 2030 is not suitable for vietnam in both benefits and technical aspects. the period of 2035-2040 seems to be more suitable for promoting offshore wind power development once both the economic potential in this stage and the benefits obtained from each project are greater, and the problem of power transmission is also partly solved. another important point is that although the electricity purchase price in the scenarios for 2030 and 2035 is assumed to be less than that of fit 3, the economic potential will increase rather than decreases as when fit 2 and fit 3 take effect. this difference mainly comes from reduced cost and increased cf. by 2035, the total economic potential coming from fixed bottom sites and its leaping increase in 2040 is the result not only of more fixed foundation areas with high economic potential, but also of the cost and cf’ reaching the efficiency threshold of low-cost floating foundations, generating an additional 2500-3000 mw. in the 2050 scenario, it is assumed that cost will be halved, and cf will increase by 23%, but there are still some uneconomically viable floating foundations areas. thus, it can be seen that vietnam will find it difficult to effectively exploit offshore wind power without reducing costs and increasing cf. the development of offshore wind power in the coming decades will highly depend on these factors. however, these factors are dependent on technology development, and this seems to be beyond vietnam’s control (vietnam can only rely on the technology from developed countries). the potential change resulting from this can be viewed as raw potential and what the vietnam government needs to do now is to calibrate this potential through policy tools. fit policy mechanism is the most suitable tool for this purpose when considering such factors country’s legal tradition and policy history or the developments of technology. vietnam is in the early stages of offshore wind power development with the aim of diversifying the power supply source and investment portfolio to ensure energy security. competitive tenders may introduce more transparent prices. however, it is typically offered periodically and required developers to incur transaction costs to compete which is not suitable for thinly capitalized projects (richkerson et al., 2012). therefore, bidding is not suitable for diversifying the project scale or attracting a broad range of capital providers to participate in the market and it is also unbecoming for the current conditions in vietnam. another reason is that vietnam still lacks the technical and management resources for the management of complex renewable energy policies. the benefits of fit in reducing the burden, not only for investors but also for managers (haas et al., 2011), making it suitable for continued application in vietnam. the characteristics of the influence from fit policy are different from costs and cf. first, the potential change brought by the change in fit policy is usually smaller than the change resulting table 5: the npv of potential sites in the bau scenario and the 2030 scenario site number capacity (mw) npv (usd) total economic potential (mw) bau_sc site 14 500 63,770,076 1000 site 15 500 65,238,565 sc3_ low_2030 site 12 500 60,876,257 2500 site 13 500 52,829,531 site 14 500 174,234,326 site 15 500 168,026,842 site 16 500 1,921,424 sc4_ ord_2030 site 8 500 1,058,109 3500 site 10 500 69,822,060 site 12 500 161,409,336 site 13 500 143,148,485 site 14 500 275,880,032 site 15 500 260,601,143 site 16 500 94,391,089 source: calculated by this study 10 00 0 0 25 00 35 00 40 00 6 50 0 12 00 0 15 50 0 15 50 0 16 00 0 16 00 0 18 00 0 b a u _s c s c 1_ f it 2 s c 2_ f it 3 s c 3_ lo w _2 03 0 s c 4_ o r d _2 03 0 s c 5_ lo w _2 03 5 s c 6_ o r d _2 03 5 s c 7_ lo w _2 04 0 s c 8_ o r d _2 04 0 s c 9_ lo w _2 04 5 s c 10 _o r d _2 04 5 s c 11 _l o w _2 05 0 s c 12 _o r d _2 05 0 m w fixed bottom floating figure 2: economic potential of offshore wind power in vietnam in 13 scenarios source: results of this study bui and nguyen: determining the offshore wind power potential in the mix-electric power of vietnam: the role of feed-in tariff policy international journal of energy economics and policy | vol 12 • issue 2 • 2022 17 from other factors because too much change in electricity prices cannot occur at each adjustment. therefore, the fit mechanism will be responsible for adjusting the marginal potential to fit the plan, and it is not the core factor for potential increase. on the other hand, it takes a long time for certain technology development to help reduce costs and increase cf while the impact of fit on the policy zone in effect can be immediately seen. this can be proved by the results of sc2 and sc3 when the economic potential is no longer decided by the change in fit price. however, this change is not considered bad outcome of the two scenarios as vietnam does not prioritize offshore wind power development in the period 2020-2025. but the rapid potential change due to fit price needs to be carefully considered. the construction and grid-connected process of a wind farm takes relatively long, so any change in electricity price policy during these periods, especially a downward change, may make it difficult for investors to accelerate the progress to reach the initial high price. offshore wind power projects in vietnam are currently facing this situation. in contrast, the upward adjustment of fit price also needs careful consideration because the price increase may cause the projects to develop massively, leading to broken planning or the incompletion of many proposed projects. as a result, there need to be a suitable roadmap for every change in fit pricing policy, avoiding sudden changes and adopting a suitable fit price not only to stimulate the development of offshore wind power but also to ensure that the number of new offshore wind plants does not exceed the government’s original plan. fit policy can be used when the economic potential of the source is higher than the required capacity, so the reduction of electricity purchase price can alleviate the attractiveness to investors and the increase in price can promote the development when the change in cost and cf has not been able to create the planned capacity. from the results of the scenarios, the economic potential of offshore wind power by 2030 will have ranged from 2500 mw to 3500 mw while the pdp 8 only proposes 500 mw, which is relatively lower than the potential. thus, the fit price can be further reduced while ensuring that the economic potential will be greater than the required capacity. in the period 2035-2040, the economic potential is slightly greater than the expected capacity in the base scenario, and it is smaller than this capacity in the low case. from 2040 to 2045, there will be a slow increase in the economic potential whereas an additional 5000mw of capacity during this period is addressed in the pdp 8. although fit price is assumed to increase after 2040, which is still not sufficient to create the desired capacity. as such, vietnam’s policymakers should maintain low fit price over the next decade. if there is no breakthrough in technology, the fit price should be increased after 2035 and it should be higher than the suggested one in analytical scenarios. the difference in the economic potential of the two types of foundations is also a matter of concern. before 2040, all economic potential comes from fixed bottom sites. the slowdown in potential growth in the period 2040-2045 is partly because all fixed bottom sites will have had their economic potential by 2040, so increased potential can only come from floating foundation areas. however, these areas have much greater costs (capex and opex), especially those that are far from shore. in addition to cost reduction and capacity factor increase, these areas require a higher electricity purchase price. another concern is whether it is appropriate to apply the same fit to both types of foundations when there is a great difference in the benefits obtained from these two types of farms (figure 3). besides the type of foundation, the location also leads to a disparity in the obtained benefits. the areas with the earliest potential and the greatest benefits are usually located in the south-central coast. wind power project operation is greatly affected by the wind regime and topographical characteristics of the farm. fixed bottom foundation sites in the north and south should be given more attention than the potential areas in the central region due to the overload of 500 kv transmission lines in this area. overall, focusing on developing sc9_low_2045 fixed bottom floating sc7_low_2040 fixed bottom floating sc8_ord_2040 fixed bottom floating sc10_ord_2045 fixed bottom floating figure 3: npv of feasibility areas source: results of this study bui and nguyen: determining the offshore wind power potential in the mix-electric power of vietnam: the role of feed-in tariff policy international journal of energy economics and policy | vol 12 • issue 2 • 202218 low-cost areas is not necessarily a good choice as it may worsen the local overload in these areas. baulch et al. (2018) concluded that the current market-independent fixed-price fit model is incapable of promoting renewable energy supplies. this research proposes that if the vietnamese government maintains the present fit price, it needs to be adjusted for local inflation and the technology for each renewable resource should be considered. for example, tran et al. (2019) proposed that the vietnamese government set a different fit price for rooftop solar panels from what it does for ground-mounted solar panels. the same principle can be applied to offshore wind power due to the seclusion between the two types of foundation and location of the offshore wind farm in order to state the new tariff to balance the profits earned among these projects. moreover, if the differential fit rates are applied early, electricity is possibly purchased at a higher price from floating foundation wind farms in unfavorable locations so as to mobilize a larger amount of capacity in the period 2040-2045. 5. conclusion and policy suggestions developing renewable energy helps combat climate change, environmental pollution and improve safety in the electrical industry. offshore wind power is one of the renewable sources that has been exploited for a long time in many countries around the world and vietnam is still in the early stages of research and electricity harness from this source, thus, the potential assessment is an essential key to effective policy research and investment orientation. the results of the study indicate that the potential of offshore wind power before 2030 is still low and will strongly develop in the period 2040-2045 based on the development of technology, which helps improve costs and cf. even so, the offshore wind power potential before 2030 will be significantly higher than the required capacity in pdp 8, and the ability to meet the desired capacity will decrease over time. the future fit price, therefore, should be lower than that in the pre-2030 scenario and higher than that in the later scenarios. the results also show the limitations of the current fit pricing mechanism, and thus, some recommendations and notes should be given. firstly, moit and the vietnamese government should develop a long-term roadmap for fit price for offshore wind power, and all cost and cf variations should be carefully considered in decision making. secondly, a new fit tariff needs developing based on the type of foundation and location of the wind farm. the benefits from the floating and fixed bottom foundation wind farms or from the wind farms located in different places are comparatively different. hence, in order to motivate the development of floating foundation wind farms and harmonize the benefits obtained from such farms, a differentiated electricity tariff should be applied. much more research needs to be done for considerable examination of the economic potential and adopting more suitable policies to motivate the development of offshore wind source to meet the energy demand in the coming decades while avoiding the fact that the installed capacity greatly exceeds the national power development plan as can be seen in the case of solar energy. references baulch, b., do, d.t., le, h.t. (2018), constraints to the uptake of solar home systems in ho chi minh city and some proposals for improvement. renewable energy, 118, 245-256. beiter, p., musial, w., kilcher, l., maness, m., smith, a. (2016), an assessment of the economic potential of offshore wind in the united states from 2015 to 2030 (report no. nrel/tp-6a2067675). united states: national renewable energy laboratory. brown, m., vu, t. (2020), vietnam’s evn faces the future: time to get renewable right. united states: the institute for energy economics and financial analysis (ieefa). available from: https://www.ieefa. org/wp-content/uploads/2020/09/vietnams-evn-faces-the-future_ september-2020.pdf [last accessed on 2021 jul 25]. caglayan, d.g., ryberg, d.s., heinrichs, h., linßen, j., stolten, d., robinius, m. (2019), the techno-economic potential of offshore wind energy with optimized future turbine designs in europe. applied energy, 255, 113794. dea. (2020), offshore wind resource potential and costs in vietnam. hanoi: dea. diaf, s., notton, g., diaf, d. (2013), technical and economic assessment of wind farm power generation at adrar in southern algeria. energy procedia, 42, 53-62. doan, q.v., dinh, n.v., kusaka, h., thanh, c., khan, a., toan, d.v., duc, n.d. (2019), usability and challenges of offshore wind energy in vietnam revealed by the regional climate model simulation. scientific online letters on the atmosphere, 15, 113-118. du, t.v., nguyen, a.h., pham, t.v. (2020), technical issues of offshore wind energy. available from: https://www.nangluongsachvietnam. vn/d6/vi-vn/news/van-de-ky-thuat-nang-luong-gio-ngoaikhoi-6-183-6533 [last accessed on 2021 jun 26]. effiom, o.s., nwankwojike, b.n., abam, f.i. (2016), economic cost evaluation on the viability of offshore wind turbine farms in nigeria. energy reports, 2, 48-53. eia. (2013), levelized cost of electricity and levelized avoided cost of electricity methodology supplement. available from: https:// www.eia.gov/renewable/workshop/gencosts/pdf/methodology_ supplement.pdf [last accessed on 2021 jun 20]. haas, r., panzer, c., resch, g., ragwitz, m., reece, g., held, a. (2011), a historical review of promotion strategies for electricity from renewable energy sources in eu countries. renewable and sustainable energy reviews, 15(2), 1003-1034. ievn-institue of energy vietnam. (2020), the third draft vietnam national power development plan 8. hanoi: moit. irena. (2019), future of wind: deployment, investment, technology, grid integration and socio-economic aspects (a global energy transformation paper). abu dhabi: international renewable energy agency. lappalainen, j. (2019), economic potential of offshore wind energy in the gulf of bothnia. master thesis, aalto university, electrical engineering. li, c., mccausland, a., taylor, j., stephenson, m. (2021), vietnam’s future transition to offshore wind auctions, global wind energy council. available from: https://wwwgwec.net/wp-content/ uploads/2021/07/en-vietnams-future-transition-to-offshore-windauctions-final.pdf [last accessed on 2021 jun 10]. moit. (2014), circular 78/2014/tt-bct guidance on the implementation bui and nguyen: determining the offshore wind power potential in the mix-electric power of vietnam: the role of feed-in tariff policy international journal of energy economics and policy | vol 12 • issue 2 • 2022 19 of the corporate income tax. hanoi: the vietnamese priminister. nldc. (2021), operational of the national electricity system 2020. hanoi: nldc. phan, t., doan, b. (2020), proposal to reduce the fit for wind power: businesses propose to extend the current price. available from: https://www.baochinhphu.vn/doanh-nghiep/de-xuat-giam-giafit-dien-gio-dn-kien-nghi-keo-dai-gia-hien-tai/418355.vgp [last accessed on 2021 jun 27]. rickerson, w., laurent, c., jacobs, d., dietrich, c., hanley, c. (2012), feed-in tariffs as a policy instrument for promoting renewable energies and green economics in developing countries, united nations environment programme (unep). available from: https://www.unfccc.int/files/documentation/submissions_from_ parties/adp/application/pdf/unep_us___ws2.pdf [last accessed on 2021 jun 27]. ryan, w., karen, j., joachim, s., baker, e., hand, m., lantz, e., smith, a. (2016), expert elicitation survey on future wind energy costs. natural energy, 1(10), 16135. shin, y. (2012), analysis of economic feasibility of offshore wind power-focusing on china and south korea. available from: https:// www.eneken.ieej.or.jp/3rd_iaee_asia/pdf/paper/116p.pdf [last accessed on 2021 jun 11]. state bank of vietnam. (2021), weekly operational information of the state bank of vietnam. available from: https://www.sbv.gov.vn/ webcenter/portal/vi/menu/sm/tcbc/ttvhdnhtt?p=4&_afrloop [last accessed on 2021 jun 20]. stephenson, m. (2021), opinion: why vietnam shouldn’t rush into offshore wind auctions. available from: https://www.thinkrcg. com/why-vietnam-shouldnt-rush-into-offshore-wind-auctions [last accessed on 2021 jun 25]. the vietnamese prime minister. (2018), decision 39/2018/qd-ttg providing the mechanism to support the development of wind power projects in vietnam. hanoi: the vietnamese prime minister. tran, h.k., kitchlu, r., chu, b.t., leybourne, m.t., whittaker, s., knight, o., dutton, a.s.p. (2021), offshore wind development program: roadmap for vietnam. washington, dc: world bank group. tran, l.t., techato, k., jirakiattikul, s. (2019), the challenge of feed-intariff (fit) policies applied to the development of electricity from sustainable resources-lessons for vietnam. international energy journal, 19(4), 199-212. wb. (2019), going global: expanding offshore wind to emerging markets. washington dc: world bank group. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(1), 401-406. international journal of energy economics and policy | vol 12 • issue 1 • 2022 401 the optimization using electric ground support equipment in aviation industry mustika sari1,2*, wan mazlina wan mohamed1, siti ayu jalil1 1malaysia institute of transport, universiti teknologi mara, malaysia 40450 shah alam, selangor darul ehsan, malaysia, 2institute transportation and logistic trisakti, jakarta, indonesia. *email: mustika0017@gmail.com received: 13 august 2021 accepted: 22 december 2021 doi: https://doi.org/10.32479/ijeep.11711 abstract an airport is one of the country’s infrastructures that provides air transportation services. in providing its services, to ensure aircraft safety, airports must conform to a set of international technical operating standards and planned operating procedures. in addition, airports also have a social responsibility to prevent pollution and support eco green. therefore, this study aims to conduct a benefit cost analysis using electric ground support equipment in aviation industry, both for using e-gse using diesel and using e-gse using electricity. the method used in this research is the benefit cost ratio method. based on the research results, it shows that the use of e-gse using both diesel and electricity is feasible because it has an net present value (npv) value of more than 0. however, when compared with the assumption of 25 years of use, the use of e-gse using diesel is considered more profitable than using electricity. keywords: benefit cost analysis, electric ground support equipment jel classifications: p41, p28, p43 1. introduction airport operators are responsible for expanding their facilities and services in order to play a role in the aviation industry. among the responsibilities are terminal services, ground services facilities, and passenger baggage and cargo movement between the airfield and terminals. airport operators are also in responsible to manage the airport’s commercial facilities, ground transportation from and to the airport, parking infrastructure, surface access links, and other related factors outside the confines of an airport terminal (graham, 2018). airports are the source of emissions that have a negative impact on the environment, and these emissions are produced by activities both inside and outside the airport. as a result, living near airports may pose a significant risk to people’s health. airport operators are becoming more aware of how the construction, operation, maintenance, and other activities at airport facilities can contribute to the industry’s overall impacts on climate change (giuffre and grana, 2011). ground handling is a service provided by airlines that assists in the crusade of aircraft while on land by using a few tools to measure in motorized and non-motorized modes for the purposes of accuracy, safety, security, and cost-effectiveness. ground handling costs a lot of money to complete work for the necessary operational coordination with all parties involved with the movement of tools for land. such tools would require diesel fuel, which has been used by all ground handling vehicles, referred to as ground support equipment (gse). ground handling, which is frequently associated with the operation of ground support equipment in airports, plays a role in emission reduction efforts. efforts are currently being made by ground handling companies to plan for and gradually implement electric vehicles or renewable fuels (aerospace, 2012). the total scope of ground handling work includes nine standard service units: passenger handling, baggage handling, cargo and mail handling, aircraft handling and loading, load control, air side management and safety, aircraft movement control, this journal is licensed under a creative commons attribution 4.0 international license sari, et al.: the optimization using electric ground support equipment in aviation industry international journal of energy economics and policy | vol 12 • issue 1 • 2022402 standard ground handling agreement, and airport handling. gse requirements (international air transport association, 2014). gse research has yet to be as extensive as that of aircraft operations, fleets, and emissions. gse’s current data is regarded as untrustworthy, limited, and out of date. in order to adequately plan and maintain the increasing demands for excellent air quality service, the faa requires accurate gse data. air quality can only be improved if airports implement effective strategies to reduce surface emissions (airport cooporative research program, 2012a). the airside ground operation contributes significantly to emissions. taxiing is one of the most emission-intensive modes of transportation during departure (bubalo et al., 2017). the emission can dangered the human health (jaafar et al., 2018), such as increase vascular dementia (li et al., 2019), degradation of lung function and many health problem (suhaimi et al., 2020) the level of polluted engine exhaust emissions, unsafe air pollution (haps), and greenhouse gases (ghgs) in every piece of gse (with the exception of electric gse) is heavily dependent on the engine size, which is typically measured in brake horsepower (bhp), the type of fuel (diesel or gasoline), the engine’s on and run time, and load factors. the load factors are defined as the average energy demand ratio on the equipment required to reach the maximum (peak load) of the equipment (airport cooporative research program, 2012b). the air pollution mainly come form vehicles, and the concertation of no and co reduce significantly during covid-19 pandemic, when less vehicles are on the road (talib et al., 2021). the use of eco fuels by air transport companies is one of the indonesian government’s efforts to reduce air pollution. government regulations must provide for the provision and use of eco fuels to support renewable energy, as required by government regulation no. 26, 2008. the usage of gas as energy source can reduce the carbon emission (farabi et al., 2019). enforcement is also aimed at assisting air transport for aircraft on the ground, also known as ground handling. the government also should have roadmap on future energy, either renewable or non-renewable energy, such as the use of wind and water energy, biomass, biodiesel, biogas, and other sources (faizah and husaeni, 2018). reduced carbon emissions from air transportation and airport operations have been included in indonesia’s action plans through the implementation of renewable energy for airport facilities and the ongoing implementation of eco-airport programs. as a result, in 2017, dgca indonesia issued a dg decree establishing an emissions reduction program for airport operations. the incorporation of the degree requires airports in indonesia to report to the director general on a regular basis their carbon emissions, including both emissions production and reduction. the decree is aimed at measuring the effectiveness of eco-airport program implementation and monitoring the emissions reduction progress as stipulated in indonesian state action plans (indonesia team, 2018). furthermore, the apec annual meeting stated that the indonesian government has committed to mitigating climate change and reducing greenhouse gas emissions. presidential decree 71/2011 on the implementation of the greenhouse gas inventory, and the energy and transportation sectors contribute 0.056 percent (samad, 2013). while a green eco vehicle costs slightly more than a conventional car, the return on investment is immediate. fuel, insurance, and maintenance costs are drastically reduced, saving a significant amount of money in the long run. proper care and responsible driving are required when operating any type of vehicle, and eco vehicles are designed to have a minimal impact on the engine (kuttner, 2015). while a green eco vehicle costs slightly more than a conventional car, the return on investment is immediate. fuel, insurance, and maintenance costs are drastically reduced, saving a significant amount of money in the long run. proper care and responsible driving are required when operating any type of vehicle, and eco vehicles are designed to have a minimal impact on the engine. 2. methodology this study makes use of secondary data from a third party, specifically data from a ground handling company and an aviation ground support equipment company. the information includes the cost of electrical gse, diesel gse, and operation. cost benefit analyst in this research is applied to transportation investments, project scenario assumptions should be aware that these frequently have infinite lifetimes. energy 25 years, water and environment 30 years, railways 30 years, roads 25 years, ports and airports 25 years, telecommunications 15 years, industry 10 years, other services 15 years are typical project lifetimes for public investment projects (jones et al., 2014). this research using nett present value (npv). npv is the difference between the value of incoming cash flows and the value of cash outflows over a period of time. the feasibility can implement if the npv value is greater than zero. the formula to calculate is: ( ) 0 (1 ) n t t t benefit cost npv r= − = +∑ where: r = discount rate t = year n = analytic horizon (in year). 3. result and discussion cost benefit analysis (cba) has been widely accustomed support the decision-making process in transport. the consideration of non-economic variables into the analysis, such as noise, accidents, air pollution and so on, has been troublesome for the application of cba (tudela et al., 2006). sari, et al.: the optimization using electric ground support equipment in aviation industry international journal of energy economics and policy | vol 12 • issue 1 • 2022 403 cba is a formal process for evaluating a project that evolved from the economic constructs of consumer surplus and externality. it then moved into a formal regulated process based upon work by economists and government agencies and is now required by many entities for project approval, seeking the efficient allocation of resources. it is a decision making tool that is one of the most widely accepted and applied methods for project appraisal for large-scale infrastructure investments in the public sector because it provides many benefits including, a model of rationality, creating, evaluating and comparing alternatives including different scales for the alternatives, monetizing the costs and benefits and guiding decision makers (jones et al., 2014). when cba is applied to investments in transportation, project scenario assumptions should be aware that these often have infinite lifetimes (lee, 2002). typical project lifetimes for public investment projects are energy 25 years, water and environment 30 years, railways 30 years, roads 25 years, ports and airports 25 years, telecommunications 15 years, industry 10 years, other services 15 years (jones et al., 2014). table 1 describe the investment of ground support equipment by diesel fuel and electric fuel which electric fuel more expensive than diesel fuel. in calculating the investment feasibility with npv analysis several aspects are considered, namely income, expenses, net profit, discount rate, and the economic age of the product. the revenue used in this calculation represents the total operating income of ground handling company in various segments. the ground handling and ahan segments contributed the highest to ground handling company operating income, which was around 76.9%. meanwhile, the cargo warehousing and non-ground handling segments contributed 17.9% and 5.2% respectively. therefore, investment in the gse is indeed needed since this segment gives the highest income earned. refers to an annual report published in 2013-2017, the financial statements show that yearly income increases by around 10% with the result that company revenue is projected to increase every year by 10%. the company expenditure on operational activities will also be estimated to increase by 10% annually. projected increases in income and spending are also made because of the possibility of inflation every year (table 2). in the company’s profit and loss projection, revenue will be reduced by total expenses to find out the gross profit. after that, gross profit will also be subject to income tax of the business entity to find the net profit obtained, in accordance with government regulations that business income tax above 100 million rupiahs is 25% of the total taxable income (gapura angkasa, 2017). after calculating the profit and loss projection, it can be seen that the cash flow is mainly to see the comparison of the total cash in and cash out during the economic life of the tool for 20-25 years. this cash flow will facilitate us in calculating the parameters of investment feasibility. this analysis aims to compare the feasibility of investment for gse products that use diesel fuel and electricity. each product is assumed can be uses for 20 until 25 years with a discount rate of 3%. the results of the analysis can be seen as follows. from the table 3 above can be known there are no significant differences from investing in gse product that uses diesel fuel either electricity. there is no npv value below 0, so investing in a product that uses diesel fuel or electricity is feasible. investing products with useful life 25 years is the best choice since there is a huge gap between npv value that assumed uses for 25 years and 20 years. the gse product that uses diesel fuel has the highest npv score than others. investing in a gse product that uses diesel fuel for 25 years can be more profitable than npv for a product that uses electricity. 3.1. the feasibility in using diesel fuel for 25 and 20 years in the use of e-gse using diesel from 2017 to 2041, the prediction of 25 years of investing in diesel for profit and loss still has a margin of around 10% annually. in 2041, the net profit will reach usd 32,259,701. in addition, the cash flow of diesel use for 25 years every year from 2017 to 2041 the expenditure will increase by 10% annually table 1: investment of ground support equipment (gse) in us dollars no name of gse diesel fuel electric 1 pax boarding stair 26,000 40,285 2 belt conveyor loader 25,000 40,000 3 baggage towing tractor 32,500 42,000 4 high lift loader 23,000 37,000 5 forklift 45,000 59,000 6 push back/att wide body 116,000 130,000 7 ground power unit 180 kva 32,000 44,000 total invest 299,500 392,285 sources: ground handling company table 2: the income projection of ground handling company 2017 to 2041 no year income/ year (usd) no year income/ year (usd) 1 2017 120,133,309 14 2030 414,732,763 2 2018 132,146,639 15 2031 456,206,040 3 2019 145,361,303 16 2032 501,826,643 4 2020 159,897,434 17 2033 552,009,308 5 2021 175,887,177 18 2034 607,210,239 6 2022 193,475,895 19 2035 667,931,262 7 2023 212,823,484 20 2036 734,724,389 8 2024 234,105,833 21 2037 808,196,828 9 2025 257,516,416 22 2038 889,016,510 10 2026 283,268,058 23 2039 977,918,161 11 2027 311,594,863 24 2040 1,075,709,977 12 2028 342,754,350 25 2041 1,183,280,975 13 2029 377,029,785 sources : ground handling company annual report, 2017 ( process by the author) table 3: the projection feasibility cost in using diesel versus electricity (usd) the gse product uses diesel fuel the gse product uses electricity 25 years 20 years 25 years 20 years 196,296,805 128,476,615 196,268,647 128,452,391 sari, et al.: the optimization using electric ground support equipment in aviation industry international journal of energy economics and policy | vol 12 • issue 1 • 2022404 (table 4). in 2041, the new cash flows will cost usd 32,271,681. the npv value for investment in gse products using diesel fuel assumes a useful life of 25 years (gapura angkasa, 2017). npv: total pvtotal investment : usd 196,596,305 – usd 299,500 : usd 196,296,805 meanwhile, for the prediction of using e-gse using diesel with an assumption of 20 years from 2017 to 2036, investing in diesel for profit and loss still has a margin of around 10% annually. in 2036, the net profit will reach usd 20,030,736 (table 5). and cash flow from the use of diesel for 20 years every year from 2017 to 2041 the expenditure will increase by 10% every year. by 2036, the new cash flows will cost usd 20,045,711 (gapura angkasa, 2017). npv: total pvtotal investment : usd 128,767,115 – usd 299,500 : usd 128,467,615 meanwhile, for the prediction of using e-gse using electricity with an assumption of 20 years from 2017 to 2036, investing in diesel for profit and loss still has a margin of around 10% annually. in 2036, the net profit will reach usd 20,030,736. and cash flow from the use of electricity for 20 years every year from 2017 to 2041 the expenditure will increase by 10% every year. by 2036, the new cash flows will cost usd 20,050,351. 3.2. the feasibility in using electric fuel for 25 and 20 years the use of e-gse uses electric fuel from 2017 to 2041, the prediction that in 25 years investing in electric fuel for profit and loss still has a margin of around 10% annually. in 2041, net profit will reach usd 32,259,701 (gapura angkasa, 2017). meanwhile, cash flow from electricity use for 25 years each year from 2017 to 2041 expenditure will increase 10% annually. by 2041, the net cash flow will cost usd 32,275,393 (tables 6 and 7). npv: totalpvtotal investment : usd 196,660,932 – us d 392,285 : usd 196,268,647 npv: total pvtotal investment : usd 128,844,676 – usd 392,285 : usd 128,452,391 there is some research literature on transportation using the bca method. this method is used to predict time savings, the impact of the number of accidents, and reduction of noise disturbances. cba is also used for transportation policy, which deals with environmental consequences such as co2 emissions. in transportation studies using cba, important issues discussed are time savings, increased traffic safety, other advantages of improving railroads. in several countries since 1981 the discount rate has decreased from 8% to 3.5% in 2012. it is quite difficult to select a discount value according to the project because it will be used as a parameter to calculate the present and future net value (andersson et al., 2018). 4. discussion from the finding, investing the electric ground support equipment in the ground handling company in indonesia is feasible, even though investing a gse product that uses diesel fuel for 25 years can be more profitable than uses electricity. this is not very surprising because indonesia just began with the electricity vehicle and somehow less power in electricity. also, indonesia does not have a nuclear power. but with the support from the indonesia government, indonesia have willingness to start built electric vehicle industry and does not depend on fossil fuel. indonesia president announced with new regulation number 55/2019 to support the electric vehicle. indonesia is committed to encouraging the acceleration of the battery-based motor vehicle program to support the realization and realization of reducing greenhouse gas emissions, increasing energy efficiency, energy security, and energy conservation in the transportation sector and realizing clean energy, clean air and environmentally friendly, and encouraging acceleration. indonesia open up new and exciting business opportunities from the upstream to downstream supply chain that is needed to build the ev industry forward. table 4: net present value using diesel fuel in 25 years year interest pv year interest pv npv 1 0.9709 4,251,164 15 0.6419 7,991,328 196,296,805 2 0.9426 3,407,201 16 0.6232 8,533,629 3 0.9151 3,637,481 17 0.605 9,112,128 4 0.8885 3,883,857 18 0.5874 9,731,049 5 0.8626 4,146,673 19 0.5703 10,391,859 6 0.8375 4,427,610 20 0.5537 11,097,652 7 0.8131 4,727,502 21 0.5375 11,849,612 8 0.7894 5,047,731 22 0.5219 12,655,642 9 0.7664 5,389,808 23 0.5067 13,515,153 10 0.7441 5,755,387 24 0.4919 14,431,845 11 0.7224 6,145,433 25 0.4776 15,412,955 12 0.7014 6,562,625 13 0.681 7,008,113 14 0.6611 7,482,864 total pv 196,596,305 sari, et al.: the optimization using electric ground support equipment in aviation industry international journal of energy economics and policy | vol 12 • issue 1 • 2022 405 one of the airports that has become a role model for environmental sustainability is an airport in sweden and the scandinavian region. swedish airports strive to minimize harmful emissions and slow down the global warming process. swedish airports have the goal of achieving fossil oil free air transportation by 2045. apart from airlines, the emission contributor in the aviation industry is gse which is used to handle and serve aircraft. gse operators are working to switch to equipment that reduces carbon. gse investment is made with a combination of electricity, biogas and fossil fuel free (airside international, 2019). meanwhile, investment in vehicles and equipment involves cooperation with several equipment providers and providing incentives for ground operators to use environmentally friendly vehicles. another airport in europe that is practicing zero emission in ground operations is stutgart airport, germany. this airport prioritizes vehicles that consume the most fossil fuels and occupy the largest emissions to be diverted to electric. the equipment are passenger bus, luggage tractor, and ground power unit. meanwhile, in asia, there are singapore and hong kong which have standards in supporting reducing emissions due to the use of gse. singapore, through the changi airport group, collaborates with ground handling to reduce emissions at the airport by diverting the use of a fossil baggage tracktor to an electric baggage tractor. currently, there are about 80 gse machines operating at changi airport that use electric power. since 2017 changi has started using electric gse, and the result is that changi can reduce 1000 tons of carbon dioxide emissions. table 7: npv for investing in the gse product uses electricity (20 years) years interest pv years interest pv npv 1 0.9709 4,258,576.48 12 0.7014 6,567,980.16 128,452,391 2 0.9426 3,414,397.19 13 0.681 7,013,312.03 3 0.9151 3,644,466.88 14 0.6611 7,487,911.29 4 0.8885 3,890,640.30 15 0.6419 7,996,228.91 5 0.8626 4,153,257.94 16 0.6232 8,538,386.37 6 0.8375 4,434,004.04 17 0.605 9,116,746.79 7 0.8131 4,733,709.71 18 0.5874 9,735,533.43 8 0.7894 5,053,757.87 19 0.5703 10,396,212.33 9 0.7664 5,395,659.21 20 0.5537 11,101,879.14 10 0.7441 5,761,067.93 11 0.7224 6,150,948.37 total pv 128,844,676 table 5: net present value using diesel fuel in 20 years years interest pv years interest pv npv 1 0.9709 4,254,072 11 0.7224 6,147,597 128,467,615 2 0.9426 3,410,024 12 0.7014 6,564,726 3 0.9151 3,640,222 13 0.681 7,010,153 4 0.8885 3,886,518 14 0.6611 7,484,844 5 0.8626 4,149,256 15 0.6419 7,993,251 6 0.8375 4,430,119 16 0.6232 8,535,495 7 0.8131 4,729,938 17 0.605 9,113,940 8 0.7894 5,050,096 18 0.5874 9,732,808 9 0.7664 5,392,104 19 0.5703 10,385,026 10 0.7441 5,757,616 20 0.5537 11,099,310 total pv 128,767,115 table 6: net present value in investing electric fuel for 25 years years interest pv years interest pv npv 1 0.9709 4,254,768 14 0.6611 7,485,318 196,268,647 2 0.9426 3,410,700 15 0.6419 7,993,711 3 0.9151 3,640,877 16 0.6232 8,535,942 4 0.8885 3,887,155 17 0.605 9,114,373 5 0.8626 4,149,874 18 0.5874 9,733,229 6 0.8375 4,430,719 19 0.5703 10,393,975 7 0.8131 4,730,520 20 0.5537 11,099,707 8 0.7894 5,050,661 21 0.5375 11,851,607 9 0.7664 5,392,653 22 0.5219 12,657,579 10 0.7441 5,758,149 23 0.5067 13,517,034 11 0.7224 6,148,115 24 0.4919 14,433,670 12 0.7014 6,565,229 25 0.4776 15,414,728 13 0.681 7,010,641 total pv 196,660,932 sari, et al.: the optimization using electric ground support equipment in aviation industry international journal of energy economics and policy | vol 12 • issue 1 • 2022406 an example of how gse can reduce carbon is the ground power unit (gpu) tool to reduce about 90% co2 and 95% nox. currently, the new eco-airport concept has been developed in five airports in indonesia, namely soekarno hatta (jakarta), juanda (surabaya), ngurah rai (denpasar), hang nadim (batam), dan sultan mahmud badarudin ii (palembang). 5. conclusion the aim of this research is to conduct the feasibility study of the usage e gse for ground support equipment in aviation industry using benefit cost analysis. based on the results of the study, it shows that the use of e-gse using both diesel and electricity is feasible because it has an npv value of more than 0, so investing in products that use diesel or electricity is possible. investments in products with a useful life of 25 years are the best choice because there is a large gap between the npv values that are assumed to be used for 25 years and 20 years. gse products that use diesel have the highest npv value compared to other products. investing in gse products that use diesel for 25 years can be more profitable than npv for products that use electricity. refference aerospace. (2012), reducing the environmental impacts of ground operations and departing aircraft: an industry code of practice. 1st ed. united states: practice working group. available from: https:// www.dft.gov.uk airport cooporative research program. (2012a), airport ground support equipment (gse): emission reduction strategies, inventory, and tutorial. washington, dc, united states: the national academies press. airport cooporative research program. (2012b), airport ground support equipment (gse): emission reduction strategies, inventory, and tutorial. washington, dc, united states: the national academies press. airside international. (2019), encouraging the transition to green gse. available from: https://www.airsideint.com/issue-article/ encouraging-the-transition-to-green-gse andersson, h., hultkrantz, l., lindberg, g., nilsson, j.e. (2018), economic analysis and investment priorities in sweden’s transport sector. journal of benefit-cost analysis, 9(1), 120-146. bubalo, b., schulte, f., voß, s. (2017), reducing airport emissions with coordinated pushback processes : a case study. in: computational logistics. cham: springer. p572-586. faizah, s.i., husaeni, u. (2018), development of consumption and supplying energy in indonesia’s economy. international journal of energy economics and policy, 8(6), 313-321. farabi, a., abdullah, a., setianto, r. (2019), energy consumption, carbon emissions and economic growth in indonesia and malaysia. international journal of energy economics and policy, 9(3), 338-345. gapura angkasa. (2017), annual report gapura angkasa company. available from: https://www.gapura.id giuffre, o., grana, a. (2011), managing greenhouse gas emissions for airport inventories: an overview. journal of sustainable development, 4(5), 67-81. graham, a. (2018), managing the airports, an international perspective. 5th ed. oxford, united kingdom: butterworth-heinemann. indonesia team. (2018), airport emissions reduction actions in indonesia through the establishment of eco airport council and emissions inventory. in: aviation and environment (dgca 55/ip/7/10dgca). international air transport association. (2014), airport handling manual. 34th ed. montreal, canada: iata. jaafar, h., razi, n.a., azzeri, a., isahak, m., dahlui, m. (2018), a systematic review of financial implications of air pollution on health in asia. environmental science and pollution research, 25(30), 30009-30020. jones, h., moura, f., domingos, t. (2014), transport infrastructure project evaluation using cost-benefit analysis. procedia-social and behavioral sciences, 111, 400-409. kuttner, d. (2015), benefits of driving eco green cars, blue & green tomorrow. available from: https://www.blueandgreentomorrow.com lee, d.b. (2002). fundamentals of life-cycle cost analysis. transportation research record, 1812(1), 203-210. li, c.y., li, c.h., martini, s., hou, w.h. (2019), association between air pollution and risk of vascular dementia: a multipollutant analysis in taiwan. environment international, 133, 105233. samad, a. (2013), indonesia green aviation initiatives for sustainable development air transportation a38-wp/164.montreal, canada: icao. suhaimi, n.f., jalaludin, j., mohd juhari, m.a. (2020). the impact of traffic-related air pollution on lung function status and respiratory symptoms among children in klang valley, malaysia. international journal of environmental health research, 31(8), 1-13. talib, m., dominick, d., syamimi, n., limi, s., asma, a., mohtar, a., othman, m. (2021), the concentration of major air pollutants during the movement control order due to the covid-19 pandemic in the klang valley, malaysia. sustainable cities and society, 66, 102660. tudela, a., akiki, n., cisternas, r. (2006), comparing the output of cost benefit and multi-criteria analysis: an application to urban transport investment. transportation research part a: policy and practice, 40(5), 414-423. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(2), 497-501. international journal of energy economics and policy | vol 12 • issue 2 • 2022 497 energy demand modeling for the eastern economic corridor of thailand: a case study of rayong province chanidaporn lunsamrong, atit tippichai* department of architecture and planning, faculty of architecture, art, and design, king mongkut’s institute of technology ladkrabang, bangkok, thailand. *email: atit.ti@kmitl.ac.th received: 03 january 2022 accepted: 13 march 2022 doi: https://doi.org/10.32479/ijeep.12884 abstract this paper assesses long-term energy consumption and greenhouse gas (ghg) emissions in rayong province which is one of the three provinces in the eastern economic corridor (eec) of thailand. leap (the low emissions analysis platform) is used to project final energy demand for each economic sector by using the 2019 data as a base year. in the model, we defined the energy consumption into two scenarios; a business-as-usual (bau) scenario and a low carbon scenario (lcs), to see different energy demand and co2 emissions up to the year 2050. there are different assumptions between bau and lcs in each sector such as energy efficiency improvement, shift to modern energy, the share of high energy-efficient vehicles, etc. in the bau scenario, the final energy consumption needed by rayong province will increase with an average annual growth rate (aagr) of 3.49%, while only 1.52% for the lcs. co2 emissions in the lcs will be reduced by 41.7% by 2050 when compared with the bau scenario. most interestingly, even though energy demand in rayong province will be increasing up to 2050, co2 emissions will peak about 2035 and then reduce. the industry and transport sectors are the most final energy consumption and the highest co2 emissions. this is because eec is driven by a production-based economy. the solution for this is to transform to alternative energies sourcing, shift all productions to sustainable ones, restructure the industrial estate to become the eco-industrial and ghg emissions management, which will also result in obvious carbon reduction. this kind of information will be beneficial to energy demand conservation and ghg emission mitigation at the provincial level which will depend on the energy policies initiated and implemented in the future. keywords: energy demand modeling, greenhouse gas, co2 emissions, scenario analysis, low carbon city, thailand jel classifications: o22, q47, q54 1. introduction rayong is one of the three provinces in the eastern economic corridor (eec) project which is a highly important economic area of thailand. this will be a huge source of employment with the most industrial estates in thailand. with rapid industrial and infrastructure development, the energy demand is constantly increasing. if there is no energy policy, it can lead to an energy shortage crisis and other environmental problems such as air pollution and greenhouse gas emissions. in addition, energy imports are costly, thus making development inefficient. it could result in disruption to economic growth in the future. in the past, energy was not planned at the provincial level. however, in thailand, energy policy and planning have been centralized to government agencies, the local governments had mainly functioned as implementing agencies of national policies and programs, which makes planning inefficient. therefore, anticipating energy demand and finding ways to reduce energy consumption at the provincial level is an option to cope with future challenges. it can be used to plan energy appropriately and meet the potential of the province. energy modeling is commonly used to assess predictions of future energy needs. we compiled and summarized the research related to energy consumption projections as follows. wangjiraniran et al. this journal is licensed under a creative commons attribution 4.0 international license lunsamrong and tippichai: energy demand modeling for the eastern economic corridor of thailand: a case study of rayong province international journal of energy economics and policy | vol 12 • issue 2 • 2022498 (2017) conducted a study to analyze changes in the energy sector in thailand. the results of this study showed that the high penetration of disruptive technologies will result in reducing greenhouse gas (ghg) emissions by 8.9% compared with thailand’s integrated energy blueprint (tieb) scenario. electric vehicle (ev) is one of the disruptive technologies which will replace the use of oil in the transportation sector in thailand. chaichaloempreecha et al. (2019) conducted a study to evaluate the long-term energy demand in the building sector and the industrial sector during 2005–2050 through the perspective of ghg mitigation potential by end-use approach by using the leap model. policies considered in this study include the energy efficiency plan and the alternative energy development plan of thailand. a review of the literature and models involved in the study found that the leap model is a favorite model for energy planning which can be used to evaluate policies and measures (wangjiraniran et al., 2017; chaichaloempreecha et al., 2019; hu et al., 2019; misila et al., 2020; dioha et al., 2021; chen et al., 2021; gebremeskel et al., 2021; kehbila et al., 2021). as a result of this study, the relevant authorities can apply the information to plan the implementation of energy efficiency improvements for future needs. in addition to creating energy security, it can also help reduce environmental problems effectively. 2. materials and methods 2.1. study area rayong is a province located in the eastern part of thailand with an area of 3,552 square kilometers and a total population of 724,979 people. rayong is a province with the highest gross provincial product (gpp) in thailand at 993,977 million baht and the province with the highest gross provincial product per capita (gpp per capita) in thailand, at 988,748 baht per year (office of the national economic and social development council, 2019). 2.2. data collection data both top-down and bottom-up information was collected according to 5 economic sectors, i.e., household sector, building sector, industrial sector, agricultural and another sector, and transport sector. the collected data used in this study were obtained from previous studies and various official data sources in thailand during 2010–2019. the collected data for each sector are as follows. • household sector: urban and rural population, number of households, and end-use energy consumption per household • building sector: sectoral value-added, and final energy consumption by fuel type • industrial sector: sectoral value-added, and final energy consumption by fuel type • agricultural and other sectors: sectoral value-added, and final energy consumption by fuel type • transportation sector: number of vehicle registration by vehicle technology and fuel type, number of vehicle sales by vehicle technology and fuel type, fuel economy, vehicle kilometer-traveled, vehicle age distribution, etc. 2.3. leap model leap is developed by the stockholm environment institute which is a software tool widely used for energy policy analysis and development of climate change mitigation assessment. leap is an integrated, scenario-based modeling tool that can account for both energy sector and non-energy sector greenhouse gas emission sources and sinks (hu et al., 2019). in general, leap calculates energy demand using four different methods: final energy demand, useful energy demand, stock, and transport analysis (dioha et al., 2021). energy demand can be estimated in leap using equations (1) (4). for a detailed description of the nigerian leap model, see the work of emodi et al. (2017). in addition, emission factors (ef) are required by specific types of energy resources or fuel to analyze the environmental impacts used in equation (5). the structure of the leap model in this study is shown in figure 1 and the structure of the sectoral modules in the leap model is shown in figures 2 and 3. final energy analysis= activity level × energy intensity (1) useful energy analysis = activity level × (useful energy intensity/ efficiency) (2) stock analysis = stock and x device intensity (3) transport analysis = stock (vehicle miles/fuel economy) (4) ghg emissions = activity data: ad × emission factor: ef (5) 2.4. scenarios and assumptions the energy demand forecasting in this study is divided into two scenarios: (1) business as usual (bau) and (2) low carbon scenario (lcs) which are defined as follows. • business as usual (bau) scenario: no change in economic structure, it is a normal energy forecast based on historical figure 1: the structure of the leap model in this study lunsamrong and tippichai: energy demand modeling for the eastern economic corridor of thailand: a case study of rayong province international journal of energy economics and policy | vol 12 • issue 2 • 2022 499 growth data. with the key driver of enhancement of economic competitiveness among provinces under the current policy plans • low carbon scenario (lcs): transformation of economic structure towards quality and sustainable growth which aims at reducing the impact of ghg-emission and environmentally friendly, due to the energy development policy and technological change to meet the climate goal. specific assumptions of each economic sector for both scenarios are shown in table 1. 3. results and discussion 3.1. final energy consumption and ghg emissions in the bau scenario in the business-as-usual (bau) scenario, during 2019–2050, results show that total final energy consumption increases from 2,109 to in 2019 to 5,915 ktoe in 2050 and accounted for an average annual growth rate of 3.49%. in 2050, the industrial sector will be the largest energy-consuming sector and accounted for 73.21% of total energy consumption. in addition, the transport, household, building agricultural and other sectors are accounted for 14.57%, 6.69%, 4.57%, and 0.95% of total energy consumption, respectively (figure 4). the total final energy consumption by fuel type in the business-asusual (bau) scenario in 2050, the highest proportion of electricity consumption at 53.01% followed by biomass, diesel, and lpg are accounted for 24.30%, 8.54%, and 6.80%, respectively (figure 5). in the future, rayong province shall promote economic zones and industrial zones; consequently, rayong province has a large potential to increase energy demand, especially for electricity. when considering the non-electricity energy consumption in bau, it found that the share of non-electricity energy consumption in 2050 will change slightly from 2019 because it is not affected by any future projects or measures. in addition, during 2019-2050, co2 emission and accounted for an annual average growth rate (aagr) of 3.20%, increases from 1,949.0 ktco2eq in 2019 to 3,756.9 ktco2eq in 2050. more than half of co2 emissions will be dominated by the transport sector. the transport sector accounts for 60% of total co2 emissions from fuel combustion, followed by the industrial, building, agricultural and other, and household sectors at 22.18%, 11.21%, 4.01%, and 2.73%, respectively (figure 6). co2 emissions will increase from 26.76 ktco2eq in 2019 to 38.45 ktco2eq in 2050 in the rural area of the household sector (increased by 1.33% annually). similarly, co2 emissions in an urban area will increase with an aagr of 5.64%. moreover, lpg demand for cooking in the urban area will be significantly higher than that in greater rural areas. therefore, co2 emission will be 64.24 ktco2eq in the urban area or 62.6% of total co2 emission in the household sector in 2050. this is the reason why the household sector in an urban area has the highest co2 emission. 3.2. final energy consumption and ghg emissions in the low carbon scenario in the low carbon scenario, due to the vigorous efforts paid toward removing fossil fuels from the rayong province (figure 4), during 2019–2050, the total final energy consumption slightly increases with an aagr of 1.52%, from 2,077 to 2019 to 3,256 ktoe in 2050. the industrial sector still is the largest energy-consuming sector as accounted for 71.1% of total energy consumption. in addition, the transport, household, building agricultural and other figure 2: the structure of the household, building, and industry modules in the leap model figure 3: the structure of the transport module in the leap model lunsamrong and tippichai: energy demand modeling for the eastern economic corridor of thailand: a case study of rayong province international journal of energy economics and policy | vol 12 • issue 2 • 2022500 sectors are accounted for 17.33%, 6.21%, 4.44%, and 0.92% of total energy consumption, respectively. in the lcs, the advanced technologies will have an impact on the non-electricity energy demand, as the result, the proportion of nonelectricity energy consumption in 2050 will change significantly from 2019, especially fossil fuels, while the proportion of alternative energy and electricity consumption will increase. in 2050, total co2 emission will be 2,190.2 ktco2eq with an aagr of 1.31% per year. in addition, our analysis showed that co2 emission in the lcs will be reduced by 1,566.7 ktco2eq in 2050 when compared to the bau scenario (figure 6) or reduced by 41.7%, by 2050 when compared with the bau scenario, and the transport sector contributes more than half (about 56%) of total co2 emission reductions from the rayong province. figure 4: final energy demand by economic sector in rayong province; (a) bau; (b) lcs ba figure 5: final energy demand by fuel in rayong province; (a) bau; (b) lcs ba figure 6: energy-related co2 emissions by sector in rayong province; (a) bau; (b) lcs ba table 1: assumptions of each economic sector by scenario economic sector key driving force business-as-usual scenario low carbon scenario household urbanization, shifting from traditional fuel to lpg energy efficiency improvement of appliances, shifting from traditional fuel to lpg, electricity, and biogas building growth of valueadded, building energy code utilization of photovoltaic rooftop towards net-zero energy buildings industry driven by eec and productionbased economy factory energy management, smart factories transport vehicle ownership, population, and income public transport promotion, penetration of electric vehicles, fuel economy improvement agricultural and other growth of valueadded productivity and technological improvement, smart framing lunsamrong and tippichai: energy demand modeling for the eastern economic corridor of thailand: a case study of rayong province international journal of energy economics and policy | vol 12 • issue 2 • 2022 501 moreover, the entry of electric vehicles and fuel economy improvement can reduce demands for petroleum products, particularly gasoline and diesel. although the increase of evs on the road will lead to higher demands for electricity, it will reduce co2 emissions in the transport sector. co2 emission in the transport sector in 2019 were about 1,477 ktco2eq and will increase to 2,248 ktco2eq in 2050. co2 emission will reduce by 878.9 ktco2eq in 2050 compared to the co2 emission level of the transport sector in the bau scenario (figure 6). as anticipated, the low carbon scenario proves to be the case with the largest co2 emission potential. 4. conclusion the results of the low emissions analysis platform (leap) can be used for inputting data, analyzing energy consumption, forecasting future energy, and assessing greenhouse gas emissions consumption to set appropriate energy measures correctly. it can be used to plan energy appropriately and meet the potential of the province. furthermore, the quality of the scenario depends on the quality of the data and the analytical process of the user. this paper defined two scenarios. the results of the businessas-usual (bau) scenario suggest a trend that it needs energy for all kinds of fuel. this is due to people lifestyles is changing gradually by income and quality of life rises. environmental damages are increasingly becoming an issue. in the low carbon scenario (lcs), the total final energy consumption will lower energy demand due to economic restructuring and intense energy efficiency push, moving toward a high value and low energyintensive sector. given the overall energy use within the various sectors in rayong, the industrial and transportation sectors are the most final energy consumption and the highest co2 emissions. the solution for this is to transform to alternative energies sources, e.g., clean electricity. the shifting of all production to the sustainable ones, by the successful restructuring of the industrial estate to become the eco-industrial and ghg emission management, will also result in obvious carbon reduction. the prospects of a sustainable urban energy system will depend on the energy policies initiated and implemented in the future. 5. acknowledgments the authors would like to thank the ministry of energy, thailand that supporting the statistical data of energy consumption of rayong province in this study. references chaichaloempreecha, a., chunark, p., limmeechokchai, b. (2019), assessment of thailand’s energy policy on co2 emissions: implication of national energy plans to achieve ndc target. international energy journal, 19, 47-60. chen, s., liu, y., lin, j. shi, x., jiang, k., zhao, g. (2021), coordinated reduction of co2 emissions and environmental impacts with integrated city-level leap and lca method: a case study of jinan, china, advances in climate change research, 12(6), 848-857. dioha, m.o., kumar, a., ewim, d.r.e., emodi, n.v. (2021), alternative scenarios for low-carbon transport in nigeria: a longrange energy alternatives planning system model application. in: chaiechi, t, editor. economic effects of natural disasters: theoretical foundations, methods, and tools. ch. 30. cambridge, massachusetts: academic press. emodi, n.v., emodi, c.c., murthy, g.p., emodi, a.s.s. (2017), energy policy for low carbon development in nigeria: a leap model application. renewable and sustainable energy reviews, 68(1), 247-261. gebremeskel, d.h., ahlgren, e.o., beyene, g.b. (2021), long-term evolution of energy and electricity demand forecasting: the case of ethiopia, energy strategy reviews, 36, 100671. hu, g., ma, x., ji, j. (2019), scenarios and policies for sustainable urban energy development based on leap model a case study of a postindustrial city: shenzhen china. applied energy, 238, 876-886. kehbila, a.g., masumbuko, r.k., ogeya, m., osano, p. (2021), assessing transition pathways to low-carbon electricity generation in kenya: a hybrid approach using backcasting, socio-technical scenarios and energy system modelling, renewable and sustainable energy transition, 1, 100004. misila, p., winyuchakrit, p., limmeechokchai, b. (2020), thailand’s longterm ghg emission reduction in 2050: the achievement of renewable energy and energy efficiency beyond the ndc. heliyon, 6, e05720. office of the national economic and social development council. (2019), gross regional and provincial product chain volume measure. available from: https://www.nesdc.go.th/main.php?filename=gross_ regional [last accessed on 2021 jul 30]. wangjiraniran, w., pongthanaisawan, j., junlakarn, s., phadungsri, d. (2017), scenario analysis of disruptive technology penetration on the energy system in thailand. energy procedia, 142, 2661-2668. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 4 • 2021 69 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(4), 69-74. energy absorption, co2 emissions and economic growth sustainability in nigeria cordelia onyinyechi omodero*, uwuigbe uwalomwa department of accounting, college of management and social sciences, covenant university ota, ogun state, nigeria. *email: onyinyechi.omodero@covenantuniversity.edu.ng received: 05 january 2021 accepted: 20 april 2021 doi: https://doi.org/10.32479/ijeep.11055 abstract economic growth sustainability and environmental preservation have become a topical issue. this study emanates from the need to assess the starring role of energy ingestion in guaranteeing sustainable economic progression in nigeria. the study investigates the influence of energy consumption and carbon dioxide emission on the economic growth of nigeria from 2008 to 2019. in this study, we employ the multiple regression techniques to assess the impact of electricity, co2, primary energy and total labour force on gdp. various indicative checks show that the model is appropriate and errorfree. out of the four energy sources examined, electricity is found inconsequential in affecting the economic growth of nigeria. the co2 emission is positively significant, implying that the economy is growing with a high level of pollution in the environment. the primary energy consumption put forth a substantial harmful effect on economic progress, while the total labour force has a strong significant affirmative impression on fiscal progression. the study suggests the use of renewable energy to preserve the environment and sustain economic growth in the country. keywords: energy consumption, co2, electricity, primary energy, labour force, sustainable economic growth jel classifications: j82, l71, l72, l94, q01, q43 1. introduction energy occupies a very important space in the growth of a nation’s economy. power is the primary input absorbed in all stages of production and manufacturing processes. the manufacturing sector of every country cannot function effectively without energy availability. the absorption of energy refers to the entire usage of power to perform an activity or produce goods and services (nguyen et al., 2020). energy consumption in african countries like nigeria is very high and comprises primary energy, electricity and human energy. the energy sector in nigeria is very vital as the economy cannot thrive without sufficient and regular power supply, especially electricity. in nigeria, electricity is in high demand and critical to the operations of all economic sectors. the fact is that the energy sources in nigeria are non-renewable and challenging to sustain (onabote et al., 2020). the bigger the energy ingestion, the more the carbon (co2) discharge emanating from absorption of relic energy (oil and gas). fossil fuel creates virtually 75% of nigeria’s energy intake because rechargeable energy is still very insignificant to meet the increasing demand for power at the moment. the pertinence of energy policies and regulation is now very crucial. the desire for an untainted and dependable source of energy to enhance living conditions in the country is passionately on the increase. the clamour to preserve the environment and reduce carbon (co2) emissions causing global warming and depletion of the ozone layer, has been a topical issue. over the years, environmental protection and sustainability have been a secondary concern among nigerians due to inadequate supply of electricity for private sector operations. the public resort to any form of energy they can afford at all cost. the use of generators becomes very rampant and unabated. the worst scenario is the crude manner of refining oil to meet the growing local demands this journal is licensed under a creative commons attribution 4.0 international license omodero and uwalomwa: energy absorption, co2 emissions and economic growth sustainability in nigeria international journal of energy economics and policy | vol 11 • issue 4 • 202170 for energy. the practice was more visible in the niger delta states of nigeria, and it even got to a point where a nigerian city known as port harcourt city in rivers state was covered with black soot (giles, 2018). the situation resulted in the loss of lives, abandonment of surrounding towns and communities due to hazards and continuous fire outbreaks. the intensive burning of fossil fuels in nigeria is the product of unstable supply of electricity that could have served as the best source of energy in the country (chindo et al., 2015). however, the importance of energy in nigeria cannot be relegated to the background. nigeria has a high population density and is also a high intensive energy consumption country. all manufacturing activities and production processes hinge on energy as a significant material input. due to the high energy demand, scholars like (okoye et al., 2020) advocate that, the right policies to encourage local refining of oil in nigeria could be profitable. they would boost a sufficient supply of energy at an affordable rate. although power is required to operate factory machines, it is also important to note that human power (physically and mentally) is necessary to augment the other forms of energy. in this study, we considered the total labour force in the country as the human energy in addition to other forms of energy used in nigeria. it is worthy to note that out of 200,964,000 million (cbn, 2019) people in nigeria, the total number of the working group is 62,447,230 million (world development indicators, 2020). this information goes further to stress the need for sufficient energy supply in the country, human and otherwise. as a unique part of the millennium expansion objectives, job creation increases the labour force, decreases the rate of unemployment and alleviates the degree of insufficiency in the state (omodero, 2019). the concept that sufficient energy availability is vital in boosting the economic growth of a nation is without a doubt. 2. literature review 2.1. explanation of notions 2.1.1. renewable energy rechargeable power is sustainable energy derived from sources that restock themselves naturally without exhaustion in the earth (owusu and asumadu-sarkodie, 2016). a maintainable power is referred to as a forceful synchronization, flanked by the unbiased obtainability of vitality concentrated merchandises and facilities to all persons, as well as safeguarding of the globe for upcoming generations (tester, 2005). the restorable vivacity is clean and sustainable. its natural supply helps to curtail carbon contaminations emanating from traditional sources of energy. refreshable energy springs are energy bases from the natural and unrelenting current of energy trendy in our instantaneous surroundings (owusu and asumadu-sarkodie, 2016). energy from resident renewable sources guarantees stability in supply and offers numerous economic and social benefits (tsagkari, 2020). the renewable energy sources include wind and ocean energy (tide and wave), direct solar energy, hydropower, geothermal energy and bioenergy (owusu and asumadu-sarkodie, 2016). there is usually a free flow of energy from these natural sources, and it is never in short supply. 2.1.2. primary energy consumption primary energy consists of traditional energy commonly used before the discovery of renewable energy which is environmentally friendly. in most countries, primary energy springs are relic petroleum like coal, oil and natural gas (alper and oguz, 2016). the global increasing energy requirement, besides growing inhabitants, occasioned continual usage of vestige fuel energy bases (coal, oil and gas), which turned out to be problematical (owusu and asumadu-sarkodie, 2016). fossil fuels generated numerous challenges which include diminution of fossil fuel reserves, conservatory gas discharges, and other ecological distresses (owusu and asumadu-sarkodie, 2016). modern energy will minimize the consumption of traditional energy in emerging nations, to prevent glasshouse gas pollutions (tariq et al., 2018). apart from the greenhouse gas effluences, there were also frequent fuel price variations, geopolitical and military clashes (owusu and asumadu-sarkodie, 2016). these complications might produce uncontrollable circumstances. the situation would ultimately lead to possible irrevocable hazardous conditions in society (unfcc, 2015). nevertheless, tiwari and mishra (2011) optimistically put forward that, renewable energy sources serve as the most acceptable and exceptional substitute that could fill the gap and remedy the hopeless situation at the moment. 2.1.3. carbon (co2) emissions co2 refers to all carbon dioxide generated in the course of gas flaring and ingestion of hard, liquescent, and fume energies. carbon dioxide productions are the pollutions emanating from the sweltering of fossil fuels and cement manufacturing. asumadusarkodie and owusu (2016) pose it that, the ascendency of energy generated from fossil fuels (coal, oil and gas) and global population growth in the last decades increased energy demand. it becomes universally problematic and more complicated due to the growing rate of co2 productions. 2.2. review of related empirical works rafal et al. (2020) considered the association amid revivable vitality intake and cost-effective progression in 29 european republics. the study covered a period from 1995 to 2016. the econometric tools used were panel co-integration test, fully modified ordinary least squares method and dynamic ordinary least squares technique. the finding showed that renewable energy consumption in the european countries had a long-run equilibrium relationship with economic growth. the study further found that renewable energy consumption had a significant positive impact on economic growth. nguyen et al. (2020) used quantitative research design and ardl to assess the relationship between energy consumption and economic development in indonesia from 2000 to 2019. the findings revealed that there was a nexus between economic growth and energy consumption in indonesia. okoye et al. (2020) analyzed the relationship between energy consumption and economic growth in nigeria from 1981 to 2017 using auto-regressive distributed lag (ardl) technique. the study provided evidence that energy consumption is critical in the evolution of the nigerian economy. onabote et al. (2020) examined the relationship existing between energy sustainability, financing and economic growth of nigeria from 1981 to 2014. the study omodero and uwalomwa: energy absorption, co2 emissions and economic growth sustainability in nigeria international journal of energy economics and policy | vol 11 • issue 4 • 2021 71 established a long to zrun relationship and also found the energy sustaining and financing variables affecting economic growth differently. anochiwa et al. (2020) employed ardl to assess the nexus between energy consumption and economic development in nigeria from 1980 to 2017. the result showed that petroleum and electricity were positive and significant to economic growth, while coal was found insignificant but positive. khan et al. (2020) also applied ardl to test the relationship between energy consumption, economic growth and carbon dioxide emissions in pakistan. the study covered 1965 – 2015. from the findings, it was revealed that energy consumption and economic growth increase the co2 emissions in pakistan, both in the short and long terms. tariq et al. (2018) examined energy consumption and economic growth of four developing countries from 1981 to 2015. the study found that a rise in the economic development of the countries also caused an increase in energy absorption. the paper also revealed that the nations were energy-dependent and thus, responded accordingly to energy shocks. the further finding showed that the rise in trade resulted in negative correlation with energy consumption. alper and oguz (2016) assessed the causal effect of renewable energy consumption on the economic growth of new eu member countries from 1990 to 2009. the study employed ardl and found that renewable energy impacted positively and significantly on the countries examined. chindo et al. (2015) studied the relationship between energy consumption, co2 emissions and economic growth in nigeria from 1971 to 2010 using ardl co-integration approach. the study found among others that co2 emission had a significant positive impact on gdp. the findings also revealed that energy consumption had a significant adverse effect on gdp in the short run. ogundipe and apata (2013) employed the johansen and juselius co-integration technique to investigate the association between electricity consumption and economic growth of nigeria from 1980 to 2008. the study established the existence of a bidirectional causal relationship and further revealed that electricity consumption impacted significantly on the economic development of nigeria. 3. materials and methods the study makes use of causative exploration strategy which seeks to unravel the causality consequence of the explanatory variable on the response variable. conferring to kothari (2004), a causative investigation approach helps to discover the impact of one variable on another, and this is consistent with this study which tries to find the effect of energy absorption and co2 discharge on the fiscal progress of nigeria. in this study, the reliant mutable is the gdp, and the data are collected from the central bank of nigeria (cbn) statistical bulletin. the independent variables are 1. primary energy. the data are collected in quadrillion btu from the world data atlas. 2. co2 emission. the data are gathered in million tonnes from the world data atlas. 3. electricity consumption. the data are derived in billion kilowatt hrs from the u.s. energy information administration. 4. the total labour force of nigeria represents the working-class group out of the total population. the data were emanating from the international labour organization, world bank population estimates and world development indicators. all data used in this study are a secondary form of data which span from 2008 to 2019 and are applied in their logarithm form. the study employs relevant statistical tools and software to carry out the data analysis. the multiple regression model for this study to evaluate the impact of the independent variables on the dependent variable is specified as follows: gdp = f(elc, co2, pec, tlf) (1) the econometric form is stated as: loggdp=β0 + β1logelc + β2logco2 + β3logpec + β4logtlf + ε (2) where: gdp =gross domestic product elc = electricity consumption co2 = carbon dioxide emissions pec = primary energy consumption tlf = total labour force β0 = constant; β1-β4 = regression coefficients; ε = error term. on the a priori, we expect; β1 >0, β2 >0, β3 >0, β4 >0. 4. results the serial correlation test on table 1 shows that the f-statistic p = 0.63 is more consequential than the 5% material level. consequently, there is the nonexistence of serial correlation in the model applied in this research. the result of durbin-watson also validates this report. the ramsey reset test is carried out to ascertain the stability of the regression model. the result in table 2 discloses that the p = 0.128 is more significant than the 0.05 level of significance. therefore, the product specifies that the model is firm. this is also established in figures 1 and 2, where the blue line falls between the two red lines showing the boundaries at a 5% significance level. the indicative test for heteroskedasticity on table 3 is to guarantee that the model coefficients assessed using ordinary least squares table 1: breusch-godfrey serial correlation lm test f-statistic 0.504255 prob. f (2,5) 0.6317 obs*r-squared 2.014162 prob. chi-square (2) 0.3653 source: authors’ calculation, 2020 table 2: ramsey reset test specification: log_gdp log_co2 log_elc log_pec log_ tlf c omitted variables: squares of fitted values value df probability t-statistic 1.765124 6 0.1280 f-statistic 3.115662 (1, 6) 0.1280 likelihood ratio 5.018815 1 0.0251 source: authors’ calculation, 2020 omodero and uwalomwa: energy absorption, co2 emissions and economic growth sustainability in nigeria international journal of energy economics and policy | vol 11 • issue 4 • 202172 are at liberty with prejudice. the presence of heteroskedasticity is noticeable when the variance of errors or the model is not identical in the entire observations. in that case, the p-value of the f-statistic will be lower than the 5% level of significance. in this study, the p = 0.47, which is bigger than the 0.05 significance level. thus, the model is heteroskedasticity free. in the same manner, the p-value for jarque-bera in figure 3, is 0.69 > 5%. the result provides evidence that the data set is normally distributed. 4.1. histogram normality multicollinearity existence test on table 4 is with the variance inflation factor (vif). the test is to verify the existence of interrelationship among the independent variable. in this study, the value of 10 (gujarati and porter, 2009) applies to confirm if the explanatory variables have any interconnection in this study. the australian property institute (2015) states that multiple regression models count on the proposition that all independent variables used in a study are not interconnected. the variables have table 4: variance inflation factors sample: 2008-2019 included observations: 12 coefficient uncentered centered variable variance vif vif log_co2 0.075135 11924.72 5.223020 log_elc 0.034576 2558.847 6.996024 log_pec 0.008012 8.566602 4.839958 log_tlf 0.088720 212410.7 5.980286 c 3.742861 149994.4 na source: authors’ calculation, 2020 table 5: regression result dependent variable: log_gdp method: arma maximum likelihood (opg bhhh) sample: 2008 2019 included observations: 12 variable coefficient std. error t-statistic prob. log_elc 0.075021 0.120452 0.622829 0.5607 log_co2 0.096297 0.034178 2.817547 0.0372** log_pec −0.048384 0.020607 −2.347984 0.0657* log_tlf 4.195262 0.170779 24.56538 0.0000*** c −27.81071 1.120987 −24.80912 0.0000 ar (5) −0.999104 0.003657 −273.1860 0.0000 sigmasq 1.03e − 06 3.11e − 06 0.332236 0.7532 r-squared 0.999965 mean dependent var 4.898809 adjusted r-squared 0.999922 s.d. dependent var 0.178503 s.e. of regression 0.001576 akaike info criterion −7.141928 sum squared resid 1.24e − 05 schwarz criterion −6.859066 log likelihood 49.85157 hannan-quinn criter. −7.246654 f-statistic 23530.19 durbin-watson stat 2.018790 prob (f-statistic) *** 0.000000 source: authors’ calculation, 2020. significant at *10%; **5%; ***1% figure 1: recursive estimates of the cusum test. cusum = cumulative sum control chart vifs that are below the value of 10. thus, there is the absence of multicollinearity in the model. the regression result in table 5 indicates a strong and positive correlation between the economic growth of nigeria and energy consumption. the correlation (r) value of 99% (square root of r-squared) connotes a strong relationship between the response and explanatory variables. the coefficient of determination is also figure 3: normality test figure 2: recursive estimates of cusum of squares test. cusum = cumulative sum control chart table 3: heteroskedasticity test: breusch-pagan-godfrey f-statistic 0.994802 prob. f (4,7) 0.4694 obs*r-squared 4.349174 prob. chi-square (4) 0.3608 scaled explained ss 0.605515 prob. chi-square (4) 0.9624 source: authors’ calculation, 2020 omodero and uwalomwa: energy absorption, co2 emissions and economic growth sustainability in nigeria international journal of energy economics and policy | vol 11 • issue 4 • 2021 73 99.99%, implying that the nigerian economy depends so much on energy consumption. the various energy sources described here determine 99.99% of the changes in the economic growth of nigeria, which is almost 100%. this is how vital energy means to the nigerian economy. the research to identify the best source of energy to improve the economy and preserve the environment is indeed substantial. in this study, the result of the standard error of regression is zero (0.00 <1). this result implies that the prediction is 100% accurate and the regression line is correctly fitted. the durbin-watson of 2 indicates the absence of autocorrelation and is confirmed by the serial correlation result in table 1. the result of the f-statistic is 23530.19 with a p = 0.00 significant at 1%. this result shows that the model used in this study is a good fit and statistically significant. figures 1 and 2 give the impression that the regression model if stable. the appearance of the blue line in between the frontiers of the dotted red lines shows the stability of the regression model. the t-statistic of each explanatory variable provides evidence on the impact of each predictor variable on the response variable. the t-statistic of elc is 0.623 while the p-value is 0.56 >0.05 significance level. the outcome specifies that electricity has an insignificant effect on economic growth. the result clashes with the discoveries of (ogundipe and apata, 2013; anochiwa et al., 2020). the co2 t-statistic is 2.817 with a p-value of 0.03 <0.05. the result reveals that co2 has a significant positive impact on the economic growth of nigeria. this result is consistent with the findings of chindo et al. (2015). the pec t-statistic is −2.348, and the p-value is 0.06. this result is significant at 10%, which implies that pec has a significant negative impact on economic growth. this finding is in line with the result of chindo et al. (2015). finally, the tlf has a t-statistic of 24.565 and a p = 0.00. the result is significant at 1% level of significant and implies that tlf has a noteworthy constructive bearing with growth. this finding is in agreement with the result of nguyen et al. (2020). 5. conclusion and recommendations 5.1. conclusion the research inspects the bearing of energy consumption with sustainable fiscal evolvement in nigeria. the scope of the study is from 2008 to 2019. the independent variables employed to explain the variations in economic development through energy consumption include electricity consumption (elc), carbon dioxide contaminations (co2), primary energy ingestion (pec) and total labour force (tlf) in the country. the study found that electricity does not impact significantly on economic growth within the period the study covers. this is as a result of epileptic and insufficient power supply which has affected the development of many businesses. electricity in nigeria is the best source of energy and ought to be regular, but the situation is pathetic. the policy implication is that, if the insufficient supply of electricity in nigeria continues, renewable energy expansion is, therefore, an emergency. otherwise, co2 emission and its resultant effect on humans and the environment will remain unavoidable. from the result in table 5, co2 has a weighty favourable influence on fiscal improvement. this is an indication that the economy is growing with the pollution emanating from the burning of fossil fuels. this result is a sign that, though the economy grows today, economic growth sustainability in the future is not guaranteed. the environmental degradation and the evaporation of the ozone layer is a serious issue of concern. nigeria is a place where people provide energy for themselves at all costs. the use of fossil fuels is inevitable for any business to remain in existence. however, the use of primary energy is negatively affecting the environment. the economy, as indicated by the result in table 5. the product also illustrates that the total labour force has a substantial bearing with economic advancement. thus, human energy (both mental and physical) is required to grow the economy. no wonder omodero (2019) opines that human capital is the greatest asset in the economic growth of a nation and should be adequately developed to achieve national development. 5.2. recommendation the study recommends policies that would promote sufficient energy generation in nigeria. economic growth sustainability is all-encompassing. it integrates environmental sustainability for the future generation. if the environment is destroyed with the burning of fossil fuels to achieve economic growth, it will only be in the short run. therefore, long-run economic growth requires a green energy policy. the implication of green energy policy in nigeria is full adoption and implementation of renewable energy to reduce greenhouse gas emissions. nigeria is naturally blessed and can benefit from refreshable energy springs (wind energy, ocean energy and solar energy) surrounding her territory. policymakers are encouraged to provide measures that will strengthen the energy sector and power generating agencies for effective and efficient service delivery. the government can only guarantee a clean and pollution-free environment if renewable energy is made available and affordable by the public. its availability and affordability will help to minimize the usage of traditional energy sources that pollute our environment. 6. acknowledgement we candidly appreciate the management of covenant university ota, ogun state, nigeria, for encouraging unrestricted access to this research output. references alper, a., oguz, o. (2016), the role of renewable energy consumption in economic growth: evidence for asymmetric causality. renewable and sustainable energy reviews, 60(1), 953-959. anochiwa, l., oguwuike, m.e., kalu, e.u., obidike, c.p., uwazie, i., ogbonnaya, i.o., ojike, o.r., anyanwu, c.k. (2020), energy consumption and economic growth nexus in nigeria: evidence based on ardl bound test approach. international journal of energy economics and policy, 10(6), 713-721. asumadu-sarkodie, s., owusu, p.a. (2016), feasibility of biomass heating system in middle east technical university, northern cyprus campus. cogent engineering, 3(1), 1-15. omodero and uwalomwa: energy absorption, co2 emissions and economic growth sustainability in nigeria international journal of energy economics and policy | vol 11 • issue 4 • 202174 australian property institute. (2015), the valuation of real estate. 2nd ed. canberra, australia: appraisal institute. central bank of nigeria. (2019), population forecast of nigeria. cbn statistical bulletin. chindo, s., abdulrahim, a., waziri, s.i., huong, w.m., ahmad, a.a. (2015), energy consumption, co2 emissions and gdp in nigeria. geojournal 80, 315-322. giles, c. (2018), port harcourt: why is this nigerian city covered in a strange black soot? available from: https://www.edition.cnn. com/2018/04/26/africa/nigeria-portharcourt-soot/index.html. gujarati, d.n., porter, d.c. (2009), basic econometrics. 5th ed. boston: mcgraw-hill irwin. khan, m.k., khan, m.j., rehan, m. (2020), the relationship between energy consumption, economic growth and carbon dioxide emissions in pakistan. financial innovation, 6(1), 1-13. kothari, c. (2004), research methodology: methods and techniques. 2nd ed. new delhi, india: newage international publishers. nguyen, d.d., nguyen, h., huyen, m.t., huy, d.t.n., lan, l.m. (2020), energy consumption and economic growth in indonesia. international journal of energy economics and policy, 10(5), 601-607. ogundipe, a.a., apata, a. (2013), electricity consumption and economic growth in nigeria. journal of business management and applied economics, 2(4), 1-14. okoye, l.u., omankhanlen, a.e., okoh, j.i., adeleye, n.b., ezeji, f.n., eze, g.k., ehikioya, b.i. (2020), analyzing the energy consumption and economic growth nexus in nigeria. international journal of energy economics and policy, 11(1), 378-387. omodero, c.o. (2019), government general spending and human development: a case study of nigeria. academic journal of interdisciplinary studies, 8(1), 51-59. omodero, c.o. (2019), government sectoral expenditure and poverty alleviation in nigeria. research in world economy, 10(1), 80-90. onabote, a., jolaade, a., osabohien, r., otobo, o., ede, c., okafor, v. (2020), energy sustainability, energy financing and economic growth in nigeria. international journal of energy economics and policy, 11(1), 433-439. owusu, p.a., asumadu-sarkodie, s. (2016), a review of renewable energy sources, sustainability issues and climate change mitigation. cogent engineering, 3(1), 1-14. rafal, k., yuriy, b., dalia, s. (2020), the renewable energy and economic growth nexus in european countries. sustainable development, 28(5), 1086-1093. tariq, g., sun, h., harris, m., javaid, h.m., kong, y. (2018), energy consumption and economic growth: evidence from four developing countries. american journal of multidisciplinary research, 7(1), 100-107. tester j.w. (2005), sustainable energy: choosing among options. london: mit press. tiwari, g.n., mishra, r.k. (2011), advanced renewable energy sources. burlington house, london: royal society of chemistry. tsagkari, m. (2020), local energy projects on islands: assessing the creation and upscaling of social niches. sustainability, 12(1), 1-18. unfcc. (2015), adoption of the paris agreement. available from: http:// www.unfccc.int/resource/ docs/2015/cop21/eng/l09.pdf. world bank. (2020), labor force, total nigeria. world development indicators. available from: https://www.data.worldbank.org/ indicator/sl.tlf.totl.in?locations=ng. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(5), 204-210. international journal of energy economics and policy | vol 11 • issue 5 • 2021204 methodological approach to improve energy efficiency by concentrating operation points an electrical transformer maintenance company andrés rodríguez toscano1, aurora patricia piñeres castillo2*, julio césar mojica herazo2, rafael ramírez restrepo3 1departamento de energíauniversidad de la costa-cuc, colombia, 2departamento de productividad e innovación, universidad de la costa-cuc, colombia, 3ingeniería mecánicauniversidad del atlántico, colombia, 4energía optima s.a.s. *email: apineres2@cuc.edu.co received: 26 february 2021 accepted: 28 may 2021 doi: https://doi.org/10.32479/ijeep.11333 abstract in recent years, companies have developed strategies to improve the environment through the efficient use of their energy resources (rodríguez toscano et al., 2019). this practice has been widely used in the goods manufacturing and transformation industry, but many opportunities for improvement remain in the services sector. in this context, this study offers a methodological and analytical approach to improve energy efficiency at a company that provides electric transformer maintenance services, based on performance of energy planning, analysis of concentration of operation points, and the implementation of operational and technological improvements to the processes. the results display total energy savings of 7% after implementation of the operational and technological improvements on only 23% of the company’s energy-intensive equipment. keywords: energy efficiency, technological improvement, electrical transformers jel classifications: i, l8 1. introduction services are currently one of the fastest growing and most dynamic economic sectors, comprised mainly of companies that provide services (lin and zhang, 2017; upme, 2017). many countries consider companies of this type to be key drivers for the development and implementation of policies and strategies related to energy efficiency (lin and zhang, 2017; upme, 2017; sinceo, 2019). numerous studies worldwide have been carried out on energy efficiency in this sector, reporting excellent results (kangas et al., 2018; zografakis et al., 2011; rodríguez toscano et al., 2019); however, the specialized literature does not report energy efficiency improvements at companies whose main business is equipment maintenance and repair services. in colombia, these companies have a major role in the economy and in terms of energy consumption (upme, 2017; unidad de planeación minero energética, 2010). close to 60% of gdp is accounted for by companies directly associated with services sector, and they consume close to 66.4% of total energy (unidad de planeación minero energetica, 2010). despite this, energy efficiency management is still incipient at these companies, and in the country in general (aceee, 2019; upme, 2017). the only studies found in the specialized literature cover the services industry, but they do not provide details on company-level energy consumption and/or efficiency (upme, 2017). consequently, there is uncertainty regarding the rational use of energy and the future trends of companies of this type. in the colombian atlantic coast region, one of the major issues that affects the community is the poor quality of electric power supply, due to poor maintenance of the equipment associated this journal is licensed under a creative commons attribution 4.0 international license castillo: methodological approach to improve energy efficiency by concentrating operation points an electrical transformer maintenance company international journal of energy economics and policy | vol 11 • issue 5 • 2021 205 with electricity distribution services (camara de comercio, 2019; semana, 2015). the government and the district promote solutions to this issue, and it is expected that soon there will be substantial growth in companies that provide equipment maintenance and repair services for the electric power service industry. in barranquilla, there has been substantial growth in the companies devoted to the repair and maintenance of equipment and machinery associated with electricity (camara de comercio, 2019); however, few of these companies have effective processes in place related to the development of energy efficiency plans (upme, 2017). this leads to uncertainty regarding their future growth. due to this above, this study focuses on the development and analysis of energy indicators using different statistical analysis tools that will provide effective guidance for rational energy use in the context of the operating dynamics of companies devoted to the repair and maintenance of electrical equipment in the city of barranquilla. 2. materials and methods this study presents an energy diagnosis and the implementation of different strategies based on energy planning at a company devoted to the maintenance of electrical transformers located in the city of barranquilla. the aim is to identify and assess the energy performance indicators that characterize before and after operating dynamics and variability in production (number of repaired transformers) in connection with significant energy usage (electricity) at a services company devoted to the repair and maintenance of low and medium voltage electrical transformers. figure 1 displays the methodological approach that was used. the energy performance indicators and the energy baseline were identified and implemented using the guidelines established in the iso 50001 and iso 50006 standards (iso, 2014; 2011). additional statistical tools were used (dendrogram and pareto diagram) to determine the main activities and points that characterize the company’s normal operational dynamics. the measurement equipment used for the electric energy load and consumption census was an electric network analyzer, over a 42-month measurement period. the equipment used to determine the technical criteria (temperature, humidity, pressure drops) included a hygrothermograph, a thermographic camera and a luxometer. 2.1. energy baseline (enb) the energy baseline is established by means of a linear regression of electricity consumption with one or more variables that affect its dynamics over a given baseline time period (iso, 2011; cabello eras et al., 2016). for this study, it was calculated based on monthly electricity consumption and the number of repaired transformers (nrt) for a given class of transformers. these account for practically 99% of all the products it repairs, given that its business focuses on low-voltage transformers. enb=m•nrt+e0 (1) m = electric energy consumption associated with the nrt. e0=electric energy consumption not associated to the nrt. 2.2. energy consumption index (ci) the energy consumption index expresses the relationship between electricity consumption and the nrt. it is used for the effects of increasing energy efficiency through planning of repairs (nrt) and to determine the existence of any failures or inefficiencies in the process (grimaldo guerrero et al., 2018; iso, 2011). ci = m+ e nrt 0 (2) 2.3. pareto as a tool to prioritize the improvements to be made at operating points based on the consumption baseline in the specialized literature, certain areas of the baseline display greater density or concentration of operating points, due to their production activities and their energy consumption ranges, i.e. the points with highest levels of operation are not uniformly distributed. this leads to uncertainty about the effectiveness of actions intended to improve a company’s energy efficiency (rodríguez toscano et al., 2020). additionally, the implementation of actions to improve energy efficiency can be fruitless or ineffective if priorities are not established based on the operation’s dynamics. in order to identify the points of greatest concentration of operations, either by production and/or electricity consumption, a pareto diagram was developed for both variables. in the case of production, the region indicates that 80% of the operating points are concentrated in 20% of the production range. the region determined by the production pareto chart is drawn vertically over the consumption baseline. in the case of electricity consumption, the region indicates that 80% of the operating points are concentrated in 20% of the electricity consumption range. the region determined by the electricity consumption pareto chart is drawn horizontally over the consumption baseline. the intersection of these two regions indicates the points to be prioritized. if the points in this region are below the consumption baseline, it means that in general the efforts made have produced good results and have a substantial effect on normal operating dynamics, while points above the baseline indicate a contrary effect. when these regions are far away from the general intersection region, it indicates a low level of overall efficiency, because these operating points are the ones that characterize the company’s typical operating dynamics. this tool developed over the consumption baseline enables focusing efforts on the effective implementation and control of energy efficiency and helps identify typical variables that have a significant effect on energy consumption. 2.4. dendrogram as a tool to visualize distances and disorder in the consumption baseline the dendrogram measures the euclidian distance of the operating points that are nearest to the baseline, in accordance with the months of operation, to visualize the disorder and its association to space and time. this enables a quick assessment of the relative energy efficiency at each point. castillo: methodological approach to improve energy efficiency by concentrating operation points an electrical transformer maintenance company international journal of energy economics and policy | vol 11 • issue 5 • 2021206 2.5. maintenance of electric transformers electric transformers are a key component for a company’s development and productivity because they are the energy source that is easiest to transport. when their maintenance is not adequately planned and implemented, their useful lives decrease and energy waste increases (metwally, 2011). with adequate maintenance, power transformers can remain in operation for up to 60 years (wang et al., 2002). however, certain critical transformer elements degrade over time, such as the taps, core, insulation (oil and paper) and the tank (murugan and ramasamy, 2019). a maintenance plan also includes preventive measures to slow down wear of the transformer’s components. preventive transformer maintenance is based on diagnostic testing. figure 2 displays the overall maintenance process for electric transformers. it is based, firstly, on a good visual inspection and verification of the overall conditions of the transformer. 3. results and discussion the following are the detailed results of this study based on the methodology applied. 3.1. energy diagnosis the only energy source used by this company is electricity. using an electric network analyzer, the following equipment and systems that consume most electric energy at the company were identified. an energy audit was carried out to determine a load census, to analyze and determine electric energy usage, including the distribution of energy consumption at the company’s facilities and the average load of each equipment unit. figure 3 displays the pareto diagram used to assess the equipment that most consume electricity at the company. 20% of the equipment account for 80% of electricity consumption, namely: 1. electric motors 2. air conditioning system 3. lighting system. as expected, given that the company’s main activities and procedures consist in rewinding and transporting the transformers at its facilities, electric motors have the highest share of overall electricity consumption, although air conditioning systems also have a high share. the excessive consumption of electricity by figure 1: methodology implemented for the study 1. energy diagnosis. • 1.1. base line. • 1.2. pareto chart to identify equipment with significant energy use. 2. identification of the concentration of operational points according to energy production and consumption. • pareto diagram of the points where the operation by production is concentrated. • pareto diagram of the points where the operation is concentrated by energy consumption. • baseline with the points where the intersection operation and energy consumption are concentrated. 3. determination of energy saving potential relative point to point. • 3.1. dendrogram. 4. determination of the theoretical and real consumption index. • 4.1. real consumption index and theoretical consumption index. 5. energy saving measures. • 5.1 energy saving proposals. 6. implementation and verification of the impact of savings measures. • 6.1. determination of the new energy consumption baseline. • 6.2. comparison of the baseline of energy consumption with the new baseline. castillo: methodological approach to improve energy efficiency by concentrating operation points an electrical transformer maintenance company international journal of energy economics and policy | vol 11 • issue 5 • 2021 207 the air conditioning system is produced by a high level of water condensation, the low set point temperature (17°c), as well as no insulation for several components and insufficient maintenance. consequently, adequate, and ongoing maintenance of this equipment is required to maintain them in good working order and to avoid over-consumption of electricity. figure 4 indicates that the consumption baseline has a high determination level, which indicates a high level of correlation between the variability of energy consumption and the nrt. it indicates that 33.33 % of the operating points are above the enb. the slope of the enb indicates that each nrt unit consumes 50.747 kwh of electricity. on the other hand, the intercept on the enb indicates that electric energy not associated to the nrt is 746.55 kwh. this energy that is not associated with the nrt could be produced by insufficient maintenance and improper usage of high-consumption equipment, but further measurement, statistical analysis and information would be required to ascertain this. 3.2. concentration of operating points in terms of production and energy consumption figure 5 displays the number of operating points in terms of nrt ranges. in figure 5, the ranges with the greatest number of points are: 32.9-38 and 15-27.6 nrt. most of the company’s activities are concentrated in these ranges, and it is highly likely that these ranges will account for almost all the company’s energy consumption. however, it is not possible to visualize the effects without analyzing energy consumption at these points, because there may be operational situations or points that consume a disproportionate amount of energy. figure 6 displays the pareto diagram of the operating points in terms of energy consumption. the ranges with the greatest number of points are: 2099-2444.2 and 2615.9-2789.4 kwh. to enable the analysis of the pareto diagrams described in figures 4 and 5, they are superimposed on the energy consumption baseline. figure 7 displays the ranges determined in the previous pareto diagram on the energy consumption baseline. considering the intercept ranges and the points that lie above the baseline, we conclude that the savings activities should focus primarily on the points or situations that are within or above the b y c area. 3.3. determining potential relative energy savings point by point figure 8 displays the dendrogram prepared based on the energy baseline. it displays a large difference in operating performance figure 3: pareto diagram on energy consumption by the company’s equipment enb = 50,747 nrt + 746,55 r² = 0,77 1,500 1,700 1,900 2,100 2,300 2,500 2,700 2,900 3,100 20 22 24 26 28 30 32 34 36 38 40 e le ct ric ity c on su m pt io n kw h/ m on th nrt figure 4: electric energy baseline (enb) visual inspection of the transformer check the general condition of the transformer verify operation of auxiliary equipment discover the transformer cleaning and painting initial repair disarmament of the active part oil inspection identify possible electrical or thermal faults oil sampling for dissolved gas analysis core testing and data collection insulation cut coil construction data collection storage of accessories electrical tests insulation resistance winding resistance transformation relation power factor short circuit impedance bushings figure 2: general transformer maintenance process castillo: methodological approach to improve energy efficiency by concentrating operation points an electrical transformer maintenance company international journal of energy economics and policy | vol 11 • issue 5 • 2021208 figure 5: pareto diagram of operating points in terms of ntr figure 6: pareto of operating points in terms of electricity consumption following the implementation of the saving measures. they display the improvements, the benefits obtained and their impact. the improvement proposals were well received by the area provisionally responsible for implementing the energy management system (ems). forms will be designed to monitor and record the variables in real time at each machine involved in the process, among other improvements to be implemented. between the august-october group and the month of june (these months are the closest ones and have similar production levels). in this sense, the dendrogram enables viewing significant changes in operations over time, which facilitates the search of atypical values and comparisons in the operation. in june, production and maintenance activities must be reinforced to improve the company’s energy efficiency. 3.4. determining the theoretical and actual consumption index figure 9 indicates that 5 operating points display impairment compared to the theoretical consumption index. this energy performance index shows that the level of performance is low and that deficiencies are caused by variables or factors that are independent from the nrt. the theoretical ci indicates that at a higher nrt, energy consumption per nrt should decrease, which is consistent with the actual results. however, there are atypical operating cases and inadequate performance levels after 37 nrt. the employees attribute this behavior to disorganization and low capacity of control when many transformers must be repaired simultaneously with other repairs. 3.5. electric energy savings measures tables 1-3 display the status of the systems, the savings measures implemented, the benefits and impacts found in the energy audit table 1: electric energy savings measures for electric motors system current situation savings measures benefits impact engines poor lubrication and lack of lubrication record increase the frequency of lubrication and keep track of your maintenance and the lubrication system energy reduction due to friction losses and increase in the useful life of electric motors improved performance in the process and its times. economic savings by reducing friction lossesnoise, vibrations, wear on the shafts, heating on the shafts bearing replacement and lubrication inefficient use of motors turn off equipment when not in use for more than a minute energy savings due to non-use economic savings by not using electrical energy table 2: electric energy savings measures for the air conditioning system system current situation savings measures benefits impact airconditioning system high electricity consumption compared to other venues. 18°c set point increase the set point temperature two degrees saving the electricity bill cost savings in electricity consumption, reduction of water vapor that condenses. reduces the carbon footprint due to the efficient use of energy excessive condensation of water vapor occurs in systems insulate walls, windows, and copper pipes of the hvac system. change the closing system of office doors and work areas to avoid the entry of hot air castillo: methodological approach to improve energy efficiency by concentrating operation points an electrical transformer maintenance company international journal of energy economics and policy | vol 11 • issue 5 • 2021 209 table 3: electric energy savings measures for the lighting system system current situation savings measures benefits impact illumination use of bulbs and lamps with high electricity consumption use of bulbs and lamps with high electricity consumption lighting electrical energy saving of about 60%. elimination of electrical faults improvement in the performance of workers, reduction in electricity consumption, increase in the useful life of systems associated with lighting flashing lighting change of wiring and maintenance to the electrical network poor placement and spacing of fixtures relocation of luminaire installation points figure 10: new electricity consumption baseline (enb) 3.6. implementation and verification of the impact of the savings measures figure 10 indicates that the slope of the new enb decreased by 8.387 kwh/nrt compared to the previous enb, and that 80% of the operating points are lower compared to the previous condition. this demonstrates the effectiveness of the electric energy savings measures compared to the consumption trends of the baseline period. under the new conditions, energy savings may range between 5% and 16 % depending on production, and total energy savings after implementing the improvements are approximately 7%. these electricity savings were substantial, considering that the strategies were only implemented at 23% of the high electric energy consumption equipment, and that the only savings measures implemented were those that did not require new investments. figure 9: electric energy consumption index 60 65 70 75 80 85 90 15 20 25 30 35 40 45 c i ( kw h/ n tr ) nrt figure 8: dendrogram figure 7: intersection of points of high concentration of operations and of energy consumption castillo: methodological approach to improve energy efficiency by concentrating operation points an electrical transformer maintenance company international journal of energy economics and policy | vol 11 • issue 5 • 2021210 the consumption of electric energy that is not associated with production (ntr) increased by 159.21 kwh. this increase was expected, because priority was assigned to maintenance of machines and instruments that are critical for operations to reduce efforts and costs. 4. conclusion the energy savings measures are effective for the effects of reducing consumption in service companies of this type. the slope of the company’s new enb and operating points decreased, though it should be noted that the energy not associated with the nrt increased. total electricity savings were approximately 7%, based on the implementation of 33% of improvements. lastly, most of the improvements do not involve significant costs because most of the required materials and equipment were available at the company. the methodology assigned priority to the equipment with highest electricity consumption, based on normal operating dynamics. electric energy consumption in the operations range displayed significant savings and an improved trend line. at the studied company, electric energy consumption was primarily concentrated in electric motors, followed by air conditioning systems and the lighting systems. regarding the motors, it is important to monitor lubrication and the conditions of bearings, which are in continuous motion because they are a key component in the process of repairing and maintaining electric transformers. 5. acknowledgments the authors thank the department of energy of the universidad de la costa and the department of productivity and innovation (intensive scientific and collaborative production days conv14 2020) of the universidad de la costa, energía óptima sas for financing the project, as well as thanks to the student andrés mauricio noguera silvera, a member of the newton research seedbed of the universidad de la costa for his technical contributions. references aceee. (2019), the international energy efficiency scorecard. obtenido de. available from: https://www.aceee.org/portal/national-policy/ international-scorecard. cabello eras, j.j., sousa santos, v., sagastome gutirrez, a., guerra palencia, m.a., haeseldonckx, d., vandecasteele, c. (2016), tools to improve forecasting and control of th electricity consumption in hotels. journal of cleaner production, 137, 803-812. camara de comercio. (2019), camara de comercio barranquilla. obtenido de. available from: http://www6.camarabaq.org.co. grimaldo guerrero, j., rodríguez toscano, a.d., vidal pacheco, l., osorio tovar, j. (2018), analysis of the energetic and productive effects derived by the installation of a conveyor belt in the metalmechanic industry. international journal of energy economics and policy, 8(6), 196-201. iso. (2011), iso 50001. requirements with guidance for use. energy management sytems. london, united kingdom: iso. iso. (2014), energy management systems e measuring energy performance using energy baselines (enb) and energy performance indicators (enpi) e general principles and guidance (e). london, united kingdom: iso. iso. (2014), obtenido de sis. available form: https://www.sis.se/api/ document/preview/918420. kangas, h.l., lazarevic, d., kivimaa, p. (2018), technical skills, disinterest and non-functional regulation: barriers to. energy policy, 114, 63-76. lin, b., zhang, g. (2017), energy efficiency of chinese service sector and its regional differences. journal of cleaner production, 168, 614-625. metwally, i.a. (2011), failures, monitoring and new trends of power transformers. ieee potentials, 30(3), 36-43. murugan, r., ramasamy, r. (2019), understanding the power transformer component failures for health index-based maintenance planning in electric utilities. engineering failure analysis, 96, 274-288. rodríguez toscano, a.d., mojica herazo, j.c., rojas millan, r.h., piñeres castillo, a.p., hinojosa rivera, m., silva, j. (2019), improving the effectiveness of energy savings measures at companies by means of a new baseline adjustment strategy: case study barranquilla-colombia. advances in intelligent systems and computing. available from: https://www.link.springer.com/ chapter/10.1007/978-3-030-30465-2_10. semana. (2015), los graves problemas de energía del caribe. semana, págs. available from: https://www.semana.com/nacion/articulo/ caribe-indignado-por-falta-de-electricidad/451423-3. sinceo. (2019), sinceo 2. obtenido de. available from: https://www. sinceo2.com/auditoria-energetica-sector-terciario. upme. (2010), proyección de demanda de energía en colombia. available from: http://www.upme.gov.co/docs/energia/proyecc_ demanda_energia_octubre_2010.pdf. upme. (2017), plan de acción indicativo de eficiencia energética 2017-2022. recuperado el 8 de 5 de 2018, de. available from: http:// www1.upme.gov.co/demandaenergetica/marconormatividad/ pai_proure_2017-2022.pdf. wang, m., vandermaar, a.j., srivastava, k.d. (2002), review of condition assessment of power transformers in service. in ieee electrical insulation magazine, 18(6), 12-25. zografakis, n., gillas, k., antrianna, p., profylienou, m., fanouria, b., tsagarakis, k.p. (2011), assessment of practices and technologies of energy saving and renewable energy sources in hotels in crete. renewable energy, 36, 1323-1328. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 5 • 2022146 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(5), 146-151. public debt – energy consumption nexus engy raouf* faculty of commerce and business administration, helwan university, egypt. *email: engy_raouf@commerce.helwan.edu.eg received: 16 may 2022 accepted: 24 august 2022 doi: https://doi.org/10.32479/ijeep.13296 abstract as energy demand has risen and continues to rise, a growing body of research examines the impact of a variety of factors on energy use, including economic development, price changes, and international trade. the public debt–energy consumption nexus, on the other hand, has received little attention. this study looks at the effect of government debt on both renewable and nonrenewable energy usage in 17 oecd countries from 1980 to 2020. using the generalized least square (gls) panel data estimation method and panel quantile regression (pqr), this paper finds that public debt has a favorable influence on the utilization of renewable energy and a detrimental influence on the use of non-renewable energy. it can be noticed from the pqr that all variables have more favorable impacts on renewable and nonrenewable energy usage at higher quantiles. keywords: public debt, renewable energy consumption, non-renewable energy consumption, panel quantile regression, oecd countries jel classifications: h63, q43, o13 1. introduction in recent decades, the global economy has been subjected to major events, which have resulted in climate change as well as political and economic uncertainty. as a result, researchers are attempting to evaluate these modern challenges to enhance the quality and substance of the global economy. almost every element of human life necessitates the use of energy. for example, there is a significant need for energy in the industries of heating, cooling, and transportation. in addition, energy is critical to the growth of the industry. in other words, energy is a necessary input for industrial production. it is essential for attaining economic growth and development objectives. energy may be classified into two main categories: the first sort of energy is non-renewable energy, which is obtained from the combustion of fossil fuels. the main sources of non-renewable energy are natural gas, crude oil, and nuclear power. the most significant advantage of using nonrenewable energy is its inexpensive cost of usage. these forms of energy, however, have several drawbacks. the widespread use of nonrenewable natural resources has a substantial impact on high emission levels and hence contributes to climate change. as a result of this situation, the public’s health is in great danger. due to climate change and air pollution, the country’s residents are at significant risk of getting respiratory illnesses. this circumstance will result in a drop in the country’s labor force as well as an increase in unemployment. another problem with these sources of energy is that governments will be unable to use them if sufficient reserves are not available (qi et al., 2020; zhe et al., 2021). the other type of energy is renewable energy sources. it emerges as a complement to traditional types of energy, and while it accounts for a large portion of the energy output in certain industrialized nations, it is still not the dominant source of energy in the energy sector. the main advantages of using renewable energy are that it emits no greenhouse gases into the atmosphere, and it allows future usage of finite fossil resources. this is the primary driver of increased investment in and use of renewable energy sources. the main disadvantage of using renewable energy is that it is primarily reliant on the weather for its supply. renewable energy sources are incapable of producing energy in case of weather that does not provide certain types of climate conditions. it is also difficult to produce in large quantities. in addition, it requires a this journal is licensed under a creative commons attribution 4.0 international license raouf: public debt – energy consumption nexus international journal of energy economics and policy | vol 12 • issue 5 • 2022 147 high initial investment or a high cost of production (ahmed and osman, 2016; maradin, 2021). in recent decades, energy demand has risen sharply and continues to rise. enhanced lifestyles, population increases, economic competitiveness, and manufacturing advancements all contribute to the rising demand for energy. energy is a critical element for meeting fundamental human needs as well as achieving economic growth and development goals. many countries lack the necessary funds to invest in energy production or even to use energy, whether renewable or non-renewable. as a result, these countries rely on borrowing to finance these investments. in recent years, the literature on energy and economic performance has expanded. however, the literature on the link between energy use and public debt is still in its early phases. this study’s main objective is to investigate the effect of public debt on energy usage, both non-renewable and renewable energy, employing panel data for seventeen oecd countries from 1980 to 2020. the rest of this paper is structured as follows. section 2 explores previous literature. section 3 presents the model description and data sources. the key findings of the study are presented in section 4. finally, section 5 illustrates the conclusion and the policy recommendations. 2. review of literature the linkage between public debt, use of energy and economic growth has been the subject of a considerable number of studies. the review of relevant literature is divided into two main subsections: the first deals with the link between energy usage and economic growth; and the second discusses the link between energy usage and public debt. 2.1. energy growth nexus the empirical research on the linkage between economic development and the use of energy is substantial, and they continue to grow. the acquired results are quite diverse, and there is no consensus among the researchers not only on the presence of the interaction but also on the direction of causation between the two variables. the energy-growth nexus is investigated using four hypotheses (campo and sarmiento, 2013; ozturk et al., 2010). first, the growth hypothesis assumes that increasing the use of energy enhances economic growth, and hence, energy is a key input for output. second, the conservative hypothesis asserts that the connection between economic growth and energy use is unidirectional, and hence policies to reduce energy use may not have a negative effect on economic growth. third, the feedback hypothesis states that using of energy and economic growth are inextricably linked, with bidirectional causality between both. fourth, according to the neutrality hypothesis, there is no causative link between energy usage and a country’s growth, and any policy that influences one will have no impact on the other (belke et al., 2012; destek and aslan, 2017; rahman and mamun, 2016). the growth hypothesis found support in many empirical studies (lee, 2005), (nkoro and ikue-john, 2020), (kabuga and mohammed, 2021), (wang and lee, 2022). according to the growth hypothesis, energy, like capital and labor, is a necessary input in the process of manufacturing and plays a significant role in economic progress. as a result, energy consumption and economic development have a one-way relationship, and energy policy implementation affects the production level. the feedback hypothesis highlights the interconnection and complementarity of energy use and economic growth. the occurrence of two-way causation between energy consumption and the growth of the economy lends credibility to the feedback hypothesis, as demonstrated by (masih and masih, 1997), (mahadevan and asafu-adjaye, 2007), (oh and lee, 2004) in the long run, (ozturk et al., 2010) (rahman, 2021), (le and sarkodie, 2020), (campo and sarmiento, 2013) and (brini et al., 2017) in the short-run. as per the neutrality hypothesis, energy usage is a negligible element of a country’s total output and so has minor or no influence on the growth of the economy. the neutrality hypothesis has been supported by (huang et al., 2008; hondroyiannis et al., 2002, and eyuboglu and uzar, 2021). finally, the conservation hypothesis claims that limiting energy use has no destructive effect on the growth of the economy. this hypothesis is verified if there is one-way causation between economic expansion to energy usage. it has been supported by (hsiao, 1981), (asafu-adjaye, 2000), (zachariadis, 2007), (magazzino, 2018), and (almozaini, 2019). 2.2. energy consumption and public debt only a few researchers have looked at the effect of government debt on energy usage. ziaei (2012) investigated the impact of government debt on energy consumption in 15 european countries over the period from 1995 to 2011 using the gmm model. the study reveals that investment, inflation and government debt have positive and significant impacts on energy consumption. sun and liu (2020) studied the impact of debt whether private or public on energy consumption in china using annual data over the period from 1996 to 2016 by employing the lmdi model. the study found that private debt per capita had a favorable influence and contributed the most to china’s energy consumption. concerning government debt, it has a detrimental influence on energy use. hashemizadeh et al. (2021) used fgls and pcse models to investigate the influence of public debt on renewable energy usage in 20 emerging nations from 1990 to 2016. the main findings of the study show that public debt and trade openness have unfavorable significant influences on renewable energy use in eight nations, while they have direct significant impacts in indonesia and the republic of korea. economic growth, on the other hand, has a favorable and substantial influence on renewable energy use in eleven nations and a significantly negative impact in three countries. to the best of our knowledge, the study of the linkage between disaggregated energy use and public debt is currently insufficient, and the results obtained are also inconclusive. as a result, further research is required to address the energy-debt nexus argument. raouf: public debt – energy consumption nexus international journal of energy economics and policy | vol 12 • issue 5 • 2022148 there are no studies that assess the consequences of public debt on renewable and non-renewable energy use. as a result, our research will fill in the gaps in the current literature. 3. data, model, and methodology 3.1. model specification and data sources as earlier literature paid less attention to the debt-energy consumption nexus, this paper investigates the influence of government debt (pd) on both renewable (ren) and non-renewable energy (nre) consumption in oecd countries. there are additionally four control variables: gdp growth rate (gdpg), trade openness (open) as a percentage of gdp, inflation rate (inf) and population growth rate (popg). two models have been constructed using previous studies to achieve the main objective of this study. 0 1 2 3 4 5 tre pd gdpg inf open popgβ β β β β β= + + + + + +∈ (1) 0 1 2 3 4 5 t nre pd gdpg inf open popg µ =∝ + ∝ + ∝ + ∝ + ∝ + ∝ + (2) this study is based on yearly data and covers the period from 1980 to 2020 for 17 oecd countries: austria, belgium, denmark, france, germany, spain, sweden, switzerland, greece, luxembourg, netherlands, norway, iceland, ireland, italy, portugal, united kingdom, and the us. the sample was chosen based on data availability. there are two main dependent variables, non-renewable energy (nre) and renewable energy (re) consumption. both sources of energy are measured in exajoules, and the data comes from the bp statistical review of world energy. public debt (pd) as a percentage of gdp, is the major independent variable, and data is acquired from the global debt database. the data for the control variables (gdp growth rate, trade openness, population growth rate, and inflation rate) is retrieved from the world development indicators. table 1 displays descriptive statistics for the underlying variables. 3.2. econometric model to investigate the influence of government debt on both renewable and nonrenewable energy use, which was introduced in the previous subsection, estimated generalized least squares and quantile regression models are to be used. 3.2.1. generalized least squares (gls) as a first step, the egls (estimated generalized least squares) estimator will be used. when one of the key assumptions of the gauss-markov theorem, namely homoscedasticity and the lack of serial correlation, is broken, the generalized least squares approach is employed to cope with the scenario where the ols estimator is not blue (best linear unbiased estimator). if the other requirements of the gauss-markov theorem are fulfilled, the gls estimator is blue. the goal of this paper is to estimate the parameters of a linear-panel model using generalized least squares approaches, which can handle the problems of correlation and heteroscedasticity (bamati and raoofi, 2020). in the beginning, equations (1) and (2) are estimated by the ols method, and the results indicate that there is an autocorrelation problem. as a result, gls is needed to eliminate autocorrelations. 3.2.2. panel quantile regression (pqr) t h e b u l k o f t h e e x i s t i n g e m p i r i c a l s t u d i e s o n e n e rg y consumption determinants assume parameter homogeneity and are based on ols and instrumental variables (iv) regressions, panel techniques, or matching estimators. furthermore, supposing that responsiveness across nations is identical may result in findings based on the entire population of countries being over-fitted to a specific subset of interest. in other words, if the data is biased due to heterogeneity, an empirical pattern discovered may have different implications for various groups of nations. as a result, using quantile regression would be preferable (dufrenot et al., 2010). in this section, panel quantile regression will be used to verify the validity and reliability of the results by estimating the parameters at various points along with the (conditional) energy consumption. koenker and bassett (1978) were the first to propose the panel quantile regression. the key benefit of employing the pqr is that it helps to reduce outlier biases, and the panel quantile regression is more reliable than ordinary least squares estimators when the residual components are not distributed normally (gozgor et al., 2018). more importantly, the repercussions of public debt, gdp growth rate, population growth rate, trade openness, and inflation rate may vary depending on the extent of energy usage. many empirical studies employ quantile regression analysis, where the variables may have varied (or differing) impacts at various points in the conditional distribution of the dependent table 1: variables’ descriptive statistics gdpg inf nre pd popg ren open mean 2.056673 3.652950 8.370473 64.57497 0.537504 0.205101 86.73432 median 2.134453 2.291701 2.072249 58.53426 0.476504 0.022630 68.66328 maximum 25.17625 27.21275 95.31857 211.2147 2.890960 5.709858 380.1042 minimum −10.82289 −5.213920 0.104818 4.063845 −1.853715 0.000000 16.60391 std. dev. 2.753817 4.333871 19.47829 33.49581 0.505680 0.586522 57.66317 skewness 0.104347 2.338171 3.626772 0.940056 0.820413 5.847098 2.220583 kurtosis 12.94235 9.528172 14.87708 4.203347 5.913316 43.95693 9.193049 jarque-bera 2863.801 1867.384 5608.619 144.2955 323.7459 52536.91 1681.837 probability 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 sum 1429.388 2538.801 5817.479 44879.61 373.5650 142.5449 60280.35 sum sq. dev. 5262.954 13035.01 263306.4 778646.9 177.4646 238.7417 2307578. observations 695 695 695 695 695 695 695 raouf: public debt – energy consumption nexus international journal of energy economics and policy | vol 12 • issue 5 • 2022 149 variable. these heterogeneous effects have been shown to provide important information that can’t be identified using traditional mean regression approaches like the ordinary least-squares (ols) method. pqr may also be used to investigate the non-linear effects of regressors on a dependent variable (albulescu et al., 2019). given a set of independent variables xit, illustrated in equations (1) and (2), the conditional distribution of the dependent variable can be written as the tth quantile (0< t <1), such that: 0( )it it t itq nre xτ τ µ=∝ + ∝ + ∝ (3) 0( )it it t itq re xτ τβ β β µ= + + (4) 4. results it can be concluded from table 2 that, according to the gls model, in column (1), the influence of public debt on renewable energy use is favorable and statistically significant. this indicates that the debt incurred by the public sector of the group of countries under consideration is geared toward investments in renewable energy sources. this result is consistent with that of florea, maria, puiu, manta, and berceanu (2021). it has been shown that the gdp growth rate has a statistically significant negative influence on the utilization of renewable energy, as found by giraud and kahraman (2014) and matei (2018), reflecting either a deficiency of investment in renewable energy or the presence of an undeveloped energy sector in some of these countries. the results also indicate that population growth has a favorable and considerable influence on renewable energy consumption. inflation and trade openness, on the other hand, have major negative effects on renewable energy usage. the ability of countries under consideration to import advanced technology is enabled by trade openness. the use of advanced techniques reduces the energy intensity. the economic consequences of deploying sophisticated technologies include using less energy and producing more output, which is referred to as the technique effect (shahbaz et al., 2014). the quantile regression results represented in columns (2), (3) and (4) give clarification and/or support for the results of the generalized least squares (gls) model. the panel quantile regression findings are really intriguing. table 2 shows that public debt has a more favorable impact on renewable energy usage in the higher quantiles. according to the quantile regression estimates at the 25th quantile, public debt and population growth rate have no significant influence on renewable energy use. in terms of the 50th and 75th quantiles, the findings are comparable to those of the gls model. in general, the gls and quantile regression analysis indicate that overall public debt plays an important role in increasing renewable energy consumption in oecd member nations. regarding the utilization of non-renewable energy, it can be noticed from the results of the gls model, illustrated in table 3, that public debt has a major detrimental influence on nonrenewable energy use. when the government debt increases, it is expected that long-term interest rates will rise, and hence investment and table 2: results of the estimation of the egls and quantile regression models for renewable energy consumption egls (1) quantile regression 0.25 (2) 0.5 (3) 0.75 (4) c 0.120403* 1.859701* 3.557820* 14.68386* pd 0.001402* 0.008044 0.043742* 0.054343* gdpg −0.003876* −0.133933 −0.479526* −0.945584* popg 0.031477* 1.060680 2.199021** 15.84622* open −0.000568* −0.011291** −0.017632* −0.118069* inf −0.006430* −0.151395* −0.314326* −1.207971* r-squared 73.11% **significant at 5%, *significant at 1% table 3: results of the estimation of the egls and quantile regression models for non-renewable energy consumption egls (1) quantile regression 0.25 (2) 0.5 (3) 0.75 (4) c 11.69472* 2.157124* 4.916381* 13.18071* pd −0.005049* −0.000514 0.008495 −0.019081* gdpg 0.064359* 0.002431 −0.01477 0.076979 popg 2.450302* 0.448526 1.64597* 4.32358* open −0.069355* −0.011791* −0.029832* −0.067520* inf −0.114411* 0.058883* −.165379* −0.351290* r-squared 89.3% **significant at 5%, *significant at 1% consumption will decrease. consequently, non-renewable energy consumption will decrease, and production will decrease as well. gdp growth rate and population growth rate have significant positive impacts on non-renewable energy consumption. finally, inflation and trade openness have significant negative impacts on the use of non-renewable energy. according to the quantile regression estimates at the 25th quantile, public debt has a negative insignificant impact, while at the 50th quantile, the impact is positive and insignificant, and finally, with respect to the 75th quantile, public debt has an adverse and minor influence on the usage of nonrenewable energy. the coefficient of gdp growth rate is positive for the 25th and 75th quantiles and significant for the 75th quantile only. it is negative and insignificant for the 50th quantile. the population growth rate has a positive coefficient for the three quantiles, but it is relevant only for the 50th and 75th quantiles. the coefficient of trade openness is negative and significant for all quantiles. finally, the inflation rate has a negative and significant coefficient for the 50th and 75th quantile and positive and significant for the 25th quantile. it can be noticed from table 3 that all variables have more favorable impacts on renewable energy usage in the higher quantiles. 5. conclusion and policy recommendations in many countries, the rapid economic expansion raises the need for energy, coupled with the fact that increased energy usage at the expense of environmental quality has become a major concern for these economies. many countries have faced substantial issues raouf: public debt – energy consumption nexus international journal of energy economics and policy | vol 12 • issue 5 • 2022150 because of global warming and climate change. these growing concerns have driven several developed and emerging countries to seek an alternate energy source to fulfill their overall energy demands while also dealing with the threat posed by the effects of global warming and rising carbon emissions. renewables play an important role in reducing carbon emissions, ensuring the security of the supply of energy, and achieving economic progress. furthermore, the move from nonrenewable to renewable sources entails financial obligations, which many governments borrow to fulfill this requirement. as a result, the goal of this research is to look at the link between public debt and renewable and nonrenewable energy usage. to accomplish this goal, gls and quantile regression models have been employed for a set of 17 oecd countries for the period 1980-2020. the key findings of this study indicate that public debt has a positive effect on renewable energy usage while having a devastating impact on the utilization of non-renewable energy. the country’s growth rate has a negative influence on renewable energy while having a good impact on non-renewable energy consumption. the inflation rate and trade openness have negative and significant impacts on energy consumption, whether renewable or non-renewable. finally, with respect to the population growth rate, it has a favorable and considerable influence on both renewable and non-renewable energy use. a number of policy recommendations have been made as a result of the current findings. policymakers should take the advantage of directing public debt to encourage using and investing in the renewable energy sector and try to substitute renewable energy for non-renewable energy. to encourage the use of renewable energy, the government debt should be allocated to renewable energy investment projects. furthermore, the government should remove legal and regulatory barriers to private sector participation in renewable energy project development. private investment can be used to lower the countries’ governmental debt. references ahmed, s.a.e., osman, a.a.m. (2016), renewable energy advantages and disadvantages. international journal of research science and management, 3(10), 1-4. albulescu, c.t., tiwari, a.k., yoon, s.m., kang, s.h. (2019), fdi, income, and environmental pollution in latin america: replication and extension using panel quantiles regression analysis. energy economics, 84, 104504. almozaini, m.s. (2019), the causality relationship between economic growth and energy consumption in the world’s top energy consumers majed. international journal of energy economics and policy, 9(4), 40-53. asafu-adjaye, j. (2000), the relationship between energy consumption, energy prices and economic growth: time series evidence from asian developing countries. energy economics, 22(6), 615-625. bamati, n., raoofi, a. (2020), development level and the impact of technological factor on renewable energy production. renewable energy, 151, 946-955. belke, a.h., dreger, c., dobnik, f. (2012), energy consumption and economic growth-new insights into the cointegration relationship. ssrn electronic journal. brini, r., amara, m., jemmali, h. (2017), renewable energy consumption, international trade, oil price and economic growth inter-linkages: the case of tunisia. renewable and sustainable energy reviews, 76, 620-627. campo, j., sarmiento, v. (2013), the relationship between energy consumption and gdp: evidence from a panel of 10 latin american countries. latin american journal of economics, 50(2), 233-255. destek, m.a., aslan, a. (2017), renewable and non-renewable energy consumption and economic growth in emerging economies: evidence from bootstrap panel causality. renewable energy, 111, 757-763. dufrenot, g., mignon, v., tsangarides, c. (2010), the trade-growth nexus in the developing countries: a quantile regression approach. review of world economics, 146(4), 731-761. eyuboglu, k., uzar, u. (2021), asymmetric causality between renewable energy consumption and economic growth : fresh evidence from some emerging countries. environmental science and pollution research, 29(15), 2189-21911. florea, n.m., maria, r., puiu, s., manta, a.g., berceanu, d. (2021), linking public finances ’ performance to renewable-energy consumption in emerging economies of the european union. sustainability, 13(11), 6344. giraud, g., kahraman, z. (2014), how dependent is growth from primary energy ? output energy elasticity in 50 countries. the dependency ratio of energy, 33, 1-21. gozgor, g., lau, c.k.m., lu, z. (2018), energy consumption and economic growth: new evidence from the oecd countries. energy, 153, 27-34. hondroyiannis, g., lolos, s., papapetrou, e. (2002), energy consumption and economic growth: assessing the evidence from greece. energy economics, 24(4), 319-336. hsiao, c. (1981), autoregressive modelling and money-income causality detection. journal of monetary economics, 7(1), 85-106. huang, b.n., hwang, m.j., yang, c.w. (2008), causal relationship between energy consumption and gdp growth revisited: a dynamic panel data approach. ecological economics, 67(1), 41-54. kabuga, n.a., mohammed, s.t. (2021), nexus between energy consumption and economic growth in nigeria. dutse international journal of social and economic research, 5(1), 10-20. koenker, r., bassett, g. (1978). regression quantiles. econometrica, 46(1), 33. le, h.p., sarkodie, s.a. (2020), dynamic linkage between renewable and conventional energy use, environmental quality and economic growth: evidence from emerging market and developing economies. energy reports, 6, 965-973. lee, c.c. (2005), energy consumption and gdp in developing countries: a cointegrated panel analysis. energy economics, 27(3), 415-427. magazzino, c. (2018), gdp, energy consumption and financial development in italy. international journal of energy sector management, 12(1), 28-43. mahadevan, r., asafu-adjaye, j. (2007), energy consumption, economic growth and prices: a reassessment using panel vecm for developed and developing countries. energy policy, 35(4), 2481-2490. maradin, d. (2021), advantages and disadvantages of renewable energy sources utilization. international journal of energy economics and policy, 11(3), 176-183. masih, a.m.m., masih, r. (1997), on the temporal causal relationship between energy consumption, real income, and prices: some new evidence from asian-energy dependent nics based on a multivariate cointegration/vector error-correction approach. journal of policy modeling, 19(4), 417-440. matei, i. (2018), is there a link between renewable energy consumption and economic growth? a dynamic panel investigation for the oecd raouf: public debt – energy consumption nexus international journal of energy economics and policy | vol 12 • issue 5 • 2022 151 countries. revue d’economie politique, 127(6), 985-1012. nkoro, e., ikue-john, n. (2020), bussecon review of social sciences energy consumption and economic growth in nigeria : a revisit of the energy-growth debate. bussecon review of social sciences, 1(2), 1-9. oh, w., lee, k. (2004), causal relationship between energy consumption and gdp revisited: the case of korea 1970-1999. energy economics, 26(1), 51-59. ozturk, i., aslan, a., kalyoncu, h. (2010), energy consumption and economic growth relationship: evidence from panel data for low and middle income countries. energy policy, 38(8), 4422-4428. qi, w., huang, z., dinçer, h., korsakiené, r., yüksel, s. (2020), corporate governance-based strategic approach to sustainability in energy industry of emerging economies with a novel interval-valued intuitionistic fuzzy hybrid decision making model. sustainability, 12(8), 3307. rahman, m.m. (2021), the dynamic nexus of energy consumption, international trade and economic growth in brics and asean countries: a panel causality test. energy, 229, 120679. rahman, m.m., mamun, s.a.k. (2016), energy use, international trade and economic growth nexus in australia: new evidence from an extended growth model. renewable and sustainable energy reviews, 64, 806-816. shahbaz, m., nasreen, s., ling, c.h., sbia, r. (2014), causality between trade openness and energy consumption: what causes what in high, middle and low income countries. energy policy, 70, 126-143. sun, x., liu, x. (2020), decomposition analysis of debt’s impact on china’s energy consumption. energy policy, 146, 111802. wang, e.z., lee, c.c. (2022), the impact of clean energy consumption on economic growth in china: is environmental regulation a curse or a blessing? international review of economics and finance, 77, 39-58. zachariadis, t. (2007), exploring the relationship between energy use and economic growth with bivariate models: new evidence from g-7 countries. energy economics, 29(6), 1233-1253. zhe, l., yüksel, s., dinçer, h., mukhtarov, s., azizov, m. (2021), the positive influences of renewable energy consumption on financial development and economic growth. sage open, 11(3), 1-10. ziaei, s.m. (2012), energy consumption in relation to government debt, inflation and investment in selected european countries. international journal of energy environment and economics, 20(5), 389-393. _goback ole_link1 tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 4 • 2021 461 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(4), 461-469. transition of electric mobility in colombia: technical and economic evaluation of scenarios for the integration of e-taxis in bucaramanga yecid alfonso muñoz maldonado1*, césar acevedo1, edward jerez1, carlos sarmiento1, miguel de la rosa1, adalberto ospino2 1autonomous university of bucaramanga unab, colombia, 2university of the coast cuc, colombia. *email: ymunoz294@unab.edu.co received: 15 january 2021 accepted: 01 may 2021 doi: https://doi.org/10.32479/ijeep.11084 abstract globally, the transport sector has been directed towards electric mobility by policies, regulations, development strategies and economic incentives. the transport sector has an important strategic role in the economic development of a country, the sustainability of this sector has an impact on political and scientific discussions due to its environmental impact. in colombia, the global targets for reducing polluting emissions begin to drive the renewal of the automotive park towards electric mobility, therefore, this research was carried out with the aim of carrying out a technical and economic analysis of scenarios for the e-taxis in bucaramanga, the incentives applied in the two projects developed in the two most important cities of colombia were taken as the basis to compare possible implementation scenarios in the short and medium term. three technologies (gasoline, gas and electric) were evaluated that were tested using the tac/km indicator, the financial viability was assessed based on two financial kindness criteria (npv and irr). the results obtained allow to conclude two strategies that make it possible to incorporate the e-taxis in bucaramanga, (1) exemption from payment of taxi registration, in case of incorporation of a new vehicle; (2) economic incentive of more than 20% at the time of purchase of the ev, accompanied by a 25% increase in the cost of the minimum service fee, in the case of the replacement of a taxi. keywords: electric taxi colombia, e-taxi policies, electric mobility, electric vehicle, public transport sector jel classifications: q01, q4, q42 1. introduction the transport sector has an important strategic role in the economic development of a country, the sustainability of this sector has an impact on political and scientific discussions. the negative environmental impact of the massive flow of goods and people, the use of fossil fuels and the fleet of vehicles in old age, deteriorate air quality, being the main motivation for political and scientific debates (carteni et al., 2020). diversification in the energy matrix that supplies the transport sector is relevant to introduce itself to electric mobility, even if it presents new risks, technological challenges, and commercial trends (nieuwenhuis et al., 2020). the world estimates 1 billion vehicles and only 1% of these are electric vehicles, yet world leaders in the car market such as china, europe and the usa are developing and implementing subsidies and public policies to enable the procurement of electric vehicles more easily (henderson, 2020; iea, 2018), in turn, there is a great deal of public intervention in new commercial trends in supply chains, renewable and non-renewable energy supplies, and the adaptation of urban spaces for the recharging of electric vehicles (henderson, 2020; keith et al., 2019; kuby, 2019). for colombia, global emission reduction targets are beginning to drive the renovation of the automotive park to electric mobility in this journal is licensed under a creative commons attribution 4.0 international license maldonado, e t al.: transition of electric mobility in colombia: technical and economic evaluation of scenarios for the integration of e-taxis in bucaramanga international journal of energy economics and policy | vol 11 • issue 4 • 2021462 some of its major cities, focusing on the public transport sector. this research presents a technical and economic analysis of scenarios for the integration of electric taxis in bucaramanga, one of the five most important cities in colombia. 2. an approach to global electric mobility globally, the transport sector has been directed towards electric mobility using policies, regulations, development strategies and economic incentives. table 1 presents a list of relevant incentives, policies, regulations, and strategies in countries that have already begun the transition to electric mobility with the vision of promoting the use of electric vehicles and reducing polluting emissions. 3. electric mobility in colombia colombia detected that its automotive park has potential for improvement to contribute to the 20% reduction in polluting emissions by 2030, according to the united nations conference on climate change (la república, 2018), because the average age of vehicles in colombia is approximately 16 years according table 1: global benchmarks of incentives, policies, and strategies to promote the use of electric vehicles country city/state incentives, policies, and strategies italy (scorrano et al., 2020) florence ecobonus: $4,513.62 6,770.43 usd 70 free taxi records government subsidy for the purchase of electric vehicle netherlands (dam et al., n.d.) amsterdam privileges at busy taxi stations such as leidseplein station subsidy of $11,291.15 usd for purchase of electric taxis italy (danielis et al., 2018) subsidy of $5,645.48 usd for electric vehicle purchase annual grant of $451.61 usd for parking and vehicle recharging locations france (crist, 2012) paris subsidy of $5,645.48 usd for electric vehicle purchase south korea (park et al., 2014) 50% discount allowance for electric taxi purchases from taxi service providers usa (park et al., 2014) subsidy of $7,500 usd for purchase of electric vehicles subsidies for the installation of wallbox for electric vehicle buyers china (yang et al., 2018) changsha subsidy of $254.26 usd/kwh of vehicle battery capacity. china (yang et al., 2018) beijing the policy is specifically designed to subsidize the adoption of bev in the taxi fleet and shorten the life of combustion gas vehicle (cgv) taxis from 8 to 6 years. if a cgv taxi is withdrawn within 7 years, you can receive a minimum subsidy of ¥10,000 per vehicle and tax exemption on the purchase in addition to government subsidies china (li et al., 2016) shenzhen government program that incentivizes: research and development of electric vehicles, charging infrastructure and new business/ utility models subsidies on the purchase of electric vehicles china (yang et al., 2013) policies, regulations and strategies (2001-2012) for electric vehicles managed by the ministry of industry and information technology of the people’s republic of china, national development and reform commission, ministry of science and technology of the people’s republic of china and the ministry of finance of the people’s republic of china china (zheng et al., 2012) governance plan called “plan of shaping and revitalizing the auto industry” it was developed in 13 cities in china the goal was to manufacture 0.5 million vehicles with alternative fuels in 3 years norway (mersky et al., 2016) oslo exemption from registration tax free public parking is possible on site toll exemptions iva exemption access to the bus lane reduced ferry fares charging station constructions united states (america, 2019; zhang et al., 2014) california, washington, massachusetts, new jersey, oregon, colorado, montana, south carolina economic incentives from $500 usd to $6,000 usd reflected in: income tax credit, sales tax exemption, purchase rebate, conversion cost credits and high-occupancy vehicle lane canada (hardman et al., 2017) economic incentives from $3,850 usd $6,850 usd at points of sale germany (hardman et al., 2017) $5,500 usd economic incentives at points of sale japan (hardman et al., 2017) $7,800 economic incentives reflected in points of sale and iva exemption netherlands (hardman et al., 2017) economic incentives between $1,110 22,000 usd in sales taxes and iva exemptions united kingdom (hardman et al., 2017) economic incentives between $7,500 -10,000 usd at points of sale maldonado, e t al.: transition of electric mobility in colombia: technical and economic evaluation of scenarios for the integration of e-taxis in bucaramanga international journal of energy economics and policy | vol 11 • issue 4 • 2021 463 to the colombian association of motor vehicles (andemos) (dinero, 2016), the colombian government has made efforts to promote the renovation of the motor park through pilot projects in cities of the country with a focus on taxi fleet companies (tfc), independent taxi drivers and the mass transit sector (electric buses) (sclar et al., 2020). the main projects that colombia has developed to promote the transition of the transport sector to electric mobility are the project of bogotá and project of medellin. 3.1. project of bogota the project of bogota consisted of the pilot operation of 50 e-taxis within the city without the mobility restrictions and the exemption from registration1 applied to conventional taxis, with a temporality of 3 years from the validity of the 677 of 2011 (de bogotá, 2011), then the current term was extended 2 years by district decree 407 of 2012 (de bogotá, 2012), for a total of 5 years, which was subsequently extended again for 5 years more, for a total of 10 years, by district decree 376 of 2013 (de bogotá, 2013). 3.2. project of medellin the project of electric taxis in medellin was presented on may 3, 2019 by the mayor of medellin and the company “empresas públicas de medellín (epm),” in order to introduce 1500 electric taxis in its first 3 years through the replacement of taxis that use conventional fuels such as gasoline. epm provided an economic incentive of $5,584.13 usd to offset an electric vehicle’s increased initial investment than internal combustion engine vehicles (ice). in addition, resolution 2019500009417 issued by the medellin mobility secretary determined that the minimum fare for individual motor land-based public transportation for passengers in electric vehicles is worth $2.07 usd different from the $1.67 fare that conventional taxis have (alcaldía de medellín, 2019). the incentives have generated a great reception by conventional taxi owners to migrate to the electric vehicle, and by users who positively value their comfort. 4. technical and economic evaluation for the integration of e-taxis in bucaramanga to technically evaluate the integration of electric vehicles in the transport sector of bucaramanga, it was decided to apply a tfc that had a long history in this sector, this tfc has 31 taxis that use two types of fuel: gas and gas, where its most representative vehicle model is the hyundai i10. the limited time of use to test the ten tfc vehicle sample gave way to a characteristic route. the development of the characteristic route was made from a heat map with the most frequent routes or routes used by taxi2 drivers. the mobile application “my track” was the tool used for the acquisition of data measured in real time during each day of the taxi travel, the data obtained were processed using the map source and microsoft excel software (3d map add-on), where the first software extracted the coordinates 1 pay-per-seater for operate as a taxi public service vehicle. 2 the average distance traveled in a day by a taxi driver is 200 km/day. of the routes made by the taxi sample and through the microsoft excel 3d map add-in the information was examined to obtain the route overlay and thus the heat map that subsequently allowed the obtaining of the characteristic route. three vehicles with different technologies were used (table 2) to simultaneously route the characteristic route, making appropriate measurements to determine actual energy consumption and associated costs. the selected vehicles were evaluated in six scenarios as shown in table 3, global considerations were assumed for all scenarios and some particular considerations varying by scenario (table 4). the financial kindness procedures chosen to evaluate the scenarios were net present value (npv) and internal rate of return (irr). table 2: technical specifications for selected vehicles technical specifications gasoline gas electric model hyundai i10 hyundai i10 byd e5 cylinder (cc) 1245 1245 battery capacity (kwh) 60 power (cv) 87 87 160 torque (nm) 120 120 310 table 3: scenarios to be evaluated in each period scenarios initial year final year 1. new taxi, natural person. 2019 2028 2. tfc vehicle replacement. 2019 2028 3. taxi replacement, natural person. 2019 2028 4. new taxi, natural person. 2026 2035 5. tfc vehicle replacement. 2026 2035 6. taxi replacement, natural person. 2026 2035 table 4: global and particular considerations global considerations 3.1. project life of 10 years 3.2. initial investment of 100% without bank financing 3.3. projected maintenance and operating costs from the 4.42% consumer price index (cpi) (historical average 2003 2019). usd 31/12/2019 (colombia, 2019) 3.4. 15% discount rate. 3.5. scenarios 4, 5 and 6 consider the technological maturation of batteries, therefore the price of the vehicle decreases (fraileardanuy et al., 2018) particular considerations a. tfc assumes operating and maintenance costs b. the taxi is driven by its owner c. exemption from the cost of registration (project of bogotá) d. cost of fuel assumed by the driver e. tfc owns the taxi records f. $5,584 incentive for purchasing an electric vehicle (project of medellin) g. the driver has his taxi record h. initial investment is equal to the cost of the vehicle ⅰ. the driver’s daily income is $45.773 usd j. tfc gets $24.41 usd of daily driver’s fare k. the driver’s daily income is $59.33 usd (projected from the average historical cpi 2003-2019) l. tfc gets the daily driver’s rate of $31.64 usd (projected from the average historical cpi 2003-2019) 3 direct private interviews with tfc taxi drivers made it possible to know the average value of their daily income. maldonado, e t al.: transition of electric mobility in colombia: technical and economic evaluation of scenarios for the integration of e-taxis in bucaramanga international journal of energy economics and policy | vol 11 • issue 4 • 2021464 below are the equations used to economically evaluate the scenarios raised previously, thus obtaining the maintenance costs (table 5), costs per operation (table 6) and the initial investment for the purchase of a taxi according to the type of energy (table 7): cma=cmm+cmsfll+cmea+cme (1) where, cma: annual maintenance cost (usd/year), cmm: cost per maintenance of the engine (usd/year), cmsfll: cost for suspension maintenance, brakes and tires (usd/year), cmea: cost for maintenance of structure and accessories (usd/ year), cme: cost for electrical maintenance (usd/year). coa=ca+cst+ct+csoat+cto (2) where, coa: cost per annual operation (usd/year), ca: administration cost (usd/year), cst: insurance taxi cost (usd/ year), ct: cost per techno-mechanical review (usd/year), csoat: cost per soat (usd/year), cto: cost per trading card (usd/year). ccrc crc pc rc � � (3) where, ccrc: fuel cost per kilometer according to characteristic route (usd/km), crc: characteristic route consumption (gal; m3; kwh), pc: fuel price (usd/gal; usd/m3; usd/kwh), rc: characteristic route distance (km). ta=td×da (4) where, ta: annual work (km/year), td: daily work 200 (km/day), da: working days per year (day/year), 312 day/year. cca=ta×ccrc (5) where, cca: annual fuel cost (usd/year). tac cm co cc tac cm co cca a a i a a aii i� � � � � ��; (6) where, tac: total annual cost (usd/year), i: year in which it is evaluated. tac km tac ta tac km tac tai i= =; / (7) where, tac/km: total annual cost per kilometer traveled over the life of the vehicle (usd/km). 5. results the heat map (figure 1) shows the overlap of the routes made by the monitored vehicles, determining the characteristic route (figure 2) that was traveled to establish the comparison of the consumption of the vehicles for each type of technology, table 8 exposes the results obtained. table 9 shows the annual fuel costs calculated for the three types of vehicles (gasoline, gas and electric) from the characteristic route and the consumption required to travel. table 10 summarizes the results obtained by evaluating the 6 scenarios presented as global, particular, and financial kindness criteria (npv and irr). in the financial comparison of scenario 1 (figure 3) it was observed that for a natural person, the most viable option based on the npv (gasoline $9,706,750 usd; gas $17,827.31 usd; electric $7,660,860 usd) is to buy a taxi that uses gas as energy; however, if an incentive such as the project of bogota is applied, purchasing table 6: costs per operation for 2019 operational requirements gasoline gas electric usd % usd % usd % administration $201.40 28.8 $201.40 28.8 $201.40 30.1 insurance $256.32 36.6 $256.32 36.6 $256.32 38.3 technomechanics $60.45 8.6 $60.45 8.6 $30.22 4.5 soat4 $120.23 17.2 $120.23 17.2 $120.23 18.0 operation card $61.03 8.7 $61.03 8.7 $61.03 9.1 total annual cost $699.42 100 $699.42 100 $669.20 100 table 7: initial investment for the purchase taxi according to the energy item gasoline gas5 electric vehicle price $15,867 $16,632 $32,650 taxi registration (ministerio de transporte., 2001) $27,463 $27,463 $27,463 initial investment $43,330 $44,095 $60,113 table 5: maintenance costs for 2019 system gasoline gas electric usd % usd % usd % engine $588.9 62.9 $619.4 64.0 $96.9 24.1 suspension, brakes, and rims $212.9 22.7 $212.9 22.0 $172.0 42.8 structure and accessories $36.6 3.9 $36.6 3.8 $35.1 8.7 electronic $98.3 10.5 $98.3 10.2 $98.3 24.4 total annual cost $937 100 $967 100 $402 100 figure 1: heat map of the route overlay from the tfc sample 4 compulsory traffic accident insurance (soat). 5 the additional cost of the gas vehicle is due to the cost per conversion to this fuel. maldonado, e t al.: transition of electric mobility in colombia: technical and economic evaluation of scenarios for the integration of e-taxis in bucaramanga international journal of energy economics and policy | vol 11 • issue 4 • 2021 465 table 8: actual consumption according to characteristic route aspect gasoline gas electric consumption 4,520 (gal) 13.228 (m3) 31,462 (kwh) characteristic route 44.6 (km) 44.6 (km) 44.6 (km) table 9: fuel costs for 2019 fuel price unit daily consumption unit annual cost6 unit gasoline $2.78 (usd/ gal) 4.520 (gal) $3,916 (usd) gas $0.46 (usd/ m3) 13.228 (m3) $1,888 (usd) electric $0.16 (usd/ kwh) 31.462 (kwh) $1,616 (usd) figure 2: characteristic route an electric taxi is the best option considering the npv (gasoline $9,706,750 usd; gas $17,827.31 usd; electric $35,123.83 usd). figure 4 presents the financial comparison of scenario 2 that the most viable option for the tfc is to buy a taxi that uses gasoline as energy according to the npv (gasoline $19,174.29 usd; gas $18,231.41 usd; electric $ 11,278.74 usd), although if policies are integrated as in the project of medellín, buying an electric taxi is the best alternative depending on the npv (gasoline $19,174.29 usd; gas $18,231.41 usd; electric $21,958.78 usd). the financial comparison of scenario 3 (figure 5) presents the replacement of a taxi driver’s vehicle, in which it was detailed that the most viable option according to the npv (gasoline $37,169.72 usd; gas $45,290.28 usd; electric $35,123.83 usd) is to renew your vehicle for one that uses gas as fuel, however, if policies such as the project of medellin are incorporated, the best choice according to the npv (gas $37,169.72 usd; gas $45,290.28 usd; gasoline electric $46,038.90usd) are electric vehicle and gas vehicle. in the financial comparison of scenario 4 (figure 6) it was observed that for a natural person, the most viable option is to buy a taxi that use electricity as energetic according to the npv (gasoline $18,536.42 usd; gas $18,788.64 usd; electric $25,611.36 usd). figure 7 presents the financial comparison of scenario 5 it was determined that for the tfc, the most viable option is to buy a taxi that uses electricity as energy according to the npv (gasoline $12,233.71 usd; gas $11,049.82 usd; electric $27,426.84 usd). the financial comparison of scenario 6 (figure 8) presents the replacement of a taxi driver’s vehicle, in which it was detailed that the most viable option according to the npv (gasoline $54,271.30 usd; gas $54,517.66 usd; electric $58,988.94 usd) is to renew your vehicle for one that uses electricity as energy. as a result, the tac/km is presented, which is set out in figure 9, demonstrating that electric vehicles have a positive gap that tends to increase relative to ice vehicles over the years. table 10: results obtained for each scenario evaluated according to particular considerations and financial kindness criteria scenarios particular considerations fuel type per vehicle initial investment (usd) npv (usd) irr (%) 1 b-c-i gasoline $43,330.46 $9,706,750 17 gas $44,094.55 $17,827.31 19 electric $60,113.39 $7,660,860 16 electric (proj. bog) $32,650.42 $35,123.83 24 2 a-d-e-f-j gasoline $15,867.49 $19,174.29 24 gas $16,631.58 $18,231.41 24 electric $32,650.42 $11,278.74 18 electric (proj. medellin) $21,970.38 $21,958.78 23 3 b-d-f-g-h-i gasoline $15,867.49 $37,169.72 30 gas $16,631.58 $45,290.28 31 electric $32,650.42 $35,123.83 24 electric (proj. medellin) $21,970.38 $46,038.90 29 4 b-d-k gasoline $56,168.84 $18,536.42 18 gas $57,159.31 $18,788.64 18 electric $62,817.53 $25,611.36 19 5 b-d-g-h-k gasoline $20,568.87 $12,233.71 20 gas $21,559.34 $11,049.82 20 electric $29,550.16 $27,426.84 23 6 a-d-e-h-l gasoline $20,568.87 $54,271.30 31 gas $21,559.34 $54,517.66 30 electric $29,550.16 $58,988.94 28 6 312 working days a year according to the direct private interviews with tfc taxi drivers. maldonado, e t al.: transition of electric mobility in colombia: technical and economic evaluation of scenarios for the integration of e-taxis in bucaramanga international journal of energy economics and policy | vol 11 • issue 4 • 2021466 figure 4: scenario 2 financial comparison of vehicles (gasoline, gas and electric) figure 3: scenario 1 financial comparison of vehicles (gasoline, gas and electric) figure 5: scenario 3 financial comparison of vehicles (gasoline, gas and electric) maldonado, e t al.: transition of electric mobility in colombia: technical and economic evaluation of scenarios for the integration of e-taxis in bucaramanga international journal of energy economics and policy | vol 11 • issue 4 • 2021 467 figure 8: scenario 6 financial comparison of vehicles (gasoline, gas and electric) figure 6: scenario 4 financial comparison of vehicles (gasoline, gas and electric) figure 7: scenario 5 financial comparison of vehicles (gasoline, gas and electric) maldonado, e t al.: transition of electric mobility in colombia: technical and economic evaluation of scenarios for the integration of e-taxis in bucaramanga international journal of energy economics and policy | vol 11 • issue 4 • 2021468 figure 9: total cost per km by vehicle type 6. conclusions globally, the path to electric mobility has been laid out through policies, regulations, development strategies and economic incentives. china being a benchmark in the evolution of its motor park, driven by government plans with an emphasis on charging infrastructure, monetary stimulus, and r and d, migrating to a value chain generated from new business trends around electric vehicles. for its part, colombia belatedly entered the transition to electric mobility, starting in its two main cities, the project of bogotá with an unambitious goal did not have an exceptional start, making it necessary to extend the deadlines of special benefits; the project of medellin supported by the public company epm was more popular, associated with the increase in income received by taxi drivers, and the sustainable culture of its citizens. the analysis of the tac/km indicator for the city of bucaramanga showed for electric vehicles a positive gap with respect to ice vehicles, which tends to increase over the years, consistent with the results obtained in medium-term scenario analyses, where electric vehicles will be the most attractive product for taxi drivers and tfc’s. in this context, it is currently feasible to incorporate e-taxis, if any of these strategies are applied: (1) exemption from payment of taxi registration, in case of incorporation of a new vehicle, (2) economic incentive of more than 20% at the time of purchase of the ev, accompanied by a 25% increase in the cost of the minimum service fee, in the case of the replacement of a taxi. to increase the acceleration of the transformation of the colombian motor park and the integration of the community into commercial trends surrounding electric vehicles, the colombian government should carry out government programs that promote the capture of markets and electric vehicle technologies so that this niche market is globalized in colombia. future studies of electric mobility could cover topics on the charging infrastructure in colombia. references alcaldía de medellín. (2019), proyecto taxis eléctricos, p6. available from: https://www.medellin.gov.co/movilidad/images/taxis_ electricos/preguntas-frecuentes.pdf. america, plug in. (2019), state and federal incentives. united states: america, plug in. banco de la república-colombia. (2019), tasa representativa del mercado. available from: https://www.banrep.gov.co/es/ estadisticas/trm. carteni, a., henke, i., molitierno, c., errico, a. (2020), towards e-mobility: strengths and weaknesses of electric vehicles. united states: advances in intelligent systems and computing. p1383-1393. crist, p. (2012), electric vehicles revisited-costs, subsidies and prospects. available from: https://www.internationaltransport forum.org. dam, j., stam, r.d., van den hoed, r. (2019), a tool for monitoring a clean taxi stand in amsterdam executive summary. available from: http://www.hva.nl/bibliotheek/contact/contactformulier/contact. html. [last accessed on 2020 jun 11]. danielis, r., giansoldati, m., rotaris, l. (2018), a probabilistic total cost of ownership model to evaluate the current and future prospects of electric cars uptake in italy. energy policy, 119, 268-281. de bogotá, d. (2011), decreto 677 de 2011. p3. available from: https:// www.simbogota.com.co/pdf/decretos/2011_decreto 677 de 2011.pdf. de bogotá, d. (2012), decreto 407 de 2012. p2. available from: https:// www.simbogota.com.co/pdf/decretos/2012_decreto407de2012.pdf. de bogotá, d. (2013), decreto 376 de 2013. p3. available from: https:// www.alcaldiabogota.gov.co/sisjur/normas/norma1.jsp?i=54408 and dt=s. dinero. (2016), informe de andemos sobre la edad del parque automotor en colombia. available from: https://www.dinero.com/pais/articulo/ informe-de-andemos-sobre-la-edad-del-parque-automotor-encolombia/239736. fraile-ardanuy, j., castano-solis, s., álvaro-hermana, r., merino, j. (2018), using mobility information to perform a feasibility study and the evaluation of spatio-temporal energy demanded by an electric taxi fl eet. energy conversion and management, 157, 59-70. hardman, s., chandan, a., tal, g., turrentine, t. (2017), the effectiveness of financial purchase incentives for battery electric vehicles-a review of the evidence. renewable and sustainable energy reviews, 80, 1100-1111. henderson, j. (2020), evs are not the answer: a mobility justice critique maldonado, e t al.: transition of electric mobility in colombia: technical and economic evaluation of scenarios for the integration of e-taxis in bucaramanga international journal of energy economics and policy | vol 11 • issue 4 • 2021 469 of electric vehicle transitions. annals of the american association of geographers, 1(1), 1-18. iea. (2018), global ev outlook 2018. available from: https://www.iea. org/reports/global-ev-outlook-2018. keith, d.r., houston, s., naumov, s. (2019), vehicle fleet turnover and the future of fuel economy. environmental research letters, 14(2), 021001. kuby, m. (2019), the opposite of ubiquitous: how early adopters of fast-filling alt-fuel vehicles adapt to the sparsity of stations. journal of transport geography, 75, 46-57. la república. (2018), colombia ratifica acuerdo de parís frente al cambio climático. available from: https://www.larepublica.co/ economia/colombia-ratifica-acuerdo-de-paris-frente-al-cambioclimatico-2749718. li, y., zhan, c., de jong, m., lukszo, z. (2016), business innovation and government regulation for the promotion of electric vehicle use: lessons from shenzhen, china. journal of cleaner production, 134, 371-383. mersky, a.c., sprei, f., samaras, c., qian, z.s. (2016), effectiveness of incentives on electric vehicle adoption in norway. transportation research part d: transport and environment, 46, 56-68. ministerio de transporte. (2001), decreto número 172 de 2001. p123. available from: https://www.mintransporte.gov.co/descargar. php?idfile=125+ and cd=1 and hl=es and ct=clnk and gl=co. nieuwenhuis, p., cipcigan, l., sonder, h.b. (2020), the electric vehicle revolution. in: future energy. amsterdam: elsevier ltd. park, e., kim, h., han, e., kwon, s.j., yoo, k., ohm, j.y. (2014), analysis of electric-powered taxis: a cross national study. journal of renewable and sustainable energy, 6(6), 1-17. sclar, r., werthmann, e., orbea, j., siqueira, e., tavares, v., pinheiro, b., albuquerque, c., castellanos, s. (2020), the future of urban mobility: the case for electric bus deployment in bogotá, colombia. available from: https://www.urbantransitions. scorrano, m., danielis, r., giansoldati, m. (2020), mandating the use of the electric taxis: the case of florence. transportation research part a: policy and practice, 132, 402-414. yang, j., dong, j., hu, l. (2018), design government incentive schemes for promoting electric taxis in china. energy policy, 115(2), 1-11. yang, l., xu, j., neuhäusler, p. (2013), electric vehicle technology in china: an exploratory patent analysis. world patent information, 35(4), 4-11. zhang, x., xie, j., rao, r., liang, y. (2014), policy incentives for the adoption of electric vehicles across countries. sustainability (switzerland), 6(11), 8056-8078. zheng, j., mehndiratta, s., guo, j.y., liu, z. (2012), strategic policies and demonstration program of electric vehicle in china. transport policy, 19(1), 17-25. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 6 • 2021 1 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(6), 1-6. the causal relationship between fuel consumption, exchange rates and economic growth in south east sulawesi, indonesia manat rahim1*, pasrun adam2, heppi millia1, la ode suriadi1, la ode saidi2 1department of economics, universitas halu oleo, kendari, indonesia, 2department of mathematics, universitas halu oleo, kendari, indonesia. *email: arifmanat@gmail.com received: 17 may 2021 accepted: 22 august 2021 doi: https://doi.org/10.32479/ijeep.11518 abtract this article reports the results of a study examining the causal relationship between fuel consumption, exchange rates, and economic growth in southeast sulawesi, indonesia. the data used are annual time series data ranging from 1988 to 2016. the estimation results of the var model and the granger causality test indicate that the causal relationship that occurs is only a short-term causality, namely from fuel consumption to economic growth. keywords: fuel consumption, exchange rate, economic growth, var model, granger causality test jel classifications: c120, c320, e21, f31 1. intoroduction fuel (crude oil and natural gas) is a useful source of energy as raw material for industries: goods, electricity, and transportation (viljoen, 1979; adam et al., 2016; millia et al., 2020). in order to grow their industries, each country needs crude oil and gas. indonesia carries out import activities to meet domestic crude oil needs. the reason is the failure of domestic crude oil production to meet domestic industry needs. this practice of importing crude oil will lead to an increase in the cost of production. indonesia is one of the exporting countries for natural gas to fulfil global needs. as such, domestic stock of natural gas becomes scarce, causing the production costs to rise. the rise in these costs may lead to an increase in goods prices, affecting changes in other macroeconomic variables, among others, economic growth (adam et al., 2016). foreign currency, meanwhile, is a medium for international trade transactions. as the exchange rate of foreign currency appreciates (the exchange rate for domestic exchange rate depreciates), the prices of foreign goods in the domestic country become more expensive, while the prices of domestic goods abroad become cheaper. thus, exports can grow, and imports can decrease. this may lead to changes in the value of the trade balance, which ultimately can influence a country’s economic growth (mauro et al., 2008; mishkin, 2008; saidi et al., 2015; adam et al., 2017) and its region such as province. in addition, the appreciation of foreign currency exchange rates (especially usd currency) can affect fuel consumption expenditure since an increase in the price of imported fuel in usd can cause domestic fuel prices to become expensive in the domestic currency (gargett and hossain, 2008). this could lead to a drop in demand for imported fuels. as a result, oil consumption can decrease (schryder and peersman, 2013). conversely, an increase in oil consumption can cause household expenditure to rise, causing aggregate income to rise. this increase in aggregate income can cause saving on rising, reducing the domestic interest rate (mankiw, 2007). a decline in the domestic rate as such, according to the uncovered interest rate parity theory, may lead to a depreciation of the foreign exchange rate (domestic currency exchange rate appreciates) (pilbeam, 2006). a number of researchers have empirically tested hypotheses concerning the relationship between fuel consumption and economic growth. their findings, however, have been inconsistent. this journal is licensed under a creative commons attribution 4.0 international license rahim, et al.: the causal relationship between fuel consumption, exchange rates and economic growth in south east sulawesi, indonesia international journal of energy economics and policy | vol 11 • issue 6 • 20212 for example, nondo et al. (2010), payne (2011), ishida (2012), and ha et al. (2018) examined the relationship between energy/ fuel consumption in different countries. nondo et al. (2010) looked at the relationship between fuel use and economic growth in africa and found a long-term, one-way relationship from energy use to gdp (gross domestic product). payne (2011) studied the connection of natural gas fuel consumption with economic growth in the us and discovered the effect of economic growth on the consumption of natural gas fuel. ishida (2012), however, found that economic growth was not linked to fuel consumption when analyzed the relationship between fuel consumption and world economic growth. finally, ha et al. (2018) examined the relationship between fuel and economic growth in china, and they revealed a two-way relationship between fuel consumption and economic growth. furthermore, scholars have also explored the relationship between exchange rates and economic growth, among others, akpan (2010) in nigeria, chen and chou (2015) in finland, italy, portugal, france and switzerland, and owoundi (2015) in sub saharan africa. ha et al. (2018) analyzed china’s fuel and economic growth relationship and found a two-way connection between fuel consumption and economic growth. furthermore, the relationship between exchange rates and economic growth was examined by, among others, akpan (2010) in nigeria, chen and chou (2015) in finland, italy, portugal, france and switzerland, and owoundi (2015) in sub saharan africa. akpan (2010) found that there is no relationship between exchange rates and economic growth. while chen and chou (2015) documented the evidence of exchange rates effect on economic growth, owundi (2015) found the reverse: that the economic growth affect exchange rates. variations in results could be attributable to (1) the period for the collection of research data or (2) socio-political and economic conditions in a country where the research has been carried out (ozturk, 2010). therefore, the question arises: “is there any a short and/or longterm relationship between fuel consumption, exchange rate and economic growth in southeast sulawesi in indonesia?” this is primarily because south east sulawesi’s cultural, socio-political and economic characteristics are distinct from other areas in indonesia or elsewhere. so far our knowledge is concerned, the issue above reflects a research void that has not been explored mainly in the case for south east sulawesi. in this regard, this study aims to examine the causal relationship between fuel consumption, exchange rates and economic growth in south east sulawesi, indonesia. the time sample chosen covers the period from 1988 to 2016 for time series data on fuel consumption, exchange rates and economic increase. to test the causal relationship, the var model and the granger causality test are used. 2. literature review this section provides a literature review on the results of empirical research. the results of the tests indicated that fuel and economic growth were not causally linked. fatai (2014) investigated the causal relationship between energy consumption and economic growth in 18 sub-saharan african countries using annual data from 1980 to 2011. these countries were grouped into four groups of countries, covering central africa, east africa, southern africa, and west africa. the var panel test results show that while there was no relationship between energy consumption and economic growth in the central and west africa sub-region, a one-way relationship existed from energy consumption to economic growth in east and southern africa. using hsiao’s granger causality test and data for the 1955-1996 period, ageel and butt (2001) examined the relationship between energy consumption and economic growth in pakistan. the test results showed that there was a one-way relationship from economic growth to energy consumption. finally, lean and smyth (2014) analyzed the disaggregate relationship between fuel consumption and economic growth in malaysia using annual time series data from 1980 to 2011. the disaggregated fuel consumption referred to here is the consumption of diesel fuel and motor petrol. using a multivariate regression model test, they discovered that fuel consumption had a long-term effect on economic growth. the link between fuel consumption, economic growth, and other economic variables has been examined by, among others, abosedra et al. (2015), asafu-adjaye (2000), and sarkodie and adom (2018). abosedra et al. (2015) investigated the relationship between financial development, energy consumption and economic growth in lebanon. to test the relationship, they employed a var model and monthly data covering the period from february 2000 to december 2010. test findings revealed that economic growth was driven by financial development and energy use. in addition, financial development and economic growth influence the use of energy. asafu-adjaye (2000) estimated the causal relationship between energy consumption, energy prices and economic growth in asian countries (india, indonesia, philippines, and thailand) using the granger causality test. the estimation results indicated a two-way relationship between energy consumption, energy prices and economic growth. in order to explore the relation between fossil fuels, non-fossil, and economic growth in 53 countries, asafu-adjaye et al. (2016) used pooled mean group (covering oil-importing countries and oil-exporting countries) and the data from 1990 to 2012. the test results indicated that fuel demand and genuine gdp only had a two-way relationship in non-oil importing countries. thus, fossil fuels had a negative causal link to economic development, meaning that conserving fossil fuels could hinder economic growth. sarkodie and adom (2018) examined the relationship between fossil fuel consumption, electricity consumption, and economic growth in kenya using the nipals (nonlinear iterative partial minimum squares) test. the test results indicated that while economic growth impacted fossil fuel use, economic growth was influenced by electricity consumption. schryder and peersman (2013) examined the relationship between the united states dollar exchange rate and oil demand in oecd countries. they observed that exchange rates affected oil demand. as the exchange rate increased, oil demand decreased. the decrease in demand for oil also reduced oil fuel consumption. aman et al. (2013), using data from 1976 to 2010, reviewed the relationship between exchange rates and economic growth in pakistan. they used a simultaneous model of the equation to rahim, et al.: the causal relationship between fuel consumption, exchange rates and economic growth in south east sulawesi, indonesia international journal of energy economics and policy | vol 11 • issue 6 • 2021 3 analyze the data. the findings of the test demonstrated a positive relationship between exchange rate and economic growth, which was due to exports, domestic investment and direct foreign investment variables. using the var model and the granger causality test, selimi and selimi (2017) analyzed the effect of exchange rates on economic growth in macedonia. they used quarterly data from the first quarter of 1998 to the first quarter of 2015. the test results showed that exchange rates affected economic growth. finally, razzaque et al. (2017) examined exchange rate movements on economic growth in bangladesh. they used yearly time series data between 1980 and 2012. to analyze the data, a vecm model was applied. the test results demonstrated that the exchange rates had a long-term impact on economic development. 3. data and method 3.1. data the data used for this study are time-series data consisting of 3-time series, namely exchange rates, the consumption of fuel and southeast sulawesi’s gross regional domestic product (grdp). the time-series data cover the period from 1988 through 2016. the idr/usd exchange rate (after this abbreviated as the exchange rate) is used as a proxy for the exchange rate, on the ground that it is commonly used as an instrument for an international trade transaction. meanwhile, grdp is used as a proxy for economic growth. the data of exchange rate are sourced from the central bank of indonesia. 3.2. method as explained in the introduction, there can be correlations between the three variables: fuel consumption, exchange rates and growth. the variable of fuel consumption is expressed in cof, exchange rates in exc and the economic growth in gro. cof, exc, and gro variables represent natural logarithmic forms. the vector autoregressive (var) model and granger causality test are used to test the relationships between fuel usage, exchange rates and economic growth. the var model with a time lag length p, written as var (p) (heij et al., 2004; lutkepohl, 2009; brooks, 2014), is as follows. z c zt i t ii p t� � ���� b1 � (1) where zt=[cof,exc,gro]’ is a vector of endogenous variables, c=[c1,c2,c2]’ is a constant vector, bi (i=1,2,…,p) is the coefficient matrix, and εt is error or white noise vector. the white noise vector εt=[ε1t,ε2t,ε3t]’ is εt~iid(0,σ) where the covariance of the matrix σ=e(εt,εt’) is a positive definite matrix. the variables in equation (1) are assumed to be stationary at the level or integrated of order d, i(d), d≥0. however, if the three variables of fuel consumption (cof), exchange rate (exc), and economic growth (gro) are stationary at first difference and are co-integrated, then the relationship between fuel consumption, exchange rate, and economic growth is tested with a vector error correction model (vecm), as follows. d z c z d zt t i t ii p t( ) ( )� � � �� �� � �� �1 1 1 � (2) where 1 p ii b i = π = −∑ , i represents identity matrix, and �i ij i p b� � � �� 1 for i=1,2,…,p-1. the matrix π in equation (2) is called the long-term coefficient matrix. meanwhile, the γi (i=1,2,…,p−1) matrix is called the short-term coefficient matrix. we followed several steps to test the causal link between fuel consumption, exchange rates, and economic growth. the first step was to check the stationarity of variables. to this end, the augmented dickey-fuller (adf) test developed by dickey and fuller (1981) was applied. the adf test used the t-ratio statistic. the null hypothesis of the adf test is h0: the time series is not stationary againts the hypothesis h1: the time series is stationary. the following step was to perform a test for cointegration between fuel consumption, exchange rates and economic growth. this kind of test is carried out if the three endogenous variables are not stationary at level but stationary at first difference. the cointegration test used was the johansen cointegration test developed by johansen (1988). this cointegration test can be used if all endogenous variables are integrated in the same order, i(d) (acaravci and ozturk, 2012). there are two types of tests used in the johansen cointegration test: the trace test and the max-eigen test. trace test using test statistics. � �trace ii r g r t r g( ) ( ), , , ,� � � � � � � �� log 1 0 1 11 (3) the λi value in (3) is the largest eigen value of the matrix π in equation (2), and t is the number of observations. the formula for the null hypothesis in the trace test is h0: the number of cointegrating vectors is less or equal to r, versus the alternative hypothesis h1: the number of cointegrating vectors is more than r. the max-eigen test statistic is � �max rr r t r g( , ) ( ), , , ,� � � � � � ��1 1 0 1 11log (4) the null hypothesis of the max-eigen test in (4) is h0: the number of cointegrating vectors is r, and the alternative hypothesis is h1: the number of cointegrating vectors is r+1 (brooks, 2014). the last step was to estimate the var model and perform a granger causality test. initially, the lag length is established. besides, in estimating the var model, the residual requirements, the impulse response function (irf), and the variance decomposition (vd) are checked. while checking irf is aimed at determining the impact of changes in one variable on other variables in the model, checking the vd is intended to determine the size of the contribution of each variable to the other variables. 4. results in the first place, we conducted a stationary test for the research variables. the results of the adf test are summarized in table 1. it can be seen from table 1 that fuel consumption, exchange rates, and economic growth are stationary at first difference, or integrated of order 1, i(1). rahim, et al.: the causal relationship between fuel consumption, exchange rates and economic growth in south east sulawesi, indonesia international journal of energy economics and policy | vol 11 • issue 6 • 20214 the results of the johansen cointegration test are shown in table 2. by comparing the statistical test values with their critical values at the 5% significance level, it is concluded that there is no cointegration between fuel consumption, exchange rates, and economic growth. as fuel consumption, exchange rate, and economic growth do not co-integrate, the var model to be estimated is that of first difference. therefore, the first step in the var estimation is to determine the lag length. the lag length is determined based on the lowest statistical value among the criteria: fpe (final prediction error), aic (akaike information criterion), sc (schwarz information criterion), and hq (hannan-quinn information criterion). of the criteria, fpe has the lowest statistical value, and thus the lag length is table 3. as mentioned above, the var(3) model at first difference is that to be estimated. table 4 sums up the estimated results for var (3). it can be seen that d(cof (-3)) is the only significant variable for the case the dependent variable is d(gro). the d(cof(-3)) variable coefficient is shown significant at 1%. koop (2013) suggests that an independent variable is the granger cause of the dependent variable if the coefficient of any one of the independent variables is significant, shown by the t-statistic. thus, d(cof) granger causes d(gro). the var granger causality/block exogeneity wald tests can also test the direction of the causal relationship. this causality test uses the chi-square distribution of wald-statistics. the results of the causal relationship test are shown in table 5. the results of the var granger causality/block exogeneity wald tests test show that d(cof) granger causes d(gro), and thus, it can be concluded that while a short-term, one-way relationship exists from fuel consumption to economic growth, and there is no shortterm relationship, from exchange rates to economic growth. since the significant variable coefficients are only the coefficient of d(cof) for the case the dependent variable is d(gro), then checking the irf is only the responses of economic growth to fuel consumption and economic growth to the exchange rate. figure 1 shows the results of the irf check. it can be seen that the response of economic growth to fuel consumption in the first ten periods was fluctuating. however, the response in the first period was positive. meanwhile, the response of economic growth to the exchange rate also fluctuated during the first ten periods. however, the response in the first period was negative. the periods for checking the variance decomposition are selected for 3 years, 6 years, 9 years, and 12 years. the statistical values of vd are summarized in table 6. the impact of fuel consumption on economic growth is greater than the impact of exchange rates on economic growth. compared to fuel consumption and exchange rates contribution, the contribution of economic growth in the past to current economic growth is the largest one. for example, the impact of past economic growth on current economic growth in the first 12 periods was 47.12%, while the effects of fuel consumption and exchange rates were 31.44% and 21.44%. 5. discussion the purpose of this research is to examine the causal link between fuel consumption, exchange rates and economic development. the table 4: estimates of model var(3) dependent variables and constant independent variables and their coefficient d(gro) d(cof) d(exc) d(gro(-1)) 0.1141 -0.4362 0.0112 [0.8674] [-0.4698] [0.0793] d(gro(-2)) -0.0195 0.1753 -0.0849 [-0.1503] [0.1910] [-0.6057] d(gro(-3)) 0.0170 -0.1205 -0.0581 [0.1295] [-0.1302] [-0.4113] d(cof(-1)) 0.0565 -0.4432 0.1037 [1.4072] [-1.5644] [2.3978] d(cof(-2)) 0.0569 0.0538 0.0689 [1.0662] [0.1444] [1.2106] d(cof(-3)) -0.1219* -0.0555 0.0174 [-2.3153] [-0.1493] [0.3074] d(exc(-1)) -0.2553 0.5628 -0.4059 [-0.9980] [0.3118] [-1.4722] d(exc(-2)) 0.3546 0.7189 -0.3858 [1.3837] [0.3976] [-1.3969] d(exc(-3)) -0.0451 0.9224 -0.0752 [-0.2116] [0.6132] [-0.3275] c 0.0840 0.15412 0.1306 [1.1071] [0.2880] [1.5970] value of statistic-t in [ ]. * means significant at 1% p-value of portmanteau tests (lag 4) is 13.53155, p-value of white joint test is 0.1938 table 2: result of johansen cointegration test null hypothesis (ho) trace test max-eigen test trace statistic 5% critical value max-eigen statistic 5% critical value r=0 18.0188 29.7971 11.7041 21.1316 r≤1 6.3147 15.4947 4.8960 14.2646 r≤2 18.0188 29.7971 1.4188 3.8415 table 3: statistical values of the information criteria lag fpe aic sc hq 0 0.0492 5.5025 5.6512 5.5375 1 0.0394 5.2672 5.8623 5.4074 2 0.0156 4.2830 5.3245 4.5284 3 0.0082* 3.4978 4.9856 3.8483 4 0.0232 4.2194 6.1535 4.6750 5 0.0376 4.0579 6.438399 4.6187 6 0.0127 1.4828* 4.3096* 2.1487* * shows the lowest statistical values of the information criteria: fpe, aic, sc and hq table 1: results of adf test variable level first difference constant constant and trend constant constant and trend cof -1.3920 -1.0287 -8.5430* -8.5583* exc -1.3074 -2.0218 -5.6877* -5.6235* gro -2.0080 -2.8448 -4.4594* -4.2914** * or ** means significant at 1 or 10% rahim, et al.: the causal relationship between fuel consumption, exchange rates and economic growth in south east sulawesi, indonesia international journal of energy economics and policy | vol 11 • issue 6 • 2021 5 estimated results of the var(3) model and the granger causal test demonstrate that only fuel consumption and economic growth have a short-term relationship, namely from fuel consumption to economic growth. this result is consistent with those of nondo et al. (2010) and lean and smyth (2014). however, on the other hand, it is in disagreement with the results shown by many studies: chen and chou (2015), owoundi (2015), fatai (2014), ageel and butt (2001), asafu-adjaye (2000), asafu adjaye et al. (2018). this disparity can occur because of variations in data period, cultural circumstances, and/or social and economic factors (ozturk, 2010). as far as the exchange rate and economic growth relationship are concerned, the present study does not find a short-term causal link between these variables. hence, this study does not match the previous studies: aman et al. (2013), selimi and selimi (2017), and razzaque et al. (2017). given these results, south east sulawesi’s provincial government is advised to implement a gas and oil policy while maintaining a steady oil and gas price. with this steady oil price, there will be a rise in demand for oil and gas, thereby raising oil and gas. it means that economic growth will improve. 6. connclusion in the economy, fuel and gas play a major part. companies and households require, for instance, these two commodities to fulfil the requirements of industry and households. meanwhile, the exchange rate also serves as a medium for oil imports, especially crude oil. this study focuses on the causal link among fuel consumption, exchange rates and economic growth in south east sulawesi indonesia. the annual time series data on fuel, exchange rate and grdp as a proxy for economic growth were analyzed in this present study. the time series data covers the periods between 1988 and 2016. the analysis show that the 3 time series: fuel consumption, exchange rates, and economic growth are stationary in the first deference. as shown by johansen cointegration test, the variables of fuel consumption, exchange rates, and economic growth are not cointegrated. meanwhile, the estimation results of the var(3) model and the granger causality test at first difference indicate that there is a significant short-term relationship from fuel consumption to the economic growth of southeast sulawesi province. references abosedra, s.a., shahbaz, m., sbia, r. (2015), the links betweenenergy consumption, financial development, and economic growth in lebanon: evidence from cointegration with unknown structural breaks. journal of energy, 2015, 1-15. acaravci, a., ozturk, i. (2012), foreign direct investment, export and economic growth: empirical evidence from new eu countries. romanian journal of economic forecasting, 2, 52-67. adam, p., rianse, u., harafah, l.m., cahyono, e., rafiy, m. (2016), a model of the dynamics of the effect of world crude oil price and world rice price on indonesia’s inflation rate. agris on-line papers in economics and informatics, 8(1), 3-12. adam, p., rosnawintang, r., nusantara, a.w., muthalib, a.a. (2017), a model of the dynamic of the relationship between exchange rate and indonesia’s export. international journal of economics and financial issues, 7(1), 255-261. ageel, a., but, m.s. (2001), the relationship between energy consumption table 6: variance decomposition of d(gro) period d(gro) d(cof) d(exc) 3 62.7567 10.7589 26.4844 6 47.7467 30.7079 21.5455 9 47.3905 31.0847 21.5249 12 47.1242 31.4358 21.4402 table 5: var granger causality/block exogeneity wald tests dependent variable independent variable chi-square test statistics prob d(gro) d(cof) 13.1581* 0.0043 d(exc) 4.5030 0.2120 d(cof) and d(exc) 13.4353 0.0366 d(cof) d(gro) 0.2933 0.9613 d(exc) 0.4265 0.9347 d(gro) and d(exc) 0.8149 0.9917 d(exc) d(gro) 0.53177 0.9119 d(cof) 6.2427 0.1004 d(gro) and d(cof) 7.4517 0.2811 * means chi-square statistic is significant at 1% figure 1: responses of economic growth to fuel consumption (left), and exchange rate (right) rahim, et al.: the causal relationship between fuel consumption, exchange rates and economic growth in south east sulawesi, indonesia international journal of energy economics and policy | vol 11 • issue 6 • 20216 and economic growth in pakistan. asia pacific development journal, 8(2), 101-110. akpan, e.o., atan, j.a. (2011), effects of exchange rate movements on economic growth in nigeria. cbn journal of applied statistics, 2(2), 1-14. aman, q., ullah, i., khan, m.i., khan, s.d. (2013), linkages between exchange rate and economic growth in pakistan (an econometric approach). european journal of law and economics, 44(1), 157-164. asafu-adjaye, j. (2000), the relationship between energy consumption, energy prices and economic growth: time series evidence from asian developing countries. energy economics, 2(2), 615-625. asafu-adjaye, j., byme, d., alvarez, m. (2016), economic growth, fossil fuel and non-fossil consumption: a pooled mean group analysis using proxies for capital. energy economics, 60, 1-44. brooks, c. (2014), introductory econometrics for finance. 3rd ed. cambridge: cambridge university press. chen, s.s., chou, y.h. (2015), revisiting the relationship betweenexchange rates and fundamentals. journal of macroeconomics, 46, 1-22. dickey, d.a., fuller, w.a. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica: journal of the econometric society, 49(9), 1057-1072. fatai, b.o. (2014), energy consumption and economic growth nexus: panel co-integration and causality tests for sub-saharan africa. journal of energy in southern africa, 25(4), 93-100. gargett, d., hossain, a. (2008), how do fuel use and emissions respond to price changes? bitre briefing-1, commonwealth of australia. available from: http://www.ag.gov.au/cca. ha, j., tan, p.p., goh, k.l. (2018), linear and nonlinear causal relationship between energy consumption and economic growth in china: new evidence based on wavelet analysis. plos one, 13(5), 1-21. ishida, h. (2012), causal relationship between fossil fuel consumption and economic growth in the world. international of global energy issues, 35(6), 427-440. johansen, s. (1988), statistical analysis of cointegration vectors. journal of economic dynamics and control, 12, 231-254. lean, h.h., smyth, r. (2014), disaggregated energy demand by fuel type and economic growth in malaysia. applied energy, 132, 168-177. lutkepohl, h. (2009), econometric analysis with vector autoregressive models. in: besley, d.a., kontoghiorghes, e.j., editors. handbook of computational econometrics. chichester: john wiley and son ltd. p281-319. mankiw, n.g. (2007), macroeconomics. 6th ed. new york: worth publishers. mauro, f.d., ruffer, r., bunda, i. (2008), the changing role of the exchange rate in a globalised economy, ecb occasional paper series, n0. 94, social science research network. available from: http://www.ssrn.com/abstract_id=1144484. millia, h., adam, p., saenong, z., balaka, m.y., pasrun, y.p., saidi, l.o., rumbia, w.a. (2020), the influence of crude oil prices volatility, the internet and exchange rate on the number of foreign tourist arrivals in indonesia. international journal of energy economics and policy, 10(6), 280-287. mishkin, f.s. (2008), the economics of money, banking, and financial markets. new jersey: pearson eduacation inc. nondo, c., kahsai, m., schaeffer, p. (2010), energy consumption and economic growth: evidence from comesa countries. virginia: working paper 2010-01, regional research institute, west virginia university. ozturk, i. (2010), a literature survey on energy-growth nexus. energy policy, 38, 340-349. payne, j.e. (2011), us disaggregate fossil fuel consumption and real gdp: an empirical note. energy sources, part b: economics, planning, and policy, 6, 63-68. pilbeam, k. (2006), international finance. 3rd ed. new york: palgrave macmillan. razzaque, m.a., bidisha, s.h., khondker, b.h. (2017), exchange rate and economic growth: an empirical assessment for bangladesh. journal of south asian development, 12(1), 42-64. saidi, l.d., kamaluddin, m., rostin., adam, p., cahyono, e. (2015), the effect of the interaction between us dollar and euro exchange rates on indonesia’s national income. wseas transaction on business and economics, 12, 131-137. sarkodie, s.a., adam, p.k. (2018), determinants of energy consumption in kenya: a nipals approach. energy, 159, 697-705. schryder, s.d., peersman, g. (2013), the u.s. dollar exchange rate and the demand for oil. pakistan: cesifo working paper no. 4126, fwo. p1-27. selimi, n., selimi, v. (2017), the effect of exchange rate on economic growth in the republic of macedonia. ecoforum, 6(3-13), 50-55. viljoen, d.a. (1979), the importance of coal. journal of the south african institute of mining and metallurgy, 1979, 493-494. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 4 • 2021 1 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(4), 1-6. the implementation of smart energy into transformation of the rural area: the use of public policies for smart villages development petr hlavacek1*, vladimír skalník2 1department of regional development and public administration, faculty of social and economic studies, jan evangelista purkyně university, pasteurova 1, 400 96 ústí nad labem, czech republic, 2innovation centre of ústecký region, ústí nad labem, czech republic. *email: petr.hlavacek@ujep.cz received: 15 february 2021 accepted: 27 april 2021 doi: https://doi.org/10.32479/ijeep.11203 abstract the article aims to evaluate the government policies in the czech republic that have an impact on energy development and energy production development in the rural areas, and to propose the areas where smart energy solutions are appropriate for rural communities. the setup of the public companies is compared with respect to current trends in the development of smart villages, where the smart energy solutions are being developed. the research and development conclude that the development policies will require a setup to make the decentralization of the energy sources strengthened. as well, to allow more intensive communication and negotiation with local communities. achieving the synergy effect, while starting up the process of use of local energy resources of the location and community energy in transformation of the rural area, should be the goal. keywords: energy policy, smart cities, smart villages jel classifications: q42, q48, r11 1. introduction in connection with how quickly new technologies appear in the field of energy production, a standalone topic of the use of these innovative technologies, or concept, in the rural areas comes to the forefront (holtmeyer et al., 2013; jenkins et al., 2018). these challenges need our intensive focus to strengthen the energy independence of the rural areas. according to clausen and rudoplh (2020), the existence of the best technology will not guarantee its use, which, rather likely with respect to the lagging of the rural areas, behind the development of urban regions, in the field of the energy. on top of that, the lower density of the population of rural areas makes unit costs for provision of available energies to inhabitants of the rural areas higher. the disadvantage of the areas is that they lack political power and the agglomeration benefits of the urban regions (o’sullivan et al., 2020; klaniecki et al., 2020). abbas et al. (2020) point out the risk of growing energy poverty being associated in particular with peripheral rural areas. not only the availability of the energy sources, but also the setup of the energy policy and other policies, which deal with the rural area development with respect to availability and use of the energies to a certain level, influences the development of the rural regions in the field of energy. to that end, the article evaluates the current setup of the public policies, what targets have been defined for development of smart energy, and for the use of the energy sources in the rural areas in association to the support for implementation of the smart solutions there. upon evaluation of the government policies, the article will define the field for implementation of smart energy to the development of the rural areas, and directions for establishing this journal is licensed under a creative commons attribution 4.0 international license hlavacek and skalník: the implementation of smart energy into transformation of the rural area: the use of public policies for smart villages development international journal of energy economics and policy | vol 11 • issue 4 • 20212 a new energy transformation policy for the rural areas for the development of the smart rural areas. 2. literature review according to oecd, the rural and interjacent areas (oecd, 2016) occupy 88.2% of the territory of the european union (eurostat, 2016), and they include most of its natural resources. many european villages, including those in the czech republic, have already been using the potential for making the projects focused on energy saving happen with the emphasis on the use of the renewable energy sources. an example of such a functional design is the energy communities in some european states where there is an environmental law, which is much more favourable for the individual and decentralized production of energy (enrd, 2018). the local system outside the grids then complements those centralized ones (groth, 2020). it is inevitable for the rural areas to avoid the import of knowledge and capital necessary for the introduction and use of innovative and smart solutions in energy in the future. however, benedek et al., (2018) draw attention that the use of the renewable energy will require good predictions of the capacities of the local energy sources. in conformity with the policy of the european union in the field of climate and energy, the czech republic prepares for the transposition of the laws from the “clean energy for all europeans” package into the czech laws. by 2050, the european union intends to be a climate-neutral area. the european commission implements initiatives at the eu level that deal with the challenges of towns and municipalities in the field of energy. one of these initiatives is the european innovation partnership, the initiative for smart cities and communities. it is a partnership across the areas of energy, transport and information and communication with the objective to catalyse progress in the said areas. energy production, distribution and use, mobility and transport, and information and communication technologies (ict) are intimately lined and offer new interdisciplinary opportunities to improve services while reducing energy consumption (european commission, 2012). the change to shift to low-carbon and a sustainable economy will require a huge effort, investments, and interdisciplinary approach. the development and use of modern energy systems, technologies, and infrastructure needed are the fundamental requirements for achieving the change (naumann and rudolph, 2020). there has already been a start with the implementation effort of the european laws in the czech republic in the field of energy represented in particular by the directive (eu) 2018/2001 of the european parliament and of the council on the promotion of the use of energy from renewable sources, directive (eu) 2018/2002 of the european parliament and of the council on energy efficiency, and directive (eu) 2018/844 of the european parliament and of the council on the energy performance of buildings, i.e., with respect to energy transformation processes and renewable energy sources (res) development. the rural area development draft of the ministry of regional development of the czech republic deals with the field of the rural area development. the draft aims to support the rural area development by a more intensive use of the local energy sources (ministry of regional development of the czech republic, 2019). it would be therefore necessary to implement the activities related to smart energy so that the rural areas have created a quality infrastructure (energy, transport, and technical), powerful, stable, and diversified economy, as well as a healthy and climate stable environment. according to mekhdiev et al., (2018), the governments should focus on increasing the energy consumer’s satisfaction level regarding quality and energy supply costs with good support from the decentralization of its production. despite increasing energy savings, the consumption and demand for energies will continue to grow. involvement of the government programs, regional, and local governments will be required to secure the new energy sources where there is just room for support of implementing the smart solutions. however, the use of the public support should be linked to collective bargaining about future forms of energy production and distribution. according to berka and creamer (2018), these factors will play a key role in the transformation processes, towards increased energy production at the local level, i.e., in the rural communities as well. 3. methods the article is structured into a couple of related chapters that conform to the phases of the methodology of the research. first, collection of information was made on current needs for development of the communities, and the description of expert publications. the next phase mapped out legal and planning dimensions, and analysis of policies of the czech ministries focused on the field of energy with impact on the rural areas. then, the smart city concept analysis followed, including identification of the main directions of the smart energy development for the rural areas. the analytical part of the present article is topped up by the specification of smart solution for rural areas with an emphasis on endogenous energy sources, including findings and recommendations for the smart energy development in the rural areas. the descriptive analysis in scripted documents, public policies, methodologies, and expert bibliography study will be used in the research. the good practice method (stockley, 2012) is being applied for the searching and mapping of the smart solutions in the field of energy in the rural areas. the good practice method has been developed in the field of management from where it expanded to other areas. the method aims at the mapping of solutions employed as model examples and uses them for the solution of other problems or development goals. 4. results and discusion a couple of planning and strategic documents indicate the development in the field of energy in the czech republic – national action plan of energy efficiency of the czech republic, national action plan for smart networks, national action plan for renewable energy sources 2010-2020 for the czech republic, state energy concept of the czech republic, and the strategy for regional development of the czech republic 2021+. the analysis hlavacek and skalník: the implementation of smart energy into transformation of the rural area: the use of public policies for smart villages development international journal of energy economics and policy | vol 11 • issue 4 • 2021 3 of the disciplinary policies of the ministries showed that they define the development goals in the field of energy impacted also by the rural areas in many of their own disciplinary policies. the ministry of industry and trade of the czech republic, being responsible for agenda in the field of the energy and energy policy of the czech republic, is the main entity responsible in the czech republic for energy development, also in the rural areas. not only, this ministry also deals with the themes of energy and transformation of energy sources, including the consequences of the transformation. the analysis of the policies of other ministries revealed that other goals of the individual programs may be found in the impact on the field of the energy production and energy also in the rural areas. for the summary of evaluation of individual goals of the government programs and policies, refer to table 1. in addition to the above-mentioned goals of government policies, the need to develop smart energy networks is also mentioned, which is associated with the expectation of achieving greater efficiency of energy networks, but creating greater independence in deciding how to meet the energy needs of the rural areas. hence, measures such as energy distribution, production, and accumulation based on the principle of smart network and smart instrumentation, including the support for the development of distributed and centralized energy accumulation systems should be adopted. at the same time, the new infrastructure should also expand the options for customer consumption management at the level of low voltage as a part of the smart network systems. the development of smart energy aimed at achieving carbon neutrality by 2050 brings about a lot of new challenges and opportunities. from the energy sources perspective, the priority is logically put on the maximum use of the res. however, the use of secondary energy sources, as well as the use of waste, must not stay aside as they are the representatives of typical examples of linear economy transformation into the circular one. the sources may be called modern or innovative energy sources. 4.1. from smart cities to smart villages recently, the smart cities concept has been penetrating, over the last years, in the development of the energy policies at the regional level, which is based on the principles of sustainable development and the organization of cities with the use of smart technologies in the field of energy as well. an important concept document from the ministry of regional development of the czech republic is the smart cities methodology (ministry of regional development, 2018) that considers smart energy, sources, and services as the main areas of the smart cities’ technological infrastructure. smart energy includes the following areas: • smart energy consumption control, including energy management of municipal buildings and support of their energy-saving solutions • use of res or combined electricity and heat production, and their safe integration into the municipal energy grid • use of the “smart grid” elements in the municipal or regional distribution grid, including smart micro-grids • smart control of municipal services towards effective use of energy and natural resources – in particular, energy-saving and environmentally-concerned public lighting, effective waste management, and effective water management (ministry of regional development of the czech republic, 2018). the development of the rural areas’ development policy is inevitable without the development of smart energy in the rural areas. smart rural areas are the rural areas and communities that build on their advantages and values to date, as well as on new opportunities in their effort to achieving increased value where both traditional and new grids are upgraded through digital communication technologies, innovation, and improved use of knowledge in favour of inhabitants (enrd, 2018). a synonym for the power development could to some extent be the energy 4.0 concept (the ústí region, 2020). from the perspective of this energy, it is a portion of the energy eco-system integrating the ict elements, in particular smart production, distribution, and energy consumption management in real time, which supports the distributed production from renewable sources of energy. table 1: evaluation of policy goals of the czech ministries with an impact on energy transformation of the rural areas ministry in the czech republic goals of the policy ministry of industry and trade to implement energy-saving measures to increase efficiency in use of energy, and reduce energy demands to process design and territorial documentation to support energy saving to make loans intended for reduction of energy demand more favourable in order to achieve energy saving ministry of agriculture to support biomass use as res ministry of regional development to permit energy transformation of the rural areas background of the regional centres to ensure effective prevention of social exclusion and energy poverty, and to support the community life in the communities to improve air quality in the communities where the emission limits are exceeded (replacement of local air-polluting energy sources) to develop new energy repositories to develop net energy sources extracting energy from res to modify the transmission and distribution grid in order to make the connection of a new res possible to use smart solutions in urban and rural areas ministry of interior to repair or maintain properties of the communities, in particular, in the field of transport and energy ministry of environment to reduce energy demand of the existing blocks of flats to fund the construction of the blocks of flats of very low energy demand to effectively use the energy sources to use heat from waste water ministry of education, youth and sports use examples of energy saving solutions and environmental measures to educate source: own processing hlavacek and skalník: the implementation of smart energy into transformation of the rural area: the use of public policies for smart villages development international journal of energy economics and policy | vol 11 • issue 4 • 20214 based on the targets and policies specified above, which directly or indirectly coordinate the energy development at the level of regions and municipalities as well, the basic smart solutions may be defined as the upcoming vision of the rural areas as being the territory attractive for true living. the effective use of the smart systems for the operation of the community and communication with inhabitants is important for the rural area in the field of energy. it is necessary to evaluate the level of self-sufficiency of the rural areas in the energy production for the system development of smart rural areas and their energy sources, and to transform the energy sources into low-carbon economy. with the change processes being set, differences of individual rural areas and endogenous principles must be considered in creating the local energy policies in the rural communities. the energy self-sufficiency of a municipality may be the potential goal of the smart solutions in the field of smart energy (figure 1). an energy self-sufficient municipality is not an isolated entity, it remains integrated with the other communities and territories in a communal way. it is able to procure all the needs, or its energy consumption right in the community. the essence is a principle that consumption and production occurs at one place with an effort to cover the consumption as most as possible from its own sources, which widely opens doors to modern technologies. in no way is the essence of the energy self-sufficiency separated from the central power supply systems, but rather to use as most as possible the local available potential, which also improves the resilience of the community and provides extended safety. the smart solution in the power field and energy production in the rural areas should be applied in the fields described in table 2. the self-sufficiency level is given by a specific layout of the community or territories to a high extent. therefore, the definition of the territorial potential and possibilities of its technical and economical use are the keys for the rural area’s development. an energy self-sufficient municipality consists of a community being able to sustain its needs, i.e., local consumption through energy production on spot. it does not mean that it is isolated from the central power supply but local energy sources will be used as much as possible. the smart energy consists in diminishing fossil fuels and the development of low-carbon economy also in the rural areas, for example by the use of res (solar and wind energy, biomass and bio-gas for electricity production, reduction of energy demand, and more) at higher levels and in overall energy management. the ability of the community’s policy to communicate with a wider area, to advance in a horizontal approach in the creation of a symbiotic relationships with other communities, and in a vertical approach in the development of energy; this will play an irreplaceable role by the integration of the rural communities and locations with the regional centres at a higher level. to achieve an acceptable level of resilience and self-sufficiency of the rural areas, it is necessary to deliver relevant technical infrastructure (local distribution systems with the elements of smart grids). figure 1: basic representation of smart village source: antoine-santoni et al., (2019) table 2: areas for implementation of the smart solutions in the rural areas energy grids reconstruction of distribution grids for connection of new sources of electricity, or res development of transmission and distribution system and energy repositories building of infrastructure for island systems for energy supply energy production reduction of energy demands use of alternate sources of energy, e.g., in bio-gas stations use of res support of new local (innovative) sources of energy support of effective use of energy sources and switching to low-carbon rural economy de-concentrated energy systems socioeconomic area reinforcement of the circular economy in the field of the energy production development of low-carbon economy reduced risk of energy poverty support of local energy producers source: own processing hlavacek and skalník: the implementation of smart energy into transformation of the rural area: the use of public policies for smart villages development international journal of energy economics and policy | vol 11 • issue 4 • 2021 5 should there be an insufficiency of individual energy sources, the smart energy solution should perform the control and coordination activity between both systems so that community inhabitants notice no inferior quality of supply or outages. in addition, a lot of smart solutions are related to internet and electricity, and thus it is necessary to eliminate potential outages as a prevention so that purely technological smart solutions will be able to operate in a continuous way. consolidation of diversification of the source base and tight cooperation with the surrounding communities and regional centres under clearly defined rules and correct management will allow the reduction of the operation expenses, and provide higher stability of the environment and resiliency of the rural areas against extreme situations. according to vallivaara (2017), the artic smart community cluster project may be an example where the community in cooperation with various organizations, including companies, funding institutions, researchers, and mediators harnessed the potential for capital outflow and increasing the local quality of services in two key areas – energy and food sale. the cluster participants have developed an integrated strategy to support local business operators, which includes education through schools, making public tenders accessible, and establishing local food and energy hubs. it has been confirmed that the implemented projects create new jobs, reduce waste and emissions, control costs, and keep local income in the local economy (enrd, 2018). 5. discussion and conclusion in essence, smart energy in the rural areas is not limited to the size of the area, and it belongs among the fundamental pillars of the smart development concept of the rural areas. the object is that it may be generally considered as a part of everyday life of all inhabitants, and it does not matter whether it is applied in a metropolis or in a rural community. it includes a set of systems and activities that a modern society may not simply operate. what distinguishes smart energy from a “traditional” perception of the energy is the achieved level of energy efficiency of all systems being used, the level of res, its availability (limitation of the energy poverty), and the resilience level towards changes to conditions. the energy self-sufficiency of a community and the development of community energy is an apposite result, however, the central energy systems should remain as a backup, or add-on, because energy self-sufficiency is the first aspect and provision of individual services in the community, so that inhabitants will live well and better in the future, as this is the other aspect. in reality, perhaps only a few communities would be capable of securing the services using its own sources at a level available from the central system, and therefore, each system needs to be interconnected. for pushing smart energy through, a properly configured energy policy is absolutely fundamental – to ensure the conditions for a long-term sustainable development and decentralization of the energy sources (yazdanie et al., 2016). the policy should be characterized by achieving the synergy in the integration of the energy and information and communication technologies (ict). for rural communities, it is better that the energy challenge (and therefore, the energy self-sufficiency) is discussed at the level of locations and not by way of individual communities, and hence, to support so-called community energy. the energy associations being formed by the communities, and therefore by inhabitants, show growing importance, and the energy policy should aim toward more intense communication and negotiation with the local communities. it would be ideal in each case, that all directions described for the new solutions in the field of the energy development of the rural areas are supported by the government policy by the system of subsidies and invitations to help in the transformation of the energy sources and higher independence of the rural communities. the next steps in the research could focus on mapping out the efficiency of the government programs and looking for successful projects of the community energy development in the rural areas. the above mentioned is associated with the need of looking for examples of an effective energy transformation of the rural regions. the knowledge gained about the transformation processes could be the examples and they may be universally portable to other rural areas. 6. acknowledgment the paper presents the results of the research within the tacr project no. tl03000066, “smart countryside: sustainable rural development using smart solutions.” references abbas, k., li, s., xu, d., baz, k., rakhmetova, a. (2020), do socioeconomic factors determine household multidimensional energy poverty? empirical evidence from south asia. energy policy, 146, 111754. antoine-santoni, t., poggi, b., federici, d. manicacci, f.m., gualtieri, j.s., aiello, a. (2019), proposition of a smart environment architecture for ressources monitoring and rural activities management. the 13th international conference on sensor technologies and application, conference paper iaria. p62-68. benedek, j., sebestyén, t., bartók, b. (2018), evaluation of renewable energy sources in peripheral areas and renewable energy-based rural development. renewable and sustainable energy reviews, 90, 516-535. berka, a.l., creamer, e. (2018), taking stock of the local impacts of community owned renewable energy: a review and research agenda. renewable and sustainable energy reviews, 82, 3400-3419. clausen, l.t., rudolph, d. (2020), renewable energy for sustainable rural development: synergies and mismatches. energy policy, 138, 111289. enrd. (2018), eu rural review 26 smart villages: revitalising rural services. available from: https://www.enrd.ec.europa.eu/ publications/eu-rural-review-26-smart-villages-revitalising-ruralservices_en. [last accessed on 2021 jan 21]. european commission. (2012), sdělení komise inteligentní města a obce evropské inovační partnerství. available from: https://www. ec.europa.eu/info/eu-regional-and-urban-development/topics/citiesand-urban-development/city-initiatives_cs. [last accessed on 2021 jan 19]. eurostat. (2016), share of land area using different typologies. available hlavacek and skalník: the implementation of smart energy into transformation of the rural area: the use of public policies for smart villages development international journal of energy economics and policy | vol 11 • issue 4 • 20216 from: https://www.ec.europa.eu/eurostat/statistics-explained/index. php?title=file:share_of_land_area_using_different_typologies_ (%25_of_land_area)_update.png. [last accessed on 2021 jan 21]. groth, a. (2020), overcoming one-way impact evaluation of rural electrification projects. international journal of energy economics and policy, 10(2), 464-476. holtmeyer, m.l., wang, s., axelbaum, r.l. (2013), considerations for decision-making on distributed power generation in rural areas. energy policy, 63, 708-715. jenkins, k., sovacool, b.k., mccauley, d. (2018), humanizing sociotechnical transitions through energy justice: an ethical framework for global transformative change. energy policy, 117, 66-74. klaniecki, k., duse, i.a., lutz, l.m., leventon, j., abson, d.j. (2020), applying the energy cultures framework to understand energy systems in the context of rural sustainability transformation. energy policy, 137, 111092. ministerstvo pro místní rozvoj čr. (2018), metodika smart cities. available from: https://www.mmr.cz/getmedia/f76636e0-88ad40f9-8e27-cbb774ea7caf/metodika_smart_cities.pdf.aspx?ext=. pdf. [last accessed on 2021 jan 15]. mekhdiev, e.t., prokhorova, v.v., makar, s.v., salikhov, g.g., & bondarenko, a.v. (2018). smart cities in future energy system architecture. international journal of energy economics and policy, 8(5), 259-266. ministerstvo pro místní rozvoj čr. (2019), koncepce rozvoje venkova. available from; https://www.mmr.cz/getmedia/279d5264-6e9e4f80-ba4a-c15a26144cd0/koncepce-rozvoje-venkova_202001.pdf. aspx?ext=.pdf. [last accessed on 2021 jan 15]. ministry of regional development of the czech republic (2018). metodika smart cities. available from; https://mmr.cz/getmedia/ f76636e0-88ad-40f9-8e27-cbb774ea7caf/metodika_smart_cities. pdf.aspx?ext=.pdf. naumann, m., rudolph, d. (2020), introduction to the special section: rural energy transitions contestations and perspectives. energy policy, 142, 111531. o’sullivan, k., golubchikov, o., mehmood, a. (2020), uneven energy transitions: understanding continued energy peripheralization in rural communities. energy policy, 138, 111288. oecd. (2016), oecd regional outlook 2016: productive regions for inclusive societies. available from: https://www.regions20.org/wpcontent/uploads/2016/08/oecd-regional-outlook-2016.pdf. [last accessed on 2021 jan 10]. stockley, d. (2012), the rise and fall of the best practice method. available from: http://www.derekstockley.com.au/newsletters05/042-best-practice-consulting.html. ustecky region. (2020), energetika 4.0. available from: https:// w w w. k ru s t e c k y. c z / a s s e t s / f i l e . a s h x ? i d _ o rg = 4 5 0 0 1 8 & i d _ dokumenty=1748688. [last accessed on 2021 jan 21]. vallivaara, j. (2017), implementation of smart specialisation arctics smart rural community. available from: https://www.enrd. ec.europa.eu/sites/enrd/files/s4_rural-businesses_aritc-cluster_ havukainen.pdf. [last accessed on 2021 jan 15]. yazdanie, m., densing, m., wokaun, a. (2016), the role of decentralized generation and storage technologies in future energy systems planning for a rural agglomeration in switzerland. energy policy, 96, 432-445. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(1), 243-249. international journal of energy economics and policy | vol 12 • issue 1 • 2022 243 the effect of financial development on energy consumption: evidence from russia shahriyar mukhtarov1,2,3*, rıdvan karacan4, fuzuli aliyev5, vuqar ismayilov6 1baku engineering university, baku, azerbaijan, 2vistula university, warsaw, poland, 3azerbaijan state university of economics (unec), baku, azerbaijan, 4kocaeli university, kocaeli, turkey, 5ada university, baku, azerbaijan, 6azerbaijan technology university, ganja, azerbaijan. *email: smuxtarov@beu.edu.az received: 19 october 2021 accepted: 03 november 2021 doi: https://doi.org/10.32479/ijeep.12534 abstract this paper explores the effect of financial development, economic growth, and energy prices represented by consumer price index (cpi) on energy consumption in russia by performing vecm, ccr, dols and fmols analyses to the annual data from 1995 to 2019. the findings of this empirical analysis reveal that financial development and economic growth have positive impact on energy consumption in russia. furthermore, the effect of energy prices expressed by cpi is revealed to be negative, which is consistent with the theory and expectations in practice. based on the findings of this study, the nexus and impacts of financial development on energy consumption are discussed, as well as plausible explanations and policy implications. keywords: economic growth, energy consumption, energy prices, financial development; russia, vecm jel classifications: g00; q40; p34; p18; f43 1. introduction energy is very important for the continuation of vital activities. increase in the human population and the widespread use of hitech products to meet basic needs such as education, health and housing require more energy consumption (encon thereafter). thus, encon plays a vital role in shaping the economic policies of countries. being either an energy-rich or an energy-poor country has a key role in shaping these policies. the primary goal of energy-poor countries is to provide the energy they need in a way that provides the maximum benefit. energy-rich countries, however, have priorities such as providing a competitive advantage among themselves and having impact on the world energy market. in this regard, encon remains important for both groups of countries. the fact that energy is so critical makes determining the factors affecting encon a priority. financial development (findev thereafter) is a key factor affecting encon. the financial sector is comprised of a set of institutions, instruments, and markets, as well as legal and regulatory frameworks, that allows transactions by lending. basically, development in financial sector considers lowering the “costs” that the financial system is exposed to. this search, aimed at minimizing the transaction costs of obtaining information, implementing obligations, and trading, has yielded in the widespread of financial contracts, markets, and intermediaries (world bank, 2021). the faster the level of findev of countries, the easier it becomes to meet the costs to be incurred as the results of increase in production and consumption. in order to meet the costs, a sustainable financial system must be found in developed and developing countries (keskingöz and i̇nançlı, 2016). the most important advantage of a sustainable and efficient financial system is that it ensures the continuity and stability of economic growth (schumpeter, 1911; mckinnon, 1973). the growth hypothesis states that an increase in encon causes an increase in real gdp, given that the economy is dependent on energy (apergis and payne, 2009). sadorsky (2010; 2011), and mukhtarov et al. (2020b) mentioned three effects of findev that lead to an increase in encon. an initial effect is that with higher findev, consumers can easily borrow funds to purchase air this journal is licensed under a creative commons attribution 4.0 international license mukhtaro, et al.: the effect of financial development on energy consumption: evidence from russia international journal of energy economics and policy | vol 12 • issue 1 • 2022244 conditioners, automobiles, etc., leading to an increase in encon. in the other hand, in a well-functioning financial system, businesses can easily access financing to invest their capital and current assets in their business. the third effect appears in the form of wealth growth. it is known that more wealth can stimulate economic activity and increase encon. considering the above facts, it is important to analyse the nexus between findev and energy use in russia, the 11th largest economy in the world according to an imf report. clearly russia is a country with a very high potential of energy resources (amelia, 2008; bayraç, 2009; mitrova and melnikov, 2019). it produces the highest amount of crude oil, as well as condensate, and it is the second largest producer of dry natural gas. russia also produces an important amount of coal. with these resources, it can be said that russia has a significant influence on the global market (eia, 2021; kutcherov et al., 2020; su et al., 2020). considering that russia produces just 3% of world gdp and has just 2% of the world population, it is impressive that it is the world’s thirdbiggest producer and consumer of energy resources, after china and the us. with energy production of nearly 1470 mtoe, russia exports a major portion of the primary energy it produces while supplying 16% of the global cross-regional energy trade, which makes russia the world leader in energy exports (eri ras, 2019). further, russia’s energy density is 2.19 times more than the world average density, and it exceeds the comparable index for european union (eu) countries by 3.08 times. in 2007-2018 the russian gdp grew by 14%, while it reduced encon by 12% (acgrf, 2020). in russia, several financial methods were developed to implement activities in the field of energy efficiency, though the main restriction regarding the implementation of an energy performance policy is the lack of present long-term borrowed funds. accordingly, the most important function for the state is to create additional financing methods while maintaining the existing ones (matraeva et al. 2019). therefore, it is of great importance to research the extent and the long-term consequences of the relationship between the level of findev and the level of encon. as far as we know, no research has been conducted on the nexus between encon and findev in russia, employing different time-series methods, namely vecm, ccr, dols, and fmols that allow for the examination of country-specific aspects of this association. as a result, the goal of this research is filling this gap by investigating the influence of findev on encon for russia, one of the largest crude oil producing economies, a unique case study for this study. the outputs of the research have significant implications for policymakers to formulate appropriate policies for sustainable energy use. moreover, the outputs of this paper are also important for post-soviet and developing oil-rich countries. the research's results are crucial for politicians as it will enable them to create appropriate policies in courtesy of sustainable encon. furthermore, the findings of this paper are significant for other post-soviet countries as well as developing oil-rich countries. the remaineder of the study is laid out as following: section 2 summarizes literature review. section 3. contains the method and data. section 4 contains the empirical findings and the last, section 5, contains the conclusion and suggestion. 2. literature review a significance amount of empirical research and publications are focused on the impact of findev on encon in different countries with various funding models. sadorsky (2010) studied the impact of findev on encon in 22 emerging economies using annual data for the period of 1990-2006. using ardl, vecm and panel gmm models, he reported positive impact. zhang et al. (2011) examined how the chinese stock market influenced encon via the granger causality test using 1992-2009 annual data, reporting a positive nexus. many other studies such as coban and topcu (2013), al-mulali and lee (2013), islam et al. (2013), chang (2014), komal and abbas (2015) and mukhtarov et al. (2018) found positive effects of findev on encon in various countries. also, gaies et al. (2019) found the same result for mena countries using the gmm model with 1996-2014 annual data. however, ali et al. (2015) reported a negative effect of findev on encon in nigeria employing the ardl model from 1972q1 to 2011q4. applying ardl, johansen cointegration, vecm and granger causality test to annual data for the timeframe 1971-2008, shahbaz and lean (2012) reported a bidirectional causality between findev and encon in tunisia. kahouli (2017) and bekhet et al. (2017) reported long run cointegration between findev and encon using ardl models for the south mediterranean and gulf cooperation council countries respectively. since financial series exhibit nonlinear structures aliyev (2019), we look at some studies that focus on nonlinear dynamics. mahalik et al. (2017) reported a non-linear inverted u-shaped association between findev and encon for the period of 1971-2011 using cointegration test and ardl model in saudi arabia. in recent studies, danish et al. (2018), khan et al. (2019), and mukhtarov et al. (2020a) reported positive effect of findev on encon employing the dsur, 3sls, gmm, and vecm methods. karacan et al. (2021) studied the impact of carbon dioxide emissions, income, and oil prices on renewable encon in russia employing the canonical cointegrating regression method and the vecm method for the period of 1990-2015. they found a negative relationship between oil prices and renewable encon, and a positive relationship between real gdp per capita and renewable encon. table 1 summarizes this literature review. as seen from this review, the impact of findev on encon in russia has not been intensively studied using vecm, ccr, dols and fmols techniques for a wider timespan. 3. model and data 3.1. equational specification and data lnencon lnfindev lneg lncpit t t t t� � � � �� � � � �0 1 2 3 # (1) following mukhtarov et al. (2018) and mukhtarov et al. (2020a), the functional specifications in this paper are described as below: mukhtaro, et al.: the effect of financial development on energy consumption: evidence from russia international journal of energy economics and policy | vol 12 • issue 1 • 2022 245 growth (eg) is proxied by real gdp per capita (2010 us dollars). the consumer price index (cpi) (2010=100) is used to measure the energy prices. because data on energy prices for all countries and all years is not readily available, energy prices are proxied by the consumer price index, as in previous studies by sadorsky (2010; 2011), komal and abbas (2015), chang (2015), mukhtarov et al. (2018), mukhtarov (2020a), and mukhtarov (2020b). the data for encon was compiled from enerdata (enerdata, 2021) while findev was obtained from the database of federal reserve bank of st. louis (fred, 2021). the eg and cpi data were provided table 1: overview of empirical researches in the literature author (s) time period country method (s) result (effect of findev on encon) sadorsky (2010) annual, 1990-2006 22 emerging countries ardl, vec granger causality and panel gmm positive zhang et al. (2011) annual, 1992-2009 china granger causality positive sadorsky (2011) annual, 1996-2006 central and eastern european panel gmm positive al-mulali and sab (2012) annual, 1980-2008 sub-saharan african economies vecm and pedroni cointegration encon has an important role to raise findev. al-mulali and sab (2012) annual, 1980-2008 19 developing and developed economies vecm and pedroni cointegration findev is cointegrated with encon. shahbaz and lean (2012) annual, 1971-2008 tunisia ardl, johansen cointegration, vecm and granger causality there is a long-run bidirectional causality between findev and encon. coban and topcu (2013) 1990-2011 eu gmm positive al-mulali and lee (2013) annual, 1980-2009 gcc economies pedroni cointegration and ols positive islam et al. (2013) annual, 1971-2009 malaysia ardl and vecm positive ali et al. (2015) quarterly, 1972-2011 nigeria ardl negative chang (2014) annual, 1999-2008 53 economies ipat model positive komal and abbas (2015) annual, 1972-2012 pakistan gmm positive alam et al. (2015) annual, 1975-2011 saarc countries panel cointegration test positive furuoka (2015) annual, 1980-2012 12 asian countries heterogeneous panel causality test positive shahzad et al. (2017) annual, 1971-2011 pakistan ardl there is a bi-directional causality between encon and findev. kahouli (2017) annual, 1995-2015 6 smcs ardl and vecm there is a long run cointegration between findev and encon. bekhet et al. (2017) annual, 1980-2011 gcc countries ardl there is a relationship between encon and findev in the long run. mahalik et al. (2017) annual, 1971-2011 saudi arabia cointegration test and ardl precense of a non-linear inverted u-shaped association between findev and encon. mukhtarov et al. (2018) annual, 1992-2015 azerbaijan adf, ardl and vecm positive danish et al. (2018) 1990-2014 next-11 countries dsur method positive gómez and rodríguez (2019) annual, 1971-2015 nafta economies dynamic ols and fully modified ols negative gaies et al. (2019) annual, 1996-2014 mena countries gmm positive khan et al. (2019) annual, 1990-2017 193 countries 3sls and gmm positive mukhtarov et al. (2020a) 1993-2014 kazakhstan vecm positive where, encont represents energy consumption, findevt is financial development, egt denotes economic growth, cpit denotes consumer price index as measure of energy prices, and εt is an error term. we utilized 1995-2019 annual data for the encon, findev, economic growth and energy prices. the dependent variable is encon, and is expressed by kilogram of oil equivalent. our key independent variable is findev, which is expressed by domestic loans to the private sector as a percentage of gdp. economic mukhtaro, et al.: the effect of financial development on energy consumption: evidence from russia international journal of energy economics and policy | vol 12 • issue 1 • 2022246 from the world bank database (wb, 2021). we used logarithmic expressions of all variables for empirical estimation. 3.2. methodology we evaluated the effect of findev, economic growth, and energy prices expressed by cpi on encon using the vecm, ccr, dols, and fmols techniques. in the beginning step, the augmented dickey fuller (adf) unit root test is employed to define non-stationarity characteristics of variables under study. as the next step, since the orders of integration of the variables are the same, johansen cointegration test is used to define if they are cointegrated. ultimately, we applied the vector error correction model (vecm) to assess the long-term relationship between the variables. the vecm method is the first-best choice if there is just one cointegration link between the variables under study. in order to achieve more reliable findings, we also used the canonical cointegrating regression (ccr), fully modified ordinary least squares (fmols), and dynamic ordinary least squares (dols) tests. to conserve space and avoid confusing readers with econometric complexities, we do not discuss the above-mentioned approaches here. in addition, these methods are extensively used and wellknown. dickey and fuller (1981), johansen (1988), phillips and hansen (1990), johansen and juselius (1990), hansen (1992a; b), park (1992), and stock and watson (1993), have all published research that provide extensive information. 4. empirical findings and discussion adf unit root test verifies the stationarity characteristics of the variables and the findings of adf are summarized in table 2. as seen from the test results all variables are non-stationary at their level, though they are stationary at their first difference. thus, the cointegration test may be applied. to identify the optimal lag interval on the sample, a vector auto regressive (var) model with the endogenous variables of encon, findev, eg, and cpi was initially specified through a random-selected lag interval, then defining test of lag interval was employed to the model residuals. table 3 shows the results of the analysis. in this study, three lag selection criteria indicated that a lag of order two is optimum, which is naturally suitable regarding the less observations in the sample. it’s worth noting that, the var model with two lags successfully passes all residual diagnostic tests, as well as the stability test, as exhibited on panels a-d of table 4. panels e and f of the table 4 above show the outputs of the johansen cointegration test on the transposed form of the var, that is the vecm model with one lag. the variables have one cointegration relationship, according to the trace and maxeigenvalue test results. thus, we decide that the variables under study are cointegrating. having verified the cointegration among the variables, vecm, ccr, dols, and fmols techniques are utilized to assess coefficients of the long-run link among the variables. if there is just one cointegration link between the variables, the vecm technique is the first-best option. furthermore, the vecm residuals were explored in diagnostic testing. table 5 shows the outputs of the vecm, ccr, dols, and fmols techniques. table 5 shows that vecm residuals carry no problems about serial correlation, instability or heteroscedasticity. as a consequence, the assessed specifications’ residuals fulfill the requirements of residual diagnostics tests, confirming the estimation findings’ robustness. as seen from the outputs, the long-run coefficients of all approaches are statistically significant and remarkably near in significance value and sign. the outputs of the vecm model, which are exhibited on the top row of table 5, are prioritized, as stated in the methodology. according to the vecm findings, findev has a statistically significant positive impact on encon. according to the findings, a 1% rise in findev caused a 0.02% rise in encon. this means that when findev increases, so does the demand for energy. our findings are consistent with several studies conducted by sadorsky (2011), shahbaz and lean (2012), coban and topcu (2013), islam et al. (2013), mallick and mahalik (2014), tang and tan (2014), shahbaz (2015), mahalik et al. (2017), mukhtarov et al. (2018), and mukhtarov et al. (2020a) for different economies. furthermore, we discovered that eg has a positive and statistically significant influence on encon. and this means that a 1% increase in eg corresponds to a 0.45% increase in encon. the results we obtained are in line with the traditional expectation. furthermore, according to the findings, energy prices table 3: lag interval tests information criteria lag logl lr fpe aic sc hq 0 −649.2032 na 5.47e+19 56.80028 56.99776 56.84994 1 −537.0302 175.5751* 1.31e+16 48.43741 49.42480* 48.68574 2 −515.9300 25.68723 9.78e+15* 47.99391* 49.77121 48.44090* *refers to lag order selected by the criterion table 2: adf unit root test results variables level 1st difference result actual value actual value encon 0.0126 −5.0703*** i (1) findev 0.1612 −3.3827** i (1) eg −0.6905 −3.6405`** i (1) cpi 1.9667 −3.4132** i (1) notes: at 10%, 5%, and 1% significance levels, accordingly, *, **, and *** imply null hypothesis rejection mukhtaro, et al.: the effect of financial development on energy consumption: evidence from russia international journal of energy economics and policy | vol 12 • issue 1 • 2022 247 represented with cpi has a negative and statistically significant influence on encon, which is reflected in economic theory. 5. concluding remarks this paper examines the influence of findev, economic growth, and energy prices denoted with cpi on encon in russian federation. adf unit root test results show all variables have the same integration order, which is i(1). therefore, the cointegration link between the variables may then be tested. long-run comovement was tested using the johansen cointegration test. the vecm, dols, ccr and fmols techniques were employed to estimate possible long-run relationships. the empirical results stated that findev and economic growth exhibit positive effect on encon, whereas the energy prices expressed by cpi has a negative impact on encon in russia. the positive influence of economic growth on encon shows that russia uses its expanding revenues to increase energy sources. the positive impact of findev, as measured by bank loans to the private sector as gdp, indicates that the russian financial system leads to a reduction in both material and transaction costs in debt markets. this enables households and companies to find “easy” money. in this way, economic units that earn more income will be able to buy the goods and services they need. since an increase in findev results in higher encon and that findev is a favourable economic outcome, a policy recommendation from our findings is that the russian government should exploit alternative energy resources such as hydropower, wind and biomass. considering the positive impact of economic growth on encon, transition from fossil fuels to renewable energy resources is important for sustainable economic growth within russia. moreover, our findings suggest to policymakers as well as to researchers the need to envision the relationships between findev, economic growth, and encon for sustainable development goals and federal macroeconomic stability in russia and similar oil-rich countries. table 4: the outcomes of var residual diagnostics and cointegration tests. panel a: lm test panel e: trace rank test (johansen cointegration) lags lm-statistic p‑value null hypothesis eigenvalue trace statistics 0.05 critical value p‑value 1 20.81359 0.1858 none* 0.849359 71.15367 55.24578 0.0011 2 18.81412 0.2784 at most 1 0.580314 27.61805 35.01090 0.2470 3 7.072581 0.9718 at most 2 0.272330 7.648327 18.39771 0.7186 4 14.70726 0.5462 at most 3 0.014522 0.336448 3.841465 0.5619 panel b: normality testb panel f: maximum eigenvalue rank test (johansen cointegration) statistic ᵡ2 d.f. p‑value null hypothesis: eigenvalue max‑eigen statistic 0.05 critical value p‑value jarque-bera 12.879 8 0.116 none* 0.849359 43.53562 30.81507 0.0009 at most 1 0.580314 19.96972 24.25202 0.1668 at most 2 0.272330 7.311880 17.14769 0.6788 panel c: test for heteroscedasticityc at most 3 0.014522 0.336448 3.841465 0.5619 white ᵡ2 d.f. p‑value statistic 166.95 160 0.337 panel d: test for stability modulus root 0.952699 0.952439−0.022284i 0.952699 0.952439+0.022284i 0.591714 0.328937−0.491859i 0.591714 0.328937+0.491859i athe null hypothesis of the lm test refers to absence of serial correlation in residuals at a 2nd order lag; bthe hypothesis of the normality test represents multivariate normality of residuals; cthe null hypothesis of the white heteroscedasticity test affirms that the residuals have no cross terms heteroscedasticity; d the results of the var stability test assert that all of the characteristic polynomial’s roots are limited inside the unit circle; ᵡ2= the chi-square distribution; d.f. represents degree of freedom. table 5: long‑run coefficients of different methods methods coefes. (t-statistic) findev eg cpi coefes. (t-statistic) coefes. (t-statistic) vecm 0.02 (5.301)*** 0.45 (6.289) *** −0.10 (−5.008) *** ccr 0.02 (3.790)*** 0.39 (5.535) *** −0.05 (−2.303)** dols 0.01 (2.954)*** 0.36 (5.001) *** −0.04 (−1.804) * fmols 0.02 (3.811)*** 0.40 (4.551) *** −0.05 (−1.887) * outcomes of vecm residuals diagnostics tests lmsc 14.69 [0.547] ᵡ2hete 99.66 [0.491] jbn 13.41 [0.098] encont shows dependent variable; ***, **, and * represent significance levels of 1%, 5%, and 10%, accordingly; p values are in brackets; lmsc represents lagrange multiplier statistic for serial correlation test; ᵡ2hete represents chi-squared statistic for heteroscedasticity; jbn test represents jarque-bera statistic for normality test mukhtaro, et al.: the effect of financial development on energy consumption: evidence from russia international journal of energy economics and policy | vol 12 • issue 1 • 2022248 references alam, a., malik, i.a., abdullah, a.b., hassan, a., faridullah, a.u., ali, g., zaman, k., naseem, i. (2015), does financial development contribute to saarc’s energy demand? from energy crisis to energy reforms. renewable and sustainable energy reviews, 41, 818-829. ali, h.s., yusop, z.b., hook, l.s. (2015), financial development and energy consumption nexus in nigeria: an application of autoregressive distributed lag bound testing approach. international journal of energy economics and policy, 5(3), 816-821. aliyev, f. (2019), testing market efficiency with nonlinear methods: evidence from borsa istanbul. international journal of financial studies, 7(2), 27. al-mulali, u.; sab, c.n.b.c. (2012), the impact of energy consumption and co2 emission on the economic growth and financial development in the sub saharan african countries. energy, 39, 180-186. al-mulali, u.; sab, c.n.b.c. (2012), the impact of energy consumption and co2 emission on the economic and financial development in 19 selected countries. renewable and sustainable energy reviews, 16, 4365-4369. al-mulali, u., lee, j.y. (2013), estimating the impact of the financial development on energy consumption: evidence from the gcc (gulf cooperation council) countries. energy, 60, 215-221. amelia, h. (2008), eu-russia energy relations: aggregation and aggravation. journal of contemporary european studies, 16(2), 231-248. analytical center for the government of the russian federation (acgrf). (2020), voluntary national review of the progress made in the i̇mplementation of the 2030 agenda for sustainable development. available from: https://www.sustainabledevelopment. un.org/content/documents/26962vnr_2020_russia_report_english. pdf [last accessed on 2021 sep 05]. apergis, n., payne, j.e. (2009), energy consumption and economic growth in central america: evidence from a panel co-integration and error correction model. energy economics, 31(2), 211-216. bayraç, h.n. (2009), global energy policies and turkey: a comparison regarding oil and natural gas resources. esogu journal of social sciences, 10(1), 115-142. bekhet, h.a., matar, a., yasmin, t. (2017), co2 emissions, energy consumption, economic growth, and financial development in gcc countries: dynamic simultaneous equation models. renewable and sustainable energy reviews, 70, 117-132. burakov, d., freidin, m. (2017), financial development, economic growth and renewable energy consumption in russia: a vector error correction approach. international journal of energy economics and policy, 7(6), 39-47. chang, s.c. (2015), effects of financial development and income on energy consumption. international review of economics and finance, 35, 28-44. coban, s., topcu, m. (2013), the nexus between financial development and energy consumption in the eu: a dynamic panel data analysis. energy economics, 39, 81-88. dickey, d., fuller, w. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica, 49, 1057-1072. danish, s.s., baloch, m.a., lodhi, r.n. (2018), the nexus between energy consumption and financial development: estimating the role of globalization in next-11 countries. environ sci pollut res 25, 18651–18661. https://doi.org/10.1007/s11356-018-2069-0 enerdata (2021). russia related research. available online: https:// www.enerdata.net/estore/energy‐market/russia/ [last accessed on 2021 sep 02]. federal reserve bank of st. louis-fred. (2021), federal reserve economic data. available from: https://www.fred.stlouisfed.org [last accessed on 2021 feb 11]. furuoka, f. (2015), financial development and energy consumption: evidence from a heterogeneous panel of asian countries. renewable and sustainable energy reviews, 52, 430-444. gaies, b., kaabia, o., ayadi, r., guesmi, k., abid, i. (2019), financial development and energy consumption: is the mena region different? energy policy, 135, 111000. gómez, m., rodríguez, j.c. (2018), energy consumption and financial development in nafta countries, 1971-2015. applied sciences, 9(2), 1-11. hansen, b.e. (1992a), efficient estimation and testing of co-integrating vectors in the presence of deterministic trends. journal of economics, 53, 87-121. hansen, b.e. (1992b), tests for parameter instability in regressions with i(1) processes. journal of business and economic statistics, 10, 321-335. imf, world economic outlook database. (2018), available from: https:// www.imf.org/external/pubs/ft/weo/2018/01/weodata/download.aspx [last accessed on 2019 aug 09]. islam, f., shahbaz, m., ahmed, a.u., alam, m.m. (2013), financial development and energy consumption nexus in malaysia: a multivariate time series analysis. economic model, 30, 435-441. johansen s., juselius, k. (1990), maximum likelihood estimation and inference on co-integration with applications to the demand for money. oxford bulletin of economics and statistics, 52, 169-210. johansen, s. (1988), statistical analysis of co-integration vectors. journal of economic dynamics and control, 12, 231-254. kahouli, b. (2017), the short and long run causality relationship among economic growth, energy consumption and financial development: evidence from south mediterranean countries (smcs). energy economics, 68(c), 19-30. karacan, r., mukhtarov, s., barış, i̇., i̇şleyen, a., yardımcı, m.e. (2021), the impact of oil price on transition toward renewable energy consumption? evidence from russia. energies, 14(10), 2947. keskingöz, h., i̇nançlı, s. (2016), the causality between financial development and energy consumption in turkey: the period of 1960-2011. eskişehir osmangazi university journal, 11(3), 101-114. khan, m.t.i., yaseen, m.r., ali, q. (2017), dynamic relationship between financial development, energy consumption, trade and greenhouse gas: comparison of upper middle income countries form asia, europe, africa and america. journal of cleaner production, 161, 567-580. khan, s., peng, z., li, y. (2019), energy consumption, environmental degradation, economic growth and financial development in globe: dynamic simultaneous equations panel analysis. energy reports, 5, 1089–1102. komal, r., abbas, f. (2015), linking financial development, economic growth and energy consumption in pakistan. renewable and sustainable energy reviews, 44, 211-220. kutcherov, v., maria, m., valery, b., alexey, l. (2020), russian natural gas exports: an analysis of challenges and opportunities. energy strategy reviews, 30, 100511. mahalik, m.k., babub, m.s., loganathan, n., shahbaz, m. (2017), does financial development intensify energy consumption in saudi arabia? renewable and sustainable energy reviews, 75, 1022-1034. matraeva, l., solodukha, p., erokhin, s., babenko, m. (2019), improvement of russian energy efficiency strategy within the framework of “green economy” concept (based on the analysis of experience of foreign countries). energy policy, 125, 478-486. mitrova, t., melnikov, y. (2019), energy transition in russia. energy transit, 3, 73-80. mukhtarov, s., humbatova, s., hajiyev, n.g.o., aliyev, s. (2020b), the financial development-renewable energy consumption nexus in the mukhtaro, et al.: the effect of financial development on energy consumption: evidence from russia international journal of energy economics and policy | vol 12 • issue 1 • 2022 249 case of azerbaijan. energies, 13, 6265. mukhtarov, s., humbatova, s., seyfullayev, i., kalbiyev, y. (2020a), the effect of financial development on energy consumption in the case of kazakhstan. journal of applied economics, 23(1), 75-88. mukhtarov, s., mikayilov, j.i., mammadov, j., mammadov, e. (2018), the impact of financial development on energy consumption: evidence from an oil-rich economy. energies, 11, 1536. park, j. (1992), canonical co-integrating regressions. econometrica, 60, 119-143. phillips, p.b., perron, p. (1988), testing for unit roots in time series regression. biometrika, 75, 335-346. sadorsky, p. (2010), the impact of financial development and energy consumption in central and eastern european frontier economies. energy policy, 39, 999-1006. sadorsky, p. (2011), financial development and energy consumption in central and eastern european frontier economies. energy policy, 39, 999-1006. shahbaz, m., lean, h.h. (2012), does financial development increase energy consumption? the role of industrialization and urbanization in tunisia. energy policy, 40, 473-479. shahzad, s.j.h., kumar, r.r., zakaria, m., hurr, m. (2017), carbon emission, energy consumption, trade openness and financial development in pakistan: a revisit. renewable and sustainable energy reviews, 70, 185-192. stock, j.h., watson, m. (1993), a simple estimator of co-integrating vectors in higher order integrated systems. econometrica, 61, 783820. su, c.w., meng q., ran, t., muhammad, u. (2020), does oil price really matter for the wage arrears in russia? energy, 208, 118350. tang, c.f., tan, b.w. (2014), the linkages among energy consumption, economic growth, relative price, foreign direct investment, and financial development in malaysia. quality and quantity, 48, 781-797. the energy research institute of the russian academy of sciences (eri ras). (2019), global and russian energy outlook 2019. available from: https://www.eriras.ru/files/forecast_2019_en.pdf [last accessed on 2021 sep 04]. world bank (wb). (2021), financial development. washington, dc, united states: world bank. available from: https://www. worldbank.org/en/publication/gfdr/gfdr-2016/background/financialdevelopment [last accessed on 2021 sep 02]. wo r l d b a n k ( w b ) . ( 2 0 2 1 ) , wo r l d d e v e l o p m e n t i n d i c a t o r s . washington, dc, united states: world bank. available from: https://www.data.worldbank.org/indicator [last accessed on 2021 feb 11]. zhang, y.j., fan, j.l., chang, h.r. (2011), impact of china’s stock market development on energy consumption: an empirical analysis. energy procedia, 5, 1927-1931. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 5 • 2022 311 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(5), 311-318. the economic impact of renewable energy on sustainable development in saudi arabia houcine benlaria1*, abu alhassan jumaa hamid hamad2 1department of business administration, jouf university, sakakah, saudi arabia, 2college of science and humanity studies, prince sattam bin abdulaziz university, al-kharj, saudi arabia. *email: hbenlaria@yahoo.fr received: 13 may 2022 accepted: 20 august 2022 doi: https://doi.org/10.32479/ijeep.13289 abstract this paper studies the asymmetric relationship between renewable energy consumption and economic growth incorporating capital and labor for the case of saudi arabia during the period 1990–2019. the nonlinear lagged cointegration (nardl) model is applied to examine the asymmetric cointegration between the variables. the results indicate that there is an asymmetric relationship between the variables considered. the negative labor shock improves economic growth, while a positive shock reduces (increases) economic growth in the short term. therefore, policies to promote economic growth, such as the need to improve the quality of financial development and preserve fiscal sustainability, are crucial to improve the renewable energy sector in saudi arabia. at the same time, it is essential that the renewable energy sector must also be oriented towards productive development projects. keywords: asymmetry, economic growth, nardl, renewable energy consumption, shocks jel classifications: q01, q43, q43, q47 1. introduction this amount includes oil and gas. but the consumption of traditional energy has two problems: first, the problem of import; and second, the problem of the greenhouse effect. for the import, oil is a strategic and very expensive asset. that is why over the years, following an oil shock, economic difficulties have arisen all over the world. developed countries such as europe and north america have planned to consume renewable energy, because this energy decreases the dependence of foreign countries and it is safe and healthy (menegaki, 2011). renewable energy created 18% of electricity production worldwide in 2007. in europe-27, energy created by wind is the highest (in renewable energy). after the wind, there is the energy created by the sun and then by biomass which are the most common. but the hydro-based energy had a negative growth in the years 1997-2007. <7% of energy in europe comes from renewable energy (menegaki, 2011). some european countries like denmark, germany and the uk increased their energy exports. in other words, renewable energy technologies have found a global market to sell and to create jobs. for example, germany sold renewable energy instruments worth 21.6 billion euros and created 200,000 jobs in 2006. denmark created 20,000 jobs in the field of wind energy (lund, 1999). currently, the gdp for each country is very important, as it shows the market size and the inhabitants’ purchasing power. if there is a significant relationship between the market size and the consumption of renewable energy, countries can apply and develop the consumption of this energy. therefore, the objective of this article is to study the causal relationship between renewable energy consumption and economic growth. apergis and payne (2010), using variables such as capital formation, gdp, labor and renewable energy consumption, showed that in eurasia there is a bidirectional relationship between economic growth and renewable energy consumption. they reported the same result for oecd countries in 2010. sadorsky (2009), wolde-rufael (2010), and menegaki (2011) have also studied the relationship between economic growth and renewable energy consumption. lund (1999) showed that subsidizing renewable energy will increase the number of jobs in denmark. this journal is licensed under a creative commons attribution 4.0 international license benlaria and hamad: the economic impact of renewable energy on sustainable development in saudi arabia international journal of energy economics and policy | vol 12 • issue 5 • 2022312 saudi arabia, aware of the interest of investment in this sector, has given great importance to the subject of renewable energies through the implementation of structural reforms since the 1990s, as part of a general policy of opening the saudi economy and its insertion in the international market. these strategies also aim to develop the national potential through the privatization of the distribution and refining of petroleum products as well as the transfer of the management of electricity and water distribution to private operators. this model is a strategic choice that allows to strengthen the security of supply and the efficiency of energy resources, in order to optimize the costs of energy services and to protect the environment by reducing greenhouse gas emissions. indeed, the saudi electricity company, the national power company, controls 70% of the country’s electricity generation with a total installed capacity of 53.4 gw. at the end of 2019, the kingdom’s installed capacity was 76.8 gw, with the electricity mix dominated by gas-fired power plants. with economic development and population growth, the installed electrical power should reach 171 gw in 2030. renewable energies should represent 34% of the electricity production capacity by this deadline. increases in electricity tariffs in 2016 and 2018 caused a sharp slowdown in consumption growth (eia, 2019). to achieve these objectives, saudi arabia plans to increase the volume of investments in this sector by 40 billion dollars by 2030, including 30 billion dollars for renewable energies (ome, 2021). it also aims to modify the structure of the energy consumed by granting a higher share to renewable energies; which would thus rise from 42% in 2020 to 52% in 2030. the remainder of the article is organized as follows. the first section is devoted to the analysis of the energy sector in morocco. the second presents a review of the literature relating to the question studied. the third section consists of empirically examining the impact of the use of renewable energies on economic growth and co2 emissions through an econometric model. the fourth and last section is devoted to the conclusion and the formulation of recommendations. 2. literature review a first-generation study based on the var method, carried out in 1978 by kraft and kraft on the american economy between 1947 and 1974, revealed the existence of a unidirectional causality which shows that in the united states, it is the gross national product that causes energy consumption. this result suggests that it is possible to envisage energy-saving policies without negative effects on economic growth. this analysis will be challenged by several researchers, namely akarka and long (1980), who were able to demonstrate that the kraft and kraft study was biased due to temporal instability at the sample level of the data used. they therefore resumed the analysis with the same technique, over a more homogeneous period from 1950 to 1968. the test revealed a lack of causality between gdp and energy consumption. virtually all of the articles that followed were devoted to the american series with very varied results (cf. for example yu and hwang (1984), yu and choi (1985)). over the past few decades, a large empirical literature has developed, focusing on the relationship between energy consumption, including renewable energy, and economic growth. this literature, known as the energy-economy-nexus, emerged in response to the global oil crisis of the 1970s and the ensuing reduction in energy supply. it is within this literature that (apergis and danuletiu, 2014) examined the relationship between renewable energy consumption and economic growth for 80 countries, using the canning and pedroni long-term causality test. the two authors showed the existence of a long-term positive causality between renewable energies and real gdp for the whole sample as well as for the different regions. the interdependence between renewable energy consumption and economic growth indicates that renewable energy is not only important for environmental quality but also for economic growth. along the same lines, (behname, 2012) examined the long-term as well as the short-term causal relationship between renewable energy consumption and economic growth in western european countries for the period 1995–2010. the pedroni test used revealed a long-term relationship between the two variables. it follows that there is a long-term and a short-term bidirectional relationship between economic growth and renewable energy consumption. another study, by (lekana, 2019), confirms some of the previous results. this work focused on cemac countries for the period 1990 and 2015 and used three panel data error correction models (mg pmg and dfe) and two causality approaches (the engel and granger causality and the dumitrescu and hurlin causality). the results showed that renewable energy consumption has a positive long-term effect, but has a negative short-term effect on economic growth in these countries. more recently, (saidi and omri, 2020) examined the effectiveness of renewable energy in promoting economic growth and reducing co2 emissions in the case of 15 countries, using ordinary least squares and vector error correction model estimation techniques. the results affirm the presence of a bidirectional causal relationship between economic growth and renewable energy in the short and long terms. on the other hand, (chen et al., 2019) explored the relationships between carbon dioxide emissions, economic growth, renewable and non-renewable energy consumption in three regions in china for the period 1995-–2012. one of the main conclusions obtained in this work is the existence of bidirectional causal relationships in the long term between renewable energy, co2 emissions and economic growth in all regions. finally, we can cite the work of (bilan et al., 2019). the authors examined the impact of a country’s use of renewable energy sources, co2 emissions, macroeconomics, and political stability on gross domestic product. for eu countries, reslike human and capital resourceshave an impact on gdp. furthermore, the results reveal a retraction of the correction when economic growth leads to an increase in renewable energy consumption. finally, the work reveals that candidate countries and potential candidate countries for eu membership should favor the development of renewable energy. finally, the work reveals that candidate countries and potential candidate countries for eu membership should promote the development of renewable energy. benlaria and hamad: the economic impact of renewable energy on sustainable development in saudi arabia international journal of energy economics and policy | vol 12 • issue 5 • 2022 313 adewuyi and awodumi (2017) provide a literature review of studies on the energy-growth-emissions relationship over the past two decades. they note that very few studies have combined the analysis of renewable energy, non-renewable energy, and co2 emissions in a single model. beyond the control of the variables’ omission bias, the multi-variable models allow to evaluate the relationship between the consumption of renewable energies and sustainable development on the one hand. on the other hand, the level of renewable energy sources aggregation affects the results. a low level of aggregation of the energy sources allows to test the hypotheses on the relationship between the renewable and the non-renewable energy sources. this approach could allow to take into account each country’s specificities in terms of renewable energy development strategies (allocation of production sources, economic policies and incentives). to the best of our knowledge, only pao and fu (2013) opted for a level of aggregation that allows for successive analysis of wind energy consumption (including biomass), total renewable energy consumption, and total non-renewable energy consumption. in addition, omission bias may remain insofar as the variables considered in the studies may fail to take into account the political and institutional context. indeed, in north african countries, komendantova et al., (2012) identify three types of risks that affect foreign direct investment in renewable energy. these risks are regulatory, political and terrorist. the complexity of administrative procedures, corruption, instability of national regulations, lack of guarantee from the national government, lack of involvement of local authorities and political instability are barriers to private investment in solar power projects. these barriers not only increase the cost of new investments but also decrease the quality and efficiency of investments already made. 3. methodology our objective is to highlight the relationship between renewable energy consumption and sustainable development over the period 1990–2019 in saudi arabia. to do so, we use gdp as a proxy for welfare and assume the following relationship: ln ln lngd ren xt t t t� � � �� � � � (1) where ingpt and inrent are respectively the renewable energy consumption and the constant gdp (2010) expressed in natural logarithm. xt is a vector of control variables including human capital and labor force; εt denotes the error term and α, β and θ are the co-integration parameter vectors to be estimated. in order to account for the asymmetric relationship both in the long and short terms between the two variables, we apply the new cointegration approach of shin et al., (2014) namely, the nonlinear distributed lag (nardl) co-integration model. the asymmetric cointegration relationship can be expressed as follows knowing the control variables: ln lngd ren ren rent t t t t� � � � � � � � �� � � � � (2) where in gdt denotes the natural logarithm of gdp and in rent indicates the logarithm of renewable electricity production. in rent + as well as in rent – are the partial sum processes associated with negative and positive shocks in in rent defined by: ln ln max( ln , ) ln ln ren ren ren ren ren t j j t j j t t j j � � � � � � � � � � �� � � 1 1 0 �� � � �� 1 1 0 t j j t renmax( ln , )� (3) � � and β– are the associated asymmetric long-term parameters. the extension of the distributed lag model, proposed by shin et al., (2014) provides the following asymmetric error correction model and knowing the control variables: � � ln ln ln ln ln gdp gdp ren ren gdp t t t t i t i i � � � � � � � � � � � � � � � � � � � 1 1 1 1 pp i t i i t i i q tren ren � � � � � � � � � � �� � � 1 0 1 ( ln ln )� � �� � (4) where the р and q symbols are the number of delays associated with gdpt and rent respectively. the nardl model expressed in this way has several advantages. firstly, it allows to estimate by the technique of moments and by the exogenous variable decomposition in positive and negative partial sums. second, we can test the long-term relationship between the levels of the variables in gdpt, in rent and in eg – t (i.e. 𝜌 = β + = β– =0) by using the fpss statistic suggested by pesaran et al., (2001) and shin et al., (2014). the tbneg statistic proposed by banerjee et al., (1998) can test the null hypothesis against the alternative hypothesis 𝜌 < 0. the estimation can provide valid statistical inferences regardless of whether the exogenous variables are stationary, nonstationary, or a mixture of the two. we can therefore calculate the long-term asymmetric coefficients as follows: in ren+= �̂�+⁄𝜌 and in ren– �̂�−⁄𝜌. third, the standard wald statistic can be used to examine long-term symmetry t 𝛽 = 𝛽+ = 𝛽− as well as the shortterm symmetry which could take one of these two following forms: � �i i � �� for every 𝑖 = 1, 𝑞−1 where � �i i q i i q � � � � � � � �� � 0 1 0 1 0 . finally, the effect of a one percent change in the dynamic asymmetric multipliers respectively rent� � 1 and rent− − 1 on gdpt can be expressed as follows: ren gdp renh t j tj h � � � � � � � � � 10 and ren gdp renh t j tj h � � � � � � � � � 10 for h = 0 1 2, , ,... (5) if h � �, then ren lh ren � � � and ren lh ren � � � in order to test for short-term symmetry, we use the wald statistic, and if symmetry was not rejected, then the nardl equation (4) could be simplified by the following asymmetric long-term relationship: � � ln ln ln ln ln gdp gdp ren ren gdp t t t t i t i i � � � � � � � � � � � � � � � � � � � 1 1 1 1 pp i t i i q tren � � � � � � � � 1 0 1 � ��ln (6) benlaria and hamad: the economic impact of renewable energy on sustainable development in saudi arabia international journal of energy economics and policy | vol 12 • issue 5 • 2022314 on the other hand, if long-term symmetry was not rejected, then equation (4) could be simplified to a nardl with an asymmetric short-term relationship: � � ln ln ln ln ln gdp gdp ren ren gdp t t t t i t i i � � � � � � � � � � � � � � � � � � � 1 1 1 1 pp i t i i q i t i tren ren � � � � � � � � � � � � � � 1 0 1 ( ln ln )� � �� � (7) 4. descriptive statistics and stationary unit root tests we used annual time series for saudi arabia during the period 1990-2020. to estimate our empirical model, we used gdp per capita (constant 2010 us$) (gdpp), renewable energy consumption (% of total final energy consumption) (rec), gross capital formation in billions (constant 2010 us$) (k) and total labor force in millions (l). the data are sourced from the world development indicators (wdi). tables 1 and 2 report the descriptive statistics and correlation of variables, respectively. during the period (1990–2016), table 2 shows that the gdp per capita varies from us$ 16,696.41 to us$ 21,399.11; the range for gross fixed capital formation for capital is from 4.75e+10 to 2.09e+11 us$; the range for total labor force is from 6358516 to 13187031 million and renewable energy consumption ranges from 0.005% to 0.010% of total final energy consumption. this table shows us that gdp is positively linked to the consumption of renewable energy and that this link between these variables is important, which implies that economic growth has a causal impact on renewable energy consumption. this implies that renewable energy consumption is related to gdp (sharma, 2010). the total labor force (l) and gross fixed capital formation (k) are positive. therefore, an increase in total labor force and gross fixed capital formation would lead to an increase in the economic growth rate. to examine the stationarity of the series, we apply the augmented dickey-fuller (1979) (adf) and phillips perron (1988) (pp) tests. the results presented in table 3 show that the k and l series are stationary in level while gdp and ren are stationary in first difference, and therefore neither of them is integrated of order 2. this confirms our choice of using the non-linear ardl. 5. results consistent with the result of the unit root test without the adf unit root test with structural break and breakpoint, we can use the bounds cointegration test without structural break between the models to demonstrate the long-run association between real gdp, carbon dioxide emissions and renewable energy in saudi arabia. according to the table reported by narayan (2005), the two crucial values are 2.734 and 3.920 at the 5% threshold and are 3.657 and 5.256 at the 1% threshold. the results in table 4 confirmed the long-term association between the selected variables for all models, as all f-statistics are strongly elevated at 1% threshold. the results of the estimations are presented in table 5. the results of the estimations on the short-term relationship are presented in the upper part of the table while the results on the long-term relationship are presented in the lower part. nonlinear and asymmetry tests are summarized by bdm, pss statistics. bdm is the statistic proposed by banerjee et al., (1998) to test the longterm null relationship and pss is the f statistic proposed by pesaran et al., (2001) to test the non-cointegration null hypothesis. these two statistics are significant, which confirms a long-term non-linear relationship between per gdp capita and renewable energy consumption, and validates the hypothesis of cointegration of the model’s variables. wlr (wsr) is the wald statistics that tests the hypothesis of the symmetry of the relationship between the long-term (short-term) series. these tests are significant. they therefore make it possible to reject the hypothesis of a symmetrical long-term and short-term relationship for saudi arabia. the short-term and long-term relationship is respectively measured by the coefficient of the variables rent� � 1 or rent− − 1 and lren + or lren − . table 2: summary statistics and correlations gdpp k l rec mean 19409.09 1.25e+11 9201535 0.007 median 19315.07 1.34e+11 8812561 0.007 maximum 21399.11 2.09e+11 13187031 0.010 minimum 16696.41 4.75e+10 6358516 0.005 sd 1344.880 5.84e+10 2184011 0.001 gdpp 1 k 0.890 1 l 0.912 0.963 1 rec 0.866 0.963 0.925 1 table 3: unit root test variables level 1st difference t–statistic t-statistic time break decision gdp 0.782 –5.842*** i (1) ren 0.103 –6.457*** i (1) k –7.421*** – i (0) l –4.667** – i (0) **p<0.01 table 1: description and source of the variables variables description sources gdp per capita (gdpp) gdp per capita (constant 2010 us$) wdi renewable energy consumption (rec) renewable energy consumption (% of total final energy consumption) wdi gross fixed capital formation for capital (k) gross fixed capital formation in billions of constant 2010 u.s. dollars for capital wdi total labor force (l) total labor force in millions wdi table 4: bounds cointegration test dependent variable f-statistic prob result gdp 9.028 0.001*** cointegration ren 7.354 0.008** cointegration *** and ** denote significance at 1% and 5% thresholds, respectively benlaria and hamad: the economic impact of renewable energy on sustainable development in saudi arabia international journal of energy economics and policy | vol 12 • issue 5 • 2022 315 the diagnostic test statistics are presented in table 5. these tests are summarized by the statistics χ χsc het pssand f 2 2 , . among these results, we note that there is no serial correlation χsc 2 and no homoscedasticity χhet 2 . in addition, the fpss statistic confirms the asymmetrical co-integration between economic growth, renewable energy consumption, capital and labor force. wlr (wlr) is the wald statistic that tests the symmetry relationship hypothesis between the variables in the long (short) run. both statistics are significant, thus rejecting the symmetric relationship hypothesis in the long and short run. therefore, the model passes all the tests that indicate a correct estimation by the nardl model. the long-run nardl results presented in table 5 confirm that an increase in renewable energy consumption would boost economic growth (coefficient of 0.215), showing that a 1% increase in renewable energy consumption improves economic growth by 21.5%. in contrast, a negative shock to renewable energy consumption has a significant and negative effect on long-term economic growth. the negative coefficient (0.110) shows that any decrease in renewable energy consumption harms economic growth. our results corroborate those of olaoye et al., (2020) and shi et al., (2017). these results indicate that negative shocks in renewable energy consumption will stimulate economic growth. the above results suggest that increased renewable energy consumption is beneficial, as an increased renewable energy promotes infrastructure development and employment opportunities; creates a peaceful environment for investment opportunities; and also contributes to the optimal use of resources and capital stock (alptekin et al., 2012). indeed, a negative relationship was noted between positive capital shocks and economic growth, while a positive relationship was noted in negative shocks. these results confirm that an increase in capital investment hinders economic growth, while a decrease in capital stimulates economic growth. similar results were noted by benkraiem et al., (2019) for the relationship between capital and economic growth. indeed, policymakers must respect capital investments. in the long run, a positive and significant effect was evident between labor and economic growth in both positive and negative shocks. our results contradict those of amna et al., (2020), who found that the labor force productivity weakens asian countries’ economic growth model. in other words, the lack of diversification of economies that are heavily dependent on the primary sector contributes to accentuating this phenomenon. moreover, the positive coefficients show that the policy concerning labor employment stimulates economic growth in tunisia. in contrast, in the short run, a negative change in renewable energy consumption was negatively correlated with economic growth (coefficient 0.022). moreover, a negative change is negatively associated with one-period lagged economic growth (with a coefficient of 0.208). these results are consistent with the results of eid (2020). they indicate that a small decrease in government expenditure will boost economic growth at lag 0 while government expenditure decreases at lag 1. this reduction in government expenditure will disrupt production activities and dampen shortterm economic growth in tunisia. furthermore, a negative impact is verified between capital and economic growth for positive shocks in the short run (at lag 0 and 1), while a positive impact for negative shocks is presented (at lag 0). our results were consistent with shahbaz et al., (2017) in india, who argue that gross capital formation is detrimental to economic growth. these results highlight the importance of capital in the short run regarding economic development, since a positive shock in capital weakens economic growth. however, positive shocks to labor have a negative impact on economic growth (at lag 0), while a positive coefficient at lag 1. these results contradict those of shahbaz et al., (2017) for india, where they found that employment is an economic growth driver. therefore, in the short table 5: nardl estimation results dependent variable: yt variables coefficients t-statistic probability long-run c 10.574*** 5.485 0.000 yt−1 0.033** 3.156 0.016 rent� � 1 0.215* 3.241 0.058 rent− − 1 –0.110** –3.615 0.025 kt� � 1 –0.075** –2.894 0.033 kt− − 1 0.084 0.571 0.425 lt� � 1 0.058* 2.697 0.085 lt− − 1 0.062* 2.463 0.066 short-run �yt�1 0.104 0.722 0.183 �yt�2 0.196 1.045 0.156 �rent � –0.022** –2.654 0.045 �rent� � 1 –0.208*** –6.134 0.000 �rent� � 2 –0.155** –2.157 0.033 �rent � 0.103*** 4.071 0.000 �rent� � 1 0.277*** 5.089 0.000 �rent� � 2 0.120*** 3.883 0.004 �kt � –0.032 –0.643 0.684 �kt� � 1 –0.046 –0.447 0.267 �kt � 0.039 0.723 0.382 �lt � –12.011** –2.703 0.022 �lt� � 1 15.057** 3.041 0.016 diagnostic tests r2 0.880 adj r− 2 0.961 dw 2.624 wlr ren. 77.083*** wsr ge. 18.462** wsr k. 15.003** wsr k. 9.088* wlr l. 2.658** wsr l. 11.097*** χsc 2 7.118 χhet 2 0.609 χef 2 0.209 fpss 9.772*** tbdm –10.011*** ***, **, and * represent significance at 1%, 5%, and 10% thresholds, respectively benlaria and hamad: the economic impact of renewable energy on sustainable development in saudi arabia international journal of energy economics and policy | vol 12 • issue 5 • 2022316 run, the government and policymakers should be cautious when designing policy regarding capital investment and employment. finally, we applied several dynamic adjustments. the results are shown in figure 1, which plots the cumulative dynamic multipliers. these multipliers show the pattern of adjustment of economic growth to its new long-run equilibrium following a negative or positive shock in renewable energy consumption, labor and capital, respectively. the asymmetric curve (solid red line) reflects the difference between the dynamic multipliers associated with positive and negative shocks, i.e., m mh h � �� . this curve is displayed with its lower and upper bands (dotted red lines) at a 95% confidence interval to provide a measure of the statistical significance of the asymmetry at any horizon h. figure 2 confirms the existence of an overall positive relationship between renewable energy consumption and economic growth. we see that the effect of a positive shock on renewable energy consumption outweighs that of a negative shock. moreover, a significant asymmetric response to renewable energy consumption shocks is observed. in addition, there is an overall positive relationship between labor and economic growth, as negative shocks to labor have dominant positive effects on economic growth. however, a positive shock to capital dominates its negative shock. this result confirms the previous result, where a negative shock to capital has an insignificant impact on economic growth. the last step in the nardl estimation is to check the stability of the parameters in the long and short terms. the cusum techniques based on the cumulative sum of the recursive residuals and the cusumq based on the cumulative sum of the square of the recursive residuals are applied (figure 1). the results show that the graph of cusum and cusumq statistics remain within the interval of critical values at the 5% threshold, implying that the model coefficients are stable. figure 2: cumulative effect of independent variables on the dependent variable figure 1: cusum and cusumq benlaria and hamad: the economic impact of renewable energy on sustainable development in saudi arabia international journal of energy economics and policy | vol 12 • issue 5 • 2022 317 6. conclusion and policy implications this study aims to investigate the asymmetric impacts of renewable energy, capital and labor on economic growth in saudi arabia during the period 1990-–2019 based on a non-linear ardl model both in the long and short terms. the results indicate that there is an asymmetric relationship between the variables considered. the positive shock of renewable energy consumption has a positive impact on gdp in the long run. in the long run, a positive and significant effect is evident between labor and economic growth in both the positive and negative shocks. however, in the short run, positive shocks to labor have a negative impact on economic growth (at lag 0), while a positive coefficient at lag 1. in general, it is important for saudi arabia to increase its renewable energy consumption by focusing on fixed capital formation and labor at the expense of its operating expenditure, which has limited growth potential. this recommendation is in line with the objectives set out in tunisia’s growth and employment strategy paper (gesp), which is to raise the investment rate to at least 13.3% of gdp. to achieve this goal, saudi arabia should implement policies aimed at reducing current account and fiscal deficits. all this requires a structural transformation of countries’ economies. it is time to move from a rentier to a transformation economy. to increase its added value, raw materials should be transformed into semi-finished or finished products. for this transformation policy to be successful, foreign investors must be brought in. the aim is to promote the relocation to developed countries of the production chains of companies that operate in these different sectors. this relocation should promote technology transfer for the benefit of local small and medium-sized enterprises which, in the medium and long terms, could become real industries. however, it would be essential for smes to migrate from the informal to the formal sector. saudi arabia should improve its companies’ competitiveness by filling the infrastructure deficit in terms of quality and quantity. these are mainly transport infrastructure and energy infrastructure. this goal can easily be achieved through the development of public-private partnerships through concession agreements. this strategy increases the consumption of renewable energy, reduces public deficits and at the same time allows companies to achieve economies of scale. they will now be more competitive and more profitable in order to better contribute to budget revenues. the public-private partnership admits, however, a constraint related to the fact that the country obtains the debt under the conditions of those who finance the implementation of the various projects. thus, capacity building would enable state actors to better negotiate within this partnership. in saudi arabia, successful disarmament operations should continue in order to end conflicts and allow the state to control the entire country. the growth sectors of the economy should be developed to generate significant revenues in the medium term in order to improve budget deficits and better meet social obligations. it is important to note that these strategies can produce relevant results only in a climate of peace, socio-political stability, good governance and security. in other words, the prevention and effective management of conflicts that rock the countries of the african region and the establishment of peace and security would boost economic growth and development in the subregion countries. it is in this context that, under the leadership of asian countries, special emphasis should be placed on combating unemployment and poverty in saudi arabia. 7. acknowledgments the authors extend their appreciation to the deanship of scientific research at jouf university for funding this work through research grant no (dsr-2020-02-527). references akarca, a.t., long, t.v., 1980. on the relationship between energy and gnp: a re-examination. journal of energy development, 5, 326-331. adewuyi, a. o., and awodumi, o. b. (2017), biomass energy consumption, economic growth and carbon emissions: fresh evidence from west africa using a simultaneous equation model. energy, 119, 453-471. alptekin, a., and levine, p. (2012), military expenditure and economic growth: a meta-analysis. european journal of political economy, 28(4), 636-650. amna intisar, r., yaseen, m. r., kousar, r., usman, m., and makhdum, m. s. a. (2020). impact of trade openness and human capital on economic growth: a comparative investigation of asian countries. sustainability, 12(7), 2930.‏ apergis, n., danuletiu, d.c. (2014), renewable energy and economic growth: evidence from the sign of panel long-run causality. international journal of energy economics and policy, 4(4), 578-587. banerjee, a., dolado, j., and mestre, r. (1998). error‐correction mechanism tests for cointegration in a single‐equation framework. journal of time series analysis, 19(3), 267-283.‏ behname, m. (2012), la consommation d’energie renouvelable et la croissance economique dans l’europe de l’ouest. romanian journal of economics, 35(44), 160-171. benkraiem, r., lahiani, a., miloudi, a., & shahbaz, m. (2019). the asymmetric role of shadow economy in the energy-growth nexus in bolivia. energy policy, 125, 405-417. bilan, y., streimikiene, d., vasylieva, t., lyulyov, o., pimonenko, t., pavlyk, a. (2019), linking between renewable energy, co2 emissions, and economic growth: challenges for candidates and potential candidates for the eu membership. sustainability, 11(6), 1528. chen, y., zhao, j., lai, z., wang, z., xia, h. (2019), exploring the effects of economic growth, and renewable and non-renewable energy consumption on china’s co2 emissions: evidence from a regional panel analysis. renewable energy, 140, 341-353. eia. (2019), us energy information administration, independent statistics and analysis, september 2019. available from: http:// www.eia.doe.gov/emeu/mer/pdf/pages/sec1_7.pdf komendantova, n., patt, a., barras, l., and battaglini, a. (2012), perception of risks in renewable energy projects: the case of concentrated solar power in north africa. energy policy, 40, 103-109. lekana, h.c. (2019), relation entre la consommation d’énergie et la croissance économique dans les pays de la cemac. annales de l’universite marien ngouabi sciences economiques et de gestion, 18, 57-72. lund, h. (1999), a green energy plan for denmark. environmental and resource economics, 14(3), 431-440. menegaki, a. n. (2011), growth and renewable energy in europe: a random effect model with evidence for neutrality hypothesis. energy benlaria and hamad: the economic impact of renewable energy on sustainable development in saudi arabia international journal of energy economics and policy | vol 12 • issue 5 • 2022318 economics, 33(2), 257-263. narayan-parker, d, editor. (2005), measuring empowerment: crossdisciplinary perspectives. washington, dc: world bank publications.‏ olaoye, o.p., aderemi, t.a., john, n.c., jude-okeke, y., ezinwa, a.d. (2020), energy consumption and foreign direct investment inflows in nigeria: an empirical perspective. international journal of energy economics and policy, 10(2), 491-496. pao, h. t., and fu, h. c. (2013), renewable energy, non-renewable energy and economic growth in brazil. renewable and sustainable energy reviews, 25, 381-392. pesaran, m. h., shin, y., and smith, r. j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. sadorsky, p. (2009), renewable energy consumption and income in emerging economies. energy policy, 37(10), 4021-4028. saidi, k., omri, a. (2020), the impact of renewable energy on carbon emissions and economic growth in 15 major renewable energyconsuming countries. environmental research, 186, 109567. shahbaz, m., van hoang, t. h., mahalik, m. k., & roubaud, d. (2017), energy consumption, financial development and economic growth in india: new evidence from a nonlinear and asymmetric analysis. energy economics, 63, 199-212.‏ sharma, s. s. (2010), the relationship between energy and economic growth: empirical evidence from 66 countries. applied energy, ‏.3565-3574 ,(11)87 shi, y., zhou, y., yang, d. r., xu, w. x., wang, c., wang, f. b., and chen, h. y. (2017), energy level engineering of mos2 by transition-metal doping for accelerating hydrogen evolution reaction. journal of the american chemical society, 139(43), 15479-15485. wolde-rufael, y. (2010), coal consumption and economic growth revisited. applied energy, 87(1), 160-167. yu, e. s., & choi, j. y. (1985), the causal relationship between energy and gnp: an international comparison. the journal of energy and development, 249-272. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 2 • 2021 325 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(2), 325-332. are urban rwandan households using modern energy sources? an exploration of cooking fuel choices fydess khundi-mkomba1,2* 1african center of excellence in energy for sustainable development, university of rwanda, kigali, rwanda, 2department of agricultural and applied economics, lilongwe university of agriculture and natural, resources, bunda college, lilongwe, malawi. *email: fkhundi@gmail.com received: 08 september 2020 accepted: 27 december 2020 doi: https://doi.org/10.32479/ijeep.10735 abstract this study employed a discrete choice framework to explore cooking energy use patterns amongst urban rwandan households using the latest eicv 5 microeconomic survey dataset. specific analysis focused on choices for three primary cooking fuels namely: firewood, charcoal and liquidified petroleum gas. the findings show that ordered model provided better prediction for primary fuel choices rather than the secondary choices for multiple fuel users with income as a key determinant. furthermore, asset index, house ownership, geographical location, number of rooms, household size and household head labor market participation were some of the non-price factors that significantly affected the choice probability for using charcoal as transitional fuel and liquidified petroleum gas as a modern fuel in rwandan country context. robustness test of the results emphasizes the need for government in collaboration with modern energy suppliers to have clean energy use campaigns and do market segmentation through repackaging of smaller gas cylinders so that many lowand middle-income households become aware and use modern energy services. this is essential to ensure good prospect of energy transition for the developing country case context amidst urbanization and climate change. keywords: energy; households; urban; rwanda; fuel jel classifications: d12, o12, q420 1. introduction most governments and development practitioners are deeply concerned with heavy use of traditional fuels closely linked to indoor pollution, environmental degradation, and high opportunity cost for women and children that eventually affect household wellbeing in general (irena, 2019). for most developing countries, energy is increasingly becoming a very scarce commodity and literature demonstrates correlation of absolute poverty with poor use of modern energy (sher et al., 2014). there is no consensus on universal definition of energy poverty. however, what is prevalent in all definitions of the energy poverty is that it depicts a situation whereby there are insufficient choice sets of getting adequate access to sustainable modern energy services and products (irena, 2019). to date, the sub saharan africa region and other developing countries face limited access to affordable and clean energy sources. it is estimated that 2.5 billion people depend on solid fuel from traditional biomass fuels such as crop residues and firewood for cooking and heating which are associated with indirect adverse health effects (buba et al., 2017). this number is projected to reach 2.7 billion by 2030 implying that depletion of forest and environmental degradation might be inevitable if proper and timely policy measures are sluggish (iea, 2006). as such, promotion of clean energy technologies is vital to facilitate energy transition in order to improve accessibility and utilization of modern energy services to reduce state of energy deprivation (morrissey, 2017; bhattacharyya, 2012). however, successful uptake of cleaner cooking technologies largely is linked to consumer demand and energy choices mostly from the household sector. therefore, this paper utilized the latest this journal is licensed under a creative commons attribution 4.0 international license khundi-mkomba: are urban rwandan households using modern energy sources? an exploration of cooking fuel choices international journal of energy economics and policy | vol 11 • issue 2 • 2021326 eicv5 2016/17 data set that captures micro economic information to analyze cooking fuel choices of urban households in rwanda within the context of urbanization and migration. this study contributes to literature by expanding the scope of the urban context research gap that was left by (marathe and eltrop, 2017) who only considered kigali city. their findings showed big differences on electricity utilization among different socioeconomic groups and dwelling types. the country has experienced rapid urban growth that is accompanied by demographic growth and migration to urban spaces with resettlement of displaced people and returnees from neighboring countries such as burundi and democratic republic of congo following the end of 1994 genocide. recent statistics show that urban population rose from 4.6% in 1978 to 16.5% in 2012 with an average urban density of 1871 inhabitants/km2 as of 2012 (minifra, 2015). the annual growth rate for urban population is pegged at 4.1% whilst the country’s vision 2020 highlighted a target of reaching an urbanization rate of 35% in 2020 (nasir, 2012). the urban planning and building department in rwanda defined a city to have a population of at least 200,000 inhabitants; a municipality at least 30,000 but <200,000 inhabitants; an agglomeration at least 10,000 but <30,000 inhabitants. by 2012, rwanda had 21 urban areas, 10 municipalities, 10 agglomerations with 7 emerging urban areas (unhabitat, 2020). this research study is timely and pertinent considering the country’s urban rapid growth. this growth may stimulate a big surge in demand for household fuels coupled with dynamic urban lifestyles which has policy implications. urban households have an added advantage of exposure towards a variety of choices for modern commercial fuels such as lpg attributed to improved accessibility and availability that may induce fuel switching (farsi and filippini, 2007). this implies that the household sector can offer an attractive market and prospect for diffusion of commercial clean energy cooking technologies. however, so many factors do influence household fuel choices and differ depending on context, level of transition by the households and the prevailing energy sources available to households based on a cross section energy ladder (smith and urperlainen, 2014; pachauri and jiang, 2008). 1.1. energy ladder versus energy stacking models theoretical explanation on household utilization of different fuels is classified into two schools of thought. first, the “energy ladder hypothesis” which states that household income and fuel switching are linked by postulating that poor households are more likely to use traditional fuels than wealthy household counterparts mainly due to their income differences (toole, 2015; van der kroon, 2013). in simple terms, the hypothesis depicts a linear movement up on arbitrary ladder such that any household shift from lower level to the next upper level corresponds to rising household income levels. for instance, high dependency of using traditional fuels reflects a poor household energy status (mainly because of low income levels) and is usually associated with the lowest weight of the energy ladder (masera et al., 2000). another school of thought referred as “fuel stacking or energy transition” asserts that utilization of both clean and unclean energy fuel sources still occurs regardless of household high-income levels for various reasons (heltberg, 2005). reasons for multiple fuel use by households in developing countries are attributed not only to economic factors but also non-economic factors as well which are deeply connected to culture, social or security purpose to ensure uninterrupted supply to always meet household demands (mekonnen and kohlin, 2009; pachauri and spreng, 2004). for this study it was possible to test the fuel stacking hypothesis since the eicv 5 dataset captured information regarding primary and secondary cooking fuels that permitted further analysis. 1.2. survey approaches and methods on cooking fuel choice the existing literature has documented a variety of studies that have analyzed household cooking energy choices and patterns in different regions based on two methodological approaches. the first approach consists of studies that usually look at possible future scenarios and therefore focus on analyzing the energy demand together with factors that influence household cooking fuel choices to make projections using either econometric techniques (daioglou et al., 2012; van ruijven et al., 2011) or simulation by least cost optimization to arrive at the optimal cooking energy choices (pachauri et al., 2013; ekholm et al., 2010). however, these methods do not handle fully multiple cooking fuel utilization and fuel stacking that is prevalent in poor economies which is a limitation (masera et al., 2000). recent development of a message-access model which was used to assess household cooking energy choices in south asia and central america brings an array of hope to overcome this limitation as a new demand model (pachauri et al., 2018; cameron et al., 2016). this new approach not only incorporates fuel stacking but also permits further calibration on using household survey data to assess household cooking fuel choice patterns. nevertheless, such approach is still limited to be carried in most developing countries including the present study due to insufficient data on energy prices and expenditures. the second methodological approach focuses mostly on the investigation of energy ladder hypothesis validity using discrete choice frameworks (buba et al., 2017; farsi and filippini, 2007; heltberg, 2005). however, these studies reveal mixed evidence regarding income and choice of fuel type especially in the sub saharan africa and other developing country context. emphatically, both recent and old studies show that demographic characteristics, economic status, public awareness, geographical location, wealth, household preferences, access to modern infrastructures play a role in determining household cooking fuel choices (makonese et al., 2018; hiemstra-van der horst and hovorka, 2008; madubansi and shackleton, 2007; arnold et al., 2006). therefore, this paper assessed household preferences towards clean cooking fuels and energy use patterns in rwanda, one of the low-income countries in the sub-saharan african region to see prospect of improving access of commercial modern cooking fuels along the urban domestic sector. this is a unique country specific case study which informs policy design and decision-making process towards promotion of clean cooking fuels especially in the sub saharan african region to support the sustainable goal number 7 agenda of ensuring affordable and clean energy sources. the paper used the newly released household survey data to provide country empirical evidence that is still limited. but why did the households choose a certain type of cooking fuel, what factors influenced these choices; what household characteristics made more probable to use traditional fuels that are deemed to be unclean than other modern energy sources such as lpg and charcoal that are regarded as clean energy sources for cooking in their homes? these were some of the guiding research questions. khundi-mkomba: are urban rwandan households using modern energy sources? an exploration of cooking fuel choices international journal of energy economics and policy | vol 11 • issue 2 • 2021 327 2. materials and methods 2.1. the research conceptual framework the study grouped the cooking fuels in three categories based on energy ladder hypothesis (cameron et al., 2016; toole, 2015; farsi and filippini, 2007). specifically, the paper focused on analyzing household energy choice probability for lpg in the modern fuel category; charcoal in the transition fuel category and wood in the traditional fuels category in order to understand the prospect of accelerating modern cooking energy services uptake in rwandan homes. the analytical approach was in three phases. first, the descriptive statistics analysis was carried out not only to help the researchers and readers understand energy use patterns but also to see the relationship that may exist between fuel choices and household income including multiple fuel use. the second part examined the linear and nonlinear relationships that may exist between cooking fuel choices versus household characteristics. final part of the analysis focused on testing the robustness of the results. 2.2. research design and data collection the study utilized the urban household responses from rwanda integrated household living survey dataset for the year 2016 /17 (eicv5). this study focused on 2434 urban households that were drawn using the 2012 rwanda population and housing census as sampling frame for enumeration areas as primary sampling units. in this census, each enumeration area was categorized as urban, semi-urban, peri-urban or rural (nasir, 2018). the current population of rwanda is pegged at 12.93 million with <30% living in urban areas (world population review, 2020). the eicv 5 data does not document energy prices and physical quantities of the fuels which is a limitation. however, its strength is that it captured a variety of information such as access to basic services, household durables, employment details, household demographics, household consumption, expenditure, and income over a calendar month. the nationally representative sample built on the previous household living condition surveys which started in 2001 known by its french acronym of “enquête integrals les conditions de vie des ménages (eicv1)” and has been done on regular basis. stata 14 as a statistical package software was used for descriptive statistics analysis and econometric estimation whilst the microsoft excel was used for graphics. brief summary statistics of independent variables that were hypothesized to influence cooking fuel choices among these urban households are presented in table 1. from table 1, the distribution of the respondents shows that 76% were male heads and 24% were female heads. the mean household size was 4.33. the real annual consumption per adult equivalent (in january prices) which was used as a proxy measure of household income. rwanda employs a basic-needs approach when measuring poverty in monetary terms. according to (nasir, 2018), poverty was defined as insufficient consumption to satisfy food and nonfood basic needs by using two poverty lines. thus, households were classified as poor if they were below the poverty line of rwf 159,375 whilst that of extreme poverty line was computed at rwf 105,064. on poverty status, 12% of the households were classified as poor based on rwandan poverty line of. with regard to occupational status, 46% were living in their own houses whilst 47% were renting houses. on education variable, 90% of the respondents have been to school. the inclusion of these variables was informed by literature (mbaka et al., 2019; adusah-poku and takeuchi, 2019). some of the variables such as ownership of dwelling, gender of the household head, education, regional dummies. a correlation matrix for the independent variables that were used in the analysis showed no serious multicollinearity. the variance inflation factor (vif) values for each of the independent variables was <10 which is a rule of thumb threshold for potential near perfect collinearity as reported in table 1a in the appendix. 2.3. the empirical model (ordered logit) this study adopts an ordered discrete choice modeling approach by assuming that the individual household i is an economic agent facing a consumer basket of fuel product alternatives {depicted as latent variables, yi *, in equation (a)}. the choice of probit over logit or other random parameters model depend on the working assumptions of the error terms despite that both models give similar results (nlom and karimov, 2015; greene, 2012). in this paper, the household fuel choices of four fuel types was estimated using ordered logit model based on the assumption that household energy consumption pattern followed a natural progression pattern (farsi and filippini, 2007). theoretically, error terms from logit model take a logistic distribution whilst that of probit model are assumed to be normally distributed. formally, assume that an individual’s choice of primary cooking fuel is chosen from a set of “j” alternatives by household “i” to maximize household utility (jumbe and angelsen, 2006). it is assumed that the individual’s choice of cooking fuel would be ranked based on efficiency, comfort and ease of use or convenience. the fuel choices would be determined also by a vector of household characteristics and other factors. the ordered logit model is specified in the equation (a) as follows: * * i iy x ui = β+ (a) where the unobservable (unj) for all “j” set of cooking fuel alternatives is identically and independently distributed having a weibull distribution with u exp~ [ , ]0 σ and βnj is a vector of unknown parameters. rearranging expression (a) based on a hypothesis that the relationship between vector of household characteristics and table 1: socioeconomic characteristics of the respondents variable obs mean std. dev. log consumption per adult equivalent 2434 13.00 0.88 log asset value 2434 8.86 3.41 received environmental information 2434 0.40 0.49 detached house 2434 0.63 0.48 participant in the labour market 2434 0.57 0.50 household size 2434 4.33 2.37 male head 2434 0.76 0.43 age of head 2434 40.70 13.99 number of rooms 2434 3.45 1.61 owner occupancy 2434 0.46 0.50 tenant occupancy 2434 0.47 0.50 education of head 2434 0.90 0.30 number of children 2434 1.23 1.25 number of elderly 2434 0.09 0.32 electricity access 2434 0.75 0.44 poor 2434 0.12 0.33 source: computed by author using eicv5 0.66 30.07 94.33 5.671.07 7.81 8.13 1.77 81.22 0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 100.00 other fuels wood charcoal lpg no secondary fuel most used secondary fuel figure 1: household cooking fuel consumption patterns (%) source: computed by author using eicv5 khundi-mkomba: are urban rwandan households using modern energy sources? an exploration of cooking fuel choices international journal of energy economics and policy | vol 11 • issue 2 • 2021328 the dependent variable is established by estimating a vector of parameters β using log-likelihood method gives the following maximizing log likelihood function. inl y inp n n j j ni nj�� � � � � �� 1 1 (b) the ordered logit model has m-1 cut -off points as threshold variables (not m categories) to avoid collinearity. for all probabilities to be positive, the threshold values are set to be 0 < ɑ1 < ɑ2 <…. <ɑm−1 and are estimated for each category. the ordered logit is a regression model where regressors do not include a constant. the individual probabilities are specified in expressions (c), (d), (e) and (f) as follows: ( ) i1 i ' 1 1 p pr(y 1) 1 exp[ x ] = = = + − + βɑ (c) ( ) ( ) ( )i2 i ' '2 1 1 1 p pr y =2 = 1 exp[ x ] 1 exp[ x ] = − + − + β + − + βɑ ɑ (d) ( ) ( ) ( )i3 i ' '3 2 1 1 p pr y =3 = 1 exp[ x ] 1 exp[ x ] = − + − + β + − + βɑ ɑ (e) ( ) ( )i4 i '3 1 p pr y 4 1 1 exp[ + x ] = = = − + − βɑ (f) where pi1 and pi4 are in reduced form because ɑ0=−∞ and ɑ4 = ∞; yi are fuel alternatives such that 1= other fuels, 2= wood, 3= charcoal and 4= lpg. this study utilized the stata 14 software package for simulations to get the probabilities and the marginal effects by using the “ologit [varlist]” command and further post estimation. therefore, the first ordered logit model was estimated without disaggregation of income categories as shown in m1 whilst the second ordered logit model included disaggregation of income categories (quintiles) as shown in m2 as expressed in equation (g) and (h) respectively. this was done to assess the robustness of the results and get an insight in terms of different income groups. all the two models that were estimated are expressed as follows: 1 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 i m x x x x x x x x u = φ +φ + φ + φ + φ + φ + φ +φ + φ + (g) 2 0 1 1 2 2 3 3 4 4 5 5 im = + x + x + x + x + x +γ γ γ γ γ γ ε (h) where m1= household fuel choice equation in equation (g) m2 = household fuel choice equation in equation (h) x1 = log annual household consumption per adult equivalent x10 = region x2= household size γs= estimated parameters from quintiles variables of equation (h) x3= age of head ϕs= estimated parameters of equation (g) x4= education ui= error term of equation (g) x5= male head εi= error term of equation (h) x6= marital status x7= asset index x8= electricity access x9= ownership of dwelling 3. results and discussion 3.1. descriptive statistics this section presents the descriptive statistics first thereafter the econometric results from ordered logit regression analysis. in terms of clean energy access and energy consumption patterns, figure 1 shows household cooking fuel consumption patterns amongest urban rwandan households. it shows that few households use modern clean energy sources. for instance, under modern fuel category, 5.67% of households reported lpg as their primary fuel whilst 1.77% of households used it as a secondary fuel. the majority of the households (94.33%) used charcoal as a primary fuel for cooking activities and also majority of the households (8.13%) used it as a secondary fuel. this finding is not surprising since (zulu and richardson, 2012) found that charcoal was not only a primary source of household energy in urban communities but also is taken as a tradable commodity for household income generation. charcoal is considered as a renewable energy source that is less polluting with fewer smoke emission compared to wood (akpalu et al., 2011). although this is the case, it attracts high opportunity cost for other economic livelihoods activities mostly for women and children thereby perpertuating gender and equity biases (ekholm et al., 2010). however, a bigger proportion of the households (81.22%) did not have any secondary cooking fuel. the choice of household cooking fuel is also linked to the income (proxied by annual household consumption per adult equivalent) and family size. figure 2 indicates that high income levels reduces the probability of choosing traditional fuels (wood) while that of 0.000 20.000 40.000 60.000 80.000 100.000 v e r y p o o r 2 n d m i d d l e 4 t h r i c h e s t s h a r e o f h o u s e h o l d s v e r s u s q u i n t i l e o f a n n u a l h o u s e h o l d c o n s u m p t i o n p e r a d u l t e q u i v a l e n t other fuels wood charcoal lpg figure 2: primary cooking fuel choice by income category (%) source: computed by author using eicv5 0.26 10.07 3.49 100.00 21.17 100.00 22.70 100.00 21.29 99.74 18.77 89.93 14.11 78.83 77.30 78.71 81.23 82.40 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% pr im ar y se co nd ar y pr im ar y se co nd ar y pr im ar y se co nd ar y pr im ar y se co nd ar y pr im ar y se co nd ar y very poor 2nd middle 4th richest clean solid no secondary fuel figure 3: fuel stacking by income category (%) 75% 24% 1% national grid no electricity others (solar, rechargeable batteries) figure 4: status of electricity access in the households (%) khundi-mkomba: are urban rwandan households using modern energy sources? an exploration of cooking fuel choices international journal of energy economics and policy | vol 11 • issue 2 • 2021 329 modern fuels (lpg) and transitional fuels (charcoal) increases. this suggests that high income levels in rwanda may be associated with fuel switching from traditional fuels to modern fuels. thus, energy ladder hypothesis may hold in this situation. 3.2. energy ladder versus energy stacking however, regarding fuel stacking, the data showed that households practiced multiple fuel use and lpg which is a commercial energy is mainly used in the wealthy households with highest socioeconomic status depicted by the relationship between quintiles of household consumption expenditure and cooking fuel choices. solid fuels still occupy large shares for both primary and secondary fuels categories across all the income categories. the figure 3 shows that some rich and richest household use clean fuels, but the number is still small. in this case for easy assessment clean fuel referred to lpg, biogas, electricity and kerosene whilst solid fuels imply saw dust, wood, charcoal and crop residue). lastly, figure 4 indicates that urban rwandan households had a high rate of national grid connection (approximately 75%) but electricity was primarily used for home lighting and other purpose instead of cooking. 3.3. factors influencing the cooking fuel choice the ordered logistic regression model (table 2) was fitted with household choice for three types of fuels namely; wood, charcoal and lpg in the ascending order of 1, 2, 3 respectively. further testing of the results involved estimating multinomial logit model(mlogit) specification to see if the assumption of ordered discrete choice modeling was feasible for the individual’s choice on primary cooking fuel type based on efficiency, comfort and ease of use (farsi and filippini, 2007; greene, 2012)1. the results showed that ordered logit model provided better prediction for household most used fuel choices (primary fuel) in both full sample (42.74%) and subsample (31.06%) of multiple fuel users2. however, the situation was different for multiple fuel users subsample. the non-ordered model (mlogit) provided better prediction for household secondary fuel choices (secondary fuel). this implies that for urban households, fuel ranking is critical when making decision regarding which cooking fuel to use most whilst for secondary the ranking does not matter. since fuel switching process is both transitional and gradual in nature, it is important to understand these household preferences to inform the policy decision making process to improve clean energy service provision within a given country. the results from table 2 show some of the non-price factors which affect the household choice for cooking fuels in urban rwanda. the parameters of these factors depict the position of the household on the energy ladder (household energy status). overall, household income, household head labor participation, wealth status, residence in kigali and western provinces had positive 1 multinomial logit was estimated for full sample and multiple users subsample. 2 the results for multiple fuel users subsample are not presented here for brevity purpose but are available upon request. table 2: ordered logit regression results fuel alternatives in ascending order: wood, charcoal, lpg coefficient std error log annual household consumption per adult equivalent 1.547*** 0.108 log asset value 0.137*** 0.026 received environmental information −0.092 0.115 detached house −0.201 0.139 labor participant head 0.350*** 0.121 household size 0.092** 0.043 male head −0.306** 0.143 age of head −0.031*** 0.006 number of rooms −0.151*** 0.049 owner occupancy −0.780*** 0.142 education of head −0.028 0.200 number of children −0.033 0.066 number of elderly 0.172 0.215 kigali 1.908*** 0.207 southern −0.228 0.215 western 0.896*** 0.209 northern 0.415 0.237 electricity access −0.773*** 0.155 log likelihood −1177.67 pseudo r squared 0.4274 percentage of correct prediction of chosen fuels primary fuel for all the sample (2434) households 42.74% both 1st and 2nd fuels for multiple-fuel users (457 households) 31.06% khundi-mkomba: are urban rwandan households using modern energy sources? an exploration of cooking fuel choices international journal of energy economics and policy | vol 11 • issue 2 • 2021330 table 4: marginal effects by income category quintile wood charcoal lpg very poor 0.468*** (0.050) −0.436*** (0.059) −0.076*** (0.012) 2nd 0.447*** (0.052) −0.402*** (0.056) −0.077*** (0.012) middle 0.457*** (0.049) −0.406*** (0.052) −0.082*** (0.013) 4th 0.325*** (0.057) −0.271*** (0.054) −0.067*** (0.012) these estimates were obtained from running ordered logit regression in stata 14. standard errors are in the parentheses. the levels of significance *p<0.05, **p<0.01, ***p<0.001 table 3: marginal effects for choice of wood, charcoal and lpg in rwanda variables wood charcoal lpg log annual household consumption per adult equivalent −0.210*** (0.016) 0.198*** (0.015) 0.012*** (0.002) log asset value −0.019*** (0.004) 0.018*** (0.003) 0.001*** (0.000) received environmental information 0.013 (0.016) −0.012 (0.015) −0.001 (0.001) detached house 0.027 (0.018) −0.025 (0.017) −0.002 (0.001) labor participant head −0.048*** (0.017) 0.046*** (0.016) 0.003*** (0.001) household size −0.013** (0.006) 0.012** (0.005) 0.001** (0.000) male head 0.039** (0.017) −0.037** (0.016) −0.003* (0.001) age of head 0.004*** (0.001) −0.004*** (0.001) 0.000*** (0.000) number of rooms 0.020*** (0.007) −0.019*** (0.006) −0.001*** (0.000) owner occupancy 0.108*** (0.020) −0.102*** (0.019) −0.006*** (0.001) education of head 0.004 (0.027) −0.004 (0.025) 0.000 (0.002) number of children 0.004 (0.009) −0.004 (0.008) 0.000 (0.001) number of elderly −0.023 (0.029) 0.022 (0.027) 0.001 (0.002) kigali −0.261*** (0.029) 0.244*** (0.027) 0.018*** (0.003) southern 0.033 (0.032) −0.031 (0.031) −0.002 (0.001) western −0.099*** (0.019) 0.090*** (0.016) 0.010*** (0.003) northern −0.050** (0.025) 0.046** (0.023) 0.004 (0.003) electricity access 0.119*** (0.028) −0.114*** (0.027) −0.005*** (0.001) these estimates were obtained from running ordered logit regression in stata 14. standard errors are in the parentheses. the levels of significance *p<0.05, **p<0.01, ***p<0.001 and significant effect as expected. however, owner occupancy, gender of household head, electricity access, number of rooms showed negative effects. on the otherhand, table 3 presents the marginal effects of these factors that show the extent of how much these factors influence the household fuel choices in urban rwanda. looking at the case of fuelwood, the results indicated that household head labor market participation and household size had weak significance effects on the probability of choosing fuelwood by decreasing the choice probability for fuelwood by 4.8% and 1.3% at 1% and 5% levels of statistical significance respectively. whereas, owner occupancy (10.8%), number of rooms (2%), electricity access (11.9%), age of household head (0.4%), female headship (3.9%) increased the choice probability for fuelwood with electricity access having bigger effects seconded by occupancy status. this finding shows that improved electricity access is not enough alone to promote fuel choices for clean energy sources and fuel switching. this finding is consistent with (paudel et al., 2018) who found that afghani households that had electricity access preferred animal dungs for cooking. however, this is contrary to what was found in bhutan which is also a developing country (bahadur et al., 2016). reliability and availability of the electricity may be critical together with price factors and other social and risk perception reasons that were not captured by the available dataset. however, being a resident of kigali (24.4%), western province (9.0%), income (19.8%) and wealth (1.8%) had positive significant effect and increased choice probability for charcoal at 1% statistical level of significance. on contrary, female headship, age of household head (0.4%), number of rooms (1.9%), owner occupancy (10.2%), and electricity access (11.4%) decreased the choice probability for charcoal at 1% statistical level of significance. this finding supports the notion that regional differences and household socio economic status play a key role by influencing the choice probability for using transitional fuels such as charcoal. in case of lpg, the results showed that income (1.2%), being a resident of kigali (1.8%) and western province (1.0%) had bigger marginal effects compared to the rest of the other significant factors such as household size (0.1%), labor market participant head (0.3%) in increasing the choice probability. some significant factors that reduced the choice probability for lpg include number of rooms (0.1%), owner occupancy (0.6%) and electricity access (0.5%). robustness testing of the results using different income categories (table 4) show that households belonging to very poor (46.8%) and the middle class (45.7%) were more likely to choose wood, compared to the richest income category with bigger effects. this result supports the notion that traditional energy sources dominate the poor households unlike those with high socioeconomic status implying the household income does influence choice probability for cooking fuel consistent with what was found in ghana (karimu, 2015). infact, very poor and the middle class were having large marginal effects across all the three fuel categories. conclusion this research study presents findings from an ordered logit regression analysis on fuel choices and patterns of cooking fuels in urban rwandan households using from eicv5 survey dataset. the study examined the choice probability of a household from selecting cooking fuel (wood, charcoal, lpg) whilst taking into consideration of socio-economic status and other household characteristics plus regional differences. the methodological aspect assumed a natural ranking of fuels depending on its khundi-mkomba: are urban rwandan households using modern energy sources? an exploration of cooking fuel choices international journal of energy economics and policy | vol 11 • issue 2 • 2021 331 efficiency, ease of use and cleanliness. the results from descriptive statistics and econometric analysis showed that the observed cooking fuel use patterns were consistent with the energy ladder hypothesis. this evidence suggests that natural order of progression, household income levels and other non-price factors play a key role in determining primary cooking fuel choices in the urban rwanda. other factors that influence fuel choices were asset index, house ownership, geographical location, number of rooms, household size and household head labor market participation significantly affected the propensity to use charcoal as transitional fuel and lpg as a modern fuel. the robustness testing of the results supports existing evidence in the literature which asserts that traditional fuel source (fuelwood) dominates in poor households. charcoal, as a transitional fuel remains the most dominant primary fuel for cooking not only for lowerand middle-income household categories but also for the richest household category. the propensity to use charcoal and lpg as primary fuels decreased steadily by their percentage points of the marginal effects corresponding to the income category of the household. the highest income household households use mostly single fuel with no secondary fuel. this suggests a key policy implication of the need to intensify “clean energy use” campaigns project and strategic activities taking into consideration of regional differences. this will reduce regional biases to allow household energy transition to take place from primitive fuels to more advanced modern energy sources whilst encouraging poverty alleviation to improve household income status and affordability ceteris paribus (paudel et al., 2018; akpalu et al., 2011). the limitation of these study findings is that these results imply correlation not causality since they are based on the cross-section data set that does not capture temporal effects of time variable in order to further examine renewable energy transition process in the households. as a result of this limitation, this paper could not employ dynamic discrete models to analyze the expected behavior following the lucas critique which allows to make predictions (tchereni, 2013; aguirregabiria and mira, 2010). for further research, it would be ideal to investigate key determinants for using clean energy sources in these households by employing a panel framework as datasets become available as well as inclusion of other important variables such as risk perception, social norms and awareness levels about clean energy technologies such as lpg. references adusah-poku, f., takeuchi, k. (2019), household energy expenditure in ghana: a double hurdle model approach. world development, 117, 266-272. aguirregabiria, v., mira, p. (2010) dynamic discrete choice structural models: a survey. journal of econometrics, 156, 38-67. akpalu, w., dasmani, i., aglobitse, p.b. (2011), demand for cooking fuels in a developing country: to what extent do taste and preferences matter? energy policy, 39, 6525-6531. arnold, m., kohlin, g., persson, r. (2006), wood fuels, livelihoods and policy interventions: changing perspectives. world development, 34, 596-611. bahadur, d., behera, b., ali, a. (2016), household energy choice and consumption intensity : empirical evidence from bhutan. renew sustain energy review, 53, 993-1009. bhattacharyya, s.c. (2012), energy access programmes and sustainable development: a critical review and analysis. energy for sustainable development, 16, 260-271. buba, a., abdu, m., adamu, i., jibir, a., usman, y.i. (2017), socioeconomic determinants of households fuel consumption in nigeria. international journal of research granthaalayah, 5, 348-360. cameron, c., pachauri, s., rao, n.d., mccollum, d., rogelj, j. (2016), policy trade-offs between climate mitigation and clean cook-stove access in south asia. nature energy, 1, 15010. daioglou, v., van ruijven, b.j., van vuuren, d.p. (2012), model projections for household energy use in developing countries. energy, 37, 601-615. ekholm, t., krey, v., pachauri, s., riahi, k. (2010), determinants of household energy consumption in india. energy policy, 38, 56965707. farsi, m., filippini, m. (2007), fuel choices in urban indian households. environment and development economics, 12, 757-774. greene, w. (2012) econometrics analysis. 7th ed. new york: pearson; 2012. p. 721-840. heltberg, r. (2005), factors determining household fuel choice in guatemala. environment and development economics, 10, 337-361. hiemstra-van der horst, g., hovorka, a.j. (2008), reassessing the “energy ladder”: household energy use in maun, botswana. energy policy, 36, 3333-3344. international energy agency. (2006), world energy outlook. paris, france: international energy agency. jumbe, c.b.l., angelsen, a. (2006), household’s choice of fuelwood source in malawi: a multinomial probit analysis. australia: paper presented at the international association of agricultural economists conference, gold coast, 12-18 august 2006. karimu, a. (2015), cooking fuel preferences among ghanaian households: an empirical analysis. energy for sustainable development, 27, 10-17. madubansi, m., shackleton, c.m. (2007), changes in fuelwood use and selection following electrification in the bushbuckridge lowveld, south africa. journal of environment management, 83, 416-426. makonese, t., ifegbesan, a.p., rampedi, i.t. (2018), household cooking fuel use patterns and determinants across southern africa: evidence from the demographic and health survey data. energy and environment, 29, 29-48. marathe, s.d., eltrop, l. (2017), domestic energy consumption patterns in kigali, rwanda how disparate are they in view of urbanisation? paper presented at 2017 international conference on the domestic use of energy (due), april, 2017. masera, o.r., saatkamp, b.d., kammen, d.m. (2000), from linear fuel switching to multiple strategies: a critique and alternative to the energy ladder model. world development, 28, 2083-2103. mbaka, c.k., gikonyo, j., kisaka, o.m. (2019), households’ energy preference and consumption intensity in kenya. energy, sustainability and society, 9, 20. mekonnen, a., kohlin, g. (2009), determinants of household fuel choice in major cities in ethiopia. working papers in economics no. 399. morrissey, j. (2017), the energy challenge in sub-saharan africa: a guide for advocates and policy makers: part 2: addressing energy poverty. united states: oxfam research backgrounder series. national institute of statistics of rwanda. (2012), republic of rwanda, fourth population and housing census of rwanda 2012. rwanda: national institute of statistics of rwanda. national institute of statistics of rwanda. (2015), republic of rwanda, ministry of infrastructure, national urbanisation policy. rwanda: national institute of statistics of rwanda. national statistics institute of rwanda. (2018), the eicv 5 rwanda khundi-mkomba: are urban rwandan households using modern energy sources? an exploration of cooking fuel choices international journal of energy economics and policy | vol 11 • issue 2 • 2021332 poverty panel thematic report 2016/2017. december 2018. kigali, rwanda: national statistics institute of rwanda. nlom, j.h., karimov, a.a. (2015), modeling fuel choice among households in northen cameroon. sustainability, 7, 9989-9999. pachauri, s., jiang, l.w. (2008), the household energy transition in india and china. energy policy, 36, 4022-4035. pachauri, s., rao, n.d., cameron, c. (2018), outlook for modern cooking energy access in central america. plos one, 13, e0197974. pachauri, s., spreng, d. (2004), energy use and energy access in relation to poverty. economic and political weekly, 39, 271-278. pachauri, s., van rjuvien, b., nagai, y., riahi, k., van vuuren, d.p. (2013), pathways to achieve universal household access to modern energy by 2030. environmental research letters, 8, 024015. paudel, u., khatri, u., krishna, p.p. (2018), understanding the determinants of household cooking fuel choice in afghanistan: a multinomial logit estimation. energy, 156, 55-62. sher, f., abbas, a., awan, r.u. (2014), an investigation of multidimensional energy poverty in pakistan: a province level analysis. international journal of energy economics and policy, 4, 65-75. smith, m.g., urpelainen, j. (2014), early adopters of solar panels in developing countries: evidence from tanzania. review of policy research, 31, 17-37. tchereni, b.h.m. (2013), a microeconomics analysis of energy choice behaviour in south lunzu township, malawi. mediterranean journal of social sciences, 4(6), 569-578. tchereni, b.h.m. (2013), an econometric analysis of energy poverty and sustainable development in blantyre (malawi). phd dissertation, north-west university. the international renewable energy agency. (2019), renewable energy: a gender perspective. abu dhabi: the international renewable energy agency. toole, r. (2015) the energy ladder: a valid model for household fuel transitions in sub-saharan africa? master thesis 2015. unhabitat. (2020), law no10/ 2012 of 02/05/2012 governing urban planning and building in rwanda. http://www.urbanlex.unhabitat. org. [last accessed on 2020 oct 08]. van der kroon, b., brouwer, r., van beukering, p.j.h. (2013), the energy ladder: theoretical myth or empirical truth? results from a meta-analysis. renew sustain energy review, 20, 504-513. van ruijven, b.j., van vuuren, d.p., de vries, b.j.m., isaac, m., van der sluijs, j.p. (2011), model projections for household energy use in india. energy policy, 39, 7747-7761. world population review. (2020), rwanda population. available from: http://www.world populationreview.com/countries/rwandapopulation. [last accessed on 2020 jun 08]. zulu, l.c., richardson, r.b. (2012), charcoal, livelihoods, and poverty reduction: evidence from sub saharan africa. energy for sustainable development, 17, 127-137. table 1a: collinearity diagnostics variable’s name vif tolerance household size 2.91 0.3432 age of head 2.76 0.3626 number of children 2.37 0.4212 number of elderly 1.88 0.5309 log of asset value 1.73 0.5784 electricity access 1.59 0.6308 owner occupancy 1.51 0.6632 number of rooms 1.45 0.6891 detached house 1.44 0.6962 male head 1.40 0.7159 poor 1.38 0.7260 education of head 1.26 0.7966 head is a labor market participant 1.23 0.8155 received environmental information 1.08 0.9285 mean vif 1.70 appendix tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 6 • 2021 91 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(6), 91-97. opportunities and potential of bioenergy development in agroindustrial complexes of kazakhstan zhomart omarov1*, abay kalykov2, roza niyazbekova3, altyn yessirkepova4 1north-kazakhstan state university, named after m. kozybayev, pushkin st. 86, petropavlovsk, kazakhstan, 2astana it university, expo business center, block c. 1, nur-sultan, kazakhstan, 3m. auezov south kazakhstan university, makarova st., 26, shymkent, kazakhstan, 4academy of public administration, under the president of the republic of kazakhstan, shymkent’ branch, zemlyachka st., 14, shymkent, kazakhstan. *email: omarov-zhomart@inbox.ru received: 21 may 2021 accepted: 29 august 2021 doi: https://doi.org/10.32479/ijeep.11530 abstarct the article examines the possibility of developing bioenergy in the agro-industrial complexes of kazakhstan which can reduce greenhouse gas emissions into the atmosphere and solve problems associated with the disposal of agricultural waste. special attention is paid to bioenergy generation technologies in agro-industrial complexes which require high capital expenditures to be equipped with modern automation and control facilities. the authors analyse the potential of biogas production from livestock and poultry waste in the agro-industrial complexes of kazakhstan. during the analysis, it was revealed that the largest volumes of organic waste are produced by cattle breeding, and the smallest – by poultry farming. the article presents an assessment method based on the construction of a two-factor correlation-regression model, in which the effective (endogenous) factor feature is the total production of biogas and the total biomass is selected as an independent (exogenous) factor feature. the results of the calculations showed that the models reflecting the dependence of the total biogas production on the total biomass for cattle, sheep and goats, as well as poultry, correspond to the real flow of processes in the economy and logic. keywords: alternative energy source, bioenergy, green economics jel classifications: q42, q50 1. introduction kazakhstan is one of the largest agro-based economies in central asia which boasts expansive crop cultivation that generates huge amounts of agricultural residues. there have been intentions to convert these residues into bioenergy for cooking, heating, and electricity production. currently, the conversation of agricultural residues to heat is limited to only a few biomass-based boiler plants, although integration of renewable energy into energy balance is highly considered as a number priority in the countries realization of green economy strategy. the concept for the transition of the republic of kazakhstan to a “green economy” (2013) provides that by 2030, the structure of electricity production by 10% should consist of renewable energy sources (res). for this purpose, the decree of the government of the republic of kazakhstan (2014) “on approval of fixed tariffs” approved fixed tariffs for 15 years for each type of renewable energy. when approving fixed tariffs for bioenergy, the international obligations of the republic of kazakhstan to reduce greenhouse gas emissions were taken into account. the conversion of unused agricultural residues to energy is one way to increase the country’s share of renewable energy. this makes renewable energy from agricultural residues is scalable because of the enormous potential it currently holds. this paper aims to point out the opportunities and potential of bioenergy development in agro-industrial complexes with the focus being on kazakhstan. this journal is licensed under a creative commons attribution 4.0 international license omarov, et al.: opportunities and potential of bioenergy development in agro-industrial complexes of kazakhstan international journal of energy economics and policy | vol 11 • issue 6 • 202192 to achieve the goal, the following tasks must be completed: • review the literature on the production of bioenergy from agricultural waste • consider bioenergy generation technologies • analyze the potential of bioenergy development in kazakhstan • evaluate the conversion of agricultural waste to bioenergy. 2. literature review currently, many scientists are studying the problems of recycling agricultural waste with the possibility of using it in the country’s energy sector. their research examines the prospects for the use of renewable energy sources in agriculture (bolyssov, 2019) and the possibility of using organic waste as a primary resource for the production of biogas, electricity and heat (tasmaganbetov, 2020). according to babaeva et al. (2017), green energy or renewable energy is processed from various physical processes. the main purpose of this form of energy is to limit the number of greenhouse emissions, reduce the over-dependence on fossil fuel that is associated with volatility in the fuel markets. moreover, the utilization of renewable energy also contributes to the countries environmental and energy goals. currently, there is an enormous potential for kazakhstan to convert agricultural residues to bioenergy. these residues make up crop cultivation, animal husbandry, which makes this undertaking viable because of the availability of raw materials. according to the recent visibility study, that summarized kazakhstan’s potential of availability for crop residues for energy conversion in kazakhstan. the production of energy from biomass volume involves a range of technologies that includes solid combustion, fermentation, gasification among others. these technologies produce gas and liquid fuels from a diverse set of biological sources, including crop residues, wastes, and traditional crops. there is also dung and organic component of urban waste. all this produce bioenergy that is used for various purposes including heating, cooking fuel, electricity, and transportation fuels (de corato et al., 2018). this diversity makes bioenergy development suitable for all stakeholders that range from policymakers to the final consumer. it has environmental, social, and economic benefits, thus, the issue at hand is developing an international framework with backup strong domestic policy instruments. moreover, bioenergy derived from sustainable agriculture practices provides an opportunity for the country to utilize its resources and attract the necessary stakeholders to accelerate its sustainable development process. some of the benefits that come with the development of bioenergy include environmental benefits from the reduction of greenhouse gases and the recuperation of soil productivity and degraded lands. the economic benefits could result from increased activity that will be a result of improved access to quality energy services (beltrán-ramírez et al., 2019). other benefits come with bioenergy development, for instance, bioenergy development is associated with poverty alleviation and development. the first set of critical energy needs includes those that satisfy human needs which includes, fuel for cooking and heating, electricity for health and education services, and energy for pumping water. another set of these critical energy needs includes those that provide energy for income generation which helps break the cycle of poverty. for instance, brazil is one such country that has benefits from biofuels, the country has had a sustainable ethanol production. sugar cane is the main source of biofuel which is transferable to other countries (fytili and zabaniotou, 2018). as it can be seen, the development of bioenergy with well-thoughtout management can reduce greenhouse gas emissions into the atmosphere, solve problems associated with the disposal of agricultural waste and increase the energy security of agriculture. 3. technologies for the production of bioenergy there are several technologies around the world being used to convert agricultural residues or waste to energy. however, biomass for energy continues to be the main source of renewable energy in several countries across the world. the current trends indicate that the heating and cooling sectors continue to be the large end-user consuming about three-quarters of all the bioenergy (fernandezmena et al., 2016). in kazakhstan the technology of converting agricultural residues is still in early stages, therefore the paper proposes some solutions as indicated below: 3.1. crop residues combustion on biomass heat only boilers this technology has a capex capacity of 700, 000 eur/mw this technology involves the combustion of the agricultural residues in standalone biomass boilers and the production of heat. feedstock are fed to grate boilers and after the combustion, heat is used for the local purpose such as space heating, and domestic hot water. the main raw material for use in this technology are crop residues and dry organic residues (mellor et al., 2021). 3.2. crops residues co-firing in the existing large only boiler plants this technology has a capex capacity of 150000 eur/mw and involves the agricultural residues in an existing boiler which is fed by a limited amount of biomass into the furnace and production of heat. moreover, the feedstock are crushed into dust in large crushers and fed to existing boilers and after the combustion, heat is used for the local purpose such as space heating, domestic hot water, and process heat of higher temperatures. the main raw materials used for this technology include dry organic residues, and crop residues (ghimire et al., 2017). 3.3. biogas plants this technology produces methane gas, through the fermentation of organic matter process. the feedstock is transported to plants and after anaerobic process biogas is then generated. some of the output products that are involved in this process include biogas, and digestate which could be used as fertilizer. omarov, et al.: opportunities and potential of bioenergy development in agro-industrial complexes of kazakhstan international journal of energy economics and policy | vol 11 • issue 6 • 2021 93 the country stands to benefit from the deployment of energy conversation system, for instance, it could benefit from less ghg emissions, carbon dioxide, and nitrous dioxide gases into the atmosphere, although agro-residue handling requirements and volume vary across the country, this volume could be captured and combined across different farms in a single specific facility, where it can be processed and converted to energy. besides, the unused agricultural residues conversion also ensures the production of useful heat that can then be used for both local and industrial sectors or electricity that can be absorbed into the national and local grid. there is also the aspect of byproduct that comes with the process, in this case, is fertilizer which could be used in other farming activity across the country and also increase soil fertility. the process also enables recirculation of the organic and green waste from farms. it also enables better waste management process at local and industrial levels (suhartini et al., 2020). there is also the aspect of the sustainable development goals, clean energy technology will help the country realize these goals faster. for instance, access to clean energy such as biomass energy can help to minimize gender inequalities and the variations in energy access across different gender dimensions, cultural and social contexts. besides, the introduction of cleaner energy, and renewable fuel sources, can bring training, entrepreneurial, and employment opportunities for different communities across the country. modern and improved energy services have the potential of improving the socio-economic status of women by reducing the amount of time required for household chores (markou et al., 2018). today majority of the manure digested to biogas is in form of slurry, although it is also possible to produce biogas for solid manure. however, the process is slow and has far less desirable economic outcomes, even in cases where subsidies are available. the slurry is fed to a digester tank where the carbon content in the slurry is broken down into methane which is later used as fuel. in digester are normally air-tight, in there, bacteria decomposes organic materials in the absence of air which then releases methane and carbon dioxide. acid-forming bacteria break down the volatile acids to methane and carbon dioxide. these bacteria are sensitive to changes in their environment. for rapid digestion and efficient biogas production to occur the environment has to main a given temperature. that is, the optimum gas production occurs in specific temperature ranges. for instance, mesophilic bacteria thrive in temperature around 35°c or 95°f and thermophilic in the 120°f–140°f or 49°c–60°c (mouratiadou et al., 2020). the main components of the digester system include a slurry handling system, slurry preparation area, manure pump, and effluent tank. other components include housing for the heating, agitation, and hydraulic equipment. the digester can either load the slurry continuously or by the batch. once the batch is filled to the required capacity, it will be sealed until it has produced all the biogas, then it will be emptied and filled again. it is also worth noting that biogas production is not consistent because bacterial digestion normally starts slowly, peaks, and then tapers off as the volatile solids are consumed. however, this can be solved by connecting a series of batch-load digesters that have been loaded at different times, this way a dependable amount of gas available at all times (searchinger et al., 2017). the digester has rigid walls, agitation equipment, and a minimum area to manage heat loss. the technology will utilize combined heat and power plant where give farms will be utilized manure residues and crop residues as an organic mix. the mix will be sent to the biogas plant for anaerobic digestion. the main output for this design will be digested and biogas. the digestate will be used as fertilizer on the other hand the biogas will be used to produce electricity and heating for the neighboring community (smith et al., 2017). the biogas produced by the digester will be approximately 70% methane and 30% carbon dioxide. this implies that the quality of the gas is 70% energy or 28 mj/m3. however, the methane content of the biogas will fluctuate according to the digester conditions. the hydrogen sulfide that is contained in the gas will be filtered through passing the gas through iron fillings given the gas is warm when it leaves the digester. the current situation in the country is that farmers benefit from the captured agricultural residues schemes in some ways, for instance, manure is used as fertilizer, which reduces expenditure on organic fertilizer. there is another part of residues that are used as animal feed bedding. nonetheless, a large part of unused residues could potentially help farmers to benefit from the production of additional alternative energy volumes and revenue streams, and high-quality fertilizer (hassan et al., 2019). as it can be presented, biogas is produced in biogas plants wherever bio-waste is available and is consumed immediately. animal waste is of interest from the point of view of its use for the production of biogas and energy only if the animals are concentrated in confined spaces. in this case, there is a possibility of economically justified collection of manure with minimal or no dirt impurities. the use of anaerobic digestion of manure for the production of biogas and organic fertilizers will be very effective for various types of farms and farms that are remote from centralized energy supply systems. nevertheless, the introduction of biogas technologies in agro-industrial complexes requires high capital expenditures. the level of these investments depends on the capacity of the installation, the equipment with modern automation and control tools, and the manufacturer of specific devices. 4. analysis of the potential for the development of bioenergy in the agro-industrial complexes of kazakhstan the agro-industrial complex of kazakhstan today faces the problem of recycling a huge amount of waste – most often they are simply exported from the territories of farms and stored. this leads to problems of soil oxidation, alienation of agricultural omarov, et al.: opportunities and potential of bioenergy development in agro-industrial complexes of kazakhstan international journal of energy economics and policy | vol 11 • issue 6 • 202194 land, contamination of groundwater and emissions of methane, a greenhouse gas, into the atmosphere. according to the statistics committee of the ministry of national economy of the republic of kazakhstan (2020), the country has an annual increase in the number of livestock and birds (table 1). over the past 10 years, the republic of kazakhstan has seen an increase in the number of cattle (1.26 million heads), sheep and goats (1.17 million) and birds (12.24 million). large livestock complexes and poultry farms in modern conditions remain the most harmful environmental pollutants. in the same places, the population is concerned about the unpleasant smell caused by the decomposition of biological waste from livestock activities or the introduction of manure into the fields. one of the possible solutions to this problem is the implementation of projects for the production of biogas from livestock and poultry waste in agro-industrial complexes. agricultural waste will be the main raw material for generating electricity and heat. the potential of biogas production from livestock and poultry waste in the republic of kazakhstan is presented in table 2. according to the data obtained (table 2), in the republic of kazakhstan, the annual output of livestock and poultry waste by dry weight – 23.3 million tons can give 8.9 billion tons. m3 of biogas. depending on the type of organic feedstock, the composition of biogas may vary, but, in general, it includes methane (ch4), carbon dioxide (co2), a small amount of hydrogen sulphide (h2s), ammonia (nh3) and hydrogen (h2). since biogas consists of 2/3 of methane-a combustible gas that forms the basis of natural gas, its energy value (specific heat of combustion) is 60-70% of the energy value of natural gas, or about 7000 kcal per m3. 1m3 of biogas is also equivalent to 1.5-2.2 kw/h of electricity and 2.8-4.1 kw/h of heat. analysis of the potential for bioenergy production from agricultural waste showed that the largest volumes of organic waste are generated by cattle breeding (26152.5 mw/h of electricity and 48818 mw/h of heat), and the smallest – poultry farming (968.88 mw/h of electricity and 1805.64 mw/h of heat). the use of biogas plants will generate 41.7 million mw/h of bioenergy per year. thus, the introduction of biogas plants will significantly improve the environmental situation near large agro-industrial complexes, as well as in the territories where animal waste is currently dumped, and reduce the cost of environmental payments. 4.1. assessment conversion of agricultural waste to bioenergy the authors propose a method of estimating, based on the construction of two-factor regression models in which effective (endogenous) factor common symptom is the production of biogas (y). as an independent (exogenous) in the factor variable is selected the total biomass (x). in general, the two-factor regression model is as follows (gusarov, 2001): ˆ xy = a0 + a1•х� (1) to find the parameters a0 and a1, the following system of linear equations is used (shmoylova et al., 2006): 0 1 2 0 1 a n a x y a x a x y x  ⋅ + ⋅ =  ⋅ + ⋅ = ⋅ ∑ ∑ ∑ ∑ ∑ (2) to determine the reserves available in an independent factor attribute, an elasticity coefficient is used, which shows the average change in the effective attribute ˆ xy when the factor attribute x changes by 1%. in general, the coefficient of elasticity is defined as follows (gusarov, 2001): э�=� 1 x a y ⋅ (3) table 2: potential of biogas production using livestock and poultry waste in the republic of kazakhstan source of biogas average livestock, numbers in millions biomass, kg/day per unit total biomass, ton/ day volume of biogas produced from 1 kg of biomass, m3 total biogas production thousand m3/day cattle 6.34 55 348700 0.05 17435 sheep and goats 18.16 6 108960 0.06 6537.6 birds 37.01 0.17 6291.7 0.07 440.4 total 463951.7 24413 annual volume of biomass and biogas 23342370.5 8910745 source: compiled by the authors according to the statistics committee of the ministry of national economy of the republic of kazakhstan (2020) table 1: number of livestock and birds in the republic of kazakhstan for 2010-2019 amount in millions source of biogas 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 average amount cattle 6.18 5.70 5.69 5.85 6.03 6.18 6.41 6.76 7.15 7.44 6.34 sheep and goats 17.99 18.09 17.63 17.56 17.91 18.02 18.18 18.33 18.69 19.16 18.16 birds 32.78 32.87 33.47 34.17 35.02 35.63 36.91 39.91 44.34 45.04 37.01 source: compiled by the authors according to the statistics committee of the ministry of national economy of the republic of kazakhstan (2020) omarov, et al.: opportunities and potential of bioenergy development in agro-industrial complexes of kazakhstan international journal of energy economics and policy | vol 11 • issue 6 • 2021 95 where а1 – regression coefficient for the factor�х; x – the average value of an independent factor attribute; y – the average value of the studied indicator. э�–�the coefficient of elasticity, which shows how many percent the effective factor attribute will change with a 1% change in the independent factor attribute. to determine the parameters of the model (1), the authors performed separate calculations for the total biomass and total biogas production for cattle, sheep and goats, as well as poultry (tables 4-6). therefore, three models and three elasticity coefficients are defined, respectively. after substituting the total values of table 4, the system of linear equations (2) will look like this: 0 1 0 1 5 a 1 844 996 a 94 558 1 844 996 a 686 511 170 936 a 35 247 237 626 ⋅ + ⋅ =  ⋅ + ⋅ = (4) having solved this system, we have: = −  = 0 1 a 4 059,79 a 0,0622 (5) thus, the desired model (1), reflecting the dependence of the total biogas production on the total biomass obtained from cattle, will look like this: ˆ xy = 0,0622 х-4059,79 (6) we will determine the reserves laid down in the independent (exogenous) factor. to do this, we calculate the elasticity coefficient using the formula (3). э�=� (1 844 996 / 5) 0,0622 1,2147 (94 558 / 5) ⋅ = (7) in general, we have the following: • the sign of the coefficient a1 in the model (6) corresponds to the real flow of processes in economics and logic • if the total biomass obtained from cattle increases by 1%, the total production of biogas will increase by 1.2147%. after substituting the values of table 5, the system of linear equations (2) will look like this: 0 1 0 1 5 a 543 704 a 30 341 543 704 a 59 124 070 216 a 3 299 363 747 ⋅ + ⋅ =  ⋅ + ⋅ = (8) table 4: data for calculating parameters a0 and a1 in the model (1) for cattle year numbers in millions total biomass, tons/day, x total biomass/per day, x total biogas production, thousand m3/day, y total output of biogas/m3/per day, y х2 х*у 2015 6.18 327 850 16 010 107 485 622 500 5 248 878 500 2016 6.41 332 080 17 340 110 277 126 400 5 758 267 200 2017 6.76 374 820 18 510 140 490 032 400 6 937 918 200 2018 7.15 402 990 20 357 162 400 940 100 8 203 667 430 2019 7.44 407 256 22 341 165 857 449 536 9 098 506 296 total 1 844 996 94 558 686 511 170 936 35 247 237 626 source: compiled by the authors according to the statistics committee of the ministry of national economy of the republic of kazakhstan (2020) table 5: data for calculating parameters a0 and a1 in the model (1) for sheep and goats year numbers in millions total biomass, tons/day, x total biomass/per day, x total biogas production, thousand m3/day, y total output of biogas/m3/per day, y х2 х*у 2015 18.02 108 001 6 002 11 664 216 001 648 222 002 2016 18.18 108 327 6 050 11 734 738 929 655 378 350 2017 18.33 108 965 6 089 11 873 371 225 663 487 885 2018 18.69 109 030 6 190 11 887 540 900 674 895 700 2019 19.16 109 381 6 010 11 964 203 161 657 379 810 total 543 704 30 341 59 124 070 216 3 299 363 747 source: compiled by the authors according to the statistics committee of the ministry of national economy of the republic of kazakhstan (2020) table 3: potential of bioenergy production using livestock and poultry waste in the republic of kazakhstan source of biogas cattle total biogas production thousand m3/day energy generation rate, per 1 m3 bioenergy generation electricity, kw/h heat energy, kw / h electricity, mw / h heat energy, mw/h sheep and goats 17435 1.5 2.8 26152.5 48818 birds 6537.6 2.0 3.6 13075.2 23535.36 total 440.4 2.2 4.1 968.88 1805.64 source of biogas 24413 40196.58 74159 annual production of bioenergy, mw / h 41739786.7 source: compiled by the authors according to the statistics committee of the ministry of national economy of the republic of kazakhstan (2020) omarov, et al.: opportunities and potential of bioenergy development in agro-industrial complexes of kazakhstan international journal of energy economics and policy | vol 11 • issue 6 • 202196 having solved this system, we have: =  = 0 1 a 974,06 a 0,05 (9) thus, the desired model (1), reflecting the dependence of the total biogas production on the total biomass obtained from sheep and goats, will look like this: ˆ xy �=�0,05�‧�х�+�974,06� (10) we will determine the reserves laid down in the independent (exogenous) factor. to do this, we calculate the elasticity coefficient using the formula (3). � э�= (543 704 / 5) 0,05 0,8395 (30 341 / 5) ⋅ = (11) in general, we have the following: • the sign of the coefficient a1 in the model (10) corresponds to the real flow of processes in economics and logic • if the total biomass obtained from sheep and goats increases by 1%, the total biogas production will increase by 0.8395%. after substituting the values of table 6, the system of linear equations (2) will look like this: 0 1 0 1 5 a 32 610 a 2 342 32 610 a 213 727 574 a 15 325 639 ⋅ + ⋅ =  ⋅ + ⋅ = (12) having solved this system, we have: =  = 0 1 a 149,43 a 0,049 (13) thus, the desired model (1), reflecting the dependence of the total biogas production on the total biomass obtained from poultry, will look like this: ˆ xy �=�0,049�‧�х�+�149,43� (14) we will determine the reserves laid down in the independent (exogenous) factor. to do this, we calculate the elasticity coefficient using the formula (3). � э�= (32 610 / 5)0,049 0,681 (2 342 / 5) ⋅ = (15) in general, we have the following: • the sign of the coefficient a1 in the model (14) corresponds to the real flow of processes in economics and logic • if the total biomass obtained from birds increases by 1%, the total biogas production will increase by 0.681%. thus, based on the results of calculations based on the construction of a two-factor correlation-regression model, the following conclusions can be drawn: 1. the models reflecting the dependence of the total biogas production on the total biomass for cattle, sheep and goats, as well as poultry, correspond to the real flow of processes in the economy and logic 2. with an increase in the total biomass by 1%, the total production of biogas will also increase (for cattle by 1.2147%, sheep and goats by 0.8395%, poultry by 0.681%). therefore, it is necessary to apply a technology for the production of biogas with a high methane yield. 5. conclusion biogas technologies should be installed near agro-industrial complexes, as well as in the territories where animal waste is currently dumped. in this case, there is a possibility of economically justified collection of manure with minimal or no dirt impurities. analysis of the potential for bioenergy production from agricultural waste showed that the largest volumes of organic waste are produced by cattle breeding, and the smallest – by poultry farming. agricultural waste will be the main raw material for generating electricity and heat. calculations based on the construction of a two-factor correlation-regression model also confirmed the dependence of the total production of biogas on the total biomass of animal waste. references babaeva, z.s., postnova, m.v., yalmaev, r.a., kasimova, z.n., isbagieva, g.s. (2017), agricultural lease as a form of financial support for the expanded reproduction of the agro-industrial complex. espacios, 38(62), 7-14. beltrán-ramírez, f., orona-tamayo, d., cornejo-corona, i., gonzález-cervantes, j.l.n., de jesús esparza-claudio, j., quintana-rodríguez, e. (2019), agro-industrial waste revalorization: the growing biorefinery. in: biomass for bioenergy-recent trends and future challenges. london: intechopen. bolyssov, t. (2019), features of the use of renewable energy sources in agriculture. international journal of energy economics and policy, 2019, 9(4), 363-368. table 6: data for calculating parameters a0 and a1 in the model (1) for birds year numbers in millions total biomass, tons/day, x total biomass/per day, x total biogas production, thousand m3/day, y total output of biogas/m3/per day, y х2 х*у 2015 35.63 6 037 453 36 445 369 2 734 761 2016 36.91 6 099 426 37 197 801 2 598 174 2017 39.91 6 342 478 40 220 964 3 031 476 2018 44.34 7 008 482 49 112 064 3 377 856 2019 45.04 7 124 503 50 751 376 3 583 372 total 32 610 2 342 213 727 574 15 325 639 source: compiled by the authors according to the statistics committee of the ministry of national economy of the republic of kazakhstan (2020) omarov, et al.: opportunities and potential of bioenergy development in agro-industrial complexes of kazakhstan international journal of energy economics and policy | vol 11 • issue 6 • 2021 97 de corato, u., de bari, i., viola, e., pugliese, m. (2018), assessing the main opportunities of integrated biorefining from agro-bioenergy co/by-products and agroindustrial residues into high-value added products associated to some emerging markets: a review. renewable and sustainable energy reviews, 88, 326-346. decree of the president of the republic of kazakhstan. (2013), dated may 30, no. 577 “on the concept of transition of the republic of kazakhstan to a green economy”. available from: https://www. online.zakon.kz/document/?docid=31399596#pos=0;167 fernandez-mena, h., nesme, t., pellerin, s. (2016), towards an agro-industrial ecology: a review of nutrient flow modelling and assessment tools in agro-food systems at the local scale. science of the total environment, 543, 467-479. fytili, d., zabaniotou, a. (2018), circular economy synergistic opportunities of decentralized thermochemical systems for bioenergy and biochar production fueled with agro-industrial wastes with environmental sustainability and social acceptance: a review. current sustainable/renewable energy reports, 5(2), 150-155. ghimire, a., kumar, g., sivagurunathan, p., shobana, s., saratale, g.d., kim, h.w., munoz, r. (2017), bio-hythane production from microalgae biomass: key challenges and potential opportunities for algal bio-refineries. bioresource technology, 241, 525-536. gusarov, v.m. (2001), statistics: textbook for universities. moscow: unity-dana. p463. hassan, s.s., williams, g.a., jaiswal, a.k. (2019), moving towards the second generation of lignocellulosic biorefineries in the eu: drivers, challenges, and opportunities. renewable and sustainable energy reviews, 101, 590-599. key indicators of animal husbandry development in the republic of kazakhstan. (2020), statistics committee of the ministry of national economy of the republic of kazakhstan available from: https://stat. gov.kz/official/industry/14/statistic/5 markou, g., wang, l., ye, j., unc, a. (2018), using agro-industrial wastes for the cultivation of microalgae and duckweeds: contamination risks and biomass safety concerns. biotechnology advances, 36(4), 1238-1254. mellor, p., lord, r. a., joão, e., thomas, r., hursthouse, a. (2021), identifying non-agricultural marginal lands as a route to sustainable bioenergy provision a review and holistic definition. renewable and sustainable energy reviews, 135, 110220. mouratiadou, i., stella, t., gaiser, t., wicke, b., nendel, c., ewert, f., van der hilst, f. (2020), sustainable intensification of crop residue exploitation for bioenergy: opportunities and challenges. gcb bioenergy, 12(1), 71-89. resolution of the government of the republic of kazakhstan. (2014), dated march 27, 2014 no. 271 on approval of the rules for determining fixed tariffs. available from: http://www.adilet.zan. kz/rus/docs/p1400000271 searchinger, t.d., beringer, t., strong, a. (2017), does the world have low-carbon bioenergy potential from the dedicated use of land? energy policy, 110, 434-446. shmoylova, r.a., minashkin, v.g., sadovnikova, n.a. (2006), workshop on the theory of statistics. 2nd ed. moscow: finance and statistics. p416. smith, c.t., lattimore, b., berndes, g., bentsen, n.s., dimitriou, i., langeveld, j.w.a., thiffault, e. (2017), opportunities to encourage mobilization of sustainable bioenergy supply chains. wiley interdisciplinary reviews: energy and environment, 6(3), e237. suhartini, s., nurika, i., paul, r., melville, l. (2020), estimation of biogas production and the emission savings from anaerobic digestion of fruit-based agro-industrial waste and agricultural crops residues. bioenergy research, 14(3), 1-16. tasmaganbetov, a.b. (2020), world practice of using biogas as alternative energy. international journal of energy economics and policy, 10(5), 348-352. international journal of energy economics and policy vol. 2, no. 2, 2012, pp. 55-62 issn: 2146-4553 www.econjournals.com energy consumption-economic growth nexus: does the level of aggregation matter? mehdi abid institute of management of sousse, rue abedelaziz el bahi b.p. 763 4000 sousse. university of sousse, tunisia. e-mail: abid.mahdi@yahoo.fr maamar sebri institute of management of sousse, rue abedelaziz el bahi b.p. 763 4000 sousse. university of sousse, tunisia. e-mail: maamar.sebri@gmail.com abstract: this study investigates the causal relationship between energy consumption and economic performance for the total economy as well as for industry, transport, and residential sectors for tunisia during the period 1980-2007. the application of vector error correction model (vecm) for non-stationary and cointegrated series suggests that causality directions at aggregated and disaggregated levels are mixed. however, the findings have important policy implications. while at the level of the total economy, energy plays an important role in development of tunisian economy, it seems not to have an impact on economic performance at sectoral level. we conclude that results appear to be dependent on the level of aggregation and therefore policy advices should be given with caution. keywords: energy sector; economic growth; granger causality; vector error correction models; tunisia. jel classifications: c01; c32; q43 1. introduction the growing concerns over energy scarcity and the sharp increase in its prices in recent years have renewed interests in the implementation of appropriate energy policies. although, the effect of energy consumption on economic growth at the level of the total economy has been the subject of many empirical studies, little attention has been paid to examine such a relationship at sectoral level. it has been discussed that conflicting results about the direction of causality relationship may arise due to the country or group of countries considered, econometric techniques, variables incorporated and time series included in the study. according gross (2012), another, even more important reason for why the evidence is so weak is the level of aggregation. the author has recommended the use of the appropriate level of aggregation when studying the energy-growth nexus. the author has argued that an absence of causality at the aggregate total economy does not indicate an absence of causality at disaggregate level1. therefore, policy implications could be misleading and affect individual sectors in both short and long run. the causal relationship between energy consumption and economic growth at aggregate and/or disaggregate level has been recently studied by jobert and kranfil (2007), zachariadis (2007), bowden and payne (2009), costantini and martini (2010), tsani (2010), cheng-lang et al. (2011)2. the case of total energy consumption and energy used in industrial sector in turkey was analyzed by jobert and kranfil (2007). the authors found an instantaneous causality between energy consumption 1 “if evidence for granger causality cannot be found at the level of the total economy, the implication that no causality exists at all is myopic (simpson’s paradox)”, (gross, 2012). 2 a detailed survey of literature on energy consumption-economic growth nexus can be found in the study of ozturk (2010) and binh (2011). energy consumption-economic growth nexus: does the level of aggregation matter? 56 and income, while at the long-run a neutral relationship was proved. zachariadis (2007) used data for g7 countries from 1949 to 2004. the results indicate no evidence for causality at the level of the total economy, but for services as well as transport sectors, gdp granger causes energy consumption. the author concluded that one should be cautious when drawing policy implications with the aid of bivariate causality tests on small samples. bowden and payne (2009) used usa time series from 1949 to 2006 to analyze primary energy consumption-gdp nexus using aggregate and sectoral measures. the authors found different results but they concluded that one should be prudent when using energy use by sector and total gdp as a pair of variables. costantini and martini (2010) used data for oecd and non-oecd countries to check the causality between economic growth and energy consumption for different sectors. for industrial sector, the two groups of countries show similar trends at the shortrun, while they behave differently toward energy consumption at the long-run. for transport sector, different results were obtained for the two sub-samples, but similar conclusions were derived from residential sector indicating no causality relationships in both developed and developing countries. tsani (2010) studied the case of greece from 1960 to 2006 and found different results at aggregated and by sectors (industrial, residential, and transport). hence, different policy implications were driven for different sectors. cheng-lang et al. (2011) investigated the causal relationship between real gdp and electricity use in industrial and residential sectors using quarterly data from 1982 to 2008 in taiwan. the authors used two types of causality, linear and non-linear. different results for different sectors were obtained according the econometric methodology used. in a recent paper, belloumi (2009) investigated the causal relationship between energy consumption and economic growth for the total economy in tunisia during the period 1971-2004. the author concluded that energy can be considered as a limiting factor to gdp growth. does this conclusion still valid when investigating the causality for the different sectors? the present attempt aims to give a response to this question by explaining the causality between energy and economic performance in the most energy-intensive sectors in tunisia (industrial, transport, and residential. the rest of the paper is organized as follows. section 2 reviews the evolution of energy use in tunisia focusing on main intensive-energy sectors. section 3 describes the methodology and data used. section 4 provides the analysis of empirical results. section 5 concludes the paper. 2. energy sector in tunisia from historical point of view, the energy sector in tunisia has known some ups and downs. until the end of 90s, tunisia had been an exporting country and during the 80s, the oil exportations had assured more than 50% of currencies takings. whereas from the beginning of the last decade the country has became a net importer of hydrocarbons. this takes the tunisian intensive-energy sectors in very sensitive situation especially with the sharp increase in energy prices in recent years. 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 0 500 1000 1500 2000 2500 figure i. total energy consumption by end-use sector source: own com pilat ion indus trial trans port residential tertiary agriculture kt o e international journal of energy economics and policy, vol. 2, no. 2, 2012, pp.55-62 57 the industrial, transport and residential sectors have the most share of energy consumption in tunisia. for example, in 2007, they represent about 83% of total energy consumption, while the tertiary and the agriculture sectors represent only 17%. figure i display the evolution of energy consumption by end-use sector in tunisia from 1980 to 2007. given the dominance of industrial, transport and residential sectors in ultimate energy use, our descriptive as well as econometrical analyses will focus only on these three sectors. moreover, we will consider that energy consumption depends only on the three basic components: oil, electricity, and natural gas because the other energy categories represent very small proportions and/or their consumption statistics are integrated in those of basic components. 2.1 industrial sector the industrial sector occupies the first place in total energy consumption of the country with a share of 35% in 2007. this sector consumes about 2047 kilo tonnes oil equivalent (ktoe) which has increased about 3.1% within last year. the most energy component in this sector is oil with a total consumption of 960 ktoe. the next two important components are natural gaz and electricity with 687 ktoe and 400 ktoe respectively. figure ii illustrates the shares of each component in total energy consumption for industrial sector from 1980 to 2007. 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 0 500 1000 1500 2000 2500 figure ii. evolution of industrial energy consumption by component source: own com pilat ion oil natural gas electricity kt o e the industrial sector plays a significant role in the tunisian economy. it contributes significantly to the gross domestic product, employment, gross fixed capital formation, merchandise exports, and the use of advanced technologies. accordingly, it has been called upon to play a key role in the transformation and development of the tunisian economy since the launching of market oriented reforms. the industrial value added has expanded rapidly from less than 8% in 1960 to 26% in 2007. during the period 1980-2007, the average annual growth rate in value added of industrial sector has been above 10%. the increase in performance of this sector has been accompanied by an average yearly growth rate in energy consumption of about 8.70%. 2.2 transport sector the transport sector by about 31% of ultimate energy consumption has the second place after the industry sector, but it stills the first consumer of oil component by nearly 47% of total oil consumption in the country. the energy consumption in the transport sector is essentially based on oil component with more than 99% and electricity which represents only 0.5% in 2007. this intensive dependency on oil consumption makes this sector as an important transmitter of greenhouse gas with a share above 25%. during the period 1980-2007, the average yearly growth rate in energy consumption in transport sector is about 7.85% which is very close to the average annual growth rate in industrial sector. the transport sector plays an important role in the development of tunisian economy. it employs 120000 persons (107000 in the public sector and 13000 in the private one), and generates about 14% of total investment in the country. however, the sharp increase in price of petroleum in recent years lets this sector (which is oil dependent) in sensitive situation which would influence economic growth of tunisia. hence, the government should adopt some policies of energy conservation such as encouragement of public transport, periodic control on vehicles. energy consumption-economic growth nexus: does the level of aggregation matter? 58 2.3 residential sector the residential sector by about 17% of ultimate energy consumption occupies the third place behind the industrial and transport sectors. total energy consumption in residential sector in 2007 reached to 990.5 ktoe which has increased by about 4.37% within last year. during the period 19802007, the average yearly growth rate in energy use in this sector is nearly 13.86% which is the highest rate among all other sectors. the most used carrier in the residential sector is oil with a total consumption of 492 ktoe in 2007, but its consumption has known a gradual decrease in 2007 and 2006 in comparison with its values in last years (see figure iii). the decrease in oil consumption is accompanied by an increase in consumption of electricity and natural gas which have an average yearly growth rate about 28.71% and 89.73% respectively from 1980 to 2007. the decrease in oil consumption and the increase in electricity and natural gas consumption imply that there is a tendency to use more clean energy. figure iii illustrates the trend of total energy consumption for residential sector by carrier from 1980 to 2007. 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 0 200 400 600 800 1000 1200 figure iii. evolution of residential energy consumption by component source: o wn comp ilat io n oil natural gas electricity kt oe energy use in the residential sector includes energy for heating, cooking, cleaning, washing, drying, lighting, cooling, and for entertainment. however, in tunisia, energy saving in this sector creates a win-win scenario. households frugal with energy reduce the amount of their power bills and they help lessen the budget allocations by the state to subsidize the consumption. thus, it is wise to invest in programs and actions to eliminate waste and streamline consumption. 3. methodology and data to test the direction of causality between aggregated and disaggregated energy consumption and economic growth in tunisia, we follow the now widely used engle-granger methodology. we first search for the order of integration of the different time series using the augmented dickey–fuller (adf) (dickey and fuller, 1979) and phillips-perron (pp) tests (phillips and perron, 1988). once, the series are integrated of the same order a long-run relationship (cointegration vector) could be exist. to test the presence of cointegration of the variables in this study, johansen’s approach (johansen, 1988; johansen and juselius, 1990) is employed. if the presence of cointegration is confirmed, then engle and granger (1987) error correction specification can be used to test for granger causality and show its direction. according engle and granger (1987), the vector error correction model (vecm) for the per capita variables can be written as follows: 11 12 10 11 12 13 1 1 1 1 (1) k k t i t i j t j t t i j y y x ect                  21 22 20 21 22 23 1 2 1 1 (2) k k t i t i j t j t t i j x x y ect                  where  is the difference operator, ty presents economic performance and tx is the energy consumption for the total and by sector; 1t and 2t are white noise error terms; 1tect  gives the lagged error international journal of energy economics and policy, vol. 2, no. 2, 2012, pp.55-62 59 correction term derived from the long-run effect. the existence of short-run causality meaning that the dependent variable responds only to short-term shocks can be determined by testing the null hypothesis of 12 0  in the equation (1) and 22 0  in the equation (2). to determine whether economic growth causes energy consumption or vice versa in the long-run, we look at the coefficients of the ect’s in equations (1) and (2) by testing the null hypothesis of 13 0  in equation (1) and 23 0  in equation (2) based on the t-statistics. these two coefficients measure the speed of adjustment. we can also check whether these two sources of causality are jointly significant by testing the joint hypothesis of 12 13 0   in equation (1) and 22 23 0   in equation (2). the rejection of the joint hypothesis indicates that after a shock to the system, both these sources of causality are responsible for the re-establishment of long-run equilibrium. annual time series data for tunisia from 1980 to 2007 are used in the present study. bivariate relationship at aggregate level includes total energy use for the whole economy (ec) and gdp. whereas, bivariate relationships at disaggregate level consider data on energy use (iec) and value added (iva) for the industrial sector, energy use (tec) and gdp for the transport sector, and energy use (rec) and the household final consumption expenditures (hfe) for the residential sector. for this last sector, we have used the gdp to represent the economic dimension, which is a common choice in literature (zachariadis, 2007; costantini and martini, 2010)3. data on economic performance are obtained from world bank world development indicators (wdi, 2010) and are expressed in constant 2000 us$. energy data are sourced from official source, national agency for energy conservation (naec) and are expressed in terms of kg oil equivalent. all series are taken in terms of per capita and defined in natural logarithms. 4. empirical results as mentioned in the methodology section, the analysis begins by testing the order of integration of the series in hand. table 1 reports the results for both adf and pp unit root tests. as shown in table i, all series are not stationary in levels but stationary in first difference. hence, they are integrated of order one (i(1)). table 1. results of adf and pp unit root tests variables adf test pp test level first difference level first difference gdp 2.228(0) -4.996(0)* 4.549(6) -4.997(1)* iva 0.855(0) -4.866(0)* 1.082(3) -4.873(1)* hfe 1.374(2) -5.352(11)* 2.754(1) -4.183(3)* ec -0.017(1) -8.077(0)* -0.049(1) -8.074(1)* iec -0.919(0) -7.389(0)* -0.919(0) -7.389(0)* tec -0.012(0) -4.618(0)* -0.063(1) -4.616(1)* rec -1.959(0) -5.499(0)* -1.294(1) -5.499(0)* * denotes the rejection of null hypothesis of non-stationarity of the variable at 1% level of significance. for the adf and the pp tests the values in parentheses indicate the optimum number of lags and bandwidth chosen based on schwarz bayesian criterion (sbc) and newey-west bartlett kernel, respectively. the critical values for the adf and pp tests t-statistics are based on mackinnon (1996). note that only intercept is included in the tests. once the series are found to be integrated of the same order, an investigation of potential cointegration relationship is carried out using both the johansen maximum eigenvalue (λ-max) and trace statistics to test the null hypothesis of no cointegration. the results reported in table 2 show that 3 gross (2012) has suggested that the use of total gdp instead of value added of transport is not appropriate choice especially when the share of value added of the transport sector in total gdp is negligible. energy consumption-economic growth nexus: does the level of aggregation matter? 60 the values of the calculated tests statistics are greater than the critical values which imply the rejection of the null hypothesis. then, long-run relationships exist between the pairs of considered series. table 2. johansen test for the number of cointegration relationships models eigenvalue h0 : ra trace λ-max critical values at 5% trace λ-max (gdp, ec) 0.561 0 26.452 21.407 20.261 15.892 0.176 1 5.044 5.044 9.164 9.164 (iva, iec) 0.641 0 32.997 23.607 20.261 15.892 0.335 1 9.389 9.389 9.164 9.164 (gdp, tec) 0.529 0 23.095 19.586 20.261 15.892 0.126 1 3.508 3.508 9.164 9.164 (hfe, rec) 0.502 0 25.063 16.746 20.261 15.892 0.292 1 8.317 8.317 9.164 9.164 a r indicates the number of cointegration relationships. the critical values for maximum eigenvalue and trace test statistics are given by johansen and jesilius (1990). we assume here that the level data have no deterministic trends and the cointegrating equations have intercepts. cointegration between series indicates a confirmed relationship in long-run but it fails to give the direction of causality. hence, to shed light on the causal relationship, a vecm is used to test the short-run as well as long-run granger causality, and the results are reported in table 3. the analysis of the granger causality will be conducted according each energy sector. full economy it can be seen that the 2-wald statistics on the lagged explanatory variables of the vecm design the absence of short-run causal effects in either direction. this implies that tunisian economic growth does not rely on energy use and energy sector is not a limiting factor to growth. the conclusion drawn from short-run context is not valid in the long-run context since the t-statistics on the coefficients of the ect indicate the significance of the long-run causal effects. the ect coefficients in the gdp and energy consumption equations are -0.10 and -0.059 respectively. this implies that the adjustment coefficients are 10% and 5.9% in the two equations. industry we find a uni-directional short-run granger causality running from industrial value added to energy consumption. these findings indicate that the knowledge of past values of industrial production influences the prediction of energy consumption. this is expected consequence as industry sector is the biggest consumer of energy. however, in the long-run the coefficient of the ect in energy equation is significant but not negative which does not imply a presence of causality. transport the results of non-causality hypothesis test indicate absence of granger causality between energy consumption in transport sector and gdp in either direction and in either run. this neutrality suggests that any public conservation policies in energy sector do not harm transport sector amelioration. on the other hand, any change in the performance of transport sector would not have an impact on energy consumption. residential the estimations of residential energy sector suggest that a feedback relationship exists in the short-run between household final consumption expenditures (proxy of income) and energy consumption, showing that household energy use level is positively influenced by the household income which is a fundamental hypothesis of demand modeling. this finding is also confirmed in long-run as the coefficient of ect in energy equation is negative and statistically significant. on other hand, an increase in energy consumption would affect household income in short-run. international journal of energy economics and policy, vol. 2, no. 2, 2012, pp.55-62 61 table 3. granger causality tests short-run causality long-run causality causality direction wald chi-sq statistics p-value 13 ; 23 t-statistics full economy ∆gdp → ∆ec 0.034 0.852 -0.059 -1.66*** ∆ec → ∆gdp 0.201 0.653 -0.100 -4.823* industry ∆iva → ∆iec 18.348 0.0011** 0.485 4.398* ∆iec → ∆iva 5.466 0.242 0.147 0.775 transport ∆gdp → ∆tec 1.840 0.174 0.01 1.950*** ∆tec → ∆gdp 0.228 0.632 0.033 4.971* residential ∆hfe → ∆rec 13.418 0.003* -0.127 -3.796* ∆rec → ∆hfe 15.525 0.0014** -0.003 -0.147 *, ** and *** denote significance level at 1%, 5% and 10% respectively. comparing our findings with results of earlier studies, we argue that at aggregate level, our results are in line with those of belloumi (2009) who found an existence of a feedback relationship between total energy consumption and economic growth in the case of tunisia. this bidirectional relationship was also found by ozturk and acaravci (2010) in the case of four eastern european countries (albania, bulgaria, hungary and romania) and belke et al., (2011) for the oecd countries. at disaggregated level, our findings are similar to those found by tsani (2010) who estimated a bidirectional causal relationship between energy consumption and economic growth in the case of residential sector and absence of causality in the case of transport sector. in the case of industrial sector, our estimation results which indicate a unidirectional relationship running from industrial value added to energy consumption are supported by costantini and martini (2010) when using data of oecd and non-oecd countries. 5. conclusion we examined the granger causality approach to investigate the relationship between energy consumption and economic growth in tunisia during 1980-2007 for the total economy as well as for the industry sector, transport sector, and residential sector. while a substantial body of literature has been related to the analysis of causality between energy consumption and growth at aggregated level (total economy), a little attention has been paid to the investigation of such a relationship at disaggregated level (by different sectors). the adoption of disaggregated analysis has the main advantage that it allows distinguishing between trends and patterns of different sectors towards energy consumption and therefore helping to implement appropriate policies. the results of estimations are mixed. at aggregate level, the estimated bidirectional causal relationship between energy consumption and growth in long-run suggests that energy could be considered as limiting factor to tunisian economic growth and economic growth stimulates further energy consumption. in contrast, an absence of causal relationship is found in the short-run. the disaggregated analysis gives different directions of causality for different sectors. results in the case of industry sector indicate a unidirectional causality running from industrial value added to energy consumption in the short-run but the neutrality hypothesis is found in the long-run. this implies that energy demand is strongly dependent from the economic performance of industry sector, while adopting some policies of energy conservation would not harm industrial production. this last conclusion remains valid in the case of transport in both short and long-run sector as energy consumption does not granger cause the performance of transport sector and vice versa. finally, estimation results suggest bidirectional causality between energy use in residential sector and energy consumption-economic growth nexus: does the level of aggregation matter? 62 household income in the short-run, but a unidirectional causality running from household income to energy consumption in the long-run. the increase in household income will be followed by improvement in living standards which leads to higher demand for energy. whereas, in long-run, no matter what measures are implemented in the residential sector the private household income will remain unaffected. in summary, the current study on the energy consumption-economic growth nexus proves the fundamental role of energy resources in increasing performance of total economy. however, at sectoral level, energy consumption seems to not be a limiting factor for industry, transport and residential sectors. references belke, a., dobnik, f., dreger, c. (2011), energy consumption and economic growth: new insights into the cointegration relationship. energy economics, 33, 782-789. belloumi, m. (2009), energy consumption and gdp in tunisia: cointegration and causality analysis. energy policy, 37, 2745-2753. binh, p.t. (2011), energy consumption and economic growth in vietnam: threshold cointegration and causality analysis. international journal of energy economics and policy, 1(1), 1-17. bowden, n., payne, j. e. (2009), the causal relationship between u.s. energy consumption and real output: a disaggregated analysis. journal of policy modeling, 31(2), 180-188. cheng-lang, y., lin, h.p., chang, c.h. (2011), linear and nonlinear causality between sectoral electricity consumption and economic growth: evidence from taiwan. energy policy, 38, 65706573. costantini, v., martini, c. (2010), the causality between energy consumption and economic growth: a multi sectoral analysis using non-stationary cointegrated panel data. energy economics, 32, 591-603. dickey, d., fuller, w. (1979), distribution of the estimators for autoregressive time series with a unit root. journal of the american statistical association, 74, 427-431. engle, r.f., granger, c.w.j. (1987), cointegration and error correction: representation, estimation and testing. econometrica, 55, 251–276. gross, c. (2012), explaining the (non-) causality between energy and economic growth in the u.s. --a multivariate sectoral analysis. energy economics. in press jobert, t. karanfil, f. (2007), sectoral energy consumption by source and economic growth in turkey. energy policy, 35, 5447-5456. johansen, s. (1988), statistical analysis of cointegration vectors. journal of economic dynamics and control, 12, 231-254. johansen, s., juselius, k. (1990), maximum likelihood estimation and inference on cointegration with applications to the demand for money. oxford bulletin of economics and statistics, 52, 169-209. mackinnon, j. g. (1996), numerical distribution functions for unit root and cointegration tests. journal of applied econometrics, 11, 601-618. mushtaq, k., abbas, f., abdul ghafour, a. (2007), energy use for economic growth: cointegration and causality analysis from the agriculture sector of pakistan. the pakistan development review, 46(4), 1065-1073. ozturk, i. (2010). a literature survey on energy-growth nexus. energy policy, 38(1), 340-349. ozturk, i., acaravci, a. (2010), the causal relationship between energy consumption and gdp in albania, bulgaria, hungary and romania: evidence from adrl bound testing approach. applied energy, 87, 1938-1943. phillips, p.c.b., perron, p. (1988), testing for unit root in time series regression. biometrica, 75, 335346. soytas, u., sari, r. (2003), energy consumption and gdp: causality relationship in g7 countries and emerging markets. energy economics, 25, 33-37. tsani, s.z. (2010), energy consumption and economic growth: a causality analysis for greece. energy economics, 32, 582-590. zachariadis, t. (2007), exploring the relationship between energy consumption and economic growth with bivariate models: new evidence from g-7 countries. energy economics, 29, 1233–1253. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 2 • 2022410 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(2), 410-425. do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break amjad ali1,2*, marc audi1,3, ismail senturk4, yannick roussel1 1european school of administration and management (esam), france, 2lahore school of accountancy and finance, university of lahore, pakistan, 3university paris 1 pantheon sorbonne, france, 4department of economics, tokat gaziosmanpasa university, turkey. *email: chanamjadali@yahoo.com received: 20 november 2021 accepted: 23 february 2022 doi: https://doi.org/10.32479/ijeep.12738 abstract this study has examined the impact of sectoral growth on co2 emissions in the case of pakistan from 1970 to 2019. adf and pp unit root tests have been applied to check the stationarity of the data series, whereas the zivot-andrew structural break unit root test has been applied to check the existence of structural break. the results of the unit root test show there is mixed order of integration among the selected variables, zivot-andrew unit root test also highlights the point of a structural break in the data series. the autoregressive distributed lag model has been applied for checking the cointegration among the variables of the model. the results show that industrial growth, population density, and time trend are positively and significantly contributing to co2 emissions in pakistan. whereas services sector growth is responsible for reducing co2 emissions in pakistan. the results show that agricultural growth and globalization are reducing co2 emissions but this relationship is insignificant over the selected time. in the short-run industrial growth, agricultural growth, and service sector growth are reducing the level of co2 emissions in pakistan. likewise, long run, trend time is promoting co2 emissions in the short run in pakistan. the government of pakistan can control co2 emissions by improvement in industrial production methods, reducing population density, and promoting services sector growth. there must be some dynamic policies are required to control the time trend impact on co2 emission in pakistan. keywords: co2 emissions, agriculture growth, industrial growth jel classifications: n5, o14, q01 1. introduction presently, climate changes and global warming have become a critical issue of discussion among policymakers, social scientists, and economists. the rising level of co2 emissions and other greenhouse gases are becoming the main inputs of global warming (rao and riahi, 2006; mongelli et al., 2006). the patterns of world energy production and consumption have become major causes of rising co2 emissions in general and global environmental degradation in specific (kaika and zervas, 2013; balsalobre-lorente et al., 2018). this change in the environment has significant impacts on human health, wildlife viability, and the smooth functioning of ecosystems. it is a known fact that economic growth is very necessary for the survival of a country and for attaining the desired level of economic growth, there must be sufficient agriculture and industrialization. either infant or improved industrialization, there is a specific amount of greenhouse gases are attached to it (nanda et al., 2016; stephenson et al., 2010). considering environmental quality as a basic necessity of human beings, united nations took serious steps to control the greenhouse gases by introducing binding agreements such as kyoto protocol (1997). the kyoto protocol forces developing and developed countries to produce a specific amount of greenhouse gases for their targeted level of economic growth. thus, there must be a reasonable trade-off between greenhouse gasses and economic growth (tan et al., 2014; malerba, 2020). this journal is licensed under a creative commons attribution 4.0 international license ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022 411 previously, millennium development goals (mdg’s) and recent sustainable development goals (sdg’s) of undp are trying to force countries to reduce those energy consumptions which are producing enough amount of co2-emissions and other greenhouse gases to meet their international commitments under the umbrella of the un. especially there is greater pressure on china to reduce its domestic co2 emissions (xiao et al., 2017). during the last two decades, there is a substantial increase in economic growth, energy consumption, and co2 emissions is witnessed in china (wang et al., 2016). the modern world is now divided into different blocks and globalization has the potential impact on the socio-economic well-being of the nations (gehring, 2013). in these blocks, developed countries favor higher economic growth with less environmental degradation, whereas developing countries prefer economic growth at any cost (suri and chapman, 1998; todaro, 2006). frankel and rose (2002) point out that co2 emissions and their analytical approach have a great deal of international political concern. it is very important to know that co2 emission is a global externality. the national regulations of developing nations do not favor reducing co2 emissions (annunziata et al., 2013; haggard, 1995; martínez-zarzoso and maruotti, 2011). three decades back, grossman and krueger (1991) have started the debate of environmental pollution and economic growth. soon after, investigating the effect of economic growth on environmental quality has become a policy debate all around the world (shafik and bandyopadhyay, 1992). economic growth may have a positive or negative relationship with environmental quality in various aspects (grossman and krueger, 1991; mcconnell, 1997). the issue of environmental conditions is still unsolved because those parties how to have different points of view about business, unemployment, and international market conditions (thomas and tow, 2002). a clean environment is a common benefit to all humans, so a large number of theoretical and empirical research has been conducted on this subject. grossman and krueger (1996) have tested the role of economic growth for environmental standards, latter it is known as the environmental kuznets curve. selden and song (1994) point out that in the beginning phases of economic growth a rise in economic growth is associated with rising environmental degradation but after a threshold level the rising economic growth discourages environmental degradation. many other researchers argue that growth may be helpful for better environmental conditions. if environmental conditions are normal, then an increase in income increases the demand for better environmental conditions. this process forces the governments to increase investment in reducing environmental degradation (warner et al., 2010). pakistan is one of the main important south asian countries, which is mainly recognized to be an agriculture country, but it has a vulnerable environmental zone with some negative effects of climate change concerned with public health (malik et al., 2012). climate change is considered to be a result of air pollution which is increasing day by day in this part of the world (ramanathan and feng, 2009). pakistan is facing many challenges i.e. including a higher rate of population growth, the inefficiency of water availability, soil-degradation, and animal-based diet with climate change (lal, 2013). according to german watch, pakistan has been ranked in the top ten of the countries most affected by climate change in the past 20 years. the reasons behind this include the impact of back-to-back floods since 2010, the worst drought episode (1998-2002) as well as more recent droughts in tharparkar and cholistan, the intense heatwave in karachi (in southern pakistan generally) in july 2015, severe windstorms in islamabad in june 2016, increased cyclonic activity and increased incidences of landslides and glacial lake outburst floods (glofs) in the northern parts of the country. in line with the commitment to the paris agreement under article 6 facility, pakistan intends to establish a robust and cohesive carbon market. the carbon market can generate fiscal resources and green jobs to support sustainable recovery from economic regression in the medium term. ministry of climate change with the support of the world bank conducted blue carbon rapid assessment for pakistan to figure 1 out how and where to act to protect and bolster blue carbon opportunities. accordingly, pakistan envisions gaining value from blue carbon in a plethora of ways that can be beneficial for the climate and the ocean. the assessment concluded that in total, mangrove forests and mapped tidal marshes store approximately 21 million tonnes of organic carbon (corg)or 76.4 million tonnes co2e. it is estimated that the sindh government’s indus delta mangroves redd+ project, which is being conducted on 350,000 ha, will remove 25 million co2e by 2030 and 150 million by 2075. 2. literature review many theoretical and empirical studies examine the relationship between co2 emissions and economic growth. here some important has been selected as a review of the literature. empirical and theoretical literature approve that co2 emissions are considered one of the main causes of global warming (cherubini et al., 2011; beckerman, 1992; panayotou, 1993; holtz-eakin and selden, 1995; stern et al., 1996; carson et al., 1997; moomaw and unruh, 1997; mcconnell, 1997; agras and chapman, 1999; magnani, 2001; dijkgraaf and vollebergh, 2005; vollebergh and kemfert, 2005; richmond and kaufmann, 2006; ang, 2007; apergis and payne, 2009; tiwari et al., 2013). the debate over economic growth and negative environmental effects was first started by grossman and krueger (1995). further, brock and taylor (2010) mention that the relationship between environmental degradation and economic growth depends on three factors i.e., production technology, production composition, and production volume. since every country is trying to achieve higher economic growth, thus there is a chance of higher environmental degradation. this inverse relationship becomes more prominent when the economy largely depends on the agricultural sector and the industrial sector is in infant conditions. lee and roland-holst (1994) conduct a comparative analysis of dirty industries and environmental risk in the case of developing countries. the empirical results show that a uni-directional relationship has existed from trade liberalization to environmental degradation. the tradeoff between the environment and industrialization shows the comparative cost of pollution. the results highlight the uniform effluent tax that is the important cost effecting tool to control so2 (sulphur dioxide) emissions. the basic instrument like uniform tax resulting from a decrease ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022412 in real gdp that is greater than the achieving target significantly using a uniform effluent tax. grossman and krueger (1995) demonstrate the relationship between economic growth and the environment. this study has tested the reduced-form relationship between income per capita and environmental emissions for 1989 to 1990. the main contribution of the present paper is that it employs reliable data and a common methodology to investigate the relationship between the scale of economic activity and environmental quality for a broad set of environmental indicators. finally, it should be reflected the technological, political, and economic conditions that existed at the time. the low-income countries of today have a unique opportunity to learn from this history and thereby avoid some of the mistakes of earlier growth experiences. with the increased awareness of environmental hazards and the development in recent years of new technologies that are cleaner than ever before, the low-income countries turn their attention to the preservation of the environment at earlier stages of development than has previously been the case. copeland and taylor (1997) examine the effect of trade liberalization on the environment. this study analyzes that if the capital-abundant country trade with the labor-abundant country then free trade reduces the pollution of the world. trade displaces the production of pollution-intensive industries to the capitalabundant country dislike its strict pollution rules. the study shows that the pollution level grows in the north and falls in the south. the result shows the reversing trend if the north-south gap in income is too larger for, then in this regard, the structure of trade is determined by the income-induced policy changes across different countries. it reveals that world pollution is dependent on the structure of the trade. the study examines that pollution is derived by the demand and supply analyses. the supply of the pollution is derived by the policy of the government and the pollution demand is derived by the behavior of the producers and consumers. the results of the study reveal that free trade and capital mobility must lead to unchanged world pollution from its autarky point. van west and dean (2000) elaborate the environmental standard that leads to having a comparative advantage in developing countries. according to this study, there are some chances that trade will harm the environmental conditions in developing countries. this research collects the existing literature on trade openness and economic growth and the environmental kuznets curve (ekc). a simultaneous equation system is derived to determine the effects of the liberalization of trade on environmental status. pooled data on water pollution in china is used for the estimation. it also suggests that free trade will cover the environmental degradation through better terms of trade. the negotiation of nafta and uruguay round shows the effects of the liberalization of trade on the environmental status on the part of both the developed and developing countries. in this study, another approach is developed by using a simple heckscher ohlin model that shows the endogenous concept of a clean environment. the simulations of this research indicate that per-unit emissions will lead to an increase in all of the provinces. the exchange regime deals with the beneficial effects of the liberalization of trade which may be very important during the period 1992-1995 kaneko and managi (2003) investigates the empirical question about free trade whether it is harmful or beneficial for the environment. for this study panel data is used for 63 developing countries and developed countries from the period of 1960-1999. the empirics reveal that the liberalization of trade will increase the emissions that have the elasticity of 0.579. this study shows the whole effects of the liberalization of trade on the environmental condition. it is found that trade has not the beneficial effects on environmental status. the recent research of cole and elliott (2003) examines that the estimates are positive but do not examine the overall impacts. in contrary to the small observations of cole and elliott (2003) which is used the data of 32 countries, this study that is about 63 countries contributes to the previous literature at two-folds. this is the first research that estimates the whole effects of the liberalization of trade. second, a beneficial simultaneous model is proved. figure 1: relative stock of blue carbon source: government of pakistan, 2021: economic survey of pakistan ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022 413 mcausland (2005) focuses on consumer-generated-tailpipepollution against the vast research of economics on the environmental quality in open economies. it highlights producergenerated-smokestack pollution. this study also examines political opposition to environmental regulations differs from trade regime and indicates the impacts of the movement from the absence of trade to free trade on environmental policy from this study we find that trade openness increases the opposition of industry to smokestack policy and decrease its opposition to the policy of tailpipe. this study focuses on trade and environmental relationships that may depend critically on pollution. it indicates that production-related pollution should re-evaluate before the assumption for the pollution concerned with consumption. the main concern of this paper is to highlight the relation between trade-openness and the environment-politics underlying the assumption that the traditional relation can be rearward. the empirical results indicate that the relationship among trade structure, politics, and environmental regulations can be different in qualitative measures. junyi (2006) tries to empirically estimate the relation of ekc and income per capita in the chinese provinces. the study employs the data for 1993-2002. this research uses the simultaneous equation model (sem) to empirically examine the relationship between per capita pollutant emissions and income per capita. 2sls method is used to estimate the sem in this study. the study uses the hausman test methodology for examining the homogeneity of income in the model. the findings of the hausman test reveal that there is simultaneity between pollution emissions and income per capita. the empirics of the study reveal that there is u shape relation between pollution and income, but in the case of poor areas, they need more wealth for better environmental conditions. rothman (1998) examines the relation of economic development and environmental-degradation in the case of some selected developed countries. the study uses the data of different times. the study concludes that the inverted u shape relation exists between economic-growth environmental-degradation. kaygusuz (2007) examines that the energy demand is growing rapidly in turkey. energy consumption has been increasing at the rate of 4.3 percent on average since 1990 in turkey. it is expected that the fast increase in the production and consumption of energy has taken with a broad range of environment-related problems at different levels. the study analyzes that carbon emissions (co2) in turkey have raised with the energy-consumption concerned with the global environmental issues. in 2004, co2 emissions increased by 193 mt. states have performed a very important role in giving protection to the environment by decreasing the emissions of greenhouse gasses (ghgs). on a global scale, state emission is proved to be significant. co2 emissions and carbon-monoxide (co) are the major greenhouse gases (ghgs) linked with global warming. at the current level, coal is the main reason for producing co2 emissions with fossil fuels. sulfur dioxide (so2) and nox have a major contribution to acid pelting. the study concludes that carbon assessment has a major contribution to controlling co2 emissions while raising revenue. bartoletto and rubio (2008) examine the empirical analysis of energy consumption, the passage from organic to fossil energy carriers, and its impact on co2 emissions in italy and spain. the study uses the data from the period of 1861-2000. this paper also employs new data for analyzing the use of energy from organic roots to the modern roots of energy. the existing studies have revealed that the traditional structure of energy transforms the views about the relation between the energy inputs and the economy. but the recent study of this paper concludes that in the long run, the traditional energy roots must be in the series of pollution intensities of energy consumption, pollution-intensities in the economy, de-carbonization, and other factors to gain a clear picture of the process include. the study also shows the trend of co2 emissions, which changes significantly with the involved traditional energy carries. it indicates that de-carbonization is not a long-run phenomenon, it prevails since the 1970s in the economy. the study analyses that modification in the placement of energy baskets has an important impact on co2 emissions in the economy. because the various energy baskets are the main reasons to emit the co2 in different degrees. akbostancı et al. (2009) empirically examine the relationship between income per capita and the environmental status of turkey in two scenarios. first, the relation between co2 emissions and income per capita is studied through the time series data with the help of the co-integration technique and the data is used from the period 1968-2003. second, the relation between air pollution and income is examined through pm10 and so2 measurement in turkey. panel data is used in this paper. the data is used from the period of 1992-2001 including 58 provinces of turkey. panel data analyze the n-shaped relationship for so2 and pm10 emissions that have no support for the inverted u shape kuznets curve which is showing the relationship between environmental degradation and income. the long-run relation is existed between income and pollution and finds that these variables are co-integrated. the result shows that the per capita income is less than 2000 in some provinces of turkey, it also reveals that air pollution increases with the increase in income. the results also show that in those provinces that have income per capita between (2000-6000), air pollution decreases with per capita income. in the provinces with an income of more than 6000, air pollution tends to increase once again. the empirical findings show that the environmental kuznets curve (ekc) is significant in some provinces during the specific period. this study concludes that the basic need is to control the pollution that will not disappear automatically, no matter what their income level will be. poumanyvong and kaneko (2010) investigate that in recent years, there have been extensive studies on the relations betwixt energy-consumption, urbanization, and co2 emissions. but there has been little attention towards the distinction in different phases of development or different levels of income. the previous existing literature has assumed that the effect of urbanization is homogeneous for all of the countries. different questions arise in this assumption that there are many distinctions across countries of various levels of comfort. this study empirically examines the impact of urbanization on energy consumption and co2 emissions at the different phases of development by using the stochastic impacts of the regression on the population. the affluence and technology model (stirpat) is employed by employing the ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022414 panel data of 99 countries from 1975 to 2005. the empirical findings of the study recommend that the effect of urbanization on energy use and co2 emissions differs at the development phases. the results of the study reveal that urbanization reduces energy consumption in low-income countries and grows energy consumption in middleand high-income countries. the effect of urbanization on co2 emissions is positive for all the groups of income, but it is strongly marked in the middle-income group than in the other groups of income. these new empirics assist to make advancements in the existing literature, and it can be proved as a special involvement to policymakers. nasir and rehman (2011) analyze the relationship between carbon emissions (co2), energy consumption, income, and foreign trade in pakistan. the study uses the data from the period of 1972 to 2008. johansen’s method of co-integration is applied in this study paper. the empirics reveal that there is a quadratic long-run relation between co2 emissions and income, which confirms the immanence of the inverted u shape hypothesis of environmental-kuznets-curve (ekc) in the case of pakistan. furthermore, foreign trade and energy consumption shows positive impacts on co2 emissions. however, the short-run findings show the immanence of the ekc hypothesis which is unique in the situation that none of the long-run determinants is significant. the empirical findings reveal a different story in the existing literature. the contradiction of the empirics of the short-run and the long-run provide opportunities to the policymakers to make various types of growth policies. the results of the causality test show that the uni-directional relation exists between growth and energy consumption. the study of this paper proposes that the policymakers must not rely on the future energy demand with various growth issues. the policymakers should focus on gaining energy at less cost. moreover, the empirics highlight that there is no causal relation exists betwixt the co2 emissions and growth, which suggests that pakistan can reduce the co2 emissions without disrupting the economic growth. jobert et al. (2012) focus on economic growth, energy consumption, and carbon-dioxide emissions. the study is employing the iterative aspect of the bayesian shrinkage method. the environmental-kuznets-curve (ekc) hypothesis is checked by using this procedure for the first time in this study. the obtained empirics suggest that: first, the environmental-kuznets-curve hypothesis is rejected for 49 countries out of 51 countries, considering when heterogeneity in the economies is present, energy-efficiencies across countries and differences in the co2 emissions are accounted; second, is that categorization of the empirical results in the countries, the growth levels reveal that an inverted u shape curve is because of the matter of fact that the growth in the gdp in the developed or higher-income countries reduces emissions, while, in the developing or lower-income countries it raises emissions. the ekc hypothesis is applied to check the dependency of environmental degradation on the level of economic development. jobert et al. (2010) examine that during the betterment of the economic structure, these economies decreased their share of the industrial sector in gdp, and hence, they might be qualified as “ecologists despite themselves”. shahbaz et al. (2013) empirically estimate the relationships among globalization, economic growth, energy intensity, and co2 emissions. the study implies the data from the period of 19702010 for turkey. co-integration and unit root tests are used in this paper. vecm granger-causality method is applied to check the causal relationship among these variables. the empirical estimates indicate that the use of globalization and energy intensity lead to a growth in the co2-emissions. it also proves the presence of the (ekc) hypothesis in the economy. the findings of the causality test show that the two-way causal relationship exists between co2 emissions and economic growth. ardl boundstesting method of co-integration is applied to check the long-run relations among co2 emission, globalization, economic growth, and energy intensity. empirics of this research confirms the existence of co-integration among these variables in the presence of structural break. the findings of this paper reveal that the energy intensity increases the co2 emissions and globalization reduces the co2 emissions. this study suggests further research of all the renewable and nonrenewable energy resources of energy that can be integrated with neo-classical production. baek and ali (2016) examine the effect of secondary school education, financial development, energy consumption, economic development, and population density on environmental degradation in the case study of lebanon. this study uses the data for 1974-2014. the augmented dickey-fuller (adf) unit-root method is used to analyze the stationarity among these selected variables of the model. ardl bounds testing method is applied to empirically examine the co-integration among the selected variables. the findings analyze that population density, energy consumption, and financial development have positive and significant relation with environmental-degradation in the case of lebanon. the findings also reveal that economic development has positive and insignificant relation with environmental degradation. the empirics also indicate that there is a negative and significant relation between secondary school education and environmental degradation in lebanon. the government of lebanon should increase the efficient methods of energy consumption to reduce environmental degradation, it also increases the educational level to improve the environmental quality in the case of lebanon. dogan and seker (2016) explore the link among real income, nonrenewable and renewable consumption of energy, and openness of trade on pollutant emission. the environmental kuznets curve model has been tested for some selected european nations from 1980 to 2012, advanced panel methods have been applied for empirical analysis. the outcomes of the analysis reveal that liberalization of trade and energy production by renewable resources diminish emissions of carbon in the environment, whereas non-renewable energy has a vice-versa impact. the findings of this study show a bidirectional causal relationship between pollutant emission and consumption of renewable and unidirectional causal relationship from real income to pollutant emission, from pollutant emission to nonrenewable energy, and from liberalization trade to pollutant emission. irfan and shaw (2017) analyze the relationship between environmental pollution and energy consumption in south asian ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022 415 countries. the study uses a panel dataset for three countries (india, pakistan, and bangladesh) from 1978 to 2011. the relationship is explored by employing a nonparametric additive model with country and time-specific fixed effects. the data for the analysis are collected by the world bank. the result of the study shows that the relationship between carbon dioxide emissions and energy consumption is nonlinear in nature and energy consumption has a positive impact on carbon dioxide emissions in the panel of countries. the study also expresses that the level of urbanization is inverted u-shaped relationship with carbon dioxide emissions. shahzad et al. (2017) study the cointegrating relationship between carbon emissions, energy consumption, trade openness, and financial development in pakistan. the study uses environmental degradation as a dependent variable and energy consumption, trade openness, and financial development as independent variables. the study has been used the ardl bounds test for the cointegration procedure. in this study annual time series data is used for the period 1971 to 2011. the data is collected from the world bank. results, the long-run results show that a one percent increase in trade openness and financial development will increase carbon emission by 0.247% and 0.165%, separately. the short-run elasticities are 0.122% and 0.087% for trade openness and financial development, individually. the granger causality results show a unidirectional causality from energy consumption, trade openness, and financial development to carbon emission; and a bi-directional causality between energy consumption and financial development. bakirtas and akpolat (2018) explore the relationship between energy consumption, economic growth, and urbanization in the case of new emerging market countries. the study has been used the dumitrescu-hurlin panel granger causality test from 1971 to 2014 in new emerging-market countries. the data is collected from the world bank. in the trivariate analysis, there is panel granger causality from energy consumption and urbanization to economic growth, from economic growth and urbanization to energy consumption, and from energy consumption and economic growth to urbanization. the result shows a negative and significant relationship. haseeb et al. (2018) explore the dynamics of environmental degradation: the world evidence. the study investigates the linkages among corruption, democracy, tourism, and co2 emissions for selected disaggregates. the study uses aggregate panel data over the period 1995-2015. the data is collected from the world bank. the fmols results indicate that corruption and tourism at disaggregate and aggregate levels are substantial contributors to co2 emissions. these empirical results also reveal that corruption and tourism in low-income countries have a higher impact on co2 emissions compared to high-income countries. besides, democracy in all panels except low-income countries has helped to reduce co2 emissions. some results are found to be illogical. adams and nsiah (2019) analyze the relationship between renewable energy and carbon emission. the study uses carbon emission as a dependent variable and economic growth or urbanization as an independent variable. the study has been used the panel cointegration technique for 28 sub-sahara african countries spanning the period of 1980 to 2014. the data is collected from the world bank. the result shows that the percentage of nonrenewable energy consumption leads to an increase of 1.07% and 1.9% to the carbon emission for the short and long run respectively. the results also show that less democratic states are more likely to pollute the environment than more democratic states. further, there is no statistically significant effect of nonrenewable energy in the short run for more democratic nations. zandi and haseeb (2019) explore the impact of democracy and environmental degradation evidence of asian countries. the study examines the relationship between corruption, democracy, military expenditure, and environmental degradation in a panel of six asian countries. the data were collected from 1995 to 2017. the data is collected from the world bank. the study uses fully modified ordinary least square (fmols) and dynamic ordinary least square (dols) to examine the results. the result shows a significant impact among the variables. military and corruption show positive impact and democracy shows negative impact. the results suggest that asean countries need environmental performance and good governance systems that are also free from corruption when they are cooperating. the results further confirm that as corruption and military spending increase, carbon dioxide emissions will be emitted in these asian countries. koengkan et al. (2020) examine the indicators of environmental degradation. the study uses co2 emissions as a dependent variable and renewable, non-renewable energy consumption, economic growth, and urbanization as independent variables. the study has been used a panel vector autoregressive model. the study collects the data from southern common market, over thirtyfive years 1980 to 2014. the data is collected from the world bank. the experimental analysis pointed to the presence of bidirectional causality between the consumption of fossil fuels, economic growth, consumption of renewable energy, and carbon dioxide emissions; and a unidirectional relationship between the consumption of renewable energy and urbanization. this research also thought that the countries from southern common market are dependent on fossil fuels consumption and that the urbanization process is highly linked with the consumption of this type of energy. the results of preliminary tests pointed to the presence of cross-sectional dependence and unit roots in the variables included in this investigation, as well as a low degree of multicollinearity between them. the preliminary tests also pointed to the presence of fixed effects in the model and to the need to use one lag length in the pvar estimation. ozcan et al. (2020) explore the determinants of environmental degradation in oecd countries. the study uses environmental degradation as a dependent variable while energy consumption, economic growth as independent variables. the study uses a sample of 35 oecd countries from 2000 to 2014. the data for the analysis were collected from the world bank. the study analyzes the dynamic causal relationships between energy consumption, economic growth, and co2 emissions and two environmental indices (ef and epi). the result shows a significant positive effect of gdp and energy consumption on all environmental quality ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022416 indicators (ef, co2 emissions, and epi). overall, the results of the study reveal the adjustment of the oecd economies to a compromising relationship between the environment and their economic development paths. oecd countries have started to harmonize their economic growth and energy consumption patterns with their environmental policies. ali et al. (2021) analysis the impact of renewable energy consumption and natural resource depletion on environmental degradation in the case of developed and developing countries from 1990 to 2014. an insignificant relation has been found between natural resource depletion and environmental degradation in the case of complete sample analysis and developing country analysis, but vice-versa in developed countries. fossil fuel energy consumption has a positive and significant impact on environmental degradation in developing countries. renewable energy consumption harms environmental degradation in the case of complete sample analysis and developed country analysis, but visa-versa in developing countries. economic growth positively and significantly affects environmental degradation in all three cases, this means for higher economic growth we have to bear some environmental degradation. but it is the need of the hour that we should find some threshold between economic growth and pollutant emissions so that a healthy environment can be safe for coming generations. so, for a healthy environment, fossil fuel consumption should be reduced and consumption of renewable energy with merchandised trade and urbanization can be encouraged. sawyer (2021) demonstrates that strategies of environmental degradation. the study discusses the nature of the present era of financialization, outlining the changes in the financial sector and its relations with the real sector which are particularly relevant for the climate emergency. the nature of the study is a primary study. the processes of financialization have involved the growth of the financial sector and its institutions, which from several perspectives have become too large (individually and collectively). the climate emergency, environmental damage, and loss of biodiversity will require, inter alia, a major re-structure of economic activity and much lower rates of its growth. the study is focused on short-term shareholder value maximization that runs into conflict with a longer-term perspective of research and development and investment directed towards sustainability. funding arrangements are also required which are capable of supporting activities and promoting de-commodification of the environment. 3. the model environmental changes have become one of the main confronting issues among policymakers throughout the world. different researchers e.g. beckerman (1992), panayotou (1993), holtz-eakin and selden (1995), stern et al. (1996), carson et al. (1997), moomaw and unruh (1997), mcconnell (1997), agras and chapman (1999), magnani (2001), dijkgraaf and vollebergh and kemfert (2005), vollebergh and kemfert (2005), richmond and kaufmann (2006), ang (2007), apergis and payne (2009), tiwari et al. (2013), kanjilal and ghosh (2013), baek and kim (2013), solarin and ozturk (2015), ali and rehman (2015), liu et al. (2015), ali (2015), dogan et al. (2015), ali and baek (2016), baek and ali (2017), zhang et al. (2017), pal and mitra (2017), audi and ali (2018), audi et al. (2020), and ali et al. (2021) have presented different determinants of greenhouse gasess. following the methodologies of ali and audi (2016), audi and ali (2017), zhang et al. (2017), pal and mitra (2017), audi and ali (2018), audi et al. (2020), and ali et al. (2021), the model of this study become as: co2t=f(indt, agrt, sert pdt, globt) (1) where, co2 = co2 emissions ind = industrial sector growth agr = agriculture sector growth ser = services sector growth pd = population density glob = globalization kof index t = time period (1970-2019) the main objective of this study is to explore the effect of industrial growth, agricultural growth, services sector growth, population density, and globalization in the case of pakistan from 1970 to 2019. data for these selected indicators has been obtained from the world development indicators (wdi) databases maintained by the world bank and various issues of the pakistan economic survey. 4. econometric methodology in time series studies, the time trends make the estimated results biased (nelson and plosser, 1982; brooks and harris 2014). the existence of time trend makes the time series data non-stationarity, there are number of procedures available which check the unit root issue in the data. for checking stationarity of our time series data, the present study uses augmented dickey -fuller (adf) (1981) and philips perrron (1988). 4.1. augmented dickey-fuller (adf) the functional form of adf becomes as: 1 1 1 q t t j t j t j x x x e − − = δ = + δ +∑ (2) 1 2 1 q t t j t j t j x x x e  − − = δ = + + δ +∑ (3) ∆ ∆x t x x et t j t j t j q = + + + +− − = ∑α β δ φ1 3 1 (4) here xt; variable having time series data is used for checking unit roots issue, t ; explains the existence of time trend in the series and et; white noise error term. the simple df can be useful if j = 0. while testing the unit root issue in the series adf test can include, until white noise error can be achieved. the simple lm test can be used for analyzing error terms serial correlation. now we can develop, the null and alternative hypotheses of adf unit root; ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022 417 0 0:h  = non-stationary time series; and series have unit root issue 0:ah  < stationary time series 4.2. phillips and perron (pp) unit root test phillips and perron (1988) present unit root and pp test is viewed as df test that made robust to serial correlation with the help of newey and west (1987) heteroskedasticity and autocorrelation consistent covariance matrix estimator. the null hypothesis of pp and adf have the same normalized bias statistics and asymptotic distributions. pp has two main advantages over adf. the first pp test has strong power to predict the heteroskedasticity and serial correlation in the error term. second, the user does not need to specify the lag length of the test regression. the pp test has the following procedure: 1i i iy y  −= + + (5) where we include the time trend and exclude the constant term. in this way zp and zτ are two statistics calculated as: ( ) ( ) 2 2 2 0,2 ˆ1 ˆˆ ˆ1 2n nn n z n s    = − − − (6) ( )0, 2 0,2 ˆ ˆ ˆ1 1 1ˆ ˆ ˆ ˆˆ 2 n n n nn n z s        − = − − (7) 1 1ˆ ˆ ˆ n i i j i jn    − = + = ∑ (8) 2 0, j, 1 ˆ ˆ ˆ2 1 1 q n n n j j q    =   = + −  + ∑ (9) 2 2 1 1 ˆ n n i i s n k  = = − ∑ (10) where τi error term of ols, k represents the number of covariates, q represents the number of lags, 2ˆn and ̂ is the standard error of ̂ . in eq. (9) when j = 0 this represents the variance of the error terms and when j > 0 this represents covariance lies between two error terms. in eq. (10) when covariances are zero or –ve the auto correlation between the residuals i,ˆ n is zero j > 0. then the second term of the eq. (10) disappears and 2 0, ˆ ˆ n n = they can be replaced with each other. if 2 0,ˆ ˆ 0n n − = the in the second term of the eq. (8) disappear. 0, 2 ˆ ˆ 1 ˆ ˆ n nz    − = and 0, 2 ˆ 1ˆ n  = then its reduce form is as ˆ 1 ˆ nz   − = (11) hence there is no autocorrelation or unit root problem between the error terms. in this way by applying this procedure to all variables, we can easily find their respective orders of integration of all variables. 4.3. zivot and andrew structural breaks unit root test the problem with pp and adf is that these tests don’t highlight the existence or non-existence of structural breaks in the data. zivot and andrews (2002) propose a unit root test to solve this issue. 1 1 k t t j t j t j y c y t du d y   − − = δ = + + + + δ +∑ (12) 1 1 k t t j t j t j y c y t dt d y   − − = δ = + + + + δ +∑ (13) 1 1 k t t t j t j t j y c y t dt du d y    − − = δ = + + + + + δ +∑ (14) where dut is an indicator dummy variable for a mean shift occurring at each possible break-date (tb) while dtt is the corresponding trend shift variable. formally, 1 0 { if t tb t otherwisedu −−−−−− > −−−−−−−= and 0 { t tb if t tb t otherwisedt − −−−−−− > −−−−−−−= α=0 is the null hypothesis for the above three equations, this reveals the series contains a unit root with a drift that excludes any structural break, while the alternative hypothesis α<0 implies that the series is a trend-stationary process with a one-time break occurring at an unknown point in time. the zivot and andrews test consider every point as a potential break-date (tb) and runs a regression for every possible break-date sequentially. 4.4. autoregressive distributive lag model to co-integration pesaran (1997), pesaran and shin (1998), pesaran et al. (1999) have developed a cointegration model which is known as the autoregressive distributive lag model (ardl). ardl procedure can be applied as follows: ∆ = + + + + +− − −1 1 2 3 1 4 1 5 1n lny lnx lnz ....y tt t t tβ β β β β 1 0 0 lny lnx lnz ....− − − = = = + δ + δ + δ + +∑ ∑ ∑   p p p h t h j t j k t k it h j k u (15) here the dependent variable is ln yt; time is presented with t; the lag of the dependent variable can be presented with ln yt−1; first independent variable is presented by ln xt; the second independent variable is presented by ln zt and so on. the rate of change can be measured with the help of δ. first, we will examine the relationship direction for the variables in the case of pakistan with the help of the f test. f-statistic decide the order of integration for the variables, here we can use either time trend or intercept for the analysis procedure. f-statistic is used for the comparison of tabulated values of pesaran (1997) or pesaran et al. (2001) which ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022418 was further revised by narayan (2005). in case the calculated f-test statistic is higher than the upper bound value, we can reject the null hypothesis and conclude that there is cointegration among the variables of the model and vice-versa for the other case. the procedure to write null and alternative hypothesis of the ardl bound test is as follow: 0 3 4 5: 0h   = = = (no co-integration among the variables) 3 4 5: 0ah   ≠ ≠ ≠ (co-integration among variables) vector error correction model is used for examining the short-run relationship among the variables. its procedure can be explained as: 1 2 1 1 0 0 lny lny lnx lnz p it h it h h p p j t j k it k t t j k t ect u       − = − − − = = δ = + + δ + δ + δ + + ∑ ∑ ∑ (16) lagged error correction can be presented by ectt−1; all the other variables that have been explained in the earlier equation. the results of the error correction term explain the speed of adjustment from short tun towards the long run. 5. results and discussions the descriptive statistics provide us with the intertemporal properties of the selected data series. the results of descriptive statistics have been given in table 1. the estimated results present mean, median, maximum, minimum, std. dev. skewness and kurtosis values of the data series. based on estimated results, it is found that all series have theoretically correct intertemporal properties. the results of jarquebera show that all the selected variables have normally distributed data series, which are also necessary for the white noise error term in any type of regression analysis. the results of the correlation have been given in table 2. the results explain that co2 emissions have a significant correlation with most of the selected variables. moreover, selected explanatory variables i.e. industrial growth, agricultural growth, services sector growth, population density, and globalization have not very high correlation to create the issue of multicollinearity among the select explanatory variables. thus, our model meets one of the necessary conditions of variable selection for regression analysis. for checking the unit root issue of the selected data series, we have applied adf and pp unit root tests. the estimated results have been given in table 3, the results show that co2 emission, population density, and globalization are not stationary at level, whereas industrial growth, agricultural growth, and services growth are stationary at level. the results show that co2 emission, population density, and globalization are stationary at first difference. in the presence of time trend, some of the selected variables are stationary at the level and some are stationary at first difference. both adf and pp outcomes show that there is mixed order of integration among selected variables without and with a time trend. these results recommend applying the autoregressive distributed lag model for examining the long-run and short coefficients of the selected model. one of the big problems with adf and pp i.e. these tests do not give the presence of a structural break in the data series, as most of the time-series data have structural break issues. dejong et al. (1992) and baum (2004) mention that in the presence of structural break, the estimated results are biased and inconsistent. the appropriate information about the structural break enables the policymakers to design comprehensive socioeconomic policies to achieve policy targets. to test the structural break in the data table 1: descriptive statistics co2 ind agr ser pd glob mean 11.10258 5.646511 3.272988 5.551787 2.683832 42.84000 median 11.22504 5.157286 3.175550 5.171768 2.759534 42.50000 maximum 12.24707 17.37416 11.72315 10.50643 3.363952 55.00000 minimum 9.848453 −5.206873 −5.286028 1.331493 2.022967 30.00000 std. dev. 0.726804 4.002646 3.416279 2.193636 0.423963 8.821032 skewness −0.255242 0.130784 −0.003140 0.351581 −0.062231 0.129161 kurtosis 1.748384 4.351646 3.842325 2.759039 1.727408 1.440866 jarque-bera 3.806535 3.948677 1.478230 1.151040 3.406211 5.203396 probability 0.149081 0.138853 0.477536 0.562412 0.182117 0.074148 sum 555.1289 282.3256 163.6494 277.5894 134.1916 2142.000 sum sq. dev. 25.88395 785.0375 571.8770 235.7899 8.807502 3812.720s observations 50 50 50 50 50 50 table 2: correlation matrix variables co2 ind agr ser pd glob co2 1.000000 ind −0.354910** 1.000000 agr −0.081314 0.218704 1.000000 ser −0.349507** 0.492734*** 0.074164 1.000000 pd −0.791372*** 0.335543** 0.197556 0.287791** 1.000000 glob 0.950828*** −0.370807*** −0.128446 −0.298745** −0.884573*** 1.000000 ***,**,* present significance level 1%, 5% and 10% respectively ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022 419 series we have applied zivot-andrew structural break unit root test. the estimated results of the zivot-andrew unit root test have been given in table 4. the results show that co2 emissions, population density, and globalization are not stationary levels without time trends in presence of structural break 1997, 1987, and globalization respectively. the results show that industrial growth, agricultural growth, and services growth are stationary at without time trend in presence of structural break 2008, 2000, and 1988 respectively. at first difference without time trend, all the selected variables of the model are stationary with different structural breaks. in presence of time trends at level co2 emissions, industrial growth, agricultural growth, and population density are stationary with structural breaks 1995, 2008, 1993, and 1997 respectively. whereas, services growth with structural break 1986 and globalization with structural break 2004 are non-stationary at the level in the presence of a time trend. all the selected variables are stationary at first difference with different structural breaks. this shows that there is mixed order of integration in the presence of structural breaks with is a very suitable condition to apply the autoregressive distributed lag model. table 5 gives us information about the lag order selection criterions. normally, hannan-quinn information criterion, akaike information criterion, final prediction error, sequential modified lr test-statistic, and schwarz criterions are used optimal selection. for the selection of lag order, the searcher should keep in mind the number of variables and number of observations (i.e. degree of freedom). the findings indicate that most of the criterions refer to the optimal-lag length as 4. hence, following the hannanquinn information criterion, akaike information criterion, final prediction error, sequential modified lr test-statistic, and schwarz criterion maximum 4 lag length is employed in this study. table 6 provides the empirical findings of ardl co-integration among co2 emissions, industrial growth, agricultural growth, services growth, population density, and globalization. f-statistic has been used to test the null hypothesis of no cointegration against the alterative hypothesis. the calculated f-statistics (7.522391) is greater as compared to the upper bound at 1 percent given by pesaran et al. (2001). so, the null hypothesis of no cointegration has been rejected. this confirms that co2 emissions, agricultural growth, services growth, population density, and globalization have cointegrated in the case of pakistan over the selected period. the long-run results of the study have been given in table 7. the results show that there is a positive and significant relationship table 3: unit root analysis augmented dickey-fuller test variables at level without trend at first difference without trend at level trend at first difference with trend co2 0.250779 −5.131523*** −2.023921 −5.089897*** ind −6.104426*** −6.571368*** agr −9.722486*** −9.667097*** ser −4.731066*** −5.008044*** pd −0.523089 −4.832824*** −3.275790* −5.789907*** glob −0.849685 −4.794825*** −1.329221 −6.338258*** phillips-perron test co2 0.114136 −5.098812*** −2.352458 −5.071919*** ind −6.138791*** −6.567494*** agr −9.671595*** −9.716695*** ser −4.677230*** −4.715144*** pd −0.188693 −2.050421** −2.494701 −2.050421*** glob −0.733070 −6.366606*** −1.329221 −6.333982*** ***,**,* present significance level 1%, 5% and 10% respectively. table 4: zivot-andrews structural break unit root test variables at level without trend at first difference without trend at level trend at first difference with trend t-statistic time break t-statistic time break t-statistic time break t-statistic time break co2 1.273008 1997 −5.173376*** 2008 −5.684998** 1995 −6.053869*** 1987 ind −7.113871** 2008 −9.308260*** 2005 −6.994745** 2008 −9.265465*** 2005 agr −4.061953* 2000 −5.281451*** 1993 −7.071922** 1993 −5.458055*** 1992 ser −5.343588** 1988 −8.036633*** 2006 −5.357183 1986 −8.096322** 2009 pd −1.791295 1987 −5.338886*** 1987 −6.045833** 1997 −7.237669*** 1980 glob 1.221071 2008 −6.946416 2008 −2.311140 2004 −6.935191** 2004 ***,**,* present significance level 1%, 5% and 10% respectively. table 5: var lag order selection criteria lag logl lr fpe aic sc hq 1 −211.2266 na 0.001894 10.74898 12.18010* 11.28509 2 −148.9735 92.02637 0.000645 9.607544 12.46977 10.67975 3 −84.81954 78.10049* 0.000230 8.383458 12.67679 9.991766 4 −34.23732 48.38299 0.000185* 7.749449* 13.47389 9.893859* * indicates lag order selected by the criterion. lr: sequential modified lr test statistic (each test at 5% level). fpe: final prediction error, aic: akaike information criterion, sc: schwarz information criterion, hq: hannan-quinn information criterion ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022420 between industrial growth and co2 emission. industrial growth is vital to attain higher economic development (ranis and fei, 1961; prebisch, 1962; amin, 1999; chen and sivakumar, 2021). while the impacts of industrial activities on the natural environment are a major concern in developed countries, much less is known about these impacts in developing countries. our results explain that a 1 percent increase in industrial growth brings (0.029972) percent rise in co2 emissions in the case of pakistan. the developing world is often seen as having a high percentage of heavily polluting activities within its industrial sector. but the sound industrialization policies are of paramount importance in developing countries’ economic development and call for the management of natural resources and the adoption of low-waste or environmentally clean technologies (freeman et al., 1992; north, 1997; ahuti, 2015; shugurov, 2018). in industrialized countries, environmental regulation and new technologies are reducing the environmental impact per unit produced, but industrial activities and growing demand are still putting pressure on the environment and the natural resource base (ehrlich et al., 1999; munasinghe, 1999). in developing countries, a double environmental effect is occurring: old environmental problems, such as deforestation and soil degradation, remain largely unsolved. at the same time, new problems linked to industrialization are emerging, such as rising greenhouse gas emissions, air, and water pollution, growing volumes of waste, desertification, and chemical pollution (ahuti, 2015; carley and christie, 2017; hasnat et al., 2018; bekabil, 2020). the estimated results show that agricultural growth has a negative and insignificant impact on co2 emissions. there is an extensive amount of literature that examines the relationship between agricultural growth and co2 emissions (jebli and youssef, 2017; chebbi, 2010; hertel et al., 2014; gokmenoglu and taspinar, 2018). though economic development in the modern age is substantially dependent on industrialization as well as the use of modern technology. the role of the traditional agriculture sector is still significant since it provides a base for the development of an agro-based industry and is a major source of food. further, the agriculture sector has the potential to assist in protecting the environment from pollution (parry, 1998; mahmood et al., 2019). almost half of the world’s population live in rural areas to attain their livelihood in agriculture where the contribution of this sector in the global gross domestic product (gdp) is near to 30% (fao, 2011). but due to the negative climatic change, agriculture-driven gdp growth for the reduction of poverty, ensuring the security of food, biodiversity, etc. are now under various challenges (torrellas et al., 2012; lloyd, 2017). the estimated results show that service sector growth has a negative and significant impact on co2 emissions in pakistan. mcewen (2013) mentions that services sector growth can protect the ecosystem, improve environmental quality, reduce deforestation, and improve environmental practices and freshwater supply. since then, services sector growth could be a solution to numerous environmental and social problems (wheeler and benshlomo, 2005; senge et al., 2007; hall et al., 2010). the results show that indicate that a 1 percent increase in service sector growth brings (-0.021752) percent decrease in co2 emissions in the case of pakistan over the selected period. over the last few decades, environmental concerns have been considered in the design of the economic policy. natural capital is considered to be an indispensable production input, and also a determinant of societal wellbeing (costantini and monni, 2008). moreover, concern about whether the social-ecological processes which allow human wellbeing to be sustained suggests that sustainable development should be a broad social goal. the role of services sector growth in achieving such a goal is emerging as a subject of some debate. it is considered as the most important channel toward the production of sustainable products and services and the implementation of new projects to address many environmental and social concerns (kemp and rotmans, 2005; garetti and taisch, 2012). the estimated results show that population density has a positive and significant impact on co2 emissions in the case of pakistan. from the last few decades, the policymakers highlight that the rapid population growth is a serious global crisis. one of the primary causes of environmental degradation in a country could be attributed to the rapid growth of population, which adversely affects the natural resources and environment (nagdeve, 2007; ray and ray, 2011; chopra, 2016). population impacts on the environment primarily through the use of natural resources and production of wastes and are associated with environmental stresses like loss of biodiversity, air, and water pollution, and increased table 6: ardl bounds test test statistic value k f-statistic 7.522391 5 critical value bounds significance lower bound upper bound 10% 2.75 3.79 5% 3.12 4.25 2.5% 3.49 4.67 1% 3.93 5.23 table 7: long run coefficients dependent variable: co2 variables coefficients std. error t-statistic prob. ind 0.029972 0.010528 2.846794 0.0074 agr −0.001980 0.004743 −0.417509 0.6789 ser −0.021752 0.009109 −2.387954 0.0226 pd 0.509724 0.121561 4.193169 0.0002 glob −0.001495 0.009746 −0.153389 0.8790 c 8.098723 0.623834 12.982182 0.0000 @trend 0.067118 0.004889 13.729092 0.0000 r-squared 0.998130 mean dependent var 11.16802 adjusted r-squared 0.997470 s.d. dependent var 0.699806 s.e. of regression 0.035200 akaike info criterion −3.626156 sum squared resid 0.042127 schwarz criterion −3.114413 log likelihood 98.21467 hannan-quinn criter. −3.433584 f-statistic 1512.315 durbin-watson stat 2.025665 prob (f-statistic) 0.000000 ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022 421 pressure on arable land. the rapidly growing population and economic development are leading to several environmental issues in pakistan because of the uncontrolled growth of urbanization and industrialization, expansion and massive intensification of agriculture, and the destruction of forests. major environmental issues are forest and agricultural degradation of land, resource depletion (water, mineral, forest, sand, rocks, etc.), environmental degradation, public health, loss of biodiversity, loss of resilience in ecosystems, livelihood security for the poor. our results show that a 1 percent increase in population density brings (0.509724) percent increase in co2 emissions in the case of pakistan over the selected period. the uprising population and the environmental deterioration face the challenge of sustainable development. the existence or the absence of favorable natural resources can facilitate or retard the process of socio-economic development. the three basic demographic factors of births (natality), deaths (mortality) and human migration (migration) and immigration (population moving into a country produces higher population) produce changes in population size, composition, distribution, and these changes raise several important questions of cause and effect. population growth is contributing to many serious environmental calamities in pakistan. the estimated results show that globalization has a negative and insignificant impact on co2 emissions in the case of pakistan over the selected period. the effect of globalization on the environment has been explored in the previous literature (laws, 1994, goudie and viles, 1997). globalization produces a technical effect due to improvements and new technologies that facilitate the reduction of co2 emissions (tisdell, 2001). globalization has a positive impact on economic efficiency (technique effect), which improves environmental quality (cavlovic et al., 2000). list and co (2000) conclude that globalization helps promote energy efficiency and reduces co2 emissions, while tamazian et al. (2009) found that globalization through foreign direct investment (fdi) encourages technological innovation and the adoption of new technologies that develop more energy-efficient processes and promote sustainable economic growth. time trend is playing an important role in the quantity enlargement of co2 emissions in pakistan. the estimated coefficient shows that a one-year time brings (0.067118) percent rise in co2 emissions in the case of pakistan over the selected period. the constant coefficient also strengthens the time trend involvement in rising co2 emissions, as pakistan has huge industrial production economies in its neighbors i.e. india and china. thus, if pakistan carries on with the existed industrial, agricultural, and services sector growth, then (8.098723) percent rise in co2 emissions will occur every year. the estimated short-run outcomes have been given in table 8. the results show that industrial growth and services sector growth has a negative and significant short-run impact on co2 emissions in pakistan. the results show that agricultural growth has a negative but insignificant short-run impact on co2 emissions in pakistan. the estimated short-run results reveal that population density and globalization have a positive and significant impact on co2 emissions in the case of pakistan. in long run, the time trend is one of the main contributors to co2 emissions in pakistan. the value of ect is theoretically correct, i.e. negative and significant, the results show that 36.61 percent variation in the dependent variable is corrected very next year. the results show that the short-run needs two years and 7 months to complete convergence in the long run. overall, short-run results show that most of the explanatory variables are contributing to co2 emissions in the long run and short run too. the estimated diagnostic tests outcomes have been given in table 9. the results show that there is no issue of heteroskedasticity, serial correlation, and omitted variable biasedness. from table 1, jarque-bera values also explain that the data of selected variables are normally distributed. the outcomes of diagnostic tests show that our estimated results are unbiased and consistent for the policy purpose. the stability of the model enables us to see either the estimated model shift or not over the selected period. hansen (1996) mentions that misspecification of the model may provide biased results that influence the explanatory power of the results. the cumulative sum (cusum) and the cumulative sum of the squares (cusum sq) tests are used for examining the stability of short-run and long-run coefficients of the model (brown, durbin, and evans, 1975). the results of cumulative sum (cusum) and the cumulative sum of the squares (cusum sq) tests are reported in figures 2 and 3. the figures show that cumulative sum (cusum) and the cumulative sum of the squares (cusum sq) are between the two critical lines and do not go outside the critical boundaries. the figures of cumulative sum (cusum) and the cumulative sum of the squares (cusum sq) confirm that our model is correctly specified. table 8: short run coefficients dependent variable: co2 variables coefficients std. error t-statistic prob. d (ind) −0.002976 0.001578 −1.885958 0.0679 d (agr) −0.000725 0.001730 −0.419158 0.6777 d (ser) −0.007964 0.003491 −2.281216 0.0289 d (pd) 0.186632 0.044143 4.227899 0.0002 d (glob) 0.014803 0.006492 2.280221 0.0290 d(@trend) 0.024575 0.004507 5.452213 0.0000 ect −0.366143 0.069922 −5.236481 0.0000 table 9: diagnostic tests heteroskedasticity test: breusch-pagan-godfrey f-statistic 1.784839 prob. f (9,39) 0.1026 obs*r-squared 14.29465 prob. chi-square (9) 0.1122 scaled explained ss 9.812373 prob. chi-square (9) 0.3659 breusch-godfrey serial correlation lm test: f-statistic 1.471199 prob. f (2,37) 0.2428 obs*r-squared 3.609636 prob. chi-square (2) 0.1645 ramsey reset test: omitted variables value df probability t-statistic 1.194345 38 0.2397 f-statistic 1.426460 (1, 38) 0.2397 ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022422 6. conclusions this study has examined the impact of sectoral growth on co2 emissions in the case of pakistan from 1970 to 2019. industrial growth, agricultural growth, services sector growth, population density, and globalization have been selected as explanatory variables. unit root issues of data series have been checked with the help of adf and pp unit root tests, whereas the zivot-andrew structural break unit root test has been applied to check the existence of structural break. the autoregressive distributed lag model has been applied for checking the cointegration among the variables of the model. adf, pp unit root tests find mixed order of integration among the selected variables of the model. the results of the zivotandrew unit root test approve the existence of different structural breaks selected data series with mixed order of integration as well. the long-run results show that industrial growth, population density, and time trend are positively and significantly contributing to co2 emissions in pakistan. in the long run services sector growth is responsible for reducing co2 emissions in pakistan. the results show that agricultural growth and globalization are reducing co2 emissions but this relationship is insignificant over the selected period. in the short-run industrial growth, agricultural growth, and service sector growth are reducing the level of co2 emissions in pakistan. likewise long run, trend time is promoting co2 emissions in the short run in pakistan. in the short-run population density and globalization have a positive impact on co2 emissions in pakistan. overall results conclude that sectoral growth is responsible for promoting co2 emissions in pakistan but it has a reverse kind of relationship in the long run and short run. on the basis above conclusions, there are some policy suggestions for pakistan to reduce the level of co2 emissions. government must control industrial sector pollution which is the major cause of environment-related problems. preventive measures including encouraging the use of cleaner fuels and diesel with lower sulfur content should be encouraged in pakistan. the old petrol-based engine should be converted into new engines to control the air pollution. the system of sanitation should be improved to control the urban population. the government of pakistan must positively increase agricultural growth to reduce environmental degradation. there should be a policy to protect environmental quality with nonpolluted agricultural growth. the government must also increase industrial growth inefficient manner to control environmental degradation in pakistan. there should be proper control on the energy consumption, negative impacts of globalization, and population density to overcome the environmental degradation in pakistan. in the end, considering a long-run phenomenon, pakistan must treat environmental issues as the primary issue for its coming generations. references adams, s., nsiah, c. (2019), reducing carbon dioxide emissions; does renewable energy matter? science of the total environment, 693, 133288. agras, j., chapman, d. (1999), a dynamic approach to the environmental kuznets curve hypothesis. ecological economics, 28(2), 267-277. ahuti, s. (2015), industrial growth and environmental degradation. international education and research journal, 1(5), 5-7. akbostancı, e., türüt-aşık, s., tunç, g.i̇. (2009), the relationship between income and environment in turkey: is there an environmental kuznets curve? energy policy, 37(3), 861-867. ali, a. (2015), the impact of macroeconomic instability on social progress: an empirical analysis of pakistan. ph. d dissertation. lahore, pakistan: ncbae. p1-152 ali, a., audi, m. (2016), the impact of income inequality, environmental degradation and globalization on life expectancy in pakistan: an empirical analysis. international journal of economics and empirical research, 4(4), 182-193. ali, a., audi, m., roussel, y. (2021), natural resources depletion, renewable energy consumption and environmental degradation: a comparative analysis of developed and developing world. international journal of energy economics and policy, 11(3), 251-260. ali, a., rehman, h.u. (2015), macroeconomic instability and its impact on gross domestic product: an empirical analysis of pakistan. pakistan economic and social review, 53: 285-316. amin, a. (1999), an institutionalist perspective on regional economic development. international journal of urban and regional research, 23(2), 365-378. ang, j.b. (2007), co2 emissions, energy consumption, and output in france. energy policy, 35(10), 4772-4778. annunziata, e., frey, m., rizzi, f. (2013), towards nearly zero-energy buildings: the state-of-art of national regulations in europe. energy, 57, 125-133. apergis, n., payne, j.e. (2009), co2 emissions, energy usage, and output in central america. energy policy, 37(8), 3282-3286. audi, m., ali, a. (2017), socio-economic development, demographic changes and total labor productivity in pakistan: a co-integrational and decomposition analysis. journal of academy of business and economics, 17(2), 7-24. figure 3: cumulative sum of the squares (cusum sq) figure 2: cumulative sum (cusum) ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022 423 audi, m., ali, a. (2018), determinants of environmental degradation under the perspective of globalization: a panel analysis of selected mena nations. journal of academy of business and economics, 18(1), 149-166. audi, m., ali, a., kassem, m. (2020), greenhouse gases: a review of losses and benefits. international journal of energy economics and policy, 10(1), 403. baek, j., kim, h.s. (2013), is economic growth good or bad for the environment? empirical evidence from korea. energy economics, 36, 744-749. bakirtas, t., akpolat, a.g. (2018), the relationship between energy consumption, urbanization, and economic growth in new emergingmarket countries. energy, 147, 110-121. balsalobre-lorente, d., shahbaz, m., roubaud, d., farhani, s. (2018), how economic growth, renewable electricity and natural resources contribute to co2 emissions? energy policy, 113, 356-367. bartoletto, s., rubio, m.m. (2008), energy transition and co2 emissions in southern europe: italy and spain (1861-2000). global environment, 1(2), 46-81. baum, c.f. (2005), stata: the language of choice for time-series analysis? the stata journal, 5(1), 46-63. beckerman, w. (1992), economic growth and the environment: whose growth? whose environment? world development, 20(4), 481-496. bekabil, u.t. (2020), industrialization and environmental pollution in africa: an empirical review. journal research development management, 69, 18-21. brock, w.a., taylor, m.s. (2010), the green solow model. journal of economic growth, 15(2), 127-153. brooks, r., harris, e. (2014), price leadership and information transmission in australian water allocation markets. agricultural water management, 145, 83-91. carley, m., christie, i. (2017), managing sustainable development. united kingdom: routledge. carson, r.t., jeon, y., mccubbin, d.r. (1997), the relationship between air pollution emissions and income: us data. environment and development economics, 2(4), 433-450. cavlovic, t.a., baker, k.h., berrens, r.p., gawande, k. (2000), a metaanalysis of environmental kuznets curve studies. agricultural and resource economics review, 29(1), 32-42. chebbi, h.e. (2010), agriculture and economic growth in tunisia. china agricultural economic review, 2(1), 63-78. chen, y., sivakumar, v. (2021), invesitigation of finance industry on risk awareness model and digital economic growth. annals of operations research, 428, 1-22. cherubini, f., peters, g.p., berntsen, t., strømman, a.h., hertwich, e. (2011), co2 emissions from biomass combustion for bioenergy: atmospheric decay and contribution to global warming. gcb bioenergy, 3(5), 413-426. chopra, r. (2016), environmental degradation in india: causes and consequences. international journal of applied environmental sciences, 11(6), 1593-1601. cole, m.a., elliott, r.j. (2003), determining the trade-environment composition effect: the role of capital, labor and environmental regulations. journal of environmental economics and management, 46(3), 363-383. copeland, b., taylor, m.s. (1997), a simple model of trade, capital mobility, and the environment. available from: https://www.ssrn. com/abstract=4836 costantini, v., monni, s. (2008), environment, human development and economic growth. ecological economics, 64(4), 867-880. dejong, d.n., nankervis, j.c., savin, n.e., whiteman, c.h. (1992), the power problems of unit root test in time series with autoregressive errors. journal of econometrics, 53(1-3), 323-343. dickey, d.a., fuller, w.a. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica: journal of the econometric society, 49, 1057-1072. dijkgraaf, e., vollebergh, h.r. (2005), a test for parameter homogeneity in co2 panel ekc estimations. environmental and resource economics, 32(2), 229-239. dogan, e., seker, f. (2016), the influence of real output, renewable and non-renewable energy, trade and financial development on carbon emissions in the top renewable energy countries. renewable and sustainable energy reviews, 60, 1074-1085. dogan, e., ulucak, r., kocak, e., isik, c. (2020), the use of ecological footprint in estimating the environmental kuznets curve hypothesis for bricst by considering cross-section dependence and heterogeneity. science of the total environment, 723, 138063. ehrlich, p.r., wolff, g., daily, g.c., hughes, j.b., daily, s., dalton, m., goulder, l. (1999), knowledge and the environment. ecological economics, 30(2), 267-284. fisheries, f.a.o. (2011), aquaculture department. 2013. global aquaculture production statistics for the year. rome, italy: fao. frankel, j., rose, a. (2002), an estimate of the effect of common currencies on trade and income. the quarterly journal of economics, 117(2), 437-466. freeman, h., harten, t., springer, j., randall, p., curran, m.a., stone, k. (1992), industrial pollution prevention! a critical review. journal of the air waste management association, 42(5), 618-656. garetti, m., taisch, m. (2012), sustainable manufacturing: trends and research challenges. production planning control, 23(2-3), 83-104. gehring, k. (2013), who benefits from economic freedom? unraveling the effect of economic freedom on subjective well-being. world development, 50, 74-90. gokmenoglu, k.k., taspinar, n. (2018), testing the agriculture-induced ekc hypothesis: the case of pakistan. environmental science and pollution research, 25(23), 22829-22841. goudie, a., viles, h.a. (1997), salt weathering hazard. united states: wiley. grossman, g.m., krueger, a.b. (1991), environmental impacts of a north american free trade agreement. grossman, g.m., krueger, a.b. (1995), economic growth and the environment. the quarterly journal of economics, 110(2), 353-377. grossman, g.m., krueger, a.b. (1996), the inverted-u: what does it mean? environment and development economics, 1(1), 119-122. haggard, s. (1995), developing nations and the politics of global integration. united states: brookings institution press. hall, j.k., daneke, g.a., lenox, m.j. (2010), sustainable development and entrepreneurship: past contributions and future directions. journal of business venturing, 25(5), 439-448. hansen, b.e. (1996), inference when a nuisance parameter is not identified under the null hypothesis. econometrica: journal of the econometric society, 64, 413-430. haseeb, m., hassan, s., azam, m., suryanto, t. (2018), the dynamics of governance, tourism and environmental degradation: the world evidence. international journal of global environmental issues, 17(4), 340-363. hasnat, g.t., kabir, m.a., hossain, m.a. (2018), major environmental issues and problems of south asia, particularly bangladesh. in: handbook of environmental materials management. germany: springer. p1-40. hertel, t.w., ramankutty, n., baldos, u.l.c. (2014), global market integration increases likelihood that a future african green revolution could increase crop land use and co2 emissions. proceedings of the national academy of sciences, 111(38), 1379913804. holtz-eakin, d., selden, t.m. (1995), stoking the fires? co2 emissions ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022424 and economic growth. journal of public economics, 57(1), 85-101. irfan, m., shaw, k. (2017), modeling the effects of energy consumption and urbanization on environmental pollution in south asian countries: a nonparametric panel approach. quality quantity, 51(1), 65-78. jebli, m.b., youssef, s.b. (2017), the role of renewable energy and agriculture in reducing co2 emissions: evidence for north africa countries. ecological indicators, 74, 295-301. jobert, t., karanfil, f., tykhonenko, a. (2010), convergence of per capita carbon dioxide emissions in the eu: legend or reality? energy economics, 32(6), 1364-1373. jobert, t., karanfil, f., tykhonenko, a. (2012), environmental kuznets curve for carbon dioxide emissions: lack of robustness to heterogeneity? bengaluru: hal. junyi, s.h.e. (2006), a simultaneous estimation of environmental kuznets curve: evidence from china. china economic review, 17(4), 383-394. kaika, d., zervas, e. (2013), the environmental kuznets curve (ekc) theory-part a: concept, causes and the co2 emissions case. energy policy, 62, 1392-1402. kaneko, s., managi, s. (2004), environmental productivity in china. economics bulletin, 17(2), 1-10. kanjilal, k., ghosh, s. (2013), environmental kuznet’s curve for india: evidence from tests for cointegration with unknown structuralbreaks. energy policy, 56, 509-515. kaygusuz, k. (2007), energy for sustainable development: key issues and challenges. energy sources, part b: economics, planning, and policy, 2(1), 73-83. kemp, r., rotmans, j. (2005), the management of the co-evolution of technical, environmental and social systems. in: towards environmental innovation systems. berlin, heidelberg: springer. p33-55. koengkan, m., fuinhas, j.a., santiago, r. (2020), asymmetric impacts of globalisation on co2 emissions of countries in latin america and the caribbean. environment systems and decisions, 40(1), 135-147. lal, r. (2013), food security in a changing climate. ecohydrology hydrobiology, 13(1), 8-21. laws, g. (1994), aging, contested meanings, and the built environment. environment and planning a: economy and space, 26(11), 17871802. lee, h., roland-holst, d. (1997), the environment and welfare implications of trade and tax policy. journal of development economics, 52(1), 65-82. liu, y., liu, x., gao, s., gong, l., kang, c., zhi, y., shi, l. (2015), social sensing: a new approach to understanding our socioeconomic environments. annals of the association of american geographers, 105(3), 512-530. lloyd, p.j. (2017), the role of energy in development. journal of energy in southern africa, 28(1), 54-62. magnani, e. (2001), the environmental kuznets curve: development path or policy result? environmental modelling software, 16(2), 157-165. mahmood, h., alkhateeb, t.t.y., al-qahtani, m.m.z., allam, z., ahmad, n., furqan, m. (2019), agriculture development and co2 emissions nexus in saudi arabia. plos one, 14(12), e0225865. malerba, d. (2020), the trade-off between poverty reduction and carbon emissions, and the role of economic growth and inequality: an empirical cross-country analysis using a novel indicator. social indicators research, 150(2), 587-615. malik, s.m., awan, h., khan, n. (2012), mapping vulnerability to climate change and its repercussions on human health in pakistan. globalization and health, 8(1), 1-10. martínez-zarzoso, i., maruotti, a. (2011), the impact of urbanization on co2 emissions: evidence from developing countries. ecological economics, 70(7), 1344-1353. mcausland, c. (2005), learning by doing in the presence of an open access renewable resource: is growth sustainable? natural resource modeling, 18(1), 41-68. mcconnell, k.e. (1997), income and the demand for environmental quality. environment and development economics, 2(4), 383-399. mcewen, t. (2013), ecopreneurship as a solution to environmental problems: implications for college level entrepreneurship education. international journal of academic research in business and social sciences, 3(5), 264. mongelli, i., tassielli, g., notarnicola, b. (2006), global warming agreements, international trade and energy/carbon embodiments: an input-output approach to the italian case. energy policy, 34(1), 88-100. moomaw, w.r., unruh, g.c. (1997), are environmental kuznets curves misleading us? the case of co2 emissions. environment and development economics, 2(4), 451-463. munasinghe, m. (1999), is environmental degradation an inevitable consequence of economic growth: tunneling through the environmental kuznets curve. ecological economics, 29(1), 89-109. nagdeve, d.a. (2007), population growth and environmental degradation in india. international institute for population sciences, 7192, 400. nanda, s., reddy, s.n., mitra, s.k., kozinski, j.a. (2016), the progressive routes for carbon capture and sequestration. energy science engineering, 4(2), 99-122. narayan, p.k. (2005), the saving and investment nexus for china: evidence from cointegration tests. applied economics, 37(17), 1979-1990. nasir, m., rehman, f.u. (2011), environmental kuznets curve for carbon emissions in pakistan: an empirical investigation. energy policy, 39(3), 1857-1864. nelson, c.r., plosser, c.r. (1982), trends and random walks in macroeconmic time series: some evidence and implications. journal of monetary economics, 10(2), 139-162. newey, w.k., west, k.d. (1987), hypothesis testing with efficient method of moments estimation. international economic review, 28, 777-787. north, k. (1997), environmental business management: an introduction. vol. 30. geneva, switzerland: international labour organization. ozcan, b., tzeremes, p.g., tzeremes, n.g. (2020), energy consumption, economic growth and environmental degradation in oecd countries. economic modelling, 84, 203-213. pal, d., mitra, s.k. (2017), the environmental kuznets curve for carbon dioxide in india and china: growth and pollution at crossroad. journal of policy modeling, 39(2), 371-385. panayotou, t. (1993), empirical tests and policy analysis of environmental degradation at different stages of economic development (no. 992927783402676). geneva, switzerland: international labour organization. parry, r. (1998), agricultural phosphorus and water quality: a us environmental protection agency perspective. journal of environmental quality, 27(2), 258-261. pesaran, h.h., shin, y. (1998), generalized impulse response analysis in linear multivariate models. economics letters, 58(1), 17-29. pesaran, m.h. (1997), the role of economic theory in modelling the long run. the economic journal, 107(440), 178-191. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. pesaran, m.h., shin, y., smith, r.p. (1999), pooled mean group estimation of dynamic heterogeneous panels. journal of the american statistical association, 94(446), 621-634. phillips, p.c., perron, p. (1988), testing for a unit root in time series regression. biometrika, 75(2), 335-346. ali, et al.: do sectoral growth promote co2 emissions in pakistan? time series analysis in presence of structural break international journal of energy economics and policy | vol 12 • issue 2 • 2022 425 poumanyvong, p., kaneko, s. (2010), does urbanization lead to less energy use and lower co2 emissions? a cross-country analysis. ecological economics, 70(2), 434-444. prebisch, r. (1962), the economic development of latin america and its principal problems. america: economic bulletin for latin america. protocol, k. (1997), united nations framework convention on climate change. kyoto protocol, kyoto, 19(8), 4-21. ramanathan, v., feng, y. (2009), air pollution, greenhouse gases and climate change: global and regional perspectives. atmospheric environment, 43(1), 37-50. ranis, g., fei, j.c. (1961), a theory of economic development. the american economic review, 51, 533-565. rao, s., riahi, k. (2006), the role of non-co2 greenhouse gases in climate change mitigation: long-term scenarios for the 21st century. the energy journal, 27, 177-800. ray, s., ray, i.a. (2011), impact of population growth on environmental degradation: case of india. journal of economics and sustainable development, 2(8), 72-77. richmond, a.k., kaufmann, r.k. (2006), is there a turning point in the relationship between income and energy use and/or carbon emissions? ecological economics, 56(2), 176-189. rothman, d.s. (1998), environmental kuznets curves-real progress or passing the buck?: a case for consumption-based approaches. ecological economics, 25(2), 177-194. sawyer, m. (2021), financialisation, industrial strategy and the challenges of climate change and environmental degradation. international review of applied economics, 35(3-4), 338-354. selden, t.m., song, d. (1994), environmental quality and development: is there a kuznets curve for air pollution emissions? journal of environmental economics and management, 27(2), 147-162. senge, p.m., lichtenstein, b.b., kaeufer, k., bradbury, h., carroll, j.s. (2007), collaborating for systemic change. mit sloan management review, 48(2), 44. shafik, n., bandyopadhyay, s. (1992), economic growth and environmental quality: time-series and cross-country evidence. vol. 904. united states: world bank publications. shahbaz, m., khan, s., tahir, m.i. (2013), the dynamic links between energy consumption, economic growth, financial development and trade in china: fresh evidence from multivariate framework analysis. energy economics, 40, 8-21. shahzad, s.j.h., kumar, r.r., zakaria, m., hurr, m. (2017), carbon emission, energy consumption, trade openness and financial development in pakistan: a revisit. renewable and sustainable energy reviews, 70, 185-192. shugurov, m.v. (2018), promising policy efforts on development and transfer of environmentally sound technologies. environmental policy and law, 48(6), 403-410. solarin, s.a., ozturk, i. (2015), on the causal dynamics between hydroelectricity consumption and economic growth in latin america countries. renewable and sustainable energy reviews, 52, 1857-1868. stephenson, j., newman, k., mayhew, s. (2010), population dynamics and climate change: what are the links? journal of public health, 32(2), 150-156. stern, d.i., common, m.s., barbier, e.b. (1996), economic growth and environmental degradation: the environmental kuznets curve and sustainable development. world development, 24(7), 1151-1160. suri, v., chapman, d. (1998), economic growth, trade and energy: implications for the environmental kuznets curve. ecological economics, 25(2), 195-208. tamazian, a., chousa, j.p., vadlamannati, k.c. (2009), does higher economic and financial development lead to environmental degradation: evidence from bric countries. energy policy, 37(1), 246-253. tan, f., lean, h.h., khan, h. (2014), growth and environmental quality in singapore: is there any trade-off? ecological indicators, 47, 149-155. thomas, n., tow, w.t. (2002), the utility of human security: sovereignty and humanitarian intervention. security dialogue, 33(2), 177-192. tisdell, c. (2001), globalisation and sustainability: environmental kuznets curve and the wto. ecological economics, 39(2), 185-196. tiwari, a.k., shahbaz, m., hye, q.m.a. (2013), the environmental kuznets curve and the role of coal consumption in india: cointegration and causality analysis in an open economy. renewable and sustainable energy reviews, 18, 519-527. todaro, m.p. (2006), in: smith, s.c., editor. economic development. united kingdom: pearson. p10. torrellas, m., antón, a., ruijs, m., victoria, n.g., stanghellini, c., montero, j.i. (2012), environmental and economic assessment of protected crops in four european scenarios. journal of cleaner production, 28, 45-55. van west, c.r., dean, j.s. (2000), environmental characteristics of the ad 900-1300 period in the central mesa verde region. kiva, 66(1), 19-44. vollebergh, h.r., kemfert, c. (2005), the role of technological change for a sustainable development. australia: university of wollongong wang, s., li, q., fang, c., zhou, c. (2016), the relationship between economic growth, energy consumption, and co2 emissions: empirical evidence from china. science of the total environment, 542, 360-371. warner, k., hamza, m., oliver-smith, a., renaud, f., julca, a. (2010), climate change, environmental degradation and migration. natural hazards, 55(3), 689-715. wheeler, b.w., ben-shlomo, y. (2005), environmental equity, air quality, socioeconomic status, and respiratory health: a linkage analysis of routine data from the health survey for england. journal of epidemiology community health, 59(11), 948-954. xiao, b., niu, d., wu, h. (2017), exploring the impact of determining factors behind co2 emissions in china: a cge appraisal. science of the total environment, 581, 559-572. zandi, g., haseeb, m. (2019), the importance of green energy consumption and agriculture in reducing environmental degradation: evidence from sub-saharan african countries. international journal of financial research, 10(5), 215-227. zhang, y.j., peng, y.l., ma, c.q., shen, b. (2017), can environmental innovation facilitate carbon emissions reduction? evidence from china. energy policy, 100, 18-28. zivot, e., andrews, d.w.k. (2002), further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. journal of business economic statistics, 20(1), 25-44. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 4 • 2022274 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(4), 274-281. does investment and energy infrastructure influence convergence in sumatra island, indonesia? muhammad hidayat1,2*, nasri bachtiar3, sjafrizal3, elvina primayesa3 1doctoral student in economics, faculty of economics and business, andalas university, padang, indonesia, 2department of economics, faculty of economics and business, universitas muhammadiyah riau, pekanbaru, indonesia, 3department of economics, faculty of economics and business, andalas university, padang, indonesia. *email: m.hidayat@umri.ac.id received: 29 march 2022 accepted: 12 june 2021 doi: https://doi.org/10.32479/ijeep.13214 abstract this research aims to prove the existence of a convergence process and analyse the effect of investment and energy infrastructure on the convergence process on sumatra island by including the element of space to understand spatial convergence better. the dataset used in panel data consists of 154 regions (district/municipality) from 2010 to 2020. the analytical tools used with a spatial econometric approach consist of spatial autoregressive and spatial error model. the results of the convergence test prove that there is convergence in both absolute and conditional convergence, and there is a difference in the speed of convergence for the two equations. meanwhile, the results of the spatial approach state that there are spatial dependencies so that neighbouring regions influence the region. the estimation results of conditional β-convergence reveal that investment and government spending in infrastructure has a positive and significant effect, in contrast to energy infrastructure, which has a negative and significant relationship, and only human capital is not significant to the convergence process in sumatra. keywords: convergence, energy infrastructure, investment, spatial panel data, sumatra jel classifications: c33, d63, h54, q43, r11 1. introduction inequality between regions is the difference in development occurring at various levels between states, provinces and districts, and rural and urban areas. inequality between regions affects the incidence of civil conflict; countries with higher income inequality tend to experience internal violence (ezcurra, 2019). too long of inequality can trigger internal conflict (lessmann, 2016). it makes the issue of inequality between regions important in the economic theory literature and attracts the attention of many researchers. the phenomenon of inequality development between regions in indonesia is a significant concern considering regional inequalities that continue to occur and trigger crime rates, for example, cases in the provinces of aceh, riau, east kalimantan, and papua (tadjoeddin et al., 2001; 2020). furthermore, two of these areas are located on sumatra island. this island is indonesia’s second region with rapid development. it has a strategic location located in the malacca strait. the province on this island produces a variety of natural resources such as oil and gas producers, various mineral mines, and oil palm plantations. according to sjafrizal (2018), the difference in ownership of natural resources is one of the causes of economic inequality between regions. sumatra’s average provincial economic growth rate for the 20112020 period was 4.46%, indicating positive economic growth. meanwhile, the income distribution based on the gini ratio shows a downward trend from 0.342 to 0.319. moreover, income inequality is generally because the index value is bigger than 0.300. based on the neoclassical hypothesis that at the beginning of development, developing countries experienced divergence conditions, namely increasing inequality between regions, and as this journal is licensed under a creative commons attribution 4.0 international license hidayat, et al.: does investment and energy infrastructure influence convergence in sumatra island, indonesia? international journal of energy economics and policy | vol 12 • issue 4 • 2022 275 development continued to develop, the conditions that occurred were convergence (sjafrizal, 2018), so the existing data indicated a convergence process. according to shankar and shah (2003), the calculation of regional inequality with a dynamic concept is based on the solow economic growth model, commonly called sigma and beta convergence. the concept of convergence uses the assumption of a diminishing return to capital, referring to a long-term process in which the gdp per capita of poor regions grows faster than rich regions (barro and sala-i-martin, 1992). in this case, catch-up will eventually become convergence, or the gdp per capita between regions will be the same in steady-state conditions (sala-i-martin, 1996). the latest empirical results related to convergence from outside indonesia are results that state there is convergence, including in europe by kubis and schneider (2016); butkus et al. (2018); alexa et al. (2019); dogan and kındap (2019); balash et al. (2020); montresor et al. (2020); postiglione et al. (2020); demidova, (2021). in america by yu and lee (2012); breau and saillant (2016); flores-chamba et al. (2019); leiva and pino (2020); aristizábal and garcía (2021), in asia by barro (2016); lee (2016; 2017); zhang et al. (2019); (mendez and santos‐marquez, 2020). on the other hand, the results suggest a divergence by goschin (2014; 2017), simionescu (2014), pietrzykowski (2019) in europe, lolayekar and mukhopadhyay (2017; 2019) in asia, and kant (2019) in africa. meanwhile, empirical results in indonesia state that there is a convergence by maryaningsih et al. (2014); rahayu et al. (2015); wau et al. (2016); kurniawan et al. (2019); mendez (2020); aginta et al. (2021), and which states the divergence by firdaus and rindayati (2012). the difference in the inconsistent empirical results creates a gap for us to examining the convergence process. furthermore, convergence analysis using new spatial elements was developed and pioneered by rey and montouri (1999) and continues to develop until now. according to capello and nijkamp (2009), analysing economic inequality using spatial elements will be much more realistic than without spatial elements. research in indonesia that examines interregional convergence with spatial aspects in terms of spatial-econometrics is still few. our knowledge of those who conducted studies, including by vidyattama (2013), aritenang (2014), and aspiansyah and damayanti (2019), specifically for the sumatra island, have not yet been conducted. in this paper, our research objective is to reveal the influence of investment and energy infrastructure on the convergence process in sumatra island on a regional scale to understand spatial convergence better. this paper is structured as follows: the next section on theoretical concepts and a brief review of the research carried out on the subject. the following section explains the data and methodology, and the fourth section presents and explains the empirical results. the final section presents the conclusions and policy implications. 2. literature review the theoretical framework in this paper begins with a neo-classical hypothesis based on the theory of equalisation of remuneration factors production between regions by borts (1960), which is a continuation of the neo-classical regional economic growth theory proposed by north (1955). this hypothesis shows that inter-regional inequality tends to be higher while inequality will be lower in developed countries. in addition, it can also be estimated that in developing countries, inequality increases or divergence, but the more advanced the development of a country, there will be a process of decreasing the level of inequality between regions or convergence. the proof of this hypothesis has been tested by williamson (1965) through a study in developed and developing countries using time series and cross-section data. the results state that the hypothesis is empirically proven. according to barro and sala-i-martin (1991), there are two concepts of convergence. first, β-convergence is a catch-up process for the economy of poor regions is faster than the economy of rich regions. in the long term, the level of income per capita between regions will be the same in steady-state conditions. second, σ-convergence, namely the occurrence of a decrease in economic inequality from time to time, means that convergence occurs if the dispersion, measured by the standard deviation, is the logarithm of per capita income between regions over time. β-convergence tends to produce σ-convergence, but factors that increase inequality offset this process. therefore, β-convergence is not always synonymous with σ-convergence (barro and salai-martin, 2004). the convergence regression model was developed by barro and sala-i-martin (1990). this model produces coefficients on the initial condition variable commonly called β-convergence and measures convergence speed. a negative coefficient value indicates convergence and otherwise describes a divergence condition. furthermore, the β-convergence model was further improved by barro (1991) and barro and sala-i-martin (1992) by bringing the idea that poor and rich economies may not converge at the same steady-state condition. they categorise convergence towards the same steady-state condition as absolute convergence and towards a different steady-state condition as conditional convergence. they argue that the expected negative relationship between initial per capita income levels and growth rates holds when structural differences between poor and rich economies are constant. furthermore, the convergence analysis by including spatial elements pioneered by rey and montouri (1999) in the us period 1929-1994 stated a strong global and local spatial autocorrelation pattern. moreover, the development by rey (2001) found that geographical factors were not a determinant of changes in income distribution between regions, and the distribution of mobility that fluctuated across states was sensitive to the position of adjacent regions in the same distribution. furthermore, the latest research on the application and development of spatial convergence is carried out with different regional analysis units, including by sanso-navarro et al. (2020) across countries worldwide, yu and lee (2012) in the united states, breau and saillant (2016) in canada, aristizábal and garcía (2021) in columbia, flores-chamba et al. (2019) in ecuador, hidayat, et al.: does investment and energy infrastructure influence convergence in sumatra island, indonesia? international journal of energy economics and policy | vol 12 • issue 4 • 2022276 leiva and pino (2020) in chile, lima and neto (2016) in brazil, alexa et al. (2019); balash et al. (2020); montresor et al. (2020); panzera and postiglione (2021); pietrzykowski (2019); postiglione et al. (2020) in the european union region, yildirim et al. (2009); dogan and kındap (2019) in turkey, goschin (2017) in romania, sun et al. (2017) in china, chatterjee (2017) in india, mendez and santos‐marquez (2020) in the asean region, and indonesia by vidyattama (2013); aritenang (2014); aspiansyah and damayanti (2019). empirical results show that geographically weighted regression increases the model’s better explanatory power. there is considerable variation in convergence speed, which traditional convergence analysis cannot capture. in conditional β-convergence, several control variables support the convergence process. based on the conditional β-convergence above, some previous studies support our research. balash et al. (2020) research evidence that investment affected russia’s convergence process from 2010 to 2014. the results of spatial autocorrelation suggest that the role of territorial proximity affects interregional convergence. furthermore, in the same region, demidova (2021) found a β-convergence only for the middle and rich regions from 2000 to 2017. poor areas are not growing faster than other regions, confirming the relevance of spatial development strategies. the convergence process of rich regions can be achieved by increasing investment and reducing investment risk. however, investment in poor and middle-income areas is not practical. meanwhile, poor and middle-income regions receive positive spillovers from the growth of neighbouring regions. it is possible to expect a reduction in the difference in living standards between poor and rich regions. the article by gömleksiz et al. (2017) found that investment was positive and significant to the convergence process that occurred in turkey. furthermore, barro (2015) reveals that the investment ratio has a positive and significant effect on convergence. meanwhile, human capital as a proxy for girls’ and boys’ average years of schooling produces different results. women have insignificant positive scores, and men have significant negative values. a plausible interpretation is that expanding women’s achievements relative to men signifies a more general improvement in the political and social arrangements that support economic growth. a seminal paper by mankiw et al. (1992) or mrw pioneered the relationship between physical and human capital in the mechanism of economic growth. they state that the output of an economy is influenced by a combination of physical capital and labour skills and that the accumulation of human capital occurs and the accumulation of physical capital. the mrw model is a development of the solow (1956) growth model or augmented solow. an essential assumption of the solow augmented model is that the accumulation of human capital is the time devoted by individuals to acquire new skills, not work. lima and neto’s (2016) study using the mrw model with spatial extension reveals a strong spatial dependence among brazil’s micro-regions and significant investment in physical capital and human resources in supporting the convergence process. empirical results by lee (2016) state that human capital proxied from the average school-age and squared has a significant effect. educational attainment shows that the growth rate increases with the educational attainment rate only when the country has reached 6.0 years of schooling, which is the threshold level. similar results were proved by lee (2017) in china. furthermore, lee (2020) proves that human capital and investment are not significant to the convergence of middle-income trap countries. zhang et al. (2019) found that human capital affects convergence in china. furthermore, the positive “underdevelopment benefits” due to lower initial income are almost outweighed by the negative impact of low levels of human capital in poor areas. meanwhile, yang et al. (2016) results in china for 1997-2006 found that investment in fixed assets, government spending on education and health as a proxy for human capital, and infrastructure development positively affected regional convergence. empirical results by leiva and pino (2020) specifically show that improving educational performance in the early stages of primary school can reduce disparities in the long term while supporting the convergence process. in the paper by rahayu et al. (2015), human capital proxies from government spending on education significantly affect the convergence process in kalimantan. furthermore, the empirical results from aspiansyah and damayanti (2019) with the mrw spatial model prove that human capital has a significant positive relationship to the convergence process. flores-chamba et al. (2019) emphasise increasing public spending on productive infrastructure to support the provincial convergence process. moreover, the results reveal that convergence speed varies according to the method used; in the “conventional” method, the speed is close to 2%. the spatial durbin model is about 43%. this shows that including an autoregressive process from the dependent variable results in a more “relevant” and “efficient” convergence estimate. hooper et al. (2018; 2020) prove that increasing infrastructure spending on roads and higher education in a given decade can reduce the gaps and thus help the convergence process. furthermore, fageda and olivieri (2019) proves the convergence process in spain and finds that road infrastructure positively impacts the convergence process. empirical results by chatterjee (2017) in india prove that one of the drivers of the convergence process is electricity infrastructure. research by firdaus and rindayati (2012) resulted in several factors that affect regional income inequality in java, including health infrastructure, availability of electricity and clean water. meanwhile, the empirical results by maryaningsih et al. (2014) emphasised the availability of basic infrastructure, including land and sea transportation and electricity, to convergence in indonesia, thus making it an important condition for achieving sustainable growth. furthermore, hidayat et al. (2020) study revealed that balanced funds and energy infrastructure significantly reduce inequality. 3. methodology in this paper, a quantitative method relates to the calculated value analysed from the use of spatial econometrics to explore the hidayat, et al.: does investment and energy infrastructure influence convergence in sumatra island, indonesia? international journal of energy economics and policy | vol 12 • issue 4 • 2022 277 convergence process at a regional scale. the area that becomes the unit of analysis is the regencies/municipalities in sumatra, totalling 154. the time-series data used are from 2010 to 2020. data sources come from several surveys from statistics indonesia (bps), including socio-economic surveys, labour force surveys, population censuses, grdp, and public finances. in simple terms, the β-convergence model is absolute if the model only includes the initial condition variable as the independent variable without any control variables. meanwhile, if there is a control variable in the model, the resulting β-convergence model is conditional. next, the stages of our research start from beta testing absolute convergence, which refers to previous research, including by barro and sala-i-martin (1992); alexiadis (2013); dogan and kındap (2019). the form of the equation is as follows: log log log, , , ,y y y ui t i t i t i t� � � �� �1 1 1� � (1) where yj,t is grdp per capita district/city i in year t, yi,t-1 is grdp per capita district/city i in the previous year, α is a constant, β1 is the regression coefficient, and ui,t are residuals. convergence conditions occur if the β1 coefficient is negative. otherwise, if the β1 coefficient is positive, the divergence condition occurs. the coefficient of β1 can be expressed as follows: � �1 1� � �� ��e t (2) where t is the analysis period, the speed of convergence between regions to achieve economic equity under steady-state conditions over a certain period can be calculated as follows: ( )1ln 1ββ + = − t (3) in addition, another indicator to characterise the speed of convergence is the half-life time (τ), which is defined as the period required to eliminate half of the initial inequality. the value of halflife time can be calculated by the following equation: (arbia, 2006) � � �half life� �� � � � ln . 2 0 693147 1 (4) the second stage is testing conditional β-convergence by adding control variables. the control variables used in this research model include investment, government spending on infrastructure, energy infrastructure, and human capital. the selection of these variables is based on theory, and previous research carried out in various places. furthermore, the conditional β-convergence model equation becomes as follows: log log log log log , , , , , y y y inv bl e i t i t i t i t i t � � � � � � � �1 1 1 2 3 4 � � � � � ii hc ui t i t i t, , ,� ��5 (5) the operational variable is defined from equation (5): inv is an investment, a proxy from gross fixed capital formation or government investment in million rupiahs. for bl, it is a proxy for government spending on infrastructure in units of thousands of rupiah. the ei variable is the energy infrastructure proxy for the household electrification ratio, indicating household access to electricity. hc is human capital, proxied from senior high school participation rate (sma/equivalent). 2.1. spatial panel data the linear regression model on panel data that has a specific spatial effect without the effect of spatial interaction, according to elhorst (2003), is stated in the following equation: y xit it i it� � �� � � (6) where i is the index for the cross-sectional dimension (spatial unit) where i=1,…, n. t is the time dimension where t=1,…,t. yit is the observation unit on the dependent variable on the data i and time t. xit shows the observation vector of the independent variable at the spatial unit i and time t (1, k). β parameter vector (k,1), and εit are independent and identically distributed errors for each i and t with mean 0 and variance σ2. μi is a spatial specific effect. the linear regression model of panel data with a specific interaction between spatial units will have a dependent variable spatial lag or spatial process on error, usually referred to as the spatial lag model and the spatial error model (sem) (elhorst, 2014). the spatial lag model states that the dependent variable depends on the neighbouring dependent variable and one of the local characteristics. the following is the equation for the spatial lag model or spatial autoregressive (sar): y w y xit ij jtj n it i it� � � ���� � � �1 (7) where ρ is the sarcoefficient, and wij is the element of the spatial weighting matrix (w). the sem states that the dependent variable depends on local characteristics and the correlation error between spaces. the following is the form of the equation for the sem: y xit it i it� � �� � � (8) � � � �it ij jtj n itw� ��� 1 where ϕ is the spatial autocorrelation on error, and λ is the spatial autocorrelation coefficient. the spatial weight matrix is used to determine the proximity of regions to one another because closer regions will have a greater effect than regions that are farther apart (anselin, 1995). the way to obtain a spatial weighting matrix (w) is to use the information on the distances of the x and y coordinates from neighbours or the proximity between one region and another based on the euclidean distance approach (dattorro, 2015). the spatial weight matrix in this study was calculated using the geoda software and the spatial panel data calculation through the stata software with hidayat, et al.: does investment and energy infrastructure influence convergence in sumatra island, indonesia? international journal of energy economics and policy | vol 12 • issue 4 • 2022278 spwmatrix command developed by jeanty (2014) and xsmle by belotti et al. (2017). 4. results and discussion in this study, the selection of spatial panel data in the first stage is by conducting the hausman test to determine the fixed-effect or random-effect model. if the probability value is lower than 0.05, the fixed-effect model is selected and vice versa. based on the estimation results in table 1, the hausman test value (prob) shows a small number of 0.05, so the best model for sar and sem is the fixed effect model. furthermore, selecting the model between sar and sem can compare the akaike information criterion (aic) value with a minor value criterion and the log-likelihood value with the higher value criterion. based on table 1, the best model for absolute β-convergence analysis is sem (3), with the smallest aic value of -7564.81 and the higher log-likelihood value of 3785.4. absolute β-convergence indication by the absence of control variables included in the model and only consists of the initial condition variable grdp per capita on the independent variable. the convergence theory states that the convergence process occurs when the coefficient value of the initial condition variable is negative. table 1 is in line with the theory, where the initial condition variable (yt-1) is negative and significant at the 1% level. the coefficient value is −0.1895. from this value, we can calculate the convergence speed and the half-life time using equations (3) and (4). the convergence speed obtained based on sem (3) is 1.91% per year, with the time required to reach convergence of around 36 years. for comparison of convergence speed other than sem (3), the following are the results for model (1) is 1.31% per year with a time of about 52 years, model (2) is 0.19% per year with a time of about 349 years, model (4) is 0.25% per year for about 278.56 years. this absolute convergence speed is smaller than the previous study by vidyattama (2013), which stated that the convergence speed was 3.6% for inter-regencies in sumatra island for the 1999-2008 period. even so, findings of the convergence speed in this study are greater than aritenang (2014) research results, with a value of 0.6% from 1994 to 2004. furthermore, from table 1, the spatial effect value for the whole model is significant at the 1% level, proving that the included spatial element affects the absolute β-convergence that occurs. in other words, neighbouring areas influence inter-regional convergence on sumatra island. some regencies/ municipalities are close to and intersect on one island, resulting in high interaction and interdependence with the surrounding area, especially for meeting primary needs. besides, urban areas are excellent for people who live in regencies, especially for work activities. the surrounding city area produces an area satellite. before we proceed to the conditional β-convergence analysis, the selection of the model is carried out again. the first stage is by conducting the hausman test to determine the fixed-effect or random-effect model, with criteria that if the probability value is lower than 0.05, then the model selected is the fixed-effect model and vice versa. based on the results presented in table 2, the hausman test value (prob) shows a value smaller than 0.05, so the best model used in this study is the fixed-effect model listed in the columns: sar (1) and sem (3). in the next stage, the aic and log-likelihood values are compared from the selected models. the best model for conditional β-convergence analysis is sem (3). the sem (3) result states a convergence process as evidenced by the value of the yt-1 coefficient, which is negative with a value of −0.2281 and is significant at the 1% level. based on this value, a convergence speed of 2.35% per year is generated with about 29 years to achieve an even distribution of grdp per capita at steady-state conditions required by several control variables in the model. this convergence speed is greater than the previous study by aspiansyah and damayanti (2019) of 1.8% per year and takes about 39 years to cover half the gap. based on the results of the sar model (1) provides evidence that there is a significant spatial effect with a value of 0.3706 and significant at the 1% level. the same thing for the sem model (3) λ value is 0.4312 and is significant at the 1% level. from the two models, there is evidence that the regional neighbours on sumatra island can affect the convergence process. sar (1) model, spatial effect illustrates that the economic convergence is influenced by the region’s characteristics and is also influenced by the convergence of other regions. in contrast, the sem model (3) illustrates that the convergence of a region is not only influenced by the characteristics of the region itself but also by random shocks that occur from other regions. table 1: absolute β-convergence models for 2010-2020 item sar fe (1) sar re (2) sem fe (3) sem re (4) yt-1 −0.1346*** (0.0108) −0.0216*** (0.0035) −0.1895*** (0.014) −0.027*** (0.0041) spatial effect ρ 0.3196*** (0.0562) 0.4597*** (0.0514) λ 0.4948*** (0.0521) 0.4966*** (0.0516) convergence speed 1.31 0.1985 1.91 0.2488 half-life time (year) 52.74 349.16 36.29 278.56 hausman (prob) 0.0000 0.0000 aic −7524.447 −7184.5 −7564.814 −7190.47 log-likelihood 3765.223 3597.25 3785.4 3600.236 r2 0.0935 0.0825 0.1113 0.1113 n 1694 1694 1694 1694 the spatial model based on euclidean distance matrix. aic: akaike information criterion. heteroskedasticity robust standard error are shown in parentheses. *p<0.1; **p<0.05; ***p<0.01 hidayat, et al.: does investment and energy infrastructure influence convergence in sumatra island, indonesia? international journal of energy economics and policy | vol 12 • issue 4 • 2022 279 based on table 2, there is evidence that investment has a positive and significant effect on convergence with a coefficient value of 0.0681. if there is an increase in investment by one unit, the convergence will increase by 0.0681 per cent, assuming other variables are held constant. these results are in line with research by balash et al. (2020), gömleksiz et al. (2017), and barro (2015), which generally proves that investment has a positive effect on the convergence process. meanwhile, specifically not for research from demidova (2021) states that investment in poor and middle-income areas is ineffective. furthermore, infrastructure funds affect convergence with a coefficient value of 0.0159 and significant at the 5% level. this result indicates that allocating funds from the centre for regions and regions to manage and allocate infrastructure spending positively supports the convergence process. the results of our study are in line with research by fageda and olivieri (2019), flores-chamba et al. (2019), hooper et al. (2018, 2020), and yang et al. (2016), which proves that infrastructure funds or physical infrastructure are significant to convergence. from the research results, the energy infrastructure coefficient is negative at -0.0002 and significant at the 5% level, which means that if there is an increase in energy infrastructure by one unit, it will slow down convergence by 0.0002 per cent with the assumption that other variables in the model are considered constant. this energy infrastructure is a proxy of the household electrification ratio, and the highest value of 100 is considered that all households can enjoy electricity. in general, for urban areas and districts, the electrification ratio has reached 98-100 per cent. however, there are still districts with a ratio value below 80 per cent, including nias, mentawai islands, pelalawan, indragiri hilir, and west lampung districts, that have not fully enjoyed access to electricity, and there are still isolated areas. electricity infrastructure plays a role in sustainable living. it increases regional productivity to support the convergence process, as proven by chatterjee (2017) in india. it turns out that for our observation area, it is not proven due to differences in the proxy variables used, and the value of the electrification ratio cannot be more than 100. furthermore, the human capital coefficient value is different between the sar (1) and sem (3) models, wherein model (1) is positive 0.0003 and model (3) is negative −0.00001, and for both models, there is no significant, so human capital not significant in influencing convergence. the insignificance of human capital puts this result in line with research by lee (2020), which has previously been proven in middle-income trap countries. reflecting on the results of previous studies, sumatra island is part of indonesia, and indonesia is included in the category of middle-income trap countries, so the results make sense. on the other hand, the regional average secondary school participation rate only reached 78.19%, so it is necessary to increase public school participation, especially in the school-age population, and which aims to increase human capital, so in the long-term will have a significant effect on convergence. meanwhile, these results are not in line with research by aspiansyah and damayanti (2019), lee (2016; 2017), and lima and neto (2016), which state that human capital has a significant effect on convergence. 5. conclusion based on the above results, the following conclusions can be drawn. first, there is evidence of a convergence process with a speed of 1.91% per year and a half-life time of about 36 years for the absolute β-convergence model, while for the conditional β-convergence, the resulting speed is 2.35% per year with about 29 years. second, taking into account the spatial element in the model proves that there is an influence from neighbouring areas, which is indicated by the positive and significant spatial effect of the sar and sem models. third, from the results of conditional β-convergence, there is evidence that investment and government spending on infrastructure can support the process of economic convergence between regions. therefore, the government should maintain an investment climate and develop appropriate and sustainable infrastructure. while electrification is negatively related to convergence, the effect’s value is not too large, and the electrification ratio itself will be stuck at the highest value by itself. there will be equality in electricity facilities for households so that policymakers can remain focused on the distribution of electricity facilities, one of the basic infrastructures. the influence of human capital is not significant on convergence. thus, it is homework for policymakers to increase further school participation, especially table 2: conditional β-convergence models for 2010-2020 item sar fe (1) sar re (2) sem fe (3) sem re (4) yt-1 −0.2187*** (0.0148) −0.0231*** (0.0042) −0.2281*** (0.0153) −0.02966*** (0.0047) inv 0.0853*** (0.0189) 0.0079*** (0.0025) 0.0681*** (0.0212) 0.0104*** (0.0026) bl 0.0146** (0.0064) −0.0094** (0.0044) 0.0159** (0.0072) −0.0146*** (0.0052) elec −0.0002** (0.0001) −0.00001 (0.00006) −0.0002** (0.0001) 0.00001 (0.00008) hc 0.00003 (0.0001) 0.00008 (0.00008) −0.00001 (0.0001) −0.0001 (0.00008) spatial effect ρ 0.3706*** (0.0551) 0.4312*** (0.0534) λ 0.4071*** (0.0571) 0.4916*** (0.0527) convergence speed 2.24 0.2124 2.35 0.2737 half-life time (year) 30.89 326.24 29.45 253.236 hausman (prob) 0.0000 0.0000 aic −7582.711 −7190.739 −7586.23 −7203.34 log-likelihood 3798.355 3604.369 3800.115 3610.67 r2 0.1385 0.0411 0.1395 0.0475 n 1694 1694 1694 1694 the spatial model based on euclidean distance matrix. aic: akaike information criterion. heteroskedasticity robust standard error are shown in parentheses. **p<0.05; ***p<0.01, sar: spatial autoregressive hidayat, et al.: does investment and energy infrastructure influence convergence in sumatra island, indonesia? international journal of energy economics and policy | vol 12 • issue 4 • 2022280 in the population of school-age, to increase the existing human capital in their respective regions. from these results, policymakers can consider the model’s significant positive or negative control variables to achieve an even condition of grdp per capita in steady-state conditions. from a spatial perspective, policymakers should not forget to coordinate between regions in infrastructure development and be sustainable. suggestions for further research to be able to add variables other than the current model and modify the proxy for energy infrastructure variables. 6. acknowledgement this paper could accomplish with the support and assistance of various parties. from the research team, we would like to thank the bpp-dn ministry of education for funding this research. the promoter team and reviewers have provided helpful input in conducting this research. we also thank the doctoral of economics at andalas university, universitas muhammadiyah riau, central statistics indonesia (bps), and various parties who have helped the team prepare this paper. references aginta, h., gunawan, a.b., mendez, c. (2020), regional income disparities and convergence clubs in indonesia: new district-level evidence. journal of the asia pacific economy, 100(2), 1868107. alexa, d., cismas, l.m., rus, a.v., silaghi, m.i.p. (2019), economic growth, competitiveness, and convergence in the european regions. a spatial model estimation. economic computation and economic cybernetics studies and research, 53(1), 107-124. alexiadis, s. (2013), empirical measures of regional convergence. in: convergence clubs and spatial externalities: advances in spatial science. berlin, heidelberg: springer. anselin, l. (1995), local indicators of spatial association-lisa. geographical analysis, 27(2), 93-115. arbia, g. (2006), motivation. in: spatial econometrics: advances in spatial science. berlin, heidelberg: springer. aristizábal, j.m., garcía, g.a. (2021), regional economic growth and convergence: the role of institutions and spillover effects in colombia. regional science policy and practice, 13(4), 1146-1161. aritenang, a.f. (2014), the spatial effect of fiscal decentralisation on regional disparities: the case from indonesia. indonesian journal of geography, 46(1), 1-10. aspiansyah, a., damayanti, a. (2019), model pertumbuhan ekonomi indonesia: peranan ketergantungan spasial. jurnal ekonomi dan pembangunan indonesia, 19(1), 62-83. balash, v., balash, o., faizliev, a., chistopolskaya, e. (2020), economic growth patterns: spatial econometric analysis for russian regions. information (switzerland), 11(6), 289. barro, r.j. (1991), economic growth in a cross section of countries. quarterly journal of economics, 106(2), 407-443. barro, r.j. (2015), convergence and modernisation. the economic journal, 125(585), 911-942. barro, r.j. (2016), economic growth and convergence, applied to china. china and world economy, 24(5), 5-19. barro, r.j., sala-i-martin, x. (1990), economic growth and convergence across the united states. nber, (no. 3419). p61. barro, r.j., sala-i-martin, x. (1991), convergence across states and regions. brookings papers on economic activity. p107. barro, r.j., sala-i-martin, x. (1992), convergence. journal of political economy, 100(2), 223-251. barro, r.j., sala-i-martin, x. (2004), economic growth. 2nd ed. london, england: the mit press cambridge. belotti, f., hughes, g., mortari, a.p. (2017), spatial panel-data models using stata. stata journal, 17(1), 139-180. borts, g.h. (1960), the equalisation of returns and regional economic growth. the american economic review, 50(3), 319-347. breau, s., saillant, r. (2016), regional income disparities in canada: exploring the geographical dimensions of an old debate. regional studies, regional science, 3(1), 463-481. butkus, m., cibulskiene, d., maciulyte-sniukiene, a., matuzeviciute, k. (2018), what is the evolution of convergence in the eu? decomposing eu disparities up to nuts 3 level. sustainability, 10(5), 1552. capello, r., nijkamp, p. (2009), handbook of regional growth and development theories. united kingdom: edward elgar publishing. chatterjee, t. (2017), spatial convergence and growth in indian agriculture: 1967-2010. journal of quantitative economics, 15(1), 121-149. dattorro, j. (2015), convex optimisation; euclidean distance geometry. 2nd ed. california: meboo publishing. demidova, o.a. (2021), convergence of russian regions: different patterns for poor, middle and rich. economy of regions, 17(4), 1151-1165. dogan, t., kındap, a. (2019), regional economic convergence and spatial spillovers in turkey. international econometric review, 11(1), 1-23. elhorst, j.p. (2003), specification and estimation of spatial panel data models. international regional science review, 26(3), 244-268. elhorst, j.p. (2014), spatial econometrics: from cross-sectional data to spatial panels. berlin, heidelberg: springer. https://doi. org/10.1007/978-3-642-40340-8 ezcurra, r. (2019), interregional inequality and civil conflict: are spatial disparities a threat to stability and peace? defence and peace economics, 30(7), 759-782. fageda, x., olivieri, c. (2019), transport infrastructure and regional convergence: a spatial panel data approach. papers in regional science, 98(4), 1609-1631. firdaus, m., rindayati, w. (2012), the dynamics of regional disparity in java island after fiscal decentralisation. international journal of economics and management, 6(1), 150-166. flores-chamba, j., correa-quezada, r., álvarez-garcía, j., río-rama, m. (2019), spatial economic convergence and public expenditure in ecuador. symmetry, 11(2), 130. gömleksiz, m., şahbaz, a., mercan, b. (2017), regional economic convergence in turkey: does the government really matter for? economies, 5(3), 27. goschin, z. (2014), regional inequalities and sigma divergence in romania. procedia economics and finance, 10, 45-53. goschin, z. (2017), exploring regional economic convergence in romania. a spatial modelling approach. eastern journal of european studies, 8(2), 127-146. hidayat, m., darwin, r., hadi, m.f. (2020), does energy infrastructure reduce inequality inter-regional in riau province, indonesia? international journal of energy economics and policy, 10(1), 160-164. hooper, e., peters, s., pintus, p. (2018), to what extent can longterm investments in infrastructure reduce inequality? journal of infrastructure, policy and development, 2(2), 193. hooper, e., peters, s., pintus, p. (2020), the impact of infrastructure investments on income inequality: evidence from us states. available from: https://halshs.archives-ouvertes.fr/halshs-02736095 hidayat, et al.: does investment and energy infrastructure influence convergence in sumatra island, indonesia? international journal of energy economics and policy | vol 12 • issue 4 • 2022 281 jeanty, p.w. (2014), spwmatrix: stata module to generate, import, and export spatial weights. statistical software components, no. s457111. kant, c. (2019), income convergence and the catch-up index. the north american journal of economics and finance, 48, 613-627. kubis, a., schneider, l. (2016), regional migration, growth and convergence-a spatial dynamic panel model of germany. regional studies, 50(11), 1789-1803. kurniawan, h., groot, h.l., mulder, p. (2019), are poor provinces catching‐up the rich provinces in indonesia? regional science policy and practice, 11(1), 89-108. lee, j.w. (2016), korea’s economic growth and catch-up: implications for china. china and world economy, 24(5), 71-97. lee, j.w. (2017), china’s economic growth and convergence. the world economy, 40(11), 2455-2474. lee, j.w. (2020), convergence success and the middle‐income trap. the developing economies, 58(1), 30-62. leiva, y., pino, g. (2020), analysis of the impact of school performance on income inequality in the long run: an application to chilean municipalities. growth and change, 51(3), 1045-1080. lessmann, c. (2016), regional inequality and internal conflict. german economic review, 17(2), 157-191. lima, r.c.d., neto, r.d.m. (2016), physical and human capital and brazilian regional growth: a spatial econometric approach for the period 1970-2010. regional studies, 50(10), 1688-1701. lolayekar, a., mukhopadhyay, p. (2017), growth convergence and regional inequality in india 1981-2012. journal of quantitative economics, 15(2), 307-328. lolayekar, a., mukhopadhyay, p. (2019), spatial dependence and regional income convergence in india 1981-2010. geojournal, 84(4), 851-864. maryaningsih, n., hermansyah, o., savitri, m. (2014), pengaruh infrastruktur terhadap pertumbuhan ekonomi indonesia. buletin ekonomi moneter dan perbankan, 17(1), 62-98. mankiw, n.g., romer, d., weil, d.n. (1992). a contribution to the empirics of economic growth. quarterly journal of economics, 107(2), 407-437. mendez, c. (2020), regional efficiency convergence and efficiency clusters: evidence from the provinces of indonesia 1990-2010. asiapacific journal of regional science, 4(2), 391-411. mendez, c., santos‐marquez, f. (2020), regional convergence and spatial dependence across subnational regions of asean: evidence from satellite nighttime light data. regional science policy and practice, 13(6), 1750-1777. montresor, e., pecci, f., pontarollo, n. (2020), structural funds, institutional quality and regional economic convergence in eu: a spatial econometric approach. in: innovations in urban and regional systems. berlin, heidelberg: springer. p281-306. north, d.c. (1955), location theory and regional economic growth. journal of political economy, 63(3), 243-258. panzera, d., postiglione, p. (2021), the impact of regional inequality on economic growth: a spatial econometric approach. regional studies, 56, 687-702. pietrzykowski, m. (2019), convergence in gdp per capita across the eu regions-spatial effects. economics and business review, 5(2), 64-85. postiglione, p., cartone, a., panzera, d. (2020), economic convergence in eu nuts 3 regions: a spatial econometric perspective. sustainability, 12(17), 6717. rahayu, d., ismail, m., santoso, d.b., pratomo, d.s. (2015), do natural resources and human capital matter to regional income convergence? (a case study at regencies/municipalities of kalimantan area-indonesia). procedia-social and behavioral sciences, 211, 1112-1116. rey, s.j. (2001), spatial empirics for economic growth and convergence. geographical analysis, 33(3), 195-214. rey, s.j., montouri, b.d. (1999), us regional income convergence: a spatial econometric perspective. regional studies, 33(2), 143-156. sala-i-martin, x.x. (1996), regional cohesion: evidence and theories of regional growth and convergence. european economic review, 40(6), 1325-1352. sanso-navarro, m., vera-cabello, m., puente-ajovín, m. (2020), regional convergence and spatial dependence: a worldwide perspective. annals of regional science, 65(1), 147-177. shankar, r., shah, a. (2003), bridging the economic divide within countries: a scorecard on the performance of regional policies in reducing regional income disparities. world development, 31(8), 1421-1441. simionescu, m. (2014), testing sigma convergence across eu-28. economics and sociology, 7(1), 48-60. sjafrizal. (2018), regional economic analysis and application in indonesia (bahasa). jakarta: rajawali pers. solow, r.m. (1956), a contribution to the theory of economic growth. quarterly journal of economics, 70(1), 1884513. sun, x., chen, f., hewings, g.j.d. (2017), spatial perspective on regional growth in china: evidence from an extended neoclassic growth model. emerging markets finance and trade, 53(9), 2063-2081. tadjoeddin, m.z., suharyo, w.i., mishra, s. (2001), regional disparity and vertical conflict in indonesia. journal of the asia pacific economy, 6(3), 283-304. tadjoeddin, m.z., yumna, a., gultom, s.e., rakhmadi, m.f., suryahadi, a. (2020), inequality and violent conflict: new evidence from selected provinces in post-soeharto indonesia. journal of the asia pacific economy, 26(2), 1-22. vidyattama, y. (2013), regional convergence and the role of the neighbourhood effect in decentralised indonesia. bulletin of indonesian economic studies, 49(2), 193-211. wau, t., sjafrizal, bachtiar, n., muhafzan. (2016), labor mobility, fiscal decentralisation, and economic convergence between regions in indonesia. international journal of management and applied science, 2(8), 123-128. williamson, j.g. (1965), regional inequality and the process of national development: a description of the patterns. economic development and cultural change, 13(4), 1-84. yang, f., pan, s.,yao, x. (2016), regional convergence and sustainable development in china. sustainability, 8(2), 121. yildirim, j., öcal, n., özyildirim, s. (2009), income inequality and economic convergence in turkey: a spatial effect analysis. international regional science review, 32(2), 221-254. yu, j., lee, l.f. (2012), convergence: a spatial dynamic panel data approach. global journal of economics, 1(1), 1250006. zhang, w., xu, w., wang, x. (2019), regional convergence clubs in china: identification and conditioning factors. annals of regional science, 62(2), 327-350. zhang, x., li, h., wang, x., fleisher, b.m. (2019), human capital and the economic convergence mechanism: evidence from china. iza. (no. 12224). tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 5 • 2021 483 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(5), 483-489. russia’s petroleum industry in the period of sanctions and covid-19 pandemic: a review and analysis meiramkul saiymova1*, nurken baikadamov2, yuliya tyurina3, georgiy kutsuri3, lola sanginova3, marija troyanskaya4 1atyrau university of oil and gas, baimukhanov st. 45a, 060027, atyrau, kazakhstan, 2academician zulkarnai aldamzhar kostanay social-technical university, kobylandy batyr ave., 27, 050010, kostanay, kazakhstan, 3financial university under the government of the russian federation, leningradsky prospekt 49, 125993, moscow, russian federation; 4orenburg state university, victory ave. 13, 460018, orenburg, russian federation. *email: meiramkul.saiymova@aogu.edu.kz received: 12 april 2021 accepted: 13 july 2021 doi: https://doi.org/10.32479/ijeep.11385 abstract russia’s four largest petroleum companies, rosneft, surgutneftegaz, gazprom neft, and lukoil, account for more than 50% of petroleum production and 70% of the demand in russia’s drilling market. all these four petroleum companies are profoundly relaying on foreign direct investments (fdi) and import of equipment and technologies. fdi have been mostly received from european union (eu) countries and united states (u.s.) and also these countries have been major providers of equipment and technologies including technologies for offshore development, horizontal, controlledangle, and directional drilling, hydraulic fracturing, catalysts for oil processing and petrochemicals, and geological and seismic exploration. however, since applying economic sanctions against russia by eu and u.s. in 2014 due to crimea annexation and ukrainian crisis, the situation with fdi and access to technologies has been dramatically changed. keeping with the analytical separation between economic and non-economic sanctions and using concept of political economy of energy, this paper focuses on economic energy sanctions, and for brevity refer to them as energy sanctions with emphasizes on technology export ban, foreign capital ban, state support of petroleum industry and in addition, because of the crucial role that petroleum industry plays in the russian economy, the paper discusses the impact of both energy sanctions and covid-19 pandemic on national economy. keywords: petroleum industry, covid-19, russia, energy sanctions jel classifications: p4, p48; q4, q43; k3, k32 1. introduction international sanctions generally refer to punitive measures taken by a country, a group of countries, or an international organization against countries that undermine international obligations, treaties, and agreements, and they are often initiated by countries with strong economic power as a means of combating and weakening the political, economic, and military power of other countries (schwartz and orleans, 1967; nossal, 1999; pape, 1997; drezner, 2011). as an important means of safeguarding national security and interests, the imposition of international sanctions could also influence international relations (brooks, 2002). in addition, many fields have also been implicated in the impact of international sanctions. first, human rights and democracy have increasingly become important policy objectives in international economic sanctions (tostensen and bull, 2002; brzoska, 2015). additionally, in the economic field, sanctions present a significantly negative impact on the trade of the target countries (ang, 2011). more seriously, economic sanctions undermine financial stability, making it more likely to generate currency crises. growth domestic product (gdp) growth is also be negatively affected by international sanctions from a macroeconomic perspective. international sanctions also cause social problems in the countries being sanctioned for example, increasing income inequality in target states and widening poverty gap (paternoster et al., 1983; marinov, this journal is licensed under a creative commons attribution 4.0 international license saiymova, et al.: russia’s petroleum industry in the period of sanctions and covid-19 pandemic: a review and analysis international journal of energy economics and policy | vol 11 • issue 5 • 2021484 2005; portela, 2005; houser et al., 2008). technological and financial sanctions targeting economic sectors are a common practice globally. however, only in the most egregious cases are they imposed on basic technologies. generally, sanctions are oriented not on undermining the offending country’s actions, but on closing off avenues for its future growth and development (kreimer, 1984; white and abass, 2006). the sanctions are designed so that their asphyxiating effect is not immediately noticeable (early, 2015). one important subset of economic sanctions is the sanctioning of energy. while not all energy sanctions lie in the economic realm, for example, the targeting of pipelines and power plants the majority of these sanctions are of an economic nature (mack and khan, 2000; allen, 2008; portela, 2010). keeping with the analytical separation between economic and non-economic sanctions, we focus in this paper on economic energy sanctions, and for brevity refer to them as energy sanctions. we focus on energy sanctions for several reasons. first, energy sanctions are a major category of economic sanctions and thus require closer attention. indeed, scholars have noted the lack of theorization and conceptualization with regard to how and when energy is used in foreign policy for means other than energy goals (miller, 2014; rasoulinezhad, 2016; mokin, 2019). second, energy is a fundamental enabling element of modern life, and thus has a direct and critical impact on the functioning, well-being, and development of nations (veebel and markus, 2015; nardin et al., 2016; wen et al., 2020). this influence can be seen, for example, in the effects of the trauma of the 1973 oil shock, specifically the perception that countries that control the oil wield an oil weapon (barrett, 1997). while opec use of the oil weapon in 1973 led to fear that energy dependence might increase an exporting country’s ability to use sanctions against their clients, energy sanctions can also be waged by importers and transit countries. the sanctions can also seriously slow the development of export pipeline infrastructure by gradually squeezing russia out of external markets, narrowing its channels for receiving export profits, and undermining the stability of its national economy. regarding the effectiveness of sanctions, abundant literature addresses the design of sanctions and their effectiveness. many have argued that sanctions are ineffective, or that their goals are overambitious and nonrealistic (andryushkevich, 2020). others argue that the assessment of effectiveness needs to take a more nuanced approach than the success, failure dichotomy; should address the issue of costs in a more comprehensive way; and needs to consider political regime differences in the sender country as well as domestic factors (newnham, 2015; neuenkirch and neumeier, 2016). one group of experts argues that the sanctions have no effect and, moreover, are finally stimulating import substitution and technological development (eaton and engers, 1999). the second group believes the sanctions will soon have catastrophic consequences due to the sector’s extreme dependence on foreign financing and technology (kaempfer and lowenberg, 2007; portela, 2010). an important feature of the sanctions is their exceedingly vague wording. this allows for significant flexibility in their interpretation and application, depending on the individual situation and the level of geopolitical tension (lektzian and souva, 2007; chikunov et al., 2019). under the current sanctions, it is possible to simply preserve the status quo. but it is also possible to intensify the restrictions, including through their stricter interpretation or active application to specific projects. in both cases, the impact depends on the time frame. understanding the design of energy sanctions is particularly important, given the considerable influence that the components of the design have over the costs, audience, and effectiveness of the sanction. nevertheless, while the design of sanctions has been extensively researched, only a small number of these studies have analyzed energy sanctions. this paper is specifically focused on energy sanctions with emphasizes on trade import restrictions, technology export ban, foreign capital ban and in addition the impact of the covid-19 pandemic. recently, there have been a number of studies that have investigated several specific resource usage and energy policy areas in resourcerich countries (rivotti, et al., 2019) and technical issues of energy such as the gas and oil consumption (karatayev et al., 2019), the impact of feed-in tariff policy (karatayev and hall, 2017), the practical application of the buy-back service contracts, or the latest reform attempts in the electricity industry (allen, 2008; bapat et al., 2013; dreyer and popescu, 2014). beyond these particular studies, the seminal work provides a comprehensive picture of the domestic and international challenges of petroleum industry in russia in the period of sanctions (artykbaev et al., 2020; karatayev et al., 2016; fishman, 2017; kilicarslan, 2019; karatayev and hall, 2020). another part of the literature provides different scenarios for the future production of oil and gas in russia by the intensive use of production and consumption data, therefore putting rather less emphasis on the political aspects of supply and demand management (zaynutdinov, 2015; afesorgbor, 2019; peksen, 2019; yermekbayev et al., 2020). some of the recent literature deals with the international prospects of the oil and gas policies of russia, but they also contain relevant data on the development of the domestic energy policy (neuenkirch and neumeier, 2015; tsaurai and ngcobo, 2020; meynkhard, 2020; movkebayeva et al., 2021). the approach used in these studies is different in a sense that the focus is only on russia and the interconnection of political and economic issues in the domestic arena (mikhaylov and sokolinskaya, 2019; bimbetova et al., 2019; ogneva, 2018; alekseev et al., 2019; movkebayeva et al., 2020). there is a need to reemphasize the importance of the political and economic embeddedness of russia concerning its petroleum industry in the period of sanctions and covid-19 pandemic. compared to these studies, this article extends the research to sanction and covid-19 pandemic period as well and provides the latest data on the issues discussed here. moreover, this paper analyses existing policies and policy challenges of petroleum industry by contextualizing them with historical and political factors. beyond the traditions of oil and gas sectors influencing energy choices, understanding organizational dynamics and the role of domestic political powerhouses in economic decision-making strengthens the human elements of energy policy analysis. in the following sections, the paper aims to provide a reliable assessment for policy makers and all interested parties on the domestic prospects and challenges of petroleum industry in the period of sanctions and covid-19 pandemic. with this overview, saiymova, et al.: russia’s petroleum industry in the period of sanctions and covid-19 pandemic: a review and analysis international journal of energy economics and policy | vol 11 • issue 5 • 2021 485 it will be possible to identify the present state and the future needs of the russia’s petroleum industry. the significant social and economic changes such as industrialization, modernity, and the widespread use of information and communication technologies offer a new picture on the internal dynamics of russia. given the current circumstances provided by the partial elimination of the sanctions, the necessity of a comprehensive assessment on the performance of the russia’s petroleum sector appears relevant. 2. method and materials there has been a large number of studies under the title of sanctions, some of them present theoretical foundation, purposes and principles of the sanctions. an overview of previous studies in in introduction and literature review shows that although different quantitative methods have been used to analyze the effects of the sanctions. to address the scientific and research tasks related to petroleum industry in the period of sanctions and covid-19 pandemic, we used the analysis of classical political economy of energy, which study energy resource production, consumption, export, import, storage in relation to governance, law, regulations, state management and public policy. the political economy analysis seeks to understand both the political and the economic aspects, and how these combines to affect patterns of power and vulnerability. vulnerability and power are therefore analyzed as a political and economic process, in terms, for instance, of neglect, exclusion or exploitation, in which a variety of groups and actors play a part. traditional concepts of political economy have focused on top down, macro-level approaches that examine systems and its rules. more recently, it was emphasized the need for a bottom up, micro-level, game theory approach. both these macro and micro approaches have been incorporated into politics of development framework. the importance of understanding political processes and political systems is also central to any political economy analysis. new political economy and drivers of change, politics of development frameworks incorporate inter-disciplinary analysis examining how economic, social and cultural systems interact with the political system and how their interactions impact on countries development. they also look at competing rules of games in formal and informal institutions; shifting coalitions that contribute to or prevent state collapse; state capacity, authority and legitimacy. these factors are particularly important in analyzing resource-rich states, where state capacity is often weak and informal practices prevalent. in addition to the descriptive analyses, a correlation analysis was performed to establish potential relationships between the study variables, with significance parameters: p < 0.05, p < 0.01, and p < 0.001. all statistical analyses were performed using spss (statistical package for social sciences, version 24.0. 3. sanctions and covid-19 crisis: impact and state support 3.1. technology export ban sanctions prohibit the sale, supply, transfer, export, and financing of equipment for oil production in deep water, shale formations, and above the arctic circle. by the time sanctions were adopted, foreign companies have already been prohibited from holding licenses in the russian arctic waters. however, their participation through service contracts with rosneft’ and gazprom was essential for active development of arctic petroleum resources offshore. without access to foreign equipment, expertise, and finance, it falls on rosneft’ and gazprom to conduct all exploration and production work, which they might not be prepared to do in the short-term. despite strong state control of russian arctic offshore resources, both government and industry agree that state companies need the expertise and technology of foreign partners. overall, experts estimate that when sanctions were imposed the development of russian offshore resources had between 80 and 90% dependency on import technologies. in 2015, gazprom, novatek, and rosneft’ requested the postponement of their existing licenses, citing sanctions, low oil prices, and difficulty in accessing finance. rosneft’ requested the biggest number of such postponements. while gazprom was developing expertise in offshore projects through prirazlomnaya, rosneft’s projects relied heavily on western partners and its operations were arguably affected more. thus, for example, when exxonmobil suspended its cooperation with rosneft’ at the pobeda field despite a significant discovery, further development at the field was postponed. delays in production are costly and problematic in the oil and gas industry, but it appears that the first steps are being made in attempts to revitalize the rosneft’s oil and gas ambitions. in 2019, it was announced that rosneft’ is going ahead alone at the license block in the kara sea, east of novaya zemlya. while previously drilling was done using the norwegian-built west alpha rig, it is not clear from publicly available reports which rig rosneft’ has been using in recent years. moreover, while rosneft’s partnerships with statoil and eni for offshore development in the okhotsk barents seas are on hold, there seems to be no change in long-term strategic cooperation. close cooperation also continues with regards to the onshore arctic fields, in which statoil holds a 33.33% stake. as the contractual arrangements were made before the sanctions, the field is located just south of the arctic circle, and onshore, such cooperation is exempt from both russian and eu restrictions. while sanctions hampered cooperation with western companies for shallow-water drilling, they did not affect any deepwater developments, as western partners also did not have established technologies for such drilling. the equipment ban has not resulted in the complete abandonment of petroleum projects but has rather led to delays and, consequently, the use of asian equipment and the accelerated development of domestic technologies. nevertheless, it is still premature to state that the lack of access to western technologies was substituted, especially since the current oil price climate puts any new production under question in the near-term. the lack of public access to technical assessment documents and environmental assessments of substituted technologies does not help the public scrutiny of their safety and adequacy for oil and gas industry. 3.2. foreign capital ban another substantial factor potentially contributing to the halt of rapid development in petroleum industry is restricted access to foreign capital imposed by the sanctions. at the dawn of the imposition of sanctions, experts predicted that restriction of foreign saiymova, et al.: russia’s petroleum industry in the period of sanctions and covid-19 pandemic: a review and analysis international journal of energy economics and policy | vol 11 • issue 5 • 2021486 capital would be more detrimental to petroleum development than the technology export ban. this is further exacerbated by the low oil prices and high costs of production. overall, some petroleum development projects in the were indeed postponed after the imposition of sanctions; currently the level of foreign direct investment is low and back to level of beginnings of 1990s (figure 1). however, it would be unfair to attribute this solely to the sanctions regime. a number of other factors contribute to the downshift in exploration and production activities, including low oil prices, high environmental risks, and lack of reliable technologies. state support for the project has been unprecedented, starting with putin’s order to liberalize the lng export market, effectively limiting gazprom’s monopoly. in addition to tax breaks, the yamal lng project has also received substantial infrastructure support, such as the construction of the sabetta port and airport, and the launch of icebreaking and lng tanker fleets. while yamal lng is exporting substantial volumes gas to, inter alia, japan and the uk, the tax breaks it receives are substantially high. further, yamal lng also receives large direct subsidies from the national welfare fund (nwf). thus, in 2015, a sum of usd 2.3 bln was transferred to yamal lng (russia’s “anti-crisis” na, 2015). this is not a unique occurrence – after sanctions were adopted, nwf also provided finance for rosneft’. 3.3. sanctions’ effects on economy energy sanctions have had considerable reduction of russia’s gdp annual growth rate (figure 2). energy sanctions lead to budget deficit due to the significant dependence of the government’s public budget (about 50%) on oil revenues. the seigniorage and borrowing from central bank ss an important tool for financing government budget deficit due to the economic recession and inadequate tax revenues in oil sanction conditions. because of the energy sanctions, the inflow of the government-owned foreign currencies due to oil export drops and then, the ability of central figure 1: russia’s foreign direct investment, 1994-2020 figure 2: russia’s gdp annual growth rate, 1994-2020 bank for managing the exchange market which is in the form of managed floating regime decreases and ultimately the exchange rate rises and domestic currency is devaluated. an increase in the exchange rate, on the one hand, will raise importation costs and then the consumer price index and production costs and ultimately decrease all kinds of imports. on the other hand, it increases the competitiveness of domestic products against foreign products, thus, raising non-oil export and partly offsets the devaluation of the domestic currencies. russia’s massive petroleum industry needs a huge amount of foreign investment and a high level of technology because oil fields are often in the second half of their lives and face severe drops in pressure and there are no adequate internal resources for financing projects. furthermore, the international oil companies are very risk-averse due to the long-run and significantly expensive oil projects and to the uncertainty, so that the oil sanctions cause their withdrawal from russian oil projects which reduce foreign investment and the level of technology in the oil industry, and ultimately reduce oil production and value-added activity that is the main component of gross domestic products. the result of the oil sanctions on gross domestic products depends on the final consequences of dynamics of oil export, non-oil export, imports and the consumption and investments of the government and households and the sanctions have resulted in a drop in domestic products and the recession. hence, the primary assumptions regarding the effects of energy sanctions in the macroeconomic variables are the decreasing financing, technology and production in the petroleum industry, increasing budget deficit and seigniorage, decreasing inflow of foreign currencies and devaluation of domestic currency, increasing non-oil export and inflation, decreasing imports and gross domestic products. 3.4. covid-19 pandemic impact with the outbreak of covid-19 and further intensification of the recession, the foreign exchange, gold, and stock markets initially experienced a slight decline but then followed an upward trend. the fluctuations in the foreign exchange and gold markets before covid-19 pandemic (february 2020) were not much different from those after february 2020; however, the total stock market index reached its highest level since the foundation of the russia stock exchange and experienced significant growth. although this situation was not very stable and the stock market went through many fluctuations, the fact that the stock market reached its peak during this period of global economic uncertainty is particularly thought-provoking since during this period, due to the fall in oil demand and prices, russia could hardly even sell oil below world prices and the oil revenues fell sharply. in addition, with the closure of many businesses following the covid-19 outbreak, the government tax revenues dropped steeply. moreover, the increase in both health expenditures and livelihood assistance to the people most affected by the outbreak led to a more severe budget deficit in majority of regions of russia. this sequence of events led to the formation of high inflation expectations among the people. thus, encouraged by the government’s protectionist policies in the stock market, the people rushed to invest in the stock market more enthusiastically than before, hoping to make a profit and maintain the value of their assets. the influx of small investors saiymova, et al.: russia’s petroleum industry in the period of sanctions and covid-19 pandemic: a review and analysis international journal of energy economics and policy | vol 11 • issue 5 • 2021 487 into the stock market and the sharp increase in the total market index created a very fragile condition. 3.5. russia’s state support our correlation analysis showed that both sanctions regime and covid-19 pandemic had significant impact on petroleum industry especially on exploration and refining sectors (table 1). since 2014, russia has taken a multifaceted approach toward sanctions that has mitigated their impact, especially in the energy sector. actually, russia’s approach has its origins in 1998 when oil prices dipped to about 10 usd per barrel. during this period of low oil prices russia absorbed the value of sharply cutting imports of foreign goods and relying heavily on ruble transactions to reduce costs in the domestic economy, especially in the purchase of equipment and services for petroleum industry development. other major elements of russia’s approach include continued efforts to boost natural gas exports to europe, an increased emphasis on exporting gas to china and elsewhere in asia, and continued efforts to limit competition in the european gas market from other former soviet producers, particularly azerbaijan, kazakhstan, and turkmenistan. another important aspect is financial reserves. in earlier 1990, the russian economy defaulted that same month during a severe slump in oil prices, underscoring to russia the value of building up financial reserves when times are good. during 1998 and 1999, russia’s international reserves were only about 12 usd billion. putting the lesson into practice, russia built up its reserves to 100 usd billion by 2004 and to a peak of nearly 600 usd billion in 2008. as oil prices decreased in recent years, the value of these financial reserves fell from about 500 usd billion in early 2014 by about 140 usd billion by 2015. however, the high starting point meant that russia still had about 360 usd billion, about thirty times the amount of foreign currency reserves held by the central bank in 1998 and 1999. russia’s large buildup in financial reserves in the years leading up to 2014 enabled russia to limit the impact of sanctions by buttressing the financial stability of its banks and providing funds to help offset the large debts of state-owned companies. russia also used its financial reserves to support investment, including in the petroleum industry. stateowned rosneft has particularly benefitted from these funds, as it had incurred considerable debt by buying assets formerly owned by yukos and other entities in previous years. at the same time, russia allowed the ruble to drop sharply to discourage imports and lower the costs of domestic supplies purchased by russian companies. this has worked particularly well in the energy sector, where domestic suppliers of equipment and services have been able to replace imported goods and services at lower costs. many foreign suppliers of goods and services are also required to accept rubles as payment in the energy sector, which lowers costs for russian companies. russian government has further supported its energy sector activities by lowering taxes on oil production operations and oil export duties in recent years. 4. conclusion overall, sanctions have significantly impacted russia’s economy, standard of living, investment capabilities, and even its options to pursue further political or military ambitions in ukraine. however, the russian energy sector—the target of some of those sanctions is doing well. financially, russia suffered the most economic pain in the first year of sanctions, as companies suddenly faced debts denominated in dollars and euros and saw their access to foreign borrowing reduced. at the same time, commodity prices were plunging, creating huge financial losses and a cash crunch, and contracting the economy. however, energy and commodity prices began to stabilize, and russia’s central bank began cutting back its defense of the ruble in 2015, reducing the drain on financial reserves. the russian government gradually resumed some investment, which benefited energy and other commodity development. this was reinforced by growing foreign investment, particularly by european companies. german investment almost disappeared after sanctions were imposed in 2014, but in 2016 germany was second only to china in investment in russia, contributing more than 2 usd billion. the dynamics of russian oil production operations also work favorably. both the value of the ruble and tax rates, including the mineral extraction tax and the export duty, fluctuate in concert with oil prices, helping to keep the economics of oil investment and production relatively stable. according to analysis by the financial times, the return on investment to russian companies for production by standard individual vertical wells in west siberia is similar to or higher than the return before the 2014-2015 price plunge. references afesorgbor, s.k. (2019), the impact of economic sanctions on international trade: how do threatened sanctions compare with imposed sanctions? european journal of political economy, 56, 11-26. alekseev, a.n., bogoviz, a.v., goncharenko, l.p., sybachin, s.a. (2019), a critical review of russia’s energy strategy in the period until 2035. international journal of energy economics and policy, 9(6), 95-102. allen, s.h. (2008), the domestic political costs of economic sanctions. journal of conflict resolution, 52(6), 916-944. andryushkevich, o. (2020). effects of anti-russian sectoral sanctions. herald of cemi. ang, a. (2011), sanctions. international relations. artykbaev, d., baibolov, k., rasulov, h. (2020), stability analysis of fine soils from a road project, m32 samara-shymkent (russiakazakhstan). international journal, 19(76), 205-212. bapat, n.a., heinrich, t., kobayashi, y., morgan, t.c. (2013), determinants of sanctions effectiveness: sensitivity analysis using table 1: petroleum industry in the period of sanctions and covid-19 pandemic petroleum industry sanctions covid-19 pandemic coeff. se p-value coeff. se p-value production 0.64 0.76 0.12 0.73 0.68 0.07*** exploration −0.39 0.10 0.08*** 0.86 0.03 0.06*** refining 0.14 3.12 0.04** 0.78 0.06 0.02** service −0.82 0.17 0.13 −0.33 0.08 0.14 import −0.41 0.13 0.00 0.42 0.02 0.00 export 0.28 0.15 0.00 0.11 −0.17 0.00 ***p<0.01, **p<0.05, *p<0.10 saiymova, et al.: russia’s petroleum industry in the period of sanctions and covid-19 pandemic: a review and analysis international journal of energy economics and policy | vol 11 • issue 5 • 2021488 new data. international interactions, 39(1), 79-98. barrett, s. (1997), the strategy of trade sanctions in international environmental agreements. resource and energy economics, 19(4), 345-361. bimbetova, b., tyurina, y., troyanskaya, m., ermakova, e., orynbassarova, a., skakova, a., agabekova, g. (2019), the impact of international sanctions on national economic regime of target states. academy of strategic management journal, 18(4), 1-9. brooks, r.a. (2002), sanctions and regime type: what works, and when? security studies, 11(4), 1-50. brzoska, m. (2015), international sanctions before and beyond un sanctions. international affairs, 91(6), 1339-1349. chesterman, s., pouligny, b. (2003), are sanctions meant to work? the politics of creating and implementing sanctions through the united nations. global governance: a review of multilateralism and international organizations, 9(4), 503-518. chikunov, s.o., ponkratov, v.v., sokolov, a.a., pozdnyaev, a.s., osinovskaya, i.v., ivleva, m.i. (2019), financial risks of russian oil companies in conditions of volatility of global oil prices. international journal of energy economics and policy, 9(3), 18-29. dreyer, i., popescu, n. (2014), do sanctions against russia work? european union institute for security studies (euiss). drezner, d.w. (2011), sanctions sometimes smart: targeted sanctions in theory and practice. international studies review, 13(1), 96-108. early, b.r. (2015), busted sanctions: explaining why economic sanctions fail. palo alto, california: stanford university press. eaton, j., engers, m. (1999), sanctions: some simple analytics. american economic review, 89(2), 409-414. fishman, e. (2017), even smarter sanctions: how to fight in the era of economic warfare. foreign affairs, 96(6), 102-110. houser, d., xiao, e., mccabe, k., smith, v. (2008), when punishment fails: research on sanctions, intentions and non-cooperation. games and economic behavior, 62(2), 509-532. kaempfer, w.h., lowenberg, a.d. (2007), the political economy of economic sanctions. in: handbook of defense economics. vol. 2., ch. 27. netherlands: elsevier. p867-911. karatayev, m., hall, s. (2017), integration of wind and solar power in kazakhstan: incentives and barriers. in: sustainable energy in kazakhstan. milton park: routledge. p65-89. karatayev, m., hall, s. (2020), establishing and comparing energy security trends in resource-rich exporting nations (russia and the caspian sea region). resources policy, 68, 101746. karatayev, m., hall, s., kalyuzhnova, y., clarke, m.l. (2016), renewable energy technology uptake in kazakhstan: policy drivers and barriers in a transitional economy. renewable and sustainable energy reviews, 66, 120-136. karatayev, m., movkebayeva, g., bimagambetova, z. (2019), increasing utilisation of renewable energy sources: comparative analysis of scenarios until 2050. in: energy security london, united kingdom: palgrave macmillan. p37-68. kilicarslan, z. (2019),the relationship between foreign direct investment and renewable energy production: evidence from brazil, russia, india, china, south africa and turkey. international journal of energy economics and policy, 9(4), 291-298. kreimer, s.f. (1984), allocational sanctions: the problem of negative rights in a positive state. university of pennsylvania law review, 132(6), 1293-1397. lektzian, d., souva, m. (2007), an institutional theory of sanctions onset and success. journal of conflict resolution, 51(6), 848-871. mack, a., khan, a. (2000), the efficacy of un sanctions. security dialogue, 31(3), 279-292. marinov, n. (2005). do economic sanctions destabilize country leaders? american journal of political science, 49(3), 564-576. meynkhard, a. (2020). long-term prospects for the development energy complex of russia. international journal of energy economics and policy, 10(3), 224-232. mikhaylov, a., sokolinskaya, n. (2019), russian banks after sanctions of 2014. orbis, 15(44), 55-65. miller, n.l. (2014), the secret success of nonproliferation sanctions. international organization, 2014, 913-944. mokin, c. (2019), review and analysis of imposed european union and united states international sanctions on ukrainian crisis and russia’s countermeasures. journal of legal, ethical and regulatory issues, 22(2), 1-11. movkebayeva, z., khamitova, d., kabdyrova, a., akhmetova, a., zholtayeva, g., duzelbayeva, a. (2020), an exploratory analysis of socio-legal factors related to the distance education learning environment: the case of disabled learners in kazakhstan. journal of legal, ethical and regulatory issues, 23, 1-10. movkebayeva, z., khamitova, d., zholtayeva, a., balmagambetova, v., balabiyev, k. (2021), factors influencing the legal regulation and management of education system in kazakhstan: a review and analysis. problems and perspectives in management, 18(4), 14-24. nardin, l.g., balke-visser, t., ajmeri, n., kalia, a.k., sichman, j.s., singh, m.p. (2016), classifying sanctions and designing a conceptual sanctioning process model for socio-technical systems. the knowledge engineering review, 31(2), 142. neuenkirch, m., neumeier, f. (2015), the impact of un and us economic sanctions on gdp growth. european journal of political economy, 40, 110-125. neuenkirch, m., neumeier, f. (2016), the impact of us sanctions on poverty. journal of development economics, 121, 110-119. newnham, r.e. (2015), georgia on my mind? russian sanctions and the end of the rose revolution. journal of eurasian studies, 6(2), 161-170. nossal, k.r. (1999), liberal-democratic regimes, international sanctions, and global governance. globalization and global governance, 1999, 127-149. ogneva, v. (2018), problems of relations between russia and european union under conditions of sanctions. the european proceedings of social and behavioural sciences. pape, r.a. (1997), why economic sanctions do not work. international security, 22(2), 90-136. paternoster, r., saltzman, l.e., waldo, g.p., chiricos, t.g. (1983), perceived risk and social control: do sanctions really deter? law and society review, 17, 457-479. peksen, d. (2019), when do imposed economic sanctions work? a critical review of the sanctions effectiveness literature. defence and peace economics, 30(6), 635-647. portela, c. (2005), where and why does the eu impose sanctions? politique européenne, 3, 83-111. portela, c. (2010), european union sanctions and foreign policy: when and why do they work? vol. 64. milton park: routledge. rasoulinezhad, e. (2016), investigation of sanctions and oil price effects on the iran-russia trade by using the gravity model. vestnik st petersburg university mathematics rivotti, p., karatayev, m., mourão, z.s., shah, n., clarke, m.l., konadu, d.d. (2019), impact of future energy policy on water resources in kazakhstan. energy strategy reviews, 24, 261-267. schwartz, r.d., orleans, s. (1967), on legal sanctions. the university of chicago law review, 34(2), 274-300. tostensen, a., bull, b. (2002), are smart sanctions feasible? world politics, 54(3), 373-403. tsaurai, k., ngcobo, l. (2020), renewable energy consumption, education and economic growth in brazil, russia, india, china, south africa. international journal of energy economics and policy, 10(2), 26-34. saiymova, et al.: russia’s petroleum industry in the period of sanctions and covid-19 pandemic: a review and analysis international journal of energy economics and policy | vol 11 • issue 5 • 2021 489 veebel, v., markus, r. (2015), lessons from the eu-russia sanctions 2014-2015. baltic journal of law and politics, 8(1), 165-194. wen, j., zhao, x., wang, q.j., chang, c.p. (2020), the impact of international sanctions on energy security. energy and environment,  32(3), 458-480. white, n.d., abass, a. (2006), countermeasures and sanctions. oxford: oxford university press. yermekbayev, a., khairullayeva, v., iztayeva, v., zhuztayeva, b., doszhanova, a. (2020), relations between turkey and russia in the context of energy partnership. international journal of energy economics and policy, 10(4), 166-171. zaynutdinov, r.r. (2015), russia and europe under sanctions: problems of energy development. international journal of energy economics and policy, 5(2), 415-421. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 2 • 2023484 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(2), 484-488. carbon tax and environmental quality in south africa sanderson abel1,2*, julius mukarati1, leward jeke1, pierre le roux1 1department of economics, nelson mandela university, port elizabeth, south africa, 2department of agricultural economics and development, midlands state university, zimbabwe. *email: abelsza.mwale@gmail.com received: 15 august 2022 accepted: 11 february 2023 doi: https://doi.org/10.32479/ijeep.13474 abstract carbon taxes are considered an important environmental policy instrument for the improvement of environment quality in developing countries. despite these premises, the implementation of the carbon tax policy in developing countries has lagged behind. the aim of this study is to analyse how carbon tax influence environmental quality and economic performance in south africa. such a country-oriented inquiry is envisaged to have some positive policy implications for the south african economy and other developing nations. the analysis was conducted using a static computable general equilibrium (cge) model of south africa, which was expected to capture the observed structure of south africa’s economy. furthermore, the parameters of the cge equations were calibrated to observed data from a social accounting matrix (sam) for 2015. the results show that environmental tax has negative effects on gross domestic product with the energy sectors which are generally the most polluting sectors suffering higher output losses due to the environmental tax. household consumption is significant reduced by 2.34% due to the reduction in emissions as a result of carbon tax policy. according to the study findings, policy-makers should consider an initial 5% carbon tax policy which may results in achieving reasonably good environmental quality without losing on investment, fixed capital investment and government revenue. keywords: ghg emissions, co2 emission, cge modelling, economic growth, south africa jel classifications: h60, q53, q56 1. introduction south africa has recently been experiencing rapid economic growth which has also been associated with environmental pollution problem. the rising energy demand of fossil fuels and non-renewable sources in the country have triggered the greenhouse gas emissions and carbon emissions. consequently, the effects of the pollution resulting from heavy industry carbonemissions generating activities have had negative effects on the economy of the country. it is generally accepted that pollution brings about huge economic and health costs to the country’s economy (lu et al., 2010, cole et al,. 2005 & dervis et al,. 1982). most countries initiated environmental regulations and tax policies to limit the industries use of coal, oil, and other non-renewable energy sources. hence, the investigation into the efficacy of these policies among countries who have implemented such policies. to control the heavy pollution from the energy industries, the south african government enacted the carbon tax policy designed to ensure safe and healthy environment through effective regulation of the emission of pollution generating activities into the environment. the policy tool is in line with the international labour organization (ilo) recommendation that pollution mitigation and adaptation efforts on climate change are obligatory to reduce its ramifications on the human existence. the south african’s carbon tax bill has the intention of building an effective climate change response and a long-term transition to a climate resilient and lower-carbon economy and society. the bill is envisaged to provide some form of motivation for large emitters of greenhouse gas (ghg) to reduce their emissions. according to the bill, the rate of the carbon tax on ghg emissions must be equal to r120 (at 7.05 usd) per ton of carbon dioxide. furthermore, in order to ensure a smooth transition to a low carbon economy, this journal is licensed under a creative commons attribution 4.0 international license abel and roux: carbon tax and environmental quality in south africa international journal of energy economics and policy | vol 13 • issue 2 • 2023 485 a number of transitional tax-free allowances were suggested (department of environmental affairs, 2019). environmental tax is believed to be an effective measure to build low-carbon and sustainable economies. however, the appropriate and desired tax level is still debatable and inconclusive. other studies argue that the tax level should be sufficiently higher to meet the emission target (de elzen et al., 2007), yet other studies state that the tax level should be equal to the social cost of carbon (tol, 2005). studies by floros and uvlacho (2005) confirmed that carbon tax could slow down climate warming, yet lee (2008) argue that the tax does have negative effects on global warming. this, however, doesn’t mean that a carbon tax in south africa would not have significant effects on the economy. most studies on the impact of carbon tax applied partial equilibrium and assumed competitive markets (pearce, 1991). the current study differs from previous studies by applying a multisectoral general equilibrium model for energy and environmental policy analysis for the modelling of carbon tax. the effects of carbon tax on the economy and emissions are analysed separately as carbon tax could change the structure of income distribution in the economy (garidzirai, 2020; putra et al., 2021; hieu, 2022). even though it has been established that the climate change has a severe impact on the society, a limited number of studies exist regarding this matter in the south african context. it is thus very important to have an integrated assessment of the impact of environmental policy on the south africa economy. apart from the contribution to literature in the area of climate change, a country-oriented inquiry such as the current study is essential for more targeted policy intervention in the country and other developing nations. therefore, the aim of the study is to investigate the impact of carbon tax on inclusive growth and environmental quality in south africa. in order to achieve this, the study will analyse the cumulative effects of the tax levied on energy commodities by adopting an environmental static cge model for south africa and apply different degrees of carbon tax into the economy. the rest of the paper is organised as follows: section 2 provides literature review, section 3 outlines data and simulation techniques. section 4 analyses results and the section 5 provides conclusion and recommendations. 2. literature review the relationship between the environment and economic development are fundamental, and as a result, the issue of climate change has captivated scientific interest in both developing and developed countries. the scientific evidence in this matter is illustrated by the various studies ((zafeiriou and azam, 2017; zou, 2018; park et al., 2018; wier, 1998; haseeb et al., 2019; agboola and bekun, 2019). these studies empirically tested the relationship between several economic drivers and carbon dioxide (co2) emissions and hence examined the concept of environmental kuznets curve (ekc) using different approaches, time periods and different countries or regions. serdeczny et al. (2016) warned that in the sub-saharan african region the consequences of climate change will be experienced in numerous ways through both natural and human systems. they maintained that the prognoses for region point to a warming trend in the inland subtropics; repeated occurrence of extreme heat events; increasing aridity; and changes in rainfall. environmental taxes are an efficient policy instrument to decrease ghg emissions and enhance environmental protection. these environmental taxes and subsidies also do have the effect of generating revenues or new public expenses that can be included in wider projects of greening the public intervention in the economic system. despite these premises, the actual implementation of the carbon taxes in developing countries has often lagged behind their full potential (ieep, 2014; eea, 2016). in some cases, their design and contents have influenced their effectiveness and impact, which, to date, have been relatively small, leading to marginal changes in the fiscal system. in other cases, the shrinking of environmental tax bases and the non-increase of nominal rates have provoked a progressive downward tendency of revenue shares ( strout, 1985; kosonen, 2010; oecd, 2017). in south africa, carbon taxes which were explicitly introduced for environmental purposes represent a very insignificant share of total environmental tax revenues, while no resource tax is reported in the database. more recently, environmentally-related concerns increasingly influenced the implementation and design of new instruments – as in the case of the auctioning of tradable permits. the effectiveness of the carbon-tax was studied by many authors, and the results differ according to the impact and objectives. the study joins the pigouvian tax is implemented on those goods which create negative externalities; the main aim of such taxes is to make the price of a good equal to social marginal costs and create socially efficient resource allocation tax theory, which deals with the environmental charges by adding the carbon-tax into total charges. a number of empirical studies have been carried out in both developing and developed countries to assess the impact of carbon tax on the economy (forsund, 1988; copeland at al., 1994, jorgenson and wilcoxen, 1990; reinert and roland-holst,2001& levinson , 2004). recently karen fisher-vanden and ian sue wing (2007) employed a cge simulation of the chinese economy for climate policy analysis. the authors constructed an analytical model to show that efficiency-improving and quality-enhancing r&d have opposing influences on energy and emission intensities, with the efficiencyimproving r&d having an attenuating effect and quality enhancing r& d having an amplifying effect. they found that the balance of these opposing forces depends on the elasticity of upstream output with respect to efficiency improving r&d, the elasticity of downstream output with respect to upstream quality enhancing r&d occurring upstream, and the relative shares of emissions intensive inputs in the costs of production of upstream versus downstream industries. they construct a theoretical model in which there are two industries, one upstream (u) and the other downstream (d), where the latter uses the output of the former as an input to production. the numerical economic simulations using the cge model of china’s economy which is calibrated based on econometric estimates of the sectoral impacts. abel and roux: carbon tax and environmental quality in south africa international journal of energy economics and policy | vol 13 • issue 2 • 2023486 callan et al. (2009) studied the effects of tax policies on the carbon and the recycling of the incomes through the distribution of income in the irish republic. the study argued that a tax on the carbon of €20/t co2 would cost the poor households less than €3/week and the richest households of more than €4/week. a tax on carbon is regressive; therefore, the revenues from taxes are used to increase the social security benefits and the tax credits. the households through the distribution of income can be better without exhausting the revenues from taxes carbon total. beghin et al. (1997) developed a theoretical computable general equilibrium (cge) model (applied in chile 2003) which underlies six country case studies. the research describes the base model specification for a series of six country case studies undertaken at the oecd development centre to analyze the links between growth and emissions, and emissions and trade instruments. the cge model of this research attempts to capture some of the key features relating to environmental emissions. lu et al. (2010) investigated the impact of the tax on carbon for the case of china. by building a model of recursive balance general dynamics, the authors have examined the damping effects of the complementary policies. the authors studied the role of taxes and the effects of damping of the complementary policies by building a model of recursive balance general dynamics. the simulation results identified that the carbon-tax is an effective political tool because it can reduce the pollution level by mitigating the carbon level. the dynamic egc analysis proves that the impact of the carbon-tax on gdp growth is relatively small, while the reduction in carbon emissions is relatively large. robinson (1990) developed a two-component general equilibrium framework to evaluate the efficiency of two policy instruments pollution taxes and government pollution cleaning in an economy where pollution is treated as a public good. the first component is a cge model which incorporates pollution and pollution cleaning. pollution is generated as a fixed-proportions by product of certain production activities and enters the households’ utility functions as a public good. pollution cleaning is undertaken by the government and financed via pigouvian taxes. for an exogenously determined pollution cleaning and specified tax rate, the solutions of the cge model satisfy the market equilibrium conditions but are not welfare maximizing. this happens because the amount of the public good, pollution and its price, the pigouvian tax, are not optimally determined, i.e. they do not maximize social welfare. using an iterative nonlinear optimization procedure (the second component), robinson maximizes the social welfare function corresponding to the economy simulated in the cge model over the values of the policy instruments. since his cge model contains only one consumer, the social welfare function is equivalent to the representative consumer’s utility function. based on the literature review, there is overwhelming scientific evidence about the effects of co2 emission on climate change. carbon emissions have been considered a grim global threat which demands an urgent global response. the most worrying matter is that air pollution is not only affecting mpumalanga only, but the satellite data shows that the whole country is affected by the pollution which blows across (meth, 2018). as raised by the department of environmental affairs (2019), the concern is that climate change caused by the impact of the air pollution, as indicated, continues to negatively impact the south african economy directly and indirectly, thus posing a threat to people’s livelihoods. it has been estimated that more than 53% of south african citizens are largely affected by climate change. this indicated a high level of vulnerability and the extent to which people’s livelihoods were threatened mainly due to hunger and drought posed by climate change. this study therefore seeks to analyse the macroeconomic effects of limiting carbon emissions by measuring the economic gains and loss on the carbon tax policy 3. methodology the above-mentioned studies have used several environmental techniques to analyse the effects of carbon tax policy. in this study, a macroeconomic approach was chosen. the cge model adopted for this study comprises of three main modules which are the production module, foreign account module, domestic demand module and the final demand module with a nested structure consisting of constant elasticity of substitution production. total sectoral output is determined by value-added and energy which are composed of intermediate input from energy and non-energy input. as in li and masui (2018), the energy input is disaggregated into electricity inputs and fossil energy. the consumption of different fossil fuels is used to calculate carbon emissions. the cge model was calibrated using the general algebraic modelling system (gams) language which was solved using the mixed complimentary programming (mcp) problem. scale and share parameters were captured in a microsoft excel file which is used into gams via the data exchange (gdx) file. using this model, two carbon tax rates (5% and 10%) were simulated in line with the department targets, and these carbon tax rates were calculated domestic production valued added & energy pollutant labour capital& energy capital energy electricity fossil fuel coal oil& gas coal co2 oil gas oil co2 gas co2 non-energy input figure 1: production structure in cge adopted from li and masui (2018) abel and roux: carbon tax and environmental quality in south africa international journal of energy economics and policy | vol 13 • issue 2 • 2023 487 by multiplying the exogenous carbon tax with the carbon content per unit of domestic production (figure 1). the dataset used for this study is the internal food policy research institute (ifpri) social accounting matrix for 2015. the model parameters are specified based on previous studies and empirical literature. for the purposes of this study, the paper adopted the shared socioeconomic pathway framework based on o’neill et al., 2014 to construct modeling scenarios based on different carbon tax levels. these scenarios include business as usual, low carbon tax rates and high carbon tax rates, and these are designed to assess the policy impacts of envisaged environmental protection act. since carbon dioxide emissions vary among different economic sectors, the energy sector is disaggregated to have a deeper understanding of the policy implication especially on energy generation sectors which are the main emitters of carbon dioxide. 4. results and discussion using the ifpri south africa cge model, the impact of carbon tax as an environmental policy are examined from the different policy simulations. this section presents the results obtained from different policy simulations carried out using cge modelling designed in this study. the simulations carried out are based on ifpri sam of south african economy. table 1 shows the simulation results of the policy impacts on the macroeconomic indicators, including gdp, household consumption, government consumption, export, and import. the numbers in the brackets are the percentage changes compared to the bau scenario. to capture the economy-wide effects of the carbon tax policy, a 5%and 10%-unit carbon tax is imposed on the model where the unit of carbon tax is calculated by multiplying the exogenous carbon tax with the carbon content per unit domestic production. changes in co2 emission is given by the difference between the baseline value and the simulated value and the effects of the tax are for the short run. table 1 shows the impact of carbon tax on carbon emissions and effects on macroeconomic variables. the results showed that the imposition of carbon dioxide tax reduces carbon dioxide emissions, which is a good move towards environmental sustainability. however, the reduction in carbon tax is also associated with a decrease in domestic production, real and nominal gdp and household consumption. a reduction in carbon emission by 1.42% leads to a reduction in real gdp by 1.17% while a 2.75 reduction in carbon emissions reduces real gdp by 2.45%. this reduction in carbon emission due to the imposition of carbon tax will reduce household consumption 2.34% and at 4.39 %. the only noticeable positive change was observed in government revenue and investment. the study results showed that household consumption decreased by 2.34% at 5% carbon tax and at 4.39% at 10% level of carbon tax from the baseline. as the tax rate increases, welfare is decreased due to loss in household consumption and an increase in household tax by almost 2%, which is a major setback to inclusive growth which is a major policy objective for national development plan (ndp) 2030. more specifically, the results showed that the imposition of carbon tax on domestic production sectors reduce the carbon emissions. a 5% and 10% simulation indicate that imposition of carbon tax result in lower carbon emissions, domestic production, exports, energy sector production, real gdp, household consumption share of gdp (table 1). however, the government revenue is positive in all the simulations in 5% tax (15.44) and 20.835 at 10% carbon tax level. investment share of nominal gdp is positive (0.43%) at 5% tax and 0.09% at 10% tax which showed that investment is higher at low level of carbon tax than when the carbon tax becomes higher (10% carbon tax). the results showed that the imposition of successively higher carbon tax (5%and 10%-unit carbon tax) result in 1.42%, and 2.57% reduction in carbon emissions respectively. however, these reductions in carbon emissions are associated with significant decrease in economic performance. real gdp decreased by 0.37%, and 1.75%. output in the energy sector which are generally the major polluters, decreased by 4.39% and 6,88% respectively exports decreased by 4.74% and 5.77% while household consumption decreased by 2,34% and 4.39%, respectively. household consumption as a share of gdp decreased by 0.45% and 0,81% respectively. however, government revenue increased by 15.44% and 20.83%. 5. conclusions and recommendations the purpose of this study was to adopt an environmental cge model to analyse the impacts of an environmental tax on the south africa economy. the results from this study are in line with the principles of environmental management, especially the polluter pay principle. this study suggests that an initial carbon tax can be applied for the central purpose of reducing the rate of growth of carbon emissions. the study findings provide several suggestions and message to policy makers, who are considering carbon taxation policy together with economic development. this study serves as a guide to selection of more feasible and appealing environmental policies. from the results, the increase in carbon tax leads to a decrease in the level of pollution generated by the energy sector. however, the decrease in carbon emissions is associated with decreased table 1: empirical results sectors % change from bau 5% carbon tax 10% carbon tax carbon dioxide emission –1.42 –2.75 domestic production –0.377 –1.75 energy sector output –4.388 –6.882 real gdp –1.172 –2.450 government revenue 15.44 20.83 household consumption –2.339 –4.386 investment 0.431 0.09 exports –4.740 –5.774 household tax 1.983 2.689 household consumption share of gdp –0.452 –0.810 source: author’s calculations, based on simulation results abel and roux: carbon tax and environmental quality in south africa international journal of energy economics and policy | vol 13 • issue 2 • 2023488 production, which translates to a significant decrease in real gdp. this study recommended that for analysis of the full distributive and accumulative impacts of the environmental policy the model should be extend to include other pollutants associated with environmental pollution such as nitrogen and sulphur dioxide. references agboola, m.o., bekun, f.v. (2019), ‘does agricultural value added induce environmental degradation? empirical evidence from an agrarian country. environmental science and pollution research international, 26(27), 27660-27676. beghin, c.j., roland-holst, d., van der mensbrugghe, d. (1994), trade liberalization and the environment in the pacific basin: coordinated approaches to mexican trade and environmental policy. oecd paper. paris, france: the organization for economic cooperation and development. beghin, c.j., roland-holst, d., van der mensbrugghe, d. (2005), trade and the environment in general equilibrium: evidence from developing economies. germany: springer. beghin, c. j., roland-holst, d. and van der mensbrugghe, d. (1994). trade liberalization and the environment in the pacific basin: coordinated approaches to mexican trade and environmental policy. oecd paper.  bergman, l. (1993), general equilibrium costs and benefits of environmental policies: preliminary results based on swedish data. memo. bullard, c.w 3rd, herendeen, r.a. (1975), the energy cost of goods and services. energy policy, 3(4), 268-278. callan, t., k. coleman and j.r. walsh, (2006). “assessing the impact of tax/transfer policy changes on poverty: methodological issues and some european evidence”, in olivier bargain (ed.) microsimulation in action. research in labor economics, emerald group publishing limited, 25, pp.125-139. copeland, b.r., taylor, m.s. (1994), north-south trade and the environment. quarterly journal of economics, 109, 755-787. department of environmental affairs. (2019), south africa’s 3rd biennial update report to the united nations framework convention on climate change. pretoria: department of environmental affairs. dervis, k., de melo, j., robinson, s. (1982), general equilibrium models for development policy. cambridge: cambridge university press. doz, y. l., & kosonen, m. (2010). embedding strategic agility: a leadership agenda for accelerating business model renewal. long range planning, 43(2-3), 370-382. eea, 2016. vector borne diseases. european environment agency. https://www.eea.europa. eu/data-and-maps/indicators/vector-bornediseases-2/assessment. fankhauser, s., and tol, r. (2005), on climate change and economic growth: resource and energy economics, 27(1), 1-17. fisher-vanden k., wing is., lanzi e., and popp d., (2013). modeling climate change feedbacks and adaptation responses: recent approaches and shortcomings, climatic change, 117(3), 481-495. floros, n., vlachou, a. (2005), energy demand and energy-related co2 emission in greek manufacturing: assessing the impact of a carbon tax. j, energy economics, (27): 387-41. forsund, f.r., strom, s. (1988), environmental economics and management: pollution and natural resources. london: croon helm. garidzirai, r. (2020), time series analysis of carbon dioxide emission, population, carbon tax and energy use in south africa. international journal of energy economics and policy, 10(5), 353-360. haseeb, a., xia, e., saud, s., ahmad, a., khurshid, h. (2019), does information and communication technologies improve environmental quality in the era of globalization? an empirical analysis. environmental science and pollution research international, 26(9), 8594-8608. hieu, v.m. (2022), influence of green investment, environmental tax and sustainable environment: evidence from asean countries. international journal of energy economics and policy, 12(3), 227-235. ieep, 2014: study supporting the phasing out of environmentally harmful subsidies: annexes to final report october 2012 project number: 07.0307/2011/611259/env.f.1 jorgenson, d.w., wilcoxen, p.j. (1990), intertemporal general equilibrium modeling of u.s. environmental regulation. journal of policy modeling, 12, 715-744. lee, h., roland-holst, d. (1993), international trade and the transfer of environmental costs and benefits. oecd development centre technical papers, no. 91. paris: the organization for economic cooperation and development. levinson, m.a., taylor, s. (2004), trade and environment: unmasking the pollution haven effect. nber working paper no. w10629. lin, b., li, x. (2011), the effect of carbon tax on per capita co2 emissions. energy policy, 39(9), 5137-5146. meth, o. (2018), new satellite data reveals the world’s largest air pollution hotspot is mpumalanga-south africa, greenpeace africa. available from: https://www.greenpeace.org/africa/en/press/4202/ new-satellite-data-reveals-the-worlds-largest-air-pollution-hotspotis-mpumalanga-south-africa [last accessed 2020 jul 08]. o’neill, b.c., kriegler, e., riahi, k. et al., (2014). a new scenario framework for climate change research: the concept of shared socioeconomic pathways. climatic change 122, 387–400. doi: 10.1007/s10584-013-0905-2 oecd (2019), model tax convention on income and on capital 2017 (full version), oecd publishing, paris, doi: 10.1787/g2g972ee-en. park, y., meng, f., baloch, m.a. (2018), the effect of ict, financial development, growth, and trade openness on co2 emissions: an empirical analysis. environmental science and pollution research international, 25(30), 30708-30719. pearce, d. (1991). the role of carbon taxes in adjusting to global warming. the economic journal, 101, 938-948. doi: 10.2307/2233865 putra, j.j.h., nabilla, n., jabanto, f.y. (2021), comparing “carbon tax” and “cap and trade” as mechanism to reduce emission in indonesia. international journal of energy economics and policy, 11(5), 106-111. reinert, k.a., roland-holst, d.w. (2001), nafta and industrial pollution: some general equilibrium results. journal of economic integration, 16(2), 165-179. robinson, s. (1990), pollution, market failure, and optimal policy in an economy-wide framework. working paper no. 559, department of agricultural and resource economics. berkeley: university of california. serdeczny, o., adams, s., baarsch, f., coumou, d., robinson, a., hare, w., schaeffer, m., perrette, m., reinhardt, j. (2017), climate change impacts in sub-saharan africa: from physical changes to their social repercussions. regional environmental change, 17, 1585-1600. stephenson, j., saha, g.p. (1980), energy balance of trade in new zealand. energy systems and policy, 4(4), 317-326. strout, a.m. (1985), energy-intensive materials and the developing countries. materials and society, 9(3), 281-330. wier, m. (1998), sources of changes in emissions from energy: a structural decomposition analysis. economic systems research, 10(2), 99-112. zafeiriou, e., azam, m. (2017), ‘co2 emissions and economic performance in eu agriculture: some evidence from mediterranean countries. ecological indicators, 81, 104-114. zou, x. (2018), ‘vecm model analysis of carbon emissions, gdp, and international crude oil prices. discrete dynamics in nature and society, 2018, 5350308. https://econpapers.repec.org/ras/pto90.htm https://econpapers.repec.org/article/eeeresene/ https://ideas.repec.org/a/spr/climat/v117y2013i3p481-495.html https://ideas.repec.org/a/spr/climat/v117y2013i3p481-495.html https://ideas.repec.org/a/spr/climat/v117y2013i3p481-495.html https://ideas.repec.org/s/spr/climat.html https://doi.org/10.1007/s10584-013-0905-2 https://doi.org/10.1787/g2g972ee-en http://dx.doi.org/10.2307/2233865 tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020370 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 370-375. biogas from cattle dung as a source of sustainable energy: a feasibility study k. abhaya kumar1, prakash pinto2, iqbal thonse hawaldar3*, b. r. pradeep kumar1 1department of mba, mangalore institute of technology and engineering, moodabidri, karnataka, india, 2department of business administration, st. joseph engineering college, mangalore, karnataka, india, 3department of accounting and finance, college of business administration, kingdom university, bahrain. *email: thiqbal34@gmail.com received: 10 june 2020 accepted: 12 september 2020 doi: https://doi.org/10.32479/ijeep.10135 abstract many studies have stated that the usage of traditional cooking fuels like firewood, dung, and coal has caused many unfortunate deaths in india. the alternative fuel sources like lpg and electricity are in scarce and. today, researches in the area of biofuel or bioenergy are of prime interest to many researchers to contribute to sustainable energy sources. bioenergy from cattle dung is one such area, particularly for a country like india where dairy farms is a major supplier of feedstock. in this study, using logistic regression methodology, we have analysed the socio-economic factors influencing the adoption of biogas digesters among dairy farmers in karnataka, india. the study revealed that the number of cattle and family size are the key factors for biogas adoption and poor knowledge of the family size and cattle ratio is the key hurdle. using cross-tabulation and some basic mathematical analysis, we concluded that the optimal number of cattle for one adult in a family is 1. keywords: sustainable energy source, biogas, cattle dung, dairy farmers, socioeconomic factors, india jel classifications: q4, p28 1. introduction the energy crisis and green environment are demanding for a carbon-neutral and efficient source of energy (mohapatro et al., 2014). increasing crude prices has resulted in expensive lpg and firewood has become a costlier source of energy owing to increased demand from industries. biogas is an alternative source of energy for cooking in rural india. harsdorff (2014) and hemme et al., (2003) states that india is the largest producer of milk and cattle dung in the world. biogas is a source of renewable energy generated from the organic wastes of animals. cattle dung is the major source of animal waste used in rural india to generate biogas. in 1950s country had a large number of cattle, however, the production of milk was not self-sufficient. oxen and buffaloes were used in the agricultural fields for the farming process, hence a good amount of dung or animal wastes were available. however, increased use of technology in farming has reduced the dependence on animals in the agricultural fields, which has resulted in the reduced yield of the dung. so the generation of biogas in rural india is decreasing. hence, today biogas from animal waste in rural india is dependent on cattle dung generated at dairy farms. according to mittal et al. (2018), the availability of feedstock is also a major hurdle for the development of biogas energy among households in india. some empirical studies on biogas revealed that cattle dung generated at the dairy farm is the best raw material input for the biogas plant. nandiyanto et al. (2018) suggest, that a combination of dairy farming with a biogas plant is more profitable for rural households. today the indian dairy sector stands first in terms of milk production and contributes 20% of the world’s total production (pant et al., 2019). farmers in india have witnessed many initiatives from the government to boost the milk production in the country, such as key village scheme (kvs), intensive cattle development project (icdp) and operation flood (of) (pandian this journal is licensed under a creative commons attribution 4.0 international license kumar, et al.: biogas from cattle dung as a source of sustainable energy: a feasibility study international journal of energy economics and policy | vol 10 • issue 6 • 2020 371 et al., 2015). dairy enterprise development scheme (deds) was launched in the year 2010 to increase self-employment in the field of dairy farming, this may boost the biogas generation among dairy farmers in india. the development in dairy farming may indirectly contribute to increased biogas usage in the country. smith and sagar (2014) explored the impact of solid fuel pollution on the health of indian women and the girl child., according to gupta and ravindranath (1997), the low-income families of the urban and rural india are forced to use firewood for cooking, the only feasible substitute is biogas. policymakers have to come up with suitable strategies to make this biogas transformation possible. hence, a detailed study on dairy farmers’ perception of biogas and the socio-economic factors deciding biogas is the need of the hour. the aim of this work is twofold; one, to analyze the socioeconomic factors contributing to penetration of biogas plant among dairy farmers in karnataka, india. two, to find out the optimum number of cattle required to meet the cooking energy requirements for different family sizes because singh and sooch, (2004) opined that households in india are not aware of the ratio of family size to cattle requirement. 2. literature review salam et al. (2020) studied the feasibility of biogas generation at the household level in bangladesh. the study states that cattle dung is readily available in rural villages, which could be a great source of material for biogas. yazan et al. (2018) have explored the commercial aspects of biogas using cattle dung and claimed that business model works only for large scale operations which operate with more than 20000 ton per year, and this is the indication of the scale of success for biogas plants in the household levels. narayan et al. (2018) conducted relevant research and argued that the commercialization of biogas in india is not a feasible solution with the present technology, however, financial incentives for dairy farming and direct incentives for household biogas producers may reduce the lpg subsidy burden on the government. nandiyanto et al. (2018) in indonesia, claims that the combination of the dairy business and biogas plant is much profitable rather than just dairy business. a study in the us believes that a farm business with a minimum of 3000 cattle will reach breakeven in the commercialization of biogas and the study also suggests that cooperative biogas plant would yield better results (lauer et al., 2018). mittal et al. (2018) state that the availability of feedstock, supply chain, policy support, and awareness among households are the strong barriers to the growth of biogas generation in india. the demand for milk in india is growing at 7% and the production of milk is growing at 4.4%. this is mainly because of the presence of traditional practices in the sector and poor access to finance (pant et al., 2019; rao, 2017; jadawala and patel, 2017). muvhiiwa et al. (2017) study from the south african perspective states that country is technology-ready and it has enough sources of materials to generate biogas in the rural areas; however, lack of awareness is the major challenge for sustainable development. traditionally farmers in india were using the by-products of their agricultural products as feed for cattle but today many have moved to commercial crops, which has resulted in a reduction of generation of cattle feed. the land available for cattle rearing is also very less (kumar et al., 2016). in india because of the low genetic potential of the cattle, the cost of milk production is high and the milk yield is not satisfactory (kumawat et al., 2016), this may lead to farmers stopping dairy business. hence, the financial incentives of the government will encourage the dairy farming business. food and agribusiness research management (farm) (2015) provided an interesting study, that proper utilization of cattle dung for biogas, direct incentives of the government and financial inclusion from organised banks will make the small dairy farming profitable in india. heubeck and craggs (2015) worked on the energy yield and concluded that a kilogram of cattle manure yielded 0.18-0.25 m3 of methane (ch4). 56m 3 of methane is equivalent to 1 tonne of co2. therefore, methane yield of 400 cattle manures is equivalent to 0.35t of co2/day. bakar et al., 2015 said that biogas kits for dairy farmers are advised as it serves two purposes, i.e. waste management and generation of low-cost energy for households. wahyudi et al. (2015) opine that 67% of poor indonesians have occupations in rural agriculture including livestock farming, this is the potential sector to generate biogas by using dairy sector wastes. keck et al. (2015) studied and reported that in switzerland, the majority of biogas facilities are attached to the dairy or animal husbandry business. in a report of the international labour organization, harsdorff (2014) states that increased dairy farming and biogas generation will add 2 million additional jobs in the biogas plants. for the development of farmer level biogas projects in italy, the government has to think about reframing institutional frameworks with attractive subsidies (carrosio, 2013). ibrahim (2012) have studied the opportunity for green energy in malaysia; the study argues that installing biogas plants in animal farms will give multiple advantages to small scale farmers by reducing their fuel and power costs. abdulsalam and mohammed (2012) provided an interesting fact that in nigeria, elephant dung is recommended to use as an alternative source of material for cattle dung based biogas plants; however, the challenge is that elephant is a wild animal. from indian perspectives, technological advancement and a planned supply chain management are necessary for commercialization of bioenergy generation using cattle dung (kumar et al., 2012); hence, it is recommended to use biogas kits in the household levels. bond and templeton (2011) informs that among developing countries, india and china are the major biogas digester users; the major source of material for this digester is cattle manure. india has immense opportunity to increase the use of biogas digesters, particularly in the household segment using cattle dung, this would increase the opportunity for employment and contributes for environment-friendly sustainable growth (bhol et al., 2011). gebrezgabher et al. (2010) study reported that by 2020 all dutch dairy farms and processors will become energy self-sufficient with the combination of biogas, wind and solar; this is because of the increase in the volume of cattle dung and dairy business. a study by ali et al. (2008) in fisheries of bangladesh proved that the survival rate of fishes using a combination of biogas slurry and raw cattle dung is better than the use of raw cattle dung or other supplements. california is technologically ready to produce biogas from dairy manure; however, the small scale of dairy’s in kumar, et al.: biogas from cattle dung as a source of sustainable energy: a feasibility study international journal of energy economics and policy | vol 10 • issue 6 • 2020372 the region is a challenge (krich et al., 2005). singh and sooch (2004) mentioned that biogas from cattle dung will become a great alternative for natural gas in rural india; however, lack of knowledge and awareness of the ratio of family size to biogas plant size is the major hurdle to harness the full potential. nagamani and ramasamy (1999) state that despite improved technology for biogas in india, lack of livestock followed by construction defects are the major hurdles for the success of biogas plant in household levels. 3. data and methodology in this cross-sectional data study, 231 dairy farmers from the karnataka state of india were randomly interviewed. state karnataka is the 8th largest state in india; there are 30 districts with a total area of 1, 91,791 km2. department of cooperation (2018) informs that there are 14,256 functioning dairy cooperatives societies (dcs) and 2.46 million, dairy farmers actively work in the state. a personal and telephonic interview method is used to gather data from dairy farmers. among 231 dairy farmers, 181 are biogas users and 50 are not biogas users. for a dichotomous dependent variable (biogas user or not), to analyze its dependency on socioeconomic factors (age, religion, education level, number of cattle, and land size) binary logistic regression methodology is used. reasons for not adopting biogas plant and the usage of alternative source of cooking energy for these non-biogas users are analyzed. among 50 non-biogas users, 23 mentioned that the quantity of cattle dung is not sufficient to adopt biogas plants for cooking energy. the cross-tabulation, simple average and cross-multiplication techniques are used to obtain the optimal number of cattle requirements for different family sizes. 4. results and discussions 4.1. dairy farmers background and biogas adoption salam et al., 2020 inform that the background of households plays a vital role in biogas plant adoption decision. in table 1, we have shown the background characteristics of dairy farm respondents. among 181 biogas users, 81.20% are hindus, 13.30% are christians and 5.5% are muslims. concerning factor age, there is not much difference between users and nonusers. 39.20% of users and 52% of nonusers fall in the same category of 41-55 age group. education level also plays a vital role in biogas adoption in rural areas, data shows that 35.9% of biogas users are pre metric and 46% of nonusers are metric. post metric, as the education level increases, even the biogas users’ number increases. data proves that biogas usage is more with large size families, 70% of respondents with a family size of 2-4 are not the users of biogas contradictorily only 2.8% of respondents with a family size of 8 and above are the users of biogas. further, the number of cattle factor is interesting as maximum numbers are modal values; the maximum biogas users (28.2%) own 3 cattle and the percentage is reducing on both the sides irrespective of the number increasing or decreasing. finally, 62.4% of biogas users are in the minimum land size category of 0.5-5 acres of land. as the size of the land increases, the number of biogas users is reducing. 4.2. reasons for not using biogas as a source of energy for cooking many studies have mentioned that the availability of cattle dung and lack of awareness about biogas are the major challenges to the growth of biogas usage in india. in this study, all 50 biogas non-users were aware of the concept and economic benefit of biogas. various reasons for not adopting of biogas by these dairy farmers are presented in table 2. for an open-ended question, 46% of respondents said that the quantity of cattle dung is insufficient to meet the cooking energy requirement of the family. the cross-tabulation analysis and an optimal number of cattle for different family size analysis in the last section of this study will address this issue of quantity of cattle dung. table 1: respondents profile respondents classification biogas users non-biogas users 181 50 religion hindu 81.20 72.00 christian 13.30 28.00 muslim 5.50 0.00 age group 25–40 24.90 22.00 41–55 39.20 52.00 56–70 34.80 22.00 above 70 1.10 4.00 the education level of the family head pre metric 35.90 30.00 metric 30.90 46.00 puc/iti 16.00 16.00 graduate 16.00 8.00 postgraduate 1.10 0.00 family size 2–4 55.20 70.00 5–8 42.00 30.00 above 8 2.80 0.00 number of cattle 1 5.00 24.00 2 19.30 24.00 3 28.20 18.00 4 18.20 18.00 5 8.30 10.00 6 7.20 2.00 7 and above 7 13.80 4.00 land size 0.5–5 acres 62.40 50.00 5.5–10 acres 26.00 32.00 10.5–15 acres 5.50 8.00 15.5–20 acres 3.30 4.00 above 20 acres 2.8 6.00 based on primary data table 2: reasons for not using biogas by dairy farmers reasons for not using biogas frequency percent additional man-hour requirement 11 22.0 availability of land 1 2.0 capital requirement 5 10.0 not necessary 1 2.0 not thought about that so far 7 14.0 quantity of cattle dung is not enough 23 46.0 un divided property 2 4.0 total 50 100.0 source: primary data kumar, et al.: biogas from cattle dung as a source of sustainable energy: a feasibility study international journal of energy economics and policy | vol 10 • issue 6 • 2020 373 the next major issue was additional domestic chores. 22% of biogas non-users specifically mentioned additional manpower requirement for processing cattle dung to generate biogas as the reason for non-usage. 14% of biogas non-users gave very light responses as they are aware of biogas however, they have not thought about the installation so far. 10% of biogas non-users said the heavy capital investment is the hurdle for biogas plant installation and this group is particularly looking for attractive incentives from the government agency in the form of subsidy. very interestingly 4% of biogas non-users were not sure about their cattle shed as it belonged to undivided family property. 2% of non-bio gas users were big landowners and they seem to have enough alternative sources available in their agricultural fields to manage their energy requirements of cooking and hence, biogas was unnecessary. the last category 2% of biogas nonusers mentioned that they don’t have sufficient land to place the biogas digesters on their dairy farm. 4.3. need for change in cooking energy and dynamics of cooking energy access for non-bio gas users the pollution caused by burning firewood, dung, coal inside the kitchen is causing more than 1.5 million deaths a year, (rehfuess, 2006). parikh et al. (2016) inform that nearly 840 million families in india still depend on solid fuels like firewood or dung, burning which, is a tremendous health hazard for the women and children in those families. more than 66% of rural families in india still use solid energy sources for cooking and electric stoves could be the better source (panagariya and jain, 2019). women in india spend more than 2 weeks a year to collect firewood for cooking energy and the same is resulting in nearly one million deaths in a year (patnaik and tripathi, 2017). in the year 2005, 364 million rural indians did not have access to electricity and 726 million rural families were using firewood, dung, or coal as their source of energy for cooking. (balachandra, 2011). figure 1 shows that 50% of non-biogas users are using firewood and lpg as a source of energy for cooking and said that firewood is abundantly available and hence, both lpg and firewood are used as cooking energy. 44% of respondents said they use only lpg for cooking. only 3 respondents are purely depending on firewood for their cooking energy requirement. 4.4. factors influencing the dairy farmers to install bio gas plants in this study, the dependent variable is a dichotomous binary variable and the independent variables are continuous or categorical variables. hence, as this data set is not satisfying the assumptions of the normal regression model, we have employed a logistic regression model to analyze the relationship between biogas usage and other socio-economic factors of dairy farmers. biogas user or not user was the dependent variable for the model, where y = 1 if the respondent dairy farmer is the user of biogas and y = 2 if the respondent is not a user of the biogas. an odds ratio is a commonly analyzed statistic in any logistic regression analysis, ratio >1 indicates that the probability of a dependent variable event occurring is more than the probability of an increase in independent variable and vice versa. in our context, if the odds ratio >1, the probability of biogas plant installation is more with an increase in any of the socio-economic variables. a coefficient indicates that after adjustment for all other independent variables in the model, how that particular independent variable will impact the outcome of the dependent variable. wald statistics in logistic regression will test the unique contribution of each independent variable with other independent predictors used in the model (karl, 2020). table 3 shows that socio-economic factors like family size and the number of cattle have significantly contributed to the installation of a biogas plant by dairy farmers in karnataka, india. further odd ratio in table 3 indicates that for an additional family member among dairy farmers, the odds of adapting biogas reduces by 24.1% or in other words the ratio (0.759 < 1) is less than one, hence the probability of biogas plant installation with an increase in the family size of dairy farmers is lower than 1. the odds ratio for independent variable land size shows that the probability of biogas plant installation is greater than 1 (1.042 > 1) for every one-acre increase in the land size of dairy farmers. 4.5. the optimal number of cattle’s requirement for varying family sizes the table shows that 46% of non-biogas user respondents stated that the quantity of cattle dung is the main reason for not installing biogas. we have attempted to make family size and number of cattle requirement analysis to give an optimal cattle number for different size of families. in the data collection process, we have enquired 2 related aspects with biogas users. one, with the current number of cattle, what percentage of cooking energy requirement is satisfied and the other one is to generate 100% of their energy requirement, what is the required number of cattle. the methodology used for the analysis is simple average and cross multiplication. in table 4, computation procedures are neatly explained using column number definitions. column no 1 shows respondents family size, the second column shows the no of cattle owned by the respondents, the third column shows how much cooking energy requirement is met by biogas, the fourth column shows respondents estimation of the number of cattle required to meet 100% of their cooking energy requirement. the fifth column in table 4 shows our estimation of the number of cattle required to meet the respondent’s 100% cooking energy requirement, the sixth column shows the average of our estimation and respondent’s estimation and the last column shows the optimum number of cattle requirements for a family of one member. the same computations source: primary data 6.0 50.0 44.0 0.0 10.0 20.0 30.0 40.0 50.0 60.0 fire wood fire wood and lpg lpg figure 1: alternative sources of cooking energy used by non-bio gas users kumar, et al.: biogas from cattle dung as a source of sustainable energy: a feasibility study international journal of energy economics and policy | vol 10 • issue 6 • 2020374 are done for all 181 responses; the same is shown in the annexure section. the final average of 181 observations in the last column of table 4 shows that the optimal number of cattle requirements for 1 member family is 1; this estimate can be used as the base to compute an optimal number of cattle requirements for different family sizes to meet their 100% cooking energy requirement. 4.6. cattle requirement and available number of cattle’s among respondents – feasibility analysis in table 5, numbers with bold and underlined font are the number of respondents who can install biogas plant, based on the number of cattle requirements in each family size category. on the other hand numbers with italic font style are the number of respondents who are not meeting the minimum number of cattle requirements to manage their 100% of cooking energy demand. cross tabulation shows that among 50 non-bio gas user respondents, 12 are with a family of 2 members, and the optimal number of cattle required to meet their 100% cooking energy demand is 2. hence, 9 out of 12 families of this category can adapt biogas as the number of owned cattle with them is equal to or more than the optimal number. similarly, there are 4 families in 3 family member categories, and 1 family each with family size categories of 4, 5, and 6 who meet the optimum number of cattle requirements. 5. conclusion biogas is one source of bioenergy, which can be a good substitute for traditional sources of cooking energy in india. green environment is looking for sources that can reduce carbon omission and the government agency is also striving to transform the traditional, polluted kitchens to a hazard-free kitchen. our objective in this study was to analyze the socio-economic factor influencing biogas adoption among dairy farmers in karnataka, india and the logistic regression analysis proved that family size and the cattle’s number are the two key factors. data also reveals that the cattle number or dung quantity, additional manpower requirement, and initial capital outlay are the reasons for not installing biogas plants. further, the study found that among 50 non-bio gas user respondents, there are 16 respondents for whom the adoption of biogas is feasible in terms of the number of cattle, however, other mentioned reasons might be a hindrance. references abdulsalam, s., mohammed, j. (2012), production of biogas from cow and elephant dung. global journal of engineering and technology, 5(1), 51-56. ali, m.h., salam, m.a., rashid, m.h., barman, a.c., bashar, m.a. (2008), fish culture in ponds by using bio-gas slurry and raw cow dung in carp polyculture system. journal of agroforestry and environment, 2(2), 151-154. bakar, n.h.b., yusoff, z., said, s.a., amirul, m., bin, r. (2015), the table 4: optimal number of cattle requirement analysis family size (1) no of cattle (2) % energy demand met (3) respondents estimation (4) our estimation (5)=[100*(2)]/(3) average for full family (6) =[ (4) + (5)]/2 optimal no of cattle for 1 member family (7) = (6)/(1) 5 2 50 3.00 4 4 1 3 5 100 4.00 5 5 2 8 3 50 5.00 6 6 1 7 22 100 5.00 22 14 2 4 4 50 3.00 8 6 1 4 3 100 3.00 3 3 1 4 3 80 2.00 4 3 1 8 8 80 8.00 10 9 1 average from 181 response estimations 1 source: authors analysis using primary data table 3: logistic regression output variable coefficient standard error wald p-value odds ratio religion 0.005 0.314 0.000 0.989 1.005 family size −0.276 0.122 5.095 0.024 0.759 age of the family head −0.003 0.015 0.044 0.834 0.997 education level of the head of the family −0.075 0.167 0.199 0.655 0.928 no of cattle’s −0.292 0.109 7.212 0.007 0.747 land size in an acre 0.041 0.032 1.666 0.197 1.042 constant 0.906 1.093 0.687 0.407 2.475 chi-square 21.999 p-value 0.001 source: authors analysis using primary data table 5: family size *no of cattle’s cross tabulation family size no of cattle’s total 1 2 3 4 5 6 7 2 3 1 1 3 2 1 1 12 3 3 4 0 4 0 0 0 11 4 4 4 3 0 1 0 0 12 5 1 3 2 1 1 0 0 8 6 1 0 2 0 0 0 1 4 7 0 0 1 0 1 0 0 2 8 0 0 0 1 0 0 0 1 total 12 12 9 9 5 1 2 50 source: authors analysis using primary data kumar, et al.: biogas from cattle dung as a source of sustainable energy: a feasibility study international journal of energy economics and policy | vol 10 • issue 6 • 2020 375 fabrication of a biogas system to produce methane gas from cow dung. india: technology and innovation national conference. p231-241. balachandra, p. (2011), dynamics of rural energy access in india: an assessment. energy, 36(9), 5556-5567. bhol, j., sahoo, b.b., mishra, c.k. (2011), biogas digesters in india : a review. in: national conference on renewable and new energy systems. odisha: siet. p1-6. bond, t., templeton, m.r. (2011), history and future of domestic biogas plants in the developing world. energy for sustainable development, 15(4), 347-354. carrosio, g. (2013), energy production from biogas in the italian countryside : policies and organizational models. energy policy, 63, 3-9. department of cooperation. (2018), government of karnataka, dairy sector. available from: http://www.sahakara.kar.gov.in/dairy.html. food and agribusiness research management (farm). (2015), making indian dairy farming competitive-the small farmer perspective. yes bank ltd and indian dairy association (ida), 1(1), 1-28. gebrezgabher, s.a., meuwissen, m.p.m., lansink, a.g.j. (2010), costs of producing biogas at dairy farms in the netherlands. international journal on food system dynamics, 1, 26-35. gupta, s., ravindranath, n.h. (1997), financial analysis of cooking energy options for india. energy conversion and management, 38(18), 1869-1876. harsdorff, m. (2014), the economics of biogas: creating green jobs in the dairy industry in india. international labour organization, 1, 1-56. hemme, t., garcia, o., saha, a. (2003), a review of milk production in india with particular emphasis on small-scale producers. international farm corporation network: pro-poor livestock policy, 3(3), 1-58. available from: http://www.worlddairymap.org/media/ pdf/2003milkproductionpakistan.pdf%5cn, available from: http:// www.faoorg/ag/againfo/programmes/en/pplpi/docarc/wp3.pdf. heubeck, s., craggs, d.r. (2015), is biogas technology right for australian dairy farms ? new york: hamilton. ibrahim, c.e., aini, m.n., siti, s.t., syed, h.s.a., kamaruddin, d. (2012), small-scale biogas plant on a dairy farm. malaysian journal of veterinary research, 3(1), 49-54. jadawala, r., patel, s. (2017), challenges of indian dairy industry. indian journal of applied research, 7(10), 9-11. karl, l. (2020), logistic-spss. available from: http://www.core.ecu.edu/ psyc/wuenschk/mv/multreg/logistic-spss.pdf. keck, m., schrade, s., steiner, b. (2015), odour impact of an agricultural biogas facility combined with animal husbandry. agrarforschung schweiz, 6, 494-499. krich, k., augenstein, d., benemann, j., rutledge, b., salour, d. (2005), biomethane from dairy waste: a sourcebook for the production and use of renewable natural gas in california. prepared for western united dairymen. united states: funded part through usda rural development. p1-282. kumar, g., rajneesh, d., singh, r.p., kataria, r. (2016), employability of biogas and bio-slurry with algae and cow dung as substrates for continuous advancement. international journal of emerging trends in research, 1(1), 19-25. kumar, s., dev kumar, h., babu, k.g. (2012), a study on the electricity generation from the cow dung using a microbial fuel cell. journal of biochemical technology, 3(4), 442-447. kumawat, r., pramendra, singh, n.k. (2016), analysis of cost and returns of milk production in rajasthan. economic affairs, 61(1), 71-80. lauer, m., hansen, j.k., lamers, p., thrän, d. (2018), making money from waste: the economic viability of producing biogas and biomethane in the idaho dairy industry. applied energy, 222, 621-636. mittal, s., ahlgren, e.o., shukla, p.r. (2018), barriers to biogas dissemination in india : a review. energy policy, 112, 361-370. mohapatro, r.n., swain, r., pradhan, r.r. (2014), a synergetic effect of vegetative waste and cow dung on bio gas production. international journal of emerging technology and advanced engineering, 4(11), 184-190. muvhiiwa, r., hildebrandt, d., chimwani, n., ngubevana, l., matambo, t. (2017), the impact and challenges of sustainable biogas implementation: moving towards a bio-based economy. energy, sustainability and society, 7(1), 20-30. nagamani, b., ramasamy, k. (1999), biogas production technology : an indian perspective. special section: fermentation science and technology, 77(1), 1-10. nandiyanto, a.b.d., ragadhita, r., maulana, a.c., abdullah, a.g. (2018), feasibility study on the production of biogas in dairy farming. iop conference series: materials science and engineering, 288(1), 012024. narayan, v., li, b., timmons, l. (2018), harnessing the energy potential of cattle dung in india : a policy memorandum to the ministry for new and renewable energy. journal of science policy and governance, 12(1), 1-7. panagariya, a., jain, a.k. (2019), electricity and clean cooking strategy for india. niti aayog. p1-3. avaialble from: https://www.niti.gov. in/writereaddata/files/document_publication/nitiblog28_vcaniljain.pdf. pandian, a.s.s., selvakumar, d.k., prabu, d. (2015), impact of dairy development programmes in india-an economic analysis. indian journal of applied research, 3(12), 131-132. pant, s., joshi, j., yadav, a.s. (2019), problems and prospects of dairy farming in almora district of uttarakhand. jetir, 6(2), 194-205. parikh, j.k., sharma, a., singh, c., neelakantan, s. (2016), providing clean cooking fuel in india: challenges and solutions. new delhi: integrated research and action for development. patnaik, s., tripathi, s. (2017), access to clean cooking energy in india-state of the sector. ceew report. p1-24. available from: http://www.ceew.in/pdf/ceew-cleancookingenergyaccessinindia21oct17.pdf. rao, m. (2017), opportunities and challenges in dairy and future ahead. approaches in poultry, dairy and veterinary sciences, 2(1), 113-115. rehfuess, e. (2006), household energy and health. who library cataloguing-in-publication data, wa754. available from: http:// www.who.int/indoorair/publications/fuelforlife.pdf. salam, s., parvin, r., salam, a., azad, s.m.n. (2020), feasibility study for biogas generation from household digesters in bangladesh : evidence from a household level survey. international journal of energy economics and policy, 10(4), 23-30. singh, k.j., sooch, s.s. (2004), comparative study of the economics of different models of family size biogas plants for state of punjab, india. energy conversion and management, 45(1-10), 1329-1341. smith, k.r., sagar, a. (2014), making the clean available: escaping india’s chulha trap. energy policy, 75, 410-414. wahyudi, j., kurnani, b.t.a., clancy, j. (2015), biogas production in dairy farming in indonesia : a challenge for sustainability. international journal of renewable energy development, 4(3), 219-226. yazan, d.m., cafagna, d., fraccascia, l., mes, m. (2018), economic sustainability of biogas production from animal manure : a regional circular economy model. management research review, 41(5), 605-624. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 6 • 2022 137 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(6), 137-145. the asymmetric impact of covid-19 pandemic on the crude oil-stock markets nexus in ksa: evidence from a nardl model zouheyr gheraia* department of business management, college of business, jouf university, skaka, saudi arabia. *email: zgheraya@ju.edu.sa received: 22 january 2022 accepted: 19/09/2022 doi: https://doi.org/10.32479/ijeep.12811 abstract this paper estimates the asymmetric relationship between the crude oil market, stock market and covid-19 pandemic in the case of ksa during the period of march 15, 2020–february 03, 2021. nonlinear and long-run asymmetric cointegration were utilized for comprehensive research on this topic. our findings are as follows: positive and negative shocks to the covid-19 pandemic reduce stock market. moreover, positive shock to crude oil market increases stock market, but negative shock has a negative and insignificant effect. based on the results, this study concludes with suitable policy prescription. keywords: covid-19 pandemic, crude oil, stock markets, nardl model, the asymmetric jel classifications:  c32, g14, g10, g11. 1. introduction world health organisation (who) declared, on march 11 2020, the covid-19 as a global pandemic. based on who’s world meters website as of october 21 2021, there are 242,916,887 confirmed cases, 220,169,977 recoveries and 4,939,857 deaths across the world. concerning the kingdom of saudi arabia, there are 548,065 confirmed cases, 537,095 recoveries and 8,770 deaths (saudi ministry of health-sehhty). the appearance of this pandemic has caused an important effect on the global trade. in this regard, along with a big knockout of domestic trading and international business, covid-19 has induced significant negative influences on the performance of different stock markets worldwide (anh and gan, 2021; al-awadhi et al., 2020; alfaro et al., 2020; zhang et al., 2020). several studies have investigated the impact of covid-19 and its lockdown on stock markets (e.g., sharif et al., 2020; kodres, 2020; al-awadhi et al., 2020; alfaro et al., 2020; eleftheriou and patsoulis, 2020; he et al., 2020; zhang et al., 2020). this idea is proved by alfaro et al. (2020), who identify a negative impact of covid-19 on us stock returns. in the same line of idea, zhang et al. (2020) underline the same relationship between covid-19 and the stock markets in neither the ten most affected countries by this novel pandemic in march 2020 nor in the stock markets of japan, korea and singapore. in addition, other studies, presented by he et al. (2020) and liu et al. (2020) as well as anh and gan (2021), stipulate that covid-19 pandemic has a negative impact on multiple countries’ stock returns. in this context, the issue of the impact of the pandemic on macroeconomic performance has attracted a lot of attention. numerous studies have attempted to explore and explain the interaction between the pandemic and macro-economic variables (leoni, 2013), governments, public and financial markets (chen et al., 2018). results from earlier studies have demonstrated a strong association between pandemic and macroeconomic performance, owing to the pandemic’s enormous economic cost (bloom et al., 2018; liu et al., 2020). related to the stock market performance and to the oil-importing economies, oil prices represent the major this journal is licensed under a creative commons attribution 4.0 international license gheraia: the asymmetric impact of covid-19 pandemic on the crude oil-stock markets nexus in ksa: evidence from a nardl model international journal of energy economics and policy | vol 12 • issue 6 • 2022138 predictor in this domain. it means, according to (narayan et al., 2014), that a decrease in the oil prices leads to a lower production cost play but an increase in the economic growth. however, the recent decline in oil prices due to the covid-19 pandemic along with plummeting stock markets globally included in oil-importing economies, raises the question of whether the well-established negative relation between oil and stock prices holds. also, according to vidya and prabheesh (2020), due to the lockdowns, the overall demand was reduced. in this way, the crude oil price fell as a result of the sharp reduction in consumption from us$61 on january 2 2020 to us$12 on april 28 2020. so, a positive relationship was distinguished between crude oil prices and stock prices. by contrast, a negative association between crude oil prices and stock prices was established. hence, ignoring the relationship between the crude oil market and the stock market and investigating the effect of the covid-19 may contribute to model misspecification problems and lead to inaccurate results and conclusions. to this end, we attempt to investigate the nexus among these three variables in a unified framework (liu et al., 2020). it is highlighted, by mensi et al. (2020), that the crude oil behaved inefficiently during the covid-19 pandemic, indicating that the oil market is susceptible to the pandemic. in addition, the increase in covid-19 cases and deaths impacted the oil and financial markets in the us, europe, and asia (shehzad et al., 2020; shehzad et al., 2021). the investigation by salisu et al., 2020 used the panel vector autoregressive model (pvar) to determine the behavior of the oil and stock markets during covid-19. the study found that both the oil market and stock markets volatility have a significant impact on oil returns (salisu et al., 2020). in other way, based in the study prepared by georgieva (2020), the covid-19 pandemic has brought the world closer to the most dangerous economic crises. in this context, the fall in oil prices due to the global lockdowns related to covid-19 requires an investigation of oil stock dynamics from the perspective of net oil-importing countries. existing research on the covid-19 pandemic pertains to the study of the oil markets and their impact on various economic factors (apergis and apergis, 2020; fu and shen, 2020; gil-alana and monge, 2020; liu et al., 2020; narayan, 2020; qin et al., 2020). therefore, it is indispensable to find out the effect of covid-19 on the stock markets. most studies to date have used the sandp 500, nasdaq composite, cac 40, shanghai composite, or nikkei 225 indices (just and echausi, 2020; rudden, 2020). however, the extent to which the covid-19 pandemic and crude oil are impacting equity markets remains unclear. thus, determining the impact of the covid-19 pandemic is not only significant for formulating the appropriate investment strategy for investors in advance, but also crucial for governments to deal with the possible fluctuation in crude oil market. therefore, the primary aim of this paper is to explore the interaction among the number of confirmed cases of the covid-19 pandemic, the crude oil market and stock market tadawel in saudi arabia by utilizing the dataset of ksa covid-19 pandemic (liu et al., 2020). our main contribution to this literature is to explore the impact of the number of confirmed cases of covid-19 in saudi arabia and crude oil prices on the stock market prices in saudi arabia during the study period (the period of complete saudi economy shutdown). in this regard, our approach to examine the relationship between oil prices, covid-19 and the stock market nexus is as follows. first, we select a country, the kingdom of saudi arabia, and draw a sample of daily observations for the period from march 1, 2020 to february 2, 2021. second, we implement the nardl model to evaluate the strength and direction of the relationship between the three variables. the rest of the paper is distributed as per the following: section 2 presents the data and methodology. section 3 analyzes the results and discussion. the last section concludes and suggests some policy implications. 2. data and methodology our applied studies are based on statistics published by (www. investing.com, (www.coronavirus-statistiques.com). the analysis from the applied side is based on a daily data series during the period form march 1, 2020 to february 2, 2021. a nardl model will be estimated to discover the non-linear relationship between covid-19 pandemic and the crude oil prices on stock prices index in the ksa. in this paper, we will try to study the effect of positive and negative changes in covid-19 pandemic and the crude oil prices on stock prices index in ksa during the period from march 1, 2020 to february 2, 2021. a nardl model is used in this case. therefore, before applying it, it is useful to define this model as follows: shin et al., (2014) presented the nardl model. it follows the ardl model (the approach that popularized through works of [pesaran and yongcheol, 1998; pesaran et al., 2001]). it follows the ardl model in its steps by specifying the model and then studying the bound test. we remind that this model itself is an expansion (development) of the long-term asymmetric regression model of the inverse relationship between stock prices index, crude oil price and covid-19 pandemic. its formula can be illustrated as follows: tad inf inf wti wti ut t t t t t� � � � � � � � � � � � �� � (1) where: tadt, inft, wtit, represent: stock prices index, covid-19 pan inft − demic (which represents the daily number of infected people in saudi arabia), and crude oil price respectively. also, inft and wtit are decomposed as: inf inf inf inft t t� � � � � 0 wti wti wti wtit t t� � � � � 0 inft + and wtit + : are partial sum processes of positive changes in inft and wtit respectively. inft − and wtit − : are partial sum processes of negative changes in inft and wtit respectively. gheraia: the asymmetric impact of covid-19 pandemic on the crude oil-stock markets nexus in ksa: evidence from a nardl model international journal of energy economics and policy | vol 12 • issue 6 • 2022 139 whereas, inft + , and wtit + , wtit − are calculated as follows: inf inf inft ii t ii t� � � � � �� �� �1 1 0max( , ) and inf inf inft ii t ii t� � � � � �� �� �1 1 0min( , ) wti wti wtit jj t jj t� � � � � �� �� �1 1 0max( , ) and wti wti wtit jj t jj t� � � � � �� �� �1 1 0min( , ) this approach for asymmetry relationship that depends on partial sum decompositions was used in (schorderet, 2001) to study the nonlinear relationship between inf, wti and tad. after that, this approach was generalized by (schorderet, 2003) and defined the stationary linear combination of the partial sum components as follows: z tad tad inf inf wti wti t t t t t t t � � � � � � � � � � � � � � � � � � � � � � � � 0 0 1 1 2 2 (2) here, we say that there is an asymmetric relationship between inf, wti and tad or we can say that these two variables are “asymmetrically cointegrated,” if and only if zt is stationary. we can illustrate the application of the nardl model by applying the following steps: first step: extending the aforementioned long-term asymmetric regression model (last part) to become in form of nardl (p, q, k) as follows: tad tad inf inf wti t j t jj p j t j j t jj q j t j � � � � �� � � � � � � � � � � �� � � � 1 0 ( ) ( �� � � � � � �� � �j t j tj k wti ) 0 (3) ϕj: the autoregressive parameter; (� j � ,� j � ) and (� j � , � j � ): are the asymmetric parameters of distributed lag; εt: error term. ( inft + , inft − ) and (wtit + , wtit − ) were calculated as we saw previously. second step: estimate the error correction model (nardl ecm) as follows: 1 1 1 1 1 1 1 1 0 1 0 ( ) ( ) ρ θ θ ϕ ϕ γ σ σ λ λ ε + + − − + + − − − − − − − − − + + − − − − −= = − + + − − − −= ∆ + + + + + ∆ + ∆ + ∆ + ∆ + ∆ + ∑ ∑ ∑ t t t t t t p q j t j j t j j t jj j k j t j j t j tj tad tad inf inf wti wti tad inf inf wti wti (4) where: ρ, θ+, θ−, �� , �� : are long-run parameters; � j � , � j � , � j � , � j � : are short-run parameters. it can also be written as follows: 1 1 1 1 0 1 0 ( ) ( ) ρξ γ σ σ λ λ ε − − −= − + + − − − −= − + + − − − −= ∆ ∆ ∆ ∆ ∆ + + + + + ∆ + ∑ ∑ ∑ p t t j t jj q j t j j t jj k j t j j t j tj tad tad inf inf wti wti (5) where: � �� ��� jj p 11 ; 1 1, 2, , 1 γ φ = + = − → = … −∑ p j ii j j p ; � �� � � �� jj q 0 ; � �� � � �� jj q 0 ; � �� � � �� jj q 0 ; � �� � � �� jj q 0 � �0 0 � �� ; � �j ji j q j q� � � � � � � � � �� 1 2 11 , , , ; � �0 0 � �� ; � �j ji j q j q� � � � � � � � � �� 1 2 11 , , , ; � �0 0 � �� ; � �j ji j k j k� � � � � � � � � �� 1 2 11 , , , ; � �0 0 � �� ; � �j ji j k j k� � � � � � � � � �� 1 2 11 , , , ; 1 1 1 1 1 1 θ θ ξ ρ ρ ϕ ϕ ρ ρ + − + − − − − − + − + − − − − − = − − − − − − t t t t t t tad inf inf wti wti � � � � �t t t t t ttad inf inf wti wti� � � � � � � � � � � � � �� � � � �1 1 1 1 1 1 2 1 2 1 (6) ξt−1 is the nonlinear error correction term. � � �1 � � � � ; � � �1 � � � � � � �2 � � � � ; � � �2 � � � � (�1 � , �1 � ) and ( �2 � , �2 � ): are asymmetric long-run parameters. third step: testing the null hypothesis of no co-integration in the long run between tadt and inft, wtit relying on the bounds testing approach as follows: 0 1 h : 0 h : 0 ρ θ θ ϕ ϕ ρ θ θ ϕ ϕ + − + − + − + −  = = = = =  ≠ ≠ ≠ ≠ ≠ (7) similarly, we can also test the short-run relationship as well as the long-run relationship by testing the following hypotheses: long-run: 0 1 h : h : θ θ θ θ + − + −  =  ≠ , 0 1 h : h : ϕ ϕ ϕ ϕ + − + −  =  = (8) short-run: 0 1 h : h : σ σ σ σ + − + −  =  ≠ j j j j , 0 1 h : h : λ λ λ λ + − + −  =  ≠ j j j j (9) gheraia: the asymmetric impact of covid-19 pandemic on the crude oil-stock markets nexus in ksa: evidence from a nardl model international journal of energy economics and policy | vol 12 • issue 6 • 2022140 fourth step: the last step of the nardl procedure derives the positive and negative multipliers with inft + , inft − and wtit + , wtit − computed as: (mazorodze and noureen, 2018). mh = tad inf + t+j t +j=0 h � � � and, mh = tad inf t+j t -j=0 h � � � mh = tad wti + t+j t +j=0 h � � � a, mh = tad wti t+j t -j=0 h � � � where ℎ=0,1,2, for inft + , inft − and wtit + , wtit − respectively. noteworthy is that ℎ→∞, mh i � �� � and m ih i � �� �� / ,1 2 . these dynamic multipliers add useful information towards the analyses of the asymmetric adjustment path taken by the model following a short-run disequilibrium with initial positive or negative partial impact of crude oil prices and covid-19 pandemic. 3. results and discussion as we have previously seen, applying the nardl model requires going through the following steps: 3.1. stationarity study of the series tadt, inft and wtit the nardl model requires none of the variables to be i (2). therefore, we first perform stationary tests to make sure that none of the variables violates this condition. to test the stationarity of series: tadt, inft, wtit, we rely on both the dicky-fuller (adf) and philips-peron (pp) tests. the results can be obtained directly at the same time using the specially prepared software in eviews 10.0. it is clear from the results of the outputs that all series are stationary in the first degree, (i(1)), where, the calculated statistics values for the pp and adf test for the differenced series in first degree became greater (in absolute value) than the tabular statistics in the three models at 5% level of significance (table 1). 3.2. bounds test the results above provide justification for the non-linear ardl approach since none of the variables is i(2). the non-linear ardl bounds testing depends on four factors (i) number of regressors (k), (ii) assumption about the intercept and trend in the cointegrating equation, (iii) number of observations (n) and (iv) whether variables are i(0) and (i(1). here, n=318, k=4 since positive and negative changes of variables are constructed into one variable. assumption iii, intercept and no trend and i (1) variables. the non-linear ardl bounds testing procedure is performed after the estimation of equation (4). based on the akaike information criterion (aic), a non-linear nardl (7, 4, 6, 0, and 6) is selected, where the hypotheses of this test are: 0 1 h : 0 h : 0 ρ θ θ ϕ ϕ ρ θ θ ϕ ϕ + − + − + − + −  = = = = =  ≠ ≠ ≠ ≠ ≠ table 1: the results of augmented dickey–fuller-type test variable t value the covid-19 pandemics −8.7956*** crude oil returns −16.9656*** stock returns −6.0176*** *significance at 1% level, **significance at 5% level and *significance at 10% level the results of the bounds test are summarized in the table 2. we note that the value of f=6.91 is greater than all the critical values at all levels of significance, implying that we cannot reject the null hypothesis. this means that stock prices index, positive and negative changes in crude oil price and covid-19 pandemic move together in the long run. 3.3. estimation of model parameters in the longand short-term and asymmetry test having established the presence of a long-run relationship, the next stage involves estimating the parameters of the nardl model in the long and short terms. but before adopting this model for use in estimating the long and short-term effects, it is necessary to ensure the quality of the performance of this model, and this is done by performing the most important diagnostic tests: jarque-bera test, breusch-godfrey serial correlation lm test, arch test, ramsey reset test, and cusum and cusumsq test. the results of estimating long-term parameters can be summarized in the table 3. from the table 3, we can infer a negative relationship between the stock prices and the increase in the number of people infected with the pandemic, and a positive relationship between stock prices and the decrease in the number of people infected with the pandemic. there is, also, a positive relationship between positive changes in crude oil prices and stock prices. this does not respond to negative changes in crude oil prices. the error correction equation will take the following form: coint eq=tadt−(−0,4021 inf_post−0,2458 inf_ negt+25,0984 wti_post−5,1791 wti_negt+6193,73) (17) 3.3.1. long-run symmetry test what is generally observed directly through the results of the estimation is the high response in stock price volume to the positive changes of the pandemic compared to the negative changes of the pandemic. as for the crude oil price variable, the stock price responds only to positive changes, since the negative changes parameter are not significant in the long term. a formal test is performed to check if the effect is really asymmetric for the two variables: inf and wti. so, to test for long-term asymmetry, we need to test the following hypothesis based on wald’s test: 0 1 1 h : (3) / (2) (4) / (2) : h : (3) / (2) (4) / (2) − = −  − ≠ − lr c c c c h c c c c for variable inft, and 0 2 1 h : (5) / (2) (6) / (2) : h : (5) / (2) (6) / (2) − = −  − ≠ − lr c c c c h c c c c for variable wtit results from the lower part of table 3 show that the null hypothesis of long-run symmetry is rejected at 1% level. this shows the gheraia: the asymmetric impact of covid-19 pandemic on the crude oil-stock markets nexus in ksa: evidence from a nardl model international journal of energy economics and policy | vol 12 • issue 6 • 2022 141 table 2: non-linear ardl bounds test results h0 there is no cointegration between the variables f-bounds test critical values pesaran et al., 2001 decision upper bound lower bound significant at 10% 2.2 3.09 the null hypothesis is rejected and accepte the alternative hypothesis. significant at 5% 2.56 3.49 significant at 1% 3.29 4.37 f-bounds test narayan 2005 dicision critical values lower bound upper bound significant at 10% 2.3 3.22 the null hypothesis is rejected and accept the alternative hypothesis. significant at 5% 3.68 3.69 significant at 1% 3.6 4.78 test statistics number of independent variables (f) statistic conclusion k=4 f=6.915148 there is cointegration validity of the alternative hypothesis that the stock prices’ response to changes in the number of people infected with the covid-19 pandemic is asymmetric. as for the symmetry test for the crude oil prices variable, it cannot be performed because the negative changes in the long-term relationship are not significant. in addition, the results of the short-term parameter estimates (results of ecm estimates of nardl model) are as follows: based on the short-term model, it is notified that stock prices generally respond positively to stock prices for the past periods. also, they generally respond positively to both positive and negative changes in the number of people infected with the covid-19 pandemic. in addition to negative changes in the price of crude oil in general. yet, they do not respond to positive changes in the price of crude oil. 3.3.2. short-run symmetry test similarly to the previous test, we can also do a test to the short-run relationship by testing the following hypotheses: ( ) ( ) ( ) ( ) ( ) ( ) 0 1 1 h : 16 17 21 (22) : h : 16 17 21 (22)  = + +  ≠ + + sr c c c c h c c c c for variable inft, results from the lower part of table 4 show that the null hypothesis of short-run symmetry is rejected at 10% level. this result shows the validity of the alternative hypothesis that the stock prices’ response to change in the number of people infected with the covid-19 pandemic is asymmetric. as for the symmetry test for the crude oil prices variable, the test cannot be performed because the short-term model does not contain variables that represent positive change in crude oil prices. 3.4. diagnosis of estimate results in light of the previous results of the long and short equations for the previous nardl model, we find that the error correction parameter (ectt−1) is significant at the level of 1% with the expected negative sign. this result is considered as a support to a long-term equilibrium relationship between the variables. this parameter (−0.17) indicates that 17% of short-run disequilibrium of stock prices is corrected each day. that is, when the stock prices index deviates during the short period (t-1) from its equilibrium values in the long run, the equivalent of 17% of this deviation is corrected in the period (t). likewise, it can be said that the stock prices index takes approximately 1 0 17 6 .  − day to adjust to its equilibrium value. also, the estimation results showed that most of the estimated parameters were statistically significant at varying significance levels, with the exception of variables d(tadt−4), d(tadt−6), d(inf_post), d(inf_post−1), d(inf_post−2), d(inf_negt−1), d(inf_negt−2), d(wti_negt) in the short run. table 3: results of estimating the long-term parameters of the nardl model results of estimating the following long-run equation for the following nardl model : tad inf inf wti wti ut t t t t t� � � � � � � � � � � � � � � � � �� � � � �1 1 2 2 dependent variable: tadt variable coefficient std.error t-statistic prob. inf_pos −0.402127 0.083996 −4.787*** 0 inf_neg −0.245809 0.067337 −3.650*** 0.0003 wti_pos 25.09845 6.891937 3.641*** 0.0003 wti_neg −5.179134 11.26501 −0.459 0.646 c 6193.736 102.3311 60.52*** 0 diagnostic tests jb lm arch reset statistic χ2=3.54 f (2,288)=0.96 f (1,315)=0.41 f (1,289)=1.98 probalility 0.17 0.41 0.52 0.16 ***denote significant at 1% long-run symmetry f-stat1=9.47 prob=0.002 the long-run symmetry joint null hypothesis is + −− − =     :or  1 1 � �� and � � �� �φ ρ φ ρ or  2 2 � �� gheraia: the asymmetric impact of covid-19 pandemic on the crude oil-stock markets nexus in ksa: evidence from a nardl model international journal of energy economics and policy | vol 12 • issue 6 • 2022142 it is also clear from the table that the value of the determination coefficient reached 0.24. this means that variations in crude oil price and covid-19 pandemic account for the 24% of the change in stock prices index. this is a low value, which indicates the model’s poor goodness fit. in addition, the durbin-watson statistic does not suggest autocorrelation errors of the first degree. finally, it appears clearly from the lower part of table 3 show that none of the relevant diagnostic tests was violated. in particular, the model does not suffer from autocorrelation of degree greater than 1, heteroscedasticity, model misspecification, residual nonnormality and parameters instability as shown in the following figures 1 and 2: from these two figures, it is clear that the estimated coefficients of the model are structurally stable over the period under study. 3.5. multiplier effect analysis the last step when estimating the nardl model is to derive asymmetric cumulative dynamic multipliers that allow us to trace out the asymmetric adjustment patterns following positive and negative changes in covid-19 pandemic variable, and crude oil price respectively. the following figures synthesizes this analysis: this figure 3 shows that the stock prices index responds positively to negative changes in the number of people infected with covid-19 pandemic and negatively to positive changes during the entire study period. we also note that the stock price index responds with a larger size to negative changes in the number of people infected with the pandemic, compared to positive changes until the twelfth period. in this context, we note that the asymmetry curve (asymmetry chart: which represents the difference between the stock price index figure 2: cusum of squares test figure 1: cusum test table 4: results of estimating the short-term parameters of the nardl model results of estimating the short-term equation for the following nardl model: d tad d tad d inf d inft i t ii p i t i i t ii ( ) ( ) ( ) ( )� � � � � �� ��� � � � � � �� � � �1 �� � � � � � � � �� �� � � �� �� � �0 0 1 q i t i i t ii k t td wti d wti ect� � � �( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ** * *** *** *** 1 2 3 4 5 6 1,172,44 1,86 4,11 3,14 1,43 1 (0,2) 0,4 0,06 ( ) 0,13 ( ) 0,1 ( ) 0, 22 ( ) 0, 06 ( ) 0,17 ( ) 0, 07 ( ) 0.01 ( _ ) 0, 02 ( _ ) 0, 004 ( _ − − − − − − − − − − = ⋅ − ⋅ + ⋅ + ⋅ + ⋅ + ⋅ + ⋅ − ⋅ − ⋅ t t t t t t t t t d untc d tad d tad d tad d tad d tad d tad d inf pos d inf pos d inf pos ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) *** *** ** ** 2 3 2,72 2,69 1 2 3 4 5 0,68 0,62 1,64 2,49 2,49 0,23 ) 0,16 ( _ ) 0,17 ( _ ) 0, 04 ( _ ) 0, 04 ( _ ) 0,1 ( _ ) 0,14 ( _ ) 0,14 ( _ ) 1, 44 ( _ ) 1 − − − − − − − − − − − − + ⋅ − ⋅ + ⋅ − ⋅ − ⋅ − ⋅ + ⋅ − ⋅ − t t t t t t t t t d inf pos d inf neg d inf neg d inf neg d inf neg d inf neg d inf neg d wti neg ( ) ( ) ( ) ( ) ( ) ( ) * * ** * ** *** 1 2 3 4 1,77 1,9 2,26 1,73 5 1 1,98 6,49 2 1, 01 ( _ ) 11, 65 ( _ ) 13, 98 ( _ ) 10, 97 ( _ ) 12, 48 ( _ ) 0,17 0, 24 1891, 56 1, 93 318 − − − − − − − − − − − − ⋅ − ⋅ − ⋅ − ⋅ − ⋅ − ⋅ = = − = = t t t t t t d wti neg d wti neg d wti neg d wti neg d wti neg ect r loglikelihood dw n the index (d) attached to all variables represents the difference in the first degree; : error correction term; *, **, ***represents the statistical significance at 10.5 and 1%, respectively. the values in parentheses represent the values of student’s stats long-run symmetry f-stat1=3.44 prob=0.06 the long-run symmetry joint null hypothesis is: , � � � ��  ji j q 1 � � � ��  ji j q 1 response to positive and negative changes in the number of people infected with the covid-19 pandemic) takes a positive sign until day 12, but after this period it becomes negative. therefore, the asymmetry curve indicates that the stock price index’s response to gheraia: the asymmetric impact of covid-19 pandemic on the crude oil-stock markets nexus in ksa: evidence from a nardl model international journal of energy economics and policy | vol 12 • issue 6 • 2022 143 figure 4: dynamic multipliers for wtit in ksa figure 3: dynamic multipliers for inft in ksa. source: prepared by researchers using the eviews 10.0 program positive changes in the number of infected people becomes greater than the price index’s response to negative changes. it should also be noted that the increase in the number of people infected with the pandemic takes about 15 days until it is completely converted to the level of the stock price index and converges with the long-term coefficient (which equals −0.4) for positive values and (−0.24) for negative values. the figure 4 shows that the stock price index responds positively to both positive and negative changes in crude oil prices during the entire study period. there, it appears that the asymmetry curve (asymmetry plot) takes a positive sign during the whole study period. we also note that the stock price index’s response to negative changes in crude oil prices is stronger than the response to positive changes until day 13, after which it becomes the opposite. in general, these multiplier effects of positive and negative changes in the two variables (number of people infected with the pandemic and the crude oil prices) are logical and consistent with economic theory and previous studies. indeed, the positive shocks in the number of people infected with covid-19 lead to a decrease in the stock price index, while negative shocks increase it. in addition, the multiplier effects of positive shocks in the number of people infected with covid-19 are stronger than the multiplier effects of negative shocks at the end of the period (i.e., in the long term). in this line, the asymmetry plot shifts down towards the multiplier curve of the positive effects, which indicates a decrease in the stock price index on the long term overall. this confirms the results of estimating the long-term equation presented in table 4. on the other hand, we find that there are positive responses to the stock price index for both positive and negative shocks in crude oil prices during the study period, which violates the economic theory, due to the decrease in the study period taken into account in calculating the size of the multiplier effects (15 days only). it should be noted, also, that the stock price index responds to negative shocks in crude oil prices in the long term. 4. conclusions and policy implications in this paper, we investigate the relationship between the crude oil market, stock market and covid-19 pandemic in the case of ksa. the study uses monthly data from march 15, 2020 to february 03, 2021. the nonlinear autoregressive distributed lag model developed by shin et al., (2014) is applied to investigate the nonlinear influence of covid-19 pandemic and crude oil market on stock market in ksa both in the long and short run. in the long-term, we note that the coefficient of the variable that represents positive changes in the number of people infected with covid-19 is negative and significant at 1% level. the interpretation of this coefficient is that the stock prices index falls by 0.4 points in the long run if the number of people infected with covid-19 increases by one unit. in addition, the coefficient associated with the negative changes of the number of people infected is negative and significant at 1% level. the interpretation of this coefficient is that a reduction in the number of people infected with covid-19 by one unit raises the stock prices index by 0.24 points in the long run. this result clearly indicates that the stock price index in saudi arabia does not respond with the same value to both the decrease and the increase in the number of infected people. this result was similar to the result of (anh and gan, 2021; al-awadhi et al., 2020; alfaro et al., 2020; eleftheriou and patsoulis, 2020; he et al., 2020; zhang et al., 2020). on the other hand, we note that the coefficient of positive crude oil prices changes is positive and significant at 1% level. the interpretation of this coefficient is that the stock price index rises by 25.09 points in the long term if positive crude oil prices increase by one unit. as for the variable that represents the negative changes in crude oil prices, it is not statistically significant. this result clearly indicates that the stock price index in saudi arabia responds only to positive changes in crude oil prices in the long term. it is clear from the long-term results that the impact of crude oil prices is large compared to the variable that represents the number of individuals infected with covid-19. the small size of the gheraia: the asymmetric impact of covid-19 pandemic on the crude oil-stock markets nexus in ksa: evidence from a nardl model international journal of energy economics and policy | vol 12 • issue 6 • 2022144 impact of the variable that represents the number of people infected with the covid epidemic can be attributed to the success of the kingdom of saudi arabia in limiting the spread of the covid-19 epidemic. the decrease in the number of injured and deaths and the application of strict protocols, as well as the great support for government and private institutions to reduce the impact of the epidemic on them, contribute to reducing its impact on the saudi financial market, on the other hand. the impact of the decline in oil prices was the greatest due to the high dependence of the saudi domestic product on oil revenues. from the above short-term model, we notice a positive and significant effect of the stock price index for the last period and retarded with three and five periods (days) on the current stock price index, where impact size reached 0.13, 0.22, 0.17, respectively. moreover, an inverse and significant relationship between the current stocks price index and the delayed one in two periods (two days), where the effect size was −0.1. this relationship shows an important fact: the dynamic nature of the stock price index. this means that the stock price index in the current period depends on the stock price index in previous periods (this is known in economics as the stock price index hysteria). the results indicate that a variable representing positive changes in the number of people infected with covid-19 that is 3 days late and is considered statistically significant at only 1% in the short term. the interpretation of this coefficient is that an increase in the number of people infected with covid-19 retarded by 3 days by one unit will raise the stock price index by 0.16 points in the short term. the results indicate that there is a positive and significant relationship between the stock price index and the variable represented by negative changes in the number of people infected with covid-19 and retarded by 2 and 4 days. the interpretation of these coefficients is that reducing the number of individuals infected with covid-19 that is delayed by two and four periods by one unit will raise the stock price index by 0.04 and 0.14 points, respectively, in the short term. moreover, there is an inverse and significant relationship between the stock price index and the negative changes in the number of people infected with the covid-19 virus retarded by 5 days. indeed, if this latter rises by one unit, the stock price index will fall by 0.14 points in the short term. finally, the short-term results indicate that the stock price index responds only to negative changes in crude oil prices and does not respond to positive changes. in general, there is a positive and significant relationship between the stock price index and the negative changes in crude oil prices at all late periods. indeed, if the late crude oil prices decreased by 1, 2, 3, 4, 5 days by one unit, the index of the stock price will rise by 11.01, 11.64, 13.98, 10.97, and 12.48 respectively, this is in line with most of the previous studies. noteworthy is that the positive relationship between crude negative oil prices changes and stock price index confirmed in table 4 (short run model) contrasts with many other relevant studies. the difference could be emanating from the fact that they assumed linearity and symmetry. overall, our main result is consistent with previous studies that confirm the linearity of the relationship between crude oil prices and stock price index. indeed, in the long term, despite the presence of asymmetry, the coefficient of negative changes in crude oil prices was insignificant, and in the short term, the stock price index is not affected by positive changes in crude oil prices. we clearly note that the size of the impact of crude oil prices on the stock price index is much greater than the size of the impact of the development of the number of people infected with the pandemic on the stock price index in the long and short term. references al-awadhi, a.m., alsaifi, k., al-awadhi, a., alhammadi, s. (2020), death and contagious infectious diseases: impact of the covid-19 virus on stock market returns. journal of behavioral and experimental finance, 27, 100326. alfaro, l., chari, a., greenland, a.n., schott, p.k. (2020), aggregate and firm-level stock returns during pandemics, in real time, working paper no. w26950. massachusetts: national bureau of economic research. anh, d.l.t., gan, c. (2021), the impact of the covid-19 lockdown on stock market performance: evidence from vietnam. journal of economic studies, 48(4), 836-851. apergis, e., apergis, n. (2020), can the covid-19 pandemic and oil prices drive the us partisan conflict index? energy research letters, 1(1), 1-4. bloom, d.e., cadarette, d., sevilla, j.p. (2018), epidemics and economics: new and resurgent infectious diseases can have farreaching economic repercussions. finance and development, 55(2), 46-49. chen, m.p., lee, c.c., lin, y.h., chen, w.y. (2018), did the sars epidemic weaken the integration of asian stock markets? evidence from smooth time-varying cointegration analysis. economic research-ekonomska istraživanja, 31(1), 908-926 eleftheriou, k., patsoulis, p. (2020), covid-19 lockdown intensity and stock market returns: a spatial econometrics approach, working paper no. 100662. munich: university library of munich. fu, m., shen, h. (2020), covid-19 and corporate performance in the energy industry. energy research letters, 1(1), 12967 georgieva, k. (2020), imf managing director kristalina georgieva’s statement following a g20 ministerial call on the coronavirus emergency. available from: https://www.imf.org/en/news/ articles/2020/03/23/pr2098-imf-managing-directorstatementfollowing-a-g20-ministerial-call-on-the-coronavirus-emergency [last accessed on 2021 oct 29]. gil-alana, l.a., monge, m. (2020), crude oil prices and covid-19: persistence of the shock. energy research letters, 1(1), 13200. he, q., liu, j., wang, s., yu, j. (2020), the impact of covid-19 on stock markets. economic and political studies, 8(3), 1-14. just, m., echaust, k. (2020), stock market returns, volatility, correlation and liquidity during the covid-19 crisis: evidence from the markov switching approach. finance research letters, 37, 101775. kodres, l. (2020), brakes or bans: protecting financial markets during a pandemic. available from: https://www.voxeu.org/article/brakes-orbans-protecting-financial-markets-during-pandemic [last accessed on 2020 jul 27]. gheraia: the asymmetric impact of covid-19 pandemic on the crude oil-stock markets nexus in ksa: evidence from a nardl model international journal of energy economics and policy | vol 12 • issue 6 • 2022 145 leoni, p.l. (2013), hiv/aids and banking stability in developing countries. bulletin of economic research, 65(3), 225-237. liu, h., manzoor, a., wang, c., zhang, l., manzoor, z. (2020), the covid-19 outbreak and affected countries stock markets response. international journal of environmental research and public health, 17(8), 2800. liu, l., wang, e.z., lee, c.c. (2020), impact of the covid-19 pandemic on the crude oil and stock markets in the us: a time-varying analysis. energy research letters, 1(1), 13154. mazorodze, b., noureen, s. (2018), on the unemployment output relation in south africa: a non-linear ardl approach. journal of economics and behavioral studies, 10, 167-178. mensi, w., sensoy, a., vo, x.v., kang, s.h. (2020), impact of covid-19 outbreak on asymmetric multifractality of gold and oil prices. resources policy, 69, 101829. narayan, p.k. (2020), oil price news and covid-19-is there any connection? energy research letters, 1(1), 13176 narayan, p.k., sharma, s., poon, w.c., westerlund, j. (2014), do oil prices predict economic growth? new global evidence. energy economics, 41, 137-146. pesaran, m., shin, y. (1998), generalized impulse response analysis in linear multivariate models, economics letters, 58, (1), 17-29. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. prabheesh, k.p., padhan, r., garg, b. (2020), covid-19 and the oil price-stock market nexus: evidence from net oil-importing countries. energy research letters, 1(2), 13745 qin, m., zhang, y.c., su, c.w. (2020), the essential role of pandemics: a fresh insight into the oil market. energy research letters, 1(1), 13166. rudden, j. (2020), impact of covid-19 on the global financial marketsstatistics and facts, statista. available from: https://www.statista. com/study/71644/impact-of-the-coronavirus-covid-19-pandemicon-global-financial-sector [last accessed on 2021 oct 29]. salisu, a.a., ebuh, g.u., usman, n. (2020), revisiting oil-stock nexus during covid-19 pandemic: some preliminary results. international review of economics and finance, 69, 280-294. saudi ministry of health-sehhty. (2021), corona statistics in saudi arabia by cities today complete statistics. available from: https:// www.sehhty.com schorderet, y. (2001), revisiting okun’s law. la jolla, ca. available from: http://www.econis.eu/ppnset?ppn=336068387 schorderet, y. (2003), asymmetric cointegration. working paper, geneva: econometrics department, university of geneva. available from: https://www.core.ac.uk/download/pdf/7134653.pdf sharif, a., aloui, c., yarovaya, l. (2020), covid-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the us economy: fresh evidence from the wavelet-based approach. international review of financial analysis, 70, 101496. shehzad, k., umer, z., xiaoxing, l., jarosław, g., carlo, p. (2021), examining the asymmetric impact of covid-19 pandemic and global financial crisis on dow jones and oil price shock. sustainability, 13(9), 4688. shehzad, k., xiaoxing, l., arif, m., rehman, k.u., ilyas, m. (2020), investigating the psychology of financial markets during covid-19 era: a case study of the us and european markets. frontiers in psychology, 11, 1924. shin, y., yu, b., greenwood-nimmo, m. (2014), modelling asymmetric cointegration and dynamic multipliers in a nonlinear ardl framework. in: horrace, w., sickles, r., editors. the festschrift in honor of peter schmidt: econometric methods and applications. berlin, germany: springer. p281-314. vidya, c.t., prabheesh, k.p. (2020), implications of covid-19 pandemic on the global trade networks. emerging markets finance and trade, 56, 2408-2421. zhang, d., hu, m., ji, q. (2020), financial markets under the global pandemic of covid-19. finance research letters, 36, 101528. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020 697 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 697-703. the impact of budget, accountability mechanisms and renewable energy consumption on environmentally sustainable development: evidence from indonesia jozef r. pattiruhu* department of management, faculty of economics and business, university of pattimura ambon, indonesia. *email: patiruhujoseph01@gmail.com received: 03 july 2020 accepted: 18 september 2020 doi: https://doi.org/10.32479/ijeep.10624 abstract the goal linked with the current article is to analyse the impact of the budget approved for environmental development, accountability mechanism of the government and renewable energy consumption on the environmental sustainability development of indonesia. the quantitative method has been executed through which secondary data has been extracted from the database of world bank along with the finance ministry of indonesia from 1985 to 2017 while for the analysis purpose ardl approach has been used. the results revealed that positive nexus among the budget approved for environmental development, accountability mechanism of the government, renewable energy consumption and environmental sustainability development of indonesia in both the short and long run. the results also revealed that negative linkage among the energy import and environmental sustainability development of indonesia. these findings provided suitable measures to the regulatory authority of the country that they should approve more budget for environmental development along with maintaining the high accountability mechanism that enhances the environmental sustainability development in indonesia. keywords: environmental development, accountability mechanism, renewable energy consumption, environmental sustainability development jel classifications: f64, o13, p18 1. introduction environmental sustainability is a very hot topic in today’s world. the environmental issues have emerged as mainstream issues in the 1960s and 1970s. the world and leaders of nations are quite inquisitive about the extent of environmental degradation. these issues are more important and substantial for the survival of the human race. the election campaigns and even the electoral reforms should include environmental sustainability as an integral and foremost part. it should be clearly stated in the constitutive documents that environmental sustainability correlates with human survival and existence. same is the case with the republic of indonesia. there is a proper clause in the constitution of indonesia (1945’s constitution) that includes or addresses environmental sustainability (ögmundarson et al., 2020). the impact of different variables like budget and other mechanisms are quite evident in this regard. the government of indonesia is working devotedly and diligently in this regard. the government has provided funds to urban as well as rural areas of indonesia. one such example is the funds provided to the province of jawa in indonesia. the province was allotted 8,373,021,018,000 rupias in 2016 and 6,384,442,058,000 indonesian rupiahs in 2017 as the budget of development and maintenance of environmental sustainability (kasayanond et al., 2019; khan and younas, 2019). the research data suggested that most of the funds are used in this journal is licensed under a creative commons attribution 4.0 international license pattiruhu: the impact of budget, accountability mechanisms and renewable energy consumption on environmentally sustainable development: evidence from indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020698 infrastructure development and roads construction in the province of jawa. this contradicts the policy of law number 6 of the constitution of indonesia (astuti, 2018). the term sustainability has vast and diverse meanings. it defines the multidimensional proposal to attain a better quality of life for everyone. the sustainable environment and economy are correlated terms. these terms are the mainstream pillars of development of a country. the distribution of resources and demand of the nation should be balanced enough to support all types of needs and requirements of present and future generations. the need is to maintain a fair balance between demand and supply (cho et al., 2018; kirwa and ngeno, 2020). the world is becoming materialistic day by day. it is not supporting the maintenance of novel and unique habitats of living beings. the biodegradation and habitat destruction of the creatures or wild animals for attaining the full advantage of human living standards is increasing day by day. nature and its resources provide all types of advantages to humans but humans are not ready to serve and conserve nature. this imbalance and selfish approach of human beings has disturbed the environmental sustainability a lot (bertella, 2019). a term which is known as sustainable development goals is adopted by the united nations in the year 2015. this policy focuses on mainstream challenges like poverty, environmental degradation and climate change. these goals are included in the national policy of indonesia. through the presidential decree no. 59/2017, indonesia has committed to mainstream the sdgs into the national context. the 17 goals were translated into national development agendas, which in turn are based on the four pillars of the national long-term development plan (rpjpn), 2005-2025: steady law and political institution, increasing wealth and prosperity, more advanced and sustainable economic structure, and biodiversity preservation. the presidential decree mandated the release of the sdgs roadmap, to serve as the general policy guideline for future. the proposed timeline and listed number of sustainability goals in the context of national action plan and sectoral division of plan into different levels of environmental sustainability parameters. it can be assessed through this information that the indonesian government takes the environmental stability and conservation of environmental resources quite seriously. they even have formulated a biodiversity related strategic action plan (halimatussadiah, 2020). the basic need here is that the accountability mechanism to maintain a proper check and balance is very necessary. the government when allocating budget for a specific purpose then that amount should be only consumed or spent for that specific purpose and to make this thing crystal clear the government should make a lot of effort. the accountability bureau of the country should be active and should give a monthly report to the finance ministry and even to the prime minister and president because they all are responsible for proper development and attainment of aims which has already set in the national action plan (muda and naibaho, 2018). renewable energy resources are those biodegradable and renewable agents of nature which could be utilized in an effective way (nawaz et al., 2019). these resources are a good source of energy and they do not emit harmful chemicals and compounds in the environment. this thing helps a lot in determining the balance between economic development and environmental development (gérardy et al., 2020). the natural resources like fossils fuels account for a total of 2% of the energy resources but these resources are energy-consuming and they are agents of environmental pollution and global warming as well. the trend changed in the world from fossil fuels consumption towards biobased energy solutions or chemicals (morone and d’amato, 2019). the composting and landfills are the new bio-based methods to avoid the pollution generated by fossil fuels consumption (fiorentino et al., 2019; nawaz et al., 2020). the academia and industry are jointly proposing links to link the production of the bio-based chemical without any harmful chemical emission and even global warming-related concerns. the proposed share of bio-based chemicals production in indonesia and the overall world will cover 22% of total chemical production by the end of the year 2025 (fiorentino et al., 2019). the bio-based chemicals can be produced by natural processes, but it is wastage of time and resources to wait for such a long time. this thing is overcome using new and latest technology and it has many advantages like timesaving and readily available methods, the raw material is quite cheap, and it is also naturally available at very low cost. the recombinant dna technology and use microbes to produce such chemicals synthetically in labs as well in industries is quite an efficient way to produce the energy and related products like biofuels and other related bio-based chemicals. the consortia of microbes produce the required amount of chemical in very less time as compared to natural ways and in industries with harmful additives and related products which causes air and water pollution (pagliaro, 2019). the indonesian economy has scaled up a lot and it is raised by 2.5% in previous years. the unique feature of their national action plan is that they have put great stress on environmental sustainability and allocated a handsome amount for this purpose. the accountability and other counter checking mechanisms are active enough to gauge the pace of developmental works. the government has allotted funds locally at the sectoral or regional level to ease the difficulties of less developed areas as well. the counter checking mechanism should be strong enough that the funds should be served for the right purpose. if this happens then national action plan and all the developmental incentives could easily reach to the common man at the grass-root level. this would be the dawn of a new era with unique, developed and sustained environment (nong et al., 2020). the share of total energy-related co2 emissions in 2018 in transport, agriculture, buildings, industries, another energy sector, electricity, were 28%, 1%, 5%, 31%, 7% and 28% respectively. when comparing this statistic with others, the highest share was of transport and electricity/heat. both pertain the same percentage. in the decarburization field, the shares of renewables, gas, oil and coal were 12%, 22%, 5% and 61%, respectively. in comparison with these statistics, the highest share was of coal. similarly, in the field of decarburization, some other shares are; biofuels, electricity, gas, oil and coal were 3.5%, 0%, 0%, 96.5% and 0. pattiruhu: the impact of budget, accountability mechanisms and renewable energy consumption on environmentally sustainable development: evidence from indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020 699 2. literature review the economy of a country is directly related to the country`s environment and natural resources. climate change and habitat destruction are two alarming things in today’s world. the climate change and related problems have increased a lot and they have reached such a critical point that things are moving towards uncontrollable loss. this concern not only instigates the developed countries but also developing ones like indonesia. a global effort is nowadays governing in this regard all across the world, a lot of rehabilitation strategies like the development of food security strategies, development of new and novel eco-friendly technologies and use of renewable energy resources are adopted to mitigate the change or damage to a minimal level (sarkodie, 2018). there link between economic growth, human well-being, industrialization, carbon dioxide emission and greenhouse effects is undeniable. these things are the true indicators of human development in terms of improved lifestyle, income, skill formation, employment opportunities, health care, gender parity, entrepreneurship and increased sense of environmental responsibility (nawaz et al., 2020). the industrialization helped a lot in improvement of food security, nutrition and technological advancements. this trend has changed the outlook of the world altogether (asumadu-sarkodie and yadav, 2019). the improved conditions hygiene and living standards let the people in a more comfortable lifestyle. air conditioners, automatic washing machines and refrigerators are present in every house. the rate of energy consumption becomes quite high nowadays and this thing triggers the need to adopt some strategies which can help to fill up the demand and supply gap. fossil fuels and other reserves like oil have started to deplete at a very high pace. this thing made the life of people difficult. the need of the hour is to adopt new and novel energy reserves from nature to cope up the upcoming challenges. technological advancements allowed us to do so. the recombinant dna technology and improved agricultural practices helped us a lot to improve our living standards at a very low cost (vergura, 2018). the strong links between economic development, energy consumption, and environmental quality render the empirical evidence of the environment kuznets curves hypothesis largely significant, particularly for a developing country such as indonesia, which is currently striving to boost its economy. over the last decade, indonesia’s economy grew rapidly at an annual average rate of 5.4 percent per year. this was followed by an increasing amount of total energy supply to approximately 1525 million barrel of oil equivalents (boe) in 2013 from 1,111 million boe in 2000, with an annual average growth rate of 2.5 percent (udemba et al., 2019). accordingly, the total emissions of carbon dioxide (co2) from fossil fuel combustion also showed an upward trend with a slightly faster average growth rate of 3.9 percent per year, amounting to 424.6 million tons co2-equivalent in 2013 from 258.3 million tons co2-equivalent in 2000. more than 38 percent of that combustion resulted from electricity generation (tannady et al., 2019). this has created serious environmental problems, including the threat of climate change. a series of energyand environment-related policies have been introduced by the government of indonesia (goi) as countermeasures to nullify the environmental impacts of greenhouse gas (ghg) emissions (sugiawan and managi, 2016). developed countries have experienced a lot of success in terms of environmental sustainability and its related fields in the last three decades (nawaz et al., 2020). the main reason is that they have very strong accountability mechanisms at both government and public sector level. they have educated their folks in such a way that they behave responsibly and play a vital role in this regard. they have promoted environmental safety, sustainability, and proper accountability mechanisms at all communicative forums like print media, social media and on networking websites. so, people become habitual to know about how they can work and play their role in environmental sustainability more effectively. the government has highlighted their action plans and agendas so clearly that even children have proper knowledge of each and everything (fisher et al., 2018). developing countries are also trying to adopt the same strategy. they are trying a lot to compete with developed countries and educate their people in the same manner. the shortcoming is that these developing countries do not have adequate resources and accountability mechanisms to do the needful. public sector accountability mechanisms are all about setting clear goals and plans to cope with emerging challenges. the level and extent of accountability mechanisms should be considered first and then the feedback from the working community should be analyzed. this thing could help the developing countries to come in competition with the developed countries (hidayat et al., 2018). the accountability mechanisms of environmental sustainability become complex in developing countries like indonesia because they rely on foreign aid and international donors like the world bank and the asian development bank. these all organizations give aid to mitigate the poverty and elevate the lifestyles of people of the inhabiting countries (paletta and bonoli, 2019). this thing made it very difficult to do honest accountability. the effects of all the projects these type of organizations initiate in developing countries is always overseen and it adversely affects the environmental sustainability (murdifin et al., 2019). united nations plays a pivotal role in shaping environmental sustainability plans and agendas. the agenda 2030 with its 17 sustainable development goals and 169 targets were adopted by all member states of the un in september 2015 and aimed to be ‘transformational’, so that this world can become a better and sustainable place for living in next 15 years (united nations general assembly, 2015) (boluk et al., 2019). the open working group of united nations ended upon negotiating and finalizing the sdgs called the goals ‘an integrated, indivisible set of global priorities for sustainable development (bebbington and unerman, 2018)’. some of the goals are themselves integrative, and they address all of the three aspects i.e. social, environmental and economic of sustainable development. pattiruhu: the impact of budget, accountability mechanisms and renewable energy consumption on environmentally sustainable development: evidence from indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020700 all the other related targets are those which can easily be attained by working on all these goals (tsalis et al., 2020). all the eight major sdgs have a major focus on the environment and natural resources: (2) food and agriculture, (6) water and sanitation, (7) energy, (11) human settlements, (12) sustainable consumption and production, (13) climate change, (14) oceans, and (15) terrestrial ecosystems, while 86 targets concern some aspect of unep’s work program, including at least one in each of the 17 sdgs. the remaining 83 targets are essentially either social or economic in focus and not directly relevant to the environment. these targets and agendas prove the importance of environmental sustainability measures and their impact on the economic development of the whole world (lu et al., 2019). the essence of all these efforts related to environmental sustainability and its related counterparts incorporate participation from all the sectors. the government should make constitutions, national action plans and rules which are to be followed by public and government employees strictly. these policies should be made clear by the print and social media campaigns. students should study all the policies, rules and regulations related to environmental sustainability and then they should try to educate their elders and youngsters about all this stuff. the funds which are allocated to the government servants and the leaders of the public to spend on different projects of environmental safety and sustainability should be honestly spent on these projects. the timeline should be well-defined, and all the people should be responsible in case of any delay or corruption during completion of the whole project. the monthly audit report should be generated and should be presented to higher authorities by the accountability bureau (dachroni and muzwardi, 2017). the renewable energy resources are utilized widely all over the world and the same is the case with indonesia. the oil reserves and all the other business of people are largely dependent upon the electricity or power generation system. it is imperative for all the sectors and people of indonesia to work devotedly in this regard. the biodegradable material should be used in all industrial practices. it would help a lot to low the cost of recycling machinery and on the other, it would lessen the pollution of air and water. the natural water supplies like rivers, streams and lakes can be protected in this regard. the natural landscape of indonesia is very beautiful. the need of the hour is to maintain its sustainability. if the steps of the national action plan are implemented by the government with full zeal and devotion then it would become very easy to attain all the stated goals (santika et al., 2020). so, it can be said that all the developing countries are also aware of environmental sustainability and its importance. they have set specific goals and targets to achieve excellence in the attainment of environmental sustainability. the only problem is of resources and lack of education in common public which hinders the development in this regard. developed countries have experienced a lot of success in terms of environmental sustainability and its related fields in the last three decades. the main reason is that they have very strong accountability mechanisms at both government and public sector level. they have educated their folks in such a way that they behave responsibly and play a vital role in this regard. they have promoted environmental safety, sustainability, and proper accountability mechanisms at all communicative forums like print media, social media and on networking websites. the only way to avoid all these problems is to simply help and cooperate with the institutions which are working for our wellbeing. only the cooperation, understanding and implementation of environmental sustainability parameters can improve the condition of this whole world and can make it a better place to live in. indonesian government and public sector institutions are working very diligently to achieve all the goals of their national action plan. the only thing which should be kept in mind that everyone is accountable for his deeds and every single person should take charge and try to improve the conditions of the environment of not only his country but also of this whole world. thus, based on all mentioned above literature, the ongoing study has developed the following hypotheses: h1: budget approved for environmental development has a direct impact on environmental sustainability development in indonesia h2: accountability mechanisms of the government have a positive impact on environmental sustainability development in indonesia h3: renewable energy consumptions are positively enhanced environmental sustainability development in indonesia. 3. methodology the current article aims to examine the impact of the budget approved for environmental development, accountability mechanism of the government and renewable energy consumption on the environmental sustainability development of indonesia. the quantitative method has been executed through which secondary data has been extracted from the database of the world bank along with the finance ministry of indonesia from 1985 to 2017. in addition, the data include environmental sustainability development (esd) that has been measured as the “ratio of primary government expenditures on the environment and the original approved budget (%).” while budget approved for environmental development has been measured as the “log of a total budget of the government for environmental development”. moreover, accountability mechanism has been measured as the “cpia transparency, accountability, and corruption in the public sector rating (1=low to 6=high)” while renewable energy consumption has been measured as the renewable energy usage in a year (percentage of goods produce) and energy import has been measured as the import of energy (percentage of energy usage). these variables along with measurement have been given in table 1. for the analysis purpose, the ardl approach has been used due to this model has some advantages, such as the efficiency of the work, even with small sample sizes. “the ardl model is equally efficient for the variables that are stationary at the level i (0) or first difference i (1) or even fractionally integrated”. therefore, this study executed the ardl approach because it can investigate the short-run as well as long-run nexus among variables. the present research has developed the equation as follow: pattiruhu: the impact of budget, accountability mechanisms and renewable energy consumption on environmentally sustainable development: evidence from indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020 701 esdt=α0+β1 lnbudt+β2 rect+β3 eit+β4 amt+ et (1) where t = time period esd = environmental sustainability development bud = budget for environmental development rec = renewable energy consumption ei = energy import am = accountability mechanism. moreover, the ardl cointegrating model has been given as under: � � � � � � esd esd lnbud rec ei t t t t t � � � � � � � � � � � � � � � � � � � � � 0 1 1 2 1 3 1 4 1 5 aam esd lnbud rec ei am t t t t t t � � � � � � � � � � � � 1 1 1 2 1 3 1 4 1 5 1 1 � � � � � � (2) in equation (2) δ1, δ2, δ3, δ4, and δ5 has been highlighted the coefficients about the short-term nexus with summation signs, however, φ1, φ2, φ3, φ4, φ5, and ε1 has been used as the coefficients about the long-term nexus and gaussian white noise term, respectively. however, in the next step, this study has estimated the error correction model: � � � � � � � esd esd lnbud rec ei t t t t t � � � � � � � � � � � � � � � � � � � � 0 1 1 2 1 3 1 4 1 5 aam ecmt t t� � �1 � � (3) 4. findings the current article has checked the stationarity before examining the dynamic linkage between environmental sustainability development, budget for environmental development, energy consumption, accountability mechanism and energy import. in addition, ardl model has been considered as the flexible cointegrating approach due to its characteristics of executing when all variables are stationary at 1(0) or 1(1) or the mixture of 1(0) and 1(1). however, the ardl has the limitation of cannot be executed in the case of 1(2) (ibrahim, 2015). thus, to test the stationarity, pp and adf unit root test has been employed by the current study. the results indicated that no variables are stationary at i (2). hence, this study can proceed with the ardl approach and these figures are mentioned in table 2. the ardl bounds testing approach has been estimated secondly by the current study, the results highlighted that the values of calculated f-test exceed the upper bounds’ critical value at 5% and 10% significance level. hence, co-integration among the constructs has been confirmed. these values have been shown in table 3. the results of the current study firstly show the short-run nexus among the budget approved for environmental development, accountability mechanism of the government, renewable energy consumption and environmental sustainability development. the figures highlighted that the positive along with significant nexus among the budget approved for environmental development, accountability mechanism of the government, renewable energy consumption and environmental sustainability development and accept h1, h2 and h3. however, negative along with insignificant association among the links of energy import and environmental sustainability development. these figures are highlighted in table 4. the findings firstly show the long run nexus among the budget approved for environmental development, accountability mechanism of the government, renewable energy consumption and environmental sustainability development. the statistics show that the positive along with significant nexus among the budget approved for environmental development, accountability mechanism of the government, renewable energy consumption and environmental sustainability development and accept h1, h2 and h3. however, negative and insignificant nexus among the links of energy import and environmental sustainability development. these figures have been mentioned in table 5. 5. discussion the results revealed that positive nexus among the budget approved for environmental development, accountability mechanism of the government, renewable energy consumption and environmental sustainability development of indonesia in both the short and long run. these findings are similar to the output of the he et al. (2016) who also examined that renewable energy consumptions have positively impacted on the environmental sustainability development. in addition, a study by de silva et al. (2020) table 1: variables with measurements s# variables measurement sources 1 environmental sustainability development primary government expenditures on the environment as a proportion of the original approved budget (%) finance ministry of indonesia 2 budget a total budget of the government for environmental development finance ministry of indonesia 3 accountability mechanism cpia transparency, accountability, and corruption in the public sector rating (1=low to 6=high) world bank database 4 renewable energy usage renewable energy usage in a year (percentage of goods produce) world bank database 5 energy import import of energy (percentage of energy usage) world bank database table 2: unit root test test esd lnbud rec ei am augmented dickey-fuller test (adf) 1(0) –2.142 –0.476 –1.484 –1.244 –1.615 1(1) –3.985 –7.611 –4.114 –4.113 –5.944 phillips–perron test (pp) 1(0) –2.402 –0.403 –2.311 –1.144 –1.715 1(1) –4.902 –8.135 –4.559 –4.448 –5.135 pattiruhu: the impact of budget, accountability mechanisms and renewable energy consumption on environmentally sustainable development: evidence from indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020702 exposed that the accountability mechanisms of the government could enhance the environmental sustainability development and this could be similar to the current study outcomes. moreover, a study conducted by gelderman et al. (2017) investigated that the approved budget for the sustainability purpose has positive influence the environmental sustainability development and this also matched with the findings of the ongoing study. the results also revealed that negative linkage among the energy import and environmental sustainability development of indonesia. 6. conclusion thus, the conclusion has drawn by the present study that the indonesian government has proved reasonable budget for the environmental sustainability purpose and also has strong accountability mechanisms along with high but effective renewable energy consumption that is the reason of high environmental sustainability development in the country. this conclusion guided to the other countries they should also focus on the measures that are taken by the indonesian government for environmental sustainability development. these findings provided suitable measures to the regulatory authority of the country that they should approve more budget for environmental development along with maintaining the high accountability mechanisms that enhance the environmental sustainability development in indonesia. this study has some limitations such as they ignore the cross country analysis and suggested to the future studies that they should add more countries in their analysis. in addition, this study has adopted the ardl adopted due to the one country time series analysis and recommended that future studies should adopt the panel analysis such as robust standard error and generalized method of moment (gmm) in the studies. finally, the time frame of the study has been used only 32 years from 1985 to 2017 and suggested that future studies should increase the data set to expand their scope of the study. references astuti, w. (2018), why village fund not yet promoting environmental sustainability? an empirical study of village fund incentives in central java province, indonesia. yustisia jurnal hukum, 7(1), 190-196. asumadu-sarkodie, s., yadav, p. (2019), achieving a cleaner environment via the environmental kuznets curve hypothesis: determinants of electricity access and pollution in india. clean technologies and environmental policy, 21(9), 1883-1889. bebbington, j., unerman, j. (2018), achieving the united nations sustainable development goals. accounting, auditing and accountability journal, 31(1), 2-24. bertella, g. (2019), sustainability in wildlife tourism: challenging the assumptions and imagining alternatives. tourism review, 74(2), 246-255. boluk, k.a., cavaliere, c.t., higgins-desbiolles, f. (2019), a critical framework for interrogating the united nations sustainable development goals 2030 agenda in tourism. journal of sustainable tourism, 27(7), 847-864. cho, c.h., laine, m., roberts, r.w., rodrigue, m. (2018), the frontstage and backstage of corporate sustainability reporting: evidence from the arctic national wildlife refuge bill. journal of business ethics, 152(3), 865-886. dachroni, r., muzwardi, a. (2017), the analysis of anti corruption behavior on bps services at batam city indonesia. jurnal ilmu pemerintahan kajian ilmu pemerintahan dan politik daerah, 2(2), 96-102. de silva, k., yapa, p.w.s., vesty, g. (2020), the impact of accountability mechanisms on public sector environmental sustainability performance: a case study of sri lanka. australasian accounting, business and finance journal, 14(3), 38-55. fiorentino, g., zucaro, a., ulgiati, s. (2019), towards an energy efficient chemistry. switching from fossil to bio-based products in a life cycle perspective. energy, 170, 720-729. fisher, m.r., moeliono, m., mulyana, a., yuliani, e.l., adriadi, a., judda, j., sahide, m.a.k. (2018), assessing the new social forestry project in indonesia: recognition, livelihood and conservation? international forestry review, 20(3), 346-361. gelderman, c.j., semeijn, j., vluggen, r. (2017), development of sustainability in public sector procurement. public money and management, 37(6), 435-442. gérardy, r., morodo, r., estager, j., luis, p., debecker, d.p., monbaliu, j.c.m. (2020), sustaining the transition from a petrobased to a biobased chemical industry with flow chemistry accounts on sustainable flow chemistry. berlin, germany: springer. p111-145. halimatussadiah, a. (2020), mainstreaming the sustainable development goals into national planning, budgetary and financing processes: indonesian experience. mpdd working paper series wp/20/06, united nations economic and social commission for asia and the pacific. table 3: ardl bound test model f-statistics lag level of significance (%) bound test critical values i(0) i(1) esd/(lnbud,rec,ei,am) 5.120 4 1 4.5 5.02 5 3.37 4.47 10 3.13 4.16 table 4: short-run coefficients variables beta s.d. t-statistics p-values d(lnbud) 0.555895 0.273246 2.034413 0.0646 d(rec) 3.664565 1.025358 3.573936 0.0038 d(ei) –126.257830 77.385978 –1.631534 0.1287 d(am) 0.733537 0.206316 3.555411 0.0040 ecm(–1) -0.581288 0.217867 –2.668091 0.0205 table 5: long-run coefficients variables beta s.d. t-statistics p-values d(lnbud) 0.956315 0.664893 1.438299 0.1759 d(rec) 6.304212 2.305644 2.734252 0.0181 d(ei) –217.203453 190.717768 –1.138874 0.2770 d(am) 1.261915 0.370850 3.402762 0.0052 c 396.388392 355.923351 1.113690 0.2872 @trend 0.502763 0.351509 1.430300 0.1781 pattiruhu: the impact of budget, accountability mechanisms and renewable energy consumption on environmentally sustainable development: evidence from indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020 703 he, y., xu, y., pang, y., tian, h., wu, r. (2016), a regulatory policy to promote renewable energy consumption in china: review and future evolutionary path. renewable energy, 89, 695-705. hidayat, n.k., offermans, a., glasbergen, p. (2018), sustainable palm oil as a public responsibility? on the governance capacity of indonesian standard for sustainable palm oil (ispo). agriculture and human values, 35(1), 223-242. ibrahim, m.h. (2015), oil and food prices in malaysia: a nonlinear ardl analysis. agricultural and food economics, 3(1), 1-14. kasayanond, a., umam, r., jermsittiparsert, k. (2019), environmental sustainability and its growth in malaysia by elaborating the green economy and environmental efficiency. international journal of energy economics and policy, 9(5), 465. khan, o., younas, m.z. (2019), interaction between energy consumption and economic growth in pakistan: a more comprehensive analysis using ardl approach. energy economics letters, 6(1), 30-51. kirwa, t., ngeno, v. (2020), organizational capital and financial performance; what is the mediation effect of firm innovation: evidence from insurance firms in kenya. journal of accounting, business and finance research, 8(2), 72-78. lu, h., villada, j.c., lee, p.k. (2019), modular metabolic engineering for biobased chemical production. trends in biotechnology, 37(2), 152-166. morone, p., d’amato, d. (2019), the role of sustainability standards in the uptake of bio-based chemicals. current opinion in green and sustainable chemistry, 19, 45-49. muda, i., naibaho, r. (2018), variables influencing allocation of capital expenditure in indonesia. paper presented at the iop conference series: earth and environmental science. murdifin, i., pelu, m.f.a., perdana, a.a.h., putra, k., arumbarkah, a.m., muslim, m., rahmah, a. (2019), environmental disclosure as corporate social responsibility: evidence from the biggest nickel mining in indonesia. international journal of energy economics and policy, 9(1), 115-120. nawaz, m.a., azam, m.a., bhatti, m.a. (2019), are natural resources, mineral and energy depletions damaging economic growth? evidence from asean countries. pakistan journal of economic studies, 2(2), 37-54. nawaz, m.a., yousaf, w., hussain, m.s., riaz, m. (2020), effect of tourism growth on co2 emissions and economic growth in south asian countries: a panel gmm approach. hamdard islamicus, 43(1), 406-415. nong, d., escobar, n., britz, w., börner, j. (2020), long-term impacts of bio-based innovation in the chemical sector: a dynamic global perspective. journal of cleaner production, 272, 122738. ögmundarson, ó., herrgård, m.j., forster, j., hauschild, m.z., fantke, p. (2020), addressing environmental sustainability of biochemicals. nature sustainability, 2(3), 1-8. pagliaro, m. (2019), an industry in transition: the chemical industry and the megatrends driving its forthcoming transformation. angewandte chemie international edition, 58(33), 11154-11159. paletta, a., bonoli, a. (2019), governing the university in the perspective of the united nations 2030 agenda: the case of the university of bologna. international journal of sustainability in higher education, 20(3), 500-514. santika, w.g., anisuzzaman, m., simsek, y., bahri, p.a., shafiullah, g., urmee, t. (2020), implications of the sustainable development goals on national energy demand: the case of indonesia. energy, 196, 100-117. sarkodie, s.a. (2018), the invisible hand and ekc hypothesis: what are the drivers of environmental degradation and pollution in africa? environmental science and pollution research, 25(22), 21993-22022. sugiawan, y., managi, s. (2016), the environmental kuznets curve in indonesia: exploring the potential of renewable energy. energy policy, 98, 187-198. tannady, h., erlyana, y., nurprihatin, f. (2019), effects of work environment and self-efficacy toward motivation of workers in creative sector in province of jakarta, indonesia. quality-access to success, 20(172), 165-168. tsalis, t.a., malamateniou, k.e., koulouriotis, d., nikolaou, i.e. (2020), new challenges for corporate sustainability reporting: united nations’ 2030 agenda for sustainable development and the sustainable development goals. corporate social responsibility and environmental management , 27(4), 1617-1629. udemba, e.n., güngör, h., bekun, f.v. (2019), environmental implication of offshore economic activities in indonesia: a dual analyses of cointegration and causality. environmental science and pollution research, 26(31), 32460-32475. vergura, s. (2018), hypothesis tests-based analysis for anomaly detection in photovoltaic systems in the absence of environmental parameters. energies, 11(3), 485. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 3 • 2021 403 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(3), 403-408. the role of electricity and energy consumption influences industrial development between regions in indonesia muhammad fikry hadi, muhammad hidayat*, dwi widiarsih, neng murialtih department of economics, faculty of economic and bussines, universitas muhammadiyah riau, indonesia. *email: m.hidayat@umri.ac.id received: 15 decemeber 2020 accepted: 04 march 2021 doi: https://doi.org/10.32479/ijeep.11082 abstract our research aims to determine the effect of electricity distribution and energy consumption on industrial development dynamics that occur between regions in indonesia by adding investment and inflation as control variables. the analysis tools that we use are static (fixed effect) and dynamic (gmm) panel data model with a dataset of 34 provinces for the 2012-2019 period. the static model results state that the distribution of electricity and investment has a significant positive effect on the industry, and so does energy consumption, but not significantly. in contrast, inflation has a significant negative effect. there are differences in dynamic results, namely, electricity distribution and energy consumption have a negative and significant effect on industrial development. these results suggest different actions in industrial development concerning timeframes. keywords: electricity distribution, energy consumption, industry, gmm, indonesia jel classifications: c33, o14, q40 1. introduction the process of industrialisation and industrial development is a pathway of activities to improve people’s welfare in the sense of a more advanced level of life or a higher standard of living. industrial development is part of long-term economic development to achieve a balanced economic structure. industrialisation is the “most popular” in development efforts, especially from improving economic conditions. industrialisation is considered a plan as well as a remedy for many countries. as a strategy, industrialisation is considered a “linear” process that must be passed through several interrelated and sequential stages in transforming economic structures in many countries. meanwhile, industrialisation is seen as useful in overcoming underdevelopment problems, poverty, inequality, and unemployment. where according to this view, it is assumed that the developed industry is labour-based based industry, prioritises local core competencies (local resources), has a high multiplier impact (output, income, labour, and technology), and brings regional spillover to the surrounding area (kuncoro, 2007). the 9th sdg’s objectives are to build long-lasting infrastructure, support inclusive and sustainable industrialisation, and foster innovation, while some of the goals of this goal are; (1) encourage inclusive and sustainable industrialisation and, by 2030, significantly increase the industry’s share of job creation and gross domestic product, in line with the national situation, and double the industry’s share in less developed countries; (2) increasing access of small scale industries and other small scale businesses, especially in developing countries to funding services, including affordable credit combined with value chains and markets. indonesia is one of the countries plotted as a new industrial country. this can be seen from the manufacturing industry sector’s contribution from 2015 to 2019, an average of 21.27% with an average growth rate of the industrial sector of 4.27%. meanwhile, the value of contributions and growth that occur fluctuates from this journal is licensed under a creative commons attribution 4.0 international license hadi, et al.: the role of electricity and energy consumption influences industrial development between regions in indonesia international journal of energy economics and policy | vol 11 • issue 3 • 2021404 year to year. in 2015 the contribution value was 21.54% with a growth rate of 4.33%, the trend in the following year decreased the value of the contribution and the growth rate became 21.38% and 4.26%. furthermore, until 2019, a continuing decline value contribution with a final value of 20.79%, for value growth increased in 2017 to 4.27%, again decreased until 2019 to 3.80%. the role of industry in structural development in an economic indicator is the manufacturing sector’s contribution to gdp, absorbed labour, and industrial commodities contribution to exports of goods and services has improved or vice versa (arsyad, 2010). furthermore, industries can be classified as capitalintensive and labour-intensive industries, and the trend of industrial development in indonesia is more labour-intensive. development of the manufacturing industry is inseparable from the flow of capital provided by investors and the support of available infrastructure, especially energy infrastructure and supply or fuel oil consumption, especially diesel. it is known that factories operate more with the use of diesel fuel. therefore, the research aims to determine the effect of energy infrastructure, fuel consumption, and investment on developing the manufacturing industry sector in indonesia’s provinces. the study is structured as follows: the next section briefly reviews the research conducted on the subject. the following section describes the data and methodology, while section 4 presents and explains the empirical results and discussion. the final section presents conclusions and policy implications. 2. literatur review haraguchi et al., (2019) analyses industrialisation drivers in developing countries. different industrialisation patterns are likely to be influenced due to significant political, technological and organisational changes. the analysis results reveal that successful industrialisation is driven by factors, including the country’s initial economic conditions, contributing factors and other characteristics, such as demography and geography. other results suggest that other variables over which policymakers can control play an important role. these include, among other things, promotion of investment (whether publicly or privately funded) and education; trade management and capital disclosure; financial sector development and promotion of macroeconomic and institutional stability. furthermore, another paper by haraguchi et al. (2019) shows that human resources and institutions represent contextual factors that support industrial growth, along with macroeconomic policies related to investment and openness to foreign trade and capital. also found, most of these factors drive the acceleration of industry and contribute to the continuous industrialisation process that characterises economic growth. research by franck and galor (2019) with research questions is industrialisation conducive to economic development in the 21st century? research shows that early industrialisation has an adverse effect on long-term prosperity, stemming from the negative impact of the adoption of labour-intensive, skillless technology in the early stages of industrialisation at the current human resource level and thus the incentive to adopt skills-intensive technology. opoku and boachie (2020) states that the main concern about the environment is greenhouse gas emissions and their impact on climate change in recent years. using the pooled mean group estimation technique, it is found that the effect of industrialisation on the environment is generally insignificant. however, the effect of foreign direct investment on the environment was found to be very significant. the empirical results from kumari and sharma (2018) on the causal relationship between gross domestic product, foreign direct investment and electricity consumption in india, show that electricity consumption plays a vital role in gdp and high gdp attracts more fdi to india. next, results by tiwari et al. (2020) provide evidence of a unidirectional causality that flows towards overall economic growth for electricity consumption at the state level. however, there is a unidirectional causal relationship at the sectoral level ranging from electricity consumption to economic growth in the agricultural sector and economic growth to electricity consumption in the industrial sector. ozturk and acaravci (2011) examined the short and long-run causality between electricity consumption and economic growth in 11 middle eastern and north african (mena) countries using the autoregressive distributed lag (ardl) testing approach of cointegration and error correction model vectors. cointegration test results show no cointegration between electricity consumption and economic growth in three of the seven countries (iran, morocco and syria). thus, a causal relationship cannot be estimated for these countries. however, cointegration and causal relationships were found in four countries (egypt, israel, oman and saudi arabia). the overall results show no relationship between electricity consumption and economic growth in most mena countries. the same previous results were also obtained from acaravci and ozturk (2010) in 15 transition countries (albania, belarus, bulgaria, czech republic, estonia, latvia, lithuania, macedonia, moldova, poland, romania, russian federation, serbia, slovak republic and ukraine). apergis and payne (2011) examined the relationship between electricity consumption and economic growth for 88 countries categorised into four panels based on world bank income classifications (high, middle-upper, middle-lower and low income) the framework of a multivariate panel for the period 1990-2006. the results reveal (1) a two-way causality between electricity consumption and economic growth in both the short and long term for the panel of highand middle-to-upper income countries; (2) unidirectional causality from electricity consumption to economic growth in the short run, but two-way causality in the long run for a panel of lower-middle-income countries; and (3) unidirectional causality from electricity consumption to economic growth for a panel of low-income countries. meidani and zabihi (2014) paper discusses the causal relationship between real gdp and energy consumption in various economic hadi, et al.: the role of electricity and energy consumption influences industrial development between regions in indonesia international journal of energy economics and policy | vol 11 • issue 3 • 2021 405 sectors including (household and commercial, industrial, transportation and agricultural sectors) for iran during 1967-2010 using a time series technique known as the toda-yamamoto method. also, an error correction model is estimated so that the results of the two methods are compared. the results find a robust unidirectional causality from energy consumption in the industrial sector to real gross domestic product. energy consumption in the industrial sector appears to be able to boost economic development. tang et al. (2016) examined the relationship between energy consumption and economic growth in vietnam using the neoclassical solow growth framework for 1971-2011. the concepts and methods of cointegration and granger causality are used to build relationships between variables. the results confirm the cointegration between variables. in particular, energy consumption, fdi and capital stock positively affect economic growth in vietnam. gungor and simon (2017) examined the relationship between energy consumption, financial development (fd), economic growth, industrialisation and urbanisation in south africa for the period 1970-2014. the results confirm that there is a longrun equilibrium relationship between these variables. moreover, urbanisation, fd, and industrialisation are positively correlated with energy consumption in the long run. the results also indicate a long-term two-way causality between industrialisation and energy utilisation, fd and energy consumption, fd and industrialisation. next, tran et al. (2020) examine the effects of energy consumption, economic growth, and the trade balance in east asian countries. they are using panel data analysis during the period 1996-2015. the results show that energy consumption has a negative impact on the trade balance, while economic growth can have a negative impact on the trade balance but is not significant. furthermore, the same results from shahbaz et al. (2017) that the results of asymmetric causality show that only negative shocks to energy consumption impact india’s economic growth during the period 1960q1-2015q4. asafu-adjaye et al. (2016) examine the relationship between economic growth and fossil and non-fossil fuels consumption. except for developing importers, evidence of a two-way causality between fossil fuel consumption and real gdp in all subsamples were observed. fossil fuel conservation efforts can directly disrupt economic growth. inflation, as an important economic indicator, can have a significant influence on gdp growth. however, during periods of negative (falling) inflation, economic structure development can create volatility and uncertainty, impacting industrial growth and potential (dinç et al., 2019). next, roncaglia de carvalho et al. (2018) show an inverse and low correlation between inflation persistence and economic development, which implies that the model can only partially explain inflation differences across different economic development levels. 3. methodology 3.1. dataset this research method is the quantitative method with static panel regression (fixed effect or random effect) and dynamic (first difference or sysgmm). this research uses analysis units of 34 provinces with the period 2012-2019. data sources come from many surveys by the central statistics agency (bps) including socio-economic, grdp, investment, and inflation surveys. besides, oil and gas data is obtained from the ministry of energy and mineral resources. for the model formula to be used, several variables must be defined as follows: (1) industry (ind), calculated from the share of the industrial sector to grdp; (2) electricity distribution (elec), this variable is the ratio of electricity distribution to total population which reflects the availability of electricity capacity (kwh), the source of data from economic surveys and regional welfare statistics by the central statistics agency; (3) energy consumption (bbm) of this variable is represented by the realization of the quota of diesel oil and data sourced from the ministry of energy and mineral resources; (4) investment (inv), the variable used is the annual investment data in units of billions of rupiah; (5) inflation (inf), is the annual inflation data obtained from bps. 3.2. model panel data the pooled data panel is a combination of cross-section and series data (greene, 2012). if we have t is time (t = 1,2,…, t) and n the number of individuals (i = 1,2,…, n), then using panel data we will have a total unit of observation n×t. if the number of time units is the same for each individual, then the data is called a balanced panel. on the other hand, the number of time units is different for each individual, called an unbalanced panel (verbeek, 2017). in this study, a balanced panel was used. in this study, the general equation used is as follows: lnindit = α + β1elecit + β2 lnbbmit + β3 invit + β4infit + εit (1) as is generally known, in panel data regression, there are three model approaches: pooled least square (pls), fixed effect model (fem), and random effect model (rem). in this study, the model used is based on the results of the selection from the hausman test. a dummy variable is added to change the intercept in the fixedeffect method, but the other coefficients remain the same for each observed province. to consider each unit’s individuality crosssection can be done by making different interceptions in each province. the equation model used is the least square dummy variable (lsdv), in which the dummy variable is added as much as the number of cross-sections is reduced by one to avoid dummy variable traps. so, the application in eq (1) becomes as follows: lnind = + elec + lnbbm + inv + inf + d + it 1 it 2 it 3 it 4 it i=1 33 i c i α β β β β α ε∑ iit (2) hadi, et al.: the role of electricity and energy consumption influences industrial development between regions in indonesia international journal of energy economics and policy | vol 11 • issue 3 • 2021406 furthermore, for the random effect method, the specific effect of each individual is αi treated as part of the error component which is random and uncorrelated with the observed explanatory variable (xit). thus, the random effect model equation can be written as follows: yit = αi + βj xit + eit (3) eit = (μit + vt + wit) (4) where: μi = component cross section error; vi = component time series error; wit = component combination error. next, the application of eq (3) to estimate the industrial model in eq (1) is as follows: lnindit = α + β1 elecit + β2ln bbmit + β3 invit + β4 infit + eit (5) the appropriate method for estimating the random-effects model is generalized least squares (gls) with homoscedastic assumptions and no cross-sectional correlation. 3.3. model dynamic panel data dynamic panel data regression describes the relationship between economic variables which is dynamic. in line with cross-section and time-series models in panel data, dynamic relationships are characterized by including the lag of the dependent variable as regressors in the regression (greene, 2012). the general form of the dynamic panel data regression model proposed by baltagi (2005) is as follows: y = y x +uit t it t itδ βi, − +1 (6) with uit it is assumed that the one-way error component is as follows: uit = εit + μit (7) next, merging eq (6) and (7) then the dynamic panel equation is obtained as follows: t it ,t 1 it it ity y x + +i −= δ + β ε μ (8) thus, the dynamic panel data regression model used in this study becomes: lnindit = δindi,t−1 + β1elecit + β2 lnbbmit + β3 invit + β4 infit + uit + εit (9) the dynamic panel model uses the generalized method of moments (gmm) approach. gmm has two models in the estimation, namely first-differences gmm and system gmm. first-differences approach was developed by arellano and bond (1991) with the generalized method of moments (gmm) method were lag of dependent variable starting from t-2, or called fdgmm is used. this approach will produce a consistent estimator of α when n→∞ with t is relatively small. the sys-gmm method is useful for estimating the system of first-differences equations and at the level, where the instruments used at that level are the first-differences lag of the series (blundell and bond, 1998). sys-gmm estimator combines the first differentiation equation group with the level value as the instrument plus the level equation group with the first difference as an instrument. the validity of these additional instruments can be determined using the sargan test for over-identifying instruments. in research used a validity test that applies to gmm. as suggested by arellano and bond (1991); arellano and bover (1995); blundell and bond (1998), there are two test specifications. firstly, the sargan test of over-identifying restrictions that tests the instruments’ overall validity and hypothesis null is that all instruments as a group are exogenous. the second test examines the hypothesis null that error term εit of the differenced equation is not serially correlated particularly in the second-order (ar2). 4. results and discussion this study’s first model selection is to pay attention to the hausman test results, which is useful for choosing a static model between fixed-effects and random-effects. based on table 1, the hausman test probability value is 0.000, which means that h0 is rejected and states that the best model to use is the fixed-effect. furthermore, for the dynamic model, the sargan test results’ prob value on the fd-gmm and sys-gmm models is greater than 0.05 and h is accepted, which means that the over-identifying restriction conditions in the use of the model are valid. the p-value of ar (2) greater than 0.05 shows no density of serial correlation problems in the second-order. the model is feasible to use, and it can be table 1: summary of static and dynamic panel data results variable fixed effect random effect fd-gmm sys-gmm constanta 9.24 (63.35) 9.115 (41.38) 1.538 (16.99) 1.072 (21.10) lnindit−1 0.848 (84.05)*** 0.898 (170.66)*** elec 0.0003 (4.75)*** 0.0003 (5.66)*** 0.000021 (1.57) −0.000026 (−4.13)*** bbm 0.012 (1.08) 0.019 (1.658)* −0.0005 (−0.59) −0.0011 (−1.81)* inv 0.0067 (6.56)*** 0.0075 (7.45)*** 0.0004 (2.48)** 0.0002 (1.83)* inf −0.01 (−3.31)*** −0.0099 (−3.18)*** −0.0026 (−5.93)*** −0.0009 (−2.68)** hausman test 54.58 (0.000) sargan test (p-value) 28.87 (0.094) 29.40 (0.293) ar (2) (p-value) −1.655 (0.098) −1.589 (0.112) adj. r2 0.9932 0.2551 f-stat 1077.59 (0.000) 24.21 (0.000) obs. 272 272 238 238 figures in the parentheses are t-statistics. ***, ** and * denote significance at 1%, 5% and 10% levels, respectively hadi, et al.: the role of electricity and energy consumption influences industrial development between regions in indonesia international journal of energy economics and policy | vol 11 • issue 3 • 2021 407 concluded that the error term in the model has no serial, and it can be said that the estimator used is efficient. the results of the fixed-effect static model estimation (table 1). state that the distribution of electricity (elec) is positively and significantly related to industrial development. if there is an increase in one unit’s electricity distribution ratio, it can increase the industry by 0.0003%. furthermore, energy consumption (bbm) is positive at 0.012, which means that an increase in energy consumption per unit will increase industrial value but not significantly. the investment coefficient is positive and significant to the industrial value, which is 0.0067. finally, inflation has a negative and significant impact on industrial value, where if there is an increase in inflation by one unit, the industrial value will decrease by 1%. the fd-gmm results state that electricity distribution has a negative and insignificant relationship with the dynamic model industry. the energy consumption (bbm) coefficient is positive and does not significantly affect the industry’s value. furthermore, the investment coefficient has a positive and significant relationship with the industry, and finally, inflation has a negative and significant relationship with the industry. meanwhile, the sys-gmm model results state that electricity distribution has a significant negative effect on the industrial value; this is different from the previous model results. furthermore, energy consumption (bbm) has a negative and significant industrial value. the investment coefficient has a positive and significant value, which means it can increase the industrial value that occurs. finally, inflation has a negative and significant value to the industry. based on the static model, the distribution of electricity supports industrial value development, which is in line with kumari and sharma (2018); tiwari et al. (2020) where existing electricity is related to economic growth based on gdp. on the other hand, electricity distribution in a sustainable term is negatively related to industrial development, and this result is not in line with amaluddin (2020); apergis and payne (2011) which states that there is a relationship between electricity and an increase in gdp. the distribution of electricity used in this study characterizes the availability of electricity for each region. in real terms, there are still areas that still depend on neighbouring power plants, even if this continues, so automatically, this area will always depend, and the costs will increase. for other reasons, the electricity-producing regions also continue to develop and meet their needs. for this reason, the government should pay attention to the supporting energy infrastructure in the form of an even distribution of electricity between regions and later it will achieve an electrification ratio of 100%. this is also in line with the results hidayat et al. (2020) state that energy infrastructure development, especially electricity, can reduce inequality between regions. next, the static model’s energy consumption positively affects the industry, and it is just not significant. however, when viewed in a relationship, this result is in line with asafu-adjaye et al. (2016); gungor and simon (2017); meidani and zabihi (2014); tang et al. (2016) which states that there is a relationship between energy consumption in improving the economy. the inverse proportion occurs in the dynamic model, and there is a negative and significant relationship, which is also in line with shahbaz et al. (2017); tran et al. (2020). in this study, energy consumption is the consumption of diesel fuel, which is the primary fuel for industrialization. consumption in a continuous-time raises the concern that this fuel is becoming scarce, resulting in this commodity’s price increase. industrial operating costs will automatically increase and will hamper industrial growth. it is only natural for policymakers to seek and continue to innovate in renewable energy to be used in sustainable industries. meanwhile, in the short term, the government is serious about monitoring subsidized diesel fuel distribution to make it useful and efficient. furthermore, the dynamic estimation results, lag-industry, are positive and significant, which states that the industrial value that occurred in the previous period can affect the current industry value. other variables in the model are considered constant or cateris paribus. in fact, the development of industries that already have supporting infrastructure will encourage industrialization development, and policymakers should continue to pay attention to these supporting facilities, and do not forget to make regulations beneficial to domestic industries. 5. conclusion based on the results and discussion above, it can be concluded that statically the distribution of electricity and investment can significantly increase industrial development, and inflation significantly reduces industrial value. on the other hand, the dynamic model states that electricity distribution and energy consumption (diesel) are negatively and significantly related to industrialization, while investment and inflation are the same. these differences provide an overview for policymakers to issue policies that are right on target based on the period, both short, medium and long term. references acaravci, a., ozturk, i. (2010), electricity consumption-growth nexus: evidence from panel data for transition countries. energy economics, 32(3), 604-608. amaluddin, a. (2020), the dynamic link of electricity consumption, internet access and economic, growth in 33 provinces of indonesia. international journal of energy economics and policy, 10(4), 309-317. apergis, n., payne, j.e. (2011), a dynamic panel study of economic development and the electricity consumption-growth nexus. energy economics, 33(5), 770-781. arellano, m., bond, s. (1991), some tests of specification for panel data: monte carlo evidence and an application to employment equations. the review of economic studies, 58(2), 277-297. arellano, m., bover, o. (1995), another look at the instrumental variable estimation of error-components models. journal of econometrics, 68(1), 29-51. arsyad, l. (2010), ekonomi pembangunan. 5th ed. yogyakarta: stie ykpn. asafu-adjaye, j., byrne, d., alvarez, m. (2016), economic growth, fossil hadi, et al.: the role of electricity and energy consumption influences industrial development between regions in indonesia international journal of energy economics and policy | vol 11 • issue 3 • 2021408 fuel and non-fossil consumption: a pooled mean group analysis using proxies for capital. energy economics, 60, 345-356. baltagi, b.h. (2005), econometric analysis of panel data. 3rd ed. chichester, united kingdom: john willey and sons. blundell, r., bond, s. (1998), initial conditions and moment restrictions in dynamic panel data models. journal of econometrics, 87(1), 115-143. dinç, d.t., gökmen, a., üstündağ, k. (2019), economic growth inflation nexus and its impact on the development of the automotive industry: the case of turkey. international journal of economics and business research, 18(1), 94-111. franck, r., galor, o. (2019), flowers of evil? industrialization and long run development. journal of monetary economics, 117, 108-128. greene, w.h. (2012), econometric analysis. 7th ed. london, england: pearson education. gungor, h., simon, a.u. (2017), energy consumption, finance and growth: the role of urbanization and industrialization in south africa. international journal of energy economics and policy, 7(3), 268-276. haraguchi, n., martorano, b., sanfilippo, m. (2019), what factors drive successful industrialization? evidence and implications for developing countries. structural change and economic dynamics, 49, 266-276. haraguchi, n., martorano, b., sanfilippo, m., shingal, a. (2019), manufacturing growth accelerations in developing countries. review of development economics, 23(4), 1696-1724. hidayat, m., darwin, r., hadi, m.f. (2020), does energy infrastructure reduce inequality inter-regional in riau province, indonesia? international journal of energy economics and policy, 10(1), 160-164. kumari, a., sharma, a.k. (2018), causal relationships among electricity consumption, foreign direct investment and economic growth in india. electricity journal, 31(7), 33-38. kuncoro, m. (2007), ekonomika industri indonesia: menuju negara industri baru 2030. 1st ed. yogyakarta: andi publisher. meidani, a.a.n., zabihi, m. (2014), energy consumption and real gdp in iran. international journal of energy economics and policy, 4(1), 15-25. opoku, e.e.o., boachie, m.k. (2020), the environmental impact of industrialization and foreign direct investment. energy policy, 137, 111178. ozturk, i., acaravci, a. (2011), electricity consumption and real gdp causality nexus: evidence from ardl bounds testing approach for 11 mena countries. applied energy, 88(8), 2885-2892. roncaglia de carvalho, a., ribeiro, r.s.m., marques, a.m. (2018), economic development and inflation: a theoretical and empirical analysis. international review of applied economics, 32(4), 546-565. shahbaz, m., van hoang, t.h., mahalik, m.k., roubaud, d. (2017), energy consumption, financial development and economic growth in india: new evidence from a nonlinear and asymmetric analysis. energy economics, 63, 199-212. tang, c.f., tan, b.w., ozturk, i. (2016), energy consumption and economic growth in vietnam. renewable and sustainable energy reviews, 54, 1506-1514. tiwari, a.k., eapen, l.m., nair, s.r. (2020), electricity consumption and economic growth at the state and sectoral level in india: evidence using heterogeneous panel data methods. energy economics, 94, 105064. tran, t.n., nguyen, t.t., nguyen, v.c., vu, t.t.h. (2020), energy consumption, economic growth and trade balance in east asia: a panel data approach. international journal of energy economics and policy, 10(4), 443-449. verbeek, m. (2017), a guide to modern econometrics. 5th ed. john wiley and sons, inc. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 6 • 2022 67 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(6), 67-72. the effect of electricity generation, thermal energy production, fixed capital investment, and consumer price index on economic growth in kazakhstan artur bolganbayev1*, baltaim sabenova2, gulmira mombekova1, gulnur sultankhanova1, tazhibayeva raikhan musamatovna1 1khoja akhmet yassawi international kazakh-turkish university, turkestan, kazakhstan, 2peoples’ friendship university named after academician a. kuatbekov, shymkent, kazakhstan. *email: artur.bolganbayev@ayu.edu.kz received: 21 july 2022 accepted: 20 october 2022 doi: https://doi.org/10.32479/ijeep.13557 abstract many local and global factors affect the growth of national economies. among these factors, energy production is one of the main sources of economic growth. this study examines the impact of energy production, especially electricity generation and thermal energy production, on economic growth in kazakhstan. to provide a better explanation for the effect of energy production on economic growth, we also included fixed capital investment and consumer price index variables in our research model. thus, economic growth data, fixed capital investments, consumer price index, electricity generation, and thermal energy production are determined as research variables. research data were obtained from the databases of the world bank and the national bureau of statistics of the republic of the agency of strategic planning and reforms of kazakhstan. the data range is from 2002 to 2020. the findings showed that fixed capital investment has the most dominant effect on economic growth. this is a natural result from a macroeconomic point of view. another critical finding is that both electricity generation and fixed capital investments have a positive effect on economic growth. when the variable of the amount of electricity generated is included in the model, the explanatory power of the model increases from 85% to 90.7%. however, the effect of thermal energy production was found to be statistically insignificant. this insignificance is a research problem that needs to be analyzed in detail, taking into account the general energy production structure of kazakhstan. keywords: kazakhstan, electricity generation, thermal energy, fixed capital investment, consumer price index, multivariate regression jel classifications: c13, c20, c22 1. introduction this study examines the impact of energy production, especially electricity generation and thermal energy production, on economic growth. to provide a better explanation for the effect of energy production on economic growth, we also included fixed capital investment and consumer price index variables in our research model. kazakhstan gained its independence after the collapse of the soviet union and soon started a major transformation in its economic mentality. in this way, it expanded its economy and experienced a rapid and great transformation by integrating with the world economy. national economies such as kazakhstan, which experienced a series of changes to adapt to the free market economy after the soviets, were called transition economies (kökocak, 2011). since transition economies are a subject of interest, many academic studies have been conducted on different dimensions of economic growth (gdp) in kazakhstan (alagöz et al., 2011; khan, et al., 2012; mudarissov and lee, 2014; xiong et al., 2015; özdil and turdalieva, 2015; kelesbayev et al., 2022a; raihan and tuspekova, 2022; mukhamediyev and spankulova, 2020, bolganbayev et al., 2022). this journal is licensed under a creative commons attribution 4.0 international license international journal of energy economics and policy | vol 12 • issue 6 • 202268 bolganbayev, et al.: the effect of electricity generation, thermal energy production, fixed capital investment, and consumer price index on economic growth in kazakhstan mukhtarov et al. (2020) emphasized that kazakhstan managed to become the second country after russia among the postsoviet countries in terms of economic size. economic growth based on natural resources alone is not enough for a country’s wealth. because when a country bases its economy only on oil and similar natural resource exports, it can be adversely affected by fluctuations in world oil prices. studies on the effect of fluctuations in global oil prices on kazakhstan’s gdp also support this effect (bolganbayev et al., 2021; kelesbayev et al., 2022b; aldıbekova, 2018). the data range is 2002-2020. the relevant data were obtained from the world bank database and the database of the bureau of national statistics of the agency of strategic planning and reforms of the republic of kazakhstan. 2. literature review due to its importance, numerous academic studies have been conducted on the different dimensions of kazakhstan’s economic growth. these studies examined different variables that affect and interact with kazakhstan’s economic growth. some of the important ones are summarized below. suleimenova (2016) tried to reveal the relationship between economic growth, energy consumption, and financial development in kazakhstan in her master’s thesis titled “empirical analysis on the relationship between energy, finance, and growth in kazakhstan (1994-2013).” she analyzed empirical data and differentiated economic growth models using models such as the vector autoregression model for cointegration, johansen cointegration, and impulse response tests for kazakhstan, using data from 1994 to 2013. she concluded that there is a strong and long-term relationship between economic growth, energy consumption, and trade openness factors in kazakhstan. aldıbekova (2018), in her doctoral thesis titled “the effects of oil prices on the economy of kazakhstan,” examined the structure of the oil market and the role of oil in economic development, the general view of the economy of kazakhstan, the importance of oil in the economy of kazakhstan and the effects of developments in oil prices on the economy of kazakhstan. she concluded that the declines in oil prices negatively affected the economic growth of kazakhstan. yağmur (2019), in her doctoral thesis titled “the curse of natural resources and kazakhstan’s economic policies,” states that kazakhstan can be defined as an economy based on natural resources and industries such as metalworking and petrochemicals that partially use these resources. she argued that most of the problems associated with the curse of natural resources thesis are valid for kazakhstan. thus she argues that problems such as low economic growth, an undiversified economy, over-dependence on natural resource exports, energy and capital-intensive production structure, low institutional and managerial quality, and insufficient investment in human capital are valid for kazakhstan. syzdykova (2020), in her article titled “kazakhstan’s renewable energy potential,” draws attention to various factors that prevent renewable energy technologies from becoming more widespread in kazakhstan. these include low electricity tariffs, transmission losses, outdated and inefficient technologies, weak regulatory and legal frameworks, and a high-risk business environment. she also presents her recommendations to overcome these obstacles. ongdash et al. (2020), in their article named “economic growth modeling for the republic of kazakhstan based on the higher energy efficiency level,” aimed to develop a model that will provide energy efficiency, which is an important factor in establishing a sustainable economy in kazakhstan. they suggest that the republic of kazakhstan should reject existing global projects and instead focus on solving local problems to reduce energy costs. they stated that further research on this subject could determine the direction that the investment policy in the energy sector should take in connection with kazakhstan’s development strategy. ahmad et al. (2017), in their article titled “multi-criteria evaluation of renewable and nuclear resources for electricity generation in kazakhstan”, subjected renewable and nuclear resources, which can be alternatives to fossil-based resources, for electricity generation in kazakhstan, to a multi-criteria evaluation. they showed that kazakhstan has the potential to develop a non-fossil fuel-based electricity system. xiong et al. (2015), in their article titled “the relationship between energy consumption and economic growth and the development strategy of a low-carbon economy in kazakhstan”, examined the relationship between energy consumption and economic growth in kazakhstan and the development strategy of a lowcarbon economy. they suggested strategies for kazakhstan, such as improving the energy consumption structure, developing renewable energy, using cleaner new production technologies, adjusting the industrial structure accordingly, and expanding forest areas. kurmanov et al. (2020), in their article titled “energy intensity of kazakhstan’s gdp: factors for its decrease in a resource-export developing economy,” revealed that kazakhstan continues to use several times more energy per production unit than the more developed countries and regions of the world. they examined the impact of various factors on gdp energy intensity, such as indicators that characterize the country’s economic growth, energy industry, and living standards. they argued that using energy primarily in the production of products with high added value is more rational for kazakhstan in terms of both economic development and energy saving. bolganbayev et al. (2021), in their article titled “the effect of oil prices on the economic growth of oil exporting countries bordering the caspian sea: panel data analysis”, examined the effects of oil price fluctuations on the economic growth of russia, iran, kazakhstan, and azerbaijan. they used the panel data analysis method and quarterly data for the period 2007–2020. karatayev and clarke (2016), in their article “a review of current energy systems and the green energy potential in kazakhstan”, international journal of energy economics and policy | vol 12 • issue 6 • 2022 69 bolganbayev, et al.: the effect of electricity generation, thermal energy production, fixed capital investment, and consumer price index on economic growth in kazakhstan first provide an overview of kazakhstan’s current energy system. then, they identified the main obstacles preventing the diffusion of renewable energy technologies in kazakhstan and suggested some measures. they emphasized that kazakhstan has resources such as wind energy, solar energy, biomass, and hydro energy that can be alternatives to fossil fuels. 3. method and analysis this research aims to analyze the effect of energy production, especially electricity generation and thermal energy production on economic growth in kazakhstan. to better explain this effect, fixed capital investment and consumer price index are also included in the research. thus, the research variables were determined as follows: x1 fixed capital investments in directions of use x2 consumer price index (2000=100) x3 electric power, mln. kwh x4 thermal energy, thsd. gcal y economic growth (gdp) we obtained data on fixed capital investments and economic growth from the world bank database (https://data.worldbank. org/indicator/ne.gdi.ftot.cd?locations=kz, https://data. worldbank.org/indicator/ny.gdp.mktp.cd?locations=kz), and consumer price index (2000=100), electricity generation and thermal power generation data from the database of the bureau of national statistics of the agency for strategic planning and reforms of the republic of kazakhstan (https://stat.gov.kz/). the data range is from 2002 to 2020. explanatory statistics are presented given in table 1 and the changes over time are presented visually in graph 1. explanatory statistics show that all variables fit normal distribution according to the jarque-bera test. as can be seen from the graph in graph 1, all of the variables follow an exponential increase trend over time. in line with these observations and the literature, the logarithms of the variables were used in the analysis. the first dimension of econometric time series to be analyzed is their stationarity. because if a series is not stationary, the results do not reflect the truth and therefore they are misleading. stationarity of a series is also an important criterion for models in which relationships between two or more variables are analyzed. the relevant variables must be at the same level and stationary. therefore, various unit root tests have been developed to examine stationarity in time series. augmented dickey-fuller (adf) test was used in this study. the test statistic is obtained using the following equation: � �y t y yt t i t i i m t� � � � �� � � �� � � � �0 1 1 1 (1) in the adf test, if the null hypothesis is rejected for the k=0, 1, 3, values, the series is considered stationary for the relevant level (sevüktekin and nargeleçekenler, 2007). the adf test findings of the research variables are given in table 2. the findings showed that logx1 and logy variables were stationary at the level, while logx2, logx3, and logx4 variables were stationary at the first difference. since the difference levels of all variables were the same, the first differences of the variables were used. regression analysis aims to model the relationship between a dependent variable and independent variables and to produce estimations with this model. anova (f) test is used to determine the significance of the model. the rate at which the independent variable explains the change in the dependent variable is expressed by the adjusted determination (adjusted r-squared) coefficient. statistically, the significance of the variable coefficients (beta coefficient) is determined by the student test. this study examines the effect of energy production on economic growth with three stepwise regression models. model 1: � � �y x xt t t� � �� � �1 1 2 2 (2) model 2: � � � �y x x xt t t t� � � �� � � �1 1 2 2 3 3 (3) model 3: � � � � �y x x x xt t t t t� � � � �� � � � �1 1 2 2 3 3 4 4 (4) the effect of the consumer price index and fixed capital investments on economic growth is included in all three models. thus, with the contribution of fixed capital investments and the consumer price index, the effect of energy production on economic growth has been demonstrated more realistically. in multivariate regression models, when there is a high level of correlation between independent variables, this is called the multicollinearity problem. multicollinearity is important and needs to be fixed as it leads to inconsistent estimates. this problem can be detected by the condition index calculated using the eigenvalues of the correlation matrix. with the largest eigenvalue of the correlation matrix being λmax, table 1: explanatory statistics x1 x2 x3 x4 y mean 3.27e+10 254.5921 85438.21 89593.62 1.38e+11 median 3.60e+10 240.5 86585.5 90829.3 1.48e+11 maximum 5.18e+10 451.5 108628.4 103350.3 2.37e+11 minimum 5.92e+09 113.4 58330.5 77759.6 2.46e+10 standard deviation 1.38e+10 107.6273 15371.34 6962.27 6.55e+10 skewness –0.740077 0.358008 –0.084444 –0.116922 –0.384523 kurtosis 2.449292 1.901472 1.934984 2.286431 1.980998 jarque-bera 1.974525 1.361225 0.920536 0.446392 1.290255 probability 0.372595 0.506307 0.631114 0.799958 0.524596 international journal of energy economics and policy | vol 12 • issue 6 • 202270 bolganbayev, et al.: the effect of electricity generation, thermal energy production, fixed capital investment, and consumer price index on economic growth in kazakhstan � � � � max i the above condition index value is calculated for each eigenvalue of λi. a condition index exceeding 15 informs about the existence of negative effects related to multicollinearity, while a value above 30 indicates that remedial measures should be taken (alpar, 2013). multicollinearity findings of the research variables are given in table 3. the findings show that there is no multicollinearity between the variables in the model. the findings regarding the effect of energy production on economic growth according to multivariate regression are presented in table 3. table 3: multicollinearity results of research variables dimension eigenvalue condition ındex 1 3.135 1.000 2 0.997 1.774 3 0.577 2.331 4 0.236 3.642 5 0.054 7.606 graph 1: line graph of the research variables table 2: adf unit root test findings of research variables level first diference conclusion t-statistics p-value t-statistics p-value logx1 –4.001375 0.0075 –1.934833 0.3099 i (0) logx2 –0.934171 0.7527 –3.102844 0.0455 i (1) logx3 –1.659840 0.4312 –4.632301 0.0026 i (1) logx4 –2.526818 0.1260 –4.013459 0.0078 i (1) logy –3.583295 0.0174 –2.407013 0.1544 i (0) test critical values 1% level –3.857386 –3.886751 5% level –3.040391 –3.052169 10% level –2.660551 –2.666593 international journal of energy economics and policy | vol 12 • issue 6 • 2022 71 bolganbayev, et al.: the effect of electricity generation, thermal energy production, fixed capital investment, and consumer price index on economic growth in kazakhstan the regression analysis findings in table 4 show that the effect of fixed capital investment on economic growth is statistically significant in all three models. in model 1, only fixed capital investment and consumer price index are used. considering that the effect of only the consumer price index in this model is statistically insignificant, it can be said that according to model 1, fixed capital investments explain 85% of the variability in economic growth. the effect of the consumer price index on economic growth was found to be statistically insignificant in all three models. the effect of energy production on economic growth is examined with two variables. the electricity generation variable is included in model 2. both in model 2 and model 3, the effect of the electrical energy production variable was found to be statistically significant. the increase in the coefficient of determination by including the electricity generation variable in model 2 was found to be statistically significant. however, the effect of thermal energy production was not statistically significant. accordingly, the inclusion of this variable in the model did not provide a statistically significant increase in the coefficient of determination. 4. conclusion and recommendations one of the main sources of economic growth is energy production. this study examined the impact of energy production, especially electricity generation and thermal energy production, on economic growth. to provide a better explanation for the effect of energy production on economic growth, we also included fixed capital investment and consumer price index variables in the research model. the findings showed that fixed capital investment has the most dominant effect on economic growth. this is a natural result from a macroeconomic point of view. another critical finding is that both electricity generation and fixed capital investments have a positive effect on economic growth. when the variable of the amount of electricity generated is included in the model, the explanatory power of the model increases from 85% to 90.7%. however, the effect of thermal energy production was found to be statistically insignificant. this insignificance is a research problem that needs to be analyzed in detail, taking into account the general energy production structure of kazakhstan. this study considers energy production throughout the country. regions can be included in statistical models and the effects of regions can be evaluated using panel analysis methods. thus, it can be revealed whether the effect of energy production varies from region to region. adding different variables to the research could also broaden our understanding of the impact of energy production on economic growth. in this context, some of the macro variables (such as population, schooling level, level of health services, and household expenditure structure) can be used as control variables, and the effect of energy production can be evaluated from a different perspective. references ahmad, s., nadeem, a., akhanova, g., houghton, t., muhammadsukki, f. (2017), multi-criteria evaluation of renewable and nuclear resources for electricity generation in kazakhstan. energy, 141, 1880-1891. alagöz, m., erdoğan, s., saçık, s.y. (2011), kazakistan cumhuriyeti’nin ekonomik performansının ölçümü: 1992-2008. avrasya etüdleri, 39(1), 3-29. aldıbekova, g. (2018), petrol fiyatlarının kazakistan ekonomisi üzerine etkileri. (phd thesis). bursa: uludağ üniversitesi, sosyal bilimler enstitüsü. alpar, r. (2013), uygulamalı çok değişkenli i̇statiksel yöntemler. ankara: detay yayıncılık. bolganbayev, a., myrzabekkyzy, k., baimaganbetov, s., kelesbayev, d. (2021), the effect of oil prices on the economic growth of oil exporting countries bordering the caspian sea: panel data analysis. international journal of energy economics and policy, 11(6), 432-437. bolganbayev, a., myrzabekkyzy, k., baimaganbetov, s., kelesbayev, d. (2022), increase the oil prices and the effect of real exchange rate on regional economic growth: the case of kazakhstan. bulletin of the kazakh university of economics finance and international trade, 46, 59-68. karatayev, m., clarke, m.l. (2016), a review of current energy systems and green energy potential in kazakhstan. renewable and sustainable energy reviews, 55, 491-504. kelesbayev, d., myrzabekkyzy, k., bolganbayev, a., baimaganbetov, s. (2022a), the impact of oil prices on the stock market and real exchange rate: the case of kazakhstan. international journal of energy economics and policy, 12(1), 163-168. kelesbayev, d., myrzabekkyzy, k., bolganbayev, a., baimaganbetov, s. (2022b), the effects of the oil price shock on ınflation: the case of kazakhstan. international journal of energy economics and policy, 12(3), 477-481. khan, s., jam, f.a., shahbaz, m. (2012), electricity consumption and economic growth in kazakhstan: fresh evidence from a multivariate framework analysis. mpra paper no. 43460. available from: https://www.mpra.ub.uni-muenchen.de/43460 [last accessed on 2012 dec 28]. table 4: results of regression analysis on the effect of smes on economic growth variables model 1 model 2 model 3 beta t beta t beta t x1 0.922 9.212 (p<0.05) 0.801 8.779 (p<0.05) 0.802 8.482 (p<0.05) x2 0.011 0.112 0.000 –0.001 0.006 0.068 x3 0.268 2.931 (p<0.05) 0.280 2.621 (p<0.05) x4 –0.025 0.244 f 42.485 (p<0.05) 45.518 (p<0.05) 31.861 (p<0.05) r2 0.850 0.907 0.907 ∆r2 0.850 (p<0.05) 0.057 (p<0.05) 0.000 (p>0.05) international journal of energy economics and policy | vol 12 • issue 6 • 202272 bolganbayev, et al.: the effect of electricity generation, thermal energy production, fixed capital investment, and consumer price index on economic growth in kazakhstan kökocak, a.k. (2011), geçiş ekonomilerinde kobi̇’lere dayalı kalkınma modeli. avrasya etüdleri, 39(1), 77-98. kurmanov, n., aliyev, u., satbayeva, a., kabdullina, g., baxultanov, d. (2020), energy ıntensity of kazakhstan’s gdp: factors for its decrease in a resource-export developing economy. international journal of energy economics and policy, 10(5), 447-453. mudarissov, b.a., lee, y. (2014), the relationship between energy consumption and economic growth in kazakhstan. geosystem engineering, 17(1), 63-68. mukhamediyev, b., spankulova, l. (2020), the ımpact of ınnovation, knowledge spillovers and oil prices on economic growth of the regions of kazakhstan. international journal of energy economics and policy, 10(4), 78-84. mukhtarov, s., humbatova, s., seyfullayev, i., kalbiyev, y. (2020), the effect of financial development on energy consumption in the case of kazakhstan. journal of applied economics, 23(1), 75-88. ongdash, a.o., omirtay, a.d., bayetova, m.t., ongdashuly, e. (2020), economic growth modeling for the republic of kazakhstan based on the higher energy efficiency level. international journal of energy economics and policy, 10(6), 396-403. özdil, t., turdalieva, a. (2015), the sources of economic growth in kazakhstan economy: an input output analysis. i̇n: approach international conference on eurasian economies. p841-845. raihan, a., tuspekov, a. (2022), dynamic impacts of economic growth, energy use, urbanization, agricultural productivity, and forested area on carbon emissions: new insights from kazakhstan. world development sustainability, 1, 100019. sevüktekin, m., nargeleçekenler, m. (2007), ekonometrik zaman serileri analizi. ankara: nobel akademik yayın. suleimenova, m. (2016), kazakistan’da enerji, finans ve büyüme i̇lişkisi üzerine ampirik analiz (1994-2013). master’s thesis. turkey: niğde ömer halisdemir üniversitesi/sosyal bilimler enstitüsü. syzdykova, a. (2020), kazakistan’ın yenilenebilir enerji potansiyeli. ekonomi i̇şletme ve maliye araştırmaları dergisi, 2(1), 79-88. xiong, c., yang, d., huo, j., zhao, y. (2015), the relationship between energy consumption and economic growth and the development strategy of a low-carbon economy in kazakhstan. journal of arid land, 7(5), 706-715. yağmur, d. (2019), doğal kaynak laneti ve kazakistan’ın ekonomik politikaları. (phd thesis). ankara: hacettepe üniversitesi, türkiyat araştırmaları enstitüsü. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 4 • 202184 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(4), 84-90. combining the concept of green accounting with the regulation of prohibition of disposable plastic use komang adi kurniawan saputra1*, daniel t. h. manurung2, lia rachmawati3, eka siskawati4, franklin kharisma genta5 1university of warmadewa, indonesia, 2stie widya gama lumajang, indonesia, 3stie mandala jember, indonesia, 4padang state polytechnic, indonesia, 5indonesia cooperative management institute, indonesia. *email: kaksaputra12@gmail.com received: 06 june 2020 accepted: 20 january 2021 doi: https://doi.org/10.32479/ijeep.10087 abstract this study aims to uncover the meaning of green accounting in the regulation of the prohibition of the use of plastic materials in bali. the research method used is a qualitative method with a phenomenological interpretive paradigm that emphasizes an in-depth understanding of the content of green accounting in government rules. the phenomenon is that after the ban on the use of plastic materials, the amount of waste in the final disposal container is increasing, so it is necessary to examine the cause and the implementation of existing regulations. the analysis knife in this research is the ideology of the tri hita karana concept from bali. the results of this study reveal that first, the concept of green accounting which is a manifestation of corporate social responsibility can be synergized with government regulations based on tri hita karana to reduce the amount of plastic waste. second, the amount of plastic waste in landfills is dominated by organic waste originating from former religious ceremonial facilities from three regencies in bali. third, the regulation of the use of plastic materials in bali is very effective and has a positive impact on society. fourth, is the implementation of green accounting has a very significant impact on the amount of waste if all entrepreneurs, especially hotels apply it and have the same goal, namely environmental preservation. keywords: green accounting, tri hita karana, corporate social responsibility, environment jel classifications: k32, q56; l65; l51 1. introduction as is known, plastic waste cannot be digested, both by the human body and animals. it is undeniable, waste that is not managed properly will cause pollution in our environment. currently, the most dominant waste in indonesia is organic waste. food and plant waste is 50%. the composition of plastic waste in indonesia is currently around 15% of the total waste generation, especially in urban areas. the available data shows that in the past 10 years, the amount of plastic waste has continued to increase. the main sources of plastic waste come from shopping bags, consumer goods packaging, food and beverage packaging, and other wrapping of goods (coe et al., 2019). of the total plastic waste generation, only about 10-15% is recycled. while 60-70% are accommodated in landfills and 15-30% have not been managed. from 15-30% of unmanaged plastic waste ends up being wasted in the environment, especially in rivers, lakes, beaches and the sea. plastic waste in the ocean (marine plastics) is currently not only a challenge for indonesia but rather a global problem (kurniawan and imron, 2019). because, marine litter or marine trash does not have a territory of the state or regional administration (steensgaard et al., 2017). in addition, the number and distribution tend to increase significantly and spread on the ocean scale (tessnow-von wysocki and le billon, 2019). although there are no valid data on the number of marine litters globally, some research results reveal that 80% of marine litters come from the mainland (coe et al., 2019). the 80% amount is 8.8 million tons of plastic waste that is wasted or discharged into the ocean each year (jepsen and de this journal is licensed under a creative commons attribution 4.0 international license saputra, et al.: combining the concept of green accounting with the regulation of prohibition of disposable plastic use international journal of energy economics and policy | vol 11 • issue 4 • 2021 85 bruyn, 2019). waste discharged into rivers, lakes, or seas disturbs the balance of the ecosystem and causes the death of aquatic animals trapped in plastic waste (coe et al., 2019). in waterways, garbage piles can clog and cause inundation or flooding (chae and an, 2018). almost all provinces in indonesia have problems with waste, including the island of bali. bali province which is a world tourist destination has problems related to waste management (sunaryo et al., 2013). regulations on waste management have been issued by local governments, and new regulation in 2019 has again been issued regarding the prohibition of the use of plastics to reduce the amount of plastic waste in bali. the existence of this regulation was not followed by a significant reduction in waste in the province of bali (sunaryo et al., 2013). this is proven by the polemic in waste management in badung regency and denpasar. the suwung landfill, denpasar experienced overload or accumulation of rubbish so that it had been closed and carried out restrictions on waste disposal and banned some districts from dumping garbage into suwung landfills. problems like this can be overcome in the synergy between the government, business people and the community. however, in waste management and environmental preservation, the concept of green accounting is very relevant to be applied (figueroa et al., 2010). however, the application of green accounting is also not without problems, there is still much that needs to be addressed in its application (stanojević et al., 2010). lack of awareness of individuals and society, in this case, is considered as the cause of the less optimal application of green accounting (kim and todorovic, 2013). the application of green accounting or specifically called environmental accounting (dewi, 2015) is still considered a burden on the company because it is considered to be able to reduce company profits (ng, 2018). this study uses the concept of green accounting to see the root of the problem in waste management in bali which has long been a concern of accountants (wulandari et al., 2019). this concept is important because companies need to convey information about social activities (dewi, 2015) and environmental protection to corporate stakeholders (verma et al., 2019). the company not only conveys financial information to existing investors and creditors and potential investors or corporate creditors, but also needs to pay attention to the social interests in which the company operates (han et al., 2018). thus, the company’s responsibility is not only to investors or to creditors (adinehzadeh et al., 2018; sitinabiha et al., 2018), but also to other stakeholders, for example employees, consumers, suppliers, governments, communities, media, industry organizations and other interest groups. social and environmental responsibility are in the corridors of financial accounting (deegan, 2013). this form of social responsibility accounting has been known as corporate social responsibility (csr) and sustainability reporting (gao and mattila, 2014). 2. methods this study is qualitative research that investigates phenomena inductively (budiasih, 2014) about the existence of government regulations on the prohibition of the use of disposable plastics to reduce the amount of waste, which does not run straight with the amount of waste increasing so that a fundamental solution is needed. moleong (2005) explains that the purpose of qualitative research is to understand social phenomena (louis, 1983) through a holistic picture and to deepen understanding (zald, 1986). this study uses an interpretive approach to phenomenology (hackley, 2003) and uses empirical data obtained through unstructured interviews (yulianti, 2016). the total informants involved were as many as 5 people who were from the community who were directly affected by the existence of landfills, the government, and business actors. the research design of phenomenology consists of various variants as the development and improvement of previous thoughts about the phenomenon (noviriani, 2012). this research was conducted in the bali-indonesia province, precisely at the suwungdenpasar landfill. the use of phenomenological methods aims to explore the essential meanings of a phenomenon (mamulati et al., 2016). phenomenology is tasked with explaining things in themselves (widiastuti et al., 2015), knowing what enters before consciousness, and understanding the meaning and essence of meaning in intuition and self-reflection (kamayanti, 2015). phenomenology requires science to consciously direct to pay attention to certain examples without theoretical prejudice (jefford and sundin, 2013) through different experiences (budiasih and sukoharsono, 2012) and not through large data collections for a general theory beyond the actual substance (sukoharsono, 2006). 3. results and discussion the problem of waste should have been addressed together by the government, entrepreneurs and the community. in indonesia, some regulations regulate waste, which is changing the paradigm of waste management (lestari and trihadiningrum, 2019). the change of paradigm from collecting, transporting, and disposing, to reducing the use of material that has the potential to become waste (reduce) and recycling of resources (recycle) (lokahita et al., 2019). the right approach to replace or combine solutions at the final processing site that has been carried out is to implement the 3r principle approach (reduce, reuse, recycle), extended producer responsibility (tulashie et al., 2019). plus the processing and utilization of waste into resources either as raw materials or renewable energy sources as well as the final processing of waste in environmentally sound landfills (o’dwyer, 2002). 3.1. impacts of banning regulations on the use of plastic materials the province of bali implements a ban on the use of disposable plastics starting in january 2019 by targeting a reduction of 60%70% plastic waste throughout 2019. the regulation is contained in the bali governor’s regulation on limiting the disposal of disposable plastic waste. the regulation has been announced since december 2018. in the regulation, the ban was carried out on three materials made or containing plastic, namely plastic bags, polystyrene or styrofoam, and plastic straws (lokahita et al., 2019). manufacturers, distributors, suppliers and business people are prohibited from producing, distributing, supplying and supplying disposable plastics. this regulation also requires every producer, distributor, supplier, and every business actor to produce, saputra, et al.: combining the concept of green accounting with the regulation of prohibition of disposable plastic use international journal of energy economics and policy | vol 11 • issue 4 • 202186 distribute, supply and supply disposable plastic substitutes (coe et al., 2019). manufacturers, suppliers, business operators, and disposable plastic providers have also been given time to make adjustments for 6 months from the time the regulation was promulgated, namely december 21, 2018. this rule is enforced to reduce the amount of plastic waste in bali. one of the leaders in the provincial government of bali stated that: “the implementation of regulations on disposable plastic waste disposal has been running optimally. now the minimarket, shops have switched to environmentally friendly materials. plastic bags are also not provided. we believe this regulation will reduce plastic waste in bali by 32 percent in 2019. we support that plastic will no longer be used. i see the community ready to implement this rule. many organic materials have been used. plastic straws have been replaced by bamboo and paper, i have seen them in the field.” the impact of the existence of restrictions on the use of plastic materials in bali is believed to be able to reduce the alarming amount of plastic waste. the bali provincial government is very consistent to oversee this regulation (ayalon et al., 2009). the statement above can be interpreted that the government does not remain silent seeing an increase in the amount of plastic waste in bali, even for the first time there are strict rules like this that are appreciated by the central government. the regulation also in addition to reducing the amount of plastic waste, is able to increase the creative economy (dikgang et al., 2012) in bali. this was stated by the leadership of the regional government as follows: “the balinese are now turning to traditional materials. do not depend on plastic material anymore. for example, now several restaurants and restaurants have switched to straws made from bamboo. this means that public support for the implementation of this regulation is a very positive response. home industries that produce straws made from bamboo could rise because of this rule. this is a business opportunity for our society. bamboo straws can turn on the community’s industry. paper straws are now widely produced again. life is our industry.” based on this statement it can be interpreted that the regulations made by the provincial government not only have an impact on reducing the amount of plastic waste but have a positive impact on the small industry or home industry (ayalon et al., 2009) in bali by re-utilizing traditional materials to replace plastic. this is certainly a very positive impact on the economy of bali. in addition to reducing plastic waste and increasing small industries in bali, this regulation has a great opportunity to be synergized with the concept of green accounting (ying et al., 2011). so that this rule touches directly on businesses in bali as a whole management, especially the hotel industry. based on research results. the hospitality industry as a major contributor to waste is required to apply the concept of green accounting (nezakati et al., 2015). this is in line with bali’s current condition with a large number of the hospitality industry so that it is very likely that provincial government regulations are synergized with the concept of green accounting (cho and patten, 2013). 3.2. the need for green accounting implementation in companies to support government programs green accounting is an accounting process that integrates recognition, measurement of value, recording, summarizing, and reporting of financial, social and environmental information in an integrated accounting reporting package (ahmad et al., 2018; seo, 2016), which is useful for users in economic and noneconomic assessment and decision making (thornton, 2013). the purpose of green accounting is to try to reduce the negative effects of economic activity (ha and quyen, 2018) and the system on the environment (figueroa, et al., 2010). therefore it is very precisely integrated with government regulations that are committed to reducing the amount of plastic waste as a measure of environmental conservation (spence et al., 2013). the concept of green accounting is applied to companies, especially hotel businesses in bali, better known as corporate social responsibility (csr) (ng, 2018). this report has been going on for a long time as recommended by financial service authorities and regulations from the central and regional governments (cho and patten, 2013). however, it is still not a requirement for industries that are classified as small businesses, including hospitality, lodging, and others (cheng, 2018). therefore, not all hotel industries in bali apply it. as stated by the head of the environment in one of the locations of star hotels in the sanurdenpasar area, namely: “until now not all hotels in our area have issued assistance in the form of csr. only hotels that have good management care about the environment. i don’t want to mention which hotel it is, so it won’t be a problem. what is clear is that not all hoteliers provide csr.” related to the statement above, it can be interpreted that the commitment to apply green accounting principles is still low among hoteliers (verma et al., 2019), so the government needs to emphasize to business operators in bali to adhere to the teachings of tri hita karana that have guide life in bali (saputra et al., 2018). this needs to be done because in applying the tri hita karana teachings to the management of their businesses, these entrepreneurs must in an integrated manner carry out environmental responsibility. because it is contained in the tri hita karana teachings, namely palemahan (saputra et al., 2018). in this teaching doctrine, all business actors are required to harmonize business with the environment. this can be done in various ways, but what is certain is to do environmental reporting (indriyani et al., 2018). the teaching of tri hita karana consists of three aspects, namely prahyangan, pawongan and palemahan (atmadja et al., 2019). tri hita karana is a concept of human harmony in life (atmadja et al., 2019). harmony is meant a harmonious relationship between humans and the creator or god (prahyangan), harmonious relations between humans (pawongan) and human harmonious relations with their environment (palemahan) (saputra et al., 2019). these three elements of harmony become the basis for the issuance of regulations by local governments in order to reduce the amount of plastic waste for the preservation of bali’s natural environment. saputra, et al.: combining the concept of green accounting with the regulation of prohibition of disposable plastic use international journal of energy economics and policy | vol 11 • issue 4 • 2021 87 thus, a form of corporate support in bali is the application of the concept of green accounting in the business with the aim of environmental preservation (artana, 2016). as stated by one of the accounting academics from famous private universities in bali is: “the tri hita karana concept is ideally used as a foundation for environmental preservation. especially with the current condition of business uncertainty, the concept of weakness is very relevant for consideration by hoteliers. this weak concept is closely related to the concept of green accounting. that’s if specified. so between tri hita karana and green accounting are two things that support each other for the purpose of environmental preservation” that is, the regulation on the prohibition of the use of disposable plastics by local governments (ayalon et al., 2009) is based on the concept of tri hita karana, it should be a basic foothold to implement the concept of green accounting in companies, especially hospitality (nielsen et al., 2019) in bali. ideally, environmental responsibility reports that are manifestations of green accounting receive serious attention from hoteliers (figueroa et al., 2010). because environmental sustainability is currently threatened by pollution from waste, mainly plastic waste (tulashie et al., 2019). to create a sustainable environment, hospitality companies and other businesses need to prioritize green hotels (nimri et al., 2017) as a commitment to support government programs in preserving the environment (gupta et al., 2019). 3.3. green accounting is an ideal concept for environmental conservation the phenomenon of the accumulation of waste in landfills was caused by various things, so it was not caused entirely by the increasing amount of plastic waste (nielsen et al., 2019). another phenomenon that arises is that bali produces 4,281 tons of waste every year. of this amount, more waste is not managed (52%) than it is managed (48%). as much as 50% of waste in bali comes from three regions, namely denpasar, badung, and gianyar. of the rubbish that is disposed of in a garbage bin, 70% of them end up in landfills (dhawan et al., 2019). the provincial government of bali makes the problem of plastic waste a common enemy (yin et al., 2019) and shows its commitment through regulations to reduce the generation of disposable plastic. for this reason, a bali partnership has been formed which collaborates with parties such as academics, research institutions, government, and professionals or the private sector as a method of waste reduction. it is in this concept that green accounting can be implemented in the field of business actors to support government regulation (ying et al., 2011). the concept of green accounting must be a commitment of entrepreneurs, especially hotel companies (stanojević et al., 2010). so companies have a responsibility to their environment (tulashie et al., 2019). because the reduction in the amount of waste is not only the responsibility of the government, but it is the responsibility of all parties (miranda and kruglianskas, 2019) to preserve the environment of bali. the concept of green accounting in hospitality can be focused on the components of environmental costs, namely the cost of environmental prevention, the cost of environmental detection, the cost of environmental internal failure, and the cost of environmental external failure (kim and todorovic, 2013). however, until now green accounting has not been fully applied (spence et al., 2013) to hoteliers (lee and cheng, 2018) in bali. as stated by one hotelier in the sanur-denpasar area: “i’ve heard and read about green accounting. if i’m not mistaken about corporate social responsibility (csr). in our hotel, csr has been running and is consistent. but i don’t know about other hotels, because it seems like many hotel businesses don’t implement csr” the statement shows that the commitment of hoteliers is needed to apply the concept of green accounting as a form of corporate environmental responsibility (wang et al., 2018). especially with the existence of regulations from the local government (dikgang et al., 2012) and the concept of local wisdom of the balinese people who highly uphold harmony with the natural environment contained in the teachings of tri hita karana (atmadja et al., 2019). the tri hita karana teachings have become the basis of balinese life in government, industry, business, and so on (saputra et al., 2019). one hotelier located in the sesetan-denpasar area stated that: “the hoteliers should have applied the concept of green accounting. the policy has entered into the vision and mission of the government. namely managing aspects of government, economy, education and so on based on the philosophy of tri hita karana. at our hotel, tri hita karana has very strong implementation. because i am a native of bali, it is appropriate to support government programs. at least through the internal application of the tri hita karana concepts. in my opinion, that’s part of green accounting” based on the statement of the informant above, it can be concluded that green accounting and tri hita karana have a very close relationship (hutasoit and wau, 2017) in carrying out the operations or management of the company (di salvo et al., 2017), especially the hospitality industry in bali. that explanation also implies that the concept that green accounting is very much in line with government programs (nezakati et al., 2015) and does not conflict with the local wisdom of tri hita karana (hutasoit and wau, 2017), so that it can be stated that the concept of green accounting is a concept that is ideal for environmental preservation (hasan et al., 2019). one tourism observer who is also a community leader in denpasar stated that: “hotels in bali and also other types of businesses have stated their commitment to support government programs not to use disposable plastic in their business operations. the proof, now in hotels, supermarkets and others no longer uses plastic. however, related to corporate social responsibility, indeed not all have implemented it. i admit that. especially with the phrase green accounting, only a few people understand. the people know it is csr. but i must admit that csr disclosure is important. because of our shared commitment to preserving the environment and freeing our environment from plastic waste” saputra, et al.: combining the concept of green accounting with the regulation of prohibition of disposable plastic use international journal of energy economics and policy | vol 11 • issue 4 • 202188 in the statement above, it must be recognized that this environmental responsibility reporting is important (afiah and azwari, 2015) because it is an expression of the commitment of the entrepreneurs towards environmental sustainability (kim and todorovic, 2013). preservation of the environment is our focus together with the government, the community, business people and investors. the point is green accounting needs to be applied (rahman and reynolds, 2016) to support government programs in preserving the environment (allam, 2019) based on the tri hita karana philosophy (hutasoit and wau, 2017). 4. conclusion based on the results of the study stated that the impact of the regulation prohibiting the use of disposable plastic in bali can reduce the amount of plastic waste in landfills. this is certainly a positive impact on the environment. however, according to observations made in the field at the final disposal site of the city of denpasar, the amount of waste has increased, to the extent that garbage disposal is limited. after conducting in-depth research, it turns out that the amount of plastic waste has declined, but because the final disposal site in denpasar holds garbage from three other districts, so the amount of waste is seen increasing. the government program to limit the use of disposable plastic is very good for the sustainability of the natural ecosystem in bali. this has been supported by commitments from businesses in bali, especially hoteliers. entrepreneurs have a commitment to support the government program by implementing green accounting in their businesses. green accounting which is a manifestation of corporate social responsibility has the same goals as government regulations, namely environmental preservation. however, not only that, green accounting and government regulations do not work if they are not supported by the general public. to support the harmony of this program, between green accounting and regulations, the implementation is interpreted through the teaching of tri hita karana. the implementation of tri hita karana in the world of government, business and society is very touching and rooted in the people of bali. so it is very relevant if synergized between tri hita karana, government regulations and green accounting in preventing the increase of plastic waste for environmental preservation. therefore, tri hita karana can be a commitment, awareness, guidelines or guidelines for governance, business and community life in bali. references adinehzadeh, r., jaffar, r., abdul shukor, z., che abdul rahman, m.r. (2018), the mediating role of environmental performance on the relationship between corporate governance mechanisms and environmental disclosure. asian academy of management journal of accounting and finance, 14(1), 153-183. afiah, n.n., azwari, p.c. (2015), the effect of the implementation of government internal control system (gicgs)on the quality of financial reporting of the local government and its impact on the princioles og good governance: a research in district, city and provincial governement in south sumatera. social and behavioral sciences, 211, 811-818. ahmad, z., ibrahim, h., tuyon, j. (2018), governance of behavioural biases in asset management industry: insights from fund managers in malaysia. asian academy of management journal of accounting and finance, 14(2), 65-102. allam, z. (2019), land use policy the city of the living or the dead: on the ethics and morality of land use for graveyards in a rapidly urbanised world. land use policy, 87(1), 104037. artana, i. (2016), tri hita karana meningkatkan kualitas modal manusia dari persfektif kesehatan. piramida, 10(2), 100-105. atmadja, a. t., saputra, k.a.k., manurung, d.t.h. (2019), proactive fraud audit, whistleblowing and cultural implementation of tri hita karana for fraud prevention. european research studies journal, 22(3), 201-214. ayalon, o., goldrath, t., rosenthal, g., grossman, m. (2009), reduction of plastic carrier bag use: an analysis of alternatives in israel. waste management, 29(7), 2025-2032. budiasih, i.g.a. (2014), fenomena akuntabilitas perpajakan pada jaman bali kuno: suatu studi interpretif. jurnal akuntansi multiparadigma, 5(3), 1-10. budiasih, i.g.a., sukoharsono, e.g. (2012), accounting practices and the use of money in the reign of king udayana in bali: an ethnoarcheological approach. banjarmasin: simposium nasional akuntansi xv. p20-23. chae, y., an, y.j. (2018), current research trends on plastic pollution and ecological impacts on the soil ecosystem: a review. environmental pollution, 240, 387-395. cheng, s.h. (2018), autocratic decision making using group recommendations based on hesitant fuzzy sets for green hotels selection and bidders selection. information sciences, 467, 604-617. cho, c.h., patten, d.m. (2013), green accounting: reflections from a csr and environmental disclosure perspective. critical perspectives on accounting, 24(6), 443-447. coe, j.m., antonelis, g.b., moy, k. (2019), taking control of persistent solid waste pollution. marine pollution bulletin, 139(1), 105-110. deegan, c. (2013), the accountant will have a central role in saving the planet really? a reflection on green accounting and green eyeshades twenty years later. critical perspectives on accounting, 24(6), 448-458. dewi, s.r. (2015), pemahaman dan kepedulian penerapan green accounting: studi kasus ukm tahu di sidoarjo understanding and application of green accounting awareness: a tofu sme case study in sidoarjo. ekonomi and bisnis, 11(4), 1-7. dhawan, r., bisht, b.m.s., kumar, r., kumari, s., dhawan, s.k. (2019), recycling of plastic waste into tiles with reduced flammability and improved tensile strength. process safety and environmental protection, 124, 299-307. di salvo, a.l.a., agostinho, f., almeida, c.m.v., giannetti, b.f. (2017), can cloud computing be labeled as “green”? insights under an environmental accounting perspective. renewable and sustainable energy reviews, 69(1), 514-526. dikgang, j., leiman, a., visser, m. (2012), analysis of the plastic-bag levy in south africa. resources, conservation and recycling, 66, 59-65. figueroa, e., orihuela, c., calfucura, e. (2010), green accounting and sustainability of the peruvian metal mining sector. resources policy, 35(3), 156-167. gao, y., mattila, a.s. (2014), improving consumer satisfaction in green hotels: the roles of perceived warmth, perceived competence, and csr motive. international journal of hospitality management, 42, 20-31. gupta, a., dash, s., mishra, a. (2019), all that glitters is not green: creating trustworthy ecofriendly services at green hotels. tourism management, 70(1), 155-169. ha, n.t.t., quyen, p.g. (2018), monetary policy, bank competitiveness saputra, et al.: combining the concept of green accounting with the regulation of prohibition of disposable plastic use international journal of energy economics and policy | vol 11 • issue 4 • 2021 89 and bank risk-taking: empirical evidence from vietnam. asian academy of management journal of accounting and finance, 14(2), 137-156. hackley, c. (2003), doing research projects in marketing, management and consumer research. milton park, milton: routledge. han, h., lee, j.s., trang, h.l.t., kim, w. (2018), water conservation and waste reduction management for increasing guest loyalty and green hotel practices. international journal of hospitality management, 75(1), 58-66. hasan, m.m., nekmahmud, m., yajuan, l., patwary, m.a. (2019), green business value chain: a systematic review. sustainable production and consumption, 20, 326-339. hutasoit, h., wau, r. (2017), menuju sustainability dengan tri hita karana (sebuah studi interpretif pada masyarakat bali). business management journal, 13(2), 151-168. indriyani, n.m.v., putri, i.g.a., suardikha, i.m.s., wirajaya, i.g.a. (2018), the effect of good corporate governance and tri hita karana culture on the quality of financial reporting. russian journal of agricultural and socio-economic sciences, 6(1), 75-84. jefford, e., sundin, d. (2013), post-structural feminist interpretive interactionism. nurse researcher, 21(1), 14-22. jepsen, e.m., de bruyn, p.j.n. (2019), pinniped entanglement in oceanic plastic pollution: a global review. marine pollution bulletin, 145(1), 295-305. kamayanti, a. (2015), sains memasak akuntansi: pemikiran udayana dan tri hita karana. journal of research and applications: accounting and management, 1(2), 73. kim, j.t., todorovic, m.s. (2013), towards sustainability index for healthy buildings via intrinsic thermodynamics, green accounting and harmony. energy and buildings, 62, 627-637. kurniawan, s.b., imron, m.f. (2019), the effect of tidal fluctuation on the accumulation of plastic debris in the wonorejo river estuary, surabaya, indonesia. environmental technology and innovation, 15, 100420. lee, w.h., cheng, c.c. (2018), less is more: a new insight for measuring service quality of green hotels. international journal of hospitality management, 68(1), 32-40. lestari, p., trihadiningrum, y. (2019), the impact of improper solid waste management to plastic pollution in indonesian coast and marine environment. marine pollution bulletin, 149(1), 110505. lokahita, b., samudro, g., huboyo, h.s., aziz, m., takahashi, f. (2019), energy recovery potential from excavating municipal solid waste dumpsite in indonesia. energy procedia, 158, 243-248. louis, m. (1983), sociological paradigms and organizational analysis. (gibson burrell; gareth morgan). administrative science quarterly, 28(1), 153-156. mamulati, i., triyuwono, i., mulawarman, a.d. (2016), fenomenologi sumber daya manusia sebagai aset intelektual dalam amal usaha muhammadiyah. el muhasaba: jurnal akuntansi, 7(1), 51. miranda, d., kruglianskas, i. (2019), critical factors for environmental regulation change management: evidences from an extended producer responsibility case study. journal cleaner production, 246, 119013. nezakati, h., moghadas, s., aziz, y.a., amidi, a., sohrabinezhadtalemi, r., jusoh, y.y. (2015), effect of behavioral intention toward choosing green hotels in malaysia preliminary study. procedia social and behavioral sciences, 172, 57-62. ng, a.w. (2018), from sustainability accounting to a green financing system: institutional legitimacy and market heterogeneity in a global financial centre. journal of cleaner production, 195, 585-592. nielsen, t.d., holmberg, k., stripple, j. (2019), need a bag? a review of public policies on plastic carrier bags where, how and to what effect? waste management, 87, 428-440. nimri, r., patiar, a., kensbock, s. (2017), a green step forward: eliciting consumers’ purchasing decisions regarding green hotel accommodation in australia. journal of hospitality and tourism management, 33, 43-50. noviriani, e. (2012), studi fenomenologi atas. international journal of energy economics and policy, 5(80), 121-128. o’dwyer, b. (2002), managerial perceptions of corporate social disclosure: an irish story. accounting, auditing and accountability journal, 15(3), 406-436. rahman, i., reynolds, d. (2016), predicting green hotel behavioral intentions using a theory of environmental commitment and sacrifice for the environment. international journal of hospitality management, 52, 107-116. saputra, k.a.k., anggiriawan, p.b., sutapa, i.n. (2018), akuntabilitas pengelolaan keuangan desa dalam perspektif budaya tri hita karana. jurnal riset akuntansi dan bisnis airlangga, 3(1), 306-321. saputra, k.a.k., pradnyanitasari, p.d., priliandani, n.m.i., putra, i.g.b. (2019), praktek akuntabilitas dan kompetensi sumber daya manusia untuk pencegahan fraud dalam pengelolaan dana desa. jurnal krisna: kumpulan riset akuntansi, 10(2), 168-176. saputra, k.a.k., sara, i.m., jayawarsa, a.a.k., pratama, i.g.s. (2019), management of village original income in the perspective of rural economic development. international journal of advances in social and economics, 1(2), 52-60. saputra, k.a.k., sujana, e., tama, g.m. (2018), perspektif budaya lokal tri hita karana dalam pencegahan kecurangan pada pengelolaan dana desa. jurnal akuntansi publik, 1(1), 28-41. seo, j.y. (2016), pro-cyclicality of small and medium enterprise (sme) loans according to financing type based on purpose: evidence from korean banks. asian academy of management journal of accounting and finance, 12(2), 23-36. siti-nabiha, a.k., azhar, z., ali-mokhtar, m.a. (2018), management control for microfinance: an examination of the belief system of a malaysian microfinance provider. asian academy of management journal of accounting and finance, 14(1), 185-208. spence, c., chabrak, n., pucci, r. (2013), doxic sunglasses: a response to green accounting and green eyeshades: twenty years later. critical perspectives on accounting, 24(6), 469-473. stanojević, m., vranes, s., gökalp, i. (2010), green accounting for greener energy. renewable and sustainable energy reviews, 14(9), 2473. steensgaard, i., syberg, k., rist, s., hartmann, n., boldrin, a., hansen, s.f. (2017), from macro to microplastics analysis of eu regulation along the life cycle of plastic bags. environmental pollution, 224, 289-299. sukoharsono, e.g. (2006), alternatif riset kualitatif sains akuntansi: biografi, phenomenologi, grounded theory, critical ethnografi dan case study. analisis makro dan mikro: jembatan kebijakan ekonomi indonesia. p230-245. sunaryo, b., susanti, p.r., irkham, a.m. (2013), dampak program pengelolaan sampah berbasis masyarakat sebagai salah satu program corporate social responsibility badak lng terhadap pembentukan budaya hijau (green culture) pada masyarakat kota bontang. metana media komunikasi rekayasa proses dan teknologi tepat guna, 9(2), 46-54. tessnow-von wysocki, i., le billon, p. (2019), plastics at sea: treaty design for a global solution to marine plastic pollution. environmental science and policy, 100(1), 94-104. thornton, d.b. (2013), green accounting and green eyeshades twenty years later. critical perspectives on accounting, 24(6), 438-442. tulashie, s.k., boadu, e.k., dapaah, s. (2019), plastic waste to fuel via pyrolysis: a key way to solving the severe plastic waste problem in ghana. thermal science and engineering progress, 11(1), 417-424. saputra, et al.: combining the concept of green accounting with the regulation of prohibition of disposable plastic use international journal of energy economics and policy | vol 11 • issue 4 • 202190 verma, v.k., chandra, b., kumar, s. (2019), values and ascribed responsibility to predict consumers’ attitude and concern towards green hotel visit intention. journal of business research, 96(1), 206-216. wang, j., wang, s., xue, h., wang, y., li, j. (2018), green image and consumers’ word-of-mouth intention in the green hotel industry: the moderating effect of millennials. journal of cleaner production, 181, 426-436. widiastuti, n.p.e., sukoharsono, e.g., irianto, g., baridwan, z. (2015), the concept of gratitude from the smes owners in bali to address the income tax evasion. procedia social and behavioral sciences, 211, 761-767. wulandari, r., natasari, d., faiz, i.a. (2019), penerapan akuntansi lingkungan pada badan usaha milik desa untuk mewujudkan green accounting (studi kasus pada badan usaha milik desa “x”). monex: journal research accounting politeknik tegal, 8(1), 169. yin, f., xue, l., liu, z., li, l., wang, c. (2019), structure optimization of separating nozzle for waste plastic recycling. procedia cirp, 80, 572-577. ying, z., gao, m., liu, j., wen, y., song, w. (2011), green accounting for forest and green policies in china a pilot national assessment. forest policy and economics, 13(7), 513-519. yulianti, m. (2016), akuntansi dalam rumah tangga: studi fenomenologi pada akuntan dan non akuntan. jurnal akuntansi dan manajemen, 11(2), 62-75. zald, m.n. (1986), the sociology of enterprise, accounting and budget rules: implications for organizational theory. accounting, organizations and society, 11(4-5), 327-340. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 3 • 2021 269 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(3), 269-279. analysis of green technology development in kazakhstan yerkin g. abdildin1*, serik a. nurkenov2,3, aiymgul kerimray4 1department of mechanical and aerospace engineering, school of engineering and digital sciences, nazarbayev university, 53 kabanbay batyr ave., nur-sultan, 010000, kazakhstan, 2best available technologies bureau, international center for green technologies and investment projects, mangilik el ave., building 55, c1.4, nur-sultan, 010000, kazakhstan, 3department of physics and technical sciences, l.n. gumilyov eurasian national university, satpayev str., 2, nur-sultan, 010008, kazakhstan, 4center of physical-chemical methods of research and analysis, al-farabi kazakh national university, tole bi str., 96a, almaty, 050012, kazakhstan. *email: yerkin.abdildin@nu.edu.kz received: 22 november 2020 accepted: 02 february 2021 doi: https://doi.org/10.32479/ijeep.10897 abstract although kazakhstan is a fossil fuel rich country, policymakers desire to develop a green and sustainable economy and to contribute to the global energy transition. to understand the overall situation in green technology development in the industrial sector, we conducted the first countrywide study in kazakhstan. in this paper, we present the results of the large survey on the use of “green technologies” by industrial companies in every region of the country. we aggregate the 380 reported cases of the use of green technologies by sectors like energy production, waste management, and others. we found the largest number of cases accumulated in the waste management sector, and the smallest in green building construction. our work shows that only 266 out of 877 (~30%) industrial organizations in kazakhstan utilize some form of green technology. based on detailed analysis of 141 organizations, the karagandy, east kazakhstan, aktobe, and atyrau regions reported the largest number of applications of green technologies among the 17 administrative-territorial units of kazakhstan. we also discuss barriers to the diffusion of clean technologies. we believe that this work will be of interest to politicians, environmentalists, and practitioners who are concerned about the impacts of global warming. keywords: clean technologies, sustainability, green economy, energy transition, power sector, climate change jel classifications: q01, q2, q53, q55, q56, o33 1. introduction global warming is one of the most important problems facing the world today. the impacts of “global warming of 1.5°c above pre-industrial levels” (ipcc report, 2018) have been discussed thoroughly in the literature. for example, (gonzález-mahecha et al., 2019) estimate that up to 16% of active power plants in latin america and the caribbean (lac) should be closed to meet carbon budgets. on the one hand, the existing coal-fired power plants are getting old (retirement); on the other hand, the electricity consumption (demand) is increasing worldwide. in the us, the gap will be closed by natural gas, nuclear, and renewable sources of energy (clemmer et al., 2013). germany is likely to use coal-fired power plants until 2038 (rinscheid and wüstenhagen, 2019). the “capital costs and carbon policy” are the most dominant factors for increasing the wind and solar share in the electricity generation mix in the us (bistline and young, 2019). it is important to develop attractive tax credits for investors to make clean technologies more competitive economically. examples of green (or, clean, sustainable) technologies include more efficient reduction of co2 emissions (by 20-25%) and energy consumption (by 18-31%) in metallurgical plants through electrolysis (dudin et al., 2017), and a better use of energy (sheppard and rahimifard, 2019) and production packaging (joachimiak-lechman et al., 2019) in food manufacturing. there are many approaches for reducing greenhouse gas (ghg) emissions and developing a sustainable future, but ambitious climate goals need the active involvement of governmental policymakers. this journal is licensed under a creative commons attribution 4.0 international license abdildin, et al.: analysis of green technology development in kazakhstan international journal of energy economics and policy | vol 11 • issue 3 • 2021270 kazakhstan is an upper-middle-income country located in the central asian region with a gross national income per capita of us$ 8,810 in 2019 (world bank, countries, 2020). the country has experienced considerable economic growth in the last two decades, but its development pathway can hardly be considered as ‘green’. as a result of the poor management of its significant natural resources the country experienced many years of environmental degradation (russell et al., 2018). the emissions intensity of the kazakhstan economy remains to be one of the highest in the world: the carbon intensity of the gross domestic product (gdp) in kazakhstan (0.6 kg per purchasing power parity (ppp) $ of gdp in 2016) is 2 times higher than the world average (0.33 kg per ppp $ of gdp) and 3 times higher than the european union’s (0.2 kg per ppp $ of gdp) (world bank, co2 emissions, 2020). major cities in kazakhstan suffer from heavy air pollution; with the concentrations of pollutants in the air exceeding the european union’s annual limit values in ten of the eleven studied cities (world bank, towards cleaner industry, 2013). kazakhstan adopted a strategic document as a concept of the transition to a green economy (strategy 2050, 2013) (green economy concept, 2013) immediately after the rio+20 world summit (rio+20 conference, 2012). the country has made some progress (soltangazinov et al., 2019) in the area of regulatory reform in support of the concept, including the development of kazakhstan’s environmental code (an ongoing process with regular improvements), energy efficiency, and renewable energy policies. one example of this effort is the 2020 construction of a gas pipeline – 1,081 km between karaozek, zhezkazgan, karagandy, and nursultan – from south-west kazakhstan to the central part of the country with the aim to reduce the use of coal in nearly 2.7 million households for heating, which was 40% in 2011-2013 (kerimray et al., 2018). besides that, two coal-fired thermal power plants in the city of nur-sultan will be converted to natural gas by the end of 2021. thus, there has been the introduction of green technologies, or cleaner production as defined in (hilson, 2000), and aspects of the green economy are becoming not just a popular trend, but also a system for ensuring the survival of humankind through achieving sustainable development. figure 1 illustrates the share of electricity produced by renewable energy sources (the orange bar for all res, with the left side axis in 1000 kwh) in the total electricity production in kazakhstan (represented by the grey shaded background, with the right side axis in 1000 kwh) according to data from the statistics committee of the ministry of national economy of the republic of kazakhstan. the share increases from 9.1% in 2011 to 10.4% in 2019, with electricity produced by hydroelectric power plants (hpp) – including large (i.e., > 35mwt) plants – in the amount of 9,993,658.8 thousand kwh, wind farms (707,135.1 thousand kwh), solar power plants (391,229.6 thousand kwh), and biogas plants (4,967.1 thousand kwh) totaling 11,096,990.6 thousand kwh. the rest of the electricity was produced by coal-fired power plants (70.25% on average for 2011-2019, with standard deviation of 2.58%), thermal power plants (tpp) on gas (µ = 12.14%, σ = 0.82%), tpp on fuel oil (µ = 0.02%, σ = 0.02%), and gas turbine power plants (µ = 7.61%, σ = 0.81%). many enterprises install solar panels and wind generators for their own needs, through which they reduce ghg emissions, reduce the use of carbon fuel, and, at the same time, receive economic benefits in the form of reduced costs for electricity payments. between 1990 and 1999, due to the economic recession in kazakhstan, ghg emissions decreased by nearly twofold, from 401.9 million tons in 1990, reaching its minimum of 203.7 million tons in 1999, followed by a gradual increase over the following years (2000 to 2018), as seen in figure 2 (unfccc, 2020). in 9. 1% 8. 4% 8. 1% 8. 7% 1 0. 3% 12 .7 % 11 .3 % 10 .2 % 10 .4 % 40,000,000 60,000,000 80,000,000 100,000,000 120,000,000 0 2,000,000 4,000,000 6,000,000 8,000,000 10,000,000 12,000,000 20,000,000 0 2011 2012 2013 2014 2015 2016 2017 2018 2019 total, thousand kwh res hydro wind solar biogas figure 1: electricity production in kazakhstan in 2011-2019 by types of res: hydro, wind, solar, and biogas 0 50000 100000 150000 200000 250000 300000 350000 400000 450000 1990 1995 2000 2005 2010 2015 2018 energy industrial processes and product use agriculture waste figure 2: ghg emissions trends in kazakhstan between 1990 and 2018 by sources1, in 1000s of tons (excluding emissions from land use, land use change, and forestry) 1. energy industries 44% 2. manufacturing industries and construction 13% 3. transport 9% 4. other sectors 12% 5. other 22% figure 3: share of emissions in the “energy” sector by sub-sectors in 2018 1 energy sector includes energy industries, manufacturing industries and construction, transport, and other sectors, as well as fugitive emissions from fuels. abdildin, et al.: analysis of green technology development in kazakhstan international journal of energy economics and policy | vol 11 • issue 3 • 2021 271 2018, ghg emissions in kazakhstan amounted to 396.6 million tons, nearly reaching its 1990 level, as seen in figure 3 (unfccc, 2020). under the paris agreement, kazakhstan’s nationally determined contribution (ndc) was to reduce ghg emissions by 15% below the 1990 levels by 2030. given the trends of emissions increasing in the last decade, the reduction of emissions 15% below the 1990 levels will require policies and measures for implementation of green technologies. climate action tracker (climate action tracker, 2020) rates kazakhstan’s ndc target as “insufficient,” meaning that kazakhstan’s climate plans are not consistent with holding warming to below 2°c, as required under the paris agreement. climate action tracker (2020) notes that kazakhstan “fails to take steps towards achieving a paris agreement-compatible emissions pathway” due to its plans to expand coal and oil production. the country’s efforts in the field of clean energy were strengthened after expo 2017 (“future energy”), which was held in kazakhstan. new renewable state programs were implemented and additional budgets were allocated for research related to creating a green economy, clean energy, and green technologies. the widespread adoption of green technologies enables kazakhstan to embark on a new path, ensuring balanced and sustainable development of regional economies. with advancements in this field of knowledge, there have been positive phenomena, such as the emergence of additional jobs, an improvement in quality of life, and a reduction in risks to human health, as well as the preservation of non-renewable resources and the replenishment of renewable resources. there is no actual single definition of the word “green” or environmentally friendly technology, as far as we know. as noted by (winterton, 2016), “green chemistry” does not simply mean chemistry “in harmony with the environment”; and “green energy” is not only about “healthier and safer technologies and processes” (kravanja et al., 2015). the general approach involves the implementation of their purpose – reducing the harmful “impact on the environment by reducing the amount of resources consumed, reducing the amount of waste” by promoting a circular economy and resource recovery program through deep processing, incorporating mechanisms and principles that work in nature in production processes, and improving energy efficiency of production (sarbassov et al., 2013), improving the properties of materials from the standpoint of environmental safety. however, with the advent of the term “green economy,” the definition of green technologies has acquired a new meaning – the use of green technologies should bring about not only an environmental impact, but also economic and social benefits. the burgeoning literature on energy transitions has an interdisciplinary nature and addresses an important goal in regards to the reduction of carbon emissions (geels et al., 2018; odell et al., 2018; vigoya et al., 2020). the energy transition towards low-carbon technologies is likely to have a significant impact on extractive industries (bazilian, 2018). nuclear energy, for example, is considered one mechanism to increase energy security and sustainability and to “reduce the use of fossil fuels” (mckie, 2020), but the safety and environmental issues of uranium mining should be carefully taken into account (abdildin and abbas, 2013). the research on the green, clean, and sustainable technologies, as well as measures of their impact on “the environment, society, and the economy” (sikdar, 2020), were conducted in many developed countries, but not very much in kazakhstan and central asia (sabyrbekov and ukueva, 2019). gaining access to research cites is often difficult in kazakhstan and the countries of central asia (jonbekova, 2020). in our search of literature related to green technologies in kazakhstan, we found that (ospanova, 2014) reported about the early progress of kazakhstan in terms of a green economy, (mukhtarova and zhidebekkyzy, 2015) surveyed six experts on the development of “green technologies” in kazakhstan, (terehovics et al., 2017) analyzed the potentials of solar energy in kazakhstan, (karatayev and clarke, 2016) reviewed the potentials of green energy, (kerimray et al., 2016) analyzed different scenarios for mitigating climate change, (kerimray et al., 2018) studied energy transition in the residential sector, (kozhakhmetova et al., 2019) conducted a survey on the efficiency of green energy projects, and (abdildin and abbas, 2016) proposed a multiattribute utility theory for addressing economic, technological, environmental, and safety concerns in the energy problem. this work presents the use of green technologies in kazakhstan based on analysis conducted throughout 2019. the main questions guiding our study were 'what is the overall situation with green, clean, and sustainable technologies in kazakhstan?', 'what proportion of industrial companies in kazakhstan use green technologies?', 'which regions of the country utilize green technologies and in which sectors of the economy?', 'what are the effects of using green technologies?', and 'what are the common barriers for developing green technologies in kazakhstan?'. the contribution of this paper is threefold. first, this is the first countrywide study on the use of green technologies in kazakhstan. our survey covers all 2,042 industrial organizations in kazakhstan, from which we selected 266 reporting the use of green technologies. second, it presents the current state of green technologies in the country. for the detailed analysis, we narrow the number of companies to 141 and present a comprehensive analysis of the industrial companies in kazakhstan that utilize green technologies. based on the reported cases, we rank all 17 administrative-territorial units of kazakhstan by the absolute number of green technologies used, presenting examples and the effects of using green technologies in each region. we also discuss the barriers for and potentials of using green technologies by presenting the distribution of the 611 enterprises (by region) that do not currently use green technologies. third, our work contributes to the literature on the topic of green technologies. our results are novel in that there has not been any similar research conducted in kazakhstan or the region of central asia regarding the use of green technologies. the remaining part of the paper is as follows: section 2 briefly describes the methodology used in this work, section 3 presents our results, section 4 discusses common barriers, and section 5 concludes the work. abdildin, et al.: analysis of green technology development in kazakhstan international journal of energy economics and policy | vol 11 • issue 3 • 2021272 2. methodology the international center for green technologies and investment projects (https://igtipc.org/en/) was the first to analyze kazakhstan’s enterprises in a large-scale survey. the implementation of the special program provided information on the use of green technologies by enterprises in industry and on the main problems and barriers impeding introduction of promising green technologies. as part of the collection of information for subsequent analysis, the center developed a questionnaire for business entities utilizing green technologies in the republic of kazakhstan. this questionnaire is also aimed at obtaining information on the environmental, economic, and social effects of green technologies presented in kazakhstan. a comparative analysis was performed based on data from questionnaires that were filled out by enterprises. the questionnaire contained the following sections: 1. information about the enterprise; 2. information on green technologies used; 3. environmental and economic effects: • resource efficiency; • reduction of greenhouse gas emissions; • reduction of emissions and discharges of pollutants into the environment as a result of economic activity; • reduction of emissions in the field of waste processing (municipal/industrial); • and others; 4. social effects (job creation by gender). the questionnaire process of surveying enterprises consisted of the following stages: interaction with the office of governors of regions and cities of republican significance. within the framework of existing memoranda, the center sent 17 letters to governors of each administrative-territorial unit with a request to assist in the collection of data from enterprises on the use of green technologies. to intensify the collection of information, the center sent official letters to enterprises, as well as organizing calls to enterprises. additionally, trips to the enterprises were organized for employees from the center. the list of enterprises for analysis (2,554 enterprises in total) was provided by the committee for environmental regulation and control of the ministry of ecology, geology and natural resources of the republic of kazakhstan. during the collection of information, it was revealed that some enterprises had irrelevant or missing contact information (addresses and phone numbers). as a result of this, the center sent a letter to the committee on statistics of the republic of kazakhstan requesting information on existing enterprises. according to the committee, 226 enterprises were inactive. in addition, in the process of contacting and analysis, the center identified 286 enterprises that were not in the category of enterprises issuing greenhouse gases. as a result, the center received 877 official letters from 2,042 enterprises (a 42.9% response rate), of which: • 266 enterprises submitted questionnaires on the use of green technologies (380 cases) in various sectors of the economy; and • 611 enterprises submitted official letters on the non-use of green technologies. at most enterprises, the questionnaires were undertaken by the environmental engineers or the environmental units involved in preparing environmental protection plans, obtaining environmental permits, and preparing environmental reports. in some enterprises, the role of environmental responsibility is limited to the collection of information, and ‘environmental decisions,’ such as environmental reporting and the preparation of action plans that are coordinated by the environmental department of the parent companies. the filling out of questionnaires in large enterprises was carried out by process engineers or environmental managers, from the management departments of large holdings. thus, the analysis of the application of green technologies was carried out for 266 enterprises, but 141 enterprises were selected for calculating the target indicator, in which the data on the questionnaires were filled in completely. 3. results and discussion 3.1. listing the enterprises by the year of foundation out of the 266 factories and enterprises that utilize green technologies, the majority (76.4%) were established after the independence of kazakhstan (1991) (figure 4). however, despite this, many enterprises require detailed modernization and implementation of environmentally friendly technologies. many enterprises in the country apply both foreign and domestic technologies. in the pavlodar region, bogatyr komir llp (http:// www.bogatyr.kz/en/), llp company neftekhim ltd (https:// nephtechim.kz/), and jsc “station ekibastuz gres-2” (http:// www.gres2.kz/index.php?view=3) reported the use of green technologies from germany, france, and kazakhstan (polyset llp). the use of green technologies brings new job positions, for example, 30 new jobs were created at the enterprises of kazzinc llp (https://www.kazzinc.com/en/), 162 jobs opened up at ekibastuz gres-1 llp (https://gres1.kz/kz/), and 25 jobs were created at the aktobe ferroalloy plant (https://www.kazchrome. com/en/business-overview/divisions/aktobe/) in 2019. 1 5 5 9 13 12 50 83 88 0 2 2 3 5 5 19 31 33 0 20 40 60 80 100 19 30 -1 93 9 19 40 -1 94 9 19 50 -1 95 9 19 60 -1 96 9 19 70 -1 97 9 19 80 -1 98 9 19 90 -1 99 9 20 00 -2 00 9 20 10 -2 01 9 no. of companies percentage (%) figure 4: year of foundation of the 266 companies that reported the use of green technologies in kazakhstan at the end of 2019 abdildin, et al.: analysis of green technology development in kazakhstan international journal of energy economics and policy | vol 11 • issue 3 • 2021 273 3.2. the use of green technologies by sectors of the economy and territorial units of kazakhstan our analysis revealed the sectors of the economy in kazakhstan where green technologies are used (figure 5). we tried to classify the 380 reported cases by sectors of economy, where, for example, the 24 cases of dust collection in coal-fired power stations are placed in “heat power engineering” and the percentage is calculated as 100*(24/380). similarly, the 99 reported cases with renewable energy sources were separated from other sectors to clearly distinguish them from, for example, technologies used to improve energy efficiency. at first, it may look like that the major share of reported cases of green technologies is predominantly in ‘green’ industries (which use green technologies by definition, such as the waste management sector and res), while major emitters of emissions – such as mining and metallurgy, as well as the oil and gas industries – reported less number of green technologies. however, such a separation gives a better understanding of the types of green technologies used. besides that, we also wanted to see the distribution of green technologies (e.g., in waste management) by regions of the country, not only by sectors of the economy. unlike other countries (darko et al., 2017), green building technologies in kazakhstan are not widespread, so there is a big potential for investors in kazakhstan. figure 6 illustrates how the 380 cases of the use of green technologies are distributed among 14 regions of kazakhstan and its three largest cities – almaty, nur-sultan (capital), and shymkent – which together represent all 17 administrativeterritorial units of the country (map is adapted from (“kazakhstan provinces,” 2020)). we found that the largest number of green technologies are used in the karagandy, east kazakhstan, aktobe, and atyrau regions, as large industrial enterprises of the country are concentrated in these regions. the total number of green technologies used in these areas is 209, or 55% of the total number (380). note that we present this information in absolute numbers, not in relative numbers, i.e., not as a share of organizations using green technologies from total number of surveyed organizations by region. such a ranking would not be accurate at this moment 161 99 84 24 4 3 3 2 42 26 22 6 1 1 1 1 0 20 40 60 80 100 120 140 160 180 w as te m an ag em en t r en ew ab le e ne rg y so ur ce s e ne rg y ef fic ie nc y h ea t p ow er e ng in ee rin g a gr ib us in es s o il an d g as g re en b ui ld in g m in in g an d m et al lu rg y no. of cases percentage (%) figure 5: the distribution of the 380 reported cases of implemented green technologies in different sectors of economy because there is no one-to-one relation between the 380 reported cases and the enterprises, as some companies presented several cases. figure 7 presents the distribution of the 380 reported cases in different sectors of the economy. the second echelon for the use of green technologies is in the following regions: pavlodar, kostanay, west kazakhstan, and zhambyl, as well as the city of nur-sultan. the total number of green technologies actually used in these areas is 97 out of 380, or 25.5% of the total number of applied green technologies in the regions of kazakhstan. the smallest amounts of green technologies used are in the almaty, kyzylorda, turkistan, mangystau, north kazakhstan, and akmola regions, and the cities of shymkent and almaty. the total number of green technologies used in these territorial units is 74 out of 380 (or 19.5%). 3.3. the effects of using green technologies: examples from regions we now present the examples of the effects of using green technologies in administrative-territorial units of kazakhstan. the numbers presented below (e.g., tons of emission reduction) (i) imply the effect after the implementation of the green technologies compared to the situation before the implementation, and (ii) represent numbers received in the 2019 study from various organizations in the administrative-territorial units. 3.3.1. karagandy region the largest number of cases of green technology use, according to our survey, was identified in the karagandy region – 90 cases. according to arcelormittal temirtau jsc (2019), the use of technologies to reduce the concentration of dolomite dust led to a reduction in atmospheric emissions from 570 mg/m3 to 50 mg/ m3, with the environmental effect of reducing dust emissions by more than 500 tons per year; the dust concentration was reduced from 500 mg/m3 to 20 mg/m3, since filters reduced dust emissions by 640 tons/year. there was also a decrease in particulate matter dust by more than 30% and lead by 87%, with dust collection improved by 95% and sulfur dioxide emissions into the atmosphere decreased by 70%. between 2014 and 2018, there was a decrease in air pollutants: sox by 19.76%, cox by 13.35%, and nox by 45.94%, as well figure 6: distribution of the 380 reported cases of the use of green technologies in kazakhstan abdildin, et al.: analysis of green technology development in kazakhstan international journal of energy economics and policy | vol 11 • issue 3 • 2021274 as a decrease in pollutants of 99% for sulfuric acid and 100% for wastewater (arcelormittal temirtau jsc, 2019). inorganic dust emissions into the environment decreased by 10%, and emissions of sio2 decreased by 20-70% (saryarka komir mining and processing company llp, 2019). 3.3.2. east kazakhstan region in the east kazakhstan region, there were 41 cases of green technology use reported. they contributed to the reduction in the emission of pollutants, mainly solid waste. according to firma etalon llp (2019), the processing of solid waste amounted to 24,000 tons/year. the enterprises also reported the reduction of solids by more than 30%, lead by 87%, and sulfur dioxide emissions by 70% after the implementation of clean technologies (kazzinc llp, 2019). 3.3.3. aktobe region in the aktobe region, 40 cases of green technology use were reported, 19 of them in the field o f w aste m anagement, n ine i n t he fi eld of energy efficiency, four in dust collection, six in renewable energy, one in oil and gas production, and one in green building construction. the technologies used by enterprises/issuers of greenhouse gases are aimed at reducing emissions of pollutants: dust by 80% (mugalzhar neftestroy llp, 2019), inorganic dust by 70% (technogran aktobe llp, 2019), and dust and gas emissions by 99% (interstyle llp, 2019), as well as a decrease in flue gases by 73.5 thousand m3/h (technogran aktobe llp, 2019) and a reduction in particle emissions into the environment of 13.5 tons/year (aktobe branch of “alties petroleum international bv,” 2019). there is a decrease in the disposal of waste (sludge tailings) in the amount of 250-400 thousand tons/year (donskoy ore mining and processing plant, 2019). filtration units have been installed in plants of this region, allowing 99% of the smallest dust particles to be captured (alina group llp, 2019). in addition, chromium-containing materials are processed by processing mineral raw materials: chrome spinel powder (khshp-01,02,03) on the wet enrichment line using hydroseparation, gravity enrichment, and chemical methods, with a capacity of up to six thousand tons/year (sailan aktobe llp, 2019). in the enterprises of the region, there is a decrease in the consumption of industrial water due to the re-use of industrial water in production (stroydetal llp 2019). 3.3.4. atyrau region in the atyrau region, the green technologies are aimed at reducing greenhouse gases, reducing the emission of pollutants, and improving resource efficiency. there is the use of technology for processing chicken waste of more than 11,200 tons of chicken waste a year (promekologia llp, 2019), as well as 50% energy savings (sbp kazmunaygas-drilling llp, 2019). the reduction of greenhouse gas emissions into the environment was: co2 15%, ch4 2.5%, and n2o 3% (sbp kazmunaygas-drilling llp, 2019). 3.3.5. pavlodar region in the pavlodar region, green technologies are mainly aimed at reducing greenhouse gases and ensuring the efficient us e of resources. for example, according to the pavlodar aluminum plant (2019), there has been a decrease in pollutant emissions of 2,376 tons/year, and technologies are used to reduce pollutant emissions into the environment to 10-15 times less than they were. they also report that particulate matter emissions are reduced from 25 mg/m3 to 5 mg/m3. at the same time, the degree of purification of the gas stream from dust corresponds to the level of 80-85% dust collector efficiency. additionally, a decrease in the concentration of particulate matter in flue gases decreased fivefold from 1,600 mg/m3 to 300 mg/m3, and the efficiency of ash collection increased from 97% to 99.6% (ekibastuz gres-1 llp https://gres1.kz/kz/). at the power plant of jsc eurasian energy corporation (2019), ash increase in ash collection efficiency rose to 99.5%, sulfur dioxide capture up to 18% (dust removal). the disposal of industrial waste in the ash dump decreased 2 1 4 3 4 3 1 1 2 4 8 17 9 8 17 5 2 1 2 2 4 3 13 5 3 7 2 19 19 27 47 1 2 1 5 4 3 8 1 1 4 2 4 6 7 7 10 13 10 8 1 6 3 16 1 1 2 1 1 1 1 1 1 1 1 0 10 20 30 40 50 60 70 80 90 shymkent city akmola region almaty city north kazakhstan region kyzylorda region almaty region mangystau region turkistan region west kazakhstan region zhambyl region nur-sultan city kostanay region pavlodar region atyrau region aktobe region east kazakhstan region karagandy region energy, energy efficiency waste management heat power engineering renewable energy sources agricultural sector oil and gas production mining and metallurgy green building figure 7: the 17 administrative-territorial units of kazakhstan ranked by the use of green technologies in different sectors of the economy abdildin, et al.: analysis of green technology development in kazakhstan international journal of energy economics and policy | vol 11 • issue 3 • 2021 275 approximately 30-100 thousand tons/year (power plant of jsc eurasian energy corporation, 2019). 3.3.6. kostanay region according to the state communal enterprise called tobol, after the implementation of green technologies, the emissions of pollutants into the atmosphere were reduced by 57.5%. there is also a decrease in the discharge of pollutants into the environment from the economic activities of the branch of jsc aluminum of kazakhstan kbru; the degree of purification is, on average, from 28.6 to 99.63%. also, there is a decrease in ghg emissions by 76.5%, a decrease in waste generation by 31%, reduction of emissions in the field of organic waste processing (manure in the amount of 44 tons/day and slaughterhouse waste in the amount of 1 ton/day), and reduction of pollutants into the environment from 96 tons/year to 1.6 tons/year (ilin llp, 2019). 3.3.7. nur-sultan city the technologies are used to reduce emissions in the field of waste processing (municipal/industrial); in particular, used tires do not end up in a landfill in the amount of 1,800 tons per year, as reported by kazkauchuk llp (2019), and there is also a decrease in specific emissions from coal ash from 1,500 to 350 mg/m3 (astana-energy jsc, 2019). at the same time, energy savings of up to 10% have occurred to other tower-type installations (astana metiz project llp, 2019). 3.3.8. zhambyl region according to the department of main gas pipelines in the taraz branch of jsc intergas central asia, the technologies for water disinfection through direct electrolysis are used with a chloride content of at least 20 mg/l and a hardness of no more than 7 meq/l at stations with a capacity of up to 5,000 m3/ day. according to kazphosphate llp (2019), the utilization of ‘boiler’ dust amounts to 21-22 thousand tons/year, and processed ‘boiler’ dust from accumulators, used as phosphoruspotassium fertilizers, is about 1-1.5 thousand tons/year. there is also a decrease in ghg emissions due to the introduction of the system of accounting of ghg emissions, which is about 18-21 thousand tons of carbon dioxide per annum, due to reducing the consumption of natural gas in the production of phosphorite agglomerate. 3.3.9. west kazakhstan region green technologies in the region (e.g., the kazakhstan branch of karachaganak petroleum operating b.v., icm recycling, and batys power llp) are aimed at reducing emissions of pollutants to 31,399 tons and the total reduction in co2 ghg emissions down to 950,591 tons. there is also a 60% reduction in the volume of liquid waste into the environment (uralskaya poultry farm llp, 2019) and a decrease in waste disposal (namely, sorted plastic, metal, waste paper, and other municipal solid waste) to 100%. technologies, which used to significantly reduce the load on landfill, also help to reduce pollution of groundwater and atmospheric air with the products of decay of solid waste, as well as reducing emissions in the field of waste processing. there is also a decrease in ghg emissions by 10%, a decrease in emissions and discharges of pollutants into the environment by 10%, reduction of emissions in the field of waste processing by 100% through processing into fertilizers (uralskaya poultry farm llp, 2019). 3.3.10. turkistan region the technologies here are aimed mainly at reducing ghg emissions and improving resource efficiency. th ere is a decrease in environmental pollutants of 65,000 tons (green technology industries llp, 2019) and a reduction in greenhouse gas emissions of 1.99 tons/year (jv inkai llp, 2019), as well as a decrease in the amount of oily waste by 80,000 tons of product/raw material per year, down from 100,000 tons of waste (kazecosolutions llp, 2019). 3.3.11. almaty region a good example of the use of green technologies from this region is the reduction of greenhouse gases, which is estimated at 2,735 tons of co2 (maek-kazatomprom llp, 2019). 3.3.12. mangystau region here, green technologies are used to reduce ghg emissions from desalination plants in the amount of up to 180 tons/year (llp “maek-kazatomprom,” 2019). 3.3.13. kyzylorda region this region reported ten cases of the utilization of green technologies. after the implementation of green technologies, the efficiency of exhaust gas treatment at a 2-stage gas treatment plant reached 85%, and at the 2nd stage (wet cleaning), it reached 95%, with the overall cleaning efficiency reported as 99 % (jsc petrokazakhstan kumkol resources, 2019). 3.3.14. north kazakhstan region the north kazakhstan region uses green technologies for energy efficiency, waste management, and dust collection. the examples include a decrease in the volume of harmful emissions into the atmosphere by 75% and plastic processing up to 4,000 tons (raduga llp). technologies are also aimed at reducing pollutants from nitrogen oxides in flue gases (jsc sevkazenergo, 2019). 3.3.15. almaty city the largest city of kazakhstan, almaty, reported only seven cases of green technology utilization. a good example of the reduction in the emission of pollutants into the atmosphere was reported by hydro-power llp (2019) as follows: solid reduced by 71 tons/ year and gaseous reduced by 119 tons/year. 3.3.16. shymkent city in the city of shymkent, green technologies are utilized in waste management and in renewable energy. the examples include the production of organic fertilizer of up to 34,000 tons/year, which leads to the reduction of unpleasant odors from sludge wastes due to the treatment of sediments by anaerobic digestion in digesters, and ‘clean’ electricity generation at 3.5 million kwh/year. 3.3.17. akmola region according to kazger-kus llp (2019), green technologies helped to reduce dust emissions by 99% and emissions of ammonia and abdildin, et al.: analysis of green technology development in kazakhstan international journal of energy economics and policy | vol 11 • issue 3 • 2021276 great potential for improvement. this can be done, in part, through the use of green, clean, and sustainable technologies. let us now discuss the barriers for developing these technologies. 4. common barriers for developing green technologies figure 10 represents the distribution of the 611 enterprises in kazakhstan that reported not using green technologies. as we can see, karagandy and east kazakhstan regions are again among the “leaders,” because they are the largest and most industrial regions. certainly, we could compare the shares of enterprises which utilized green technologies to the total number of enterprises participating in the survey (877) and then rank the regions, but again, this may not be accurate, since not all (2,042) enterprises provided data and/ or participated in our study. it is more important to understand the common barriers for developing green technologies. our analysis of enterprises by sectors and regions on the green technologies used revealed a low degree of awareness and interest of enterprises in the implementation of green technologies. this is because we generally observe: • a weak degree of development of the market for green technologies; • there is no methodology and terminology for green technologies, with no classification of green technologies; • there is not enough statistical information (national and regional) on the implementation of green technologies; • weak incentive support measures for businesses using green technologies; • enterprises cannot calculate the economic component from the introduction of green technologies, in this regard, they do not feel the economic effect of their use; • there are no qualified personnel in the field of green technologies, including ecologists, economists, engineers, and technologists; • the market for the service and supply of green equipment is not sufficiently developed; • there is no single platform for participants in the green technology market (investors, owners and developers, suppliers of technologies and equipment, business, public and private quasi-sectors of the economy, etc.). the existing system of environmental regulation is weak: • technical emission standards for power and heat industries are several times too high for european standards for so2, 0.246 0.21 0.22 0.218 0.234 0.214 0.23 0.231 0.236 0.212 0.215 0.224 0.204 0.213 0.193 0.193 0.2 0.2 0 0.05 0.1 0.15 0.2 0.25 0.3 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 to e/ 10 00 u s d 2 01 0 p p p kazakhstan world united kingdom figure 9: energy intensity measured in terms of primary energy and gdp, 2000-2017 83 41 37 52 25 23 0 20 40 60 80 100 solid household waste sewage water petrochemical waste no. of cases percentage (%) hydrogen sulfide by 35%. another example was presented by rsu16 llp (2019), where green technologies helped them achieve a 90% reduction in pollutants and ghg emissions. 3.4. the use of green technologies in waste management the major use of green technologies in the regions of kazakhstan is observed in the waste management sector, which accounts for 42.3% of the total number of clean technologies. figure 8 illustrates the use of green technologies in waste management by sub-sectors. recycling is an important component of sustainable resource use. this indicator is an important component of solid waste management. the current situation in the field o f waste management in kazakhstan is characterized by the following problems the transportation, removal, and disposal of solid waste do not meet the standards; the legacy of historical waste; the growth of new industrial waste and household waste. to address these issues, it is necessary to rebuild an integrated waste management system. 3.5. dynamics of the energy intensity of the economy one of the key indicators of the development of the country, as well as its energy sector, is the energy intensity of the economy. the energy intensity is the ratio of total energy use to the gdp measured in the tons of oil equivalent (toe) per 1000 us dollars. based on data from the international energy agency (iea, energy intensity, 2019), we compare the energy intensity of kazakhstan to the world and to the united kingdom as an example of a country with excellent energy intensity (figure 9). as we can see, between 2000 and 2017 kazakhstan improved the energy intensity of the economy from 0.246 to 0.2 toe per 1,000 usd (a 23% improvement); however, in comparison with the world’s and uk’s statistics, there is figure 8: green technologies in waste management by sub-sectors abdildin, et al.: analysis of green technology development in kazakhstan international journal of energy economics and policy | vol 11 • issue 3 • 2021 277 nox, and pm (oecd: addressing industrial air pollution in kazakhstan, 2019); • in the permitting system, emission limit values for enterprises are determined based on compliance of concentration levels with environmental quality standards rather than emission limits that an industry could achieve when applying the best available techniques (bat) (oecd: addressing industrial air pollution in kazakhstan, 2019); • enterprises in kazakhstan obtain emission limit values based on the highest level of emissions measured during the maximum production output. this allows enterprises to comply with the legislation without investing in processes, technologies, and techniques (oecd: addressing industrial air pollution in kazakhstan, 2019). some of the above mentioned barriers (e.g., the lack of professionals) were also found in developing green buildings in malaysia (samari et al., 2013) and in ghana (chan et al., 2018), for example; and some other barriers were found in res development in the central asian region (kaliakparova et al., 2020). kazakhstan is faced with many reasons that slow down the adoption of green technology strategies at the enterprise level and at the national policy level. many kazakhstani enterprises are branches of large industrial or communal holdings, or groups with headquarters in nur-sultan, almaty, or abroad. in such large enterprises, decisions on significant investments in environmental management are made at the head offices, while the enterprises themselves do not have sufficient authority to make such decisions. the market for green technologies in kazakhstan is at an early stage. in general, compared to the international green technology market, kazakhstan is rather lagging behind. over time, domestic enterprises will begin to switch to green technologies and, in this case, western experience will contribute to the rapid development of ‘green’ industries. so far, ‘green’ technologies come to our country through the transfer of foreign technologies, and not from their own developments. in the process of collecting information, it was revealed that there is no common understanding of the term ‘green technologies’ in the country and no unified statistics on the technologies implemented. it was also revealed that at some enterprises, technologies are not fully accounted for, there is no description of technologies, no documentation is maintained, there are not always calculated indicators of resource and economic efficiency of the implemented technologies, there is no monitoring of the use of the introduced technologies, and there are no additional motivational measures for enterprises that stimulate the use of green technologies. the introduction and widespread use of green technologies in kazakhstan requires coordinated actions on various fronts, including the regulatory framework, removing barriers and introducing institutional and economic incentives. although kazakhstan has environmental legislation and regulations, a comprehensive strategy needs to be developed, including several possible instruments for policy implementation. 5. conclusions in this work, we presented the results of the survey of all kazakhstani companies that have a relation to green technologies. the idea was to analyze the state of the development of green technologies in kazakhstan, identifying the sectors of the economy where green technologies are better developed and where there is a high potential for improvement. out of the 380 reported cases presented by the enterprises, the majority were in the waste management sector (42%), renewable energy sector (26%), or energy efficiency (22%). the green building construction sector (1%) turned out to be the least developed sector of the economy. kazakhstan is making some progress in developing its energy infrastructure, focusing on electrification and gas transmission infrastructure. the share of the population with access to electricity is almost 100%, however, a high share of electricity generation from coal (~70.25%) – mainly on high-ash coals of the ekibastuz basin – and significant losses in electric networks (~20%) cause high levels of environmental impact from the electric power industry. our results also show that more cases of using green technologies are found in the industrial regions of the country. the results also reveal that other regions of the country, located mainly in the south part of kazakhstan, as well as the largest industrial regions (karagandy and east kazakhstan), have high potential for the use of green technologies. analysis of data on the applied ‘green technologies’ by issuing enterprises in the regions showed that some enterprises have already implemented ‘green’ technologies, while some have partially implemented them. the technologies used differ greatly in the effectiveness of the impact of the enterprise on the environment. each technology itself is multifactorial; for example, by purifying wastewater, we get the opportunity to obtain an additional secondary product – in the form of either fertilizer or biogas – for generating electricity or components of production residues that can be returned to the production cycle, while the purified water can also be reused in production or be used for other economic purposes; additionally, the effect of reducing air emissions is obtained. the net results are both environmental and economic benefits. the problems lie in assessing and calculating all the effects of the introduction of green technology. in general, we observe that kazakhstan is progressing in the right direction, 1 14 16 21 24 25 27 27 37 39 39 43 47 51 58 67 75 0.16% 2.29% 2.62% 3.44% 3.93% 4.09% 4.42% 4.42% 6.06% 6.38% 6.38% 7.04% 7.69% 8.35% 9.49% 10.97% 12.27% 0 10 20 30 40 50 60 70 80 90 almaty city turkistan region pavlodar region west kazakhstan region north kazakhstan region kyzylorda region shymkent city akmola region nur-sultan city mangystau region aktobe region atyrau region kostanay region zhambyl region east kazakhstan region karagandy region almaty region no. of enterprises percents out of 611 enterprises figure 10: distribution of 611 enterprises that reported not using green technologies abdildin, et al.: analysis of green technology development in kazakhstan international journal of energy economics and policy | vol 11 • issue 3 • 2021278 but a lot of work should be done in the near future to better contribute to the world’s effort on achieving a green economy and more sustainable development. 6. acknowledgement this work was supported in part by the governmental grant number “бп044” provided to the international center for green technologies and investment projects by the ministry of ecology, geology, and natural resources of the republic of kazakhstan. work of aiymgul kerimray was supported by the postdoctoral fellowship provided by al-farabi kazakh national university. references abdildin, y.g., abbas, a.e. (2013), canonical multiattribute utility functions: enumeration, verification, a nd a pplication. procedia computer science, 18, 2288-2297. abdildin, y.g., abbas, a.e. (2016), analysis of decision alternatives of the deep borehole filter restoration problem. energy, 114, 1306-1321. bazilian, m.d. (2018), the mineral foundation of the energy transition. the extractive industries and society, 5(1), 93-97. bistline, j.e.t., young, d.t. (2019), economic drivers of wind and solar penetration in the us. environmental research letters, 14(12), 124001. carbon dioxide emissions (kg per ppp $1 of gdp), data. (2020), available from: https://www.data.worldbank.org/indicator/en.atm. co2e.pp.gd. chan, a.p.c., darko, a., olanipekun, a.o., ameyaw, e.e. (2018), critical barriers to green building technologies adoption in developing countries: the case of ghana. journal of cleaner production, 172, 1067-1079. clemmer, s., rogers, j., sattler, s., macknick, j., mai, t. (2013), modeling low-carbon us electricity futures to explore impacts on national and regional water use. environmental research letters, 8(1), 015004. climate action tracker. (2020), available from: https://www. climateactiontracker.org/countries/kazakhstan. conception of kazakhstan on transition to green economy, strategy 2050. (2013), available from: https://www.strategy2050.kz/en/ news/1211. darko, a., chan, a.p.c., gyamfi, s., olanipekun, a.o., he, b.j., yu, y. (2017), driving forces for green building technologies adoption in the construction industry: ghanaian perspective. building and environment, 125, 206-215. dudin, m.n., reshetov, k.y., mysachenko, v.i., mironova, n.n., divnenko, o.v. (2017), “green technology” and renewable energy in the system of the steel industry in europe. international journal of energy economics and policy, 7(2), 310-315. energy intensity-sdg7: data and projections-analysis. (2019), international energy agency. available from: https://www.iea.org/ reports/sdg7-data-and-projections/energy-intensity. geels, f.w., schwanen, t., sorrell, s., jenkins, k., sovacool, b.k. (2018), reducing energy demand through low carbon innovation: a sociotechnical transitions perspective and thirteen research debates. energy research and social science, 40, 23-35. global warming of 1.5oc. (2018), available from: https://www.ipcc. ch/sr15. gonzález-mahecha, e., lecuyer, o., hallack, m., bazilian, m., vogtschilb, a. (2019), committed emissions and the risk of stranded assets from power plants in latin america and the caribbean. environmental research letters, 14(12), 124096. green economy concept. (2013). available from: https://greenkaz. org/images/for_news/pdf/npa/koncepciya-po-perehodu.pdf. [last accessed on 2020 sep 15] hilson, g. (2000), barriers to implementing cleaner technologies and cleaner production (cp) practices in the mining industry: a case study of the americas. minerals engineering, 13(7), 699-717. joachimiak-lechman, k., selech, j., kasprzak, j. (2019), eco-efficiency analysis of an innovative packaging production: case study. clean technologies and environmental policy, 21(2), 339-350. jonbekova, d. (2020), educational research in central asia: methodological and ethical dilemmas in kazakhstan, kyrgyzstan and tajikistan. compare: a journal of comparative and international education, 50(3), 352-370. kaliakparova, g.s., gridneva, y.e., assanova, s.s., sauranbay, s.b., saparbayev, a.d. (2020), international economic cooperation of central asian countries on energy efficiency and use of renewable energy sources. international journal of energy economics and policy, 10(5), 539-545. karatayev, m., clarke, m.l. (2016), a review of current energy systems and green energy potential in kazakhstan. renewable and sustainable energy reviews, 55, 491-504. kazakhstan provinces and province capitals. (2020), in wikipedia. available from: https://www.en.wikipedia.org/wiki/file:kazakhstan_ provinces_and_province_capitals.svg. kerimray, a., baigarin, k., de miglio, r., tosato, g. (2016), climate change mitigation scenarios and policies and measures: the case of kazakhstan. climate policy, 16(3), 332-352. kerimray, a., de miglio, r., rojas-solórzano, l., ó gallachóir, b.p. (2018), causes of energy poverty in a cold and resource-rich country: evidence from kazakhstan. local environment, 23(2), 178-197. kerimray, a., suleimenov, b., de miglio, r., rojas-solórzano, l., amouei torkmahalleh, m., ó gallachóir, b.p. (2018), investigating the energy transition to a coal free residential sector in kazakhstan using a regionally disaggregated energy systems model. journal of cleaner production, 196, 1532-1548. kozhakhmetova, a.k., gabdullin, k.t., kunanbayeva, d.a., tazhiyeva, s.k., kydaybergenova, r.e. (2019), green energy project`s efficiency: a cross-industry evaluation. international journal of energy economics and policy, 9(5), 207-215. kravanja, z., varbanov, p.s., klemeš, j.j. (2015), recent advances in green energy and product productions, environmentally friendly, healthier and safer technologies and processes, co2 capturing, storage and recycling, and sustainability assessment in decisionmaking. clean technologies and environmental policy, 17(5), 1119-1126. mckie, r.e. (2020), an environmental harm perspective to examine our understanding of uk nuclear energy expansion. the extractive industries and society, 7(2), 556-564. mukhtarova, k., zhidebekkyzy, a. (2015), an analysis of green technologies’ development in kazakhstan: problems and perspectives. the journal of economic research and business administration, 111(5), 1. odell, s.d., bebbington, a., frey, k.e. (2018), mining and climate change: a review and framework for analysis. the extractive industries and society, 5(1), 201-214. oecd. (2019), addressing industrial air pollution in kazakhstan: reforming environmental payments policy guidelines. available from: http://www.oecd.org/tax/addressing-industrial-air-pollutionin-kazakhstan-0e04ea86-en.html. ospanova, s. (2014). assessing kazakhstan’s policy and institutional framework for a green economy. london: international institute for environment and development. p33. rinscheid, a., wüstenhagen, r. (2019), germany’s decision to phase out coal by 2038 lags behind citizens’ timing preferences. nature abdildin, et al.: analysis of green technology development in kazakhstan international journal of energy economics and policy | vol 11 • issue 3 • 2021 279 energy, 4(10), 856-863. russell, a., ghalaieny, m., gazdiyeva, b., zhumabayeva, s., kurmanbayeva, a., akhmetov, k.k., mukanov, y., mccann, m., ali, m., tucker, a., vitolo, c., althonayan, a. (2018), a spatial survey of environmental indicators for kazakhstan: an examination of current conditions and future needs. international journal of environmental research, 12(5), 735-748. sabyrbekov, r., ukueva, n. (2019), transitions from dirty to clean energy in low-income countries: insights from kyrgyzstan. central asian survey, 38(2), 255-274. samari, m., ghodrati, n., esmaeilifar, r., olfat, p., mohd shafiei, m.w. (2013), the investigation of the barriers in developing green building in malaysia. modern applied science, 7(2), 1. sarbassov, y., kerimray, a., tokmurzin, d., tosato, g., de miglio, r. (2013), electricity and heating system in kazakhstan: exploring energy efficiency improvement paths. energy policy, 60, 431-444. sheppard, p., rahimifard, s. (2019), improving energy efficiency in manufacturing using peer benchmarking to influence machine design innovation. clean technologies and environmental policy, 21(6), 1213-1235. sikdar, s. (2020), measures for sustainability. clean technologies and environmental policy, 22(2), 279-280. soltangazinov, a., smagulova, z., amirova, m., kashuk, l., karimbergenova, m., kadyrova, a., zhaltyrova, o. (2019), energy efficiency as a factor of sustainable development in kazakhstan. international journal of energy economics and policy, 10(1), 325-330. terehovics, e., khabdullin, a., khabdullin, a., khabdullina, z., khabdullina, g., veidenbergs, i., blumberga, d. (2017), why solar electricity has high potential for kazakhstan industries. energy procedia, 113, 417-422. unfccc. (2020), available from: https://www.unfccc.int/docum ents?f%5b0%5d=country%3a1379&f%5b1%5d=docume nt_type%3a4147. united nations conference on sustainable development, sustainable development knowledge platform. (2012), available from: https:// www.sustainabledevelopment.un.org/rio20. [last accessed on 2012 jun 20]. vigoya, m.f., mendoza, j.g., abril, s.o. (2020), international energy transition: a review of its status on several continents. international journal of energy economics and policy, 10(6), 216-224. winterton, n. (2016), green chemistry: deliverance or distraction? clean technologies and environmental policy, 18(4), 991-1001. world bank country and lending groups–world bank data help desk. (2020), available from: https://www.datahelpdesk.worldbank.org/ knowledgebase/articles/906519-world-bank-country-and-lendinggroups. world bank group. (2013), towards cleaner industry and improved air quality monitoring in kazakhstan. washington, dc : world bank group. available from: http://www.documents.worldbank. org/curated/en/132151468047791898/towards-cleaner-industryand-improved-air-quality-monitoring-in-kazakhstan. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 2 • 2022188 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(2), 188-197. asymmetric effect of oil prices on export performance: the role of export financing schemes in pakistan shazia kousar1, iqra khalid2, farhan ahmed3*, josé pedro ramos-requena4 1department of economics, lahore college for women university, lahore, 54000, punjab, pakistan, 2superior university lahore, 55150, punjab, pakistan, 3department of economics and finance, greenwich university, karachi, 75500, sindh, pakistan, 4departamento de economía y empresa, universidad de almería, ctra. sacramento, s/n, 04120 la cañada de san urbano, almería, spain. *email: drfarhan@greenwich.edu.pk received: 03 november 2021 accepted: 28 january 2022 doi: https://doi.org/10.32479/ijeep.12746 abstract this study aims to check the impact of export financing (ef) schemes like ef-25, oil prices, exchange rate, and foreign direct investment on export performance in pakistan. the study utilized textile exports and non-textile exports to measure the export performance in pakistan. data for modelled variables are taken from the state bank of pakistan (sbp), and international financial statistics (ifs) for the period from 2004 to 2020. this study employed auto regressive distributive lags (ardl) and non-linear auto regressive distributive lags (nardl) models from 2004 to 2020 to check the symmetric and asymmetric impact of modelled variables on export performance in pakistan. it is observed that there is a positive and significant impact of export financing schemes and oil prices on the performance of the export of pakistan in both time regimes before and after the world financial crisis 2008. asymmetric effects showed that positive shock in oil prices leads to a positive change in exports and negative shock also leads to a positive change in exports. the impact of export financing on the textile sector is significant and positive but it is insignificant in the case of oil prices. whereas the impact of oil prices on non-textile exports of pakistan is significant and a positive rather insignificant impact of export financing is found for non-textile exports. according to the results, export financing is favorable for pakistan’s export performance so it should be encouraged and more schemes should be introduced. keywords: financing scheme, export performance, pakistan, oil price, foreign direct investment, exchange rate jel classifications: c22, c50, f30, g10, g12, q43 1. introduction exports are just like fuel for the engine of economic stability, growth, and long-term development of an economy. determinants of exports are of two types i.e. external and internal. demand-side conditions are known as external factors and supply-side conditions are associated with internal factors. internal factors are; exporting country’s characteristics (size of natural resources, labour force participation, credit financing, market orientation, the country’s revealed comparative advantage), managerial characteristics (international experience and educated entrepreneurs), and product characteristics (type of good either it is a consumer good or capital good, production cost and technology sophistication). external factors consist of domestic and foreign market characteristics (similarity or difference in the environment, geographical distance, cultural difference, political factors and legal requirements, consumer preferences, trade barriers) and industry characteristics (industry type and technological orientation). there is a history of international trade which starts from the barter system and then it was substituted with mercantilism in the era of the 16th and 17th centuries. when the world entered the 18th century it saw transference to liberalism. that was the time when first time in the history of economics adam smith known as the father of economics wrote the legendary book ”the wealth of nations” in 1976. in that book, he explained gains of international trade can this journal is licensed under a creative commons attribution 4.0 international license kousar, et al.: asymmetric effect of oil prices on export performance: the role of export financing schemes in pakistan international journal of energy economics and policy | vol 12 • issue 2 • 2022 189 be acquired by getting an absolute advantage in the production of any commodity. after him, david ricardo extended the theory by developing the principle of comparative advantage, which has maintained its importance even today. nowadays every nation wants to increase its exports to survive in the world. every nation is competing with one another. pakistan is also in this race and trying hard to expand its exports to increase its foreign reserves but still not achieved its goal. due to fewer exports, pakistan’s financial status is very low and still lies on the list of developing countries. in this study, it is to be checked that pakistan is spending on export financing to strengthen its exporter. should it be increased more to get surplus in exports and on the other hand pakistan is a labour abundant nation but oil prices strongly affect its import performance and similarly oil prices are important to utilized capital intensive techniques in the export sector. as exports are a great support for the open economy, this study aims to investigate the symmetric impact of export financing schemes and the asymmetric impact of oil prices on export performance in the context of pakistan. most of the researchers who worked on export performance used linear models (katsikeas et al., 1996; ram, 1985). however, the majority of the macroeconomic variables show nonlinearities, mainly in oil prices because these are volatile (falk, 1986; neftci, 1984). asymmetric modelling is not rare or unusual rather many studies are there which encouraged asymmetric modelling and claimed that within social sciences asymmetries are usual and vital to the human state (kahneman and tversky, 2013; shiller, 1994; 2015). though the chief purpose of the present study is to investigate the asymmetric impact of export financing and oil prices on export performance; hence, many types of prices documented asymmetric patterns. this consists of the exchange rate (arghyrou and pourpourides, 2016; bahmani-oskooee and fariditavana, 2016; delatte and lópez-villavicencio, 2012; verheyen, 2013a; 2013b), inflation (katrakilidis and trachanas, 2012), and oil prices (ibrahim, 2015; lardic and mignon, 2008; qin et al., 2016; raza et al., 2016). in the literature on oil price, the asymmetric effect on export performance is unnoticed. higher oil prices may lead to an increase in the cost of production in various sectors; this may lead to decreased production and raise unemployment and might be a reason for inflation. the proof which backed up this statement seemed in the study of doğrul and soytas (2010) and also mentioned by katircioglu et al. (2015) in his study. the justification behind the interface between oil prices and exports is that pakistan is a country which is an importer of oil and among world oil-importing countries it is on 33rd number (the world factbook); so, it can be said that exports are affected by oil prices higher. moreover, export financing, exchange rate, and fdi are also major factors of export performance in pakistan. the textile sector is pakistan’s major export sector. by dividing exports into two main categories textile and non-textile, this study investigated the impact of export financing and oil prices on them. in figure 1 indicated that pakistan’s export growth is miserable for the previous two years and it has declined about 12.9% during 2016-17. pakistan’s exports are soaring between 19 billion since 2008-2017 and no substantial progress and progression has been observed in exports of pakistan. exports percentage of gdp is 13.39 in 2003 but dropped down to 7.46 in 2016. figure 2 indicated that the textile sector comprises 51% of total exports. 544 billion rs. are earned from hosiery and garments only. so it can be said that textile is the main export sector of pakistan whose importance cannot be forgettable. since 2005 many of the asian economies have been taking the benefits of quota closure for clothing and textile zone. this study examines the impact of export financing and oil prices on pakistan’s total exports. the study also examines the impact of export financing and oil prices on pakistan’s total exports before and after the financial crisis of 2008. the symmetric impact of oil prices on pakistan’s total exports has also been examined. 2. literature review 2.1. export financing and export performance akgündüz et al. (2018) investigated that do subsidized loans increased exports. a study mentioned that turkey’s central bank is giving a subsidized loan to its exporters, so the study was source: gillani research foundation figure 2: in 2018-19 pakistan’s largest export industry is the textile industry source: state bank of pakistan figure 1: export trends in pakistan kousar, et al.: asymmetric effect of oil prices on export performance: the role of export financing schemes in pakistan international journal of energy economics and policy | vol 12 • issue 2 • 2022190 conducted to check the performance of those firms which are getting benefits from such a rediscount credit policy. behind this policy, the central bank of the republic of turkey (cbrt) has two goals i.e. expansion in foreign reserves and the other one is the promotion of exports. as it is a firm-level analysis so the results showed that the rediscount credit receiving firms have a positive relationship with exports rather the non-receivers. the findings are qualitatively comparable to the case of binary therapy with considerable beneficial effects on exports, sales, and workers and no influence on national sales and revenues. the estimates indicate that not only the current year’s credits impact the company’s output, but also the past year’s credit. this is similar to the rediscount credits structure. a company that receives the rediscount credit must document a total export value in 2 years that is not less than the credit amount. a 1% rise in rediscount credits appears to boost exports in the same year by around 0.028% and in the following year by 0.029%. the impact of sales is 0.005% in the same year and 0.012% in the subsequent year. similarly, felbermayr and yalcin (2013), investigated that credit markets were collapsed in the crisis of 2008-2009 which badly affect exporters more than other firms. so many countries protect their exporting firms to be the defaulters against their foreign buyers both in the presence or absence of a financial crisis. in general export credit guarantees are considered as export subsidies which are not allowed by world trade organization (wto) but there is a space under wto agreement on subsidies and countervailing measures regarding export credit guarantees. risks regarding export credits are not properly covered by privately organized financial markets so that’s why the government has to interfere. the study concluded that there exists a positive relationship between export credit guarantees and exports. if public guarantees are increased by 1 % it will cause a.012 % increase in exports on average. moreover, broocks and van biesebroeck (2017), utilized two approaches to address a probable upward bias due to self-selection in assistance: study concentrated on sub-samples of companies where endogenous therapy choice is less probable, and (ii) use companies that receive the weakest type of assistance as compared to companies receiving wider assistance. the impacts stay positive and statistically significant, but in magnitude, they are smaller and much less accurately estimated in the second case. 2.2. oil prices and export performance tried to investigate the relationship between oil prices and exports performance in china. theoretically being an oil-importing country there should be a negative relationship between oil prices and exports but after applying the ardl approach to the model where the impact of oil prices, labour productivity, real exchange rate, and foreign income on exports of china was checked over the monthly data for the period of 1992-2005. a study found that the relationship between oil prices and exports of china is positive and concluded as china is a labour abundant country so oil prices did not affect negatively. qianqian (2011) explained that oil is an essential element for economic development. due to increased demand for oil, as oil is used in every field of the economy nowadays, the reliance on imported oil is also increasing day by day in china. by applying the co-integration and error correction model, the study found that there exists a long-run relationship between oil prices and china’s economic growth, inflation, net exports, and monetary policy. the results showed that the increase in global oil prices will lead to shrinking net exports and the real gdp and the real money supply whereas inflation will go up. jawad (2013), examined the effect of oil price volatility on economic growth in pakistan. coefficients were estimated using secondary data from 1973 to 2011. linear regression analysis is used to evaluate the dependence between dependent and independent variables. trade balance, private sector investment has a major impact on gross domestic output and public sector investment, oil price volatility has a negligible impact on gross domestic product. the study suggests that a proper plan and procedure must be put in place by the government in line with pakistan’s economic growth and demand that would help maintain a balance between oil demand and supply and reduce the effect of oil price volatility on growth. meanwhile, pakistan’s government has also focused on its trade balance and is also trying to boost investment by the private sector to support its economic growth. 2.3. fdi and export performance fetai and morina (2019), checked the impact of inflows of fdi on export performance on the transition economies of europe from 2000 to 2015. the study showed that there is a positive relationship between fdi and exports and some other factors like investments and trade liberalization have also positive effects whereas real gdp and real exchange rate affect exports negatively. liu and shu (2003), empirically investigated the determinants of chinese export performance using cross-sectional data at the industry level. the study found that the export performance of different sectors is significantly affected by labour costs, foreign direct investment (fdi), and the size of the company. the study used cross-sectional industry-level data to explore the factors affecting the chinese industry’s export performance. the study found that fdi, labour costs, and size of the company significantly affect export performance. china produced 18% of the total labour-intensive commodities in the world. however, both india and pakistan are abundant in labour, but china’s exports are still much larger than both. these results show that chinese companies have realized their relative advantages, but point to the need for the industry to improve its export structure to maintain growth. contrary et al. (2019), checked whether fdi contributes to exports in india or not. the period chosen for this purpose is from 1980-to 2017. the study found that the fdi affects real exports adversely in the long-run period. 2.4. exchange rate and export performance for some moment, policymakers, scholars, and professionals have been gaining attention from the link between export performance and exchange rate policy, especially for emerging countries. recently, vo and zhang (2019) investigated the connection between devaluation of the exchange rate, volatility, and performance of exports. the assessment focuses on the production industry and ten of its subsectors involved in exporting products in vietnam during the period 2000-2015 and twenty-six kousar, et al.: asymmetric effect of oil prices on export performance: the role of export financing schemes in pakistan international journal of energy economics and policy | vol 12 • issue 2 • 2022 191 main export partners. the study confirmed that a strategy that depreciates the currency of vietnam appears in the brief term to improve manufacturing exports, whereas the resulting volatility of the exchange rate has clear adverse long-term impacts. the effect on manufacturing subsectors of exchange rate volatility relies on two variables, namely export type and export destination. (thuy and thuy, 2019), used quarterly information from the first quarter of 2000 to the fourth quarter of 2014 to investigate the effect of exchange rate volatility on the exports in vietnam. the study utilized the autoregressive distributed lag (ardl) testing method to analyze the relationships between the volatility of exchange rates and exports. the study also considered the impact of depreciation and foreign earnings on vietnam’s exports using the demand function of exports. the study found that export quantity is negatively affected by exchange rate volatility. domestic currency depreciation hurts exports in the short run, but it has a positive impact in the log-run, consistent with the j. curve impact. surprisingly, a rise in a foreign country’s real income effectively reduces the number of vietnamese exports. these results indicate some political consequences for the management of the exchange rate scheme and the promotion of vietnam’s exports 2.5. financial crisis and export performance iacovone and zavacka (2009), analyzed the impact of banking crises on exports. the study distinguished the effect of banking crises on export development from other exogenous shocks i.e. demand shock) based on information from twenty-three episodes of banking crises containing both developed and developing nations. results indicated that, during a recession, exports of industries are more dependent on internal financing as compared to other industries. however, sectors with a higher degree of asset tangibility tend to be more resilient to a banking crisis. the effect of banking crises on exports is strong, as well as internal demand shocks. the impact of the latter is autonomous and complements that of a banking shock, and is of special importance to industries producing sustainable products. during the worldwide economic crisis, chor and manova (2012), studied the collapse of international trade flows using comprehensive information on monthly us imports. the study demonstrated that long-term loans are a significant channel through which trade volumes were impacted by the crisis, exploiting the variation in capital cost across nations and over time, as well as the variation in economic vulnerability across industries. countries with greater interbank prices and thus tighter credit markets during the crisis peak exported less to the us. this impact was particularly pronounced in industries requiring comprehensive external funding, having restricted access to trade credit, or having few assets that can be collateralized. exports from financially fragile sectors were, therefore, more sensitive to internal capital costs than exports from less susceptible sectors, and during the financial crisis, this sensitivity increased. this study highlighted the quantitative impacts of financial crises on export volume. similarly, bricongne et al. (2012), identified that during the global crisis, global trade declined rapidly and severely. this study utilized a distinctive french company dataset to match export information with firm-level loan limitations and demonstrates that most of the trade crash in 2008-2009 was due to unprecedented demand shock and product features. while the crisis impacted all companies, the impact on big companies was primarily on the intensive margin and resulted in a lower product portfolio being offered to export destinations. the impact on smaller exporters was to decrease or completely prevent exporting the variety of locations served. credit limitations were an additional aggravation on companies operating in industries of strong economic reliance. 3. data and methodology in this study monthly data is used from 2004 to 2020 and data for modelled variables is taken from the state bank of pakistan (sbp), and international financial statistics (ifs). this study developed six models to check the effect of export financing schemes, oil prices, exchange rate, and fdi on exports performance in pakistan. in models 1, 2, 3, and 4 this study utilized total exports to measure the export performance (xp) as dependent variables while export financing scheme (ef), oil prices (op), foreign direct investment (fdi) and exchange rate (er) are used as independent variables. however, in model 5, textile export (t.xp), and in model 6 nontextile exports are used to measure export performance. this study utilized auto regressive distributive lag models that are considered a powerful tool to calculate long-term economic time series relationships. the simple form of autoregressive distributive lags (ardl) regression model is as follow: yt = α0 + α1•yt-1 + β0 xt + β1 xt-1 + εt (1) equation 1 indicates that both independent and dependent variables have the lag order of 1. the regression coefficient of x in the long-run equation and ecm equation can be expressed as follow: k = β0 + β1/1 + α1 δyt = α0 + (α1 − 1) (yt−1 – k xt−1) + β0 δ xt-1 + εt (2) a general ardl (p0, p1, p2, p3,..., pn) model for one dependent variable y and a set of independent variables x1, x2, x3,..., xn, in which p0 is lag of dependent variable and p1----pn are lags of the independent variable can be written as follows: �y y x x x t t i t j t k t l i p i p k p l � � � � � � � � � � � � � � � �� � � � � 0 1 2 3 4 1 1 0 2 0 3 0 1 2 3 pp m pm n t m tx 4 0 4� �� � ���...... � � (3) 3.1. ardl specified models model 1 � � � � � ex ex ef op fdi t t i t i t i t i n i n i n � � � � � � � � � � � �� � �� � � � � 0 1 2 3 4 1 1 1 ii t i t t t t i n i n er ex ef op fdi er � � � � � � � � �� � � � � 1 1 5 1 1 2 1 3 1 4 1 5 � � � � � � � tt t� ��1 kousar, et al.: asymmetric effect of oil prices on export performance: the role of export financing schemes in pakistan international journal of energy economics and policy | vol 12 • issue 2 • 2022192 model 2 � � � � � ex ex ef op op t t i t ii n i n i n t i t � � � � � � � � � � �� � � � � � � � � � 0 1 2 3 4 1 1 1 iii n i n i n t i t i t t t fdi er ex ef op � � � � � � � �� � �� � � � 1 1 1 5 6 1 1 2 1 3 � � � � � � � �� � �� � ��1 4 1 5 1� �fdi ert t t model 3 � � � � � � � � � � ex ex ef op fdi t t i t i t i n i n i n t i � � � � � � � � � � � � � � � 0 1 2 3 4 1 1 1 ii t i t t t t i n i n er ex ef op fdi er � � � � � � � � �� � � � � 1 1 5 1 1 2 1 3 1 4 1 5 � � � � � � � tt t� ��1 model 4 � � � � � ex ex ef op fdi t t i t i t i n i n i n t i � � � � � � � � � � � � � � � � � � � � 0 1 2 3 4 1 1 1 ii t i t t t t i n i n er ex ef op fdi er � � � � � � � � �� � � � � 1 1 5 1 1 2 1 3 1 4 1 5 � � � � � � � tt t� ��1 model 5 � � � � � tex tex ef op fdi t t i t i t i i n i n i n � � � � � � � � � � � � � � � � � � � 0 1 2 3 4 1 1 1 tt i t i t t t t i n i n er tex ef op fdi � � � � � � � �� �� � � � � 1 1 5 1 1 2 1 3 1 4 1 � � � � � � � 55 1 ert t� �� model 6 � � � � � ntex tex ef op f nt t i t i t i i n i n i n � � � � � � � � � � � � � � � � � � � 0 1 2 3 4 1 1 1 ddi er tex ef op fdin t i t i t t t t i n i n � � � � � � � �� �� � � � 1 1 5 1 1 2 1 3 1 4 � � � � � � 11 5 1 � ���� ert t 4. results before the empirical investigation, it is necessary to ensure the stationarity of the time series data; it implies that the mean and variance of the time series data remain the same over time. this study applied augmented dickey-fuller (adf) (dickey and fuller, 1979) and phillips and perron (phillips and perron, 1988) to confirm the stationarity of the data. the null hypothesis of the adf test states that yt has unit root or series is non-stationary while alternative hypothesis states that yt has no unit root and the series is stationary. to test for unit root, the adf test statistic is compared with a corresponding critical value; if the absolute value of the test statistic is lower than that of the critical value, the null hypothesis is accepted and the series is non-stationary and then we can use the difference of the series. if the time series is stationary at level, it is called series is integrated at level [i (0)] and if the time series is non-stationary at the level and stationary at the first difference, it is called [i (1)]. the results of the adf test and descriptive statistics have been reported in table 1. the probability value of jarque bera for all modelled variables is greater than a 5% level of significance that indicating that the data of all modelled variables are normally distributed. moreover, the data of exports and oil prices is skewed towards the right side and has a long tail on the left side as the value of skewness has a negative sign for both variables. the other variables possess left side skewness and long tails on the right side which is shown by the positive value of skewness. all the variables have a kurtosis value less than 3 which means data is normally distributed and has a fine peak. moreover, the results of adf are reported in the lower panel of table 2 and results indicate that all the variables are integrated at first difference except xp and op which are stationary at level. these mixed results lead to applying ardl for long-run cointegration. 4.1. ardl bound test before the empirical investigation of short-run and long-run relationships; it is necessary to check the long-run co-integration among the series. conventionally, engle and granger (1987) or johansen (1988) are utilized to examine the long-run cointegration among series but it has been observed that these methods may produce biased results regarding long-run co-integration when some series are integrated at level [i (0) ] and some are integrated at first difference [i (1)] (engle and granger, 1987; johansen, 1988). thus to obtain unbiased estimations, regardless of whether variables in the model are integrated i(0) and i(1), this study utilized ardl bound test which was proposed by pesaran et al. (2001). therefore, the ardl bounds test is used to check the longtable 1: descriptive statistics measures xp op ner fdi ef mean 1714.239 78.10826 115.7740 262.8010 629.1087 median 1774.500 75.72500 103.0989 200.3941 641.8000 maximum 2665.000 132.8300 161.4620 973.4399 990.1000 minimum 873.0000 31.33000 79.37794 47.43328 217.0000 standard deviation 391.0022 25.45068 27.57248 179.8286 204.6644 skewness -0.064853 -0.040369 0.353809 0.810036 0.081157 kurtosis 2.122381 1.846992 1.453114 1.340234 1.895778 jarque-bera 4.559760 5.681690 1.63808 5.08196 0.027841 probability 0.751411 0.14006 0.82441 0.14982 0.91841 source: authors’ calculations kousar, et al.: asymmetric effect of oil prices on export performance: the role of export financing schemes in pakistan international journal of energy economics and policy | vol 12 • issue 2 • 2022 193 run co-integration between the modelled variables, and results are reported in table 3. the results indicate that the calculated value of f-statistic is greater than the lower and upper bound values; so there is significant long-run co-integration among modeled variables in model 1, 2, 3, 4, 5 and 6. after confirmation of long-run co-integration among defined series, this study applied ardl co-integration technique to estimate short-run and long-run estimates for its several advantages; first, in the case of small sample size, ardl produce unbiased and reliable estimates, second, it incorporates various lag order of all variables while estimating short-run and long-run estimates and third, it produces short-run and long-run estimates in a single equation. the results of short-run and long-run estimates are reported in tables 4, and 5. in table 4, the result of model 1 indicates that oil prices, and export financing schemes have positive and significant while the exchange rate has a negative and significant long-run association with export performance. however, foreign direct investment has an insignificant impact on export performance in pakistan. similarly, in model 2, results indicate that op+ and ophave a positive and significant long-run association with export performance; as oil prices increase export performance will increase and when oil prices decrease export performance increases. model 3 indicates that before financial crises oil price, export finance, and foreign direct investment positively and significantly affect export performance while the exchange rate negatively and significantly affects export performance. however, model 4 indicates that after financial crises only oil prices and export financing significantly affect export performance while exchange rate and foreign direct investment insignificantly affect export performance. model 6 indicates that ef positively and significantly while fdi and er negatively and significantly affect textile export in long run. however, oil prices have an insignificant association with textile exports. moreover, model 6 indicates that only oil prices have a significant impact on non-textile export in the long run while all other variables like er, fdi, and ef have an insignificant impact on export performance in pakistan. table 2: unit root test variables augmented dickey‑fuller phillip‑perrons at level at first difference adf pp adf pp xp -1.742 -2.507* -4.450* -4.384* ef 0.028 2.417 -3.577* -2.925* op -3.662* -2.597 -2.310* -2.925* fdi -1.473 1.249 -3.596* -3.577* er -0.923 -1.629 -3.577* -2.925** t.xp -1.473 1.249 -3.596* -3.577* n.t.xp -1.868 -1.313 -6.245* -6.224* source: authors’ calculations table 3: ardl bounds test critical values f. statistics f (xp/ef, op, er, fdi) f (t.xp/ef, op, er, fdi) f (n.t.xp/ef, op, er, fdi) model 1 model 2 model 3 model 4 model 5 model 6 12.98397 11.38290 17.78739 7.458755 7.434475 26.16476 l.b u.b l.b u.b l.b u.b l.b u.b l.b u.b l.b u.b 1% 3.74 5.06 3.41 4.68 3.74 3.52 3.74 5.06 3.74 5.06 3.74 5.06 2.5% 3.25 4.49 2.96 4.18 3.25 4.49 3.25 4.49 3.25 4.49 3.25 4.49 5% 2.86 4.01 2.62 3.79 2.86 4.01 2.86 4.01 2.86 4.01 2.86 4.01 10% 2.45 3.52 2.26 3.35 2.45 3.52 2.45 3.52 2.45 3.52 2.45 3.52 decision long run co-integration exists l.b stands for lower bound while u.b indicates upper bound table 4: estimated long run coefficients variables dependent variable: export performance model 1: ardl model 2: nardl model 3:before financial crisis model 4: after financial crisis β p‑value β p‑value β p‑value β p‑value c 2289.9 0.00 1592.8 0.02 2140.6 0.00 1418.7 0.01 op 3.93* 0.00 4.24* 0.00 5.25* 0.00 op+ 5.52* 0.00 op_ 4.21* 0.00 ef 0.44* 0.00 0.32* 0.02 0.14* 0.02 0.63* 0.00 fdi -0.11 0.43 -0.11 0.37 0.20* 0.00 -0.42 0.16 er -9.87* 0.00 -4.37* 0.02 -8.25* 0.00 -2.10 0.65 iv model 5: dep. variable: txp model 6: dep. variable: ntxp β p‑value β p‑value c 1263 0.00 935212.5 0.11 ef 284.11* 0.00 -223.62 0.54 op 1016.15 0.16 7694.59** 0.05 fdi -245.43* 0.00 -22.24 0.95 er -4370.22 0.00 -4850.44 0.16 source: authors’ calculations kousar, et al.: asymmetric effect of oil prices on export performance: the role of export financing schemes in pakistan international journal of energy economics and policy | vol 12 • issue 2 • 2022194 table 5 indicates the results of short-run dynamics. the results of the error correction term (ect) indicate that if any external shock deviates the export performance from its trend growth path; in the case of model 1, 65% disturbance will be adjusted in the year while in mode 2, 68%, in model 3, 56%, in model 4, 63%, in model 5, 43% and in model 6, 38% disturbance will be adjusted in one year. so all the models are stable and will converge toward a trend growth path with the speed of 65%, 68%, 56%, 63%, 43%, and 38%. moreover, the cusum test for models 1,3,4,5, and 6 ensure that series are stable in all defined error correction models. furthermore, this study derived multiplier dynamic adjustments for model 2. the cumulative multipliers for oil prices are shown in figures 3-5, and they confirm the existence of a positive nexus between oil prices figure 3: cusum test for model 1 and multiplier dynamics for model 2 figure 4: cusum test: model 3 and 4 table 5: the short‑run dynamics variables dependent variable: export performance model 1: ardl model 2: nardl model 3:before financial crisis model 4: after financial crisis β p‑value β p‑value β p‑value β p‑value δop 1.97 0.00 11.47 0.00 3.33 0.01 δop+ 9.46 0.02 δop2.90 0.00 δef 0.82 0.00 0.81 0.00 0.17 0.03 1.10 0.00 δfdi 0.14 0.05 0.12 0.08 0.12 0.04 0.10 0.40 δer -19.83 0.04 -16.84 0.08 -24.63 0.00 -1.33 0.65 ect(-1) -0.65 0.00 -0.68 0.00 -0.56 0.00 -0.63 0.00 model 5: dependent variable: t.xp model 6: dependent variable: n.t.xp β p‑value β p‑value δef 122.233 0.0007 -224.6749 0.5495 δop 437.169 0.1686 7730.556 0.0529 δfdi 9.7463 0.7672 -22.3463 0.9547 δer -1880.150 0.0000 -4873.112 0.1653 ect(-1) -0.43 0.0000 -0.38 0.0000 source: authors’ calculations kousar, et al.: asymmetric effect of oil prices on export performance: the role of export financing schemes in pakistan international journal of energy economics and policy | vol 12 • issue 2 • 2022 195 and export performance. the positive shock in oil price is more dominant than the negative shock. 5. conclusion and policy recommendations this study has examined six empirical models; model one examined the impact of export financing schemes like ef-25, oil prices, exchange rate, and foreign direct investment on export performance in pakistan. model two examined the asymmetric impact of oil prices on export performance; models three and four studied the impact of export financing schemes like ef-25, oil prices, exchange rate, and foreign direct investment on export performance before and after financial crises 2008. model five and six examined the impact of export financing schemes, oil prices, exchange rate, and foreign direct investment on textile and non-textile export. the results indicate that export financing schemes have a positive and significant long-run association with export performance in all models except model six. our results are consistent with existing literature (martincus and carballo, 2008; ribeiro et al., 2020; van biesebroeck et al., 2015) found the vital role of export financing schemes to increase export performance. specifically, the global financial crisis of 2008 has forcefully demonstrated that export finance plays a key role to motivate local exporters to perform their jobs in international trade (ter wengel and rodriguez, 2006). this research is conducted on the export performance of pakistan. pakistan has tried hard to enhance exporters and to motivate people to export more and more. in this regard, the pakistan government is benefiting the exporter with different export financing schemes as pakistani exporter’s main issue is finance as it’s a capital-lacking country. in this study, the fe-25 scheme is taken for export financing which is used to finance the local exporter in foreign currency so that it can meet its import bills required to produce its exporting products (zia, 2008). studies proved that export financing has a positive significant impact on exports of pakistan. it’s proved that it is beneficial for local exporters especially for textile exporters and it should be increased. the second variable is oil prices. theory suggests that oil prices affect the cost of production positively which can make goods expensive and can affect exports negatively but this study proved that oil prices affect exports positively. even before and after the financial crisis of 2008 and non-textile exports are also affected by oil prices positively but textile exports are not affected by oil prices. in this regard, faria et al. (2009) also revealed these results that oil prices have a positive impact on china’s exports and the reason behind this is that china is labour abundant country and does not too much rely on machines that are affected by oil prices. so is the case with pakistan because pakistan is also a labour-abundant country and this rule can also be applied to pakistan. this case is also checked via a non-linear approach as the behaviour of oil prices is asymmetric. oil prices affect positively exports both with positive shock and negative shock. the world financial crisis affected the whole world (carvalhal and leal, 2013), so in this study, it is also checked that before the financial crisis and after the financial crisis what will be the results. in this regard, there is a positive and significant impact of both export financing and oil prices before and after the world financial crisis of 2008 (baumann and braga, 1988). when the total exports are segregated into textile and non-textile exports the results show that on textile exports except oil prices all variables have a significant impact, fdi has a negative impact, export financing and exchange rate have a positive impact on textile export performance (ahmed, 2008). on non-textile exports only oil prices have significant impact and it is positive. this shows that a major sector of pakistan in which pakistan has a revealed comparative advantage does not affected by the change in oil prices. for non-textile exports when oil prices increase the cost of production increases overall the world but as pakistan is a labor abundant nation so her cost of production is less affected by oil prices. comparatively low cost of production leads to lower prices in world market due to which in spite of increase in oil prices non-textile exports increase and overall exports also increase. when oil prices decrease the products are much cheaper in the domestic market so the domestic demand increase and the major portion of produced goods is sold in domestic market and less is left to export. for this reason decrease in oil prices leads to decrease the exports of non-textile sector and so as the overall exports. figure 5: cusum test: model 5 and 6 kousar, et al.: asymmetric effect of oil prices on export performance: the role of export financing schemes in pakistan international journal of energy economics and policy | vol 12 • issue 2 • 2022196 the government of pakistan should increase export financing facilities to encourage exporters for the betterment of export performance. results indicate that the exchange rate hurts exports. to take advantage of this government should increase exports in quantity and quality both to increase the receipts and on the other hand imports should be reduced by imposing trade restrictions on imports for example tariffs and quotas etc. citizens of the nation should prefer national products to imported products so the import bill will be reduced and the exchange rate will be favourable. four variables are used to check their impact on exports of pakistan; however, more variables should be added in this model like labour force and human capital as pakistan is a labour abundant nation so labour force could be a significant factor that can enhance the export sector of pakistan. references ahmed, y. (2008), the textile industry of pakistan. report on textile industry of pakistan. horizon securities. akgündüz, y.e., kal, s.h., torun, h. (2018), do subsidised export loans increase exports? the world economy, 41(8), 2200-2215. arghyrou, m.g., pourpourides, p. (2016), inflation announcements and asymmetric exchange rate responses. journal of international financial markets, institutions and money, 40, 80-84. bahmani-oskooee, m., fariditavana, h. (2016), nonlinear ardl approach and the j-curve phenomenon. open economies review, 27(1), 51-70. baumann, r., braga, h.c. (1988), export financing in ldcs: the role of subsidies for export performance in brazil. world development, 16(7), 821-833. bricongne, j.c., fontagné, l., gaulier, g., taglioni, d., vicard, v. (2012), firms and the global crisis: french exports in the turmoil. journal of international economics, 87(1), 134-146. broocks, a., van biesebroeck, j. (2017), the impact of export promotion on export market entry. journal of international economics, 107, 19-33. carvalhal, a., leal, r.p.c. (2013), the world financial crisis and the international financing of brazilian companies. bar-brazilian administration review, 10, 18-39. chor, d., manova, k. (2012), off the cliff and back? credit conditions and international trade during the global financial crisis. journal of international economics, 87(1), 117-133. delatte, a.l., lópez-villavicencio, a. (2012), asymmetric exchange rate pass-through: evidence from major countries. journal of macroeconomics, 34(3), 833-844. dickey, d.a., fuller, w.a. (1979), distribution of the estimators for autoregressive time series with a unit root. journal of the american statistical association, 74(366a), 427-431. doğrul, h.g., soytas, u. (2010), relationship between oil prices, interest rate, and unemployment: evidence from an emerging market. energy economics, 32(6), 1523-1528. engle, r.f., granger, c.w. (1987), co-integration and error correction: representation, estimation, and testing. econometrica: journal of the econometric society, 55, 251-276. falk, b. (1986), further evidence on the asymmetric behaviour of economic time series over the business cycle. journal of political economy, 94(5), 1096-1109. faria, j.r., mollick, a.v., albuquerque, p.h., león-ledesma, m.a. (2009), the effect of oil price on china’s exports. china economic review, 20(4), 793-805. felbermayr, g.j., yalcin, e. (2013), export credit guarantees and export performance: an empirical analysis for germany. the world economy, 36(8), 967-999. fetai, b., morina, f. (2019), does fdi inflow accelerate export performance in countries in transition? an empirical analysis of european countries in transition. research in economics and business: central and eastern europe, 11(1), 5-16. iacovone, l., zavacka, v. (2009), banking crises and exports: lessons from the past. washington, dc: the world bank. ibrahim, m.h. (2015), oil and food prices in malaysia: a nonlinear ardl analysis. agricultural and food economics, 3(1), 2. jawad, m. (2013), oil price volatility and its impact on economic growth in pakistan. journal of finance and economics, 1(4), 62-68. johansen, s. (1988), statistical analysis of cointegration vectors. journal of economic dynamics and control, 12(2-3), 231-254. kahneman, d., tversky, a. (2013), prospect theory: an analysis of decision under risk. in: handbook of the fundamentals of financial decision making: part i. singapore: world scientific. p99-127. katircioglu, s.t., sertoglu, k., candemir, m., mercan, m. (2015), oil price movements and macroeconomic performance: evidence from twenty-six oecd countries. renewable and sustainable energy reviews, 44, 257-270. katrakilidis, c., trachanas, e. (2012), what drives housing price dynamics in greece: new evidence from asymmetric ardl cointegration. economic modelling, 29(4), 1064-1069. katsikeas, c.s., piercy, n.f., ioannidis, c. (1996), determinants of export performance in a european context. european journal of marketing, 30(6), 6-35. lardic, s., mignon, v. (2008), oil prices and economic activity: an asymmetric cointegration approach. energy economics, 30(3), 847-855. liu, x., shu, c. (2003), determinants of export performance: evidence from chinese industries. economics of planning, 36(1), 45-67. martincus, c.v., carballo, j. (2008), is export promotion effective in developing countries? firm-level evidence on the intensive and the extensive margins of exports. journal of international economics, 76(1), 89-106. mohanty, s., sethi, n. (2019), does inward fdi lead to export performance in india? an empirical investigation. global business review, 22(2), 0972150919832770. neftci, s.n. (1984), are economic time series asymmetric over the business cycle? journal of political economy, 92(2), 307-328. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. phillips, p.c., perron, p. (1988), testing for a unit root in time series regression. biometrika, 75(2), 335-346. qianqian, z. (2011), the impact of international oil price fluctuation on china’s economy. energy procedia, 5, 1360-1364. qin, x., zhou, c., wu, c. (2016), revisiting asymmetric price transmission in the us oil-gasoline markets: a multiple threshold error-correction analysis. economic modelling, 52, 583-591. ram, r. (1985), exports and economic growth: some additional evidence. economic development and cultural change, 33(2), 415-425. raza, n., shahzad, s.j.h., tiwari, a.k., shahbaz, m. (2016), asymmetric impact of gold, oil prices and their volatilities on stock prices of emerging markets. resources policy, 49, 290-301. ribeiro, j., figueiredo, a., forte, r. (2020), export promotion programs: differences between advanced and emerging economies. journal of east-west business, 26(3), 213-234. shiller, r.j. (1994), macro markets: creating institutions for managing society’s largest economic risks. oxford, united kingdom: oup oxford. shiller, r.j. (2015), irrational exuberance: revised and expanded. 3rd ed. kousar, et al.: asymmetric effect of oil prices on export performance: the role of export financing schemes in pakistan international journal of energy economics and policy | vol 12 • issue 2 • 2022 197 princeton, new jersey: princeton university press. ter wengel, j., rodriguez, e. (2006), sme export performance in indonesia after the crisis. small business economics, 26(1), 25-37. thuy, v.n.t., thuy, d.t.t. (2019), the impact of exchange rate volatility on exports in vietnam: a bounds testing approach. journal of risk and financial management, 12(1), 6. van biesebroeck, j., yu, e., chen, s. (2015), the impact of trade promotion services on canadian exporter performance. canadian journal of economics, 48(4), 1481-1512. verheyen, f. (2013a), exchange rate nonlinearities in emu exports to the us. economic modelling, 32, 66-76. verheyen, f. (2013b), interest rate pass-through in the emu-new evidence using the nonlinear ardl framework. economics bulletin, 33(1), 729-739. vo, d.h., zhang, z. (2019), exchange rate volatility and disaggregated manufacturing exports: evidence from an emerging country. journal of risk and financial management, 12(1), 12. zia, b.h. (2008), export incentives, financial constraints, and the (mis) allocation of credit: micro-level evidence from subsidized export loans. journal of financial economics, 87(2), 498-527. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 5 • 2022124 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(5), 124-131. integration of lean methodology and energy management in wooden industry tran le phong1, nguyen dat minh2* 1university of economics-technology for industries, vietnam, 2electric power university, hanoi, vietnam. *email: minhndm@epu.edu.vn received: 19 may 2022 accepted: 22 august 2022 doi: https://doi.org/10.32479/ijeep.13327 abstract the application of lean thinking to energy management is the methodology based on the application of the lean values and the principles of wastes elimination of lean system. one is then challenging and questioning why a process is using the amount of energy that it does and why it is using energy during non-production hours. one strives to continuously improve and reduce the energy used by implementing improvement ideas. todays, the pressure of competition in the energy sector is very high. a enterprise that wants to make a difference should continuously run optimization from the production lines. the objective of this study is to measure the impact of lean tools on energy consumption and energy efficiency improvement. through a case study, authors point out changes in production and energy efficiency before and after implementing improvement (kaizen) projects. besides, this paper illustrate the framework of lean tools application into energy sector as a guideline for energy efficiency management in industrial enterprises. keywords: energy saving, energy efficiency, lean production, industrial enterprise, wooden industry jel classifications: e23, l23, l6, m11, q01, q4 1. introduction lean term firstly known in 1990 by womack and jones in the book “the machine that changed the world” when they were talking about the success of toyota with the toyota production system (tps) which is developed in the 1950s (pascal, 2015; womack et al., 1990). the most significant theory of lean is the non-value-added perspective via eliminating wastes, operational enhancement, and continuous improvement (dey et al., 2019; ohno, 1988; saini and singh, 2020). the strength of lean is reduce manufacturing cost through elimination all types of waste and guide a company to become a world-class organization. in reality, lean is now being applied widely in various areas to optimize cost, reduce waste and irrationalities in business operation so that the enterprise can achieve lower production costs and improve competitiveness for enterprises (caiado et al., 2018; fercoq et al., 2013). lean has played an important role in enterprises in terms of improving the processes and increasing customers’ satisfaction and organizational performance (salah et al., 2010). besides, lean principles and tools are believed to contribute to sustainable achievement in its economic dimension by reducing resources and cost within enterprises’ operation, social dimension through enhancing working environment conditions for employees, and finally environmental dimension by reducing eliminating wastes and pollution (caiado et al., 2018). the energy sector and energy efficiency (ee), which is one of the pillars of national strategy to improve economic competitiveness and sustainability of the economy. the increase in energy consumption depending on the increase of the world population and innovative technological developments require closer attention to the changes in energy sources (apak et al., 2012). energy management will contribute to protecting the environment by using less energy or at least improve ee and hence combat climate change by reducing co2 emissions (thollander, 2020). the environmental improvement factor is a particularly strong factor due to the urgency to reduce global warming and high awareness in the public and hence also this journal is licensed under a creative commons attribution 4.0 international license phong and minh: integration of lean methodology and energy management in wooden industry international journal of energy economics and policy | vol 12 • issue 5 • 2022 125 among the employees. this high awareness among employees can be important when communicating about the energy management initiative and in trying to get improvement suggestions coming in (mkhaimer et al., 2017). ee is the core dimensions of the energy union, next to energy security, solidarity and trust; the internal energy market; decarbonization of the economy; and research, innovation and competitiveness. co-benefits of energy efficiency like the reduction of emissions, enhanced competitiveness, health and economic benefits can be significantly higher than the cost of production measures (zhang et al., 2016). energy-saving is a key element to achieve decarbonization at a global level. indeed, existing evidence suggests that strong energy efficiency policies are key to attaining the 1.5°c objective and reducing energy and climate mitigation costs as increased energy efficiency can provide up to 50% of the emission reduction required to meet the objectives of the paris agreement (allen et al., 2019). within the framework of the paris agreement, different countries commit to reducing emissions in this area through the objectives and actions collected in their nationally determined contributions (labandeira et al., 2020). during the last three decades, many countries have introduced policies to reduce energy demand and improve energy efficiency (bertoldi and mosconi, 2020). however, achieve large savings can be very difficult as the actual implementation of energy efficiency actions has been consistently below the optimal level (labandeira et al., 2020; linares and labandeira, 2010). in recent decades, vietnam has been one of the active and fastest growing economics in the region and the world. economic growth is still a high priority by the government of vietnam, however governmental strategies emphasize that fast development has to go side by side with sustainable development. the energy sector plays a significant role in promoting economy development. economic growth requires secure and affordable supply of energy to all of the society participants and economic sectors. at the same time, in order to be sustainable, the energy sector must be able to attract the capital required to expand infrastructure, securing the needed supply of energy sources in the long term, and reducing negative environmental impacts as well as controlling green-house gas emissions (danish energy agency, 2017; hoang, 2021). thus, the purpose of this paper is to review the lean concepts, principles, and tools that are integrated into the energy management goals of enterprises. additionally, lean practices result of the previous research will be shown as pieces of evidence to indicate the positive influences of lean application on the sustainable improvement of enterprises. 2. vietnam’s energy efficiency target vietnam government has strengthened the policy framework on ee improvement of various end-users in the economy. a number of legal documents covering the planning and implementation of ee policy and the program has been approved and enforced by the government. in this regard, the vietnam government has also strengthened the institution for ee improvement by creating a special agency named energy efficiency and conservation office (ee&co) under the ministry of industry and trade (moit). this agency is tasked to formulate, develop and implement ee&c policies and programs. as the part of ee improvement strategy, the government of vietnam developed and launched a comprehensive national ee&c program called the vietnam national energy efficiency program (vneep). the vneep layouts ee programs for the period 2006-2015, which was approved and enforced on 14 april 2006 by the prime minister decision no.79/2006/qd-ttg (the government of vietnam, 2006) (minh, 2021). the national program on ee&c is an important target of the national energy development strategy, which the ministry of industry and trade (moit) was assigned by the government to develop. so far, the industry and trade sector has made concerted efforts to adopt many energy-saving solutions, with initial positive results. the energy security and sustainable have always been one of the top concerns of the vietnamese government, and the moit is tasked with administering sufficient energy supplies for the country, ee&c is one of the most effective solutions to reduce pressure in the exploitation, processing and supplies of different kinds of energies. it also helps preserve national energy resources, protect the environment and reduce greenhouse gas emissions, contributing to mitigating the impacts of global climate change. the vietnam national energy efficiency program (vneep) was approved in 13th march 2019 in decision no. 280/2019/qd-ttg by the prime minister to set up the energy efficiency goals as well as activities, and outcomes for period 2019-2025 and 2026-2030 (prime minister of vietnam, 2019). in accordance with the vneep program, all city/provincial governments have been developing their own action plans of ee to achieve the goals of 5%-7% of energy consumption. through case study, the main purpose of this study is to develop the action plan of ee implementation (eeap) at provincial level of vietnam. besides, the energy consumption in the industrial sector accounts for more than 47% of the country’s total energy consumption. therefore, the potential for energy saving in the industrial sector in vietnam is estimated at 20-30%, even up to 40* in some industries. in summary, the purpose of this study is to introduce the application of lean in the industrial energy consumption sector to contribute the achievable of energy-saving by 2025, vision to 2030 of vietnam. 3. lean production management and its impact on energy consumption 3.1. lean introduction lean is a combination of principles, tools, and techniques designed to deal with the root problems of ineffective activities in manufacturing. lean aims to optimize the values of productivity, quality, cost, and ability to meet customer’s requirements (delivery) while still ensuring the safety conditions of production. as to meet these goals, lean tries to get rid of three main sources leading to damages from the production management system: waste, volatility, and inflexibility. one of the other goals of lean is to use fewer resources to generate the same results. this is obviously environmentally phong and minh: integration of lean methodology and energy management in wooden industry international journal of energy economics and policy | vol 12 • issue 5 • 2022126 friendly: since using fewer materials in production leads to reduced environmental impact. besides, quality improvement reduces reusing, reconditioning, or remanufacturing, then waste is reduced and pollution costs are diminished, so the environmental benefits are obvious. lean practices represent the lean principles in an implementation form. there are many tools and techniques of lean that vary from one study to another. the basic system of tools and techniques in different levels build up “lean house” with the foundation and pillars illustrated in figure 1 as below. the foundation of the lean house includes 5ss system, visual management (vm), waste/muda elimination, total productive maintenance (tpm), standardized work (sw) and continuous improvement (kaizen). these platforms of tools and techniques play a role in creating the stability of production systems and build up the lean culture in the entreprise (liker, 2006; ohno, 1988; womack and jones, 2003). the first pillar of the lean house is just in time (jit). jit means producing the right item at the right time in the right quantity, anything else is wasted, it means jit just only producing what is necessary at that time with a necessary quantity (pascal, 2015). therefore, all of the activities providing more or earlier than planned are considered as waste (womack and jones, 2003). performing jit in manufacturing is such an important activity to obtain the inventory reduction objection and eliminate overproduction (achanga, 2007). the few main principles of jit is do not supply anything unless the customer has ordered it; level demand so that work may proceed smoothly throughout the plant; link all processes to customer demand through simple visual tools; maximize the flexibility of people and machinery. therefore, to meet jit rules, we need to utilize tools, techniques, and principles to build up the continuous flow, synchronized production and achieve a “pull” production system. there are several tools are produced including kanban, cell layout, takt time, leveling production, value stream mapping (vsm), one-piece flow, smed, etc… that illustrated in figure 1 (pascal, 2007; womack and jones, 2003). the second pillar of the lean house is jidoka. the japanese word ji-do-ka comprises three chinese characters. the first “ji” refers to the worker himself, if he feels “something is wrong” he must stop the production line. “do” refers to motion or work, and “ka” refers to the suffix or action. therefore, taken together jidoka has been defined by toyota as “automation with a human mind” and intelligent production and taking quick countermeasures (ohno, 1988; pascal, 2007). in this way, automation prevents low-quality products from being sent to the next steps and does not create uncommon mistakes (pascal, 2015). the goal of jidoka is to prevent the risk of malfunction in production or to recognize the problems before it occurs. jidoka also helps to identify errors, to prevent and control mistakes (liker, 2004). implementing jidoka ensures standard quality and also preventing faults of machines, equipment and reducing the human-related activities in the production process. some tools performing jidoka are error prevention system (poka-joke) and work control system, production introductions (andon). 3.2. waste of energy consumption from perspective of lean production substantial energy savings typically ride the coattails of lean. by eliminating manufacturing wastes such as unnecessary processing and transportation, business also reduce the energy needed to power equipment, lighting, and cooling.” without explicit consideration of energy wastes, however, lean may overlook significant opportunities to improve performance and reduce costs. energy is a vital input to most production processes and value streams. by thinking explicitly about unnecessary energy use as another “deadly waste”, lean implementers can significantly reduce costs and enhance competitiveness, while also achieving environmental performance goals. energy wastes increase the costs of business. the energy use hidden in lean wastes is shown in table 1. in summary, energy waste should also be linked and controlled by the enterprises. all the enterprises management system are in tremendous pressure to increase productivity and reduce energy waste. top managers should view energy waste as an obstacle in achieving profits, so they are encouraging to improve energy performance of their factories. table 1: energy used hidden in lean waste waste type energy use overproduction energy consumed in operating equipment to make unnecessary products inventory energy used to heat, cool, and light inventory storage and warehousing space transportation and motion more energy used for transportation and delivery more space required for work in process (wip) movement, increasing lighting, heating, and cooling demand and energy consumption defects energy consumed for making defective products; space required for rework and repair; increasing energy use for heating, cooling, and lighting over processing energy consumed in operating equipment related to unnecessary processing waiting wasted energy from heating, cooling, and lighting during production downtime. source: the author conducted from (gogula et al., 2011) figure 1: a simple view of main elements in the house of lean phong and minh: integration of lean methodology and energy management in wooden industry international journal of energy economics and policy | vol 12 • issue 5 • 2022 127 3.3. lean tools application for energy consumption reduction although, all the lean tools are not energy saving tools, there are a great deal of lean tools, six tools that are frequently used to implement lean and can be used to greatly reduce energy consumption have be identified. these tools are: standard work, visual workplace, error proofing/poka-yoke, tpm, quick changeover/smed, value stream mapping, and right-sized equipment. in the following paragraphs we show how the different tools mentioned above can play a significant role in the reduction of energy consumption: • 5s and visualize: visual workplace provides visual indicators so that goals and current status of the workplace can be easily identified. these indicators can include energy usage goals, which can help workers and managers to be conscious of energy use and opportunities for energy reduction. • standardized work: standard work is a set of work procedures that establish the best and most reliable method of performing a task or operation. work procedures maintained at each work station incorporating energy reduction best practices can reduce the energy waste. for instance: • building energy reduction best practices into training materials, standard work for equipment operation and maintenance. • adding energy reduction practices into 5s checklists. • poka-yoke (mistake-proofing): mistake proofing refers to procedures that are used to prevent defects and processing errors. reducing the errors or completely eliminating the errors or defective parts reduces the energy consumption per unit of good parts. • total productive maintenance (tpm): systematic care and maintenance of the equipment increases the life of machines and reduces machining downtime. with proper equipment and system maintenance, facilities can reduce manufacturing process defects and save an estimated more than 20% in energy cost. different strategies that can be adopted for integrating energy-reduction efforts into tpm are: • integrate energy reduction opportunities into autonomous maintenance activities. • train employees on how to identify energy wastes and how to increase equipment efficiency through maintenance and operations. • conduct energy kaizen events to make equipment more efficient. • build ee best practices into systems for management of safety, health, and environmental issue. • smed/quick change-over: quick change-over is a procedure to reduce the setup and changeover time for a process. this tool reduces the time the line is down. it also reduces the energy used to make the changeover and provide light and heat during non-productive time. • value stream mapping vsm: vsm is one way to understand the overall of energy consumption in shop floor. the information of energy consumption added into the vsm makes everyone to be able to easily understand the complete impact that the value stream has on the operational performance, energy efficiency. • right-sized equipment: it is a method that ensures that the appropriate machines and equipment are used to complete a process step. selecting equipment that has just enough capability and speed to satisfy the flow of a production cell can provide energy savings over an outdated machine that has much more capacity than it is required. 4. methodology this study focuses on the potential in combining lean principles and ee through a case study from wooden manufacturer in vietnam. accordingly, primary evidence was collected through multiple sources of evidence including interview of energy and production managers that followed and deployed lean energy projects, and a participants observation by the author. the data was collected over period of time from jan, 2022 to june, 2022, allowing participants to have an in-depth reflection upon their experience from the projects as well as and impact of their experience on the factories. all interviewees participated with ee improvements projects in their plants. the interviews focused on the interviewees’ experiences with and perceived impact of the lean application to the ee improvement. the interview questions were structured around the following themes that also served as the foundation for data analysis: personal influence; knowledge and lessons learned… besides, the authors also participated into energy audit and ee improvement (called project kz) from mar, 2022 to june 2022 provide insights and understanding about the problems and answer “how” and “why” lean can success applied and achieved ee improvement in the case company. a leading manufacturer in wooden industry in vietnam are selected to conduct this study because of high rate of energy consumption and its impacts to production total cost. the case study is the most common research approach that is generally used in lean research. this is probably because this approach is valuable in terms of providing explanations of linkages among events, and it is suitable when a real-world event is being examined as in the case of lean implementation for ee improvement at the empirical level. participation observing through joining ee improvement projects in case company to get more data and compared to interview table 2: data collection sources and information gathered sources description information gathered document review energy audit reports; lean implementation reports. data on energy consumption and lean operation; data on before-after lean/ qcc implemented. interviews managers of electromechanical department; managers of production department; supervisors from shop floors general aspects of the company on ee improvement and lean targets; mechanism of ee projects was implemented and its results; observation on site survey; participated one lean energy project how the lean tools solved the problems occurred during the project and achieved the targets on ee improvement phong and minh: integration of lean methodology and energy management in wooden industry international journal of energy economics and policy | vol 12 • issue 5 • 2022128 results on project implementation. after receiving the interview and observe results, the authors recorded and took notes on all the related documents including ee outcomes (table 2). the findings are presented in the next section, starting with an individual description of the company lean energy practices. 5. research results 5.1. case study profile the case company is one of the biggest wooden furniture manufacturers in the northern of vietnam (called wl). wl is introducing furniture products from wood including indoor and outdoor furniture, tableware and decoration, vanity and kitchen cabinet, doors, plywood, and film-faced plywood. the yearly turnover in 2020 is more than two million us dollars from six factories and more than 3,000 employees. the company’s mission is to create the best products by constant innovation and optimizing resources in a productive sustainable way. the company has faced the pressure of cost reduction in the context of covid-19 and force from their customers in requirement of energy use reduction for export products. then, the kz project is deployed in wl from mar 2022 to june 2022 to reduce total production cost, improve production efficiency, and improve energy consumption through lean tools implementation. this project is led by the company president and the author of this study participated as a consultant. the thuan hung factory is selected to implement as a model process of the project. there are 33 steps in the production line from five main processes including raw material sorting and insulation, drying and handling, machining, assembly, and finishing. the overall production process of the model line is showed in figure 2. 5.2. energy consumption situation 5.2.1. energy management system to evaluate the status of energy management system in thuan hung, the auditor team used the energy management matrix emm to consider the factors impact to energy management and verifying which factors should to be improved to achieve ee improvement. the emm evaluation results as shown in table 3. currently, investment for high performance machines and equipments are received the highest points from emm evaluation at level 4. there are also many projects are deployed for energy saving, ee improvement in recent years. however, the company does not have a clear and systematic of ee policy. top manager has assigned a full-time energy manager to setup and operate energy management system but did not setup an organization for ee improvement. the measurement system is focused on power system only. 5.2.2. specific energy consumption sec is a commonly used as ee performance indicators is the ratio between amount of energy consumption and production volume during the baseline period, which the amount of energy consumption requirement to complete a product. the purpose of sec is to identify potential of energy improvements. this is an important tool of energy management. sec is used as an energy performance indicator to measure the performance of ee in both literature and practices. besides, sec can be used indirectly to calculate the value of energy efficiency index (eei). the deviation between the actual value of sec and the standard value of sec is a guide to explore the improvement chances when the best available ee practices are established (minh et al., 2021). the unit used for the sec in thuan hung factory is kwh/m3 of product as shown in formula 1. sec energyused product samount = ' (1) the total of energy consumption in the thuan hung factory in 2019 is 1,397.5 toe; in 2020 is 1,224 toe; 2021 is 1068 toe. besides, the fuel consumption from 2018 to 2020 also more than 49,000 litre per year. the average specific energy consumption (sec) in the factory in 2021 is 21.52 kwh/m3. the detailed sec in 2021 as shown in figure 3. 5.2.3. lean implementation for ee improvement results with the aim of evaluating changes in terms of ee improvement, the evaluation criteria for wl project is carried out during the whole time of the project from the beginning to the end. the figure 2: main processes of furniture production line in the kz project phong and minh: integration of lean methodology and energy management in wooden industry international journal of energy economics and policy | vol 12 • issue 5 • 2022 129 table 3. the emm evaluation result level energy policy organization staff motivation measurement, supervision marketing investment 4 energy policy, action plan and regular review, have commitment of top management as part of an environmental strategy energy / environmental management fully integrated into management structure. clear delegation of responsibility for energy use formal and informal channels of communication regularly exploited by energy / environmental manager and staff at all levels comprehensive system sets targets, monitors materials and energy consumption and wastes and emissions, identifies faults, quantifies costs and savings and provides budget tracking marketing the value of material and energy efficiency and the performance of energy / environmental management both within the organisation and outside it positive discrimination in favour of energy / environmental saving schemes with detailed investment appraisal of all new build and plant improvement opportunities 3 formal energy policy, but no activc commitment from top management energy / environmental manager accountable to energy committee, chaired by a member of the management board energy / environmental committee used as main channel together with direct contact with major users monitoring and targeting reports for individual premises based on sub-metering / monitoring, but savings not reported effectively to users programme of staff training, awareness and regular publicity campaigns same pay back criteria as for all other investments. cursory appraisal of new build and plant improvement opportunities 2 unadopted / informal energy / environmental policy set by energy / environmental manager or senior departmental manager energy / environmental manager in post, reporting to ad-hoc committee but line management and authority are unclear contact with major users through adhoc committee chaired by senior departmental manager monitoring and targeting reports based on supply meter / measurement data and invoices. env. / energy staff have ad-hoc involvement in budget setting. some ad hoc staff awareness and training nvestment using short term pay back criteria mostly 1 an unwritten set of guidelines energy / environmental management the part-time responsibility of someone with only limited influence or authority informal contacts between engineer and a few users cost reporting based on invoice data. engineer compiles reports for internal use within technical department informal contacts used to promote energy efficiency and resource conservation only low cost measures taken 0 no explicit policy no energy / environmental manager or any formal delegation of responsibility for env / energy use no contact with users no information system. no accounting for materials and energy consumption and waste no awareness raisingof energy efficiency and resource conservation no investment in increasing environmental performance / energy efficiency in premises source: authors authors attended all meetings of the improvement teams and recorded data carefully. the capability assessment results (total energy consumption, sec, number of kaizen was implemented). from the findings in the kaizen implementation in three months, we can see that there are a lot of opportunities in order to decrease the production cost in general and decrease in energy consumption of the shop floor. in the case of kz project, most of the energy wastages that are related to lean seven wastes such as over-processing, defective or rework, machine waiting or noload running… there are 85 kaizen problems related to ee are identified after three months, 43 kaizen problems were deployed. the detail of week to week kaizen follow up as shown in figure 4. sw, tpm, visualize, and poka-yoke are the most frequency tools of lean applied to decrease wastes of energy consumption in thuan hung. a systematic of job instruction for machine operating and maintenance of the equipment help increase the life-cycle of machine and reduce downtime or stop time. the results showed positive improvements in all of the production lines after the kz projects ended. the staff’s motivation is figure 3: the monthly sec in thuan hung in 2021 phong and minh: integration of lean methodology and energy management in wooden industry international journal of energy economics and policy | vol 12 • issue 5 • 2022130 figure 4: number of kaizen activity of kz project table 4: percentage of energy reductions by applying different lean tools for main equipments equipment quantity waste (problems) lean tool application % energy reduction conveyor 144 no-load running visual, 5s, tpm. 14.9 drill machine 125 long cutting journey sw, pokayoke, tpm 13.7 vacuum machine 49 no-load running sw, 5s, tpm 18.3 drying oven 20 over-heat, over-time drying sw, right-size equipment, tpm 39.1 cutting machine 35 no-load running, long cutting journey sw, pokayoke, tpm 9 cnc machine 12 tmp 2 compress machine 4 defective smed, sw, pokayoke 3.7 sanding machine 37 defect, no-load running smed, sw, pokayoke 25.2 source: the author 6. conclusion in this study, the concept of the contribution of lean implementation in energy-saving for achieving a better performance of production systems was carried out. lean concepts were implemented in the shop floor from the perspective of waste of energy consumption. the energy utilization in the production processes including machinery, conveyors, robots, lights… can be decreased by applied several lean tools. the energy efficiency improvement can be increase and sec can be also reduced (through reduce the energy consumption per part index). this study has highlighted the possibility of lean tools implementation in the enterprises’ shop floor and its impact on energy consumption through a case study. this approach can be further applied and confirmed for vietnam industrial sector to achieve the target of energy-saving and production cost reduction. this result will provide a good guideline about ee improvement via lean tools application. the result of this study also could be useful guideline for managers of manufacturers and enterprises in developing countries to deploy a productivity, sustainable production, and ee programs. although the results of this paper is valuable, this study has some limitations. this study was conducted from a single case of lean increased from level 2 to level 3, organization and energy policy evaluation are improved to level 3; measurement system for production line no.3 is increased to level 4 while line no.1 and no.2 are still keep at level 2. the oee (overall equipment effective) increase from 36% to 59% in the production line no.1, while reducing ng (not good) ratio, lead time, delivery time, and energy consumption (table 4). 5.2.4. sec improvement a part of the reporting to describe the improvement of the current sec value from the previous years. the improvement can be calculated as mentioned in fomula no.2 (nguyen dat minh et al., 2021). improvement � �sec sec sec previousyear present previousyear �100 (2) thus, the average present of sec up to jun 2022 has measured is 18.3 kwh/m3 of wood product. therefore, the sec improvement is 14.9%: improvement � � � 21 52 3 18 3 3 21 5 3 100 14 9 . . / . / % . % kwh m kwh m kwh m � phong and minh: integration of lean methodology and energy management in wooden industry international journal of energy economics and policy | vol 12 • issue 5 • 2022 131 methodology into energy sector from one is limited to generalized to other enterprises. this topic can be further improved by consider and expanse to other sectors. 7. acknowledgement this work was funded by the vietnam electric power university in the scientific research at university level. references achanga, p.c. (2007), development of an impact assessment framework for lean manufacturing within smes. united kingdom: cranfield university. allen, m., antwi-agyei, p., aragon-durand, f., babiker, m., bertoldi, p., bind, m., cartwright, a. (2019), technical summary: global warming of 1.5° c. an ipcc special report on the impacts of global warming of 1.5° c above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. apak, s., üngör tuncer, g., atay, e. (2012), hydrogen economy and innovative six sigma applications for energy efficiency. procedia social and behavioral sciences, 41, 410-417. bertoldi, p., mosconi, r. (2020), do energy efficiency policies save energy? a new approach based on energy policy indicators (in the eu member states). energy policy, 139, 111320. caiado, r., nascimento, d., quelhas, o., tortorella, g., rangel, l. (2018), towards sustainability through green, lean and six sigma integration at service industry: review and framework. technological and economic development of economy, 24(4), 1659-1678. danish energy agency. (2017), vietnam energy outlook report. denmark: danish energy agency. dey, p.k., malesios, c., de, d., chowdhury, s., abdelaziz, f.b. (2019), could lean practices and process innovation enhance supply chain sustainability of small and medium‐sized enterprises? business strategy and the environment, 28(4), 582-598. fercoq, a., lamouri, s., carbone, v., lelièvre, a., lemieux, a.a. (2013), combining lean and green in manufacturing: a model of waste management. ifac proceedings, 46(9), 117-122. gogula, v., wan, h.d., kuriger, g. (2011), impact of lean tools on energy consumption. sistemas and telemática, 9(19), 33-53. hoang, t.h., kien, d.t., minh, n.d. (2021), development of energy efficiency action plan at provincial level of vietnam. international journal of energy economics and policy, 11(6), 60-67. labandeira, x., labeaga, j.m., linares, p., lópez-otero, x. (2020), the impacts of energy efficiency policies: meta-analysis. energy policy, 147, 111790. liker, j. (2004), the 14 principles of the toyota way: an executive summary of the culture behind tps. in: the toyota way. vol. 14. new york: mcgraw hill. p35-41. liker, j. (2006), the toyota way fieldbook: esensi. linares, p., labandeira, x. (2010), energy efficiency: economics and policy. journal of economic surveys, 24(3), 573-592. minh, n.d., kien, d.t. (2021), assessment of the impact of managing large energy-using users on national energy efficiency of vietnam. international journal of energy economics and policy 11(5), 519530. minh, n.d., kien, d.t., hoang, t.h. (2021), energy benchmarking management for beer and beverage industry in vietnam. management, 25(2), 36-58. mkhaimer, l.g., arafeh, m., sakhrieh, a.h. (2017), effective implementation of iso 50001 energy management system: applying lean six sigma approach. international journal of engineering business management, 9, 1-12. ohno, t. (1988), toyota production system: beyond large-scale production. united states: crc press. pascal, d. (2007), lean production simplified. 2nd ed. new york: productivity press inc. pascal, d. (2015), lean production simplified: a plain-language guide to the world’s most powerful production system. united states: crc press. prime minister of vietnam. (2019), decision 280/qd-ttg on approval of the national energy efficiency programme (vneep) for the period of 2019-2030. vietnam: prime minister of vietnam. saini, s., singh, d. (2020), impact of implementing lean practices on firm performance: a study of northern india smes. international journal of lean six sigma, 11(6), 1019-1048. salah, s., rahim, a., carretero, j.a. (2010), the integration of six sigma and lean management. international journal of lean six sigma, 1(3), 249-274. the government of vietnam. (2006), decision 79/2006/qd-tt the vn national energy efficiency program. vietnam: the government of vietnam. thollander, p., karlsson, m., rohdin, p., wollin, j., rosenqvist, j. (2020), energy management using lean. introduction to industrial energy efficiency. united states: academic press. womack, j., jones, d. (2003), lean thinking. new york: free press. womack, j.p., jones, d.t., roos, d. (1990), machine that changed the world. united states: simon and schuster. zhang, s., worrell, e., crijns-graus, w., krol, m., de bruine, m., geng, g., cofala, j. (2016), modeling energy efficiency to improve air quality and health effects of china’s cement industry. applied energy, 184, 574-593. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 4 • 2023634 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(4), 634-640. the energy demand elasticity in relation to gross domestic product in indonesia: sectoral approach suharno suharno*, nurul anwar department of economics and development studies, faculty of economics and business, jenderal soedirman university, indonesia. *email: suharno@unsoed.ac.id received: 15 july 2022 accepted: 28 april 2023 doi: https://doi.org/10.32479/ijeep.13385 abstract this paper aims at estimating the energy demand elasticity in relation to gross domestic product in indonesia based on data from 1995 to 2018. the sectors examined are industry, trading, transportation, and housing sectors. the method of analysis is the autoregressive distributed lag (ardl). an interesting estimation result here is that the elasticity of the industry sector is negative both short and long term. the other three sectors show positive elasticity. this paper contributes to the discussion of the energy demand ardl model to be used as a reference in developing countries. keywords: the elasticity of energy use, sectoral, economic growth, autoregressive distributed lag model jel classifications: c23, o11, o13 1. introduction community welfare can be achieved through economic development. in economic development, energy is needed in many activities to drive the economy in many sectors. if there is not enough energy, it will be difficult to move the wheels of the economy. the more developed a country, the higher its energy needs. energy demand reflects the activity in each sector, logically without activity there is no use of energy, because it is assumed that all sectors act rationally and do not want to pay without a clear purpose. each activity must produce economic benefits to economic growth (gross domestic product gdp), therefore it is necessary to study how much elasticity the use of energy has on economic growth in each sector. this is to assist the government in making policies related to the use of increasingly scarce fuels. for all developed and developing countries, energy is an important factor of production such as capital and labor. in addition, energy demand is one of the basic indicators of development and economic growth. as stated by halıcıoglu (2008), he stated that economic development and output can be determined together because economic development is closely related to energy demand and that higher economic development requires more energy demand. this is supported by stern (2011), and pirlogea and cicea (2012) who are both conducting research to determine the key factors that have an impact on economic growth, using energy use variables. in the energy sector, apart from the potential for renewable energy, indonesia has a large capacity, the share of fossil fuels currently around 96% of total primary energy demand (nec, 2015). in countries with growing populations, such as indonesia, sustainable development requires them to increase not only national income, but also per capita income. the greater population growth will reduce the income per capita, if not balanced economic growth, because they use more natural capital, such as fossil fuels (unu-ihdp and unep, 2012). the deployment of renewable energy in indonesia still faces some obstacles, such as lack of fiscal and financial incentives for investors, and limited access to advanced technologies (aperc, 2007). for example, the development of indonesia’s this journal is licensed under a creative commons attribution 4.0 international license suharno and anwar: the energy demand elasticity in relation to gross domestic product in indonesia: sectoral approach international journal of energy economics and policy | vol 13 • issue 4 • 2023 635 vast geothermal potential is constrained by a lack of technological capability and financial support, and by an electricity pricing structure that does not provide enough incentives for its distribution (tanoto and wijaya, 2011). 2. literature review in fact, it has long been known the importance of studies on the elasticity of energy use to gdp not only in indonesia, but in many countries. namely studies that study the percentage change in energy use associated with a 1% change in gross domestic product (gdp). in a preliminary study, mentioning the separameters in slightly differentterms, eventhough the meaning is the same. for example, adams and miovic (1968) refer to this parameter as “energy elasticity,” as is the case with brookers (1972) and ang (1991) they refer to this parameter as “energy coefficient.” then there are those who call it “income elasticity” from energy use and energy intensity and income growth (van benthem, 2015). furthermore, using cross-sectional data, csereklyei et al. (2016) recently reported that the average long-term energy-gdp elasticity is around 0.7, and this has been quite stable over time. early economic growth theories (neoclassical and endogenous growth models) only analyzed the effect of primary production factors such as capital and labor on economic growth. while energy is only considered as a material used in the production process, and is often ignored, or only considered as an intermediate input. as stern (1998) emphasizes the basic model of economic growth which is based on the neoclassical model proposed by solow (1974), which does not include energy as a factor of production at all. according to this theory, the only cause of economic growth is technological progress. but technological progress is assumed to occur exogenously. then, endogenous growth models seek to incorporate technological advances in growth models as a result of decisions taken by companies and individuals (stern, 1998). literature that studies the causal relationship between energy demand and economic growth has advanced. the first relevant study that links between energy use and economic growth began around the late 1970s. in their pioneering work, kraft and kraft (1978) linked energy demand to economic growth (gross domestic product gdp), using annual us data from 1947 to 1974. they used sims causality test procedures to infer causal relationships, and found that an increase in gnp leads to an increase in energy demand. in another study, erol and yu (1987) applied the sims and granger causality procedure to examine the causal relationship between energy demand and real gnp in japan, germany, italy, canada, france, and england. the results show that there was a two-way causal relationship between two variables in japan. in germany and italy, an increase in gnp led to an increase in energy demand. an increase in energy demand caused an increase in gnp in canada, but there was no causal relationship between the two in france and the united kingdom. long-term energy demand forecasts, usually based on the functional relationship between energy demand and economic activity (represented by gdp), therefore income elasticity, the percentage change in energy demand related to the percentage change in gdp, plays a key role in the forecast. previous studies for developed countries found elasticities of >1 (nordhaus, 1977). in the literature on the relationship between energy demand and economic growth, it relies on the hypothesis that growth in energy demand plays an important role in economic growth both directly and as a complement to capital and labor. in this case apergis and payne (2012) relies on three hypotheses, namely the conservative hypothesis, the neutrality hypothesis, and the feedback hypothesis. the conservation hypothesis states that energy demand is determined by economic growth. the feedback hypothesis states it depends on the interdependent relationship between energy demand and economic growth. the neutrality hypothesis rests on the assumption that energy demand has a relatively small role in the process of economic growth. the next literature review is that written by tugcu et al. (2012) which classifies literature according to the type of energy consumed. the first focuses on studies that relate to aggregate energy demand and economic growth. the second group analyzes the relationship between renewable energy demand and economic growth. the last one, a study of the effects of both renewable and non-renewable energy demand with economic growth (tugcu et al., 2012: 1944; purnomo et al., 2023). our study aims to add information related to the analysis of the relationship between energy demand and economic growth, especially studying the elasticity of energy demand on economic growth. the study followed the elasticity of energy demand to economic growth by sector. demand of energy that is not elastic to economic growth may deplete capital, reducing the capacity for economic development (mumford, 2016). in recent years stakeholders have paid attention that resources, especially those that are not renewable, should function as drivers of economic growth and reduce poverty (aubynn, 2009). whereas mundial (2011) examine the policies that support this. this includes policies relating to the efficiency of resource extraction, the tax and royalty system, as well as those related to productive investment. 3. methodology and data energy usage data is sectoral data which includes the industrial sector; transportation; commercial; the household; and economic growth data, from the period 1995-2018. the data measurement was based on constant prices in 2010, in us dollars. variables examined include gdp as a proxy for economic growth; the use of industrial energy sector (ind); the use of the energy sector of transportation (tr); the use of commercial energy sector (co); and the use of the household energy sector (re). to avoid heteroschedasticity all data is transformed into logarithms. the data in this study is only 24 years, meaning that it includes small data, and has met the requirements of the relationship test both short term and long term, so that according to the provisions suharno and anwar: the energy demand elasticity in relation to gross domestic product in indonesia: sectoral approach international journal of energy economics and policy | vol 13 • issue 4 • 2023636 of pesaran et al. (2001) the auto-regressive distributed lag (ardl) model can be used. according to nkoro and uko (2016) the ardl model has several advantages such as, “variables stands as a single equation, endogeneity is less problem because it is free of residual correlation. the main advantage of ardl is the ability to identify the cointegrating vector where there are multiple cointegrating vectors. according to pesaran et al. (2001), when there is a single long run relationship, ardl can distinguish between dependent and explanatory variables. another advantage of the ardl model is the bound test approach that can be applied regardless of whether the understanding of the underlying regressors are integrated of order one (1) or order zero (0). usually ardl models produce unbiased estimates of long run models and valid t-statistics. the ardl model related to the variables used is as follows: e e e e eind tr co re� � � �� � � (1) e = energy demand y: total gross domestic product ind: energy from industrial sector tr: transportation sector co: commercial sector re: residential sector differentiang equation (1) by time (t) dividing by e and denoting dx/dt by dot over the variables, then we have     e e e e e e e e e e e e e e e e e e ind ind iind tr tr tr co co co re re re � � � � (2) deviding by real growth rate of gdp ( )y y and using ee to denote the type equation here. energy-gdp elasticity. our estimates: y s s s se α β ε= + + (3) ln lnyeind ind� � �� � �0 (4a) ln lnyetr tr� � �� � �0 (4b) ln lnyeco co� � �� � �0 (4c) ln lny ere re� � �� � �0 (4d) � �e y ys s s t t n t t� � � �� � ��� � � �0 1 1 0 1 1 (5) s = sectoral n = lag length δ = the first difference operator h0: no long run cointegration relationship between the variables tested h1: the exixtence of long run cointegration relationship between the variables tested. therefore the model including multiple equation to analyze the elasticity of four variables to gdp asfollow: �e yind t t� �� �� �� �0 1 1 1 (6a) �e � � �� � �� �0 1 1 1tr t ty (6b) �e=� � 0 1 1 1 � �� � �co t ty (6c) �e � � �� � �� �0 1 1 1re t ty (6d) following equation (6) the error correction model (ecm) will be formulated to estimate the short run coefficient, consequently the ecm must be providing in the following equations: � � � � � e y e es t n t t n ind t t n tr t t n � � � � � � � � � � � � � � � � � � � � 0 0 1 1 0 2 1 0 3 1 0 4 ee eco t t n re t t� � �� ��1 0 5 1 � �� (7) this ardl test has many advantages and first developed by pesaran et al. (1999), and then extended by pesaran et al. (2001) and has extensively been used in recent empirical modeling. the advantages of this test i.e: this test permit to test for co-integration even when all variables are 1(1) or (0) or mix of two; unlike the previous test by engel and granger (1987) and johansen (1991) multivariate co-integration approach, the ardl bound cointegration test is not sensitive to the value of nuisance parameters in finite sample, thereby making it small sample properties superior; this test also unbiased long run estimates and valid in t-statistical even when some of the variables are endogenous. 4. empirical results 4.1. indonesian economic growth based on data from bps (2018), indonesia’s economic growth over the past 15 years has fluctuated. in 2005 economic growth reached 5.69%. then in 2006 the growth decreased to 5.5%, but in 2007 rose again to 6.35%. in 2008 it decreased again to 6.01%, even in 2009 economic growth decreased again to 4.63%. the decline in growth was mainly due to external factors, namely the impact of the global financial crisis, which not only affected indonesia, but also other countries. during the year, the central bank of the united states (the fed) raised interest rates which caused global commodity prices to rise. however, at that time indonesia was able to maintain its economic growth even though it was slow, and indonesia’s economic growth was among the three best in the world. in 2010 the indonesian economy grew again by 6.22%, even in 2011 the indonesian economy grew by 6.49%, and in 2012 it grew by 6.23%, but the following 2 years declined again to 5.56% in 2013 and 5.01% in 2014. during the new government under the leadership of president joko widodo started at the end of 2014, more emphasis on investment in infrastructure, and an increase in efficiency in different sectors, but the economy had not risen. in 2015 the suharno and anwar: the energy demand elasticity in relation to gross domestic product in indonesia: sectoral approach international journal of energy economics and policy | vol 13 • issue 4 • 2023 637 indonesian economy weakened again and grew by only 4.88%. the budget deficit got bigger because of an increase in the number of imports and a decline in exports. only in 2016, the impact of infrastructure development began to be seen, marked by economic growth rising to 5.03%, followed by 2017 with economic growth of 5.17%. to overcome the ups and downs of economic growth, the government made various efforts to boost economic growth. one thing that emphasized was the equitable distribution of welfare, by expanding the reach for growth in eastern indonesia, the border region, and other areas that are still lagging. other efforts undertaken were to strengthen ultra-micro businesses, micro, small and medium enterprises and cooperatives. the government also made efforts to reduce inequality between regions and reduce disparities between income groups. sectorally, the government encourages sectors that have added value and can create greater employment opportunities. in this connection the investment climate is developed, improving the licensing system so as to create efficiency. an online single submission (oss) was made which made it easy to arrange investment permits. the implementation of the one stop integrated service (osts) to reduce the bureaucratic chain making it easier for businessman. 4.2. indonesia’s energy conditions previously, indonesia was an oil producing country that played a significant role in the world, resulting in a surplus of oil products. but now the situation is different, many studies have proven that in the future indonesia has the potential to become an oil importer country, if the pattern of oil demand does not change. the pattern of world energy demand, as well as in indonesia at this time is still dominated by fossil energy in the form of oil, gas and coal. this is a threatening challenge in the energy sector. at present the condition of indonesia’s petroleum has gone up to a threshold (bppt, 2018). since 1991 indonesian oil production has continued to decline. this was caused by the reduced productivity of oil wells owned. in 2018, from the production target of 800 thousand barrels per day, it would only reach around 773 thousand barrels. this amount was far below the production in 2017 which reached 949 thousand barrels per day (bppt, 2018). by contrast, in the areas of fuel demand, while oil production continues to decline, fuel demand has increased in line with population growth and population of motor vehicles, both motorcycles and cars. car sales in 2017 reached 1079 million units, or there was an increase of almost 150% in 10 years, or an average increase of 15% per year. in the same period, motorcycle sales rose 33%, or 3.3% per year. beyond that, pt kai consumes 200 million liters of fuel per year on average annually. to overcome this, there are options that can be done, namely reducing fuel demand, or with a mixture of ethanol (premium) or biodiesel (diesel). the first choice obviously does not make sense, because the increase in population will automatically increase energy demand, especially fuel oil. until now household demand expenditure is still the largest contributor to gdp. the biggest expenditure occurred in 2016 which reached 56.50% of gdp. based on table 1 this study was conducted from 1985 to 2018 or 24 years of observation. the average gdp value of the indonesian economy was 154.17 (billion usd), with a maximum gdp value of 257.70 (billion usd) and a minimum gdp value of 96.61 (billion usd). 4.3. the unit root test this test is to check the mean and variance of the variables change over time or not, and the time series data are stationary or not stationary. here we check the unit root based on null hypothesis of non stationary against the alternative hypothesis of stationary data. the result of augmented dickey fuller (adf) test and phillip perron (pp) test of unit root are shown in tables 2 and 3 below. from table 2, the unit root test reveals that in levels all variables are not stationary, and at their first difference both test show that all variables are stationary at 5% and 10% significant level, except residential sector (re). the ardl estimates are dynamically and structurally stable, consistent, and reliable. based on figures 1 and 2 through the cumulative sum of the recursive residual (cusum) and the cumulative sum of the squares of recursive residuals (cusumsq) test, the graphical result that residuals were within the critical bounds at 5% level of significant. 4.4. bound co-integration test this test is approach to co-integration test the existence of long run relationship between the variables. from the lag length can help us in capturing the dynamic relationship to select the best table 1: descriptive statistic measure y ind co tr re ot mean 2,102,397 2.81e+08 27,860,725 2.19e+08 1.38e+08 29,924,770 median 1,905,727 2.83e+08 24,952,581 1.79e+08 1.45e+08 29,818,538 maximum 3,514,281 3.75e+08 43,153,003 3.91e+08 1.55e+08 38,791,254 minimum 1,317,588 1.90e+08 14,182,727 1.06e+08 96,092,729 16,100,231 sd 707,850.4 51,943,240 9,859,460 92,785,729 17,023,503 5,434,639 skewness 0.590218 0.101434 0.289657 0.490593 −1.285150 −0.682801 kurtosis 2.005719 2.507431 1.554796 1.721808 3.412552 3.404464 jarque-bera 2.382023 0.283779 2.424218 2.596500 6.776638 2.028458 probability 0.303914 0.867717 0.297569 0.273009 0.033765 0.362682 sum 50,457,527 6.73e+09 6.69e+08 5.26e+09 3.32e+09 7.18e+08 sum square deviation 1.15e+13 6.21e+16 2.24e+15 1.98e+17 6.67e+15 6.79e+14 observations 24 24 24 24 24 24 sd: standard deviation suharno and anwar: the energy demand elasticity in relation to gross domestic product in indonesia: sectoral approach international journal of energy economics and policy | vol 13 • issue 4 • 2023638 table 2: phillips-perron unit root test measure t-statistic at level log (y) log (ind) log (tr) log (co) log (re) with constant t-statistic 1.1979 −2.0471 −0.2355 −1.0914 −4.0830*** with constant and trend t-statistic −2.5697 −2.3239 −2.0943 −2.2473 −2.3626 without constant and trend t-statistic 4.4171 1.5994 4.3571 4.0482 1.8731 measure t-statistic at first difference d (log[y]) d (log[ind]) d (log[tr]) d (log[co]) d (log[re]) with constant t-statistic −3.7691** −4.5357*** −3.7427** −5.1788*** −2.5139 with constant and trend t-statistic −4.3955** −5.5083*** −3.6585** −5.0825*** −3.1503 without constant and trend t-statistic −2.4786** −4.2225*** −2.4695** −3.5478*** −2.2716** source: data processing result, 2022. * ,** and ***significant at 10%, 5%, and 1% respectively table 3: unit result of unit root test (augmented dickey fuller) measure t-statistic at level log (y) log (ind) log (tr) log (co) log (re) with constant t-statistic −1.0687 −2.1143 −0.2355 −1.0725 −4.3741*** with constant and trend t-statistic −1.0291 −2.8129 −2.6644 −2.1824 −2.7240 without constant and trend t-statistic 17.6061 0.9789 4.3571 3.7973 1.0272 measure t-statistic at first difference d (log[y]) d (log[ind]) d (log[tr]) d (log[co]) d (log[re]) with constant t-statistic −16.4894*** −4.1777*** −3.7311** −5.1788*** −2.6305 with constant and trend t-statistic −3.2687 −3.8638** −3.6479** −5.0825*** −3.1503 without constant and trend t-statistic −1.8374* −4.0375*** −2.5222** −2.2508** −2.4225** source: data processing result, 2022. *,** and ***significant at 10%, 5%, and 1% respectively this result differ from the similar studi in australia, burke and csereklyei, 2016, using time series data 1960-2010 from 132 countries resulted that residential energy use is very inelastic to gdp. residential use of energy is more tighly linked to gdp, as is emergy use by the transportation, industrial, and service sectors. other result shown by petrice 1986, used data from 1950 to 1980 in 18 countries resulted that on average the elasticity was eual to or >1 before cricis event (1973). as far as after crisis periods the average elasticity is 0.74 (23 examples). however, seven examples (out of 23 examples) correspond to an elasticity >1.1. but in five instances (out of seven) the elasticity drop to 0.6. in 15 cases (out of 23) the elasticity is <0.75, but in eight (out of 15) show an energy-growth correlation coefficient which invalidates the calculation. there remain therefore seven cases at most which are meaningful from a purely statistical point of view and their average elasticity is 0.56. ardl model to estimate. based on table 4, the result shows that it is evident that for all the normalized equation, the estimated f-statistic of 35.49763 is above the upper critical bound at 5% significant level. thus we fail to accept the null hypothesis, meaning that we can treat the developed models. meaning the there is existence of a long run equilibrium relationship between energy use and gdp elasticity in indonesia during 1995 to 2018. 4.5. test of elasticity here we want to test the 1% change in each of energy use of four factors associated with a 1% change in gdp. the previous study on this topic has been conducted by (e.g. nakicenovic et al., 1998; judson et al., 1999; smil, 2000; medlock and soligo, 2001; lascaroux, 2011; arsenau, 2012), that resulted the contribution of end-use sector to the aggregate energy-gdp elasticity are less well understood. our estimates are potentially useful for energy planning and forecasting in indonesia. our study involves studying final energy use by four sectors that have been mentioned before. based on table 5 the long run coefficients are statistically significant at 1% significant level. the result show that all variable are positively elastic to change in gdp, except industrial sector that has negative elasticity. these indicates that a 1% change in energy use of primary solid biofuels of transportation sector, commercial sector, and residential sector have 0.224706%; 0.771167%; 0.626047% respectively increased changing in gdp. compared to all variables, the commercial sector contributed the biggest positive change in gdp. in contrast, for every 1% change in energy use of industrial sector, decreased 0.341321% in gdp. table 4: bounds test results test statistic value significant (%) i (0) i (1) f-statistic 35.49763 10 2.2 3.09 k 4 5 2.56 3.49 2.5 2.88 3.87 1 3.29 4.37 table 5: long run model result variable coefficient se t-statistic probability log (ind) −0.341321 0.149428 −2.284179 0.0624 log (tr) 0.224705 0.149504 1.503009 0.1835 log (co) 0.771167 0.163318 4.721876 0.0033 log (re) 0.626047 0.218593 2.863983 0.0287 c −8.013924 4.118063 −1.946042 0.0996 se: standard error suharno and anwar: the energy demand elasticity in relation to gross domestic product in indonesia: sectoral approach international journal of energy economics and policy | vol 13 • issue 4 • 2023 639 especially related to energy use. as mention above that the use of all resources must be productive and efficient. 5. conclusion this study investigates the long run interrelationship between energy consumption in four sectors; industrial, transportation, commercial, and residential sectors toward economic growth in indonesia periods of 1995-2018. we used the ardl model bound approach to test the existence of long run relationship between economic growth and four sectors mentioned above. while to test the elasticity of energy consumption of four sectors and economic growth used the coefficient of log equation 4 and table 5. the empirical results confirm the existence of long run relationship between energy consumption of four sectors and economic growth. based on the ardl model, the long run elasticities are statistically significant at 1% significant level. the energy consumption of three sectors, transportation, commercial, and residential have positively elasticity toward economic growth, except industrial sector that show negative elasticity. based on the result government must pay more attention especially to industrial sector due to the negative elasticity toward economic growth. this sector must support economic growth with higher productivity and efficiency. there must be appropriate and accurate policy with learn and compare to other countries that successfully applied the similar policy. 6. acknowledgment our grateful for the universitas jenderal soedirman indonesia, which has provided funding through further development research under contract number 27.59/un23.37/pt.01.03/ii/2023. our sincere appreciation goes to the data provider, the indonesian central statistics agency, and thanks to all anonymous reviewers for their critical input to this article. table 6: the result of short run model variable coefficient se t-statistic probability dlog (y[−1]) −0.103104 0.053880 −1.913588 0.1042 dlog (ind) −0.007231 0.020451 −0.353548 0.7358 dlog (ind[−1]) 0.118564 0.020549 5.769739 0.0012 dlog (ind[−2]) 0.127675 0.019932 6.405643 0.0007 dlog (co) 0.344941 0.035907 9.606519 0.0001 dlog (co[−1]) −0.036884 0.038178 −0.966114 0.3713 dlog (co[−2]) −0.178943 0.034901 −5.127120 0.0022 dlog (re) −0.216543 0.080237 −2.698806 0.0356 dlog (re[−1]) −0.314808 0.078066 −4.032599 0.0069 cointeq(−1)* −0.514833 0.026054 −19.76041 0.0000 r2 0.974601 mean dependent var 0.039888 adjusted r2 0.953820 sd dependent var 0.043460 se of regression 0.009339 akaike info criterion −6.203404 sum squared resid 0.000959 schwarz criterion −5.706012 log likelihood 75.13574 hannan-quinn criterion −6.095457 durbin–watson statistic 2.810180 se: standard error, sd: standard deviation for the empirical short run, we can table 6. the result shows that like in long run energy use in industrial sector with negative elasticity. this must be a special attention to the indonesian government to role of industrial sector in economic development, figure 1: cumulative sum (cusum) of recursive residual figure 2: cumulative sum square (cusumsq) of recursive residual suharno and anwar: the energy demand elasticity in relation to gross domestic product in indonesia: sectoral approach international journal of energy economics and policy | vol 13 • issue 4 • 2023640 references adams, f.g., miovic, p. (1968), on relative fuel efficiency and the output elasticity of energy consumption western europe. journal of industrial economics, 17(1), 41-56. ang, b.w. (1991), a statistical analysis of energy coefficients. energy economics, 13(2), 93-110. aperc. (2007), a quest for energy security in the 21st century. tokyo: asia pacific energy research centre. apergis, n., payne, j.e. (2012), renewable and non-renewable energy consumption-growth nexus: evidence from a panel error correction model. energy economics, 34, 733-738. arseneau, d.m., (2012), explaining the energy consumption portfolio in a cross-section of countries: are the brics different? law bus rev am, 18(4), 553–584. aubynn, a. (2009), sustainable solution or a marriage of inconvenience? the coexistence of large scale mining and artisanal and small scale mining on the abosso goldfields concession in western ghana. resources policy, 34(1), 64-70. bppt. (2018), available from: https://www.bppt.go.id/teknologiinformasi-energi-dan-material/3296-bppt-indonesia-darurat-energi bps. (2018), statistik indonesia. indonesia: badan pusat statistik indonesia. brookers, l.g. (1972), more on the output elasticity of energy consumption. journal of industrial economics, 21(1), 8-92. burke, p.j., csereklyei, z. (2016), understanding the energy-gdp elasticity: a sectoral approach. energy economics, 58, 199-210. csereklyei, z., rubio-varas, m.d.m., stern, d.i. (2016), energy and economic growth: the stylized facts. the energy journal, 37(2), 223-255. engel, r.f., granger, c.w.j. (1987), co-integration and error correction: representation, estimation, and testing. econometrica, 55(2), 251-276. erol, u., yu, e.s.h. (1978), on the causal relationship between energy and income for industrialzed countries. journal of energy and development, 13(1), 11-122. halıcıoglu, f. (2008), a econometric study of co2 emissions, energy consumption, income and foreign trade in turkey. mpra paper no:11457. johansen, s. (1991), estimation and hypothesis testing of cointegrated vectors in gaussian vector autoregressive model. econometrica, 59(6), 1551-1580. judson, r.a., schmalensee, r., stoker, t.m., (1999), economic development and the structure of the demand for commercial energy. energy j 20 (2), 29–57. kraft, j., kraft, a. (1978), on the relationship between energy and gdp. journal of development, 3, 410-430. lescaroux, f., (2011), dynamics of final sectoral energy demand and aggregate energy intensity. energy policy 39, 66–82. medlock iii, k.b., soligo, r., (2001), economic development and enduse energy demand. energy j 22(2), 77–105. mumford, k.j. (2016), prosperity, sustainability and the measurement of wealth. asia and the pacific policy studies, 3(2), 226-234. mundial, b. (2011), the changing wealth of nations: measuring sustainable development in the new millennium. washington: the international bank for reconstruction and development/the world bank. nakićenović, n., grübler, a., mcdonald, a., (1998), global energy perspectives. cambridge university press, cambridge, uk. nec (national energy council). (2015), executive reference data: national energy management. jakarta: nec. nkoro, e., uko, a.k. (2016), autoregressive distributed lag (ardl) cointegration technique: application and interpretation. journal of statistical and econometric methods, 5(4), 63-91. nordhaus, w.d., editor. (1977), the demand for energy: an international perspective. amsterdam: north holland publisher. pesaran, m.h., shin, y., smith, r. (2001), bound testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. pesaran, m.h., shin, y., smith, r.p. (1999), pooled mean group estimation of dynamic heterogeneous panels. journal of the american statistical association, 94(446), 621-634. petrice, r. (1986), the energy demand in relation to gross domectic product. a relevant indicator? journal of energy economic, 8, 29-38. pirlogea, c., cicea, c. (2012), econometric perspective of the energy consumption and economic growth relation in european. union renewable and sustainable energy reviews, 16(8), 5718-5726. purnomo, s. d., wani, n., suharno, s., arintoko, a., sambodo, h., badriah, l. s. (2023), the effect of energy consumption and renewable energy on economic growth in indonesia. international journal of energy economics and policy, 13(1), 22. smil, v., (2000), energy in the twentieth century: resources, conversions, costs, uses, and consequences. annu rev energy environ 25, 21–51. solow, r.m. (1974), intergenerational equity and exhaustible resources. review of economic studies, 41, 29-46. stern, d. (1998), a multivariate cointegration analysis of the role of energy in the u.s. macroeconomiy. working paper in ecological economic number 9803. stern, d.i. (2011), the role of energy in economic growth. ecological economics reviews, 1219(1), 26-51. tanoto, y., wijaya, m.e. (2011), economic and environmental emissions analysis in indonesian electricity expansion planning: low-rank coal and geothermal energy utilization scenarios. in: 2011 ieee conference on clean energy and technology (cet). united states: ieee. p177-181. tugcu, c.t., ozturk, i., aslan, a. (2012), renewable and non-renewable energy consumption and economic growth relationship revisited: evidence from g7 countries. energy economics, 34, 1942-1950. unu-ihdp, unep (united nations university-international human dimensions programe, and united nations environment programme). (2012), inclusive wealth report 2012: measuring progress towards sustainability. cambridge: cambridge university press. van benthem, a. (2015), energy leapfrogging. journal of the association of environmental and resource economist, 2(1), 93-132. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(5), 275-280. international journal of energy economics and policy | vol 11 • issue 5 • 2021 275 a model suggestion for determining the values of firms the energy sector: an application in bist electricity index ayten turan kurtaran1*, burhan gunay2, ahmet kurtaran3, 1faculty of health sciences, karadeniz technical university, turkey, 2şereflikoçhisar berat cömertoğlu vocational school, ankara yıldırım beyazıt university, turkey, 3faculty of economics and administrative sciences, karadeniz technical university, turkey. *email: kurtaran@ktu.edu.tr received: 08 february 2021 accepted: 29 may 2021 doi: https://doi.org/10.32479/ijeep.11520 abstract investors in financial markets have recently sought rational investment decisions with advanced technology and information obtained from various sources. therefore, investors need to accurately determine the value of the firm. the value of companies in the energy sector contains different dynamics than companies in other sectors. the aim of this study is to develop models that best represent the values of companies in the energy sector and make them available to shareholders. for this purpose, ols regression and panel data analysis were used in the study. the data of the models to be tested in the study were obtained from the data of 11 companies traded in the borsa istanbul (bist) electricity index between 2009 and 2018. in the analysis of the study, 3 models, namely market to book value, standardized economic value added and standardized market value added, were created to represent the company value, and the model that best represents the company value for the shareholder was presented. keywords: panel data analysis, economic value added, market value, market value added, energy sector jel classifications: g20, g32, m41, q43 1. introduction correct determination of the market values of the companies in the energy sector is very important for the sustainability of these companies. while the aim of companies was only profit maximization between the years 1930 and 1960, today the main purpose of companies is to maximize the value of the company. it is also a very complex issue for shareholders to determine what the value of the company is and to measure it realistically. because the value of a company will vary according to the situation of the company, the position of the companies against its competitors, the people who will make the valuation of the company, the purpose of the valuation and what methods will be used in the valuation. therefore, there are different factors that affect the value of companies in the energy sector. for example, lucas and mendes-da-silva (2018) analyzed the effect of climate change on firm value and found that temperature and precipitation affect firm value in the energy sector. shareholders expect a higher return than the risk they bear when investing in a company. each strategic decision made by the company management in response to these demands of the shareholders should be aimed at increasing the value of the company (topak, 2010. p. 14). when investors invest their savings in a company, their most important goal is to get the highest return on their investments in line with the risk they bear. this can be achieved by managing the company value effectively and by maximizing the company value for shareholders as a result of this effective management. in addition to the problem of how to determine the value of the company in a healthy and realistic way, it is also important to use the company value as a tool for investors to make better decisions (demirkol, 2006. p. 13). when this issue is handled in terms of the energy sector, different dynamics emerge from other sectors. many performance criteria have been developed to determine the value of any company. with the help of these performance this journal is licensed under a creative commons attribution 4.0 international license kurtaran, et al.: a model suggestion for determining the values of firms the energy sector: an application in bist electricity index international journal of energy economics and policy | vol 11 • issue 5 • 2021276 criteria, investors want to make their investments at the optimal level by determining the real company value. likewise, company executives are looking for the answer to the question of what the value of their company contributes to the shareholders and stakeholders associated with the company. at this point, the performance criteria developed can be very useful to those who are interested in the value of the companies. when the literature is examined, it is seen that although there are performance criteria that are traditionally called and need accounting data, in recent years, value-based performance criteria have also been developed with value-oriented management approach. in recent years, a value-based management approach has emerged, which argues that companies are elements that create value and that these factors directly contribute to economic profit. in the infrastructure of the value-based management approach, it is stated that all strategies of companies should be about creating shareholder value. this situation has brought along the necessity of determining the value of the intangible assets of the companies, which only create value for the company, and to investigate the contribution of these assets to the company and shareholder value. with the establishment of the mentioned value-based management approach in financial markets, value-based criteria have started to be used in company valuation. the issue of determining company value is not a new phenomenon. various criteria have been used to determine the value of the company for more than a century. ampuero, goranson and scott have historically described the approaches used in company valuation and the process of using valuation criteria as in table 1. in this study, it is aimed to create various econometric models from company valuation methods for shareholders and related parties, to present a model that best explains the value of companies in the energy sector and to gain a new perspective to the literature. for this reason, three econometric models have been developed with a total of 10 variables consisting of value-based and traditional performance criteria. the data of the models to be tested in the study were obtained from 11 companies traded in the bist electricity index. the 10-year period including the years 2009-2018 has been chosen as the analysis period. the data of the companies in the relevant years were obtained from the public disclosure platform (kap), finnet share export and is investment web database. in the application part of the study, ordinary least squares regression and panel data analysis method was used and the hypotheses of the models were tested. stata 16.0 and e-views 9.0 programs were used for panel data analysis in the econometric model tests used in the study. 2. literature review measuring company value is an issue that gains importance day by day. many academicians and consultancy companies have carried out various studies on the realistic determination of the company value. some of the studies in the literature are included in this section. considering the studies conducted to determine the values of the companies in the energy sector; perez-gonzalez and yun (2013), and auffhaummer and mansur erin (2014) investigated impacts of the climate on the value of the firm in the electric sector and found that firm values were affected by climate changes. similarly, as mentioned before, lucas and mendes-da-silva (2018) found that temperature and rainfall affect the value of companies in the energy sector. looking at the subject from a financial perspective; bayraktaroğlu (2009), using the data of 96 companies in the bist manufacturing industry between 1998 and 2007, researched which criteria can best explain stock returns. as a result of the study using the logistic regression method, a very low relationship was found between stock returns and financial performance criteria. sharma and kumar (2012) conducted a panel data analysis to test that the eva is superior to traditional accounting-based performance measures in explaining the change in mva in their studies, which they carried out using the data of manufacturing companies in india between 2000 and 2009. as a result of his work; they could not find a significant difference between eva and accounting-based performance measures. khan et al. (2012), using the data of 60 non-financial companies registered on the pakistan karachi stock exchange between 2004 and 2010, the relationship between stock returns and financial metrics were investigated. as a result of the study, a positive relationship was found with cash flow from operations, while a negative relationship was found with eva in explaining stock returns. alsaboa (2017) investigated the relationship between the created shareholder value and the value-based measure, eva, and the traditional accounting-based roa, using multiple regression analyzes. as a result of his study, he found a significant positive and very strong relationship between the created shareholder value and both criteria. kurmi and rakshit (2017) investigated whether value-based or accounting-based criteria are better in explaining changes in market value. they carried out their studies by using the data of 50 companies registered on the indian stock exchange between april 1, 2000 and march 31, 2016. as a result of their studies, they revealed that the eva is a superior criterion compared to traditional accounting-based criteria. gounder and venkateshwarlu (2017) investigated the criteria that best explain shareholder value by using the data of public and table 1: the process of using company valuation method period methods used 1920s *du pont model *roi (return on investment) 1970s * eps (earnings per share) * p/e (price-to-earnings ratio) 1980s *m/b (market-to-book ratio) *roe (return on equity) *rocf (return on cash flow) *cash flow 1990s *eva (economic value added) * ebitda (earnings before interests, taxes, depreciation and amortization) *mva (market value added) *cfroi (cash flow return on investment) *total shareholder return source: gürbüz & ergincan, 2008: 88 kurtaran, et al.: a model suggestion for determining the values of firms the energy sector: an application in bist electricity index international journal of energy economics and policy | vol 11 • issue 5 • 2021 277 private banks in india between 2001 and 2015. in their studies, mva dependent variable, traditional roe based on value-based eva and accounting, eps and tv (dividend yield) were taken as independent variables. as a result of their studies, while eva explained the change in mva in public banks, “traditional dy based on accounting” explained the change in mva in private banks. behere (2019) econometrically compared the relationship between eva and traditional accounting-based benchmarks and stock market values, using data from 69 large-capital companies on the bombay stock exchange. as a result of his study, they found a relationship with r2 42% between eva and stock market values. traditional measures have been insufficient to explain the market value. the most successful of the traditional metrics was the fcfe method with r2 18% correlation value. 3. analysis 3.1. data and methods in the study, three models were created by using the 2009-2018 data of the companies in the bist electricity index, using ols regression and panel data analysis methods. m/b, seva, and smva values of companies are dependent, mvns, pe, pcf, dy, tobinq, eps, mvnsg criteria were used as independent variables in the models. in the study, the relevant variables were created using the data of 11 companies and converted into a suitable format for analysis. since there are both time series (t = 10 years) and cross-sectional series (n = 11 companies) in the generated data, the study data are suitable for creating econometric models. the 10-year period including the years 2009-2018 has been chosen as the model for which the analysis period was created is planned to be tested during the after the global crisis period. the data of the companies in the relevant years were obtained from the public disclosure platform (kap), finnet share export, and is investment web database. within the scope of the study, the models created as model a, model b, and model c representing the value of the company are as follows. model a: mbratioit = β0 + β1peit + β2pcfit + β3epsit + β4mvnsit + β6dyit + β7tobinqit +β8mvnsgi+………+μit1 model b: sevait = β0 + β1peit + β2pcfit + β3epsit + β4mvnsit + β6dyit + β7tobinqit +β8mvnsgi+………+μit1 model c: smvait = β0 + β1peit + β2pcfit + β3epsit + β4mvnsit + β6dyit + β7tobinqit +β8mvnsgi+………+μit1 the literature was used while determining the models and variables developed in line with the purpose of the study. 1 dependent 8 independent variables were created to be used in the analysis of the study. table 2 shows the dependent and independent variables used in the analysis of the study. the data of the variables used in the study were taken from three databases and formed by the formulas shown in table 2. eva and mva, which are dependent variables, have been standardized by proportioning to total assets and used in the analysis by coding as seva and smva. since the calculation of the seva is complex, the process of creating the variable is explained in detail in the following section. seva calculation: in the calculation of seva, first of all, nopat (net operating profit after tax) criterion was calculated. in calculating nopat, net profit, other profit/loss and financing expenses were found. the after-tax value has been calculated to clear the financing expenses from tax effect. in the study, the nopat values of the companies are reached by the sum of net profit, other profit/loss, and after-tax financing expenses. the capital invested criteria are derived from the sum of net working capital and fixed assets. weighted average cost of capital (wacc) is used in the calculation of the eva. in the wacc calculation, companies’ equity costs were calculated first. capital asset pricing model (capm) has been applied while calculating the equity costs of companies. after all the specified criteria were calculated, individual eva values of the companies were calculated. finally, the seva variable was obtained by dividing these eva values by total assets. 3.2. findings in this part of the study, the findings obtained as a result of ols regression analysis and panel data analysis are included. in the study, some assumptions should be investigated to perform ols and panel data analysis. these assumptions are that there are no autocorrelation, heteroscedasticity and cross-section dependency table 2: the variables used in this study and their calculation methods variables calculation methods market to book ratio (m/b) (end of the term) market value per share/book value per share standardized economic value added (seva) (net operating profit after tax weighted average cost of capital * invested capital)/total assets standardized market value added (smva) (market value – book value of company)/total assets price to earnings ratio (p/e) market value per share/earnings per share price to cash flow ratio (p/cf) market value per share/operating cash flow per share earnings per share (eps) net income/end of period common shares outstanding market value/net sales (mvns) market value/net sales dividend yield (dy) annual dividends per share/ market value per share tobinq ratio (market value + total debt)/ total assets market value/net sales growth (mvnsg) market value/net sales growth % kurtaran, et al.: a model suggestion for determining the values of firms the energy sector: an application in bist electricity index international journal of energy economics and policy | vol 11 • issue 5 • 2021278 problems between variables. making predictions by ignoring the mentioned problems will cause the standard errors to be deviated and cause the t values to lose their validity (tatoğlu, 2016. p. 8). therefore, these assumptions need to be tested beforehand. pesaran (2006) test was used in the study for the cross-section dependency test, which is the first assumption. modified wald test was used for the heteroscedasticity problem. likewise, durbin watson and baltagi-wu lbi tests were used to determine the autocorrelation problem and the statistics of all models regarding the assumptions (wooldridge, 2002: 211) are shown in table 3. when table 3 is examined, it is observed that there are autocorrelation, heteroscedasticity and cross-section dependency problems in all 3 models created in the study. all these problems were solved with robust estimators after the panel data analysis model was selected. this situation is shown in table 5. in addition, it is important that the variables are stationary in panel data analysis. the peasaran (2007) unit root test, one of the second generation unit root tets, was applied to determine the stationarity of the variables. with this application, it was decided whether the variables were stationary or not, by looking at the cips test statistics and cips critical values. all variables used in the models were used in the analysis with their stationary values. after all the tests mentioned in the application phase of the study were carried out, variables were created using the data of the companies included in the bist electricity index between 2009 and 2018 and converted into a suitable format for analysis. later, 3 models were created for analysis. table 4 shows the ols regression results analyzed with the relevant models. as can be seen in table 4, the explanation power of model a established with m/b for the changes in m/b value is 92.12%. this rate is quite high and means that the variables in the model can explain the entire m/b criterion, which is the dependent variable. in model a, mvnsg and tobinq criteria have a significant positive effect on the m/b criterion. the explanation power of the changes in seva value of model b established with seva has reached 98.38% r2. this ratio is higher than other models established in the other study, and it shows that the variables in the model explain the dependent variable seva almost completely. in model b, eps and tobinq criteria have a significant positive effect on the seva criterion. the explanation power of model c, which was established with the last model smva, for the changes in the smva value has reached 83.01%. although this rate is high, model c’s explanatory power is low compared to the other two models established in the study. as in model a, the mvnsg and tobinq criteria have a significant positive effect on the smva criterion. when the ols test results are examined in general, it is seen that all 3 models are successful and can explain the selected criteria to represent the value of the company very well. in addition, the models in the study suggest that individuals or organizations interested in company values, such as shareholders should focus specifically on the eps, mvnsg and tobinq criteria. table 3: statistical results of the hypothesis tests modified wald statistic for groupwise heteroscedasticity models test statistic value probability value model a 3978.81 0.0000* model b 2.0e+05 0.0000* model c 0.4e+07 0.0000* *significant at the 0.05 level autocorrelation models durbin watson value baltagi-wu lbi value model a 2.616602 2.6767842 model b 1.942094 1.9611044 model c 1.6507481 1.8952307 cross-section dependency (pesaran cdlm test) models test statistic value probability value model a -1.023 0.0000* model b 2.547 0.0000* model c 1.185 0.0000* *significant at the 0.05 level table 4: ols regression results variables m/b ratio seva smva pe 10.99718 0.0022874 0.0113436 (−0.45) (1.48) (−0.37) pcf 13.83313 0.0028773 0.0142688 (0.60) (−1.51) (0.17) eps 1.963003 0.0004083* 0.0020248 (1.54) (23.16) (2.41) mvns 4.909274 0.0010211 0.0050639 (−0.68) (0.76) (1.26) dy 0.4131694 .0000859 0.0004262 (1.46) (0.01) (−0.95) mvnsg 6.078448* 0.0012643 0.0062699* (−2.65) (2.10) (−3.21) tobinq 0.4253427* 0.0000885* 0.0004387* (16.33) (24.99) (9.26) number of observ. 110 110 110 r2 0.9212 0.9838 0.8301 fprobability 0.0000 0.0000 0.0000 *1%, **5% and ***10% mean significance level. the table was created from the models representing the company value. standard error and t statistic value are shown in the table table 5: panel data analysis results variables m/b ratio seva smva pe 10.58986 0.002622*** 0.0100053 (−0.71) (1.93) (−1.11) pcf 15.70529 0.00354*** 0.0152044 (0.87) (−2.01) (1.25) eps 10.8292 0.0043451*** 0.0134321** (0.15) (1.88) (2.07) mvns 7.032896 0.0011993 0.005948 (−0.77) (1.63) (−1.21) dy 0.3232099 0.0001645 0.0003382 (1.26) (−0.01) (0.01) mvnsg 6.072411* 0.0007813* 0.0024223* (−3.20) (3.40) (−4.16) tobinq 1.906606** 0.0004318* 0.0009771* (3.31) (4.93) (6.92) number of obs. 110 110 110 r2 0.6895 0.7223 0.6132 fprobability 0.0000 0.0000 0.0000 hausman test 0.0005** 0.0005** 0.0005** significant at the *%1, **%5 and ***%10 level. the table was created from the models representing the company value. drisscoll-kraay standard error and t statistic value are shown in the table. robust estimator, drisscoll-kraay robust estimator kurtaran, et al.: a model suggestion for determining the values of firms the energy sector: an application in bist electricity index international journal of energy economics and policy | vol 11 • issue 5 • 2021 279 in this section, the results of the study found by the panel data analysis method are shown. which of the basic models used in panel data analysis should be used for analysis can be tested with hausman (1978) test. for the models to be created according to various situations in the study, the appropriate panel data model was selected by hausman test. in addition, in the study, it was assumed that all problems occurring in the basic assumptions shown in table 3 were resolved with the drisscoll-kraay robust estimator. the results of the 3 models created in the analysis, performed by panel data analysis, are presented in table 5. hausman test statistics were calculated for each model in the study, and it was accepted that there was a fixed effects model at a significance level of 0.05 (table 5). since variance, autocorrelation and inter-unit correlation problems were encountered in the panel models created in the study, it was assumed that the related problems were corrected by using the drisscoll-kraay resistive estimator, which is the only test that can correct the problems for the fixed effects model. among the models estimated according to the fixed effects model, the explanation power of model a for the changes in the m/b value is 68.95%. in other words, the variables in the model explain about 69% of the changes in the m/b value. the criteria associated with the m/b value in the model are mvnsg at the 1% significance level and tobinq at the 5% significance level, respectively. in the model, it has been determined that the coefficients of these criteria are positive and have an increasing effect on the m/b value. according to the fixed effects model, the explanation power of model b for the changes in seva value was calculated as 72.23%. in other words, the variables in the model explain about 72% of the changes in the seva value. in the model created, the criteria related to the seva value are mvnsg and tobinq at 1% significance level, pe, fnao and mci at 10% significance level, respectively. it has been determined that all of the criteria in the model have a positive coefficient and increase the seva value. likewise, the explanation power of the changes in the smva value of model c estimated according to the fixed effects model was calculated as 61.32%. in other words, the variables in the model explain about 61% of the changes in the smva value. in the model created, the criteria related to the smva value are mvnsg and tobinq at the 1% significance level, and the mci at the 5% significance level, respectively. in the model, it has been determined that these criteria are positive and have an increasing effect on the smva value. according to the results of the panel data analysis, it was determined that the most successful model representing the value of the company is seva, one of the value-based criteria. both the explanatory power of the variables of model b and the number of significant positive correlated criteria were higher than other models. in addition, the mvnsg and tobinq criteria were found to be significant in all 3 models, and it was observed that they had an increasing effect on the value of the dependent variable. likewise, it was observed that the eps criterion positively affected model b and model c. this result reached in the study means that eva, one of the valuebased criteria, is the most effective method in determining the value of companies in the bist electricity index. however, it was seen that the model established with the mva criterion, which is related to eva, is in the last step in the ranking. 4. conclusion while stakeholders such as company managers and investors are trying to make efficient and optimal investment decisions according to the profitability structure of the companies, but nowadays they are trying to shape their decisions on the value created by companies. all over the world, the understanding that companies can maximize the wealth of their shareholders if they can create value is accepted. at this point, there is a need for criteria that can accurately determine the value of the company. when the literature is examined, it is seen that although there are performance criteria that are traditionally called and need accounting data, value-based performance criteria have also been developed with value-oriented management approach in recent years. advocates of value-based performance metrics argue that firm value can only be determined by value-based performance metrics. stern & stewart consulting firm is the head of these claim holders. they tried to prove that the criterion they called economic value added, which they developed themselves, is the best criterion that determines the value of companies (stewart, 1991:136). with the spread of this criterion in the field of finance, other value-based and traditional criteria have also been developed. these developments have enabled hundreds of academic studies to be conducted on the criteria related to the value of the company. in most of the related studies, the superiority of traditional or value-based performance criteria over each other has been tried to be proven. in the study, analyzes were carried out using the data of 11 companies included in the bist electricity index, covering the 10-year period between 2009-2018. in this study, various econometric models are created by using the criteria that best represent the value of companies for shareholders and other investors, and it is aimed to gain a new perspective to the literature by presenting the model that best explains the value of the company. in the study, three models, namely a, b, and c, were created by using ols regression and panel data analysis methods. the m/b, seva and smva values of the companies are dependent, mvns, pe, fnao, dy, tobinq, eps, mvnsg criteria were used as independent variables in the models. in the study, when the results of the ols regression test are examined, it is seen that the 3 models established are successful and the m/b, seva and smva criteria that are chosen to represent the value of the company can be explained very well. in addition, the models created in the study reveal that individuals or organizations interested in corporate values, such as shareholders, should focus on the eps, mvnsg and tobinq criteria. these findings are compatible with the study of sharma and kumar (2012). in the study, when the results of the panel data analysis were examined, it was determined that the most successful model kurtaran, et al.: a model suggestion for determining the values of firms the energy sector: an application in bist electricity index international journal of energy economics and policy | vol 11 • issue 5 • 2021280 representing the value of the company was seva, one of the value-based criteria (model b). in other words, model b’s power to explain the variables and the number of significant positive correlated criteria are higher than other models. this result means that eva is the best benchmark for bist electric companies, in line with the stern and stewart consulting firm’s claim that “eva, one of the value-based criteria, is the best measure in relation to company values.” these findings are consistent with the studies of kurmi and rakshit (2017) and behere (2019). in the academic studies to be carried out after this study, researchers are recommended to perform analyzes with more performance criteria and data covering longer analysis periods. references alsaboa, s. (2017), the influence of economic value added and return on asset on created shareholders value: a comparative study in jordanian public industrial firms. international journal of economics and finance, 9(4), 63-78. auffhaummer, m., mansur erin, t. (2014), measuring climatic impacts on energy consumption: a review of the empirical literature. energy economics, 46(c), 522-530. bayraktaroğlu, a. (2009), hissedar değeri ile geleneksel ve çağdaş finansal performans ölçütleri arasındaki i̇lişki: i̇mkb firmaları üzerine bir uygulama. yayınlanmamış doktora tezi, erciyes üniversitesi sosyal bilimler enstitüsü, kayseri. behere, s. (2019), eva as periodic performance measure for indian companies. international journal of scientific research and reviews, 8(2), 3705-3719. demirkol, i̇. (2006), entellektüel sermayenin firma değerine etkisi ve i̇mkb’de sektörel uygulamalar. yayınlanmamış doktora tezi, gazi üniversitesi sosyal bilimler enstitüsü, ankara. gounder, c.g., venkateshwarlu, m. (2017), shareholder value creation: an empirical analysis of indian banking sector. accounting and finance research, 6(1), 148-157. gürbüz, a.o., ergincan, y. (2008), şirket değerlemesi: klasik ve modern yaklaşımlar. i̇stanbul: literatür yayıncılık. güriş, s., editor. (2015), stata ile panel veri modelleri. i̇stanbul: d & r yayınları. hausman, j. a. (1978), specification test in econometrics. econometrica, 46(6), 1251-1271. is investment. (2021), available from: https://www.isyatirim.com.tr/tr-tr/ analiz/hisse/sayfalar/temel-degerler-ve-oranlar.aspx#page-1. [last accessed on 2021 jan 10]. khan, m.a. (2012), the relatıonshıp between stock return and economıc value added (eva): a revıew of kse-100 index. available from: https://www.papers.ssrn.com/sol3/delivery.cfm?. [last accessed on 2021 apr 10]. kurmi, m.k., rakshit, d. (2017), information content of eva and traditional accounting based financial performance measures in explaining corporation’s change of market value. international journal of research in finance and marketing, 7(2), 1-14. lucas, e.c., mendes-da-silva, w. (2018), impact of climate on firm value: evidence from the electric power industry in brazil. energy, 153, 359-368. perez-gonzalez, f., yun, h. (2013), risk management and firm value: evidence from weather derivatives. journal of finance, 68(5), 2143-2176. pesaran, h. (2006), a simple panel unit root test in the presence of cross section dependence. journal applied econometrics, 22(2), 265-312. public disclosure platform. (2021), financial statements. available from: https://www.kap.org.tr/en/endeksler. [last accessed on 2021 jan 10]. sharma, a.k., kumar, s. (2012), eva versus convenational performance measures-empirical evidence from indıa. proceedings of asbbs, 19(1), 804-815. stewart, g.b. (1991), the quest for value: the eva management guide. new york: harper business. tatoğlu, y.f. (2016), panel veri ekonometrisi. i̇stanbul: beta yayıncılık. topak, m.s. (2010), ekonomik katma değer ve hisse senedi verimini belirlemedeki etkisi, yayınlanmamış doktora tezi, i̇stanbul üniversitesi sosyal bilimler enstitüsü, i̇stanbul. wooldridge, j.m. (2002), econometric analysis of cross section and panel data. cambridge: the mit press. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 4 • 2021230 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(4), 230-239. futures trading, spot price volatility and structural breaks: evidence from energy sector sanjeeta shirodkar*, guntur anjana raju goa business school, goa university, goa, 403206, india. *email: sanjeeta.parab@unigoa.ac.in received: 16 january 2021 accepted: 20 april 2021 doi: https://doi.org/10.32479/ijeep.11086 abstract the present study empirically examines the impact of stock futures on india’s underlying energy sector stocks by incorporating the structural breaks in the ar (1)-garch (1, 1) model. although the issues relating to the effect of derivatives trading on cash market volatility have been empirically discussed in two ways: by evaluating cash market volatilities during the pre-and post-derivatives trading periods and, secondly, by determining the influence of derivatives trading on the conduct of cash markets by comparing it with proxies. nevertheless, these methodologies cannot isolate the influence of derivatives trading from the effects of other market reforms on the volatility of the underlying cash market. the study offers mixed results for the select sample of energy sector stocks. however, there is evidence of a reduction in unconditional volatility for most energy sector stocks. the study’s findings suggest that trading in stock futures may not necessarily be associated with the destabilization of the underlying energy sector stocks. keywords: stock futures, volatility modelling, icss test, ar (1)-garch (1, 1), structural breaks, futures trading, energy sector jel classifications: g11, g14 1. introduction energy and power sector is one of the most critical infrastructure components crucial to nations’ economic growth and well-being. for the sustainable growth of the indian economy, the presence and construction of adequate infrastructure are essential. power generation options range from traditional sources such as coal, lignite, natural gas, shale, hydro and nuclear power, to suitable non-conventional sources such as wind, solar, and household and agricultural waste. the country’s energy demand has grown steadily and is expected to grow more in the years to come. a significant addition to the installed generating capacity is expected to satisfy the growing demand for electricity in the region. india ranked fourth out of 25 nations in the asia pacific region in may 2018 on an index that assessed their total strength. as of 2018, india was ranked fourth in wind power, seventh in solar power and fifth in installed renewable power capacity. in the list of countries to make significant investments in renewable energy, india placed sixth at us$ 90 billion. modelling financial asset volatility has remained one of the essential facets of economic analysis as it advises investors on risk trends found in investment and transaction processes. trading of derivatives started in the indian markets in 2000 by introducing futures contracts on the national stock exchange (nse) s&p cnx nifty index and bse sensex bombay stock exchange (bse). trading options began in indian markets in june 2001. until then, the f&o market has expanded in terms of the number of contracts exchanged, price, and new product offering. the impact of introducing derivatives on spot market volatility and, in turn, its role in stabilizing or destabilizing cash markets have remained an essential subject of analytical and empirical interest. issues relating to the effect of derivatives trading on cash market volatility have been empirically discussed in two ways: by evaluating cash market volatilities during the pre-and postfutures/options trading periods and, secondly, by determining the influence of options and futures trading on the conduct of cash markets by comparing it with proxies. furthermore, most of the this journal is licensed under a creative commons attribution 4.0 international license shirodkar and raju: futures trading, spot price volatility and structural breaks: evidence from energy sector international journal of energy economics and policy | vol 11 • issue 4 • 2021 231 studies that analyzed the effect of derivatives on the volatility of the underlying spot market used some form of garch model with dummy variable repressors. however, this approach is based on the implied presumption that any adjustments are observed during the time following derivatives trading’s implementation due solely to derivatives trading activity. various factors such as introducing the rolling settlement system, circuit breakers, and stock exchange regulatory changes can also contribute to market volatility reduction. failure to identify structural breaks in variances in the financial series under consideration will lead to a significant upward change in projected garch models’ persistence. various research studies such as diebold (1986); mikosch and starica (2000); diebold and inoue (2001) have reported that neglect of structural disturbances may cause the garch model to be spuriously estimated. the presence of structural breaks in the volatility of financial markets has long been assumed. “the primary explanations for these systemic breaks may be due to changes in exchange rate system structures, global financial markets turmoil, or stock market evolution. the shocks caused by such significant economic or political events can cause financial time series behaviour to deviate from its tranquil time.” (andreou and ghysels, 2002; wang and moore, 2009) 2. literature review the derivatives market’s effect on the underlying spot market remains a topic frequently discussed with arguments both in favour and against. bae et al. (2004) analyzed the effect of the listing of index futures on the volatility and market efficiency of the underlying kospi 200 stocks, using non-kospi 200 stocks, and observed a parallel increase in volatility and market efficiency during the post-derived era. other studies that find substantial rises in index return volatility following the implementation of futures include harris (1989), brorsen (1991), lee and ohk (1992), antoniou and holmes (1995), and yao (2016). others argue that the introduction of futures reduces the spot market’s volatility and thereby stabilizes the market. “one of the clarifications for the destabilizing hypothesis is that a derivative trading destabilizes the underlying spot market by providing an additional route for information transmission and reflection in the spot market” (cox and ross, 1976; ross, 1989). gulen and mayhew (2000) analyzed index futures’ effect on international stock markets’ volatility by using the gjr-garch and bekk model to sample 21 european countries and found that spot market volatility has declined for most of the countries under study. another school of thought suggests that spot market volatility is increasing due to the liquidity provided by speculators. this extra liquidity helps spot traders to hedge their position, thereby curbing uncertainty due to an order imbalance. several studies such as stoll and whaley (1990); pilar and rafael (2002); bandivadekar and ghosh (2003); t. mallikarjunappa (2008); thenmozhi (2002); kavussanos (2008); raju and karande (2003); sarangi and patnaik (2006) reported substantial declines in indian spot market volatility. rahman (2001) investigated the impact of index futures trading on the volatility of component stocks for the dow jones industrial average (djia) by employing the garch (1, 1) model and reported no change in conditional volatility. t.mallikarjunappa (2008) and afzal (2008); thenmozhi (2002); kavussanos (2008) inferred that the changes in the volatility process are not due to the introduction of derivatives, but due to many other factors such as better information dissemination and more transparency. anjana raju and shirodkar (2020) stated that “the listing of stock futures may not have any clear effect on the underlying stock’s volatility.” chen et al. (2014) investigated the impact of structural breaks on the spot–futures oil prices and concluded that existing breakpoint indeed affects the forecast of oil futures volatility. tabak and cajueiro (2007) investigated the brent and wti crude oil markets’ performance and noticed that oil spot markets had been more competitive over time. alvarezramirez et al. (2008) have indicated that oil markets have demonstrated inefficiency in the short term, but have been influential in the long term. however, the literature is inconclusive about whether the introduction of derivatives leads to spot market volatility increasing or decreasing. the vast majority of studies in the derivative segment arena focus on index futures’ spot market impact. indian stock futures studies concentrate on conceptual specifics or span a short time. the index-focused analysis does not consider the stock’s unique characteristics, which may also play a significant role in volatility creation. this study contributes in two ways to the on-going discussion of the effect derivatives on the underlying stock market volatility. first, this research uses a different methodology based on aggarwal et al. (1999); andreou and ghysels (2002); malik and hassan (2004); kang et al. (2009); wang-chen (2007). the analysis attempts to model with stock futures the volatility of the underlying energy sector stocks by considering the volatility breaks. the present study investigates the effect of stock futures on the underlying energy sector stocks empirically; by defining the structural break, if any, in stock price volatility since the advent of derivatives trading, using inclan and tiao’s (1994) icss test. the energy sector or industry comprises those companies involved in the exploration and expansion of oil or gas reserves, oil and gas drilling, and refining. it also includes integrated power utility companies such as renewable energy and coal. second, studying the impact of single stock futures would allow us to directly examine a company’s response to futures trading instead of index futures’ market-wide influence. 3. methods the individual stock futures (isf) has proven to be a principal financial instrument, and the nse continues to account for most of the total volumes traded worldwide on the isf. our study’s resulting sample consists of 14 stocks in the energy sector and their respective future contracts. data is sourced from the bloomberg database. the analysis period ranges from 1 january 2000 to 31 march 2019, or the stock listing date (whichever is prior). shirodkar and raju: futures trading, spot price volatility and structural breaks: evidence from energy sector international journal of energy economics and policy | vol 11 • issue 4 • 2021232 3.1. testing for arch effect testing for arch involves testing the presence of heteroscedasticity in the time-series model. engle introduced the lagrange multiple (lm) test to check for arch disorders. let εt=yt−ut be the residual series. the squared series 2t∈ is utilized to implement the lm test for checking conditional heteroscedasticity. under the null hypothesis, we have: 0 i: = 0, = 1, 2,……,h i qα versus 1 : 0,≠ih for at least one iα in the linear regression 2 2 2 1 1 , 1, ..,t t q t q t q nε ω α ε α ε− −= + +…+ = + … , where q is the length of arch lags, and n is the number of observations used in the regression equation. the test statistic for lm-test is defined by: lm = nr2 in this r2 is the r-squared from the regression of εt 2 in the equation and defined by: r2 = regressionsumof squares totalsumof squares under the null hypothesis, the test statistics nr2 is distributed as a chi-squared distribution with q degrees of freedom. h0 is rejected when lm > 2 ( )qαχ suggests that the arch effect exists in the time-series. 3.2. testing for multiple structural breaks (iterated cumulative sums of squares [icss]) algorithm of inclan and tiao (1994) the inclan and tiao (1994) proposed iterative cumulative sum of squares (icss) algorithm enables identifying several breakpoints in variance in a time series. the idea behind the icss algorithm provided by inclan and tiao can be summarized in sequential steps. a time series of interest has an absolute stationary variance over an initial period before a sudden split occurs. the unconditional variance is stationary before the next abrupt shift occurs. this process repeats through time, giving a time series of observations with multiple breakpoints in n observations’ unconditional variance. 3.3. associating the volatility breaks with derivative trading first, the dates of structural breaks in the stocks will be predicted, and later we will seek to correlate those dates with the dates of launch of derivative trading on individual stocks. ar (1)-garch (1, 1) is a garch family model, in which the mean is modelled by a first-order auto-regressive ar (1), with a garch (1, 1) error: [ ] 2, e 0, e 1, i.i.d.t t t t t t tx u σ ∈ ∈ ∈ ∈ = + = =  .., � �t tx� �1 , 2 2 2 0 1 1 1( )σ µ σ− − −= + − +t t t ta a x b once all structural breakpoints have been identified, dummy variables are created for each break detected. each dummy variable is denoted with a value ‘1’ from the location identified to the end of the data series and ‘0’ elsewhere. 4. results and discussion augmented dickey-fuller test results are shown in table 1. all variables are non-stationary at the level since the p-value is more than 0.05%. the unit root test is, therefore performed in the first difference for all variables. all the series are stationary at a 1% level of significance at the first difference. the results of the adf test indicate that all variables are integrated in the same order. table 2 depicts the arch test results for all the fourteen stocks traded at the cash segment of nse. the standard diagnostic test table 1: unit root test (augmented dickey-fuller test) stock spot futures stock spot futures adf at level adf at first difference adf at level adf at first difference adf at level adf at first difference adf at level adf at first difference adanipower −2.669 (−0.079) −77.982 (−0.000) −1.840 (−0.361) −25.085 (−0.00) ntpc −1.903 (−0.330) −252.62 (−0.000) −1.840 (−0.361) −251.08 (−0.000) bpcl −3.075 (−0.112) −14.385 (−0.000) −3.067 (−0.114) −14.026 (−0.000) oil −2.843 (−0.052) −264.13 (−0.000) −2.696 (−0.074) −264.04 (−0.000) gail −2.496 (0.116) (−240.73) (−0.000) −420.76 (−0.000) −420.76 (0.000) ongc −1.793 (−0.389) −435.00 (−0.000) −1.887 (−0.333) −297.51 (−0.000) hindpetro −1.471 (−0.548) −305.75 (−0.000) −1.505 (−0.531) −189.26 (−0.000) petronet −1.436 (−0.565) −169.53 (−0.000) −1.450 (−0.558) −218.42 (−0.000) igl −1.476 (−0.546) −296.19 (−0.000) −1.189 (−0.681) −186.67 (−0.000) powergrid −2.496 (0.116) −240.73 (−0.000) −420.76 (−0.000) −420.76 (0.000) ioc −1.903 (−0.330) −252.62 (−0.000) −1.840 (−0.361) −251.08 (−0.000) tatapower −1.683 (−0.389) −435.00 (−0.000) −1.797 (−0.333) −298.51 (−0.000) mgl −2.843 (−0.052) −264.13 (−0.000) −2.696 (−0.074) −264.04 (−0.000) torntpower −1.803 (−0.320) −242.62 (−0.000) −1.740 (−0.351) −241.08 (−0.000) note: ( ) denote p value shirodkar and raju: futures trading, spot price volatility and structural breaks: evidence from energy sector international journal of energy economics and policy | vol 11 • issue 4 • 2021 233 of the residuals from the model confirms the presence of arch effect. the absence of the arch effect hypothesis is false in the closing return series of all the variables. following the detection of structural breaks in the return series of 14 energy sector stocks, an attempt has been made to relate these dates to the launch of derivatives trading on the individual stocks as shown in figure 1. after incorporating the detected structural breaks into the ar (1)-garch (1, 1) model, detailed analysis is presented in the appendix. if a structural break is observed within 6 months following the introduction of derivative trading, it has been attributed as possible to derivative trading. following this structural break date, the change in volatility persistence, the unconditional volatility and the rate of adjustment of the volatility to the new information are observed and reported in table 3. in the case of bpcl, gail, and hindpetro, the persistence of the volatility have increased; while, the adjustment coefficient and unconditional volatility declined for the period after this break. on the contrary, ioc, ntpc, and oil demonstrated a decline in the persistence of volatility, unconditional volatility, and rate of volatility adjustment to new information. we noticed a rise in the adjustment coefficient, persistence of volatility and the unconditional volatility of ongc and petronet for the period following the introduction of derivative trading. for mgl and tatapower, the adjustment coefficient and unconditional volatility are reduced. still, the persistence rate of adjustment volatility has increased during the observed volatility structural break. however, no structural break is found in proximity to the introduction of derivatives trading for adanipower, igl and powergrid. the results of this study show a mixed picture. out of the fourteen stocks, no structural break has been observed in three stocks within the 6 months following derivative trading’s introduction. out of the remaining eleven stocks, which show a structural break during the vicinity of derivative trading, the unconditional volatility of eight stocks declined. the study’s findings show that, following the futures contracts’ implementation, the unconditional volatility of most stocks declined. volatility persistence increased in four stocks and decreased in seven stocks. the rate of adjustment of volatility to new information increased in five stocks, while it decreased in six stocks. table 2: results of arch test stock p-value result stock p-value result adanipower 0.000 present ntpc 0.000 present bpcl 0.000 present oil 0.000 present gail 0.000 present ongc 0.000 present hindpetro 0.000 present petronet 0.000 present igl 0.000 present powergrid 0.000 present ioc 0.000 present tatapower 0.000 present mgl 0.000 present torntpower 0.000 present table 3: impact of derivatives trading on volatility of underlying stock stock impact on the volatility this structural break caused by derivative trading direction of impact persistence α unconditional volatility adanipower no bpcl yes decreased increased decreased gail yes decreased increased decreased hindpetro yes decreased increased decreased igl no ioc yes decreased decreased decreased mgl yes increased decreased decreased ntpc yes decreased decreased decreased oil yes decreased decreased decreased ongc yes increased increased increased petronet yes increased increased increased powergrid no tatapower yes increased decreased decreased torntpower yes decreased decreased increased total=14 yes=11 no=03 increased=04 decreased=07 increased=05 decreased=06 increased=03 decreased=08 shirodkar and raju: futures trading, spot price volatility and structural breaks: evidence from energy sector international journal of energy economics and policy | vol 11 • issue 4 • 2021234 5. conclusion in this analysis, an attempt was made to model with stock futures the volatility of the underlying energy sector stocks by considering the breaks in volatility. we used the iterated cumulative sums of squares (icss) algorithm to detect multiple structural breaks for 14 energy sector stocks. the results of this study show a mixed picture. out of the fourteen stocks, no structural break has been observed in three  figure 1: multiple structural breaks (iterated cumulative sums of squares [icss]) algorithm of (inclan and tiao, 1994) stocks within the 6 months following derivative trading’s introduction. out of the remaining eleven stocks, which show a structural break within the 6 months of derivative trading, eight stocks’ unconditional volatility declined. the study’s findings show that, following the futures contracts’ implementation, the unconditional volatility of most stocks declined. volatility persistence increased in four stocks and decreased in seven stocks. the rate of adjustment shirodkar and raju: futures trading, spot price volatility and structural breaks: evidence from energy sector international journal of energy economics and policy | vol 11 • issue 4 • 2021 235 of volatility to new information increased in five stocks, while it decreased in six stocks. the mixed result may probably be attributed to different stock characteristics which could also play a significant role in volatility development. the study results indicate that stock futures trading may not inherently be correlated with the underlying stock destabilization. references aggarwal, r., inclan, c., leal, r. (1999), volatility in emerging stock markets. the journal of financial and quantitative analysis, 34(1), 33-55. alvarez-ramirez, j., alvarez, j., rodriguez, e. (2008), short-term predictability of crude oil markets: a detrended fluctuation analysis approach. energy economics, 30(5), 2645-2656. andreou, e., ghysels, e. (2002), detecting multiple breaks in financial market volatility dynamics. journal of applied econometrics, 17(5), 579-600. andreou, e., ghysels, e. (2002), detecting multiple breaks in financial market volatility dynamics. journal of applied econometrics, 17(5), 579-600. https://doi.org/10.1002/jae.684 anjana raju, g., shirodkar, s. (2020), derivative trading and structural breaks in volatility in india: an icss approach. investment management and financial innovations, 17(2), 334-352. antoniou, a., holmes, p. (1995), futures trading, information and spot price volatility: evidence for the ftse-100 stock index futures contract using garch. journal of banking and finance, 19(1), 117-129. bae, s.c., kwon, t.h., park, j.w. (2004), futures trading, spot market volatility, and market efficiency: the case of the korean index futures markets. the journal of futures markets, 24(12), 1195-1228. bandivadekar, s., ghosh, s. (2003), derivatives and volatility on indian stock markets. vol. 24. in: reserve bank of india occasional papers. brorsen, b.w. (1991), futures trading, transaction costs, and stock market volatility. journal of futures markets, 11(2), 153-163. chen, p.f., lee, c.c., zeng, j.h. (2014), the relationship between spot and futures oil prices: do structural breaks matter? energy economics, 43, 206-217. cox, j.c., ross, s.a. (1976), a survey of some new results in financial option pricing theory. the journal of finance, 31(2), 383-402. diebold, f., inoue, a. (2001), long memory and regime switching. journal of econometrics, 105(1), 131-159. diebold, f.x. (1986), modeling the persistence of conditional variances: a comment. econometric reviews, 5(1), 51-56. gulen, h., mayhew, s. (2000), stock index futures trading and volatility in international equity markets. the journal of futures markets, 20(7), 661-685. harris, l. (1989), s and p 500 cash stock price volatilities. the journal of finance, 44(5), 1155-1175. inclan, c., tiao, g.c. (1994), use of cumulative sums of squares for retrospective detection of changes of variance. journal of the american statistical association, 89(427), 913-923. kang, j., lee, s. (2006), an empirical investigation of the lead-lag relations of returns and volatilities among the kospi200 spot , futures and options markets and their explanations. journal of emerging market finance, 3. available from: https://doi. org/10.1177/097265270600500303 kavussanos, m.g., visvikis, i.d., alexakis, p.d. (2008), the lead-lag relationship between cash and stock index futures in a new market. european financial management, 14(5), 1007-1025. lee, s.b., ohk, k.y. (1992), stock index futures listing and structural change in time-varying volatility. journal of futures markets, 12(5), 493-509. malik, f., hassan, s. a. (2004), modeling volatility in sector index returns with garch models using an iteratd algorithm. journal of economics and finance, 28(2), 211-225. mallikarjunappa, t. (2008), the impact of derivatives on stock market volatility: a study of the nifty index. asian academy of management journal of accounting and finance, 4(2), 43-65. pilar, c., rafael, s. (2002), does derivatives trading destabilize the underlying assets? evidence from the spanish stock market. applied economics letters, 9(2), 107-110. rahman, s. (2001), the introduction of derivatives on the dow jones industrial average and their impact on the volatility of component stocks. journal of futures markets, 21(7), 633-653. raju, m.t., karande, k. (2003), price discovery and volatility on nse futures market (issue working paper series no. 7). available from: https://www.sebi.gov.in/sebi_data/attachdocs/1293096997650.pdf. ross, g.j. (1989), modeling financial volatility in the presence of abrupt changes. the journal of finance, 44(1), 1-17. sarangi, s.p., patnaik, k.u.s. (2006), impact of futures and options on the underlying market volatility: an empirical study on s&p cnx nifty index. ssrn electronic journal, 2006, 962036. stoll, h.r., whaley, r.e. (1990), the dynamics of stock index and stock index futures returns. the journal of financial and quantitative analysis, 25(4), 441. tabak, b.m., cajueiro, d.o. (2007), are the crude oil markets becoming weakly efficient over time? a test for time-varying long-range dependence in prices and volatility. energy economics, 29(1), 28-36. thenmozhi, m. (2002), do the s&p cnx nifty index and nifty futures really lead/lag? error correction model: a co-integration approach (issue nse working paper no. 18). wang, p., moore, t. (2009), sudden changes in volatility: the case of five central european stock markets. journal of international financial markets, institutions and money, 19(1), 33-46. yao, y. (2016), the impact of stock index futures on spot market volatility. international conference on education, sports, arts and management engineering (icesame 2016), p1244-1247. shirodkar and raju: futures trading, spot price volatility and structural breaks: evidence from energy sector international journal of energy economics and policy | vol 11 • issue 4 • 2021236 volatility breaks in adanipower date of commencement of derivative trading: 30-july-2010 ω α β total persistence: (α+β) unconditional volatility: ω/(1−α−β) 05 january 2000_16 november 2001 3.256 0.310 0.540 0.850 21.713 17 november 2001_01 january 2003 0.142 0.266 0.784 1.051 −2.803 02 january 2003_18 november 2004 0.172 0.096 0.888 0.984 10.853 19 november 2004_04 may 2006 3.323 0.085 0.411 0.497 6.601 05 may 2006_18 january 2008 2.728 0.259 0.453 0.712 9.478 19 january 2008_18 august 2009 2.281 0.079 0.815 0.894 21.560 19 august 2009_07 june 2012 1.175 0.146 0.558 0.704 3.962 08 june 2012_20 november 2014 0.056 0.039 0.940 0.979 2.657 21 november 2014_24 september 2015 0.840 0.032 0.703 0.735 3.169 25 september 2015_31 january 2017 1.287 −0.019 0.264 0.245 1.705 01 february 2017_29 march 2019 1.037 0.276 0.123 0.400 1.726 volatility breaks in bpcl date of commencement of derivative trading: 02-july-2001 ω α β total persistence: (α+β) unconditional volatility: ω/(1−α−β) 05 january 2000_04 october 2000 5.439 0.159 0.458 0.617 14.200 05 october 2000_17 september 2001 0.006 −0.021 1.017 0.996 1.761 18 september 2001_16 july 2004 0.793 0.060 0.815 0.875 6.353 17 july 2004_12 september 2005 0.480 0.033 0.692 0.725 1.749 13 september 2005_13 march 2007 0.331 0.224 0.736 0.960 8.348 14 march 2007_21 january 2008 0.720 0.038 0.748 0.786 3.368 22 january 2008_06 october 2009 1.128 0.096 0.776 0.872 8.822 07 october 2009_03 july 2012 1.592 0.241 0.100 0.341 2.415 04 july 2012_25 july 2013 1.019 0.167 0.085 0.252 1.362 26 july 2013_10 march 2015 0.166 0.087 0.861 0.947 3.148 11 march 2015_05 august 2016 0.354 0.104 0.623 0.728 1.299 06 august 2016_29 march 2019 0.513 0.022 0.807 0.829 3.004 volatility breaks in gail date of commencement of derivative trading: 26-september-2003 ω α β total persistence: (α+β) unconditional volatility: ω/(1−α−β) 05 january 2000_05 january 2001 1.467 0.188 0.651 0.839 9.129 06 january 2001_09 october 2003 0.336 0.187 0.744 0.931 4.841 10 october 2003_11 may 2004 0.968 −0.108 0.862 0.754 3.933 12 may 2004_18 may 2006 0.416 0.081 0.799 0.881 3.488 19 may 2006_27 june 2008 0.160 0.056 0.921 0.976 6.773 28 june 2008_22 december 2011 0.050 0.055 0.934 0.990 4.850 23 december 2011_06 august 2013 0.904 0.023 0.553 0.576 2.133 07 august 2013_06 october 2015 0.178 0.054 0.890 0.944 3.172 07 october 2015_29 march 2019 0.216 0.052 0.833 0.885 1.872 volatility breaks in hindpetro date of commencement of derivative trading: 02-july-2001 ω α β total persistence: (α+β) unconditional volatility: ω/(1−α−β) 05 january 2000_19 july 2000 13.355 0.229 0.021 0.249 17.791 20 july 2000_23 october 2001 1.187 0.049 0.772 0.820 6.605 24 october 2001_28 april 2003 0.779 0.046 0.466 0.513 1.599 29 april 2003_06 july 2004 1.756 0.187 0.476 0.663 5.214 07 july 2004_02 february 2006 1.546 0.100 0.384 0.484 2.994 03 february 2006_18 august 2009 0.745 0.135 0.729 0.864 5.466 19 august 2009_15 august 2014 0.946 0.014 0.549 0.562 2.162 16 august 2014_03 september 2015 0.217 0.011 0.930 0.941 3.664 04 september 2015_28 december 2016 1.343 0.252 0.138 0.390 2.201 29 december 2016_23 may 2017 0.210 0.197 0.547 0.744 0.818 24 may 2017_29 march 2019 0.530 0.144 0.646 0.790 2.527 shirodkar and raju: futures trading, spot price volatility and structural breaks: evidence from energy sector international journal of energy economics and policy | vol 11 • issue 4 • 2021 237 volatility breaks in mgl date of commencement of derivative trading: 28-april-2017 ω α β total persistence: (α+β) unconditional volatility: ω/(1−α−β) 12 november 2015_22 january 2016 11.610 0.304 −0.109 0.196 14.436 23 january 2016_16 february 2016 10.775 −0.123 0.663 0.540 23.432 17 february 2016_19 august 2016 2.533 −0.050 0.600 0.550 5.632 20 august 2016_29 april 2017 2.401 0.212 −0.098 0.114 2.711 30 april 2017_29 march 2019 0.977 0.024 0.828 0.852 6.613 volatility breaks in ntpc date of commencement of derivative trading: 23-august-2004 ω α β total persistence: (α+β) unconditional volatility: ω/(1−α−β) 27 january 2004_26 april 2004 0.149 0.047 0.919 0.966 4.339 27 april 2004_15 october 2005 0.634 0.012 0.608 0.619 1.666 16 october 2005_25 july 2006 0.463 0.169 0.709 0.878 3.796 26 july 2006_06 july 2007 1.290 0.342 0.159 0.501 2.588 07 july 2007_29 october 2008 0.333 0.116 0.856 0.971 11.669 30 october 2008_13 august 2009 11.142 0.241 −0.171 0.070 11.982 14 august 2009_05 august 2011 1.133 0.134 0.460 0.594 2.794 06 august 2011_10 may 2012 0.168 0.041 0.921 0.961 4.366 11 may 2012_26 june 2013 0.021 −0.041 1.030 0.988 1.823 27 june 2013_20 october 2014 0.808 0.027 0.692 0.719 2.873 21 october 2014_29 december 2017 1.048 0.151 0.232 0.383 1.699 30 december 2017_29 march 2019 0.363 0.047 0.799 0.846 2.353 volatility breaks in igl date of commencement of derivative trading: 30-september-2010 ω α β total persistence: (α+β) unconditional volatility: ω/(1−α−β) 26 july 2013_19 september 2013 10.009 0.113 −0.079 0.034 10.358 20 september 2013_02 june 2014 1.584 0.032 0.771 0.803 8.039 03 june 2014_22 march 2016 1.929 0.037 0.589 0.626 5.158 23 march 2016_01 november 2018 0.271 0.086 0.855 0.942 4.641 02 november 2018_29 march 2019 3.118 −0.063 0.716 0.652 8.969 volatility breaks in ioc date of commencement of derivative trading: 26-september-2005 ω α β total persistence: (α+β) unconditional volatility: ω/(1−α−β) 05 january 2000_27 february 2001 0.710 0.100 0.852 0.951 14.612 28 february 2001_03 november 2001 6.251 −0.196 1.046 0.850 41.605 05 november 2001_17 may 2004 1.033 0.108 0.778 0.886 9.097 18 may 2004_28 february 2006 0.447 0.005 0.810 0.814 2.408 29 february 2006_24 july 2006 5.691 0.336 −0.126 0.210 7.206 25 july 2006_01 may 2009 0.053 0.061 0.931 0.992 6.624 02 may 2009_12 july 2012 0.628 0.230 0.598 0.828 3.650 13 july 2012_11 january 2013 0.360 0.030 0.737 0.767 1.545 12 january 2013_13 march 2014 0.560 1.277 0.205 1.482 −1.163 14 march 2014_18 july 2016 0.850 −0.018 0.699 0.681 2.661 19 july 2016_ 3/29/2019 1.292 0.170 0.137 0.307 1.864 shirodkar and raju: futures trading, spot price volatility and structural breaks: evidence from energy sector international journal of energy economics and policy | vol 11 • issue 4 • 2021238 volatility breaks in ongc date of commencement of derivative trading: 31-january-2003 ω α β total persistence: (α+β) unconditional volatility: ω/(1−α−β) 05 january 2000_15 march 2001 0.263 0.071 0.893 0.964 7.290 16 march 2001_25 april 2003 0.427 0.266 0.707 0.973 15.935 26 april 2003_27 april 2004 0.073 0.082 0.900 0.981 3.916 28 april 2004_26 july 2005 0.149 0.047 0.919 0.966 4.339 27 july 2005_15 may 2006 0.767 0.074 0.639 0.713 2.671 16 may 2006_08 october 2007 0.305 0.015 0.919 0.935 4.669 09 october 2007_31 july 2009 0.569 0.079 0.875 0.954 12.340 01 august 2009_01 august 2011 0.271 0.060 0.861 0.921 3.418 02 august 2011_24 october 2017 0.215 0.071 0.874 0.946 3.953 25 october 2017_08 june 2018 0.484 −0.111 0.976 0.865 3.582 09 june 2018_29 march 2019 0.179 0.081 0.869 0.950 3.598 volatility breaks in oil date of commencement of derivative trading: 29-october-10 ω α β total persistence: (α+β) unconditional volatility: ω/(1−α−β) 05 january 2000_15 march 2001 2.278 0.189 0.655 0.844 14.638 16 march 2001_06 february 2002 2.859 0.356 0.041 0.397 4.743 07 february 2002_05 may 2003 0.372 0.081 0.855 0.937 5.862 06 may 2003_07 december 2006 1.365 0.118 0.754 0.872 10.630 08 december 2006_09 march 2007 0.969 −0.211 1.177 0.966 28.330 10 march 2007_22 july 2009 0.736 0.094 0.872 0.966 21.552 23 july 2009_02 november 2010 3.850 0.260 0.223 0.483 7.450 03 november 2010_02 april 2012 5.351 0.184 −0.181 0.002 5.364 03 april 2012_20 june 2014 0.049 0.057 0.933 0.989 4.644 21 june 2014_16 november 2016 0.362 0.034 0.808 0.842 2.292 16 november 2016_29 march 2019 0.127 0.101 0.833 0.935 1.957 volatility breaks in petronet date of commencement of derivative trading: 14-may-2007 ω α β total persistence: (α+β) unconditional volatility: ω/(1−α−β) 13 march 2007_10 april 2007 1.942 −0.050 0.589 0.540 4.219 11 april 2007_15 october 2009 0.982 0.093 0.831 0.923 12.803 16 october 2009_06 august 2010 0.384 0.004 0.935 0.940 6.357 07 august 2010_04 june 2013 3.145 0.198 0.007 0.205 3.958 05 june 2013_12 january 2017 3.275 0.150 0.600 0.750 13.101 13 january 2017_29 march 2019 7.650 0.306 −0.082 0.224 9.861 volatility breaks in powergrid date of commencement of derivative trading: 05-october-2007 ω α β total persistence: (α+β) unconditional volatility: ω/(1−α−β) 05 october 2007_29 october 2008 0.333 0.116 0.856 0.971 11.669 30 october 2008_13 august 2009 11.142 0.241 −0.171 0.070 11.982 14 august 2009_05 august 2011 1.133 0.134 0.460 0.594 2.794 06 august 2011_10 may 2012 0.168 0.041 0.921 0.961 4.366 11 may 2012_26 june 2013 0.021 −0.041 1.030 0.988 1.823 27 june 2013_20 october 2014 0.808 0.027 0.692 0.719 2.873 21 october 2014_29 december 2017 1.048 0.151 0.232 0.383 1.699 30 december 2017_29 march 2019 0.363 0.047 0.799 0.846 2.353 shirodkar and raju: futures trading, spot price volatility and structural breaks: evidence from energy sector international journal of energy economics and policy | vol 11 • issue 4 • 2021 239 volatility breaks in tatapower date of commencement of derivative trading: 02-july-2001 ω α β total persistence: (α+β) unconditional volatility: ω/(1−α−β) 05 january 2000_05 february 2001 0.602 0.241 0.724 0.965 17.222 06 february 2001_16 october 2001 1.111 0.386 0.474 0.860 7.939 17 october 2001_22 may 2003 0.501 0.306 0.484 0.791 2.393 23 may 2003_14 may 2004 1.487 0.145 0.448 0.593 3.656 15 may 2004_30 march 2006 0.548 0.028 0.770 0.798 2.712 31 march 2006_28 november 2008 0.352 0.103 0.855 0.958 8.337 29 november 2008_08 november 2010 0.036 0.045 0.941 0.985 2.477 09 november 2010_04 january 2012 3.047 −0.064 0.009 −0.055 2.889 05 january 2012_03 june 2014 0.032 0.039 0.948 0.986 2.355 04 june 2014_07 october 2015 0.598 0.024 0.521 0.545 1.314 08 october 2015_29 march 2019 0.407 0.057 0.461 0.517 0.843 volatility breaks in torntpower date of commencement of derivative trading: 30 december 2015 ω α β total persistence: (α+β) unconditional volatility: ω/(1−α−β) 28 december 2012_07 june 2013 1.175 0.146 0.558 0.704 3.962 08 june 2013_20 november 2014 0.056 0.039 0.940 0.979 2.657 21 november 2014_24 january 2016 0.840 0.032 0.703 0.735 3.169 25 january 2016_31 january 2017 1.287 −0.019 0.264 0.245 1.705 01 february 2017_29 march 2019 1.037 0.276 0.123 0.400 1.726 tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 1 • 2022 427 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(1), 427-435. the effects of gross domestic product and energy consumption on carbon dioxide emission in uganda (1986-2018) jacob otim1, geoffrey mutumba1*, susan watundu2, geoffrey mubiinzi3, milly kaddu1,3 1department of economics and statistics, kyambogo university, uganda, 2department of management science, makerere university business school, uganda, 3department of economics, uganda martyrs university, nkozi, uganda. *email: gmutumba@kyu.ac.ug received: 29 september 2021 accepted: 17 december 2021 doi: https://doi.org/10.32479/ijeep.12552 abstract this study examines the effects of energy consumption and per capita gross domestic product on carbon dioxide emission which is a precursor for global warming due to its large scale impact on the environment. the effect of per capita gross domestic product and per capita energy consumption on carbon emission per capita in uganda is not clearly known. this study fills the empirical gap for uganda for 1986-2018. the study used vector error correction techniques and the results suggest evidence of a long-run relationship between the variables at a 5% significance level using the johansen cointegration test. the estimated elasticity of carbon dioxide emission per capita with respect to gross domestic product per capita is 1.856. the results for the existence and direction of granger causality show a unidirectional causality running from gross domestic product per capita to carbon dioxide emission per capita and the environmental kuznets curve hypothesis is supported. in addition, there is no causal link between energy consumption per capita and gross domestic product per capita, which supports the growth neutrality hypothesis. the overall results indicate that gross domestic product per capita has a positive effect on carbon dioxide emission in uganda while energy consumption does not granger cause carbon dioxide emission. keywords: co2 emission, energy consumption, gdp per capita, johansen cointegration test, granger causality, vecm jel classifications: k32, p18, q43, q48, q54 1. introduction global warming has attracted considerable debate in the area of environment in the last three decades (held and rogers 2018). this has been attributed to the risk of change in climate on human beings and the ecosystem. due to large-scale impact of human activities, most countries of the united nations have agreed to keep the global warming below 2°c by cutting down greenhouse gases (ghgs) emission mainly due to co2. the commitment ratified through the signatures of the kyoto protocol in 1997 (protocol, 1997). this was followed by the paris agreement with the main aim of addressing the global response to the threat of climate change (horowitz, 2016). carbon emission is the release of carbon to the atmosphere. the emission is composed of ghgs which are the main contributors to climate change. ghgs are often calculated as carbon equivalent. the kyoto protocol spelled out six main ghg pollutants which have significant impact on the environment namely; co2, ch4 (methane), n2o (nitrous oxide), hfcs (hydrofluorocarbons), pfcs (perfluorocarbons) and sf6 (sulfur hexafluoride). co2 is considered to be the main contributor to global warming (zhang and da, 2015). the summit on sustainable development held in 2002 in johannesburg, south africa highlighted the detrimental impact of energy consumption on the environment despite its key role in economic growth and development (sghari and hammami, 2016). in uganda, co2 emission from hydrocarbon combustion and industrial use contribute roughly to 0.099% of the global carbon stock. even though uganda contributes less to the potentially catastrophic accumulation of man-made carbon footprints, the this journal is licensed under a creative commons attribution 4.0 international license otim, et al.: the effects of gross domestic product and energy consumption on carbon dioxide emission in uganda (1986-2018) international journal of energy economics and policy | vol 12 • issue 1 • 2022428 country is susceptible to the influence of climate change. uganda’s carbon stock is among the lowest in the world and is estimated at 1.39 tons of carbon equivalent less than the world average of 7.99 tons of carbon emission equivalent per capita (gou, 2015). however, the contribution of carbon emissions to the growth trajectory of uganda is not clearly known (markandya et al., 2015). the uganda’s vision 2040 may be severely hampered by climate factors in the absence of adaptation actions (gou, 2020) due to overreliance on traditional biomass as the main source of energy (bamwesigye et al., 2020). therefore, the achievement of sustainable development goal (sdg) 7 (affordable clean energy) geared towards ensuring access to affordable, reliable and sustainable modern energy for all and sdg 13 (climate action) may be hampered. actions to combat climate change and its impacts on the environment would all be practically impossible unless serious policy measures are put in place (walters, 2021). in this paper, we examine the effects of energy consumption per capita and per capita gdp on co2 emission per capita, in uganda using the johansen cointegration testing approach and vector error correction model (vecm) based on granger causality for uganda over 1986-2018 period. the major contribution of this paper is to provide the theoretical understanding of the effect of gdp and energy consumption on the environment in a multivariate framework using a vector error correction model. the rest of the paper is organized as follows. the next section presents the literature review. the third section shows the methods. the fourth section reports the empirical results and discussion. the final section is the conclusion of the study. 2. literature review the link between carbon emission, energy consumption and economic growth has been widely analyzed and is a center of controversy and debate since the 1950s (kuznets, 1955). climate and energy are intrinsically linked. the quality of our environment, by and large, is determined the way we consume energy. as a result, examining the productive use of energy is key to the sustainable development goals 11 (develop sustainable cities and communities) and 13 (climate change). the awareness of the change in climate and its implication on planet earth makes it vital to examine the causal effect of energy consumption on development. energy consumption is key in the development process since it is a main driver for sustainable development (ma, 2019). the rise in energy consumption is expected to lead to the growth in gdp in real terms through a transmission mechanism that cascades to co2 emission increase, which is an important factor in global warming and eventual climate change. studying nexus among these global variables is pivotal. there are numerous stock pollutants that lead to climate change but co2 is a dominant gas of all ghgs (sadik-zada and loewenstein, 2020). investigating a causal link between carbon emission, energy consumption and economic growth has become a landmark of recent studies since energy consumption is the best vehicle to achieve sustainable development (akadiri, 2019). several studies have used a multivariate framework to examine the causal link between co2 emission, energy consumption, and economic growth, they find mixed results. alam (2011) uses a johansen test and autoregressive distributed lag to explain a long-run relationship between electricity consumption, energy consumption, co2 emission, and gdp in bangladesh. his results show a one-way causality running from energy consumption to economic development both in the short-run and the long-run. additional results show a bidirectional causality between co2 emission and energy consumption and also electricity consumption and economic development. in chang‘s (2010) study, different energy sourcescrude oil, natural gas, electricity and coal are used to examine the relationship between co2 emission, energy consumption, and gdp in china. the results show that more co2 emission is a caused by energy consumption and gdp growth. ang (2007) employs a multivariate error correction model to investigate the causal link between energy consumption, co2 emission and output in france. the results show energy consumption to increase emissions, while the study by halicioglu (2009) shows that there is bidirectional causality between output and co2 emission both in the short-run and long-run for turkey. a couple of studies have been conducted in sub-saharan africa (ssa) menyah and wolde-rufael’s (2010) study, show causality between economic development, energy consumption, and pollutant emission in south africa and there exist long-run relationships between the variables. the result also indicates that there is one-way causality running from both energy consumption and carbon emission to economic development. adom et al. (2012) find a bidirectional relationship between co2 emission and economic growth in morocco and one-way causality running from economic growth to co2 emission in senegal. a study by appiah (2018) on the multivariate granger causality between energy consumption, economic growth and co2 emission in ghana from 1960-2015 using toda-yamamoto and granger causality test shows a feedback granger causality between energy consumption and co2 emission. further still, a unidirectional granger causality from energy consumption to economic growth was detected. studies in uganda’s context, include senkantsi and okot (2016) on electricity consumptionand gdp for uganda from 1982-2013 using ardl bound test and the granger causality framework. their study found a unidirectional causal flow from economic growth to electricity consumption. mawejje and mawejje (2016) also conducted a similar study using vector error correction techniques and granger causality test, where they found a unidirectional causal link running from electricity consumption to gdp. appiah et al. (2019) studied the causal link between industrialization, energy intensity, and gdp and carbon oxide emission using data from uganda from 1990 to 2014. the existence of unidirectional causality comes from energy intensity to co2 and from gdp to co2. this implies that the increase in energy intensity leads to more environmental pollution. a similar study that investigates the effect of energy on co2 emission in uganda is by appiah et al. (2019). they use energy intensity as a predictor for co2 emission in uganda yet its applications in real world policy making is troublesome. due to the fact that the gdp of the individual economies are converted to a common currency otim, et al.: the effects of gross domestic product and energy consumption on carbon dioxide emission in uganda (1986-2018) international journal of energy economics and policy | vol 12 • issue 1 • 2022 429 using the purchasing power parity or the market exchange rates (samuelsson, 2014), energy intensity becomes a poor predictor of co2 emission. the weakness in appiah et al. (2019) paper gives a justification for our paper to make a theoretical contribution and use energy consumption per capita as a better predictor for co2 emission in uganda. 3. methods 3.1. research design a correlational research design and quantitative approach for time series analysis were adopted. all the data from the selected variables are continuous in nature over time and statistical methods of measurement are used (beard et al., 2020). the study covered a period of 33 years from 1986 to 2018. this period has been selected because there has been a stable government under one leadership without any serious interruption from war or takeover of government as always common in developing countries. 3.2. expected signs of the variables the expected signs, symbols, measurements, and data sources used in the model are presented in table 1. the data used for this paper obtained from the world bank development indicators. 3.3. model specifications following the empirical literature in economics, we have observed that energy is a significant factor of co2 emission. according to the ekc hypothesis co2 emission and output have a nonlinear quadratic relationship (dinda 2004). at a steady state, the cointegrating relationship between carbon emissions, energy and output can be specified as follows: c ec gdpt t t t� � � �� � � � (1) where ct=ln(co2t/lt) is per capita co2 emission, ect=ln(ect/lt) is per capita energy consumption, gdpt=ln(gdpt/lt) is per capita gdp and εt is the residuals. lt is the total population over time. equation one is expressed in the natural logarithmic form to reduce the effect of heteroskedasticity and to obtain the growth rate of the relevant variables by differencing their natural logarithmic form. the expected sign in equation 1 is such that θ>0 because high energy consumption is expected to increase co2 emission. the parameters θ, and γ are long-run elasticities of co2 emission per capita with respect per capita energy use, and per capita gdp respectively. 3.4. unit root tests the stationarity was tested using the augmented dickey-fuller (adf) and philips-perron (pp) developed by phillips and perron (1988). dickey and fuller (1981) examine the unit root in each time series with the following hypothesis: ho: θ=0, when the time series has unit root h1: θ<0, when the time series has no unit root following the ordinary least square (ols) assumption, adf is expressed as: � �y y y ut t t i i p t i t� � � � �� � ��� � � �1 1 (2) where t is a deterministic trend, ψ and β are the constants, p is the lag order selection based schwartz bayesian criterion (sbc). if the calculated value in the absolute term, is more than the t-statistic, we reject the h0 (θ=0), if h0 is rejected it implies the series is stationary and is an i(0) process. when h0 is rejected at the first difference, the series is i(1). similarly, when the series becomes stationary at the second difference, the series exhibits an i(2) process. the pp test is used to correct for any serial correlation and heteroskedasticity in the error ut since it is more robust than dickey-fuller. 3.5. cointegration test we applied the johansen cointegration test by johansen and juselius (1990). it is used to check for existence long-run cointegrating equation(s) between or among variables of the i(1) series. the cointegration is performed in levels but not in first difference. but since the variables are in natural logarithmic form, the log transformed variables are used to interrogate the long-run relationship. the multivariate cointegration model of johansen and juselius is expressed as: � � �y y y ut t i t i p t� � � �� � � � �� � 1 1 1 1 (3) where, π and гi are coefficient matrices, δ is the difference operator and p is the lag order selected based on sbc. johansen and juselius cointegration uses two likelihood ratio test-the trace and max eigenvalue tests and they are computed as follows: 1 ˆ( ) ln(1 ) n i i r t r t λ = + = − −∑ (4) ( ) ( )max 1ˆ, 1 ln 1 rr r tλ λ ++ = − − (5) where, îλ is the expected eigenvalue of the characteristic roots and t is the sample size. in λtrac test, the h1 investigates the number table 1: variable description and expected signs variables symbol measure expected sign data source per capital co2 emission ct co2 emission in kiloton n/a world bank: world development indicators per capita gdp gdpt gdp constant 2010 us$ + world bank: world development indicators per capita energy consumption ect energy consumption measured in terra joules + world bank: sustainable energy for all. otim, et al.: the effects of gross domestic product and energy consumption on carbon dioxide emission in uganda (1986-2018) international journal of energy economics and policy | vol 12 • issue 1 • 2022430 of cointegrating vector r against h1 of n cointegrating vector. whereas, for λmax test, h0 investigates the number of cointegrating vectors r against h1 of r+1 cointegrating vector. when using johansen and juselius cointegration test, where there is one or more cointegrating vectors, there is evidence of long-run equilibrium between or among variables. to establish the relationship we set the null hypothesis as follows: h0: no cointegrating equation(s) the decision criteria is based on 5% level of significance. we reject the null if the value of λtrac and λmax is greater than 5% critical value. otherwise, we fail to reject the null. 3.5. vector error correction model (vecm) vecm is a system of vector of two or more variables that are exogenous. if the variables are non-stationary but i(1) time series and they are cointegrated, we can run vecm to examine both short-run and long-run dynamics of the series. the vecm for all the endogenous variables appears as follows: � � � � c c ec gdp ec t i i k t i j t j j k m t m m k � � � � � � � � � � � � � � � � � � � � � � 1 1 1 1 1 1 1 tt ut t� �1 1. . (6) � � � � ec c ec gdp t i i k t i j t j j k m t m m k � � � � � � � � � � � � � � � � � � � � � � 1 1 1 1 1 1 2 . eect ut t� �1 21. (7) � � � � gdp c ec gdp t i i k t i j t j j k m t m m k � � � � � � � � � � � � � � � � � � � � � � 1 1 1 1 1 1 3 eect ut t� �1 3 (8) where k−1 the lag length is reduced by 1 and αi, βj, μm are the short-run coefficients of the model’s adjustment long-run equilibrium. λi is the coefficient of ect and is the speed of the adjustment parameter towards long-run equilibrium. it has to be negative and statistically significant for it to maintain its economic interpretation. ectt−1 = the term error correction relates to the fact that last year period deviation from long-run equilibrium (error) influences the short-run dynamics of the dependent variables. uit= residuals (stochastic error term often called impulses or innovations or shocks. to find the long-term causality flowing from the dependent variable(s) to the dependent variable, the coefficient of the ect ( λ ) should be significant and is defined as: ect c c ec gdpt i i k t j j k t j m m k t m� � � � � � � � � � � � � �� � �� � � �� � � � 1 1 1 1 1 1 1 (9) 3.6. granger causality test we used a two-steps procedure from engle and granger (1987) model to investigate the link between co2 emissions per capita, energy consumption per capita, and gdp per capita. in the first step, we estimate the long-run model in equation 6 in order to get the estimated residuals. the second step is to estimate error correction based on the granger causality approach. the error correction based on causality tests allows the inclusion of the lagged error term derived from the cointegration equation (ozturk and acaravci 2010). we also validated our result using the pairwise granger causality test. 4. results and discussions 4.1. unit root tests most variables may not exhibit -stationarity, therefore we test for unit root. the time series properties of the variables under investigation are tested using augmented dickey-fuller (adf) test developed by dickey (1981) and philips-perron (pp) tests by phillips and perron (1988) at a constant intercept without a trend are applied. this is always done to avoid spurious results in the data generation process. table 2 illustrates the results. from table 2 all variables are non-stationary in levels and they are all stationary at first difference i.e, i(1). since all the variables are i(1) series, we proceed to test for the existence of the cointegration equation. to do this we determine the appropriate lag length. 4.2. optimal lag length structure the key issue in time series analysis is the optimal lag selection process for a finite set of observations (hamilton, 2020). the selection of a lag structure in vecm is an empirical question because both over-fitting and under-fitting of the model with lags result into insignificant coefficients and spurious outcomes. for the purpose of this study, we consider final prediction error (fpe), akaike information criterion (aic), schwarz information criterion (sc) and hannan-quinn information criterion (hq) for the selection of the optimal lag structure. table 3 shows the results; the optimal lag length selected by the criteria is one. this is appropriate because we are dealing with annual observations for 33 years. 4.3. cointegration test the existence of long-run cointegration is tested using johansen cointegration test developed by johansen (1988). it was carried out to establish whether the series are linearly related. in such a situation if there are shocks in the short-run, which often affect the individual series, they can convergein the long-run. if the series are not integrated we only estimate vector auto regressive (var) model. to use the johansen cointegration test, our null hypothesis supports the existence of no cointegrating equation and the decision criteria is based at a 5% level of significance. we reject the null hypothesis if the value of the trace and max statistics is greater than 5% critical value. otherwise we fail to reject the null hypothesis. table 4 depicts the johansen unrestricted integrated rank test. we reject the null hypothesis of no cointegrating equation since the value of trace statistic (λtrace) and max-eigen (λmax) value are above the critical value at 5%. we conclude that there are otim, et al.: the effects of gross domestic product and energy consumption on carbon dioxide emission in uganda (1986-2018) international journal of energy economics and policy | vol 12 • issue 1 • 2022 431 long-run cointegration equation. this implies that the series are related and can be combined in a linear fashion and in case there is a shock in the short-run, which may affect the movement in the individual series they would converge in the long-run. therefore, we can proceed a head to estimate the long-run equation in the vector error correction (vec) model framework, because there is at least one cointegrating equation confirmed by the analysis of both trace and max-eigen statistics. the normalise johansen cointegration results from our estimation is expressed in table 5. the figures in the parentheses are standard errors. thus the johansen long-run cointegration equation is expressed as follows: c ec gdpt t t� � � �18 613 0 526 1 856. . . (10) the result in equation 10 indicates that economic growth measured in terms of real gdp per capita is positively and statistically is associated with co2 emission. while energy consumption is positively corrected with co2 emission but it is not statistically significant. specifically, a 1% increase in gdp per capita tends to increase co2 emission by about 1.856%, ceteris paribus. we conclude that the null hypothesis of no cointegration is rejected against its alternative of cointegrating relationship in the model. the positive link between co2 emission and gdp per capita makes rational economic sense, since the growth in gdp per capita is associated with the increase in the economic activities through consumption of goods and services which are likely to have negative effect of the environment. however, there is a lot of debate on this area in terms of causality between economic growth and co2 emission with no consensuses reach yet among the scholars as shown in the literature section. 4.4. granger causality and short-run dynamics this paper also explores the direction of causality between the variables by using error-correction based granger causality models which are weak (short-run) granger causality and long-run causality. the results for models in tables 6-8 can be summarised as follows: (i) there is no causality between co2 emission per capita and energy consumption. (ii) a unidirectional relationship running from gdp per capita to co2 emissions per capita and supports ekc hypothesis in the short-run. (iii) there is no causality running from energy consumption per capita to gdp per capita. (iv) there is no causality from gdp per capita to energy consumption per capita. (v) long-run relationship exists for co2 emission per capita equation and gdp per capita granger cause co2 emission per capita. the findings of positive relationship between economic growth and carbon emissions are in line with appiah et al. (2019) in uganda’s context. sekantsi and okot (2016) and mawejje and mawejje, (2016) but did not test the causality between co2 emissions and economic growth. the generally, the results support energy growth neutrality hypothesis. energy consumption does not pay a pivotal role in economic growth and economic growth does not impact on energy consumption. in addition, the result also support ekc hypothesis where economic growth leads to environmental degradation in the short-run. uganda should take care on its energy table 2: adf and pp unit root tests adf test pp test level 1st difference level 1st difference variables test statistics prob. test statistics prob. adj. t-stat prob. adj. t-stat prob. ct 0.625201 0.9883 −4.904261 0.0004*** 0.595226 0.9874 −4.895838 0.0004*** ect −2.023753 0.2757 −5.528474 0.0001*** −2.021908 0.2764 −5.528490 0.0001*** gdpt −0.969973 0.7518 −4.534485 0.0011*** −0.880853 0.7813 −4.561942 0.0010*** *** indicates statistical significance at 1% table 3: optimal lag selection criteria lag logl lr fpe aic sc hq 0 55.52782 na 6.77e-06 −3.388892 −3.250119 −3.343655 1 177.0059 211.6070* 4.80e−09* −10.64554* −10.09045* −10.46460* 2 184.5813 11.72953 5.36e−09 −10.55363 −9.582219 −10.23697 *indicates lag order selected by the criterion, lr: sequential modified lr test statistic (each test at 5% level). fpe: final prediction error, aic: akaike information criterion, sc: schwarz information criterion, hq: hannan-quinn information criterion table 4: johansen unrestricted cointegration rank test (maximum eigenvalue and trace) hypothesized no. of ce (s) eigenvalue trace max-eigen statistic critical value at 5% prob. statistic critical value at 5% prob.** none * 0.386379 29.84717 29.79707 0.0493 15.13972 21.13162 0.2792 at most 1 0.291161 14.70745 15.49471 0.0655 10.66792 14.26460 0.1717 at most 2* 0.122174 4.039530 3.841466 0.0444 4.039530 3.841466 0.0444 trace test indicates 1 cointegrating equation (s) at the 0.05 level, * denotes rejection of the hypothesis at the 0.05 level, **mackinnon-haug-michelis (1999) p values table 5: long-run equilibrium variables coefficient standard errors t-statistic ct 1.000000 ect −0.525794 0.55246 −0.95175 gdpt −1.853266 0.16542 −11.2034*** constant 18.61247 error correction term −0.292670 0.08426 −3.47344*** *** indicates statistical significance at 1% otim, et al.: the effects of gross domestic product and energy consumption on carbon dioxide emission in uganda (1986-2018) international journal of energy economics and policy | vol 12 • issue 1 • 2022432 polices, the absence of causality between energy consumption and economic growth should not bring complacency because we see economic growth contributing to the environmental degradation in terms of increased co2 emission per capita. we expect when uganda starts to extract the oil in 2022 (wolf and potluri, 2018) the consumption of fossil fuels will increased, which is likely to have an adverse effect on the environment. the government expect to refine 150,000bbl daily and generates us$ 1billions in profits yearly through import substitution industrialization and export earnings (wolf and potluri, 2018). if we are to go by these figures, we expect growth in gdp per capita and energy consumption of fossil fuels, which may affect the environment adversely unless strong policy action are put in place to mitigate the possibility of environmental degradation. 4.5. vecm estimation diagnostics the estimated error correction term (ect) is negative (−0.29267) and statistically significant at 1% confidence level (tables 6 and 7). ect indicates that any deviation from the long-run equilibrium between variables is corrected by about 29.27% for each period to return to the long-run equilibrium. in addition, figure 1 presents the plot of recursive estimate for cumulative sum (cusum) and cumulative sum square (cusumsq) of recursive residuals illustrated in figure 1. the coefficients were generated from vecm coefficients. the results indicate the absence of any instability of coefficients because the plots of cusum and cusumsq statistics fall inside the critical band of the 5% confidence interval parameter stability. after estimating the vecm we tested for the robustness of the model through checking for serial correlation, residual normality, heteroskedasticity and model stability. table 9 illustrates the results. we did not detect presence of serial correlation, and heteroskedasticity and the data is normality distributed. we can conclude that our model is pretty robust. 4.6. variance decomposition variance decomposition in multivariate analysis used in economic forecasting (lutkepohl, 2010). tables 10-12 illustrate our result. each row represents the percentage of the forecast error variance table 6: estimated coefficients error correction: δct δect δgdpt cointeq1 −0.292670 [−3.47344]*** −0.035658 [−0.68657] 0.005443 [0.22625] δct (−1) 0.129217 [0.75817] 0.018054 [0.17186] 0.047877 [0.98390] δect (−1) −0.262820 [−0.82787] −0.042364 [−0.21650] 0.104407 [1.15187] δgdpt (−1) −0.881842 [−1.31081] −0.442069 [−1.06608] 0.135236 [0.70407] constant 0.058032 [2.46469] 0.003028 [0.20866] 0.025616 [3.81040] r2 0.331001 0.050923 0.129214 adj. r2 0.228078 −0.095089 −0.004753 *** indicates statistical significance at 1% table 7: granger causality test results variables short-run (or weak) granger causality long-run granger causality δct δect δgdpt λi, i=1,2,3, δct (−1) …………. 0.02954 (0.8635) 0.96805 (0.3252) −0.29267 (0.0018)*** δect (−1) 0.68536 (0.4077) ………… 1.32681 (0.2494) 0.18749 (0.4984) δgdpt (−1) 1.71821 (0.3083) 1.13652 (0.2864) ………. −0.01009 (0.8228) *** indicates statistical significance at 1% .the null hypothesis is that there is no causal relationship between variables. values in the parentheses are p values for wald tests with distribution. δ is the first difference operator table 9: vecm post estimation test vec residual serial correlation lm tests residual normality tests vec residual heteroskedasticity tests lm stat prob. jarque-bera prob. chi-sq prob. 11.75350 0.2276 2.721445 0.25475 40.35525 0.7755 table 10: variance decomposition of ct period s.e. ct ect gdpt 1 0.072954 100.0000 0.000000 0.000000 2 0.093225 99.21564 0.327769 0.456591 3 0.102775 99.11120 0.297937 0.590868 4 0.110923 96.13280 1.456243 2.410956 5 0.119320 90.63697 3.958921 5.404113 6 0.128017 83.97681 7.144363 8.878828 7 0.137032 77.05142 10.52745 12.42112 8 0.146279 70.44342 13.80077 15.75581 9 0.155610 64.45631 16.79723 18.74646 10 0.164897 59.18318 19.45627 21.36055 table 8: pairwise granger causality tests null hypothesis: f-statistic p-value decision ect does not granger cause ct 2.12796 0.1554 fail to reject the null hypothesis ct does not granger cause ect 0.07516 0.7859 fail to reject the null hypothesis gdpt does not granger cause ct 7.36712 0.0111** reject the null hypothesis ct does not granger cause gdpt 3.34088 0.0779 fail to reject the null hypothesis gdpt does not granger cause ect 0.34235 0.5630 fail to reject the null hypothesis ect does not granger cause gdpt 0.38798 0.5382 fail to reject the null hypothesis *** indicates statistical significance at 1% otim, et al.: the effects of gross domestic product and energy consumption on carbon dioxide emission in uganda (1986-2018) international journal of energy economics and policy | vol 12 • issue 1 • 2022 433 by the all the variables under investigation. we made a forecast of 10 year period. we divide our forecast in the short-run, mid-term and long-run. table 10 shows that in the short-run 100% of the forecast error variance is explained by co2 emission per capita itself. the contribution from energy consumption per capita, and gdp per capita to co2 emission per capita are strongly exogenous implying that they have very weak influence in predicting co2 emission per capita in the short-run. in the mid-term period, 90.6% co2 emission per capita is explained by its standard innovation shock. this further still show that the weak influence of energy consumption per capita and gdp per capita is explained by co2 emission per capita in uganda. in the long-run, we see the influence of co2 emission per capita on itself dwindling the further we move to the future. it implies that energy consumption and economic growth will start to have a strong endogenous influence on the carbon emission in uganda. table 11 shows that in the short-run 99.32% of the forecast error variance is explained by energy consumption itself and the contribution from gdp per capita and carbon emission per capita throughout the period of 10 years are very weak at less than 5%. in table 12 we see only carbon emission per capita having fairly strong endogenous influence on gdp per capita while energy consumption is having weakly endogenous effect on gdp per capita. the forecast error variance reflect the granger causality test results. 5. conclusions this paper examines the long-run and causal links between emissions co2, energy consumption, and economic growth in uganda using vecm and johansen cointegration test for long-run relationship and granger causality models for 1986-2018 period. empirical results suggest an evidence of a long-run relationship between variables at 5% levels of significance in uganda. the estimated elasticity of co2 emission per capita with respect to gdp capita is 1.856. the main results for the existence and direction of granger causality are as follows: (i) the interesting finding is that energy consumption does not granger cause co2 emission per capita, although the main cause of co2 emission in literature is energy consumption. uganda can still continue to engage in oil exploration and start oil extraction to boost its economic growth without causing much damage to the environment at least in the short-run. (ii) there is a unidirectional causality flowing from gdp per capita to co2 emissions per capita. the result does support the environmental kuznets curve hypothesis, implying that economic growth leads to environmental pollution through co2 emissions. (iii) there is no causal link between energy consumption per capita and gdp per capita. the result support growth neutrality hypothesis. the government of uganda can pursue policies that promote energy consumption and economic growth such us increasing the level of industrialisation. to take care of environment green energy growth policy can be adopted for sustainable growth and development in the long-run. (iv) long-run causality exists only for co2 emission per capita equation. figure 1: plot of cusum and cusumsq recursive residuals table 11: variance decomposition of ect period s.e. ct ect gdpt 1 0.044967 0.671658 99.32834 0.000000 2 0.062794 0.381364 98.38387 1.234766 3 0.076261 0.650727 97.81901 1.530259 4 0.088252 0.859977 97.70996 1.430061 5 0.099174 0.995514 97.70586 1.298622 6 0.109195 1.109107 97.70500 1.185889 7 0.118496 1.209148 97.70150 1.089355 8 0.127215 1.295287 97.69797 1.006740 9 0.135443 1.369108 97.69441 0.936483 10 0.143247 1.432719 97.69057 0.876707 table 12: variance decomposition of gdpt period s.e. ct ect gdpt 1 0.020829 20.20908 0.414469 79.37645 2 0.033550 27.24880 3.421960 69.32924 3 0.042056 29.14400 4.257522 66.59848 4 0.048961 29.03441 4.722091 66.24350 5 0.055195 28.41374 5.180753 66.40551 6 0.060931 27.74243 5.614048 66.64352 7 0.066245 27.11078 5.994692 66.89453 8 0.071213 26.53698 6.324101 67.13892 9 0.075894 26.02628 6.609572 67.36415 10 0.080331 25.57655 6.857346 67.56610 cholesky ordering ct, ect, gdpt otim, et al.: the effects of gross domestic product and energy consumption on carbon dioxide emission in uganda (1986-2018) international journal of energy economics and policy | vol 12 • issue 1 • 2022434 the main result of this study indicates that gdp is key determinant of co2 emissions in the long-run. as the growth in an economy is reflected through the increase in gdp at both nominal and real terms. this is because the growth in gdp is characterised by the growth in a number of economic activities besides energy consumption. a country like uganda is predominantly agrarian and peasantry in nature. therefore, the growth in its gdp is facilitated by unregulated economic practices. therefore policies that are pro-growth may certainly conflict with policies that promote reduction in co2 emission. the growth in gdp as the country strive to attain a middle income status is a precursor for future emission in uganda. thus, whereas growth in gdp is necessary for the welfare of the people, it should be sustainable for the posterity. the goals for economic growth and sustainable development are all important. therefore, green growth strategy is likely to be the future of uganda’s economy, if the country is to strike a balance between the two. the impact on energy consumption on the co2 emission was found to be insignificant. this result suggests that there are other causal factors responsible co2 emission. we used 33 years observations which may affect the predictive ability of our model. when more data are available in future, this study can be repeated to take care of the long-run time variation. however, the study did not consider the effect of population growth on the economic growth which could have been control variable to bite the influence of endogeneity in the model. therefore, further research should investigate the impact of population activities on the environment as key factors for co2 emission. even though energy consumption is not the cause of co2 emission in uganda, we expect the long-run sustained economic growth to make energy consumption to be a key driver that will propel future emission like what is happening in china, where there is a huge utilisation of fossil fuels in construction and manufacturing sectors (jiang et al., 2019; yang et al., 2020; zhu and shan, 2020). the long-run scaled effect of economic growth and energy consumption on the environment can be mitigated by creating public awareness on the importance of green investments, supporting and adopting the clean use of energy technologies such as solar, hydro, geothermal and wind. references adom, p.k., bekoe, w., amuakwa-mensah, f., mensah, j.t., botchway, e. (2012), carbon dioxide emissions, economic growth, industrial structure, and technical efficiency: empirical evidence from ghana, senegal, and morocco on the causal dynamics. energy, 47(1), 314-325. akadiri, s.s., bekun, f.v., taheri, e., akadiri, a.c. (2019), carbon emissions, energy consumption and economic growth: a causality evidence. international journal of energy technology and policy, 15(2-3), 320-336. alam, m.j., begum, i.a., buysse, j., rahman, s., van huylenbroeck, g. (2011), dynamic modeling of causal relationship between energy consumption, co2 emissions and economic growth in india. renewable and sustainable energy reviews, 15(6), 3243-3251. ang, j.b. (2007), co2 emissions, energy consumption, and output in france. energy policy, 35(10), 4772-4778. appiah, k., du, j., yeboah, m., appiah, r. (2019), causal relationship between industrialization, energy intensity, economic growth and carbon dioxide emissions: recent evidence from uganda. international journal of energy economics and policy, 9(2), 237. appiah, m.o. (2018), investigating the multivariate granger causality between energy consumption, economic growth and co2 emissions in ghana. energy policy, 112, 198-208. bamwesigye, d., kupec, p., chekuimo, g., pavlis, j., asamoah, o., darkwah, s.a., hlaváčková, p. (2020), charcoal and wood biomass utilization in uganda: the socio economicand environmental dynamics and implications. sustainability, 12(20), 8337. beard, e., marsden, j., brown, j., tombor, i., stapleton, j., michie, s., west, r. (2019), understanding and using time series analyses in addiction research. addiction, 114(10), 1866-1884. bunn, d.w., fezzi, c. (2008), a vector error correction model of the interactions among gas, electricity and carbon prices: an application to the cases of germany and the united kingdom. cheltenham: markets for carbon and power pricing in europe: theoretical issues and empirical analyses. p145-159. chang, c.c. (2010), a multivariate causality test of carbon dioxide emissions, energy consumption and economic growth in china. applied energy, 87(11), 3533-3537. destek, m.a., aslan, a. (2017), renewable and non-renewable energy consumption and economic growth in emerging economies: evidence from bootstrap panel causality. renewable energy, 111, 757-763. dickey, d.a., fuller, w. a. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica: journal of the econometric society, 1981, 1057-1072. dinda, s. (2004), environmental kuznets curve hypothesis: a survey. ecological economics, 49(4), 431-455. dogan, e. (2016), analyzing the linkage between renewable and nonrenewable energy consumption and economic growth by considering structural break in time-series data. renewable energy, 99, 11261136. engle, r.f., granger, c.w. (1987), co-integration and error correction: representation, estimation, and testing. econometrica: journal of the econometric society, 1987, 251-276. fan, w., hao, y. (2020), an empirical research on the relationship amongst renewable energy consumption, economic growth and foreign direct investment in china. renewable energy, 146, 598-609. gou. (2015), environment and water ministry: water and environment sector performance report. government of uganda. available from: http://www.mwe.go.ug halicioglu, f. (2009), an econometric study of co2 emissions, energy consumption, income and foreign trade in turkey. energy policy, 37(3), 1156-1164. hamilton, j.d. (2020), time series analysis. united states: princeton university press. held, d., roger, c. (2018), three models of global climate governance: from kyoto to paris and beyond. global policy, 9(4), 527-537. horowitz, c.a. (2016), paris agreement. international legal materials, 55(4), 740-755. jiang, p., yang, h., ma, x. (2019), coal production and consumption analysis, and forecasting of related carbon emission: evidence from china. carbon management, 10(2), 189-208. johansen, s. (1988), statistical analysis of cointegration vectors. journal of economic dynamics and control, 12(2-3), 231-254. kuznets, s. (1955), economic growth and income inequality. the american economic review, 45, 1-28. lütkepohl, h. (2010), variance decomposition. in: macroeconometrics and time series analysis. london: palgrave macmillan. p369-371. ma, x., wang, c., dong, b., gu, g., chen, r., li, y., li, q. (2019), carbon emissions from energy consumption in china: its measurement and driving factors. science of the total environment, 648, 1411-1420. markandya, a., cabot-venton, c., beucher, o. (2015), economic assessment of the impacts of climate change in uganda. otim, et al.: the effects of gross domestic product and energy consumption on carbon dioxide emission in uganda (1986-2018) international journal of energy economics and policy | vol 12 • issue 1 • 2022 435 united kingdom: cdkn. mawejje, j., mawejje, d.n. (2016), electricity consumption and sectoral output in uganda: an empirical investigation. journal of economic structures, 5(1), 21. menegaki, a.n., tugcu, c.t. (2016), the sensitivity of growth, conservation, feedback and neutrality hypotheses to sustainability accounting. energy for sustainable development, 34, 77-87. menyah, k., wolde-rufael, y. (2010), energy consumption, pollutant emissions and economic growth in south africa. energy economics, 32(6), 1374-1382. ozturk, i., acaravci, a. (2010), co2 emissions, energy consumption and economic growth in turkey. renewable and sustainable energy reviews, 14(9), 3220-3225. phillips, p.c., perron, p. (1988), testing for a unit root in time series regression. biometrika, 75(2), 335-346. protocol, k. (1997), united nations framework convention on climate change. kyoto protocol, kyoto, 19, 497. rahman, m.m., velayutham, e. (2020), renewable and non-renewable energy consumption-economic growth nexus: new evidence from south asia. renewable energy, 147, 399-408. rou. (2020), third national development plan (ndpiii) 2020/212024/25: uganda vision 2040. the republic of uganda. tamil nadu: rou. sadik-zada, e.r., loewenstein, w. (2020), drivers of co2-emissions in fossil fuel abundant settings: (pooled) mean group and nonparametric panel analyses. energies, 13(15), 3956. samuelson, r.d. (2014), the unexpected challenges of using energy intensity as a policy objective: examining the debate over the apec energy intensity goal. energy policy, 64, 373-381. sekantsi, l.p., okot, n. (2016), electricity consumption-economic growth nexus in uganda. energy sources, part b: economics, planning, and policy, 11(12), 1144-1149. sghari, m.b.a., hammami, s. (2016), energy, pollution, and economic development in tunisia. energy reports, 2, 35-39. walters, d. (2021), lumpy social goods in energy decarbonization: why we need more than just markets for the clean energy transition. colorado: university of colorado law review, forthcoming. wolf, s., potluri, v.a. (2018), uganda’s oil: how much, when, and how will it be governed? (no. 2018/179). wider working paper. finland: world institute for development economics research yang, j., cai, w., ma, m., li, l., liu, c., ma, x., chen, x. (2020), driving forces of china’s co2 emissions from energy consumption based on kaya-lmdi methods. science of the total environment, 711, 134569. zhang, y.j., da, y.b. (2015), the decomposition of energy-related carbon emission and its decoupling with economic growth in china. renewable and sustainable energy reviews, 41, 1255-1266. zhu, b., shan, h. (2020), impacts of industrial structures reconstructing on carbon emission and energy consumption: a case of beijing. journal of cleaner production, 245, 118916. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 4 • 2023394 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(4), 394-403. antecedents of workplace energy saving behaviour: an integration of the theory of planned behaviour and norm activation model olawale fatoki* department of business management, university of limpopo, private bag x1314, sovenga, 0727, south africa. *email: olawale.fatoki@ul.ac.za received: 14 june 2022 accepted: 29 april 2023 doi: https://doi.org/10.32479/ijeep.13301 abstract hotels are energy intensive facilities and have contributed to environmental problems such as high consumption of natural resources, high emissions of carbon dioxide and waste pollution. therefore, it is important to understand the factors that can reduce energy (electricity) consumption in hotels. the study examined the antecedents of employee energy saving behaviour in hotels by integrating the theory of planned behaviour (tpb) and the norm activation model (nam). data was collected from the respondents through the cross-sectional survey method. the partial least square structural equation modelling (pls sem) was used to analyse data and test the hypotheses. the results indicated that two tpb constructs (attitude and perceived behavioural control) are significantly positively related to energy saving intention. in addition, three nam constructs (awareness of consequences, ascription of responsibility and personal norms) are significantly positively related to energy saving intention. energy saving behaviour is influenced by intention. recommendations focus on awareness about the negative effects of energy consumption on the environment through education and training. keywords: employees, hotels, energy saving behaviour, theory of planned behaviour, norm activation model jel classifications: m10, m11 1. introduction energy plays a significant role in human lives and in the socioeconomic development of countries. energy consumption per capita is one of the significant indicators of economic development (esen and bayrak, 2017). in recent times, energy consumption has significantly increased in many countries due to population growth, urbanisation and increasing levels of industrialisation (alshami and sabah, 2019).the most widely used energy sources for the generation of electricity in many countries are fossil fuels especially coal, oil and natural gas (yildiz, 2018). although the production and use of environmentally friendly renewable sources have increased, fossil fuels are still of vital importance in meeting global energy needs (international energy agency, 2021). coal dominates south africa’s energy resource base and approximately 77% of the energy needs of the country are powered by coal (department of mineral resources and energy, 2021).the burning of fossil fuel to generate energy releases stored carbon and other greenhouses gases into the atmosphere (united states environmental protection agency, 2022). an excess amount of greenhouse gases in the atmosphere is one of the major causes of air and water pollution and global warming (martins et al., 2019). one of the fastest, cheapest and safest ways to mitigate climate change is to improve energy efficiency and reduce energy use especially electricity demand (sorrell, 2015). energy-saving behaviours are pro-environment behaviours that help reduce the use of fossil fuels and mitigate climate change (hussain et al., 2021). energy-saving behaviours can be described as practices that reduce energy consumption (maqbool and haider, 2021). this journal is licensed under a creative commons attribution 4.0 international license fatoki: antecedents of workplace energy saving behaviour: an integration of the theory of planned behaviour and norm activation model international journal of energy economics and policy | vol 13 • issue 4 • 2023 395 energy saving behaviour can be divided into purchasing energy saving behaviour (energy efficiency) and habitual or daily energy saving behaviour (azizi et al., 2019). purchasing energy saving behaviour focuses on the use of energy efficient equipment or new technologies without changing lifestyles to reduce energy use (karlin et al., 2014). habitual energy saving behaviour centres on changes to certain habits or adjustments to certain behaviours to reduce energy use (wang et al., 2018). despite the significance of energy efficiency, changes in human behaviour are important because gains related to technical efficiency from energy efficient appliances tend to be overtaken by consumption growth (steg and vlek, 2009; wang et al., 2018). energy conservation such as turning down heating, using less air-conditioning, reducing commuting by working from home, car-pooling or using public transport can significantly help to reduce energy use, reduce cost of electricity to individuals and businesses, reduce energy dependence and ensure energy security (sorell, 2015; international energy agency, 2022). climate change is largely anthropogenic and the occupants of buildings can make a significant reduction to energy consumption through behavioural change (paone and bacher, 2018; lynas et al., 2021). energy saving behaviour by individuals in the workplace is a major factor in reducing overall energy use (leygue et al., 2017). the main form of energy consumption by employees at work is electricity (zhang et al., 2014). therefore, it is important to understand the determinants of employee energy (electricity) saving behaviour in the workplace (carrus et al., 2021). the theoretical frameworks for explaining individual proenvironmental behaviour include the theory of planned behaviour (tpb), the norm activation model (nam) and the value belief norm theory (vbn) (schwartz and howard, 1981; ajzen, 1991; stern, 2000). this is because the two major approaches to predict individual pro-environmental behaviour are self-interest motives and pro-social motives (shin et al., 2018). self-interest motives suggest that individual engage in pro-environmental behaviour because of personal interest (such as developing a favourable attitude towards pro-environmental behaviour. self-interest motives can be linked to attitudinal theories such as the theory of reasoned action (tra) and the tpb (fishbein and ajzen, 1977; ajzen, 1991). pro-social motives are linked to moral considerations in pro-environmental behaviour and can be explained by the nam and vbn (schwartz and howard, 1981; stern, 2000). both the tpb and the nam have been used separately to explain individual pro-environmental behaviour (der werff and steg, 2015; du and pan, 2021). however, pro-environmental behaviour by individuals is usually a mixture of self-interest motives ad pro-social concerns (budovska et al., 2020). in addition, the use of an integrated model addresses the shortcomings of using a single theory to explain pro-environmental behaviour (liu et al., 2017). while the nam is more internal and argues that individual pro-environmental behaviour is derived from personal norms, the tpb is more external with the individual taking into consideration the external factors such as subjective norms (wang et al., 2018). the aim of the study is to predict energy saving behaviour of hotel employees by integrating the tpb and the nam. the study will be significant in the following ways. first, current efforts to reduce energy use in workplaces have primarily focused on appliances, system efficiency and improvement of physical infrastructure. however, investigations that focus on employees with no energy responsibilities save are sparse (leygue et al., 2017). second, studies have integrated the tpb and the nam into a single model for predicting employee energy saving behaviour in the context of firms in developing countries are scarce (hien and chi, 2020). third, understanding the antecedents of energy conservation in the workplace will help to reduce energy use, increase energy security and positively contribute to the achievement of net zero emission target (united nations climate change conference, 2021). 2. literature review 2.1. tpb and nam the tpb is a psychological theory that links beliefs to behaviour and was developed to improve the predictive power of the tra. according to the tra by fishbein and ajzen (1975), the intention to perform a behaviour is dependent on a positive evaluation of the behaviour (attitude) and the belief that significant others want the individual to perform the behaviour (subjective norms). intention is associated with actual behaviour (fishbein and ajzen, 1975). the tpb by ajzen (1991) proposes that the intention to perform a behaviour is shaped by three factors namely attitude, subjective norms and perceived behavioural control (pbc). therefore, in developing the tpb, ajzen added pbc (the degree to which an individual is of the belief that he/she can perform a behaviour) to the two constructs of the tra. the tpb has been used as the theoretical foundation for studies on pro-environmental behaviour and energy conservation behaviour (leeuw et al., 2015; yadav and pathak, 2017; macovei, 2015; canova and manganelli, 2020). although the tpb has demonstrated its usefulness in predicting behaviour, its use is limited for some behaviours and contexts. ajzen (1991) argues that the tpb is open to the addition of new constructs provided they can improve the explanatory power of the theory. human behaviours are complex and their prediction through the three tpb constructs may be impossible. therefore, it is necessary to employ other behavioural models to predict some behaviours especially pro-environmental behaviour that is not only based on rational decision-making but also moral obligations (esfandiar et al., 2019; sang et al., 2020). the norm activation model (nam) by schwartz (1977) proposes a sequential model that links awareness of consequences to ascription of responsibility, personal norms and prosocial intention or behaviour. awareness of consequences describes an individual’s perception of the severity of his/her behaviour on the welfare of other people. ascription of responsibility refers to the feeling of responsibility for the negative consequences that can occur from an individual’s failure to act. personal norms describe a sense of moral obligation to abstain from or engage in certain behaviour. the nam has been used as the theoretical foundation of studies on pro-environmental behaviour and energy conservation behaviour (der werff and steg, 2015; fang et al., 2019; li et al., 2019). the tpb is a rational selection model that ignores the effects of irrational and altruistic motives and cannot fully explain proenvironmental behaviour (zhang et al., 2017) the nam does fatoki: antecedents of workplace energy saving behaviour: an integration of the theory of planned behaviour and norm activation model international journal of energy economics and policy | vol 13 • issue 4 • 2023396 not take into consideration the variables of the rational choice model and does not fully describe the factors that can affect proenvironmental behaviour (han, 2015). therefore, the integration of the tpb and nam in the context of pro-environmental behaviour takes into consideration individual self-interested and rational motives and belief based on norms and morality (shi et al., 2017; li et al., 2019; sang et al., 2020). 2.2. hypotheses 2.2.1. tpb and employee energy saving intention yadak and pathak (2017) used the tpb to investigate consumer green purchasing intention and behaviour in india. the findings of the study indicate that the three constructs of the tpb are positively related to intention to purchase green products. setyawan et al. (2018) used the tpb as the theoretical framework to examine young consumers’ intention to purchase green products. the findings indicate that attitude does not significantly affect intention, however, the effects of subjective norms and perceived behavioural control are significant. in the context of energy saving behaviour, macovei (2015) finds that attitude has a significant positive relationship with intention to conserve energy. however, the effects of subjective norms and perceived behavioural control on intention are insignificant. the findings of the study by liu et al. (2020) indicate that attitude is the most significant factor in household energy conservation intention. the effect of perceived behavioural control is also significant. however, the relationship between subjective norms and intention is insignificant. canova and manganelli (2020) find that the three tpb constructs are positively related to intention to conserve energy at work. dixon et al. (2015) find that attitude, subjective norms (injunctive and descriptive) and perceived behavioural control are significantly positively related to intention to conserve energy at work. the findings of the study by chen and chen (2021) show that that attitude and perceived behavioural control are positively correlated to employee energy conservation habit. the effect of subjective norm is insignificant. based on the tpb, the following hypotheses are developed. h1: attitude towards energy saving and employee energy saving behaviour are significantly positively related. h2: subjective norms and employee energy saving behaviour are significantly positively related. h3: perceived behavioural control and employee energy saving behaviour are significantly positively related. 2.2.2. nam and energy saving intention 2.2.2.1. awareness of consequences zhang et al. (2013) find that awareness of consequences is positively related to ascription of responsibility in the context of electricity saving. the findings of the study by setiawan et al. (2021) indicate that awareness of consequences has a significant positive relationship with personal norms. awareness of consequences towards bin use has a positive effect on personal norms toward binning behaviour (esfandiar et al., 2020). wan et al. (2014) in a study that integrated the tpb and nam to predict recycling intention in hong kong point out that a high level of awareness of consequences will increase the intention to perform recycling of waste. the study by wan et al. (2014) finds that awareness of consequences has a significant positive relationship with recycling intention. fang et al. (2019) used the nam to investigate the pro-environmental behaviour of public servants in taiwan. the findings indicate that awareness of consequences positively affects employee pro-environmental behaviour. dalvi-esfahani et al. (2017) in a study that used nam to investigate the adoption of green information systems find that awareness of adverse consequences of environmental conditions positively affects the intention to adopt green information systems. in addition, awareness of consequences and ascription of responsibility are significantly positively related. zhang et al. (2013) remark that the consumption of electricity leads to energy insecurity and environmental problems. if employees are aware of these negative effects, they are likely to develop feelings of moral obligation to save electricity. therefore, awareness of consequences can positively influence employee energy saving behaviour at work. de grrot and steg (2009) and onwezen et al. (2013) remark that studies on nam have used personal norms either as a mediator or a moderator in a mediation model, it is assumed that awareness of consequences affects personal norms through ascription of responsibility. in a moderation model, the effect of personal norms on behaviour is moderated by awareness of consequences and ascription of responsibility. de groot and steg (2009) compared five studies on the moderating and mediating effects of personal norms and find a strong evidence that nam is a mediating model. the findings by de groot and steg (2009) reveal that a person must be aware of consequences of a behaviour before developing responsibility for it. thus, the feelings of responsibility trigger personal norms, which then encourage individual behaviour. the findings of the study by onwezen et al. (2013) show that awareness of consequences positively influences ascription of responsibility and this in turn affects personal norms. dalvi-esfahani et al. (2017) find that the relationship between awareness of consequences of adverse environmental condition and intention to adopt green information system is partially mediated by personal norms. wang et al. (2016) in a study on the intention to recycle e-waste in china find that both awareness of consequences and ascription of responsibility activate personal norms which in turn positively affect the recycling intention of residents. it is hypothesised that: h4: awareness of consequences is significantly positively related to ascription of responsibility. h5: awareness of consequences is significantly positively related to personal norms. h6: awareness of consequences is significantly positively related to intention. h7: the relationship between awareness of consequences and personal norms is mediated by ascription of responsibility h8: the relationship between awareness of consequences and intention is mediated by personal norms. 2.2.2.2. ascription of responsibility ascription of responsibility reflects the feeling of responsibility by an individual of the adverse effects of not acting and is one of the factors that can influence pro-environmental behaviour (steg and de groot, 2010). xu et al. (2020) examine the effect of ascription of responsibility on intention to save energy at work. ascription of responsibility is particularly important in the fatoki: antecedents of workplace energy saving behaviour: an integration of the theory of planned behaviour and norm activation model international journal of energy economics and policy | vol 13 • issue 4 • 2023 397 workplace because occupants in the office obtain no financial benefits for saving energy and so tend to see the responsibility to save energy as that of their organisation and not their own. this lack of responsibility may negatively influence the need to change behaviour. the study finds that ascription of responsibility positively affects employee energy saving behaviour at work. the findings of the study by shin et al. (2018) indicate a significant positive relationship between ascription of responsibility and personal norm. han (2015) in a study on the pro-environmental behaviour of travellers in the green context finds that ascription of responsibility is positively related to the sense of obligation to take pro-environmental action. zhang et al. (2013) remark that when employees have ascription of responsibility especially responsibility for the negative consequences of electricity use, this is likely to trigger personal norm about electricity saving in a firm. the study finds a significant personal relation between ascription of responsibility and personal norm. mamun et al. (2022) in a study on the energy conservation behaviour of malaysian youth find that ascription of responsibility positively affects personal norm. it is hypothesised that: h9: ascription of responsibility is significantly positively related to personal norms. h10: ascription of responsibility is significantly positively related to intention. h11: the relationship between ascription of responsibility and intention is mediated by personal norms. 2.2.2.3. personal norms personal norms have a positive influence on pro-environmental intention and behaviour because it describes the feelings of moral obligations to do the appropriate thing (wang et al., 2019; de groot et al., 2021). wang et al. (2016) find that personal norms are positively related to the intention to adopt hybrid electric vehicles in china. zhang et al. (2013) remark that in the context of electricity saving in a firm, personal norms refer to an employee’s moral obligation to save electricity. the study finds that personal norms is positively related to energy saving behaviour. wang et al. (2018) find that personal norms positively affect urban residents’ energy saving behaviour. hien and chi (2020) remark that individuals with high levels of personal normss will have the feeling of responsibility to save energy. the study finds that personal norms significantly influence household electricity saving intention. the findings of the study by wang et al. (2019) show a significant positive relationship between personal norms and employee workplace energy saving behaviour. it is hypothesised that: h12: personal norms and employee energy saving intention are significantly positively related. 2.2.2.4. intention and energy saving behaviour intention is the antecedent of behaviour (ajzen, 1991). yadak and pathak (2017) used the tpb to investigate consumer green purchasing intention and behaviour in india. the findings of the study indicate that intention has a significant positive relationship with green purchase behaviour. gkargkavouzi et al. (2019) in a study that focused on environmental behaviour in the private sphere context find that behavioural intention positively affects the performance of the behaviour. macovei (2015) and mamun et al. (2022) find that intention to conserve energy positively affects energy conservation behaviour. it is hypothesised that: h13: intention to save energy is positively related to employee energy saving behaviour. figure 1 depicts the conceptual model of the study. 3. research methodology the study employed the cross-sectional survey method to collect data from hotel employees. according to cingoski and petrevska (2018), hotels are generally energy intensive facilities with associated high energy costs and are ranked amongst the top five with respect to energy consumption in the tertiary building sector. data was collected with the assistance of a data collection agency from hotel employees in the johannesburg, pretoria and polokwane in the gauteng and limpopo provinces of south africa. the permissions of both the participation hotels and their employees were sought and a pilot study was conducted before actual data collection to improve face and content validity. the self-administered questionnaire method was used to collect data from the respondents who were assured of anonymity and confidentiality. the questions were adopted from previous studies and were anchored on the five point likert scale with “1 strongly disagree and 5” strongly agree. appendix one shows the measures of the constructs of the study. data was analysed using the partial least square structural equation modelling (pls sem). according to hair et al. (2019). pls sem is used to evaluate the measurement of latent variables and test relationships between latent variables pls-sem normsally achieves higher levels of statistical power and demonstrates much better convergence behaviour than cb-sem. 4. results 4.1. response rate and biographical details of the respondents 930 questionnaires were distributed during data collection and 444 returned and found usable. table 1 depicts the biographical details of the respondents. table 2 depicts the measurement model. the results show that the factor loadings are above 0.708, cronbach’s alpha >0.700, average variance explained >0.500. thus convergent validity is established. table 3 depicts the results of the fornell lacker criterion. in addition, the values of the htmt are lower than 0.850 as depicted by table 4 thus confirming adequate discriminant validity. 4.2. structural model the evaluation of the structural model considered the common method bias (cmb), the r2, the q2, and the evaluation of the path coefficients. the cmd values were lower than the 3.3 threshold and the integrated model’s (r2) explained 68.5% of the variance of intention to save energy. the gof of 0.337, and q2 of 0.415 suggest the significant predictive power of the model. the effect size values range from 0.277 to 0.291and the standardised root fatoki: antecedents of workplace energy saving behaviour: an integration of the theory of planned behaviour and norm activation model international journal of energy economics and policy | vol 13 • issue 4 • 2023398 mean square residual (srmr) obtained in the study is 0.01. table 5 depicts the results of the testing of the hypotheses. the results (β = 0.264, t = 7.409, p < 0.01) show that attitude and intention are significantly positively related supporting hypothesis one. the results (β = 0.058, t = 0.103, p > 0.05) depict an insignificant relationship between subjective normss and intention. hypothesis two not supported. the results (β = 0.204, t = 3.008, p < 0.05) indicate that perceived behavioural control and intention are significantly positively related, supporting hypothesis three. the results (β = 0.198, t = 5.071, p < 0.05) show that awareness of consequences and ascription of responsibility are significantly positively related supporting hypothesis four. the results (β = 0.311, t = 3.402, p < 0.01) depict an significant positive relationship between awareness of consequences and personal norms. hypothesis five is supported. the results (β = 0.207, t = 4.481, p < 0.01) indicate that awareness of consequences and intention are significantly positively associated, supporting hypothesis six. the results (β = 0.192, t = 3.737, p < 0.05) show that ascription of responsibility and personal norms are significantly positively related supporting hypothesis nine the results (β = 0.208, t = 4.102, p > 0.01) depict a significant positive relationship between ascription of responsibility and intention. hypothesis ten is supported. the results (β = 0.277, t = 5.609, p < 0.05) indicate that personal norms and intention are significantly positively associated, supporting hypothesis eleven. the results (β = 0.195, t = 3.664, p < 0.05) show that intention and behaviour are significantly positively related supporting hypothesis twelve. the mediation results are depicted by table 6. the results indicate that the direct effects and indirect effects are significant. also, the variance accounted (vaf) value bigger than 80% represents full mediation, a vaf value of between 20% and 80% means a partial mediation, while a value below 20% means no mediation. in addition, for complementary mediation, the indirect effect and the direct effect are significant and point in the same direction. for competitive mediation, the indirect effect and the direct effect are significant but point in opposite directions while for indirect-only mediation, the indirect effect is significant, but not the direct effect (hair et al., 2019). the vaf values are below 80% and a complimentary partial mediation is confirmed. the results indicate that the relationship between awareness of consequences and personal norms is partially mediated by ascription of responsibility supporting hypothesis 7. also, the results show that the relationship between awareness of consequences and intention is fully mediated by personal norms supporting hypothesis 8. in addition, the results indicate that the relationship between ascription of responsibility and intention is partially mediated by personal norms supporting hypothesis 11. 5. discussion the hospitality industry positively contributes to job creation, poverty reduction and socio-economic development. however, the industry is generally energy intensive facilities with associated high energy and environmental costs. therefore, it is important to understand the factors that can help to reduce energy (electricity) figure 1: conceptual model table 1: biographical details of the respondents biographical details no of respondents gender male female 229 215 age 21-30 31-40 41-50 51-60 135 185 98 26 educational qualification matric above matric 256 188 fatoki: antecedents of workplace energy saving behaviour: an integration of the theory of planned behaviour and norm activation model international journal of energy economics and policy | vol 13 • issue 4 • 2023 399 consumption by hotels. the study examined the antecedents of employee energy saving behaviour in hotels by integrating the tpb and the nam. this approach enables the researcher to take into consideration employee self-interested and rational motives and belief based on normss and morality. the findings indicated that two of three constructs of the tpb, attitude and perceived behavioural control are significantly positively related to energy saving intention. the effect of subjective normss is insignificant. the findings suggest that when an employee has a positive attitude towards energy saving, he/she will develop the intention to save energy. in addition, employees are likely to develop intention to save energy if they have the necessary skills and resources to do so. the findings are consistent with prior empirical studies that have used the tpb to investigate energy saving behaviour. macovei (2015) finds that attitude has a significant positive relationship with intention to conserve energy. the findings of the study by liu et al. (2020) show that attitude and perceived behavioural control are significant factors in household energy conservation intention. canova and table 2: measurement model construct measurement item factor loading cronbach’s alpha composite reliability ave awareness of consequences (awa) awa1 0.804 0.811 0.849 0.585 awa2 0.782 awa3 0.743 awa4 0.729 ascription of responsibility (asc) asc1 0.772 0.775 0.867 0.620 asc2 0.801 asc3 0.826 asc4 0.749 personal norms (per) per1 0.764 0.782 0.861 0.608 per2 0.807 per3 0.799 per4 0.748 attitude (att) att1 0.813 0.860 0.852 0.591 att2 0.782 att3 0.749 att4 0.727 subjective norms (sub) sub1 0.764 0.770 0.803 0.576 sub2 0.782 sub3 0.731 perceived behavioural control (per) per1 0.829 0.808 0.833 0.626 per2 0.801 per3 0.738 intention (int) int1 0.844 0.841 0.839 0.635 int2 0.804 int3 0.739 behaviour (beh) beh1 0.819 0.762 0.901 0.564 beh2 0.729 beh3 0.808 beh4 0.731 beh5 0.747 beh6 0.726 beh7 0.759 table 4: htmt con awa asc per att sub per int beh awa asc 0.588 per 0.604 0.617 att 0.531 0.588 0.602 sub 0.601 0.597 0.608 0.611 pec 0.618 0.603 0.557 0.618 0.577 int 0.600 0.651 0.628 0.639 0.572 0.608 beh 0.604 0.552 0.607 0.672 0.699 0.593 0.606 table 3: fornell-lacker con awa asc per att sub per int beh awa 0.765 asc 0.541 0.787 per 0.601 0.526 0.780 att 0.499 0.416 0.508 0.769 sub 0.373 0.388 0.407 0.386 0.760 pec 0.562 0.601 0.582 0.495 0.608 0.791 int 0.693 0.601 0.555 0.487 0.599 0.542 0.797 beh 0.505 0.402 0.557 0.538 0.604 0.615 0.588 0.751 diagonals in bold signify the square root of the ave while the other figures depict the correlations. table 5: path coefficient and t‑statistics hypothesised path path coefficient t-statistics decision h1 att→int 0.264 7.409* supported h2 sub→int 0.058 0.103 rejected h3 per→int 0.204 5.071** supported h4 awa→asc 0.198 2.808** supported h5 awa→per 0.311 3.402* supported h6 awa→int 0.207 4.481* supported h9 asc→per 0.192 3.737** supported h10 asc→int 0.208 4.102* supported h11 per→int 0.277 5.609** supported h12 int→beh 0.195 3.664** supported *p<0.01; **<0.05 fatoki: antecedents of workplace energy saving behaviour: an integration of the theory of planned behaviour and norm activation model international journal of energy economics and policy | vol 13 • issue 4 • 2023400 manganelli (2020) find that attitude and perceived behavioural control are positively related to intention to save energy at work. the findings of the study by chen and chen (2021) show that that attitude and perceived behavioural control are positively correlated to employee energy conservation habit. the three constructs of nam are positively related to intention to save energy. in addition, the findings indicate that awareness of consequences is positively related to ascription of responsibility, personal normss and intention. in addition, the findings show that the relationship between awareness of consequences and personal norms is mediated by ascription of responsibility. also, the relationship between awareness of consequences and intention is mediated by personal norms. the findings suggest that when employees are aware of the negative consequences of energy consumption, this will affect their moral obligation and intention to save energy. the findings are consistent with the results of prior empirical studies. zhang et al. (2013) find that awareness of consequences is positively related to ascription of responsibility and personal norms in the context of electricity saving. the findings of the study by onwezen et al. (2013) show that awareness of consequences positively influences ascription of responsibility and this in turn affects personal norms. dalvi-esfahani et al. (2016) find that the relationship between awareness of consequences of adverse environmental condition and intention to adopt green information system is partially mediated by personal norms. wang et al. (2018) find that both awareness of consequences and ascription of responsibility activate personal norms which in turn positively affect the recycling intention of residents. the findings indicated that ascription of responsibility is significantly positively related to personal norms and intention. in addition, the relationship between ascription of responsibility and intention is mediated by personal norms. the findings suggest that the feelings of responsibility by an individual of the adverse effects of not saving energy can positively affect energy saving behaviour. the findings are consistent with the results of prior empirical studies. zhang et al. (2013) find a significant personal relation between ascription of responsibility and personal norms. mamun et al. (2022) find that ascription of responsibility positively affects personal norms. xu et al. (2020) find that ascription of responsibility positively affects employee energy saving behaviour at work. the findings indicate that personal norms has a positive and significant impact on intention to save energy. personal norms describes the feelings of moral obligations to do the appropriate thing. the findings are consistent with prior empirical studies. zhang et al. (2013) find that personal norms are positively related to energy saving behaviour. wang et al. (2018) find that personal norms positively affects urban residents’ energy saving behaviour. mamun et al. (2022) finds that personal norms affects the energy conservation intention of malaysian youth. the findings of the study by wang et al. (2019) show a significant positive relationship between personal norms and employee workplace energy saving behaviour. the findings indicated that intention to save energy is positively related to employee energy saving behaviour. ajzen (1991) points out that intention is the antecedent of behaviour. macovei (2015) find that intention positively affects energy conservation behaviour. mamum et al. (2022) find that intention to conserve energy positively affects energy conservation behaviour. 6. conclusion the study examined the antecedents of employee workplace energy saving behaviour by integrating the tpb and nam. the findings showed that two tpb constructs, attitude and perceived behavioural control are significantly positively related to energy saving behaviour. the findings also indicated that three nam constructs, awareness of consequences, ascription of responsibility and personal norms are positively related to intention to save energy. in addition, energy saving intention has a significant positive effect on energy saving behaviour. theoretically, the findings of the study confirm the applicability of the integrated tpb and nam in explaining energy saving behaviour by employees in the workplace. two constructs of the tpb and three constructs of nam are positively linked to employee energy saving intention. the findings of the study provide empirical support for combining tpb and nam variables in the context of employee energy saving behaviour. the findings of the study have practical implications for hospitality firms. hotel owners must take into consideration employees in their efforts to reduce energy consumption. training and organisational policy on energy conservation can help to develop a favourable attitude. to improve personal norms, awareness of consequences and ascription of responsibility, there is the need for enhanced publicity campaign by government about the negative effects of energy consumption on the environment. the study has the following limitations: data was collected from employees of hospitality firms in only three south african cities. the generalisability of the findings can be improved by expanding data collection to hotels in other cities of south africa. self-report bias might have occurred during data collection from employees. table 6: mediation results mediation path indirect effect total effect and t-statistics confidence interval bias (corrected) decision vaf ll ul h7awa→asc→per 0.194* 0.308* (1.499) 0.064 0.228 accepted (partial mediation) 62.99% h8awa→per→int 0.139* 0.171* (1.116) 0.046 0.182 accepted (full mediation) 81.29% h11asc→per→int 0.171** 0.302** 0.052 0.177 accepted (partial mediation) 56.62% *p<0.01; **<0.05 fatoki: antecedents of workplace energy saving behaviour: an integration of the theory of planned behaviour and norm activation model international journal of energy economics and policy | vol 13 • issue 4 • 2023 401 therefore, it may be necessary to also collect data from the owners/managers of hotels about energy conservation behaviour of employees. demographic factors such as age and gender can moderate the relationship between intention and energy saving behaviour. these variables were not included in the study and can be examined by future research. the use of the cross-sectional research design limits causality and a longitudinal research approach by other studies can help to overcome this limitation. references ajzen, i. (1991), the theory of planned behaviour. organizational behaviour and human decision processes, 50, 179-211. ajzen, i., fishbein, m. (1980), understanding attitudes and predicting social behavior. englewood cliffs, nj: prentice-hall. alshami, m.a., sabah, a. (2019), the strategic importance of energy consumption to economic growth: evidence from the uae. international journal of energy economics and policy, 10(1), 114-119. azizi, z.m., azizi, n.s., abidin, n.z., mannakkara, s. (2019), making sense of energy-saving behaviour: a theoretical framework on strategies for behaviour change intervention. procedia computer science, 158(1), 725-734. budovska, v., delgado, a., øgaard, t. (2020), pro-environmental behaviour of hotel guests: application of the theory of planned behaviour and social norms to towel reuse. tourism and hospitality research, 20(1), 105-116. canova, l., manganelli, a.m. (2020), energy-saving behaviours in workplaces: application of an extended model of the theory of planned behaviour. europe’s journal of psychology, 16(3), 384-400. carrus, g., tiberio, l., mastandrea, s., chokrai, p., fritsche, i., klöckner, c.a., masson, t., vesely, s., panno, a. (2021), psychological predictors of energy saving behaviour: a meta-analytic approach. frontiers in psychology, 12, 648221. chen, c., chen, y. (2021), assessment of enhancing employee engagement in energy-saving behaviour at workplace: an empirical study. sustainability, 13(5), 2457. dalvi-esfahani, m., ramayah, t., rahman, a.a. (2017), moderating role of personal values on managers’ intention to adopt green is: examining norm activation theory. industrial management and data systems, 117(3), 582-604. de groot, j.i., steg, l. (2009), morality and prosocial behaviour: the role of awareness, responsibility, and norms in the norm activation model. journal of social psychology, 149(4), 425-449. department of mineral resources and energy. (2021), coal resources. available from: http://www.energy.gov.za/files/coal_frame.html [last accessed on 2022 feb 10]. der werff, e., steg, l. (2015), one model to predict them all: predicting energy behaviours with the norm activation model. energy research and social science, 6, 8-14. dixon, g., deline, m.b., mccomas, k.a., chambliss, l., hoffman, f. (2015), saving energy at the workplace: the salience of behavioural antecedents and sense of community. energy research and social science, 6, 121-127. du, j., pan, w. (2021), examining energy saving behaviours in student dormitories using an expanded theory of planned behaviour. habitat international, 107, 1-35. esen, o., bayrak, m. (2017), does more energy consumption support economic growth in net energy-importing countries? journal of economics, finance and administrative science, 22(42), 75-98. esfandiar, k., dowling, r., pearce, j., goh, e. (2020), personal norms and the adoption of pro-environmental binning behaviour in national parks: an integrated structural model approach. journal of sustainable tourism, 28(1), 10-32. fang, w., chiang, y., ng, e., lo, j. (2019), using the norm activation model to predict the pro-environmental behaviours of public servants at the central and local governments in taiwan. sustainability, 11(13), 3712. gao, l., wang s., li, j., li, h. (2017), application of the extended theory of planned behavior to understand individual’s energy saving behaviour in workplaces. resource conservation and recycling, 127, 107-113. gkargkavouzi, a., halkos, g., matsiori, s. (2019), environmental behaviour in a private-sphere context: integrating theories of planned behaviour and value belief norm, self-identity and habit. resources conservation and recycling, 148, 145-156. hair, j., risher, j., sarsstedt, m., ringle, c. (2019), when to use and how to report the results of pls-sem. european business review, 31, 2-24. han, h. (2015), travelers’ pro-environmental behaviour in a green lodging context: converging value-belief-norm theory and the theory of planned behaviours. tourism management, 47, 164-177. hien, n.n., chi, p.h. (2020), the factors affecting household electricity saving behaviours: a study in vietnam. international journal of sustainable development and planning, 15, 1241-1250. hussain, w.n.h., halim, l., chan, m.y., abd rahman, n. (2021), predicting energy-saving behaviour based on environmental values: an analysis of school children’s perspectives. sustainability, 13, 7644. international energy agency]. (2021), global electricity demand is growing faster than renewables, driving strong increase in generation from fossil fuels. available from. https://www.iea.org/ news/global-electricity-demand-is-growing-faster-than-renewablesdriving-strong-increase-in-generation-from-fossil-fuels [last accessed on 2022 feb 12]. international energy agency. (2022), playing my part. available from: https://www.iea.org/reports/playing-my-part [last accessed on 2022 feb 12]. karlin, b., davis, n., sanguinetti, a., gamble, k., kirkby, d., stokols, d. (2014), dimensions of conservation: exploring differences among energy behaviours. environment and behaviour, 46(4), 423-452. leeuw, a., valois, p., ajzen, i., schmidt, p. (2015), using the theory of planned behaviours to identify key beliefs underlying proenvironmental behaviours in high-school students: implications for educational interventions. journal of environmental psychology, 42, 128-138. leygue, c., ferguson, e., spence, a. (2017), saving energy in the workplace: why, and for whom? journal of environmental psychology, 53, 50-62. li, d., xu, x., chen, c., menassa, c. (2019), understanding energysaving behaviours in the american workplace: a unified theory of motivation, opportunity, and ability. energy research and social science, 51, 198-209. liu, x., wang, q., wei, h., chi, h., ma, y., jian, i. (2020), psychological and demographic factors affecting household energy-saving intentions: a tpb-based study in northwest china. sustainability, 12(3), 836. liu, y., sheng, h., mundorf, n., redding, c., ye, y. (2017), integrating norm activation model and theory of planned behavior to understand sustainable transport behaviour: evidence from china. international journal of environmental research and public health, 14(12), 1593. lynas, m., houlton, b., perry, s. (2021), greater than 99% consensus on human caused climate change in the peer-reviewed scientific literature. environmental research letters, 16(11), 114005. macovei, o. (2015), applying the theory of planned behaviour in predicting fatoki: antecedents of workplace energy saving behaviour: an integration of the theory of planned behaviour and norm activation model international journal of energy economics and policy | vol 13 • issue 4 • 2023402 proenvironmental behaviour: the case of energy conservation. acta universitatis danubius oeconomica, 11(4), 15-32. mamun, a., heyat, n., masud, m.m., yang, q., salameh, a., salleh, m. (2022), energy conservation behaviour among the malaysian youth: a study under the premises of value-belief-norm model. frontiers in energy research, 10, 1-10. maqbool, g., haider, z. (2021), the impact of individual behaviour on household energy saving. journal of economic impact, 3(1), 39-46. martins, f., felgueiras, c., smitkova, m., caetano, n. (2019), analysis of fossil fuel energy consumption and environmental impacts in european countries. energies, 12(6), 964. onwezen, m.c., antonides, g., bartels, j. (2013), the norm activation model: an exploration of the functions of anticipated pride and guilt in pro-environmental behaviour. journal of economic psychology, 39, 141-153. paone, a., jean-philippe, b. (2018), the impact of building occupant behavior on energy efficiency and methods to influence it: a review of the state of the art. energies, 11(4), 953. sang, p., yao, h., zhang, l., wang, s., wang, y., liu, j. (2020), influencing factors of consumers’ willingness to purchase green housing: a survey from shandong province, china. environment, development and sustainability, 22(5), 4267-4287. schwartz, s.h. (1977), normative influence on altruism. in: berkowitz, l., editor. advances in experimental social psychology. new york: academic press. p221-279. schwartz, s.h., howard, j.a. (1981), a normative decision-making model of altruism. in: rushton, j.p., sorrentino, r.m., editors. altruism and helping behaviour. hillsdale, nj: lawerence erlbaum. p89-211. setiawan, b., afiff, a., heruwasto, i. (2021), personal norm and proenvironmental consumer behaviour: an application of norm activation theory. asean marketing journal, 13(1), 36-43. setyawan, a., noermijati, n., sunaryo, s., aisjah, s. (2018), green product buying intentions among young consumers: extending the application of theory of planned behaviour. problems and perspectives in management, 16(2), 145-154. shi, h., fan, j., zhao, d. (2017), predicting household pm2.5-reduction behavior in chinese urban areas: an integrative model of theory of planned behavior and norm activation theory. journal of cleaner production, 145, 64-73. shin, y.h., im, j., jung, s.e., severt, k. (2018), the theory of planned behavior and the norm activation model approach to consumer behavior regarding organic menus. international journal of hospitality management, 69, 21-29. steg, l., de groot, j. (2010), explaining prosocial intentions: testing causal relationships in the norm activation model. british journal of social psychology, 49(4), 725-743. steg, l., vlek, c. (2009), encouraging pro-environmental behaviour: an integrative review and research agenda. journal of environmental psychology, 29(3), 309-317. stern, p.c. (2000), toward a coherent theory of environmentally significant behaviour. journal of social issues, 56(3), 407-425. united nations climate change conference. (2021), uniting the world to tackle climate change. available from: https://ukcop26.org [last accessed on 2022 feb 10]. united states environmental protection agency. (2022), sources of greenhouse gas emissions. available from: https://www.epa.gov/ ghgemissions/sources-greenhouse-gas-emissions [last accessed on 2022 feb 10]. wan, c., shen, g.q., yu, a. (2014), the moderating effect of perceived policy effectiveness on recycling intention. journal of environmental psychology, 37, 55-60. wang, b., zhang, b., gou, d., zhang, b., wang, z. (2018), analysis of factors influencing residents’ habitual energy-saving behaviour based on nam and tpb models: egoism or altruism? energy policy, 116, 68-77. wang, s., fan, j., zhao, d., yang, s., fu, y. (2016), predicting consumers’ intention to adopt hybrid electric vehicles: using an extended version of the theory of planned behavior model. transportation, 43(1), 123-143. wang, s., wang, j., ru, x., li, j., zhao, d. (2019), understanding employee’s electricity conservation behavior in workplace: do normative, emotional and habitual factors matter? journal of cleaner production, 215, 1070-1077. wang, z., guo, d., wang, x. (2016), determinants of residents’ e-waste recycling behaviour intentions: evidence from china. journal of cleaner production, 137, 850-860. xu, x., chen, c., li, d., menessa, c. (2020), energy saving at work: exploring the role of social norms, perceived control and ascribed responsibility in different office layouts. frontiers in built environment, 6, 1-12. yadav, r., pathak, g.s. (2017), determinants of consumers’ green purchase behavior in a developing nation: applying and extending the theory of planned behavior. ecological economics, 134, 114-122. yildiz, i. (2018), energy fundamentals. in: comprehensive energy systems. available from https://www.sciencedirect.com/ referencework/9780128149256/comprehensive-energy-systems [last accessed on 2022 feb 10]. zhang, x., geng, g., sun p. (2017), determinants and implications of citizens’ environmental complaint in china: integrating theory of planned behavior and norm activation model. journal of cleaner production, 166, 148-156. zhang, y., wang, z., zhou, g. (2013), antecedents of employee electricity saving behavior in organizations: an empirical study based on norm activation model. energy policy, 62, 1120-1127. zhang, y., wang, z., zhou, g. (2014), determinants of employee electricity saving: the role of social benefits, personal benefits and organizational electricity saving climate. journal of cleaner production, 66, 280-287. fatoki: antecedents of workplace energy saving behaviour: an integration of the theory of planned behaviour and norm activation model international journal of energy economics and policy | vol 13 • issue 4 • 2023 403 appendix one measures construct items adapted from awareness of consequences 1. electricity consumption at work exhausts available electricity. 2. electricity consumption at work damages the local ecological environment. 3. electricity consumption at work leads to global warming and contributes to climate change 4. electricity consumption at work can lead to negative consequences de groot and steg (2009); onwezen et al. (2013) zhang et al. (2013) ascription of responsibility 1. i feel partly responsible for the exhaustion of electricity. 2. i feel partly responsible for the impact of consumption on global warming 3. i feel partly responsible for the effect of electricity consumption on local environment. 4. i feel partly responsible for the negative consequences of electricity consumption. de groot and steg (2009); onwezen et al. (2013); zhang et al. (2013) personal norms 1. not saving electricity at work will be against my moral principles. 2. i would feel guilty if i do not save electricity at work 3. it is my moral obligation to save electricity at work. 4. i feel obliged to save electricity at work. de groot and steg (2009); onwezen et al. (2013); zhang et al. (2013) attitude 1. i think that saving electricity in my workplace is useful to protect the environment. 2. i think that saving electricity in my workplace is significant to reduce carbon emissions. 3. i think that saving electricity in my workplace is valuable to reduce electricity shortage. 4. i think that saving electricity in my workplace is a wise decision. ajzen (1991) and gao et al. (2017) subjective norms 1. my colleagues that that i should save electricity in the workplace. 2. my managers think that i should save electricity in the workplace. 3. other people that are important to me think that i should save electricity in the workplace. ajzen (1991) and gao et al. (2017) perceived behavioural control 1. i think that i am capable of saving electricity in my workplace. 2. i have the knowledge and skill to save electricity in the workplace. 3. whether or not i save electricity is completely up to me. ajzen (1991) and gao et al. (2017) intention 1. i am willing to save electricity at work. 2. i intend to save electricity at work 3. i plan to save electricity at work. zhang et al. (2014) behaviour 1. i turn off the lights when going out at work 2. i open the windows to reduce the use of the fan/air conditioner at work 3. when not in use, i switch off the computer at work 4. i limit the duration that the refrigerator door is kept open at work 5. i turn off the lights when the sunshine is bright enough at work. 6. when the air conditioner is on, i properly close the room door at work 7. when leaving work, i switch off all lights. zhang et al. (2014) tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 1 • 2023544 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(1), 544-551. does the “environmental kuznets curve” phenomenon happening in high, medium, and low income countries? marselina*, tri joko prasetyo faculty of economics and business, universitas lampung, lampung, indonesia. *email: marselina@feb.unila.ac.id received: 20 october 2022 accepted: 07 january 2023 doi: https://doi.org/10.32479/ijeep.13507 abstract the most significant reduction in environmental quality is thought to have occurred in low-income countries, while low environmental degradation occurred in those high-income countries. using the cluster purposive sampling technique, countries from 5 continents were examined to see if they had complete data and represented three categories. seventy-eight countries were found to meet these requirements and were then used as research samples from 2015 to 2019. the data panel regression technique was used to analyses the data. this study is expected to be able to produce policies in the form of a sustainable environmental management model that continues to support economic growth. this study proved that the environmental kuznets curve (ekc) phenomenon applies from 2015 to 2019 in high-income countries, and population growth rates have a significant negative impact on carbon dioxide (co2) emissions. this means that the more prosperous a country, the less the environmental degradation, while in lowincome countries, carbon emissions increase when economic growth increases. in developing countries, as the population increases, environmental degradation increases, while in low-income countries the amount of carbon emissions is affected by economic growth and population. some compensate and subsidies low-income countries which are able to care for their environment. keywords: environment degradation; emission; environmental kuznets curve; sustainable development jel classifications: o44, q43, q56, q58 1. introduction the issue of environmental degradation is more common in developing countries, but this statement is still debatable. this statement is thought to be due to high population growth rates, low economic growth rates, lack of infrastructure also public awareness. this environmental issue is a worldwide concern because it is considered in the case of global warming and human survival as a whole. hence, the factor endowment hypothesis (feh) theory states that rich countries are very concerned about this problem by being willing to pay more to protect the environment (marton and hagert, 2017). increased environmental damage will turn against humans because the impact will be reduced production and decreased capital and labor productivity (borhan et al., 2012). changes will follow environmental degradation in climate patterns, such as increased rainfall, changes in storm intensity, and melting of polar icebergs. climate change will cause considerable losses to human life, such as a clean water crisis, damage to coastal area infrastructure, decreased agricultural productivity, and increased frequency of diseases transmitted by mosquitoes (irmansyah, 2004). environmental degradation can be suppressed if the process of industrialization and population growth is managed wisely. one of the indicators showing a decrease in environmental quality is the increase in co2 emissions. according to the world resource institute-wri (2019) report in 2016, asean countries contributed about 7.35% to the addition of co2 emissions from the whole world produced. in the kyoto protocol, six emissions have a significant impact on the environment, namely co2 (carbon dioxide), ch4 (methane), n2o (nitrous oxide), hfc (hydrofluorocarbons), pfc (perfluorocarbons), and sf6 (sulfur this journal is licensed under a creative commons attribution 4.0 international license marselina and prasetyo: does the “environmental kuznets curve” phenomenon happening in high, medium, and low income countries? international journal of energy economics and policy | vol 13 • issue 1 • 2023 545 hexafluoride), and co2 emissions. co2 is the most prominent and rapidly increasing emission. the average co2 emission in 2020 was 412.5 parts per million (ppm), an increase of 2.6 ppm from the previous year and the highest increase in the last 65 years (lindsey, 2020). according to (eiteman et al., 2001), 80% of global co2 emissions come from human activities such as burning vehicle fuels, power plants, construction operations, and industry. rapid population growth will increase the demand for food and high energy and water consumption. the increasing demand for natural resources tends to over-exploit the environment, impacting the short term and long term (kolstad and krautkraemer, 1993). an increase in population will cause an increase in the amount of co2 emissions due to increased energy use (khusna and kusumawardani, 2021). (mantra, 2003) argued that population is one of the factors causing environmental degradation, which will reduce the level of productivity of agricultural land for food production per capita. environmental damage is also inseparable from the process of globalization, one of which is an investment. growth of economics and foreign investment inflow tends to increase co2 emissions (omri et al., 2014). besides being able to have a positive impact as an engine of economic growth, investment is also suspected that it can worsen environmental quality through the application of technologies that are not environmentally friendly even it can shorten the life expectancy (hendrawaty et al., 2022). the world bank in 2021 reported that foreign investment entering developing countries has increased in number, and the inflow of this investment is suspected to affect the level of environmental pollution in that country. the pollution halo hypothesis states that investment will reduce environmental pollution by contributing to new energysaving technologies or production methods. it increases renewable energy in the host country, increases productivity and energy efficiency, and provides management skills (kızılkaya, 2017). (ren et al., 2014) a study in china also found that foreign investment inflows exacerbated co2 emissions. their study that fdi increases not only economic growth but also energy consumption. research conducted by (tang and tan, 2015) in vietnam from 1976 to 2009 revealed that co2 and fdi are correlated with each other, and according to (zhang and zhou, 2016), the correlation is negative. it means that the inflowing of fdi reduces emissions. this opinion is evidenced by the research they did according to the study by (zhang and zhou, 2016) in china from 1995 to 2010, foreign investment contributed to reducing co2 emissions. in energy, economics book claims that in developing countries, fdi and financial market development are expected to transfer clean technology with low emissions (batten and vo, 2009). simon kuznets criticizes the development model, which is only oriented toward economic development. according to the ekc hypothesis, pollution levels increase as the country grows, reducing income growth. therefore, there is a threshold level of economic growth beyond a further increase that can increase the environmental impact of the early stages of economic development (kızılkaya, 2017). the curve of environmental kuznets draft also tells the quality of the environment, which co2 emissions can count, deteriorates in the early stages and the improvement in later life for the economic growth (dinda, 2004). the curve of environmental kuznets hypothesis rarely happened in countries. some research in growing countries shows that the curve of the environmental kuznets hypothesis is not proven, so environmental degradation is directly proportional to economic growth (almulali et al., 2015). (iwata et al., 2010) confirmed that the ekc hypothesis (acaravcı and ozturk, 2010) and (jalil and mahmud, 2009) also found that carbon emissions are influenced by gdp and energy consumption in the long term. there are two different views on environmental degradation that occur in several countries in the world. empirically, foreign investment inflows and gdp growth tend to increase environmental degradation in lowincome countries, as reflected in increased co2 emissions due to population pressure. high-income environmental degradation is getting lower due to the very selective incoming investment and the high awareness and concern of the population on the environment. based on the explanation and previous researches, we interested in analyzing whether the kuznetss theory still applies in 3 categories of countries, namely in high, middle, and low income countries, according to the categories made by the world bank and whether there are differences in the magnitude of the effect of population, investment and growth. gdp against the level of environmental damage as proxied by co2 emissions. the goal of this study is to prove whether does phenomena of ekc occur in high, middle, and low income countries and determine the effect of population size, foreign investment, and economic growth on environmental quality degradation in co2 emissions in high, middle, and low income countries. 2. literature review 2.1. government intervention in public goods government intervention in determining the price of public goods with no market involves making regulations and pro-environmental budget policies. government policies in the environmental sector are useful for the public interest of environmental preservation and the degree of government intervention in environmental quality protection from environmental quality standards. the target standard is usually determined by taking into account the effect of the pollutant on a particular environmental medium, such as water, air, or soil (ogus, 2004). environmental quality standards describe the extent to which how still tolerate damage due to waste/pollution. 2.2. environmental degradation environmental degradation will reduce the productivity of natural resources to encourage an increase in production costs. destruction of soil, water sources, and forests through inefficient and unplanned production methods can significantly reduce productivity, especially in the long term, however, these negative excesses are often eliminated when obtaining a high gni. therefore, the current performance measurement must also consider quality and envirconsiderbility (todaro and smith, 2009). the calculation of gni must be corrected to become nni (sustainable net national income) or sustainable net national product. this is the total amount consumed without eroding social capital, where nni = gni-dm-dn, nni is net national marselina and prasetyo: does the “environmental kuznets curve” phenomenon happening in high, medium, and low income countries? international journal of energy economics and policy | vol 13 • issue 1 • 2023546 income, dm is depreciation of manufacturing capital assets, and dn is depreciation of environmental capital expressed in monetary units years. the amount of ei emission depends on energy consumption, sulfur content, and the technology used to remove sulfur emissions. reducing sulfur emissions is possible but comes at a cost. the total cost to issue ci is as follows: ci = ci(ei) + ci(di), i = 1,2,...n, in which ci(ei) is a decreasing control cost function on ei, and ci(di) is a loss cost function. 2.3. emissions of carbon dioxide (co2) waste, emissions, and environmental quality have different meanings, as distinguished by (field and olewiler, 2015). total emissions produced are the sum of various sources according to time, type and location. emissions are released into the environment through water, soil, and air media, which can naturally handle these emissions. emissions that natural systems cannot process can affect environmental quality. environmental quality is the number of pollutants (emissions) that have a negative impact on the environment, for example, the concentration of sulfur (so2) in the air. 2.4. relationship between population and environment residents play a role as a driving factor for environmental damage, and eventually, residents will also receive the consequences of environmental damage. the limit to growth contains the relationship between environmental variables, namely: population, agricultural production, industrial production of natural resources, and pollution (mantra, 2003). when the supply of natural resources is abundant, per capita food, manufactured goods, and population will increase rapidly. this growth will eventually slow down as supplies of natural resources are depleted by 2100, followed by hunger and pollution. humans must limit their growth and use natural resources balanced to avoid this. 2.5. foreign investment the country needs investment, while the company’s goals are inseparable from foreign investors (ambarsari and purnomo, 2005). according to, the motives underlying foreign investment activities are strategic, behavioral, and economic motives. strategic motives include market seeking, knowledge-seeking, and political security seeking. using fdi, especially profitability includes using foreign production factors, raw materials, and technology, behavioral motives such as external environmental stimuli and individual obligations, and economic motives by maximizing long-term profits and stock price. 2.6. the relationship between foreign direct investment (fdi) and environment quality fdi is not only a crucial factor for economic growth but is also at risk of causing environmental degradation. the negative effect of fdi on the environment is explained in the pollution haven hypothesis or the pollution haven effect, when industrialized developed countries plan to build factories or offices abroad, they tend to look for cheaper options for resources and human resources. work, to meet the land and material access needed. usually, industrialized countries relocate to countries with less stringent environmental regulations, such as developing countries (levinson and taylor, 2004). 2.7. economic growth the economy’s growth shows how far too much economic activity generates income within a certain period, wherein economic activity will use the factors of production to produce products. the economy is considered high growth when all real rewards for using factors of production in a given year are higher than the previous year. the principal capital of economic growth is a technology that produces more efficient, massive, and many types of production (romer, 1990). 2.8. relationship between economic growth and environmental quality economic development activities exploit natural resources to improve people’s lives and take few concrete steps to preserve the raw materials. the level of pollution in a country can be determined by the ability of the environment to bear the burden of pollution. therefore, the ability of the environment to take responsibility of environmental pollution without having to cause negative impacts is stipulated in the environmental quality standards. this quality standard is then used as a reference for assessing the environmental impact of each development activity, adjusted to the nature and potential of different countries. according to (panayotou, 2000), economic growth has an impact on environmental degradation, when a country experiences rapid growth, the problem of air pollution is also increasing rapidly, and the number of polluters will increase when economic activity is more significant. there are two reasons for environmental degradation. first, the limited capacity of the environment to absorb waste generated by economic activities, and second, limited non-renewable natural resources. this affects the choice between economic growth and the environment. 2.9. kuznets theory the assumption of kuznets relates to the per capita income of the country’s environment is known as ekc. his assumption shows the attention will be directed toward increasing the country’s income if it is still relatively low, either through production or investment that encourages income growth, excluding issues of environmental quality income growth is followed by increasing the pollution and then it declines again if income growth conditions persist. this assumption is from the amount for the quality of the environment, which improves social control and government rules therefore, people are more prosperous (mason and swanson, 2002). it will give a big contribution to the national products if the country’s income improves in line with economic development, manufacturing products. to conclude, industrialization starts in small industries and continues in large industries. the increment of using the natural resources and degradation of environment intensification degradation is the phase of middle-income level, the development phase dominates industrialization by increasing the share of its internal social items when industrial activity grows steadily. in this case, the utility of uncooked materials will marselina and prasetyo: does the “environmental kuznets curve” phenomenon happening in high, medium, and low income countries? international journal of energy economics and policy | vol 13 • issue 1 • 2023 547 decrease, and the elimination of waste per unit of production will increase. 2.10. hypothesis construction 1. the kec phenomenon indeed cursors in high and low income countries 2. it is suspected that population, fdi, and economic growth affect the level of co2 emissions in a country 3. the population increases co2 emissions higher in low-income countries than in high-income countries 4. investments that enter a country increase co2 emissions higher in low-income countries than in high-income countries 5. gdp growth increases co2 emissions more in low-income countries than in high-income countries. 3. materials and methods this research is descriptive quantitative. the research area is in countries around the world that are on 6 continents. of the 198 countries, only 73 countries have complete data representing 6 continents. then the 73 countries are grouped into 3 categories based on the criteria for the level of per capita income made by the world bank, namely countries with high per capita income, middle, and low income countries. the data used include: data on co2 emissions, population, fdi data, gdp growth data all sources world bank. 3.1. population and sample the population in this study is 198 countries representing 6 continents, namely the countries in asia, europe, america, africa, and australia, consisting of high-income countries, medium and low. sample selection using cluster purposive sampling method, with criteria: 1. the country represents the continents of asia, africa, australia, europe, africa, and america 2. the country represents high, middle, and low income countries 3. data is available at the world bank, namely in wdi and wgi 4. so that a total sample of 73 countries was selected, which had the complete data with the following details: 18 countries represent countries on the asian continent, 4 countries represent the australian continent, 18 countries represent the americas, 22 countries represent the european continent and 11 countries representing the african continent. 3.2. definition of operational variable 3.2.1. environment quality the environmental quality in this study will be proxied using the emission level measure co2, which comes from all activities that emit gases and methane or so-called greenhouse gases. this type of gas can change the environment is getting worse, which is accelerating climate change. many researchers use this and the world bank uses co2 indicator units of metric tons per capita (mtco2). population counts all residents residing in countries according to the above categories, regardless of legal status or nationality. data population sourced from the world bank. 3.2.2. foreign investment foreign investment in this study uses the value of fdi, which is the net inflow of investment made by a company from countries to invest their capital for an extended period in companies in other countries (world bank, 2021), in the form of inward and outward flows and stock, expressed in units of million us dollars (us$). data obtained from the world bank. 3.2.3. economic growth economic growth is the gdp growth rate at market prices by currency constant local money. the aggregate is based on the 2010 stable us dollar. units measure of economic growth is the percentage (consistent) sourced from the world bank. 3.3. data analysis data analysis begins with forming 4 equation models as follows: co2it all = β0+β1popit+β2fdiit+β3pdbgit+μit (1) co2it high = β0+β1popit+β2fdiit+β3pdbgit+μit (2) co2it moderate = β0+β1popit+β2fdiit+β3pdbgit+μit (3) co2it low = β0+β1popit+β2fdiit+β3pdbgit+μit (4) where: co2: carbon dioxide emission (mtco2) pop: population (total) fdi: foreign direct investment (us$) pdb: economic growth (%) β0: intercept or constanta β1, β2, β3: regression coefficient on each independent variable i: 1, 2, 3.,30 (cross-section countries data) t: 1, 2, 3, 4 (time series data, period 2018-2021) е: disturbance error. the data processing technique uses a panel data regression analysis model covering 73 countries during the observation period. the methods and steps used for panel data regression use three test table 2: data panel regression for all countries (73 countries sample) variable coef. t sig. constant population fdi economic growth f adj. r2 4.714695 0.000000038 0.000000000274 0.029592 212.8612 0.86478 1.682883 0.0080242 1.884251 4.377377 0.0946 0.9362 0.0616** 0.000* 0.000 *df 5%, **df 10% table 1: statistic descriptive variable countries low income middle income high income carbon emission (metric ton) population (billion) fdi ($million) economic growth (percent) 1.118493 40.469.921 541.886.909 −1.595% 4.013283 37.060.079 4.018.892.355 −0.657% 8.787946 100.206.055 2.308.834.676 +0.045% marselina and prasetyo: does the “environmental kuznets curve” phenomenon happening in high, medium, and low income countries? international journal of energy economics and policy | vol 13 • issue 1 • 2023548 approaches: the cem or common effect model, fem or fixed effect model, and rem or random effect model, followed by chow test and haussman test. ols assumption test is also carried out in the form of autocorrelation, multicollinearity, and heteroscedasticity test. 3.4. hypothesis test t-statistical test (partial test) was used to determine the significance of the effect of the independent variable on the dependent variable partially (individually). this study uses a one-way test with a significance level of = 5% with the following hypothesis: • hypothesis 1: high-income countries have lower levels of carbon emissions than middle and low-income countries • hypothesis 2: there are differences in the magnitude of the influence of the factors that affect the level of carbon emissions in high, middle, and low income countries. 3.5. coefficient determination (r2) the coefficient of determination test is used to measure the percentage of variation in the total independent variables that the regression model can explain. the model is better if the r2 value is close to 1 or 100%. suppose the value of r2 is small or close to zero. in that case, it means that the ability of the independent variables to explain the dependent variables is minimal because there are other factors outside the model that are not observed, and vice versa. 4. results and discussion the research sample includes 73 countries representing 5 continents, namely 18 countries from the asian continent, 4 countries representing australia and oceania, 18 countries from the americas, 22 european countries, and 11 african countries. these countries represent 23 developing countries mostly from africa, asia, and america, 27 developing countries, and 23 developed countries, mostly from europe, north america, asia, and australia. the research period from 2015 to 2019 and 2020 was not observed because average data due to the covid-19 crisis was not relevant. the results of descriptive statistics illustrate that currently, in developed countries, the level of co2 carbon emissions is higher than the level of emissions in developing and developing countries. the average co2 emission in developed countries is 8.7878 metrics per capita, while in developing and poor countries it is only 4.0132 and 1.118 metrics per capita, respectively. the high level of carbon emissions in developed countries is due to the high population. the average population in developed countries is 100 million, while in developing and poor countries the average is 37.06 million and 40.46 million, respectively. however, foreign investment entering developing countries far exceeds developed countries. investment in developed countries began to experience saturation. factors that drive high levels of co2 carbon emissions in developed countries (as shown on table 1) compared to poor and developing countries are because developed countries have the largest population, complete and modern infrastructure in terms of quality and quantity, also equipped with social, public, and trade facilities, all of which require a lot of land and energy. the number of foreign investment activities that enter developed countries is the second largest after developing countries or amounting to $ 2.3 million billion, which also requires a lot of energy and natural resources. most of the energy needed by these facilities and infrastructure is met from fossil fuels and land and forest use. high energy use will result in increased emissions as well. referring to this condition where developed countries are the world’s largest emitters, these countries are very interested in reducing co2 emissions, including many offers of compensation for developing countries and poor countries that can maintain forests and preserve the surrounding environment. in contrast, in poor countries, many rely on the engine of growth from the natural resource sector, agriculture which tends to use conventional technology so that emission levels are still low. still, due to population explosion and teaching growth and food supply, there is a tendency to increase the growth of carbon emissions. from the results of data processing using the longitudinal data regression method as shown on table 2, it was found that in all countries, both developed, developing, and poor, co2 emission levels were significantly affected by the economic growth of 0.029%, and the amount of incoming foreign investment (fdi), but for fdi affects the number of carbon emissions in the world at the 10% degree of freedom level. it was also found that population does not affect co2 carbon emissions in both developed, developing, and poor countries. the description above is shown in the table below. in general, almost all countries, impoverished countries, in pursuing economic growth and the welfare of their people, tend to utilize abundant natural resources very massively and tend to sacrifice the environment. keep production capacity high. the fullday operation of the industrial sector in pursuit of growth targets tends to produce high pollution. foreign investment that enters poor and developing countries is also dominated by the intention of a quick return on capital rather than the motivation to participate in protecting, preserving, or improving the environment. this phenomenon is by the theory put forward by kuznets in the kuznets environment curve (kec) that environmental degradation will be higher in poor countries than in rich countries, while in developed countries, due to increased awareness supported by high levels of education, environmental damage is reduced which results in reduced environmental damage indicated by reduced co2 carbon emissions despite increasing economic growth. 4.1. high income countries on average, the amount of co2 emissions in developed countries is the highest (table 3) but the annual growth in the number of emissions is because the population is aware that they have to reduce it. because of this high awareness, the increasing table 3: estimation in high-income countries variable coef. t-test sig. constanta population fdi economic growth f adj. r2 2.873003 0.537779 0.013669 −0.018761 10.4 0.079508 1.583720 0.165075 0.466249 2.095757 0.1223 0.8706 0.6463 0.0497* 0.0000 marselina and prasetyo: does the “environmental kuznets curve” phenomenon happening in high, medium, and low income countries? international journal of energy economics and policy | vol 13 • issue 1 • 2023 549 economic growth will be negatively correlated with the amount of co2 emissions. through research and development (r/d), the government and the private sector strive to continue to develop technologies that are low in carbon dioxide. the higher the economic growth, the lower the level of co2 emissions. developed countries are proven to emit more carbon emissions compared to developing countries or poor countries, this happens because of the use of more fossil fuels such as for household needs such as electricity and others, as well as the needs of the community and more significant industry. developed countries should be more responsible for polluting the world’s carbon emissions due to higher fuel use and pollution. cause developed countries have high levels of carbon emissions due to their larger population. the average population in developed countries is 100 million, while it is only 40 million in poor countries. with a large population, the need for living necessities for energy, such as household needs, transportation, and other needs, increases the emission of carbon emission pollution. high carbon emissions are also needed by industry and the economy so that the economic growth of developed countries is higher than that of poor and developing countries. the behavior of developed countries that pursue prosperity and economic growth is increasingly using fuel that emits carbon emissions. in developed countries with higher economic growth, the level of investment is also higher because of the well-established infrastructure that makes it easy to do business; this increases the expenditure of carbon emissions in developed countries compared to poor countries. 4.2. low income countries partially, in poor countries represented by 23 countries, it is interesting to find that the level of carbon emissions is influenced by population, foreign investment inflows, and economic growth. people in poor countries still use technology that produces high carbon emissions to meet their daily needs. old, less feasible, and non-massive modes of transportation will increase carbon emissions from vehicles. likewise, the existence of old production machines is inefficient and produces more exhaust gases. the target of pursuing community welfare and economic growth is due to population pressure. it is evident from the results of the study that in poor countries the level of carbon emissions is significantly affected by population, a 1% increase in population will increase co2 emissions by 0.45%, the highest compared to the increase in economic growth and the amount of foreign investment entering. therefore, investors from developed countries tend to ignore the use of environmentally friendly technologies. the rate of population growth must be managed properly so that the growth of carbon emissions can also be driven so that it does not damage nature and disturb the balance of nature. development in poor countries that still rely a lot on natural resources will increase carbon emissions, which can be seen from the level of investment significance and economic growth on the level of carbon emissions (table 4). seeing this condition, developed countries must help poor countries manage carbon emissions because the level of absorption (absorption) of the carbon emissions produced can be carried out by the large number of forests that are still widely spread in poor and developing countries and have not yet been developed optimally explored. developed countries must provide compensation to countries that maintain their forests as the world’s lungs. these countries are sacrificing not to carry out the industrialization process on a large scale by keeping their forests sustainable as the lungs of the world in the hope of helping developed countries that have run out of land. with high emission levels as the lungs of the world. 4.3. middle income countries in developing countries, carbon emissions are higher than in poor countries but lower than in developed countries as found statistically on table 5. the study results found high carbon emissions in this developing country because it is influenced by the population. meeting the energy needs of the population uses fossil fuels and a rapidly growing industry with a lot of incoming investment. land and energy are needed to meet the population’s supply. the forest area as the world’s lungs has decreased significantly in developing countries. economic needs and the household life in developing countries require energy, transportation, and space needs that increase fuel and land use. to reduce world carbon emissions, developed countries must also provide technical assistance and compensation so that population growth in developing countries does not cause pollution and high carbon emissions. developing countries need to get the world’s attention to help control the population. 4.4. population effect on carbon dioxide (co2) emission level residents play a role as a driving factor for environmental damage, and ultimately residents will also receive the consequences of environmental damage. the study results found that in developing and poor countries, population growth will lead to increased levels of co2 emissions. this occurs significantly in poor and developing countries. population growth in both categories of this country is relatively high between 1% and 2% per year. according to (suparmoko, 1997), population growth will cause the demand for goods and services to increase, which must be met by increasing the use of natural resources which in doing so through forest fires, fuels from fossils, forest defoliation, and to produce table 5: estimation of middle income countries variable coef. t-test sig. constant population (milion) fdi ($ milion) economic growth (%) f adj. r2 0.973178 0.212584 0.063286 0.004728 5.839 0.617 0.902089 3.100543 1.484601 0.073667 0.4018 0.0211* 0.1882 0.4891 0.03265 table 4: estimation of low-income countries variable coef. t-test sig. constanta population (person) fdi (us $ milar) economic growth (%) f adj. r2 1.674104 0.455600 0.428103 0.040673 19.94 0.56 1.386057 6.751047 5.428201 1.974303 0.1732 0.0000 0.0000 0.0551 0.0000 marselina and prasetyo: does the “environmental kuznets curve” phenomenon happening in high, medium, and low income countries? international journal of energy economics and policy | vol 13 • issue 1 • 2023550 the chlorofluorocarbons (cfcs) all of which cause an increase in the amount of co2 emissions due to increasing energy use (khusna and kusumawardani, 2021). (mantra, 2003) argued that population is one of the factors causing environmental degradation, which will reduce the level of productivity of agricultural land for food production per capita. to avoid further environmental damage, humans must limit their growth, although, in the end, this population growth will slow down itself along with the depletion of natural resource supplies, which are projected to be exhausted by 2100, followed by hunger and pollution. developing and poor countries to reduce carbon emission levels by controlling population growth, including the provision of energy-efficient residential, office, and commercial facilities. 4.5. the effect of direct investment that enters a country on the level of carbon dioxide emissions in low-income countries that are needed investment to pursue economic growth, create job opportunities and complement the infrastructure, foreign investment inflows tend to be uncontrolled by environmental protection regulations. foreign investors will tend to exploit resources, nature and the environment. this will spur an increase in carbon emissions. this supports the rentseeking theory where foreign investors tend to implement the motive of exploiting natural resources to return their capital when the government does not strictly regulate it. according to (eiteman et al., 2001), foreign investors entering poor countries tend to be economically motivated, pursuing profits to maximize long-term profits by exploiting natural resources. another reason for using fdi is usually profitability, for example, the use of foreign factors of production, raw materials, or technology. for this reason, investors from developed countries must have a moral and social responsibility to poor countries by investing and transferring environmentally friendly technology. it is different in developed and developing countries, with high public awareness and wellestablished economic growth, so incoming foreign investment is very selective, primarily related to environmental conservation. 4.6. the effect of economic growth on carbon dioxide emissions in high and low income countries, the level of co2 emissions is affected by economic growth, but in the opposite direction. this means that in the higher incomes countries with increasing welfare of the people as reflected by their economic growth, the lower the carbon emissions produced, on the contrary, the lower the income of countries, the higher the carbon emissions released into the air. this phenomenon illustrates that the kec occurs, wherein in developed countries the higher the income, environmental degradation decreases, on the other hand, the poorer a country, the higher the environmental damage. developed countries must provide compensation to countries that maintain their environment. 5. conclusion environmental kuznets curve (ekc) phenomenon happened, in which the higher the income country, the less the environment is degraded, on the contrary, the poorer a country is, the higher the environmental damage occurs. in developed countries, only economic growth is significant to the level of carbon emissions, and the effect is negative, meaning that an increase in economic growth will reduce the level of carbon emissions. in developing countries, the population is a factor in increasing carbon emissions, while in low income countries, apart from the population, foreign investment inflows and economic growth exacerbate co2 levels. 6. acknowledgments the author would like to thank the team of local enumerators who have gone to great lengths to help. references acaravcı, a., ozturk, i. (2010), electricity consumption-growth nexus: evidence from panel data for transition countries. energy economics, 32(3), 604-608. al-mulali, u., ozturk, i., lean, h.h. (2015), the influence of economic growth, urbanization, trade openness, financial development, and renewable energy on pollution in europe. natural hazards, 79(1), 621-644. ambarsari, i., purnomo, d. (2005), studi tentang penanaman modal asing di indonesia. jurnal ekonomi pembangunan kajian masalah ekonomi dan pembangunan, 6(1), 26-47. batten, j.a., vo, x.v. (2009), an analysis of the relationship between foreign direct investment and economic growth. applied economics, 41(13), 1621-1641. borhan, h., ahmed, e.m., hitam, m. (2012), the impact of co2 on economic growth in asean 8. procedia social behavioral sciences, 35, 389-397. dinda, s. (2004), environmental kuznets curve hypothesis: a survey. ecological economics, 49(4), 431-455. eiteman, d.k., michael, h.m., stonehilll, a.l. (2001), manajemen keuangan multinasional (sembilan). jakarta: pt indeks gramedia. field, b.c., olewiler, n.d. (2015), environmental economics. 4th ed. canada: mcgraw hill ryerson. hendrawaty, e., shaari, m.s., kesumah, f.s.d., ridzuan, a.r. economic growth, financial development, energy consumption and life expectancy: fresh evidence from asean countries. international journal of energy economics and policy, 2022, 12(2), 444-448. irmansyah. (2004), mengurangi emisi gas rumah kaca. available from: https://www.rudyct.com/pps702ipb/08234/irmansyah.pdf iwata, h., okada, k., samreth, s. (2010), empirical study on the environmental kuznets curve for co2 in france: the role of nuclear energy. energy policy, 38(8), 4057-4063. jalil, a., mahmud, s.f. (2009), environment kuznets curve for co2 emissions: a cointegration analysis for china. energy policy, 37, 5167-5172. khusna, v.a., kusumawardani, d. (2021), decomposition of carbon dioxide (co2) emissions in asean based on kaya identity. indonesian journal of energy, 4(2), 101-114. kızılkaya, o. (2017), the impact of economic growth and foreign direct investment on co2 emissions: the case of turkey. turkish economic review, 4(1), 106-118. kolstad, c., krautkraemer, j.a. (1993), natural resource use and the environment. in: kneese†, a.v., sweeney, j.l., editors. handbook of natural resource and energy economics. vol. 3., ch. 26. netherlands: elsevier. p1219-1265. levinson, a., taylor, m.s. (2004), unmasking the pollution haven effect. united states: nber working paper. available from: https://www. ssrn.com/abstract=565828 lindsey, r. (2020), climate change: atmospheric carbon dioxide. marselina and prasetyo: does the “environmental kuznets curve” phenomenon happening in high, medium, and low income countries? international journal of energy economics and policy | vol 13 • issue 1 • 2023 551 available from: https://www.climate.gov/news-features/ understanding-%0aclimate/climate-change-atmospheric-carbondioxide mantra, i.b. (2003), demografi umum/ida bagoes mantra. indonesia: pustaka pelajar. marton, c., hagert, m. (2017), the effects of fdi on renewable energy consumption-a study of the effects of foreign investments in middle-income countries. available from: https://www.file:///d:/ sentri/marselina/bachelors_thesis_hagert_marton.pdf mason, r., swanson, t. (2002), the costs of uncoordinated regulation. european economic review, 46(1), 143-167. ogus, a.i. (2004), regulation : legal form and economic theory. hart. available from: https://www.site.ebrary.com/id/10276334 omri, a., nguyen, d.k., rault, c. (2014), causal interactions between co2 emissions, fdi, and economic growth: evidence from dynamic simultaneous-equation models. economic modelling, 42, 382-389. panayotou, t. (2000), economic growth and the environment. cambridge, ma: harvard university. cid working paper. ren, s., yuan, b., ma, x., chen, x. (2014), international trade, fdi (foreign direct investment) and embodied co2 emissions: a case study of chinas industrial sectors. china economic review, 28, 123-134. romer, p.m. (1990), endogenous technological change. journal of political economy, 98(5), s71-s102. suparmoko, m. (1997), ekonomi sumberdaya alam dan lingkungan : suatu pendekatan teoritis (edisi keti). yogyakarta: bpfe. tang, c.f., tan, b.w. (2015), the impact of energy consumption, income and foreign direct investment on carbon dioxide emissions in vietnam. energy, 79, 447-454. todaro, m.p., smith, s.c. (2009), pembangunan ekonomi. 9th ed., vol. 2. indonesia: erlangga. world bank. (2021) foreign direct investment, net inflows (bop, current us$). world bank: world development indicators. zhang, c., zhou, x. (2016), does foreign direct investment lead to lower co2 emissions? evidence from a regional analysis in china. renewable and sustainable energy reviews, 58, 943-951. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 1 • 2021126 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(1), 126-135. shale gas: an indian market perspective dipen paul1*, sushant malik1, dharmesh k. mishra1, rushik hiwale2 1symbiosis institute of international business, symbiosis international (deemed university), india, 2idam infra, india. *email: dipen.paul@siib.ac.in received: 20 july 2020 accepted: 22 october 2020 doi: https://doi.org/10.32479/ijeep.10471 abstract energy demand has been increasing day by day with the advancement in industrialization and urbanization all across the world. most of the demand is fulfilled with the help of primary conventional energy sources viz. coal and oil. one such source of energy is the shale from which oil and gas are extracted to be used as fuel. shale gas resource has been visible on the global energy scenario map since the 1950s but was not being significantly focussed upon until 1990s when it gained economic and technical accessibility. the fast-technological breakthrough in the us resulted in fall in the breakeven cost of shale gas which had brought about a revolution in the us energy market in the 2000s. this revolution helped the us to turn itself from an importer of gas to an exporter of gas. thus, it is important to discuss the current shale gas scenario, its prospects as well as its scope for growth in the future indian energy market. thus, the country needs to focus on the development of shale oil and shale gas resources as they have the potential to significantly contribute to the gas supply at a relatively low cost. keywords: shale gas, indian shale, american shale revolution, hydraulic fracturing, horizontal drilling, shale gas policy jel classifications: o3, o4 1. introduction shale is a sedimentary rock which forms under high-pressure compaction of fine-grained silt and clay. the shale rock is characterised by the high content of clay (chamosite and kaolinite) of 55% along with 29% presence of quartz. the organic shale can be categorised into three types viz. type-1 kerogen, type-2 kerogen and type-3 kerogen. (u.s department of energy, 2015). this organic-rich sedimentary rock which is found deep inside the ground converts organic matter into oil and gas due to high pressure at a suitable temperature. the major chunk of this oil and gas gets expelled and on migration, gets trapped in ideal places from where it can be extracted with greater ease, thus, constituting the conventional oil and gas. the remaining minor chunk of oil and gas is retained inside the original rock-forming shale oil and gas which is unconventional to extract. these shale oil and shale gas are in the form of free hydrocarbons that are trapped inside pores, cracks, natural fractures, etc. some of the gas also gets stored as an adsorbed gas on the organic texture of the rock. as a result of this, there is very less free movement of the oil and gas inside the sedimentary rock. hence, the shale has low matrix permeability (alexander and bartik, 2019). shale oil and gas is an unconventional form of oil and gas, is characterised by a large area of distribution and variation in abundance of availability. the source rocks i.e. the shale rocks act as reservoirs for the shale oil and gas and they are spread widely throughout the area. they act as continuous reservoirs with no or very fewer traps which in turn results in the distribution of shale oil and gas extensively with no distinct boundaries. this increases the likelihood of the formation of large oil and gas provinces. presence of water is also a significant factor that needs to be considered while studying and evaluating a reservoir for the extraction of oil and gas. shale rocks do not have gas-water contacts. hence, the flow of gas is not affected by the flow of adjacent water. also, shale rocks are continuously distributed throughout the area of the basin. this continuous and spread-out accumulation of shale oil this journal is licensed under a creative commons attribution 4.0 international license paul, et al.: shale gas: an indian market perspective international journal of energy economics and policy | vol 11 • issue 1 • 2021 127 and gas primarily depends on three factors viz. extensive reservoir rocks, good source rocks and coexisting reservoir-source intervals (negi et al., 2017). any reserve of oil and gas, be it conventional or unconventional, needs to be studied properly so that it is easier to determine the processes to be carried out on the reservoir, the technologies that need to be employed, etc. for this, the first step is to classify the reserve into different groups. broadly, reserves or resources can be classified into four major types: (kumar et al., 2017). 1. remaining oil and gas in place 2. technically recoverable resources 3. economically recoverable resources 4. proved reserves. daniel and jarvie defines a “shale gas system” to be a system that considers the nature of shale found in the basin, as well as the extraction process, incorporated followed by storage and distribution. the study classifies such systems into two main types: biogenic and thermogenic. biogenic gas plays (a play is where the oil and gas are found in a basin) contain dry gas adsorbed to organic matter whereas thermogenic systems include high thermal-maturity shale rocks, low thermal-maturity shale rocks, a mixed-lithology intraformational system that contains shale, silt and sand, “informational” system where gas is generated in a mature shale and gets stored in less mature shale rock and a combination of plays that have production of both conventional and unconventional resources (chen et al., 2012). whereas describes a shale gas system saying that the system boundaries are divided into five phases viz. preproduction, production, processing, transmission and distribution. he thus focuses on the upstream shale gas industry (jarvie et al., 2007). 2. shale oil and gas extraction conventional hydrocarbon is usually found in the positive elements like craton large uplift, passive continental margin and macrotectonic zone in the down faulted basin and secondary structural units look over the hydrocarbon distribution. on the other hand, an unconventional hydrocarbon is primarily distributed within the negative elements such as depression slopes in foreland basin, central depression basin and craton syncline. the unconventional hydrocarbon occupies the centre of the basin and the slope and is distributed continuously in a large space (dwivedi, 2016). since the unconventional oil and gas are distributed irregularly all over the reservoir, traditional vertical drilling is less useful. hence, to effectively extract shale oil and gas, other technologies need to be focussed on. among these, two main technologies that are usually used in the extraction of shale oil and shale gas are hydraulic fracturing (fracking) and horizontal drilling. a brief process of extraction of shale oil is as follows and is represented by figures 1 and 2. the preliminary process of extraction is the exploration of the reservoir and various studies being conducted on the identified reservoir. the contract company like ongc starts drilling only after verifying the presence of economically recoverable resources. the type of drilling that is initially employed is the vertical drilling that is useful in breaking through the solid rock layers of the earth’s crust. the vertical drilling is employed only until the drill reaches the production layer where the oil and gas are present. after reaching this layer, horizontal drilling is employed where horizontal is not a perfect 90° angle with the vertical but an 85° angle with the vertical so that the pressurised oil and gas in the ground is concentrated towards the mouth of the well for efficient figure 1: horizontal fracturing versus vertical fracturing source: authors, adapted from: “hydraulic fracturing: how it works and recent state oversight actions” (legislative analyst’s office, 1 december 2016), <https://lao.ca.gov/publications/report/3513> figure 2: hydraulic fracturing and directional drilling source: authors, adopted from gong (2018) paul, et al.: shale gas: an indian market perspective international journal of energy economics and policy | vol 11 • issue 1 • 2021128 extraction. it should be noted that the slope goes to a maximum distance through the production layer. the maximum step out of a well is 14,129 m but the average is as low as 600–900 m (fangzheng, 2019). it is observed that horizontal drilling facilitates the best selection of shale gas. it is obtained by drilling horizontal wells using a horizontal trunk that passes through the production layer. the horizontal well can be in the shape of a fan, a fork or a spine in the same production layer that can be shallow. the number of wells drilled in the exploration phase can be between 2 and 15 in numbers. although, it is advised to drill around thirty wells to obtain enough data about the reservoir pressure and other characteristics of the reservoir. this data can then be used to devise a model and thus help in forecasting the resource volume, production capacity and development economics which helps in determining the long-term viability of the production of shale oil and gas from the reservoir (hamada and singh, 2018). to further enhance the performance of horizontal fracturing, recent developments have been made to give a direction to the well as the availability of shale in the production layer may not be horizontal. in this case, to attain maximum efficiency, it is important to drill the well such that it is inside the production layer for the maximum part. for this purpose, “directional drilling” served as the solution. this technique was first used in the usa were based on the oilfield market report, the total revenue of the oilfield services rose by 183% from 2005 to 2015. the hydraulic fracturing segment and the directional drilling gave a massive response with an increase in revenue of 395% and 287% respectively during the same period. this is concrete proof that these two techniques are the driving force. but like almost anything else, it has a positive side as well as a negative side. the positive side is that these techniques generated a huge amount of revenues and were successful in generating sufficient energy resources leading to reduced energy prices and energy storage. the negative side to it was that such innovations require huge capital investment in its research and development (r and d) which hides behind the curtains various risks like uncertainty, financial risks, operational risks, low input-output ratio and its sustainability. hence, it is hard to determine the profitability of the implementation of these techniques (glass, 2011). xuli talks about carrying out hydraulic fracturing using a technique called “stimulated reservoir volume (srv)” which is used for stimulation of shale oil and gas wells through fracturing technique. this technique helps in case when the effective flow channels inside the shale reserves are created, the productivity of shale oil and gas may be maximized (gong, 2018). once the hole is drilled till the production layer, the fracking liquid is pumped inside the well under high pressure. the fracking liquid may consist of water and propping agents and chemicals that dissolve the carbonate reservoirs. this fracking liquid is responsible to push the oil and gas from the well upwards through the good pipe and fill the well so that it does not collapse under vacuum. it does this by making micro-cracks in the production layer. the fracking liquid is later extracted with the oil and the two are separated and transferred to isolated reservoirs as the fracking liquid cannot be used again. it is to be noted that a major part of the fracking fluid comprises of water. hardly <1% are other chemicals. some of the chemicals used are proppants which are sandy materials used to hold open fractures, gelling agents like xantham gum and guar gum which serve the same purpose as proppants, surfactants which are used to reduce surface friction and biocides to kill bacteria (anjirwala and bhatia, 2016). after extraction, the produce undergoes pyrolysis to decompose kerogen which is a macromolecular and organic solvent-insoluble organic matter. on a general sense, pyrolysis is a process of thermal decomposition of materials at high temperature in an inert atmosphere. it involves a change in chemical composition and hence is irreversible. the pyrolysis of oil shale is a bit complicated though as it involves a large number of series and parallel reactions. this is because the kerogen exists in a complicated heterogeneous mixture which contains different types of elements like nitrogen, oxygen, sulphur, etc. and different kind of organic groups like carboxyl group, ketones and esters. to characterize the physical properties of the products obtained from pyrolysis of the oil shale, the authors (honglei and yan, 2020) suggest a unique method called terahertz time-domain spectroscopy (thz-tds). it is an optical method with the baseline idea that the method has different sensitivities to gas, oil, water and minerals (singh and khanna, 2012). when it comes to successful and effective production of shale oil and gas from a reservoir, the process of evaluation of the reservoir basin holds parity with the process of extraction of the fuel. chen et al. assert that depressions or basins with varying levels of exploration degr degree need respective evaluation methods for conducting exploration and appraisal activities with higher efficiency. the authors thereby suggest the following two methods for evaluation: volume method is an evaluation method that is used for evaluating areas with a high degree of exploration and when the data for the same is available in abundance. it is used mostly to evaluate reserves of shale oil and shale gas using gas-bearing properties of shale. this method states that the total gas resource is equal to the sum of free gas, adsorbed gas and the dissolved gas. the analogue method is an evaluation method used in areas with a low degree of exploration and limited availability of data. hence, the result produced from the method is not of high accuracy but still is capable enough to guide decisions of initial exploration and investment (hoffman, 2014). on a general note, shale oil is considered to be more valuable than shale gas because of energy intensity, ease of storage and ease of handling and transportation. hence, when one finds shale oil while searching for shale gas, it is like a bonus to the production of shale gas. this is because it creates a secondary stream of income. the opposite might not be true since a significant amount of shale gas is usually produced while the extraction of shale oil. the thing about shale gas is that if shale gas cannot be sold, then it creates hindrance in the shale oil production. this issue is usually sorted by employing flaring which is burning of gas in the open atmosphere but it creates carbon emissions contributing to global warming (honglei and yan, 2020). paul, et al.: shale gas: an indian market perspective international journal of energy economics and policy | vol 11 • issue 1 • 2021 129 the objective of this report is understanding the current indian shale oil and shale gas scenario and assess the indian shale market in comparison with the shale gas market of leading nations in the sector. on understanding basics of shale gas production and overview of the local and global shale gas scenarios, the report aims to provide insights on the scope of development of shale resources in india as well as the challenges faced by the sector. 3. research methodology the methodology that is used to research the selected topic is to first understand the sources of data that could be available to extract the information required to fulfil the above-mentioned objective. data is obtained from various research papers, review papers, journal articles, published articles and books that are available on online databases like scopus and google scholar. numerical or statistical data is referred from the official websites of regulating and governing bodies like ministry of petroleum and natural gas (mopng), ministry of power (mop), directorate general of hydrocarbons (dgh), the energy research institute (teri), ministry of new and renewable energy (mnre), central electricity authority (cea), etc. also, the data from websites of various international agencies like us’s energy information administration (eia), germany’s schlumberger, british petroleum (bp), etc. are used as their studies, surveys and data collection are mostly cited by experts all around the world. 4. effects of shale gas extraction 4.1. economic effect fracking, even if it seems to be an effective technique, has its effects, both positive and negative. alexander and bartik found three major findings when it comes to the effects of fracking and the use of shale gas. 1. a positive effect that came out of the fracking technique was for the countries which have fracking potential has experienced a boom in energy resources. they have produced almost 400 million usd worth of oil and gas annually in three years post the discovery of hydraulic fracking techniques compared to shale producing countries which do not employ fracking. this annual increase in income also increased economic activities with an increase in income, employment and salaries. local governments also observed an increase in revenues that are higher than the average increase in expenses 2. the authors estimate that annual willingness-to-pay for hydraulic fracking-induced changes in the local conveniences is almost -1400 usd per household yearly i.e. −2.7% of average yearly household income 3. the authors estimate that considering all the us shale plays, the willingness-to-pay for allowing hydraulic fracking equals 2500 usd per household annually i.e. 4.9% of the average income of a household (howarth, 2019). 4.2. social effect oil and gas extraction is a process that creates a huge amount of emissions. these emissions can be in the form of harmful gases, particulate matter or even heat. these factors directly affect the health of the people who are working on the site or even those who are living in the vicinity of the operation. reports have emerged discussing people who live close to the fracking sites being affected by the emissions and falling sick by getting in contact with contaminated water or air. most of the emissions and chemicals involved in the process are potential threats to human health as they can severely affect the smooth normal functioning of the body. some of the chemicals are identified to be endocrine disruptors while few others were found to be disruptive towards hormone functioning in the body. not just the emissions from the extraction process, but the particulate matter that gets lifted off into the air from extraction as well as transportation activities has the potential to get lodged in the lungs causing silicosis. apart from health, the extraction process very largely contributes to local air and noise pollution. the drilling activity is one which creates intense noise. 4.3. environmental effect the air quality, especially that pertaining to the local area i.e. the site of extraction and its vicinity, gets severely affected by oil and gas operations. also, equipment and machinery used during the production process create emissions that include methane releases from compressor blowdown and valves, volatile organic compounds like btex (benzene, toluene, ethylbenzene and xylene) which escape from oil tanks and condensates. but it is to be noted that gas has less than half carbon footprint than that of coal and carbon dioxide emissions are two-thirds of oil when combusted, making gas a better energy source from an environmental perspective (nakano et al., 2012). air quality, due to oil and gas production process, in mainly affected due to emission of methane when wells are tested or flowed back as well as those from flaring of excess gas. the procedures and techniques involved in the extraction of unconventional oil and gas differ from those that are used in the extraction of conventional oil and gas. however, the amount of methane in the conventional gas and unconventional gas is almost the same, thus creating a similar climatic effect. methane is called as a “high-leverage” greenhouse gas (ghg). one kilogram of methane can produce a radiative forcing that is multiple times higher than that produced by a kilogram of carbon dioxide. hence, it is important to quantify this radiative forcing which the gas has on the environment. to do this, all ghgs are assigned certain values of “global warming potential” (gwp) which reflect the severity of their effect on the environment by trapping heat radiations. higher the value of gwp, more dangerous is the gas emission for the atmosphere. this value of gwp is used to obtain the value of carbon footprint in terms of “carbon dioxide equivalent” (co2e). the gwp takes into account several factors like strength of radiative forcing as well as the expected time of decay of the ghg in the atmosphere. gwp is calculated on three timescales: 20 years (20y), 100 years (100y) and 500 years (500y) where gwp of co2 is defined to exactly 1 for each scale. methane has a significantly high value of ghg owing to the high capacity of methane to absorb infrared radiation but a short life in the atmosphere. the ipcc has estimated that it has a gwp of 72 on 20y scale and 25 on 100y scale.(laurent, 2018) hence, taking into account the amount of ghg emissions in the atmosphere, methane is the second most significant ghg behind carbon dioxide contributing to global warming. as per ipcc, it contributes almost 1 w/m2 to paul, et al.: shale gas: an indian market perspective international journal of energy economics and policy | vol 11 • issue 1 • 2021130 global warming behind co2 which contributes 1.66 w/m 2. this has raised a concern regarding safeguarding of the planet and ecology as a whole because the concentration of methane in the atmosphere has been on a continuous steady rise for many years. (hultman et al., 2011 and padhy et al., 2016). 5. indian shale scenario indian shale oil and gas industry is at a very nascent stage. not only are the “technically recoverable shale gas resources” in india very less, but the research and the technology employed behind exploration and extraction of shale oil and gas is also very limited in india. although the government of india is slowly considering shale gas resource as a viable source of energy, the indian shale market is far behind the giants like usa and china. the exploration and exploitation of indian shale gas will need the acquisition of advanced exploration and extraction technologies and a large amount of drilling. hence, commercialization of indian shale gas is at least 7 years away (ingole et al., 2014 and mop, india). to identify resources of shale oil and shale gas in the country, government of india, with the help of national organisations as well as international organisations, has undertaken research studies. although obtained results do not show consistency, the country is said to hold promising reserves of the resources. as per the study by the us agency energy information administration (eia) in 2010, only 61 tcf of shale gas potential lied in the indian sedimentary basins. while when the same agency did a study next year, 2011, it asserted 290 tcf of shale gas in four main basins while in 2013 they asserted the potential presence of 87 billion barrels of shale oil and 584 tcf of shale gas in the same basin areas. ongc asserted the presence of shale gas of volume 187.5 tcf inside 5 basins while schlumberger was very optimistic to state the shale gas presence of 300–2100 tcf all over the nation. in case schlumberger is true, it will put india ahead of most of the shale gas producing giants in today’s world. but as eia’s study is the most cited study by experts all over the world, their survey can be considered to be closest to reality. the above mentioned possible amount of shale gas is distributed all over the indian subcontinent but can be mainly found in the following basins: • krishna-godavari basin (kg basin) • indo-gangetic basin • cambay basin • gondwana basin • cauvery basin • assam and assam-arakan basin. a total of 50 blocks are distributed amongst the above-mentioned basins. the technological prowess of india in shale gas market might not be much compared to usa, china or other giants, but india, is in the initial stage of shale gas production is showing promising advancement in the future towards the development of shale gas resources. india, thus as of now, have employed following techniques and technologies in the shale gas production from the indian sedimentary basins: • wide azimuth surveys • long offset 2d seismic surveys for deeper imaging • onshore carpet 3d surveys • 3d-3c/4d seismic surveys • broadband surveys • bean psdm processing • node-based wide-angle refraction cum reflection profiling • discrete fracture network analysis • csem surveys and microgravity data for delineation • permeability structure analysis and fluid replacement studies • common reflection angle migration processing (ariketi et al., 2015). 5.1. shale gas policy of india directorate general of hydrocarbons (dgh) is the upstream sector regulating body of india which was established in the year 1993. it operates under the ministry of petroleum and natural gas (mopng) which is the governing body that drafts the shale gas policy. indian shale gas policy was announced on 14th october 2013. government of india has issued certain guidelines regarding “new exploration and licensing policy (nelp)” in 1998. under the policy, the first round of the bidding process for exploration blocks commenced in 1999 (ross, 2014). the shale gas policy initially gave exploration and exploitation permission to national oil companies (nocs) viz. oil and natural gas corporation (ongc) ltd. and oil india ltd. (oil). exploration blocks were awarded on nomination basis to the nocs. following are brief highlights of the indian shale gas policy: • three assessment phases have been given to the nocs for exploration of shale oil and gas viz. phase-i, phase-ii and phase-iii with a time duration of 3 years each • the policy obligates the nocs to follow a work program with commitment concerning the following• water sourcing and disposal eia baseline studies • geological and geophysical (g and g) studies • test well drilling • hydraulic fracturing • study of geochemical properties • s t u d i e s r e l a t e d t o g e o h a z a r d / g e o m e c h a n i c a l / geotechnical properties • assessment of resource of shale oil and shale gas. the above-mentioned possible amount of shale gas is distributed all over the indian subcontinent but can be mainly found in the following basins (shale oil and gas, 2020).: the least no. of mining lease (ml)/petroleum exploration license (pel) areas to be taken up by nocs are: (shale gas policy, 2003) phase/company ongc oil phase i 50 5 phase ii 75 5 phase iii 50 5 total 175 15 grand total 190 • nocs shall apply for a grant of shale gas rights for ml/ pels to be taken up in the first phase of assessment within six months of notification of this policy • total exemption from customs duty and additional charges on customs for specified goods needed in connection with paul, et al.: shale gas: an indian market perspective international journal of energy economics and policy | vol 11 • issue 1 • 2021 131 petroleum operations undertaken under petroleum licences or mining leases issued on nomination basis would be available for e and e of shale oil and gas resources • the noc shall submit, monthly, a report regarding production and sale of shale gas and shale oil to the dgh • holder of pel/ml will be responsible for ensuring the health, safety and environment (hse), the site restoration and adoption of the best industry practices and follow statutory requirements for all objectives under the license and mining lease • royalty, cess and taxes on shale gas and oil will be payable at par with conventional gas/oil being produced from the respective areas at the prevailing rate • phase-i will commence on the date of the agreement granting permission to the company. phase-ii will begin after the conclusion of phase-i and phase-iii after the end of phase-ii • the company shall pay to the government, within 60 days following the end of the assessment phase, an amount which shall be equivalent to the liquidated damages (ld) of usd 0.25m per pel/ml area. assessment phase can be extended by 1 year • withdrawal from shale oil and shale gas operations after g and g studies are carried out without ld would be allowed in consultation with dgh in case the assessment shows the absence of shale gas and oil resources • after completion of the assessment phase, the company needs to prepare an estimate of the potential production of shale oil and shale gas to be achieved vis-à-vis wp, if any, and submit “field development plan (fdp)” to the dgh in 12 months. the profile of annual production with a count of producing wells has to be submitted as well • on submission of the annual production profile vis-à-vis wp, the company has to start development activities under 6 months • eia study is to be carried out by the companies from the list of companies authorised by moef at the cost of the decided project proponent • company has to take care of the following before undertaking shale gas and oil exploration in any of the fields: (a) adequate water availability suitable for fracking. approval from the central ground water authority (cgwa), the state ground water authority (sgwa) and other regulatory institutions is prerequisite. (b) taking approval of the concerned state pollution control board (spcb) for the treatment and disposal of wastewater and ensuring appropriate action (shale gas policy, 2020). 5.2. challenges for shale gas development in india challenging geological conditions concerning the wide variety of the ground and underground properties that vary from place to place. this results in a variety of shale found in different places in the country. 5.2.1. technology and knowledge india also lacks that level of technical sophistication and expertise in the field. technology can be imported but it is expensive leading to higher production costs. also, the workforce that is employed for the extraction of the oil and gas need to be skilled and should have sufficient knowledge of the processes involved. 5.2.2. lack of competitive industry willing to take risks the responsibility of the development of shale resources in india falls entirely in the hands of government nocs viz. ongc and oil. hence there are no private players, big or small, who can serve as a competition for these companies. although competition is indeed necessary for the innovation to take place in the shale industry. 5.2.3. subsurface rights in india, the owner of the land does not own the minerals that are found under the land. hence, there is often seen disputes regarding the same that needs to be settled first hand. 5.2.4. insufficient pipeline network india has less than 10,000 km of trunk pipeline in india compared to 500,000 km that of usa. this limits the areas where shale gas can be explored as exploring in new areas need ensured pipeline network in that area. 5.2.5. restricted access to pipelines similar to the carriage and content separation in the electricity sector in india which happened recently, the usa has already applied the same concept in their gas network where gas producers and carriers are separate. in india, the gas producer owns the pipeline network as well and hence will not transport gas produced by other producers. 5.2.6. regulatory framework a concrete framework is yet to be established in india. it was only by 2013, that the government of india came up with a policy for shale gas production. 5.2.7. historical speed of development of the industry indian shale gas industry is at a very nascent stage. hence it does not have a significant history or historical records to look at for reference while working on the present and prospects of shale gas production. 5.2.8. competition from alternatives shale gas revolution takes time. although alternative unconventional resources like tight gas, coalbed methane (cbm) as well as the conventional oil and gas are much easier to produce, it is important to continue putting efforts in the development of shale gas resources as well regulated the prices of shale gas to keep it as an economically recoverable resource of energy (umekwe, 2019). 5.2.9. screening shale gas exploration targets as shale gas is yet to be effectively developed in the indian market, the government has not yet set any concrete targets that the nocs can look forward to achieving. 5.2.10. predicting production rate since india lacks advanced technology to study the reservoir and technologies involved in exploration and extraction of shale reserves, it is difficult for the nocs to determine the rate of production of shale gas and shale oil effectively. this disturbs the forecasting and scheduling of supply. paul, et al.: shale gas: an indian market perspective international journal of energy economics and policy | vol 11 • issue 1 • 2021132 5.2.11. determining drainage areas the fracking fluid used for the extraction of shale oil and gas cannot be used again since it contains a concentration of harmful and toxic chemicals. thus, this fluid needs to be drained to a closed safe pit where it will not be in contact with any flora or fauna habitation. this is a difficult task as such lands need to be searched for and extreme care needs to be taking while disposing of fracking fluid (shcherba et al., 2019). 5.2.12. lack of political will apart from conflicts between neighbouring nations, india also needs to take care of the internal conflicts which can be in the form of corruption, political instability, bureaucracy, local mafia and prohibitive regulations that lead to delays in schedule and subsequent losses. 5.2.13. water scarcity in the hydraulic fracturing process, a huge quantity of chemically treated water is used which is never reused again. hence, it needs to be disposed of and a new batch of water needs to be again chemically treated and again disposed of away. this consumes a massive quantity of water resources. india, being a tropical country is already in a waster stressed condition and as per the energy and resource institute (teri), india is approaching the drought benchmark of 1000 cubic metres per capita consumption. it is estimated that water consumption will increase by over 50% in the next 12–15 years while during the same period, the supply will increase by only 5–10%, thus, leading to a situation of water scarcity. there is a decreasing trend seen in the water availability per capita in india over the years from 1991 to present and also extrapolating the graph with estimation till 2050. as can be seen, the availability has dropped down from around 2300 l in 1991 to 1150 l in 2050 (as per the estimation). the current data sits somewhere around 1400 l per capita. 6. global shale gas recoverable shale resources are spread all over the world in an irregular pattern. although shale rock is practically evenly distributed in the world, its recoverability varies from place to place depending on the depth at which the gas-bearing layer is situated, which may vary from 200 m to 7000 m. some have ample shale gas reserves; some have few while some have none. hence, it is important to focus our attention to the countries who have ample of shale reserves as they are the hubs of innovation and shale gas development. if the shale gas reserves have to be quantified, it takes huge efforts has many of the basins in the world cannot be accurately estimated for the shale gas content. as per the us department of energy, the quantity of technically recoverable shale gas is more than 200 tcm distributed mainly amongst 41 countries. shown in table 1 are the top 12 countries with the highest amount of recoverable shale gas reserves. it will not be fair if we take a look at only the top countries having recoverable shale gas. to have a comprehensive study, we must look at the reserves of shale oil and gas region-wise, as studying the topic country-wise will be very difficult. hence, the shale resources can be demographically separated into six regions as asia and oceania, north america, latin america and the caribbean, africa, the european union and eastern europe. as you can see in table 1, the asia and oceania is the region with the biggest share in the regional distribution of recoverable shale resources, thanks to china of course. following, the second region in the list is north america because of the shale gas reserves in the united states and how they are successful in exploiting the shale resource as for the credit goes to the american shale revolution (salygin et al., 2019; li et al., 2019). thus, if one wants to see the bigger scenario from the perspective of indian shale market and where it stands in the international shale market and where and why it has lagged, one needs to have a comparative study done between the shale oil and gas market of the top countries as mentioned in the above list and the indian shale gas market. but for our ease of study and content understanding, let us study only the chinese and the american shale gas markets. 6.1. the chinese shale market versus indian shale market china has achieved the first position in the above list due to the advancement in their technical studies, techniques and procedures, thus, increasing their shale gas production prowess. they have invested heavily in r and d and have excelled in employing techniques of drilling and hydraulic fracking which enables them to dig wells till the depth of 3500 m, or even 4000 m. china has made a breakthrough in their production of shale in 2017 when successfully developed continental deposits of shale resources. the carbon dioxide gas is pushed in the reservoir at high pressure and shale gas starts to flow back into the reservoir, thus reducing the environmental impact as well as saving huge on water resources. the us energy information administration (eia) estimates that the shale gas reserve in china is about 1247.85 tcf, while the international energy agency claims it to be 918.18 tcf and china national petroleum corporation claims it to be 1084 tcf, which is much higher than what eia estimated for india. hence, they have greater raw material in hand to develop as an economically viable unconventional energy resource. table 1: country-wise highest recoverable shale gas reserves. (adapted from salygin et al., 2019 and li et al., 2019) country trillion cubic feet (tcf) trillion cubic meter (tcm) percentage china 1115 31.6 14.7 argentina 802 22.7 10.6 algeria 707 20 9.3 us 623 17.6 8.2 canada 573 16.2 7.6 mexico 545 15.4 7.2 australia 429 12.2 5.7 south africa 390 11 5.1 russia 285 8.1 3.8 brazil 245 6.9 3.2 uae 205 5.8 2.7 venezuela 167 4.7 2.2 world 7577 214.5 paul, et al.: shale gas: an indian market perspective international journal of energy economics and policy | vol 11 • issue 1 • 2021 133 moreover, the gas pipeline network in china is far more developed than that of india. this enables the country to positively explore new areas for shale oil and gas as the transportation infrastructure is readily available. this is not the case with india where the gas pipeline network is limited and new pipelines need to be constructed till the surveyed reservoir site before the production process is started on the site. as far as the extraction of shale is concerned, although china has all the technologies and infrastructure in place, it still is in the initial phase of assessment of resources. china, under its 12th fiveyear plan, 2012, aimed to complete the initial assessment of shale gas resources and confirm current reserves. going ahead, under the 13th five-year plan, china planned on scaling up development of shale gas and its exploration in 19 regions. it should be noted that the estimates about the reserves in china declared by various agencies are very close to each other in amount. the same is not true for india. thus, we can safely say that india lacks effective exploration and survey techniques that china has which it can use to determine its shale gas reserves to a high level of accuracy. china has not yet finalised its shale gas policy which will provide guidelines for the extraction of shale oil and gas in the country. on the contrary, india has been quick in establishing a shale gas policy which was announced by the ministry of petroleum and natural gas (mopng) on 14th october 2013. these guidelines addressed specifically to shale gas production. but the chinese policy is suspected to mirror the policy related to cbm. similar to chinese state-owned oil companies, indian state-owned and private oil companies are searching for foreign investments. however, india’s aggression in the same cause is not as much as that china’s and it is not as widespread either. china being a country with very high economic growth rate and a trillion-dollar economy, can afford to pay huge amount of money for importing technologies and a high premium on resources. on the contrary, some foreign investments in india shale faced few complications and indian companies are not in a state to pay a huge amount of premium for the resources either (xuli, 2016). 6.2. the us shale market versus indian shale market the shale gas exploration and exploitation in the usa started much early compared to the rest of the world. the decade of 2000s is said to witness a revolution in shale gas industry of the us. by the year 2015, shale gas production had already started on a commercial scale in the us and canada with both of them holding 87% and 13% of world shale production respectively at that time. it is because of this early head start, the usa has been successful in recovering shale resources much more effectively than the rest of the world. current statistics show that in 2018, shale oil production reached 329 million tonnes and shale gas production reached 607.2 million cubic metres in the united states (zou et al., 2014). the us shale revolution has seen a rapid rise in shale oil and shale gas production and consumption in the nation. the contribution of shale resources in the american energy mix has increased by 5% in 2000 to 29.2% in 2016. this impressive growth has made the country a net gas exporter from a net gas importer. thus, shale gas has effectively reduced the consumption of natural gas whose production reduced at an average rate of −0.14% per annum. in a decade long development of shale resources, the us invested heavily in r and d and successfully devised advanced technologies that increased the efficiency of the operations in the production process. for instance, the technique of multi-pad drilling helped increase the economies of scale as it decreased the number of rigs required for drilling a similar number of wells. the us has also come up with a new extraction method called “anhydrous rupture method” in which a mix of water, sand, gel and chemical reagents are used along with gas in liquid form. on a demographic perspective, the us is a huge nation with much less population compared to china and india. hence, they have a lot of lands uninhabited by humans. thus, making a large vacant area available for shale gas exploration. even if it is inhabited, the local population can be easily rehabilitated to a different location. this is a herculean task when it comes to indian demographical and population situation. also, since the us has such low population density, the number of people who are affected by the activities of shale gas production is much less than that in india, thus reducing the risk of health issues to a great extent. the mineral rights of the minerals found under the land remain with the landowner in the us compared to india, where it is not the case. this helps the government to easily take up the ownership of land and employ it to develop shale gas. this, along with other factors, contributing to ease of land availability, has helped the us to effectively harness the shale resources. this, in turn, has dropped the production costs involved in the whole operation. the production costs in india are much higher than that of the us. the reduction in production costs has ultimately reduced the prices of wholesale electricity at the consumer side for both residential as well as industrial sectors. this, in turn, helps in boosting industrialisation and urbanisation on a broader scale. if shale resource is currently used to feed power into the electricity grid in india, the cost of electricity is likely to go up as the production cost in shale production in india are still high. the boom of the shale industry in the usa has also led to job openings and thus has increased employment in the country. the sector has employed 601,000 people across the shale oil and gas value chain (zou et al., 2013). some of the factors that set apart the us shale industry from the indian shale industry are: • advancement in hydraulic fracturing technologies • advancement in horizontal drilling technologies • surge in gas prices in india even if there is a continuous increase in demand for the oil and gas resources, thus, increasing the cost of the services • investment in r and d • pipeline infrastructure for oil and gas throughout the country • easy leasing framework • stable fiscal regimes • tax credits. paul, et al.: shale gas: an indian market perspective international journal of energy economics and policy | vol 11 • issue 1 • 2021134 7. conclusion it can be safely concluded that the indian shale market is far behind the likes of giants like china and the us. the government needs to, first, invest in r and d related to the exploration of shale gas and shale oil. this will help the government accurately determine the quantity of recoverable shale gas present within the national boundaries. this data will further enhance the forecasting and scheduling of production of shale resources and thus enhance the calculation of estimated revenue and costs. as a result, the government can formulate a concrete framework for the development of shale gas and shale oil resources. either india needs to heavily invest in r and d or import technologies from the developed countries. either will greatly increase the capital cost but will aim to reduce the operational cost to a greater extent. also, the thing about importing technology is that the particular technology was successful in a particular environment and operating condition. hence, it may not operate with the same efficiency in local indian conditions. thus, india needs to develop technologies that are suitable for indian conditions. not just for the sake of shale gas development, but for overall fluid transport, india needs to urgently work on its pipeline network which needs to be robust, safeguarded and very effectively spread throughout the indian landmass. that way, the energy resources that are explored at any place in the country can be effectively supplied to the refineries for further processing on the upstream side as well as the transportation of fuel and its distribution on the downstream side. also, these pipelines will be operative for a long period. india needs to take into account the water scarcity present in the country which gets severe during the summer season. hence, it would be great if india can come up with a technology that can replace hydraulic fracking and use much less amount of water, something like how china uses carbon dioxide as fluid to save on water. if india looks forward to work on economical extraction of shale gas, it needs to settle disputing factors which may not be monetised but are a strong obstruction viz. bureaucracy, political opposition, land disputes and tax credits. although not all issues, like corruption and local mafia threats, can be eliminated it should be reduced wherever possible. one concept from the us that might be effective in india as well as the separation of ownership of carriage and content of the gas. that is, the gas generator will have the responsibility to produce the demanded amount of gas resource while the ownership of the pipeline network should be in the hands of a separate company, not the generator, and will have the responsibility to expand and maintain the pipeline network. that way, the gas generator cannot own the flow of gas in the grid and restrict the supply of gas from competition to earn more share in an unethical way. the government of india can sign various mous with national and international agencies who will contribute in exploration and exploitation of indian shale gas resources. proper incentives should be provided to keep their interests as well as attract more companies and increase the competition. this is will significantly increase the innovation in the shale gas sector in attempts to reduce the capital and operating costs, which in turn will reduce the final shale gas prices. references administration, u.e. (2015), technically recoverable shale oil and shale gas resources. washington, dc: u s department of energy. alexander, w., bartik, j.c. (2019), the local economic and welfare consequences of hydraulic fracturing. american economic journal: applied economics, 11(4), 105-155. anjirwala, h., bhatia, m. (2016), shale gas scenario in india and comparison with usa. international journal of science and research, 5(8), 1069-1075. ariketi, r., behera, b.k., bhui, u.k. (2015), shale gas in india: opportunities and challenges. international journal of scientific research, 4(3), 2277-8179. chen, x., bao, s., hou, d., mao, x. (2012), methods and key parameters for shale gas resource evaluation. petroleum exploration and development, 39(5), 605-610. dwivedi, a.k. (2016), petroleum exploration in india a perspective and endeavours. indian national science academy, 82, 881-903. fangzheng, j. (2019), re-recognition of “unconventional” in unconventional oil and gas. petroleum exploration and development, 46(5), 847-855. glass, k. (2011), shale gas and oil terminology explained: technology, inputs and operations. washington, dc: environmental and energy study institute. gong, b. (2018), the shale technical revolution cheer or fear? impact analysis on efficiency in the global oilfield service market. energy policy, 112, 162-172. hamada, g.m., singh, s.r. (2018), mineralogical description and pore size description characterization of shale gas core samples, malaysia. american journal of engineering research, 7(7), 1-10. hoffman, a.o. (2014), shale gas and hydraulic fracturing no. 34. stockholm: stockholm international water institute, siwi. honglei, z., yan, w. (2020), an optical mechanism for detecting the whole pyrolysis process of oil shale. energy, 190, 1-8. howarth, r. (2019), ideas and perspectives: is shale gas a major driver of recent increase in global atmospheric methane? biogeosciences, 16, 3033-3046. hultman, n., rebois, d., scholten, m., ramig, c. (2011), the greenhouse impact of unconventional gas for electricity generation. environmental research, 6, 044008. ingole, p.r., kathoke, t.b., bhagat, a., bhoyar, v.v. (2014), oil shale: the next energy revolution. international journal of innovative research and studies, 3(7), 397-406. jarvie, d.m., hill, r.j., ruble, t., pollastro, r.m. (2007), unconventional shale-gas systems: the mississippian barnett shale of north-central texas as one model for thermogenic shale-gas assessment. aapg bulletin, 91(4), 475-499. kumar, b.v., kumar, a., raghavendran, c. (2017), shale oil and gas in india. ssrg international journal of thermal engineering, 3(2), 1-7. laurent, a. (2018), commodities at a glance-shale gas. geneva, switzerland: united nations conference on trade and development. li, x., mao, m., ma, y., wang, b. (2019), life cycle greenhouse gas emissions of china shale gas. resources, conservation and recycling, 2019, 158. nakano, j., pumphrey, d., price, r.f. jr., walton, m.a. (2012), prospects paul, et al.: shale gas: an indian market perspective international journal of energy economics and policy | vol 11 • issue 1 • 2021 135 of shale gas development in asia. washington, dc: centre for strategic and international studies. negi, b.s., pandey, k.k., sehgal, n. (2017), renewables, shale gas and gas import striking a balance for india. energy procedia, 105, 3720-3726. padhy, p.k., kumar, a., chandra, y.r., das, s.k., jha, s.k., advani, d.r. (2016), shale oil exploration from paleocene-early eocene sequence in cambay rift basin, india. indian national science academy, 82(3), 945-963. ross, m.m. (2014), diversification of energy supply: prospects for emerging energy sources. mandaluyong city, philippines: asian development bank. salygin, v., guliev, i., chernysheva, n., sokolova, e., toropova, n., egorova, l. (2019), global shale revolution: successes, challenges and prospects. mdpi sustainability, 2019, 1-18. shale gas policy. (2020), ministry of petroleum and natural gas. available from: http://www.petroleum.nic.in/sites/default/files/ circulars_notifications_3.pdf. shale oil and gas. (2020), directorate general of hydrocarbons. available from: http://www.dghindia.org/index.php/page?pageid=37. shcherba, v.a., butolin, a.p., zieliński, a. (2019), current state and prospects of shale gas production. iop conference series: earth and environmental science, 272, 032020. singh, h.k., khanna, a.r. (2012), india’s energy options: the road ahead. icrier wadhwani chair in india us policy studies. p1-27. umekwe, d.b. (2019), shale-oil development prospects: the role of shale-gas in developing shale-oil. mdpi energies, 2019, 1-21. xuli, l. (2016), shale-gas well test analysis and evaluation after hydraulic fracturing by stimulated reservoir volume (srv). natural gas industry b, 3(6), 577-584. zou, c., yang, z., zhang, g., hou, l., zhu, r., tao, s., yuan, x., dong, d., wang, y., guo, q., wang, l. (2014), conventional and unconventional petroleum “orderly accumulation”: concept and practical significance. petroleum exploration and development, 41(1), 14-30. zou, c., zhang, g., yang, z., tao, s., hou, l., zhu, r., yuan, x., ran, q. (2013), concepts, characteristics, potential and technology of unconventional hydrocarbons: on unconventional petroleum geology. petroleum exploration and development, 40(4), 413-428. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 1 • 2021 333 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(1), 333-340. the causal relationship between, electricity consumption and economic growth in kingdom of saudi arabia: a dynamic causality test ibrahim abdelrasoul mohammed belal1*, sumaya awad khader ahmed2,3, faouzi hedi boujedra1 1department of economics and finance, college of business administration, university of hail, ha’il, saudi arabia, 2department of economics, sudan academy of science, sudan, 3department of business administration, al jouf university, saudi arabia. *email: fize1970@gmail.com received: 20 july 2020 accepted: 22 october 2020 doi: https://doi.org/10.32479/ijeep.10488 abstract the main objective of this study is to empirically test whether there exist short run and long run causality between, residential electricity consumption (rec), industrial electricity consumption (iec) and economic growth in kingdom of saudi arabia (ksa). time series data for this study spans from 1990 to 2019. the study adopts granger causality and co. integration analysis to estimate a vector error correction model (vecm). results from error correction model show that there exist long run co. integration relationship between targeted variables. in addition, vecm results indicates that, industrial electricity consumption is inelastic to the changes in electricity prices with respect to economic growth, while residential electricity consumption shows elastic relationship. granger causality test indicates there is unidirectional relationship, running from economic growth to industrial electricity consumption, which lead to accept, proactive (conservative) hypothesis. in this case, energy conservative policy will have little or no effect on economic growth. nevertheless, results proof acceptance of neutrality hypothesis in the case of residential electricity consumption and economic growth. the study therefore, recommends that in saudi arabia, policy makers should consider expanding their energy-mix alternatives, in order to cope with the future industrial electricity demand arising from increased economic growth. keywords: electricity consumption, gdp growth, co-integration and causality jel classifications: o3, o4 1. introduction ksa is one of the largest exporter of petroleum and possess about 18% of the world petroleum reserves, saudi arabia oil and gas sector account for about 50% of the gdp, and about 85% exports earning (maghrebi et al., 2018). in late april 2016 ksa vesion2030 announced, based on three main pillars, they are a vibrant society, a thriving economy and an ambitious nation. a key goal of the thriving economy build on themes of diversified economy of less dependent on oil revenues, to achieve this goal and others, saudi arabia authority announced a set of parallel programs, which include the national transformation programs, which providing more information about the implication of energy sector (fattouha and amrita 2016). as one of the main energy policy implications, at the end of december 2015, the saudi arabian government raised some of its administered retail energy prices. for example, the price of automotive diesel fuel increased from 0.25 saudi arabian riyal (sar) per liter to 0.45 sar, while the price of 95 gasoline increased from 0.60 sar to 0.90 sar increases of 80% and 50%, respectively (platts, 2015). in addition, the price of natural gas increased from $0.75/mmbtu to $1.25/mmbtu, an increase of 67% (platts, 2015). however, if saudi arabia efforts to transitions towards a more diverse and energy efficient-economy are unsuccessful, then social wale fare this journal is licensed under a creative commons attribution 4.0 international license belal, et al.: the cuasal relationship between, electricity consumption and economic growth in kingdom of saudi arabia: a dynamic causality test international journal of energy economics and policy | vol 11 • issue 1 • 2021334 will remain vulnerable to sowing in international oil markets, increasing the risks of declining gdp growth over time. in ksa, the retail prices of energy (oil products, natural gas, and electricity), have traditionally been set by public authorities, resulting in the retail prices being below the international market price (ecra, 2015). given the fact that, energy prices, more specifically oil price has been historically, volatile and uncertain; inevitably it influences ksa economy differently, at different point of time. electricity consumption in ksa has been a accompanied by large increase in gdp growth. indeed, ec in saudi arabia grow annually at a rate of 12% and 25% during 1970s and 1980s, and by 6%, this high level of ec is due to some main factors, such as growth of industrial sector; electricity subsidies and modernization of cities (narayan and smyth, 2009). the largest proportion of ec in ksa is attributed to the residential sector account about 53% of total ec, followed by industrial sector account about 18% (on average) of total ec, this mean that residential sector derive ec rather than industrial sector, which is the case in many developed and developing countries. nevertheless, many measures have taken by ksa authority to reduce the adverse effects of climate changes and global warning to achieve sustainable development. for instance, acceptance of kyoto protocol of climate changes (2005), and launch of 2008 national energy program (nep), which takes about eight measures aimed to increase energy efficiency by 30% up to 2030 (mezghany and haddad, 2016). the step that has been taken by the saudi arabia government to the environment by preserving energy resources have important implications for the sustainable development of the country. notwithstanding, any effective energy policy should consider the dynamic nature of the relationship between ec and gdp growth should have a long-term vision (sari and soytas, 2009) and micheal and alegre (2009). therefore, in this paper we try to empirically analyzes the impact of changes of electricity consumption on real gdp growth, during the period between 2000 and 2019, to explain significances of energy policy in short-run as well as in the long-run. in fact, the effect of electricity consumption resulting from electricity tariff changes, is differ from one country to another, depending on economic structure of the country, historically, there is no exactly defined direction and causality relationship between electricity consumption, and economic growth. in literature there are four energy consumption and gdp growth hypothesis namely, growth hypothesis; proactive hypothesis; neutrality hypothesis and feedback hypothesis (syzdykova et al., 2020). growth hypothesis indicates economic growth is energy dependence; if there exist one-way causality from energy consumption to economic growth in this case increasing energy prices aiming at energy saving will adversely affect economic growth. in the case of proactive (conservative) hypothesis, it is one-way causality running from growth to energy consumption; in this case, energy conservative policy will have little or no effect on economic growth. on the other hand neutrality hypothesis, exist when there is lack of causal relationship between energy consumption and economic growth, finally feedback hypothesis mean, there is two-way causal relationship between energy consumption and economic growth which shows a complementary effect between the two variable (apergis and payne, 2010). the choice of saudi arabia for this study motivated by the fact that saudi arabia has experienced a sharp increase in energy consumption and carbon emissions in recent years because of its strong economic and industrial growth. historically high international oil prices and large domestic fuel subsidies also play an important role in the recent economic growth and high-energy consumption in the country. this study aims to test empirically the causality between energy consumption represented by electricity consumption for both residential and industrial sectors, and real gdp growth in ksa. the principal hypothesis of this study based on various literatures and other related studies; such that, there exist bidirectional growth hypothesis, running from electricity consumption of both sectors to gdp growth in ksa. using time series data for the period extended from 1990 to 2019, in the second part theoretical background presented about the historical development of theories of economic growth, third part, summarizes previous studies on the relationship of electricity consumption, and economic growth. the fourth part explain the methodology and the sources of data. in the fifth part, empirical analysis and results discussed, finally main concluding points and recommendations presented. 2. overview of electricity sector in saudi arabia despite stable and favorable macroeconomic indicators in the past years, the saudi economy faces many challenges. the main concerns are related to its demographic dynamics leading to an urgent need to generate enough employment for its young population and addressing the issue of its energy system sustainability (said and marie 2015). the ksa government has prioritized sustainable measures as gateway to better future. as mentioned earlier, the saudi 2030 vision was implemented in april 2016; in this respect, the government has taken serious steps to change the country’s economy, from oil-based economy to multisources economy. therefor saudi government introduced many programs and other efficiency measures. for instance in 2017 the international energy (iea) stated that, ksa was targeting 120 gigawatt electricity generating capacity by the of 2032 to accommodate the country growing electricity demand, in 2018 the government increase investment fund to increase electricity generation to about 200 gigawatt by the end of 2030 (institute for energy economics and financial analysis, 2018). in the context of hot-arid climates, ksa was ranked among the top 10 countries of the highest electricity consumption, nevertheless electricity generation consume nearly one-third of daily oil production in ksa (alshibani and alshamrani, 2017). notwithstanding, annual electricity usage growing by approximately 6-8%, according saudi electricity company (sec) residential and industrial sectors consuming about 71% of electricity power, commercial consumption 12%, government consumption 11% and about 2% of electricity consumed by agricultural sector (m.o.w.a. electricity, 2014). climate is the major factor as 70% of electricity sold attributed to air conditioning. other factors such as population growth, and rabid increases of industrial sector derived electricity consumption. in light of these facts, there is a wide acceptance in ksa; this path of electricity consumption is not sustainable in long run. because the rising consumption of electricity and other energy generation belal, et al.: the cuasal relationship between, electricity consumption and economic growth in kingdom of saudi arabia: a dynamic causality test international journal of energy economics and policy | vol 11 • issue 1 • 2021 335 sources would result of a net loss of about more than 3 million barrels of oil per day, or so cold “burning oil to get cool” (lahn and stevens, 2008). the sectoral distribution of electricity consumption presented in the following figure 1. to sum up, it is essential to make plans to promote alternative energy sources. nonetheless, knowing the causes of high-energy consumption is critical to ensure holistic, sustainable future development. the ksa government implemented several action to avoid future economic crisis as a consequences of high-energy consumption, which include implementing of new saudi building code (sbc) and activate saudi energy efficiency center (seec) and plans for renewable energy sources. notably the decision to stop subsidizing the electricity has led to growth in energy efficiency uses and awareness (apicorp energy res, 2018). the focus of this study is to test empirically the cases of rabid increases of electricity consumption, with reference to different measures, which has been taken by ksa government to sustain electricity generation and distribution. notwithstanding, various model has been utilized to explain electricity-growth relationship, this study rely on emerging model to explain causal relationship, between residential electricity consumption (rectt), industrial electricity consumption (iect) and gdp growth in ksa, to evaluate the significances of energy policy in short-run as well as in the long-run. 3. literature review number of past studies examine the relationship between electricity consumption and gdp growth causal relationship, some of these studies focused on group of countries, while other study individual countries sheilla et al. (2016), dossou, (2019), hasan et al., (2017), njindan (2014) and nyasha et al., (2016). the fact that electricity consumption represent the highest percentage of energy consumption in most countries has shifted debates to what our study examine. the first group concludes that electricity consumption causes economic growth (electricity led growth thesis); the second group concludes that economic growth causes electricity consumption (the growth-driven electricity consumption thesis). the third group concludes that there is bidirectional causality between electricity consumption and economic growth (the feedback thesis); finally, the fourth group argues that there is no causal link between electricity consumption and economic growth (the neutrality thesis) bernard (2016). the electricity led growth studies has been confirmed by studies such as, masih and msih (1996) for india, lee (2005) for 15 developing countries, ho and siu (2007) for hong kong. the growth-driven hypothesis paper has been confirmed by studies such as, kraft and kraft (1978) for usa, al-iriani (2006) for the gulf co-operation countries and rufael (2006) unisa (2016) and odularu (2008) for the case of cameron, ghana and nigeria. in addition, feedback hypothesis was identified by various studies such as, asafu-adjaye (200) for thailand and philippines, soytas and sari (2003) for argentina and odhiambo (2009) for the case of tanzania and south africa. others studies found no causal link between electricity consumption and gdp growth such as, erol and chu (1987), and yu and jin (1992) for the case of the usa; murray and nan (1996) for france; germany, india, israel, luxembourg, norway, portugal, uk, usa and zambia and akinlo (2008) for cameron, cote d`ivoire and kenya. some other studies examine the causal relation between energy consumption as a whole and gdp growth. such as athanasois et al. (2020) and amany (2010) study revisiting the impact of energy prices on economic growth; lesson learned from the european union, they concluded that, for residential electricity sector shows highest level of influence on real gdp, while industrial electricity sector and crude oil price “granger cause” residential electricity prices. gonand et al. (2018), investigates the intergenerational welfare impact of raising administered retail energy prices in saudi arabia, they developed first model of overlapping generation (called megir-sa), it is shown that the additional oil income associated with the increase in domestic energy prices tends to be relatively more beneficial to future generations if it is recycled through public investment. athanasios et al. (2020), study revisiting the impact of energy prices on economic growth; lesson learned from the european union; they concluded that, for residential electricity sector shows highest level of influence on real gdp, while industrial electricity sector and crude oil price “granger cause” residential electricity prices. the following table 1 summarizes some empirical studies examining causal relationship between electricity consumption and economic growth. most of the previous studies focused on the causal relationship between electricity consumption and economic growth, while our study disaggregates electricity consumption in to residential and industrial sectors to test for short run and long run relationship between the targeted variables. mostly important here is policy implications of impact of causality results between the target variables; if growth hypothesis is achieved, it indicates that economic growth is energy dependency, in this case economic policy aimed at raising energy prices to reduce energy consumption or energy saving would adversely affect economic growth. a bidirectional relation between energy consumption and economic growth (feedback) reflect interdependence and complementary effects between energy consumption, and economic growth. in the case of neutral hypothesis energy saving policies may has little or no effect of energy consumption changes on economic growth syzdykova et al. (2020). 4. data and methodology the study adopt causality and co-integration analysis to empirically estimates the short run and long run effects of figure 1: distribution of electricity consumption by sector source: saudi arabia electricity company database belal, et al.: the cuasal relationship between, electricity consumption and economic growth in kingdom of saudi arabia: a dynamic causality test international journal of energy economics and policy | vol 11 • issue 1 • 2021336 electricity consumption(residential and industrial sectors) on real gdp growth in ksa. the study time spams from 19902019, time series data includes real gdp growth, residential and industrial electricity consumptions will be obtain by consulting different sources. real gdp growth data obtained from world band database, and electricity consumption (mwh) received from saudi arabian monetary authority (sama) statistics.to test the main study hypothesis. h1: there is bidirectional growth hypothesis running from industrial electricity consumption (iect) and residential electricity (rect) consumption to gdp growth in ksa, during the study period extended from 1990 to 2019 (bekun et al., 2019). alternatively, h2: there is unidirectional hypothesis running from industrial electricity consumption (iect) and residential electricity(rect) consumption to gdp growth in ksa, during the study period extended from 1990 to 2019 (shabestari, 2018). for the purpose of data analysis, we specify the following steps: 4.1. unit root test unit root test, allow specifying the order of integration, as many econometrics data shows, non-stationary behavior, therefore a series of ∆y = yt–yt-1, is often stationary. then the order of integrated series written as i (1) satisfies the first difference of yt, we use the adf test (dickey and fuller, 1981), (dickey and fuller, 1996) to examine whether a series has a unit root. consider the adf tests as follows: 1 1 t 1 1 1 p t it y ty yφ εβ− + − = ∆ −∆ = +∑ (1) 0 1 1 t 1 1 1t p t i y y ytβα φ ε − − = ∆ −∆ = +∑ (2) 0 1 1 1 1 t 1 1 p it t y t y ytβα α φ ε+ − − =+ ∆ = + ∆ +−∑ (3) from the above, system equations. it is clear that equation(1) did not include either drift or trend, but the drift term α0 added to equation (2) and both α0 and deterministic trend α1 t added to equation (3). if augmenting lag (p) known, augmented test is identical to the simple augmented dicky-fuller test, otherwise, lag dropped until the last lag is statistically significant. based on adf test the following hypothesis tested to obtain stationary of the variables. h0: ϕ -1= 0 or h1: ϕ -1˂0 (4) h0 mean that the variable not stationary h1 mean the variable stationary or has no unit root. 4.2. johansen co-integration test to estimate short-run and long-run dynamic impact, of electricity consumption on gdp growth, johansen and juselus (1990) cointegration test will employ, after determining the optimal lag length (p) for the model. two-time series data for variables xt and yt, co-integrated, if they have the same order of co-integration and there exist a linear combination of these series. in this paper, we apply johansen maximum likelihood method (1991), to obtain the number of co-integration equations. 4.3. estimation of vector error correction model to estimate vecm, based on the previous co. integration test, in order to examine the impact of explanatory variables on gdp growth in ksa. the model presented in the following reduced form equations: lngdpt = b0+b1 lnrect+b2 lniect+ut (5) where: u is the disequilibrium error, t: time series (1990-2019), gdp: is real gdp growth rate, residential electricity consumption (rect), and industrial electricity consumption (iect) in the short run. assuming there is only one co-integrated relationship among the examined variables, and then equation (5) as multivariate model used to obtain the following equation. ut = lngdpt–b0–b1 lnrect–b2 lniect (6) where: ut is the disequilibrium error, shows the range of changes in real gdp, residential electricity consumption (rect), and industrial electricity consumption (iect) in the short run. if the variables are stationary at first difference i (1), and ut is stationary, it mean there exist a linear combination among the variables. if table 1: summary of empirical studies author period country method result kraft and kraft (1978) 1947-1974 usa granger causality eg→ec asafu-adjaye (2000) 1973-1995 india, indonesia co-integration, ecm ec→eg alshehry and belloumi (2015) 1971-2010 ksa johansen co-integration eg↔ec long et al. (2015) 1952-2012 china co-integration analysis eg↔ec shahbaz et al. (2016) 1970-2012 australia vecm eg↔ec jebli and yousef (2017) 1980-2011 tunisia vecm eg ↔ec riti et al. (2017) 1970-2015 china ardl-vecm eg ←ec shabestari (2018) 1970-2016 sweden ardl-vecm eg↔ec bekun et al. (2019) 1960-2016 south africa pesaran et al., 2001 eg←ec iyke, 2015 1971-2011 nigeria vecm ec→eg saleheen khan et al., 2018 1991-2014 kazakhstan adrl and vecm ec→eg kumari and sharma, 2016 1974-2014 india co. integration and granger causality eg→ec anon, 2016 1972-2011 lesotho adrl eg→ec aslan, 12 aug 2013 1978-2008 turkey adrl eg↔ec sekantsi and okot, 2016 1981-2013 uganda adrl and granger causality eg↔ec eg: economic growth, ec: energy consumption, →: represent unidirectional, ↔: represent bidirectional, ~ represent neutral: source syzdykova et al. (2020) belal, et al.: the cuasal relationship between, electricity consumption and economic growth in kingdom of saudi arabia: a dynamic causality test international journal of energy economics and policy | vol 11 • issue 1 • 2021 337 the variables are stationary at first difference i (1), then we can run the following vecm. ∆gdpt = α1 zt-1+lagged (∆gdpt, ∆rect, ∆iect )+є1t (7) ∆iect = α2 zt-1+lagged (∆gdpt, ∆rect, ∆iect)+є2t (8) ∆rect = α3 zt-1+lagged (∆gdpt, ∆rect, ∆iect)+є3t (9) were, zt-1 is the error correction term, obtained from the result of estimation of co-integration relationship, and є is error term stationary at |α1|+|α2|+|α3|≠0. recent developments of the co-integration concept indicate that a vector autoregressive (var) model specified in differences is valid only if, the variables under study are not co-integrated. if they are co-integrated, an error correction model (vecm) should be estimated rather than a var (granger, 1988). hendry and juselius (2000) emphasize the importance of correct model specification. following granger (1988), we use a vecm instead of a var model, since the var model is missspecified in the presence of co-integration. in addition, var models may suggest a short run relationship between the variables, because long run information removed in the first differencing, while a vecm can avoid such shortcomings. in addition, the vecm can distinguish between a long run and a short run relationship among the variables and can identify sources of causation that cannot detected by the usual granger causality test (suharsono et al., 2017). 5. empirical results 5.1. unit roots test in time series analysis, financial and economic data is commonly associated with trending behavior or non-stationary, to determine whether a time series data are stationary or not, an important task to avoid the spurious of estimated model and inaccurate forecasting. for the purpose of this study, it is necessary to test for stationary before running the co. integration analysis. we use the adf test (dickey and fuller, 1981), to examine whether a series has a unit root. equation (3) employed to test previously mentioned hypothesis of equation (4). results of test stationary at level and 1st difference, for gdpt growth, rect and iect variables obtained and summarized in the following table 2. results in table 2, unit root tests at the level, show that the values of adf is less than the critical value at 5% level of significant. this mean that we cannot reject the null hypothesis that the series of gdpt growth, rect and iect were not stationary. but when the variable converted to 1st difference, the absolute values of adf is more than the absolute values of critical values at 5% level of significant for all the three variables, therefore we accept the alternative hypothesis, meaning that gdpt; rect and iect variables are stationary in the 1st differences. this result is in line with most of resent studies that, most of macroeconomic series are non-stationary at the levels, only became stationary after taken the first differences (nelson and plosser, 1982). 5.2. johansen co-integration test in order to run johansen co. integration test to determine whether the variables has short run and long run causal relationship, the model must satisfies some of basic requirements, firstly the series must stationary at first difference not in the level, in the above discussion, unit root test indicates that all three variables are stationary at first difference. secondly, perform johansen co. integration optimal lag length (p) for the model, shown by var lag order selection criteria result presented in the following table. referring to results in table 3, we chose aic optimal lag, in this case, the lag selected by this criteria is equal two, then we can proceed to run the co. integration model to determine whether our three variables gdpt growth, iect and rect has long run relationship or in the long run they move together. then, we apply johansen maximum likelihood method (1991), to obtain the number of co-integration equations and the analysis results shown the following table. table 4 present unrestricted co. integration rank test, it become clear we rejected the hypothesis of having non-co. integration equation, since trace test indicates 1 co. integration equation at 5% level, the estimated eigenvalue ratios and trace statistic also indicate at most there is one co. integration equation in this model. we can conclude that there exist long run co. integration relationship between the series and the model that we are going to estimate is not spurious. 5.3. estimation of vector error correction model (vecm) to identify short run and long run causal relationship between the study variables, in order to determine the responsiveness of one variable to each other’s. vecm estimated based on the test statistics presented in table 4. before running the basic vecm model, we run some of co. efficient diagenetic test to insure if the model has some statistical errors or not. chi-square is significant there for we reject existence of serial correlation, while jarquebera probability indicate the series under study are normally distributed. in addition r2 = 60%, meaning that the model has good fit, and p (f.stat. = 0.007) the overall model is suitable to explain the long run causality between targeted variables. estimates of basic model for the targeted variables presented in the following table. table 2: unit root tests variable level 1s difference t.stat. adf prob*. result t.stat. adf prob*. result gdpt –2.9677 0.933199 0.9945 non-stationary –2.9718 4.498624 0.0014 stationary rect –3.6891 0.985709 0.7443 non-stationary –2.9718 4.923212 0.0005 stationary iect –2.9677 0.152657 0.9340 non-stationary –2.9718 9.214431 0.0000 stationary source: author’s own calculation based on eviews9. results. *mackinnon (1996) one-sided p-values (indicate sig.at 5%) belal, et al.: the cuasal relationship between, electricity consumption and economic growth in kingdom of saudi arabia: a dynamic causality test international journal of energy economics and policy | vol 11 • issue 1 • 2021338 result in table 5, shows one co. integration econometric model of vecm estimates, the results indicate that, there exist long run causality running from iect and rect to gdpt growth , since the error correction term or speed of adjustment c(1) is negative and statistically significant. this result consistent with various studies that energy consumption-driven growth (stern and enflo, 2013). iect is negatively affect gdpt growth in the long run, provide that 1% decreases in iect lead to about 3.9% increases in gdpt growth at 5% level of significant. thus industrial electricity consumption in ksa is inelastic to the changes in electricity prices with respect to gdpt growth. in other words, even if industrial electricity prices raised, industrial electricity consumption did not response to changes because in the long run, industrial sector can absorb these increases, and can levey the burden to the consumers. therefore, electricity conservation policy in ksa must implement with some caution, although the result in this analysis indicate that, electricity tariffs did not pose any risks to gdp growth. this will held true, only when granger causality proof economic growth causes industrial electricity consumption. with respect to residential electricity consumption, result in table 5 indicate that, there exist positive effect on gdp growth providing 1% increase in rect will increase gdp growth by about 6% at 5$ level of significant, this mean that raising electricity tariffs in the residential sector, will decreases rect ,consequently will result in adverse effect on gdp growth. to chick for short run dynamic, wald test employed. results in table 6 indicate, chi-square probability of null hypothesis c(4) = c(5) = 0 is insignificant at 5% level , which mean there is no short run causality running from iect to gdpt growth, also the null hypothesis c(6) = c(7) = 0 shows no short run causality running from rect to gdpt growth in ksa. 5.4. granger causality test according to granger theory, if variables are co. integrated there must be at least one direction of causality between the variables to sustain the long run equilibrium relationship. notwithstanding, engle-granger, 1987, stated that in present of co. integration, there exist always a corresponding error-correction representation. the present of co. integration vector in the electricity consumptiongdp growth model in ksa, shows that the variables included in the model of this study are co. integrated and possess long run relationship. vecm plays an important role in detecting the indigeneity and exogenity of the variables, and direction and causality effects between these variables. since, not captured in the co. integration model (masih et al., 2009). table 7 summarized results of granger causality test based on vecm model as follows: results in table 7 indicates there is unidirectional relationship between industrial electricity consumption (iect) and gdp growth, since the relevant test reject the null hypothesis. this table 3: lag order selection criteria endogenous variables: gdpgt rect iect lag logl lr fpe aic sc hq 0 -1029.404 na 6.20e+30 79.41569 79.56085 79.45749 1 -957.6856 121.3694* 5.02e+28 74.59120 75.17186* 74.75841* 2 -947.6492 14.66860 4.79e+28* 74.51148* 75.52763 74.80410 3 -942.7776 5.995816 7.16e+28 74.82905 76.28070 75.24707 4 -933.5094 9.268215 8.32e+28 74.80842 76.69556 75.35185 source: eviews9 software results.*indicates lag order selected by the criterion table 4: unrestricted co. integration rank test (trace) hypothesized eigenvalue trace 0.05 prob.** no. of ce(s) statistic critical value none* 0.585862 29.94355 29.79707 0.0481** at most 1 0.202468 6.141513 15.49471 0.6788 at most 2 0.001229 0.033200 3.841466 0.8554 source: eviews9 software results. trace test indicates 1 co. integrating eqn(s) at the 0.05 level. *denotes rejection of the hypothesis at the 0.05 level. **denotes stationary at 5% significant level table 5: vecm estimates cointegrating eq: cointeq1 gdpgt(–1) 1.000000 iect(–1) –3.96e-08 (4.3e-08) [–0.92695] rect(–1) 6.06e-05 (0.00051) [0.11943] c –2.109404 coefficient std. error t-statistic prob. c(1) –1.106088 0.315674 –3.503897 0.0024 c(2) 0.138789 0.204744 0.677868 0.5060 c(3) 0.011452 0.176479 0.064889 0.9489 c(4) –9.98e-08 6.35e-08 –1.571044 0.1327 c(5) –9.67e-08 6.57e-08 –1.471080 0.1576 c(6) –0.000370 0.004128 –0.089534 0.9296 c(7) 0.004348 0.004072 1.067714 0.2990 c(8) -0.456559 1.351428 -0.337834 0.7392 source: eviews9 software results table 6: wald test: null hypothesis: c (4)=c (5)=0 normalized restriction (=0) chi-square probability c(4)=c(5)=0 3.031161 0.2197 c(6)=c(7)=0 1.143965 0.5644 source: eviews9 software results table 7: granger causality test results from vecm pairwise granger causality tests lags: 1 null hypothesis obs f-statistic prob. iect does not granger cause gdpgt 29 0.00586 0.9396** gdpgt does not granger cause iect 4.41644 0.0454** rect does not granger cause gdpgt 29 2.38337 0.1347* gdpgt does not granger cause rect 0.74377 0.3963* source: eviews9 software results. **donates 5% level of significant. *donates 1% level of significant belal, et al.: the cuasal relationship between, electricity consumption and economic growth in kingdom of saudi arabia: a dynamic causality test international journal of energy economics and policy | vol 11 • issue 1 • 2021 339 results support proactive (conservative) hypothesis, it is one-way causality running from growth to energy consumption, in this case, energy conservative policy will have little or no effect on economic growth. this finding implies that in ksa economic growth derives industrial electricity consumption. this mean that ksa is growth-dependence industrial electricity consumption, and any indiscriminate energy-saving policy to promote economic growth, may result in adverse effects on industrial sector, therefore policy makers should consider expanding their energy-mix options, in order to cope with the future demand arising from increased economic growth. the result is in line with kraft and kraft (1978) study of us energy-growth relationship and cheng and lai (1997) study of taiwan. result shows that bidirectional or feedback hypothesis developed from the hypothesis of this study, which relate the relationship between industrial electricity consumption (iect) and gdp growth in ksa is invalid. on the other hand, result in table 7, indicates acceptance of neutrality hypothesis, since there is lack of causal relationship between residential electricity consumption (rect) and gdp growth. our finding is in line with khalid (2012), who found the absent of causality between electricity consumption and gdp growth in ksa, but our study is differ slightly from the others. because we focus solely in saudi arabia, while most other studies focus on group if countries, also we disaggregates electricity consumption in to main sectors, namely residential and industrial sector, which adding values to the analysis results. 6. conclusion and policy implications in this study, we try to critically, evaluate the causal relationship between electricity consumption and gdp growth in saudi arabia. using time series data for sample period extended from 1990 to 2019, the fundamental differences of other energy-growth nexus we disaggregate electricity in residential and industrial sectors to capture their effects on economic growth in ksa within multivariate framework. for this purpose, we employ co. integration and vector error correction model to capture short run as well as long run elasticities. two-stapes of engle-granger (1987) methodology followed for estimating vecm. the empirical results, indicate that there exist long run co. integration relationship between the series, while vecm results is quite robust, indicating that in the long run, industrial electricity consumption in ksa is inelastic to the changes in electricity prices with respect to economic growth, while residential electricity consumption shows elastic relationship. granger causality test indicates there is unidirectional relationship between industrial electricity consumption and economic growth running from economic growth to industrial electricity consumption. nevertheless, results proof acceptance of neutrality hypothesis, since there is lack of causal relationship between residential electricity consumption and economic growth. the study therefore, recommends that in saudi arabia, policy makers should consider expanding their energy-mix alternatives, in order to cope with the future demand of electricity arising from increased economic growth. in addition, there is urgent need to address the challenge of fast growing energy demand by attracting more private investment in the electricity sector, and by introducing more competition to increase efficiency and reduce the burden on the public budget. references adedokun, a.j. (2012), oil export and economic growth: descriptive analysis and empirical evidence from nigeria. pakistan journal of social sciences, 9(1), 46-58. akinlo, a.e. (2008), energy consumption and economic growth: evidence from 11 african countries. al-iriani, m.a. (2006), energy-gdp relationship revisited an example from gcc countries using panel causality. energy policy, 34(17), 3342-3350. alshibani, a., alshamrani, o.s. (2017), ann/bim-based model for predicting the energy cost of residential buildings in saudi arabia. journal of taibah university for science, 11, 1317-1329. amany, a.e. (2010), oil prices and economic growth in oil-exporting countries. abu dhabi: united arab emirates university. apergis, n., payne, j.e. (2010), the emissions, energy consumption, and growth nexus: evidence from the commonwealth of independent states. energy policy, 38(1), 650-655. apicorp. (2018), saudi energy price reform getting serious. apicorp energy research, 3, 3-5. asafu-adjaye, j. (2000), the relationship between energy consumption, energy prices and economic growth: time series evidence from asian developing countries. energy economics, 22, 615-625. aslan, a. (2013), causality between electricity consumption and economic growth in turkey: an ardl bounds testing approach. energy sources, part b: economics, planning, and policy, 9, 25-31. athanasois, sd., micheal, l.p., symeoni, e, (2020), revisiting the impact of energy prices on economic growth: lessons learned from the european union. economic analysis and policy, 66, 85-95. bekun, f.v., emir, f., sarkodie, s.a. (2019), another look at the relationship between energy consumption, carbon dioxide emissions, and economic growth in south africa. science of the total environment, 655, 759-765. bernard, n.i. (2016), electricity consumption and economic growth in nigeria: a revisit of the energy-growth debate, mpra paper no. 70001. available from: https://www.mpra.ub.uni-muenchen. de/70001. cheng, b.s., lai, t.w. (1997), an investigation of co-integration and causality between energy consumption and economic activity in taiwan. energy economics, 19, 435-444. dickey, d.a., fuller, w.a. (1996), distribution of the estimators for autoregressive time series with a unit root. journal of the american statistical association, 74, 427-431. dossou, t.a.m. (2019), electricity consumption and economic growth nexus in the republic of benin. socio-economic challenges, 3(2), 63-69. ecra. (2015), annual report 2014. riyadh. available from: http://www. ecra.gov.sa/en-us/mediacenter/doclib2/pages/subcategorylist. aspx?categoryid=4. erol, u., yu, e.s.h. (1987), on the causal relationship between energy and income for industrialized countries. journal of energy development, 13, 113-122. fattouha, b., amrita, s. (2016), saudi arabia’s vision 2030, oil policy and the evolution of the energy sector. oxford: the oxford institute for energy studies, oxford energy comment. gonand, f., hasanov, j.f. (2018), estimating the impact of energy price reform on saudi arabian intergenerational welfare using the megirsa model. the energy journal, 40(3), 55-77 granger, c.w.j. (1988), some recent developments in a concept of causality. journal of econometrics, 39, 199-211. http://www.ecra.gov.sa/en-us/mediacenter/doclib2/pages/subcategorylist http://www.ecra.gov.sa/en-us/mediacenter/doclib2/pages/subcategorylist belal, et al.: the cuasal relationship between, electricity consumption and economic growth in kingdom of saudi arabia: a dynamic causality test international journal of energy economics and policy | vol 11 • issue 1 • 2021340 hasan, d., serhat, y., zafer, a. (2017), identifying causality relationship between energy consumption and economic growth in developed countries. international business and accounting research journal, 1(2), 71-81. hendry, d.f., juselius, k. (2000), explaining cointegration analysis: part 11. the energy journal, 22, 5161060. ho, c.y., siu, k.w. (2007), a dynamic equilibrium of electricity consumption and gdp in hong kong: an empirical investigation. energy policy, 35(4), 2507-2513. institute for energy economics and financial analysis. (2018), 14900 detroit avenue, suite 206, lakewood, oh 44107, 216-712-6612, available from: http://www.staff@ieefa.org. ieefa. (2018), sunny saudi arabia plans a $200 billion bet on solar. cleveland: institute for energy economics and financial. iyke, b.n. (2015), electricity consumption and economic growth in nigeria: a revisit of the energy growth debate. energy economics, 51(c), 166-176. johansen, s. (1995), likelihood-based inference in co integrated vector autoregressive models. oxford: oxford university press. johansen, s., juselus, k. (1990), maximum likelihood estimation and inference on cointegration-with applications to the demand for money. oxford bulletin of economics and statistics, 52, 169-210. khalid, h.a. (2012), causal relationship between energy consumption and economic growth in the kingdom of saudi arabia. journal of energy and development, 37(1), 129-142. khan, s., jam, f.a., shahbaz, m., mamun, m.a. (2018), electricity consumption, economic growth and trade openness in kazakhstan: evidence from cointegration and causality. available from: https:// www.mpra.ub.uni-muenchen.de/87977. king abdullah petroleum studies and research center. (2017), available from: https://www.kapsarc.org/research/publications. kraft, j., kraft, a. (1978), on the relationship between energy and gnp. journal of energy and development, 3, 401-403. lahn, g., stevens, p. (2011), burning oil to keep cool: the hidden energy crisis in saudi arabia. london: chatham house. lee, c.c. (2006), the causality relationship between energy consumption and gdp in g-11 countries revisited. energy policy, 34, 1086-1093. m.o.w.a. electricity. (2014), chapter 30: state plans, performance and problems, in 9th development plan, ksa, ministry of water and electricity. p581. maghrebi, f., zouaoui, c.e., ibrahim, a. (2018), test of causality between oil prices and gdp: case study saudi arabia. economic computation and economic cybernetics studies and research, 52(3), 279-289. masih, a.m.m., masih, r. (1996), on the temporal causal relationship between energy consumption, real income, and prices: some new evidence from asian-energy dependent nics based on a multivariate cointegration/vector error-correction approach. journal of policy modeling, 19(4), 417-440. masih, m., al-elg, a., madani, h. (2009), causality between financial development and economic growth: an application of vector error correction and variance decomposition methods in saudi arabia. journal of applied economics, 41(13), 1691-1699. mezghany, i., haddad, h.b. (2016), energy consumption and economic growth: an empirical study of the electricity consumption in saudi arabia. renewable and sustainable energy reviews, 75(c), 145-156. available from: https://www.elsevier.com/locate/rser. michael, s., alegre, j.g. (2009), fiscal policy challenges in oil exporting countries. a review of key issues; social research network, electronic library. available from: http://www.ssrn.com/abstract. narayan, p.k., smyth, r. (2009), multivariate granger causality between electricity consumption, exports and gdp: evidence from a panel of middle eastern countries. energy policy, 37, 229-236. nelson, c.r., plosser, c.r. (1982), trends and random walks in macroeconomics time series: some evidence and implications. journal of monetary economics, 10(2), 139-162. njindan, i.b. (2014), electricity consumption and economic growth in nigeria: a revisit of energy-growth debate. available from: https:// www.mpra.ub.uni-muenchen.de/70001. nyasha, s., gwenhure, y., odhiambo, n.m. (2016), energy consumption and economic growth in ethiopia: a dynamic causal linkage. odhiambo, n.m. (2009), energy consumption and economic growth nexus in tanzania: an ardl bounds testing approach. energy policy, 37(2), 617-622. odularu, g.o. (2008), crude oil and the nigerian economic performance, oil and gas business. available from: http://www.ogbus.ru/eng. platts. (2015), available form: http://www.platts.com/latest-news/naturalgas/dubai/saudi-arabia-hikes-price-of-gas-for-power-production 26323825. said nachet, marie-claire aoun. (2015), the saudi electricity sector: pressing issues and challenges. ifri-bruxelles, brusselsbelgium. available from: http://www.ifri.org. sari, r., soytas, u. (2009), are global warming and economic growth compatible? evidence from five opec countries? applied energy, 86, 1887-1893. sekantsi, l.p., thamae, r.i. (2016), electricity consumption and economic growth in lesotho. energy sources, part b: economics, planning, and policy, 11(10), 969-973. shabestari, n.b. (2018), energy consumption, co2 emissions and economic growth: sweden’s case. available from: http://www. diva-portal.org/smash/get/diva2:1214695/fulltext01.pdf. sheilla, n., yvonne, g., nicholas, m.o.(2016), energy consumption and economic growth in ethiopia: a dynamic causal linkage. south africa: unisa, economic research working paper series no. 10/2016. soytas, u., sari, r. (2009), energy consumption, economic growth, and carbon emissions: challenges faced by an eu candidate member. ecological economics, 68, 1667-1675. stern, d.i., enflo, k. (2013), causality between energy and output in the long run. energy economics, 39, 135-146. suharsono, a., aziza, a., pramesti, w. (2017), comparison of vector autoregressive (var) and vector error correction models (vecm) for index of asean stock price. aip conference proceedings, 1913, 020032. syzdykova, a., gulmira, a., khairulla, m., aigul, k., darkhan, s. (2020), analysis of the relationship between energy consumption and economic growth in the commonwealth of independent states. international journal of energy economics and policy, 10(4), 318-324. the world bank. (2014), nigeria economic report. available from: https://www.worldbank.org/data. wolde-rufeal, y. (2006), electricity consumption and economic growth: a time series experience for 17 african countries. energy policy, 34, 1106-1114. yu, e.s.h., jin, j.c. (1992), cointegration tests of energy consumption, income and employment. resources and energy, 14, 259-266. mailto:staff@ieefa.org http://www.platts.com/latest-news/natural-gas/dubai/saudi-arabia-hikes-price-of-gas-for-power-production26323825 http://www.platts.com/latest-news/natural-gas/dubai/saudi-arabia-hikes-price-of-gas-for-power-production26323825 http://www.platts.com/latest-news/natural-gas/dubai/saudi-arabia-hikes-price-of-gas-for-power-production26323825 international journal of energy economics and policy vol. 5, no. 1, 2015, pp.206-230 issn: 2146-4553 www.econjournals.com 206 coal based electricity generation in south east europe: a case study for croatia alfredo višković faculty of engineering rijeka, university of rijeka, vukovarska 58, 51 000 rijeka, croatia. email: aviskovic@riteh.hr vladimir franki polytechnic of rijeka, trpimirova 2, 51 000 rijeka, croatia. email: vfranki@veleri.hr abstract: in this paper, we have provided an evaluation of the techno-economic performance of a coal-fired power generation unit designed and constructed following the current best available techniques (bat) principle and situated in south east europe (see). we have provided the framework of a technical model of an ultra supercritical pulverized coal-fired power plant (usc or uscpc), conducted a detailed analysis of associated costs, presented a composite cost model and performed a sensitivity analysis to identify the main cost-drivers for this type of technology. furthermore, a market analysis has been carried out to best determine the impact of the surrounding environment on the overall performance of the project. keywords: ultra supercritical unit; south east europe; feasibility jel classifications: l1; m3; o2 1. introduction europe is one of the world’s major energy consumers, but possesses limited indigenous energy resources of its own. global geopolitical developments, global economic turbulence and sometimes extreme energy prices have, especially in recent years, caused the need to carefully examine all possible options that might influence on the economic performance of an investment in the electricity sector. citizens and industry are reliant on energy, particularly electricity, and require it to be available at all times and at affordable prices. over the past decade, fossil fuels, and particularly coal, have satisfied the major share of the incremental growth in primary energy demand. at the moment, fossil fuels supply around 81% of the world’s primary energy. when looking at the electricity generation by fuel, fossil fuels are used to produce around two thirds of the world’s electricity; coal, natural gas, and oil contribute about 41%, 22% and 5% respectively (iea, 2012). emissions of environmental pollutants from power plants have led to an increase in stack emissions that are causing air quality degradation. despite emerging as an overall global issue, directly related to the quality of life, as the global demand for energy continues to grow, paired with a relative abundance of fossil fuels and the proven technologies for using them, it seems that fossil fuels will continue to be used in the future as well. despite the fact that recent movements towards renewable energy during the past few years were made possible with the adoption of various schemes and investment incentives in several european countries, conventional technologies such as nuclear, coal and gas generation continue to form the basis of the generation mix mostly due to their reliability and lower generation costs. although, at present, renewable energy sources represent a small share in the total energy consumption, solar and wind power plants are considered the fastest growing energy sources (de oliveira and fernandes, 2012). however, in a transition phase towards a sustainable worldwide energy system fossil fuels (coal in particular) should remain a significant source of energy for several decades to come (lucquiaud et al., 2011). every large project requires an equivalently large investment; this is one of the main reasons that careful planning and detailed analysis of different factors influencing the financial performance of such an investment are imperative to best understand the project specifics and be able to commit to an coal based electricity generation in south east europe: a case study for croatia 207 arduous task such as constructing a large-scale power generation unit. our paper is aimed to provide for a better perspective on the techno-economic performance of a coal-fired power generation plant situated in south east europe. our principal objectives in this paper are to (1) provide a detailed cost model of an uscpc power plant; (2) conduct a market analysis with sensitivity cases to determine the impact of several factors on the techno-economic performance of the investment. the long run marginal cost (lrmc) calculated has been adapted to the surroundings of see. the uscpc unit is considered a part of the see regional electricity market (see rem) and the eu emission trading scheme (eu ets). moreover, a sensitivity analysis has been carried out to estimate the effects of potential variation of the most uncertain parameters such as the investment costs, availability and fuel and carbon costs. technical model of the plant has been implemented into the see database and market analysis has been carried out based on the results gained through a number of simulations of the see rem. using an extended version of the software tool, we were able to determine the influence of different external factors on the performance of the unit in study. what adds value to this type of research is the consideration of the surrounding environment of the power plant object of investment. the results here provided are a combination of a mathematical model and a simulation model and are applicable to the real electricity market with costs best representing current costs of the electricity sector. the paper is organized as follows. in section 2 we talk about the electricity sector and the current situation regarding coal fired electricity generation. section 3 explains the basic technical aspects of the unit in study. section 4 describes the project framework along with the unit’s surroundings. in section 5 we provide a cost structure of the investment. after a brief description of the software used to obtain the dispatching results and electricity prices in section 6, a detailed market analysis paired with sensitivity cases is presented in section 7. section 8 brings a brief review of the conclusions. 2. situation regarding coal based electricity generation in recent years, the electricity market is no longer a happy island in a sea of troubled crisis. today, it faces a whole new panorama with extremely risky margins and closures due to lack of demand. before us now stands a dramatic new novelty: one of the fundamental rules of energy economics was that the demand for electricity is always on the rise – it is no longer the case. throughout global crisis and instability of the power market, coal has remained a competitive source of energy. it is particularly favoured for electricity generation by developing economies. as far as eu energy policy, the future of coal is often linked to the co2 market and the development of the carbon capture and storage (ccs) technology. to enable the coal industry to contribute to climate protection, modernisation of existing installations and the construction of new state-of-the-art power plants, as well as the proving of new power plant designs with efficiencies over 50 %, have to be pushed forward. investment will be needed in both generation and network assets, including conventional power plants, renewable generation, as well as “smart” transmission and distribution grids. in order to promote these developments, policymakers should embrace incentives for energy efficiency improvements along the whole electricity supply chain. as far as the issue of coal is concerned, it is currently the second most important primary energy source, behind oil. coal has a rapid growth of use which has affected its international trade substantially during the years. as this growth has been considerably stronger for some regions than the others, the coal market has changed. apart from the spike in the price of coal in 2007-2008, prices have been relatively stable and are predicted to remain so for the foreseeable future despite the growth of consumption. as for any technology choice, there are a number of pros and cons whether to invest in coal generation or not. the drawback regarding this type of technology is its highly unfavourable environmental impact. there are a number of critics claiming that coal-fired electricity generation is facing strong headwinds that will in close future lead to abandoning this type of generation in favour of environmentally more acceptable technologies. another concern and closely related to the environmental impact is the social acceptability issue. in addition to these two issues, the unpredictable nature of the carbon market might also present a deal-breaker for this type of projects. requirements for environmental protection and economic viability make high efficiency and operating flexibility a natural matter of course not only in the eu, but also around the world. these higher efficiencies can be achieved only along the path of higher steam temperatures and pressures. power plants operating at supercritical steam pressure have already demonstrated their operational international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.206-230 208 capabilities and high availability. the next step is achieving steam temperatures higher than 600°c, which decisively affects many aspects of the design of the power plant, especially of the boiler. today, there are clear evidences that high efficiency usc technology is an established and available power generation technology in europe. at present, there are a number of high efficiency usc power plants, like the one considered in this study, across europe; avedøre 2, nordjylland 3, rdk 8, maasvlakte 3, staudinger 6 are just a few with net lower heating value (lhv) efficiencies equal or superior than 46%. high efficiency usc technology is offered by more than one technology suppliers (hitachi, alstom, siemens, bwe, ihi, etc.). despite problems, there is a number of coal projects currently planned, in the tender process or under construction not only around the world, but also in the eu. europe’s choice today doesn’t seem to be “either coal or renewables” but “coal and renewables”. this can be confirmed by observing the analysis provided by the world resources institute (wri). their analysis claims there are currently 1,199 new coal-fired plants, with a total installed capacity of 1,401,278 megawatts (mw), being proposed on a global scale. these projects are spread across 59 countries. it should be noted, however, that the new rising economies of china and india together account for 76 percent of the mentioned proposed new coal power capacities (wri, 2012). as far as europe is concerned, it is planning to build 40gw of new coal-generation plants to replace its ageing coal fleet. in europe today, there are over 15 gw of coal-fired generation power plants under construction, most of which are in germany. in addition, central/southern europe is planning to add another 20 gw of new coal-fired generation plants by 2020. eastern europe and the balkans should contribute with an important role in the future of coal power generation is planning to build more than 10 gw of new coal-fired generations plants (datamonitor, 2013). however, all these should be taken with a certain dose of reserve. first of all, european energy utilities are simply replacing, or planning to replace, their ageing coal-fired generation power plants with newer and higher-efficiency coal plants – not building new capacities. secondly, the already mentioned difficulties regarding investments in coal-fired power plants proved to be too challenging for a number of projects as several of them have encountered problems that led to delays or even abandonment due to technical, legal and/or financial/economic matters. taking everything into consideration, the future of coal based electricity generation is uncertain, but at present, it plays an important role in broadening the energy mix and providing for a safe source of supply. what might prove to be of crucial significance is the speed of technological progress of coal based technology. work is being undertaken in eu, japan, usa, india and china to develop high temperature (700-720˚c) and high pressure (350-375 bar) systems to increase the efficiency of generation to around 50% lhv and to reduce co2 emissions (bugge et al., 2006). commercialisation at 48% lhv efficiency might be expected around 2020. whether this transition to high steam temperatures is economical depends not only on the choice of main steam pressure, reheat pressure and feedwater temperature, but also on the range of fuel. 3. technical description of the power plant there are a number of factors that determine the efficiency of pulverized coal (pc) plants. the most effective means of achieving high efficiency is to use steam temperatures and pressures above the supercritical point of water, i.e. at pressures above 22.1 mpa. usc units are often defined as units with pressures above 22.1 mpa and temperatures above 600°c. state-of-the-art usc units operate with steam parameters between 25 mpa and 29 mpa, and temperatures up to 620°c (iea, 2012). the unit in study will employ a pulverized coal fired, steam cycle based power generation technology with ultra-supercritical conditions and shall be designed for a nominal continuous ratio (ncr) in which it will work most of the lifespan. in the mentioned nominal continuous ratio, the plant shall have the best efficiency factor and be cost-effective and most profitable. the plant must be able to work in any other defined operating conditions without a drastic drop of efficiency factor and the drop of the plant costeffectiveness. the boiler shall be designed in such a way to guarantee outlet steam temperature of 600°c on super heater and of 610°c on reheater for a load of minimum 60%.the firing system shall be designed in such a way to secure stable ignition, and fuel switching to coal dust. net efficiency as determined by the acceptance tests must be not less than 46 per cent based on the lower heating value (lhv) of the reference coal and operating under referent climate conditions. the main technical characteristics of the power plant in study are given in the following table (table 1). coal based electricity generation in south east europe: a case study for croatia 209 table 1. technical parameters of the power plant thermal input 1090 power output (net) 500 mw gross minimum power 280 mw start-up fuel extra light fuel oil fuel pulverized coal (pc) main steam pressure at steam turbine stop valves 250-300 bar main steam temperature at steam turbine stop valves ≥600 °c hot reheat steam temperature ≥610 °c net efficiency (lhv) 46% availability 7600 h flexibility on a weekly basis dispatch ramp rate (35-50% load) 5 mw/min dispatch ramp rate (50-100% load) 10 mw/min minimum run rate 35% or lower nominal system frequency 50 hz nominal frequency variation 49.5/50.5 hz highest/lowest frequency 47.5/51.5 hz nominal voltage 400 kv minimum/maximum voltage 360/420 kv minimum/maximum voltage (at disturbance conditions) 340/460 kv 3.1. the process the pulverized coal and air mix prepared is blown by fans through burners into the boiler furnace. the furnace is additionally supplied with secondary hot air needed for combustion and reduction of nox emission. hot flue gases from the boiler furnace are vertically transported to the boiler top. in the process, they transfer the generated heat to heaters, evaporators and steam superheaters. from the boiler, the flue gases are conveyed into the system for removal of nitrogenous nox compounds. the flue gases are then cooled in a regenerative rotational air heater (rah). rah uses the flue gas heat to warm up fresh process air. the boiler is of ultra-supercritical parameters (≥600°c / ≥610°c/ ≥250 bar), single reheat, once-through, sliding pressure, balanced draft, tower-type boiler designed for firing pulverized coal as the main fuel employing the extra light fuel oil firing system. feed-water pumps shall feed the boiler with water. burner management system (bms) should control, protect and supervise the boiler unit. the system must ensure that the combustion in the furnace, as well as the main and auxiliary boiler equipment operation, shall be performed with maximum safety and with maximum reliability and availability, all within the plant distributed control system (dcs). boiler island minimum load should be at 35% of nominal continuous ratio (ncr), while 100% coal fired and with sliding pressure. up to 20% of nominal continuous ratio (ncr) boiler needs to work on extra light fuel oil (elfo). from 2035% of ncr boiler works on the extra light fuel oil (elfo) and coal, and from 35% to a maximum continuous load (mcr) (103%) on coal. the feed-water, after being heated through low pressure (lp) and high pressure (hp) preheaters, will enter the inlet chambers of the boiler water heaters to be heated to a temperature somewhat lower than the evaporation temperature. the water heater outlet chambers shall be connected to the evaporator inlet chambers. upon leaving the evaporator, the steam shall be superheated in a multi-stage steam super heater to ≥600°c and ≥250 bar, and be conveyed to the turbine hp section. after it had done its work in hp turbine, the steam shall be returned into the boiler as cold reheated steam (mcr) to be heated (hot reheating) at ≥610 ºc, and returned into the turbine to enable expansion through the intermediate pressure – low pressure (ip-lp) part section and do the work. the boiler shall be designed so that at 60% loading it still guarantees the steam temperature at heater 600 °c and reheater of 610 ºc. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.206-230 210 a bottom ash (slag) silo should be located in the vicinity of the boiler house, as well as the dry ash silo. they are located so as to enable simultaneous removal by conveyors to the pier for byproducts and if necessary removal by trucks or conveyors to the bottom and fly ash stockyard. they also serve as a standby to each other. the power house of the unit will accommodate a three-stage steam turbine with a generator, condenser, condensate pumps, lp and hp condensate heaters, deaerator feed-water tank, feed-water pumps, injector vacuum pumps, auxiliary equipment for lubrication of turbine and generator bearings, process control and regulation, and protection devices. the chemical water treatment plant shall be located si of power house together with the neutralization basins, demineralized water tank and chemicals tank. a detailed scheme of the process is presented in figure 1. figure 1. the process 3.2. referent climate conditions thermal power plant will be designed to operate under all climate conditions that might be encountered considering the surrounding environment. basic referent climate conditions are defined by table 2. table 2. referent climate conditions minimum maximum air temperature -12°c 37°c relative humidity 12% 98% air pressure 932 mbar 1050 mbar sea temperature 10°c 22°c 3.3. permissive emissions and by-products according to the eu directive 2010/75/eu emission limit values for new plants that come in operation after 7th january 2014 must be equal or lower than the values presented in table 3. unit shall be equipped with all necessary equipment so that the flue gases and cooling water, wastewater and other substances released into the environment meet the strictest european regulations. all other process waste materials such as slag and ashes, and process by-products such as gypsum shall be disposed of in an environmentally acceptable manner. lp turb& feed water heating generator lp turbine hp turbine steam to and from turbine super heater re heater economiser nox reduction sox removal fly ash removal ash by product air heater ash coal handling coal milling boiler furnace coal in air in gas to chimney steam cycle coal based electricity generation in south east europe: a case study for croatia 211 table 3. permissive emissions so2 emissions for design coal mg/nm³ ≤150 nox emissions for design coal mg/nm³ ≤150 particulate emissions for design coal mg/nm³ ≤10 3.4. connection to the grid the generators and related control plant must be designed to comply with the requirements of the croatian grid code. the plant will be designed to operate on three phase 400 kv gas-insulated switchgear (gis) and permissible generator voltage variation of at least ± 5% of nominal voltage and with an initial short-circuit current 7500 mva (40 ka) at 400 kv. respecting the conditions prescribed for electric grid system the generators and generator-transformer combination should be able to supply the following: 1. maximum continuous rating at the unit power factor within the 400 kv ±10% line voltage range 2. maximum continuous rating within the grid frequency range of 49.5 to 50.5 hz. 3. maximum continuous rating at the power factor of 0.85 inductive, within the line voltage range of 400 kv ±10%. 4. maximum continuous rating at the power factor of 0.95 capacitive within the line voltage range of 400 kv ±10%. 3.5. fuel issue extra light fuel oil should be used as starting fuel for the boiler unit. good quality imported hard coal will be the main fuel. according to iea estimates, global hard coal consumption increased by more than 70% from 3,700 million tonnes (mt) in 2000 to 6,317 mt in 2010 (iea, 2011). croatia does not produce coal and has to rely on imports. since the price of coal is generally low, means of transportation become a much more important topic as delivery costs hold a higher percentage in the overall fuel costs than for other fossil fuels. we have, therefore, envisaged that the unit will be positioned along the coast of the adriatic and coal will be supplied by sea. this will also facilitate an easier and more efficient solution for the units cooling system. the permissible limit values of the imported coal basic characteristics are listed in the table below (table 4). the reference lower heating value of coal used for further analysis and calculation has been set at 26.3 gj/t. table 4. coal characteristics data units lower boundary higher boundary lower heating value mj/kg 24.0 29.3 ash % 8 15 humidity content % 6 15 volatility % 25 45 sulphur % 0.3 1.5 nitrogen % 1.2 1.85 chlorine % 0.01 0.15 hardgrove index hgi 45 60 ash softening temperature °c 1,200 1,300 ash fusion temperature °c 1,350 1,550 coal transporters shall supply the coal to the boiler daily bunkers by the silo conveyor system or a direct system. the coal feeders feed coal into the coal mills located under the daily bunkers for pulverization. in the mills, coal dust will be mixed with hot and cold air blown by the primary air fans (paf). the pulverized coal and air mix prepared in this way is blown by fans through burners into the boiler furnace. the furnace is additionally supplied with secondary hot air needed for combustion and reduction of nox emission. hot flue gases from the boiler furnace are vertically transported to the boiler top. in the process, they transfer the generated heat to heaters, evaporators and steam superheaters. from the boiler, the flue gases are conveyed into the system for removal of nitrogenous nox international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.206-230 212 compounds. the flue gases are then cooled in a regenerative rotational air heater (rah). rah uses the flue gas heat to warm up fresh process air. the coal storage shall be designed to allow mixing of different coal types to reach the specifications required to supply the plants (this refers in particular, but not exclusively, to sulphur levels).boiler designs today usually encompass a broader range of typical coals than initially intended to provide future flexibility (mit, 2007). coal types with lower energy content and higher moisture content significantly affect capital cost and generating efficiency. 3.6. quadratic hourly consumption during operation, power plants occasionally need to adjust their power output to be able to cope with the fluctuations of the market. the efficiency in these cases does not remain constant. if a unit does not operate at nominal power, it will have a higher consumption and an accordingly lower efficiency. usc units operate at higher efficiencies and lower emissions than traditional (subcritical) coal-fired plants, producing more power from less coal and with lower emissions. the quadratic hourly consumption curve (qhcc) [gcal/hour] is presented to best depict these fluctuations of fuel consumption. for a better understanding, the usc unit specific consumption modelled by the qhcc was compared to a quadratic curve of consumption of a unit of 35% lhv efficiency. our analysis confirmed that the installed capacity of coal and lignite based units in the see region has an average efficiency of 35%. this is why, in further text, we have provided a comparison of economic performance and environmental impact between a subcritical unit of the same capacity as the reference usc unit. as it can be noticed from figure 2, a typical subcritical system has a significantly higher fuel consumption resulting in higher operating costs and higher specific emissions. the following equation (equation 1) expresses the consumption of fuel in the operating power range, between the minimum and the maximum operating power: c = c ∙ p + c ∙ p + c (1) where is c = consumption (gcal/h), c2= coefficient of second degree (gcal/mw2h), c1 = coefficient of first degree (gcal/mwh), c0= constant term (gcal/h), p= operating power (mw).coefficients used to describe the specific consumption curve for the two units mentioned are shown in table 5. table 5. coefficients of the specific consumption curve power plant c2 c1 c0 uscpc 0.000196 1.566389 102.6426 subcpc 0.000330 2.058683 105.2233 the following figure (figure 2) represents the two curves of specific consumption in gj/mwh. as it can be seen, consumption depends on the output of the plant and is higher when the plant is operating at lower capacity. the importance of qhcc of a unit lies in the fact that through them, specific fuel costs and specific emission costs can be calculated. these two costs form the major part of overall variable costs by which the merit order curve (moc) that defines units’ hourly dispatch is based on rubin et al., 2007. an independent power producer (ipp) can make a profit only when it sells its production on the market at a price higher than the mentioned variable costs. our analysis showed that, at nominal power, the usc unit in study would consume 0.297 tonnes of coal per megawatt hour compared to 0.390 t/mwh consumed by an average subcritical unit. 3.7. co2 emissions in this paragraph we present a short analysis of the correlation between specific consumption (power plant efficiency) and co2 emissions. as mentioned, usc units burn less coal and have lower specific emissions than typical subcritical power plants. the dependence of specific emissions on power plant efficiency is presented in figure 3. the case considered in our study regards a new entrant usc unit with net efficiency of 46% and the 35% average efficiency of coal-fired generation in see. it can be seen that the usc unit would emit almost a quarter less co2 (0.75 tco2/mwh compared to 0.99 tco2/mwh).if we were to compare overall carbon emissions for these two types of generating capacities, the difference on an annual scale would amount to approximately 920,000 tonnes (for a presumed production of 3.8twh).this represents a significant cut in harmful emissions greatly helping with the improvement of the environmental impact of coal based generation. coal based electricity generation in south east europe: a case study for croatia 213 figure 2. specific consumption curve figure 3. specific emissions curve 4. project framework a growing number of investments in the power sector are being realized by project financing arrangements. at the moment, the non-recourse project financing (nrpf) structure seems to be international best practice for the development of large scale power projects. project financing refers to a loan which is structured to primarily rely on the project’s income to repay the loaned amount. it uses project’s assets as collateral in case the income is insufficient to cover the debt instalment. lenders have no direct recourse to the project sponsors and are guaranteed only by project’s assets and cash flows. this means that a utility involved in building a power plant by this structure does not hold responsibility through its own assets or, in other words, if a project (for any reason) is not able to repay its debt, the company can only lose its share of equity invested in that very project. this type of arrangement requires for the establishment of a project company, a special purpose vehicle (spv). spv is often formed by more than a single company. companies having a share in the project become strategic partners. they transfer assets and involve resources as their stake in the project. this contribution creates a liability on the business in the shape of capital as the project is a separate entity 7,5 8 8,5 9 9,5 10 10,5 11 280 300 320 340 360 380 400 420 440 460 480 500 [g j/ m w h] [mw] specific consumption curve [gj/mwh] usc avg see 0,6 0,7 0,8 0,9 1 1,1 1,2 0, 3 0, 31 0, 32 0, 33 0, 34 0, 35 0, 36 0, 37 0, 38 0, 39 0, 4 0, 41 0, 42 0, 43 0, 44 0, 45 0, 46 0, 47 0, 48 0, 49 0, 5 [t co 2/ m w h] [lhv net efficiency] specific emissions [tco2/mwh] international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.206-230 214 from its owners. the amount of assets invested compared to the amount of debt forms the debt-toequity ratio of the project. figure 4 depicts the high level structure and main characteristics of an spv. it shows the way participants are involved with the spv as well as the main inputs of this type of structure for a thermal power plant project. figure 4. spv high level structure lenders loan the necessary funds to the equity sponsors. after obtaining all the project agreements (pa), after the engineering, procurement and construction (epc) contractor has completed the plant and after the unit has successfully passed the test phase, it can officially commence with operation– this date is called the commercial operation date (cod). from then on, the spv functions as an ipp and sells its production on the electricity market or via bilateral agreements. spv might sign a power purchase agreement (ppa) with an off-taker that guarantees a sale of a proportion of its production during a certain period of time (usually a couple of years) at a prearranged price. if this agreement has been signed prior to applying for a loan, it can prove to be a very valuable asset for the spv lowering merchant risks and providing not only for a safer investment, but also a lower debt risk premium resulting in lower costs. quality ppas are not easily obtained, especially considering recent climate. an off-taker can be a strategic partner in the spv or a different (independent) utility looking to cut electricity market volatility risks. 4.1. high level risk assessment power plant projects are dependent on a series of mandatory requirements and challenging interfaces. the main challenges are not only of technical (e.g. bat criteria, efficiency demand), but also economical (e.g. feasibility, risk acceptability) as well as legislative (e.g. location and building permits) and regulatory (e.g. permissible emissions, ets) nature. we have identified eight main types of risks involving thermal power plant projects: financial; construction; macroeconomic; environmental protection; carbon cost volatility; fuel cost volatility; operational; merchant. figure 5 depicts a high level risk assessment for a coal-based ipp. coal based electricity generation in south east europe: a case study for croatia 215 figure 5. ipp main risks the concern for the environment caused strict and sometimes demanding restrictions that thermal units nowadays face during planning, construction and/or operation. coal-based electricity generation, in particular, is facing problems due to its extremely negative environmental impact. one of the new risks that arose in recent years and that thermal units face is the emission trading scheme (ets). ets is a market-based scheme that allows parties to buy and sell permits for emissions or credits for reductions in emissions of certain pollutants. croatia, being a part of the eu has adopted this scheme and as of 1st of january 2013, a new entrant unit based in croatia needs to account for every tone of co2 emitted to the atmosphere (ec, 2009). within the eu climate and energy package there is a legally binding overall emission reduction target of 20% by 2020 (compared to 1990 emission levels). it comes from a mutual agreement between the european council, the european parliament and the european commission. eu ets is one of the tools being used to help reduce these emissions. 4.2. surrounding peculiarity south east europe is a specific region, especially when it comes to the field of the electric power sector. the see electricity markets are undergoing structural changes following the reforms imposed by the eu. electricity reform in the eu has been primarily driven by two electricity directives in 1996 and 2003 (jamasb et al., 2005). on 19th september 2007, the european commission (ec) adopted the so called “third energy package” of legislative proposals concerning electricity and gas markets. the primary aim of reform is to improve the productive efficiency of the sector and lower costs and prices by providing for a competitive and integrated energy market that allows european consumers to choose between different suppliers and enables all suppliers to have an access to the market. having an efficient and well-developed power sector enables growth and boosts the economy affecting the improvement of living standard of the population and development of society (cerović et al., 2014). best practice in regulatory reform involves three aspects: form, progress and outcome of regulation (green et al., 2006). with the assistance of eu, the see countries have not only a clear reform model to follow, but also an access to technical assistance to help with the process. because of this, see is and will be a test of transferability of the eu reform model within the eu as well as its transferability to a set of developing countries (green et al., 2006; pollitt, 2009). we have identified two of the main difficulties for an ipp competing on the rem of see. number one is concerning the see countries’ affiliation to the eu ets scheme. as it can be seen from figure 6, not all countries of the region are a part of the ets. this creates an imbalance between competitors on the market. if carbon costs rise to a certain point, they might prove to be too much of a burden for a thermal power plant competing with players with no obligations to purchase co2 certificates. this, potentially high imbalance between competitors on the market is a considerable risk rather unappealing for investors (višković et al., 2014a). with a number of forecasts claiming that prices of emission unit allowances (eua) will rise during the course of years, one must wonder whether it is a wise decision to invest in coal-fired generation when just across the border there is a number of international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.206-230 216 players using similar technology (mostly lignite) and not being burdened with such heavy costs – it is certainly a risky liability to hold. figure 6. south east europe countries ets affiliation despite its accession to the eu, croatia is still moving slowly to fully applying the acquis communautaire in a practical manner. the unbundling process is only at the beginning as only recently a model of unbundling for transmission system operators was selected and croatia’s power exchange seems to be a long way from being operational. despite all the problems, it is only a matter of time when all this will be sorted and croatia will have a fully liberalised and deregulated electricity market. however, as things currently stand, the croatian electricity market is one of the lowest competitive electricity markets in europe (ranked 28th on 33 countries analyzed in 2013) (datamonitor, 2013). with regard to the wholesale market structure, croatia is a strongly concentrated market: the generation segment is entirely dominated by the country’s main utility company – hep (other players in the generation sector are tpp plomin d.o.o. and krško nuclear power plant (npp) (both co-owned at 50% by hep), which also controls 100% of electricity imports. the same situation is perceivable also in the retail-end segment of the value chain. dominance of hep across all segments of the value chain does not facilitate market transparency as well as access to consumer information. current market dynamics along with the mentioned dominance mean that croatia is perceived as a challenging market for new entrants. figure 7 shows the results of the datamonitor mci index competition intensity analysis (datamonitor, 2013). mci is the index which measures the development of the electricity markets competitiveness, comparing between each other 34 european markets. 4.3. croatian electricity market legal framework regarding the electricity sector, the framework recognises five types of activity: generation, transmission, distribution and sale of electricity and organisation of the electricity market. generation, supply and trading on the electricity market are market activities in which price and quantity are freely negotiated. however, generation of electricity for tariff customers, transmission and distribution of electricity, electricity market organisation and supply for tariff customers all remain regulated activities. the electricity legal framework is regulated by the following three acts: energy act, the energy activities regulations act and the electricity market act. as mentioned, there is a lot of work to be done to bring croatia to the standards needed to attract foreign investment. at present, it is a rather unfamiliar terrain for foreign capital and the changes imposed by the eu are of great value and coal based electricity generation in south east europe: a case study for croatia 217 importance not only in improving the conditions in the electricity sector, but providing for better transparency and image. one of the key and crucial issues for foreign investors or financial institutions is the country’s regulatory framework that is capable of ensuring transparency and certainty over the long run. figure 7. mci score 2013 (source: datamonitor) 4.4. why coal in croatia? rationale in order to provide development and growth of the energy potential of croatia, replacement and modernisation of existing power plants is no longer the only solution. new power plants using modern technologies are needed to keep pace with the fast-changing and fast-evolving demands of the electricity sector and competition. the majority of existing thermal power plants in croatia have too many years of service behind them and are unable to meet with the demands of the modern electricity market. a number of them uses obsolete technology and have far too expensive costs to be competitive on the market. unfortunately, for the most part, it is considerably cheaper to import electricity then produce it at croatian-based thermal units. during the new generation mix planning and designing one should take into account the diversity of energy sources and ensure not only a cheaper source of electricity, but also the security of supply at all times for the consumers. thus, besides the construction of hydro-energy, gas, wind, solar and other facilities, the construction of coal thermal power plants is essentially needed. in addition, the development of the unit in study is in compliance with the croatian energy strategy which aims at achieving security of supply & a competitive energy system. the three pillars of the strategy are identified as security of energy supply, competitive energy system and sustainable energy sector development (og, 2009). these objectives imply the following targets: reduce the dependency on energy imports; maintain the percentage of energy produced by large hydro power plants and renewables at 35% in 2020 (same level of today); compensate for the increase in electrical energy consumption in croatia; compensate for the planned shutdown of plants that cannot meet emission legislation in the next years. the new production unit in study would be very important for the development of the croatian power system as a whole. by its construction, it would be one of the most important production facilities in the croatian power system and would have a role of a base power plant in the electrical power management and control system. according to this proposal of technical solution, the new unit has been conceived as an independent non competitive markets 0 1 2 3 4 5 6 7 8 9 10 s d s e e s u k s o ru r o p t s i p l no n l m a l u l t l v i t i e hu gr d e fr tr e e d k cz c y fn b g b e a u a l croatia low high competitiveness international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.206-230 218 and technology-independent plant which is intended solely to generate electricity with power rating of 500 mw net (the power submitted to the grid). 4.5. overview on the croatian thermal generation set when evaluating a techno-economic performance of an ipp on the electricity market it is necessary to have an extensive knowledge of its surrounding environment. for this purpose, we have made a model of the thermal generation set that represents the assumed state of the croatian thermal sector in year 2015 (višković et al., 2014a; višković et al., 2014b). we have assumed that the installed capacity will amount to 2015 mw (excluding npp krško). thermal power plants used in the technoeconomic analysis are presented in table 6, along with the fuel they use. each of the units listed is described by the constraints and technical characteristics needed to successfully form the electric power system model. when comparing the thermal generation set used in the study to the current status of the thermal sector of croatia, the main difference is in a solemn extra unit predicted to be operational by 2015 – the 230 mw combined-cycle in te sisak. table 6. installed thermoelectric capacity in croatia in the year 2015 power plant fuel used installed capacity el-to zagreb gas 207 te-to zagreb gas+oil 208+120 te-to osijek gas+oil 22+63 kte jertovec gas+oil 45+50 te sisak gas+oil 230+420 te rijeka oil 320 te plomin coal 330 5. economic assessment while making the assessment of the main driving parameters of the unit in study we have given particular consideration to the specifics of the surrounding environment and their influence on the costs presumed. in other words, some cost components of the long run marginal cost presented in this paper are, in a certain amount, country specific and differ from other surroundings. for a better and easier economic assessment of a power plant, we have divided all the costs that the unit might encounter into four divisions: investment, operation and maintenance (o&m), fuel and co2 costs. 5.1. investment costs investment costs assumed for the purposes of this study include costs encountered on the project until its successful commercial operation date (cod). they comprise of capital and financing costs with a debt repayment term which was set at 15 years. we have presumed a 75:25 debt to equity ratio with a financing methodology which considers a bridge loan during the epc period (with capitalization of interest) and a straight line repayment loan during the designated period. as far as the interest rates considered in the study, it should be noted that, as a whole, the electric utility industry's credit rating is in lower tier of the investment grade category (bbb). in addition, because ipp debt is considered risky, most private entities and lead investors tend to demand for higher interest rates. bridge loan interest rate is set at 8.5%. we have also considered an interest rate on term loan at 6.5% and a discount rate of 8.7% – value presumed as the investor’s weighted average cost of capital (wacc). capital expenditures (capex) assumed are shown in table 7, they comprise of construction costs, costs for mechanical equipment and intangible costs. the assumed capital costs of the uscpc unit in study equal 760m€; 570 m€ of which are financed through debt and 190 m€ through equity. the specific capital cost is presumed at 1.52 m€ per megawatt of installed net output capacity. all costs of the project prior to construction are considered to be financed by equity. after completing the necessary documentation and obtaining financing the construction is able to start. the bridge loan duration is 4 years – during this period we have presumed the unit’s construction, connection to the croatian electrical grid, completion of the testing phase and a successful cod. taking into account the bridge loan interest during the period, the yearly distribution of capital costs shown in figure 8, as well as the financing fee considered at 2% of the overall senior debt (2% of 570 m€ = 11.4 m€), we have calculated the overall investment in the spv to reach its maximum at 865.85 coal based electricity generation in south east europe: a case study for croatia 219 m€; 675.85 m€ of which are debt. under the financing conditions specified in the text above, the specific investment cost equals 1.73 m€ per megawatt of installed net output capacity. table 7. capital costs investment [m€] main plant building 370 fgd system 65 fuel supply and storage 45 electric block & protection system 35 cooling system 35 electrical plant unit 25 contingencies 25 water system 20 environment regulation 15 slag and dry ash 15 auxiliary building & plants 10 spare parts 30 engineering 35 project management 20 supervision & other expenses 15 figure 8. capital costs yearly distribution during bridge loan term 5.2. operation and maintenance costs the o&m costs presumed in this study have been considered as part of the fixed annual costs of the power plant. this is because our analysis showed that the variable part of the o&m costs does not greatly change depending on the units’ predicted output and therefore does not have a significant impact on the overall costs of the ipp. as mentioned, the unit in study is predetermined to cover the base load and as such, its presumed output does not change in a significant matter. costs of programmed and unscheduled maintenance, labour costs, taxes and assurance as well as a number of other different expenses have all been taken into consideration. 5.3. fuel costs as already mentioned, good quality imported hard coal has been selected as the main fuel of the unit in study. we have presumed the reference value of the cost of imported coal to be 80€/t. this value includes the cost, insurance and freight (cif), the additional transport cost to croatia and the croatian excise duty of 0.3€/gj (og, 2013). the prices of fuel have been modelled according to the futures contracts obtained from the european energy exchange website (eex, 2014) and team analysis. the cost of fuel oil was presumed at 9.52 €/gj and the cost of natural gas (ng) 8.57 €/gj – all the costs have been adapted to the croatian surroundings. prices in croatia are projected to remain 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2012 2013 2014 2015 international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.206-230 220 aligned with international prices and are forecasted stable across the years due to supply/demand balance (coal plant decommissioning in eu and us) and wide availability from different countries. 5.4. co2 costs carbon costs are the ones most difficult to predict due to the number of different unforeseeable factors that influence the formation of emission unit allowance (eua) cost; despite that eu aims at increasing co2 prices, the prices’ evolution remains uncertain. one eua gives the right to emit one tonne of co2 in the atmosphere. as of 1st of january 2013, electricity producers based in the eu have to account for the co2 emissions by purchasing these rights. at the moment, the price of a tonne of co2 is 4.78€/tco2 (eex, 2014) and seems to be inadequate to promote a more extensive use of renewable sources. however, a number of pundits are claiming that it is only a matter of time when this price will rise. for the purposes of our study, we assumed a referent cost of co2 to equal 10 €/tco2 for all the countries inside the ets scheme (cro; si; hu; ro; bg). co2 price is a very high impact parameter for our analysis. the specific costs of co2 emissions can be calculated by using the specific emission coefficient for the unit considered (it equals 0.75 tco2/mwh for the unit in study) and multiplying it by the cost of one certificate. it can now easily be seen why the specific co2 cost for the referent case scenario equals 7.5 €/mwh. 5.5. overall long run marginal cost combining the four aforementioned elements we have calculated the referent overall lrmc of the unit in study. the model is used for the purposes of further analysis and is presented to enhance the understanding of costs an ipp encounters on a yearly basis. with the conditions considered, the calculated lrmc equals 55.27 €/mwh. investment, o&m, fuel and co2 costs contribute with 34%, 9%, 43% and 14% respectively. referent lrmc is shown in table 8. it should be noted that it contains an annual investment cost of 71.87 m€; this is because it was projected on a straight line basis during the course of the debt repayment term. 5.6. sensitivity analysis when assessing costs, the majority of the parameters considered are affected by uncertainty. this is the reason why we have run a sensitivity analysis on some of the key factors to best determine their influence on the lrmc of the ipp in study. the two scenarios considered a 10% change in the parameters observed. the results of the sensitivity case analysis are presented in figure 9. as it can be noticed, a 10% variation on the factors considered does not result in drastic changes in the overall lrmc. it should be noted, however, that the cost of eua can significantly vary from the 10 €/tco2 considered and represents the most uncertain parameter of the cost assessment. as mentioned earlier, the current cost of an allowance is approximately 50% lower than our reference one while a number of pundits predict it will rise up to even 40 €/tco2 which would make a 400% increase. taking this worst case scenario of eua cost into consideration, we have calculated that the lrmc of the unit in study would equal 77.85 €/mwh which would represent an increase of 22.58 €/mwh. figure 9. sensitivity analysis -3,00 -2,00 -1,00 0,00 1,00 2,00 3,00 eua price fuel cost availability investment [€/mwh] -10% +10% coal based electricity generation in south east europe: a case study for croatia 221 5.7. comparison with different types of coal based generation we have taken into consideration the difference between the operating costs of a new entrant unit in study and a hypothetical subcritical coal based generation capacity. as mentioned earlier in the text, out analysis revealed that the average efficiency of coal based generation in the see region is 35%. we have assumed that the 500 mw capacity does not bare investment costs; only o&m, fuel and co2.despite the considerable difference in investment costs burden, a new entrant unit has far superior specific fuel consumption making its variable costs far more favourable. our analysis showed that a 46% efficient uscpc plant would have 24.5% lower specific consumption than an average 35% unit of the same size working at nominal rate – this results in 7.47 €/mwh difference between the specific fuel costs. paired with lower specific emissions and accordingly lower co2 costs, the difference between the variable (operating) costs of the two capacities are almost 10 €/mwh for the referent case considered (10 €/tco2); that makes a difference of 37.4 m€ on a yearly basis excluding the o&m expenditures. after including all costs of the project, the overall difference of the two lrmc analysed equals 7.03 €/mwh. table 8. referent long run marginal cost investment costs capital costs [m€] 760 economic time [years] 30 debt/equity ratio 75/25 bridge loan duration [years] 4 bridge loan interest [%] 8.5 debt repayment time [years] 15 debt interest 6.5 discount rate [%] 8.7 presumed annual working hours [h] 7600 presumed annual production [twh] 3.80 annual investment costs [m€] 71.87 quote for investment costs [€/mwh] 18.92 operation and maintenance costs maintenance [m€/year] 15.2 personnel [m€/year] 1.7 assurance [m€/ year] 0.95 general and administrative costs [m€/year] 0.38 others taxes (amonia; limestone; so2; nox) [m€/year] 0.95 annual o&m costs [m€/year] 19.18 quote for o&m costs [€/mwh] 5.05 fuel costs specific consumption [t/mwh] 0.30 presumed coal price [€/t] 80 annual fuel costs [m€] 90.61 quote for fuel costs [€/mwh] 23.78 co2 costs specific emission coefficient [tco2/mwh] 0.75 estimated emissions [mtco2] 2.87 eua price [€/tco2] 10 annual co2 costs [m€/year] 28.69 quote for emission costs [€/mwh] 7.53 annual total costs [m€] 210.0 referent long run marginal cost (lrmc) [€/mwh] 55.27 international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.206-230 222 6. market simulator in the new framework of competitive electricity markets, all power market participants need accurate price forecasting tools (murthy et al. 2014). the forecast of the wholesale energy prices and power units’ production in the year 2015 is performed using a software tool called promed, a dayahead market simulator developed by cesi. we have created an extension to this software and modified cesi’s database of the region so it can best correspond to the up-to-date situation. the main goal of the market analysis is to investigate the impacts of different factors on the techno-economic performances of a new entrant ipp based on coal on the see rem. promed operates using a detailed database of the region’s electricity sector. the database contains (cesi, 2009): zonal market structure and relative net transfer capacities, equivalent influence of energy exchanges between see regional electrical system and its neighbouring systems on an hourly basis, hourly load demand, fuel prices &emission prices, thermal generation set & thermal units constrains, hydro generation set, competitors bidding strategy on the day-ahead electricity market. assuming full competition in all hours, the competitors’ bid-up strategy is aimed to cover the estimated lrmc of power units. electricity price forecasting is performed trough two computational steps (cesi, 2009): 1) unit commitment; during which the hourly merit order is formed based on the constraints of the power system. 2) dispatching; during which the hourly production schedule of each thermal unit in coordination with the hydro dispatching is formed. the main problem in creating a database of the region and modelling the electricity sector so it can best represent the real life situation lies in the difficulty to predict future demand. as our analysis confirmed, the global crisis significantly affected the economies of see countries. in the past few years, they have recorded a drop or, at best, a stagnation in the demand for electricity. we based our forecast of the future national demands on the basis of an elaboration of the historical data of the national electricity consumption published by entso-e. the demand modelled represents the load to be covered by the plants that offer their electricity production in the regional system. another important issue is the ever changing generation portfolio that requires constant monitoring and updating. our model of the system was based on the research provided by cesi and team analysis by which the model was updated and modified. 7. economic and financial assessment different external influences require that plant utilization factors be evaluated in the context of a network of generating plants meeting a specified (time-dependent) electricity demand (rubin, 2007). this is the main reason why we have conducted the electricity market analysis. after building a model of the see electricity sector, we have made a number of simulations of the see rem. the goal was to simulate the situation of the electricity sector of see in the year 2015. the referent scenario showed a rather interesting result confirming the current troubled status of electricity generation through the use of traditional sources. our analysis showed that the main problem of an ipp based on coal is not the obligation to purchase emission allowances (despite our predicted price of eua being double the current value), but the overall state of the electricity sector. the mentioned stagnation/drop of consumption along with the eu support to the renewable energy sources resulted in a highly unfavourable situation of the thermal sector. the power plant in study, despite using the best available technology, having lower specific emissions and a higher efficiency than any other coal unit currently connected to the grid in see, did not achieve full dispatch. from the predicted maximum of 3.8 twh, the annual production calculated amounts to 3.53 twh – this significantly affects the profitability of the project as well as it raises another issue. is a coal fired power plant with a 500 mw net output really needed to the croatian electricity sector? under current conditions and with the uncertain future of eu policies towards coal, it seems a safer investment might be in a unit of lower output. in addition, another problem regarding low consumption is its correlation to the average marginal price of electricity. current price of electricity does not support the construction of new traditional sources of electricity generation. the following figure (figure 10) represents the electricity price duration curve obtained from the yearly series of the hourly prices sorted in a decreasing way. coal based electricity generation in south east europe: a case study for croatia 223 figure 10. market price duration curve for see 7.1. overview of the croatian electricity sector we forecasted the electricity demand of croatia to equal 17.8 twh on an annual scale. despite the decrease in consumption in year 2013, we predicted an increase in the two following years. total production from the thermal sector equalled 8.67 twh, 3.53 twh of which were achieved by the unit in study and 5.14 twh was produced by the rest of the sector. this means the new 500 mw unit would satisfy around 20% of the annual croatian demand by producing approximately 40% of all electricity generated by the country’s thermal sector. table 9. croatian electricity sector basic data 2010 2011 2012 2015 (sim) load demand 17.94 17.70 17.51 17.83 hydro 8.30 4.58 4.77 6.42 thermal 4.78 5.17 4.69 … 8.67 renewables 0.14 0.20 0.33 0.35 industrial 0.03 0.03 0.09 0.1 exchange balance -4.67 -7.70 -7.62 -2.77 7.2. dependence of electricity price on electricity demand one of the general rules of supply and demand dictates lower prices at lower demand and higher prices at higher demand. price of electricity derives from the bid-up strategy modelling: an hourly bid-up proportional to the demand level has been superimposed on the marginal cost curve of each thermal unit. the resulting price has a trend following the demand: it’s high in peak load hours and lower off peak hours. the trend during the course of the referent year (2015) can be observed in figure 11. 7.3. economic analysis in order to best depict the overall economic and financial performance of the investment in study, we have built a detailed model comprising of all the effective costs and profits that the ipp should encounter during the lifetime of operation of the power plant. the analysis conducted has been carried out by the year by year evaluation of the effective and present cash flow. the starting year of commercial operation is predetermined by the market simulation at 2015. for this year, the simulation provided us with two important values upon which we have based our further assessment of the performance of the project during its lifetime: unit dispatch and unit revenues. using the technical 0 20 40 60 80 100 120 140 1 1001 2001 3001 4001 5001 6001 7001 8001 [€ /m w h] [hours] international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.206-230 224 parameters of the unit in study, we have calculated the data presented further in text. the cash flow during the first year of operation is shown in table 10. figure 11. yearly profile of the load and marginal price curve for croatia table 10. cash flow during referent year of operation (all values in m€) revenue 211.57 o&m 19.18 fuel 84.57 co2 26.57 ebitda 81.23 amortization 39.33 ebit 41.90 interest 43.93 ebt -2.02 taxes 0.00 net income -2.02 when evaluating annual costs we have taken into consideration a 0.1% per year degradation of the power plant efficiency which results in a higher specific consumption as well as higher specific emissions; both of these, in a certain amount, raise the operating costs of a unit. the fuel costs reported include start-up costs as well as the costs of higher consumption when operating at capacities below nominal. capital costs have been considered with their financial amortization schedule with an amortization rate of 6.67% which corresponds to an amortization period of 15 years. as far as the annual o&m costs are concerned, we have considered them to be sufficient for all the planned and unplanned maintenance as well as the overhauls during the project lifetime. the components of the model have been recalculated year by year on the basis on the inflation rate provided by global insight. the analysis also considers all the taxes imposed with special consideration given to the croatian company tax which, at the rate of 20%, presents the most significant burden among these duties. figure 12 shows the annual costs of an ipp during the project lifetime. 0 500 1000 1500 2000 2500 3000 0 50 100 150 200 250 300 350 400 1 1001 2001 3001 4001 5001 6001 7001 8001 lo ad [m w h] pr ic e [€ /m w h] time [hours] price load coal based electricity generation in south east europe: a case study for croatia 225 figure 12. annual costs of an ipp the ipp in study is presumed to generate revenue by selling its output on the energy exchange. primarily, its production is used to satisfy the needs of the croatian demand and, when possible, used for export. its bidding strategy is aimed at covering the lrmc of the unit. using the data from table 10 along with necessary assumptions we built a model with the projected revenues of the project during the course of its lifetime. the revenues on an annual basis are presented in figure 13. figure 13. annual net income of the ipp with the help of the two projections (of costs and revenues), we were able to calculate the net present value of the investment (npv). considering the project lifetime and the discount rate of 8.7% (investor’s presumed wacc), the investment of 190 m€ would have an npv of 138.92 m€. the internal rate of return (irr) is the value of the discount rate that makes the net present value of all cash flows equal to zero. for the referent scenario, the irr would equal 12.4%. we have also calculated the investment’s profitability index (pi) and its payback period (pbp). relevant parameters of the investment are presented in table 11. it should be noted that, despite achieving a good irr, the project should be considered a risky investment not only because of the associated risks, but also the 0 50 100 150 200 250 300 20 15 20 16 20 17 20 18 20 19 20 20 20 21 20 22 20 23 20 24 20 25 20 26 20 27 20 28 20 29 20 30 20 31 20 32 20 33 20 34 20 35 20 36 20 37 20 38 20 39 20 40 20 41 20 42 20 43 20 44 a nn ua l c os ts [m €] project life [years] investment co2 fuel o&m 0 20 40 60 80 100 120 140 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 a nn ua l n et in co m e [m €] project life [years] international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.206-230 226 influence of a number of unpredictable factors and the uncertainty of future eu policy and regulation regarding coal fired electricity generation. the net loss during the first year of operation should also be a sign to take greater precaution when deciding whether to invest in this type of project or not. table 11. investment parameters resume equity 190 m€ npv 138.92 m€ irr 12.4 % pi 0.731 pbp 11.16 years 7.4. sensitivity market analysis because of the uncertainty regarding some of the parameters in the market analysis have conducted a sensitivity market analysis offering a more detailed perspective on the possible changes in the electricity sector that directly reflect the performance of the unit in study. we have focused on five major factors: eua prices, fuel costs, hydrology, demand and renewables to see the strength of their impact on the performance of the project. we would like to point out that our analysis of the variations of factors focused on the boundaries of optimal and pessimal possible scenarios. it is unlikely that the parameters considered in the sensitivity analysis would remain such for a prolonged period of time (project lifetime), but the results obtained represent a valuable insight on the dynamics of the market in study. we have covered a variation of eua prices from 0-80 €/tco2 (figure 13, cases 2-6).our analysis showed that the ipp can bare this heavy burden (e.g. over 50 m€/annum for the 20 €/tco2 scenario) and still achieve profit up to a certain extent. the breakpoint occurs for prices of co2 higher than 30 euros per tonne. taking into account the competition in place and the characteristics of the see rem, our analysis showed that prices of eua ranging from 30-50 €/tco2 seem to be highly unfavourable for the ipp in study. the unit loses its place in the moc and, along with lower dispatch, achieves an accordingly worse financial performance. for the prices above the 50 euros per tonne mark, the situation within the sector improves and the ipp is able to achieve a positive npv despite the extreme carbon costs it faces. the main reason for this is the competition the unit faces. firstly, it is important to note that the price of electricity on the market is formed by other thermal units. if these units have higher costs, their bidding strategy (aimed to cover these costs) will lead to the rise of the overall average marginal price of electricity (ampe). other coal fired units in the region have high specific emissions and are more affected by the changes in eua prices. due to the high efficiency of an uscpc unit and much lower specific carbon emissions, the unit in study is able to hold its position within the moc, sell its production and still make a profit even with a cost of a tonne of co2 at 80 €/tco2. the main results of the eua variation analysis are presented in table 12. table 12. eua prices sensitivity cases eua [€/tco2] 0 20 40 60 80 ampe [€/mwh] 47.49 63.35 75.62 90.62 106.18 production [gwh] 3571 3500 3236 3690 3760 revenues [m€] 184.3 239.3 256.8 345.5 407.1 co2 emissions [tco2] 2.70 2.65 2.44 2.78 2.83 npv [m€] 129.11 156.32 -22.43 48.81 46.64 irr [%] 12.2 12.9 8.1 10.0 10.0 fuel prices were analysed with four additional scenarios by changing the prices of both coal and natural gas (figure 13, cases 7-10). compared to the referent case, coal price was set at -20%, -10%, +10% and +20%, while the price of gas was set at +20%, +10%, -10% and -20%. the pessimistic predictions of coal prices were paired with the optimistic for gas and vice versa. we identified the fuel costs breakpoint at which the ipp is no longer able to achieve a satisfying dispatch and a positive npv coal based electricity generation in south east europe: a case study for croatia 227 at prices of coal higher than 90 €/t and natural gas lower than 7€/gj. this can be seen by observing case 10 of figure 13 where we assumed 20% higher costs for coal and 20% lower for natural gas. the main results of the fuel prices variation analysis are presented in table 13. table 13. fuel prices sensitivity cases coal price [€/t] 64 72 88 96 ng price [€/gj] 10.28 9.42 7.71 6.85 ampe [€/mwh] 51.62 53.63 56.79 56.27 production [gwh] 3576 3563 3480 2583 revenues [m€] 199.7 206.6 215.1 149.7 co2 emissions [tco2] 2.69 2.68 2.62 1.94 npv [m€] 138.74 88.91 127.69 -235.61 irr [%] 12.6 11.2 12.1 the two scenarios observing different hydrological conditions were based on situations encountered in years 2010 and 2011 (figure 13, cases 11-12). 2010 was a year of extremely favourable conditions resulting in a 30% higher production of the hydro sector; year 2011 was the opposite, resulting in a bit less than 30% lower production. the market analysis revealed that the variations of hydrological conditions have a great impact on the dispatching and financial results of the unit. this is emphasised because of the high share the hydro sector holds in the overall croatian production capacity. the comparison between the two scenarios revealed an 800 gwh difference per annum in electricity production which amounts to a 334 m€ difference in the two npvs achieved. the main results of the analysis on the influence of hydrology on the ipp are presented in table 14. table 14. hydrological conditions sensitivity cases hydrology optimal pessimal ampe [€/mwh] 52.16 55.72 production [gwh] 2732 3534 revenues [m€] 151.0 214.5 co2 emissions [tco2] 2.06 2.66 npv [m€] -173.35 160.97 irr [%] 3.9 13.0 as mentioned earlier in the text, before, it was common to assume that the electricity demand is always on the rise (figure 13, cases 13-14). due to a number of reasons, this is no longer a possibility. predicting a country’s consumption has become an arduous task to undertake. it is because of the unpredictable uncertainties encountered whilst facing this type of forecasting, that the referent values from prior scenarios were altered. the variations considered were +10% for the optimistic and -10% for the pessimistic scenario. results that were obtained showed a staggering influence of demand on the performance of the unit. a raise in the predicted demand allowed the unit not only to achieve the highest dispatch of all scenarios, but the greatest npv as well. on the other hand, a 10% drop in demand results in the lowest possible dispatch paired with the most negative npv of all scenarios. between the two scenarios there is a 1660 gwh/annum and a 756m€ difference. the main results of electricity consumption sensitivity cases are presented in table 15. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.206-230 228 table 15. electricity consumption sensitivity cases electricity consumption [%] -10 +10 ampe [€/mwh] 60.45 47.41 production [gwh] 3756 2094 revenues [m€] 237.1 99.7 co2 emissions [tco2] 2.83 1.58 npv [m€] 286.85 -469.34 irr [%] 16.2 the last of the sensitivity cases involved the use of renewable sources (figure 14, cases 15-18). despite the scenarios being somewhat of a stretch considering the state of the croatian electricity sector, they envisage the annual production of renewables in croatia (excluding the hydro sector) to be 1000 gwh, 2000 gwh, 3000 gwh and 4000 gwh, or, in other words, 6%, 11%, 17% and 22% of the annual overall croatian consumption respectively. somewhat surprisingly, the ipp is not influenced by this growth and still achieves a satisfying dispatch along with a positive npv. partially it still serves as base load power for the croatian system and partially it sells its production across the borders. observing the electricity sector as a whole, it can be noticed that the most significant influence manifests in the energy exchanges. more renewables mean less imports; 3000 gwh at settings listed results in a breakpoint at which the import/export equals approximately zero. for any quote of renewables higher that this value, croatia becomes a net exporter of electricity. the negative aspect regards the rest of the thermal sector which gradually lowers its output as it has less consumption to bid for on the market. table 16. renewables production sensitivity cases production from renewable sources [gwh] 1000 2000 3000 4000 ampe [€/mwh] 55.1 55 54.92 54.8 production [gwh] 3525 3519 3501 3471 revenues [m€] 211.1 210.7 209.7 207.6 co2 emissions [tco2] 2.65 2.65 2.64 2.61 npv [m€] 137.44 133.80 127.50 118.89 irr [%] 12.4 12.3 12.1 11.9 figure 14. market analysis sensitivity cases coal based electricity generation in south east europe: a case study for croatia 229 7.5. results and discussion primarily, we would like to advise the reader of this article to refrain from thinking that the numbers presented are “real”. as detailed as the analysis, they are only of indicative nature. just because a computer can calculate numbers to the penny does not mean that the numbers are true. the biggest pitfall of this type of analyses is a significant amount of uncertainty due to the high number of assumptions that have to be made. the uncertainties regarding these types of investments cause projects to flop in the very beginnings without reaching financial close. financial close occurs when all the project and financing agreements have been signed and all the required conditions contained in them have been met. it enables funds to start flowing so that project implementation can actually start. despite plans of adding new generation capacities by building new thermal units, most of the projects in eu these days are being cancelled or at best postponed mainly due to the risks and uncertainties involved. most of the projects nowadays are being financed by financial institutions. these institutions do not to bare uncertainties and charge risk premiums to compensate for them. if they adjudge the project risks as too high, they are unwilling to finance the project. because of these issues, ipp companies pioneered the use of the discounted cash flow (dcf) model. it was mostly used for smaller power projects. in this model, the developers attempt to fix as many costs as possible by obtaining fixed price contracts for all of the major cost contributors such as the epc price, fuel contracts, o&m and, most preferably, a ppa. having a quality ppa presents one of the most significant assets of an ipp as it can diminish one of the biggest risks that projects in the electricity sector face – the merchant risk. having reduced the risks of the project, proper financing can be achieved and at a lower cost. this is a perquisite for a successful investment. as for the ipp in study, our analysis established it as a risky investment, highly dependent on external factors that cannot be influenced. however, after observing all the scenarios, there are only four cases in which the investment achieves a negative npv. prices of eua at 40 €/tco2, a combination of fuel prices 20% different from predicted, 30% higher hydro production and 10% lower demand are all conditions less likely to happen and the likelihood of them to be maintained through a prolonged period of time is deemed very low. despite all the uncertainties, we consider the ipp in study a stable investment relatively resistant to external influences and likely to achieve a profit as much as any other coal fired unit in the region. 8. conclusions investing in electricity generation and achieving a profit has in recent years become an increasingly difficult task. the fast changing dynamics of the electricity market paired with harsh eu policies towards fossil based electricity generation make investments in coal fired power plants extremely risky. uncertainties inevitably raise costs and tend to postpone or even cancel a number of projects. now more than ever, feasibility studies, market analysis, detailed risk assessments and consideration to a string of possible influencing factors are needed to understand the possibilities when investing in the thermal sector. only carefully planned, well structured projects can obtain the necessary licenses, achieve financing and get through the construction period. as this paper showed, it is very difficult to predict whether this type of investment will have a future; will it achieve a positive cash flow during the course of years and will it, in the end, be financially successful. despite providing the numbers, this paper cannot give the answer whether to invest in coal based electricity generation in see or not. it can and it does, however, provide a clearer picture of the possible problems, risks and outcomes when investing in this type of projects. references bugge, j., kjær, s., blum, r. (2006). high-efficiency coal-fired power plants development and perspectives, energy, 31, 1437-1445. cerović, lj., maradin, d., čegar, s. (2014). from the restructuring of the power sector to diversification of renewable energy sources: preconditions for efficient and sustainable electricity market. international journal of energy economics and policy, 4(4), 599–609. cesi. (2009). promed vs. 2009a, software package user`s manual, (mtsp/mtspq vs 2009a, bum) croatian official gazette 130/09. croatian official gazette 177/04 and 76/07. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.206-230 230 croatian official gazette 177/04, 76/07, 152/08, 14/11 and 59/12. croatian official gazette 68/01, 177/04, 76/07, 152/08 and 127/10. datamonitor. (2014). energy, market landscape: croatia. retrieved from https://www.datamonitor.com, last accessed 29th october 2014. datamonitor. (2014). european power assets database. retrieved from https://www.datamonitor.com, last accessed 29th october 2014. de oliveira, w.s., fernandes, a.j. (2012). optimization model for economic evaluation of wind farms how to optimize a wind energy project economically and technically. international journal of energy economics and policy, 2, 10-20. directive 2009/29/ec of the european parliament and of the council. directive 2010/75/eu of the european parliament and of the council on industrial emissions. entso-e. (2014). https://www.entsoe.eu/, last accessed 29th october 2014. european energy exchange. (2014). retrieved from http://www.eex.com/en/, last accessed 29th october 2014. green, r., lorenzoni, a., perez, y., pollitt, m. (2006). benchmarking electricity liberalization in europe. electricity policy research group working papers no. 06/09. university of cambridge, cambridge. his global insight. (2014). https://www.ihs.com/products/global-insight/index.aspx, last accessed 29th october 2014. international energy agency (iea). (2011). medium-term coal market report. international energy agency (iea). (2012). key world energy statistics. international energy agency (iea). (2012). technology roadmap: high efficiency, low emissions coal-fired power generation. jamasb, t., pollitt, m. (2005). electricity market reform in the european union: review of progress toward liberalization and integration. energy journal 26, 11–41. special issue on european electricity liberalization. lucquiaud m., gibbins j. (2011). on the integration of co2 capture with coal-firedpower plants: a methodology to assess and optimise solvent-based post-combustion capture systems. chemical engineering research and design, 89, 1553-1571. massachusetts institute of technology (mit). (2007). the future of coal – options for a carbonconstrained world. mit press, cambridge, mass. official gazette 22/2013. murthy, g.g.p., sedidi, v., panda, a.k., rath, b.n. (2014). forecasting electricity prices in deregulated wholesale spot electricity market: a review. international journal of energy economics and policy, 4(1), 32-42. pollitt, m. (2009). evaluating the evidence on electricity reform: lessons for the south east europe (see) market. utilities policy, 17, 13–23. rubin, e.s., chen, c., rao, a.b. (2007). cost and performance of fossil fuel power plants with co2 capture and storage. energy policy, 35, 4444-4454. višković, a., franki, v., valentić, v. (2014a). ccs (carbon capture and storage) investment possibility in south east europe: a case study for croatia. energy, 70, 325-337. višković, a., franki, v., valentić, v. (2014b). effect of regulation on power-plant operation and investment in the south east europe market: an analysis of two cases. utilities policy, accepted for publication may 2014. višković, a., valentić, v., franki, v. (2013). the impact of carbon prices on ccs investment in south east europe. economics and policy of energy and the environment, volume 2013/3. world resources institute (wri). (2012). global coal risk assessment: data analysis and market research. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020310 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 310-317. the impact of oil price fluctuations on saudi arabia stock market: a vector error-correction model analysis nouf bin ayyaf al-mogren* department of finance, college of business administration, prince sultan university, riyadh, saudi arabia. *email: nbinayyaf@psu.edu.sa received: 20 june 2020 accepted: 19 september 2020 doi: https://doi.org/10.32479/ijeep.10525 abstract this paper examine the relationship between oil prices and the saudi stock market by testing the null hypothesis that oil prices are statistically significant predictors of the saudi stock market’s movements for the period 2000-2019. finding the time series to be cointegrated, the paper performs the testing procedure by employing a vector error correction model (vecm) and results obtained indicate that oil prices are not statistically significant predictors of saudi stock market movements, thus giving us reason to reject our null hypothesis. we also find evidence that the new york stock exchange nyse is a better predictor of both the saudi stock index and oil price fluctuations, paving the way for further research into these correlations in the future. keywords: oil price, stock exchange, vector error correction model, saudi arabia jel classifications: e44, g12, g15, c32 1. introduction as the kingdom of saudi arabia is one of the largest oil market producers in the world, its stock market is widely expected to be affected by oil price shocks and fluctuations. since its discovery in the early 1850s, oil has surpassed gold, coal and all other minerals in proving to be the most important commodity in modern times, as it is now considered the main driving force behind modernization and industrialization. looking back at the history of oil prices in the last century, it is clear that oil is a volatile commodity which is very sensitive to changing political events, as seen in figure 1.1 as oil’s role continues to increase, the importance of understanding the economies of the countries that produce and export it, including the main world exporters of oil, the gulf cooperation council (gcc), increases as well. the gcc, which was established in 1981, includes six member countries: saudi arabia, kuwait, united arab emirates (uae), 1 goldman sachs, 2016, the long history of oil prices, business insider, http:// uk.businessinsider.com/timeline-155-year-history-of-oil-prices-2016-12. bahrain, qatar, and oman. the gcc’s oil output accounts for two thirds of the organization of the petroleum exporting countries’ (opec) oil production and reserves. as james d. hamilton said regarding the detriments of oil prices, ‘in the modern era, it is sovereign countries rather than private companies which would be calling the shots’, stating that the role of opec in influencing oil prices cannot be emphasized enough (hamilton, 2008). therefore, understanding the complex structure of the gcc economies is important for many reasons: first, the gcc is one of the major oil exporting area in the world, with economies that heavily depend on oil’s price performance. second, all gcc countries achieved high economic growth rates in the wake of oil price surges in the last decade. as a result, gcc countries are now considered as an attractive investment hub for international investors looking for diversification, due to its high growth and profit potential. lastly, gcc markets are an enticingly unique area to study in the sense that they differ from both developed and emerging markets; they are predominately–segmented markets, largely isolated from the international markets, and are overly sensitive to regional and political events (arouri and rault, 2012). as mohanty et al. (2011) explained that gcc countries, oil exports largely determine foreign earnings and the governments’ budget this journal is licensed under a creative commons attribution 4.0 international license al-mogren: the impact of oil price fluctuations on saudi arabia stock market: a vector error-correction model analysis international journal of energy economics and policy | vol 10 • issue 6 • 2020 311 revenues and expenditures; thus, they are the primary determinant of aggregate demand. the aggregate demand effect influences corporate output and domestic price levels, which eventually impacts corporate earnings. such a strong oil influence on the national economy of these countries presumably makes share prices in their stock markets very vulnerable to oil prices and changes in the oil market. thus, one would expect that an increase in oil price would positively affect economic output and corporate earnings at the aggregate level for gcc countries, but the impact of oil price movements on stock prices at the country and industry level is ambiguous. it is an empirical question, determining which of the positive (increased revenues, cash flows, and earnings) and negative (inflation, interest rate, and discount rate) effects offset the other. to be able to accurately assess an economy, one must take a closer look at the driving factors behind it. a major indicator of a country’s economy is its stock exchange, which in saudi arabia is referred to as tadawul (arabic for trade). the main index in tadawul is called tasi (tadawul all share index), with twenty sectors listed, amounting to 171 different companies.2 in addition to tasi, in the 2 official saudi tadawul website, knowledge center, capital market overview, https://www.tadawul.com.sa/wps/portal/tadawul/knowledgecenter/about/capital-market-overview. first quarter of 2017 tadawul launched another index called nomu (arabic for growth), which is a parallel equity market but with less strict listing requirements serving as an alternative platform for growing companies to go public. nomu was created with the aim of developing a more advanced capital market open to the world, allowing greater capital inflows which in turn stimulate economic growth. nomu was launched with seven companies, requiring a market value of at least ten million sar (2.6 million usd), a minimum shareholder size of 35–50 shareholders, and an offering percentage of at least 20%. with the goal of creating greater stock price stability, traders at nomu are restricted to institutional and qualified investors only.3 the share price movement of tasi, and more recently nomu, can be quite volatile and sometimes seem disconnected from company fundamentals, which highlights the existence of other factors that might be influencing returns and stock prices. this begs the important question: is the fluctuation in oil prices one of those factors? the foremost goal of a thriving saudi economy for achieving vision 2030 is diversifying revenue streams and raising non–oil 3 official saudi tadawul website, knowledge center, nomu parallel market, https://www.tadawul.com.sa/wps/portal/tadawul/knowledge-center/about/ parallel-market. figure 1: the long history of oil prices al-mogren: the impact of oil price fluctuations on saudi arabia stock market: a vector error-correction model analysis international journal of energy economics and policy | vol 10 • issue 6 • 2020312 exports share of gdp from 16% to 50% by the year 2030. doing so can be achieved by many methods, such as increasing foreign direct investment from 3.8% to the targeted international level of 5.7% of gdp, as well as the privatization of state-owned assets and government services. the main example and forefront project of this objective is the plan to offer a 5% stake of saudi–aramco, the huge state–owned oil company, to the public in an ipo in late 2018. this is expected to be the largest ipo in history with an expected value of $2 trillion. for that reason, closely examining the relationship between oil price volatility and stock market return, especially for a country as heavily reliant on oil as saudi arabia, is of great importance. the motivation behind this paper is to fill the gaps in existing literature regarding understanding this ambiguous yet important area. for investors, understanding the drivers behind the saudi stock market’s movements and its relationship with oil prices is more important now than ever, especially after the major efforts being implemented to position the saudi market as a major world player. saudi arabia represents a promising new area for regional and international portfolio diversification. thus, understanding the main drivers behind its stock return movements is integral to making sound investment decisions by local and foreign investors alike. as for policy makers, being able to correctly determine and understand whether such a relationship exists can play a vital role in creating relevant policies and implementing appropriate regulations, based on facts that would help in creating the coherent, motivating and competitive working environment they aspire to reach. basing decisions on a clear understanding of all surrounding factors can indeed aid in making the saudi market a safe and attractive world–ranked investment hub. the purpose of this paper is to investigate the dynamic relationship by using a vector error correction model (vecm). more precisely, vecm’s variance decomposition and impulse responses techniques will be executed after running the necessary diagnostic tests of assessing stationarity by the modified dickey–fuller test, determining the correct equation order by the var lag order test, and examining if the variables are cointegrated by using the johansen procedure. the remaining structured as follows: section 2 will provide related literature. section 3 will explain the data, testing methodology implemented and results respectively. findings and analysis of results will be discussed in full in section 6. finally, the conclusion of the paper will be presented in section 4. 2. theory and evidence although numerous studies have been conducted relating to the correlation between oil prices and different world–wide stock indices, the results found are rather conflicting. and with the majority of the available papers examining this relationship in the context of developed economies such as the us, europe, australia and japan, very few have endeavored to investigate the existence and degree of such a connection in emerging markets which happen to also be major oil exporters, such as saudi arabia. samontaray et al. (2014) examined the relationship between stocks in the saudi stock market —denoted by the saudi stock index tasi—and a number of diverse macroeconomic variables. their investigation came to conclusion based on empirical testing by using the factors into three independent variables: oil wt, saudi exports and the pe ratio and they found that a significant correlating relationship does in fact exist between the chosen factors and the movement of the saudi stock market index. mohanty et al. (2011) using a linear factor pricing model, tried to evaluate whether a relationship exists between oil prices and equity returns in both country–level and industry–level in the gcc countries. the testing showed that a significant positive relationship does exist between fluctuations in oil prices and stock market returns in all of the gcc countries, except kuwait, but found that the exposure is asymmetric between a rise and a fall in prices. as for the industry–level correlation, the test finds that twelve out of the twenty industries tested have a positive significant relationship, which indicates that the exposure differs significantly between different industries and countries even within the similar gcc area. on the other hand, arouri and fouquau (2009), who endeavored to examine the short-term relationship, and arouri and rault (2012), who intended to study the long–term relationship between stock markets in the gcc region and oil prices, came to an opposite conclusion. the short–term test was conducted by using a non– parametric method, after testing for heteroscedasticity, correlation and homogeneity of error terms; the long–term test used bootstrap panel cointegration techniques along with regression sur methods. surprisingly, both studies found that positive evidence suggest a significant link in all the countries except saudi arabia on the long– term and all countries except saudi arabia, kuwait and bahrain on the short–term. lastly, a paper focusing on kuwait approached the examination of this complex relationship from a new angle. al hayky and naim (2016) attempted to assess whether or not the degree of volatility in the stock market affected the extent of the relationship with oil prices. the paper first ran the augmented dickey fuller (adf) test, as well as a unit root test and johansen (1988) and johansen and juselius (1990) cointegration analysis, then applied markov switching model to examine oil price’s effect on both high and low volatility regimes. interestingly, the paper found that different volatility periods yielded different results, with low volatility periods showing no relationship, and a positive and significant relationship in high volatility periods. fayyad and daly (2011), who investigated the relationship between oil prices and stock markets by employing vector autoregressive (var), variance decomposition and impulse response techniques, then compared the results between major exporters of oil (the five gcc countries of kuwait, oman, uae, bahrain, and qatar) and advanced countries who are major importers of oil (usa and uk). the overall empirical findings were that all of the tested countries exhibited a significant inter–relationship with oil prices, but to varying degrees. another study, aiming to investigate whether a rise in oil price affects its relationship with stock markets, focused mainly on the gcc countries in the period between 2001 and 2005. al-mogren: the impact of oil price fluctuations on saudi arabia stock market: a vector error-correction model analysis international journal of energy economics and policy | vol 10 • issue 6 • 2020 313 zarour (2006) divided the study into two sub–periods (the first being 2001–2003 which represent normal/low prices and the second being 2003–2005 representing the period when the huge surge in prices occurred) and estimated a separate var for each. the paper found that oil price, as a predictive mechanism, does in fact increase in power the more its price increase, so does the speed of response of the markets to any shocks in oil prices. furthermore, the study found that the saudi market is more responsive to changes in oil prices and vice versa, as well as, alongside oman, have the power to predict oil prices. sadorsky (1999) used a similar methodology by first applying a cointegration test for nonstationary variables, which showed that no long–run relationship exists and hence the vector autoregressive (var) model can be used. then the var test was carried out through variance decomposition analysis and impulse responses function. unsurprisingly, it was found that oil prices and oil price volatility are both significant affecting factors on the us stock market, but not vice–versa. it is noticed that similar findings are discovered when studying different parts of the world as well. taking the case of turkey, which is neither a major oil exporter nor importer, eryiğit (2012) examined the short–term relationship between interest rates, the istanbul stock exchange market index, and the exchange rate with the changing oil prices by using weekly data from the period 2005-2008. the paper found that oil price shocks affect the main turkish stock market, which is explained by the author as perhaps due to the fact that turkey is a net oil importing country with the majority of the listed companies affected directly or indirectly by the changes in world–wide oil prices. but just as there are studies supporting each other’s findings, some studies contradict the notion that oil price must have an effect on stock markets. such results were found by cong et al. (2008), who used a multivariate vector autoregressive model to uncover a result that oil price shocks do not show a statistically significant impact on the chinese stock market index, except for some indices of specific sectors which are heavily reliant on oil. masih et al. (2011) also investigated the relationship between south korea’s stock market and oil fluctuations and found that a long–term relationship exists among the factors included in their study (interest rates, economic activity, real stock returns, real oil prices, and oil price volatility) and that fluctuations in oil price significantly affects the south korean stock market. similarly, cuñado and de gracia (2013) uncovered similar results that oil price fluctuations (whether shocks in supply or in demand) have significant negative effects on most of the european countries, but with the supply shocks generating a greater negative impact than demand shocks. filis (2010) found a significant negative relationship between oil prices and the greek stock market. however, interesting results have been obtained when this relationship was studied with regards to oil prices and three turkish stock market indices in the period between 2000 and 2010 in istanbul, turkey. kapusuzoglu (2011) found that all stock indices examined were cointegrated with oil prices, but that a one–way causal relationship existed between the indices and oil prices but not vice–versa, meaning oil price does not have a causal relationship with any of the three indices. falzon and castillo (2013), examined same relationship in the us and uk across ten industries by using arch and garch modelling methodology and found that each industry’s dependence on oil. more precisely, first, changes in oil price do not impact every industry. second, changes in oil prices can explain changes in equity returns for several industries in both countries. and finally, oil has a positive effect on oil–producing industries and negative effect on oil–consuming industries. even if it is evident that a relationship does exist in most of the world–wide stock indices, the nature of this relationship, whether positive or negative, still needs to be examined. for the case of hasan and ratti (2012), who examined this relationship in the context of the australian stock market using conditional volatility as a measure oil price risk and employed the garch–m model to find the risk and return patterns in some chosen sectors: an inverse relationship was found between oil and index fluctuations, where an increase in oil price return or volatility decreased the index’s return or volatility. similarly, regarding the relationship between oil price volatility and stock market returns using an egarch–m model to specify the effect on each of the country’s stock market returns and volatility, dhaoui and khraief (2014) found a negative relationship in all of the eight developed economies tested (us, uk, canada, switzerland, france, australia, japan) except singapore, where no relationship was found. in contrast, a significant positive relationship was noticed between oil price volatility and stock market volatility in all countries except france and the uk, where again, no relationship was empirically found. furthermore, a study by aloui and jammazi (2009) used the two–regime markov–switching egarch model to examine this relationship in the context of the uk, france and japan for the period between 1989-2007 using monthly data. it was found that the volatility of these countries’ stock market returns as well as their probability to transition across political regimes are greatly influenced by an increase in oil prices. finally, filis et al. (2011) investigated this dynamic correlation by focusing on three oil–exporting countries (canada, mexico and brazil) and then contrasting the results with tests on three oil–importing countries (us, germany and the netherlands). their findings suggested that the time–varying correlation is similar in both oil–importing and oil–exporting economies and that, in periods of international uncertainties, the oil market does not provide protection against stock market losses. after considering the previously mentioned studies and their testing methodologies, it becomes clear that the researchers prefers to use either a var model or an arch/garch model to examine closely any existing relationship—or lack thereof—between oil prices and stock indices. that is why the paper by constantinos et al. (2010) is unique as it applied both var and arch/garch models alongside each other to do their investigation. the var model in conjunction with granger–causality analysis was used to investigate the linkage between the greek stock market and the international oil prices, al-mogren: the impact of oil price fluctuations on saudi arabia stock market: a vector error-correction model analysis international journal of energy economics and policy | vol 10 • issue 6 • 2020314 and the volatilities were quantified using arch/garch modelling techniques. focusing on the period between 2004 and 2006, the paper’s findings confirm the mainstream notion and detect signs of a significant positive relationship between oil price fluctuations and the greek stock market. arouri et al. (2011) implemented the vector autoregressive moving average generalized autoregressive conditional heteroscedasticity technique (var-garch), mainly due to its computational ease and the fact that it allows the examination of both the volatility and the interdependence simultaneously. their empirical findings suggest a considerable presence of volatility and return spillover between the examined gcc stock markets and oil prices. in addition to var and arch/garch variations, other testing methods have been used to further examine this interrelated relationship as well. such as the case of el-sharif et al. (2005) who used a multi–factor model to focus their investigation on the relationship between crude oil prices and the uk oil and gas sector equity prices. the paper found that oil and gas stock returns are primarily impacted by the volatility of crude oil prices as the main risk factor. moreover, it was found that a weak relationship exists between crude oil prices and non–oil and gas sectors equity returns. the evidence from the paper suggests that the relationship is always positive, highly significant, and reflects the direct impact of crude oil price volatility on oil and gas sector equity returns. finally, basher and sadorsky (2006) focused their research on emerging markets and examined the correlation between oil price volatility and the respective stock market’s returns. the paper used daily, weekly and monthly data for twenty–one emerging markets indices (including brazil, india, russia and china) in an international multi–factor model which allows for both unconditional and conditional risk factors—this model is related to the international capital asset pricing model (capm). the paper found that oil price risks affect stock prices significantly across all emerging markets. jarrah and salim (2016) and samontaray et al. (2014) found evidence of a strong correlation between tasi and several macroeconomic factors including oil prices in the context of saudi arabia. also, the research conducted by zarour (2006) found similar evidence in that the saudi market is more responsive than the other tested countries to changes in oil prices and vice versa. 3. model and results it is clear from previous studies that the relationship between oil price fluctuations and world indices in general, and the saudi index in particular, are contradictory. therefore, this paper hypotheses, while endeavoring to examine this relationship more closely in the context of the saudi market, is based on the findings by the majority of previous world–wide research papers’ results, such as fayyad and daly (2011), sadorsky (1999) and eryiğit (2012). the null and alternative hypotheses used are as follows: ho: oil prices are statistically significant predictors of saudi stock market movements ha: oil prices are not statistically significant predictors of saudi stock market movements. the data used in this paper were gathered from the bloomberg terminal, the saudi arabian monetary authority (sama) website, and the saudi stock exchange (tadawul) website. all data are reported on a monthly basis for the period 2000-2019. this period was chosen to account for the major fluctuations of both oil prices and world–wide stock markets. the paper used the variable of interest represented by the saudi stock index called tadawul all share index (tasi). the main predictor will be oil price and its fluctuations, represented in this paper by the west texas intermediate (wti), which is a grade of crude oil often used as the international benchmark for oil prices. other variables thought to have some effect on the saudi economy and thus be related to the fluctuations in tasi have been introduced as controlling variables. seeing the importance of the united states’ economy to the well–being of the saudi economy, and due to the fact that the us is one of the major import and export countries from and to saudi arabia, certain key us indicators are vital to include. the first of which is the new york stock exchange (nyse), which is included as a proxy for us market risk. also, to represent the effects of changing interest rates, the us 1 month interest rate is added and named (us1m). furthermore, to account for the effects of world–commodities on the changes of such macroeconomic variables, the pallfnf index, which is the weighted average of all commodity prices, is included and renamed as ‘commodities’ for ease. returns are calculated by taking the first difference of the natural logarithm. a summary of statistical properties of the data used is exhibited in the table 1. the methodological framework used in this paper is based on a p–th order var: yt=v+a1 yt–1+⋯+ap yt–p+εt (1) where yt is a vector of endogenous variable, a vector of constants, ai for i=1,…,p are matrices of coefficients, and εt is a vector of disturbances.4 estimation requires that the components of yt are covariance stationary. a series is said to be covariance or weakly stationary 4 j. dinardo, 1997, econometrics methods, fourth edition (new york, ny: mcgraw–hill education). table 1: descriptive statistics descriptives tasi wti nyse comm us1m mean 8.7000 4.0220 4.9648 4.7183 0.9983 maximum 9.8653 4.9485 9.7218 5.3215 5.5000 minimum 7.3215 3.0012 8.3416 3.9900 0.1500 std. dev. 0.5361 0.4899 0.2334 0.4185 1.5830 skewness –0.5340 –0.2750 –0.1510 –0.2526 1.9930 kurtosis 2.6510 1.8650 2.1270 1.8280 5.4550 probability 0.0000 0.0000 0.0000 0.0001 0.0002 sum 1827.0020 844.6279 1882.6110 990.8451 124.7991 observations 234 234 234 234 140 source: authors’ estimation al-mogren: the impact of oil price fluctuations on saudi arabia stock market: a vector error-correction model analysis international journal of energy economics and policy | vol 10 • issue 6 • 2020 315 when it has a constant mean, a constant variance and constant auto–covariances for each given lag.5 stationary variables tend to cross their mean frequently while the nonstationary differences can wander a long way from their mean value. we determine the appropriate var equation’s lag order through the selection–order criteria. this test reports four criteria which are: the final prediction error (fpe), akaike’s information criterion (aic), schwarz’s bayesian information criterion (sbic), and the hannan and quinn information criterion (hqic), as well as a sequence of likelihood ratios (lr), giving us the option of comparing among them to make the most appropriate decision for our model. it is important to distinguish between stationary and nonstationary data before testing for many reasons, namely because this can strongly influence the properties and behavior of the time-series. moreover, the use of nonstationary data can lead to a spurious regression (granger and newbold 1974), which is a regression that appears to be good but is worthless in reality, or to invalid assumptions, meaning that the usual ‘t-ratios’ will not follow a t-distribution, and the f–statistic will not follow an f–distribution, and so on (brooks, 2014). this paper uses another extension of the adf test (df–gls) as suggested by elliott et al. (1996). table 2 shows the df-gls test to verify the order of integration. the results show that all series are nonstationary at the level and stationary at the first difference. we then proceed to test for cointegration between our variables using the johansen procedure, the results of which are shown in table 3. 5 c. brooks, 2014, introductory econometrics for finance, third ed. (cambridge, uk: cambridge university press). as indicated by the table, since the test statistic of 36.50 does not exceed the 5% critical value of 47.21, we fail to reject the null hypothesis that the rank of the cointegrating matrix is 1 at this significance level, against the alternative hypothesis that it is more than 1. this means that we find evidence for 1 cointegrating relationship. since evidence of cointegration exists, we will now implement a vector error correction model (vecm) and results given in table 4. different information criteria indicate different results (as shown in table 4), but since three (lr, fpe, aic) out of five (not sc, hq) tests suggest that the appropriate lag should be 2 not 1, we will adopt 2 as our appropriate corresponding vecm lag of order p-1. we then proceed with implementing our vecm to capture the dynamics of our cointegrated system. in the summarized results shown in table 5, the error correction term for each variable represents the speed of mean reversion to equilibrium. at 5% significance, we find that only oil and commodities have statistically significant coefficient values, this indicates there is only evidence for error correction in these variables. the vecm results (table 5) indicate that, in the short run at a 5% significance level, tasi returns are predicted by nyse lagged returns and by us1m 2 period lagged change. more precisely, table 2: dickey–fuller generalized least square (df-gls) test variables level first difference i(0) i(1) c c & t c c & t tasi –1.062 –2.932* –7.778 –2.933* oil –1.72 –2.932* –8.693 –2.933* nyse –2.144 –2.932* –5.69 –2.925* comm –1.41 –2.932* –6.904 –2.933* us1m –0.511 –2.997* –8.085 –2.999* mckinnon critical values for intercept (c); 1% level=–3.6394, 5% level=–2.9511, and for intercept & trend (c & t); 1% level=–4.2529, 5% level=–3.5485. lag length in all cases is one. *shows stationarity at the 1% level of significance. source: authors’ estimation table 3: co-integration test results hypothesized no. of ce(s) t. statistics 5% critical values maxeigenvalue statistics 5% critical values none 72.0869 68.5800 27.7100 27.0700 at most 1 36.5008* 47.2100 19.7400 20.9700 at most 2 17.5400 29.6800 8.0600 13.6000 at most 3 6.8500 15.4100 3.9800 14.0700 at most 4 0.6500 3.7600 1.0750 3.7600 source: authors’ estimation table 4: var lag order selection criteria lag ll lr fpe aic sc hq 0 683 .2000 8.50e -12 –11.3033 –11.1872 –11.2562 1 757 .8060 149.2100 3.70e –12 –12.1301 –11.4332* –11.8471* 2 791 .7570 67.9020* 3.2 e-12* –12.2793* –11.0017 –11.7604 3 809 .0230 34.5310 3.70 e-12 –12.1504 –10.2921 –11.3957 4 824 .1380 30.2310 4.40 e-12 –11.9856 –9.54658 –10.9951 * indicates lag order selected by the criterion. source: authors’ estimation table 5: results of vector error correction model variable variable relationship with coefficient probability tasi e* –0.0237 0.3820 nyse ld 0.6746 0.0000 us1m l2d –0.0463 0.0440 wti e* 0.1165 0.0000 nyse ld 0.7435 0.0000 commodities ld 0.7444 0.0000 commodities l2d 0.4255 0.0420 nyse e* 0.0232 0.2220 tasi ld –0.1600 0.0180 us1m l2d 0.0373 0.0210 commodities e* 0.0429 0.0210 nyse ld 0.3871 0.0000 commodities l2d 0.3022 0.0400 us1m e* 0.0288 0.7910 tasi l2d –0.8906 0.0190 nyse l2d 1.7027 0.0090 e* = error correction. source: authors’ estimation al-mogren: the impact of oil price fluctuations on saudi arabia stock market: a vector error-correction model analysis international journal of energy economics and policy | vol 10 • issue 6 • 2020316 figure 2: vecm stability analysis graphical result table 6: vector error correction model—cointegrating vector results variables coef. std. err. t. statistic probability 5% critical values 10% critical values constant –1.6264 tasi 1.0000 wti –3.7798 0.6849 –5.5200 0.0000 –5.1221 –2.4374 nyse –1.3368 0.2118 –6.3100 0.0000 –1.7519 –0.9218 comm 4.2064 0.8869 4.7400 0.0000 2.4682 5.9446 us1m 0.8347 0.3255 2.5600 0.0100 0.0197 0.1473 source: authors’ estimation a 1% change in nyse last period is associated with a 0.675% change in tasi, and a 1 percentage point change in us1m in the two previous periods is associated with a 0.046% change in tasi today. this is a significantly more modest association than that between nyse and tasi, as may be expected. at the same significance level, we find no statistically significant short run relationship between tasi and wti. taking a look at the other variables at the 5% significance level, in the short run we find evidence that wti is predicted by both nyse and commodities. with a significant error correction term in wti, it is indicative of a long–run component of the dynamics of oil with respect to all the other variables. as for nyse, the first lag of tasi returns and us1m appear to be the only factors which are statistically significant short-run predictors of nyse. tasi’s predictive power over nyse is counter intuitive and hence may be a result of omitted variable bias (ovb). the fact that nyse is not the main focus of our study means that major factors influencing its daily movements are not included; thus tasi’s relationship might be reflecting all other omitted factors resulting in a bias to the coefficient. furthermore, commodities seem to be predicted only by nyse. with its error correction term also statistically significant, this indicates a strong connection between commodities and nyse in the short run and between commodities and all of the other variables in the long run. finally, in the short run, changes in the us 1 month interest rates are predicted by both tasis 2 period lagged returns and those of nyse. table 7: vecm stability analysis result eigenvalue modulus 1 1 1 1 1 1 1 1 0.6638047 + 0.2864086i 0.722957 0.6638047 – 0.2864086i 0.722957 –0.00110266 + 0.686821i 0.686822 –0.00110266 – 0.686821i 0.686822 –0.4878489 + 0.733506i 0.493332 –0.4878489 – 0.733506i 0.49332 0.4746181 0.474618 –0.1935413 + 0.2085671i 0.284532 –0.194513 – 0.2085671i 0.284532 0.1762624 + 0.1845036i 0.255167 0.1762624 – 0.1845036i 0.255167 the vecm specification imposes 4-unit moduli. source: authors’ estimation the results shown in table 6 imply a long run relationship of the form: logtasi=3.78logwti+ 1.34lognyse–4.21logcom+0.08us1m here, the coefficients on logwti, lognyse and logcom represent the long–run elasticities. thus, a 1% change in wti would in the long run be associated with a 3.78% change in tasi, and so on. these are signed as expected, particularly for wti and nyse, which both have positive long–run elasticities. as we can see, the results in table 7 indicate that the moduli of all real roots are far from 1, with the closest being at 0.722957, which is still not a concerning degree. these results provide no evidence that the cointegrating equations are non–stationary, resulting in a stable vecm. this finding is supported by the graph exhibited below: figure 2 plots the roots of the companion matrix of the vecm, and gives a visual indication of the distances between the roots and the unit circle. as we can see, all of the tested roots lie far from the unit circle, which reinforces the table’s finding that our vecm is indeed stable. 4. conclusion and policy recommendation the paper found reason to test for cointegration after the df– gls unit root test indicated that the variables are first difference al-mogren: the impact of oil price fluctuations on saudi arabia stock market: a vector error-correction model analysis international journal of energy economics and policy | vol 10 • issue 6 • 2020 317 stationary, and testing for cointegration thereafter using the johansen procedure confirmed that our series are indeed cointegrated. for that reason, the vector error correction model (vecm) was used, which is the appropriate specification for cointegrating vectors because it differentiates among the vectors of endogenous variables and includes an error–correction term to capture long–run dynamics. the vecm results indicate that, at the 5% significance level, no predictive relationship exists between tasi and wti in the short run, and that the biggest short–term predictor of tasi returns are nyse lagged returns. interestingly, nyse is found to be a good short–term predictor of wti at the 5% significance level as well, indicating that in the short term the nyse can be used to predict both tasi and wti. wti is also thought to have long–term dynamics with all variables, as its error correction term was significant at the same significance level. additionally, the results indicate that a 1% change in wti would be associated with a 3.78% long–run change in tasi, and that a 1% change in nyse would be associated with a 1.34% long–run change in tasi as well. these results suggest that wti holds a greater magnitude of long–term effect over tasi, and that an increase in both wti and nyse will be associated with a positive increase in tasi in the long run. the results revealed in this paper give us reason to reject our original null hypothesis that oil prices are statistically significant predictors of the saudi stock market movements. the new york stock exchange (nyse) is noticed to be a better predictor of tasi, and therefore additional research must be conducted to closely examine this relationship. additionally, it is observed that the new york stock exchange holds predictive power over oil fluctuations as well, indicating the possibility of the nyse being used as a projection instrument of future oil price fluctuations. these findings open the door for future research to study these relationships more closely and indicate the magnitude at which these relationships can be most observed. references al hayky, a., naim, n. (2016), the relationship between oil price and stock market index: an empirical study from kuwait. kuwait: middle east economic association, 15th international conference. aloui, c., jammazi, r. (2009), the effects of crude oil shocks on stock market shifts behaviour: a regime switching approach. energy economics, 31(5), 789-799. arouri, m., fouquau, j. (2009), on the short-term influence of oil price changes on stock markets in gcc countries: linear and nonlinear analyses. economic bulletin, 29(2), 795-804. arouri, m.e.h., lahiani, a., nguyen, d.k. (2011), return and volatility transmission between world oil prices and stock markets of the gcc countries. economic modelling, 28(4), 1815-1825. arouri, m.e.h., rault, c. (2012), oil prices and stock markets in gcc countries: empirical evidence from panel analysis. international journal of finance and economics, 17(3), 242-253. basher, s.a., sadorsky, p. (2006), oil price risk and emerging stock markets. global finance journal, 17(2), 224-251. brooks, c. (2014), introductory econometrics for finance. 3rd ed. cambridge, united kingdom: cambridge university press. cong, r.g., wei, y.m., jiao, j.l., fan, y. (2008), relationships between oil price shocks and stock market: an empirical analysis from china. energy policy, 36(9), 3544-3553. constantinos, k., ektor, l.a., dimitrios, m. (2010), oil price and stock market linkages in a small oil dependent economy: the case of greece. journal of applied business research, 26(4), 55-64. cuñado, j., de gracia, f.p. (2013), environment and happiness: new evidence for spain. social indicators research, 112(3), 549-567. dhaoui, a., khraief, n. (2014), empirical linkage between oil price and stock market returns and volatility: evidence from international developed markets. economics discussion papers. germany: kiel institute for the world economy. elliott, g., rothenberg, t.j., stock, j.h. (1996), efficient tests for an autoregressive unit root. econometrica, 64(4), 813-830. el-sharif, i., brown, d., burton, b., nixon, b., russell, a. (2005), evidence on the nature and extent of the relationship between oil prices and equity values in the uk. energy economics, 27(6), 819-830. eryiğit, m. (2012), the dynamical relationship between oil price shocks and selected macroeconomic variables in turkey. economic research, 25(2), 263-276. falzon, j., castillo, d. (2013), the impact of oil prices on sectoral equity returns: evidence from uk and us stock market data. journal of financial management, markets and institutions, 1(2), 247-68. fayyad, a., daly, k. (2011), the impact of oil price shocks on stock market returns: comparing gcc countries with the uk and usa. emerging markets review, 12(1), 61-78. filis, g. (2010), macro economy, stock market and oil prices: do meaningful relationships exist among their cyclical fluctuations? energy economics, 32(4), 877-886. filis, g., degiannakis, s., floros, c. (2011), dynamic correlation between stock market and oil prices: the case of oil-importing and oil-exporting countries. international review of financial analysis, 20(3), 152-164. granger, c.w.j., newbold, p. (1974), spurious regressions in econometrics. journal of econometrics, 2(2), 111-120. hamilton, j.d. (2008), oil and the macroeconomy. in: the new palgrave dictionary of economics. london: palgrave macmillan. hasan, m., ratti, r. (2012), oil price shocks and volatility in australian stock returns. melbourne: global accounting, finance and economics conference, business conference papers. jarrah, m., salim, n. (2016), the impact of macroeconomic factors on saudi stock market (tadawul) prices. saudi arabia: international conference on advances in big data analytics. johansen, s. (1988), statistical analysis of cointegration vectors. journal of economic dynamics and control, 12(2-3), 231-254. johansen, s., juselius, k. (1990), maximum likelihood estimation and inference on cointegration-with applications to the demand for money. oxford bulletin of economics and statistics, 52(2), 169-210. kapusuzoglu, a. (2011), relationships between oil price and stock market: an empirical analysis from istanbul stock exchange (ise). international journal of economics and finance, 3(6), 99-106. masih, r., peters, s., mello, l.d. (2011), oil price volatility and stock price fluctuations in an emerging market: evidence from south korea. energy economics, 33(5), 975-986. mohanty, s.k., nandha, m., turkistani, a.q., alaitani, m.y. (2011), oil price movements and stock market returns: evidence from gulf cooperation council (gcc) countries. global finance journal, 22(1), 42-55. sadorsky, p. (1999), stock markets and energy prices. energy economics, 21(5), 449-69. samontaray, d.p., nugali, s., sasidhar, b. (2014), a study of the effect of macroeconomic variables on stock market: saudi perspective. international journal of financial research, 5(4),120-27. zarour, b.a. (2006), wild oil prices, but brave stock markets! the case of gcc stock markets. operational research, 6(2), 145-162. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 5 • 202166 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(5), 66-77. electricity price fundamentals in hydrothermal power generation markets using machine learning and quantile regression analysis andrés oviedo-gómez1*, sandra milena londoño-hernández1, diego fernando manotas-duque2 1school of electrical and electronic engineering, universidad del valle, cali, colombia, 2school of industrial engineering, universidad del valle, cali, colombia. *email: oviedo.andres@correounivalle.edu.co received: 01 march 2021 accepted: 10 june 2021 doi: https://doi.org/10.32479/ijeep.11346 abstract a hydrothermal power generation market is characterized by a strong dependence on water reservoir capacity and fossil fuel sources, which causes differences in generation marginal costs and high variability of the electricity spot price. therefore, this study proposes an empirical approach to identify the price determinants and their effects on price dynamics. this paper presents two methodologies: a machine learning approach and a quantile regression analysis. the first method is used to validate the price determinants through a prediction process, and the second, the quantile regression, to identify the non-linear effects. the most important factors observed are total market demand, water reservoirs capacity for generation, and fossil fuel consumption. the results offer a new perspective about the market structure and spot price volatility. keywords: electricity prices, hydrothermal power generation markets, machine learning, quantile regression, gaussian process regression jel classifications: c22, q41, q43, q47 i. introduction the different reforms in electricity markets defined electricity as a commodity, which can be sold, bought, and traded in a market (berrie and hoyle, 1985). however, its storage limitations make the market price shows characteristics such as seasonal patterns, high volatility, mean reversion, price spikes, and others (girish and vijayalakshmi, 2013; huisman and mahieu, 2003). besides, modeling the price dynamic requires understanding its asymmetric distribution, high dispersion, and serial correlation (ciarreta et al., 2011). therefore, analyzing and predicting the spot prices is a challenge for academics and market agents. on the other hand, the market structure and generation technologies are fundamentals factors in the price formation. based on a particular case of a hydrothermal power generation market which presents: (i) significant differences in the marginal costs of the generation sector; (ii) a small renewable generation capacity; (iii) a strong dependence on exogenous variables as fossil fuel prices and climatology factors; and, where (iv) the risk and uncertainty are higher for market agents, it has been observed that these features cause further increased in price variability (mosquera-lópez et al., 2017a; fernández-blanco et al., 2017; cotia et al., 2019). hence, it is relevant to recognize the determinants that explain the electricity price behavior in this market structure. for this reason, the objective of this study was to identify the economic and technological fundamentals in the hydrothermal power generation market. also, it was sought to evaluate fundamentals effects on spot price dynamic. for the empirical analysis, the colombian electricity market was selected. moreover, the methodology applied in this analysis was divided into two: a machine learning approach and a quantile regression analysis. first, a gaussian process regression (gpr) model was trained to this journal is licensed under a creative commons attribution 4.0 international license oviedo-gómez, et al.: electricity price fundamentals in hydrothermal power generation markets using machine learning and quantile regression analysis international journal of energy economics and policy | vol 11 • issue 5 • 2021 67 validate the determinants and compute the spot price prediction for the next 6 months of the dataset. this method identifies complex patterns in a large volume of data and reviews the data to predict future behavior (castelli et al., 2020; díaz et al., 2019; gonzalez-briones et al., 2019; imani et al., 2020; ribeiro et al., 2020). second, a quantile regression model was fitted because it allows modeling electricity prices seasonality and quantifying the non-linear effects of determinants (ma and koenker, 2006; maciejowska, 2020; mosquera-lópez et al., 2017b; uribe and guillen, 2020). according to aggarwal et al. (2009) and girish and vijayalakshmi (2013), the spot price determinants were grouped into five categories: (i) market characteristics, (ii) fundamental factors, (iii) operation factor, (iv) strategic factors, and (v) historical factors. in the first group, it was identified variables such as energy supply and demand, electricity exports/imports, market-clearing quantity, and energy policy (deng and oren, 2006; mandal et al., 2007; mosqueralópez and nursimulu, 2019; zhang et al., 2008). in the second group, the fundamental factors considered were price volatility, fuel price, weather factors, and hydrological conditions. by contrast, operational factors describe fundamentals as a system load rate, electricity production (deficit/surplus), energy sources (nuclear, hydric, or thermal), line status and limits, and power transmission costs (he et al., 2010; rodriguez and anders, 2004; zhang et al., 2008). meanwhile, strategic factors correspond to energy purchasing agreements, bilateral contracts, bidding strategy, and market design (crespo-cuaresma et al., 2004; kian and keyhani, 2001; rodriguez and anders, 2004). finally, in the fifth group, it has been identified that past observations of variables as demand and supply, hydric reserves, and electricity price affect the present spot price dynamic (ciarreta et al., 2011; mandal et al., 2007). however, and based on the power generation structure selected, the results of the empirical application described that total market demand, water reservoirs capacity for generation, and fossil fuel consumption, are the most relevant determinants of the spot price. also, this paper provides a new contribution in terms of market structure analysis and a new perspective of the spot price distribution. the paper is structured, after section 1, as follows: section 2, it is described the structure of the colombia electricity market. section 3 presents the empirical methodologies, and, in section 4, the dataset is described. in section 5, the results are reported, and section 6 presents the conclusions. 2. colombian electricity market since 1990, the colombian energy sector has presented relevant reforms. garcía et al. (2011) described that the liberalization process allowed an improvement in the electricity market by introducing competition in different sectors, and hence, abolish the limitations of the vertical structure. besides, the wholesale energy market (wem) was created under a regulatory framework, and its operation is through a trade spot structure. however, the electricity sector presents limitations such as a low generation capacity and high demand, which do not allow structuring a competitive market, and electricity prices cannot capture the relationships between the supply and demand (barrientos et al., 2012). on the other hand, colombia is part of a region with a lot of hydric sources. according to international energy agency (iea) statistics, in 2018, approximately 86% of power generation in central and south america was through hydric and thermal generation. therefore, colombia is part of these hydrothermal generation systems, where hydroelectric power generation represents 68% and thermal power generation (gas, coal, and liquid) 31% (figure 1). while, renewable sources do not have a representative value in the power generation matrix (0.21%). due to hydrothermal power generation dependence, the colombian electricity sector presents a high vulnerability by two exogenous factors: el niño–southern oscillation (enso) and energy fossil price fluctuations. figure 2 shows the daily spot price dynamic for the period 2000-2019, and significant effects of enso were observed in four periods during 2003 and 2014; however, the most important shock was observed between 2015 and 2016, where the price reached a maximum peak, and the gas prices increased considerably. besides, the thermal generation sector did not have an economic guaranty to cover the demand1; hence, the state intervened in the market to avoid rationing (botero-duque et al., 2016; montes, 2018). 1 thermal generation is a backup source for hydropower generation in two specific moments: high demand or low water reservoir levels. figure 1: power generation net capacity by technology for january 2020 source: xm information system. oviedo-gómez, et al.: electricity price fundamentals in hydrothermal power generation markets using machine learning and quantile regression analysis international journal of energy economics and policy | vol 11 • issue 5 • 202168 according to castaño and sierra (2012), díaz-contreras et al. (2014), lira et al. (2009), and quintero-quintero and isaza-cuervo (2013), the spot price is related to weather changes, fossil fuels to the thermal power generation, and electricity demand and supply. likewise, power transmission failures, energy policy, or agent strategies are significant. finally, mosquera-lópez et al. (2017b) described that differences in the marginal costs are forwarded into the spot price dynamics and, consequently, increases the risk to agent decision making. 3. methodology two approaches were considered to analyze the fundamentals of the electricity spot price in a hydrothermal power generation market. first, a machine learning approach was used, through a gpr, to fit a multivariable model to predict daily electricity price and validate the importance of variables considered; second, a quantile regression model was fitted to evaluate the effects of these predictors on the electricity price dynamic. 3.1. gaussian process regression models according to rasmussen and williams (2006), and the mathworks (2020), the gpr models are nonparametric kernel-based models of supervised learning, used for regression analysis and probabilistic classification. these models capture uncertainty and allow predictions where the data have unknown distributions. besides, the gpr is a powerful method to perform bayesian inference, and it is much better when the availability of the data is a problem (aye and heyns, 2017; gonzalez-briones et al., 2019). a training set is defined as {(xi,yi);i=1,2,…,n}, where xi∈r d and yi∈r, and have an unknown distribution. based on a linear regression model, a gpr model predicts the response variable by introducing latent variables, f(xi),i=1,2,…,n, from a gaussian process (gp), and explicit basis function, h. a gp is defined by its mean function, m(x), and covariance function, k(x,x’). if {f(x),x∈rd} is a gp, then e(f(x))=m(x) and cov[f(x),f(x’)}=e[{f(x)-m(x)}{f(x’)-m(x’)}]=k(x,x´). therefore, it considers the following model: h x f xt� � � � �� , (1) where f(x)~gp(0,k(x,x´)), i.e. f(x) is zero mean gp with covariance function k(x,x´). besides, h(x) is a set of basis functions that project the input x into a new p-dimensional feature space vector (rp) and β is a px1 dimension vector of basis function coefficients. this is a representation of gpr model and the response variable can be described as: ( )( ) ( ) ( )( )2| , ~ | , .ti i i i i ip y f x x n y h x f xβ σ+ (2) therefore, a gpr model is a probabilistic model. furthermore, the gpr model is nonparametric model because of the observation xi has a latent variable f(xi). the joint distribution of latent variable f(x1),f(x2),f(x3),…,f(xn) in the gpr model is p(f|x)~n(f|0,k(x,x)), close to a linear regression model, where k(x,x) is the covariance function and can be parametrized by a set of kernel parameters, θ. hence, k(x,x’) is written as k(x,x’ |θ) to explicitly indicate the dependence on kernel parameters. 3.1.1. kernel function options the kernel parameters are based on the signal standard deviation σf and the characteristic length scale σl. the characteristic length scales define the distance between the input values xi and response values to become uncorrelated. the standard deviation and the characteristic length scale must be greater than zero, given θ1=logσl and θ2=logσf. the following four built-in kernel function with the same length scale were considered: • rational quadratic kernel k x x r i j f l , ,|� � �� � � � � � � � �� � � �� � 2 2 2 1 2 (3) where σl is the characteristic length scale, α is the positive-valued scale-mixture parameter, and r x x x xi j t i j� �� � �� ���� � � � is the euclidean distance between xi and xj. figure 2: electricity spot price dynamic for the period 2000-2019 source: xm information system. oviedo-gómez, et al.: electricity price fundamentals in hydrothermal power generation markets using machine learning and quantile regression analysis international journal of energy economics and policy | vol 11 • issue 5 • 2021 69 • squared exponential kernel k x x ei j f x x x xi j t i j l , ,|� � � � � � � �� � �� �� � � � � � � � � �2 1 2 2 (4) where σl is the characteristic length scale and σf is the signal standard deviation. • matern 5/2 k x x r r ei j f l l r l, ,|� � � � �� � � � � � � �� � � �� � � � � � � � 2 2 2 5 1 5 5 3 (5) • exponential k x x ei j f r l, ,|� � �� � � � � � � � � � 2 (6) where σl is the characteristic length scale and r is the euclidean distance between xi and xj. 3.1.2. parameter estimation to estimate the parameters β, θ, and σ2 of a gpr model, the likelihood p(y|x) must be maximized as a function of parameters: 2 2 2 , , , , argmax ( | , , , ).ˆ ˆ ˆ logp y x β θ σ β θ σ β θ σ= (7) because, p(y|x,β, θ, σ2)=n(y|hβ,k(x,x|θ)+σ2 in), the marginal log-likelihood function is as follows: ( ) ( ) ( ) ( ) 2 12 2 1 ( | , , , ) 2 , | 2 2 1 log , | , 2 t n n logp y x y h n k x x i y h log k x x i β θ σ β θ σ β π θ σ − = − −  + + − −  − + (8) where, h is the vector of explicit basis functions, and k(x,x│θ) is the covariance function. to estimate the parameters, first, 2ˆ ( , )β θ σ is determined and its estimation is used to compute the β-profiled likelihood. second, the β-profiled log-likelihood is given by 2 2ˆ( | , ( , ) , , )logp y x β θ σ θ σ , where it maximizes the β-profiled log-likelihood over θ, σ2 to find their estimates. finally, during the estimation process, principal component analysis (pca) was applied to avoid multicollinearity and dimensionality problems. 3.1.3. response variable forecast to predict a value of a response variable ynew, given a new input vector xnew, and the training data, it is defined the density p(ynew|y,x,xnew) by conditional probabilities: ( ) ( ) ( ) , | ,| , , . | , new new new new new p y y x x p y y x x p y x x = (9) to find the joint density in the numerator, it is necessary to introduce the latent variables fnew and f corresponding to ynew, and y, respectively. thus, it is possible to use the joint distribution for ynew, y, fnew, and f to compute (9). the gp models assume that each response only depends on the corresponding latent variable fi and the feature vector xi. after we found the density p(ynew|y,x,xnew), the expected value of prediction ynew at a new point xnew, given y, x, and parameters β, θ, σ2 is: ( ) ( )2| , , , , , ( ) , | ,t tnew new new newe y y x x h x k x xβ θ σ β θ α= + (10) where, � � � �� � ��� � ��k x x i y hn, ( )| 2 1 . 3.1.4. performance indicators to check the gpr model performance, different calibration metrics were used such as root mean square error (rmse), r-squared (r2), and mean absolute error (mae). these metrics are described in the following: • rmse ( )2 1 1 ,ˆ n i i i rmse y y n =    = −     ∑ (11) • r2 ( ) ( ) 2 2 1 2 1 ˆ 1 , n i ii n i ii y y r y y = = − = − − ∑ ∑ (12) • mae 1 ,ˆ 1 n i i i mae y y n = = −∑ (13) where n is the number of observations, yi is the i-th observed value, and ˆiy is the i-th predicted value. for rmse and mae lower values are desired, and for r2, a closest value to one shows a better performance. besides, the performance metrics of the estimated gpr model were compared with two supervised learning models: support vector machines (svm) and tree-based methods. the performance metrics are described in the result and discussion section. 3.2. quantile regression approach the quantile regression is a semi-parametric approach, with high flexibility that captures the stochastic relationship between variables, allows consistent estimation in non-gaussian environmental, and requires a minimal distributional assumption on the data generating process (koenker, 2004; ma and koenker, 2006; uribe and guillen, 2020). to describe the quantile regression model, a linear regression model was assumed, where the response variable yi,t represents the electricity spot prices and is related to a set of explanatory variables or fundamentals in a matrix xi,t. following koenker and bassett (1978), the quantile regression model can be written as: oviedo-gómez, et al.: electricity price fundamentals in hydrothermal power generation markets using machine learning and quantile regression analysis international journal of energy economics and policy | vol 11 • issue 5 • 202170 q y x xq i t i t i t i q , , , ' ,|� � � � (17) where, yi,t is a (tx1) vector, with t denoting the number of observations (t=1,2,3,…t). besides, the matrix xi t, ' of dimensions (txd), has (d-1) predictors that also includes a constant, and βq is a (dx1) vector of unknown parameters for each quantile q, q∈(0,1). the regression coefficients ˆ qβ of the quantile q were estimated as a solution to the following minimization problem: ( )' ', , , , 1 1 min [ ], q i t q q i t i t i i t i t i t q i y x y x tβ β β =  − < −  ∑ (18) where, ( ) ' ' , , , , 1 , , 0, q q i t i t i i t i t i y x i y x otherwise β β  < < =   (19) yi,t is defined as in equation (17) and must be computed in separate regressions for each i, i=1,…n. according to mosqueralópez et al. (2017b), and uribe and guillen (2020), the quantile regression is a special case of the least absolute deviation estimator (lad), that allows robust estimations when the data present heavy tails as for electricity spot prices. 4. data the fundamentals of spot price are determined by the generation technologies. for example, in central and south america, the generation is based, principally, on hydroelectric and thermal power sources. in this cases, different studies have described the following determinants: demand, hydrology changes, fossil fuel price variation, investment decisions making, the structure of the transmission system, and agent strategies (barria and rudnick, 2011; barrientos-marín and toro-martínez, 2017; blazsek and hernández, 2018; samudio-carter et al., 2019; vaca et al., 2019; xavier et al., 2016). therefore, the first database contained variables such as (i) total demand: real, commercial, and national interconnected system (nis); (ii) reservoir levels: daily volume in percentage and generation capacity; (iii) climatology factors as quantity of water that fuel reservoirs; and (iv) fuel fossil consumption: gas, coal, fuel oil, and kerosene. on the other hand, variables as the bilateral bidding price, electricity imports/exports, or the price regulatory policies were not selected due to the spot price is contained in their structures or missing observations were identified. according to the variables described, finally, the correlation analysis was used to select the spot price determinants. besides, considering the capacity of generation (figure 1), the volume of water available in the reservoirs and the consumption of fossil fuels from two of the most important sources, gas and coal, were selected. also, nis demand was chosen because this variable is calculated based on the net generation of the plants. these variables were chosen due to they allow the structure of a parsimonious model characterized by describing a classic supply and demand model. the dataset applied in this research represents the market structure and seeks to explain the spot price dynamic. table 1 shows the variables, specifying data source and units. in summary, the database is a balanced panel composed of daily data that starts in august 2009 and ends in december 2019. the period was determined because of the availability of data with no methodological changes, and the current supply scheme for the generation sector is included (creg 051 of 2009, article 10). likewise, 2020 data were not selected because regulated and nonregulated demand decreased by 4.2% and 12.9%, respectively, during the first quarterly by the sars-cov-2 (covid-19) pandemic (vidal et al., 2020).2 table 2 reports summary statistics and unit root test (augmented dickey-fuller adf) of the variables and figure 3 describes their dynamics during the sample period. the spot price presents a high variability and dispersion, especially in the last quartile due to enso effects during 2015 and 2016, where the price increased to 1943 cop$/kwh. then again, the demand has a dynamic growth and shows a correlation of 0.26 with the price, which is positive and weak, despite the demand is a significant price determinant. regarding water volume, it was observed a high variability by seasonal patterns and a negative correlation with price. likewise, gas and coal are sources used to supply the demand when the hydropower system presents any limitation. hence, these variables have a high dispersion in the last quartiles 2. cop is the representative sign of the colombian peso. table 1: data description variable description units source spot price daily electricity spot price cop2$ / kwh xm information system demand total demand with energy losses mw/h xm information system water volume reservoirs capacity for hydropower generation percentage or gw/h xm information system gas gas quantity consumption mbtu xm information system coal coal quantity consumption mbtu xm information system source: au thor’s construction table 2: summary and adf test for selected variables statistical parameters spot price demand water volume (gw/h) gas coal mean 184.47 173571 10527 231712 121932 std. dev. 166.96 18334.57 2122.958 94968.62 71163.86 minimum 35.36 115438 5777 63336 0 25th percentile 97.93 160645 9022 155753 61913 50th percentile 146.88 173729 10712 211287 117501 75th percentile 194.68 188247 12303 289651 174210 maximum 1942.69 217021 14502 543258 356137 spot price correlation 0.23 −0.26 0.45 0.60 t-adf −4.63*** −8.53*** -3.70** −4.10*** −6.06*** ** and *** indicates that null hypothesis of a unit root is rejected at 5% and 1% level, respectively. source: authors’ analysis oviedo-gómez, et al.: electricity price fundamentals in hydrothermal power generation markets using machine learning and quantile regression analysis international journal of energy economics and policy | vol 11 • issue 5 • 2021 71 and a significant and positive correlation with the price. finally, adf test was computed, and the result shows evidence against the presence of unit root in the variables for a 1% and 5% level of confidence. therefore, the variables do not require stationary transformation before the estimation. 4.1. determining, training and testing set for machine learning approach figure 4 summarizes the machine learning methodology through the variable set described. first, the dataset was imported from xm information system, explored, and processed to find their descriptive statistics and identify their characteristics. in general, the variables did not transform, except for the spot prices due to outliers observed during the 2015-2016 period. spot price outliers were filled through the piecewise cubic hermite interpolating polynomial (pchip) to avoid their effects in the prediction process and a possible overfitting. second, a training set is used to train the model, while a validation set is used to evaluate the model performs with the dataset by the performance indicators, and a final test is used to confirm the model specification and identify overfitting. therefore, holdout method was used to divide the dataset into three parts: train (65%), validation (15%), and test (20%) sets3. in this process stage, 3 for train, validation, and test sets, the period august 2009-july 2019 was used. the response of the variables and their predictors were defined. according to the gpr model described in equation (2), we can write it in vector form: ( ) ( )2| , ~ | , ,p y f x n y h f iβ σ+ (20) where, the response variable y is the spot prices and the vector x has the fundamentals: demand, water volume, and gas and coal consumption. third, the best models were identified through performance indicators and the prediction of the daily spot price for the period august 2019-december 2019 was implemented. 4.2. determining quantile regression model based on equation (17), the linear quantile regression model can be written as a function of the response variable and their predictors: q p d w cq i t i q i q t i q t i q t, , , , , ,� � � � � �� � � �1 2 3 4 (21) where, pt is the response variable, spot price, while dt is the demand, wt is water volume, and ct is the total gas and coal consumption. for estimating the quantile regression model, the period august figure 4: summary for machine learning methodology source: authors’ analysis. figure 3: evolution of fundamental variables for august 2009-december 2019. (a) the national interconnected system (nis) demand in mw/h; (b) water volume or reservoir capacity in gw/h; (c) gas consumption for generating in mbtu; (d) coal consumption for generating in mbtu. source: author’s construction. a b dc oviedo-gómez, et al.: electricity price fundamentals in hydrothermal power generation markets using machine learning and quantile regression analysis international journal of energy economics and policy | vol 11 • issue 5 • 202172 2009-december 2019 was used and the natural logarithms were computed to interpret the coefficients as elasticities. 5. empirical results and discussion the main findings are presented below for the variables and timespan selected. first, the machine learning training results and performance metrics are described. then, the daily spot price prediction is shown. second, in this section, the results of the quantile regression analysis are described to identify the effects of the main determinants on the spot price. 5.1. machine learning results the performance of the gpr model fitting is assessed using rmse, r2, and mae metrics4. besides, the gpr model was compared with the support vector machine, which is categorized as a supervised learning method for the application of regression and classification. this method is based on determining hyperplanes that maximize the margin between classes (gao et al., 2008). the following svm kernels were used: • quadratic • cubic • gaussian: fine, medium, and coarse. on the other hand, tree-based methods were considered due to their fast for fitting and prediction, low memory usage, and ease of interpretation. therefore, the models used were: fine, medium, and coarse, for tree regression. besides, the training process is computed through pca. therefore, it was observed that models were estimated through the first two principal components due to these factors explained 98% of the variation of the selected determinants. tables 3-5 describe the metric performance for different fitting models and the kernels selected. based on all performance metrics, the results show that the gpr exponential performs better. in general, good performance was observed for the gpr models because the metrics for the three sets used were similar, in contrast to the svm models that present a significant difference in the rmse between the train and the other two datasets. therefore, this leads us to conclude the possibility of overfitting in the svm models. however, the svm models presented a similar performance in validation and test sets in the mae metric, this could suggest that the models still have a good predictive process. then again, some differences were observed in tree regresion metrics; but the medium and coarse models presented a similar rmse and mae during the train, validation, and test sets. finally, the r2 shows the percentage of the dependent variable variation that explain by the model, but some of these models are not linear, so the use of this indicator may be subject to criticism (díaz et al., 2019). according to barrientos-marín and toro-martínez (2017), another performance indicator is the mean absolute percentage error (mape). this metric describes the relative absolute deviation in 4 rmse and mae metrics value in cop$/mwh. per unit value. for each of the gpr models, the mape is 21%, for svm models, the lowest mape is 21% for fine and medium gaussian kernels through the test dataset. likewise, the coarse for tree regression has a mape equal to 22%. table 4: metrics performance for svm models model’s stages rmse r2 mae kernel: quadratic train 58.19 0.67 39.55 validation 54.66 0.71 37.13 test 54.26 0.67 36.54 kernel: cubic train 53.72 0.72 36.33 validation 48.82 0.76 33.50 test 50.32 0.72 34.29 kernel: gaussian fine train 49.12 0.76 30.38 validation 45.07 0.80 29.76 test 44.94 0.78 28.82 kernel: gaussian medium train 51.09 0.74 33.67 validation 45.87 0.79 31.14 test 46.71 0.76 30.95 kernel: gaussian coarse train 61.33 0.63 39.78 validation 59.12 0.65 38.26 test 56.96 0.64 36.39 source: authors’ analysis table 3: metrics performance for gpr models model’s stages rmse r2 mae kernel: rational quadratic train 47.57 0.78 32.21 validation 43.42 0.81 30.11 test 43.40 0.79 29.48 kernel: squared exponential train 48.20 0.77 32.21 validation 43.52 0.81 30.16 test 43.51 0.79 29.55 kernel: matern 5/2 train 47.82 0.78 32.40 validation 43.43 0.81 30.10 test 43.22 0.79 29.39 kernel: exponential train 44.45 0.81 30.16 validation 43.17 0.82 29.79 test 42.55 0.80 28.94 source: authors’ analysis table 5: metrics performance for tree regressions model’s stages rmse r2 mae fine model train 36.32 0.87 22.96 validation 51.97 0.73 34.76 test 50.37 0.72 33.40 medium model train 43.24 0.82 28.66 validation 43.69 0.79 31.17 test 44.76 0.78 30.82 coarse model train 46.62 0.79 31.19 validation 43.69 0.81 29.65 test 45.99 0.77 30.76 source: authors’ analysis oviedo-gómez, et al.: electricity price fundamentals in hydrothermal power generation markets using machine learning and quantile regression analysis international journal of energy economics and policy | vol 11 • issue 5 • 2021 73 in summary, it was observed better performance metrics for the gpr models, especially the gpr exponential model. these models provide predictions for a given spectrum and a predictive distribution that allows computing the first and second moments: the mean and the standard deviation. likewise, the kernels that provide rankings of the input variables or variance estimation of the data noise. hence, the gpr models offer an alternative for analyzing a variable that presents mean reversion, spikes, and seasonal patterns. therefore, the daily prediction was computed through this model for the period from august 2019 to december 2019 (figure 5). the dynamics of the spot price generated by the selected predictors were observed and it was conclude that the model allows a good approximation for lower prices, i.e., under 250 cop$/kwh. however, the prediction has not reached the true value for high prices, especially during the period from september to november. barrientos-marín and toro-martínez (2017) described for the spanish market, an asymmetry response between the high and low prices. when the price is high, the model does not believe that prices will be higher. likewise, when the price is low, the model is not confident that prices will be lower. therefore, the authors explained that their model could capture the agent behavior, who submit bids with low prices to compete. nevertheless, weron (2014) and ziel (2016) described there is not a standard structure for the electricity markets. hence, it is not possible to make a comparison between markets and performance metrics for machine learning approach. by contrast, the average spot price during july 2019 was 123.57 cop$/kwh, and during october 2019, the price reached an average of 390.4 cop$/kwh. a reduction in hydric sources during august and september could explain the high price increase; however, the water reservoirs had a percentage of 74% and 67% in august and september, respectively. besides, the water reservoir percentage in october and november was approximately 69%. therefore, the generation concentration index or an oligopolistic indicator must be considered because the hydropower generation tries to make speculations when the water sources decrease and, thus, increase the price in the following months (aggarwal et al., 2009; zhang and luh, 2005). 5.2. quantile regression results for estimating the quantile regression model, the complete sample was used: august 2009-december 2019. likewise, the response variable was not transformed by outliers due to quantile regression models are robust to these data and according to uribe and guillen (2020) the financial time series presents crises and booms with high or low observations. figure 6 describes the spot prices’ quantile against the corresponding fraction of data. a low spot price was observed for the lower quantiles, approximately equal to 35 cop$/kwh, and around 147 cop$/kwh for the median price. from the lower to higher quantiles, a smooth increase was identified; however, after 85% quantile, the price presents a sharp peak related to exogenous effects during 2015 and 2016. the linear model described in (21) was estimated for different percentiles of the distribution of electricity prices, i.e. from the 10th to the 90th percentile. furthermore, the gas and coal consumption were added to analyze the proportion of fossil fuel consumption due to these two variables are around 22% of total generation capacity. the main results are summarized in figure 7 and the quantile regression coefficients are presented in the appendix a. 5.2.1. effects of the determinants variables of the electricity spot price for different percentiles 5.2.1.1. demand effects the sensitivity to changes in demand is positive and significant statistically, but its effects vary over the different spot price quantiles. in the 10th percentile, where the price is low, the demand presents a high impact, e.g. for a demand variation of 1%, the price variation is approximately 2%. however, around the 20th to the 50th percentile, the demand impact decreases significantly. for figure 5: electricity spot price daily prediction for august 2019-december 2019. the continues blue line is the real spot price for the sample. the dotted red line is the spot price prediction, and the dotted black lines are the prediction intervals source: authors’ analysis. oviedo-gómez, et al.: electricity price fundamentals in hydrothermal power generation markets using machine learning and quantile regression analysis international journal of energy economics and policy | vol 11 • issue 5 • 202174 figure 6: quantiles for electricity spot price for august 2009 – december 2019. source: authors’ analysis. prices in the 60th and the 80th percentile, the demand tries to stabilize, but for prices over the 80th percentile, the effect associated with variation in demand is lower. therefore, with a demand variation of 1%, the price variation is equal to 1.4%. given the inverse relationship between prices and demand, its impact is less on high quantiles. according to barrientos et al. (2012), barrientos-marín and toro-martínez (2017), and garcía et al. (2011), demand is one of the most relevant spot price determinants. it is concluded that the price has a positive trend in the future by a positive demand shock. however, the effect is higher in the short-term. besides, the price captures the complex effects of supply and demand source: authors’ analysis. figure 7: fundamental variables effects on the electricity spot price for different percentiles. the vertical axis in each subplot corresponds to the spot price response by effects of predictors, while the horizontal axis corresponds to quantiles, from the 10th to the 90th percentile. the dotted black lines represent the quantile regression coefficients and the gray area is the 95% confidence interval. the continuous red line is the linear regression coefficient estimated by ols, and the discontinuous red lines are the 95% confidence intervals. the variables are defined as follows: (a) effects of the intercept; (b) effects of the demand; (c) effects of the water volume or reservoir capacity; (d) effects of the gas and coal consumption for generating ba c d oviedo-gómez, et al.: electricity price fundamentals in hydrothermal power generation markets using machine learning and quantile regression analysis international journal of energy economics and policy | vol 11 • issue 5 • 2021 75 generation plants must turn on, affecting the price. by contrast, the elasticity of the water volume or reservoir capacity is negative, with increased impact on lower and higher quantiles. that is, seasonal patterns of reservoirs cause a strong price fluctuation, e.g., each rainy season, the spot price decrease significantly. an important aspect is the generation sector’s influence on the price by future speculation of water volume; for this reason, it must be added a fundamental that captures the oligopoly structure. positive elasticities were found for fossil fuel consumption. it was revealed how gas and coal increased the price significantly on last quantiles. exogenous effects such as dry seasons or the demand changes, increase the spot price through generation costs. therefore, it has described how the magnitude changes in fundamental variables in a hydrothermal power, explain the electricity spot price. the effect of reservoir changes represents the main risk factor for generators. besides, the generation sector faces risk by fossil fuel price fluctuation; hence, they cannot recover the costs through the electricity price increases. likewise, this study allowed identifying the importance of renewable energy because they can become a smoother of the volatility prices and prevent their extreme changes caused by exogenous effects. finally, to improve the model prediction it will be required the inclusion of generation concentration index or agent strategies. however, the model can serve as a point of reference, given the hydrothermal generation sector characteristic and exogenous factors that explain the electricity price dynamics. references aggarwal, s.k., saini, l.m., kumar, a. (2009), electricity price forecasting in deregulated markets: a review and evaluation. international journal of electrical power and energy systems, 31(1), 13-22. aye, s.a., heyns, p.s. (2017), an integrated gaussian process regression for prediction of remaining useful life of slow speed bearings based on acoustic emission. mechanical systems and signal processing, 84, 485-498. barria, c., rudnick, h. (2011), investment under uncertainty in power generation: integrated electricity prices modeling and real options approach. ieee latin america transactions, 9(5), 785-792. barrientos, j., rodas, e., velilla, e. (2012), modelo para el pronóstico del precio de la energía eléctrica en colombia. lecturas de economía, 77, 91-127. barrientos-marín, j., toro-martínez, m. (2017), análisis de los fundamentales del precio de la energía eléctrica: evidencia empírica para colombia. revista de economía del caribe, 19, 34-63. berrie, t.w., hoyle, m. (1985), treating energy as a commodity. energy policy, 13(6), 506-510. blazsek, s., hernández, h. (2018), analysis of electricity prices for central american countries using dynamic conditional score models. empirical economics, 55(4), 1807-1848. botero-duque, j.p., garcía, j.j., velásquez, h. (2016), efectos del cargo por confiabilidad sobre el precio spot de la energía eléctrica en colombia. cuadernos de economía, 35(68), 491-519. castaño, e., sierra, j. (2012), sobre la existencia de una raíz unitaria en la serie de tiempo mensual del precio de la electricidad en colombia. lecturas de economía, 76, 259-291. activity through the influence of the operational determinants: technological and organizational (díaz-contreras et al., 2014; girish and vijayalakshmi, 2013). 5.2.1.2. water volume effects the elasticity of the water volume is negative and significant statistically, independent of the quantiles. therefore, an increased impact of water volume sensitivity was observed on lower and higher quantiles, i.e. when the water reservoir capacity is high, it always leads to a reduction in the electricity prices. in the first quantile, the price is low by a high water volume. it was observed that a water volume variation of 1% causes a price variation equal to −0.41%. in the last quantiles, the impact is higher because water volume becomes the most important source and an alternative to reduce the spot price when the thermal plants are on. in the 20th-70th percentiles the effects measured by quantile regression are similar to the median effects. hydraulic technology presents lower generation costs than thermal technology. however, hydric sources are high uncertainty to the energy and market reliability. given the seasonal patterns in hydric sources, the electricity spot prices are lower in the rainy season and higher in the dry season (garcía et al., 2011). according to barrientos-marín and toro-martínez (2017) a positive effect on the available hydric capacity causes a negative real price. likewise, hydropower generation depends on the future situation (or not observable); hence, this sector tries to influence on the spot prices. 5.2.1.3. fossil fuel consumption effects positive and significant elasticities were observed for fossil fuel consumption. around the 10th percentile, the effects are minor, but for prices over the 40th percentile, the effects are becoming higher. this means that the thermal plants must turn on by a decrease in water volume or an increase in demand and, as a result, the generation costs and spot prices increase. in the 90th percentile, the price variation is approximate 1.25% when the fossil fuel consumption is 1%. according to mosquera-lópez et al. (2017a), when the thermal generation plants are on, they present marginal costs of up to 300%, higher than hydropower plants. therefore, the marginal generation costs show a relevant difference between the two most important generation technologies, which explains the price fluctuations. 6. conclusions considering the colombian power generation market structure, where hydropower generation is the most relevant source, followed by thermal power technology, a set of market fundamentals was validated through a price prediction using a machine learning trained model. besides, by using quantile regression, the non-linear effects of these variables on the spot price were measured. in the sensitivity analyses for the different variables across the price distribution, it was observed how the demand, the water reservoir capacity, and the fossil fuel consumption influence the price. therefore, positive changes were observed in the spot price through demand variations. when the electricity consumption increases, all generation technologies must produce to meet demand. however, if the demand is not cover, the thermal power oviedo-gómez, et al.: electricity price fundamentals in hydrothermal power generation markets using machine learning and quantile regression analysis international journal of energy economics and policy | vol 11 • issue 5 • 202176 castelli, m., groznik, a., popovič, a. (2020), forecasting electricity prices: a machine learning approach. algorithms, 13(5), 119. ciarreta, a., lagullón, m., zarraga, a. (2011), modelación de los precios en el mercado eléctrico español. cuadernos de economía, 30, 227-250. cotia, b.p., borges, c.l.t., diniz, a.l. (2019), optimization of wind power generation to minimize operation costs in the daily scheduling of hydrothermal systems. international journal of electrical power and energy systems, 113, 539-548. crespo-cuaresma, j., hlouskova, j., kossmeier, s., and obersteiner, m. (2004), forecasting electricity spot-prices using linear univariate time-series models. applied energy, 77(1), 87-106. deng, s., oren, s. (2006), electricity derivatives and risk management. energy, 31(6-7), 940-953. díaz, g., coto, j., gómez-aleixandre, j. (2019), prediction and explanation of the formation of the spanish day-ahead electricity price through machine learning regression. applied energy, 239, 610-625. díaz-contreras, j.a., macías-villalba, g.i., luna-gonzález, e. (2014), estrategia de cobertura con productos derivados para el mercado energético colombiano. estudios gerenciales, 30(130), 55-64. fernández-blanco, r., kavvadias, k., hidalgo gonzález, i. (2017), quantifying the water-power linkage on hydrothermal power systems: a greek case study. applied energy, 203, 240-253. gao, c., bompard, e., napoli, r., wan, q., zhou, j. (2008), bidding strategy with forecast technology based on support vector machine in the electricity market. physica a: statistical mechanics and its applications, 387(15), 3874-3881. garcía, j., gaviria, a., salazar, l. (2011), determinantes del precio de la energía eléctrica en el mercado no regulado en colombia. ciencias estratégicas, 19, 225-246. girish, g.p., vijayalakshmi, s. (2013), determinants of electricity price in competitive power market. international journal of business and management, 8(21), 70-75. gonzalez-briones, a., hernandez, g., corchado, j.m., omatu, s., mohamad, m.s. (2019), machine learning models for electricity consumption forecasting: a review. in: 2019 2nd international conference on computer applications and information security (iccais). p1-6. he, y.x., zhang, s.l., yang, l.y., wang, y.j., wang, j. (2010), economic analysis of coal price-electricity price adjustment in china based on the cge model. energy policy, 38(11), 6629-6637. huisman, r., mahieu, r. (2003), regime jumps in electricity prices. energy economics, 10, 425-434. imani, m.h., bompard, e., colella, p., huang, t. (2020), predictive methods of electricity price: an application to the italian electricity market. in: 2020 ieee international conference on environment and electrical engineering and 2020 ieee industrial and commercial power systems europe (eeeic/i and cps europe). p1-6. kian, a., keyhani, a. (2001), stochastic price modeling of electricity in deregulated energy markets. in: proceedings of the 34th annual hawaii international conference on system sciences. p7. koenker, r. (2004), quantile regression for longitudinal data. journal of multivariate analysis, 91(1), 74-89. koenker, r., bassett, g. (1978), regression quantiles. econometrica, 46(1), 33. lira, f., muñoz, c., núñez, f., cipriano, a. (2009), short-term forecasting of electricity prices in the colombian electricity market. iet generation, transmission and distribution, 3(11), 980-986. ma, l., koenker, r. (2006), quantile regression methods for recursive structural equation models. journal of econometrics, 134(2), 471-506. maciejowska, k. (2020), assessing the impact of renewable energy sources on the electricity price level and variability-a quantile regression approach. energy economics, 85, 104532. mandal, p., senjyu, t., urasaki, n., funabashi, t., srivastava, a.k. (2007), a novel approach to forecast electricity price for pjm using neural network and similar days method. ieee transactions on power systems, 22(4), 2058-2065. montes, c. (2018), la incertidumbre climática y el dilema energético colombiano. revista de la academia colombiana de ciencias exactas, físicas y naturales, 42(165), 392-401. mosquera-lópez, s., manotas-duque, d.f., uribe, j.m. (2017a), risk asymmetries in hydrothermal power generation markets. electric power systems research, 147, 154-164. mosquera-lópez, s., nursimulu, a. (2019), drivers of electricity price dynamics: comparative analysis of spot and futures markets. energy policy, 126, 76-87. mosquera-lópez, s., uribe, j.m., manotas-duque, d.f. (2017b), nonlinear empirical pricing in electricity markets using fundamental weather factors. energy, 139, 594-605. quintero-quintero, m.c., isaza-cuervo, f. (2013), dependencia hidrológica y regulatoria en la formación de precio de la energía en un sistema hidrodominado: caso sistema eléctrico colombiano. revista ingenierías universidad de medellín, 12(22), 85-95. rasmussen, c.e., williams, c.k.i. (2006), gaussian processes for machine learning. united states: mit press. ribeiro, m., stefenon, s., de lima, j., nied, a., mariani, v., coelho, l. (2020), electricity price forecasting based on self-adaptive decomposition and heterogeneous ensemble learning. energies, 13(19), 5190. rodriguez, c.p., anders, g.j. (2004), energy price forecasting in the ontario competitive power system market. ieee transactions on power systems, 19(1), 366-374. samudio-carter, c., vargas, a., albarracín-sánchez, r., lin, j. (2019), mitigation of price spike in unit commitment: a probabilistic approach. energy economics, 80, 1041-1049. the mathworks, inc. (2020), statistics and machine learning toolbox user’s guide. united states: the mathworks, inc. available from: https://www.la.mathworks.com/help/pdf_doc/stats/stats.pdf. uribe, j.m., guillen, m. (2020), quantile regression for cross-sectional and time series data: applications in energy markets using r. berlin: springer international publishing. vaca, j., núñez, g., kido, a. (2019), análisis multisectorial del incremento de precios de la electricidad en la economía de méxico. problemas del desarrollo. revista latinoamericana de economía, 50(196), 167-189. vidal, p., sierra, l., cerón, j. (2020), demanda nacional de energía y crecimiento económico en tiempos de cuarentena. colombia: pontificia univerdiad javeriana. weron, r. (2014), electricity price forecasting: a review of the stateof-the-art with a look into the future. international journal of forecasting, 30(4), 1030-1081. xavier, e.m., pereira, g.m., friedrich, l.r., schneider, l.c., danesi, l.c., borchardt, m. (2016), requirements to leverage the electricity distributors’ sales and revenues in the brazilian free market. ieee latin america transactions, 14(10), 4293-4303. zhang, l., luh, p.b. (2005), neural network-based market clearing price prediction and confidence interval estimation with an improved extended kalman filter method. ieee transactions on power systems, 20(1), 59-66. zhang, y., zhou, q., sun, c., lei, s., liu, y., song, y. (2008), rbf neural network and anfis-based short-term load forecasting approach in real-time price environment. ieee transactions on power systems, 23(3), 853-858. ziel, f. (2016), forecasting electricity spot prices using lasso: on capturing the autoregressive intraday structure. ieee transactions on power systems, 31, 4977-4987. oviedo-gómez, et al.: electricity price fundamentals in hydrothermal power generation markets using machine learning and quantile regression analysis international journal of energy economics and policy | vol 11 • issue 5 • 2021 77 table a.i: quantile regression coefficients for different quantiles predictors β0.1 β0.2 β0.3 β0.4 β0.5 β0.6 β0.7 β0.8 β0.9 intercept −26.857 −27.877 −25.152 −24.142 −22.338 −22.600 −22.521 −21.739 −23.425 demand 1.988 1.941 1.719 1.657 1.491 1.478 1.479 1.439 1.355 water volume −0.412 −0.289 −0.254 −0.275 −0.275 −0.273 −0.319 −0.419 −0.358 fossil fuel consumption 0.899 0.935 0.912 0.912 0.933 0.971 1.005 1.062 1.247 source: authors’ analysis appendix a table a.i shows the quantile regression coefficients from 10th to 90th percentiles. all coefficients are significant statistically for a 1% level of confidence. tx_1~at/tx_2~at international journal of energy economics and policy | h42 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(5), 42-51. selection of large-scale nuclear power plant based on economic and reliability aspects in indonesian power system rizki firmansyah setya budi1, moch. djoko birmano2*, elok satiti amitayani2 1department of electrical and information engineering, gadjah mada university, indonesia; 2center for nuclear energy system. national nuclear energy agency of indonesia, jakarta, indonesia. *email: birmano@batan.go.id received: 22 january 2021 accepted: 28 may 2021 doi: https://doi.org/10.32479/ijeep.11107 abstract choosing the indonesia’s power systems that are suitable with the large-scale nuclear power plant (npp) and the npp’s vendor country are crucial problems faced by indonesian government. therefore, this research analyzes the npp impact on the power system reliability to choose the suitable power systems and the npp economics of each possible vendor country to choose the optimal vendor that provides minimize cost. this research uses two electricity price scenarios: electricity production cost (scenario 1) and adjustment tariff (scenario 2). the results show that only sumatra and java-bali system can be connected with the npp. for both of these systems, japanese npp is not economical to be developed because it provides a levelized unit electricity cost (luec) of 0.116 usd/kwh, which is higher than the electricity prices. meanwhile, chinese and south korean npp is economical to be developed in both systems. for the java-bali system, chinese npp is the best choice in scenario 1 with a luec of 0.036 usd/kwh. in scenario 2, south korean npp that has a luec of 0.058 usd/kwh becomes the best choice because it has better public perception than chinese. for the sumatra system, south korean npp is the best choice in both scenarios. keywords: large-scale npp selection, indonesia power system, reliability, minimize cost, electricity price jel classifications: d21, d22, e39 1. introduction indonesia’s power system is a large power system that is divided into three operating areas, i.e., sumatera, java-bali, and east indonesia (budi et al., 2017). the east indonesia areas consist of kalimantan, sulawesi, papua, and other islands. the installed capacities of each operation area are sumatra 6.5 gw, java-bali 32.5 gwe, and east indonesia 4.4 gw. based on the electricity supply business plan of pt. pln 2017-2026, by 2026, the forecast of installed capacity in each area is sumatra 25.6 gwe, java-bali 70.5 gwe, and east indonesia 16.5 gwe. the total installed capacity will reach 112.6 gw in 2026. this leads to the need for optimal utilization of all energy sources by considering the aspects of reliability and economics. indonesia’s power plants are dominated by fossil power plants that have high co2 emissions (dutu, 2016). also, the power generation sector is the second-largest co2 contributor, so co2 reduction in this sector will have a significant impact (hejazi, 2017). and in some regions, oil power plants that depend on oil imports still dominated (silberglitt and kimmel, 2015; handayani et al., 2017). these conditions make the indonesia energy security index (esi) low. indonesia esi rank is 55th from 71 countries with an esi value of 0.475 (erahman et al., 2016). it is certain that a sufficient, economical, and environmentally friendly energy supply is needed to improve the esi. the new and renewable energy (nre) especially nuclear can be one of the most attractive options to supply indonesia’s electricity demand in the future due to low co2 emissions and nuclear can generate enormous amounts of energy (hejazi, 2017; prăvălie and bandoc, 2018; kumar, 2016). by using nuclear energy, esi can be increased and it has a direct impact on energy adequacy and this journal is licensed under a creative commons attribution 4.0 international license budi, et al.: selection of large-scale nuclear power plant based on economic and reliability aspects in indonesian power system international journal of energy economics and policy | vol 11 • issue 5 • 2021 43 economic growth (bakirtas and akpolat 2018). also, indonesia has the most advance progress on nuclear power infrastructure development, has the highest public acceptance in southeast asia, and has a lot of experience in operating a nuclear research reactor (putra, 2017). from 2010 to 2016, public acceptance showed a positive trend from year to year and reached 77.53% in 2016 (batan, 2017). from 77.53% of respondents who accepted npp, the reasons why they accepted npp are that npp increases power system reliability and npp decreases electricity price in indonesia. from 22.47% who declined npp development, the reason why they declined is that they are worried about a nuclear accident and radioactive contamination (batan, 2017). based on those reasons, we can conclude three important points that great effect on npp development, i.e., economy, reliability, and safety. the indonesian government should concern about those points to make a successful npp project. some research mentioned that npp was a favorable power plant to utilize in indonesia (budi et al., 2011, aritonang et al., 2018, pioro and duffey, 2015). in addition, based on indonesia’s national energy policy (nep), the opportunity for utilization of npp to realize the target of the nre portion is widely open (jaelani et al., 2017; khairunnisa et al., 2017). therefore, an npp study on reliability and economy is needed. the reliability analysis is needed because the npp capacity is big enough to disrupt the reliability system while the economic analysis is needed because the npp has a massive investment cost. research (budi et al., 2015) has performed an analysis on improving the lolp index in the bangka power system. the research’s results showed that using npp was necessary to improve the lolp. while in research (nuryanti et al., 2014), it was conducted an economic analysis of the small-medium reactor (smr) by using levelized unit electricity cost (luec). the analysis was conducted using 3 models, i.e., puslitbang pln model, mini g4econs model, and levelized cost model. the research results showed that the luec was not much different between the three models, which were 14.59 (puslitbang pln model), 15.06 (mini g4econs), and 14.24 (levelized cost) cents usd/kwh. other research has conducted an economic analysis on smr with varying investment costs (nasrullah, 2014). the research’s results showed the luec of smr was ranging from 9.31 cents usd/ kwh up to 19.07 cents usd/kwh. the economic analysis of npp has been done not only in smr but also in large-scale npp (nasrullah and sriyana, 2010). in addition, some research included uncertainty factor to the economic analysis of large scale npp (nuryanti et al., 2012). research showed that large-scale npp gave lower luec than smr. it showed that large-scale npp was more economical and suitable to be developed in indonesia than smr (budi et al., 2015; nuryanti et al., 2014; nasrullah, 2014; nasrullah and sriyana 2010; nuryanti et al., 2012). but the calculation in research (budi et al., 2015; nuryanti et al., 2014; nasrullah, 2014; nasrullah and sriyana, 2010; nuryanti et al., 2012) used old data. while the npp investment cost increases in line with escalation, inflation, and improvement of safety system specifications (oecd, 2015), the old data will make imprecise calculations because the data is different from factual data. therefore, a research conducting an economic analysis of large-scale npp based on factual data and indonesia’s condition is needed. many previous studies have discussed the reliability and the economics of npp. but none of them discussed the power systems in indonesia that can be connected to large-scale npp and the vendor country that potentially can build the npp. choosing the proper power system that can be connected to the npp is an important factor in supporting the government policy on nuclear energy development. based on the report (oecd, 2015), there are 10 vendor countries in the world. the economic analysis is needed to help the indonesian government to choose the npp vendor country. therefore, this research conducted reliability and economic analysis of large-scale npp. this research analyzed the impact of large-scale npp operation on the system reliability and analyzed the economics of large-scale npp by using the latest data based on indonesia’s condition. reliability analysis was used as a constraint for npp location. if in the reliability analysis, npp caused the lolp index greater than its standard, the npp will not be developed and will not need the economic analysis. in other words, reliability analysis determined the npp location. the location determined the electricity tariff that used in the economic calculation of large-scale npp. this was because based on minister of energy and mineral resources’s (moemr) decision no. 1404 k/20/mem/2017, each region in indonesia had different electricity production costs. for the economic analysis, this research used 1000 mwe npp from china, south korea, and japan as reference power plants. based on the economic analysis results, the npp of specific country feasible to be developed in indonesia power systems was obtained. the purposes of this research are to determine the power system in indonesia that can be connected to large-scale npp and to determine the npp vendor country. the research’s results can be used as a stakeholder’s consideration in deciding the nuclear energy policy in indonesia. by using this research’s result, the indonesian government can choose where they will build npp and from which country the npp comes from. 2. research method this research was conducted using a method as shown in figure 1. this research was started with making a problem formulation of large-scale npp effect to each indonesia power system reliability. the detailed problem formulation was explained in the subchapter problem formulation. from the subchapter, it was got a lolp index when large-scale npp connected to the power system and it can be known that the system is still reliable or not when it is connected with the npp. budi, et al.: selection of large-scale nuclear power plant based on economic and reliability aspects in indonesian power system international journal of energy economics and policy | vol 11 • issue 5 • 202144 to ensure the quality of service, pt. pln applied lolp index <0.274% as a reliability standard (budi et al., 2017). lolp <0.274% means the maximum number of the system allowed to not supply is 1 day/year. based on those values, we conclude that the power system can be connected to the npp or not. if the npp made the lolp index equal to or more than 0.274%, the power system was not reliable to be connected with the npp and the economic analysis of npp was not done. if the lolp index remains below 0.274%, the power system was still reliable when it is connected to the npp, and we continued the process with its economic analysis. the detailed problem formulation of the npp economic analysis discussed in the subchapter problem formulation. the npp used as reference plants is 1000 mwe npp originating from china, south korea, and japan. the countries are selected based on a recommendation from the international atomic energy agency, i.e., a country that will build its first npp should do an affiliation with npp vendor countries in their regional area and they are major nuclear states (nian, 2018). the discount rate used was 10% by considering the inflation rate in indonesia was around 6-7% and risk margin around 3-4%. 2.1. problem formulation of large-scale npp effect on the power system reliability the analysis of the large-scale npp effect on the reliability was done by replacing the biggest power plant at each power system with the npp. the replacement was done each year starting from 2017 until 2026, so it can be known the impact of npp on the system reliability at each power system in each year. the impact can be known from the lolp index. lolp is a reliability index based on the probabilistic method (yu et al., 2019). the calculation of the lolp index that is used to analyze the large-scale npp effect to the power system was conducted by using the matlab program and followed flowchart as shown in figure 2. collecting the power systems data (installed capacity and for) and load data (peak load and ldc) was the first step of the lolp index calculation. the installed capacity and load data were typically for each indonesia’s power system. indonesia’s power system divided into three operational areas, i.e., sumatra, javabali, and east indonesia. each area divided into several regions. the sumatra area consists of only one region, i.e., sumatra region. the java-bali area consists of only one region, i.e., javabali region. the east indonesia area consists of 3 regions, i.e., kalimantan, sulawesi nusa tenggara, and maluku papua region (budi et al., 2017). 2.1.1. sumatra region sumatra region currently consists of 2 interconnection systems, 2 isolated systems that have peak loads above 50 mwe, and some isolated systems that have peak loads below 10 mwe. the two interconnection systems are sumbagut and sumbagselteng power systems. both systems will be interconnected in 2022 and become the sumatra system. the isolated systems that have peak loads above 50 mwe are bangka and tanjung pinang. in 2017, the sumbagut system had power plant capacity 2.8 gw and peak load 2.3 gw, while the sumbagselteng system has power plant capacity 4.1 gw and peak load 3.6 gw. in 2026, sumatra system which is an interconnection of sumbagut and sumbagselteng will have power plant capacity 25.6 gw and peak load 15 gw. in addition, the ldc of the sumatera power system is shown in figure 3. the ldc data was obtained from pt. pln. 2.1.2. java-bali region java-bali region consists of 1 interconnection power system, i.e., the java-bali system. in 2017, the system had a peak load of 26.6 gw and it becomes 49.9 gw in 2026. while the power plant capacity is 33.9 gw in 2017 and becomes 70.5 gw in 2026. in addition, the ldc of java bali is shown in figure 4. the ldc data was obtained from pt. pln. 2.1.3. kalimantan region kalimantan region consists of two power systems, i.e., kalbar system and kalseltengtimra system. until 2026, there has been no plan to interconnect the systems. in 2017, the kalbar system had power plant capacity 0.64 gw and a peak load of 0.38 gw, while the kalseltengtimra system has power plant capacity 1.71 gw and a peak load of 1.26 gw. in 2026, the kalbar system will have power plant capacity 1.58 gw and a peak load of 1.06 gw, while the kalseltengtimra system will have power plant capacity 5.92 gw and peak load 3.39 gw. in addition, the ldc of the no yes problem formulation of large-scale npp effect on the power system reliability the power system cannot be connected to large-scale npp lolp index < 0.274% problem formulation of large-scale npp economic analysis figure 1: research’s flowchart stop no yes set year = 2017 read power plant data (installed capacity and forced outage rate (for)) and tload data (peak load and load duration curve (ldc)) from each power system capacity outage probability table (copt) calculation calculation of lolp index year = year +1 year < 2027 figure 2: lolp calculation’s flowchart budi, et al.: selection of large-scale nuclear power plant based on economic and reliability aspects in indonesian power system international journal of energy economics and policy | vol 11 • issue 5 • 2021 45 kalimantan region is shown in figure 5. the ldc data was obtained from pt. pln. 2.1.4. sulawesi nusa tenggara region sulawesi nusa tenggara region consists of sulbagut, sulbagsel, lombok, and timor system. the systems have not yet planned to be interconnected by pt. pln due to small peak load and archipelago area. the largest system in the region is sulbagsel. the system will have power plant capacity 5.57 gw and a peak load of 3.94 gw in 2026. 2.1.5. maluku papua region maluku papua region consists of ambon and jayapura systems. both systems are small. in 2026, power plant capacity will reach 0.25 gw in ambon and 0.39 gw in jayapura. the ldc of sulawesi nusatenggara and maluku papua region is shown in figure 6. the ldc data was got from pt. pln. the installed capacity and load data were typical for each indonesia’s power system. while for is assumed to have the same value for each plant with the same technology all over indonesia. table 1 shows the for for each power plant in indonesia. after getting the data, the next step was the copt calculation. the calculation can be done by using a traditional method (budi et al., 2015; budi et al., 2017) or recursive method (widiastuti et al., 2017). by considering the effectiveness, this research used the recursive method. the calculation using the recursive method is shown in equation (1) (widiastuti et al., 2017; marko, 2019). p(x)=(1–u) p’ (x) + u p’ (x–c) (1) where: x = capacity outage (mwe) c = new capacity that has been added (mwe) p(x) = cumulative probability when the outage is x mwe after a power plant c mwe is added p’(x) = cumulative probability when the outage is x mwe before a power plant c mwe is added u = forced outage rate (for) (%) by using the copt and ldc, the lolp index can be calculated using equation (2). equation (2) means that the lolp index is calculated by summing the value of all possibility outage that makes the demand not being able to be supplied by the system (sarjiya et al., 2019; adefarati et al., 2017). lolp p t x n x x� � � 0 � (2) where n = maximum number of capacity outage (mwe) px = cumulative probability of power plant when the outage is x mwe (%) tx = load loss duration when the outage is x mwe (hours) 2.2. problem formulation of large-scale npp economic analysis large-scale npp economic analysis was done by the following flowchart as shown in figure 7. the economic analysis was done if the lolp of the power system was <0.274%. if the lolp was equal or larger than 0.274%, it could be concluded that the power system cannot be connected to the npp. the economic parameters used in the economic analysis were investment cost, o & m cost, fuel cost, and external cost (samadi, 2017; lovering et al., 2016; qvist and brook, 2015). the parameters were almost the same as those used in largescale npp, the differences lay on the structure of fuel cost and decommissioning cost. the decommissioning cost can be included in the external cost. contingency cost is an additional cost that must be prepared to accommodate the possibility of uncertainties and risks in the project (ortiz et al., 2019; traynor and mahmoodian, 2019). 0.0 0.2 0.4 0.6 0.8 1.0 1 38 2 76 3 11 44 15 25 19 06 22 87 26 68 30 49 34 30 38 11 41 92 45 73 49 54 53 35 57 16 60 97 64 78 68 59 72 40 76 21 80 02 83 83 l oa d (p u) hour figure 4: ldc of java bali region 0.0 0.2 0.4 0.6 0.8 1.0 1 33 8 67 5 10 12 13 49 16 86 20 23 23 60 26 97 30 34 33 71 37 08 40 45 43 82 47 19 50 56 53 93 57 30 60 67 64 04 67 41 70 78 74 15 77 52 80 89 84 26 l oa d (p u) hour figure 3: ldc of sumatra region 0.0 0.2 0.4 0.6 0.8 1.0 1 36 6 73 1 10 96 14 61 18 26 21 91 25 56 29 21 32 86 36 51 40 16 43 81 47 46 51 11 54 76 58 41 62 06 65 71 69 36 73 01 76 66 80 31 83 96 lo ad (p u) hour figure 5: ldc of kalimantan region table 1: for value of power plants in indonesia powerplant for nuclear power plant 0.015 coal power plant 0.05 combined cycle power plant 0.023 gas power plant 0.023 hydro power plant 0.03 geothermal power plant 0.03 diesel power plant 0.09 budi, et al.: selection of large-scale nuclear power plant based on economic and reliability aspects in indonesian power system international journal of energy economics and policy | vol 11 • issue 5 • 202146 in this research. contingency cost was not included in other costs but was separated. contingency cost simply calculated by adding some percent of oc to the value of oc, i.e., 20% (zhang et al., 2019). the value of contingency cost has a range between 5% and 25% of oc. this research used 20% of oc as a contingency cost. 2.2.1. o & m cost o & m cost is divided into two kinds, namely variable o & m cost and fixed o & m cost (cebulla and jacobson, 2018). fixed o & m cost is a routine operational cost that includes employee cost, property tax, plant insurance, and life-cycle maintenance. life-cycle maintenance cost includes back-end cost and decommissioning cost. the decommissioning cost is treated as an o & m cost by setting aside a sum of money each year from the beginning of npp operating until the end of npp’s lifetime. the same treatment is also done for back-end costs. variable o & m cost is a cost that depends on the production function of the npp includes consumables materials. 2.2.2. fuel cost nuclear fuel cost consists of front-end cost and back-end cost (ganda et al., 2016). front-end cost is a cost associated with fuel processes before used in a reactor. front-end cost consists of uranium purchase cost, conversion cost, enrichment cost, and fabrication cost. back-end cost is a cost associated with fuel processes after used in the reactor. the back-end cost is determined by the type of fuel cycle that used, whether open cycle or closed cycle. on a closed cycle, the back-end cost includes all costs after the fuel is used in the reactor to the reprocessing cost. while on an open cycle, the back-end cost consists of all costs after the fuel is used in the reactor to the ultimate dispossal (kim et al., 2015). this research used an open cycle based on a consideration that natural uranium prices still lower than the reprocessing cost. back-end costs in this research were interim storage cost and ultimate disposal cost. 2.2.3. decommissioning cost decommissioning cost represents the amount of money that must be allocated yearly from the first operating year of npp. the money is accumulated as a reserve fund for the npp decommissioning at the end of the operation (khattak et al., 2018; torp and klakegg, 2016). a study has been calculated decommissioning cost of npp in indonesia (pt.pln, 2013). the calculated decommissioning cost is 0.17-0.2 cents usd/kwh. while the decommissioning cost of npp in the usa is between 0.1 and 0.2 cents usd/kwh, while the average decommissioning cost in europe is 0.4 cents euro/kwh (moore et al., 2017). another study showed that the decommissioning cost of npp is varied depending on the investment cost and the vendor country (oecd, 2015). the study (pt.pln, 2013) used atmea and ap1000 as a reference power plant. atmea manufactured by a joint venture of mitsubishi heavy industry-areva and has overnight costs between 6261 and 6396 usd/kwe. ap1000 manufactured by westinghouse owned by toshiba japan and has overnight costs between 5840 and 6111 usd/kwe. while this research used reference plants from china, south korea, and japan that have different overnight costs. therefore, we assumed the decommissioning cost for this research was 0.1 usd cent/kwh. by using the economic parameters, we calculated the luec and irr. the luec calculation was done by using equation (3) (wna, 2017). the data used in the luec calculation was shown in table 2. luec � � � � �� � �� � � � t t t t t t t t t t c xcap o f d xe r e r ( ) (( ) ) 1 1 (3) table 2: main parameters used in luec (oecd, 2015; pt.pln, 2013; moore et al., 2017) parameter npp south korea jepang china construction (year) 6 6 6 capacity (mwe) 1343 1152 1080 disc. rate 10% 10% 10% npp lifetime (year) 60 60 60 overnight cost (us$/kw) 2021 3883 1087 fuel price (cent us$/kwh) 0.467 0.467 0.467 waste management (cent us$// kwh) 0.1 0.1 0.1 o&m cost (cent us$//kwh) 0.965 0.65 0.274 decommissioning cost (cent us$//kwh) 0.1 0.1 0.1 capacity factor 90% 90% 90% own use 5% 5% 5% 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1 36 6 73 1 10 96 14 61 18 26 21 91 25 56 29 21 32 86 36 51 40 16 43 81 47 46 51 11 54 76 58 41 62 06 65 71 69 36 73 01 76 66 80 31 83 96 l oa d (p u) hour figure 6: ldc of sulawesi nusatenggara and maluku papua region read lolp index for each power system lolp<0.274% read npp’s economic parameters levelized unit electricity cost (luec) calculation internal rate of return (irr) calculation luec and irr analysis the power system cannot be connected to npp large scale figure 7: flowchart of large-scale npp economic analysis budi, et al.: selection of large-scale nuclear power plant based on economic and reliability aspects in indonesian power system international journal of energy economics and policy | vol 11 • issue 5 • 2021 47 where: cap = capacity (mwe) ct = overnight cost in year t (usd/kwe) ot = o & m cost in year t (usd/kwh) ft = fuel cost in year t (usd/kwh) dt = decommissioning costs in year t (usd/kwh) et = electricity power generated in year t (kwh) r = discount rate (%) net present value (npv) and internal rate of return (irr) can be known by using the luec and the electricity sale price. the value of npv and irr will indicate whether the npp is profitable to use or not. npv is a difference of total income to the total outcome by considering the time value of money. npv calculation was done by using equation 3. r is a discount rate. irr is the rate of capital return. the function of irr is to measure the rate of return on investment by considering the time value of money. irr is obtained when the npv value is equal to zero. the r-value when npv is zero is the irr value. equation (4) was used to calculate npv and equation (5) was used to calculate irr. revenue was obtained from electrical power that sold multiplied by electricity price. the electricity that sold is the generated electric minus own use. npv revenue r cost r xe x price t t t t t t t � �� � � �� � � � � � � � � � � � � � 1 1 0 95 1 . rr c xcap o f d xe rt t t t t t t� � � � � � �� � � � � � � � � � ( ) (( ) ) 1 (4) npv = 0 t t t t t t t t t xe x price irr c xcap o f d xe irr � �� � � � � � �� � � � 0 95 1 1 . ( ) (( ) ) �� � � � � � � 0 (5) where: revenuet = revenue at year t (usd) costt = cost at year t (usd) r = discount rate (%) et = electricity power generated in year t (kwh) price = electricity price (cent usd/kwh) cap = capacity (mwe) ct = overnight cost in year t (usd/kwe) ot = o & m cost in year t (usd/kwh) ft = fuel cost in year t (usd/kwh) dt = decommissioning costs in year t (usd/kwh) npv net present value (usd) irr = internal rate of return (%) this research used 2 electricity price scenarios. scenario 1 used each regional electricity production cost as the electricity price. scenario 2 used the pln adjustment tariff as the electricity price. the scenarios affected the value of npv and irr. table 3 shows the electricity production cost of each region and the pln adjustment tariff. 3. results and discussion large-scale npp has capacity 1000 mwe. the capacity is too large for some power systems in indonesia. in addition, npp 1000 mwe has relatively expensive investment costs. the capacity and investment cost will affect the power system reliability and economic feasibility. this research has analyzed the effect of large-scale npp on reliability and economic analysis. based on the reliability analysis, it can be obtained results as shown in table 4. the red color in table 4 shows that the lolp index exceeds the standard. large-scale npp makes the sumbagut and sumbagselteng unreliable (lolp ≥0.274%). in 2022, both systems will be interconnected so the status becomes not available (na). sumatra system is a new system that is an interconnection between sumbagut and sumbagselteng systems. the sumatra system will be formed in 2022, so the status becomes na before 2022. largescale npp can be connected to the sumatra system without makes the lolp index exceeding the standard because the power plant installed capacity is large. the npp cannot be connected to sumbagut and sumbagselteng because the installed capacity is not too large for npp 1000 mwe. the installed capacity will become 7238 mwe for sumbagut and 8256 mwe for sumbagselteng in 2021 while the installed capacity of the sumatra system will reach 17,807 mwe in 2022. these results are in accordance with the planning that has been done by pt.pln. in the planning, the largest power plant added by pt.pln is 500 mwe for the sumbagut system and 600 mwe for the sumbagselteng system. as for the sumatra system, the largest capacity added is 1000 mwe. for sumbagut and sumbagselteng system, there is a possibility to connect the systems with npp that has a capacity of fewer than 600 mwe (small-medium reactor = smr) because of pt.pln has been planned to add a coal power plant 600 mwe. the pt. pln’s plan shows that a power plant with capacity 600 mwe did not make the reliability out of standard. but it needs research that calculates the impact of smr on the reliability index of the power system to prove the possibility. besides the reliability analysis, the implementation of smr will change the economic feasibility because smr relatively more expensive than large-scale npp. those problems are beyond this research problem. in the java-bali region, large-scale npp can be connected to the power system. this is indicated by the lolp index. the lolp index is still in the pln standard. java-bali system is a power table 3: electricity production cost of each region and the pln adjustment tariff based on moemr regulations region elec. prod. cost (cent usd/kwh) tarif adjust. pln (cent usd/kwh) sumatra 8.98 11.28 java-bali 6.52 11.28 kalimantan 10.31 11.28 sulawesi nusatenggara 10.68 11.28 maluku papua 15.09 11.28 budi, et al.: selection of large-scale nuclear power plant based on economic and reliability aspects in indonesian power system international journal of energy economics and policy | vol 11 • issue 5 • 202148 system that has installed capacity 33.89 gw in 2017 so the npp does not cause the lolp index out of the standard. this is in accordance with the pt. pln planning has added a 1000 mwe power plant that has the same capacity as large-scale npp into the java-bali system. npp cannot connect to the systems in other regions. the npp will cause the lolp index out from the standard because the capacity of the systems is not too big. this is in accordance with the planning of pt. pln which used 450 mwe as the largest power plant to be added to the systems. smr that has a capacity of fewer than 450 mwe. to prove the possibility, it needs future research on reliability and economic analysis of smr as an alternative of npp large scale. based on the reliability analysis. it can be seen that only two power systems in indonesia that can be connected to the npp 1000 mwe. the systems are sumatra and java-bali. the sumatra system will able to be connected with the npp starting in 2022, while for javabali starting in 2017. by using the construction time 6 years, the fastest time of npp to be operated is in 2027. the economic analysis was performed in sumatra and javabali system. the electricity sale price used for the analysis were electricity production cost of each system and the pln adjustment tariff. the electricity production cost in the sumatra system is 0.0898 usd/kwh. the electricity production cost in java-bali is 0.0652 usd/kwh. while the pln adjustment tariff is 0.1128 usd/kwh. figure 8 shows the comparison of the luec of npp 1000 mwe of the three countries in java bali. npp 1000 mwe from south korea and china are economically feasible to use in the java-bali power system. this is indicated by the luec that is smaller than the electricity production cost and the adjustment tariff. npp 1000 mwe from japan is not economically feasible to use in the java-bali system because the luec is higher than the electricity production cost and the adjustment tariff. if the japanese npp will be built in java-bali systems, then a subsidy ta bl e 4: t he e ffe ct o f l ar ge -s ca le n p p on th e l o l p in de x on e ac h po w er y ea r su m at ra r eg io n ja va -b al i r eg io n k al im an ta n re gi on su la w es i n us a te ng ga ra r eg io n m al uk u p ap ua r eg io n su m ba gu t su m ba gs el te ng su m at er a ja w ab al i k al ba r k al se lt en gt im ra su lb ag ut su lb ag se l l om bo k t im or a m bo n ja ya pu ra 20 17 ≥0 .2 74 % ≥0 .2 74 % n a <0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % 20 18 ≥0 .2 74 % ≥0 .2 74 % n a <0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % 20 19 ≥0 .2 74 % ≥0 .2 74 % n a <0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % 20 20 ≥0 .2 74 % ≥0 .2 74 % n a <0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % 20 21 ≥0 .2 74 % ≥0 .2 74 % n a <0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % 20 22 n a n a <0 .2 74 % <0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % 20 23 n a n a <0 .2 74 % <0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % 20 24 n a n a <0 .2 74 % <0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % 20 25 n a n a <0 .2 74 % <0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % 20 26 n a n a <0 .2 74 % <0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % ≥0 .2 74 % 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 japan south korea china $/ kw h deco mmission in g c ost fuel c ost o&m c ost overnigh t co st electricity cost produ ctio n of java bali adjustment tariff figure 8: comparison of npp’s luec on each country to the electricity production cost and adjustment tariff in java bali budi, et al.: selection of large-scale nuclear power plant based on economic and reliability aspects in indonesian power system international journal of energy economics and policy | vol 11 • issue 5 • 2021 49 is needed to cover the difference between the luec and the electricity price. the higher luec of japanese npp is caused by the overnight cost (oc). the oc of japanese npp is greater than npp from south korea and china. the oc of japanese npp is almost 2 times higher than npp from south korea and 3.5 times higher than npp from china. the difference in oc is due to differences in labor wage, experience, licensing, regulation and npp specifications of each country (nasrullah and sriyana, 2010). japan which is in the ring of fire will make their npp more resistant to an earthquake that causes the oc increases. the oc increment will have a major impact on npp luec because oc has the largest portion in luec. oc has a 70% portion of luec in japanese npp, 72% portion of luec in south korean npp, and 64% portion of luec in chinese npp. the south korean and chinese npp is economically feasible to use in the java-bali system. by looking at the npv and irr values, it can be known the economic feasibility. table 5 shows the value of npv and irr of south korean and chinese npp for 2 types of the electricity sale price. south korean and chinese npp provides a benefit. it can be known by looking at their luec and npv. in scenario 1 (electricity production cost as electricity sale price), south korean npp provides only a small profit margin (irr 11.4% and npv 467.6 million usd). the irr is almost closer to the discount rate. it will make the feasibility more vulnerable to the changes in economic conditions. the changing of the economic condition will affect the discount rate. if the discount rate increases, the irr will decrease and makes the irr lower than the discount rate. the lower irr will make npv becomes minus while the chinese npp provides irr 19% and npv 1,503.6 million usd. the chinese npp is a promising npp to be developed in the javabali system. however, it is necessary to consider again the risks of a public perception who think that chinese technology has poor quality. the perception is building from the fact that many products from china have poor quality. the perception is also supported by many power plant accidents in indonesia which show that many chinese power plants in indonesia have poor performance and poor quality (pt pjbs, 2015). the perception can make public acceptance low and public acceptance is an important key to the npp development in indonesia. by using chinese npp, we need more effort to keep public acceptance high and to change the perception of chinese technology. when the adjustment tariff is used as the electricity sale price, south korean and chinese npp provides higher irr dan npv. the irr for south korean npp is 18.9% and 28.8% for chinese npp. in this condition, both npp is equally profitable to be developed in the java-bali system. south korean provides a lower irr than the chinese. but the public perception of south korean technology is much better than chinese technology. economic analysis in the sumatra system has been done by using 2 scenarios. figure 9 shows the comparison of the luec of npp 1000 mwe of the three countries in the sumatra system. npp 1000 mwe from south korea and china are economically feasible to use in the sumatra because the luec is smaller than the electricity production cost and the adjustment tariff. npp 1000 mwe from japan is not economically feasible to use in the java-bali system because the luec is higher than the electricity production cost and the adjustment tariff. if the japanese npp will be built in java-bali systems, then a subsidy is needed to cover the difference between the luec and the electricity price. electricity production cost in sumatra is higher than java-bali because there are many oil-fueled power plants in the sumatra system. with higher-production cost, south korean npp will provide a greater profit. table 6 shows a comparison of npv and irr of south korea and china npp based on 2 scenarios in the sumatra system. whether using the electricity production cost or adjustment tariff, south korean and chinese npp will give profit with an acceptable margin. south korean npp will give npv 1999 million usd and irr 15.6% when using electricity production cost scenarios. chinese npp will give npv 2735.1 million usd 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 japan south korea china $/ kw h deco mmission in g c ost fuel c ost o&m c ost overnigh t co st electricity cost produ ctio n of sumatera adjustment tariff figure 9: comparison of npp’s luec on each country to the electricity production cost and adjustment tariff in sumatra table 6: npv and irr of south korean and chinese npp in sumatra project feasibility parameter south korea china elec. cost prod. adjust. tariff elec. cost prod. adjust. tariff npv (106 usd) 1999.0 3433.6 2735.1 3888.8 irr (%) 15.6 18.9 24.5 28.8 table 5: npv and irr of south korean and chinese npp in java-bali project feasibility parameter south korea china elect. cost prod. adjust. tariff elec. cost prod. adjust. tariff npv (106 usd) 467.6 3433.6 1503.6 3888.8 irr (%) 11.4 18.9 19.0 28.8 budi, et al.: selection of large-scale nuclear power plant based on economic and reliability aspects in indonesian power system international journal of energy economics and policy | vol 11 • issue 5 • 202150 and irr 24.5% when using the electricity production cost scenario. when used adjustment tariff as electricity sale price, south korean npp will give npv 3433.6 million usd and irr 18.9%, while chinese npp gives npv 3888.8 million usd and irr 28.8%. public acceptance is an important factor in nuclear energy development in indonesia (wang and kim, 2018; sugiawan and managi, 2019; zhu et al., 2018; bisconti, 2018). the acceptance has a linear correlation with the public perception of technology. so the public perception is important, especially in a sensitive matter such as nuclear energy (yuan et al., 2017). based on indonesia’s public acceptance, the most reason why people disagree to develop npp is a safety factor. report (pt. pjbs, 2015) show that chinese power plant in indonesia has poor quality, especially in safety factor. by considering people’s perception of chinese technology, indonesia’s public acceptance, and historical data of chinese power plants in indonesia, south korean npp is a better choice than chinese npp to be developed in the sumatra system. although the npv and irr are less than chinese, the risk of public acceptance will be smaller. 4. conclusion and policy implications sumatra and java-bali systems are the power system that can be connected to large-scale npp. sumatra system can be connected starting in 2022 and the java-bali system can be connected starting in 2017. japanese npp is not economically feasible to be developed in sumatra and java-bali systems. chinese and south korean npp are economically feasible to be developed in both systems. for the java-bali system, chinese npp is the best choice when using electricity production cost as electricity sale price because it gives an acceptable margin of profit, while south korean npp just gives a slight profit margin so it’s more vulnerable to the economic situation. when used adjustment tariff as electricity sale price, south korean npp gives an acceptable profit margin and becomes the best choice. although south korean npp gives less npv and irr, public perception is better than chinese technology. for the sumatra system, south korean npp is the best choice when using electricity production cost or adjustment tariff as the electricity sale price. although south korean npp gives less npv and irr. the public perception of south korean technology is better than chinese technology. 5. acknowledgment the authors would like to thank the staff of the infrastructure division for providing the data. references adefarati, t., bansal, r.c., justo, j.j. (2017), reliability and economic evaluation of a microgrid power system. energy procedia, 142, 43-48. aritonang, s., parlina, n., kuntjoro, y.d. (2018), government strategy to improve public acceptance toward nuclear power plant. jurnal pertahanan, 4(1), 61-75. bakirtas, t., akpolat, a.g. (2018), the relationship between energy consumption, urbanization, and economic growth in new emergingmarket countries. energy, 147, 110-121. batan. (2017), survei jajak pendapat iptek nuklir tahun 2016. bisconti, a.s. (2018), changing public attitudes toward nuclear energy. progress in nuclear energy, 102, 103-113. budi, r.f.s., birmano, m.d., bastori, i. (2017), pemodelan perhitungan indeks lost of load probability untuk n unit pembangkit pada sistem kelistrikan opsi nuklir. jurnal pengembangan energi nuklir, 19(2), 61-68. budi, r.f.s., sarjiya, s., hadi, s.p. (2017), a review of potential method for optimization of power plant expansion planning in jawa-madurabali electricity system. communications in science and technology, 2(1), 29-36. budi, r.f.s., suparman, amitayani, e.s. (2015), peran pltn dalam meningkatkan indeks keandalan lost of load probability (lolp) sistem kelistrikan bangka. in: seminar nasional xi sdm teknologi nuklir. p169-179. budi, r.f.s., suparman, salimy, d.h. (2011), the analysis of co2 emission at the study of electricity generation development planning with nuclear option for bangka belitung region. jurnal pengembangan energi nuklir, 13(1), 44-55. cebulla, f., jacobson, m.z. (2018), carbon emissions and costs associated with subsidizing new york nuclear instead of replacing it with renewables. journal of cleaner production, 205, 884-894. dutu, r. (2016), challenges and policies in indonesia’s energy sector. energy policy, 98, 513-519. erahman, q.f., purwanto, w.w., sudibandriyo, m., hidayatno, a. (2016), an assessment of indonesia’s energy security index and comparison with seventy countries. energy, 111, 364-376. ganda, f., dixon, b., hoffman, e., kim, t.k., taiwo, t., wigeland, r. (2016), economic analysis of complex nuclear fuel cycles with necost. nuclear technology, 193(2), 219-233. handayani, k., krozer, y., filatova, t. (2017), trade-offs between electri fi cation and climate change mitigation: an analysis of the java-bali power system in indonesia. applied energy, 208, 1020-1037. hejazi, r. (2017), nuclear energy: sense or nonsense for environmental challenges. international journal of sustainable built environment, 6(2), 693-700. jaelani, a., firdaus, s., jumena, j. (2017), renewable energy policy in indonesia: the qur’anic scientific signals in islamic economics perspective. international journal of energy economics and policy, 7(4), 193-204. khairunnisa, n.f., hasanuddin, u., maskun, m., hasanuddin, u. (2017), indonesian implementation of nuclear energy for sustainable development. journal of law, policy and globalization, 67. 102-109. khattak, m.a., omran, a.a.b., khan, m.s., ali, h.m., nawaz, s., khan, z. (2018), cost evaluation of proposed decommissioning plan of candu reactor. journal of engineering science and technology, 13(10), 3173-3189. kim, s.k., ko, w.i., youn, s.r., gao, r.x. (2015), nuclear fuel cycle cost estimation and sensitivity analysis of unit costs on the basis of an equilibrium model. nuclear engineering and technology, 47, 306-314. kumar, s. (2016), assessment of renewables for energy security and carbon mitigation in southeast asia: the case of indonesia and thailand. applied energy, 163, 63-70. lovering, j.r., yip, a., nordhaus, t. (2016), historical construction costs of global nuclear power reactors. energy policy, 91, 371-382. marko, č. (2019), evaluation of the power system reliability if a budi, et al.: selection of large-scale nuclear power plant based on economic and reliability aspects in indonesian power system international journal of energy economics and policy | vol 11 • issue 5 • 2021 51 nuclear power plant is replaced with wind power plants. reliability engineering and system safety, 185, 455-464. moore, m., korinny, a., shropshire, d., sadhankar, r. (2017), benchmarking of nuclear economics tools. annals of nuclear energy, 103, 122-129. nasrullah, m. (2014), perhitungan ekonomi dan pendanaan pltn smr 100 mwe. in: seminar nasional teknologi energi nuklir. p107-116. nasrullah, m., sriyana, s. (2010), harga dan tarif listrik pltn di dunia. jurnal pengembangan energi nuklir, 12(1), 20-30. nian, v. (2018), technology perspectives from 1950 to 2100 and policy implications for the global nuclear power industry. progress in nuclear energy, 105, 83-98. nuryanti, n., hidayanto, a., suparman, s., muslim, e., moeis, a.o. (2012), analisis probabilistik pada perhitungan biaya pembangkitan listrik teraras pltn. jurnal pengembangan energi nuklir, 14(1), 23-33. nuryanti, n., nasrullah, m., suparman, s. (2014), studi komparasi model perhitungan biaya pembangkitan listrik teraras pltn. jurnal pengembangan energi nuklir, 16(2), 95-105. oecd. (2015), projected costs of generating electricity. paris, france: oecd. ortiz, j.i., pellicer, e., molenaar, k.r. (2019), determining contingencies in the management of construction projects. project management journal, 50(2), 226-242. pioro, i., duffey, r. (2015), nuclear power as a basis for future electricity generation. journal of nuclear engineering and radiation science, 1(1), 1-19. prăvălie, r., bandoc, g. (2018), nuclear energy: between global electricity demand, worldwide decarbonisation imperativeness, and planetary environmental implications. journal of environmental management, 209, 81-92. pt pembangkitan jawa bali services. (2015), pt pembangkitan jawa bali services annual report 2014. pt.pln, japc, lapi-itb. (2013), feasibility study for bangka nuclear power plant project-non site aspect. putra, n.a. (2017), the dynamics of nuclear energy among asean member states. energy procedia, 143, 585-590. qvist, s.a., brook, b.w. (2015), potential for worldwide displacement of fossil-fuel electricity by nuclear energy in three decades based on extrapolation of regional deployment data. plos one, 10(5), 1-10. samadi, s. (2017), the social costs of electricity generation-categorising different types of costs and evaluating their respective relevance. energies, 10(356), 1-37. sarjiya, budi, r.f.s., hadi, s.p. (2019), game theory for multi-objective and multi-period framework generation expansion planning in deregulated markets. energy, 174, 323-330. silberglitt, r., kimmel, s. (2015), energy scenarios for southeast asia. technological forecasting and social change, 101, 251-262. sugiawan, y., managi, s. (2019), public acceptance of nuclear power plants in indonesia: portraying the role of a multilevel governance system. energy strategy reviews, 26, 100427. torp, o., klakegg, o. (2016), challenges in cost estimation under uncertainty-a case study of the decommissioning of barsebäck nuclear power plant. administrative sciences, 6(4), 14. traynor, b.a., mahmoodian, m. (2019), time and cost contingency management using monte carlo simulation. australian journal of civil engineering, 17(1), 11-18. wang, j., kim, s. (2018), comparative analysis of public attitudes toward nuclear power energy across 27 european countries by applying the multilevel model. sustainability, 10(5), 1-21. widiastuti, a.n., sarjiya, s., pinanditho, k.a., prastyo, e.t. (2017), evaluasi keandalan perencanaan pembangkit wilayah jawa-bali dengan mempertimbangkan ketidakpastian peramalan beban. jurnal nasional teknik elektro dan teknologi informasi, 6(2), 230-234. world nuclear association. (2017), nuclear power economics-nuclear energy costs. available from: http://www.world-nuclear.org/ information-library/economic-aspects/economics-of-nuclear-power. aspx. [last accessed on 2017 oct 12]. yu, h.h., chang, k.h., hsu, h.w., cuckler, r. (2019), a monte carlo simulation-based decision support system for reliability analysis of taiwan’s power system: framework and empirical study. energy, 178, 252-262. yuan, x., zuo, j., ma, r., wang, y. (2017), how would social acceptance affect nuclear power development? a study from china. journal of cleaner production, 163, 179-186. zhang, d., liu, g., chen, c., zhang, y., hao, y., casazza, m. (2019), medium-to-long-term coupled strategies for energy efficiency and greenhouse gas emissions reduction in beijing (china), energy policy, 127, 350-360. zhu, w., lu, s., huang, z., zeng, j., wei, j. (2018), study on public acceptance of nuclear power plants: evidence from china. human and ecological risk assessment, 1(1), 1-17. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 5 • 2021112 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(5), 112-120. investigating growth-energy-emissions trilemma in south asia bosede ngozi adeleye1,2,3*, darlington akam4, nasiru inuwa5, muftau olarinde6, victoria okafor1,3, ifeoluwa ogunrinola1,3, paul adekola1,3 1department of economics and development studies, covenant university, nigeria; 2regional centre of expertise (rce) ogun, nigeria; 3centre for economic policy and development research (cepder), covenant university, nigeria; 4department of economics, university of lagos, nigeria; 5department of economics, gombe state university, nigeria; 6department of economics, uthman dan fodio university, nigeria. *email: ngozi.adeleye@covenantuniversity.edu.ng received: 04 january 2021 accepted: 28 may 2021 doi: https://doi.org/10.32479/ijeep.11054 abstract this paper situates the 2030 united nations sustainable development goals (sdgs) 7, 8, and 13 to investigate the growth-energy-emissions trilemma. it uniquely contributes to the discourse by using carbon emissions per capita (emissions), gdp per capita (economic growth), energy use per capita (nonrenewable energy) and renewable energy from seven south asian countries covering 1990 to 2019 to determine the effect of economic growth and energy use on emissions and if its interaction with either energy variant enhances or dims the effect of energy on emissions. consistent findings from panel-corrected standard errors (pcse), feasible generalized least squares (fgls) and bootstrapping ordinary least squares (bols) reveal that: (1) economic growth intensifies emissions, (2) renewable energy exhibit emissions-reducing properties; (3) nonrenewable energy intensifies emissions, (4) economic growth sustains the emissions-reducing impact of renewable energy; and (5) economic growth diminishes the harmful effect of nonrenewable energy. given these, we submit that the interaction of economic growth enables the “good” effect of renewable energy. at the same time, it reduces the “bad” effect nonrenewable energy on carbon emissions. these outcomes engender a new line of argument that the extent of economic growth cuts carbon emissions level. therefore, economic growth is an essential determinant of carbon emissions. policy implications discussed. keywords: carbon emissions, economic growth, nonrenewable energy, renewable energy, south asia jel classifications: c52, o40, o55, q40, q50 1. introduction this study fills a lacuna in the literature by interrogating the growth-energy-emissions trilemma. it presents some empirical discoveries which provoke a new perspective and highlights findings on whether economic growth ameliorates the impact of energy (renewable and nonrenewable) consumption on carbon emissions. that is, does the interaction of economic growth with either energy variant accelerates or diminishes the level of carbon emissions? conclusions reveal, among other things, that renewable energy attenuates carbon emissions while economic growth and nonrenewable energy intensify emissions, the interaction of economic growth strengthens the “good” effect of renewable energy. at the same time, it slows the “bad” effect of nonrenewable energy. the complementary role of economic growth demonstrates that it is an essential determinant of emissions. these are significant incursions to the growth-energy-emissions discourse which justify engaging in this study – especially, from a crossregional perspective. importantly, the drive to maintain a sustainable environment necessitated the 2030 united nations sustainable development goal (sdg) 13 agenda, which is to “take urgent action to combat climate change and its impacts.” therefore, to address climate change, it becomes imperative to understand its contributing factors: one of which is carbon dioxide (co2) emissions. this study positions on south asia for three reasons: (1) pollution, (2) economic growth, and (3) energy demand. from united nations (2019), in contrast to pakistan, the economic conditions in bangladesh, bhutan and india are mostly positive with positive gdp growth projections. lastly, this journal is licensed under a creative commons attribution 4.0 international license adeleye, et al.: investigating growth-energy-emissions trilemma in south asia international journal of energy economics and policy | vol 11 • issue 5 • 2021 113 energy demand is higher in asia and projected to double between 2018 and 2050, making it both the largest and fastest-growing region in the world for energy consumption (eia, 2019). besides, india is one of the world’s fastest-growing economies during much of the past decade, and they remain primary contributors to future growth in world energy demand (iea, 2019b; 2019a). to address the lacuna in the growth-energy-emissions literature, this study attempts to answer two questions: (1) does economic growth, renewable and nonrenewable energy individually influence emissions? (2) does the interaction of growth and energy (renewable and nonrenewable) exacerbate or weaken emissions? to answer these questions, an unbalanced panel data of per capita gdp (a proxy for economic growth), renewable energy per capita, nonrenewable energy use, and carbon emissions per capita from seven selected south asian1 countries (bangladesh, bhutan, india, maldives, nepal, pakistan, and sri lanka) spanning 1990–2019 is used to investigate if energy and economic growth contribute to carbon emissions. similar to shahbaz et al. (2016), this paper further differs from previous studies on south asian countries (see sharma et al. (2014), uddin and wadud (2014), pandey and mishra (2016), osmani (2018), rahman et al. (2020)) by strictly engaging a trivariate model to analyze the relationship. the empirical investigation employs the praise-winsten panel-corrected standard errors (pcse), feasible generalized least squares (fgls) and bootstrapping ordinary least squares (ols). the results, for the most part, align with previous studies. however, the novel contribution is that economic growth does not dampen the “good” impact of renewable energy on carbon emissions such that the emissions-reducing effect of renewable energy is sustained. at the same time, it reduces the harmful impact of nonrenewable energy. the rest of the paper is structured as follows: section 2 reviews the empirical literature; section 3 outlines the data and empirical model; section 4 discusses the results, and section 5 concludes with policy recommendations. 2. brief literature review rising environmental degradation has gained the attention of policymakers across the world with climate change constituting one of the sustainable development goals (sgd) as sdg13. the drive towards economic growth and development of most nations seems to be putting the planet at risk in severe ways. (afridi et al., 2019) noted that the key contributor to environmental degradation is human activities. these human activities, however, geared towards enhancing the standard of living and economic growth enables urbanization and with urbanization, comes an increase in consumption and demand for energy (adedoyin et al., 2020). some studies like (chikaraishi et al., 2015); and (xu et al., 2018) concluded that energy usage encourages modernization and smart cities while other studies like (zhang et al., 2015) opined that economic development increases energy consumption. (li and lin, 2015), on the other hand, reported that energy use and environmental degradation have a varying relationship at the initial stage of economic development proxied by urbanization. 1 afghanistan is excluded due to lack of data on nonrenewable energy. arguments revolving around the carbon emission-growth relationship is currently ongoing with no consensus on the nature of their relationship. the results of uddin and wadud (2014) after employing vector autoregressive analysis (var) estimation technique on a panel data set of seven south asian countries showed that growth-emission has a positive and significant relationship. similarly, (saidi and hammami, 2015) pointed out that carbon emission increases with economic growth for 58 countries across four continents based on the generalized method of moments (gmm) analysis. the study by (pandey and mishra, 2016) on how economic growth is affected by carbon emission performed cointegration analysis on panel data of south asian countries equally proved that economic growth increases carbon emission and not the other way round as observed for south asian countries as well. (hasnisah et al., 2019) established that carbon emissions and economic growth exhibited a long-run relationship from the dynamic and fully modified ordinary least squares techniques. efforts to ensure that carbon emissions are reduced in the world led to the alternative sourcing of renewable energy. (pimentel et al., 2002), established that renewable energy presents an alternative option for the united states of america to meet the future energy needs of her population by half approximately without compromising the national security of the country. 2.1. carbon emissions and renewable energy since environmental challenges are rising as a result of increasing carbon emissions from the conventional energy source, more attention is given to renewable energy. (adams and nsiah, 2019) noted that renewable energy resource availability makes it a preferred source of energy consumption as proposed by the united nations in sdg 7 mainly as it emits less carbon compared to the traditional source of energy. (hasnisah et al., 2019) while engaging carbon dioxide, per capita gdp, fossil fuels and renewable energy concluded that for 13 asian countries, renewable energy had no significant impact on the quality of the environment. contrarily, (abolhosseini et al., 2014) on the study of 15 european union countries revealed that renewable energy sources led to a decrease in carbon emissions. the disparity in outcomes could be as a result of the diverse regions having different levels of energy consumption. more so, the population density of asian countries is higher than that of europe, thereby affecting human activities in regards to energy consumption. furthermore, (nguyen and kakinaka, 2019) examined the relationship between renewable energy, nonrenewable energy, carbon emissions, real oil prices and economic growth. the result revealed that in low-income countries, renewable energy consumption and carbon emissions exhibit a positive relationship. likewise, (wahid et al., 2018) performed the granger causality test in an attempt to determine the direction of causality between carbon emissions, renewable energy and economic growth for malaysia and indonesia. the outcomes showed that renewable energy causes economic growth and carbon emissions for indonesia. in contrast, for malaysia, renewable energy and economic growth have a unidirectional causal relation from renewable energy to economic growth. it was observed that the availability of a variety of renewable resources in malaysia might be responsible for this result. (pata, 2018) used urbanization, financial development, adeleye, et al.: investigating growth-energy-emissions trilemma in south asia international journal of energy economics and policy | vol 11 • issue 5 • 2021114 carbon emission per capita, income, hydropower consumption, total renewable energy per capita and alternative energy variable to explain the income-emission relationship in turkey. findings showed that the inverted u-shaped environmental kuznets curve (ekc) hypothesis holds for turkey, and total renewable energy has no effect on carbon emissions. on the other hand, (al-mulali et al., 2016) examined the role of renewable energy on environmental pollution for seven regions namely east asia, western europe, east europe and central asia, the americas, south asia, sub-saharan africa and the middle east and north africa. the findings of the study revealed that a long-run relationship exists among all the variables employed, which included carbon emissions, urbanization, trade openness, gdp, financial development and renewable energy consumption. furthermore, the result indicates that renewable energy reduced carbon emission for all regions except sub-saharan africa, where ekc cannot be confirmed and the variables are statistically not significant. 2.2. carbon emissions and income per capita according to (pandey and mishra, 2016), the core of the ekc is that carbon emissions is determined by income. however, this hypothesis is protested on the basis that carbon emissions mostly occurs at the production stage; hence, carbon emission is expected to determine growth (per capita income). in other words, (pandey and mishra, 2016) discovered that per capita income encouraged carbon emission, not the other way round. similarly, (osabuohien et al., 2014) after carrying out panel cointegration for 50 african countries ranging from the year 1995 to 2010, discovered that the existence of long-run equilibrium relationship among the variables used. additionally, ekc inverted u shape was verified in the emissions-income relationship implying that per capita income tends to increase enough beyond the threshold to bring about a reduction of carbon emissions eventually. furthermore, the study by (aye and edoja, 2017), showed the existence of unidirectional causality from gdp per capita to carbon emission for 10 out of the 31 african countries used in the analysis. the ten countries consisted of a mixture of low income and middle-income countries. using threshold analysis with the pegging of gdp per capita threshold at 0.93 per cent, countries below the threshold are classified as low-income. in contrast, those above are classified as high-income countries. the outcomes revealed that for low growth regime, gdp per capita had a positive effect on co2 emission and vice versa in high growth regime. the result of (asumadu-sarkodie and owusu, 2017) contradicts how per capita income responds to carbon emission after employing the ardl bounds test to examine the existence of a long-run relationship between gdp per capita and carbon emission for rwanda. findings showed that in the long-run, a percentage increase in gdp per capita led to a 1.45 per cent decrease in carbon emissions which confirms the existence of a long-run relationship among the variables. however, the granger causality test did not establish any directional relationship between carbon emission and gdp per capita. (adu and denkyirah, 2017) tested the environmental kuznets curve hypothesis for west african countries in the same income category (lower middle-income) and how economic growth influenced ecological degradation in these countries by employing a panel data analysis from 1970 to 2013. the study analyzed the relationship among environmental degradation measured by carbon emissions, combustible renewable waste, economic growth measured by per capita income, and other determinants such as trade openness, population density, and official exchange rate using the fixed effect and random effect models. the results showed that gdp per capita had a positive impact on co2 emissions and was statistically significant at 1% and 5% significance levels. the study, therefore, concluded that while per capita income increased carbon emissions in the short-run, it did not decrease environmental degradation in the long run. hence, the ekc hypothesis does not exist in west africa in the long run, and pollution does not decrease as income increases. however, empirical findings on single country analyses like that of nigeria (ejuvbekpokpo, 2014; ali et al., 2016; egbetokun et al., 2020) yielded conflicting results. while (ejuvbekpokpo, 2014) employed the use of ordinary least squares (ols) estimation technique to determine the impact of carbon emissions on economic growth and discovered that carbon emissions negatively impacted growth, (ali et al., 2016) modelled carbon emissions as a function of the urban population, income, trade openness and energy consumption using the ardl approach. it showed that urban population, although positive, has no significant impact on carbon emissions whereas, income measured by gdp and energy consumption are both statistically significant. (egbetokun et al., 2020) on the other hand, measured environmental pollution with six distinct variables – carbon dioxide, nitrous oxide, suspended particular matter (spm), total greenhouse (tgh) emissions, temperature and rainfall. these variables are modelled individually and showed that the ekc hypothesis was applicable in nigeria but not for all pollution variables. another single country empirical literature from west africa on how income per capita impacted on carbon emissions was carried out by (twerefou et al., 2016) that attempted to verify the ekc hypothesis for ghana. it was observed that the ekc hypothesis does not apply in ghana, given that the long-run estimates indicated a negative yet significant relationship between carbon emissions and income per capita after a long-run relationship was detected. this suggested that as per capita income increases, carbon emissions increase. the result of this study corresponds with that of (sarkodie and strezov, 2018) that equally rejected the existence of ekc hypothesis for ghana in the empirical study to establish ekc hypothesis for ghana, china, australia and the united states of america. (ali et al., 2017) found ekc present in the long-run for malaysia after carrying out a study using ardl bounds testing technique to determine if a long-run relationship existed between real gdp per capita, trade openness, financial development, foreign direct investment (fdi) and carbon dioxide emissions. the study showed that per capita gdp and trade openness caused a significant increase in carbon emissions. similarly, the ekc hypothesis was discovered in some oecd countries after (churchill et al., 2018) employed panel data cointegration techniques for 20 oecd countries from 1870 adeleye, et al.: investigating growth-energy-emissions trilemma in south asia international journal of energy economics and policy | vol 11 • issue 5 • 2021 115 to 2014. the carbon emissions per capita, which represented environmental indicator, gdp per capita as well as its squared, financial development measured by broad money to gdp, trade and population were the variables considered in the study. using the pooled mean group (pmg) estimator, the study noted that in the long-run, the effect of per capita income on environmental degradation gradually increased. the robustness of the study can be due to the coverage of over 145 years. (apergis, 2016) examined the validity of the ekc hypothesis by analyzing the income-emissions relationship for 15 oecd countries using a panel data time-varying fully modified ols and quantile cointegration approach from 1960 to 2013. the quantile cointegration approach validated the ekc hypothesis for 12 of the countries studied. the results also showed that the link between income per capita and carbon emissions per capita for most of the countries is nonlinear. also, (afridi et al., 2019) examined income-emissions relationship for the south asian countries from 1980 to 2016 while also testing the ekc hypothesis. using the generalized least squares (gls) verified that ekc exhibits an n-shaped relationship. for space, table 1 details the summary of selected and additional literature on carbon emissions, renewable energy consumption and per capita income. 3. data, model, and empirical approach 3.1. data and sources the study scope covers seven south asian countries (bangladesh, bhutan, india, maldives, nepal, pakistan, and sri lanka) from 1990 to 2019. afghanistan is dropped due to a lack of data on table 1: summary of literature review authors period methodology results abolhosseini et al. (2014) 1995–2010 panel data estimation positive relationship between carbon emission and gdp per capita ejuvbekpokpo (2014) 1980–2010 ordinary least squares carbon emission adversely affect economic growth osabuohien et al. (2014) 1995–2010 panel cointegration estimation techniques existence of inverted-u ekc curve, long-run equilibrium relationship among the variables uddin and wadud (2014) 1972–2012 vector autoregressive analysis long-run equilibrium relationship present. gdp → co2 al-mulali et al. (2016) 1980–2010 non-stationary panel cointegration technique, dols, vecm and granger causality long-run relationship among the variables in all the 7 regions, ekc hypothesis, cannot be confirmed in africa. renewable energy reduced carbon emission in all regions except africa ali et al. (2016) 1971–2011 ardl cointegration technique long-run equilibrium relationship among the variables, ec→co2 apergis (2016) 1960–2013 panel data time-varying, fully modified ols and quantile cointegration approach validated ekc hypothesis for 12 out of 15 countries. per capita income and carbon emissions exhibited a nonlinear relationship pandey and mishra (2016) 1972–2010 panel vector error correction model and panel cointegration analysis gdp per capita → co2 twerefou et al. (2016) 1970–2010 ardl bounds testing presence of long-run equilibrium relationship among the variables. non-existence of ekc hypothesis in ghana aye and edoja (2017) 1971–2013 dynamic threshold model and panel causality test estimated gdp threshold to be 0.93% gdp→ co2 adu and denkyirah (2017) 1970–2013 panel data fixed effect and random effect model ekc does not exist in the long run in west african countries. per capita income does not decrease environmental degradation in the long run ali et al. (2017) 1971–2012 ardl cointegration technique the presence of ekc in malaysia, per capita income, significantly causes environmental pollution churchill et al. (2018) 1870–2014 panel cointegration estimate techniques ekc holds for 9 out of 20 countries oecd countries pata (2018) 1974–2014 ardl bounds testing, gregoryhansen and hatemi-j cointegration tests. inverted u ekc hypothesis was validated for turkey wahid et al. (2018) 1980–2011 johansen cointegration and granger causality test long-run relationship among the variables. indonesia re → co2, re → gdp, malaysia, ec→ co2, re →gdp, gdp → re afridi et al. (2019) 1972–2010 gls estimation technique, granger causality tests bi-directional causality between co2 and income per capita. long-run relationship between the variables hasnisah et al. (2019) 1980–2014 fmols and dols foss → co2, gdp → co2, ekc hypothesis validated nguyen and kakinaka (2019) 1990–2013 panel data cointegration, fmols and dols rec → co (low-income countries), rec → gdp (high-income countries), nrec → gdp and y (high and low income egbetokun et al. (2020) 1971–2010 ekc model, ardl cointegration and ecm the presence of ekc for a selected measure of environmental pollution in nigeria. long-run equilibrium relationship among the variables adeleye, et al.: investigating growth-energy-emissions trilemma in south asia international journal of energy economics and policy | vol 11 • issue 5 • 2021116 table 3: summary statistics variables full sample bangladesh bhutan india mean sd mean sd mean sd mean sd co2pc 0.79 0.64 0.29 0.12 0.73 0.38 1.14 0.34 pc 1879.99 1968.55 692.16 254.88 1672.92 791.87 1140.21 486.81 renw 3.65 1.27 3.96 0.23 4.52 0.03 3.87 0.16 enu 375.69 144.31 162.94 34.28 277.92 101.09 453.58 86.80 variables maldives nepal pakistan sri lanka mean sd mean sd mean sd mean sd co2pc 1.86 0.78 0.14 0.07 0.81 0.12 0.56 0.22 pc 6604.67 1072.67 536.90 145.78 926.71 136.87 2366.88 929.02 renw 0.66 0.51 4.50 0.03 3.91 0.08 4.16 0.09 enu 701.35 274.98 344.74 35.27 450.60 26.72 421.02 69.06 source: authors' computations. co2pc=carbon dioxide emissions per capita; pc=gdp per capita; renw=renewable energy; enu=energy consumption per capita table 2: correlation matrix variables lnco2pc lnpc lnrenw lnenu lnco2pc 1.000 lnpc 0.779*** 1.000 lnrenw −0.614*** −0.759*** 1.000 lnenu 0.619*** 0.617*** −0.343*** 1.000 source: authors' computations. ***indicate statistical significance at the 1% level; co2pc=carbon dioxide emissions per capita; pc=gdp per capita; renw=renewable energy; enu=energy consumption per capita. energy per capita. carbon emissions (co2pc) is the dependent variables measured in metric tonnes per capita. the explanatory variables are share of renewable energy (renw) in total final energy consumption measured as percentages of total energy consumption, gross domestic product per capita (pc) measured by gross domestic product divided by the population is the proxy for economic growth and total energy used (enu) proxy by kilogram of oil equivalent per capita energy. lastly, interaction terms of per capita income and renewable energy (pc*renw) and per capita income and nonrenewable energy (pc*enu) are included to address the study questions. all the variables are sourced from world bank (2019) world development indicators. table 2 details the relative association (correlation matrix) among the variables. from table 2, all the explanatory variables show significant associations at the 1% level with carbon emissions. while both per capita income and energy use are positively associated, renewable energy reveals a negative relationship. the statistical properties of the variables are displayed in table 3. the sample average for co2pc is 0.79 and the standard deviation of 0.64 reveals that the countries hover around the sample average. that is, there are not many differences in the level of carbon emissions per country. the standard deviation of 1968.55 for pc indicates a wide dispersion from the sample average of us$1879.99. also, the average value of renw is 3.65, and the standard deviation of 1.27 shows the countries are within the sample mean. lastly, enu has a mean value of 375.69 and a standard deviation of 144.31 evidencing greater dispersion from the sample mean. comparatively, maldives shows to have the highest statistics for carbon emissions (1.86), per capita income (us$6,604.67), and energy use (701.35) while bhutan marginally edges nepal to earn the highest renewable energy per average (4.52). 3.2. model specification and estimation techniques to address the first objective about the impact of economic growth, renewable and nonrenewable energy on carbon emissions, the relation specifies carbon emissions (co2pc) as a linear function of per capita income (pc), renewable (renw) and nonrenewable energy (enu) expressed thus: 0 1 2 3ln 2 ln ln ln it it it it itco pc pc renw enu dψ ψ ψ ψ+= +++ (1) where the variables are as defined in section 3.1; ψi are the parameters to be estimated; i=1….n represents the number of cross-sections, t is the period; dit is the general error is the general error terms. on a priori expectations, economic growth and nonrenewable energy consumption have positive relationships with carbon emissions. in contrast, renewable energy exerts a declining relation to emissions as higher consumption of cleaner energy lowers the level of carbon emissions. (nguyen and kakinaka, 2019; destek and sinha, 2020; nathaniel et al., 2020b). similarly, to address the second and third objectives on whether the impact of energy (renewable and nonrenewable) on carbon emissions is bolstered or hampered by economic growth, this paper adopts the methodical approach of adeleye et al. (2020) and adeleye and eboagu (2019). the growth-energy relation is indicated by the interaction of pc with each of renw and enu, and the explicit models are specified as: 0 1 2 3 4 ln 2 ln ln ln ln( * ) it it it it it it co pc pc renw enu pc renw e + + =γ +γ γ γ γ ++ (2) 0 1 2 2 4 ln 2 ln ln ln ln( * ) it it it it it it co pc pc renw renw pc enu v + + =ϕ +ϕ ϕ ϕ ϕ ++ (3) where γi and φt are the parameters to be estimated; eit and vit are the general error terms. to evaluate the overall impact of renw on co2pc, the first differential of equation [2] is derived as: 2 4 ln 2 ln ln co pc pc renw ∂ = γ + γ ∂ (4) adeleye, et al.: investigating growth-energy-emissions trilemma in south asia international journal of energy economics and policy | vol 11 • issue 5 • 2021 117 and from equation [3], the total effect of enu on co2pc is derived as: � � � � ln ln ln co pc enu pc 2 3 4 � � (5) note, the signs of the coefficients of the interaction terms, γ4 and φ4 evaluate if the interaction of renw and enu with pc enhances or distorts the impact of either energy variant on co2pc. also, given that γ2 is expected to be negative, if γ4<0 then pc enhances the “good” effect of renw on co2pc. however, if γ4>0 it indicates that pc distorts the “good” effect of renw. however, if the positive sign of γ4 is less than the negative sign of γ2, it implies that the destabilizing impact of pc is not sufficient to deter the “good” effect of renw on co2pc. on the contrary, if the positive sign of γ4 exceeds the negative sign of γ2, then pc eliminates the “good” impact of renw on co2pc. correspondingly, since φ3 is expected to be positive if φ4>0 then pc worsens the “bad” effect of enu on co2pc. however, if φ4<0 it shows that pc reduces the “bad” effect of enu. however, if the negative sign of φ4 is less than the positive sign of φ3, then the improving-impact of pc is not sufficient to eliminate the “bad” effect of enu. on the contrary, if the negative sign of φ4 exceeds the positive sign of φ3, then pc eliminates the “bad” impact of enu on co2pc. finally, if γ4,φ4=0 it is an indication that the interaction of both variables with pc has no significant impact on co2pc. in the event of cross-sectional dependence in the data and cointegration among the variables, the prais-winsten regression model with panel-corrected standard errors (pcse) which also controls for heteroscedasticity and serial correlation is used to estimate equations [1] and [2]. for robustness checks and to observe the consistency of the results, we deploy the bootstrapping ordinary least squares (bols) and the feasible generalized least squares (fgls) techniques. the bootstrap technique is a nonparametric approach that allows for resampling of the data in memory with replacement (mooney and duval, 1993). 3.3. empirical approach 3.3.1. pre-estimation checks2 before engaging the econometric analyses, it becomes imperative to subject the data to some pre-estimation checks such as (1) cross-sectional dependence, (2) stationarity and (3) cointegration tests. failure to control for cross-sectional dependence (csd) can result in biased estimates due to high dependence across countries (pesaran, 2004; 2015). the csd test is suited for both balanced and unbalanced data. the null hypothesis is either strict crosssectional independence (pesaran, 2004) or weak cross-sectional dependence (pesaran, 2015). upon examination, evidence confirms the presence of csd and the results from stata routine xtcdf are shown in table 4. having confirmed the existence of cross-sectional dependence, the study applies the t-test for unit roots in heterogeneous panels with cross-section dependence, proposed by pesaran (2003)3. the null hypothesis which assumes 2 to avoid proliferation, the tables for csd, stationarity and cointegration tests are compressed into table 4. 3 due to the unbalanced nature of the sample coupled with several missing observations, we were unable to apply the cross-sectionally im, pesaran and shin (ips, 2003) test. table 4: pre-estimation checks variables csd pescadf westerlund statistics level 1st diff. statistic lnco2pc 21.511*** −1.101 −3.344*** −1.708** lnpc 23.664*** 2.722 −1.858** lnrenw 20.154*** −1.429 −2.460** lnenu 14.719*** insufficient observations source: authors' computations. *** and ** indicate statistical significance at the 1% and 5% levels, respectively; co2pc=carbon dioxide emissions per capita; pc=gdp per capita; renw=renewable energy; enu=energy consumption per capita; csd=crosssectional dependence; pescadf=pesaran cross-sectional augmented dickey-fuller that all series are non-stationary removes dependence across the panels and the regressions are augmented with the cross-section averages of lagged levels and first-differences of the individual series using the augmented dickey-fuller approach (cadf). the result of the test derived from pescadf stata syntax is shown in table 4. correspondingly, the second-generation westerlund (2005) cointegration test suited for heterogeneous and crosssectionally dependent panels is applied. the null hypothesis of no cointegration can be rejected if the variables are cointegrated in all the panels or some of the panels. the cointegration result generated from the xtcointtest westerlund stata code is shown in table 4. 4. results and discussions 4.1. pre-estimation tests from table 4, the results show the presence of cross-sectional dependence among countries since the null hypothesis of crosssectional independence is rejected at 1% statistical level of significance. thus, any shocks that occur in any of the south asian countries may be easily transmitted to others. also, for the panel unit root tests, the variables became stationary after taking their first difference at the 1%, and 5% level of significance, respectively. due to insufficient observations, the statistics for energy use per capita could not be generated. for cointegration, evidence from westerlund cointegration test shows that the variables are cointegrated across some panels, thus rejecting the null hypothesis of no cointegration at the 5% level. 4.2. composite econometric results next, we probe if economic growth and each of the energy variants have any significant impact on carbon emissions. further, the study interrogates whether economic growth boosts or slows the impact of energy (both renewable and nonrenewable) on carbon emissions. it becomes necessary to separate these two energy variants and examine their overall impact on emissions because of the preponderance of literature reporting a possible association between energy use and emissions level (adeelfarooq et al., 2020; jiao, 2020; khan et al., 2020; nasreen et al., 2020; nathaniel et al, 2020a; parker and bhatti, 2020; rahman and velayutham, 2020; shaari et al., 2020; udemba et al., 2020). we obtain the results (table 5) from estimating equations [1], [2], and [3] using the panel-corrected standard errors technique (main) shown in columns [1] to [3], feasible generalized least squares (robustness) in columns [4] to [6] and bootstrap ordinary least squares (robustness) in columns [7] to [9]. we discuss each set of results in turns. adeleye, et al.: investigating growth-energy-emissions trilemma in south asia international journal of energy economics and policy | vol 11 • issue 5 • 2021118 from column [1] of the main results, the coefficient of pc is positive and statistically significant at the 1% level. as expected, this suggests that economic growth intensifies emissions and validates earlier the position of related studies (uddin and wadud, 2014; pandey and mishra, 2016; parker and bhatti, 2020) and that a percentage change in growth leads to a 0.867 increase in emissions level, on average, ceteris paribus. this outcome is unsurprising as the spate of economic progress in south asia is likely to drive up the level of carbon emissions. as expected, the coefficient of nonrenewable is positive and statistically significant at the 10% level and aligns with previous findings (chen et al., 2019; raza et al., 2019; sharif et al., 2019; awodumi and adewuyi, 2020; nathaniel et al., 2020a). though the coefficient of renewable energy is statistically not significant, the negative outcome indicates that it is a negative predictor of emissions. nevertheless, when renewable energy interacts with economic growth, the overall outcome suggests that the growth does not mitigate the “good” impact of renewable energy on carbon emissions. in column [2], the coefficient of the interaction term (0.763), which indicates whether pc enhances or distorts the impact of renewable energy on co2pc is statistically significant at the 1% level. since the magnitude of the positive coefficient determines the influence of economic growth, the differential4 of −5.8342 (that is, −6.5972 + 0.763) gives the total effect of renewable energy on carbon emissions and shows that the positive interaction coefficient is not sufficient to dampen the “good” impact of renewable energy on carbon emissions. in order words, the emissions-reducing effect of renewable energy is sustained. this finding is a significant incursion to the literature. we, therefore, argue that there is a complementary effect of renewable energy and economic growth in south asia. similarly, the initial “bad” effect of nonrenewable energy on emissions is marginally reduced when interacted with economic growth. in column [3], 4 the differential is obtained by deducting the coefficient of the interaction term from that of renewable energy. the coefficient of the interaction term (−0.317) is statistically significant at the 1% level and evaluates that the overall impact of nonrenewable energy as 2.041 (that is, 2.358–0.317). this outcome shows that economic growth can slow down the harmful impact of nonrenewable energy on the emissions level. the most plausible argument, in deference to the environmental kuznets curve (ekc) hypothesis, is that when an economy grows to a certain point, the optimal and efficient use of nonrenewable energy sources may yield “emissions-reducing” outcomes. again, this finding is a significant contribution to the literature. to test the robustness of our results, the fgls and bols techniques are deployed. the outcomes which are not significantly different from those of the psce shows that both economic growth and nonrenewable energy exacerbate emissions while renewable energy attenuates. also, the overall effect of renewable energy is computed as −7.149 and −7.244; while those of nonrenewable energy are 1.361 and 8.609, respectively. given these results, we submit that the interaction of economic growth enables the “good” effect of renewable energy. at the same time, it reduces the “bad” effect nonrenewable energy on carbon emissions. it engenders a new line of argument that the extent of economic growth cuts carbon emissions level. therefore, economic growth is an essential determinant of carbon emissions. 5. conclusion and policy implications this paper situates the 2030 united nations sustainable development goals (sdgs) 7, 8, and 13 (united nations, 2015) to investigate the trilemma of energy use – “ensure access to affordable, reliable, sustainable, and modern energy for all” (sdg 7); economic growth – “promote sustained, inclusive and sustainable economic growth” (sdg 8); and carbon emissions – “take urgent action to combat climate change and its impacts” (sdg 13). similarly, it questions the growth-energy-emissions trilemma by presenting empirical findings which fill a lacuna in the literature. this study takes a new perspective and highlights table 5: composite results (dep. var: lnco2pc) variables pcse fgls bootstrap ols main regression robustness checks [1] [2] [3] [4] [5] [6] [7] [8] [9] constant −8.1093*** 19.6892*** −19.6577*** −4.3274*** 28.5812*** −14.2547*** −6.4797*** 26.3600*** −60.7769*** (−10.33) (7.10) (−5.66) (−3.09) (10.30) (−4.60) (−3.89) (3.87) (−4.64) lnpc 0.8676*** −2.2624*** 2.6709*** 0.5503*** −3.2186*** 1.7537*** 0.4760*** −3.4879*** 9.3078*** (8.48) (−8.39) (4.84) (4.39) (−11.75) (3.60) (4.18) (−3.37) (4.60) lnrenw −0.0149 −6.5972*** −0.1628*** −0.5605*** −8.0593*** −0.1029** −0.3230 −8.1654*** −0.8795*** (−0.41) (−11.04) (−3.37) (−3.10) (−14.06) (−2.16) (−0.89) (−4.99) (−3.72) lnenu 0.1996* 0.1320 2.3577*** 0.3342** 0.0651 1.5413*** 0.6317*** 0.7460*** 10.0819*** (1.70) (1.40) (3.94) (2.48) (0.56) (2.83) (5.63) (6.12) (4.78) lnpc*lnrenw 0.7630*** 0.9096*** 0.9211*** (11.25) (13.99) (3.87) lnpc*lnenu −0.3170*** −0.1807** −1.4723*** (−3.52) (−2.27) (−4.45) no. of obs. 134 134 134 134 134 134 134 134 134 r-squared 0.782 0.904 0.809 wald statistic 1062.01*** 643.01*** 600.91*** 174.03*** 667.15*** 635.06*** no. of replications 50 50 50 source: authors' computations. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% significance levels; panel-corrected t-stats in ( ); co2pc = carbon dioxide emissions per capita; pc=gdp per capita; renw=renewable energy; enu=energy consumption per capita adeleye, et al.: investigating growth-energy-emissions trilemma in south asia international journal of energy economics and policy | vol 11 • issue 5 • 2021 119 discoveries on whether economic growth reduces the energy (renewable and nonrenewable) consumption and if its interaction with either energy variant reduces or exacerbate the level of carbon emissions. using an unbalanced panel data sample from seven south asian countries (bangladesh, bhutan, india, maldives, nepal, pakistan, and sri lanka) covering 1990–2019, findings from the psce, fgls, and bols techniques provide sufficient evidence that (1) renewable energy attenuates carbon emissions, (2) economic growth and nonrenewable energy intensify emissions, (3) economic growth strengthens the “good” effect of renewable energy on emissions, and (4) economic growth slows the “bad” effect of nonrenewable energy. the complementary role of economic growth shows it to be an essential factor that predicts the level of carbon emissions. policy implications are not far-fetched. the finding above does provide information for stakeholders in the region. at the same time, each country in the panel may strengthen its economic growth strategies aimed at reducing the level of carbon emissions. lastly, tackling climate change and ensuring a sustainable environment (sdg13) requires that de-carbonization measures be pursued to enable a healthy environment that will reduce health impacts due to energyrelated air pollution (sdg3) by 2030. further investigation is required and may be taken up in the future. references abolhosseini, s., heshmati, a., altmann, j. (2014), the effect of renewable energy development on carbon emission reduction: an empirical analysis for the eu-15 countries. iza discussion papers, no. 7989. adams, s., nsiah, c. (2019), reducing carbon dioxide emissions; does renewable energy matter? science of the total environment, 693, 133288-133288. adedoyin, f.f., nathaniel, s., adeleye, n. (2020), an investigation into the anthropogenic nexus among consumption of energy, tourism, and economic growth: do economic policy uncertainties matter? environmental science and pollution research, 28(3), 2835-2847. adeel-farooq, r.m., raji, o., adeleye, b.n. (2020), economic growth and methane emission: testing the ekc hypotheses in asean economies. management of environmental quality, 32(2), 1-13. adeleye, b.n., adedoyin, f.f., nathaniel, s. (2020), the criticality of ict-trade nexus on economic and inclusive growth. information technology for development, 27, 1-22. adeleye, n., eboagu, c. (2019), evaluation of ict development and economic growth in africa. netnomics: economic research and electronic networking, 20(1), 31-53. adu, d.t., denkyirah, e.k. (2017), economic growth and environmental pollution in west africa: testing the environmental kuznets curve hypothesis. kasetsart journal of social sciences, 30(2017), 8-15. afridi, m.a., kehelwalatenna, s., naseem, i., tahir, m. (2019), per capita income, trade openness, urbanization, energy consumption, and co2 emissions: an empirical study on the saarc region. environmental science and pollution research, 26(29), 29978-29990. ali, h.s., law, s.h., zannah, t.i. (2016), dynamic impact of urbanization, economic growth, energy consumption, and trade openness on co2 emissions in nigeria. environmental science and pollution research, 23(12), 12435-12443. ali, w., abdullah, a., azam, m. (2017), re-visiting the environmental kuznets curve hypothesis for malaysia: fresh evidence from ardl bounds testing approach. renewable and sustainable energy reviews, 77(2017), 990-1000. al-mulali, u., ozturk, i., solarin, s.a. (2016), investigating the environmental kuznets curve hypothesis in seven regions: the role of renewable energy. ecological indicators, 67, 267-282. apergis, n. (2016), environmental kuznets curves: new evidence on both panel and country-level co2 emissions. energy economics, 54, 263-271. asumadu-sarkodie, s., owusu, p.a. (2017), carbon dioxide emissions, gdp per capita, industrialization and population: an evidence from rwanda. environmental engineering research, 22(1), 116-124. awodumi, o.b., adewuyi, a.o. (2020), the role of nonrenewable energy consumption in economic growth and carbon emission: evidence from oil producing economies in africa. energy strategy review, 27, 100434. aye, g.c., edoja, p.e. (2017), effect of economic growth on co2 emission in developing countries: evidence from a dynamic panel threshold model. cogent economics and finance, 5(1), 1379239. chen, y., wang, z., zong, z. (2019), co2 emissions, economic growth, renewable and non-renewable energy production and foreign trade in china. renewable energy, 131, 208-216. chikaraishi, m., fujiwara, a., shinji, k.s.p., komatsu, s., kalugin, a. (2015), the moderating effects of urbanization on carbon dioxide emissions: a latent class modeling approach. technological forecasting and social change, 90(part a), 302-317. churchill, s.a., inekwe, j., ivanovski, k., smyth, r. (2018), the environmental kuznets curve in the oecd: 1870-2014. energy economics, 75(2018), 389-399. destek, m.a., sinha, a. (2020), renewable, non-renewable energy consumption, economic growth, trade openness and ecological footprint: evidence from organisation for economic co-operation and development countries. journal of cleaner production, 242, 118537. egbetokun, s., osabuohien, e., akinbobola, t., onanuga, o., gershon, o., okafor, v. (2020), environmental pollution, economic growth and institutional quality: exploring the nexus in nigeria quality. management of environmental quality: an international journal, 31(1), 18-31. eia. (2019), international energy outlook 2019: with projections to 2050. us energy information administration. available from: http:// www.eia.gov/ieo. ejuvbekpokpo, s.a. (2014), impact of carbon emissions on economic growth in nigeria. asian journal of basic and applied sciences, 1(1), 15-25. hasnisah, a., azlina, a.a., taib, c.m.i. (2019), the impact of renewable energy consumption on carbon dioxide emissions: empirical evidence from developing countries in asia. international journal of energy economics and policy, 9(3), 135-143. iea. (2019a), southeast asia energy outlook 2019. international energy agency. available from: http://www.iea.org. iea. (2019b), world energy outlook 2019. international energy agency. available from: http://www.iea.org. jiao, z. (2020), consumption-based carbon emissions and international trade in g7 countries: the role of environmental innovation and renewable energy. science of the total environment, 2020, 138945. khan, h., khan, i., tien, t. (2020), the heterogeneity of renewable energy consumption, carbon emissions and financial development in the globe : a panel quantile regression approach. energy reports, 6, 859-867. li, k., lin, b. (2015), impacts of urbanization and industrialization on energy consumption/co2 emissions: does the level of development matter? renewable and sustainable energy reviews, 52, 1107-1122. mooney, c.z., duval, r.d. (1993), bootstrapping: a nonparametric approach to statistical inference. newbury park, ca: sage. nasreen, s., mbarek, m.b., atiq-ur-rehman, m. (2020), long-run adeleye, et al.: investigating growth-energy-emissions trilemma in south asia international journal of energy economics and policy | vol 11 • issue 5 • 2021120 causal relationship between economic growth, transport energy consumption and environmental quality in asian countries: evidence from heterogeneous panel methods. energy, 192, 116628. nathaniel, s., barua, s., hussain, h., adeleye, n. (2020a), the determinants and interrelationship of carbon emissions and economic growth in african economies: fresh insights from static and dynamic models. journal of public affairs, e2141, 1-15. nathaniel, s.p., adeleye, n., adedoyin, f.f. (2020b), natural resource abundance, renewable energy, and ecological footprint linkage in mena countries. estudios de economia aplicada, 39-2, 1-16. nguyen, k.h., kakinaka, m. (2019), renewable energy consumption, carbon emissions, and development stages: some evidence from panel cointegration analysis. renewable energy, 132, 1049-1057. osabuohien, e.s., efobi, u.r., gitau, c.m.w. (2014), beyond the environmental kuznets curve in africa: evidence from panel cointegration. journal of environmental policy and planning, 16(4), 517-538. osmani, s.r. (2018), socio-economic development in south asia. united nations university. pandey, s., mishra, m. (2016), co2 emissions and economic growth of saarc countries: evidence from a panel var analysis. world journal of applied economics, 1(2), 23-33. parker, s., bhatti, m.i. (2020), dynamics and drivers of per capita co2 emission in asia. energy economics, 89, 1-11. pata, u.k. (2018), renewable energy consumption, urbanization, financial development, income and co2 emissions in turkey: testing ekc hypothesis with structural breaks. journal of cleaner production, 187(2018), 770-779. pesaran, m.h. (2004), general diagnostic tests for cross section dependence in panels. university of cambridge, faculty of economics, cambridge working papers in economics, no. 0435. pesaran, m.h. (2015), testing weak cross-sectional dependence in large panels. econometric reviews, 34(6-10), 1089-1117. pimentel, d., herz, m., glickstein, m., zimmerman, m., allen, r., becker, k., evans, j., hussain, b., sarsfeld, r., grosfeld, a., seidel, t. (2002), renewable-energy-article-pimental. bioscience, 52(12), 1111-1120. rahman, m.m., saidi, k., mbarek, m.b. (2020), economic growth in south asia: the role of co2 emissions, population density and trade openness. heliyon, 6(5), e03903. rahman, m.m., velayutham, e. (2020), renewable and non-renewable energy consumption-economic growth nexus: new evidence from south asia. renewable energy, 147, 399-408. raza, s.a., shah, n., sharif, a. (2019), time-frequency relationship between energy consumption, economic growth and environmental degradation in the united states: evidence from transportation sector. energy, 173, 706-720. saidi, k., hammami, s. (2015), the impact of co2 emissions and economic growth on energy consumption in 58 countries. energy reports, 1, 62-70. sarkodie, s.a., strezov, v. (2018), empirical study of the environmental kuznets curve and environmental sustainability curve hypothesis for australia, china, ghana and usa. journal of cleaner production, 201, 98-110. shaari, s., karim, z.a., abidin, n.z. (2020), the effect of energy consumption and national output on co2 emission: using a panel ardl analysis. sustainability, 12, 1-12. shahbaz, m., jam, f.a., bibi, s., loganathan, n. (2016), multivariate granger causality between co2 emissions, energy intensity and economic growth in portugal: evidence from cointegration and causal analysis. technological and economic development of economy, 22(1), 47-74. sharif, a., raza, s.a., ozturk, i., afshan, s. (2019), the dynamic relationship of renewable and nonrenewable energy consumption with carbon emission: a global study with the application of heterogeneous panel estimations. renewable energy, 133, 685-691. sharma, s., kishan, r., doig, a. (2014), low-carbon development in south asia: leapfrogging to a green future. twerefou, d.k., adusah-poku, f., bekoe, w. (2016), an empirical examination of the environmental kuznets curve hypothesis for carbon dioxide emissions in ghana: an ardl approach. environmental and socio-economic studies, 4(4), 1-12. uddin, m., wadud, a. (2014), carbon emission and economic growth of saarc countries: a vector autoregressive (var) analysis. international journal of business and management review, 2(4), 7-26. udemba, e.n., magazzino, c., bekun, f.v. (2020), modelling the nexus between pollutant emission, energy consumption, foreign direct investment, and economic growth: new insights from china. environmental science and pollution research, 27, 17831-17842. united nations. (2015), sustainable development goals. available from: https://www.sustainabledevelopment.un.org/?menu=1300. united nations. (2019), world economic situation and prospects 2019. new york: united nations. wahid, i.n., aziz, a.a., kamaludin, m., anang, z. (2018), the influence of energy consumption, renewable energy and economic growth on co2 emission in malaysia and indonesia. journal of sustainability science and management, (special issue 4), 117-131. westerlund, j. (2005), new simple tests for panel cointegration. econometric reviews, 24, 297-316. world bank. (2019), world development indicators. available from: https://www.data.worldbank.org/data-catalog/world-developmentindicators. xu, q., dong, y.x., yang, r. (2018), urbanization impact on carbon emissions in the pearl river delta region: kuznets curve relationships. journal of cleaner production, 180, 514-523. zhang, y.j., yi, w.c., li, b.w. (2015), the impact of urbanization on carbon emission: empirical evidence in beijing. energy procedia, 75, 2963-2968. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 3 • 202120 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(3), 20-26. the relationship between renewable energy production and employment in european union countries: panel data analysis gulmira azretbergenova1*, beybit syzdykov2, talgat niyazov3, turysbekova gulzhan4, nazira yskak5 1department of finance and accounting, khoja akhmet yassawi international kazakh, turkish university, turkestan, kazakhstan, 2department of business, international humanitarian technical university, shymkent, kazakhstan, 3department of economics, khoja akhmet yassawi international kazakh, turkish university, turkestan, kazakhstan, 4department of tourism, khoja akhmet yassawi international kazakh, turkish university, turkestan, kazakhstan, 5administrative affairs, khoja akhmet yassawi international kazakh, turkish university, turkestan, kazakhstan. *email: gulmiraazretbergenova@gmail.com received: 12 october 2020 accepted: 14 january 2021 doi: https://doi.org/10.32479/ijeep.10744 abstract renewable energy, which is the type of energy that plays a major role in the development and growth of countries, plays an important role in today’s world, considering that the life of depleted energy resources is finite. compared to fossil energy sources, except that its source is infinite, a noticeable difference in carbon dioxide emission is seen as the reason for preferring renewable energy sources. many studies in the literature investigate the relationship between the consumption of renewable energy resources and economic growth. this study was conducted on renewable energy production in 27 european union member countries explores its impact on employment. in the study, panel ardl test was conducted with the data for the years 2006-2019. according to the results of the study, renewable energy generation has a positive effect on employment in european union countries in the long term. in the long run, a 1% increase in renewable energy primary production increases employment by 0.08%. increasing the use of renewable energy resources should go beyond being a policy recommendation in international conventions. the fact that these resources provide employment in large areas can be a good alternative today with high unemployment rates. keywords: renewable energy, employment, developed countries, panel autoregressive distributed lag model jel classifications: o40, q43, q40 1. introduction the development of renewable energy alternatives, increasing energy efficiency and thus reducing the effects of energy consumption on climate change, increasing energy supply security and contributing to the economy, as well as its positive impact on employment have been a subject of study in recent years. environmental, energy efficiency and renewable energy investments create thousands of job opportunities around the world. environmental awareness, kyoto protocol, carbon tax, renewable energy investments and energy security, international agreements and cooperation in energy trade enable the emergence of new employment areas defined as green professions (lehr et al., 2008; elfani, 2011; lehr et al., 2012; jaber et al., 2015; muniyoor, 2020; majid, 2020). especially developed countries with high energy consumption in industry have increased their investments in technology to be used for renewable energy. as renewable energy technologies develop, both the cost of renewable energy will decrease and its useful life will increase. investments made in the field of renewable energy will create new employment areas. according to the renewable energy and employment report published by the international renewable energy agency (irena), the employment figure in the field of renewable energy was 11 million in 2018, compared to 10.34 million in 2017. on a sectoral basis, solar energy, biofuel energy and wind energy stand out. it is seen that most of the early studies this journal is licensed under a creative commons attribution 4.0 international license p between renewable energy production and employment in european union countries: panel data azretbergenova, et al.: the relationshi analysis international journal of energy economics and policy | vol 11 • issue 3 • 2021 21 and related institution reports in the field of renewable energy create positive and high employment expectations by taking into account the direct employment in the sector. however, directing macro policies by considering only direct employment may cause structural problems in the labor market in the long run (markandya et al., 2016; cameron and van der zwaan, 2015). the aim of this study is to investigate whether renewable energy consumption creates employment for eu countries, representing developed countries. when the relevant literature is examined, it is seen that there are fewer empirical applications despite many theoretical studies. it is striking that econometric analysis, which takes into account net employment in particular, is insufficient. with this study, it is aimed to contribute to these areas, which are indicated to be insufficient, and to make long-term political implications. at this point, the study consists of 5 parts. the following part of the study includes empirical literature on the subject. then, the data set and model used in the analysis are explained. in the fourth part, the findings obtained as a result of empirical application are evaluated. the study ended with the conclusion part. 2. literature review there are many studies in the literature on the relationship between renewable energy consumption and economic growth. although different variables are used in studies, the most common variables are renewable energy production-consumption, gross domestic product or per capita gross domestic product, energy dependency, capital, labor power, carbon dioxide emission. while there is a causality relationship between variables in some studies (tugcu et al., 2012; al-mulali et al., 2014; paramati et al., 2017), there is no causality relationship in some studies (jebli and youssef, 2015; chang et al., 2015). in 2012, tugcu et al. conducted a study for g-7 (canada, france, germany, italy, japan, united kingdom, usa) countries. as a result of the study using ardl (autoregressive distributed lag model) and khatami causality method, the bi-directional causality of renewable energy consumption to economic growth and economic growth to renewable energy consumption was found. almulali et al. (2014) examined the period between 1980 and 2011 of 18 latin american countries. renewable energy consumption, real gross domestic product, consumable energy consumption, labor force, foreign trade and fixed capital formation variables are used in the study. by using pedroni cointegration, dols (dynamic least squares), granger causality method, bidirectional causality was found between renewable energy consumption and real gross domestic product. in amri’s 2016 study, he studied 75 different countries between 1990 and 2010. in the analysis made by using the variables of renewable energy consumption, real gross domestic product, consumable energy consumption, labor power, capital and foreign direct investment, the causality from renewable energy consumption to real gross domestic product has been reached with the gmm method. paramati et al. (2017) examined g20 countries in the period from 1991 to 2012. in their studies, they used the variables of renewable energy consumption, real gross domestic product, consumable energy consumption, carbon dioxide emission, fixed capital formation, foreign direct investment, energy efficiency, market capitalization. through the panel cointegration and dumitrescu-hurlin causality method, the conclusion of causality from renewable energy consumption to real gross domestic product for developing countries has been reached. bhattacharya et al. (2016) examined 38 countries between 1991 and 2012. renewable energy consumption, real gross domestic product, consumable energy consumption, labor force, fixed capital formation were used as variables. as a result of the analysis using pedroni cointegration, dols, granger causality methods, causality from renewable energy consumption to real gross domestic product was found. jebli and youssef (2015) examined the period between 1980 and 2010 in 69 countries. renewable energy consumption, real gross domestic product, consumable energy consumption, labor force, capital, foreign trade variables are used in the study. in the analysis made by using pedroni cointegration, dols and granger causality, causality between real gross domestic product and renewable energy consumption could not be reached in the panel. al-mulali et al. (2013) examined this relationship for 108 countries. renewable energy consumption and real gross domestic product are used in the analysis that examines the period between 1980 and 2009. the result obtained from the fmols (fully modified least squares) method is a bidirectional relationship between renewable energy consumption and real gross domestic product for 85 countries, causality from real gross domestic product to renewable energy consumption in two countries, and any causality was not found. chang et al. (2015) analyzed g-7 countries. by using emirmahmutoğlu-köse causality and granger causality method, from real gross domestic product to renewable energy consumption in two countries, from renewable energy to real gross domestic product in two countries, a two-way relationship was found in the total panel. in three countries, causality was not found. mahmoodi (2017) examined the relationship between economic growth, renewable energy and carbon dioxide emissions for a panel of 11 developing countries. the results of the kao and pedroni panel cointegration test showed the existence of a longterm relationship between these variables. panel causality results demonstrated bidirectional causality between renewable energy and co2 emissions, bidirectional causality between gdp and co2, and unidirectional causality from gdp to renewable energy. burakov and freidin (2017) investigated the causal relationship between financial development, economic growth and renewable energy consumption in the case of russia. the results of the vec model showed that the system of variables corrected the previous period imbalance at 22.98% in 1 year. the results of the granger causality test showed that there is a bidirectional causality between economic growth and financial development in russia, while renewable energy consumption does not cause economic growth or financial development. there are relatively few studies investigating the relationship between renewable energy and employment empirically. major studies in the literature investigating this relationship are fragkos and paroussos (2018), rafiq et al. (2018), hondo and moriizumi (2017), zhao and luo (2017), ge and zhi (2016), apergis and salim (2015), cai et al. (2014), fanning et al. (2014), rivers (2013), lambert and silva (2012), cai et al. (2011), tourkolias p between renewable energy production and employment in european union countries: panel data azretbergenova, et al.: the relationshi analysis international journal of energy economics and policy | vol 11 • issue 3 • 202122 and mirasgedis (2011), frondel et al. (2010), sastresa et al. (2010), ozturk and acaravci (2010), payne (2009), moreno and lópez (2008), hillebrand et al. (2006), ziegelmann et al. (2000). in their study for eu countries, fragkos and paroussos (2018) combined the employment factor approach, which is a bottom-up approach, and the overall balance analysis, which is a top-down approach, to achieve a consistent result. employment from energy expansion will be in the construction of pv installations, the production of advanced biofuels, the manufacture and installation of wind turbines. the transition to a low carbon economy will enable the reallocation of approximately 1.3% of jobs in eu countries in 2050. rafiq et al. (2018) worked with data from 41 countries. according to the result; while non-renewable energy consumption reduces unemployment, renewable energy increases unemployment. in the linear panel estimation, government spending and trade deficit, while in the nonlinear panel estimation, industrialization and service sector unemployment decrease. in addition, agriculture increases unemployment. hondo and moriizumi (2017) investigated the employment creation characteristics of nine different renewable energy generation technologies. the total employment opportunities created over the life cycle range from 1.04 to 5.04 person-years per gwh, depending on the type of technology. in addition, for the total of nine sectors, the highest indirect contribution to employment is provided by the service sector. zhao and luo (2017) found a quadratic relationship between income and renewable energy generation for china. there is no significant relationship between renewable energy and delayed unemployment rate. income and employment have a negative impact on renewable energy. in addition, regulation has positive effects on renewable energy. according to the literature review by ge and zhi (2016), there are some gaps in the literature such as lack of information about new energy types and the results obtained are not based on a clear theory. in addition, while the green economy has positive effects on employment in countries such as china, south africa, usa and france; for some countries such as spain, germany and italy, it may create unemployment, not employment. apergis and salim (2015) discuss the dynamic link between renewable energy consumption and unemployment for 80 countries. overall, although renewable energy consumption has a positive effect on unemployment, certain regions such as asia and latin america show that the impact of renewable energy consumption on job creation depends on the cost of adopting renewable energy technologies and energy efficiency that differs between regions. jaraitė et al. (2015) made an analysis for eu countries with the data for the years 1990-2012. according to the findings, solar energy has a positive effect on employment in machinery and equipment manufacturing, but it is not at a level that will affect the overall economy level. in addition, wind energy has a positive effect on overall employment in the short term at the overall economy level, but not at the level of the manufacturing and machinery sector. again, ortega et al. (2015) investigated the net employment effect of renewable energy in both member countries and specifically in each member country, unlike the previous literature on european union member countries. the study covers the period 2008-2012. it is seen that solar pv technology and wind energy (land typemarine type) technologies are taken into consideration. in the study, a new kind of dynamic analytical method is presented that takes into account the do-learning effect, the current industrial structure of the countries and regional trade data. as a result of the analysis, they determined that 548 019 new jobs were created by the pv and wind energy sectors in 2012. it is stated that 45.7% of new employment originates from the land-type wind energy sector, 45.6% from the solar energy sector and 8.7% from the marine-type wind energy sector. in addition, it was seen that 56% of the total new employment emerged during the production phase. 27% was revealed during the installation phase and 17% during the operation-maintenance phase. the ranking in terms of countries is germany, denmark, italy, spain and england. fortes et al. (2015) focused on portugal, which is the third country with the highest unemployment rate among eu countries. although the results are not comparable because their assumptions and inputs are not the same, two different simulation methods have been used: hybgem (hybrid bottom-up general equilibrium model) and hybtep (hybrid technological-economic platform). in this study, the effects of high financing costs of renewable energy investments on employment and welfare have been investigated. the results show that whether the financing is reflected to households with lump-sum taxes or when it is reflected to employers through insurances, it negatively affects employment. in short, negative net employment result was obtained in all scenarios applied in the study. 3. data and methodology 3.1. data set and model the analysis was made using the annual data of eu (27) countries between 2006 and 2019. the following model has been established to investigate the contribution of renewable energy generation to employment for eu countries: empit=β0+β1 repit+β2 gdpit+β3 fcapfit+εit (1) in equation number 1, emp variable is the dependent variable and expresses employment. independent variables are rep renewable energy production, gdp gross domestic product per capita, and fcapf are fixed capital formation variables, respectively. renewable energy primary production includes primary production of solar energy, biomass energy and wastes, geothermal energy, hydraulic energy, wind energy and marine energy, and the data are taken from eurostat’s data base ten00081. the ktoe unit, equivalent to one thousand tons of oil, is used as the primary renewable energy production criterion. gross domestic product per capita, gross fixed capital formation data and employment data were obtained from the world bank database. employment variable has been selected and taken as total labor force on the basis of person. all variables are used in logarithmic form. 3.2. methodology in this study, panel data analysis was applied to investigate the relationship between renewable energy production and p between renewable energy production and employment in european union countries: panel data azretbergenova, et al.: the relationshi analysis international journal of energy economics and policy | vol 11 • issue 3 • 2021 23 employment in eu countries. panel data is created by combining the time series of economic individuals with the cross-sectional dimension (baltagi, 2008). in the study, after checking the stationary properties of the variables, static panel data analysis was applied, and then the error correction coefficient of the panel ardl model was calculated. panel ardl (distributed delay autoregressive model) boundary test approach pesaran et al. (2001) has been developed by. this approach makes it possible to examine the cointegration relationship when the explanatory variables are stationary at different levels such as level [i (0)] and first difference [i (1)]. but if the unit root degree of one of the variables is greater than i (1), pesaran et al. (2001) and narayan and narayan (2005) cannot use the critical values. these critical values are based on i (0) and i (1). for this reason, at the first stage of the analysis, it is necessary to check whether the ardl boundary test approach complies with the assumptions by performing unit root test to the variables. the ardl method is based on the standard least squares method in which both the dependent variable and the delayed values of the independent variables are used as explanatory variables. the most important advantage of this approach is that it does not require a comprehensive data set and analysis can be made with a small data set. also, in this approach, the optimal lag levels of variables at different levels can be taken into account. finally, although the ardl approach can be applied to single equation systems, long-term relationships in traditional cointegration techniques can only be calculated with the help of system equations (ozturk and acaravci, 2010a). 4. analysis findings 4.1. panel cross-section dependence test firstly, cross section dependency was checked with lm tests in the study. the dependency of the cross section units means that a shock to one of them will affect the other section units as well (syzdykova et al., 2020). testing the cross section dependency is important in choosing the unit root tests to be applied. because there are two generations of unit root tests, first generation unit root tests may give incorrect results in case of cross-sectional dependency between series (de hoyos and sarafidis, 2006). three lm tests were applied to check the cross-sectional dependence. one of these, lm1, was developed by breusch and pagan (1980). other lm tests are lm2 and lm tests developed by pesaran (2004). the results obtained from the lm tests are shown in table 1. the null hypothesis for lm tests is that there is no cross-sectional dependency. as can be seen from table 1, the null hypothesis that argues that there is no cross-sectional dependency has been rejected, so there is a cross-section dependence between the european union countries included in the analysis in the selected series. considering that the economies of the countries today are in close relationship with each other, it is a realistic approach that the countries that make up the panel are affected by a shock coming to one of the countries. 4.2. panel unit root test since there is a cross sectional dependency in the series used in the study, the second generation unit root test, which takes this situation into account, was applied. pesaran’s cadf test was used for this type of analysis. pesaran (2007) proposed a simple method to eliminate the correlation between units instead of estimating factor loads. instead of a unit root test based on taking the difference from the estimated common factors, he added the cross section averages of the lagged levels and first differences of the individual series as factors to the df or adf regression. therefore, in this method, the extended version of the adf regression with lagged cross-section means is used, and the first difference of this regression eliminates the inter-unit correlation. cross-sectional augmented dickey-fuller (cadf) test results are reported in table 2. as a result of the unit root test, it is seen that the level values of the series both on individual country basis and throughout the panel are stable and carry an i (0) process. 4.3. panel ardl test the ardl test is based on the estimation of the least-squares estimator and the unconstrained error correction model. the cointegration relationship of equation (1) can be determined by estimating the unconstrained error correction model with the boundary test approach. in this context, the equation (1) can be expressed in ardl form as follows: �emp emp rep gdp fcapfit i i i t i it i it i it j pi ij � � � � � �� � � � � � � � � � , 1 1 1 *** ** ** , , , � � � emp rep gdp i t j j qi ij i t j j ki ij i t j j � � � � � � � � � � � 0 0 0 � � ffi ij i t j itfcapf u� � �� ** ,� (2) where; � � � � � � � � i ijj pi i ijj qi i ijj ki i ij � � �� � � � � � � � � � � �� � �1 1 0 0, * , * , * , jj fi �� 0 i = 1, 2,… 27; t = 2006, 2007,…, 2019. panel ardl results were calculated with stata 11.0 and estimates are given in table 3. as a result of hausman test, pmg regression was preferred instead of mg. the coefficient of the variable rep has a positive sign. this means that renewable energy generation has a positive effect on employment in european union countries in the long run. the sign of the gross domestic product per capita variable, table 1: cross section dependency test results variables cdlm1 cdlm2 cdlm emp 373.06** 18.88** –3.97* rep 396.09* 14.30** 4.71*** gdp 385.36** 13.02** –3.87* fcapf 309.65*** 12.09*** 3.61* *, ** and *** show that the null hypothesis is rejected and the significance level of 10%, 5% and 1% respectively p between renewable energy production and employment in european union countries: panel data azretbergenova, et al.: the relationshi analysis international journal of energy economics and policy | vol 11 • issue 3 • 202124 which is considered as economic growth, is negative, while the variable of fixed capital formation is positive. as a result, while a 1% increase in primary production of renewable energy in the long term increases the workforce by 0.08%, in the long term increase of 1% in the formation of fixed capital increases the labor force by 0.13%, while the 1% increase in per capita gross product decreases the workforce by 0.07% in the long term. the negative effect can be explained by the income effect and technological unemployment in economic theory. in general, all three explanatory variables are statistically significant in the model established. in addition, the error correction coefficient was statistically significant and negative, indicating that the ardl model is working correctly. according to the error correction model coefficient, approximately 48% of the deviations that occur in the short term reach the long term balance by leveling in the next period. it takes 2.08 periods for the deviations in the model in the short run to reach long-term equilibrium. since the data used in the analyzes are annual, it takes approximately 2 years for shortterm deviations to reach long-term equilibrium. 5. conclusion in this study, the effect of the shift towards renewable energy use due to environmental degradation and energy supply security in the world on employment in eu countries was examined. investments to be made in the field of renewable energy and the positive externalities that these investments will create provide significant support to economic growth and development by causing an table 2: cadf unit root test results countries emp rep gdp fcapf cadf stat lag cadf stat lag cadf stat lag cadf stat lag austria –8.06*** 1 –4.01** 1 –2.7* 2 –3.8** 3 belgium –2.99* 1 –3.91** 1 –3.02* 5 –5.41*** 2 bulgaria –2.47 2 –3.03** 3 –2.98* 1 –3.29* 1 croatia –3.33* 1 –4.04** 5 –2.10 2 –3.76** 2 cyprus –3.08* 1 –3.49** 1 –3.12* 1 –3.13* 2 czech republic –5.4*** 1 –1.12 1 –3.01* 2 –1.39 2 denmark –4.03** 2 –3.65** 3 –2.76 3 –2.81 1 estonia –2.05 1 –3.07* 2 –3.43** 1 –3.46** 1 finland –3.12** 1 –1.90 2 –1.23 2 –4.01*** 1 france –3.06** 3 –2.32 1 –3.23 1 –2.76 2 germany –3.13** 2 –5.29*** 1 –3.88** 3 –3.71** 3 greece –3.11**** 1 –1.44 1 –4.12 1 –8.13* 2 hungary –2.12 1 –3.81* 3 –5.85*** 1 –2.98 3 ireland –1.45 1 –3.06** 2 –3.23 1 –3.67** 2 italy –3.02* 3 –5.78*** 1 –4.21*** 2 –2.55 4 latvia –2.78 2 –4.10** 1 –4.72** 3 –1.23 1 lithuania –3.20* 1 –5.22*** 3 –3.01* 3 –2.78 1 luxembourg –1.98 1 –3.02* 2 –2.87 2 –3.03* 1 malta –3.45** 1 –3.26* 2 –3.23** 2 –3.18* 2 netherlands –5.81*** 2 –6.65** 2 –2.56 1 –2.09** 2 poland –3.03* 2 –3.08* 1 –3.23* 1 –3.20* 1 portugal –1.28 1 –3.67** 1 –3.37* 2 –2.04 4 romania –4.13*** 2 –4.13*** 1 –2.34 1 –1.99 2 slovakia –4.02*** 1 –2.95 1 –2.01 1 –2.67 2 slovenia –2.04 1 –3.09* 3 –3.23** 3 –4.60*** 1 spain –1.19 3 –3.78** 2 –2.31 1 –4.01** 1 sweden –3.24* 1 –3.04* 2 –2.10 3 –3.62** 3 panel geneli (cips) –3.32*** –2.87*** –2.29** –2.13** constant term and trend are included from the determenistic components. *, ** and *** show that the null hypothesis is rejected and the significance level of 10%, 5% and 1% respectively. the critical values of cadf statistics are taken from table 1b in pesaran (2007). critical values indicate the significance levels of –4.11***, –3.36** and –2.97*, respectively 1%, 5% and 10%. cips statistics critical values are taken from table 2b in pesaran (2007). critical values show the significance levels of 1%, 5% and 10%, respectively, as –2.57***, –2.33** and –2.21* table 3: panel ardl forecast results pooled mean group regression mean group regression independent variables coefficient std. error independent variables coefficient std. error rep 0.0898** 0.0176 rep –0.3743 3.2200 gdp –0.0717** 0.0103 gdp –0.0201 0.7302 fcapf 0.0135*** 0.0048 fcapf 0.0876 0.6831 ec –0.483*** 0.0741 ec –0.486*** 0.0622 ∆rep 0.224** 0.0611 ∆rep 0.213*** 0.0568 ∆gdp 0.0474 0.0104 ∆gdp 0.0209 0.0126 ∆fcapf 0.1209 0.1108 ∆fcapf 0.4532 0.7651 constant 1.517*** 0.0431 constant 1.487*** 0.3806 hausman test results: chi2 (2) = 1.98 and probability value > chi2 0.37 *, ** and *** show the significance level of 10%, 5% and 1% respectively p between renewable energy production and employment in european union countries: panel data azretbergenova, et al.: the relationshi analysis international journal of energy economics and policy | vol 11 • issue 3 • 2021 25 increase in domestic production, creating more employment and decreasing import bills. in this study, unlike many other studies, the relationship between renewable energy primary production and employment was revealed by panel ardl method. for this purpose, the gross domestic product per capita and fixed capital formation variables are also included in the model established in the study as control variables. within the scope of the analysis results, the long-term effects of renewable energy primary production and other variables on employment in european union countries were found to be significant and interpreted. in this context, capital investments of countries in renewable energy technologies should increase, the use of fossil fuels should be reduced, and suitable lands for renewable energy resources facilities should be determined. collaborations, statistical transfers, support projects and joint projects should be intensified among eu countries on renewable energy. on the other hand, if countries reduce the dependency of imported fossil fuels, the prices of consumable energy resources will decrease and the emission strategy will be supported. reproduction of studies and analyzes on renewable energy will help countries determine their policies in line with the results to be obtained. references al-mulali, u., fereidouni, h.g., lee, j.y. (2014), electricity consumption from renewable and non-renewable sources and economic growth: evidence from latin american countries. renewable and sustainable energy reviews, 30, 290-298. al-mulali, u., fereidouni, h.g., lee, j.y., sab, c.n.b. (2013), exploring the relationship between urbanization, energy consumption, and co2 emission in mena countries. renewable and sustainable energy reviews, 23, 107-112. apergis, n., salim, r. (2015), renewable energy consumption and unemployment: evidence from a sample of 80 countries and nonlinear estimates. applied economics, 47(52), 5614-5633. baltagi, b.h. (2008), forecasting with panel data. journal of forecasting, 27(2), 153-173. bhattacharya, m., paramati, s.r., ozturk, i., bhattacharya, s. (2016), the effect of renewable energy consumption on economic growth: evidence from top 38 countries. applied energy, 162, 733-741. breusch, t.s., pagan, a.r. (1980), the lagrange multiplier test and its applications to model specification in econometrics. the review of economic studies, 47(1), 239-253. burakov, d., freidin, m. (2017), financial development, economic growth and renewable energy consumption in russia: a vector error correction approach. international journal of energy economics and policy, 7(6), 39-47. cai, w., mu, y., wang, c., ve chen, j. (2014), distributional employment ımpacts of renewable and new energy a case study of china. renewable and sustainable energy reviews, 39, 1155-1163. cai, w., wang, c., chen, j., wang, s. (2011), green economy and green jobs: myth or reality? the case of china’s power generation sector. energy, 36(10), 5994-6003. cameron, l., van der zwaan, b. (2015), employment factors for wind and solar energy technologies: a literature review. renewable and sustainable energy reviews, 45, 160-172. chang, t., gupta, r., inglesi-lotz, r., simo-kengne, b., smithers, d., trembling, a. (2015), renewable energy and growth: evidence from heterogeneous panel of g7 countries using granger causality. renewable and sustainable energy reviews, 52, 1405-1412. de hoyos, r.e., sarafidis, v. (2006), testing for cross-sectional dependence in panel data models. the stata journal, 6(4), 482-496. elfani, m. (2011), the impact of renewable energy on employment in indonesia. international journal of technology, 2(1), 47-55. fanning, t., jones, c., munday, m. (2014), the regional employment returns from wave and tidal energy: a welsh analysis. energy, 76, 958-966. fragkos, p., paroussos, l. (2018), employment creation in eu related to renewables expansion. applied energy, 230, 935-945. frondel, m., ritter, n., schmidt, c.m., vance, c. (2010), economic ımpacts from the promotion of renewable energy technologies: the german experience. energy policy, 38(8), 4048-4056. ge, y., zhi, q. (2016), literature review: the green economy, clean energy policy and employment. energy procedia, 88, 257-264. hillebrand, b., buttermann, h.g., behringer, j.m., bleuel, m. (2006), the expansion of renewable energies and employment effects in germany. energy policy, 34(18), 3484-3494. hondo, h., moriizumi, y. (2017), employment creation potential of renewable power generation technologies: a life cycle approach. renewable and sustainable energy reviews, 79, 128-136. irena. (2019), renewable energy and jobs. annual review 2019. abu dhabi, united arab emirates: international renewable energy agency. available from: https://www.is.gd/klbdwp. [last access on 2020 jul 20]. jaber, j.o., elkarmi, f., alasis, e., kostas, a. (2015), employment of renewable energy in jordan: current status, swot and problem analysis. renewable and sustainable energy reviews, 49, 490-499. jaraitė, j., karimu, a., kažukauskas, a., kazukauskas, p. (2015), renewable energy policy, economic growth and employment in eu countries: gain without pain? economic growth and employment in eu countries: gain without pain. ssrn electronic journal, 2015, 2615894. jebli, m.b., youssef, s.b. (2015), output, renewable and non-renewable energy consumption and international trade: evidence from a panel of 69 countries. renewable energy, 83, 799-808. lambert, r.j., silva, p.p. (2012), the challenges of determining the employment effects of renewable energy. renewable and sustainable energy reviews, 16(7), 4667-4674. lehr, u., lutz, c., edler, d. (2012), green jobs? economic impacts of renewable energy in germany. energy policy, 47, 358-364. lehr, u., nitsch, j., kratzat, m., lutz, c., edler, d. (2008), renewable energy and employment in germany. energy policy, 36(1), 108-117. mahmoodi, m. (2017), the relationship between economic growth, renewable energy, and co2 emissions: evidence from panel data approach. international journal of energy economics and policy, 7(6), 96-102. majid, m.a. (2020), renewable energy for sustainable development in india: current status, future prospects, challenges, employment, and investment opportunities. energy, sustainability and society, 10(1), 2-10. markandya, a., arto, i., gonzález-eguino, m., román, m.v. (2016), towards a green energy economy? tracking the employment effects of low-carbon technologies in the european union. applied energy, 179, 1342-1350. moreno, b., lopez, a.j. (2008), the effect of renewable energy on employment. the case of asturias (spain). renewable and sustainable energy reviews, 12(3), 732-751. muniyoor, k. (2020), is there a trade-off between energy consumption and employment: evidence from india. journal of cleaner production, 255, 120262. narayan, s., narayan, p.k. (2005), an empirical analysis of fiji’s import demand function. journal of economic studies, 32, 158-168. ortega, m., del río, p., ruiz, p., thiel, c. (2015), employment effects of renewable electricity deployment. a novel methodology. energy, p between renewable energy production and employment in european union countries: panel data azretbergenova, et al.: the relationshi analysis international journal of energy economics and policy | vol 11 • issue 3 • 202126 91, 940-951. ozturk, i., acaravci, a. (2010), co2 emissions, energy consumption and economic growth in turkey. renewable and sustainable energy reviews, 14(9), 3220-3225. ozturk, i., acaravci, a. (2010a), the causal relationship between energy consumption and gdp in albania, bulgaria, hungary and romania: evidence from ardl bounds testing approach. applied energy, 87(6), 1938-1943. paramati, s.r., mo, d., gupta, r. (2017), the effects of stock market growth and renewable energy use on co2 emissions: evidence from g20 countries. energy economics, 66, 360-371. payne, j.e. (2009),on the dynamics of energy consumption and employment in ıllinois. journal of regional analysis and policy, 39, 126-130. pesaran, m.h. (2007), a simple panel unit root test in the presence of cross‐section dependence. journal of applied econometrics, 22(2), 265-312. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. rafiq, s., salim, r., sgro, p.m. (2018), energy, unemployment and trade. applied economics, 50(47), 5122-5134. rivers, n. (2013), renewable energy and unemployment: a general equilibrium analysis. resource and energy economics, 35(4), 467-485. sastresa, e.l., usón, a.a., bribián, i.z., scarpellini, s. (2010), local ımpact of renewables on employment: assessment methodology and case study. renewable and sustainable energy reviews, 14(2), 679-690. syzdykova, a., azretbergenova, g., massadikov, k., kalymbetova, a., sultanov, d. (2020), analysis of the relationship between energy consumption and economic growth in the commonwealth of ındependent states. international journal of energy economics and policy, 10(4), 318-324. tourkolias, c., mirasgedis, s. (2011), quantification and monetization of employment benefits associated with renewable energy technologies in greece. renewable and sustainable energy reviews, 15(6), 2876-2886. tugcu, c.t., ozturk, i., aslan, a. (2012), renewable and non-renewable energy consumption and economic growth relationship revisited: evidence from g7 countries. energy economics, 34(6), 1942-1950. zhao, x., luo, d. (2017), driving force of rising renewable energy in china: environment, regulation and employment. renewable and sustainable energy reviews, 68, 48-56. ziegelmann, a., mohr, m., unger, h. (2000), net employment effects of an extension of renewable-energy systems in the federal republic of germany. applied energy, 65(1-4), 329-338. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 4 • 2021276 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(4), 276-282. the relationship between gold and brent crude oil prices: an unrestricted vector autoregression approach izabela pruchnicka-grabias* warsaw school of economics, collegium of socio-economics, institute of banking, poland. *email: ipruch@sgh.waw.pl received: 20 february 2021 accepted: 28 april 2021 doi: https://doi.org/10.32479/ijeep.11229 abstract there is an ongoing scientific debate on how gold and crude oil affect each other prices. it is of high importance as both of them are strategic assets. the aim of the study is to check whether prices of these two assets influence each other. if so, if this is a short-term or a long-term relation and what the causality between these assets prices is. daily data from january 2005 to december 2020 are used. the author applies johansen cointegration test, granger causality test and var model, denies a long-term and confirms a short term relation between gold and crude oil prices. however, it goes only in one direction that is from gold to crude oil. such an interaction has significant consequences for investors, traders, producers, authorities, policymakers. keywords: var, gold, crude oil price, granger causality jel classifications: g15, c51, f37 1. introduction there is an ongoing scientific debate on how gold and crude oil affect each other prices. it is of high significance because of several reasons. first is that volatility of oil prices endangers industrial producers and consumers with the risk of offering their goods at unfair prices, as well as it can change their incentives to invest in production facilities. besides, volatility of crude oil prices is important for derivatives valuation and constructing hedging strategies as emphasized by pindyck (2003). crude oil is a special commodity as it significantly influences economic growth and activity in many countries (brown et al., 1995; jahangir and dural, 2018; he et al., 2010; difiglio, 2014; ftiti et al., 2016, arezki et al., 2017). furthermore, crude oil is thought to cause inflation (sek et al., 2015; brown et al., 1995; choi et al., 2017; zivkov et al., 2019). furthermore, gold plays a role of a safe haven and a hedge asset. goodman (1956) emphasizes that gold has a monetary status and is an international means of exchange and an inflation hedge, so its price fluctuations are very imnportant for participants of the economic process. salisu et al. (2020) show that gold can be also a hedge against crude oil price fluctuations. le and chang (2011) show that the price of gold can be a signal for high inflation expectations. sikiru and salisu (2021) argue that gold can play a role of a hedging instrument and safe haven for tourism stocks, especially during the covid-19 pandemic. it is both a precious metal and a monetary asset. during a crisis investors increase their risk aversion and they go buying it to save their assets or generate an additional income. however, taking into consideration the above described mechanisms, such transactions may have further consequences for the economy. a review of gold as an investment and its market efficiency is presented in o’connor et al. (2015). the aim of the study is to check the relationship between gold and crude oil prices. if it appears, if this is a short-term or a longterm relation and what the causality between these assets is. both gold and crude oil are an important part of commodity markets all over the word. so, it is desirable to check their relationship in order to be able to forecast the behavior of this significant part of the financial market. crude oil price is influenced by its supply and demand, economical political and ecological factors, as well as financial markets situation. since the johansen cointegration this journal is licensed under a creative commons attribution 4.0 international license pruchnicka-grabias: the relationship between gold and brent crude oil prices: an unrestricted vector autoregression approach international journal of energy economics and policy | vol 11 • issue 4 • 2021 277 equation shows no long-term relationship between crude oil and gold prices in the examined period of time, the author conducts granger causality test and develops a vector autoregresive model (var) to show the short-term dependence between crude oil prices and gold prices. the advantage of the paper is that examined and control variables which were used in the study let conclusions be valid both for european and american investors. there are many studies which apply wti crude oil to check the relations between gold and oil. this study is different for several reasons. the author uses the american index of 500 biggest companies and europe brent crude oil, as well as eurusd currency rate. such a choice of variables lets link the european and american markets together making conclusions to be applied to a wide variety of market participants. besides, using daily data which is not always possible because of their unavaibility lets capture even small fluctuations in the analyzed markets. what’s more, the chosen period of time 2005 – 2020 covers both the american crisis and the covid-19 crisis, as well as other cycles of the global economy. it lets make overall conclusions independent on the economic cycle. this problem is very important both for policymakers, traders, authorities, producers and investors. gold is a safe asset which means that during the crises investors buy it and increase its prices. if gold influences crude oil prices, it means that during such a time crude oil prices are increased because of investors buying the safe asset and it results in the price increase of costs of transport and rises prices in the economy, which makes the situation of participants of the economic process worse and deepens the crisis. besides, the knowledge of relations between gold and oil prices can help authorities monitor commodities markets. 2. literature review there exist many studies on the relationship of gold and crude oil prices, however their conclusions depend on methods applied, control variables chosen for the study, the research period, data frequency or the market examined. the cause for contradictory results may lie in different reactions of investors in different time of the economic reality which is shown by sheikh et al. (2020). conclusions on the relationship between gold and oil which are present in the literature can be generally divided into the following groups: • there is a long term relationship between gold and oil • there is a short-term relationship between gold and oil • there is both a long term and a short term relationship between gold and oil or authors do not concentrate on the length of the relation period. in each of the above defined groups, there are papers where the causality goes from gold to oil, from oil to gold or both. thus, it is undoubtful that there exists a relationship between gold and oil prices, however there is no unity concerning both the time and the direction of this dependence. in the first mentioned group, there is a paper prepared by simakova (2011) who uses monthly data for the period 1970 – 2010, confirms a high correlation of gold and crude oil returns and constructs the vecor error correction model (vec). the study shows that there is a long term relationship between oil prices and gold. gold and oil prices relations together with the stock market reflected by s&p index are investigated in gokmenoglua and fazlollahi (2015). authors use the ardl model with the error correction applied on daily observations for the period from january 2013 to november 2014, report moderate positive correlation between gold and oil prices and find out that there is a long term equilibrium between all these assets. stoklasova (2018) proves that in the long term gold influences crude oil prices, however the relation does not work in the opposite direction. the author uses monthly data between april 1983 and december 2016. narayan et al. (2010) confirmed a long-run relationship between gold and oil prices and any of these markets can be used to predict the behavior of another. in the second group, it is worth mentioning the research conducted by eryigit (2017) who constructs the vecm model which shows that there is no long-term relationship between gold and crude oil, however there is a short-term one. the research is conducted for different precious metals (gold, silver, platinum, palladium), crude oil and gas with the use of monthly data from july 1990 to february 2014. le and chang (2012/2013) conclude that there is no long-term relationship between gold and oil prices, but only a short term one. they apply the monthly data not only for gold and crude oil, but also for american dolar index, libor, world industrial production, world commodity price index, as well as msci global equity index between may 1994 and april 2011 and a multivariate var model. wang and chueh (2013) analyze relations between gold prices, crude oil prices, interest rate and american dolar. they summarize that gold and crude oil prices influence each other positively in both directions in the short period of time. galyfianakis et al. (2017) makes a vector auto regresive model with such variables as oil, gold, silver, us industrial production,, eurusd currency rate, as well as a 3-month interest rate and finds a short term relationship between crude oil and gold. wang et al. (2010) analyze dependencies among such variables as gold, crude oil, currency rates, and stock prices for such countries as united states, chaina, taiwam, japan and germany and conclude that there is no stable long-term relationship between gold and crude oil prices, however shortterm relations occur in taiwan. bildiricia and türkmenb (2015) confirm both short term and long-term relationship between crude oil and precious metals (also gold). they use monthly prices from january 1973 to november 2013 and construct nonlinear ardl model and causality tests. arfaoui and rejeb (2015) examine relations between gold, crude oil, stock market and american dollar and suggest that gold rate is influenced by crude oil and other factors. zhang and wei (2010) check the equillibrium between the gold and crude oil market using the data from the beginning of january 2000 to the end of march 2008. they conclude that there is a positive correalation between these two assets and that crude oil price influences the gold price volatility, however that this relationship does not work in a reverse direction. reboredo (2013) and toramana et al. (2011) stress the positive correlation between gold and crude oil. yıldırım et al. (2020) document effects going from oil to gold markets. pruchnicka-grabias: the relationship between gold and brent crude oil prices: an unrestricted vector autoregression approach international journal of energy economics and policy | vol 11 • issue 4 • 2021278 all in all, it is undisputable that gold and crude prices are correlated, although there is no unity on the direction of the impact. there are also different results concerning the time span in which these assets influence each other. if one considers the strategic role of gold and crude oil in the economy, it creates the need of further research in this field. 3. methodology and main statistics for examined variables the author uses daily rates of return for gold and europe brent crude oil prices. the following control variables were taken to build a model: quotations of the standard and poor’s 500 index (sp500) and eurusd currency rate. time period is from january 2005 to december 2020. gold is quoted in american dollars per ounce and prices are indexed since 1999. eurusd currency rates are fx close prices. standard and poor’s 500 are close prices. brent crude oil is quoted in american dollars per barrel. eurusd and sp500 come from the database: www.stooq.com. data concerning gold prices come from the world gold council. the source of the data on crude oil prices is thomson reuters (download from: www.eia.gov). the data were ordered and synchronized by adding the data for missing days under the assumption that if there was no quotation on the given day, the missing day is filled in by the value from the previous day. in most cases, missing days were days when for example there are public holidays in the united states and there are no stock quotations and at the same day the fx market is open and gold quotations are presented. table 1 summarizes the most important statistical features of variables. standard deviations show that crude oil is the most volatile asset of all. it is more than twice as much volatile as gold. the least volatile is eurusd currency rate whereas sp500 is only a little more volatile than gold and more than twice less volatile than crude oil. kurtosis for crude oil is much higher than for gold, so it is associated with higher risk than gold not only measured with standard deviation, but also with the fourth central moment of the distribution. nevertheless, both gold and crude oil have high kurtosis and negative skewness which can be interpreted as high risk. as data depicted in table 2 show, there exists statistically significant week correlation between rates of return on gold and crude oil, gold and eurusd, crude oil and eurusd, crude oil and sp500, as well as eurusd and sp500. there is no statistically significant correlation between rates of return on gold and sp500. although rather weak, however positive and significant correlation coefficient (0.1596) between crude oil and gold prices encourages to dwell on the relationship between these two assets. introductiory characteristics of these assets let conlcude that their skewness and kurtosis are far away from the normal distribution which makes their risk more difficult to monitor and knowledge on their interrelations may help to do it. 4. results and discussion 4.1. test of the unit root tests of the unit root for each of the data were conducted with the use of augmented dickey-fuller test (dickey and fuller, 1979; harris, 1992). the null hypothesis which is tested says that the data is non-stationary. results are depicted in table 3. all variable are stationary in i(0) without any doubts. next they are transformed to first logarithmic differences to check their stationarity. for all first differenced variables the null hypothesis should be rejected (table 4) which means that they are stationary in i(1). thus, considering the above presented results of the introductory analysis, there are indications to conduct the johansen cointegration test to check for long-term relations between examined variables. table 1: summary statistics for logarithmic daily returns crude oil percentiles smallest mean 0.0000455 5% –0.035797 –0.2563894 standard deviation 0.0269719 50% 0 largest variance 0.0007275 95% 0.0337062 0.3016126 skewness –2.52275 99% 0.0649383 0.4120225 kurtosis 106.2913 gold percentiles smallest mean 0.0003462 5% –0.0175706 –0.0797019 standard deviation 0.0112626 50% 0.000061 largest variance 0.0001268 95% 0.0175857 0.0601371 skewness –0.3736183 99% 0.0305836 0.0684235 kurtosis 8.499098 eurusd percentiles smallest mean –0.000026 5% –0.0091655 –0.0267329 standard deviation 0.0058172 50% 0.0000754 largest variance 0.0000338 95% 0.0093078 0.0319846 skewness 0.05828 99% 0.0153686 0.0341572 kurtosis 5.469529 sp500 percentiles smallest mean 0.0002682 5% –0.0182622 –0.0999449 standard deviation 0.0122825 50% 0.0004159 largest variance 0.0001509 95% 0.0162332 0.1024573 skewness –0.5696868 99% 0.0337102 0.109572 kurtosis 17.64599 table 2: correlation table for logarithmic rates of returns crude oil gold eurusd sp500 crude oil 1 0.1596 (p=0.0000) 0.1178 (p=0.0000) 0.2435 (p=0.0000) gold 0.1596 (p=0.0000) 1 0.2455 (p=0.0000) 0.0209 (p=0.1781) eurusd 0.1178 (p=0.0000) 0.2455 (p=0.0000) 1 0.2200 (p=0.0000) sp500 0.2435 (p=0.0000) 0.0209 (p=0.1781) 0.2200 (p=0.0000) 1 table 3: results of unit root tests for variables in i(0) variable adf test statistics 5% critical value p-value stationarity crude oil –1.926 –2.860 0.3201 non-stationary gold –1.329 –2.860 0.6160 non-stationary eurusd –1.961 –2.860 0.3041 non-stationary sp500 0.567 –2.860 0.9868 non-stationary pruchnicka-grabias: the relationship between gold and brent crude oil prices: an unrestricted vector autoregression approach international journal of energy economics and policy | vol 11 • issue 4 • 2021 279 4.2. johansen cointegration test in order to test a long term relationship between crude oil and gold prices the author uses johansen cointegration test. it can be conducted when all variables are non-stationary at i(0) and stationary in i(1) (johansen, 1988), which is fulfilled for all examined variables. it is widely used in the scientific literature for checking long term relations (hjalmarsson and osterholm, 2007; wang and wu, 2013; naser, 2017; naidu et al., 2017). johansen cointegration test is done with the use of two statistics to make it more reliable. these are trace statistics and max statistics. the null hypothesis is that there is no cointegration. the alternative hypothesis for rank zero says that there are zero cointegration equations. the alternative hypothesis for rank 1 says that there is one cointegration equation. the alternative hypothesis for rank 2 or more says that there are two or more cointegration equations. results of johansen cointegration test are depicted in table 5. trace statistics and max eigenvalue statistics indicate that for zero cointegration equations the null hypothesis should be accepted. thus, there is no cointegration between crude oil and gold prices. such results suggest that we cannot confirm long term relationships between examined variables. it means that the proper model to examine the existence of short term relations among variables is unrestricted vector autoregression model (var). 4.3. selection of the optimum number of lags the optimum number of lags for each asset was selected according to akaike’s information criterion – aic (akaike, 1974). the following numbers of lags were indicated: crude oil – 2 lags, gold – 1 lag, eurusd – 1 lag, sp500 – 4 lags. 4.4. unrestricted vector autoregression var model in order to build an unrestricted vector autregression var model, it is necessarry that variables are instationary at level and stationary at first order with no cointegration. these conditions are fulfilled, so var model will be a good model to examine relations between crude oil and gold. the optimum number of lags shown by aike’s information criterion for crude oil is 2 and for gold is 1. so, for var model to assure its utility a higher number is taken. var model which is assessed in the paper is: crudeoil = α0+ α1crudeoil (l1)+α2crudeoil (l2)+ α3gold (l1)+α4gold (l2)+α5eurusd (l1)+α6eurusd (l2)+α7 sp500 (l1)+α8 sp500 (l2)+ξ1t (1) gold = α9+α10crudeoil (l1)+α11crudeoil (l2)+α12gold (l1)+α13gold (l2)+α14eurusd (l1)+α15eurusd (l2)+α16sp500 (l1)+α17sp500 (l2)+ξ2t (2) table 5: results of johansen cointegration test rank eigenvalue trace statistics 5% critical value for trace statistics max statistics 5% critical value for max statistics 0 67.9615 68.52 33.1518 33.46 1 0.00794 34.8097 47.21 19.1638 27.07 2 0.00459 15.6459 29.68 10.9903 20.97 3 0.00264 4.6557 15.41 4.3511 14.07 4 0.00105 0.3046 3.76 0.3046 3.76 table 4: results of unit root tests for variables in i(1) variable adf test statistics 5% critical value p-value stationarity diffcrude oil –65.574 –2.860 0.0000 stationary diffgold –64.559 –2.860 0.0000 stationary diffeurusd –64.853 –2.860 0.0000 stationary diffsp500 –74.417 –2.860 0.0000 stationary eurusd = α18+α19crudeoil (l1)+α20crudeoil (l2)+α21gold (l1)+α22gold (l2)+α23eurusd (l1)+α24eurusd (l2)+α25 sp500 (l1)+α26sp500 (l2)+ ξ3t (3) sp500 = α27+α28crudeoil (l1)+α29crudeoil (l2)+α30gold (l1)+α31gold (l2)+α32eurusd (l1)+α33eurusd (l2)+α34sp500 (l1)+ α35sp500 (l2)+ξ4t (4) where: α0, α1 … α35 – model structural parameters ξ1t…ξ4t – random errors parameters of var model are depicted in table 6. the var model shows that gold significantly influences crude oil in l2. the relation between these two variables is positive. however crude does not influence gold in any of lags. further conclusions will be drawn from granger causality test showing the direction of relations. 4.5. var diagnostics and granger causality test a widely accepted method of checking the direction of the dependence between variables often applied in the scientific literature is granger causalilty test (granger, 1969). it means that the present value of some variable is determined by past values of some other variables. it is applied here to determine mutual twoway interactions between crude oil and gold prices. so, in short, granger causality test requires sationary variables, so all variables were transformed into logarithmic first differences and used in such a form. the test confirms that there is a short run relationship going from gold to crude oil and there is no relationship in the opposite direction. the null hypothesis which is tested is that independent variable does not cause dependent variable. the alternative hypothesis is that independent variable causes dependent variable. apart from that, granger causality suggests causality going from gold and crude oil markets to the stock market, from stock market to crude oil, from currency market to gold market, from gold to currency market and vice versa. although these relations are not a subject of this study, it should be amphasized that they are worth further analysis. details are shown in table 7. granger causality test proves with p = 0.002 that gold prices influence crude oil prices in the short run. there is no dependence going in the opposite direction (p = 0.556). granger test confirms that the constructed unrestricted var model is well suited. pruchnicka-grabias: the relationship between gold and brent crude oil prices: an unrestricted vector autoregression approach international journal of energy economics and policy | vol 11 • issue 4 • 2021280 table 7: granger causality wald test results equation excluded chi2 df prob>chi2 crude oil gold 12.575 2 0.002 eurusd 2.2431 2 0.326 sp500 18.199 2 0.000 all 33.549 6 0.000 gold crude oil 1.1754 2 0.556 eurusd 101.83 2 0.000 sp500 .68128 2 0.711 all 115.21 6 0.000 eurusd crude oil 3.4018 2 0.183 gold 6.2452 2 0.044 sp500 3.5676 2 0.168 all 13.445 6 0.036 sp500 crude oil 11.233 2 0.004 gold 21.46 2 0.000 eurusd 5.8901 2 0.053 all 42.1 6 0.000 table 6: var model results variable and its lags coefficient standard error z p>|z| dependent variable: crude oil crude oil l1 –0.0379787 0.016196 –2.34 0.019 crude oil l2 –0.0590858 0.0161219 –3.66 0.000 gold l1 0.022516 0.0391152 0.58 0.565 gold l2 0.1362481 0.0386466 3.53 0.000 eurusd l1 0.0642059 0.0759442 0.85 0.398 eurusd l2 –0.0904803 0.0767991 –1.18 0.239 sp500 l1 0.1546812 0.0362717 4.26 0.000 sp500 l2 0.0223796 0.0363066 0.62 0.538 constant –0.0000585 0.0004167 –0.14 0.888 dependent variable: gold crude oil l1 0.0072566 0.0067057 1.08 0.279 crude oil l2 –0.0001557 0.006675 –0.02 0.981 gold l1 –0.0453256 0.016195 –2.80 0.005 gold l2 –0.0103876 0.0160009 –0.65 0.516 eurusd l1 0.3171513 0.0314433 10.09 0.000 eurusd l2 0.0112343 0.0317973 0.35 0.724 sp500 l1 0.0096296 0.0150177 0.64 0.521 sp500 l2 0.0093415 0.0150321 0.62 0.534 constant 0.0003733 0.0001725 2.16 0.031 dependent variable: eurusd crude oil l1 0.0010194 0.003504 0.29 0.771 crude oil l2 0.0063874 0.003488 1.83 0.067 gold l1 0.0173857 0.0084626 2.05 0.040 gold l2 0.0128275 0.0083612 1.53 0.125 eurusd l1 –0.018015 0.0164305 –1.10 0.273 eurusd l2 –0.0136351 0.0166155 –0.82 0.412 sp500 l1 0.0084408 0.0078474 1.08 0.282 sp500 l2 –0.0105768 0.0078549 –1.35 0.178 constant –0.0000337 0.0000902 –0.37 0.708 dependent variable: sp500 crude oil l1 0.0016783 0.007303 0.23 0.818 crude oil l2 0.0243542 0.0072696 3.35 0.001 gold l1 –0.0375034 0.0176377 –2.13 0.033 gold l2 0.0695637 0.0174263 3.99 0.000 eurusd l1 0.0821905 0.0342444 2.40 0.016 eurusd l2 –0.006984 0.0346299 –0.20 0.840 sp500 l1 –0.1497507 0.0163555 –9.16 0.000 sp500 l2 –0.0184131 0.0163712 –1.12 0.261 constant 0.0003074 0.0001879 1.64 0.102 another important step of the model diagnostics is to check the autocorrelation of residuals. it is done with two tests that is with ljung-box (improved portmaneau) statistics (ljung and box, 1978) and lagrange multiplier test. table 8 summarizes the results. table 8: unrestricted var model diagnostics portmanteau statistics 0.0313 prob>ch2 0.9845 aic criterion –24.20816 chi2, l1 20.3803 prob>ch2, l1 0.20358 chi2, l2 19.1594 prob>ch2, l2 0.26049 ac< l1 0.0021 pac, l1 0.0021 q, l1 0.01766 prob>q, l1 0.8943 ac< l2 0.0018 pac, l2 0.0018 q, l2 0.03127 prob>q, l2 0.9845 in both tests the tested null hypothesis is that there is no autocorrelation. the alternative hypothesis is that there is autocorrelation. both tests show that there are no fundamentals to reject the null hypotheses. correlogram was also run for autocorrelation (ac) and partial autocorrelation (pac) showing the same conclusions. thus it is confirmed that residuals are not autocorrelated which means that they are white noise which is required for the well fitted model. 5. conclusion gold and crude oil play a special role on financial markets. gold is a monetary asset, hedge asset and safe haven. crude oil influences economic growth. the overall effect of this process depends also on mutual interrelations between these two assets, which is why the author decided to analyze them. another stimuli for the study were contradictory conclusions on relations between gold and crude oil prices and their causality. the research question is if crude oil prices depend on gold prices. if so, is it a long term relation or a short term relation and in which direction it works? the conducted research shows that gold prices influence crude oil prices in the short run, however the relations does not work in the opposite direction. besides, the research shows that there are no relations between these assets in the long period of time. however, such fluctuations, even in the short run may be dangerous if the situation of rising gold prices lasts for a long period of time, which often happens during a crisis when investors shift their assets into safe haven. the study suggests that it would be desirable to look for other kinds of safe assets than gold to avoid deepening the crises more than necessary. the research has a wide influence as it gives implications for investors, traders, producers, authorities and policymakers. knowing relations and the causality between crude oil and gold prices lets monitor their risk in a more efficient way, which should have a positive effect on the whole economy. although the relation is only short term, if the crisis lasts for a long time, crude oil prices resulting from rising gold prices may last for a long time and deteriorate the economy in the long run. another advantage of the study is that examined and control variables which were used here let conclusions be valid both for european and american investors. there are many studies which apply wti crude oil to check the relations between pruchnicka-grabias: the relationship between gold and brent crude oil prices: an unrestricted vector autoregression approach international journal of energy economics and policy | vol 11 • issue 4 • 2021 281 gold and oil. this study is different for several reasons. the author uses gold and europe brent crude oil prices, as well as control variables such as eurusd currency rate and the american index of 500 biggest companies. such a choice of variables lets link the european and american markets together making conclusions to be applied to a wide variety of market participants. furthermore, the analyzed time period between 2005 and 2020 covers both the american crisis and the covid-19 crisis, as well as other cycles of the global economy. it lets draw general conclusions independent on the economic cycle. the research is consistent with for example such studies as eryigit (2017), le and chang (2012/2013). nevertheless, it gives new conclusions compared to studies by simakova (2011), (gokmenoglua and fazlollahi, 2015), stoklasova (2018), both concerning the time of dependencies between gold and crude oil as well as their direction. the research conduced by the author confirms some literature results and denies some other. different conclusions in different studies may be caused by different study periods, methods, control variables or behavior of market participants in different economic conditions. thus, further research could comprise the dynamic study on changes of gold and crude oil prices relations during different periods of time depending on gold or oil market trends. references akaike, h. (1974), a new look at the statistical model identification. ieee transactions on automatic control, 19(6), 716-723. arezki, r., jakab, z., laxton, d., matsumoto, a., nurbekyan, a., wang, h. and yao, j. (2017), oil prices and the global economy, imf working paper, international monetary fund. p1-30. arfaoui, m., rejeb, a.b. (2015), oil, gold, us dollar and stock market interdependencies: a global analytical insight. european journal of management and business economics, 26(3), 278-293. available from: http://www.stooq.com; http://www.gold.org; http://www. eia.gov. [last accessed on 2021 feb]. bildiricia, m., türkmenb, c. (2015), the chaotic relationship between oil return, gold, silver and copper returns in turkey: non-linear ardl and augmented non-linear granger causality. procedia social and behavioral sciences, 210, 397-407. brown, s.p.a., oppedahl, d.b., yucel, m.k. (1995), oil prices and inflation, research department working paper, no. 95-10, federal reserve bank of dallas. p1-28. choi, s., furceri, d., loungani, p., mishra, s., poplawski-ribeiro, m. (2017), imf working paper, international monetary fund, p1-55. dickey, d.a., fuller, w.a. (1979), distribution of the estimators for autoregressive time series with a unit root. journal of the american statistical association, 74, 427-431. difiglio, c. (2014), oil, economic growth and strategic petroleum stocks. energy strategy reviews, 5, 48-58. eryigit, m. (2017), short-term and long-term relationships between gold prices and precious metal (palladium, silver and platinum) and energy (crude oil and gasoline) prices. economic research-ekonomska istraživanja, 1, 499-510. ftiti, z., guesmi, k., teulon, f., chouachi, s. (2016) relationship between crude oil prices and economic growth in selected opec countries. the journal of applied business research, 32(1), 11-22. galyfianakis, g., garefalakis, a., mantalis, g. (2017), the effects of commodities and financial markets on crude oil. ifp energies nouvelles, 72(3), 1-10. gokmenoglua, k.k., fazlollahi, n. (2015), the interactions among gold, oil, and stock market: evidence from s&p500. procedia economics and finance, 25, 478-488. goodman, b. (1956), the price of gold and international liquidity. journal of finance, 11(1), 15-28. granger, c.w.j. (1969), investigating causal relations by econometric models and cross-spectral methods. econometrica, 37(3), 424-438. harris, r.i.d. (1992), testing for unit roots using the augmented dickeyfuller test: some issues relating to the size, power and the lag structure of the test. economics letters, 38(4), 381-386. he, y., wang, s., lai, k.k. (2010), global economic activity and crude oil prices: a cointegration analysis. energy economics, 32(4), 868-876. hjalmarsson, e., osterholm, p. (2007), testing for cointegration using the johansen methodology when variables are near-integrated, imf working paper, wp/07/141, international monetary fund. p1-21. jahangir, s.m.r., dural, b.y. (2018) crude oil, natural gas, and economic growth: impact and causality analysis in caspian sea region. international journal of management and economics, 54(3), 169-184. johansen, s. (1988), statistical analysis of cointegration vectors. journal of economic dynamics and control, 12(2-3), 231-254. le, t.h., chang, y. (2011), dynamic relationships between the price of oil, gold and financial variables in japan: a bounds testing approach, mpra paper 33030. germany: university library in munich. p1-30. le, t.h., chang, y. (2012/2013), oil price shocks and gold returns. economie internationale, 131, 71-103. ljung, g.m., box, g.e.p. (1978), on a measure of a lack of fit in time series models. biometrika, 65(2), 297-303. naidu, s., pandaram, a., chand, a. (2017) a johansen cointegration test for the relationship between remittances and economic growth of japan. modern applied science, 11(10), 137-151. narayan, p.k., narayan, s., zheng, x. (2010), gold and oil futures markets: are markets efficient? applied energy, 87(10), 3299-3303. naser, h. (2017), on the cointegration and causality between oil market, nuclear energy consumption, and economic growth: evidence from developed countries. energy, ecology and environment, 2, 182-197. o’connor, f., lucey, b., batten, j., baur, d.g. (2015), the financial economics of gold-a survey. international review of financial analysis, 41(c), 186-205. pindyck, r.s. (2003), volatility in natural gas and oil markets. cambridge, ma: massachusetts institute of technology. p1-19. reboredo, j.c. (2013), is gold a hedge or safe haven against oil price movements. resources policy, 38(2), 130-137. salisu, a.a, vo, x.v., lewal, a. (2020), hedging oil price risk with gold during covid-19 pandemic. resources policy, 2020, 101897. sek, s.k., teo, x.q., wong, y.n. (2015), a comparative study on the effects of oil price changes on inflation. procedia economics and finance, 26, 630-636. sheikh, u.a., asad, m., ahmed, z., mukhtar, u. (2020), asymmetrical relationship between oil prices, gold prices, exchange rate, and stock prices during global financial crisis 2008: evidence from pakistan. cogent economics and finance, 8(1), 1-21. sikiru, a.a., salisu, a.a. (2021) hedging against risks associated with travel and tourism stocks during covid-19 pandemic: the role of gold. international journal of financial economics, 2021, 2513. simakova, j. (2011), analysis of the relationship between oil and gold prices. journal of finance, 51(1), 651-662. stoklasova, r. (2018) short-term and long-term relationships between gold prices and oil prices. vol. 43. scientific papers of the university of pardubice, series d, faculty of economics and administration, pardibuce. p221-231. toramana, c., basarirb, c, bayramoğlu, m.f. (2011), determination of factors affecting the price of gold: a study of mgarch model. business and economics research journal, 2(4), 37-50. pruchnicka-grabias: the relationship between gold and brent crude oil prices: an unrestricted vector autoregression approach international journal of energy economics and policy | vol 11 • issue 4 • 2021282 wang, m.l., wang, c.p., huang, t.y. (2010), relationships among oil price, gold price, exchange rate and international stock markets. international research journal of finance and economics, 47(47), 1450-2887. wang, y., wu, c. (2013), are crude oil spot and futures prices cointegrated? not always! economic modelling, 33, 641-650. wang, y.s., chueh, y.l. (2013), dynamic transmission effects between the interest rate, the us dollar, and gold and crude oil prices. economic modelling, 30(c), 792-798. yıldırım, d.c., cevik, e.i., esen, o. (2020), time-varying volatility spillovers between oil prices and precious metal prices. resources policy, 68(c), 101783. zhang, y.j., wei, y.m. (2010), the crude oil market and the gold market: evidence for cointegration, causality and price discovery. resources policy, 35(3), 168-177. zivkov, d., duraskovic, j., manic, s. (2019), how do oil price changes affect inflation in central and eastern european countries? a waveletbased markov switching approach. baltic journal of economics, 19(1), 84-104. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 3 • 2022 441 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(3), 441-450. consumer preference for energy label in the purchase decision of refrigerator: a discrete choice experiment approach in the east coast, malaysia muhammad azrin shah razali, mahirah kamaludin*, a. a. azlina universiti malaysia terengganu, malaysia. *email: mahirah.k@umt.edu.my received: 18 february 2022 accepted: 29 april 2022 doi: https://doi.org/10.32479/ijeep.13063 abstract energy label is a widely used policy instrument to increase consumer awareness of energy-efficient home appliances. it helps consumers make better informed purchasing decision intending to save on the electricity bill. the increase in energy efficiency for a household can generate significant energy savings and emissions reduction which can reduce environmental impact. the energy label targets to fight climate change, protect the environment and is significant to support sustainable development goals (sdgs). this study presents the results of a discrete choice experiment (dce) on the east coast, malaysia to investigate the consumer preferences for energy label in the purchasing decision of a refrigerator. multinomial logit (mnl) and mixed logit (ml) models are specified to measure the attributes that consumers assess when choosing refrigerators. this study focuses on four attributes, namely energy star, energy consumption, energy saving and refrigerator price. findings show that consumers have responded positively to the labels, in which about 88.11% of respondents are willing to pay to get better quality appliances that promote a safe environment while 11.89% of respondents are not willing to pay. the findings are useful in improving the effectiveness of existing energy efficiency and labelling programs to accelerate the adoption of energy-efficient technology in malaysia. hence, the implementation of energy label promotes energy-efficient appliances, which is in line with sdg goal 7: ensuring access to affordable, reliable, sustainable, and modern energy for all. keywords: energy efficient, energy label, discrete choice experiment, refrigerator, sustainable development goals, malaysia jel classifications: q0, q40, q49 1. introduction developing low-carbon technologies is crucial to achieving international climate mitigation goals (van et al., 2018). the differences in the responses to categories of energy efficiency (ee) on labels studied so far is likely to be biased due to interattribute correlation in the experiment design (sammer and wüstenhagen, 2006; jeong and kim, 2015). renewable energy and energy-efficient technologies are among those critical aspects in addressing several energy-related challenges, mostly in emerging economies. after the oil crisis in the 1970s, countries with developed economies responded by implementing several policies to promote energy-efficient technologies (saidel and alves, 2003). establishing energy performance standards and labels push the market by eliminating the least efficient appliances. the ee standards and labels are being established internationally, as a simple and effective strategy for guiding consumers in their purchases of household appliances. the minimum energy performance standards (meps) prohibit manufacturers from selling products with lower efficiency, below a specified level. these appliance labels inform consumers about the energy consumption or energy efficiency of appliances. the meps program aims to ban the production and sales of low-efficiency products to phase-out low-efficiency products from the market. it means that, to sell their products in the market, manufacturers this journal is licensed under a creative commons attribution 4.0 international license razali, et al.: consumer preference for energy label in the purchase decision of refrigerator: a discrete choice experiment approach in the east coast, malaysia international journal of energy economics and policy | vol 12 • issue 3 • 2022442 must meet the minimum efficiency level set by the standards. furthermore, according to mahlia et al. (2003) energy-efficient appliances can reduce energy consumption and consumers’ utility bills, as well as helping the country from becoming a dumping site for inefficient electrical appliances. besides, the implementation of ee label may indirectly combat co2 emission and mitigate global warming. by establishing energy efficiency and co2 emissions reductions at every stage of production and process, those appliances offer a more effective solution with a lower carbon footprint, assisting the consumers in meeting their sustainability objectives. hence, the societies’ commitments and actions are in line to attain goals in sustainable development goals (sdg). arrow et al. (1996) stated that in the prior stage of economic growth, people in poorer countries tend to emphasise material well-being over environmental amenities and assume increased pollution as a side effect of economic growth. when per capita income in a nation or a region attains a certain point, people start demonstrating more interest in environmental protection. therefore, that was when the environmental conservation policies began in developed countries. the rise in average income and quality of people’s lives has led to greater demand for household appliances, resulting in higher consumption of electricity among households and an increased carbon dioxide (co2) emissions from the production and consumption processes. developed countries that have higher income levels proportionate more to co2 emission. table 1 illustrates the gross domestic product (gdp) and co2 emission by current income status for the selected asia pacific and asean countries in 2018. developed nations with higher incomes like singapore, japan and south korea have greater demand for energy consumption, causing higher carbon emissions when compared to other developing countries. table 1 demonstrates that the reduce in carbon emissions is an urgent issue globally. many previous studies have employed the decomposition method to investigate the driving factors of carbon emissions with comparative analyses between countries, such as china, usa, uk, greece, turkey, and south korea (zhao et al., 2016; hammond and norman, 2012; freitas and kaneko, 2011; akbostancı et al., 2011; oh et al., 2010). however, most previous studies have analysed carbon emissions at the national level only due to the limited number of reliable co2 emission data available. for example, lee and oh (2006) used a cross-sectional decomposition method to analyse the co2 emissions in apec countries. fernandez gonzález et al. (2014b) examined changes in co2 emissions in the eu at the country level and identified diverse patterns in large and small economies. according to xu et al. (2016), the possibilities of achieving the national carbon reduction target depend on the implementation of regional carbon reductions. to achieve the co2 reduction targets, the national emission reduction targets are often allocated to various provinces or states. the industrial structure has an impact on air quality. the proportion of gdp is contributed by primary industries, which make direct use of natural resources, secondary industries, which produce manufactured goods, and tertiary industries, which generate services that affects air quality to a different degree. it has been indicated that primary and secondary industries, occupying a great portion of the gdp, have a significant correlation with air quality (jiang et al., 2014). for instance, the manufacturing sector fundamentally contributes to industrialisation and development in cities and has a significant positive correlation with the average air pollution index (api) data (zhang et al., 2011; shi, 2014). taghizadeh-hesary and taghizadeh-hesary (2020) stated that carbon emissions are one of several contributions to air pollution. hence, as illustrated in table 2, it can be seen the gdp of states proportionate to quality of api in peninsular malaysia for the year 2016. the states with higher gdp tend to contribute more to the increase in api. selangor, kuala lumpur and johor are the focal points of various manufacturing industries that recorded the worst air pollution with 115, 112 and 102 respectively, these index are unhealthy for sensitive groups with big concern (air pollutant index of malaysia, 2018). thus, energy efficiency policy and legislation are necessary to avoid the overconsumption of energy resources caused by developed nations. although not all developed countries’ energy-efficiency policies can be followed by developing countries, ee label is one of the most common solutions for many countries that guide consumers to purchase an efficient appliance (association of water and energy research malaysia, 2012). abu saleh et al. (2011) highlighted that implementing ee label table 1: gdp and co2 emission indicators for selected asia pacific and asean countries in 2018 current income status country gdp per capita (million us$) co2 emissions per capita (metric tons) high income singapore 66,679.046 8.399 japan 39,808.169 8.742 south korea 33,422.944 12.225 upper middle income malaysia 11,380.082 7.6 thailand 9,905.342 3.714 china 7,296.880 7.352 lower middle income indonesia 3,893.860 2.178 india 1,996.915 1.8 lower income cambodia 1,512.127 0.687 source: data.worldbank.org. table 2: gdp and api for states in peninsular malaysia regions in peninsular malaysia states in peninsular malaysia gdp for 2016 (rm million) api for 2016 minimum maximum central region kuala lumpur 190,075 10.0 112.0 selangor 280,698 2.0 115.0 negeri sembilan 42,389 7.0 96.0 northern region penang 81,284 2.0 84.0 perak 67,629 2.0 95.0 kedah 40,596 4.0 96.0 perlis 5,642 1.0 76.0 east coast region pahang 52,452 2.0 82.0 terengganu 32,270 1.0 84.0 kelantan 23,020 1.0 74.0 southern region johor 116,679 6.0 102.0 malacca 37,274 12.0 86.0 source: www.apims.doe.gov.my razali, et al.: consumer preference for energy label in the purchase decision of refrigerator: a discrete choice experiment approach in the east coast, malaysia international journal of energy economics and policy | vol 12 • issue 3 • 2022 443 on cloth washers would likely urge manufacturers to produce energy-efficient products and boost competition in the local and international markets. it encourages companies to develop and invest in energy-efficient product design (ward et al., 2011). table 2 also shows that the east coast region has recorded the lowest api compared to other regions of peninsular malaysia. the east coast region plays a very important role in preserving the environment in peninsular malaysia. the economic region of the east coast includes three states and one district which is very large with an area of 51% of the area of peninsular malaysia, namely terengganu, kelantan, and pahang as well as the district of mersing. figure 1 shows the area of the east coast of peninsular malaysia. according to the past literature on stated preferences, fewer papers have focused on the effects of energy label based on the willingness to pay (wtp). most past studies examined consumers’ additional wtp for energy-efficient products employed stated preference techniques, such as contingent valuation (cv) and choice experiment (ce). the impacts of label on consumers’ decisions have been extensively studied in the literature using questionnaire-based studies, econometric models, and discrete choice analysis. jain et al. (2018), highlighted that in questionnaire-based studies, respondents were directly asked about their wtp for label and higher efficiency. elicitation of consumers’ wtp for labelled appliances and energy-efficient appliances using questionnaire-based surveys indicated positive responses but produced a large range of estimates (zheng et al., 2014; dhingra, 2016). discrete choice experiments (dce) have been used in several studies to elicit consumer preference from the stated preference data (sammer and wüstenhagen, 2006; shen and saijo, 2009; jeong and kim, 2015; jain et al., 2018). in the short and medium-term, technology policies would be essential in energy and climate-related policy portfolios (meckling, 2018). carbon pricing policies, such as a carbon tax and cap and trade regulation are mandatory in increasing the diffusion of these technologies in the long term. several studies have reported that the ee standards and labels program was an effective policy intervention and has contributed to energy and emission reduction (meyers et al., 2003; lane et al., 2007; tao and yu, 2011). studies using econometric and statistical models on market data gave robust results, yet they had large data requirements and were likely to suffer from unobserved factors in consumer choices (galarraga et al., 2011; mills and schleich, 2010). the household choices were observed in hypothetical choice situations. the literature studies suggest that the ee labelling has already been implemented in households’ appliances in more than 50 countries globally before the voluntary and mandatory environmental or energy certification schemes were gradually introduced in the early 1990s (wong and kruger, 2017). energy labelling has become more common in marketplaces all around and offered considerable promise for reducing the financial costs and environmental damages associated with energy use (gerarden et al., 2017). standardization procedures and ee labelling can create awareness in using energy efficiently among consumers. a growing number of studies have used dce to value household preferences on energy efficiency and labelling improvement. table 3 provides an overview of the key findings of various dce studies on energy label attributes for both developed and developing countries. these studies use consumers’ wtp of energy label attributes to value preferences for energy efficiency and labelling improvement. one of the earliest studies using dce for energy label attributes is the study by moxnes (2004) in norway. the dce was used to estimate utility functions for individuals that have recently bought a refrigerator. the researcher used four attributes in the study: (1) inside volume; (2) height; (3) energy cost; and (4) price of the refrigerator. the study found that energy efficiency standards and labels could lead to an increase utility for the average customer. the study considered the attribute price as a sensitive detail of the findings. hence, the price of the most efficient refrigerators must drop by 15% to prevent reductions in average utility. sammer and wüstenhagen (2006) presented an empirical data on the influence of ecolabels on consumer behaviour for household appliances. the study reported the results of a survey involving 151 choice-based conjoint interviews conducted in switzerland in 2004. choice-based conjoint analysis (also known as a discrete choice) was applied to reveal the relative importance of various product attributes for consumers. the study used six attributes: (1) brand; (2) equipment version; (3) water consumption; (4) energy consumption; (5) energy efficiency rating; and (6) price. the analysis showed that brands were important. the wtp for a premium brand compared with a no-name product was about figure 1: east coast region in peninsular malaysia source: www.ecerdc.com.my razali, et al.: consumer preference for energy label in the purchase decision of refrigerator: a discrete choice experiment approach in the east coast, malaysia international journal of energy economics and policy | vol 12 • issue 3 • 2022444 a 50% premium. the result was relevant to manufacturers of energy-efficient appliances since it provided them with quantitative information for comparing investments in brand value versus in research and development for energy-efficient appliances. shen and saijo (2009) conducted a hypothetical choice experiment in shanghai, china with 1200 observations. the study examined whether the china energy efficiency label could influence consumers’ choices of air conditioners and refrigerators. a latent class approach was applied to observe both heterogeneities among the respondents and product brands. the study used eight attributes: (1) energy consumption; (2) cooling space; (3) capacity; (4) air purifier function; (5) noise reduction; (6) energy efficiency ranks on the labels; (7) labels indicating the savings in electric bills and (8) price. the results suggested that consumers in shanghai were aware of the china energy efficiency label and tended to pay more attention to air conditioners rather than refrigerators with such labels. in addition, air conditioners and refrigerators affixed with a hypothetical label that indicated savings in the electricity bills compared with a standard model received significant preferences, which suggested that the more information manufacturers provided, the more of their products would be preferred by consumers. jeong and kim (2014) used a dce approach to investigate the effects of energy efficiency and environmental labels on households’ choice of appliances. this paper found that most households showed a positive preference for labelled appliances, and an intention to pay more to purchase appliances with energy efficiency. two appliances were selected in this study; refrigerator and laptop, because both appliances were typical electrical appliances used at homes, compared to other household appliances. the results suggested implications for both the government and manufacturers. the south korean government was recommended to expand the number of product types that were required to participate in the labelling program to further promote green technologies. the results showed that consumers learned the information about energy efficiency with reasonable monetary value, hence improving the energy efficiency of the products will increase the mwtp of the consumers, thus increasing the demand. in this sense, manufacturers should concentrate on improving energy-efficiency grades and acquiring environmental labels for their products. one of the more recent studies conducted in the largest developing country is a study by zhou and bukenya (2016). they examined the extent to which consumers’ wtp for energy-efficient room air conditioners might be altered by correcting the information inefficiency on the china energy label. the data were collected using the dce approach that was distributed randomly to 1602 potential consumers in nanjing, china and a sample of 1569 was obtained. this study used four attributes: (1) brand; (2) energy grade; (3) type of room air conditioner; and (4) price. the analysis with multinomial and mixed logit models revealed that the price premium that consumers were willing to pay increased significantly when energy consumption information became comparable and additional energy-related information was provided. jain et al. (2018) used the dce method to describe consumers’ choices in the hypothetical purchase of an air conditioner and a refrigerator. the data were collected from households’ survey in face-to-face interviews from the suburban district in mumbai. the valid responses from a total of 149 households for air conditioners and 153 households for refrigerators were obtained. this study used separated attributes for the air conditioner and refrigerator. for air conditioner: (1) brand; (2) star; (3) air filters; (4) noise level; and (5) price of the air conditioner. for refrigerator: (1) brand; (2) star; (3) freezer spaces; (4) deodorizer; and (5) price of the refrigerator, indicating that consumers responded positively to labels. the implicit value placed by consumers in the highest energy efficiency category was found to be within the 95% confidence level in both appliances. these findings contrasted with the results reported by shen and saijo (2009) who found that consumer wtp for energy efficiency ranked more in air conditioners than refrigerators. literature review shows that many studies have performed a conjoint survey to obtain stated preference data, and discrete choice models, especially the mixed logit model, which have been widely used to examine the preference structure for labelled appliances. moreover, refrigerators have been chosen as a research topic in many studies for a fact that refrigerator is the most common appliance that typically owned by majority households, when compared to other household appliances. in malaysia, 96% of table 3: review of several dce studies on energy efficiency label attributes author (s) study site key findings moxnes (2004) norway energy efficiency standards and labels could lead to an increased utility for the average customer. attribute price was considered as the most important element of the findings. sammer and wüstenhagen (2006) switzerland consumers preferred premium brands compared to a no-name product. relevant for manufacturers to invest in brand value or in research and development (r&d) for energy-efficient appliances. shen and saijo (2009) china consumers tended to pay more attention to air conditioners rather than refrigerators. jeong and kim (2014) south korea consumers showed a positive preference for labelled appliances, and an intention to pay more to purchase appliances with energy efficiency. zhou and bukenya (2016) china price that consumers were willing to pay increased significantly when energy consumption information became comparable. jain et al. (2018) india the implicit value placed by consumers on the highest energy efficiency category was found to be within the 95% confidence level in both appliances; air conditioner and refrigerator. source: authors’ own research. razali, et al.: consumer preference for energy label in the purchase decision of refrigerator: a discrete choice experiment approach in the east coast, malaysia international journal of energy economics and policy | vol 12 • issue 3 • 2022 445 households own a refrigerator in their home, and this percentage is the highest among other household appliances (khazanah research institute, 2014). 1.2. energy-efficient label in malaysia the electrification rate in malaysia is at 100%, with the purchasing residential electricity tariff of 0.069 usd/kwh. electricity power consumption is about 4,636 kwh per capita. the malaysian government has an ambitious target in strengthening the energy efficiency agenda by increasing the power capacity mix from renewable energy from 5% in 2017 to 20% by 2025. the energy commission malaysia (st) evaluates electrical appliances using the star rating that defines its fulfilment for energy efficiency under the energy labelling program. the st has imposed minimum energy performance standards (meps) and electricity regulations, 1994 (amendment 2012) for refrigerators, televisions, air conditioners, lamps and domestic fans on 3rd may 2014. from 2018 to 2021, st has added several appliances under the requirements of the meps such as television, washing machines, microwave ovens, electric rice cookers and freezers. to meet the requirements of meps, the performance criteria that are tested using the relevant testing standards must be met. all the appliances should fulfil the meps standards with at least a 2-star rating prior to entering the market as shown in figure 2. the label is an improved version with three new elements added i.e., qr code, certificate of approval (coa) and year of the rating given. these improvements will make it easier for consumers to access label information. to obtain the coa, the products (i) must pass both safety standards and energy performance standards, (ii) must have a test report assessment letter from the standard, and (iii) industrial research institute of malaysia (sirim) is required for foreign products to verify that the test conducted meets the star rating standards. information presented in figure 2 can benefit the consumers when purchasing the most energy-efficient appliances models. the eleventh malaysia plan has been focusing on improving the suitable methods to ensure efficiency in the use of energy in buildings, industries and households and the meps for appliances would be supported (economic planning unit, 2015). this paper assesses household preferences with respect to ee label based on consumers’ willingness to pay (wtp), particularly on refrigerators. this study employed stated preference method to examine household preferences. refrigerators were chosen as selected appliances due to its pervasiveness and as it is the most-own household item (96%) in malaysia (khazanah research institute, 2014). this study assessed how labels that implied the relative efficiency of appliances influenced preferences among households by calculating the marginal wtp for each attribute of label. the method is organized as follows i) determination of product attributes ii) specification of attribute levels, iii) experimental design, iv) visual presentation of choice set to respondents, and v) estimation of choice model (verma et al., 1999). 2. methodology 2.1. model specification choice experiment (ce) was based on random utility theory (rut) which emphasised that a consumer’s utility was based on a product’s attributes (lancaster, 1966). respondents decided rationally and would opt for the best-case scenario which focused on the utility maximisation. consumers were expected to create trade-offs between the attributes of energy label in this study. hence, the utility of a household is stated as follows: uij = βxijk + εij where uij denotes the ith household’s utility from energy label j, xijk signifies the kth attribute of the energy label j for household i, β is a vector of coefficients which is homogenous among households, and εij is a type i extreme value distributed error term. the household’s utility is associated with alternative j as follows: uij = vij + εij where vij presents the utility derived from the label attributes and εij is a stochastic component. the probability that alternative j is chosen by household i is modelled as follows: pij = prob (vij + εij > vis + εis) then, the probability of household i selecting alternative j can be conveyed with the model specification of multinomial logit (mnl): 1 vij j j j ik i v prob e e = = ∑ the mnl is specified to measure the product attributes that households search for when choosing refrigerators in this study. previous research by hensher et al. (2005) assumed that all respondents should have similar preferences, in which this is figure 2: improved version of ee label in malaysia source: www.st.gov.my razali, et al.: consumer preference for energy label in the purchase decision of refrigerator: a discrete choice experiment approach in the east coast, malaysia international journal of energy economics and policy | vol 12 • issue 3 • 2022446 possible to be disobeyed. this hypothesis was based on the random parameter logit model (rpl) which conformed the respondents’ preferences could be heterogeneous across all respondents. 2.2. estimation of marginal willingness to pay the ce method is eliciting respondents’ preferences via the calculation of marginal willingness to pay (mwtp) with an amount of money that the respondents are willing to pay for a specific product or service attribute. mathematically, the mwtp is defined as marginal rate of substitution (mrs) which is estimated by dividing between attributes’ coefficient value (numerator) and coefficient of price attribute (denominator). this study presents the trade-offs that the respondents are willing to choose between the energy label’s attributes. jwtp p m vj v = the above equation presents mwtpj as the mwtp of attribute j, vj as the coefficient value of energy label’s attributes and vp denotes the coefficient value of price attribute. a negative value of the mwtp shows that the attribute is less favoured by the respondents than the baseline. 2.3. experimental design a rational number of attributes is crucial in constructing the ce method, in which too many attributes lead to exhaustion and cognitive stress on respondents while too few attributes portray unrepresentative situations in the questionnaire (jianhua et. al, 2018). there are four non-monetary attributes involved in this study i.e., energy star, energy consumption, energysaving, and price of a refrigerator (monetary attribute) as (table 4). selection of attributes is based on focus group discussions, officers, and expert opinions from the energy commission in the subject matter. efficient experimental design is vital in experimental design because the frequency of each level that appears within an attribute is likely to be the same, and each pair of levels appear equally often across all combinations of those attributes. there is a chance to reduce the confidence intervals for parameters of interest in choice models or to reduce the required number of sample sizes. even with an equal or lesser sample size, an efficient experimental design will still be able to produce reliable parameter estimation (louviere et al., 2000). this study generates about (4 x 4 x 4 x 3) with 192 possible combinations from three attributes (estar, econ, esav) with four levels and a monetary attribute (price) with three levels. experts claimed the efficient experimental design fulfils high requirements of statistical efficiency. this study applies fractional factorial design with d-efficiency experimental design using stata econometric software. the literature on choice sets has highlighted that a fatigue effect is possible to occur among respondents when being presented with 15-20 choice sets (allenby and rossi, 1998). each choice set consists of three alternatives i.e., option a, option b and no-option as shown in table 5. according to the rut, an opt-out option can always be inserted in the choice set if the condition is tallied with respondents’ real-life choice (jorien et al., 2014). the opt-out option reveals the respondents are not compulsory to make a choice that does not replicate their real preferences (hole, 2007). 3. data analysis and results a field survey was conducted in 429 households in east coast regions in peninsular malaysia, namely kuala terengganu, kota bharu and kuantan. this study focused on the head households to assess their preferences and awareness of malaysia’s ee label. the number of selected respondents was considered acceptable as suggested by hensher et al. (2005). they stated a total sample of 50 respondents with 16 choice sets and fully generic parameter specification for attributes with no covariate effects was tolerable. in this case, 429 respondents multiplied by 4 choice sets have offered about 1716 observations. table 6 illustrates that the average age of respondents was 38.24 years with 43.12% of male and 56.88% of female respondents. most of the respondents have graduated from secondary school (48.72%) and work as privatesector employees (41.03%) with an average monthly income rm2,223. 3.1. multinomial logit model table 7 shows the estimated results for the multinomial logit model. the model includes all the energy label attributes. the coefficients for estar2, estar3, estar4, econ2, econ3, econ4, esav2, esav3 and esav4 have generated positive preferences table 4: energy label attributes and levels attributes levels descriptions energy star (estar) 2-star 3-star 4-star 5-star star rating energy consumption (econ) rm132.70 rm106.20 rm84.92 rm67.98 average energy consumption cost per year in ringgit malaysia (rm) energy saving (esav) no saving saved rm26.50 per year saved rm47.78 per year saved rm64.72 per year total energy savings per year compared to the lowest 2-star rated products. price rm950 rm1400 rm2000 price of refrigerator in ringgit malaysia (rm) source: authors’ own research. table 5: an example of choice set in survey attributes option a option b no-option energy star 3 star 4 star energy consumption rm132.70 rm106.20 energy saving saved rm47.78 per year saved rm47.78 per year price rm1400 rm2000 please tick your choice √ source: authors’ own research. razali, et al.: consumer preference for energy label in the purchase decision of refrigerator: a discrete choice experiment approach in the east coast, malaysia international journal of energy economics and policy | vol 12 • issue 3 • 2022 447 where the respondents chose characteristics of energy star, energy consumption and energy saving as factors in purchasing refrigerators. all variables of estar_3star, estar_4star, estar_5star, econ_106.20, econ_84.92, esav_26.50, esav_47.78 and esav_64.72 portrayed a positive preference with high significant level at 1%, except econ_67.98 which portrayed a positive preference at 10% significant level. the negative sign of price with 1% significance level was as expected since preference or utility for a given choice would be lower when the cost of the choice increases, suggesting respondents were sensitive to price changes (ward et al., 2011). therefore, an increase in the price of refrigerators specified the reduction of respondents’ wtp because of the decrease in the utility level. this indicated that as the price of refrigerators increased, their preferences decreased. 3.2. mixed logit model the results of the simple mixed logit (ml) model are illustrated in table 8. the first section of the table presents the estimated values for the means of preferences for the energy labelling of refrigerator attributes, while the last section presents the summary of statistics. four variables were found to be highly significant at 1% level with an expected sign, namely the esav_26.50, esav_47.78, esav_64.72 and price. the high positive coefficients for esav_47.78 have implied that respondents preferred it more compared to esav_0, esav_26.50 and esav_64.72. this explained that the respondents expected to have an improvement on energy savings of refrigerator from the current condition, but they did not have a high expectation for this attribute. price was significant at 1% level with correct negative expected signage, which indicated that the respondents were less willing to pay a higher price for a refrigerator because of the decrease in the utility level. based on both the simple mnl and ml models, the simple ml has better goodness of fit as compared to the simple mnl model. there are notable features about the statistical results in ml model as compared to mnl model. the ml model has a higher level of model fitness with improvements in likelihood value from -1541.279 (simple mnl model) to -1393.612 (simple ml model). furthermore, the pseudo value increased from -0.0574 (simple mnl model) to 0.2607 (simple ml model). the ml model was the best-fit model as it had higher log-likelihood values and pseudo values as compared to multinomial logit (mnl) model. according to louviere et al. (2000), the pseudo goodness-of-fit test that formed estimation between 0.2 and 0.4, implies a good model fit for cross-sectional data. 3.3. marginal wtp analysis the coefficient β can be used to estimate the marginal willingness to pay (mwtp) for each attribute in the study. the mwtp or marginal rate of substitution stipulated the wtp of the respondents according to their preferences (siebert, 2008) and could be estimated using non-monetary attribute coefficient ratio over the monetary attribute coefficient as follows: marginal wtp non monetary attribute monetary attribute   = − the calculation of mwtp was produced through wald test with econometric software nlogit 5.0 (table 9). it should be noted that the marginal values correlated to the energy label, which was estimated in ringgit malaysia (rm). table 6: socioeconomic characteristics of respondents (n=429) characteristics frequency (%) χ2 p-value gender 0.8204 0.365 male 185 43.12 female 244 56.88 age 15.1852 0.010 less than 20 years old 5 1.17 21–30 years old 122 28.44 31–40 years old 140 32.63 41–50 years old 75 17.48 51–60 years old 68 15.85 more than 60 years old 19 4.43 mean: 38.82 at 38 years old education level 14.0316 0.015 no education 5 1.17 primary school (upsr) 18 4.20 secondary school (spm) 209 48.72 higher certificate education/diploma 116 27.04 bachelor 75 17.48 master/phd 6 1.40 occupation 0.4380 0.508 government employee 86 20.05 private employee 176 41.03 business owner 115 26.8 farmer/fisherman 8 1.86 retiree/housewife/ part-timer 44 10.26 household income 24.3017 0.111 less than rm 2,000 274 63.87 rm 2,001 – rm 4,000 126 29.37 rm 4,001 – rm 6,000 12 2.8 rm 6,001 – rm 8,000 8 1.86 rm 8,001 – rm 10,000 8 1.86 more than rm 10,000 1 0.23 mean: rm 2223 total 429 100 source: authors’ own research table 7: multinomial logit model variables coefficient standard error z-value estar_3star 0.62657 0.09349 6.70*** estar_4star 0.71228 0.09298 7.66*** estar_5star 0.74395 0.08400 8.86*** econ_106.20 0.42534 0.08919 4.77*** econ_84.92 0.45871 0.08354 5.49*** econ_67.98 0.16873 0.09409 1.79* esav_26.50 0.91724 0.09519 9.64*** esav_47.78 1.00299 0.09467 10.59*** esav_64.72 0.81100 0.08085 10.03*** price −0.00033 0.00006985 −4.67*** summary statistics number of observations 429 log-likelihood −1541.279 pseudo r2 −0.0574 adjusted r2 −0.0604 significance at 1% (***), 5% (**), 10% (*). source: authors’ own research razali, et al.: consumer preference for energy label in the purchase decision of refrigerator: a discrete choice experiment approach in the east coast, malaysia international journal of energy economics and policy | vol 12 • issue 3 • 2022448 4. discussion the results of mwtp values in table 9 shows that all wtp estimated values were very different across the two models. in terms of energy star rating, the result illustrates that the highest estimated value for the simple mnl model was rm 2282.20, which was estar_5star, while the highest estimated value for the ml model was rm 183.51, which was estar_3star. it can be explained that the respondents valued 2-star, 3-star and 4-star energy ratings for the simple mnl model less, while 2-star, 4-star and 5-star were less valued by the respondents for the simple ml model. the respondents preferred to have a 5-star and 3-star energy ratings for the simple mnl and ml model, respectively. in terms of energy consumption, the result illustrates that the highest estimated value for the simple mnl model was rm 1407.19, which was econ_84.92, while the highest estimated value for the ml model was -rm 266.20, which was econ_67.98. it can be explained that the respondents valued econ_132.70, econ_106.20 and econ_67.98 less for the simple mnl model, while the respondents for the simple ml model valued econ_132.70, econ_106.20 and econ_84.92 less. the respondents preferred to have rm84.92 and rm67.98 as energy consumption per year in terms of ringgit malaysia (rm) for the simple mnl and ml model, respectively. in terms of energy savings, the result illustrates that the highest estimated value for the simple mnl model was rm 3076.86, with esav_47.78, while the highest estimated value for the ml model was rm 1273.06, with_47.78 of esav as well. it can be explained that the respondents valued esav_0, esav_26.50 and esav_64.72 less for the simple mnl and the simple ml model. the respondents preferred to have rm47.78 as energy savings per year in terms of ringgit malaysia (rm) for the simple mnl and ml model. although the respondents preferred the highest value of rm 3349.69 for a simple mnl model and rm 1475.31 for a simple ml model on energy-saving attribute esav3_47.78 (rm47.78 per year), they still favoured refrigerator with energy-saving features mostly due to the advantage of saving their monthly utility bills. according to the findings, the ce method has helped specified which attribute played a significant determinant of the values in the respondents’ choices. ‘energy saving’ attribute was the major reason for the willingness to pay since it produced the highest marginal value. therefore, these valuations used in the study can convince the government to support more investment and to fund more resources to improve the energy efficiency development in malaysia in the future. hence, the objective of this study to evaluate ee labelling attributes in determining the consumer’s wtp towards refrigerator has been achieved. it is believed that more consumers in the east coast region in peninsular malaysia are more aware of the labels and they tend to look for energysaving attributes when buying a refrigerator. the results of the study are in line with goal 7: affordable and clean energy in sdgs, which focuses on global effort to ensure access to affordable, reliable, sustainable, and modern energy for all. this is to ensure consumers understand that choosing an energy-efficient appliance is an important step in tackling environmental issues. the purpose is not solely because the sdg 7 target is to be achieved, though energy efficiency efforts are interconnected with all the other sdgs. for instance, the ineffective consumption of energy access can unnecessarily impact on the use of fossil fuel and can harm greenhouse gas emission, leading to a greater conflict on climate change. as such, it is contradictory that the objective of sdg 13 is to take urgent action to combat climate change and its impacts only. the main goal is to work together to accelerate action and deliver results that will transform the lives of billions through sustainable energy access that also helps combat climate change. 5. conclusion ee label has been broadly used as a policy instrument to improve energy efficiency in appliances. this research analyses household preferences relating to ee label and the effects of the label on the table 8: mixed logit model variables coefficient standard error z-value estar_3star 0.12662 0.10828 1.17 estar_4star −0.01160 0.11618 −0.10 estar_5star 0.11307 0.10706 1.06 econ_106.20 −0.23730 0.10885 −2.18** econ_84.92 −0.20736 0.11491 −1.80* econ_67.98 −0.18368 0.12373 −1.48 esav_26.50 0.70982 0.13384 5.30*** esav_47.78 0.87841 0.14804 5.93*** esav_64.72 0.37044 0.10559 3.51*** price −0.00069 0.00010 −6.68*** derived standard deviations of parameter distributions estar_3star 0.31205 0.40770 0.77 estar_4star 0.60140 0.27868 2.16** estar_5star 0.58121 0.22003 2.64*** econ_106.20 0.30364 0.49163 0.62 econ_84.92 0.04917 0.27065 0.18 econ_67.98 0.60192 0.32717 1.84* esav_26.50 0.46993 0.38010 1.24 esav_47.78 0.73743 0.22426 3.29*** esav_64.72 0.52308 0.25938 2.02** summary statistics number of observations 429 log-likelihood −1393.612 pseudo r2 0.2607 adjusted r2 0.2560 significance at 1% (***), 5% (**), 10% (*). source: authors’ own research table 9: marginal values for mnl and ml models variables marginal value (rm) mnl model ml model estar_3star 1922.11 183.51 estar_4star 2185.06 −16.81 estar_5star 2282.20 163.87 econ_106.20 1304.83 −343.91 econ_84.92 1407.19 −300.52 econ_67.98 517.603 −266.20 esav_26.50 2813.81 1028.72 esav_47.78 3076.86 1273.06 esav_64.72 2487.90 536.87 rm1=usd0.24. source: authors’ own research razali, et al.: consumer preference for energy label in the purchase decision of refrigerator: a discrete choice experiment approach in the east coast, malaysia international journal of energy economics and policy | vol 12 • issue 3 • 2022 449 purchasing behaviour of households. dce is used to obtain and analyse household preferences. this study has chosen refrigerator as a measurement tool with four attributes, namely energy star rating, annual energy consumption, annual energy saving and price of refrigerators. the ce offers to calculate marginal values according to the attributes where it shows the monetary value that consumers are willing to place for each change in attributes. this study has contributed to the empirical knowledge in assessing the economic valuation of energy efficiency labelling via consumers’ wtp. furthermore, the initiative of using the ce method will help contribute to various methodological approaches in the economic valuation of energy efficiency labelling in malaysia for instance in marketing and policy purposes. according to dianshu et al. (2010), consumers need to learn about the benefits they would get when appliances become more efficient. providing relevant information to consumers will encourage them to select energyefficient appliances. thus, by implementing an economic valuation study, many investments programs can be suggested to benefits the public. in this regard, the ee label can guide the efficient use of energy and at the same time reduce dependency on fossil fuel through good purchasing decisions among consumers. on top of that, the energy efficiency agenda is consistent with goal 7: affordable and clean energy in sdgs which focuses to double the global improvement rate in energy efficiency by 2030. hence, executing energy efficiency solutions is necessary to counter climate change, which is one of the biggest threats globally. in line with the implementation of malaysia’s energy efficiency that targets 8% of demand to be reduced by 2025, which is equivalent to a total of 52,233 gwh of electricity savings for over 10 years from 2016 to 2025, this policy was authorised by asean member state as of june 2020 and contributed by asean climate change and energy project (accept). in 2022, malaysian government initiatives through the sustainable energy development authority (seda) has recently launched a program that encourages consumers to purchase efficient appliances. the sustainability achieved via energy efficiency (save) 3.0 is a program that grants up to rm400 e-rebate to domestic households that purchase appliances like refrigerator, air conditioner, television, washing machine, microwave oven or rice cooker with 4or 5-star energy efficiency labels from the energy commission (ec). the objective of this program is to increase the number of 4or 5-star energy-efficient electrical appliances in the market. this program can increase public awareness of appliances that will save electricity consumption as well as reduce greenhouse gas emissions. the program is a continuation of a successful save 2.0 and it has received a favourable response from the consumers so far. a total of 134,000 redeemed e-rebates and managed to save up to rm26.8 million (sustainable energy development authority, 2022). besides, there were several efforts have been initiated globally to support sdg 7 that could relate to this study. according to the international energy agency (2015), annual investments of $45 billion were needed to meet the sdgs. the world bank group (wbg) has been investing in all three of the principal target areas of sdg 7: energy access, energy efficiency, and renewable energy. for instance, in mexico, with the help of their climate finance and global environmental facility support, the wbg has implemented a program of replacing over 25 million inefficient light bulbs, and almost two million old refrigerators with new and highly efficient ones, all targeted to low-income households. the aim was to reduce household expenses and save energy consumption as well as to combat climate change and its impacts. acknowledgment we would like to thank the ministry of higher education (mohe) for supporting this research under fundamental research grant scheme frgs/1/2019/ss08/umt/03/1. all the views written in this manuscript and any errors or omissions are the sole responsibility of the researchers. references abu saleh, a., hamdan, s., shazali, s.t.s. (2011), electricity savings by implementing energy efficiency standards and labels for clothes washers in malaysia. journal of engineering science and technology, 6(1), 29-38. air pollutant index of malaysia. (2018), regional haze situasion. available from: https://www.apims.doe.gov.my akbostancı, e., tunç, g.i̇., türüt-aşık, s. (2011), co2 emissions of turkish manufacturing industry: a decomposition analysis. applied energy, 88(6), 2273-2278. allenby, g.m. & rossi, p.e. (1998), marketing models of consumer heterogeneity. journal of econometrics, 89, 57-78. arrow, k., bolin, b., costanza, r., dasgupta, p., folke, c., holling, c.s., pimentel, d. (1996), economic growth, carrying capacity, and the environment. environment and development economics, 1(1), 104-110. association of water and energy research malaysia. (2012), incandescent (gls) phase-out: is malaysia doing it right? dhingra, n., walia, a.a., mukherjee, p.k. (2016), measuring the impact of india’s standard and labeling program. amsterdam: international energy policies and programmes evaluation conference. p 7-9. dianshu, f., sovacool, b.k., vu, k.m. (2010), the barriers to energy efficiency in china: assessing household electricity savings and consumer behavior in liaoning province. energy policy, 38(2), 1202-1209. economic planning unit. (2015), eleventh malaysia plan 2016-2020: anchoring growth on people. malaysia: economic planning unit, prime minister’s department. energy commission, malaysia. (2020), guideline for energy efficiency label. available from: https://www.st.gov.my/en/web/consumer/ details/7/2 freitas, l.c., kaneko, s. (2011), decomposition of co2 emissions change from energy consumption in brazil: challenges and policy implications. energy policy, 39(3), 1495-1504. galarraga, i., gonzález-eguino, m., markandya, a. (2011), willingness to pay and price elasticities of demand for energy-efficient appliances: combining the hedonic approach and demand systems. energy economics, 33, s66-s74. gerarden, t.d., newell, r.g., stavins, r.n. (2017), assessing the energyefficiency gap. journal of economic literature, 55(4), 1486-1525. gonzález, p.f., landajo, m., presno, m.j. (2014b), tracking european union co2 emissions through lmdi (logarithmic-mean divisia razali, et al.: consumer preference for energy label in the purchase decision of refrigerator: a discrete choice experiment approach in the east coast, malaysia international journal of energy economics and policy | vol 12 • issue 3 • 2022450 index) decomposition. the activity revaluation approach. energy, 73, 741-750. hammond, g.p., norman, j.b. (2012), decomposition analysis of energy-related carbon emissions from uk manufacturing. energy, 41(1), 220-227. hensher d.a, rose j.m, greene w.h. (2005), applied choice analysis: a primer. cambridge: cambridge university press. hole, a.r. (2007), a comparison of approaches to estimating confidence intervals for willingness to pay measures. health economics, 16, 827-840. international energy agency. (2015), achievements of appliance energy efficiency standards and labelling programs. paris, france: iea. jain, m., rao, a.b., patwardhan, a. (2018), appliance labeling and consumer heterogeneity: a discrete choice experiment in india. applied energy, 226, 213-224. jeong, g., kim, y. (2015), the effects of energy efficiency and environmental labels on appliance choice in south korea. energy efficiency, 8(3), 559-576. jiang, h.y., li, h.r., yang, l.s., li, y.h., wang, w.y., yan, y.c. (2014), spatial and seasonal variations of the air pollution index and a driving factors analysis in china. journal of environmental quality, 43(6), 1853-1863. jianhua, w., ge, j., ma, y. (2018), urban chinese consumers’ willingness to pay for pork with certified labels: a discrete choice experiment. sustainability, 10(603), 1-14. jorien, v., lambooij, m.s., de bekker-grob, e.w., smit, h.a., ardine de wit, g. (2014). the effect of including an opt-out option in discrete choice experiments. plos one, 9(11), e111805. khazanah research institute. (2014), the state of households. kuala lumpur: khazanah research institute. lancaster, k.j. (1966), a new approach to consumer theory. journal of political economy, 74, 132-157. lane, k., harrington, l., ryan, p. (2007), evaluating the impact of energy labelling and meps-a retrospective look at the case of refrigerators in the uk and australia. paris: european council for energy-efficient economy: proceedings of the 2007 eceee summer study. saving energy-just do it. p743-751. lee, k., oh, w. (2006), analysis of co2 emissions in apec countries: a time-series and a cross-sectional decomposition using the log mean divisia method. energy policy, 34(17), 2779-2787. louviere, j., hensher, d., swait, j. (2000), conjoint preference elicitation methods in the broader context of random utility theory preference elicitation methods. in: conjoint measurement. berlin, heidelberg: springer. p279-318. mahlia, t.m.i., masjuki, h.h., saidur, r., choudhury, i.a., noorleha, a.r. (2003), projected electricity savings from implementing minimum energy efficiency standard for household refrigerators in malaysia. energy, 28(7), 751-754. meckling, j. (2018), the developmental state in global regulation: economic change and climate policy. european journal of international relations, 24(1), 58-81. meyers, s., mcmahon, j.e., mcneil, m., liu, x. (2003), impacts of us federal energy efficiency standards for residential appliances. energy, 28(8), 755-767. mills, b., schleich, j. (2010), what’s driving energy efficient appliance label awareness and purchase propensity? energy policy, 38(2), 814-825. moxnes, e. (2004), estimating customer utility of energy efficiency standards for refrigerators. journal of economic psychology, 25(6), 707-724. oh, i., wehrmeyer, w., mulugetta, y. (2010), decomposition analysis and mitigation strategies of co2 emissions from energy consumption in south korea. energy policy, 38(1), 364-377. saidel, m.a., alves, s.s. (2003), energy efficiency policies in the oecd countries. applied energy, 76(1-3), 123-134. sammer, k., wüstenhagen, r. (2006), the influence of eco‐labelling on consumer behaviour-results of a discrete choice analysis for washing machines. business strategy and the environment, 15(3), 185-199. shen, j., saijo, t. (2009), does an energy efficiency label alter consumers’ purchasing decisions? a latent class approach based on a stated choice experiment in shanghai. journal of environmental management, 90(11), 3561-3573. shi, x. (2014), setting effective mandatory energy efficiency standards and labelling regulations: a review of best practices in the asia pacific region. applied energy, 133, 135-143. siebert, h. (2008), property-rights approach to the environmental problem. economics of the environment: theory and policy, 2008, 97-104. taghizadeh-hesary, f., taghizadeh-hesary, f. (2020), the impacts of air pollution on health and economy in southeast asia. energies, 13(7), 1812. tao, j., yu, s. (2011), implementation of energy efficiency standards of household refrigerator/freezer in china: potential environmental and economic impacts. applied energy, 88(5), 1890-1905. van vuuren, d.p., stehfest, e., gernaat, d.e., van den berg, m., bijl, d.l., de boer, h.s., van sluisveld, m.a. (2018), alternative pathways to the 1.5 c target reduce the need for negative emission technologies. nature climate change, 8(5), 391-397. verma, r., thompson, g.m., louviere, j.j. (1999), configuring service operations in accordance with customer needs and preferences. journal of service research, 1(3), 262-274. ward, d.o., clark, c.d., jensen, k.l., yen, s.t., russell, c.s. (2011), factors influencing willingness-to-pay for the energy star® label. energy policy, 39(3), 1450-1458. wong, l., krüger, e. (2017), comparing energy efficiency labelling systems in the eu and brazil: implications, challenges, barriers and opportunities. energy policy, 109, 310-323. xu, s.c., he, z.x., long, r.y., chen, h., han, h.m., zhang, w.w. (2016), comparative analysis of the regional contributions to carbon emissions in china. journal of cleaner production, 127, 406-417. zhang, j., ouyang, z., miao, h., wang, x. (2011), ambient air quality trends and driving factor analysis in beijing, 1983-2007. journal of environmental sciences, 23, 2019-2028. zhao, y., wang, s., zhang, z., liu, y., ahmad, a. (2016), driving factors of carbon emissions embodied in china-us trade: a structural decomposition analysis. journal of cleaner production, 131, 678-689. zheng, s., kahn, m.e., sun, w., luo, d. (2014), incentives for china’s urban mayors to mitigate pollution externalities: the role of the central government and public environmentalism. regional science and urban economics, 47, 61-71. zhou, h., bukenya, j.o. (2016), information inefficiency and willingnessto-pay for energy-efficient technology: a stated preference approach for china energy label. energy policy, 91, 12-21. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 5 • 2021 157 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(5), 157-171. review on rural energy access policies juan-enrique cabello-vargas1, azucena escobedo-izquierdo1, arturo morales-acevedo2* 1universidad nacional autónoma de méxico, facultad de ingeniería división de ingeniería eléctrica, departamento de sistemas energéticos, méxico, 2centro de investigación y de estudios avanzados del ipn-méxico, departamento de ingeniería eléctrica – sees, méxico. *email: amorales@solar.cinvestav.mx received: 05 febraury 2021 accepted: 02 june 2021 doi: https://doi.org/10.32479/ijeep.11268 abstract rural energy in all their dimensions, not only access, but also sources, supply, consumption, program management, project maintenance, control and evaluation has been a neglected area in national energy planning in developing countries. as a result, nearly two billion people all around the world lack access to commercial energy, particularly to electricity and clean cooking appliances. poor people still depend on traditional sources of energy that are used inefficiently. the unplanned exploitation of local biomass resources, mainly for basic needs such as cooking, generates serious environmental problems. in this sense, women face hardship in the collection of biomass and exposure to smoke that adversely affect their health. therefore, this study aims to explore rural energy policies through a systematic literature review about rural energy access as a problem to be solved by means of an adequate rural energy policy. the study tries to raise the general settings of rural energy access, their challenges, barriers, and alternatives for solution, especially through the consideration of rural energy policy as an alternative to achieve a sustainable solution for rural poverty. besides, by organizing and collecting concepts, this review contributes to a better understanding of these topics and their general issues, particularly in latin america. considering the general context as an initial condition, and the universal energy access as the perfect condition, rural energy policy becomes the central strategy to ensure universal energy access in all rural areas, trying to transit from an initial to a perfect condition. keywords: rural energy policy, rural energy access, rural energy poverty, rural electrification, clean cooking alternatives jel classifications: q40, q43, q48, q49, r10, r58 1. introduction the link between energy and development moved into the international agenda during the world summit for sustainable development held in 2002, highlighting the need for new efforts and policies to promote electrification in developing regions (gómez and silveira, 2010). the decade of sustainable energy declared by the united nations organization, between 2014 and 2024 (martínez-gómez, guerrón and riofrio, 2017) has as the main purpose, closing the rural areas gap for efficient, sustainable and affordable energy resources for all. in this sense, the design of effective policies is necessary and the recovery of information through exploratory and descriptive works, e.g., literature reviews, is helpful to achieve this purpose. goldemberg and prado (2013) pointed out that increases in electrification benefit more than increases in income because electricity induces social and individual development. in 2016, the secretary-general of united nations and the president of the world bank called to all countries to commit themselves to universal modern energy access by 2030. several international agencies such as the international energy agency, the european union, and the energy management assistance program (esmap) are building scenarios about how to accomplish these purposes (van der vleuten, stam and van der plas, 2013). this manuscript intends to offer a holistic insight into the evolution of rural energy access and rural energy policies, covering the transition from a planned economy to a market economy through this journal is licensed under a creative commons attribution 4.0 international license cabello-vargas, et al.: review on rural energy access policies international journal of energy economics and policy | vol 11 • issue 5 • 2021158 structural reforms in latin america1. broadly, a comprehensive rural energy policy is lacking, and most policies focus on technoeconomic aspects. commonly, techno-economic rural energy policies are concentrated in a single aspect of one or multiple energy sources2. rural energy policies are problem-oriented, deficient in predictability, and are often designed to solve specific energy issues (he, hou and liao, 2018; nygaard, 2010). only when these issues require an urgent solution, governments attend and promulgate related policies (pinheiro, rendeiro, pinho, and macedo, 2012; panos, densing and volkart, 2016; jimenez, 2017; gacitua, et. al., 2018). however, due to a lack of planning, the formulation and implementation of these policies are uncertain and policy makers are unsure to what extent rural energy issues can be addressed by these policies (wu, 2019; ciller and lumbreras, 2020; quratul-ann and mirza, 2020). then, here a conceptual analysis for energy access, providing insights about electrification and clean cooking alternatives in the regional rural energy policy context. we also make a proposal for a problem-solving oriented approach that includes a revision of transcendental issues related to rural energy poverty. 2. instrumentation of the study this study aims to address rural energy access through a policy perspective, i.e., making emphasis on the need to employ specific rural energy policies to increase energy access. the manuscript has been configured by a systematic literature review about general aspects, challenges and issues to solve through the adoption of policy strategies. in this regard, a systematic literature review is a type of data analysis that represents a transparent and reproducible methodology “that locates existing works, selects and evaluates contributions, analyses and synthesizes data, and reports the evidence in such a way that allows reasonably clean conclusions to be reached” (denyer and tranfield, 2009). several works address only electrification from a techno-economic perspective, while other literature reviews address only clean cooking3. despite the importance of these contributions, there is a need to provide a more comprehensive analysis of the elements affecting rural energy access and the distinctive traits of energy for rural areas that pose the need for a specific energy policy. specifically, adopting a systematic approach, this study addresses the following research questions: 1. what are the drivers and barriers that influence rural energy access, considering the resources to cover all household needs? 2. how the problem of rural energy access, considering electrification and clean cooking access, is related to the need for a rural energy policy? 1 to the best of the authors´ knowledge, this manuscript is pioneer in approaching a specific regional context. 2 however, rural energy policies evolve according to the change in rural energy issues, e.g., consumption paths. 3 lewis and pattanayak (2012) analyzed 32 manuscripts to identify the determinants of fuel and stove choice, while puzzolo et al. (2016) reviewed 44 articles focusing on the adoption of clean fuels. bonan et al. (2017) conducted a review to identify barriers and drivers of the adoption of different clean fuels and their impact on development and poverty reduction. in this sense, it is necessary to point out that almost all works about rural energy access are approached in a singular specific-project, technical or economic perspective, but not from a policy perspective. taking these assumptions as our starting point, the purpose of this manuscript is to develop a systematic literature review that helps to understand the general settings to approach the rural energy access problem better. from a methodological perspective, a systematic literature review involves several steps that have been applied to this study, these steps are (denyer and tranfield, 2009): 1. formulate and define questions to be investigated, establishing the focus of the literature review 2. locate documents as the materials for review 3. evaluate and apply selection criteria to identify the documents relevant to the scope of the study 4. proceed to apply analysis and synthesis methods that involve the evaluation and comparison of selected articles. this process allows associations and recognizing knowledge that is not apparent from reading the individual manuscripts in isolation. 3. analysis of the research theme rural energy access can be modeled as a multifactorial task connected to large number of social, economic, and environmental aspects. it is necessary to consider not only technoeconomic competitiveness, but also socio-cultural dynamics and environmental consequences, making rural energy a complex challenge. many electrification, and clean cooking access projects have failed due to lack of attention in issues beyond financial and technical dimensions (rahman et al., 2013). thereby, this research aims to address the problem from a policy perspective. despite increasing attention towards this topic, few works have explored the factors influencing energy access in rural areas and the adoption of a specific rural energy policy. then, this review aims to identify the main drivers and barriers to achieve rural energy access – electrification and clean cooking – from a political perspective. also, it contributes to explain the general problematic. a thematic analysis revealed the elements that may act as drivers and barriers to rural energy access, and which need to be addressed by a rural energy policy. in a broader classification, the elements are grouped in economic aspects; socio-demographics; fuel availability; attitude toward technology; awareness of the risks of traditional manners and the benefits of energy services; location; and social and cultural influences. previous findings suggest that the availability and affordability of technology are not enough to cause energy adoption. rather, policymakers and governments should approach energy access and customer needs with a less technical and a more social and personalized approach that considers the local context and its social and cultural dynamics (vigolo et al., 2018). 4. basic conceptual aspects: from energy poverty to energy access energy poverty refers to people that do not have regular, reliable, confident, and accurate access to electricity (nagothu, 2016; yadoo and cruickshank, 2017; ozughalu and ogwumike, 2019). pachauri cabello-vargas, et al.: review on rural energy access policies international journal of energy economics and policy | vol 11 • issue 5 • 2021 159 and spreng (2003) defined energy poverty according to the access to energy services, since access to more efficient energy sources enhance the quality of human development and social prosperity (pereira et al., 2013)4. on the other hand, according to the world energy outlook 2011 (oecd/iea, 2011), energy access is defined “as a household having reliable and affordable access to clean cooking facilities, connection to electricity and an accessibility to increase their electricity consumption across time to reach the national average”. the definition of energy access usually includes both electricity access and access to modern fuels for cooking to replace traditional biomass (sarr, dafrallah, ndour, and fall, 2008; hou, et. al., 2017), because only electricity for basic needs is not enough for poverty alleviation and economic development. energy is essential to economic development, poverty alleviation, and social progress, necessary to achieve the millennium development goals (yadoo and cruickshank, 2012; van ruijven, schers, and van vuuren, 2012; rosenthal, quinn, grieshop, pillarisetti, and glass, 2018). energy services are necessary for the successful implementation of all development programs, productive activities, health, education, water, food security and agricultural development (coelho and goldemberg, 2013; detchon and van leeuwen, 2014). energy access envisages two ambits for a rural household: the electric perspective, enough connection that solves the basic lighting needs, the use of radio, tv, and electric appliances; besides, a more ambitious step is electricity for productive uses like education and telecommunications (zuluaga and dyner, 2007; bazilian, et. al., 2012). moreover, a clean cooking approach that allows transiting to a sustainable solution5. 5. insights on political issues and energy access in a latin america regional context electricity coverage in latin america has increased substantially in recent decades, rising from 50% of the population in 1970 to more than 95% in 2015 (sheinbaum-pardo and ruiz, 2012). growth, however, slowed in the 1990s as many countries had trouble in extending their networks further, in particular to serve those living in isolated and rural areas (krauter and kissel, 2005). in spite of this, the process of electrification continued and at the beginning of the 2010s decade, most countries in the region achieved access to electricity for almost all their populations. a combination of policy efforts has made it possible to achieve the current situation of universal electrification in the region (banal-estañol et al., 2017). however, the per-capita consumption levels remain beneath the suggested rates and the access to clean cooking are still limited. this situation is a consequence of the restricted political perspective. 4 some countries has reached universal electrification. however, remains a lack in clean cooking access, exacerbating rural energy poverty, because electricity is irrelevant to cook, main activity in rural households (he, hou, & liao, 2018). 5 in this sense, a more sustainable solution considers reliable and affordable at household income levels, clean in the source and friendly with the environment, and healthy and equitable for people. since the 1980s, governments, international donors, and cooperation agencies have actively worked to boost the region electrification. most of the resulting coverage increase in countries such as bolivia, peru, and honduras, has been generated in urban areas, where per capita income is high, and the costs of expanding the grid are relatively cheap. nevertheless, electrification rates in rural areas have remained beneath the country averages, especially in central america and the andes. this situation is still affecting the great economies in the region such as brazil and mexico (gómez-hernández, et. al., 2019). another salient feature of the latin america electricity markets is the significant differences in consumption levels across countries, which suggests that access to electricity alone does not mean that all consumers can reap all the service benefits. while per capita consumption is quite high in argentina, uruguay and venezuela, it is significantly low in countries like haiti, guatemala, nicaragua, honduras, bolivia, and el salvador (banal-estañol et al., 2017). wolfram et al. (2012) examined the patterns of electrification across the developing world and found that electrification is consistently correlated with gdp per capita. brown and mobarak (2009) analyzed a group of 57 countries in the period 1973–1997 and showed that in poor countries democratization has meant an increase in the proportion of residential electricity above the industrial consumption, suggesting that democratic governments reflect better the preferences of the population and dedicate more resources and efforts to electrification. part of the increase in access and electricity consumption in latin america can be attributed to the reform of the electricity markets that took place in the region during the last century. until the 1990s, power sectors in the region were mostly managed by vertically integrated state-owned firms; based on the rationale that public monopolies could harness scale economies, make efficient use of scarce managerial skills and offer the service at an affordable price, even generating social tariffs to attend the poor people. however, by the mid-1990s, the economic situation of the region together with the inefficiencies and managerial problems of these firms led many governments to reform the sector, introducing several changes mostly oriented to the economic aperture of the industry. many countries privatized their public monopolies and liberalized the energy market intending to attract investors and promote free-market competition (victor, 2005; calzada and sanz, 2009). the macroeconomic fluctuations of the 1970s and 1980s in most latin american countries had a strong negative impact on public investment in the power sector. as the global economy slowed down, many countries simply could not afford to invest in their power sectors, leading to a decline in the quality of public services and multiple lack of enough capacity in their provision. simultaneously, consumer demand steadily rose due to the development of the region and the urbanization process, resulting in considerable supply gaps and dissatisfaction with public supply. consumer prices in the state-owned power sectors were heavily subsidized, which meant state-owned power firms ran continual losses. against this backdrop, energy sector reforms became a means for governments to gain much-needed capital through the cabello-vargas, et al.: review on rural energy access policies international journal of energy economics and policy | vol 11 • issue 5 • 2021160 sale of public infrastructure, and to reduce public spending on subsidized tariffs (wamukonya, 2003). international institutions were also a large driving force behind the power sector reform. in 1993, the world bank made power sector loans conditional on commitments to private sector participation and liberalization (world bank, 1993). many other institutions, including the interamerican development bank, began similar practices shortly afterward. liberalization and privatization are often presented in the literature as attempts not only to improve efficiency in the power sector but also to bring about a wholesale change in ideology, with electricity going from a public service to a market commodity. initially, power sector liberalization brought in the needed private sector investment to all latin america. by the 1990s, the region had the largest share of private electricity projects among all developing regions worldwide. more than 38% of total investment in the developing world’s power sector was concentrated in latin america (henisz et al.). although the promised investment arrived, it was largely concentrated in the more profitable areas with cheap costs and large demands. there is evidence that the power sector reforms brought loss reductions while extending coverage, increasing consumption, and reducing prices in several countries (henisz et al, 2005 and balza et al., 2013). the privatization process in the region took place in conjunction with the vertical unbundling of the sector into its three basic business units generation, transmission, and distribution. most governments transferred generation, and to a lesser extent distribution and transmission, to the private sector. simultaneously, they established new regulatory frameworks and market mechanisms to encourage competition. these transformations changed the institutional framework and the regulatory instruments available to supervise the sector, opening the door to new scenarios that favored the mix of public and private intervention to solve policy problems (banal-estañol et al., 2017)6. however, some countries in latin america have partially reversed their policies due to changes in their governments´ ideology and a certain disenchantment with the results of the reforms. this is the case of bolivia, which in 2010 initiated a nationalization process that reversed the changes introduced in the 1990s. similarly, in venezuela several industries have been nationalized in the last few years. in spite of this, most latin american countries have consolidated a regulated competition system and have tried to equilibrate the undesirable effects of liberalization by implementing electrification policies. a common effect of privatization is that private investors tend to focus their efforts on urban areas, where they have more highincome consumers and benefit from scale economies. in rural and remote areas, by contrast, the service is usually non profitable 6 balza et al. (2013) show that in la the intensity of private investment in power sector didn´t significantly affected the increase in coverage. by contrast, liberalization and creation of independent agencies had a positive effect on the expansion of service. during the 1990s, new regulatory models were established to introduce competition in the supply chain, especially in generation, but also in transmission and distribution. moreover, price regulations and subsidy schemes were established to allow fair conditions for consumption, regulated users, and set the financial sustainability of firms. for private investors. to compensate this lack of attention, since the 1990s, national governments have implemented specific electrification programs by investing part of the profits derived from the energy industry structural changes. chile has been a pioneer launching such an electrification program. other countries, like colombia and peru, have implemented specific rural electrification policies, and many others have created funds for rural electrification (e.g., mexico and argentina). the brazilian program “luz para todos” is considered the biggest rural electrification program in the world. most latin american countries use social (subsidized) tariffs to boost affordability of the service (slough, urpelainen and yang, 2015). the regional heterogeneity of rural residents’ willingness and interests are not adequately considered in the process of rural energy policy design and implementation. the current rural energy strategy and policies emphasize the nationwide use of renewable energy and clean biomass energy to achieve sustainable development in the new era, while the roles of commercial energy, such as liquefied petroleum gas (lpg) and electricity, are frequently neglected (wu, 2019). while there are very few countries where, apart from traditional biomass, renewable energies have been able to provide a solution to energy access for the poor, governments has abandoned its “menu of alternatives approach” and replaced this with a “renewable energy approach” (vleuten et al., 2013), complicating the coverage of energy needs and reducing the effective solutions. in many countries, a significant percentage of the population still uses biomass for cooking and heating, rather than clean energies. for example, this is the case of 12.5 million people in brazil, 10.7 in peru, 9.6 in guatemala, and 7.1 in colombia (iea, 2014). there is a broad consensus in the literature that households tend to replace traditional cookstoves with modern ones when their socio-economic situation improves (hosier and kipondya, 1993; masera et al., 2000; heltberg, 2004; pachauri and spreng, 2004 as cited in banal-estañol et al., 2017). however, the challenges faced are rather more complex because poor-income households usually consume a fuel portfolio composed by a mix of resources to satisfy their different needs (ruiz-mercado et al., 2011; hanna and oliva, 2015). at regional level, brazil is the most representative case for success in rural electrification through a massive and specific program. the country has translated the electrification policy into the own institutional and legal framework. this implies a clear transfer of responsibility to the concessionaires to implement the policy in their concession areas according to well-defined guidelines. this responsibility went from information provision to implementation of connections and cost allocation within their specific concession areas (gómez and silveira, 2010). however, there is a program gap measuring the programs´ success and identifying the drivers for rural electrification. in this sense, a key aspect is the development of indicators to know the transcendence of programs, for instance, some authors have developed indicators clustered into four sustainability dimensions: institutional, economic, environmental, and social (feron and cordero, 2018). in this sense, more comprehensive energy poverty measurement frameworks such as the multidimensional energy cabello-vargas, et al.: review on rural energy access policies international journal of energy economics and policy | vol 11 • issue 5 • 2021 161 poverty index (mepi), and more recently the multi-tier framework (mtf), have been introduced to encourage decision makers to generate long-term and holistic energy policies. these tools might help encouraging better policies for rural energy access. some of the main drivers of electrification in latin america have been related to economic growth and democratization. the reforms, characterized by privatization and regulated market competition, have also attracted investment for key issues, but more significantly, the establishment of independent regulatory agencies has provided policy stability and transparency. however, the implementation of rural electricity policies is often ineffectual, resulting in policy failures. 6. rural energy access the seventh goal of the millennium development goals suggests that universal access to affordable, reliable, and modern energy services is central to energy poverty alleviation. to measure and promote access to modern energy services, the international energy agency (iea) created an energy development index (edi), which was designed as a composite measure of a country’s progress in the access and transition to modern energy services. the index (edi-2004) contained three dimensions: per capita commercial energy consumption; share of commercial energy in the total final energy use; and the share of the population with access to electricity. the united nation development program (undp) has recreated the energy development index (edi) and its use as an energy indicator has helped to approximate the state of energy access and consumption all around the world. however, this index cannot be applied in the rural context due to the lack of information. energy poverty usually roots in rural areas and the quality and cleanliness of energy services are not considered. thus, a more appropriate indicator for rural energy development and renewable energy development is required to indicate the status of the energy poverty problem (wang et al., 2017). national energy policies have been urban-biased and industry-biased, i.e., priority has been given to the energy demand of urban areas and industrial sectors. moreover, rural energy policies need to serve or be subject to national policies (bhanot and jha, 2012). for instance, some rural energy policies are embodied in national socioeconomic policies (e.g., rural reform and accelerating agricultural modernization in brazil), (ehnberg, ahlborg and hartvigsson, 2020). experience gained in several developing countries has demonstrated that renewable energy can be harnessed in cost-effective ways for decentralized energy applications in rural areas. these energy resources are abundant and locally available (palit and chaurey, 2011; brass, carley, maclean, and baldwin, 2012). however, supply issues of conventional energy projects make a sustainable market difficult to realize because in some cases technology transfer limits the renewable energies spread. although no clear consensus has been established on the definition of minimum energy consumptions, the minimum threshold proposed by the iea is 100 kwh of electricity and 100 kg oil equivalent of modern fuels (equivalent to 1200 kwh) per person per year for fulfilling basic human needs (agecc, 2010). a figure of 50 kwh, of electricity consumption for rural households, per person per year, which progressively increases to 160 kwh by 2030, has been used by the iea (iea, 2011). the indian government has stipulated an electricity supply of 1 kwh/day/ household, which equates to 365 kwh per household annually. for a general and relative comparison, the residential consumption of electricity varies from 1500 kwh/capita in europe, around 2000 kw h/capita in oecd asia and pacific, and around 4500 kw h/ capita in north america (narula et al., 2012). there are currently around 2.7 billion people in developing countries who rely primarily on traditional biomass for cooking and heating and about 82% of them live in rural areas (iea, 2019). the income level is the principal aspect that determines the rural households´ energy consumption (cheng and chen, 2004; wang et al., 1998; wang and song, 1993; yao et al., 2012). the principal aspects affecting residential energy consumption can be described using the conceptual framework of the energy ladder (smith et al., 1993; yao et al., 2012). this approach argues that the economic development allows people to go up in an energy ladder. as people tend to have better income, they can spend more money in energy and then move up the ladder and use cleaner, more efficient, and more convenient fuels, replacing traditional biomass and coal gradually. 7. regional electrification process kruckenberg and loubere (2016) identifies three evolutionary stages for developing countries electrification programs. the initial stage, the “donor paradigm”, occurred between 1970 and 1990, when international donors and cooperation agencies intervened in rural areas through the diffusion and transfer of renewable energy technologies (ret´s). these programs were based on the transmission of small-scale ret´s such as biogas, stoves, wind turbines, and solar heaters, which were barely self-sustainable (martinot et al., 2002). development agencies sought to demonstrate to local authorities and communities how these technologies could solve energy needs. however, many of these projects had several problems and stopped working. the projects often lacked resources to maintain and operate the equipment that was delivered to the communities. moreover, the beneficiaries were not trained to use or repair the systems, and there were no specific regulations or institutions available to guarantee the continued sustainability of projects (martinot et al., 2002; kruckenberg, 2015). the second stage, the “market-oriented paradigm”, was initiated after the 1992 united nations conference on environment and development (the rio earth summit), where new forms of multilateral assistance were adopted for ret´s transfer, including solar home systems, biogas for lighting and cooking and smallscale mini-grids (martinot et al., 2002). the development of these progressive programs, designed by development agencies, aimed to promoting these technologies by creating business models for firms and cooperation agencies in which funding programs shouldered part of the costs and risks. these interventions were based on the expectation that renewable energies would be economically profitable and technologically competitive in rural areas, but their adoption would require some institutional and financial support to local firms. cabello-vargas, et al.: review on rural energy access policies international journal of energy economics and policy | vol 11 • issue 5 • 2021162 many of these initiatives were adopted in argentina, brazil, and chile rural areas. however, usually, they were only successful in economically able communities that were already undergoing development and that had access to other public services such as water, telecommunications, health, and education; and for urban and rural communities allocated close to cities and grid connections7. this suggests that effective instruments for targeting poor communities still required government involvement and participation being complemented with more active private participation, under the light of public measures. here, it should be recalled that in many latin american countries the pro-market period coincided with a process of administrative and political decentralization that transformed public policymaking in many different areas (falleti 2010 as mentioned in banal-estañol et al., 2017). at the regional level, faguet (2004) reports that a major decentralization process in countries such as bolivia, ecuador, paraguay, colombia, peru and chile led to greater investment in human capital and social services, and the poorest regions were able to choose projects according to their needs. the third stage in electrification identified by kruckenberg and loubere (2016), the “participation paradigm,” was introduced in the early years of the 2000s. many rural electrification programs in developing countries have found that the projects impact and sustainability are usually constrained by persistent resource, capacity, and participation barriers. hence, contrary to traditional electricity technologies, the introduction of ret´s in the form of off-grid and hybrid systems in rural areas requires the creation of new development pathways related to a rural systemic perspective8. most countries in latin america complement their electrification policies with universal service policies that seek to make the service more affordable for households that have already been electrified. this practice contrasts with the trend in oecd countries to eliminate social tariffs, where they are believed to create inefficiencies and to have little impact on the energy poor9. in latin america, social tariffs are an essential part of social policies, having an important redistribution effect among poor people (pantanali and benavides, 2006 as cited in banalestañol et al., 2017). in many cases, social tariffs have been created to moderate the increase in energy prices following to the introduction of renewable energies and as a plan to increase market efficiency or to protect the vulnerable population in periods of economic difficulties, e.g., in argentina social tariffs were introduced after the 2001 crisis. 7 both, peri-urban and, isolated and remote rural areas have been forgotten in this process of electrification. 8 in this context, partnerships between organizations can help obtain the complementary resources, skills and knowledge that are necessary to promote sustainable off-grid solutions, and promote the participation of local communities. 9 the world summit for sustainable development in 2002 called for partnerships between governments, international organizations, companies, ngos, and scientific institutions, as a way to accelerate development (forsyth, 2010). within this paradigm, electrification projects are recognized as multi-level, cross-sector nature and socio-technical issues. so investment, cost-sharing models, foster knowledge transfer and capacity building, and enhance the involvement of policy initiatives and donor organizations with local communities are necessary to promote access (banal-estañol et al, 2017). in most countries, social tariffs are tied to energy consumption, although several countries also link them to other indicators such as the geographical household location or household income. for example, in argentina, brazil, chile, colombia, and peru the beneficiaries of social tariffs have been included in the census as beneath poverty income consumers. in these countries, it is believed that electricity consumption is determined by household income; but the size and location of households are used to determine their energy needs. the main challenge in rural areas is to tie energy consumption and energy needs, but the more complex communities are the most poor too. initially, the key aspect is the information, for instance in peru, sisfoh (sistema de focalización de hogares) is a system that collects information about household socioeconomic characteristics, and which calculates a poverty index that allows households being classified into seven categories. this information is used by national agencies to determine the beneficiaries of social programs (banal-estañol et al., 2017). olade (2013) has analyzed the use of social tariffs in the region and shows that in most countries, the percentage of beneficiaries of these tariffs is higher than the percentage of people living below the poverty line. rural electrification initially allows access to a low electricity consumption, and after some years this initial consumption increases to higher consumption levels, causing immediate social benefits for households through major uses of electricity. then, the results of this revision emphasize the need for government and other actors to integrate rural electrification into a broader rural energy policy to enable long-term welfare increases through electricity use (obermaier et al., 2012). in developing countries rural areas, the main use of electricity is for light and watching television, given that most households are too poor to pay and being able to afford other appliances, such as fridges or heating (khandker et al., 2013 as cited in banal-estañol et al., 2017). 8. access to clean cooking alternatives regionally, there are more than 85 million people that remain without access to clean cooking facilities. lpg and biogas are the alternatives adopted by governments and development agencies in the region to reduce health risks and environmental impacts of traditional firewood burning. electricity, as an alternative for cooking in poor rural communities, is hardly a complex choice for clean cooking due to the limited electricity availability and the lack of electric cook appliances (banerjee et al., 2016). in the 1980s, dissemination strategies mainly focused on support approaches or distribution of free stoves. experience shows that these approaches were not always supportive of the construction of high-quality stoves thus evoking a negative image of stoves that break easily are not worth spending money on them, and in consequence, are not used. commercialization10 is considered a more successful approach for sustainable stove dissemination. 10 stove producers have more routine in building stoves according to certain design standards, and because they earn money running stove businesses, they have a strong interest in selling stoves (kees & feldmann, 2011). cabello-vargas, et al.: review on rural energy access policies international journal of energy economics and policy | vol 11 • issue 5 • 2021 163 in latin america, peru and argentina have developed specific programs for dissemination of local clean stoves; brazil and colombia have received guide and support from the global alliance for clean cookstoves. however, developing countries’ governments have not dedicated efforts to introduce electricity as a fuel option for cooking in their programs and projects of access to clean cooking alternatives, neither universal access to electricity (berrueta, edwards and masera, 2008, martínez-gómez et al., 2017). according to estimations from the international energy agency (iea), the number of people relying on biomass worldwide will increase rather than decrease in the future. furthermore, even many grid-connected households still use traditional cooking devices because they are familiar with them or because cannot afford an electrical stove nor can pay for the electricity bill. the main advantage of biomass fuels is that they are available in almost everywhere and can be burnt directly. they are cheaper than other fuels and when collected from ground there are no monetary costs. biomass is a renewable and clean energy source, but the maintenance of this condition depends on the level of sustainability in the production and use of biomass: in the production side by bioenergy crops and in the use side by clean and efficient appliances. biomass is commonly burnt inefficiently in traditional cookstoves, which causes severe health problems in women and children and affects the environment (kees and feldmann, 2011), being unsustainable. increase access to modern, affordable, and clean energy services is central for sustainable poverty reduction. this situation is more relevant in the rural context because economic and energy poverty are common conditions. for this, the un millennium project (2005) calls to reduce the number of people without effective access to modern cooking fuels by 50% and make improved, efficient and clean cookstoves widely available. the efficient use of biomass or the switch to other fuels reduces the pressure on forest resources and contributes to decrease land degradation (gtz, 2007). induction stoves will be considered cleaner cooking options if the electricity is produced from a renewable energy source such as solar, wind, or hydro. however, even if renewable resources are available in rural areas, in some cases covering the energy needs must stay above the condition of renewable energy, or at least never miss the main target of alleviating energy poverty. however, even at enough and sustainable levels of electricity coverage, the shift from firewood to electricity as a primary cooking fuel was observed in only 7% of the households (banerjee et al., 2016). at the current level of rural electrification and consumption patterns, induction stoves are not suitable for addressing the access to clean cooking challenges. induction stoves spread depends on a massive access to electricity, a consolidation of a basic per capita consumption, and a consistent electricity access maintenance process is necessary to be taken up before initiating any policy introducing electricity as clean cooking fuel. areas in developing countries with high levels of household electrification and low tariff rates provide an ideal location to implement induction stoves pilot projects. induction stove technology is efficient in all cases, but can be truly clean, only if the electricity generation is also renewable based. in areas where power supply is available, specialized electrical appliances such as electric kettles, rice cookers, and microwaves are used for specific purposes only. however, not all the electric alternatives are sustainable; for instance, the electric coil stoves have been considered a bad option due to their low efficiency and high-power consumption (smith and sager, 2014). induction stoves beats the above-mentioned limitations, can be used for all cooking, and are considered 73% more efficient than electric coil stove (smith and sager, 2014). industrial production of efficient stoves has started in the last years. however, in many cases, these products are far too expensive for poor people. little experience exists with the export to other countries where sales structures for large quantities of stoves still have to be set up, being indicative that efficient stoves must run in a local production approach. however, two main technical principles are always the same: improved combustion and improved heat transfer to the pot. the best stoves have improved heat transfer and combustion efficiency, simultaneously. increased heat transfer reduces fuel requirements, whereas increased combustion efficiency decreases harmful emissions (bryden et al., 2006 as mentioned in kees and feldmann, 2011). experience has shown that the best technological solution is not necessarily the most attractive one for the customer. even very efficient stoves will fail in the market if they are not affordable for the poor, if they do not allow to prepare the most common dishes or if they are not considered to be ‘‘modern’’ and thus attractive in the opinion of the target group (kees and feldmann, 2011)11. then, the general policy framework should be supportive. it is the role of national governments to formulate complete and specific policies, to integrate cooking energy into a social and environmental perspective, to promote awareness-raising campaigns, and to provide required public funds. according to the points argued by kees and feldmann (2011), table 1 shows the main aspects to enhance clean cooking access through the role of rural energy policy in different ambits. technology access is often inadequate in the region, especially in rural areas, reducing the ability to move from traditional methods and sources to more sustainable options12. the location has a significant effect on the type of cooking fuel adopted and differences are evident between urban and rural areas. households from rural areas are less interested in adopting clean fuels because of the easy access to cheap biomass sources. efficient cookstoves could represent a step on the energy ladder towards cleaner and more sustainable solutions, e.g., electric cookstoves. improved cookstoves (ics) are devices that burn biomass, designed “to maximize thermal and fuel efficiency, operate safely and minimize emissions harmful to human health”, thus improving the cooking sustainability processes. 11 despite the advantages, improved stoves do not sell as easy as cell phones or similar gadgets. changing cooking habits is not an easy task. behavioral changes take many efforts and thus needs a long-term investment. 12 the effect of variables on ics adoption may differ according the context. each variable plays a role as a driver or a barrier to ics depending on the studies considered in the literature review (vigolo et al, 2018). cabello-vargas, et al.: review on rural energy access policies international journal of energy economics and policy | vol 11 • issue 5 • 2021164 the term “improved cookstove” refers to a range of different cooking technologies that may have different performance and cost degrees13. researchers have shown that social and cultural variables affect customers’ decisions bout cooking systems. urmee and gyamfi (2014) reviewed clean cooking programs around the world and highlighted that the reason for the failure of many projects might be that none have considered local culture and social background in the target areas (vleuten, stam, & plas, 2013)14. poor income, together with a perception of high price for efficient cookstoves in rural locations, causes resistance towards the adoption of efficient cookstoves (vigolo et al., 2018)15. the lack of electricity and cook patterns in households do not support the use of induction stoves for cooking. 9. proposal to address rural energy access problematics the analysis of the above situation suggests addressing rural energy access issues in a more systematic perspective, and a process that considers all the necessary elements to attack the lack of energy access should be developed. the proposed process, based in the ackoff´s theoretical approach (1978) to attend problems (peters, 2018), starts by pointing the initial position towards the ideal route, indicating the gap to surmount the difference. after this initial step, the key elements are enlisted, i.e., barriers, strategies, and resources, to achieve the rural coverage of energy needs at a household level. this process might be the basis to planning a rural energy policy that considers each necessary issue. the policy design must include as a part of the solution, the reconfiguration of the system that reverberates in all the system and removes the problematic causes, keeping the “solution condition” as a permanent condition in the reconfigured system. this 13 the design of stoves varies according to location and type of fuel available (vigolo et al, 2018). 14 in addition, while younger age is mostly associated with a higher propensity to purchase efficient cookstoves, some works found that older age increases the probability of efficient cookstoves adoption. 15 for example, a higher level of education positively influences the intention to purchase more sustainable cooking systems, although other scholars have found that an open mind rather than education as such may affect consumers’ choices. reconfigured condition must allow the system to work efficiently and dissolve any clue of the previous problematic condition16. for this, it is necessary to launch a problem-solving approach which considers all the elements from a systemic perspective, giving the necessary aspects to structure a holistic and exhaustive policy (jackson, 1982; moosavi, 2017). this suggested approach is outlined in table 2. rural energy access needs policy innovation that would achieve a “perfect system”17 (moosavi, 2017).18 in this redesigned system, the previous problem condition should19 be dissolved (ackoff, 1978). the creation of the “perfect system” starts identifying the difference between the current position and the perfect position to reach in the system. and20 to consider barriers, strategies, and necessary resources required to get the so called perfect position (peters, 2018). in table 2, this approach is applied for solving the rural energy access problem.21 each aspect marks the route for accurate energy access in rural areas. all of them must integrate the rural energy policy, as a core strategy to attend this issue in the order given in table 2. 16 the contributions of this work are the holistic perspective to analyze the rural energy access from the political context, and the systematic approach to propose the solution through an exhaustive policy design. 17 according to ackoff, the alternatives to solve a problem are absolution that means policy inaction, considering as solution the migration from rural to urban areas due to the lack of conditions in rural areas. resolution that is the policy extension of previous and current policies from urban to rural areas. solution that means the policy adaptation of policies for cover each problem as “bau” perspective, i.e., specific and isolated solutions for certain communities beneficiated by some technologies; and dissolution that is the policy innovation by redesign the system in absence of problem conditions. 18 in the context of this research, the prevalence of brushwood as a primary resource for cooking is due to their condition of more common and more employed resources in rural areas. however, sustainably considering their exploitation through efficient stoves. the assumption of this study is to push for clean and sustainable exploitation of brushwood through clean and efficient stoves that take advantage of the more abundant and profitable resource in rural regions. 19 to increase the diffusion of more sustainable cooking behavior among households in developing countries, there is a need to improve understanding of consumers’ cooking choices, in particular concerning to the factors affecting the use of electric cookstoves. 20 biomass strategies has shown that politicians are away from the problem and their solutions, or deny its relevance, considering biomass as an oldfashioned habit of poor people they do not have to attend (gtz, 2009). 21 access programs need enhance being evaluated to improve them and keep them in line with these changes. table 1: role of rural energy policy to enhance clean cooking access18 technical economical social19 political20 the technology is convenient, modern, and affordable for consumers the system acknowledges the relevance of efficient and modern cookstoves and supports a massive scaling-up by setting clear targets21 the dissemination approach– local producers employing local materials and providers, and ngos training and promoting campaignsstrengthens local chains attach cooking energy into the public sector agenda of countries. as well as into the activities of ngos, and other implementing agencies support research and testing centers a system for the beginning guarantees of stoves quality promote stoves and awareness in the population support partner countries in launching biomass strategies develop capacities in trainers and producers raise awareness among organizations/ international agenda support development of technologies create awareness in governments and ministries cabello-vargas, et al.: review on rural energy access policies international journal of energy economics and policy | vol 11 • issue 5 • 2021 165 table 2: assumptions to approach rural energy access situational position: initial position electricity consumption: for developing countries, access to electricity is lower than access to safe water and sewerage. so is the most transcendent problem in developing countries, although some countries have made progress due to energy reforms (davidson and sokona, 2002 & mwakasonda, 2008). access to electricity is associated with access to roads, street lighting, and paving cooking resources: cooking firewood is the main alternative in developing countries as it is generated and processed on-site. in rural areas is the cheapest resource and emits less carbon dioxide than fossil fuels per unit of mass (broadhead et al., 2001); heating and cooking wood will be the main resource for the next 25 years (iea, 2004 & broadhead et al., 2001) position to reach: ideal position: having constant and quality electricity, and intradomiciliary contamination-free cooking schemes, friendly to the environment and more efficient and sustainable than traditional ones (iea, 2016); according to the iea energy model the position is: 2030 access rural coverage alternatives to achieve the goal electricity 100% 37% connected to the grid. 63% not in the grid: 70% mini grids and 30% autonomous generation clean cooking 100% 37% by lpg stoves. 38% by clean cookstoves and 25% by biogas space to achieve=ideal position—initial position affordability, social local perspective, and community connection; and counteract inaccessibility, dispersed households, low density, unavailability of generating and distribution companies, maintenance, lack of qualified resources, dependence on support barriers: geographical difficulties, remoteness, and dispersion of households, climate, reduce demands, losses, high investment, tariffs and costs limit grid extension22. also, some causes affecting programs are political instability, poor market structure, lack of regulatory frameworks and tariff transparency, corruption and weak institutional configuration; also the costs inhibit investment and multilateral support, limit technical capacity and evaluation tools, affecting the execution of projects context: rural characteristics: ample dispersion, the remoteness of generation points, low consumption, and low density, high supply and maintenance costs, and limited capacity to pay. this increases the unit cost of energy (eclac, gtz, 2000). by 2035 from 100% of the population without access, 90% will live in developing countries23 and much in rural areas24 actions to remove barriers: laws are necessary to manage renewable energies; policies should encourage private investment, regulate them, and the stakeholder linkage. integrating the community is necessary to create transparent, effective, coordinated, and efficient schemes to provide training, promote development, and empower communities25 productive uses of electricity will be encouraged by increasing complementary infrastructure, access to services, and the market. it is important to consider that because resources are scarce, policies should drive cost-effective technologies, and projects should consider the availability and characteristics of resources to choose technologies. supports must focus on renewable energy technologies to make them competitive26 institutional support: national level: generate the legal and regulatory framework, plans, and programs. it covers tariff regulation, generation control, coverage targets, investment, access maps, technological development, incentives, and community support. this level is responsible for planning and regulatory control regional and state-level: provide the link between the national and local levels. at this level are state and municipal governments, rural electrification agencies. besides, levels are being responsible for strategies and tactical control. county or local level: at this level, communities must engage, coordinate management, be connected to higher levels, and check compliance with quality standards. in this range are executed the projects management: property and management must be adapted to the needs and context of the community27. at high demands, companies would own and manage. at low demands and little productive activity, communities would exercise property but being management granted, and maintaining the property of government to ensure energy supply and create bases for tenders and concessions, and to sponsor competitiveness actions: rural areas are moving to depend on energy products and not from natural resources28. when evaluating policies it is necessary to consider information, location, and legitimation (derlien, 2012). there is great emphasis on proposing projects, but no longer in their review and evaluation, characterized by disinterest and lack of mechanisms of action. (pereira, 2013) requirement resources investment: problems in electrification programs are attributable to tariff structure (elias and victor, 2005; almeshqab and ustun, 2019), as it is designed without adapting to the characteristics of communities and without considering the ability to pay at increasing tariffs, and do not incentivize the increase in demand according to staggered schemes to increase per capita consumption technologies: creating tools to assess local characteristics and resources by region and choose technologies and strategies according to the region. these practices need formalization being institutionalized, being regulated, and being replicated (pereira, 2010) rural energy agency: creating institutions with national competence would make it easier to formalize and strengthen the institutional framework and make investing and creating markets more attractive; it also institutionalizes and standardizes access29 available resources: renewables energies are available and helps to generate enough energy, although being intermittent it is necessary to create hybrid systems in micro-networks. besides, distributed generation is a sustainable alternative in remote and dispersed regions necessary resources (constrains) integration in communities: it takes 7 years for households to use electricity and after these 7 years, still the process of adoption is slow (cook, 2011). that is why it is important to distinguish between policies for coverage and policies to enhance consumption30. in electrified regions, the marginal cost31 of electrifying additional households is beneath because costs are falling down scales.32 technology: users have problems using technology because is complex (bazilian, nussbaumer, eibs-singer and brew-hammond, 2012; espinoza, muñoz-cerón, aguilera and de la casa, 2019) . already working, technology thunder, creating flashing, breakdowns, dissatisfaction, disuse, replacement problems, misuse, and abandonment by non-friendly design investment: is necessary to increase resources towards rural areas, managing them based in a congruent policy to accurate access rural energy agency is necessary a specific agency to attend coverage quality, per capita consumption and all issues of rural energy cabello-vargas, et al.: review on rural energy access policies international journal of energy economics and policy | vol 11 • issue 5 • 2021166 according to this approach, a key aspect is the identification of barriers, because once the barriers are identified, the definition of strategies and resources to achieve the ideal position is more accurate. in table 3, the entire barriers are enlisted according to their category. each stage can integrate parts of the policy to consolidate a complete, efficient, and general set of instruments to increase electricity access and consumption and to introduce clean and affordable cooking alternatives for all, in rural areas. this activity can help in planning and developing general guidelines for a rural energy policy.2223242526272829303132 10. final general discussion until now, rural energy policies mainly have involved the extension of existing electric systems in densely populated areas to rural areas that cannot benefit from scale economies, promoting renewable energies, such as solar and mini-grids. they also have tried to attain universal policies for electrification, making electricity affordable and promoting its use in poor households (banal-estañol et al., 2017). however, rural energy problems are 22 decentralized distributed generation alternatives that include small, dispersed sources of generation from renewable energy technologies are emerging as a viable alternative to grid supply. these technologies are particularly suited for areas that have low demand for electricity and have low load factors (kapil narula, 2012). 23 resource pressure will remain constant, depletion will advance; energy demand will increase 95% by 2035. 24 much of the efforts of developing countries will address access in cities (iea, 2015). by 2035, developing countries would have full access in cities, but not in rural areas where the changes will not be as significant. 25 the world bank suggests as conditions to take advantage of the benefits of energy: infrastructure and markets with productive activities, agricultural growth and alternatives to improve income and social development. 26 the level and approach of supports is basic, as their indiscriminate use makes competition and market creation irrelevant; few supports cannibalize the market and over stimulate indiscriminate competition, affecting rets, and devaluing those with potential. by directing support to a certain technology, it grows, limiting others. 27 in order for users being interested and involved, they can assume ownership of the schemes, paying with government support. this will help to appropriate and learn how to use technologies. when generation schemes are far away, there is no economic strength, households’ lack of sufficient income, and costs are high, government must maintain ownership of facilities and equipment renting to companies and charge fees to users, making a difference to maintain the social approach. the service must be permanent, adaptable to demand, generate alternating and non-direct current, manage the load, reduce losses, efficient, and control discharges. 28 the use of electricity and gas arises from the expansion of cities and the industrial revolution; demand for these energy products and their economic efficiency, generates economies of scale, centralizing production in large generation plants with extensive distribution networks and complex logistics structures of delivery. 29 in developing countries, rural projects are un-regulated and support lack to extend to consumers. 30 it is necessary to increase coverage and incentivize demand. world bank studies showed that in rural areas poor with electricity, connections remain low from high connection costs for income level. 31 to the extent that tariffs cover execution and maintenance costs, the costs of new connections, based on cost reduction due to a beneath marginal cost in comparison to the initial connections, generating a positive effect in energy dissemination through these communities. 32 as the basic input electricity is its demand and cross elasticity are inelastic, in addition to some fuels tend to behave as substitutes for others (cook, 2011). not limited to electrification only, since the more critical issue is associated to the absence of clean cooking alternatives, which has forced a large majority of rural populations to use biomass in primitive and unsustainable cookstoves (balachandra, 2011). national energy policies and poverty reduction strategies very often focus only or mainly on electrification and do not reflect adequately the energy–poverty nexus (undp, 2006) and the relevance of sustainable cooking access in the energy equation for the coverage of rural household needs. on the international agenda, sustainable energy access started to become important, especially under the framework of the carbon market initiatives (kees and feldmann, 2011). in the case of cooking by electric appliances, like electric induction stoves, the consideration of these alternatives keeps the approach of clean cooking alternatives, but the evaluation runs in the context of electrification, due to the dependence on electricity as a primary resource of these appliances. however, in a long term, and as a part of a continuous energy policy for rural areas, the transition towards electric appliances like induction stoves is a suitable goal to target, but the key is to increase coverage and consumption of electricity in a complete, constant, and continuous manner, to ensure the total energy coverage. therefore, this situation is part of the issues that push the need for specific policies in the context rural areas because issues like coverage, consumption, and appliance transition of are transcendental for rural regions regions (gómez and silveira 2011)33. there is a need to enhance the insertion of policies and configure them as a part of an energy policy, in which local institutions and communities are better placed to share their knowledge34. these local institutions will be useful for designing, implementing, and operating effective off-grid rural energy policies. in order to attend rural energy, our central proposition is to adopt a rural energy policy which encompass all multidimensional aspects related to energy in rural areas in a holistic perspective. some frameworks emerge as alternatives to evaluate rural energy issues. the multi-tier framework developed by esmap, and the multidimensional energy poverty index (mepi) (nussbaumer et al., 2011) could serve as instruments to evaluate the evolution and relevance of rural energy access but using only rural areas information and adapting each variable to this context. the mepi is a composite index that measures energy poverty through a set of quantities related to energy access, consumption, services and impacts for people. compared to the multi-tier framework, the mepi is more feasible to be used in the rural context due to a simpler process and availability of local information. at a regional level, a study conducted by santillán et al. (2020) analyzed energy poverty in 7 countries of the latin 33 these motivate collaborative efforts and agreements among agents with different interests, and activates synergies. 34 in brazil, the national government has launched a digital universalization initiative that aims to provide universal access to information technologies. the initiative pursues social inclusion and has electricity access as a prerequisite. cabello-vargas, et al.: review on rural energy access policies international journal of energy economics and policy | vol 11 • issue 5 • 2021 167 america region. the authors determined a high correlation between mepi and hdi indices in countries like guatemala, peru, méxico and colombia. this study has applied the mepi, as a practical tool, in a comparative form at a regional level, but it considers only national averages and does not attend specifically the rural energy situation.353637 11. recommendations and considerations for further research comprehensive rural energy policies should be promulgated to guide rural energy aspects. the fact that rural energy is an aggregated concept determines that the rural energy policy system consists of single policies for specific energy sources, while different government administrations promulgate these policies38. 35 economic barriers stem from high costs of technologies, capital, and investment, decentralized structures, lack of pricing policies, and support for renewables. 36 centralizing on a small-scale increase efficiency, profitability, durability, economies of scale, low losses, and costs, offsetting low demands from low-income scattered households. 37 technical standards, infrastructure costs, tariffs, losses, regional structure, and city priority, raise the cost of distribution to rural areas; private companies do not invest in rural electrification out of fear and because workers do not want to work in rural areas; benefits and incentives are necessary in this regard. 38 the government should investigate rural residents demand and attitudes the promulgation of a comprehensive rural energy policy can help to define the functions of different departments, different importance of energy sources, and allocation of resources for rural energy development. rural energy policy makers should be aware that energy transition often takes decades, and this implies that the design and implementation of policies should focus not only on current issues, technologies, and conditions, but also on long-term planning. the government should formulate rural energy policies according to the different energy demands. also, the government should communicate policies to make rural residents aware of policy content, which can improve policy awareness and support39. the emphasis should be on innovative policies, institutional mechanisms, and financial support40. some recommendations to design a rural energy policy are: • creation of rural energy authorities • establishment of funds to enable delivery of energy resources • integration of business principles to make energy affordable and equitable for households • treatment of entrepreneurs as strategic targets. towards new rural energy policies and combine them with local conditions before the design and implementation of rural energy policies. 39 governments’ functions relating to rural energy should be centralized. it is unavoidable that the design and implementation of rural energy policies involve many government departments. 40 government should support market-oriented approaches that make the energy market equally accessible and attractive to local investors, communities, and consumers (barnes and floor, 1996 & balachandra, 2011). table 3: general barriers for rural energy access barriers characteristics affects to economics16 absence of economic supports high initial costs of capital high transactional costs inattention in remote areas by high costs incorrect management of rates use of candles, waste, and wood market attractiveness17 unknown business high volatility of investments high associated expenses no creation of technician jobs does not improve access in regions migration to cities insufficient technical knowledge no resource assessments available no economic information reduced economic support lack of technical standards no increase access in rural areas lack of replacement of parts and specific tools absence of qualified human resources geographical environment natural barriers climate barriers the economic gap for high supply costs companies don’t accept to participate design of advice programs inefficient management no complete information on maintenance and postacquisition service lack of technical standards does not improve access in regions delay to provide technical tools lack of trained human resources legal gaps and lack of political involvement18 regulatory framework specific laws loss of consumer confidence communities not involved economic problems technological barriers misuse and complexity of technologies bad approach to technology and conception on users corruption, conflict of interest, reduced credits and manipulation barriers associated with managing the generation systems configuration of the distribution network: is necessary not to build too many nearby networks to successfully configure them rates: electric meters to prevent equal rates from being at different consumptions and, to prevent rates from changing at equal consumption interconnection: is necessary enough infrastructure to support hybrid systems barriers associated with supply system management energy inconsistency: renewable energies are intermittent. it is recommended to have hybrid systems equipment: by not serving generators in distant areas, their arrangement and replacement are complex. it is necessary to have a substitute generator capacity: micro-networks are demand-adaptive and autonomous schemes are not; must be integrated to complement cabello-vargas, et al.: review on rural energy access policies international journal of energy economics and policy | vol 11 • issue 5 • 2021168 rural energy policies should pay attention to introducing market mechanisms to support the development of rural energy markets. although some rural energy projects are effective with support from the government, they are unsustainable in the long-term. gollwitzer highlights the importance of the organizational set-up, which includes adopting and enforcing norms and regulations because once the government eliminates subsidies or ends preferential policies, rural residents discontinue using energy technologies or equipment intended to alleviate climate change or achieve sustainable development. consequently, governments should establish an encompass rural energy market frameworks, encourage private investment, and provide some incentivizing policies (wu, 2019). this research has systematically reviewed the literature about rural energy access in relation to electrification and clean cooking from a policy perspective. by identifying the main barriers, resources, and drivers affecting rural access, this review contributes to better understanding the theme, especially remarking the need to launch a core, complete and specified rural energy policy based on the rural energy needs and not as a part of another development programs. some key findings at regional level (gnesd, 2008)41 to go from energy poverty to energy access in rural areas of latin america are: (i) lack of strategic planning and long-term vision. (ii) inaccessibility of clean fuels due to the nature of rural settlements (rural slums). (iii) inability to afford clean fuels because of upfront connection costs. (iv) a lack of formal monitoring mechanisms. (v) mistargeted supports. (vi) a lack of awareness regarding the use of clean fuels and clean cooking appliances. 12. conclusion compared to rural electrification, the situation for clean cooking access is even worst. on many occasions, the problems are accentuated by fuel insufficiency, biomass overexploitation, and poor reliability and services quality available to the rural households, despite numerous initiatives by the local governments (neudoerffer et al., 2001). also there are difficulties for poor households financing for lighting and cooking fuels (rao et al., 2009 and balachandra, 2011). the current situation for rural energy access is characterized by • a lack of effective policies and programs • a lack of an institutional framework • inefficient and ineffective governance • misdirected focus and targets • ineffective delivery mechanisms • a lack of private incentives. according to this revision, cooking access is still behind in the race for energy access because it is a complex issue. in many countries, it is not clear which ministry (energy, environment, or economy) would be involved, e.g., in setting up a stove program or firewood energy. the same applies to donor organizations and their different departments. many stove programs failed due to 41 gnesd is the global network on energy for sustainable development, an unep network to energy issues. their approach or the technology involved42. moreover, cooking energy is not considered a central topic among many politicians in developing countries nor donor organizations. policies related to clean cooking usually focus either on the demand side, e.g., promoting the production and use of clean stoves, or on the supply side, e.g., in reforestation and forest management programs (kees and feldmann, 2011). however, a complete intervention must pay attention to both aspects simultaneously. policymakers should use the hdi more systematically to make sure that rural electrification efforts reach the poorest communities. we agree with gómez and silveira (2010) that the hdi can be a useful planning tool, but it should be used considering other factors43. subsidized electricity tariffs are the typical instruments used by latin america governments to foster consumption, but it has been economic growth experimented in recent years that has enabled millions of people to leave poverty, beginning the purchase of electrical equipment, such as fridges and heating systems. increased consumption levels in rural and isolated areas is a much more difficult goal and will require a different set of policy instruments. many communities in these areas live below the poverty line and lack access to other basic services, such as roads, safe water, and telecommunications. this means that electrification strategies cannot rely on market solutions. besides, the electrification of these regions has been based on off-grid renewable energies that are enough only to use basic services such as light and television, but not to other appliances that consume more energy, such as fridges, clean stoves, and agricultural machinery. this is a central point because in some cases electricity supply is enough to consider access and statistically account a community as electrified, but not enough for a sustainable consumption covering all the needs of the rural house. in the coming years, the latin american countries will have to define the quality of the electricity service that they want to offer to their rural communities and they will need to verify whether the technological solutions that they currently offer are appropriate for meeting this goal (banal-estañol et al., 2017) in a sustainable manner, i.e., economically affordable, socially inclusive and enough, and environmentally clean and efficient. also, the appropriate and multifactorial decision choices are an integral part of long-term project sustainability to ensure rural energy access consistently. the multidimensional nature of rural energy access request complete attention at all levels, but it is necessary to start at the normative level to approach and attend access correctly. based on our revision, it is concluded that (1) a comprehensive rural energy policy is lacking, and most policies focus on techno-economic aspects; (2) most rural energy policies are problem-oriented and deficient in predictability; (3) the regional heterogeneity of rural residents’ willingness and interests are not 42 while biomass is used widely as an energy source and is of high economic importance in many economies, political frameworks often do not reflect this situation. biomass is and will remain the most important fuel for onethird of the world’s population and considering its negative impacts on people and environment, the challenge is how to make its use sustainable. 43 a relevant area for further research would be an examination of the community-based projects implemented in the region. cabello-vargas, et al.: review on rural energy access policies international journal of energy economics and policy | vol 11 • issue 5 • 2021 169 adequately considered in rural energy policies; (4) the current energy administrative systems restricts the implementation of rural energy policies; (5) the role of the energy market system has been overlooked and (6) there are no responsible institutions for rural energy. the respective policy implications at regional level are (1) designing and implementing a comprehensive rural energy policy; (2) establishing a rural energy management system; (3) taking into consideration the regional heterogeneity of rural residents toward rural energy policy elaboration; (4) centralizing functions relating to rural energy; (5) introducing market mechanisms and strengths to develop rural energy and (6) creating a specific agency to coordinate rural energy access. rural energy access is a topic lacking a correct perspective. the problem is approaches from a general perspective and at the micro-level, but solving the problem needs a specific perspective exclusively for rural regions and a macro level approach at normative and policy levels. the different aspects of rural energy access are not complicated concepts to understand and many of them are intuitive. the issue is the consideration of all these aspects in a systemic and integrated manner that accurately accomplish the exhaustive condition of complexity in the study of rural energy access and the need to develop a complete rural energy policy. this is the core contribution of this study. the structuration of a complete and systematic approach will help to better understanding the general aspects of rural energy policy as a solution of the related rural energy poverty problem. 13. acknowledgments juan-enrique cabello-vargas acknowledges the support received from consejo nacional de ciencia y tecnología (conacyt) de méxico through a ph. d. scholarship. he also acknowledges araceli vargas ponce de león for the additional support provided to allow the continuity of this research work. the authors also acknowledge the invaluable help provided by dr. naín pedroza and dr. pablo álvarez-watkins, who suggested several improvements to the content and writing of this paper. author contributions: j. enrique cabello-vargas: investigation, data curation, writing-original draft. azucena escobedoizquierdo: supervision, resources. arturo morales-acevedo: conceptualization, validation, writing-reviewing and editing. references ackoff, r.l. (1978), the art of problem solving: accompanied by ackoff’s fables. new york: wiley. almeshqab, f., ustun, t.s. (2019), lessons learned from rural electrification initiatives in developing countries: insights for technical, social, financial and public policy aspects. renewable and sustainable energy reviews, 102, 35-53. balachandra, p. (2011), modern energy access to all in rural india: an integrated implementation strategy. energy policy, 39(12), 78037814. balza, l., jimenez, r., mercado, j. (2013), privatization, institutional reform, and performance in the latin american electricity sector. idb technical note tn-599. washington, dc: inter-american development bank. banal-estañol, a., calzada, j., jordana, j. (2017), how to achieve full electrification: lessons from latin america. energy policy, 108, 55-69. banerjee, m., prasad, r., rehman, i.h., gill, b. (2016), induction stoves as an option for clean cooking in rural india. energy policy, 88, 159-167. bazilian, m., nussbaumer, p., eibs-singer, c., brew-hammond, a., modi, v., sovacool, b., aqrawi, p.k. (2012), improving access to modern energy services: insights from case studies. the electricity journal, 25(1), 93-114. bazilian, m., nussbaumer, p., rogner, h.h., brew-hammond, a., foster, v., pachauri, s., kammen, d.m. (2012), energy access scenarios to 2030 for the power sector in sub-saharan africa. utilities policy, 20(1), 1-16. berrueta, v.m., edwards, r.d., masera, o.r. (2008), energy performance of wood-burning cookstoves in michoacan, mexico. renewable energy, 33(5), 859-870. bhanot, j., jha, v. (2012), moving towards tangible decision-making tools for policy makers: measuring and monitoring energy access provision. energy policy, 47, 64-70. bonan, j., pareglio, s., tavoni, m. (2017). access to modern energy: a review of barriers, drivers and impacts. environment and development economics, 22(5), 491-516. brass, j.n., carley, s., maclean, l.m., baldwin, e. (2012), power for development: a review of distributed generation projects in the developing world. annual review of environment and resources, 37, 107-136. broadhead, j., bahdon, j., whiteman, a. (2001), woodfuel consumption modelling and results. rome, italy: food and agricultural organisation of the united nations. brown, d.s., mobarak, a.m. (2009), the transforming power of democracy: regime type and the distribution of electricity. american political science review, 103, 193-213. calzada, j., sanz, a. (2018), universal access to clean cookstoves: evaluation of a public program in peru. energy policy, 118, 559-572. ciller, p., lumbreras, s. (2020), electricity for all: the contribution of large-scale planning tools to the energy-access problem. renewable and sustainable energy reviews, 120, 109624. coelho, s.t., goldemberg, j. (2013), energy access: lessons learned in brazil and perspectives for replication in other developing countries. energy policy, 61, 1088-1096. cook, p. (2011), infrastructure, rural electrification and development. energy for sustainable development, 15(3), 304-313. davidson, o.r., sokona, y. (2002), a new sustainable energy path for african development: think bigger act faster. cape town: energy and development research centre, university of cape town. p28. denyer, d., tranfield, d. (2009), producing a systematic review. washington, dc: american psychological association. detchon, r., van leeuwen, r. (2014), policy: bring sustainable energy to the developing world. nature news, 508(7496), 309. ehnberg, j., ahlborg, h., hartvigsson, e. (2020), approach for flexible and adaptive distribution and transformation design in rural electrification and its implications. energy for sustainable development, 54, 101-110. elias, r.j., victor, d.g. (2005), energy transitions in developing countries: a review of concepts and literature. in: program on energy and sustainable development, working paper. stanford: stanford university. espinoza, r., muñoz-cerón, e., aguilera, j., de la casa, j. (2019), feasibility evaluation of residential photovoltaic self-consumption cabello-vargas, et al.: review on rural energy access policies international journal of energy economics and policy | vol 11 • issue 5 • 2021170 projects in peru. renewable energy, 136, 414-427. falleti, t.g. (2010), decentralization and subnational politics in latin america. cambridge university press. feron, s., cordero, r.r. (2018), is peru prepared for large-scale sustainable rural electrification. sustainability, 10(5), 1683. gacitua, l., gallegos, p., henriquez-auba, r., lorca, a., negretepincetic, m., olivares, d., wenzel, g. (2018), a comprehensive review on expansion planning: models and tools for energy policy analysis. renewable and sustainable energy reviews, 98, 346-360. goldemberg, j., prado, l.t.s. (2013), the decline of sectorial components of the world's energy intensity. energy policy, 54, 62-65. gómez, m., silveira, s. (2011), the institutional dimension of rural electrification in the brazilian amazon. in: world renewable energy congress-sweden. linköping; sweden. linköping university electronic press. p3444-3451. gómez, m.f., silveira, s. (2010), rural electrification of the brazilian amazon-achievements and lessons. energy policy, 38(10), 62516260. gómez, m.f., silveira, s. (2015), the last mile in the brazilian amazon-a potential pathway for universal electricity access. energy policy, 82, 23-37. gómez-hernández, d.f., domenech, b., moreira, j., farrera, n., lópezgonzález, a., ferrer-martí, l. (2019), comparative evaluation of rural electrification project plans: a case study in mexico. energy policy, 129, 23-33. hanna, r., oliva, p. (2015), moving up the energy ladder: the effect of an increase in economic well-being on the fuel consumption choices of the poor in india. american economic review, 105(5), 242-246. he, l.y., hou, b., liao, h. (2018). rural energy policy in china. china agricultural economic review, 10(49), 0190. henisz, w.j., zelner, b.a., guillén, m.f. (2005), the worldwide diffusion of market-oriented infrastructure reform, 1977–1999. american sociological review, 70(6), 871-897. hou, b.d., tang, x., ma, c., liu, l., wei, y.m., liao, h. (2017), cooking fuel choice in rural china: results from microdata. journal of cleaner production, 142, 538-547. jackson, m.c. (1982), the nature of soft systems thinking: the work of churchman, ackoff and checkland. journal of applied systems analysis, 9(1), 17-29. jimenez, r. (2017), barriers to electrification in latin america: income, location, and economic development. energy strategy reviews, 15, 9-18. kees, m., feldmann, l. (2011), the role of donor organisations in promoting energy efficient cook stoves. energy policy, 39(12), 7595-7599. khandker, s.r., barnes, d.f., samad, h.a. (2012), the welfare impacts of rural electrification in bangladesh. the energy journal, 33(1), 187-206. krauter, s.c., kissel, j.m. (2005), re in latin america: actual state and potential of renewable energies in the region. refocus, 6(1), 20-26. kruckenberg, l.j. (2015), renewable energy partnerships in development cooperation: towards a relational understanding of technical assistance. energy policy, 77, 11-20. kruckenberg, l.j., loubere, n. (2016), social innovations for energy access: organizing sustainable energy for all. lausanne switzerland: in call for papers, tech4dev conference. p2-4. lewis, j.j., pattanayak, s.k. (2012), who adopts improved fuels and cookstoves? a systematic review. environmental health perspectives, 120(5), 637-645. martínez-gómez, j., guerrón, g., riofrio, a.j. (2017), analysis of the plan fronteras for clean cooking in ecuador. international journal of energy economics and policy, 7(1), 135. martinot, e., chaurey, a., lew, d., moreira, j.r., wamukonya, n. (2002), renewable energy markets in developing countries. annual review of energy and the environment, 27, 309-348. moosavi, v. (2017), grand technologies for grand energy challenges: a futuristic scenario for solar energy in the age of information. arxiv,1708.06600. nagothu, s. (2016), measuring multidimensional energy poverty: the case of india, master’s thesis. norway: nhh norwegian school of economics. narula, k., nagai, y., pachauri, s. (2012), the role of decentralized distributed generation in achieving universal rural electrification in south asia by 2030. energy policy, 47, 345-357. nussbaumer, p., bazilian, m., modi, v. (2012), measuring energy poverty: focusing on what matters. renewable and sustainable energy reviews, 16(1), 231-243. nussbaumer, p., nerini, f.f., onyeji, i., howells, m. (2013), global insights based on the multidimensional energy poverty index (mepi). sustainability, 5(5), 2060-2076. nygaard, i. (2010), institutional options for rural energy access: exploring the concept of the multifunctional platform in west africa. energy policy, 38(2), 1192-1201. obermaier, m., szklo, a., la rovere, e.l., rosa, l.p. (2012), an assessment of electricity and income distributional trends following rural electrification in poor northeast brazil. energy policy, 49, 531-540. ozughalu, u.m., ogwumike, f.o. (2019), extreme energy poverty incidence and determinants in nigeria: a multidimensional approach. social indicators research, 142(3), 997-1014. pachauri, s., spreng, d. (2011), measuring and monitoring energy poverty. energy policy, 39(12), 7497-7504. palit, d., chaurey, a. (2011), off-grid rural electrification experiences from south asia: status and best practices. energy for sustainable development, 15(3), 266-276. panos, e., densing, m., volkart, k. (2016), access to electricity in the world energy council’s global energy scenarios: an outlook for developing regions until 2030. energy strategy reviews, 9, 28-49. pereira, m.g., freitas, m.a.v., da silva, n.f. (2011), the challenge of energy poverty: brazilian case study. energy policy, 39(1), 167-175. pereira, m.g., sena, j.a., freitas, m.a.v., da silva, n.f. (2011), evaluation of the impact of access to electricity: a comparative analysis of south africa, china, india and brazil. renewable and sustainable energy reviews, 15(3), 1427-1441. peters, b.g. (2018), policy problems and policy design. united kingdom: edward elgar publishing. pinheiro, g., rendeiro, g., pinho, j., macedo, e. (2012), sustainable management model for rural electrification: case study based on biomass solid waste considering the brazilian regulation policy. renewable energy, 37(1), 379-386. puzzolo, e., pope, d., stanistreet, d., rehfuess, e.a., bruce, n.g. (2016), clean fuels for resource-poor settings: a systematic review of barriers and enablers to adoption and sustained use. environmental research, 146, 218-234. qurat-ul-ann, a.r., mirza, f.m. (2020), meta-analysis of empirical evidence on energy poverty: the case of developing economies. energy policy, 141, 111444. rahman, m.m., paatero, j.v., lahdelma, r. (2013), evaluation of choices for sustainable rural electrification in developing countries: a multicriteria approach. energy policy, 59, 589-599. rosenthal, j., quinn, a., grieshop, a.p., pillarisetti, a., glass, r.i. (2018), clean cooking and the sdgs: integrated analytical approaches to guide energy interventions for health and environment goals. energy for sustainable development, 42, 152-159. ruiz-mercado, i., masera, o., zamora, h., smith, k.r. (2011), adoption and sustained use of improved cookstoves. energy policy, 39(12), 7557-7566. cabello-vargas, et al.: review on rural energy access policies international journal of energy economics and policy | vol 11 • issue 5 • 2021 171 santillán, o.s., cedano, k.g., martínez, m. (2020), analysis of energy poverty in 7 latin american countries using multidimensional energy poverty index. energies, 13(7), 1608. sarr, s., dafrallah, t., ndour, a., fall, a. (2008), global network on energy for sustainable development (gnesd). united states: united nations sheinbaum-pardo, c., ruiz, b.j. (2012), energy context in latin america. energy, 40(1), 39-46. slough, t., urpelainen, j., yang, j. (2015), light for all? evaluating brazil’s rural electrification progress, 2000-2010. energy policy, 86, 315-327. urmee, t., gyamfi, s. (2014), a review of improved cookstove technologies and programs. renewable and sustainable energy reviews, 33, 625-635. van der vleuten, f., stam, n., van der plas, r.j. (2013), putting rural energy access projects into perspective: what lessons are relevant. energy policy, 61, 1071-1078. van ruijven, b.j., schers, j., van vuuren, d.p. (2012), model-based scenarios for rural electrification in developing countries. energy, 38(1), 386-397. vigolo, v., sallaku, r., testa, f. (2018), drivers and barriers to clean cooking: a systematic literature review from a consumer behavior perspective. sustainability, 10(11), 4322. wang, b., li, h.n., yuan, x.c., sun, z.m. (2017), energy poverty in china: a dynamic analysis based on a hybrid panel data decision model. energies, 10(12), 1942. wolfram, c., shelef, o., gertler, p. (2012), how will energy demand develop in the developing world? journal of economic perspectives, 26(1), 119-38. world bank. (2016), sustainable energy for all. wu, s. (2020), the evolution of rural energy policies in china: a review. renewable and sustainable energy reviews, 119, 109584. yadoo, a., cruickshank, h. (2012), the role for low carbon electrification technologies in poverty reduction and climate change strategies: a focus on renewable energy mini-grids with case studies in nepal, peru and kenya. energy policy, 42, 591-602. yadoo, a., cruickshank, h. (2017), the value of cooperatives in rural electrification. energy policy, 38(6), 2941-2947. yao, c., chen, c., li, m. (2012), analysis of rural residential energy consumption and corresponding carbon emissions in china. energy policy, 41, 445-450. zuluaga, m.m., dyner, i. (2007), incentives for renewable energy in reformed latin-american electricity markets: the colombian case. journal of cleaner production, 15(2), 153-162. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020704 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 704-712. the role of intellectual human capital, human resource practices and intention to use of energy resources on the company performance didin fatihudin1*, murpin josua sembiring2, muhammad anang firmansyah1, iis holisin3 1department of economics and business, muhammadiyah university, surabaya, indonesia, 2department of economics and business, ma chung university, malang indonesia, 3department of mathematics educations, muhammadiyah university, surabaya, indonesia. *email: didin.fatihudin@fe.um-surabaya.ac.id received: 15 july 2020 accepted: 17 september 2020 doi: https://doi.org/10.32479/ijeep.10623 abstract the study aimed to analyze the relationship between the performance of companies and human capital with the help of moderating role of intention to use of renewable energy through various modes while providing an eminent view of the literature. the approach of quantitative has been used by this study. while reviewing the literature, the permitted issues are covered into three categories which were neglected previously: human capital analysis – relationships of management performance along with the intention to use of renewable energy, measuring and defining of human and intellectual capital, and hrm. intention to use renewable energy significantly and positively moderates among the relationship between intellectual human capital, and the company’s performance. the results of this study are pertinent to the relationship among various aspects of human resources and performance of companies which were lately experienced in rapid developments. these findings provided the guidelines to the policymakers that they should provide the focus on the formulation of the policies related to the intellectual human capital and effective use of renewable energy that enhance the company performance. keywords: human capital, human resources management, management performance, intentions to use renewable energy jel classifications: q2, j24, o15 1. introduction performance evaluation of human capital based companies is an interesting thing that companies need to develop in the future. one of the important and main elements of intellectual capital is termed as human capital under the ownership of a company. during the company’s performance assessment, the use of physical resources is more this time. for the measurement of company’s performance, the element of financial perspective dominates with its accuracy but the actual basis of driving financial values is considered as human capital inducing the innovations, ideas, and knowledge (handayani and sinulingga, 2019). additionally, for the company, human capital is considered as a core. the role of human resources in the future of companies countered as crucial, even though mentioning of capital for the hr widely not seems to be embraced by the people of business. the continuity of human resources counted as capital exits over time and the businesses dynamic environments and scientific progress (suryani et al., 2017). the advantages of hr compared to other factors of production in a company’s competitive strategy that is inclusive of a special enterprise, entrepreneurship and innovation, different capabilities of products and services, unique quality which could be developed according to needs. using the intentions of renewable energy countered as dominant sources that contribute to various elements significant for this journal is licensed under a creative commons attribution 4.0 international license fatihudin, et al.: the role of intellectual human capital, human resource practices and intention to use of energy resources on the company performance international journal of energy economics and policy | vol 10 • issue 6 • 2020 705 companies. whether discussing individual elements of companies or singly, the intentions of using renewable energy positively exit between all the relevant factors. the importance of renewable energy dominates among economic grounds and companies (ari and yikmaz, 2019; chen et al., 2018). link of renewable energy exits in performance of companies whether having positive or negative interpretations. various factors contribute towards the company performance, while the intention of using renewable energy positively exits among the contributions (bozorgparvar et al., 2018). plenty of factors influences the performance of companies where intellectual human capital dominates an important one, while the using of renewable energy strongly inserts the effects among them. various intentions are used to enhance the performance of companies whereas the existence of renewable energy dominates among the intentions for enhancing performance (demirbag and yilmaz, 2020). training and development countered as eminent sources for company performance, while the use of renewable energy and its intentions puts significant impact between them. peoples are recruited and placed in various sites for increasing the performance but the importance of renewable energy intentions and its usage inserts important aspects among them (dogan and ozturk, 2017). the effect of using intentions of renewable energy exits between the factors in companies that are used to enhances the level of performance. there are five components of human capital or human resources which are named as organizational climate, individual capability, leadership, workgroup effectiveness, and individual motivation (handayani and sinulingga, 2019). the determination of a company’s values is dependent on the components of human capital and hr which has a variant role in the creation of human capital of companies. therefore, given the enormous role of hr in the company, the company’s management should be more proactive in making hr as a human capital that must be given attention and continuous development with significant variations in the environment of businesses (omran and baharuddin, 2017). this study aimed to conduct eminent review both empirically and theoretically about the role of human capital or human resources in the company’s performance improvement. the overview on human capital in indonesia 2008-2017 are reported in figure 1. attention to human resources and hc considered as the main producing factors for most companies is often under-ranked compared to other factors of production such as capital, technology, and money. many company leaders are less aware that the profits derived by the company come from human capital, this is because the company’s activities are seen more from the perspective of the business (hunter et al., 2017). companies are not seen as a unit by the leaders of companies which contain unique skills and knowledge, or unique parts of business elements that could distinguish products and services in the competitive markets from competitors. 2. literature review there is the relevance of human capital which could be interpreted as human resources value of the economy that is linked to the commitment and energy, ideas, ability, innovation, and knowledge. the combination of human capital is linked with the innovation, skills, knowledge and the person ability for performing duties in creating values to the goal achievements (korauš et al., 2017). the contributions of human capital in sort of added value formations for performing works and tasks could provide revenue sustainabilities for organizations in future. in the intellectual capital, human capital is considered as lifeblood, an eminent source of improvement and innovation, while also considered as an eminent component which has difficulty in measurement (ferreira and franco, 2017). studies enumerated human capital into three elements of combination that named as (1) talent and creativity, namely intelligence, person’s learning ability, and imagination, (2) traits and characters that took for work, for instance, commitment, energy, reliability, intelligence, and positive attitude, (3) motivations for goals orientation, team spirit, knowledge and information (adelere, 2017). the literature further described human capital that consists of things namely: time, effort, behaviour, and ability which are all employees controlled and owned. studies further mentioned the relevance of company expenses that are linked to human resources might be seen as human capital investments (luftman et al., 2017). for instance, programs of training which are aimed for adding values of employees must be focused on financing in the future. studies widely contributed the intention of using renewable energy an important source that significantly contributes towards various factors. however, the significance of renewable energy positively dominates among the factors that exit for company performance. the eminent usage of renewable energy positively enumerated in wide literature recalling the effects on factors influencing the company’s performance (hai et al., 2017). different capabilities are used in wide literature for the increase of performance in companies but the prevalence of renewable energy intentions positively exits between them. the literature discussed the intentions of using renewable energy widely with various factors where the dominance of renewable energy has lasted the impacts with significant enumerating measures (higueras-castillo et al., 2019). the positive relationship between intellectual human capital and company performance dominates in vast literature but the importance of renewable energy could not be overlooked. the role of renewable energy intentions relates to the intellectual human capital which is linked with the performance of companies (husin and alrazi, 2017). although, many factors contribute eminence in companies the prevalence of intellectual capital is significant where the intentions of using renewable energy put significant impact. intentions of using renewable energy contribute various measures on intellectual capital, while the existence of company performance among them is also important. for the improvement of the performance of companies as possible optimal, there is a requirement of professional and efficient human resource management. to face different challenging situations in the environment of businesses both externally and internally, the conducting of a definite process of human resource management is required by the managers of hr which could establish human capital (behera and mohapatra, 2017). while reviewing studies, the six dominant factors in hrm have a significant impact on the performance of the business and could also improve the competitivity of companies. employees fatihudin, et al.: the role of intellectual human capital, human resource practices and intention to use of energy resources on the company performance international journal of energy economics and policy | vol 10 • issue 6 • 2020706 placement and recruitment is an eminent process with significant importance for the companies. for the insertion of people which could be imminent for the achievement of objectives, the first step belongs to the conducts of proper placements and recruitments in fields (iamsomboon et al., 2020). recruitments through human resources are considered as a process of potential withdrawals and identification of employees out of the company over the time for activities of operations. programs of recruitments are established for evaluating the right person having talent and considerably countered as capable of vacant designations fulfilment at different stages in the organizations (manjula and balachandra, 2017). the success of the company in the future depends very much on the selection made on the recruitment of hr that will be accepted. it’s not easy to choose the right hr in the right place. therefore it is necessary to carry out a testing and screening process in stages both directly and indirectly. the hr selection process requires the right tools and methods to estimate the quality of prospective employees (harlow, 2017). therefore, the test to be carried out has been tested for validity and reliability. the process of training employees exits in literature with a variety of impacts on companies, whether it costs or enhance the performance but the intentions of using renewable energy could prevail with dominance among them. renewable energy could have a positive influence on the development and training in the various areas which are required for the company’s performance (kahia et al., 2017). the prevalence of renewable energy positively dominates among the factors of training and development of employees which are used for company performance but could also inert positive contribution to renewable energy intentions. among the development and training of employees in organizations the existence of energy dominates in far literature with various examples (komendantova and yazdanpanah, 2017). the role of intentions of using renewable energy prevail upon the employees’ rehabilitation which robustly influences the performance of companies. several procedures are adopted in literature for the employee’s induction where renewable energy significantly exits on the measures (oduor, 2017). for the renewable energy enumerations, the role of placement and recruitment are widely elaborated in studies but the eminence of renewable energy puts significant impacts upon the performance of companies and recruitments and placements. for anticipating the rapid environmental changes, development and training is a significant element for the companies. the literature stated: “training and development are terms of reference to planned efforts designed to facilitate the acquisition of relevant skills, knowledge, and attitudes by organizational members.” various studies mentioned development and training through arguments of relevance with plans of businesses which are performed to the achievement of mastery employees attitude, skills, organization members, and knowledge (ikram and hanim, 2020). the dominant focus is upon the development which helps for improving the abilities of decision making and human relations broadening for the managements whether middle level or upper level while for the lower-level employees, training intends (implementation). organizations that achieve higher performance and can attain high levels usually have hr reliability with the robust motivation of work and robust commitments for achieving the missions and goals of companies (hamdan et al., 2017). performance of the companies could be improved optimally if the performance management of hr strives in all dimensions in organizational structures of companies. the literature described the inclusion of expected goals of companies: to attain the significant information that relates to the decisions of compensation and promotion, and the performance evaluation of employees at both levels whether managerial or subordinate (obeidat et al., 2017). therefore, managers effectiveness is required for the employees’ valuation, management, assessment, and developments as well as continuity in performance evaluation, coaching and feedback and poor performance consequences management. various measures are used through the steps of placement and recruitment but the existence of intentions of using renewable energy could influence the measures through a variety of channels as stated in the literature. the use of energy resource has been positively influenced the growth of the economy around the globe (nawaz et al., 2019). the majority of elements are designed in company procedures to attain performance forecasted but the existence of renewable energy intentions among the elements dominates in studies (rezaei and ghofranfarid, 2018). various courses of renewable energy are used to establish links with countries and companies but the ultimate cooperation elements significantly enumerate the possible eminence of renewable energy. studies used a variety of elements in the company’s where different strategic measures help to enhances performance whereas the intentions of using renewable energy insert various elements that put effects among the strategies (shakeel and rahman, 2018). with the relevance of different factors, intentions of renewable energy usage positively described among the literature. intellectual capital is considered as a positive key contributor among the economy whereas the intentions of using renewable energy also dominate in the ground of economy for plenty of reasons (uyar and beşikci, 2017). 3. research method the motive of the ongoing study is to examine the impact of intellectual capital and hr practices on the company’s performance along with the moderating role of intention to use of renewable energy. the data has been gathered by using the questionnaires from the respondents. a personal visit has been conducted and distributed around 740 questionnaires but after one month only 510 questionnaires have been received that have 68.92% response rate. the pls-sem has been conducted for the analysis of the data that has been collected from the respondents. the model of the study is very complex and the smart-pls provided the best estimation in this case. the variables that have been adopted in the ongoing study consist of the one predictive variable named as company’s performance (cp) that has five items along with one moderator such as the intention to use of renewable energy (iure) that has four items. in addition, the present research also took three predictors such as intellectual human capital (ihc) that has seven items, training and development (td) that has five items and recruitment and placement (rp) that has four items. these variables along with their links are mentioned in figure 2. intellectual human capital training & development recruitment & placement intention to use of renewable energy company’s performance figure 2: theoretical framework figure 1: overview on human capital in indonesia 2008-2017 source: word economic forum (2017) figure 3: measurement model assessment source: authors fatihudin, et al.: the role of intellectual human capital, human resource practices and intention to use of energy resources on the company performance international journal of energy economics and policy | vol 10 • issue 6 • 2020 707 fatihudin, et al.: the role of intellectual human capital, human resource practices and intention to use of energy resources on the company performance international journal of energy economics and policy | vol 10 • issue 6 • 2020708 4. results the findings of the ongoing research include the reliability along with validity analysis such as convergent along with the discriminant validity. in addition, the analysis also includes path analysis related to hypotheses testing. firstly, the convergent validity has been tested by the study that highlighted the links among the items. the figures show that high values of ave and loadings than 0.50 while high values of cr and alpha than 0.70. these figures highlighted that high linkage among the items and valid convergent validity. these figures have been mentioned in table 1. secondly, the discriminant validity has been tested with the help of fornell larcker and cross-loadings that highlighted the links among the constructs. the figures show that the values that show the links with construct itself are larger than the links with other constructs. these figures highlighted that no high linkage among the constructs and valid discriminant validity. these figures have been mentioned in tables 2 and 3. thirdly, the discriminant validity has been checked by using heterotrait monotrait (htmt) ratio. the figures show that the values of ratios are not larger than 0.90. these figures highlighted that no high linkage among the constructs and valid discriminant validity. these figures have been mentioned in table 4 and figure 3. finally, the path analysis has been executed for the testing of the hypotheses of the study and the figures show that positive association among the intellectual human capital, and hr practices such as training and development, recruitment and placement and company’s performance. in addition, intention to use of renewable energy has positively moderated among the links of intellectual human capital, and the company’s performance. however, intention to use of renewable energy has insignificantly and negatively moderated among the links of hr practices such as training and development, recruitment and placement and company’s performance. these links are shown in table 5 and figures 4-7. 5. discussions variant performances could be produced by companies if companies are managed by various people, means that managing the assets of the same company by various hr could generate variant added values. companies that own tangible assets are considered as passive without hr which could generate and manage value for companies as concluded by the studies (mcdowell et al., 2018). different studies proved the relationship between the process of hrm and performance of the companies. in the 1980s, studies table 1: convergent validity constructs items loadings alpha cr ave company’s performance cp1 cp3 cp4 cp5 0.823 0.831 0.855 0.821 0.852 0.900 0.693 intellectual human capital ihc1 ihc2 ihc3 ihc4 ihc5 ihc6 ihc7 0.832 0.863 0.845 0.811 0.876 0.861 0.794 0.931 0.944 0.707 intention to use of renewable energy iure1 iure2 iure3 iure4 0.932 0.930 0.446 0.911 0.831 0.893 0.690 recruitment and placement rp1 rp2 rp3 rp4 0.695 0.897 0.769 0.898 0.835 0.890 0.671 training and development td1 td2 td3 td4 td5 0.938 0.855 0.937 0.854 0.939 0.944 0.958 0.820 table 4: heterotrait monotrait ratio cp ihc iure rp td cp ihc 0.468 iure 0.516 0.651 rp 0.833 0.398 0.513 td 0.566 0.429 0.554 0.457 table 2: fornell larcker cp ihc iure rp td cp 0.832 ihc 0.421 0.841 iure 0.446 0.499 0.831 rp 0.721 0.365 0.438 0.819 td 0.510 0.404 0.503 0.414 0.905 table 3: cross-loadings cp ihc iure rp td cp1 0.823 0.324 0.305 0.598 0.381 cp3 0.831 0.346 0.4 0.625 0.494 cp4 0.855 0.365 0.437 0.606 0.45 cp5 0.821 0.366 0.337 0.569 0.364 ihc1 0.33 0.832 0.405 0.308 0.298 ihc2 0.353 0.863 0.422 0.286 0.346 ihc3 0.321 0.845 0.397 0.279 0.311 ihc4 0.302 0.811 0.435 0.238 0.359 ihc5 0.389 0.876 0.435 0.323 0.364 ihc6 0.417 0.861 0.437 0.378 0.376 ihc7 0.342 0.794 0.403 0.314 0.312 iure1 0.418 0.419 0.932 0.408 0.465 iure2 0.421 0.375 0.93 0.443 0.473 iure3 0.177 0.67 0.446 0.152 0.19 iure4 0.407 0.399 0.911 0.381 0.47 rp1 0.423 0.207 0.348 0.695 0.284 rp2 0.723 0.369 0.35 0.897 0.408 rp3 0.501 0.245 0.34 0.769 0.247 rp4 0.655 0.34 0.41 0.898 0.387 td1 0.465 0.344 0.46 0.365 0.938 td2 0.459 0.395 0.446 0.398 0.855 td3 0.468 0.345 0.462 0.363 0.937 td4 0.453 0.399 0.448 0.394 0.854 td5 0.463 0.344 0.457 0.352 0.939 figure 4: structural model assessment source: authors figure 5: ihc*iure source: authors figure 6: rp*iure source: authors fatihudin, et al.: the role of intellectual human capital, human resource practices and intention to use of energy resources on the company performance international journal of energy economics and policy | vol 10 • issue 6 • 2020 709 empirically mixed the findings to the link among the performance of companies and human capital. authors examined the relation among the performance of business and planning of hr and found no correlation among them (oduor, 2017). these findings are supported by literature based on surveys which conclude no relation among corporate performance financially and practices of hr. while empirical studies in the 1990s now prove more positive and dominant link among the performance of the company and human capital. variant studies conducted the relation among the performance of companies and capital investments dominating the 366 companies in the uk. findings show the association of more hr with low turnover labour which can produce higher profits per worker but low productivity (kweh et al., 2019). by the performance estimation, there is the existence of a robust link between financial performance and productivity of hr. different authors widely discussed the elements of renewable energy in various studies with the dominance of measures exits in it. the use of renewable energy existed between various factors that are used to interpret the relationships and influences (wojuola table 5: path analysis relationships beta s.d. t-statistics p-values l.l. u.l. ihc → cp 0.175 0.055 3.160 0.002 0.062 0.277 ihc*iure → cp 0.109 0.045 2.396 0.017 0.017 0.198 rp → cp 0.512 0.046 11.202 0.000 0.416 0.594 rp*iure → cp −0.110 0.050 2.186 0.029 −0.219 −0.023 td → cp 0.164 0.052 3.179 0.002 0.066 0.267 td*iure → cp −0.062 0.046 1.343 0.180 −0.141 0.033 fatihudin, et al.: the role of intellectual human capital, human resource practices and intention to use of energy resources on the company performance international journal of energy economics and policy | vol 10 • issue 6 • 2020710 and alant, 2017). even though renewable energy is countered as an eminent source for building of collaborating relationships but the effective use of renewable energy put significance among the relationship. authors used renewable energy at various stages for the interpretation of relationships and effects though various modes of examinations (dogan and ozturk, 2017). the contributions toward companies are performed through enormous channels, while the reliance on renewable energy could put all possible measures among the contributing elements. the link among the development of hr and training with the performance of a company is carried out by various authors. employees skills and knowledge through the activities of training become dominant in improving the performance of the company. authors state the market competition where the company successfully dealing is primarily determined by hc, not pc and so the company is encouraged to invest in various training to increase the abilities, skills and knowledge of employees more compared to the competitors (gracioli camfield et al., 2018). therefore, company expenditures for hr training and development activities are eminent to increase and maintain employee knowledge and expertise to be able to create a sustainable competitive advantage. a significant planned effort termed by the development and training in the companies to improve employees abilities, skills and knowledge. furthermore, added the similar two concepts of development and training, namely to increase abilities, skills and knowledge. however, purposely judging, generally, twice concepts could be differentiated. for the increasing of abilities to perform specific jobs, the focus is on training at the moment, and for performing the work, knowledge enhancement is focused through development in the future, performed through the approach integrated with variant activities to change the behaviour of works (arifah, 2020). if the knowledge of individual based on strength maintained and managed, the achievement of competitive advantage could be dominant. authors stated the determination of the success of companies is based on the abilities of companies to manage the asset of knowledge. companies could not generate knowledge despite using interactions and actions of employees. compensation and rewards to continue to be able to maintain and improve the owned hr qualities. the organization is required to provide appropriate compensation and appreciation to its employees. the company’s goals are to encourage company competitiveness, align individual/group work goals with company goals, and to strengthen positive behaviour towards customers. also, employee involvement in the design of compensation and rewards programs, an explanation of the workings of the compensation and reward systems provided by the company, the combinational use of non-financial and financial rewards and compensation components that distinguish between basic salary, incentives and variable salary are a positive thing for companies to increase employee participation (alzuod et al., 2017). compensation planning by a company is a strategy related to how a company positions the level of compensation given compared to its competitors. besides compensation also illustrates how the company provides rewards to employees. with good compensation planning, it is expected that employees will be able to be maintained, especially for employees who have good performance. 6. conclusion rapidly increasing literature have attempted to enumerate the relationship between the performance of a firm and human resources. this paper tries to carry out a brief review both theoretical and empirical link among the performance of companies and human capital, and the importance of hr company managers that how their support is linked with the significant performance. robust performance is eminent for the companies to enhance the value of the company that can satisfy all parties, especially stockholders. the dominance of elected factors significantly influences the performance of companies whether for enhancing or disrupting measures, while the use of renewable energy also attained much importance among them. the role of intentions of using renewable energy positively influence the relationships that are countered in this study for evaluating the impacts on the company’s performance. although the company’s performance could be evaluated by various means the elected factors significantly elaborated the impacts whereas the prevalence of using renewable energy intentions inserts moderating effects among them. between the elected factors in this study used to enhance the performance of companies, the use of intentions of renewable energy positively inserts role between the factors affecting the relationship. with all the limitations, especially the theoretical review that has not been completed, this paper is expected to provide input for companies to prepare higher quality human resources in improving the company’s best performance. company leaders are required to realize at this time about the benefits derived by the company come from human capital, not the company’s activities are seen from a business perspective. leaders of the companies are required to view companies as units which contain significant sets of skills and knowledge, or uniqueness. references adelere, m.a. (2017), effect of staff training and development on organisational performance: evidence from nigerian bottling company. oman chapter of arabian journal of business and management review, 34(5476), 1-15. alzuod, m., isa, m., ismail, s. (2017), intellectual capital, innovative performance and the moderating effect of entrepreneurial orientation figure 7: td*iure source: authors fatihudin, et al.: the role of intellectual human capital, human resource practices and intention to use of energy resources on the company performance international journal of energy economics and policy | vol 10 • issue 6 • 2020 711 among small and medium-sized enterprises in jordan. international review of management and marketing, 7(2), 308-314. ari, i., yikmaz, r.f. (2019), the role of renewable energy in achieving turkey’s indc. renewable and sustainable energy reviews, 105(2), 244-251. arifah, p. (2020), the role of beta as a moderating variable on the relationship between intellectual capital and financial performance in consumer goods industry at indonesia stock exchange 2010-2017. asian journal of business and entrepreneurship, 1(1), 1-9. behera, m.p., mohapatra, d. (2017), strategic imperatives of training and development practices on sales performance: a case analysis of insurance company in bhubaneswar city, odisha. training and development journal, 8(2), 103-112. bozorgparvar, e., yazdanpanah, m., forouzani, m., khosravipour, b. (2018), cleaner and greener livestock production: appraising producers’ perceptions regarding renewable energy in iran. journal of cleaner production, 203(1), 769-776. chen, z., hossen, m.m., muzafary, s.s., begum, m. (2018), green banking for environmental sustainability-present status and future agenda: experience from bangladesh. asian economic and financial review, 8(5), 571-585. demirbag, m., yilmaz, s. (2020), preservice teachers’ knowledge levels, risk perceptions and intentions to use renewable energy: a structural equation model. journal of education in science, environment and health, 6(3), 193-206. dogan, e., ozturk, i. (2017), the influence of renewable and nonrenewable energy consumption and real income on co2 emissions in the usa: evidence from structural break tests. environmental science and pollution research, 24(11), 10846-10854. ferreira, a., franco, m. (2017), the mediating effect of intellectual capital in the relationship between strategic alliances and organizational performance in portuguese technology-based smes. european management review, 14(3), 303-318. gracioli camfield, c., giacomello, c.p., sellitto, m.a. (2018), the impact of intellectual capital on performance in brazilian companies. journal of technology management and innovation, 13(2), 23-32. hai, m.a., moula, m.m.e., seppälä, u. (2017), results of intentionbehaviour gap for solar energy in regular residential buildings in finland. international journal of sustainable built environment, 6(2), 317-329. hamdan, a.m., buallay, a.m., alareeni, b.a. (2017), the moderating role of corporate governance on the relationship between intellectual capital efficiency and firm’s performance: evidence from saudi arabia. international journal of learning and intellectual capital, 14(4), 295-318. handayani, p., sinulingga, n.a.b. (2019), the effect of employee recruitment and selection on employee performance on the cv. lpk. journal of management science (jmas), 1(3), 19-23. harlow, h.d. (2017), chief knowledge officers and other knowledge management executives effect on strategic intent, intellectual capital generation, and firm performance? an empirical research study of chief knowledge officers and knowledge executives in the usa. electronic journal of knowledge management, 15(3), 170-182. higueras-castillo, e., liébana-cabanillas, f., muñoz-leiva, f., molinillo, s. (2019), the role of collectivism in modeling the adoption of renewable energies: a cross-cultural approach. international journal of environmental science and technology, 16(4), 2143-2160. hunter, s.t., shortland, n.d., crayne, m.p., ligon, g.s. (2017), recruitment and selection in violent extremist organizations: exploring what industrial and organizational psychology might contribute. american psychologist, 72(3), 242. husin, n., alrazi, b. (2017), renewable energy investment in malaysia: an integrated model in evaluating public decision making process. journal of clean energy technologies, 5(4), 343-346. iamsomboon, n., sukortprommee, s., klinpratum, v. (2020), creating employee working skills and performance through organizational training practices in abc tire manufacturing company. rmutt global business accounting and finance review, 4(1), 104-110. ikram, s., hanim, w. (2020), effects of growth and learning and internal business processes on financial performance (survey of regional water company (pdam) in java). international journal of psychosocial rehabilitation, 24(2), 259-270. kahia, m., aïssa, m.s.b., lanouar, c. (2017), renewable and nonrenewable energy use-economic growth nexus: the case of mena net oil importing countries. renewable and sustainable energy reviews, 71(3), 127-140. komendantova, n., yazdanpanah, m. (2017), impacts of human factors on willingness to use renewable energy sources in iran and morocco. environmental energy and economic research, 1(2), 141-152. korauš, a., kaščáková, z., parová, v., veselovská, s. (2017), sustainable economic development through human resource management: social intelligence of managers and performance. journal of security and sustainability issues, 6(3), 59-81. kweh, q.l., ting, i.w.k., hanh, l.t.m., zhang, c. (2019), intellectual capital, governmental presence, and firm performance of publicly listed companies in malaysia. international journal of learning and intellectual capital, 16(2), 193-211. luftman, j., lyytinen, k., zvi, t.b. (2017), enhancing the measurement of information technology (it) business alignment and its influence on company performance. journal of information technology, 32(1), 26-46. manjula, p., balachandra, p. (2017), a study on various training programmes and their effects offered by the it firms. in: paper presented at the proceedings of the 5th international conference on frontiers in intelligent computing: theory and applications. berlin, germany: springer. mcdowell, w.c., peake, w.o., coder, l., harris, m.l. (2018), building small firm performance through intellectual capital development: exploring innovation as the black box. journal of business research, 88(1), 321-327. nawaz, m.a., azam, m.a., bhatti, m.a. (2019), are natural resources, mineral and energy depletions damaging economic growth? evidence from asean countries. pakistan journal of economic studies, 2(2), 45-53. obeidat, b.y., tarhini, a., masa’deh, r.e., aqqad, n.o. (2017), the impact of intellectual capital on innovation via the mediating role of knowledge management: a structural equation modelling approach. international journal of knowledge management studies, 8(3-4), 273-298. oduor, o.g. (2017), talent attraction strategy and employees’ productivity in private sugar companies in kakamega county, kenya. international journal of multidisciplinary and current research, 5(2), 1174-1180. omran, a., baharuddin, a.h. (2017), determining the causes and effects of project manager’s turnover on project performance in penang state, malaysia. journal of academic research in economics, 9(3), 10-23. rezaei, r., ghofranfarid, m. (2018), rural households’ renewable energy usage intention in iran: extending the unified theory of acceptance and use of technology. renewable energy, 122(3), 382-391. shakeel, s.r., rahman, s.u. (2018), towards the establishment of renewable energy technologies’ market: an assessment of public acceptance and use in pakistan. journal of renewable and sustainable energy, 10(4), 045907. fatihudin, et al.: the role of intellectual human capital, human resource practices and intention to use of energy resources on the company performance international journal of energy economics and policy | vol 10 • issue 6 • 2020712 suryani, n.k., made, w., ketut, s.d., ketut, s.i.b. (2017), human resources management practice and organizational performance (a case study of line manager support in star hotel bali indonesia). international business management, 11(7), 1523-1531. uyar, t.s., beşikci, d. (2017), integration of hydrogen energy systems into renewable energy systems for better design of 100% renewable energy communities. international journal of hydrogen energy, 42(4), 2453-2456. wojuola, r.n., alant, b.p. (2017), public perceptions about renewable energy technologies in nigeria. african journal of science, technology, innovation and development, 9(4), 399-409. world economic forum (2017), the global human capital report 2017 https://www.weforum.org/reports/the-global-human-capitalreport-2017 tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 5 • 2022 303 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(5), 303-310. renewable energy (solar and wind) generation and its effect on some variables for selected eu countries with panel var model shahi md. tanvir alam* stipendium hungaricum phd. fellow, doctoral school of economics, faculty of economics and business administration, university of szeged, hungary. *email: shahi.tanvir@gmail.com received: 20 may 2022 accepted: 29 august 2022 doi: https://doi.org/10.32479/ijeep.13292 abstract keeping the world livable, the policy makers are giving their extended focus on green energy. they are trying to move on hand-on-hand with rising green energy and lessening carbon dioxide (co2) emission steading the economic activities especially for the open and developing countries. this can be helpful to provide a more lucrative economic environment to meet the extended demand of the society. the paper highlights to find out whether the economic growth, renewable energy (re) consumption, fossil fuel-based energy generation and co2 emission are significantly impactful on re generation or not? is there any mutual, bi-directorial, unidirectional relationship with each other? for this, the vector autoregression (var) model is run. the paper focuses on six eu countries who are practicing auction scheme for deploying robust green energy (especially solar and wind) by reducing dependency on fossil fuel and expanding their economy with less co2 emission. the result of the analysis shows that a positive influence of each concern variable on re generation and auction scheme might have a significant impact if robustness of the generation occurs. keywords: auction scheme, co2 emission, economic growth, fossil fuel, re generation jel classifications: c32, d44, o44, p18, q42 1. introduction depending more on fossil fuel (ff) based power plants, the developed countries released thousands of tons of carbon dioxide (co2) and other green house gases (ghg) in the troposphere and energy sector emits two-third of the global ghg (matthaus 2020). according to our present knowledge, the excessive amount of co2 in the air is the root cause of global warming and climate change.1 observing the detrimental significances of climate modification, a strong opinion is growing in the countries against using ff in power generation and paying attention to energy transition, i.e., increased usage of renewable energy sources (res). they are 1 https://www.carbonbrief.org/solar-wind-nuclear-amazingly-low-carbonfootprints 4−6 grams co2 emits for generating one kilowatt-hour (kwh) electricity from solar/wind. the emission range is 109 grams for coal, 78 grams for gas, 700 grams for high-speed furnish oil (hfo) and 350 grams for liquified natural gas (lng). investing in research and development of related technologies. international organizations and development agencies of the world also prefer and encourage investments in renewable energy (re) field. in that the universal policy makers are focusing on 100% zero carbon free energy generation by 2050. according to the report iea (2021b), almost 90% of electricity should come from res, with wind and solar photovoltaic (pv) together accounting for nearly 70% by 2050. a special analysis has also been carried out with the participation of international monetary fund (imf) and international institute of applied system analysis. it shows that the enormous challenges of transforming our energy system is also a huge opportunity for our economics, with the potential to create millions of new jobs and boost economic growth. the report also states that the transition to net zero is for and about people to provide around 4% of cumulative emissions reductions. finding out the potentiality of solar and wind this journal is licensed under a creative commons attribution 4.0 international license https://www.carbonbrief.org/solar-wind-nuclear-amazingly-low-carbon-footprints https://www.carbonbrief.org/solar-wind-nuclear-amazingly-low-carbon-footprints alam: renewable energy (solar and wind) generation and its effect on some variables for selected eu countries with panel var model international journal of energy economics and policy | vol 12 • issue 5 • 2022304 technologies, those are included in the energy system targeted by the energy democracy as a prime site of political-economic contests and those are picked-up for deploying high volume of re (angel, 2016; burke and stephens, 2018). mu et al. (2018) found an impact of the re policy of china on employment generation. they find that there is an increase of employment due to the expansion of solar pv and wind power generation. oh et al. (2020) finds a positive relation among re policies, re generation and ghg emission reduction (i.e., environment). the large share of re will support to emit less amount of ghg in the environment. zhang et al. (2021) used the provincial data of china for the period 2000–2017 to investigate the aggregate effects of low-emission electricity. the investigation shows that if the ratio of low-emission electricity to total electricity is increased by 1%, then the gross domestic product (gdp) will up by 0.16%, and co2 will decrease by 0.848%. literally, it has said that low-emission can chase the target of low-carbon economic development. rennkamp et al. (2017) depicts that re policy lessens the co2 emission and creates socio-economic upliftment for the state. with the sufficient democratic support, re policy may be implemented in middle-income countries. getting these co-benefits, the robustness of re deployment is highly prioritized and the robust deployment depends on the market-independent policies rather than market dependent policies due to its stronger, cost-effectiveness, higher investment security and lower cost. those mentioned features are mostly associated with the re ‘auction scheme’ (couture and gagnon, 2010). 2. theoretical background and theoretical model res have started its remarkable role in sustaining the current economic growth and in recent years, it has been instrumental in pushing the energy access frontier all over the world. simelyle and dudzeviciute (2017) says considering the competitiveness of a specific country in the international arena, energy consumption and its efficiency are interrelated, especially in the case of consumption in the industrial sector. further, high implications are found for using extended amount of re in changing the competitiveness of nations and having an accumulated beneficial return in global stage. the global scenario is rapidly changing and the share of res in the energy-mix across the globe is increasing due to the drastic fall in res price, technological progress, and growing environmental concerns. as a feasible substitute font of energy globally, re is getting priority due to climate change, ff exhaustion, subjects of energy security, technology modernization and high and unpredictable prices of petroleum-based fuels (ferrer et al., 2018; do xuan et al., 2020). shifting from ff-based energy to re, energy subsidy for ff poses substantial constraints and a lot of evidences says that the continuation of subsidies has adverse effect on the countries’ social, fiscal and environment sector (beaton et al., 2013; pegels et al., 2018). sometimes, the high volatility of ff becomes an obstacle for economic growth. when the energy prices are fairly stable, then economic growth might improve and if they are unstable, the price could rise that would be negatively impactful to the economic growth (frimpong et al., 2018; takentsi et al., 2022). according to monthly electricity statistics report of iea (december 2020), globally re production was 3,269.1 terawatt-hour (twh) in 2020 that was 7.5% higher than in 2019. the share of renewable electricity in the mix was 31.6% in same year, up from 28.6% in 2019. wind and solar production were mainly responsible for this increase in renewables, up respectively by 95.8 twh or 11.6% and 73.0 twh or 20.2% in 2020 compared to 2019. since 2018, wind production has increased by 20.1% and solar production by 28.4% highlighting the dynamic growth of the wind and solar power sector. as per the report of iea (2021a), global co2 emission declined by 5.8% in 2020, or almost 2 gigatons (gt) co2-the largest ever decline and almost 5 times greater than the decline of 2009 that followed the global financial crisis, co2 emissions fell further than energy demand in 2020 owing to the pandemic hitting demand for oil and coal harder than other energy sources while renewables increased. furthermore, the report of iea (2021b) says that an unparalleled clean energy investment boom lifts global economic growth. total annual energy investment surges to us$ 5 trillion by 2030, adding an extra 0.4% point a year to annual global gdp growth. not only that the environmental protection activities ensure economic merit by creating the net job in the whole economy, in that the related reallocation of resources is typically channeled to labor-intensive renewable sector (bmu, 2009; frondel et al., 2010). by stimulating the demand for local installation, locallymanufactured components and local planning, solar pv is found as a scope to support the local employment and engagement of labor (sweeney, 2015). the public awareness and robust support are increasing due to the growing emphasis on environmental issues. power generation from the ff-based sources may gain price benefits from higher efficiency on smart technologies; but re market is moving faster than that market. cost reduction of clean energy arise from fundamental physics and material cost from scale as well as lower labor costs through manufacturing automation and lower waste driven by higher efficiency. the country trend like scandinavian countries or germany are shifting ff subsidies to re investments while creating new decant and healthy job and ensuring a just, inclusive transition. irena-gcget (2019) report emphasizes that re can be utilized at outmost level at any scale and it is possible to lend them better to decentralized forms of energy production and consumption. the report also mentions that re sources have about zero marginal cost and especially solar and wind sources enjoy cost reduction about 20% for doubling of capacity. abolhosseini and heshmati (2014) states that the three support mechanisms, used to finance re development programs: auction, tax incentives, and tradeable green certificates. some countries are familiarized cash incentives in private sector for utility-scale re generation. some have initiated interest free/negligible level of interest-based credit scheme to the expansion of re. focusing on alam: renewable energy (solar and wind) generation and its effect on some variables for selected eu countries with panel var model international journal of energy economics and policy | vol 12 • issue 5 • 2022 305 auction scheme pegels et al. (2018) states that auction helps to fix the tariff level in a competitive way, i.e., testing the market prior to approving subsidies. the emerging market like china, india, brazil, south africa practiced auction scheme and in the most cases they found it highly effective for gaining re capacity growth and ensuring supply of clean electricity at low cost. supporting the cost savings beg et al. (2002) and rennkamp et al. (2017) argue that cost savings and implementing re programs have been pointed as potential fields to create win-win situation where emission reduction and economic development go hand in hand. based on the other papers, we got that executing so many variables may not upsurge the possibility to discover more factors of re generation rather those hamper the results and their explanation. thus, the energy generation from re and finding its significance on different variables like sovereign spread (10yi-us,t), gravity (gdpi-w,t), ff-based energy generation (eff,i,t), renewable consumption (solar and wind) (rcom s-w,i,t), carbon dioxide emission (co2i,t) using var model added with exogenous shocks like auction dummy and imf dummy will be implemented in this paper. for constructing the theoretical model, the paper has attentive on the postulation of a prolonged cobb-douglas function (1) pointing to the broad economic activity (thompson, 2006; moyer et al., 2013) with capital (kt), labor (lt) and energy (et) plus damages (dt) due to greenhouse gas (ghg) emission which studies as: (1 )(1 ) * *α β α β− −= −t t t t t ty d a l k e (1) here, at is a technology-parameter reliant on time. all the countries in european union (eu) are shifting their economy towards the green economy and for lowering down the ghg to mitigate the dt damages, they are picking-up the res for electricity by diminishing ff-based sources highlighting the “net zero emission target by 2050’. in connection with the target, the countries are practicing the re auction scheme for robust deployment of re; side by side reducing dependency on ff-based energy generation. for the sake of the theoretical model and quantitative analysis of the paper, the author has differentiated between globally and locally practiced variables as the authors have picked-up some eu countries (like greece, italy, poland, portugal, romania, spain) whose economies are open in nature, close geographic similarities and following re auction scheme for the last few years to chase the net zero target. in the model, it is considered the sovereign spread (10yi-us,t) variable. because, capital accumulation (i.e., kt) and funding scenario for the selected countries are extremely settled by the world market sentiment which may be steered by the home-grown monetary policy. in this regard, for explaining the comparative affluence of funding, the sovereign spread between the ith trial state and the 10-year bond of us have been measured as benchmark for unfolding the comparative comfort of funding – where higher values signify liquidity scarcity (capelle-blancard et al., 2019; shimbar and ebrahimi, 2020). in the case of output (yt), less strong economies do not play a vigorous role and they are not price taker from the global market and for this, the author planned to use a gravity-proxy that generally explains the gap between the gdp of sample countries and the global economy (gdpi-w,t). here is mentionable that the higher values of (gdpi-w,t) indicate the relative smallness. due to robust disposition of re by following auction scheme, the eu countries are lessening their dependency on ff-based electricity generation (eff,i,t) along with the economy becomes more energy efficient. side by side, the economies emit less carbon dioxide (co2,i,t) locally for consuming/producing less electricity based on ff by which ghg has negative feedback on the economy in the form of various damages (dt). but it is needed to point out that the damages are not solely acknowledged by the local co2 emission (co2,i,t). to denote the exogenous shocks in the model, we augmented west-texas intermediate oil price (pwti.i,t) to represent the situation of ff pricing; an imf dummy (dimf,i,t) variable that postulates country precise emergency periods when ith country required funding from the imf and an auction scheme dummy (das,i,t) variable to epitomize the support instrument for installing re robustly by the sample countries. notably, the systematic auctioning schedule ensures a continuation of re project in the pipeline and helps to add more re in the system (irena-cem, 2015; irena, 2017). in this paper, we categorized the re into two main slices: solar and wind energy (rgen s-w,i,t). these two types of re generation do not emit any direct co2 after the asset is bent and fitted. 2 the usage of higher-level re can care of the impression of circular economy and the higher the consumption of re (rcom s-w,i,t) and lessen the usage of ff. however, the paper focuses on the identification of the country-specific factors in re to comprehend the ith country’s capability to encounter the net zero emission target by 2050 under the applied cobb-douglas specifications following the below mentioned theoretical model: gen s w ,i, t 1 i us, t 2 i w , t 3 ff ,i, t 4 , , 5 i, t 1 wti,i, t 2 imf,i, t 3 as,i, t t lnr constant ln10y lngdp lne lnco2 lnp d d − − − − ∆ = + α ∆ +α ∆ + α ∆ + α ∆ +α ∆ +β ∆ +β +β + ε com s w i tlnr (2) based on the set model, the expected outcome is: in all-purposes high sovereign spread level can hamper investment, reasoning sluggish economic growth and thus low level of co2 discharge for deploying re by reducing dependency on ff-based electricity generation (α1<0) -nevertheless an extreme liquidity-scarcity can distract funding from green energy venture as well (α1>0). this assorted symbol points on the deficiency of market impartiality for a green monetary policy. when the underlying economy has a lesser portion in the global economy, then the worth of the gravity-proxy is higher. as economic productivity depends on energy practice, this variable should have optimistic stimulus on co2 emission (α2>0); but the condition is to attain a country at a certain post-industrial level of growth. as higher level of re2 https://www.carbonbrief.org/solar-wind-nuclear-amazingly-low-carbonfootprints https://www.carbonbrief.org/solar-wind-nuclear-amazingly-low-carbon-footprints https://www.carbonbrief.org/solar-wind-nuclear-amazingly-low-carbon-footprints alam: renewable energy (solar and wind) generation and its effect on some variables for selected eu countries with panel var model international journal of energy economics and policy | vol 12 • issue 5 • 2022306 generated electricity reduces the gradual dependency on ff-based electricity, so energy consumption from res has analogous effect as re has still small stake in energy blend (α3>0; α4>0). for the substitute of ff, re usage mentionable solar and wind energy can potentially reduce the co2 emission (α5<0). we see that the last three variables have capableness to methodically diminish the ghg in the set model. 3. data and methods 3.1. data the selected eu countries started to emit a large amount of co2 after 1982 aligning with global scenario and the growing trend continues since 2010 with some hindrances only when there were some experiences of recession (figure 1). after the tremendous attention to the green energy, how the countries’ economic, financial and industrial sectors are performing by keeping the carbon-neutrality target in the prime position in future and the paper attains this phenomenon. the figure shows the gradual declination of co2 emission due to high focus in green energy. re generation especially solar and wind has started to rise in the selected countries in the 2000 s and the increasing production has the inspiration to consume more re and this inspiration insists to reduce persistent dependency on the ff-based energy generation (figures 2-4). the figure depicts the high expansion of solar and wind energy especially after 2000 s. the figure explains the higher-level consumption of solar and wind energy after 2000 s. the figure shows the gradual fall of ff-based energy generation due to the expansion of re (both generation and consumption). it can be focused that the above mentioned figures are satisfying our assumption primarily, i.e., the higher level of re generation increases the higher level of re consumption, on the other side reduces the dependency on ff-based energy generation and it also lessens the emission of co2. in the paper, the author analyzed the annual data between 2001 and 2020 as the robustness of the re basically started in these periods. comparatively six developing and open economies (greece, italy, poland, portugal, romania and spain) of eu are considered as sample where the auction scheme is being practicing after 2010 for vigorous deployment of re. for a stipulation of homogenous load-factor for premeditated solar figure 1: co2 emission (million tons) source: author’s edition, bp statistical review of world energy july 202131 3 http://www.bp.com/statisticalreview figure 2: total solar and wind generation (terawatt-hour) source: author’s edition, bp statistical review of world energy july 20214 figure 3: total solar and wind consumption (exajoules) source: author’s edition, bp statistical review of world energy july 20215 figure 4: fossil fuel based energy generation (gigawatt-hour) source: author’s edition, bp statistical review of world energy july 202161 2 3 4 http://www.bp.com/statisticalreview 5 http://www.bp.com/statisticalreview 6 http://www.bp.com/statisticalreview http://www.bp.com/statisticalreview http://www.bp.com/statisticalreview http://www.bp.com/statisticalreview alam: renewable energy (solar and wind) generation and its effect on some variables for selected eu countries with panel var model international journal of energy economics and policy | vol 12 • issue 5 • 2022 307 and wind generation potential, all the selected countries are pigeon-holed by similar climate, costal belt and geographical position. moreover, most of the countries were affected by developing debt-crisis in different times which is directing on their acquaintance towards external funding conditions. energy sector are being retrieved from the database of bp statistical review of world energy, financial data are obtained from refinitiv eikon database and world bank database is the source of gdp data (table 1). as the selected eu countries were taking part in various imf programs, so just the general resources account was measured only when the payout occurred from imf towards the ith state. it is required to mention that the paper does not reflect the poverty reduction and growth trust due to other reasons. further, the paper counts down the auction scheme for at least a single time practiced by the sample countries. as it is mentioned earlier that the robustness of re started in 2000 s and afterward and all the sample countries did not occupy re from that period, so due to missingness of data, the panel data can be treated as unbalanced which is measured by the panel var model (table 2). on the other hand, there is no unit-root in the data and the standard deviation and mean of the data are time-invariant and for this the var satisfies the stability condition. 3.2. method in the vector autoregression (var) model, the variables are in the form of time series and autocorrelated, the model is appropriate for handling such time series and autocorrelation problems. further, the var model considers the dynamic and causal relationships among economic variables, which is a benefit that classical regression models cannot ensure so. for this, var is suitable in policy analysis (kumar and paramanik, 2020). var is able to process even a lesser amount of time series variables, where a priori endogeneity is presumed for individual variable and their dynamics are taken into interpretation. this dynamic interpretation of a set of n time series variables yt = (y1t,…., ykt)’ can be defined simply by the below mentioned basic var model form (3) (lütkepohl-kratzig, 2004; gábor et al., 2020): 1 1 ε− −= +…+ +t t p t p ty a y a y (3) where yt is the model variables for the (nx1) vector, fi is the matrix which contains (nxn) autoregression coefficients and the εt= (u1t,…ukt)’ is the unobserved error term vector with (nx1) gaussian distribution where (εt ~(0,e(ut,ut’)) is a positive definite covariance matrix. optimal lag-length of the model is nominated by the schwarz (or bayesian) information criteria (sc), akaike information criteria (aic), hannan–quinn information criteria (hq) to check steadiness and asymptotic normality of the data. after that the standardized condition for stability is tested to see whether the modulus values are smaller than one or not that infers the invertible explanations and the explanations of infinite ordervector moving averages (lütkepohl, 2005; gábor et al., 2020). at the time of forming the equation (3), quite a few boundaries of the parameters are conceivable: the short-term restrictions can be casted-off to explain the arrangement of shocks in case of cholesky’s formation. on the other hand, the long-term restrictions can be described of the shocks for blanchard-quah’s formation. for doing this, firstly we need to familiarize the structural version of the shorten var form (4) (with a time lag ρ and three variables with structural coefficients a and as): , 1 1 ( 1) ( 1)ε − − − − = +…+ + = = s s t t p t p t t t y a y a y bu where a bu ands a b (4) table 1: data sources name of the variables sources renewable generation (solar and wind) (rgen s-w, i,t) bp statistical review of world energy july 2021 sovereign spread (10yi-us,t) refinitiv eikon database gravity (gdpi-w,t) world bank fossil fuel based energy generation (eff,i,t) eurostat renewable consumption (solar and wind) (rcom s-w,i,t) bp statistical review of world energy july 2021 carbon dioxide emission (co2i,t) bp statistical review of world energy july 2021 wti oil price (pwti, i,t) bp statistical review of world energy july 2021 imf dummy (dimf,i,t) imf country report auction scheme dummy (das,i,t) aures ii reports source: author’s edition. imf: international monetary fund table 2: descriptive statistics and unit-root tests head of the descriptive statistics co2i,t eff,i,t gdpi-w,t 10yi-us,t rcom s-w, i,t rgen s-w, i,t mean 10.35002 −0.026552 −0.003473 −0.063736 1.539328 6.218036 median 10.37727 −0.021017 −0.00112 −0.2902 1.750746 6.431424 maximum 10.44307 0.840846 0.057437 24.3555 3.075278 7.799048 minimum 10.14681 −0.706975 −0.05911 −23.5253 −0.65332 3.971268 sd 0.077858 0.238875 0.022535 3.868075 1.090909 1.12139 skewness −0.977287 0.322562 0.138542 0.43251 −0.327972 −0.323379 kurtosis 3.106358 5.877313 5.506677 29.67932 1.896296 1.893788 jarque-bera 16.44426 37.31655 27.29587 3057.96 7.074491 7.046921 p 0.000269 0.0000000 0.000001 0.0000000 0.029093 0.029497 unit-root test levin, lin and chu t* −6.69910 −8.39954 −2.91101 −5.24036 −8.18219 −8.19192 p 0.0000 0.0000 0.0018 0.0000 0.0000 0.0000 observations 103 103 103 103 103 103 source: author’s edition, eviews 10 alam: renewable energy (solar and wind) generation and its effect on some variables for selected eu countries with panel var model international journal of energy economics and policy | vol 12 • issue 5 • 2022308 it is our assumption that the value of certain coefficients is zero and u1t affects instantly the other variables simultaneously, while u2t affects only the variables 2 and 3 simultaneously and u3t only the third in cholesky’s restriction (5): 11 1 21 22 2 31 32 33 3 0 0 0ε = = t t t t t s u su s s u s s s u (5) the structure of the s-matrix unfolds the short-term possessions and in the eviews 10 econometric program it is resolute by the loading order of the variables into the var model-presumptuous that there exists a shock which affects every variable, and the end variable of the order is the one which affects itself only. the construction of the s-matrix (table 3) was determined by the paper’s theoretical model provided with the highest global influence for the exchange rate as an external balance proxy variable and the smallest, local for the liquidity. the impulse response analysis is a vital stage in econometric analysis that is used in var model. the functions under this analysis are being considered as the effect of a unit shock on a given model variable where the shock of variable i is to variable j and ceteris paribus. again, for a definite time horizon, variance decomposition denotes to the breakdown of the prediction error variance. the decomposition process specifies the short-term and long-term influence of certain variables, i.e., the percentage of the uncertainty of variable i that is to be accredited to the jth shock after period h (dinh, 2020). 4. results and analysis the paper considers 0–2 lag length of the model following the lag order selection criteria for meeting the stability condition. the model does not get any of the inverse roots of the characteristic polynomial lied outside the unit circle with this circumstance rather all modulus were smaller than 1 that means the var model satisfies the stability condition (table 4). impulse responses are presenting the progress of each variable’s stimulus on the total re (solar and wind) generation in time with a 95% (±2 standard error) confidence intervals (figure 5). all the variables have positive effect on re (solar and wind) generation. the co2 emission, ff-based electricity generation and re (solar and wind) consumption have the highest significant impact, meaning that the more the re is being generated, the co2 emission will be reduced highly; ff-based energy generation tendency will be reduced as well and re (solar and wind) consumption will be table 3: structure of the s‑matrix of the short‑term effects variable shocks co2i,t eff,i,t gdpi-w,t 10yi-us,t rcom s-w,i,t rgen s-w,i,t co2i,t s11 0 0 0 0 0 eff, i,t s21 s22 0 0 0 0 gdpi-w,t s31 s32 s33 0 0 0 10yi-us,t s41 s42 s43 s44 0 0 rcom s-w,i,t s51 s52 s53 s54 s55 0 rgen s-w,i,t s61 s62 s63 s64 s65 s66 source: author’s calculation in eviews 10 table 4: roots of characteristic polynomial root modulus 0.972501 − 0.073899i 0.975305 0.972501 + 0.073899i 0.975305 0.283287 − 0.858387i 0.903925 0.283287 + 0.858387i 0.903925 − 0.434899 − 0.533967i 0.688664 − 0.434899 + 0.533967i 0.688664 − 0.354528 − 0.567282i 0.668953 − 0.354528 + 0.567282i 0.668953 − 0.119546 − 0.580733i 0.592909 − 0.119546 + 0.580733i 0.592909 0.525375 − 0.126983i 0.540503 0.525375 + 0.126983i 0.540503 source: author’s edition, eviews10 figure 5: accumulated impulse response functions of the total re (solar and wind) genera-tion to model variables on the long run source: author’s edition, eviews10 alam: renewable energy (solar and wind) generation and its effect on some variables for selected eu countries with panel var model international journal of energy economics and policy | vol 12 • issue 5 • 2022 309 enhanced which will help the sample countries to reach the carbon neutrality target. not only that if the re generation increases, then auction scheme will play a significant role on the robustness of the generation (the testing of quantile process estimate explains this). so, regularity of auction scheme is a potential tool to ensure the robustness of re and its diversified gains. sovereign spread maintained a significant positive influence up to 7 years, meaning that the relatively high premium diverts financial resources toward the usage of ffs for a certain period; after that it will motivate the usage of their renewable counterparts. meanwhile, gdp has slightly significant impact on the total re generation up to 8 years; later on, the level of significance is found more positive, meaning that the change of energy-mix will affect the country’s gdp more significantly in the long-run. variance decomposition underlines that a major (~60%) of total re (solar and wind) generation is explained by the model on the long-run (figure 6). reinforcing our previous results, the data paints on the importance of generating more energy from renewable sources and inclusion of those into the energy mix will stop the further growth of co2 emission, expansion of re consumption and reduction of ff-based energy generation. these results are parallel with our previously described anticipations at the theoretical model part. 5. conclusion after analyzing the data for the period 2001–2020, for the countries in question, the results remark that the var model soothes the stability condition. the paper gets a positive influence of each concern variable on the re generationmore significant variables are co2 emission; ff based energy generation and re consumption and sovereign spread. the extended cobb-douglas function for the six eu countries is being used in this paper keeping total re (solar and wind) generation as a dependent variable. there were used the panel var (vector autoregression) model to scrutinize the exogenous shocks (i.e., practicing auction scheme, imf funding requirement at the countries’ crisis session and environment for ff pricing) where the shocks affect all of the considered variables. the paper points to the sample countries’ ability to align with the carbon neutrality goal under the cobb-douglas function. for getting the significant impact of the sovereign spreads, initiation of green monetary policy might be helpful. a green monetary policy indicates a more favorable refinancing, collateral conditions or asset purchase programs on the field of green bonds. interest free credit scheme or negligible level of interest-based credit scheme might be a supportive instrument. for supporting high energy growth and prompt capacity addition, re auction scheme is getting its high attention as a re support scheme. the scheme attracts more bidders to offer competitive unit price for renewables that is competitive with traditional ffs. systematic/regular auctioning scheme keeps re project in continuation and diversified gains will come out. but the auction scheme must be tailored specifying the specific countries. the author points some literature gap for the targeted countries. the six relatively, developing, open, and emerging economies (greece, italy, poland, portugal, romania, spain) from eu were chosen as the representative sample. we considered them to be good subjects of a research that may show the difficulties of the parallel challenges of ff subsidy, economic development, greenhouse gases and the energy consumption. after analyzing the data for the period 2001–2020, the results remark that the var model soothes the stability condition. the paper gets an instinct retort on behalf of the expansion of each concern variable on the re generation mentionable. for attracting more investor to the re generation, the policy makers are withdrawing subsidy from ff. in this transition period, the consumers should be insisted to be energy efficient and energy saver. szabo (2022) suggests natural gas as the transitional fuel due to its comparative cleanliness features (compare with coal, liquefied natural gas-lng, high-speed furnish oil-hfo). systematic political support and support from the local community would be able to present a economically viable clean energy transition to the society and shape the next progress of re. so, central level decision is highly required. finally, the research was limited some variables. but the paper does not pay its attention to some burning topics like expansion of re and contribution to regional economic development (like job creation, local gdp growth). so, further research can go on this issue. 6. acknowledgments the author is dedicatedly grateful to dr. dávid kiss gábor and dr. somosi sarolta, faculty of economics and business administration, university of szeged, hungary and dr. balázs felsmann tibor, university of corvinus, hungary for improving the main concept of this paper. figure 6: variance decomposition of total renewable energy (solar and wind) generation using var factors source: author’s edition, eviews10 alam: renewable energy (solar and wind) generation and its effect on some variables for selected eu countries with panel var model international journal of energy economics and policy | vol 12 • issue 5 • 2022310 references abolhosseini, s., heshmati, a. (2014), the main support mechanisms to finance renewable energy development. working paper, 40(c), 876-885. angel, j. (2016), towards energy democracy: discussions and outcomes from an international workshop. amsterdam: transitional institute. bmu (2009). the international climate initiative of the federal republic of germany. berlin: federal ministry for the environment, nature conservation and nuclear safety. beaton, c., gerasimchuk, i., laan, t., lang, k., vis-dunbar, d., wooders, p. (2013), a guidebook to fossil-fuel subsidy reform for policy makers in southeast asia: global subsidies initiative. geneva: international institute for substantial development. beg, n., morlot, j.c., davidson, o., afrane-okesse, y., tyani, l., deston, f., sokona, y., thomas, j.p., la rovere, e.l., parikh, j.k., parikh, k., rahman, a.a. (2002), linkages between climate change and sustainable development. climate policy, 2, 129-144. burke, m.j., stephens, j.c. (2018), political power and renewable energy futures: a critical review. energy research and social science, 35, 78-93. capelle-blancard, g., crifo, p., diaye, m.a., oueghlissi, r., scholtens, b. (2019), sovereign bond yield spreads and sustainability: an empirical analysis of oecd countries. journal of banking and finance, 98, 156-169. couture, t., gagnon, y. (2010), an analysis of feed-in-tariff remuneration model: implications for renewable energy investment. energy policy, 38(2), 955-965. dinh, d.v. (2020), impulse response of inflation to economic growth dynamics: var model analysis. journal of asian finance, economics and business, 7(9), 219-228. do xuan, h., nepal, r., jamasb, t, rabindra n. (2020), electricity market integration, decarbonization and security of supply: dynamic volatility connectedness in the irish and great britain market. energy economics, 92(c), 1-11. ferrer, r., shahzad, s.j.h., lopez, r., jareno, f. (2018), time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices. energy economics, 76, 1-20. frimpong, p.b., antwi, a.o., brew, s.e.y. (2018), effects of energy policy on economic growth in the ecowas sub-region: investigating the channels using panel data. journal of african business, 19(2), 227-243. frondel, m., ritter, n., schmidt, c.m., vance, c. (2010), economic impacts from the promotion of renewable energy technologies: the german experience. energy policy, 38, 4048-4056. gábor, d.k., gábor, z.t., lippai-makra, e., tamás, r. (2020), last resort: european central bank’s permanent engagement in tackling foreign exchange liquidity disruptions in the euro area banking system. financial and economic review, 19(4), 83-106. international energy agency. (2020). monthly oecd electricity statistics. paris: international energy agency. international energy agency. (2021a), global energy review 2021. paris: international energy agency. international energy agency. (2021b), net zero by 2050a roadmap for the global energy sector. paris: international energy agency. irena. (2017), renewable energy auctions: analyzing 2016. abu dhab: international renewable energy agency. irena-cem. (2015), renewable energy auctions-a guide to design. abu dhabi: international renewable energy agency and clean energy ministerial. irena-gcget. (2019), a new world: the geopolitics of the energy transformation. international renewable energy agency-global commission on the geopolitics of energy transformation. kumar, k., paramanik, r.n. (2020), nexus between indian economic growth and financial development: a non-liner ardl approach. journal of asian finance economics and business, 7(5), 454-464. lütkepohl, h. (2005), new introduction to multiple time series analysis. new york: springer. lütkepohl, h., kratzig, m. (2004), applied time series econometrics. cambridge: cambridge university press. matthaus, d. (2020), designing effective auctions for renewable energy support. energy policy, 142, 1-9. moyer, e.j, woolley, m.d., glotter, m.j., weisbach, d.a. (2013), climate impacts on economic growth as drivers of uncertainty in the social cost of carbon. journal of legal studies, 43(2), 401-425. mu, y., cai, w., evans, s., wang, c., roland-holst, d. (2018), employment impacts of renewable energy policies in china: a decomposition analysis based on a cge modeling framework. applied energy, 210(15), 256-267. oh, i., yoo, w.j., kim, k. (2020), economic effects of renewable energy expansion policy: computable general equilibrium analysis of korea. int j environmental research and public health, 17(13), 4762. pegels, a., vidican-auktor, g., lütkenhorst, w., altenburg, t. (2018), politics in green energy policy. journal of environment and development, 27(1), 26-45. rennkamp, b., haunss, s., wongsa, k., ortega, a., casamadrid, e. (2017), competing coalitions: the politics of renewable energy and fossil fuels in maxico, south africa and thailand. energy research and social science, 34, 214-223. shimbar, a., ebrahimi, s.b. (2020), political risk and valuation of renewable energy investments in developing countries. renewable energy, 145, 1325-1333. simelyte, a., dudzeviciute, g. (2017), consumption of renewable energy and economic growth. in: 5th international scientific conference on contemporary issues in business, management and education’ 2017. vilnius: vilnius gediminas technical university. pp232-241. available from: https://cibmee.vgtu.lt/index.php/verslas/2017/paper/ viewfile/48/90 [last accessed on 2021 dec 12]. sweeney, s. (2015), energy democracy in greece: syriza’s program and the transition to renewable energy. brussels: trade unions for energy democracy. szabo, j. (2022), energy transition or transformation? power and politics in the european natural gas industry’s trasformismo. energy research and social science, 84, 102391. takentsi, s., sibanda, k., hosu, y.s. (2022), energy prices and economic performance in south africa: an ardl bonds testing approach. cogent economics and finance, 10(1), 1-24. thompson, h. (2006), the applied theory of energy substitution in production. energy economics, 28(4), 410-425. zhang, z., chen, y.h., wang, c.r. (2021), can co2 emission reduction and economic growth be compatible? evidence from china. frontiers in energy research, 9, 1-11. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 4 • 2022 217 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(4), 217-225. forecasting uncertainty intervals for return period of extreme daily electricity consumption katleho makatjane* department of statistics, university of botswana, gaborone, botswana. *email: makatjanek@ub.ac.bw received: 03 march 2022 accepted: 13 june 2022 doi: https://doi.org/10.32479/ijeep.12901 abstract the use of extreme value theory (evt) is usually aimed at quantifying the asymptotic behaviour of extreme quantiles. the generalised pareto distribution (gpd) with peaks-over-threshold approach is applied to bootstrap uncertainty intervals for the return periods of extreme daily electricity consumption in south africa (sa) for the period of 02 january 2014–29 march 2021. the leeway of extremes in daily electricity consumption studied here is the impetus behind this study. to examine the effect of a time-based and extreme non-stationary trend in a dataset, a non-stationary gpd is cast-off in computing the shape parameter ξ and, this resulted in the establishment of a type iii gpd known as a weibull class for the sa electricity sector. results of this study revealed a non-stationary trend with a prediction power of 89.6% for the winter season and 85.65% non-winter season. this means that evt provides a robust basis for statistical modelling of extreme values. furthermore, a base for future researchers for conducting studies on emerging markets, more specifically in the sa context has also been contributed. keywords: bayesian; extreme value theory; generalised pareto distribution; markov-chain-monte-carlo; peaks-over-threshold jel classifications: c1, c4, c5 1. introduction south africa (sa) is considered to be the highest electricity producer and consumer in africa. it has been reviewed that, more than 50% of engendered electricity in africa comes from sa. likewise, the nation-state is archaeologically well-thought-out to have one of the peak electricity reserve margins sigauke (2014). these margins decreased from 25% in 2002 to 20% in 2004 and thereafter to 16% in 2006. meanwhile, in 2008, the reserve margins were projected to be 8-10% which was extremely below the target margin of 15%. since the year 2013, electricity consumption has increased remarkably in the residential sector and this increase was from 18200 kwh in 2013 to 19000 kwh in 2016. the combined effects of all these changes in demography, and economy can be investigated using historical patterns, but contribute to uncertainties when forecasting future electricity consumption. the infiltration of different sources of electricity, for example, renewables, sunlight based and wind, could equally have added to a decrease in electricity demand. due to the absence of capacity experienced by eskom by 2007 to generate enough electricity, some organisations and families had to find different ways of power sources and mokilane (2018) emphasised that this would have brought about a decrease in demand for electricity. shockingly, the genuine size of the power consumption market is yet obscure because of the inaccessibility of sustainable power sources and different types of power generation. the joined impact of everyone on adjustments in demography, economy and energy consumption patterns are explored utilising chronicled designs; thus far add to vulnerabilities when attempting to predict and forecast future electricity consumption. ever since the year 2008, different interventions toward electricity supply were implemented because of high electricity demand. this fused a national awareness campaign among others (khobai, 2018). in some instances, load shedding had to be used as the last resort to prevent a system-wide blackout. these interventions slightly brought electricity demand this journal is licensed under a creative commons attribution 4.0 international license makatjane: forecasting uncertainty intervals for return period of extreme daily electricity consumption international journal of energy economics and policy | vol 12 • issue 4 • 2022218 close to its supply, while at the same time reasonable reserve margins were being maintained. in energy sectors risk denotes a probability distribution of future returns; hence, uncertainty is considered as a broader concept that incorporates indistinctness about the parameters of this probability distribution babatunde et al. (2020) and anwar et al. (2020). there are various types of measures seeking to estimate risk and uncertainty: (1) realised and derivatives-implied distributions of returns across assets, (2) news-based measures of policy and political insecurity, (3) survey-based indicators, (4) econometric measures, and (5) ambiguity indices. the benefits of macro trading are threefold. first, uncertainty measures provide a basis for comparing risk assessment of the prevailing market with private information and research. second, changes in economic indicators often forecast near-term flows in and out of risky asset classes. third, the level of public and any market uncertainty is indicative of risk premia offered across asset classes. however, daily return periods necessitate planning under uncertainty, and one must contend with operational, tactical, and strategic considerations. the energy sector planning under uncertainty entails determining the appropriate location of a sector, its size, transmission, and distribution (returns flow analysis, analysis of the frequency, and occurrence of extreme losses and scheduling of risk factors). uncertainties in forecasting extreme daily losses may arise because of increased technology allowing energy fraud systems; resulting in a stock market crash, population growth, and general randomness in individual energy market participants, as well as current economic insecurity and political conditions sigauke et al. (2014). the inborn vulnerabilities in predictions suggest that forecasts ought to be probabilistic in an ideal world. in other words, they should take the form of probability distributions over future quantities or events (gneiting and katzfuss, 2014). probabilistic forecasting of electricity uncertainty and risk promotes the management of electricity use and planning. the use of var and or es is a measure that aims at lowering risk effects such as that of credit risk, exchange rate risk, and interest rate risk—to mention a few that harm the economy and some other sectors of the economy. this also gives a positive impact on market values that are associated with the use of other portfolios such as an aggressive portfolio. short-term forecasting has a superior impact on the safety and financial implication of the economic network. since the energy sector has a stochastic and uncontrollable nature, the current study makes use of generalised pareto distribution (gpd) via peaks-over-threshold (pot) through the bayesian procedure. this approach helps to obtain more robust credible estimates and solve uncertainty problems. to achieve this objective, a more robust methodology for modelling uncertainty is considered, and beutner et al. (2018) defined this method as a bootstrap to probability forecasting. these authors emphasised that different bootstrap procedures have been studied and are based only on generalized autoregressive conditional heteroscedasticity (garch) estimates. therefore, this study extends the garch bootstrap estimates to an extreme approach by utilising the gpd and comparing the performance of four risk measures namely value—at—risk (var), expected shortfall (es), conditional tail expectation (cte) and glue—value—at—risk (gvar) in estimating associated risk on daily electricity uncertainty, and currently, no other study has taken this approach. bootstrapping of extreme intervals for return periods with gpd estimates gives precise and accurate extreme return or loss periods. since the number of recent contributions related to forecasting returns and loss periods is extremely large, the main contribution of this study is forecasting and bootstrapping extreme returns periods on losses of daily electricity consumption by the use of gpd. this approach takes into consideration real-time forecasting and it improves the accuracy of the forecasts, and one to identify extreme changes in the immediate, especially when dealing with economic conditions that are constantly changing. most researchers when forecasting extreme daily return periods overlook this feature. the second contribution is the development of a truncated wild bootstrap (twb). however, siegl and west (2001) used a monte-carlo (mc) bootstrapping method which refined the computational results in different ways through resampling. but, with the proposed truncated wild bootstrap, the procedure accounts for asymmetric distributions; moreover, under further assumptions, if the observations belong to the domain of attraction of a symmetric stable law, it performs equally well in terms of average coverage, and yet, shorter intervals in smaller samples as compared to recursive bootstrap through the mc procedures. the last contribution is the estimation of risks associated with losses on daily electricity consumption and comparing the prediction performance of these risk measures. 2. methodology the data that is used in this paper comprises of total daily electricity consumption of sa for the period of 02 january 2014 to 29 march 2021. data for the period 01 august to 30 april of each year are defined as the non-winter season while the remaining period of 01 may to 31 july is defined as the winter season period. in total there are 2645 observations from which 2644 daily consumption is calculated. let xt be daily electricity consumption on day t and xt-1 be daily electricity consumption on day t-1, then, daily consumption is defined as a day-to-day change in electricity consumption. the south african power utility company (eskom) provided this data. assuming that xt has a density function of f; an access distribution over according to sigauke (2014) has the following density function f x p x u x|x f x u f u f u u � � � � � �� � � �� �� � � � � � 0 1 (1) for0 ≤ x <xf–u, where f ≤ ∞ is the right endpoint of f. according to fotouhi (2019) and sigauke et al. (2013) the right endpoint is understood as xf = sup (x ∈ r: f(x) < 1). 2.1. the gpd and pot the gpd plays a role in a natural distribution of excesses over a reasonably high threshold maposa et al. (2016). according to arnold (2014), the shape parameter ξ in a gpd serves the same purpose as in the generalised extreme value distribution (gevd). nortey et al. (2015) and scarrott and macdonald (2012) disclosed makatjane: forecasting uncertainty intervals for return period of extreme daily electricity consumption international journal of energy economics and policy | vol 12 • issue 4 • 2022 219 that for a sequence of observations say x1,…,xn, the extremes x-u of some suitably high threshold u can be well approximated by gpd (μ; σ; ξ); while chinhamu et al. (2015) revealed that a three parameter gpd with σ as a scale parameter and ξ as a shape parameter is given by ( ) ( ) ( ) 1 , 1 1 , 0 1 exp , 0 x g x x ξ ξ β ξ µ ξ σ µ ξ σ −  − − + ≠     =    − −  − − =     (2) where, x > 0 when ξ ≤ 0, tsay (2014) and huang et al. (2015). for the selection of a threshold value, the hill’s and mean excess life plots are used in this study. if the behaviour of both plots increases, these results provide a piece of evidence that the tails of a series studied are heavier than the exponential distribution. the point from which an increasing and linear behaviour starts can be a rough indication of an appropriate threshold value. 2.2. bayesian inferences to parameter estimates in the bayesian methodology, all obscure quantiles are considered as irregular factors and vulnerabilities over those quantiles that are addressed utilizing the likelihood contingent of the accessible data. when estimating any parameter using classical or frequentist methods, the sampling distribution of a parameter is most likely assumed to be normal or gaussian. this methodology is very unrefined in the sense that in real situations the sampling distributions of parameters can deviate from normality. with bayesian analysis, reasonable approximations to the sampling distribution are thought of; and their inferences are arrived at utilizing non-exclusive procedures and observed data. the fundamental standard behind bayesian statistics is as follows. some prior thoughts regarding any parameter or data set can neither be acquired from prolonged, some detailed observations nor by comparing them with similar conditions pu et al. (2021). the bayesian approach also allows for an additional source of variation, which implies that the parameters now have probability distributions with hyper-parameters giving small standard errors. this is achieved through the naive standard errors, which are computed by dividing the actual standard deviation by the number of iterations just as maposa et al. (2016) has suggested. furthermore, droumaguet (2012) also emphasized that bayesian methods provide densities of the model parameters, which solves the problem of a confidence interval, and finally bayesian shrinkage techniques allow models to be estimated with higher dimensions and these would have complex shapes of the likelihood function and be more difficult to estimate with classical algorithms. sigauke et al. (2012) declared that ambiguity about the parameters is very minimal. 2.3. the likelihood function for the gpd, a parameter vector θ = (μ, σ, ξ) and its bayes estimates for discrete and continuous functions are given by f x f f x f x f f x f f x i i i i i j j j � � � � � � � � �� � � � � � � � � � � � � � � � � �� (3) and, f x f f x f x f f x f f x d � � � � � � � � � � � � � � � � � � � � � � � � � �� (4) where, f (θ), f (x|θ), f (x|θ) f (x) are the prior, posterior, likelihood, and normalization constant respectively. in addition to that, vidal (2014) has indicated that posterior information is a combined sum of prior and sample information. with these computations, model (4) is further modified to p x p p x p x p p x p p x d p p x� � � � � � � � � �� � � � �� � � � � � � �� � � � �� � � � � �� � � � ¦ 1 (5) where θ is the vector parameters of the generalized pareto distribution, p (θ|x) is the posterior distribution, x is a vector of observations; φ is the space parameter, p(θ) is the prior distribution, and p(x|θ) is the likelihood function of the gpd. therefore, three parameters are estimated following a joint posterior distribution of µ, σ and ξ and this joint distribution is given by � � � � � � � � � , , y y i n iu� � � � �� �� � � � � � � �� � � � 1 11 1 1 (6) where π (μ, σ, ξ) ∝ (1⁄σ) exp –ξ is the maximal data information(mdi) before jonathan et al. (2021), nμ is the number of observations above the threshold. the three parameters are estimated by simulating a large number of μʹ s, σʹ s, and ξʹ s values from the posterior distribution and taking the mean of the simulated values to obtain estimates. to simulate a set of (μ, σ, ξ)’s from the posterior metropolis-hastings algorithm by simulating alternatively μ and, σ from their conditional density function given a fixed ξ. the parameter ξ is then simulated from its conditional density given the selected σ. this process is repeated numerous times. future posterior predictive tail probabilities of a future observation y0, can be predicted through the following posterior predictive density p y y y y y0 0 0 1 1�� � � � � � �� ��� � � � � �� � � � � � � � , , , ,� � � � � � (7) according to jonathan et al. (2021), equation (7) cannot be computed analytically but can be approximated easily by simulation. hence, equation (6) is used to simulate the values of µ, σ, and ξ which are then substituted into equation. (7). the average over all the tail probabilities is then used to estimate the posterior predictive tail probability. 2.4. risk measures having obtained estimators for ξ, σ and μ the conditional var, cte, gvar and es for a one-period ahead are estimated at the makatjane: forecasting uncertainty intervals for return period of extreme daily electricity consumption international journal of energy economics and policy | vol 12 • issue 4 • 2022220 α level. employing the proposed gpd, the conditional var according to anjum and malik (2020) is estimated as  ( ) ˆ 1 , 0 log 1 , 0 ˆ ˆˆ ˆ ˆ ˆ ˆ u u n u n var n u n −ξ π    β   + π − ξ ≠   ξ    =      −β − π ξ =     (8) β̂ and ξ̂ are the estimates of the gpd parameters, and nu is the number of observations above the threshold µ in a given sample see, for instance, pfaff (2016). expected shortfall considers a loss beyond value-at-risk level and is shown to be sub-additive, while var disregards a loss beyond the percentile and is not sub-additive. nadarajah et al. (2014) provided a general computation of es with a given probability π which is defined as es e xi x var x var x var x pr x var x � � � � � � � � � � �� �� �� � �� � � � � �� � � � � � � � 1 �� � , (9) where i(.) denotes the risk indicator function. adopting theorem 3 of yang et al. (2015), the conditional tail expectation is computed as 2.5. theorem 3 of yang et al. (2015) let {x1, x2,…, xn} be a real-valued independent random variable with the following density function {f1, f2,…, fn} and the row vector {θ1, θ2,…,θn} to be nonnegative and nondegenerate zero random variables which is independent of {x1, x2,…, xn} but subjective on each other. if f jk k k k k� � � �� �l d, ,� �� and  � �k k k kx x x x�� � � �� �� �0 for all k ∈ {1,2,…, n}, then,  s ii x iin s i n x x n x � �� �)� � �� � �� �  1 1 1 1 1 (10) under the additional condition  � �k kx x x x�� � �� � � �� � 1 1 1 2, , , ,k n theorem 3 implies that  s ii x iin s i i x xi n n x i i � �� �)� �� �� �� �  1 (11) if θ1 = θ2,…,θn ≡ 1. tang and yuan (2014) publicised that asymptotic cte of level q is cte s s s xq n n n q � � �� � � �� � | , (12) where, x var s y s y qq q n n� � � � � �� � �� �� �inf :  . equation (12) has been later modified by yang et al. (2015) to cte s x c var xq n q k k i n q � � � �� �� � � � � � � � � � � � �� � ��~1 1 1 1  (13) given a confidence level α, the distortion function for glue-var is ( ) ( )1 2 1 h ,h 1 1 1, h .u, 0 u 1 1 h h k u h . u 1 , 1 u 1 1, 1 u 1 β α  ≤ < −β −β  −  = + − −β −β ≤ < −α  β−α  −α ≤ <   (14) where, α, β ∈ [0,1] so that α ≤ β, h1 ∈ [0,1] and h2 ∈ [h1, 1], β is the additional confidence parameter in addition to α. bellessampera et al. (2014), showed that the shape of the glue-var is determined by distorted survival probabilities h1 and h2 and levels 1-β and 1-α respectively. h1 and h2 are known as the distortion function heights. therefore, glue-var is computed by gluevar x cte x cte x var x h h � � � � �� � �, , . . . ,1 2 1 2 3� � � � �� � �� � � (15) where, ω1, ω2 and ω3 are from the notation � � � � � � � � � � � 1 1 2 1 2 2 1 3 1 2 2 1 1 1 1 � � �� � �� � � � � � �� � � � � � � � � � � h h h h h h . . ��� � � � � � the choice of this measure is based on the omega ratio as a tool for effective measurement and it also helps in dividing a set of investment outcomes into two groups: the area of profits and the area of losses. furthermore, no other study has applied this measure for risk assessment for financial market risk. for a continuous random variable, omega is computed by � x f x dx f x dx � � � � � �� � � � � �� � � � � 1 , (16) where τ is a given threshold. 2.6. return level periods the return level is a common and relatively simple measure of extreme events. the return level for the first year is the quantile that in a particular year has a 1 1 π probability to be exceeded (hu and scarrott, 2018). assuming that a two-parameter gpd is appropriate to model a variable xt for the exceedances of u, coles et al. (2001) revealed that the return level for x > u is as follows pr x x x u x u � �� � � � �� � � � � � � � � � � � � 1 1 � (17) it follows that: pr x x x u x u � �� � � � �� � � � � � � � � � � � � 1 1 � (18) makatjane: forecasting uncertainty intervals for return period of extreme daily electricity consumption international journal of energy economics and policy | vol 12 • issue 4 • 2022 221 where, ζu = pr {x > x}. the level xm that exceeded observation is the solution of 1 1 1 m x u u� � �� � � � � � � � � � � � � � � � � (19) when rearranged it simplifies to x u mm u� � � � ���� � �� � � � � 1 , (20) provided m is sufficiently large to ensure that xm > u. this all assumes that ξ ≠ 0. if working with ξ = 0, showed that equation (18) leads to x u mm u� � � �� �log (21) by definition, xm is a return level for m– observation. hu and scarrott (2018) pointed out that plotting xm against m on a logarithmic scale produces the same qualitative characteristics as return plots based on a gpd distribution when ξ = 0, it is concave when ξ > 0 and it is convex when ξ < 0. coles et al. (2001). it is quite convenient to present the return level on the annual scale so that the n year return level is the level expected to be exceeded once every n year. hence, the n-year return level is defined by z u nnn y u� � � � ���� � �� � � � � 1 (22) but, if ξ = 0, then (20) becomes x u mnm y u� � � �� �log (23) 2.7. bootstrapping predictive uncertainty intervals the truncated wild bootstrap (twb) is a bootstrap algorithm that is similar in construction to the wild bootstrap (wb) of cavaliere and georgiev (2013) but is only limited to several observations that are truncated based on some critical values around an axis of symmetry, hence its name. the twb is more general than the wb because it accounts for asymmetric distributions. moreover, under further assumptions, namely, if the observations belong to the domain of attraction of a symmetric stable law, the twb is the wb of cavaliere and georgiev (2013). the truncated wild bootstrap for testing the following hypothesis h h 0 0 1 0 : : � � � � � � that is propose here is described by algorithm 1 below. algorithm 1: truncated wild bootstrap generate a sample  : { }( )= =xi i n 1 of i.i.d1 random variables from model 2 for f 21� � � da� � � �, ,0 estimate  ˆˆ, , β σ α from  . select a per cent data to be truncated based on β ,� and α̂ . hence, select vn 1. i.i.d is referenced independently and identically distributed choose the mode m based on β ,� and α̂ end procedure: generate bootstrap samples xi j i n j , *� ��� � � � �� �1 1 � as follows x k m m k m x k m i j i j i n i i n , * � �� � �� � ��� �� � �� � � � �� � � � � � �  0 1 1 where ki≔ σ̂ -1 (xi–θ0) and b represents the number of bootstrap samples created based on a single sample  . return: bootstrap p value which is equal to the proportion of bootstrap statistics sn * more extreme than sn ( )ˆˆ* *,, , , 1 1 1 n n b n i nb n i p s s bα β = = ≤∑ where s xn j n i n i j, * , * : , .� �� � � �� � �� �1 1 0 1 is an indicator function, and s xn n ii n : ( )� �� ��� � 1 0 1 . 3. empirical analysis and discussion a gpd is fitted to the daily electricity consumption of sa using a pot approach. a non-stationary gpd denoted gpd (φ0}is fitted. various r packages, such as mcmc4extremes of e silva and do nascimento (2022), extremes’ version 2.0-11 of gilleland and katz (2016), ismev of gilleland (2018), evdbayes’ version 1.1-1 of stephenson and ribatet (2015) among others are used to execute the main analysis. the distribution of electricity consumption is not normally distributed as evidenced in figure 1. the first panel shows some upward and downward trends in conjunction with seasonality. this is also confirmed by the logarithmic returns on the middle panel as the series shows volatile patterns. regarding the marginal distribution, the quantile-quantile (q-q) plot in the right panel reveals a strong departure from linearity in the tails. this evidence is seen in table 1 because the reported kurtosis is greater than three and the skewness is less than zero indicating that electricity consumption is asymmetry with negatively skewed innovations. 3.1. winter and non-winter monthly electricity consumption over a specified threshold using the mean residual life and hills plots, a threshold value of 19671 kwh for the winter season is selected and for the non-winter season, 19752kwh is selected as a threshold value. initially, 75 and 104 data points are respectively collected for both winter and non-winter seasons. unlike thevaraja and sanjel (2016) who used a maximum likelihood method, this study makes use of bayesian mcmc methods for the proposed non-stationary gpd. according table 1: descriptive statistics electricity kurtosis skewness 69.36 −17.83 makatjane: forecasting uncertainty intervals for return period of extreme daily electricity consumption international journal of energy economics and policy | vol 12 • issue 4 • 2022222 to stroud et al. (2017), the mcmc approach provides accurate and full probabilistic inference for the parameter estimates. as revealed in tables 2 and 3 the estimated shape parameter of a non-stationary gpd which is denoted by ξ̂ is negative implying that the fitted gpd is a type iii gpd known as a weibull-gpd. the standard errors are calculated by dividing the actual standard deviation by the number of iterations. as stephenson (2016) has indicated, this is because the bayesian approach allows for an additional source of variation, which implies that the parameters now have a probability distribution with hyper-parameters that gives small standard errors; showing that ambiguity about the parameters is very minimal. since for both winter and non-winter extremes, the shape parameter is high above the threshold estimate of 10, the implication is that ξ̂ roughly plays the role of a scale parameter under the exponentiated gpd (lee and kim, 2019). in addition, the 95% confidence interval for ξ̂ is estimated for both winter and non-winter seasons by the following formula 2 ˆ ( ˆ ˆ)z seαξ ξ ξ=± × . note that these intervals for both seasons have negative limits which enclose ξ̂ endorsing the appropriateness of a weibull class of distributions. the estimates of the slope, µ are positive values for all seasons, indicating that daily extreme electricity consumption had an increasing trend over the past decade in sa. the same results of negative shape parameter and positive slope were found by gagaza et al. (2019) in their study of modelling non-stationary temperature extremes in kwazulunatal using the generalised extreme value distribution. furthermore, it can be seen that the slope of distribution for both winter and non-winter seasons falls faster near zero and produces infinitely long and thick tails. nevertheless, the four risk measures that are discussed in the previous section are used to compute the risk of losses in the energy sector in sa for daily electricity consumption and the results are presented in table 4. table 2: winter daily electricity consumption mcmc estimates threshold proportion gpd 95% ci for u p ξ̂ se ( ξ̂ ) ββ � se ( ββ � ) µ̂ se ( µ̂ ) electricity 19671 0.845 −0.076 0.019 443.637 192.818 0.207 0.068 (−0.416; −0.090) table 4: computation risk measures on daily losses in electricity consumption p winter season non-winter season var es cte glue var-risk var es cte glue var-risk electricity consumption 0.95 1.738 1.413 3.211 1.572 1.140 1.370 8.479 0.842 0.99 1.206 0.984 5.351 3.074 1.140 1.890 10.719 0.953 figure 1: returns on electricity consumption and q-q plot table 3: non-winter daily electricity consumption mcmc estimates threshold proportion gpd 95% ci for u p ξ̂ se ( ξ̂ ) ββ � se ( ββ � ) µ̂ se ( µ̂ ) electricity 19752 0.876 −0.253 0.083 648.280 358.495 0.168 0.074 (−0.416;-0.090) makatjane: forecasting uncertainty intervals for return period of extreme daily electricity consumption international journal of energy economics and policy | vol 12 • issue 4 • 2022 223 for the winter season, the extreme losses at 99% for var 1.206. this indicates that 99% of the time eskom is expected not to lose more than 1.206% while the expected loss using es at 99% is 0.984%. nevertheless, while using cte, the extreme losses are estimated at 5.35%. the implication here is that the highest losses expected by daily electricity consumption in the winter season are estimated at 5.351%. but in the non-winter season, the highest extreme losses are estimated at 10.719% when using cte which is surprisingly shocking because in winter more electricity is consumed by every sector of the economy. moreover, huang et al. (2015a), revealed that a one-day change in the financial market’s value would not decrease. to take into account market liquidity constraints and basel regulations, 5-day risk horizons in addition to the more typical 1-day horizon were being considered. the computation of economic capital using the glue-var measure is more conservative than using other risk measures under the winter season. therefore, the conclusion made is that winter and non-winter estimates of glue-var risk under different confidence levels exhibit analogous characteristics as observed from var, es and cte. generally, it can be noticed from table 5 that the nonwinter season has fewer bias estimates for all the risk measures as opposed to the winter seasons. 4. comparison analysis some of the posterior predicted tail probabilities for various extreme daily increases in peak electricity demand are given in table 6. ξ's, σ's and μ's are simulated as discussed in the section on methodology and the empirical results show the gpd is a good distribution show that both the gsp distribution and the gpd are a good fit to the data. the density comparison of truncated intervals in figure 2 shows that the truncated bootstrap intervals with sampling are much better to mimic the bootstrap intervals as this figure shows that truncated bootstraps intervals are closer to the true value intervals. furthermore, the average computation of the risk measure indicates that glue-var provides fewer bias estimates for the risk of extreme electricity consumption; giving the prediction power of 58.4% in the winter season and 84.4% in the non-winter season and finally giving the overall predictive power of 89.7%. 5. return level periods and bootstrapping uncertainty intervals the performance of two distributions as a function of return period t is explored. persson et al. (2010), disclosed that it is not phenomenal to calculate return periods as high as 10,000 years, relating to small risk. therefore, 10 months, 20 months and 50 months are used and the results are reported in table 7. according to table 7, the 20 month return period is 20799.7 kwh for winter table 6: posterior predictive tail probabilities winter non-winter y0 (kwh) ( )0 0 ,p y y y > 4000 0.0081 0.0261 4500 0.0280 0.0060 5000 0.0688 0.0106 5500 0.0150 0.1966 table 7: return level periods and uncertainty interval bootstraps period winter bootstrap replicates 95% ci non-winter bootstrap replicates 95% ci 10 months 20545.00 4000 (20544.96; 20545.04) 20834.62 2500 (20834.65; 20834.78) 20 months 20799.70 4500 (20799.66; 20799.74) 21072.64 2500 (21072.48; 21116.60) 50 months 21116.44 5000 (21116.40; 21116.48) 21329.57 2500 (21329.41; 21329.73) table 5: average computation of risk measures model ci var es cte glue-var risk winter 95% 3.933 3.611 5.822 1.572 99% 3.492 3.217 8.562 3.074 non-winters 95% 1.460 1.831 8.241 0.988 99% 1.460 2.311 10.549 2.226 figure 2: densities of truncated bootstrap intervals makatjane: forecasting uncertainty intervals for return period of extreme daily electricity consumption international journal of energy economics and policy | vol 12 • issue 4 • 2022224 electricity consumption, which means for every 20 months an average electricity consumption is 20799.7 kwh or more in sa with a probability of 5% is expected. but with non-winter consumption, for every 20 months, only 20799.7 kwh is expected to be exceeded on monthly average with the same probability of 5%. the estimated bootstrap confidence intervals are not wide but nearer to the returns letting to conclude that the prediction performance of mcmc gpd is accurate giving a prediction power of 89.6% for winter and 85.65% for non-winter seasons respectively. 6. conclusion and recommendations time series analysis and forecasting have been an active research area over the past decades. the accuracy of time series forecasting is fundamental to many decision processes and hence the research for improving the effectiveness of forecasting models has never stopped. this paper makes use of evt to forecast uncertainty intervals for a return period of extreme daily electricity consumption in sa. to achieve this objective, a bayesian mcmc is proposed and showed how it can be used in estimating the parameters of a three-parameter gpd. the importance of an mcmc approach is emphasised for parameter estimates as compared to other methods. a pot is also emphasised and the mean residual life and the hills plots respectively are used to find an optimal threshold value. based on the results of this study, the area of interest may have experienced too much extreme electricity consumption in the non-winter season than the winter season. this is however strange as in winter, more electricity is expected to be consumed because more people are consuming electricity for some other purposes such as heating in the house or workplaces. these empirical results showed that bootstrapping uncertainty intervals for the return period of extreme daily electricityhelp in determining critical peak months, and risk management including load shifting between transmission substations which is important for the stability of a power network. policy implications derived from this study are that policymakers and consumer side managers of electricity should play a fundamental role in attaining behavioural consumption of electricity, particularly during the non-winter season. in addition, there should be consumer response strategies designed for electricity consumers where the consumers will be exposed to inducements for time—of—day electricity pricing. current developed technology for electricity billing such that is similar to mobile or landline billing technology should be improved and give a realistic day—time electricity billing. future studies may also adopt multivariate loss distributions and multivariate copula methods to test the interdependence and extreme relationships within the households and business sectors for the consumption of electricity and further uses machine learning methods to predict the extreme multivariate losses and the probability of interdependence and default and finally automate the models to long term solutions. another area that requires future research is a probabilistic description and modelling of extreme peak loads using the poison point process. this modelling approach helps in estimating the frequency of occurrence of peak losses. a sensitivity analysis concerning daily losses performed for each daily electricity consumption for winter and non-winter seasons and the development of a two-stage stochastic integer recourse model to optimise returns’ distribution is an interesting future research direction with sa n data. references anjum, h., malik., f. (2020), forecasting risk in the us dollar exchange rate under volatility shifts. american journal of economics and finance, 54, 101257. anwar, m., naeem, a., gul, h., arif, a., fareed, s., javaid, n. (2020), electricity price and load forecasting using data analytics in smart grid: a survey. in: barolli, l., okada, y., amato, f, editors. advances in internet, data and web technologies. eidwt 2020. vol. 47. springer, cham: lecture notes on data engineering and communications technologies. p427-439. arnold, b. (2014), pareto distribution. wiley statsref: statistics reference. babatunde, o.t., oranye, h.e., nwafor, c.n. (2020), the volatility of some selected currencies against the naira using generalized autoregressive score models. international journal of statistical distributions and applications, 6(3), 42-46. belles-sampera, j., guillén, m., santolino, m. (2014), beyond value‐atrisk: gluevar distortion risk measures. risk analysis, 34(1):121-134. beutner, e., heinemann, a., smeekes, s. (2018), a residual bootstrap for conditional value-at-risk. arxiv, 2018, 09125. cavaliere, g., georgiev, i. (2013), exploiting infinite variance through dummy variables in non-stationary autoregressions. econometric theory, 29(6), 1162-1195. chinhamu, k., huang, c.k., huang, c.s., chikobvu, d. (2015), extreme risk, value-at-risk and expected shortfall in the gold market. international journal of business and economic research, 14(1), 107-122. coles, s., bawa, j., trenner, l., dorazio, p. (2001), an introduction to statistical modeling of extreme values. berlin, heidelberg: springer. droumaguet, m. (2012), markov-switching vector autoregressive models: monte carlo experiment, impulse response analysis, and granger-causal analysis. european university institution. phd theses, department of economics. fotouhi, a.r.j. (2019), bayesian analysis of extreme values in economic indexes and climate data: simulation and application. arxiv, 2019, 02175. gagaza, n., nemukula, m.m., chifurira, r., roberts, d.j. (2019), modelling non-stationary temperature extremes in kwazulunatal using the generalised extreme value distribution. in. annual proceedings of the south african statistical association conference. south african statistical association (sasa). p1-8. gilleland, e., katz, r.w.j. (2016), extremes 2.0: an extreme value analysis package in r. journal of statistical software, 72(8), 1-39. gilleland, m.e. (2018), package “ismev”. available from: http://cran. pau.edu.tr/web/packages/ismev/ismev.pdf gneiting, t., katzfuss, m. (2014), probabilistic forecasting. annual review of statistics and its application, 1, 125-151. hu, y., scarrott, c. (2018). evmix: an r package for extreme value mixture modeling, threshold estimation and boundary corrected kernel density estimation. journal of statistical software, 84(5), 1-27. huang, c.k., huang, c.s., hammujuddy, j. (2015), empirical analyses of extreme value models for the south african mining index. south african journal of economics, 83(1), 41-55. jonathan, p., randell, d., wadsworth, j., tawn, j. (2021), uncertainties in return values from extreme value analysis of peaks over threshold makatjane: forecasting uncertainty intervals for return period of extreme daily electricity consumption international journal of energy economics and policy | vol 12 • issue 4 • 2022 225 using the generalised pareto distribution. ocean engineering, 220, 107725. khobai, h. (2018), electricity consumption and economic growth: a panel data approach for brazil, russia, india, china and south africa countries. international journal of energy economics and policy, 8(3), 283-289. lee, s., kim, j.h. (2019), exponentiated generalized pareto distribution: properties and applications towards extreme value theory. communication in statistics-methods and theory, 48(8), 2014-2038. maposa, d., lesaoana, m., cochran, j.j. (2016), modelling non-stationary annual maximum flood heights in the lower limpopo river basin of mozambique. jàmbá, 8(1), 185. mokilane, p. (2018), density forecasting for long-term electricity demand in south africa using quantile regression. south african journal of economics and management sciences, 21(1), 1-14. nadarajah, s., zhang, b., chan, s. (2014), estimation methods for expected shortfall. quantitative finance, 14(2), 271-291. nortey, e.n., asare, k., mettle, f.o. (2015), extreme value modelling of ghana stock exchange index. springerplus, 4(1), 1-17. persson, k., stockholm, s., rydén, j. (2010), exponentiated gumbel distribution for estimation of return levels of significant wave height. journal of environmental statistics, 1(3), 1-12. pfaff, b. (2016), financial risk modelling and portfolio optimization with r. 1st edn. hoboken, new jersey: john wiley and sons. pu, z., liu, c., shi, x., cui, z, wang, y. (2021), road surface friction prediction using long-short-term memory neural network based on historical data. journal of intelligent transportation systems, 26(1), 34-45. scarrott, c., macdonald, a. (2012), a review of extreme value threshold estimation and uncertainty quantification. revstat-statistical journal, 10(1), 33-60. siegl, t., west, a. (2001), statistical bootstrapping methods in var calculation. applied mathematical finance, 8(3), 167-181. sigauke, c. (2014), modelling electricity demand in south africa. (doctoral dissertation university of the free; state department of mathematical statistics and actuarial science). available from: http://hdl.handle.net/11660/1569. sigauke, c., verster, a., chikobvu, d. (2013), extreme daily increases in peak electricity demand: tail-quantile estimation. energy policy, 53, 90-96. silva e.w., do nascimento, f. (2022), mcmc4extremes: an r package for bayesian inference for extremes and its extensions. communications in statistics-simulation and computation, 51(2), 432-442. stephenson, a. (2016), bayesian inference for extreme value modelling. in extreme value modeling and risk analysis. boca raton: chapman and hall/crc, 277-300. stephenson, a., ribatet, m. (2015), a user’s guide to the evdbayes package (version 1.1). journal of statistical software, 1-14. available from: https://cran.r-project.org/web/packages/evdbayes/evdbayes.pdf stroud, j.r., stein, m.l., lysen, s. (2017), bayesian and maximum likelihood estimation for gaussian processes on an incomplete lattice. journal of computational and graphical statistics, 26(1), 108-120. tang, q., yuan, z. (2014), randomly weighted sums of subexponential random variables with application to capital allocation. extremes, 17(3), 467-493. thevaraja, m., sanjel, d. (2016), statistical modelling immoderate weather event by using r and sas: a case study of minneapolis/st paul region in minnesota, usa. international journal of research and scientific innovation, 5(6), 115-134. tsay, r.s. (2014), an introduction to the analysis of financial data with r. hoboken, new jersey: john wiley and sons. available from: https://dl.acm.org/doi/abs/10.5555/2560070 vidal, i. (2014), a bayesian analysis of the gumbel distribution: an application to extreme rainfall data. stochastic environmental research and risk assessment, 28(3), 571-582. yang, y., ignatavičiūtė, e., šiaulys, j. (2015), conditional tail expectation of randomly weighted sums with heavy-tailed distributions. statistics and probability letters, 105, 20-28. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 6 • 2021170 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(6), 170-179. is india financing its emissions through external debt? emrah bese1*, haven swint friday1, cihan ozden2 texas a and m university rellis, corpus christi, texas, usa, 2near east university, mersin, turkey. *email: phdebese@gmail.com received: 24 april 2021 accepted: 05 august 2021 doi: https://doi.org/10.32479/ijeep.11533 abstract the main aim of this study is to analyze the effect of external debt on different types of emissions in india as carbon dioxide emissions, methane emissions, emissions from liquid fuel consumption, emissions from solid fuel consumption, and emissions from gaseous fuel consumption. india has a fast growing in external debt especially after 2008 world financial crisis. india has a similar situation to china and turkey which also started to increase external debt significantly after 2008 world crisis. this study aims to fill the gap in the literature by analyzing the effect of external debt on emissions. this study is the first study in the literature for india. the second aim of the study is to investigate whether inverted u relationship exists between economic development, and carbon oxide emissions, methane emissions, methane emissions, emissions from liquid fuel consumption, emissions from solid fuel consumption, and emissions from gaseous fuel consumption. this study confirmed inverted-u relationship between methane gas emissions and economic development, and emissions from gaseous fuel consumption and economic development. the positive and significant effect of external debt on carbon dioxide emissions, methane emissions, emissions from gaseous fuel consumption and emissions from solid fuel consumption is confirmed by this study. the analysis is important since after 2008 crisis many countries such as china and turkey besides india started to borrow external debt heavily to create government investments to boost employment market which collapsed due to global economic crisis. this study carries importance since global greenhouse gas emissions may be financed through external debt in india. since sustainability is the main issue in current world and reduction of emissions is one of the highest priorities of humanity, necessary measures should be taken into account to reduce financing of emissions through external debt in india. this study recommends further analysis to be done with updated intervals. keywords: external debt, india, ardl model, emissions, economic growth jel classifications: q01, q56, c01 1. introduction this study investigated the effect of external debt (ex) on greenhouse gas emissions which are carbon dioxide emissions (ce), methane emissions (mn), emissions from solid fuel consumption (sfco), emissions from gaseous fuel consumption (gfco), and emissions from liquid fuel consumption (lfco) for india for the period 1971 to 2012. this is the first study in the literature that investigates the effect of external debt on greenhouse gas emissions for india. in this study, ce, mn, ex, gfco, sfco and lfco are chosen to be investigated by autoregressive distributed lag model by pesaran et al. (2001). world bank website is used to gather the data analyzed in this study. data used in this study are gathered from world bank database. ce are emissions from manufacturing of cement and burning of fossil fuels. ce are in kilo tons term. mthn are emissions from industrial methane production and agriculture. mn are in kilo tons of ce equivalent. sfco are in kilo tons term. sofc are emissions from mainly of coal use as energy source. lfco are in kilo tons term. lfco are emissions from mainly of petroleum derived fuels as energy source. gfco are in kilo tons term. gfco are emissions from mainly of natural gas use as energy source. ex is in current us dollars term. ex is the total external debt which includes long-term debt and short-term debt. economic development (gd) which is gross domestic per capita are in terms of constant 2010 us$. gd2 is the square of gd. energy consumption (ecm) is in terms of kg of oil equivalent per capita. time period of this this journal is licensed under a creative commons attribution 4.0 international license bese, et al.: is india financing its emissions through external debt? international journal of energy economics and policy | vol 11 • issue 6 • 2021 171 study is between 1971 and 2012 which chosen according to the availability of data in data sources. ce increased by 8.7 times between 1971 and 2012. mn increased by 0.58 times in the same period. sfco increased by 8.7 times between 1971 and 2012 (figure 1). gd increased by 2.7 times and ecm increase 1.2 times (figure 2). ex increased by 41 times and ex increase rapidly after 2008 (figure 3). gfco increased 71 times and lfoc increased by 6.84 times between 1971 and 2012 (figure 1). all the variables used in this study are in increasing trend in india for the period 1971-2012. the main aim of this study is to investigate the effect of ex on emissions so to answer the question whether india is financing its emissions through ex. although the main of the study is to investigate the effect of ex on emissions, the kuznets curve relationship is also investigated as second aim of this study in india. there is a gap in the literature for the investigation of the effect of external debt on emissions for india. this study aims to fill this gap by performing this study. h1: ex has a significant impact on ce in india for the period 1971-2012. h2: there is inverted u relationship between ce and gd in india for the period 1971-2012. h3: ex has a significant impact on mn in india for the period 1971-2012. h4: there is inverted u relationship between mn and gd in india for the period 1971-2012. h5: ex has a significant impact on sfco in india for the period 1971-2012. h6: there is inverted u relationship between sfco and gd in india for the period 1971-2012. figure 1: ce, mn, lfco and sofc figure 2: gd and ecm bese, et al.: is india financing its emissions through external debt? international journal of energy economics and policy | vol 11 • issue 6 • 2021172 h7: ex has a significant impact on lfco in india for the period 1971-2012. h8: there is inverted u relationship between lfco and gd in india for the period 1971-2012. h9: ex has a significant impact on gfco in india for the period 1971-2012. h10: there is inverted u relationship between gfco and gd in india for the period 1971-2012. second part discusses literature for the ekc hypothesis and external debt. third part discusses the methodology used in this study. fourth part discusses results and discussion of this study. fifth and final part is conclusion. 2. review of literature in this part, most recent studies in the literature are discussed. overall summary of this part is given in table 1. saxena and shanker (2017) confirmed negative relationship between external debt and economic development for india for the period 1991 to 2016. although a negative relationship is found, up to a certain level of external debt, external debt positively affects economic development. nath (2020) examined the relationship between external debt, export and economic development in india for the period 1970-2018. nath confirmed that the effect of external debt on economic growth is positive in india. irfan et al., (2020) analyzed the moderating effect of capital formation for external debt an stock market performance for pakistan, sri lanka, bangladesh and india for the period 1992-2017. irfan, rao, akbar, and younis confirmed that capital formation has a positive effect for external debt and stock performance and external debt has negative effect on economic development. chisti and shabir (2019) analyzed the effect of external debt on economic development, government spending, revenue, inflation and exports in india for the period 2007-2017 on quarterly data. chisti and shabir confirmed that there is no significant relationship figure 3: ex table 1: summary of literature review study main findings saxena and shanker (2017) confirmed negative relationship between ex and economic development nath (2020) confirmed the positive effect of ex on economic development irfan et al., (2020) confirmed the negative effect of ex on economic development chisti and shabir (2019) confirmed no significant relationship between ex and economic development pahwa (2018) confirmed the negative effect of ex on economic development joy and panda (2019) confirmed ex negatively affected non-developmental expenditure and positively affected inflation sinha and bhatt (2017) confirmed n-shaped relationship between emissions and economic development sultan et al., (2021) confirmed the ekc hypothesis in india murthy and gambhir (2018) confirmed n-shaped relationship between emissions and economic development khan et al. (2020) confirmed the ekc hypothesis for panel countries of india, china, and pakistan alam and adil (2019) did not confirm the ekc hypothesis in india katircioglu and celebi (2018) did not confirm the effect of ex on emissions beşe et al., (2021) confirmed the effect of ex on emissions beşe et al., (2020) confirmed the coal kuznets curve magazzino et al., (2020) confirmed the coal kuznets curve qiao et al., (2019) confirmed the coal kuznets curve shahbaz and sinha (2019) recommended new methodologies to be used to investigate the ekc hypothesis purcel (2020) recommended new methodologies to be used to investigate the ekc hypothesis bese, et al.: is india financing its emissions through external debt? international journal of energy economics and policy | vol 11 • issue 6 • 2021 173 between external debt and economic development, external debt and export, external debt and revenue, and external debt and government spending. they found that external debt causes increase in inflation. pahwa (2018) examined the relationships between external debt, internal debt, population, investment and trade openness for india for the period 1980-2014. pahwa confirmed that external debt and internal debt affect economic growth significantly and negatively. joy and panda (2019) analyzed the relationship between external debt, external debt servicing, gross domestic capital formation, gross domestic savings, developmental expenditure, nondevelopmental expenditure, export, inflation and foreign direct investment for india. joy and panda confirmed the long run relationship between the variables. joy and panda confirmed that external debt postively affected inflation but negatively affected non-developmental expenditure. sinha and bhatt (2017) analyzed the relationship between nitrogen dioxide emissions (no2), ce and economic growth for india. sinha and bhatt examined ce for 1960-2011 and no2 for 19702012. sinha and bhatt confirmed n-shaped relatinship between emissions and economic growth for no2 and ce. sultan et al., (2021) confirmed the ekc hypothesis in india for the period 1978 to 2014. murthy and gambhir (2018) confirmed n-shaped relationship between ce and economic development in india for the period 1991-2014. khan et al. (2020) confirmed the ekc hypothesis for panel countries of china, india and pakistan for the period 1970-2016. khan et al. confirmed u-shaped relationship between ecological footprint and economic development for india and china, and the ekc hypothesis for pakistan for the period 1970-2016. alam and adil (2019) did not confirm the ekc hypothesis in india for the period 1971-2016. for the effect of external debt on emissions, the most recent studies are belong to katircioglu and celebi (2018) and beşe et al., (2021). katircioglu and celebi (2018) analyzed the case in turkey and beşe et al., (2021) analyzed the case in china. while katircioglu and celebi (2018) did not find any evidence for the effect of ex on emissions in turkey, beşe et al., (2021) confirmed the effect of ex on emissions in china. since this study analyzed the emissions from coal consumption, the most recent studies for coal consumption and economic development are belong to beşe et al., (2020), magazzino et al., (2020) and qiao et al., (2019). for literature review studies for the ekc hypothesis, the most recent studies are belong to shahbaz and sinha (2019) and purcel (2020). both literature reviews stated that new methodologies should be included for the investigation of the ekc hypothesis. literature review shows that the general tendency in the literature is to analyze the relationship between external debt and economic development. there is a gap in the literature for the analysis of the effect of external debt on emissions for india. 3. data and methodology 3.1. data the variables used in this study are as follows. ce are emissions from manufacturing of cement and burning of fossil fuels. ce are in kilo tons term. mthn are emissions from industrial methane production and agriculture. mn are in kilo tons of ce equivalent. sfco are in kilo tons term. sofc are emissions from mainly of coal use as energy source. lfco are in kilo tons term. lfco are emissions from mainly of petroleum derived fuels as energy source. gfco are in kilo tons term. gfco are emissions from mainly of natural gas use as energy source. ex is in current us dollars term. ex is the total external debt which includes long-term debt and short-term debt. economic development (gd) which is gross domestic per capita are in terms of constant 2010 us$. gd2 is the square of gd. energy consumption (ecm) is in terms of kg of oil equivalent per capita. data used in this study are retrieved from world bank website. data used in this study range between 1971 and 2012 since the data in world bank website is limited till 2016 for used variables in this study. range is determined till 2012 for the analyzed variables to provide the stability for established models. 3.2. methodology ( ) ( ) ( ) ( ) ( ) 2 0 1 2 3t t t t 4 tt ln ce = r +r ln gd + r ln gd + r ln ecm + r ln ex + e (1) ( ) ( ) ( ) ( ) ( ) 2 0 5 6 7t t t t 8 tt ln mn = r +r ln gd + r ln gd + r ln ecm + r ln ex + e (2) ( ) ( ) ( ) ( ) ( ) 2 0 9 10 11t t t t 12 tt ln gfco = r +r ln gd + r ln gd + r ln ecm + r ln ex + e (3) ( ) ( ) ( ) ( ) ( ) 2 0 13 14 15t t t t 16 tt ln lfco = r +r ln gd + r ln gd + r ln ecm + r ln ex + e (4) ( ) ( ) ( ) ( ) ( ) 2 0 13 14 15t t t t 16 tt ln sfco = r +r ln gd + r ln gd + r ln ecm + r ln ex + e (5) relationship between gd, square of gd, ecm and ex, with ce, mn, gfco, lfco and sfco are modelled above in equation 1-5. for the equation 6 below, v0, v1, v2, v3, v4 are coefficients for the examined variables which are gd, square of gd, em and ex and bt is for error term. em is for emissions which are ce, mn, gfco, lfco and sfco. ( ) ( ) ( ) ( ) ( ) 2 0 1 2 3t t t t 4 tt ln em = v +v ln gd + v ln gd +v ln ecm +v ln ex + b (6) bese, et al.: is india financing its emissions through external debt? international journal of energy economics and policy | vol 11 • issue 6 • 2021174 the ardl model which is used as to investigate the relationship between the variables is mentioned as below in equation 7. in the model below, m coefficients are long run coefficients. n coefficients are short run coefficients. bt is for white noise residuals. ( ) ( ) 0 1 1 2 1 2 3 4 1 5 11 2 1 1 2 1 3 1 1 0 0 4 1 5 1 0 0 ln ln b t t t t tt s h c i i i i i i i i i pm i i i i t i i lnem m m lnem m lngd m gd m lnecm m lnex n lnem n lngd n gd n lnecm n lnex − − − −− − − − = = = − − = = ∆ = + + + + + + + + + + + ∑ ∑ ∑ ∑ ∑ (7) hypothesis of no cointegration is h0 = m1 = m2 = m3 = m4 = m5 = 0 hypothesis of cointegration is h1 = m1 ≠ m2 ≠ m3 ≠ m4 ≠ m5 ≠ 0 when cointegration is confirmed, short-run coefficients, long-run coefficients, and error correction model of the ardl model are as below in equation 8, equation 9 and equation 10. ( ) 0 1 1 2 1 1 0 2 3 4 11 0 0 5 1 0 ln b s h t i t i t i i c m i i tt i i p i t t i lnem c c lnem c lngd c gd c lnecm c lnex − − = = −− = = − = ++ + + + + = ∑ ∑ ∑ ∑ ∑ (8) ( ) 0 1 2 1 0 2 3 4 0 0 5 1 0 ln b s h t i t i i t i i i c m i i t it i i i p i t i t t i lnem d d lnem d lngd d gd d lnecm d lnex ectγ − − = = −− = = − − = ∆ + ∆ + ∆ ∆ ∆ = + + + + + ∑ ∑ ∑ ∑ ∑ (9) ( ) 1 2 1 0 2 3 4 5 0 0 0 ln s h t t i t i i t i i i pc m i i t i i t it i i i i ect lnem y lnem y lngd d gd d lnecm d lnex − − = = − −− = = = ∆ − ∆ − ∆ − − − ∆ = ∆ ∑ ∑ ∑ ∑ ∑ (10) equation 8 is to determine the long-run coefficients of ardl model and equation 9 is to determine the short-run coefficients of ardl model. error correction model is specified in equation 10. zivot and andrews (1992) unit root test is used to investigate the unit root of the variables in this study. the break dates for the variables are 1997 for ce, 1985 for gd, 1985 for square of gd, 2004 for ecm, 1990 for mthn, 1982 for gfco, 2001 for lfco and 1992 for sofc. all the variables used in this study are stable at i(1) level. ramsey reset test (rrat), heteroskedasticity test: breuschpagan-godfrey (bpgodt), heteroskedasticity test: arch (htaht), heteroskedasticity test: white (htwt), breuschgodfrey serial correlation lm test (bdgodlmt), normality test (nmtt), cusum test (ctu) and cusum square test (ctusq) are used in this study to investigate the stability of each model. 1997 is used as a break for ce-ex relationship. 1990 is used as a break for mn-ex relationship. 1991 is used as a break for gfco-ex relationship and sfco-ex relationship. 1991 is used as a break date for lfco-ex relationship. after carrying out stability tests for each model, bounds test of the ardl model is applied to decide whether cointegration between the variables exist or not. after cointegration is confirmed, cointegration and long run form is run to investigate the long-run relationships between the variables. eviews is used for all the calculations in this study. 4. results and discussion analysis of the relationship between ce-ex, mn-ex, gfco-ex, lfco-ex and sfco-ex in each sub-chapter. ardl model is used for each relationship and the effect of ex on emissions is analyzed for the period 1971-2012 in india. 4.1. analysis of ce-ex relationship bounds test results show that f-statistics value is 6.69 and it is above i1 value of 1% which is 5.06. long-run relationship between the analyzed variables is confirmed. for further analysis, ardl-ecm model is applied to calculate short-run and long-run coefficients for each variable. 1997 is used as structural break in the analysis. further analysis show that inverted u relationship is not confirmed between ce and gd, and ex has positive and significant effect on ce (table 3). the long-run relationship between the variables is confirmed with negative coefficient of cointegration equation with significance of 1%. rrat, bpgodt, htaht, htwt, bdgodlmt and nmtt shows that the model satisfies the criteria for stability (table 2). further stability tests are carried out by ctu and ctusq tests and the model satisfies the criteria for stability for these tests as well (figures 4 and 5). this analysis confirms the main aim of the study that ex has positive and significant effect on ce. 4.2. analysis of mn-ex relationship bounds test results show that f-statistics value is 13.17 and it is above i1 value of 1% which is 5.06. long-run relationship between the analyzed variables is confirmed. for further analysis, ardl-ecm model is applied to calculate short-run and long-run coefficients for each variable. 1990 is used as structural break in the analysis. further analysis show that inverted u relationship is confirmed between mn and gd, and ex has positive and significant effect on mn (table 5). the long-run relationship between the variables is confirmed with negative coefficient of bese, et al.: is india financing its emissions through external debt? international journal of energy economics and policy | vol 11 • issue 6 • 2021 175 figure 6: ctu test results for ardl model of mn-ex relationship figure 5: ctusq test results for ardl model of ce-ex relationship table 2: stability test results for ardl model of ce-ex relationship test f-statistic jarque-bera prob rrat 0.057861 0.8130 bpgodt 0.777274 0.7077 htaht 0.266431 0.8971 htwt 0.752802 0.7305 bdgodlmt 1.469063 0.2677 nmtt 0.897383 0.6384 table 3: ardl-ecm test results for ce-ex relationship variable coefficient std. error t-statistic prob. short-run coefficients d(ce(−1)) −0.433507 0.179387 −2.416608 0.0272 d(ce(−2)) −0.452926 0.142230 −3.184459 0.0054 d(ce(−3)) −0.333486 0.118207 −2.821203 0.0118 d(gd) 8.254545 2.218748 3.720361 0.0017 d(gd(−1)) 7.619568 2.857079 2.666909 0.0163 d(gd2) −0.638575 0.177909 −3.589344 0.0023 d(gd2(−1)) −0.647722 0.230572 −2.809192 0.0121 d(ecm) 1.472394 0.280417 5.250725 0.0001 d(ecm(−1)) 0.953091 0.428490 2.224300 0.0400 d(ecm(−2)) 1.142190 0.332804 3.432015 0.0032 d(ex) 0.063998 0.039061 1.638409 0.1197 d(ex(−1)) −0.071699 0.071397 −1.004225 0.3294 d(ex(−2)) 0.025794 0.080463 0.320565 0.7524 d(ex(−3)) −0.176854 0.061796 −2.861898 0.0108 d(d1997) 0.026637 0.022372 1.190616 0.2502 cointeq(−1) −0.600626 0.150815 −3.982542 0.0010 long-run coefficients gd 2.468839 2.642847 0.934159 0.3633 gd2 −0.094888 0.220521 −0.430289 0.6724 ecm −1.242166 1.120652 −1.108432 0.2831 ex 0.451679 0.134558 3.356761 0.0037 d1997 0.044348 0.035762 1.240096 0.2318 c −2.349624 10.726289 −0.219053 0.8292 figure 4: ctu test results for ardl model of ce-ex relationship cointegration equation with significance of 1%. rrat, bpgodt, htaht, htwt, bdgodlmt and nmtt shows that the model satisfies the criteria for stability (table 4). further stability tests are carried out by ctu and ctusq tests and the model satisfies the criteria for stability for these tests as well (figures 6 and 7). the analysis shows that there is inverted u relationship between mn and economic growth for india for the period 1971-2012. this analysis confirms the main aim of the study that ex has positive and significant effect on mn. 4.3. analysis of gfco-ex relationship bounds test results show that f-statistics value is 13.48 and it is above i1 value of 1% which is 5.06. long-run relationship table 4: stability test results for ardl model of mn-ex relationship test f-statistic jarque-bera prob. rrat 0.346012 0.5621 bpgodt 0.956173 0.5202 htaht 0.595183 0.5571 htwt 0.939207 0.5349 bdgodlmt 0.788675 0.4669 nmtt 2.706450 0.2584 between the analyzed variables is confirmed. for further analysis, ardl-ecm model is applied to calculate short-run and long-run coefficients for each variable. 1991 is used as structural break in the analysis (table 6). further analysis show that inverted u relationship is confirmed between gfco and gp, and ex has bese, et al.: is india financing its emissions through external debt? international journal of energy economics and policy | vol 11 • issue 6 • 2021176 figure 8: ctu test results for ardl model of gfco-ex relationship figure 7: ctusq test results for ardl model of mn-ex relationship figure 9: ctusq test results for ardl model of gfco-ex relationship table 5: ardl-ecm test results for mn-ex relationship variable coefficient std. error t-statistic prob. short-run coefficients d(mn(−1)) −0.192606 0.094999 −2.027446 0.0539 d(gd) 0.510976 0.717617 0.712045 0.4833 d(gd(−1)) 0.538228 0.773099 0.696195 0.4930 d(gd(−2)) −1.692379 0.693996 −2.438599 0.0225 d(gd2) −0.027690 0.057137 −0.484626 0.6323 d(gd2(−1)) −0.043899 0.062236 −0.705359 0.4874 d(gd2(−2)) 0.129929 0.055772 2.329635 0.0286 d(ecm) 0.221518 0.079634 2.781709 0.0104 d(ex) 0.015420 0.017009 0.906573 0.3736 d(d1990) −0.055863 0.004976 −11.227411 0.0000 cointeq(−1) −0.847836 0.121827 −6.959325 0.0000 long−run coefficients gd 3.146752 0.261553 12.031014 0.0000 gd2 −0.235291 0.021665 −10.860388 0.0000 ecm 0.261275 0.094311 2.770358 0.0106 ex 0.063899 0.010036 6.366885 0.0000 d1990 −0.065889 0.009644 −6.831824 0.0000 c −0.408473 1.028746 −0.397059 0.6948 positive and significant effect on gfco (table 7). the long-run relationship between the variables is confirmed with negative coefficient of cointegration equation with significance of 1%. rrat, bpgodt, htaht, htwt, bdgodlmt and nmtt shows that the model satisfies the criteria for stability (table 5). further stability tests are carried out by cmm and cmmsq tests and the model satisfies the criteria for stability for these tests as well (figures 8 and 9). the analysis shows that there is inverted u relationship between gfco and economic growth for india for the period 1971-2012. this analysis confirms the main aim of the study that ex has positive and significant effect on gfco. 4.4. analysis of lfco-ex relationship bounds test results show that f-statistics value is 10.84 and it is above i1 value of 1% which is 5.06. long-run relationship between the analyzed variables is confirmed. for further analysis, ardl-ecm model is applied to calculate short-run and long-run coefficients for each variable. 2001 is used as structural break in the analysis. further analysis show that inverted u relationship is not confirmed between lfco and gp, and ex has positive and insignificant effect on lfco (table 9). the long-run relationship between the variables is confirmed with negative coefficient of cointegration equation with significance of 5%. rrat, bpgodt, htaht, htwt, bdgodlmt and nmtt shows that the model satisfies the criteria for stability (table 8). further stability tests are carried out by ctu and ctusq tests and the model satisfies the criteria for stability for these tests as well (figures 10 and 11). 4.5. analysis of sfco-ex relationship bounds test results show that f-statistics value is 4.46 and it is above i1 value of 5% which is 4.01. long-run relationship table 6: stability test results for ardl model of gfcoex relationship test f-statistic jarque-bera prob. rrat 0.273494 0.6050 bpgodt 1.017255 0.4488 htaht 1.003738 0.3768 htwt 0.968455 0.4846 bdgodlmt 0.796760 0.4607 nmtt 0.469341 0.7908 bese, et al.: is india financing its emissions through external debt? international journal of energy economics and policy | vol 11 • issue 6 • 2021 177 table 7: ardl-ecm test results for gfco-ex relationship variable coefficient std. error t-statistic prob. short-run coefficients d(gfco(−1)) 0.488247 0.105460 4.629695 0.0001 d(gd) 18.074163 8.526407 2.119786 0.0424 d(gd2) −1.475396 0.680229 −2.168971 0.0381 d(ecm) 5.163414 0.973284 5.305145 0.0000 d(ex) 0.229352 0.096956 2.365528 0.0247 d(d1991) −0.072736 0.060475 −1.202733 0.2385 cointeq(−1) −0.867392 0.095171 −9.114030 0.0000 long-run coefficients gd 41.141068 2.550409 16.131166 0.0000 gd2 −3.189567 0.204377 −15.606289 0.0000 ecm 5.952802 1.012707 5.878110 0.0000 ex 0.264416 0.106311 2.487181 0.0187 d1991 −0.083856 0.071675 −1.169948 0.2512 c −164.165369 9.989036 −16.434555 0.0000 table 8: stability test results for ardl model of lfcoex relationship test f-statistic jarque-bera prob. rrat 2.410850 0.1362 bpgodt 1.092169 0.4180 htaht 1.870781 0.1801 htwt 1.084328 0.4240 bdgodlmt 0.671995 0.4220 nmtt 1.199199 0.5490 table 9: ardl-ecm test results for lfco-ex relationship variable coefficient std. error t-statistic prob. short-run coefficients d(gd) 12.543669 4.404050 2.848212 0.0096 d(gd(−1)) 18.731811 4.818237 3.887690 0.0008 d(gd2) −0.993277 0.353822 −2.807279 0.0106 d(gd2(−1)) −1.560840 0.388453 −4.018089 0.0006 d(ecm) −0.265872 0.828896 −0.320754 0.7516 d(ecm(−1)) 1.236287 0.606389 2.038768 0.0543 d(ecm(−2)) 1.147087 0.592453 1.936165 0.0664 d(ecm(−3)) −1.762657 0.617923 −2.852553 0.0095 d(ex) 0.100969 0.087785 1.150184 0.2630 d(ex(−1)) −0.205482 0.128926 −1.593791 0.1259 d(d2001) −0.199082 0.041550 −4.791439 0.0001 cointeq(−1) −0.300436 0.131110 −2.291477 0.0324 long-run coefficients gd −1.685412 11.253471 −0.149768 0.8824 gd2 0.562308 1.083166 0.519134 0.6091 ecm −7.538468 6.546226 −1.151575 0.2624 ex 0.667089 0.505226 1.320377 0.2009 d2001 −0.662643 0.362383 −1.828571 0.0817 c 27.989636 51.982378 0.538445 0.5959 figure 10: ctu test results for ardl model of lfco-ex relationship figure 11: ctusq test results for ardl model of lfco-ex relationship between the analyzed variables is confirmed. for further analysis, ardl-ecm model is applied to calculate short-run and long-run coefficients for each variable. 1991 is used as structural break in the analysis. further analysis show that inverted u relationship is not confirmed between sfco and gd, and ex has positive and table 10: stability test results for ardl model of n2etln relationship test f-statistic jarque-bera prob. rrat 0.675745 0.4207 bpgodt 0.940736 0.5426 htaht 0.515670 0.4775 htwt 0.957380 0.5280 bdgodlmt 3.605245 0.0721 nmtt 0.760169 0.6838 bese, et al.: is india financing its emissions through external debt? international journal of energy economics and policy | vol 11 • issue 6 • 2021178 table 11: ardl-ecm test results for n2-etln relationship variable coefficient std. error t-statistic prob. short-run coefficients d(gd) 3.283821 2.747638 1.195143 0.2454 d(gd(−1)) 2.564799 3.425273 0.748787 0.4623 d(gd(-2)) −7.836568 3.080892 −2.543603 0.0189 d(gd2) −0.242091 0.218190 −1.109543 0.2797 d(gd2(−1)) −0.227386 0.275263 −0.826071 0.4181 d(gd2(−2)) 0.641744 0.244523 2.624474 0.0158 d(ecm) 0.931616 0.333519 2.793292 0.0109 d(ecm(−1)) 0.141965 0.382550 0.371101 0.7143 d(ecm(−2)) 0.065501 0.370397 0.176840 0.8613 d(ecm(−3)) −0.802893 0.396938 −2.022715 0.0560 d(ex) 0.149908 0.032383 4.629278 0.0001 d(d1991) 0.030137 0.020592 1.463546 0.1581 cointeq(−1) −0.618359 0.162180 −3.812789 0.0010 long-run coefficients gd 2.922026 1.952837 1.496298 0.1495 gd2 −0.210805 0.145462 −1.449213 0.1620 ecm 1.237978 0.456519 2.711775 0.0131 ex 0.242429 0.055891 4.337518 0.0003 d1991 0.048737 0.029651 1.643700 0.1151 c −10.392346 5.953342 −1.745632 0.0955 figure 12: ctu test results for ardl model of meth-etln relationship figure 13: ctusq test results for ardl model of meth-etln relationship significant effect on sfco (table 11). the long-run relationship between the variables is confirmed with negative coefficient of cointegration equation with significance of 1%. rrat, bpgodt, htaht, htwt, bdgodlmt and nmtt shows that the model satisfies the criteria for stability (table 10). further stability tests are carried out by ctu and ctusq tests and the model satisfies the criteria for stability for these tests as well (figures 12 and 13). this analysis confirms the main aim of the study that ex has positive and significant effect on sfco. 5. conclusion main findings of this study are as below. 1. no inverted u relationship between ce and gd (hypothesis 2) 2. ex has significant and positive effect on ce (hypothesis 1) 3. inverted u relationship between mn and gd (hypothesis 4) 4. ex has significant and positive effect on mn (hypothesis 3) 5. inverted u relationship between gfco and gd (hypothesis 10) 6. ex has significant and positive effect on gfco (hypothesis 9) 7. no inverted u relationship between lfco and gd (hypothesis 8) 8. ex has insignificant and positive effect on lfco (hypothesis 7) 9. no inverted u relationship between sfco and gd (hypothesis 6) 10. ex has significant and positive effect on sfco (hypothesis 5). time period of this study for india is from 1971 to 2012. period is chosen according to the availability of data on energy consumption side. india’s external debt continued to rise after 2012 till today. the results of this study confirmed hypothesis 1, 3, 4, 5, 9 and 10. the results of this study did not confirm hypothesis 2, 6, 7 and 8. mn kuznets curve and gfco kuznets curve are confirmed by this study. the main aim of this study is to prove the effect of ex on emissions. according to study results, ex has significant and positive effect on sfco, gfco, mn and ce. the results of this study confirm that india finances its emissions through external debt. as stated above, although the study period covers from 1971 to 2012, india’s external debt continued to increase after 2012. it is highly likely india continued to finance its emissions through external debt after 2012 till today. since sustainability is the main issue in current world and reduction of emissions is one of the highest priorities of humanity, necessary measures should be taken into account to reduce financing of emissions through external debt in india. although this study did not confirm inverted u relationship between sfco and gd, we recommend further studies to investigate coal kuznets curve for india which is another gap in the literature and coal is one of the major contributors to greenhouse gas emissions. beşe et al., (2020), magazzino et al., (2020) and qiao et al., (2019) are the most recent studies in the literature that confirmed coal kuznets curve. the time period analyzed and the country of the study which is india are the limits of this study. this study recommends further policies to be taken to control the use of external debt for creating environmental pollution in india. for future research direction, bese, et al.: is india financing its emissions through external debt? international journal of energy economics and policy | vol 11 • issue 6 • 2021 179 further studies need to be carried out to analyze the effect of external debt on emissions for developing countries. references alam, r., adil, m.h. (2019), validating the environmental kuznets curve in india: ardl bounds testing framework. opec energy review, 43(3), 277-300. beşe, e., friday, h.s., özden, c. (2020), coal consumption environmental kuznets curve (ekc) in china and australia: evidence from ardl model. journal of applied business and economics, 22(11), 25-36. beşe, e., friday, h.s., ozden, c. (2021), the effect of external debt on emissions: evidence from china. international journal of energy economics and policy, 11(1), 440-447. beşe, e., friday, h.s., spencer, m. (2021), analysıs of the relatıonshıp between ıncome growth and, coal consumptıon and emıssıons from nonlınear perspectıve. journal of academy of busıness and economıcs, 21(1), 52-72. chisti, k.a., shabir, t. (2019), impact of external debt on various macro economic variables: indian evidence. journal of economics, management and trade, 25(4), 1-16. irfan, m., rao, m.w., akbar, j., younis, i. (2020), impact of external debt on stock market performance and economic growth: moderating role of capital formation. journal of finance and accounting research, 2(1), 1-27. joy, j., panda, p.k. (2019), pattern of external debt and its ımpact on macroeconomic variables in india. international journal of economic research, 16(1), 261-272. katircioglu, s., celebi, a. (2018), testing the role of external debt in environmental degradation: empirical evidence from turkey. environmental science and pollution research, 25, 8843-8852. khan, a., chenggang, y., xue yi, w., hussain, j., sicen, l., bano, s. (2020), examining the pollution haven, and environmental kuznets hypothesis for ecological footprints: an econometric analysis of china, india, and pakistan. journal of the asia pacific economy, 26, 462-482. magazzino, c., bekun, f.v., etokakpan, m.u., uzuner, g. (2020), modeling the dynamic nexus among coal consumption, pollutant emissions and real income: empirical evidence from south africa. environmental science and pollution research, 27(8), 8772-8782. murthy, k.v.b. and gambhir, s. (2018), analyzing environmental kuznets curve and pollution haven hypothesis in ındia in the context of domestic and global policy change. australasian accounting, business and finance journal, 12(2), 134-156. nath, s. (2020), an analysis of the relationship among economic growth, external debt and exports in india (1970-2018). economy, 7(1), 59-68. pahwa, n. (2018), impact of debt on short-run and long-run growth: empirical evidence from i̇ndia. in: current issues in economics and finance. germany: springer. p3-18. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. purcel, a.a. (2020), new insights into the environmental kuznets curve hypothesis in developing and transition economies: a literature survey. environmental economics and policy studies, 22(4), 585-631. qiao, h., chen, s., dong, x., dong, k. (2019), has china’s coal consumption actually reached its peak? national and regional analysis considering cross-sectional dependence and heterogeneity. energy economics, 84, 104509. saxena, s.p., shanker, i. (2017), external debt and economic growth in india. social science asia, 4(1), 15-25. shahbaz, m., sinha, a. (2019), environmental kuznets curve for co2 emissions: a literature survey. journal of economic studies, 46(1), 106-168. sinha, a., bhatt, m. (2017), environmental kuznets curve for co2 and nox emissions: a case study of india. european journal of sustainable development, 6(1), 267-276. sultan, z.a., alkhateeb, t.t.y., adow, a.h. (2021), verifying the environmental kuznets curve hypothesis in the case of india. international journal of energy economics and policy, 11(2), 127-132. zivot, e., andrews, d.w.k. (1992), further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. journal of business and economic statistics, 10(3), 25-44. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 4 • 2022 249 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(4), 249-262. toward to “green deal” legal and natural aspects of the development of small hydropower plants the example of poland michał marszelewski1*, adam piasecki2 1faculty of law and administration, nicolaus copernicus university in toruń, poland, 2faculty of earth sciences and spatial management, nicolaus copernicus university in toruń, poland. *email: marszelewski@umk.pl received: 14 march 2022 accepted: 20 june 2022 doi: https://doi.org/10.32479/ijeep.13078 abstract the article contains a legal-environmental analysis covering the development and operational aspects of small hydropower plants (shps) in poland. from legal perspective, the paper presents conditions that have to be met during the investment process. it was shown that such a process is highly formalized. the need to protect the water and the environment results in necessity to obtain various administration decisions like water permits or decision on environmental conditions. second discussed law-related field is the support system. in poland there are three categories of shps support system: green certificates, auction system and feed-in tariff (fit) or feed-in premium (fip) system. the last one is the most optimal for shps and significantly helps to make them profitable. moving on to an environmental perspective, polish topography is relatively unfavorable for shps because of water resources and significant part of flat lowlands. taking into account that shp may have a visible impact on ecosystems and – in most cases – are localized and managed by private entities, it is crucial to use the shps potential in poland as effective as possible. conducted analysis also shown the legal regulation should be changed to more friendly for shps operators. keywords: small hydropower plant, shp, polish law, feed-in tariff, feed-in premium, ecology, environment, european climate law jel classifications: q25, o10, k32, k39 1. introduction hydropower plants are among the most commonly used types of renewable energy sources, providing around 20% of the world’s total electricity. in terms of capacity, power plants are categorised as small or large. hydro-electric power production usually exploits the energy of falling water or river velocity (king, 2018; sensibe et al., 2018; wieteska et al., 2018). a small hydropower plant (shp) has been described as a “welldeveloped small-scale renewable energy technology that can provide safe and clean electricity to rural and urban areas” (warren, 2017). there is no globally or internationally agreed definition of an shp (warren, 2017; lowenstein and panarella, 2018; mesquita 2019). moreover, there are differences in the classifications adopted in different countries of europe (mesquita 2019). eu member states recognise installations with a maximum capacity of 10 mw as shps, while greece even counts 15 mw units as such. by contrast, in sweden and germany, an shp is considered to be an installation with a capacity of less than or equal to 3 mw (mesquita 2019). in poland, there is no legal definition of maximum shp capacity. however, there is a definition of a small “renewable energy source” (res) installation that covers all installations of up to 0.5 mw. in this context, 5 mw is widely accepted in poland as the maximum for an shp (malicka, 2018; świątek 2016, pga 2021). in the usa, definitions vary from state to state (king, 2018), despite the term “small hydroelectric power project” having been statutorily defined by the us congress. it is set as an installation with a capacity of 10 mw or less that generates electricity through using an existing dam or a natural water feature such as a natural lake, waterfall or the gradient of a natural stream, without utilizing a dam, a man-made impoundment or any retention of water for storage-and-release operation (lowenstein and this journal is licensed under a creative commons attribution 4.0 international license marszelewski and piasecki: toward to “green deal” legal and natural aspects of the development of small hydropower plants the example of poland international journal of energy economics and policy | vol 12 • issue 4 • 2022250 panarella, 2018; u.s. code of federal regulations, 2016). it should be noted that some countries have set the maximum shp capacity much higher; e.g. in india it is 15 mw (kucukali and baris 2009), in china it is 25 mw, and in turkey it is as much as 50 mw (capi et al., 2012). the lack of compliance on the maximum power of an shp meant that the european small hydropower association, the european commission and international union of producers and distributors of electricity adopted 10 mw as the upper limit of an shp power back in 2009 (kucukali and baris 2009). this study assumes 5 mw as the upper limit of shp capacity. this is because of the support system for electricity production in place in poland, as well as the use of this threshold for statistical works in this area. according to the data of energy regulatory authority, as of december 31, 2020 in poland there were 767 shps with a power less than or equal to 5 mw (including 2 pico hydro with power under 5 kw), and these constituted as much as 98% of the country’s total number of all run-of-river hydropower plants (energy regulatory authority 2021). the total installed capacity in shps was 255.5 mw, which is 26.2% of poland’s total hydropower plant capacity. of total energy production in poland, hydropower plants account for only about 2%. some researchers point to the negligible importance of shp in the polish energy system, alongside the unfavourable balance of environmental costs and material benefits associated with their operation (radtke et al., 2012). in 2015, the european union launched an energy strategy setting out principles and goals to increase energy efficiency, to support greener energy sources and to better link national energy markets. within its framework, the member states undertook, for example, to increase the share of renewables by at least 32% by 2030 (european council 2021). due to the climate crisis and severe environmental degradation processes, in december 2019 the european commission published communication the european green deal (european commission 2012) this is a development strategy to transform the european union into a climate-neutral, fair and prosperous society with a resource-efficient and competitive economy (wojtkowskałodej, 2021). it stimulates, among other things, the decarbonising of the eu’s energy system. such a decarbonisation is necessary because more than 75% of greenhouse gas emissions in the european union come from the use and production of energy (european commission, 2012). in december 2020, european union leaders approved the target of reducing greenhouse gas emissions by at least 55% by 2030 compared to 1990 (european council, 2020). it is indicated that the consequence of climate goals thus formulated will include the need for a review of energy policy legislation and targets (european council, 2021). as part of the european green deal, a european climate law was adopted setting in art. 2 legally binding target of net zero greenhouse gas emission by 2050 (european commission, 2021; european parliament, 2021). the need for european union countries to achieve climate neutrality by 2050 requires a far-reaching transformation of the current energy system into a more efficient integrated energy system in which renewable energy will play an important role (european council, 2021; european commission, 2019). for the reasons given above, a general assessment of shp issues from the perspective of the european climate law (european parliament, 2021) is justified. thus, the installations in question are in accordance with art. 1 of this act, which concerns the gradual reduction of anthropogenic greenhouse gas emissions. moreover, shps are one of the elements conducive to achieving the objective of the european climate law, which is climate neutrality (art. 2). however, when analysing shp issues in the light of the themes contained in the european climate law (whose nature help draw out a concise justification of the basic provisions of the normative part of the law), it can be concluded that shp is especially realised by: • theme 5: by increasing retention and preventing flooding, • theme 9: by protecting ecosystem integrity and biodiversity against the threat of climate change, • theme 10: by the energy sector (as a sector of the economy) contributing to achieving climate neutrality, • theme 11: by switching to energy systems based on renewables, • theme 32: by protecting local catchments against extreme climate change effects, as well as preventing damage to ecosystems caused by climate change (droughts, water scarcity, forest fires), • theme 38: by stimulating public involvement at all levels to accept and actively participate in climate change efforts. one element in this regard is shp (european parliament, 2021). this article aims to analyse the operation of shps in poland in terms of their potential role in the coming energy transformation that is hailed by the european union’s adoption of the european green deal strategy. the research objective required that the main conditions for the operation of shp in poland be considered, especially environmental and legal ones. the literature analysis indicated the existence of a clear gap in the theoretical knowledge relating to this area. 2. materials and methods the shp issues addressed herein were considered in the context of natural and legal conditions. this allowed for a multi-faceted approach to the research problem, and the need for interdisciplinary research. the study was based on the descriptive method and a formal-dogmatic method typical of legal research that consists in examining legal provi-sions. the legal analysis also includes comments of legal comparison. the legal analysis cited legal acts that are significant to the discussed issues. views expressed in the scien-tific literature are also presented, and existing and planned legislative solutions are as-sessed. press interviews given by people linked to poland’s shp industry played a major role. the considerations are supplemented with statistical data on the operation of shps in poland taken mainly from the energy regulatory authority – a central polish state administrative body. 3. results 3.1. natural and cultural conditions for locating shps poland has relatively small water resources. this is mainly due to is low sums of precipitation, averaging 600 mm per year nationwide. as a result, in many years, average total surface water resources amount marszelewski and piasecki: toward to “green deal” legal and natural aspects of the development of small hydropower plants the example of poland international journal of energy economics and policy | vol 12 • issue 4 • 2022 251 to 61.6 km3. due to the terrain, the main direction of water outflow is northwards. as a result, over 95% of water resources flow directly into the baltic sea (gutry-korycka, 2014). it is worth noting that water resources vary greatly across the country. runoff coefficients range from 4 dm3/s/km2 (the greater poland kuyavia lakeland) to over 50 dm3/s/km2 (mountain areas). the average for the entire country is about 5.5 dm3/s/km2 (jokiel, 2004). values exceed 8 dm3/s/ km2 only in the upland area of the pomeranian lake district, in the north of the masurian lake district (in the north of the country), and in foothill and mountain areas (in the south of the country). poland’s river network was shaped mainly in the quaternary. it is densest in areas where precipitation significantly exceeds evaporation. such areas exist in the north of the country (the pomeranian and masurian lakelands) and in the south (mountain and foothill areas). to be effective, hydropower requires appropriate natural conditions. the key requirements are adequate water resources and topography. as already mentioned, poland essentially has few water resources, which can be considered suitable for shps in only in a few regions. the topography is similarly unfavourable. most of the country is relatively flat lowlands. these two factors put great limitation on where hydropower can be developed in poland. most of poland’s shps are found in the north. here, the natural conditions (topography, geological structure and precipitation) are the most favourable for locating shps. southern poland also has much hydropower potential due to its steep terrain differentials in the mountain and foothill areas of the carpathians and sudetes. the concentration of shps in voivodeships is shown in figure 1. even in the middle ages, hydropower was already being used to power water mills in what is today poland. about 3,000 such facilities are estimated to have been in operation in the 16th century. with the spread and advancement of technology, the use of hydropower has evolved over the centuries. however, at the beginning of the 20th century, there were about 6,500 plants powered by water engines in poland (bajkowski and górnikowska, 2013). after the second world war, a socialist system was put in place in poland that supported only large industrial facilities, including power plants. as a result, the vast majority of shps were then shut down and demolished. only since the 1990s, with the end of the communist era, has there been a slow but systematic reconstruction of shps in poland. most of the shps currently operating are located on the site of a former water mill. 3.2. legal conditions for investments in shp locating shp facilities requires numerous administrative decisions to be sought. a list of required permits was made by e. malicka (2018). in polish law, all hydropower plants, regardless of size or energy-generation method, are considered to be projects with a potentially significant environmental impact (§3, sect. 1, pt. 5 of the regulation of the council of ministers of september 10, 2019 on projects that may have a significant environmental impact, journal of laws 2019, item 1839). this requires that administrative proceedings be conducted and a decision on environmental conditions – “dec“ be obtained (art. 71, sect. 2, pt. 2 of the act of 3 october 2008 on the provision of information on the environment and its protection, public participation in environmental protection and on environmental impact assessments, consolidated text journal of laws 2021, item 247 as amended). the dec plays a particularly important role in the investment process. its aim is to indicate directions for implementing shp projects that have minimal negative environmental impact. although it is not a decision that constitutes sufficient grounds for the shp investor to proceed with a project, the dec is required for the issuance of other administrative decisions (e.g. building permit decisions). at the same time, the dec acts as a “preliminary ruling” with regard to future consent for the project to proceed. the conditions specified in the dec may not be modified during subsequent project implementation stages, which results from the analysis of court judgments (filipowicz, 2020). the procedure for issuing a dec may also require that an environmental impact assessment – “eia“ be conducted for the planned shp. a decision on this matter is issued by an administrative body based on specific criteria. these include, but are not limited to: the size of the shp, the use of natural resources (water), emissivity and nuisance to the environment, and location (art. 59, sect. 1, pt. 2 and art. 63 of the act on the act of 3 october 2008 on the provision of information on the environment and its protection, public participation in environmental protection and environmental impact assessments). at a later stage, the shp investor is obliged to prepare and submit another project document: an environmental impact report – “eir”. this report requires that much data on the environment and the planned shp be collected. for this reason, the eir takes a long time to prepare – often more than 12 months (filipowicz, 2020). in some cases, irrespective of the above-mentioned documents, another document may be figure 1: the shp concentration with a power less than or equal to 5 mw in polish voivodeships marszelewski and piasecki: toward to “green deal” legal and natural aspects of the development of small hydropower plants the example of poland international journal of energy economics and policy | vol 12 • issue 4 • 2022252 required – a water law assessment (kuśnierkiewicz, 2018; art. 428 and 437 of the act of july 20, 2017, water law, consolidated text, journal of laws of 2021, item 624, as amended). the legal relationship of the eia to the water law assessment gives priority to the former (rakoczy, 2018). the next stage of shp investment implementation requires that a zoning decision be obtained, unless the location of the planned shp is covered by a local spatial development plan “lsdp”. this plan contains arrangements regarding the intended use of the land and the distribution of public-purpose investments, as well as specifying development methods and construction conditions (art. 4 of the act of 27 march 2003 on spatial planning and development, consolidated text, journal of laws of 2022, item 503). the lsdp is adopted by the commune council, but its adoption is not required each time (plucińska-filipowicz and filipowicz, 2018). hence, when investing in shp, the requirement to obtain a planning permission should also be considered. then, it is necessary to obtain an shp building permit. this permit is an administrative decision that allows construction (or construction works other than the construction of the building itself) to commence and proceed (art. 3, pt. 12 of the act of july 7, 1994, construction law, consolidated text, journal of laws 2021, item 2351 as amended). another group of requirements for the implementation of shp investments relates to obtaining rights to use water and rights to real estate. the waters exploited by the shp, i.e. natural watercourses or canals, are classified as inland flowing waters (art. 22, points 1 and 4 of the water law). they are excluded from civil law transactions (except in special cases) and are the property of the public treasury (art. 211 and 212 of the water law). similarly, the land beneath inland flowing waters is the property of the public treasury and – except in certain cases – is excluded from civil law transactions (art. 216, sect. 1 and 2 of the water law). thus, the private shp investor is not able to acquire ownership of the land and watercourse (or, section thereof) on which the shp will be located. however, land beneath water for owned by the public treasury can be transferred for a fee (art. 261, sect. 1, pt. 1 of the water law). furthermore, it is imperative that approval for the use of water facilities be obtained. pursuant to art. 16, pt. 65 of the water law, these are devices or structures used to shape or exploit water resources. this category includes, among others, damming devices or structures, manmade reservoirs on flowing waters, or hydropower facilities. if the devices required for the shp investment (e.g. weirs) have already been built and are the property of public treasury, they can be rented or leased, among other things (art. 264 of the water law). in other cases, a water permit is required for the construction of water devices. the water permit is an instrument of water resources management (art. 11 and 388 of the water law). it is a form of administrative decision (rakoczy, 2018) in which authorised administrative bodies define the permissibility of individual water uses and the conditions for such use. in addition, the document provides for control to ensure that the way the water is used complies with the conditions of the water permit (sznajder, 2020). water-law permits are regulatory in nature (behnke, 2010), and take priority regarding the use of water (rotko, 2018), including priority (preliminary ruling) with regard to the issuing of other decisions – e.g. a building permit decision. the permit, which covers many different activities related to water use, is not a single decision rakoczy, 2018). the role of water permits extends beyond the shp project implementation itself, and is very significant. pursuant to art. 389, pt. 6, the requirement to obtain them was imposed with particular regard to the following water facilities: hydropower facilities and regulatory damming devices or structures, as well as canals, ditches and man-made reservoirs (located e.g. on rivers). in addition to water devices, water permits are required for: use of water for hydropower, damming, storage or retention of surface waters, and for the exploitation of such waters (art. 35, sect. 3 and 389 of the water law), as well as water regulation and changes to the relief on land adjacent to water (art. 389 of the water law). water-law permits are issued for a specified period not exceeding 30 years (art. 400, sect. 2 of the water law). in addition to water law permits, polish law also distinguishes water law notifications. these relate to activities that interfere less with the environment – e.g. the construction of a platform of specific parameters, of drainage devices for buildings, or of specific ponds. such activities may accompany the location of an shp facility (art. 388 and 394, sect. 1 of the water law). if an shp project requires both a water permit and a water law notification, the application is examined as part of a single procedure, which ends with the issuance of a water permit (art. 394, sect. 4 of the water law). the last group of requirements for implementing shp projects relates to connection to the power grid. this requires that connection conditions be obtained and a contract for connecting to the power grid be concluded. art. 7 of the energy law of april 10, 1997 (consolidated text, journal of laws 2021, item 716, as amended) obliges energy companies to conclude an agreement for connection to the power grid. due to the monopoly that energy companies have on the electricity distribution and transmission market, the legislature made this a public-law obligation (jankowski, 2020). if an shp entity applying for connection meets the conditions provided for in art. 7 of the energy law, the energy company is obligated to conclude a grid connection agreement. moreover, pursuant to art. 7, sec. 8, pt. 3.a of this act, for an shp of installed electrical capacity not exceeding 5 mw, the fee charged for connection to the network is half actual cost. at this point, it should be clarified that the polish legislature also employs the terms “micro-installation” and “small installation”. micro-installations include shps with a total installed electrical capacity not exceeding 50 kw connected to a power grid with a rated voltage below 110 kv. meanwhile, a small installation is an shp with total installed electrical capacity exceeding 50 kw and not more than 1 mw connected to a power grid with a rated voltage below 110 kv (art. 2, points 18 and 19 of the act of 20 february 2005 on renewable energy sources, consolidated text journal of laws 2021, item 610 as amended). an shp classified marszelewski and piasecki: toward to “green deal” legal and natural aspects of the development of small hydropower plants the example of poland international journal of energy economics and policy | vol 12 • issue 4 • 2022 253 as a micro-installation can be connected to the grid based only on an application submitted to an energy company (art. 7, sect. 8d4 of the energy law). moreover, pursuant to art. 7, sect. 8, pt. 3.b of the energy law, for micro-installations no fee is charged for connection to the electricity distribution network. finally, it should be noted that no license is required to conduct economic activity using an shp classified as a microor small installation (art. 32., sect. 1, pt. 1.c of the energy law). on the other hand, energy generation using an shp of capacity exceeding 1 mw, and thus above the limit for a small installation, requires a license. the obtaining of a license is a condition for commencing operations and results in the licensee being subject to supervision by the president of the energy regulatory office (będkowskikozioł, 2020). a simplified representation of the above-described legal conditions for investment in shp is given in figure 2. measures facilitating connection to the grid and the absence of a distribution-grid connection fee for micro-installations are intended to encourage the start-up and functioning of such installations. this is a good solution to help households and small enterprises to use hydropower for the sake of the environment. running an shp electricity-generation business (i.e. a small installation) is a regulated activity and requires an entry in the register of small-installation energy producers (art. 7 of the act on renewable energy sources). conversely, shp energy generation by a natural person not recognised as an entrepreneur and the sale of such energy are not considered an economic activity. shp start-up costs vary greatly. this is due to the multiplicity of local, national, environmental (e.g. reservoir size, ecological condition, size of water flow) and infrastructure conditions. these include especially: land rights, fees for essential permits, fees for preparing relevant documents, real-estate costs, hydraulic engineering works, technical infrastructure and employee remuneration. in poland, these usually total from around 100,000 to several million euros. only pico hydro has lower costs. in each case, input rates translate into output rates (revenue), as greater financial investments allow for greater energy production. however, this energy generally sells at below market price and therefore requires state support. the support system is mentioned in section 3.5. 3.3. environmental aspects of shp operation the construction of hydropower facilities on rivers always has an impact on the aquatic ecosystem. the impact that an shp can have will vary considerably depending on the facility. the individual characteristics of the river, its physical and ecological state, including species and types of habitats that will lie within the power plant’s range of influence, will also be important. these factors require that the impact of each power plant should be analysed individually. an shp has an impact on the natural ecosystem at every stage of the hydropower plant’s lifetime. the construction, operation and decommissioning of the power plant will differ in the extent of their effects on the environment, and especially on the river ecosystem. despite the individual nature of the shp’s ecosystem impact, there are a few features that are usually observed. one is any change in river bed morphology. these can disturb existing hydrological and hydromorphological processes. downstream of a damming structure, bottom erosion will accelerate. directly related to this, the sediment displacement process will be disturbed, with sediments starting to accumulate above the damming. sedimentation can create various habitats directly and indirectly providing space for numerous species. creating a barrier to the river’s current in the form of a dam or weir disrupts natural sediment dynamics. sediments accumulating in front of the dam may negatively impact plant and animal species, disturbing their existing habitats. another important factor is the variation in velocity rate. too little velocity may result in fish spawning grounds drying out and prevent the growth of young specimens. it may also hamper the upstream migration of fish due to reduced velocity and/or a physical obstacle that the fish will not be able to overcome. reducing the velocity of water in a river may cause it to warm more quickly and reduce its oxygen saturation. the damming of water also significantly shapes hydrogeological conditions. above a dam, the water table will rise. additionally, if there are frequent fluctuations in the level of damming during shp operation, there will also be fluctuations in groundwater. this may result in biocenotic changes. the ill-thought-through location of an shp may also contribute to economic losses. above the dam, floodwater flow conditions will change (przedwojski et. al., 2007) which may result in inundation or flooding. these examples of changes that shp may cause on the natural ecosystem do not constitute an exhaustive list. other consequences are referred to in the literature, such as: ● intensification of the channel overgrowing, increasing channel roughness and water flow resistance, ● changes in the species composition of aquatic vegetation, ● disruption of the natural state–flow relationship (wierzbicki 2008), ● an artificial step increases piezometric pressure and intensifies filtration within the physical structure, figure 2: legal conditions for investment in shp marszelewski and piasecki: toward to “green deal” legal and natural aspects of the development of small hydropower plants the example of poland international journal of energy economics and policy | vol 12 • issue 4 • 2022254 ● erosion may lower the water table below a dam (bojarski et. al., 2005), ● changes and depletion of flora along sections of rivers dammed by an shp (jansson, 2002), ● a decrease in the number of invertebrate taxa (growns and growns, 2001), ● change in birdlife species distribution. it should be noted each of these is conditioned by both anthropogenic factors (choice of shp technology and construction, especially fish ladders; the servicing of the shp; and its method of exploitation) and the specific natural conditions of each aquatic ecosystem. 3.4. legal aspects of shp operation the operation of an shp is based on using water for electricity production. this requires the payment of water services consisting in the returnable abstraction of water. with regard to water services, the above-mentioned water permit is also required (art. 389, pt. 1 of the water law). according to the current polish water policy, fees for water services are an economic instrument of water management (art. 267, pt. 1 of the water law). pursuant to art. 270, sect. 4 of the water law, the fee for the abstraction of water for hydropower plants is charged only for the amount of electricity that the hydropower facility generates using returnable water. this is understood as water that is abstracted, used and then discharged in the same quantity and of undeteriorated quality, as well as water abstracted non-returnably that is not intended for electricity generation. the fees are: eur 0.27 per mwh of electricity generated and eur 0.077 for non-returnable consumption of 1 m3 of process water (art. 274, pt. 3.a of the water law). in this aspect, the polish legislature removed doubts that had arisen regarding the possibility of hydropower plants incurring an additional, “flat” fee. it is independent of the variable fee, which includes the abovementioned fees for the amount of energy produced and process water abstracted (robakowska, 2018). the functioning of an shp – like any other activity – entails the need to pay fees for the rights to the real estate and movables that make up the entirety of the business. among the other costs, it is worth mentioning insurance. in poland, no bespoke insurance products are available for shps. they constitute a particularly advanced form of insurance protection, being those most suited to the risks incurred. on the polish insurance market, it is possible to join a group property insurance programme devised for shp owners (koropis, 2013). additionally, non-obvious costs should be considered such as the management of waste not coming from the shp operator that collect on the grates of the facility having been carried on the watercourse’s current, as results from the applicable legal regulations (wróblewska, 2013). 3.5. the system of support for shps poland’s existing shp support systems are divided into three categories. this division also reflects the evolution of legal solutions adopted to optimise support for electricity production from renewable sources (malicka, 2018). the first category of support, in force since 2005, was based on a system of certificates of origin – “co” of res electricity generation. such a certificate confirms that the energy it covers has been generated from renewable energy sources (art. 44, sect. 1 of the act on renewable energy sources). due to the lack of a statutory definition, a co is defined in legal science as a carrier of specific property rights, and thus having a certain economic value that varies depending on the supply and demand for certificates of origin within a given period. it is defined as a quasi-security (przybojewska, 2020). the property rights pertaining to a co are transferable and constitute a commodity. they are first created when the co is entered on the recording account in the certificate of origin register (art. 63 of the act on renewable energy sources). the number of property rights corresponds to the amount of energy shown in the co, while the nominal value of one property right corresponds to 1 kwh of electricity (district court in warsaw, 2019; trela and dubiel, 2017). the property rights created as a result of co registration are commonly referred to as a tradable green certificate – “tgc”. tgcs are purchased by entities that have been obliged by the legislature to obtain and submit for redemption a certain number of cos from renewable energy sources (including energy companies and industrial customers). failure to meet the requirement to obtain a tgc results in the need to pay a substitution fee (trela and dubiel, 2017; art. 52 and 59 of the act on renewable energy sources). a system constructed in this way, consisting in the imposition of an obligation on relevant entities to purchase and submit for redemption a co, is designed to support shp electricity producers, providing them with a secondary, autonomous income from the sale of certificates of origin. the producer’s primary income is the sale of generated energy (supreme administrative court, 2011). in addition, for an shp of capacity below 500 kw, the legislature guaranteed energy producers 15 years of energy sales by imposing on certain entities the obligation to purchase said energy at the average selling price of electricity on the competitive market in the previous quarter, as announced by the president of energy regulatory office (przybylska, 2018; przybylska-cząstkiewicz, 2017; art. 23, sect. 2, pt. 18.a of the energy law, art. 41, 42 and 43, sect. 1 of the act on renewable energy sources). article 44, sect. 11 of the act on renewable energy sources shows that a co is due only in the case of shps whose power does not exceed 5 mw. hence, shps with a total installed capacity of more than 5 mw cannot benefit from this form of support. furthermore, currently, only some producers are entitled to a co: producers who are entrepreneurs generating energy in a micro-installation shp (if the micro-installation first generated energy before july 1, 2016) and electricity producers in other shps not exceeding 5 mw capacity (if the energy was first generated there before 1 july 2016). finally, it should be noted that the entitlement to a co only pertains for the 15 years following the initial date of energy generation (art. 44, sect. 1 and 5 of the act on renewable energy sources). the time frame of this support system is set to run concurrently with the aforementioned 15-year obligation to purchase electricity (szambelańczyk, 2016). the co employed in the support system should be distinguished from other documents – the guarantee of origin for res electricity. guarantees of origin only certify to the end-user the environmental marszelewski and piasecki: toward to “green deal” legal and natural aspects of the development of small hydropower plants the example of poland international journal of energy economics and policy | vol 12 • issue 4 • 2022 255 value resulting from the avoidance of greenhouse gas emissions and that the amount of electricity they injected into the distribution network or transmission network was generated from res in renewable energy installations. no property rights arise from guarantees of origin, and their sale is independent of the trading in property rights that result from a co (art. 120 of the act on renewable energy sources). like tgcs, they are marketable, but do not noticeably increase the res-energy use (przybojowska, 2020). their real value is created by any “green policy” that a company might have to demonstrate to society that they are using green energy (szambelańczyk, 2016). in light of this, the polish legislature distinguishes two documents that have been assigned entirely different functions. the first is a guarantee of origin, which has an informational value to the endrecipient as to whether and to what extent the energy received was produced from renewable sources. the second is a co, which plays a key role in a demand-driven support system that specifies standards relating to what share of energy comes from renewable sources (przybojowska, 2020). the second category of support for shp energy producers is based on an auction system. this system was introduced into the polish legal system in 2015 under the act on renewable energy sources. the reform of the support system created a dichotomous model. on the one hand, support provided by the co was maintained, while the auction system, which had not previously been in force, was added. such procedures as that aimed at concluding contracts for the sale of shp-generated electricity are conducted in accordance with specific rules provided for in the act on renewable energy sources (przybylska, 2018). in the auction, participants compete for public aid (support) consisting in: the conclusion of an electricity sale agreement with an entity obligated to purchase (for shps with total installed capacity below 500 kw) or the granting of a negative balance coverage guarantee (pokrzywniak, 2016; muszyński, 2020). “old” shp energy producers (those generating energy since before 1 july 2016) were left the choice of whether to use co support or switch to the auction system. in turn, “new” shp energy producers (those generating energy since july 1, 2016) must participate in auctions if they wish to use support. this relationship between the support systems means that the co-based system is gradually being phased out by the polish legislature in favour of the auction system (przybojewska, 2020). for the “old” generators, the requirements for joining an auction were simplified, being limited to the requirement to submit a declaration. by contrast, “new generators” are subject to formal assessment of whether they meet legal conditions for admission to an auction and must obtain a certificate of admission to the auction (przybylska, 2018; pokrzywniak, 2016; art. 44, 71, 75 and 76 of the act on renewable energy sources). the period of support granted on winning an auction shall not exceed 15 years from the date of first generation of energy by the shp as confirmed by co release, or from the date of sale of electricity after the auction is closed (art. 77, sect. 1 of the act on renewable energy sources). article 73, sect. 1 of the act on renewable energy sources provides that auctions must be held at least once a year. auctions for different categories of res installations are conducted separately. these categories are determined based on technology used (“technology mixes”). thus, one shared technology mix is relevant for shp, and consists of: facilities using only hydropower to generate electricity: of capacity below 500 kw, of capacity not <500 kw and exceeding 1 mw, and of capacity exceeding 1 mw; facilities using bioliquids; and facilities using geothermal energy. within each technological basket, the legislator also introduced the obligation to conduct separate auctions for facilities of capacity not exceeding 1 mw and separate auctions for facilities of capacity exceeding 1 mw (art. 73, sect. 3a and 4 of the act on renewable energy sources). the shp energy producer submits a bid using an online form. the bid should include the total amount of electricity (in mwh) and the price (in pln) for which the generator undertakes to sell energy under the auction in the specified bid period. it is also required to indicate the planned start date for the period in which the auction support scheme and the period of this support will be used (art. 79, sect. 1 and 3 of the act on renewable energy sources). the price offered by the shp producer may not exceed a “reference price”, which can be offered in the call for bids for a given technology mix in accordance with the relevant regulation (art. 77, sect. 3 of the act on renewable energy sources). pursuant to art. 80, sect. 1, pt. 1 of the act on renewable energy sources, the auction is won by the participants who offer the lowest electricity selling price. pursuant to art. 79, sect. 6 of the act on renewable energy sources, a bid submitted by an auction participant is not available to competing participants. hence, it is not possible to decide to lower a previously offered price. in this regard, auctions are thus similar to tender procedures (muszyński, 2020). failure to produce at least 85% of the amount of electricity declared in the bid within the three-year settlement period is subject to a penalty. penalties do not apply in the event of specific circumstances – e.g. a change in the hydrological flow that exceeds 25% of the average long-term flow in at least one of the verified years or a technical failure of shp constituting damage or destruction of the shp, objects or devices determining the operation shp that is sudden, unforeseen, and not dependent on the producer (art. 168, sect. 15 of the act on renewable energy sources). the third category of shp producer support is valid in poland since 2018. the new system introduced instruments based on a fixed purchase price as an alternative to the previous support systems, i.e. the co and auctions. the choice of support scheme is left to the generators, with each shp being allowed to use only one support instrument. the essence of fixed-purchase-price instruments is the possibility for the preferential sale of unused electricity fed into the distribution network (trupkiewicz, 2020). such instruments include: the feed-in tariff system – “fit” and the feed-in premium system – “fip”. the choice between them depends primarily on the power of the shp. based on art. 70a, sect. 1 of the act on renewable energy sources, an energy producer with an shp of less than 500 kw may marszelewski and piasecki: toward to “green deal” legal and natural aspects of the development of small hydropower plants the example of poland international journal of energy economics and policy | vol 12 • issue 4 • 2022256 sell unused electricity introduced to the grid at a fixed purchase price to an obligated entity or one of his or her own choosing. in such an approach, fit grants the energy producer the right to conclude an electricity sale agreement with an obligated entity. the obliged entity is designated by the competent administrative authority. that entity has a public-law obligation to directly purchase a certain amount of electricity produced by a given shp at a fixed purchase price (established by administrative process). this structure of the system means that the fit support (state aid) is transferred to the producer under the contract concluded with the obligated entity, as it is included in the fixed purchase price (trupkiewicz, 2020; art. 70c of the act on renewable energy sources). an electricity producer with an shp of less than 500 kw may use the fip system instead of the fit system. in such a case, no contract whose content is determined by the fit instrument is concluded with an obligated entity, and the purchase of energy by the obligated entity is not guaranteed. instead of such a contract, the producer concludes an electricity sale agreement with an entity he has found and selected at market prices on a competitive electricity market. then, the support under the fip system consists in the producer being granted the right to coverage of a negative balance of selling price to feed-in tariff level. the design of the fit and fip instruments in relation to energy producers with shps of less than 500 kw provides producers a choice: to use the fit or fip system (trupkiewicz, 2020; art. 70a, 70c, sect. 6 of the act on renewable energy sources). the system of supporting electricity producers with shps of not less than 500 kw and not more than 2.5 mw is different. such entities are eligible for fip support only. consequently, by selling electricity at market prices, they are also entitled to negative balance coverage (art. 70a, sect. 2, 2a and 3 of the act on renewable energy sources). support under the fit and fip systems is based on a fixedpurchase-price parameter. the fixed purchase price is the price of electricity at which an obligated entity purchases from an energy producer using fit support, or the base price for calculating a negative balance for producers using fip support (art. 2, pt. 33b of the act on renewable energy sources). thus, for an shp of less than 500 kw, the fixed purchase price is 95% of the reference price, and for an shp of not less than 500 kw and not more than 2.5 mw the fixed purchase price is 90% of the reference price (art. 70e of the act on renewable energy sources). the price of hydropower depends on the shp capacity, and in 2021 is eur 141.07 for <500 kw, eur 126.74 for 500 kw to 1mw and eur 121.23 for power >1 mw (§2, sect. 1 of the regulation of the minister of climate and environment of april 16, 2021, journal of laws 2021, item 722). pursuant to art. 70f of the act on renewable energy sources, both the obligation to purchase unused electricity under the fit and the right to negative balance coverage under the fip arises on the first day of sale of electricity covered by the support scheme and lasts for the next 15 years. meanwhile, for shps that have benefited from co support and changed system to fit or fip, the support period is counted from the first day of electricity generation confirmed by the issued co. in this case, it is deemed that there is a continuation of support, because the total period that an shp is covered by support in the co system and support in the fit or fip system may not exceed a maximum of 15 years (trupkiewicz, 2020). this confirms the rule that state aid for an shp is granted for a maximum period of 15 years. during this period, however, changes of support system are allowed. 3.6. legal conditions for shp investments and operation – selected remarks on the example of european countries the length of administrative procedure required for the investments in shp in poland, ranging from at least 1 to about 5 years, is no exception in comparison to other european countries. in accordance with conducted research, obtaining the necessary permits (apart from the length of building shp instalation itself) may last: from 4 to 11 years in france, about 7 years in greece, from 1,5 to 7 years in italy or <2 years in sweden (restor hydro, 2014). the key role in the location of planned shp is obtaining obligatory decisions in the field of environmental protection. for example, in belgium (flanders, wallonia) and greece it is necessary to procure an environmental impact decision. in italy, slovenia and slovakia an environmental impact assessment shall be obtained. the requirements for the impact assessment of the planned shp on the environment may, however, differ due to installed power by being less restrictive in the case of small installations. the construction of rights to use water for hydropower purposes results from the water and land management system adopted in the law of each country. for instance, in belgium (flanders, wallonia) there are differences resulting from the classification of waterways which depending on shp location results in the need to obtain a water collection permit and/or consent to modify a watercourse. in greece, a water use permit shall be obtained, in italy – a water use license while in lithuania an investor should procure a permit for special water use (restor hydro, 2014). in european countries the use of the same shp support can also be noticed. thus, in belgium, romania and sweden support is based on tgcs. on the other hand, in germany, greece, france, italy, the czech republic and lithuania the support is distributed through fit and fip tariffs. in denmark, portugal, slovakia and slovenia, support is provided only under the form of fit tariffs. depending on the country, support periods range from 10 to 30 years, but – for example in denmark – there is no time limit (european small hydropower association, 2022; council of european energy regulators, 2021). the above remarks allow to conclude that the legal regulations in general aspects concerning the establishment and operation of shp is similar in european countries. the differences reveal especially in more detailed issues which reflect the state policy (such as the duration of the support systems) or in the integration of the conditions for the location and operation of the shp into the applicable institutions and legal acts. marszelewski and piasecki: toward to “green deal” legal and natural aspects of the development of small hydropower plants the example of poland international journal of energy economics and policy | vol 12 • issue 4 • 2022 257 4. social conflicts, environmental losses and problems resulting from errors in the management of shp and the lack of optimal legal regulation: case studies 4.1. case study 1 this case study concerns a 44-kw shp on the niechwaszcz watercourse, 3.7 km upstream of its confluence with the wda river in northern poland. in july 2020, downstream of the shp, there was a mass die-off of fish and water pollution, caused in part by a high concentration of suspended matter. the results of a water quality inspection by the environmental protection services showed a rapid increase in total phosphorus and total nitrogen in both rivers, with concentrations reaching 2.26±0.27 mg/dm3 and 9.6 mg/dm3, respectively. furthermore, high suspended matter content (360±83 mg/dm3) and a mass die-off of fish was found in the niechwaszcz watercourse, downstream of the shp and in the wda river. the fish died from their gills being blocked by suspended matter. the heavy pollution of the rivers was caused by the rapid discharge (discharge) of water from the shp reservoir, which caused sediments accumulated in it to be drained off. the draining of the reservoir had been necessitated by the obligation on the shp owner to renovate a bridge on a public road running through the shp. the rapid discharge (dumping) of water from the reservoir resulted from the need to complete the repair of the bridge in just 1.5 months in order not to impede the spawning of fish species. the renovation date thus appears to have been selected with due care. analysis of numerous documents that the shp owner received three years earlier when buying the shp revealed no information on the volume of sediment in the tank, nor recommendations on how to periodically drain it. this example shows that, despite the costly and extensive documentation required for shp, it lacks a lot of relevant data and guidance. moreover, the obligation on owners to carry out repairs to bridges and roads through the shp is also questionable, given that they do not necessarily have adequate experience in such works. as a result, a conflict arose between the owner of the shp and the local community, pro-ecological organisations, environmental protection services and the manager of surface waters, despite the owner of the shp having undertaken to cover any losses to the fish life in both rivers. conflicts of this kind are not conducive to public support for developing shps. 4.2. case study 2 an shp was established at the site of a former water mill on the warta river in karcze-wice (central poland) in the late 1990s. water flows to the shp through a man-made mill chute (młynówka), which begins at km 702.9 of the river and rejoins it at km 701.5. ini-tially, about 50% of the warta river’s water flowed through this canal, and the rest flowed along its natural historical channel. in the vicinity of both watercourses there are areas classified flood-risk areas. presented case is shown in figure 3. explanations: 1 – rivers and canals; 2 – flood zones (up to 0.5 m); 3 – flood zones (up to 2.0 m), 4 – river kilometere to mouth; 5 – shp; 6 – stone threshold; 7 – forests and bushes; 8 – meadows and arable land; 9 – dispersed building develompment; 10 – main roads. prepared on the basis of informatic system for country protection – flood hazard map, https://isok.gov.pl/hydroportal. html. in shp karczewice, two turbine sets were installed that required a velocity of 3.5 m3/s, i.e. almost double the needs of the historical mill. the damming level was also raised by about 0.5 m. moreover, droughts began to increase in frequency as a result of global warming. to increase the water volume in the chute, a stone threshold was built in the warta river without the required permit. this significantly reduced the velocity in the natural section of the river to approx. 1.2 m3/s. the river bed was exposed, and locals became unable to bathe or fish. in turn, during high water levels, due to the increased damming of water by the shp, real-estate was flooded that had not previously been af-fected during floods. public protests began that lasted for several years, resulting in 2016 in the competent administrative authority refusing to issue a water permit for special use of the warta river’s waters by the shp. despite this, the shp continued to function, arguing from the standpoint of ful-filling its contractual obligation to the energy recipient. in 2020, after more than four years of documentation being sent back and forth between multiple offices and the shp owner, the competent administrative authority anulled the 2016 decision and granted a permit for the operation of the shp. a permit was also granted for the additional damming of the figure 3: location of shp karczewice on the background of the flood-hazard area marszelewski and piasecki: toward to “green deal” legal and natural aspects of the development of small hydropower plants the example of poland international journal of energy economics and policy | vol 12 • issue 4 • 2022258 warta river with the above-mentioned stone threshold fixing the damming level (at 219.29 m a.s.l.) and maintaining 2.37 m3/s of uninterrupted velocity in the natural river channel. however, it does not seem that the parameters indicated in the above permit can be fully met. the water velocity volume into the shp will be sufficient during high flows and medium flows (7.4 m3/s) in the warta, even after deducting the required minimum velocity (2.37 m3/s) that must be maintained in the natural section of the river. however, during low flows (below 3 m3/s), flow to the shp via the mill chute cannot be maintained in the expected amount while also maintaining the required minimum velocity in the natural river bed. this observation is significant, all the more so given that low water levels and low river flows have been prolonged in this part of europe for well over a decade (tomaszewski and kozek, 2021; kozek and tomaszewski, 2021; feyen and dankers, 2009). however, the shp raising the damming level will pose an additional threat to the population. this example shows the negative effects of a lack of precision in decisions when commissioning shps and failure to consider the true hydropower potential of a river. the resulting problems have been made particularly visible by ongoing climate warming and the reduction in water resources and increase in extreme hydrological events (droughts, floods). meanwhile, already in the 20th century, it was known that water levels and velocity in the section of the warta river in question fluctuated greatly, with velocity ranging from 2.6 to 39 m3/s. thus, a lack of precision in assessing natural conditions causes many administrative and legal complications, as well as contributing to a local public dissatisfaction and lack of acceptance of such projects. 4.3. case study 3 this example does not apply to a specific installation, but illustrates a systemic difficulty for shps that are or might be located in a natura2000 site – e.g. in a natural park buffer zone. natura2000 is a network of areas within the european union where nature is subject to protection. the aim of the natura2000 programme is to preserve natural habitat types and species considered valuable and endangered on a european scale, in accordance with directive 2009/147/ec of the european parliament and of the council of 30 november 2009 on the conservation of wild birds and council directive 92/43/eec of 21 may on the conservation of natural habitats of wild fauna and flora. the difficulty in question consists in the refusal to issue a decision for the construction or renovation and modernisation of shp as part of the procedure discussed in part 3.2. – for issuing a dec. as a consequence, an investor’s ability to obtain a dec is significantly impeded or even excluded. at the same time, however, from a legal standpoint, the problem is not complicated. in the shp industry, it is indicated that it would be sufficient to amend the real-estate management act (consolidated text, journal of laws 2021, item 1899) by qualifying – as a public goal within the meaning of this act – activities consisting in modernising existing res installations using the hydro energy of rivers or constructing new ones. in conjunction with other legal provisions, a change in this respect would facilitate the development of shp in poland. unfortunately, despite such a postulate having been submitted to the legislator several years ago, it has not been processed. 5. discussion despite conditions for the construction of shps being unfavourable in most of poland, there are still convenient locations for such facilities in the country. according to renewable energy sources transforming our regions (restor) hydro (2021), an eu-funded project, there are over 8,000 potential sites for the construction of an shp in poland (figure 4). the project aims to increase energy production from micro and small hydro by identifying and restoring currently inoperative mills and other historical sites and also promotes the cultural heritage. restor indicates that the area of greatest potential is the south and southwest of the country. simultaneously modern shp technologies provide additional optimism as to the warrantedness of building an shp in poland. they allow even small water drops to be used for energy production (drzewiecki, 2011). this is extremely important, considering the topography of poland mentioned earlier. it is worth noting that a small hydropower plant can operate in a hybrid system with, for example, photovoltaics. the construction and operation of an shp will always be associated with an impact on animate and inanimate nature. so too is the structure and operation of any anthropogenic facility. however, relevant provisions regulate in detail the functioning of an shp, and define the conditions to be met for an shp to be established in a given location. meeting all these requirements minimises the negative consequences associated with the construction and operation of the shp. the link between shp activity and nature is extremely complex. many changes in natural ecosystems that figure 4: potential sites for the construction of an shp in poland according to restor aq2 marszelewski and piasecki: toward to “green deal” legal and natural aspects of the development of small hydropower plants the example of poland international journal of energy economics and policy | vol 12 • issue 4 • 2022 259 stem from an shp may be long-term and spatially far-reaching. therefore, it is extremely important to properly manage shps through appropriate water management. this should take into account not only energy production, but above all the possibility of negative phenomena associated with the operation of the shp. it should be emphasised that, in many cases, shps are set up in places that have already been transformed by humans building water mills, sawmills, etc. (radtke et al., 2012). these facilities’ operation also involved damming a river and building a reservoir. therefore, locating an shp in their stead should not be equated with the locating of entirely new facilities that will transform the aquatic ecosystem. the construction of small hydropower plants is usually socially accepted, and only extremely rarely provokes protests. this is because this form of energy is widely recognised to be safe and ecological. a small hydroelectric power plant also has a positive effect on the landscape, enriching and diversifying the local area. due to the nature of the shp, the support systems based on feedin tariffs (fit) and market price subsidies (fip) are particularly important. they are optimal for small-scale electricity producers, which is reflected in the positive opinions of them on the part of entities operating shps. from this perspective, the role played by the other two systems is not so important. in the case of the system based on tgcs, there is an oversupply that translates into a low market price (malicka, 2018). furthermore, until the end of 2009, the sale of property rights from tgcs was taxed separately as autonomous income from cash capitals and was not included in the income from the sale of renewable energy produced, which is classified as income from non-agricultural, shp business activities. this state of affairs was unfavourable for taxpayers gaining revenue from the sale of tgcs (pasiewicz and brysz, 2013). on the other hand, the auction system is highly formalised and, consequently, its lack of flexibility does not necessarily allow it to correspond to the specificity of the shp. over the course of 2020 and 2021, the subject of shp again became a subject of interest to the legislature and energy producers. this is because the aforementioned 15-year period of combined shp support was closing for about 400 hydroelectric power plants (the parliament of the republic of poland, 2021). a lack of publicsector operational support via appropriate legal regulations makes shp dependent for its existence on selling the energy it produces on the wholesale market. the prices there do not ensure the profitability of shp operations (chojnacki 2021). consequently, many shps may close. this fact led to an amendment of the act on renewable energy sources in september 2021. the support period was extended from 15 to 17 years, but only within the fit and fip systems (provisions entered into force on october 30, 2021). this extension of support applies to shps not exceeding 1 mw, however. shp energy producers with a capacity of no more than 1 mw who lost support during the drafting of the amendment have the right to apply for coverage of the negative balance on energy they generated and sold during the “transitional period” (art. 11, sect. 6 of the act of 17 september 2021 amending the act on renewable energy sources and certain other acts, journal of laws 2021, item 1873). when making the two-year extension, the polish legislature was guided by an intention to temporarily reduce the risk of some shp being terminated by an absence of support. at the same time, the legislature assumes that an operational support system in the form of guaranteed bonuses will be adopted and announced in the meantime, including for shps whose support period has expired and whose operating costs make it impossible to operate on the basis of wholesale market energy prices (the parliament of the republic of poland, 2021). the legislator is aware that the operating costs for shps are significantly higher than for, for example, producers of photovoltaic energy. this is due not only to technological issues, but also to the costs associated with water and environmental management (the parliament of the republic of poland, 2021). legislative solutions regarding support under the fit and fip systems reflect the shp industry’s assertions that they constitute a “life line” for hundreds of shps. the legal framework for shp functioning in poland can be divided into two separate areas being evaluated. the first concerns the great complexity of facility location and operation conditions for shps. this is due to the nature of shps and their close integration with the (mainly aquatic) environment. at the same time, water management is a particularly sensitive area that is influenced not only by the polish legislature, but also by the eu legislature. hence, on the one hand, we should strive for proper water management, especially water protection, and, on the other, to facilitate the location and operation of shp in all feasible areas. it is very important to ensure a balance between these two areas using stable, “friendly” legal conditions. meanwhile, in evaluating the shp support systems, it should be stated that they are evolving in the right direction. the legislature has gradually adopted new solutions, creating alternatives for entities operating shps and ultimately developing the fit and fip system, which largely meets their needs. however, this has taken many years. it seems, however, that further changes will be desirable with time. work on the targeted support system for shp is of particular importance given eu member states’ obligation to gradually increase the production of electricity from renewable sources. in march 2021, the polish government adopted a resolution on poland’s energy policy until 2040. the document contains a vision of poland’s energy transformation strategy, including the selection of technologies to build a low-emission energy system. the document largely ignored the role and importance of small hydropower plants. according to the presented analyses and forecasts, the volume of net electricity production from hydropower (mainly large hydropower plants) will not change up until 2040. it will be around 1.8 twh per year. this is confirmed by the lack of funds allocated to investment outlays for expanding the generation capacity of hydroelectric power plants. according to the adopted strategy, the main thrust of investment in renewable energy is to be towards wind (onshore and offshore) and solar energy. these forms of energy are planned to receive, respectively: eur 35.6 billion and eur 6.3 billion. in poland, the current high use of fossil fuels makes the implementation of the climate neutrality goal by 2050 particularly difficult. this is because of the extremely high costs of energy marszelewski and piasecki: toward to “green deal” legal and natural aspects of the development of small hydropower plants the example of poland international journal of energy economics and policy | vol 12 • issue 4 • 2022260 transformation that the country will have to bear in a relatively short time. the document defining poland’s energy policy until 2040 indicates a systematic shift from fossil-fuel energy to nuclear and wind energy. however, heavy socio-economic pressure, especially in coal-mining regions, may make it difficult to achieve the goals set. projected expenditure on energy-transformation investments in poland totals eur 355 billion for 2021–40 – from an annual national budget of approximately eur 111 billion. therefore, key to achieving climate neutrality goals is eu financial support. bearing in mind poland’s existing electricity production being based on coal and the obligations stemming from the european green deal, it should be concluded that changes in the structure of energy production sources in the country will increasingly move towards renewable sources over the next few decades. of these sources, small hydropower engineering, which is by definition an expression of private initiatives, deserves special attention. providing steady electricity generation, it is not as heavily dependent on weather conditions as are wind or solar energy. at the same time, it is starting to be noticeably influenced by progressive global warming, which is reducing poland’s water resources. in general however, investing in a small hydropower plant is more complicated than investing in certain other renewable energy installations. although the polish legal environment creates a similar framework for all renewable energy installations and is not more amenable to other methods of producing green energy, shp has special location considerations. there is a noticeable difference in ease of locating a photovoltaic installation or small wind turbine on land owned by a private individual. shps must be integrated into specific water–environment relations and usually require a more complex infrastructure. additionally, a private entity running an shp will never own the waters, nor the land beneath them, as these are the property of the state treasury. therefore, because shp is associated with public waters and land, it is – from the private owner’s perspective –more difficult to perceive them as a coherent economic unity dependent solely on the owner. the data presented and analysis carried out herein clearly indicate the need to introduce changes to the functioning of shp in poland. these changes must be complementary in terms of legal and environmental solutions. recommendations in the form of final guidelines are presented below. they implementation should, according to the authors, bring about positive changes and help increase the significance of shp in poland. 1. to increase the awareness of the general public and local authorities with regard to the importance of shp in shaping the water resources of a catchment area (slowing runoff, increasing the water resources of the catchment area). highlighting this aspect is extremely important in the face of climate change and water scarcity problems in some parts of the country. 2. reviewing poland’s strategy for its hydroenergy policy until 2040 in accordance with european climate law. 3. providing the possibility of obtaining financing to build shp under programmes promoting small water retention. this applies especially to areas of water deficits – such as the wielkopolska-kujawskie lakeland. 4. stimulating local communities and private investors to construction of new shps through additional financial support and friendly legal environment. 5. simplifying – at every possible step – the legal procedure for obtaining approval for building shps by creating fast legal paths dedicated to shp. such a procedure should be significantly accelerated in the light of european climate law commitments. this remark concerns especially locations where an installation of the same or similar nature (water sawmill, water mill) existed in the past. 6. developing a stable and predictable support system targeted at shp that encourages investments in shps through ensure the economic profitability of such projects. it can be achieved by fit and fip support system which is not limited in time. this proposition however, does not exclude the possibility of a partially reduction of the support after the depreciation of the shp facility investment. 7. conducting widespread activities to achieve universal public acceptance of the energy transformation from coal energy to green energy. references bajkowski, s., górnikowska, b. (2013), hydropower production against energy from other renewable sources. scientific review-engineering and environmental sciences, 59, 77-87. będkowski-kozioł, m. (2020), in energy law. act on the renewable energy sources. act on the capacity market. in: czarnecka, m., ogłódek, t., editors. the wind energy investments act commentary. warsaw, poland: c.h. beck; 2020. behnke, m. (2010), water permit as a legal measure to protect the environment. in: rakoczy, b., pchałek, m., editors. selected problems of environmental protection law. warsaw, poland: wolters kluwer. bojarski, a., jeleński, j., jelonek, m., litewka, t., wyżga, b., zalewski, j. (2005), zasady dobrej praktyki w utrzymaniu rzek i potoków górskich. warsaw, poland: ministry of the environment. capik, m., yilmaz, a.o., cavusoglu, i. (2012), hydropower for sustainable energy development in turkey: the small hydropower case of the eastern black sea region. renewable and sustainable energy reviews, 16, 6160-6172. chojnacki, i. (2021), the end of support for small hydropower plants could wipe them out. available from: https://www.wnp.pl/ energetyka/koniec-wsparcia-dla-malych-elektrowni-wodnych-mozeje-unicestwic,428588.html [last accessed on 2021 nov 18]. council of european energy regulators. (2021), renewables work stream of electricity working group. status review of renewable support schemes in europe for 2018 and 2019. ceer report. available from: https://www.ceer.eu/documents/104400/-/-/ffe624d4-8fbbff3b-7b4b-1f637f42070a [last accessed on 2022 jan 30]. district court in warsaw. (2019), judgment of the district court in warsaw of may 8, 2019, file reference number: xvi gc 803/17. warsaw: district court in warsaw. drzewiecki, m. (2011), rozwój niskospadowej energetyki wodnej. czysta energia, 11, 48-49. energy regulatory authority. (2021), available from: https://www.ure. gov.pl/pl/oze/potencjal-krajowy-oze/8108,instalacje-odnawialnychzrodel-energii-stan-na-30-czerwca-2021-r.html [last accessed on 2021 nov 18]. european commission. (2019), communication from the commission to the european parliament, the european council, the council, the marszelewski and piasecki: toward to “green deal” legal and natural aspects of the development of small hydropower plants the example of poland international journal of energy economics and policy | vol 12 • issue 4 • 2022 261 european economic and social committee and the committee of the regions-the european green deal. brussels 11.12.2019 com (2019) 640 final. document 52019dc0640. brussels: european union. european commission. (2021), the european climate law. available from: https://www.ec.europa.eu/clima/eu-action/european-greendeal/european-climate-law_pl [last accessed on 2021 nov 18]. european council. (2020), european council meeting (10 and 11 december 2020)-conclusions. brussels 11 december 2020. euco 22/20. europe: european council. european council. (2021), council of the european union. clean energy: fuelling the transition to a low-carbon energy. available from: https://www.consilium.europa.eu/en/policies/clean-energy/# [last accessed on 2021 nov 18]. european parliament. (2021), regulation (eu) 2021/1119 of the european parliament and of the council of 30 june 2021 establishing the framework for achieving climate neutrality and amending regulations (ec) no 401/2009 and (eu) 2018/1999. european climate law. france: european parliament. european small hydropower association. (2022), small hydropower roadmap. condensed research data for eu-27. available f r o m : h t t p s : / / w w w. g l o b a l c c s i n s t i t u t e . c o m / a r c h i v e / h u b / publications/138208/small-hydropower-roadmap-condensedresearch-data-eu-27.pdf [last accessed on 2022 jan 30]. feyen, l., dankers, r. (2009), impact of global warming on streamflow drought in europe. journal of geophysical research: atmospheres, 114(d17), d011438. filipowicz, t. (2020), in: filipowicz, t., plucińska-filipowicz, a., wierzbowski, m., editors. act on the provision of information on the environment and its protection, public participation in environmental protection and environmental impact assessments commentary. warsaw, poland: c.h. beck. growns, i.o., growns, j.e. (2001), ecological effects of flow regulation on macroinvertebrate and periphytic diatom assemblages in the hawkesbury-nepean river, australia. regulated rivers: research and management: an international journal devoted to river research and management, 17(3), 275-293. gutry-korycka, m., sadurski, a., kundzewicz, z. (2014), zasoby wodne a ich wykorzystanie. nauka, 1, 77-98. jankowski, ł. (2020), in energy law. act on the renewable energy sources. act on the capacity market. in: czarnecka, m., ogłódek, t., editors. the wind energy investments act commentary. warsaw, poland: c.h. beck. jansson, r. (2002), the biological cost of hydropower. hong kong: ccb report. jokiel, p. (2004), zasoby wodne środkowej polski na progu xxi wieku. łódź, poland: wydawnictwo uniwersytetu łódzkiego. king, r. (2018), net-metered infrastructure-based hydropower. vermont journal of environmental law, 19(4), 407-437. koropis, r. (2013), shp insurance-it’s safer to be together. hydropower, 2, 24-25. kozek, m., tomaszewski, e. (2021), selected characteristics of hydrological drought progression in the upper warta river catchment. acta scientiarum polonorum formatio circumiectus, 17(3), 77-87. kucukali, s., baris, k. (2009), assessment of small hydropower (shp) development in turkey: laws, regulations and eu policy perspective. energy policy, 37, 3872-3879. kuśnierkiewicz, n. (2018), water law assessment in the new water law act. hydropower, 2, 33. lowenstein, j.d., panarella, s.j. (2018), troubled water: building a bridge to clean energy through small hydropower regulatory reform. ucla journal of environmental law and policy, 36(2), 231-302. malicka, e. (2018), small hydroenergy sector in poland-facts, opportunities and challenges. hydropower, 3, 16-19. mesquita, r. (2019), barriers to the development of small hydropower due to the water framework directive. renewable energy law and policy review, 9(2), 37-44. muszyński, i. (2020), in energy law. act on the renewable energy sources. act on the capacity market. in: czarnecka, m., ogłódek, t., editors. the wind energy investments act commentary. warsaw, poland: c.h. beck. pasiewicz, m., brysz, w. (2013), taxation of sales of green certificatescontroversial judgment of the supreme administrative court. hydropower, 2, 26-27. pga. (2021), technical evaluation of re and ee projects for fls personnel. small hydropower plants. available from: http:// www.pga.org.pl/biblioteka/multimedia/prezentacje/male%20 elektrownie%20wodne.pdf [last accessed on 2021 nov 18]. plucińska-filipowicz, a., filipowicz, t. (2018), in: plucińskafilipowicz, a., wierzbowski, m., editors. act on spatial planning and development commentary. warsaw, poland: wolters kluwer. pokrzywniak, p. (2016), in: baehr, j., lissoń, p., pokrzywniak, j., szambelańczyk, m., editors. act on the renewable energy sources commentary. warsaw, poland: wolters kluwer. przedwojski, b., wierzbicki, m., wicher-dysarz, j., walczak, n. (2007), stan zagrożenia powodziowego powyżej zbiornika jeziorsko. nauka, przyroda, technologie, 1(2), 229-240. przybojewska, i. (2020), in act on the provision of information on the environment and its protection. in: filipowicz, t., plucińskafilipowicz, a., wierzbowski, m., editors. public participation in environmental protection and environmental impact assessments. commentary. warsaw, poland: c.h. beck. przybylska, m. (2018), an auction as a mode of concluding a contract for the sale of electricity from renewable sources. public law review, 2, 61-71. przybylska-cząstkiewicz, m. (2017), the legal conditions for the development of renewable energy in poland after 2015. energy policy journal, 1(20), 103-116. radtke, g., bernaś, r., skóra, m. (2012), small hydropower stationsmajor ecological problems: some examples from rivers of northern poland. let’s protect our native nature, 68(6), 424-434. rakoczy, b. (2018), water law. practical guide. warsaw, poland: wolters kluwer. restor hydro map. (2021), available from: http://www.hydropower. kamilpiwowarski.pl/app [last accessed on 2021 nov 18]. restor hydro. (2014), micro hydropower plants and small hydropower plants. a complete rebuild guide. available from: http://www.trmew.pl/fileadmin/user_upload/current_version/trmew. pl/strona_glowna/aktualnosci/2015/07/podrecznik_mew_restor_ hydro.pdf [last accessed on 2022 jan 30]. robakowska, m. (2018), water law-subsequent changes. hydropower, 4, 28-29. rotko, j. (2018), legal bases of water management. wrocław, poland: university of information technology and management “copernicus”. sensiba, c.r., swiger, m.a., white, s.l. (2018), deep decarbonization and hydropower. environmental law reporter, 4(48), 10309-10333. supreme administrative court. (2011), judgment of the supreme administrative court of june 14, 2011, file reference number: ii fsk 269/10. sweden: supreme administrative court. świątek, m. (2016), small hydropower in western pomerania-the history and the present. annales universitatis paedagogicae cracoviensis. studia geographica, 10, 166-178. szambelańczyk, m. (2016), in: baehr, j., lissoń, p., pokrzywniak, j., szambelańczyk, m., editors. act on the renewable energy sources. commentary. warsaw, poland: wolters kluwer. sznajder, a. (2020), water permit as an instrument of water resources marszelewski and piasecki: toward to “green deal” legal and natural aspects of the development of small hydropower plants the example of poland international journal of energy economics and policy | vol 12 • issue 4 • 2022262 management. warsaw, poland: c.h. beck. the parliament of the republic of poland. (2021), bill print no. 1129. warsaw. 26 april 2021. available from: https://www.orka.sejm.gov. pl/druki9ka.nsf/0/c981e65dabe43f18c12586c700344217/%24 file/1129.pdf [last accessed on 2021 nov 18]. tomaszewski, e., kozek, m. (2021), dynamics, range, and severity of hydrological drought in poland. in: zeleňáková, m., kubiakwójcicka, k. negm, a.m., editors. management of water resources in poland. berlin, germany: springer. p229-252. trela, m., dubiel, a. (2017), comparing the support systems for renewable energy sources in poland: green certificates vs auction systems. energy policy journal, 2(20), 105-116. trupkiewicz, m. (2020), in energy law. act on the renewable energy sources. act on the capacity market. in: czarnecka, m., ogłódek, t., editors. the wind energy investments act. commentary. warsaw, poland: c.h. beck. u.s. code of federal regulations. (2016), conservation of power and water resources, 18 u.s. code of federal regulations § 4.30 (b) (31). united states: u.s. code of federal regulations. warren, g.s. (2017), small hydropower, big potential: considerations for responsible global development. idaho law review, 53, 149-178. wierzbicki, m., hammerling, m., przedwojski, b. (2008), the erosion process downstream the jeziorsko reservoir on the warta river. scientific review. engineering and environmental sciences, 17, 136-145. wieteska, s., jeziorska, m. (2018), risk assessment of the small hydropower plants operation for insurance purposes. economic studies. scientific journals of the university of economics in katowice, 353, 125-138. wojtkowska-łodej, g. (2021), eu energy and climate policies: challenges and opportunities for poland. international journal of energy economics and policy, 11(4), 433-442. wróblewska, k. (2013), waste management within shp. hydropower, 3, 28-29. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 6 • 2022168 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(6), 168-174. industrialization and consumption of fossil energy are the main determinants of environmental degradation in water catchment areas in indonesia hadi sasana, panji kusuma prasetyanto*, nuwun priyono faculty of economics, tidar university, magelang, indonesia. *email: panjikusuma@untidar.ac.id received: 29 july 2022 accepted: 09 october 2022 doi: https://doi.org/10.32479/ijeep.13546 abstract economic growth is the main goal of the global economy. however, increasing economic growth often results in increased co2 emissions and encourages environmental degradation. this study analyzes the impact of industrialization, consumption of fossil energy, economic growth, and population activities on co2 emissions in upland water catchment areas. data analysis using panel data regression, in a span of 20 years. the results of the study show that economic factors, namely industrialization and consumption of fossil energy, are the main determinants of increasing co2 emissions. meanwhile, social aspects such as education, waste generation, and population have no effect on co2 emissions. keywords: co2 emissions, economic growth, fossil energy, industrialization jel classifications: o44, q43, q56 1. introduction massive economic development has a positive impact on people’s welfare, but also has a negative impact, namely the decline in environmental quality. environmental degradation due to air pollution, water pollution, and soil pollution has become a global issue. global warming as a result of rising concentrations of carbon dioxide (co2) and other gases in the atmosphere has driven climate change. global warming is one of the global issues that is increasingly being echoed by various countries. greenhouse gases, especially co2, are the cause. the incessant economic development with industrialization and consumption of fossil energy in various regions has pushed up co2 emissions and decreased environmental quality in the regions (fadholah et al., 2017). sustainable or sustainable economic development must have a balance between economic growth on the one hand and the preservation of natural resources or the environment on the other (todaro and smith, 2009). sustainable economic development is an effort to improve the welfare of the population by taking into account the environmental impact. increasing the welfare of the population does not have to be followed by a decrease in environmental quality, such as polluted water sources, deforestation, and air pollution due to various types of pollutants. indonesia is one of the largest co2 emitters in the world. based on data as shown in figure 1, co2 emissions in indonesia have spread to the regional level with agricultural concentrations. co2 emissions in the regions, especially highland areas as water catchments in central java province, tend to increase. this is partly due to the existence of industrialization activities in various fields, which causes the consumption of fossil energy to increase. the largest contributor to co2 emissions in various regions comes from the fossil energy sector, industrial activities, and inorganic waste that is not managed properly. the data in figure 1 below shows co2 emissions in the six study areas that tend to increase. this journal is licensed under a creative commons attribution 4.0 international license sasana, et al.: industrialization and consumption of fossil energy are the main determinants of environmental degradation in water catchment areas in indonesia international journal of energy economics and policy | vol 12 • issue 6 • 2022 169 the industrial sector has become the main driving factor for economic growth. industrialization as the engine of economic development is increasingly massive in various regions. energy consumption, especially fossil energy as an industrial input, is increasingly expanding in an effort to maintain economic growth. energy consumption, especially fossil energy, tends to increase with increasing economic activity, thereby increasing co2 emissions. the increasing use of fossil energy in many areas is not only carried out by medium and large industries, but also small industries, to home industries. li and chunshan (2021) stated that the use of fossil energy is one of the main sources of environmental degradation by increasing the level of co2 emissions. economic growth is always closely related to the exploitation of natural resources and the environment. through economic development in all fields, economic growth tends to increase, although it fluctuates. this is due to changes in the production of goods and services and inefficiencies in industrial activities. an economy that grows efficiently is considered to be able to reduce the impact on environmental degradation (sheng et al., 2021). for developing countries, it is important to investigate the environmental impacts caused by rapid economic growth through massive energy consumption (uddin, 2014). environmental damage (arista, 2019). meanwhile, the population as a production factor continues to increase in number, although it has not been followed by the availability of facilities and infrastructure, as well as public facilities such as adequate waste disposal sites. so that there is a lot of waste that cannot be controlled and continues to increase, especially inorganic waste which has a bad impact on the environment, and encourages an increase in greenhouse gases. plastic waste, for example, which relies on the extraction of fossil fuels will continue to generate greenhouse gases until the waste decomposes (zheng and suh, 2019). based on the above background, economic activities that are not followed by environmental balance are thought to have an effect on increasing co2 emissions in the region. therefore, further research is needed to formulate the right strategy so that co2 emissions are reduced in a sustainable manner so that environmental quality can be maintained. 2. literatur review natural resources are factors of production in economic activities. understanding of resources is not limited as an input factor, because the production process will also produce output which then becomes an input factor for the continuity and availability of natural resources (fauzi, 2006). according to yusgiantoro (2000) natural resources can be divided into two, namely renewable natural resources and non-renewable resources. the use of natural resources in the production process that continues to increase has an impact on increasing carbon dioxide (co2) gas. akpan and akpan (2012) state that since the 1850s the global use of fossil fuels (coal, oil and gas) has increased sharply to dominate the world’s energy consumption and supply. the research of sheinbaum et al. (2012) states that in mexico in the period 1990–2008 there were several important changes in the structural effect that could reduce emissions in 10 sub-sectors of the manufacturing industry. the energy intensity and carbon index tested had negative effects on all subsectors with the exception of cement and some other subsectors. total energy use continues to show an increase due to production activities that continue to grow and industrial products that continue to drain energy in meeting the demands of a growing population (shamsuzzaman et al., 2021). there is an interrelated relationship between economic development and the environment. the environmental kuznets curve (ekc) explains the relationship between economic development and environmental quality (shaharir and alinor, 2013). at a time when per capita income is still low, steps to reduce environmental damage are not carried out by humans, because it is better to use their limited income to meet basic consumption needs. when a certain level of income has been reached, individuals begin to consider the trade-off between environmental quality and consumption. in this condition the rate of environmental damage begins to slow down. the third condition, after a certain point, spending on reducing environmental damage dominates individuals to prefer improve environmental quality compared to subsequent consumption. in the end, the quality of the environment began to improve along with economic growth. chen’s (2007) study in china found that the relationship between environmental damage and per capita income is in the form of a u-curve. bartz and kelly’s (2004) study of the relationship between welfare and environmental degradation concluded that welfare affects environmental degradation in a pattern as shown by the environmental kuznet curve (ekc). garbage is solid waste consisting of organic and inorganic substances which are considered useless so that it needs to be managed so that it is not harmful to the environment and can provide protection for development investment (sni 19-24542002). the amount of waste that results from the activities of living things in a certain period of time is called waste generation. waste generation is the amount or amount of waste in gravimetric units of weight (kilograms) or volume (liters) volumetric (tchobanoglous et al., 1993). the effect of waste generation on environmental figure 1: co2 emissions study area year 2000–2019. source: department of environment and forestry, central java, 2000–2020 source: department of environment and forestry, central java, 2000– 2020 sasana, et al.: industrialization and consumption of fossil energy are the main determinants of environmental degradation in water catchment areas in indonesia international journal of energy economics and policy | vol 12 • issue 6 • 2022170 degradation can be caused by an increase in population, with increasing demand for plastic because the material is cheap and light to carry out daily activities (ford et al., 2022). rapid industrial growth has resulted in increased retention of carbon and other greenhouse gases over time (martines, 2005). industry requires high fossil energy to support its business activities. according to stolyarova (2013), industry causes carbon and greenhouse gas emissions to increase because industrial activities cause the conversion of forest functions and the use of fossil energy. fossil energy in the form of oil, natural gas, and coal is a source of air pollution. energy is one of the main needs in various sectors, both in consumption activities and in production activities. chontanawat et al. (2006) stated that energy plays an important role in promoting an economic system on the demand side and supply side. on the demand side, energy is an important product for consumers, this can be seen in the consumer’s decision to buy so that the quality is maximized. on the supply side, energy is an important factor in production activities in addition to labor, capital and materials. the use of fossil energy had decreased during the first and second world wars, which then increased again in 1950 and 1970 when fossil energy in the form of oil and gas became the dominant energy source for production purposes. until now and in the future, this energy source has become a commodity in world trade activities followed by coal as an energy source in the field of electrification such as electricity and various electronic devices which began to develop rapidly in 1975 and beyond (bach, 1980). population plays an important role in economic development. the population as an important human resource in the production process to support economic growth and provide goods and services for a larger market. however, excessive population is defined as human activities that are too dense to cause excessive co2 emissions (rahman et al., 2020). the increase in population will affect the behavior/lifestyle and consumption patterns of the people. according to arbulú et al. (2015), the higher the education level of the population, the significantly higher the commitment to care for the environment. chen (2010) also argues that universities will produce more graduates with environmentally conscious behavior. education about the environment began to be obtained by high school students from the curriculum that was included as an additional subject (zeeshan et al., 2021). study cordero et al. (2020) to groups of students providing confidence about the existence of good awareness about environmental conditions. 3. methods this study uses a quantitative descriptive approach to test hypotheses about the influence of economic and social factors on environmental quality in the upland areas of water catchment areas in central java. the research area covers kebumen regency, purworejo regency, wonosobo regency, magelang regency, temanggung regency, and magelang city. the independent variables that determine environmental quality consist of: economic growth, industrialization, consumption of fossil energy, waste generation, quality of human resources, and population. the dependent variable is co2 emissions. secondary data comes from the central bureau of statistics and the department of environment and forestry. quantitative analysis uses a panel data regression model, which is a combination of time series data and corss section data (gujarati and porter, 2020). time series data for a period of 20 years (2000–2019), while cross section data covers six research areas. the panel data regression model is formulated in the following equation: emiit = α0 + β1wasit + β2ecoit + β3indit + β4eduit + β5engit + β6popit + e (1) logemiit = α0 + β1logwasit + β2ecoit + β3 logindit + β4 logeduit + β5 logengit + β6logpopit + e (2) information: emi: co2 emission; was: waste; eco: economic growth; ind: industrialization; edu: average length of school; eng: energy consumption; pop: total population; α: constant; β (1,2,3,4,5,6): regression coefficient i: research area; t: time; e: error term. 4. results and discussion the research area covers six highland and water catchment areas in central java province. in the archaeological history of indonesia, this area was the place where the ancient javanese civilization of the syailendra dynasty developed. borobudur temple is located in this area. most of the gross regional domestic product (gdp) is still contributed by the agricultural sector, because the six research areas rely on the agricultural sector as the main support for the economy. the majority of the population works in the agricultural sector and industrial workers. the description of the population, area, and grdp in the study area is as follows: based on the data from table 1, gross regional domestic product (grdp), the largest population and area is in magelang regency. magelang city is the area with the least population, the narrowest area and the smallest grdp. the topography of the six research areas is at an altitude of 500–2,250 meters above sea level. based on the topographical conditions, this research area is a highland area so it is suitable for plantations, agriculture, and is a water catchment. however, over the last two decades, various business fields have gradually industrialized. the location and position of the six research areas can be seen in figure 2, given a red line. sasana, et al.: industrialization and consumption of fossil energy are the main determinants of environmental degradation in water catchment areas in indonesia international journal of energy economics and policy | vol 12 • issue 6 • 2022 171 global warming is one of the global issues that is increasingly being echoed by various parties. the effect of greenhouse gases, especially from co2 gas, is the main cause (fadholah et al., 2017). during the study period, co2 emissions in the study area tended to increase. this is due to the massive industrial activity in various fields which causes energy consumption to increase sharply. the largest contributor to co2 emissions comes from the consumption of fossil energy due to industrialization, and the amount of waste that is not managed properly. data processing of co2 emission determinant variables used panel data regression model, to determine the appropriate analysis model used chow test. the test results show that the fix effect model is more appropriate for estimating panel data. based on the results of the chow test in table 2, it is shown that the probability value of the resulting chi-square cross-section is 0.0000. this shows that the probability value is <5% (0.05), so it can be seen that the fixed effect model is more appropriate to use than the common or random effect model. the estimation results are shown in table 3 below. based on the estimation results as shown in table 3, the following regression equation is written: log(emi) = –173640.2–367.4993 log(was) + 2058.330 (eco) + 55842.08 log(ind) + 239331.9 log(edu) + 7494.443 log(eng) –25981.82 log(pop) + e (3) the results of the f test show that all variables simultaneously affect co2 emissions in the six research areas for the period 2000–2019. based on the estimation results, it shows that waste generation has no effect on co2 emissions. garbage generation tends to increase but is still well managed by residents and local governments. every day there are officers from the local government who transport residents’ waste to the final disposal site. in addition, most of the waste is from households and is organic waste. research results kiswandayani et al. (2016) stated that waste generation and co2 emissions have a negative effect. landfilling can produce tons of methane gas (ch4), and composting is beneficial for the environment. subsequent research findings show that economic growth has a positive value to co2 emissions, but it is not statistically significant. positive economic growth will increase co2 emissions. in the research area, economic growth tends to increase every year, although it fluctuates. fluctuations in economic growth have become one of the main factors for environmental degradation (li and chunshan, 2021). but the impact of economic growth on the environment also depends on the efficiency of economic activity through the type of technology used in producing goods/services. changes in the production of goods and services and inefficiencies in the processing of industrial activities are the causes. in addition, it is also supported by increased production of various types of table 2: chow test result effects test statistic d.f. prob. cross-section f 6.876252 (5,107) 0.0000 cross-section chi-square 33.157136 5 0.0000 secondary data processed with e views 10, 2022 table 3: panel data regression results with fixed effect approach variable coefficient se t-statistic prob. c –173640.2 1321662. –0.131380 0.8957 log (was) –367.4993 4127.742 –0.089032 0.9292 (eco) 2058.330 3434.916 0.599237 0.5503 log (ind) 55842.08 22705.63 2.459393 0.0155* log (edu) 239331.9 174319.1 1.372953 0.1726 log (eng) 7494.443 4367.319 1.716028 0.0891* log (pop) –25981.82 232084.3 –0.111950 0.9111 r-squared 0.400843 adj r-squared 0.339248 f statistic 6.507662 prob f statistic 0.000000 secondary data processed with eviews 10, 2022. *signifikan α=5% table 1: total population, area, and grdp year 2019 no daerah penelitian population (people) large (km2) grdp (milyar rp) 1 kebumen regency 1.197.982 1211.74 19.825 2 purworejo regency 718.316 1091.49 13.353 3 wonosobo regency 790.504 981.41 13.793 4 magelang regency 1.290.591 1102.93 23.253 5 temanggung regency 772.018 837.71 15 214 6 magelang city 122.111 16.06 6.473 badan pusat statistik central java province, 2020 figure 2: environment kuznet curve. source: shaharir and alinor, 2013 sasana, et al.: industrialization and consumption of fossil energy are the main determinants of environmental degradation in water catchment areas in indonesia international journal of energy economics and policy | vol 12 • issue 6 • 2022172 output with technology and activities to support economic growth. the results of this study are in line with research by lin and xu (2017) which shows that economic growth leads to an increase in co2 emissions in the short term, but is conducive to reducing co2 emissions in the long term, due to differences in fixed asset investment and export trade. the results of the next study stated that industrialization had a positive and significant impact on co2 emissions. industrialization has a significant effect on co2 emissions. industrialization in the research area was very massive during the period 2000–2019 and tends to increase. this is due to the support of the government and the private sector in various regions and various sectors. as a result of increasing industrialization, there is an increase in the production of output produced, so that the purchasing power and consumption level of the people increase, but on the other hand co2 emissions also tend to increase. industrialization has increased the output and income of the people. increasing people’s purchasing power of industrial output will increase the amount of waste. since 1990, the industrial sector has grown by around 174% and is thought to be the largest contributor to greenhouse gases (sheng et al., 2021). the industrial sector is the difference, how much the industry contributes to the level of co2 emissions. the research of singh et al. (2017) shows that the process of industrialization activities is identical to an activity that has an impact on increasing co2 emissions in the world (labiba and pradoto, 2018). this study is also in line with research by aye and prosper (2017) which states that industrial activities, especially the manufacturing industry, have a positive and significant influence on air pollution. in addition, according to the intergovernmental panel on climate change (ipcc) there are five main sources of co2 emissions, namely industrial processes and product use, forestry exploitation, agriculture and land use, energy use, and waste (islam et al., 2017). the results of the next study stated that industrialization had a positive and significant impact on co2 emissions. industrialization has a significant effect on co2 emissions. industrialization in the research area was very massive during the period 2000–2019 and tends to increase. this is due to the support of the government and the private sector in various regions and various sectors. as a result of increasing industrialization, there is an increase in the production of output produced, so that the purchasing power and consumption level of the people increase, but on the other hand co2 emissions also tend to increase. industrialization has increased the output and income of the people. increasing people’s purchasing power of industrial output will increase the amount of waste. since 1990, the industrial sector has grown by around 174% and is thought to be the largest contributor to greenhouse gases (sheng et al., 2021). the industrial sector is the difference, how much the industry contributes to the level of co2 emissions. the research of singh et al. (2017) shows that the process of industrialization activities is identical to an activity that has an impact on increasing co2 emissions in the world (labiba and pradoto, 2018). this study is also in line with research by aye and prosper (2017) which states that industrial activities, especially the manufacturing industry, have a positive and significant influence on air pollution. in addition, according to the intergovernmental panel on climate change (ipcc) there are five main sources of co2 emissions, namely industrial processes and product use, forestry exploitation, agriculture and land use, energy use, and waste (islam et al., 2017). the results of the next study stated that fossil energy consumption had a positive and significant effect on co2 emissions. the estimation results of the study are also supported by the research of kurniawati et al. (2021) which explains that energy consumption using lpg has a positive impact on co2 emissions. this study is also in line with the findings of riyakad and chiarakorn (2015) which state that lpg consumption has a positive and significant impact on co2 emissions. according to mikayilov et al. (2018) economic growth along with inefficient energy consumption causes figure 3: research area position source: bps jawa tengah, 2022 sasana, et al.: industrialization and consumption of fossil energy are the main determinants of environmental degradation in water catchment areas in indonesia international journal of energy economics and policy | vol 12 • issue 6 • 2022 173 a bad impact on the environment by increasing co2 emissions, and environmental damage will have negative effects on humans and nature itself. the study of sasana and aminata (2019), found that the total use of primary energy (pe) in indonesia has a positive and significant effect on co2 emissions. the results show that increasing the use of primary energy significantly increases co2 emissions. industrial intensification with fossil fuels in economic activities has a negative impact on environmental quality. this is an urgency for countries that depend on the world’s fossil fuel energy (gani, 2021). the findings of the next study explained that the population had no effect on co2 emissions. the population tends to increase but is not accompanied by an increase in co2 emissions, because most of the population works in agriculture with simple technology and a narrow land area (0.25 ha on average). so that the activities of farmers do not have an impact on co2 emissions. the estimation results of this study are supported by the research of shaari et al. (2020) which states that the population has no effect on co2 emissions. this is also in line with the research by mansoor and baserat (2018), that the population has no effect on co2 emissions because the technological development of a country is still low, causing low co2 emissions. the relationship between population and environmental conditions has become an interrelated problem when it comes to influencing co2 emission levels (yeh and liao (2017). in the broad context of the study of gyms and aminata in indonesia (2019)), population has a positive effect on increasing co2 emissions. 5. conclusion based on the results and analysis that has been carried out, the conclusions in this study are as follows: (1) industrialization in all business fields has a positive and significant effect on co2 emissions. the development of industry will increase co2 emissions in upland water catchment areas because the pollutants produced are getting bigger. consumption of fossil energy that continues to increase for industrial needs has a positive and significant effect on increasing co2 emissions. industrialization with fossil energy inputs that continues to increase will increase co2 emissions. (2) the next finding is that waste generation has no effect on co2 emissions. most of the waste generated in the research area is organic waste, and the rest can still be managed properly by the local government and the community. the number of population, and the level of education have no effect on the increase in co2 emissions because the average level of public education is still low. the same thing also happens to economic growth where this variable has no effect on co2 emissions. (3) based on the conclusions above, the researcher provides suggestions to stakeholders as follows: (a) energy raw materials for industry and transportation use energy that is more environmentally friendly, namely renewable energy. (2) implementing a non-organic waste recycling program based on the 3r concept (reduce, reuse, recycle). (3) implementing a minimal waste lifestyle, namely by refusing to use single-use plastic packaging, shopping without packaging, sorting waste from home, and recycling consumption waste into compost or craft products. references akpan, u.f., akpan, g.e. (2012), electricity consumption, carbon emissions, and economic growth in nigeria. international jurnal of energy economics and policy, 4(2), 292-303. arbulu, i., lozano, j., rey-maquieira, j. (2015), tourism and solid waste generation in europe: a panel data assesment of the environmental kuznets curve. waste management, 46, 628-636. arista, t.r., amar, s. (2019), analisis kausalitas emisi co2, konsumsi energi, pertumbuhan ekonomi, dan modal manusia di asean. jurnal kajian ekonomi dan pembangunan, 1(2), 519-532. aye, g.c., edoja, p.e. (2017), effect of economic growth on co2 emission in developing countries: evidence from a dynamic panel threshold model. cogent economics and finance, 5(1), 1-22. bach, w. (1980), fossil fuel resources and their impacts on environment and climate. international journal hydrogen energy, 6(2), 185-201. badan pusat statistik. (2018), rata-rata lama sekolah. semarang: badan pusat statistik. bartz, s., kelly, d.l. (2004), economic growth and the environment: theory and facts. resource and energy economics, 30(2), 115-149. bps jawa tengah, 2022. statistik jawa tengah tahun 2020. semarang: badan pusat statistik. chen, c. (2010), spatial inequality in municipal solid waste disposal across regions in developing countries. international journal of environment science and technology, 7(3), 447-456. chontanawat, j., hunt, l.c., dan pierse, r. (2006), causality between energy consumption and gdp. evidence from 30 oecd and 78 non-oecd countries. surrey energy economics discussion paper series seeds 113. surrey, uk: surrey energy economics centre (seec) departement of economics, university of surrey. cordero, e.c., centeno, d., todd, a.m. (2020), the role of climate change education on individual lifetime carbon emissions. plos one 15(2), 1-23. fadholah, r., setyawan, a., suryoto, s. (2017), konsumsi energi dan emisi gas rumah kaca (co2) pada proses pelaksanaan pekerjaan pekerasan jalan. matriks teknik sipil, 5(1), 326-334. fauzi, a. (2006), ekonomi sumber daya alam dan lingkungan teori dan aplikasi. jakarta: pt gramedia pustaka utama. ford, h.v., jones, n.h., davies, a.j., godfley, b.j., jambeck, j.r., napper, i.e., suckling, c.c., williams, g.j., woodwall, l.c., koldewey, h.j. (2022), the fundamental links between climate change and marine plastic pollution. science of the total environment, 806(pt 1), 150392. gani, a. (2021), fossil fuel energy and environmental performance in an extended stirpat model. journal of cleaner production, 297, 126526. gujarati, d.n., porter, d.c. (2020), basic econometrics. 4th ed. new york: mcgraw-hill higher education. islam, r., bashawir, a., ghani, a., mahyudin, e. (2017), carbon dioxide emission, energy consumption, economic growth, population, poverty and forest area : evidence from panel data analysis. international journal of energy economics and policy, 7(4), 99-106. kurniawati, b., diva maulida n, wulandari, m., nisa indah, w., revido aji, j. (2021), estimation of emissions generated by merchants at cfd on slamet riyadi surakarta city. journal of global environmental dynamics (jged) contents, 2(1), 4-7. kiswandayani, a.t, susanawati, i.d, wirosoedarmo, ruslan. 2016. komposisi sampah dan potensi emisi gas rumah kaca pada pengelolaan sampah domestik: studi kasus tpa winongo kota madiun. jurnal sumber daya alam dan lingkungan. 2, 9-17. labiba, d., pradoto, w. (2018), sebaran emisi co2 dan implikasinya terhadap penataan ruang area industri di kabupaten kendal. jurnal pengembangan kota, 6(2), 164-170. sasana, et al.: industrialization and consumption of fossil energy are the main determinants of environmental degradation in water catchment areas in indonesia international journal of energy economics and policy | vol 12 • issue 6 • 2022174 li, s., zhou, c. (2021), science of the total environment what are the impacts of demographic structure on co 2 emissions ? a regional analysis in china via heterogeneous panel estimates. science of the total environment, 650(pt 2), 2021-231. mansoor, a., sultana, b. (2018), impact of population, gdp and energy consumption on carbon emissions : evidence from pakistan using an analytic tool ipat. asian journal of economics and empirical research, 5(2), 183-190. martines, l.h. (2005), post industrial revolution human actovity and climate cahnge: why the united states must implement mandatory limits on industrial greenhouse gas emissions. journal of land use, 20(2), 407-426. mikayilov, j.i., marzio g., hasanov, f.j. (2018), the impact of economic growth on co2 emissions in azerbaijan. journal of cleaner production, 197(1), 1558-1572. rahman, m.m., saidi, k., mbarek, m.b. (2020), economic growth in south asia: the role of co2 emissions, population density, and trade openness. heliyon, 6(5), e03903. riyakad, p., chiarakorn, s. (2015), 79 energy procedia energy consumption and greenhouse gas emission from ceramic tableware production: a case study in lampang, thailand. amsterdam: elsevier b.v. sasana, h., aminata, j. (2019), energy subsidy, energy consumption, economic growth, and carbon dioxide emission: indonesian case studies. international journal of energy economics and policy, 9(2), 117-122. sasana, h., setiawan, a.h., ariyanti, f., ghozali, i. (2017), the effect of energy subsidy on the environmental quality in indonesia. international journal of energy economics and policy, 7(5), 245-249. shaari, m.s., abdul karim, c., abidin, n.c. (2020), the effects of energy consumption and national output on co2 emissions: new evidence from oic countries using a panel ardl analysis. sustainability (switzerland), 12(8), 3312. shaharir, b.m.z., dan alinor, m.b.a. (2013), the need for a new definition of sustainability. journal of indonesian economy and business, 28(2), 251-268. shamsuzzaman, m., shamsuzzoha, a., maged, a., haridy, s., bashir, h., karim, a. (2021), effective monitoring of carbon emissions from industrial sector using statistical process control. applied energy, 300, 117352. sheinbaum-pardo c., ruiz-mendoza, b.j., rodriguez-padilla, v. (2012), mexican energy policy and sustainability indicators. energy policy, 46(c), 278-283. sheng, p., li, j., zhai, m., majeed, m.u. (2021), economic growth efficiency and carbon reduciton efficiency in china: coupling or decoupling. energy reports, 7, 289-299. singh, d., pachauri, s., zerriffi, h. (2017), environmental payoffs of lpg cooking in india. environmental research letters, 12(11), 1-8. tchobanoglous, g., theisen h., dan vigil s.a. (1993), intergrated solid waste management: engineering principle and management issue. new york: mcgraw hill inc. todaro, m.p., smith, s.c. (2009), economic development. boston: addison-wesley. uddin, m.m. (2014), causal relationship between education, carbon dioxide (co2) emission and economic growth in bangladesh. iosr journal of humanities and social science, 19(4), 60-67. xu, bin & lin, boqiang, 2017. "factors affecting co2 emissions in china’s agriculture sector: evidence from geographically weighted regression model," energy policy, elsevier, 104, 404-414. yeh, j.c., chih-hsiang, l. (2017), impact of population and economic growth on carbon emissions in taiwan using an analytic tool stirpat. sustainable environment research, 27(1), 41-48. yusgiantoro, p. (2000), ekonomi energi: teori dan praktik. jakarta: lp3es. zeeshan, m., sha, l., tomlinson, k.w., azeez p.a. (2021), factors shaping students perception of climate change in the western himalayas, jammu and kashmir, india. current research in environmental sustainability, 3, 100035. zheng, j., and suh, s.. 2019. strategies to reduce the global carbon footprint of plastics. nature climate change. no. 9. 374-378 tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(3), 1-7. international journal of energy economics and policy | vol 12 • issue 3 • 2022 1 predictive control algorithm for a variable load hybrid power system on the basis of power output forecast andrey i. vlasov*, boris v. artemiev, kirill v. selivanov, kirill s. mironov, jasur o. isroilov bauman moscow state technical university, russian federation. *email: vlasov.a.i@ymservices.ru received: 03 january 2022 accepted: 06 april 2022 doi: https://doi.org/10.32479/ijeep.12912 abstract harmonious integration of renewable energy sources into current energy systems has taken on increasing importance amid the scarcity of carbon resources. among the key problems is the imbalance in power consumption, power generation, and significant peak overloads. to deal with this issue, an intelligent software and hardware system is needed, which will effectively implement predictive control algorithms for various energy sources. the research examines the fundamental provisions of the concept of predictive control over a variable load hybrid power system on the basis of power output forecast. the analysis performed has allowed developing a method of predictive control over the power system in a small locality based on machine learning algorithms. the method was tested using an electric power complex simulation, which included four energy sources (solar panel, wind turbines, small hydrogenerator, and standard carbon-fueled generator). the proposed predictive control method has proved to be productive. the algorithms have allowed diversifying the reliability of power supply by ensuring the sustainability of the power grid. keywords: hybrid power system, energy efficiency, renewable energy sources, power balance, decision tree methodology jel classifications: l94, q42, q47 1. introduction renewable energy sources (res) are becoming increasingly widespread (makarova et al., 2019; anagnostopoulos et al., 2020). installations converting the energy of physical processes into electricity are commonplace: wind turbines, solar panels, hydroelectric power stations, geothermal power plants, etc. (renewables 2021 global status report). the reason behind this trend is the constantly growing consumption of energy, which, in order to be produced, requires a rising amount of expensive fuel resources. the increased use of extractable resources leads to their rapid depletion, and the burning of them causes serious damage to the environment (rahman et al., 2020). electricity generation using res exhibits a broad spread of timerelated characteristics, variable load, and imperfect energy storage systems. in order to tackle these problems, a smart software and hardware system is needed, which will switch automatically between different energy sources based on the results of the generated and consumed power analysis. the article aims to develop a concept for implementing predictive control of a variable load hybrid energy system including power output on renewable and non-renewable energy sources and batteries. during the study, the following objectives were attained: to develop an algorithm for controlling the power system that provides uninterrupted power supply to a small locality with a hybrid power system; to implement predictive analysis functions based on the machine learning method that automatically selects the best energy sources at a given time under certain conditions; to carry out a predictive assessment of a locality’s power consumption. the forecast results are primarily focused on solving applied problems of resource conservation and reducing the use of non-renewable energy sources for power supply of small and this journal is licensed under a creative commons attribution 4.0 international license vlasov, et al.: predictive control algorithm for a variable load hybrid power system on the basis of power output forecast international journal of energy economics and policy | vol 12 • issue 3 • 20222 medium-sized localities (smls) depending on the consumer value of electricity. 2. literature review analyze the development of hybrid power systems. in the global practice, there is no clear conventional definition of the term “hybrid power system.” it is logical to assume that any power system, which combines several energy sources is considered a hybrid one. a closer study shows that most power systems are of a hybrid nature. with respect to electric power capacity, the concept of hybrid was first used in the car industry. hybrid vehicles combine an internal combustion engine and an electric motor. the next step involves the active promotion of electric cars that were able to store more power in batteries due to reverse charging technology (yaïci et al., 2020). building upon this, we can make an assumption about significant advantages provided by the hybrid power supply method. virtually all renewables-based power supply complexes have energy storage devices that act as an inertial element in the event of short-term power outages, and as sources of stored energy in the event of an increase in their number. due to changes in natural conditions, the stochasticity of renewables-based power generation is often compensated by traditional fuel generators included in electric power systems. it is quite common to combine wind turbines and solar panels in a single complex; in some cases, small hydroelectric power plants are added to them (mammadov, 2019). to determine what energy sources to use, we analyze the advantages and disadvantages of the main methods of industrial renewable electricity generation. 2.1. solar energy there is no need to purchase fuel cells and expensive service equipment to derive it (helios house, n.d.). among the key disadvantages are a frequent clean of solar panels from dust and pollution, power harvesting during sun hours, and weather dependency. figure 1 shows the average energy yield of solar panels per day in central russia during 1 year. insolation varies according to weather conditions and reaches its maximum on clear and cloudless days. figure 2 presents energy yield of solar panels during a clear/cloudy summer day. thus, the efficiency of electricity generation using solar panels is affected by numerous factors, such as the length of the daylight hours and cloudiness. however, with the weather forecast and sun rise and set times known, it is possible to determine the estimated energy yield by solar panels with high accuracy. 2.2. wind turbines along with solar energy, wind turbines are also gaining in popularity (renewables 2021 global status report; echeistov et al., 2018). to obtain wind energy, an open area with regular abundant air currents is a sufficient criterion. on the other hand, the installation and maintenance of a wind turbine entail considerable costs. wind turbine power output is dependent on the strength of the wind. the average energy yield of a hy1000 wind turbine at a height of 15 m per day during 1 year is given in figure 3. wind turbines produce the maximum power output with medium or strong air flows. if wind speeds exceed the cut-out speed, power stops being generated. the relationship between wind speed and the amount of electricity delivered by a turbine is demonstrated in figure 4. based on the wind speed data, it is possible to determine the estimated power output. figure 1: average energy yield of solar panels per day during 1 year source: helios house, n.d. figure 2: energy yield of solar panels during a clear/cloudy summer day source: helios house, n.d. figure 3: average energy yield of a wind turbine at a height of 15 m per day during 1 year source: khan et al., 2019 vlasov, et al.: predictive control algorithm for a variable load hybrid power system on the basis of power output forecast international journal of energy economics and policy | vol 12 • issue 3 • 2022 3 however, as with solar panels, the wind turbines-based power system should include cyclic energy storage units, i.e. batteries, in order to maintain its sustainability (renewables 2021 global status report; todorov et al., 2019). renewables-based power generating systems in locations with a significant amount of sunlight (california [usa], spain) or the active movement of air masses (norway’s shores) can reduce an average household’s energy consumption from the central electrical power grid by 20–25%; in some cases, this share reaches up to 80–90% (todorov et al., 2019; stave et al., 2021). the types of energy sources used in different countries vary significantly. the structure of production by sources of energy in russia is represented by thermal power stations (64%), nuclear power plants (19%), hydroelectric power stations (17%), and renewable sources (kuzmin et al., 2019). having analyzed the main sources of energy generation and storage, we can conclude that a complete transition to res is currently impossible. the best option is to implement a distributed hybrid scheme that provides for the use of alternative sources under favorable conditions, thus supplying smls with electricity and, at the same time, storing it in batteries. in situations, where such generation is impossible, it is expedient to use either the charge stored in the batteries or a backup energy source, such as a fuel generator. it is worth noting that the widespread use of renewable energy has complicated the problem of uneven electricity consumption by adding a new variable, since the amount of electricity generated by renewables-based systems depend on the stochastic nature of weather conditions. however, most electrical grids are designed to deal with a change in capacity of up to 20%. in modern conditions, this interval is far from enough when forming a hybrid energy system. despite the recent introduction of smart electricity metering technologies, the problem of imbalanced power consumption during the day and significant peak overloads still persists. another challenge is a lack of single electrical networks between states and even within one state. 3. methods and data most renewable energy sources depend on external conditions, so it is reasonable to implement a hybrid system that includes renewables-based generating capacities, storage systems, and backup generating capacities based on non-renewable energy sources. at that, it is of high importance to ensure correct automatic switching between different energy sources using the findings of predictive analytics and smart data processing capabilities (crespo márquez et al., 2020; selivanov et al., 2021; todorov et al., 2020). the general model of the hybrid distributed power generation for smls is presented in figure 5. determine the conditions for the effective use of various energy sources in a hybrid power supply model. the power consumption of a locality varies and is dependent on a range of different factors. production capacities available in the territory are not taken into account as they are designed for special-purpose consumers and recognized as an individual power consumption unit. figure 6 shows the locality’s power consumption per day in summer/winter season. by distributing data according to the factors that affect generation capacity and power consumption, it is possible to create a smart power management system based on power output, which will determine the best ways to use various energy sources based on figure 5: model of a hybrid power supply station in a small locality figure 4: relationship between the wind speed and the wind turbine power output source: khan et al., 2019 figure 6: power consumption per day in summer/winter season source: zhou et al., 2020 vlasov, et al.: predictive control algorithm for a variable load hybrid power system on the basis of power output forecast international journal of energy economics and policy | vol 12 • issue 3 • 20224 input data (jamil et al., 2021; shakhnov et al., 2019; kononov and kononov, 2018; hernández-cedeño et al., 2021). in the process of constructing an experimental model of a system for predictive control of a hybrid power system, the following provisions were laid down: 1. possibility of automating the most important control functions, primarily safety functions (automated shutdown of a part of the system) 2. realization of the power system management based on the function of pollutant emissions minimization (according to the function embedded in the algorithm, the system tends to use renewable energy sources in the first place, and traditional energy sources are utilized on a second-priority basis in the event of a power shortage) 3. possibility of exercising autonomous control over power sources (the system performs real-time monitoring of the power harvested from renewable energy sources and analyzes power consumption; if the amount of power consumed significantly exceeds the incoming power produced by renewable energy sources, the system automatically enables traditional fuel generators) 4. possibility of performing predictive analysis of the renewables-generated power based on the weather forecast (the system monitors the weather forecast and estimates power balance on its basis, then it determines the required amount of extra fuel that will be needed to provide the adequate level of power consumption) 5. possibility of accumulating surplus energy from renewable energy sources and using it when needed (electricity can be stored in batteries or in the form of thermal energy). 4. results and discussion to realize automatic control of the power supply system in smls, a hardware and software complex (selivanov et al., 2021) is developed that implements the concept of predictive control of energy efficiency based on power output forecast (shcherbatov, 2019; arakelian et al., 2019; shcherbatov et al., 2019). this concept is in line with the trends in infrastructure solutions for the internet of things (yudin et al., 2017; grigoriev et al., 2018). it allows combining the decisionmaking module and heterogeneous sensor elements with energy generation and transmission technologies (figure 7). the proposed hardware and software complex is classed as embedded solutions, the development and debugging of which imposes a number of requirements. the most relevant issues are the application of basic universal structures, ensuring the flexibility and reconfigurability of the control system used, and the possibility of operational maintenance and predictive repair (yudin et al., 2017; khan et al., 2021; andryushin et al., 2020). the hardware and software complex is built according to the agent-manager scheme; agent applications collect heterogeneous data from the sensor network elements and transfer them to management modules. to serve the smart functions of the system, machine learning algorithms are used, which select the best option for generating electricity based on the input parameters (sharifzadeh et al., 2019; prudius et al., 2019). predictive control algorithms are designed to increase the efficiency of renewables-based electric power complexes by coordinating the incoming power and the power consumption. if coordination is impossible or the incoming power significantly exceeds the consumed power, predictive control ensures power accumulation. if the incoming power is less than the power consumption, it automatically enacts additional generating capacity to harvest the required amount of electricity and meet energy demands. the quantitative parameters of the electric power complex (power consumption, power generation, the amount of batterystored power, generation cost of 1 kw using different methods of electricity generation, etc.) can be considered predicates with their own tolerance range. if the predicates go beyond it, the algorithm will perform necessary control actions to balance the system. based on the predicates and the established tolerance range, it is possible to form a decision tree, which primarily aims at reaching the maximum efficiency for a given parameter (yuldashev and vlasov, 2020; bakhtadze et al., 2021). monitoring data are transferred to a single cloud storage. the key estimated parameters are the following: hourly costs of active and reactive power (the shift with the highest and lowest power demand during the day); electrical energy quality indicators (voltage deviation, fluctuation, asymmetry, and non-sinusoidal voltage) during the day; load current of electrical networks, transformers and electrical receivers; on/off time of electrical receivers during the day. general predictive control algorithm for energy efficiency of a variable load hybrid power system based on power output forecast is shown in figure 8 (part 1) and figure 9 (part 2). the proposed method was tested using simulation modelling of an electric power complex, which included four power sources (a solar panel, a wind turbine, a small hydrogenerator, and a standard carbon-fueled generator). first, power consumption and generation are measured and the power balance is calculated. if the power balance is positive (generated power exceeds consumed power), the algorithm evaluates the functioning of a standard carbon-fueled generator and, if it is on, turns it off. if the positive power balance is preserved, the algorithm turns off the hydrogenerator and accumulates excess power in the following order – battery and then kinetic energy of water. once all energy carriers are charged and the power balance is still positive, generating capacities are gradually shutting down, and solar panels are the first to turn off. to stop power generation completely or maintain it at a low level, the wind turbine is switched to ballast resistance. if the generated power is not enough to satisfy electricity demand, the algorithm receives and processes the negative power balance. at the first step, all wind generators in the electric power complex are turned on; at the second step, solar panels are activated. with every power generating unit turned on, the algorithm compares the power balance, and, if it is still negative, initiates more expensive power sources. the hydrogenerator is activated following solar panels and wind turbines. the switching sequence is due to the vlasov, et al.: predictive control algorithm for a variable load hybrid power system on the basis of power output forecast international journal of energy economics and policy | vol 12 • issue 3 • 2022 5 fact that the first two power sources are stochastic, but infinite in terms of incoming power (no fuel is needed). hydrogeneration is limited by the amount of water stored (if available), and it is mostly recommended to use it sparingly. next, the battery in power generation mode turns on. if it is impossible to meet the electricity demand after activating all the available alternative energy sources due to insufficiently small power input and/or high peak power consumption, the algorithm switches on the standard carbon-fueled generator. the cyclic algorithm periodically scans the power balance and, if the power consumption falls, gradually turns off the power sources in reverse order. the proposed predictive control algorithm for energy efficiency on the basis of power output forecast has demonstrated its productivity in ensuring the power balance, which allowed diversifying the power supply and improving the reliability of power systems (if the centralized power supply system shuts down, renewables-based systems remain operational). moreover, the batteries embedded in renewables-based power supply systems provide additional energy storage used if all the other energy sources are unavailable. it is noteworthy that the algorithm can be applied in locations with a serious power shortage and the need to purchase it from any producer even with its additional conversion to be transmitted through public power grids. the algorithm is two-dimensional and controls the power output depending on the power consumption, which imposes a number of restrictions. it does not take into account the possibility to control the load and increase it in case of the incoming power is figure 8: predictive control algorithm for energy efficiency on the basis of power output forecast (part 1) figure 7: concept of a hardware and software complex for predictive control of energy efficiency based on the power output forecast vlasov, et al.: predictive control algorithm for a variable load hybrid power system on the basis of power output forecast international journal of energy economics and policy | vol 12 • issue 3 • 20226 significant and energy storage is already filled. theoretically, the power consumption load can be reduced in case of a shortage of incoming power and then distributed evenly over a certain period of time. further research will focus on testing various methods of power matching and power accumulation. conversion of res energy into other types of energy suitable for further (delayed) use is of primary interest. at that, attention should be paid to controlling the power balance and a more detailed consideration of the class of consumers whose power consumption can be managed by distributing it over time. 5. conclusion as found in the research, a complete transition to res is currently impossible. the best option is to implement a distributed hybrid scheme that provides for the use of alternative renewable energy sources in favorable conditions, thus supplying smls with electricity. the quantitative parameters of the electric power complex can be considered as predicates with their own tolerance range. based on the predicates and the established tolerance range, it is possible to form a decision tree, which primarily focuses on reaching the maximum efficiency for a particular parameter. to realize automatic control of the hybrid power supply system, a hardware and software complex is proposed that follows the established algorithm. predictive control algorithms are designed to improve the efficiency of renewables-based electric power complexes by coordinating the incoming power and the power consumption load. the proposed method of predictive control has proved its productivity in a simulation model for ensuring energy balance. the algorithm has allowed diversifying the power supply. 6. acknowledgments the results were partially obtained within the project under the development program of bauman moscow state technical university as part of the priority-2030 federal academic leadership program. references anagnostopoulos, t., ntanos, s., gkika, e., asonitou, s., kyriakopoulos, g.l. (2020), intelligent predictive analytics for sustainable business investment in renewable energy sources. sustainability, 12(7), 2817. andryushin, a., shcherbatov, i., dolbikova, n., kuznetsova, a., tsurikov, g. (2020), outlier detection in predictive analytics for energy equipment. studies in systems, decision and control, 259, 193-203. arakelian, e., shcherbatov, i., tsurikov, g., titov, f., pashchenko, a. (2019), creation of predictive analytics system for power energy objects. in: proceedings of 2019 12th international conference “management of large-scale system development” (mlsd 2019). bakhtadze, n., maximov, e., maximova, n. (2021), digital identification algorithms for primary frequency control in unified power system. mathematics, 9(22), 2875. crespo márquez, a., fernández, j.f.g., del castillo, a.c. (2020). integrating artificial intelligent techniques and continuous time simulation modelling. practical predictive analytics for energy efficiency and failure detection. computers in industry, 115, 103164. echeistov, v.v., krivoshein, a.i., shakhnov, v.a., filin, s.s., vlasov, a.i., migalin, v.s. (2018), an information system of predictive maintenance analytical support of industrial equipment. journal of applied engineering science, 16(4), 515-522. grigoriev, p.v., krivoshein, a.i., shakhnov, v.a., filin, s.s., vlasov, a.i., migalin, v.s. (2018), smart management of technologies: predictive maintenance of industrial equipment using wireless sensor networks. entrepreneurship and sustainability issues, 6(2), 489-502. helios house. (n.d.), online calculator of solar, wind, and thermal figure 9: predictive control algorithm for energy efficiency on the basis of power output forecast (part 2) vlasov, et al.: predictive control algorithm for a variable load hybrid power system on the basis of power output forecast international journal of energy economics and policy | vol 12 • issue 3 • 2022 7 energy. available from: https://www.helios-house.ru/on-linekalkulyator.html hernández-cedeño, i., nelson, p.f., anglés-hernández, m. (2021), social and environmental conflict analysis on energy projects: bayesian predictive network approach. energy policy, 157, 112515. jamil, f., iqbal, n., imran, a.s., kim, d. (2021), peer-to-peer energy trading mechanism based on blockchain and machine learning for sustainable electrical power supply in smart grid. ieee access, 9, 39193-39217. khan, a.n., iqbal, n., rizwan, a., kim, d.h., ahmad, r. (2021), an ensemble energy consumption forecasting model based on spatialtemporal clustering analysis in residential buildings. energies, 14(11), 14113020. khan, m.a., çamur, h., kassem, y. (2019), modeling predictive assessment of wind energy potential as a power generation sources at some selected locations in pakistan. modeling earth systems and environment, 5(2), 555-569. kononov, y.d., kononov, d.y. (2018), analytical methods for forecasting development in the electric power industry. studies on russian economic development, 29(5), 527-532. kuzmin, e.a., volkova, e.e., fomina, a.v. (2019), research on the concentration of companies in the electric power market of russia. international journal of energy economics and policy, 9(1), 130-136. makarova, a.a., mitrovoy, t.a., kulagina, v.a. (2019), the energy industry development in the world and russia 2019. eri ras the moscow school of management skolkovo. p66-69. mammadov, f.f. (2019), fuzzy logic controller application in hybrid solar and wind energy system. 2019 international artificial intelligence and data processing symposium (idap). p1-4. prudius, a.a., karpunin, a.a., vlasov, a.i. (2019), analysis of machine learning methods to improve efficiency of big data processing in industry 4.0. journal of physics conference series 1333(3), 032065. rahman, m.m., velayutham, e. (2020), renewable and non-renewable energy consumption-economic growth nexus: new evidence from south asia. renewable energy, 147, 399-408. renewables 2021 global status report. market and industry trends. p89-161. selivanov, k.v., vlasov, a.i., nalimov, n.a. (2021), software package for managing the state of systems based on forecast of incoming power. computer program registration certificate 2021661541 of july 13, 2021. application no. 2021660765 of july 7, 2021. shakhnov, v.a., filin, s.s., krivoshein, a.i., vlasov, a.i. (2019), sustainable energy systems in the digital economy: concept of smart machines. entrepreneurship and sustainability issues, 6(4), 1975-1986. sharifzadeh, m., sikinioti-lock, a., shah, n. (2019), machine-learning methods for integrated renewable power generation: a comparative study of artificial neural networks, support vector regression, and gaussian process regression. renewable and sustainable energy reviews, 108, 513-538. shcherbatov, i.a. (2019), current state of predictive analytics systems development in the energy sector. journal of advanced research in technical science, 14(2), 118-123. shcherbatov, i.a., tsurikov, g.n., maksimova, e.v., bukanyov, a.n., nazarenko, a.s. (2019), data processing in predictive analytics system for energy facilities. journal of advanced research in technical science, 16, 92-94. stave, v.s., dynge, m.f., farahmand, h., korpås, m., cali, ü. (2021), optimal utilisation of grid capacity for connection of new renewable power plants in norway. 2021 international conference on smart energy systems and technologies (sest). p1-6. todorov, g.n., vlasov, a.i., volkova, e.e., osintseva, m.a. (2020), sustainability in local power supply systems of production facilities where there is the compensatory use of renewable energy sources. international journal of energy economics and policy, 10(3), 14-23. todorov, g.n., volkova, e.e., vlasov, a.i., nikitina, n.i. (2019), modeling energy-efficient consumption at industrial enterprises. international journal of energy economics and policy, 9(2), 10-18. yaïci, w., kouchachvili, l., entchev, e., longo, m. (2020), performance analysis of battery/supercapacitor hybrid energy source for the city electric buses and electric cars. 2020 ieee international conference on environment and electrical engineering and 2020 ieee industrial and commercial power systems europe (eeeic/ i&cps europe), p1-6. yudin, a.v., shakhnov, v.a., usov, k.a., vlasov, a.i., salmina, m.a. (2017), design methods of teaching the development of internet of things components with considering predictive maintenance on the basis of mechatronic devices. international journal of applied engineering research, 12(20), 9390-9396. yuldashev, m.n., vlasov, a.i. (2020), software package for dynamic classification of an object based on ranges of decision tree predicates. computer program registration certificate 2020665601 of november 27, 2020. application no. 2020664889 of november 20, 2020. zhou, z., wang, b., dong, m., ota, k. (2020), secure and efficient vehicle-to-grid energy trading in cyber physical systems: integration of blockchain and edge computing. ieee transactions on systems, man, and cybernetics: systems, 50(1), 43-57. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 2 • 2022 111 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(2), 111-119. implementation of the hierarchical analytical process in the selection of the best source of renewable energy in the colombian caribbean region christian manuel moreno rocha*, josé ricardo nuñez alvarez, daniel a. díaz castillo, esnaider d. florian domíngue, juan camilo barrera hernandez department of energy, universidad de la costa (cuc), barranquilla, atlántico, colombia. *email: cmoreno7@cuc.edu.co received: 10 october 2021 accepted: 05 january 2022 doi: https://doi.org/10.32479/ijeep.12537 abstract in this study, the analytic hierarchy process methodology is implemented to provide decision criteria in the selection, planning, and development of electric power generation projects from renewable energy sources in the caribbean region of colombia. six sources of renewable energy; biomass combustion; anaerobic digestion of biomass; biogas landfills; waste incineration; photovoltaic energy and solar thermal radiation were considered in this study due to their energy potential in rural areas and areas not interconnected to the national electricity system. to determine the order of priority in the development of energy conversion technologies, a questionnaire was developed and sent to a group of experts. given the need to generate electricity sustainably, the information was analyzed under four main criteria: technical, environmental, social, and economic. sixteen additional sub-criteria were selected based on a literature review. in general, the economic criterion is the most relevant in the area due to the high investment and operating costs of electricity generation. the social criterion highlights the opportunity to create new jobs, while the environmental criterion highlights the component of substitution of renewable energy, a key aspect in the diversification of the energy matrix, which is part of the country’s political agenda. regarding the technological component, photovoltaic energy seems the most favorable due to its low environmental impact and the considerable reduction in prices experienced by the solar panel market in recent years. keywords: hierarchical analytical process ahp, renewable energy, decision making, multi-criteria jel classifications: c44, c45, c46 1. introduction one of the greatest challenges facing humanity today lies in obtaining electrical energy that meets quality standard parameters, that is always available, that is easily accessible, and that does not pollute the environment. the accessibility objective is directly linked to the pricing policy that is managed, availability is linked to the quality, safety and continuity of the electricity supply, and acceptability is fundamentally linked to a set of social, economic and environmental objectives. the technological advances that have been presented in the energy sector have been able to respond to each of the aforementioned objectives or factors, and have contributed, to a greater or lesser extent, to satisfy social, economic and environmental demands (diaz et al., 2021; ochoa et al., 2019; ochoa et al., 2019), although there is still much to analyze and investigate. on the other hand, scientific studies have made it possible to know the probable date on which fossil fuels and some minerals may be exhausted, taking into account how the historical evolution has been in terms of their extraction and use (gaete-morales et al., 2019), so the study and the use of renewable sources of energy plays a fundamental role in reversing this alarming situation. the daily use and consumption of electricity is a vital service for the development and evolution of a country, constituting the main this journal is licensed under a creative commons attribution 4.0 international license rocha, et al.: implementation of the hierarchical analytical process in the selection of the best source of renewable energy in the colombian caribbean region international journal of energy economics and policy | vol 12 • issue 2 • 2022112 input in the vast majority of industrial activities worldwide, which sustain the economy and the generation of jobs. furthermore, electrical energy is an essential factor to guarantee the quality of life of the inhabitants (ferretti and montibeller, 2016). in colombia, as in other countries in the region, there is great interest in increasing the coverage and electricity supply to the entire territory, guaranteeing the quality of said energy and achieving a diverse energy matrix where the use of renewable sources predominates of energy (hacatoglu et al., 2015). government policies can affect the two indicators mentioned and also the sales prices of renewable energy projects. many policies are applied around the world to support research and development investments, for example, low interest rate investment incentives, tax incentives such as accelerated depreciation opportunities, fee incentives such as feeding fees (fit), certificates negotiable, among others; however, the planning, evaluation and selection of alternative energies for an adequate investment is a complex decision. in the first place, it is very important to consider that in addition to satisfying the projected demand, electric power generation plants must be economically viable and be environmentally and socially sustainable. taking into account these criteria and others that have been used in recent years (ghavami, 2019), our research aims to provide a solution that allows selecting the best investment alternative in terms of electricity generation using renewable energy sources, also considering the option of hybrid systems (nuñez et al., 2020; zeng et al., 2019). companies that invest in renewable energies must choose between different technologies, diverse structures and varied costs and uncertainties, so it is essential to select those that offer the highest profitability for a given level of risk (john et al., 2014); however, making a proper selection among several alternatives is not an easy task. investment decisions in renewable energy depend mainly on economic, environmental and technical aspects, therefore there is a great need to develop tools that support the decisions of potential investors in renewable energy (algarín et al., 2017). the objective of this research seeks to develop a mathematical model that allows choosing the best investment alternative in the use of energy sources. that is why the analytic hierarchy process (ahp) decision-making aid method is proposed, which establishes, based on the multi-criteria decision method, the importance weights of both the criteria and the alternatives evaluated (saaty, 1980). the model has a differentiating factor in terms of other investigations that have been developed due to the implementation of ahp as a solution method to address the best solution taking into account qualitative criteria such as economic and environmental and quantitative criteria such as technical, social, environmental, pathways. access, among others. in the development of the research, energy planning in colombia in the last 10 years is taken into account, considering changes that may occur in the availability of resources and a limited investment budget. as a result, there is a tool that serves as a guide for government entities or other private companies to access electricity generation projects using renewable energies (suresh et al., 2020; mehrjerdi, 2019; budes et al., 2020). similar investigations have been initiated in colombia, with the support of the ministry of mines and energy, aimed at selecting the best power generation alternatives to solve the connectivity problem of non-interconnected zones (niz) (robles-algarín et al., 2018). in 1999, the mining-energy planning unit (upme) contracted the design of a structural, institutional and financial plan for the supply of electricity to the niz of the national territory with the collaboration of the communities and the private sector (rosso et al., 2017). the study carried out in (vides-prado et al., 2018) indicates that in colombia projects involving niz are analyzed taking into account technical feasibility and economic viability, without taking into account other evaluation criteria. however, this traditional scheme is modified by investigations such as those of (alptekin, 2021; zhou, 2012; zhou et al., 2019) where, in addition to technical and economic feasibility, other criteria such as social and natural are considered. in (robles-algarín et al., 2018) the methodology of sustainable livelihoods is used for the selection of projects that seek to supply electrical energy to the town of calamar, guaviare, colombia, using renewable energy sources. the study carried out in (garces, et al., 2021) shows the evaluation of policies for the electrification of niz in southwestern colombia and in (cherni et al., 2007) an analytical tool called sustainable rural energy decision support system is presented, which aims to that of maximizing the five main criteria that represent a locality (physical, financial, natural, social and human), and whose variations depend mainly on the provision of electrical energy and other complementary productive and social projects. the energy institute of the national university of colombia, medellín campus, has developed planning tools and methodologies for the development of rural electrification, studying various objectives and genetic algorithms (mamaghani et al., 2016; balbismorejón et al., 2021). in the work of (moghadam and lombardi, 2019) an economic, technological and environmental optimization model of energy generation projects is developed with the aim of minimizing greenhouse gases, economic energy costs and increasing energy efficiency; the uncertainty treatment was carried out using monte carlo simulation (milanés-hermosilla et al., 2021). these investigations, both nationally and internationally, help to set an important precedent for future research on energy planning in colombia and serve as a starting point for our work focused on energy planning in the colombian caribbean region (silvera et al 2021; zanghelini et al., 2018). this article is organized in three sections; in the first one, a review of the scientific results on various evaluation methods on the application of renewable energies is presented. in the second section, the method under study is applied, analyzing the selection criteria and sub-criteria. in third place, the discussion of the results obtained and the comparison with those of other researchers is presented, and finally the conclusions of the work are provided. 2. materials and methods this research performs an analysis to determine the renewable energy potential to be implemented in the colombian caribbean region using the hierarchical analytical process, also known as ahp. in this analysis, it is necessary to evaluate a series of criteria rocha, et al.: implementation of the hierarchical analytical process in the selection of the best source of renewable energy in the colombian caribbean region international journal of energy economics and policy | vol 12 • issue 2 • 2022 113 and sub-criteria associated with the different energy alternatives of renewable energies and also the environmental, economic and social problems of the communities that comprise this area. that is why this research aims to propose a hierarchy of use of renewable energy sources taking into account the energy potential of each area in particular. 2.1. renewable energy alternatives in the study and analysis of the potential of renewable energies in the colombian caribbean region, technical, social, environmental and economic criteria are evaluated, as well as a series of subcriteria associated with them. the alternatives for the use of renewable energies present in the area under study are also taken into account. figure 1 shows the hierarchical structure of the decision-making problem according to the criteria, sub-criteria and alternatives considered. on various occasions, the social, economic and environmental problems of the communities become more complex and to find the best solution requires the analysis of many variables, criteria, studies and other aspects that justify obtaining the most viable solution from all points of view. therefore, it is proposed to use the ahp method due to its advantages to identify problems and propose solutions according to the best response to complex and difficult decisions (escrivá, 2016; ashek-al-aziz et al., 2020). 2.2. model training decision-making is a very important mechanism that becomes more complex every day, fundamentally due to the number of variables that are present and the constant transformation of the scenarios in which we work. in this context, multi-criteria methodologies are born as a way to face this type of challenge. the ahp methodology contemplates the construction of a hierarchical structure to define the problem in its entirety and includes the creation of goals, the definition of evaluation criteria and subcriteria, the identification of alternatives to solve the problem, until a ranking of the best options is obtained. to maximize and facilitate the choice of the best energy source that can be used in a certain area. among the advantages of the ahp method are that it presents mathematical support, allows to break down and analyze a problem by parts, analyzes quantitative and qualitative criteria and allows verifying the consistency index by making corrections if necessary. the hierarchical analysis process developed by (saaty, 1980) is based on the conception of a complex problem with multiple criteria that can be solved by classifying the problems posed, for which subjective evaluations are required on the relative importance of each of the criteria and also their preference for each of the decision alternatives. with the result of applying the ahp method, it is possible to generate a ranking with the priorities of each of the decision alternatives (escrivá, 2016). the ahp method tries to break down a problem and then unite all the solutions of the subproblems into a conclusion and is divided into 4 fundamental stages: 2.2.1. stage 1. modeling in this stage the hierarchical order of the problem is carried out, the objectives, criteria and alternatives to be implemented are defined. the objective of the process is defined according to the criteria of experts. then the alternatives through which we want to achieve our objective are defined and consequently, the criteria to be evaluated are determined. these criteria must take into account the problem and must identify the attributes that contribute to a good decision. these criteria must be measured and quantified in order to use a comparison scale (mamaghani et al., 2016). the solution of the problem passes 3 levels, the first level is the fundamental objective that we must achieve to solve the problem, in the second level the criteria would be located according to a descending hierarchical structure of one or more specific objectives, which will allow evaluating the alternatives for each of the criteria. in the third and last level would be the alternatives in the decision-making of (escrivá, 2016). 2.2.2. stage 2. reviews knowing the alternatives and defining the criteria, we proceed to order and weight each of the criteria in the selection of alternatives. the objective of this procedure is to measure the importance figure 1: ahp hierarchical analytical process modeling rocha, et al.: implementation of the hierarchical analytical process in the selection of the best source of renewable energy in the colombian caribbean region international journal of energy economics and policy | vol 12 • issue 2 • 2022114 that the decision-maker assigns to each criterion. it is carried out through paired comparisons, that is, each criterion or alternative i is compared with each criterion or alternative j. an underlying scale with values from 1 to 9 is used to rate the relative preferences of the items (john et al., 2014; rosso et al., 2017), table 1. with this, we proceed to construct the matrix of paired comparisons, it will be a square matrix anxn = [aij], with 1≤ i, j ≤ n. for the construction of the matrix, the following axioms must be taken into account: axiom of reciprocity: if a is a matrix of paired comparisons, then it is true that if aij = x then aji = 1/x with 1/9 ≤ x ≤ 9. for the reciprocity property only n (n-1)/2 comparisons are needed: axioma of homogeneity: the elements that are compared to each other will be of the same order of magnitude and hierarchy. axioma of independence: when the decision-maker makes the comparisons, it is assumed that the criteria do not depend on the properties of the different alternatives. axiom of expectations: to make a decision, the hierarchy is assumed to be complete (algarín et al., 2017; escrivá, 2016). fulfilling the previous axioms, it is possible to determine the paired comparison matrix, table 2. 2.2.3. stage 3. prioritization and synthesis after having the paired comparison matrix, the prioritization is calculated. this emphasizes the importance that the decision maker has assigned to each element. the priorities are expressed in the form of vectors. the priorities are expressed in the form of vectors. let a matrix a (nxn) be like the one obtained when carrying out the paired comparisons, we call the eigenvalues or proper eigenvectors of a (ʎ1, ʎ2,…, ʎn) to the solutions of the equation: det (a-ʎi) = 0. the principal eigenvalue of the matrix (ʎmax) is the maximum of the eigenvalues obtained by performing the previous equation, n is the dominant eigenvalue of {a} and {a} the associated eigenvector. the eigenvector associated with the dominant value is the weight vector to be obtained. when the eigenvector obtained is that of the criteria matrix, we will call it vc, and it indicates the weight or relative importance that each of the selected criteria has in the assessment of the set of alternatives on which we are going to work. when the eigenvector obtained is that of the alternative matrix for a given criterion, we will call it vai (column vector), which indicates the weight or relative importance of each of the alternatives for criterion i. as many eigenvectors as criteria will be obtained. one consideration to take into account that affects the final decision will be the consistency of the decisions of the decisionmaker when filling in the paired matrices (vinogradova‐ zinkevič et al., 2021). this is because the decision-maker makes a personal judgment, which can lead to a certain inconsistency that will have to be evaluated to see if it is below the limits (escrivá, 2016). 2.2.4. stage 4. consistency analysis this analysis takes into account the subjectivity of the decision maker. when performing the paired matrix comparison procedure, subjectivity is sought to be as real and objective as possible since the different elements of the matrix are successively compared to form another matrix. there is a procedure to calculate it. if it is acceptable, the decision process can continue, but if it is unacceptable, a new analysis will be necessary because it is likely to modify the judgments about the paired comparisons (escrivá, 2016). the consistency relationship is calculated using equation 1 obtaining the normalized matrix a: 1 y n kjk a a normalized a −         ∑ (1) the sum of rows is obtained from equation 2: 111 12 1 1 21 1 1 . n n n n n n nnn n n aa a b a a a − − − + +…………… + = ∑ ∑ ∑ 111 12 2 1 21 1 1 . n n n n n n nnn n n aa a b a a a − − − + +…………… + = ∑ ∑ ∑ (2) 111 12 1 21 1 1 . n nn n n n n nnn n n aa a b a a a − − − + +…………… + = ∑ ∑ ∑ the priority vector b that is formed is given by equation 3: b n b n b n n t 1 2 , , . ,�� � � � � � � (3) the product of the original matrix a and the priority vector b forms a column c matrix, equation 4: t 1, 2 .., na*b c c c c……… = =   (4) table 1: implementation of the saaty scale according to the degree of importance (saaty, 1980) value definition 1 equal importance 3 moderate importance 5 great importance 7 very great importance 9 extreme importance 2, 4, 6 and 8 intermediate values table 2: paired comparison matrix a1 a2 a3 a1 1 a12 a13 a2 a21 1 a23 a3 a31 a32 1 rocha, et al.: implementation of the hierarchical analytical process in the selection of the best source of renewable energy in the colombian caribbean region international journal of energy economics and policy | vol 12 • issue 2 • 2022 115 we proceed to calculate the quotient between the matrix column c and the vector of priorities b, obtaining another column vector d, equation 5: c b d= (5) adding and averaging its elements, the value of the consistency index (ci) is obtained, equation 6: max nci n 1 −= − λ (6) subsequently, the ci obtained is compared with the random ci in table 3: the random consistency (ci) value as a function of the size of the matrix represents the value that the ci should obtain if the numerical judgments with the scale of (saaty, 1980) had been completely randomly introduced into the comparison matrix. therefore, the ci is divided by the random consistency, thus obtaining the inconsistency ratio (ir), equation 7: ci ir random consistency = (7) finally, a consistent matrix will be considered when the following values stipulated for the size of each matrix are not exceeded, table 4. if any matrix exceeds the consistency ratio, the valuations made by the decision-maker are reviewed and modified to reduce this consistency ratio to admissible values (escrivá, 2016). 2.3. criteria and sub-criteria approach in the selection of criteria and sub-criteria, a set of qualitative criteria was established that are considered as a means of comparison between the different alternatives. these parameters influence multi-criteria decision making for the selection of technologies to be used. the criteria considered in the analysis are based on the study of different articles and/ or publications from different databases (john et al., 2014; robles-algarín et al., 2018; jamal et al., 2020; ruiz et al., 2012). table 5 shows the classification of the sub-criteria according to the social (c1), economic (c2), environmental (c3) and technical (c4) criteria. o n c e t h e f i n a l l i s t o f c r i t e r i a h a s b e e n o b t a i n e d , t h e interrelationships between the elements are determined in order to make pairwise comparisons. the theoretical definitions of the elements were carefully examined and the literature reviewed to establish precise interrelationships. the initial relationships were decided based on information obtained from the literature. on the other hand, the participation of experts from the energy sector plays a very important role. in our study, and taking into account the multidisciplinary nature of energy investments, a team of experts of 16 people was assembled. the experts have a minimum of 2 years of experience and know about the topics of investments in renewable energy sources. the experts were asked to review the interrelationships obtained from the literature and complete the interrelationship matrix. the set of scales suggested by (saaty, 1980) was used in the pairwise comparison matrices and the numbers 1 to 9 are used to indicate the relative importance of the items. in the next step, the relative importance indices of the clusters were determined and the items were determined. the set of scales suggested by (saaty, 1980) was used in the pairwise comparison matrices. the profile of the experts is shown in table 6. the objective of this methodology is to be able to analyze the criteria, sub-criteria and alternatives of a hierarchical structure in order to obtain the judgments issued by each of the experts consulted. in the method, the comparison is made in pairs, where it is necessary to generate the evaluation issued by one or more experts; success at this stage will depend on the knowledge and expertise of the group of decision makers. the evaluated criteria are assigned the satty scale to obtain the weightings of each one of them. 3. results and discussion according to the opinion and assessment of the experts in each of the decision matrices, and with the help of the ahp methodology, table 3: comparison between the ci obtained and the random ci array size (n) 1 2 3 4 5 6 7 8 9 10 random consistency 0.0 0.0 0.52 0.89 1.11 1.25 1.35 1.40 1.45 1.49 ci: consistency index table 4: consistency limits (saaty, 1980) matrix size (n) consistency ratio 3 5% 4 9% 5 or more than 5 10% table 5: classification of sub‑criteria according to criteria criteria sub-criteria social (c1) social acceptance (c 1.1) generation of work (c 1.2) obstacles in zones (c 1.3) disponibilidad de zona (c 1.4) vandalism and/or terrorism (c 1.5) economical (c2) initial capital (c 2.1) operation and maintenance cost (c 2.2) net present value (c 2.3) electricity generation cost (c 2.4) environmental (c3) renewable faction (c 3.1) carbon footprint (c 3.2) ecosystem impact (c 3.3) technicians (c4) efficiency (c 4.1) reliability (c 4.2) source availability (c 4.3) technology maturity (c 4.4) rocha, et al.: implementation of the hierarchical analytical process in the selection of the best source of renewable energy in the colombian caribbean region international journal of energy economics and policy | vol 12 • issue 2 • 2022116 it is possible to establish, as shown in figure 2, the weighting of the criteria used in the study area, managing to determine that the weighting and ranking of the economic criteria are the most. to validate the reliability of the results obtained in the weightings and ranking of criteria and sub-criteria, the experts consulted calculate the consistency index and the consistency radius of each of the decision matrices. the paired comparison matrix reflects the importance of one attribute with respect to another, however, it is always necessary to validate the consistency of the judgments provided by the experts to obtain a valid and accurate comparison matrix in their responses. table 7 shows the decision matrix of some of the experts, where the comparison between the criteria is observed (hernández et al., 2021). table 8 shows the normalization of the decision matrix of some of the experts, which is an important step in determining the consistency index and the consistency radius. table 9 shows the consistency index and the consistency radius of the obtained values, it is noted that the consistency radius is <0.1, allowing us to determine the validity and precision of the values reflected in the matrix. 1. influential with 38%, followed by the environmental criteria with 34%, and finally, the technical and social criteria with 15% and 13% respectively. one aspect to take into account is the high percentage that environmental criteria have in recent years, this is due to the fact that today there is greater concern for the conservation of natural resources and the efficient exploitation of these. it was also possible to evaluate and classify each of the subcriteria associated with the evaluated criteria. the results shown in figure 3 reflect the behavior of the economic sub-criteria where it is evidenced that the one with the highest weighting is due to costs, operation and maintenance with 38%, followed by the subcriterion of cost of electricity generation with 28% and then the sub-criteria of initial capital and net present value with 22% and 11% respectively. within the social criteria and bearing in mind the area where the research was carried out, the predominant sub-criterion was the generation of work, because in these areas the lack of a job opportunity, the almost or null presence of a state or its representative, conditions the lifestyle of each individual and family, that is why this sub-criterion acquires great value within the social criteria, as reflected in the weighting and ranking in figure 4. for the environmental and technical criteria, results were obtained where it is reflected that the renewable fraction sub-criterion with 49% and the efficiency sub-criterion with 43% lead the weighting and ranking of the results shown in figures 5 and 6. it should be noted how the the group of experts takes into account the efficiency and implementation values of the renewable fraction within the project to be executed. table 6: categorization of the group of experts expert number occupation academic training years of experiences 1 professor magister 2 2 professor magister 2 3 professor magister 2 4 professor magister 2 5 professor magister 4 6 professor magister 4 7 professor magister 4 8 lawyer magister 4 9 lawyer magister 6 10 field engineer magister 6 11 field engineer magister 6 12 administrative magister 6 13 administrative magister 8 14 administrative magister 8 15 professor doctor more than 10 16 professor doctor more than 10 table 7: comparison matrix between criteria economic social environmental technicians economic 1 3 7 5 social 1/3 1 1/7 1/3 environmental 0.14 7 1 9 technicians 1/5 3 1/9 1 sum 1.68 14.00 8.25 15.33 table 8: matrix of normalized values economic social environmental technicians economic 0.60 0.21 0.85 0.33 social 0.20 0.07 0.02 0.02 environmental 0.09 0.50 0.12 0.59 technicians 0.12 0.21 0.01 0.07 sum 1.00 1.00 1.00 1.00 table 9: determination of the consistency index and consistency radius ʎ max consistency index consistency radius 4.1005 0.0335 0.0338 figure 2: criteria weighting by ahp% figure 3: the weighting of economic criteria by ahp% rocha, et al.: implementation of the hierarchical analytical process in the selection of the best source of renewable energy in the colombian caribbean region international journal of energy economics and policy | vol 12 • issue 2 • 2022 117 figure 7 shows the overall percentage weighting of each of the subcriteria. it should be noted that for the group of experts consulted, the sub-criteria of removable fraction and work generation are the most important because it is a project where the efficient use of different sources of renewable energy is implemented. according to the international renewable energy agency, reaching the paris agreement requires doubling the share of renewable energies in electricity generation to 57% worldwide by 2030. to achieve this requirement it is necessary to increase investments annually in renewable energy from 330 billion dollars today to 750 billion dollars, with the consequent boost to job creation and growth linked to the green economy of the international energy agency (iea). the level of importation of each of the criteria varied according to the renewable energy sources that are present in the area, figure 8. according to the experts, the economic criterion was the most important in the use of wind energy, while for the solar collectors the most important criterion was social. these results demonstrate the variability in the degree of importance of the criteria for each of the renewable energy sources. table 10 shows the percentage obtained in each of the four criteria analyzed (c1, c2, c3 and c4). in addition, the table reflects the values of the local and global weights of each sub-criterion, and finally, the percentage of each one of them compared to the alternatives of renewable energy sources. it is necessary to mention that the union of these figures forms what is called the decision matrix. the growth of renewable energies worldwide is on the rise according to the data provided annually by the iea. according to iea forecasts, the share of renewable energies in world electricity supply will go from 26% in 2018 to 44% in 2040 and will contribute 2/3 of the increase in electricity demand in that period, mainly to through the use of wind and photovoltaic technologies. according to the iea, global electricity demand will increase by 70% in 2040, which will allow an increase in the share of final energy use from 18% to 24%, mainly in emerging regions such as india, china, africa, middle east and east and southeast asia (khan et al., 2021). the development and use of clean energy is essential to reverse the serious situation of the environment and mitigate the effects of climate change. for example, 2019 was the second warmest year on record, behind 2016. the average temperature recorded over the past 5 years has been about 1.2 oc higher than pre-industrial, according to the copernicus climate change service. in addition, approximately 860 million people in the world did not have access to electricity in 2018, which requires a great additional effort in the deployment of clean energy to achieve universal access to electricity by 2030. the poor decision to choose a renewable energy that has the resources available in an application area leads to great losses of time and money. the methodology described in this research would then help to make better decisions that could converge in public policies aimed at taking advantage of the energy resources available in a given area. the methodology selected in this study was ahp, which provides the hierarchical analysis process. by applying the methodology in the colombian caribbean region, table 10: hierarchy associated with criterion weight c1 (15%) c2 (38%) c3 (34%) c4 (12%) c1.1 c1.2 c1.3 c1.4 c1.5 c2.1 c2.2 c2.3 c2.4 c3.1 c3.2 c3.3 c4.1 c4.2 c4.3 c4.4 l % 21% 42% 7% 17% 13% 28% 38% 11% 22% 49% 22% 30% 43% 33% 9% 15% g % 0.03 0.06 0.01 0.03 0.02 0.11 0.14 0.04 0.08 0.17 0.07 0.10 0.06 0.04 0.01 0.02 a1 0.33 0.22 0.26 0.31 0.28 0.35 0.05 0.07 0.05 0.16 0.08 0.24 0.38 0.39 0.31 0.32 a2 0.27 0.20 0.16 0.12 0.23 0.29 0.06 0.18 0.15 0.20 0.09 0.19 0.10 0.19 0.20 0.21 a3 0.09 0.14 0.11 0.14 0.14 0.09 0.11 0.30 0.27 0.14 0.30 0.15 0.20 0.18 0.12 0.11 a4 0.10 0.13 0.11 0.14 0.11 0.07 0.20 0.21 0.25 0.15 0.24 0.18 0.17 0.10 0.11 0.11 a5 0.08 0.13 0.10 0.08 0.08 0.03 0.35 0.08 0.18 0.24 0.11 0.08 0.06 0.04 0.08 0.08 a6 0.13 0.19 0.26 0.22 0.17 0.17 0.22 0.15 0.10 0.11 0.18 0.15 0.10 0.09 0.18 0.17 figure 4: the weighting of social criteria by ahp% figure 5: the weighting of technical criteria by ahp% figure 6: the weighting of environmental criteria by ahp% rocha, et al.: implementation of the hierarchical analytical process in the selection of the best source of renewable energy in the colombian caribbean region international journal of energy economics and policy | vol 12 • issue 2 • 2022118 the result is that the most feasible renewable energy source to use is photovoltaic solar, with a rating of 20%, followed by wind energy with 16.88%. in the third step is the energy from biogas with 16.24%, followed by the energy produced by digester with 16.12%, in fifth place we have the energy obtained by solar collectors with 15.46% and in sixth place is the energy obtained by waste incineration with 15.10%, figure 9. it should be noted that the variation between the selection of one source of renewable energy and another is very small, in the order of thousandths, which shows how complex the process of selection. the result obtained in this research corroborates the results obtained by other researchers and serves as a reference for the colombian government and decision makers to improve the quality of life of the inhabitants of the area under study. 4. conclusion the application of the proposed ahp method allowed the participation of a group of experts for the weighting and ranking of the 4 criteria and the 16 sub-criteria used, which can be generalized in energy planning projects in rural and non-interconnected areas of colombia using renewable energy sources. the calculation of the consistency index and consistency radius made it possible to measure the level of relevance and reliability of each of the decision matrices by the experts. the selected sub-criteria allowed the comprehensive evaluation of energy planning projects taking into account technical, economic, social and environmental criteria, as well as each of the 16 subcriteria that were used in the colombian caribbean region. in addition, it is concluded that the environmental criterion, as well as the sub-criteria assigned to it in energy planning, have increased their percentage value, which shows a greater concern for the conservation and proper use of each of the energy sources that are currently used. they use. the proposed methodology allowed the consolidation of 4 criteria and 16 sub-criteria that, in the opinion of the experts, are relevant for energy planning projects in rural areas and not colombian interconnected networks, especially in the colombian caribbean region. references algarín, c.r., llanos, a.p., castro, a.o. (2017), an analytic hierarchy process based approach for evaluating renewable energy sources. international journal of energy economics and policy, 7(4), 38-47. alptekin, s.e. (2021), a fuzzy decision support system for digital camera selection based on user preferences. expert systems with applications, 39(3), 3037-3047. ashek-al-aziz, m., mahmud, s., islam, m.a., mahmud, j.a., hasib, k.m. (2020), a comparative study of ahp and fuzzy ahp method for inconsistent data. international journal of sciences: basic and applied research, 54(4), 16-37. balbis-morejón, m., cabello-eras, j. j., rey-hernández, j.m., reymartínez, f.j. (2021), global air conditioning performance indicator (acpi) for buildings, in tropical climate. building and environment, 203, 108071. budes, f.a.b., ochoa, g.v., obregon, l.g., arango-manrique, a., álvarez, j.r.n. (2020), energy, economic, and environmental evaluation of a proposed solar-wind power on-grid system using homer pro®: a case study in colombia. energies, 13(7), 1662. cherni, j.a., dyner, i., henao, f., jaramillo, p., smith, r., font, r.o. (2007), energy supply for sustainable rural livelihoods. a multicriteria decision-support system. energy policy, 35(3), 1493-1504. figure 7: global sub-criteria % figure 8: comparison of alternatives and each criterion figure 9: weighting of renewable energies by ahp rocha, et al.: implementation of the hierarchical analytical process in the selection of the best source of renewable energy in the colombian caribbean region international journal of energy economics and policy | vol 12 • issue 2 • 2022 119 díaz, s., moreno, c., berdugo, k., silva, j., caicedo, j., ruiz, j., gordon, j. (2021), electric power losses in distribution networks. turkish journal of computer and mathematics education, 12(12), 581-591. escrivá, l. (2016), aplicación del proceso analítico jerárquico (ahp) al dimensionamiento de sistemas renovables. thesis, technical school of industrial engineering, universidad politécnica de valencia, spain. p84. ferretti, v., montibeller, g. (2016), key challenges and meta-choices in designing and applying multi-criteria spatial decision support systems. decision support systems, 84, 41-52. gaete-morales, c., gallego-schmid, a., stamford, l., azapagic, a. (2019), life cycle environmental impacts of electricity from fossil fuels in chile over a ten-year period. journal of cleaner production, 232, 1499-1512. garces, e., tomei, j., franco, c.j., dyner, i. (2021), lessons from last mile electrification in colombia: examining the policy framework and outcomes for sustainability. energy research and social science, 79, 102156. ghavami, s.m. (2019), multi-criteria spatial decision support system for identifying strategic roads in disaster situations. international journal of critical infrastructure protection, 24, 23-36. hacatoglu, k., dincer, i., rosen, m.a. (2015), sustainability assessment of a hybrid energy system with hydrogen-based storage. international journal of hydrogen energy, 40(3), 1559-1568. hernández, j.c.b., moreno, c., ospino-castro, a., robles-algarin, c.a., tobón-perez, j. (2021), a hybrid energy solution for the sustainable electricity supply of an irrigation system in a rural area of zona bananera, colombia. international journal of energy economics and policy, 11(4), 521-528. jamal, t., urmee, t., shafiullah, g.m. (2020), planning of off-grid power supply systems in remote areas using multi-criteria decision analysis. energy, 201, 117580. john, a., yang, z., riahi, r., wang, j. (2014), application of a collaborative modelling and strategic fuzzy decision support system for selecting appropriate resilience strategies for seaport operations. journal of traffic and transportation engineering, 1(3), 159-179. khan, i., hou, f., zakari, a., tawiah, v.k. (2021), the dynamic links among energy transitions, energy consumption, and sustainable economic growth: a novel framework for iea countries. energy, 222, 119935. mamaghani, a.h., avella, s., najafi, b., shirazi, a., rinaldi, f. (2016), techno-economic feasibility of photovoltaic, wind, diesel and hybrid electrification systems for off-grid rural electrification in colombia. renewable energy, 97, 293-305. mehrjerdi, h. (2020), modeling, integration, and optimal selection of the turbine technology in the hybrid wind-photovoltaic renewable energy system design. energy conversion and management, 205, 112350. milanés-hermosilla, d., codorniú, r.t., lópez-baracaldo, r., sagarózamora, r., delisle-rodriguez, d., villarejo-mayor, j.j., núñezálvarez, j.r. (2021), monte carlo dropout for uncertainty estimation and motor imagery classification. sensors, 21(21), 7241. moghadam, s.t., lombardi, p. (2019), an interactive multi-criteria spatial decision support system for energy retrofitting of building stocks using communtiy viz to support urban energy planning. building environment, 163, 106233. nuñez, j.r., mestre, j., cabello, j.j., dominguez, h., fong, j., peña, l., benítez, i. and de oliveira, d. (2020), design of a fuzzy controller for a hybrid generation system. iop conference series: materials science and engineering, 844, 012017. ochoa, g.v., alvarez, j.n., acevedo, c. (2019), research evolution on renewable energies resources from 2007 to 2017: a comparative study on solar, geothermal, wind and biomass energy. international journal of energy economics and policy, 9(6), 242-253. ochoa, g.v., alvarez, j.n., chamorro, m.v. (2019), data set on wind speed, wind direction and wind probability distributions in puerto bolivar colombia. data in brief, 27, 104753. robles-algarín, c.a., taborda-giraldo, j.a., ospino-castro, a.j. (2018), a procedure for criteria selection in the energy planning of colombian rural areas. información tecnológica, 29(3), 71-80. rosso, a.m., kafarov, v., latorre-bayona, g. (2017), a fuzzy logic decision support system for assessing sustainable alternative for power generation in non interconnected areas of colombia case of study. chemical engineering transactions, 57, 421-426. ruiz, m.c., romero, e., pérez, m.a., fernández, i. (2012), development and application of a multi-criteria spatial decision support system for planning sustainable industrial areas in northern spain. automation in construction, 22, 320-333. saaty, t.l. (1980), the analytic hierarchy process. new york: mcgrawhill; 1980. silvera, o.c., chamorro, m.v., ochoa, g.v. (2021), wind and solar resource assessment and prediction using artificial neural network and semi-empirical model: case study of the colombian caribbean region. heliyon, 7(9), e07959. suresh, v., muralidhar, m., kiranmayi, r. (2020), modelling and optimization of an off-grid hybrid renewable energy system for electrification in a rural areas. energy reports, 6, 594-604. tavana, m., arteaga, f.j.s., mohammadi, s., alimohammadi, m. (2017), a fuzzy multi-criteria spatial decision support system for solar farm location planning. energy strategy reviews, 18, 93-105. vides-prado, a., camargo, e.o., vides-prado, c., orozco, i.h., chenlo, f., candelo, j.e., sarmiento, a.b. (2018), techno-economic feasibility analysis of photovoltaic systems in remote areas for indigenous communities in the colombian guajira. renewable and sustainable energy reviews, 82(3), 4245-4255. vinogradova-zinkevič, i., podvezko, v., zavadskas, e.k. (2021), comparative assessment of the stability of ahp and fahp methods. symmetry (basel), 13(3), 13030479. zanghelini, g.m., cherubini, e., soares, s.r. (2018), how multi-criteria decision analysis (mcda) is aiding life cycle assessment (lca) in results interpretation. journal of cleaner production, 172, 609-622. zeng, y., guo, w., wang, h., zhang, f. (2019), a two-stage evaluation and optimization method for renewable energy development based on data envelopment analysis. applied energy, 262, 114363 zhou, j., wu, y., wu, c., deng, z., xu, c., hu, y. (2019), a hybrid fuzzy multi-criteria decision-making approach for performance analysis and evaluation of park-level integrated energy system. energy conversion and management, 201, 112134. zhou, x. (2012), fuzzy analytical network process implementation with matlab. in: matlab a fundamental tool for scientific computing and engineering applications. vol. 3. london: intech. p132-160. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 1 • 2023 61 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(1), 61-66. return and volatility spillovers of asian pacific stock markets’ energy indices manivannan babu1*, c. hariharan2, s. srinivasan3, p. s. shabi shimny4, gayathri jayapal5, g. indhumathi6, j. sathya7, brintha rajendran8, veeramani anandhabalaji9, chinnadurai kathiravan10 1bharathidasan school of management, bharathidasan university, india, 2nehru institute of technology, coimbatore, tamil nadu, india, 3sri ramachandra institute of higher education and research, india, 4gulf centre for university education (ignou), india, 5department of commerce and financial studies, bharathidasan university, india, 6mother teresa women’s university, india, 7sri sanda college for women, india, 8bharathidasan school of management, india, 9bharathidasan school of management, bharathidasan university, india, 10vit business school, vit university, india. *email: drbabu@bdu.ac.in received: 17 august 2022 accepted: 10 december 2022 doi: https://doi.org/10.32479/ijeep.13492 abstract the aim of the study was to investigate the presence of volatility among the energy indices of asia pacific stock markets. to test the volatility among the daily returns of energy indices of asia pacific stock markets, the study selected five sample asian pacific stock markets’ energy indices on the basis of availability of data. the findings of descriptive statistics and the adf test revealed, that the daily returns of the sample energy indices of asian pacific stock markets were not normally distributed and achieved stationarity at level difference, over the research period. hence the data may be used for additional analysis. the data were then analysed, by using the garch (1,1) model to assess the considerable volatility of daily returns of sample energy indices and the study, which revealed that during the study period, all of the sample energy indices were volatile. keywords: asian pacific stock market, energy index, garch (1,1), volatility spillovers jel classifications: c50;g10;q40 1. introduction volatility has evolved as an importance factor in derivative pricing and hedging, risk management, and portfolio management. studying and predicting volatility is a significant and difficult aspect of finance research (balaji et al., 2022). financial market volatility has affected network connections, especially during the covid-19 outbreak (wang et al., 2022). carbon emission futures are the volatility transmitter while green bonds are the volatility beneficiary. international political, economic, and other events have an effect on the overall dynamic connection (zhang et al., 2022). oil and gold price variations have an opposite effect on global clean energy stock returns, during bullish market sentiments (fu et al., 2022). climate policy has a greater ability to forecast renewable energy volatility, provides a novel perspective for accurate renewable energy volatility prediction, and provides a reliable guarantee for the long-term growth of the energy and financial markets (liang et al., 2022). the disparity in the estimated effect of positive and negative oil shocks on the volatility of green investments, registered asymmetry effect (olaoluwa et al., 2022). as investor concerns about environmental sustainability drive them to invest in environmentally sustainable companies, this study may appeal to shareholders, wishing to reduce carbon emissions in their portfolios, by owning renewable energy assets (dutta et al., 2022). at the same time, investors may continue holding the assets despite their high risk due to the fact that there are risk-return trade-offs (babu et al, 2022a). both investors and manufacturers took diverse investment decisions, based on the this journal is licensed under a creative commons attribution 4.0 international license babu, et al.: return and volatility spillovers of asian pacific stock markets’ energy indices international journal of energy economics and policy | vol 13 • issue 1 • 202362 crude oil market’s response to various uncertain measures, and employed diversified investment strategies before and during the covid-19 pandemic (niu et al., 2022). it is reasonable to believe that clean energy, oil, and carbon pricing, which are critical areas of discussion, under the world’s current efforts at climate change (mohammed et al., 2022). the extent of shock spillovers from oil price volatility to renewable energy sectors was larger in the medium and long run (urom et al., 2022). during the years 2018 and 2019, oil and natural gas corporation ltd’s stock price had only moderate fluctuation (babu et al., 2022b). forecasting the total network connectedness requires information on the transmitted returns and volatility spillover from markets (ghaemi et al., 2022). energy inflation should be regulated, globalization should be revised and human capital like education and technical skills should be enhanced, in order to optimize natural resource (liang et al., 2022). agricultural commodities’ prices are positively impacted by fluctuations in energy prices. it is, therefore, imperative that climate change be considered trying to mitigate food insecurity in iran’s provinces (kargar dehbidi et al., 2022). clean energy, realized volatility is successfully predicted by both uncertainty indices and global economic conditions. a shrinkage method consistently outperforms a dimensionality reduction method and a combination forecast method, with respect to clean energy and natural gas (wang et al., 2022). it has been found that oil volatility causes spillovers to us stock sectors, with the effect being especially pronounced in high volatility regimes. even though the energy sector accounts for only a small portion of the us stock market, its network connectedness is quite significant (hernandez et al., 2022). in the non-price-regulated scenario, energy price fluctuations use a high level of conduction efficiency for influencing the general price index. the effect of fluctuating energy prices shows clear hysteresis, and the lag time of the transmission effect on ppi is larger than that on cpi (xu et al., 2021). green returns have been enhanced, especially after the paris agreement concerning the sector’s uncertainty and str model is employed, to assess and quantify the influence of fluctuation on the nonlinear behaviour of clean energy etfs (fahmy, 2021). the sharp difference may be due to the fact that increased energy prices might harm the profitability of s&p 500 corporations while not affecting gce and eco enterprises (kanamura, 2019). prevention of possible risk spillover among carbon and energy markets, might help to construct china’s united carbon market and prevent systematic financial problems in the energy market (qiao et al., 2021). the effectiveness of clean energy asset allocating strategies, as well as the heterogeneous diversification advantages among clean energy stocks sub-sectors, report substantial implications for shareholders, establishing clean energy portfolios to achieve investment objectives (kuang, 2021). clean energy shares are more than the oil price when the oil price is low by using var model (tan et al., 2021). there is a negative association between oil volatility spillover shocks and stock returns in specific stock markets, particularly during covid-19 downturns (boateng et al., 2021). the fluctuation of the rare earth stock index is highly correlated with the price of crude oil (song et al., 2021). the volatility spillover interactions in the renewable energy market economy are much more complicated among two markets (zhou et al., 2021). the energy sector plays a major role in spillover transfer to the other market segments through volatility (ben ameur et al., 2021). at various time periods and frequency, commodity price indices considerably influenced the energy price indices (kirikkaleli and güngör, 2021). farmers can protect themselves against unfavorable price changes in the future with the help of commodity futures market (srinivasan et al., 2022). only at the lower quantiles, throughout the same timeframes, does the volatility study reveal a strong bidirectional correlation among oil price volatility and renewable energy stock volatility (hammoudeh et al., 2021). volatility spillover from the natural gas futures market has significantly decreased, but volatility has not been decoupled from the crude oil, gasoline and heating oil future markets after the u.s. shale gas revolution (gong et al., 2021). ever since covid-19 pandemic’s emergence, the price of oil and other commodities has changed drastically. in order to more effectively reduce moral hazard and preserve financial prosperity, it is essential to investigate the reasons behind price variations and comprehend the origin and route of risk transmission. szczygielski et al. (2022) devised a new “overall impact of uncertainty” measure and explained by using a natural phenomenon analogy of the overall impact of a rainstorm, to gauge the magnitude and intensity of the impact of uncertainty on energy sector returns and come to the conclusion that covid-19 linked uncertainty exercised a larger impact on the energy industries of nations. curto and serrasqueiro (2022) discovered an increase in unpredictability after february 2020. energy, grain, and textiles are net beneficiaries of risk spill over among china’s commodities, whereas chemical goods and metals are net hazard exporters, according to shen et al. (2022). businesses have favourable risk spill over effects on textiles and metals, two worldwide goods. china’s commodities were the primary exporters of risk contagion even during early stages of the outbreak. the geopolitical risk index appears to be better in predicting long-term crude oil fluctuation than some other ambiguity indicators, and it also improves performance than other uncertainty indicators in predicting, the u.s. petroleum market equities liquidity tracker has the finest predictive ability, to predict the fluctuation of the price of oil, during non-crisis, and economic growth periods (li et al., 2022). wang et al., (2022) discovered that clean energy realised volatility could be accurately predicted by both uncertainty indicators and global economic situations. for renewable power and natural gas, contraction approaches regularly outperform dimension reduction methods and combination forecast methods. there is a statistically significant non-linear relationship among the markets under study and all energy metals, except cobalt, have a significant positive linkage with clean energy stock indices and such associations do hold during episodes of high volatility (gustafsson et al., 2022). in contrast to volatility, which showed up at lesser frequencies, the overall economic instability spill over to the return of the three renewable energy stocks, was concentrated at high frequency (liu et al., 2021). the markets for clean energy and oil are both subject to spill over instability. it has been discovered that the oil market is a net recipient of volatility, and that volatility overflow is larger in times of extreme positive and negative stress than in babu, et al.: return and volatility spillovers of asian pacific stock markets’ energy indices international journal of energy economics and policy | vol 13 • issue 1 • 2023 63 periods of moderate shock (attarzadeh and balcilar, 2022). in the long run, the impact of crude oil price fluctuation on turkey’s producer and consumer price indices is not equal. consumer price index and producer price index are more affected over the long term by rising world oil prices rather than by falling prices (altunöz, 2022). the aim of the study was to investigate the volatility among the energy indices of asia pacific stock markets. for analysing the aim of the study, following objectives were formulated. • to test the normality and stationarity of daily returns of sample energy indices of asia pacific stock markets. • to analyse the significant volatility of daily returns of sample energy indices of asia pacific stock markets. • to explore the causal relationship among daily returns of sample energy indices of asia pacific stock markets. 2. methodology and data description to test the volatility among the daily returns of energy indices of asia pacific stock markets, the study selected five sample asian pacific stock markets’ energy indices, on the basis of availability of data. the list of the sample stock markets and energy indices are shown in the table 1. in view of economic reforms and covid19, the study selected the sample period from january 2017 to december 2021 and the corresponding data (daily prices) of sample energy indices were collected from the yahoo finance and investing.com, for the period of january 2017 to december 2021. at the outset, logarithmic daily returns were calculated, by the following formula: rt � � ln p p t t 1 where r denotes the return during the “t” time period pt denotes the price of the stock at the end of the time period; pt-1 denotes the price of the stock at the start of the time period; and ln denotes the natural log. the study used the following statistical tools to testing the hypotheses of the study a) descriptive statistics – it was used for describe the daily returns of the sample energy indices of asia pacific stock markets. b) augmented dickey-fuller (adf) test was used to examine the unit root of the daily returns of the sample energy indices of asia pacific stock markets. c) garch (1, 1) model was used for testing the volatility of sample energy indices of asia pacific stock markets. d) granger causality test was used for testing the causal relationship among the sample energy indices of asia pacific stock markets. 3. preliminary analysis and empirical results the table 2 give the description information of sample asian pacific nations, energy stock indices. as can be seen from the results, the mean values for all sample countries, energy indices were negative except nifty energy index. the standard deviation implied that the selected variables were unconditionally volatile. further, the daily returns of the sample indices were negatively skewed, during the study period, it implying that negative values or losses were much more likely (i.e., the left tail particularly extreme). the leptokurtic feature of return distribution was very salient in the sample. based on the jarque-bera test, the daily returns of the sample energy indices were not normally distributed, during the study period. to test the unit root of the daily returns of the sample asian pacific countries’ energy indices, the augmented dickey fuller test was used. the corresponding results are shown in table 3. each energy index of asian pacific countries’ stock markets attained stationarity at level difference (i.e. this means that the daily returns of sample asian pacific countries’ emerging indices were i(0) process). the q-q plots (figure 1) also confirmed the table 1: list of sample asian pacific stock markets’ energy indices sample country sample stock markets sample indices india national stock exchange of india ltd. nifty energy new zealand nzx, new zealand's exchange s&p nzx energy capital australia australian securities exchange ltd. s&p asx 200 energy china shanghai stock exchange sse energy japan tokyo stock exchange tokyo se topix17 energy table 2: distribution statistics of the daily returns of asian pacific stock markets’ energy indices nifty energy s&p nzx energy capital s&p asx 200 energy sse energy tokyo se topix17 energy mean 0.000636 −0.000628 −0.000114 −0.0000748 −0.0000963 sd 0.013929 0.015229 0.017871 0.014917 0.016905 skewness −0.716323 −0.547663 −2.029084 −0.231698 −0.184925 kurtosis 11.28109 18.47922 28.35884 6.513156 5.385965 jarque-bera 3637.389 12702.51 34790.71 636.2213 296.3388 probability 0.000 0.000 0.000 0.000 0.000 babu, et al.: return and volatility spillovers of asian pacific stock markets’ energy indices international journal of energy economics and policy | vol 13 • issue 1 • 202364 figure 1: q-q plots for daily returns of asian pacific stock markets’ energy indices table 3: unit root test of the daily returns of asian pacific stock markets’ energy indices augmented dickey‑fuller test statistic test critical values prob. t-statistic 1% level 5% level 10% level nifty energy −35.63274 −3.43543 −2.86367 −2.56796 0.000 s&p nzx energy capital −34.02502 −3.43531 −2.86362 −2.56793 0.000 s&p asx 200 energy −36.39551 −3.43531 −2.86362 −2.56793 0.000 sse energy −35.92175 −3.43552 −2.86371 −2.56798 0.000 tokyo se topix17 energy −33.47755 −3.4355 −2.8637 −2.56797 0.000 table 4: garch (1,1) model for the daily returns of asian pacific stock markets’ energy indices α1 β1 c prob. nifty energy 0.107865 0.824431 0.0000114 0.000 s&p nzx energy capital 0.102048 0.904722 0.00000169 0.000 s&p asx 200 energy 0.11904 0.878383 0.0000044 0.000 sse energy 0.13184 0.825451 0.0000105 0.000 tokyo se topix17 energy 0.067028 0.916771 0.00000535 0.000 daily returns sample asian pacific countries’ emerging indices to be negatively skewed and unit root identified in the sample data, during the study period. according to the results of garch (1,1) model, as shown in the table 4, the sample asian pacific countries’ energy stock indices were volatile, during the study period. the sum of resid (-1) and garch (-1), for all the sample indices, were closer to one for all the sample indices (α1+ β1<1). the residual graph (figures 2) also confirmed the fluctuations of the daily returns of babu, et al.: return and volatility spillovers of asian pacific stock markets’ energy indices international journal of energy economics and policy | vol 13 • issue 1 • 2023 65 figure 2: residual graph for daily returns of asian pacific stock markets’ energy indices sample energy indices. a c c o r d i n g t o r e s u l t s o f t h e g r a n g e r c a u s a l i t y te s t , as displayed in the table 5, f value of the sample energy indices indicated that unidirectional relationship between s&pnzxenergycapital and s&pasx200energy, sseenergy and tokyosetopix17energy while the rest of the asian pacific energy stock indices did not have any bidirectional or unidirectional relationship with other sample indices. 4. conclusion the aim of the study was to analyse the casual relationship and volatility of asian pacific stock markets’ energy indices, for the period of january 2017 to december 2021. analyse the data descriptive statistics, adf test, garch (1,1) model, and granger causality assess were employed to analyse the data. according to the findings of descriptive statistics and the adf test, the daily returns of the sample energy indices of asian pacific stock markets were not normally distributed and achieved stationarity at level difference, over the research period. as a result the data may be used for additional analysis. the data were then analysed, by using the garch (1,1) model to assess the considerable volatility of daily returns of sample energy indices and the study revealed that all the sample energy indices were volatile during the study period. further, the result of granger causality test found unidirectional relationship between s&pnzxenergycapital and s&pasx200energy, sseenergy and tokyosetopix17energy, during the study period. the study also found another interesting result there was no bidirectional relationship among the asian pacific stock market energy indices, during the study period. therefore, the study concluded that the investors of global stock markets should concentrate and analyse the market movement, during the period of introduction of economic reforms or the incidence of natural disasters like, cyclone, earthquake, covid-19, etc. references alkathery, m.a., chaudhuri, k., nasir, m.a. (2022), implications of clean energy, oil and emissions pricing for the gcc energy sector stock. energy economics, 112, 106119. altunöz, u. (2022), the nonlinear and asymetric pass‐through effect of crude oil prices on inflation. opec energy review, 46(1), 31-46. asl, m.g., adekoya, o.b., rashidi, m.m., doudkanlou, m.g., dolatabadi, a. (2022), forecast of bayesian-based dynamic connectedness between oil market and islamic stock indices of islamic oil-exporting countries: application of the cascade-forward backpropagation network. resources policy, 77, 102778. attarzadeh, a., balcilar, m. (2022), on the dynamic connectedness of the stock, oil, clean energy, and technology markets. energies, 15(5), 1893. babu, m., lourdesraj, a.a., hariharan, c., sathya, j., kathiravan, c. (2022a). dynamics of volatility spillover between energy and environmental, social and sustainable indices. international journal of energy economics and policy, 12(6), 50-55. babu, m., lourdesraj, a.a., jayapal, g., indhumathi, g., sathya, j. (2022b), effect of covid-19 pandemic on nse nifty energy index. international journal of energy economics and policy, 2022, 12(4), 141–145. balaji, l., anita, h.b., kumar, b.a. (2023), volatility clustering in nifty energy index using garch model. in: rajakumar, g., du, kl., vuppalapati, c., beligiannis, g.n, editors. intelligent communication technologies and virtual mobile networks. lecture notes on data engineering and communications technologies. vol. 131. singapore: springer. ben ameur, h., ftiti, z., louhichi, w. (2021), intraday spillover between commodity markets. resources policy, 74, 102278. boateng, e., adam, a.m., junior, p.o. (2021), modelling the babu, et al.: return and volatility spillovers of asian pacific stock markets’ energy indices international journal of energy economics and policy | vol 13 • issue 1 • 202366 heterogeneous relationship between the crude oil implied volatility index and african stocks in the coronavirus pandemic. resources policy, 74, 102389. curto, j.d., serrasqueiro, p. (2022), the impact of covid-19 on s&p500 sector indices and fatang stocks volatility: an expanded aparch model. finance research letters, 46, 102247. dehbidi, n.k., zibaei, m., tarazkar, m.h. (2022), the effect of climate change and energy shocks on food security in iran’s provinces. regional science policy and practice, 14(2), 417-437. dutta, a., dutta, p., (2022), geopolitical risk and renewable energy asset prices: implications for sustainable development. renewable energy, 196, 518-525. fu, z., chen, z., sharif, a., razi, u. (2022), the role of financial stress, oil, gold and natural gas prices on clean energy stocks: global evidence from extreme quantile approach. resources policy, 78, 102860. gong, x., liu, y., wang, x. (2021), dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method. international review of financial analysis, 76, 101790. gustafsson, r., dutta, a., bouri, e. (2022), are energy metals hedges or safe havens for clean energy stock returns? energy, 244, 122708. hammoudeh, s., mokni, k., ben-salha, o., ajmi, a.n. (2021), distributional predictability between oil prices and renewable energy stocks: is there a role for the covid-19 pandemic? energy economics, 103, 105512. hernandez, j.a., shahzad, s.j.h., sadorsky, p., uddin, g.s., bouri, e., kang, s.h. (2022), regime specific spillovers across us sectors and the role of oil price volatility. energy economics, 107, 105834. kirikkaleli, d., güngör, h. (2021), co-movement of commodity price indexes and energy price index: a wavelet coherence approach. financial innovation, 7(1), 15. kuang, w. (2021), which clean energy sectors are attractive? a portfolio diversification perspective. energy economics, 104, 105644. li, x., liang, c., chen, z., umar, m. (2022), forecasting crude oil volatility with uncertainty indicators: new evidence. energy economics, 108, 105936. liang, c., umar, m., ma, f., huynh, t.l.d. (2022), climate policy uncertainty and world renewable energy index volatility forecasting. technological forecasting and social change, 182, 121810. liang, j., razzaq, a., sharif, a., irfan, m. (2022), revisiting economic and non-economic indicators of natural resources: analysis of developed economies. resources policy, 77, 102748. liu, t., nakajima, t., hamori, s. (2021), the impact of economic uncertainty caused by covid-19 on renewable energy stocks. empirical economics, 62(4), 1495-1515. niu, z., ma, f., zhang, h. (2022), the role of uncertainty measures in volatility forecasting of the crude oil futures market before and during the covid-19 pandemic. energy economics, 112, 106120. qiao, s., zhao, c.x., zhang, k.q., ren, z.y. (2021), research on time-varying two-way spillover effects between carbon and energy markets: empirical evidence from china. frontiers in energy research, 9, 789871 shen, h., pan, q., zhao, l., ng, p. (2022), risk contagion between global commodities from the perspective of volatility spillover. energies, 15(7), 2492. song, y., bouri, e., ghosh, s., kanjilal, k. (2021), rare earth and financial markets: dynamics of return and volatility connectedness around the covid-19 outbreak. resources policy, 74, 102379. srinivasan, s., babu, m., shabi shimny, p., hariharan, c., gayathri, j., indhumathi, g. (2022). dataset on farmers’ perception of commodity futures market. data in brief, 43, 108429. szczygielski, j.j., brzeszczyński, j., charteris, a., bwanya, p.r. (2022), the covid-19 storm and the energy sector: the impact and role of uncertainty. energy economics, 109, 105258. tan, x., geng, y., vivian, a., wang, x. (2021), measuring risk spillovers between oil and clean energy stocks: evidence from a systematic framework. resources policy, 74, 102406. urom, c., mzoughi, h., ndubuisi, g., guesmi, k. (2022), directional predictability and time-frequency spillovers among clean energy sectors and oil price uncertainty. the quarterly review of economics and finance, 85, 326-341. wang, j., ma, f., bouri, e., zhong, j. (2022), volatility of clean energy and natural gas, uncertainty indices, and global economic conditions. energy economics, 108, 105904. wang, x., li, j., ren, x. (2022), asymmetric causality of economic policy uncertainty and oil volatility index on time-varying nexus of the clean energy, carbon and green bond. international review of financial analysis, 83, 102306. xu, h., pan, x., song, m., lu, y. (2021), how do energy prices affect economic environment under different price regulation policies? environmental science and pollution research, 29(13), 1 8460-18471. yaya, o.s., ogbonna, a.e., vo, x.v. (2022), oil shocks and volatility of green investments: garch-midas analyses. resources policy, 78, 102789. zhang, w., he, x., hamori, s. (2022), volatility spillover and investment strategies among sustainability-related financial indexes: evidence from the dcc-garch-based dynamic connectedness and dccgarch t-copula approach. international review of financial analysis, 83, 102223. zhou, w., gu, q., chen, j. (2021), from volatility spillover to risk spread: an empirical study focuses on renewable energy markets. renewable energy, 180, 329-342. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 3 • 2022184 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(3), 184-191. asymmetric causality relationship between oil prices and inflation in bric countries aziza syzdykova1*, aktolkin abubakirova1, lyazzat kudabayeva2, ardak zhantayeva2, aizhan omarova3 1khoja akhmet yassawi international kazakh-turkish university, turkestan, kazakhstan, 2taraz regional university named after m.kh.dulaty, taraz, kazakhstan, 3yessenov university, aktau, kazakhstan. *e-mail: aziza.syzdykova@ayu.edu.kz received: 23 december 2021 accepted: 06 april 2022 doi: https://doi.org/10.32479/ijeep.12814 abstract sharp and persistent increases in oil prices continue to attract the attention of policy makers and economists, and many studies are conducted on the inflationary effects of oil price shocks. knowledge of the inflationary effects of oil price increases will help monetary authorities adopt appropriate policies to meet these shocks. in this study, the asymmetric relationship between inflation rates and oil prices in the bric countries, which alone consumes approximately 28% of the world’s total oil consumption in 2020, has been examined. in this context, the relationship between the variables was investigated with the asymmetric causality analysis method developed by hatemi-j and roca (2014) using monthly data for the period january 2001 to september 2021. as a result of the analysis applied in the study, different results were obtained for the bric countries. keywords: asymmetric causality relationship, bric countries, inflation, oil prices jel classifications: c23, g15, q40 1. introduction oil is one of the most important energy sources for all countries in the world. oil has the power to affect all export and import balances at the global level (syzdykova, 2018a; 2018b). energy use is one of the important factors affecting economic growth. on the other hand, the increase in oil prices, which is one of the main inputs of energy and economies, causes an increase in input costs in oil importing countries and a deterioration in the balance of payments. with the increase in costs, inflation rates increase and economic growth slows down (ahmad, 2013). conversely, oil producing and exporting countries can increase their growth rates by being positively affected by the increase in oil prices, as they will increase their incomes (azretbergenova and syzdykova, 2020). the effect of oil prices on inflation is not actually a direct effect. the importance of this effect is due to the high tax on fuel products. especially in periods of economic recession and high unemployment, governments can prevent the reflection of increases in oil prices on domestic inflation by reducing taxes on fuel. for this reason, the use of energy resources and the energy policies to be implemented are of vital importance for countries. today, oecd countries are the leading countries in energy production and consumption, while rapidly growing and developing bric countries are partners in this consumption. bric countries are among the countries whose economies are growing and developing rapidly. the common features of these countries are that they have a wide geography in the world, large population and very rich underground resources. bric countries have 25% of the world’s surface area, 40% of foreign currency and gold reserves, 41% of the world’s population and 44% of the workforce (syzdykova, 2018). the bric countries lead the world economy in many respects. in particular, china has become one of the largest economies in the world with its economic performance this journal is licensed under a creative commons attribution 4.0 international license syzdykova, et al.: asymmetric causality relationship between oil prices and inflation in bric countries international journal of energy economics and policy | vol 12 • issue 3 • 2022 185 since the early 2000s. in terms of oil production and consumption, these countries direct the global economy and oil prices. in 2020, bric countries alone accounted for 28% of the world’s total oil consumption. among these countries, india (5.3%) and china (16.4%) stand out as the countries with the highest consumption shares (bp, 2021). because these countries are in the position of countries with rapidly changing economic and high population. having oil reserves or importing oil significantly due to the country’s structure is of great importance for countries in the global economic system. in this study, the selection of bric countries is particularly important in this respect. because these countries have important similarities, but they also have various distinctions. russia, one of the bric countries, is the third largest oil producer after saudi arabia and the usa (bp, 2021). on the other hand, the economy of russia, which is one of the countries that cannot diversify sufficiently in the economy, is very sensitive to oil prices. brazil is one of the most important countries in latin america in terms of its oil reserves (11.9 thousand million barrels). in india, oil is the second largest tradable energy source after coal, and more than 70% of its crude oil needs are imported. china seems to be the determinant of world oil prices. india and china have an important place in the ever-increasing need for oil and the formation of oil demand (kim, 2018). as a result, russia and brazil, the world’s major oil exporting countries, china and india as important oil importers, have to be closely concerned with changing oil prices. it is important for policy makers to examine the effects of oil price shocks on the macroeconomic factors of countries. the fluctuations in international oil prices have been caused by different reasons over the years (dey et al., 2020). since 1970, four major oil shocks have occurred in the world economy. the first shock came in 1973 when opec decided to cut oil supply, oil prices rose from 11.24 usd per barrel in 1972 to 20.18 usd in 1975 (80% increase). the second shock occurred in 1980 due to the iran-iraq war, oil prices rose from 19.67 usd to 53.74 usd (173% increase). the third shock occurred 10 years later, due to iraq’s intervention in kuwait, and oil prices rose from 16.62 usd to 24.55 usd (48% increase). the fourth shock occurred as a result of the usa-iraq war in 1999–2000 and the increase in geopolitical tension in the middle east; oil prices rose from 11.27 usd in 1998 to 15.90 usd and in 2000 to 26.72 usd. the price of brent oil, which was 25–30 usd per barrel in the early 2000s, and the increase in demand due to the growth in the global economy after 2002 led to a rapid increase in oil prices. this upward trend continued until the 2008 crisis. in this period, the price of oil per barrel increased up to 132 usd (figure 1). then, right after the global crisis in the world, oil prices dropped sharply and fell to 39.9 usd in december 2008. oil prices, which rose again in 2010–2014, in the fourth quarter of 2014, global oil prices again dropped sharply and have remained low since then. the energy market has also been affected by the radical changes experienced by the covid-19 pandemic. comprehensive measures implemented due to the global epidemic triggered an unprecedented collapse in oil demand in march 2020. on the other hand, oil stocks increased, creating a downward pressure on prices. therefore, as of 2020, demand-driven collapses have occurred in oil prices (jia et al., 2021). in this study, the relationship between international oil prices and inflation rates in bric countries is examined. it has been extensively studied in the literature that positive and negative shocks in oil prices have different effects on the economy. for this reason, the effects of positive and negative oil price shocks on the inflation rate in bric countries were investigated using the asymmetric causality analysis method developed by hatemi-j and roca (2014). the study consists of four parts. in the section following the introduction, the studies in the literature are summarized, and in the third section, the data set and econometric method included in the analysis are explained. in the fourth chapter, the obtained findings are evaluated. the study ended with the conclusion part. 2. literature review sharp and persistent increases in oil prices have attracted the attention of policy makers and economists, and many studies have been conducted on the inflationary effects of oil price shocks. although there is no consensus on whether oil shocks cause economic recession, it is one of the generally accepted facts that oil prices at least partially affect inflation. the successive rises 132.72 39.95 111.8 47.76 30.7 18.38 74.49 0 20 40 60 80 100 120 140 01 .0 1. 20 01 01 .1 0. 20 01 01 .0 7. 20 02 01 .0 4. 20 03 01 .0 1. 20 04 01 .1 0. 20 04 01 .0 7. 20 05 01 .0 4. 20 06 01 .0 1. 20 07 01 .1 0. 20 07 01 .0 7. 20 08 01 .0 4. 20 09 01 .0 1. 20 10 01 .1 0. 20 10 01 .0 7. 20 11 01 .0 4. 20 12 01 .0 1. 20 13 01 .1 0. 20 13 01 .0 7. 20 14 01 .0 4. 20 15 01 .0 1. 20 16 01 .1 0. 20 16 01 .0 7. 20 17 01 .0 4. 20 18 01 .0 1. 20 19 01 .1 0. 20 19 01 .0 7. 20 20 01 .0 4. 20 21 figure 1: development of world oil prices over time (2001-2021 period) source: u.s. energy information administration (eia), 2021. (https://www.eia.gov/) syzdykova, et al.: asymmetric causality relationship between oil prices and inflation in bric countries international journal of energy economics and policy | vol 12 • issue 3 • 2022186 in inflation indicators, especially following the increases in oil prices in the 1970s, have made the relationship between oil price increases and inflation an important research topic. the moderate course of oil prices in the 1980s removed the current issue from the agenda. however, the rising trend of oil prices, which started in the early 2000s, has made the issue one of the current research topics again. studies conducted after 2000, examining the relationship between oil price shocks and inflation in the context of oil prices’ pass-through to inflation, seem to provide a consensus that the passthrough of oil prices to inflation has decreased over time. knowledge of the inflationary effects of oil price increases will help monetary authorities adopt appropriate policies to meet these shocks. leblanc and chinn (2004) examined the transition of changes in oil prices to inflation and determined that increases in oil prices in the usa, japan and european countries affect inflation. de gregorio et al. (2007) examined the inflationary effects of oil prices for thirty-four developed and developing countries with the var method and found that this effect was low. blanchard and gali (2007) investigated the effects of oil shocks on inflation and economy in different periods, before 1983 and after 1984, using the data of six industrialized countries, using the var method. according to empirical evidence, the dynamic impact of oil shocks has decreased significantly. in contrast, jacquinot et al. (2009) investigated the effect of oil prices on inflation in the eurozone with the dynamic stochastic general equilibrium (dgse) model. within the scope of the research, the inflationary effects of oil prices in the short and medium terms were pointed out. according to the results, it has been determined that the changes in oil prices are more effective for the short term. ito (2012) analyzed the effects of oil prices on inflation, real effective exchange rate and real gdp in russia for the period 1995:q1-2009:q3 using the var model. according to the findings, it has been determined that a 1% change (increase and decrease) in oil prices causes a change of 0.44% in real gdp. in the short term, it has been determined that rising oil prices have a negative effect on inflation and a positive effect on economic growth. in addition, it is concluded that oil prices cause an increase in the real effective exchange rate. cavalcanti and jalles (2013) examined the effects of oil prices on growth and inflation in the 1975–2008 period in brazil and the usa. as a result, oil prices in the usa are negative on growth; it has been concluded that it has positive effects on inflation and these effects decrease over time. bass (2019) investigated the relationship between oil prices (brent), exchange rate and consumption price index for russia based on the data for the period 2010–2017 with the vec model. according to the results of the research, it has been found that oil prices, exchange rate and consumer inflation in russia are cointegrated in the long run, and there are significant relationships between the variables in the short run. sultan et al. (2020) investigated with the johansen cointegration method whether the changes in oil prices in india for the period from 1970 to 2017 affect the inflation level in the country. they found that the oil price in india affects the inflation level both in the short run and the long run. in addition, the authors argue that the government should encourage the development of alternative energy source and technology to save energy use. many studies confirm that the transmission of global crude oil prices to domestic prices is asymmetrical and non-linear, and that the impact of rising and falling global crude oil prices on domestic prices is different. first, mork (1989) identified the asymmetric and nonlinear responses of inflation to oil price changes in the usa. later, hamilton and herrera (2004) found similar results and determined that there were nonlinear and asymmetrical relationships between oil prices and us inflation. kilian (2008) stated that the inflationary effect of exogenous oil price shocks for g7 countries was quite low, and even that the effect was negligible in the 2002–2003 period. he stated that the effect of the shock is even less when the gdp deflator is used instead of the consumer price index. in addition, the authors made two caveats for researchers who want to work on this issue. first, it should be noted that there is a non-linear relationship between oil prices and macroeconomic variables. the other stated that although geopolitical risks cause the oil price to increase, these shocks will not cause oil shortages. he stated that it should be noted that geopolitical risks create temporary panic and cause oil prices to increase. zhao et al. (2016) examined the effects of oil price shocks on output and inflation in china using the dgse model. they determined that oil supply shocks as a result of political events have short-term effects on output and inflation, while the effects of other shocks are seen in the long-term. choi et al. (2018) analyzed the effects of fluctuations in world oil prices on domestic inflation using the data of 72 developed and developing countries in the period 1970–2015. according to the results of the analysis, 10% increase in global oil prices increases domestic inflation rates by 0.4% on average, and this effect ends at the end of 2 years. they also determined that the effect is asymmetrical and the effect of positive oil price shocks is greater than negative ones. using ardl and nardl models, long and liang (2018) determined that the transmission of changes in oil prices to china’s producer and consumer price indices is asymmetric in the long run, and the effect of oil price increases is greater than the effect of the decrease. chen et al. (2020) in their study for china, oil shocks; they divided them into four groups: oil supply shocks, global demand shocks, domestic demand shocks and oil-specific demand shocks. using monthly data from january 1999 to december 2016, they analyzed the time-varying effects of these oil price shocks on inflation during china’s import, production and consumption phases. he argues that the effects of oil shocks on china’s inflation differ at each stage. while the increase in oil prices caused by oil-specific demand shocks was the most important cause of chinese inflation in import and production stages during the entire sampling period, china’s consumption inflation is largely affected by domestic demand shocks. in addition, the authors argue that the inflationary effects of oil price shocks have weakened significantly since the international financial crisis compared to the pre-crisis. a summary of empirical studies on the subject is given in table 1. 3. dataset and method 3.1. data in this study, the asymmetric causality relationship between global oil prices and inflation rates for bric countries was analyzed using syzdykova, et al.: asymmetric causality relationship between oil prices and inflation in bric countries international journal of energy economics and policy | vol 12 • issue 3 • 2022 187 monthly data from january 2001 to september 2021. global oil prices are taken into account as brent type. data on oil prices have been obtained from the us energy information administration. inflation data for the countries (2010 = 100) were obtained from the international bank of settlements database. table 2 includes some descriptive statistics of the variables. according to the results of table 2, the average price of brent oil in the period included in the analysis is 65 dollars, the highest price is 132 dollars and the lowest price is 18 dollars. the date of the lowest price is the price decrease due to the covid-19 pandemic. in addition, it is seen that the oil price is skewed and oblique to the right. when the inflation rates of the bric countries (2010 = 100) are evaluated, we see that china is the most stable country in terms of inflation compared to other countries. compared to 2010, the highest and lowest levels of the inflation rate are seen in russia. therefore, the country with the highest standard error indicator of the variable is russia. this means that inflation rates in russia have a wide range; inflation series in other bric countries have low standard deviations compared to russia. the highest level of the inflation rate corresponds to september 2021 and the lowest level to january 2001. the inflation rate in brazil is 113% on average compared to 2010, and it is seen that the price increase in this country is higher than the price increase in other bric countries except china. table 3 shows the correlation relationship of the variables. accordingly, there is a positive and low correlation between oil prices and inflation rates in bric countries. the correlation between inflation rates and oil price in russia and brazil, which are oil exporters, is lower than the correlation coefficients found for oil importers, china and india. 3.2. method in the study, the asymmetric causality analysis method developed by hatemi-j and roca (2014) is used on the idea that the effects of positive and negative shocks experienced in variables may be different from each other. there are three important elements in the method developed by granger and yoon (2002) on the idea that positive and negative shocks can be different from the relationship between the variables: determining the lag length in the created table 1: studies on the effect of oil prices on inflation author country/country group method result volkov and yuhn (2016) russia, brazil, mexico and norway toda and yamamoto there is a relationship dec the exchange rate, inflation and oil prices. the change in one of them affects all of them trang and hong (2017) usa and oecd var model the increase in oil prices leads to an increase in inflation rates. however, it also reveals unemployment and budget deficits in developing countries choi et al., (2018) developed and developing countries literature review the increase in the global oil price is increasing inflation rates. inflation, on the other hand, should be controlled by monetary policy instruments hammoudeh and reboredo (2018) usa ardl (auto regressive distributed lag) regression model oil prices positively affect inflation expectations. changes in oil prices shape inflation expectations meo et al., (2018) pakistan non-linear ardl model changes in oil prices affect inflation rates. depending on this issue, the tourism sector is also adversely affected nasir et al., (2018) brics tv-sva each nation reacted in various ways in regards to the link between oil price and inflation prices kartaev and medvedev (2019) 11 developed and 27 developing countries dynamic panel model there is a relationship between oil prices and inflation. this relationship can be controlled by monetary policy istiak and alam (2019) usa var model and survey method expectations in oil prices affect inflation rates cerra (2019) venezuela general equilibrium model inflation rates increase when oil revenues decrease. devaluations reduce inflation rates wen et al., (2021) g7 countries svar the biggest impact of oil price shocks is on us inflation. each country’s response to oil price shocks is different. the impact of supply shocks before the financial crisis is very strong. the impact of demand shocks increases sharply during the financial crisis oloko et al., (2021) top ten (10) oil-exporting and oil-importing countries fractional cointegration vector autoregressive (fcvar) approach the results show that the persistence of oil-exporting and oil-importing countries in inflation rates did not increase due to oil price shocks source: created by the authors table 2: descriptive statistics of variables brazil russia india china op mean 113.0279 111.3034 112.6564 103.7812 65.30554 median 106.4240 108.5708 109.1232 104.9242 62.47000 maximum 190.8563 201.2713 185.7763 131.0416 132.7200 minimum 54.36082 34.41660 61.20725 79.71273 18.38000 std. dev. 38.08171 50.23136 38.06702 15.96217 28.89955 skewness 0.303686 0.167307 0.253953 0.017926 0.393388 kurtosis 1.840077 1.691070 1.705376 1.655060 2.192729 jarque-bera 17.78611 18.93711 20.06545 18.78030 13.18355 probability 0.000137 0.000077 0.000044 0.000084 0.001372 observations 249 249 249 249 249 table 3: correlation matrix of variables brazıil russia india china op op 0.1837 0.2128 0.2202 0.3059 1 syzdykova, et al.: asymmetric causality relationship between oil prices and inflation in bric countries international journal of energy economics and policy | vol 12 • issue 3 • 2022188 var model, determining the number of additional delays to be added to the model, and determining the critical values for the wald test statistic. the results obtained from the analysis help to understand the dynamics of the series. thus, it is aimed to find the hidden structure that will allow to develop predictions for the possible future. the basis of the asymmetric causality test is to determine whether the causality relationships vary in the presence of different shock types. this process unfolds as follow: p1t and p2t being two co-integrated variables (hatemi-j and roca, 2014: 7) p p pt t t i t i1 1 1 1 10 1 1� � � �� � ��� �, (1) p p pt t t i t i2 2 1 2 2 0 1 2� � � �� � ��� �, (2) t is t t� �1 2, , . ; p10, and p2 0, the constant terms are ε1i and 2 (0i iidε , δ 2 ). positive and negative changes in each variable, respectively ( ) ( ) ( )1 1 2 2 1 1max , 0 , max , 0 ; min , 0i i i i i iε ε ε ε ε ε+ + −= = = and ( )2 2 min , 0i iε ε− = will be. the results are estimated as follows: � � �1 1 1i i i � � �� � ve � � �2 2 2i i i � � �� � . thereby p p pt t t i t i i t i1 1 1 1 1 0 1 1 1 1 � � � � �� � � � �� �� � �, (3) p p pt t t i t i i t i2 2 1 2 2 0 1 2 1 2 � � � � �� � � � �� �� � �, (4) the sum of the positive and negative shocks in each variable i s pt ti t 1 11 � � � �� � , pt ti t 1 11 � � � �� � , pt tt t 2 22 � ��� � , pt tt t 2 22 � ��� � respectively. the vector p p pt t t� � �� ( , )1 2 is used to test the causality relationship between positive shocks. in a var (l) model with k delay, the vector is defined as shown below. p v ap a p a p ut t t l t k t � � � � � � � �� � � � � �1 1 2 2 . in the above equation, v is the vector of constant variables of dimension 2×1. ut + is a vector of error terms that occurs when positive shocks with a size of 2×1 occur. ar is a 2×2 parameter matrix and r k=1 2, ,..., . the optimal delay length is defined by the test statistics developed by hatemi-j (2003; 2008). ( ) 1 22 ( 2 ( ))fhjc in k t m int min int−= ω + + ˆ fω the error terms for each k-length delay length show the covariance matrix. m shows the number of equations in the var model, and �t is the number of samples (hatemi-j and roca, 2014:9). the null hypothesis is that the matrix ar is k. column and j. is defined as the line being equal to zero. for detailed wald statistics, lütkepohl (2005) can be examined. if the test statistics are greater than the critical values, the null hypothesis that there is no causality is rejected. 3.3. analysis results the data to be used in time series analysis must first be stationary. the raw data of time series are generally not stationary and the use of non-stationary series in econometric models causes some problems. in the analysis part, the stationarity of the series was investigated with augmented dickey-fuller (adf) and phillipsperron (pp) unit root tests and the results are shown in table 4. the optimal number of lags in unit root tests was determined according to the akaike information criterion. according to the results in table 4, according to the adf and pp tests, the oil prices variable has a unit root in the level value both with and without a trend. when the first order difference of the variable is taken, it becomes stationary when both adf and pp tests are applied. it was found that the inflation rates calculated for all bric countries have a unit root at the 5% significance level. if the adf test is applied with a trend to the inflation series calculated for china, the 1st order difference also includes a unit root. according to the pp test result, the inflation series in china is stationary when the 1st rank difference is taken. as a result, oil prices and inflation series of bric countries do not have a unit root in the 1st order difference. after applying the unit root test to the series, the asymmetric causality test developed by hatemi-j and roca (2014) was conducted using the optimal lag length obtained from the var model. as a result of the stationarity analysis, since the series were not stationary at the level, the maximum degree of integration was considered as one in all causality tests. the causality test results for brazil are presented in table 5. accordingly, the null hypothesis of asymmetric causality test results stating that there is no causality relationship between oil prices and inflation could not be rejected. this result shows that oil prices and oil price shocks in brazil are not directly related to inflation in the period under consideration. according to the causality results for russia in table 6, it is seen that brent oil prices are the granger cause of inflation. the causality relationship exists from negative oil price shocks to positive inflation shocks, but the same situation is not seen in positive oil price shocks. this gives the conclusion that the change in oil prices only affects the inflation rate in case of decrease, but does not affect the rate of increase. according to the causality test results for india in table 7, there is a 90% confidence level of causality from positive oil shocks to positive inflation shocks. there is no causality running from negative oil price shocks to inflation shocks. china is the world’s largest oil consumer after the usa, and imports a significant portion of the oil it consumes. therefore, theoretically, changes in oil prices are expected to affect inflation syzdykova, et al.: asymmetric causality relationship between oil prices and inflation in bric countries international journal of energy economics and policy | vol 12 • issue 3 • 2022 189 rates in china. according to the causality results in table 8, no causality relationship was found from oil price shocks to inflation shocks. according to this result, it can be said that the increase or decrease in inflation rates in china is not caused by oil prices. 4. conclusion in this study, the asymmetric relationship between brent oil prices and inflation has been examined within the scope of bric countries. the country group in question has significant differences between oil exporting (russia and brazil) and oil importing (china and india) countries. in this context, the increase in oil prices has an impact on the markets, negatively affecting the importing countries in various aspects, and inflation comes first. since oil exporting countries are positively affected by increasing prices, its impact on macroeconomic indicators including inflation is positive. on table 4: results of unit root tests variables deterministic components adf philips perron level 1st difference level 1st difference op intercept –2.597180 [–2.873045] –10.47756 [–2.873045] –2.137374 [–2.872998] –9.994405 [–2.873045] trend and intercept –2.609762 [–3.428123] –10.46270 [–3.428123] –2.083180 [–3.428049] –9.968708 [–3.428123] brazil intercept 2.547099 [–2.873045] –7.205808 [–2.873045] 2.687082 [–2.872998] –7.324429 [–2.873045] trend and intercept 0.042855 [–3.428123] –7.715626 [–3.428123] –0.148420 [–3.428049] –7.867539 [–3.428123] russia intercept 1.178816 [–2.873093] –7.409253 [–2.873093] 1.296286 [–2.872998] –6.900545 [–2.873045] trend and intercept –2.419977 [–3.428123] –7.554676 [–3.428198] –1.960023 [–3.428049] –7.002962 [–3.428123] india intercept 2.973137 [–2.873289] –8.579817 [–2.873289] 2.361258 [–2.872998] –10.73996 [–2.873045] trend and intercept –2.361842 [–3.428503] –9.372239 [–3.428503] –2.222736 [–3.428049] –10.98320 [–3.428123] china intercept –0.631058 [–2.873596] –3.079724 [–2.873596] 0.314437 [–2.872998] –11.70297 [–2.873045] op trend and intercept –4.189310 [–3.428981] –2.992286 [–3.428981] –3.804551 [–3.428049] –11.69241 [–3.428123] note: values in parentheses show mckinnon critical values at 5%, adf: augmented dickey-fuller table 6: asymmetric causality results for russia direction of causality mwald bootstrap critical value (1%) bootstrap critical value (5%) bootstrap critical value (10%) oilp+↛cpi+ 3.180 (0.563) 9.234 6.093 2.896 oilp+↛cpi3.401 (0.876) 9.012 6.742 3.001 oilp-↛cpi3.023 (0.129) 11.231 8.036 2.902 oilp-↛cpi+ 6.091** (0.03) 10.003 6.002 3.128 note: the notation↛indicates the null hypothesis that there is no causality. the values in parentheses indicate the probability values asymptotoically. ** indicates the causality relationship between the variables at the 5% significance level. bootstrap count is 10,000 table 7: asymmetric causality results for india direction of causality mwald bootstrap critical value (1%) bootstrap critical value (5%) bootstrap critical value (10%) oilp+↛cpi+ 7.023*(0.06) 10.003 7.213 4.290 oilp+↛cpi2.003 (0.408) 10.127 7.018 3.024 oilp-↛cpi3.092 (0.652) 11.023 6.563 5.930 oilp-↛cpi+ 0.823 (0.310) 10.902 7.720 6.346 note: the notation↛indicates the null hypothesis that there is no causality. the values in parentheses indicate the probability values asymptotoically. * indicates the causality relationship between the variables at the 10% significance level. bootstrap count is 10,000 table 8: asymmetric causality test results for china direction of causality mwald bootstrap critical value (1%) bootstrap critical value (5%) bootstrap critical value (10%) oilp+↛cpi+ 0.902 (0.556) 10.231 7.092 3.678 oilp+↛cpi0.345 (0.897) 10.743 7.005 3.920 oilp-↛cpi4.092 (0.231) 12.389 9.034 6.826 oilp-↛cpi+ 4.098 (0.390) 11.978 8.703 6.037 note: the notation↛indicates the null hypothesis that there is no causality. the values in parentheses indicate the probability values asymptotoically. the number of bootstrap is 10,000 table 5: asymmetric causality results for brazil direction of causality mwald bootstrap critical value (1%) bootstrap critical value (5%) bootstrap critical value (10%) oilp+↛cpi+ 2.091 (0.509) 9.012 6.013 3.093 oilp+↛cpi1.023 (0.901) 6.592 6.093 3.120 oilp-↛cpi2.027 (0.481) 9.993 6.231 3.015 oilp-↛cpi+ 0.936 (0.487) 8.906 6.012 2.997 note: the notation↛indicates the null hypothesis that there is no causality. the values in parentheses indicate the probability values asymptotoically. the number of bootstrap is 10,000 syzdykova, et al.: asymmetric causality relationship between oil prices and inflation in bric countries international journal of energy economics and policy | vol 12 • issue 3 • 2022190 the other hand, it is known that oil importing countries struggling with inflation are adversely affected by increasing prices. as a result of the analysis applied in the study, different results were obtained for the bric countries. when the results for brazil and china are analyzed, no asymmetric causality relationship was found between oil price shocks and inflation shocks in these countries. while there is a causal relationship from negative oil price shocks to positive inflation shocks in russia, the same situation was not observed in positive oil price shocks. according to the causality test results for india, there is causality from positive oil shocks to positive inflation shocks at the 90% confidence level. there is no causality running from negative oil price shocks to inflation shocks. the results of the study reveal that inflation rates in brazil and china should be investigated with factors other than oil prices, and pointed out the importance of the effect on inflation for russia and india. however, it is argued in the literature that the effect of oil prices on macroeconomic variables may change over time. therefore, the result of the study may not mean that oil prices will never have an effect on inflation rates in brazil and china, as well as the effect of oil prices on inflation in different time periods for russia and india. for this reason, the scope of the study can be expanded and investigated with different analysis methods by taking these factors into consideration in future studies. 5. references ahmad, f. (2013), the effect of oil prices on unemployment: evidence from pakistan. business and economics research journal, 4(1), 43-50. azretbergenova, g., syzdykova, a. (2020), the dependence of the kazakhstan economy on the oil sector and the importance of export diversification. international journal of energy economics and policy, 10(6), 157. bass, a. (2019), do oil shocks matter for inflation rate in russia: an empirical study of imported inflation hypothesis. international journal of energy economics and policy, 9(2), 288. blanchard, o.j., gali, j. (2007), the macroeconomic effects of oil shocks: why are the 2000s so different from the 1970s? (no. w13368). united states: national bureau of economic research. bp. (2021), statistical review of world energy. available from: https:// www.bp.com/content/dam/bp/business-sites/en/global/corporate/ pdfs/energy-economics/statistical-review/bp-stats-review-2020-fullreport.pdf [last accessed on 2021 dec 18]. cavalcanti, t., jalles, j.t. (2013), macroeconomic effects of oil price shocks in brazil and in the united states. applied energy, 104, 475-486. cerra, v. (2019), how can a strong currency or drop in oil prices raise inflation and the black-market premium? economic modelling, 76, 1-13. chen, j., zhu, x., li, h. (2020), the pass-through effects of oil price shocks on china’s inflation: a time-varying analysis. energy economics, 86, 104695. choi, s., furceri, d., loungani, p., mishra, s., poplawski-ribeiro, m. (2018), oil prices and inflation dynamics: evidence from advanced and developing economies. journal of international money and finance, 82, 71-96. de gregorio, j., landerretche, o., neilson, c., broda, c., rigobon, r. (2007), another pass-through bites the dust? oil prices and inflation. economia, 7(2), 155-208. dey, a.k., edwards, a., das, k.p. (2020), determinants of high crude oil price: a nonstationary extreme value approach. journal of statistical theory and practice, 14(1), 1-14. granger cw, yoon g. hidden cointegration. u of california, economics working paper, (2002-02); 2002. hamilton, j.d., herrera, a.m. (2004), comment: oil shocks and aggregate macroeconomic behavior: the role of monetary policy. journal of money, credit and banking, 36, 265-286. hammoudeh, s., reboredo, j.c. (2018), oil price dynamics and marketbased inflation expectations. energy economics, 75, 484-491. hatemi-j, a. (2003), a new method to choose optimal lag order in stable and unstable var models. applied economics letters, 10(3), 135-137. hatemi-j, a. (2008), forecasting properties of a new method to determine optimal lag order in stable and unstable var models. applied economics letters, 15(4), 239-243. hatemi-j, a., roca, e. (2014), brics and pigs in the presence of uncle sam and big brothers: who drive who? evidence based on asymmetric causality tests. australia: griffith business school discussion papers finance. istiak, k., alam, m.r. (2019), oil prices, policy uncertainty and asymmetries in inflation expectations. journal of economic studies, 46(2), 324-334. ito, k. (2012), the impact of oil price volatility on the macroeconomy in russia. the annals of regional science, 48(3), 695-702. jacquinot, p., kuismanen, m., mestre, r., spitzer, m. (2009), an assessment of the inflationary impact of oil shocks in the euro area. the energy journal, 30(1), 49-83. jia, z., wen, s., lin, b. (2021), the effects and reacts of covid-19 pandemic and international oil price on energy, economy, and environment in china. applied energy, 302, 117612. kartaev, p., medvedev, i. (2019), monetary policy and the effect of the oil prices pass-through to inflation. russian journal of economics, 5, 211. kilian, l. (2008), a comparison of the effects of exogenous oil supply shocks on output and inflation in the g7 countries. journal of the european economic association, 6(1), 78-121. kim, m.s. (2018), impacts of supply and demand factors on declining oil prices. energy, 155, 1059-1065. leblanc, m., chinn, m.d. (2004), do high oil prices presage inflation? the evidence from g-5 countries. uc santa cruz economics working paper (561), 04-04. available from: https://ssrn.com/ abstract=509262 or http://dx.doi.org/10.2139/ssrn.509262 long, s., liang, j. (2018), asymmetric and nonlinear pass-through of global crude oil price to china’s ppi and cpi inflation. economic research-ekonomska istraživanja, 31(1), 240-251. lütkepohl, h. (2005), new introduction to multiple time series analysis. berlin, germany: springer science and business media. meo, m.s., chowdhury, m.a.f., shaikh, g.m., ali, m., sheikh, s.m. (2018), asymmetric impact of oil prices, exchange rate, and inflation on tourism demand in pakistan: new evidence from nonlinear ardl. asia pacific journal of tourism research, 23(4), 408-422. mork, k.a. (1989), oil and the macroeconomy when prices go up and down: an extension of hamilton’s results. journal of political economy, 97(3), 740-744. nasir, m.a., naidoo, l., shahbaz, m., amoo, n. (2018), implications of oil prices shocks for the major emerging economies: a comparative analysis of brics. energy economics, 76, 76-88. oloko, t.f., ogbonna, a.e., adedeji, a.a., lakhani, n. (2021), oil price shocks and inflation rate persistence: a fractional cointegration var approach. economic analysis and policy, 70, 259-275. sultan, z.a., alkhateeb, t.t.y., fawaz, m.m. (2020), empirical investigation of relationship between oil price and inflation: the case of india. international journal of energy economics and policy, 10(3), 90-94. syzdykova, et al.: asymmetric causality relationship between oil prices and inflation in bric countries international journal of energy economics and policy | vol 12 • issue 3 • 2022 191 syzdykova, a. (2018a), the impact of oil prices on bric countries’ stock markets. international journal of economics, business and politics, 2(1), 1-20. syzdykova, a. (2018b), the relationship between the oil price shocks and the stock markets: the example of commonwealth of independent states countries. international journal of energy economics and policy, 8(6), 161-167. trang, n.t.n., hong, d.t.t. (2017), nonlinear effects of oil prices on inflation, growth, budget deficit, and unemployment. journal of economic development, 24(1), 73-89. volkov, n.i., yuhn, k.h. (2016), oil price shocks and exchange rate movements. global finance journal, 31, 18-30. wen, f., zhang, k., gong, x. (2021), the effects of oil price shocks on inflation in the g7 countries. the north american journal of economics and finance, 57, 101391. zhao, l., zhang, x., wang, s., xu, s. (2016), the effects of oil price shocks on output and inflation in china. energy economics, 53, 101-110. international journal of energy economics and policy vol. 2, no. 2, 2012, pp. 63-70 issn: 2146-4553 www.econjournals.com factors influencing the usage of compact fluorescent lamps in existing residential buildings in lagos, nigeria olusola olugbemileke johnson department of estate management, yaba college of technology, nigeria. e-mail: estatessj1004@yahoo.co.uk abayomi joseph odekoya department of estate management, university of lagos, nigeria. e-mail: abayomiodekoya@gmail.com obinna lawrence umeh department of estate management, university of lagos, nigeria. e-mail: umelobinna@yahoo.com abstract: nigeria as a developing nation is facing increasing demand for electricity especially in the residential areas. the use of compact fluorescent lamps (cfls) is one of the several measures towards reducing the demand. however, in nigeria, the use of cfls is low. the present study was designed to investigate some factors responsible for the low usage of cfls in lagos, nigeria. questionnaires were administered by hand on 984 households, selected through systematic random sampling techniques from 5 local government areas in lagos state. the first building along the major street in each of the local government was selected randomly and every tenth building constituted the sample. a household head was surveyed in each of the building selected, and was asked to rate some factors that might have influenced the usage of cfls. the data generated from the questionnaire were analysed using ranking method. the findings show that inability to measure the saving benefits of cfls on electricity bills, lack of affordability and high initial cost of acquisition and installation were the most important factors which influence the use of the cfls. the study concludes by providing some recommendations on how to achieve sustainable energy management in the lagos and beyond through more efficient residential house lighting. keywords: electricity; energy usage; energy efficiency; incandescent bulbs; compact fluorescent lamps jel classification: q 1. introduction in spite of the slow growth in economic activities in recent years, the demand for electricity in nigeria has continued to increase (ibitoye and adenikinju, 2007; subair and oke, 2008; akinlo, 2009; adaramola and oyewola, 2011). nigeria has electricity peak demand of 2,000 gwh of electricity per day (united nation development programme, 2010). of this electricity demand, residential buildings consume the highest megawatt per hour of electricity than industrial and commercial buildings (central bank of nigeria, 2009). electricity consumption pattern in nigeria for 1979-2007 period in given in figure 1. according to dineen and gallachóir (2011), the residential areas offer significant opportunity for improved energy efficiency. gujba et al., (2011) identified that the nigeria government has focused on the economic and technical viability within its own means to develop its energy plans and policies and has not seriously considered and incorporated environmental and social issues in its plans. investing in energy efficiency measures would help to achieve sustainable energy management especially in residential buildings (community research and development centre, 2009; adaramola and oyewola, 2011). international journal of energy economics and policy, vol. 2, no. 2, 2012, pp.63-70 64 figure 1. electricity consumption pattern in nigeria (1979-2007). source: cbn, 2009 compact fluorescent lamp (cfl) is a kind of energy efficient lamp which consumes much less of energy than incandescent bulbs (ils). cfls are simply miniature version of full-sized fluorescent. the usage of cfls instead of incandescent bulbs (ils) in residential areas offer significant measures through which nigeria can achieve sustainable energy management in the residential areas. a considerable body of research exists on the technical benefits of retrofitting ils with cfls. for instance, casillas and kammen (2011) stipulated that the cfls installation provided the most attractive financial investment, with an internal rate of return (irr) of 528%. bertoldi and atanasiu (2006) also reported that the payback for switching from ils to cfls depends on the initial purchasing costs, the cost of electricity, and the rate of use. the authors opined that the evidence that the payback is typically less than a year is unambiguous to identify. xing, hewitt and griffiths, (2011) opined that the replacement of inefficient lamps is usually the first choice for low carbon refurbishment due to the fact of a significant reduction in electricity usage with relatively cheaper means. furthermore, cfls consume 1/4th to 1/5th of the energy used by incandescent light bulbs to provide the same level of light (kumar et al., 2003; iea, 2006; waide, 2006). cfls now fit the sockets of incandescent bulbs, which is an improvement that reduces cost of installation. furthermore, about 25% of energy consumed by cfls is converted to visible light compared with just 5% for a conventional incandescent lamp (xing, et al., 2011). cfls also have much longer lifetimes with rated life spans of 5,000 to 25,000 hours compared to 1,000 hours on average for incandescent lamps (iea, 2006). globally, incandescent lamps are estimated to have accounted for 970 twh of final electricity consumption in 2005 and given rise to about 560 mt of co2 emissions (iea, 2006). about 61% of this demand was in the residential sector with most of the rest in commercial and public buildings (iea, 2006). in the hypothetical case that all these lamps were to be replaced by compact fluorescent lamps (cfls), cumulatively this would reduce global net lighting costs by usd 1.3 trillion from 2008 to 2030, and avoid 6.4 gtco2 emissions at negative abatement cost. in nigeria, saving potentials of retrofitting ils with cfls have been estimated, community research and development centre (credc, 2009) opined, if a particular household using 20 incandescent bulbs of 60w decides to replace them with energy saving bulbs of 20w, instead of spending 1200w/h (20 x 60w) for lighting, they will be spending 400 watts per hour (20 x 20w). thus this saves approximately 67% of energy for lighting alone. on a larger scale, if nigeria as a country phase out one million incandescent bulbs and replace them with energy saving bulbs, the factors influencing the usage of compact fluorescent lamps in existing residential buildings in lagos, nigeria 65 country will be saving about 40mw of electricity. this is enough to provide electricity to many communities in nigeria. if each of the 36 states and the fct replace one million incandescent bulbs each, we can save up to 1480mw of electricity. in another project feasibility report by global environment facility (gef, 2010) towards promoting energy efficiency in residential and public sector in nigeria, it was estimated that the replacement of 1 million energy inefficient incandescent of 60w light bulbs with more efficient cfl 15w will result in direct greenhouse gas emission reductions during the project’s implementation phase of 4 years, direct greenhouse gas emission reductions totalling 92,000 tco2e will be achieved from the energy savings (184,000 tco2e or 0.184 mtco2e over the lifetime of cfl (8,000 hours). sule et al., (2011), also investigated savings potential of retrofitting ils with cfls from university of ilorin government reserved area (gra) quarters and lower niger river basin staff quarters. the authors hypothesized that “the energy consumption before the installation of cfls is not significantly different from energy consumption after the installation of cfls”. results show that there were significant differences between the energy consumption before and after installations of cfls, and about 40 per cent reduction in electricity consumption was achieved through the use of cfls in the residential households. despite the proven benefits, the usage of cfls has been puzzling slow all over the world (menanteau and lefebvre, 2000; iea, 2006). according to iea (2006), ils represents the most commonly sold lamps in the world. ils dominates retail lamp sales especially in the residential sector in most countries. the author estimated that 13.2 billion ils were sold in 2003 representing over 72% of the global lamp market by volume that year. in contrast, cfls sales in 2003 are estimated at 1.1 billion units, representing approximately 6% of the global lighting market by volume; the low sales invariably translate to low usage of cfls. it is therefore worrisome that despite the introduction of cfls in the early 1980’s, the improvement in its functionality and the associated benefits, the usage of cfls is still low. a variety of factors from different countries have been advanced to explain this phenomenon. for instance, the upfront cost of purchase and installing cfls is a deterrent to household usage of cfls (gadgil and de martino jannuzzi, 1991; balachandra and shekar, 2001; kumar et al., 2003). a city size is also an important factor, which has been reported in literature as a factor supporting low usage of cfls. sandahl et al., (2006) opined that large cities may have a greater array on retail outlets, making it easier for households to find and purchase cfls. large cities may also have been differentially targeted by electrical utilities with information campaigns on energy-saving bulbs, given decreased transaction costs of such campaigns in high density areas (sandahl et al., 2006). information and awareness constraints have often been cited as a significant barrier to adoption of cfls (kumar et al., 2003; sathaye and murtishaw, 2004). income or affordability and lack of guarantee of performance and where to purchase cfls were other factors considered by (kumar et al., 2003). other factors found in literature are as follows: problem of disposal due to mercury content of cfls; proliferation of sub-standard cfls and difficulty in measuring the economic advantages of the usage of cfls (community research and development centre, 2009). to the best of our knowledge, no published articles in the literature have investigated the factors influencing the low usage of cfls in existing residential buildings in lagos, nigeria, which has the highest number of households as at 2007 with an estimate of 2,497, 419 million (national bureau of statistics, 2009) and most populated in nigeria (lagos state government, 2006). this study therefore investigates these factors. it is hoped that the result will contribute to the understanding of how to increase the acceptability of the cfls aimed at a sustainable energy usage the residential areas. the remainder of this paper is organised as follows. section 2 provides a description of methodology. section 3 provides the result. the concluding section 4 proffers recommendations. 2. methodology a survey of households was conducted during may to july, 2011 to investigate the factors influencing the usage of cfls in residential areas of lagos, nigeria. several factors influencing the usage of cfls in residential areas were identified in literature (kumar et al., 2003; sathaye and murtishaw, 2004; community research and development centre, 2009). these factors were then rephrased and expanded into 7 statements based on the characteristics of the study area. these factors include: high initial cost, inability to measure benefits of cfls, health hazard of cfls because of its international journal of energy economics and policy, vol. 2, no. 2, 2012, pp.63-70 66 mercury content, proliferation of inferior cfls in the market, lack of awareness of cfls, nonaffordability and no guarantee from retailers in case of mal-function of cfls. the questionnaire was broadly divided into the following sections: section a covers personal information about the respondent’s sex, age, educational qualifications, income, etc. section b covers information on the level of usage of cfls by household and the factors influencing their usage of cfls. the respondents were asked to rank how significant these factors influence their usage of cfls based on a five point likert scale (1=not significant, 2=somewhat significant, 3=fairly significant, 4=significant and 5=very significant). the five point likert scale was selected as it provides unambiguous results and has ease of use (ekanayake and ofori, 2004). questionnaires were self-administered to households who were selected from five local governments out of the twenty in lagos state. the selected local governments were: shomolu, kosofe, mushin, oshodi-isolo and lagos mainland local governments. in each of the selected local governments, 300 questionnaires were administered to a head of household. in all, a total of 1,500 households were selected systematically through random technique. having identified the major streets in the selected local government, the first building along the streets was chosen randomly and every tenth building constituted the sample. out of the 1,500 households, 988 questionnaires were retrieved, while only 4 questionnaires were invalid due to error of partial completion, 984 valid questionnaires were therefore used for the analysis representing 66%. in this study, the cronbach’s coefficient alpha was calculated to ascertain the reliability of the five-point scale which has been used in the survey. the reliability test measures the internal consistency among the factors influencing the usage of cfls. the reliability test of the 7 factors was 0.8411 which is above 0.5, indicating that the five-point scale measurement was reliable at the 5 percent significance level. kendall’s coefficient of concordance of the sample data was also computed, which was useful to measure the agreement of household on their rankings of the factors influencing the low usage of cfls in their homes. according to yeung et al., (2007), a value of the kendall’s coefficient of concordance that is equal to 1 means that all the respondents’ rank of the factors are similar, while a value of the kendall’s coefficient of concordance that is equal to 0 indicates that all the respondents’ rank of the factors are totally differently. after checking the reliability of the scale, the data collected were then analysed using spss 17.0 package. the analyses were divided into two parts. part one focused on the presentation of the characteristics of the household; frequency tables were used for these presentations. part two focused on the factors influencing the usage of cfls in existing residential areas of lagos state; this was presented using the “mean score”. to be able to quantify these, the authors used the following criteria based on a scale of 1-5: 1. if the mean score is less than or equal to 1.49, then household perceived the factors responsible for the low usage of cfls as being “very insignificant”; 2. if the mean score is between 1.50 and 2.49, then household perceived the factors responsible for the low usage of cfls as being “insignificant”; 3. if the mean score is between 2.50 and 3.49, then household perceived the factors responsible for the low usage of cfls as being “average”; 4. if the mean score is between 3.50 and 4.49, then household perceived the factors responsible for the low usage of cfls as being “significant”; and 5. if the mean score is between 4.50 and 5, then household perceived the factors responsible for the low usage of cfls as being “very significant” 3. results and discussions 3.1 characteristics of the respondents responses to questions on the characteristics of the respondents in terms of their gender, age, level of education and annual income are presented in table 1. from the responses, it can be deduced that males’ responses were greater than females within the study areas. specifically 96.1% of the respondents were male and 3.9% females. this huge disparity is expected since the culture and tradition of the country place men households heads. in terms of the age, respondents in the age bracket of 51 years above dominated the sample. a total of 804 respondents fell within this group representing 81.7%. while 28 respondents fell within the less than 30 years group; 43 respondents fell factors influencing the usage of compact fluorescent lamps in existing residential buildings in lagos, nigeria 67 within the age bracket between 31 – 40 years representing 4.4% and 109 respondents fell within the age bracket between 41 – 50 years representing 11.1%. the results of the analysis on educational qualification of the respondents revealed that 9% of the respondents hold primary school certificate; 20.6% hold secondary school certificate; 22.0% ond/nce; 41.6% hold hnd/bsc and 6.8% hold msc/phd representing 6.8%. the analysis on the level of income of the households revealed that 12 of the households representing 1.2% of the total responses fell within the group of those earning below n100,000 per annum. a total of 102 respondents representing 10.4% fell within the income group of between n101,000 and n300,000, while 153 respondents representing 15.9% fell within the income group of between n301,000 and n500,000. those earning between n501,000 and n700,000 were 408 respondents representing 41.5% of the entire responses. earning between n701,000 and n1,000,000 were 219 household accounting for 22.3% of the entire responses. 63 household representing 6.4% were those earning between n1,010,000 and n3,000,000. earning above n3,000,000 were 27 respondents representing 2.74% of the total responses. this result therefore confirmed there was a general low level income among household in the study areas. this is because, 309 households representing 31.4% were earning above n700,000 per annum. table 1. characteristics of households descriptions gender frequency percentage male 946 96.1 female 38 3.9 total 984 100 age < 30 28 2.8 between 31-40 43 4.4 between 41-50 109 11.1 >51 804 81.7 total 984 100 educational level primary school certificate 89 9.0 secondary school certificate 203 20.6 ond/nce 216 22.0 hnd/bsc 409 41.6 msc and above 67 6.8 total 984 100 income < n100,000 12 1.2 between n101,000 – n300,000 102 10.4 between n301,000 – n500,000 153 15.5 between n501,000 – n700,000 408 41.5 between n701,000 – n1,000,000 219 22.3 between n1,010,000 – n3,000,000 63 6.4 > n3,000,000 27 2.7 total 984 100 3.2 usage of cfls results to the question that focused on investigating the usage of cfls among the respondents are presented in table 2. this result confirmed the low usage of cfls in the study areas. it is observed from table 2 that only 9.6% of them had bought or used cfls in all spaces requiring lighting in their homes, while 90.4% did not. the factors responsible for this, among those who did not use cfls were investigated in the next section. international journal of energy economics and policy, vol. 2, no. 2, 2012, pp.63-70 68 table 2. usage of cfls usage of cfls frequency percent yes 94 9.6 no 781 90.4 total 984 100 3.3 factors responsible for household’ low usage of cfls this section investigates the factors responsible for the low usage of cfls in the study areas. the means and standard deviations of the 7 factors influencing the low-level usage of cfls in existing residential areas in lagos state are shown in table 3 below. the computed mean score revealed that inability to measure the saving benefits of cfls on electricity bills was ranked 1st with a mean score of 4.76. this result is ‘very significant’ based on the scale adopted in this study. the result could be attributed to the apparent inefficient metering system by power holding company of nigeria (phcn) (the organisation that is responsible for power generation and distribution in nigeria). the use of prepaid meters, which was recently introduced by phcn can help achieve accurate billings. however, this has not been widely distributed in many parts of nigeria. in many homes, the meters installed by phcn are no longer functioning. phcn therefore results to the use of estimated bill, this practice further makes it difficult for households to measure the benefits of cfls. in 2nd position was affordability with a mean score of 4.69. this is also ‘very significant’ based on the study mean classifications. this result was also expected; about 70.8% of nigerians live below the international poverty line of $1 per day (united nations development program, 2007). the cost of ils is averagely n40 for 60 watts, while inferior cfls are in the range of n100 to n150 for 15 watts and standard 60 watts cfls are in the range of n1,000 to n1,500. thus, many households are not able to afford the cost of purchase and installation of good quality or standard cfls. ranked 3rd was high initial cost of acquisition and installation of cfls with a mean score of 4.51. this is also ‘very significant’. this result could be attributed to the apparent lack of cfls manufacturing companies in nigeria. the country therefore heavily relies on importation to meet her housing lighting needs. cost of shipment, insurance and import duties paid on cfls importation could be further causing high cost of acquisition. in 4th position was proliferation of inferior or sub-standard cfls in the market with a mean a score of 4.21. the result is ‘significant’ based on the classification of the mean score rating adopted for the study. the outcome of the study could be attributed to the fact that some nigerian businessmen import inferior cfls from countries like china, indonesia, and india into the nigerian market. they capitalise on the apparent weak laws and regulations governing importation of products into nigeria. standard organisation of nigeria (son), the organisation that is responsible for ensuring products are of quality standards is therefore underperforming. furthermore, nigeria regional boarders are porous and become avenues for massive smuggling of inferior cfls into the country. this implies that cfls in the market would not last long, making household preferring to continue using the ils instead of cfls. awareness of cfls was ranked 5th with a mean score of 3.59. this result is ‘fairly significant’. in 6th was no guarantee of the performance from cfls retailers with a mean score of 1.67. this result is ‘insignificant’ based on the mean classification adopted for the study. this factor is contrary to the findings of kumar et al., (2003), they found guarantee to be a major deterrent in the purchase of cfls among all income groups sampled in indian. ranked 7th was health hazard associated with cfls due to presence of mercury content with a mean score of 1.34. this factor is ‘very insignificant’, suggesting that respondents do not find it as a deterring variable influencing their usage of cfls. kendall’s coefficient of concordance of the sample data was computed for measuring the agreement of the respondents on their rankings of the factors influencing the low usage of cfls. the kendall’s coefficient of concordance for ranking the 7 factors is 0.218, which is statistically significant at 1 percent level, implying that the respondents in the study areas survey shared similar opinions about the relative importance of the 7 factors influencing their low usage of cfls. factors influencing the usage of compact fluorescent lamps in existing residential buildings in lagos, nigeria 69 table 3. factors responsible for household’ low usage of cfls factor mean sd rank high initial cost/expensive 4.51 0.89 3 inability to measure benefits of cfls 4.76 1.18 1 health hazard of cfls because of its mercury content 1.34 0.04 7 proliferation of inferior cfls in the market 4.21 0.69 4 awareness of cfls 3.59 0.44 5 lack of affordability 4.69 0.91 2 no guarantee upon mal-functioning of cfls 1.67 0.07 6 4. conclusion this study has presented the findings from a questionnaire survey conducted in lagos, nigeria investigating the factors influencing the low usage of cfls in existing residential buildings. ranking analysis was used to identify the relative importance of the 7 factors gleaned from literature. the findings show that “inability to measure the saving benefits of cfls on electricity bills as the most important factor influencing the low usage cfls. this is followed by affordability, high initial cost of acquisition and installation of cfls, proliferation of inferior cfls in the market, awareness of cfls, no guarantee of the performance from cfls retailers and health hazard associated with cfls due to presence of mercury content. the results revealed in this study are of great benefit to the three tiers of government in nigeria. nigeria governments could use the outcome of the study as a sound platform towards promoting the usage of cfls in the study areas and in nigeria as whole. the results also help deepen electric power authorities’ understandings about the major barriers they would encounter in promoting the usage of cfls, so that attention and efforts can be devoted to solving them. based on the findings, the following recommendations might help promote the use of cfls in the study areas and in nigeria as a whole: 1. consumer awareness should be increased in the study areas and in nigeria as a whole through more advertising efforts, seminars, conferences and trade shows both by the government and ngos. 2. there is need for accurate and credible metering system so that household can easily measure economic benefits associated with use of cfls. 3. groups such as landlord associations, community development associations (cdas), residents association and professionals in the built environment in the different states of the federation should be furnished with results from the demonstration projects so that they can be used effectively. 4. there should be incentives from the government of nigeria towards manufacturers of energy efficient bulbs to site their plants in nigeria. most of the manufacturers are presently located in china and they export these bulbs to many countries around the globe. nigeria has a viable market for lighting with an estimated population of 154 million and a strong workforce that can support the industry. when these companies are sited in nigeria, the cost of the light bulbs will go down considerably to the extent that many poor households can afford to pay the initial cost which in most cases deters them. 5. the standard organization of nigeria (son) should ensure that the energy efficient bulbs in the nigerian market are of good quality in terms of the number of hours they take to burn out. references adaramola, m.s., oyewola, o.m. (2011) evaluating the performance of wind turbines in selected locations in oyo state, nigeria. renewable energy, 36(12), 3297-3304. adaramola, m.s., oyewola, o.m. (2011) on wind speed pattern and energy potential in nigeria. energy policy, 39, 2501–2506. akinlo, a.e. (2009): electricity consumption and economic growth in nigeria: evidence from cointegration and co-feature analysis. journal of policy modelling. 31, 681–693. balachandra, p., shekar, g.l. (2001) energy technology portfolio analysis: an example of lighting for residential sector energy conversion and management, 42, 813-832. international journal of energy economics and policy, vol. 2, no. 2, 2012, pp.63-70 70 bertoldi, p., atanasiu, b. (2009) electricity consumption and efficiency trends in the enlarged european union. status report 2009. european commission, directorate-general joint research center. institute for environment and sustainability. ispra, italy. casillas, c.e., kammen, d.m, (2011) the delivery of low-cost, low-carbon rural energy services. energy policy, 39(8), 4520-4528. central bank of nigeria (2009). central bank of nigeria statistical bulletin. cbn press, abuja. community research and development centre (2009): energy efficiency survey in nigeria, a guide for developing policy and legislation. dineen, d., gallachóir, b.p. (2011) modelling the impacts of building regulations and a property bubble on residential space and water heating. energy and buildings, 43(1), 166-178. ekanayake, l.l., ofori, g. (2004) building waste assessment score: design-based tool. building and environment, 39, 851-861. gadgil, a.j., de martino jannuzzi, g., (1991) conservation potential of compact fluorescent lamps in india and brazil. energy policy, 19(5), 449–463. global environment facility (2010) nigeria– ee appliances – ceo endorsement request. gujba, h., mulugetta, y., azapagic, a., (2011) power generation scenarios for nigeria: an environmental and economic assessment. energy policy, 39, 968–980. ibitoye, f.i., adenikinju, a., (2007) future demand for electricity in nigeria. applied energy, 84, 492–504. iea, (2006) light’s labour’s lost: polices for energy efficient lighting, iea/oecd, paris. kumar, a., jain, s.k., bansal, n.k. (2003) “disseminating energy-efficient technologies: a case study of compact fluorescent lamps in india.” energy policy. 31, 259-272. lagos state government (2010) household survey 2010 edition, lagos bureau of statistics. menanteau, p., lefebvre, h. (2003) “competing technologies and the diffusion of innovations: the emergence of energy-efficient lamps in the residential sector.” research policy, 29(3), 375389. national bureau of statistics (2009) social statistics in nigeria, federal republic of nigeria sathaye, j., murtishaw, s. (2004) market failures, consumer preferences, and transaction costs in energy efficiency purchase decisions. consultant report no. cec-500-2005-020 for the california energy commission. sandahl, l.j., gilbride, t.l., ledbetter, m.r., steward, h.e., calwell, c. (2006) compact fluorescent lighting in america: lessons learned on the way to the market. pacofoc northwest national laboratory. subair, k., oke, d.m. (2008) privatization and trends of aggregate consumption of electricity in nigeria: an empirical analysis. african journal of accounting economics finance and banking research, 3(3), 18-27. sule, b.f., ajao, k.r., ajimotokan, h.a., garba, m.k. (2011) compact fluorescent lamps and electricity consumption trend in residential buildings in ilorin, nigeria international journal of energy sector management, 5(2), 162-168. united nations development program (2007). human development report. waide, p. (2006) light’s labour’s lost – policies for energy-efficient lighting. international energy agency: paris. xing, y., hewitt, n., griffiths, p. (2011) zero carbon buildings refurbishment––a hierarchical pathway, renewable and sustainable energy reviews, 15(2011), 3229–3236. yeung, f.y., chan, a.p.c., chan, w.m., li, l.k. (2007), “developing of a partnering performance index (ppi) for construction projects in hong kong: a delphi study”, construction management and economics, 25(12), 1219-37. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 3 • 2022236 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(3), 236-246. investigating the interactive role of demand side factors potentially responsible for energy crisis in pakistan sohail amjed1, iqtidar ali shah2*, adnan riaz3 1department of business administration, university of technology and applied sciences, muscat, oman, 2department of business administration, yorkville university, british columbia, canada, 3department of business administration, allama iqbal open university islamabad, pakistan. *email: ishah@yorkvilleu.ca received: 19 january 2022 accepted: 15 april 2022 doi: https://doi.org/10.32479/ijeep.12930 abstract this paper attempts to investigate the dynamic relationship among energy consumption (e), financial system development (f), industrailization (i), agriculture development (a) and economic growth (y) in case of pakistan for the period 1971-2018 by using cointegration approach. after confirming the level of stationarity, the presence of long run relationship among the series was tested through newly developed combined cointegration approach in addition to ardl bound testing with structural break dummy. the short run and long run parameter coefficients were estimated by unrestricted error correction model (uecm) because all the series are found stationary at 1st difference i(1) and sufficient evidence of cointegration. finally, the direction of causality among the considered variables was achieved through granger causality test within the framework of vecm. the long run parameter coefficient estimates by uecm indicate that financial development, industrialization, economic growth and decrease in agricultural contribution to gdp induce electricity consumption in pakistan. we also found that a long-run unidirectional causality is running from the economic growth to electricity consumption which favors the electricity conservation hypothesis in case of pakistan. the causality running from the electricity consumption to agriculture output coupled with negative parameter coefficient value suggests that electric power deficit is responsible for hampering the agricultural growth in pakistan. the study suggests that electricity conservation policy in addition to prudent rationing of electric power among the various sectors may greatly contribute to minimize the adverse effects of energy crisis in pakistan. keywords: financial development, industrialization, agriculture development, economic growth, energy crises, pakistan jel classifications: q43, o14, q18, f43, g00 1. introduction energy is undoubtedly a driver of economic growth and a crucial input to nearly every good and service produced in the economy. however, energy is a capital-intensive sector which requires substantial investments and long hatching time. therefore, a prudent energy policy is crucial for the sustainable and balanced economic growth of a country. according to the international energy agency (2021) cumulative global energy investment is set to rise 1.9 trillion which is nearly 10% higher than 2020. this unprecedented 10% increase is a reversal to the all-time low caused by pandemic (world energy investment, 2021). the significant growth in the investment in energy sector is result of increased energy demand which is estimated to be 4.6% in 2021. this rapidly increasing energy demand would be one of the biggest challenges confronting the world (khan and ahmed, 2008). the relationship between energy consumption, economic growth and related factors is well-researched in the literature. however, there is a lack of consensus in the extant literature over the direction of causality between energy consumption and economic growth patterns across countries. the inconsistency of empirical evidence regarding the direction of causality may be attributed to the selection of variables, econometric approaches, period this journal is licensed under a creative commons attribution 4.0 international license amjed, et al.: investigating the interactive role of demand side factors potentially responsible for energy crisis in pakistan international journal of energy economics and policy | vol 12 • issue 3 • 2022 237 of the study, and specification of the model. karanfil (2009) contended that the replication of energy-growth nexus studies in different economies produces conflicting and mixed results which merely serve the purpose of policy makers. thus, it is essential to undertake specific research studies by considering the specific challenges confronting the economy. we argue that a country’s peculiar economic development pattern and institutional differences associated with the level of economic development affect the energy-growth nexus in different ways. therefore, it is important to scan the interactive role of factors affecting the energy consumption patterns with reference to the particular economic challenges confronting an economy to offer viable solutions to the policy makers. during the last few decades many developing countries have experienced a manifold growth in electricity demand as a result of economic development. however, few countries like pakistan failed to expand the electric power generation capacity in anticipation to growing demand for electricity, resultantly suffering acute energy crises. the energy crises of pakistan are deep rooted and multifaceted with numerous possible solutions. as a short-term measure, the government of pakistan prioritized the household sector over industrial sector for electric power supply to avoid the public demonstrations and agitation. the temporary relief to household sector at the cost of economic growth has worsened the crisis. this panic action of the government has adversely affected the industrial sector and agricultural sector. aziz et al. (2010) estimated a loss of $3.8 billion to the economy in 2009—about 2.5 percent of the gross domestic product (gdp) as a result of power shortages in the industrial sector alone. half a million jobs and exports worth $1.3 billion were lost. many industrial units that could not afford the private power generation were either shut down or moved to other countries like bangladesh, malaysia and middle eastern countries, resultantly many people lost their jobs. private power generation companies were unable to produce at the full capacity due to financial distress resulting from non-collection of revenues and increased level of circular debt. a variety of factors is generally considered responsible for the present energy crisis in pakistan, for instance, circular debt, lack of political will, lack of good governance, theft and non-payment of electricity bills, line losses, and deteriorated transmission infrastructure. pakistan is facing energy shortage since very beginning, however, the energy crises start worsening after the year 2007 because the power generation could not be proportionately increased to cater the growing energy demand stemming from increased economic activity. the role of liberal credit policies during 2002 to 2007 in energy crises cannot be overlooked. the irrational exuberance in car financing and other domestic loans by banks for energy consuming household items such as refrigerators, air conditioners, and televisions significantly increased the energy demand. pakistan is basically an agrarian economy; agriculture sector contributed 19.2 percent in gdp in 2020-21 and is a source of livelihood of 38.5 percent of the labor force (latest; pakistan economics survey 2020-21). the agriculture sector is third biggest consumer of energy after household and industry (economic survey of pakistan 2020-2021). the share of energy consumption in agriculture has continuously decreased from 19 percent and 14 percent in 1972 to 11 percent and 1 percent in 2005 in the case of electricity and petroleum respectively (mushtaq et al., 2007). agriculture sector is a huge supporter to industrial sector because it provides various inputs/raw materials to industries such as cotton, sugarcane etc. for example, the textile industry is the biggest industry in pakistan, consume a large volume of cotton which in turn is used to produce 55% of pakistan’s textile exports. thus, a strong link exists between agriculture and industrial sector in pakistan. low productivity in agriculture due to energy deficiency or any other reasons will greatly affect the industrial output. industrial sector is the biggest consumer of energy in pakistan. the growth rate of the large-scale manufacturing has been dropped from 18.8% in 2004-2005 to −6.1% in fiscal year 2009 due to severe energy shortages (pakistan economic survey 2009-10 and 2020-21). after year 2009 lsm start recovering due to the government’s efforts to provide energy to the industry. the large scale manufacturing sector reported steady growth until fy2019 when pandemic badly affected the world economy. the similar trend of low production rate has been seen in most of the small-scale manufacturing industries (qazi et al., 2012). thus, the energy deficiency affects the industrial sector in two ways, a direct effect as energy is considered as a factor of production. secondly, low production of agriculture due to energy deficiency also affect industrial sector. it has been well recognized that a long run relationship of financial system, industrial sector and agriculture development, economic growth exist in a country. however, the direction of causality remains an open research question in most of the developing economies. therefore, an investigation into the interactive relationship and direction of causality between financial system development, industrialization and agriculture development in a particular economic environment may greatly improve our understanding and provide insights to the policy makers. this study contributes to the literature in two novel ways. first, a pioneering study to investigate the dynamic relationship among the demand-side macroeconomic factors potentially responsible for the energy crisis in pakistan and the discussions on the results are carried out with reference to the economic challenges amid energy crises. moreover, this is the first study, with reference to pakistan, which considered financial development, industrial growth, agricultural development and economic growth into the energygrowth nexus by using the longest available data from 1971 to 2018 and contemporary econometric approaches such as bayer and hanck (2013) combined cointegration. second, methodologically this study has four-fold contribution to the literature; (i) the time series properties of the variables were tested by using zaviot and andrews unit root test in presence of structural breaks in addition to standard unit root tests such as augmented dicky fuller (adf) and philips-perron (pp), (ii) the presence of long run relationship is confirmed by using combined cointegration approach newly proposed by bayer and hanck (2013) and as robustness check breaks was also applied auto regressive distributed lag (ardl) bound testing approach in presence of structural breaks, (iii) the short run and long-run elasticity estimates were achieved by amjed, et al.: investigating the interactive role of demand side factors potentially responsible for energy crisis in pakistan international journal of energy economics and policy | vol 12 • issue 3 • 2022238 unrestricted vector auto regressive (var) model, (iv) the short run and long run causal relationship was tested by granger cause approach within the framework of vector error correction model (vecm). the study is limited to the macroeconomic variables which directly impact economic growth such as financial development, industrial development and agriculture. the other demand side macroeconomic variables such housing and population growth, income growth, livening standard and weather are not included in this study. this paper attempts to investigate the interactive role of demand side factors such as financial development, industrialization, agricultural development and economic growth in electricity consumption in pakistan using cointegration methodology over the period 1971 to 2018. the empirical findings show that a long run relationship exists among the model variables. industrialization, financial development and economic growth induce energy consumption in long run. the decrease in the contribution of agricultural sector to gdp also affect the electricity consumption positively. the long run unidirectional causality running from economic growth to electricity consumption validates the conservation hypothesis in the long run, in case of electricity consumption in pakistan. the rest of the paper has been organized as follows; section 2 presents the brief account of existing literature related to our topic, in section 3 we have described the data collection and empirical framework, the results have been discussed in section 4 and section 5 concludes the paper with some policy implications. 2. review of the literature it has become a stylized fact that energy consumption is crucial for the economic growth of a country. however, the empirical evidence about the direction of causality between energy consumption and economic growth show mixed and conflicting results. in a comprehensive survey of literature payne (2010) suggested that the empirical inquiries into the energy-growth nexus may greatly contribute to the policy formulation if the direction of causality is established between energy consumption and economic growth. squalli (2007) proposed the following four testable hypotheses with great policy implications for energygrowth nexus; (i) growth hypothesis, postulate the unidirectional causality running from the energy consumption to growth (ii) conservation hypothesis, suggesting the unidirectional causality running from the economic growth to energy consumption, (iii) neutrality hypothesis, suggesting no causal relation between energy consumption and economic growth, (iv) feedback hypothesis, which suggests a bidirectional causal relation between energy consumption and economic growth. if the causality is running from the energy consumption to the economic growth, any energy conservation policy may adversely affect the economic growth and if the unidirectional causality is running from the economic growth to energy consumption, the energy conservation policy may contribute to the reduction of co2 emissions without compromising the economic growth (ozturk, 2010; shahbaz and lean, 2012). similarly, the relationship between energy consumption and other variables (determinants economic growth) can be tested in light of similar four hypotheses. 2.1. relationship between economic growth and energy consumption beginning with the seminal work of kraft and kraft (1978), there has been growing number of studies that have investigated the energy consumption and economic growth nexus. the empirical results pose a great deal of controversies for the direction of causality between economic growth and energy consumption (e.g., asafu-adjaye, 2000; aqeel and but, 2001; ang, 2008; ozturk and acaravci, 2010; wang et al., 2011; apergis and payne, 2010; arouri et al., 2012; choudhray et al., 2012; menegaki, 2019; emir and bekun, 2019; žiković et al., 2020; cheng et al., 2021). this contradiction in the energy economics literature may be attributed to the variety of econometric approaches used to study the energygrowth nexus in addition to the institutional differences associated with the level of economic development of a country (shahbaz and lean, 2012). the ambiguity stemming from the inconsistent research findings deteriorate the value of research for policy formulation (shahbaz et al., 2013). a variety of control variables is used to study the energy-growth nexus depending on the research objectives. the inclusion of financial development, industrial development and agriculture development in this study enables us to highlight the role of the demand side factors in the present energy crises of pakistan. karanfil (2008) suggested that the relationship between official gdp and energy consumption may not produce reliable results in developing economies due to unrecorded economic activities. therefore, the interactive role of determinates of economic growth may provide better insights into the issue under the consideration. 2.2. relationship between financial development and energy consumption a sound financial system by efficient channeling of funds from lenders to borrowers and effective placement of capital in the progressive and innovative investment projects may greatly contribute to the economic development of a country (siva and rao, 2018; nyasha and odhiambo, 2018; asteriou and spanos, 2019). financial system development plays an important role in economic growth of a country by generating positive economic activity through attracting fdi (frankel and romer, 1999). however, financial development with poor regulatory environment and inefficient funds transmission mechanism may potentially harm the economic growth in transition economies (de gregorio and guidotti, 1995; hassan et al., 2011). the financial liberalization without considering the dynamics of the economy may adversely affect the economic growth (arestis and demetriades, 1997; levine, 2001; tamazian et al., 2009; stiglitz, 2010). during last few decades, many transition economies have undergone structural transformation and shifting from planned to market economy. a rapid increase in the energy demand as the result of financial development, industrialization, and infrastructure expansion have been recorded during the period of the transformational stage. sadorsky (2010) confirmed the impact amjed, et al.: investigating the interactive role of demand side factors potentially responsible for energy crisis in pakistan international journal of energy economics and policy | vol 12 • issue 3 • 2022 239 of financial system development on the energy consumption in 22 emerging economies by applying generalized moment method on the capital market data. sadorsky (2011) also found similar results in the case of central and eastern european countries. almulali and sab (2012) by applying the panel data methodologies found a significant and positive relationship between energy consumption and financial system developments. shahbaz and lean (2012) investigated the role of financial development and industrialization in energy consumption level in case of tunisia and confirmed the long run bidirectional causality between financial system development and energy consumption as well as between industrialization and energy consumption. islam et al. (2013) also confirmed the long-run relationship between energy consumption and financial development in malaysia by using vecm approach. shahbaz et al. (2013) found empirical evidence to validate the long-run relationship between energy consumption and financial development. çoban and topcu (2013) reported a positive link between energy consumption and financial development in the case of uae. similarly, salahuddin et al. (2015) also confirmed the positive relationship between financial development and energy consumption in gulf cooperation council (gcc) countries. however, in 27 eu countries, no significant relationship is detected (çoban and topcu, 2013). tang and tan (2014) reported the unidirectional causality from energy consumption to financial development in the case of malaysia. similar results of unidirectional causality between money supply and energy consumption was found in case of pakistan (kakar et al., 2011). zeren and koc (2014) conducted study for newly industrialized 7 countries spanning the period 1971 till 2010 and found unidirectional causality from energy consumption to financial developments in philippines and two-way causality occurred for india, turkey and thailand. 2.3. relationship between industrial development and energy consumption according to the industrial development report 2011 (unido, 2011) industry is the largest energy user worldwide, consume about 31 percent of world energy since the early 1990s. in developed economies, industry consume only 24 percent of energy (0.8 gtoe) while in developing economies, energy consumption in industry is much faster and remains the main user of energy (1.7 gtoe). the industrial sector of pakistan is the largest sector contributes 20.30% to the gdp (pakistan economic survey, 2020-21). on average industrial sector consumed 37.3% of energy which is higher from all sectors (khan and ahmed, 2008). theoretically, a strong relationship between industrial growth and energy consumption exists but is less focused in the literature and there is lack of empirical evidence in case of pakistan. therefore, shahbaz et al. (2013) suggested the inclusion of industrialization in energy-growth nexus for a better understanding. exploring the relationship between industrial growth and energy consumption is very important because the “use of energy in industry affects every single personally citizen through the cost of goods and services, the quality of manufactured products, the strength of the economy, and the availability of jobs” (national academy of sciences, 2008). a case study of pakistan conducted by qazi et al. (2012), a unidirectional causality was identified which is running from electricity consumption to industrial output. similarly, a uni-directional causality running from electricity consumption and gas consumption to industrial gdp in long-run is identified in tunisia (abid et al., 2012). 2.4. relationship between agriculture development and energy consumption energy is a key input for agriculture development and the dependency of agriculture on electricity consumption in pakistan has increased over time, while power generation has not kept up with demand (ahmed and zeshan, 2014). in pakistan, the relationship between agriculture development and energy consumption has been less focused and is not clear in literature because this relationship has been changed due to rising energy prices and changes in agriculture policies. traditionally, the relationship has been one-way, with agriculture using energy products as an input in production (beckman et al., 2013). moreover, during the past decade, the energy sector’s use of agricultural products as renewable-fuel feed stocks and the use solar energy has increased substantially. although, it is well known that a strong correlation exists between agriculture development and energy consumption. however, no empirical evidence is available in pakistan to show the direction of causality which needs to be investigated which may provide an insight for the policy makers. 3. methodology to investigate the dynamic relationship among energy consumption, financial development, industrialization, agricultural development and economic growth in pakistan, we specified the log-linear model. the empirical relationship among the selected series is represented in the following general form. lnet, = α+βft+βit+ βat+βyt+ԑt (1) where e stands for logarithmic per capita electric power consumption in kwh, f is the logarithmic share of domestic credit by private sector in gdp as a proxy for financial development, i is logarithmic contribution of industry value added in the gdp as a proxy for industrialization, a is logarithmic contribution of agricultural value added in the gdp as proxy for agricultural development and y is economic growth measured as logarithmic per capita real gdp. the data of these variables for the period 1971 to 2018 is taken from the world development indicators (wdi, 2021). all data except electric power consumption is available till 2018. electric power consumption data is available till 2014 which is extrapolated for 4 years. the time series data is generally non-stationary at the level which may produce spurious results if regressed at level. to avoid spurious regression the time series data are transformed to a higher order to induce stationarity. the long run relationship is lost in this transformation process if the appropriate statistical approach is not used. we apply the cointegration to achieve these seemingly contradictory objectives. we specify the following error correction model for estimation of dynamic relationship among the considered variables. amjed, et al.: investigating the interactive role of demand side factors potentially responsible for energy crisis in pakistan international journal of energy economics and policy | vol 12 • issue 3 • 2022240 � � � � � lne lnf lni lnat j p t j k q t k l r t l m s � � � � � � � � � � � � � � � � � � � � � 0 1 1 1 1 llny lne ectt m m t t m t t� � � �� � �� 1 1 � � �� as a standard procedure for time series analysis, we start with an investigation into the order of integration by applying augmented dickey-fuller (adf) and philips-parron (pp) tests of stationarity. adf and pp stationarity tests are often criticized for their inability to handle the possible structural breaks in the series. in the presence of structural breaks, the conventional unit root tests such as adf and pp may produce biased results towards rejection of the null hypothesis of no unit root (perron 1989). in order to avoid this bias we apply zivot and andrews (1992) test of stationarity which considers the structural break in the series thus provides robust results in the presence of one unknown structural break. zaviot and andrews (1992) proposed the following three models to test the order of integration among the variables in the presence of one unknown structural break. a. y du t y c yt a a t a a t j k j a t j t� �� � �� � � �� � ��� � � � �1 1 � b. y t dt y c yt b b b t a t j k j b t j t� � �� � �� � �� � ��� � � � �1 1 � c. y du t dt y c y t c c t c b t a t j k j c t j t � �� � �� �� � �� � � � � �� � � � � � � 1 1 � where dut in model-a represents the dummy intercept showing one structural break in the series, dut =1 in case (t >tb) and zero otherwise. dtt in model-b represents the slope dummy; dtt = (t–tb) provided (t >tb) which shows a change in the slope, tb indicates the year of structural break. after having information about the order of integration we proceed to lag length selection and testing the cointegration among the variables. numerous approaches are used to tests the cointegration for studying the long run relationship such as engle and granger test (1987) johansen and juselius test (1990) boswijik approach (1994) and banerjee et al. (1998) test. the results of these conventional cointegration tests are often inconsistent which complicate the interpretation of the results. the choice of cointegration test is, therefore, always questioned as there is no any single criterion to select the most powerful test, even asymptotically (elliott et al., 2005). modified and robust approaches such as combined cointegration approach and ardl bound testing approach may provide more accurate results to decide about the presence of long run relationship among series. bayer and hanck (2013) proposed a combined cointegration approach which overcomes the biases of conventional methodologies by combining the p-values of individual tests of cointegration by fisher’s (1932) chi-squared test in the following manner. x pii  � � � � �2 2 ln( ) (2) the long run relationship estimation schemes with bayer and hanck (2013) framework is presented below: t p padf max tadf max� �� �� � � � �� � ���� ���2 ln ln (3) ( ) ( ) maxmax ˆ 2 ln lˆ n f f p pλλ  − = − +  (4) ( ) ( )ˆ2 ln lnˆ ecrecr f tf t p pγγ  − = − +   (5) ( ) ( ) ˆ 2 ln ln ln( ) ln( ) ˆ adf max ecr adf ecr max t f t t f t p p p p γ γ γ γ λλ − − − = − + + +  (6) where tadfγ stand for engel-granger, λmax is for johanson, f̂ for boswijk, λmax for banerjee et al. cointegration tests and ˆ, , andadf ecrmax ft tp p p pγ γλ are the p-values of these cointegration tests respectively. the null hypothesis of no cointegration is rejected if the calculated value of the p-values through fisher’s formula is greater than the corresponding critical value tabulated by bayer and hanck (2013) or we accept the null hypothesis otherwise. we also applied ardl bound testing approach to check the cointegration among model variables. ardl bound testing in presence of structural breaks provides robust results by simultaneous inclusion of i(0) and i(1) variables in the model. ardl bound testing approach also provides robust results even in small sample size and in presence of exogenous variables in the model. we specify the ardl model as follows. � � lne t f i a y e lnf t t f t i t a t y t e t j p � � � � � � � � � � � � � � � � � � � � � � � 0 1 1 1 1 1 1 tt j k q t k l r t l m s t m n t t lni lna lny lne � � � � � � � � � � � � � � � � 1 1 1 1 � � � � � � � � mm t� �� where δ is the first difference operator, t is the dummy for structural breaks in the series and ԑt is normally distributed error term. following shahbaz et al. (2015) we include the dummy variable in the model to allow the structural breaks in the series. we calculate ardl f-statistics to check the cointegration among the model variables. we apply wald test to confirm the cointegration with null hypothesis of no cointegration h0: αec=αfd=αid=αad=αed=αco2=0 against the alternative hypothesis h 1: α ec≠α fd≠α id≠α ad≠α ed≠α co2≠0. pesaran et al. (2001) tabulated asymptotic critical upper and lower bound values as decision criteria for hypothesis testing, which are mostly used for large sample size. since we have sample size t-43 we preferred narayan (2005)’s values as decision criteria due to its suitability for small sample size (t=30 to t-80). we compare the calculated f-statistics achieved through wald test with the upper and lower bound critical values tabulated by narayan (2005) for the decision on the no-cointegration hypothesis. we can reject the null hypothesis if the computed f-statistic value is greater than the upper bound critical value. we cannot reject the null hypothesis if the computed f-statistic is smaller than the lower bound critical value. the relationship is nondecisive if the computed f-statistic fall between the upper and lower critical bounds. we also perform various diagnostic tests for amjed, et al.: investigating the interactive role of demand side factors potentially responsible for energy crisis in pakistan international journal of energy economics and policy | vol 12 • issue 3 • 2022 241 time series data to confirm the robustness of our cointegration results. once we get the evidence of cointegration we go for causality analysis. we apply vector error correction model (vecm) to estimate the short run and the long run dynamic causal relationship among the variables. we specify the vecm as follows: ( ) 1 11 12 13 14 15 2 21 22 23 24 25 3 31 32 33 34 35 1 4 41 42 43 44 45 5 51 52 53 54 55 1 1 (1 ) t i i i i i t i i i i ip t i i i i i i t i i i i i t i i i i i t ln e a b b b b b ln f a b b b b b l ln i a l b b b b b ln a a b b b b b ln y a b b b b b ln e = −                        − = + −                        × ∑ 1 1 2 21 3 1 31 4 41 5 51 t tt t tt tt tt ln f ectln i ln a ln y γ ε γ ε γ ε γ ε γ ε − −− − −                     + +                     where (1–l) is the lag operator, ectt–1 is one period lagged error correction term, γ1 to γ6 are the adjustment coefficients and εjt (j=1, 2, 3, 4, 5) are normally distributed residual errors. long run causal relationship is explained by statistical significance of negative lagged error correction terms. the short run causal relationship is determined by the combined statistical significance of parameter coefficients of lag period independent variables achieved through wald test. we use cumulative sum (cusum) and cumulative sum of squires (cusumsq) to check the stability of the ardl parameters. we also check the robustness of the results of causal relationship with innovative accounting approach. 4. empirical results and discussion descriptive statistics and correlation matrix have been presented in table 1. the results show that average electric power consumption over the period of study is 287.04 kwh, which is far less than the world average of 2737 kwh. the domestic credit to the private sector remained 23.44% of the gdp, industrial value added 21.82% of the gdp, agricultural value added 24.98% of the gdp and real per capita gdp remained us constant $780.78 over the period of study. the contribution of the agriculture sector to gdp has decreased more than 10% of the gdp over the 47 years period from 36% in the year 1971 to 25% in the year 2018. the correlation coefficients show that industrialization and economic growth have highly significant and positive link with the electricity consumption. financial development has a positive but weak correlation with electricity consumption. however, agricultural development has a negative and significant correlation with the electricity consumption. the significant correlation among the independent variables causes spurious regression if regressed at their level. the transformation of variables to different order and use of cointegration approach can effectively handle this problem. as the first step in cointegration analysis, we perform the unit root test on the considered variables to check the time-series properties of the variables. table 2 presents the results of standard tests of unit root such as adf and pp, first by including only constant and then both constant and trend in the equation. the results provide evidence in support of stationarity of series electricity consumption, financial development, industrialization, agricultural development and economic growth when first differenced but not at their level. the adf and pp unit root tests results suggest that all the series are integrated at their first difference level i(1) but not at their level i(0). the results of the unit root tests that do not consider the structural breaks in the series may lead to biased judgment about the order of integration if there are structural breaks in the series. in order to avoid this biase in the decision about the order of integration, we also apply zaviot and andrews (1992) unit root test. this test by considering the one unknown potential endogenous structural breaks in the series provides better results about the order of integration for the unbiased conclusion. the results of zavior and andrews unit root test are presented in table 3. overall the results are consistent irrespective which unit root test is applied. the structural break unit root test results show that all the series under the consideration are stationary at the first difference level in the presence of structural breaks but nonstationary at their level. the test results identified the time break in the series electricity consumption, financial development, and agricultural development in the year 2004, which correspond to the year of financial liberalization, prudent economic reforms, and all macroeconomic indicators exhibited a great improvement in pakistan. during this year credit rating agencies including moody’s and standard & poor upgraded the credit rating of pakistan due to sound economic growth and prudent financial policies. after having information about the order of integration among the model variables we proceed to test the presence of a long run relationship. since all of our model variables are i(1) integrated, we can use the combined cointegration approach developed by bayer and hanck (2013) to check the presence of cointegration among the model variables. the results of the bayer and hanck’s combined cointegration approach are exhibited in table 4. the results provide evidence in support of presence of long run relationship among the model variables. the calculated combined p-values, through fisher’s formula for all combinations of cointegration table 1: descriptive statistics and correlation matrix at level e f i a y mean 287.04 23.44 21.82 24.98 780.78 std. dev. 134.3779 3.2381 2.7040 3.9000 145.1440 jarque-bera 3.8318 0.7036 1.6897 4.1548 2.3966 probability 0.147213 0.7034 0.4296 0.1253 0.3017 log level lne lnf lni lna lny mean 5.5355 3.1604 3.0753 3.3037 6.2797 std. dev. 0.5561 0.1421 0.1242 0.1371 0.2744 jarque-bera 3.9753 1.1131 1.7067 2.4480 2.8553 probability 0.1370 0.5562 0.4260 0.2940 0.2399 correlations at level lnf 0.0420 lni 0.9557 −0.0019 lna −0.9159 −0.1391 −0.9058 lny 0.9775 −0.0137 0.9839 −0.9214 amjed, et al.: investigating the interactive role of demand side factors potentially responsible for energy crisis in pakistan international journal of energy economics and policy | vol 12 • issue 3 • 2022242 tests, are consistently greater than the tabulated values at 1% level in case of electricity consumption and financial development models. however, in the case of economic growth model the calculated combined p-values is lower than 1% but greater than 10% which indicates the rejection of the null hypothesis of nocointegration at 10% level. the calculated combined p-values in industrialization and agriculture development models are lower than the critical values of the tests thus lead to non-rejection of the null hypothesis. the results provide evidence in support of at least three cointegration vectors in our model. the ardl bound testing approach was also used to confirm the existence of cointegration among the model variables as a robustness check. following shehbzaz and lean (2012), shahbaz et al. (2013) and alkhathlan and javid (2015), we also included a dummy variable for the structural breaks in the ardl equation to capture the effect of time break in series. the results of ardl bound testing are exhibited in table 5. the results are consistent with the bayer and hanck approach and confirm the presence of cointegration among the variables at i(1) level in case of electricity consumption and financial development models at 1% significance level. in the case of economic growth, the test results support to reject the null hypothesis at 5% significance for i(1) integration. nonetheless, in the case of industrialization and agricultural development, the results do not support rejection of the null hypothesis. the ardl bound testing approach leads to the decision in favor of long-run relationship among the model variables and presence of three cointegration vectors at i(1) level. after having information about the order of integration and existence of long run relationship among the model variables, we proceed to estimate the short run and long run dynamic relationship among the variables through uecm. the results are interpreted in terms of elasticities as our model holds the logarithmic specifications. the long run and short run estimates of elasticities are exhibited in table 6. the results show that financial development has positive and statistically significant impact on the electric power consumption both in the short run and long run. a 1% increase in the domestic credit growth requires 0.29% increase in the electric power consumption in the long run and 0.42% in the short run, at 1% significance levels. it indicates that the electric power consumption is more elastic to financial development in the short run compared to the long run. industrial growth is another significant determinant of long run electric power consumption in pakistan. a 1% increase in industrial growth results in 0.50% increase in electric power consumption in the long run at 1% significance level. however, the short-run positive link is not statistically significant, this result was anticipated as the electric power supply is not driven by industrial sector consumption rather some other supply side factors. another interesting result that we found is the negative link between agriculture and electric power consumption. the results show that a 1% decrease in the contribution of agricultural value added in gdp results in 0.23% increase in electric power consumption in the short run and 0.29% in the long run, the relationship is statistically significant at l% and 10% levels respectively. there are three possible reasons of this unusual result. first, the rapid transformation of agricultural land into housing colonies and industrial states cause the decrease in agricultural output and increase in energy demand. second, the migrations to cities in search of a better life as most of the villages in pakistan lack basic necessities such as education, healthcare, clean drinking water, and electricity. third, the government prioritizes the cities for electric supply over the rural areas. the electricity outage sometimes reaches to 18 h per day in villages, resulting in low agriculture output. the economic growth has a positive impact on energy consumption both in the short run and long run. however, in the long run the electric power consumption is less elastic to economic growth as a 1% increase in economic growth results in 0.55% increase in electric power consumption and the relationship is statistically significant at 1% level. in short run, 1% increase in economic growth results in 0.92% increase in electric power consumption at 10% significance level. the negative and statistically significant value of one period lagged error correction term indicates that any disequilibrium due to random shocks is corrected 15.26% per year. figure 1 depicts the plot of cusm and cusm of square show that our electricity consumption model is stable. other diagnostic tests also favor the robustness of the estimated models. the presence of cointegration among the variables under the consideration indicates the existence of at least one-way causality table 2: augmented dicky fuller and philips parron test results variables adf test p-p test level first difference level first difference c c&t c c&t c c&t c c&t pt −1.5632 −0.3285 −5.4487* −5.7875* −1.5632 −0.3285 −5.4526* −5.7851* ft −2.7495 −2.3937 −5.1707* −5.1257* −1.6377 −1.2234 −5.2117* −5.1709* it −0.7494 −2.8518 −3.3349** −3.2582** −1.0628 −3.4324 −8.1332* −8.1378* at −1.9224 −1.6393 −6.1539* −6.4701* −1.9418 −1.6393 −6.1545* −6.5267* yt −1.6416 −1.4880 −5.6259* −5.8409* −0.9433 −1.4492 −5.6688* −5.8429* *and ** show significant at 1% and 5% levels respectively table 3: zivor and andrews test results variables level first difference time break time break lnet −2.8205 (0) 2004 −6.2355* (1) 1987 lnft −3.4606 (0) 2004 −5.2355* (0) 2003 lnit −3.9850 (0) 1995 −10.0169* (1) 2004 lnat −3.1665 (0) 2004 −7.2415* (1) 2000 lnyt −4.2474 (2) 1997 −6.7317* (0) 2004 *and ** show significant at 1% and 5% levels respectively amjed, et al.: investigating the interactive role of demand side factors potentially responsible for energy crisis in pakistan international journal of energy economics and policy | vol 12 • issue 3 • 2022 243 between variables. the uecm does not suggest the direction of causality. therefore, we applied vecm based granger causality test to investigate the direction of causality between the considered variables. the direction of combined joint short run and long run causality is achieved through wald test. the chi-square values and corresponding p-values of the granger causality test are exhibited in table 7. we found a reciprocal causality between electricity consumption and economic growth, thus, favoring the feedback hypothesis in the case of pakistan. raza et al. (2015) have also reported the reciprocal causal relation between aggregate energy consumption and economic growth. the results imply that electricity conservation policies may impede the economic growth in pakistan. there is also a bi-directional causality between economic growth and financial development. electricity consumption and financial development granger cause each other. a unidirectional causality is running from industrialization to electricity consumption and financial development. agricultural development and industrialization granger cause the economic growth. further investigation into the disaggregate short run and long causality may provide better insights to assist the policy makers in the formulation of effective policies to curb the energy crisis in pakistan. the results of disaggregate causal relationship are reported in table 8. the results show that one-period lag error correction term is negative and statistically significant in ep and fd equations, which indicates a bidirectional long run causality between the electricity consumption and financial development. the ectt–1 in the case of agricultural development and economic growth equations is positive which indicate the absence of long-run joint causality running from the set of independent variables to dependent variable. in industrialization equation, the ectt–1 is negative but statistically insignificant, which does not support the long run causality hypothesis running from the set of independent variables to industrial growth in the equation. the results suggest a long-run unidirectional causality running from the industrialization, agricultural development, and economic growth to electricity consumption and financial development. this finding supports the conservation hypothesis in the case of electric power as energy sources in pakistan in the long run. jamil and ahmed (2010) also reported the empirical results favoring the conservation hypothesis by sectoral analysis of electricity consumption in relation to electricity prices and gdp. it is worth noting that raza et al. (2015) reported a bidirectional causality between total energy consumption and economic growth in case of pakistan over the same period. the difference in the results of electric power consumption and total energy consumption suggests that long-term electric power conservation policies may not impede the economic growth of pakistan. the difference in the direction of causality running from electricity consumption to economic growth and total energy consumption to economic growth as reported by raza et al. (2015) may be attributed to the dependence of electricity consumers on alternate energy sources because of scheduled and nonscheduled power cuts. the short run causal relation among the model variables is tested through wald test for the combined significance of lagged period table 4: bayer and hanck combined cointegration test results estimated models tadf max� �� ˆ max fλ − ˆ ecrf tγ− ˆ adf ecr maxt f tγ γλ− − − decision ept = ƒ(fdt, idt, adt, edt, co2t) 17.3947 15.8735 18.2361 32.5267 yes* fdt = ƒ(ept, idt, adt, edt, co2t) 18.2385 16.3845 16.3456 31.6744 yes* idt = ƒ(fdt, ept, adt, edt, co2t) 5.6743 6.2945 6.6135 14.7840 no adt = ƒ(fdt, idt, ept , edt, co2t) 9.6241 8.4563 7.2345 12.4987 no edt = ƒ(fdt, idt, adt, ept, co2t) 11.6352 10.9475 8.524 23.5928 yes*** critical values at 1% 15.701 15.143 17.813 29.850 critical values at 10% 8.242 8.105 8.339 15.804 *and *** show significant at 1% and 10% levels respectively table 5: ardl bound testing results variables lnpt lnft lnit lnat lnyt f-statistics 5.2210* 4.9628* 1.4423 2.5534** 5.4595* p-values of wald 0.0015 0.0024 0.2480 0.0497 0.0009 structural break (1987) (2003) (2004) (2000) (2004) decision yes** yes** n0 n0 yes** critical value narayan 1% 5% 10% upper bound 5.898 4.338 3.708 lower bound 4.045 2.962 2.483 *and ** show significant at 1% and 5% levels respectively table 6: short term and long run and long run elasticity estimates dependent variable e variables coefficient std. error t-statistics long-run results constant −1.8521* 0.3766 −4.9174 lnf 0.2897* 0.0855 3.3883 lni 0.5058* 0.1126 4.4920 lna −0.2258* 0.0794 −2.8438 lny 0.5497* 0.1495 3.6780 short run results ∆lnfd 0.4212* 0.1188 3.5454 ∆lnid 0.1239 0.3110 0.3982 ∆lnad −0.2912*** 0.1465 −1.9876 ∆lned 0.9391** 0.4611 2.0337 ecmt–1 −0.1526* 0.0550 −3.7731 r2 0.6372 adj-r2 0.5980 f-statistics 41.7629 (0.0000) diagnostic tests f-statistics p-value ϰ2normal 1.7454 0.4175 ϰ2serial 2.2185 0.3041 ϰ2white 0.9837 0.6742 ϰ2remsay 2.3265 0.2976 *, **and *** show significant at 1%, 5% and 10% significance levels respectively amjed, et al.: investigating the interactive role of demand side factors potentially responsible for energy crisis in pakistan international journal of energy economics and policy | vol 12 • issue 3 • 2022244 variable parameter coefficients. the results show that short-run causality is running from the financial development and industrial growth to electricity consumption. electricity consumption granger causes the agricultural development. we also note that the short run causality is running from the agricultural growth to industrialization and from industrialization to economic growth. this finding suggests that a balanced economic growth cannot be achieved without a sound agriculture sector in pakistan. the development of agriculture sector may also greatly contribute to curbing the energy crises and environmental degradation. 5. conclusion and policy implications this paper aims to investigate the interactive role of financial development, industrialization, agricultural growth and economic growth in electricity consumption in pakistan over the period 1971 to 2018. we used structural break unit root test in addition to standard tests of stationarity to confirm the time series properties of the model variables. the presence of cointegration among the variables was tested with the combined cointegration technique newly developed by bayer and hanck (2013) as well as ardl bound testing approach in the presence of structural breaks. the short run and long run elasticities were estimated by linear transformation of ardl model to uecm. the direction of causality among the variables was checked through granger causality test within the framework of vecm. the empirical results support the presence of long run relationship among the model variables at i(1) level of integration. the presence of cointegration among the model variables indicates the existence of long-run equilibrium path. the elasticity estimates show that financial development and economic growth induce electricity consumption in the long run as well as in the short run. we note that in the long run a 1% increase in the contribution of the industrial sector to gdp requires 0.51% increase in electricity consumption, contrary to that a 1% increase in the contribution of agriculture sector to gdp results in 0.23% decrease in electricity consumption. meanwhile, the agricultural growth granger causes the industrial growth. this finding suggests a unique opportunity for pakistan to sustain the economic growth despite the crippling energy crisis by developing and promoting the agriculture sector. the agriculture-based economic growth would greatly help in mitigating the negative impact of the energy crisis and also contribute in achieving sustainable green growth. although the unrestricted error correction model indicates the presence at least one-way causal relation among the model variables, it does not suggest the direction of causality. the direction of causality among the model variables has great policy implications. we achieved the direction of causality through granger causality within the framework of vecm. the joint short run and long run chi-square statistics favor the feedback hypothesis in the case of pakistan. the combined short run and long run causal relation have limited policy implications, therefore, the disaggregate analysis may provide better insights. table 7: joint short and long run causality effects ϰ2 statistics variables e&ectt–1 f&etct–1 i&etct–1 a&etct–1 y&etct–1 ∆e 17.2039* (0.0006) 7.9710** (0.0466) 7.5149 (0.0572) 9.3005** (0.0256) ∆f 7.9252** (0.0476) 16.9982** (0.0007) 7.6278 (0.0544) 10.1044** (0.0177) ∆i 5.8321 (0.1201) 5.2416 (0.1549) 5.0224 (0.1702) 4.9700 (0.1740) ∆a 8.9470** (0.0300) 1.4667 (0.6900) 2.1497 (0.5419) 2.7748 (0.4277) ∆y 9.5821** (0.0225) 9.7400** (0.0209) 10.1759** (0.0171) 8.3236** (0.0398) *, ** and *** indicate significance at 1% and 5% levels. p-values within parenthesis table 8: granger causality/block exogeneity tests within framework of vecm results variables e ϰ2 f ϰ2 i ϰ2 a ϰ2 y ϰ2 ectt-1 ∆e 7.0502* (0.0240) 6.9648** (0.0307) 0.7978 (0.6711) 1.9202 (0.3829) −0.1470** (0.0294) ∆f 2.4478 (0.2941) 1.1470 (0.5636) 2.6505 (0.2657) 2.3279 (0.3123) −0.1460** (0.0146) ∆i 3.8350 (0.1470) 0.5086 (0.7754) 5.0192*** (0.0813) 0.3217 (0.8514) −0.5526 (0.1104) ∆a 8.8620** (0.0119) 0.4556 (0.7963) 2.1496 (0.3414) 2.6890 (0.2607) 0.2181 (0.4161) ∆y 3.9106 (0.1415) 0.5070 (0.7761) 10.1202* (0.0063) 2.0172 (0.3647) 0.2191 (0.1460) *, ** and *** indicate significance at 1%, 5% and 10% levels. p values within parenthesis  figure 1: cumulative sum and cumulative sum of squares of recursive residuals amjed, et al.: investigating the interactive role of demand side factors potentially responsible for energy crisis in pakistan international journal of energy economics and policy | vol 12 • issue 3 • 2022 245 further investigation into causal relationship reveals that there is a unidirectional causality running from economic growth to electricity consumption in the long run which supports the conservation hypothesis. however, there is no sign of short run causal relation which favors the neutrality hypothesis. the results show that short run unidirectional causality is running from the electricity consumption to agricultural growth. if we interpret the one-way causality along with negative parameter coefficient of agriculture growth in electricity consumption equation, it is clear that the short supply of electricity is responsible for the dwindling contribution of agriculture sector in the gdp. the decrease in agriculture output also adversely affect the industrial sector as suggested by the short-run causality running from agriculture growth to industrialization. a significantly large part of pakistan’ industrial sector consists of agriculture-based industries such as textile, sugar, chemical and engineering. the findings have significant policy implications for pakistan. the empirical results confirm the industry driven financial development. this finding suggests that short-term conservative financial policy may be implemented to decrease the energy consumption without compromising the economic growth. prudent rationing of available electric power among the agricultural, industrial and household sector may also help in minimizing the adverse effects of the energy crisis. being an agricultural economy, pakistan has great potential for agriculture-led green growth. more specifically, the policy makers should make a composite policy to promote and develop the agriculture sector of pakistan. the inefficiencies in agriculture sector may be eradicated by promoting the culture of corporate farming, liberal credit policy for agriculture sector and technical assistance to use modern agricultural technologies. provision of technical and financial assistant to the farmers to encourage the use of biofuel and renewable energy sources may greatly help in combating the energy crisis. references abid, m., abdallah, k.b., mraihi, r. (2012), causality relationship between energy industrial consumption and economic growth: application on tunisian country. in: 2012 first international conference on renewable energies and vehicular technology. united states: ieee. p396-404. ahmed, w., zeshan, m. (2014), decomposing change in energy consumption of the agricultural sector in pakistan, agrarian south. journal of political economy, 3(3), 1-34. alkhathlan, k., javid, m. (2015), carbon emissions and oil consumption in saudi arabia. renewable and sustainable energy reviews, 48, 105-111. al-mulali, u., sab, c.n.b. (2012), the impact of energy consumption and co2 emission on the economic growth and financial development in the sub saharan african countries. energy, 39(1), 180-186. ang, j.b. (2008), economic development, pollutant emissions and energy consumption in malaysia. journal of policy modeling, 30(2), 271-278. apergis, n., payne, j.e. (2010), the emissions, energy consumption, and growth nexus: evidence from the commonwealth of independent states. energy policy, 38(1), 650-655. aqeel, a., butt, m.s. (2001), the relationship between energy consumption and economic growth in pakistan. asia-pacific development journal, 8(2), 101-110. arestis, p., demetriades, p. (1997), financial development and economic growth: assessing the evidence. the economic journal, 107(442), 783-799. arouri, m.e.h., youssef, a.b., m’henni, h., rault, c. (2012), energy consumption, economic growth and co2 emissions in middle east and north african countries. energy policy, 45, 342-349. asafu-adjaye, j. (2000), the relationship between energy consumption, energy prices and economic growth: time series evidence from asian developing countries. energy economics, 22(6), 615-625. asteriou, d., spanos, k. (2019), the relationship between financial development and economic growth during the recent crisis: evidence from the eu. finance research letters, 28, 238-245. aziz, s.j., burki, a., ghaus-pasha, s., hamid, p., hasan, a., hussain, h.a., ghaus-pasha, a., sherdil, a.z.k. (2010), third annual report-state of the economy: pulling back from the abyss. lahore, pakistan: beaconhouse national university, institute of public policy. p66. bayer, c., hanck, c. (2013), combining non-cointegration tests. journal of time series analysis, 34(1), 83-95. beckman, j., borchers, a., jones, c.a. (2013), agriculture’s supply and demand for energy and energy products, eib-112, u.s. united states: department of agriculture, economic research service. cheng, y.s., li, r., woo, c.k. (2021), regional energy-growth nexus and energy conservation policy in china. energy, 217, 119414. choudhray, i.s., safdar, n., farooq, f. (2012), energy consumption and economic growth: empirical evidence from pakistan. pakistan journal of social sciences, 32(2), 371-382. çoban, s., topcu, m. (2013), the nexus between financial development and energy consumption in the eu: a dynamic panel data analysis. energy economics, 39, 81-88. de gregorio, j., guidotti, p.e. (1995), financial development and economic growth. world development, 23(3), 433-448. elliott, g., jansson, m., pesavento, e. (2005), optimal power for testing potential cointegrating vectors with known parameters for nonstationarity. journal of business and economic statistics, 23(1), 34-48. emir, f., bekun, f.v. (2019), energy intensity, carbon emissions, renewable energy, and economic growth nexus: new insights from romania. energy and environment, 30(3), 427-443. engle, r.f., granger, c.w. (1987), co-integration and error correction: representation, estimation, and testing. econometrica: journal of the econometric society, 55(2), 251-276. frankel, j.a., romer, d. (1999), does trade cause growth? the american economic review, 89(3), 379. hassan, m.k., sanchez, b., yu, j.s. (2011), financial development and economic growth: new evidence from paneld. the quarterly review of economics and finance, 51(1), 88-104. international energy agency. (2014), special report on world energy investment outlook-2014, international energy agency 9 rue de la fédération 75739 paris cedex 15, france. paris, france: international energy agency international energy agency. (2021), world energy outlook-2021, international energy agency 9 rue de la fédération 75739 paris cedex 15, france. paris, france: international energy agency. islam, f., shahbaz, m., ahmed, a.u., alam, m.m. (2013), financial development and energy consumption nexus in malaysia: a multivariate time series analysis. economic modelling, 30, 435-441. jamil, f., ahmad, e. (2010), the relationship between electricity consumption, electricity prices and gdp in pakistan. energy policy, amjed, et al.: investigating the interactive role of demand side factors potentially responsible for energy crisis in pakistan international journal of energy economics and policy | vol 12 • issue 3 • 2022246 38(10), 6016-6025. johansen, s., juselius, k. (1990), maximum likelihood estimation and inference on cointegration-with applications to the demand for money. oxford bulletin of economics and statistics, 52(2), 169-210. kakar, z.a., khilji, b.a., khan, m.k. (2011), financial development and energy consumption: empirical evidence from pakistan. international journal of trade, economics and finance, 2(6), 469-471. karanfil, f. (2008), energy consumption and economic growth revisited: does the size of unrecorded economy matter? energy policy, 36(8), 3029-3035. karanfil, f. (2009), how many times again will we examine the energyincome nexus using a limited range of traditional econometric tools? energy policy, 37(4), 1191-1194. khan, m. a., ahmad, u. (2008). energy demand in pakistan: a disaggregate analysis. the pakistan development review, 47(4), 437-455. kraft, j., kraft, a. (1978), on the relationship between energy and gnp. the journal of energy and development, 3(2), 401-403. levine, r. (2001), international financial liberalization and economic growth. review of international economics, 9(4), 688-702. menegaki, a.n. (2019), the ardl method in the energy-growth nexus field; best implementation strategies. economies, 7(4), 105. mushtaq, k., abbas, f., ghafoor, a. (2007), energy use for economic growth: cointegration and causality analysis from the agriculture sector of pakistan. the pakistan development review, 46, 1065-1073. narayan, p.k. (2005), the saving and investment nexus for china: evidence from cointegration tests. applied economics, 37(17), 1979-1990. national academy of sciences. (2008), what you need to know about energy. united states: national academy of sciences. nyasha, s., odhiambo, n.m. (2018), financial development and economic growth nexus: a revisionist approach. economic notes: review of banking, finance and monetary economics, 47(1), 223-229. ozturk, i. (2010), a literature survey on energy-growth nexus. energy policy, 38(1), 340-349. ozturk, i., acaravci, a. (2010), co2 emissions, energy consumption and economic growth in turkey. renewable and sustainable energy reviews, 14(9), 3220-3225. pakistan economic survey. (2009-10), ministry of finance, islamabad, 183. available from: https://www.finance.gov.pk/survey_0910.html [last accessed on 2015 apr 15]. pakistan economic survey. (2014-15), economic adviser’s wing, finance division, government of pakistan, islamabad. pakistan: pakistan economic survey. payne, j.e. (2010), survey of the international evidence on the causal relationship between energy consumption and growth. journal of economic studies, 37(1), 53-95. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. qazi, a.q., ahmed, k., mudassar, m. (2012), disaggregate energy consumption and industrial output in pakistan: an empirical analysis, economics, discussion paper no. 2012-29. available from: http://www.economics-ejournal.org/economics/ discussionpapers/2012-29/file [last accessed on 2016 jan 23]. raza, s.a., shahbaz, m., nguyen, d.k. (2015), energy conservation policies, growth and trade performance: evidence of feedback hypothesis in pakistan. energy policy, 80, 1-10. sadorsky, p. (2010), the impact of financial development on energy consumption in emerging economies. energy policy, 38(5), 2528-2535. sadorsky, p. (2011), financial development and energy consumption in central and eastern european frontier economies. energy policy, 39(2), 999-1006. salahuddin, m., gow, j., ozturk, i. (2015), is the long-run relationship between economic growth, electricity consumption, carbon dioxide emissions and financial development in gulf cooperation council countries robust? renewable and sustainable energy reviews, 51, 317-326. shahbaz, m., hye, q.m.a., tiwari, a.k., leitão, n.c. (2013), economic growth, energy consumption, financial development, international trade and co2 emissions in indonesia. renewable and sustainable energy reviews, 25, 109-121. shahbaz, m., lean, h.h. (2012), does financial development increase energy consumption? the role of industrialization and urbanization in tunisia. energy policy, 40, 473-479. shahbaz, m., lean, h.h., shabbir, m.s. (2012), environmental kuznets curve hypothesis in pakistan: cointegration and granger causality. renewable and sustainable energy reviews, 16(5), 2947-2953. shahbaz, m., mutascu, m., azim, p. (2013), environmental kuznets curve in romania and the role of energy consumption. renewable and sustainable energy reviews, 18, 165-173. siva, k.g.k., rao, r.p. (2018), the causal relationship between financial development and economic growth: an experience with brics economies. journal of social and economic development, 20(2), 308-326. squalli, j. (2007), electricity consumption and economic growth: bounds and causality analyses of opec members. energy economics, 29(6), 1192-1205. stiglitz, j.e. (2010), risk and global economic architecture: why full financial integration may be undesirable. american economic review, 100(2), 388-92. tamazian, a., chousa, j.p., vadlamannati, k.c. (2009), does higher economic and financial development lead to environmental degradation: evidence from bric countries. energy policy, 37(1), 246-253. tang, c.f., tan, b.w. (2014), the linkages among energy consumption, economic growth, relative price, foreign direct investment, and financial development in malaysia. quality and quantity, 48(2), 781-797. unido. (2011), industrial development report 2011: industrial energy efficiency for sustainable wealth creation: capturing environmental, economic and social dividends. vienna, austria: united nations industrial development organization. wang, s.s., zhou, d.q., zhou, p., wang, q.w. (2011), co2 emissions, energy consumption and economic growth in china: a panel data analysis. energy policy, 39(9), 4870-4875. zeren, f., koc, m. (2014), the nexus between energy consumption and financial development with asymmetric causality test: new evidence from newly industrialized countries. international journal of energy economics and policy, 4(1), 83-91. žiković, s., žiković, i.t., lenz, n.v. (2020), a disaggregated approach to energy-growth nexus: micro-regional view. energy strategy reviews, 28, 100467. zivot, e., andrews, d.w. (1992), further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. journal of business and economic statistics, 10(3), 251-270. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 1 • 2023 431 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(1), 431-442. critical factors impacting the implementation of environmental protection strategies among malaysia industries abdullah sarwar1*, s. m. ferdous azam2, nasreen khan1, murali raman3, vincent oh kim seng1, aysa siddika4 1faculty of management, multimedia university, cyberjaya, malaysia, 2postgraduate centre, management and science university, shah alam, malaysia, 3director postgraduate and continuing education, asia pacific university of technology and innovation, kuala lumpur, malaysia, 4center for consumer research and education, multimedia university, cyberjaya, malaysia. *email: sunabdullah@gmail.com received: 06 june 2022 accepted: 18 december 2022 doi: https://doi.org/10.32479/ijeep.13279 abstract environmental protection is a heavily debated topic along with development. uncontrolled development will sacrifice our environmental and causing issues such as pollution, land slide, flash flood, etc. the objective of this study is to understand drivers of the implementation of environmental protection strategy among industries in malaysia. questionnaire was designed and tested with 130 malaysian organizations. the framework consisted of independent variables such as client’s requirement, corporate social responsibility, government grants and subsidy versus the dependent variable environmental protection strategy. from the exploratory factor analysis (efa), it was found out that only client’s requirement and corporate social responsibility are relevant towards implementation of environmental protection strategy. one of the very important findings is that government regulation is no longer a mandatory driver for organizations to implement environmental protection strategy. this could be a positive sign that organizations are working the self-regulatory direction than the instrumental enforcement. this is in par with department of environment’s latest focus to implement guided self-regulation through environmental mainstreaming tools. outcome of the study can help the policy makers, regulatory bodies and nongovernment organizations (ngos) to shape their direction to form strategies that is most effective. keywords: environmental protection strategy, corporate social responsibility, government grant and subsidy, malaysia jel classification: q56 1. introduction mother earth is the most precious resources gifted to human without charge but is often abused. in the context of environmental protection and conservation, individuals play substantial role by minimizing waste or maximizing recycling in their day-to-day life. even so, the results are not so obvious compared to the impact on implementation of environmental protection strategy by businesses (gillespie, 2019). the waste generated from industry activities are huge and more hazardous compared to domestic waste generated by individual (xiang et al., 2021). the negative impacts along with environmental pollution due to uncontrolled development are sometimes irreversible and lead to disasters like ozone depletion, climate change, and extinction of rare species as well as endangering human health (rahman et al., 2021). environmental protection strategy is series of action plans to maintain or upkeep our natural world from damages and pollution which causes short or long term impact (undp, 2021). this is vital especially under industrialization economy as those developments will lead to environmental destruction if it is not properly controlled and monitored (ukaogo et al., 2020). hence, sustainable development with minimal impact to the environment this journal is licensed under a creative commons attribution 4.0 international license sarwar, et al.: critical factors impacting the implementation of environmental protection strategies among malaysia industries international journal of energy economics and policy | vol 13 • issue 1 • 2023432 is always more beneficial to mankind as compared to short-term monetary return. this study examines how various factors interacted within malaysia’s industries in forming their environmental protection strategy. the factors of interest are government grants and subsidy, client’s requirement, corporate social responsibility and regulatory reformation. a report from blacksmith institute in year 2013 disclosed that the health impact of industrial pollutants in third world nations could be as serious as world major diseases like malaria and tuberculosis. amongst all type of industries, chemical related industries had the highest blame. a study focused the impact of toxic waste in developing countries like india, indonesia and philippines was carried out to calculate the risk due to various type of chemicals. table 1 below shown the per capita cancer and non-cancer human health risks by chemical and media for chemicals other than lead (chatham-stephens et al., 2013). the table depicts that air contamination contributed to the highest human health risk per capita for both cancer and non-cancer risk followed by water contamination and soil contamination. this may be due to direct inhalation of the contaminants into human body without any special protection (chatham-stephens et al., 2013). over the last few decades, with rapid growth in industrialization, agriculture and tourism the kualalumpur, malaysia came in ranked 14th place in air quality1 and pollution city ranking as on may 20, 2022 among all the countries in the world1. malaysia’s air is 3.9 times above the world health organization (who) recommended air quality value2. problems faced currently are forest clearing, water pollutions, erosion of soil and coastal, along with air pollution, water pollution and waste disposal. the typical impacts of these environmental issues are like frequent occurrence of flash floods due to deforestation, poor air quality index due to open burning, etc. as a result, more and more concerns aroused on all potential environmental issues towards the citizens’ safety and health. the main objective of this study is to determine the critical factors like goverments grants and subsidy, client’s requirement, 1 air quality and pollution city ranking, https://www.iqair.com/malaysia accessed on may 20, 2022. 2 air quality in malaysia , https://www.iqair.com/malaysia accessed on may 20, 2022. corporate social responsibility, goverments rules and regulation that businesses in malaysia consider during the formation of environmental protection strategy. this study was conducted on 130 malaysian organization that do business within malaysia and outsidemalaysia by exporting goods. from the exploratory factor analysis (efa), it was found that only client’s requirement and corporate social responsibility are relevant factors towards implementation of environmental protection strategy. moreover, government grants and subsidy was not a significant predictor of environmental protection strategy. this study findings provide theoretical insights in the field of environmental protection strategy that can advance the literature on proactive strategies in a sustainable way. the study is organized as follows. section two presents literature review on different varaibles affecting the environemntal protection strategy in the context of different economy. section three presents the methodology of the study. section four discusses the results and findings of the study. section five presents the implications of the study and finally section six presents conclusions. 2. literature review our environment is facing several crisis that are increasing day by day, and has become crucial issue to be addressed to reduce the negative impact. a number of research, policy regulation and environment protection starategy, awareness development program has been formulated globally. however, still pollution is responsible for one in six deaths, 3 times more deaths than from malaria, tubercolosis and aids combined, totaling 9 million death per year (fuller et al. 2022) globally. therefore, the importance of further research on sustainable development in the environmental protection sphere is never overrated. from the existing literature review it is observed that most of the studies on environmental protection strategy are analysed based on the pest model (huang et al., 2021; jain and sharma, 2021; liu et al., 2020; mohammad, 2011; naderi et al., 2021; suki, 2013; punitha and rasdi, 2013; sushchenko et al., 2019; zafar et al, 2019; zailani et al., 2015; and zailani, et al., 2015). the pest model is a macro-environmental framework which gives overview of how various macro-environmental factors affect strategy planning. macro-environmental factors for basic pest model consist of political, economic, social and technological, table 1: per capita cancer and non-cancer human health risks chemical (media assessed) cancer risk non-cancer risk per µg/m3 in air per µg/kg in soil per µg/l in water per µg/m3 in air per µg/kg in soil per µg/l in water aldrin (w) na na 5.35×10-4 na na 2.22×10-6 asbestos (a) 2.30×10-1a na na na na na cadmium (a, s, w) 1.80×10-3 na na 5.00×10-8 2.67×10-5 1.33×10-7 chromium vi (a, s, w) 8.40×10-2 9.71×10-5b 2.09×10-5 na na na ddt (w) na na 1.07×10-5 na na 1.33×10-7 lindane (s, w) na 5.08×10-6 3.45×10-5 na 8.85×10-8 2.22×10-7 mercury, inorganic (a, s, w) na na na 5.68×10-8 8.85×10-8 2.22×10-7 a: air, ddt: dichlorodiphenyltrichloroethane, na: not assessed, s: soil, w: water. afibers/cubic centimeter. binhaled airborne dust (source: chatham-stephens et al., 2013) https://www.iqair.com/malaysia https://www.iqair.com/malaysia sarwar, et al.: critical factors impacting the implementation of environmental protection strategies among malaysia industries international journal of energy economics and policy | vol 13 • issue 1 • 2023 433 that can be extended to pestle adding legal and environmental factors. political factor includes government strategies and movement like tax policies, laws and regulation, intellectual property protection, government stability and security, government grants, subsidies etc. if business strategy is aligned with the relevant government strategy, the company’s growth and expansion will definitely be benefited. economical factor coveres economic growth in terms of gdp per capita, purchasing power parity, interest and inflation rate, and trade balance etc. often businesses form organization strategies trying to fulfill the client’s requirement so that more products can be sold as well as earning more profit as increased business transactions linked with economic improvement. apart of profit orientation, socially responsible business addresses social issues like demographic distribution, education level, social safety and others. for the socially responsible businesses, one of the consideration factor is how will the new strategy impact the current social culture lifestyle, either positively or negatively. strategies that are beneficial to the social environment tend to be more receptive and easily adopted. technological development and innovation promote productivity of an organization. advancement in information technologies can shorten the communication time, thus enhancing the decision making process. in an empirical investigation in mexico carrete et al. (2014) examined how firms perceived drivers and barriers to move towards green. the qualitative research had gathered information from 34 firms which consists of multinationals, mexican firms with international operations, and mexican firms with local operations. three main drivers studied were economic factor, legitimation and social responsibility. according to the study’s findings, social responsibility for the environment was the primary motivator of green behaviours, followed by economic motivation. in a similar study, by zailani et al. (2015) 153 automative supply chain industries operating in malaysia found that environmental regulations, market demand, and firm internal initiatives are the main determinants in adopting green innovation initiatives. legal compliance due to government regulations is an instrumental action where people is concerned about consequences (or punishments to be exact) for not doing it instead of normative compliance where they will be self-regulated as they felt the law is just. in several studies (hecht, 2007; hezri and hasan, 2006; tyler, 2006) it is found that normative principles of sustainable development is of utmost importance as well as the fundamental task of policy implementation. other studies by the environmental protection department of hong kong (2006)3, hecht (2007) found government regulationsare amore critical determinant factor along with other business strategies. 3 support on environmental management information and iso14001 environmental management systems for small and medium enterprise (smes) in the electrical/ electronic and construction sectors in hong kong” https://www.epd.gov.hk/epd/misc/env_management_sme/presentation/elvis. pdf accessed on may 20, 2022. moreover, in another study mohammad (2011) investigated the stage of the environmental laws and policy as well as drivers and barriers in malaysian context. the study found that factors affecting the implementation of environmental laws and policies are lack of enforcement and short of trained environmentalexpertise lawyers. following that, mokthsim and salleh (2014) investigated the concerns, challenges, and opportunities of environmental management strategies, as well as the formation of national policies in malaysia, in a separate research. he concluded that malaysia has good efforts in policy development, law and regulations enactment in order to become a sustainable development country. several studies (brecard et al., 2009; gandenberger et al. 2020; le, 2021; shah et al., 2021; suki, 2013; timbur 2012) on green or environmental products found that consumers’ awareness of green products and brand image positively related to the green products purchasing decision. an environmentally-sensitive person would prefer to make green product buying decision. it was suggested that marketers should disclose and display more information about green products and eco-labels to familiarize and educate consumer with their green products. in environmental protection strategy the role of corporate social responsibility is rarely overlooked (huang et al., 2021; jain and sharma, 2021; liu et al., 2020; seroka-stolka, 2013; yuan et al., 2020; zafar et al., 2019). csr in term of environment is defined as the responsibility to protect the environment resulted from the company’s operations, products and facilities; minimization of waste and emissions; improving the efficiency and productivity and eliminate practices that might negatively affect the future environmentaccording to sushchenko et al. (2019), improving resource efficiency and environmental consciousness, as well as the development of eco-technologies and environmental management tools, are essential components of a comprehensive environmental protection plan and csr components are positively related to consumers’ buying behavior (abd rahim et al., 2011). stavins and reinhardt (2010) concluded that promoting sustainable business practices being environmentally responsible will generates remarkable profits in the long run. however, the relationship between csr activities and profitability may denoted as only some parties will be rewarded with profits from some of the csr activities after a certain period. therefore, rather than sacrificing profits, firms may opt to some socially beneficial activities which is limited but also more profitable to meet the financial goal. research by yazid et al. (2015), yazid et al. (2012), zailani et al. (2015), studied the role of green marketing in malaysian context. puvanasvaran et al. (2012) explored the support of innovation development that leads to green technology sustainability in malaysia. the study found that malaysia’s industries are in par with development of green technology. when the government implemented the green technology policy, programs and incentive were provided for the innovation in malaysian industries. according to them, setting up green technology incentive and budget accelerated invention, and creation of greater green technology is beneficial to the nation. https://www.epd.gov.hk/epd/misc/env_management_sme/presentation/elvis.pdf%20accessed%20on%20may%2020 https://www.epd.gov.hk/epd/misc/env_management_sme/presentation/elvis.pdf%20accessed%20on%20may%2020 sarwar, et al.: critical factors impacting the implementation of environmental protection strategies among malaysia industries international journal of energy economics and policy | vol 13 • issue 1 • 2023434 punitha and rashdi (2013) found that green marketing is not only csr but also improves competitiveness and mediates development and environmental balance. a recent study by siddique and hossain (2018) found that awareness of green products is a crucial issue in consumers green purchasing decision. therefore, organizatons that aid in green awareness development program are in ahead of selling their green products to the consumers. in another empirical study it was found that consumer’s green purchase decision are strongly influenced by their environmental concern, green perceived benefits, their willingness to purchase the green products (nekahmud and fekete, 2020). the empirical studies indicated that there are positive relationships between government regulations, client’s requirement, corporate social responsibility, with environmental protection strategies. these relationships are strong in other countries as well as within malaysia. these variables were verified through the study conducted by gandenberger et al. (2020), huang et al. (2021), jain and sharma (2021), liu et al. (2020), mohammad (2011), naderi et al. (2021), sharma (2021), suki (2013), punitha and rasdi (2013), sushchenko (2019), zafar et al. (2019), zailani (2015), and zailani, et al. (2015). however, there are limited and indirect relationship and implementation between technology innovation and government grants and subsidy, with of environmental protection strategies in an organization. ibrahim and jaafar (2015) discussed how technological factor influence environmental awareness and later affect the environment management practices options. on the other hand, research done by salim and padfield (2017) proposed that malaysian government should provide extensive support such as special tax exemption for certified companies that adopted environmental management system (ems). 3. methods the independent variables of this study includes government regulations, client’s requirement, corporate social responsibility, technology innovation as well as government grants and subsidy. the dependent variable of this study is the environment protection strategy, which acts as the outcome of the independent variables, either positively or negatively. 3.1. conceptual framework studies conducted in mexico and malaysia identify three drivers i.e. legitimation (environmental regulation), economic (market demand) and social responsibility (firm internal initiatives) (carrete et al., 2014; zailani et al., 2015) related to green policy. the factors that were used in this study are government regulations, client’s requirement and corporate social responsibility to identify how these factors are related to the environmental protection strategies of a company. the two other factors that were used in this study are technology innovation and government grant and subsidy. these two factors were added to identify if these could also be significant factors for companies to implement environmental protection strategy (figure 1). this study used five hypotheses as each hypothesis is the logical relationship between independent variables and the dependent variable. the hypotheses were: • h1: there is a positive relationship between government regulations and environmental protection strategy • h2: there is a positive relationship between client’s requirement and environmental protection strategy • h3: there is a positive relationship between corporate social responsibility and environmental protection strategy • h4: there is a positive relationship between technology innovation and environmental protection strategy • h5: there is a positive relationship between government grants and subsidy and environmental protection strategy. 3.2. research design descriptive study was used to describe the current implementation of environmental protection strategy in malaysia. it follows the quantative analysis. the population of the study is the customer database of an environmental consultant company where the business operated in all of the malaysian peninsular states. the consultant company consulted 500 organizations. a total of 300 questionnaires were distributed to the 500 organizations who received consultation from the consultation company. however, only 130 organization completed the distributed questionnaire. simple random sampling was adopted in this research to minimize any biasness throughout the process. each of these organizations was treated with equal chance of being selected. this method is more effective in terms of cost and time to reach out to these organizations throughout malaysia. there were two sections in the questionnaire. part a and part b respectively focused on the demographic profile and hypothesis testing questions regarding relationship between determinant factors and dependent variable environmental protection strategies. this questionnaire asked about the organizations as a whole rather than the individual point of view. the questionnaries used both nominal and likert scale to measure the responses. the questionnaire designed in google form was sent through email and whatapp application. besides, manual distribution was carried out as well and the collected data was key in to the same online google form. the purpose of the manual distribution is to explain and guide computer illiterate target, ensuring an adequate coverage of target participants. a sample of the questionnaire is attached in the appendix for further reference. a pilot test was conducted among a small group of respondents. a total of 21 participants answered the questionnaire. any constructs that has a cronbach’s alpha value <0.7 is not reliable and has to be redesigned. table 2 shows the summary of pilot test. according to this table, all the six constructs had achieved cronbach’s alpha value near to or higher than 0.7. thus, the survey questions were sent out for further responses collection. 3.3. research method descriptive statistics was used for part a – demographic information to describe the basic features of the study. the information was broken down into frequency or percentage for each category and was represented with pie chart. on the sarwar, et al.: critical factors impacting the implementation of environmental protection strategies among malaysia industries international journal of energy economics and policy | vol 13 • issue 1 • 2023 435 other hand, inferential statistics were used at part b through factor analysis and one-way anova. by removing duplicate or strongly linked variables, the factor analysis approach was utilised to decrease a significant quantity of data. to see how each demographic group reacts differently to the factor, a oneway anova was employed. finally, multiple linear regression analysis was used to determine the association between the independent and dependent variables. 3.4. data analysis spss was used to do the data analysis. before the real questionnaire was circulated, a pilot test was undertaken. the questionnaire was deemed sufficient since the cronbach’s alpha value was more than or equal to 0.7. after receiving all of the comments, exploratory factory analysis (efa) was used to decrease the quantity of data by eliminating duplicated or strongly associated variables. anova tests were run for all variables vs the demographic profile after the irrelevant factor was eliminated using efa. the link between four independent factors and the dependent variable was investigated using multiple linear regression analysis. finally, weak independent variable (s) were eliminated using stepwise regression, and the final correlation was generated, confirming the hypothesis. 4. results and discussion 4.1. demographic profile in this study, responses were collected from 130 participating organizations out of 300 distributed questionnaires, resulted into 43.3% response rate. in analysing the organizatiosn reaction towards implementation of environmental protection strategy, demographic profile studied were company business scope, company target market, company setup period, numbers of full time employees and company annual sales turnover. the analysis of the demographic profile revealed that there were only 35 organizations (26.9%) considered as large organizations, established more than 10 years ago, employed more than 200 employees and have an annual turn over of more than rm 50 million. a total of 19 organizations (14.6%) were considered as small organizations that were established <5 years ago, employed <10 employees and have an annual sales turnover of less than rm 1 million. the remaining 76 organizations (41.5%) were considered as medium size organizations. table 3 summarizes the demographic profile of the participating organizations 4.2. exploratory factor analysis (efa) efa was used to guarantee that all constructs were appropriately correlated with one another. this test is also used to reorganise any constructs that were previously grouped incorrectly. the efa was run 3 times to exclude items that did not display the same feature as the rotated component matrix result, such as not being loaded, cross-loaded, or saturated. during all of these trials, it was also critical to ensure that the kmo value was always equal to or greater than 0.7. table 4 shows the results of the efa experiments. a few items were eliminated and a few items were regrouped after the third efa trial. item 2 and 3 from government regulations and item 2 from technology innovation were regrouped as a new independent variable which was renamed as regulatory reformation. figure 2 illustrates the new modified framework. figure 1: proposed framework of the study table 2: summary of pilot test s. no. construct no. of item cronbach’s alpha value (after recoding)before recoding after recoding 1 eps 5 5 0.905 2 gr 5 3 0.679 3 cr 5 5 0.879 4 csr 5 5 0.710 5 ti 5 5 0.697 6 ggs 5 4 0.722 eps: environmental protection strategy from business, gr: government regulations, cr: client’s requirement, csr: corporate social responsibility, ti: technology innovation, ggs: goverments grants and subsidy table 3: demographic profile of participating organizations s. no. variable frequency (percentage) n=130 i. company business scope manufacturing 35 (26.9) services 55 (42.3) construction 17 (13.1) others 23 (17.7) ii. company target market within malaysia only 46 (35.4) export only 8 (6.2) both 76 (58.5) iii. company setup period <1 year 5 (3.8) 1-5 years 24 (18.5) 6-10 years 15 (11.5) >10 years 86 (66.2) iv. nos. of full time employee <10 employees 21 (16.2) 11-75 employees 52 (40) 76-200 employees 15 (11.5) >200 employees 42 (32.3) company annual sales turnover <1 million 19 (14.6) 1-10 million 36 (27.7) 11-50 million 40 (30.8) >50 million 35 (26.9) sarwar, et al.: critical factors impacting the implementation of environmental protection strategies among malaysia industries international journal of energy economics and policy | vol 13 • issue 1 • 2023436 the earlier framework consisted of five independent variables. the five variables were government regulations, client’s requirement, corporate social responsibility, technology innovation and government subsidy. in the modified framework, variables government regulations and technology innovation were regrouped into regulatory reformation. following statistical analysis were done based on the modified framework. 4.3. reliability test a reliability test was performed to ensure that the analysis was consistent. the cronbach’s alpha value is utilised as a consistency indicator. constructs with a cronbach’s alpha value of more than 0.7 are deemed consistent. the summary of reliability test for the five constructs is shown in table 5. except for regulation reformation (rr), each of the five constructs had a cronbach’s alpha value of close or more than 0.7. as a result, the survey was deemed trustworthy. 4.4. one-way anova following the elimination of the irrelevant component, an analysis of variance (anova) test was run for all factors vs the demographic profile to see how each demographic group reacted to the factor differently. the demographic profile of the study included business scopes, target market, setup period, numbers of employees and annual sales turnover responded towards the implementation of environmental protection strategy and other relevant factors. table 6 shows the one-way anova analysis for demographic profile versus environmental protection strategy. all organizations agreed or somehow agreed on the importance of environmental protection strategy (mean ≤ 2). the result of the anova test indicated that all demographic profiles had no different reaction towards the implementation of environmental protection strategy. however, for target market, there is a difference (p < 0.05). through post hoc test (dunnett t3), organizations that do business within malaysia and outside malaysia by exporting goods, agree on the importance of environmental protection strategy than organizations that active within malaysia only. tables 7 and 8 summarise the results of a one-way anova analysis undertaken to see how demographic profiles react to factors like customer requirements and regulatory reformation. in general, all types of companies agreed or agreed in some way that these elements will influence decision-making when it comes to implementing environmental protection strategies (mean 2). in terms of business scopes, target markets, setup time, personnel numbers, and yearly sales turnover, however, there is no substantial difference. the one-way anova analysis for demographic profile vs corporate social responsibility is shown in table 8. in general, all firms agreed or at least agreed that corporate social responsibility is a crucial factor of environmental protection strategy (mean 2). figure 2: modified framework table 5: summary of reliability test s. no. construct no. of items cronbach’s alpha value 1 eps 5 0.886 2 csr 5 0.874 3 cr 4 0.889 4 ggs 3 0.827 5 regulation reformation 3 0.586 eps: environmental protection strategy from business, cr: client’s requirement, csr: corporate social responsibility, ggs: goverments grants and subsidy table 6: one-way anova for environmental protection strategy (eps) s. no. variable mean±s p-value for test of differencw between groups i. business scope 0.294* manufacturing 1.44±0.56 services 1.57±0.66 construction 1.67±0.67 others 1.77±0.78 ii. target market 0.039** within malaysia only 1.82±0.78 export only 1.48±0.72 both 1.45±0.53 iii. setup period 0.321** <1 year 2.00±1.16 1-5 years 1.64±0.79 6-10 years 1.75±0.62 >10 years 1.51±0.58 iv. nos. of full time employee 0.648* <10 employees 1.69±0.79 11-75 employees 1.62±0.62 76-200 employees 1.59±0.67 >200 employees 1.48±0.65 v. annual sales turnover 0.094** <1 million 1.81±0.90 1-10 million 1.56±0.69 11-50 million 1.65±0.54 >50 million 1.41±0.57 *based on parametric one-way anova procedure, **based on nonparametric kruskal-wallis test, eps: environmental protection strategy from business, cr: client’s requirement, csr: corporate social responsibility table 4: efa trials and outcome no of trial kmo value total variance explained items eliminated efa trial 1 0.848 34.8% ti 3, ti 4, ti 5, cr 5 and ggs4 efa trial 2 0.847 37.3% gr 1 and ti 1 efa trial 3 0.859 37.8% gr 2, gr 3 and ti 2 efa: exploratory factor analysis sarwar, et al.: critical factors impacting the implementation of environmental protection strategies among malaysia industries international journal of energy economics and policy | vol 13 • issue 1 • 2023 437 according to the findings, no demographic profile showed a distinct reaction to the hypothesis that corporate social responsibility will impact decision making on environmental protection strategy except for annual sales turnover (p < 0.05). through post hoc test (tukey hsd), organizations that earned more than 50 million annually tends to agree more than organizations that earned <1 million annually that corporate social responsibility is a very important factor in determining environmental protection strategy. in conclusion, it was noticed that the smaller organizations that started a year ago and had <10 employees, earned <1 million annually. these organizations and focused on malaysia market only do not believed strongly (mean >> 1) on the importance of environment protection strategy. 4.5. descriptive statistics to determine the distribution pattern of questionnaire responses, descriptive statistics were used. the standard deviation and standard error are both measurements of dispersion, while the mean, median, and mode are three frequent measures of central tendency. for the purposes of this study, the mean and standard deviation will be employed. the questionnaire was created to collect input using a likert scale of 1-5, with 1 indicating agreement and 5 indicating disagreement with the statement. the descriptive statistics for all five constructs are presented in table 9. there was agreement on all of the elements for each construct with a mean value between 1 and 2 based on the mean value in table 10 (agree and somehow agree). for all items, the standard deviation was near to or <1.000. this showed that the replies were somewhat clustered around the mean value. the mean of the items in each construct was calculated and saved with the appropriate name for later analysis. the correlation matrix of the five components is shown in table 11. with the exception of ggs, the maximum correlation value for each item with at least one other item in the construct is between 0.3 and 0.9. ggs was omitted from the later analysis since it did not converge with the others. the kmo value in factor analysis (after removing ggs) was 0.768, which is deemed satisfactory. a single factor was found to account for 59.9% of the total variation in the five items. the factor loading was as low as 0.669. as a result of this inter-item correlation study, it was discovered that government grants and subsidies (ggs) are not a meaningful element in interpreting the execution of malaysia’s environmental protection strategy. 4.6. regression analysis multiple linear regression analysis was performed at the end of the analysis. the association between the three independent variables (client requirement, corporate social responsibility, and regulation reformation) and environmental protection strategy was discovered by this study. the r-square value will be calculated, which represents the percentage of dependent variables that were explained by all of the independent variables. to provide a clearer view, stepwise regression was utilised to exclude weak independent variables (s). the r-square result for this regression analysis is 0.350, indicating that the three independent variables can explain 35.0% of the variation in environment protection strategy. because the table 7: one-way anova for client’s requirement (cr) s. no variable mean±s p-value for test of differencw between groups i. business scope 0.929* manufacturing 2.06±0.98 services 1.95±0.82 construction 1.96±0.85 others 2.03±0.80 ii. target market 0.503** within malaysia only 2.11±0.82 export only 1.88±1.39 both 1.94±0.81 iii. setup period 0.518* <1 year 2.15±0.82 1-5 years 1.82±0.78 6-10 years 2.23±0.98 >10 years 1.99±0.86 iv. nos. of full time employee 0.784* <10 employees 2.12±0.93 11-75 employees 2.03±0.80 76-200 employees 1.85±0.61 >200 employees 1.95±0.97 v. annual sales turnover 0.239* <1 million 2.11±0.76 1-10 million 1.83±0.83 11-50 million 2.19±0.82 >50 million 1.89±0.95 *based on parametric one-way anova procedure table 8: one-way anova for corporate social responsibility (csr) s. no. variable mean±sd p-value for test of differencw between groups i. business scope 0.267* manufacturing 1.49±0.60 services 1.59±0.64 construction 1.72±0.73 others 1.80±0.56 ii. target market 0.281* within malaysia only 2.11±0.82 export only 1.88±1.39 both 1.94±0.81 iii. setup period 0.115* <1 year 2.15±0.82 1-5 years 1.82±0.78 6-10 years 2.23±0.98 >10 years 1.99±0.86 iv. nos. of full time employee 0.069* <10 employees 2.12±0.93 11-75 employees 2.03±0.80 76-200 employees 1.85±0.61 >200 employees 1.95±0.97 v. annual sales turnover 0.004** <1 million 2.11±0.76 1-10 million 1.83±0.83 11-50 million 2.19±0.82 >50 million 1.89±0.95 *based on parametric one-way anova procedure sarwar, et al.: critical factors impacting the implementation of environmental protection strategies among malaysia industries international journal of energy economics and policy | vol 13 • issue 1 • 2023438 anova table’s p < 0.05, at least one of the three variables may be utilised to predict the environmental protection strategy. table 12 displayed the results from regression analysis of environmental protection strategy versus client’s requirement (cr), corporate social responsibility (csr) and regulation reformation (rr). the results proves that interrelationship of these variables can be written as: equation 1 ps = 0.412 +0.170 (cr) + 0.373 (csr) + 0.133 (rr) it stated unequivocally that all independent factors influenced the environmental protection strategy in an effective way. equation 2 eps= 0.531+0.420(csr)+0.187 (cr) regulation reformation has a p > 0.05, indicating that it is not a significant predictor of environmental protection strategy. client’s requirement and corporate social responsibility, on the other hand, have p = 0.05, making them significant predictors. there is no concern of multicollinearity because the variance inflation factor (vif) values for all independent variables are <5. eps = 0.412+0.170 (cr) +0.373 (csr) + 0.133 (rr) despite the fact that all three independent variables have a beneficial effect on the environmental protection strategy, regulation reformation was automatically omitted from the stepwise regression analysis since it is not a significant predictor. after removing the variables, the interdependence of the remaining variables may be expressed using the formula below. the r-square value remained unchanged at 0.336. this suggests that the remaining two independent variables may explain 33.6% of the variation in environment protection strategy. stepwise regression analysis is shown in table 13. the p-values for corporate social responsibility and client requirement are both <0.05, indicating that they are all significant predictors. there is no difficulty with multicollinearity because the vif values for the remaining independent variables are still <5. 5. implications from the study, it was identified that only economical factor (client’s requirement) and social factor (corporate social table 9: one-way anova for regulatory reformation (rr) s. no variable mean±s p-value for test of differencw between groups i. business scope 0.601* manufacturing 1.66±0.68 services 1.72±0.68 construction 1.57±0.59 others 1.84±0.64 ii. target market 0.872* within malaysia only 1.71±0.59 export only 1.58±0.64 both 1.71±0.71 iii. setup period 0.385* <1 year 2.07±0.49 1-5 years 1.72±0.56 6-10 years 1.87±0.64 >10 years 1.65±0.69 iv. nos. of full time employee 0.598* <10 employees 1.75±0.63 11-75 employees 1.76±0.63 76-200 employees 1.76±0.76 >200 employees 1.95±0.69 v. annual sales turnover 0.590* <1 million 1.75±0.62 1-10 million 1.67±0.61 11-50 million 1.80±0.67 >50 million 1.60±0.73 *based on parametric one-way anova procedure table 10: descriptive statistics for eps, cr, csr, ggs and rr item mean sd eps1 1.49 0.718 eps2 1.70 0.860 eps3 1.52 0.750 eps4 1.59 0.869 eps5 1.61 0.773 cr1 1.98 1.007 cr2 2.12 1.027 cr3 2.04 1.007 cr4 1.85 0.910 csr1 1.78 0.950 csr2 1.44 0.610 csr3 1.61 0.831 csr4 1.65 0.744 csr5 1.60 0.700 ggs1 1.56 0.826 ggs2 1.46 0.769 ggs3 1.46 0.769 rr1 1.75 1.064 rr2 1.55 0.716 rr3 1.81 0.864 eps: environmental protection strategy from business, cr: client’s requirement, csr: corporate social responsibility, ggs: goverments grants and subsidy table 11: inter-item correlation for eps, cr, csr, ggs and rr correlation eps cr csr ggs rr eps 1.000 0.480 0.545 0.139 0.367 cr 0.480 1.000 0.588 0.169 0.359 csr 0.545 0.588 1.000 0.192 0.430 ggs 0.139 0.169 0.192 1.000 0.144 rr 0.367 0.359 0.430 0.144 1.000 table 12: regression analysis of eps versus cr, csr and rr independent variables unstandadized coefficients standadized coefficients t sig vif b std. error beta (constant) 0.412 0.156 2.643 0.009 cr 0.170 0.069 0.221 2.465 0.015 1.561 csr 0.373 0.097 0.358 3.856 0.000 1.669 rr 0.133 0.080 0.134 1.662 0.099 1.253 sarwar, et al.: critical factors impacting the implementation of environmental protection strategies among malaysia industries international journal of energy economics and policy | vol 13 • issue 1 • 2023 439 responsibility) are related to environment factor. it revealed that 33.6% of the variation in environment protection strategy were explained through these two factors. the balance 76.4% of the variation were not explained and requires further research. other researches may propose other theoretical model which is more appropriate and relevant to explore other potential factors towards implementation environmental protection strategy. this denoted great research potential to findout other factors having significant relationship with implementation of environment protection strategy. this study found that government regulations and government grants and subsidy do not have significant relationship towards implementation of environmental protectionstrategy. this harmonizes with the latest direction on guided self regualtion (gsr) by the department of environment (gsr, 2016). policy makers and regulatory bodies can prepare policies and future regulations towards promoting the environmental related strategy in future. the strategies are useful for the small and medium industries as the cost, resources and manpower are the major barrier. to maximize cost saving in resources such as time, funding and manpower as well as to effectively tackle environmental related issues it is very important for the non-government organizations (ngo), to know the most significant driven factor of environmental protection strategy. therefore, this study can help ngo’s working on this issue can minimize the waste of resources and focuses the highest impact. 6. conclusion the study found that government grants and subsidy does not significantly promote the implementation of evironmental protection strategy. the inter-correlation of government grants and subsidy did not converged with others and therefore, it was not considered as a relevant factor. the other two variables namely client’s requirement and sorporate social responsibility exhibited positive relationship with evironmental protection strategy. furthermore, corporate social responsibility is the most important aspect, outweighing the needs of the client. in the final regression analysis, these two independent variables explain 33.6% of the variation in environmental protection approach, implying that there are 66.4% possible components that have yet to be examined, indicating opportunities for additional research. this research examined the significant determinants why organizations implement environmental protection strategy. this not only revalidates the relevance of previous study, but it also excludes certain other potential elements like technological progress, government funds, and subsidies, narrowing the field of future research. the findings of the study is necessary to identify the critical determinant factors that promotes the implementation of environmental protection strategy. it is important to academia, policy makers and regulatory bodies as well as non-government organizations. the study did, however, have several shortcomings. first, without a fixed sample frame, the questionnaires were dispersed at random to the participants. as a result, demographic criteria such as the nature of the business, the size of the organisation, the years of operation, and yearly turnover were not appropriately varied, resulting in an erroneous outcome. the sample size was small, and the west malaysian states of sabah and sarawak were left out. for a more exact conclusion, the follow-up study will narrow the scope to specific company types and include businesses from sabah and sarawak. moreover, participants who were new, or do not serve managerial level were unable to understand the corporate culture thoroughly in order to give an accurate respond. references abd rahim, r., jalaludin, f.w., tajuddin, k. (2011), the importance of corporate social responsibility on consumer behavior in malaysia. asian academy of management journal, 16(1), 119-139. brécard, d., hlaimi, b., lucas, s., perraudeau, y., salladarré, f. (2009), determinants of demand for green products: an application to eco-label demand for fish in europe. ecological economics, 69(1), 115-125. carrete, l., arroyo, p., trujillo, a. (2014), why do firms implement voluntary environmental actions and how are these activities evaluated? an empirical investigation in mexico. journal of management and sustainability, 4(4), 55-69. chatham-stephens, k., caravanos, j., ericson, b., sunga-amparo, j., susilorini, b., sharma, p., landrigan, p.j., fuller, r. (2013), burden of disease from toxic waste sites in india, indonesia, and the philippines in 2010. environmental health perspectives, 121(7), 791-796. fuller, r., landrigan, p.j., balakrishnan, k., bathan, g., boseo’reilly, s., brauer, m., caravanos, j., chiles, t., cohen, a., corra, l., cropper, m., ferraro, g., hanna, j., hanrahan, d., hu, h., hunter, d., janata, g., kupka, r., lanphear, b., lichtveld, m., martin, k., mustapha, a., sanchez-triana, e., sandilya, k., schaefli, l., shaw, j., seddon, j., suk, w., téllezrojo, m.m., yan, c. (2022), pollution and health: a progress update. the lancet planatery health, 6(6), e535-e547. gandenberger, c., kroll, h., walz, r. (2020), the role of frugal innovation in the global diffusion of green technologies. international journal of technology management, 83(1-3), 97-113. gillespie, s. (2019), climate crisis and consciousness: re-imagining our world and ourselves. london: routledge. hecht, a.d. (2007), the next level of environmental protection: business strategies and government policies converging on sustainability. sustainable development law and policy, 19(25), 79-80. table 13: stepwise regression analysis of eps versus cr and csr independent variables unstandadized coefficients standadized coefficients t sig vif b standard error beta (constant) 0.531 0.140 3.802 0.000 cr 0.420 0.093 0.403 4.502 0.000 1.529 csr 0.187 0.069 0.243 2.716 0.008 1.529 sarwar, et al.: critical factors impacting the implementation of environmental protection strategies among malaysia industries international journal of energy economics and policy | vol 13 • issue 1 • 2023440 hezri, a.a., hasan, m.n. (2006), towards sustainable development? the evolution of environmental policy in malaysia. natural resources forum, 30(1), 37-50. huang, s.y.b., ting, c.w., fei, y.m. (2021), a multilevel model of environmentally specific social identity in predicting environmental strategies: evidence from technology manufacturing businesses. sustainability, 13(8), 4567. ibrahim, i., jaafar, h.s. (2015), determinant factor of environment management practices: a theoretical framework. international review of management and business research, 4(4), 1180-1192. jain, p.k., sharma, p. (2021), protection of environmental factors and effecting actions on global warming. international journal of multidisciplinary education research, 9(6), 117-121. le, q.h. (2021), factors affecting consumer purchasing behavior: a green marketing perspective in vietnam. the journal of asian finance economics and business, 8(5), 433-444. liu, h., wang, y., shao, s. (2020), the situation and development strategies for environmental protection standardization in transportation industry of china. in: e3s web of conferences. edp sciences, les ulis, france. p145. mohammad, n. (2011), environmental law and policy practices in malaysia: an empirical study. australian journal of basic and applied sciences, 5(9): 1248-1260. mokthsim, n., salleh, k.o. (2014), malaysia’s efforts toward achieving a sustainable development: issues, challengesand prospects. in: procedia-social and behavioral sciences. vol. 120. p299-307. naderi, b., roshanaei, v., begen, m.a., aleman, d.m., urbach, d.r. (2021), increased surgical capacity without additional resources: generalized operating room planning and scheduling. production and operations management, 30(8), 2608-2635. nekmahmud, m., fekete-farkas, m. (2020), why not green marketing? determinates of consumers’ intention to green purchase decision in a new developing nation. sustainability, 12(19), 7880. punitha, s., rasdi, r.m. (2013), corporate social responsibility: adoption of green marketing by hotel industry. asian social science, 9(17), 79-93. puvanasvaran, a.p., zain, m.f.y., al-hayali, z.a., mukapit, m. (2012), sustainability of green technology in malaysia industry. in: international conference on design and concurrent engineering. p160-165. rahman, m.m., alam, k., velayutham, e. (2021), is industrial pollution detrimental to public health? evidence from the world’s most industrialised countries. bmc public health, 21(1), 1175. salim, h., padfield, r. (2017), environmental management system implementation in the food and beverage sector: a case study from malaysia. chemical engineering transactions, 56, 253-258. seroka-stolka, o. (2013), environmental corporate social responsibility (ecsr) in polish food sector enterprises from częstochowa regionempirical analysis. applied studies in agribusiness and commerce, 7(4-5), 101-106. shah, s.k., zhongjun, t., sattar, a., xinhao, z. (2021). consumer’s intention to purchase 5g: do environmental awareness, environmental knowledge and health consciousness attitude matter? technology in society, 65(c), 101563. sharma, a.p. (2021), consumers’ purchase behaviour and green marketing: a synthesis, review and agenda. international journal of consumer studies, 45(6), 1217-1238. siddique, m.z.r., hossain, a. (2018), sources of consumers awareness toward green products and its impact on purchasing decision in bangladesh. journal of sustainable development, 11(3), 9-22. stavins, r.n., reinhardt, f.l. (2010), corporate social responsibility, business strategy, and the environment. oxford review of economic policy. 26(2), 164-181. suki, n.m. (2013), green awareness effects on consumers’purchasing decision: some insights from malaysia. international journal of asia pacific studies, 9(2), 49-63. sushchenko, o., trunina, i., klok, o., loseva, o. (2019), management technologies of ensuring environmental protection as the territory development strategic priority. shs web of conferences. vol. 61. edp sciences, les ulis, france. p01026. timbur, m. (2012), the necessity of environmental goods trade liberalization. the usv annals of economics and public administration, 12(2), 77-86. tyler, t.r. (2006), why people obey the law. princeton university press, princeton, new jersey. ukaogo, p.o., ewuzie, u., onwuka, c.v. (2020), environmental pollution: causes, effects, and the remedies. in: microorganisms for sustainable environment and health. elsevier, netherlands. p419-429. united nations development programme [undp]. (2021), undp social and environmental standards. available from: https://www.undp. org/publications/undp-social-and-environmental-standards [last accessed on 2022 mar 28]. xiang, d., li, p., yuan, x., cao, h., liu, l., liu, y. (2021), energy consumption and greenhouse gas emissions of shale gas chemical looping reforming process integrated with coal gasification for methanol production. applied thermal engineering, 193, 116990. yazid, a.m.a., emam, m.a.a., shaaban, s., el-nashar, m.a. (2015), effect of spokes structures on characteristics performance of nonpneumatic tires. international journal of automotive and mechanical engineering, 11(1), 2212-2223. yazid, a.s., razali, a.r., hussin, m.r. (2012), determinants of enterprise risk management (erm): a proposed framework for malaysian public listed companies. international business research, 5(1), 80-86. yuan, y., lu, l.y., tian, g., yu, y. (2020), business strategy and corporate social responsibility. journal of business ethics, 162(2), 359-377. zafar, t.b., ding, w., khan, g.m., he, l., hao, c. (2019), environment protection strategies and climate change adaption for sustainable development: an overview of bangladesh. international journal of science and business, 3(3), 107-113. zailani, s., govindan, k., iranmanesh, m., shaharudin, m.r., chong, y.s. (2015), green innovation adoption in automotive supply chain: the malaysian case. journal of cleaner production, 108, 1115-1122. sarwar, et al.: critical factors impacting the implementation of environmental protection strategies among malaysia industries international journal of energy economics and policy | vol 13 • issue 1 • 2023 441 appendix (questionnaire) environmental protection strategy from business perspective in malaysia dear all, we are conducting this survey to identify the “critical factors impacting the implementation of environmental protection strategies among malaysia industries”. appreciate if you can take your time to go through and complete answering all questions carefully for the most representative result. thank you for your valuable time and support. regards part a demographic (select the most relevant) company business scope no of full time employee manufacturing < 10 employees services 11 – 75 employees construction 76 – 200 employees others > 200 employees company target market company annual sales turnover within malaysia only < 1 million export only 1 million – 10 million both 11 million – 50 million >50 million company setup period <1 year 1-5 years 6-10 years >10 years part b hypothesis testing (select the most relevant) environment protection strategy from business perspective strongly disagree somehow disagree neutral somehow agree strongly agree we will make sure all of our business process do not harm the environment we develop new products and processes that minimize negative environmental impact we are committed to protect the environment apart from daily business operation implementation of environmental related strategy is important to us we form our business strategy with minimal impact to the environment government regulations strongly disagree somehow disagree neutral somehow agree strongly agree environmental regulation play a significant role on our future growth stricter environmental regulation is a major reason why we protect the natural environment our environmental efforts will help to shape future environmental legislation client’s requirement strongly disagree somehow disagree neutral somehow agree strongly agree our customers prefer us to be environmentally friendly our customers are demanding environmentally friendly products and services. our market share will be increased by making our current products more environmentally friendly certification of “green” or “environmental friendly” product is important to our export client we will implement environmental protection plan if client required us to do it. sarwar, et al.: critical factors impacting the implementation of environmental protection strategies among malaysia industries international journal of energy economics and policy | vol 13 • issue 1 • 2023442 corporate social responsibility (csr) strategy strongly disagree somehow disagree neutral somehow agree strongly agree people will see our company as being environmental committed if it is stated inside our csr strategy positive environmental impact is good for our company image public preferred a company which is dedicated towards environmental protection being environmentally responsible will gain positive impact to company business incorporation of environmental protection plan in our csr can promote company to more recognition technology innovation strongly disagree somehow disagree neutral somehow agree strongly agree by reducing the negative impact of our activities on the natural environment we can improve the quality of our products and processes by regularly investing in research and development of cleaner products and processes we can become the leader in the industry we have realized significant cost savings by experimenting with ways to improve the environmental quality of our products and processes implementation of latest technology can help to minimize waste and thus improve protection to environment we will consider investing machines/equipment that can generate payback from our waste government grants and subsidy strongly disagree somehow disagree neutral somehow agree strongly agree we will improve environmental protection strategy if government grant is available government subsidy will improve willingness to protect environment. government grants and subsidies are a boosting factor towards formation of environmental protection strategy. cost is the major concern for us to implement effective environmental protection plan tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(2), 181-187. international journal of energy economics and policy | vol 12 • issue 2 • 2022 181 microgrid system evaluation using capacity factor for an off-grid community in nigeria elizabeth oses amuta1*, wara samuel tita2, agbetuyi ayoade felix1, orovwode hope evwieroghene1, matthew simeon3, tobi somefun1 1department of electrical and information engineering, covenant university, ota, nigeria, 2department of electrical and computer engineering, afe babalola university, ado-ekiti, nigeria 3department of electrical and electronics engineering, federal university of agriculture, abeokuta, nigeria. *email: elizabeth.amuta@covenantuniversity.edu.ng received: 25 april 2021 accepted: 29 december 2021 doi: https://doi.org/10.32479/ijeep.11523 abstract with the high rate of economic development, there is an increasing load demand even in rural communities and obayantor in nigeria. obayantor, having zero connection to the primary grid, needs an alternative source of electricity. following the community located in a tropical regoin of nigeria, it has enough solar energy that could be harnessed for electricity generation. with the high price of diesel fuel, solar microgrid seems to be the best energy solution for the rural community. in this study, technical and economic analysis was carried out on the solar-based microgrid and compared with a diesel-only microgrid using matlab software tool. the results showed that the solar microgrid was cost-effective and affordable for the rural community compared with the diesel microgrid, which is more expensive to afford. the annual system cost for the solar microgrid was lower compared with the diesel source. the result also revealed that the diesel-alone microgrid system is 4.71 times and 0.2 times more costly than the solar-based microgrid system in terms of energy and annualized system costs, respectively. this made the diesel microgrid not to have technical and economic feasibility for the community. keywords: microgrid, net present cost, capacity factor, simple payback period, cost of electricity jel classifications: q2, q42, p51 1. introduction electricity is the life wire of the economic growth and development of any nation. about 1.6 billion people living in isolated regions worldwide have no access to electricity, resulting in energy poverty (jiang et al., 2020). chances for economic development are a result of access to electric power (ali et al., 2021) (amuta et al., 2021). renewable energy sources are gaining more awareness globally due to global warming and are considered for electricity in homes and rural locations without access to electricity (energy access outlook, 2017) (orovwode et al., 2021). the minimum cost of energy in a microgrid can be determined by economic evaluation. therefore a technical and financial analysis on microgrid is vital to determine if its deployment is economically feasible when implemented. generating more energy from resources that can be cost-effective and contributing less to climate change or having adverse effects on the environment has been the focus of researchers presently (habibullah et al., 2017) (amuta et al., 2018) (astriani et al., 2019) considered techno-economic evaluation of a small-scaled microgrid with of solar-pv and storage battery energy source that could improve reliability. the result showed that the microgrid was cost is economically feasible when equipped with modern technology for control. the authors considered only net present value and internal rate of return economic indices. (sommerfeldt and madani, 2017) proposed a monte carlo method to present the techno-economic evaluation using solar photovoltaic for the swedish residential area. the result showed that the solar pv investor would have a 71% opportunity to get this journal is licensed under a creative commons attribution 4.0 international license amuta, et al.: microgrid system evaluation using capacity factor for an off-grid community in nigeria international journal of energy economics and policy | vol 12 • issue 2 • 2022182 a real return of 3% on investment, while the possibility dropped to 8% without subsidies. the authors in (cani et al., 2017) presented the feasibility and economic analysis of the sugar can power plant industry with renewable energy resources. the methodology implemented homer pro software in the existing and proposed structure considering the payback time. the result of the optimized plant configuration gave a shorter payback time compared to the proposed plant. this work aims to propose a micro-grid with a renewable power system that can satisfy the electricity load of the obayantor community by carrying out an economic and feasibility study. the following steps were taken (i) economics and technical analysis of the existing solar-pv electricity. (ii) evaluation of the dieselonly electricity system and finding out the best optimal system. 2. methodology most microgrid project in rural electrification studies fail as revealed in the literature due to low renewable energy systems (ress) utilization and detailed technical-economic analysis before designing a dependable power system, especially in developing countries. evaluation of the system economics helps to establish the various costs involved in micro-grid power projects. the cost includes the initial capital, operation, and maintenance costs, and cost of energy (coe). to attract potential investors into energy projects, the power system’s technical feasibility and financial viability assessment is needed to have a successful commercial application and implementation. especially for rural electrification. technical feasibility is essential because it helps to provide continuous access to electricity. at the same time, the financial viability assessment is vital to make the energy affordable for the community and encourage potential investors, including energy decision planners. the proposed microgrid structure is given in figure 1, comprising of solar pv, battery, and bi-directional converter. 2.1. assessment of the area of study the obayantor community in benin city is situated in edo state, in the southern part of nigeria, with an 862 km2 approximate area. the rural community does not have high energy consumption like the urban area. the appliances commonly used include domestic appliances such as fans lighting, and fridges. the solar microgrid has solar modules of 300 w, 65 kw diesel generator the microgrid consists of 300 w solar pv modules, a diesel generator of 65 kw, a battery backup system, a charge controller, a bi-directional converter system. the micro-grid structure is as shown in figure 1. the community aerial view is given in figure 2, 2.2. load assessment the field research method used was quantitative analysis, which involved analyzing data gathered from interviews and questionnaires administered to the community members. the operation hours of the users’ electrical loads decide the entire communities’ energy utilization and load profile. the appliances operating time and the amount of energy consumption vary from one house to another. visiting different remote homes allowed the author to ascertain the common appliances used by energy users. the data makes the 24-h analysis possible in this work. most of the dwellers are not available in the afternoon. the power consumption is higher in the morning and evening times than in the afternoon figure 3. 2.3. resources assessment solar energy is the energy source used in the off-grid power system under study in obayantor, nigeria. the hourly solar irradiance information serves as an input to the simulation software model (al-falahi et al., 2017). a constant reduction in photovoltaic solar prices over the years has increased the installed pv capacity worldwide. solar radiation in the area with latitude: 6° 20’ 21.0660’’ n, longitude: 5° 37’ 2.8092’’ e co-ordinate is 4.35 kwh/m2/day as given in figure 4 from the nasa data site (nasa, 2020). 2.4. micro-grid component 2.4.1. solar pv the power output of the solar-pv system is based on the rated capacity, de-rating factor, and irradiance as in equation 1-2 (kharrich et al., 2019) (esan et al., 2019): figure 1: structure of the proposed micro-grid figure 2: obayantor community aerial view amuta, et al.: microgrid system evaluation using capacity factor for an off-grid community in nigeria international journal of energy economics and policy | vol 12 • issue 2 • 2022 183 p p [1+ (t -t )]pv r p c c,stc� � � �� � � �� f h h t t stc, � (1) t t noct xgc amb� � �� � �� � � �� 20 800 o (2) tc was computed using equation (2). the tc value of a pv module is when the ambient temperature is 20oc. where: ppv =pv output power, pr = capacity rating of the pv module under standard test conditions in kw, f = pv de-rating factor, ht = solar irradiation incident of the location on the pv array (kw/m2), ht,stc = incident irradiation at standard test conditions (1 kw/m2), αp = temperature coefficient of power ( oc) for the selected module, tc= pv cell temperature ( oc), tc,stc = pv cell temperature under standard test conditions.(25oc), tamb =ambient temperature (oc), noct =norminal cell temperatute, (oc) usually in manufacturer’s datasheet. 2.4.2. diesel generator (dg) a diesel generator was utilized to smoothly meet the electrical power demand as a backup source whenever the solar pv is absent. the fuel (diesel) consumption rate qt (t) is obtained by using equation (3) (kharrich et al., 2019) (aderibigbe et al., 2017): q t p t pt dg dg gen dg dg rat( ) ( ) , ,� �� � (3) where: qt (t) = consumption rate of diesel (l/kwh), p t dg gen( ) , = power output generated (kw), pdg rat, = diesel generator rating (kw), αdg = fuel consumption coefficient i.e. generator fuel curve slope typically 0.246 l/kwh (mohamed et al., 2016), βdg = fuel consumption coefficient i.e. fuel curve intercept coefficient (typically 0.08145 l/kwh (mohamed et al., 2016). 2.4.3. batteries a battery energy storage system was used as a backup to supply power when the renewable energy source generator is not supplying. eq (4) gives the battery system size (a-h) (alzahrani et al., 2017) (elizabeth et al., 2019). bsize e days dod load off b inv � � � �max � � (4) where: eload is the demand for the community which must be satisfied. daysoff, is the number of days the battery will run (usually 3-5 days). ηinv, is the inverter efficiency, 92%, ηb, is the efficiency of battery 95%, dodmax is the depth of discharge of the battery system (usually 50-80% standard for deep cycle batteries). 3. technical-cost parameters the economic performance of the isolated microgrid was evaluated using the economic mathematical models in equations 5-15 in matlab 2018a code. 3.1. cost of electricity the cost of electricity is the primary part applied in technical and economic research. it calculates the unit cost of energy generated and the overall energy that can be produced during the project lifetime. the unit price of electricity was presented in equation (5) (kuznetsov et al., 2019). coe coe $ kwh totalnetpresentcost $ p * h yearl kw � � � � � � � � � ( ) ( / )8760 (5) each model was calculated by using parameters listed in table 1. 3.2. net present cost npc = 𝐶c𝑎𝑝. + 𝐶r𝑝. + 𝐶𝑂&𝑀 (6) where: 𝐶c𝑎𝑝. = initial capital cost 𝐶r𝑝. = replacement cost 𝐶𝑂&𝑀= operation & maintenance cosf equation (6) (mehrpooya et al., 2018) estimated the existing micro-grid system’s npc. figure 3: community hourly load demand profile figure 4: solar radiation amuta, et al.: microgrid system evaluation using capacity factor for an off-grid community in nigeria international journal of energy economics and policy | vol 12 • issue 2 • 2022184 3.3. financial assumptions the paper used inflation and interest rates of 8% and 12%, respectively. inflation rate (f) and nominal discount rate (i’) were used to determine the real discount rate (𝑖) according to trading economics’ report (tradingeconomics, 2019). 1usd is equivalent to n365 in nigeria, as at the time of this report. 3.4. annual system cost (asc) asc is the sum of the annual capital cost (acc), replacement cost (arc), and maintenance cost, respectively, and the sum is multiplied by the capital recovery factor (crf), mathematically represented in eqs. (7) – (9) (fodhil et al., 2019). asc acc aomc arc xcrf i z) i n � � � � �( ( )) ( , 1 (7) c asc crf i z npc = ( , ) (8) asc = npctot × crf (9) 3.5. annual capital cost the cost of different components in the micro-grid system are presented using the capital cost per kw (nejabatkhah, 2018). acc is expressed as in equation (10) (nejabatkhah, 2018): acc spv batt+c con dig] x crf i zcap i n � � � � � � � 1 [ , (10) the capital recovery factor (crf) for each component of a micro-grid is given in equation (11) crf i z, ( ) ( ) � � � � � � i x i i z z 1 1 1 (11) the annual real rate of interest (%) i i f f � � � ' 1 (12) 3.6. annual replacement cost the annual replacement cost (arc) is the component replacement cost during the project lifetime. (fodhil et al., 2019). the arc was estimated in equation (13). arc = crepbatt × sff (i, yrep) (13) crepbatt is the cost of replacing the storage banks in us$, yrep is the storage bank’s lifetime within a year. sff is the sinking fund factor, calculated as shown in equation (14). sff � � � i i yrep( )1 1 (14) 3.7. annual operation and maintenance cost the annualized maintenance cost (aomc) of a microgrid power system can be calculated considering the annual inflation rate (adefarati and bansal, 2019). the operation maintenance cost calculations used the parameters shown in table 1. the annual operation and maintenance cost of the system was evaluated using equation (15) (javed et al., 2019) amc = aom (1) (1+f) y [spv + batt+con +dig] (15) where: aom (1) is the maintenance cost of each component for the first year of the project. f = inflation rate (%), i’ = nominal interest rate (i’), cic = initial capital cost z = project lifetime, ($), ccap is the capital cost of each component. 3.8. micro-grid evaluation using capacity factor the interest in capacity factor (cf) analysis of an hpms is that the study provides an intelligent, summarized indication about the combined interaction between the microgrid and the site. the accurate microgrid capacity reduces the need for balancing energy and reserve power. 3.8.1. capacity factor capacity factor (cf) is the ratio of actual energy produced to the maximum possible power that could have been made during a given period. the cf is expressed in equation (16) cf actualenergy produce = maximumplantrating*timeduration (16) 3.8.2. simple payback period simple payback (spbp) is an economic index for measuring generation plants to consider the time-dependent valuation of the electrical power to determine the optimal design better than coe. spbp = c a ic ar (17) aar is calculated from equation (18) aar= cf × t × pratedx x coe (18) roi where: cic= initial capital cost, aar= average annual revenue based on hourly production. cf= capacity factor, t= time in hours, prated= rated power of solar pv. 3.8.3. return on investment the rate of investment (roi) is just the inverse of a simple payback period. unlike spbp, roi is usually expressed in percentage as seen in equation (19). table 1: the operational cost value of system components parameters name of components capital cost replacement cost o&m cost/ year solar pv (w) 3400 ($/kw) 3400 ($/kw) 10 ($/yr.) diesel generator/kw 5479 ($) 5479 ($) 0.0273 ($/hr.) battery kwh 270 ($/unit) 240 ($/unit) 10($/yr) bidirectional converter/kw 350($/kw) 350($/kw) 10($/kw/yr.) amuta, et al.: microgrid system evaluation using capacity factor for an off-grid community in nigeria international journal of energy economics and policy | vol 12 • issue 2 • 2022 185 roi = a c ar ic *100 (19) 3.8.4. net present value the initial capital cost cic is the present cost value of the microgrid power production, assuming the production to be constant annually from year to year. then the uniform cash flow must be discounted as it occurs in the future. npv is calculated, as shown by equation (20) (muyiwa et al., 2017). npv � �� � � �� � � � � � � � � � �a i i i car z z ic * * 1 1 1 (20) 4. results and discussion the optimization process in matlab simulated a range of equipment options over varying constraints depending on the annual system cost (asc). the combination of system components is arranged from the most effective cost to the least effective cost. the result for capital cost, net present cost, and asc of the solar pv cost was higher than the result for the diesel generator, which is an indication that the initial cost of solar is always more expensive (abdilahi et al., 2014). the diesel’s annual energy production and capacity factor were higher than that of the solar, indicating that the diesel generator performs very close to the rated capacity. the npv was positive and high, which is proved in (richard et al., 2020), suggesting that solar pv has better present investment worthiness over the project’s lifespan. the diesel-based micro-grid has a shorter spbp of 1.5yrs, considering the payback period because of its lifetime of 20000 hours, which is approximately two years, meaning the micro-grid owners will get back the money invested within a short period. still, the energy source will not function for an extended period, unlike the solar with an spbp of approximately nine years and the lifetime of solar being twenty-five years. the cost of diesel energy is $0.3, which is higher than that of solar of $0.10. hence solar micro-grid could be chosen primarily for a remote location with low-income earners and affordable, thereby making their energy consumption cost lower. but the diesel microgrid has higher annual energy production, which can be very useful in areas where solar irradiance is low. also, the rate of return on investment of project for the solar microgrid is seen to be lower, 33%, than that of the diesel microgrid of 67%, indicating that the energy planner will get back their capital invested on a diesel micro-grid within a short period because of the diesel operating hours than the solar microgrid. these results coincide with the results (abdilahi et al., 2014) and (tsuanyo et al., 2015). tsuanyo et al. 2015 reported that the coe and npc of the stand-alone diesel generators were higher than the hybrid solar pv/battery but increased the cost of investment in the solar system components. the economic evaluation was conducted, assuming that the microgrid is also supplied by another energy source, including a diesel generator table 2. figure 5 showed that the solar microgrid’s capital cost and net present value had the highest share in all the economic value than the diesel generator. the work showed that renewable energy sources have higher capital costs while the diesel generator alone has lower capital costs. the result is comparable with other literature works (tsuanyo et al., 2015). also, the diesel microgrid showed a higher cost of energy and ror than that of the solar pv. it was also seen that the solar pv microgrid had a higher percentage of spbp. for a microgrid with this energy resource type, the diesel will have less impact on the system economy but with a higher spbp rate, but might not be considered the best option for an energy source because of its environmental impact. the solar microgrid produced less green gas, as reported in the literature (hafez and bhattacharya, 2012). hafez and bhattacharya 2012, in their work, noted that renewable micro-grid reduced emissions of co2 significantly compared to conventional energy resources. table 2: economy of existing microgrid item solar pv system diesel generator capital cost ($) 227,957.41 58,954.04 capacity factor 0.57 0.69 net present cost ($) 37,085.30 32,020 cost of energy ($) 0.10 0.3 asc ($) 290,865.08 59,517.9 simple bay back period (years) 3 1.5 rate of return (%) 0.33 0.67 net present value ($) 476,952.6 8,948.92 annual energy production (kwh) 210240 175200 figure 5: generating sources cost compared amuta, et al.: microgrid system evaluation using capacity factor for an off-grid community in nigeria international journal of energy economics and policy | vol 12 • issue 2 • 2022186 figure 6 presents the cost of energy for each energy source. the values are 0.10 and 0.3 usd/kwh, which are competitive with the energy market electricity price (0.12-0.24 usd/kwh). however, the energy price of diesel was higher than that of solar pv, indicating that the existing micro-grid is economically viable compared to a diesel-only microgrid. 4. conclusions a techno-economic study of microgrid systems and the existing base case has been executed with certain assumptions. the area considered in this study was the obayantor community in nigeria, using the matlab tool. the study investigated some economic indicators: net present cost, annual system cost, cost of electricity generated, simple payback period, rate of return, net present value, and compare the existing power system with a diesel micro-grid in terms of cost. the result gave an extensive range of differences between the solar pv microgrid and the diesel microgrid system taking the project lifetime to be 25 years. the results showed that the dieselalone microgrid system is 4.71 times and 0.2 times more costly than the solar-based microgrid system in terms of energy and asc costs, respectively, primarily due to the present increasing diesel fuel rate. this study will further motivate investors to know the technical and economic prospects of a solar pv -based microgrid power system. the study also illustrates the serious drivers for proposing and implementing such an energy system in any rural community with zero grid connection. the policymakers could take a clue from this study. further studies would include other renewable energy sources, like wind and biomass, for cleaner energy generation. 5. acknowledgments authors express their appreciation to covenant university for sponsoring this research. references abdilahi, a.m., mohd yatim, a.h., mustafa, m.w., khalaf, o.t., shumran, a.f., mohamed nor, f. (2014), feasibility study of renewable energy-based microgrid system in somaliland’s urban centers. renewable and sustainable energy reviews, 40, 1048-1059. adefarati, t., bansal, r.c. (2019), economic and environmental analysis of a co-generation power system with the incorporation of renewable energy resources. energy procedia, 158, 803-808. aderibigbe, m.a., wara, s.t., airoboman, a.e. (2017), diesel engine generators consumption/emission controls by retrofitting for sustainable environment. in: ieee pes-ias powerafrica. p143-151. al-falahi, m.d.a., jayasinghe, s.d.g., enshaei, h. (2017), a review on recent size optimization methodologies for standalone solar and wind hybrid renewable energy system. energy conversion and management, 143, 252-274. ali, f., ahmar, m., jiang, y., alahmad, m. (2021), a techno-economic assessment of hybrid energy systems in rural pakistan. energy, 215, 119103. alzahrani, a., ferdowsi, m., shamsi, p., dagli, c.h. (2017), modeling and simulation of microgrid. procedia computer science, 114, 392-400. amuta, e., wara, s.t., agbetuyi, f., matthew, s. (2018), smart grid technology potentials in nigeria: an overview. international journal of applied engineering research, 32(2), 1191-1200. amuta, e.o., wara, s.t., agbetuyi, a.f., adoghe, u.a., olajube, a. (2021), reliability assessment of an off-grid hybrid micro-grid power system (hmps) for a remote community in nigeria. iop conference series: earth and environmental science, 655(1), 012053. astriani, y., shafiullah, g.m., anda, m., hilal, h. (2019), technoeconomic evaluation of utilizing a small-scale microgrid. energy procedia, 158, 3131-3137. cani, a.a., da costa mendes, p.r., normey-rico, c.b.j. (2017), economic viability analysis of a hybrid power system including renewable sources in the sugar cane industry. iet renewable power generation, 11(8), 1237-1245. elizabeth, a., wara, s.t., felix, a., simeon, t. (2019), hybridization of biomass-solar pv (photovoltaic) microgrid power system potentials for kaduna in nigeria. international journal of mechanical engineering and technology (ijmet), 10(4), 1022-1030. energy access outlook. (2017), energy access outlook 2017. esan, a.b., agbetuyi, a.f., oghorada, o., ogbeide, k., awelewa, a.a., afolabi, a.e. (2019), reliability assessments of an islanded hybrid pv-diesel-battery system for a typical rural community in nigeria. heliyon, 5(5), 1-13. fodhil, f., hamidat, a., nadjemi, o. (2019), potential, optimization and sensitivity analysis of photovoltaic-diesel-battery hybrid energy system for rural electrification in algeria. energy, 169, 613-624. habibullah, m., mahmud, k., koçar, g., islam, a.k.m., salehin, s. (2017), economic challenges of hybrid microgrid: an analysis and approaches for rural electrification. aip conference proceedings, 1851, 1-8. hafez, o., bhattacharya, k. (2012), optimal planning and design of a renewable energy based supply system for microgrids. renewable energy, 45, 7-15. javed, m.s., song, a., ma, t. (2019), techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm. energy, 176, 704-717. jiang, l., yu, l., xue, b., chen, x., mi, z. (2020), who is energy poor? evidence from the least developed regions in china. energy policy, 137, 111122. kharrich, m., mohammed, o.h., akherraz, m. (2019), assessment of renewable energy sources in morocco using economical feasibility figure 6: energy cost compared amuta, et al.: microgrid system evaluation using capacity factor for an off-grid community in nigeria international journal of energy economics and policy | vol 12 • issue 2 • 2022 187 technique. international journal of renewable energy research, 9(4), 1856-1864. kuznetsov, o.n., sultan, h.m., aljendy, r.i., zaki diab, a.a. (2019), economic feasibility analysis of pv/wind/diesel/battery isolated microgrid for rural electrification in south egypt. in: proceedings of the 2019 ieee conference of russian young researchers in electrical and electronic engineering, elconrus 2019. p1001-1006. mehrpooya, m., mohammadi, m., ahmadi, e. (2018), techno-economicenvironmental study of hybrid power supply system: a case study in iran. sustainable energy technologies and assessments, 25, 1-10. mohamed, m.a., eltamaly, a.m., alolah, a.i. (2016), pso-based smart grid application for sizing and optimization of hybrid renewable energy systems. plos one, 11(8), 1-22. muyiwa, a., quansah, d., agelin-chaab, m., paul, s. (2017), multipurpose renewable energy resources based hybrid energy system for remote community in northern ghana. sustainable energy technologies and assessments, 22, 161-170. nasa. (2020), nasa surface meteorology and solar energy. washington, dc, united states: nasa. available from: https:// www.power.larc.nasa.gov/data-access-viewer [last accessed on 2020 jun 30]. nejabatkhah, f. (2018), optimal design and operation of a remote hybrid microgrid. cpss transactions on power electronics and applications, 3(1), 3-13. orovwode, h.e., matthew, s., amuta, e., agbetuyi, f.a., odun-ayo, i. (2021), carbon footprint evaluation and environmental sustainability improvement through capacity optimization. international journal of energy economics and policy, 11(3), 454-459. richard, w., shu-chien, h., saina, z., jieeh-haur, c., xuran, i.l. (2020), renewable energy microgrids: economic evaluation and decision making for government policies to contribute to affordable and clean energy. applied energy, 274, 1-11. sommerfeldt, n., madani, h. (2017), revisiting the techno-economic analysis process for building-mounted, grid-connected solar photovoltaic systems: part two-application. renewable and sustainable energy reviews, 74, 1394-1404. tradingeconomics. (2019), nigeria inflation rate. available from: https:// www.tradingeconomics.com/nigeria/inflation-cpi [last accessed on 2019 dec 05]. tsuanyo, d., azoumah, y., aussel, d., neveu, p. (2015), modeling and optimization of batteryless hybrid pv (photovoltaic)/diesel systems for off-grid applications. energy, 86, 152-163. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 2 • 2023 427 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(2), 427-432. evaluation and analysis of wind speed with the weibull and rayleigh distribution models for energy potential using three models muhammad fitra zambak1*, catra indra cahyadi1,2, jufri helmi1, tengku machdhalie sofie1, suwarno1 1department of electrical engineering, universitas muhammadiyah sumatera utara, medan, indonesia, 2politeknik penerbangan medan, medan, indonesia. *email: mhdfitra@umsu.ac.id received: 07 january 2022 accepted: 14 january 2023 doi: https://doi.org/10.32479/ijeep.12775 abstract medan has a tropical climate and has the potential to support additional renewable energy, one of which is wind energy. analysis of wind speed in medan in particular has not been conducted to determine the potential for renewable energy. research on wind speed in medan, which ranges from 3.5 m/s to 7.5 m/s, has been carried out, but its potential has not been analyzed and evaluated. this study was conducted to analyze the shape factor and scale for wind speed using the weibull and rayleigh distribution, and three evaluation models were proposed, namely the correlation coefficient (r2), chi-square (ꭓ2), and root mean square error (rmse). wind speed data that is used to analyze and evaluate obtained from the meteorology, climatology, and geophysics agency for a period of 3 years, 2017-2019 in medan. the probability density distribution function (pdf) is described based on the shape (k) and scale (c) parameters obtained from the above data analysis. these two parameters are very important to be observed related to the potential of electrical energy produced in a place or area. the analysis result shows that weibull is better than rayleigh distribution based on pdf. meanwhile statistical analysis, weibull distribution is better than rayleigh distribution based on r2. but on the other hand, the rayleigh distribution is better than the weibull distribution based on chi-square and rmse. in addition to the analysis and evaluation, the potential for wind energy to be obtained is around 79.5 watt/m2. keywords: wind speed, pdf, weibull and rayleigh distribution, wind energy potential, r2, ꭓ2, rmse jel classifications: c25, c36, c44, c93, l94, q42 1. introduction the wind is a renewable energy source that can be used as an alternative energy source. energy supply-demand is increasing throughout the world resulting in the depletion of the global energy supply, so it is necessary to find alternative energy as a source of energy reserves. this energy limitation has the potential to produce energy that is not used and is clean from air pollution and does not pollute the environment. public awareness of environmental problems is increasing due to the energy crisis, climate change, environmental problems (skogen et al., 2018). these last few years, the company has been considering the condition of the environment to use energy consumption ecological clean and does not pollute the surrounding environment (goncalves et al., 2016), (jan urban, štěpán bahník, 2019). environmental problems can be overcome effectively by buying environmentally friendly products in daily consumption (ramayah et al., 2010), (nguyen et al, 2019), (sheng et al., 2019). wind speed probability distribution has been widely used for offshore wind farm planning and is used to estimate various amounts of power output and load (morgan et al., 2011), (mohammadi and mostafaeipour, 2013). this journal is licensed under a creative commons attribution 4.0 international license zambak, et al.: evaluation and analysis of wind speed with the weibull and rayleigh distribution models for energy potential using three models international journal of energy economics and policy | vol 13 • issue 2 • 2023428 wind speed information be useful to researchers involved in the study of renewable energy and wind energy use can reduce the things that are caused by fossil fuels and carbon dioxide emissions. statistical analysis can help to predict the renewable energy conversion from wind energy and several attempts to model it, to obtain energy estimates by the facts on the ground (weisser, 2003), (bivona et al., 2003). in its application, the wind speed distribution is used to represent the distribution function (van der auwera et al., 1980), (ashkar and ouarda, 1996). the statisticians are interested in using weibull models in modeling and analysis of wind energy, as it can be approached by the measurement data (ayodele et al., 2012). mathematically, the two-parameter weibull distribution function has been widely used compared to the three parameters (bobee, 1975). characteristics of wind are one of the most important parameters in the design and performance analysis system to determine the potential energy conversion. many researchers have developed statistical models to model the frequency distribution of wind speed. to determine the probability density function of wind speed using the rayleigh and weibull model (li and li, 2005). geographically, medan has daily and monthly wind speeds with varying duration and speed. availability of wind speed data can help to analyze more accurately the distribution also can help in constructing wind power sources (daut et al., 2011), (suwarno et al., 2017). wind speed characteristics in medan are assessed from the amount of potential wind energy generally, these characteristics use pdf and other functions. pdf has been studied and applied in all regions of the world, but selecting pdf is very important in analyzing wind energy because wind energy is formulated as an explicit function of several parameters of wind speed distribution (suwarno and rohana, 2021). pdf is suitable for evaluating the wind speed that will be used to estimate the power output. rayleigh and weibull distribution most used in the analysis of wind speeds, and the most common way to study wind energy estimation (ahmed shata and hanitsch, 2006), (akpinar and akpinar, 2005), (mirhosseini et al., 2011), (petković et al., 2014), (suwarno and m fitra zambak, 2021). so far, the weibull distribution is most widely used to analyze the characterization of the wind speed and the most common among models (celik, 2003). in previous research, the analysis of the characteristics of wind speed using weibull and rayleigh distribution, but not many studies that relate to the evaluation of the feasibility of using the model data used correlation coefficient, chi-square, and rmse. therefore, this study proposes pdf analysis with the weibull and rayleigh distribution and evaluates it with statistical analysis models, namely r2, ꭓ2, and rmse 2. research methods this research, analyzes using two models of weibull and rayleigh. then analyzed using a statistical probability density function (pdf), then the results were compared to two models to find the most appropriate model to use in analyzing the characteristics of wind speed and potential electrical energy. the research step is to analyze the wind speed with pdf using the weibull and rayleigh distribution, and then evaluate it with three models (r2, ꭓ2, and rmse) to see the suitability of the data studied and the results compared to select the best model proposed and to be applied, then calculate the energy potential electricity generated from the conditions of wind speed is being investigated. this research was carried out according to the proposal using two models, namely the weibull and rayleigh distribution models. the analysis is performed using probability density function statistics, then the results of the two models are compared to find the most suitable model to be used to analyze wind speed and energy potential. 2.1. wind speed distribution pdf function and other functions form an important aspect to analyze wind speed. the use of a probability density function for a variety of applications, including identification and analysis of the parameters of the distribution function of wind speed data (bivona et al., 2003), (akpinar and akpinar, 2005). the rayleigh and weibull distributions are used to adjust the pdf of the measured wind speed at the site over a specified period and the weibull pdf distribution is expressed as (akpinar and akpinar, 2005), (ramrez and carta, 2005), (egbert boeker, 1999): f v k c v c exp v c k k ( ) =             −               −1 (1) here, f(v) is the incremental probability, c and k represent scale and shape parameters, respectively. the following equation to estimate the shape (k) and the scale (c) factor is expressed by (carta and ramirez, 2007), (carta et al., 2009). k v =       − σ 1 086. and c v k = +                  γ 1 1 (2) the distribution for the cdf is given by (ramrez and carta, 2005), (akpinar and akpinar, 2005), (egbert boeker, 1999), (carta and ramirez, 2007), (celik, 2003). f v exp v c k ( ) = − −               1 (3) the shape factor equal to 2, substituted for equation (1), will give the pdf of the rayleigh and is represented by (akpinar and akpinar, 2005), (egbert boeker, 1999), (carta and ramirez, 2007), (algifri ah, 1998). f v v c exp v c k ( ) =       −               2 2 (4) zambak, et al.: evaluation and analysis of wind speed with the weibull and rayleigh distribution models for energy potential using three models international journal of energy economics and policy | vol 13 • issue 2 • 2023 429 the average value (vm) and standard deviation (σ) can be calculated, respectively (celik, 2003), (algifri, 1998). v c km = +      γ 1 1 (5) σ = +      − +            c k k γ γ1 2 1 12 1 2/ (6) here, γ is the gamma function. the rayleigh scale (cr) parameter is obtained from the equation (7) which is represented by c n vr i n i= = ∑ 1 2 1 2 (7) here, vi is the i th wind speed, the average rayleigh value is determined by the equation (8), given by; v cr r= π 2 (8) 2.2. wind power density function the magnitude of the wind speed directly proportional to 3 times the wind speed (v) through a blade sweep area (a) so that its magnitude is as follows; (akpinar and akpinar, 2005), (algifri, 1998), (jaramillo and borja, 2004). p v av( ) = 1 2 3ρ (9) here, ρ is the average air density. the power for the monthly or annual wind speed per unit area at a location can be expressed as: p v kw = +       1 2 1 13ρ γ (10) here, c is expressed as follows; c v k m= +      γ 1 1 (11) the parameters will affect the shape and scale of the average wind speed mv (algifri ah, 1998), (jaramillo oa, 2004), (ali naci celik, 2004). model rayleigh obtained by adjusting the shape parameter (k) is equal to 2 in the equation (8), then the parameters rayleigh scale model can be expressed by (celik, 2003), (al-mohamad and karmeh, 2003). p vr m= 3 3 π ρ (12) 2.3. modeling of wind data the wind speed modeling will depend on the height of the installed instruments. based on empirical, the wind speed model can be approached empirically in the following equation (13); v n v i n i= = ∑ 1 1 (13) here, v is the wind speed average; vi is the measured wind speed; n is the number of measurement data. 2.4. analysis of the distribution function the analysis model uses weibull and rayleigh and is evaluated using the correlation coefficient (r2), chi-square and root mean square error (rmse) which is stated by the following equation; r y z x y y z i n i i i n i i i n i i 2 1 2 1 2 1 2 = −( ) − −( ) −( ) = = = ∑ ∑ ∑ (14) χ2 1 2 = −( ) − =∑i n i iy x n n (15) rmse n y x i n i i= −( )        = ∑ 1 1 2 1 2/ (16) here, yi the i th measured data, zi the average value, xi the i th predictive data with the weibull or rayleigh, n and n are the number of observations, and the number of constants, respectively (li and li, 2005). 3. results and discussion 3.1. shape and scale parameters variable wind speed is usually described using the density function of two parameters, ie the shape (k) and scale (c) factor. the shape and scale parameters for the 3 years are shown in table 1. the results were calculated approach to these two parameters, each year is shown in table 1, wherein the shape parameter ranges table 1: shape and scale parameters for 3 years years 2017 2018 2019 parameters k c k c k c january 4.897 4.849 4.897 4.849 4.887 5.017 february 4.667 5.343 4.744 5.318 4.053 5.389 march 4.930 5.549 4.959 5.573 3.833 5.053 april 5.729 5.049 5.722 5.029 5.303 5.228 may 5.820 5.717 5.857 5.757 4.813 5.303 june 4.783 5.834 4.747 5.857 5.122 5.866 july 4.373 5.848 4.341 5.867 6.952 5.095 august 5.056 5.848 5.187 5.456 5.253 5.740 september 4.306 5.536 4.161 5.354 6.714 5.702 october 4.631 5.261 4.834 5.097 5.725 5.833 november 4.572 5.449 4.540 5.490 5.688 5.596 december 4.556 4.585 4.459 4.611 6.048 6.113 years 4.560 5.373 4.916 5.347 5.266 5.496 zambak, et al.: evaluation and analysis of wind speed with the weibull and rayleigh distribution models for energy potential using three models international journal of energy economics and policy | vol 13 • issue 2 • 2023430 0 1 2 3 4 5 6 7 8 0 0.05 0.1 0.15 0.2 0.25 wind speed (m/s) p ro ba bi lit y rayliegh 2017 rayliegh 2018 rayliegh 2019 figure 2: rayleigh pdf 3 years 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 -0.2 0 0.2 0.4 0.6 0.8 1 1.2 0 0.5 1 0 1 2 3 4 5 6 7 8 -0.2 0 0.2 0.4 0.6 wind speed (m/s) p ro ba bi lit y weibull 2018 rayliegh 2018 difference 2018 figure 4: comparison of weibull and rayleigh in 2018 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 -0.2 0 0.2 0.4 0.6 0.8 1 1.2 0 0.5 1 0 1 2 3 4 5 6 7 8 -0.2 0 0.2 0.4 0.6 wind speed (m/s) p ro ba bi lit y weibull 2017 rayliegh 2017 difference 2017 figure 3: comparison of weibull and rayleigh in 2017 0 1 2 3 4 5 6 7 8 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 wind speed (m/s) p ro ba bi lit y pdf wd 2017 pdf wd 2018 pdf wd 2019 figure 1: weibull pdf 3 years from 4.560 to 5.266, and the scale parameter ranges from 5.347 to 5.496, and the average shape parameter is 4.914, and the scale parameter around 5.405. comparison pdf each year for the weibull distribution is shown in figure 1. comparison pdf each year for the weibull distribution (wd) is shown in figure 1. the amount pdf of the weibull distribution is influenced by two parameters related to the wind speed, the wind speed of about 5.34 m/s can be seen that the highest pdf occurred in 2019, followed in 2018 and 2017. comparison pdf each year for rayleigh distribution is affected by the scale parameter is related to the wind speed, the wind speed of about 3.73 m/s is obtained pdf highest in 2018, followed by 2019 and 2017, as shown in figure 2. the comparison between the weibull and rayleigh models for each year is shown in figures 3-5. figure 3 shows a comparison between the weibull and rayleigh models for 2017, the difference of the two models for 2017 indicated by the red line in the amount of about 1.3253%. figure 4 shows a comparison between the weibull and rayleigh models for 2018, the difference between the two models is indicated by the red line in the amount of about 0.7363%. 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 -0.2 0 0.2 0.4 0.6 0.8 1 1.2 0 0.5 1 0 1 2 3 4 5 6 7 8 -0.2 0 0.2 0.4 0.6 wind speed (m/s) p ro ba bi lit y weibull 2019 rayliegh 2019 difference 2019 figure 5: comparison of weibull and rayleigh in 2019 zambak, et al.: evaluation and analysis of wind speed with the weibull and rayleigh distribution models for energy potential using three models international journal of energy economics and policy | vol 13 • issue 2 • 2023 431 table 2: the statistic analysis parameters for monthly wind speed distribution in medan evaluation models january february march april may june r2 weibull 0.965 0.970 0.967 0.946 0.934 0.978 rayleigh 0.311 0.663 0.630 0.309 0.641 0.788 ꭓ2 weibull 0.041 0.041 0.045 0.048 0.072 0.046 rayleigh 0.807 0.459 0.501 0.611 0.391 0.438 rmse weibull 0.198 0.190 0.208 0.211 0.264 0.208 rayleigh 0.8839 0.6650 0.6959 0.7688 0.615 0.6506 july august september october november december r2 weibull 0.971 0.964 0.974 0.970 0.970 0.974 rayleigh 0.726 0.610 0.609 0.502 0.646 0.195 ꭓ2 weibull 0.049 0.044 0.040 0.039 0.043 0.031 rayleigh 0.463 0.473 0.473 0.640 0.507 0.957 rmse weibull 0.218 0.207 0.207 0.193 0.200 0.173 rayleigh 0.669 0.677 0.677 0.787 0.700 0.962 table 3: wind energy in medan potential years 2017 2018 2019 power density (w/m2) 74.7158 72.2078 79.4618 jan feb mar apr may jun jul aug sep oct nov dec 0 10 20 30 40 50 60 70 80 90 100 w in d po w er d en si ty (w /m .m ) monthly wind speed (m/s) figure 6: power density (w/m2) figure 5 shows the comparison between the weibull and rayleigh models for 2019, the difference between the two models is shown by the red line which is about 0.3277%. the difference in average for the 3rd year about 0.7964%, the difference in average for 3 years showed quite good, this shows that the two models are proposed to be well received by a probability density function and statistical tests. 3.2. distribution function analysis they analyze the potential of wind energy using the correlation coefficient (r2), chi-square (ꭓ2), and rmse are shown in table 2. table 2 shows the results of the evaluation using the correlation coefficient, chi-square and, root mean square error (rmse). the correlation coefficient for the weibull distribution ranges from 0.9338 to 0.9775, while for the rayleigh distribution it ranges from 0.1946 and 0.7876. weibull models maintain the correlation coefficient (r2) is best for all distribution functions. however, for statistical analysis based on chi-square and rmse, the weibull distribution has the lowest value compared to the rayleigh distribution. 3.3. energy density and power density potential the power density of the monthly wind speed is shown in figure 6. wind speed for 3 years (2017-2019) has a minimum, maximum, and average speed between 2.33 and 2.71 m/s, 7.35 and 7.71 m/s, and 4.91 and 5.06 m/s, respectively. meanwhile, the annual power density is shown in table 3, with the power density between 72,2078 and 79.4618 w/m2. this power density is only capable of producing a maximum power per square meter of 79.4618 watts. the potential wind speed converted to energy and power density in medan based on actual wind speed data is shown in table 3. 4. conclusion wind speed characteristics in medan were statistically analyzed and wind speed data collected for 3 years (2017-2019) were used for analysis. the results of the analysis and evaluation show that; 1. comparison of pdf that, weibull model is better than rayleigh. 2. statistical analysis using the correlation coefficient (r2), the weibull distribution is best compared to the rayleigh distribution. however, using chi-square and rmse that, the rayleigh distribution is better than the weibull distribution. 3. the power density is only capable of producing a small amount of usable power for street lighting, which is around 79.5 watt/m2. zambak, et al.: evaluation and analysis of wind speed with the weibull and rayleigh distribution models for energy potential using three models international journal of energy economics and policy | vol 13 • issue 2 • 2023432 references ahmed shata, a.s.a., hanitsch, r. (2006), evaluation of wind energy potential and electricity generation on the coast of mediterranean sea in egypt. renewable energy, 31(8), 1183-1202. akpinar, e.k., akpinar, s. (2005), a statistical analysis of wind speed data used in installation of wind energy conversion systems. energy conversion and management, 46(4), 515-532. algifri, a.h. (1998), wind energy potential in aden-yemen. renewable energy, 13(2), 255-260. al-mohamad, k.a., karmeh, h. (2003), wind energy potential in syria. renewable energy, 28, 1039-1046. ashkar, f., ouarda, t.b.m. (1996), on some methods of fitting the generalized pareto distribution. journal of hydrology, 177, 117-141. ayodele, t.r., jimoh, a.a., munda, j.l., agee, j.t. (2012), wind distribution and capacity factor estimation for wind turbines in the coastal region of south africa. energy conversion and management, 64, 614-625. bivona, s., burlon, r., leone, c. (2003), hourly wind speed analysis in sicily. renewable energy, 28, 1371-1385. bobee, b. (1975), the log pearson type 3 distribution and its application in hydrology. water resources research, 11(5), 681-689. carta, j.a., ramirez, p. (2007), analysis of two-component mixture weibull statistics for estimation of wind speed distributions. renewable energy, 32(3), 518-531. carta, j.a., ramirez, p., velazquez, s. (2009), a review of wind speed probability distributions used in wind energy analysis: case studies in the canary islands. renewable and sustainable energy reviews, 13(5), 933-955. celik, a.n. (2003), weibull representative compressed wind speed data for energy and performance calculations of wind energy systems. energy conversion and management, 44(19), 3057-3072. daut, i., irwanto, m., suwarno, irwan, y.m., gomesh, n., ahmad, n.s. (2011), potential of wind speed for wind power generation in perlis, northern malaysia. telkomnika, 9(3), 575-582. egbert boeker, r.v.g. (1999), environmental physics. 2nd ed. united states: john wiley and sons, ltd. goncalves, h.m., lourenco, t.f., silva, g.m. (2016), green buying behavior and the theory of consumption values: a fuzzy-set approach. journal of business research, 69, 1484-1491. jaramillo, o.a., borja, m.a. (2004), wind speed analysis in la ventosa, mexico: a bimodal probability distribution case. renewable energy, 29, 1613-1630. li, m., li, x. (2005), mep-type distribution function: a better alternative to weibull function for wind speed distributions. renewable energy, 30, 1221-1240. mirhosseini, m., sharifi, f., sedaghat, a. (2011), assessing the wind energy potential locations in province of semnan in iran. renewable and sustainable energy reviews, 15(1), 449-459. mohammadi, k., mostafaeipour, a. (2013), using different methods for comprehensive study of wind turbine utilization in zarrineh, iran. energy conversion and management, 65, 463-470. morgan, e.c., lackner, m.m., baise, l.g., vogel, r.m. (2011), probability distributions for offshore wind speeds. energy conversion and management, 52, 15-26. nguyen, t.t.t., yang, z., nguyen, n., johnson, l.w., cao, t.k. (2019), greenwash and green purchase intention: the mediating role of green skepticism. sustainability, 11, 2653. petković, d., shamshirband, s., anuar, n.b., saboohi, h., wahab, a.w.a., protić, m., zalnezhad, e., mirhashemi, s.m.a. (2014), an appraisal of wind speed distribution prediction by soft computing methodologies: a comparative study. energy conversion and management, 84, 133-139. ramayah, t ., lee j.w.c., mohamad, o. (2010), green product purchase intention: some insights from a developing country. resources, conservation and recycling, 54, 1419-1427. ramrez, p., carta, j.a. (2005), the use of wind probability distributions derived from the maximum entropy principle in the analysis of wind energy. a case study. energy conversion and management, 47, 2564-2577. sheng, g., xie, f., gong, s., pan, h. (2019), the role of cultural values in green purchasing intention: empirical evidence from chinese consumers. international journal of consumer studies, 43, 315-326. skogen, k., helland, h., kaltenborn, b. (2018), concern about climate change, biodiversity loss, habitat degradation and landscape change: embedded in different packages of environmental concern. journal for nature conservation, 44, 12-20. suwarno, s., rohana, r. (2021), wind speed modeling based on measurement data to predict future wind speed with modified rayleigh model. international journal of power electronics and drive system, 12(3), 1823-1831. suwarno, s., zambak, m.f. (2021), the probability density function for wind speed using modified weibull distribution. international journal of energy economics and policy, 11(6), 544-550. van der auwera, l., de meyer, f., malet, l.m. (1980), the use of the weibull three-parameter model for estimating mean wind power densities. journal of applied meteorology, 19(7), 819-825. weisser, d. (2003), a wind energy analysis of grenada: an estimation using the ‘weibull’density function. renewable energy, 28(11), 1803-1812. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 5 • 2022420 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(5), 420-424. a causal assessment of nigeria’s crude oil revenue, health expenditure, and economic growth olanike bosede awoyemi1*, divine amarachi nwibe2 1department of economics, college of social and management sciences, afe babalola university, ado-ekiti, nigeria, 2department of economics, college of social and management sciences, afe babalola university, ado-ekiti, nigeria. *email: nikeawoyemi@abuad.edu.ng received: 28 may 2022 accepted: 03 september 2022 doi: https://doi.org/10.32479/ijeep.13318 abstract economic growth and health expenditure in nigeria have become major priorities, and there is no doubt that health expenditure in nigeria has risen over the years. according to studies, revenue and expenditure are important factors that contribute to a country’s economic growth. using pairwise granger causality, the study investigated the relationship between oil revenue, health expenditure, and economic growth. the variables of interest were oil revenue, health expenditures, real gross domestic product, consumer price index, and money supply. the annual time series data from 1980 to 2020 were obtained from the central bank of nigeria (cbn) statistical bulletin, annual reports, and the world bank database. according to the findings, there is a bidirectional relationship between total health expenditure and real gdp. however, there is a unidirectional relationship between oil revenue and gdp. furthermore, there is a unidirectional relationship between oil revenue and health expenditure. the study concluded that oil revenue and health expenditure granger cause nigerian economic growth. therefore, the government should make better use of oil revenue, close loopholes, and increase health spending. to increase productivity and economic growth, the government should increase public spending on health. keywords: health expenditure, economic growth, oil revenue, nigeria, granger causality jel classifications: i18, o47, q34, q47 1. introduction nigeria is africa’s largest oil producer and the world’s 13th largest, with oil accounting for more than 90% of exports. crude oil has been vital to the nigerian economy since its discovery in 1956. after nearly 50 years of exploration, the oil and gas sector remain critical to the nigerian economy. crude oil and natural gas have provided the nigerian government with unprecedented revenue in recent decades. they generate 75% of the government’s total revenue. nigeria is africa’s largest oil producer and the world’s 13th largest oil producer, with a maximum crude oil production capacity of 2.5 million bpd. in recent decades, crude oil and natural gas have provided the nigerian government with unprecedented revenue. in addition, average crude oil production and export increased by 9.3 and 12.6%, respectively, to 1.88 mbpd and 1.43 mbpd in 2018, compared to 2017. in addition, average crude oil production and export increased by 9.3 and 12.6%, respectively, to 1.88 mbpd and 1.43 mbpd in 2018, compared to 2017. according to the cbn’ (2018; 2019) annual report, nigeria has nearly 40 billion barrels of proven oil reserves, with oil revenue accounting for roughly 70 and 69% of total government revenue in 2018 and 2019, respectively. however, as kjell and petter (2011) demonstrate, while the economies of other oil-exporting countries are thriving, nigeria, one of africa’s largest oil producers, has continued to face poor health and slow economic growth. according to baghebo (2017), nigeria’s health status remains poor, trailing the global average. nigeria’s health situation is marked by low birth-age life expectancy, high infant and maternal mortality rates, and malaria and tuberculosis infections. nigeria this journal is licensed under a creative commons attribution 4.0 international license awoyemi and nwibe: a causal assessment of nigeria’s crude oil revenue, health expenditure, and economic growth international journal of energy economics and policy | vol 12 • issue 5 • 2022 421 has the world’s fourth highest maternal mortality rate, with 576 deaths per 100,000 live births (unicef, 2021). there is also a high infant mortality rate of 69 per 1000 live births and a rate of under-five mortality of 128 per 1000 live births. malaria, pneumonia, and diarrhea account for more than half of all deaths in children under the age of five, according to a unicef report (64 percent). despite recent increases in investment in this area, the number of patients who can receive proper care remains limited. every year, approximately 262,000 babies die at birth, making it the world’s second highest national total. in 2021, nigeria’s life expectancy at birth was estimated to be 55 years (wdi, 2021), and the prevalence of hiv/aids infection has also contributed significantly to the country’s low life expectancy. it was estimated to be 1.3% of the population aged 15-49 years, which is higher than the global average (0.7%). this poor health situation has hampered the country’s growth because adequate and effective health care spending is widely regarded as critical to improving health outcomes (anyanwu and erihijakpor, 2009). at the macro level, investments in health personnel and infrastructure are intended to improve health conditions, resulting in better human capital and, consequently, higher productivity (output). in sub-saharan africa (ssa) and other developing regions where resources are scarce, health spending has received less attention in government budgets (world health organization (who), 2016). as a result, there is a need to investigate the role of oil revenue, which is the nigerian government’s primary source of revenue, in the relationship between health expenditure and economic growth. to address this concern, this paper investigates the relationship between oil revenue, health spending, and economic growth. the remainder of this study includes a review of the literature, methodology, the results and discussion of the findings, conclusion, and recommendations. 2. literature review 2.1. situational analysis of oil revenue, health expenditure and real gdp in nigeria over the last five decades, the oil sector of the economy has grown, with oil production increasing from 390.5 barrels in 1987 to 675.3 barrels in 1998. in 1970, oil revenue totaled n166.6 million. additionally, it increased to n1,591.7 billion in 2000 and to n5,545.8 billion in 2018. the economy has become oil-dependent as a result of the high revenue generated by the oil sector, complicating macroeconomic management (akinlo, 2012). according to onaolapo et al. (2013), nigeria’s petroleum industry is the country’s largest and primary source of gdp, accounting for 70% of government revenue and approximately 95% of foreign exchange earnings. oil revenue, on the other hand, has been declining in recent years (figure 1). this is believed to have resulted in decreased government spending, particularly on health care. oil revenue and total health expenditure as a percentage of gdp both increased from the early 1980s to 2011, but then declined. despite deliberate efforts to increase public health spending, nigerian governments have failed to meet the un’s recommended benchmark of 8% to 10% of gdp (oni, 2014). the covid-19 pandemic hit nigeria and many other african countries hard, exposing a broken healthcare system and low health indicators. with a population growth rate of 3.2 percent and a gdp growth rate of 3.4% in 2021, nigeria’s health indicators are among the worst in africa according to usaid. economic growth is promoted by increased government spending on socioeconomic and infrastructure. accordingly, yusuf et al. (2021) suggest increasing health budget allocations to boost economic growth in nigeria and sub-saharan africa. 2.2. theoretical literature the wagner (1958) and keynes' theories have been the most prominent theoretical debates on the link between government spending and growth. domestic economic growth is seen as an important factor in the wagner law, according to ampah and kotosz (2016). wagner predicted that as trade and industrialization advanced, the role of the private sector would grow. as private sector activity grows, government spending to regulate the now-vibrant private sector will grow as well. it states that: (i) the expansion of state functions leads to increased public expenditure on economic administration and regulation; (ii) modern industrial society leads to increased political pressure for social progress and increased social consideration in industrial conduct; (iii) the increase in public expenditure is greater than the proportional increase in state functions. musgrave and musgrave (1988) argued that as progressive nations industrialize, the public sector’s share of the national economy grows steadily, as noted by chude and chude (2013). keynes (1936) noted that countries’ over-reliance on wagner’s hypothesis interpretations hampered economic recovery during the great depression. to help economies recover from the depression, keynes advised countries to increase public spending. unlike wagner’s hypothesis, keynes (1936) believes that government spending is an autonomous and exogenous variable. exogenous factors like government spending can be used to foster economic growth. this is because, increased government consumption will likely increase employment, profitability, and investment. keynes went on to say that government spending increases aggregate demand and thus output by smoothing out business cycle fluctuations and stimulating economic activity. this means that government spending is the cause rather than the effect of economic growth (wu et al., 2010). among others, thabane and lebina (2016) and okoye et al. (2019) have validated this framework. 2.3. empirical literature empirical research has yielded conflicting results regarding the effects of oil revenue on growth and health. specifically, akinleye et al. (2021) use augmented dickey fuller (ardl) to examined the impact of oil revenue on economic growth in nigeria from 1981 to 2018. the variables used in this study are exchange rate, oil revenue, petroleum profit tax and inflation. the result shows that oil revenue have a positive and significance effect on economic growth (rgdp) in both short and long run. the findings were consistent to aminu and raifu (2019) which indicate oil revenues have significant positive effects on economic growth in both the short-run and long-run. similarly, fasina and adegbite (2016), conducted research on the impact of the petroleum profit tax (ppt) on the nigerian economy from 1970 to 2010. the variables used in this work were the exchange rate, inflation, petroleum profit tax, and gdp (gdp). data was analyzed using multiple regression awoyemi and nwibe: a causal assessment of nigeria’s crude oil revenue, health expenditure, and economic growth international journal of energy economics and policy | vol 12 • issue 5 • 2022422 analysis. the study discovered that crude oil revenue was very beneficial to the nigerian economy during the study period, and natural resources had a positive relationship with economic growth and development. likewise, aregbeyen and kolawole (2015) examined the relationships among oil revenue, government spending, and economic growth in nigeria from 1980 to 2012. granger causality was to determine the direction of causality and findings from the analysis revealed that oil revenue granger caused both total government spending and growth. odularu (2018) also discovered that domestic consumption and crude oil exports significantly contribute to the improvement of the nigerian economy. this finding was consistent with the evidence provided by olatunji and adegbite (2018); abdul-rahamoh et al. (2017), which indicates that petroleum profits contribute positively to economic growth in nigeria. while some studies have provided evidence about the positive impact of revenue from oil on economic growth, others have shown negative effects. gopar et al. (2017) conducted a longitudinal study on the impact of petroleum profits tax on economic growth in nigeria and found no causal link between petroleum profit tax and real gross domestic products. abimbola and onazi (2018) investigate the nexus between oil revenue and economic growth in nigeria using ols technique. the paper therefore concludes that oil revenue is negatively related to economic growth in nigeria based on its findings. akinlo (2019) investigated the importance of oil in the development of the nigerian economy from 1960 to 2016. the study used multivariate var model. the results revealed that potential growth in non-oil sectors can be brought about by oil; it also revealed that oil has a negative effect on the manufacturing sector. in the case of the relationship between health expenditure and growth, aboubacar and xu (2017) found that significant and positive relationship exist between health expenditure and economic growth in sub-saharan africa using generalised method of moment (gmm). likewise, piabuo and tieguhong (2017) show that a unit change in health expenditure increased gdp per capital by 0.38 for some selected african countries. in contrast, olayiwola et al. (2021) applying the wagner law indicate no causal relationship between health expenditure and gdp in nigeria. overall, the effect of oil revenue on economic growth has received much positive and significant results, while the effect of health expenditure on economic growth has largely remained mixed. 3. methodology the scope of the study covers the periods between 1981 and 2020 because of data availability that span these periods, data for this study was obtained from the central bank of nigeria (cbn) statistical bulletin, annual reports and world bank database. the variables such as oil revenue (oilr), total health expenditures (thex), and real gross domestic product (rgdp), consumer price index (cpi) and money supply (m2) were used. descriptive statistics was used to describe the variables and pair wise granger causality was used to determine the direction of causality among the variables and the statistical significance was at p ≤ 0.05 level of significance. 4. result and discussion of findings the summary statistics for the variables used in the analysis are presented in table 1. according to the table, nigeria’s rgdp average is n34690.6 billion, but it ranges from n13779.26 billion to n71387.83 billion. similarly, the average value of oil revenue (oilr) is n2430.35 billion, with a range of n7.25 billion to n8878.97 billion. similarly, the average total health expenditure (thexp) is n231.06 billion, which appears to be skewed to the right (positively skewed) when compared to the median value of n159.81 billion. there appears to be evidence of wide variability from the average value, as revealed by the standard deviation value of n132.26 billion. the consumer price index (cpi) average is n107.76, with a standard deviation of n83.34. these simply demonstrate that the variable is positively (right) skewed, albeit with a small variation. finally, the mean and median values of the money supply (m2) are 6585.141 billion and n9911.37 billion, respectively, with a standard deviation of n9911.37 billion. because of the volatility of their values over time, the oilr and m2 exhibit greater variation than other variables. the pairwise granger causality test was used to determine the direction of causality among the variables, and the results are shown in table 2. according to the findings, thexp and rgdp, m2 and thexp, and m2 and rgdp all have a bi-directional figure 1: trend of real gross domestic product, oil revenue and total health expenditure. source: central bank of nigeria and world bank development indicators awoyemi and nwibe: a causal assessment of nigeria’s crude oil revenue, health expenditure, and economic growth international journal of energy economics and policy | vol 12 • issue 5 • 2022 423 relationship, according to the findings. however, there is a one-way relationship between oilr and rgdp, thexp and oilr, and cpi and thexp, but no causal relationship between cpi and oilr or m2 and cpi. according to the table, rgdp granger causes oilr, thexp, and m2. similarly, oilr granger causes rgdp, thexp, and m2, while thexp granger causes rgdp, oilr, and m2. the findings of this study are consistent with the theoretical propositions of both wagner law and the keynesian view, as health expenditure granger causes economic growth and growth granger causes health expenditure in nigeria. according to ampah and kotosz (2016), the wagner law views domestic economic growth as a critical component that leads to increased government spending. according to keynes, an increase in government spending is likely to increase employment and investment through multiplier effects on aggregate income. according to anyanwu and erihijakpor (2009), adequate and effective healthcare spending is widely regarded as critical to boosting economic growth by improving health outcomes. according to aboubacar and xu (2017), piabuo and tieguhong (2017), there is a positive relationship between health spending and economic growth in sub-saharan africa. furthermore, akinleye et al. (2021), aminu and raifu (2019), and aregbeyen and kolawole (2015) found that oil revenue influences government spending and economic growth in nigeria. thus, improved economic growth and increased health spending are linked to increased government revenue from oil in nigeria. 5. conclusion and recommendations this study investigates the relationship between oil revenue, health expenditure, and economic growth in nigeria. in view of the finding, this study concludes that there is a bi-directional relationship between total health expenditure and economic growth, while there is a unidirectional relationship that runs from oil revenue to economic growth and health expenditure. based on these findings, there is a need for the government to develop appropriate policies that would result in better and more prudent use of oil revenue to boost nigerian economic growth. to ensure that funds are properly channelled for economic growth, all loopholes in oil revenue generation should be closed. over the years, a reasonable proportion of the budget has not been allocated to the health sector. there is a need for an increase in government spending on health at all levels (primary, secondary and tertiary institution). this will make government health expenditure to have a robust effect on nigerian health status and meet who recommended budgetary allocation to the sector. the government should increase and restructure the public expenditure allocation to the health sector in order to provide more health facilities, such as drugs, laboratories, equipment, amongst other thing. increasing government allocation and restructuring public expenditure on health could overall improve general health outcomes in nigeria and also improve the nation economic growth. references abdul-rahamoh, o.a., taiwo, f.h., adejare, a.t. (2017), analysis of the effect of petroleum tax on nigeria economy. asia journal of humanities and social sciences, 1(1),1-12. abimbola, w.o., onazi, a.a. (2018), an investigation into the nexus between oil revenue and economic growth in nigeria. international journal of business and managerial studies, 7(2), 597-606. aboubacar, b., xu, d. (2017), the impact of health expenditure on the economic growth in sub-saharan africa. theoretical economics letters, 7(3), 615-622. akinleye, g.t., olowookere, j.k., fajuyagbe, s.b. (2021), the impact of oil revenue on economic growth in nigeria (1981-2018). acta universitatis danubius. economica,17(3), 1-10. akinlo, a.e. (2012), how important is oil in nigeria’s economic growth? journal of sustainable development, 5, 165-179. aminu, a., raifu, i.a. (2019), dynamic nexus between oil revenues and economic growth in nigeria. economics bulletin, 39(2), 1556-1570. ampah, i.k., kotosz, b. (2016), wagner versus keynes: the causal nexus between government expenditures and economic growth: an table 2: granger causality test null hypothesis: obs f-statistic prob. oilr does not granger cause rgdp 37 4.46520 0.0195** rgdp does not granger cause oilr 37 2.12048 0.1365 thexp does not granger cause rgdp 37 3.73558 0.0348** rgdp does not granger cause thexp 37 7.30962 0.0024*** cpi does not granger cause rgdp 23 1.67976 0.2144 rgdp does not granger cause cpi 23 0.49819 0.6158 m2 does not granger cause rgdp 37 6.18712 0.0053*** rgdp does not granger cause m2 37 8.79816 0.0009*** thexp does not granger cause oilr 37 0.26617 0.768 oilr does not granger cause thexp 37 7.18781 0.0026*** cpi does not granger cause oilr 23 0.54492 0.5892 oilr does not granger cause cpi 37 2.13143 0.1476 m2 does not granger cause oilr 37 0.24197 0.7865 oilr does not granger cause m2 37 3.93925 0.0296** cpi does not granger cause thexp 23 1.29154 0.2991 thexp does not granger cause cpi 23 2.93223 0.079* m2 does not granger cause thexp 37 5.57716 0.0084*** thexp does not granger cause m2 37 3.51087 0.0418** m2 does not granger cause cpi 23 2.14405 0.1461 cpi does not granger cause m2 23 2.31362 0.1276 source: author’s computation based on the data from the cbn and world bank (2022). ***, ** and * correspond with 1%, 5% and 10% levels of significance respectively. table 1: summary statistics variable obs. mean sd median maximum minimum rgdp 39 34690.67 20237.78 23688.28 71387.83 13779.26 oilr 39 2430.35 2723.42 1230.85 8878.97 7.25 thexp 39 231.06 132.26 159.81 484.34 110.70 cpi 25 107.76 83.34 77.93 307.47 20.96 m2 39 6585.14 9911.37 878.46 34251.70 14.47 source: author’s computation based on the data from the cbn and world bank (2022) awoyemi and nwibe: a causal assessment of nigeria’s crude oil revenue, health expenditure, and economic growth international journal of energy economics and policy | vol 12 • issue 5 • 2022424 empirical study of burkina faso. journal of heterodox economics, 3(2), 74-101. anyanwu, j.c., erihijakpor, a.e.o. (2009), health expenditure and health outcomes in africa. african development review, 21(2), 400-433. aregbeyen, o., kolawole, b.o. (2015), oil revenue, public spending and economic growth relationships in nigeria. journal of sustainable development, 8(3), 113-126. baghebo, m. (2018), petroleum and energy economics. bayelsa: kadmon printing press and publishing house. central bank of nigeria. (2018), central bank of nigeria annual report. nigeria: central bank of nigeria. available from: https://www.cbn. gov.ng/out/2019/rsd/2018%20ar%20kama1.pdf central bank of nigeria. (2019), nigeria: central bank of nigeria. available from: https://www.cbn.gov.ng/out/2020/rsd/cbn%20 2019%20annual%20report-final.pdf chude, d.i., chude, n.p. (2017), impact of company income taxation on the profitability of companies in nigeria: a study of nigerian breweries. european journal of accounting auditing and finance research, 3(8), 1-11 gopar, j.k., dalyop, l.m., yusuf, b.d. (2017), impact of petroleum profits tax on economic growth in nigeria: a longitudinal study. tax academy research journal, 1(1), 139-150. kjell, l., petter, o. (2011), petroleum taxation: experience and issues. european journal of social sciences, 16(41), 2-6. musgrave, r.a., musgrave, b. (1988), public finance in theory and practice. new york: mcgraw-hill book company. odularu, o.g. (2018), crude oil and the nigerian economic performance. oil and gas business journal, 12(18), 22-32. okoye, l.u., omankhanlen, a.e., okoh, j.i., urhie, e., ahmed, a. (2019), government expenditure and economic growth: the case of nigeria. in: proceedings of socioint. p1184-1194. olatunji, t.e., adegbite, t.a. (2014), the effects of petroleum profit tax, interest rate and money supply on nigerian economy. global journal of commerce and management perspective, 3(3), 81-87. olayiwola, s.o., bakare-aremu, t.a., abiodun, s.o. (2021), public health expenditure and economic growth in nigeria: testing of wagner’s hypothesis. african journal of economic review, 9(2), 130-150. onaolapo, a.a., fasina, h.t., adegbite, t.a. (2013), the analysis of the effect of petroleum profit tax on nigerian economy. asian journal of humanities and social sciences, 1(1), 1-10. oni, l.b. (2014), analysis of the growth impact of health expenditure in nigeria. iosr journal of economics and finance, 3(1), 77-84. piabuo, s.m., tieguhong, j.c. (2017), health expenditure and economic growth-a review of the literature and an analysis between the economic community for central african states (cemac) and selected african countries. health economics review, 7(1), 23. thabane, k., lebina, s. (2016), economic growth and government spending nexus: empirical evidence from lesotho. african journal of economic review, 4(1), 86-100. unicef. (2021), new york: united nations children’s fund. available from: https://www.data.unicef.org/topic/maternal-health/maternal-mortality wagner, a. (1958), three extracts on public finance. in: classics in the theory of public finance. london: palgrave macmillan. p1-15. wdi. (2021), world development indicators. available from: https:// www.databank.worldbank.org/source/world-developmentindicators#selecteddimension_wdi_series world health organization. (2016), world health statistics. geneva: world health organization. wu, s.y., tang, j.h., lin, e.s. (2010), the impact of government expenditure on economic growth: how sensitive to the level of development? journal of policy modeling, 32(6), 804-817. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(5), 600-608. international journal of energy economics and policy | vol 11 • issue 5 • 2021600 indicators of environmental and economic problems priority arising from energy use in food manufacturing sector in realizing sustainable development policy under thai environmental law framework pruethsan sutthichaimethee1*, danupon ariyasajjakorn1, apinyar chatchorfa2, boonton dockthaisong2, sthianrapab naluang3, sirapatsorn wongthongdee4, nachatchaya thongjan3 1faculty of economics, chulalongkorn university, wang mai, khet pathum wan, bangkok 10330, thailand, 2department of political sciences, faculty of social sciences, mahachulalongkornrajavidyalaya university, phahon yothin road, kilometer 55 lam sai, wang noi, phra nakhon si ayutthaya 13170, thailand, 3school of law, assumption university, 592/3 ramkhamhaeng 24, hua mak, bangkok 10240; thailand, 4faculty of public administration, dhurakij pundit university, 110/1-4 prachachuen road, laksi district, bangkok, thailand. *email: pruethsan.s@chula.ac.th received: 15 april 2021 accepted: 27 july 2021 doi: https://doi.org/10.32479/ijeep.11515 abstract this research was conducted to examine the true benefit of energy consumption within the scope of energy cost, as well as model a forecasting tool for energy cost in food manufacturing industry. it was limited to the analysis of true benefit of the consumption, energy cost, forward-and-backward relationship, and prediction of future energy cost during the next 10 years ranging from 2021 to 2030, and 20 years ranging from 2021 to 2040. the analysis was made possible via an application of arimax model optimizing the input-output table of thailand. as for the result, it reveals that the product of tobacco is found with the highest true value of benefit. while candy and sweets, sugar, breweries, corn, distilled spirit, slaughtering, milled rice, coffee and tea, and canned meat are respectively detected. in taking forward-and-backward relationship into account, a close monitoring is required for the sector of canned meat and milled rice, respectively. since the developed model is confirmed for its validity, an optimization of rmse, mae, and mape measurement for 10 years (2021-2030) and 20 years (2021-2040) prediction of energy cost would result in the following outcomes; (1) a gradual increase of 41.86 percent is estimated for the energy cost by 2030 compared to 2021 per illustration in model 1, and (2) energy cost is calculated at a steadily increased 70.79% by 2040 in comparison with 2021 per presentation in model 2. keywords: economic problem, environmental law, sustainability, food manufacturing sector, energy cost jel classifications: p28, q42, q43, q47, q48 1. introduction global warming is one of many global concerns contributing negative effect and challenges to the world. since mid-century to date, a rise of average temperature has been observed by the intergovernmental panel on climate change or known as ipcc (the world bank: energy use (kg of oil equivalent per capita) home page, 2021; office of the national economic and social development council: nesdc, 2021; national statistic office ministry of information and communication technology, 2021). human activities are among many key causes sparking tenses in greenhouse gas (ghg) effect (nesdc, 2021). during 21st century (2001-2100), an increase of 1.1 up to 6.4 degree celsius of average temperature surface is estimated to happen. in most cases, this journal is licensed under a creative commons attribution 4.0 international license sutthichaimethee, et al.: indicators of environmental and economic problems priority arising from energy use in food manufacturing sector in realizing sustainable development policy under thai environmental law framework international journal of energy economics and policy | vol 11 • issue 5 • 2021 601 developed country annex 1 group has the ability to reduce such a challenge (department of alternative energy development and efficiency, 2021; thailand greenhouse gas management organization (public organization), 2021). unfortunately, it is not the case for developing countries, including thailand and most countries in asean community, in coping and dealing with the issue (nesdc, 2021; united nations framework convention on climate change, unfccc, bonn, germany, 2016). thailand has rapidly and continuously developed proper economic system while ghg emission is found to increase day by day at the same time (nesdc, 2021; pollution control department ministry of natural resources and environment. enhancement and conservation of national environmental quality act, b.e. 2535, 2021); pollution control department ministry of natural resources and environment. navigation of thai waterways act, b.e. 2546, 2021; pollution control department ministry of natural resources and environment. principle 4: in order to achieve sustainable development, environmental protection shall constitute an integral part of the development process and cannot be considered in isolation from it, 2021). the data retrieved from the office of natural resources and environmental policy and planning presents the release of real ghg emission at 379.61 mtco2e in 2020 (pollution control department ministry of natural resources and environment. principle 4: in order to achieve sustainable development, environmental protection shall constitute an integral part of the development process and cannot be considered in isolation from it, 2021). the energy consumption sector was found as the major contributor to this emission discharging about 272.49 mtco2e or 75.15 percent of entire greenhouse gas in thailand. in comparison to the year 2000, the emission growth is progressed more than 65% as illustration in figure 1 (department of alternative energy development and efficiency, 2021; thailand greenhouse gas management organization (public organization), 2021). with the information given, it implies that our world is gradually falling to a warmer state (thailand greenhouse gas management organization (public organization), 2021). the later consequence due to climate change leads to various massive natural disasters, including floods, droughts, and many more. these events have a direct impact on consumers in relation to food security. eventually, it causes economic growth to shrink (nesdc, 2021). thailand has made a number of drafting laying out plans and policies designed to improve manufacturing structure and business productivity. unfortunately, energy plans and policies are observed incomplete and interrupted. thailand needs energy input-output analysis (ioa) by acquiring most recent data and energy input-output information. in addition to this analysis, a forecasting model is required to predict greenhouse gas emission in energy consumption, and it must be fit and valid in order to manage and administer energy and environment for a better sustainability. thus, this research is developed to explain the development of prediction model for optimal national use in energy sector. the research extends on arima model integrating exogenous x variable. the analyses are systematically carried out in line with research methodology and statistical procedure in order to obtain research results with least residuals. the research also depicts no studies focusing on a forecasting model development with an integration of exogenous variables and the aforementioned model. hence, this research is believed beneficial and practical for policy and plan formulation, and expected to benefit other countries as well. 2. materials and methods 2.1. arima model the model arima comprises of three core components: auto regressive (ar), integrated (i), and moving average (ma). these components can be explained and detailed out below (zhang and broadstock, 2016; zhang and xu, 2012). 1. auto regressive (ar) is composed of general characteristics of order p are as shown below yt=α+β1yt–1+β2yt–2+…+βpyt–p+εt (1) where; β1…βp are parameters; α is a content, εt is the random variable (white noise) (yalta and cakar, 2012) 2. integrated (i) means to retrieve the difference of variables. since the arima is non-stationary, it is essential to define the differences of order p so that stationary data can be obtained from non-stationary data (zhang and lin, 2012; lu, 2017) 3. moving average (ma) is to estimate the error term from forecasting by the differences in actual variables (y actual) with dependent variables (y forecast) or εt =yat–yft with prediction of needed variables in the future as formulated below (xu et al., 2014; ren et al., 2014). yt=δ+εt–y1εt–1–y2εt–2–…–yqεt–q (2) where moving average of order q or ma(q) by q indicates the last order of error value applied. the model development form of arima can be explained as arima (p,d,q). that is order of ar=p, i=d, and ma=q, respectively. 2.2. arimax model the arimax model is a newly-introduced model developed from arima model. when ghg emission is given to be dependent variable, various factors consisting of population, co2, ch4, and energy, 79.15%, 79% waste, 1.03%, 1% afolu, 13.06%, 13% ippu, 6.76%, 7% emission in 2020 by energy sector (%) energy waste afolu ippu figure 1: ratios of greenhouse gas discharged in thailand given by different sectors as of 2020 sutthichaimethee, et al.: indicators of environmental and economic problems priority arising from energy use in food manufacturing sector in realizing sustainable development policy under thai environmental law framework international journal of energy economics and policy | vol 11 • issue 5 • 2021602 n2o emission becomes independent variables (dai et al., 2018; liu, 2019). in fact, the arimax model is expected to provide accurate and effective outcomes in the event of predicting future ghg emission due to following details (ma, 2018). 2.2.1. steps for modeling and forecasting 1. analyze the data for stationary property by testing the unit root guided by augment dickey and fuller theory stationary stochastic process also known as stationary in short is time series data which presents together mean or expected value, constant overtime, variance, and covariance (qin et al., 2019). this type of data does not lie within time but distance or lag. by assuming yt as stochastic time series and stationary in the same time, three key properties must exist, and they can be expressed below (dickey and fuller, 1981; mackinnon, 1991). eyt=eyt+k=µ (3) var(yt)=e(yt–µ) 2=e(yt–k–µ) 2=σ2 (4) e(yt–µ)(yt+k–µ)=γk (5) upon observing equation (3), (4), and (5), γk is seen as covariance between yt and yt+k, where distance exists between two values of y. however, probability distribution remains unchanged but not expected value and constant variance due to εt lacks of property of white noise (johansen and juselius, 1990; johansen, 1995). under this phenomenon, autocorrelation is detected with high correlations or higher order autoregressive process. therefore, a test of augmented dickey fuller (adf) form is required (enders, 2010; harvey, 1989). this requirement is due to its addition of lagged variables at a higher level so that autocorrelation of residual, heteroskedasticity, and multicollinearity, can be eliminated as per discussion below (sims, 1980). � � �y y yt t i p i t i t� � � � � �� � �1 2 1 (6) � � �y y yt t i p i t i t� � � �� � � �� � � �1 1 1 2 1 (7) � � �y t y yt t i p i t i t� � � � �� � � �� � � � �1 2 1 2 1 (8) with the above equations, the p value is explained to be lagged value of first difference variable, and that can be tested by using unit root testing with the augmented dickey fuller method. the later equation can be written as follows (byrne, 2009; sutthichaimethee, 2018). � � �y t y yt t i p i t i t� � � � �� � � �� � � � �1 2 1 2 1 (9) the equation (9) lays out a fact that three key issues are considered, particularly autocorrelation of εt is set to experience white noise. when a tau-statistic of the co-efficient δ is found in the absolute term, more critical values are expected to list in the adf table. however, this expectation fails to hold in core hypotheses. yet, this fact implies that time series variables are stationary explaining ∆yt integrated number d is represented by ∆yt∼ i(d) (sutthichaimethee, 2016; 2017). 2. analyze all the stationary data at the same level both dependent variables and independent variables (at level of 1st moment and/or 2nd moment only) for the long-term relationship or examine co-integration when variables of the model are relevant in the long term but the same level (sutthichaimethee and ariyasajjakorn, 2017). in order to ensure the best model in property, vector error-correction model (ecm) must be applied (sutthichaimethee and ariyasajjakorn, 2018) as for this research, the co-integrated relationship is presented based on the full information maximum likelihood (fiml) approach as introduced by johansen and juselius (1990) due to the followings. 3. the model is applicable to apply with two variables or more 4. number of co-integrated vectors can be examined without a need of variables specification whether they are exogenous or endogenous. according to johansen and juselius method, it lies within the form of multivariate co-integration by denoting to vector autoregressive (var) model, and that can be exchanged below (sutthichaimethee and ariyasajjakorn, 2017; sutthichaimethee and dockthaisong, 2018) � � � � � �x x x x ut i k i t t t k t� � � � � � � �� 1 1 1 , (10) from johansen and juselius approach point of view, it is interested to seek co-integrating vectors of variables xt in var model. it is also essential to get the right lag to activate the var model by considering the likelihood ratio test of sims (1980) or the minimum final prediction error test akaike approach. the test is composed with the following stages (sutthichaimethee and kubaha, 2018). • prepare a needed equation for testing based on vector autoregressive model (var) • conduct the test to obtain numbers of lag fitting for the above equation • compute co-integrating vectors between model variables and retrieve a metric π rank, in which it is independent of π equal to rows or columns • apply two statistical testing tools to obtain numbers of co-integrating vectors (r) inside the model, and they can trace test and maximum eigenvalue test, for instance. the both tools often function simultaneously to determine result accuracy (sutthichaimethee et al., 2019) • estimating the best model: true impact of independent variables on dependent variable must be detected. this impact can be observed tau-statistic values with different significance level of 5%, 10%, and 15% • testing the best model for three core issues as follows • autocorrelation is tested by deploying lagrangian multiplier test or known as lm test (valipour et al., 2019; pacheco, 2013). sutthichaimethee, et al.: indicators of environmental and economic problems priority arising from energy use in food manufacturing sector in realizing sustainable development policy under thai environmental law framework international journal of energy economics and policy | vol 11 • issue 5 • 2021 603 the lm test can be taken when lagged dependent variables in an equation become independent variables. in fact, the lm test can be used to detect error terms in relation to autocorrelation in high level. the following equation presents the test’s method yt=α0+α1xt+β1ut–1+β2ut–2+…+βput–p (11) process the equation yt=α1xt+ut to obtain residual; major hypothesis can be h1:β1=β2=…=βp=0 and the statistical test is expressed as nr2∼χ2p, while f-test= n k m r� � � 2 2 1( r ) if χ2p and fm,n-k – test statistic is found greater than critical χ 2 value and f critical value at a selected level of significance, it means that the major hypothesis is rejected, and at least one β has a value difference from 0, presenting autocorrelation problem in the model (sutthichaimethee, 2017). • heteroskedasticity is tested by applying arch test. the arch testing is taken to examine heteroskedasticity in time series data. when the residual is observed, lagged variables of the residual is evaluated by accounting f and nr2 value with chi-square distribution. if the χ2p statistical test value is greater than critical value of χ2p at a chosen significance level, that means the hypothesis is rejected due to the presence of heteroskedasticity problem (sutthichaimethee, 2018) • multicollinearity is tested by deploying correlation test as to check on responses from the correlogram value in comparison to chi-square value (sutthichaimethee, 2016). 2.3. measurement of the forecasting performance accuracy checking is assessed to see prediction capability. this forecasting accuracy is evaluated by comparing three different evaluation statistics, namely root mean square error (rmse), mean absolute (mae), and mean absolute percentage error (mape). these statistics are written as follows (enders, 2010; harvey, 1989): rmse = ( ) /f a ni i i n � � � 2 1 (12) mae = f a ni i i n � � � 1 / (13) mape = f a a ni i i i n �� � � � � / / 1 100 (14) from the above equations, fi and ai are the forecasted value and actual value, respectively, while n is the total number of forecasting. as for this research, it aims to retrieve results with the least error, and that reason accounts models with mape values of less than 30%. the expansion of the ghg emission model developed in this research is made possible with the use of the arimax model as per illustration below (sutthichaimethee, 2018). where ghgt represents greenhouse gas at time t, ghgt–i denotes dependent variables in the duration t–i, populationt–i expresses of population number, techt–i denotes technology, (co2)t–i in the duration t–i, refers to carbon dioxide, (ch4)t–i represents methane in the duration t–i, (n2o)t–i signifies nitrous oxide in the duration t–i , ecm embodies error correction model, mai refers to moving average at time i, εt signifies residual at time i, ∆ refers to first difference operator, and ln is explained as natural logarithm. 3. empirical analysis 3.1. indicator analysis findings on environmental and economic problems priority arising from energy use cost in food manufacturing sector the results of the real benefit, energy costs, forward linkage and backward linkage are classified by each category of the production. this research can be summarized as following: table 1 lists the top ten food manufacturing sectors in terms of forward linkage, backward linkage real benefit, and energy cost. in this study, “forward linkage” presents the relationships among each production line. it can show where input are sent from. it also signifies that the higher level of the forward linkage, the higher relationships among the involved sectors. real benefit is the revenue for a sector, minus the environmental costs. the average real benefit was 0.96. if the real benefit for a given industry is lower than the average, it can be considered to represent a loss, while values higher than the average represent profit. besides, table 1 has further explained the analysis outcome by highlighting key features as follows: 3.1.1. highlights from the findings include the following 1. the highest real benefit in the food manufacturing sectors was tobacco products, while the lowest real benefit was canning and preserving of meat. the lowest real benefit could signify loss in profit (figure 2) 2. the highest forward linkage in the food manufacturing sectors was for canning and preserving of meat, while the lowest forward linkage was rice milling 3. the highest backward linkage in the food manufacturing sectors was for ice, while the lowest forward linkage was canning and preserving of meat. analyzing the indicator of environmental impacts from the food manufacturing sectors of thailand. the average carrying capacity value for energy cost was 0.071, if the cost for a particular industry � � �ln( ) ln( ) lnghg ghg populationt i t i i n i t i i n � � � �� � � � � �� � � � 1 1 2 1 33 1 4 2 1 5 4 1 i t i i n i t i i n i t i i tech co ch � � � ln( ) ln( ) ln( ) � � � � � � � �� �� � nn i t i i n i i m t n o ma ecm � � � � � � � � � � � � � � 5 2 1 6 1 7 �ln( ) sutthichaimethee, et al.: indicators of environmental and economic problems priority arising from energy use in food manufacturing sector in realizing sustainable development policy under thai environmental law framework international journal of energy economics and policy | vol 11 • issue 5 • 2021604 is lower than the average carrying capacity value, there is further capacity for production. environmental cost values that are higher than the average carrying capacity value signify that there is no further capacity for production. 3.1.2. highlights from the findings include the following the food manufacturing sectors with the highest environmental cost in terms of energy cost was ice. the cost indicator was above the average carrying capacity value, signifying that this sector does not have capacity for further production (figure 3). 3.2. formation of analysis modeling with the arimax model the results of the forecasting model of energy costs is classified by each category of the production. this research can be summarized as following: 1. unit root test: with the augmented dickey-fuller test is shown in table 2 table 2: the adf test statistic at level of all variables has a variable unit root component or non stationary i.e. the value table 1: indicator of environmental and economic problems priority arising from the use of energy cost in food manufacturing sectors forward linkage backward linkage real benefit energy cost value sectors value sectors value sectors value sectors 0.7855 canning and preserving of meat 0.6576 ice 0.9212 tobacco products 0.4893 ice 0.7607 monosodium glutamate g 0.6117 monosodium glutamate 0.8053 confectionery 0.1569 monosodium glutamate 0.7292 tapioca milling 0.5119 tapioca milling 0.7931 sugar 0.1444 tapioca milling 0.7213 coconut and palm oil 0.3958 coconut and palm oil 0.7712 breweries 0.1436 coconut and palm oil 0.6853 noodles and similar products 0.3796 dairy products 0.7490 grinding of maize 0.1297 noodles and similar products 0.6827 coffee and tea 0.3664 animal oil, animal fat, vegetable oil and byproducts 0.7433 distilling and spirits blending 0.1207 confectionery 0.6460 slaughtering 0.3231 canning and preservation of fish and other sea foods 0.7413 slaughtering 0.1184 canning and preserving of meat 0.6392 grinding of maize 0.3098 canning and preservation of fruit and vegetables 0.7219 rice milling 0.1173 sugar 0.6332 confectionery 0.3025 grinding of maize 0.7065 coffee and tea 0.1138 canning and preservation of fruit and vegetables 0.6308 rice milling 0.3019 canning and preserving of meat 0.6996 canning and preserving of meat 0.1107 canning and preservation of fish and other sea foods 0 0.2 0.4 0.6 0.8 1 1.2 to ba cc o pr od uc ts c on fe ct io ne ry s ug ar b re w er ie s g rin di ng o f m ai ze d is til lin g an d sp iri ts bl en di ng s la ug ht er in g r ic e m ill in g c of fe e an d te a c an ni ng a nd p re se rv in g of m ea ta ve ra ge c ar ry in g ca pa ci ty v al ue sectors average carrying capacity value real benefit linear (average carrying capacity value) figure 2: real benefit sutthichaimethee, et al.: indicators of environmental and economic problems priority arising from energy use in food manufacturing sector in realizing sustainable development policy under thai environmental law framework international journal of energy economics and policy | vol 11 • issue 5 • 2021 605 calculated from the adf, all lower than the critical value. from the table at the significance level of 1%, 5% and 10%, so that it must be to qualify as stationary by the difference moment. this research found that all variables stationary at the first differencing included energy consumption (ec), population (population), technology (tech), and gdp per capita (gdp). the value of the test based on the “tau-test” is greater than the all “tau-critical” at the first difference, results in table 3. 2. result of the co-integration test the result in table 4 brings all variables are stationary at the first difference to test co-integration by using the method of “jansen juselius” shown in table 3. table 3 as the results, “co-integration test” showed that model is a co-integration because of the trace test is 178.28, which is higher than the critical value at significance level of 1% and 5%, the maximum eigen value test at 127.75 which is higher than the critical value significance level of 1% and 5%. 3. the result of arimax model 1. arimax model 1 (2,1,1) ∆in(ec)t=–0.031+2.61∆in(ec)*t–1+2.95∆in(ec)*t–2+4.16∆in (population)**t–1–7.12 ∆in(tech)**t–1+5.78∆in(gdp)**t–2+2.02 ma*1+5.23ecm*** where ** is significance α = 0.01, * is significance α = 0.05, r-squared is 0.95, adjusted r-squared is 0.93, durbin-watson stat is 2.02, f-statistic is 154.75 (probability is 0.00), arch-test is 43.05 (probability is 0.11), lm – test is 1.63 (probability is 0.10) and response test (χ2>critical) is significance. 2. arimax model 1 (2,1,2) ∆in(ec)t=–0.073+4.12∆in(ec)**t–1+3.78∆in(ec)**t–2+6.53∆in (population)**t–1–6.97 ∆in(tech)**t–1+5.05∆in(gdp)**t–1+2.12 ma*1+2.78ma**1+2.10ecm* where ** is significance α = 0.01, * is significance α = 0.05, r-squared is 0.92, adjusted r-squared is 0.89, durbin-watson stat is 2.17, f-statistic is 165.05 (probability is 0.00), arch-test is 33.05 (probability is 0.12), lm – test is 2.71 (probability is 0.11) and response test (χ2>critical) is significance. 3.3. the results of forecasting model when the modeling arimax model 1 (2,1,1) and arimax model 2 (2,1,2), which is the best model that was used to predict 2 models. the first, 10 years forecast (year 2021-2030), the second, 20 years forecast (2021-2040) the forecast results shown in figures 4 and 5. the results forecasts found that the model 1 (year 2021-2030) energy cost volume increased steadily and average rising up to 41.86% in 2030, and the model 2 (year 2021-2040) energy cost volume increased steadily as well and average rising to 70.79% in 2040. however, that model 1 and model 2 were tested the effectiveness of the model compared with actual value found that both models are highly effective with the low deviation can be used to decision making that shown in table 5. this study, the first of its kind in thailand, creates the forecasting model of energy cost using arimax model and from review of literature of many of sources such as qin et al. (2019) constructed autoregressive (ar) model and long short-term memory (lstm) model in python language based on the tensorflow framework aimed at simulating and predicting the hydrological time series. as of their study’s result, the feasibility of the models is captured for the prediction of the hydrological time series. mosavi et al. (2018) revisited the existing literature and studies to illustrate the state of the art of machine learning (ml) models in flood prediction and to investigate the most suitable models. by taking ml models as a benchmark, hybridization, data decomposition, 0 0.1 0.2 0.3 0.4 0.5 0.6 ic e m on os od iu m g lu ta m at e t ap io ca m ill in g c oc on ut a nd p al m o il n oo dl es a nd s im ila r pr od uc ts c on fe ct io ne ry c an ni ng a nd p re se rv in g of m ea t s ug ar c an ni ng a nd p re se rv at io n of fr ui t a nd v eg et ab le s c an ni ng a nd p re se rv at io n of fi sh a nd o th er s ea fo od s av er ag e ca rr yi ng c ap ac ity v al ue sectors average carrying capacity value energy cost linear (average carrying capacity value) figure 3: energy cost table 2: unit root test at level variables lag adf test mackinnon critical value status 1% 5% 10% in(ec) 1 –2.71 –4.31 –3.45 –3.25 i(0) in(population) 1 –2.47 –4.31 –3.45 –3.25 i(0) in(tech) 1 –3.08 –4.31 –3.45 –3.25 i(0) in(gdp) 1 –2.74 –4.31 –3.45 –3.25 i(0) table 3: co-integration test by johansen juselius variables hypothesized no. of ce(s) trace statistic test mackinnon critical value max-eigen statistic test mackinnon critical value status 1% 5% 1% 5% ∆in(ec), ∆in(population), ∆in(tech), ∆in(gdp) none** 178.25 21.16 15.41 127.75 17.78 15.21 i(1) at most 1** 70.05 4.75 3.25 78.03 4.75 3.25 i(1) sutthichaimethee, et al.: indicators of environmental and economic problems priority arising from energy use in food manufacturing sector in realizing sustainable development policy under thai environmental law framework international journal of energy economics and policy | vol 11 • issue 5 • 2021606 algorithm ensemble, and model optimization are found as the most effective strategies in improving the quality of the flood prediction models. while lohani et al. (2014) proposed peak percent threshold statistic (ppts) as a new model performance criterion to examine the performance of a flood forecasting model using hourly rainfall and discharge data as a sample. they also compared the result of the proposed model with artificial neural networks (ann), self-organizing map (som) based ann model and subtractive clustering-based takagi sugeno fuzzy model (sc-t-s fuzzy model). as of their analysis, the sc-t-s fuzzy model is shown with reasonably accurate forecast coupled with sufficient lead-time. to shrestha et al. (2013) examined the quality of precipitation forecasts from four numerical weather prediction (nwp) models, namely access-g 80 km resolution, access-r 37.5 km, access-a 12 km, and access-vt 5 km, based on the australian community climate earth-system simulator (access). as part of their findings, it presents that the systematic biases in rainfall forecasts has to be removed before using the rainfall forecasts for streamflow forecasting. jabbari et al. (2020) deployed a numerical weather prediction and a rainfall-runoff model to assess the precipitation and flood forecast for the imjin river (south and north korea). as a result, they no result, they notice that the weather research and forecasting (wrf) model underestimates precipitation in point and catchment assessment. however, there has not been any study done at all. therefore, this study is a guide for the studying and applying in other countries in the future. 4. conclusion and discussion in conclusion, this research indicates that tobacco products come with the highest value of true benefit. whereas confectionery, sugar, breweries, maize, distilled spirit, slaughtering, milled rice, coffee and tea, and preserved meat, are found respectively. by taking the relationship value of forward-and-backward linkage into account, preserved meat and milled rice segments are shown 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18 20 19 20 20 20 21 20 22 20 23 20 24 20 25 20 26 20 27 20 28 20 29 20 30 pe rc en ta te o f e ne rg y co st year actual arimax model1 figure 4: forecasting from arimax model 1 (2,1,1) 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 20 00 20 02 20 04 20 06 20 08 20 10 20 12 20 14 20 16 20 18 20 20 20 22 20 24 20 26 20 28 20 30 20 32 20 34 20 36 20 38 20 40 pe rc en ta te o f e ne rg y co st year actual arimax model2 figure 5: forecasting from arimax model 2 (2,1,2) table 5: the performance monitoring of forecasting model forecast of energy cost rmse mae mape model 1: arimax model (2,1,1) (2021-2030) 0.013 0.040 1.05 model 2: arimax model (2,1,2) (2021-2040) 0.058 0.077 1.02 table 4: unit root test at the first difference variables lag adf test mackinnon critical value status 1% 5% 10% in(ec) 1 –4.37 –4.31 –3.45 –3.25 i(1) in(population) 1 –5.57 –4.31 –3.45 –3.25 i(1) in(tech) 1 –4.75 –4.31 –3.45 –3.25 i(1) in(gdp) 1 –6.47 –4.31 –3.45 –3.25 i(1) sutthichaimethee, et al.: indicators of environmental and economic problems priority arising from energy use in food manufacturing sector in realizing sustainable development policy under thai environmental law framework international journal of energy economics and policy | vol 11 • issue 5 • 2021 607 with a need of close control and administration, respectively. this research also predicts energy cost in 10 years (2021-2030) and 20 years (2021-2040) by measuring rmse, mae, and mape. the prediction results can be summarized as per presentation in two sub-models; model 1 and model 2 have been estimated with a gradual rise in energy cost by 41.86% and 70.79%, respectively. this research has made an assurance of sustainable development through policy making and planning by carefully controlling specified sectors suggested by this research finding. some sectors have been observed with higher energy cost, yet they are lower in real benefit. the sectors cover various fields across consumer production lines, including ice, monosodium glutamate, milled tapioca, palm oil and coconut, noodles and similar products, preserved food in meat, fruits, vegetables, fish and other sea foods. in the meanwhile, some sectors have also found with high value of forward-and-backward connection. this finding signifies an urgency alarm for the government and policy makers to take a serious caution and control over these sectors. in relation to the prediction of energy cost in both terms, 10 years (2021-2030) and 20 years (2021-2040), this research indicates that thailand has witnessed an increment in rates making it experience in higher energy cost as per confirmation by this study. this phenomenon implies an impact on economy and society, especially environmental damage due to higher predicted ratio than thailand’s carrying capacity to handle. with this effect, it spreads a rise of greenhouse gas worldwide. nevertheless, findings from this research can be used as a noble guideline for effective and efficient national policy and planning, enabling thailand and other countries in application to achieve sustainable development. 5. acknowledgments this research is supported by rachadapisek sompote fund for postdoctoral fellowship, chulalongkorn university. references byrne, b.m. (2009), structural equation modeling with amos: basic concepts, applications, and programming. london: routledge. dai, s., niu, d., li, y. (2018), forecasting of energy consumption in china based on ensemble empirical mode decomposition and least squares support vector machine optimized by improved shuffled frog leaping algorithm. applied sciences, 8(5), 678. department of alternative energy development and efficiency. (2021), available from: http://www.dede.go.th/ewtadmin/ewt/dede_web/ ewt_news.php?nid=47140. [last accessed on 2021 jan 20]. dickey, d.a., fuller, w.a. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica, 49, 1057-1072. enders, w. (2010), applied econometrics time series, wiley series in probability and statistics. tuscaloosa: university of alabama. harvey, a.c. (1989), forecasting, structural time series models and the kalman filter, cambridge: cambridge university press. jabbari, a., so, j.m., bae, d.h. (2020), precipitation forecast contribution assessment in the coupled meteo-hydrological models. atmosphere, 11(1), 34. johansen, s. (1995), likelihood-based inference in cointegrated vector autoregressive models. new york: oxford university press. johansen, s., juselius, k. (1990), maximum likelihood estimation and inference on cointegration with applications to the demand for money. oxford bulletin of economics and statistics, 52, 169-210. liu, x., lin, j., hu, j., lu, h., cai, j. (2019), economic transition, technology change, and energy. energies, 12(13), 2581. lohani, a.k., goel, n.k., bhatia, k.k.s. (2014). improving real time flood forecasting using fuzzy inference system. journal of hydrology, 509, 25-41. lu, w.c. (2017), electricity consumption and economic growth: evidence from 17 taiwanese industries. sustainability, 9(1), 50. ma, j., oppong, a., acheampong, k.n., abruquah, l.a. (2018), forecasting renewable energy consumption under zero assumptions. sustainability, 10(3), 576. mackinnon, j. (1991), critical values for cointegration test. in: engle, r., granger, c., editors. long-run economic relationships. oxford: oxford university press. mosavi, a., ozturk, p., chau, k.w. (2018), flood prediction using machine learning models: literature review. water, 10(11), 1536. national statistic office ministry of information and communication technology. (2021), available from: http://www.web.nso.go.th/ index.htm. [last accessed on 2021 jan 25]. nesdc. (2021), office of the national economic and social development council. available from: http://www.nesdb.go.th/ nesdb_en/more_news.php?cid=154 and filename=index. [last accessed on 2021 jan 10]. pacheco, f.a.l., fernandes, l.f.s. (2013), the multivariate statistical structure of drastic model. journal of hydrology, 476, 442-459. pollution control department ministry of natural resources and environment. (2021), enhancement and conservation of national environmental quality act, b.e. 2535. available from: http://www. pcd.go.th/info_serv/reg_envi.html. [last accessed on 2021 feb 05]. pollution control department ministry of natural resources and environment. (2021), navigation of thai waterways act, b.e. 2546. available from: http://www.pcd.go.th/info_serv/reg_envi.html. [last accessed on 2021 feb 05]. pollution control department ministry of natural resources and environment. (2021), principle 4: in order to achieve sustainable development, environmental protection shall constitute an integral part of the development process and cannot be considered in isolation from it. available from: http://www.infofile.pcd. go.th/law/environmental%20law55_1.pdf?cfid=1741861 and cftoken=32274043. [last accessed on 2021 feb 05]. qin, j., liang, j., chen, t., lei, x., kang, a. (2019), simulating and predicting of hydrological time. polish journal of environmental studies, 28(2), 795-802. ren, s., yin, h., chen, x.h. (2014), using lmdi to analyze the decoupling of carbon dioxide emissions by china’s manufacturing industry. environmental development, 9, 61-75. shrestha, d., robertson, d., wang, q.j., pagano, t.c., hapuarachchi, p. (2013), evaluation of numerical weather prediction model precipitation forecasts for short-term streamflow forecasting purpose. hydrology and earth system sciences, 17(5), 1913-1931. sims, c.a. (1980), macroeconomics and reality. econometrica, 48, 1-48. sutthichaimethee, p. (2008), forecasting economic, social and environmental growth in the sanitary and service sector based on thailand’s sustainable development policy. journal of ecological engineering, 19(1), 205-210. sutthichaimethee, p. (2016), model of environmental problems priority arising from the use of environmental and natural resources sutthichaimethee, et al.: indicators of environmental and economic problems priority arising from energy use in food manufacturing sector in realizing sustainable development policy under thai environmental law framework international journal of energy economics and policy | vol 11 • issue 5 • 2021608 in machinery sectors of thailand. environmental and climate technologies, 17(1), 18-29. sutthichaimethee, p. (2017), varimax model to forecast the emission of carbon dioxide from energy consumption in rubber and petroleum industries sectors in thailand. journal of ecological engineering, 18(3), 112-117. sutthichaimethee, p., ariyasajjakorn, d. (2017), forecasting model of ghg emission in manufacturing sectors of thailand. journal of ecological engineering, 18(1), 18-24. sutthichaimethee, p., ariyasajjakorn, d. (2017), the revised input-output table to determine total energy content and total greenhouse gas emission factors in thailand. journal of ecological engineering, 18(6), 166-170. sutthichaimethee, p., ariyasajjakorn, d. (2018), forecast of carbon dioxide emissions from energy consumption in industry sectors in thailand. environmental and climate technologies, 22(1), 107-117. sutthichaimethee, p., ariyasajjakorn, d. (2020), a forecasting model on carrying capacity for government’s controlling measure under environmental law in thailand: adapting non-recursive autoregression based on the var-x model. international journal of energy economics and policy, 10(6), 645-655. sutthichaimethee, p., chatchorfa, a., suyaprom, s. (2019), a forecasting model for economic growth and co2 emission based on industry 4.0 political policy under the government power: adapting a secondorder autoregressive-sem. journal of open innovation: technology, market, and complexity, 5, 69. sutthichaimethee, p., dockthaisong, b. (2018), a relationship of causal factors in the economic, social, and environmental aspects affecting the implementation of sustainability policy in thailand: enriching the path analysis based on a gmm model. resources, 7(4), 87. sutthichaimethee, p., kubaha, k. (2018). a relational analysis model of the causal factors influencing co2 in thailand’s industrial sector under a sustainability policy adapting the varimax-ecm model. energies, 11(7), 1704. sutthichaimethee, p., naluang, s. (2019), the efficiency of the sustainable development policy for energy consumption under environmental law in thailand: adapting the sem-varimax model. energies, 12, 3092. thailand greenhouse gas management organization. (2021). available from: http://www.tgo.or.th/2015/thai/content.php?s1=7 and s2=16 and sub3=sub3. [last accessed on 2021 feb 16]. the world bank. (2020), energy use (kg of oil equivalent per capita) home page. available from: https://www.data.worldbank.org/ indicator/eg.use.pcap.kg.oe. [last accessed on 2020 10 jan ]. united nations framework convention on climate change, unfccc, bonn, germany. (2016), global progress in environmental law. environmental policy and law, 46(1), 23-27. valipour, m., banihabib, m.e., behbahani, s.m.r. (2013), comparison of the arma, arima, and the autoregressive artificial neural network models in forecasting the monthly inflow of dez dam reservoir. journal of hydrology, 476, 433-441. xu, s.c., he, z.x., long, r.y. (2014), factors that influence carbon emissions due to energy consumption in china: decomposition analysis using lmdi. applied energy, 127(c), 182-193. yalta, a.t., cakar, h. (2012), energy consumption and economic growth in china: a reconciliation. energy policy, 41(c), 666-675. zhang, c., lin, y. (2012), panel estimation for urbanization, energy consumption and co2 emissions: a regional analysis in china. energy policy, 49(c), 488-498. zhang, c., xu, j. (2012), retesting the causality between energy consumption and gdp in china: evidence from sectoral and regional analyses using dynamic panel data. energy economics, 34(6), 1782-1789. zhang, j., broadstock, d. (2016) the causality between energy consumption and economic growth for china in a time-varying framework. the energy journal, 37(01), 29-53. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020 185 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 185-189. enterprise resource planning and firm value: case of oil and gas firm in indonesian stock exchange d. p. emrinaldi nur*, adhitya agri putra university of riau, indonesia. *email: emrinaldinur@lecturer.unri.ac.id received: 06 juıly 2020 accepted: 04 september 2020 doi: https://doi.org/10.32479/ijeep.10044 abstract since oil price crash has big impact on oil and gas firm value, it is important to implements information technology for value improvement, such as enterprise resource planning implementation. this research is aimed to examine the effect of enterprise resource planning implementation on oil and gas firm value. research sample are oil and gas firms which listed in indonesian stock exchange 2013-2018. enterprise resource planning implementation is measured by dummy variable. firm value is measured by return on assets and market to assets value. based on random effect regression analysis, enterprise resource planning implementation increases firm value. enterprise resource planning provides higher information quality, integrated relationship between firms’ functions and departments, integrated relationship between supplier and customer, also efficiency in resource usage. keyword: enterprise resource planning, firm value, indonesian stock exchange, oil and gas, return on assets, market to assets value jel classifications: m15, o33, q40 1. introduction in era of globalization, firms should be adaptive and have competitive advantage. one of factor that can help firms to be competitive is information technology that can help their business process. information technology is important to create new method for problem solving, task working, and communication management (ferrell et al., 2016). technology strategy that can be implemented specifically as business investment is enterprise resource planning. enterprise resource planning is a system to integrates information across functions in a firm (scapens and jazayeri, 2003). basically, enterprise resource planning is an automatized and integrated system (kristianti and achjari, 2017), include modules of finance, human resource and payroll, order to cash, manufacture purchase to pay, project management, customer relationship, tools system (romney and steinbart, 2018). enterprise resource planning is built because the needs of business complexity and will help management to achieve efficiency (scapens and jazayeri, 2003). some studies find the benefit of enterprise resource planning implementation for firm business. kanellou and spathis (2013) find that erp system implementation helps firm to make less costly and timely accounting process. poston and grabski (2001) find that eenterprise resource planning implementation increases employee effectivity to generate sales and reduce production cost. enterprise resource planning implementation also improves higher financial performance (such as return on investment and assets turnover) (hunton et al., 2003) and market give positive response to it (hitt et al., 2002). in case of indonesia, enterprise resource planning implementation helps firm to improve return on assets (kristianti and achjari, 2017). since enterprise resource planning implementation helps firm business in many aspects (include in operational, financial, market share aspects), it can be conclude that enterprise resource planning implementation has positive effect on firm value. in the context of finance, maximization of firm value is main objective of firm. currently, the issue of firm value declining comes from oil and gas industry. in 2014-2016, global experiences the fall of oil price this journal is licensed under a creative commons attribution 4.0 international license nur and putra: enterprise resource planning and firm value: case of oil and gas firm in indonesian stock exchange international journal of energy economics and policy | vol 10 • issue 6 • 2020186 significantly (mikhaylov, 2019), include in indonesia. in 2014, global market has been shocked with oil price crash. oil price has been decreased globally. the lowest price level is in 2016 since last 10 years. figure 1 shows the global oil price volatility in last 10 years. oil price declining surprises the oil industry. because of this phenomenon, fifteen big oil firms are bankrupt (helman, 2016). as one of oil supplier, indonesia is also get shock. linear to global oil price crash, national oil price also falls from 2014 to 2016. graphic of indonesian oil price can be seen in figure 2. the volatility of oil price can give impact to oil and gas firms and industry market value (ulusoy and özdurak, 2018). since market value is indicator of firm value (kesten, 2010), oil and gas firm value is easily fall when there is negative global issue that can make oil price decline. enterprise resource planning implementation is one way to help oil and gas firms to improve firm value. 2. literature review 2.1. enterprise resource planning the business today face the challenging environment to create competitive advantages. it is harder to beat the competitor, market pressure, and customer needs. firms are expected to reduce the costs, includes costs of supply chain, inventory, expanding and improves product quality (nawaz and channakeshavalu, 2013). firms have to upgrade their business system to generate efficient operational activities. in order to solve it, enterprise resource planning can be implemented by the firms. enterprise resource planning is a result of evolution from traditional resource planning to automated and integrated planning system. enterprise resource planning is an integrated and multi-module application which has a concept to plan and manage firm resource (pracita et al., 2018). enterprise resource planning suggests two main benefits, which are (nawaz and channakeshavalu, 2013): 1. a unified enterprise view of the business that encompasses all functions and departments. 2. an enterprise database where all business transactions are entered, recorded, processed, monitored, and reported. enterprise resource planning integrates various procedures, applications, and functions into one whole business and as database to help firm working with real-time information (kanellou and spathis, 2013). it covers wide function of daily business operation and decision making application (hitt et al., 2002). enterprise resource planning puts integration between firms departments and function in first place so the information can be accessed together (kristianti and achjari, 2017). enterprise resource planning system consists of some modules to fulfill any firm needs. the enterprise resource planning modules include in (romney and steinbart, 2018): 1. financial module, which has function to make transaction journal and reporting system between receivable, fixed assets, budgeting, cash management, and managerial and financial reporting plan. 2. human resources and payroll module, which used to manage human resource, payroll, employee benefit, training, working absence, other compensation, and reporting for stakeholders. 3. order to cash module, which used to entry the sales order, product delivery, inventory, cash inflow, and charge. 4. purchase to pay module, which related to purchasing order, purchase delivery, inventory delivery and control, inventory and warehouse management, and cash outflow. 5. manufacturing module, which used to manage production schedule, raw material and processed good factures, working path management, control, cost management, and manufacturing project and process. 6. project management (costing) module, which used to manage collection, time and expenses, working unit, and activities management 7. customer relationship management module, which related to sales and marketing, sales charge, service, customer contact, and call center support 8. system tools module, which used to make data master, determine information flow, access monitoring etc. 2.2. oil and gas sector in indonesia in indonesia, oil and gas business regulated by uud 1945 art. 33 s 3 (dwi qurbani, 2012). in 2013, indonesia is 22nd biggest crude oil and gas supplier country while in 2016, indonesia is 21st biggest crude oil and gas supplier country in the world (putri et al., 2019). there are seven locations as the biggest crude oil suppliers, which are south sumatera, riau islands, java ocean sector, riau, east java, west papua, and east kalimantan (putri et al., 2018). 2.3. hypothesis enterprise resource planning implementation focuses on integration between functions and departments of firm. enterprise resource planning also helps the firm activities to be automated 64.29 71.12 96.99 61.76 79.04 104.01 105.01 104.08 96.24 50.75 42.81 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 crude oil price (average) usd/barrel figure 1: global crude oil price source: world bank (2017) 64.27 72.31 96.13 61.58 79.4 111.55 112.73 105.85 96.51 49.21 40.13 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 indonesian crude oil price (average) usd/barrel figure 2: indonesian crude oil price source: ministry of energy and mineral resources republic of indonesia (2017) nur and putra: enterprise resource planning and firm value: case of oil and gas firm in indonesian stock exchange international journal of energy economics and policy | vol 10 • issue 6 • 2020 187 (tambovcevs and tambovceva, 2013). enterprise resource planning makes manual activities are able to be done by a system. it help firm to reduce the needs of large employees and working forces. enterprise resource planning improves firm productivity (tambovcevs and tambovceva, 2013). in the context of financial performance, hunton et al. (2003) find that firms that by implementing enterprise resource planning at least 3 years will achieve better return on assets, return on investment and assets turnover than non-adopter enterprise resource planning. in enterprise resource planning implementation, integration is important concept. enterprise resource planning can help integrates better communication between customer and supplier, so it can give positive impact to receivable and payable management (hitt et al., 2002). it helps the performance of supply chain. forslund (2010) finds that firms that implement enterprise resource planning with oracle program helps improves supply chain performance to generate revenue, further, it improves firm value. another benefit of eenterprise resource planning implementation is improvement of inventory management. enterprise resource planning system can integrates information between sales department and production department to generate better schedule and avoid idle goods in the warehouse (matolcsy et al., 2005). enterprise resource planning improves information integration to generate better information quality (elragal and al-serafi, 2011; loh et al., 2006; nicolaou, 2004). it helps manager to perform better monitoring and control function. integrated system can eliminates limitation across firms’ functions so manager can get reliable information to make best decision. an automated and integrated system like enterprise resource planning is needed by oil and gas firms. oil and gas firm is sensitive to global oil and gas industry condition. the case of oil price crash in 2014 make oil and gas firms need enterprise resource planning system to maintain cost efficiency and production management so it will not followed by firm value fall as well. ha: enterprise resource planning implementation increases oil and gas firm value. 3. research method 3.1. sample research sample are oil and gas firms listed in indonesian stock exchange 2013-2018. it easier for this research to accesses the data if firms are publicly held that listed indonesian stock exchange. firms sample can be seen in table 1. 3.2. variables dependent variable is firm value. firm value refers to shareholders’ wealth. firm value consist of accounting and market measurements. since earnings are include in shareholders’ wealth, accounting measurement is occurred by return on assets, which calculated by earnings after tax divided by total assets. returnonassets earningsaftertax total assets = (1) another shareholders’ wealth indicator is market share value, so market measurements will be occurred by market to assets value, which calculated by market capitalization divided by total assets. market toassetsvalue share price numberof outstanding share to = × � ttal assets (2) i n d e p e n d e n t v a r i a b l e i s e n t e r p r i s e r e s o u r c e p l a n n i n g implementation. it is measured by dummy variable, score 1 if firm implements enterprise resource planning, score 0 if otherwise. control variables are size, leverage, and crude oil price. size and leverage are factors to determine the firm value (muzir, 2011). the bigger the firms, the larger resource and it easier to improve firm value. the higher leverage indicates the higher firm risk so it will reduce firm value. size is measured by natural logarithm of total assets while leverage is measured by debt to total assets ratio. crude oil price is indicator of oil and gas industry in specific year. crude oil price is measured by average of national crude oil price. 3.3. analysis method hypothesis test uses regression analysis. since enterprise resource planning implementation is not easily change each year in the certain firm, this research rather use random effect regression than fixed effect regression analysis. this research also uses pooled least regression as robustness test with fulfillment of heteroscedasticity and multicollinearity assumptions. regression model is as follow. value a b erp b size b lev b price= + + + + 1 2 3 4 (3) where value is firm value, erp is enterprise resource planning implementation, size is firm size, lev is firm leverage, price is crude oil price. 4. result 4.1. descriptive statistics table 2 shows average return on assets (roa) for firms that do not implement enterprise resource planning is −0.1960. average return on assets (roa) for firms that implement enterprise resource planning is 0.0742. as expected, return on assets of firms that do not implement enterprise resource planning is lower than return table 1: research sample firms stock code apexindo pratama duta apex benakat integra bipi elnusa elsa energi mega persada enrg medco energi international medc perdana karya perkasa pkpk radiant utama interinsco ruis ratu prabu energi arti surya esa perkasa essa source: indonesian stock exchange nur and putra: enterprise resource planning and firm value: case of oil and gas firm in indonesian stock exchange international journal of energy economics and policy | vol 10 • issue 6 • 2020188 on assets or firms that implement enterprise resource planning with t-statistics value 2.246 (significant in 0.05). average market to assets value (mav) for firms that do not implement enterprise resource planning is 0.3467. average market to assets value (mav) for firms that implement enterprise resource planning is 0.6432. as expected, market to assets value of firms that do not implement enterprise resource planning is lower than return on assets or firms that implement enterprise resource planning with t-statistics value 2.280 (significant in 0.10). 4.2. hypothesis test this research uses random effect regression as hypothesis test. result of random effect regression can be seen in table 3. table 3, in return on assets model, shows that enterprise resource planning has coefficient value 0.224914 with t-statistics 1.720487 (significant in 0.10). it shows that enterprise resource planning has positive effect on return on assets. in market to assets value mode, enterprise resource planning has coefficient value 0.267078 with t-statistics 2.180103 (significant in 0.05). it shows that enterprise resource planning has positive effect on market to asset value. the result indicates that hypothesis, enterprise resource planning implementation increases oil and gas firm value, is accepted. the result is consistent with previous researches that enterprise resource planning helps firm to provide productivity improvement (tambovcevs and tambovceva, 2013) and performance improvement (hunton et al., 2003). enterprise resource planning provides automated system so efficiency will be occurred. it also produces higher financial performance. enterprise resource planning helps firm to performs better supply chain, because it provide higher information quality and integrates customer, supplier, and production well. enterprise resource planning system can integrates information between sales department and production department to generate better schedule. it helps manager to perform better monitoring and control function. integrated system can eliminates limitation across firms’ functions so manager can get reliable information to make best decision. since oil and gas firms are shocked by oil price crash, enterprise resource planning is important to be implemented by oil and gas firms to avoid performance lost, or event, avoid bankruptcy. 4.3. robustness test this research performs pooled least square as robustness test. in order to fill the pooled least square assumptions, heteroscedasticity and multicollinearity tests are examined first. result of heteroscedasticity and multicollinearity tests can be seen in table 4. table 4 shows that vif values for return on assets and market to assets value models are below 10. it indicates that there is no multicollinearity problems. in return on assets model, significance value of white test is 0.2217 (insignificant). it indicates that there is no heteroscedasticity problems for return on assets model. in market to assets value model, significance value of white test is 0.0072 (significant in 0.01). it indicates that there is heteroscedasticity problems for market to assets value model. since there is heteroscedasticity problems, market to assets value model will be examined by huber-white test with heteroscedasticity condition. result of pooled least square regression can be seen in table 5. in table 5, in return on assets model, shows that enterprise resource planning has coefficient value 0.235394 with t-statistics 1.924233 (significant in 0.10). it shows that enterprise resource planning has positive effect on return on assets. in market to assets value mode, table 4: heteroscedasticity and multicollinearity test return on assets model market to assets value model vif vif below 10 vif below 10 white test value of sig.=0.2217 value of sig.=0.0072* source: data proceed. *significant in 0.01 table 2: descriptive statistics roa mav size dar price not implement erp n 48 48 48 48 48 mean −0.0196 0.3467 12.6816 0.6578 67.9017 implement erp n 6 6 6 6 6 mean 0.0742 0.6432 12.6623 0.3954 67.9017 total n 54 54 54 54 54 mean −0.0092 0.3796 12.6794 0.6287 67.9017 t-statistics 2.246** 2.280*** 0.175 2.786* source: data proceed. *significant in 0.01, **significant in 0.05, ***significant in 0.10 table 3: random effect regression coefficient t-statistics coefficient t-statistics notes erp 0.224914 1.720487*** 0.267078 2.180103** ha is accepted size 0.053318 2.090737** 0.468493 3.93619* lev −0.266210 −3.562000* −0.840049 −3.30277* price 0.000901 2.139126** 0.002493 2.281405** constant −0.581765 6.671193 dependent variable return on assets market to asset value f-statistics 6.167622* 8.246810* adj r2 0.280580 0.353558 source: data proceed. *significant in 0.01, **significant in 0.05, ***significant in 0.10 nur and putra: enterprise resource planning and firm value: case of oil and gas firm in indonesian stock exchange international journal of energy economics and policy | vol 10 • issue 6 • 2020 189 enterprise resource planning has coefficient value 0.290977 with t-statistics 1.757908 (significant in 0.10). it shows that enterprise resource planning has positive effect on market to asset value. it indicates that pooled least regression result is consistent with random effect regression result. 5. conclusion based on analysis data, enterprise resource planning has positive effect on oil and gas firm value. enterprise resource planning provides higher information quality, integrated relationship between firms’ functions and departments, integrated relationship between supplier and customer, also efficiency in resource usage. limitation of this research is this research only occurs enterprise resource planning by seeing if firm implement occurs enterprise resource or do not implement. this research does not occurs which modules of enterprise resource planning implemented and how difficult enterprise resource planning integrated into firms’ old business system. future research expected to measures enterprise resource planning enterprise resource planning deeper so it can be occurred accurately. references dwi qurbani, i. (2012), politik hukum pengelolaan minyak dan gas bumi di indonesia. arena hukum, 5(2), 115-121. elragal, a., al-serafi, a.m. (2011), the effect of erp system implementation on business performance: an exploratory case-study. communications of the ibima, 19, 1-20. ferrell, o.c., hirt, g., ferrell, l. (2016), business: a changing world. 10th ed. new york: mcgraw-hill education. forslund, h. (2010), erp systems’ capabilities for supply chain performance management. industrial management and data systems, 110(3), 351-367. helman, c. (2016), the 15 biggest oil bankruptcies (so far). f o r b e s . av a i l a b l e f r o m : h t t p s : / / w w w. f o r b e s . c o m / s i t e s / christopherhelman/2016/05/09/the-15-biggest-oil-bankruptciesso-far/#753788077ff9. [last accessed on 2019 nov 17]. hitt, l.m., wu, d.j., zhou, x. (2002), investment in enterprise resource planning: business impact and productivity measures. journal of management information systems, 19(1), 71-98. hunton, j.e., lippincott, b., reck, j.l. (2003), enterprise resource planning systems: comparing firm performance of adopters and nonadopters. international journal of accounting information systems, 4(3), 165-184. kanellou, a., spathis, c. (2013), accounting benefits and satisfaction in an erp environment. international journal of accounting information systems, 14(3), 209-234. kesten, j. (2010), managerial entrenchment and shareholder wealth revisited: theory and evidence from a recessionary financial market. byu law review, 5(4), 1609-1660. kristianti, c.e., achjari, d. (2017), penerapan sistem enterprise resource planning: dampak terhadap kinerja keuangan perusahaan. jurnal akuntansi and auditing indonesia, 21(1), 1-11. loh, t.c., koh, s.c.l., simpson, m. (2006), an investigation of the value of becoming an extended enterprise. international journal of computer integrated manufacturing, 19(1), 49-58. matolcsy, z.p., booth, p., wieder, b. (2005), economic benefits of enterprise resource planning systems: some empirical evidence. accounting and finance, 45(3), 439-456. mikhaylov, a. (2019), oil and gas budget revenues in russia after crisis in 2015. international journal of energy economics and policy, 9(2), 375-380. ministry of energy and mineral resources republic of indonesia. (2017), handbook of energy and economic statistics of indonesia 2017. jakarta: ministry of energy and mineral resources republic of indonesia. muzir, e. (2011), triangle relationship among firm size, capital structure choice and financial performance. journal of management research, 11(2), 87-98. nawaz, m.n., channakeshavalu, k. (2013), the impact of enterprise resource planning (erp) systems implementation on business performance. asia pacific journal of research, 2(4), 30-47. nicolaou, a.i. (2004), firm performance effects in relation to the implementation and use of enterprise resource planning systems. journal of information systems, 18(2), 79-105. poston, r., grabski, s. (2001), financial impacts of enterprise resource planning implementations. international journal of accounting information systems, 2(4), 271-294. pracita, s.a., soewarno, n., isnalita, i. (2018), analisis pengaruh iimplementasi erp terhadap profitabilitas dan nilai perusahaan. jurnal akuntansi universitas jember, 16(1), 55-64. putri, d.h., anika, m., wahyuni, w. (2019), bioinformatics study genes encoding enzymes involved in the biosynthesis of carotenoids line cassava (manihot esculenta). eksakta: berkala ilmiah bidang mipa, 20(1), 10-16. putri, d.h., fifendy, m., putri, m.f. (2018), diversity of bacterial endophytes in young and old leaves of andaleh plant (morus macroura miq.). eksakta: berkala ilmiah bidang mipa, 19(1), 125-130. romney, m.b., steinbart, p.j. (2018), accounting information system. 14th ed. harlow: pearson education. scapens, r.w., jazayeri, m. (2003), erp systems and management accounting change: opportunities or impacts? a research note. european accounting review, 12(1), 201-233. tambovcevs, a., tambovceva, a. (2013), erp system implementation: benefits and economic effectiveness. island, greece: international conference on systems, control, signal processing and informatics. ulusoy, v., özdurak, c. (2018), the impact of oil price volatility to oil and gas company stock returns and emerging economies. international journal of energy economics and policy, 8(1), 144-158. world bank. (2017), world bank commodity price data (the pink sheet): annual prices, 1960 to present, nominal us dollars. united states: world bank. table 5: pooled least square regression coefficient t-statistics coefficient t-statistics notes erp 0.235394 1.924233*** 0.290977 1.757908*** result is consistent size 0.047574 2.745052* −0.04521 −1.00211 lev −0.22585 −3.94224* −0.01793 −0.04755 price 0.000943 2.063306** 0.003836 1.580693 constant −0.53834 0.671311 dependent variable return on assets market to asset value**** f-statistics 7.706216* 3.038690** adj r2 0.336046 0.051024 source: data proceed. *significant in 0.01, **significant in 0.05, ***significant in 0.10, ****huber-white with heteroscedasticity condition https://www.forbes.com/sites/christopherhelman/2016/05/09/the-15-biggest-oil-bankruptcies-so-far/#753788077ff9 https://www.forbes.com/sites/christopherhelman/2016/05/09/the-15-biggest-oil-bankruptcies-so-far/#753788077ff9 https://www.forbes.com/sites/christopherhelman/2016/05/09/the-15-biggest-oil-bankruptcies-so-far/#753788077ff9 tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 5 • 2021418 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(5), 418-424. the impact of oil price and other macroeconomic variables on the islamic and conventional stock index in indonesia muhammad syafii antonio1, aam s. rusydiana2, wahyu sugeng imam soeparno3, lina nugraha rani4*, wahyu ario pratomo3, abdillah arif nasution3 1tazkia islamic university college, jawa barat, indonesia, 2sharia economics applied research and training, indonesia, 3universitas sumatera utara, indonesia, 4faculty of economic and business, airlangga university, indonesia. *email: linanugraha@ feb.unair.ac.id received: 26 november 2020 accepted: 20 april 2021 doi: https://doi.org/10.32479/ijeep.10911 abstract the islamic capital market plays an important role in the growth of the economy in indonesia. during its development, the performance of the stock index in a country is often influenced by other stock indices in other countries. this study tries to analyze dependence of macroeconomic variable towards jii and ihsg price, using autoregression distributed lag (ardl). the results show that the consumer price index (cpi) and exchange rate (exc) significantly affect the movement of the jii and ihsg price index. this indicates that the movement of the jii and ihsg index in the short term is influenced by domestic production and exchange rate. furthermore, the results of the research show a little uniqueness in the crude oil price (cop) variable and the issue of energy consumption in the future. keywords: ardl, macroeconomic, oil price, islamic stock jel classifications: e44, f41, q43 1. introduction the presence of the islamic capital market in indonesia plays an important role in the growth of the economy in this country. in the concept of economic growth, the capital market is one indicator of the stability of macroeconomic conditions where the capital market is an alternative source of financing for companies. in its development, the capital market acts as a place to raise capital. meanwhile, from the public side, the islamic capital market acts as an investment alternative to maintain the value of their currency. the advancement of the capital market in indonesia occurs as people’s knowledge increases about how to invest optimally and is supported by domestic economic conditions. the emergence of sharia products in the capital market originated from a desire to accommodate the needs of muslims who wish to invest in sharia principles. this was the reason behind pt danareksa investment management to launch danareksa syariah on july 3, 1997. then on july 3, 2000, the indonesia stock exchange in collaboration with pt danareksa investment management launched the jakarta islamic index (jii). furthermore, islamic investment products in the capital market continued to develop with the presence of islamic bonds (sukuk), islamic mutual funds, and the sharia securities list (des) which later transformed into the indonesian sharia stock index (issi). investment in indonesia is currently experiencing a fairly good development. this is indicated by the better performance of the composite stock price index (ihsg), lq45, jakarta islamic index (jii), and the indonesian sharia stock index (issi), which represent the actual conditions of the national islamic capital market. this journal is licensed under a creative commons attribution 4.0 international license antonio, et al.: the impact of oil price and other macroeconomic variables on the islamic and conventional stock index in indonesia international journal of energy economics and policy | vol 11 • issue 5 • 2021 419 the figure 1 above explains that the existence of islamic stocks is in great demand by investors, this is reflected in the number of islamic stocks which always increase every year. furthermore, the value of islamic stock capitalization as shown by the jakarta islamic index (jii) has an increasing trend every year. this shows that the performance of the jakarta islamic index has increased quite well. the figure 2 above explains the development of the jci and jii indices from january 2010 to december 2019. from the graph above, it can be seen that the jci and jii have strong ties, which is indicated by almost the same movements, such as in the period may 2015 to september 2015 where the two indices corrected deep enough before moving to rebound in the next period, then fluctuating from march 2018 to december 2018. in its movement, the movement of the stock index almost always fluctuates. the fluctuations that occur in the stock index can be influenced by macroeconomic variables. tangjitprom (2012) explains that there are macroeconomic variables that affect the rise and fall of the stock price index, which can be grouped into four groups. the first group reflects general economic conditions such as the level of employment and the industrial production index. the second group includes variables of interest rates and monetary policy. the third group of variables focuses on the price level, which can be the general price level and the inflation rate or the price of a major asset such as the price of oil. the last group is variables involving international activities such as exchange rates and foreign direct investment. another research was conducted by valcarcel (2012) which examined the relationship between stock prices and inflation in the us. one of the macroeconomic variables that affect the rise and fall of the stock price index is the world crude oil price. crude oil is considered a source of driving force for the prosperity of the country’s economy and maintaining the operational system because every production, transportation and factory industry requires product development from crude oil to run smoothly (arouri and rault, 2012). at the end of 2019, the price of west texas intermediate (wti) crude oil was us $ 58.85 per barrel. crude oil prices are quite volatile, where the lowest point of wti crude oil prices in the 2010 to 2019 period was 30.37 in february 2016, and the highest point occurred in april 2011 at a price of 109.75 us dollars per barrel (figure 3). during this period also, there was a drastic decline in world crude oil prices from july 2014 to january 2015, where in july 2014 it was at 101.85 and continued to fall to 49.35 in january 2015. this occurred due to an abundant supply which was exacerbated by strong production. from opec and the united states. prices have been slumping especially since december 4, when the organization of the petroleum exporting countries (opec) decided to oppose production restrictions, as members struggle to maintain market share (tempo, 2016). there have been several studies regarding the correlation between crude oil prices and stock indices in the last decade. research from alzyoud et al. (2018) shows that there is no cointegration between cop, exchange rates and stock market returns. the regression analysis shows that cop and exchange rates, and their variations, have a positive and significant effect on canadian stock market returns. in addition, research from anyalechi et al. (2019) shows that changes in oil prices have a positive but insignificant impact on stock returns both in the long and short term. on the other hand, research from arouri and rault (2010) shows a negative relationship between oil prices and stock prices in the saudi arabian stock market. therefore, this study intends to evaluate the relationship between macroeconomic variables and islamic and conventional stock indices regarding whether these macroeconomic variables have a positive or negative impact on each other. 2. literature review 2.1. stock stock/shares are defined as proof or certificate of ownership of a person or entity against the company that issued the securities, which can also be interpreted as the participation of investors as investors in a company, so that they have a claim on the company’s income and assets (harsono, 2013). stocks are one of the most popular forms of investing. shares are issued by companies to raise capital. shares in the form of securities as proof of deposit of funds from investors to the company. companies that issue shares to be owned by the public are called public companies (go public). the share trading mechanism is regulated by the indonesia stock exchange (idx) under the supervision of the ojk (financial services authority). in investing, especially in stocks, there are two important things, namely the rate of return or return (return) and risk. investors generally want a maximum return with minimum risk (nastiti and suharsono, 2012). according to rivai and buchari (2013), in general, there are two categories of stocks that are generally known in stock trading, namely preferred stocks and common stocks. preferred stocks have the right to claim against the earnings and assets in the company where they invest the funds, but they cannot have voting rights in the election of directors and company decisions. and if a company goes bankrupt, preferred shareholder claims will take precedence over payments over common shareholders. meanwhile, common stock has voting rights in the election of directors and decisions relating to the company. the dividends received by owners of common shares may be greater than the owners of preferred shares. 2.2. islamic stocks sharia stocks are investment activities in the form of equity participation in companies that do not violate sharia principles in their activities (heykal, 2012). according to soemitra (2009), islamic shares are shares issued by a company that has met the following requirements: 1. the type of business, goods or services provided and the contract and management method of the company that issues shares (issuer) or public company that issues sharia shares must not be contrary to sharia principles. types of business activities that are contrary to sharia principles, among others: a. conventional financial institutions (ribawi), including conventional banking and insurance b. producers, distributors and/providers of goods or services that destroy morals and are harmful c. conducting transactions with issuers which at the time of the transaction the company’s debt level to the ribawi financial institution is more dominant than its capital antonio, et al.: the impact of oil price and other macroeconomic variables on the islamic and conventional stock index in indonesia international journal of energy economics and policy | vol 11 • issue 5 • 2021420 d. issuers or public companies that issue sharia shares are required to sign and comply with the terms of the contract in accordance with the sharia shares issued. 2. issuers or public companies that issue islamic shares are required to ensure that their business activities comply with sharia principles (fatwa dsn no. 40/2003). 2.3. stock price index the stock price index is an indicator that shows stock price movements. the index serves as a trend indicator of the stock market that describes market conditions in certain conditions, both in active and sluggish conditions, the movement of the index is an important indicator for investors to determine whether they will sell, hold or buy a certain amount of shares (rusbariand, et al. 2012). in general, almost all countries have their own stock index. there are even some countries that have more than one stock index, such as in indonesia which has the composite stock price index (ihsg), the jakarta islamic index (jii), and the indonesian sharia stock index (issi). the united states has dow jones, dow jones islamic market us (imus), and nasdaq. 2.4. composite stock price index (ihsg) the jakarta composite index or jsx composite is a type of index on the indonesia stock exchange. ihsg is to measure the performance value of all shares listed on a stock exchange by using all shares listed on the stock exchange as a component of the index calculation. jci is used to determine the development and general situation of the capital market, not the situation of a particular company. this index includes the price movements of all common shares and preferred shares listed on the idx. according to anoraga and pakarti (2001), the ihsg is an index that shows general stock price movements listed on the stock exchange, which is a reference for the development of activities in the capital market. this jci can be used to assess the general market situation or to measure whether stock prices have increased or decreased. jci also includes all share prices listed on the stock exchange. 2.5. jakarta islamic index (jii) the jakarta islamic index (jii) is one of the islamic stock indices in indonesia which is used as a measure of the performance of islamic stocks. the jakarta islamic index was introduced by the idx and danareksa investment management (dim) on july 3, 2000 which aims to provide guidance to investors who wish to invest their funds in sharia. according to hidayat (2011), shares that are included in the 30 shares of jii are stocks that meet the criteria, namely that the main type of business does not conflict with sharia principles and has been recorded for more than 3 months (unless included in the top ten capitalization), based on annual financial statements or mid-year has a maximum ratio of liabilities to assets of 90 percent, including into 60 shares of the stock composition based on the largest average market capitalization order during the past year, then entering into 30 shares in order based on the level of liquidity of the average regular trading value for one last year. 2.6. world crude oil prices price is an exchange rate that can be equated with money or other goods for the benefits obtained from a good or service for a person or group at a certain time and place. crude oil (crude oil) is a commodity and a source of energy that is needed for the growth of a country. crude oil can be processed into an energy source, such as liquified petroleum gas (lpg), gasoline, diesel, lubricating oil, fuel oil and others. the world crude oil price is measured from the spot price of the world oil market, generally used as standards are west texas intermediate and brent. the world oil traded in west texas intermediate (wti) is high quality crude oil. this type of oil is very suitable to be used as fuel, which causes the price of this oil to become the benchmark for world oil trade. 2.7. autoregressive distributed lag (ardl) this study uses an estimation method with autoregressive distributed lag (ardl) analysis. the ardl method is an econometric method that can estimate linear regression models in analyzing long-term relationships that involve cointegration tests between time series variables. the ardl method was first introduced by pesaran and shin (1999) with a cointegration test approach with bound test cointegration testing. the cointegration test in this method is carried out by comparing the f-statistic value with the f-table value compiled by pesaran and shin (1999). some of the literature regarding the cointegration test that can be used, such as johansen, engel-granger, phillips and hansen, phillips and loretan, requires the need for the estimated variables to be integrated in the same level in order i (1) or first difference. to overcome this problem, pesaran and shin (1997) developed the ardl method using bound testing cointegration. according to fosu and magnus (2006), the ardl method has several advantages compared to other econometric methods, namely: 1. the cointegration test is simpler than the johansen-juselius cointegration test. this is because the use of bound testing cointegration is sufficient to test the cointegration which is estimated using ols when the lag of the model has been identified. 2. the bounds test procedure does not require unit root testing of the variables used in the study. this cointegration test can be applied to models where all the variables are stationary at i (0), i (1), or the integration of both (pesar et al., 2001). 3. testing with ardl is relatively more efficient for small and limited data samples. estimation and identification of the ardl model can use ordinary least square (ols) if the ardl order has been determined (pesaran et al., 2001). furthermore, ols can be used if several ols assumptions that are binding on the related econometric estimates are met. an estimator that meets the best linear un] estimator (blue) is a requirement for an ols estimation model that can be used as the basis for analysis. meanwhile, some problems in violating ols assumptions include: multicollinearity problems, heteroscedasticity problems, autocorrelation, and errors in functional specifications. antonio, et al.: the impact of oil price and other macroeconomic variables on the islamic and conventional stock index in indonesia international journal of energy economics and policy | vol 11 • issue 5 • 2021 421 the steps in ardl testing in this study are as follows (dilla, 2014): 1. stationarity test is done by using the phillip perron (pp) test. the test hypothesis of the pp test is as follows: h0: δ = 1; there is root unit/not stationary h1: δ< 1; no root unit/stationary unit the test result criterion is to compare the t-statistical value of pp with the critical value of mackinnon. if the t-statistic value of pp is smaller than the critical value of mackinnon, the test result is rejecting h0 which states the data is stationary at the level. if the test results show that the data used is not stationary at degree i (0) or level, then there are two possible ardl models to be used. in the co-integrated data, the ardl for cointegration model is used, while the data without cointegration uses the first difference ardl model. 2. to determine whether there is a cointegration relationship between non-stationary variables, a bounds test cointegration is performed. estimation of the equation is done using ols by applying the f test which is intended to determine the existence of a long-term (cointegration) relationship between variables. this f test is used to see the joint test for long-term coefficients. the hypothesis being tested is: h0: δ1 = δ2 = 0; no cointegration h1: δ1 ≠ δ2 ≠ 0; there is cointegration the test result criterion is to compare the f-statistic value with the critical value that has been compiled in the table by pesaran and shin (1999). in the ardl bounds test, there are two asymptotic critical limit values for testing cointegration. the lowest critical value (lower critical value) assumes the regressor is integrated at i (0) while the highest critical value (upper critical value) assumes the regressor is integrated at i (1). if the f-statistic is above the highest critical value, then the null hypothesis about no cointegration or no long-term relationship is rejected. conversely, if the f-statistic is below the lowest critical value, the null hypothesis is not rejected. if the f-statistic is between the lowest and highest critical values, there is no conclusion (pesaran et al., 2001). 3. research methods this study uses a quantitative method of autoregressive distributed lag (ardl) followed by an error correction model (ecm), if there is cointegration. previously, the available data would go through several tests, namely the unit root test (stationarity) and the cointegration test. the time period used in this study is january 2010 to december 2019. the data used are monthly data taken from various institutions, especially the indonesia stock exchange. the data used in this study is secondary data in the form of monthly time series obtained from several sources such as the indonesia stock exchange and yahoo finance. all data starts from the period january 2010 to december 2019. as the dependent variable, the jakarta islamic index (jii) is an islamic stock index which is a composite of 30 islamic stocks that have the highest level of liquidity. in addition, the composite stock price index (ihsg) is a composite stock index of all issuers available on the indonesia stock exchange (idx). furthermore, the independent variable used is the consumer price index (ihk), the rupiah exchange rate against the usd. industrial production index, wti world crude oil price (cop) total money supply (jub) or m2 and government bond yields with a tenor of 10 years. 4. results and discussion 4.1. stationarity test the test method used to test the stationarity of the data in this study is the adf (augmented dickey fuller) and phillips-perron test using the five percent real level. if the t-adf and t-pp values are less than the critical value of mackinnon, it can be concluded that the data used is stationary (does not contain a unit root). this unit root test is carried out at the level up to the first difference. in the adf test, the variables that reach stationary at the level are ln_idx and ln_ipi. after the first difference is made, then all data are stationary at the real level of five percent. this means that the data used in this study are integrated in order one or can be abbreviated as i (1). meanwhile, in the phillips perron test only the ln_ipi variable is stationary at the level, so the variables used only experience stationary at the first difference. the results of the unit root test can be seen in table 1. 4.2. cointegration test to determine the existence of cointegration in the model, namely by using the bounds testing cointegration cointegration test method. the determination of the level of cointegration confidence based on the limits of critical value (critical value bounds) for the bounds testing cointegration method as stated in pesar et al. (2001). if the f-statistic value is below the lowest critical value (lower bound), it can be concluded that there is no cointegration in the model. if the f-statistic value is above the highest critical value (upper bound), it can be concluded that there is cointegration in the model. however, if the f-statistic is between the lower bound and upper bound, the result is inconclusive. the results of the cointegration test can be seen in table 2. based on the results of the cointegration test on the two research models, all models are not cointegrated to the long run. this means that the estimation of the two models is carried out using the first difference or short term ardl method. 4.3. optimum lag test selection of the best ardl model with an optimal lag combination, selected based on akaike information criteria (sc). the optimum lag test results in table 3 show that the two models have the same lag size in this study. table 1: stationarity test results variable adf value phillips-perron value level 1st difference level 1st difference ln_jii –3.177394 –11.32755 –3.091177 –11.40112 ln_idx –4.195763 –8.201633 –3.224484 –8.239732 ln_cop –2.489252 –7.773195 –2.005571 –7.426494 ln_exc –2.358280 –8.703402 –2.166193 –8.655385 ln_ihk –0.600488 –1.761104 –0.210170 –5.829564 ln_ipi –10.52651 –12.78234 –10.51928 –23.96851 ln_mm2 –2.401181 –11.36489 –3.319532 –12.24385 yield –2.622421 –8.241258 –1.899717 –8.134183 antonio, et al.: the impact of oil price and other macroeconomic variables on the islamic and conventional stock index in indonesia international journal of energy economics and policy | vol 11 • issue 5 • 2021422 4.4. ardl model estimation results based on the short-term estimation results in the table 4, it is known that in model 1 (jii) there are three significant variables, namely the variable itself (ln_jii) at lag 1 which has a significant effect on the five percent real level with a coefficient of –0.206. then the exchange rate variable (ln_exc) has a significant effect on the real level of one percent with a coefficient of –1.372. in addition, the consumer price index (ln_ihk) variable has a significant effect on the real level of five percent with a coefficient of 1,672. next, the short-term estimation results in model 2 (ihsg) have two significant variables, namely the exchange rate variable (ln_exc) which has a significant effect on the real level of one percent with a coefficient of -1.058. in addition, the consumer price index (ln_ihk) variable has a significant effect on the real level of one percent with a coefficient of 2.123. the findings in the two models above illustrate the strong relationship between islamic and conventional stock indexes on currency exchange rates and the consumer price index (cpi). 4.5. findings the results of this study indicate that the cpi has a positive correlation with the jii and ihsg stock indexes. these findings indicate that in the long run, an increase in the cpi (inflation) rate will increase the share price in each model. stocks are generally considered to be a good hedge against inflation because of their tendency to move together (kumar and tripathi, 2015). in addition, the findings from valcarcel (2012) state that in theory, inflation can affect stock prices, either positively or negatively depending on the theory being considered. gordon’s (1962) growth model shows that stock prices are directly related to the growth rate of current and expected dividend returns, inversely related to the rate of return on equity required. given this, inflation has a positive impact on stock prices in two ways: first, monetary easing that stimulates the economy together with inflation will have a positive table 2: ardl cointegration test results model f-statistic decision model 1 (jii) 1.067704 not cointegrated model 2 (ihsg) 2.297412 not cointegrated significance i(0) bound i(1) bound 10% 1.99 2.94 5% 2.27 3.28 1% 2.88 3.99 table 3: ardl optimum lag test results model lag optimum ln_ jii ln_ ihk ln_ mm2 ln_ exc ln_ ipi yield model 1 (jii) 1 0 2 0 0 0 model 2 (ihsg) 1 0 2 0 0 0 table 4: ardl short-term estimation results variable coefficient model 1 (jii) model 2 (ihsg) d(ln_jii(–1)) –0.206069** d(ln_idx(–1)) 0.133720 d(ln_cop) –0.004527 0.036639 d(ln_exc) –1.372666*** –1.058452*** d(ln_ihk) –0.767395 –0.285644 d(ln_ihk(–1)) –0.136679 –0.651036 d(ln_ihk(–2)) 1.671861** 2.123403*** d(ln_ipi) 0.070478 0.051826 d(ln_mm2) –0.020169 –0.081169 d(yield) –0.081507 –0.018856 c 0.001314 0.001839 ***, and *significant at the real level of 1%, and 5% 1000 1200 1400 1600 1800 2000 2200 2400 200 250 300 350 400 450 500 2014 2015 2016 2017 2018 2019 id r t ril lio n year jumlah saham syariah kapitalisasi jii figure 1: number of sharia shares period ii and stock market capitalization jii source: financial services authority (data processed) 0 200 400 600 800 1000 0 1000 2000 3000 4000 5000 6000 7000 ja n10 o ct -1 0 ju l-1 1 a pr -1 2 ja n13 o ct -1 3 ju l-1 4 a pr -1 5 ja n16 o ct -1 6 ju l-1 7 a pr -1 8 ja n19 o ct -1 9 ji i ih s g ihsg jii (rhs) figure 2: jci and jii index chart for 2010-2019 source: investing.com (data processed) 20.00 40.00 60.00 80.00 100.00 120.00 ja n10 ju l-1 0 ja n11 ju l-1 1 ja n12 ju l-1 2 ja n13 ju l-1 3 ja n14 ju l-1 4 ja n15 ju l-1 5 ja n16 ju l-1 6 ja n17 ju l-1 7 ja n18 ju l-1 8 ja n19 ju l-1 9 u s d p er b ar re l month figure 3: wti crude oil price chart for 2010-2019 source: investing.com (data processed) antonio, et al.: the impact of oil price and other macroeconomic variables on the islamic and conventional stock index in indonesia international journal of energy economics and policy | vol 11 • issue 5 • 2021 423 impact on the dividend growth rate. second, a monetary expansion that depresses bond yields will result in an increase in demand for equity, which in turn causes the average investor to lower the expected rate of return on equity. the findings of this study indicate that in the long run, the relationship between the exchange rate and the jii index is positive, in accordance with the main theory linking the interaction between the foreign exchange market and the stock market: the flow-approach model (dornbush and fisher, 1980) and the stock model. approach (branson, 1983; frankel, 1983). in the stockapproach model, it is based on the assumption that exchange rates are determined by the supply and demand for financial assets, such as equities and bonds. these models can be divided into portfolio equilibrium models and monetary models. the portfolio balance model shows that there is a negative relationship between exchange rates and stock prices (frankel, 1983; branson and henderson, 1985). in this model, individuals hold domestic and foreign assets, including currency in their portfolios. the exchange rate plays the role of balancing the demand and supply of assets. the increase in domestic share prices causes individuals to demand more domestic assets. to buy more domestic assets, local investors sell foreign assets which causes the local currency to appreciate. as a result, the relationship between share prices and exchange rates becomes negative. furthermore, the results of the above research show a little uniqueness in the crude oil price (cop) variable. this variable shows different results between the jii index and the ihsg index, where cop has a negative effect on jii while having a positive effect on the jci. the results of the study showing that the cop variable has a negative effect on jii is in accordance with the research of park and ratti (2008), who analyzed the effect of oil price movements on the stock market in the united states and thirteen european countries between 1986 and 2005. they revealed that oil price fluctuations have a negative impact on the stock market. theoretically, an increase in oil prices could increase income for oil exporting countries because it is expected to support foreign exchange earnings and build reserves in the short term. however, for an oil importer like indonesia, rising oil prices may impact fiscal policy tendencies to be weighed down, limiting the government’s ability to finance large import bills and meet other international obligations. the result can be detrimental to economic growth arising from an increase in domestic production costs and a decrease in aggregate demand (onyeke et al., 2020). on the other hand, the results show that the cop variable has a positive effect on the jci in accordance with research from aggarwal and manish (2020) which states that there is a positive relationship between crude oil prices and indian stock index in the long term. higher oil prices, as a result of an unexpected global expansion, had a positive effect on stock returns. the volatility of oil prices can affect the sensitivity of changes in oil prices to the risk premium component of the discount rate and cash flows through demand-side consequences (narayan and narayan, 2010). in addition, kollias et al. (2013) suggest that investors may associate rising oil prices with booming economies. thus, higher oil prices could reflect stronger business performance and have an impact on the stock market. the relationship between world crude oil prices to the jii and jci indices has different directions, but the above results show that the relationship between cop and the jii stock index and jci is not significant. akoum et al. (2012) stated that the indonesian stock market is not affected by fluctuations in crude oil prices even though indonesia is a producer of crude oil, this is because industrialization and rapid population growth have forced the government to import oil from the international oil market, so that it does not affect the stock price index so much. in addition, the price of petroleum can affect the stock market in a country either positively or negatively depending on the fluctuation of the crude oil market (arouri et al., 2011), so the direction of the relationship between crude oil prices and the stock index depends on the study period. 5. conclusion based on the results of research that has been conducted regarding the influence of macroeconomic variables on two research models; jii and ihsg, several conclusions were obtained, namely: there is no long-term co-integration of the jakarta islamic index (jii) and the composite stock price index (ihsg), so the estimates in these two models only use the short-term model. in the short term, the exchange rate and the consumer price index (cpi) significantly influence the price movements of the jii and jci indexes. this indicates that the movement of the jii and jci indexes in the long term is influenced by the fluctuation of the rupiah exchange rate against the us dollar. in addition, the movement of these two indices is also influenced by inflation (represented by the cpi). the recommendations that the author can give are: for investors, it is advisable to be more critical in analyzing the factors that influence the movement of the jii and jci. investors can look for information related to external factors that affect market conditions, such as macroeconomic variables. this information can help investors to make investment decisions and predict the right time to sell or buy shares on the stock exchange. references aggarwal, p., manish, m.k. (2020), effect of oil fluctuation on stock market return: an empirical study from india. international journal of energy economics and policy, 10(2), 213-217. akoum, i., graham, m., kivihaho, j., nikkinen, j., omran, m. (2012), co-movement of oil and stock prices in the gcc region: a wavelet analysis. the quarterly review of economics and finance, 52(4), 385-394. alzyoud, h., wang, e.z., basso, m.g. (2018), dynamics of canadian oil price and its impact on exchange rate and stock market. international journal of energy economics and policy, 8(3), 107-114. anoraga, p., pakarti, p. (2001), pengantar pasar modal. jakarta: rineka cipta. anyalechi, k.c., ezeaku, h.c., onwumere, j.u.j., okereke, e.j. (2019), does oil price fluctuation affect stock market returns in nigeria? antonio, et al.: the impact of oil price and other macroeconomic variables on the islamic and conventional stock index in indonesia international journal of energy economics and policy | vol 11 • issue 5 • 2021424 international journal of energy economics and policy, 9(1), 194-199. arouri, m.e., jouini, j., nguyen, d.k. (2011), volatility spillovers between oil prices and stock sector returns: implications for portfolio management. journal of international money and finance, 30(7), 1387-1405. arouri, m.e., rault, c. (2010), causal relationships between oil and stock prices: some new evidence from gulf oil-exporting countries. economie international, 122, 41-56. branson, w.h. (1983), macroeconomic determinants of real exchange rate risk. in: herring, r.j., editor. managing foreign exchange risk. ch. 1. cambridge: cambridge university press. branson, w.h., henderson, d.w. (1985), the specification and influence of asset markets. handbook of international economics, 2, 749-805. dilla, s. (2014), exchange rate pass-through dalam konteks inflation targeting framework: kasus empiris di 19 negara di dunia [skripsi]. bogor: institut pertanian bogor. dornbush, r., fisher, s. (1980), exchange rates and the current account. american economic review, 70(5), 960-971. fosu, e., magnus, j.f. (2006), bounds testing approach: an examination of foreign direct investment, trade, and growth relationships, munich personal repec archive. frankel, j. (1983), monetary and portfolio balance models of exchange rate determination. in: bhandari, j., putnam, b., editors. economic interdependence and flexible exchange rates. cambridge, ma: mit press. p84-114. gordon, m.j. (1962), the savings, investment, and valuation of a corporation. review of economics and statistics, 44, 37-51. harsono, b. (2013), efektif bermain saham. jakarta: kompas gramedia. heykal, m. (2012), tuntunan dan aplikasi investasi syariah. jakarta: pt elex media komputindo. hidayat, t. (2011), buku pintar investasi syariah. jakarta: mediakita. kollias, c., kyrtsou, c., papadamou, s. (2013), the effects of terrorism on the oil price-stock index relationship. energy economics, 40, 743-752. kumar, a., tripathi, v. (2015), relationship between macroeconomic factors and aggregate stock returns in brics stock markets-a panel data analysis. in: new age business strategies in emerging global markets. new delhi: excel india publishers. p104-123. narayan, p., narayan, s. (2010), modelling the impact of oil prices on vietnam’s stock prices. applied energy, 87(1), 356-361. nastiti, k.l.a., suharsono, a. (2012), analisis volatilitas saham perusahaan go public dengan metode arch-garch. jurnal sains dan seni its, 1(1), 259-264. onyeke, c.e., nwakoby, i., onwumere, j.u.j., ihegboro, i. (2020), impact of oil price shocks on sectoral returns in nigeria stock market. international journal of energy economics and policy, 10(6), 208-215. park, j., ratti, r.a. (2008), oil price shocks and stock markets in the us and 13 european countries. energy economics, 30(5), 2587-2608. pesaran, m.h., shin, y. (1999), an autoregressive distributed lag modeling approach to co-integration analysis. in: econometrics and economic theory in the 20th century: the ragnar frisch centennial symposium. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. rivai, h.v., buchori, a. (2013), islamic economics: ekonomi syariah bukan opsi, tetapi solusi: pt bumi aksara, jakarta. rusbariand, s.p., masodah, r., herawati, s. (2012), analisis pengaruh tingkat inflasi, harga minyak dunia, harga emas dunia, dan kurs rupiah terhadap pergerakan jakarta islamic indek di bursa efek indonesia. united states: prosiding seminar nasional forum bisnis dan keuangan i. soemitra, a. (2009), bank dan lembaga keuangan syariah. jakarta: kencana prenadamedia group. tangjitprom, n. (2012), the review of macroeconomic factors and stock returns. international business research, 5(8), 107-115. tempo. (2016), oil prices drop amid doubts about opec agreement available from: https://www.bisnis.tempo.co/read/816564/hargaminyak-turun-di-tengah-keraguan-kesepakatan-opec/full&view=ok. varcarcel, v. (2012), the dynamic adjustments of stock prices to inflation disturbances. journal of economics and business, 64(2), 117-144. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 2 • 2021 49 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(2), 49-56. examining the relationship between electricity consumption, financial development and economic growth in asean countries: evidence from a bayesian analysis canh chi hoang faculty of business administration, university of finance marketing, ho chi minh city, vietnam. *email: canhchihoang@ufm.edu.vn received: 21 september 2020 accepted: 20 december 2020 doi: https://doi.org/10.32479/ijeep.10642 abstract the literature has suggested that financial development and electricity consumption are key determinants of economic growth. however, existing studies usually was applied the frequentist inference, which is an outdated estimator. by applying the bayesian approach via the metropolis-hasting and gibbs samplers as the mcmc methods, the study aims to re-examine the impact of financial development and electricity consumption on economic growth in asean+6 countries from 1980 to 2016. the obtained outcome shows that the impact of both financial development and electricity consumption is strong and positive on economic growth. there is a uni-directional causality running from economic growth to energy consumption, supported the conversation hypothesis. based on the empirical result, several policy implications are suggested for emerging countries, asean+6 nations, in particular. keywords: financial development, energy consumption, economic growth, bayesian, asean countries jel classifications: f43, o13, o47, q42, q43 1. introduction physical capital accumulation is a crucial factor contributing to economic growth (romer, 1990; stiglitz, 2000). following the pioneering of schumpeter (1912), majority of the economic researcher is persuaded that financial development allows foreign direct investment flows, encourages the investment of enterprises, reduces costs of loans, boost household consumption, and increase banking activities, less financial risks. the pressure of improving income per capita leads to pumping more money into the financial system by government. the consequence of more money is a high-inflation situation, and the financial crisis of 2008 provided practical evidence to re-examine the benefit of financial development to growth. now, the notion “more money, more oversight” has been supported by many governments worldwide. however, a financial reduction is not good for economic growth. mckinnon (1974), shaw (1974) argues that financial reduction leads to a fixed interest rate, decreasing banking activities, increasing the real exchange rate, reducing export, discourage the development of capital markets, and hurts economic growth. understanding and quantifying the relationship between energy consumption and economic growth is one of the hot topics for economics researchers and administrators. energy is used as an input in the production, transportation, and consumption of nearly all goods or services (ha and ngoc, 2020; long et al., 2018; stern, 2000). the linkage between energy consumption and economic growth has been well-studied by several researchers. nevertheless, the conclusion of existing studies has failed to provide a consistent answer. for example, tang (2009) investigates the connection between electricity consumption, income, foreign direct investment, and population in malaysia from 1970 to 2005. the obtained results by the ardl approach shows that economic growth has a positive impact on electricity consumption, this journal is licensed under a creative commons attribution 4.0 international license hoang: examining the relationship between electricity consumption, financial development and economic growth in asean countries: evidence from a bayesian analysis international journal of energy economics and policy | vol 11 • issue 2 • 202150 supported the conversation hypothesis. however, yoo (2005) used the cointegration and vector error correction model to analyzes the shortand long-run causality between electricity consumption and economic growth in korea from 1970 to 2002. the empirical outcome reveals that there is bi-directional causality between economic growth and electricity, supported the feedback hypothesis. even using the panel data, the results of chen et al. (2007) are mixed in ten newly industrializing and developing asian countries. accordingly, there is a uni-directional shortrun causality running from economic growth to electricity consumption and a bi-directional long-run causality between electricity consumption and economic growth if the panel data procedure is implemented. the above mentioned previous studies indicate that the linkage between financial development, electricity consumption, and economic growth is an interesting topic, which is still the subject of an ongoing debate (omri, 2014; tiba and omri, 2017). the main aim of this work is to inspect the impact of financial development, electricity consumption, and economic growth in asean+6, including indonesia, malaysia, philippines, singapore, thailand, vietnam during the period 1980-2016. our study is different from several previous studies in multiple points, as follows: first, to the best of our knowledge, the available studies analyzed in the case of asean countries have drawn little attention. second, most previous studies have been conducted in a linear framework and used the frequentist inference. in the study, we employed the bayesian inference approach through the integrated markov chain monte-carlo sampler to provide probabilistic interpretations of model uncertainty and varying effects of financial development and electricity consumption on economic growth. the advantage of bayesian inference compared to frequentist inference is presented in section 3. to our knowledge, the obtained result could be enrichment in existing economic literature and for the asean+6 countries in particular. the rest of the study is organized as follows: section 2 focuses on present the literature and the existing studies. section 3 describes the model, data, and methodology. the obtained outputs are shown in section 4, while section 5 provides a conclusion and policy implication. 2. literature review 2.1. financial development and economic growth the role of the financial development and financial system is a vital one for any economy. the pioneering of schumpeter (1912) found that a developed financial system boost investment activities, increase transparency between lenders and borrowers, reduces costs of credits, and leads to beneficial for economic growth. schumpeter (1912) stated that most of the enterprises need credit in order to buy material, machinery, and paying salaries. in simple capital markets, the bank becomes the producer of this commodity. thus, the banking system plays the most critical channel, where intermediating financial activities are supported and enhance growth. consistent with this view, mckinnon (1974) and shaw (1974) devote to financial liberalization. they pointed out that the government should not strictly control interest rates because it will reduce the return rate of financial assets. besides, it encourages people/enterprises to invest in non-financial assets (e.g., gold, real estate) and generates back financial markets. indeed, bretschger and steger (2004) showed two channels that financial development affects on economic growth, including (i) the scale-effect channel; (ii) the factor-reallocation effect channel. accordingly, they confirmed that the efficiency banking system is the vital factor for economic development due to its role in mobilizing and allocating saving and the funding of economic activity investment. regarding empirical studies, king and levine (1993) found that the development of the financial sector is robustly related to per capita gdp growth, and it positively enhances the accumulation of physical capital. likewise, ben jedidia et al. (2014) used the ardl approach to analyze the connection between financial development and economic growth in tunisia from 1973 to 2008. the obtained result shows that domestic credit to the private sector positively affects economic growth, and financial development is a driver of long term economic growth. the positive impact of financial development on economic growth is supported by the study of liang and teng (2006), komal and abbas (2015), salahuddin and gow (2016). another study by alsamara et al. (2018) examines the impact of financial development and trade openness on the real gdp per capita in turkey during the period 1960-2014. the empirical result from the ardl approach with structural break reveals that both the trade openness and financial development have a positive impact on per capita real gdp. accordingly, a 1% increase in money supply to gdp ratio leads to a 0.36% increase in real gdp per capita. using the non-linear framework, masten et al. (2008), law and singh (2014) found that the impact of financial development was depended on the critical threshold, exceed this critical threshold, the more money is not good for economic growth. goldsmith (1969) was the first to work a positive correlation between economic growth and financial development in his 35 countries sample. abid et al. (2016) used a multivariate vector autoregressive model to inspect the linkage between financial development (measured by the stock market return) and economic growth in ten mena (the middle east and north africa) countries. the result provides evidence that the gdp growth response to qatar gdp growth shock is statistically significant for all countries, while the stock market response to morocco stock market shock is insignificant in qatar, saudi arabia, and uae. the positive impact of financial development on economic growth is confirmed by the study of ibrahim and alagidede (2018). applying the system gmm method, ibrahim and alagidede (2018) found that financial development supports economic growth. the extent of finance helps growth depends crucially on the simultaneous growth of real and financial sectors in 29 sub-saharan african countries over the period 1980-2014. greenwood and jovanovic (1990) explained that individuals or enterprises have many opportunities to invest in several projects. the developed financial system, as mentioned by schumpeter (1912) must mobilize and allocate saving capital flows into projects, which have high productivity or output. that means stock market allocates these capital flows into priority sectors, which have the highest return rate, and generates several optimal stock lists. greenwood and jovanovic (1990) pointed out hoang: examining the relationship between electricity consumption, financial development and economic growth in asean countries: evidence from a bayesian analysis international journal of energy economics and policy | vol 11 • issue 2 • 2021 51 that if individual or enterprises select an optimal stock list, which leads to beneficial for economic growth. however, some administrators and economics researchers are not advocating for financial development. edwards (2001), okada (2013) argues that the overload of financial development leads to an increase in inflation, which harms economic growth in the longrun. emerging markets have a low financial institution, and should be highly susceptible to the volatility of the global financial market, which is especially severe for countries with an open capital account. demetriades and hussein (1996) used the var model to examines the influence of financial development on economic growth in 16 countries. the obtained result reveals that the money supply is the danger of economic growth. likewise, rousseau and vuthipadadorn (2005) found that financial development has a dampening effect on investment and growth in ten asian countries. similarly, ono (2017) found that there is no causality from money supply to economic growth in the case of russia during the period of 2009-2014. 2.2. energy consumption and economic growth in developing countries, administrators and economic researchers have advocated analysis of the linkage between energy consumption and economic growth with the expectation that energy production and energy consumption are key determinants of economic growth. in fact, energy is a necessary input of economic activities, such as transportation, production (abosedra et al., 2009; chandran et al., 2010; golam and nazrul, 2011; ngoc, 2019; zhang et al., 2017). the energy-growth nexus has been well-studied in the energy economics literature. however, the available studies have failed to provide a consistent answer (ha and ngoc, 2020; tiba and omri, 2017), and it is still the subject of an ongoing policy debate. there are four hypotheses found by existing works about the relationship between energy consumption and economic growth, including the “conversation,” the “growth,” the “feedback” and the “neutrality” hypothesis. supporting the feedback hypothesis, based on the cobb-douglas production function, hamdi et al. (2014) inspect the linkages between electricity consumption, foreign direct investment, capital, and economic growth from 1980q1 to 2010q4 for the kingdom of bahrain. the empirical result from the ardl bounds testing and vecm causality shows that there exist a positive impact and bi-directional causality between electricity consumption and economic growth. likewise, ibrahiem (2015) analyzes the relationship between renewable electricity consumption, foreign direct investment, and economic growth in egypt from 1980 to 2011. the existence of cointegration among the examined variable is found by the ardl bounds testing, and the granger causal test identifies the bi-directional causality between economic growth and renewable electricity consumption. the positive influence of electricity consumption on economic growth is confirmed by the study of tang (2009) for malaysia, long et al. (2018) for vietnam, or zhang et al. (2017) for china’s economy. about the growth hypothesis, golam and nazrul (2011) discover the connection between per capita electricity consumption and per capita gdp in the case of bangladesh from 1971 to 2008. the obtained outcome reveals mixed results. accordingly, there is a uni-directional causality in the short-run, a bi-directional causality between per capita electricity consumption and per capita gdp in the long-run. another study by acaravci (2010) explores the shortand long-run causality between electricity consumption and economic growth in turkey from 1968 to 2005. the vecm granger causality shows that there is a uni-directional causality running from electricity consumption to economic growth. the conversation hypothesis was found by the pioneering study of kraft and kraft (1978). they examine the impact of economic growth on electricity consumption in the united states over the period 19471974. the granger causality provides that there is a uni-directional causality running from economic growth to electricity consumption. likewise, balcilar et al. (2019) used the maki cointegration to inspect the linkage between electricity consumption, real gross domestic product, and carbon dioxide emissions in pakistan. a uni-directional causality running from economic growth to electricity consumption was found by the toda-yamamoto causality test, which supported the conversation hypothesis. some studies found the neutrality hypothesis. ghosh (2009) does not found the interaction between electricity supply, employment, and real gdp for india. similarly, payne (2009) applied the todayamamoto causality tests. the obtained result shows that the absence of granger-causality between renewable or non-renewable energy consumption and real gdp in the case of the united states from 1949 to 2006, which supports the neutrality hypothesis. the impact of financial development and energy consumption on economic growth has been studied by several previous works, such as kahouli (2017), rafindadi and ozturk (2016), burakov burakov and freidin (2017), and mahi et al. (2019). however, the conclusion of these studies is not consistent, even ambiguous. to explain the different above-mentioned conclusion, apergis and payne (2010) point out that the interaction between energy consumption and economic growth nexus is depended on the level of national development. in poor countries, economic activities based on natural extraction (e.g., planting, fishing). thus, the demand for energy is low, and the energy consumption does not enhance economic growth. however, it is not true in developing or developed countries. the pressure improving income per capita leads to many projects or policies were issued by the government, which requires more energy as a driving force of production of goods or services. so, energy production and energy consumption is an essential factor for development. of course, the above-mentioned studies do not adequately represent all previous studies on financial development-energy consumption-growth nexus. nevertheless, this review showed that most of the available studies use frequentist inference. no studies apply bayesian inference. it is a methodology gap, which this work want to address. 3. research model and methodology the main aim of this study is to investigate the impact of financial development and electricity consumption on economic growth hoang: examining the relationship between electricity consumption, financial development and economic growth in asean countries: evidence from a bayesian analysis international journal of energy economics and policy | vol 11 • issue 2 • 202152 in asean+6 countries from 1980 to 2016, so the model is preliminarily set as follows: lngdp lnec lnfi ln ec fi ub i t i i t i t i t , , , , . . . ( . ) . � � � � � � � � � � � � 0 1 2 3 4 ii t i te, ,� (1) where, i is the country (1,…, n: including indonesia, malaysia, philippines, singapore, thailand, vietnam, respectively), t is time (1,…, t: from 1980 to 2016). υi are random intercepts, e(i,t) is an error. in eq.1, lnfi variables is the logarithm of financial development (measured by m2 money supply, units: million u.s. dollar), lnec variable is the logarithm of the electricity consumption per capita, unit: kwh/year), ln(ec.fi) is the interaction variable (= lnec*lnfi), and ub is the rate of urbanization (unit: percentage), which plays as the control variable in the model. annual data is collected from the imf and the world bank. the dependent variable is lngdp per capita (at the fixed price 2010, unit: u.s. dollar). this work used the bayesian inference, which has several advantages outperforms the frequentist inference, as follows: first, bayesian analysis is based on the bayes rule and the posterior distribution results from updating the prior knowledge about model parameters with evidence from the observed data. the bayesian analysis rests on bayes’ theorem of probability theory: p y p y p p y ( ) ( ). ( ) ( ) � � � � (2) where, θ stands for a set of unknown parameters, y represents a marginal distribution of data, p(θ) denotes the prior distribution of the parameters θ (pre-existing information such as expert opinion, theory, or other external resources), p(y|θ) is a likelihood distribution, p(y) is the marginal distribution of y, and p(y|θ) denotes the posterior distribution, which is the probability of the parameters θ conditional on the data x. equation (2) may be expressed as: p y p y p( ) ( ) ( )� � �� (3) where, ∝ implies “proportional to.” the posterior is proportional to the prior multiplied by the likelihood. second, the frequentist inference assumes that all parameters are considered unknown but fixed quantities, while bayesian inference allows all parameters are random quantities and thus can incorporate prior knowledge. hence, bayesian analysis yields an entire probability distribution of a parameter, while frequentist results are point estimates. also, the bayesian paradigm allows for probability statements, such as a variable is likely or unlikely to impact on another, or the true value of a parameter falls into a certain interval with a pre-specified probability (bernardo and smith, 1994; thompson, 2012). because our data sample size is sufficiently large, noninformative priors are enough for our model specification. for comparison purposes, we also specify informative priors for the model parameters. accordingly, we conduct five posterior simulations. a sensitivity analysis to prior choice will be performed through a bayes factor test and a model test. we assume to have models mj parameterized by vectors θj,j=1,2,…r. by applying bayes’s theorem, we calculate the posterior model probabilities: p m y p y m p m p yj j j ( ) ( ) ( ) ( ) = (4) since it is challenging to calculate p(y), a popular practice is to compare two models, for example, mj and mk via posterior odds ratio: po p m y p m y p y m p m p y m p mj k j k j j k k , ( ) ( ) ( ) ( ) ( ) ( ) = = (5) if all models are equally plausible, that is p(mj)=1/r, the posterior odds ratio is transformed into the bayes factor, which is simply ratios of marginal likelihoods (jeffreys, 1962). bf p y m p y mj k j k , ( ) ( ) = (6) the detailed process of estimation is acted through three steps, as follows: first, we use the fixed-effect model (fem) and the random-effect model (rem) to provide a general view of the influence of financial development and electricity consumption on economic growth. second, we apply the bayesian approach via the metropolishasting and gibbs samplers as the mcmc methods to estimate the impact of financial development and electricity consumption on economic growth. finally, we use dumitrescu and hurlin (2012) test to check the causality between energy consumption and economic growth. 4. empirical results 4.1. descriptive statistic in two past decades, the asean+6 countries, including indonesia, malaysia, philippine, singapore, thailand, and vietnam, have changed rapidly in most socio-economic fields. rapid growth leads to a change in the structure of the economy. the industry sector is focused on investing by the government. also, urbanization leads to a great demand for energy. acknowledge that financial development and energy consumption are actively contributing to growth in these countries. the descriptive statistic of all variables is shown in table 1. 4.2. model comparison this subsection compares five posterior regression models, where the respective gaussian prior distributions specified are n(0,1), n(0,10), n(0,100), n(0,1000), and n(0,10000). the results of the model comparison are presented in tables 2 and 3. in general, the less the dic value, the more the log(ml) and log(bf) estimate, the better a model fits the data. p(my) shows the posterior model probability. consequently, model 1 is the best. table 1: the descriptive statistic of all variables variables mean maximum minimum std. error lngdp 8.128 10.885 5.735 1.234 lnec 6.763 9.088 3.832 1.358 lnfi 2.573 4.275 -1.472 0.725 lnecfi 17.301 31.028 -11.528 4.734 ub 50.26 100 19.25 25.56 hoang: examining the relationship between electricity consumption, financial development and economic growth in asean countries: evidence from a bayesian analysis international journal of energy economics and policy | vol 11 • issue 2 • 2021 53 4.3. mcmc convergence test in the application of an mcmc method, a convergence check is needed before proceeding to inference. once chain convergence is established, the model parameters have converged to equilibrium values. to avoid pseudo convergence, in this study, we simulate three mcmc chains and verify whether the results satisfy the convergence rule. this is because pseudo convergence takes place when the chains have seemingly converged, but indeed, they explored only a portion of the domain of a posterior distribution. as demonstrated in table 4, the maximum gelman-rubin statistic rc of 1.0001 is close to 1.1, indicating mcmc convergence. the model summary reports the rate of acceptance and algorithm efficiency as initial indicators of mcmc convergence. the acceptance rate is the number of proposals accepted in the total proposals, whereas algorithm efficiency is the mixing properties of mcmc sampling. concerning the chosen model 2, the acceptance rate of 0.84 is larger than the minimum level of 0.1, whereas average efficiency is equivalent to 0.35, which is more than the acceptable level of 0.01. this implies that the obtained results from bayesian multilevel regression are reliable. additionally, it is useful to conduct a graphical inspection. for this, cusum plots as an accessible tool are applied. as shown in figure 1, the cusum plots of the parameters corresponding to three chains are jagged, not smooth, running across the x-axis. so mcmc chains for the model parameters are well-mixed, which is a sign of sequence convergence. 4.4. fem, rem and bayesian estimation the estimation of the eq.1 by frequentist and bayesian inference is presented in table 5. the obtained outcome from fem and rem model shows that there is a positive impact of electricity consumption on economic growth. accordingly, a 1% increase in electricity consumption leads to 0.747% increase in economic growth. besides, financial development is helpful to economic growth (p_value = 0.000). a 1% increase in financial development leads to 0.629% increase in economic growth. with the bayesian inference, the result in the lower section of table 5 reveals that both the influence of electricity consumption and financial development is beneficial for economic growth. with a probability of mean between 0.7 and 1, electricity consumption and financial development exert a powerfully positive effect on economic growth. the 95% credible intervals also point to similar results. thus, we can confirm that the value of 0.7951 of the coefficient for lnec belongs to the interval [0.6587, 0.9315] with a 95% probability. similar interpretations can be made for the remaining parameters of the model. with a probability of mean table 2: bayesian information criteria model gaussian distribution dic log(ml) log(bf) 1 n(0,1) 103.8528 −75.6626 2 n(0,10) 104.0392 −79.5551 -3.8924 3 n(0,100) 104.0978 −85.1067 -9.4441 4 n(0,1000) 104.1043 −90.8425 −15.1799 5 n(0,10000) 104.1050 −96.5969 −20.9342 table 3: bayesian model tests model gaussian distribution log(ml) p(m) p(my) 1 n(0,1) −75.6626 0.2000 0.9799 2 n(0,10) −79.5551 0.2000 0.0200 3 n(0,100) −85.1067 0.2000 0.0001 4 n(0,1000) −90.8425 0.2000 0.0000 5 n(0,10000) −96.5969 0.2000 0.0000 table 4: gelman-rubin convergence diagnostic max gelman-rubin rc=1.000142 <convergence rule (=1.1) rc value dependent variable: lngdp lnec 1.000142 lnfi 1.00009 lnecfi 1.000076 ub 1.00008 intercept 1.00013 var 0.999963 table 5: fem, rem and bayesian simulation results variables coefficient p_value coefficient p_value fem result rem result lnec 0.8324 0.000 0.7461 0.000 lnfi 0.5715 0.000 0.6298 0.000 lnecfi −0.0824 0.000 -0.0891 0.000 ub −0.009 0.000 0.0054 0.021 intercept 2.916 0.000 2.7009 0.000 f-test f-statistic=254.24 (p_value = 0.000) hausman test f-statistic=467.59 (p_value = 0.000) variables mean bayesian result std. dev. mcse probability of mean>0 equal-tailed (95% cred. interval) dependent variable: lngdp lnec 0.7951 0.0691 0.0004 1 (0.6587, 0.9315) lnfi 1.0226 0.1652 0.0009 1 (0.6983, 1.3473) lnecfi -0.1469 0.0230 0.0001 1* (−0.1919, −0.1019) ub 0.0251 0.0016 0.0000 1 (0.0221, 0.0280) intercept 1.3753 0.4849 0.0028 0.99 (0.4216, 2.3275) * is probability of mean < 0 hoang: examining the relationship between electricity consumption, financial development and economic growth in asean countries: evidence from a bayesian analysis international journal of energy economics and policy | vol 11 • issue 2 • 202154 is one, we can state that urbanization is a good contribution to economic growth in examined countries. 4.5. the causality test finally, the study used dumitrescu and hurlin (2012) test to examine the causality relationship between energy consumption and economic growth. both the w-bar and z-bar statistic test presented in table 6 provides evidence in favor of the rejection of the null hypothesis (p_value < 0.05). this result implies that there is a uni-directional causality running from economic growth to energy consumption in examined countries, which supported the conversation hypothesis. 5. discussion the empirical result shows that the impact of financial development and electricity consumption on economic growth is beneficial. these results are in line with the conclusion by ben jedidia et al. (2014) for tunisia, sarkar et al. (2019) for malaysia, glasure and lee (1997) for south korea and singapore, or long et al. (2018); ngoc (2019); nguyen and ngoc (2020) for vietnam. physical capital accumulation and a developed financial system will enhance economic growth through the process of mobilizing and allocating the saving capital flows into projects, which have high productivity or output. all six countries in our sample are developing or developed countries, so the demand for production, distribution, or household consumption is rapid growth. according to the forecasting of the international energy agency, the energy demand is growing by 1.4% per year until 2035. this is valid for both emerging or developed countries. 6. conclusion the study applies the bayesian approach via the metropolishasting and gibbs samplers as the mcmc methods to investigate the impact of financial development and electricity consumption on economic growth in asean+6 countries over the period 1980 to 2016. five simulations are conducted with gaussian prior distributions ranging from (0,1) to (0,10000). as shown by model comparison results via a bayes factor and a model test, the model with a noninformative, namely, n(0,1) prior fits the best. according to the estimation results, we claim in view of the probability that both electricity consumption and financial development strongly and positively affects economic growth. based on the empirical results, some policy implications are suggested, as detailed: firstly, electricity consumption is beneficial for growth, so the government should intend to expand energy supply through the development of renewable or green energies, such as solar, wind, biofuels, and geothermal power. secondly, financial development will drive economic growth if the country has a transparent and efficient financial system. thus, the rate of the money supply should be calculated corresponding to the rate of growth. a deficiency in the money supply will result in a decrease in economic growth, negatively impacting other economic activities. references abid, f., bahloul, s., mroua, m. (2016), financial development and economic growth in mena countries. journal of policy modeling, 38(6), 1099-1117. abosedra, s., dah, a., ghosh, s. (2009), electricity consumption and economic growth, the case of lebanon. applied energy, 86(4), 429-432. figure 1: cusum plots of model parameters table 6: results of the causality test null hypothesis: no causality w-bar z-bar p-value lnec does not granger cause lngdp 1.9879 1.711 0.087 lngdp does not granger cause lnec 4.6660 6.3549 0.000 hoang: examining the relationship between electricity consumption, financial development and economic growth in asean countries: evidence from a bayesian analysis international journal of energy economics and policy | vol 11 • issue 2 • 2021 55 acaravci, a. (2010), structural breaks, electricity consumption and economic growth: evidence from turkey. romanian journal of economic forecasting, 2, 140-154. alsamara, m., mrabet, z., barkat, k., elafif, m. (2018), the impacts of trade and financial developments on economic growth in turkey: ardl approach with structural break. emerging markets finance and trade, 55(8), 1671-1680. apergis, n., payne, j.e. (2010), energy consumption and growth in south america: evidence from a panel error correction model. energy economics, 32(6), 1421-1426. balcilar, m., bekun, f.v., uzuner, g. (2019), revisiting the economic growth and electricity consumption nexus in pakistan. environmental science and pollution research, 26(12), 12158-12170. ben jedidia, k., boujelbène, t., helali, k. (2014), financial development and economic growth: new evidence from tunisia. journal of policy modeling, 36(5), 883-898. bernardo, j.m., smith, a.f.m. (1994), bayesian theory. hoboken: john wiley & sons, inc. bretschger, l., steger, t.m. (2004), the dynamics of economic integration: theory and policy. international economics and economic policy, 1(2-3), 119-134. burakov, d., freidin, m. (2017), financial development, economic growth and renewable energy consumption in russia: a vector error correction approach. international journal of energy economics and policy, 7(6), 39-47. chandran, v.g.r., sharma, s., madhavan, k. (2010), electricity consumption-growth nexus: the case of malaysia. energy policy, 38(1), 606-612. chen, s.t., kuo, h.i., chen, c.c. (2007), the relationship between gdp and electricity consumption in 10 asian countries. energy policy, 35(4), 2611-2621. demetriades, p.o., hussein, k.a. (1996), does financial development cause economic growth? time-series evidence from 16 countries. journal of development economics, 51(2), 387-411. dumitrescu, e.i., hurlin, c. (2012), testing for granger non-causality in heterogeneous panels. economic modelling, 29(4), 1450-1460. edwards, s. (2001), capital mobility and economic performance: are emerging economies different? nber working paper no. 8076. available from: https://www.nber.org/papers/w8076. ghosh, s. (2009), electricity supply, employment and real gdp in india: evidence from cointegration and granger-causality tests. energy policy, 37(8), 2926-2929. glasure, y.u., lee, a.r. (1997), cointegration, error-correction, and the relationship between gdp and energy: the case of south korea and singapore. resource and energy economics, 20, 17-25. golam, a.m., nazrul, i.a.k. (2011), electricity consumption and economic growth nexus in bangladesh: revisited evidences. energy policy, 39(10), 6145-6150. goldsmith, r.w. (1969), financial structure and development. new haven: yale university press. greenwood, j., jovanovic, b. (1990), financial development, growth, and the distribution of income. journal of political economy, 98(5), 1076-1107. ha, n.m., ngoc, b.h. (2020), revisiting the relationship between energy consumption and economic growth nexus in vietnam: new evidence by asymmetric ardl cointegration. applied economics letters, 2020, 1789543. hamdi, h., sbia, r., shahbaz, m. (2014), the nexus between electricity consumption and economic growth in bahrain. economic modelling, 38, 227-237. ibrahiem, d.m. (2015), renewable electricity consumption, foreign direct investment and economic growth in egypt: an ardl approach. procedia economics and finance, 30, 313-323. ibrahim, m., alagidede, p. (2018), effect of financial development on economic growth in sub-saharan africa. journal of policy modeling, 40(6), 1104-1125. jeffreys, h. (1962), theory of probability. geophysical journal international, 6(4), 555-558. kahouli, b. (2017), the short and long run causality relationship among economic growth, energy consumption and financial development: evidence from south mediterranean countries (smcs). energy economics, 68, 19-30. king, r.g., levine, r. (1993), finance, entrepreneurship and growth: theory and evidence. journal of monetary economics, 32(3), 513-542. komal, r., abbas, f. (2015), linking financial development, economic growth and energy consumption in pakistan. renewable and sustainable energy reviews, 44, 211-220. kraft, j., kraft, a. (1978), on the relationship between energy and gnp. the journal of energy and development, 3(2), 401-403. law, s.h., singh, n. (2014), does too much finance harm economic growth? journal of banking and finance, 41, 36-44. liang, q., teng, j.z. (2006), financial development and economic growth: evidence from china. china economic review, 17(4), 395-411. long, p.d., ngoc, b.h., my, d.t.h. (2018), the relationship between foreign direct investment, electricity consumption and economic growth in vietnam. international journal of energy economics and policy, 8(3), 267-274. mahi, m., phoong, s.w., ismail, i., isa, c.r. (2019), energy-financegrowth nexus in asean-5 countries: an ardl bounds test approach. sustainability, 12(1), 1-16. masten, a.b., coricelli, f., masten, i. (2008), non-linear growth effects of financial development: does financial integration matter? journal of international money and finance, 27(2), 295-313. mckinnon, r.i. (1974), money and capital in economic development. the economic journal, 84(334), 422-423. ngoc, b.h. (2019), energy consumption and economic growth nexus in vietnam: an ardl approach. in beyond traditional probabilistic methods in economics. in: kreinovich, v., thach, n., trung, n., van thanh, d., editors. beyond traditional probabilistic methods in economics. econvn 2019. studies in computational intelligence. vol. 809. cham: springer. p311-322. nguyen, h.m., ngoc, b.h. (2020), energy consumption-economic growth nexus in vietnam: an ardl approach with a structural break. the journal of asian finance, economics and business, 7(1), 101-110. okada, k. (2013), the interaction effects of financial openness and institutions on international capital flows. journal of macroeconomics, 35, 31-143. omri, a. (2014), an international literature survey on energy-economic growth nexus: evidence from country-specific studies. renewable and sustainable energy reviews, 38, 951-959. ono, s. (2017), financial development and economic growth nexus in russia. russian journal of economics, 3(3), 321-332. payne, j.e. (2009), on the dynamics of energy consumption and output in the us. applied energy, 86(4), 575-577. rafindadi, a.a., ozturk, i. (2016), effects of financial development, economic growth and trade on electricity consumption: evidence from post-fukushima japan. renewable and sustainable energy reviews, 54, 1073-1084. romer, p.m. (1990), endogenous technological change. journal of political economy, 95(5), 71-102. rousseau, p.l., vuthipadadorn, d. (2005), finance, investment, and growth: time series evidence from 10 asian economies. journal of macroeconomics, 27(1), 87-106. salahuddin, m., gow, j. (2016), the effects of internet usage, financial hoang: examining the relationship between electricity consumption, financial development and economic growth in asean countries: evidence from a bayesian analysis international journal of energy economics and policy | vol 11 • issue 2 • 202156 development and trade openness on economic growth in south africa: a time series analysis. telematics and informatics, 33(4), 1141-1154. sarkar, m.s.k., al-amin, a.q., mustapa, s.i., ahsan, m.r. (2019), energy consumption, co2 emission and economic growth: empirical evidence for malaysia. international journal of environment and sustainable development, 18(3), 318-334. schumpeter, j.a. (1912), the theory of economic development: harvard economic studies. shaw, e.s. (1974), financial deepening in economic development. the journal of finance, 29(4), 1345-1348. stern, d.i. (2000), a multivariate cointegration analysis of the role of energy in the us macroeconomy. energy economics, 22, 267-283. stiglitz, j.e. (2000), capital market liberalization, economic growth, and instability. world development, 28(6), 1075-1086. tang, c.f. (2009), electricity consumption, income, foreign direct investment, and population in malaysia. journal of economic studies, 36(4), 371-382. thompson, s.k. (2012), sampling. 3rd ed. hoboken, new jersey: john wiley & sons. inc. tiba, s., omri, a. (2017), literature survey on the relationships between energy, environment and economic growth. renewable and sustainable energy reviews, 69, 1129-1146. yoo, s.h. (2005), electricity consumption and economic growth: evidence from korea. energy policy, 33(12), 1627-1632. zhang, c., zhou, k., yang, s., shao, z. (2017), on electricity consumption and economic growth in china. renewable and sustainable energy reviews, 76, 353-368. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 3 • 2021100 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(3), 100-109. the influence of oil price fluctuations on stock market of developing economies: a focus on nigeria chuke nwude1, damilola felix eluyela2, elias igwebuike agbo1, francis o. iyoha3* 1department of banking and finance, faculty of business administration, university of nigeria, nigeria, 2department of accounting and finance, landmark university, nigeria, 3department of accounting, college of business and social sciences, covenant university, nigeria. *email: iyoha.francis@covenantuniversity.edu.ng received: 22 june 2020 accepted: 28 december 2020 doi: https://doi.org/10.32479/ijeep.10140 abstract the inconclusiveness of findings from various studies on nigeria on the effect of crude oil price fluctuation on the stock market has led to an argument in literature, thus necessitating further exploration of the subject. this study examines the effect of variations in the price of crude oil on selected stock market performance variables in nigeria using monthly frequency data covering january 1997-december 2016. variance decomposition, impulse response analysis, and var estimations were employed for the study. the results reveal that oil price variations are slowly transmitted in some stock market performance variables. the findings indicate that the effect of crude oil price fluctuations in the nigerian stock market is greatly minimized and does not sufficiently account for market activities. keywords: emerging economy, nigeria, oil price shocks, stock market, vector autoregressive jel classifications: c25, q47, f4 1. introduction this study aims to examine whether fluctuations in crude oil price impact on stock market performance in developing economy from january 1997 to december 2016. nigeria is used as a proxy for developing economies because she is the sixth largest member of opec and the largest net exporter of crude oil in africa but also a highly promising economy for international portfolio diversification. in many industrialized economics, the production process uses crude oil as an essential raw material. because of this, its demand is highly presumed to correlate with the growth of industrial production of many economies. from the economic perspective, higher demand for any commodity without marching increase in its supply paves the way for its price appreciation. similarly, the cash flow of producing firms will be affected by an increase in raw material required in the production process. nigeria exports crude oil and imports refined crude oil from international markets. it is assumed that any apparent movements in the international oil market will affect some macroeconomic variables which can affect the performance of the stock market. considering the producer (exporter) and consumer (importer) nature of nigeria, an increase in oil prices will likely affect the cash flow of companies and individuals. corporate earnings will be subdued, which may lead to falling investors’ appetite towards investing in the capital market. therefore, investigating the effect of oil price movements on the stock market performance is a study worth engaging. in nigeria, the increase in crude oil price at international markets usually attracts more money into the federation account. as a result, more money is released to government tiers, which will put pressure on the inflation rate and exchange rate. the question here is; does this reflect in the performance of the stock market? various studies on the effect of crude oil price fluctuation on the stock market in nigeria show mixed results. for instance, omisakin et al. (2009), mordi et al. (2010), abbas and terfa (2010), adebiyi et al. this journal is licensed under a creative commons attribution 4.0 international license nwude, et al.: the influence of oil price fluctuations on stock market of developing economies: a focus on nigeria international journal of energy economics and policy | vol 11 • issue 3 • 2021 101 (2010), akomolafe and danladi (2014), akinlo (2014), iheanacho (2016), lawal et al. (2018), soyemi et al. (2017), ojikutu et al. (2017), obi et al. (2018) observe a positive effect of oil price shock on the stock price. on the contrary, studies like adaramola (2012) and effiong (2014) reported an inverse correlation between the price of oil movements and returns from stocks. for okany (2014), the two constructs do not react to each other. however, babatunde et al. (2013) and effiong (2014) recorded a very weak relationship oil price shock and stock price in nigeria. this inconclusiveness of findings has created much doubt in literature. this study is an effort aimed at providing further insight into the subject. the study’s significance lies in its ability to generate results that will improve the forecasting accuracy of stock market behavior from crude oil price variations, which will aid investors and policymakers in decision making. this study’s latest year with valid, accurate data was 2016 while the commencement year 1997 was the period the journey to stable leadership in nigeria started. the stability of leadership of any nation says much about the functioning of various organs of the economy which includes the stock market. the remainder of the study is presented; thus, section 2 presents the literature review, while section 3 indicates the material and methods adopted in the study. section 4 reports the empirical results and discussion, while section 5 is the conclusion. 2. literature review conceptually, oil price shock or fluctuation refers to unanticipated changes in the prices of oil. in the wake of the oil price shocks of the 19,970, there emerged a body of literature that started growing and interrogating the effect oil prices changes have on the real economic activity. among the early researchers that probed the oil price and aggregate economy nexus is hamilton (1983) who emerged with the finding that fluctuations in the price of oil precipitated ten out of the eleven post-war recessions in the united states up to 1983. this motivated many scholars to carry out similar investigations. oil price shocks usually cause some increases in the general price levels and a significant decrease in productivity. thus, fluctuation in oil price is seen as a key ingredient for forecasting the capital market activities. still, research has provided conflicting results, and several authors have disagreed with their findings on the nature of the nexus between oil price and the stock market. the conflicts in results have left doubt which this study intends to investigate in an emerging market economy. while crude oil is considered universally as the life-wire of every nation, stock markets are generally regarded as an engine of economic growth (uwubanmwen and omorokunwa, 2015). results of some empirical inquiries on the oil price movements and stock market connection are highlighted below. kilian and park (2009) observe that returns on stock in the usa react to movement in oil price whether as a result of supply or demand shocks. the authors further opine that shocks in oil prices impact stock returns. papapetrou (2001) argues that true economic activity, jobs and stock prices are a substantial reaction to changes in oil prices. others like jones and kaul (1996), sadorsky (1999), basher et al. (2012) and cunado and perez de gracia (2003) find a negative relationship, although faff and brailsford (1999) observe a positive link. a study on the effects of changes to oil prices on the australian paper and packaging and transportation industries was carried out by faff and brailsford (1989). the relationship between oil price and industries was significantly negative. jones and kaul (1996), conducted a similar study with a cash flow assessment model in the developed countries of the united states, canada, great britain and japan. the result showed an inverse connection between oil and stock prices. sadorsky (1999) studied the link between oil price volatility in the usa between 1947 and 1996 using var and garch modeling and established a strong correlation between oil price volatility and inventory return. the relationships between the fluctuation in oil prices and stock market between 13 european nations and the usa have been studied by park and rati (2008). the result showed a strong negative effect of oil price shock on the oil-importing countries and positive effect on the oil-exporting countries. magyereh et al. (2016) found no relationship between the stock market index returns of developing countries and oil price shocks and applying unrestricted vector autoregressive (var) approach on daily oil future returns and the daily us returns. it has also been observed that spot oil returns do lead some individual oil company stock returns (huang et al., 1996). still, general market indices are not much impacted by oil future returns. zhang (2017), nandha and faff (2008) confirm that large oil shocks occasionally contribute a big way to stock markets. 3. materials and methods 3.1. materials this study adopted an expo facto research design. the stock market data for the study were obtained from the nigeria stock exchange (nse) and central bank of nigeria (cbn) statistical bulletins. the data frequency is monthly from january 1st 1997 to december 31st 2016 and contains naira dominated value-weighted stock market indices. the stock market variables which form our dependent variables consist of market capitalization, all-share index, the market value of shares traded, the market volume of shares traded, average closing price and several deals. market capitalization is the monthly sum of all the listed firms on the nse as documented by the nse. all-share index is the barometer that measures the strength of the stock market in terms of share price appreciations and depreciation in the market. the market value of shares traded is the product of the number of shares traded on each stock multiply by the market price per share. market volume of shares traded presents the number of shares traded on the nse for all the listed firms. the average closing price is the monthly mean market price per share of each stock for all the listed firms. several deals are the monthly sum of individual transactions on all the listed stocks. in all the above-mentioned stock market variables were collected from the nse and central bank of nigeria statistical bulletins. the crude oil price data were sourced from us energy information administration data stream (2018), and this encompasses spot historical prices of brent crude oil from january 1997 to december 2016. this variable was employed as our independent variable to measure oil price shocks’ effect on some selected stock market variables. we choose to use the brent spot nwude, et al.: the influence of oil price fluctuations on stock market of developing economies: a focus on nigeria international journal of energy economics and policy | vol 11 • issue 3 • 2021102 crude oil price indices rather than other local oil price or other oil prices such as west texas intermediate and dubai-serve for several reasons. first, brent spot crude oil price was expressed in u.s. $/barrel. second, brent spot crude oil price measures the spot price of various oil barrels, which are quoted in the global oil market. thirdly, brent oil serves as a benchmark in the crude oil market. however, consistent with convention, all data used in this study were transformed by taking the raw data’s natural logarithm. the control variables that captured and factored nigerian economic moods in this study are the exchange rates and the inflation rates, which are quite high compared to developed economies. 3.2. methods the study employed vector autoregressive (var) model to estimate the effect of oil price shocks on selected stock market variables. this enables the endogeneity of all remaining variables tested when oil price shocks are introduced as exogenous variables. the appropriate diagnostic tests were used to ascertain the linear or non-linear effects of crude oil price shocks on some selected stock market variables. we conducted unit root based on augmented dickey-fuller and phillips and perron to verify the order of integration of the variables. extant literature is on the position that var modelling employs a series of unit root tests to ensure our variables are integrated on the order of one 1(1). we employed the akaike information criterion (aic), and schwarz bayesian criterion (sbc) to determine the appropriate number of lag length of the var model. however, the study employed the variance decomposition and impulse response functions to analyze the variables’ short-run dynamics. 4. empirical results and discussion 4.1. descriptive statistics table 1 demonstrates that all the variables selected for the study have positive mean values. the standard deviation of the all-share index (9.171) is the highest among the variables, implying that it is the riskiest and most highly volatile period of study. the positive mean monthly oil price changes indicate an upward trend during the study period. the mean value of the all-share index is 99544.04 points for the 240 months and the highest. market capitalization and several deals equally exhibited high variability during the period. probably, the innovation in these selected stock market variables in nigeria has been fueled by the unstable money supply regimes and the frequent movements in the international oil price. according to this summary statistics, the average monthly closing price fluctuated rather slowly during the period. the negative value of skewness for our data set revealed that the data points are clustered to the left side of the mean, except lnappa with a positive cluster which implies that data points are skewed to the right of the data average. the variables indicated that the data are not normally distributed as a result of sets of data not balanced normal distribution (skewness of zero), except for lnnod that the data are normally distributed. confirming the above analytics, kurtosis results in table 1 showed that the variables are not normally distributed which revealed symmetric distribution with no well-behaved tails excluding lnappb, lnnod and voppb with more than the expected value of 3 indicating that symmetric distribution is well-behaved. although kurtosis confirmed that all the variables are heavily-tailed distribution with positive expected values, though, jarque-bera test statistic of our dataset exceeds the critical value of 5% significance level, resulting in the conclusion that the adopted variables follow a normal distribution. 4.2. tests for stationarity to determine the stationarity of the employed variables, the result of unit root tests in table 2 shows the order of integration (does not have unit root). traditionally, the null hypothesis assumes that variables have a unit root. the outcomes for the unit root test are based on the assumption of augmented dickey-fuller (adf) and phillips and perron (pp) are attained at 5% level of significance. however, the decision rule for the position to accept the null hypothesis that the variable has a unit root or does not support the outcome of the two statistical tests. the outcomes from table 2 above revealed that the employed variables attained stationarity (does not have unit root), but these were obtained at the first difference. based on the above outcomes, the study rejects the null hypothesis assumption of augmented dickey-fuller (adf) and phillips and perron (pp). it concludes that our employed variables do not have a unit root. nevertheless, stationarity was attained at 1(1), but none of the variables attained stationarity at 1(2). on this note, the overall outcomes satisfy the condition for johansen cointegration test since all the variables attained stationarity after first differencing. the outcomes of the johansen cointegration test was subject to satisfying the precondition for running cointegration model, which states that variables must be nonstationary at the level. still, when the variables are converted into the first difference, then they become stationary. this position was table 1: descriptive statistics variable mean maximum minimum std. dev. skewness kurtosis jarque-bera lnoppb 3.828 4.897 2.282 0.683 −0.318 2.052 11.352 %∆oppb 0.802 25.080 −26.910 9.171 −0.340 3.115 4.146 lnappb 3.257 4.993 2.283 0.3754 0.629 5.957 89.914 lnmc 7.819 9.549 5.375 1.422 −0.433 1.614 23.279 lnmvalue 23.316 26.369 19.755 1.601 −0.538 2.066 17.677 lnmvol 21.049 23.723 17.332 1.528 −0.388 2.013 13.718 lnnod 10.838 12.885 2.493 1.478 −2.323 11.396 801.933 lnnseasi 9.854 11.051 8.495 0.694 −0.522 2.105 16.490 source: researcher’s estimation using e-view. lnappb: natural log of average closing oil price per barrel in us$, lnoppb: natural log of oil price per barrel in us$ at month-end, %∆oppb: percentage change in oil price per barrel in us$, lnmc: natural log of market capitalization in billion naira, lnnseasi: natural log of nigerian stock exchange all-share index, lnmvol: natural log of the market volume of trade, lnmval: natural log of market value of trade in naira, lnnod: natural log of number of deals or trades. nwude, et al.: the influence of oil price fluctuations on stock market of developing economies: a focus on nigeria international journal of energy economics and policy | vol 11 • issue 3 • 2021 103 highlighted in the previous section, where employed variables attained stationarity after first difference. the outcomes for the trace test and the max-eigen value test both indicate the existence of no cointegration at 5% level. this implies that the variables of the study have no long-run equilibrium relationships among themselves. however, the johansen cointegration test’s outcome led to the employment of the unrestricted var model in favour of vector error correction model (vecm). 4.3. var model estimation 4.3.1. var model estimates using oil price per barrel the outcome from table 3 indicates a significant influence of crude oil price on itself which implies that the variable is strongly endogenous but has a strongly exogenous influence on other employed variables, that is, the crude oil price has a weak influence on dependent variables. although, exceptional among the variables is nse all-share index that appeared to be least exogenous, which implies that crude oil price has a strong influence on nse all-share index. the result of var estimation showed that average closing oil price per barrel has strong endogeneity since the variable has a significant influence on itself. the influence of average closing table 3: var model estimates using oil price per barrel lnoppb lnappb lnmc lnmvalue lnmvol lnnod lnnseasi lnoppbt−1 1.136 (14.625) 0.006 (0.030) 0.380 (1.803) −0.241 (−0.371) 0.153 (0.201) −0.082 (−0.089) 0.151 (1.989) lnoppbt−2 −0.216 (−2.781) 0.019 (0.090) −0.262 (−1.243) 0.399 (0.614) −0.078 (−0.103) 0.167 (0.180) −0.121 (−1.602) lnappbt−1 −0.012 (−0.439) 0.466 (6.113) 0.038 (0.501) −0.022 (−0.094) 0.199 (0.717) −0.045 (−0.133) 0.056 (2.017) lnappbt−2 −0.040 (−1.371) 0.381 (4.791) 0.007 (0.089) 0.116 (0.467) 0.153 (0.527) −0.803 (−2.281) −0.025 (−0.885) lnmct−1 0.037 (1.186) 0.053 (0.626) 0.276 (3.250) −0.076 (−0.291) −0.215 (−0.701) −0.142 (−0.380) 0.046 (1.499) lnmct−2 −0.018 (−0.579) −0.073 (−0.852) 0.654 (7.571) −0.052 (−0.194) 0.174 (0.555) 0.079 (0.206) −0.057 (−1.823) lnmvaluet−1 0.005 (0.477) 0.003 (0.108) 0.012 (0.418) 0.375 (4.148) 0.202 (1.907) 0.074 (0.578) 0.012 (1.123) lnmvaluet−2 0.005 (0.418) 0.020 (0.662) 0.006 (0.211) 0.292 (3.183) 0.279 (2.599) −0.144 (−1.097) 0.006 (0.543) lnmvolt−1 0.005 (0.569) −0.002 (−0.080) −0.007 (−0.301) 0.146 (1.972) 0.322 (3.708) −0.003 (−0.032) −0.004 (−0.431) lnmvolt−2 −0.005 (−0.602) −0.005 (−0.202) 0.020 (0.819) −0.023 (−0.314) −0.009 (−0.109) 0.028 (0.266) 0.006 (0.647) lnnodt−1 −0.005 (−0.775) −0.002 (−0.144) 0.050 (2.858) 0.027 (0.498) −0.035 (−0.557) 0.036 (0.465) 0.010 (1.538) lnnodt−2 −0.002 (−0.320) −0.020 (−1.127) −0.004 (−0.238) 0.054 (0.986) 0.109* (1.699) 0.257* (3.299) −0.002 (−0.254) lnnseasit−1 0.127 (1.455) −0.095229 (−0.40547) 0.457221 (1.93784) −0.327279 (−0.44842) −1.826236 (−2.1384) 2.690449 (2.58740) 0.759094 (8.92865) lnnseasit−2 −0.107 (−1.271) 0.136 (0.600) −0.579 (−2.543) 0.774 (1.100) 1.966 (2.386) −1.501 (−1.496) 0.174 (2.123) c −0.056 (−0.191) 0.487 (0.619) −1.913 (−2.465) 7.509 (3.169) 9.049 (3.270) −2.196 (−0.630) −0.283 (−0.996) r-squared 0.984 0.624 0.973 0.783 0.675 0.540 0.985 adj. r-squared 0.982 0.591 0.970 0.764 0.647 0.500 0.984 sum sq. resids 1.232 8.992 9.075 86.837 118.897 176.262 1.178 s.e. equation 0.091 0.245 0.246 0.761 0.890 1.084 0.089 f-statistic 691.532 19.126 412.563 41.674 24.003 13.534 772.771 log likelihood 168.358 5.385 4.629 −180.567 −206.334 −238.619 172.029 akaike aic −1.882 0.105 0.114 2.373 2.687 3.081 −1.927 schwarz sc −1.618 0.370 0.379 2.637 2.952 3.345 −1.663 mean dependent 3.827 3.265 7.861 23.346 21.078 10.862 9.875 s.d. dependent 0.679 0.383 1.431 1.567 1.499 1.533 0.701 table 3 is oil price per barrel. the underlying cointegrated var model is of order 2, contains unrestricted intercepts, and lag order was selected using akaike information criterion (aic). standard errors generated from none replications and factorization is based on cholesky decomposition. we do capture the out of sample dynamics in the subsequent impulse responses. table 2: stationarity results variable aaugmented dickey‑fuller (adf) aphillips and perron (pp) order of integration lnoppb −19.32647*** −18.99767*** 1 (1) %∆oppb −11.36989*** −94.20518*** 1 (1) lnappb −14.42972*** −30.30106*** 1 (1) lnmc −12.70675*** −28.63905*** 1 (1) lnmvalue −12.44347*** −38.51012*** 1 (1) lnmvol −13.98515*** −84.53476*** 1 (1) lnnod −11.13418*** −100.0612*** 1 (1) lnnseasi −15.98697*** −15.89726*** 1 (1) source: researcher’s estimation using e-view. lnappb: natural log of average closing oil price per barrel in us$, lnoppb: natural log of oil price per barrel in us$ at month-end, %∆oppb: percentage change in oil price per barrel in us$, lnmc: natural log of market capitalization in billion naira, lnnseasi: natural log of nigerian stock exchange all-share index, lnmvol: natural log of the market volume of trade, lnmval: natural log of market value of trade in naira, lnnod: natural log of number of deals or trades nwude, et al.: the influence of oil price fluctuations on stock market of developing economies: a focus on nigeria international journal of energy economics and policy | vol 11 • issue 3 • 2021104 oil price per barrel on other variables recorded weak influence, which implies that the variable is strongly exogenous. our observation for market capitalization revealed that this variable is weakly endogenous and least exogenous, that is, natural log of market capitalization has a weak influence on itself and strong influence from nse all-share index and crude oil price. the outcome for the natural log of the market value of trade was the same as that of market capitalization. similarly, we also observed that natural log of market volume of trade and the natural log of deals traded are weakly endogenous, least exogenous and strongly endogenous to other variables. nse all-share index has a significant influence on itself which implies that this variable is strongly endogenous but has a strongly exogenous on other employed variables, that is, nse all-share index has a weak influence on dependent variables. the results align with existing literature. in the diagnostic tests conducted, it was observed that most of the variables used are not normally distributed and heteroscedastic. 4.3.2. var model estimates using percentage change in oil price per barrel the var estimation, as revealed in table 4, depicted significant outcomes. we observed that percentage variation in the price per barrel of oil recorded a weak influence on itself on lag 1 and 2. this is an indication that percentage variation in the price per barrel of oil is weakly endogenous when lagged by 2 periods. the percentage variation in the price per barrel of oil appeared to have strong endogeneity on the average closing oil price per barrel, natural log of market capitalization, and the natural log of nse all-share index. this implies that it has a strong influence on these highlighted variables but a weak influence on the other variables. for the estimation on the average closing oil price per barrel, we ascertained that this variable is weakly endogenous, which implies that average closing oil price per barrel has a weak influence on itself on the lagged period. the influence of average closing oil price per barrel on the other variables shows that the variable is strongly exogenous, indicating a weak influence on the dependent variables and other variables. table 4: var model estimates using percentage change in oil price per barrel %∆oppb lnappb lnmc lnmvalue lnmvol lnnod lnnseasi %∆oppbt−1 0.044* (0.554) −0.002*** (−0.903) 0.003*** (1.370) −0.001*** (−0.183) 0.004*** (0.549) −0.003*** (−0.355) 0.001*** (1.066) %∆oppbt−2 −0.064* (−0.836) 0.001*** (0.534) 0.002*** (1.021) 0.005*** (0.762) 0.006*** (0.796) 0.012*** (1.224) 0.002*** (2.915) lnappbt−1 −2.518 (−0.909) 0.458* (5.909) 0.058* (0.746) −0.065 (−0.276) 0.192 (0.708) 0.0181 (0.053) 0.066** (2.435) lnappbt−2 −3.585 (−1.288) 0.357* (4.575) 0.003* (0.038) 0.036 (0.150) 0.073 (0.266) −0.778 (−2.256) −0.027 (−1.007) lnmct−1 1.453 (0.475) 0.052* (0.610) 0.230* (2.702) 0.087 (0.336) −0.029 (−0.095) −0.217 (−0.574) 0.030** (1.021) lnmct−2 −2.484 (−0.781) −0.043* (−0.480) 0.620* (7.001) 0.280 (1.037) 0.565 (1.809) 0.037 (0.095) −0.051 (−1.659) lnmvaluet−1 0.051 (0.048) 0.002** (0.072) 0.030** (1.014) 0.324* (3.590) 0.149 (1.430) 0.098 (0.744) 0.015*** (1.463) lnmvaluet−2 −0.002 (−0.002) 0.012** (0.401) 0.021** (0.685) 0.211* (2.295) 0.199 (1.872) −0.125 (−0.932) 0.008*** (0.751) lnmvolt−1 0.571 (0.660) −0.007** (−0.271) 0.003** (0.112) 0.107* (1.454) 0.269* (3.163) −0.003 (−0.024) −0.004*** (−0.509) lnmvolt−2 −0.286 (−0.33) −0.005** (−0.219) 0.033** (1.369) −0.050* (−0.679) −0.053* (−0.632) 0.062 (0.586) 0.010*** (1.234) lnnodt−1 −0.296 (0.479) −0.002** (−0.130) 0.046** (2.684 0.048* (0.909) −0.010* (−0.169) 0.033* (0.427) 0.009*** (1.486) lnnodt−2 −0.622 (−0.992) −0.020** (−1.116) −0.007** (−0.390) 0.064* (1.200) 0.121* (1.965) 0.259* (3.334) −0.001 (−0.205) lnnseasit−1 8.122 (0.974) −0.120 (−0.512) 0.505 (2.174) −0.308 (−0.436) −1.794 (−2.191) 2.662 (2.578) 0.757* (9.337) lnnseasit−2 −5.594 (−0.657) 0.150 (0.631) −0.429 (−1.808) 0.158 (0.219) 1.112 (1.329) −1.276 (−1.209) 0.212* (2.559) c 7.705 (0.277) 0.372 (0.476) −2.094 (−2.699) 7.147 (3.021) 8.864 (3.238) −2.712 (−0.785) −0.397 (−1.464) r-squared 0.076 0.625 0.974 0.796 0.700 0.543 0.987 adj. r-squared −0.011 0.590 0.971 0.777 0.671 0.500 0.985 sum sq. resids 11318.08 8.879 8.776 81.584 109.214 173.739 1.070 s.e. equation 8.7155 0.244 0.243 0.740 0.856 1.080 0.085 f-statistic 0.870 17.757 393.541 41.573 24.781 12.652 777.826 log likelihood −579.918 6.425 7.379 −175.451 −199.368 −237.436 179.945 akaike aic 7.255 0.105 0.093 2.323 2.614 3.078 −2.012 schwarz sc 7.539 0.388 0.376 2.606 2.898 3.362 −1.728 mean dependent 1.884 3.269 7.860 23.346 21.072 10.851 9.869 s.d. dependent 8.667 0.381 1.430 1.567 1.493 1.527 0.697 table 4 is the percentage change in oil price per barrel. the underlying cointegrated var model is of order 2, contains unrestricted intercepts, and lag order was selected using akaike information criterion (aic). standard errors generated from none replications and factorization is based on cholesky decomposition. we do capture the out of sample dynamics in the subsequent impulse responses nwude, et al.: the influence of oil price fluctuations on stock market of developing economies: a focus on nigeria international journal of energy economics and policy | vol 11 • issue 3 • 2021 105 table 5: variance decompositions using oil price per barrel horizon s.e. lnoppb lnappb lnmc lnmvalue lnmvol lnnod lnnseasi shock to lnoppb, explained by innovations in 1 0.091 100.00 0.000 0.000 0.000 0.000 0.000 0.000 4 0.201 94.390 1.720 1.324 1.490 0.037 0.160 0.880 8 0.2684 84.249 7.179 2.570 4.515 0.107 0.134 1.246 16 0.340 68.770 14.885 4.757 8.142 0.304 0.851 2.291 shock to lnappb, explained by innovations in 1 0.245 0.0003 100.00 0.000 0.000 0.000 0.000 0.000 4 0.325 0.031 98.697 0.216 0.316 0.027 0.611 0.102 8 0.376 0.148 96.990 0.303 1.283 0.028 1.162 0.087 16 0.412 0.550 93.902 0.659 3.152 0.024 1.372 0.341 shock to lnmc, explained by innovations in 1 0.246 0.202 0.032 99.766 0.000 0.000 0.000 0.000 4 0.355 2.823 0.281 89.149 1.121 0.248 4.825 1.554 8 0.456 4.937 0.326 83.216 4.348 0.577 5.441 1.155 16 0.587 9.343 1.858 71.236 9.521 0.929 5.972 1.141 shock to lnmvalue, explained by innovations in 1 0.761 0.004 5.599 0.142 94.254 0.000 0.000 0.000 4 0.972 0.175 4.431 0.227 91.769 2.390 0.782 0.226 8 1.085 0.922 3.581 0.278 88.908 2.407 1.453 2.452 16 1.230 3.811 2.805 0.396 79.701 2.025 1.538 9.723 shock to lnmvol, explained by innovations in 1 0.890 1.355 0.0002 0.434 16.443 81.768 0.000 0.000 4 1.084 1.204 0.077 1.288 31.896 62.600 0.878 2.056 8 1.170 1.307 0.270 1.119 38.872 54.090 1.420 2.922 16 1.280 3.139 0.539 1.007 40.847 45.362 1.462 7.643 shock to lnnod, explained by innovations in 1 1.084 0.080 0.081 0.122 0.013 0.019 99.685 0.000 4 1.183 0.436 2.047 0.387 0.837 0.075 90.685 5.534 8 1.235 0.989 5.424 0.704 0.970 0.086 84.310 7.517 16 1.287 1.651 7.487 0.782 1.853 0.098 78.114 10.015 shock to lnnseasi, explained by innovations in 1 0.089 2.172 0.526 5.984 1.551 0.309 0.381 89.077 4 0.163 7.740 2.349 7.802 7.226 0.265 2.063 72.555 8 0.227 9.795 1.938 5.483 16.666 0.234 2.354 63.530 16 0.322 11.922 1.304 2.939 27.047 0.316 2.284 54.188 table 5 is oil price per barrel. the underlying cointegrated var model is of order 2, contains unrestricted intercepts, and lag order was selected using akaike information criterion (aic). standard errors generated from none replications and factorization is based on cholesky decomposition. we do capture the out of sample dynamics in the subsequent impulse responses market capitalization results, the market value of share traded, the market volume of share traded, number of deals, and the nse allshares index are weakly endogenous on themselves for the lagged period, which implies that the variables have weak influence on themselves. however, these variables recorded weak influence on other employed variables which is an indication that the variables are strongly exogenous. though except for the market volume of share traded and several deals that recorded strong influence on nse all-shares index, which implies that these variables are strongly endogenous with nse all-shares index. for the validity of var results, the researchers carried out diagnostic tests. most of the employed variables are not normally distributed, and the result showed the presence of heteroscedasticity. the outcomes for variance decompositions for our first model in both the short and the long horizons showed that price per barrel of oil is a strong predictor of itself but does not predict other variables as the total forecasted values for all the variables in the whole period is less than the predicted value of itself in the first period. this outcome for oil price per barrel is in line with our outcome for var estimation where we found oil price per barrel to be strongly endogenous on itself and strongly exogenous on other variables. in the same pattern, average closing oil price per barrel is a strong predictor of itself and does not predict other variables. this outcome did not deviate with our observation on var estimation. market capitalization followed the same pattern; as a result, showed that this variable is a strong predictor of itself and does not predict other variables. this outcome did not deviate with our observation on var estimation. however, the outcomes for the remaining employed variables followed the same pattern as we observed that these variables are a strong predictor of themselves, and they do not forecast the outcomes of the other variables. in table 6 as shown above, in both short and long-run horizon, we ascertained that percentage change in oil price per barrel predict itself and does not forecast the short-run and long-run variation of other employed variables. also, average closing oil price per barrel predict itself and does not predict variation in other employed variables. in the same pattern, market capitalization, the market value of share traded, the market volume of share traded, number of deals and nse all-share index predicted the variation of themselves. still, these variables do not forecast the outcomes nwude, et al.: the influence of oil price fluctuations on stock market of developing economies: a focus on nigeria international journal of energy economics and policy | vol 11 • issue 3 • 2021106 table 6: variance decompositions for the percentage change in oil price per barrel horizon s.e. %∆oppb lnappb lnmc lnmvalue lnmvol lnnod lnnseasi shock to %∆oppb, explained by innovations in 1 8.716 100.00 0.000 0.000 0.000 0.000 0.000 0.000 4 8.938 95.444 2.556 0.579 0.172 0.225 0.485 0.539 8 8.995 94.241 3.674 0.660 0.174 0.222 0.487 0.541 16 9.024 93.643 4.202 0.715 0.190 0.221 0.491 0.538 shock to lnappb, explained by innovations in 1 0.244 0.395 99.605 0.000 0.000 0.000 0.000 0.000 4 0.321 1.073 97.857 0.254 0.043 0.120 0.534 0.119 8 0.362 1.036 97.266 0.348 0.122 0.175 0.952 0.100 16 0.383 0.988 96.853 0.569 0.290 0.178 1.025 0.097 shock to lnmc, explained by innovations in 1 0.243 0.303 0.044 99.652 0.000 0.000 0.000 0.000 4 0.345 1.857 0.301 84.635 5.268 1.119 4.307 2.513 8 0.452 2.600 0.207 73.754 12.805 1.775 5.364 3.496 16 0.596 3.837 0.367 60.772 19.718 1.999 6.601 6.705 shock to lnmvalue, explained by innovations in 1 0.740 0.014 6.692 0.940 92.354 0.000 0.000 0.000 4 0.870 0.258 6.498 3.220 86.519 1.106 2.267 0.131 8 0.930 0.591 6.524 7.408 80.134 1.230 3.786 0.327 16 1.003 1.278 6.519 12.110 72.536 1.427 4.716 1.415 shock to lnmvol, explained by innovations in 1 0.856 0.722 5.68e-06 0.008 12.987 86.284 0.000 0.000 4 0.968 0.677 0.112 2.995 18.553 73.039 1.906 2.717 8 1.015 0.700 0.218 7.849 19.070 66.589 3.007 2.567 16 1.072 0.905 0.561 13.149 19.274 59.983 3.722 2.405 shock to lnnod, explained by innovations in 1 1.080 0.059 0.042 0.035 0.002 0.049 99.813 0.000 4 1.184 1.613 1.610 0.138 1.233 0.257 89.772 5.378 8 1.240 2.410 4.263 0.261 1.959 0.310 82.786 8.011 16 1.299 3.197 5.272 0.265 3.390 0.311 75.822 11.744 shock to lnnseasi, explained by innovations in 1 0.085 0.964 0.472 5.214 2.246 0.345 0.124 90.634 4 0.160 6.825 2.725 5.656 10.613 0.395 1.398 72.387 8 0.226 8.520 2.109 4.599 18.508 0.326 1.859 64.078 16 0.312 9.219 1.399 4.472 23.792 0.321 2.534 58.262 table 6 is the percentage change in oil price per barrel. the underlying cointegrated var model is of order 2, contains unrestricted intercepts, and lag order was selected using akaike information criterion (aic). standard errors generated from none replications and factorization is based on cholesky decomposition. we do capture the out of sample dynamics in the subsequent impulse responses of the other variables. though the forecasted values themselves, and that of other variables vary significantly. these highlighted results for variance decompositions are in line with our observation on var estimation on the employed variables. the results are consistent with existing literature. the results of variance decomposition analysis and impulse response function provide the same conclusions regardless of the order of decomposition since their estimation is independent of the ordering. 4.4. implication of the results figures 1 and 2 plot the responses of each of the employed variables to a one standard error shock in the other variable. this is presented in the appendix section. the figures show that variations in the price of crude oil in the market are slowly transmitted to some selected stock market variables. the nigerian stock market responds to the global crude oil price shock some months after the shock. the response to the shock may be attributed to inflation and foreign exchange policy of the nation. these results show the inefficiency of the nigeria stock market in transmitting shocks in the international crude oil market. the situation is also reflected in the international crude oil market as the outcomes of our var estimations and variance decompositions indicate. the insignificant responses of the selected stock market performance variables to price shock in international crude oil market show the weak influence of the selected stock market variables in nigeria in the international crude oil market. the result is consistent with that of mordi et al. (2010), al hayky and naim (2016) and ojikutu et al. (2017). 5. conclusions this study examined the effect of oil price shock on selected performance variables in the nigerian stock market. vector autoregression (var) analysis was carried on monthly data for the period, january 1, 1997, to december 31, 2016. this study utilized variance decomposition and impulse response analysis to compliment var estimations for the models. in line with the existing empirical literature, the results from var estimation nwude, et al.: the influence of oil price fluctuations on stock market of developing economies: a focus on nigeria international journal of energy economics and policy | vol 11 • issue 3 • 2021 107 revealed that international crude oil price is strongly exogenous to nigerian stock market performance variables, which indicated that the oil price fluctuations in the international crude oil market have weak influence on stock market performance variables in nigeria. the results from the variance decomposition analysis also indicate a very weak relationship between the crude oil price shocks and stock market variables in nigeria. in the international crude oil market, the impulse analysis reveal that variation in oil price is slowly transmitted to the nigeria stock market. it is also established that crude oil price in the nigerian capital market is greatly minimized, and the effect does not sufficiently account for changes in the stock market activities. references abbas, t., terfa, w.a. (2010), the impact of oil price volatility on the nigerian stock market: evidence from autoregressive distributed lag model. a conference paper presented at nasarawa state university. adaramola, a.o. (2012), oil price shocks and stock market behavior: the nigerian experience. journal of economics, 3(1), 19-24. adebiyi, m.a., adenuga, a.o., abeng, m.o., omanukwue, p.n. (2010), oil price shocks, exchange rate and stock market behavior: empirical review from nigeria. available from: http://www.africanetics.org/document/conference09/papers/ adebiyi͜ adenuga͜abeng ͜omanukwue.pdf. akinlo, o.o. (2014), oil prices and stock market: empirical evidence from nigeria. european journal of sustainable development, 3(2), 33-40. akomolafe, k.j., danladi, j.d. (2014), oil price dynamics and the nigerian stock market: an industry-level analysis. international journal of economics, finance and management, 3(6), 1-9. al hayky, a., naim, n. (2016), the relationship between oil price and stock market index: an empirical study from kuwait. in: presented at middle east economic association 15th international conference. babatunde, m.a., adenikinju, o., adenikinju, a.f. (2013), oil price shocks and stock market behaviour in nigeria. journal of economic studies, 40(2), 180-202. basher, s., haung, a., sadorsky, p. (2012), oil prices, exchange rates and emerging stock markets. energy economics, 34(1), 227-240. cunado, j., perez de gracia, f. (2003), do oil price shocks matter? evidence from some european countries. energy economics, 25, 137-154. effiong, e.l. (2014), oil shocks and nigeria stock market: what have we learned from crude oil market shocks? oxford: john wiley and sons ltd., opec. p36-38. faff, r.w., brailsford, t.j. (1999), oil price risk and the australian stock market. journal of energy finance and development, 4(1), 69-87. hamilton, j.d. (1983), oil and the macro-economy since world war ii. journal of political economy, 91, 228-248. huang, r., musulis, r., stoll, h. (1996), energy shocks and financial markets. journal of futures markets, 16(1), 1-27. iheanacho, e. (2016), the dynamic relationship between crude oil price, exchange rate and stock market performance in nigeria. international multidisciplinary journal, 10(4), 224-240. jones, c.m., kaul, g. (1996), oil and the stock markets. journal of finance, 51, 463-491. kilian, l., park, c. (2009), the impact of oil price shocks on the us stock market. international economic review, 50(4), 1267-1287. lawal, a.i., babajide, a.a., nwanji, t.i., eluyela, d. (2018), are oil prices mean reverting? evidence from unit root tests with sharp and smooth breaks. international journal of energy economics and policy, 8(6), 292-298. magyereh, a.i., awartani, b., bouri, e. (2016), the directional volatility connectedness between crude oil and equity markets: new evidence from implied volatility indexes. energy economics, 57, 78-93. mordi, c.n.o., michael, a., adebiyi, a.m. (2010), the asymmetric effects of oil price shock on output and prices in nigeria using a structural var model. economic and financial review, 481, 1-32. nandha, m., faff, r. (2008), does oil move equity prices? a global view. energy economics, 30, 986-997. obi, b., oluseyi, a.s., olaniyi, e. (2018), impact of oil price shocks on stock market prices volatility in nigeria: new evidence from a nonlinear ardl co-integration. journal of global economy, 14(3), 1-17. ojikutu, o.t., onolemhemhen, r.u., isehunwa, s.o. (2017), crude oil price volatility and its impact on nigeria stock market performance (1985-2014). international journal of energy economics and policy, 7(5), 302-311. okany, c.t. (2014), effect o0f oil price movement on stock prices in the nigerian equity market. research journal of finance and accounting, 5(15), 1-15. omisakin, o., adeniyi, o., omojolaibi, a. (2009), a vector error correction modelling of energy price volatility of an oil-dependent economy: the case of nigeria. pakistan journal of social sciences, 6(4), 207-213. papapetrou, e. (2001), oil price shocks, stock market, economic activity and employment in greece. energy economics, 23(5), 511-532. park, j., ratti, r.a. (2008), oil price shocks, stocks market in the u.s. and 13 european countries. energy economics, 30(5), 2587-2068. sadorsky, p. (1999), oil price shocks and stock market activity. energy economics, 21, 449-469. soyemi, k.a., akingunola, r.o., ogebe, j. (2017), effects of oil price shock on stock returns of energy firms in nigeria. kasetsart journal of social sciences, 30, 1-8. u.s. energy administration. (2018), list of countries by oil production. available from: https://www.en.wikipedia.org/wiki/list-of-counriesby-oil-production. uwubanmwen, a.e., omorokunwa, o.g. (2015), oil price volatility and stock price volatility: evidence from nigeria. academic journal of interdisciplinary studies, 4(1), 253. zhang, d. (2017), oil shocks and stock markets re-visited: measuring connectedness from a global perspective. energy economics, 62, 323-333. nwude, et al.: the influence of oil price fluctuations on stock market of developing economies: a focus on nigeria international journal of energy economics and policy | vol 11 • issue 3 • 2021108 appendix figure 1: impulse response for model 1 (oil price per barrel) nwude, et al.: the influence of oil price fluctuations on stock market of developing economies: a focus on nigeria international journal of energy economics and policy | vol 11 • issue 3 • 2021 109 figure 2: impulse response for model 2 (percentage change in oil price per barrel) tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 3 • 2021 395 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(3), 395-402. indonesia’s new sdgs agenda for green growth – emphasis in the energy sector suparjo suparjo1, surya darma2*, nia kurniadin1, jati kasuma3, priyagus priyagus4, dio caisar darma5, haryadi haryadi6 1department of geomatics technology, politeknik pertanian negeri samarinda, indonesia, 2department of agrotechnology, faculty of agriculture, mulawarman university, indonesia, 3faculty of business and management, universiti teknologi mara (sarawak branch), malaysia, 4department of economics, faculty of economics and business, mulawarman university, indonesia, 5department of management, sekolah tinggi ilmu ekonomi samarinda, indonesia, 6department of economics, faculty of economics and business, jambi university, indonesia. *email: surya_darma@faperta.unmul.ac.id received: 17 december 2020 accepted: 06 march 2021 doi: https://doi.org/10.32479/ijeep.11091 abstract the concept of green growth is one part of the realization of sustainable development. to support this mission, indonesia is taking part in global change by accelerating the development programs contained in the sdgs. we need to study green growth (gg) which is determined by the empowerment of the energy sector such as source of electric lighting (sel), renewable energy mix (rem), and primary energy intensity (pei) in indonesia. timeseries data were analyzed using ordinary least squares (ols) modeling in the 2015-2024 period. the result, of the three targeted hypotheses, only two can be accepted which are explained by sel and pei have a positive effect on gg. in another exploration, one hypothesis that was rejected was that rem had a negative effect on gg. the implications of this study are brought to the attention of our findings that have raised important points, especially in the sdgs document on the energy sector. keywords: sustainability, electric lighting, renewable energy, energy intensity, green growth, indonesia jel classifications: q56, l94, q42, q43, o13 1. introduction esquivel (2016) reflects on the “2030 agenda documents” published by large foundations and non-governmental organizations from all over the country that spend billions of dollars in budgets that have determined various aspects contained in the sustainable development goals (sgds). in addition, intergovernmental institutions that handle major financial and trade issues, especially from large countries, are influential actors who determine certain aspects of the sdgs. the designs in the millennium development goals (mdgs) have resulted in innovations, new partnerships, shown rapid progress, and dragged public opinion with ambitious goals (kumar et al., 2016). however, the limitations of the mdgs gave rise to sharp criticism of important development goals, so the sdgs were adopted to reflect the convergence that is getting stronger in the global development agenda (hulme, 2010). in addition, the sdgs also strengthen human rights, gender equality, and non-discrimination for the weak. the target of increasing economic growth of 9.2% is consistently considered the main driver of development and countries are expected to support this significantly. the relevance between gross domestic product (gdp) and the share of industrial jobs that are part of the sdgs, needs to focus on this (ruhil, 2017; rahman et al., 2019). the development mission can also be aligned by combining the subjects represented by the government, business this journal is licensed under a creative commons attribution 4.0 international license suparjo, et al.: indonesia’s new sdgs agenda for green growth – emphasis in the energy sector international journal of energy economics and policy | vol 11 • issue 3 • 2021396 people, and other private sectors with the object of development itself, namely the community. cappo and verity (2014) focuses on an inclusive paradigm defined as a “participatory concept,” in which they begin to be valued, involved, and their basic needs are met by considering local wisdom and community. in 2013, something surprising happened, because the population density is in a large number of cities in indonesia. as an illustration, the area of these big cities is proportional to the area of europe today. the general picture in figure 1 projects four major cities (dki jakarta, bandung, surabaya, and makassar) which qualify based on gdp growth and proportion of population density. the size of the map has also been adjusted with several other cities for comparison, achieving economic growth of around 7%/year. generally, cities that are classified as “developing” have a low growth category or <5% and the rest comes from the basis of “fast-growing” cities whose growth potential accounts for around 5% to 7%. we focused on the criteria of “developed cities” in surabaya, bandung, dki jakarta, and makassar which had gdp growth above 7%, which were more prominent because of high political support, trade advantages, human resource interests, infrastructure, geography, investment flows abundant, and other factors which caused particular attention to these cities. in essence, a transition to a “green” paradigm is urgently needed through fundamental changes as a consequence of shifting conventional gdp to green gdp. this requires a scenario that involves the transformation of social, economic, and environmental policies. a must integrate these three elements in a special policy. explicitly, it is necessary to formulate solutions that are appropriate and mutually beneficial. pasaribu (2013) emphasizes that a green perspective is not a new topic for indonesia. indonesia’s development strategy must refer to four important points in development, including pro-jobs, pro-growth, pro-environment, and pro-poor. the prediction by yusuf (2010) that takes into account the value of green gdp in indonesia has reduced the quality of the environment and also has an impact on the depletion of natural resources. the estimates indicated for the last several periods, green gdp growth in indonesia amounted to 87% of the total conventional gdp. in 2010, around idr 835 trillion was spent and spent on environmental costs. in the same year, the central government has budgeted the environmental costs of idr 900 trillion from the initial plan. given the vital role of sgds towards economic prosperity that takes into account environmental sustainability, we need to consider several goals in sgds related to the energy sector to support indonesia’s green economic growth. the composition of this article is arranged in several stages. the first section describes the background and objectives. the second part is the literature review that is relevant to the article. in the third section, outline the steps in the method. part four discusses the results and findings. next, part five is for confirmation of the conclusion. 2. literature review 2.1. mdgs versus sdgs the concept of environmentally friendly has been initiated since 2000 which involves the participation of all countries to agree on eight measurable and specific global elements related to development goals. the mdgs are the missionary responsibility of all components in the “millennium summit” for the togetherness of the government and its people (diouf, 2019). the mdgs are deemed to have failed to address sustainability in a complex manner. ideally, objectives that are relevant to the situation in some cases, eg extra measures to tackle climate change are not a “priority.” ranked 13th, climate change is considered figure 1: gdp growth and population density by cities in indonesia, 2030 source: agre (2020) suparjo, et al.: indonesia’s new sdgs agenda for green growth – emphasis in the energy sector international journal of energy economics and policy | vol 11 • issue 3 • 2021 397 less important and it shows relative importance by objective. vandemoortele (2018) explains that climate change is not among the top three priorities, so issues in the mdgs such as hunger, poverty, and child mortality raise questions about whether the three problems are urgent by the world today. the weaknesses in the mdgs are only aimed at developing countries, while the sdgs have a more universal prospect. thus, the sdgs are presented to replace the mdgs in a direction that is more in line with the challenges of the global future. the concept of sdgs is also needed as a new development framework that accommodates changes that have occurred after the mdgs, especially focusing on every global situation since 2000 such as health (who, 2015). 2.2. sustainable development lack of understanding of the concept of “sustainable development” is still a serious problem faced by the government, academics, private companies, and the government. mostly, the interpretation of sd is more likely to be caused by the incomplete concept of sd (shi et al., 2019). the basic principles of certain sd organizations or groups have partly influenced the mindset of individuals towards sd. in practice, sd is not based on suggestions and goals but is interpreted as a simple process of transformation that takes place without limitations (broman and robert, 2017). the aim of sd is to demonstrate that protection of the environment need not sacrifice well-being. in this conception, sd as opposed to “green growth” directly reacts to economic growth. according to kasztelan (2017), sd also ignores vital issues related to the consequences of environmental protection, economic growth, and business aspects of the main objectives of sd. in relation to the emphasis on compatibility, the sd contained in green growth also claims that environmental protection can contribute to the expansion of growth. 2.3. green growth unep (2011) links green economic growth as a green economy idea that is oriented towards strengthening social justice and community welfare along with ecological deficiencies and reducing the resulting environmental impacts. although this concept is relatively new in the scientific community, has become a recent topic on the global scene, has been highlighted for discussion, and needs analysis in the last few decades, its role has been extraordinary in the ecological and environmental economics sectors (kasztelan, 2017). throughout history, it was the first time the concept was used in the international “blueprint for a green economy” report, as the british government had been the leader since 1989 to prepare a board of leading environmental economists (barbier, 2011). stjepanović et al. (2019) respond to the importance of the economic dimension to a green growth approach that is very different from traditional gdp benchmarks, so it is necessary to integrate additional information qualitatively through method scouring of the opportunity costs of lost turnover and the costs of environmental damage (rahman et al., 2017). 2.4. alternative policies to crisis figure 2 categorizes the elements that formulate goals against the socio-economic paradigm aligned with the notion of progress, thus contributing to shaping discourse on alternative policies. the ilo (2009) designed several solutions to overcome the crisis and were categorized into three groups, namely projects for the green economy, projects for socio-economic transformation, and national stimulus packages that focus on all changes. bernard et al. (2009) instructed each policy to be differentiated by its conception, socioeconomic paradigm, and main objective. at present, bina and la kamera (2011) draw a process that goes to the right and centers on ecological economic theory, explicitly provides a theoretical basis for environmental sustainability, has a systematic effect, illustrates the notion of boundaries, then highlights the need for the broad meaning of welfare, and raises important questions covering intergenerational and intra-generational justice. 3. methodology 3.1. measurement of variables and hypotheses the variables that we determine are measured by two types, namely the independent variable and the independent variable. the provisions for independent variables as determinants directly predict or influence the dependent variable and vice versa the dependent variable is the variable predicted by the independent variable (e.g. wijayanti and darma, 2019; asih et al., 2020). those that act as independent variables are source of electric lighting (sel), renewable energy mix (rem), and primary energy intensity (pei). meanwhile, green growth (gg) is an independent variable. table 1 describes the operational definition of each of these variables. based on this linear equation, figure 3 is compiled for the completeness of the study model design. sel indicator is located in sdg 1 “ending poverty in all forms, everywhere,” then sdgs 2 “ensuring access to affordable, reliable, sustainable and modern energy for all” divides the two indicators (rem and pei), and gg is the ultimate goal expected in the green economy concept. the hypothesis proposals are sorted as follows: hypothesis-1: there is a positive effect of sel on gg. hypothesis-2: there is a positive effect of rem on gg. hypothesis-3: there is a positive effect of pei on gg. 3.2. data the data is concentrated on time series data for a decade that refers to the national medium-term development plan (rpjmn). the data intended are for two planning periods for 2015-2019 and planning for 2020-2024 under the leadership of jokowi (president of the republic of indonesia). we obtained the data collection through government agencies (bps-statistics of indonesia) and private institutions (3gi of indonesia) as the institutions authorized to compile indonesia’s sdgs documents. the scope of the consistency study to invest in the effect of sel, rem, and pei on gg with different units in the 2015-2024 period, where specifically for the period 2020 to 2024 uses projection suparjo, et al.: indonesia’s new sdgs agenda for green growth – emphasis in the energy sector international journal of energy economics and policy | vol 11 • issue 3 • 2021398 data shown in table 2. evaluation of jokowi’s performance the indicators sel, rem, pei, and gg during the two eras are clearly striking. with the sdgs target in 2019, as a comparison for the first leadership period (2015-2019), only sel had achieved success, while rem and pei did not meet the target, and gg tended to fluctuate, showing that in 2015-2017 there was an increase and had decreased by 2.58% in 2018 and again increasing by 0.73% for 2019. comparisons for the 2020-2024 period or the second leadership era (present) which are supported by projection data, the results in the sel have consistently increased as before. table 2 also presents rem in 2024 has met the criteria, but in 2020-2023 it has not been achieved. the pei target is also similar to the previous era, which has not met the target and gg even fell from 2020 to 2021, then there was an increase of 2.25% and 2.31% in 2022 and 2023. then, in 2024, gg has decreased again, so it is classified as inconsistent. 3.3. empirical model to implement the econometric method, we use the ordinary least squares (ols) method in multiple linear analysis to invest in the effects of the identified variables. in the data presentation process, it is presented with spss 25 software. ols specification model, we replicate the equation function created by aldieri and vinci (2018) with the following simulation: table 1: variable constraints indicator targeted concept interpretation function percentage of households with electricity as the main source of electricity from the state electricity company (pln) and non-pln electricity increased access to information for the lowest 40% of the population to 100% by 2019 percentage of poor and vulnerable households whose main source of lighting is pln and non-pln. pln electricity is a source of electric lighting managed by pln. non-pln electricity is a source of electric lighting managed by agencies or parties other than pln, including those using lighting sources from batteries, generators, and solar power plants (which are not managed by pln) the greater this value, the better the level of household/community welfare to see household welfare from the housing side renewable energy mix in 2019, the national energy mix originating from the new and renewable energy sector was achieved 19% final energy is energy that can be consumed directly by the end-user. government regulation of the republic of indonesia number 79 of 2014 concerning “national energy policy” is energy derived from renewable energy sources, including from geothermal energy, wind, bioenergy, sunlight, water flows, and falls, movement, and differences in sea layer temperature the renewable energy mix is the percentage between the total final consumption of renewable energy to the total final energy consumption knowing how large the proportion of renewable energy use is to total energy primary energy intensity primary energy intensity (1% decrease per year) to 463.2 barrels of oil equivalent (boe) in 2019 primary energy is energy provided by nature and has not undergone further processing based on government regulation number 79 of 2014 concerning “national energy policy”. primary energy intensity as the total primary energy supply per unit of gross domestic product in units of sbm per idr billion the success of the application of energy conservation or how much energy can be saved to produce the same product identify how much energy is used to produce one unit of economic output. primary energy intensity is a proxy for measuring how efficiently the economy can utilize energy to produce output. the lower the ratio of the primary energy intensity, the less energy is needed to produce one unit of output green growth increase in average green gdp growth a movement towards a more integrated and comprehensive approach to incorporating social and environmental factors in the economic process, in order to achieve sustainable development economic growth contributes to the responsible use of natural capital, prevents and reduces pollution, and creates opportunities to improve overall social welfare by building a green economy and enabling the achievement of sustainable development goals. the components in gg include the cost of natural resource consumption (agricultural land, minerals, forests, water, fish resources, environmental depletion costs, and the level of environmental degradation) to measure the level of natural values other than goods and services that have been measured in conventional gdp (without the cost of environmental impact) source: bps-statistics of indonesia (2020a, b), 3gi of indonesia (2020) suparjo, et al.: indonesia’s new sdgs agenda for green growth – emphasis in the energy sector international journal of energy economics and policy | vol 11 • issue 3 • 2021 399 figure 2: response to multiple crisis policies source: developed from bina (2013) figure 3: model report source: inserts from un (2020a, b) table 2: summary of data components obs. sel (%) rem (%) pei (idr billlion) gg (%) 2015 91.47 5.19 145.00 5.53 2016 92.73 7.47 145.30 5.81 2017 93.55 8.39 135.05 6.02 2018 94.15 10.42 134.65 3.44 2019 94.83 12.20 140.62 4.17 2020* 95.78 13.40 144.75 6.29 2021* 96.46 14.28 141.82 5.35 2022* 97.01 15.51 142.24 7.60 2023* 97.54 15.93 148.97 9.91 2024* 97.62 16.70 145.10 8.78 source: bps-statistics of indonesia (2020a, b), 3gi of indonesia (2020). information: *projection data lnggit = αi + β1lnselit + β2lnrem + β3lnpeiit + εit (1) the provisions, ln: natural logarithm, α: constant, β: vectors of parameters, ggit: green growth effects, selit: source of electric lighting for gg i and year t, remit: renewable energy mix for gg i and year t, peiit: primary energy intensity for gg i and year t, and εit: disturbance term. as for the summary statistics from data observations, we estimate it based on the gg, sel, rem, and pei variables reviewed in table 3 which confirms that the comparison of all variables is varied. the maximum value, mean, and standard deviation are highest for pei because its benchmarks are the most prominent among the others. meanwhile, of the three indicators, the smallest contribution is gg. however, gg is the only variable whose skewness calculation is positive, while for kurtosis values, all of them are negative. 4. results and discussions the first step that needs to be presented is the assumption of normality. the principle in figure 4 is to detect normality by table 3: descriptive statistics (obs. = 10) model min. max. mean sd skewness kurtosis sel 91.47 97.62 95.1140 2.11959 −0.395 −1.031 rem 5.19 16.70 11.9490 3.93634 −0.492 −1.057 pei 134.65 148.97 142.3500 4.57940 −0.697 −0.121 gg 3.44 9.91 6.2900 1.98332 0.553 −0.101 source: own result looking at the spread of observations (points) on the diagonal axis of the graph on the residuals. thus, we make a decision if the data has spread around the diagonal line and followed the direction of the diagonal line so that the pattern is normally distributed and the regression model meets the assumption of normality. the second requirement is the assumption of heteroscedasticity with the aim of testing whether the regression model has inequality of variance from the residuals of one observation to another through a scatter plot (figure 5). in practice, this observational variance means that there is no heteroscedasticity disorder because there is no certain pattern that causes irregular data distribution under and over the main axis. selection through the person correlation feasibility test to determine the closeness of the linear relationship between variables based on ratio and interval data, so that it fits in this study. we conclude that there is a positive coefficient which implies that the direction of the relationship is directly proportional. table 4 also provides significant signals from gg, sel, and rem to gg. the next interpretation is to test the regression results in a complex manner to compare the proposed hypothesis with the suitability of the estimates. table 5 attaches the partial test values of sel, rem, and pei and their predictions for gg which are also supported by the coefficient of determination. with reference to the probability level of 5% (1.96), the three variables have a significant effect on gg. partially, sel, rem, and pei have p < 0.05, so it has a significant impact on increasing gg significantly. what prevents the relationship from being unidirectional is indicated by rem to gg which has a negative coefficient value. on the other hand, sel and pei have a positive contribution to encourage gg (ceteris paribus). the reflection of the coefficient of determination is used as information on the suitability of a model and is interpreted to determine the extent to which a number of dependent variables are suparjo, et al.: indonesia’s new sdgs agenda for green growth – emphasis in the energy sector international journal of energy economics and policy | vol 11 • issue 3 • 2021400 able to explain the independent variables for the regression model as a whole (rachmawatie et al., 2021). because the determination of the ols method is more than 50%, it is concluded that it is very feasible to use. gg is determined by sel, rem, and pei at 85.5%, and 14.5% is explained by other variables outside the study model. in more detail, the built model has achieved very good criteria with the following structure: gg = −423.919 + 4.470 sel + −2.176 rem + 0.218 pei + 0.145 (2) the success of the economic system is very relevant to enable the efficient use of goods and services in the current industrial era. the concept of green growth must support this implementation in synergy with policies that are in line with energy savings (aldieri and vinci, 2018). it is the key to success in considering the progress of green growth, stjepanović et al. (2017) describe important efforts and encouragement that require organization, energy security, industry, and the economic problem itself when measuring gdp. abdullah et al. (2017) highlighted that at the fundamental level, in general, some countries still make resource-allocation errors. the level of capital invested in acquiring energy efficiency, renewable energy, sustainable agriculture, ecosystems, biodiversity, water conservation, and public transportation is relatively small. the pattern of growth and development actually has a negative impact on the welfare of the current generation. it is not impossible, it also presents challenges and presents risks for future generations. gdp growth largely determines aggregate economic indicators, but the economic impact is not fully reaching at the sectoral level. dai et al. (2016) present certain reasons that give a message if there is no negotiation that links economic growth and renewable energy consumption. meanwhile, the views of taskin et al. (2020) focuses on the consumption of renewable energy and its impact on green growth in oecd countries. the factor of openness to international trade is explained by a green economy that drives broad opportunities and creates benefits in social equality, productivity, and quality of life. case studies in several countries in the european union, such as lithuania, slovenia, and hungary consume increasingly renewable energy to increase green growth, while in bulgaria and romania they are in progress. two-way causality that connects the level of renewable energy consumption and green growth in the long run, further confirms the validated hypothesis in a group of countries analyzed. in the 2020 target, the feasibility of a number of countries in europe should be studied regarding public policy goals and increasing energy efficiency to achieve it (marinaş et al., 2018). no less interesting, the study of ziolo et al. (2020) presents sdgs which present the right steps to reduce energy consumption, so that the use of renewable energy and energy efficiency runs optimally. an approach to closing the gap by investigating the relationship between economic development, financial support, and energy efficiency is in the spotlight of this century. the transition from developed countries such as china, finland, japan, and germany has led to green growth leading to an economic and environmental figure 4: normal plot of model source: own result figure 5: scatter plot of model source: own result table 4: correlations (obs. = 10) model gg sel rem pei gg 1.000 0.632 (0.025*) 0.581 (0.039*) 0.677 (0.016*) sel 0.632 (0.025*) 1.000 0.995 (0.000*) 0.301 (0.199*) rem 0.581 (0.039*) 0.995 (0.000*) 1.000 0.293 (0.206*) pei 0.677 (0.016*) 0.301 (0.199*) 0.293 (0.206*) 1.000 source: own result. information: *p<0.05 table 5: regression display model unstd. coef. beta se t sig. vif reality signs constant −423.919 126.140 −3.361 0.015* sel 4.470 1.428 3.129 0.020* 96.341 (+) rem −2.176 0.767 −2.836 0.030* 95.833 (−) pei 0.218 0.071 3.083 0.022* 1.104 (+) r=0.925 f=11.779 r square=0.855 sig. = 0.006 adjusted r square=0.782 df=9 dw test=2.094 source: own result. information: *p<0.05, predicted to gg suparjo, et al.: indonesia’s new sdgs agenda for green growth – emphasis in the energy sector international journal of energy economics and policy | vol 11 • issue 3 • 2021 401 assessment system. the approach pioneered by matraeva et al. (2017) focuses on fundamental considerations with the experience of leaders of a group of countries who have switched to energy efficiency through economic policy packages 5. conclusions our findings confirm that sel and pei have a positive impact on gg, while rem has a negative effect. through medium-term calculations, with an increase in sel 1%, it will increase gg by 4.470%, and an increase in pei of idr 1 billion per period, will also increase gg by 0.218%. conversely, if rem increases by 1%, it will reduce gg by 2.176%. in addition, the constant value reaches −423,919, which means that the average contribution of other variables outside the ols model has a negative impact on gg. this article has explored three vital points. empirical findings do enrich scientific evidence regarding the impact of sel, rem, and pei on gg. one thing that must be considered is the follow-up on the externalities outside the model to calculate how much in the process of disseminating other knowledge in the environmental context. contributions in both practical and theoretical spheres are needed to enrich the present invention. for the future, practical insights put forward truly mature solutions initiated by the government in the sdgs document. in addition, the output theoretically refers to the constraints of this study which are limited by the data set published by the government. another downside is that the time lag used is still medium-term. therefore, it is hoped that future studies will consider this matter so that the presentation of the findings is more interesting and varied. 6. acknowledgment the authors gratefully acknowledge receipt of internal sponsorship (grant) from each institution. we also appreciate the performance and collaboration of the authors in this study. references abdullah, h., bakar, n.a., jali, m.r., ibrahim, f.w. (2017), the current state of malaysia’s journey towards a green economy: the perceptions of the companies on environmental efficiency and sustainability. international journal of energy economics and policy, 7(1), 253-258. aldieri, l., vinci, c.p. (2018), green economy and sustainable development: the economic impact of innovation on employment. sustainability, 10(10), 1-11. asia green real estate. (2020), indonesia’s second-tier cities on the move. asia insights. electronic resource. available from: https:// www.asiagreen.com/en/news-insights/indonesia-s-second-tier-citieson-the-move. [last accessed on 2021 jan 16]. asih, d., setini, m., soelton, m., muna, n., putra, i., darma, d., judiarni, j. (2020), predicting green product consumption using theory of planned behavior and reasoned action. management science letters, 10(14), 3367-3374. barbier, e. (2011), the policy challenges for green economy and sustainable economic development. natural resources forum, 35(3), 233-245. bernard, s., asokan, s., warrell, h., lemer, j. (2009), “the greenest bail-out?” the financial times. electronic resource. available from: http://www.cachef.ft.com/cms/s/0/cc207678-0738-11de9294-000077b07658.html#ixzz2bq0acirs. [last accessed on 2021 jan 10]. bina, o. (2013), the green economy and sustainable development: an uneasy balance? environment and planning c: politics and space, 31(6), 1023-1047. bina, o., la camera, f. (2011), promise and shortcomings of a green turn in recent policy responses to the “double crisis”. ecological economics, 70(12), 2308-2316. bps-statistics of indonesia. (2020a), national socio-economic survey in 2019. electronic resource. available from: https://www.sirusa. bps.go.id/sirusa/index.php/dasar/view?kd=1558&th=2020. [last accessed on 2021 jan 03]. bps-statistics of indonesia. (2020b), sustainable development indicator data compilation, 2019. electronic resource. available from: https://www.sirusa.bps.go.id/sirusa/index.php/dasar/ view?kd=131&th=2019. [last accessed on 2021 jan 03]. broman, g.i., robert, k.h. (2017), a framework for strategic sustainable development. journal of cleaner production, 140(1), 17-31. cappo, d., verity, f. (2014), social inclusion and integrative practices. social inclusion, 2(1), 24-33. dai, h., xie, x., xie, y., liu, j., masui, t. (2016), green growth: the economic impacts of large-scale renewable energy development in china. applied energy, 162, 435-449. diouf, g. (2019), millenium development goals (mdgs) and sustainable development goals (sdgs) in social welfare. international journal of science and society, 1(4), 17-24. esquivel, v. (2016), power and the sustainable development goals: a feminist analysis. gender & development, 24(1), 9-23. global green growth institute of indonesia. (2020), green growth and investment planning: a guide to using extended cost-benefit analysis (ecba). electronic resource. available from: https:// www.greengrowthknowledge.org/sites/default/files/downloads/ policy-database/mainstreaming%20green%20growth%20in%20 investment%20planning%20(idn).pdf. [last accessed on 2021 jan 17]. hulme, d. (2010), lessons from the making of the mdgs: human development meets results-based management in an unfair world. ids bulletin, 41(1), 15-25. international labour organization. (2009), green stimulus measures. european commission, paper series no. 15. electronic resource. available from: https://www.ec.europa.eu/social/blobservlet?doci d=7247&langid=en. [last accessed on 2021 jan 04]. kasztelan, a. (2017), green growth, green economy and sustainable development: terminological and relational discourse. prague economic papers, 26(4), 487-499. kumar, s., kumar, n., vivekadhish, s. (2016), millennium development goals (mdgs) to sustainable development goals (sdgs): addressing unfinished agenda and strengthening sustainable development and partnership. indian journal of community medicine, 41(1), 1-4. marinaş, mc., dinu, m., socol, ag., socol, c. (2018), renewable energy consumption and economic growth. causality relationship in central and eastern european countries. plos one, 13(10), e0202951. matraeva, l.v., goryunova, n.a., smirnova, s.n., babenko, m.i., erokhin, s.g., solodukha, p.v. (2017), methodological approaches to the assessment of energy efficiency within the framework of the concept of green economy and sustainable development. international journal of energy economics and policy, 7(4), 231-239. pasaribu, r.b. (2013), indonesia’s green economy. electronic resource. suparjo, et al.: indonesia’s new sdgs agenda for green growth – emphasis in the energy sector international journal of energy economics and policy | vol 11 • issue 3 • 2021402 available from: https://www.rowlandpasaribu.files.wordpress. com/2013/02/11-perekonomian-hijau-indonesia.pdf. [last accessed on 2020 dec 28]. rachmawatie, d., rustiadi, e., fauzi, a., juanda, b. (2021), driving factors of community empowerment and development through renewable energy for electricity in indonesia. international journal of energy economics and policy, 11(1), 326-332. rahman, d.h., majidi, n., huwaina, f., harun, n.f., kasuma, j. (2017), economic growth in malaysia: a causality study on macroeconomics factors. journal of entrepreneurship and business, 5(2), 61-70. rahman, d.h., majidi, n., kasuma, j., yacob, y., marikan, d.a. (2019), the dynamic of macroeconomics elements in malaysia: further insight into causality analysis. journal of international business, economics and entrepreneurship, 4(1), 1-9. ruhil, r. (2017), millennium development goals to sustainable development goals: challenges in the health sector. international studies, 52(1-4), 118-135. shi, l., han, l., yang, f., gao, l. (2019), the evolution of sustainable development theory: types, goals, and research prospects. sustainability, 11(24), 1-16. stjepanović, s., tomić, d., škare, m. (2017), a new approach to measuring green gdp: a cross-country analysis. entrepreneurship and sustainability issues, 4(4), 574-590. stjepanović, s., tomić, d., škare, m. (2019), green gdp: an analysis for developing and developed countries. e a m: ekonomie a management, 22(4), 4-17. taskin, d., vardar, g., okan, b. (2020), does renewable energy promote green economic growth in oecd countries? sustainability accounting, management and policy journal, 11(4), 771-798. united nations environment programme. (2011), towards a green economy: pathways to sustainable development and poverty eradication. electronic resource. available from: http://www.unep. org/greeneconomy/portals/88/documents/ger/ger_final_dec_2011/ green%20economyreport_final_dec2011.pdf. [last accessed on 2021 jan 07]. united nations. (2020a). end poverty in all its forms everywhere. department of economic and social affairs, sustainable development. electronic resource. available from: https://www. sdgs.un.org/goals/goal1. [last accessed on 2021 jan 15]. united nations. (2020b). ensure access to affordable, reliable, sustainable and modern energy for all. electronic resource. available from: https://www.sdgs.un.org/goals/goal7. [last accessed on 2021 jan 15]. vandemoortele, j. (2018), from simple-minded mdgs to muddle-headed sdgs. development studies research, 5(1), 83-89. wijayanti, t.c., darma, d.c. (2019), the role of investment and government expenditure on grdp and human development in east kalimantan. international journal of scientific & technology research, 8(9), 1232-1237. world health organization. (2015), health in 2015: from mdgs to sdgs. electronic resource. available from: https://www.who.int/ docs/default-source/gho-documents/health-in-2015-mdgs-to-sdgs/ health-in-2015-from-mdgs-to-sdgs.pdf?sfvrsn=8ba61059_2. [last accessed on 2021 jan 16]. yusuf, a.a. (2010), estimates of the “green” or “eco” regional domestic product of indonesian provinces for the year 2005. economics and finance indonesia, 58(2), 131-148. ziolo, m., jednak, s., savić, g., kragulj, d. (2020), link between energy efficiency and sustainable economic and financial development in oecd countries. energies, 13(22), 1-28. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 2 • 2023404 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(2), 404-409. causality relationship between the development of the oil and gas sector and foreign investments bahman huseynli* azerbaijan state university of economics, chief specialist, azerbaijan public employment agency, baku, azerbaijan. *email: bahmanhuseynli@gmail.com received: 12 september 2022 accepted: 15 february 2023 doi: https://doi.org/10.32479/ijeep.13573 abstract in this study on azerbaijan, which is dependent on oil, the causality relationship between economic growth, foreign investments, total capital increases in the country and oil and gas sector revenues have been examined. as a result of the analysis made using the granger method, a row of causality relationships was obtained. the data used in the analysis were obtained from the world bank, an important data disclosure platform. the result of the analysis made for a period from 2000 to 2020 shows the importance of the oil and gas sector in attracting foreign investments in this country. as a result of the study, a bidirectional causality relationship was obtained between economic growth and foreign investments in azerbaijan. in other words, while attracting foreign investments to the country supports economic growth, the realization of economic growth at the same time shows its own effect on the growth of the country’s economy. namely, these variables become the granger causality of each other. bilateral causality relationship has also been determined between foreign investments and the incomes obtained from the total oil and gas sector. at the same time, the development of this sector makes the country more attractive for foreign investors. increases in revenues in the oil and gas sector also have an impact on the overall capital increase in the country. in other words, this variable is the granger cause of capital increases. keywords: oil, gas, energy sector, foreign investments, azerbaijan jel classifications: o13, q40 1. introduction foreign direct investment (fdi) is referred to as an investment aimed at generating long-term returns from an investment firm in a trade in a different economy (husain et al., 2021). in general, fdi is viewed as a financial enterprise resulting from capital growth (mkpakan, 2004). however, fdi is often perceived as a major priority in the central government’s development strategy in developing countries (du et al., 2008). fdi not only plays a vital role in the development of an industry, but also significantly influences macro and micro levels (nejati and bahmani, 2020). the influx of foreign direct investment can have direct effects such as increasing the capital stock, providing access to modern technology, improving employment, stimulating production and tax revenues, increasing the foreign exchange supply and increasing exports in the host country (blomstrom et al., 2000; anwar and nguyen, 2010). foreign companies can indirectly affect the host country by influencing the productivity of local companies, known as the “spillover effect” (görg and strobl, 2003; hamida, 2013). markusen (1997) argues that various services and production are located in different countries for different reasons, depending on the availability of certain factors of production. in particular, production using relatively low-skilled labor will take place in countries with relatively abundant labor, leading to vertical fdi (kemme et al., 2021). most countries are trying to remove barriers to foreign investment and adopt policies that can facilitate fdi inflow. according to unctad’s annual report for 2018, the ratio this journal is licensed under a creative commons attribution 4.0 international license huseynli: causality relationship between the development of the oil and gas sector and foreign investments international journal of energy economics and policy | vol 13 • issue 2 • 2023 405 of global fdi stock to gdp increased from 9.58% to 39.24% in the period 1990–2017. this rate increased from 9.32% to 43.79% in developed countries and from 12.86% to 32.58% in developing countries (nejati and bahmani, 2020). with all this, industry is driven by energy production, which provides the vital functions of the state and at the same time guarantees its security and independence. energy production is a vital component of the world economy. in a study by ahmadova et al. (2021), the characteristics of the diversification of the azerbaijani economy were evaluated, the dependence of the country’s economic development on the degree of diversification of the economy and exports was analyzed. as a result of the study, it has been revealed that it is necessary to develop processing industries, expand the access of small and medium-sized enterprises to financial resources and encourage foreign investment in the non-oil sector in order to overcome oil dependence and ensure effective economic diversification. the development and future of the country’s economy largely depends on the energy sector. widiyanti et al. (2019), energy is the only thing that can meet the development needs of the country. the energy sector is of particular importance for the future development of the country as it must develop as a competitive country and maintain a stable economic conflict. as a result of globalization, increasing international trade volume and widespread internet use, people are forced to consume more. in order to mix inputs and generate an output, energy is needed. consumption of energy enhances living standards as well as economic growth. for the implementation of practically any direct and indirect generation, there is always an energy requirement (huseynli, 2022a). considering all these, the aim of this study is to investigate the causal relationship between economic growth, foreign investments, total capital increases in the country and oil and gas sector revenues in azerbaijan. 2. review of literature 2.1. foreign investment heinrich et al. (2002) examined the political economy of foreign direct investment in the russian oil and gas industry to explain the limited role of foreign capital in this sector. foreign direct investment is defined as an investment made in a company operating in a country other than the host country’s investors to make permanent profits and to obtain at least 10% of the equity share (mwilima, 2003). according to another definition, fdi can be seen as a long-term investment by an international industrialist in a business located far from his home country (hill, 2005). a study by ghosh roy and van den berg (2006) demonstrated the positive and major effects of foreign direct investment (% of gdp) on economic development for the usa. in a study by myachin et al. (2015), the investment attractiveness aspects of the constituent entities of the russian federation, where the special economic zones (sez) mode is implemented, are reviewed. as a result of the study, the importance of small business development in creating a suitable investment environment has been revealed. a study by murari (2017) based on data from 1980 to 2013 examined the link between financial development and economic development as a gdp for south asian countries. as a result of the study, it was concluded that fdi and domestic investment contributed to south asian countries. a study by sahoo and sethi (2017) examined the causal relationship between foreign direct investment and economic development for india and found that india’s public development policy should focus on the profitable use of foreign direct investment and domestic investment. a study by husain et al. (2021) is to find out the impact of foreign direct investment on manufacturing industries in oman, based on primary and secondary data from the world bank database (1984-2018). the results of the study found that spillover effects on local companies such as new technology, marketing strategies, organizational skills, money, jobs, export growth, diversification of the economy and more competition led to increased domestic market efficiency and increased efficiency in skills. in a study by grabara et al. (2021), the relationship between foreign direct investment, economic growth and renewable energy consumption in kazakhstan and uzbekistan was discussed in the light of data obtained from 1992 to 2018. as a result of the study, it has been revealed that there is a two-way link between foreign direct investment and renewable energy consumption in these two countries. fdi is a source of financing that enables companies to grow. fdi can also be a driver for promoting energy efficiency innovation (grabara et al., 2021). arain et al. (2021) investigated the effect of foreign direct investment (fdi) on pakistan’s economic growth. as a result of the study, it was shown that fdi did not cause cpi in any leg value (as its effects were not significant) and the effects of cpi on fdi were not significant in the first lag, but these effects became significant in the second and third lags, respectively. arain et al. (2021) investigated the effect of foreign direct investment (fdi) on pakistan’s economic growth. as a result of the study, it was shown that fdi did not cause cpi in any leg value (as its effects were not significant) and the effects of cpi on fdi were not significant in the first lag, but these effects became significant in the second and third lags, respectively. a study by luu et al. (2022) investigated how re-centralization could affect foreign direct investment (fdi) inflows in vietnam. as a result of the study, it was revealed that re-centralization led to a significant decrease in foreign direct investment inflows. a study by luu et al. (2022) investigated how re-centralization could affect foreign direct investment (fdi) inflows in vietnam. as a result of the study, it was revealed that re-centralization led to a significant decrease in foreign direct investment inflows. in a study by ezejiofor and emeneka (2022), the effect of leverage on the social sustainability reporting of listed oil and gas companies in nigeria was examined. 2.2. foreign investment and oil-gas sector traditional energy has historically been the most popular option and is still in use today (huseynli, 2022b). although renewable huseynli: causality relationship between the development of the oil and gas sector and foreign investments international journal of energy economics and policy | vol 13 • issue 2 • 2023406 energy sources have been put forward in recent years, energy has been produced from oil and natural gas sources for decades. oil and natural gas are also fuel sources for pharmaceuticals, solvents, fertilizers, pesticides, and other chemicals, including plastics (anderson, 2017). if fossil fuel prices continue to rise, fossil fuel companies will need to develop new technologies and strengthen their operations to increase efficiency and enhance existing capabilities (sircar et al., 2021). a study by nejati and bahmani (2020) tried to examine the effects of fdi in the oil and gas sector on the iranian economy using a regional cge model. as a result of the study, it has been shown that if fdi does not lead to productivity spillover, it causes dutch disease in iranian economy. dube (2009) and tang (2009) described the cointegration between energy consumption and foreign direct investment in south africa and malaysia. according to mudakkar et al. (2013) found that causality differs from energy consumption to fdi in bangladesh and sri lanka, whereas causality ranges from fdi to energy consumption for india. azam et al. (2015) revealed that both fdi and gdp are significantly correlated with energy consumption in thailand, malaysia and indonesia. in a study by filimonova et al. (2020), the impact of foreign investment on the development of the oil and gas sector in russia was analyzed. today, the interdependence experienced on a global scale has gained even more importance with the increasing demand for energy resources. in a devastating competitive environment, hydrocarbons, especially natural gas, continue to be an important competitive tool as a strategic energy source (tutar et al., 2022). a study by sircar et al. (2021) provides a state-of-the-art in-depth review of machine learning and artificial intelligence to solve oil and gas industry problems. 3. research methodology 3.1. data set variables that are reliable in the explanation of macroeconomic data and used on an international basis are popularized by a few institutions. one such institution is the world bank. as a matter of fact, the data part of this study was obtained from this institution. among the variables described as different slices, those on an annual basis were preferred in this article. granger casuality test, which is one of the methods that best measures the causality relationship, was preferred for analysis. the data covers the period from 2000 to 2020. the main purpose of the study is to investigate the causality of azerbaijan, which is oil addicted and earns serious income from this sector, in attracting foreign investment and in total capital increases. the variables in the study are economic growth, foreign investments, total capital increases and revenues from the oil and natural gas sector. logarithmic values of the variables in the study were used to obtain more robust results. 3.2. analysis method the more data available to measure a relationship, the more robust the result. in this study, a 21-year data set is used to measure causality. data obtained from the world bank were analyzed using the ewievs program. the amounts in the data set are given in dollars. in the granger causality, it is important to do co-integration tests on the variables in order to determine whether or not there is a longterm equilibrium link between the variables. this may be done in order to assess whether or not there is a relationship. engle and granger (1987) came to the conclusion that a non-stationary time series combined with a linear function can produce a stationary result. in the event that such a stationary linear combination does exist, then the co-integration of non-stationary time series is performed. granger (1988) explains that the term “co-integration” refers to a situation in which two or more non-stationary variables are integrated in the same order with the stationary of residuals. granger proposed that if two time series variables are not cointegrated, then there may be unidirectional or bidirectional granger causality in the short run. this was based on the idea that co-integration ensures that no granger causality exists. both hypotheses on the rank of co-integration (the number of linearly co-integrating vectors) and hypotheses on the shape of co-integrating vectors may be assessed using the johansen test. 4. analyses and results in order to apply the granger analysis, a series of tests must first be applied. if necessary, consistency is achieved, analysis can be started. one of these tests is to measure whether the data set is stationary. the values given in table 1 show us that this data set is not stationary. so, the h0 hypothesis is valid. according to the test result using the vertical-fuller unit root test, it is shown that the level values of the data are not stationary with every three percent share (h0: the series is not stationary, h1: the series is stationary. variables in the analysis: economic growth, oil and gas sector revenues, foreign investments and total. for the capital increase series, the fact that the t statistical values are less than the test critical values in absolute value at all the given significance levels indicates that these variables are not stationary in azerbaijan. table 2 shows the quadratic differences and stationary states of the variables for the 21-year period in azerbaijan (p ≤ 0.05). in this table, the fact that the t statistical values are greater than the test critical values at the significance levels indicates that the data are stationary. then, the var model was established using the variables and the appropriate lag numbers of these data were determined with the help of akaike (aic), ll, lr, fbe, sc and hq information criteria. appropriate lag lengths for this study are listed in table 3. according to the lag length test result, the most appropriate lag length was determined as four, as can be seen from the table. after the necessary tests were done, granger analysis was performed to measure the causality relationship. the causality relationship between the grangder results and the variables is given in table 4. it is possible to interpret whether there is a causal huseynli: causality relationship between the development of the oil and gas sector and foreign investments international journal of energy economics and policy | vol 13 • issue 2 • 2023 407 table 4: granger nedensellik testi hypotheses f-value probability value (p) decision at 5% significance level there is a causal relationship between economic growth and total capital increase. 3.855411 0.1455 rejected there is a causal relationship between economic growth and foreign investments. 7.802965 0.0202 acceptable there is a causal relationship between economic growth and revenues from the oil and gas sector. 2.768269 0.2505 rejected there is a causal relationship between total capital increase and economic growth. 4.358495 0.1131 rejected there is a causal relationship between total capital increase and foreign investments. 1.631736 0.4423 rejected there is a causal relationship between total capital increase and revenues from the oil and gas sector. 1.922303 0.3825 rejected there is a causal relationship between foreign investments and economic growth. 24.63979 0.0000 acceptable there is a causal relationship between foreign investments and total capital increase. 5.337602 0.0693 rejected there is a causal relationship between foreign investments and revenues from the total oil and gas sector. 18.35789 0.0001 acceptable there is a causal relationship between income from the oil and gas sector and economic growth. 2.267958 0.3218 rejected there is a causal relationship between the revenues from the oil and gas sector and the total capital increase. 7.630553 0.0220 acceptable there is a causal relationship between revenues from the oil and gas sector and foreign investments. 13.51719 0.0012 acceptable table 3: appropriate delay length lag logl lr fpe aic sc hq 0 -31.56892 na 0.000772 4.184578 4.380629 4.204066 1 35.00849 93.99163 2.16e-06 −1.765704 −0.785453 −1.668266 2 64.19175 27.46660 6.88e-07 −3.316677 −1.552225 −3.141287 3 124.3735 28.32083* 1.64e-08* −8.514530 −5.965878 −8.261189 4 1561.840 0.000000 na −175.7459* −172.4130* −175.4146* *indicates the appropriate lag length for the relevant test. relationship between the variables according to the determined hypotheses and probability values. causality analysis was conducted to measure how effective the oil sector is in attracting foreign investment and increasing total capital in azerbaijan, which is oil dependent. the obtained results reveal the relationship between the four variables. according to the granger result, there is a bilateral causality relationship between foreign investments and economic growth in azerbaijan. in this case, hypothesis h1 is accepted (p < 0.05). in other words, while attracting foreign investments to the country supports economic growth, the realization of economic growth at the same time shows its own effect on the growth of the country’s economy. in other words, these variables become the granger cause of each other. a bilateral causality relationship was also found between foreign investments and income from the total oil and gas sector (p < 0.05). in other words, the arrival of foreign investors to the country and the increase in foreign currency inflows show their own effect on the increase in earnings from the oil sector. at the same time, the development of this sector makes the country more attractive for foreign investors. increases in revenues in the oil and gas sector also have an impact on the overall capital increase in the country (p < 0.05). in other words, these variable capital increases are the granger cause. 5. discussion and conclusion fdi is known to have a positive and enormous impact on economic development for high-wage countries (de mello, 1997). in the research on azerbaijan, which is oil addicted, the causality relationship between the economic growth in this country, foreign table 1: level values of series test critical values gdp tourism revenues foreign direct investment capital formation t-statistics possibility t-statistics possibility t-statistics possibility t-statistics possibility adf testing statistics –2.221847 0.2055 –2.227842 0.2032 0.366743 0.7808 –2.436537 0.1457 test critical values 1% –3.831511 –3.808546 –2.685718 –3.831511 5% –3.029970 –3.020686 –1.959071 –3.029970 10% –2.655194 –2.650413 –1.607456 –2.655194 table 2: second difference values of series test critical values gdp tourism revenues foreign direct investment capital formation t-statistics possibility t-statistics possibility t-statistics possibility t-statistics possibility adf testing statistics −3.928386 0.0092 –4.020071 0.0089 –6.856195 0.0000 –4.980644 0.0012 test critical values 1% –3.886751 –3.959148 –3.857386 –3.886751 5% –3.052169 –3.081002 –3.040391 –3.052169 10% –2.666593 –2.681330 –2.660551 –2.666593 huseynli: causality relationship between the development of the oil and gas sector and foreign investments international journal of energy economics and policy | vol 13 • issue 2 • 2023408 investments, total capital increases in the country and oil and gas sector revenues have been tried to be determined. a number of important results were obtained in the causality relationship measured using the granger method. the data used in the analysis were obtained from the world bank, an important data disclosure platform. the information obtained as a result of a 21-year process analysis really shows the importance of the oil and gas sector for this country in attracting foreign investments. as a result of the study, there is a bidirectional causality relationship between economic growth and foreign investments in azerbaijan. in other words, while attracting foreign investments to the country supports economic growth, the realization of economic growth at the same time shows its own effect on the growth of the country’s economy. in other words, these variables become the granger cause of each other. a bilateral causality relationship was also found between foreign investments and income from the total oil and gas sector (p < 0.05). in other words, the arrival of foreign investors to the country and the increase in foreign currency inflows show their own effect on the increase in earnings from the oil sector. at the same time, the development of this sector makes the country more attractive for foreign investors. increases in revenues in the oil and gas sector also have an impact on the overall capital increase in the country (p < 0.05). in other words, these variable capital increases are the granger cause. fdi can not only increase the capital supply in the host country, but also increase the productivity of domestic firms through knowledge transfer (nejati and bahmani, 2020). in addition, as a result of the study, a bilateral causality relationship was found between foreign investments and the revenues from the total oil and gas sector. from this point of view, the increase in foreign currency inflows into the country can also improve the earnings from the oil sector in different sectors. the oil and gas sector had improved the economic outlook for many countries around the world. the industry recognizes it as the main source of energy generation on the planet. after a period of falling crude oil prices, the oil and gas industry is considering redefining its boundaries through digitalization (gezdur and bhattacharjya, 2017). the development of the internet and technology affects digitalization in the oil and natural gas sector as well as in different sectors. the workforce that provides the services needed by workers or employers meets in the labor market, where labor supply and demand meet. new digital labor markets claim to be flexible, lean and economical for both customers and independent contractors (huseynli and huseynli, 2022). in future studies, the relationship between foreign investments, especially oil and natural gas, and digitalization in the energy sector in general can be investigated. references ahmadova, e., hamidova, l., hajiyeva, l. (2021), diversification of the economy in the context of globalization (case of azerbaijan). in: shs web of conferences. vol. 92. les ulis, france: edp sciences. p07002. anwar, s., nguyen, l.p. (2010), foreign direct investment and economic growth in vietnam. asia pacific business review, 16(1-2), 183-202. arain, k., qureshi, n.a., suthar, v., pirzado, a.a., khanzada, a.h., baloch, a.b., memon, a.k. (2021), impact of foreign direct investment on economic growth in pakistan. international journal of management, 12(4), 41-55. azam, m., khan, a.q., zaman, k., ahmad, m. (2015), factors determining energy consumption: evidence from indonesia, malaysia and thailand. renewable and sustainable energy reviews, 42, 1123-1131. blomstrom, m., kokko, a., zejan, m. (2000), foreign direct investment: firm and host country strategies. london: macmillan press. de mello, l.r jr. (1997), foreign direct investment in developing countries and growth: a selective survey. journal of development studies, 34(1), 1-34. du, j., lu, y., tao, z. (2008), economic institutions and fdi location choice: evidence from us multinationals in china. journal of comparative economics, 36(3), 412-429. dube, s. (2009), foreign direct investment and electricity consumption on economic growth: evidence from south africa. economia internazionale/international economics, 62(2), 175-200. engle, r.f., granger, c.w.j. (1987), co-integration and error correction: representation, estimation, and testing. econometrica, 55(2), 251-276. ezejiofor, r.a., emeneka, o.l. (2022), leverage and social sustainability reporting on listed oil and gas firms in nigeria. international journal of advanced academic research, 8(3), 1-14. filimonova, i.v., nemov, v.y., shumilova, s.i. (2020), evaluation of the mutual influence of foreign investment and the development of the oil and gas complex of russia. iop conference series: earth and environmental science, 459(6), 062026. gezdur, a., bhattacharjya, j. (2017), digitization in the oil and gas industry: challenges and opportunities for supply chain partners. in: camarinha-matos, l., afsarmanesh, h., fornasiero, r., editors. collaboration in a data-rich world. pro-ve 2017. ifip advances in information and communication technology. vol. 506. cham: springer. ghosh roy, a., van den berg, h.f. (2006), foreign direct investment and economic growth: a time-series approach. global economy journal, 6(1), 1-21. görg, h., strobl, e. (2003), multinational companies, technology spillovers and plant survival. scandinavian journal of economics, 105(4), 581-595. grabara, j., tleppayev, a., dabylova, m., mihardjo, l.w.w., dackopikiewicz, z. (2021), empirical research on the relationship amongst renewable energy consumption, economic growth and foreign direct investment in kazakhstan and uzbekistan. energies, 14(2), 332. granger, c.w.j. (1988), some recent development in a concept of causality. journal of econometrics, 39(1-2), 199-211. hamida, l.b. (2013), are there regional spillovers from fdi in the swiss manufacturing industry? international business review, 22(4), 754-769. heinrich, a., kusznir, j., pleines, h. (2002), foreign investment and national interests in the russian oil and gas industry. post-communist economies, 14(4), 495-507. husain, u., javed, s., al araimi, a.a. (2021), a study of foreign direct investment on manufacturing industries in sultanate of oman. international journal of research-granthaalayah, 9(3), 1-9. huseynli, b., huseynli n. (2022), digitalisation and transformation in labour market. turan-csr: turan center for strategic researches, 14, 210-218. huseynli, n. (2022a), econometric analysis of the relationships between growth, exports and energy exports in azerbaijan. international journal of energy economics and policy, 12(2), 379-385. huseynli, n. (2022b), econometric analysis of the relationships between growth, exports and energy exports in azerbaijan. international huseynli: causality relationship between the development of the oil and gas sector and foreign investments international journal of energy economics and policy | vol 13 • issue 2 • 2023 409 journal of energy economics and policy, 12(2), 379-385. kemme, d.m., akhmetzaki, y., mukhamediyev, b.m. (2021), the effects of the eurasian economic union on regional foreign direct investment and implications for growth. the journal of international trade and economic development, 30(5), 643-660. luu, h.n., nguyen, m.n., nguyen, h.t. (2022), the impact of recentralisation on fdi: evidence from a quasi-natural experiment. post-communist economies, 34(4), 543-563. markusen, j.r. (1997), trade versus investment liberalization. national bureau of economic research working paper, 6231. p1-29. mudakkar, s.r., zaman, k., shakir, h., arif, m., naseem, i., naz, l. (2013), determinants of energy consumption function in saarc countries: balancing the odds. renewable and sustainable energy reviews, 28, 566-574. murari, k. (2017), financial development-economic growth nexus: evidence from south asian middle-income countries. global business review, 18(4), 924-935. myachin, d.a., royzen, a.m., pershikov, a.n. (2015), regional features of attracting foreign investments into the russian economy. procediasocial and behavioral sciences, 166, 131-134. nejati, m., bahmani, m. (2020), the economic impacts of foreign direct investment in oil and gas sector: a cge analysis for iranian economy. energy strategy reviews, 32, 100579. sahoo, k., sethi, n. (2017), impact of foreign capital on economic development in india: an econometric investigation. global business review, 18(3), 766-780. sircar, a., yadav, k., rayavarapu, k., bist, n., oza, h. (2021), application of machine learning and artificial intelligence in oil and gas industry. petroleum research, 6(4), 379-391. tang, c.f. (2009), electricity consumption, income, foreign direct investment, and population in malaysia: new evidence from multivariate framework analysis. journal of economic studies, 36(4), 371-382. tutar, h., sarkhanov, t., guliyeva, n. (2022), eastern mediterranean area in energy security of the european union: from sea border issues to economic conflicts of interest. international journal of energy economics and policy, 12(1), 332-341. widiyanti, m., sadalia, i., irawati, n., hendrawaty, e. (2019), determining firm’s performance: moderating role of csr in renewable energy sector of indonesia. polish journal of management studies, 19(2), 432-441. international journal of energy economics and policy vol. 2, no. 1, 2012, pp.41-49 issn: 2146-4553 www.econjournals.com using sarfima model to study and predict the iran’s oil supply hamidreza mostafaei department of statistics, north tehran branch, islamic azad university, tehran, iran. & department of economics energy, institute for international energy studies, (affiliated to ministry of petroleum). e-mail: h_mostafaei@iau-tnb.ac.ir leila sakhabakhsh department of statistics, north tehran branch, islamic azad university, tehran, iran. e-mail: leila.sakhabakhsh@yahoo.com abstract: in this paper the specification of long memory has been studied using monthly data in total oil supply in iran from 1994 to 2009. because monthly oil supply series in iran are showing nonstationary and periodic behavior we fit the data with sarima and sarfima models, and estimate the parameters using conditional sum of squares method. the results indicate the best model is sarfima (0, 1, 1) (0, -0.199, 0)12 which is used to predict the quantity of oil supply in iran till the end of 2020. therefore sarfima model can be used as the best model for predicting the amount of oil supply in the future. keywords: long memory; conditional sum of squares; sarfima model; oil; iran jel classification: c12; c13; c22; c50 1. introduction the recent finance and economic literature has recognized the importance of long memory in analyzing time series data. a long memory can be characterized by its autocorrelation function that decays at a hyperbolic rate. such a decay rate is much slower than that of the time series, which has short memory. traditional models describing short memory, such as ar (p), ma (q), arma (p, q), and arima (p, d, q) can not describe long memory precisely. a set of models has been established to overcome this difficulty, and the most famous one is the autoregressive fractionally integrated moving average (arfima or arfima (p, d, q)) model. arfima model was established by granjer and joyeux (1980). an overall review about long memory and arfima model was model by baillie (1996). in many practical applications researchers have found time series exhibiting both long memory and cyclical behavior. for instance, this phenomenon occurs in revenues series, inflation rates, monetary aggregates, and gross national product series. consequently, several statistical methodologies have proposed to model this type of data including the gegenbauer autoregressive moving average processes (garma), k-factor garma processes, and seasonal autoregressive fractionally integrated moving average (sarfima) models. the garma model was first suggested by hosking (1981) and later studied by gray et al. (1989) and chung (1996). other extension of the garma process is the k-factor garma models proposed by giratis and leipus (1995) and woodward et al (1998). this paper investigates a special case of the k-factor garma model, which is considered by porter – hudak (1990) and naturally extends the seasonally integrated autoregressive moving average (sarima) model of box and jenkins (1976). katayama (2007) examined the asymptotic properties of the estimators and test statistics in sarfima models. there are several methods for estimating the parameters in time series models. in this paper, we estimate the parameters using conditional sum of squares (css) method and testing procedures using residual autocorrelations such as the lagrange multiplier (lm) test are shown. we intend to forecast the iran’s oil supply in the future. iran, a member of the organization of the petroleum exporting countries (opec), ranks among the world’s top three holders of both international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.31-49 42 proven oil and natural gas reserves. iran is opec’s second largest producer and exporter after saudi arabia and in 2008 was the fourth-largest exporter of crude oil globally after saudi arabia, russia, and the united arab emirates. this paper is organized of follows: the section 2 gives some definitions and properties for the arfima and sarfima processes then we explain using css method and lm test. section 3 illustrates the use of the sarima and sarfima models and section 4 presents our final conclusions. 2. materials and method 2.1 arfima model let  t t � be a white noise process with zero mean and variance 2   > 0, and b the backward-shift operator, i.e., kb (x ) xt t k  . if  t tx � is a linear process satisfying d t t(b)(1 b) x (b)     (1) where d ( 0.5,0.5)  , (.) , (.)  are polynomials of degree p and q, respectively, given by 2 p 1 2 p(b) 1 b b b      000 , 2 q 1 2 q(b) 1 b b b      000 where , 1 i p, , 1 j qi j      are real constants, than  t tx � is called general fractional differentiation arfima (p, d, q) process, where d is the degree or fractional differentiation parameter. if d ( 0.5,0.5)  , then  t tx � is a stationary, and an invertible process. the most important characteristic of an arfima (p, d, q) process is the property of long dependence, when d (0.0,0.5) , short dependence, when d = 0, and intermediate dependence, when d ( 0.5,0.0)  . 2.2 sarfima (p, d, q) (p, d, q)s processes in many practical situation time series exhibit a periodic pattern. we shall consider the sarfima (p, d, q) (p, d, q)s process, which is an extension of the arfima process (bisognin and lopes, 2009). definition 1. let  t tx � be a stationary stochastic process with spectral density function xf (.) .suppose there exists a real number b (0,1) , a constant cf and one frequency g [0, ]  (or a finite number of frequencies ) such that bf ( ) c gx f  � when, g  then,  t tx � is a long memory process. remark 1. in definition 1, when b (0,1) , we say that the process  t tx � has the intermediate dependence property (doukhan et al., 2003). definition 2. let  t tx � be a stochastic process given by the expression             dds s st tb b 1 b 1 b x b b t         � (2) where  is the mean of the process, { }t t � is a white noise process with zero mean and variance 2 2( ) , s t       � is the seasonal period, b is the backward-shift operator, that is  sk t t skb x x  , d s d(1-b ) s   is the seasonal difference operator, (.) , (.) , (.)   and (.) are the polynomials of degrees p, q, p, and q, respectively, defined by using sarfima model to study and predict the iran’s oil supply 43         p q i j i j i 0 j 0 b b b b                  qp k l k l k 0 l 0 b b b b          (3) where, ,1 i p, ,1 j q, ,1 k p i j k          , and ,1 l q l    are constants and 0 0 0 0 1         . then,  t tx � is a seasonal fractionally integrated arma process with period s, denoted by sarfima (p, d, q) (p, d, q)s, where d and d are, respectively, the differencing and the seasonal differencing parameters. theorem 1. let  t tx � be a sarfima (p, d, q) (p, d, q)s process given by the expression (2), with zero mean and seasonal period s � . suppose s(z) (z ) 0   and s(z) (z ) 0   have no common zeroes. then, the following is true. (i) the process  t tx � is stationary if d + d < 0.5, d < 0.5 and s(z) (z ) 0,   for z 1. (ii) the stationary process  t tx � has a long memory property if 0 < d + d < 0.5, 0 < d < 0.5 and s(z) (z ) 0,   for z 1. (iii) the stationary process  t tx � has an intermediate memory property if -0.5 < d + d < 0, -0.5 < d < 0 and s(z) (z ) 0,   for z 1. 2.3 css method there are several methods for estimating the parameters in time series models. in this paper, we implement the css method to estimate the sarima and sarfima models of oil supply in iran. this method is equivalent to the full maximum likelihood estimator (mle) under quite general conditional homoskedastic distributions. a description of the properties of the css estimator and its finite sample performance is presented in chung and baillie (1993). 2.4 lm test this section discusses testing for the integration order, namely, the lm test, which draws on lm tests for the integration order of the arfima model by robinson (1991), robinson (1994), agiakloglou and newbold (1994), and tanaka (1999). for the purpose of practical implementation, godfrey's (1979) lm approach is also used. for the sarfima model, we consider the testing problem of the null hypothesis h0: sarfima (p, d, q) (p, d, q)s against the alternative: ha, 1: sarfima (p, d + α0, q) (p, d, q)s or ha, 2: sarfima (p, d, q) (p, d + αs, q)s. the assumed null model is obtained by imposing the restriction α0(αs) = 0 and the alternatives are α0(αs) > 0 or α0(αs) < 0. we get the p-values for testing the integration order corresponding to tests. 3. empirical results 3.1 the data the data employed in this study are the monthly oil supply in iran from 1994 to 2009. the data are obtained from the energy information administration of the u.s. department of energy. figure 1 displays the data of oil supply in iran, t{x } . international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.31-49 44 figure 1. time plot of oil supply in iran, 1994-2009 1995 2000 2005 2010 time 36 00 38 00 40 00 42 00 (u ni t: t ho us an d b ar re ls p er d ay ) as seen in figure 1, the monthly data are seasonally therefore we consider s=12. figure 2 displays the autocorrelation function (acf) of the transformed data. the acf decays very slowly and exhibits non-stationary. figure 2. the sample autocorrelation function (acf), (a) the acf of monthly data of iran's oil supply, (b) the acf of differenced data (a) 0 5 10 15 20 lag 0. 0 0. 2 0. 4 0. 6 0. 8 1. 0 a c f using sarfima model to study and predict the iran’s oil supply 45 (b) 0.0 0.5 1.0 1.5 lag -0 .2 -0 .0 0. 2 0. 4 0. 6 0. 8 1. 0 a c f as seen in figure 2, there non-stationary in the observed data and this time series doesn't require seasonal differencing. the one approach to trend removal by differencing the series {x } t that the best transform for this data is y (1-b)xt t . 3.2 model selection to search for the best representation of this data, we first fitted differenced data y (1-b)xt t by the css method, where we used a sample mean of {y } t , y as an estimator of (y ) t    , and set s = 12. aic and bic criteria are also used under the assumption of normality [see, e.g., brockwell and davis (1991, section 9.3)]. fitting sarfima models or sarima models is limited to having sarma parameters with 0 p,q,p,q 3  , and where the total number of estimated sarfima parameters (d, d, sarma parameters, and 2 ) is less than 4. the total number of models is 70. as mentioned earlier, in addition to sarima models, sarfima models are fitted as well, because we intend to determine if the total oil supply in iran have long memory. from among these estimation results, we selected models in terms of aic and bic that satisfy the following conditions: (i) lm tests are not rejected with the significance level 5% and 10 to 30 degrees of freedom (ii) the sarfima parameters all converged. all calculations were made using s-plus. table 1 shows the best five models in terms of aic model selection with estimators. id denotes the model identification within 70 models. ne indicates the corresponding parameter is not estimated and is set to be 0. the numbers in parentheses in the column of aic (bic) denote the ranking of models in terms of aic (bic). table 1. summary of aic and bic model selection estimates 2 1 1 2 1 d d bic aic id 5754.7 5755.1 5696.0 5755.9 5697.8 ne 0.230 0.243 0.235 ne 0.341 ne ne 0.334 ne ne ne -0.184 ne -0.186 ne ne -0.300 ne -0.301 -0.199 ne ne ne -0.204 ne -0.264 ne ne ne (1)2020.4 (2)2020.4 (4)2023.7 (3)2020.5 (5)2023.8 (1)2010.5 (2)2010.7 (3)2010.7 (4)2010.8 (5)2010.8 54 46 23 24 53 international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.31-49 46 sarfima (0, 0, 1) (0, -0.199, 0)12 model (model id: 54) is the best model in terms of aic among the 70 model candidates. from theorem 1, the process {y } t has intermediate memory property. table 2 shows the p-values for testing the integration order corresponding to the best five models using the lm test statistics. table 2. p-values for testing the integration order corresponding to the best five models alternative hypotheses model 0≠ αs , 0 ≠ α0 α0 =0, αs < 0 α0 < 0, αs =0 0.0060 0.00009 0.5629 0.4722 0.0051 5.5 × 10-10 0.2471 0.2858 0.3430 0.0002 0.3206 0.00002 0.3173 0.2811 0.2989 sarfima (0, α0, 1) (0, αs , 0) sarfima (0, α0, 0) (0, αs , 1) sarfima (2, α0, 0) (0, αs , 1) sarfima (0, α0, 1) (0, αs , 1) sarfima (2, α0, 0) (0, αs , 0) in this table, models id 54, id 46 and id 53 correspond to some models in alternative hypotheses of the first, second and fifth rows of sarfima models, and models id 23 and id 24 correspond to null hypotheses of the third and forth rows of sarfima models. our findings as follows: (i) results for sarfima (0, α0, 1) (0, αs, 0), sarfima (0, α0, 0) (0, αs , 1), and sarfima (2, α0, 0) (0, αs , 0) support the estimation of d or d for models id 54, id 46, and id 53. (ii) except for sarfima (0, α0, 0) (0, αs, 1), results for sarfima models show large pvalues for the alternative α0< 0, αs =0. (iii) results for some sarfima models show relatively small p-values for the alternative α0 =0, αs < 0 and α0  0, αs  0. the best model for ty is sarfima (0, 0, 1) (0, -0.199, 0)12 model therefore the best model for tx is sarfima (0, 1, 1) (0, -0.199, 0)12 model. 3.3 forecasting upon determination of appropriate model, it can be used for forecasting. the best model is sarfima (0, 1, 1) (0, -0.199, 0)12 model which is used to predict the total oil supply in iran till the end of 2012 and 2020, as shown in figures 6 and 7. tables 3 and 4 show the results of the in-sample and out-sample forecasts for the sarfima model. as seen in figures 6 and 7, total oil supply in iran has increasing trend for the future. 1 99 5 2 0 00 20 0 5 2 0 10 t im e 34 00 36 00 38 00 40 00 42 00 44 00 46 00 2 0 08 2 00 9 2 0 10 2 01 1 20 1 2 t im e 40 00 42 00 44 00 46 00 figure 6. prediction plot of oil supply in iran (2010-2012) using sarfima model to study and predict the iran’s oil supply 47 199 5 2000 2005 20 10 2015 202 0 t ime 35 00 40 00 45 00 50 00 2008 20 10 2012 201 4 2 016 20 18 2020 t ime 40 00 42 00 44 00 46 00 48 00 50 00 figure 7. prediction plot of oil supply in iran (2010-2020) table 3. out-sample forecasts for the sarfima (0, 1, 1) (0, -0.199, 0)12 model uppercl lowercl prediction date 4372.939 4423.095 4446.569 4464.660 4489.326 4483.343 4486.284 4499.173 4519.272 4533.748 4541.347 4551.095 4555.127 4569.854 4575.812 4584.655 4597.244 4588.720 4589.843 4595.965 4607.346 4615.601 4618.773 4624.912 4076.793 4064.985 4043.063 4024.765 4018.676 3985.836 3964.796 3955.928 3956.049 3952.008 3942.313 3935.812 3934.799 3942.150 3940.624 3941.999 3947.204 3931.412 3925.400 3924.526 3929.054 3930.595 3927.192 3926.889 4224.866 4244.040 4244.816 4244.713 4254.001 4234.589 4225.540 4227.551 4237.660 4242.878 4241.830 4243.453 4244.936 4256.002 4258.218 4263.327 4272.224 4260.066 4257.622 4260.245 4286.200 4273.098 4272.982 4275.901 2010-01 2010-02 2010-03 2010-04 2010-05 2010-06 2010-07 2010-08 2010-09 2010-10 2010-11 2010-12 2011-01 2011-02 2011-03 2011-04 2011-05 2011-06 2011-07 2011-08 2011-09 2011-10 2011-11 2011-12 lowercl: lower confidence limits of forecasts uppercl: upper confidence limits of forecasts international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.31-49 48 table 4. in-sample forecasts for the sarfima (0, 1, 1) (0, -0.199, 0)12 model error forecasts actual date -67.884 -78.823 -23.022 35.125 12.984 27.312 30.811 13.106 -1.363 0.694 5.358 13.334 4199.122 4167.687 4119.831 4123.085 4167.386 4155.733 4158.006 4181.294 4201.535 4205.248 4204.310 4211.703 4131.228 4088.864 4096.809 4158.210 4180.370 4183.045 4188.817 4194.400 4200.172 4205.942 4209.668 4225.037 2009-01 2009-02 2009-03 2009-04 2009-05 2009-06 2009-07 2009-08 2009-09 2009-10 2009-11 2009-12 4. conclusions this paper has examined a seasonal long memory process, denoted as the sarfima model. as an illustration of the use of sarfima model, we considered monthly oil supply in iran. we fitted the data with sarima and sarfima models, and estimated the parameters using css method. the results indicated the best model was sarfima (0, 1, 1) (0, -0.199, 0)12 model which was used to predict the data. on the basis, we conclude that the sarfima model is effective and can be usefully employed as a substitute for the sarima model when fitting iran's oil supply data. references agiakloglou, c., newbold, p., 1994. lagrange multiplier tests for fractional difference. journal of time series analyisis, 15, 253-262. baillie, r.t., 1996. long memory processes and fractional integration in econometrics. journal of econometrics, 73, 5-59. bisognin, c., lopes, r.c., 2009. properties of seasonal long memory processes. mathematical and computer modeling, 49, 1837-1851. box, g.e.p., jenkins, g.m., 1976. time series analysis forecasting and control, 2nd ed. holden-day. san francisco. brockwell, p.j, davis., 1991. time series: theory and methods. springer, new york. chung, c.f., 1996. estimating a generalized long memory process. journal of econometrics, 73, 237259. chung, c.f., baillie, r.t., 1993. small sample bias in conditional sum-of-squares estimators of fractionally integrated arma models. empirical economics, 18, 791-806. doukhan, p, oppenheim, g., m.s. taqqu, m.s., 2003. theory and applications of long-range dependence. birkheuser, boston. giraitis, l., leipus, r., 1995. a generalized fractionally differencing approach in long memory modeling. lithuanian mathematical journal, 35, 65-81 godfrey, l.g., 1979. testing the adequacy of a time series model. biometrika, 66, 67-72. granjer, c.w., joyeaux, r., 1980. an introduction to long-memory time series models and fractional differencing. journal of time series analysis, 1, 15-29. gray, h.l., zhang, n.f., woodward, w.a., 1989. on generalized fractional processes. journal of time series analysis, 10, 233-257. hosking, j.r.m., 1981. fractional differencing. biometrika, 68, 165-176. international energy outlook 2010. www.eia.gov/oiaf/ieo/index.html. july 2010 katayama, n., 2007. seasonally and fractionally differenced time series. hitotsubashi journal of economics, 48, 25-55. porter-hudak., 1990. an application of the seasonal fractionally differenced model to the monetary aggregates. journal of american statistical association, 84, 410, 338-344. robinson, p.m., 1991. testing for strong serial correlation and dynamic conditional heteroskedasticity in multiple regressions. journal of econometrics, 47, 67-84. using sarfima model to study and predict the iran’s oil supply 49 robinson, p.m., 1994. efficient tests of non-stationary hypotheses. journal of american statistical association, 89, 1420-1437. tanaka, k., 1999. the non-stationary fractional unit root. econometric theory, 15, 549-582. woodward, w.a., cheng, q.c., gray, h.l., 1998. a k-factor long memory model. journal of time series analysis, 19, 485-504. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 2 • 2023462 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(2), 462-466. output and energy prices fluctuations in response to market shocks: system dynamic modeling valeriy kozytskyy1, marianna oliskevych1*, galyna beregova2, nelya pabyrivska2 1ivan franko national university of lviv, ukraine, 2lviv polytechnic national university, ukraine. *email: olisk@ukr.net received: 08 july 2022 accepted: 10 february 2023 doi: https://doi.org/10.32479/ijeep.13371 abstract regardless of the fact, whether governments of particular country implemented the strong lockdown measures to prevent the spread of covid-19 or not, the economies of each country all over the word have been suffered considerably due to the shocks caused by the pandemic. we observed slowdown of economic activity, macroeconomic instability and shifts in consumption preferences supplemented by rising unemployment as well as significant fluctuation of demand and production capability. the research problem addressed in this paper focuses on dynamic properties of output and inflation fluctuations that occur in response to economic shocks different magnitudes and types. we use a system dynamic approach and constructs two system dynamic models to examine the dynamics of output, prices, wage and inflation. the paper indicates ranges of relevant parameters’ values that correspond with sensitivity of output to demand and production capability changes related to possibility of reaching new equilibrium point. to explore the variety of prices and wage behavior in response to shocks we evaluate distinguish possible phase diagrams associated with stable node, stable focus, circle, unstable focus and unstable node. the results is a contribution to discussion of the policy issues related to mitigation of recession caused by unpredictable and strong shocks. keywords: output fluctuation, system dynamic model, energy prices, shock jel classifications: o13, с 63, e37 1. introduction the last year the whole word has been suffered from the deep crisis caused by covid-19 pandemic. the economy of every country has been hurt. regardless of the fact, whether governments implemented the strong lockdown measures or not, economies of each country has been suffered considerably (dorczak et al., 2021; hryhoruk et al., 2021). the economic activity showed declining trend, macroeconomic instability has been observed (skrypnyk and nehrey, 2015; guryanova et al., 2020) and, in result, the severe recession has occurred. the consumers were influenced not only by lack of doing their wonted traditional shopping but also by future uncertainty and general fear. some part of demand turned into online shopping with flexible and very fluctuating prices. the output was restricted by many reasons that were brought about by lockdowns and border closures. international trade system and financial market incurred losses (hayakawa and mukunoki, 2021). the demand shocks as well as production shocks, that had been taking place almost simultaneously, disturbed the dynamics of output, wages and energy prices, had a huge asymmetric impact on dynamics unemployment and labor force participation (lukianenko and oliskevych, 2017), industrial enterprise (matviychuk et al., 2019), wages, energy prices and socio-economic development of regions (hryhoruk et al., 2020). the severe and unpredictable disturbances are able to produce the nonlinear permanent effect (maman and maleki, 2022). the behavior of all economic indicators has undergone changes and their convergence to a new steady state (oliskevych and lukianenko, 2020) is a big question that is in interest of scientists as well as policymakers and public. shepherd (2018) focused on impact of negative shocks that provide transmission through an input-output network emphasizing this journal is licensed under a creative commons attribution 4.0 international license kozytskyy, et al.: output and energy prices fluctuations in response to market shocks: system dynamic modeling international journal of energy economics and policy | vol 13 • issue 2 • 2023 463 the importance of network structure, international output-input linkages and interlinkages among the sectors of the economy and role of propagation. he discovered that the negative market shocks have significant impact on distant nodes that correspond to the eigenvector centrality scores of those nodes. bazhenova et al. (2020) developed a wide range of contemporary nonlinear econometric models that take into account regime switching in unemployment rate and labor force to investigate the asymmetric nonlinear peculiarities in dynamics of european labor market indicators in response to shocks. heimberger (2020) discusses the technical restriction of european union fiscal rules and their impact on the fiscal space during of the covid-19. they provided evidence for declining revision of eu output estimation and evaluated the potential consequences in term of fiscal policy. scientists also emphasized that the estimation of direction and magnitudes for labor market factors responses on negative as well as on positive economic shocks are vitally important (tokarchuk et al., 2018). to investigate the behavior impact of economic variables in response to different shocks scientists often used econometrics vector autoregressive models as well as machine learning approaches (babenko et al., 2021) that include supervised and unsupervised learning, fuzzy logic approach (matviychuk, 2006) and predictive analytics (guryanova et al., 2020). oduyemi and owoeye (2020) explored the fluctuation of oil prices and health outcomes in nigeria. they showed that in oil exporting countries the dependence of government finance from oil revenue and its trend caused instability in income, fiscal balance, growth rate and human capital development. the researches combined evaluation of long-term relationships between energy sources and their short-term dynamics description. it was found two equilibrium relationships and adjustments forces that determined the fuel consumption dynamics in ukraine (oliskevych et al., 2019). hernández (2019) revealed the synchronization of fluctuation in latin america and us. based on panel data analysis he suggested the reasons of latin american macroeconomic exposure to external shocks and emphasized the importance of geo-economic source of output fluctuations for the region. kaminskyi et al. (2020) estimated the sensitivity to shocks in probability and based on measuring variability with applying the value-at-risk concept represented the risk analysis for investment decisions in agriculture exchange trade funds. bielinskyi et al. (2021) indicated the instability of the price dynamics of the energy market formed the inadequacy of the quantitative approach for evaluation of pricing processes and could cause abnormal shocks and crashes. 2. methodology the research paper examines the fluctuation of output and energy prices fluctuations as result of shocks influencing economic market. for modeling output and energy price adjustments, we denote y – the total output of firms; pe – the equilibrium energy price level that is described as a marginal wage cost. in equilibrium, aggregate demand is related to equilibrium price level and full employment, inflation is equal to expected inflation. the short-term fluctuations of energy price and output are given by system of differential equations p´ = μ (d(f(y), p) – y), (1) y´ = ω (p–ml(y)) (2) that corresponds with system dynamic model represented in figure 1. in our research, we consider different type of functions for the marginal wage cost function f´(y) and aggregate demand function evaluation and take into account possible shocks that disturb output production. suppose that gw is the real wage gap; gπ – gap between the actual inflation and desired level of inflation. the dynamics of wage and inflation gaps is given by the model gw´ = π, (3) gπ´ = δ(1–gw2) gπ–gw (4) the system has singular fixed point gwe=0, gπe=0. the linearized system has the following form gw gw gw gw g ´ ´ ( ) ( )g g� � � � � � � � � � � �� � � � � �� � � �� � � � � � � 1 0 1 2 1 2� � � (5) the expansion of system around the equilibrium point is gw gw g ´ ´g� � � � � � � � � � � � � � � � � � � � � 1 0 1 � � (6) the matrix of linearized system d � � � � � � � � 1 0 1 � (7) has two eigenvalues �1 2 4 2� � �� �� � / , �2 2 4 2� � �� �� � / (8) 3. results we consider different possible combinations of demand and output shocks in model (1) – (2) and represent the impact of market indicators in response to unpredictable disturbances. the sensitivities adjustment are important factors of economic stabilization. figures 2 and 3 represent the dynamics of output and price fluctuations after simultaneous moderate demand shock and strong output shock for different level of price adjustment for different values of parameter μ. the greater is sensitivity of price to demand-output gap the larger is the amplitude of fluctuations and less stable are output responses. the price shows very distinguish pattern for different values of adjustment coefficient. particularly for μ = 5 the price demonstrate the huge uncertainty during the long term that correspond to online shopping price changes that were observed during the pandemics. the convergence (figure 4) reveals a wide range of patterns that depends on sensitivity of price to discrepancy between capacity to kozytskyy, et al.: output and energy prices fluctuations in response to market shocks: system dynamic modeling international journal of energy economics and policy | vol 13 • issue 2 • 2023464 figure 1: system dynamic model of output and energy prices adjustments to shocks source: elaborations of authors figure 2: the dynamics of output fluctuation after simultaneous for different level of price adjustment source: authors’ evaluation figure 3: the dynamics of price fluctuation after simultaneous for different level of price adjustment source: authors’ evaluation figure 4: the convergence path of output and price for different level of price adjustment after different shocks source: authors’ evaluation figure 5: the phase diagram of wage and inflation convergence dynamics in case of stable node (δ = –3) source: authors’ evaluation consume and real output production capability. if sensitivity is not strong, the economics reaches a new steady state much faster. on the other hand, for large price susceptibility the market oscillates for long period after shock occurred and does not characterizes by close restricted area of convergence points. the stronger is shocks the complicated is the convergence path. the dynamic properties of system (3) – (4) significantly depend on properties of its eigenvalues. we investigate five different cases starting with the case when δ is negative and next moving of the system along the axis of δ. if δ < –2 both eigenvalues ρ1, ρ2 are kozytskyy, et al.: output and energy prices fluctuations in response to market shocks: system dynamic modeling international journal of energy economics and policy | vol 13 • issue 2 • 2023 465 figure 8: the dynamics of wage gap in transitory period for different value of δ in case of unstable focus source: authors’ evaluation figure 7: the phase portrait of wage and inflation convergence to a stable focus with various values of parameter δ from (–2; 0) area source: authors’ evaluation figure 6: the dynamics of wage and inflation in transion period and steady state from different initial points for δ = –1.5 source: authors’ evaluation real and negative so equilibrium point (0,0) is steady and describes the stable node. regardless of the initial point the system moves to the equilibrium point where wage gap as well as inflation gap are zero (figure 5). if δ is negative but greater than –2 both eigenvalues ρ1, ρ2 are complex with negative real parts and variables reach the equilibrium in the long-run (figure 6). the fixed point describes the stable focus (figure 7). for δ = 0. the both eigenvalues have table 1: the simulation results for wage and inflation gaps in case of unstable node parameter’s value δ=2.2 δ=3 δ=4.5 δ=6 gpi gw gpi gw gpi gw gpi gw initial values of system variables 0.5000 0.9053 0.5000 0.9053 0.5000 0.9053 0.5000 0.9053 t=1 1.3261 0.1507 1.3830 0.0514 1.4279 –0.1095 1.4368 –0.1636 t=2 0.9607 –0.8054 1.0192 –0.7038 1.1070 –0.5099 1.1765 –0.3651 t=3 –1.1751 –3.9491 –1.2726 –4.9061 –0.8868 –7.0814 0.0776 –4.4773 t=4 –1.9395 0.2995 –1.9568 0.2252 –1.9985 0.1470 –2.0387 0.1072 t=5 –1.5863 0.4210 –1.7061 0.2833 –1.8416 0.1686 –1.9266 0.1177 t=6 –1.0155 0.8404 –1.3656 0.4269 –1.6570 0.2047 –1.8022 0.1323 t=7 1.1042 4.0805 –0.6657 1.3369 –1.4201 0.2826 –1.6597 0.1549 t=8 1.9559 –0.2954 2.0659 0.0508 –1.0251 0.6171 –1.4869 0.1964 t=9 1.6086 –0.4116 1.8705 –0.2426 1.8194 3.6385 –1.2469 0.3091 t=10 1.0591 –0.7928 1.5954 –0.3191 1.9765 –0.1497 –0.6295 1.6218 t=11 –0.8830 –4.0974 1.1871 –0.5584 1.8163 –0.1728 2.0611 –0.1053 t=12 –1.9716 0.2882 –0.1333 –3.5467 1.6262 –0.2123 1.9512 –0.1152 t=13 –1.6305 0.4027 –2.0136 0.2106 1.3768 –0.3032 1.8297 –0.1287 t=14 –1.1003 0.7506 –1.7771 0.2642 0.9237 –0.7806 1.6917 –0.1491 t=15 0.6677 3.9276 –1.4686 0.3718 –2.0698 –0.2839 1.5270 –0.1848 t=16 1.9868 –0.2796 –0.9372 0.8480 –1.9541 0.1525 1.3076 –0.2711 t=17 1.6519 –0.3944 1.7756 2.8670 –1.7904 0.1772 0.8701 –0.8537 t=18 1.1394 –0.7129 1.9319 –0.2302 –1.5941 0.2209 –2.0830 0.1002 t=19 –0.4659 –3.6421 1.6746 –0.2927 –1.3302 0.3285 –1.9752 0.1128 t=20 –2.0015 0.2685 1.3173 –0.4575 –0.7914 1.0590 –1.8565 0.1254 source: authors’ evaluation kozytskyy, et al.: output and energy prices fluctuations in response to market shocks: system dynamic modeling international journal of energy economics and policy | vol 13 • issue 2 • 2023466 zero real parts so are purely imaginary. in this case ρ1 = –i, ρ2= i and the fixed point exhibits a center for positive value of δ the shape of the phase diagram change dramatically and the fixed point becomes unstable. therefore, the system reveals a bifurcation point at the value δ = 0. if δ is positive and <2, the eigenvalues are complex. their real parts are positives and fixed point exhibits an unstable focus (figure 8). for δ greater than 2 the eigenvalues are real and both positive. the fixed point establishes an unstable node (table 1) and is determined as a repeller. 4. conclusions these days when we experience many consequences of covid-19 crisis and even more severe problems caused by war in ukraine the concern of policymakers in the whole word is real output stability, energy prices predictability, unemployment recovering and providing safe employment. the policy of each country is focused on issues related to mitigation of recession. the situation is unstable and substantive complicated. it is important that not all output and energy prices movement are undesirable. in the short and medium period, some part of output fluctuation reflect not only demand shocks, lack of flexibility in energy prices and nominal wages, but correspond with changes in growth rate of the productivity and production capacity. some short run fluctuations are related to changes in technologies, trade conditions, labor force movement. thus, it is vital for policymakers to be able to minimize fluctuations of output and inflation around their natural trends, as well as around their flexible-price levels. references babenko, v., panchyshyn, a., zomchak, l., nehrey, m., artymdrohomyretska, z., lahotskyi, t. (2021), classical machine learning methods in economics. wseas transactions on business and economics, 18, 209-221. bazhenova, o., oliskevych, m., lukianenko, i. (2020), regime switching modeling of unemployment rate in eastern europe. journal of economics, institute of economic research of slovak academy of sciences, 68(4), 380-408. bielinskyi, a., khvostina, i., mamanazarov, a., matviychuk, a., semerikov, s., serdyuk, o., solovieva, v., soloviev, v. (2021), predictors of oil shocks, econophysical approach in environmental science. iop conference series: earth and environmental science, 628(1), 012019. dorczak, r., farnicka m., nowosad, i. (2021), dilemmas in managing the covid-19 crisis, risks. mdpi, 9(5), 1-14. guryanova, l., yatsenko, r., dubrovina, n., babenko, v. (2020), machine learning methods and models, predictive analytics and applications. in: ceur workshop proceedings. vol. 2649, p. 1-5. guryanova, l., bolotova, o., gvozdytskyi, v., sergienko, o. (2020), long-term financial sustainability: an evaluation methodology with threats considerations. rivista di studi sulla sostenibilita, 2020(1), 47-69. hayakawa, k., mukunoki, h. (2021), the impact of covid-19 on international trade: evidence from the first shock. journal of the japanese and international economies, 60(c), 101135. heimberger, p. (2020), potential output, eu fiscal surveillance and the covid-19 shock. inter-economics, 55(3), 167-174. hernández, g. (2019), output co-movement between latin america and the united states: the export structure matters. international review of applied economics, 33(3), 402-425. hryhoruk, p., khrushch, n., grygoruk, s. (2020), using multidimensional scaling for assessment economic development of regions. international journal of industrial engineering and production research, 31(4), 597-607. hryhoruk, p., khrushch, n., grygoruk, s., gorbatiuk, k., prystupa, l. (2021), assessing the impact of covid-19 pandemic on the regions’ socio-economic development: the case of ukraine. european journal of sustainable development, 10(1), 63-80. kaminskyi, a., nehrey, m., komar, m, (2020), complex risk analysis of investing in agriculture etfs. international journal of industrial engineering and production research, 31(4), 579-586. maman, y.k., maleki, a. (2022), energy mix optimization from energy security perspective based on stochastic models. international journal of energy economics and policy, 12(1), 1-8. matviychuk, a. (2006), fuzzy logic approach to identification and forecasting of financial time series using elliott wave theory. fuzzy economic review, 11(2), 51-68. matviychuk, a., novoseletskyy, o., vashchaiev, s., velykoivanenko, h., zubenko. i. (2019), fractal analysis of the economic sustainability of industrial enterprise. ceur workshop proceedings. vol. 2422, p. 455-466. lukianenko, i., oliskevych, m. (2017), evidence of asymmetries and nonlinearity of unemployment and labour force participation rate in ukraine. prague economic papers, 26(5), 578-601. oduyemi, g., owoeye, t. (2020), oil price fluctuation and health outcomes in an oil exporting country: evidence from nigeria. international journal of energy economics and policy, 10(4), 212-220. оliskevych, m., beregova g., tokarchuk, v. (2019), fuel consumption in ukraine: evidence from vector error correction model. international journal of energy economics and policy, 8(5), 58-63. oliskevych, m., lukianenko, i, (2020), european unemployment nonlinear dynamics over the business cycles: markov switching approach. global business and economics review, 22(4), 375-401. shepherd, b. (2018), international input-output linkages and exogenous shock transmission: a simple model. economics bulletin, 38(4), 2362-2370. skrypnyk, a., nehrey, m. (2015), the formation of the deposit portfolio in macroeconomic instability. in: ceur workshop proceedings. vol. 1356. p. 225-235. tokarchuk, v., оliskevych, м. (2018), dynamic modelling of nonlinearities in the behaviour of labour market indicators in ukraine and poland. economic annals xxi, 169(1-2), 35-39. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 1 • 2022 383 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(1), 383-389. the impact of urbanization on energy demand: an empirical evidence from somalia abdimalik ali warsame1,2* 1faculty of economics, simad university, mogadishu, somalia, 2garaad institute for social research and development studies, mogadishu, somalia. *email: abdimalikali1995@gmail.com received: 17 august 2021 accepted: 21 december 2021 doi: https://doi.org/10.32479/ijeep.11823 abstract somalia is recovering from a long-period of civil unrest and political instability. the urbanized population are growing at unprecedented rate, and there is an energy supply shortage. little is understood the nexus between urbanization and energy consumption in the context of somalia. to this end, this study assesses the effect of urbanization on energy demand in somalia while controlling the effects of economic growth and population growth. to achieve the aim, the study employs fully modified ordinary least square (fmols), canonical cointegration regression (ccr) and impulse response function (irf) with time series data spanning from 1990 to 2018. before the long-run model estimation, augmented dickey-fuller (adf) and philips’s perron (pp) tests – used for unit root test – demonstrated that all the variables are stationary at the first difference i (1). the empirical results indicate that urbanization impedes energy consumption, whereas economic growth and population growth increase energy demand in the long-run. besides, the result of irf demonstrate that one standard deviation shock in urbanization (lnub) results in energy consumption to decrease (lnec) in the whole 10 periods. this calls for the somali policy makers to consider urbanization as an effective determinant while targeting energy conservation policy in order to mitigate the fossil fuel energy use. keywords: energy demand, urbanization, fmols, irf, somalia jel classifications: q41, q43, q48 1. introduction urbanization is an issue of social and economic modernization. it does not only imply the transformation of rural labor from agriculture-based economy to industrial and service sector economy in urban areas, but it also involves the structural change of rural areas into urban areas. however, these processes lead to rapid growth in fossil fuel energy demand which releases carbon dioxide emissions into the atmosphere (nguyen and ngo, 2019). nevertheless, the nexus between urbanizationenergy-environment issues have been studying extensively in the literature in recent decades including, inter alia, energy consumption and urbanization; environmental pollution and urbanization. (poumanyvong and kaneko, 2010; sbia et al., 2017; shahbaz et al., 2017). somalia is considered one of the fastest urbanizing countries in africa. its current urban population is estimated at 6.45 million people which makes up 45% of the total population. and it is growing a substantial annual average rate of 4.2%. the un department of economic and social affairs predicted that somalia urban population will overtake the rural population in 2026 (aubrey and cardoso, 2019). the urbanization – which is measured for the urban population – shows an increasing trend in somalia since in 1990, despite there were periodical reductions in some years, namely in 2006-2007 (figure 1). but 2008 and onward, the urban population soared back substantially. the rapid urban population in somalia is partly attributed to internal displacements that resulted from conflicts and droughts. but unfortunately, these internal displaced people are reported to live in vulnerable circumstances and require durable solutions. this journal is licensed under a creative commons attribution 4.0 international license warsame: the impact of urbanization on energy demand: an empirical evidence from somalia international journal of energy economics and policy | vol 12 • issue 1 • 2022384 energy insecurity is one of the hurdles currently confronting by the rapid growth of the urban population due to limited supply of energy in somalia. firewood and charcoal are the predominant energy consumption which represents 80% 90% of the total energy consumption (federal government of somalia, 2015; african development bank, 2015) somali population who can access electricity is one of the lowest rates in east african countries. only 36% of the total population have access to the electricity energy compared to 69.7% in kenya and 48.3% in ethiopia as of 2019. it is notable that electricity price in somalia is one of the highest in the world (world bank, 2021). depending on traditional biomass energy does not cover energy demand sufficiently, rather than it erodes the ecosystem, depletes natural resources and degrades the environment (warsame & sarkodie, 2021). hence, this ultimately induces climate change and hamper agriculture production (warsame et al., 2021). there is no a consensus reached about urbanization and energy consumption nexus in the existing literature. some plausible explanations for this inconclusive result can be the data and methods used, and the impacts of urbanization on energy consumption at different levels of development. on one hand, urbanization enhances energy consumption through the linkages of urban infrastructure, energy usage within civil buildings, mobility and transportation needs, and industrial production (madlener and sunak, 2011; liu et al., 2020). accordingly, the extant literature revealed that urbanization increases electricity, energy and coal consumption in china (lv et al., 2019; yang et al., 2019). in the same vein, the positive impact of urbanization on energy consumption has been found in middle east and north african (mena) countries. but the positive result was only found in high income countries (al-mulali et al., 2013). urbanization exerts an increase in energy demand through urban infrastructure. the impact of urbanization on energy demand is examined in china (madlener and sunak, 2011). it is reported that energy demand rises due to an increase in urbanization through an expansion in infrastructure. utilizing a panel data of 78 countries, sheng et al. (2017) reported that urbanization stimulates energy consumption. this result corroborates with several cross country studies (see; mrabet et al., 2019). in a recent study conducted by torasa et al. (2020) in thailand – utilizing a time series data and an ardl bound test – has found that urban sprawls exerts energy demand to increase (torasa et al., 2020). on the other hand, urbanization inhibits energy demand through economies of scale, shortened travel distances due to compact city layout and urban transportation system. accordingly, several empirical studies uncovered the reducing impact of urbanization on energy demand (sarkodie and adom, 2018; poumanyvong and kaneko, 2010). determinants of energy consumption in kenya were modeled using the nonlinear iterative partial least squares (nipals) method. it is reported that urbanization reduces energy consumption due to economies of scale (sarkodie and adom, 2018). some studies argue that the effect of urbanization on energy demand is dependent on the stage of development of a country or region. this implies that urbanization reduces energy demand in low-income countries and stimulates it in high income nations. a cross country analysis that divided the sample countries into low-income and high-income countries reported that urbanization reduces energy demand in low-income countries (poumanyvong and kaneko, 2010). likewise, li and lin (2015) reveals that urbanization undermines energy consumption in low-income countries but rises it in high-income countries. according to the literature reviewed above, the nexus between urbanization and energy consumption has shown inconsistent results. even though the relationship between these two variables was extensively investigated in developed and developing countries, but in the context of less developed countries, including somalia, there are limited studies. furthermore, unplanned and rapid urbanization may entrench the dynamics of clan and conflicts in somalia resulting from the evolution of cities in somalia (aubrey and cardoso, 2019). considering the unprecedented growth of urban population, severe energy shortages and significant environmental degradation that somalia is currently encountering, there is a dire need to address the role of urbanization in energy demand in somalia. nevertheless, this study contributes to the literature in several ways. first, the urbanization-energy demand nexus has been studied extensively in the literature, but no study has been considered in the context of somalia. hence, to bridge that gap this study examines the role of urbanization in energy consumption in somalia using fully modified ordinary least square (fmols) and canonical cointegration regression. second, the study also considers the response of energy demand to shock effects in urbanization by utilizing the impulse response function (irf). to achieve the aim, the study utilizes time series data spanning 1990 to 2018. the rest of the study is structured as follows; material and methods are presented in chapter two, chapter three reports empirical result and analysis and finally, chapter four concludes the study and suggests policy recommendations. 2. materials and methods 2.1. data sources to achieve the objective of the study, we utilize time series data extracted from world development indicators, the organization of islamic cooperation (oic) and our world data. the time-series data utilized spans 1990-2017. the variables include energy consumption, urbanization, economic growth and population growth. measurements and sources of the variables are presented figure 1: urban population in somalia. source: world bank, (2021) warsame: the impact of urbanization on energy demand: an empirical evidence from somalia international journal of energy economics and policy | vol 12 • issue 1 • 2022 385 table 1: variable description and source variable code description source energy consumption ec energy consumption per capita world data urbanization ub urban population world bank real growth domestic product per capita rgdpc rgdpc constant 2010 oic database population growth pg rate of population growth oic database in table 1. moreover, the trend of the series is reported in figure 2. urbanization and population growth show an increasing trend, whereas economic growth and energy consumption exhibit a decreasing trend. 2.2. econometric methodology this study examines energy consumption as a function of urbanization, economic growth and population growth in somalia. the model of the study is formulated, by following the studies of (sarkodie and adom, 2018; lv et al., 2019), as follows: lnec = + lnub + lneg + lnpgt t t t t� � � � �0 1 2 3 � (1) lnect is the natural logarithm of energy consumption, lnubt is the natural logarithm of urbanization, lnegt the is natural logarithm of economic growth, lnpg is the natural logarithm of population growth and εt is the disturbance term. all the series were converted into natural logarithm, to avoid heteroskedasticity problem, model mis-specification functional form and non-normality. the objective of this study is to investigate the long-run effects of urbanization, economic growth and population growth on energy consumption in somalia, hence, we utilize fully modified ordinary least square (phillips and hansen, 1990) and canonical cointegration regression (park, 1992). some of the limitations in time series data include endogeneity problem and serial correlation, however, fully modified ordinary least square and canonical cointegration regression are robust for these issues. it implies that they address the serial correlation and endogeneity problem that arises from the cointegration results. these two methods are asymptotical equivalent. one of the strengths of fully modified ordinary least square is that its ability to eradicate the second-order bias issues (phillips and hansen, 1990). it is also robust for series containing a unit root problem or not and produces a consistent and efficient results even in the absence of level relations. however, to model the parameters’ long-run coefficient elasticities by employing fully modified ordinary least square; yt the regressand – and xt (is a vector of explanatory variables where xt is an m x 1 vector and t= 1,2,3,….,n) should satisfy the following condition: y x dt t t t� � �' ' µ� � 1 (2) x xt t t� ��1 2µ (3) where dt is a vector of deterministic trend regressors; µt= (µ1t, µ2t’)’ are the error terms. following this, λ and ω, which are the long-run covariance matrix, can be estimated by using the following two equations. e t ti ( )µµ ' ��� �10 11 12 21 22 � � � � � (4) figure 2: trends of the sampled variables. (a) population growth (b) energy consumption (c) economic growth (d) urbaization a b dc warsame: the impact of urbanization on energy demand: an empirical evidence from somalia international journal of energy economics and policy | vol 12 • issue 1 • 2022386 table 2: descriptive statistics lnec lneg lnpg lnub mean 5.720889 4.580071 0.992356 3.562565 median 5.732026 4.518522 1.117071 3.538173 maximum 6.334368 4.988526 1.177336 3.779999 minimum 5.496287 4.498364 0.117356 3.389732 std. dev. 0.156198 0.144161 0.291145 0.122808 skewness 2.071193 2.030195 −2.123202 0.403549 jarque-bera 73.94418 25.93314 32.58924 2.074847 probability 0.000000 0.000002 0.000000 0.354367 correlation lnec 1 lneg 0.6445 1 lnpg −0.2872 −0.7798 1 lnub −0.6926 −0.6267 0.5392 1 table 3: unit root tests variable adf pp level first difference level first difference lnec −7.0145** −9.9176*** −5.7692*** −9.9176*** lneg −25.4733*** −6.2791*** −3.0029 −6.1671*** lnpg −5.8071*** −6.1932*** −2.0597 −3.2030 lnub −2.2708 −5.1483*** −2.2706 −5.2270*** ***, ** and * indicate significance level at 10%, 5% and 1% respectively. the t-statistics reported are intercept and trend � � � � � � ����� e t ti ( )µµ ' 1 11 12 21 22 � � (5) s u b s e q u e n t l y , s u p p o s e 1t 12 22 ty x + −= − φ ω ∆ty ; 12 12 12 22 t x +λ λ − φ λ ∆= , where λ12 , φ12 , �22 1� and λ22 are estimated parameters. fully modified ordinary least square employs the transformation of data and estimation transformation. if we let (yt,xt) be n+1 dimensional process i (1). then, the cointegration system can be formulated in triangular form as follows: y x dt t t t� � �' ' µ� � 1 (6) �y t t2 2� � (7) εt represent µ1t, ε2t which are assumed that they are stationary accompanied with zero mean and infinite covariance matrix ∑ and ∑ is not block diagonal. 3. empirical results and analysis 3.1. descriptive statistics the summary statistics, presented in table 2, reveals that energy consumption has a mean value of 5.7; economic growth, 4.5; population growth, 0.99; and urbanization, 3.5. energy consumption has the highest maximum value, whereas population growth has the lowest minimum value. furthermore, all the interesting parameters are positively skewed, while population growth is negatively skewed. in contrast, table 2 also reports the correlation of the interested variables. energy consumption is negatively correlated with population growth and urbanization. but it has a positive association with economic growth. economic growth is negatively correlated with population growth and urbanization. on the contrary, population growth and urbanization are positively correlated. 3.2. unit root time series data often displays a trending persistence which results in the violation of the moment of condition. as a pre-requisite step in time series data, it should be checked for persistence. this study utilized augmented dickey-fuller (adf) and philip perron (pp) tests to detect the presence of unit root problem. hence, the result reported in table 3 indicates that most of the series in level exhibit a unit root problem. nevertheless, at first difference i (1), all the series did not exhibit any unit root. it implies that the series are stationary at the first difference i(1). hence, we can proceed to estimate the long-run cointegration of the study. to assess the presence of a common deterministic trend in the variables, we use johansen multivariate cointegration test. table 4 presents the result of the johansen cointegration test. trace test indicates that there are at least two cointegrating equations. this is also verified by the maximum-eigen value which shows the existence of two cointegrating vectors. therefore, the interested parameters move together in the long-run. this implies that there is a common deterministic trend in these series. thus, economic table 4: result of johansen cointegration test hypothesis trace statistic 0.05 critical value prob.** trace test r≤0 131.7046 47.85613 0.0000 r≤1 46.95484 29.79707 0.0002 r≤2 7.753062 15.49471 0.4922 r≤3 2.94e-05 3.841466 0.9979 max-eigen r≤0 84.74980 27.58434 0.0000 r≤1 39.20178 21.13162 0.0001 r≤2 7.753033 14.26460 0.4044 r≤3 2.94e-05 3.841466 0.9979 trace and max-eigenvalue tests indicate 2 cointegrating equations at the 0.01 level growth, urbanization and population growth can be considered as the long-run forcing variables for energy consumption in somalia. the examination of the long-run coefficient parameters of the variables is conducted after finding out the presence of longrun cointegration of the series. for robustness purpose, two cointegration methods namely, fmols and ccr estimated and compared their results accordingly as reported in table 5. the empirical results of fmols reveal that economic growth exerts a positive effect on energy consumption increase. a 1% increase in economic growth leads to energy consumption to increase 0.95% in the long-run. the canonical cointegration regression verifies and produces an asymptotically equivalent result. a 1% increase in economic growth results in energy consumption increasing by 0.85% in the long-run. the long-run results of economic growth on energy demand are in line with several previous studies (see; adom et al., 2012; konuk et al., 2021; salari et al., 2021) who found that economic growth enhances energy consumption. warsame: the impact of urbanization on energy demand: an empirical evidence from somalia international journal of energy economics and policy | vol 12 • issue 1 • 2022 387 furthermore, population growth tends to increase energy consumption of energy. as reported in table 5, population growth has a significant positive effect on energy consumption in somalia in the long-run. in fmols results, a 1% increase in population growth leads to an energy consumption by about 0.33% in the long-run. this result is verified by the findings of canonical cointegration regression which reports that 1% increase in population growth leads to an energy consumption to increase by about 0.31% in the long-run. these results are corroborated with sarkodie and adom (2018) and rahman (2020) who concluded that population growth tends to rise energy consumption. on the contrary, urbanization effect on energy consumption is far from conclusive. even though majority of the literature found out that urbanization leads to increase in energy consumption, but some others concluded that urbanization exerts a negative effect on energy consumption. in fmols results, it shows that urbanization affects energy consumption negatively. a 1% increase in urbanization leads to energy consumption to decrease by about 0.76% in somalia in the long-run. in same vein, urbanization hampers energy consumption by about 0.80% in the long-run, if it is increased in 1% as shown by canonical cointegration regression. the adverse effect of urbanization on energy consumption is supported by several previous studies (li and lin, 2015; poumanyvong and kaneko, 2010). but it contradicts with numerous studies that revealed that urbanization enhances energy consumption (sheng et al., 2017; yu et al., 2020). however, the rise in urbanization induces an increase in energy consumption in high-income countries. but in low-income countries, it impedes energy demand (poumanyvong and kaneko, 2010). regarding our finding of the negative impact of urbanization on energy consumption seems to emphasize the presence of urban compaction, even though, the services of somalia cities are yet to be fully functioning, hence, this omits the possibility that the negative effect of urbanization on energy demand results from the economies of scales for public infrastructure. but, it could be attributed to the modernization of using high efficiency and modern energy (pachauri, 2004; pachauri and jiang, 2008). 3.3. impact accounting one of the limitations of johansen multivariate cointegration, fmols and ccr are their lack of estimating the shock effects. to find out the shock effects of urbanization, economic growth and population growth on energy demand, we utilize impulse response function (irf). the result of irf reported in figure 3 demonstrate that one standard deviation shock in urbanization (lnub) results in energy consumption to decrease (lnec) in the whole 10 periods. hence, this result is in line with the long-run findings of fmols table 5: long‑run coefficient elasticities dependent variable: lnsp method (fmols) (ccr) variable coefficient coefficient lnrgdpc 0.9476*** (−3.1518) 0.8472** (2.8140) lnpg 0.3271** (2.7794) 0.3132** (2.5307) lnub −0.7593*** (−4.3895) −0.7973*** (−4.3310) constant 3.7693** (2.1570) 4.3737** (2.4228) r−squared 0.2419 0.3140 adjusted r-squared 0.1385 0.2204 long-run variance 0.0070 0.0070 figure 3: impulse response function. (a) response of lnec to lnub (b) response of lnec to lneg (c) response of lnec to lnpg a b c warsame: the impact of urbanization on energy demand: an empirical evidence from somalia international journal of energy economics and policy | vol 12 • issue 1 • 2022388 and ccr. furthermore, it is established that energy consumption responds negatively for one standard deviation shock in population growth from period 1.5 to 2.5. but from period 2.5 and onwards, the response turns into positive. this is consistent with the long-run results which revealed that population growth leads to the increase in energy demand. on the contrary, one standard deviation shock in economic growth leads to decrease in energy consumption from the first period to 8.5 period. but from 8.5 the response of energy consumption to the shocks in economic growth becomes a positive. 4. conclusion and policy implication somalia is emerging from a long period of civil war and conflicts. the urban population are growing and the cities are booming accompanied by increasing demand for energy consumption. there is a limited supply of energy to cover these growing demands. the relationship between energy demand and urbanization in somalia is not understood. however, this study ascertains the role of urbanization in energy consumption in somalia while accounting the role of economic growth and population growth in energy demand. to this end, fmols, ccr cointegration methods and irf were employed with time-series data spanning 1990 to 2018 was also used. before testing the long-run coefficients of the explanatory variables, we utilize johansen multivariate cointegration method to establish the long-run cointegration of the scrutinized variables. the empirical results demonstrate that energy consumption, urbanization, economic growth and population growth are cointegrated in the long-run. furthermore, the long-run results of fmols and ccr methods reveal that urbanization impedes the energy consumption in the long-run. in the same vein, the irf shock effects of urbanization leads to energy consumption to respond negatively in the short-run which is consistent with the long-run findings. in contrast, economic growth and population growth tend to increase energy consumption in the long-run. besides, it is established that energy consumption responds negatively for one standard deviation shock in population growth from period 1.5 to 2.5. but from period 2.5 onwards, the response turns into positive. this is consistent with the long-run results which revealed that population growth leads to an increase in energy demand. on the contrary, one standard deviation shock in economic growth leads to decrease in energy consumption from the first period to 8.5 period. but from 8.5 the response of energy consumption to the shocks in economic growth becomes a positive. this is contradictory with the long-run results which revealed that economic growth exerts a positive effect on energy consumption. in light of this finding, to tackle the energy consumption – typically fusil fuel energy – and ensure the sustainable development in somalia, energy policies relate to the reduction of firewood and charcoal should be instigated. notably, firewood and charcoal are the main sources of energy consumption in somalia. hence, somali policy makers should consider urbanization as an effective determinant while targeting energy conservation policy in order to mitigate the fossil fuel energy use. moreover, a paradigm shift from nonrenewable energy to clean energy are also critical for sustainable economic growth and the growing demand for energy due to the rapid growth of the population and economy. references adom, p.k., bekoe, w., akoena, s.k.k. (2012), modelling aggregate domestic electricity demand in ghana: an autoregressive distributed lag bounds cointegration approach. energy policy, 42, 530-537. african development bank. (2015), somalia energy sector needs assessment and investment programme. abidjan, côte d’ivoire: african development bank. al-mulali, u., fereidouni, h.g., lee, j.y.m., sab, c.n.b. (2013), exploring the relationship between urbanization, energy consumption, and co2 emission in mena countries. renewable and sustainable energy reviews, 23, 107-112. aubrey, d., cardoso, l. (2019), towards sustainable urban development in somalia and idp durable solutions at scale. united nations. federal government of somalia. (2015), somalia’s intended nationally determined contributions (indcs). villa somalia: federal government of somalia. konuk, f., zeren, f., akpınar, s., yıldız, ş. (2021), biomass energy consumption and economic growth: further evidence from next-11 countries. energy reports, 7, 4825-4832. li, k., lin, b. (2015), impacts of urbanization and industrialization on energy consumption/co2 emissions: does the level of development matter? renewable and sustainable energy reviews, 52, 1107-1122. liu, x., sun, t., feng, q., zhang, d. (2020), dynamic nonlinear influence of urbanization on china’s electricity consumption: evidence from dynamic economic growth threshold effect. energy, 196, 117187. lv, y., chen, w., cheng, j. (2019), modelling dynamic impacts of urbanization on disaggregated energy consumption in china: a spatial durbin modelling and decomposition approach. energy policy, 133, 110841. madlener, r., sunak, y. (2011), impacts of urbanization on urban structures and energy demand: what can we learn for urban energy planning and urbanization management? sustainable cities and society, 1(1), 45-53. mrabet, z., alsamara, m., saleh, a.s., anwar, s. (2019), urbanization and non-renewable energy demand: a comparison of developed and emerging countries. energy, 170, 832-839. nguyen, d.t., ngo, t.q. (2019), dynamics of household-level energy access in vietnam during 2002-2014. international journal of energy economics and policy, 9(2), 132-145. pachauri, s. (2004), an analysis of cross-sectional variations in total household energy requirements in india using micro survey data. energy policy, 32, 1723-1735. pachauri, s., jiang, l. (2008), the household energy transition in india and china. energy policy, 36, 4022-4035. park, j. (1992), canonical cointegrating regressions. econometrica, 60(1), 119-143. phillips, p.c.b., hansen, b.e. (1990), statistical inference in instrumental variables regression with i(1) processes. review of economic studies, 57(1), 99-125. poumanyvong, p., kaneko, s. (2010), does urbanization lead to less energy use and lower co2 emissions ? a cross-country analysis. ecological economics, 70(2), 434-444. rahman, m.m. (2020), exploring the effects of economic growth, population density and international trade on energy consumption and environmental quality in india. international journal of energy sector management, 14(6), 1177-1203. salari, m., kelly, i., doytch, n., javid, r.j. (2021), economic growth and renewable and non-renewable energy consumption : evidence from the us states. renewable energy, 178, 50-65. sarkodie, s.a., adom, p.k. (2018), determinants of energy consumption in kenya: a nipals approach. energy, 159, 696-705. sbia, r., shahbaz, m., ozturk, i. (2017), economic growth, financial warsame: the impact of urbanization on energy demand: an empirical evidence from somalia international journal of energy economics and policy | vol 12 • issue 1 • 2022 389 development, urbanisation and electricity consumption nexus in uae. economic research-ekonomska istrazivanja, 30(1), 527-549. shahbaz, m., chaudhary, a.r., ozturk, i. (2017), does urbanization cause increasing energy demand in pakistan? empirical evidence from stirpat model. energy, 122, 83-93. sheng, p., he, y., guo, x. (2017), the impact of urbanization on energy consumption and efficiency. energy and environment, 28(7), 673-686. torasa, c., sittisom, w., mekhum, w. (2020), what difference urban sprawl, industrialization and migration can make in energy consumption? a time-series analysis of thailand. international journal of energy economics and policy, 10(5), 577-583. warsame, a.a., sarkodie, s.a. (2021), asymmetric impact of energy utilization and economic development on environmental degradation in somalia. environmenatl science and pollution research, 67, 1–13. warsame, a.a., sheik-ali, i.a., ali, a.o., sarkodie, s.a. (2021), climate change and crop production nexus in somalia: an empirical evidence from ardl technique. environmental science and pollution research, 28, 19838-19850. world bank. (2021), world bank. available from: https://data.worldbank. org/indicator/eg.elc.accs.zs?locations=so [last accessed on 2021 aug]. yang, y., liu, j., lin, y., li, q. (2019), the impact of urbanization on china’s residential energy consumption. structural change and economic dynamics, 49(2019), 170-182. yu, y., zhang, n., dae, j. (2020), impact of urbanization on energy demand: an empirical study of the yangtze river economic belt in china. energy policy, 139, 111354. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 6 • 2021 35 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(6), 35-42. electric power bid determination and evaluation for price taker units under price uncertainty ahmet yucekaya1*, jorge valenzuela2 1department of industrial engineering, kadir has university, 34083, turkey, 2department of industrial and systems engineering, 304 shelby center, auburn university, auburn, alabama 36849, usa. *email: ahmety@khas.edu.tr received: 10 april 2021 accepted: 20 july 2021 doi: https://doi.org/10.32479/ijeep.11382 abstract power companies aim to maximize their profit which is highly related to the bidding strategies used. in order to sell electricity at high prices and maximize their profit, power companies need suitable bidding models that consider power operating constraints and price uncertainty within the market. price taker units have no power to affect the prices but need to determine their best bidding strategy to maximize their profit assuming a quadratic cost function and uncertain market prices. price taker units also need to evaluate their bidding strategy under different price scenarios. in this paper, we first model the bidding problem for a price taker unit and then propose quadratic programming, nonlinear programming and marginal cost based bidding models under price uncertainty. we use case studies to study the computation burden and limitation to reach a solution. we also propose a simulation methodology to evaluate the performance of each bidding strategy for different market prices in an effort to help decision makers to assess their bidding decisions. keywords: bidding, nonlinear programming, quadratic programming, simulation, electricity markets jel classifications: l94, d44, d47, e17 1. introduction electricity is generally accepted as different from other commodities. it is still not storable economically, and its demand is instantaneous, so it must be produced and used in real time while the demand is continuous. these unique characteristics of electricity and the necessity of real time balance create a need for coordinated markets in which power plants, transmission grid, and distribution lines have to be in a close but well-defined relationship. the price is strongly load dependent, highly volatile, seasonal and consumption dependent. the elasticity of electricity demand to price is low as electricity is a unique commodity, and it is difficult to replace it. also, small consumers are not affected by instant price changes as a utility company usually provides their electricity. the parameters are stochastic, which gives a stochastic behaviour to the electricity price. energy consumption, fuel costs, availability of fuels, equipment capacity and market participants’ behaviour are stochastic and unknown to other players. the market prices are set based on the economic principles where all sellers’ agree to deliver the cumulative demand and all buyers’ agree to buy the offered quantity at a determined price level. the bilateral energy markets have their own structure; and the price is unique in that it is determined between the buyer and the seller. in poolco and power exchanges, on the other hand, the buyers and sellers receive the market price determined in auctions after the buy and sell offers are submitted. the main objective of the market is to provide a perfect competitive environment in which an independent system operator (iso) is responsible for the coordination of physical operations that include scheduling the generation, making sure they continue the balance of supply and demand, supporting services for reliability, and coordination with other markets. iso oversees the system operation; determines the transmission schedule; and has the right this journal is licensed under a creative commons attribution 4.0 international license yucekaya and valenzuela: electric power bid determination and evaluation for price taker units under price uncertainty international journal of energy economics and policy | vol 11 • issue 6 • 202136 to take measures against players that do not respect the generation or the consumption plan. perfect competition and oligopoly are two models of interest in the deregulation of the electricity market. thermal plants such as coal and gas fired units have nonlinear cost functions; and their marginal costs are related to the quantity of produced electricity. in practice, a deregulated market is not considered perfectly competitive due to the limited number of suppliers. a supplier tends to bid higher than its marginal cost as a solution to strategic bidding problem (sbp) (david and wen, 2000). a power supplier or producer aims to maximize its profit and decrease its risks, and he needs to submit bids to the market considering its constraints and market conditions. the markets that the bids are submitted to can be classified as day-ahead, hourahead, real time; and the reserve market in which the actual time remaining for operation differs. a submitted bid might be accepted if the price is lower than the market clearing price (mcp), and the offer will be cleared with the market price. on the other hand, if the offered bid is above the hourly mcp, then the offer will not be selected; and there will be no revenues. assuming a uniform bidding mechanism, all bidders will be paid with mcp as it is important to be in accepted bids for the price taker units since they do not have the power to affect the market price. on the other hand, for the pay as bid (pab) type mechanism, the bidder will receive what he has offered if his bid is accepted. then, the main objective of sbp is to determine the proper price and quantities for the power that will be submitted to the market. knowledge about mcp is the most important parameter for the decision making process about bidding blocks. a block consists of a price and corresponding power quantity. if a player is a market maker, then he can affect the market price using his power capacity as in oligopoly models such as cournot (kian et al., 2005) or the supply function equilibrium (rajaraman and alvarado, 2003). these models need the cost data of the market players, which are often not available. they also face some issues such as lack of equilibrium or the existence of multiple equilibriums. on the other hand, if the future values of mcp can be accepted as a random variable like in (valenzuela and mazumdar, 2003) and (yucekaya et al., 2009), mcp can be considered exogenous, and can be included in the decision making process (mazzi et al., 2017). such an approach is even more suitable for price taker units as they do not have the power to affect the mcp. it is shown that generating units can be considered separately if the price is assumed exogenous (valenzuela and mazumdar, 2003). when analysing a price taker and other players in a competitive market, the behaviours of other players are ignored, and the problem of the price taker player is simplified. such an approach requires the price taker player to predict the final price of the market according to which he will take an action. if the interactions need to be analyzed, game theory is commonly used to analyze the behaviours of the players and finding the equilibrium. agent based simulation models also provide a framework to reach the equilibrium; and they are commonly used when the complexity of the problem increases (yucekaya and valenzuela, 2013). these models also help to observe the interaction between players when they aim to maximize their individual objective function until all of them reach an equilibrium. as the day-ahead market is repeated daily, the players are able to learn the rules and observe the consequences of their strategies and reactions of other players. the market prices might converge to stable distributions for off-peak periods or when the demand forecast is simplified. on the other hand, repetition also gives suppliers the option to change their bidding strategies if an opportunity arises as a result of factors such as transmission congestion, higher demand, and rule change (mathur et al., 2017a). there are many efforts in the literature to analyse the bidding mechanism in the markets. the bidding strategies used in the market are discussed in (david and wen, 2000), (prabavathi and gnanadass, 2015) and (mathur et al. 2017b). they present a detailed review of the bidding strategies in competitive markets. as bidding problem has dynamic interaction and market operations, both optimization and heuristic approaches are used to model and solve the bidding problem for market players. optimal control (liu and wu, 2006), game theory (song et al., 2003) and (kian and cruz, 2005), lagrangian relaxation (zhang et al., 2000), dynamic programming (jiang and powell, 2015), bilevel programming and swarm (zhang et al., 2010), information gap decision theory (nojavan et al., 2015), shuffled frog leaping algorithm (kumar and kumar, 2014), point estimate method (peik-herfeh et al., 2013), stochastic cournot model (sharma et al., 2014), stochastic optimization (davatgaran et al., 2018), and (song and amelin, 2017), and simulation (yucekaya, 2013) are some of the recent research areas on the bidding problem. it is also possible to use hybrid models and include operational characteristics to model and solve the bidding problem. senthilvadivu et al. (2019) propose a hybrid technique that includes recurrent neural network, support vector machine, and the lightning search algorithm to develop bidding strategies aiming to reach maximum profit for suppliers and consumers. nazari and ardehali (2019) propose a bidding strategy development method in day-ahead and spinning reserve markets considering emission and wind, pumped storage, and thermal system. the research for price maker and price taker bidding strategy need to be separated (sadeghi-mobarakeh and mohsenian-rad, 2016). song and amelin (2017) develop a bidding strategy for a price-maker retailer with flexible demands including the risk levels. kohansal and mohsenian-rad (2015) develop a stochastic optimization framework to determine bid and a corresponding quantity for the market. such studies need to analyse the impact of their bids on the market price. there are some studies that only focus on developing price taker bidding approaches such as conejo et al. (2002); de ladurantaye et al. (2007); and fleten and pettersen (2005). mazzi et al. (2017) propose a stochastic optimization method for a price taker unit that is bidding in a two-settlement way, and pab electricity market. they generate electricity market prices and use scenarios for the day-ahead and balancing market. mathur et al. (2017) propose a genetic algorithm based method for price taker units in which they consider both symmetric and asymmetric information for the decision making process. in this paper, as a contribution to literature, we model the sbp for price taker electric power generators, and find a solution yucekaya and valenzuela: electric power bid determination and evaluation for price taker units under price uncertainty international journal of energy economics and policy | vol 11 • issue 6 • 2021 37 using quadratic and nonlinear programming given that the power producer has imperfect price estimations. however, an optimal solution can only be obtained within a reasonable computational time for a limited number of price scenarios as the computational time increases exponentially as the size of the problem increases. we also propose a marginal cost based bidding methodology where a power producer can submit its marginal cost as a bid. it is worth mentioning that the prices are accepted as exogenous and a market player has no perfect information for the upcoming prices. hence, the offered bids need to be evaluated for different price scenarios. in order to evaluate a bidding strategy for any given market price scenarios, we propose a spreadsheet based simulation algorithm to evaluate bids and help companies with their decision analysis. the remainder of this paper is organized as follows. section 2 provides a description of the market design and bidding mechanism. the formulation of the problem with different methods is introduced in section 3. section 4 provides a case study for different price scenarios in an effort to measure the performance of the proposed methods. finally, in section 5, the concluding remarks are provided. 2. the market design and bidding 2.1. the pjm market design federal energy regulatory commission in the usa proposed a standard market design (smd) concept in 2002 for the standardization of electric power markets in the usa. this design and its variants are adopted by many other markets in different regions (cramton, 2017). the objective of a typical smd is to develop a market structure that brings together the physical system and the financial operations. this is achieved by defining the roles and the interaction of system components. smd also deals with the system governance, market operations, risk management, market monitoring and conflict resolutions that might occur among the members. the pjm interconnection is a federally regulated and non-profit organization that manages the transmission of wholesale electricity in 13 states involving more than 65 million people. pjm’s members include power generators, transmission owners, electricity distributors, power marketers, and large consumers. pjm assumed its iso position in 1996, and introduced bid based pricing and locational marginal while it acts independently in managing the wholesale electricity market. smd aims to increase competition; hence, it is a good place where suppliers and consumers meet under the supervision of an iso and economic fundamentals. the balancing of supply and demand is always crucial in an economic market. however, it is vital for an electricity market since the lack of electricity when needed can lead to very costly consequences. 2.2. bidding in pjm power market the market players need to submit bids for both buying and selling the power in the day ahead market. an offer includes at most ten price and corresponding quantity pairs. these blocks need to be submitted to the day ahead market until noon before the actual operation day. the players might estimate the hourly mcp’s but need not communicate with each other, and need to keep their offers and cost data as a secret. smds usually use uniform price auctions and pab auctions to govern the market mechanism. after the bids are submitted, and the market is settled by the system operator, all the dispatched generators in the uniform price auction are paid the market price whereas they got paid their bid price in pab auction. the selection process for winning generators and the equilibrium price are the same for both designs with the difference that the generators would make different revenues. a supplier or generator expects to maximize its profit once its generation cost is deducted. when the player is a price taker unit, his first objective is to be selected as a dispatched unit; and for that, he needs to submit a price lower than the mcp. on the other hand, if the mcp is lower than his marginal cost he might be making a loss instead of a profit if he submits a price lower than his marginal cost. pjm also limits the offered prices with a price cap. the day ahead bids are financially binding commitments; and the day ahead prices remain fixed for all transactions scheduled in the day ahead market. the deviations from the day ahead prices are expected; and the real time prices are used to price these deviations. on the other hand, if a generator bids into the market, and fails to deliver as scheduled, he is still liable for the quantity for which he will be charged at the real time market price. a generator offer for the pjm market is composed of two components: the price and quantity of electricity that a supplier is willing to generate. offers are submitted in blocks of price quantity pairs. pjm allows submitting at the most ten blocks for a generator offer. figure 1 illustrates a valid offer curve in pjm power market. each generating unit also submits its minimum run time, minimum down time, no-load costs and start-up costs to the pjm market. pjm runs the “two-settlement” software to determine the hourly commitment schedules and the lmps. generating units that have minimum run times that exceed 24 h are asked by pjm to submit binding offer prices for the next 7 h. 3. the problem formulation and solution approach the suppliers and buyers bid into the market in an effort to maximize their objective, which is to maximize its profit and minimize its cost, respectively. if the supplier has a capacity enough to impact the price, then he might manipulate the market with his actions. on the other hand, if the supplier has a limited capacity, he has to follow the market flow and accept the mcp. we assume a thermal power generator, which obtains its revenue by selling its power to pjm market. such a generator has no power to affect mcp in the day-ahead market, and is willing to accept the hourly price to generate committed quantity (yucekaya et al., 2009). sbp then can be modeled for a price taker unit in which its decisions do not affect the market prices. in order to submit to the day ahead market, n price-quantity blocks at the most need to be determined each day considering the capacity and estimated market prices. given that the purpose of this paper is to analyze and test the proposed models, we exploit a fundamental model for generating market prices, instead of using real market data. mcp values at each hour are assumed as random variables whose probability distribution has known parameters, and they are fed to the model as exogenous values. yucekaya and valenzuela: electric power bid determination and evaluation for price taker units under price uncertainty international journal of energy economics and policy | vol 11 • issue 6 • 202138 the bids are valid for the day ahead market for the next day, and this process is repeated each day. for such a generator, there are n pairs of decision variables bi and ∆qi need to be determined. the variable ∆qi denotes the amount of energy increase in block i to get the bid price bi for delivery at any hour of the next day which are represented by the vectors ∆q and b, respectively. as the smd assumes uniform bidding, if the mcp at hour t is equal to or higher than the bi, then the last offer at this price or lower are accepted and got paid by mcp. thus, the total energy to be produced at time t and sold to the market at a price pt is given by: q qt i i i pt � � �� 1 ( ) , where i p j b pt j t( ) � �max such that for t=1.t; i=1.i(pt) (1) the profit for the day-ahead market for a 24-h period can be assumed as the total revenue gained from power sales at each hour, and the cost of generation is deducted for the generated power quantities. note that the generator makes a revenue if it generated power during hour t at the market price, pt ($/mwh). as pt is a random variable, then the total profit over a period of t hours is also a random variable. for the cases where there are price scenarios, k samples of the hourly prices which have an equal probability of occurrence can be assumed. then, the objective becomes maximizing the expected profit over the time period t (usually 24 h) considering prices at each hour t of sample k as pt k and generated power of at each hour t of sample k as qt k. under the light of these assumptions, the bidding problem p(δq, b) can be represented as follows: p( e[profit]”q b ”q b , ) max [ ( )] , � � � �� ��1 11 k p q c qt k t k t k t t k k for k=1.k; t=1.t; (2) there are some constraints that are related to market conditions, and generator operations as stated below. a bid price is limited with the price cap as in eq. 3. a bid quantity increase and total commitment cannot be above the generator capacity (eq. 4 and eq. 5). a bid is selected only if the bid price is lower than mcp (eq. 6). the cost of the energy produced by the generating unit depends on the amount of fuel consumed and is typically approximated by a quadratic cost function (eq. 7). the coefficient a1 represents the fixed cost or no-load cost for each hour. the value a2 represents the linear cost which is proportional to the amount of power produced. the parameter a3 is the quadratic cost coefficient, and it is related to the amount of fuel used to produce electricity. 0 < bi < b max for i=1.n. (3) �q qi i n � � � 1 max (4) 0 < δqi < q max for i=1.n. (5) q qt k i i i pt k � � � � 1 ( ) , i p i b pt k i t k ( ) � �max such that for k=1.k; t=1.t; i=1.i(pt k) (6) c q a a q a qt k t k t k ( ) ( )� � � 1 2 3 2 for k=1.k; t=1.t. (7) 3.1. quadratic programming model the supplier aims to maximize its expected profit considering that the market prices are uncertain and he has constraints related to generation. given that the submitted bidding strategy is valid for 24 h, and there are 24 hourly prices, one might reach a solution by finding a bid price for each hour. however, the number of price-quantity blocks n is limited to 10; and then at most 10 pairs of price and quantity pairs need to be determined and submitted to the market. quadratic programming (qp) is one way to find an optimal solution to the bidding problem. however, it can solve relatively smallsized problems as the solution space gets larger when the number of prices increases. by setting the number of samples to one, and the number of maximum bidding blocks equal to the number of hours of the time horizon, a quadratic programming model can be formulated. notice that when the market price consists of one sample and the number of blocks are equal to the number of hours, the optimal bidding price of a block of power is equal to one of the market prices. therefore, the bidding problem in eq.2, 4, and 6 is reduced to the following mathematical representation: max z = [ ]pq a q a qt t t t t t � � � � 2 3 2 1 for t=1...,n (8) subject to the following constraints: �q qi i n � � � 1 max for i=1...,n (9) q qt i i t � � �� 1 for t=1...,n (10) δqi ≥ 0 for i=1...,n (11) as the objective function has a polynomial component, and the constraints are linear, a solution for at most 10 hourly prices can be found by using such an approach. however, if the supplier has more price scenarios than he expects, it will not be possible to include all samples in this method. 3.2. nonlinear programming model it is still possible to force the bid prices to be in close proximity of the expected hourly prices, and also include more samples if additional constraints are added. nonlinear programming (nlp) figure 1: a generator’s offer curve in the pjm day-ahead market yucekaya and valenzuela: electric power bid determination and evaluation for price taker units under price uncertainty international journal of energy economics and policy | vol 11 • issue 6 • 2021 39 is the process of solving a problem that includes equalities, inequalities, constraints, and an objective function some of which is nonlinear. the proposed problem has nonlinear equalities which make the computation time larger than expected. the process finds a set of unknown real variables that makes the objective function maximized or minimized. the market prices are unknown when the bidding decision is made; hence the problem should be developed for scenarios instead of only one price sample. having the same problem as in eq. 2, the nlp will have the following constraints: mz i p bt k t k i( ) .� �1 001 for i = 1..n; t = 1..t; k = 1..k. (12) m z i p bt k t k i( ( ) )� � �1 for i = 1..n; t = 1..t; k = 1..k. (13) z i z it k t k ( ) ( )� � �1 0 for i = 1..n; t = 1..t; k = 1..k. (14) bi ≤ bi+1 for i=1..n. (15) 1–ri ≤ mδqi for i=1..n. (16) δqi ≤ q max (1–ri) for i=1..n. (17) ri ≤ ri+1 for i=1..n. (18) q z i qt k t k i i n � � � ( )� 1 q z i qt k t k i i n � � � ( )� 1 for i = 1..n; t = 1..t; k = 1..k. (19) eq. 3, 4, 5, and 7. note that m is a large number, and z and r are binary variables that force the bid prices to be in close proximity to market prices. it is expected that a solution can be found for a limited number of price samples using nlp. it is also important to note that the bidding is a daily process, and a solution should be determined each day within a limited time frame. 3.3. marginal cost bidding in a perfectly competitive market, each player is expected to submit its costs as it will get paid by mcp when selected if it is in a uniform price auction. such an approach is practical as an offer is selected only if the mcp is larger than the bid price. as an alternative, the power supplier could split the maximum capacity into n blocks of identical sizes, and offer them at prices equal to the marginal costs of producing each block. as the number of blocks is limited in different markets, n can be determined based on the market. then, for the same problem of eq. 2, the constraints can be formulated as below. �q q ni � max for i=1..n. (20) b a a qi t k� � 2 3 2 for k=1..k; t=1..t; i=1..n. (21) eq. 3, 6, and 7. such an approach will let the generator run for different levels of market prices as the bidding strategy will have n different prices. the amount of power the generator will supply will be different at each price level, and the generator will increase the chance of being selected as a unit for dispatch in the market. this approach needs no computational time; hence, it might be preferred by the suppliers who need a reliable but less time-consuming methodology, given that the bidding is a daily process, and it has tight time schedules for bid submission. 3.4. bid simulator in order to evaluate a bidding strategy for given market price scenarios, a simulation methodology can be utilized. the simulation method should include different price samples, and should be able to work for different cost functions. we develop a simulation model called the bid simulator that includes market price scenarios and calculates hourly profits according to the market prices to evaluate a bidding curve. this fundamental model generates a set of electricity market price forecasts, which is required as an input to our proposed offering strategy. if the market price at a particular hour is larger or equal to any given price bid, the supplier would sell power. otherwise, it would not sell power at that hour. in order to generate market price samples, the simulation methodology uses the monte carlo method and mean and variance of the historical prices. the pseudocode for the simulation is given in figure 2. it is obvious that a bidding strategy can return a different profit for different market price scenarios. the methodology provides the expected profit of each bidding strategy over k price samples, and supportive statistical outputs to the decision maker such as statistical outputs, probabilistic distributions and confidence intervals. it is also worth mentioning that a bidding strategy that is found using qp, nlp or marginal cost based bidding can still be evaluated over k price samples. also, expected profits can be analyzed to make better analyses considering that those solutions are found for limited price samples; and simulation includes k price samples. 4. numerical studies for bidding the proposed models are tested in the pjm market mechanism using pjm market prices. the power producer needs to determine his/her bidding offer which consists of at the most 10 prices ($/mwh) and corresponding quantity mwh pairs to be submitted figure 2: pseudo code of the simulation model 0: determine bid prices and quantities, bi and ∆qi 1: generate k price samples each for 24 hours 2: for each k 3: for each hour t 4: for each block i in the bidding curve 5: if bidding price bi <= market price ptk 6: calculate hourly profit 7: else 8: hourly profit=0 9: next block i 10: next hour 11: daily profit = sum (hourly profit) 12: next sample 13: average profit = sum (daily profit )/k yucekaya and valenzuela: electric power bid determination and evaluation for price taker units under price uncertainty international journal of energy economics and policy | vol 11 • issue 6 • 202140 table 2: optimum solution to nlp problem block 1 2 3 4 5 6 7 8 9 bi ($/mwh) 45.01 45.54 46.10 46.16 46.39 46.52 46.56 46.87 47.56 qi (mwh) 51.19 65.47 130.94 138.08 165.46 180.93 211.88 222.59 261.28 table 3: bid prices and quantities for marginal cost bidding block 1 2 3 4 5 6 7 8 9 10 bi ($/mwh) 45.25 45.50 45.75 46.00 46.26 46.51 46.76 47.01 47.26 47.52 qi (mwh) 30 60 90 120 150 180 210 240 270 300 table 1: optimum solution to qp problem block 1 2 3 4 5 6 bi ($/mwh) 45.50 45.90 46.10 46.80 47.10 50.20 qi (mwh) 59.52 107.14 130.95 214.28 250.00 300.00 figure 3: market price samples from pjm day ahead market to iso until noon each day. iso will collect sell bids and buy bids consecutively will run the security constrained economic dispatch mechanism in which the resources are assigned based on their offer characteristics; and day ahead market price is determined for each hour based on the cumulative supply and demand. the market price data is released regularly paying attention to confidential cost data of each supplier. as the proposed methodologies consider price taker bidding strategies, we have arbitrarily selected 10 price samples from pjm power market. figure 3 shows the price samples. note that pjm market is one of the largest power markets, and the shape of the market prices is affected by habits and work hours. the demand is low at night, but it starts to increase as people go to their daily routines, and it is higher in the evening with different patterns on weekdays, weekends, and on public holidays. we consider a thermal generator whose cost function is c(q) = 45q + 0.0042q2 with a maximum capacity of 300 mw. such a generator can be considered a price taker, and he has no power to affect with such a capacity the day ahead market price. the supplier is willing to accept the market price, and he needs to submit a bid strategically in an effort to cover different price levels and maximize its expected profit. the supplier might target specific hours in the day-ahead market, and prefer to reach an optimum solution. for such a case, the qp model can be used to solve the problem by setting the time horizon to 10 h as it is equivalent to the number of bidding blocks. the solution for 10 h market prices is given in table 1. after solving the above model using cplex, the optimal profit is found to be $1772.48. in order to increase the reliability of his bidding strategy, the supplier can include more price samples and can find a bidding strategy. as qp is limited with the number of blocks, the bidding problem under market price uncertainty is solved with nlp. the problem is structured in ampl and submitted to one of the neos servers minlp to get a solution. after a number of iterations and computational time, a solution is found for 3 day price samples. table 2 provides the optimum solution. the objective function of the optimum solution was $44,779.83. however, it takes about 5 h to solve the problem with 3 price samples and 300 mwh capacity. if we increase the capacity to 1500 mwh and try to solve the problem with the same price samples, we could not find an optimal solution after a 24-h run. results show that it is not likely to solve the problem with more than 3 price samples. the marginal cost bidding model requires splitting the maximum capacity into equal block sizes. pjm accepts a maximum of ten energy blocks in its daily bidding process, so the maximum capacity can be split into 10 blocks, and the marginal cost of these quantities can be offered to the market. we solve the problem by using the same generator with the price samples given in figure 2. table 3 gives the price and quantities for marginal cost bidding. if a high variability is expected at the market prices, the supplier prefers the marginal cost based bidding model in an effort to yucekaya and valenzuela: electric power bid determination and evaluation for price taker units under price uncertainty international journal of energy economics and policy | vol 11 • issue 6 • 2021 41 decrease his risk, cover the different price levels, and increase the chance of being selected as a dispatched unit. the marginal cost model is evaluated for both price samples used in qp and nlp. the profit found for 10-h price sample is $1766.58 where the optimum solution in qp is $1,772.48. the profit found in 3 day price samples is $44,750.86 where the optimum solution in nlp is $44,779.83. although the profit increases by 0.33% and 0.06% in qp and nlp respectively might seem to be small, such numbers represent huge gains considering the volume of the transactions for each operation day. we also verified the solutions using a bid simulator. it is also possible to increase the number of price samples and evaluate the effectiveness of each bidding strategy using a bid simulator. the success level of a bidding strategy is related to its effectiveness against different market price scenarios. a bid simulator is designed to include the desired number of market prices from different power markets to increase the reliability of a bidding strategy. the solution to the marginal cost based bidding model is to evaluate in the bid simulator using 10 price samples given in figure 3. the supportive statistics for the decision making process is given in table 4. it is also possible to calculate the mean profit with a defined confidence interval. 5% confidence interval for the mean profit is $49709.59 and $49954.39. the distribution of the profits along with the probabilities are provided in an effort to support the decision making process. figure 4 provides the cumulative distribution function of the profits. 5. conclusions and policy implications the bidding process is daily and the suppliers need to make a decision within a limited time frame. the bidding strategy should be carefully determined according to the price taker or price maker nature of the unit. in this paper, the strategic bidding model for price taker units is analysed; and possible solution approaches and their limitations are explained. it is shown that qp is able to find a solution for small problems where the number of price scenarios is limited. nlp can find a solution for more price scenarios, but as the problem gets larger, it gets difficult to find a solution. the solution method should require low computational time as there is a tight schedule each day. as another alternative, it is shown that a generator can turn its marginal cost into bidding blocks and submit them to the market. the simulation methodology is used to evaluate the bidding offers found in quadratic programming, nonlinear programming, and marginal cost bidding, as well as to present the statistical results for each offer. the bid simulator can be used to extend the analysis to increase the number of price samples, and the presented statistical results can be used. also, a sensitivity analysis can be performed for the decision making process. the presented models and solution approaches, besides filling a gap in the literature, can be used by market players if they do not affect the market price and have imperfect information about market prices. the paper proposes fast and reliable solution methods to the strategic bidding problem that can be adapted by the suppliers, and the proposed simulation methodology has the potential to help decision makers when evaluating a bidding strategy. references conejo, a.j., nogales, f.j., arroyo, j.m. (2002), price-taker bidding strategy under price uncertainty. ieee transactions on power systems, 17(4), 1081-1088. cramton, p. (2017), electricity market design. oxford review of economic policy, 33(4), 589-612. davatgaran, v., saniei, m., mortazavi, s.s. (2018), optimal bidding strategy for an energy hub in energy market. energy, 148, 482-493. david, a.k., wen, f. (2000), strategic bidding in competitive electricity markets: a literature survey. in: 2000 power engineering society summer meeting (cat. no. 00ch37134). vol. 4. ieee. p2168-2173. de ladurantaye, d., gendreau, m., potvin, j.y. (2007), strategic bidding for price-taker hydroelectricity producers. ieee transactions on power systems, 22(4), 2187-2203. fleten, s.e., pettersen, e. (2005), constructing bidding curves for a price-taking retailer in the norwegian electricity market. ieee transactions on power systems, 20(2), 701-708. jiang, d.r., powell, w.b. (2015), optimal hour-ahead bidding in the realtime electricity market with battery storage using approximate dynamic programming. informs journal on computing, 27(3), 525-543. kian, a.r., cruz, j.b. jr. (2005), bidding strategies in dynamic electricity markets. decision support systems, 40(3-4), 543-551. kian, a.r., cruz, j.b., thomas, r.j. (2005), bidding strategies in oligopolistic dynamic electricity double-sided auctions. ieee transactions on power systems, 20(1), 50-58. figure 4: market price samples from pjm day ahead market table 4: statistics for the expected profits parameter value maximum profit ($) 53340.23 minimum profit ($) 47784.47 expected profit ($) 49831.99 standard deviation 1974.83 variation 3899952 95% percentile ($) 53083.52 5% percentile ($) 47870.75 yucekaya and valenzuela: electric power bid determination and evaluation for price taker units under price uncertainty international journal of energy economics and policy | vol 11 • issue 6 • 202142 kohansal, m., mohsenian-rad, h. (2015), price-maker economic bidding in two-settlement pool-based markets: the case of time-shiftable loads. ieee transactions on power systems, 31(1), 695-705. kumar, j.v., kumar, d.v. (2014), generation bidding strategy in a pool based electricity market using shuffled frog leaping algorithm. applied soft computing, 21, 407-414. liu, y., wu, f.f. (2006), generator bidding in oligopolistic electricity markets using optimal control: fundamentals and application. ieee transactions on power systems, 21(3), 1050-1061. mathur, s., arya, a., dubey, m. (2017), a review on bidding strategies and market power in a competitive energy market. ieee international conference on energy, communication, data analytics and soft computing. mathur, s.p., arya, a., dubey, m. (2017), optimal bidding strategy for price takers and customers in a competitive electricity market. cogent engineering, 4(1), 1358545. mazzi, n., kazempour, j., pinson, p. (2017), price-taker offering strategy in electricity pay-as-bid markets. ieee transactions on power systems, 33(2), 2175-2183. nazari, m.e., ardehali, m.m. (2019), optimal bidding strategy for a genco in day-ahead energy and spinning reserve markets with considerations for coordinated wind-pumped storage-thermal system and co2 emission. energy strategy reviews, 26, 100405. nojavan, s., zare, k., ashpazi, m.a. (2015), a hybrid approach based on igdt-mpso method for optimal bidding strategy of price-taker generation station in day-ahead electricity market. international journal of electrical power and energy systems, 69, 335-343. peik-herfeh, m., seifi, h., sheikh-el-eslami, m.k. (2013), decision making of a virtual power plant under uncertainties for bidding in a day-ahead market using point estimate method. international journal of electrical power and energy systems, 44(1), 88-98. prabavathi, m., gnanadass, r. (2015), energy bidding strategies for restructured electricity market. international journal of electrical power and energy systems, 64, 956-966. rajaraman, r., alvarado, f. (2003), optimal bidding strategy in electricity markets under uncertain energy and reserve prices. power systems engineering research center report, wi. sadeghi-mobarakeh, a., mohsenian-rad, h. (2016), strategic selection of capacity and mileage bids in california iso performance-based regulation market. in: 2016 ieee power and energy society general meeting (pesgm). ieee. p1-5. senthilvadivu, a., gayathri, k., asokan, k. (2019), modeling of bidding strategies in a competitive electricity market: a hybrid approach. international journal of numerical modelling: electronic networks, devices and fields, 32, e2594. sharma, k.c., bhakar, r., tiwari, h.p. (2014), strategic bidding for wind power producers in electricity markets. energy conversion and management, 86, 259-267. song, m., amelin, m. (2017), price-maker bidding in day-ahead electricity market for a retailer with flexible demands. ieee transactions on power systems, 33(2), 1948-1958. song, y., ni, y., wen, f., hou, z., wu, f.f. (2003), conjectural variation based bidding strategy in spot markets: fundamentals and comparison with classical game theoretical bidding strategies. electric power systems research, 67(1), 45-51. valenzuela, j., mazumdar, m. (2003), commitment of electric power generators under stochastic market prices. operations research, 51(6), 880-893. yucekaya, a. (2013), bidding of price taker power generators in the deregulated turkish power market. renewable and sustainable energy reviews, 22, 506-514. yucekaya, a., valenzuela, j. (2013), agent-based optimization to estimate nash equilibrium in power markets. energy sources, part b: economics, planning, and policy, 8(2), 209-216. yucekaya, a.d., valenzuela, j., dozier, g. (2009), strategic bidding in electricity markets using particle swarm optimization. electric power systems research, 79(2), 335-345. zhang, d., wang, y., luh, p. (2000), optimization based bidding strategies in the deregulated market. ieee transactions on power systems, 15(3), 981-986. zhang, g., zhang, g., gao, y., lu, j. (2010), competitive strategic bidding optimization in electricity markets using bilevel programming and swarm technique. ieee transactions on industrial electronics, 58(6), 2138-2146. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 4 • 2023 383 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(4), 383-388. can digital human capital mitigate co2 emissions? empirical test for post-communist countries bekhzod djalilov1, islomjon kobiljonov1, raufhon salahodjaev2,3* 1tashkent metropolitan university, tashkent, uzbekistan, 2akfa university, tashkent, uzbekistan tashkent state university of economics, uzbekistan, 3ergo analytics, tashkent, uzbekistan. *email: salahodjaev@gmail.com received: 25 april 2022 accepted: 22 april 2023 doi: https://doi.org/10.32479/ijeep.11885 abstract this study investigates the relationship between internet users, a proxy for digital human capital, and co2 emissions in a sample of post-communist countries over the period 1990-2019. the results suggest that internet diffusion is negatively and significantly correlated with co2 emission even after controlling for other economic antecedents of environmental degradation. moreover, using fixed effects two-stage least squares estimator, we document that internet has causal impact on carbon emissions. in the full specification, a 10 percentage points increase in internet use leads to 4.2% decrease in co2 emissions across post-communist countries. these results remain intact even when we introduce additional control variables in the model and conduct analysis on sub-samples. the papers highlights that human capital leads to sustainable development in developing countries. keywords: ict, internet, carbon emissions, post-communist jel classifications: q5 1. introduction carbon emissions is one of the most important global problems and have negative implications for the society. as suggested by who 4.2 million people die annually due to the health impacts of air pollution. empirical studies report that carbon emissions increase infant mortality (currie and neidell, 2005), decrease life expectancy (murthy et al., 2021) and life satisfaction (ferreira et al., 2013). present study aims to explore the effect of internet on co2 emissions across post-communist countries. internet play a crucial role in the technological advance, but albeit the internet usage has substantially increased over the past decade, its diffusion remains to be significantly uneven. for example, in 2018 only approximately 75% of population in former communist countries had access to internet compared to 82% in oecd countries or 83% in euro area nations. internet as one of the dimensions of digital revolution is an important catalyst for the development of society as it carries numerous hopes for the developing economies, enabling them to jump across the levels of development and reach developed nations. at the same time in emerging and transition economies, ict infrastructure quality has been underdevelopment and the policymakers tend to place lower priorities compared to industries on the development agenda. for example, ict investment in russia is forecast to reach 1.4% of gdp1 compared to 3.5% in switzerland or 2.3% in uk. consequently, the ict penetration in developing countries is relatively low and the speed of internet relative to its cost is better in developed countries. cross-country studies suggest that internet is essential for social and economic progress and quality of life. for example, canh et al. (2020) using data for 87 nations over the period 2002-2014 1 https://store.globaldata.com/report/kg0220ci--ict-investment-trends-inrussia-enterprise-ict-spending-patterns-through-to-the-end-of-2017/ this journal is licensed under a creative commons attribution 4.0 international license djalilov, et al.: can digital human capital mitigate co2 emissions? empirical test for post-communist countries international journal of energy economics and policy | vol 13 • issue 4 • 2023384 reports that internet diffusion is an important tool to decrease income inequality. moreover, the scholars estimate that digital economy accounts for the 15.5% of global output (huawei and oxford economics, 2017). considering that some of the economic activities are now in the ict sector, these shifts may influence energy consumption influencing carbon emissions. while economics growth/development and energy consumption are among two crucial variables that explain significant variations in carbon emissions, there is evidence that internet diffusion may have direct and indirect effects on co2 emissions. for example, a number of studies show that ict sector development has impact on the energy consumption across countries. salahuddin and alam (2016) document that a 10 percent rise in internet diffusion leads to nearly 0.3% rise in electricity consumption across oecd nations in the long run. furthermore, sadorsky (2012) finds that a 10% increase in internet penetration leads to an increase in 0.11% in per person electricity consumption. on the other hand, a number of studies report that internet diffusion decreases energy consumption (schulte et al., 2016). for instance, pelau and acatrinei (2019), using data from 29 nations in europe for the years 2010-2016, find that energy consumption decreases when countries make a transformation to a digital society. therefore, the results for the link between internet usage and energy (electricity) consumption are mixed and require further investigations. overall, there a number of reasons how internet usage may influence co2 emissions via energy consumption channel. first, internet sector may reduce demand for energy by improving efficiency and sectoral transformations. second, digitalization may lead to greater energy demand, and, consequently, to rise in co2 emissions due to ict sector growth, energy rebound effects and rapid economic growth (lange et al., 2020). indeed, the large strand of existing research explores the effect of internet on co2 emissions along with economic growth (lee and brahmasrene, 2014; al-mulali et al., 2015; salahuddin et al., 2016a) and energy consumption (gelenbe and caseau, 2015; lu, 2018). for example, ozcan and apergis (2018), using data for 20 emerging countries over the period 1990-2015, investigate the effect of internet diffusion on co2 emissions. the study reports that internet usage has negative effect on carbon emissions and confirms that causality runs from ict to environment. salahuddin et al. (2016b) explores the role that internet usage plays in explaining changes on carbon dioxide emissions in australia over the years 1985-2012. the authors relying on autoregressive distributive lag (ardl) bounds fail to find evidence on the significant link between ict and co2 emissions in the short run, however, impulse response and variance decomposition analysis show that internet will have impact on co2 emissions in the longrun. on the other hand, park et al. (2018) finds that internet has positive and causal long run effect on co2 emissions in selected eu countries accounting for the role of financial development, gdp growth and trade openness. one of the potential explanations the authors propose is that ict development increases the demand for energy use which has in turn effect on carbon emissions. awan et al. (2022) investigates the link between renewable energy, ict use, fdi and co2 emissions in a sample of 10 emerging countries over the years 1996-2015, using method of moments quantile regression estimator. the empirical findings confirm the evidence on non-linear relationship between gdp and environmental degradation. urbanization increases co2 emissions, while renewable energy and internet penetration mitigates environmental degradation. liu et al. (2023) explore the drivers of climate change in belt and road initiative countries over the period 2008-2020. the authors apply a large set of empirical methods such as unit root tests, granger causality tests, amg and pmg estimators. the study among others shows that energy intensity and internet use are positively linked to co2 emissions. renewable energy and economic development is inversely linked to environmental degradation. altinoz et al. (2021) assess the nexus between ict use, tfp and co2 emissions over the period 1995-2014 using the panel vector autocorrection model. the empirical results suggest that some dimension of digital human capital increase co2 emissions such as internet users and fixed phone users, while mobile usage reduces co2 emissions. however, to the best of our knowledge, no research has been carried out in the post-communist countries. in addition, extant research offers inconclusive empirical evidence on the effect of internet diffusion on co2 emissions and, hence, may not be interpolated for former communist countries. thus, ours is the first study to robustly empirically assess the relationship between internet and carbon emissions for this group of countries for the period 19902019. our study contributes to extant research in a number of ways. first, we focus on a specific group of countries that have common cultural and political heritage. as a result, our baseline results should not be significantly affected by heterogeneity in political experience that may exist in cross-country studies. second, based on carbon atlas the carbon emissions in postcommunist countries have decreased by approximately 32% since 1990. at the same time, according to world bank internet usage has increased from <1% in early 1990s to nearly 75% of population. third, from the empirical viewpoint, we enhance the framework of ahmed et al. (2019) to explore the effect ict on air pollution. compared to other panel studies, we rely on a wide range of empirical strategies and robustness checks. we also assess the causal effect of internet diffusion on co2 emissions in this region. our results suggest that internet usage is significantly and negatively linked to carbon emissions even after accounting for mediating channels such as energy use and economic growth. moreover, our empirical results show that internet has causal negative effect on co2 emissions in post-communist countries. in particular, a 10 percentage points increase in internet diffusion leads to 4.2% decrease in co2 emissions. 2. model, methodology and data in this study we depart from the stripat (stochastic impacts by regression on population, affluence and technology) framework to explore the relationship between internet and carbon emissions. the conventional specification of the model is: i p a ti i i c i d i=α ε β (1) where i is for co2 emissions; p denotes population, a is for affluence, t represents technology. we use urbanization as a proxy djalilov, et al.: can digital human capital mitigate co2 emissions? empirical test for post-communist countries international journal of energy economics and policy | vol 13 • issue 4 • 2023 385 for population, and gdp per capita is as our measure of affluence. following, xu and lin (2015) and ahmed et al. (2019) we include energy use to produce gdp in our model. internet usage, measured by percentage of population using internet, is used to capture the role of ict technology. in addition, as suggested by shahbaz et al. (2016) we include trade openness (exports + imports as a share of gdp) to capture the role of global interdependencies play in environmental degradation. as a result, we use the modified stripat model in its linear form which can be expressed as: co a internet a gdp a urban a trade a e i t i t i t i t i t 2 0 1 2 3 4 5 , , , , , = + + + + + α nnergyi t i t, ,+ε (2) where co2 is co2 emissions per capita, internet is individuals using the internet (% of population), gdp is gdp per capita adjusted for purchasing power parity, urban is share of urban population, trade is the sum of exports and imports as % of gdp and energy is energy use (kg of oil equivalent) per $1,000 gdp (constant 2017 ppp). our study uses data covering years 1990-2019. the data on carbon emissions comes from carbon atlas. the data on gdp per capita, urbanization, trade and energy intensity are obtained from world bank. the descriptive statistics are reported in table 1. while the goal of this study is to completely take advantage of the panel data that exists for post-communist nations, we first start from estimating eq. (1) using conventional ordinary least squares (ols) regression estimator. next, we proceed with fixed effects and random effects methods – a standard approach in panel data econometrics. the fixed effects (fe) method enables the researchers to take into account unobserved country specific time-invariant heterogeneity which leads to omitted variable bias (adams, 2009). the random effects (re) model also useful to assess the overall robustness of our main findings when deviations across sub-groups are random from a parent group. we also adopt panel corrected standard errors (pcse) estimator as the data in our study may be induced by simultaneous correlation across panel and heteroskedasticity. consequently, fixed effects or random effects results may generate inefficient estimates. in order to confirm the strength of our findings we re-estimate eq. (1) using pcse. on the other hand, the effect of internet on co2 emissions may not be endogenous or it could be that air polluting nations may be relying on outdated technologies or rely on economic sectors that hamper ict development. therefore, following the work of lapatinas (2019) we adopt fixed effects instrumental variable twostate least squares (fe iv 2sls) regression model strategy. we use logged number of secure internet servers per million population from world bank and civil liberties index from freedom house. 3. empirical results the baseline results are reported in table 2. column 2 presents the results from estimating eq. (2) using conventional ols regression. the coefficient for internet is negative statistically significant, suggesting that internet usage is negatively correlated with carbon emissions across post-communist countries. turning to our control variables we find that urbanization, gdp and energy intensity are positively linked to co2 emissions in our sample. these results are similar to the findings reported by qi et al. (2020) for china and chen et al. (2020) for mercosur nations. trade openness seems to be insignificant correlated of carbon emissions in our sample. column 2 re-visits our primary results using fixed effects regression estimator. the coefficients suggest that the estimates for internet usage and control variables are not quantitatively and qualitatively affected once we consider for the role that unobserved time-invariant country characteristics may play in predicting environmental degradation. for example, a 10% percentage points increase in internet usage is associated with 5.8% decrease in co2 emissions. in column 3, we adopt random effects regression model to estimate eq. (2). again, the results are nearly identical to our baseline results in columns 1 and 2. therefore, the findings in table 2 suggest that internet usage is negatively and significantly associated with co2 emissions across post-communist countries. in table 3, we attempt to overcome the limitations of the conventional estimators adopted in panel data empirical analysis. column 1 reports the results from estimating pcse estimator. the coefficient is negative and statistically significant. the signs and values of control variables are similar to the ones reported in table 2. we proceed assessing the causal effect of internet usage on co2 emissions in column 2. as discussed above we rely on fe iv 2sls strategy. the 2nd stage results confirm that internet is negative and statistically significant. this suggests that internet may have causal impact on co2 emissions. if causal, a 10 percentage points increase in internet use leads to 4.2% decrease in co2 emissions across post-communist countries. the results from the 1st stage suggest that only secure internet servers is positive and significant. the f-stat from the 1st stage is above the threshold level of 10 suggesting that our instruments are overall valid and credible. in table 4, to check robustness of our main results we extend our model by incorporating additional variables as suggested by extant cross-country studies. following, yang et al. (2020) we account for the role of globalization in explaining co2 emissions by including table 1: descriptive statistics variable description mean sd co2 emissions territorial emissions in tco₂ per person 6.05 3.86 gdp gdp per capita, ppp (constant 2017 international $) 15,022.83 9116.44 internet individuals using the internet (percentage of population) 29.20 28.49 urban urban population (percentage of total population) 57.51 11.92 trade trade (percentage of gdp) 97.89 33.18 energy energy use (kg of oil equivalent) per $1000 gdp (constant 2017 ppp) 221.40 153.17 sd: standard deviation, ppp: purchasing power parity, co2: carbon dioxide djalilov, et al.: can digital human capital mitigate co2 emissions? empirical test for post-communist countries international journal of energy economics and policy | vol 13 • issue 4 • 2023386 kof index of globalization. in order to capture the effect of economic institutions on carbon emissions, we include economic freedom index from heritage foundation. in addition, a number of studies suggest that renewable energy sector development and fdi may serve as antecedents of co2 emissions in cross-country research (naz et al., 2019). therefore, we include renewable table 2: main results variable i ii iii internet −0.0060 (7.67)*** −0.0058 (5.78)*** −0.0056 (6.09)*** urban 0.0030 (2.22)** 0.0422 (2.91)*** 0.0293 (3.49)*** gdp 1.2906 (47.13)*** 1.0402 (9.21)*** 1.0346 (9.28)*** trade −0.0002 (0.47) −0.0004 (0.74) −0.0004 (0.66) energy 0.0041 (27.25)*** 0.0032 (6.81)*** 0.0031 (6.54)*** constant −11.4180 (48.07)*** −11.1417 (7.77)*** −10.3250 (9.29)*** r2 0.87 0.70 0.70 n 521 521 521 method ols re fe *p<0.1, **p<0.05, ***p<0.01. ols: ordinary least square, fe: fixed effect, re: random effect table 3: iv 2sls and pcse variable i ii iii internet −0.0054 (8.22)*** −0.0042 (2.27)** urban 0.0043 (3.08)*** −0.0108 (0.47) 1.1646 (0.74) gdp 1.2156 (35.34)*** 1.2473 (6.42)*** 9.3554 (0.70) trade −0.0004 (1.19) −0.0037 (4.73)*** −0.1491 (2.49)** energy 0.0038 (20.57)*** 0.0034 (5.75)*** 0.0015 (0.04) servers 7.4939 (7.04)*** civil liberties 2.0549 (0.84) constant −10.7033 (34.29)*** −9.7895 (4.04)*** −128.9399 (0.79) r2 0.87 0.82 0.61 1st stage f-statistics 33.88 n 521 130 130 notes pcse fe iv 2sls 2nd stage fe iv 2sls 1st stage *p<0.1, **p<0.05, ***p<0.01. fe iv 2sls: fixed effects instrumental variable two-state least square, pcse: panel corrected standard error table 4: robustness test variable i ii iii internet −0.0059 (2.51)** −0.0034 (3.38)*** −0.0036 (4.96)*** urban −0.0198 (0.98) 0.0364 (2.27)** 0.0029 (1.61) gdp 1.1846 (7.06)*** 0.9361 (5.71)*** 1.1128 (22.71)*** trade −0.0044 (4.92)*** 0.0000 (0.06) −0.0000 (0.08) energy 0.0027 (4.75)*** 0.0025 (4.57)*** 0.0033 (17.45)*** freedom −0.0085 (1.42) −0.0035 (1.09) −0.0001 (0.10) globalization 0.0201 (2.07)** −0.0050 (1.06) −0.0032 (1.55) fdi 0.0012 (0.60) 0.0026 (1.85)* 0.0004 (0.54) renewable −0.0059 (5.03)*** −0.0044 (2.07)** −0.0042 (5.66)*** constant −9.1343 (4.11)*** −9.1885 (4.91)*** −9.3439 (20.83)*** n 130 464 464 r2 0.76 0.59 0.85 method fe iv 2sls fe pcse *p<0.1, **p<0.05, ***p<0.01. fe iv 2sls: fixed effects instrumental variable two-state least square, pcse: panel corrected standard error, fe: fixed effect, fdi: foreign direct investment table 5: sub-samples variable i ii iii internet −0.0046 (4.32)*** −0.0058 (5.25)*** −0.0049 (6.01)*** urban 0.0208 (1.10) 0.0592 (3.18)*** 0.0305 (2.99)*** gdp 0.9537 (6.73)*** 1.0302 (9.99)*** 1.1163 (10.41)*** trade 0.0001 (0.10) 0.0002 (0.31) −0.0008 (1.38) energy 0.0024 (4.92)*** 0.0034 (8.34)*** 0.0041 (11.30)*** constant −9.0254 (4.63)*** −12.1619 (8.55)*** −11.3562 (9.19)*** r2 0.55 0.76 0.77 n 357 386 472 notes 2000–2019 1990–2010 excluding outliers *p<0.1, **p<0.05, ***p<0.01 djalilov, et al.: can digital human capital mitigate co2 emissions? empirical test for post-communist countries international journal of energy economics and policy | vol 13 • issue 4 • 2023 387 electricity output as % of total electricity output and fdi as % of gdp from world bank. of these variables, only renewable energy production is robustly and negatively associated with co2 emissions. turning to our main variable of interest, internet diffusion is negative and statistically significant. finally, we test whether our results are sensitive to the choice of data points. therefore, we re-estimate eq. (1) for various subsamples in table 5. first, we restrict our time period only for 20002019. post-communist countries were associated with instable economic growth and transition shocks at early 1990’s. moreover, the internet penetration levels were relatively low until the early 2000’s across countries in this region. therefore, this may impact our main results. in column 2, we restrict our time period for the years 1990-2010 to reduce the effect of various external shocks that had effect on the development of these countries. finally, in column 3 we remove influential data points that were reported by regression post-estimation plots, namely tajikistan, uzbekistan and turkmenistan. across all columns the coefficient for internet is negative and significant. 4. conclusion the main goal of this study is to assess the effect of internet diffusion on carbon dioxide emissions in a sample of postcommunist countries. in the first step, we have used conventional methods such as ols, re and fe to assess the baseline findings. in the next step, we resorted on more sophisticated empirical strategy to account for cross-sectional dependence among panels and causality between ict and co2 emissions. thus, the study applied fixed effects instrumental variable regression estimator to assess the direction of causality. in this study, following lapatinas (2019) we used the number of secure internet servers (per 1 million people) and civil liberties index as our instruments for internet diffusion. the main results in this study are as follows. the fe and re regressions confirm that internet usage is negatively and significantly correlated with co2 emission even after controlling for other economic antecedents of environmental degradation. the fe iv 2sls coefficients suggest that internet is has causal effect on co2 emissions in the region. in the full specification, a 10 percentage points increase in internet use leads to 4.2% decrease in co2 emissions across post-communist countries. these results remain intact even when we introduce additional control variables in the model and conduct analysis on sub-samples. based on the empirical results of our study, following policy implications can be derived for countries in this region. first, internet diffusion seems to play important role in curbing air pollution in our sample. therefore, further investments in the ict sector should also have non-economic benefits for the society. our results contribute to the findings that ict sector enhances economic growth (mičetić and vlahinić-dizdarević, 2006) and innovative activities in transition countries (gërguri₂rashiti et al., 2017). second, we also document renewable energy sector is also robustly linked to reduction in co2 emissions in our analysis. therefore, policy makers can resort to a number of fiscal and economic incentives such as tax reduction, investment grants, low interest loans and grants to motivate companies invest in ict and renewable energy sectors. a number of studies from this region suggest that investment in human capital is instrumental to foster renewable energy adoption (eshchanov et al., 2021). third, our findings suggest that energy intensity has significant positive effect on co2 emissions. therefore, it is crucial to adopt energy efficient technologies to reduce the rising pressure of energy use in these countries on the environmental quality. prospective studies should explore the role that other economic variables (finance, trade, fdi) may play in explaining carbon emissions in this region. in addition, our results could be extended by exploring the link between ict and co2 emissions using subnational data from these countries. references adams, s. (2009), foreign direct investment, domestic investment, and economic growth in sub-saharan africa. journal of policy modeling, 31(6), 939-949. ahmed, z., wang, z., ali, s. (2019), investigating the non-linear relationship between urbanization and co 2 emissions: an empirical analysis. air quality, atmosphere and health, 12(8), 945-953. al-mulali, u., sheau-ting, l., ozturk, i. (2015), the global move toward internet shopping and its influence on pollution: an empirical analysis. environmental science and pollution research, 22, 9717-9727. altinoz, b., vasbieva, d., kalugina, o. (2021), the effect of information and communication technologies and total factor productivity on co2 emissions in top 10 emerging market economies. environmental science and pollution research, 28(45), 63784-63793. awan, a., abbasi, k.r., rej, s., bandyopadhyay, a., lv, k. (2022), the impact of renewable energy, internet use and foreign direct investment on carbon dioxide emissions: a method of moments quantile analysis. renewable energy, 189, 454-466. canh, n.p., schinckus, c., thanh, s.d., ling, f.c.h. (2020), effects of the internet, mobile, and land phones on income inequality and the kuznets curve: cross country analysis. telecommunications policy, 44(10), 102041. chen, s., saleem, n., saud, s., ahmad, a., ahmad, f. (2020), potential influential economic indicators and environmental quality: insights from the mercosur economies. air quality, atmosphere and health, 13, 751-762. currie, j., neidell, m. (2005), air pollution and infant health: what can we learn from california’s recent experience? the quarterly journal of economics, 120(3), 1003-1030. eshchanov, b., abdurazzakova, d., yuldashev, o., salahodjaev, r., ahrorov, f., komilov, a., eshchanov, r. (2021), is there a link between cognitive abilities and renewable energy adoption: evidence from uzbekistan using micro data. renewable and sustainable energy reviews, 141, 110819. ferreira, s., akay, a., brereton, f., cuñado, j., martinsson, p., moro, m., ningal, t.f. (2013), life satisfaction and air quality in europe. ecological economics, 88, 1-10. gelenbe, e., caseau, y. (2015), the impact of information technology on energy consumption and carbon emissions. united states: ubiquity. p1-15. gërguri₂rashiti, s., ramadani, v., abazi₂alili, h., dana, l.p., ratten, v. (2017), ict, innovation and firm performance: the transition economies context. thunderbird international business djalilov, et al.: can digital human capital mitigate co2 emissions? empirical test for post-communist countries international journal of energy economics and policy | vol 13 • issue 4 • 2023388 review, 59(1), 93-102. huawei & oxford economics. (2017), digital spillover. measuring the true impact of the digital economy. available from: https://www. huawei.com/minisite/gci/en/digital-spillover/files/gci_digital_ spillover.pdf lange, s., pohl, j., santarius, t. (2020), digitalization and energy consumption. does ict reduce energy demand? ecological economics, 176, 106760. lapatinas, a. (2019), the effect of the internet on economic sophistication: an empirical analysis. economics letters, 174, 35-38. lee, j.w., brahmasrene, t. (2014), ict, co2 emissions and economic growth: evidence from a panel of asean. global economic review, 43(2), 93-109. liu, f., khan, y., marie, m. (2023), carbon neutrality challenges in belt and road countries: what factors can contribute to co2 emissions mitigation? environmental science and pollution research, 30(6), 14884-14901. lu, w.c. (2018), the impacts of information and communication technology, energy consumption, financial development, and economic growth on carbon dioxide emissions in 12 asian countries. mitigation and adaptation strategies for global change, 23(8), 1351-1365. mičetić, l., vlahinić-dizdarević, n. (2006), the impact of ict on economic growth of transition countries. computers in education, 2006, 138-144. murthy, u., shaari, m.s., mariadas, p.a., abidin, n.z. (2021), the relationships between co2 emissions, economic growth and life expectancy. the journal of asian finance, economics, and business, 8(2), 801-808. naz, s., sultan, r., zaman, k., aldakhil, a.m., nassani, a.a., abro, m.m.q. (2019), moderating and mediating role of renewable energy consumption, fdi inflows, and economic growth on carbon dioxide emissions: evidence from robust least square estimator. environmental science and pollution research, 26(3), 2806-2819. ozcan, b., apergis, n. (2018), the impact of internet use on air pollution: evidence from emerging countries. environmental science and pollution research, 25(5), 4174-4189. park, y., meng, f., baloch, m.a. (2018), the effect of ict, financial development, growth, and trade openness on co2 emissions: an empirical analysis. environmental science and pollution research, 25(30), 30708-30719. pelau, c., acatrinei, c. (2019), the paradox of energy consumption decrease in the transition period towards a digital society. energies, 12(8), 1428. qi, x., han, y., kou, p. (2020), population urbanization, trade openness and carbon emissions: an empirical analysis based on china. air quality, atmosphere and health, 2020, 1-10. sadorsky, p. (2012), information communication technology and electricity consumption in emerging economies. energy policy, 48, 130-136. salahuddin, m., alam, k. (2016), information and communication technology, electricity consumption and economic growth in oecd countries: a panel data analysis. international journal of electrical power and energy systems, 76, 185-193. salahuddin, m., alam, k., ozturk, i. (2016a), the effects of internet usage and economic growth on co2 emissions in oecd countries: a panel investigation. renewable and sustainable energy reviews, 62, 1226-1235. salahuddin, m., alam, k., ozturk, i. (2016b), is rapid growth in internet usage environmentally sustainable for australia? an empirical investigation. environmental science and pollution research, 23(5), 4700-4713. schulte, p., welsch, h., rexhäuser, s. (2016), ict and the demand for energy: evidence from oecd countries. environmental and resource economics, 63(1), 119-146. shahbaz, m., loganathan, n., muzaffar, a.t., ahmed, k., jabran, m.a. (2016), how urbanization affects co2 emissions in malaysia? the application of stirpat model. renewable and sustainable energy reviews, 57, 83-93. xu, b., lin, b. (2015), how industrialization and urbanization process impacts on co2 emissions in china: evidence from nonparametric additive regression models. energy economics, 48, 188-202. yang, b., jahanger, a., khan, m.a. (2020), does the inflow of remittances and energy consumption increase co2 emissions in the era of globalization? a global perspective. air quality, atmosphere and health, 13(11), 1313-1328. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(1), 355-364. international journal of energy economics and policy | vol 12 • issue 1 • 2022 355 decomposition factors household energy subsidy consumption in indonesia: kaya identity and logarithmic mean divisia index approach eka sudarmaji1*, noer azam achsani2, yandra arkeman3, idqan fahmi2 1doctoral student, ipb university and university of pancasila, jakarta. indonesia, 2school of business, ipb university, bogor, indonesia, 3department of agro-industrial technology, faculty of agricultural technology, ipb university, bogor, indonesia. *email: esudarmaji@univpancasila.ac.id received: 12 september 2021 accepted: 28 november 2021 doi: https://doi.org/10.32479/ijeep.12629 abstract for decades, the subsidy had prompted excessive waste while offering little motivation to boost energy efficiency or reduce domestic greenhouse gas emissions in indonesia. this paper aimed to measure household subsidy energy by examining the relationship between the ten variables factors with household energy subsidy. the logarithmic mean divisia index (lmdi) decomposition index were deployed to recognize the determinant effects that drive a household’s subsidy energy consumption. this study also presented an ardl model applied. the robustness of the granger causality, long-run, and short-run causality during 1990-2017 was assessed. based on lmdi analysis, we found out that population, income per capita, ratio national renewal energy over fuel fossil, gross capital stock, urban household consumption, and ratio household subsidy were the positive factors that aggravated the change in household energy subsidy. the negative sign of ratio national energy intensity effect, ratio fossil renewal energy effect, ratio capital labour substitution, and ratio household over labour force signified the decreasing of less household energy subsidy. on the ecm, we identified a negative sign speed-of-adjustment and significant at 1%. it implied that all the ten variable factors were converging in the long run after an experience shock. the equation parameters were considered stable since the cusum gets inside the two critical lines. additional reset test of the stability to ascertain whether the estimated model was linear or correctly specified has been performed. keywords: ardl, ecm, households subsidies energy, lmdi, kaya index jel classifications: p18, p28, q47 1. introduction the increasing population of indonesia also increased the number of households and urbanization. according to the ministry of energy and mineral resources republic of indonesia (2018), indonesia’s population reached 261,891 million, with the number of households reaching 67.173 million people. based on the world bank data, more than 55.33% of the total population lives in the cities (world bank group, 2016). that makes indonesia had become one of the fastest urbanized countries in the world. the increase in households triggered demand and the drastic use of electronic household appliances and increased energy consumption in indonesia. as a result, the household sector had become the second-largest energy consumer. most of the sources of energy consumption were derived from fossil sources, which led to an increase in co2 emissions (krstic and krstic, 2015). the increase in energy use was also due to subsidies provided by the government (nasip and sudarmaji, 2018). these subsidies in the household sector encouraged industries to use fossil energy wastefully. therefore, the research problems this journal is licensed under a creative commons attribution 4.0 international license sudarmaji, et al.: decomposition factors household energy subsidy consumption in indonesia: kaya identity and logarithmic mean divisia index approach 356 international journal of energy economics and policy | vol 12 • issue 1 • 2022356 discussed in this study were: (1) indicators of household energy consumption subsidies, explaining many developments in energy use and energy subsidies, and (2) there were so many factors that affect the relationship between energy use, activity, and economic structure. these problems were clear indicators for different industries, and background information on factors affecting the relationship between energy use and necessary activities can provide a reasonable interpretation of aggregate indicators. this study outlined indonesia’s energy consumption subsidy into ten variables factors and incorporated them into ten effects using the lmdi approach. we analyzed changes in every ten variables’ effects then deployed the time series to investigate the causality between all effects related to indonesia’s energy consumption growth. it used cointegration panels and causality analysis. research on decoupling analysis between economic-gdp growth and co2 emissions to provide indicators of determining factor measurement or energy consumption had become popular since the oecd environment minister in 2001 placed it as the oecd’s environmental strategy. then popularity grew as several studies, such as kojima and bacon (2009) also de freitas and kaneko (2011), combined decoupling with an index decomposition approach. some researchers used the decoupling decomposition analysis with lmdi and econometrics methods such as vecm (moutinho et al., 2015; sadikova et al., 2017; wu, 2014; zhao et al., 2017). with most researchers taking the study in the national sphere, the other researchers decided to enter into different business sectors fields, such as zhao et al. (2017). as they argue, it was essential to assess the sectoral industrial situation at every stage to know the root of the problems. this study took toba and seck’s (2016) framework that put all decomposition factors into social, technical, environmental, and economic aspects. they integrate technical, environmental, and social aspects into the energy system to become the primary support tool for energy policy. zhang and su (2016) selected ten rural household energy consumption indicators, then put all of the factors into dimensions: social, economic, technical, and environmental. their research used the same concept as pui and othman (2019): aggregate decomposition results in economic, technical, and social aspects. the aim was to determine the relative intensity of these three effects on changes in emissions. the objectives to be achieved in this study were to investigate the impacts of energy subsidy and how the government explores energy savings targets for 2025 and 2050 in line with government expectations. therefore, this study mainly analyzed the relationship between household energy subsidies in indonesia with the other ten variables from 1990 to 2017. the logarithmic mean divisia index (lmdi) and kaya index were used to recognize the effects that drive indonesia’s energy subsidy’s evolution. 2. literature review the laspeyres index and the divisia index were two standard index decomposition (ida) analyses. the laspeyres index calculates percentage changes in some aspects of a variable over time using weights based on the value in a few previous years. the divisia index, on the other hand, was a weighted number of logarithmic growth rates, where weight was a component factor in total value. ida was a commonly used decomposition method due to its adaptability, ease of use, and relatively low data requirements. ang (2015) provided a rundown of ida’s advantages and drawbacks, advocating for the general use of the logarithmic average divisia index (lmdi). under the laspeyres index method, the effect was calculated in the same way as presented in the section above on the ‘scenario’ but taken the percentage change from base year to year. this approach had disadvantages because, among other things, it did not consider interactions in decomposition. it meant that variations in decomposition variables did not always add to the exact energy consumption change. the aim was to determine the relative intensity of these three effects on changes in emissions (cansino et al., 2019). lmdi was used to replace the laspeyres index and amdi in early 1990. lmdi is used by the iea then widely followed by most researchers in the field of energy. prospective lmdi analysis, usable: 1) future forecasts based on the predicted unraveling effects of retrospective analysis, 2) parse energy saving projections or emissions reductions for next year periodically through decomposition or emission levels for the year for two different scenarios, where one scene is the usual business case (bau), and 3) align and compare projection results across different models and scenarios through measuring drivers or underlying effects that provide an everyday basis for comparison. 2.1. household energy subsidy consumption model the authors used variables that expanded to ten variables using the extended kaya identity to estimate household energy subsidy consumption (hesconsumption = e.c.). the formula was as follows: national energy consumption gdp� � � primaryenergy gdp nationalennergyconsumption primaryenergy (1) for household energy consumption subsidy, the formula become: household energy subsidy population� � � gdp population primaryennergy gdp nationalenergyconsumption primaryenergy household � � eenergyconsumption nationalenergyconsumption householdenerg � yysubsidi householdenergyconsumption (2a) when we include renewal energy, capital formation, and labour force, the formula is as follows: sudarmaji, et al.: decomposition factors household energy subsidy consumption in indonesia: kaya identity and logarithmic mean divisia index approach international journal of energy economics and policy | vol 12 • issue 1 • 2022 357 household energy subsidy population� � � gdp population primaryennergy gdp renewalenergyconsumption primaryenergy fossil fue � � � llenergyconsumption renewalenergyconsumption capitalformati � oon fossil fuelenergyconsumption� (2a) the lmdi formula can be rewritten as follows: hes =pop t t × × × × × × × × gdp pop e gdp re e fr re k fr l k hs l he t t t t t t t t t t t t t t cc hs hes hec t t t t × (3) hest = popt × ipt × eit × ret × frt × iet × klt × hst × hect × hest (4) hest= popteffect × ipeffect × ei t effect × re t effect × fr t effect × ieteffect × kl t effect × hs t effect × hec t effect × hes t effect (5) whereas: pop = population effect ip = income per capita effect gdp pop t t ei= ratio national energy intensity effect e gdp t t re= renewal energy energy substitution, ratio national renewal energy effect re e t t fr= fossil fuels renewal energy substitution, ratio fossil renewal energy effect fr re t t ie= investment efficiency ratio gross capital stock over renewal energy k re t t kl= capital labour substitution ratio capital labor l k t t hs= ratio household over labor force hs l t t hec= ratio urban household consumption per household hec hs t t hes= ratio household subsidy over household consumption hes hec t t � �hes hest � � ��tk1 ); if un-decompensated ; ( 1( hes ( pop ip ei re fr ie)=∆ = ∑ ∆ + ∆ + ∆ + ∆ + ∆ + ∆kt f decompensated. 3. methodology/materials to capture the different effects of changes in household subsidy energy, the authors used addictive lmdi decomposition is used to get ten variables effects: population effect, income per capita effect gdp pop t t , ratio national energy intensity effect e gdp t t , renewal energy energy substitution, ratio national renewal energy effect re e t t , fossil fuels renewal energy substitution, ratio fossil renewal energy effect fr re t t , investment efficiency ratio gross capital stock over renewal energy k re t t , capital labour substitution ratio capital labor l k t t , ratio household over labor force hs l t t , ratio urban household consumption per household hec hs t t , and ratio household subsidy over household consumption hes hec t t . the data of household subsidy energy was taken to decompose the ten variables, consisting of 864 observation data. the data was coming from british petroleum world statistics, world development indicators (world bank), international energy association (iea), minister sumber daya mineral (msdm) and biro pusat statistik (bps) for the year 1990-2017. using the decomposition approach, the authors used a regression method in data analyst techniques using the logarithmic mean divisia index (lmdi) and kaya index. several researchers have used lmdi to extend kaya identity (ma and stern, 2008; wang et al., 2014; zhang, 2019). ma and cai (2018) and ma et al. (2018) conducted studies in the building industry that combined kaya identity and lmdi for decomposition to total energy-related co2 (saunders, 2015). ardl analysis was used to recognize the effects that drive the evolution of energy subsidies in indonesia. the regression analysis was a statistical technique to model and investigate nine independent variables on one response variable (dependent variable). the regression equation used was as follows: y = α + β1pop+ β2ip+ β3ei+ β4re+ β5fr + β6ie+ β7kl+ β8hs+ β9se+ e description: y = household energy subsidy effect (hes) α = regression constant β1= regression coefficient for population effect (pop) β2= regression coefficient for income per capita effect (ip) β3= regression coefficient for ratio national energy intensity effect (ei) β4= regression coefficient for ration national renewal energy effect (re) sudarmaji, et al.: decomposition factors household energy subsidy consumption in indonesia: kaya identity and logarithmic mean divisia index approach 358 international journal of energy economics and policy | vol 12 • issue 1 • 2022358 β5= regression coefficient for fossil renewal energy effect (fr) β6= regression coefficient for ration capital stock over renewal energy effect (ie) β7= regression coefficient for capital labour substitution effect (kl) β= regression coefficient for household over labor force effect (hs) β9= regression coefficient for household subsidy over household consumption effect (se) e = error. the dependent variable in this study was household energy subsidy effect, and there were nine independent variables. after applying the lmdi kaya analysis, the next step was to use ardl and ecm. by accommodating in the model of information related to time series. 4. results and findings we analyze the outputs after applying the lmdi kaya analysis. we applied ardl time series analysis to seek more precise and reliable results in the data analyst technique. the method selection was based on the unit root test results that define the variable’s stationarity for time series analysis. the empirical framework of the analysis has the following components: 1. unit root tests and cointegration tests 2. optimal lags selection 3. vec model estimations 4. causality analysis tests 5. diagnostic and stability tests. 4.1. decomposition analysis as explained in the previous paragraph, this study used the kaya identity to decompose the household energy subsidy into several components to determine the subsidy factor’s significance. the components were population, income per capita, ratio national renewal energy, gross capital stock, urban household consumption, and ratio household subsidy, ratio national energy intensity effect, ratio fossil renewal energy effect, ratio capital labor substitution, and ratio household over labor. the sum of all ten of these factors was equal to that of household subsidy. based on lmdi, we found out that population, income per capita, ratio national renewal energy, gross capital stock, urban household consumption, and ratio household subsidy were the positive factors that aggravated the change in household energy subsidy. the negative sign of ratio national energy intensity effect, ratio fossil renewal energy effect, ratio capital labor substitution, and ratio household over labor force signified the decreasing significance of less household energy subsidy, figure 1. another factor that aggravated the increase in household subsidies was the population effect, characterized by urbanization. based on figure 2, for almost 27 years from 1990-2017, indonesia’s household subsidy effect was generated solely based on the population and gdp. urbanization was the correct indication of the outcome of decomposition. most factors have contributed to household subsidy due to the energy increases being consumed by households. on the contrary, since the household subsidy was targeting the low-income family. the ratio percentage of household subsidy over the total household was decreasing. over the last decade, the outcome shows that indonesia’s gdp impact was taking off due to indonesia’s government enhancing the private sector’s growth. the results showed that the gdp effect was the most influential factor in the annual household subsidy increase. this study found indonesia’s most crucial gdp effect contributing to household subsidy in the last four decades. the effect of gdp, characterized by the share of gdp production, was in line with existing literature. the exciting facts were that both ratio national renewal energy and the ratio fossil renewal energy effect have a different contribution to the household subsidy. when the government improved the renewable energy policy, it hampered all its efforts without imposing the energy conservatism policy. hence the cornerstone of regulating rising subsidies was energy efficiency. as better energy-saving technology was adopted over time, more energy-efficient equipment can be used by economies that develop later. in this case, indonesia could request economists to organize "nudge units" to put the nudge plan into action. the figure 1: energy subsidy decomposition sudarmaji, et al.: decomposition factors household energy subsidy consumption in indonesia: kaya identity and logarithmic mean divisia index approach international journal of energy economics and policy | vol 12 • issue 1 • 2022 359 government can lower the cost of family energy usage by making limited options (framing) via the nudge program. the aim is energy efficiency, conservation, and carbon emission reduction (sudarmaji and thalib, 2020). the labor effect factors were also very noteworthy. energy usage increased along with gdp, and increasing energy consumption made the subsidy for households also increase. fortunately, the rate of increase slowed over time as the economy continued to develop. it was driven by structural and technological changes in indonesia’s economy. the structure of indonesia’s economy was industry-based. industrial societies were used more energy and realized rapid changes as indonesia’s economy transformed. in fact, in the last decade, services-oriented economies such as finance, healthcare, and software tend to grow and use less energy-intensive. 4.2. descriptive analysis there were 864 total data observations on the original data taken from 1990 to 2017. in table 1, the descriptive statistical test results on each value of ten variables showed a mean average with the data distribution having a maximum value, minimum value, and standard deviations for each decomposition variable. 4.3. estimate the ardl model using the “restricted constant and no trend” case, as shown in table 2, there was a cointegration relationship between dependent and independent variables. hence it can be said that the independent and dependent variables exhibited a long-run relationship. it meant that short-run shock would converge with time in the long run. hence based on the bounded cointegration test, the authors pursued ardl and ecm model. based on the test above, we connected our short-and long-run effects to the notable predictive framework on the effects of energy intensity. our econometric method emphasizes us to estimate short-run effects relevant to the region. the framework can also be defined as an error-correction model (ecm), where short-and long-run effects from an ardl model were mutually measured. when the data was strictly i(0) or purely i(1) or a mixture of both but not i(2), the ardl model was sufficient. the entry of i(2) variables in the analysis should be avoided since the ardl model only provides critical boundary values for the i(0) and i(1) series. therefore, this research conducts adf and p.p. tests to determine the order in which targeted variables were integrated. these two tests in econometric literature have been widely used. the results of both root unit tests have been included in table 3 below. all the variables were checked by both the unit root checks i(1). in table 4, the outputs of lmdi analysis in percentage-based of increasing and decreasing for each decomposition variable. by reformulating eq. (5) above as an ardl(p, q., q) model. ardl model as forecasting model for hes effect, can be written as follows: � � hes x hes hesit j j t 1 i t it� �� � � � �� � � � � � � � � � � � � �� .j k j p j k i q i 1 1 1 0 jj itu, .t j t 1 t 1x ect� � �� ��3 (6) and � � �1 0 1ect y xt 1 t 1 t t� � �� � � (7) note: k−1= optimal lags (−1) β1, α1, δj= short-run, dynamic coefficient and& long-run equilibrium λi= speed of adjustment ectt−1= the error correction term uit= error. 4.4. lags selection based on table 5, the akaike information criterion (aic) and schwarz bayesian criterion (sbc) obtained two optimal lag lengths. the authors selected the max second lags for deploying the panel vec model. 4.5. validity and stability test several diagnostic tests were used, such as the residual serial correlation problem in the estimated model. the authors used breusch-godfrey serial correlation l.m. the test obtained a serial correlation test that the value of probability f 0.4924 >0.05. l.m. resulted can be concluded that serial correlation between figure 2: energy subsidy decomposition sudarmaji, et al.: decomposition factors household energy subsidy consumption in indonesia: kaya identity and logarithmic mean divisia index approach 360 international journal of energy economics and policy | vol 12 • issue 1 • 2022360 table 1: descriptive analysis he’s pop gdp epc rec ffc gfc labour household house-cons effect effect effect effect effect effect effect effect effect effect mean 30209120 4952221 14509699 −9170448 8698135 −9016813 12815734 −15876970 −1930085 647547,5 median 21041329 2856252 7591553 −95749,43 456413,1 −471094,5 1302592 −9949280 8415,172 −144685,6 max 1,50e+08 13285659 37905078 18724760 1,71e+08 2,05e+08 1,09e+08 23109964 21790706 45749729 min −1,59e+08 186603,8 −8182137 −1,14e+08 −1,98e+08 −1,77e+08 −22775590 −52692724 −58472865 −35395223 std. dev. 61695414 4711390 15230182 26324912 62401589 64650186 28579408 20072421 13132476 15053197 skewness −0,973 0,514 0,365 −2,635 −0,389 0,389 1,831 −0,133 −2,942 1,237 kurtosis 5,193 1,711 1,559 10,640 7,336 7,347 6,459 2,238 14,270 6,837 jar-bera 9,667 3,058 2,937 96,895 21,829 21,936 28,548 0,733 181,84 23,448 prob 0,008 0,217 0,230 0,000 0,000 0,000 0,000 0,693 0,000 0,000 sum 8,16e+08 1,34e+08 3,92e+08 −2,48e+08 2,35e+08 −2,43e+08 3,46e+08 −4,29e+08 −52112307 17483783 sumsq.dev 9,90e+16 5,77e+14 6,03e+15 1,80e+16 1,01e+17 1,09e+17 2,12e+16 1,05e+16 4,48e+15 5,89e+15 table 2: bounded cointegrated test f-bounds test null hypothesis: no levels relationship test statistic value sign in. i (0) i (1) asymptotic: n=1000 f-statistic 57,320 10% 1,800 2,800 k 9 5% 2,040 2,080 2,50% 2,240 3,350 1% 2,500 3,680 table 3: individual unit root series level 1st differences adf test adf test phillips-perron test adf test adf test phillips-perron test aic sic bartlett kernel aic sic bartlett kernel hes-effect 0,619 0,001 * 0,001 * 0,000 * 0,000 * 0,000 * pop-effect 0,207 0,207 0,936 0,563 0,563 0,123 gdp-effect 0,925 0,925 0,948 0,000 * 0,000 * 0,000 * epc-effect 0,994 0,064 0,064 0,657 0,001 * 0,000 * rec-effect 0,045 ** 0,000 * 0,000 * 0,000 * 0,000 * 0,000 * ffc-effect 0,045 ** 0,000 * 0,000 * 0,000 * 0,000 * 0,000 * gfc-effect 0,987 0,026 * 0,026 ** 0,001 * 0,001 * 0,000 * labor-effect 0,766 0,766 0,145 0,000 * 0,000 * 0,000 * household-effect 0,001 * 0,001 * 0,000 * 0,001 * 0,000 * 0,000 * house-cons-effect 0,002 * 0,001 * 0,003 * 0,006 * 0,006 * 0,000 * group statistik adf fisher chi-square 0,001 * 0,000 * 0,000 * 0,000 adf choi z-stat 0,162 0,000 * 0,000 * 0,000 p.p. fisher chi-square 0,000 * * 0,000 * p.p. choi z-stat 0,000 * * 0,000 * independent variables did not occur, which means there was no correlation between independent variables. meanwhile, the normality test was conducted by testing independent and dependent variable data on the resulting regression equation, whether normally distributed or abnormally distributed. regression equations were good if they had independent variable data and dependent variable data near-normal or normal. the test showed a probability of 0.2258, meaning normally distributed data. the cusum test was based on the total sum of 5 percent regression equation errors with critical lines. as the sum of recursive errors gets within the two critical lines, the equation parameters are stable. the overall results were deemed stable based on the cusum test. the squares cusum test was similarly measured and interpreted as the cusum test, except that we use recursive duplicated errors instead of recursive errors. according to this test, the equation’s values were not stable; see figure 3 below. hence, the authors took another test, i.e., test the stability—this test ascertained whether the estimated model was linear or correctly specified. based on the reset test, see table 6—the result showed that the model was correctly specified. authors also need to satisfy the homoscedasticity assumption for the valid regression results. white’s heteroscedasticity test was the last validity test. the null hypothesis of the test stated that there was no current heteroscedasticity. based on table 7, the result showed breusch-pagan-godfreyin occurred symptoms of heteroscedasticity due to prob values. f and prob. chi-square sig < 0.05. however, different results occurred when the authors used the harvey and arch-lm methods. hence, based on the tests, it was assumed that heteroskedasticity does not affect the stated ecm. the authors preferred to use arch-lm output because it was more reliable than another test. sudarmaji, et al.: decomposition factors household energy subsidy consumption in indonesia: kaya identity and logarithmic mean divisia index approach international journal of energy economics and policy | vol 12 • issue 1 • 2022 361 table 4: energy consumption subsidy decomposition per unit variable year household subsidy pop effects gdp effect epc effect rec effect ffc effects gfc effects labour effect household effect house-cons effect hes effect 1990-1991 −4,05% 1,70% 4,85% 1,41% 2,29% −2,37% −1,69% −2,20% −1,26% −0,89% −5,89% 1991-1992 12,07% 1,79% 4,88% 3,16% 15,34% −15,92% −4,15% −0,94% −1,21% −0,73% 9,85% 1992-1993 13,22% 1,75% 4,95% −0,81% −13,58% 14,10% −0,51% −2,96% 0,05% −1,60% 11,83% 1993-1994 7,49% 1,65% 5,89% −0,59% −11,14% 11,52% 6,05% −10,52% 0,06% −1,08% 5,67% 1994-1995 25,59% 1,73% 7,14% −1,77% 3,18% −3,28% 7,71% −11,62% 0,06% −0,47% 22,91% 1995-1996 37,44% 1,76% 7,10% −1,27% −0,41% 0,42% 8,35% −12,86% 0,81% −1,96% 35,48% 1996-1997 77,02% 1,96% 4,23% 4,99% −46,50% 47,78% −1,37% −7,50% −0,52% 0,91% 73,04% 1997-1998 43,51% 1,71% −18,66% 14,72% 57,95% −59,66% −44,31% 52,70% −1,73% −0,17% 40,96% 1998-1999 53,59% 1,74% −0,76% 9,94% −4,94% 5,12% −36,19% 29,42% 0,18% 0,62% 48,44% 1999-2000 21,00% 1,52% 3,77% 3,97% −4,97% 5,15% 7,61% −15,55% 0,22% 2,05% 17,23% 2000-2001 17,36% 1,48% 2,40% 2,28% 12,53% −12,99% 1,11% −6,38% 4,27% −3,31% 15,96% 2001-2002 14,79% 1,46% 3,26% −0,01% −14,29% 14,80% −0,31% −5,11% 1,61% −0,94% 14,31% 2002-2003 16,56% 1,46% 3,59% 2,97% −13,31% 13,73% −7,80% 0,33% 2,08% −1,36% 14,87% 2003-2004 33,39% 1,56% 4,13% −6,25% 7,43% −7,66% 16,67% −13,62% 1,03% −1,49% 31,59% 2004-2005 38,76% 1,58% 4,97% −3,64% 4,12% −4,26% 9,45% −12,53% 3,65% −3,76% 39,17% 2005-2006 27,93% 1,51% 4,56% −4,44% −8,63% 8,90% 1,00% −0,69% −1,03% −1,54% 28,30% 2006-2007 21,84% 1,46% 5,34% 1,03% 5,14% −5,30% 2,19% −4,25% −13,44% 9,59% 20,08% 2007-2008 17,92% 1,44% 4,91% −7,71% 10,18% −10,52% 13,91% −9,94% −0,89% −2,33% 18,87% 2008-2009 −16,71% 1,21% 2,92% −0,88% 0,58% −0,60% −0,27% −1,59% 3,49% −5,66% −15,90% 2009-2010 16,46% 1,45% 5,08% 3,60% 17,99% −18,68% −0,63% −6,38% −0,78% −2,96% 17,78% 2010-2011 28,37% 1,53% 5,27% 2,96% −32,67% 33,86% −1,31% −7,37% 0,41% 0,95% 24,74% 2011-2012 16,03% 1,46% 4,86% −0,70% −3,28% 3,38% 3,70% −6,71% −1,91% 5,88% 9,34% 2012-2013 6,53% 1,38% 4,20% −2,80% 14,24% −14,70% 2,72% −4,25% 0,57% 1,20% 3,97% 2013-2014 10,96% 1,38% 3,77% −11,85% 2,33% −2,41% 11,37% −3,09% −0,14% 0,87% 8,73% 2014-2015 −14,40% 1,17% 3,24% −5,25% −3,49% 3,61% 5,24% −3,33% −0,04% −0,62% −14,94% 2015-2016 3,38% 1,24% 3,75% −2,29% 18,67% −19,37% 2,45% −3,35% 0,14% −0,45% 2,60% 2016-2017 3,63% 1,20% 3,84% −1,10% 2,87% −2,99% 2,27% −3,18% −1,70% 0,20% 2,23% figure 3: cusum of square and cusum table 5: lags selection analysis lag lo lolrfpo aic sc hq 0 −4458,38 na 8,90e+136 343,7216 344,2055 343,8609 1 −4082,57 433.6273* 9.6e+127* 322.5054* 327.8281* 324.0381* *indicates lag order selected by the criterion. l.r.: sequential modified l.r. test statistic (each test at 5% level). fpe: final prediction error. aic: akaike information criterion. sc: schwarz information criterion. h.q.: hannan-quinn information criterion table 6: reset test description value df probability t-statistic 0,277 16 0,785 f-statistic 0,077 (1, 16) 0,785 likelihood ratio 0,130 1 0,719 4.6. causality analysis test based on table 8, statistically, there were only two bi-direct granger causality between gfc and population and household and labour on the pair-wise granger causality tests. the several variables had a uni-direct granger causality. in tables 9 and 10, respectively, long-term and short-term results were published. the long-term results show that nine variables harmed energy subsidy (δhes). there was almost a negative impact on the 1st lag for all nine variables see table 9. however, it was partly pointed out that all independent variables, such as gdpeffect, epc-effect, gfc-effect, labour-effect, household-effect, and house-cons-effect, had no insignificant impact on the δhes. the empirical result above showed that all variable effects have a significant impact at the 0.01 level and 0.05 for gfc-effect in the long-run causality. except for population-effect had a positive effect with coefficient 1.595 has a significant impact at 0.05. it did sudarmaji, et al.: decomposition factors household energy subsidy consumption in indonesia: kaya identity and logarithmic mean divisia index approach 362 international journal of energy economics and policy | vol 12 • issue 1 • 2022362 table 7: hetereocadasity test breusch pagan-godfrey harvey arch f-statistic 4,600 0,288 0,229 obs*r-squared 19,140 3,567 0,245 scaled explained ss 12,034 9,459 prob. f (9,17) 0,003 0,969 * 0,637 * chi-square (9) 0,024 0,938 * 0,620 * chi-square (9) 0,211 0,396 table 8: granger causality pop gdp epc rec ffc gfc labour household house-cons he’s effect effect effect effect effect effect effect effect effect effect pop-effect 1,417 3,312 3,312 3,335 5,429 4,923 0,688 1,683 0,178 0,266 0,057 0,057 0,056 0,013** 0,018** 0,514 0,211 0,838 gdp-effect 3,158 2,980 6,247 6,255 4,892 9,546 0,350 0,382 0,962 0,064 0,074 0,008* 0,008* 0,019** 0,001* 0,709 0,687 0,399 epc-effect 17,669 2,314 13,385 13,425 0,137 0,480 0,141 0,197 21,760 0,000* 0,125 0,000* 0,000* 0,873 0,625 0,870 0,823 0,000* rec-effect 0,291 0,280 1,420 0,990 0,264 0,181 0,376 1,607 1,122 0,751 0,759 0,265 0,389 0,771 0,836 0,691 0,225 0,345 ffc-effect 0,288 0,280 1,408 1,001 0,261 0,181 0,377 1,608 1,114 0,753 0,759 0,268 0,385 0,773 0,836 0,691 0,225 0,348 gfc-effect 11,303 4,280 0,271 12,913 12,967 0,468 1,356 0,729 12,935 0,001* 0,028** 0,765 0,000* 0,000* 0,633 0,280 0,495 0,000* labor-effect 0,278 3,161 1,684 2,093 2,093 1,732 3,877 1,796 0,097 0,760 0,064 0,211 0,150 0,150 0,202 0,038** 0,192 0,908 household-effect 2,993 3,447 1,018 1,276 1,273 1,875 4,385 2,698 2,705 0,073 0,052 0,379 0,301 0,302 0,179 0,026** 0,092 0,091 house-cons 8,467 6,789 10,188 2,580 2,570 6,579 4,013 0,179 4,034 0,002 0,006* 0,001* 0,101 0,102 0,006* 0,034** 0,838 0,034&& hes 4,565 0,103 0,832 18,691 18,686 1,373 0,135 0,965 1,158 0,023** 0,903 0,450 0,000* 0,000* 0,276 0,875 0,398 0,334 table 9: ardl – short run causality variable coefficient std. error t-statistic prob.* he’s(−1) −1,056 0,049 −21,723 0,000* pop-effect 152,192 4,197 36,261 0,000* pop-effect(−1) −148,912 4,805 −30,990 0,000* gdp-effect 0,051 0,582 0,088 0,933 gdp-effect(−1) −4,375 0,632 −6,918 0,001* epc-effect 0,183 0,598 0,306 0,770 epc-effect(−1) −2,981 0,786 −3,792 0,009* rec-effect −41,910 11,270 −3,719 0,010* rec-effect(−1) −67,742 15,958 −4,245 0,005* ffc-effect −40,519 10,903 −3,716 0,010* ffc-effect(−1) −65,627 15,382 −4,266 0,005* gfc-effect 0,443 0,501 0,885 0,410 gfc-effect(−1) −2,440 0,725 −3,367 0,015** labour-effect 0,246 0,464 0,530 0,615 labour-effect(−1) −2,660 0,682 −3,899 0,008* household-effect −−0,033 0,185 −0,176 0,866 household-effect(−1) −1,497 0,153 −9,797 0,000* house-cons-effect −0,054 0,133 −0,408 0,698 house-cons-effect(−1) −0,719 0,229 −3,148 0,020** c 157275,5 749739,6 0,209774 0,8408 r-squared 1 mean dep. var 31395840 adjusted r-squared 0,999216 sd dep. var 62602172 se of regression 1752473 aic 31,66308 sum squared resid 1,84e+13 schwarz-criterion 32,63085 log-likelihood −391,62 hq criterion 31,94176 f-statistic 1678,73 durbin-watson 2,719588 sudarmaji, et al.: decomposition factors household energy subsidy consumption in indonesia: kaya identity and logarithmic mean divisia index approach international journal of energy economics and policy | vol 12 • issue 1 • 2022 363 mean that 1% change in population-effect increased 1.595% in energy subsidy. on the other hand, for all nine variables that had adverse effects, 1% change in every nine variables decreased as much as the coefficient stated. in table 11, the result showed that the models’ approximate results showed that the ect coefficient was almost negative, −2.056, with long-term statistical causality. it has been shown that the long-term balance of δhes was valid significant with 0.01%. it means that the previous period’s imbalance shocks reconnected into a longrun equilibrium. in other words, there was a long-term causality between δhes with the other nine variables. 5. conclusion in the study, we have investigated the dynamic causal linkages of household energy subsidy with nine other variables in indonesia from 1990 to 2017. the study of decomposition decoupling measured how much energy was used relative to an activity measure. the elements of decomposition depend on the structure of the economy and the environment of the country. this type of indicator aimed to quantify how effectively we use energy and how decomposition factors differ. comparing decomposition factors and energy used in the household was valuable when decomposing energy subsidy consumption. based on lmdi results, we found out that the gdp and population effect were the most significant factors aggravating energy consumption change for the household table 10: ardl long run causality variable coefficient std. error t-statistic prob. pop-effect 1,595 0,635 2,514 0,046 ** gdp-effect −2,103 0,334 −6,300 0,001 * epc-effect −1,361 0,277 −4,915 0,003 * rec-effect −53,339 12,730 −4,190 0,006 * ffc-effect −51,634 12,295 −4,200 0,006 * gfc-effect −0,971 0,316 −3,072 0,022 ** labor-effect −1,174 0,313 −3,757 0,009 * household-effect −0,744 0,106 −6,997 0,000 * household-consumption −0,376 0,089 −4,250 0,005 * c 76505,230 364714,100 0,210 0,841 * significant level at the 0.01 level, ** at 0.05 level table 11: error correction model variable coefficient std. error t-statistic prob. d (pop-effect) 152,192 0,919 165,546 0,000 * d (gdp-effect) 0,051 0,154 0,334 0,750 d (epc-effect) 0,183 0,078 2,334 0,058 d (rec-effect) −41,910 1,510 −27,763 0,000 * d (ffc-effect) −40,519 1,457 −27,802 0,000 * d (gfc-effect) 0,443 0,078 5,701 0,001 * d (labour-effect) 0,246 0,082 3,018 0,023 ** d (household-effect) −0,033 0,040 −0,808 0,450 d (house-cons-effect) −0,054 0,028 −1,960 0,098 cointeq(−1)* −2,056 0,007 −296,959 0,000 * r-squared 1,000 mean dep. var 834112,4 adjusted r-squared 1,000 s.d. dep. var 86174523 s.e. of regression 1073166 aic 30,89385 sum squared resid 1,84e+13 schwarz criterion 31,378 log-likelihood −391,620 quinn criterion 31,033 durbin-watson 2,720 subsidy. energy efficiency has been the cornerstone in controlling the rising energy used in the household subsidy. on the other hand, reducing the labor force effect for household and industrial sectors contributed to the lowest change to the energy used for both sectors. the negative sign of subsidy energy signifies the decreasing significance of less energy subsidy. the result showed that the models’ approximate results show that the ect coefficient was almost negative, -2.056, with long-term statistical causality. it had been shown that the long-term balance of 𝚫hes was valid significant with 5.73%. it meant that the previous period’s imbalance shocks reconnected into a long-run equilibrium. in other words, there was a long-term causality between 𝚫hes with the other nine variables. under time series ecm, there were no anomalies in the cusum test. we established that the models were stable. the equation parameters were stable for households as the entire total of recursive errors gets within the two critical lines. the cusum test was based on 5 percent regression equation errors with critical lines. the equation parameters were stable as the entire sum of recursive errors gets within the two critical lines. based on the cusum measure, the overall outcomes were considered stable. the squares cusum test was calculated and interpreted similarly to the cusum test, except that we use recursive duplicate errors instead of recursive errors. moreover, the reset test was an additional test was deployed to confine the result of the squares sudarmaji, et al.: decomposition factors household energy subsidy consumption in indonesia: kaya identity and logarithmic mean divisia index approach 364 international journal of energy economics and policy | vol 12 • issue 1 • 2022364 of cusum since the test was based on the total sum of 5 percent regression equation errors outside the critical lines. according to this reset test, the general aspects were considered stable. the last validity test was white’s heteroscedasticity test. the test’s null hypothesis states that no existing heteroscedasticity exists. based on the outcome, the null hypothesis of heteroscedasticity should not be discarded since the p-value carried out approaches the significance stage. it was, therefore, presumed that heteroscedasticity does not impact the specified ecm. the waste of spending caused by wrong subsidy targets has long been a problem for the indonesian economy. it has become a trap for almost decades fuel subsidies have always been difficult to solve. the current government’s political courage was indispensable to advancing strategic actions in managing the bloated fuel subsidy budget. the reduction of subsidies periodically, pertamina’s lpg prices, and periodic electricity tariff adjustments for specific groups by pt pln were subsidy reforms undertaken by the government. the decline was expected to support the ministry and other governments’ spending needs in other sectors. these subsidy reforms were acceptable based on environmental considerations because low-cost fuels tend to cause people to buy more fuel (rebound effect), boosting co2 emission. moreover, increasing the construction of coal-fired power plants was contrary to reducing greenhouse gas emissions. nevertheless, then the subsidy savings expected to drive renewable energy generation were not proven. many renewables exist, such as geothermal, solar energy; micro-hydro was generally converted into electrical energy but not easily used as fuel. only biofuels (bbn) or biofuels, namely biodiesel, and bioethanol were quickly converted into fuel. references ang, b.w. (2015), lmdi decomposition approach: a guide for implementation. energy policy, 86, 233-238. cansino, j.m., roman-collado, r., merchan, j. (2019), do spanish energy efficiency actions trigger jevon’s paradox? energy, 181, 760-770. de freitas, l.c., kaneko, s. (2011), decomposing the decoupling of co2 emissions and economic growth in brazil. ecological economics, 70, 1459-1469. kojima, m., bacon, r. (2009), changes in co2 emissions from energy use. washington, dc, united states world bank. krstic, b., krstic, m. (2015), models of irrational behaviour of household and firm. ekonomika, 61(4), 1-10. ma, c., stern, d.i. (2008), biomass and china’s carbon emissions: a missing piece of carbon decomposition. energy policy, 36, 2517-2526. ma, m., cai, w. (2018), what drives carbon mitigation in the chinese commercial building sector? evidence from decomposing an extended kaya identity. science of the total environment, 634, 884899. ma, m., cai, w., cai, w. (2018), carbon reduction in china’s commercial building sector: a bottom-up measurement model based on kaya-lmdi methods. energy, 165, 350-368. ministry of energy and mineral resources republic of indonesia. (2018), energy and economic statistics of indonesia. in: handbook of energy and economic statistics of indonesia. indonesia: ministry of energy and mineral resources republic of indonesia. moutinho, v., madaleno, m., silva, p.m. (2015), which factors drive co2 emissions in eu-15? decomposition and innovative accounting. energy efficiency, 9(5), 1087-1113. nasip, i., sudarmaji, e. (2018), managing tax dispute due to ifrs-16 on the retrofits implementation in indonesia. international journal of engineering and technology, 7(3.21), 200-208. pui, k.l., othman, j. (2019), the influence of economic, technical, and social aspects on energy-associated co2 emissions in malaysia: an extended kaya identity approach. energy, 181, 468-493. sadikova, m., faisal, f., and resatoglu, n.g. (2017), influence of energy use, foreign direct investment, and population growth on unemployment for the russian federation. procedia computer science, 120, 706-711. saunders, h.d. (2015), recent evidence for large rebound: elucidating the drivers and their implications for climate change models. the energy journal, 36(1), 23-48. sudarmaji, e., thalib, s. (2020), to nudge or not to nudge households: energy efficiency case in indonesia. international journal of production economics, 24(6), 3225-3241. toba, a.l., seck, m. (2016), modeling social, economic, technical and environmental components in an energy systems. procedia computer science, 95, 400-407. wang, w., liu, x., zhang, m., song, x. (2014), using a new generalized lmdi (logarithmic mean divisia index) method to analyze china’s energy consumption. energy, 67, 617-622. world bank group. (2016), the role of cities in sustainable economic development. washington, dc, united states: world bank group. wu, j. (2014), urban ecology and sustainability: the state-of-the-science and future directions. landscape and urban planning, 125, 209-221. zhang, m., su, b. (2016), assessing china’s rural household energy sustainable development using improved grouped principal component method. energy, 113, 509-514. zhang, y. (2019), energy rebound effect analysis based on technological progress. in: iop conference, series earth and environmental science no. 300. zhao, x., zhang, x., li, n., shao, s., geng, y. (2017), decoupling economic growth from carbon dioxide emissions in china: a sectoral factor decomposition analysis. journal of cleaner production, 142, 3500-3516. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 5 • 2022132 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(5), 132-137. research trends of waste heat recovery technologies: a bibliometric analysis from 2010 to 2020 alfonso rodríguez peña1*, daniel maestre cambronel2, guillermo valencia ochoa2, lisandro vargas henríquez3 1conformat research unit, department of mechanical engineering, universidad del atlántico, carrera 30 # 8 – 49, puerto colombia, barranquilla, colombia, 2kaí research unit, department of mechanical engineering, universidad del atlántico, carrera 30 # 8 – 49, puerto colombia, barranquilla, colombia, 3imtef research unit, department of mechanical engineering, universidad del atlántico, carrera 30 # 8 – 49, puerto colombia, barranquilla, colombia. *email: alfonsorodriguez1@mail.uniatlantico.edu.co received: 17 may 2022 accepted: 21 august 2022 doi: https://doi.org/10.32479/ijeep.13293 abstract waste heat recovery (whr) technologies have become vital to promote efficient operation in energy systems. the present investigation presents a bibliometric analysis of the research trends in the whr field in the last decade (2010-2020). the study implements advanced methodologies to gather relevant information for interested readers on this topic. results indicated that whr technologies have registered more than 14,000 articles in the selected timeline with an increasing tendency. moreover, the number of citations escalated to more than 25% in 2020, using 2010 as the baseline. three primary research clusters stated that power cycles are the most cited topic in the whr field. the journal “energy” featured the highest citation margin, whereas the most relevant author from the database was bejan et al. lastly, china is leading the progress in the number of articles and subsequently the citation score, which is primary promoted by the “chinese academy of science.” the study identified that the reduction of citations of whr topics in the last 5 years might be primarily attributed to a transition in a more complex concept of multigeneration. in conclusion, the area of whr technologies has maintained an increased interest in academia in the last 10 years while contributing to the exploitation of power cycle proposals, turbomachinery, heat exchangers, among others. also, whr plays a central role in the development of the next generation of multigeneration units. keywords: bibliometrics, waste heat recovery, energy, multigeneration jel classification: q42 1. introduction global energy is increasingly engaging advanced technologies to promote sustainable development while reducing the alarming rate of greenhouse emissions (valencia et al., 2020; herrera et al., 2018; duarte et al., 2014; ramirez et al., 2019). the unprecedented growth of the world population and convectional energy practices triggers a tremendous concern about environmental pollution and future energy sources (jamel et al., 2013; muk and he., 2007; demirbas, a., 2008; valencia et al., 2020; gutierrez et al., 2020). the energy market has been primarily governed by fossil fuels, which remains as the primary mover of the global economy (bae and kim, 2017). specifically, internal combustion engines governed electricity generation in non-interconnected areas, which possess significant challenges towards the implementation of alternative power generation systems. therefore, there is an increasing necessity to integrate alternative technologies from small to large power plants that improve the overall conversion efficiency. power cycles have emerged as a concrete facilitator of the utilization of waste heat at large scales. in this sense, the operational functionality is described as bottoming cycle that uses the energetic contribution of flue gases as the thermal source this journal is licensed under a creative commons attribution 4.0 international license peña, et al.: research trends of waste heat recovery technologies: a bibliometric analysis from 2010 to 2020 international journal of energy economics and policy | vol 12 • issue 5 • 2022 133 to promote energy conversion. several power cycles such as rankine, kalina, organic rankine (orc), and brayton have been proposed in the literature to conceptualize a waste heat recovery system from a primary energy source (valencia et al., 2020). moreover, thermodynamic modeling emerges as an essential tool to unravel the feasibility of energy systems from a technoeconomic perspective since it identifies the operational parameters that increase energy efficiency, maximize net power output, and reducing exergy destruction (orozco et al., 2019; duarte et al., 2017; mouaky and rachek, 2020). one of the important aspects of the operation of power cycles is the appropriate selection of the working fluid. for example, the working fluid variety in orc applications is extensive but they commonly represent an environmental hazard and the adverse feasibility in high energy sources is a concrete limitation (alibaba et al., 2020). in contrast, carbon dioxide (co2) has demonstrated enormous advantages while implemented in brayton cycles such as low toxicity index and inflammability, low capital cost, and most importantly the adaptability to operate with supercritical conditions (32°c at 3.4 kpa) compared to other fluid such like water (374°c at 22mpa) (pacheco et al., 2018). the last pattern enables to design of components with less complexity and size which reflects on improving compatibility (orozco et al., 2019; chu et al., 2019). precisely, supercritical co2 brayton cycles (scbc) has been implemented in several applications demonstrating its versatility with a wide range of energy sources. vasquez et al, (2015) found that the scbc cycle maintains high energetic efficiencies (>50%) for concentrated solar power applications which demonstrates the efficacy of this energy conversion system. the authors used python as the computational modeling environment and the optimization was based on the sequential least squares programming (slsqp). on the other hand, exergy analysis is an important mechanism to compare the quality of energy of every component of the system while characterizing key design aspects to improve the overall conversion efficiency (diaz et al., 2017). marchionni et al. (2019) implemented a complete analysis of different scbc configurations for whr applications based on energy, exergy, and economic perspectives. in this study, matlab® software was implemented as the modeling tool due to the simplicity and robustness within the calculations and optimization tasks. overall, based on the literature review there is concrete progress towards the implementation and optimization of power cycles that contribute to whr systems. however, the amount of published research condensing the research trends of whr systems is significantly reduced. a few examples can be found in the literature. yu et al. (2021) examined the main characteristics of supercritical brayton cycles according to the emerging trends and developments in this topic. the study concluded that the u.s lead the investigation in brayton cycles, followed by china, whereas the main contributions of published articles centered on new configuration proposals and integration in power plants such as solar and nuclear applications. moreover, the authors revealed that the average citation margin in this field is 13.45. however, the main drawback of this investigation is the low spectrum of the analysis as it only analyzed a database of 774 articles. similarly, sultan et al. (2021) performed a recent survey on co2 power technologies while relating scientific research mappings. the main contribution of this study was the identification of the increased attention of the design of heat exchangers and the implementation of optimization methodologies. in general, most of the studies dealing with research trends in whr technology center on a specific topic such as brayton cycles or orc cycles. therefore, there is a pressing need to close the knowledge gap immersed in the current state of whr technologies from a global perspective. the main contribution of the investigation is to describe the main trends immersed in whr technologies in the last decade. the study implements a complete bibliometric characterization to accurately measure research impact indications that serve as a robust tool to create a comprehensive framework in the investigation field. the incorporation of technical aspects about the energy potential of a great variety of energy sources emerges as a novel aspect from former research. therefore, this investigation contributes to close the knowledge gap associated with the role of whr technologies. this paper is structured as follows: section 2 describes the main parameters of the bibliometric analysis and research impact metrics. section 3 displays the core findings of the investigation and critically discusses the results. finally, section 4 provides the conclusive remarks, limitations, and oncoming perspectives in this field. 2. methodology the section describes the main characteristic of the bibliometric analysis performed in whr trends in the timeline of 2010-2020. accordingly, the database was extracted from the sci-expanded online version of thomson reuters web of science, where the filter by title was used to search the following keywords: “bottoming cycle or waste heat recovery or energy recovery or cogeneration or poligeneration or trigeneration or combined heat and power or energy conversion system or waste heat to power or power cycles or power generation.” the software used to process the wos files (web of science) was histcite tm as it provides historical maps of bibliographic collections resulting from searches of subjects, authors, institutional journals, or sources in the isi web of science. the software generates chronological historiographies that highlight the most cited works in the recovered collection; other listings include classifications by authors, journals, institutions, countries, cited documents, and keywords (yonoff et al., 2019). moreover, the database processing and analysis of scientific results, subject categories, journals, authors, countries, and institutes were processed via microsoft excel 2020 and grapher® (figure 1). 3. results and discussion 3.1. research output according to figure 2, the number of articles related to whr technologies presented a sharp and constant rise since 2010. in contrast, the number of citations in this area is reducing significantly in the last 5 years. remarkably, the highest number peña, et al.: research trends of waste heat recovery technologies: a bibliometric analysis from 2010 to 2020 international journal of energy economics and policy | vol 12 • issue 5 • 2022134 of citations occurred in 2013 with nearly 2200, whereas in 2020 this amount did not exceed 800. this trend could be associated with a transitional state of this field to a more complex characterization of multigeneration systems that comprise cogeneration (whr), trigeneration, and multigeneration units. therefore, one might assume that whr technology has been immersed in a wider research cluster that still deals with whr systems, which is in line with the magnification of articles that contain this topic. table 1 summarizes the bibliometric distribution. the characterization of the type of document from the database becomes essential to understand the trends immersed in the publication of this field, as well as the interest of readers and publishers. accordingly, table 2 displays the distribution of the publication in the database according to the document type. notice a new parameter is introduced in the description section (tc/na) that represents the publication density. based on the results, the original article submissions represent nearly 86% of the total submissions in the database, followed by review papers. accordingly, in the last decade, more than 14,000 articles remain available online, representing the largest citation mark from the batch with around 245,000 citations in total. review papers overcome more than 660 documents that are 21 times less than original articles. notably, the citation density of review articles (54.82) is at least 30% higher than original article submissions. the latter demonstrates that the review articles feature high-citation marks per unit, which can be associated with the wide content characteristics that are driven to condense relevant information in the topic, thus fostering increased attention of occasional readers and researchers. moreover, proceeding papers represent the third place in document production and present higher citation density than articles, which demonstrates the relevance of such conferences to create connections within research units and academics. consequently, it is important to examine the performance metrics of the different journals in terms of bibliometric distribution, as shown in table 3. based on the results of table 3, the journal “energy” features both the highest number of articles (1151) and citation margin (4810 tc/year). the second contributor to the number of articles correspond to “energy conversion and management” with more than 900 publications, however, the citation index of the journal “applied energy” is 2.2% higher. the latter demonstrates the figure 2: distribution of bibliometric records figure 1: methodology flowchart table 1: bibliometric distribution metrics year na tc 2010 667 23606 2011 801 33306 2012 880 28468 2013 1061 35955 2014 1131 33300 2015 1414 34668 2016 1616 33079 2017 1665 26147 2018 2013 23706 2019 2265 16762 2020 2305 6635 table 2: bibliometric distribution document type documents percent tc tc/na article 14567 86.4 245448 16,85 proceedings paper 750 4.4 12964 17,29 review paper 669 4.0 36676 54,82 editorial material 185 1.1 387 2,09 article; early access 184 1.1 77 0,42 correction 94 0.6 207 2,20 letter 13 0.1 14 1,08 review; book chapter 9 0.1 223 24,78 book chapter 2 0.0 20 10,00 table 3: top 10 journals in the whr technology from 2010-2020 no. journal na % tc tc/year 1 energy 1151 6.8 31937 4810.58 2 energy conversion and management 964 3.9 22178 4256.50 3 applied energy 662 5.7 23801 3793.20 4 energies 586 1.7 4403 955.07 5 applied thermal engineering 583 3.5 13812 2160.61 6 renewable energy 344 2.0 7749 1319.46 7 renewable & sustainable energy reviews 295 0.7 16363 2287.53 8 journal of cleaner production 284 0.7 4131 1051.99 9 international journal of hydrogen energy 257 1.0 4391 718.00 10 international journal of energy research 184 0.3 1642 273.29 peña, et al.: research trends of waste heat recovery technologies: a bibliometric analysis from 2010 to 2020 international journal of energy economics and policy | vol 12 • issue 5 • 2022 135 impact factor of this journal in this research field that reaches 5.7% of the database analyzed. interesting a journal that specialized in hydrogen technologies is placed in the ninth position, which elucidates the links of both whr and hydrogen fields. in fact, future predictions point that this trend will increase since the next generation of polygonation units (which included whr technologies) is increasingly perusing the incorporation of hydrogen production within the useful commodities. once again, a journal that focuses on review papers (seventh position) features a higher citation index than other journals that incorporates more publications. this behavior supports the importance of review papers for the continuous development and state-of-the-art characterization in a research field (table 4). based on the results, the most relevant document corresponds to thermal design optimization which states the basics of thermoeconomics modeling while involving a vast variety of whr systems. notice that in the top 10 distribution the journal renew sustainable energy reviews contains four documents, which demonstrates the relevance of review papers for interested readers. subsequently, figure 3 displays the main countries that support research involving whr technologies. based on the distribution map presented in figure 4, china is significantly leading the research clusters around whr progress with more than 4,000 documents in the database. the near competitor in terms of presence in the field is the u.s with more than 2,500 which represents 59% of the presence of china. england represents the most significant contributor in this field in europe with 963 publications in the database. on the other hand, figure 4 assists in evaluating the association of keywords within the database analyzed. notice that the colors are related to the association strength within the list of keywords. according to the results, it can be highlighted that the keyword “waste heat recovery” presents intensive correlation (2015.6) to “organic ranking cycle,” “thermodynamic analysis,” “algorithm,” and “plant.” the aforementioned can be associated with the numerous applications in power plants that integrated whr systems using orc and therefore the thermodynamic modeling via advanced algorithms has paved the consolidation of technoeconomic characterization. in contrast, a less correlation strength figure 4: keywords mapping of the whr database figure 3: top ten countries in whr technologies table 4: top 10 author publications in the whr technology from 2010-2020 no. main author/year/journal ct % 1 bejan et al., 1996, thermal design optimization 5400 2.6 2 chen et al., 2010, renewable sustainable energy reviews 1495 1.3 3 quoilin et al., 2013, renewable sustainable energy reviews 1340 1.2 4 saleh et al., 2007, energy 1401 1.2 5 logan et al., 2006, environmental science and technology 5520 1.1 6 bao et al., 2013, renewable sustainable energy reviews 1207 1.1 7 tchanche et al., 2011, renewable sustainable energy reviews 1192 1.1 8 hung et al., 1997, energy 1155 1.0 9 dai et al., 2009, energy conversion and management 874 1.0 10 wang et al., 2011, energy 695 0.9 peña, et al.: research trends of waste heat recovery technologies: a bibliometric analysis from 2010 to 2020 international journal of energy economics and policy | vol 12 • issue 5 • 2022136 can be seen for keywords such as “hydrogen,” “trigeneration,” “biomass,” “gasification” and “electricity generation” which is in agreement with the evolution of whr (cogeneration) field into a more complex concept of multigeneration units that promote the diversification of the useful products of an energy system. 4. conclusions this investigation reports the bibliometric analysis of the whr field between 2010 and 2020. the study implements advanced methodologies to gather a wide database while identifying the main trends and research perspectives on the topic. in general, it can be concluded that the whr topic has been extensively studied in the last decade with more than 14,000 articles with a citation margin of more than 16.2 per year. interested readers should stress on available information on the journals “energy” and “energy conversion and management,” which represents wide acceptance in the audience. also, the study identified that review papers overcome the most cited documents per unit, despite not being the most published type of document (research article). the latter can be associated with the pressing need for new researches to obtain condensed information on a specific topic. on the other hand, china is leading the global citations and publication in this field, followed by the u.s. moreover, the keyword association demonstrated that orc and brayton technologies overcome the vast majority of publications of the database. also, it was identified that keywords like hydrogen, trigeneration, and energy storage features increased attention in the whr field. the latter demonstrates that the whr field is experiencing a transitional state to multigeneration units that combine cogeneration (whr) and other useful commodities. this pattern is in agreement with the reduction of citation of whr topic in the last 5 years. in conclusion, whr technologies have contributed to close the knowledge gap regarding power cycle proposals, turbomachinery, heat exchangers, among others. however, the demanding necessity of efficient energy management has accelerated the consolidation of advanced multigeneration units. references alibaba, m., pourdarbani, r., manesh, m.h.k., ochoa, g.v., forero, j.d. (2020), thermodynamic, exergo-economic and exergo-environmental analysis of hybrid geothermal-solar power plant based on orc cycle using emergy concept. heliyon, 6, e03758. bae, c., kim, j. (2017), alternative fuels for internal combustion engines. proceedings of the combustion institute, 36, 3389-3413. bao, j., zhao, l. (2013), a review of working fluid and expander selections for organic rankine cycle. renewable and sustainable energy reviews, 24, 325-342. bejan, a., tsatsaronis, g., moran, m.j. (1996), thermal design and optimization. hoboken, new jersey: wiley. chen, h., goswami, d.y., stefanakos, e.k. (2010), a review of thermodynamic cycles and working fluids for the conversion of lowgrade heat. renewable and sustainable energy reviews, 14, 3059-3067. chu, w., bennett, k., cheng, j., chen, y., wang, q. (2019) numerical study on a novel hyperbolic inlet header in straight-channel printed circuit heat exchanger. applied thermal engineering, 146, 805-814. dai, y., wang, j., gao, l. (2009), parametric optimization and comparative study of organic rankine cycle (orc) for low grade waste heat recovery. energy conversion and management, 50, 576-582. demirbas, a. (2008), emissions from combustion of biomass. energy sources, part a: recovery, utilization and environmental effects, 30, 170-178. diaz, g.a., duarte, j.o., garcía, j., rincón, a., fontalvo, a., bula, a., padilla, r.v. (2017), maximum power from fluid flow by applying the first and second laws of thermodynamics. the journal of energy resources technology, 139, 4035021. duarte, j., amador, g., garcía, j., fontalvo, a., vásquez, r., sanjuan, m., gonzález, a. (2014), auto-ignition control in turbocharged internal combustion engines operating with gaseous fuels. energy, 71, 137-147. duarte, j., garcía, j., jiménez, j., sanjuan, m.e., bula, a., gonzález, j. (2017), auto-ignition control in spark-ignition engines using internal model control structure. journal of energy resources technology, transactions of the asme, 139, 022201. gutierrez, j.c., valencia, g., duarte, j. (2020), regenerative organic rankine cycle as bottoming cycle of an industrial gas engine: traditional and advanced exergetic analysis. applied sciences, 10, 4411. herrera, m., castro, e., duarte, j., fontalvo, a., vásquez, r. (2018), análisis exergético de un ciclo brayton supercrítico con dióxido de carbono como fluido de trabajo. research paper. hung, t.c., shai, t.y., wang, s.k. (1997), a review of organic rankine cycles (orcs) for the recovery of low-grade waste heat. energy, 22, 661-667. jamel, m.s., abd rahman, a., shamsuddin, a.h. (2013), advances in the integration of solar thermal energy with conventional and nonconventional power plants. renewable and sustainable energy reviews, 20, 71-81. logan, b.e., hamelers, b., rozendal, r., schröder, u., keller, j., freguia, s., aelterman, p., verstraete, w., rabaey, k. (2006), microbial fuel cells: methodology and technology. environmental science and technology, 40, 5181-5192. marchionni, m., chai, l., bianchi, g., tassou, s.a. (2019), numerical modelling and transient analysis of a printed circuit heat exchanger used as recuperator for supercritical co2 heat to power conversion systems. applied thermal engineering, 161, 114190. mouaky, a., rachek, a. (2020), energetic, exergetic and exergeoeconomic assessment of a hybrid solar/biomass poylgeneration system: a case study of a rural community in a semi-arid climate. renewable energy, 158, 280-296. muk, h., he, b. (2007), spark ignition natural gas engines a review. energy conversion and management, 48, 608-618. orozco, t., herrera, m., duarte, j. (2019), cfd study of heat exchangers applied in brayton cycles: a case study in supercritical condition using carbon dioxide as working fluid. the international review on modelling and simulations, 12, 72. orozco, w., acuña, n., duarte, j. (2019), characterization of emissions in low displacement diesel engines using biodiesel and energy recovery system. the international review of mechanical engineering, 13, 420-426. pacheco, e.c., forero, j.d., lascano, a.f. (2018), análisis exergético de un ciclo brayton supercrítico con dióxido de carbono como fluido de trabajo exergetic analysis of a supercritical brayton cycle with carbon dioxide as working fluid. inge cuc, 14, 159-170. quoilin, s., van den broek, m., declaye, s., dewallef, p., lemort, v. (2013), techno-economic survey of organic rankine cycle (orc) systems. renewable and sustainable energy reviews, 22, 168-186. ramirez, r., gutiérrez, a.s, eras, j.j.c, valencia, k., hernández, b., peña, et al.: research trends of waste heat recovery technologies: a bibliometric analysis from 2010 to 2020 international journal of energy economics and policy | vol 12 • issue 5 • 2022 137 forero, j.d. (2019), evaluation of the energy recovery potential of thermoelectric generators in diesel engines. journal of cleaner production, 241, 118412. saleh, b., koglbauer, g., wendland, m., fischer, j. (2007), working fluids for low-temperature organic rankine cycles. energy, 32, 1210-1221. sultan, u., zhang, y., farooq, m., imran, m., khan, a.a., zhuge, w., khan, t.a., yousaf, m.h., ali, q. (2021), qualitative assessment and global mapping of supercritical co2 power cycle technology. sustainable energy technologies and assessments, 43, 100978. tchanche, b.f., lambrinos, g., frangoudakis, a., papadakis, g. (2011), low-grade heat conversion into power using organic rankine cycles a review of various applications. renewable and sustainable energy reviews, 15, 3963-3979. valencia, g., acevedo, c., duarte, j. (2020), combustion and performance study of low-displacement compression ignition engines operating with diesel-biodiesel blends. applied sciences, 10, 907. valencia, g., cárdenas, j., duarte, j. (2020), exergy, economic, and lifecycle assessment of orc system for waste heat recovery in a natural gas internal combustion engine. resources, 9, 2. vasquez, r., chean, y., too, s., benito, r., stein, w. (2015), exergetic analysis of supercritical co2 brayton cycles integrated with solar central receivers. applied energy, 148, 348-365. wang, e.h., zhang, h.g., fan, b.y., ouyang, m.g., zhao, y., mu, q.h. (2011), study of working fluid selection of organic rankine cycle (orc) for engine waste heat recovery. energy, 36, 3406-3418. yonoff, r.e., ochoa, g.v., cardenas-escorcia, y., silva-ortega, j.i., meriño-stand, l. (2019), research trends in proton exchange membrane fuel cells during 2008-2018: a bibliometric analysis. heliyon, 5, e01724. yu, a., su, w., lin, x., zhou, n. (2021), recent trends of supercritical co2 brayton cycle: bibliometric analysis and research review. nuclear engineering and technology, 53, 699-714. international journal of energy economics and policy vol. 2, no. 2, 2012, pp. 50-54 issn: 2146-4553 www.econjournals.com cross section translog production and elasticity of substitution in u.s. manufacturing industry sooriyakumar krishnapillai department of agricultural economics and rural sociology, auburn university, u.s.a. email: kzs0008@auburn.edu henry thompson department of agricultural economics and rural sociology, auburn university, u.s.a. email: thomph1@auburn.edu abstract: this paper examines elasticity of substitution among electricity, labor and capital in u.s. manufacturing industry, using cross section data of 2007. in this analysis, manufacturing industries were categorized into three categories based on input use and technology. translog homothetic and non-homothetic production functions for each category were estimated but the restrictions imposed for homothetic production were rejected. the estimated parameters of non homothetic production function were used to estimate the own, cross price and morishma elasticities of inputs for three different manufacturing categories. these elasticities indicate that capital, electricity and labor are substitutes each other. cross price elasticities indicate that that electricity is weak substitute to capital and labor but capital and labor are strong substitutes to electricity. these elasticities and the availability of nonrenewable energy source suggest that price of electricity or energy will rise faster than wage and interest rate increase with economic growth. this implies that policies promoting the development and commercialization of alternative energy sources would be a better solution than policies promoting new energy saving physical capital or increasing labor productivity to meet the increasing demand for electricity. keywords: elasticity of substitution; manufacturing industries; translog production function jel classifications: d24; l60 1. introduction economists have debated about whether energy and capital are substitutes or complements (apostolakis, 1990). there are large number of conflicting econometric estimates of the elasticity of substitution between energy and capital. for example, using time-series data hudson and jorgenson (1973) and berndt and wood (1975) found that energy and capital are complements. but, humphrey and moroney (1975), griffin and gregory (1976) and halvorsen (1977) found energy and capital substitutable based on their cross-section estimates. field and grebenstein (1980), hazilla and kopp (1984), nguyen and andrews (1989) and morrison (1993) found mixed results. griffin and gregory (1976) and apostolakis (1990) suggest that because cross-section data capture the long run response to price changes the estimated result may show the substitutable relationship between two inputs. in contrast, since time-series data reflect short run responses to price changes the estimation may lead to a complementary relationship between the two inputs. miller (1986) points out that, at aggregate levels, (mixtures of many industries), when energy prices change the product mix substitution effects dominate the true factor substitution effects because energy intensive products are often produced where energy costs are lowest. as a result, elasticity of substitution estimates based on aggregate cross-section data are most likely to be biased upward, while the elasticity of substitution estimates based on aggregate time-series data are most likely to be biased downward. when energy prices goes up, prices of products, particularly energy-capital intensive products, goes up. this will reduce the demand and production for these products and then the demand for factor inputs including capital and energy. international journal of energy economics and policy, vol. 2, no. 2, 2012, pp.50-54 51 in this study, cross section data of four digits four hundred sixty u.s. manufacturing industries in 2007 were used to estimate three-input translog production function. there are large variations across the industries in terms of input use and technology. these industries were categorized into three categories based on input use and technology. these groups are naics 311 & 312 (food, beverages and tobacco manufacturing), naics 334 – 339 (computer and electronic product manufacturing, electrical equipment, appliance, and component manufacturing, transportation equipment manufacturing,) and naics 313-333 (all other manufacturing). a translog production function for each category was separately estimated. the homothetic and non-homothetic production functions were estimated and selected most suitable one for each category. then, own and cross price elasticities of factor inputs for each category. 2. production function the translog function is a flexible function. this function has both linear and quadratic terms with the ability of using more than two factor inputs. the three-input translog production function can be written in terms of logarithms as follows, ln y = αo +βk ln k+ βl ln l+ βe ln e+½ βkk ln k2 +β kl ln k ln l +β ke ln k ln e ½ βll ln l2 +β le ln l ln e + ½βee ln e2 (1) where y is the gross manufacturing output, k is real stock of capital input, l is labor input, and e is electricity. αo is the intercept or the constant term. βk , βl and βe are first derivatives. βkk, βll, and βee are own second derivatives. β kl , β ke , and β le are cross second derivatives. under perfect competition assumption, output elasticity with respect to input equals to cost share of that input. thus, we can get a system of equations from differentiating the translog production function with respect to each factor input, ∂ln y/ ∂ln k = βk + βkk ln k+ βkl lnl+ βke ln e ∂ln y/ ∂ln l = βl + βlk ln k+ βll lnl+ βle ln e ∂ln y/ ∂ln e = βe + βek ln k+ βel lnl+ βee ln e (2) coefficients in (2) are symmetric across equations due to young’s theorem on partial derivatives applied to (1). simultaneous estimation improves estimation properties over single equations, and imposing the symmetry constraints in (2) typically improves estimates further. (marginal product of the input) equals own derivative of marginal product equals cross derivative of marginal product equals we assumed that the economy minimizes the cost of producing a unit of output by choosing the level of inputs based on the input prices given. first order conditions of the cost minimization leads to the symmetric hessian matrix of the constrained cost minimization 0 yk yl ye λ 0 . ykk ykl yke k = r (3) . . yll yle l w . . . yee e e cross section translog production and elasticity of substitution in u.s. manufacturing industry 52 the inverted hessian matrix is used to derive own price and cross price input elasticities such as εke = (k/e)(e/k). elasticities are calculated at estimated marginal products such as ye = e. in this model, we assume factor prices are exogenous because us is a price taker in global energy and capital markets. wage is considered as exogenous because of wage contacts. 3. estimation and empirical results the cross section data of u.s. manufacturing data were collected from the u.s census bureau report for 2007. the available data for the four digit (naics) four hundred and fifty four manufacturing industries were value added, number of employees, pay roll, purchased electricity and expenditure on electricity, and expenditure of fuel. in order to estimate three input transolg production, the dependent variable for production function was calculated by subtracting expenditure of fuel from value added. then, residual capital expenditure was estimated by subtracting payroll and expenditure on electricity from the dependent variable. share of input expenditures were estimated. the translog production function (1) is non homothetic and imposes no restrictions except symmetry. for a homothetic production function, the marginal rate of technical substitution is homogenous of degree zero in inputs which requires ∑j βij= 0. the production function is homogenous of degree θ if ∑i αi= θ and ∑j βij= 0. the linear homogeneity obtains if θ = 1. the translog production function is additively separable if βij =0 ( i # j) and reduces to a cob-douglas technology. we estimate three input translog production function without restriction except symmetry and also with restriction for homothetic production ∑j βij= 0 and symmetry. we did not restrict linear homogeneity. the three-input symmetric translog production was estimated by using seemingly unrelated regression method. because of additive condition, we drop one of the three equations to avoid singularity problem in estimation and we estimate only two equations. the restrictions imposed for homothetic production were rejected. the estimated parameters of regressions for non homothetic production function were given in table 1 and own, cross price elasticities of inputs and morishma elasticities for three different manufacturing categories were given in table 2. all these elasticity estimates are evaluated at the sample mean. table 1. regression parameter estimates by manufacturing categories --------------------------------------------------------------------------------------------------- parameter 311-312 313-333 334-339 ------------------------------------------------------------------------------------------ αk 0.1517* 0.1253* 0.1451* (0.0489) (0.0219) (0.0467) αl 0.7704* 0.8659* 0.8636* (0.0465) (0.0239) (0.0442) αe 0.1002* 0.0279* 0.0165* (0.0246) (0.0113) (0.0041) βkk 0.1313* 0.1536* 0.1563* (0.0064) (0.0037) (0.0073) βll 0.1109* 0.1397* 0.1514* (0.0050) (0.0037) (0.0074) βee 0.0223* 0.0327* 0.0129* (0.0024) (0.0011) (0.0006) βkl -0.1038* -0.1243* -0.1472* (0.0056) (0.0031) (0.0073) βke -0.0226* -0.0262* -0.022* (0.0027) (0.0015) (0.0033) βle -0.0052* -0.0071* 0.0091* (0.0026) (0.0014) (0.0033) n 51 291 112 ------------------------------------------------------------------------------------------------ * significant at 1% level, standard errors are given in parentheses. international journal of energy economics and policy, vol. 2, no. 2, 2012, pp.50-54 53 table 2. elasticities by manufacturing categories -------------------------------------------------------------------------------------------------- elasticity 311-312 313-333 334-339 ------------------------------------------------------------------------------------------------------------- price demand ηkk -1.12 -2.05 -1.91 ηll -3.75 -3.17 -3.26 ηee -5.11 -12.26 -8.08 ηkl 0.96 1.53 1.77 ηke 0.16 0.52 0.14 ηlk 3.71 2.89 3.18 ηle 0.05 0.27 0.09 ηek 4.76 9.59 6.02 ηel 0.35 2.67 2.07 morishma σmkl 4.72 4.70 5.03 σmke 5.27 12.78 8.22 σmlk 6.25 4.95 5.08 σmle 5.15 12.53 8.17 σmek 7.60 11.64 7.93 σmel 4.10 5.84 5.32 ------------------------------------------------------------------------------------------------------------- all the estimated parameters in the regressions for three categories of manufacturing are significant at 1% level. these results shows that all the own price elasticities are negative and cross price elasticities are positive. the greater own price elasticities for electricity suggest that demand for electricity is more elastic than demand for capital and labor. capital is less elastic than labor and electricity. the cross price elasticity estimates ηke and ηle suggest that one percent increase in electricity price leads to less than one percent increase in capital and in labor demand. this means that electricity is weak substitute to capital and labor but the cross price elasticities ηek and ηel suggest that one percent increase in capital and labor price leads to more than one percent increase in electricity. this means the capital and labor are strong substitutes to electricity. this suggests that price of electricity or energy will increase at the higher rate than the increase in real wage and interest rate with economic growth. this implies that, for the increase in the electricity price from current available energy sources, energy conservation policies promoting new energy saving physical capital or increasing labour productivity will not be a better solution in long run than the policies promoting the development and commercialization of alternative energy sources. morishma elasticity is not symmetric because the morishma elasticity measures the responsiveness of input ratios to changes in different input prices. morishma elasticities show that the change in electricity and capital ratio for one percent increase in capital price is greater than the change in electricity and labor ratio for one percent increase in labor price. this indicates that capital is stronger substitutes to electricity than labor. since we use aggregate cross section data across the industries the elasticities are higher than the elasticities estimated previous studies from time series data. in this study, manufacturing categories (313-333 naics series) have more variation among industries and they are high energy intensive product and should be produced in the place where electricity price is low. in manufacturing categories (313-333 naics series), all the own price and cross price elasticities related to electricity are greater than those of other manufacturing categories. 4. conclusion the empirical findings show that capital, electricity and labor are substitutes each other in the u.s. manufacturing sector. cross price elasticities indicate that that electricity is weak substitute to capital and labor but capital and labor are strong substitutes to electricity. these elasticites and the availability of nonrenewable energy source suggest that price of electricity or energy will rise faster than wage and interest rate increase with economic growth. this implies that policies promoting the cross section translog production and elasticity of substitution in u.s. manufacturing industry 54 development and commercialization of alternative energy sources would be a better solution than policies promoting new energy saving physical capital or increasing labor productivity to meet the increasing demand for electricity. references apostolakis, b.e. (1990), energy-capital substitutability/complementarity: the dichotomy, energy economics, 1, 48-58. berndt, e.r., and d.o. wood (1975), technology, process, and the derived demand for energy, the review of economics and statistics, 68, 647-656. field, b.c., grebenstein, c. (1980), capital-energy substitution in u.s. manufacturing, review of economics and statistics, 2, 207-212. griffin, j.m., gregory, p.r. (1976), an intercountry translog model of energy substitution responses, american economic review, 66, 845-857. halvorsen, r. (1977), energy substitution in u.s. manufacturing, review of economics and statistics, 59, 381-388. hazillia, m., kopp, r. (1984). industrial energy substitution: econometric analysis of u.s. data, 1958-1974, ea-3462, final report, palo alto, ca: electric power research institute. hudson, e.a., jorgenson, d.w. (1973), u.s. energy policy and economic growth, 1975-2000, bell journal of economics, 5, 461-514. humphrey, d.b., moroney, j.r. (1975), substitution among capital, labor and natural resources products in american manufacturing, journal of political economy, 83, 57-82. miller, e.m. (1986), cross-sectional and timeseries biases in factor demand studies: explaining energy-capital complementary. southern economic journal 52(3), 745-762. morrison, c. (1993), energy and capital: further exploration of e-k interactions and economic performance, the energy journal, 1, 217-243. nguyen, s.v., andrews, s.h. (1989), the effect of energy aggregation on energy elasticities: some evidence from u.s. manufacturing data, the energy journal, 1, 149-156. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 2 • 2021220 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(2), 220-226. risk analysis of firm energy coverage in colombia in the medium term ricardo moreno1*, sergio a cantillo1, lilian a. carrillo-rodriguez2 1departamento de energética y mecánica, universidad autónoma de occidente, calle 25 # 115-85 km 2 vía cali-jamundí, colombia, 2departamento de ciencias sociales y económicas, universidad autónoma de occidente, calle 25 # 115-85 km 2 vía cali-jamundí, colombia. *email: rmoreno@uao.edu.co received: 20 august 2020 accepted: 10 december 2020 doi: https://doi.org/10.32479/ijeep.10490 abstract the recent auction of firm energy and the decisions on medium-term coverage give rise to risks in the supply of electricity in colombia in the coming periods. taking into account the possible risks that may arise, such as: non-compliance with feo due to generation units (six [6] non-compliances during 2015-2016 term), the delay of generation projects with committed firm energy (hidroituango case) and the availability of firm energy in the market, imply a systemic risk for the electric power supply in the medium term. through the study of technical documents and resolutions, issued by the creg, about the medium term energy balances in 2018, firm energy supply and demand balances were reconstructed, including the results of the last feo auction carried out in the first quarter of 2019, in order to carry out a risk analysis based on these same scenarios. it was observed that the amount of feo auctioned exceeds the quantity of demand projected, meaning that the creg assumed a conservative position by purchasing more energy than necessary (8650 gwh-year and 1027 gwh-year respectively), this is a situation that has occurred on more than one occasion. keywords: reliability charge, firm energy, firm energy obligation, risk jel classifications: l78, l94, q41, q42, q48 1. introduction installed capacity to produce electrical energy in colombia is constitute by hydraulic generation plants that correspond to 70% of the total, thermal generation plants in their different technologies: coal (10%), natural gas (11%) and liquid fuels (9%), and non-conventional energy sources (1%) (upme, 2018; garcía-rendón and pérez-libreros, 2019). with regard to energy coverage in the national interconnected system, in the medium and long term, given the high vulnerability to climate change of producing electricity with this type of energy in (olaya et al., 2016; pupo-roncallo, 2019), the energy and gas regulation commission (creg) established in december 2006, by means of resolution 071 of 2006, the methodology for the assignment and remuneration of the reliability charge (cxc), which has the objective to guarantee, at all times, a reliable energy supply at efficient prices, meeting the demand when water resources are critically scarce in periods of drought (creg, 2006a; acolgen, 2019). this mechanism aims to promote the expansion of the generation park, in principle efficiently, in the long term through auctions or other allocation mechanisms, when the creg identifies a firm energy deficit in the medium or long term (creg, 2018a; creg, 2018c). in principle, new generation projects and existing units of both conventional and non-conventional technologies can access the reliability charge through firm power auctions and therefore, commit firm power obligations (fsos) (creg, 2006a; harbord, 2016), which correspond to the commitment that generators acquire to produce an amount of energy according to the enficc in critical supply conditions; covered by generation assets that are in the capacity to produce under these circumstances (creg, 2018a). the generator to which a feo is assigned is committed to this journal is licensed under a creative commons attribution 4.0 international license moreno, et al.: risk analysis of firm energy coverage in colombia in the medium term international journal of energy economics and policy | vol 11 • issue 2 • 2021 221 deliver the agreed amount of energy when the stock market price at least in 1 h exceeds the cap established by the creg, called the shortage price (bedoya et al., 2016; gonzalez-castellanos et al, 2018). during the normal period between firm energy auctions, other allocation mechanisms can be carried out, given that, as mentioned in (creg, 2006a), “during the first semester of each year, the creg will verify if the sum of the enficc for each generation unit is equal to the target demand calculated for the term beginning on december 1, in accordance with the provisions of article 19 of this resolution.” this verification process is carried out by means of balances of enficc and target demand. however, since the entrance of the reliability charge mechanism in 2008, and the auctions of the following years, the allocation mechanism and its validity was put to the test during the great period of rainfall shortage caused by the el niño phenomenon, that occurred between 2015 and 2016 (mcrae and wolak, 2019). recent creg reports indicated that during this event, financial guarantees were made effective to six (6) hydraulic plants for non-compliance with firm energy commitments. in this way, the effectiveness (avoiding risk of shortages) of the execution of the financial guarantees depends on the availability of energy in the market. in this sense, the creg commissioners realized that the energy balance, based on which the calls and subsequent allocations of feos are made, must explicitly incorporate the risk of including firm energy bids from hydroelectric plants in the auction. therefore, through the creg 115 document of 2016, it is proposed that the annual firm energy balance should discriminate from the total firm energy, that energy which is committed by the agents of hydroelectric power plants. in other words, firm energy, but associated with a risk of default on as already observed during the 2015-2016 period. in this way, calculating the firm energy that can be guaranteed by hydropower plants under low hydrological conditions may represent a risk, given the intrinsic contradictions involved in calculating firm energy from hydropower plants that exploit a scarce resource under drought conditions. this condition suggests constant study and monitoring by both researchers and monitoring entities. this article provides an analysis inspired by the technical document d-050, presented by the creg in 2018, where three scenarios were proposed based on different operating conditions of the generation units that have feos in place, given the high probability of the appearance of the el niño phenomenon in the next 4 years from the publication of the document. these scenarios include information corresponding to the new feo allocations made through an auction held in february 2019, describing the respective effect. the article is structured as follows: chapter 2 provides a context of the implications of firm energy calculation for the different technologies for the reliability charge and the motivations that induced creg to hold an auction to allocate new ftos for the 2022-2023 period. the methodology used to propose scenarios and analyze the information is contained in chapter 3. chapter 4 presents the results and the respective analysis of the proposed scenarios. finally, chapter 5 presents the conclusions of the article. 2. problem formulation in reliability charge auctions, the auctioned market product is firm energy, called enficc (firm energy for reliability charge), which is defined in (creg, 2006a) as “the maximum amount of electrical energy that a generation unit is capable of delivering continuously under low hydrologic conditions, over a period of 1 year.” the methodology to calculate or determine firm energy is defined by creg according to the methodology presented in resolution 071 of 2006. according to annex 3 of this resolution, the calculation of the enficc for thermal power plants depends on the capacity of the plant, the availability of fuel(s) through the supply contracts and unavailability index of forced outputs, among other parameters according to fuel and technology. on the other hand, the calculation of the enficc for hydroelectric plants is done through a mixed integer linear programming optimization model (milp) whose complete formulation is found in annex 9 of resolution 071 of 2006. the objective of the optimization problem is to maximize the capacity to generate electric energy for each generation plant for all years with historical records of monthly water flows. in this way, the fe calculation is based on historical records, including the chronological order of each of the series, that is, there is a replica of the hydrological events (both drought and high rainfall) (osorno-cardona et al., 2018). the second step in the methodology for calculating the fe of hydroelectric power plants consists of organizing the annual historical fe values from lowest to highest and thus constructing a probability distribution curve for each unit, expressed in kilowatt hours per day per year (kwh-day/year). the lowest value corresponds to the 100% probability of available energy surplus and is identified as the base enficc, which according to (creg, 2006b) “corresponds to that generation that is capable of delivering a plant in the condition of 100% pss” (pss: probability of being exceeded). the base enficc is used in the firm energy auctions for the reliability charge as the reference value in the firm energy declaration. if the agent representing a hydropower plant chooses to offer a higher energy value than the base enficc, then it must back up this difference with a guarantee. from the probability distribution, a key value is obtained in the estimate of the fe, corresponding to the 95% pss enficc, that according to the resolution creg 079 of 2006, “corresponds to that generation that is capable of delivering the plant in the condition of 95% pss of the probability distribution curve” (creg, 2007). in firm energy auctions for the reliability charge, the agent can make bids between the base enficc and the 95% enficc. this 5% bidding margin represents a risk indicator since the base enficc assumes that historical low-hydrological events will be replicated in the medium and long term and this level represents the minimum bid value. in this context, in 2018, the creg published res. 104 of 2018, which provides for the holding of an auction to assign the feos moreno, et al.: risk analysis of firm energy coverage in colombia in the medium term international journal of energy economics and policy | vol 11 • issue 2 • 2021222 of the reliability charge for the period from december 1, 2022 to november 30, 2023. this resolution follows the recommendations of creg documents 050 and 075 of 2018 and the draft resolution creg 064 of 2018, regarding the requirement to convene an auction for the entry of new generation projects for the period 2022-2023, given that projections indicate a deficit in firm energy for the period 2022-2023, as shown in figure 1. about risk analysis, resolution 104 creg of 2018 points out some key aspects detected during the el niño phenomenon 2015-2016 that highlight the risk in energy coverage in the medium term. the creg finds “convenient that in the annual firm energy balance sheet, the portion corresponding to the incremental enficc to be discriminated from the total firm energy” (creg, 2018b). the incremental enficc corresponds to the agent’s supply from each plant that is greater than the base enficc and is backed by a financial guarantee that is activated in the event of default and which, in principle, would allow the missing energy to be purchased from another agent. in this sense, the document emphasizes about: “the need to reassess the concept or parameterization of the incremental enficc, particularly in a scenario of a more restricted power supply, where the financial guarantees are insufficient to mitigate the risk of default in the event that there is no more physical energy in the system to cover the shortfall” (creg, 2018b). in this sense, and initially in accordance with the evidence and findings, article 7 of that resolution indicates that enficc 98% pss will be used in the auction as the highest bid level for agents representing existing hydraulic generation plants. the allocation of feos is done through auctions, which are held with the objective of delivering these obligations among generators and investors that guarantee the reliability of long-term energy supply at efficient prices (creg, 2006a). these auctions are normally held between 3 and 4 years before the agreed firm energy is required, that was the case until 2012 (cramton, 2015). in this case, it occurs because of the described shortage condition. in feo auctions can participate generation agents that already deliver energy to the system and investors in new projects of this type, that meet the requirements of both financial and environmental guarantees of operation to deliver this energy, as well as the declaration of parameters and firm energy in the stipulated times, where those agents or investors whose reserve prices are lower than the closing price of the auction will be winners of these auctions, in order to guarantee efficient energy resources. 3. methodology according to the verification, creg has allocation mechanisms to perform annual verifications, if the comparison shows a deficit (less supply of enficcs than demand) an allocation is called by auction, encouraging the entry of new plants (for those plants feos are allocated for up to 20 years [creg, 2018b]). on the other hand, if there is a surplus (more supply than demand), a managed allocation is made (creg, 2018a) for a period of 1 year among existing units on a “pro-rata” basis of their share of total supply, without the inclusion of new plants (creg, 2018b). the creg, at the end of the 2018-2019 period, considered it appropriate to determine the mechanism for allocating feo for four periods, i.e., 2019-2020, 2020-2021, 2021-2022 and 2022-2023. for the first three periods through resolution 065 of 2018, it made the allocation through the mechanism of managed allocation, however, the balances made in (creg, 2018a) show that the firm energy available was still sufficient to meet the demand, but recommended the incentive to the entry of projects in the effect of 2021-2022, given the uncertainty of entry of the ituango project. similarly, for the period 2022-2023, the technical document recommended holding an auction for the allocation of feo, as there was a deficit in meeting the demand (creg, 2018b). 72,953 75,542 78,184 80,774 82,802 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 2018-2019 2019-2020 2020-2021 2021-2022 2022-2023 enficc total demanda proyectada figure 1: demand projections versus enficc totals moreno, et al.: risk analysis of firm energy coverage in colombia in the medium term international journal of energy economics and policy | vol 11 • issue 2 • 2021 223 the analyses carried out by (creg, 2018a) firstly, pointed to a re-evaluation of the participation of the incremental firm energy of the hydroelectric plants in the feo allocations, taking into account the little margin that the system would have to solve failures during critical periods, making necessary the reduction of the risk that the agents can assume. during the 2015-2016 el niño phenomenon, a third of the incremental enficc could not be delivered to the system, an amount of energy that cannot be neglected, especially during critical periods, and, secondly, creg identified possible delays in generation projects that were to come into operation in 2018 and that had feo from auctions held previously, such as the cases of hidroituango and termonorte. thanks to the analysis and conclusions mentioned above, creg decided that, by the first quarter of 2019, a reconfiguration auction should be held for the period 2022-2023 (creg, 2018c), in order to meet the growing demand and mitigate all the risks described above. however, the colombian electricity sector is characterized by three aspects: (a) being highly regulated, (b) centralized planning and (c) vertically integrated, therefore, firm energy auctions commonly reflect a conservative stance that tends towards excessive security, thus shifting the investment costs of additional resources directly to consumers (buriticá-arboleda et al., 2019). thus, through the system operator’s platform (xm), the feo results assigned for the four (4) terms described were extracted, including those assigned in the auction held in the first quarter of 2019 for the term 2022-2023. from this information, the scenarios presented in (creg, 2018a) were reconstructed as firm energy supply and demand balances (that is, feo defaults by water generation units, as well as delays in generation projects such as hidroituango and termonorte), whose results were analyzed according to what each scenario initially proposed, as well as the impact of the auction held under said circumstance. the detail of each scenario as well as its respective analysis is found in the results section. 4. results and discussion firstly, the information resulting from the auction in the first quarter of 2019 highlights the inclusion of feos from renewable energy sources such as wind power plant projects and solar panels, with a low percentage of participation (1%). however, the inclusion of this type of energy is a starting point for further analysis regarding trends, applicable policies, characteristics, and scenarios for the medium and long term planning and operation of the colombian electricity sector regarding these resources, such as the studies carried out by paez et al. (2017), barrientos and villada (2020), cabello et al. (2019), obregon et al. (2019) and forero et al. (2019), castro et al. (2019) among others. on the other hand, this result also reflects the effect of the incentives derived from the application of law 1715 in colombia, referring to the inclusion of re in terms of environmental sustainability and resilience of the sector to adverse weather conditions (ariasgaviria et al., 2019). in the same way, there was a strong reduction in the re from water generation units (9.67%) and the increase of re for most of the thermal generation technologies (i.e., gas and liquid fuels) with respect to the existing firm energy obligations before the auction, as shown in figure 2. in order to visualize the impact of the creg’s position on the risk of shortage, two (2) scenarios were created to reconstruct those proposed by the creg in its official technical document (creg, 2018a), including the feos auctioned for the 2022-2023 term in the first quarter of 2019. the description and results of the scenarios are set out in the following subsections. for a better understanding of the results of the proposed scenarios, two (2) additional concepts should be considered: the incremental executed guarantee enficc, which refers to firm energy that cannot be delivered by one or more generating units, with the activation of the respective economic guarantees, and on the other hand, the incremental non-executed guarantee enficc, which is considered the incremental firm energy that can be delivered in critical periods by the generating units without any inconvenience. 4.1. non-compliance of feo from hydropower plants in the first scenario, as mentioned in the creg document, it is proposed that an amount of firm committed energy equivalent to the greatest historical non-compliance of feo presented (i.e., 33.3% of feo during el niño phenomenon of 2015-2016) that comes from water generating units, given the vulnerability of the resource, cannot be delivered during an eventual period of extensive drought, activating the condition of scarcity price. this information was contrasted with the demand forecast for each of the periods under study. this scenario was considered to verify the effects of the auctioned feo in mitigating the impacts of non-compliance of said generating units, which were evidenced in the creg technical document. the results are shown in the supply and demand balance of fe presented in figure 3. the supply-demand balance for this scenario shows that for the 2022-2023 period, the amount of firm energy acquired is sufficient to supply the demand projection without resorting to the available incremental enficc, showing the mitigation effect of the new feos included in that period. on the other hand, the incremental enficc of the 2022-2023 period show a lower amount of incremental energy compared to the other periods under study that were not adjusted and were assigned from a previous feo assignment, which shows a positive effect on the resilience of the electricity sector to climate change. however, there is a surplus of firm energy (fe) for this same period, given that the difference between the total feos and the demand projection shows a surplus fe of 8650 gwh-year, equivalent to the amount of firm energy that the largest generating plant in the country (ituango) could offer. this means that, under this scenario, creg will have to go out to the market to resell this large amount of fe surplus to interested agents not necessarily at the price it acquired them, which could represent higher costs to the end user, where the conservative stance assumed by creg in this regard is evident. moreno, et al.: risk analysis of firm energy coverage in colombia in the medium term international journal of energy economics and policy | vol 11 • issue 2 • 2021224 on the other hand, it can be seen that for the 2021-2022 term, the demand projection matches with the amount of enficc without including the incremental one, which suggests that, under any contingency of any of the generation units with feo for that term, it would represent a great risk of shortage, having to resort to the incremental ones or go to the market to buy this missing energy. 4.2. delay in generation projects the second scenario refers to the delays that the new generation projects acquired by feo in the period under study would present. in this particular case, as the creg document explicitly refers to the cases of hidroituango (8529 gwh-year including incremental enficc) and termonorte (619 gwh-year), this is due to the fact that recent audit reports have shown delays of more than 8 months in some cases, and the high probability of further delays and inconveniences for the implementation of these projects. as in the previous scenario, this information was contrasted with the demand forecast for each of the periods under study. this scenario was developed to determine the effects of these delays, especially that presented by hidroituango on the medium-term energy reliability of the sin, given that firm energy committed by this plant represents a large percentage of the feos in the period under study, as evidenced in the creg document. the effects of the auctioned feos on mitigating the aforementioned impacts will also be determined. the results of this scenario are shown in the corresponding fe supply and demand balance presented in figure 4. the supply-demand balance for this scenario shows that, for the period 2022-2023, the amount of firm energy acquired is enough to supply the demand projection under these circumstances without resorting to the available incremental enficcs, which effectively shows that the feos allocated in the auction can amortize the negative effects of the proposed scenarios. as in the previous scenario, the incremental enficcs for the 2022-2023 period show a lower amount of incremental, making evident the case 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% enficc de hidroeléctricas enficc de térmicas a gas enficc de térmicas acarbón enficc de térmicas alíquidos enficc solar enficc eólicas 2022-2023 previo a subasta 2022-2023 incluyendo subasta figure 2: enficc 2022-2023 versus new reconfiguration auction results for the 2022-2023 72,953 75,542 78,184 80,774 82,802 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 2018-2019 2019-2020 2020-2021 2021-2022 2022-2023 enficc garantias ejecutadas enficc garantias no ejecutadas enficc sin incremental demanda proyectada figure 3: supply and demand balance of firm energy default scenario, including those allocated at auction in 2019 moreno, et al.: risk analysis of firm energy coverage in colombia in the medium term international journal of energy economics and policy | vol 11 • issue 2 • 2021 225 of hidroituango (base and incremental enficc) with respect to other periods under study that were not adjusted and were allocated from a previous feo allocation. however, the firm energy surplus (fe) presented for the same term is much lower in comparison to the previous scenario, given that the difference between the total feos and the demand projection shows a fe surplus of 1027 gwh-year. this means that, under this scenario, creg will also have to go out to the market to resell this amount of fe surplus to interested agents, not necessarily at the price it acquired them, which could represent a higher costs to the end user, although these costs will be comparatively lower than those that could be presented in the previous scenario. this fact confirms the effect of the conservative position taken by the creg, given that under these circumstances there are still fe surplus. on the other hand, for the previous periods, with the exception of the 2018-2019 period, the demand projection coincides at least with the incremental enficcs with executed guarantees, taking as the most critical case the 2021-2022 period (including hidroituango’s feo to satisfy the demand). this situation means that any contingency with any of the generating units, that have feos assigned for those terms, represents a very high risk of shortage to the sin. in this way, it is necessary to buy the energy that is lacking in the market, which eventually represents an increase in the price of electricity to users. 5. conclusions given the updated description of the scenarios that can be presented for the 2022-2023 period, supported by the creg technical document and the update corresponding to the auction held in the first half of 2019, it is concluded that there is a significant risk of coverage in the 2020-2021 period for any of the proposed scenarios and for other periods (2019-2020 and 2020-2021) in the case of the absence of the hidroituango feos, taking into account the high probability of occurrence of el niño phenomenon for any of the periods under study. on the other hand, even though for the auction held in the first quarter of 2019, the amount of feo belonging to hydroelectric plants has significantly decreased (9.7%) with the associated decrease in the incremental enficc, replacing it with more reliable firm energy for periods of drought and with firm energy belonging to renewable energy sources, which effectively mitigates the impacts of the proposed scenarios for the period 2022-2023, the creg took a rather conservative position by auctioning an amount of feos that was excessive in relation to the deficit that would potentially arise in a case of shortage, resulting in large amounts of surplus in relation to the two (2) proposed scenarios (8650 gwh-year and 1027 gwh-year respectively). consequently, this energy must be sold again by the creg to interested agents. this situation represents additional charges to consumers due to the surplus amount auctioned with respect to the demand projection, and it may also represent greater economic losses depending on the price of the energy at the time when the sale is made. references arias-gaviria, j., carvajal-quintero, s., arango-aramburo, s. (2019), understanding dynamics and policy for renewable energy diffusion in colombia. renewable energy, 139, 1111-1119. asociación colombiana de generadores de energía (acolgen). (2019), análisis de la evolución del cargo por confiabilidad. available from: https://www.acolgen.org.co/wp-content/uploads/2019/08/acolgen_ analisis-de-la-evolucio%cc%81n-del-cargo-por-confiabilidad.pdf. barrientos, j., villada, f. (2020), regionalized discount rate to evaluate renewable energy projects in colombia. international journal of energy economics and policy, 10(2), 332-336. bedoya, j.c., rodas, e.a., garcía, d.f. (2016), aspectos comerciales del esquema del cargo por confiabilidad en el mercado eléctrico colombiano. scientia et technica, 21(1), 5. buriticá-arboleda, c., ramírez-escobar, c., álvarez-bel, c. (2019), la 72,953 75,542 78,184 80,774 82,802 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 2018-2019 2019-2020 2020-2021 2021-2022 2022-2023 enficc ituango incremental enficc ituango base enficc garantias ejecutadas enficc garantias no ejecutadas enficc sin incremental demanda proyectada figure 4: supply-demand firm energy balance – delay generation projects scenario, including those allocated in the 2019 auction moreno, et al.: risk analysis of firm energy coverage in colombia in the medium term international journal of energy economics and policy | vol 11 • issue 2 • 2021226 seguridad de abastecimiento eléctrico en mercados liberalizados. 1st ed. bogotá: universidad distrital francisco josé de caldas. cabello, j., morejón, m.b., gutiérrez, a.s., garcía, a.p., ulloa, m.c., martínez, f.j.r., rueda-bayona, j.g. (2019), a look to the electricity generation from non-conventional renewable energy sources in colombia. international journal of energy economics and policy, 9(1), 15-25. castro, a.o., robles-algarín, c., gallardo, r.p. (2019), analysis of energy management and financial planning in the implementation of pv systems. international journal of energy economics and policy, 9(4), 1-11. cramton, p. (2015), colombia firm energy auction: descending clock or sealed-bid? available from: https://www.creg.gov.co/images/ contenidos_estaticos/documentos/cramton-colombia-firm-energyauction-format.pdf. creg. (2006a), comisión de regulación de energía y gas. por la cual se adopta la metodología para la remuneración del cargo por confiabilidad en el mercado mayorista de energía, resolución no. 071. creg. (2006b), comisión de regulación de energía y gas. por la cual se adicionan, aclaran y modifican algunas disposiciones de la resolución creg-071 de 2006, resolución no. 079. creg comisión de regulación de energía y gas. (2007), manual del programa para calcular la energía firme para el cargo por confiabilidad de plantas hidráulicas. creg comisión de regulación de energía y gas. (2018a), documento técnico creg-050-2018-subasta del cargo por confiabilidad 2022-2023. creg. (2018b), comisión de regulación de energía y gas. por la cual se fija la oportunidad para llevar a cabo la subasta para la asignación de las obligaciones de energía firme del cargo por confiabilidad para el período comprendido entre el 1 de diciembre de 2022 y el 30 de noviembre de 2023 y se hacen modificaciones a la resolución creg 071 de 2006, resolución no. 064. creg comisión de regulación de energía y gas. (2018c), documento técnico creg-075-2018 subasta de expansión del cargo por confiabilidad 2022-2023. forero, j.d., hernandez, b., orozco, w., acuña, n., wilches, m.j. (2019), analysis of the use of renewable energies in colombia and the potential application of thermoelectric devices for energy recovery. international journal of energy economics and policy, 9(5), 125-134. garcia-rendón, j., pérez-libreros, a. (2019), the electricity spot price and inclusion of non-conventional renewable energies: evidence for colombia. available from: https://www.ssrn.com/ abstract=3443910. gonzalez-castellanos, a., pozo, d., martinez, s., lopez, l., oliveros, i. (2018), economic impact of wind generation penetration in the colombian electricity market, arxiv preprint no. 1810.11458. harbord, d. (2016), creg expert panel on colombian energy market reform. available from: http://www.apolo.creg.gov.co/publicac.ns f/52188526a7290f8505256eee0072eba7/536e4d4ad166cd5a05258 0420070e8d0/$file/circular069-2016%20anexo2.pdf. obregon, l., valencia, g., duarte, j. (2019), study on the applicability of sustainable development policies in electricity generation systems in colombia. international journal of energy economics and policy, 9(6), 492-502. olaya, y., arango-aramburo, s., larsen, e.r. (2016), how capacity mechanisms drive technology choice in power generation: the case of colombia. renewable and sustainable energy reviews, 56, 563-571. osorno-cardona, y.a., mejía-giraldo, d.a., muñoz-galeano, n. (2018), metodología para estimación de energía firme a través de series hídricas sintéticas desacopladas. información tecnológica, 29(5), 35-46. paez, a.f., maldonado, y.m., castro, a.o. (2017), future scenarios and trends of energy demand in colombia using long-range energy alternative planning. international journal of energy economics and policy, 7(5), 178-190. p u p o r o n c a l l o , o . , c a m p i l l o , j . , i n g h a m , d . , h u g h e s , k . , pourkashanian, m. (2019), large scale integration of renewable energy sources (res) in the future colombian energy system. energy, 186, 115805. upme unidad de planeación minero energética. (2018), informe mensual de variables de generación y del mercado eléctrico colombiano-agosto de 2018. available from: http://www.siel.gov. co/portals/0/generacion/2018/informe_de_variables_ago_2018.pdf. mcrae, s., wolak, f. (2019), market power and incentive-based capacity payment mechanisms, working paper. available from: https://www.tse-fr.eu/sites/default/files/tse/documents/conf/2019/ energy_climate2019/mcrae.pdf. xm s.a.e.s.p. (2019), resultados generales subasta feo 2022-2023. available from: https://www.xm.com.co/resultado%20subasta%20 cargo%20por%20confiabilidad/resultadossubasta%20feo22-23.pdf. tx_1~at/tx_2~at international journal of energy economics and policy | vol 6 • issue 2 • 2016152 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2016, 6(2), 152-158. indexing oil from a financial point of view: a comparison between brent and west texas intermediate cem berk* department of accounting information systems, school of applied sciences, istanbul arel university, turkey. *email: cemberk@arel.edu.tr abstract brent crude and west texas intermediate (wti) are major indices for purchases of oil worldwide among with some others such as opec basket. brent is traditionally a european index whereas wti representing slightly sweeter and lighter crude is more applicable in usa. until 2010, the spread between wti and brent hasn’t been more than few dollars. however in recent years, the spread is widening in favor of brent and then returning to the mean. wti which historically taken over brent, has fallen below brent which is now claimed to be the global oil index for the world. this is sometimes argued with the shale production and over-supply in the u.s. and several macroeconomic events such as libyan crisis. the aim of this paper is to analyze which of these indices is a better indicator for the energy industry. the variables from nyse exchange traded funds namely energy select sector spdr etf (xle), teucrium wti crude oil etf (crud), and united states brent oil etf (bno) for the period december 1994 and september 2014. the variables are analyzed for long-run and short-run relationships with unit root tests, vector autoregression models, and vector error correction models as well as cointegration and granger causality tests. keywords: energy modeling, oil indexing, cointegration, granger causality jel classifications: c58, p48, q37 1. introduction for most trades and especially commodities, certain categorizations are required to see the quality of the goods. for oil trade, this is done through indices such as brent, west texas intermediate (wti), dubai, urals, isthmus, lls and opec. all of these oil have different characteristics, qualities, and market penetration and therefore have different prices. opec is a basket composed of arab, basrah, bonny, es sider, girassol, iran, kuwait, marine, merey, murban, oriente, and saharan oil. the number of global indices used are over 150. these indices are used while pricing oil, so they have importance for international oil trade. other crude oils are priced against major indices such as brent, wti, and dubai. technically wti is the best quality oil among these. but this is just a slight difference in quality, which means wti should trade a few u.s. dollars premium to brent. this is a light weight and low sulphur oil. this means when refined it could generate more gasoline. this is traditionally an american oil, however its production is decreasing. brent represents a european index, and often characterized by the north sea. the oil is in very different locations. the oil is still known to be light and sweet, however wti is lighter and sweeter. so we know from law of one price that the price differential should be equal and otherwise arbitrage opportunities arise. this is true however, it is the supply and demand conditions, and the location differences as well as political risks (as in the case of libyan crisis and many others) that could create spread between these two indices. historically, brent and wti have traded very close to each other, spread almost mean reverted to zero level until 2010. there are many reasons, but to tell the result wti has lost value against brent, and nowadays recovered a bit. the most important considerations are supply related and geostrategic. u.s. also started to switch alternative and modern ways of using energy, berk: indexing oil from a financial point of view: a comparison between brent and wti international journal of energy economics and policy | vol 6 • issue 2 • 2016 153 such as shale gas. when wti loses value, people producing and trading based on wti lose money. this spread is very important for international trade, which is the research topic of this paper. in this paper, it is investigated whether any of these indices have explanatory power on energy industry. the remainder of this paper is organized as follows. in section 2, some of the recent and important works in this research area are presented. then the methodology and research model is given in section 3. the information on data, as well as research results are available in section 4. in section 5, some of the important findings of the study are discussed. in section 6, policy and financial implications are discussed. 2. literature review liao et al., performed a unit root with structural breaks to test whether international crude oil markets are globalized or regionalized. unit root is detected for lower quantiles however mean reversion is detected for upper quantiles. with kolmogovsminov methodology it is proven that the price differential is mean reverting and thus globalization view supported. oil traded in usa is more commonly used in wti whereas out of usa brent is used. wti is also a higher quality with larger quality and less sulphur. it is argued that until 2010 wti is traded with a premium and after 2010 there is a structural break such that wti crude oil is traded at discount compared to brent. due to the non-normality and structural breaks, the method in koenker and xiao, and enders and lee, is used instead of conventional techniques. the spreads show unit root in the lower quantiles but mean reversion in the upper counterparts. the quantile kolmogorov–smirnov test statistic over the whole range rejects the null hypothesis of unit root which means that the differentials are globally stationary and supports globalization hypothesis (liao et al., 2014). creti et al., studies the relationship between oil price and stock market in oil importing and oil exporting countries. the longrun relationship with engle-granger causality are studied for this purpose. the short run co-spectral analysis of priestley and tong (1973) is also studied. the research period is 2000-2010. brent oil is chosen as the oil index for this study. the relationship between oil index and stock market is found as a medium-term phenomenon. the relationship is more recognizable for oil exporting countries where oil shocks move together with stock market (creti et al., 2014). huang and chao studies international and domestic oil prices and indices in taiwan. the results are interesting; domestic oil prices don’t granger cause international indices. threshold vector error correction model (vecm) and threshold autoregression is used for this purpose. brent crude oil is chosen to represent international oil index. another conclusion is the mean reversion is faster when a small shock occurs than a big shock. government intervention to the oil market is ineffective (huang and chao, 2012). arouri analyzes the respond of european stock movements to oil changes. the power of this relationship varies according to the industry. the markets are analyzed between 1998 and 2010. brent oil is used as an indicator for oil index. zivot–andrews is used for testing unit root. the study is a multifactor analysis including return of stocks, industry, oil, and a dummy variable to include whether there is a crisis. furthermore granger causality is short term variable. it is found that there is a relationship between oil price changes and stock markets. for the automotive industry there is a clear negative correlation between industry returns and oil. but the relationship is not such strong in other industries (arouri, 2011). wang et al., analyze oil price shocks with stock market activities. as expected the results state that there are different effects on oil exporting and oil importing countries. also the dependence on oil, increases the negative effects on stock market in case of a price increase in oil. wti is chosen as the benchmark oil for this study. granger causality and vector autoregression (var) is used in this study. the results show that oil price shock explain 20-30% of global stock return variations (wang et al., 2013). lee et al., study stock market returns in g7 countries. the research period is 1999-2009. the research is interesting since it focuses on developed countries. oil price changes don’t significantly affect the stock markets, however stock price changes lead oil prices. var, vector error correction and granger causality are used in this study (lee et al., 2012). basher et al., study the relationship between oil price changes, exchange rates and emerging market stocks. the research method is structural var. positive shocks of oil prices depress emerging market stock prices and us dollar exchange rates. most of this dynamic movements take place in the short run. oil importers’ currency depreciate, whereas oil exporters’ currency appreciate in case of an increase in oil price (basher et al., 2011). tao et al., explain indexing in shale oil for industrial purposes for bogda mountain oil shale in china. the oil is classified according to petrological type, organic component content, hydrocarbon generating potential. the findings show that lithologic types and industrial classification of oil shales can be classified as follows: the content of organic component lower than 5%, between 5% and 15%, between 15% and 25%, and over 25% correspond to low-quality, medium-quality, and high-quality oil shale (tao et al., 2010). buyuksahin et al., has shown that starting from fall of 2008, the benchmark wti crude oil has traded at discount to brent benchmark. however the same discount isn’t reflected to other oil indices. this spread is detected on oil futures positions when controlled macroeconomic and physical market fundamentals. wti is historically a more reliable benchmark for u.s.a, where brent is a european benchmark. the spread is also analyzed for several components both for wti and brent; such as wti and louisiana light sweet, louisiana light sweet and brent, and brent for international oil and brent. the macroeconomic events are considered in the analysis namely libyan crisis and arab spring. the research period is between 2000 and 2012. there is clear evidence that wti crude oil traded at discount compared to brent. (buyuksahin et al., 2013). berk: indexing oil from a financial point of view: a comparison between brent and wti international journal of energy economics and policy | vol 6 • issue 2 • 2016154 kasibhatla studied whether there is a causal relationship between crude oil and u.s. dollar. the relationship is studied empirically with co-integration and error correction modeling. the study reveals that there is granger causality from u.s. dollar to crude oil price. over the past 15 years there wasn’t a stable correlation between s and p and crude oil ranging from plus or minus 20%. the data used in the study is u.s. dollar index (usdx) and crude oil prices (coil) for the period january 1990-may 2010. the series are stationary with their first differences (i(1)) according to augmented dickey-fuller (adf) and kwiatkowski–phillips– schmidt–shin. the series are then tested with trace test and maximum eigenvalue cointegration where one vector is found which is an indicator of long-run relationship. there is some doubt on short term relationship; however there is a tendency to restore equilibrium following a shock to the system. there is also proven causality, u.s. dollar index granger causes the crude oil price (kasibhatla, 2011). gammara et al., study the granger causality between the price of oil and integrated latin american market index. the framework proposed by hatemi (2012) is used as methodology. the result shows no significant causality. the authors further argue from the law of one price that there is no arbitrage opportunity between oil and index (gamarra et al., 2015). lee et al., study the relationship between stock prices and wti oil index for the period january 1998 and march 2012. garch methodology is used for g7 countries’ stock market performance and wti oil index. according to the results canada has the highest hedge effectiveness and japan has the lowest. because of low correlation between the stock market index of japan and the oil price, the optimal portfolio weight of japan is higher (lee, 2014). wei and chen examine the relationship between wti oil spot returns and the s&p 500 energy index. daily data is used for the period january 2000 and september 2009. multivariate garch methodology is used in this paper. the result shows that wti is significantly affected by energy index returns. investors can also use energy index returns’ past volatility as the basis for wti oil price forecasting (wei and chen, 2014). 3. research model in the study the variables are checked to see whether they are stationary. this is done first with adf methodology. if any of the roots of the polynomial (1∂1l∂2l 2-…∂pl p) of an ar (p) stochastic process lie outside the unit circle, the process is said to non-stationary. the traditional adf way of testing for nonstationarity of an ar (p) process involves testing for the null of one unit root in: ∆ = + ∆ + + +− − − − ∑y y y t ut t j t j t j p γ φ α β* 1 1 1 the stationary characteristics of the variables are tested also with phillip-perron (pp) methodology. pp test is a non-parametric modification to the standard dickey-fuller t-statistic to account for the autocorrelation that may be present if the underlying dgp is not ar (1). instead of adding ar terms in the dgp to account for (possible) ma terms, they modify the test statistic. however, schwert (1989) showed that pp test suffers from poor size properties if the ma term is large negative. thus, adf and pp tests suffer from quite opposite problems. while the adf test does not suffer from as severe size distortions, it is not as powerful as the pp test. the other “problem” with the pp test is that of consistent estimation of the so called long-run variance or the variance of the sum of the errors: (virmani, 2001). σ ε2 1 2 2 1 = − − ∑p t e j j t lim [( )] since there are differenced variables the variables are tested for cointegration according to johansen procedure. if the coefficient matrix π has reduced rank r<n, then there exist nxr matrices α and β each with rank r such that π = αβ′ and β yt ′ is stationary. r is the number of cointegrating relationships, the elements of α are known as the adjustment parameters in the vecm and each column of β is a cointegrating vector. it can be shown that for a given r, the maximum likelihood estimator of β defines the combination of yt−1 that yields the r largest canonical correlations of δyt with yt−1 after correcting for lagged differences and deterministic variables when present. johansen proposes two different likelihood ratio tests of the significance of these canonical correlations and thereby the reduced rank of the π matrix: the trace test and maximum eigenvalue test (hyalmarsson and osterholm, 2007). the variables are tested also for long run and short run causality with granger methodology. as it turns out, a notion of causality that is highly relevant to the present context of temporal causal modeling called granger causality has been introduced in the area of econometrics. this notion is based on the idea that a cause should be helpful in predicting the future effects, beyond what can be predicted solely based on their own past values. more specifically, a time series (or a feature in the terminology of the present paper) x is said to granger cause another time series y, if and only if regressing for yin terms of both past values of y and x is statistically significantly more accurate than doing so with past values of y only (arnold et al.). 4. data analysis the variables used in this paper are from nyse exchange traded funds namely energy select sector spdr etf (xle), teucrium wti crude oil etf (crud), and united states brent oil etf (bno) for the period december 1994 and september 2014. the data is daily, a total of 901 for all three variables. the energy select sector spdr fund performs a passive investment strategy to mimic the returns of energy select sector index before the expenses. the replication strategy berk: indexing oil from a financial point of view: a comparison between brent and wti international journal of energy economics and policy | vol 6 • issue 2 • 2016 155 requires buying all of the securities represented in the energy index. fund has a minimum of 95% limit for extreme cases for buying the assets in the exchange. this index include oil, gas and consumable fuels; and energy equipment and services. the companies selected are also in s and p 500 index. the variable is denoted as xle (like in the nyse) shortly in for this paper in the analysis. the figure 1 below provides descriptive statistics for the variable xle. teucrium wti crude oil etf provides access to crude oil investment through futures. the fund is unleveraged and diversified with instruments of different maturities. this reduces contango and backwardation and minimizes maturity risk. the daily changes in net asset value of weighted average closing price in wti crude futures is reflected to etf price. the benchmark index is wti crude oil futures contracts, which are traded in nymex. the variable is denoted as crud (like in the nyse) shortly in for this paper in the analysis. the figure 2 below provides descriptive statistics for the variable crud. united states brent oil etf uses short term oil futures which are traded on ice futures exchange as the benchmark. therefore the daily changes in brent crude oil affects the performance of etf. the duration of the contracts does in no circumstances exceed 6 weeks. depending on market conditions fund sometimes invest in other crude oil investments that are more liquid. the variable is denoted as bno (like in the nyse) shortly in for this paper in the analysis. the figure 3 below provides descriptive statistics for the variable bno. the variables are tested with adf methodology to check whether they are stationary. the test is applied under 5% level of significance. the test statistic for the variable bno is higher than critical value with absolute values. this shows that variable bno is stationary in level (i(0)). this variable will be used in level so there is no test for differenced series. the test statistic for variable crud however doesn’t exceed critical value. therefore the variable isn’t stationary in level. the variable is then tested with its first difference where test statistic is higher than critical value. this means that the variable crud is stationary with its first difference (i(1)). the test statistic for variable xle fail to exceed critical value. therefore the variable isn’t stationary in level. the variable is then tested with its first difference where test statistic is higher than critical value. this means that the variable xle is stationary with its first difference (i(1)). the variables are tested also with respected pp methodology to check whether they are stationary. the findings are the same. the test is applied under 5% level of significance. the test statistic for the variable bno is higher than critical value with figure 1: histogram and descriptive statistics for the variable xle figure 2: histogram and descriptive statistics for the variable crud berk: indexing oil from a financial point of view: a comparison between brent and wti international journal of energy economics and policy | vol 6 • issue 2 • 2016156 absolute values. this shows that variable bno is stationary in level (i(0)). this variable will be used in level so there is no test for differenced series. the test statistic for variable crud however doesn’t exceed critical value. therefore the variable isn’t stationary in level. the variable is then tested with its first difference where test statistic is higher than critical value. this means that the variable crud is stationary with its first difference (i(1)). the test statistic for variable xle fail to exceed critical value. therefore the variable isn’t stationary in level. the variable is then tested with its first difference where test statistic is higher than critical value. this means that the variable xle is stationary with its first difference (i(1)). these findings are presented in table 1. the variables bno (in level), d(xle) and d(crud) are tested to be with var. (var) first lag length is determined with selection criteria. according to table 2, schwarz information criterion 1 lag is suggested. hannan-quinn suggests 2 lags, final prediction error and akaike suggests 3 lags. for the principle of parsimony, 1 lag is used as suggested by schwarz information criterion. 1 lag model var(1) is developed for most degrees of freedom. var(1) model with inserted coefficients is given below. d(xle)=−0.0236144462846*d(xle(−1))+0.011845650094 *d (crud(−1))-0.0120636442044*bno(−1)+0.511881384436 d(crud)=0.107683738179*d(xle(−1))−0.149917215877*d (crud(−1))− 0.00554718257705*bno(−1)+0.210270842466 bno=0.0116398272568*d(xle(−1))−0.0499537852161*d(cr ud(−1))+0.979721715954*bno(−1)+0.822174262873 the model is checked for robustness. this is done by checking ar roots. for any autoregression model all the roots should be within the unit circle. this is to say the modulus should be less than one for the model to be reliable. according to table 3, no roots are outside the unit circle, so the model passes the stability check. cointegration test is made to check the long-run relationship between the variables. the test is made according to trace and max eigenvalue methodology. according to both tests there are 3 cointegrating equations among the variables. this means the variable d(xle), crud, and bno is cointegrated. this is an important result since we have i(1) data in our model. the results are presented in table 4. figure 3: histogram and descriptive statistics for the variable bno table 2: lag length selection criteria for var model lag logl lr fpe aic sc hq 0 −4022.146 na 1.667556 9.024990 9.041112 9.031151 1 −2300.739 3427.376 0.035861 5.185512 5.249999* 5.210157 2 −2271.062 58.88656 0.034236 5.139153 5.252004 5.182282* 3 −2255.888 30.00811 0.033765* 5.125310* 5.286525 5.186922 4 −2249.410 12.76799 0.033957 5.130964 5.340544 5.211059 5 −2238.034 22.34278* 0.033777 5.125638 5.383582 5.224216 6 −2232.571 10.69398 0.034046 5.133567 5.439876 5.250630 7 −2227.915 9.083242 0.034379 5.143306 5.497980 5.278852 8 −2226.964 1.848059 0.035006 5.161354 5.564392 5.315383 *indicates lag order selected by the criterion. lr: sequential modified lr test statistic (each test at 5% level), fpe: final prediction error, aic: akaike information criterion, sc: schwarz information criterion, hq: hannan-quinn information criterion, var: vector autoregression table 1: augmented dickey-fuller and pp test results model adf test crıtıcal value test statıstıc pp test crıtıcal value test statıstıc bno −2.8645 −3.1101 −2.8645 −3.0093 crud −2.8645 −2.7147 −2.8645 −2.6338 xle −3.4115 −2.9845 −1.9412 0.6668 d(crud) −1.9412 −32.22 −1.9412 −32.19 d(xle) −1.9412 −30.61 −1.9412 −30.70 adf: augmented dickey-fuller, pp: phillip-perron berk: indexing oil from a financial point of view: a comparison between brent and wti international journal of energy economics and policy | vol 6 • issue 2 • 2016 157 to test the short run relationship among the variables vecm(1) vecm with one lag is developed. differenced series for xle and crud, and bno in level is used for regression. the model with substituted coefficients is given below. d ( x l e , 2 ) = 0 . 0 1 3 3 9 0 3 7 0 5 4 2 3 * ( d ( x l e ( − 1 ) ) 4 . 4 0 4 9 3 3 8 7 5 0 5 * d ( c r u d ( − 1 ) ) + 0 . 0 1 5 2 6 3 1 0 0 2 8 1 8 * bno(−1)-0.684215817684)−0.462598756341*d(xle(−1),2 )+0.0628008941327*d(crud(−1),2)-0.553787639821*d(b no(−1))−0.000810155617473 d ( c r u d , 2 ) = 0 . 2 9 3 7 6 9 7 6 8 6 5 5 * ( d ( x l e ( − 1 ) ) − 4 . 4 0 4 9 3 3 8 7 5 0 5 * d ( c r u d ( − 1 ) ) + 0 . 0 1 5 2 6 3 1 0 0 2 8 18*bno(−1)-0.684215817684)−0.14750935372*d(xle(−1), 2)+0.0580699809554*d(crud(−1),2)+0.108753698777*d(b no(−1))−0.00198005307708 d ( b n o ) = 0 . 0 0 7 3 9 4 2 9 1 8 6 6 5 6 * ( d ( x l e ( − 1 ) ) 4.40493387505*d(crud(−1))+0.0152631002818*bno(−1)0.684215817684)−0.00501435687067*d(xle(−1),2)+0.0 0793526657202*d(crud(−1),2)−0.0679807866109*d(b no(−1))+0.00169334201357 finally the variables are tested for granger causality. the test is run both with var(1) and vecm (1) to test for long run and short run effects respectively. the test is applied to check whether bno or d(crud) granger causes d(xle). according to table 5, in the short run (with vecm(1))bno granger causes xle, no other granger causality is detected for 5% level of significance. 5. discussion the variables representing brent crude oil, wti crude oil, and energy industry are checked to see whether they are stationary. this is done according to adf and pp methodology. both test indicate that brent crude oil is stationary in level, whereas wti crude oil and xle. the variables are modeled with var and vecm. this is done by first testing number of lags in the model where 1 lag is chosen as suggested by schwarz information criterion. the vecm(1) is run for the short run and var(1) for the long run analysis. ar roots table also support stability of the models since all the roots are within the circle. the cointegration results according to johansen procedure also indicate that the variables are cointegrated. the final test is granger causality. this is to see which index which index provide better explanation in the energy industry. according to granger causality results, brent oil explains energy industry perfectly in the short run. this is to say, brent crude oil index is a better indicator of explaining energy industry in the short run. however in the long run this effect disappears. wti doesn’t have a statistical explanatory value for energy industry. 6. conclusion according to the research, brent crude is statistically an excellent indicator of energy industry in the short run. brent traditionally is a better global benchmark although once taken over by wti. this means brent crude is now more reliable in representing oil industry. wti, being an american index from texas region, fails to represent energy industry for the research period statistically. this is an early warning signal for usa, and there is a lot to do for marketing and balancing the supply for wti, which despite its superior quality loses market penetration. another finding of the study is that there is no relationship between oil and energy industry in the long run. this is partly because long extraction and refinement period for crude oil. this result table 4: cointegration results unrestricted cointegration rank test (trace) hypothesized number of ce(s) eigenvalue trace statistic 0.05 critical value probality** none* 0.454493 982.8148 29.79707 0.0001 at most 1* 0.380460 438.5907 15.49471 0.0001 at most 2* 0.009583 8.647326 3.841466 0.0033 trace test indicates 3 cointegratingeqn(s) at the 0.05 level *denotes rejection of the hypothesis at the 0.05 level **mackinnon-haug-michelis (1999) p values unrestricted cointegration rank test (maximum eigenvalue) hypothesized number of ce(s) eigenvalue max-eigen statistic 0.05 critical value probality** none* 0.454493 544.2241 21.13162 0.0001 at most 1* 0.380460 429.9433 14.26460 0.0001 at most 2* 0.009583 8.647326 3.841466 0.0033 max-eigenvalue test indicates 3 cointegrating eqn(s) at the 0.05 level. *denotes rejection of the hypothesis at the 0.05 level. **mackinnon-haug-michelis (1999) p values table 3: ar roots table root modulus 0.979884 0.979884 −0.159148 0.159148 −0.014546 0.014546 no root lies outside the unit circle var satisfies the stability condition var: vector autoregression berk: indexing oil from a financial point of view: a comparison between brent and wti international journal of energy economics and policy | vol 6 • issue 2 • 2016158 has important implications for oil industry. the industry should actively look for alternative ways to extract and refine oil in less time consuming and more efficient ways. finally, as it is stated in this paper for wti, one source of oil may not be adequate for explaining oil pricing. this has important consequences for traders and decision makers who rely on oil prices. in order to better grasp changes in the industry, there should be more sophisticating work on indexing oil. this will probably come with introducing a basket including oil such as brent, wti and perhaps dubai. this is left for future studies in this field. references arnold, a., liu, y., abe, n. (2007), temporal causal modeling with graphical granger methods. kdd’07. p3. arouri, m.e.h. (2011), does crude oil move stock markets in europe? a sector investigation. economic modelling, 28, 1716-1725. basher, s.a., haug, a.a., sadorsky, p. (2011), oil prices, exchange rates, and emerging stock markets. energy economics, 34, 227-240. buyuksahin, b., lee, t.k., moser, j.t., robe, m.a. (2013), physical markets, paper markets and the wti-brent spread. the energy journal, 34, 129-150. creti, a., ftiti, z., guesmi, k. (2014), oil price and financial markets: mu ltivariate dynamic frequency analysis. energy policy, 73, 245-258. gamarra, k.h., sabogal, j.s., faloon, e.c. (2015), a test of the market efficiency of the integrated latin american market (mila) index in relation to changes in the price of oil. international journal of energy economics and policy, 5(2), 534-539. hatemi, j.a. (2012), asymmetric causality tests with an application, empirical economics, 43(1), 447-456. huang, w., chao, m. (2012), the effects of oil prices on the price indices in taiwan: international or domestic oil prices matter?, energy policy, 45, 730-738. hyalmarsson, e., osterholm, e. (2007), testing for cointegration using the johansen methodology when variablesare near-integrated. imf working paper. p5. kasibhatla, k.m. (2011), does the dollar call the tune for securities and oil? an empirical investigation. the international journal of finance, 23(3), 6870-6880. lee, b., yang, c.w., huang, b. (2012), oil price movements and stock markets revisited: a case of sector stock price indexes in the g-7 countries. energy economics, 34, 1284-1300. lee, y.h. (2014), dynamic correlations and volatility spillovers between crude oil and stock index returns: the implications for optimal portfolio construction. international journal of energy economics and policy, 4(3), 327-336. liao, h., lin, s., huang, h. (2014), are crude oil markets globalized or regionalized? evidence from wti and brent. applied economics letters, 21(4), 235-241. priestley, m.b., tong, h. (1973), on the analysis of bivariate nonstationary processes. journal of royal statistic society: series b, 35, 135-166. schwert, g.w. (1989), tests for unit roots: a monte carlo investigation, journal of business and economic statistics, 7(2), 156-158. tao, s., tang, d., li, j., xu, h., li, s., chen, x. (2010), indexes in evaluating the grade of bogda mountain oil shale in china. oil shale, 27(2), 180-188. virmani, v. (2001), unit root tests: results from some recent tests applied to select indian macroeconomic variables. indian institute of management, 3-5. available from: http://www.iimahd.ernet.in/ publications/data/2004-02-04vineet.pdf. wang, y., wu, c., yang, l. (2013), oil price shocks and stock market activities: evidence from oil-importing and oil-exporting countries. journal of comparative economics, 41, 1220-1239. wei, c.c., chen, c.h. (2014), does wti oil price returns volatility spillover to the exchange rate and stock index in the u.s.? international journal of energy economics and policy, 4(2), 189-197. table 5: granger causality probability table for d(xle) model bno d (crud) vecm (1) 0 0,3594 var (1) 0,2981 0,8395 vecm: vector error correction model, var: vector autoregression tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020 325 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 325-336. evaluation of near-net-zero-energy building strategies: a case study on residential buildings in jordan hikmat h. ali1*, fahmi a. abu al-rub2, bashar shboul3, hind al moumani1 1department of architecture, college of architecture and design, jordan university of science and technology, irbid-jordan, 2department of chemical engineering, college of engineering, jordan university of science and technology, irbid-jordan, 3department of mechanical engineering, college of engineering, jordan university of science and technology, irbid-jordan. *email: hikmat@just.edu.jo received: 17 june 2020 accepted: 08 september 2020 doi: https://doi.org/10.32479/ijeep.10107 abstract residential buildings contribute a significant share of energy consumption in jordan, consuming 23% of total energy demand. it is the highest electrical energy consuming sector in jordan, where it accounted for approximately 43% of the total electricity consumption in the year 2016. therefore, improving the energy performance of existing residential buildings in jordan is likely to reduce energy usage (approach net zero energy) and would be a means to minimizing national electrical consumption. a typical house model located in irbid is selected as a case study for the near zero energy design and saving energy objective. the study investigates the economic and computational potential of various integrated passive and active design systems for the jordanian residential building sector, by focusing on several parameters including orientation, layout, type of insulation, type of windows, shading system, type of ventilation system which used a comprehensive and detailed model of the natural convection air-cooled condenser integrated to stack (ncacc) as new efficient ventilation method, and using of two renewable energy technologies; pv and flat plate solar thermal collector during the design of the buildings. this study uses three-strategies of building energy analysis in order to achieve near net zero energy building (nnzeb) in irbid, jordan. two approaches (computational and analytical) could be utilized for the identification of energy building performance analysis. a dynamic building energy modeling and simulation software with different climatic conditions was utilized to identify the best building energy model. a suitable economic evaluation criterion was used to estimate the payback period of all systems applied. keywords: near-net-zero-energy building, residential buildings, energy usage, design strategies jel classification: q2 1. introduction a nearly net zero energy building (nnzeb) is a building that has optimum energy performance (rezaie et al., 2013) (d’agostino and mazzarella, 2019) and should meet its energy requirements largely amount from renewable sources produced on-site or nearby (department of the environment, 2012). the purpose of nnzeb is carried out by using a set of different design strategies which apply efficient technologies that diminish energy demands of building and subsequently use renewable energy systems. more specifically, net zero energy strategies include; minimizing household electricity consumption by using energy efficient devices; minimizing energy demand via efficient demands; minimizing space cooling and heating load through an energy efficient building envelope; and selecting adequate site-based renewable energy technologies to generate electricity and heat. the concept of a net zero energy building (nzeb) that was introduced by torcellini et al. (2006) compared two types of renewable energy sources: on-site energy supply versus off-site renewable energy supply. the study encompassed five renewable energy technologies, two on-site options: pv and micro combined this journal is licensed under a creative commons attribution 4.0 international license ali, et al.: evaluation of near-net-zero-energy building strategies: a case study on residential buildings in jordan international journal of energy economics and policy | vol 10 • issue 6 • 2020326 heat and power, and three off-site options: off-site windmill, the share of a windmill farm and purchase of green energy from a 100% renewable utility grid. (marszal et al., 2011). a net-zero energy building for dwellings could mainly produce energy via photovoltaic modules, wind turbines, or biogas generators. the net-zero energy residential building studied in this research utilizes pv modules to offset the electricity cost purchased from the grid (www.jordinvest.com.jo. (accessed 19 march 2015)., n.d.). wittchen et al. (2010) utilized two on-site renewable technologies: pv and flat solar thermal panels in order to generate energy needed to meet the nnzeb. the study found that this technology is the most appropriate and commonly used in denmark (wittchen et al., 2010). the appropriate use of energy requires three effective energy management strategies by; reducing the demand, employing energy efficiency, and using renewable energy systems. most of the energy loss comes because the breadth of the windows or canals and old appliances or ineffective heating and cooling systems. interestingly, energy savings of up to 25% in buildings can be achieved through the following long-term strategies: lighting lamps, air leakage testing, insulation, heating and cooling, checking the surfaces, landscapes, heating the air, windows, electrical appliances, and electronics (panão et al., 2013) (asadi et al., 2012). this study investigated the economic and computational of various integrated passive and active design strategies for jordanian residential building sector by focusing on building physical attributes such as orientation, layout, type of insulations, type of windows, shading system, type of ventilation system and use of renewable energy; pv and solar water heating system during the design of the buildings. a typical single house model located in irbid was selected as a case study for near zero energy design and energy saving objectives. the main purpose of the study was to minimize energy consumption (approach net zero energy) and improve resident’s quality life (minimize environmental effect) in irbid city by introducing the concept of three-strategy building energy analysis to develop near net zero energy buildings in hot climate regions using passive and active advanced strategies for implementing nnzeb. the aim of this study was to evaluate a cost-optimal nnzeb of two options by using life cycle cost analysis and explore different designing strategies of a nearly net zero energy for residential buildings in jordan, to compare and collect existing standards and their criteria in order to find differences and similarities with a focus on both passive design (building layout, orientation, envelope configurations, window design and ratio to wall, ventilation and infiltration), and active design (flat plate solar collectors and pv systems). this can be achieved by proposing an applicable solution for reducing energy consumption in new residential buildings in jordan, by introducing the concept of threestrategies building energy analysis. the findings can be beneficial by providing decision-makers, engineers and manufacturers with policies, tools, and strategies to develop new building codes using the energy efficient technologies and renewable energy systems for nearly net zero energy building in jordan. the results indicate that off-site renewable supply options are more cost effective than on-site renewable supply options to invest in renewable energy technologies. 2. literature review 2.1. the concept of net zero energy building (nzeb) this study conducted implementation strategies in terms of passive strategies and active strategies based on the basic concept of nzeb. to illustrate, building that reduces the initial load through passive strategies and then saves the remaining residual load through active strategies, so that the sum of the amount of energy consumption and energy generation is zero). a variety of studies have been carried out in relation to the reduction of building energy demand to reach nzeb. marszal et al. (2011) presented a definition for a net-zero energy of single house building. the net-zero energy residential building studied in this research utilized photovoltaic modules (pv) to offset the electricity cost purchased from the grid (marszal et al., 2011). it indicates that a net zero energy building for dwellings could produce energy via photovoltaic modules, a wind turbine, or a biogas generator. torcellini et al. (2006) introduced the concept of a net zero energy building (nzeb) through comparing two types of renewable energy sources: on-site or off-site renewable energy supply. this study encompassed five renewable energy technologies comprising two on-site options: photovoltaic and micro combined heat and power and three off-site options. the main purpose of the study was to evaluate a cost-optimal nzeb of two options by using life cycle cost analysis. the results indicate that the off-site renewable supply options are more cost effective than on-site renewable supply options to invest in renewable energy technologies (marszal et al., 2011). to study and investigate renewable technologies, wittchen et al. (2010) utilized two on-site renewable technologies: pv and flat solar thermal panels in order to generate the energy needed to meet the nzeb. this technology is the most commonly used in denmark (wittchen et al., 2010). venturi et al. (1997) discussed the technology options for the energy aspects which seem to not to be sufficient to ensure the diffusion of a nnzeb model in achieving a nnzeb objective; a significant role be played by designers and architects (venturi et al., 1977). on the other hand, meral ozel (2012) used an implicit finite difference method under steady periodic conditions to estimate the optimum insulation thickness with different wall orientation related to the cooling and heating demands of buildings in antalya, turkey during the summer season (ozel, 2013). fayez aldawi et al. (2013) studied energy savings and thermal performance for new three alternative single house wall designs using accurate software as well as a conventional single house wall system (aldawi et al., 2013). shady attia et al. (2013) used an energy building simulation tool (energy plus) to study the performance of buildings in the hot humid climate region and took an apartment in cairo, egypt as a case study. the purpose of the study was to improve new tools that help the decision making in designing nzebs, net zero energy building. it was found that the early conceptual design stages of nzebs enhance the design of nzebs (attia, 2012). ali, et al.: evaluation of near-net-zero-energy building strategies: a case study on residential buildings in jordan international journal of energy economics and policy | vol 10 • issue 6 • 2020 327 alaidroos and krarti (2014) studied the residential building envelope systems for five climate zones in saudi arabia as a case study: riyadh, jeddah, dhahran, tabuk and abha. this study aimed to improve the energy performance of residential buildings in saudi arabia to select the optimal design by optimizing the building envelope components based on life cycle cost and energy savings analysis. these components include wall and roof insulation, window glazing and shading system, and thermal mass associated with exterior walls. the optimization and sensitivity analysis results presented that the government of saudi arabia could save up to 36% in annual energy cost subsidies by supporting the investments and energy efficiency projects of the residential building sector (alaidroos and krarti, 2015). 2.2. energy efficiency of residential buildings in jordan the energy demand in jordan has increased progressively at a higher rate up to about 5.1% overall and about 4.6% annually in electricity consumption. rising oil prices have recently impacted the budget, causing a high financial burden which reached 1.9 billion jordanian dinars (jod) in 2016, approximately 7% of gdp. total energy consumption in the household sector in 2017 around (1342.5) toe, accounting for 23% of the total energy consumption in jordan. household consumption of electricity is 46% (the ministry of energy and mineral resources, 2017). according to the jordanian urban and housing development corporation and department of statistics, the number of housing units in jordan is over 2.35 million as of 2015. residential dwellings of the single-family house type accounts for 55.1% of housing units (the ministry of energy and mineral resources, 2017). numerous studies have been conducted about the energy efficiency of residential buildings in jordan. one study tried to optimize residential energy usage through adopting several design strategies in different climatic regions in jordan. the tasks performed for this study included selection of five climatic locations, simulation of the baseline building, analysis of the on-site availability of renewable energy, minimization of building energy use with passive design and energy efficiency measures, and the sizing of systems for the collection and storage of renewable energy to meet the reduced building needs (attia and zawaydeh, 2014). the percentage of homes that have knowledge of the means of energy savings is about (96.5%). the percentage of homes that use thermal insulation to insulate the walls is about (21%) and in irbid is (15%). polystyrene is considered the most popular material used in thermal insulation, where accounting for approximately (10%) of homes in jordan and (16%) in irbid. the percentage of homes with surface insulation is around (18%) in jordan and (14%) in irbid. slope pouring is considered the most common method used to insulate the roofs of single houses, where the percentage of homes using this method in jordan and irbid is (11%) and (14%) respectively (the ministry of energy and mineral resources, 2017). the most popular method used in the reduction of electricity consumption in residential dwellings is to switch off lights during natural light (94%), as well as switching off lights in unoccupied rooms. one less popular method used to reduce of electricity consumption in homes is the periodic maintenance of electrical appliances (47%). the percentage of houses using energy saving lamps in jordan is 80% (ministry of public works and housing, 2013). hammad et al. (2014) investigated the feasibility of implementing “green building” technology systems in jordan, studying the latest trends in this technology worldwide and developing a customized version with respect to the local context of jordan for retrofitting an older building toward green building conditions (hammad et al., 2014). kiwan used two types of renewable energy systems, pv and wind, in addition to thermal insulation, which was implemented to achieve the maximum energy requirement for a house building. it was found that insulation of external walls only accounts for reduceing 30% of the heating load without any change in cooling load (kiwan et al., 2020). furthermore, adding insulation on roof could minimize heating and cooling loads to 70% and 20%, respectively (attia and al-khuraissat, 2016; hammad et al., 2014). on the other hand, al-salaymeh et al. (2009) studied the feasibility of installing two types of pv technology, stand-alone and grid-connected, in a commercial building in amman, jordan. the results indicated that utilizing a grid-connected pv-system is more economical than stand-alone pv in a single house building. the estimated payback period for stand-alone and grid-connected pv system was 50 and 30 years respectively (al-salaymeh et al., 2010). alzyood et al. (2010) studied the thermal and economic impact of employing passive and active solar systems in a typical jordan residence, in which it was noted that the single houses were oriented towards south as the first step in zero heating houses (alzyood et al., 2010). another study evaluated the thermal performance of different test rooms with different covering constructions. it indicated that the thermal transmittance (u-value) has a major role in choosing building materials and the results also investigated the importance of using the ground as a cooling source through the active concrete system. a comparative study was conducted between existing residential buildings with high and low energy consumption and three different hybrid systems and three different renewable energy resources were designed for a certain size. it observed that, without taking into account the economic factors, hybrid systems are dominant (rezaie et al., 2013). 3. methodology the methodology implemented in this paper included multi design and energy efficiency strategies to achieve the target of near-netzero energy building (nnzeb). first, a survey was conducted in the city of irbid to study and evaluate the current situation of residential buildings. second, a base case representative to the entire housing units was selected to study and analyze the attributes of building configurations. third, different energy efficiency strategies to achieve nnzeb were applied. in phase one combinations and permutations fundamentals used in the energy analysis to identify all possibilities of the design alternatives end with understanding the characteristics of ali, et al.: evaluation of near-net-zero-energy building strategies: a case study on residential buildings in jordan international journal of energy economics and policy | vol 10 • issue 6 • 2020328 buildings taken from a survey. this phase analyzed the building parameters and made iterations to print out all design alternatives, to end with the optimum design single house from the existing residential building. in this phase, all parameters that presented form the survey are used with some adjustments through using building envelope sequence with insulation and new u-value, infiltration, lighting energy and cooling system taken from jordanian building code. the second phase is the efficiency system which divided into two parts: first part is passive design approach to end with base case building. the second part apply active design which creates a comprehensive and detailed model of the (ncacc). the results of the mathematical model consist of a set of linear and nonlinear mathematical equations. in phase three, two systems of renewable energy be adapted: first applying photovoltaic cells in electricity generation, and flat plate collector for domestic hot water (dhw). pvsyst software has been utilized to find the optimal system configuration which it is more economical. strategies in the study used in order to achieve near net zero energy building (nnzeb) in irbid, jordan by select the optimum design of three strategies. the computational study was based on energy simulation as a tools for design decision making, optimizing energy efficiency, reducing operating costs, life cycle cost analysis, and defining/validating performance targets. building simulation used to answer architectural questions during the early design phase in order to provide a higher level of energy efficiency from the outset and save time during the design process. design used for modeling and simulation that performs detailed analysis to predict how a building performs relative to; energy use, energy cost, and system sizing and performance. the engineering equation solver (ees) was used to solve the system equations of (ncacc). the study took place in the city of irbid which is located about 80 kilometers north of the capital, amman. irbid governorate is characterized by its outstanding location and economic, archaeological and historical importance, and is the second largest governorate after the capital, amman, in terms of population. irbid governorate is located in the far north, among fertile plains and valleys. jordan is also classified into three climatic regions: region 1, the jordan river valley, region 2, the eastern highlands and region 3, the desert. amman, the capital city of jordan, is the most densely populated city and irbid, zarqa, ma’an, karak, and ajloun are also more population spread cities after amman (hammad et al., 2014). irbid governorate constitutes a major source for the needs of jordan’s plant and animal production as well as livestock and contains many of the industries that make up a large part of jordan’s exports (http://www.essaymania. com. (accessed 09 january 2015)., n.d.). jordan is well-situated to utilize renewable energy sources, especially photovoltaic cells and solar thermal systems, because it has about 310 sunny days a year, providing a sunshine duration of about 3125 h/year (www.jordinvest.com.jo. (accessed 19 march 2015)., n.d.), and the average daily solar radiation on a horizontal surface about 5.64 kwh/m2 per days. (ministry of public works & housing, 2013). the climate data for irbid city used in this study taken by the jordanian green building guide. this data presents the maximum number of sunshine hours (11.9 h) occurred in june and july, while the minimum number of sunshine hours (5.4 h) occurred in january and december (hammad et al., 2014) (kaynakli, 2012). there is potential for bioclimatic design in all climatic regions of jordan. the climate of irbid governorate is mediterranean. the weather description for climate zones in this region is characterized by cold and rainy in winters and hot, dry summers, with rainfall in the irbid ranging between (290-550) mm and average relative humidity between (70-80%) in winter, which drops to (40-50%) in summer. the average annual minimum temperatures range between (2-4) °c and the average annual maximum temperature rise to (36-38) degrees celsius. 3.1. archival data and field survey a multi-stage cluster sampling method was used in this survey by selecting seven regions of irbid city: nuzha, manarah, barha, hashemiyah, naser, rowdah, and al-rabia. the sample of 726 single house units had been taken through site visiting of the municipality of each region. the survey studied various aspects of building attribute, including construction material, windows system, orientation, average living space, and layout. one-zone and typical one-story single-family residential building were studied in the survey. it was found that most residential building layouts are of rectangular shape and represent about 61% of the total samples, whereas 3.6% of buildings have a u-shape layout, which is the least popular, as shown on table 1. it is assumed that each of these layouts have their own energy performance attributes. the areas of these buildings ranged between 80 m2 and 310 m2. around 38.1% of buildings in this sample had an area of 120 m2. construction materials used varied between concrete bricks, which were used for around 48.5% of buildings, and around 31.1% used stones, while 20.4% used a mixture of concrete and stone. some of these buildings used insulation materials as shown in table 2. the percentage of units using insulation material for walls in irbid is around (18.5%). polystyrene is the most popular insulation material which represents around 9.5%, and air represent 7.3% while rockwool represent around 2.8% of the total surveyed units. on the other hand, the use of insulation in roof comprises 35.6% of the total units. the most used material for slab is pouring which represent around 11%, while flagstone represents around 4.5% and asphalt represents around 1.9%. opening was operable single sliding pane with single glazed and double glazed, aluminum framed without any exterior shading equipment. almost of windows (51%) in the four facades of buildings covers 20%-30% of the total wall area (wwr). 3.2. the proposed building characteristics the selected single house represents a typical housing unit in the irbid region. the area of the building is 120 m2. it consists of five rooms: two bedrooms, guest room, living room, kitchen and two bathrooms. the entrance is oriented south and the building ali, et al.: evaluation of near-net-zero-energy building strategies: a case study on residential buildings in jordan international journal of energy economics and policy | vol 10 • issue 6 • 2020 329 table 2: wall and floor system configurations and properties for the prototypical house design wall construction sections construction element thermal conductivity (w/m.k) density (kg/m3) specific heat capacity (j/kg.k) wall construction 1. stone 1.7 2200 1000 2. polystyrene 0.03 35 1400 3. concrete 1.75 2300 840 4. bricks 1.0 1900 840 5. plaster 1.2 1850 840 roof construction 1. tile 0.55 1900 837 2. polystyrene 0.03 35 1400 3. mortar 1.4 2100 650 4. sand 1.83 2200 712 5. concrete 1.75 2300 840 6. ribs 0.95 1900 837 7. screed 1.83 2200 712 height is 3 m. the number of family members is 5 occupants. as shown in figure 1. the wall is composed of 3 cm plaster, 20 cm concrete block and 3 cm plaster for inner layer (system 5). the roof is composed of table 1: the geometrical layout of the prototypical houses in jordan and their percentage floor layout rectangle square l-shape u-shape shape percentage 61.0% 27.2% 8.2% 3.6% ali, et al.: evaluation of near-net-zero-energy building strategies: a case study on residential buildings in jordan international journal of energy economics and policy | vol 10 • issue 6 • 2020330 table 3: base case building properties and envelope specifications climate characteristics 1. location of study irbid city 2. latitude, longitude 32, 35 4. altitude 616 general building characteristics 7. building code (classification) c: front, side, rear setback (4,3,4) m and 48% building area ratio 8. average area 120 m2 9. no. of room five rooms; three bedrooms, guest, living room, kitchen and 2 bathrooms 10. orientation south facade 11. layout rectangle 12. building type one story single family 13. construction material cement bricks. (block) 14. insulation type no insulation material used 15. wall system configuration 3 cm, plaster board, 20 cm bricks, 3 cm plaster (system 5) 16. roof system configuration screed 5 cm, concrete 7 cm, ribs 18 cm, plaster 3 cm 17. windows type clear single pane 18. wwr 20% 19. overhang and louvers none 20. doors made of solid wood/one outer door 21. average water consumption 3.333 l/m2-day 23. thermostat set point 20°c for heating, 25°c for cooling 24. lighting energy 4.5 w/m2-100 lux, surface mount 25. infiltration 0.7 ach 26. electrical ventilation no fan used 27. natural ventilation manual opening of windows and doors when internal thermal comfort is reduced 28. mechanical ventilation not used figure 1: floor plan of the selected houses 5cm screed, 7 cm concrete, 18 cm ribs, and 3 cm plaster. a flat roof has an inclination angle of 0° table 3. summarize all envelope configurations. 4. results and computational energy demand heat transfer is the transient flow of thermal energy from one system to another due to temperature difference between the two systems. based on theoretical one-dimensional heat transfer equations of three modes (conduction, convection, and radiation) as mentioned below by using warner and arpaci equations. these equations are used to estimate the heat loss or gain through the existing single house wall system monthly and annually. warner and arpaci equations were used to estimate the heat gain or loss through wall and roof by using one dimensional steady conduction, natural convection and radiation for vertical wall and horizontal roof composite materials determined [2]. the main purpose of these equations is to validate the results from simulation. equation (1) below was to find heat gain or loss by conduction & convection. ( ), , 1 in air in air out loss gain out out in total h a t t q h a h a h a k a = æ ö + +ç ÷ è ø (1) for radiant heat loss or gain through the air inside house to inside wall, equation (2) is used. ( )4 4, ,loss air in wall in gain q a t tes= (2) 4.1. stage one the first stage uses designbuilder energy building modeling software. the building parameters of existing residential units are listed in table 4 below. the table below summarizes the characteristics of three strategies which are used to evaluate the energy performance. the simulation results estimate the annual electrical energy consumption to be 3670.1 kwh and district heating consumption to be 2472.2 kwh, composed of 1333.2 and 1139.024 kwh of heating requirements and water system respectively. total energy end use is 6142.3 kwh (51.2 kwh/m2). according to the irbid electricity company annual report, 2017, the average household ali, et al.: evaluation of near-net-zero-energy building strategies: a case study on residential buildings in jordan international journal of energy economics and policy | vol 10 • issue 6 • 2020 331 table 4: characteristics of adopted strategies used to improve energy performance of buildings parameters strategy 1 strategy 2 (active) strategy 3 (renwable) phase 1(base) phase 2 (passive) wall u-value 2.381 w/m2.k 0.57 w/m2.k 0.2 w/m2.k 0.2 w/m2.k wall insulation thickness 0.0 cm 4.08 cm 4.0 cm 4.0 cm roof u-value 2.371 w/m2. k 0.55 w/m2. k 0.1 w/m2. k 0.1 w/m2. k roof insulation thickness 0.0 cm 3.71 cm 4.19 cm 4.19 cm window u-value 5.8 w/m2.k 3.1 w/m2.k 0.5 w/m2.k 0.5 w/m2.k window shading none none venetian blinds venetian blinds overhang and louvers none none. 0.5 m overhang 0.5 m overhang lighting energy 4.5 w/m2-100 lux, surface mount 3.4 w/m2-100 lux, surface mount 3.3 w/m2-100 lux, surface mount 3.3 w/m2-100 lux, surface mount lighting control none none. used. used domestic water consumption 3.333 l/m2-day 3.333 l/m2-day 3.333 l/m2-day 3.333 l/m2-day infiltration 0.7 ach 0.5 ach 0.35 ach 0.35 ach electrical ventilation none none the fan used for comfort cooling the fan used for comfort cooling natural ventilation manual opening of windows and doors when internal thermal comfort is reduced manual opening of windows and doors when internal thermal comfort is reduced manual opening of windows and doors when internal thermal comfort is reduced manual opening of windows and doors when internal thermal comfort is reduced mechanical ventilation none none ncacc ncacc thermostat set point 20°c for heating, 25°c for cooling. 20°c for heating, 25°c for cooling 20°c for heating, 25°c for cooling 20°c for heating, 25°c for cooling cooling system none split unit, cop 2.25 split unit: heat pump cop 4.5 split unit: heat pump cop 4.5 heating system gas furnace: cop 75% gas furnace: cop 75% gas furnace: cop 90% gas furnace: cop 90% dhw system instantaneous hot water only, cop 85% instantaneous hot water only, cop 85% stand-alone water heater, cop 85% flat plate solar collector. pv system none none none 9 m2 monocrystalline modules, pv field nominal power (pnom) 1.3 kwp, 2.5 mwh/year sector electricity consumer bill is 3247 kwh (27.06 kwh/m2). this value validates the simulation result of electricity consumption, which is found 3670.1 kwh (30.6 kwh/m2). irbid’s comfort temperature range was calculated according to ashrae’s adaptive thermal comfort equation below: top.com 18.9 + 0.255 tout (3) where top.com is the operative comfort temperature, tout is the mean monthly outdoor air temperature. maximum and minimum ambient air temperature and climatic parameters of irbid city are used for monthly analytical calculations as illustrated in the table 5 to find the total gross heat gain or loss. the analytical results show that the total heat loss or gain through the house wall system of strategy one-phase one (basecase) is about (−184.1) kwh/m2/year, while, the total heat loss or gain through the house wall system of strategy two (new efficient) is approximately 156.8 kwh/m2/year. the simulation results show that the energy saving of the second phase compared to existing residential buildings is 20.44% with total energy consumption equivalent to 40.7 kwh/m2, in the square shape. meanwhile the energy saving in the u shape was 12.9%. 384 iterations took place in order to predict the optimum building models and it is noticed that the square layout which is the best floor layout used and the u-shape is the worst one. a south facing orientation is the best and east is the worst one. wall system 2 and roof system 2 work best when used in combination with each other. the windows to wall ratio (wwr) that gives minimum consumption is 15%. different values of energy consumption could be printed out with different layouts, construction details, orientations, and wwr. it is observed that square layout is the best one while the u – shape is the layout achieved the minimum energy savings. the energy consumption increased with an increase in wwr. table 6 represents the relationship between energy consumption and layout, orientation, wall and roof details, and windows ratio (wwr). these results compare the best energy consumptions and the worst one. 4.2. stage two after selecting the best design alternative of base case strategy, six efficient parameters of passive design were added in order to achieve (nnzeb). these parameters are; wall u-value, roof u-value, windows u-value, infiltration, overhang and louvers, and shading. second part is applying active design: this part of study creates a ali, et al.: evaluation of near-net-zero-energy building strategies: a case study on residential buildings in jordan international journal of energy economics and policy | vol 10 • issue 6 • 2020332 ta bl e 5: a na ly ti ca lly d et er m in ed d at a fo r th e ex is ti ng s in gl e ho us e w al l s ys te m c om pa ri ng w it h se co nd p ha se in i rb id m on th h um an co m fo rt te m p. in si de ° c m ax . a ir te m p. o ut si de ° c m in a ir te m p. o ut si de ° c t he e xi st in g si ng le h ou se w al l s ys te m ( b as e ca se ) t he s ec on d ph as e si ng le h ou se w al l s ys te m q lo ss /g ai n w it h m ax . te m p. (c on d. – c on v. – r ad .) kw h/ m 2 /m on th q lo ss /g ai n w it h m in . te m p. (c on d. – c on v. – r ad .) kw h/ m 2 /m on th to ta l q lo ss / ga in (c on d. – c on v. – r ad .) kw h/ m 2 /m on th q lo ss /g ai n w it h m ax . te m p. (c on d. – c on v. – r ad .) kw h/ m 2 /m on th q lo ss /g ai n w it h m in . te m p. (c on d. – c on v. – r ad .) kw h/ m 2 /m on th to ta l q lo ss / ga in (c on d. – c on v. – r ad .) kw h/ m 2 /m on th ja n 21 .2 13 5. 9 −1 1. 43 −1 9. 84 −3 1. 26 −4 .0 7 −1 4. 38 −1 8. 45 fe b 21 .4 14 .1 5. 4 −1 0. 39 −2 4. 15 −3 4. 54 −3 .0 6 −1 4. 93 −1 7. 99 m ar 22 .0 17 7. 4 −7 .0 0 −1 9. 53 −2 6. 53 −1 .5 4 −1 3. 72 −1 5. 25 a pr 23 .1 22 .1 10 .7 −1 .3 8 −1 8. 54 −1 9. 92 −0 .0 2 −1 1. 58 −1 1. 60 m ay 24 .2 27 14 .2 3. 97 −1 3. 85 −9 .8 7 −0 .7 0 −9 .4 5 −1 0. 15 ju n 24 .9 30 17 .5 7. 27 −9 .4 5 −2 .1 8 −3 .3 0 −7 .0 1 −1 0. 31 ju l 25 .3 31 .1 19 .3 8. 13 −8 .8 6 −0 .7 3 −5 .3 0 −5 .7 9 −1 1. 09 a ug 24 .4 31 .4 19 .7 9. 84 −5 .4 8 4. 37 −9 .8 7 −4 .2 7 −1 4. 14 se p 25 .0 29 .8 18 .2 6. 86 −9 .2 0 −2 .3 4 −3 .1 9 −6 .4 0 −9 .5 9 o ct 24 .3 26 .7 15 .2 3. 35 −1 3. 45 −1 0. 10 −0 .5 6 −8 .5 3 −9 .1 0 n ov 22 .9 20 .7 10 .1 −3 .0 5 −1 8. 73 −2 1. 78 −0 .2 9 −1 1. 88 −1 2. 18 d ec 21 .6 15 6. 4 −9 .4 6 −1 9. 79 −2 9. 25 −2 .6 3 −1 4. 33 −1 6. 96 to ta l g ro ss h ea t l os s/ ga in (k w h/ m 2 /y ea r) −1 84 .1 −1 56 .8 0 comprehensive and detailed model of the (ncacc). this model takes from book “design of thermal systems” (stocker, 1989). the main purpose is designing minimum cost of a natural draft air-cooled condenser (acc) that rejects 140 kw of heat. the results of the mathematical model consist of a set of linear and nonlinear mathematical equations. the engineering equation solver (ees) used to solve the system equations. indeed, lighting control, ventilation, cooling and heating system efficiencies and mechanical ventilation used in this strategy. the simulation result shows the annual energy consumption reduced to 4073.6 kwh (33.9 kwh/m2), achieving 33.7% in total energy savings. the table 7 shows the detailed energy consumption of electricity and district heating and cooling. the ncacc system is solved using ees. this system is preferred to use in summer and spring, over 6 months. the annual total energy produced is 56.1 kwh/year (0.47 kwh/m2/year). the total energy saving of cooling consumption is 6.2%, therefore the annual energy consumption is reduced to 3820.2 kwh (31.8 kwh/m2), achieving 37.8% in total energy savings. 4.3. stage three the pv solar technology type used in this study is monocrystalline modules. this module needed to cater the total electrical power consumption of 2415.8 kwh/year could be achieved in standard test conditions (stc) when the solar radiation is 1000 w/m2 and the cell temperature is 25 degrees centigrade. after running the data through photovoltaic system software (pvsys), the optimal results data for installation of the pv system in residential buildings in irbid is shown in table 8. the results of the pv system which include mean solar radiation and system output indicate that the system has minimum electricity production in december (153 kwh) and maximum productivity in august (232 kwh) with total output reach along the year to 2400 kwh. the total energy saving after applied all energy saving techniques from strategy 1 to strategy 3 is 82.4% for final total consumption 1080.2 kwh/year. table 9 shows the comparison between strategy 1, strategy 2 and strategy 3 according to total annual energy consumption of electricity and district heating and highlights the total energy savings. figure 2 shows the variation of energy consumption of each strategy. 4.4. economic energy saving analysis economical energy savings analyses for the residential sector depend on construction materials, weather characteristic and occupant energy behavior. the table below shows the average cost of building materials. the average construction cost of the conventional house wall system is about 25.6 jod/m2 and of the new, efficient wall system is about 66.5 jod/m2. the cost of ceiling changes from 90.9 jod/m2 to 61.5 jod/m2. the cost of gas and electricity are taken into consideration in the estimation of energy costs. the average cost of electricity is about 0.086 jod/kwh for strategy one and 0.072 jod/kwh, whereas the cost of gas is 0.063 jod/kwh for residential targets according ali, et al.: evaluation of near-net-zero-energy building strategies: a case study on residential buildings in jordan international journal of energy economics and policy | vol 10 • issue 6 • 2020 333 table 6: maximum/minimum energy efficiency parameters of the selected house layout square u shape energy consumption (kwh/m2)/layout 40.724 44.563 energy saving (%)/layout 20.44 12.94 wall system system 2 stone 7 cm, insulation 2 cm, concrete 10 cm, insulation 2.08 cm, bricks 10 cm, plaster 3 cm system 6 plaster 3 cm, bricks 10 cm, insulation 4 cm, bricks 10 cm, plaster 3 cm roof system system 2 tile 3 cm, mortar 2 cm, sand 10 cm, mortar 5 cm, insulation 3.71 cm, concrete 12 cm, ribs 18 cm, plaster 3 cm system 1 screed 5 cm, insulation 4.19 cm, concrete 7 cm, ribs 18 cm, plaster 3 cm wwr 15% 30% energy consumption (kwh/m2)/wwr 40.724 41.834 energy saving (%)/wwr 20.44 18.27 layout south east energy consumption (kwh/m2)/ orientation 40.724 42.740 energy saving (%)/orientation 20.44 16.50 table 8: pv system adopted as major part of the third strategy used to improve performance on-grid pv system sizing 1. geographical site 1. location irbid city 2. country jordan 3. latitude 32.0 on 4. longitude 35.0 oe 5. altitude 616.0 m 6. orientation of collector plane tilt 30o 2. main features of pv-field installation 1. module type standard 2. technology monocrystalline 3. mounting method flat roof 4. back ventilation properties free standing 3. system characteristics and pre-sizing evaluation 1. pv field nominal power (pnom) 1.3 kwp 2. collector area (acoll) 9 m 2 3. annual energy yield 2.5 mwh/year 4. economic gross evaluation (eyear) 4274 jd 5. energy price 0.2 jd/kwh figure 2: the variation of energy consumption of each strategy used to minimize energy consumption to jordan petroleum refinery and jordanian electric power companies. according to the total energy required, the total cost of gas reduced from 3.2 jod/kwh in strategy 1 (step 1) to reach 0.75 jod/kwh after reaching step 3. meanwhile the total cost of electricity decreases from 4.4 jod/kwh to 0.72 jod/kwh. the payback period estimated for the new efficient house wall system (strategy 3) is 8.3 years when gas is the main source and 7.5 years when electricity is the main source, as represented in table 10. estimating the payback period by using the following relationship: total construction cost total investmentt payback period or saving total yearly cost = estimating the saving by using the following: • total cost of gas power (strategy 2) total cost of gas power (strategy 1) table 7: the annual energy consumption of the second strategy used to improve building performance consumption electricity district heating district coolingheating water system annual energy consumption (kwh) 2415.8 209.2 1139.0 309.7 annual energy consumption per meter square (kwh/m2) 20.1 1.7 9.5 2.6 table 9: comparison of energy consumption and saving from the first strategy to the third strategy consumption strategy 1 strategy 2 strategy 3 saving (%) annual energy consumption of electricity (kwh) 3670.0 2415.8 0 100 annual energy consumption of district heating (kwh) 2472.2 1348.2 533.4 78.4% total annual energy consumption (kwh) 6142.3 3820.2 1080.2 82.4 total annual energy consumption (kwh/m2) 51.2 31.8 9.0 82.4 ali, et al.: evaluation of near-net-zero-energy building strategies: a case study on residential buildings in jordan international journal of energy economics and policy | vol 10 • issue 6 • 2020334 ta bl e 10 : c os t e st im at io n of im pl em en ti ng d if fe re nt s tr at eg ie s to b e us ed fo r re ac hi ng (n n z e b ) p ar am et er st ra te gy 1 sa vi ng 1 st ra te gy 2 sa vi ng 2 st ra te gy 3 sa vi ng 3 p ha se 1 p ha se 2 t he to ta l e ne rg y re qu ir ed o f e ac h st ra te gy (k w h/ m 2 .y ea r) 51 .2 40 .7 31 .8 9. 0 c on st ru ct io n co st (j d /m 2 ) 11 6. 1 12 8 12 811 6. 1= 11 .9 12 8 12 811 6. 1= 11 .9 12 8 12 811 6. 1= 11 .9 e xi st in g sy st em (j d /m 2 ) n ew w al l sy st em (j d /m 2 ) w al l r en de r 5. 4 st on e 11 .5 b ri ck s 16 .2 b ri ck s 7. 0 pl as te r 4. 0 po ly st yr en e 3. 0 r . c on cr et e 41 .5 pl as te r 4. 0 to ta l c os t/w al l 25 .6 j d /m 2 66 .5 j d /m 2 r oo f sc re ed 40 .0 ti le 3. 0 co nc re te 41 .0 po ly st yr en e 3. 0 ri bs 5. 0 r . c on cr et e 30 .0 pl as te r 4. 5 pl as te r 4. 0 r ib s 3. 5 sa nd 10 .5 m or ta r 7. 5 to ta l c os t/r oo f 90 .5 j d /m 2 61 .5 j d /m 2 g as p ow er c os t ( jd /k w h) 0. 05 8 0. 05 8 0. 05 8 0. 05 8 to ta l c os t w ith g as (j d /k w h) l pg ; b ul k c en tr al d is tr ib ut io n 0. 06 3 jd /k w h 3. 22. 6= 0. 6 2. 00 2. 62. 00 =0 .6 0. 57 2. 00 -0 .5 7= 1. 4 51 .2 * 0 .0 63 =3 .2 2. 6 pa yb ac k pe ri od w he n ga s is m ai n so ur ce (y ea r) 18 .3 20 .8 8. 3 e le ct ri ci ty p ow er c os t ( jd /k w h) 0. 08 6 jd /k w h (l ay . 1 ).& 0 .0 72 j d /k w h (l ay . 2 )/ re si de nt ia l s ec to r 0. 07 2 0. 08 0. 08 6 0. 08 6 to ta l c os t w ith e le ct ri ci ty (j d /k w h) 51 .2 *0 .0 86 =4 .4 3. 5 4. 40 -3 .5 0= 0. 90 2. 3 3. 52. 3= 1. 2 0. 72 2. 30. 7= 1. 6 pa yb ac k pe ri od w he n el ec tr ic ity is m ai n so ur ce (y ea r) 13 .2 9. 2 7. 5 ali, et al.: evaluation of near-net-zero-energy building strategies: a case study on residential buildings in jordan international journal of energy economics and policy | vol 10 • issue 6 • 2020 335 • total cost of electricity power (strategy 2) total cost of electricity power (strategy 1). 5. conclusions the aim of these passive and active strategies is to reduce building energy demands along the life cycle of buildings. in this study improving the energy efficiency of residential building sectors in jordan, irbid has been analyzed through analytical and computational methods to identify the energy performance of buildings. three strategies building energy analysis is utilized to achieve near net zero energy building (nnzeb) in irbid, jordan through economic and computational of various integrated passive and active design systems for the jordanian residential building sector. set of parameters have been considered in order to achieve maximum efficiency of nnzeb: layout, orientation, and window to wall ratio (wwr). the simulation results showed an estimate of annual electrical energy consumption as 3670.09 kwh and district heating consumption as 2472.236 kwh, composed of 1333.212 and 1139.024 kwh of heating requirements and water system respectively. total energy end use of the existing single house building (strategy 1) is 6142.327 kwh (51.186 kwh/m2). for (strategy 1/phase 2) the energy saving compared to existing residential building is 20.44% with total energy consumption at 40.724 kwh/m2. also, for strategy two the annual energy consumption reduced to 3820.181 kwh (31.835 kwh/m2) that achieved 37.81% total energy savings. photovoltaic system was proposed to generate the electricity needed by the building. it was found that the pv system generates 2415.79 kwh/year. flat-plate collectors type “hc100” is generally used for open-loop solar water heating systems. total number of collectors needed to meet the annual water heating demand (1139.024 kw) is four collectors. the payback period estimated for the new efficient single house wall system (strategy 3) is 8.3 years when gas is the main source and 7.5 years when electricity is the main source finally the total saving in energy for the whole single house is found to be 82.41%, which approaches a near zero energy building. green building practices aim to reduce energy consumption and the environmental impact of buildings. in this work, a building in irbid is redesigned moving towards low energy building, and based on the result obtained from this study it can be concluded that applying passive strategies to buildings is efficient. applying thermal insulation (polystyrene) and double glazing windows (aluminum frames) reduce the energy required by the building. after applying thermal insulation according to jordanian building code on existing house building, it can be achieved 18.2% total energy saving. the optimum passive design strategy can be applied on jordanian residential building when taken jordanian building code into consideration: square layout, entrance of building oriented to south and wwr is 15%. this strategy can save about 20.44% from energy. on other hand the worst passive design strategy which the maximum energy saving cannot exceed 6% can be applied on jordanian residential buildings when u-shape layout, entrance of building oriented to east and wwr is 30% used. total energy saving can be obtained after applied all energy efficient active and passive strategies on conventional building is 37.8%. natural convection air-cooled condenser integrated to stack technology reduce the district cooling load required by the house building to achieve 6.2% and 4.1% energy saving in cooling load and total building code respectively. the total cost is 5329 jd with payback period 9.5 years. using of photovoltaic system help to generate the electricity for the building during the year and for this case photovoltaic system generate 2415.8 kwh/yr. that happen by investment cost equal to 4274 jd with payback period 8.3 years. flat-plate collectors type “hc100” is generally used for open-loop solar water heating systems, the technical specification of flat-plate collectors type “hc100” from hanania company which is used in this study. total number of collectors needed to meet the annual water heating demand (1139.0 kwh) is four collectors. annual actual useful gain of heat is 324.2 kwh which achieved 71.5% saving of the annual water heating demand. investment cost equal to 875 jd with payback period 6.7 years. the payback period estimated for the new efficient single house wall system when renewable energy systems installed is 8.3 years when gas is the main source and 7.5 years when electricity is the main source. the total saving in energy in the whole single house was found to be 82.4% which is considered as a near zero energy building. 6. recommendations in light of the results and conclusions obtained through this study, some recommendations can be proposed. it is recommended to use renewable energy system as single system to generate the energy required by the building. energy conservation methods (thermal insulation, double glazing windows, wwr, shading, and pv system) are recommended to be applied in jordan. it is strongly recommended to use building monitoring system to manage the energy using inside the building. finally it is strongly recommended to rewrite and redesign jordanian building code to cover the new technology. it’s expected that this study can be used as a base or guideline for energy researchers, architects, policymakers to understand the current situation for residential buildings and to establish future directions toward nnzeb. references alaidroos, a., krarti, m. (2015), optimal design of residential building envelope systems in the kingdom of saudi arabia. energy and buildings, 86, 104-117. aldawi, f., date, a., alam, f., khan, i., alghamdi, m. (2013), energy efficient residential house wall system. applied thermal engineering, 58(1-2), 400-410. al-salaymeh, a., al-hamamre, z., sharaf, f., abdelkader, m.r. (2010), technical and economical assessment of the utilization of photovoltaic systems in residential buildings: the case of jordan. energy conversion and management, 51(8), 1719-1726. alzyood, m., harahsheh, h., hammad, m. (2010), thermal economical analysis of renewable energy buildings, towards low energy house in jordan. tunisia: international renewable energy congress. asadi, s., hassan, m., beheshti, a. (2012), development and validation of a simple estimating tool to predict heating and cooling energy demand for attics of residential buildings. energy and buildings, 54, 12-21. attia, s. (2012), a tool for design decision making: zero energy ali, et al.: evaluation of near-net-zero-energy building strategies: a case study on residential buildings in jordan international journal of energy economics and policy | vol 10 • issue 6 • 2020336 residential buildings in hot humid climates. belgium: presses universitaires de louvain. attia, s., al-khuraissat, m. (2016), life cycle costing for a near zero energy building in jordan: initial study. the 5th architectural jordanian international conference. attia, s., zawaydeh, s. (2014), strategic decision making for zero energy buildings in jordan. available from: http://www.essaymania.com. [last accessed on 2015 jan 09]. available from: http://www.jordinvest.com.jo. [last accessed on 2015 mar 19]. d’agostino, d., mazzarella, l. (2019), what is a nearly zero energy building? overview, implementation and comparison of definitions. journal of building engineering, 21, 200-212. department of the environment, community and local government. (2012), towards nearly zero energy buildings in ireland, planning for 2020 and beyond. hammad, m., ebaid, m.s.y., al-hyari, l. (2014), green building design solution for a kindergarten in amman. energy and buildings, 76, 524-537. kaynakli, o. (2012), a review of the economical and optimum thermal insulation thickness for building applications. renewable and sustainable energy reviews, 16(1), 415-425. kiwan, s., kandah, m., kandah, g. (2020), zero energy building in jordan. 1st international conference on mechanical, aeronautical, and industrial engineering technologies (mechanitek 2020), 1(1), 49-60. marszal, a.j., heiselberg, p., bourrelle, j.s., musall, e., voss, k., sartori, i., napolitano, a. (2011), zero energy building-a review of definitions and calculation methodologies. energy and buildings, 43(4), 971-979. ministry of public works and housing. (2013), housing and urban development jordanian housing sector, accomplishments and performance evaluation for the period 2005-2013. ozel, m. (2013), determination of optimum insulation thickness based on cooling transmission load for building walls in a hot climate. energy conversion and management, 66, 106-114. panão, m.j.n., rebelo, m.p., camelo, s.m.l. (2013), how low should be the energy required by a nearly zero-energy building? the load/ generation energy balance of mediterranean housing. energy and buildings, 61, 161-171. rezaie, b., dincer, i., esmailzadeh, e. (2013), energy options for residential buildings assessment. energy conversion and management, 65, 637-646. the ministry of energy and mineral resources. (2017), energy consumption in the domestic sector 2017. torcellini, p., pless, s., deru, m., crawley, d. (2006), zero energy buildings: a critical look at the definition. united states: national renewable energy laboratory, golden, co. venturi, r., robert, i.v., brown, d.s., izenour, s., steven, r.v.d. (1977), learning from las vegas: the forgotten symbolism of architectural form. cambridge: mit press. wittchen, k.b., jensen, s.ø., kamper, s., kvist, l. (2010), bolig+an energy neutral multifamily building. toronto: proceedings of euro sun. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 4 • 2021 121 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(4), 121-126. volatility spillovers between oil prices and stock returns in developing countries khairulla massadikov* department of public administration and regional development, khoja akhmet yassawi international kazakh-turkish university, turkestan/kazakhstan. *email: k.massadikov@ayu.edu.kz received: 25 january 2021 accepted: 22 april 2021 doi: https://doi.org/10.32479/ijeep.11117 abstract risk and uncertainty have always been an important issue for investors, researchers and policymakers. thus, the explanation of the mechanism of spreading volatility between different markets has been the focus of attention by researchers. determining the return and volatility interaction between oil prices and stock markets will be useful not only for pricing and hedging financial assets, but also for detecting and interpreting the reflection of the problems arising in the oil industry on the country’s economies. in this study, the var-garch model introduced by ling and mcaleer (2003) was used to determine the interaction between oil prices and stock markets in terms of return and volatility for developing countries (brics-t). the reason for choosing this model is to reveal whether the shocks and volatility in these markets have a transitional effect. keywords: oil price, stock return, volatility spillovers, var-garch model jel classifications: g11, g15, q4 1. introduction the oil markets in the world are known as the deepest markets in terms of the volume of transactions realized in terms of their positions. on the other hand, oil is the input material of most enterprises and factories. therefore, any fluctuation in the oil markets affects the prices of the products produced and reflects on the stock markets. this means that there is a close relationship between capital markets and oil markets. the share of oil in the total energy consumption in the world constitutes an undeniably large proportion. as of 2018 and 2019, 33.2% and 33.05% of the total amount of energy consumed worldwide were met from petroleum resources, respectively (bp, 2020). in fact, the fact that approximately one third of the amount of energy consumed is met from petroleum resources is an indicator that industry, production and other sectors are largely dependent on oil. therefore, the fluctuations in the prices of oil, which has an important role as the main input of most production sectors, due to various reasons will affect the rates of return of the relevant sectors and affect the market values. when viewed rationally, the reduction of gdp by oil shocks will cause economies to shrink and as a natural result of this, the economic balances will be broken by triggering the inflation rate. therefore, changing macroeconomic variables will indirectly affect capital markets and stock markets throughout the country. studies investigating the relationship between oil price movements and macroeconomic variables are more frequently encountered in the literature. in studies investigating the relationship between oil prices and stock markets, it has been found that there is generally a positive relationship between oil markets and stock markets (sadorsky, 1999; sadorsky, 2001; el-sharif et al., 2005; lescaroux and mignon, 2008; bjornland, 2009; mendoza and vera, 2010; wang et al., 2013; hanif, 2020). in some other studies, the existence of a negative relationship between oil markets and stock markets has been advocated (filis, 2010; filis et al., 2011; cunado and gracia perez, 2014). in recent years, studies arguing this journal is licensed under a creative commons attribution 4.0 international license massadikov: volatility spillovers between oil prices and stock returns in developing countries international journal of energy economics and policy | vol 11 • issue 4 • 2021122 that oil prices affect stock prices asymmetrically have increased (tsai, 2015; narayan and gupta, 2015; syzdykova, 2018; mokni, 2020; chang, 2020; chang et al., 2020). when looking at the shocks and crises experienced in the oil market in recent years, it is seen that it has reached regional even global dimensions due to the contamination effect. the spreading mechanism of this effect, also known as the domino effect, has been a matter of curiosity. this has led to the investigation of issues such as the causes of volatility, its effect and the mechanism of spreading. in this study, the interaction between oil markets and stock markets is analyzed with the help of the var-garch model introduced by ling and mcaleer (2003). the reason for choosing this model is to reveal whether the shocks and volatility in these markets have a transitional effect. for this purpose, the relationship between the stock markets of developing countries and oil markets has been investigated. 2. literature review studies examining the relationship between oil price and stock markets on the basis of country or country groups differ from each other in terms of their results. in the literature, concepts such as interaction, transmission, propagation, and pass-through are used to express the relationship between cross markets. malik and hammoudeh (2007) reported the existence of volatility and shock interaction between the oil market (wti) and the stock market of the usa and three different gulf countries (bahrain, kuwait and saudi arabia) with data for the period between february 14, 1994 and december 25, 2001. they researched it with the garch model. the authors found evidence that there is a significant relationship between the oil market and the second moment of the us stock market, and that there is a volatility interaction from the oil market to the stock market in bahrain, kuwait and saudi arabia in all circumstances. in addition, the researchers, stating that there is volatility interaction from the saudi arabian stock market to the oil market, state that the news and shocks in the us stock market affect the stock market volatility of the gulf countries. driesprong et al. (2008), using daily data for the period between october 1973 and april 2003, examined the interaction between the stock market returns of developed and developing countries and oil prices with the garch model. the researchers stated that if oil prices increase compared to the previous month, stock market returns tend to decrease, and if oil prices decrease, stock market returns tend to increase, because investors react to information about the oil price. howewer they found that an increase in oil prices would greatly reduce stock market returns in the upcoming period. the findings obtained show that oil prices allow us to make predictions for stock market returns, and this prediction is more meaningful and powerful for developed country stock markets. constantinos et al. (2010) investigated the yield interaction between the greek stock market and oil prices with the var model and the volatility interaction with the egarch model. the authors identified a positive and statistically significant causal effect from oil price returns and oil price volatility to stock market returns. also, it is determined that there is a bidirectional causality relationship between stock market returns and stock market volatility. chang et al. (2013), using ccc-garch, dcc-garch, varma-garch and varma-agarch models, investigated the conditional correlation and volatility interaction between spot, futures and forward oil returns and ftse 100, nyse, dow jones and s&p 500 index returns. the researchers, based on the daily data of january 1998 november 2009, found that the conditional correlation estimated for returns between markets according to the ccc model is low and not statistically significant, and the conditional correlation estimated in the dcc model is significant. although the varma-garch and varma-agarch models provide less information about the volatility interaction between markets; the asymmetric effect of equally sized positive and negative shocks on conditional variance shows that the varmaagarch model is a more effective model. hamma et al. (2014) examined the relationship between oil prices (wti and brent) and the tunisian stock exchange (tunindex) industry indices and the volatility interaction with multivariate garch models (bekk, vec, ccc-garch). they aimed to determine the rate of protection and the best prevention strategy. as a result of the analysis, they determined that there is a oneway relationship from the petroleum market to the tunisian stock exchange, that the sector’s stock returns are affected by the stock market volatility and the oil markets, and the bekk-garch method is the most effective method to minimize the risk of the portfolio of oil and stocks. gomes and chaibi (2014) examined the shock and volatility interaction between 21 frontier markets and oil prices using the bivariate bekk-garch(1,1) model. the authors used weekly returns from february 8, 2008 to february 1, 2013, as a result they found a significant shock and volatility spread between oil prices and some markets. moreover, this spillover effect is bi-directional for some markets. khalfaoui et al. (2015) investigated the volatility interaction between oil prices and the stock markets of g-7 countries (usa, germany, france, england, italy, japan and canada) with daily data for the period between 2 june 2003 and 7 february 2012. the authors have obtained strong evidence that volatility changes over time for markets examined with the bekk-garch model. they determined that oil prices and stock market prices were directly affected by their own news and volatility, and indirectly by other market price volatility. ewing and malik (2016) studied the volatility interaction between oil prices and us stock market prices using univariate and bivariate garch models, including structural breaks, in their study based on daily data for the period between 1 july 1996 and 30 june 2013. according to the research findings; when the structural breaks in the variance in the model are ignored, the researchers stated that there is no volatility interaction between oil prices and the us stock market, and after the structural breaks were calculated massadikov: volatility spillovers between oil prices and stock returns in developing countries international journal of energy economics and policy | vol 11 • issue 4 • 2021 123 in the model, they found a strong volatility interaction between the two markets. yu et al. (2020) investigated the volatility interaction between the crude oil market (wti) and the us and chinese stock markets with data for the 1991-2016 period. in the study in which varbekk-garch method was used; it has been determined that the oil market triggered rapid and continuous fluctuations in market dependencies, which emerged most sharply after the 2008 financial crisis and showed the increasing interdependence between oil and stock markets. sarwar et al. (2020) analyzed the volatility spread between oil prices and the stock exchanges of karachi, shanghai and bombay using the bivariate bekk-garch model with data for the period 1997-2014. the study looks at the role of spreading volatility in different economic scenarios by dividing it into pre and post-crisis periods. according to the results of the study, there is no significant difference between the spread between oil prices and stock markets, and the spread before and after the crisis. on the other hand, the estimated results vary according to the data frequencies used (daily, weekly and monthly). 3. data set and methodology 3.1. data different indices are used for oil prices at the international level. in this study, european brent spot prices are used for crude oil prices per barrel. representing the developing countries in the study; brazil (ibovespa), russia (micex), india (sensex), china (shanghai), south africa (jalsh) and turkey (bist 100) have been selected exchanges. the data of the stock market indices of the countries were obtained from the bloomberg database and the oil price data from the us energy information agency. between january 2010 and december 2019, logarithmic return series were created based on monthly data and analyzes were carried out using eviews and stata package programs. 3.2. method: bivariate var (1) garch (1,1) model the model introduced by ling and mcaleer (2003) has some important advantages over traditional multivariate garch models. in the implementation of this model, there is less complexity in calculation and estimation compared to other volatility pass-through models. it also follows a very flexible process in explaining the mutual conditional effects and volatility pass-through between different series. in particular, the var (1) mgarch (1.1) model has recently confirmed its power in revealing the mutual volatility pass-through between different markets. based on the var (1) mgarch (1,1) model regarding the basic stock market index returns of developing countries included in the study and oil price returns, the conditional average equation has the following properties for each series: 1 1/2 t t t t t t r r h µ φ ε ε η −= + +  = (1) where, r r rt t stock t oil= ( , )' , �rt stock ve rt oil denote stock and oil price index return vectors, respectively. in the conditional mean equation, ϕ representing the coefficients consists of a 2x2 dimensional diagonal matrix � � � � � � � � � � 1 2 0 0 . � � �t t stock t oil� ( , )' , �εt stock and εt oil shows the error terms vector obtained from the conditional average equations of sub-stock market index returns and oil price index returns, respectively. � � �t t stock t oil� ( , )' denotes the random errors vector showing an independent and homogeneous distribution (i, i, d). h h h h h t t stock t stock oil t stock oil t oil � � � � � � � � � � � forms the conditional variance matrix of stock and oil returns. based on the above definitions, rt stock and rt oil equations are as follows: r r rt stock t oil stock oil t st� � � � � � � � � � � � � � � � � � � � � � � � �� � � � 1 2 10 0 oock t oil t stock t oil t stock t oil r r r � � � � � � � � � � � � � � � � � � � � � � � � 1 � � �� � � � � � � � � � � � � � � � � � � � �� � � � � � �stock oil t stock t oil t stocr r 1 1 2 1 kk t oil� � � � � � � � � (2) from the simplification of the above matrices, the conditional average equations of stock and oil price returns are obtained as follows: r r r r t stock stock t stock t stock t oil oil t oil t o � � � � � � � � � � � � � � 1 1 2 1 iil � � � �� (3) also, when coefficient matrices for variance equations are defined as: 2 2 1 2 2 2 2 1 2 2 1 2 2 2 2 1 stock stock t stock stock t oil oil t oil oil t stock stock oil oil r r a and b r r α α α α β β β β       = =                     (4) ht stock , �ht oil and ht stock oil− equations can be obtained as follows: ( ) ( ) 2 2 2 2 11 2 2 2 2 2 2 1 1 2 2 1 2 1 2 2 2 1 1 2 2 stockstock tt stock stock stock oil oilt oil oil oil t stock stock stock t oil oil oil t stock t stock oil t oil h c h c h h h c h c εα α α α ε β β β β − − − −          = +                        +          =     ( ) ( ) ( ) ( ) 2 22 2 1 1 2 1 2 22 2 2 1 1 1 2 2 1 1 2 1 2 2 2 1 1 1 stock oil stock t stock t stock oil oil t oil t stock oil stock t stock t stock oil oil t oil t h h h h α ε α ε α ε α ε β β β β − − − − − − − −  +    +         +    + +  +   (5) massadikov: volatility spillovers between oil prices and stock returns in developing countries international journal of energy economics and policy | vol 11 • issue 4 • 2021124 from the simplification of the above matrices, the conditional equations of variance of stock sectors and oil price returns are obtained as follows: ( ) ( )2 22 2 21 1 2 1 2 2 1 1 2 1 stock stock oil t stock stock t stock t stock oil stock t oil t h c h h α ε α ε β β − − − − = + × + × + × + × (6) ( ) ( )2 22 2 21 1 2 1 2 2 2 1 1 1 oil oil stock t oil oil t oil t stock oil oil t oil t h c h h α ε α ε β β − − − − = + × + × + × + × (7) as can be seen in (6) and (7), the quadratic inclusion of all coefficients in the variance equations provides the positivity of the equations. it is assumed here that negative and positive shocks of equal magnitude have the same effects on conditional variances. depending on the time, volatilities in stock and oil markets for period t are directly affected by the delays of their shocks � �t stock t stock � �� � � �� �� � �� 1 2 1 2 , and indirectly by the lagged shocks of each other. in addition, the volatilities in the said markets are affected by both their own volatility ( ht stock −1 ve ht oil −1 ) and reciprocal lagged volatility. therefore, this model has a more advantageous position in analyzing possible volatilities in terms of dynamic shocks and volatilities in the market. in order to guarantee stationarity in var (1) bivariate garch (1,1) model, the roots of the i al bl2 0� � � equation must remain outside the unit circle. here l is the polynomial delay value and i2 is the 2 × 2 dimensional unit matrix. in this model, ρ is taken as the constant conditional correlation independent of time. therefore, taking into account ρ, it is possible to explain the conditional common variance between these bilateral markets as follows: h h ht stock oil t stock t oil� � � �� (8) although the constant conditional correlation assumption is seen as a restrictive assumption under changing economic conditions, the statistical properties for the dynamic conditional correlation for the var-mgarch model have not yet been analyzed theoretically. however, it has been emphasized in previous studies that this model is a possible model in terms of providing the permanence of long-term fluctuations and the transmission of volatility and shock between oil and stock markets included in the study. the parameters of the bivariate var (1) -garch model used as the basic model are estimated by the quasi-maximum likelihood method. the quasi-maximum likelihood method is a robust method against all kinds of deviation and convergence problems in normality conditions (ling and mcaleer, 2003). 4. results in this study, which investigates the shock and volatility spread between oil markets and stock markets in developing countries, first some basic statistics are included. first of all, descriptive statistics and correlation table of the variables were presented and then the stationarity of the variables was examined with the unit root test. from the descriptive statistics in table 1, it is seen that the average return of brent oil is higher than all other developing countries except brazil. however, it also appears to be even more risky. for this reason, those who will invest in this market should closely monitor the variables that affect oil prices, the policies followed and the existence of the markets it is affected by. in addition, whether the riskiness in oil markets spreads to stock markets or not is important for stock investors. looking at the correlation relationship in table 2; compared to other countries, it is seen that a high correlation between the india-brazil-turkey and turkey. in addition, it is seen that the country with high correlation with the oil price is russia, followed by brazil. after basic statistics, we will look at the stationarity of variables. it is important that the variables are stationary in order to avoid spurious regression in the models table 1: descriptive statistics brent brazil russia india china south africa turkey mean −0.045130 −0.162836 −0.089348 0.147743 −0.050594 0.087180 −0.163553 median 0.473759 −0.114509 −0.205055 0.269789 −0.024328 −0.077921 0.000000 maximum 8.511181 11.50221 8.289696 7.643441 7.667250 6.001519 7.311989 minimum −11.57025 −10.27799 −10.82758 −7.128142 −11.72918 −7.919362 −7.489669 sd 3.457602 3.745150 3.189083 2.680377 2.922102 2.566163 3.505569 skewness −0.797760 −0.040906 −0.345481 −0.091206 −0.480121 −0.188313 −0.176999 kurtosis 4.464080 3.677143 4.338015 3.222459 5.410388 3.054474 2.447288 table 2: correlation matrix brent brazil russia india china south africa turkey brent 1 0.3198 0.4674 0.1534 0.1918 0.1160 0.1116 brazil 0.3198 1 0.6148 0.5512 0.3377 0.4473 0.4773 russia 0.4674 0.6148 1 0.4174 0.2566 0.4039 0.3911 india 0.1534 0.5512 0.4174 1 0.2131 0.3989 0.4935 china 0.1918 0.3377 0.2566 0.2131 1 0.0751 0.2577 south africa 0.1160 0.4473 0.4039 0.3989 0.0751 1 0.4172 turkey 0.1116 0.4773 0.3911 0.4935 0.2577 0.4172 1 massadikov: volatility spillovers between oil prices and stock returns in developing countries international journal of energy economics and policy | vol 11 • issue 4 • 2021 125 table 4: var (1) garch (1,1) estimation results brazil russia india china south africa turkey oil stock oil stock oil stock oil stock oil stock oil stock conditional mean equation constant 0.1329* −0.1287 0.0719 0.1870* 0.2009 −0.0531 0.1034* 0.0310 0.1309* 0.0305 0.1397* 0.2401 oil (1) 0.0290 0.1520* 0.0345 0.0230 0.3029* −0.2034* −0.0021 −0.2043* 0.1506* 0.1303* 0.0213* −0.1423* stock (1) 0.0530 0.1540* 0.0512 0.0408 0.0912 0.2620* −0.0231 0.0523 0.0941 0.2175* 0.0031 0.1321* conditional variance equation constant 0.2095* 0.3213* 0.3003* 0.1601* 2.1390 2.1094 0.0902* 0.0029 0.0690* 0.0421* 0.0312* 0.0897** ( )t stock −1 2 0.0021 0.4023* 0.0456 0.3045* −0.2032 0.4560* 0.0901* 0.1306* 0.0612 0.1590 0.0201 0.1009* ( )t oil −1 2 0.3098* −0.0071 0.3349** −0.1025 0.0233 −0.0677 0.0204* 0.0713* 0.0897** 0.0926* 0.1020* −0.0876* �t stock �1 ) 0.1087 0.5023* 0.0032 0.6710* −0.2787 0.4054 −0.7307 0.6087* 0.6012 0.7634* 0.1200 0.7891** ( )�t oil �1 0.6256* 0.2304** 0.6341* −0.0765 0.9680 0.0987 0.9267* 1.1230 0.8529* −0.0207 0.8321* 0.2709* jb 72.90* 83.05* 45.09* 125.02 52.90* 150.50* 80.34* 90.80* 40.30* 90.24* 60.50* 95.07* lb-q (10) 6.5 12.04 10.93 15.05 12.50 8.01 7.8 6.40 20.33* 16.19 6.90 10.02 lbq2 (10) 7.01 13.90 9.91 11.08 8.05 5.90 8.03 18.07 14.84 10.91 7.90 12.76 log likelihood −5090.401 −5502.03 −5003.40 −3605.56 −4802.76 −5809.36 akaike 7.9030 8.9035 8.0105 -8.0701 -8.2071 7.9020 ccc 0.1505* 0.0780* 0.0906* 0.1590 0.1302 0.1401** ccc: constant conditional correlation coefficient, lb: ljung-box, jb: jarque-bera, (*,**) indicates the rejection of the zero hypothesis at 1%, 5% significance level, respectively table 3: unit root test results adf unit root test pp unit root test intercept trend and intercept intercept trend and intercept brent −8.453586* −8.420041* −8.251997* −8.211873* brazil −11.05401* −11.05208* −11.06099* −11.06110* russia −10.38852* −10.34535* −10.62113* −10.57288* india −10.28590* −10.27440* −12.30450* −12.27718* china −9.162510* −9.116206* −9.071232* −9.022504* south africa −13.94756* −13.91233* −14.15977* −14.12797* turkey −9.677585* −9.657140* −9.717914* −9.681629* test critical values 1% level −3.486551 −4.037668 −3.486551 −4.037668 5% level −2.886074 −3.448348 −2.886074 −3.448348 10% level −2.579931 −3.149326 −2.579931 −3.149326 *is statistically significant at 99% confidence level used in the study. misleading results are obtained when experimental analysis is performed between non-stationary series (syzdykova et al., 2021). for this reason, augmented dickeyfuller (adf) and phillips-perron (pp) tests were applied to test stationarity in the study. in table 3, it is seen from the adf and pp unit root test results that all return series are stable at level value and 99% reliability level. the results of the var (1) garch (1,1) model that will measure the impact of shock and volatility spillover between oil markets and stock markets after stabilization are presented in table 4. table 4 shows the results of var (1) -garch (1,1) estimates made for developing countries. looking at the average equation results, it is seen that the lagged value of oil returns has an effect on the stock market indices of all countries except russia. this effect brazil and south africa while creating a positive impact on stock index returns, india, china and turkey constitute a negative impact on stock market index returns. that increase in the return of oil to china, turkey and india while decreasing returns in the stock market, causing an increase in yields in brazil and south africa markets. the obvious conclusion from this is that the increase in oil returns in oil-importing developing countries has a negative effect. in turkey, south africa, brazil and india, equity returns are affected by both self-and oil returns. the impact of oil returns in turkey and india is seen to be greater than the impact of stock returns. the impact of stock returns in south africa is greater than the impact of oil returns. in china, however, it seems that only oil returns have an effect on stock returns. in the conditional variance equation, when the persistence degree of short term shocks is examined, it is seen that the permanence degree of short term oil shocks in russia (0.3349) and the degree of permanence of stock shocks (0.3045) is higher. stock shocks are more effective in all other countries. while the persistence of short-term oil shocks is low in south africa and china, this effect is stronger in other countries. according to the shock and volatility pass-through results, the shock pass-through from the stock market to the oil markets was determined only in china. a shock that will occur in the stock markets of other countries has no significant effect on the oil markets. south of shocks in the oil market in africa, china, and russia were identified significant effect on turkey. oil markets, volatility when the stock market right pass-through only examined were found to be a positive influence in turkey and brazil. in the conditional variance equation, it is seen that the arch and garch coefficients are significant in all countries except india. in these countries, it is observed that the previous period shock and volatility had a strong impact on both the stock and oil markets in the current period. past shocks are changing the volatility of developing countries more rapidly. looking at the garch coefficients, it is seen that the volatility in the past period has a strong effect on the current period in all countries except india. it is seen that the fixed conditional correlation coefficients are significant in all countries. this indicates the relationship between oil markets and stock markets. however, the coefficients obtained are generally small values. massadikov: volatility spillovers between oil prices and stock returns in developing countries international journal of energy economics and policy | vol 11 • issue 4 • 2021126 5. conclusion according to the findings of the study, the significant effect of oil markets on the stock markets of countries except russia was determined. it has been found to have a positive effect for brazil and south africa and a negative effect for other countries. the negative impact in these countries is an indicator of the countries’ dependence on oil. although there is no significant relationship in the russian market, it is thought that the spillover effect of oil shocks in the russian market may also affect this market indirectly, though not directly. it is seen that oil shocks have a significant effect on the stock markets of other countries except india and brazil. looking at the volatility spread, no spread from stock markets to oil could be detected. turkey and brazil on the other hand the stock market has seen the oil market is right to spread. when the fixed conditional correlation coefficients are examined, it is seen that it is significant in all countries. since the coefficients are not very large, it can be said that they are not the most important determinant of the stock markets, but one of the important factors. addressing the volatility phenomenon against oil prices on the basis of sectors will provide important advantages in presenting different perspectives. such studies will provide opportunities for investors to create more effective portfolios, as they will provide an opportunity for effective diversification at the international level. in other words, in this case, the sub-sectors will present a more transparent perspective for researchers and investors by demonstrating their direct reactions to oil shocks according to their structural characteristics. this will provide additional information on building effective portfolios. references bjørnland, h.c. (2009), oil price shocks and stock market booms in an oil exporting country. scottish journal of political economy, 56(2), 232-254. chang, b.h. (2020), oil prices and e7 stock prices: an asymmetric evidence using multiple threshold nonlinear ardl model. environmental science and pollution research, 27(35), 4418344194. chang, b.h., sharif, a., aman, a., suki, n.m., salman, a., khan, s.a.r. (2020), the asymmetric effects of oil price on sectoral islamic stocks: new evidence from quantile-on-quantile regression approach. resources policy, 65, 101571. chang, c.l., mcaleer, m., tansuchat, r. (2013), conditional correlations and volatility spillovers between crude oil and stock index returns. north american journal of economics and finance, 25, 116-138. constantinos, k., ektor, l.a., dimitrios, m. (2010), oil price and stock market linkages in a small and oil dependent economy: the case of greece. journal of applied business research, 26(4), 55-64. cunado, j., de gracia, f.p. (2014), oil price shocks and stock market returns: evidence for some european countries. energy economics, 42, 365-377. driesprong, g., jacobsen, b., maat, b. (2008), striking oil: another puzzle? journal of financial economics, 89(2), 307-327. el-sharif, i., brown, d., burton, b., nixon, b., russell, a. (2005), evidence on the nature and extent of the relationship between oil prices and equity values in the uk. energy economics, 27(6), 819-830. ewing, b.t., malik, f. (2016), volatility spillovers between oil prices and the stock market under structural breaks. global finance journal, 29, 12-23. filis, g. (2010), macro economy, stock market and oil prices: do meaningful relationships exist among their cyclical fluctuations? energy economics, 32(4), 877-886. filis, g., degiannakis, s. and floros, c. (2011), dynamic correlation between stock market and oil prices: the case of oil-importing and oil-exporting countries. international review of financial analysis, 20(3), 152-164. gomes, m., chaibi, a. (2014), volatility spillovers between oil prices and stock returns: a focus on frontier markets. journal of applied business research, 30, 509-526. hamma, w., jarboui, a., ghorbel, a. (2014), effect of oil price volatility on tunisian stock market at sector-level and effectiveness of hedging strategy. procedia economics and finance, 13, 109-127. hanif, m. (2020), relationship between oil and stock markets: evidence from pakistan stock exchange. international journal of energy economics and policy, 10(5), 150. khalfaoui, r., boutahar, m., boubaker, h. (2015), analyzing volatility spillovers and hedging between oil and stock markets: evidence from wavelet analysis. energy economics, 49, 540-549. lescaroux, f., mignon, v. (2008), on the influence of oil prices on economic activity and other macroeconomic and financial variables. opec energy review, 32(4), 343-380. ling, s., mcaleer, m. (2003), asymptotic theory for a vector armagarch model. econometric theory, 19, 280-310. malik, f., hammoudeh, s. (2007), shock and volatility transmission in the oil, us and gulf equity markets. international review of economics and finance, 16(3), 357-368. mendoza, o., vera, d. (2010), the asymmetric effects of oil shocks on an oil-exporting economy. cuadernos de economía, 47(135), 3-13. mokni, k. (2020), a dynamic quantile regression model for the relationship between oil price and stock markets in oil-importing and oil-exporting countries. energy, 213, 118639. sadorsky, p. (1999), oil price shocks and stock market activity. energy economics, 21(5), 449-469. sadorsky, p. (2001), risk factors in stock returns of canadian oil and gas companies. energy economics, 23(1), 17-28. sarwar, s., tiwari, a.k., tingqiu, c. (2020), analyzing volatility spillovers between oil market and asian stock markets. resources policy, 66, 101608. syzdykova, a. (2018), the relationship between the oil price shocks and the stock markets: the example of commonwealth of independent states countries. international journal of energy economics and policy, 8(6), 161-166. syzdykova, a., abubakirova, a., erdal, f.b., saparova, a., zhetibayev, z. (2021), analysis of the relationship between renewable energy and economic growth in selected developing countries. international journal of energy economics and policy, 11(1), 110-116. wang, y., wu, c., yang, l. (2013), oil price shocks and stock market activities: evidence from oil-importing and oil-exporting countries. journal of comparative economics, 41(4), 1220-1239. yu, l., zha, r., stafylas, d., he, k., liu, j. (2020), dependences and volatility spillovers between the oil and stock markets: new evidence from the copula and var-bekk-garch models. international review of financial analysis, 68, 101280. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 1 • 2021584 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(1), 584-590. impact of custom duties, energy import and government health spending on greenhouse gas emission in thailand thammarak srimarut1*, witthaya mekhum2 1suan sunandha rajabhat university, bangkok, thailand, 2suan sunandha rajabhat university, bangkok, thailand. *email: thammarak.sr@ssru.ac.th received: 25 july 2020 accepted: 15 november 2020 doi: https://doi.org/10.32479/ijeep.10722 abstract greenhouse gas emission has become a great problem throughout the world and many countries are facing serious outcomes in this regard. there may be various factors that may affect the emission of greenhouse gases but in this study the author has discussed the impact of custom duty, energy imports and government health spending on greenhouse gas emission. data was collected from thailand for research purpose for period of 28 years. several tests such as unit root test, co-integration test and ardl test in long and short run have been applied on the collected data for various purposes. the results of these tests indicate that the impact of three independent variables, custom duty, energy imports and government health spending is significant while the impact of only one control variable, energy consumption is significant in regard of greenhouse gas emission. after the detailed discussion of results, the author has mentioned some important implications related to this study in various contexts. these implications revolve around one common point i.e. reduction in greenhouse gas emission. in the last, the limitations associated with the study have also been discussed. keywords: custom duties, energy import, government health spending, greenhouse gas emission jel classifications: h51, k32 1. introduction rising global population has exerted pressure on the demand of nonrenewable energy consumption, which consequently has caused the higher emission of greenhouse gases (dogan and seker, 2016; jebli and youssef, 2015). various sectors such as transport, household, industry, power are contributing in the greenhouse gas emission in southeast asian economies. furthermore, many studies have also emphasized that besides the agriculture, industrial, and transport industry, the rubber production is also contributing in global warming and greenhouse gas emission in thailand (chanchaichujit et al., 2017). in order to control environmental degrading due to rising greenhouse gas emission, alternative energy resource may employed. sharma et al. (2016) mentioned in their study that greenhouse emission may control by adopting the alternative nonrenewable energy resources. further, government efforts to bring structure reforms in the energy sectors to control the rising greenhouse emission will have positive results (covert et al., 2016; mohr et al., 2015). this study aims to explore the impact of government policies and role in controlling greenhouse emission. rising greenhouse emission in thailand is also mainly attributed to the country high reliance on the nonrenewable energy resources. the purpose of this study is to empirically measure the role of custom duties (on nonrenewable energy resource), energy import and government health spending on greenhouse gas emission. according to literature, tariff policies of government may positively contribute in controlling the environmental degradation and greenhouse gas emission through levying custom duties on environment unfriendly imports (cottier et al., 2014). contrastingly, lowering custom duties and tariffs on environmentally friendly machines, goods, or products will encourage the diffusion of cleaner technologies. in addition, energy import in the form of crude oil and natural gas import, has also a striking impact on the diffusion of greenhouse emission in this journal is licensed under a creative commons attribution 4.0 international license srimarut and mekhum: impact of custom duties, energy import and government health spending on greenhouse gas emission in thailand international journal of energy economics and policy | vol 11 • issue 1 • 2021 585 thailand. in order to control the prevalent environmental threats, government spending on alternative environmental-friendly energy technology will check the emission of greenhouse gases (figure 1). the increasing global warming due to greenhouse gas emission has a matter of concern for policy makers and environmentalist. greenhouse gas emission is measured on global carbon atlas. according to 2014 data, the thailand’s greenhouse emission level stands on 337 mtco2, which is lower than global average and has 0.84% share in global greenhouse gas emission. however, due to increasing consumption of crude oil and natural gas-based energy resources, the country has much miles to go in dealing the global warming problem. though many studies has uttered this issue but no empirical study has found in literature which has explored the linkages of greenhouse gas emission with customs duties, energy import and government health spending, particularly for thailand. the study aims to add in the literature of by exploring the empirical relationship of greenhouse gas emission with government fiscal and tariff policies (khan et al., 2018). novelty of this study is to examine the role of government’s policy in controlling the import of environment unfriendly products. additionally, the study opted multivariate time series econometric techniques to empirically infer the results. the objective of the study is to: • to study the impact of custom duties (tariff policy) on greenhouse gas emission in thailand. • to explore the relationship between energy import and greenhouse gas emission in thailand. • to find the role of government health spending in greenhouse gas emission in thailand. past studies on greenhouse gas emission have very useful policy implication for alleviating the emission of harmful pollutants (oertel et al., 2016; pearson et al., 2017; prairie et al., 2018). moreover, the studies have supported policy makers and government to introduce reforms in controlling the greenhouse gas emission and global warming. additionally, the past studies also presented sufficient theoretical and empirical framework which broaden the aspects of research on greenhouse gas emission. this study also aims to add in the same lines. the study is organized as follows: section two discusses the literature review and theoretical background; section three focuses methodology and data analysis; section four enunciate the empirical findings and results, section five concludes the results and suggests policy in the light of results. 2. literature review and theoretical framework thailand being the second biggest economy of southeast asian countries, after indonesia has recorded the higher consumption of fossil fuels during recent year. energy information administration (eia) also stressed that greenhouse emission has enlarged multifold over the last 150 years. the main impetus rising greenhouse emission is majorly emanated from growing consumption of crude oil and energy import. greenhouse gas emission is the main culprit of global warming and underlying factors behind this issue are industrialization, transportation, electric production through nonrenewable resources, deforestation, commercial residence, and urbanization (emissions, 2015; pérez-lombard et al., 2008). the greenhouse emission in thailand is also majorly contributed by agriculture sector, industrial sector, and rubber production. however, the country measures such as issuance of oil and gas exploration license in 2014 has able to keep greenhouse gas emission below to global average. 2.1. custom duties and greenhouse gas emission increasing international trade has contributed in the trade of carbon intensive products which aggravate the emission of greenhouse gases across the world (andersson, 2018; kander et al., 2015). moreover, expansion of international trade due to free trade agreements among the countries has caused gradual reduction of trade barriers such as custom duties. the average duties in europe and north america reduce from 18% to 15% in 1950s to current average level of 4%, respectively. consequently, the greenhouse gas emission in the country also decrease drastically. the role of carbon tariffs levied by usa on the imports from china to control the greenhouse gas emission. custom duties may play significant role in checking the greenhouse gas emission. in order to fulfill the emission allowance requirement (ear) usa target its major import partners. however the usa carbon tariffs and era is against the wto provision of trade. cottier et al. (2014) proposed that custom duties and tariffs policy of a country can play key role in controlling the greenhouse gas emission (bakhtyar et al., 2017). custom duties on high carbon dioxide releasing goods may mitigate the environmental degradation. further, increasing duties on trade of pollutants and greenhouse gas emission products are an efficient way to force polluting country to comply international climate agreement. the results indicate that 5% increase in custom duties on pollutant products will cause 1.4% decrease in carbon intensive import. chen and guo (2017) analyzed the impact of custom duties on greenhouse gas emission due to china’s trade of industrial product to usa, japan, and european union. the study deduce that increase in custom duties will decrease the china’s export of high carbon intensive product. moreover carbon tariff will be more effective in mitigating the greenhouse gas emission. therefore, on the basis of above studies following hypothesis is proposed: h1: custom duties plays key role in controlling greenhouse gas emission in thailand. 39 39.5 40 40.5 41 41.5 42 42.5 43 2011 2012 2013 2014 energy import figure 1: energy imports of thailand srimarut and mekhum: impact of custom duties, energy import and government health spending on greenhouse gas emission in thailand international journal of energy economics and policy | vol 11 • issue 1 • 2021586 2.2. energy import and greenhouse gas emission greenhouse gas emission is mainly emanated through the energy consumption of nonrenewable fossil fuels such as gas and crude oil (covert et al., 2016). the growing industrial growth has also bolstered the demand of imported energy, which is considered as stimulus to output growth. high energy import, caused the unbridle increase in the greenhouse gas emission across in thailand as well. most of the energy importing countries are energy dependent countries which use the nonrenewable energy resource to generate energy. therefore, energy import has stimulated the emission of greenhouse gases in thailand. moreover, importing, refining, transporting of crude oil emit considerable greenhouse gas at each level. according to the study the better understanding of greenhouse gas emission by energy import will helpful in switching towards the alternative renewable energy channels. anwar (2016) also emphasized on the role of primary energy import on environmental emission and energy supply in pakistan . the study analyzed the data during the period of 2005-2050 by using integrated energy system. the study indicates that 10% reduction in energy import, greenhouse gas emissions will decrease by 8%. the rationalization of nonrenewable energy import will bring significant reduction in greenhouse gas emission. therefore, on the basis of above studies following hypothesis is built. h2: energy import has significant role in controlling greenhouse gas emission in thailand. 2.3. government health spending and greenhouse gas emission the literature of greenhouse emission has explored the impact of economic growth on co2 emission, where the impact of government health spending on greenhouse emission is highly ignored. whereas few studies have highlighted the causal relationship between government health’s spending and greenhouse gas emission (ahmad et al., 2018; ullah et al., 2019; wang et al., 2019). moreover, few studies supports that environmental degradation exert pressure on fiscal budgeting by increasing health expenditure (khoshnevis yazdi and khanalizadeh, 2017). moreover, khoshnevis yazdi and khanalizadeh (2017) empirically explored the linkages between health care, air pollutants, and economic growth by employing autoregressive distributed lag (ardl) method on panel data of mena region from 1995 to 2014. the study inferred that health policy should incorporate environment degradation issues, to control environment degradation; failing to do so will further increase the health spending of government. moreover, the health care policy of country has potential to spend on controlling environment degradation, by investing on environmental friendly system such as power generation in hospital through renewable energy. ghorashi and rad (2017) empirically explored the causal relationship between carbon dioxide emission, economic growth, and health expenditure by using simultaneous equation models. the scope of their study is limited to iran for the period of 1972-2012. the empirical results indicate that there is significant bilateral relationship between carbon dioxide emission and health expenditures. government spending of health will cause the installation of environment control devices, renewable energy bases power plants, electric vehicles that will resultantly check the greenhouse gas emission. chaabouni et al. (2016) also examined the causal relationship between greenhouse gas emission, economic growth, and health expenditure. the study used the panel data of 51 countries over the year of 1995 and 2013. to empirically analyze the data, study used the dynamic simultaneous equation modeling. the results indicates that health expenditure will helpful in controlling the co2 emission though economic growth which usually limits the environmental degradation. hence on the light of above discussion following hypothesis can build: h3: government health spending plays significant role in controlling greenhouse gas emission in thailand. 3. methodology 3.1. data the variables used in this study include custom duty, energy imports, and government health spending and greenhouse gas emission. apart from these variables, the author has also included two other variables as control variables named as population growth and energy consumption. consequently, all these variables have been used in the process of data collection. in other words, data about these variables has been collected. this data comprises of 28 years and has been collected from thailand. being the most important and foremost part of a research, data collection requires emphasis and effort in this regard. the author has used world bank and global economy as the databases of data collection process. the detailed discussion about the variables has been given in the next part. 3.2. model specification in model specification, the author has categorized the variables into three categories i.e. dependent, independent and control variables. custom duty, energy import and government health spending have been put in the category of independent variables while greenhouse gas emission is considered to be the dependent variable. two control variables, population growth and energy spending have also been considered. moving towards the measurement units’ allocation, the greenhouse gas emission has the measurement unit of thousands of tons. in the same way, custom duty has the measurement units of us dollars. energy import has the measurement units of the percentage of total imports while government spending on health has the measurement unit of us dollars. the measurement unit of population, a control variable is number of people of a country while that of energy consumption is billion kilowatt hours. after designating the measurement units to all the variables, the author has formed a regression equation by using specific notations for each variable. gge cd ei ghs pop enet t t t t t t= + + + + + +α β β β β β ε1 2 3 4 5 in the above given equation, the notations are used according to the variables, the details of which are given here. gge has been used to represent greenhouse gas emission, cd for custom duty, ei for energy imports, ghs for government health spending, pop for population growth and ene for energy consumption. apart from these, εt is used for error term. srimarut and mekhum: impact of custom duties, energy import and government health spending on greenhouse gas emission in thailand international journal of energy economics and policy | vol 11 • issue 1 • 2021 587 3.3. estimation procedure as the collected data is time series data and particular test must be used for this type of data. in this study the author has used unit root test, bounds co-integration test and ardl long run and short run estimation test. the details as well as results of these tests have been given in the upcoming portions. 3.4. unit root test first step in the research process is to determine the order of integration as well as the stochastic properties of the variables and the collected data. the reason behind this exploration of order of integration is that variables with specific order of integration may only move further in the research process (dickey and fuller, 1981). there are two conditions in this regard i.e. the order of integration of dependent variables be zero while that of independent variables be zero and one i.e. mixed order. the variables that are not fulfilling these conditions will be restricted to move forward in the process. for this purpose, the unit root tests are generally used and in this particular study, the author has used two types of unit root tests i.e. adf (augmented dickey fuller) and llc (levin lin chu). these tests involve null and alternate hypothesis where null hypothesis indicating the presence of unit root and non-stationary state of the data while alternate hypothesis indicating the absence of unit root and stationary state of the collected data. these tests can be used in accordance with the following equations: ∆x x t cdt t t= + + +−α α β1 ∆ ∆x x ct bdt dj xt t t j k t j t= + + + + +− = −∑β β ε1 1 ∆ ∆x x ctb ddt dj xt t t j k t j t= + + + + +− = −∑γ γ ε1 1 ∆ ω ω ∆x x ct dd ddt dj xt t t t j k t j t= + + + + + +− = −∑1 1 ε in this equation, t represents the time period. 3.5. bounds co-integration test the next step after determination of order of integration and stationary properties of the collected data is to find out that whether co-integrated or long run equilibrium relationship between the variables exists or not (pesaran et al., 2001). an important point that must be noted here is that smaller the sample size of data, more accurate will be the results. in this regard, wald test and f test are the mostly used options that are used in accordance with the following equation: ∆ ∆ ∆ ∆ ln ln ln ln gge gge cd ei t i p i t i k q k t k l r l t = + + + = − = − = − ∑ ∑ ∑ β β β β 0 0 0 0 ll m s m t m gge t cd t ei t gh ghs gge cd ei + + + + + = − − − − ∑ 0 1 1 1 β λ λ λ λ ∆ln ln ln ln ss t tghs vln − +1 in the above equation vt represents the error while δ shows the first difference level. there is an important point regarding the application of wald test that is it will only be applied if the coefficient of short run variable is >1 but as in this study the coefficient of short run variables in zero, the wald test cannot be applied here. the author is left with f test to apply in this case. as unit root test, this test also involves null and alternate hypotheses but with different conditions. in this test, null hypothesis will indicate the absence of co-integrated relationships while alternate hypothesis will indicate the presence of co-integrated relationships. a very important and main aspect of this test is the f statistic value that is generally compared with the estimated values called as upper bound and lower bound values. these values are actually based on the levels of significances i.e. 90%, 95% and 99%. the comparison of f statistic value with lower and upper bound may have three outcomes. it may be greater than the upper bound value indicating the rejection of null hypothesis, it may be lower than lower bound value indicating the acceptance of null hypothesis or it may be in between the both lower and upper bound values creating ambiguity in the results. after this comparison, the elasticity of coefficients of the variables is estimated both in long run and short run in accordance with the following equation: ln ln ln ln gge gge cd ei t i p i t i k q k t k l r l t l = + + + ∂ = − = − = − ∑ ∑ ∑ α ϕ ω 1 1 1 1 1 1 1 ++ ∅ + = −∑ m s m t m tghs 1 ln µ 4. empirical results 4.1. results of unit root test the detailed results of adf and llc unit root tests have been given in table 1. as these tests were used for the purpose of exploring the order of integration and stationary properties of the collected data, the results are interpreted accordingly. in results of adf test, it can be seen that all the variables in level series have rejected the null hypothesis but greenhouse gas emission and government health spending have accepted the null hypothesis. on the other hand, all the variables in first difference series have rejected the null hypothesis. it can be stated that the data in level series is non stationary while it becomes stationary when first difference is applied to it. in the same way, llc unit root tests can also be interpreted. all the variables in level series except government health spending have accepted the null hypothesis but all of them have rejected it in the first difference section giving the same results as that in adf test. 4.1.1. results of bounds co-integration test after unit root test, the next test that was applied on the data in this study was co-integration test and f test was preferred over wald test. in this regard, different estimated values were determined according to the aic criteria as well as proper lag length and then these values i.e. upper bound and lower bound values were compared with the actual value of f statistic. the results of this test can be seen in table 2 which shows that the value of f statistic is greater than the upper bound estimated values therefore it can srimarut and mekhum: impact of custom duties, energy import and government health spending on greenhouse gas emission in thailand international journal of energy economics and policy | vol 11 • issue 1 • 2021588 be stated that the null hypothesis has been rejected in this case. it would have been accepted if f statistic value was lesser than lower bound estimated value. as in this case, the null hypothesis of no co-integration is rejected it can be stated that there is co-integrated and long run relationship between the variables. 4.2. results of ardl long run and short run after the determination of co-integrated relationship between the variables, the next step was the application of long run and short run ardl tests so that the elasticity of coefficients of the variables can be determined. the results of short run ardl have been presented in table 3 and interpreted here. in the table, it can be seen that custom duty has negative significant and elastic impact on greenhouse gas emission with 10% significance level. with 1% increase in custom duty, greenhouse gas emission will be decreased by 12.6%. in the same fashion, the impact of energy imports is also significant, positive and elastic in regard of greenhouse gas emission. it means that with 1% increase in energy imports, the greenhouse gas emission will be increased by 28.64%. government health spending however has insignificant impact in this regard. apart from these independent variables, the impact of the control variable, energy consumption has also significant and elastic impact on greenhouse gas emission with 5% significance. these results can be summarized by stating that custom duty, energy imports and energy consumption have significant impacts in short run on greenhouse gas emission. after analyzing the results of short run ardl, the results of long run ardl have been presented in table 4 and are interpreted by the author. according to the table, the impacts of all the independent and control variables except population growth is significant and elastic in regard of greenhouse gas emission with different significance values. in other words, with increase of 1% custom duty, greenhouse gas emission will drop by 27.2%. in the same way, with increase of 1% energy imports, the greenhouse gas emission will also increase by 12.3%. when the government will increase 1% spending on health, the greenhouse gas emission will show a decrease by 23.3%. in short, custom duty, energy imports, government health spending and energy consumption have significant impacts in long run on greenhouse gas emission. 5. discussion and conclusion 5.1. discussion in this portion, the acceptance or rejection statuses of all the hypotheses formed for the purpose of this study have been discussed. the basic aim of this study was to find out and study the impact of custom duty, energy imports and government health spending on the emission of greenhouse gases. the first hypothesis in this regard was that custom duty has significant impact on greenhouse gas emission. this hypothesis was accepted according to the results and this is in accordance with a relevant past study (blodgett et al., 2008). the second hypothesis was that energy imports have significant impact on greenhouse gas emission. the author has also accepted this hypothesis on the basis of the results obtained. the same results are evident in a past study conducted by another researcher (knudson, 2009). the last hypothesis was that government health expenditure has significant impact on greenhouse gas emission and ultimately this hypothesis was also considered as accepted by the author. this behavior has also been shown by a past study (chaabouni and saidi, 2017). apart from these variables, the impact of two control variables was also studied. the impact of population has been rejected as being significant but the impact of energy consumption has been accepted by the author. this result is exactly in concordance with a past study (bilgen, 2014). 5.2. conclusion custom duty, energy imports and government health spending are the aspects that may have direct or indirect impact on the emission of greenhouse gases. in this study, the author is supposed to investigate the same impact i.e. of the above given aspects on table 2: co-integration test o.p.l. length (a.i.c) f-stat. (bound test) v.c l.b.c.v. u.b.c.v. (4,0,0,0,0) 7.7357** 3% 3.23 6.92 7% 5.725 5.23 11% 3.624 4.34 table 4: ardl long run results variable coefficient se t-stat. gge 1.7476 0.173 2.241*** gge (−1) −0.7254 1.836 3.425 gge (−2) 0.2643 0.919 2.836*** cd 0.2725 0.133 6.725*** ei 0.1235 0.631 3.275*** ghs 0.2333 0.724 4.235* pop 1.0916 1.725 3.286 ene 0.1357 0.913 2.245** c 0.1863 0.234 4.254*** r2 0.9163 f-stat 243.725*** adj. r2 0.1753 d.w. 5.45 diagnostic test x2sc x2w x2ar indonesia 2.864 (2.724) 5.32 (1.376) 1.35 (0.344) table 3: ardl short run results variable coefficient se t-stat. cd 0.1264 0.241 3.532*** ei 0.2864 0.423 4.522*** ghs 0.2832 0.134 2.826 pop 1.2643 0.425 0.725 ene 0.2764 0.286 3.275** ectt-1 −0.8235 0.274 −6.275 r2 0.1653 f-stat 130.254*** adj. r2 0.8163 d.w. 1.762 diagnostic test x2sc x2w x2ar indonesia 5.13 (1.753) 21.21 (1.754) 0.53 (0.754) table 1: unit root analysis constructs adf test llc test level 1st difference level 1st difference gge 4.7548* 6.7486*** −1.7476 −2.8547*** cd 7.7547 8.2757** −3.3565 −4.3528*** ei 5.2354 11.9675** −4.9546 −3.8547*** ghs 3.8543* 5.2457*** −2.2424* −5.3435*** pop 4.5432 7.8437*** −3.8547 −3.6478*** ene 8.9885 3.2658*** −1.2434 −7.4575** srimarut and mekhum: impact of custom duties, energy import and government health spending on greenhouse gas emission in thailand international journal of energy economics and policy | vol 11 • issue 1 • 2021 589 greenhouse gases. the author has collected data from thailand for 28 years in context of the above mentioned variables and after collecting, the data has been carefully analyzed. the tests that are used in the analysis of the collected data include unit root, bounds co-integration and ardl tests. it has been evident from the results of these tests that the impact of all the independent variables i.e. custom duty, energy imports and government health spending have significant impact on greenhouse gas emission both in long run and short run. in addition, it has also been investigated that the impact of one control variable i.e. energy consumption has been found as significant in context of greenhouse gas emission. the author has identified and discussed some of the important theoretical, practical and policy making implications of this study. some basic limitations have also been discussed along with the ways to improve them. 5.3. implications this study has found to have some theoretical, practical and policy making implications in different aspects. first of all, this study contains detailed literature to be used especially by the researchers, authors or any other person. this will not provide knowledge to them but may also give the direction of research. in addition, this study will also guide the custom department to consider their rates of duty as well as to manage the energy imports so that the greenhouse gas emission may be decreased. it will also provide guidance to the government to increase spending for health purposes in order to increase awareness about the harmful effects of greenhouse gases so that it may be controlled. the policy making and regulatory authorities may also get guidance from this study to make policies of high custom prices, low energy imports and high spending on health. all these policies will ultimately lead towards the decrease in greenhouse gas emission. 5.4. limitations and future research indications in the last of the study, the author has discussed some of the limitations that have the scope of improvement by the future researchers. in this regard, the sample size of data may be increased by other researchers, which is very small in this study. in addition, the other researchers may go to the other variables as well in order to increase the scope of their researches. they may go to some other country for data collection purpose other than thailand so that more places can be explored in context of this study. as the data was time series, particular tests were used in this study. the future researchers may use some other sets of tests that are suitable for time series data. references ahmad, m., rahman, z.u., hong, l., khan, s., khan, z., naeem khan, m. (2018), impact of environmental quality variables and socio-economic factors on human health: empirical evidence from china. pollution, 4(4), 571-579. andersson, f.n. (2018), international trade and carbon emissions: the role of chinese institutional and policy reforms. journal of environmental management, 205, 29-39. anwar, j. (2016), analysis of energy security, environmental emission and fuel import costs under energy import reduction targets: a case of pakistan. renewable and sustainable energy reviews, 65, 1065-1078. bakhtyar, b., kacemi, t., nawaz, m.a. (2017), a review on carbon emissions in malaysian cement industry. international journal of energy economics and policy, 7(3), 282-286. bilgen, s. (2014), structure and environmental impact of global energy consumption. renewable and sustainable energy reviews, 38, 890-902. blodgett, m.s., hunter, r.j. jr., lozada, h.r. (2008), a primer on international environmental law: sustainability as a principle of international law and custom. ilsa journal of international and comparative law, 15, 15-21. chaabouni, s., saidi, k. (2017), the dynamic links between carbon dioxide (co2) emissions, health spending and gdp growth: a case study for 51 countries. environmental research, 158, 137-144. chaabouni, s., zghidi, n., mbarek, m.b. (2016), on the causal dynamics between co2 emissions, health expenditures and economic growth. sustainable cities and society, 22, 184-191. chanchaichujit, j., saavedra-rosas, j., kaur, a. (2017), analysing the impact of restructuring transportation, production and distribution on costs and environment-a case from the thai rubber industry. international journal of logistics research and applications, 20(3), 237-253. chen, w., guo, q. (2017), assessing the effect of carbon tariffs on international trade and emission reduction of china’s industrial products under the background of global climate governance. sustainability, 9(6), 1028-1033. cottier, t., nartova, o., shingal, a. (2014), the potential of tariff policy for climate change mitigation: legal and economic analysis. journal of world trade, 48(5), 1007-1037. covert, t., greenstone, m., knittel, c.r. (2016), will we ever stop using fossil fuels? journal of economic perspectives, 30(1), 117-138. dickey, d.a., fuller, w.a. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica: journal of the econometric society, 49(4), 1057-1072. dogan, e., seker, f. (2016), the influence of real output, renewable and non-renewable energy, trade and financial development on carbon emissions in the top renewable energy countries. renewable and sustainable energy reviews, 60, 1074-1085. ghorashi, n., rad, a.a. (2017), co2 emissions, health expenditures and economic growth in iran: application of dynamic simultaneous equation models. growth, 9, 11-15. jebli, m.b., youssef, s.b. (2015), output, renewable and non-renewable energy consumption and international trade: evidence from a panel of 69 countries. renewable energy, 83, 799-808. kander, a., jiborn, m., moran, d.d., wiedmann, t.o. (2015), national greenhouse-gas accounting for effective climate policy on international trade. nature climate change, 5(5), 431-435. khan, h.u.r., siddique, m., zaman, k., yousaf, s.u., shoukry, a.m., gani, s., saleem, h. (2018), the impact of air transportation, railways transportation, and port container traffic on energy demand, customs duty, and economic growth: evidence from a panel of low-, middle-, and high-income countries. journal of air transport management, 70, 18-35. khoshnevis yazdi, s., khanalizadeh, b. (2017), air pollution, economic growth and health care expenditure. economic research ekonomska istraživanja, 30(1), 1181-1190. knudson, w.a. (2009), the environment, energy, and the tinbergen rule. bulletin of science, technology and society, 29(4), 308-312. mohr, s., wang, j., ellem, g., ward, j., giurco, d. (2015), projection of world fossil fuels by country. fuel, 141, 120-135. oertel, c., matschullat, j., zurba, k., zimmermann, f., erasmi, s. (2016), greenhouse gas emissions from soils-a review. chemie der erde geochemistry, 76(3), 327-352. pearson, t.r., brown, s., murray, l., sidman, g. (2017), greenhouse srimarut and mekhum: impact of custom duties, energy import and government health spending on greenhouse gas emission in thailand international journal of energy economics and policy | vol 11 • issue 1 • 2021590 gas emissions from tropical forest degradation: an underestimated source. carbon balance and management, 12(1), 3-11. pérez-lombard, l., ortiz, j., pout, c. (2008), a review on buildings energy consumption information. energy and buildings, 40(3), 394-398. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. prairie, y.t., alm, j., beaulieu, j., barros, n., battin, t., cole, j., harby, a. (2018), greenhouse gas emissions from freshwater reservoirs: what does the atmosphere see? ecosystems, 21(5), 1058-1071. sharma, a.k., dubey, a.k., singh, p., swarnkar, n.k. (2016), reduction in greenhouse gases emission using distributed energy resources (der) in distribution network. journal of advanced research in power electronics and power systems, 3(1-2), 37-41. ullah, i., ali, s., shah, m.h., yasim, f., rehman, a., al-ghazali, b.m. (2019), linkages between trade, co2 emissions and healthcare spending in china. international journal of environmental research and public health, 16(21), 4298-4301. wang, z., asghar, m.m., zaidi, s.a.h., wang, b. (2019), dynamic linkages among co2 emissions, health expenditures, and economic growth: empirical evidence from pakistan. environmental science and pollution research, 26(15), 15285-15299. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 1 • 2023118 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(1), 118-127. the impact of covid-19 on oil market returns: has market efficiency being violated? clement moyo, izunna anyikwa, andrew phiri* nelson mandela university, south africa. *email: phiricandrew@gmail.com received: 07 august 2022 accepted: 13 december 2022 doi: https://doi.org/10.32479/ijeep.13453 abstract this study examines the effect of covid-19 pandemic on the efficiency of oil markets from february 2nd, 2020 to august 4th, 2021. by relying on dynamic conditional correlation garch and wavelet coherence techniques, we able to provide correlations between the variables across time and frequency domains. our empirical findings point to significant yet weak correlations between covid-19 recovery/death rates for the time period extending from early february to early may even though we observe strong correlations between wti prices and covid-19 health statistics in mid-april. moreover, during this identified time period, the length of frequency cycles within the correlations decreases from 16 days to 8 days. altogether, these findings imply that oil markets were inefficient between february and early may and have since turned market efficient for the remaining duration of the pandemic. keywords: dcc-garch, wavelet coherence, wti, brent, opec, efficiency market hypothesis, covid-19 jel classifications: c02, c22, g14, g15 1. introduction the role which oil markets play in ensuring overall global stability cannot be overemphasized and this has recently been demonstrated during the ongoing coronavirus pandemic. take for instance, the us stock market crash experienced in mid-april 2020 which was a direct result of the historical collapse of wti prices and expiring wti futures contracts in the midst of a geopolitically-induced oil price war between saudi arabia and russia (jefferson, 2022; hanieh, 2021; ma et al., 2021). initially, energy markets were the most affected sectors during the early stages of the pandemic with market prices declining by over 60% (albulescu, 2020) and via contagion effects resulted in adverse spillovers into international equity and currency markets (elgammal et al., 2021; ghorbel and jeribi, 2021; jababli et al., 2021), which, in turn, led to heightened financial market panic and distorted global investor sentiments (salisu et al., 2020; chen et al., 2021; shaikh, 2021). since irrational behaviour by investors arising from financial market distress contradicts the efficient market hypothesis of fama (1970), many academics have re-ignited the classical debate on information efficiency of financial markets in context of the covid-19 pandemic (al-awadhi et al., 2020; aslam et al., 2020; dima et al., 2021; kakinaka and umeno, 2021; navratil et al., 2021; vasileiou, 2021; wang and wang, 2021) and yet it remains surprising that very little attention has been paid to examining the efficiency of oil markets during the periods of the pandemic. our study examines market efficiency in international oil markets during the covid-19 pandemic and we consider this to be an important empirical exercise as it bears substantial implications for investors, portfolio managers, market regulators as well as global policymakers. from the perspective of risk management and optimal portfolio design, market participants such as investors and portfolio managers would be interested in knowing whether oil markets are informationally efficient since oil has been found to be an effective hedge in diversifying risk against equity markets (ali et al., 2021; batten et al., 2021; mandaci and kirkpinar, 2021; abuzayed et al., 2022), precious metals and this journal is licensed under a creative commons attribution 4.0 international license moyo, et al.: the impact of covid-19 on oil market returns: has market efficiency being violated? international journal of energy economics and policy | vol 13 • issue 1 • 2023 119 agricultural commodities (hernandez et al., 2019; naeem et al., 2022), conventional currencies (olstad et al., 2020; liu, 2022), cryptocurrencies (okorie and lin, 2020; moussa et al., 2021) as well as political risk (bouoiyour et al., 2019) particularly during periods of financial turmoil and distress. on the other hand, market regulators need to be assured that information is rapidly absorbed into oil prices and this is important for reducing the scope of speculative investment behaviour geared towards making abnormal profits as well as for preventing the build-up of market bubbles in oil markets (gharib et al., 2021). moreover, international policymakers should be concerned with state of efficiency of oil markets as the pandemic has intensified global efforts to shift from dirty energy use to cleaner renewable sources which could distort demand and supply factors in energy markets through declining demand, technological-led supply response, intense competition, and investor scepticism; all which pose a threat to the stability of oil markets (masnadi et al., 2021; halttunen et al., 2022). in this sense, ensuring informational efficiency within oil markets is important for navigating the world into a “greener earth” without compromising the stability of commodity markets. whilst we acknowledge the existence of many previous studies which have investigated market efficiency in oil markets, it is interesting to note that most of these studies exclusively focus on weak-form informational efficiency, that is, examining whether past historical information can be used to predict future oil returns by subjecting the time series to tests for random walk behaviour (ghazani and ebrahimi, 2019; ghazani and jafari, 2019; shao, 2020; arshad et al., 2021). moreover, only the works of gil-alana and monge (2020), mensi et al., (2020) and okoroafor and leirvik (2022) have examined weak-form informational efficiency in oil markets for periods covering the covid-19 pandemic. notably, a handful of recent studies have further investigated semi-strong form market efficiency in financial markets during the pandemic by examining whether covid-19 statistics help to predict international equity market returns at national level (ashraf, 2020; he et al., 2020; liu et al., 2020; rakshit and neog, 2021; xu, 2021) or at industry/firm level (alfaro et al., 2020; mazur et al., 2021; narayan et al., 2021). however, to the best of our knowledge, there are no previous studies which have examined semi-strong-form informational efficiency in oil markets by testing the predictability of covid-19 statistics on oil returns. our study contributes to scientific literature by treating the coronavirus pandemic as a natural experiment to investigating semi-strong form market efficiency in oil markets, that is, we question whether publicly available covid-19 health statistics (cases, recoveries, and deaths) can be used to predict oil returns in opec, brent and wti markets. to test this hypothesis, we examine dynamic correlations between the time series and make use of dynamic conditional correlation generalized autoregressive conditional heteroscedasticity (dcc-garch) and complex wavelet coherence as empirical frameworks. on one hand, we use dcc-garch model to capture time-varying relationship between covid-19 statistics and oil returns and this allows us to examine whether oil markets switch between being efficient and inefficient at different time periods as speculated by the adaptive market hypothesis (amh) of lo (2004). recent evidence of time-varying informational efficiency in oil markets is provided in the studies of ghazani and ebrahimi (2019), ghazani and jafari (2019), shao (2020), arshad et al., (2021) and okoroafor and leirvik (2022) albeit these previous works strictly focus on weak-form market efficiency and establish time-variation for periods prior to the covid-19 pandemic. on the other hand, we make use of complex wavelet coherence techniques which allows us to decompose the time series along a time-frequency space and thereafter yield localized time-frequency information on the series. this differs from econometrical tools such as the dcc-garch in which the framework is strictly localized in time and therefore provides little to no information on the frequency components. distinguishing between the different cyclical components in oil market efficiency is important for capturing for the heterogenous activity of different market participants who base their decisions across different frequency horizons. for instance, speculative traders and myopic investors would be interested in obtaining public information related to shorter time horizons where the time series data is characterized by higher frequency oscillations. conversely, long-term, or safer investors would be more concerned with long-term or lower frequency variations between covid-19 information and oil returns. all-in-all, our study enriches the current knowledge of time-varying and cyclical varying informational efficiency in oil markets using more recent data covering the covid-19 pandemic. interestingly, both dcc-garch and wavelet coherence analysis mutually show that the oil markets has been generally market inefficient with respect absorbing information from covid-19 cases and deaths, and less so for recoveries. moreover, both analyses provide similar evidence of time-variation in oil market (in) efficiency which can be summarized in two points. firstly, we mutually find that semiweak market efficiency was most compromised during the periods of the initial announcement of the pandemic by the who in early march, during the oil and stock market crashes in mid-april as well as during the emergence of the delta variant which marks the beginning of the second wave of the pandemic. secondly, we find that during periods corresponding to intervention of global policymakers in financial markets; the us diplomatic intervention into the oil price-war in mid-april; as well as during the start of the vaccines, market efficiency is improved. altogether these findings bear important implications for different stakeholder in oil markets. the remainder of our study is structured as follows. section 2 presents a review of the associated literature. section 3 outlines the dcc-garch, and wavelet coherence methods used in our empirical analysis. section 4 presents the empirical findings whereas section 5 concludes the study in the form of policy implications. 2. literature review theoretically, efficient market hypothesis (emh) developed by fama (1970) stipulates that asset prices reflect all the available information and therefore precludes any likelihood of investors moyo, et al.: the impact of covid-19 on oil market returns: has market efficiency being violated? international journal of energy economics and policy | vol 13 • issue 1 • 2023120 earning abnormal returns. in this context, assets prices adjust with the arrival of new information to reflect the real value of the asset. this theory categorises market efficiency into three forms based on the type of information incorporated in the asset price namely the weak, semi-strong and strong form efficiency. the weak form efficiency holds that future price of an asset cannot be predicted based on the past and current price movements. this implies that future price changes are independent of past and current price changes, and it assumes that future price movements follow a random walk process. the semi-strong efficiency holds that an asset price should reflect all publicly available information and that investors cannot earn abnormal returns by relying on any publicly available information. in term of strong form efficiency, the theory holds that private information in addition to historical and public information are reflected in the market price of an asset. earlier criticism of the emh in literature is taken from grossman and stiglitz (1980), leroy and porter (1981) and shiller (1981). grossman and stiglitz (1981) point to the cost of obtaining information in their rejection of the emh. leroy and porter (1981) and shiller (1981) argue that excess volatility of stock prices provide enough information to invalidate the emh. furthermore, as alluded to by lo (2004), the emh has be criticised by authors in fields such as behavioural economics, psychology and sociology who outline departures from the standard assumptions in mainstream economics with regards to preferences and behaviour of market participants. specifically, critics argue that there is behavioural bias (irrational behaviour) among market participants in the event of uncertainty, which invalidates the emh. lo (2004) advocates for the adaptive market hypothesis (amh) as an alternative to the efficient market hypothesis, which suggests the co-existence of both market efficiency and inefficiency. empirically, a number of studies have investigated whether the emh applies to the crude oil market by focusing on weak-form efficiency. studies by charles and darné (2009), chen et al., (2020), mensi et al., (2012), lin et al. (2014), mensi et al. (2014) as well as arshad et al., (2021) found evidence that support the emh. charles and darné (2009) investigated the weak-form efficient market hypothesis for the uk brent and us wti and found that brent crude oil is characterised by weak-form efficiency while the wti oil market was found to be inefficient during the period 1994-2008. chen et al. (2020) assessed the efficiency of the newly developed crude oil futures market in china and found support for weak-form efficiency in the shanghai international exchange (ine) crude oil futures. mensi et al., (2012) found evidence of weak-form market efficiency for crude oil (wti and europe brent) between the period may 1987 and march 2012. lin et al. (2014) found evidence of market efficiency in 13 energy markets thus supporting the efficient market hypothesis. furthermore, technical analysis was thus found to be ineffective in improving the prospects of making higher profits. mensi et al., (2014) found evidence of weak-form efficiency in both wti and brent crude markets. arshad et al., (2021) found that the benchmark crude oil prices follow the weak-form efficiency for the period 1996-2018. furthermore, the authors reported improvements in the efficiency of the oil market in the short-term compared to the long-term. some studies reported that efficiency in the oil market is dependent on financial stability. ortiz-cruz et al. (2012) investigated the efficiency of crude oil markets during the period january 1986 to march 2011 and found that the crude oil market is efficient over the selected sample period. however, efficiency decreased during the late 1990s and late 2000 s due to the financial crises. zhang (2013) investigated weak-form efficiency in crude oil markets. the author concluded that crude oil markets exhibit week-form efficiency in the long-term. however, the degree of efficiency is dependent on the time period. ftiti et al. (2021) investigated the weak-form efficiency in oil and gas prices during stable and crisis periods using multifractal approach. the study found that oil and gas markets are inefficient for horizon less than two weeks but become efficient after two weeks. in addition, the oil and gas markets displayed increased multifractal behaviour during the post-crisis period. also, jiang et al. (2014) investigated the weak-form efficiency of the wti crude oil futures market for the period 1983-2012 and reported that the crude oil market is efficient when the entire sample is considered. however, the market was inefficient during periods of instability such as the gulf war, iran war and the oil price crash of 2008. zhang et al. (2014) investigated the weakform efficiency of crude oil spot markets in europe, us, uae and china during the period december 2001 to august 2013 and found evidence of efficiency in all the four markets despite brief periods of inefficiency especially the 2008/2009 global financial crisis. however, studies by gόrsha and krawiec (2016), ghazani and ebrahim (2019), shao (2020), ghazani and jafari (2021) and okoroafor and leirvik (2022) found evidence which refutes the emh. gόrsha and krawiec (2016) investigated the weakform efficiency hypothesis in the crude oil market during the period 2000-2015 and failed to find evidence to support the hypothesis. ghazani and ebrahimi (2019) employed the automatic portmanteau and generalised spectral test to investigate the presence of the adaptive market hypothesis (amh) in crude oil prices. the authors found evidence of the amh, an alternative to the efficient market hypothesis, which suggests the co-existence of both market efficiency and inefficiency in a consistent manner. ghazani and jafari (2021) also confirmed that the oil market is best explained by the amh. shao (2020) found evidence of improvements in the oil market after the lifting of the ban on us oil exports. furthermore, crude oil market is characterised inefficiency in the short-term, although the weak-form hypothesis holds in the long-run. okoroafor and leirvik (2022) found evidence of time-varying efficiency in crude oil markets which supports the amh. furthermore, the efficiency of the brent crude market has improved compared to that of the wti market during the period may 1987 till september 2020. a number of studies investigated the effect of the covid-19 pandemic on the efficiency of the oil market. narayan (2020) found that the covid-19 pandemic contributed 30% towards oil price clustering behaviour which is an indication of market inefficiency. furthermore, clustering during the covid-19 period is 8% more compared to the pre-pandemic period mensi et al., (2020) found that before the covid-19 pandemic the oil moyo, et al.: the impact of covid-19 on oil market returns: has market efficiency being violated? international journal of energy economics and policy | vol 13 • issue 1 • 2023 121 market was inefficient during periods of upward trends in the price. however, during the period of the covid-19 pandemic the oil market was inefficient during the downward trends in the price. overall, the covid-19 pandemic had a negative impact on oil market efficiency. gil-alana and monge (2020) reported evidence of market efficiency in its weak-form for crude oil prices before the covid-19 pandemic. however, there is evidence of some inefficiency during the period of the pandemic which is expected to be transitory. tudor and anghel (2021) examined the efficiency of the crude oil market by investigating the predictive performance of technical analysis trading rules (ttr) for the period 1999-2021. the authors found that weak-form efficiency is applicable to the wti crude oil market as ttrs have no effect on the oil market. however, there is evidence of temporal inefficiency in the oil market during the 1st year and quarter period of the covid-19 pandemic. usman and akadiri (2021) confirmed the presence of weak-form efficient market hypothesis in oil markets for the period 1st january 2015 to 24th december 2020. however, it should be noted that the covid-19 pandemic caused a significant increase in persistence of oil returns. wang et al. (2022) investigated the effect of the covid-19 pandemic on the energy market (wti crude and coal). the authors found that market efficiency reduced significantly in the first quarter of 2020. market efficiency improved in the second half of 2020 after the implementation of quantitative easing. furthermore, in the early part of 2021 market efficiency deteriorated due to increased market risk. most studies in the literature examine the effect on the covid-19 pandemic on oil markets, investigate the weak-form market hypothesis. our study contributes to scientific literature by treating the coronavirus pandemic as a natural experiment to investigating semi-strong form market efficiency in oil markets for a longer time period. the study employs the dcc-garch and wavelet coherence analysis as empirical frameworks and these are discussed in detail in the next section. 3. methodology the empirical approach employed in this paper composed of two frameworks, the dcc-garch model and wavelet coherence analysis. these two methodological approaches are discussed below. 3.1. dcc-garch model to analyze the time evolution of correlation between the global crude oil prices and covid-19, this paper relies on a bivariate ar (1)-gjr-garch-dcc. as a first step, it is assumed that each series (rt) follows an autoregression of order one, ar (1). this can be expressed as: r r n ht t t t t t� � �� �� � � �1 1 0� ~ ( , ) (1) where rt denotes a vector of returns of the crude oil or change in covid indicators. μ is constant vector. rt-1 is the vector of past returns and μt is a vector of error term conditional on past information ωt–1 at time t–1. the conditional variance ht follows the univariate garch mode proposed by glosten et al. (1993) and it is expressed as: h h i i nit i i i t i i t i t i t� � � � � �� � � �� � � � � �, , , ,1 1 2 1 1 2 1for (2) where ht captures the conditional variance of each series. the parameters α and β are the arch and garch coefficients respectively. it is a dummy variable that takes the value of 1 if εit < 0 but 0 if otherwise, indicating the evidence of asymmetry in returns. in the second step, the dcc model proposed by engle (2002) is applied to provide time-varying correlation between crude oil and covid-19 indicators. in dcc, the variance -covariance matrix (ht) is define as: h d r dt t t t= (3) where d diag h ht t t� �� �11 2 21 2/ /, .., is a diagonal matrix of timevarying conditional standard deviation derived from equation (2) rt is the conditional correlation matrix which is given as: r diag q q diag qt t t t� � � [ ( ) ] [ ( ) ] / /1 2 1 2 (4) where, q qt ij t= , is the conditional covariance matrix of the standardised residuals, εt. the dcc model is given as: q b q bqt t t t� � � � �� � �( ) ' 1 1 1 1� �� � (5) where α and b are positive scalar parameters satisfying α + b <1 condition. the conditional correlation is expressed as: � � �� � � �� ij t ij it jt ijt ii it b q bq b q b , ' [ � � �� � � � � �� � � � � � � � 1 1 1 1 1 1 2 qq b q bq iit jj jt jjt � � �� �� � � � 1 1 2 11 ] [ ]� �� (6) the coefficient ρij,t indicates the strength and direction of correlation between crude oil returns series and covid-19 at time t. following engle (2002), the estimation of this model is done by using two-step quasi-maximum likelihood estimation method. 3.2. wavelet coherence analysis the second approach used in this paper is the wavelet analysis which enables simultaneous analysis of co-movement between stock markets and covid-19 infections. this approach offers a way of analysing localised variations of power within time series. as such, it provides a framework to determine the level of interdependencies between two time series variables in both frequency and time spaces (aguiar-conraria and soares, 2011). in addition, the model captures the possible dynamic changes in the relationship by accounting for both short-run and long-run movements. specifically, this paper employed the wavelet coherence (wtc) and cross-wavelet phase angle (phase difference) to analyse the dependencies between stock market and covid-19 infections. this framework is briefly presented below. we begin the discussion of our methodology by defining a continuous wavelet transform (cwt) for a wavelet 𝜓through the following function: moyo, et al.: the impact of covid-19 on oil market returns: has market efficiency being violated? international journal of energy economics and policy | vol 13 • issue 1 • 2023122 w s x t s t s dtx , * ( )� � � � � � �� � � 1 � (7) where * denotes a complex conjugation, τ is the translation parameter which dictates where the wavelet is centred, and s is the scaling parameter controlling the length of the wavelet which is compressed if |s| < 1 and stretched if |s| > 1. since the wavelet coefficients contain combined information on both x(t) and ψ(t), aguiar-conraria et al. (2008) and aguiar-conraria and soares (2011, 2014) propose the use of a complex-valued wavelet function since its corresponding transform will also be complex and can be separated into an amplitude and a phase. the following morlet wavelet is employed as the continuous ‘mother’ wavelet and is defined as: � �t i t t� � � � � � � 1 4 0 21 2 exp ( )exp (8) to ensure that the parameterization of the morlet wavelet depicts an inverse relation between wavelet scales and the frequencies, f≈s– 1, aguiar-conraria et al. (2008) and aguiar-conraria and soares (2014) propose that the morlet be set to approximately 6 (i.e. ω0 = 2π) in order for the wavelet scale, s, to be almost equal to the fourier period. within the continuous mother wavelet domain, the wavelet power spectrum (wps) can be extracted, which measures the variance of a time series across a two-dimension plane i.e. time and scale (aguiar-conraria et al., 2008, aguiar-conraria and soares, 2011, 2014). formally, the wps for a discrete time series, xn, can be expressed as: w s t s x n m t sm s nn n � � � � � � � � � � � � �� � * (( ) , ., , , ., 0 1 0 0 n n 1 m n 1 (9) where δt is a uniformed time step. the cross-wavelet power spectrum (cwps) is then introduced to measure the covariance between two time series variables, x(t) and y(t). by defining the wps of x(t) and y(t) as wxx = |wx| 2 and wyy = |wy| 2, respectively, the cwps between x(t) and y(t) is computed as: (wps)xy = wxy = |wxy| (10) we finally compute the wavelet coherence, which is analogous to the correlation between x(t) and y(t) across time and frequency, as the ratio of the cross spectrum to the product of the product of the spectrum of the individual series i.e. r s s w s w s w n xy x y � � � ( ) [( )( )] 2 2 1 2 (11) where s is a smoothing operator in both time and scale. aguiarconraria et al. (2008) and aguiar-conraria and soares (2011, 2014) further propose the use the phase-difference to describe the relative positions of the pair of time series. aguiar-conraria and soares (2014) note that “phase differences” are important since the wavelet coherence cannot distinguish between negative and positive correlation between two time series as well as identifying causal relationships between the variables. the phase-difference can be defined as: �x y x x tan w w, ( { } { } ))� � �1 � (12) where φx,y is parametrized in radians, bound between π and −π. if φx,y ∈ (0, π 2 ) and φx,y ∈ (0, � � 2 ), then the series are said to be in-phase (positive correlation) with y leading x in the former and x leading y in the latter. conversely, if φx,y ∈ ( π 2 , π) and φx,y ∈ ( � � 2 −π), then the series are said to be in an anti-phase (negative correlation) with x leading y in the former and y leading x in the latter. a phase-difference of zero implies co-movement between the pair of series at the specified frequency. 4. data and empirical results 4.1. data description our study makes use of 4 time series variables, namely, the covid-19 recovery rates which are sourced from the “worldometers” online statistics; the wti oil prices, brent oil prices and opec oil prices which are all sourced from “inveting com” database. all data is collected in daily frequencies over the period 2nd february 2020 to 4th august 2021, given us a sample size of 550 observations to work with. table 1 summarises the statistical properties of the variables. more specifically, the table shows that the average global cases and death associated with covid-19 infection per thousand population was growing at a rate of 1.8% per day while recovery rate was growing at a fast pace of 2.4% daily. the daily global oil price returns ranges between 0.01% for opec and 0.06% for wti. however, the skewness coefficients shows that the distribution of return series for brent and opec crude were negatively skewed, suggesting high probability of realising negative returns than positive returns. also, the oil returns series have leptokurtic distribution, indicating that oil returns were highly concentrated around the mean values. consequently, the jarque bera test shows deviation of the oil return series from normality. further analysis shows that the variables are first difference stationary series as shown by the results of the augmented dickey-fuller (adf) and phillips and perron (pp) tests. lastly, the analysis also shows evidence of arch effect in the residuals up to ten lags as indicated by the arch test and ljung-box (lb) tests. this finding confirms that the use of the dcc-garch model is appropriate for this study. table 2 shows the unconditional correlation between the oil returns and covid-19 indicators. the analysis of the unconditional correlation shows that oil returns were negatively correlated with the changes in the number of coronavirus cases, death, and recovery. in other words, the global oil returns fall as the number of coronavirus cases, death and recovery increased. this suggests that the global oil market investors may be very cautious about investing in the global oil market as the virus spreads. however, some studies have cautioned against the use of the unconditional correlation method as a decision-making tool (hemche et al., 2016 and pukthuanthong and roll, 2009). hence, this study utilises more advance tools namely the dcc-garch and wavelet techniques. moyo, et al.: the impact of covid-19 on oil market returns: has market efficiency being violated? international journal of energy economics and policy | vol 13 • issue 1 • 2023 123 4.2. dcc-garch results we firstly make use of a dcc-garch (1,1) specification in examining the time-varying conditional volatility and correlations between the covid-19 indicators and oil prices. table 3 present the estimation result from dcc-gjrgarch and the results show that oil returns volatility is mostly influenced by shocks to the conditional variance as indicated by the significant garch parameters. this further indicate evidence of persistence of volatility in the oil returns given that the garch coefficients ranges from 0.85 to 0.89, suggesting that it takes time for a shock to the conditional variance to die out. moreover, the second moment condition α+β + ( 1 2 ) γ < 1 is satisfied by each oil return series, indicating long memory and weak form efficiency of oil market. it is also shown that opec oil return is more volatile compared to others with a garch coefficient of 0.89. in addition, the analysis in the table shows evidence of significant asymmetry in the oil returns volatility as indicated by the coefficient γ. this finding indicates that negative shocks have significant impact on oil returns compared to positive shocks of equal magnitude. also, it suggests that bad news associated with the number of coronavirus cases and death is likely to cause more volatility than good new as a result of number individuals who had recovered from the virus infection. the analysis of the residual diagnostic tests shows that the estimated dcc-gjr-garch model was adequately specified and that the model is robust in capturing all the data generating process. specifically, the diagnostic tests show there is no further serial correlation and arch effect in the oil returns series as indicated by the lb and arch tests. furthermore, the dcc parameters (a and b) are statistically significant, and the sum of the parameters is less than unity, indicating shock to model die out after some time. hence, this finding emphasises the stability of the estimated dcc model. to analyse the dynamic correlation between covid-19 and oil returns, figure 1 provides the visual plots of the dynamic volatility co-movement across time. the figures shows that dynamic comovement of oil returns is more volatile in relation to the number of covid-19 cases and deaths compared to recoveries. in other words, oil returns exhibited more correlation with the number of cases and death, this can be inferred from the number of spikes. another important evidence emerging from the figure is that the oil returns exhibited high correlation with the covid-19 during the early period of the pandemic, from february to july 2020. in addition, there is evidence of more negative co-movement during this early phase. it is also, shown that the co-movement intensified during the period september 2020-january 2021, which coincides with the second wave of the pandemic. however, following the rollout of mass vaccinations by governments around the in january 2021, we observe les significant co-movements between health statistics and oil returns. 4.3. wavelet coherence results in this section of the paper we present the findings from our wavelet coherence analysis of the time series variables. figure 2 presents the wavelet coherence plots between covid-19 recoveries and oil prices (top panel) and covid-19 death rate and oil prices (bottom panel). the coherence plots provide a 3-dimensional analysis of the dynamic correlations between the pairs of time series, with the time-varying domain being measured across the horizontal axis between february 2nd, 2020 and august 4th, 2021, the frequency domain being measured along the vertical axis which captures cycles from 1 to 512 days and the strength of the correlations being measured by the colour contours which range from blue (weak correlation), to green (moderate correlations) to red (strong correlations). the 5% significance levels of the correlations across different time and frequency components represented by the faint white lines whilst the phase difference dynamics are captured by the arrows within the diagrams. note that arrows pointing to the right (left) indicate the phase-in (phase-out) or positive (negative) correlations between the series whereas arrows facing north-east, table 1: summary statistics cases recovery death brent opec wti panel a: descriptive statistics mean 1.763 2.399 1.770 0.038 0.015 0.061 median 0.958 0.907 0.623 0.121 0.077 0.108 maximum 33.500 36.683 22.630 8.285 9.932 13.882 minimum 0.167 −12.656 0.155 −12.150 −14.382 −12.276 std dev. 2.899 4.597 3.240 1.536 1.865 1.971 skewness 4.803 4.482 3.044 −1.383 −0.841 0.030 kurtosis 36.749 27.564 12.212 19.704 20.323 18.581 jarque bera 28165.6*** 15641.4*** 2788.9*** 6569.7*** 6941.6*** 5563.7*** adf level 0.920 10.463 0.859 −0.581 −0.393 −0.817 adf 1st diff −1.608 −3.879*** −2.343 −17.708*** −9.348*** −18.413*** pp level 5.766 7.576 6.184 −0.618 −0.471 −1.334 pp 1st diff −4.129*** −22.164*** −7.712*** −17.967*** −19.537*** −18.553*** lb (10) 3788.100*** 51.104*** 2433.000*** 14.900 67.800*** 25.080*** lb2 (10) 306.450*** 0.828 1504.300*** 174.840*** 200.130*** 208.070*** arch (10) 121.460*** 0.807 415.060*** 113.470** 92.550*** 111.220*** ***, ** and * indicate 1%, 5% and 10% levels of significant respectively table 2: correlation matrix cases recovery death brent opec wti cases 1.000 recovery 0.696 1.000 death 0.932 0.743 1.000 brent −0.085 −0.046 −0.096 1.000 opec −0.070 −0.029 −0.076 0.518 1.000 wti −0.101 −0.037 −0.120 0.805 0.428 1.000 moyo, et al.: the impact of covid-19 on oil market returns: has market efficiency being violated? international journal of energy economics and policy | vol 13 • issue 1 • 2023124 or south-west (north-west or south-east) indicate causality running from covid-19 to oil prices (oil prices to covid-19). from figure 2, it is clear to observe that the dynamic correlations between covid-19 health outcomes and oil prices do not differ much amongst the three markets which is not surprising considering the observed interconnectedness of oil markets (bhanja et al., 2021). secondly, in all markets, we observe significant co-movements between health statistics and covid-19 across the entire time window which implying correlation between the series throughout the entire pandemic. secondly, judging from the colour contours in the wavelet plots, we observe stronger correlations between covid-19 cases/deaths and oil market returns and weaker correlations for recovery data which shows that cases and death statistics are more efficient at predicting oil market returns. thirdly, whilst co-movements are dominated by low frequency synchronizations at cycles of between 125 and 512 days, we observe some short-run frequency components of 8 to 64 days which are clustered (i) during the march 2020-april 2020 period which corresponds to the “black swan” period in turmoil in financial markets which encompasses the oil market crash event (ii) during the 2020 october-2020 december periods, particularly for recovery statistics, which coincides with the announcement of the alpha and beta variants as well as the peak of the second wave (iii) during the post-april 2020 period which corresponds to period when the delta variant was announced. lastly, from the table 3: dcc-gjr-garch (1,1) countries mean equation variance equation diagnostic tests μ rt-1 ω α β γ lq (10) lq 2 (10) arch (10) cases 0.146 0.965*** 0.000 0.715** 0.554*** 0.412 194.17*** 1.837 1.888 recovery 2.232 0.091 10.008 0.153 0.540 -0.252 2004.1*** 62.290*** 130.220*** death −0.134 0.987*** 0.001 0.063 0.707*** 0.638** 267.27*** 20.433*** 23.865** brent 0.041 0.250*** 0.028** 0.033 0.852*** 0.200** 5.361 6.103 6.639 opec 0.008 0.284*** 0.018** −0.012 0.887*** 0.244** 13.273 3.721 3.808 wti 0.044 0.178*** 0.027** 0.039 0.857*** 0.196** 10.068 11.177 11.429 dcc parameters a b a + b cases/brent/opec/wti 0.068*** (0.012) [5.835] 0.684*** (0.053) [12.818] 0.752 recovery/brent/opec/wti 0.072*** (0.012) [5.787] 0.669*** (0.055) [12.119] 0.741 death/brent/opec/wti 0.065*** (0.012) [5.897] 0.703*** (0.052) [13.471] 0.768 ***, ** and * indicate 1%, 5% and 10% levels of significant respectively. the number in the normal brackets are the standard errors while number in the squared brackets are z-statistics -.4 -.2 .0 .2 .4 .6 i ii iii iv i ii iii 2020 2021 cases vs brent -.4 -.2 .0 .2 .4 i ii iii iv i ii iii 2020 2021 cases vs opec -.4 -.2 .0 .2 .4 .6 i ii iii iv i ii iii 2020 2021 cases vs wti -.6 -.4 -.2 .0 .2 .4 i ii iii iv i ii iii 2020 2021 recovery vs brent -.4 -.3 -.2 -.1 .0 .1 .2 i ii iii iv i ii iii 2020 2021 recovery vs opec -.3 -.2 -.1 .0 .1 .2 i ii iii iv i ii iii 2020 2021 recovery vs wti -.3 -.2 -.1 .0 .1 .2 .3 i ii iii iv i ii iii 2020 2021 death vs brent -.4 -.2 .0 .2 .4 i ii iii iv i ii iii 2020 2021 death vs opec -.4 -.2 .0 .2 .4 i ii iii iv i ii iii 2020 2021 death vs wti figure 1: dynamic conditional correlation moyo, et al.: the impact of covid-19 on oil market returns: has market efficiency being violated? international journal of energy economics and policy | vol 13 • issue 1 • 2023 125 phase difference dynamics within the wavelet coherence the plots, we find that the cases and deaths series are predominantly antiphase (negative) at lower frequency and more in-phase (positive) at high frequency oscillations. altogether the findings from our wavelet coherence analysis compliments those obtained from the dcc-garch model, and the findings can be collectively summarized in three points. firstly, we find evidence against the semi-weak form market efficiency since we find that covid-19 statistics are correlated with oil returns during the entire pandemic. secondly, we our findings mutually show evidence of time-variation in the synchronization between the time series which we treat as evidence in favour of the amh and these findings compliment previous literature which found similar time-variation in oil market efficiency in the weak-form sense (mensi et al., 2020; gil-alana and monge, 2020; usman and akadiri, 2021; okoroafor and leirvik, 2022). lastly, indicate that market efficiency is has been most compromised during the periods corresponding to the oil-price war as well as during the announcements of different variants of the covid disease, whereas market efficiency has been generally improving after the mas rollout of vaccines in january 2021 as observed by rouatbi et al. (2021) for the case of stock markets. 5. conclusion the ongoing covid-19 pandemic is the deadliest wave of viral infection our current generation has faced and there has increasing evidence that information contained within public available covid-19 health statistics are influencing movements in financial markets. in our study, we examine the co-movement between covid-19 and global oil prices for wti, brent and opec markets between 02 february 2020 and 04 august 2021 using the dccgarch model and wavelet coherence analysis in our empirical analysis. on one hand, the dcc-garch estimates capture the time-varying co-movement between the variables whereas, on the other hand, the wavelet coherence analysis captures both the time-varying and frequency-varying co-movements between the time series. mutually, both the dcc-garch and the wavelet coherence estimates reveal time-varying co-movements between covid-19 health statistics and oil market prices throughout our entire study sample which is evidence in support of the amh. moreover, the wavelet coherence analysis further shows that synchronizations between the time series are dominated by low frequency components whereas short frequency components are dominant during (i) periods of financial turmoil and geopolitical instability (ii) periods around the announcements of the various covid-19 variants. however, both dcc-garch and wavelet analysis inform us that the co-movement between health statistics and oil returns is weaker after the roll out of mass vaccinations around the world. altogether, our has important implications for investors, market regulators, policymakers and academics. for investors, our evidence demonstrates that the market returns can be predicted using publicly available information on health statistics particularly those for cases and death statistics. for market regulators and policymakers, our study provides evidence that the oil market has been most vulnerable during periods of geopolitical instability as well as when newer variants of the disease have been discovered and yet improves after the rollout of vaccines. in turn, this emphasizes the importance which a vaccinated population plays towards oil market stability during the pandemic and highlights figure 2: wavelet coherence plots moyo, et al.: the impact of covid-19 on oil market returns: has market efficiency being violated? international journal of energy economics and policy | vol 13 • issue 1 • 2023126 the threat of the recent russian-ukraine tensions, as a more recent geopolitical event, on the informational efficiency of oil markets. lastly, our study demonstrates the importance of using more updated time series and empirical techniques to draw novel information on the efficiency of oil markets and encourages future studies to keep monitoring the evolving nature of the pandemic on oil markets as more data becomes available. references abuzayed, b., al-fayoumi, n., bouri, e. (2022), hedging uk stock portfolios with gold and oil: the impact of brexit. resources policy, 75, e102434. al-awadhi, a., alsaifi, k., al-awadhi, a., alhammadi, s. (2020), death and contagious infectious disease: impact of the covid-19 virus on stock market returns. journal of behavioural and experimental finance, 27, e100326. aguiar-conraria l, soares m. (2011), oil and the macroeconomy: using wavelets to analyze old issues. empirical economics, 40, 645-655. aguiar-conraria l, soares m. (2014), the continuous wavelets transform: moving beyond uniand bivariate analysis. journal of economic surveys, 28(2), 344-375. aguiar-conraria l., azevedo n, soares m. (2008), using wavelets to decompose the time-frequency effects of monetary policy, physica a: statistical mechanics and its applications, 387(12), 2863-2878. albulescu c. (2020), coronavirus and oil price crash. available from: https://hal.archives-ouvertes.fr/hal-02507184v2 alfaro, l., chari, a., greenland, a., schott, p. (2020), aggregate and firm-level stock returns during pandemics, in real time. (nber working papers no. 26950). united states: national bureau of economic research. ali, s., bouri, e., czudaj, r., shahzad, s. (2021), revisiting the valuable roles of commodities for international stock markets. resource policy, 66, e101603. ashrad, s., rizvvi, s., haroon, o., mehmood, f., gong, q. (2021), are oil prices efficient? economic modelling, 96(c), 362-370. ashraf, b. (2020), stock markets’ reaction to covid-19: cases or fatalities? research in international business and finance, 54, e101249. aslam, f., aziz, s., nguyen, d., mughal, k., khan, m. (2020), on the efficiency of foreign exchange markets in times of the covid-19 pandemic. technological forecasting and social change, 161, e120261. batten, j., kinateder, h., szilagyi, p., wagner, n. (2021), hedging stocks with oil. energy economics, 93, 104422. bhanja, n., nasreen, s., dar, a., tiwari, a. (2021), connectedness in international crude oil markets. computational economics, 59, 227-262. bouoiyour, j., selmi, r., wohar, m. (2019), safe havens in the face of presidential election uncertainty: a comparison between bitcoin, oil and precious metals. applied economics, 51(57), 6076-6088. charles, a., darné, o. (2009), the efficiency of the crude oil markets: evidence from variance ratio tests. energy policy, 37(11), 4267-4272. chen, d., hu, h., chang, c. (2021), the covid-19 shocks on the stock markets of oil exploration and production enterprises. energy strategy reviews, 38, e100696. chen, y., fei, l., libing, f., xingxing, s. (2020), the pricing efficiency of crude oil futures in the shanghai international exchange. finance research letter, 36, 101329. dima, b., dima, s., ioan, r. (2021), remarks on the behaviour of financial market efficiency during the covid-19 pandemic: the case of vix. finance research letters, 43, e101967. elgammal, m., ahmed, w., alshami, a. (2021), price and volatility spillovers between global equity, gold, and energy markets prior to and during the covid-19 pandemic. resources policy, 74, e102334. fama, e.f. (1970), efficient market hypothesis: a review of theory and empirical work. journal of finance, 25(2), 28-30. ftiti, z., jawadi, f., louhichi, w., madani, m.a. (2021), are oil and gas futures markets efficient? a multifractal analysis. applied economics, 53(2), 164-184. gharib, c., mefteh-wail, s., jabeur, s. (2021), the bubble contagion effect of covid-19 outbreak: evidence from crude oil and gold markets. finance research letters, 38, e101703. ghazani, m., ebrahimi, s. (2019), testing the adaptive market hypothesis as an evolutionary perspective on market efficiency: evidence from the crude oil prices. finance research letters, 30, 60-68. ghazani, m., jafari, m. (2019), cryptocurrencies, gold, and wti crude oil market efficiency: a dynamic analysis based on the adaptive market hypothesis. financial innovation, 7(1), 1-26. ghorbel, a., jeribi, a. (2021), volatility spillovers and contagion between energy sector and financial assets during the covid-19 crisis period. eurasian economic review, 11, 449-467. gil-alana, l., monge, m. (2020), crude oil prices and covid-19: persistence of the shock. energy research letters, 1(1), 1-4. glosten l., jagannathan r., runkle d. (1993), on the relation between expected value and the volatility of the nominal excess return to stocks, the journal of finance, 48(5), 1779-1801. grossman, s.j., stiglitz, j.e. (1980), on the impossibility of informationally efficient markets. the american economic review, 70(3), 393-408. halttunen, k., slade, r., staffell, i. (2022), what if we never run out of oil? from certainty of “peak oil” to “peak demand’’. energy research and social science, 85, e102407. hanieh, a. (2021), covid-19 and global oil markets. canadian journal of development studies, 42(1-2), 101-108. he, q., liu, j., wang, s., yu, j. (2020), the impact of covid-19 on stock markets. economic and political studies, 8(3), 275-288. hemche o., jawadi f., maliki s., cheffou a. (2016), on the study of contagion in the context of the subprime crisis: a dynamic conditional correlation-multivariate garch approach, economic modelling, 52(a), 292-299. hernandez, j., shahzad, s., uddin, g., kang, s. (2019), can agriculture and precious metal commodities diversify and hedge extreme downside and upside oil market risk? an extreme quantile approach. resources policy, 62, 588-601. jababli, i., kouaissah, n., arouri, m. (2021), volaility spillovers between stock and energy markets during crises: a comparative assessment between the 2008 global financial crisis and the covid-19 pandemic crisis. finance research letters, 46(a), e102363. jefferson m. (2022), a crude future? covid-19s challenges for oil demand, supply and prices, energy research and social science, 68, e101669. jiang, z.q., xie, w.j., zhou, w.x. (2014), testing the weak-form efficiency of the wti crude oil futures market. physica a: statistical mechanics and its applications, 405, 235-244. kakinaka, s., umeno, k. (2022), cryptocurrency market efficiency in short-and long-run horizons during covid-19: an asymmetric multifractal analysis approach. finance research letters, 46(a), e102319. leroy, s.f., porter, r.d. (1981), the present-value relation: tests based on implied variance bounds. econometrica, 49(3), 555-574. lin, z.w., hsu, s.h., huang, c.s. (2014), technical analysis and market efficiency: an empirical examination on energy markets. investment management and financial innovations, 11(1), 189-199. liu, h., manzoor, a., wang, c., zhang, l., manzoor, z. (2020), the moyo, et al.: the impact of covid-19 on oil market returns: has market efficiency being violated? international journal of energy economics and policy | vol 13 • issue 1 • 2023 127 covid-19 outbreak and affected countries stock market response. international journal of environmental research and public health, 17(8), e2800. lo, a. (2004), the adaptive market hypothesis: market efficiency from an evolutionary perspective. the journal of portfolio management, 5(30), 15-29. ma, r., xiong, t., bao, y. (2021), the russia-saudi arabia oil price war during the covid-19 pandemic. energy economics, 102, e105517. mandaci, p., kirkpinar, a. (2021), oil assets and portfolio diversification: firm-level analysis for borsa istanbul. borsa instabul review,  22(3), 571-585. masnadi, m., benini, g., el-houjeiri, h., milivinti, a., anderson, j., wallington, t., de kleine, r., dotti, v., jochem, p., brandt, a. (2021), carbon implications of marginal oils from market-derived demand shocks. nature, 599, 80-84. mazur, m., dang, m., vega, m. (2021), covid-19 and the march 2020 stock market crash. evidence from s and p1500. finance research letters, 38, 101690. mensi, w., aloui, c., hamdi, m., nguyen, d.k. (2012), crude oil market efficiency: an empirical investigation via the shannon entropy. économie internationale, 1, 119-137. mensi, w., beljid, m., managi, s. (2014), structural breaks and the time-varying levels of weak-form efficiency in crude oil markets: evidence from the hurst exponent and shannon entropy methods. international economics, 140, 89-106. mensi, w., sensoy, a., vo, x.v., kang, s.h. (2020), impact of covid-19 outbreak on asymmetric multifractality of gold and oil prices. resources policy, 69, 101829. moussa, w., mgadmi, n., bejaoui, a., regaieg, r. (2021), exploring the dynamic relationship between bitcoin and commodities: new insights through stecm model. resource policy, 74, e102416. naeem, m., hasan, m., arif, m., suleman, m., kang, s. (2022), oil and gold as a hedge and safe haven for metals and agricultural commodities with portfolio implications. energy economics, 105, e105758. narayan, p.k. (2022), evidence of oil market price clustering during the covid-19 pandemic. international review of financial analysis, 80, 102009. narayan, p.k., gong, q., ahmed, h.j.a. (2021), is there a pattern in how covid-19 has affected australia’s stock returns?. applied economics letters, 29, 179-182. navratil, r., taylor, s., vecer, j. (2021), on equity market inefficiency during the covid-19 pandemic. international review of financial analysis, 77, e101820. okorie, d., lin, b. (2020), rude oil price and cryptocurrencies: evidence of volatility connectedness and hedging strategy. energy economics, 87, e104703. okoroafor, u., leirvik, t. (2022), time varying market efficiency in the brent and wti crude market. finance research letters, 45, e102191. olstad, a., filis, g., degiannakis, s. (2020), oil and currency volatilities: co-movements and hedging opportunities. international journal of finance and economics, 26(2), 2351-2374. ortiz-cruz a., rodriguez e., ibarra-valdez c., alvarez-ramirez j. (2012), efficiency of crude oil markets: evidences from informational entropy analysis, energy policy, 41, 365-373. pukthuanthong k., roll r. (2009), global market integration: an alternative measure and its application, journal of financial economics, 94(2), 214-232. rakshit, b., neog, y. (2021), effects of covid-19 pandemic on stock market returns and volatilities: evidence from selected emerging economies. studies in economics and finance, 39(4), 549-571. rouatbi, w., demir, e., kizys, r., zaremba, a. (2021), immunizing markets against the pandemic: covid-19 vaccinations and stock volatility around the world. international review of financial analysis, 77, e101819. salisu, a., ebuh, g., usman, n. (2020), revisiting oil-stock nexus during covid-19 pandemic: some preliminary results. international review of economics and finance, 69, 280-294. shaikh, i. (2021), on the relation between the crude oil market and pandemic covid-19. european journal of management and business economics, 30(2), 331-356. shao, y. (2020), does crude oil efficiency improve after the lift of the u.s. export ban? evidence from time-varying hurst component. frontiers in physics, 8, e551501. shiller, r.j. (1981), do stock prices move too much to be justified by subsequent changes in dividends?. the american economic review, 71(3), 421-436. tudor, c., anghel, a. (2021), the financialization of crude oil markets and its impact on market efficiency: evidence from the predictive ability and performance of technical trading strategies. energies, 14(15), 4485. usman, n., akadiri, s.s. (2022), the persistence of precious metals and oil during the covid-19 pandemic: evidence from a fractional integration and cointegration approach. environmental science and pollution research, 29(3), 3648-3658. vasileiou, e. (2021), behavioural finance and market efficiency in the time of the covid-19 pandemic: does fear drive the market. international review of applied economics, 35(2), 224-241. wang, j., wang, x. (2021), covid-19 and financial market efficiency: evidence from an entropy-based analysis. finance research letters, 42, e101888. wang, q., yang, x., li, r. (2022), the impact of the covid-19 pandemic on the energy market-a comparative relationship between oil and coal. energy strategy reviews, 39, e100761. xu, l. (2021), stock return and the covid-19 pandemic: evidence from canada and the us. finance research letters, 38, e101872. zhang, b. (2013), are the crude oil markets becoming more efficient over time? new evidence from a generalized spectral test. energy economics, 40, 875-881. zhang, b., li, x.m., he, f. (2014), testing the evolution of crude oil market efficiency: data have the conn. energy policy, 68, 39-52. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 3 • 2021140 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(3), 140-148. relationship between oil prices and stock prices in brics-t countries: symmetric and asymmetric causality analysis aktolkin abubakirova1, aziza syzdykova2*, assan dosmakhanbet1, lyazzat kudabayeva3, gulnar abdulina4 1department of tourism, khoja akhmet yassawi international kazakh, turkish university, turkestan, kazakhstan, 2department of finance and accounting, khoja akhmet yassawi international kazakh, turkish university, turkestan, kazakhstan, 3m.kh.dulaty taraz regional university, taraz, kazakhstan, 4narxoz university, almaty, kazakhstan. *email: azizayesevi@gmail.com received: 20 august 2020 accepted: 10 january 2021 doi: https://doi.org/10.32479/ijeep.10487 abstract in this study, by considering the period between january 2010 and december 2019 of brics-t countries, the relationship between oil prices and stock prices was examined through the hatemi-j asymmetric causality test (2012). the stationarity levels of the series were determined by augmented dickey-fuller (adf) and phillips-perron (pp) unit root tests. hatemi (2012) asymmetric causality test, which takes into account the presence of asymmetric information in financial markets by distinguishing positive and negative shocks, was used. accordingly, hidden relationships that could not be detected using the symmetric causality test were revealed with the help of the asymmetric causality test. keywords: brics-t, oil prices, stock prices, asymmetric causality jel classifications: c23, g15, q40 1. introduction oil prices, which directly or indirectly affect many sectors in the economy, are an important indicator of economic performance. the reason why the changes in the oil market or oil prices create chain interactions on both the country and the world economy is that the oil price is independent of each other or depends on many factors that affect each other. it is possible to see the chain interaction of increases in crude oil prices on macroeconomic variables such as inflation, unemployment and economic growth (hamilton, 1983). for example, the effect of fluctuations in oil prices on economic growth and their effect on stock prices are a knock-on effect (takashi and bong-soo, 1995). oil prices can indirectly affect macroeconomic indicators and stock market returns primarily by affecting industrial production and inflation. high oil prices cause production costs to rise and then production to decrease or expected earnings to decrease (miller and ratti, 2009). however, oil prices can negatively affect the overall performance of the stock market, both directly and indirectly. a direct negative effect can be explained by the upward movement in oil prices creating uncertainty in financial markets, which in turn leads to a fall in share prices. as a result of the increase in oil prices, the decrease in stock prices due to low production level and higher inflation rates is an indirect negative effect (filis, 2010). considering the studies in the literature investigating the effects of oil prices on the stock market index, they differ from each other in terms of their results. while some of the studies argue that there is a linear relationship between oil prices and stock market index (phan et al, 2015; filis and chatziantoniou, 2014; narayan and sharma, 2014; miller and ratti, 2009; henriques and sadorsky, 2008; maghyereh, 2004; sadorsky, 2001; papapetrou, 2001), and some mention the existence of a non-linear relationship (park and ratti, 2008; chen, 2010; broadstock et al., 2014; narayan and gupta, 2015; tsai, 2015; syzdykova, 2018). in addition, according to the direction of the relationship between oil prices and stock this journal is licensed under a creative commons attribution 4.0 international license abubakirova, et al.: relationship between oil prices and stock prices ın brics-t countries: symmetric and asymmetric causality analysis international journal of energy economics and policy | vol 11 • issue 3 • 2021 141 market index, they are divided into studies that accept negative (cunado and de gracia, 2014) or positive effect (arouri and rault, 2012). this situation may arise from the differences in the data sets and econometric methods covered by the studies. however, the differences in the internal dynamics of each country /country group cause the results of the study to be complex and the discussions on this issue continue. the aim of this study is to contribute to the literature by revealing the relationship between oil prices and stock market index by using a large data set for brics-t countries, considering the inconsistent results on the subject. for this purpose, the study consists of four parts. after mentioning the relationship between variables in the introduction part, the studies on the subject in the literature are summarized in the second part. in the third chapter, the data set and econometric methodology used are included. in the fourth chapter, empirical analysis results are given. in the last part, the contribution of the study to the literature is mentioned by interpreting the analysis results. 2. literature review energy, financial markets and economy act in conjunction with each other in the economic growth stage of a country (basher and sadorsky, 2006: 225). since oil is both an energy source and an important input in production and logistics activities, volatility in oil prices affects all units of the economy directly or indirectly. since the evaluation of the increase in oil prices as a negative situation by the markets causes the decrease in stock prices, it can be mentioned that there is a negative correlation between oil returns and stock returns. however, it is expected that both oil and stock prices will increase in times of economic expansion. as a different situation, in oil producing and exporting countries, there is a positive correlation between oil returns and stock returns as the increase in wealth and income in parallel with oil price increases will positively affect stock prices. although the effect of oil on stock returns is explained by some transmission mechanisms, the opposite effect is more acute. stock markets, acting according to future expectations, may decline before the crisis or rise before the economic recovery begins. however, as oil prices depend on supply and demand, they change simultaneously with cyclical fluctuations. even though there are some statistical regularities among the variables, the direction of the correlation between oil returns and stock returns may change depending on the leading nature of the stock market as well as how these variables behave against cyclical fluctuations (awartani and maghyereh, 2013: 28, hamma et al., 2014: 110). in studies investigating the relationship between oil prices and stock markets, different variables such as real oil price, nominal oil price, net oil price increase, oil price volatility, oil futures price increases, oil price shocks have been used. on the other hand, different findings have been made in studies conducted to examine the relationship between oil prices and stock markets. park and ratti (2008) analyzed the effect of oil price shocks and oil price volatility on the real stock returns of the usa and 13 european countries using the var model using monthly data from january 1986 to december 2005. stating that oil price shocks have a statistically significant and negative effect on real stock returns in the same month or the next month, the researchers state that these shocks and the increase in oil price volatility have a strong effect on stock returns in all european countries except the usa. unlike other countries, norway, which is an oil exporter, has a positive response to real stock returns to the oil price shock increases. the result of the analysis of variance decomposition shows that oil price shocks explain 6% of real stock return volatility. cong et al. (2008) used the multivariate var model in their study based on january 1996 and december 2007 monthly data to examine the interaction between oil price shocks and volatility and the chinese stock market. as a result of the analysis, it was concluded that the oil price shocks do not have a statistically significant effect on the chinese stock market index returns, except for the production index and the oil companies. significant oil price shocks affect the stock prices of oil companies, and the increase in oil price volatility increases the mining and petrochemical industry index returns. gay (2008) used the arima model to analyze the relationship between oil price and exchange rate and the stock market index prices of brazil, russia, india and china. in the study using monthly data between march 1999 and june 2006, it is revealed that there is no significant relationship between the oil price and exchange rate and the stock market index prices of brazil, russia, india and china, and the past stock prices do not have an effect on the current price of the stocks. ono (2011), investigating the effect of oil prices on brazil, russia, india and russia stock market returns for the period january 1999 september 2009, used the multivariate var model. it has been found that oil price changes positively affect the stock market returns of china, india and russia, and that there is no significant effect on the brazilian stock market. variance segregation analysis result is; it shows that the impact of oil price shocks on china and russia stock market return volatility is large and statistically significant. in addition, it has been determined that oil price shocks have an asymmetric effect only for the indian stock market. filis et al. (2011) used the dcc-garch-gjr model for the time-varying correlation between the stock prices and oil prices of oil-importing (usa, germany and netherlands) and oilexporting countries (canada, mexico and brazil) for the period january 1987 and december 2009.. they stated that, except for the 2008 financial crisis period, oil prices had a negative effect on stock markets and the correlation that changed over time was not different for oil exporting countries and oil importing countries. however, they argue that non-economic crises create a stronger negative correlation between oil prices and stock markets, while economic crises trigger a strong positive correlation between variables. they determined that precautionary demand shocks cause negative correlation, aggregate demand shocks cause a positive correlation, while supply side shocks do not affect the relationship between oil prices and stock markets. according to the researchers, in times of economic turmoil, the oil market is not considered as a tool to reduce potential losses of investors. wang et al. (2013), using the monthly data for the period january 1999 december 2011, investigated the effects of oil price shocks abubakirova, et al.: relationship between oil prices and stock prices ın brics-t countries: symmetric and asymmetric causality analysis international journal of energy economics and policy | vol 11 • issue 3 • 2021142 on the stock markets of oil-exporting and oil-importing countries using structural var analysis. the size, duration and direction of the response of the country’s stock markets to oil price shocks vary depending on whether the country is a net importer or exporter in the world oil market and the changes in oil prices arise from supply or total demand. the relative contribution of oil price shocks to the national economy is related to its net position in the oil market and the importance of oil. cunado and de gracia (2014), in their study for 12 european oil-importing countries (germany, austria, belgium, denmark, finland, france, the netherlands, england, spain, italy, luxembourg, portugal), the response of real stock returns to oil prices is negative. they also found that the aforementioned reactions varied greatly depending on the underlying reasons for the oil price change. in table 1, studies investigating the symmetrical and asymmetrical relationships between oil prices and stock market indices are presented in summary. 3. data set and methodology 3.1. data set in this study, the relationship between stock market indices from developing countries with exchange rates in brazil, russia, india, china, turkey and south africa (brics-t) has been investigated using monthly data. in the study, the closing prices of the main stock market index of each country are used to represent the stock price variable, and the brent type crude oil prices to represent the oil prices. the monthly data set used in the analysis for countries covers the period january 2010-december 2019. in addition, oil price data were obtained from the international energy agency (iea), and stock market index data were obtained from the bloomberg database. 3.2. econometric methodology hacker and hatemi (2006) use the toda-yamamoto causality test (1995) to determine the causality between variables in the bootstrap granger causality test, but the critical values are obtained by bootstrap mounted carlo simulation against the possible risk of normal distribution of errors. however, the drawback of this model is that it cannot distinguish between positive and negative shocks. in this context, in the asymmetric causality test developed by hatemi (2012), in the presence of asymmetric information in financial markets and heterogeneity of market participants, the results of this test may be misleading because the participants do not give similar responses to positive and negative shocks of the same magnitude. in this context, the hatemi-j asymmetric causality test (2012) hacker and hatemi (2006) is the decomposition of positive and negative shocks of the bootstrap granger causality test. in other words, this method is very suitable for studies using financial time series. hacker and hatemi (2006) causality test examines the causality relationship between variables with the toda-yamamoto causality test, but the critical values used are obtained by the bootstrap method against the possibility of normal distribution of errors. the following vector autoregressive (var) model is used to test the causality relationship between variables with the hacker and hatemi causality test. yt=α+ai yt–1+…+ap yp–1+ut (1) yt used in the model indicates the variable vector and a indicates the parameter vector. in order to obtain the wald statistics to be used, the var model shown in the equation can be written as follows. y=nz+δ (2) the variables in the model are expressed as follows, respectively. ( )1 2 3, , , , , ( )tx x x x x n t+ + + += … × (3) n=(v, a1, a2, a3,…, ap), (n×(1+n(p+d))) z=(z0, z1, z2,…, zt–1), (1+n(p+d)×t) ( )( )( )1 1 1 , 1 1 , 1, , . . t t t t p x x z n p d t t x + + − + − +          = + + × = …            (4) ( )1 2 3, , , , , ( )t t t ttu u u u n tδ = … × (5) the wald statistic used to test causation is as follows (hacker and hatemi, 2006:). w=(cβ)’ [c((z’ z)–1)⊗su) c’ ] –1) (cβ) (6) the asymmetric decomposition technique developed by granger and yoon (2002) was applied by hatemi (2012) in causality analysis. hatemi (2012) set out from the following random walk process for causality analysis (hatemi, 2012: 449). y y yt t t i t i1 1 1 1 10 1 1� � � �� � �� �, (7) y y yt t t i t i2 2 1 2 2 0 1 2� � � �� � �� �, (8) where, y1t and y2t show the initial values of y1,0 and y2,0, being two integrated series. in order to examine the causality relationship between the components of the variables, positive and negative shocks are defined as follows. � � � �1 1 1 10 0i i i i � �� � � � � �max , , min , (10) � � � �2 2 2 20 0i i i i � �� � � �max , , min( , ) (11) the equations for these two variables including positive and negative shocks are formed as follows: abubakirova, et al.: relationship between oil prices and stock prices ın brics-t countries: symmetric and asymmetric causality analysis international journal of energy economics and policy | vol 11 • issue 3 • 2021 143 table 1: summary of empirical literature review authors country/country group method variables results studies on the symmetrical assumption alzyoud et al. (2018) canada johansen cointegration and vecm crude oil prices, exchange rate and stock market return there is no cointegration relationship between variables. however, the regression analysis results showed that the oil price and exchange rate and their changes have a positive and significant effect on canadian stock returns basher et al. (2018) canada, norway, russia, kuwait, saudi arabia and uae markov model world oil supply, global real economic activity, global crude oil stocks, oil prices and stock market indices oil price shocks in oil exporting countries have a non-linear relationship with stock returns. peculiar oil shocks affect stock returns in norway, russia, kuwait, saudi arabia and uae. oil supply shocks are important for the uk, kuwait and uae. mexico is the only country where stock market returns are not affected by oil market shocks phan et al. (2015) usa garch (1,1) wti crude oil prices, index prices of various sectors rising oil prices raise oil producers ‘stock prices, while lowering oil consumers’ stock prices filis and chatziantoniou (2014) uk, germany, italy, spain, netherlands, portugal, russia, norway var method brent crude oil prices, cpi, short term interest rates, stock market indices while oil-importing countries’ stock markets reacted negatively to the increases in oil prices, the opposite is true for oil-exporting exchanges. the magnitude of responses to changes in oil prices is higher in newly established and/or less liquid stock markets (such as russia and norway) degiannakis et al. (2013) eu countries diag-vech garch model brent crude oil prices, stock market basic and sub-sector indices there is a time-varying relationship between oil and stock returns for all oil consuming countries arouri and rault (2012) bahrain, oman, kuwait, qatar, saudi arabia, uae bootstrap panel cointegration and sur stock market indices, opec spot prices there is a long-term and positive relationship between oil prices and the stock markets of the gulf countries al-fayoumi (2009) turkey, tunisia and jordan johansen cointegration and vecm oil prices and stock returns it is concluded that the change in oil prices in these countries has no effect on stock returns gay (2008) bric countries box-jenkins arima model exchange rate, oil prices and stock returns as a result of the analysis, no relationship was found between oil prices and stock returns studies on the asymmetric assumption al-hajj et al. (2018) malaysia nonlinear ardl oil price, basic and sub-sector indices, interest rate, exchange rate, industrial production index, and inflation he concluded that oil price shocks negatively affect stock market returns. it has shown that the malaysian stock exchange is very sensitive to fluctuations in oil prices. in addition, the findings found a long-term asymmetric link between oil price shocks, interest rate, exchange rate, industrial production, inflation and stock market returns in most cases, both at the aggregate and industry level benkraiem et al. (2018) england, germany, france and italy quantile ardl model wti oil prices and stock market indices the findings show that the distinction between short and long term, quantities and countries is of particular importance narayan and gupta (2015) usa linear regression models s&p 500 stock index, positive and negative wti crude oil price returns negative changes in oil prices provide a better forecast of stock prices compared to positive changes broadstock et al. (2014) japan, india, korea, taiwan capm-garch wti crude oil prices, japan, india, korea, taiwan basic and sub-stock market indices stock exchanges are more responsive to increases in oil prices (eg tokyo, korea and taiwan) wang et al. (2013) 9 oil importers and 7 oil exporters var model wti oil prices, industrial production, real economic activity index and stock prices it is concluded that the magnitude, duration and even the direction of the response of stock prices varies depending on whether the country to which it is an oil exporter or importer, and whether the price shock is caused by demand/supply source: created by authors abubakirova, et al.: relationship between oil prices and stock prices ın brics-t countries: symmetric and asymmetric causality analysis international journal of energy economics and policy | vol 11 • issue 3 • 2021144 y y yt t t i t i i t i1 1 1 1 10 1 1 1 1� � � � �� � � � �� �� � �, (12) y y yt t t i t i i t i2 2 1 2 2 0 1 2 1 2� � � � �� � � � �� �� � �, (13) the positive and negative shocks for the causality test of hatemi (2012) are generated in cumulative form as follows: 1 1 1 1 2 2 2 2 1 1 1 1 , , t t t t i i i i i i i i i i i i y y y ve yε ε ε ε+ + − − + + − − = = = = = = = =∑ ∑ ∑ ∑ (14) after this step, to find the causality relationship between positive components with the assumption that y y yt t t� � � � ( , ) 1 2 , the var model with p delay is defined as follows. y ay a y ut t p t t � � � � � �� � � � �� 1 1 1... (15) where, p shows the delay number, yt (2×1) size variable vector, and ar is (2×2) dimensional r-order parameter matrix. likewise, the causality relationship between negative components can be tested with the following p lagged var model with the assumption y y yt t t � � �� � �1 2, . y ay a y ut t p t t � � � � � �� � � � �� 1 1 1... (16) the wald statistics to be used for the test are obtained with the help of the var model used in the hacker and hatemi causality test, and the causality test is performed following the same path. 4. results since the data set is a financial time series, the stationarity structures of the price series and logarithmic return series must first be determined. since the probability of the occurrence of false relationships in the analyzes made with non-stationary time series will affect the reliability of the estimation results, the stationary condition must be met (syzdykova et al., 2020). the graph of price series regarding the variables is shown in figure 1. when the graphics are analyzed, it is observed that all series contain trend movements. on the other hand, the decline in oil prices that started in 2014 is parallel to the decline in the oil exporter russia, figure 1: graph of price series abubakirova, et al.: relationship between oil prices and stock prices ın brics-t countries: symmetric and asymmetric causality analysis international journal of energy economics and policy | vol 11 • issue 3 • 2021 145 brazil and south africa stock markets. all series show a fluctuating course in the long run. based on this effect, it is possible to say that the series is not static. augmented dickey-fuller (adf) and phillips-perron (pp) unit root tests were used to determine whether oil prices and stock index series are stable. the hypothesis established for the unit root test will be as follows: • h0: series is not stationary (has a unit root) • h1: series is stationary (has no unit root). analysis results of the unit root tests of brent oil prices and the price and return series of brics-t countries’ stock markets are summarized in table 3. since the t-statistics values obtained as a result of the test for price series are higher than the critical value of mackinnon at the significance level of 0.10, it was concluded that the price series is not stationary and the series contains unit root. in order to accurately determine the interaction between oil prices and brics-t countries’ stock markets, their returns must be calculated. for this purpose, the monthly return rates of oil and stock markets are calculated by taking the first logarithmic difference of price indices with the help of the formula below: r p pt t t � � � � � � �� � log 1 100 (17) rt is the monthly return of the oil markets on day t or the stock markets of brics-t countries, and pt indicates the closing value of the index on day t. the purpose of the creation of the yield series is to ensure stability by eliminating the seasonal and trend effect in the financial time series. the graphics of the yield series are shown in the figure 2. in the unit root tests for the return series, large negative values were obtained for each case. considering all return series, the null hypothesis was rejected because the adf and pp test statistics were higher than the mackinnon critical values at the 1% significance level in intercept and trend and intercept models, and therefore the return series was determined to be stationary. all variables have unit roots in price series values and are stationary in return series values (table 2). after this stage, the causality relationships between the series were examined with symmetric and asymmetric causality tests. table 3 shows the results of symmetrical and asymmetrical figure 2: graph of return series abubakirova, et al.: relationship between oil prices and stock prices ın brics-t countries: symmetric and asymmetric causality analysis international journal of energy economics and policy | vol 11 • issue 3 • 2021146 table 2: unit root test results variables price series return series adf pp adf pp brent intercept –1.6306 –1.6150 –8.1558* –8.1504* trend and intercept –2.4816 –2.5033 –8.208* –8.2171* brazil intercept –1.1569 –1.6590 –11.942* –11.331* trend and intercept –1.3481 –1.2322 –11.143* –11.402* russia intercept –1. 1456 –1.8223 –10.419* –10.887* trend and intercept –1.5715 –1.6039 –10.509* –10.855* india intercept –1.6419 –1.6107 –12.122* –12.103* trend and intercept –1.7462 –1.8248 –12.117* –12.113* china intercept –1.7532 –1.7478 –10.951* –10.942* trend and intercept –2.2126 –2.1295 –10.002* –10.011* south africa intercept –1.6403 –1.5335 –12.444* –12.010* trend and intercept –2.405 –2.4222 –12.469* –12.062* turkey intercept –2.0202 –2.0364 –10.084* –10.135* trend and intercept –2.2105 –2.3345 –10.106* –10.122* mackinnon p–value 1% 5% 10% intercept –3.4865 –2.8860 –2.5799 trend and intercept –4.0369 –3.4480 –3.1491 *i̇s statistically significant at 99% confidence level table 5: summary of symmetric and asymmetric causality test results countries symmetrical asymmetrical positive negative country op→sp sp→op op→sp sp→op op→sp sp→op brazil       russia       india       china       south africa       turkey       op is oil price, sp is stock price table 3: symmetric and asymmetric causality test results (oilp→stockp) countries hypothesis wald stat. 1% 5% 10% brazil oilp↛stockp 7.709** 11.603 5.302 3.679 oilp+stockp+ 11.911*** 10.540 5.529 3.773 oilp–stockp– 0.473 14.707 9.155 5.632 russia oilp↛stockp 17.170*** 9.541 5.003 3.615 oilp+↛stockp+ 20.045 11.837 5.090 3.626 oilp–↛stockp– 6.641 13.333 5.921 3.191 india oilp↛stockp 3.260 9.433 5.078 3.693 oilp+↛stockp+ 5.553** 8.031 4.228 2.928 oilp–↛stockp– 5.305** 7.394 3.853 2.806 china oilp↛stockp 2.264 9.968 5.244 3.770 oilp+↛stockp+ 2.965*** 9.487 5.818 3.330 oilp–↛stockp– 9.502** 11.843 8.075 6.323 south africa oilp↛stockp 19.005*** 9.637 5.151 3.636 oilp+↛stockp+ 47.347 13.365 7.283 3.573 oilp–↛stockp– 19.279 13.840 7.093 5.020 turkey oilp↛stockp 34.205 9.817 5.150 3.653 oilp+↛stockp+ 23.207** 7.559 4.142 2.928 oilp–↛stockp– 15.323 13.769 7.305 3.936 ↛ i̇ndicates no causation. *, ** and *** show the existence of a causality relationship between series at 1%, 5% and 10% significance levels, respectively table 4: symmetric and asymmetric causality test results (stockp→oilp) countries hypothesis wald stat. 1% 5% 10% brazil stockp↛oilp 0.020 11.138 5.377 3.728 stockp+↛oilp+ 6.756 11.084 5.483 3.738 stockp–↛oilp– 0.309 18.811 7.522 3.769 russia stockp↛oilp 0.295 8.684 5.257 3.635 stockp+↛oilp+ 3.075* 8.766 5.052 2.810 stockp–↛oilp– 2.770 10.838 5.741 3.008 india stockp↛oilp 0.412 8.388 5.027 3.725 stockp+↛oilp+ 0.432 7.680 3.850 3.301 stockp–↛oilp– 3.004** 7.743 4.345 2.693 china stockp↛oilp 5.966 8.882 5.278 3.773 stockp+↛oilp+ 0.674 8.838 5.370 3.553 stockp–↛oilp– 26.076*** 13.280 8.450 3.570 south africa stockp↛oilp 3.266 8.518 5.255 3.637 stockp+↛oilp+ 1.366 8.546 5.735 2.862 stockp–↛oilp– 6.192 11.508 5.973 3.856 turkey stockp↛oilp 0.131 8.561 5.170 3.638 stockp+↛oilp+ 0.001 6.331 3.715 3.791 stockp–↛oilp– 1.217 15.445 5.510 3.717 ↛ i̇ndicates no causation. *, ** and *** show the existence of a causality relationship between series at 1%, 5% and 10% significance levels, respectively causality from oil price to stock price. accordingly, a causality relationship from oil price to stock price has been determined in all brics-t countries. in addition, the asymmetrical relations determined between the variables can be explained as follows: (i) according to the asymmetric causality result for brazil, there is a causality relationship between the positive shocks from oil price to stock price, but not for negative shocks. (ii) there is no asymmetric relationship between variables in russia and south africa, the relationship is symmetrical. (iii) a causality relationship from oil price to stock price has been identified for both positive and negative shocks for india and china. (iv) there was no symmetrical relationship between the variables for turkey. asymmetrically, a causality relationship between specific shocks from oil price to stock price has been found. table 4 shows the results of symmetrical and asymmetrical causality from stock price to oil price in brics-t countries. according to the results, there is no symmetrical relationship from stock price to oil price in any of the brics-t countries. asymmetric causality are as follows: (i) brazil, an asymmetric relationship between variables is not the case for south africa and turkey. (ii) there is a causality relationship from stock price to oil price among positive shocks at the 10% significance level for russia. there is no causality relationship between negative shocks. (iii) a causality relationship from stock price to oil price has been identified for negative shocks in india and china. table 5 summarizes the symmetric and asymmetric causality test results. accordingly, hidden relationships that could not be abubakirova, et al.: relationship between oil prices and stock prices ın brics-t countries: symmetric and asymmetric causality analysis international journal of energy economics and policy | vol 11 • issue 3 • 2021 147 detected using the symmetric causality test were revealed with the help of the asymmetric causality test. 5. conclusion in this study, the relationship between brent crude oil prices and stock prices is analyzed using the january 2010-december 2019 period data for brics-t countries. symmetric and asymmetric causality tests were used to compare the causality results of the relationships between variables. according to the asymmetric causality results, the results are as follows: (i) asymmetric causality relationship from oil price to stock price; brazil, and the positive shock for turkey, india and china relations said to have been detected in both positive and negative shocks. (ii) an asymmetric causality relationship from the stock price to the oil price was determined among the positive shocks in russia, while it was determined among the negative shocks in india and china. as a result, considering that the responses of economic variables to positive and negative shocks may be different, it is observed that symmetrical tests are insufficient in revealing the causality relationships between variables such as oil prices and stock prices. in this case, a test that can distinguish the responses of variables to economic shocks should be used. therefore, using asymmetric tests instead of symmetric tests in economic and financial time series where volatility is high is of great importance in order to obtain more reliable results. the combination of symmetric and asymmetric causality test to compare the results in the study separates the study from the existing studies in the literature. this situation can be seen as a positive contribution of the study to the literature. references al-fayoumi, n.a. (2009), oil prices and stock market returns in oil ımporting countries: the case of turkey, tunisia and jordan. european journal of economics, finance and administrative sciences, 16(1), 84-98. al-hajj, e., al-mulali, u., solarin, s.a. (2018), oil price shocks and stock returns nexus for malaysia: fresh evidence from nonlinear ardl test. energy reports, 4, 624-637. alzyoud, h., wang, e.z., basso, m.g. (2018), dynamics of canadian oil price and its ımpact on exchange rate and stock market. international journal of energy economics and policy, 8(3), 107-114. arouri, m.e.h., rault, c. (2012), oil prices and stock markets in gcc countries: empirical evidence from panel analysis. international journal of finance and economics, 17(3), 242-253. awartani, b., maghyereh, a.i. (2013), dynamic spillovers between oil and stock markets in the gulf cooperation council countries. energy economics, 36, 28-42. basher, s.a., haug, a.a., sadorsky, p. (2018), the ımpact of oil-market shocks on stock returns in major oil-exporting countries. journal of international money and finance, 86, 264-280. basher, s.a., sadorsky, p. (2006), oil price risk and emerging stock markets. global finance journal, 17(2), 224-251. benkraiem, r., van hoang, t.h., lahiani, a., miloudi, a. (2018), crude oil and equity markets in major european countries: new evidence. economics bulletin, 38(4), 2094-2110. broadstock, d.c., wang, r., zhang, d. (2014), direct and ındirect oil shocks and their ımpacts upon energy related stocks. economic systems, 38(3), 451-467. chen, s.s. (2010), do higher oil prices push the stock market into bear territory? energy economics, 32(2), 490-495. cong, r.g., wei, y.m., jiao, j.l., fan, y. (2008), relationships between oil price shocks and stock market: an empirical analysis from china. energy policy, 36, 3544-3553. cunado, j., de gracia, f.p. (2014), oil price shocks and stock market returns: evidence for some european countries. energy economics, 42, 365-377. degiannakis, s., filis, g., floros, c. (2013), oil and stock returns: evidence from european ındustrial sector ındices in a time-varying environment. journal of international financial markets, institutions and money, 26, 175-191. filis, g. (2010), macro economy, stock market and oil prices: do meaningful relationships exist among their cyclical fluctuations?. energy economics, 32(4), 877-886. filis, g., chatziantoniou, i. (2014), financial and monetary policy responses to oil price shocks: evidence from oil-importing and oilexporting countries. review of quantitative finance and accounting, 42(4), 709-729. filis, g., degiannakis, s., floros, c. (2011), dynamic correlation between stock market and oil prices: the case of oil-importing and oil-exporting countries. international review of financial analysis, 20(3), 152-164. gay, r.d. jr. (2008), effect of macroeconomic variables on stock market returns for four emerging economies: a vector regression model for brazil, russia, india, and china. florida: nova southeastern university. granger, c.w., yoon, g. (2002), hidden cointegration. university of california san diego. economics working paper series, no. 2. p1-48. granger, c.w., yoon, g. (2002), hidden cointegration. university of california, economics working paper, no. (2002-02). hacker, r.s., hatemi, j.a. (2006), tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application. applied economics, 38(13), 1489-1500. hacker, s., hatemi, j.a. (2012), a bootstrap test for causality with endogenous lag length choice: theory and application in finance. journal of economic studies, 39(2), 144-160. hamilton, j.d. (1983), oil and the macroeconomy since world war ii. journal of political economy, 91(2), 228-248. hamma, w., jarboui, a., ghorbel, a. (2014), effect of oil price volatility on tunisian stock market at sector-level and effectiveness of hedging strategy. procedia economics and finance, 13, 109-127. hatemi, j.a. (2012), asymmetric causality tests with an application. empirical economics, 43(1), 447-456. henriques, i., sadorsky, p. (2008), oil prices and the stock prices of alternative energy companies. energy economics, 30(3), 998-1010. maghyereh, a. (2004), oil price shock and emerging stock markets: a generalized var approach. international journal of applied econometrics and quantitative studies, 1(2), 27-40. miller, j.i., ratti, r.a. (2009), crude oil and stock markets: stability, ınstability, and bubbles. energy economics, 31(4), 559-568. narayan, p.k., gupta, r. (2015), has oil price predicted stock returns for over a century? energy economics, 48, 18-23. narayan, p.k., sharma, s.s. (2014), firm return volatility and economic gains: the role of oil prices. economic modelling, 38, 142-151. ono, s. (2011), oil price shocks and stock markets in brics. the european journal of comparative economics, 8(1), 29-45. papapetrou, e. (2001), oil price shocks, stock market, economic activity and employment in greece. energy economics, 23(5), 511-532. park, j., ratti, r.a. (2008), oil price shocks and stock markets in the us and 13 european countries. energy economics, 30(5), 2587-2608. abubakirova, et al.: relationship between oil prices and stock prices ın brics-t countries: symmetric and asymmetric causality analysis international journal of energy economics and policy | vol 11 • issue 3 • 2021148 phan, d.h.b., sharma, s.s., narayan, p.k. (2015), oil price and stock returns of consumers and producers of crude oil. journal of international financial markets, institutions and money, 34, 245-262. sadorsky, p. (2001), risk factors in stock returns of canadian oil and gas companies. energy economics, 23(1), 17-28. syzdykova, a. (2018), the relationship between the oil price shocks and the stock markets: the example of commonwealth of ındependent states countries. international journal of energy economics and policy, 8(6), 161-166. syzdykova, a., azretbergenova, g., massadikov, k., kalymbetova, a., sultanov, d. (2020), analysis of the relationship between energy consumption and economic growth in the commonwealth of ındependent states. international journal of energy economics and policy, 10(4), 318-324. takashi, k., bong-soo, l. (1995), relative ımportance of economic factors in the us and japanese stock markets. journal of the japanese and international economies, 9(3), 290-307. tsai, c.l. (2015), how do us stock returns respond differently to oil price shocks pre-crisis, within the financial crisis, and post-crisis? energy economics, 50, 47-62. wang, y., wu, c., yang, l. (2013), oil price shocks and stock market activities: evidence from oil-ımporting and oil-exporting countries. journal of comparative economics, 41(4), 1220-1239. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 4 • 2021 75 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(4), 75-83. world oil price shocks in macroeconomic asean +3 countries: measurement of risk management and decision-making a linear dynamic panel approach anuar sanusi1, faurani santi singagerda2*, ahmad zaharuddin sani3 1faculty of economics and business, darmajaya institute of informatics and business, lampung, indonesia, 2faculty of economics and business, darmajaya institute of informatics and business, lampung, indonesia, 3school of languages civilization and philosophy, universiti utara malaysia, malaysia. *email: fsingagerda@gmail.com received: 05 february 2021 accepted: 21 april 2021 doi: https://doi.org/10.32479/ijeep.11249 abstract the increase in oil prices in the 1970s has had a quite significant impact over the decades since the rise in inflation has had an impact on hyperinflation, recession, lowered productivity and economic growth. the world bank (2021) forecasts that oil prices will exceed us$44 per barrel in 2021 and us$50 per barrel in 2022, while several factors affect the world bank’s projections, including the persistence of economic issues in the coming years. the purpose of this paper was to empirically assess the impact of oil prices on asean+3 inflation and economic growth. the framework that can be applied to linear dynamic panel data to achieve this goal is the first difference-generalized moment method (fd-gmm) estimator method. this study used panel data representing asean+3 countries and annual data over the period 2011-2020. the findings of the study indicated that, over the period, increasing oil prices were associated with higher inflation, and higher economic growth in asean+3. another result was that higher inflation is related to lower economic growth. lower and higher economic growth was related to decreased inflation. high inflation creates high costs of economic development and social prosperity, therefore that policymakers are expected to adopt policies that are not only good for the short term, but also good for the long term to establish long-term prosperity and long-term price stability. in addition, a variety of non-economic variables that affect global market price volatility should also be considered to reduce potential market risks. keywords: oil price shock, inflation, production growth, economic development, econometrics jel classifications: e31, e42, e63, f43, f62 1. introduction energy plays an important and strategic role since it is an essential part of the circulation of the world’s economy. petroleum, as one of the world’s energy sources, has been the energy with the highest level of consumption for the production process relative to other sources. the impact of rising world oil prices on inflation and economic growth at the beginning of the 1970s differed from those of the 2000s. in the 1970’s, rising oil prices lead to high inflation, depression, low productivity and low or negative growth rates. the increase in oil prices in the early 2000s led to an increase in inflation, but was relatively much smaller than in the 1970s, and global economic growth remained strong (unalmis et al., 2010; blanchard and riggi, 2013; baffes et al., 2015). study findings from (du et al., 2010; basher et al., 2012; mohaddes and pesaran, 2016) concluded that the increase in oil prices is related positively to output and inflation in china and indonesia. the contribution of oil demand in asean countries to total world is quite large, that is 32% in 2018, while the contribution of production to global production is quite low, and that is 7.4% (pratiwi et al., 2020). during 2011-2020, the average growth in oil consumption in asean countries has been 5.3% per year, while the average growth in oil production (supply) was only 0.5% per this journal is licensed under a creative commons attribution 4.0 international license sanusi, et al.: world oil price shocks in macroeconomic asean +3 countries: measurement of risk management and decision-making a linear dynamic panel approach international journal of energy economics and policy | vol 11 • issue 4 • 202176 year (https://www.cnbcindonesia.com/news/ 2018071018024616-22880/largest-oil-importer-country-in-southeast asia, retrieved 12/11/2020). it means that there is a discrepancy of 2% per year between demand and oil production. increasing oil consumption without sufficient oil supplies would increase the reliance of asean countries on oil, especially asean 3+ (indonesia, malaysia, and singapore). the excessive dependence of asean+3 countries on oil products would be detrimental to the countries in the region, particularly if there is a high enough increase in oil prices. this also contributes to the financial condition of the asean + 3 regions, which is still emerging and which, of course, requires a lot of resources. in addition, the existence of asean+3 economic integration, such as the asean economic community (asean economic community) in 2015, has triggered economic shocks in a country that may have an effect on other countries in the region (figure 1). the objective of this study is to examine the impact of global oil price shocks on inflation and economic growth in asean+3 countries and the impact of inflation on economic growth and the impact of economic growth on inflation in asean+3 countries; inflation in the previous year in asean+3 countries and the impact of economic growth in the previous year on economic growth in asean+3 countries. 2. literature review research conducted by aisen and veiga (2007); nyangarika and tang (2018); bala and chin (2018) have shown that the annual change in oil prices has a positive and statistically significant impact on inflation. in addition, foreign trade, which is a percentage of gdp, has a positive coefficient indicating that the greater the rate of openness to trade causes higher inflation. as far as economic performance is concerned, the results are as expected: real gdp growth, the real effective exchange rate has a negative effect. this is consistent with the intuition that inflation is associated with low growth and undervalued currency values. real currency devaluation reduces inflation. the marginal effect of real gdp growth per capita and u.s. treasury bill rates is higher. inflation increases when treasury bill rate increases by 1% (mishkin, 2004). the positive impact of the global oil price shocks in indonesia (apriani, 2007) on output inflation, real exchange rates, and money supply also occurred in the asean countries (basnet and upadhyaya, 2015: dahalan et al. 2015; kisswani, 2016) using the var approach, as well as the positive impact of the increase in oil prices due to the asymmetrical effect. projections by dahalan et al. (2015) also indicate that gdp responds adversely to increasing oil prices in the long run without having substantial short-term growth. while malaysia and indonesia are developing and exporting oil, while singapore has a fast-growing oil refining industry, their contribution to the economy is relatively small, this means that the windfall revenues from the oil sector that indonesia and malaysia are earning will not be adequate to support the economic slowdown experienced by their neighbors and major trading partners. olomola et al. (2006); iwayemi and fowowe (2011) conducted researches on the effect of world oil price shocks on inflation, output, real exchange rates, and the money supply in nigeria using the vector auto-regression (var) method. the research used quarterly data from 1970 to 2003. the findings suggested that global oil price shocks have a major influence on the actual exchange rate, but do not affect nigeria’s production and inflation. in contrast, it has been observed that the increase in world oil prices has strengthened people’s welfare (zaouali, 2007). this is due to the appreciation of the real exchange rate in nigeria, which has an impact on the trade sector. using longer time periods and different countries, salman et al. (2008) examined the short-term effect of changes in oil prices on the business cycle of the g-7 countries just using the co-integration test and the granger causality test. the data used was quarterly data for the period 1970: 1–2006: 4. several facts have been established in this study: there is a short-term neutrality of real gdp as a consequence of shifts in oil prices in italy, japan and the united kingdom. however, oil has had a real impact on economies of other g7 countries, particularly germany and france. on the other hand, adjustments in government policies have played an important role in reducing the impact of high oil prices in japan, italy and france. in addition, the characteristics of the economies of the united states, the united kingdom, germany and canada have influenced the role of oil impact in their business cycle. these differences suggest that fluctuations in oil prices have a time effect on the business cycle in several g-7 economies (salman et al. 2008; cologni and manera, 2009; engemann et al., 2010; lee et al. 2012; baffes et al. 2015; sato et al. 2011; dungey and vehbi, 2015; mohaddes and pesaran, 2016; jan van de ven and fouquet (2016) found that global oil price shocks are increasingly important to the stability of real market growth in a number of countries. it reflects an increase in reliance on world oil supplies associated with industrialization in these countries. even the findings of sato et al. (2011); found that the variance decomposition of suggests that global oil price shocks are a major cause of price volatility in most economies, followed by a shock to the united states. china’s impact on domestic price levels is constant and is largely recorded in hong kong, reflecting the high degree of economic convergence between the two economies. ftiti et al. (2016) found that oil price shocks in periods of volatility in the global business cycle and/or financial turmoil have had an influence on the association between oil and economic figure 1: world consumption and oil production by region 2018 source: eia, 2020 retrieved from https://www.eia.gov/international/ data/world/petroleum-and-other-liquids/annual-petroleum-and-otherliquids-production? sanusi, et al.: world oil price shocks in macroeconomic asean +3 countries: measurement of risk management and decision-making a linear dynamic panel approach international journal of energy economics and policy | vol 11 • issue 4 • 2021 77 development in opec countries. kurihara (2015) discussed the relationship between the price of oil and economic growth. their research examined the impact on the economy differed for oilimporting countries. meanwhile, the oil price shocks of berument et al. (2010) do not appear to have a statistically significant impact on the production of bahrain, djibouti, egypt, israel, jordan, morocco and tunisia. in accordance with this, ahmed (2016) found in his study not all countries would have a positive impact of oil prices on growth and development. in his research in middle east and north african (mena) countries, the mena region is vulnerable to shifts in oil prices only because certain member countries are the major producers and exporters most likely to be impacted by the decline in oil prices because most of their income comes from oil exports. meanwhile, other member countries are oil importers which may benefit from lower oil prices as substitutes for the production of some products but may have a negative impact in the form of reduced remittances, foreign aid, and foreign direct investment as a result of lower revenues from oil exporting countries due to lower prices lardic and mignon (2006); mehrara (2008); mendoza and vera (2010); çatik and önder (2013); serletis and istiak (2013); moshiri (2015); charfeddine and barkat (2020); jibril et al. (2020) have demonstrated that oil price shocks are asymmetrical in that positive and negative shocks to oil prices of the same size may have different consequences on the country’s economic development. study results by fischer et al. (2002); haider et al (2012); hourcade et al.(2014) reported that: higher inflation tends to be more volatile; in high inflation countries, there is a strong relationship between fiscal balance and seigniorage in both the short and long term; inflation inertia is decreasing with increasing average inflation; and high inflation is related to weak macroeconomic efficiency. meanwhile jha and dang (2012), barro (2014), mohseni and jouzaryan (2016) concluded that high inflation had a negative and significant impact on economic growth. the results of a study by gylfason and herbertsson ( 2001), arai et al. (2004), gokal and hanif (2004), baharumshah et al. (2016), ben s. bernanke, thomas laubach, frederic s. mishkin (2018) show that there is no evidence to support the view that inflation is generally injurious to gdp growth. on the other hand, there is a negative correlation between intra-country inflation and development over the period under study due to the positive oil price shock of kim and hammoudeh (2013). meanwhile, aisen and veiga (2013), nguyen et al. (2015) analyzed the role of political instability on economic growth using the system-gmm estimator for dynamic data panel models. the findings indicate that high inflation has a negative and statistically significant impact on growth. 3. research method the type of research used in this study is exploratory. the data obtained is panel data, which is a combination of annual time series data for the period 2009-2018 and cross-section data from asean+3 countries. asean+3 countries included in the study include indonesia, malaysia, the philippines, singapore, thailand, china, japan and south korea. this study uses a dynamic panel analysis method, called the first differences-generalized moments method (fd-gmm) (table 1). the advantage of the use of annual data is as continues to follow: (1) information on the variation of the period used for the estimation; (2) it is important to measure the consistency of the predicted parameters over time (3) the dynamic structure of the problem can be analyzed using the lag variable. the reasons for selecting asean+3 countries are partially due to the fact that the economic conditions of these countries were diverse and divided into developed and developing countries. it is expected that the impact of global oil price shocks will be observed across countries with different per capita incomes (zaouali, 2007; kurihara, 2015). moreover, the reason for selecting these countries though is that opec supplies asia to the most oil compared to other regions of the world (ftiti et al., 2016). asia is expected to see the fastest increase in oil demand in the world. from opec’s forecast of world oil demand, this rising need is mainly in developing countries, two-thirds of which are asian countries based on previous research, the specification of the dynamic panel model to be used in this study refers to the model (aisen and veiga, 2008; 2013), i.e.: ln yi,t = β ln yi,t-1 + λ xi,t + νi + εi,t (1) d.ln yi,t = β d.ln yi,t-1 + λ d.xi,t + dεi,t (2) and for inflation model (eq. 1), the dependent variable is the consumer price index (cpi) as well as the vector x is the variable that affects inflation. for the economic growth model (eq. 2), the dependent variable is gdp and the vector x is the variable that influences economic growth. based on the considerations of several previous studies, the model specifications in this analysis can be seen in the following two equations: 1. the inflation model; the influence of global oil prices on inflation applies to the modified aisen and veiga (2008) models: d.cpiit = β1d.cpii, t-1 + β2d.opiit + β3d.gdpit + β4d.ririt + β5d.tit + d.eit (3) this model uses a variable instrument for the contribution of the agricultural sector to gdp and industry variables for the contribution of the sector to gdp. table 1: data and data sources used in research variables units sources world oil prices (opi) us $ per barel ifs consumer price indeces (cpi) 2012=100 wdi real gdp (gdp) international $ (ppp 2012=100) wdi real interest rates (rir) percentage wdi trade openess (t) percetage wdi middle school enrollment (edu) percentage wdi sources: international financial statistics (2018), world development index (2019) sanusi, et al.: world oil price shocks in macroeconomic asean +3 countries: measurement of risk management and decision-making a linear dynamic panel approach international journal of energy economics and policy | vol 11 • issue 4 • 202178 2. global economic growth model; the impact of world oil prices on economic growth refers to the modified model of aisen and veiga (2013) d.gdpit = β1d.gdpi, t-1 + β2d.opiit + β3d.cpiit + β4d.eduit + d.eit (4) the model uses the foreign direct investment instrument (fdi) and the contribution of the industrial sector to gdp. note: cpi = log consumer price index (2005 = 100) d = first difference operator edu = education level (percentage) gdp = log real gdp (international 2005 ppp $ = 100) opi = log average world price of crude oil (us $ per barrel) rir = real interest rate (percentage) t = trade (percentage of gdp) e = error it = country i, year t. 4. results and discussions based on the results of the dynamic panel estimation with fdgmm, the first lag of the dependent variable (previous year inflation) has a positive but not statistically significant coefficient. this indicates that there is no persistent inflation (arellano and bover, 1995; aisen and veiga, 2013). the insignificant dependent lag also means that current inflation is not affected by previous inflation (backward-looking) but is influenced by inflation expectations (forward looking). this also shows the progress of the monetary authorities in the asean + 3 region in resolving the inflation crisis. meanwhile, economic growth has a negative and significant inflation coefficient. each 1% increase in economic growth would result in a 1.32% decline in inflation, ceteris paribus. according to fischer et al. (2002), and hourcade et al. (2014) high inflation is also characterized by a reduction of gdp levels where high inflation is correlated with low macroeconomic results. changes in the world price index of crude oil have a positive and significant effect on inflation. every 1% increase in the rate of change in oil prices would result in an inflation increase of 0.0553%, ceteris paribus. that because the increase in oil prices has led to an increase in manufacturing costs and prices (cost push inflation). an increase in the price of oil can lead to an increase in the prices of other goods. when there is an increase in the price of oil, not only will the price of fuel increase, but the price of goods and services related to fuel oil will also increase (jha and dang, 2012; barro, 2014; mohseni and jouzaryan, 2016). as a result, inflationary pressures may be intensified if the rise in fuel prices increased or the price of other goods, such as food and housing, increased (olomola et al., 2006). the high price of oil in recent years has also encouraged the development of biofuel production as an alternative energy source (singagerda et al., 2018). it led to a shift in the use of a large number of commodities that were initially used only as food to become raw materials for the biofuel industry (such as palm oil, corn, wheat, soybeans) which, in turn, caused price increases (farida and santi singagerda, 2021). the condition is consistent with the implementation of policies and targets for aggressive conversion of resources to biofuels by various countries. the increase in energy prices has contributed to an increase in the fiscal deficit. one of the determinants of inflation is the consequence of fiscal imbalances where the fiscal deficit is the amount of seigniorage and borrowing (fischer et al., 2002 ; haider et al., 2012); hourcade et al. (2014). therefore, the relationship between deficit and inflation derives from the relationship between seigniorage and inflation. according to fischer et al. (2002); haider et al. (2012); mohaddes and pesaran (2017) in high inflation countries, there is a strong relationship between fiscal stability and seigniorage in both the short and long term. luis catão (2001); (mishkin, 2004); fakher (2016), found that there is a strong positive relationship between fiscal deficits and inflation among high inflation groups in developing countries, but not in developed countries with low inflation. estimates suggest that changes in real interest rates have a negative but insignificant impact on inflation. each 1% increase in the rate of change in real interest rates will affect prices to decline by 0.0032%, ceteris paribus. higher interest rates would reduce investment, shifting the aggregate demand curve to the left and, in turn, lower interest rates, and vice versa (table 2). changes in trade openness have a negative however insignificant effect on inflation. every 1% increase in the rate of change in trade openness would affect prices to decline of 0.0002%, ceteris paribus. the implication is that countries that are open to international trade are more likely to raise funds through import duties and are less dependent on seigniorage income and furthermore reduce inflation (aisen and veiga, 2008; özşahin and üçler, 2017; alam et al., 2019). based on the estimation of the results in table 3 of the fd-gmm dynamic panels, the first lag of the predictor variables (previous year’s economic growth) has a positive but not significant coefficient. it shows that the economic growth of asean+3 is not influenced by the economic growth of the previous year. table 2: estimation of inflation model coefficient variables1) twostep twostep‑robust2) ∆ln_cpi l1 0.6252 0.6252 (0.4203) (0,3847) ∆ln_gdp −1.3241*** −1,3241*** (0.5140) (0.5067) ∆ln_opi 0.0553*** 0.0553*** (0.0134) (0.0148) ∆rir −0.0032* −0.0032 (0.0019) (0.0020) ∆openness −0.0002** −0.0002 (0,0001) (0.0004) wald test 31.45 [0.0000] 40.16 [0.0000] arelano-bond m1 −2.4853 [0.0129] −2.6582 [0.0079] arelano-bond m2 −1.4107 [0,1583] −1.3815 [0.1671] sargan test 1.4940 [1,0000] **significant at the 1% actual level, **significant at the 5% actual level, *significant at 10% of the actual level. (1) dependent variable: ∆ln_cpi, (2) two-step robust results using a robust standard error that is corrected for limited samples (bun and windmeijer, 2010). sources: arellano and bover, 1995; aisen and veiga, 2013 sanusi, et al.: world oil price shocks in macroeconomic asean +3 countries: measurement of risk management and decision-making a linear dynamic panel approach international journal of energy economics and policy | vol 11 • issue 4 • 2021 79 inflation is creating a negative and significant impact on economic growth. each 1% increase in inflation would lead to a 0.7027% decline in economic growth, ceteris paribus. high inflation, as economists recognize, has a negative effect on economic growth and social welfare (rousseau and wachtel, 2011; ftiti et al., 2016). high inflation triggers high social costs to be paid by governments, businessmen and society (friedman, 2017; özşahin and üçler, 2017). the social cost consists of the cost of shoe leather, the cost of the menu, the volatility of relative costs, the distorted tax rates and the inconvenience of living with shifting prices (mankiw, 2012). an increase in the price level would reduce the stock of real capital, which in turn contributes to a decrease in demand and output. in general, inflation increases the cost of production and transport and reduces people’s purchasing power, which has a negative impact on the economy. according to lardic and mignon (2006); mehrara (2008); mendoza and vera (2010); çatik and önder (2013); serletis and istiak (2013); moshiri (2015); charfeddine and barkat (2020); jibril et al. (2020), which concluded that inflation uncertainty has contributed to a three-month decline in output growth. inflation may also have a positive impact on output growth. it occurs when inflation tends to be small, around 2 or 3% per year, regardless of inflation, it can allow the labor market work better. without inflation, real wages would be pushed above the level of equilibrium leading to higher unemployment (mankiw, 2012). the rate of change in the oil price index has a positive and significant impact on economic growth. each 1% increase in the rate of change in oil prices would result in an increase in economic growth of 0.0686%, ceteris paribus (figuer 2). it is also in line with the studies by du et al. (2010); basher et al. (2012); mohaddes and pesaran (2016), which concluded that the increase in oil prices is related positively to output and inflation in china and indonesia. it is related to an improvement in incomes derived from the export of crude oil and its processed products, an increase in revenue of other commodity exporting countries whose prices are followed by an increase in oil prices, a decline in oil intensity, an increase in aggregate demand and the availability of fuel subsidies in several countries. therefore, thus, the positive impact of oil prices on economic growth is related to an increase in revenues derived from the export of crude oil and its processed products. the increase in oil price also led to an increase in income for other commodity exporting countries whose prices followed table 3: estimation coefficient of the economic growth model variable fd-gmm dynamic models ∆ln_gdp l1 0.0255 (0.1781) ∆ln_cpi −0.0727*** (0.1787) ∆ln_opi 0.0686*** (0.0104) ∆edu 0.0006*** (0.0009) wald’ test 65.64 [0.0000] arelano-bond m1 −1.9741 [0.0484] arelano-bond m2 0.40639 [0.6845] sargan’s test 4.613979 [1,0000] ***significant at the 1% actual level, **significant at the 5% actual level, *significant at 10% of the actual level. sources: arellano and bover, 1995; aisen and veiga, 2013 figure 2: changes in oil prices and inflation in asean + 3 countries (2009-2020) source: imf1, eia2 (2020) the increase in oil prices (figure 3). the growth in exports, in particular, has an effect on the economic growth of the country concerned. the asean region itself is the largest supplier of a number of important world food commodities, including rice and palm oil. approximately 90% of total of rice is produced in the asian region and mostly in asean countries. exports of milled rice in thailand increased from us$ 2.701 million in 2009 to us$ 6.359 million in 2018, while china increased from us$ 719.58 million in 2009 to us$ 475.768 million in 2018. based on the asean trade database, in 2019, rubber and rubber products were among the top ten asean traded commodity groups with an export value of us$21,844 million, with an import value of us$8,597 million. indonesia and malaysia are the largest producers of palm oil in the world, and therefore increase in world oil prices has an effect on the amount in the volume of exports within these countries. table 4 reveals that malaysia’s palm oil exports increased from us$4,738 million in 2009 to us$14,768 million in 2018, or almost 2.5 times higher. indonesia’s palm oil exports increased from us$2.114 million in 2009 to us$13.576 million in 2018, or 10-fold. meanwhile, singapore’s palm oil exports improved by 100% from us$ 276 million in 2009 to us$ 361 million in 2018. indonesia and thailand reported for both the main exports of rubber/rubber nat dry (singagerda et al., 2018; alam et al., 2019).12 developing energy intensity, which is the ratio of energy consumption to gdp in china, is much lower than in previous decades. from 1990 to 2018, china’s energy intensity declined sharply by 55.4% from 43,084.41 btu per gdp dollar to 10,457.42 btu per gdp dollar. this increase of energy consumption is due to energy conservation as a result of growing energy prices in the 1970s and1980s, including energy crisis in mid of 2000s (cabral, 2002; mirchi et al., 2012). however, china’s energy intensity is still higher than other asean+3 countries. it is because china is an industrial country that also needs a lot of energy. during the period 2009-2018, almost all asean+3 countries experienced a decline in intensity, including indonesia, malaysia and thailand, which were classified as asia’s largest palm oil export countries (desfiandi et al., 2019). as a consequence of sustainable economic and population growth, electrification, industrialization and 1 https://data.imf.org/?sk=388dfa60-1d26-4ade-b505-a05a558d9a42 &sid=1479329334655 2 https://www.eia.gov/petroleum/data.php#prices https://data.imf.org/?sk=388dfa60-1d26-4ade-b505-a05a558d9a42&sid=1479329334655 https://data.imf.org/?sk=388dfa60-1d26-4ade-b505-a05a558d9a42&sid=1479329334655 sanusi, et al.: world oil price shocks in macroeconomic asean +3 countries: measurement of risk management and decision-making a linear dynamic panel approach international journal of energy economics and policy | vol 11 • issue 4 • 202180 urbanization, asean’s energy demand will more than triple during 2010-2035, creating tremendous pressure on energy supply and security (shi, 2015). meanwhile, oil intensity, which is the ratio of oil consumption per dollar of gdp (btu per gdp constant at the 2005 international dollar ppp) has decreased in almost all asean+3 countries over the last 10 years. it indicates that there is public awareness of the consumption of petroleum per unit of output. singapore has the highest oil intensity, far above other asean+3 countries (figure 4). one of the factors behind the decline in oil intensity is the effort to reduce oil consumption and the technological changes that play a role in the business so that it is no longer too disrupted by the increase in oil prices, which is actually more servicebased (baumeister and peersman, 2013; shi, 2015). in general, the service industry requires less energy to produce than the manufacturing sector. therefore, even though the price of oil is rising, its impact on the macroeconomics at this time would be smaller. the use of fuel oil is increasingly widespread in developing countries due to the strengthening of economic growth, expanded use of transport and the development of industrial activities. increased industrial activity eventually led to increased economic growth. the contribution of asean + 3 countries to gdp in the industrial sector has seen positive average annual growth since 2009 to 2018. japan experienced an average annual growth rate of 1.2% per year, followed by the philippines and indonesia at 4.5% per year. malaysia, singapore, thailand and south korea had an average growth rate of 5.1%, 5.2%, 6.1% and 6.8% respectively. china is an asean+3 country with the highest annual average growth rate of 10% (eia, 2019). the improvement in aggregate demand also plays a role in increasing economic growth, so that the increase in oil prices, which has an effect on inflation, is not accompanied by a decline in economic growth as in the 1970s (jan van de ven and fouquet, 2016). the economic structure of asean+3 countries dominated by consumption is increasing aggregate demand, which in turn would increase economic growth. almost all asean+3 countries have economic structures driven by consumption (lescaroux and mignon, 2008; dahalan et al., 2015; pratiwi et al., 2020). the increase in world oil prices would also trigger an increase in domestic goods prices, as most domestic firms also use oil as raw material for production. the increase in world oil prices would also result to an increase in domestic goods prices, as most domestic companies also use oil as raw material for production (aisen and veiga, 2007; salman et al., 2008; basher et al., 2012; baffes et al., 2015; baharumshah et al., 2016; jan van de ven and fouquet, 2016; alam et al., 2019). the impact on domestic goods prices would cause the real domestic exchange rate to depreciate against the us dollar. the depreciating domestic exchange rate makes domestic goods more competitive than foreign goods, increasing net exports. this raise in net exports will further improvement domestic production. under the free-floating exchange rate regime, the exchange rate is allowed to float according to the market mechanism (kisswani, 2016). the nominal exchange rate in a country would be largely determined by the supply and demand of domestic exchange rates on the foreign exchange market (olomola et al., 2006; iwayemi and fowowe, 2011; basher et al., 2012; kisswani, 2016). the strength of the exchange rate in the forex market is ultimately determined by the scale of the economy of the country. if the economy tends to be a small open economy, exchange-rate figure 4: development of the crude oil intensity of asean + 3 countries 2009-2018 source: eia, 2019 retrieved from https://www.eia.gov/international/ data/world/petroleum-and-other-liquids/annual-petroleum-and-otherliquids-production? figure 3: contribution of the consumption and production of oil of asean+3 countries to the world in 2008 source: eia, 2020 retrieved from https://www.eia.gov/international/ data/world/petroleum-and-other-liquids/annual-petroleum-and-otherliquids-production? table 4: exports of crude oil and processed petroleum products from asean+3 countries in 2010 and 2018 countries crude oil exports products export of processed petroleum 2009 2017 2009 2017 indonesia 372 337 16 23 malaysia 344 390 46 59 the philippines 20 4.4 25 24 singapore 12 27 771 924 thailand 43 33 24 27 china 102 59 234 285 japan 0 0 87 68 south korea 0 0 153 152 source: eia, 2020 retrieved from https://www.eia.gov/international/data/world/ petroleum-and-other-liquids/annual-petroleum-and-other-liquids-production? sanusi, et al.: world oil price shocks in macroeconomic asean +3 countries: measurement of risk management and decision-making a linear dynamic panel approach international journal of energy economics and policy | vol 11 • issue 4 • 2021 81 fluctuations tend to be more volatile (mankiw, 2012). moreover, whether it is not supported by a strong domestic market structure, high exchange rate volatility seems to depreciate (olomola et al., 2006; iwayemi and fowowe, 2011; basher et al., 2012; mohaddes and pesaran, 2016) the provision of fuel subsidies in many countries also encourages economic development. according to research conducted by resosudarmo (2012); braithwaite et al. (2012); garnaut (2015); (deendarlianto et al. (2017); ramadhan et al. (2019) the policy of subsidizing fuel prices and lng (increase in subsidies and actual subsidies) has contributed to an increase in indonesia’s real gdp, which has also raised the rate of economic growth. it was based on the fact that the value of government spending has increased significantly relative to the value of consumption, investment and net exports. this policy allows customers to purchase more fuel and lng since the market sale price of fuel and lng has decreased (braithwaite et al., 2012). however, according to ramadhan et al. (2019) fuel subsidies are a bad creature because indonesia has a number of other sources of energy. according to him, the issue of fuel subsidies is closely linked to the country’s very high reliance on fuel in its national energy usage, so a step out of the fuel subsidy trap is required. part of the issue of fuel subsidies can be resolved by the implementation of national energy management, which emphasizes the efficiency of fuel consumption and the development of diversification of energy sources, as illustrated by the development of energy installed capacity (braithwaite et al., 2012; ramadhan et al., 2019). the implementation of the policy on fuel subsidies has also caused controversy. on the one hand, subsidies may help to reduce people’s purchasing power, and on the other hand, subsidies program becomes a burden on the government budget (resosudarmo, 2012). the distribution of subsidies should take into account precisely those most in need of assistance and their economic impact on society as a whole. restriction of subsidies will also generate environmental degradation and, if implemented, it would be difficult to eliminate them because they are vulnerable to the development of special interests and dominant rent-seeking behavior (braithwaite et al., 2012; tullock, 2013; kim and hammoudeh, 2013; kurihara, 2015; ramadhan et al., 2019). fuel price incentives are considered insufficient to deal with the impact of rising oil prices, despite that world oil prices are continuously rising. for that kind of reason, shifting price subsidies to direct subsidies is one of the targets for the energy mix in indonesia. meanwhile, the result also shows that the rate of change in the standard of education has a positive but insignificant impact on economic growth. every 1% increase in the rate of change in oil prices would lead to an increase in economic growth of 0.0006%, ceteris paribus. the research also indicates that an increase in the level of education suggests an increase in human capital, which in turn generates the productivity of the workforce and subsequently increase economic growth. 5. conclusion annual average oil prices increased significantly during the years 2009-2018, an increase of 32.47% per year. in the same time, the average inflation and economic growth in the asean+3 countries show that each growth in 3.31%. in addition, there was a rise in world oil prices, generally followed by an increase in inflation in the respective asean+3 countries, except indonesia in that periods. this is related to the implementation of very high subsidies for fuel prices in indonesia. meanwhile, so many other countries have introduced a fuel tax in order to match the increase in world oil prices. the objective of implementing subsidies is to reduce the effect of increasing inflation, while introducing fuel taxes would have an impact on inflation. the study results show that the relationship between world oil prices and economic development in many asean+3 countries is generally positive except in japan, the philippines and thailand. it indicates that the huge increase in world oil prices is not always accompanied by negative economic growth. similarly, there is a positive relationship between world oil prices and economic development in, among others, indonesia and malaysia, since both countries are exporters of crude oil and its processed products. in contrast, the research also found that the significant increase in the rate of change in world oil prices triggers inflation in asean+3 countries. it was related to the reasons that asean+3 countries do not generally subsidize fuel prices. an increase in oil prices may also result in an increase in the prices of other goods, such as the price of fuel oil goods and services, and an increase in the prices of other commodities (rice, rubber, palm oil, coffee, gold, silver, coal, natural gas, and other mining materials). the high price of oil has also promoted the growth of biofuel production as a renewable energy source. the change in the use of a large number of commodities originally used only as food to become raw materials for the biofuel industry (e.g. palm oil, corn, wheat, soybeans) has eventually contributed to price increases. moreover, the increase in oil prices also contributes to an increase in the fiscal deficit where one of the factors of inflation is the result of a fiscal imbalance. the role of the government in the distribution of targeted incentives (subsidies), the implementation of fuel taxes, and the regulation of the monopoly system in energy sectors. in this study, it is known that the increase in the rate of change in world oil prices has led significantly to economic growth in asean+3 countries. these are related to an improvement in income earned from the export of crude oil and its processed products, an increase in incomes of other commodity exporting countries whose prices were followed by an increase in oil prices and a decrease in oil intensity. the decline in oil intensity is related to initiatives to reduce oil consumption and technological changes that play a role in the economy so that rising oil prices are no longer too disrupted. today’s economy is more service-based, not manufacturing-based. in particular, the service industry consumes less energy to produce than the industrial sector. the growth in aggregate demand also plays a role in increasing economic growth, so that the increase in oil prices, which has an impact on inflation, is not accompanied by a decline in economic growth as in the 1970s. the increase in aggregate demand was due to the economic structure of asean+3 countries, which was dominated by demand and higher exports due to the depreciating domestic exchange rate, which made domestic sanusi, et al.: world oil price shocks in macroeconomic asean +3 countries: measurement of risk management and decision-making a linear dynamic panel approach international journal of energy economics and policy | vol 11 • issue 4 • 202182 goods more competitive than foreign goods. economic growth has a negative and significant effect on inflation. high inflation is also characterized by a contraction in gdp where high inflation is associated with poor macroeconomic performance. besides that, inflation has a disruptive and significant effect on economic growth. high inflation is having a negative impact on economic growth and social security. high inflation induces high social costs to be paid by governments, businessmen and society. an increase in the price level would reduce the stock of real money, which in turn contributes to a decrease in demand and output. in general, inflation increases the cost of produce and transport and decreases people’s purchasing power, which has a negative impact on the economy. inflation and economic growth have been positively affected by inflation and economic growth in the previous year, but not significantly in asean+3 countries it implies that there is no persistent inflation, the insignificance suggests that current inflation is not influenced by inflation in the previous year (backward-looking), but is influenced by inflation expectations (forward-looking). however, to assess market risk due to world price volatility, multiple proxies, particularly those with current issues other than economic phenomena, for including the global pandemic that attacked most of the world’s economic market activities in early 2020 also need to be considered in further study. references aisen, a., veiga, f.j. (2007), does political instability lead to higher and more volatile inflation? a panel data analysis. panoeconomicus, 54(1), 5-27. aisen, a., veiga, f.j. (2008), the political economy of seigniorage. journal of development economics, 87(1), 29-50. aisen, a., veiga, f.j. (2013), how does political instability affect economic growth? european journal of political economy, 29, 151-167. ali alam, i., singagerda, f.s. (2019), price determination model of world vegetable and petroleum. international journal of energy economics and policy, 9, 7916. apriani, d.k. (2007), analisis dampak guncangan harga minyak dunia terhadap inflasi dan output di indonesia: periode 1990-2006. berlin, germany: international peace bureau. arai, m., kinnwall, m., thoursie, p.s. (2004), cyclical and causal patterns of inflation and gdp growth. applied economics, 36(15), 1705-1715. arellano, m., bover, o. (1995), another look at the instrumental variable estimation of error-components models. journal of econometrics, 68(1), 29-51. baffes, j., kose, m.a., ohnsorge, f., stocker, m. (2015), the great plunge in oil prices: causes, consequences, and policy responses. ssrn electronic journal, 2015, 23611. baharumshah, a.z., slesman, l., wohar, m.e. (2016), inflation, inflation uncertainty, and economic growth in emerging and developing countries: panel data evidence. economic systems, 40(4), 638-657. bala, u., chin, l. (2018), asymmetric impacts of oil price on inflation: an empirical study of african opec member countries. energies, 11(11), 3017. basher, s.a., haug, a.a., sadorsky, p. (2012), oil prices, exchange rates and emerging stock markets. energy economics, 34(1), 227-240. baumeister, c., peersman, g. (2013), the role of time-varying price elasticities in accounting for volatility changes in the crude oil market. journal of applied econometrics, 28(7), 1087-1109. bernanke, b.s., laubach, t., mishkin, f.s., posen, a.s. (2018), inflation targeting: lessons from the international experience. princeton: princeton university press. berument, m.h., ceylan, n.b., dogan, n. (2010), the impact of oil price shocks on the economic growth of selected mena 1 countries. energy journal, 31(1), 149-176. blanchard, o.j., riggi, m. (2013), why are the 2000s so different from the 1970s? a structural interpretation of changes in the macroeconomic effects of oil prices. journal of the european economic association, 11(5), 1032-1052. braithwaite, d., chandra, a., diah, p., ami, r.l., kerryn, i., lucky, l., nataliawati, l., damon, s., bobby, v.d., wattimena, a., widhiantoro, u., wooders, p. (2012), indonesia’s fuel subsidies: action plan for reform. http://www.iisd.org/gsi. [last accessed on 2020 sep 02]. bun, m.j.g., windmeijer, f. (2010), the weak instrument problem of the system gmm estimator in dynamic panel data models. the econometrics journal, 13(1), 95-126. cabral, l. (2002), the california energy crisis. japan and the world economy, 14(3), 335-339. çatik, a.n., önder, a.ö. (2013), an asymmetric analysis of the relationship between oil prices and output: the case of turkey. economic modelling, 33, 884-892. charfeddine, l., barkat, k. (2020), shortand long-run asymmetric effect of oil prices and oil and gas revenues on the real gdp and economic diversification in oil-dependent economy. energy economics, 86, 104680. cologni, a., manera, m. (2009), the asymmetric effects of oil shocks on output growth: a markov-switching analysis for the g-7 countries. economic modelling, 26(1), 1-29. dahalan, j., izraf, m., aziz, a. (2015), oil price shocks and macroeconomic activities in asean-5 countries: a panel var approach. eurasian journal of business and economics, 8(16), 101-120. deendarlianto, widyaparaga, a., sopha, b.m., budiman, a., muthohar, i., setiawan, i.c., lindasista, a., soemardjito, j., oka, k. (2017). scenarios analysis of energy mix for road transportation sector in indonesia. in: renewable and sustainable energy reviews. vol. 70. amsterdam, netherlands: elsevier. p13-23. desfiandi, a., singagerda, f.s., sanusi, a. (2019), building an energy consumption model and sustainable economic growth in emerging countries. international journal of energy economics and policy, 9(2), 51-66. doi: 10.32479/ijeep.7353. du, l., yanan, h., wei, c. (2010), the relationship between oil price shocks and china’s macro-economy: an empirical analysis. energy policy, 38(8), 4142-4151. dungey, m., vehbi, t. (2015), the influences of international output shocks from the us and china on asean economies. journal of asian economics, 39, 59-71. engemann, k.m., kliesen, k.l., owyang, m.t. (2010), working paper series do oil shocks drive business cycles? some u.s. and international evidence do oil shocks drive business cycles? some u.s. and international evidence. available from: http://www. research.stlouisfed.org/wp. fakher, h.a. (2016), the empirical relationship between fiscal deficits and inflation (case study: selected asian economies). iranian economic review, 20(4), 551-579. farida, i., singagerda, f.s. (2021), volatilitiy of world food commodity prices and renewable fuel standard policy. international journal of energy economics and policy, 11(1), 516-527. fischer, s., sahay, r., végh, c.a. (2002), modern hyper and high inflations. journal of economic literature, 40(3), 837-880. friedman, m. (2017), the social responsibility of business is to increase its profits. in: corporate social responsibility. milton park, milton: taylor and francis. p31-35. sanusi, et al.: world oil price shocks in macroeconomic asean +3 countries: measurement of risk management and decision-making a linear dynamic panel approach international journal of energy economics and policy | vol 11 • issue 4 • 2021 83 ftiti, z., guesmi, k., teulon, f., chouachi, s. (2016), relationship between crude oil prices and economic growth in selected opec countries. journal of applied business research, 32(1), 11-22. garnaut, r. (2015), indonesia’s resources boom in international perspective: policy dilemmas and options for continued strong growth. bulletin of indonesian economic studies, 51(2), 189-212. gokal, v., hanif, s. (2004), relationship between inflation and economic growth. working paper no. 2004/04, suva economics department. gylfason, t., herbertsson, t.t. (2001), does inflation matter for growth? japan and the world economy, 13(4), 405-428. haider, a., ud din, m., ghani, e. (2012), monetary policy, informality and business cycle fluctuations in a developing economy vulnerable to external shocks. the pakistan development review, 5(1), 3-17. available from: https://www.jstor.org/stable/23734791?seq=1. hourcade, j.c., aglietta, m., perrissin-fabert, b., hourcade, j.c., aglietta, m., perrissin-fabert, b. (2014), transition to a low-carbon society and sustainable economic recovery, a monetary-based financial device. working paper. iwayemi, a., fowowe, b. (2011), impact of oil price shocks on selected macroeconomic variables in nigeria. energy policy, 39(2), 603-612. jan van de ven, d., fouquet, r. (2016), historical energy price shocks and their changing effects on the economy. energy economics, 62, 204-216. jha, r., dang, t.n. (2012), inflation variability and the relationship between inflation and growth. macroeconomics and finance in emerging market economies, 5(1), 3-17. jibril, h., chaudhuri, k., mohaddes, k. (2020), asymmetric oil prices and trade imbalances: does the source of the oil shock matter? energy policy, 137, 111100. kim, w.j., hammoudeh, s. (2013), impacts of global and domestic shocks on inflation and economic growth for actual and potential gcc member countries. international review of economics and finance, 27, 298-317. kisswani, k.m. (2016), does oil price variability affect asean exchange rates? evidence from panel cointegration test. applied economics, 48(20), 1831-1839. kurihara, y. (2015), oil prices and economic growth in developed countries. international journal of business and social science, 6(11), 1-10. lardic, s., mignon, v. (2006), the impact of oil prices on gdp in european countries: an empirical investigation based on asymmetric cointegration. energy policy, 34(18), 3910-3915. lee, b.j., yang, c.w., huang, b.n. (2012), oil price movements and stock markets revisited: a case of sector stock price indexes in the g-7 countries. energy economics, 34(5), 1284-1300. lescaroux, f., mignon, v. (2008), on the influence of oil prices on economic activity and other macroeconomic and financial variables. opec energy review, 32(4), 343-380. luis catão, m.e.t. (2001), fiscal deficits and inflation a new look at the emerging market evidence. washington, dc: international monetary fund. available from: https://www.papers.ssrn.com/sol3/ papers.cfm?abstract_id=879583. mankiw, n.g. (2012), principles of macroeconomics. boston, massachusetts: south-western cengage learning. mehrara, m. (2008), the asymmetric relationship between oil revenues and economic activities: the case of oil-exporting countries. energy policy, 36(3), 1164-1168. mendoza, o., vera, d. (2010), the asymmetric effects of oil shocks on an oil-exporting economy. cuadernos de economia latin american journal of economics, 47(135), 3-13. mirchi, a., hadian, s., madani, k., rouhani, o.m., rouhani, a.m. (2012), world energy balance outlook and opec production capacity: implications for global oil security. energies, 5(8), 2626-2651. mishkin, f. (2004), can inflation targeting work in emerging market countries? (no. w10646). mohaddes, k., pesaran, m.h. (2016), country-specific oil supply shocks and the global economy: a counterfactual analysis. energy economics, 59, 382-399. mohaddes, k., pesaran, m.h. (2017), oil prices and the global economy: is it different this time around? energy economics, 65, 315-325. mohseni, m., jouzaryan, f. (2016), examining the effects of inflation and unemployment on economic growth in iran (1996-2012). procedia economics and finance, 36, 381-389. mory, j.f. (1993), oil prices and economic activity: is the relationship symmetric? the energy journal, 14(4), 20-30. moshiri, s. (2015), asymmetric effects of oil price shocks in oil-exporting countries: the role of institutions. opec energy review, 39(2), 222-246. nguyen, v.b. (2015), effects of fi scal defi cit and money m2 supply on inflation: evidence from selected economies of asia. journal of economics, finance and administrative science, 20(38), 49-53. nyangarika, a.m., tang, b.j. (2018), influence oil price towards economic indicators in russia. iop conference series: earth and environmental science, 192(1), 012066. olomola, p., olomola, p.a., adejumo, a.v. (2006), oil price shock and macroeconomic activity in nigeria. international research journal of finance and economics, 3, 25-35. özşahin, ş., üçler, g. (2017), the consequences of corruption on inflation in developing countries: evidence from panel cointegration and causality tests. economies, 5(4), 49. pratiwi, m.u., ekonomi, f., bisnis, d. (2020), pengaruh konsumsi energi terhadap pertumbuhan ekonomi di negara maju dan berkembang laporan tugas akhir. [universitas pertamina]. available from: https://www.library.universitaspertamina.ac.id// xmlui/handle/123456789/948. ramadhan, g.a., kumorotmo, w., sumarto, m., pitoyo, j.a. (2019), policy simulation of fuel subsidy reduction and impact on strategic sectors (input output analysis). jurnal ilmu pemerintahan, 4, 119-131. resosudarmo, b. (2012), is reducing subsidies on vehicle fuel equitable? a lesson from indonesian reform experience. in: fuel taxes and the poor: the distributional effects of gasoline taxation and their implications for climate policy. milton park, milton: taylor and francis. rousseau, p.l., wachtel, p. (2011), what is happening to the impact of financial deepening on economic growth? economic inquiry, 49(1), 276-288. salman, a.a., ghali, k.h., shammari, n.a. (2008), oil-price effects on the real business cycle: evidence from the g-7 countries. european journal of economics finance administrative sciences, 14, 74-83. sato, k., zhang, z., mcaleer, m. (2011), identifying shocks in regionally integrated east asian economies with structural var and block exogeneity. mathematics and computers in simulation, 81(7), 1353-1364. serletis, a., istiak, k. (2013), is the oil price-output relation asymmetric? journal of economic asymmetries, 10(1), 10-20. shi, x. (2015), energy efficiencies in asean region. in: handbook of clean energy systems. hoboken, new jersey: john wiley and sons, ltd., p1-19. singagerda, f.s., hendrowati, t.y., sanusi, a. (2018), indonesia growth of economics and the industrialization biodiesel based cpo. international journal of energy economics and policy, 8(5). tullock, g. (2013), the economics of special privilege and rent seeking. berlin: springer science and business media. unalmis, d., unalmis, i., unsal, d.f. (2010), on the sources of oil price fluctuations (no. 09; 385). zaouali, s. (2007), impact of higher oil prices on the chinese economy. opec review, 31(3), 191-214. . international journal of energy economics and policy | vol 5 • issue 4 • 2015 1125 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2015, 5(4), 1125-1132. economic growth and carbon dioxide emissions: investigating the environmental kuznets curve hypothesis in algeria miloud lacheheb1,4*, a. s. abdul rahim2, abdalla sirag3 1department of economics, universiti putra malaysia, serdang, malaysia, 2department of economics, universiti putra malaysia, serdang, malaysia, 3department of economics, universiti putra malaysia, serdang, malaysia, 4department of management, universite kasdi merbah, ouargla, algeria. *email: miloulach@yahoo.fr abstract this study examines the existence of environmental kuznets curve (ekc) hypothesis between economic growth and carbon dioxide (co2) emission in algeria for the period 1971-2009 using autoregressive distributed lag co-integration framework. data were retrieved from world bank development indicators. importantly, our findings reveal that ekc hypothesis does not exist. in addition, the long run models show that income and population appear to have significant impact on co2 emission especially from solid fuel consumption and electricity and heat production. however, only population is revealed to promote co2 from liquid fuel consumption. these findings suggest a dire need for algeria to shift towards service intensive economy rather than resource intensive, and alternative renewable energy sources in order to mitigate environmental degradation as well as promote economic development. keywords: air pollution, economic growth, environmental kuznets curve hypothesis jel classifications: q53, o47, q56 1. introduction the increasing threat of air pollution and global warming has been widely discussed in various international reunions. as per the intergovernmental panel on climate change (ipcc), carbon dioxide emissions (co2) are the major source of global warming. ipcc (2007) projected a global temperature increment from 1.1° to 6.4° and 16.5 to 53.8 cm rise in sea level by 2100. co2 emission as a main source of greenhouse gases is mainly indorsed to energy consumption mostly, fossil fuels burning such as oil and gas. unlike other gases such as so2 and nox, co2 emission spreads beyond the borders to other countries and indirectly affect the health, thus a country is likely less incentive in co2 emission reducing especially during rapid economic expansion period. environmental kuznets curve (ekc) become an independent research issue and motivated a bulky number of studies. ekc claims an inverted u-shaped relationship between income and co2; at early stage of development, environmental degradation occurs, but at certain point the increase in economic development will decrease co2 emission (grossman and helpman, 1991; panayotou, 1993; shafik and bandyopadhyay, 1992). the application of ekc hypothesis is increasingly important since no policy prevention is required as the effect of economic progress on co2 tend to become negative at the turning point. apart from other environmental indicators such as deforestation, carbon emission, sulfur dioxide, and municipal waste, the existence of ekc hypothesis amid co2 emission and economic development has been largely probed, but yet this relation is still inconclusive. shafik and bandyopadhyay (1992), shafik (1994) and azomahou et al. (2006) probed and found a linear relationship between co2 emission and income. while, roberts and grimes (1997), cole et al. (1997), schmalensee et al. (1998), galeotti and lanza (1999), apergis and payne (2009a), lean and smyth (2010) and saboori et al. (2012) confirmed the existence of ekc hypothesis. however, numerous studies employed ekc hypothesis in tempting to overcome environmental degradation using several environmental quality indicators. for instance, panayotou (1993), koop and tole (1999), bhattarai and hammig (2001) and bulte and van soest lacheheb, et al.: economic growth and carbon dioxide emissions: investigating the environmental kuznets curve hypothesis in algeria international journal of energy economics and policy | vol 5 • issue 4 • 20151126 (2001) utilized deforestation. dinda (2004), holtz-eakin and selden (1995), roberts and grimes (1997) and ozturk and uddin (2012) used carbon emissions. de bruyn (1997), grossman and helpman (1991), kaufmann et al. (1998), selden and song (1994), and stern et al. (1996) employed sulfur dioxide. despite the bulky number of literatures that investigated the existence of ekc among income and co2, only few studies applied individual countries to explore the hypothesis. consequently, lack of policy implications to each country arises, since pollution feature differs from country to another (ang, 2008). studies employed time series technique include de bruyn et al. (1998) for netherlands, west germany, uk and usa; roca et al. (2001) for spain; day and grafton (2003) for canada and friedl and getzner (2003) for austria; fodha and zaghdoud (2010) for tunisia; saboori et al. (2012) for malaysia; shahbaz et al. (2013) for turkey; shahbaz et al. (2014a) for tunusia; shahbaz et al. (2014b) for uae; ozturk and al-mulali (2015) for cambodia; shahbaz et al. (2015) for portugal; al-mulali et al. (2015) for vietnam. on the other hand, few studies found inclusive results include ozturk and acaravci (2010) for turkey; menyah and wolderufael (2010) for south africa. findings in exploring ekc hypothesis between co2 emission and economic growth for individual countries is likely to vary as a result of various econometrics techniques, time span, and different employed proxies. earlier studies tend to employ causality and cointegration methods in order to investigate the relationship between co2 emission and economic growth. for instance, (ghosh, 2010) utilized granger causality based on vector error correction model for india; jalil and mahmud (2009) used pair wise granger causality for china; soytas and sari (2009) used toda and yamamoto for turkey. the relationship between co 2 emission and economic development has been extensively explored. table 1 provides an overview of several studies probed this relation in order to validate the existence of ekc hypothesis. obviously, this hypothesis is still questionable. moreover, the relationship between co2 emission and economic growth may vary from one country to the other as a result of different individual country specifications. this study investigates the dynamic relationship between co2 emission and economic growth and the existing of ekc hypothesis in algeria. algeria as a country of well-endowed fossil fuel resources has experienced rapid growth rate since 1970s. these resources permitted algeria to promote economic expansion. the over-use of energy resources led to higher environmental degradation as co2 emission augmented gradually. the increase in energy use is a result of domestic usage as well as oil and gas export. algeria owns large of oil and gas resources. the oil and gas sector is the backbone of the economy, accounting for about 35% of the gross domestic product (gdp), and two-thirds of total exports. algeria holds the third-largest amount of proved crude oil reserves in africa. energy use in algeria relies solely on fossil fuels (oil and natural gas), causing huge co2 emissions that contribute to global climate. co2 emission from liquid fuel consumption was about 7623 million metric tons in 1971, and reaches 27,308 million table 1: summary of the existing empirical studies on the relationships between co2 emissions and economic growth study countries period methodology results saboori et al. (2012) malaysia 1980-2009 the ardl bounds testing approach, vecm granger causality ekc hypothesis exist lau et al. (2014) malaysia 1970-2008 the ardl bounds testing approach, vecm granger causality ekc hypothesis exist ozturk and acaravci (2010) turkey 1960-2005 the ardl bounds testing approach, vecm granger causality ekc hypothesis exist for denmark and italy esteve and tamarit (2012) spain 1857-2007 threshold vecm model ekc hypothesis exist hamit-haggar (2012) canada 1990-2007 pedroni co-integration test, fmols, vecm granger causality ekc hypothesis exist day and grafton (2003) canada 1958-1995 johansen co-integration, ols model, and var granger causality no evidence of ekc hypothesis fodha and zaghdoud (2010) tunisia 1961-2004 johansen co-integration test, vecm granger causality ekc hypothesis exist osabuohien et al. (2014) africa 1995-2010 pedroni co-integration, and dols ekc hypothesis exist dols: dynamic ordinary least squares, ardl: autoregressive distributed lag, vecm: vector error correction model, fmols: fully modified ordinary least squares, var: vector autoregressions, ekc: environmental kuznets curve, co2: carbon dioxide figure 1: carbon dioxide (co2) emission in algeria, lcos: co2 emissions from solid fuel consumption, lcos: co2 emissions from liquid fuel consumption, and lcos: co2 emissions from electricity and heat production source: world bank database 2014 lacheheb, et al.: economic growth and carbon dioxide emissions: investigating the environmental kuznets curve hypothesis in algeria international journal of energy economics and policy | vol 5 • issue 4 • 2015 1127 metric tons in 1988. figure 1 highlights the slow advancement of income in algeria from 1971 till 2009. gdp per capita in algeria experienced a gradual increase till 1985, after that and due to fallen oil prices, income per capita fall to 7245 dzd in 1994, while it was 8996 dzd in 1985. figure 2 shows the gradual increase in the three co2 emission. it is worthwhile to investigate the policies proven effect on co2 emission reduction in algeria. this paper attempts to test the hypothesis of: (1) the long-run co-integration among co2 emission and economic growth. this hypothesis is investigated employing three co2 resources, namely: co2 emission from solid fuel consumption, co2 emission from liquid fuel consumption, and co2 emission from electricity and heat production, (2) unidirectional causality occurs from energy use to economic growth, (3) ekc theory on the association between each type of co2 emission towards economic growth in algeria over the period of 1971-2009. the rest of the paper is organized as follows: section 2 describes the data and section 3 presents used methodology and model. section 4 provide the empirical findings. and section 5 discuss results and policy implication. while section 6 concludes the paper. 2. data this study uses annual data from 1971 to 2009. co2 emission is measured in metric tons and categorized into three types as follows: (1) co2 emissions from solid fuel consumption, (2) co2 emissions from liquid fuel consumption and (3) co2 emissions from electricity and heat production. per capita gdp, gross fixed capita formation, import, and export are measured in local currency dzd. time series data were retrieved from world bank database. 3. model and methodology based on ekc hypothesis, a non-linear quadratic association exists between pollution and income. that is ekc hypothesis may formulated as follows: e f y y z= ( , , )2 (1) where, e refers to environmental degradation, y is income and z represents other descriptive variables that may influence environmental degradation. co2 emission has been widely used as dependent variable (al-mulali et al., 2014; lau et al., 2014; osabuohien et al., 2014; pao and tsai, 2011a; pao and tsai, 2011b; tiwari et al., 2013; wang et al., 2011; yavuz, 2014). economic growth is widely used as economic development and to incorporate ekc hypothesis. apergis and payne (2009b), ghali and el-sakka (2004) and huang et al. (2008) validated the influence of gross fixed capital formation and labor towards pollution level. furthermore, several studies have employed import and export as an indicator to trade such as al-mulali et al. (2014), du et al. (2012), osabuohien et al. (2014) and tiwari et al. (2013). in this study, we employ autoregressive distributed lag approach (ardl) bound testing approach, which proposed, by pesaran et al. (2001). this approach has several advantages over alternatives. for instance, this method can be applied whether variables are stationary or integrated in different order. hence, it overcomes problem of integration order related to johansen (1995). this approach redresses heterogeneity and mitigates serial correlation problems through accurate order augmentation of the repressor and appropriate lag selection. co-integration test will be performed using f-statistics. the computed f-statistic value will be evaluate with the critical values presented in table 2 of narayan (2005). consequently, if the computed f-statistic is greater than the upper bound value, then agriculture area and its determinants share a long-run relationship level. conversely, if the computed f-statistic is smaller than the lower bound value, then the null hypothesis is not rejected and we can conclude that there is no long-run relationship between co2 emission and its determinants. on the other hand, if the computed f-statistic falls within these bounds, inference would be inconclusive. once co-integration is performed, short-run and long-run relationship will be estimated. (narayan and narayan, 2010) suggested an alternative method to investigate ekc hypothesis in order to eliminate multicollinearity problem. multicollinearity may arise between gdp per capita and gdp per capita square. this approach suggests a comparison between short-run and long-run elasticity. if the long-run income elasticity is smaller than the short run income elasticity, then we can conclude that, over time, income leads to less co2 emission. following al-mulali et al. (2014), narayan and narayan (2010) and above discussed empirical literatures, the ardl model is estimated as follows: ∆ = + ∆ + ∆ + ∆ − = − = ∑ ∑lncos a lncos a lngdpclcu a lngfcf t t i n t i n β0 1 1 1 2 1 1 3 llcu a lnpop a lnexplc a lnimpl t i n t t i n i n − = − − == + ∆ + ∆ + ∆ ∑ ∑∑1 1 4 1 5 1 11 6 cc lncos lngdpclcu lngfcflcu lnpo t i n t t t − = − − − + + + + ∑ 1 1 1 1 2 1 3 1 4 β β β β pp lnexplc lnimplc ect t t t t t − − − − + + + + 1 5 1 6 1 1 β β θ ε (2) figure 2: plot of cumulative sum for case 1 lacheheb, et al.: economic growth and carbon dioxide emissions: investigating the environmental kuznets curve hypothesis in algeria international journal of energy economics and policy | vol 5 • issue 4 • 20151128 ∆ = + ∆ + ∆ + ∆ − = − = ∑ ∑lncof a lncof a lngdpclcu a lngfcf t t i n t i n β0 1 1 1 2 1 1 3 llcu a lnpop a lnexplc a lnimpl t i n t t i n i n − = − − == + ∆ + ∆ + ∆ ∑ ∑∑1 1 4 1 5 1 11 6 cc lncof lngdpclcu lngfcflcu lnpo t i n t t t − = − − − + + + + ∑ 1 1 1 1 2 1 3 1 4 β β β β pp lnexplc lnimplc ect t t t t t − − − − + + + + 1 5 1 6 1 1 β β θ ε (3) ∆ = + ∆ + ∆ + ∆ − = − = ∑ ∑lncoe a lncoe a lngdpclcu a lngfcf t t i n t i n β0 1 1 1 2 1 1 3 llcu a lnpop a lnexplc a lnimpl t i n t t i n i n − = − − == + ∆ + ∆ + ∆ ∑ ∑∑1 1 4 1 5 1 11 6 cc lncoe lngdpclcu lngfcflcu lnpo t i n t t t − = − − − + + + + ∑ 1 1 1 1 2 1 3 1 4 β β β β pp lnexplc lnimplc ect t t t t t − − − − + + + + 1 5 1 6 1 1 β β θ ε (4) where, t and εt stand for time period and white noise, respectively. θ ectt-1 in equation (2), equation (3), and equation (4) corresponds to the error correction term (ect). ect indicates the speed of the adjustment and shows how quickly the variables return to the long-run equilibrium. in equation (2) cos represent co2 emissions from solid fuel consumption (kt). in equation (2) cof stands for co2 emissions from liquid fuel consumption (kt), in equation (4) coe refers to co2 emissions from electricity and heat production. αi where i = 1, 2, 3, 4, 5, 6 are the corresponding short-run multipliers, while the parameters βi, where i = 1, 2, 3, 4, 5, 6 are the long-run dynamic coefficients of the underlying ardl model. in equation (2) gdpclcu, gfcflcu, pop, explc, and implc correspond to real gdp per capita in dzd, gross fixed capital formation, population, export of goods and services, and import of goods and services in dzd, respectively. the same applies for equation (3) and equation (4). once all equation are estimated, diagnostic tests are performed to validate model adequacy. these tests include serial correlation, functional form, normality and heteroscidasticity as well as cumulative sum (cusum) and cusum of squares (cusumsq) tests to verify the stability of the coefficient in the estimated models (pesaran et al., 2001). 4. empirical results although ardl bound testing approach is applicable regardless of co-integration order of the variables (whether variables are i(0), i(1), or are integrated in different order), unit root test is conducted to avoid spurious regression results. augmented dickey and fuller (dickey and fuller, 1979) (adf) test is performed1. results of unit root test confirm the absence of i(2) for all the variables; hence utilizing ardl is feasible. results of computing f values for testing the existence of longrun relationship are demonstrated in table 2. the maximum lags length is calculated following akaike information criterion (aic) minimization criteria in order to prevent classical assumptions violation. calculated f-statistic is sensitive to the number of lags imposed for co-integration test (bahmani-oskooee and brooks, 1999; narayan et al., 2008). case 1 represents calculated f-statistic of co-integration result of equation (2). since f-statistic is greater than the upper bound in all cases, co-integration amongst co2 emission from solid fuel consumption and its determinants. baseline equation (3) and equation (4) are as reported in table 2 in which co2 emission is replaced by co2 emission from liquid fuel consumption and co2 emission from electricity and heat production, respectively. the existence of long-run relationship between co2 emission and its determinants based on bound testing approach permits us to estimate longand short run models of environmental degradation in algeria. in order to examine the existence of ekc hypothesis, long-run and short-run models were compared (narayan and narayan, 2010). tables 3 and 4 report long-run and short-run estimated models, respectively. the estimated ardl models are set to 1 lag length. aic-base suggests (1, 0, 0, 0, 0, 0), (0, 1, 0, 1, 0, 1), and (1, 0, 0, 0, 1, 0) for case 1, 2 and 3, respectively. while negative and significant ect in table 4 provides an extra evidence of long-run co-integration among variables. ect indicates the adjustment speed of the variables towards the longrun equilibrium. 1 to save space, the results from unit root analysis are not reported here but available upon request. table 2: co-integration bound test results model optimal lag f-test [p] result case 1 flncos [lncos|lny, lny  2, lnz] (1,2, 0, 0, 0, 0) 5.3267 [0.002]** co-integration case 2 flncof [lncof|lny, lny  2, lnz] (1,2, 0, 0, 0, 0) 4.9073 [0.003]** co-integration case 3 flncoe [lncoe|lny, lny  2, lnz] (1,2, 0, 0, 0, 0) 5.7388 [0.001]** co-integration critical values for f-statistics (%) lower i(0) upper i(1) 1 4.045 5.898 5 2.962 4.338 10 2.483 3.708 critical values were retrieved from narayan (2005). case 3: unrestricted intercept and no trend. **denotes significance at 5% level lacheheb, et al.: economic growth and carbon dioxide emissions: investigating the environmental kuznets curve hypothesis in algeria international journal of energy economics and policy | vol 5 • issue 4 • 2015 1129 provided long-run and short-run computed models, there is no evidence of ekc hypothesis in all cases. moreover, regardless of co2 emission sources, whether from solid fuel consumption, liquid fuel consumption, or from electricity and heat production ekc hypothesis is unproven. the estimated results are in line with other studies such as jalil and mahmud (2009), saboori et al. (2012). a possible explanation of non-existence of ekc hypothesis in algeria is that the algerian economy is still resource intensive rather than services intensive; in which oil sector donates 45.9% of total gdp per capita in 2006, while services and agriculture sectors contribute 20.1% and 7.6% respectively (oecd, 2008). in long-run models (table 3), income and population appear to have a positive impact on co2 emission from solid fuel consumption, that is, an increase by 1% in real gdp per capita leads to 6% increase in co2 emission from solid fuel consumption; while, investment and import seem to have a negative effect. however, only population appears to promote co2 from liquid fuel consumption (case 2). in case 3, co2 emission from electricity and heat production appears to be positively affected through income and population growth (table 3), where an increase by 1% in income level leads to 1.41% increase in co2 emission from electricity and heat production. in short-run models (table 4), coefficients of real gdp per capita and population appears to have significant and positive impact towards co2 emission from solid fuel consumption; increase by 1% in income level leads to 6.23% increment in co2 emission from solid fuel consumption. while in case 2, only population appears to be significant and positively affecting co2 emission from liquid fuel consumption. however, in case 3 real gdp per capita and population seem to be significantly and positively associated to co2 emission from electricity and heat production; increase by 1% in income level leads to 1.41% increment in co2 emission from electricity and heat production. in table 4, ect indicates to the speed of the adjustment and shows how quickly the variables return to the long-run equilibrium; the negative and significances of ect is an efficient way of establishing cointegration among variables (kremers et al., 1992). for instance, ect of −0.52 in case 1 reveals that 52% of discrepancy between the actual and value of real gdp per capita is corrected each year. comparing income coefficient in the long-run (table 3) with itself in short-run model (table 4) reveal no evidence to an inverted-u shape relationship between co2 emission and income, since the coefficients are almost equal in both short-run and long-run equations. these findings are in line with jalil and mahmud (2009). in order to verify the adequacy of the estimated results, a bulky of diagnostic tests were applied. table 5 presents serial correlation, functional form, normality, and heteroscedasticity tests. the null hypothesis of serial correlation is not rejected in all cases, except case 2 at 10% level of significance. also, null hypothesis of functional form is accepted in case 1 and case 2 only. apart from case 2, all cases are free from normality harms. similarly, null hypothesis of heteroscedasticity is accepted; with no heteroscedasticity in all cases. furthermore, the stability test for the model applies the cusumsq of recursive residuals and the cusum of recursive residuals proposed by brown et al. (1975), which are presented in figures 3-7. obviously, the cusum and cusumsq statistics stay within the critical bounds except for case 3 for cusumsq. since cusum and cusumsq lines stay within the critical bounds, there is an indication of significant relationship between dependent and independent variables. table 3: long-run ardl model variables case 1 case 2 case 3 lncos 0.47344 (0.12264)*** lncof lncoe 0.51725 (0.12002)*** lngdpclcu 6.2331 (1.4552)*** −1.2907 (0.94235) 1.4181 (0.60134)** lngfcflcu −2.0343 (0.64218)*** 0.49548 (0.24432)* 0.052513 (0.17291) lnpop 3.4692 (1.0477)*** 28.9410 (12.6162)** 2.1229 (0.71437)** lnimplc −2.5326 (0.70479)*** −0.10093 (0.19931) −0.21876 (0.15237) lnexplc 0.24757 (0.54176) −0.028509 (0.46214) −0.37381 (0.34486) c 8.9228 (3.4208)** −6.6817 (3.4584)* 1.0643 (1.0199) figures in parentheses ( ) indicate the standard errors. while, *,**,***denotes statistical significance at 10%, 5%, and 1% level, respectively. ardl: autoregressive distributed lag table 4: short-run ardl model variables case 1 case 2 case 3 lncos lncof lncoe lngdpclcu 6.2331 (1.4552)*** −1.2907 (0.94235) 1.4181 (0.60134)** lngfcflcu −2.0343 (0.64218)*** 0.49548 (0.24432)* 0.052513 (0.17291) lnpop 3.4692 (1.0477)*** 28.9410 (12.6162)** 2.1229 (0.71437)*** lnimplc 0.24757 (0.54176) −0.10093 (0.19931) −0.21876 (0.15237) lnexplc −2.5326 (0.70479)*** −0.028509 (0.46214) −0.37381 (0.34486) c 8.9228 (3.4208)** −6.6817 (3.4584)* 1.0643 (1.0199) ect (−1) −0.52656 (0.12264)*** −0.48275 (0.12002)*** figures in parentheses ( ) indicate the standard errors. while, *,**,***denotes statistical significance at 10%, 5%, and 1% level, respectively. ardl: autoregressive distributed lag lacheheb, et al.: economic growth and carbon dioxide emissions: investigating the environmental kuznets curve hypothesis in algeria international journal of energy economics and policy | vol 5 • issue 4 • 20151130 5. discussion and policy implication economic expansion and development is key target for most emerging countries to be fully developed nations. in the same time, economic expansion usually causes environmental degradation. hence, implementation of appropriate policies regarding halt environmental degradation without harming economic development in the country is crucial for policy makers. long-run findings suggest that co2 emission from solid fuel consumption and from electricity and heat production are significantly associated to the economic development in algeria. while, co2 emission from liquid fuel consumption is statistically unrelated to the economic growth in the country. obviously, any reduction in co2 emission from solid fuel consumption or from electricity and heat production will harm economic expansion. thus, any control towards co2 emission must suitably implied, and appropriate policies may be favored to efficient energy consumption. moreover, reduction in co2 emission from liquid fuel consumption may reduce pollution as well as it does not harm economic growth in algeria. oil and gas sector remains the driving force of the algerian economy which contribute up to 50% of gdp and 97% of algerian exports; as a result, the choice of renewable energy in algeria is needed. in fact, algeria has implemented energy efficiency program (eep) to reduce pollution through pollution free sources. eep includes solar water heating development, spreading the use of low energy consumption lamps, and promoting energy efficiency in the industrial sector. algeria needs to embrace a new integral policies of controlling co2 emission and find alternative energy source, such as solar energy. this may reduce environmental degradation, reduce air pollution, and protect individuals’ health with no damage to the algerian economy. of late, algeria government has commenced initiatives meant to make full usage of solar energy through desertec project. this project with total plant output of 150 mw may cause reduction in non-renewable resources such as oil and gas, and hence, mitigate co2 emission. the implementation of solar energy will permit algeria to reduce one-third of its co2 emissions (sahnoune et al., 2013). thus, it is recommended to invest in clean energies include wind and solar energy to reduce co2 emission from solid fuel consumption, electricity and heat production, this may also save the quantity of oil and gas available for export purpose. at the same time, an energy efficiency usage would be implemented to reduce co2 emission. for instance, figure 3: plot of cumulative sum-squared for case 1 figure 4: plot of cumulative sum for case 2 figure 5: plot of cumulative sum-squared for case 2 figure 6: plot of cumulative sum for case 3 figure 7: plot of cumulative sum-squared for case 3 table 5: diagnostic results model serial correlation functional form normality heteroscedasticity case 1 2.0704 [0.150] 1.2753 [0.259] 2.1361 [0.344] 0.099363 [0.753] case 2 2.7163 [0.099]* 1.8006 [0.180] 52.2746 [0.000]*** 0.50937 [0.475] case 3 0.72587 [0.394] 5.4394 [0.020]** 0.25425 [0.881] 0.40907 [0.522] values in parenthesis represent p value, while *,**,***denote significance at 10%, 5%, and 1%, respectively lacheheb, et al.: economic growth and carbon dioxide emissions: investigating the environmental kuznets curve hypothesis in algeria international journal of energy economics and policy | vol 5 • issue 4 • 2015 1131 industries are encouraged to minimize their air pollution through adopting green technologies. 6. conclusion this paper examines whether the ekc hypothesis holds in the case of algeria or not. the co2 emission from different sources, such as solid fuel consumption, liquid fuel consumption, and from electricity and heat production, is separately used to have evidence that is more robust. the study adopts time series analysis for the period from 1971 to 2009. the ardl bound test approach is employed since it is more appropriate for small sample size and applicable if there are some variables i(0) and other are i(1). the results reveal that co2 emission from solid fuel consumption, liquid fuel consumption, and electricity and heat production fail to show any evidence of ekc hypothesis. these findings indicate that the hypothesis of ekc does not exist in the case of algeria. however, the long-run models show that income and population appear to have significant impact on co2 emission especially from solid fuel consumption and electricity and heat production. however, only population is revealed to promote co2 from liquid fuel consumption. the findings draw some serious policy implications, especially energy consumption, need to be addressed by the government of the country. applicable policies that aim to efficient energy consumption, control co2 emission and reduce environmental degradation must immediately implemented. in addition, clean energies include wind and solar energy to reduce co2 emission from solid fuel consumption, electricity and heat production can be alternative sources of energy that the country can consider. references al-mulali, u., fereidouni, h.g., lee, j.y. (2014), electricity consumption from renewable and non-renewable sources and economic growth: evidence from latin american countries. renewable and sustainable energy reviews, 30, 290-298. al-mulali, u., saboori, b., ozturk, i. (2015), investigating the environmental kuznets curve hypothesis in vietnam. energy policy, 76, 123-131. ang, j.b. (2008), economic development, pollutant emissions and energy consumption in malaysia. journal of policy modeling, 30(2), 271-278. apergis, n., payne, j.e. (2009a), co2 emissions, energy usage, and output in central america. energy policy, 37(8), 3282-3286. apergis, n., payne, j.e. (2009b), energy consumption and economic growth: evidence from the commonwealth of independent states. energy economics, 31(5), 641-647. azomahou, t., laisney, f., van, p.n. (2006), economic development and co2 emissions: a nonparametric panel approach. journal of public economics, 90(6), 1347-1363. bahmani-oskooee, m., brooks, t.j. (1999), bilateral j-curve between us and her trading partners. review of world economics, 135(1), 156-165. bhattarai, m., hammig, m. (2001), institutions and the environmental kuznets curve for deforestation: a cross country analysis for latin america, africa and asia. world development, 29(6), 995-1010. brown, r.l., durbin, j., evans, j.m. (1975), techniques for testing the constancy of regression relationships over time. journal of the royal statistical society, series b (methodological), 37(2), 149-192. bulte, e.h., van soest, d.p. (2001), environmental degradation in developing countries: households and the (reverse) environmental kuznets curve. journal of development economics, 65(1), 225-235. cole, m.a., rayner, a.j., bates, j.m. (1997), the environmental kuznets curve: an empirical analysis. environment and development economics, 2(4), 401-416. day, k.m., grafton, r.q. (2003), growth and the environment in canada: an empirical analysis. canadian journal of agricultural economics/ revue canadienne d’agroeconomie, 51(2), 197-216. de bruyn, s.m. (1997), explaining the environmental kuznets curve: structural change and international agreements in reducing sulphur emissions. environment and development economics, 2(04), 485-503. de bruyn, s.m., van den bergh, j.c.j., opschoor, j.b. (1998), economic growth and emissions: reconsidering the empirical basis of environmental kuznets curves. ecological economics, 25(2), 161-175. dickey, d.a., fuller, w.a. (1979), distribution of the estimators for autoregressive time series with a unit root. journal of the american statistical association, 74(366a), 427-431. dinda, s. (2004), environmental kuznets curve hypothesis: a survey. ecological economics, 49(4), 431-455. du, l., wei, c., cai, s. (2012), economic development and carbon dioxide emissions in china: provincial panel data analysis. china economic review, 23(2), 371-384. esteve, v., tamarit, c. (2012), threshold cointegration and nonlinear adjustment between co 2 and income: the environmental kuznets curve in spain, 1857-2007. energy economics, 34(6), 2148-2156. fodha, m., zaghdoud, o. (2010), economic growth and pollutant emissions in tunisia: an empirical analysis of the environmental kuznets curve. energy policy, 38(2), 1150-1156. friedl, b., getzner, m. (2003), determinants of co2 emissions in a small open economy. ecological economics, 45(1), 133-148. galeotti, m., lanza, a. (1999), richer and cleaner? a study on carbon dioxide emissions in developing countries. energy policy, 27(10), 565-573. ghali, k.h., el-sakka, m.i. (2004), energy use and output growth in canada: a multivariate cointegration analysis. energy economics, 26(2), 225-238. ghosh, s. (2010), examining carbon emissions economic growth nexus for india: a multivariate cointegration approach. energy policy, 38(6), 3008-3014. grossman, g.m., helpman, e. (1991), trade, knowledge spillovers, and growth. european economic review, 35(2-3), 517-526. available from: http://www.dx.doi.org/10.1016/0014-2921(91)90153-a. hamit-haggar, m. (2012), greenhouse gas emissions, energy consumption and economic growth: a panel cointegration analysis from canadian industrial sector perspective. energy economics, 34(1), 358-364. holtz-eakin, d., selden, t.m. (1995), stoking the fires? co2 emissions and economic growth. journal of public economics, 57(1), 85-101. huang, b., hwang, m., yang, c.w. (2008), causal relationship between energy consumption and gdp growth revisited: a dynamic panel data approach. ecological economics, 67(1), 41-54. jalil, a., mahmud, s.f. (2009), environment kuznets curve for co2 emissions: a cointegration analysis for china. energy policy, 37(12), 5167-5172. johansen, s. (1995), likelihood-based inference in cointegrated vector autoregressive models. oup catalogue. oxford: oxford university press. kaufmann, r.k., davidsdottir, b., garnham, s., pauly, p. (1998), the determinants of atmospheric co2 concentrations: reconsidering the environmental kuznets curve. ecological economics, 25(2), 209-220. lacheheb, et al.: economic growth and carbon dioxide emissions: investigating the environmental kuznets curve hypothesis in algeria international journal of energy economics and policy | vol 5 • issue 4 • 20151132 koop, g., tole, l. (1999), is there an environmental kuznets curve for deforestation? journal of development economics, 58(1), 231-244. kremers, j.j., ericsson, n.r., dolado, j.j. (1992), the power of cointegration tests. oxford bulletin of economics and statistics, 54(3), 325-348. lau, l., choong, c., eng, y. (2014), investigation of the environmental kuznets curve for carbon emissions in malaysia: do foreign direct investment and trade matter? energy policy, 68, 490-497. lean, h.h., smyth, r. (2010), co2 emissions, electricity consumption and output in asean. applied energy, 87(6), 1858-1864. menyah, k., wolde-rufael, y. (2010), energy consumption, pollutant emissions and economic growth in south africa. energy economics, 32(6), 1374-1382. narayan, p.k. (2005), the saving and investment nexus for china: evidence from cointegration tests. applied economics, 37(17), 1979-1990. narayan, p.k., narayan, s. (2010), carbon dioxide emissions and economic growth: panel data evidence from developing countries. energy policy, 38(1), 661-666. narayan, p.k., narayan, s., prasad, a. (2008), a structural var analysis of electricity consumption and real gdp: evidence from the g7 countries. energy policy, 36(7), 2765-2769. oecd. (2008), african economic outlook 2007/2008. paris: oecd. osabuohien, e.s., efobi, u.r., gitau, c.m.w. (2014), beyond the environmental kuznets curve in africa: evidence from panel cointegration. journal of environmental policy & planning, 16(4), 517-538. ozturk, i., acaravci, a. (2010), co2 emissions, energy consumption and economic growth in turkey. renewable and sustainable energy reviews, 14(9), 3220-3225. ozturk, i., uddin, g.s. (2012), causality among carbon emissions, energy consumption and growth in india. economic research, 25(3), 752-775. ozturk, i., al-mulali, u. (2015) investigating the validity of the environmental kuznets curve hypothesis in cambodia. ecological indicator, 57, 324-330. panayotou, t. (1993), empirical tests and policy analysis of environmental degradation at different stages of economic development. pao, h., tsai, c. (2011a), modeling and forecasting the co2 emissions, energy consumption, and economic growth in brazil. energy, 36(5), 2450-2458. pao, h., tsai, c. (2011b), multivariate granger causality between co2 emissions, energy consumption, fdi (foreign direct investment) and gdp (gross domestic product): evidence from a panel of bric (brazil, russian federation, india, and china) countries. energy, 36(1), 685-693. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. roberts, j.t., grimes, p.e. (1997), carbon intensity and economic development 1962-1991: a brief exploration of the environmental kuznets curve. world development, 25(2), 191-198. roca, j., padilla, e., farré, m., galletto, v. (2001), economic growth and atmospheric pollution in spain: discussing the environmental kuznets curve hypothesis. ecological economics, 39(1), 85-99. saboori, b., sulaiman, j., mohammed, s. (2012), economic growth and co2 emissions in malaysia: a cointegration analysis of the environmental kuznets curve. energy policy, 51, 184-191. sahnoune, f., belhamel, m., zelmat, m., kerbachi, r. (2013), climate change in algeria: vulnerability and strategy of mitigation and adaptation. energy procedia, 36, 1286-1294. schmalensee, r., joskow, p.l., ellerman, a.d., montero, j.p., bailey, e.m. (1998), an interim evaluation of sulfur dioxide emissions trading. the journal of economic perspectives, 12, 53-68. selden, t.m., song, d. (1994), environmental quality and development: is there a kuznets curve for air pollution emissions? journal of environmental economics and management, 27(2), 147-162. shafik, n. (1994), economic development and environmental quality: an econometric analysis. oxford economic papers. p757-773. shafik, n., bandyopadhyay, s. (1992), economic growth and environmental quality: time-series and cross-country evidence. washington, d.c: world bank publications. shahbaz, m., ozturk, i., afza, t., ali, a. (2013), revisiting the environmental kuznets curve in a global economy. renewable and sustainable energy reviews, 25(2013), 494-502. shahbaz, m., khraief, n., uddin, g.s., ozturk, i. (2014a), environmental kuznets curve in an open economy: a bounds testing and causality analysis for tunisia. renewable and sustainable energy reviews, 34, 325-336. shahbaz, m., sbia, r., hamdi, h., ozturk, i. (2014b), economic growth, electricity consumption, urbanization and environmental degradation relationship in united arab emirates. ecological indicators, 45, 622-631. shahbaz, m., dube, s., ozturk, i., jalil, a. (2015), testing the environmental kuznets curve hypothesis in portugal. international journal of energy economics and policy, 5(2), 475-481. soytas, u., sari, r. (2009), energy consumption, economic growth, and carbon emissions: challenges faced by an eu candidate member. ecological economics, 68(6), 1667-1675. stern, d.i., common, m.s., barbier, e.b. (1996), economic growth and environmental degradation: the environmental kuznets curve and sustainable development. world development, 24(7), 1151-1160. tiwari, a.k., shahbaz, m., hye, q.m.a. (2013), the environmental kuznets curve and the role of coal consumption in india: cointegration and causality analysis in an open economy. renewable and sustainable energy reviews, 18, 519-527. wang, s., zhou, d., zhou, p., wang, q. (2011), co2 emissions, energy consumption and economic growth in china: a panel data analysis. energy policy, 39(9), 4870-4875. yavuz, n.ç. (2014), co2 emission, energy consumption, and economic growth for turkey: evidence from a cointegration test with a structural break. energy sources part b: economics planning and policy, 9(3), 229-235. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 5 • 2021490 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(5), 490-498. improve the incremental block tariffs of electricity: to harmonize pricing policy targets in the new context of power supply and demand in vietnam xuan hoi bui* hanoi university of science and technology, vietnam. *email: hoi.buixuan@hust.edu.vn received: 24 april 2021 accepted: 10 july 2021 doi: https://doi.org/10.32479/ijeep.11534 abstract the existing retail electricity tariff for households in vietnam is the incremental block structure. however, the most recent revision of the electricity tariff structure was in 2014 which it was 7 years a long period of change in conditions of electricity supply and consumption leading to the need to adjust this structural price appropriately. this article provides an in-depth analysis of the current residential block tariff of residential electricity use to identify shortcomings, thereby, for building options to improve this incremental block tariff structure to ensure the harmonization of different pricing targets especially the equity, efficiency and promote the electricity saving, in the new context of electricity supply and demand in vietnam. keywords: electricity pricing policy, incremental block tariff, electricity of vietnam jel classifications: d4, q31, q41, q43. q48 1. introduction in vietnam, the electricity tariff level, tariff structure and tariff adjustment regime1 for end-users are determined by the authority of the prime minister. until now, electricity user types are divided into four categories: residential, industrial, administrative and business users and there are three tariff types applied: incremental block tariffs (ibts); time of use (tou)2 and tariff according to voltage levels. the ibts have been applied 1 tariff level is defined by the average retail tariff that allows the operator to break even under a regulated rate of return; tariff structure is the multidimensional combination of charges (fixed, variable), user types (residential, industrial, business or administrative etc..); services (hv, mv, lv), etc. which define the tariff grid; tariff adjustment regime is set of rules and procedures by which retail tariffs are updated and changed over time. 2 tou tariffs are implemented for industrial and business users. accordingly, from monday to saturday, there are 5 peak hours with 2 time frames: from 9:30 a.m. to 11:30 a.m., from 5:00 p.m. to 8:00 p.m., there are 6 low hours with the frame from 10 p.m. to 4 a.m. the next morning, the rest is 13 normal. there is no set peak hour for sunday. for households for a long time and through many adjustments of tariff structure. revised by decision 28/2014/ttg in 2014, the last version tariff has six-tiers structure (table 1). this current block tariff structure still increases the price effects that drive residential consumers to use electricity efficiently and at the same time, enforcing social policies for users with low income, especially on the consumption of the first blocks. however, this tariff structure has been in use for 7 years while there are changes and adjustments observed from both consumer and power producer sides. it is necessary to conduct research on the improvement of the electricity tariff structure in accordance with the new context of the electricity supply and demand for the current period and the coming years. the research scope of the paper only focuses on the ibts for households. therefore, improving studies must ensure a financial balance for evn, that is to reform the tariff structure (number of blocks, limits between them and value of each block) in a way that is appropriate to the current context and the years to come but ensure the necessary revenue for evn such as that when applying this journal is licensed under a creative commons attribution 4.0 international license bui: improve the incremental block tariffs of electricity: to harmonize pricing policy targets in the new context of power supply and demand in vietnam international journal of energy economics and policy | vol 11 • issue 5 • 2021 491 the current price of electricity. the assessments are based on quantitative analysis with primary data collected from households and secondary data provided by evn and its member units. the final result is the basis for governmental decision makers to adjust the current ibts structure appropriately. so, the remainder of this paper is organized as follow: section 2 and 3 give the literature review on theoretical and practical on ibts after that analysis methodology, section 4 analyzes the existing increasing block tariffs for households. with the objective of improving the current tariff, section 5 designs the new ibts for residential electricity users followed by conclusions and suggestions in section 6. 2. literature review of ibts for electricity pricing policy historically, electricity pricing policy is always regulated by the government. there are normally 4 regulatory objectives, the first one is the sustainability defined by covering economic costs of the electricity service; the second is the allocative efficiency – that means providing signals for efficient use of resources; the third objective is productive efficiency defined by creating incentives for cost minimization and the last one is the equity – that means protecting poor users in terms of access and affordability bui (2008) and percebois (1988). therefore, there are many electrical tariffs that can be applied to end-users and the choice of the tariff structure depends on many factors: the level of reflection about cost by nature and characteristics in consumption; an effect about the price towards efficient use and power saving; and social macro-economic policy issues in electricity pricing and the conditions of technical infrastructure of the sector aiming (2012) and munasinghe (2009). the application of incremental block pricing is widespread in the water and electricity sectors because with the constraint of compensation cost, this pricing approach was an optimal method of second best pricing compared to marginal cost pricing, porter (1996). the ibts is a pricing for incremental blocks of consuming electricity as we observed the electric tariff system around the world such as usa, japan, india, china, thai lan, malaysia, vietnam or korea etc., usaid (2013).3 3 in fact, electricity sector is very specific because an electricity supply process always consists of two components: required capacity and used energy. for that matter, there is another type of block tariff that is a pricing for block of required capacity with unique tariff or time of use tariff for electricity consumption as we can observe in france (edf) for example. the reason why it is called incremental block is that this tariff structure is designed with electricity consumption divided into different blocks, arranged in ascending cumulative order, and also gradually increasing prices of blocks. especially, the ibts is applied to residential consumers due to the nature, characteristics and uniformity of electricity consumption that is the increase in electricity consumption mainly at the peak period of the power system. with the technical and economic characteristics of the electric power sector, and the increase in consumption during peak periods we must use high-cost power plants to meet electricity demand. the ibts with the logic of using more, the more expensive it is, reflects the specific characteristics of the cost of the electricity system and of electric consumption of households ibts according to incremental costs they impose on the electric power supply. the ibts structure implies an increasing marginal price for electricity (figure 1). on the other hand, with the construction logic of an increasing blocks price, households that consume less electricity will pay a lower price for their electricity consumption and the more electricity households consume, the higher the price. in this respect, the ibts for residential users allows the implementation of social policies in electricity pricing policy as the principle of a value-in-use pricing system. in other words, the theoretical basis for ibts is ramsey pricing, which obeys the rule “contrast with elasticity.” an increasing block tariff seeks to emphasize the goal of equity based on the assumption that higher electric consumption is correlated with higher income and therefore reflects, to some extent, a greater ability to pay and vice-versa… borenstein (2008), boqiang and zhujun (2012). in addition, logic of higher price for high-income people cannot only reflect the incremental cost due to more residential electricity consumption usually at peak hours but also restrain electrical waste and promote energy efficiency. this is, therefore, a fairly effective type of the pricing policy for the electric power sector while simultaneously achieving different pricing targets. it is not obvious that the ibts applies only to residential users, but not to other electricity consumers (bui, 2019). the domestic studies on the residential electricity pricing mechanism are rare. it is easy to understand because since the figure 1: the cost of the electricity system in order to answer the evolution of electricity demand source: conseil français de l’energie (2014) table 1: structure of the current ibts for residential electricity user group of households (kwh) proportion in comparing with adjusted average retail price approved by government (%) latest electricity retail price (vnđ/kwh) -2020 (excl. vat) block 1: 0–50 92 1,678.00 block 2: 51–100 95 1,734.00 block 3: 101–200 110 2,014.00 block 4: 201–300 138 2,536.00 block 5: 301–400 154 2,834.00 block 6: 401 or more 159 2,927.00 source: decision 28 of prime minister and decision 648 of moit bui: improve the incremental block tariffs of electricity: to harmonize pricing policy targets in the new context of power supply and demand in vietnam international journal of energy economics and policy | vol 11 • issue 5 • 2021492 power system unified the three regions in 1994, the electricity tariff system has always been designed by government and the ibts was used for residential customers. the adjustments realized by government and the last version of tariff structure was adjusted in 2014. some projects financed by ministry of industry and trade (moit) and world bank (wb) and realized by foreigner specialists focus on assessment of tariff structure and tariff framework pardina (2015). 3. methodology and data the ibts is popular tariff type and is used quite a lot in the process of building structure of electricity pricing in many countries. generally speaking, the electricity bill under the ibts can be established by formula (i) taking the vietnamese six-tiers structure as an example. ( ) ( ) ( ) ( ) ( ) ( ) q * p1 q q1 q1* p1 q q1 * p2 q1 q q2 q1* p1 q2 q1 * p2 q q2 * p3 q2 q q3 q1* p1 q2 q1 * p2 q3 q2 tc *p3 q q3 * p4 ≤ + − ≤ ≤ + − + − ≤ ≤ + − + − = + − ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 1* 1 2 1 2 3 2 3 4 3 4 5 4 5 5 5 q3 q q4 q1* p1 q2 q1 * p2 q3 q2 * p3 q4 q3 * p4 q q4 * p5 q3 q q4 q p q q * p q q * p q q * p q q * p q q * p q q          ≤ ≤  + − + − + − + − ≤ ≤   + − + −  + − + −  + − < (1) where: • tc is the expenditure on electricity consumption • qi (i = 1, 6) is the threshold of electricity consumption in the ith block • q is the real amount of electricity use • pi is the price in the ith block. in terms of constructing method, the key of the ibts design includes: numbers of blocks, the volume of electricity consumption and price for each block. ibts design is often based on income groups, the consumption structure of households and the structure of costs incurred by users to the electricity system, thus determining numbers of blocks, limits between them and the value of each block. an appropriate ibts structure cannot only promote social equity and efficiency of the subsidies mechanism, but reflect the supply costs, improve energy efficiency and encourage energy saving. the first step is to design of the number of blocks. in theory, the larger the gaps between incomes of households are, the more tiers should be set to ensure the efficiency of income redistribution. however, considering the structure of electricity supply cost, the common structure of ibts usually consists of three to seven tiers. in other words, the income, expenditure and life style among different groups of households are the most important basics to determine the number of blocks. the second step is to set the volume of electric energy consumption in each block. the income is usually used as a measurement for the residential user’s ability to pay electricity bill. we adopt the approach whereby demand in electricity increase with income level barnes et al. (2004). thus, in this research the essential objective is to improve the current ibts, we will re-design the electric energy consumption of each block based on income, combining the electricity use of all equipment of typical groups households. the last step is to determine the electricity price for each block. considering the aims of ibts, multi-tiered increasing prices can be constructed so that lowest prices is a subsidized price and higher prices compensate for this subsidy, especially for the incremental cost of electricity supply for households. we will combine three different objectives: income redistribution, reflection of costs incurred by households for the power system; promotion of energy efficiency and energy saving to design the electricity price for block tariff structure. in fact, despite the same increasing block tariff principle, the literature review indicates that due to different national context, the design and structure of ibts vary among different countries. in general, the first blocks are designed to meet household needs for principal purposes, and the volume is higher in developed countries in comparing to that in developing countries boqiang and zhujun (2012). the number and scale of blocks are also different depending on the characteristics of residential consumers as well as social policies in electricity pricing of each country. in this paper, we will analyze and evaluate the key of current ibts structure (numbers of blocks, the volume and price in each block) implemented since 2014 before improve it. our analysis and evaluations will be based on the regulatory objectives as described in table 2 below. for improving the tariff structure, a new design of ibts for residential electricity use in vietnam will be proposed. the key of ibts will be designed on the basis of reasonable harmonization of electricity pricing policy targets in the new context of power supply and demand. on the issue of data collection for evaluation analysis, all secondary data on the power system is collected at evn and its member electricity distribution companies, the income of table 2: regulatory objectives for analysis of current tariff structure objective definition sustainability cover economics cost of electric service, reflect the cost incurred by customer for power system allocative efficiency provide the price signals for efficient use of resources productive efficiency create incentives for cost minimization equity protect poor households in terms of access and affordability source: elaborated by author bui: improve the incremental block tariffs of electricity: to harmonize pricing policy targets in the new context of power supply and demand in vietnam international journal of energy economics and policy | vol 11 • issue 5 • 2021 493 household data is collected at the general statistics office. for the primary data that determines the characteristics of residential users (characteristic of income, expenditure for electricity consumption, volume of electricity consumption, tou structure of consumption etc.), surveys are conducted on a large scale (more than 8000 households surveyed) to ensure the reliability of the statistical data. the method of calculating sample size of households according to the normal distribution function is used to determine the minimum number of samples. 4. assessment of the current situation of the ibts for domestic use 4.1. setting the number of blocks and the volume of electricity consumption in each block in vietnam, the current ibts structure is divided into 6 blocks without considering the difference between rural and urban residents, and residents in mountainous, island, border areas not connected to the national grid, even though the income, expenditure and lifestyle among different areas differ clearly. large gaps between rural and urban households in electricity consumption are also found by analyzing the survey results specially the ownership of electrical equipment. table 3 shows the structure of residential users and indicates that 69.65% (2019’s data) residents consume less than 200 kwh/month and most of them are in the countryside (surveyed in three regional electricity distribution companies). however, it isn’t necessary to separate the rural and urban households for following two reasons: first, poor households, according to government standards, will be paid the first 30 kwh of electricity from the state’s budget; second, with the characteristics of the increasing block tariff, low electricity consumption means that at the first blocks the price of electricity is also low. in contrast, we believe that it will be more reasonable and practical to re-design the ibts with five-tier structure rather than the current six-tier structure. there are many reasons to explain our re-structure. first, six-tier structure seems too many, too detailed compared to the changes in electricity consumption of households in current blocks structure and complicated in the process of electric power business management especially when there are more than 26 million consumers. it is necessary to study the reduction to ensure the simpler and more effective application. second, the volume of electricity use in the first block of 50 kwh/month, designed in 2014, is too low in the actual context of electric power consumption. moreover, the percentage of these households has decreased continuously over time (table 3) and it is only 14.29% in 2019. thus, the basic electricity demand of low income residents in rural and urban area has gradually increased and it would be appropriate to combine the first two blocks into one with the more suitable volume. third, according to the date of the general statistics office, people’s income is now divided into 5 groups, so the five-tier should be set for residential user instead of the actual six-tier structure. therefore, from the structure of consumer households according to the current 5 levels of income and current 6-tiers of electricity consumption, we will propose a new five-tier structure. for setting the volume of electricity consumption in each block, as mentioned above, our method is based on the statistic on income of groups of households, combined with the electricity use for all appliances that we surveyed all over vietnam. in fact, the analysis of business data for the past 3 years (2017-2019) continues to maintain the same household structure: the largest number of households consuming 101 to 200 kwh/month was 36.6%; a very small proportion of 6-7% of households consumed over 300 and over 400 kwh; regarding the variable trend, the number of households in the first two blocks has decreased continuously over the years,; moreover, households that consume a lot of electricity gradually increase, although the number of households has not increased much, but the volume of electricity consumption increases remarkably, according to the statistic in 2019, the households in the last block (consuming >400 kwh/month) only account for 8.32% of the total number of households, but they consumed up to 36% of the total residential electricity quantity and contributing about 42% of the household turnover. based on the surveyed data, we found that the income, expenditure and lifestyle among different households in the last blocks differ greatly. these analysis results allow us to re-design a new tariff structure aiming at improving the ibts to better suit the new context of electricity supply and demand. 4.2. electricity supply cost reflection and price of each block according to evn’s electricity load research in 2019, household’s electric load is the worst load of the power system when the difference between pmin and pmax is over 50.7% (table 4) and households electric load mainly contribute to power system’s evening peak. therefore, using an ibts is still suitable for this customer type because electricity consumption volume affects supply costs and also reflects demand characteristics. we clarify the relevance of the structure of incremental blocks prices with the electricity supply cost by analyzing household’s cost in the first and last blocks. for households of first block whose consumption is less than 50 kwh/month, the current price is only 92% of the average retail price approved by government. to do this analysis, in the first step, we conducted a survey of households of all 5 distribution companies-members of evn to find out the electricity consumption characteristics of these households and the survey data is treated as typical daily electricity consumption and in details according to low, normal and peak hours. according to the table 3: structure of residential users following consumption blocks cumulative structure of electricity consumers (%) 2017 (%) 2018 (%) 2019 (%) number of households below 50 kwh (block 1) 17.1 16.5 14.29 number of households <100 kwh (block 2) 39.8 38.2 32.99 number of households <200 kwh (block 3) 76.1 75.5 69.65 number of households <300 kwh (block 4) 89.0 89.0 85.06 number of households <400 kwh (block 5) 94.0 94.1 91.69 number of households >400 kwh (block 6) 100 100 100 source: results of survey, treated by author bui: improve the incremental block tariffs of electricity: to harmonize pricing policy targets in the new context of power supply and demand in vietnam international journal of energy economics and policy | vol 11 • issue 5 • 2021494 survey data, households with consumption below 50 kwh/month have the consumption structure of 12.7% in low hours, 38.9% in normal hours, and 48.5% in peak period. in second step, we calculated the cost of electricity supply and determine the variation of costs according to peak, normal and low hours. after that, we processed the secondary data about electricity supply cost in time of use from the marginal cost interpolated from the marginal price of the electricity market of vietnam (smpthat means the price of the most expensive offer per hour needs to be mobilized to meet the load after arranging bids in ascending order from low to high). however, the electricity market in vietnam is designed with “cost based” method, so in addition to smp, power plants are also compensated with the hourly capacity price (can) calculated in advance annually according to the operational plan in the electricity market. therefore, the full market price for electricity is paid for power plant: fmp = smp + can (figure 2 for results of 3 years of fmp variations). on the basis of the full marginal price of the hours of the typical day in 2019, we perform the necessary calculation of variable trend of cost for 3 time frames and extra charge with the costs, the value of loss of transmission and distribution to low-voltage level for households purchasing electricity (in 0.4 kv), we have the results of variation of supply cost in time of use (tou) compared with the total average cost: 85.2% for low hours, 102.8% for normal hours and 110.5% for peak period. in combination with the electricity consumption structure of household user below 50 kwh/month, we calculate the average cost caused by this residential user is: 104.7% = (85.2% * 12.7% + 102.8% * 38.9% + 110.5 * 48.5%) compared with the total average cost. with the similarity between the total average cost and average retail price, the retail price for these households is much lower than the cost of supply. indeed, the supply cost for the users of the first block is 104.7% of total average price but the selling price for these users is only 92% of average retail price. furthermore, poor households, according to government standards, are paid the first 30 kwh/ month. in the analysis of households in the last block consuming over 400 kwh/month, we also obtained similar results: the retail price structure setting for each block is very different from the cost caused to the electricity system. moreover, according to the data provided by evn that we treated and showed in table 3, up to 69.65% of residential households have consumption below 200 kwh/month. calculations in table 5 show that, 69.65% of households corresponding to 43% of total residential electricity consumption are enjoying a lower price than the electricity supply average cost. in this situation, 400 500 600 700 800 900 1000 1100 1200 1300 1400 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 fmp (vnd/kwh) of 3 years 2017-2018-2019 figure 2: variation of full market price of typical day in electricity market of vietnam source: evnnational load dispatching centre table 5: summary of average electricity price for groups of residential households in 2017-2019 average electricity price for each household by block (vnd / kwh) 2017 2018 2019 less than 50 kwh 1484.0 1484.0 1549.0 from 51-100kwh 1500.6 1501.0 1566.8 from 101-200 kwh 1593.2 1593.3 1662.0 from 201-300 kwh 1750.2 1750.1 1825.6 from 301-400 kwh 1929.5 1929.2 2013.2 from 401 or more 2248.7 2251.9 2365.2 the electricity supply average cost (vnd/kwh) 1665.35 1667 1723.3 source: sales department, evn finance department, compiled by the author to ensure the financial balance of evn, households consuming more than 300 kwh/month must pay a much higher price. the important cross-compensation is happening among residential consumers while they share the same characteristics and nature of electricity consumption. the price between the levels is no longer appropriate. thus, in terms of electricity prices for each block, it is also necessary to make adjustments to ensure more harmonization of different pricing objectives. 5. an improvement of tariff structure: the new design of ibts for residential electricity use in vietnam as mentioned above, the improvement of incremental block tariff includes: re-setting the numbers of blocks, the volume of electricity consumption in each block and re-determining the electricity table 4: difference between pmin et pmax (in %) of household’s electric load for typical day 6 low hours 49.3% 49.8% 51.9% 51.9% 55.6% 57.9% 13 normal hours 61.7% 62.4% 65.3% 68.1% 71.3% 73.7% 75.9% 76.1% 77.3% 77.7% 78.2% 79.0% 80.9% 5 peak hours 82.2% 88.5% 89.5% 99.9% 100% source: evn’s data, treated by author bui: improve the incremental block tariffs of electricity: to harmonize pricing policy targets in the new context of power supply and demand in vietnam international journal of energy economics and policy | vol 11 • issue 5 • 2021 495 table 7: electrical load structures of lowpeak points according to the new structure of five-tiers structure of new five-tiers (kwh/month) <100 101-200 201-400 401-700 >700 lownormalpeak electricity use structure (in %) normal period 41.366% 43.350% 43.390% 42.906% 42.828% low period 14.245% 18.459% 21.165% 23.991% 25.216% peak period 44.389% 38.192% 35.444% 33.103% 31.956% supply cost structure at 0.4 kv normal period 104.7% low period 87.1% peak period 112.5% source: synthetized and calculated by author table 6: new structure of numbers of blocks and the volume of electricity use in each block structure of the current 6-tiers (kwh/month) 50 51-100 101-200 201-300 301-400 >400 percentage of households in 2019 14.29% 18.70% 36.66% 15.41% 6.63% 8.32% proposed fivetiers structure (kwh/month) <100 101-200 201-400 401-700 >701 percentage of households in new tariff structure 32.99% 36.66% 22.04% 6.06% 2.26% income of 5 levels of household (in millions vnđ) <5 5 to <10 10–<15 15–<20 above 20 source: evn’s data collected by author and general statistics office for income data price of each block. the increasing block tariff structure will be improved based on the following fundamental combinations: (1) variation of supply cost in time of use; (2) electric load characteristics of residential use, electricity consumption, income structure; expenditure for electricity of households and structure of current number of consumers; (3) effective and saving electricity use (4) efficiency of income redistribution; (5) assurance of the financial balance for electricity of vietnam and its member units in comparison with the current situation. 5.1. regrouping of households for designing of numbers of blocks and the volume of electricity use in each block the first step of the improvement is to design the numbers of block by more suitable regrouping of households. from the analysis results of the current situation, the current number of levels (6 levels) is too much compared to the fluctuation of costs and complexity in business management, therefore, in the proposed plan, we have studied 03 options to reduce the number of blocks: five-tiers, four-tiers, and three-tiers. balancing between other pricing targets, the most optimal one is the five-tier structure. this option is researched on the basis of the regrouping of households in the current blocks 1 and 2 into one block and re-dividing the volume of electricity to suit the consumption characteristics and the income pyramid of the current households especially for group of high-consuming households. in addition, the reorganization of five-tier structure corresponds to the classification of 5 income levels of households according to the classification of the general statistics office (we adopted the logic according to which demand for electricity increases with income level of households, barnes et al., 2004). the description of the new design of numbers of blocks and electricity volume for each block is specified in table 6. 5.2. calculating the electricity price of each block and proposal of new ibts for improving the tariff structure in term of electricity price for each block, we combined the cost-plus method to determine the supply cost by voltage levels and the marginal cost method to calculate the low, normal and peak cost structure at each voltage level. the calculation results show that at 0.4 kv (all residents consume at this voltage level) the time of use cost structure is: 87.1% in low hours, 104.7% for normal and 112.5% in peak hours compared to the average cost of commercial electricity. to get these results, we are based on different cost data from the past 3 years 2017-2019 and analyzed the forecast of these costs for the current and future years according to the fluctuating trends of the past and some other hypothesis for determining this time of use cost structure. after that, from the new design of number of blocks and limits between them, we will calculate the electricity price of each block. the method of calculation is as follows: from the surveyed data, we synthesize and calculate the structure (in %) of electricity consumption in the low-normal and peak periods for each type of household as demonstrated in table 7. from that we calculate electricity volume of each time period for typical households and allocate it into each block according to the principle “increasing volume from low to normal to peak periods corresponding increasing block.” combined with the time of use cost structure, the household’s cost simulated by each block will be calculated for each typical household in each block, the description of these calculation results is indicated in table 8. from the calculation results specified in table 8, with the weighted average method, according to the proportion of households consuming the volume of electricity level at each tier, the price of the 5 different blocks is calculated. for example, 32,99% of users consume up to 100 kwh/month; 36,66% consume from 101 up to 200 kwh/month, 22,03% from 201 up to 400 kwh/month, 6.06% from 401 up to 700 kwh/month and 2.26% from 701 kwh/month or more. that means the same structure of households at each block consume all the first 100 kwh. with the calculation of house’s cost simulation for the first tier (that means 100 kwh): 105.7% for consumer block 1, 98% for block 2, 89.8% for block 3, 87.1% for block 4 and 87.1 for consumer block 5. by the weighted average calculation method, we find the price following supply cost of the first block is 97.83% (97.83 = 32.99%*105.7% + 36.66%*9 8%+22.03%*89.8%+6.06%*87.1%*+2.26%*87.1%). similarly, we calculated the price of second block, we have in total 67% of bui: improve the incremental block tariffs of electricity: to harmonize pricing policy targets in the new context of power supply and demand in vietnam international journal of energy economics and policy | vol 11 • issue 5 • 2021496 table 8: calculations of typical household’s cost simulated by each block household in block 1: ≤100 kwh/month structures blocks structure ≤100 time of use volumes structure (kwh) low 14.25 14.25 normal 41.37 41.37 peak 44.39 44.39 time of use costs structure (%) low 87.1% 87.1% normal 104.7% 104.7% peak 112.5% 112.5% household’s cost simulated by each block 105.7% household in block 2: ≤200 kwh/month structures blocks structure ≤100 101-200 time of use volume structure (kwh) low 36.92 36.92 normal 86.70 63.08 23.62 peak 76.38 76.38 time of use costs structure (%) low 87.1% 87.1% normal 104.7% 104.70% 104.70% peak 112.5% 112.5% household’s cost simulated by each block 98.0% 110.66% household in block 3: ≤400 kwh/month structures blocks structure <100 101-200 201-400 time of use volume structure (kwh) low 84.66 84.66 normal 173.56 15.34 100.00 58.2 peak 141.78 141.78 time of use costs structure (%) low 87.1% 87.1% normal 104.7% 104.70% 104.70% 104.70% peak 112.5% 112.50% household’s cost simulated by each block 89.8% 104.7% 110.2% household in block 4:≤ 700 kwh/month structures blocks structure <100 101-200 201-400 401-700 time of use volume structure (kwh) low 167.94 100.00 67.9 normal 300.34 32.06 200.0 68.3 peak 231.72 231.7 time of use costs structure (%) low 87.1% 87.1% 87.1% normal 104.7% 104.70% 104.70% 104.70% peak 112.5% 112.5% household’s cost simulated by each block 87.1% 92.3% 104.7% 110.7 household in block 5: >700 kwh/month structures blocks structure <100 101-200 201-400 401-700 >700 time of use volume structure (kwh) low 226.98 100.00 100.00 26.98 normal 385.47 173.02 212.45 peak 287.64 87.55 200.09 time of use costs structure (%) low 87.1% 87.1% 87.1% 87.1% normal 104.7% 104.70% 104.70% peak 112.5% 112.5% 112.5% household’s cost simulated by each block 87.1% 87.1% 102.3% 107.0% 112.5% source: calculated by author table 9: calculation of price structure following supply cost structure structure of households kwh/month ≤100 (%) 101-200 (%) 201-400 (%) 401-700 (%) >700 (%) total (%) proportion of households consuming by each electricity consumption tier (%) tier 1-100 kwh 32.99 36.66 22.03 6.06 2.26 100 tier 2-100 kwh 54.70 32.88 9.04 3.37 100 tier 3-200 kwh 72.60 19.97 7.44 100 tier 4-300 kwh 72.86 27.14 100 tier 5-over 700 100 100 structure of price following supply cost kwh/month ≤100 (%) 101-200 (%) 201-400 (%) 401-700 (%) >700 (%) structure price (%) cost and calculation of price of each block (%) block 1 105.7 98.0 89.8 87.1 87.1 97.83 block 2 110.7 104.7 92.3 87.1 106.27 block 3 110.2 104.7 102.3 108.51 block 4 110.7 107.0 109.70 block 5 112.5 112.50 source: calculations of author bui: improve the incremental block tariffs of electricity: to harmonize pricing policy targets in the new context of power supply and demand in vietnam international journal of energy economics and policy | vol 11 • issue 5 • 2021 497 table 10: proposal of new ibts structure for residential electricity use structure group of customers proportion in comparing with adjusted average retail price approved by government (%)retail price of electricity for residential electricity use incremental block tariff block 1: from 0 to 100 kwh 95 block 2: from 101 to 200 kwh 113 block 3: from 201 to 400 kwh 137 block 4: from 401 to 700 kwh 151 block 5: from 701 kwh or more 156 source: proposal of the study residential users consume from 101 kwh/month or more. it can be seen that 54.70% of users consume from 101 up to 200 kwh/ month, 32.88% from 201 up to 400 kwh, 9.04% from 401 up to 700 kwh and 3.37% from 701 and more. again, using the weighted average calculation method, the price of second block is 106.27%. with the same calculation, we find the price of all other blocks as demonstrates table 9. from these results, we proceed to propose the new incremental block tariff structure to improve the current structure. we have developed options based on objective of harmonizing other pricing targets including cost reflection, efficient use of electricity savings, income redistribution, and financial balance and assessed the impact of each option on consumers, evn’s financial balance and on the economy in comparison to the current price structure. after the impact analysis, the best option for improving the tariff structure for households is proposed in table 10. indeed, the calculation results show that the above proposal is a positive one and creates a good effect when calculating the impacts on both consumers, evn and society. firstly, evn’s revenue from household customers remains unchanged and for that, evn’s financial balance is not affected by this price structure adjustment. in addition, electricity businesses will find management much simpler when the number of levels is reduced to five-tiers. for electricity consumers, the reorganization of numbers of blocks and the volume of electricity consumption in each block is more suitable for actual consumption structure and income groups. especially, if the current tariff is often criticized by charging too low for low-consumption households and too high for important-consumption households, the prices in new structure are more reasonable for all. in fact, the monthly electricity bills of the users of the first two blocks insignificantly increase up to only 2,797 vnd/month (the actual bill for the first 50 kwh/month is 83,900.00 vnd). the expenditure for electricity of the households of blocks 3 and 4 also increase slightly by vnd 6,525 and vnd 8,390/month, respectively. these prices more closely reflect the cost of electricity supply for this group of households in comparing with the current tariff structure. in contrast, for the users consuming from 301 kwh/month onwards, the electricity bills decrease. we calculated household consuming 900 kwh/month, the monthly electricity bill will decrease: -81,100 vnd/month and the larger the consumption output, the larger the reduction in money expenditure will be. this result allows to reduce cross-compensation between households, that is one of vietnamese’s government objectives in electricity pricing policy. regarding the cpi, there would be no negative impact when total expenditure on residential electricity remains unchanged compared to the current tariff structure. finally, regarding the support policy for poor household, the current support is equivalent to first 30 kwh/month, calculated at the price of the first block. if the price of block 1 is adjusted upwards, it will increase the government’s spending on supporting the poverty group. however, this increase is not significant, so it does not create negative effects on the government’s budget. altogether, the proposed ibts for residential electricity use is developed in balancing pricing goals. the results of the impact assessment show that from consumers, to evn, the government and the economy is very harmonious: the price structure reflects supply costs more closely, ensuring more equity among households. the proposed improvement of tariffs structure ensures revenue of electricity sector from household consumption and does not cause negative impacts on social life, and does not significantly increase the budget to support the low income group related to electricity consumption. 6. conclusion and suggestions the paper aims to research on improving the current ibts implemented in vietnam for residential electricity use. the current situation assessment showed that the current ibts structure designed in 2014 is no longer suitable due to changes in electricity supply and consumption in the new context and for other objectives of electricity pricing policy. the research has built the basis of calculation and proceeds to propose the most reasonable solution to improve the tariffs structure. by reducing the numbers of blocks, based on the costs incurred by different group of households and the characteristics of households’ income, the new structure of five-tiers is designed for residential electricity use. the proposed new ibts structure is detailed, specific, clearly grounded and consideration of the possibility of adjustment in the coming years to ensure the effectiveness of the proposed tariffs structure. the new ibts structure has also reached its objective of harmonizing different pricing targets in the new context of electricity supply and demand in vietnam. some suggestions can be drawn from this research. first, this article only focuses on the research objective of improving the incremental block tariff for residential electricity use without studying other types of tariff for this customer group. therefore, the limitations of the ibts still exist for example, a sudden increase in electricity bills of households in the summer due to the incremental tariff effect especially in the north of vietnam or the hypothesis of low income-low electricity use is not completely true when some low income users with a large family may consume more bui: improve the incremental block tariffs of electricity: to harmonize pricing policy targets in the new context of power supply and demand in vietnam international journal of energy economics and policy | vol 11 • issue 5 • 2021498 electricity and pay the high price. furthermore, in parallel with the improvement of the tariff structure for residential electricity users, it is necessary to study and propose a periodic adjustment mechanism of retail prices. electricity’s retail prices are regulated by the government with the authority of the prime minister and price adjustments are not cyclical. for example, the last adjustment of electricity retail prices was made in march 2019, which means that the retail price has not changed for more than 2 years. this will cause great pressure for the next adjustment, so electricity prices are always a hot topic in vietnam. references aiming, z. (2012), comparative analysis and policy study on residential electricity bills in selected adb member countries, adb sustainable development wp series, asian development bank. barnes, d.f., krutilla, k., hyde, w.f. (2004), the urban household energy transition: energy, poverty and the environment in the developing world, world bank energy sector management assistance program. boqiang, l. and zhujun, j. (2012), designation and influence of household increasing block electricity tariffs in china. energy policy, 42, 164-173. borenstein, s. (2008), equity effects of increasing-block electricity pricing, csem wp, no. 180. bui, x.h. (2008), energy pricing theory. ch. 2. hanoi, vietnam: statistics. p99-236. conseil français de l’energie. (2014), analyse théorique et modélisation de la formation des prix de l’électricité en france et en allemagne. vol. 79. rapport final, contrat. p30. evn. (2020), report of electricity load research for different users. department of electricity business, report, electricity of vietnam. munasinghe, m. (2009), electric power pricing policy. staff working paper no. swp 340. washington, dc: the world bank. pardina, m.r. (2015), assessment of tariff structure and tariff framework, distribution efficiency project (p 125996), moit-wb. percebois, j. (1988), economie de l’energie, edition economica. ch. 4. energie et théorie des prix, la recherche de l’optimum collectif. p235-244. porter, r.c. (1996), the economics of water and waste: a case study of jakarta, indonesia. ashgate publishing limited, farnham, united kingdom. usaid. (2013), challenges in pricing electric power service in selected asean countries, report produced for usaid prepared by the center for the advancement of trade integration and facilitation (catif), inc., international resources group (irg). 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 2 • 2022394 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(2), 394-399. parametric study of a hybrid renewable energy power generation system in the colombian caribbean region jhan piero rojas1*, gonzalo romero garcía2, dora villada castillo3 faculty of engineering, universidad francisco de paula santander, cúcuta, norte de santander, colombia. *email: jhanpierorojas@ufps.edu.co received: 17 december 2021 accepted: 01 march 2022 doi: https://doi.org/10.32479/ijeep.12828 abstract the global environmental problems have increased the interest in renewable energies, in this article a wind-solar hybrid system is proposed as an alternative for energy production. to carry out this study, the research was divided into three stages, the first one consists of determining the behavior of a solar and wind system, the second stage focuses on determining the ideal location to implement the hybrid system and the third stage determines the composition of wind and pv devices that offers greater efficiency. after completing the three stages proposed above, the optimal locations for the implementation of a wind-solar hybrid system are simón bolívar and puerto bolívar. keywords: renewable energies, solar energy, wind energy, wind potential jel classification: q42 1. introduction renewable energies are an alternative to fossil fuels that can significantly reduce carbon dioxide emissions, including geothermal, solar, wind, biofuel and biomass; renewables have seen rapid growth in recent years due to cost reductions in wind and photovoltaic systems, in addition to a shift in energy policies in favor of renewables, they accounted for 26% of global electricity generation in 2018, however electricity only accounts for 20% of global energy demand, making the use of renewable sources in sectors such as transportation and thermal applications critical to accomplish the transition (croutzet and dabbous, 2021; ahmed et al., 2021; cole et al., 2021). in addition, it has been seen how corporations have increased their participation in the use and purchase of renewable energy, due to the pressure imposed by customers, investors and competitors, this behavior is expected to continue and increase, in the united states in 2010 the use of renewable energy in corporations was 5% by 2019 was approximately 13%, it is expected to exceed 20% by 2030 (o’shaughnessy et al., 2021; bistline et al., 2021). the use of renewable energies not only offers environmental benefits, but also economic and political benefits as they are considered less volatile than fossil energy sources. their integration into the energy grid requires work and planning in order to obtain a good synergy with other energy generation alternatives (noorollahi et al., 2021), wind and solar energy are widely used energy sources that have recently gained space due to their lower cost of implementation. the effect that the social aspect has on the development of alternative energy sources is seldom studied, which is why the social aspect of the development of alternative energy sources is rarely studied (pavlowsky and gliedt, 2021) the study of the local perception in the region of oklahoma, usa, where the impact and perception of wind energy in the community that inhabits the region is studied, shows a mostly positive perception, which increases the knowledge of how it affects individuals and communities that host the turbines and the infrastructure related to the system. this journal is licensed under a creative commons attribution 4.0 international license rojas, et al.: parametric study of a hybrid renewable energy power generation system in the colombian caribbean region international journal of energy economics and policy | vol 12 • issue 2 • 2022 395 it is important to know the effect that certain factors have on the energy production of a system (diaz et al., 2021) performed a cfd (computational fluid dynamics) simulation to know the effect of the wake and the terrain on the energy generation of a wind system, by applying an interpolation-extrapolation methodology to the simulation the computational cost was reduced; from the results it was obtained that only taking into consideration the wake and the terrain adversely affects the results, while taking into consideration both parameters values close to the measured ones are obtained, also increasing the number of simulated direction sectors from 16 to 32 affects the results significantly. wind energy can not only be harnessed on the ground, it can also be harnessed at sea, for this case offshore wind turbines (owts) are used, (wang et al., 2022) propose a design optimization for systems using this type of turbines using a differential evolution algorithm accelerated by the use of gpu, the optimized hybrid farm had 37.75% more energy output and 43.65% less wave load at the base of the wind turbines. solar energy has been implemented to supply the existing energy demand in mining, since solar thermal and solar photovoltaic energy can be used to produce energy and heat needed in the mining process, so its applicability has been investigated in several academic works (behar et al., 2021; igogo et al., 2021). the main contribution of this research lies in the determination of the energy potential with renewable sources, present in the caribbean region of colombia; thus, showing the key points for the development and installation of projects whose renewable sources in obtaining energy are solar or wind. in the following sections of the article, the technical parameters concerning the proposed hybrid plant design are provided, as well as all the information corresponding to solar and wind resource inputs, the fundamental equations and the research method used are also presented, and the information corresponding to the results of this research is shown, using graphs and data tables. finally, the conclusions formulated at the end of this research are shown. 2. methodology to perform this study, the investigation was subdivided in three stages, which are related and are consequent. the first stage to perform consist to determinate the behavior of both wind and solar energy generating devices, in function of data collected from the meteorological stations up to 10 years of measurements. this stage is focused from an energetic perspective, which means only will take care of results like energetic production and renewable fraction, without data concerning costs, to estimate in which places the system will take more advantage of the renewable sources. the second stage consists into realize a study to determinate in which place is more efficient the use of a hybrid system compounded by wind and pv system, working at the time. this stage is focused from an economic perspective, this time it will be take care of energetic production, renewable fraction, and results like total net present cost and the cost of energy, to determinate in which place the system will get the optimal behavior. the third and most important stage is to determinate what composition of wind and pv devices are the most efficient, in function of the load demand and the characteristics of the selected place. once this is finished, it will have the net power that the plant can develop and his optimal composition. the first and second stage are calculated through specific equations, and the collected data from the results is digitalized in excel tables and presented as graphs. the third stage is more complex than his previous one, because the optimization process to be implemented here is through multi-objective solver from optimtool complement of matlab® and plotted as a pareto front. however, before of this it is necessary to obtain data varying the number of devices for pv and wind turbines for the selected place. later these data are used in curve fitting complement of matlab® to determinate the corresponding function for two main objectives of optimization (cost of energy and co2 emissions) which will be used in optimtool. the large-scale implementation of an energy production system based on non-conventional sources is important in the future because it can eliminate the dependence on fossil fuels for this purpose, and also directly confront the problem of global warming, thus increasing the quality of life of many populations around the world. this is why renewable energy is currently a growing and young field of research, technology, and production, projected to be the main axis of the first world countries in a few years (adib, 2019). solar energy is a renewable energy source which is obtained from the solar radiation emitted and there are 3 methods of obtaining this resource: photovoltaic, photo-thermal, and thermoelectric. of which the photovoltaic method stands out, since it is the method used to directly obtain electrical energy and consists of transforming solar radiation into electricity through photovoltaic panels. to date, photovoltaic panels are used as an autonomous system and currently these systems have been spreading in the industrial and commercial sector (adib, 2019). wind energy is a resource which is obtained through the force of the wind, where the use of wind turbines or wind turbines are the most efficient and most used mechanism for obtaining this resource. this is produced by transforming the kinetic energy of the wind into mechanical energy using a wind turbine which transforms mechanical energy into electrical energy through a generator. one of the main trends or objectives in the development of wind turbines is the increase of the blade span, head height, and the increase of the total efficiency of the device, operating in coastal environments or even in the ocean, as well as reduction or braking mechanisms that help to maintain a constant speed in the turbine head to avoid overheating or failures due to vibrations (adib, 2019). 2.1. win turbines power output equations the power of the wind passing through the wind turbine,, is expressed according to the equation (1). 31· · · 2w w a vρ= (1) rojas, et al.: parametric study of a hybrid renewable energy power generation system in the colombian caribbean region international journal of energy economics and policy | vol 12 • issue 2 • 2022396 where ρ is the air density, a is the area displaced by the motor, and v is the wind velocity. the rotor shaft power is expressed according to the equation (2). ·s p vw c p= (2) where cp is the aerodynamic efficiency of the blades, which is a function of rotor speed ratio λ, and the angle of inclination of the blade β. the speed ratio of the rotor is given by equation (3). ·r r  = (3) where ωr is the speed of the rotor shaft turbine power output sw is expressed for the equation (4). ÿ 31 · · · · 2t p m g w a c   = (4) where ηm and ηg represent the efficiency of the gearbox and the generator respectively (chen et al., 2018). 2.2. pv output power equations the power of a pv array pvw can be calculated by the equation (5). · · · · · 1pv p ph p d s qv w n i v n i v exp ktan    = − −       (5) where np is the number of photovoltaic arrays connected in parallel, ns is the number of photovoltaic arrays connected in series, v is the output voltage of the pv array, q is the charge of an electron, k is boltzmann’s constant, a is the ideal junction factor which varies from 1 to 5 with 1 being the ideal value, t is the temperature of the solar cell. iph e id represent the photovoltaic current and the reverse saturation current, respectively iph in turn depends on solar irradiance and cell temperature, and can be calculated by the equation (6). iph=[iscr+ki•(t–tc)]•[s/100] (6) where iscr is the short-circuit current of the cell at reference temperature, ki is the short circuit temperature coefficient, tc is the reference temperature of the cell and s is the solar irradiance at mw/cm2. id depends on the temperature according to the equation (7). 3 1 1·( / ) · · ·gd c c c e i i t t exp q ka t t      = −         (7) where ic is the reverse saturation current under conditions of tc and eg is the band gap energy of the semiconductor used in the cell (singh, 2013). 2.3. energetic demand and fundamental variables for the correct development of this research, it was necessary to use an energy demand profile that best fits the current events in terms of energy requirements in the region. the objective of establishing an energy demand does not obey in a truthful way to the current real demand of the colombian caribbean region; on the contrary, it is based on the establishment of a comparison parameter to which all the parameters corresponding to each of the locations must be submitted, using the previously proposed energy generation system. figure 1 shows the type of profile used and its pre-established values (budes et al., 2020). it is also important to define the fundamental variables required by the software prior to the simulations. table 1 shows the values concerning each of the mentioned variables. it is important to highlight that each of these values plays a fundamental role in order to avoid errors in the simulations, so it is recommended not to modify them if you want to replicate this simulation. 3. results and discussion in this section of the article, you can find in a clear and concise manner, the results and their respective interpretation for each of the phases previously described in the development process of this research. 3.1. solar radiation assessment solar radiation is the main resource used by photovoltaic arrays to produce electrical energy, which is why figure 2 shows the different values for incident solar radiation; it should be noted that the values for total solar radiation, which is the sum of direct radiation and diffuse radiation, are shown in figure 2. the brightness index is a value between 0 and 1 that represents the fraction of incident solar rays that manage to completely penetrate the atmosphere until reaching the ground, being 1 the value in which all of them manage to penetrate the atmosphere, and 0 in null value; this parameter is directly related to the climatic state of the area, so it tends to vary depending on the day and the time of the year. temperature is a resource that alters the operation of wind turbines, due to the modification of air density as a function of this, but in turn alters the operation of photovoltaic arrays in terms of energy delivery, which is why the values for the temperature of the region are presented in figure 3. 3.2. first stage: energetic perspective in order to determine where in the caribbean region of colombia the installation of a hybrid wind-solar power generation system table 1: parameters used in the simulation processes by homer pro parameter value unit grid price* 0.2 usd/kwh simulation period 10 years annual scaled average 24000 kwh/day pike 1833.2 kw discount rate* 8 % rate of inflation* 2 % wind turbine hub height 80 meters grid co2* 0.1 kg/kwh pv o&m cost per unit 10 usd/year wind o&m cost per unit 30000 usd/year rojas, et al.: parametric study of a hybrid renewable energy power generation system in the colombian caribbean region international journal of energy economics and policy | vol 12 • issue 2 • 2022 397 can work best, it is assumed that our previously proposed system is the optimal one to be installed. in that order of ideas, the results of the simulations of the first phase will show the technical specifications that our system must have to be considered as optimal according to the location in which it is located, considering only the variables of solar radiation, temperature, and wind speed, in each of the measurement stations. similarly, a comparison is made between the nominal power of the photovoltaic system for each location, against the energy production produced by this system during a year, as shown in figure 4. from the above graph it can be seen that there is a variation between the nominal power and energy production for each location, likewise, it can be seen that the places where more energy is produced per year are puerto bolivar and alfonso lopez; however, this does not mean that they are the ideal locations. to determine in which locations the photovoltaic system works optimally, it is necessary to quantify the efficiency of these devices. the fraction between the energy produced per year and the nominal power, in equivalent units, results in a value expressed in hours per year (h/year), whose value is nothing more than an estimate of hours in which, in theory, the system should work compared to the total hours of 1 year; thus, an ideal system is one that takes figure 1: load profile used for this case study figure 2: (a and b) load solar radiation data for the meteorological stations a b figure 3: (a and b) temperature data for the meteorological stations a b rojas, et al.: parametric study of a hybrid renewable energy power generation system in the colombian caribbean region international journal of energy economics and policy | vol 12 • issue 2 • 2022398 advantage of the greatest amount of solar energy possible and can generate a good amount of electrical energy. considering the above, it can be seen that the systems that develop a greater amount of “hours per year” are those located in puerto bolivar, alfonso lopez, and simon bolivar; which means that in these places our photovoltaic systems will take better advantage of solar energy. after determining our optimal locations for the photovoltaic system, it is necessary to determine the optimal locations for the wind system. since we have designated the use of wind turbines with a head height of 80 meters, and rated power of 1.5 mw, it is necessary to run a comparison between the number of turbines determined by the software to make the system “optimal,” and the production per year that we have for each location, as shown in figure 5. it can be clearly seen that in 3 locations 3 wind units are required for the system to be optimal, in other 3 only 2 are required, and in simón bolívar a total of 9 are required, likewise, it can be seen that the locations that stand out for their energy production are simón bolívar, puerto bolívar, rafael nuñez, and ernesto cortissoz; however, in order to consider the ideal locations for the wind system, it is necessary to verify the fraction of energy produced by each wind unit, with the objective of determining in which location 1 unit can produce more energy than in any other location. considering the above, it can be clearly seen that simón bolívar, puerto bolívar, rafael nuñez, and ernesto cortissoz have the highest wind production indexes, among which puerto bolívar and simón bolívar stand out because they are also optimal locations for the photovoltaic system. knowing the ideal locations for the wind system, it’s necessary to determine which of the aforementioned locations for both systems are ideal to take maximum advantage of both solar and wind energy, which is why it is necessary to analyze the percentage of the renewable fraction present in each of the aforementioned locations, as shown in figure 6. the renewable fraction of a system is nothing more than the fraction between the amount of clean energy produced against the total amount of energy demanded in our simulation, considering that all the energy that the system cannot supply must be compensated with energy from coal-fired power plants or other means of conventional energy production. once the optimal location for the installation of a hybrid system of wind and solar production is found, it is possible to make modifications to the system in order to reduce production costs, which represents a reduction in the unit cost of energy and increases the quality of life of the potential beneficiaries of such a system. considering the locations selected above, and taking into account that the same energy demand was applied for all locations, it is assumed that the renewable fraction is directly proportional to the amount of clean energy produced in this case. due to this, it can be clearly seen that the optimal locations for the installation of a hybrid wind-solar system are simón bolívar and puerto bolívar, which in turn will be the pilot locations for the development of phase 2 of this research. 4. conclusions the global environmental problems have increased the interest in renewable energies, in this article a wind-solar hybrid system figure 4: comparison between nominal system power and energy production per year of the photovoltaic system figure 6: comparison between production and renewable fraction for each location figure 5: comparison between number of wind turbines and annual production for each location rojas, et al.: parametric study of a hybrid renewable energy power generation system in the colombian caribbean region international journal of energy economics and policy | vol 12 • issue 2 • 2022 399 is proposed as an alternative for energy production. to carry out this study, the research was divided into three stages, the first one consists of determining the behavior of a solar and wind system, the second stage focuses on determining the ideal location to implement the hybrid system and the third stage determines the composition of wind and pv devices that offers greater efficiency. la guajira has a high energy potential compared to other departments in the caribbean region of colombia, due to the high availability of the resources in question, which in turn is attributed to the relief of the terrain that does not pollute the air currents too much, and the low atmospheric concentration which favors that a large amount of solar radiation can be harnessed. in addition, it is established that it is possible to use a hybrid generation plant using solar and wind devices to meet the energy demand of a particular region, and that this type of project is not only energy efficient, but also considerably reduces the emissions of polluting gases from coal-based thermoelectric plants that are mainly used in this region of colombia. in this way, dependence on fossil fuels is reduced without altering energy production. this investigation also contributes a methodology to recreate this kind of studies on another location. references adib, r. (2019), renewables 2019 global status report collaborative, ren21. available from: http://www.ren21.net/gsr-2019/pages/ foreword/foreword ahmed, s., li, z., javed, m.s., ma, t. (2021), a review on the integration of radiative cooling and solar energy harvesting. materials today energy, 21, 100776. behar, o., peña, r., kouro, s., kracht, w., fuentealba, e., moran, l., sbarbaro, d. (2021), the use of solar energy in the copper mining processes: a comprehensive review. cleaner engineering and technology, 4, 100259. bistline, j., blanford, g., mai, t., merrick, j. (2021), modeling variable renewable energy and storage in the power sector. energy policy, 156, 112424. budes, f.a.b., ochoa, g.v., obregon, l.g., arango-manrique, a., álvarez, j.r.n. (2020), energy, economic, and environmental evaluation of a proposed solar-wind power on-grid system using homer pro®: a case study in colombia. energies, 13(7), 13071662. chen, j., wang, f., stelson, k.a. (2018), a mathematical approach to minimizing the cost of energy for large utility wind turbines. applied energy, 228, 1413-1422. cole, w., gates, n., mai, t. (2021), exploring the cost implications of increased renewable energy for the u.s. power system, 34, 106957. croutzet, a., dabbous, a. (2021), do fintech trigger renewable energy use? evidence from oecd countries. renewable energy, 179, 1608-1617. diaz, g.p.n., saulo, a.c., otero, a.d. (2021), full wind rose wind farm simulation including wake and terrain effects for energy yield assessment. energy, 237, 121642. igogo, t., awuah-offei, k., newman, a., lowder, t., engel-cox, j. (2021), integrating renewable energy into mining operations: opportunities, challenges, and enabling approaches. applied energy, 300, 117375. noorollahi, y., pourarshad, m., veisi, a. (2021), the synergy of renewable energies for sustainable energy systems development in oil-rich nations; case of iran. renewable energy, 173, 561-568. o’shaughnessy, e., heeter, j., shah, c., koebrich, s. (2021), corporate acceleration of the renewable energy transition and implications for electric grids. renewable and sustainable energy reviews, 146, 111160. pavlowsky, c.e., gliedt, t. (2021), individual and local scale interactions and adaptations to wind energy development: a case study of oklahoma, usa. geography and sustainability, 2(3), 175-181. singh, g.k. (2013), solar power generation by pv (photovoltaic) technology: a review. energy, 53, 1-13. wang, y., liu, z., wang, h. (2022), proposal and layout optimization of a wind-wave hybrid energy system using gpu-accelerated differential evolution algorithm. energy, 239, 121850. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 4 • 2022 575 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(4), 575-583. pass-through in colombia’s unregulated retail electricity market alex perez1*, jaime carabali2, luis meneses3 1professional, banco de la república de colombia, colombia, 2universidad icesi, colombia, 3 universidad cooperativa de colombia and universidad icesi, colombia. *email: alex.perez@correounivalle.edu.co received: 13 march 2022 accepted: 25 june 2022 doi: https://doi.org/10.32479/ijeep.13086 abstract this study analyzes the pass-through of wholesale costs to retail prices for unregulated users in the colombian electricity market, using monthly data from 2012 to 2019. this period encompasses moments with and without an el niño phenomenon. we use an empirical model to analyze the pass-through heterogeneity according to the characteristics of users and firms, showing that the pass-through is incomplete, differs according to the presence of el niño, and is heterogeneous. the pass-through was greater from september 2015 to may 2016 because an el niño caused hydrological resource scarcity and several critical thermal plants halted operations. in other words, the pass-through tends to be more comprehensive during an el niño event. additionally, the pass-through differs between firms with a high concentration of the market and the remaining firms and between urban and non-urban users. keywords: pass-through, electricity markets, wholesale costs, retail prices jel classifications: d82, d83, q49, l11, l94 1. introduction during the last decade, colombia has been hit by two el niño phenomena, one in 2009-2010 and one in 2015-2016, which were largely responsible for price increases in various markets. bejarano-salcedo et al. (2020) found that food prices and the general consumer price index increased substantially during these climate events. the impact on general prices runs through two channels, food prices and electricity prices. lozano-espitia et al. (2010) studied the relationship between inflation and the final price of electricity in colombia and found that a 10% shock in the final price of electricity implies annual inflation of 0.78%. since the el niño phenomenon affects hydrological resource availability, and colombia is a hydro-dominated country in electricity generation, electricity prices increase substantially during an el niño event. the relationship between el niño and electricity prices implies that the pass-through from wholesale costs to retail electricity prices varies substantially between periods. additionally, the regulation on retail electricity prices establishes mechanisms that protect users from abrupt changes in wholesale costs resulting from events like el niño; however, this consumer protection mechanism varies depending on the characteristics of the consumers. large consumers, called unregulated users, can freely negotiate a component of final electricity tariffs with wholesale firms; therefore, the protection mechanism is less decisive for these users. the protection mechanism is relevant for forming the final tariff for the remaining consumers, called regulated users. similarly, for regulated users, lower-income households have stronger protection mechanisms than higher-income households or other consumers, such as industrial or commercial companies. these factors imply that, from a market operation point of view, there is a high degree this journal is licensed under a creative commons attribution 4.0 international license perez, et al.: pass-through in colombia’s unregulated retail electricity market international journal of energy economics and policy | vol 12 • issue 4 • 2022576 of heterogeneity in the pass-through between wholesale costs and retail electricity prices in the colombian market. this work focuses on studying the pass-through for unregulated users, which has not been addressed in the extant literature concerning colombia. this paper uses data from colombia’s retail and wholesale electricity market from 2012 to 2019. this period includes years with and without an el niño event. these data are disaggregated by firms and well-defined market segments at various levels of the retail market. the market operator provides the wholesale market data and does not have a high degree of disaggregation. the data at the firm level are confidential. we use these data to define an empirical model to estimate the pass-through between wholesale costs and retail electricity prices in colombia. likewise, we study how pass-through changes between the different years and the heterogeneity for different aspects of consumers and firms. our results show an incomplete pass-through of wholesale costs to retail prices for the colombian market, which tends to take values near 45% and is heterogeneous. we found evidence that the pass-through tended to increase in el niño years with a shortage of hydrological resources. conversely, we find evidence of heterogeneity in the pass-through according to the firms’ market share and ubication of users. in terms of total consumption, the three largest firms in the retail market tended to charge a lower pass-through than other firms for unregulated users. this is consistent with the hypothesis that explains the pass-through’s incompleteness with the firms’ market power. concerning users, we find evidence that urban users have a greater pass-through than non-urban. this discrepancy can be explained because the urban user segment is more competitive than the non-urban one, given that more firms serve the urban market than the non-urban market. the rest of this manuscript is organized into five sections. section 2 briefly presents the theoretical framework explaining the existence of a pass-through in retail markets. section 3 presents some details of the operation of the colombian electricity market. section 4 presents this paper’s empirical strategy, and sections 5 and 6 present the results and conclusions. 2. theoretical framework of pass-through in retail markets the literature on the pass-through of costs to prices is quite extensive. among the first outstanding works are the seminal theoretical papers from bulow and pfleiderer (1983) and bresnahan and reiss (1985). one of the main predictions established by these models is the pass-through’s dependence on market power. subsequently, weyl and fabinger (2013) generalized both models, obtaining new predictions associated with the pass-through’s dependence, under imperfect competition, on the elasticities of demand, supply, and parameters associated with firms’ conduct and consumer surplus. a significant result of the weyl-fabinger model is that the pass-through of costs to retail prices in oligopolistic markets is incomplete; an increase in costs implies less than proportional growth in prices. this result is explained as pass-through increases with the degree of competition. for markets where firms exercise greater market power, the pass-through tends to be incomplete. conversely, various empirical studies have found evidence that the elasticity of demand is close to zero in electricity markets (burke and abayasekara, 2018; zhu et al., 2018). barrientos et al. (2018) and perez et al. (2016) found similar evidence in colombia; following the weyl-fabinger model, this evidence implies that pass-through in competitive electricity markets should be close to unity. market power has been confirmed as a determinant of incomplete pass-through for different goods markets. according to duso and szacs (2017), the literature on industrial organization offers reasonable explanations for this evidence. retail price rigidities explain an incomplete pass-through since cost movements tend not to transfer completely because retail firms are reluctant to modify their prices (goldberg and hellerstein, 2013). in contrast, long-term contracts (bettendorf and verboven, 2000) or strategic markup adjustments (hellerstein and villas-boas, 2010) allow for absorbing short-term cost movements, allowing a slower price adjustment in the face of cost movements. finally, nonlinear pricing contracts and vertical restraints, such as wholesale price discrimination in the supply chain, explain the incomplete passthrough (bonnet et al., 2013). these studies estimate structural models to evaluate a relationship between these determinants and incomplete pass-through. a good portion of the literature on pass-through has focused on grocery goods, petroleum, coffee, cement, or automotive retail markets; few studies apply to electricity markets. some studies focused on estimating the pass-through between wholesale electricity prices and carbon emissions; zachmann and von hirschhausen (2008) examined eu emissions and electricity future prices in germany, and fabra and reguant (2014) analyzed the spanish market. the evidence from zachmann and von hirschhausen (2008) shows an incomplete and asymmetric passthrough; positive shocks to electricity prices are transmitted more intensely and quickly than adverse shocks. fabra and reguant (2014) show that the pass-through is almost complete and propose that firms have little incentive to make markup adjustments. works that study the pass-through of wholesale costs to retail prices of electricity include mirza and bergland (2012), duso and szacs (2017), and mulder and willems (2019). mirza and bergland (2012) used data from time series to study the norwegian market. they estimated a partial adjustment model and found an incomplete and asymmetric pass-through. duso and szacs (2017) analyzed the pass-through of cost changes to retail prices in the german electricity market using a large and disaggregated panel dataset; they found an incomplete average pass-through rate of around 60%. in addition, they found evidence of heterogeneity of pass-through due to demand and supply factors, such as consumers’ willingness to switch and firms’ market power. they found that pass-through in the competitive market segment has been approaching unity, indicating a rise in competitive pressure. mulder and willems (2019) analyzed the pass-through of wholesale to retail prices in the dutch electricity market with an perez, et al.: pass-through in colombia’s unregulated retail electricity market international journal of energy economics and policy | vol 12 • issue 4 • 2022 577 error-correction model. they found no evidence for asymmetric price pass-through; however, the pass-through rate was slow and incomplete. correa-giraldo et al. (2021) conducted a work specific to colombia. their research examined the pass-through between retail prices and the wholesale cost of supplying electricity. while it has objectives and data similar to ours, correa-giraldo et al. (2021) focused only on the retail market for residential regulated users. in this market, the different parts that set the retail price of electricity are regulated, including generation, which the regulator determines. this may partly explain why the authors found evidence of a more than complete pass-through, which contradicts the theory and evidence for retail markets under imperfect competition. as the method of calculating wholesale costs is regulated, the movements of wholesale costs to retail prices have an almost direct relationship; that is, a complete pass-through is expected. as the authors emphasize, the presence of a more than complete pass-through entails increasing electricity prices for end-users, which firms’ presence of market power can explain. our study follows duso and szacs (2017) and correa-giraldo et al. (2021). we estimate cost pass-through to retail electricity prices using a large and disaggregated panel dataset for colombia’s unregulated retail electricity market. unlike duso and szacs (2017), we study the case of an electricity market dominated by renewable technologies. as with correa-giraldo et al. (2021), we focus on unregulated users, who can freely negotiate the components of the retail price associated with generation and commercialization. this possibility of negotiating two components of the rate makes our study closer to international research, where an incomplete pass-through is expected for retail markets with imperfect competition. 3. colombia’s electricity market the colombian electricity market corresponds to a single area and node so that all electricity transmission networks are connected; it is called the national interconnected system (sin). this system corresponds to several interconnected elements, including generating plants, interconnection networks, regional and interregional transmission networks, distribution networks, and users’ electrical loads (creg, 2009). the sin covers 28 of 32 departments of colombia, and areas not part of the sin are called non-interconnected zones (zni). the sin comprises about 26,700 km of transmission networks. in 2018, the electricity coverage for columbian households was 96.53%, 99.52% for urban households, including sin and zni (upme, 2019). retailers and generators in the wholesale electricity market (wem) negotiate the energy required by end-users. wem agents have long-term energy transactions through bilateral contracts, or short-term transactions in the spot market, under the administration of the system operator, called xm. in addition, in wem, there is a capacity market under auctions whose purpose is to provide reliability to the system in critical periods, obligating firms’ plants to generate electricity in adverse weather conditions, such as the el niño phenomenon. conversely, after law 143 of 1994 (congreso de la república de colombia, 1994), firms that integrated vertically throughout the chain before 1994 could continue unchanged, maintaining separate accounts for each activity. the legislation allows integration between generation and retail activities for new firms only. the market regulator (creg) subsequently set limits on participation in the electricity supply chain to ensure competition, establishing that no firm could have more than 25% of participation in generating or retail activities. it was also determined that no generating firms could have shares, quotas, or parts of social interest representing more than 25% of the social capital of a distributing firm (creg, 1996). however, in 2007, creg established a differential regulation for generators, allowing them to have a market share between 25% and 30% if the market power herfindahl-hirschman index is less than 1800 (creg, 2007a). 3.1. retail market the retail market includes two types of users, regulated and unregulated/liberalized (congreso de la república de colombia, 1994), that differ in monthly electricity consumption. unregulated users consume more than 55 megawatt-hours (mwh) in a month, or their power demand exceeds 2 megawatts (mw); their tariff is established by the creg (regulated tariffs). unregulated users can freely negotiate the costs of generating and marketing electricity activities, and these users are industrial, commercial, and other large consumers associated with the state. this paper focuses on unregulated industrial and commercial users. in 2018, regulated users represented 68.3% of total demand, while unregulated comprised 31.7%. this paper studies the pass-through from wholesale costs to retail prices for unregulated users, describing how the retail prices of both types of users are determined. this allows us to understand the scheme of subsidies and contributions in the retail electricity market, which protects low-income consumers through contributions from large consumers. the end-user retail price for regulated users in the colombian electricity market was established in resolution 119 of 2007 (creg, 2007b). the price per kwh (p) for the end-user was set using six components, described in the following equation: pv,t,f,d = gt–1,f,d+tt+dv,t+ct,f,d+pv,t,f,d+rt,f (1) where v denotes user connection voltage level, t is the month the price per kwh of service is calculated, f denotes retailer and d is a trading market that depends on a department or region. the following is a description of each component of equation 1. 3.1.1. generation (g) the costs transferred to regulated users for generation only consider purchases made by retailers in the spot market and bilateral contracts in the previous month. through resolution 119 of 2007, the generation costs transferred to the end-user comprised a weighted average between the prices in two markets. the firms take a monthly average of the price for the spot market, weighted by the quantities purchased in this market. when the spot price exceeds the shortage price (precio de escacez in spanish) in a given hour, firms charge end-users the perez, et al.: pass-through in colombia’s unregulated retail electricity market international journal of energy economics and policy | vol 12 • issue 4 • 2022578 shortage price, not the spot price at which they bought electricity. this mechanism was designed under creg resolution 071 of 2006 and protects all end-users from spot price fluctuations caused by changes in weather conditions associated with el niño and the scarcity of hydrological resources. regarding the price of the contracts, the firms establish prices with the generators, which are confidential; however, the market operator reports the average price of the firms’ contracts, both for regulated and non-regulated users. the g component is a weighted average between the average price of purchases in the spot market and the price of contracts, where the weight is the share of monthly purchases in each market. 3.1.2. transmission (t) this activity comprises the national transmission system (stn) and the regional transmission system (str). the creg defined the stn as the interconnected electric power transmission system comprising a set of lines, with corresponding connection modules, operating at voltages equal to or greater than 220 kv. the str comprises regional or interregional transmission networks of lines and substations with associated equipment, operating at voltages lower than 220 kv and not belonging to a local distribution system (sdl) (creg, 1998). the stn fees are unique at the national level and independent of the users’ connected voltage level. the str is divided into north and south areas1, and str fees depend on the transmission area. these costs are established monthly and are set by creg (2009). the transmission component is calculated using a relationship between the transmitter’s monthly income and the sin’s electricity demand. 3.1.3. distribution (d) this service comprises the set of lines and substations, with their associated equipment, operating at voltages lower than 220 kv and not belonging to the str because they are dedicated to the service of a municipality, district, or local distribution system (creg, 1998). according to decree 1111 of 2008 (presidencia de la república, 2008a), decree 3451 of 2008 (presidencia de la república, 2008b), and decree 2492 of 2014 (presidencia de la república, 2014), the cost of distribution depends on the areas of distribution (add). the legislation establishes a single fee per voltage level for each add2. 3.1.4. retail (c) resolution creg 180 of 2014 established the remuneration for retailers as a maximum cost, so it is possible to apply a lower value in this component. however, this cost depends largely on the particular resolutions approving the base retail cost and portfolio risks for each incumbent firm, which is one of the primary reasons for the differences in this component (creg, 2014). 1 northern str covers la guajira, atlántico, magdalena, cesar, sucre, and córdoba y bolívar. southern str covers the remaining sin departments. 2 central: santander, norte de santander, caldas, risaralda, quindío, and antioquia. west: valle del cauca, cauca, and nariño. east: boyacá, arauca, huila, cundinamarca, and bogotá d.c. south: caquetá, meta, putumayo, and casanare. north: atlántico, bolívar, cesar, córdoba, la guajira, magdalena, and sucre. tolima represents an add by itself. 3.1.5. losses (p) this makes up the difference between the sum of hourly electricity imports and exports at the commercial frontier points of the national transmission system. this component recognizes to the service provider the cost that is typically considered tolerable in bringing electricity to the end-user. this cost depends on the voltage level, the retailer, and the user type for each month the service is offered. 3.1.6. constraints (r) this component of the tariff compensates for system surcharges generated by electricity dispatches associated with the technical limits of the transmission network. this cost is assigned to each retailer per month, independent of user type and voltage level. users are divided into industrial, commercial, residential, and others according to consumer type. colombia’s residential users are divided into six socioeconomic strata, determining the tariff paid. thus, strata 1, 2, and 3 receive subsidies, while strata 5 and 6 pay contributions. stratum 4 does not receive subsidies or pay contributions. the tariff paid by residential end-users varies according to their socioeconomic status. similarly, unregulated users pay contributions. unlike regulated users, the unregulated users’ component of retail prices for commercialization and generation is agreed upon freely through a negotiation process between firms and end-users. creg regulates the other components of the retail price for both types of users: transmission, distribution, losses, and constraints. this implies that the main difference between the retail prices between the two types of users is how the parties negotiate the wholesale cost of electricity and commercialization. however, it is impossible to observe the tariffs negotiated by the parties involved; therefore, we designed a strategy to approximate the wholesale cost that retail firms pay for electricity. this closely follows how the generation component for regulated users is set, which is a reasonable approximation of how retail firms pay for the electricity they use to satisfy their unregulated users. subsequently, we developed a strategy to estimate the pass-through from the wholesale cost to the retail price of electricity for unregulated users. 4. methodology 4.1. data we employ monthly data from january 2012 to december 2019. this novel dataset is from different public information sources available through colombia’s official authorities. we define the level of disaggregation at which the information is available as a market. a market is defined as those users with an equal characteristic concerning the type of market (regulated or not) to which they belong, the department, the ubication (rural, urban or populated center), voltage level (1-4), and the type of consumer (industrial, commercial, or residential). for each market, we have the amount billed with and without subsidies/contributions in colombian pesos (cop), the level of electricity consumption, and the number of users in the market. we focus on the data that corresponds to unregulated users and define the retail price as the quotient between the amount billed and the amount of electricity perez, et al.: pass-through in colombia’s unregulated retail electricity market international journal of energy economics and policy | vol 12 • issue 4 • 2022 579 consumed, giving us a measure of the average cost of electricity in cop/kwh for end-users in a given market. since unregulated users tend to pay contributions for their electricity consumption, consumers’ retail prices include distortions associated with taxation. therefore, we use the amount billed without contributions to calculate the retail price. additionally, given that the series of retail prices presents outliers in the sample’s lower and upper values, we take the distribution of retail prices for the entire period and eliminate the smallest 1% and largest 1%. the data to elaborate on the wholesale cost of electricity is taken from portal bi of xm (2019). we do not observe the exact cost for each firm supplying the electricity to each user since this has associated confidential aspects, such as contract prices at the firm level. for this reason, we designed a strategy to measure the wholesale cost of supplying electricity with information on purchases in the spot market and public contracts at the firm’s level. the wholesale cost is the weighted average between the monthly weighted average spot price of electricity3 and the previous month’s average contract price of firms for unregulated users4. the weight used for the contracts’ prices and spot prices is their share in total negotiations for the month. this method of calculating the wholesale cost of electricity is similar to the calculation approach for regulated users, except that the price of unregulated contracts is considered while regulated contract prices are not. we focus only on departments with distribution charges assigned to a corresponding add. we do not use the departments that are not part of an add because they are unreliable. these departments are small, representing 0.08% of the total consumption in the complete database. the monthly cpi deflates the retail prices and wholesale costs data with banco de la república (central bank of colombia) data. table 1 shows the average values of some relevant variables of the unregulated market. the table is organized into four parts, corresponding to user classifications according to voltage levels, ubication, type of consumer, and the area of the country in which they are located. we calculate the average retail price and wholesale cost for each month and the total consumption and users for each classification category. the table presents the average values of these calculations for 2012 and 2019. in general, retail prices and wholesale costs are higher in 2019 than in 2012. given that we are deflating the units by the cpi, this indicates an increase in retail prices of electricity for unregulated market users, partly explained by an increase in wholesale costs. the average retail price tends to decrease with the voltage level; conversely, the wholesale cost tends to be similar between voltage levels. this is due to differences in distribution costs between low and high voltages, an aspect that is not part of the wholesale cost calculation. the highest average number of users is at voltage level 2, and the highest average consumption level is at voltage level 3. urban users have the highest average retail 3 the weights are the monthly weight of daily purchases in the spot market. additionally, we set the maximum price to charge end users the scarcity price. 4 data on contract prices at the firm level are confidential; however, the market operator only reports the average contract prices for regulated or unregulated users. price and wholesale costs, the highest average number of users, and the highest consumption levels. industrial users have average retail prices and wholesale costs lower than commercial ones and present higher consumption levels; however, in 2012, commercial users represented the market majority, but in 2019 they numbered fewer than industrial users. regarding the distribution areas, the average retail price is higher in the south and lower in the north. in contrast, wholesale costs are similar between groups. most generating plants are located in the east, center, and north of the country, so the south, being further away, has higher distribution costs. the west had the highest number of average users in 2012, followed by the center in 2019; the highest average consumption levels were in the eastern region. figure 1 shows the retail prices’ mean and percentiles, 5th and 95th, for unregulated users and the average wholesale electricity cost in 2012-2019. it should be noted that the series of average retail prices largely reflect the average wholesale cost movements that we calculate. additionally, substantial increases in wholesale cost tend to increase the dispersion of retail prices, as observed by the size of the area comprised by the 5th and 95th retail price percentiles. furthermore, the retail price dispersion increased slightly in 2016, 2018, and 2012-2014, and it decreased in 2019. in contrast, figure 2 shows the distribution of retail prices in the years 2012 and 2019. significantly, the distribution of prices is more symmetrical for 2019 and has a positive asymmetry in 2012. 4.2. empirical strategy this section develops an empirical model that allows studying the pass-through from wholesale costs to retail prices, following duso and szacs (2017). when there is an increase in wholesale costs, either due to a change in spot prices or contracts prices, firms tend to transmit these changes to end-users. following the theoretical results of weyl and fabinger (2013), the pass-through in oligopolistic markets with imperfect competition tends to be incomplete. the existence of market power tends to make the passthrough more incomplete, while increasing levels of competition tend to make the pass-through more complete. additionally, the pass-through may be heterogeneous depending on the users’ characteristics. this paper explores this possibility in the case of industrial and commercial users. a model of pass-through with the following specification is proposed for the price of retailer i, in department d, ubication l, voltage level k, type of consumer s, at time t: pidlkst = β0 + β1wft + xidlkst’δ + θ + εidlkst, (2) where β1 captures the pass-through of wholesale costs to retail prices. x is a vector of the control variables: consumption and the number of users. θ is a vector of fixed effects by department-time, firm, ubication, voltage level, and type of consumer. ε is allowed to cluster at the market level. including department-time fixed effects allows controlling for other components of the retail price, such as distribution and transmission costs, losses, and constraints. we estimate equation 2 in different specifications to check the robustness of the pass-through coefficient of wholesale cost and perez, et al.: pass-through in colombia’s unregulated retail electricity market international journal of energy economics and policy | vol 12 • issue 4 • 2022580 retail prices. first, we estimate the pass-through by year to assess how it evolves and depends on the presence of el niño. second, we evaluate the heterogeneity of pass-through by consumer type and user ubication. finally, we estimate the model by dividing the passthrough between the three largest firms’ load and the remaining firms. this additional exercise allows testing the differences in pass-through between firms that can exercise potential market power and those that cannot. from a theoretical perspective, the pass-through is expected to be lower for firms with greater market power than those with less. mackay et al. (2014) suggest potential sources of bias in the reduced form estimation of pass-through. the partial information bias arises if the unobserved cost components are not independent of the observed components in the wholesale cost. in our setting, including the department-time fixed effects allows controlling for the components that we do not observe in the cost of supplying electricity. 5. results 5.1. estimations for pass-through this section presents the results estimating the pass-through from wholesale costs to retail electricity prices. we estimate equation 2 using ordinary least squares for different specifications summarized in table 2. all columns include department-time fixed effects. for column 1, we estimate the pass-through without including controls or the set of fixed effects by the firm, ubication, voltage level, and type of consumer. column 2 includes controls, and column 3 introduces the set of fixed effects. this exercise allows us to evaluate the robustness of the pass-through to the different specifications. the results in table 2 show that pass-through is incomplete, close to 45%. this result is robust to including controls and the set of fixed effects. we found a negative relationship between retail prices and consumption regarding the controls used. additionally, the estimated coefficient is close to 0; this may result from the inelastic demand found in the colombian market. conversely, retail prices tend to be higher when the firm serves more users in a particular market segment. table 1: descriptives of users retail price wholesale cost number of users consumption (cop/kwh) (cop/kwh) (thousands) (gwh-month) 2012 2019 2012 2019 2012 2019 2012 2019 voltage level 1 393,91 421,05 139,18 181,15 1,68 0,36 20,64 17,83 2 337,42 365,75 138,33 182,40 5,87 3,45 344,49 431,03 3 282,73 322,54 138,50 181,94 1,09 1,05 404,57 478,61 4 236,85 275,75 137,41 181,64 0,04 0,09 173,92 295,62 ubication urban 329,43 354,04 138,81 182,73 7,48 3,99 618,85 991,85 rural 313,10 356,82 138,13 179,93 1,13 0,95 311,53 228,88 populated center 318,29 354,59 135,71 177,45 0,07 0,01 13,24 2,37 type of consumer commercial 335,35 362,82 138,59 183,05 6,10 1,96 210,35 204,54 industrial 315,99 349,01 138,44 181,35 2,58 2,98 733,27 1018,56 zone add center 334,00 356,67 138,93 182,25 1,24 1,31 251,40 291,03 north 305,01 342,51 138,78 183,68 0,60 1,19 102,52 260,67 west 322,84 348,10 136,76 181,03 4,84 1,00 169,94 203,12 east 317,85 362,28 138,86 181,12 1,64 1,22 352,71 377,60 south 344,43 366,96 139,33 182,22 0,19 0,12 43,37 71,51 tolima 338,63 364,81 139,62 181,73 0,17 0,10 23,67 19,17 figure 1: retail prices and wholesale costs source: author’s elaboration with supersociedades and xm data. figure 2: distribution of retail prices source: author’s elaboration with supersociedades and xm data. perez, et al.: pass-through in colombia’s unregulated retail electricity market international journal of energy economics and policy | vol 12 • issue 4 • 2022 581 the colombian electricity market is characterized by a high share of hydroelectric generation, representing 75% of the annual generation in years with normal hydrological conditions. however, the qualifier “normal” is relevant for this calculation. colombia is subject to two weather phenomena that drastically alter the availability of hydrological resources: el niño and la niña. when el niño occurs, the hydrological resources are scarce, and thermal generation gains strength; when la niña occurs, hydrological resources are abundant. the scarcity price mechanism and firm energy obligations reduce the impact on retail prices resulting from increases in the spot price. our wholesale cost measure takes this characteristic into account; however, during the el niño from september 2015 to may 2016, the market experienced a complex situation when some thermal plants were unable to cover their obligations, and the spot price shot up to historical levels. emergency measures were implemented to avoid energy rationing during these months; these measures could affect the pass-through, an aspect that we evaluated. column 4 of table 2 shows the results of estimating equation 2, assuming that the pass-through can be different from september 2015 to may 2016. the results show significant differences in the pass-through for a normal period and september 2015 to may 2016. the passthrough during the 2015-2016 el niño was, on average, higher than for the normal period; the pass-through tended to be more comprehensive. for normal periods, the estimated pass-through is 31.2%, increasing to 67.8% in the presence of el niño. this increase in pass-through is exclusively due to the notable increase in spot prices of electricity during this period, which notably affected how firms transmit cost movements to end-users. this can be understood from the behavior of retail firms, which, to avoid high losses, largely decided to pass on the cost increase to their users. almost all the firms took this action in the market; figure 1 shows the increasing distribution of retail prices in this period. 5.2. heterogeneity of pass-through and market power the previous section examined the pass-through between wholesale costs and retail prices, finding evidence of an incomplete pass-through and the differences between normal and el niño (2015-2016) periods. this section studies the pass-through heterogeneity between firms with privileged market positions according to the type of consumers or ubication. these supply and demand factors are related to the possibility of exercising market power and the characteristics of users, respectively. table 3 shows the results of assuming that pass-through is different between commercial and industrial users (column 1), urban and non-urban users (column 2), and different for the three firms with the largest participation in total consumption compared to the remaining firms (column 3). it is reasonable to expect that firms transmit costs differently to users according to their type (industrial or commercial, urban or non-urban). table 1 indicates differences in retail prices; although wholesale costs tend to be similar, the differences may be due to a differentiated pass-through or simply variances in consumption levels, like those observed in the table. column 1 shows the results of this exercise for industrial and commercial users, leaving the pass-through of an industrial user as the base category. our results show no significant differences between the pass-through of industrial and commercial users. in other words, this consumer characteristic does not present a heterogeneous pass-through. column 2 shows the results for urban and non-urban users, indicating that firms tend to charge a higher pass-through to urban users than non-urban ones. this can be explained because the urban user segment is more competitive than the non-urban and more firms serve the urban market than the non-urban market. on average, during 2012, 20 firms were serving non-urban users compared to 28 in the urban market; for 2019, the numbers were 17 and 27, respectively. the results so far indicate that the pass-through tends to be incomplete, a finding reflected in other studies applied to oligopolistic markets with imperfect competition. this result can be largely explained by the firms’ potential exercise of market power. thus, we conduct an additional exercise evaluating whether the pass-through differs between large firms that concentrate a significant part of the market and the rest. in 2019, the three largest firms represented 64.3% of total consumption and 48.4% of total users. it is reasonable to suggest that these firms may charge a table 2: pass-through of wholesale costs to retail prices (1) (2) (3) (4) retail price retail price retail price retail price wholesale cost 0.496*** 0.456*** 0.437*** 0.312*** (0.0449) (0.0430) (0.0350) (0.0332) wc x el niño 0.364*** (0.0692) consumption 0.00348*** 0.000345*** 0.000343*** (0.000408) (0.000112) (0.000113) users 63.08* 9.247*** 9.474*** (35.78) (2.523) (2.549) constant 262.3*** 274.0*** 272.1*** 286.3*** (7.506) (7.183) (5.561) (5.157) fe depto-time yes yes yes yes other fe no no yes yes observations 63,024 63,024 63,024 63,024 r-squared 0.158 0.222 0.690 0.692 standard errors are corrected by market level. a market is defined as an observation unit that is not repeated in the same month: it is an observation unit in which one firm establishes a price for a type of user, in a department, with a ubication, a voltage level, and a type of consumer. other fixed effects correspond to firm, type of user, ubication, voltage level, and type of consumer. ***p<0.01, **p<0.05, *p<0.1 perez, et al.: pass-through in colombia’s unregulated retail electricity market international journal of energy economics and policy | vol 12 • issue 4 • 2022582 different pass-through to their users, anticipated to be lower than others. column 3 of table 3 presents the results of estimating the model with a differentiated pass-through for the three largest firms and the remaining firms. the results indicate that the largest firms in the market tend to carry a lower pass-through than other firms, which is consistent with the hypothesis relating the incompleteness of the pass-through with market power. 6. conclusions this paper studies the pass-through between wholesale electricity costs and retail prices for the colombian unregulated retail market, which is hydro-dominated in electricity generation. price formation tends to be substantially affected by weather conditions, such as the el niño phenomenon, which causes hydrological resource scarcity. international literature has found evidence of an incomplete pass-through for retail markets with imperfect competition. additionally, the extant literature has found evidence of heterogeneity in the pass-through according to the characteristics of consumers and market segments. we study these aspects for the colombian market. the research applied to the markets of emerging countries is scarce, and our work aims to complement the existing literature by studying the market of unregulated users. the case of regulated users has been widely studied by correa-giraldo et al. (2021). we use retail price data set by firms for fairly disaggregated market segments of unregulated users. these include prices by department, type of consumer (industrial or commercial), ubication (urban or rural), and voltage level. regarding the wholesale costs of supplying electricity, we use measurements of the costs of buying electricity in the spot market or contracts according to unregulated users. subsequently, we establish an empirical strategy to estimate the pass-through of wholesale costs to retail prices. we find evidence of an incomplete pass-through of wholesale costs to retail prices in the colombian market, which tends to take values close to 45%; however, the pass-through presents a high degree of heterogeneity depending on the presence of el niño and the characteristics of consumers and firms. from september 2015 to may 2016, the country experienced a difficult situation when the strongest el niño occurred, and several critical thermal plants shut down, increasing spot prices to historic levels. our results show that the firms loaded a higher pass-through during this period; the pass-through tended to be more comprehensive. concerning users, we find evidence that urban users have a greater pass-through than non-urban. this result can be explained by more firms competing for the urban user market than the non-urban market. finally, in terms of total consumption, the three largest firms in the retail market tend to charge a lower pass-through than the remaining firms for unregulated users. this is consistent with the hypothesis that explains the pass-through’s incompleteness with the firms’ market power. future research can design a structural model to evaluate the economic benefits of implementing demand response mechanisms against the current regulatory scheme. following the structure proposed by weyl and fabinger (2013) and the interpretations made by duso and szacs (2017), the elasticity of demand in the colombian market can explain the incomplete pass-through and the relevant heterogeneity. policies designed to change the elasticity of demand, such as the implementation of distributed energy resources, advanced metering infrastructure, or facilitating the change of retail providers to end-users, have a relevant effect on the pass-through (hortacsu et al., 2017; duso and szacs, 2017; garcia et al., 2019). the weyl-fabinger model indicates that increasing the elasticity of demand tends to decrease the pass-through. since users are more likely to respond to price movements, firms tend to modify their prices less to avoid significant demand movements; thus, the pass-through between retail prices and wholesale costs tends to be lower. therefore, more active participation from end-users can provide more protection from strong movements in wholesale costs, replacing the existing regulation in the sector. this can have implications on the passthrough between retail prices and wholesale costs. the structural model indicates which aspects are the most relevant to explaining the pass-through changes: elasticity of demand or supply and the behavior of the firms associated with the exercise of market power. 7. acknowledgements “we appreciate the research support provided by “energetica 2030” in the research project: regulation policy and markets with code 58864 of the initiative “scientific colombia,” financed by the world bank through the call “778-2017 scientific ecosystems”, administered by the ministry of science, technology, and table 3: pass-through: type of consumers and market power (1) (2) (3) retail price retail price retail price wholesale cost 0.279*** 0.214*** 0.305*** (0.0430) (0.0551) (0.0344) wc x el niño 0.359*** 0.397*** 0.396*** (0.0680) (0.0686) (0.0718) wc x commercial 0.0573 (0.0461) wc x el niño x comm. 0.0263 (0.0180) wc x urban 0.130** (0.0523) wc x el niño x urb. 0.0449** (0.0223) wc x 3 largest firms 0.0122 (0.0714) wc x el niño x 3lf 0.0999*** (0.0165) consumption 0.000342*** 0.000343*** 0.000342*** (0.000112) (0.000112) (0.000113) users 9.243*** 9.573*** 9.539*** (2.525) (2.553) (2.564) constant 286.0*** 286.8*** 287.3*** (5.289) (5.171) (5.174) observations 63,024 63,024 63,024 r-squared 0.692 0.692 0.693 standard errors are corrected by market level. a market is defined as an observation unit that is not repeated in the same month: it is an observation unit in which one firm establishes a price for a type of user, in a department, with a ubication, a voltage level, and a type of consumer. other fixed effects correspond to firm, type of user, ubication, voltage level, and type of consumer. ***p<0.01, **p<0.05, *p<0.1 perez, et al.: pass-through in colombia’s unregulated retail electricity market international journal of energy economics and policy | vol 12 • issue 4 • 2022 583 innovation (minciencias). we appreciate the comments made by manuel correa. references barrientos, j., velilla, e., orozco, d.t., villada, f., lopez-lezama, j.m. (2018), on the estimation of the price elasticity of electricity demand in the manufacturing industry of colombia. lecturas de economía, 88, 155-182. bejarano-salcedo, v., caicedo-garcia, e., lizarazo-bonilla, n.f., julioroman, j.m., cardenas-cardenas, j.a. (2020), hechos estilizados de la relación entre el niño, la niña y la inflación en colombia. borradores de economía, no. 1105. bettendorf, l., verboven, f. (2000), incomplete transmission of coffee bean prices: evidence from the netherlands. european review of agricultural economics, 27(1), 1-16. bonnet, c., dubois, p., villas boas, s.b., klapper, d. (2013), empirical evidence on the role of nonlinear wholesale pricing and vertical restraints on cost pass-through. review of economics and statistics, 95(2), 500-515. bresnahan, t.f., reiss, p.c. (1985), dealer and manufacturer margins. the rand journal of economics, 1985, 253-268. bulow, j.i., pfleiderer, p. (1983), a note on the effect of cost changes on prices. journal of political economy, 91(1), 182-185. burke, p.j., abayasekara, a. (2018), the price elasticity of electricity demand in the united states: a three-dimensional analysis. the energy journal, 39(2), 1-10. congreso de la república de colombia. (1994), ley 143 de 1994 ley eléctrica. congreso de la república de colombia. correa-giraldo, m., garcia-rendon, j.j., perez, a. (2021), strategic behaviors and transfer of wholesale costs to retail prices in the electricity market: evidence from colombia. energy economics, 99, 105276. creg. (1996), resolución 020. por la cual se dictan normas con el fin de promover la libre com petencia en las compras de energía eléctrica en el mercado mayorista. comisión de regulación de energía y gas. creg. (1998), resolución 051. por la cual se aprueban los principios generales y los procedimientos para definir el plan de expansión de referencia del sistema de transmisión nacional y se establece la metodología para determinar el ingreso regulado. comisión de regulación de energía y gas. creg. (2007a), resolución 060. por la cual se dictan normas sobre la participación en la actividad de generación de energía eléctrica. comisión de regulación de energía y gas. creg. (2007b), resolución 119. por la cual se aprueba la fórmula tarifaria general que permite a los comercializadores minoristas de electricidad establecer los costos de prestación del servicio a usuarios regulados en el sistema interconectado nacional. comisión de regulación de energía y gas. creg. (2009), resolución 011. por la cual se establecen la metodología y fórmulas tarifarias para la remuneración de la actividad de transmisión de energía eléctrica en el sistema de transmisión nacional. comisión de regulación de energía y gas. creg. (2014), resolución 180. por la cual se establecen los criterios generales para determinar la remuneración de la actividad de comercialización de energía eléctrica a usuarios regulados en el sistema interconectado nacional. comisión de regulación de energía y gas. duso, t., szücs, f. (2017), market power and heterogeneous passthrough in german electricity retail. european economic review, 98, 354-372. fabra, n., reguant, m. (2014), pass-through of emissions costs in electricity markets. american economic review, 104(9), 2872-2899. garcia, j.j., gutierrez, a., tobon, l.v., ceballos, h.v. (2019), redes inteligentes y mecanismo de respuesta de la demanda. revista de economía del caribe, 23, 33. goldberg, p., hellerstein, r. (2013), a structural approach to identifying the sources of local currency price stability. review of economic studies, 80(1), 175-210. hellerstein, r., villas-boas, s.b. (2010), outsourcing and pass-through. journal of international economics, 81(2), 170-183. hortacsu, a., madanizadeh, s.a., puller, s.l. (2017), power to choose? an analysis of consumer inertia in the residential electricity market. american economic journal: economic policy, 9(4), 192-226. lozano-espitia, l.i., rincon-castro, h., lozano-espitia, i. (2010), formación de las tarifas eléctricas e inflación en colombia. borradores de economía, no. 634. mackay, a., miller, n.h., remer, m., sheu, g. (2014), bias in reducedform estimates of pass-through. economics letters, 123(2), 200-202. mirza, f.m., bergland, o. (2012), pass-through of wholesale price to the end user retail price in the norwegian electricity market. energy economics, 34(6), 2003-2012. mulder, m., willems, b. (2019), the dutch retail electricity market. energy policy, 127, 228-239. perez, j., velasquez, j.d., franco, c.j. (2016), calculation of hourly price-demand elasticity in the colombian electricity market. ieee latin america transactions, 14(7), 3242-3246. presidencia de la república. (2008a), decreto 1111. por el cual se modifica el decreto 388 de 2007. presidencia de la república. presidencia de la república. (2008b), decreto 3451. por el cual se modifica el decreto 388 de 2007. presidencia de la república. presidencia de la república. (2014), decreto 2492. por el cual se adoptan disposiciones en materia de implementación de mecanismos de respuesta de la demanda. presidencia de la república. upme. (2019), sistema de información eléctrico colombiano siel. unidad de planeación minero-energética. weyl, e.g. and fabinger, m. (2013), pass-through as an economic tool: principles of incidence under imperfect competition. journal of political economy, 121(3), 528-583. xm. (2019), portal bi: información inteligente. available from: http:// www.portalbissrs.xm.com.co/paginas/home.aspx zachmann, g., von hirschhausen, c. (2008), first evidence of asymmetric cost pass-through of eu emissions allowances: examining wholesale electricity prices in germany. economics letters, 99(3), 465-469. zhu, x., li, l., zhou, k., zhang, x., yang, s. (2018), a meta-analysis on the price elasticity and income elasticity of residential electricity demand. journal of cleaner production, 201, 169-177. . international journal of energy economics and policy | vol 6 • issue 2 • 2016290 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2016, 6(2), 290-304. an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on data envelopment analysis method mohd alsaleh1*, a.s. abdul-rahim2, h.o. mohd-shahwahid3, lee chin4, fakarudin kamarudin5 1faculty of economics and management, universiti putra malaysia, 43400 upm serdang, selangor, malaysia, 2faculty of economics and management, universiti putra malaysia, 43400 upm serdang, selangor, malaysia, 3faculty of economics and management, universiti putra malaysia, 43400 upm serdang, selangor, malaysia, 4faculty of economics and management, universiti putra malaysia, 43400 upm serdang, selangor, malaysia, 5faculty of economics and management, universiti putra malaysia, 43400 upm serdang, selangor, malaysia. *email: moe_saleh222@hotmail.com abstract over the last few years concerns have enhanced about the bioenergy industry as main source for renewable and sustainable energy in many countries. these concerns have been major magnitude for countries with joint green energy legislation such as european union (eu) member states. a significant aspect to be considered when selecting a provided bioenergy is the efficiency involved in its production. in this context, the current study analyzes the technical efficiency (te) components in bioenergy industry in eu28 region between 1990 and 2013. to this end, parametric and non-parametric frontier models are applied, where both are particularly appropriate in this special context due to their treatment of undesirable outputs. results are presenting higher means for te and pure te in developing countries in compare with developed countries. in the other hand, scale efficiency mean presenting high value in developed countries in compare with developing ones. keywords: bioenergy industry, technical efficiency, eu28 region jel classifications: q4, d61 1. introduction the world economy is on the edge of one of the biggest model transfer since the beginning of the industrial revolution worldwide. wide convert from utilizing fossil fuel energy to renewable and sustainable energy, due to many serious reasons such as: producing and consuming fossil fuels energy is enhancing relentlessly and along with the emission of climate killer co2. moreover, traditional fossil fuel energy supplies can barely meet the world requirement for energy. furthermore, as per the international energy agency report, by 2012 oil production will reach the peak and will not be able to meet the world demand (geheeb, 2007). in addition, the price of energy imports has been increased significantly affecting the international market economies. nevertheless, climate change caused by co2 emission is threating the renewable energy sources through destroying the natural resource and environment. the world society requires serious changes in energy systems, away from fossil fuel energy sources to a renewable and sustainable energy sources (geheeb, 2007). bioenergy is one of the most sources of renewable and sustainable energy which can provide an essential contribution to supply future green energy in a sustainable approach. bioenergy is the biggest world contributor of renewable and sustainable energy, and has an important role in different fields such as heating and cooling, electricity and power, and fuel for transportation. biomass is the main source to produce bioenergy, presented by the organic raw materials and biological waste from different source (such as: forestry, agriculture, food, fishery, municipality, etc.). in 2010, national renewable energy action plan (nreap) schedule gives detailed road maps of how the european union (eu) countries can reach the 2020 targets, which can be summarized as follow: 20% mitigation of greenhouse gas emission in comparing alsaleh, et al.: an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on dea method international journal of energy economics and policy | vol 6 • issue 2 • 2016 291 with 1990 emission level, 20% increment of the portion of energy production from renewable energy sources, 20% reduction of energy consumption from conventional sources through increasing the efficiency. scowcroft and nies (2011) have indicated that bioenergy is a significant player to reach the 2020 (nreap) targets. also, reddy and assenza (2007) have pointed out that increasing energy efficiency can help to meet the gap between increased demand and shortage in supply without any change in the quality of produced energy. based on jossart and calderon (2013), there is relation between the level of efficiency and the level of the country economic development, where developed eu countries have high level of efficiency presented in high production and export, less consumption and import, while developing countries have low level of efficiency presented in high consumption and import, less production and export (burck et al., 2012). the european union (eu28) is an economic and political union of 28 countries or members. the eu countries manage a single and an internal market which authorize free transfer of goods, capital, services and citizens between eu member states. the latest statistics related to the bioenergy balance in europe in 2011 has showed that eu countries with high rate of efficiency in bioenergy production, such as: bulgaria, czech republic, estonia have registered high rate of efficiency in bioenergy production (electricity and heat sections in specific) with the average of (83.33%, 50.07%, 79.19%) respectively, have less import, more export, less final energy consumption and more primary energy production. on the other hand, countries with low rate of efficiency in bioenergy production for the same above fields, such as: greece, spain, croatia have registered low rate of bioenergy efficiency in electricity and heat sections with the rate of (31.58%, 33.74%, 23.08%) respectively, have presented more import, less export, more final energy consumption and less primary energy production (jossart and calderon, 2013). the need for efficiency in bioenergy industry has become a necessary requirement in the eu28 energy economic, due to the shortage in bioenergy production. for example the biofuel production in 2011 was (250.45 thousand barrels per day) which needs to be improved efficiently to meet the biofuel consumption (340.43 thousand barrels per day) in 2011. moreover, the co2 emission increment from fossil fuel use has not decreased significantly since 1990 to meet the set (nreaps) targets in 2020 (scowcroft and nies, 2011). the inefficacy of bioenergy industry has affected eu28 countries economy negatively through; the over consumption of bioenergy and inability of bioenergy production to meet the required consumption. moreover, failed to reach the (nreap) 2020 targets as per the estimation of scowcroft and nies (2011) due to biomass supply gap, which is need to be imported from different regions for bioenergy production purpose. furthermore, the mitigation of the co2 emission in eu28 region is unbalanced due to the over consumption and inefficient production of bioenergy (scowcroft and nies, 2011) the main objective of this paper is to investigate the technical efficiency (te) and analyze pertaining to the decomposition of bioenergy industry in the eu28 countries. while the output of this paper will identify which eu28 countries have high efficiency rate or low efficiency rate (inefficiency). moreover, we will be able to recognize the factors behind the efficiency in bioenergy industry in some countries which will help to derive the required policies to improve the bioenergy industry process and obtain better efficiency in other inefficient countries. furthermore, policy makers will be able to identify the needed policies and procedures in the bioenergy industry to develop and improve the bioenergy industry in eu28 region. 2. literature review 2.1. empirical review for efficiency of bioenergy industry in this part an empirical review for efficiency of bioenergy industry will be discussed in different regions/countries and sectors (electricity and power, heat and cooling, and transport) using different methods to measure the efficiency. in china, biomass is playing a main source for bioenergy production which presents the majority of renewable energy sources (chang et al., 2013). however, bioenergy production could not meet the local demand in china for bioenergy due to the shortage of biomass. therefore, china has transformed to become a net energy imported country (chang et al., 2013). in south africa, winkler (2003) has granted with the other group of researchers regarding the importance of developing the renewable energy for electricity field to implement environmental, health and economical goals without losing sight of social development targets. winkler (2003) has found that proper investment in renewable energy (bioenergy) and energy efficiency is significant to minimize the negative economic, social and environment effects from energy production. scarlat et al. (2013) admits that bioenergy industry is a main player in the process to convert for renewable energy in electricity and power, heating and cooling, and transportations sectors in italy and achieve the set targets to transform to green energy. in addition, biomass is anticipated to provide the largest source of renewable energy in italy. kythreotou et al. (2012) have analyzed the biomass potential for bioenergy production in cyprus. however, the results indicated to that anaerobic digestion pertaining to bioenergy would give decentralization of bioenergy production in locations that are outlaying. moreover, give the farms the opportunity to be energy self-governing and less impacted by the fuel prices variation. balat and balat (2009) have pointed that bioenergy (hydrogen energy) generated from biomass, organic and waste resources can provide an economical and environmental friendly energy output free of pollution, free of carbon, and can be utilized in household service, industry, and transports sectors. shafie et al. (2012) has referred to that bioenergy is the highest potential energy source to meet the increasing demand for energy and provide a sustainable renewable energy security with proper environment protection in malaysia. berndes et al. (2009) has found that in 2nd generation of biofuel production output, there is an inverse relationship between the age of capital plant and the potential of bioenergy production. evans et al. (2010) have found in their paper that the sustainable bioenergy production in australia can be implemented through improving hardy crops on marginal or unutilized land. in malaysia, tye et al. (2011) has resulted that alsaleh, et al.: an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on dea method international journal of energy economics and policy | vol 6 • issue 2 • 2016292 the second generation of bioethanol is considered significant, due to the potential as energy source for transportation sector and its long term strategies and development. hu and wang (2005) have analyzed in details the bioenergy efficiency for 29 regions in china for the period between 1995 and 2002. empirically, there is an inverse relationship between the efficiency of energy production and used input (labor, capital stock, etc.) in the process of energy production. 2.2. theoretical review for overall te approach the study by lee (2009) is among different studies which measured the operational efficiency of (173) mediumsized audit firms in 2005 by employing frontier efficiency approach. lee (2009) has employed different parametric and non-parametric tests to a panel analysis for the studied sample. lee (2009) has indicated that there are (24) audit firms with the overall te value of (1 = fully efficient). in terms of overall te, pure te (pte) and scale efficiency (se), the result shows that the average se of all samples is higher than the average pte. by using the dea statistical mathematic, yudistira (2004) examines the efficiency the performance of (18) islamic banks during the period between 1997 and 2000. yudistira (2004) has found that the islamic banks suffered slight of inefficiencies during the world crisis for the period between 1998 and 1999 due to pure technical inefficiency rather than scale inefficiency. in another study, sufian (2007) supposed that the te of malaysian islamic banks reduced during the period between 2002 and 2004. sufian (2007) has found that the local islamic banks were more technical efficient compared to foreign islamic bank in malaysia. sufian (2007) has pointed that the source of technical inefficiency of malaysian islamic banks is se but not pte. another study, sufian and haron (2008) has examined the efficiency of islamic banks in the mena (middle east and north african) and asian countries. by applying the dea statistical mathematic sufian and haron (2008) evaluated the te, pte and se. sufian and haron (2008) has found that pure technical inefficiency override scale inefficiency since islamic banks were found to have been operating at a relatively optimal se of operations but they were managerially inefficient to utilize their resources to the fullest. sufian and habibullah (2011) have examined the effect of economic freedom on bank efficiency in a developing economy. sufian and habibullah (2011) employed data envelopment analysis (dea) statistical method to measure the te of the chinese banking industry for the period between 2000 and 2008. sufian and habibullah (2011) have founds that the inefficiency of the chinese banking sector was major in se than pte. 3. research method the present study collects data on the bioenergy industry from european union (eu28) countries which are listed in table 1, for the period between 1990 and 2013. the main source of biomass and bioenergy data is the eurostat database produced by the european union commission which provides all related data for biomass and bioenergy industry. we obtained data related to the used input and output variables from eurostat databases. the final sample comprised (23) member/country operating in eu28 region, can be divided into (15) developed countries and (13) developing countries in eu28 region (table 1). all input and output have been converted to thousand toe (tonnes of oil equivalent) for the purpose of comparability. 3.1. the dea first stage the level of te is identified by using the dea statistical approach. the dea statistical method builds a frontier of the observation of input and output ratio through linear programming techniques. the linear programming substitution is acceptable between observed input groups on an isoquant (the same volume of output is generated while amending the volume of two or more inputs) that was assumed by the dea statistical method. charnes et al. (1978) were the first to version for the method of dea to scale the efficiency of each decision making unit (dmu), obtained as a maximum of a ratio of weighted outputs to weighted inputs. the more the output generated from provided inputs, the more efficient is the generation of the (dmu). this study applies efficiency assessment under the variable returns to measure (vrs) hypothesis. the vrs hypothesis was given by banker et al. (1984). the banker, charnes, and cooper (bcc) structured model (vrs) expanded the charnes, cooper, and rhodes model which was first suggested by charnes et al. (1978) by relieve the constant return to measure hypothesis. the found bcc model was applied to evaluate the efficiency of dmus specified by vrs hypothesis. the vrs hypothesis gives the degree of pte. pte measure the efficiency of dmus without getting infectious by scale effects. moreover, outcomes concluded from the vrs hypothesis gives extra trustworthy information on dmus’ efficiency compared to the constant return to scale (crs) hypothesis (coelli et al., 1998). the te model is given in equation (1). as resulted, the technical, pure technical and se scores are limited between the values (0) and (1) range. to choose optimum weights we selected the below mathematical programming problem: u y min i i i i u y v x u y v x , ' ' , ' ' ( ) , j , ,..., n, u, v≤ = ≥1 1 2 0 (1) table 1: list of eu28 region member countries european union (eu28) region developed countries (15) developing countries (13) member countries year of entry member countries year of entry austria 1995 bulgaria 2007 belgium 1958 croatia 2013 denmark 1973 cyprus 2004 finland 1995 czech republic 2004 france 1958 estonia 2004 germany 1958 hungary 2004 greece 1981 latvia 2004 ireland 1973 lithuania 2004 italy 1958 malta 2004 luxembourg 1958 poland 2004 netherlands 1958 romania 2007 portugal 1986 slovakia 2004 spain 1986 slovenia 2004 sweden 1995 united kingdom 1973 source: official website of european union (www.europa.eu) alsaleh, et al.: an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on dea method international journal of energy economics and policy | vol 6 • issue 2 • 2016 293 the above equation1 has an issue to infinite solution and therefore we impose the constraint (v’ xi = 1), which drives to: u i i u y x u y k j n , min ' ' , ' ' ( ) , , , ,..., , ,ϕ ϕ ϕ ϕ µ1 11 0 1 2 0= − ≤ = ≥ (2) in equation 2 we have adjusted the notations to reverberate the conversion from (u) and (v) to the (µ) and (φ) respectively, employing the duality in linear programming, an equivalent envelopment method of this issue can be derived as follow: θ λθ λ θ λ λ, min , , ,y y x x i i + ≥ − ≥ ≥ 0 0 0 (3) where (θ) is a scalar illustrating the value of the efficiency score for the (ith) country will score between the values (0) and (1) (λ) is the vector of (n*1) constants. the linear programming has to be computed (n) times, once for each country in the eu region. due to compute the te under the hypothesis of vrs, the convexity constraint identify the how nearly the production function envelop the observed input and output integrations and is not required in the crs situation (sufian, 2009). by computing the three efficiency measures (e.g., technical, pure technical, scale), we will be capable to observe a more robust result for the bioenergy industry developed and developing countries in eu28 region over the period under study between 1990 and 2013. however, the present study point’s greater emphasis on the te measure compared to the other decomposition efficiency measures (e.g., pure technical and scale). 3.2. the input and output variables in dea based on cooper et al. (2002), there is a standard requirement to be met in order to choose the number of inputs and outputs. the basic rule formula which can give instruction can be presented as: n ≥ max {m * s, 3 (m + s)} (4) where, (n) refer to the number of dmus; (m) point to the number of inputs; and (s) indicate to the number of outputs. given the underdevelopment of bioenergy industry in eu28, the importance of efficiency of bioenergy production is critical as a significant source of renewable and sustainable energy. therefore, it is reasonable to suppose that the efficiency of bioenergy industry in terms of their intermediation function is crucial as an effective channel to provide energy for different sectors (power, electricity, heat, cold, and fuel) from renewable and sustainable sources. in this vein chang et al. (2013) has pointed out that bioenergy industry play an important economic role in providing renewable and sustainable source of energy by converting biomass into energy and contribute to develop the economic sector. winkler (2003) has granted that the efficiency of renewable energy industry has also been shown to perform a critical role electricity field to implement environmental, health and economical goals without losing sight of social development targets. as confirmed by different scholars to the significant role of efficiency in bioenergy industry in the economic (kythreotou et al., 2012; scarlat et al., 2013; balat and balat, 2009; shafie et al., 2012; evans et al., 2010). following sufian (2008), sufian and habibullah (2013), sufian and kamurdin (2015), and coelli (1996) among others, the present study uses the te approach which views te as the solution to develop the bioenergy industry in eu28 countries. accordingly, three inputs and one output variables were chosen. the three input vector variables consist of x1: raw material, x2: labor and x3 physical capital, the output vector is y1: production. 4. empirical results and discussion following many studies related to the same statistical approach such as sufian and kamurdin (2015), gilani (2015), omar and jones (2015), md and kashfia (2015), and sufian (2008). table 2 shows the means of te (0.77), and the decomposition of te into se (0.91) exceeded pte (0.85) of eu28 zone of bioenergy industry for the period between 2000 and 2013, which can reflect the eu28 zone inefficiency for the same study period resulted as technical inefficiency (0.23), and the decomposition into pure technical inefficiency (0.15) overrides scale inefficiency (0.09). table 2 shows the mean technical, pure technical and scale efficiencies of developing and developed countries in bioenergy for the period between 2000 and 2013 (for further details refer appendix a and appendix b). the empirical findings seem to indicate that the developing countries have exhibited higher means in te and pte in compare with developed countries as follow and respectively: te (0.80 vs. 0.75), pte (0.89 vs. 0.80), but not se where mean of developed countries is higher than developing countries as showed (0.90 vs. 0.91). despite the fact that the empirical findings clearly highlight that both the developing and developed countries in bioenergy industry have not been fully efficient in producing outputs by using the available input resulted technical inefficiency, pure technical inefficiency, and scale inefficiency. in essence, the empirical findings seem to indicate that developing and developed countries have not fully utilized the inputs efficiently to produce the same outputs (technical inefficiency). moreover, empirical results trend to indicate that developing and developed countries have not took the proper decision pertaining to both raw material and human resources properly (pure technical inefficiency). also, empirical findings seem to indicate that developing and developed countries have not fully utilized the capital inputs efficiently to generate the same outputs (scale inefficiency). the empirical findings given in table 2 clearly indicate that in developing and developed countries the level of technical inefficiencies are (0.20 vs. 0.25), pure technical inefficiencies are (0.11 vs. 0.20), scale inefficiencies are (0.10 vs. 0.09) respectively. as for te, the average developing and developed countries could only generate (0.80 vs. 0.75) of output, less than what it was initially expected to generate. hence, te is lost by (0.20 vs. 0.25) indicating that the average developing and developed countries loses an opportunity to receive (0.20 vs. 0.25) more output given the same amount of resources, or it could have produced (0.20 vs. 0.25) of its outputs given the same level of inputs. this result shows that the developing countries are generating more output and experiences less loses of input compared to the developed countries for the period between 2000 and 2013, as the level of the te in the developing countries is higher than that of developed countries. alsaleh, et al.: an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on dea method international journal of energy economics and policy | vol 6 • issue 2 • 2016294 while, developed countries shows that they are utilizing a large volume of resources to produce outputs that lead to the higher wastage inputs for the study period between 2000 and 2013. for the se, the results seem to suggest that the average developing and developed countries could only utilize (0.90 vs. 0.91) of what was available. therefore, both developing and developed countries lost the opportunity to generate (0.10 vs. 0.09) more optimal outputs from the minimum level of inputs that may lead to higher se. the results state that the level of se is higher in the developed countries compared to that in the developing countries. this implies that developed countries are capable of producing more outputs by utilizing less input to generate higher se. meanwhile, developing countries are utilizing more inputs and produce fewer outputs that may lead to the lower se (table 2). for the period between 1990 and 1999, the results present the means of te (0.71), and the decomposition into se (0.91) exceeded pte (0.78) of eu28 zone of bioenergy industry for the period between 1990 and 1999, which can reflect the eu28 zone inefficiency for the same study period resulted as technical inefficiency (0.29), and the decomposition into pure technical inefficiency (0.22) overrides scale inefficiency (0.09). in the period between 1990 and 1999, the empirical findings seem to indicate that the developing countries have exhibited higher means in te and pte in compare with developed countries as follow and respectively: te (0.75 vs. 0.67), pte (0.84 vs. 0.72), but not se where mean of developed countries is equal to the one in developing countries as showed (0.91 vs. 0.91) (appendix e). despite the fact that the empirical findings clearly highlight that both the developing and developed countries in bioenergy industry have not been fully efficient in producing outputs by using the available input resulted technical inefficiency, pure technical inefficiency, and scale inefficiency. the empirical findings are clearly indicates that in developing and developed countries the level of technical inefficiency is (0.25 vs. 0.33), pure technical inefficiency is (0.16 vs. 0.28), scale inefficiency is (0.09 vs. 0.09) respectively for the period between 1990 and 1999 (appendix c and d). 5. rubostness tests after examining the results derived from the dea method, the issue of interest now is whether the difference in the te, pte, and se of developing and developed countries is statistically significant. mann–whitney wilcoxon test is a relevant test for two independent samples coming from populations having the same distribution. the most relevant reason is that the data violate the stringent assumptions of the independent group’s t-test. in what follows, we perform the non-parametric mann–whitney wilcoxon test along with a series of other parametric (t-test) and non-parametric kruskall–wallis tests to obtain more robust results. table 3 shows detailed robustness tests for developing and developed countries in bioenergy industry between the period 2000 and 2013. based on table 4, the results from the parametric t-test for the period between 2000 and 2013 suggest that the developing countries have exhibited a higher mean te level compared to the developed countries (0.804 > 0.745). which statically insignificant because p value is greater than the significant level at 10% table 2: average of technical efficiency of bioenergy industry in eu28 over 2000‑2013 year efficiency average of developing countries by year average of developed countries by year average of eu28 by year 2000 te 0.80 0.74 0.77 pte 0.90 0.82 0.86 se 0.90 0.87 0.89 2001 te 0.83 0.75 0.79 pte 0.91 0.79 0.85 se 0.92 0.92 0.92 2002 te 0.86 0.76 0.81 pte 0.93 0.80 0.86 se 0.93 0.92 0.93 2003 te 0.82 0.72 0.77 pte 0.92 0.78 0.85 se 0.90 0.90 0.90 2004 te 0.82 0.73 0.77 pte 0.90 0.81 0.86 se 0.91 0.88 0.89 2005 te 0.81 0.72 0.77 pte 0.90 0.83 0.87 se 0.91 0.85 0.88 2006 te 0.82 0.75 0.79 pte 0.90 0.79 0.84 se 0.92 0.93 0.93 2007 te 0.80 0.74 0.77 pte 0.89 0.81 0.85 se 0.90 0.89 0.90 2008 te 0.79 0.75 0.77 pte 0.88 0.81 0.84 se 0.90 0.92 0.91 2009 te 0.77 0.75 0.76 pte 0.88 0.80 0.84 se 0.88 0.93 0.91 2010 te 0.77 0.75 0.76 pte 0.88 0.80 0.84 se 0.88 0.93 0.91 2011 te 0.74 0.73 0.74 pte 0.85 0.78 0.81 se 0.88 0.94 0.91 2012 te 0.78 0.75 0.76 pte 0.87 0.81 0.84 se 0.91 0.93 0.92 2013 te 0.81 0.81 0.81 pte 0.90 0.83 0.86 se 0.91 0.97 0.94 average by group type te 0.80 0.75 0.77 pte 0.89 0.80 0.85 se 0.90 0.91 0.91 te: technical efficiency, pte: pure technical efficiency, se: scale efficiency regarding pte, the results indicate that, on average, developing and developed countries have utilized only (0.89 vs. 0.80) of the resources or inputs to produce the same level of outputs. in other words, on average, both of developing and developed countries have wasted (0.11 vs. 0.20) of its inputs, or it could have saved (0.11 vs. 0.20) of its inputs to produce the same level of outputs. noticeably, the level of the pte is higher in developing countries rather than developed countries. this indicates that the developing countries are capable to utilize the minimum resources and involve with lower wastage of inputs. alsaleh, et al.: an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on dea method international journal of energy economics and policy | vol 6 • issue 2 • 2016 295 ta bl e 3: d et ai ls o f p ar am et ri c an d no n‑ pa ra m et ri c m ea n te st s du ri ng 2 00 0‑ 20 13 y ea r g ro up su m m ar y of p ar am et ri c an d no n– pa ra m et ri c te st s p ar am et ri c te st n on -p ar am en tr ic te st t– te st m an n– w hi tn ey w ilc ox on te st k ru sk al –w al lis t e t p t e t se t t e z p t e z se z t e c hi -s qu ar e p t e c hi -s qu ar e se c hi -s qu ar e 20 00 d ev el op in g 0. 80 7 0. 25 0 0. 90 2 0. 06 2 0. 89 9 0. 42 8 14 .8 10 –0 .3 03 15 .3 80 –0 .7 44 13 .2 30 –0 .7 85 14 .8 10 0. 03 5 15 .3 80 0. 31 2 13 .2 30 0. 61 7 d ev el op ed 0. 73 8 0. 81 5 0. 87 2 14 .2 30 13 .7 30 15 .6 00 14 .2 30 13 .7 30 15 .6 00 20 01 d ev el op in g 0. 82 9 0. 16 3 0. 91 2 0. 02 1 0. 91 6 0. 71 9 15 .0 00 –0 .3 26 15 .6 90 –0 .4 13 13 .5 40 –0 .2 22 15 .0 00 0. 09 2 15 .6 90 0. 55 3 13 .5 40 0. 37 9 d ev el op ed 0. 74 8 0. 79 1 0. 92 1 14 .0 70 13 .4 70 15 .3 30 14 .0 70 13 .4 70 15 .3 30 20 02 d ev el op in g 0. 85 8 0. 31 9 0. 92 5 0. 03 0 0. 93 2 0. 68 3 16 .1 20 –0 .9 98 16 .4 20 –1 .2 52 14 .8 50 –0 .2 42 16 .1 20 0. 99 6 16 .4 20 1. 56 7 14 .8 50 0. 05 9 d ev el op ed 0. 76 1 0. 80 3 0. 92 2 13 .1 00 12 .8 30 14 .2 00 13 .1 00 12 .8 30 14 .2 00 20 03 d ev el op in g 0. 82 2 0. 18 7 0. 92 2 0. 02 3* 0. 89 9 0. 84 5 16 .3 10 –1 .1 01 16 .9 20 –1 .5 51 14 .8 80 –0 .2 43 16 .3 10 1. 21 2 16 .9 20 2. 40 7 14 .8 80 0. 05 9 d ev el op ed 0. 72 1 0. 78 5 0. 89 6 12 .9 30 12 .4 00 14 .1 70 12 .9 30 12 .4 00 14 .1 70 20 04 d ev el op in g 0. 81 7 0. 23 0 0. 90 3 0. 09 0 0. 91 2 0. 55 1 15 .9 60 –0 .8 90 16 .5 00 –1 .2 82 15 .6 50 –0 .7 20 15 .9 60 0. 79 3 16 .5 00 1. 64 4 15 .6 50 0. 51 8 d ev el op ed 0. 72 7 0. 80 8 0. 87 6 13 .2 30 12 .7 70 13 .5 00 13 .2 30 12 .7 70 13 .5 00 20 05 d ev el op in g 0. 81 5 0. 48 1 0. 90 3 0. 16 2 0. 90 9 0. 46 4 15 .9 20 –0 .8 67 15 .5 80 –0 .6 90 15 .5 80 –0 .6 72 15 .9 20 0. 75 2 15 .5 80 0. 47 6 15 .5 80 0. 45 2 d ev el op ed 0. 72 5 0. 83 2 0. 85 2 13 .2 70 13 .5 70 13 .5 70 13 .2 70 13 .5 70 13 .5 70 20 06 d ev el op in g 0. 81 3 0. 37 9 0. 89 8 0. 17 0 0. 91 2 0. 50 0 15 .4 20 –0 .5 62 15 .9 20 –0 .9 11 14 .5 40 –0 .0 26 15 .4 20 0. 31 6 15 .9 20 0. 83 0 14 .5 40 0. 00 1 d ev el op ed 0. 76 0 0. 79 9 0. 93 3 13 .7 00 13 .2 70 14 .4 70 13 .7 00 13 .2 70 14 .4 70 20 07 d ev el op in g 0. 80 1 0. 45 8 0. 89 5 0. 04 6 0. 90 3 0. 88 6 15 .4 20 –0 .5 62 15 .6 90 –0 .7 63 15 .3 50 –0 .5 16 15 .4 20 0. 31 6 15 .6 90 0. 58 3 15 .3 50 0. 26 6 d ev el op ed 0. 73 6 0. 80 7 0. 89 2 13 .7 00 13 .4 70 13 .7 70 13 .7 00 13 .4 70 13 .7 70 20 08 d ev el op in g 0. 80 5 0. 64 4 0. 83 8 0. 87 0 0. 96 2 0. 05 7* 15 .1 20 –0 .3 77 15 .7 70 –0 .8 12 14 .2 70 –0 .1 46 15 .1 20 0. 14 2 15 .7 70 0. 66 0 14 .2 70 0. 02 1 d ev el op ed 0. 69 9 0. 80 4 0. 86 4 13 .9 70 13 .4 00 14 .7 00 13 .9 70 13 .4 00 14 .7 00 20 09 d ev el op in g 0. 77 5 0. 83 3 0. 88 1 0. 19 9 0. 88 6 0. 32 2 14 .8 10 –0 .1 87 16 .0 40 –0 .9 85 12 .6 50 –1 .1 52 14 .8 10 0. 03 5 16 .0 40 0. 97 1 12 .6 50 1. 32 8 d ev el op ed 0. 74 9 0. 80 0 0. 93 4 14 .2 30 13 .1 70 16 .1 00 14 .2 30 13 .1 70 16 .1 00 20 10 d ev el op in g 0. 77 3 0. 59 1 0. 86 8 0. 22 0 0. 89 9 0. 22 0 13 .9 60 –0 .3 26 15 .1 90 –0 .4 32 12 .7 30 –1 .1 17 13 .9 60 0. 10 7 15 .1 90 0. 18 7 12 .7 30 1. 24 8 d ev el op ed 0. 78 3 0. 80 7 0. 96 4 14 .9 70 13 .9 00 16 .0 30 14 .9 70 13 .9 00 16 .0 30 20 11 d ev el op in g 0. 74 3 0. 59 3 0. 85 2 0. 15 7 0. 88 4 0. 07 3 14 .5 40 –0 .0 23 15 .5 40 –0 .6 42 11 .6 50 –1 .7 98 * 14 .5 40 0. 00 1 15 .5 40 0. 41 2 11 .6 50 3. 23 1* d ev el op ed 0. 73 3 0. 77 9 0. 94 6 14 .4 70 13 .6 00 16 .9 70 14 .4 70 13 .6 00 16 .9 70 20 12 d ev el op in g 0. 77 9 0. 29 1 0. 86 7 0. 05 1 0. 90 7 0. 23 1 15 .0 80 –0 .3 49 15 .3 80 –0 .5 66 14 .1 90 –0 .1 92 15 .0 80 0. 12 2 15 .3 80 0. 32 1 14 .1 90 0. 03 7 d ev el op ed 0. 74 5 0. 80 9 0. 92 8 14 .0 00 13 .7 30 14 .7 70 14 .0 00 13 .7 30 14 .7 70 20 13 d ev el op in g 0. 81 5 0. 43 4 0. 81 5 0. 10 5 0. 91 3 0. 00 1 14 .2 30 –0 .1 65 15 .4 60 –0 .6 07 13 .9 20 –0 .3 83 14 .2 30 0. 02 7 15 .4 60 0. 36 8 13 .9 20 0. 14 7 d ev el op ed 0. 81 0 0. 81 0 0. 97 4 14 .7 30 13 .6 70 15 .0 00 14 .7 30 13 .6 70 15 .0 00 20 12 d ev el op in g 0. 77 9 0. 63 6 0. 86 7 0. 45 1 0. 90 7 0. 61 9 15 .0 80 0. 72 7 15 .3 80 0. 57 1 14 .1 90 0. 84 8 15 .0 80 0. 72 7 15 .3 80 0. 57 1 14 .1 90 0. 84 8 d ev el op ed 0. 74 5 0. 80 9 0. 92 8 14 .0 00 13 .7 30 14 .7 70 14 .0 00 13 .7 30 14 .7 70 20 13 d ev el op in g 0. 81 5 0. 94 5 0. 81 5 0. 34 2 0. 91 3 0. 13 7 14 .2 30 0. 86 9 15 .4 60 0. 54 4 13 .9 20 0. 70 2 14 .2 30 0. 86 9 15 .4 60 0. 54 4 13 .9 20 0. 70 2 d ev el op ed 0. 81 0 0. 81 0 0. 97 4 14 .7 30 13 .6 70 15 .0 00 14 .7 30 13 .6 70 15 .0 00 t e : t ec hn ic al e ffi ci en cy , p t e : p ur e te ch ni ca l e ffi ci en cy , s e : s ca le e ffi ci en cy , * ** ,* * an d* : i nd ic at e si gn ifi ca nc e at th e 1% , 5 % , a nd 1 0% le ve ls re sp ec tiv el y alsaleh, et al.: an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on dea method international journal of energy economics and policy | vol 6 • issue 2 • 2016296 likewise, the developing countries have also exhibited a higher mean pte level compared to the developed countries (0.884 > 0.804), which statically insignificant because p value is greater than the significant level at 10% statistically significant at the 10% level. in the other hand, the developing countries have exhibited lower mean se level compared to the developed countries (0.909 > 0.912) which statically insignificant because p value is greater than the significant level at 10%. as per table 4, the results from the non-parametric test mann–whitney wilcoxon test for the period between 2000 and 2013 suggest that the developing countries have exhibited a higher mean te level compared to the developed countries (15.193 > 13.900) which statically insignificant because p value is greater than the significant level at 10%. likewise, the developing countries have also exhibited a higher mean pte level compared to the developed countries (15.820 > 13.356) which statically insignificant because p value is greater than the significant level at 10%. in the other hand, the developing countries have exhibited lower mean se level compared to the developed countries (14.470 > 14.480) which statically insignificant because p value is greater than the significant level at 10%, statistically significant at the 10% level. as per table 4, the results from the non-parametric test kruskall–wallis test for the period between 2000 and 2013 suggest that the developing countries have exhibited a higher mean te level compared to the developed countries (15.193 > 13.900) which statically insignificant because p value is greater than the significant level at 10%. likewise, the developing countries have also exhibited a higher mean pte level compared to the developed countries (15.820 > 13.356) which statically insignificant because p value is greater than the significant level at 10%. in the other hand, the developing countries have exhibited lower mean se level compared to the developed countries (14.470 > 14.074) which statically insignificant because p value is greater than the significant level at 10%, statistically significant at the 10% level. regarding the period between 1990 and 1999, the results from t-test parametric test, non-parametric mann–whitney wilcoxon test, and kruskall–wallis test suggests that the developing countries have exhibited a higher means te and pte level compared to the developed countries, statistically significant at the 5%, 10% and 10% levels respectively. on the other hand, the results from t-test parametric test, non-parametric mann– whitney wilcoxon test, and kruskall–wallis test suggests that the developing countries have exhibited a lower means se level compared to the developed countries for the period between 1990 and 1999 (appendix f and g). in t-test for the year 2000, the mean of te is statistically insignificance, because p-value is greater than the significant level at 10% as follow 0.514 > 0.1, where pte is statistically insignificance because p value is greater than the significant level at 10% as follow 0.262 > 0.1, while se is statistically insignificance, because p value is greater than the significant level at 10% as follow 0.761 > 0.10. moreover, in mann–whitney test for the same year 2000, the mean of te is statistically insignificance, because p value is greater than statistical level at 10% as follow 0.864 > 0.1, where pte is statistically insignificance because p value is lesser than the significant level at 10% as follow 0.577 > 0.1, while se is statistically insignificant because p value is greater than the significant level at 10% as follow 0.432 > 0.10. furthermore, in kruskal–wallis test for the same year 2000, the mean of te is statistically insignificance because p value is greater than the statistical level at the level 10% as follow 0.854 > 0.1, where pte is statistically insignificance because p value is greater than the statistical level at 10% as follow 0.577 > 0.1, while se is statistically insignificant because p value is greater than the significant level at 10% as follow 0.432 > 0.10. in 2006, t-test results have presented that means of te, pte and se are statistically insignificance because of p values are greater than the statistical level at 10% as follow 0.554 > 0.10, 0.227 > 0.10 and 0.734 > 0.10 respectively. moreover, in mann whitney test for the same year 2006, the results have indicated to te, pte and se are statistically insignificance because of p values are greater than the statistical level at 10% as follow 0.574 > 0.10, 0.362 > 0.10 and 0.980 > 0.10 respectively. furthermore, in kruskal–wallis test for the same year 2006, the results have indicated to te, pte and se are statistically insignificance because of p values are greater than the statistical level at 10% as follow 0.574 > 0.10, 0.362 > 0.10 and 0.980 > 0.1) respectively. in t-test for the year 2013, te is statistically insignificance because of p value is greater than the statistical level at 10% as follow table 4: summary of parametric and non-parametric mean tests during 2000-2013 test groups (2000-2013) parametric test non-parametric test individual test t-test mann–whitney [wilcoxon] test kruskall–wallis test hypothesis test t-test median developed and developing equality of populations test test statistics t (p>t) z (p>z) χ2 (p>χ2) mean t mean rank z mean rank χ2 (p>χ2) te developing countries 0.804 0.418 15.193 –0.503 15.193 0.353 developed countries 0.745 13.900 13.900 pte developing countries 0.884 0.158* 15.820 –0.832 15.820 0.807 developed countries 0.804 13.356 13.356 se developing countries 0.909 0.427* 14.470 –0.587* 14.074 0.597* developed countries 0.912 14.870 14.870 note: ***, ** and * indicate significance at the 1%, 5%, and 10% levels respectively, te: technical efficiency, pte: pure technical efficiency, se: scale efficiency alsaleh, et al.: an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on dea method international journal of energy economics and policy | vol 6 • issue 2 • 2016 297 0.945 > 0.10, where pte is statistically insignificance because of p value is greater than the statistical level at 10% as follow 0.342 > 0.1, while (se) is statistically insignificance because of p value is greater than the statistical level at 10% as follow 0.137 > 0.10. moreover, in mann–whitney test and kruskal–wallis test for the year 2013 the results have referred to that te, pte and se are statistically insignificance because the p values are greater that the statistical level at 10% as follow 0.869 > 0.10, 0.544 > 0.10 and 0.702 > 0.10 respectively. 6. conclusion and policy implications the paper has attempted to investigate the efficiency of eu28 bioenergy industry during the period between 1990 and 2013. the employed non-parametric dea method has gave us the chance to distinguish between three distinction kinds of efficiency which are technical, pure technical and scale efficiencies. moreover, we have applied a series of parametric and non-parametric tests to examine whether the developing and developed countries were drawn from the same population. finally, we have employed non parametric tests (mann–whitney u and kruskal–wallis tests) and parametric test (t-test). for the period between 2000 and 2013, we have resulted that the mean of te in developing countries is higher than the one in developed countries in eu28 region, suggesting minimal waste of inputs by developing countries lower than the one in developed countries. overall, our results suggest that the mean of se dominates pte effects in determining eu28 developing countries in te. moreover, our results suggest that se dominates the pte effects in determining eu28 developed countries in te. in eu28 and for the same study period between 2000 and 2013, bioenergy industry has exhibited relatively higher efficient in developing countries than developed countries during the same study period. our findings through robustness test have indicated to that in te from the parametric and non-parametric tests in table 4 rejected the null hypothesis and accepted the alternative hypothesis due to that the average means of te in developing and developed countries are different and statistically insignificant because p value is greater than the statistical level at 10%. moreover, the results for pte from the parametric and non-parametric tests in table 4 have rejected the null hypothesis and accepted the alternative hypothesis due to that the average means of pte in developing and developed countries are different and statistically insignificant because p value is greater than the statistical level at 10% in the different employed t-test, mann–whitney u test and kruskal–wallis test respectively. nevertheless, the results for se from the parametric and non-parametric tests in table 4 have rejected the null hypothesis and accepted the alternative hypothesis due to that the average means of se in developing and developed countries are different and statistically insignificant because p value is greater than the statistical level at 10%. the finding shows that in developing and developed countries se is dominating pte. moreover, the contributing of pure technical inefficiency is outweighs scale inefficiency in eu28 bioenergy industry. therefore, our results do not support further increasing in the size of the plants, because in further enhance in size will only result smaller enhance in output for every proportionate enhance in inputs, giving from the fact that eu28 bioenergy industry has been producing at decreasing returns to scale between the period 2000 and 2013, but our results recommend more efforts to be given to the top management and decision makers with regard to attaining optimal utilization of capacity, improvement in managerial and skills expertise, efficiency allocation of available resources and most productive scale in production of bioenergy industry in eu28, which may facilitate directions for sustainable competitiveness on bioenergy industry in the future. furthermore, our results from the parametric and non-parametric tests could reject relatively the null hypothesis (6 results) that the means of te in developing and developed countries are not the same (different) and were drawn from the different population. due to the study limitations, the current study may be expanded in different of ways. first, if information on input prices is available, further analysis could be performed to investigate the overall cost efficiency decomposition te and allocative efficiency. second, interested researchers may employ the malmquist productivity index method to examine the sources of total factor productivity changes of bioenergy industry in eu28 countries. third, to obtain more robust results, empirical findings from the current study could be compared to the results derived from improved statistical methods, i.e., bootstrap dea. references balat, m., balat, m. (2009), political, economic and environmental impacts of biomass-based hydrogen. international journal of hydrogen energy, 34(9), 3589-3603. banker, r.d., charnes, a., cooper, w.w. (1984), some models for estimating technical and scale inefficiencies in data envelopment analysis. management science, 30(9), 8-92. berndes, g., hansson, j., egeskog, a., johnsson, f. (2009), strategies for 2nd generation biofuels in eu co-firing to stimulate feedstock supply development and process integration to improve energy efficiency and economic competitiveness. biomass and bioenergy, 34(2), 227-236. burck, j., hermwille, l., krings, l. (2012), climate change performance index result 2013. bonn: germanwatch. chang, j., leung, d., wu, c., yuan, z. (2013), a review on the energy production, consumption and prospect of renewable energy in china. renewable and sustainable energy reviews, 7(5), 453-468. charnes, a., cooper, w.w., rhodes, e. (1978), measuring the efficiency of decision making units. european journal of operations research, 2(6), 429-444. coelli, t. (1996), a guide to deap version 2.1: a data envelopment analysis (computer program). working paper. armidale: cepa, university of new england. coelli, t., prasada-rao, d.s., battese, g.e. (1998), an introduction to efficiency and productivity analysis. boston: kluwer academic publishers. cooper, w.w., seiford, l.m., tone, k. (2002), data envelopment analysis, a comprehensive text with models, applications, references and dea-solver software. boston: kluwer academic publishers. evans, a., strezov, v., evans, t. (2010), sustainability considerations alsaleh, et al.: an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on dea method international journal of energy economics and policy | vol 6 • issue 2 • 2016298 for electricity generation from biomass. renewable and sustainable energy reviews journal, 14(5), 1419-1427. geheeb, g. (2007), the renewable energy source act: the success story of sustainable policies for germany. federal ministry for the environment, nature conservation and nuclear safety report, 2007. gilani, h. (2015), exploring the ethical aspects of islamic banking. international journal of islamic and middle eastern finance and management, 8(1), 85-98. hu, j., wang, s. (2005), total-factor energy efficiency of regions in china. energy policy journals, 34(17), 3206-3217. jossart, j.m., calderon, c. (2013), european biomass association. european bioenergy outlook report 2013 aebiom. kythreotou, n., savvas, t., georgios, f. (2012), an assessment of the biomass potential of cyprus for energy production. energy journal, 47(1), 253-261. lee, c.c. (2009), analysis of overall technical efficiency, pure technical efficiency and scale efficiency in the medium-sized audit firms. expert systems with applications, 36, 11156-11171. md, d.m., kashfia, s. (2015), relationship between capital, risk and efficiency: a comparative study between islamic and conventional banks of bangladesh. international journal of islamic and middle eastern finance and management, 8(2), 203-221. omar, r.f., jones, e. (2015), critical evaluation of the compliance of online islamic forex trading with islamic principles. international journal of islamic and middle eastern finance and management, 8(1), 64-84. reddy, s., assenza, g. (2007), barriers and drivers to energy efficiency a new taxonomical approach. mumbai: indira gandhi institute of development research (igidr). sufian, f. (2008), determinants of bank efficiency during unstable macroeconomic environment: empirical evidence from malaysia. research in international business and finance, 23, 54-77. sufian, f., habibullah, m. (2011), opening the black box on bank efficiency in china: does economic freedom matter. global economic review perspectives on east asian economies and industries, 40(3), 269-298. sufian, f., haron, r. (2008), the sources and determinants of productivity growth in the malaysian islamic banking sector: a non-stochastic frontier approach. international journal of accounting and finance, 1(2), 193-215. sufian, f. (2007), the efficiency of islamic banking industry in malaysia: foreign versus domestic banks. humanomics, 23(3), 174-192. sufian, f., habibullah, m. (2013), the impact of forced mergers and acquisitions on banks, total factor productivity: empirical evidence from malaysia. journal of the asia pacific economy, 19(1), 151185. sufian, f., kamurdin, f. (2015), determinants of revenue efficiency of islamic banks: empirical evidence from the southeast asian countries. international journal of islamic and middle eastern finance and management, 8(1), 36-63. sufian, f., habibullah, m. (2013), the impact of forced mergers and acquisitions on banks, total factor productivity: empirical evidence from malaysia. journal of the asia pacific economy, 19(1),151-185. sufian, f. (2009), assessing the impact of mergers and acquisitions on bank profit efficiency: empirical evidence from malaysia. international journal decision sciences, risk and management, 1(3-4), 258-285. scowcroft, j., nies, s. (2011), biomass 2020: opportunities, challenges and solutions. the union of the electricity industry. shafie, s., mahlia, t., masjuki, h., yazid, a. (2012), a review on electricity generation based on biomass residue in malaysia. renewable and sustainable energy reviews journal, 16(8), 5879-5889. scarlat, n., dallemand, j., motola, v., monforti, f. (2013), bioenergy production and use in italy: recent developments, perspectives and potential. renewable energy journal, 57(3), 448-461. tye, y., lee, k., abdullah, w., leh, c. (2011), second-generation bioethanol as a sustainable energy source in malaysia transportation sector: status, potential and future prospects. renewable and sustainable energy reviews journals, 15(9), 4521-4536. winkler, h. (2003), renewable energy policy in south africa: policy options for renewable electricity. energy policy journals, 33(1), 27-38. yudistira, d. (2004), efficiency in islamic banking: an empirical analysis of 18 banks. islamic economic studies, 12(1), 1-19. alsaleh, et al.: an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on dea method international journal of energy economics and policy | vol 6 • issue 2 • 2016 299 appendices appendix a: technical efficiency of bioenergy industry in developing countries during 2000‑2013 year 2000 2001 2002 2003 2004 country te pte se te pte se te pte se te pte se te pte se bulgaria 0.50 0.51 0.98 0.52 0.52 1.00 0.53 0.53 1.00 0.53 0.54 1.00 0.52 0.52 0.99 czech 0.73 0.78 0.93 0.77 0.83 0.92 0.78 0.87 0.90 0.77 1.00 0.77 0.82 1.00 0.82 estonia 0.78 0.87 0.89 0.77 0.87 0.89 0.77 0.87 0.89 0.72 0.83 0.87 0.73 0.83 0.88 croatia 0.94 0.94 0.99 0.98 0.98 1.00 0.94 0.95 1.00 0.88 0.96 0.92 0.93 0.97 0.96 cyprus 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 latvia 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 lithuania 1.00 1.00 1.00 0.97 1.00 0.97 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 hungary 0.69 0.70 0.99 0.76 0.76 1.00 0.81 0.81 1.00 0.81 0.81 1.00 0.81 0.81 1.00 malta 0.88 0.95 0.93 0.93 0.97 0.97 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 poland 0.98 1.00 0.98 0.93 0.93 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 romania 0.92 0.98 0.93 0.89 0.99 0.90 1.00 1.00 1.00 0.76 0.84 0.91 0.61 0.61 1.00 slovenia 0.14 1.00 0.14 0.41 1.00 0.41 0.39 1.00 0.39 0.39 1.00 0.39 0.38 1.00 0.38 slovakia 0.93 1.00 0.93 0.85 1.00 0.85 0.93 1.00 0.93 0.83 1.00 0.83 0.82 1.00 0.83 average by year 0.80 0.90 0.90 0.83 0.91 0.92 0.86 0.93 0.93 0.82 0.92 0.90 0.82 0.90 0.91 year 2005 2006 2007 2008 2009 country te pte se te pte se te pte se te pte se te pte se bulgaria 0.52 0.53 0.98 0.52 0.52 1.00 0.51 0.51 0.99 0.52 0.52 0.99 0.52 0.52 0.99 czech 0.82 1.00 0.82 0.84 1.00 0.84 0.81 1.00 0.81 0.76 1.00 0.76 0.79 1.00 0.79 estonia 0.70 0.84 0.84 0.75 0.88 0.85 0.77 0.89 0.87 0.74 0.85 0.87 0.74 0.96 0.77 croatia 0.94 0.99 0.96 0.78 0.82 0.95 0.79 0.82 0.97 0.78 0.80 0.97 0.71 0.76 0.94 cyprus 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 latvia 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 lithuania 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.90 1.00 0.90 hungary 0.91 0.92 0.99 0.92 0.93 1.00 0.93 0.96 0.97 0.85 0.88 0.96 0.73 0.78 0.93 malta 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 poland 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 romania 0.56 0.56 1.00 0.62 0.62 1.00 0.58 0.59 0.99 0.63 0.63 1.00 0.63 0.66 0.96 slovenia 0.37 1.00 0.37 0.50 1.00 0.50 0.34 1.00 0.34 0.36 1.00 0.36 0.46 1.00 0.46 slovakia 0.77 0.90 0.85 0.71 0.91 0.78 0.68 0.86 0.80 0.64 0.79 0.81 0.60 0.77 0.78 average by year 0.81 0.90 0.91 0.82 0.90 0.92 0.80 0.89 0.90 0.79 0.88 0.90 0.77 0.88 0.88 year 2010 2011 2012 2013 average by country country te pte se te pte se te pte se te pte se te pte se bulgaria 0.52 0.52 0.99 0.45 0.45 1.00 0.45 0.45 1.00 0.45 0.45 1.00 0.50 0.51 0.99 czech 0.79 1.00 0.79 0.75 1.00 0.75 0.77 1.00 0.77 0.79 1.00 0.79 0.78 0.96 0.82 estonia 0.74 0.96 0.77 0.72 0.93 0.77 0.76 0.91 0.84 0.92 0.99 0.93 0.76 0.89 0.85 croatia 0.71 0.76 0.94 0.72 0.78 0.92 0.72 0.75 0.95 0.85 0.85 1.00 0.83 0.87 0.96 cyprus 1.00 1.00 1.00 0.95 0.96 0.99 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 latvia 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 lithuania 0.90 1.00 0.90 0.88 1.00 0.88 0.83 1.00 0.83 0.69 0.91 0.76 0.94 0.99 0.94 hungary 0.73 0.78 0.93 0.72 0.73 0.99 0.76 0.76 1.00 0.86 0.86 1.00 0.81 0.82 0.98 malta 1.00 1.00 1.00 0.82 0.84 0.98 0.85 0.87 0.98 1.00 1.00 1.00 0.96 0.97 0.99 poland 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.99 0.99 1.00 romania 0.63 0.66 0.96 0.59 0.60 0.99 0.72 0.72 1.00 0.78 0.79 1.00 0.71 0.73 0.97 slovenia 0.46 1.00 0.46 0.51 1.00 0.51 0.63 1.00 0.63 0.61 1.00 0.61 0.42 1.00 0.42 slovakia 0.60 0.77 0.78 0.55 0.78 0.71 0.64 0.81 0.79 0.65 0.84 0.78 0.73 0.89 0.82 average by year 0.77 0.88 0.88 0.74 0.85 0.88 0.78 0.87 0.91 0.81 0.90 0.91 0.80 0.89 0.90 te: technical efficiency, pte: pure technical efficiency, se: scale efficiency alsaleh, et al.: an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on dea method international journal of energy economics and policy | vol 6 • issue 2 • 2016300 appendix b: technical efficiency of bioenergy industry in developed countries over 2000‑2013 year 2002 2003 2004 2005 2006 country te pte se te pte se te pte se te pte se te pte se belgium 0.69 0.69 0.99 0.67 0.68 0.99 0.60 0.61 0.98 0.58 0.60 0.97 0.52 0.52 1.00 denmark 0.63 0.63 1.00 0.52 0.53 0.97 0.52 0.61 0.85 0.52 0.68 0.76 0.60 0.60 1.00 germany 0.80 0.81 0.98 0.77 0.84 0.93 0.76 0.78 0.98 0.84 0.84 1.00 0.82 0.85 0.96 ireland 1.00 1.00 1.00 0.88 1.00 0.88 1.00 1.00 1.00 0.91 1.00 0.91 0.83 1.00 0.83 greece 0.38 0.41 0.93 0.36 0.41 0.88 0.43 0.49 0.88 0.41 0.49 0.83 0.42 0.45 0.93 spain 0.61 1.00 0.61 0.58 0.96 0.60 0.47 1.00 0.47 0.56 1.00 0.56 0.87 1.00 0.87 france 0.77 0.77 1.00 0.75 0.75 1.00 0.74 0.74 1.00 0.69 0.69 1.00 0.65 0.65 1.00 italy 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 luxembourg 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 netherlands 0.90 0.90 1.00 0.99 1.00 0.99 0.88 0.92 0.95 0.77 0.93 0.83 1.00 1.00 1.00 austria 0.08 0.23 0.36 0.11 0.27 0.39 0.07 0.37 0.19 0.04 0.56 0.07 0.12 0.24 0.51 portugal 0.60 0.60 1.00 0.56 0.56 1.00 0.60 0.61 0.99 0.66 0.69 0.96 0.68 0.68 1.00 finland 0.95 1.00 0.95 0.62 0.77 0.81 0.92 1.00 0.92 1.00 1.00 1.00 0.93 1.00 0.93 year 2007 2008 2009 2010 2011 country te pte se te pte se te pte se te pte se te pte se belgium 0.55 0.56 0.98 0.62 0.62 0.99 0.66 0.66 1.00 0.66 0.66 1.00 0.68 0.68 1.00 denmark 0.54 0.65 0.83 0.57 0.63 0.90 0.66 0.66 1.00 0.66 0.66 1.00 0.53 0.53 1.00 germany 0.82 0.86 0.95 0.86 0.86 0.99 0.66 0.67 0.99 0.66 0.67 0.99 0.70 0.70 1.00 ireland 0.87 1.00 0.87 0.88 1.00 0.88 0.80 1.00 0.80 0.80 1.00 0.80 0.74 1.00 0.74 greece 0.38 0.43 0.89 0.46 0.57 0.82 0.48 0.65 0.74 0.48 0.65 0.74 0.45 0.51 0.89 spain 0.66 1.00 0.66 0.65 1.00 0.65 0.73 1.00 0.73 0.73 1.00 0.73 0.73 1.00 0.73 france 0.62 0.63 0.99 0.68 0.68 1.00 0.68 0.71 0.96 0.68 0.71 0.96 0.73 0.80 0.92 italy 1.00 1.00 1.00 1.00 1.00 1.00 0.96 1.00 0.96 0.96 1.00 0.96 1.00 1.00 1.00 luxembourg 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 netherlands 0.95 1.00 0.95 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.94 0.95 1.00 austria 0.13 0.37 0.35 0.19 0.35 0.54 0.23 0.27 0.83 0.23 0.27 0.83 0.22 0.24 0.91 portugal 0.68 0.68 0.99 0.70 0.70 1.00 0.62 0.63 1.00 0.62 0.63 1.00 0.68 0.68 1.00 finland 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 year 2012 2013 average country te pte se te pte se belgium 0.67 0.67 1.00 0.74 0.74 1.00 0.76 denmark 0.59 0.59 0.99 0.54 0.54 0.99 0.71 germany 0.65 0.67 0.97 0.70 0.71 0.98 0.83 ireland 0.79 1.00 0.79 1.00 1.00 1.00 0.92 greece 0.53 0.62 0.86 0.58 0.60 0.97 0.61 spain 0.72 1.00 0.72 0.83 1.00 0.83 0.78 france 0.88 1.00 0.88 0.96 0.99 0.97 0.82 italy 1.00 1.00 1.00 1.00 1.00 1.00 0.99 luxembourg 1.00 1.00 1.00 1.00 1.00 1.00 1.00 netherlands 1.00 1.00 1.00 1.00 1.00 1.00 0.97 austria 0.25 0.28 0.92 0.20 0.22 0.89 0.34 portugal 0.65 0.65 1.00 0.76 0.76 1.00 0.77 finland 0.80 1.00 0.80 1.00 1.00 1.00 0.96 te: technical efficiency, pte: pure technical efficiency, se: scale efficiency alsaleh, et al.: an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on dea method international journal of energy economics and policy | vol 6 • issue 2 • 2016 301 appendix c: technical efficiency of bioenergy industry in developing countries over 1990‑1999 year 1990 1991 1992 1993 country te pte se te pte se te pte se te pte se bulgaria 0.53 0.53 1.00 0.54 0.54 1.00 0.54 0.54 1.00 0.50 0.50 1.00 czech 0.54 0.54 1.00 0.53 0.53 1.00 0.56 0.57 0.98 0.52 0.59 0.88 estonia 1.00 1.00 1.00 1.00 1.00 1.00 0.82 1.00 0.82 1.00 1.00 1.00 croatia 0.88 0.90 0.98 0.81 0.81 1.00 0.88 0.88 1.00 0.82 0.83 1.00 cyprus 0.83 0.83 1.00 0.78 0.78 1.00 0.88 0.88 1.00 0.98 0.98 1.00 latvia 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 lithuania 0.52 0.52 1.00 0.54 0.54 1.00 0.70 0.70 1.00 0.55 0.69 0.80 hungary 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.79 0.94 0.84 malta 0.28 0.29 1.00 0.28 0.28 1.00 0.53 0.53 1.00 0.54 0.55 0.98 poland 1.00 1.00 1.00 1.00 1.00 1.00 0.89 0.90 0.99 0.85 0.85 0.99 romania 0.89 0.90 0.99 0.57 0.57 1.00 0.52 0.52 1.00 0.71 0.71 1.00 slovenia 0.42 1.00 0.42 0.47 1.00 0.47 0.50 1.00 0.50 0.09 1.00 0.09 slovakia 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.44 0.65 0.69 average by year 0.76 0.81 0.95 0.73 0.77 0.96 0.75 0.81 0.94 0.68 0.79 0.87 year 1994 1995 1996 1997 country te pte se te pte se te pte se te pte se bulgaria 0.53 0.53 1.00 0.52 0.52 1.00 0.54 0.54 1.00 0.55 0.55 1.00 czech 0.56 0.61 0.91 0.58 0.60 0.96 0.60 0.62 0.97 0.62 0.70 0.88 estonia 1.00 1.00 1.00 0.84 1.00 0.84 0.87 1.00 0.87 0.85 1.00 0.85 croatia 0.75 0.75 1.00 0.75 0.75 1.00 0.76 0.76 1.00 0.83 0.83 1.00 cyprus 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 latvia 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 lithuania 0.79 0.92 0.86 0.91 0.96 0.94 0.95 1.00 0.95 1.00 1.00 1.00 hungary 0.81 0.87 0.93 0.73 0.75 0.98 0.76 0.77 0.98 0.75 0.75 1.00 malta 0.52 0.53 0.99 0.80 0.82 0.98 0.98 1.00 0.98 0.92 0.93 0.99 poland 1.00 1.00 1.00 0.90 0.91 0.99 0.86 0.87 0.99 0.79 0.79 1.00 romania 0.74 0.76 0.98 0.76 0.80 0.95 0.72 0.79 0.90 0.75 0.78 0.96 slovenia 0.12 1.00 0.12 0.24 1.00 0.24 0.27 1.00 0.27 0.24 1.00 0.24 slovakia 0.48 0.65 0.74 0.85 1.00 0.85 0.86 1.00 0.86 0.83 1.00 0.83 average by year 0.71 0.82 0.89 0.76 0.85 0.90 0.78 0.87 0.90 0.78 0.87 0.90 year 1998 1999 average by country country te pte se te pte se te pte se bulgaria 0.57 0.57 1.00 0.57 0.57 1.00 0.54 0.54 1.00 czech 0.65 0.71 0.92 0.65 0.74 0.88 0.58 0.62 0.94 estonia 0.89 1.00 0.89 0.79 0.88 0.89 0.91 0.99 0.92 croatia 0.81 0.81 1.00 0.89 0.89 0.99 0.82 0.82 1.00 cyprus 1.00 1.00 1.00 1.00 1.00 1.00 0.95 0.95 1.00 latvia 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 lithuania 1.00 1.00 1.00 1.00 1.00 1.00 0.80 0.83 0.95 hungary 0.73 0.73 1.00 0.69 0.69 0.99 0.83 0.85 0.97 malta 0.80 0.82 0.98 0.79 0.85 0.93 0.65 0.66 0.98 poland 0.97 0.97 0.99 1.00 1.00 1.00 0.93 0.93 1.00 romania 0.84 0.87 0.96 0.80 0.81 0.99 0.73 0.75 0.97 slovenia 0.25 1.00 0.25 0.19 1.00 0.19 0.28 1.00 0.28 slovakia 0.81 1.00 0.81 0.89 1.00 0.89 0.81 0.93 0.86 average by year 0.79 0.88 0.91 0.79 0.88 0.90 0.75 0.84 0.91 te: technical efficiency, pte: pure technical efficiency, se: scale efficiency alsaleh, et al.: an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on dea method international journal of energy economics and policy | vol 6 • issue 2 • 2016302 appendix d: technical efficiency of bioenergy industry in developed countries over 1990‑1999 year 1990 1991 1992 1993 country te pte se te pte se te pte se te pte se belgium 0.68 0.68 1.00 0.69 0.69 1.00 0.71 0.71 1.00 0.45 0.45 0.99 denmark 0.34 0.34 1.00 0.35 0.36 1.00 0.36 0.36 1.00 0.25 0.26 0.97 germany 0.77 0.77 1.00 0.81 0.81 1.00 1.00 1.00 1.00 0.91 1.00 0.91 ireland 0.96 1.00 0.96 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 greece 0.49 0.49 1.00 0.51 0.51 1.00 0.50 0.50 1.00 0.30 0.49 0.62 spain 0.14 0.58 0.25 0.14 0.61 0.24 0.49 0.50 0.97 0.48 0.71 0.68 france 0.55 0.55 1.00 0.54 0.54 1.00 0.53 0.53 1.00 0.47 0.47 1.00 italy 0.88 0.88 1.00 0.90 0.90 1.00 0.94 1.00 0.94 1.00 1.00 1.00 luxembourg 0.50 0.50 1.00 0.52 0.52 1.00 0.56 0.57 1.00 0.16 0.16 0.99 netherlands 1.00 1.00 1.00 1.00 1.00 1.00 0.72 0.76 0.96 0.55 0.57 0.96 austria 0.07 0.09 0.75 0.07 0.10 0.72 0.08 0.10 0.82 0.06 0.11 0.56 portugal 0.55 0.55 1.00 0.56 0.56 1.00 0.52 0.52 1.00 0.72 0.73 0.99 finland 0.77 0.77 1.00 0.91 0.91 1.00 0.53 0.53 1.00 0.20 0.60 0.34 sweden 0.94 0.95 0.99 1.00 1.00 1.00 0.68 0.71 0.96 1.00 1.00 1.00 uk 0.92 0.92 1.00 0.79 0.79 1.00 0.62 0.62 0.99 1.00 1.00 1.00 average by year 0.64 0.67 0.93 0.65 0.69 0.93 0.62 0.63 0.98 0.57 0.64 0.87 year 1994 1995 1996 1997 country te pte se te pte se te pte se te pte se belgium 0.45 0.45 0.99 0.63 0.64 1.00 0.55 0.55 0.99 0.58 0.58 1.00 denmark 0.29 0.29 0.98 0.34 0.34 0.99 0.52 0.56 0.94 0.47 0.48 0.99 germany 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 0.71 0.80 0.89 ireland 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 greece 0.38 0.49 0.78 0.46 0.51 0.90 0.46 0.51 0.92 0.45 0.48 0.93 spain 0.51 0.72 0.71 0.51 0.60 0.86 0.51 0.76 0.68 0.54 0.88 0.61 france 0.49 0.49 1.00 0.52 0.52 1.00 0.63 0.63 1.00 0.67 0.67 1.00 italy 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 luxembourg 0.21 0.21 1.00 0.40 0.48 0.83 0.44 0.54 0.82 0.97 1.00 0.97 netherlands 0.81 0.82 0.98 0.78 0.78 1.00 0.92 0.96 0.95 1.00 1.00 1.00 austria 0.11 0.14 0.83 0.07 0.11 0.64 0.07 0.16 0.43 0.07 0.16 0.40 portugal 0.77 0.79 0.98 0.90 1.00 0.90 0.84 0.94 0.89 0.84 0.86 0.98 finland 0.28 0.62 0.45 0.46 0.72 0.64 0.65 0.88 0.74 0.75 1.00 0.75 sweden 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 uk 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 average by year 0.62 0.67 0.91 0.67 0.71 0.92 0.71 0.77 0.89 0.74 0.79 0.90 year 1998 1999 average by country country te pte se te pte se te pte se belgium 0.62 0.62 0.99 0.61 0.64 0.96 0.60 0.60 0.99 denmark 0.50 0.51 0.97 0.47 0.55 0.85 0.39 0.40 0.97 germany 1.00 1.00 1.00 0.84 0.88 0.95 0.90 0.93 0.97 ireland 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 greece 0.47 0.50 0.94 0.49 0.52 0.95 0.45 0.50 0.90 spain 0.52 0.74 0.70 0.39 0.95 0.41 0.42 0.70 0.61 france 0.68 0.68 1.00 0.74 0.75 1.00 0.58 0.58 1.00 italy 1.00 1.00 1.00 1.00 1.00 1.00 0.97 0.98 0.99 luxembourg 0.93 0.97 0.95 0.84 0.86 0.98 0.55 0.58 0.95 netherlands 0.98 1.00 0.98 0.80 0.83 0.97 0.86 0.87 0.98 austria 0.06 0.16 0.38 0.06 0.32 0.18 0.07 0.14 0.57 portugal 0.77 0.82 0.93 1.00 1.00 1.00 0.75 0.78 0.97 finland 0.77 1.00 0.77 0.92 1.00 0.92 0.62 0.80 0.76 sweden 1.00 1.00 1.00 0.69 0.83 0.82 0.93 0.95 0.98 uk 1.00 1.00 1.00 1.00 1.00 1.00 0.93 0.93 1.00 average by year 0.75 0.80 0.91 0.72 0.81 0.87 0.67 0.72 0.91 te: technical efficiency, pte: pure technical efficiency, se: scale efficiency alsaleh, et al.: an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on dea method international journal of energy economics and policy | vol 6 • issue 2 • 2016 303 appendix e: average of technical efficiency of bioenergy industry in eu region over 1990‑1999 year efficiency average of developing countries by year average of developed countries by year average of eu28 by year 1990 te 0.76 0.64 0.70 pte 0.81 0.67 0.74 se 0.95 0.93 0.94 1991 te 0.73 0.65 0.69 pte 0.77 0.69 0.73 se 0.96 0.93 0.94 1992 te 0.75 0.62 0.69 pte 0.81 0.63 0.72 se 0.94 0.98 0.96 1993 te 0.68 0.57 0.62 pte 0.79 0.64 0.71 se 0.87 0.87 0.87 1994 te 0.71 0.62 0.67 pte 0.82 0.67 0.74 se 0.89 0.91 0.90 1995 te 0.76 0.67 0.71 pte 0.85 0.71 0.78 se 0.90 0.92 0.91 1996 te 0.78 0.71 0.74 pte 0.87 0.77 0.82 se 0.90 0.89 0.90 1997 te 0.78 0.74 0.76 pte 0.87 0.79 0.83 se 0.90 0.90 0.90 1998 te 0.79 0.75 0.77 pte 0.88 0.80 0.84 se 0.91 0.91 0.91 1999 te 0.79 0.72 0.76 pte 0.88 0.81 0.84 se 0.90 0.87 0.88 average by group type te 0.75 0.67 0.71 pte 0.84 0.72 0.78 se 0.91 0.91 0.91 te: technical efficiency, pte: pure technical efficiency, se: scale efficiency a pp en di x f : d et ai ls o f p ar am et ri c an d no n‑ pa ra m et ri c m ea n te st s du ri ng 1 99 0‑ 19 99 y ea r g ro up su m m ar y of p ar am et ri c an d no npa ra m et ri c te st s p ar am et ri c te st n on -p ar am et ri c te st tte st m an n– w hi tn ey w ilc ox on te st k ru sk al -w al lis t e t p t e t se t t e z p t e z se z t e c hi -s qu ar e p t e c hi -s qu ar e se c hi -s qu ar e 19 90 d ev el op in g 0. 76 1 0. 84 4 0. 80 9 0. 56 8 0. 95 3 0. 92 2 16 .5 40 –1 .2 27 16 .9 20 –1 .4 69 14 .8 80 –0 .3 03 16 .5 40 1. 50 6 16 .9 20 2. 15 7 14 .8 80 0. 09 2 d ev el op ed 0. 63 7 0. 67 1 0. 93 0 12 .7 30 12 .4 00 14 .1 70 12 .7 30 12 .4 00 14 .1 70 19 91 d ev el op in g 0. 73 2 0. 62 3 0. 77 3 0. 96 8 0. 95 9 0. 42 4 15 .6 90 –0 .7 23 16 .1 20 –0 .9 84 14 .9 20 –0 .4 72 15 .6 90 0. 52 3 16 .1 20 0. 96 9 14 .9 20 0. 22 3 d ev el op ed 0. 65 3 0. 68 7 0. 93 1 13 .4 70 13 .1 00 14 .1 30 13 .4 70 13 .1 00 14 .1 30 19 92 d ev el op in g 0. 75 5 0. 98 6 0. 80 9 0. 89 4* * 0. 94 5 0. 06 7 16 .8 80 –1 .4 34 17 .5 80 –1 .8 67 * 15 .1 20 –0 .4 30 16 .8 80 2. 05 5 17 .5 80 3. 48 4* 15 .1 20 0. 18 5 d ev el op ed 0. 61 6 0. 62 7 0. 97 6 12 .4 30 11 .8 30 13 .9 70 12 .4 30 11 .8 30 13 .9 70 19 93 d ev el op in g 0. 67 6 0. 19 0 0. 79 2 0. 04 7 0. 86 7 0. 89 2 15 .8 10 –0 .7 87 16 .3 10 –1 .0 95 15 .1 90 –0 .4 28 15 .8 10 0. 61 9 16 .3 10 1. 20 0 15 .1 90 0. 18 3 d ev el op ed 0. 57 0 0. 63 7 0. 86 7 13 .3 70 12 .9 30 13 .9 00 13 .3 70 12 .9 30 13 .9 00 19 94 d ev el op in g 0. 71 5 0. 09 9 0. 81 7 0. 03 3 0. 88 7 0. 63 8 15 .8 80 –0 .8 43 16 .5 00 –1 .2 26 14 .3 80 –0 .0 73 15 .8 80 0. 71 1 16 .5 00 1. 50 3 14 .3 80 0. 00 5 d ev el op ed 0. 62 0 0. 66 8 0. 91 3 13 .3 00 12 .7 70 14 .6 00 13 .3 00 12 .7 70 14 .6 00 19 95 d ev el op in g 0. 76 0 0. 03 7 0. 85 5 0. 03 3 0. 90 2 0. 65 1 15 .4 60 –0 .5 81 16 .3 80 –1 .1 65 13 .6 50 –0 .5 28 15 .4 60 0. 33 7 16 .3 80 1. 35 7 13 .6 50 0. 27 9 d ev el op ed 0. 67 1 0. 71 3 0. 91 7 13 .6 70 12 .8 70 15 .2 30 13 .6 70 12 .8 70 15 .2 30 19 96 d ev el op in g 0. 78 2 0. 11 8 0. 87 3 0. 04 8 0. 90 5 0. 87 4 15 .3 10 –0 .4 88 16 .4 20 –1 .2 00 14 .7 70 –0 .1 65 15 .3 10 0. 23 8 16 .4 20 1. 44 0 14 .7 70 0. 02 7 d ev el op ed 0. 70 6 0. 76 6 0. 89 1 13 .8 00 12 .8 30 14 .2 70 13 .8 00 12 .8 30 14 .2 70 19 97 d ev el op in g 0. 77 9 0. 22 6 0. 87 2 0. 05 9 0. 90 4 0. 97 2 15 .0 40 –0 .3 26 15 .1 50 –0 .4 13 14 .8 50 –0 .2 22 15 .0 40 0. 10 7 15 .1 50 0. 17 0 14 .8 50 0. 04 9 d ev el op ed 0. 73 7 0. 79 4 0. 90 1 14 .0 30 13 .9 30 14 .2 00 14 .0 30 13 .9 30 14 .2 00 19 98 d ev el op in g 0. 79 4 0. 21 6 0. 88 3 0. 04 3 0. 90 8 0. 96 1 14 .8 80 –0 .2 33 15 .3 80 –0 .5 58 14 .9 20 –0 .2 64 14 .8 80 0. 05 4 15 .3 80 0. 31 2 14 .9 20 0. 07 0 d ev el op ed 0. 75 3 0. 88 0 0. 90 7 14 .1 70 13 .7 30 14 .1 30 14 .1 70 13 .7 30 14 .1 30 19 99 d ev el op in g 0. 78 9 0. 36 7 0. 87 9 0. 17 5 0. 90 4 0. 53 4 15 .3 80 –0 .5 36 15 .8 80 –0 .8 56 15 .5 00 –0 .2 64 15 .3 80 0. 28 8 15 .8 80 0. 73 2 15 .5 00 0. 37 6 d ev el op ed 0. 72 3 0. 80 9 0. 86 6 13 .7 30 13 .3 00 13 .6 30 13 .7 30 13 .3 00 13 .6 30 t e : t ec hn ic al e ffi ci en cy , p t e : p ur e te ch ni ca l e ffi ci en cy , s e : s ca le e ffi ci en cy , * ** , * * an d * in di ca te s ig ni fic an ce a t t he 1 % , 5 % , a nd 1 0% le ve ls re sp ec tiv el y alsaleh, et al.: an empirical analysis for technical efficiency of bioenergy industry in eu28 region based on dea method international journal of energy economics and policy | vol 6 • issue 2 • 2016304 appendix g: summary for developing and developed countries over 1990‑1999 test groups (1990-1999) parametric test non-parametric test individual test t-test mann–whitney [wilcoxon] test kruskall–wallis test hypothesis test t-test median developed and developing equality of populations test test statistics t (p>t) z (p>z) χ2 (p>χ2) mean t mean rank z mean rank χ2 te developing countries 0.754 0.371 15.687 –0.718 15.687 0.644 developed countries 0.669 13.470 13.470 pte developing countries 0.836 0.287** 16.264 –1.083* 16.264 1.332* developed countries 0.725 12.969 12.969 se developing countries 0.913 0.694 14.818 –0.350 14.181 0.149 developed countries 0.910 14.223 14.223 note: ***,** and * indicate significance at the 1%, 5%, and 10% levels respectively, te: technical efficiency, pte: pure technical efficiency, se: scale efficiency tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 1 • 2023454 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(1), 454-464. impact of economic growth, energy use and research and development expenditure on carbon emissions: an analysis of 29 oecd countries aisha sheikh1*, owais ibin hassan2 1department of economics, miranda house, university of delhi, new delhi 110016, india, 2department of economics, jamia millia islamia, okhla 110025, india. *email: aisha.sheikh@mirandahouse.ac.in received: 03 september 2022 accepted: 25 december 2022 doi: https://doi.org/10.32479/ijeep.13647 abstract this study attempts to investigate the impact of economic growth, energy use and research and development expenditure on carbon dioxide emissions for a panel of 29 organisation for economic development and cooperation (oecd) countries over 1995-2019. we employ two sets of econometric techniques.the first set of estimation techniques assumes cross sectional independence in the panel (also known as the first generation tests). the first generation tests include the panel unit root testslevin et al. (llc), im et al. (ips) adf-fisher and pp-fisher unit root tests, pedroni (1999) and kao cointegration tests and the fully modified ordinary least square (fmols) for computing output elasticities. the second set of econometric tests are performed after checking for cross sectional dependence using the second generation tests. these include pesaran cd test, breusch pagan cd test, to establish cross sectional dependence followed by cross-sectional augmented im-pesaran-shin (cips) panel unit root test developed by pesaran (2007) to test for panel stationarity followed by the error correction based panel cointegration test proposed by westerlund and edgerton (2007) with bootstrap. augmented mean group (amg) is performed to estimate output elasticities while dumitrescu-hurlin (dh) panel causality tests is done to ascertain causality between variables. we obtain the same results for the effect of gdp and energy use on carbon emissions from the two strategies but conflicting results for the impact of research and development spending on carbon emissions, although there is evidence of stronger cointegration under the first generation tests. based on findings from the two approaches, we conclude that with a rise in gdp, carbon emissions fall in oecd but increase with a rise in energy use. aggregate research and development expenditure has a positive effect on carbon emissions under cross sectional independence but a neutral effect when estimated using cross-sectional dependence tests giving inconclusive results. keywords: carbon emissions, cross-sectional dependence, oecd, energy, gdp, westerlund, augmented mean group jel classifications: q430, o13, p28, q540 1. introduction there has never been a collective human endeavour more ambitious than stabilising the climate (economist october 30th, 2021). the environmental outcomes of a warmer earth are too well documented to need another review. there is no doubt that anthropogenic activities have contributed significantly to this situation, primarily through the burning of fossil fuels among other factors.the recently concluded 26th conference of parties (cop26) at glasgow may not have been able to garner the expected commitments and outcomes yet it remains the only multilateral framework for negotiating global climate policy and for keeping the quest alive. the resolve and capabilities of nations and regions to decarbonise are asymmetric. the organisation for economic co-operation and development (oecd) block is relatively more politically committed and proactive in the common quest for attaining carbon neutrality. nevertheless, the global trajectory of climate action is short of warranted action to achieve the paris temperature goals. this journal is licensed under a creative commons attribution 4.0 international license sheikh and hassan: impact of economic growth, energy use and research and development expenditure on carbon emissions: an analysis of 29 oecd countries international journal of energy economics and policy | vol 13 • issue 1 • 2023 455 a vast body of income-pollution literature addresses this issue, with carbon dioxide being the most studied pollutant. the determinants of carbon dioxide emission have been widely investigated for different regions using a variety of functional forms and econometric techniques. as a block of countries, oecd is the second largest carbon emitter in the world, first being asia (ritchie and roser, 2020). however recent trends indicate that greenhouse gas emissions (ghg) per capita of gdp, from oecd countries are decreasing (international energy agency, 2018, oecd climate report 2015). the energy sector is the leading source of greenhouse gas emissions globally (world energy outlook, 2018). a strand of literature identifies energy and income (gross domestic product) as the principal sources of carbon emissions (zhang and gao (2016); dogan and turkekul (2016); javid and sharif (2016); farhani and ozturk (2015); al-mulali et al. (2015); seker et al. (2015); tang and tan (2015); dogan et al. (2015); shahbaz et al. (2014); lean and smyth (2010, kasman and duman (2015); (soytas et al. (2007). global energy demand has been consistently rising and increased by nearly 2% in 2017. this fastest rise in the decade is attributable to changes in consumer behaviour and economic prosperity (world energy outlook, 2018). 81% of the global energy needs are met by fossil energy sources, the primary source of carbon dioxide emissions. the relationship between gdp and environmental degradation has been explained by grossman and kruegner (1991) by scale, composition and technique effects. scale effect is the situation where growth in output leads to greater pollution emissions because of increased use of energy and resources. the composition effect is structural in nature implying that as the economy advances, the cleaner service sector has a greater share in the output. the third is the technique effect which means that with economic advancement cleaner technologies replace pollution intensive technologies that environmental stress.this phenomenon of an initial rise and subsequent fall in pollution with economic growth can be depicted as an inverted u-shaped curve also called the environmental kuznets curve (ekc) (grossman and kruegner 1991; 1995). the theoretical perspective on the effect of aggregate research and development spending on carbon emissions postulates that research and development spending tends to mitigate carbon emissions expectedly through the development and dissemination of energy saving technologies. however empirical evidence does not uphold this view and produces mixed results petrovic and lobanov (2019) cite the discovery of the higgs boson, which involved large scale investments in particle accelerators in the european organization for nuclear research. the discovery however did not lead to a reduction in carbon emission. the investment was colossal and the accelerator was energy intensive. in all likelihood, it increased carbon emissions from greater fossil fuel consumption. research and development spending also comprises research outlay on medical, pharmaceutical and other areas which don’t have a direct bearing on increasing energy efficient research output. overall the impact of research and development spending on carbon emissions can range from positive, negative to neutral and the empirical experience of different countries vary (churchill et al., 2019). we articulate a model that incorporates energy use and research and development spending as additional explanatory variables besides gdp. our motivation is to analyse the behaviour of carbon emissions with an increase in gdp and research and development spending for the oecd countries post 1995. besides gdp, our second variable of interest is aggregate research spending (as a percentage of gdp) as empirical evidence about the effect of r&d spending is, at best, ambiguous in available literature.energy use is the leading source of carbon emissions, we have included it in our model to avoid potential omitted variable bias. the income-pollution literature prior to 2010 relied mostly on first-generation tests which assume cross sectional independence. an emerging section of literature addressed cross-sectional dependence (csd) in panel data. csd is a correlation that arises from common shocks with heterogeneous impacts across different countries, like the oil shock of 1970’s and the global financial crisis of 2007. local spillover effects between regions and economies, spatial effects and interactions among economies are other reasons for cross-correlated errors (atasoy, 2017). this paper investigates the role of gross domestic product, energy consumption and research and development spending (as a percentage of gross domestic product) on carbon dioxide emissions for a group of 29 oecd countries over the span of 1995-2019 using estimation techniques that assume cross sectional independence and a second set of techniques designed for accommodating cross sectional dependence.the econometric techniques employed an their sequence is discussed in detail in the methodology section. the rest of the paper is organised as follows. section two consists of a review of literature. the data and methodology is described in section 3. estimation results are discussed in section 4 and the conclusion is presented in section 5. 2. literature review the determinants of carbon emissions in general and for the oecd block in particular (for the post 90’s period) have been widely investigated. however findings are sensitive to econometric techniques, functional forms, choice of regressors and even the time period studied. broadly, trade, financial development, energy use, technology and urbanization have been studied as explanatory variables in the oecd-carbonisation literature. the stirpat model (stochastic impacts by regression on population, affluence and technology) posits that population, income and technology are the principal sources of environmental degradation. (shafiei and salim 2014; poumayvong and kaneko, 2010; zhang and lin, 2012; liddle, 2011; wang et al., 2012; liddle and lung 2010; lin et al., 2009; york et al.) and the ekc framework (dogan and seker, 2016; ahmad et al., 2017; zhang et al., 2014) have been tested widely to analyse the relationship between carbon emissions and factors causing them. hamilton and turton (2002) analysed the causes of greenhouse gas emissions over 1982-1997 using the decomposition formula.the sheikh and hassan: impact of economic growth, energy use and research and development expenditure on carbon emissions: an analysis of 29 oecd countries international journal of energy economics and policy | vol 13 • issue 1 • 2023456 study concludes that growth in emissions are principally driven by increase in population and gdp per capita. chiu and chang (2009) used a panel threshold regression model and confirmed a significant and positive relationship between real gdp and carbon dioxide emissions. menz and welsch (2012) analysed the data from 1960 to 2005 using the augmented version of standard macroeconomic emissions regressions for a panel of 26 oecd countries. their findings indicate that a shift in the composition and age of the population positively affected carbon dioxide emissions. energy consumption has been widely treated as an explanatory variable in the growth-carbonisation literature, since it is a principal determinant of carbon dioxide emissions. (say and yucel (2006); apergis and payne, (2009); soytas et al. (2007); ang, (2007); halicoglu, (2009); atici, (2009); acaravci and ozturk (2010); lean and smyth, (2010); pao and tsai, (2011); pao et al. (2011); hossain (2011); jalil and feridun (2011); nasir and rehman (2011); park and hong (2013); alam et al. (2012); lau et al. (2014); omri (2013); farhani et al. (2014); shahbaz (2013, 2014); kasman and duman (2015); yavuz (2014); dogan (2015); serker (2015); baek (2015); shahbaz et al. (2015); al-mulali et al. (2015); tang and tan (2015); farhani and ozturk (2015); dogan and turkekul (2016); javed and sharif (2016) and zhang and gao (2016). another section of literature has explored the relationship between carbon dioxide and it’s determinants for the oecd block . zaidi et al. (2021) examine the dynamic linkages between carbon emissions and financial inclusion for 21 oecd countries over 2004-2017. corruption, infrastructure and economic growth are also used as control variables. the study finds that financial inclusion negatively impacts carbon emissions. iqbal et al. (2021) investigate the role of carbon neutrality, scal decentralization, ecoinnovation for achieving carbon neutrality target for 37 oecd economies from 1970 to 2019. the study applies second generation tests and the augmented mean group (amg) to determine the long run dynamic equilibrium. findings show that export diversification, scale, gdp and scale decentralization positively affect carbon emissions. environmentally friendly technological improvements and renewable energy improve environmental outcomes. the study recommends that oecd partner countries emphasize on growing renewable energy and expand environment friendly technological innovation. ahmed (2020) explored if environmental regulations have the potential to mobilize technological innovation that can lead to carbon abatement. the paper empirically investigates the role of environmental rules in affecting environmentally compatible technological innovations, carbon emissions exports, imports and gdp for a sample of 20 oecd countries. findings reveal that stricter environmental regulations in combination with environmentally compatible technological innovations are effective in carbon abatement. international trade does not have a meaningful impact on green innovation though in the short run imports are found to be emission intensive while exports are emission reducing. the paper suggests that oecd countries should reconsider trade related environmental regulations. bashir et al. (2020) explore the contribution of export diversification (using the indicators of export diversification, extensive margin and intensive margin) for energy intensity and carbon intensity in 29 oecd countries over 1995-2015 by using alternative panel data estimations, sequential estimations, panel quantile regression, gmm and difference gmm. the paper concludes that export diversification helps in reducing energy intensity. pan x, et al. (2019) use the symbolic regression method to find the determinants of carbon dioxide emissions intensity using six regressorspopulation, gdp, foreign direct investment, industrialization, technological innovation and urbanization. for 34 oecd countries during 1995-2014. although factors influencing carbon dioxide emissions are different for different countries, the most common influencer is gross domestic product. technological innovation is found to be the third important factor in countries with low population density, a low amount of average fdi but high rate of urbanization. paramati et al (2021) investigated the role of financial deepening, foreign direct investment (fdi), green technology, trade openness and per capita income on carbon dioxide emissions for a panel of 25 oecd countries from 1991 to 2016. green technology is represented by the use of energy efficient technology (used in the process of production and consumption). findings reveal that fdi and green technology are major factors that help in reducing carbon dioxide emissions, while per capita income and financial deepening increase carbon dioxide emissions. petrovic and lobanov (2019) analyze the effect of research and development expenditure in 16 oecd countries during 19812014. the other regressors included in the analysis are gdp, foreign trade and gross fixed capital formation. the study applies parametric techniques for testing the cross sectional dependence of the dataset. common correlated effects mean group (ccemg) and augmented mean group (amg) are used to calculate the coefficient elasticities. estimates of the long run regression model show that the long run average effect of research and development expenditure on carbon dioxide emissions is negative. however, the short run nonparametric time varying coefficient panel data show that the effect of research and development expenditure on carbon dioxide emissions is insignificant over years. in cases where it is significant it can be either negative or positive. such ambiguous findings imply that country wise empirical estimates should be obtained for purposeful policy making. ganda (2019) analyzed technology investments and innovation influenced carbon emissions in select oecd countries using the generalized method of moments (gmm’s). the indicators for innovation and technology investment are renewable energy consumption, research and development expenditure, number of researchers and the number of triadic patent families. results of the study are as follows: research and development spending sheikh and hassan: impact of economic growth, energy use and research and development expenditure on carbon emissions: an analysis of 29 oecd countries international journal of energy economics and policy | vol 13 • issue 1 • 2023 457 negatively affects carbon emissions whereas the number of triadic patent families, number of researchers and human capital positively affects carbon emissions. hashmi and alam (2019) studied the effect of environmental regulation and innovation on carbon abatement over the span of 1999-2014 using the modified stirpart framework.the augmented model articulated by hashmi and alam incorporates regulation as an additional regressor. the augmented model is tested using a generalized method of moments, panel fixed effects and random effects using driscoll-kraay corrected robust standard errors performed under condition of cross-sectional dependence, time and panel fixed effects. findings of the analyses reveal that growth in environmentally friendly patents as well as enlarging the environmental tax facilitates carbon abatement. the study emphasises the necessity for the implementation of instruments like carbon pricing and patents. gozgor (2017) analyzed the impact of trade openness, per capita energy consumption and per capita income on the level of per capita carbon emissions in a panel dataset of 35 oecd countries over 1960-2013. the paper confirms the existence of a conventional ekc (inverted u shaped) between income and carbon dioxide emissions. the study supports the extensively reported finding that energy consumption increases carbon emissions while both trade indices have a mitigating effect on carbon emissions. dogan and serker (2016) examined the effect of trade openness, financial development and energy consumption and real income on carbon emissions for oecd using homogenous panel econometric techniques within the ekc framework. main findings suggest that energy consumption contributes to carbon emissions and confirms the existence of an ekc for the sample.trade openness and financial development reduce carbon emissions. saboori et al. (2014) studied the long run association between gdp, transport sector energy consumption and co2 emissions in oecd countries over 1960-2008 by applying fully modified ordinary least squares (fmols). the study reports a positive, significant and bi-directional relationship between co2 emissions, road sector energy consumption and gdp. the paper also uses the generalized impulse response approach to detect the response of each variable to shocks in the values of other variables. results show that the initial response of co2 emissions is shorter to economic growth compared to road transport energy consumption. the authors advocate a transition to renewable energy. wang et al. (2015) explored the nature of the relationship between urbanization and carbon emissions using the stirpat framework using a semi-parametric panel fixed effects regression estimator. the paper attempts to check for the presence of an urbanizationcarbon emissions ekc. results detect a more pronounced conventional inverted u shaped ekc using the semi-parametric panel fixed effects regression estimator. jebli et al. (2016) examine a panel of 25 oecd countries by employing panel cointegration techniques for the period 1980-2010 to infer that increase in the volume of trade reduces co2 emissions. this paper modestly contributes to the oecd-carbonisation literature by examining the impact of research and development spending (research and development spending as a percentage of gdp), energy use and gross domestic product on carbon emissions. while these variables have been studied formerly as determinants of carbon emissions in oecd, this functional form has not been examined previously. secondly, to the best of our knowledge this is the first study to make this analysis in the context of oecd using two estimation strategies, with and without the assumption of cross dependence and heterogeneity. jardon et al. (2017) performed a similar comparative analysis using cross sectional independent and cross sectional dependent techniques for countries of latin america and caribbean.finally, we use the most updated dataset spanning from 1995 to 2019. 3. data and methodology 3.1. data annual frequency data from 1995 to 2019 for 29 oecd countries is used in this study. the countries included in the panel are: australia, austria, belgium, canada, czech republic, denmark, estonia, finland, france, germany, greece, hungary, iceland, ireland, italy, japan, korea, latvia, lithuania, netherlands, new zealand, norway, portugal, slovak republic, sweden, spain, turkey, united kingdom, united states. the data for carbon dioxide emissions, gross domestic product, research and development spending (r&d expenditure) and energy use is taken from world development indicators (wdi), the database of world bank (2021). all variables have been taken at their natural logarithm form. 3.2. definition of the variables variables definition gross domestic product (gdp) gdp is defined as the sum of gross value added generated in an economy calculated at factor cost, without adjusting for depreciation or environmental degradation r&d expenditure gross domestic expenditure on research and development is expressed as a percent of gdp. it includes expenditure on basic research, experimental development and applied research by government, businesses, higher education and private non-profit on both current and capital account carbon dioxide emissions carbon dioxide emissions emanate for the production of cement and burning of fossil fuels (solid, liquid and gas fuels) energy use energy use refers to the use of primary energy before conversion to end use fuels. this includes the indigenous production, net exports, changes in stock and fuel supplied to ships and aircrafts for international travel source: world development ındicators 3.3. the model to study the impact of income, energy use and r&d expenditure on carbon emissions, we articulate the following model: sheikh and hassan: impact of economic growth, energy use and research and development expenditure on carbon emissions: an analysis of 29 oecd countries international journal of energy economics and policy | vol 13 • issue 1 • 2023458 lnco eit lng lneu lnrd it= + + + +β β β β0 1 3 (1) where lnco is carbon emissions, the dependent variable. the independent variables are in the above equation, the dependent variable is carbon emissions (lnco). the independent variables are lng (gdp), lneu (energy use) and lnrd (r&d expenditure). the subscripts i and t denote country and year respectively, β0 is the intercept term and eit denotes the error term. 3.4. methodology this paper uses two parallel estimation strategies, commonly known as the first and second generation tests. the first generation estimation method consists of the following steps: (i) determining the stationarity properties of the series using conventional panel unit root tests (ii) performing the pedroni and kao cointegration tests (iii) computing the coefficient elasticities using fmols. the second generation tests are performed in the following sequence: (i) the pesaran (2007) cross sectional dependence test (ii) the augmented cross sectional dependence panel unit root test to examine the stationarity properties of the variables (iii) the westerlund (2007) cointegration test (iv) amg is employed to compute the elasticities of the coefficients. 3.5. panel unit root the first part of the estimation strategy entails the panel unit root tests to check for stationarity properties under the assumption of cross sectional independence. the procedure includes performing the levin et al. (llc), im et al. (ips) adf-fisher and pp-fisher unit root tests. to evaluate the stationarity properties of the series under the assumption of cross-sectional independence the following panel unit root test is conducted: ∆ = + + +∈ − −− = ∆∑y p yit it i t j ni ij iti i yi t j ϕ ϕβ , ,* ,1 1 1 (2) (balsalobre-lorente et al. 2019). 3.6. panel cointegration test after establishing the stationarity properties of the variables and rejecting the null hypothesis of unit root, the next step is to determine if a long run relationship exists between the variables of interest by performing the appropriate panel cointegration tests. the pedroni (1999) and kao cointegration tests extend the englegranger framework to test for panel cointegration. the pedroni cointegration test given below accommodates heterogeneous intercepts and trend coefficients within crosssections. y x x xit it it i it i it mi m it it= + + + …… + ++α δ β β β ε1 1 2 2, , ,. where t = 1.,t; i = 1.,n, m = 1.,m, where y and x are expectedly integrated of i(i). the parameters αit and δit indicates individual and trend effects. the objective is to compute the residuals from equation 2 to ascertain whether the residuals are i(i) according to the auxiliary regression. ε ρ εit i i t itu= +−, 1 ε ρ ϕε εit i i t it j p ij i t j itu v= + + +− = ∆ −∑, ,1 1 pedroni (1999) proposes several methodologies to construct statistics for testing the null hypothesis of no cointegration (ρ i = 1). two alternate hypothesis in this test are: (a) the within-dimension test or panel statistic test which is also the homogenous alternative (pi = p) < 1for all i. (b) the between dimension or group statistic is the heterogeneous alternative, pi < 1 for all. the pedroni cointegration test includes seven different statistics, four within-dimension of the panel and three along between dimensions of the panel. all test statistics are normalized to be distributed under n (0,1). the kao cointegration test is based on the same methodology. however in case of the kao test, the cross sectional intercepts and homogeneous coefficients are specified on the first stage regressors. following os the bivariate case in kao: y ai t ix t it, ,= + +1 1 1β ε y y ui t t i t, , ,= +−1 1 x xi t t i t, , ,= +−1 1 ε where t = 1., t; i = 1., n. the first stage regression is done lacking the a1 to be heterogeneous, βi to be homogenous through cross-sections, and setting all the trend coefficients ρi to zero. (balsalobre-lorente et al., 2019). 3.7. fully modified ordinary least square (fmols) the fmols technique is applied as it handles endogeneity issues. fmols is a nonparametric approach through which optimal results can be obtained from cointegrating regression. it handles serial correlation and endogeneity due to the presence of cointegrating relationships. the following equation is articulated: w t t i ni t i i x i ti t, � ,, , , , .. , ,, ,= + + ∀ = … = …α β ε 1 2 1 allowing for wi and xi,t are cointegrated with slopes βi where w t t ii t i ix k ki ki i k x i ti t i t k, , ,, , , , , , , , ,= + + + ∀ = … = … =− ∆∑ −α β γ ε 1 2 1 2 ,,n the assumption is: i,t i,t i,t( )ˆ xξ ρε ∆= . and ωi,t = lim e (σ t i=1ξi,t) (σti=1ξi,t)] the long covariance is divided into ωi = ωi 0 + γ i+ γ i ’, where ωi 0 is the simultaneous covariance and + ti ’ is the weighted sum of autocovariance. fmols is obtained as follows: , , , 1 1 1 1ˆ * ( ) ( ) *β = = =        = − − −        ∑ ∑ ∑ n t t fmols i t i i t i i t yi i i i x x x x w t n sheikh and hassan: impact of economic growth, energy use and research and development expenditure on carbon emissions: an analysis of 29 oecd countries international journal of energy economics and policy | vol 13 • issue 1 • 2023 459 where, ( ) 0 , , , 2,1, 2,1, 2,2, 2,2, ˆ ˆˆˆ ˆ ˆ ˆˆ 2,1, * * 2, 2, 02,1, 02, 2ˆ , γ ω = − ∆ = γ + ω ω ω − γ + ω ω i t i t i i t i i i i i i w w w x and i i i (balsalobre-lorente et al., 2019). 3.8. cross-sectional dependence test panel datasets tend to have the disadvantage of cross-sectional dependence which can lead to inconsistent estimates (zhao et al., 2020). cross-sectional dependence in panel data sets implies the existence of a correlation between individual units. global economic integration is likely to make countries considerably interdependent. it can also arise from a common exogenous shock suffered by all countries with spillover effects between countries (mania, 2019). as a prerequisite to choosing the appropriate econometric techniques, a preliminary step is to check for cross-sectional dependence in the panel dataset. breusch-pagan lagrange multiplier (lm) test, pesaran scaled lm test and pesaran crosssectional dependence (cd) test are the most widely applied cross sectional dependence tests. this paper employs all the aforementioned cross-sectional dependence tests. the pesaran cd test developed by pesaran (2004) can be expressed as follows: cd i i tpesaran k jpk j nj k i j k i ( ) , , ~ ( , )2004 01 11 12 1 = −( ) = += + − ∑∑ (2) 3.9. panel unit root test (cross-sectional dependent) in the second part of the analysis, we perform the panel unit root tests for cross sectional dependence. the pesaran (2007) cross-sectional augmented im-pesaran-shin (cips) panel unit root test developed by pesaran (2007) is performed to test for panel stationarity. this technique is known to produce rather consistent and reliable stationarity properties by accommodating cross-sectional dependence(wang et al., 2020).the null hypothesis in cips is non-stationarity. the test statistic for pesaran cips is given as follows: ∆ = + + + ∆ +− − = −∑y y y yit i i i t i t i p i t itγ α β γ ε, 1 1 0 1 1 (3) in equation 3 yt-1 and ∆yt-1 are the cross sectional averages of lagged levels and first differences of respective series. the cips test statistic is derived from the cross sectional augmented dickey fuller (cadf) as follows: cips n cadf i n i= = ∑ 1 1 (4) in equation 4, cadfi is the t-statistic in the cadf regressions. 3.10. cross-sectional dependent panel cointegration test the panel unit root tests are followed by error correction based panel cointegration test proposed by westerlund and edgerton (2007) with bootstrap to check for the presence of a long run cointegrating relationship among carbon emissions, gross domestic product, technology and energy use. the westerlund and edgerton (2007) cointegration test accounts for cross-sectional dependence (ali et al., 2020) and includes four statistics: two group statistics (ga and gt) and two-panel statistics (pa and pt). this technique effectively predicts the cointegrating properties in a crosssectionally dependent homogenous panel dataset and computes four error-correction-based panel non cointegration test statistics under the null hypothesis of no cointegrating relationship (khan et al., 2021). the test equation for the four statistics are expressed below: g n a set i n = − − ∑1 1 ( )α (5) g n ta t i n = − − ∑1 1 1α( ) (6) p a se aa = ( ) (7) p ta a= � (8) 3.11. augmented mean group (amg) once the presence of a cointegration relationship among the variables is confirmed we proceed to estimate the long run coefficients using augmented mean group (amg). eberhardt and bond (2009) formulated the amg estimator which takes both cross-sectional dependence and heterogeneity into consideration. y u u fit i x it it it i i i it= + = + +β α λ ε, , , (9) x f fnmtvmit mi migration imi mt nmi mit= + + +…+π δ ρ ρ ' 1 (10) f f and g gt t t t t t= + = +− −ϕ ε ω ε1 1� � � � � � � � (11) xit is a vector of covariates and ft and gt denote observed common factors. λi indicates unit-specific factor loadings. the amg estimator was developed by eberhardt and bond (2009). amg stage i y b x c eit it t t tdt it− ( )∆ = ∆ + + = ∑ 2 (12) amg stage i y a bx c eit i it it di t it− ( )∆ = + + ++� � µ (13) the heterogeneous-based approach included in the second set of analyses done by this study has certain advantages. it is more impeller than de-facto regressions. it generates more robust results in the presence of different stationary regressors and does sheikh and hassan: impact of economic growth, energy use and research and development expenditure on carbon emissions: an analysis of 29 oecd countries international journal of energy economics and policy | vol 13 • issue 1 • 2023460 not preclude the possibility of cointegrating modeling and takes a fuller account of all-time variant information (liddle, 2014). 4. estimation results 4.1. oecd table 1 shows the results from the llc, ips, adf-fisher, and pp-fisher panel unit root tests. lngdp is found stationary at level according to the llc and pp-fisher unit root tests (at intercept). lngdp, lnco, lnrd, lneu are stationary at their first difference according to all four-panel unit root tests. it can be concluded that the series lngdp, lnco, lnrd, lneu are integrated of order (1). once we have determined that the variables are i(i), next we ascertain whether a long run relationship exists between the variables by applying the cointegration tests. results of the pedroni cointegration test (1999, 2004) are reported in tables 2 and 3 reports the results of the kao (1999) cointegration tests. according to the pedroni test, the null hypothesis of no cointegration is rejected by two out of the four panel statistics and two out of the four group statistics (taken at intercept). the kao test (reported in table 3) strongly rejects the null of no integration. in general, considering the results of both cointegration tests we can infer that the variables in question lngdp, lnco, lneu, lnrd exhibit a long-run relationship. the long run elasticities are estimated by employing pedroni’s (2000, 2001) fully modified ordinary least square (fmols). the fmols results are presented in table 4. the coefficients of all three variables are found to be statistically significant. the coefficient for lngdp is negative and significant (−0.854) while the coefficients for lneu (0.479) and lnrd (0.768) are positive and significant. this can be interpreted as follows: a 1% increase in gdp reduces the carbon dioxide emissions by 0.85% approximately, while a 1% increase in energy use will increase carbon dioxide emissions by 0.47% approximately, and a 1% increase in lnrd will increase carbon dioxide emissions by 0.76%. 4.2. second generation tests table 5 and show the findings of the cross-sectional dependence tests. cross sectional dependence in the panel data is established by all three cross-sectional dependence tests-breusch pagan lm, pesaran scaled lm, and the pesaran cd test.the null hypothesis of cross sectional independence is rejected by all three tests. table 6 contains the findings of the pesaran (2007) cross-sectional dependence test, providing more evidence of strong rejection of the null hypothesis of no cointegration. it can be inferred that the panel dataset of 29 oecd countries employed in this study exhibits cross-sectional dependence or homogeneity. after establishing the existence of cross-sectional dependence of the panel of 29 oecd countries used in this study, we proceed to perform a sequence of econometric tests designed for accommodating cross-sectional dependence. table 7 presents the pesaran (2007) cips panel unit root test results which account for cross-sectional dependence. lnco, lnrd, and lneu contain a unit root at the level when considered with and without trend. the variables lnco, lnrd, and lneu are found stationary at their first difference whereas lngdp is found stationary at level, both at the “with” and “ no trend” options. since the variables are integrated of order (i) the possibility of obtaining spurious regressions is eliminated. table 3: kao residual cointegration test model t-statistic lnco {lngdp, lneu, rd} 4.624 (0.000) parentheses shows probability values. source: authors` own calculations table 1: panel unit roots test variable level first difference llc ips adf-fisher pp-fisher llc ips adf-fisher pp-fisher lngdp −4.409 (0.000) 0.0063 (0.502) 55.280 (0.577) 181.72 (0.000) 6.9215 (1.000) −9.2263 (0.000) 195.511 (0.000) 751.47 (0.000) lnco 1.0030 (0.842) 4.2369 (1.000) 28.548 (0.999) 27.507 (0.999) −7.382 (0.000) −10.959 (0.000) 238.13 (0.000) 549.05 (0.000) lnrd −3.8165 (0.000) 0.285 (0.612) 59.910 (0.406) 52.993 (0.661) −7.3020 (0.000) −9.839 (0.000) 208.66 (0.000) 387.10 (0.000) lneu 0.11261 (0.544) 2.426 (0.992) 33.730 (0.995) 55.610 (0.564) −9.578 (0.000) −11.993 (0.000) 255.24 (0.000) 569.60 (0.000) parentheses shows p-value. source: authors` own calculations table 2: pedroni cointegration test results lnco {lngdp, lneu, lnrd} test statistic p-value panel v 25.258 0.000 pane lrho −3.897 0.000 panel pp −0.278 0.390 panel adf −1.610 0.053 group rho 1.080 0.861 group pp −4.687 0.000 group adf −3.585 0.000 above computations are done at intercept. source: authors` own calculations table 4: fmols estimation results model/variables lnco {lngdp, lneu, lnrd} lngdp −0.854 (0.004) lneu 0.4798 (0.000) lnrd 0.768 (0.000) parentheses shows probability values. source: authors` own calculations sheikh and hassan: impact of economic growth, energy use and research and development expenditure on carbon emissions: an analysis of 29 oecd countries international journal of energy economics and policy | vol 13 • issue 1 • 2023 461 having established that the variables are i(i) the next step is to apply the westerlund (2007) cointegration test to check for the existence of cointegration among the variables. westerlund and edgerton (2007) cointegration results are given in table 8. the group statistics strongly reject the null hypothesis of no cointegration for the model lnc {lngdp, lneu, lnrd}. we infer that a long run association exists between the variables lnc, lngdp, lneu, lnrd. in the next step, we compute the long-run coefficients of the independent variables that affect carbon dioxide emissions. table 9 shows the amg estimation results. the amg estimators show that the coefficient for lngdp is negative and significant (−0.224), the coefficient for lneu is positive and significant (0.143) while that of lnrd is negative and insignificant. these results can be interpreted as follows: a 1% increase in gdp will reduce carbon dioxide emissions by 0.224%, a 1% increase in energy use will increase carbon dioxide emissions by 0.143%. our findings regarding lngdp and lneu are consistent with the results obtained from fmols, both sets of tests suggest the same results that an increase in gdp will reduce carbon emissions. an increase in energy use will increase carbon emissions for the sample of oecd countries over 1995-2019. however, it’s worth noting that once we account for the issues of cross-sectional dependence and homogeneity (using the amg estimator) the elasticities obtained for income and energy use are smaller than the elasticities obtained through fmols. the statistically significant negative coefficient of the gdp can be explained by the technique and composite effect. technique and composite effect is the phenomenon that sets it at later stages of economic growth (after attaining a certain threshold level of “income”) when a greater share in the gdp belongs to the cleaner service sector and pollution intensity of manufacturing reduces owing to cleaner and more sophisticated technologies. our findings regarding the impact of gdp on carbon emissions is consistent with the findings of the reports of the international energy agency 2018 and oecd 2015. the positive and statistically significant coefficient for energy consumption is consistent with the findings of say and yucel (2006); apergis and payne (2009); soytas et al., (2007); ang (2007); atici (2009); acaravci and ozturk (2010); lean and smyth (2010); pao and tsai (2011); pao et al. (2011); hossain (2011); jalil and feridun (2011); nasir and rehman (2011); park and hong (2013); alam et al. (2012); lau et al. (2014); omri (2013); farhani et al. (2014); shahbaz (2013, 2014); kasman and duman (2015); yavuz (2014); dogan (2015); serker (2015); shahbaz et al. (2015); tang and tan (2015); farhani and ozturk (2015); dogan and turkekul (2016); javed and sharif (2016) and zhang and gao (2016). a probable reason for the positive role of energy use in increasing co2 emissions is the heavy dependence of the oecd region on fossil fuel energy sources. the share of fossil fuel sources in total energy sources for the oecd were 91% in 2000 and reduced marginally to 87% in 2015 (iea 2018). however, we find conflicting results for the impact of research and development spending on carbon emissions. the amg results suggest that research and development spending is statistically insignificant with a negative sign in sharp contrast with the results produced by fmols which suggests that an increase in r&d spending increases carbon emissions. petrovic and lobanov (2019) report similar mixed results about the impact of research and development expenditure on carbon emissions.the results that research and development spending is statistically insignificant when analyzed as a determinant of carbon emissions (also coined as the “neutrality hypothesis”) supports the findings of garronen and grilli (2010); cheng et al. (2017); amri (2018). table 5: results of cross-sectional dependence test test statistics p-value breusch pagan lm 4936.34 0.0000 pesaran scaled lm 158.984 0.0000 pesaran cd 47.914 0.0000 source: authors` own calculations table 6: results of cross-sectional dependence test: pesaran (2007) variables statistics p-value lnco 4694.255 0.000 lngdp 258.117 0.000 lneu 4063.529 0.000 lnrd 3960.501 0.000 source: authors own calculations table 7: results of pesaran unit root test variables i (0) i (i) no trend with trend no trend with trend lnco −1.860 −2.325 −4.405* −4.565* lngdp −3.003* −3.821* −5.207* −5.272* lnrd −1.808 −1.759 −3.947* −4.123* lneu −0.916 −2.250 −4.091* −4.053* *1% significance level, **5% significance level, ***10% significance level. source: authors` own calculations table 8: results of westerlund cointegration test for the model lnco {lngdp, lneu, lnrd} value gt ga pt pa z-value −0.796 2.359 1.085 1.095 p-value 0.213 0.991 0.061 0.863 robust p-value 0.000 0.000 0.600 0.200 parentheses shows probability values. source: authors` own calculations table 9: amg estimation results lnc {lngdp, lneu, lnrd} variables coefficient lngdp −0.224 0.006 lneu 0.143 0.000 lnrd −0.073 0.363 parentheses shows probability values. source: authors` own calculations sheikh and hassan: impact of economic growth, energy use and research and development expenditure on carbon emissions: an analysis of 29 oecd countries international journal of energy economics and policy | vol 13 • issue 1 • 2023462 while the findings from fmols that indicate that research and development spending increases co2 emissions is consistent with the conclusions of danish and baloch 2018, park et al. 2018; jardon et al. (2017) also report conflicting findings from estimation techniques with and without the assumption of crosssectional dependence. table 10 reports the results of dh panel causality tests. results show a unidirectional causal relationship between gdp and co2 suggesting that an increase in income causes carbon dioxide emissions. (pan et al., 2019). a unidirectional causal relationship is also confirmed between energy use and carbon dioxide emissions indicating that increased energy use causes carbon dioxide emissions. 5. conclusion this paper examines the impact of income, technology, and energy use on carbon dioxide emissions for 29 oecd countries over the span of 1995-2019 using two parallel estimation strategies. the first, under the assumption of cross-sectional independence, is more commonly known in the literature as the first generation tests, and the second under the assumption of cross-sectional dependence, also known as the second generation tests. the first strategy entails-the panel unit root tests (adf-fisher, ppfisher, llc, and ips), pedroni and kao panel cointegration tests, pedroni’s fmols for calculating elasticity of coefficients. under the second strategy, we perform the pesaran cross-sectional dependence test, cips unit root test, westerlund cointegration test, and the augmented mean group to estimate coefficient elasticities. when we juxtapose the results of the two strategies we notice that we get the same results for the impact of income and energy use on carbon dioxide emissions. both the methods suggest that with an increase in gdp, carbon dioxide emissions reduction. we can infer that the empirical evidence of declining carbon emissions with gdp growth is fairly robust. the same results are obtained from both the strategies for the impact of energy use on carbon emissions. both the first and second-generation tests indicate that energy use positively and significantly impacts carbon emissions. however, when we probe the impact of research and development spending on carbon emissions we get conflicting results from the two strategies. the first generation tests indicate that technology has a positive and significant coefficient whereas the second generation tests suggest that technology has a negative and insignificant coefficient. though it’s worth mentioning that the first-generation tests produce evidence of stronger cointegration results compared to the second-generation tests. overall, we can conclude that our results show that for oecd countries over the span of 1995-12019 the increase in gdp has reduced carbon emissions while the increase in energy use has increased carbon emissions. the mixed results obtained for research and development spending warrant further research to explore the impact of research and development spending on carbon emissions. oecd’s 2015 report. “climate change mitigation: policies and progress (2015) observed the climate change mitigation in 44 countries (including the oecd nations) and the european union. it observed that almost all the analyzed nations showed a decrease in greenhouse gas emissions per unit of gdp, although achieving decarbonization targets will require radical acceleration of effort. the report also noted that the introduction and implementation of carbon-pricing instruments, slashing of fossil fuel subsidies, investment in research efforts for green technology, reduction of emissions from factories, landfill sites, and farms have contributed to the reduction of greenhouse gas emissions. the report emphasized that these efforts showed progress but were clearly insufficient to meet mitigation targets. it’s noteworthy that the political commitment for achieving carbon neutrality is asymmetric across the world and the oecd is relatively more politically committed to climate action. america’s 45q tax incentives for carbon capture show some promise and can be copied in europe. in the european union, electricity generators and an increasing number of other businesses face penal costs for burning fossil fuels (economist, 31st oct 2021). world energy outlook report 2015 identified five the following opportunities that could facilitate an early peak in energy-related greenhouse gas emissions: boosting end-use energy efficiency, growing investment in renewables, phasing out inefficient fossil fuel subsidies, phasing out inefficient coal power plants, controlling methane emissions from oil and gas production. the global trajectory is far from what is required to achieve the paris temperature targets. though in the most optimistic scenario of sustained progress, emissions reductions are unlikely to be drastic enough to keep the warming as low as 1.5°. decarbonization efforts need to be supplemented by “negative emissions” or carbon withdrawal, mechanisms for which are at best embryonic. ambitious and transformative changes are needed to meet climate targets. this study sets the direction for further research, in the particular country-wise analysis of the oecd members. a country-wise analysis of the determinants of co2 and their coefficients will be more revealing and insightful for policy formulation. references acaravci, a., ozturk, i. (2010), on the relationship between energy consumption, co2 emissions and economic growth in europe. table 10: dumitrescu-hurlin (dh) panel causality tests null hypothesis w-stat zbar stat prob gdp does not homogeneously cause co 8.259 12.684 0.000 co does not homogeneously cause gdp 5.564 6.674 0.175 eu does not homogeneously cause co 4.001 3.679 0.000 co does not homogeneously cause eu 4.8444 5.455 5.e-08 rd does not homogeneously cause co 4.543 4.820 1.e-06 co does not homogeneously cause rd 5.564 6.995 3.e-12 source: authors` own calculations sheikh and hassan: impact of economic growth, energy use and research and development expenditure on carbon emissions: an analysis of 29 oecd countries international journal of energy economics and policy | vol 13 • issue 1 • 2023 463 energy, 35(12), 5412-5420. ahmad, n., du, l., lu, j., wang, j., li, h.z., hashmi, m.z. (2017), modelling the co2 emissions and economic growth in croatia: is there any environmental kuznets curve? energy, 123, 164-172. ahmed, k. (2020), environmental policy stringency, related technological change and emissions inventory in 20 oecd countries. journal of environmental management, 274, 111209. ali, s., dogan, e., chen, f., khan, z. (2020), international trade and environmental performance in top ten emitter countries: the role of eco-innovation and renewable energy consumption. sustainable development, 29, 378-387. al-mulali, u., ozturk, i. (2015), the effect of energy consumption, urbanization, trade openness, industrial output, and political stability on environmental degradation in the mena (middle east and north african) region. energy, 84, 382-389. amri, f. (2018), carbon dioxide emissions, total factor productivity, ict, trade, financial development, and energy consumption: testing environmental kuznets curve hypothesis for tunisia. environmental science and pollution research international, 25, 33691-33701. ang, j. b. (2007), co2 emissions, energy consumption, and output in france. energy policy, 35(10), 4772-4778. apergis, n., payne, j. e. (2009). energy consumption and economic growth in central america: evidence from a panel cointegration and error correction model. energy economics, 31(2), 211-216. atasoy, b.s. (2017), testing the environmental kuznets curve hypothesis across the us: evidence from panel mean group estimators. renewable and sustainable energy reviews, 77, 731-747. atici, c. (2009), carbon emissions in central and eastern europe: environmental kuznets curve and implications for sustainable development. sustainable development, 17(3), 155-160. balsalobre-lorente, d., shahbaz, m., jabbour, c.j.c., driha, o.m. (2019), the role of energy innovation and corruption in carbon emissions: evidence based on the ekc hypothesis. in: energy and environmental strategies in the era of globalization. new york city: springer international publishing. bashir, m.a., sheng, b., doğan, b., sarwar, s., shahzad, u. (2020), export product diversification and energy efficiency: empirical evidence from oecd countries. structural change and economic dynamics, 55, 232-243. cheng, z., li, l., liu, j. (2017), the emissions reduction effect and technical progress effect of environmental regulation policy tools. journal of cleaner production, 149, 191-205. chiu, l.c., chang, t.h. (2009), what proportion of renewable energy supplies is needed to initially mitigate co2 emissions in oecd countries? renewable and sustainable energy reviews, 13, 1669-1674. churchill, s., inekwe, j., smyth, r., zhang, x. (2019), r and d intensity and carbon emissions in the g7: 1870-2014. energy economics, 80, 30-37. danish, k., baloch, m. (2018), the effect of ict on co2 emissions in emerging economies: does the level of income matters? environ sci pollut res, 25, 22850-22860. dogan, e., seker, f. (2016), an investigation on the determinants of carbon emissions for oecd countries: empirical evidence from panel models robust to heterogeneity and cross-sectional dependence. environmental science and pollution research, 23(14), 14646-14655. dogan, e., seker, f. (2016), determinants of co2 emissions in the european union: the role of renewable and non-renewable energy. renewable energy, 94, 429-439. dogan, e., seker, f., bulbul, s. (2015), investigating the impacts of energy consumption, real gdp, tourism and trade on co2 emissions by accounting for cross-sectional dependence: a panel study of oecd countries. current issues in tourism, 20, 1701-1719. dogan, e., turkekul, b. (2016), co2 emissions, real output, energy consumption, trade, urbanization and financial development: testing the ekc hypothesis for the usa. environmental science and pollution research, 23(2), 1203-1213. eberhardt, m., bond, s. (2009), cross-section dependence in nonstationary panel models: a novel estimator (no. 17692: mpra paper). germany: university library of munich. farhani, s., ozturk, i. (2015), causal relationship between co2 emissions, real gdp, energy consumption, financial development, trade openness, and urbanization in tunisia. environmental science and pollution research, 22, 15663-15676. ganda, f. (2019), the impact of innovation and technology investments on carbon emissions in selected organisations for economic cooperation and development countries. journal of cleaner production, 217, 469-483. garronen, p., grilli, l. (2010), is there a relationship between public expenditures in energy r and d and carbon emissions per gdp?an empirical investigation. energy policy, 38, 5600-5613. global energy and co2 status report 2017. (2017), available from: https://www.iea.org/reports/global-energy-co2-status-report-2017  gozgor, g. (2017), does trade matter for carbon emissions in oecd countries? evidence from a new trade openness measure. environmental science and pollution research, 24(36), 27813-27821. grossman, g., krueger, a. (1991), environmental i̇mpacts of a north american free trade agreement. united states: national bureau of economic research, inc. grossman, g.m., krueger, a.b. (1995), economic growth and the environment. quarterly journal of economics, 110(2), 353-377. hamilton, c., turton, h. (2002), determinants of emissions growth in oecd countries. energy policy, 30(1), 63-71. hashmi, r., alam, k. (2019), dynamic relationship among environmental regulation, innovation, co2 emissions, population, and economic growth in oecd countries: a panel investigation. journal of cleaner production, 231, 1100-1109. hossain, m.s. (2011), panel estimation for co2 emissions, energy consumption, economic growth, trade openness and urbanization of newly industrialized countries. energy policy, 39(11), 6991-6999. iea (2018), global energy and co2 status report 2017, iea, paris https://www.iea.org/reports/global-energy-co2-status-report-2017 iea (2018), world energy outlook 2018, iea, paris. im, k., persaran, m., shin, y. (2003), testing for unit roots in heterogeneous panels. journal of econometrics, 115, 53-74. iqbal, n., abbasi, k.r., shinwari, r., guangcai, w., ahmad, m., tang, k. (2021), does exports diversification and environmental innovation achieve the carbon neutrality target of oecd economies? journal of environmental management, 291, 112648. jalil, a., feridun, m. (2011), the impact of growth, energy and financial development on the environment in china: a cointegration analysis. energy economics, 33(2), 284-291. javed, m., sharif, f. (2016), environmental kuznets curve and financial development in pakistan. renewable and sustainalbe energey reviews, 54, 406-414. jebli, m.b., youssef, s.b., ozturk, i. (2016), testing environmental kuznets curve hy-pothesis: the role of renewable and non-renewable energy consumption and trade in oecd countries. ecological indicator, 60, 824-831. kao, c. (1999), spurious regression and residual-based tests for cointegration in panel data. journal of econometrics, 90, 1-44. kasman, a., duman, y. (2015), co2 emissions, economic growth, energy consumption, trade and urbanization in new eu member and candidate countries: a panel data analysis. economic modelling, 44, 97-103. khan, z., murshed, m., dong, k., yang, s. (2021), the roles of export diversification and composite country risks in carbon https://www.iea.org/reports/world-energy-outlook-2018, https://www.iea.org/reports/world-energy-outlook-2018, https://www.iea.org/reports/world-energy-outlook-2018, sheikh and hassan: impact of economic growth, energy use and research and development expenditure on carbon emissions: an analysis of 29 oecd countries international journal of energy economics and policy | vol 13 • issue 1 • 2023464 emissions abatement: evidence from the signatories of the regional comprehensive economic partnership agreement. applied economics, 53(41), 4769-4787. lau, l.s., choong, c.k., eng, y.k. (2014), investigation of the environmental kuznets curve for carbon emissions in malaysia: do foreign direct investment and trade matter?. energy policy, 68, 490-497. lean, h.h., smyth, r. (2010), co2 emissions, electricity consumption and output in asean. applied energy, 87(6), 1858-1864. levin, a., lin, c., chu, c. (2002), unit root tests in panel data: asymptotic and finite sample properties. journal of econometrics, 108, 1-24. liddle, b. (2011), consumption-driven environmental impact and age structure change in oecd countries: a cointegration-stirpat analysis. demographic research, 24, 749-770. liddle, b. (2015), what are the carbon emissions elasticities for income and population? bridging stirpat and ekc via robust heterogeneous panel estimates. global environmental change, 31, 62-73. liddle, b., lung, s. (2010), age-structure, urbanization, and climate change in developed countries: revisiting stirpat for disaggregated population consumption-related environmental impacts. population and environment, 31(5), 341-347. lin, s., zhao, d., marinova, d. (2009), analysis of the environmental impact of china based on the stirpat model. environmental impact assessment review, 29(6), 341-347. mania, e. (2020), export diversification and co2 emissions: an augmented environmental kuznets curve. journal of international development, 32(2), 168-185. menz, t., welsch, h. (2012), population aging and carbon emissions in oecd coun-tries: accounting for life-cycle and cohort effects. energy economics, 34(3), 842-849. nasir, m., rehman, f.u. (2011), environmental kuznets curve for carbon emissions in pakistan: an empirical investigation. energy policy, 39(3), 1857-1864. omri, a. (2013), co2 emissions, energy consumption and economic growth nexus in mena countries: evidence from simultaneous equations models. energy economics, 40, 657-664. pan, x., uddin, m.k., ai, b., pan, x., saima, u. (2019), influential factors of carbon emissions intensity in oecd countries: evidence from symbolic regression. journal of cleaner production, 220, 1194-1201. pao, h.t., tsai, c.m. (2011), modeling and forecasting the co2 emissions, energy consumption, and economic growth in brazil. energy, 36(5), 2450-2458 paramati, s.r., mo, d., huang, r. (2021), the role of financial deepening and green technology on carbon emissions: evidence from major oecd economies. finance research letters, 41, 101794.  park, y., meng, f., baloch, m. (2018), the effect of ict, financial development, growth, and trade openness on co2 emissions: an empirical analysis. environmental science and pollution research, 25, 30708-30719. pedroni, p. (1999), critical values for cointegration tests in heterogeneous panels with multiple regressors. oxford bulletin of economics and statistics, 61, 653-678. pedroni, p. (2000), fully modified ols for the heterogeneous cointegrated panels. advances in econometrics, 15, 93-130. pesaran, h. (2004), general diagnostic tests for cross-sectional dependence in panels. (no. 435: cambridge working papers in economics), united kingdom: university of cambridge. pesaran, m. (2007), a simple panel unit root test in the presence of crosssection dependence. journal of applied economics, 22(2), 265-312. petrović, p., lobanov, m.m. (2020), the impact of r and d expenditures on co2 emissions: evidence from sixteen oecd countries. journal of cleaner production, 248, 119187. poumayvong, p., kaneko, s. (2010), does urbanization lead to less energy use and lower co2 emissions? a cross-country analysis. ecological economics, 70(2), 434-444. ritchie, h., roser, m. (2020), co₂ and greenhouse gas emissions. united kingdom: our world in data. saboori, b., sapri, m., baba, m.b. (2014), economic growth, energy consumption and co2 emissions in oecd (organization for economic co-operation and development)’s transport sector: a fully modified bi-directional relationship approach. energy, 66, 150-161. say, n. p., yücel, m. (2006), energy consumption and co2 emissions in turkey: empirical analysis and future projection based on economic growth. energy policy, 34(18), 3870-3876. seker, f., ertugrul, h., cetin, m. (2015), the impact of foreign direct investment on environmental quality: a bounds testing and causality analysis for turkey. renewable and sustainable energy reviews, 52, 347-356. shafiei, s., salim, r. (2014), non-renewable and renewable energy consumption and co2 emissions in oecd countries: a comparative analysis. energy policy, 66, 547-556. shahbaz, m., khraief, n., uddin, g., ozturk, i. (2014), environmental kuznets curve in an open economy: a bounds testing and causality analysis for tunisia. renewable and sustainable energy reviews, 34, 325-336. soytas, u., sari, r., ewing, b. (2007), energy consumption, income, and carbon emissions in the united states. ecological economics, 62(3), 482-489. tang, c.f., tan, b.w. (2015), the impact of energy consumption, income and foreign direct investment on carbon dioxide emissions in vietnam. energy, 79, 447-454. wang, l., chang, h.l., rizvi, s.k.a., sari, a. (2020), are eco ınnovation and export diversification mutually exclusive to control carbon emissions in g-7 countries? journal of environmental management, 270, 110829. wang, y., zhang, x., kubota, j., zhu, x., lu, g. (2015), a semi-parametric panel data analysis on the urbanization-carbon emissions nexus for oecd countries. renewable and sustainable energy reviews, 48, 704-709. wang, z., yin, f., zhang, y., zhang, x. (2012), an empirical research on the influencing factors of regional co2 emissions: evidence from beijing city, china. applied energy, 100, 277-284. westerlund, j., edgerton, d. (2007), a panel bootstrap cointegration test. economics letters, 97(3), 185-190. yavuz, n.ç. (2014), co2 emission, energy consumption, and economic growth for turkey: evidence from a cointegration test with a structural break. energy sources, part b: economics, planning, and policy, 9(3), 229-235. york, r., rosa, e.a., dietz, t. (2003), stirpat, ipat and impact: analytic tools for unpacking the driving forces of environmental impacts. ecological economics, 46(3), 351-365. zaidi, s.a.h., hussain, m., zaman, q.u. (2021), dynamic linkages between financial inclusion and carbon emissions: evidence from selected oecd countries. resources, environment and sustainability, 4, 100022. zhang, c., lin, y. (2012), panel estimation for urbanization, energy consumption and co2 emissions: a regional analysis in china. energy policy, 49, 488-498. zhang, l., gao, j. (2016), exploring the effects of international tourism on china’s economic growth, energy consumption and environmental pollution: evidence from a regional panel analysis. renewable and sustainable energy reviews, 53, 225-234. zhao, j., jiang, q., dong, x., dong, k. (2020), would environmental regulation improve the greenhouse gas benefits of natural gas use? a chinese case study. energy economics, 87, 104712. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 3 • 2023 171 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(3), 171-176. effects of oil consumption, urbanization, economic growth on greenhouse gas emissions: india via quantile approach uzma khan* college of business administration, prince sattam bin abdul aziz university, alkharj, kingdom of saudi arabia. *email: uzmakhanafridi@gmail.com received: 17 january 2023 accepted: 08 april 2023 doi: https://doi.org/10.32479/ijeep.14225 abstract although low-carbon economic growth has been emphasized in both the paris agreement and the sustainable development goals, this is the first study to examine the interplay between oil consumption, urbanization, and economic growth in india’s ghg emissions from 1965 to 2021. a quantile regression analysis found that a 1% rise in greenhouse gas emissions is linked to a 0.34% rise in economic growth, a 0.599% rise in oil consumption, and a 0.28% drop in urbanization. using the granger causality technique, researchers found that co2 emissions cause economic development and urbanization in only one direction. on the other hand, oil consumption only has a one-way influence on carbon emissions and urbanization, and economic expansion only has a one-way effect on urbanization. keywords: oil consumption, urbanization, economic growth, greenhouse gas emissions, quantile regression jel classifications:  o44, q40, q56, r11, r23 1. introduction greenhouse gas (ghg) emissions far surpass what the environment can handle. most of this is due to the growth of different economic activities. in reality, over the past few years, worsening environmental conditions have been linked more and more to rising global ghg emissions. estimates show that all human activities worldwide produced about 46 billion metric tons (or the same amount in co2 equivalents) of ghgs in 2010. because of this, environmental degradation has become one of the most critical problems in many developing countries, like india. in 2014, india was alone responsible for 7% of all carbon dioxide (co2) emissions worldwide. this was primarily due to the burning of fossil fuels and industrial activity. india is one of the countries with the most people, and its economy is based chiefly on industrial companies, which are the primary source of carbon emissions (pachiyappan et al., 2022). so, pollution from human activities has been hurting the environment worldwide for a long time. because of this, it is imperative to decarbonize the global economy in ways that are good for the environment, such as by lowering carbon production and consumption activities (siddik et al., 2023). the industrial revolution made urbanization and industrialization the most important ways to modernize the economy and society. however, these paths speed up the use of fossil fuels and cause a lot of carbon dioxide (co2) and other ghgs to be released into the air (li and lin, 2015). india’s total primary energy consumption in 2019 was 570 million metric tons of oil equivalent, which is expected to increase by 63% over the next decade (energy statistics, 2020). nearly 75% of ghg emissions in india come from making and using energy (iea, 2020). this makes india the third-largest carbon emitter in the world. carbon emissions have become a problem worldwide, and building a good infrastructure for the economy is essential. the environmental kuznets curve (ekc) hypothesis is now a common way to look at how the environment affects economic growth. the ekc depicts the environment-growth nexus as an inverted u. the damage to the environment worsens as economic growth slows, peaks as this journal is licensed under a creative commons attribution 4.0 international license khan: effects of oil consumption, urbanization, economic growth on greenhouse gas emissions: india via quantile approach international journal of energy economics and policy | vol 13 • issue 3 • 2023172 growth speeds up, and then gets better as growth continues. the main idea behind the ekc hypothesis is the “develop first, clean up later” argument. in the early stages, governments only care about economic growth and only pay attention to environmental concerns when economic growth is higher (tenaw and beyene, 2021). unfortunately, growing nations such as india adhere to the preceding norm. emerging economies and cities are growing because of policies meant to increase national income, which may be bad for the environment. the world’s ecosystem needs to be balanced because cities are proliferating. this is because everything people do releases ghgs, which is becoming a concern for more and more people worldwide concerning the effects of urbanization that cause carbon emissions, so they are paying more attention to infrastructure development that is good for the economy and has low carbon emissions. to thrive in a way that is sustainable and good for the economy, all countries must include goals for protecting the environment in their growth plans. however, burning dirty energy sources is a significant source of ghg emissions, which makes it hard to keep the environment in good shape (raihan et al., 2022). the environment is no longer just a problem for one person or country but for everyone worldwide. reducing ecological harm and enhancing environmental quality are among the top economic growth priorities. traditional businesses’ reliance on fossil fuels, which drives their economic growth at the expense of natural resources and environmental damage, is not the same as a model for sustainable development. businesses must promptly undertake economic restructuring under the umbrella of environmental protection. it is imperative to make changes to production and consumption that are good for the environment and use less carbon to decarbonize the global economy. with this in mind, the paris agreement under the un framework convention on climate change (unfccc) has stressed the need to reduce ghg emissions, mainly to keep global warming well below 2 degrees celsius above pre-industrial levels (li et al., 2022). the united nations made 17 broad sustainable development goals (sdg) to promote low-carbon development by combining economic, social, and environmental well-being (razzak et al., 2023). in particular, sdg8 and sdg13 call for accelerating economic growth in a way that is good for the environment while reducing the adverse effects of growth on the environment. this study contributes to the environmental economics literature in the following ways: first, it looks at how developing countries like india use oil, become more urban, grow their economies, and release carbon dioxide. as far as the authors know, this study will also be the first to look at these factors together with india’s carbon emissions. so, this study is different from others because it looks at developing countries that have yet to get much or any attention in the past. second, this study employs quantile regression (qr) for empirical analysis. another thing that makes this study stand out is that it uses the most up-to-date methods to estimate. this article is structured as follows: the second section is a survey of the existing literature. the third portion contains data and procedures. in the fourth part, empirical results and discussions have been covered. the final portion delivers the conclusions and policy proposal, too. 2. literature review economists have looked at the link between rising energy use and growing economies. they have used many econometric methods to determine if there is a link between the two. economists have been motivated to investigate the relationship between energy, economic growth, and the environment since the late 1990s, when the kyoto protocol was adopted out of concern for climate change. many of these studies have focused on the long-standing tensions between energy and economic growth and the environmental costs of rapid economic expansion. higher value addition, or economic growth, is inextricably linked to production and consumption, which can be good or bad for the environment, depending on what is causing them. economic activities that use clean resources are generally seen to affect the environment positively. on the other hand, using dirty resources is likely to hurt the quality of the environment (jahanger et al., 2022). household co2 emissions grew by 2.9% and 1.1% for every 1% rise in urbanization, according to li et al. (2015) calculations in china using the input-output method from 1996 to 2012. jiang and lin (2012) used the cointegration method to examine how much energy china’s growing cities use. he found that the rate of urbanization and the number of new buildings in china greatly affected how much co2 the country made. as a result, it was shown that the rate of change in energy intensity was affected by different energy policies. xu and lin (2015) looked at how industrialization and urbanization affected china’s co2 emissions from 1990 to 2011. they did this by using nonparametric additive regression models. in the eastern area, they found that industrialization and co2 emissions were linked in the shape of an upside-down u. however, a positive u-shaped pattern in the centre region indicates that different actions should be taken in these two locations. khan (2020) suggested that the urbanization rate drove the growth of the global economy. it could set the stage for long-term economic growth if handled correctly. it is a worldwide phenomenon linked to the expansion and diversification of economies. according to zi et al. (2016), urbanization is directly linked to co2 emissions, where seasonal and regional patterns speed up and slow down urbanization and co2 emissions. they use a threshold model to test periodic properties and look at data from china’s region from 1979 to 2013. their findings confirm the following effect of urbanization on co2 emissions: (a) emissions increased when the threshold of 0.43 was surpassed. (b) emissions increased as residential income rose. (c) the effect of urbanization on emissions rose initially but then fell as the industry’s share of overall gdp rose. (d) patterns of threshold points vary geographically. using toda and yamamoto’s method, jafri et al. (2015) looked at the granger causality correlations between economic growth, energy consumption, and emissions from 1980 to 2007 in bahrain, adjusting for factors like capital and urban population. in particular, they found that environmental degradation is linked khan: effects of oil consumption, urbanization, economic growth on greenhouse gas emissions: india via quantile approach international journal of energy economics and policy | vol 13 • issue 3 • 2023 173 to urbanization, gdp growth, capital investment, and energy use. alam (2021) found that trade and economic growth harmed the environmental quality of bahrain. bhattacharya et al. (2020) looked at data from 70 economies. they found that even though industrialization increases carbon intensity, total factor productivity, use of renewable energy, and urbanization help keep it low. using resources more efficiently, using clean energy, and making cities more sustainable are all ways to decrease carbon dioxide emissions. nguyen et al. (2020) used data from 33 emerging economies between 1996 and 2014 and the panel-corrected standard errors estimator to figure out how the total amount of energy used affects carbon emissions. higher energy consumption was shown to be connected with a higher total carbon emission discharge. in the research done by murshed et al. (2022) between 2007 and 2018 in seven developing countries, they think that improvements in energy efficiency, the use of renewable energy, financial inclusion, economic growth, globalization, and urbanization will all increase carbon productivity. the research is also essential because it helps figure out how increasing energy efficiency will affect carbon production in the long run. this has yet to be done and is a missing piece of the existing literature. the results back up the idea that a 1% increase in energy efficiency leads to a 0.3% increase in carbon productivity over time. also, the expected net effects show that improvements in energy efficiency reduce the huge downward pressure on carbon productivity caused by financial inclusion, globalization of trade, and urbanization. khan et al. (2022) used data from 1997 to 2018 to look at the effects of using more renewable energy on the environment in the g7 and e7 countries. they took into account economic growth and population size. economic growth and population size harm environmental quality by lowering load capacity factor levels. they also found evidence that economic growth and population size have a one-way effect on load capacity factor levels in the g7 and e7 nations. murshed et al. (2023) looked into whether the next 11 countries could meet their goals for reducing carbon dioxide emissions if they used energy more efficiently. they looked at financial inclusion, the use of renewable energy, economic growth, international trade, and urbanization. their carbon dioxide emissions decreased when these countries used more renewable energy. nevertheless, faster economic growth, more international trade, and more people living in cities led to higher carbon dioxide emissions. dogan and turkekul (2023) looked at the relationship between many aspects of the u.s. economy, such as co2 emissions, energy consumption, real gdp, the square of real gdp, trade openness, urbanization, and financial development, from 1960 to 2010. cointegration is confirmed by bounds testing to exist between the variables under consideration. both energy usage and urbanization exacerbate long-term environmental deterioration. the granger causality test shows that co2 and gdp, co2 and energy use, co2 and urbanization, and gdp and urbanization are all caused by bidirectional causality. based on the literature review above, different studies have come to different conclusions about how oil use, urbanization, and economic growth affect the environment. nevertheless, more research is needed to figure out how the use of oil, the urbanization of land, and the growth of the economy all affect the sustainability of the environment. this study will likely fill in these gaps in india’s narrative. 3. data and methodology 3.1. data in this analysis, i use oil consumption as a proxy for energy consumption, economic growth in current us dollars, and urbanization as a measure of the percentage of the population that lives in cities to estimate the impact of these factors on ghg emissions measured in carbon dioxide emissions in metric tons. this study analysed annual statistics from 1965 until 2021. the information about ghg emissions and oil use was gathered from british petroleum’s website. economic output and urbanization rates were gathered from the world bank’s website as delineated in table 1. 3.2. econometric methodology in this article, koenkar and bassett’s (1978) qr method examines how oil use, urbanization, and economic growth affect india’s ghg emissions. before estimating, we must check the log-form data for introductory statistics. the data failed to meet the criteria of linearity, homoscedasticity, and normality. thus, qr is used due to the absence of a robust distributional assumption. q y x x xi oc ioc u iu g ig itτ β τ β τ β τ β τ ε( ) = ( )+ ( ) + ( ) + ( ) +0 in the quantile above regression equations, i represents the period from 1965 to 2021, respectively; i represents the unobserved individual impact; and indicates the number of quantiles of the conditional distribution, whereas β∝, βu, βg and are variables used against oil consumption, urbanization and economic growth to investigate the impact of these elements on carbon dioxide emissions. additionally, the τth quantile of the conditional distribution was used to estimate the coefficients using the following equation: βτ τ τρ β = = = ∑arg min i n i iy x 1 ( ). in the above equation ρ µ µ τ µ µ µ µτ ( ) = − <( )( ) <( ) = < >    1 0 0 1 0 0 0 , , , i , indicating the checking function, and i (.) is an indicator function 4. results the descriptive statistics look at the variables’ means, standard deviations, minimums, and maximums in table 2. the results show that the average amount of carbon dioxide emissions is 6.49, khan: effects of oil consumption, urbanization, economic growth on greenhouse gas emissions: india via quantile approach international journal of energy economics and policy | vol 13 • issue 3 • 2023174 while the lowest value is 7.84 and the highest is 5.12. in addition, descriptive data reveal that economic growth has a mean of 27.1 and a standard deviation of 0.89. oil consumption and urbanization have respective mean values of 4.16 and 1.08. regarding oil consumption, the minimum, maximum, and standard deviation numbers are 5.47, 2.54, and 0.87, while the same numbers for urbanization are 1.36, 0.75, and 0.18. there are a total of 57 observations. our study aims to test the null hypothesis that urbanization, oil consumption, and economic expansion do not significantly impact india’s carbon emissions. table 3 shows the results of the qr at the median. in table 3, the lng and lno are significant since their p<0.05, while for the lnu, the significant value is <0.10. thus, if there is a rise of 1% in the median value of lng, then the lnc will increase by 0.34% in the median value; likewise, a 1% increase in the median value of lno will increase the lnc by 0.599% in the median value. similarly, a 1% increase in the median value of lnu will decrease the lnc by 0.28% in the median value. the adjusted r-squared is 94%, and the pseudo-r-squared is 95%. so, lno, lnu, and lng are responsible for 94% of the difference between the conditional and actual means in lnc. the quasi-lr statistic value is 1106.02, and the p<5%, which means the quantile model is stable. in table 4 the 10th quantile or 0.100 the lng will increase by 0.379% and after the 30th quantile it starts declining till 90th quantile and in all the quantiles the p-value is significant. while for the lno is start declining from the 10th quantile till 50th quantile and their onwards its start increasing till 70th quantile and again gains in 90th quantile, for lno all the p-values is also significant. the lnu has a negative coefficient values whose value is significant at 40th, 80th, and 90th quantile, thus there is inverse relationship between lnu and lnc. figure 1 presents the graph of the quantile process, which displays the impacts of lng, lno, and lnu on the lnc. also included in this figure is the graph of the quantile process. the graph depicting lng demonstrates rising tendencies up to the 30th percentile of the starting quantile, also known as the 10th. at that point, however, the graph starts to decrease and stays that way until the conclusion of the quantile process. also, the lnu goes up until the 20th quantile, when it goes down until the 40th quantile. it then goes back up until the 70th quantile, when it starts to go down until the end of the quantile process. this pattern repeats itself until the end of the quantile process. even though the lno shows an opposite relationship at first, with a trend of going down until the 30th quantile and then going up until the 70th quantile, it quickly shows a trend of going down until the 80th quantile. then it increases until the 90th quantile, shortly after the 70th quantile. this occurs shortly after the 70th percentile. table 5 displays the results of a pairwise granger causality test, which indicates that economic growth and oil consumption both show one-way granger causality towards urbanization, and oil consumption also shows unidirectional causality towards carbon emissions. this suggests that urbanization is a direct result of both factors. the increase in economic activity and urbanization are shown to be caused by carbon emissions in a unidirectional manner. table 2: descriptive statistics parameters mean median maximum minimum sd observations lnc 6.49 6.54 7.84 5.12 0.87 57 lno 4.16 4.14 5.47 2.54 0.87 57 lnu 1.08 1.06 1.36 0.75 0.17 57 lng 27.1 26.98 28.63 25.81 0.89 57 sd: standard deviation table 1: description of data symbols variables description source lnc greenhouse emissions million tonnes of carbon dioxide emission from energy bp lno oil consumption million tonnes bp lnu urbanization urban population in percentage world development indicators (world bank) lng economic growth constant us$ world development indicators (world bank) bp: british petroleum table 3: quantile regression (median) parameters coefficient probability lng 0.34 0.0006 lno 0.599 0.000 lnu −0.28 0.0724 c −5.006 0.0343 pseudo r2 0.95 adjusted r2 0.94 quasi-lr statistic 1106.02 probability (quasi-lr statistic) 0.000 table 4: quantile regression with different quantiles parameters/τ lng lno lnu c 0.100 coefficient 0.379 0.616 −0.04 −6.39 probability 0.00 0.00 0.816 0.002 0.200 coefficient 0.388 0.605 −0.004 −6.598 probability 0.0002 0.00 0.983 0.0042 0.300 coefficient 0.387 0.567 −0.205 −6.19 probability 0.00 0.00 0.197 0.006 0.400 coefficient 0.318 0.607 −0.376 −4.274 probability 0.0015 0.00 0.03 0.078 0.500 coefficient 0.318 0.599 −0.28 −5.006 probability 0.0015 0.00 0.07 0.034 0.600 coefficient 0.326 0.614 −0.25 −4.61 probability 0.0004 0.00 0.1 0.036 0.700 coefficient 0.304 0.638 −0.256 −4.11 probability 0.0008 0.00 0.08 0.05 0.800 coefficient 0.317 0.587 −0.44 −4.026 probability 0.0001 0.00 0.02 0.029 0.900 coefficient 0.211 0.684 −0.509 −1.46 probability 0.011 0.00 0.005 0.46 khan: effects of oil consumption, urbanization, economic growth on greenhouse gas emissions: india via quantile approach international journal of energy economics and policy | vol 13 • issue 3 • 2023 175 5. discussion and conclusion environmental sustainability is now more critical than ever for developed and developing economies worldwide. as seen in developed and developing countries, economic growth and social change are only possible with urbanization. energy consumption and co2 emissions directly result from urbanization and industrialization processes. urbanized zones account for approximately 2% of the earth’s land use, yet 75% of the world’s energy consumption (zi et al., 2016). more harmful fossil fuels are utilized to meet rising energy demands. although the economy and living conditions did improve, too much power was used to do so. because of this, pollution and carbon dioxide emissions increased, harming the natural world (baz et al. 2022). so, most of the world’s economies have signed several environmental pacts to support the global goal of slowing the rate of environmental damage. even though people think there are many ways to stop environmental degradation, limiting the use of fossil fuels has often been seen as the most important thing to do. in light of this, the goal of this study was to find out the effects of oil consumption, urbanization, and economic growth on the environmental quality of india. this study is meant to shed light on how india’s ghg emissions are affected by its use of oil, its fast urbanization, and its fast economic growth. this study looks at information from 1965 to 2021, which is enough to back up its conclusions. first, it was found that the series had problems with linearity, homoscedasticity, and normality. these findings were the basis for the qr. the qr results show that an increase of 1% in ghg emissions causes an increase of 0.34% in economic expansion and 0.599% in oil consumption. however, the qr also shows that urbanization has a negative impact. if ghg emissions increase by 1%, the number of people living in cities will decrease by 0.28%. using the paired granger causality test to look at the data in more depth shows that the granger effect of carbon emissions drives economic growth and urbanization, but only in one direction. on the other hand, there is evidence that the use of oil is a unidirectional cause of urbanization and carbon emissions. lastly, the economy’s growth is a granger causality that leads to urbanization in a one-way direction. because this study only looked at one country and got its data from secondary sources, its results can only be applied to some developing countries. however, they can help the policymakers of the studied country and the policymakers of other developing countries close to india. to continue their research, the other researchers need to use a more robust econometric model, do it in more depth, and figure out how much these factors affect india’s micro-level ghg emissions. references alam, m.s. (2021), is trade, energy consumption and economic growth threat to environmental quality in bahrain-evidence from vecm and ardl bound test approach. international journal of emergency services, 11(3), 396-408. .0 .1 .2 .3 .4 .5 .6 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 quantile lng .3 .4 .5 .6 .7 .8 .9 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 quantile lno -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 quantile lnu -12 -8 -4 0 4 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 quantile c figure 1: depicts the quantile process estimates table 5: pairwise granger causality observations parameters f-statistic probability inference 55 lng lnc 1.085 0.35 lng≠lnc lnc lng 3.75 0.03 lnc→lng 55 lno lnc 3.14 0.05 lno→lnc lnc lno 1.696 0.194 lnc≠lno 55 lnu lnc 0.87 0.43 lnu≠lnc lnc lnu 6.398 0.003 lnc→lnu 55 lno lng 0.855 0.43 lno≠lng lng lno 1.687 0.195 lng≠lno 55 lnu lng 0.74 0.48 lnu≠lng lng lnu 5.22 0.008 lng→lnu 55 lnu lno 0.9 0.38 lnu≠lno lno lnu 5.148 0.009 lno→lnu khan: effects of oil consumption, urbanization, economic growth on greenhouse gas emissions: india via quantile approach international journal of energy economics and policy | vol 13 • issue 3 • 2023176 baz, k., xu, d., ali, h., khan, u., cheng, j., abbas, k., ali, i. (2022), nexus of minerals-technology complexity and fossil fuels with carbon dioxide emission: emerging asian economies based on product complexity index. journal of cleaner production, 373, 133703. bhattacharya, m., inekwe, j.n., sadorsky, p. (2020), consumptionbased and territory-based carbon emissions intensity: determinants and forecasting using club convergence across countries. energy economics, 86, 104632. dogan, e., turkekul, b. (2016), co2 emissions, real output, energy consumption, trade, urbanization and financial development: testing the ekc hypothesis for the usa. environmental science and pollution research international, 23(2), 1203-1213. energy statistics. (2020), energy statistics. available from: https://www. niua.org/csc/assets/pdf/key-documents/phase-2/energy-greenbuilding/energy-statistics-2020.pdf iea. (2020), india 2020-energy policy review. france: international energy agency. jafari, y., ismail, m.a., othman, j., mawar, m.y. (2015), energy consumption, emissions and economic growth in bahrain. chinese journal of population resources and environment, 13(4), 1-12. jahanger, a., yu, y., hossain, m.r., murshed, m., balsalobre-lorente, d., khan, u. (2022), going away or going green in nafta nations? linking natural resources, energy utilization, and environmental sustainability through the lens of the ekc hypothesis. resources policy, 79, 103091. jiang, z., lin, b. (2012), china’s energy demand and its characteristics in the industrialization and urbanization process. energy policy, 49, 608-615. khan, u. (2020), the nexus between urbanization, gross capital formation and economic growth: a study of saudi arabia. journal of asian finance, economics and business, 7(12), 677-682. khan, u., khan, a.m., khan, m.s., ahmed, p., haque, a., parvin, r.a. (2022), are the impacts of renewable energy use on load capacity factors homogeneous for developed and developing nations? evidence from the g7 and e7 nations. environmental science and pollution research international, 30, 24629-24640. k o e n k a r, r . , b a s s e t t , g . j r. ( 1 9 7 8 ) , r e g r e s s i o n q u a n t i l e s . econometrica, 46, 33-50. li, k., lin, b. (2015), impacts of urbanization and industrialization on energy consumption/co2 emissions: does the level of development matter? renewable and sustainable energy reviews, 52, 1107-1122. li, y.m., zhao, r., liu, t., zhao, j. (2015), does urbanization lead to more direct and indirect household carbon dioxide emissions? evidence from china during 1996-2012. journal of cleaner production, 102, 103-114. li q, sharif a, razzaq a, yu y (2022). do climate technology, financialization, and sustainable finance impede environmental challenges? evidence from g10 economies. technol forecast soc change, 185:122095. murshed, m., apergis, n., alam, m.s., khan, u., mahmud, s. (2022), the impacts of renewable energy, financial inclusivity, globalization, economic growth, and urbanization on carbon productivity: evidence from net moderation and mediation effects of energy efficiency gains. renewable energy, 196, 824-838. murshed, m., khan, u., khan, a.m., ozturk, i. (2023), can energy productivity gains harness the carbon dioxide-inhibiting agenda of the next 11 countries? implications for achieving sustainable development. sustainable development, 31, 307-320. nguyen, c.p., schinckus, c., su, t.d. (2020), economic integration and co2 emissions: evidence from emerging economies. climate and development, 12(4), 369-384. pachiyappan, d., alam, m.s., khan,u., khan,a.m., mohammed,s., alagirisamy, k., manigandan, p (2022). environmental sustainability with the role of green innovation and economic growth in india with bootstrap ardl approach. frontiers in environmental science. doi: 10.3389/fenvs.2022.975177 razzaq a, sharif a, afshan s, li cj (2023). do climate technologies and recycling asymmetrically mitigate consumption-based carbon emissions in the united states? new insights from quantile ardl. technol forecast soc change, 186:122138. raihan, a., muhtasim, d.a., pavel, m.i. (2022). dynamic impacts of economic growth, renewable energy use, urbanization, and tourism on carbon dioxide emissions in argentina. environmental process. 9, 38. siddik, a.b., khan, s., khan, u., yong, l., murshed, m. (2023), the role of renewable energy finance in achieving low-carbon growth: contextual evidence from leading renewable energy-investing countries. energy, 270, 126864. tenaw, d., beyene, a.d. (2021), environmental sustainability and economic development in sub-saharan africa: a modified ekc hypothesis. renewable and sustainable energy reviews, 143, 110897. xu, b., lin, b.q. (2015), how industrialization and urbanization process impacts on co2 emissions in china. energy economics, 48, 188-202. zi, c., jie, w., hong-bo, c. (2016), co2 emissions and urbanization correlation in china based on threshold analysis. ecological indicators, 61(2), 193-201. https://doi.org/10.3389/fenvs.2022.9 tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 3 • 2023292 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(3), 292-305. the role of environmental conditions and purchasing power parity in determining quality of life among big asian cities marc audi1,2,3, amjad ali2,1,4* 1abu dhabi school of management (adsm), uae, 2the european school of leadership and management (eslm), belgium, 3university paris 1 pantheon sorbonne, france, 4lahore school of accountcy and finance, university of lahore, pakistan. *email: chanamjadali@yahoo.com received: 13 september 2022 accepted: 12 march 2023 doi: https://doi.org/10.32479/ijeep.13583 abstract this article has examined the role of environmental conditions and purchasing power parity in deciding the quality of life among big asian cities. the study has constructed an index for quality of life with the help of housing, crime rates, death rate, average life expectancy, environmental degradation, and level of education. quality of life has been selected as the dependent variable and the level of pollution, availability of health care facilities, local purchasing power, availability of groceries, level of democracy, cost of living, restaurants, level of traffic, and level of rents are selected explanatory variables. for empirical analysis, this study uses data for the years 2017, 2018, and 2019. the estimated results show that pollution has a negative and significant impact on the quality of life in the case of asian cities. local purchasing power has a positive and significant relationship with the quality of life in the cities of asia. groceries and democracy are very important parts of the daily life of human beings but they have insignificant impacts on the quality of life in asian cities. restaurants have a positive and significant impact on quality of life. this study finds that level of traffic and the level of rent have a negative and significant impact on the quality of life in the case of asian cities. the overall results conclude that selected indicators play a significant role in determining the quality of life in asian cities. keywords: quality of life, environmental conditions, purchasing power parity jel classifications: e31, j17, r11 1. introduction the most recent, sustainable development goals (sdgs) put special attention on the quality of life among the nations. sdgs encourage national governments, international institutions, and civil societies to help in achieving the targeted quality of life. following, the famous slogan of uno “health and education for all”, the world bank and the uno publish different reports and articles related to the ranking of the quality of life among the countries and cities. the basis of every field of science is a better quality of life, but traditional societies forget this target of the human being (kant, 1785). after the emergence of the uno, quality of life gets special importance in the socioeconomic policies of each nation (mcgillivray, 2007). this general understanding of the quality of life explains that an individual or social group should work for the fulfillment of physiological needs. there are some main indicators for the measurement of quality of life i.e. rate of infant mortality, the mean life expectancy, sanitary facilities, percent of people having safe drinking water, and mean daily calorie supply per person (diener and diener, 1995). the quality of life has also some subjective as well as some objective traits. the best traditional tools for measuring the quality of life at the macro level are the gross domestic product and at the micro level per capita income. tobin and nordhaus (1972), the united nations development program (1990), and anand and sen (1992) mention that traditional tools for measuring the quality of life are unable to explain the actual socioeconomic conditions of the individual household. tobin this journal is licensed under a creative commons attribution 4.0 international license audi and ali: the role of environmental conditions and purchasing power parity in determining quality of life among big asian cities international journal of energy economics and policy | vol 13 • issue 3 • 2023 293 and nordhaus (1972) point out that net economic welfare is the best criterion for the measurement of quality of life because it is based on the aggregate consumption of the nation. international labor organization (1976) has developed physical quality of life index. in this study, we have constructed an index of quality of life (availability of housing, crime rates, death rate, average life expectancy, environmental degradation, and level of education) with the help of principle components analysis. the idea of environmental conditions related to the quality of life has a wider scope, and this depends on the quality of mediums (e.g. soil, water, and air). the quality of the environment is considered very important to the quality of human life because human health is greatly impacted by the existing physical conditions of the environment (coan and holman, 2008, kahn, 2002). extreme environmental conditions (earthquakes, cyclones, floods, droughts, and volcanic eruptions) have seriously damaged the physical and mental health of human beings (ahmad and yamano, 2011). it has been observed empirically that environmental conditions strongly impact the quality of life (diener and suh, 1997, unece, 2009). the quality of the environment has intrinsic value to the human being (brajša-žganec et al., 2011). the preserving environment is one of the most important factors in ensuring and the preservation of well-being over time (liere and dunlap, 1980). thus, the policies related to the environment have a critical role to deal with global health priorities, as well as improving environmentally responsible behavior and lives (felix and garcia-vega, 2012). in the frictionless world, the prices of the same goods should be the same across different locations. the law of the one price is considered an important determinant of quality of life. if the prices differ in two locations, excess demand and supply in the cheap and expensive locations would ultimately equalize them. the cross-location and international prices infer that the price dispersion changes little over time, but the international price declines over time and has a deep-rooted impact on quality of life (reif et al., 2021). in recent years, price convergence among the regions has fascinated policymakers to check its impact on different socioeconomic factors. as this refers to the convergence of quality of life among the regions and nations at the same time. the differences between the prices in the two countries are temporary if the prices are measured with the same exchange rate (pires-júnior et al., 2018). the role of wages and rents in allocating workers’ locations, also decide the quality of life within that locations. if the amenity of production and the wage gradient is unclear while the rent gradient is positive, this would produce an unclear level of quality of life. hence, the housing market and the non-traded good price level are also unclear (roback, 1982). the long-run behavior of the cost of a given consumption basket at each point in time to document the behavior of absolute price levels (devereux and griffith, 2003). average relative price variability has a significant impact on the quality of life in the same region (chmelarova and nath, 2008). price level convergence is referred to as the overall consumer price index as well as the index without housing prices (dreger and kosfeld, 2010). the overwhelming evidence in support of price level convergence over time in major cities in the us (huang et al., 2011). border plays an important role in the variations of prices of similar goods and services in different cities, but the variations in the prices are higher in the cities located in different countries than in the cities in the same country (engel and rogers, 1994). based on the law of one price, purchasing power parity states that exchange rates do not affect relative goods, relative inflation will be proportional to the exchange rates, and there is weak evidence of purchasing power parity and quality of life (serletis and gogas, 2003). this study has examined the role of environmental conditions and purchasing power parity on quality of life in the case of selected asian cities. 2. literature review there are extensive theoretical and empirical studies that investigate the link between environmental conditions and quality of life, purchasing power, and quality of life. here, the most relevant studies have been selected for the literature review. quality of life refers to reasonable and good living conditions (cella, 1992; felce and perry, 1995; sarvimäki and stenbock‐hult, 2000; kelley-gillespie, 2009; lagadec et al., 2018; ohta et al., 2021; solberg et al., 2022). good and reasonable living conditions are comprised of material sources and subjective perceptions e.g. feelings and emotions. ventegodt et al., (2003) mentioned that quality of life has its integrated attributes. this study provides three notions of quality of life i.e., objective quality of life, existential quality of life, and subjective quality of life. environmental conditions being the objective indicators i.e. the concentrations and emissions of various pollutants should be combined here with indicators based on people’s subjective perceptions of the quality of the environment where they live. as in the case of other subjective data, indicators of satisfaction with environmental quality may be affected by cultural biases and other limits that could affect cross-country comparisons, so these indicators are excluded from the assessment of environmental indicators of quality of life (liao, 2009). local environmental conditions have a direct influence on the quality of life in general and human health in specific. better quality of the environment is a big foundation for human satisfaction and improved mental health, and it permits individuals to recover from the stresses of everyday life and perform physical activities. sufficient availability and access to physical resources e.g., green spaces, forests, and rivers contribute to the quality of life. economies rely not only on healthy and productive workers but also on natural resources like water, timber, fisheries, plants, and crops (zheng, 2010). the consumption of environmental services and amenities has a direct impact on quality of life, and conversely, the quality of these services is affected by human behavior. environmentally responsible behavior through activities such as saving energy, using renewable resources and sustainable consumption is the main driver of the quality of environmental services provided (osbaldiston and sheldon, 2003, thogersen, 2006). following the theories related to the quality of life, the wider spectrum incorporates the subjective and objective realm of living (berleant, 1997; ya-wen and hsiao, 2006; ventegodt et al., 2003). the process considers diverse dimensions ranging from audi and ali: the role of environmental conditions and purchasing power parity in determining quality of life among big asian cities international journal of energy economics and policy | vol 13 • issue 3 • 2023294 economic status to personal security (durand, 2015; balestra and tonkin, 2018). there has been quite a bit of recent scholarly effort aiming to understand the relationship between economic status and quality of life (cella, 1994; smith, 1999; tang, 2007; kautonen et al., 2017). purchasing power is one of the practical indicators representing economic condition (guesalaga and marshall, 2008; rogoff, 1996). frenkel (1981) studies the trend of purchasing power parities among the us dollar and france franc for may 1979–july 1979. the study finds that during the 1970 s currency rate of exchange between the usa dollar and the france franc has fallen. the study concludes that the currency rate of exchange and level of price cannot be separated from each other, so any variation in the rate of exchange will impact the domestic price level and lifestyle of the masses. taylor and brown (1988) investigates the long-run trend of purchasing power parity with the help of co-integration techniques among five major exchange currencies from 1973 to 1985. seasonally unadjusted monthly based data has been used in this study. the outcomes of this study are against the traditional hypothesis of purchasing power parity, there is no integration has been found among the major exchange currency during the selected period. this study concludes that proportionality exists among the relative prices ad exchange rates over the long run. apte et al. (1994) examine the relative purchasing power parity monthly. the data have been used in this study post-1972. the authors argue that martingale behavior deviates from the purchasing power parity. this study uses all information implicit in all cross-rates too. secondly, an instrumental variable that is specifically designed to cope with lead-and-lag effects in nontraded versus traded-goods inflation. our estimates indicate that most lead-and-lag effects seem to occur within a 6-month window. engel and rogers (2001) explore the failures of the law of one price across european cities. the focus of this study is to explore the local currency pricing and floating exchange rates for the international failures of the law of one price. this study is paying more attention to the local currency instead of previous studies. this study derives an expression for the variance of the relative prices across locations in terms of nominal exchange rate and transportation costs. it is concluded that the border effects are coming from the local currency pricing with the fluctuating nominal exchange rate. the border effect has a positive and significant effect on real exchange variations. silvester et al. (2004) investigate the purchasing power in the panel of cities. this study uses a long-time span of panel data and the short-run deviations measured by the half-lives, thus, the results show non-rejection of the purchasing power parity. in highly integrated economies, real factors may be due to a slow rate of convergence to a common price index. coakley et al. (2005) investigate the first test of purchasing power parity and the theory of general relativity. the study finds that inflation differentials reflect, on average one-for-one in long-run nominal exchange rate reduction that general relative purchasing power parity holds. reif and rumler (2014) examine the price dispersion in the euro area. for this purpose, the disaggregated price data set has been taken from the ac nielsen to the euro system. the study concludes that the price dispersion moves together closely in locations that are closer to each other, but the price dispersion across the cross-country price dispersion is by an order of magnitude larger than within-country price dispersion even after controlling for product heterogeneity. tax rates, income level, and consumption intensities could be explained as a large part of the cross-country price difference. it also indicates that price dispersion in the euro area has declined since the start of the monetary union. beko and kavkler (2019) reexamining the purchasing power parity for small central and eastern european economies. the results show that even after considering the nonlinear reversion of real exchange rates of choosing central and eastern economies, there is no confirmed validity of purchasing power parity. the nonstationarity hypothesis of the real exchange rate is rejected in the case of 3 countries out of 10. this study gives the direction for further research to point out the determinants that cause the violation of the purchasing power parity concepts in the central eastern european economies. 3. the model quality of life has been the prime objective of all human activities (shin and johnson, 1978; elizur and shye, 1990; mckee-ryan et al., 2005). simply, quality of life presents the overall situation of peoples’ lives in the country (mcgillivray, 2007). somehow, this general understanding of the quality of life is unable to explain an individual or any particular social group’s living standard. literature (headey and wearing, 1989; costanza et al., 2007; renwick et al., 2017; mouratidis, 2021) has highlighted that there are some objective as well as some subjective traits attached to the quality of life. thus, for this purpose, the selection of key indicators and their assigned weight matter a lot. for a couple of years, there are some measures have been used for judging the quality of life (veenhoven, 1993). the best traditional tools for measuring the quality of life at the macro level are the gross domestic product and at the micro level per capita income. nordhaus and tobin (1973), the united nations development program (1990), and anand and sen (1992) mention that traditional tools for measuring the quality of life are unable to explain the actual socioeconomic conditions of the individual household. quality of life directly explains the participation of an individual in the socioeconomic activities of the community (coleman and rainwater, 1978; rainwater, 1990; sen 1992). sen (1992) further points out that aggregate household consumption is not quality of life, whereas it is the ability to consume and the capability to participate in socio-economic activities that are called real quality of life. united nations development program (1990) has developed a comprehensive index for measuring the quality of life with the help of health, education, and income. following the methodologies of duesenberry (1949), scitovsky (1976), layard (1980), frank (1985), schor (1998), cooper et al. (2001), ravallion and lokshin (2001), ferrer-i-carbonell (2002), ali (2015), ali and rehman (2015), ali and bibi (2017), and ali (2018) we have constructed an index of quality of life in the case of selected asian cities. the functional form of the model becomes as: qli=f (pii, hcii, ppii, gii, dmi, clii, riii, tii, rii) (1) audi and ali: the role of environmental conditions and purchasing power parity in determining quality of life among big asian cities international journal of energy economics and policy | vol 13 • issue 3 • 2023 295 ql= quality of life index has been constructed with the help of availability of housing, crime rates, death rate, average life expectancy, environmental degradation, and level of education by using principle component analysis (pca). pi = level of pollution (co2 emissions) hci = availability of health care facilities (number of hospitals, doctors, nurses, hospitals beds, lady health workers, etc.) ppi = local purchasing power (local purchasing power shows relative purchasing power in buying goods and services in a market) gi = grocery index comprised of availability of necessary grocery items dm= democracy (measured with a dummy variable, 1 for democracy and 0 otherwise) cli= cost of living (the prices of food, shelter, transportation, energy, clothing, healthcare, childcare, etc.) rii = availability of restaurants ti= availability of transportation ri= housing rent to examine the elasticity of the explanatory variables to the dependent variable, the econometric model of the study becomes as: qli=a+β1pii+β2hcii+β3ppii+β4gii+β5dmi+β6clii+β7riii+β8t ii+β9rii+ui (2) all the variables explained above expect a and u, a=constant intercept u=error term i.e. white noise having zero mean and constant variance in this study, cross-sectional data from the years 2017, 2018, and 2019 have been used. the data of selected asian cities have been taken from the world bank and some national databases of each country. 42 cities of asian countries have been collected for selected: dubai (uae), tokyo (japan), singapore (singapore), bangalore (india), pune (india), istanbul (turkey), kuala lumpur (malaysia), chennai (india), delhi (india), mumbai (india), bangkok (thailand), tehran (iran), kolkata (india), shanghai (china), doha (qatar), hong kong (hong kong), hyderabad (india), ankara (turkey), beirut (lebanon), jakarta (indonesia), tbilisi (georgia), manila (philippines), amman (jordan), riyadh (saudi arabia), bursa (turkey), taipei (taiwan), seoul (south korea), tel aviv-yafo (israel), izmir (turkey) almaty (kazakhstan), yerevan (armenia), beijing (china), karachi (pakistan), ho chi minh city (vietnam), colombo (sri lanka), mangalore (india), muscat (oman), gurgaon (india), baku (azerbaijan), lahore (pakistan), ahmedabad (india) and hanoi (vietnam). 4. results and discussion this section consists of a discussion and estimated results that how selected indicators can impact the quality of life in the selected cities of asia. quality of life is taken as an explained variable, whereas traffic, the cost of living, rent, grocery, restaurant, local purchasing power parity, pollution, health care, and democracy have been used as independent variables. appendix table a presents the descriptive statistic of the selected variables, the results of the descriptive show the mean, standard deviation, minimum, maximum, skewness, kurtosis, and jarque-bera values of explained as well as explanatory variables. based on the estimated results, all of our selected variables have reasonable intertemporal properties to estimate the regression analysis. the estimated results of correlation have been given in appendix table b. the results show that most selected variables have a significant relationship with each other, but there is no higher correlation which creates the issue of multicollinearity among our decided regressors. pollution is a major risk contributor to human health (mckenzie et al., 2012; audi and ali, 2018; huang et al., 2018; rinklebe et al., 2019; beni and esmaeili, 2020). different human activities produce different gases (sulfur oxides, nitrogen oxides, carbon monoxide, carbon dioxide, volatile organic compounds, particulate matter, chlorofluorocarbons, and ammonia) which hurt human health (who, 2002; cohen et al., 2005; sadalla, 2005; mathew et al., 2013). our estimated results of regression for the years 2017, 2018, and 2019 have been given in table 1. the outcomes present that pollution level has a negative and significant influence on the quality of life in asia cities. the rising level of pollution creates more chances of different diseases i.e. respiratory, lung and skin cancer, and asthma, etc., (sadalla, 2005; pruss-ustun and corvalán, 2006). under such an environment, there are more chances of children and adult respiration (who, 2014 and cdc, 2010). about 5% of lung cancer has been attributed to pollution and it has a continuously rising trend (who, 2002; cohen et al., 2004). exposures to pollution accounted for approximately 2 % of the global cardiopulmonary disease burden (cohen et al., 2004; who, 2002). empirics show that pollution is estimated to be responsible for about 3% of adult cardiopulmonary disease mortality; about 5% of the trachea, bronchus, and lung cancer mortality; and about 1% of mortality in children from acute respiratory infection in urban areas worldwide (cohen et al., 2005). thus, specifically, the rising level of pollution reduces the quality of life in a nation and a city in general. our results reveal that a 1% rise in the pollution level, (−0.917000) %, (−0.672991) % and (−0.780301) % fall happened in the quality of life in asian cities during the years 2017, 2018, and 2019. literature from the last three decades (van aardenne et al., 1999; brunekreef and holgate, 2002; sadalla, 2005; bell et al., 2008; ali and audi, 2016; audi and ali, 2016; ali et al., 2021) show that pollution contributes to illness and death in all age groups, but the association between child death rate and pollution is very strong. the availability of health care facilities will make the citizen of the nation more assured to get the health services they needed. better quality of life is directly and indirectly attached to health care standards (testa and nackley, 1994; ferrans et al., 2005; karimi and brazier, 2016), as by keeping the public health status promotive, rehabilitative, curative, and preventive, we may have better health outcomes (engineer et al., 2008; de mello and pisu, 2009; todaro and smith, 2011; craigwell, et al., 2012). our results for the year 2017 show that there is a positive but insignificant link existed between health care audi and ali: the role of environmental conditions and purchasing power parity in determining quality of life among big asian cities international journal of energy economics and policy | vol 13 • issue 3 • 2023296 and the quality of life in asia. better health care is attached to an educated population, skilled labor, and better medication. based on the results, this reveals that asian countries have more uneducated populations, unskilled labor, and less medication for the population. moreover, asian cities have poor health care systems i.e. medical staff is not competent and skilled, examining and reporting is slow, modern equipment for disease diagnosis is not available, the convenience of location for the center is not available, and huge and congested cities (kaplan, 2003; amaghionyeodiwe, 2009; allin et al., 2010; and kim et al., 2017). this creates an insignificant impact on the health care system for the masses of cities in asia. so, deficiencies in health care are impacting badly the quality of life in the cities of asia. but health care is positively and significantly influencing the quality of life during the years 2018 and 2019. health care should be the basic priority of governments, so over time, asian governments are paying much attention to the health of the masses. purchasing power is one of the practical indicators representing the economic condition of the masses of the country (frenkel, 1978; abuaf and jorion, 1990; rogoff, 1996; taylor and taylor, 2004), thus there is a strong relationship is existed between purchasing power and quality of life (chin, 2001; fisher, 2006; tan et al., 2018). there are numerous studies (costanza et al., 2007; coletto et al., 2017; greco and polli, 2021) that highlighted that security perception has an important role in determining the level of human well-being. the purchasing power presents the currency value in terms of buying goods and services relative to other international currencies (balassa, 1964; taylor and taylor, 2004; haidar, 2011). the physical needs are the initial basis of the realization of quality of life (hyde et al., 2003; aivazian, 2016). the degree to which material needs are satisfied depends on the level of income (diener and oishi, 2000; diener and biswasdiener, 2002). purchasing power can be the indicator representing the level of income (gelb and diofasi, 2016; chen and hu, 2018; bronchetti et al., 2019). empiric shows that the purchasing power of asian cities is increasing and it has a significant influence on the quality of life. the rising purchasing power has created a positive economic environment. our results indicate that if the purchasing power increases, then the quality of life enhances because higher purchasing power enables individuals to buy more goods and services (de estado, 2013). the results indicate that the 1% rise in the local purchasing power rises by (0.265952) %, (0.478234) %, and (0.466222) % during 2017, 2018, and 2019 respectively. so, empirics show that as purchasing power increases the people buying capacity of people, thus it raises the standard of living in the cities of asia. following the objective factors of quality of life (lawton et al., 1999; ruggeri et al., 2001; parra et al., 2010), the intake of calories is directly impacted by the availability of groceries (schroeter et al., 2008; valin et al., 2014). the poor population of developing countries has a low amount of groceries, hence there is a low level of quality of life (zezza and tasciotti, 2010; popkin et al., 2012). our estimated results for the years 2017 and 2018 show that in the case of asian cities, there is a positive and insignificant impact of groceries on the quality of life. although, groceries play a vital role in our basic life. if the quality of groceries is not good, then it depressed the quality of life among the masses (drewnowski and evans, 2001; lim and taylor, 2005; rasheed and woods, 2013). but during the year 2019 groceries have a negative and significant impact on quality of life. this also shows that the standard of groceries in asian cities is very bad which is harmful to human table 1: regression outcomes-year dependent variable: ql variables year-2017 year-2018 year-2019 coefficient std. error coefficient std. error coefficient std. error pi −0.917000*** 0.324959 −0.672991** 0.309342 −0.780301*** 0.147959 hci 0.470872 0.499288 0.931557** 0.410969 0.853693*** 0.274245 ppi 0.265952* 0.135231 0.478234*** 0.163878 0.466222*** 0.091359 gi 0.652375 1.203359 0.288499 1.019981 −1.443005*** 0.469808 dm −27.02107 17.53992 −18.93161 14.01571 4.678003 6.718584 cli −1.687793 1.814835 −1.185922 1.567984 1.713598** 0.678702 rii 1.481704* 0.813700 1.427618* 0.753392 −0.037075 0.345602 ti −0.209172** 0.076728 −0.194604*** 0.065118 −0.178981*** 0.038908 ri −0.959136*** 0.478294 −1.120078** 0.421298 −0.755148*** 0.248177 c 198.0765 58.51343 125.9796 43.36071 115.0171 24.93568 r-squared 0.645458 0.719446 0.890869 adjusted r-squared 0.531499 0.642932 0.860176 s.e. of regression 27.58177 24.74640 12.25112 sum squared resid 21301.12 20208.69 4802.874 log likelihood −174.1693 −193.2967 −159.1207 f-statistic 5.663911 9.402724 29.02499 prob (f-statistic) 0.000180 0.000001 0.000000 mean dependent var 104.6724 104.7119 115.8748 s.d. dependent var 40.29644 41.41297 32.76304 akaike info criterion 9.693122 9.455661 8.053368 schwarz criterion 10.12407 9.865243 8.467099 hannan-quinn criter. 9.846448 9.606702 8.205016 durbin-watson stat 2.080583 1.781287 1.943951 ***1% significant level **5% significant level *10% significant level audi and ali: the role of environmental conditions and purchasing power parity in determining quality of life among big asian cities international journal of energy economics and policy | vol 13 • issue 3 • 2023 297 life, thus groceries impact badly on the quality of life. the results illustrate that a 1% in the groceries −1.443005% fall is happening in the quality of life in the selected asian cities. many social scientists believe that political rights have an intrinsic impact on the human well-being of individuals within a nation (dasgupta, 1990; diener and suh, 2003; tov and diener, 2009; murphy, 2014). most of them are agreed that these are political and democratic rights that enable individuals to demand such public policies which enhance their welfare. sen (1999) mentions that each society has faced a trade-off between adopting those institutions that preserve the essential political rights exercised by individuals to raise their quality of life, and demanding such institutions that reduce constraints to produce equal opportunities for all individuals to raise their wellbeing. our estimated results show that democracy has an insignificant impact on the quality of life in asian cities. numerous studies (kosack, 2003; wong et al., 2011; buhaug and urdal, 2013) show that developing countries have weak institutions for political and democratic rights, thus, our finding has an insignificant relationship between democracy and quality of life among asian countries. in a democracy, people have the right to select the legislature, they all have equal rights and the government is run under the rules and regulations. in asia, democracy puts an insignificant effect on the quality of life of the general public (bloom et al., 2001; chang and chu, 2006; buhaug and urdal, 2013). democracy is attached to an educated population, in asia, mostly the population is uneducated and they don’t understand the true benefits of being democratic. the cost of living is comprised of the price of food, childcare, healthcare, clothing, energy, etc. quality of life is the direct link to the cost of living (boskin, 1996; bernanke and mishkin, 1997; piazzesi et al., 2007). the cost of living is negatively and insignificantly impacting the quality of life in the selected cities of asia. empiric shows that the cost of necessities has risen trend in asia and the living standard is directly attached to the basic requirement of living human beings i.e. food, health, and housing, but in the case of asia, most population have little or insufficient access to necessities (johansen, 1993; hossain and fischer, 1995; chang et al., 2013). moreover, in asian population have fewer earnings and an insufficient amount of money, which is required for maintaining the standard of living (banerjee and duflo, 2007; saxena et al., 2007). this creates an insignificant link between the quality of life and the cost of living in asia. availability of food is part and parcel of human life in general and quality of life in specific (dasgupta and weale, 1992; rapley, 2003; neulinger et al., 2020). presently, the availability of food from outside the home has become an integral part of human life, and the demand for such food depends upon the availability of restaurants (mccracken and brandt, 1987; gustafsson et al., 2006; mehta and chang, 2008). it is the availability of restaurants in cities, which presents the eating habits of the inhabitants, and the quality of food and services given in the restaurants have a direct influence on the quality of life (edwards and hartwell, 2009; williams, 2009). our results show that restaurants are positively and significantly impacting the quality of life in selected cities. the results reveal that a 1% increase in restaurants brings a 1.481704% and 1.427618% rise in quality of life during the years 2017 and 2018 respectively. but restaurants have an insignificant impact on the quality of life during the year 2019. this insignificance of the relationship shows that during the year 2019, the quality of restaurants deteriorated which automatically impacted the quality of life in general. the availability of transportation is one of the important factors in human personal life and business activities (popova, 2017). the availability of transportation in its simple meaning is to carry passengers and freight from one place to another (bruzzone et al., 2021). when transportation is considered from the quality of life frame, it simply refers to carrying individuals to their job, education, health centers, tourist places, etc., (myers, 1988; macke et al., 2018). the development of transportation, vehicles, and infrastructure and using new technologies in this sector speed up traveling facilities. but in the case of developing countries, the available transportation is insufficient to facilitate a huge amount of population (suzuki et al., 2015; demissie et al., 2016). thus, our results show that the availability of transportation has a negative and significant impact on the quality of life in the case of asian cities. the role of transportation in our daily life is very important because when cities have bad transportation and people spend more time in traffic, then they bear mental depression and lower quality of life (downs, 2005; novaco and gonzalez, 2009). in asia, there are big, old, and congested cities that hurt the quality of life in these cities (glaeser, 2011; wen et al., 2019). moreover, mostly the cities of asia do have not proper road infrastructure which creates traffic issues if the roads are blocked by traffic and the vehicles get stuck on the road and creating depression and noise pollution for the masses (forman et al., 2003; who, 2012; newman and kenworthy, 2013; cervero et al., 2017). the availability of housing facilities covers both subjective and objective dimensions for quality of life. housing facilities are directly linked with rent, thus, house rent is one of the important indicators of quality of life (shapiro, 2006; mccrea et al., 2006; aragonés et al., 2017). as a concern to objective dimensions, the fluctuations in house rent may have a significant impact on individual wealth and reduces his/her capacity to spend on health and education. whereas, subjective dimensions of quality of life (i.e. mental health, etc.) are also impacted by the fluctuations in rent (mccrea et al., 2006). the drivers of housing rent potentially influence the quality of life, as house rent reflects the benefits derived from living in better areas in addition to possible wealth shocks (glaeser and gottlieb, 2009; stone et al., 2015). moreover, the exposure to better neighborhood conditions points towards a positive relationship between housing rent and quality of life irrespective of tenure status and could lead to a positive relationship with overall renters if living in better areas outweighs any negative wealth shocks (byrne and diamond, 2007; rowley and ong, 2012). but in the case of developing countries, most of the population has a weak shock absorption capacity, and any fluctuations in rent may disturb the overall quality of life (collier et al., 2010; barma et al., 2012). our estimated results show that rent has a negative and significant impact on quality of life. the results explain that a 1% rise in housing rent −0.959136%, audi and ali: the role of environmental conditions and purchasing power parity in determining quality of life among big asian cities international journal of energy economics and policy | vol 13 • issue 3 • 2023298 −1.120078%, and −0.755148% fall has occurred in the quality of life during the years 2017, 2018, and 2019, respectively. 4.1. comparative analysis of outcomes we also make the comparative analysis based on our estimated results and discussion. the calculated outcomes of all the models explain that level of pollution is negatively and significantly influencing the quality of life (audi and ali, 2018; huang et al., 2018; rinklebe et al., 2019). availability of health care facilities positively but insignificantly influenced the quality of life during the year 2017 but during the years 2018 and 2019, availability of health care facilities positively and significantly influenced the quality of life in the case of selected asian cities. it shows that asian cities are improving their health care system the raising their living quality (neirotti et al., 2014). the calculated outcomes show that local purchasing power is positively and significantly influencing the quality of life during all the selected years 2017, 2018, and 2019. this shows that higher quality of life is attached to higher purchasing power parity (taylor and taylor, 2004). the outcomes of the years 2017 and 2018 show that the availability of groceries has a positive and insignificant impact on quality of life, but during the year 2019, the availability of groceries is negatively and significantly influencing the quality of life in asian cities. this highlights that the quality and availability of groceries are very low, so there is an inverse link between the availability of groceries and the quality of life in selected asian cities (lucan and mitra, 2012). the level of democracy negatively and insignificantly influenced living quality during the years 2017 and 2018 but during 2019 there is a positive but insignificant impact of the level of democracy on quality of life. this shows that the masses of asian cities are unable to enjoy the true fruits of democracy (kurlantzick, 2013). the cost of living has a negative and insignificant impact on the quality of in selected cities during the years 2017 and 2018, but the cost of living has a positive and significant impact on the quality of life in 2019. restaurants have a positive and significant impact on quality of life during the year 2017 and 2018 but the restaurants are negatively and insignificantly influencing the quality of life in asian cities during 2019. the calculated outcomes reveal that level of traffic is negatively and significantly influencing the quality of life in asian cities during the years 2017, 2018, and 2019. this highlights that rising levels of traffic reduce human well-being (douglas, 2012). the results show that level of rent put an inverse influence on living quality in asian cities during the years 2017, 2018, and 2019. this shows that with the rising level of rents the people of selected cities are unable to get affordable residents for their families (wu, 2004), thus, the overall quality of life is depressed in asian cities. 4.2. diagnostics outcomes the estimated outcomes of diagnostic tests have presented in appendices c, d, e, etc. breusch-godfrey’s lm method of autocorrelation is used for checking the autocorrelation in the data series. breusch-pagan-godfrey has been applied the checking the heteroskedasticity of the data. the results of tables c-e show that there is no issue of serial correlation and heteroskedasticity in the selected data for the years 2017, 2018, and 2019 models. thus, simple, ordinary least squares are the best fit for empirical analysis. hansen (1996) points out that misspecification of the model and variables may generate biased outcomes that impact the predicting power estimated results. the most famous, cusum and cusumsq tests have been utilized for this checking the predicting power of the parameters. brown et al. (1975) highlight that these methods provide facilities to check the gradual variations in the parameters. the expected value of recursive residual is zero leading to accepting the null hypothesis of parameter constancy is correct, otherwise not. this study has examined the determinants of quality of life in the case of selected asian cities in 2017, 2018, and 2019. the plots of both cusum and cusumsq are shown in figures 1-6 at a 5% level of significance. results indicate that plots of both tests are within critical bounds at a 5% level of significance. this shows that our selected models are correctly specified in the case of selected asian cities. -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 12 14 16 18 20 22 24 26 28 30 32 34 36 38 cusum of squares 5% significance figure 2: year 2017 -16 -12 -8 -4 0 4 8 12 16 12 14 16 18 20 22 24 26 28 30 32 34 36 38 cusum 5% significance figure 1: year 2017 -20 -15 -10 -5 0 5 10 15 20 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 cusum 5% significance figure 3: year 2018 audi and ali: the role of environmental conditions and purchasing power parity in determining quality of life among big asian cities international journal of energy economics and policy | vol 13 • issue 3 • 2023 299 5. conclusions policy suggestions the article has investigated the influence of environmental conditions and purchasing power parity on the quality of life in selected asian cities. quality of life index (availability of housing, crime rates, death rate, average life expectancy, environmental degradation, and level of education) has been taken as regressand. level of pollution, availability of health care facilities, local purchasing power, availability of groceries, level of democracy, cost of living, restaurants, level of traffic, and level of rents are selected regressors. the empirical analysis is based on 42 cities in asia for the years 2017, 2018, and 2019 have been selected. the results show that level of pollution, level of traffic, and level of rent has a negative and significant impact on the quality of life in asian cities. availability of health care facilities had an insignificant impact on quality of life during 2017, it has a positive and significant impact on quality of life during the years 2018 and 2019. the results show that local purchasing power has a positive and significant impact on the quality of life in the case of asian cities. availability of groceries has a positive but insignificant impact on quality of life during the years 2017 and 2018, but this relationship turns negative and significant during the year 2019. the level of democracy and the cost of living has an insignificant impact on the quality of life in asian cities. cost of living has a positive and significant impact on the quality of life of asian cities during the year 2019. restaurants have a positive and significant impact on quality of life but this relationship turns insignificant during the year 2019. the overall results conclude that selected independent variables play a significant role in determining the quality of life in asian cities. based on estimated results, there are some policy suggestions drawn for improving the quality of life in asian cities. based on the results, it is suggested that asian governments should take serious steps to reduce levels of pollution for attaining a higher level of quality of life. health cares is one of the basic needs of the general public. so, if the health care system of selected cities can be improved a higher quality of life can be achieved. the purchasing power of the currency is directly attached to investment and the level of employment in the country. thus, by enhancing purchasing power the overall higher quality of life in asian cities can be attained. moreover, the government provides charity funds and other monetary benefits to the people, which enhance the purchasing power of the masses. this study suggests that by lowering the cost of living, the level of quality of life can be increased. as with the higher cost of living, the people are unable to meet their necessities. for this purpose, governments of these cities provide subsidies on basic needs, so with the higher cost of living people can afford necessities. as restaurants have a positive and significant impact on quality of life, this reveals that for a higher quality of life the standard of restaurants can be improved. for the improvement of restaurants, the city government of selected cities should properly check the standards of restaurants. although, numerous cities have separate departments for this purpose, and for the improvements of the restaurants these departments should improve their working efficiency. the quality of life environment is directly impacted by the quality of the environment, and the environment is directly impacted by the level of traffic. so, for the improvement in environmental quality, the level of traffic can be reduced. for this purpose, the governments of the selected cities can motivate their people to use public transport rather than private one, this will reduce the number of vehicles on the road and the level of environmental degradation comes down. moreover, the fuel-efficient and environment-friendly technology of the vehicles should be encouraged and fuel inefficient, environmentally unfriendly, and outdated vehicles should be discouraged in asian cities. references abuaf, n., jorion, p. (1990), purchasing power parity in the long run. the journal of finance, 45(1), 157-174. ahmad, n., yamano, n. (2011), carbon dioxide emissions embodied -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 cusum of squares 5% significance figure 4: year 2018 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 cusum of squares 5% significance figure 6: year 2019 -20 -15 -10 -5 0 5 10 15 20 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 cusum 5% significance figure 5: year 2019 audi and ali: the role of environmental conditions and purchasing power parity in determining quality of life among big asian cities international journal of energy economics and policy | vol 13 • issue 3 • 2023300 in goods and services: domestic consumption versus production. oecd statistics directorate working papers. paris: oecd. [forthcoming]. aivazian, s.a. (2016), quality of life and living standards analysis. in: quality of life and living standards analysis. germany: de gruyter. ali, a. (2015), the impact of macroeconomic instability on social progress: an empirical analysis of pakistan. (doctoral dissertation, national college of business administration and economics lahore). ali, a. (2018), issue of income inequality under the perceptive of macroeconomic instability: an empirical analysis of pakistan. pakistan economic and social review, 56(1), 121-155. ali, a., audi, m. (2016), the impact of income inequality, environmental degradation and globalization on life expectancy in pakistan: an empirical analysis. international journal of economics and empirical research (ijeer), 4(4), 182-193. ali, a., audi, m., bibi, c., roussel, y. (2021), the impact of gender inequality and environmental degradation on human well-being in the case of pakistan: a time series analysis. international journal of economics and financial issues, 11(2), 92-99. ali, a., bibi, c. (2017), determinants of social progress and its scenarios under the role of macroeconomic instability: empirics from pakistan. pakistan economic and social review, 55(2), 505-540. ali, a., rehman, h.u. (2015), macroeconomic instability and its impact on the gross domestic product: an empirical analysis of pakistan. pakistan economic and social review, 285-316. allin, s., grignon, m., le grand, j. (2010), subjective unmet need and utilization of health care services in canada: what are the equity implications? social science and medicine, 70(3), 465-472. amaghionyeodiwe, l.a. (2009), government health care spending and the poor: evidence from nigeria. international journal of social economics, 36, 220-236. anand, s., sen, a. (1994), human development index: methodology and measurement. (human development occasional papers). new york: human development report office. apte, p., kane, m., sercu, p. (1994), relative ppp in the medium run. journal of international money and finance, 13(5), 602-622. aragonés, j.i., amérigo, m., pérez-lópez, r. (2017), residential satisfaction and quality of life. in: handbook of environmental psychology and quality of life research. new york city: springer international publishing, p311-328. audi, m., ali, a. (2017), environmental degradation, energy consumption, population density and economic development in lebanon: a time series analysis (1971-2014). journal of international finance and economics, 17(1), 7-20. audi, m., ali, a. (2018), determinants of environmental degradation under the perspective of globalization: a panel analysis of selected mena nations. journal of academy of business and economics, 18(1), 149-166. balassa, b. (1964), the purchasing-power parity doctrine: a reappraisal. journal of political economy, 72(6), 584-596. balestra, c., tonkin, r. (2018), inequalities in household wealth across oecd countries: evidence from the oecd wealth distribution database. paris, france: oecd. banerjee, a.v., duflo, e. (2007), the economic lives of the poor. journal of economic perspectives, 21(1), 141-168. barma, n., kaiser, k., le, t.m., editors. (2012), rents to riches?: the political economy of natural resource-led development. washington, d.c.: world bank publications. bekő, j., kavkler, a. (2019), do real exchange rates in small central and eastern european economies obey purchasing power parity? international journal of sustainable economy, 11(2), 121-140. bell, b.s., kanar, a.m., kozlowski, s.w. (2008), current issues and future directions in simulation-based training in north america. the international journal of human resource management, 19(8), 1416-1434. beni, a.a., esmaeili, a. (2020), biosorption, an efficient method for removing heavy metals from industrial effluents: a review. environmental technology and innovation, 17, 100503. berleant, a. (1997), living in the landscape: toward an aesthetics of environment. theories of contemporary cultural. kansas, united states: university press of kansas. bernanke, b.s., mishkin, f.s. (1997), inflation targeting: a new framework for monetary policy? journal of economic perspectives, 11(2), 97-116. bloom, d.e., craig, p.h., malaney, p.n. (2001), the quality of life in rural asia. philippines: asian development bank. boskin, m.j. (1996), toward a more accurate measure of the cost of living. advisory commission to study the consumer price index. brajša-žganec, a., merkaš, m., šverko, i. (2011), quality of life and leisure activities: how do leisure activities contribute to subjective well-being? social indicators research, 102(1), 81-91. bronchetti, e.t., christensen, g., hoynes, h.w. (2019), local food prices, snap purchasing power, and child health. journal of health economics, 68, 102231. brown, r. l., durbin, j., & evans, j. m. (1975), techniques for testing the constancy of regression relationships over time. journal of the royal statistical society: series b (methodological), 37(2), 149-163. brunekreef, b., holgate, s.t. (2002), air pollution and health. the lancet, 360(9341), 1233-1242. bruzzone, f., cavallaro, f., nocera, s. (2021), the integration of passenger and freight transport for first-last mile operations. transport policy, 100, 31-48. buhaug, h., urdal, h. (2013), an urbanization bomb? population growth and social disorder in cities. global environmental change, 23(1), 1-10. byrne, j.p., diamond, m. (2007), affordable housing, land tenure, and urban policy: the matrix revealed. fordham urban law journal, 34, 527. cella, d.f. (1992), quality of life: the concept. journal of palliative care, 8(3), 8-13. cella, d.f. (1994), quality of life: concepts and definition. journal of pain and symptom management, 9(3), 186-192. centers for disease control and prevention (cdc). (2010), vital signs: colorectal cancer screening among adults aged 50-75 years-united states, 2008. mmwr morb mortal wkly rep, 59(26), 808-12. cervero, r., guerra, e., al, s. (2017), beyond mobility: planning cities for people and places. washington, d.c.: island press. chang, a., chu, y.h., welsh, b. (2013), southeast asia: sources of regime support. journal of democracy, 24(2), 150-164. chang, e.c., chu, y.h. (2006), corruption and trust: exceptionalism in asian democracies? the journal of politics, 68(2), 259-271. chen, m., hu, x. (2018), linkage between consumer price index and purchasing power parity: theoretic and empirical study. the journal of international trade and economic development, 27(7), 729-760. chin, e.m.l.s. (2001), purchasing power: black kids and american consumer culture. minnesota: university of minnesota press. chmelarova, v., nath, h.k. (2008), do regions matter for the behavior of city relative prices in the us? economics and international business working paper no. shsu_eco_wp08-03, sam houston state university. coakley, j., flood, r.p., fuertes, a.m., taylor, m.p. (2005), purchasing power parity and the theory of general relativity: the first tests. journal of international money and finance, 24(2), 293-316. coan, t.g., holman, m.r. (2008), voting green. social science quarterly, 89(5), 1121-1135. cohen, j.a., mannarino, a.p., knudsen, k. (2004), treating childhood audi and ali: the role of environmental conditions and purchasing power parity in determining quality of life among big asian cities international journal of energy economics and policy | vol 13 • issue 3 • 2023 301 traumatic grief: a pilot study. journal of the american academy of child and adolescent psychiatry, 43(10), 1225-1233. cohen, l.h., gunthert, k.c., butler, a.c., o’neill, s.c., tolpin, l.h. (2005), daily affective reactivity as a prospective predictor of depressive symptoms. journal of personality, 73(6), 1687-1714. coleman, r. p., rainwater, l., & mcclelland, k. a. (1979), social standing in america: new dimensions of class. taylor & francis. coletto, m., esuli, a., lucchese, c., muntean, c.i., nardini, f.m., perego, r., renso, c. (2017), perception of social phenomena through the multidimensional analysis of online social networks. online social networks and media, 1, 14-32. collier, p., van der ploeg, r., spence, m., venables, a.j. (2010), managing resource revenues in developing economies. imf staff papers, 57(1), 84-118. cooper, c.l., dewe, p.j., dewe, p.j., o’driscoll, m.p., o’driscoll, m.p. (2001), organizational stress: a review and critique of theory, research, and applications. thousand oaks, ca: sage publications. costanza, r., fisher, b., ali, s., beer, c., bond, l., boumans, r., snapp, r. (2007), quality of life: an approach integrating opportunities, human needs, and subjective well-being. ecological economics, 61(2-3), 267-276. craigwell, r., bynoe, d., lowe, s. (2012), the effectiveness of government expenditure on education and health care in the caribbean. international journal of development issues, 11(1), 4-18. dasgupta, p. (1990), well-being and the extent of its realisation in poor countries. the economic journal, 100(400), 1-32. dasgupta, p., weale, m. (1992), on measuring the quality of life. world development, 20(1), 119-131. de estado, c. (2013), sala de lo contencioso administrativo, sección tercera. sentencia del, 6, 13-232. de mello, l., pisu, m. (2009), the effectiveness of education and health spending among brazilian municipalities. oecd economic department working papers, 712. paris, france: oecd publishing. demissie, m.g., phithakkitnukoon, s., sukhvibul, t., antunes, f., gomes, r., bento, c. (2016), inferring passenger travel demand to improve urban mobility in developing countries using cell phone data: a case study of senegal. ieee transactions on intelligent transportation systems, 17(9), 2466-2478. devereux, m.p., griffith, r. (2003), evaluating tax policy for location decisions. international tax and public finance, 10(2), 107-126. diener, e., biswas-diener, r. (2002), will money increase subjective well-being? social indicators research, 57(2), 119-169. diener, e., diener, c. (1995), the wealth of nations revisited: income and quality of life. social indicators research, 36(3), 275-286. diener, e., oishi, s. (2000), money and happiness: income and subjective well-being across nations. in: culture and subjective well-being. united states: mit press, p185-218. diener, e., suh, e.m. (2003), 22-national differences in subjective wellbeing. in: well-being: the foundations of hedonic psychology. new york: russell sage foundation. diener, e.d., suh, m.e. (1997), subjective well-being and age: an international analysis. annual review of gerontology and geriatrics, 17(1), 304-324. douglas, i. (2012), urban ecology and urban ecosystems: understanding the links to human health and well-being. current opinion in environmental sustainability, 4(4), 385-392. downs, a. (2005), still stuck in traffic: coping with peak-hour traffic congestion. washington, d.c.: brookings institution press. dreger, c., kosfeld, r. (2010), do regional price levels converge? jahrbücher für nationalökonomie und statistik, 230(3), 274-286. drewnowski, a., evans, w.j. (2001), nutrition, physical activity, and quality of life in older adults: summary. the journals of gerontology series a: biological sciences and medical sciences, 56(suppl_2), 89-94. duesenberry, j.s. (1949), income, saving, and the theory of consumer behavior. cambridge: harvard university press. durand, m. (2015), the oecd better life initiative: how’s life? and the measurement of well‐being. review of income and wealth, 61(1), 4-17. elizur, d., shye, s. (1990), quality of work life and its relation to quality of life. applied psychology, 39(3), 275-291. engel, c., rogers, j. (1994), relative returns on equities in pacific basin countries. cambridge: national bureau of economic research, inc. engel, c., rogers, j.h. (2001), deviations from purchasing power parity: causes and welfare costs. journal of international economics, 55(1), 29-57. engineer, a. (2008), the rights of women in islam. uttar pradesh: sterling publishers pvt. ltd. felce, d., perry, j. (1995), quality of life: its definition and measurement. research in developmental disabilities, 16(1), 51-74. felix, r., garcia-vega, j. (2012), quality of life in mexico: a formative measurement approach. applied research in quality of life, 7(3), 223-238. ferrans, c.e., zerwic, j.j., wilbur, j.e., larson, j.l. (2005), conceptual model of health‐related quality of life. journal of nursing scholarship, 37(4), 336-342. ferrer-i-carbonell, a. (2002), income and well-being (no. 02-019/3). tinbergen institute discussion paper. fisher, i. (2006), the purchasing power of money: its’ determination and relation to credit interest and crises. new york: cosimo, inc. forman, r.t., sperling, d., bissonette, j.a., clevenger, a.p., cutshall, c.d., dale, v.h., winter, t.c. (2003), road ecology: science and solutions. washington, d.c.: island press. frank, r.h. (1985), choosing the right pond: human behavior and the quest for status. oxford: oxford university press. frenkel, j.a. (1978), purchasing power parity: doctrinal perspective and evidence from the 1920s. journal of international economics, 8(2), 169-191. frenkel, j.a. (1981), the collapse of purchasing power parities during the 1970’s. european economic review, 16(1), 145-165. gelb, a., diofasi, a. (2016), what determines purchasing-power-parity exchange rates? revue d economie du developpement, 24(2), 93-141. glaeser, e. (2011), cities, productivity, and quality of life. science, 333(6042), 592-594. glaeser, e.l., gottlieb, j.d. (2009), the wealth of cities: agglomeration economies and spatial equilibrium in the united states. journal of economic literature, 47(4), 983-1028. greco, f., polli, a. (2021), security perception and people well-being. social indicators research, 153(2), 741-758. guesalaga, r., marshall, p. (2008), purchasing power at the bottom of the pyramid: differences across geographic regions and income tiers. journal of consumer marketing, 25(7), 413-418. gustafsson, i.b., öström, å., johansson, j., mossberg, l. (2006), the five aspects meal model: a tool for developing meal services in restaurants. journal of foodservice, 17(2), 84-93. haidar, j.i. (2011), currency valuation and purchasing power parity. world economics journal, 12(3), 1-12. hansen, b. e. (1996), inference when a nuisance parameter is not identified under the null hypothesis. econometrica: journal of the econometric society, 413-430. hartwell, h., edwards, j. (2009), descriptive menus and branding in hospital foodservice: a pilot study. international journal of contemporary hospitality management, 21(7), 906. headey, b., wearing, a. (1989), personality, life events, and subjective well-being: toward a dynamic equilibrium model. journal of personality and social psychology, 57(4), 731. audi and ali: the role of environmental conditions and purchasing power parity in determining quality of life among big asian cities international journal of energy economics and policy | vol 13 • issue 3 • 2023302 hossain, m., fischer, k.s. (1995), rice research for food security and sustainable agricultural development in asia: achievements and future challenges. geojournal, 35(3), 286-298. huang, h.c., wang, c.w., miao, y.c. (2011), securitisation of crossover risk in reverse mortgages. the geneva papers on risk and insuranceissues and practice, 36(4), 622-647. huang, y., chen, q., deng, m., japenga, j., li, t., yang, x., he, z. (2018), heavy metal pollution and health risk assessment of agricultural soils in a typical peri-urban area in southeast china. journal of environmental management, 207, 159-168. hyde, m., wiggins, r.d., higgs, p., blane, d.b. (2003), a measure of quality of life in early old age: the theory, development and properties of a needs satisfaction model (casp-19). aging and mental health, 7(3), 186-194. johansen, f. (1993), poverty reduction in east asia. world bank discussion papers, united states: world bank. kahn, m.e., matsusaka, j.g. (1997), demand for environmental goods: evidence from voting patterns on california initiatives. the journal of law and economics, 40(1), 137-174. kant, i. (1785), von der unrechtmäßigkeit des büchernachdrucks. berlinische monatsschrift, 5, 403-417. kaplan, r.m. (2003), the significance of quality of life in health care. quality of life research, 12(1), 3-16. karimi, m., brazier, j. (2016), health, health-related quality of life, and quality of life: what is the difference? pharmacoeconomics, 34(7), 645-649. kautonen, t., kibler, e., minniti, m. (2017), late-career entrepreneurship, income and quality of life. journal of business venturing, 32(3), 318-333. kelley-gillespie, n. (2009), an integrated conceptual model of quality of life for older adults based on a synthesis of the literature. applied research in quality of life, 4(3), 259-282. kim, k.h., kabir, e., jahan, s.a. (2017), exposure to pesticides and the associated human health effects. science of the total environment, 575, 525-535. kosack, s. (2003), effective aid: how democracy allows development aid to improve the quality of life. world development, 31(1), 1-22. kurlantzick, j. (2013), democracy in retreat: the revolt of the middle class and the worldwide decline of representative government. new haven, connecticut: yale university press. lagadec, n., steinecker, m., kapassi, a., magnier, a.m., chastang, j., robert, s., ibanez, g. (2018), factors influencing the quality of life of pregnant women: a systematic review. bmc pregnancy and childbirth, 18(1), 455. lawton, m.p., winter, l., kleban, m.h., ruckdeschel, k. (1999), affect and quality of life: objective and subjective. journal of aging and health, 11(2), 169-198. layard, r. (1980), human satisfactions and public policy. the economic journal, 90(360), 737-750. liao, p.s. (2009), parallels between objective indicators and subjective perceptions of quality of life: a study of metropolitan and county areas in taiwan. social indicators research, 91(1), 99-114. liere, k.d.v., dunlap, r.e. (1980), the social bases of environmental concern: a review of hypotheses, explanations and empirical evidence. public opinion quarterly, 44(2), 181-197. lim, k., taylor, l. (2005), factors associated with physical activity among older people-a population-based study. preventive medicine, 40(1), 33-40. lucan, s.c., mitra, n. (2012), the food environment and dietary intake: demonstrating a method for gis-mapping and policy-relevant research. journal of public health, 20(4), 375-385. macke, j., casagrande, r.m., sarate, j.a.r., silva, k.a. (2018), smart city and quality of life: citizens’ perception in a brazilian case study. journal of cleaner production, 182, 717-726. mathew, j., goyal, r., taneja, k.k., arora, n. (2013), environmental and occupational respiratory diseases-1057. correlation between air pollution and respiratory health of school children in delhi. world allergy organization journal, 6(1), 55. mccracken, v.a., brandt, j.a. (1987), household consumption of food‐ away‐from‐home: total expenditure and by type of food facility. american journal of agricultural economics, 69(2), 274-284. mccrea, r., shyy, t.k., stimson, r. (2006), what is the strength of the link between objective and subjective indicators of urban quality of life? applied research in quality of life, 1(1), 79-96. mcgillivray, m. (2007), human well-being: issues, concepts and measures. in: human well-being. london: palgrave macmillan, p1-22. mckee-ryan, f., song, z., wanberg, c.r., kinicki, a.j. (2005), psychological and physical well-being during unemployment: a meta-analytic study. journal of applied psychology, 90(1), 53. mckenzie, l.m., witter, r.z., newman, l.s., adgate, j.l. (2012), human health risk assessment of air emissions from development of unconventional natural gas resources. science of the total environment, 424, 79-87. mehta, n.k., chang, v.w. (2008), weight status and restaurant availability: a multilevel analysis. american journal of preventive medicine, 34(2), 127-133. mouratidis, k. (2021), urban planning and quality of life: a review of pathways linking the built environment to subjective well-being. cities, 115, 103229. murphy, m. (2014), self-determination as a collective capability: the case of indigenous peoples. journal of human development and capabilities, 15(4), 320-334. myers, d. (1988), building knowledge about quality of life for urban planning. journal of the american planning association, 54(3), 347-358. neirotti, p., de marco, a., cagliano, a.c., mangano, g., scorrano, f. (2014), current trends in smart city initiatives: some stylised facts. cities, 38, 25-36. neulinger, a., bársony, f., gjorevska, n., lazányi, o., pataki, g., takács, s., török, a. (2020), engagement and subjective well‐being in alternative food networks: the case of hungary. international journal of consumer studies, 44(4), 306-315. newman, p., kenworthy, j. (2013), greening urban transportation. in: state of the world 2007. england, uk: routledge. p98-121. nordhaus, w.d., tobin, j. (1973), is growth obsolete? in: the measurement of economic and social performance. cambridge: nber, p509-564. novaco, r.w., gonzalez, o.i. (2009), commuting and well-being. technology and well-being, 3, 174. ohta, r., sato, m., kitayuguchi, j., maeno, t., sano, c. (2021), the association between the self-management of mild symptoms and quality of life of elderly populations in rural communities: a crosssectional study. international journal of environmental research and public health, 18(16), 8857. osbaldiston, r., sheldon, k.m. (2003), promoting internalized motivation for environmentally responsible behavior: a prospective study of environmental goals. journal of environmental psychology, 23(4), 349-357. parra, d.c., gomez, l.f., sarmiento, o.l., buchner, d., brownson, r., schimd, t., lobelo, f. (2010), perceived and objective neighborhood environment attributes and health related quality of life among the elderly in bogota, colombia. social science and medicine, 70(7), 1070-1076. piazzesi, m., schneider, m., tuzel, s. (2007), housing, consumption and asset pricing. journal of financial economics, 83(3), 531-569. audi and ali: the role of environmental conditions and purchasing power parity in determining quality of life among big asian cities international journal of energy economics and policy | vol 13 • issue 3 • 2023 303 pires-júnior, r., coledam, d.h.c., de aguiar greca, j.p., de arruda, g.a., teixeira, m., de oliveira, a.r. (2018), physical fitness and healthrelated quality of life in brazilian adolescents: a cross-sectional study. human movement, 19(2), 3-10. popkin, b.m., adair, l.s., ng, s.w. (2012), global nutrition transition and the pandemic of obesity in developing countries. nutrition reviews, 70(1), 3-21. popova, y. (2017), relations between wellbeing and transport infrastructure of the country. procedia engineering, 178, 579-588. prüss-üstün, a., corvalán, c. (2006), preventing disease through healthy environments. towards an estimate of the environmental burden of disease. geneva: world health organization. rainwater, l. (1990), poverty and equivalence as social constructions (no. 55). lis working paper series. rapley, m. (2003), quality of life research: a critical introduction. thousand oaks, california: sage. rasheed, s., woods, r.t. (2013), malnutrition and quality of life in older people: a systematic review and meta-analysis. ageing research reviews, 12(2), 561-566. ravallion, m., lokshin, m. (2001), identifying welfare effects from subjective questions. economica, 68(271), 335-357. reif, j., szarvas, f., šťastný, k. (2021), ‘tell me where the birds have gone’-reconstructing historical influence of major environmental drivers on bird populations from memories of ornithologists of an older generation. ecological indicators, 129, 107909. reif, a., rumler, f. (2014), within-and cross-country price dispersion in the euro area. ecb working paper series no. 1742. renwick, l., drennan, j., sheridan, a., owens, l., lyne, j., o’donoghue, b., clarke, m. (2017), subjective and objective quality of life at first presentation with psychosis. early intervention in psychiatry, 11(5), 401-410. rinklebe, j., antoniadis, v., shaheen, s.m., rosche, o., altermann, m. (2019), health risk assessment of potentially toxic elements in soils along the central elbe river, germany. environment international, 126, 76-88. roback, j. (1982), wages, rents, and the quality of life. journal of political economy, 90(6), 1257-1278. rogoff, k. (1996), the purchasing power parity puzzle. journal of economic literature, 34(2), 647-668. rowley, s., ong, r. (2012), housing affordability, housing stress and household wellbeing in. mental health, 76(69), 67. ruggeri, m., warner, r., bisoffi, g., fontecedro, l. (2001), subjective and objective dimensions of quality of life in psychiatric patients: a factor analytical approach: the south verona outcome project 4. the british journal of psychiatry, 178(3), 268-275. sadalla, e., editor. (2005), the us-mexican border environment: dynamics of human-environment interactions. vol. 11. united states: scerp and irsc publications. sarvimäki, a., stenbock‐hult, b. (2000), quality of life in old age described as a sense of well‐being, meaning and value. journal of advanced nursing, 32(4), 1025-1033. saxena, s., thornicroft, g., knapp, m., whiteford, h. (2007), resources for mental health: scarcity, inequity, and inefficiency. the lancet, 370(9590), 878-889. schor, j.b. (1998), the overspent american: upscaling, downshifting, and the new consumer. new york: basic books. p272. schroeter, c., lusk, j., tyner, w. (2008), determining the impact of food price and income changes on body weight. journal of health economics, 27(1), 45-68. scitovsky, t. (1976), the joyless economy: an inquiry into human satisfaction and consumer dissatisfaction. new york: oxford university press. sen, a. (1992), the political economy of targeting. washington, d.c.: world bank. serletis, a., gogas, p. (2004), long-horizon regression tests of the theory of purchasing power parity. journal of banking and finance, 28(8), 1961-1985. shapiro, j.m. (2006), smart cities: quality of life, productivity, and the growth effects of human capital. the review of economics and statistics, 88(2), 324-335. shin, d.c., johnson, d.m. (1978), avowed happiness as an overall assessment of the quality of life. social indicators research, 5(1), 475-492. silvester, k., lendon, r., bevan, h., steyn, r., walley, p. (2004), reducing waiting times in the nhs: is lack of capacity the problem? clinician in management, 12(3), 20-29. smith, k.w., avis, n.e., assmann, s.f. (1999), distinguishing between quality of life and health status in quality of life research: a metaanalysis. quality of life research, 8(5), 447-459. solberg, ø., sengoelge, m., johnson-singh, c.m., vaez, m., eriksson, a.k., saboonchi, f. (2022), health-related quality of life in refugee minors from syria, iraq and afghanistan resettled in sweden: a nation-wide, cross-sectional study. social psychiatry and psychiatric epidemiology, 57(2), 255-266. stone, w., sharam, a., wiesel, i., ralston, l., markkanen, s., james, a. (2015), accessing and sustaining private rental tenancies: critical life events, housing shocks and insurances. ahuri final report. melbourne: australian housing and urban research institute limited. p259. suzuki, h., murakami, j., hong, y.h., tamayose, b. (2015), financing transit-oriented development with land values: adapting land value capture in developing countries. washington, d.c.: world bank publications. tan, k.g., chuah, h.y., luu, n.t.d. (2018), a case study on malaysia and singapore: nexus amongst competitiveness, cost of living, wages, purchasing power and live ability. competitiveness review: an international business journal, 28, 172-179. tang, t.l.p. (2007), income and quality of life: does the love of money make a difference? journal of business ethics, 72(4), 375-393. taylor, a.m., taylor, m.p. (2004), the purchasing power parity debate. journal of economic perspectives, 18(4), 135-158. taylor, s.e., brown, j.d. (1988), illusion and well-being: a social psychological perspective on mental health. psychological bulletin, 103(2), 193. testa, m.a., nackley, j.f. (1994), methods for quality-of-life studies. annual review of public health, 15(1), 535-559. thøgersen, j. (2006), norms for environmentally responsible behaviour: an extended taxonomy. journal of environmental psychology, 26(4), 247-261. tobin, j., nordhaus, w.d. (1972), economic growth. cambridge: national bureau of economic research. todaro, m.p., smith, s.c. (2020), economic development. london, united kingdom: pearson. tov, w., diener, e. (2009), the well-being of nations: linking together trust, cooperation, and democracy. in: the science of well-being. dordrecht: springer. p155-173. unece. (2009), measuring sustainable development. new york/ geneva: united nation economic commission for europe united nations publication. united nations development program (undp). (1990), human development report 1990. new york: oxford university press. valin, h., sands, r.d., van der mensbrugghe, d., nelson, g.c., ahammad, h., blanc, e., willenbockel, d. (2014), the future of food demand: understanding differences in global economic models. agricultural economics, 45(1), 51-67. van aardenne, j.a., carmichael, g.r., levy ii, h., streets, d., hordijk, l. audi and ali: the role of environmental conditions and purchasing power parity in determining quality of life among big asian cities international journal of energy economics and policy | vol 13 • issue 3 • 2023304 (1999), anthropogenic nox emissions in asia in the period 19902020. atmospheric environment, 33(4), 633-646. veenhoven, r. (1993), happiness in nations. subjective appreciation of life in 56 nations 1946-1992. rotterdam: erasmus university rotterdam. ventegodt, s., merrick, j., andersen, n.j. (2003), quality of life theory i. the iqol theory: an integrative theory of the global quality of life concept. the scientific world journal, 3, 1030-1040. wen, l., kenworthy, j., guo, x., marinova, d. (2019), solving traffic congestion through street renaissance: a perspective from dense asian cities. urban science, 3(1), 18. williams, b. (2009), philosophy as a humanistic discipline. in: philosophy as a humanistic discipline. united states: princeton university press. wong, t.k.y., wan, p.s., hsiao, h.h.m. (2011), the bases of political trust in six asian societies: institutional and cultural explanations compared. international political science review, 32(3), 263-281. world health organization. (2002), the world health report 2002: reducing risks, promoting healthy life. geneva: world health organization. world health organization. (2012), health in the green economy: health co-benefits of climate change mitigation-transport sector. geneva: world health organization. world health organization. (2014), global status report on noncommunicable diseases 2014 (no. who/nmh/nvi/15.1). geneva: world health organization. wu, w. (2004), sources of migrant housing disadvantage in urban china. environment and planning a, 36(7), 1285-1304. ya-wen, c., hsiao, s. (2006), quality of life: scaling with maslow’s need hierarchy. gerontology, 52(6), 376. zezza, a., tasciotti, l. (2010), urban agriculture, poverty, and food security: empirical evidence from a sample of developing countries. food policy, 35(4), 265-273. zheng, y. (2010), association analysis on pro-environmental behaviors and environmental consciousness in main cities of east asia. behaviormetrika, 37(1), 55-69. table a: descriptive statistic ql pi hci ppi gi dm cli rii ti ri mean (2017) 104.6724 70.30462 67.09143 78.16987 44.33133 0.743590 45.63669 33.57515 189.0997 23.21733 mean (2018) 104.7119 71.91448 66.28445 68.44116 45.56605 0.813953 46.67628 35.23814 186.4379 21.20884 mean (2019) 115.8748 71.53800 65.62095 62.14976 39.68762 0.785714 42.48667 33.03024 178.8988 18.91548 med (2017) 104.4700 75.57000 67.99000 80.59000 43.02000 1.000000 43.47000 28.25000 167.6600 14.84000 med (2018) 104.7800 75.07000 67.36000 56.89000 37.48000 1.000000 40.97000 29.18000 162.9300 12.10000 med (2019) 112.6200 76.96000 67.17000 56.05500 34.27000 1.000000 38.02500 26.62500 172.7500 12.46500 max (2017) 188.4800 95.35000 86.96000 184.0900 91.92000 1.000000 83.67000 89.20000 366.7900 82.57000 max (2018) 188.4800 94.60000 85.73000 129.2000 107.0600 1.000000 93.81000 97.21000 366.7900 79.54000 max (2019) 174.0400 93.21000 85.38000 135.9600 97.22000 1.000000 88.45000 86.44000 283.6800 76.83000 min (2017) 31.41000 18.45000 35.88000 26.39500 25.20000 0.000000 24.06000 13.87000 85.78000 5.730000 min (2018) 24.13000 24.90000 36.67000 27.62000 24.65000 0.000000 25.46000 16.04000 85.78000 5.700000 min (2019) 65.11000 27.21000 36.87000 26.24000 19.21000 0.000000 21.58000 15.83000 95.94000 4.580000 s.d (2017) 40.29644 18.69303 11.68147 38.33626 17.61380 0.442359 17.50942 17.30736 67.24994 21.68495 s.d (2018) 41.41297 17.21894 11.72955 30.39780 21.20206 0.393750 19.69294 17.67874 68.44578 19.51739 s.d (2019) 32.76304 17.24454 10.01587 28.94254 18.62143 0.415300 17.89212 15.92315 55.29497 15.89434 skew (2017) −0.015534 −0.908954 −0.497182 0.729451 0.997842 −1.115718 0.736190 1.374765 0.507416 1.597806 skew (2018) −0.121584 −0.883579 −0.659579 0.364454 1.360427 −1.613559 1.093440 1.503164 0.658396 1.678162 skew (2019) 0.239282 −0.905487 −0.432997 0.889151 1.491108 −1.392621 0.996888 1.307787 0.470625 1.598025 kurtosis (2017) 2.280672 3.260371 3.527305 3.008179 3.454726 2.244828 2.544235 4.484521 2.601466 4.449991 kurtosis (2018) 2.280334 3.129392 3.221381 1.827880 3.962438 3.603571 3.085996 4.969441 2.621423 4.822596 kurtosis (2019) 1.926570 2.973072 3.422534 2.984470 4.678774 2.939394 3.070961 4.323392 2.191553 5.623537 j-bera (2017) 0.820797 5.480451 2.058569 3.458749 6.807982 9.018093 3.860386 15.86605 1.931661 20.01091 j-bera (2018) 1.033881 5.625097 3.205631 3.413437 14.92340 19.31163 8.581796 23.14242 3.363429 26.13463 j-bera (2019) 2.417233 5.740613 1.624843 5.534543 20.49581 13.58219 6.965316 15.03704 2.694193 29.92095 ob. (2017) 39 39 39 39 39 39 39 39 39 39 ob. (2018) 43 43 43 43 43 43 43 43 43 43 ob. (2019) 42 42 42 42 42 42 42 42 42 42 appendix audi and ali: the role of environmental conditions and purchasing power parity in determining quality of life among big asian cities international journal of energy economics and policy | vol 13 • issue 3 • 2023 305 table c: diagnostics test-year 2017 breusch-godfrey serial correlation lm test: f-statistic 1.692909 prob. f (2,26) 0.2036 obs*r-squared 4.378340 prob. chi-square (2) 0.1120 heteroskedasticity test: breusch-pagan-godfrey f-statistic 0.831333 prob. f (9,28) 0.5936 obs*r-squared 8.012960 prob. chi-square (9) 0.5328 scaled explained ss 3.348587 prob. chi-square (9) 0.9489 table e: diagnostics test-year 2019 breusch-godfrey serial correlation lm test f-statistic 0.008802 prob. f (1.31) obs*r-squared 0.011922 prob. chi-square (1) heteroskedasticity test: breusch-pagan-godfrey f-statistic 0.605927 prob. f (9.32) obs*r-squared 6.115353 prob. chi-square (9) scaled explained ss 5.305575 prob. chi-square (9) table b: correlation matrix variables ql pi hci ppi gi dm cli rii ti pi (2017) −0.577210*** hci (2017) 0.43290*** −0.520*** lppi (2017) 0.272333* −0.140107 0.117120 gi (2017) 0.154722 −0.416183 0.31510** 0.227488 dm (2017) −0.178861 0.160104 −0.069714 −0.4005** −0.682*** cli (2017) 0.240171 −0.432*** 0.296211* 0.254556 0.9379*** −0.732*** rii (2017) 0.319105* −0.3334** 0.184361 0.199080 0.6689*** −0.609*** 0.8590*** ti (2017) −0.5282*** 0.40749** −0.244757 0.022788 −0.246801 0.167364 −0.305962 −0.30724* ri (2017) 0.064473 −0.29217* 0.086951 0.32521** 0.82533** −0.765*** 0.8643*** 0.7346*** −0.210953 pi (2018) −0.5632*** hci (2017) 0.49938*** −0.38020** ppi (2018) 0.52509*** −0.4328*** 0.37890** gi (2018) 0.233748 −0.5383*** 0.4807*** 0.4357*** dm (2018) −0.236462 0.233587 −0.158753 −0.4118*** −0.4784*** cli (2018) 0.274144* −0.5291*** 0.4250*** 0.4580*** 0.9441*** −0.5977*** rii (2018) 0.32729** −0.3931*** 0.253219 0.4437*** 0.6545*** −0.6161*** 0.8463*** ti (2018) −0.5456*** 0.4934*** −0.23918 −0.164771 −0.2661* 0.165474 −0.2781* −0.243161 ri (2018) 0.097941 −0.3605** 0.179911 0.4748*** 0.7247*** −0.6774*** 0.8244*** 0.8017*** −0.180699 pi (2019) −0.7259*** hci (2019) 0.4961*** −0.4283*** ppi (2019) 0.6645*** −0.4166*** 0.4231*** gi (2019) 0.28689* −0.4565*** 0.5051*** 0.3740** dm (2019) −0.108014 0.137562 −0.16677 −0.4139*** −0.4717*** cli (2019) 0.3775** −0.4745*** 0.4217*** 0.4652*** 0.9449*** −0.5694*** rii (2019) 0.4143*** −0.4280*** 0.19493 0.5323*** 0.6656*** −0.6088*** 0.8404*** ti (2019) −0.5274*** 0.3751** −0.02317 −0.18668 −0.202181 0.040147 −0.230312 −0.191029 ri (2019) 0.201781 −0.3691** 0.24311 0.4905*** 0.7417*** −0.6832*** 0.8203*** 0.7526*** −0.151503 ***1% significant level **5% significant level *10% significant level table d: diagnostics test-year 2018 breusch-godfrey serial correlation lm test f-statistic 0.195141 prob. f (2,31) 0.8237 obs*r-squared 0.534629 prob. chi-square (2) 0.7654 heteroskedasticity test: breusch-pagan-godfrey f-statistic 1.067395 prob. f (9,33) 0.4115 obs*r-squared 9.695267 prob. chi-square (9) 0.3757 scaled explained ss 7.465962 prob. chi-square (9) 0.5887 tx_1~at/tx_2~at international journal of energy economics and policy | vol 11• issue 3 • 2021 529 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(3), 529-536. computer analysis of energy and resource efficiency in the context of transformation of petrochemical supply chains alexey i. shinkevich1*, farida f. galimulina1, yulia s. polozhentseva2, alla a. yarlychenko1, naira v. barsegyan1 1department of logistics and management, kazan national research technological university, kazan, russian federation, 2department of regional economics and management, southwestern state university, kursk, russian federation. *email: ashinkevich@mail.ru received: 04 january 2021 accepted: 06 march 2021 doi: https://doi.org/10.32479/ijeep.11270 abstract the purpose of this study is to identify areas of energy-efficient development in petrochemical supply chains through the use of computer analysis tools. the study uses system approach methods, comparisons, vertical dynamic analysis, economic and mathematical modeling, forecasting, factor analysis. listed implementation methods helps to meet number of scientific results: systematized programs are applicable for petrochemical product supply management chains, as well as for a number of methods and algorithms developed by the authors in the framework of ensuring resource-saving development of petrochemical enterprises; dynamics assessment of supply chains' petrochemical products in terms of energy consumption and energy efficiency consumption indicators; a production function expressed in the form of dependence of the production energy efficiency between the factors of capital (costs per 1 ruble of sold products) and labor (labor intensity) is proposed, allowing rational planning in the parameters of the production and logistics system of the pjsc “nizhnekamskneftekhim” enterprise; a factorial model is developed, as a result of which two factors (energy and economic) formed energy resource efficiency indicator of petrochemical supply chains is proposed. as a result, promising directions for reducing energy intensity production and improving of supply chains for petrochemical products energy efficiency are identified. keywords: petrochemical products, supply chains, energy resource efficiency, energy saving, energy intensity of production jel classifications: о14, d24, с41 1. introduction the economy’s petrochemical sector presents a particular interest to government bodies in the context of all levels of the country’s economic system. this is due to high potential of sector’s enterprises in terms of the production of competitive products as a result of deep processing of hydrocarbons. these products, in turn, are subject to sale in domestic and foreign markets and determine the volumes of the gross regional product and gross domestic product (kvon et al., 2019). thus, it seems obvious that it is necessary to analyze microeconomic systems that determine the importance of petrochemical enterprises efficiency increase and the economic development of the corresponding region. the effectiveness of their functioning is due to many factors, in particular energy. in addition, during modern economic conditions pandemics, falling oil prices, reduced activity of related industries and industries that consume petrochemical products the strategic importance of resource consumption stregthens. changes in the procedure for exporting products due to restrictive measures and, as a result, an increase in delivery times, significantly strengthens the role of logistics, that is also being an active consumer of microeconomic system energy resources. this journal is licensed under a creative commons attribution 4.0 international license shinkevich, et al.: computer analysis of energy and resource efficiency in the context of transformation of petrochemical supply chains international journal of energy economics and policy | vol 11• issue 3 • 2021530 the foregoing determines the feasibility for diagnosis of energy intensity and energy efficiency in petrochemical enterprise. we believe that the study of the activities of pjsc “nizhnekamskneftekhim” a major consumer of energy resources among petrochemical enterprises may ensure the achievement of significant scientific results of practical interest. in this regard, the development of solutions set to improve subsystem of pjsc “nizhnekamskneftekhim” production and logistics energy efficiency seems to be relevant. energy efficiency as a subject of research for many years has been a deep interest for domestic and foreign scientists. approaches to the study of the issue are evolving, but the resulting aspect of energy consumption management is irreplaceable. a number of authors, in particular shi et al. (2010), bing and rui (2011), brunoroa et al. (2019), locmelis et al. (2019), a team led by farrou et al. (2020), explore energy conservation through a country-specific lens. particular attention is paid to the study of chemical plants’ energy efficiency meshalkin (2009), panarin and meshalkin (2008), meshalkin et al. (2019), bobkov et al. (2018). the specifics of the use of renewable energy sources in the petrochemical industry are disclosed in a study by dellano-paz et al. (2015). the idea of using clean energy sources, taking into account the need to assess the social effect as a result of energy efficiency, is justified in the study by dunlop (2019). directions for rationalizing energy consumption, taking into account investment features, are presented in the works of ayres et al. (2013). ensuring energy savings within microeconomic systems is reflected in the works of thiede et al. (2012), brahmana and ono (2020). despite the fact that production process is a key link in energy consumption industry, energy efficiency in the supply and transportation of products is also essential (shinkevich et al., 2020). a number of scientific works are also devoted to the study of energy efficiency in supply chains, including the works of kalenoja et al. (2011), demonstrating a system of indicators for assessing the energy efficiency of supply chains; marchi and zanoni (2017), who highlighted a methodological approach to energy management in supply chains and reflected a systematic view of improving energy efficiency. the practical implementation of energy-efficient technologies is based on preliminary modeling and computer analysis of energyefficient supply chains. so the issues of designing resource-saving processes in petrochemistry are also devoted to the works of meshalkin et al. (1997), moshev and meshalkin (2014) and others. at the same time, despite a wide range of scientific research in the field of improving energy efficiency, we consider it necessary to build economic and mathematical models that reflect the dependence between supply chain of petrochemical products economic efficiency energy factors and indicators at the microeconomic level. 2. description of data ensuring supply chains energy efficiency requires a systematic approach to the integration of a number of functional subsystems of an enterprise: production, logistics, information, etc. the solution to the problem is possible modernization of business processes organization in the supply chain, as well as automation and computer modeling. currently, there are a number of programs that make it possible to implement logical-informational and economic-mathematical modeling of organizing production and supply chains processes. petrochemical supply chain management is often based on the ibm decision optimization center (ibm) platform. the platform’s functionality allows you to develop and implement highly effective planning and scenario modeling based on the principles of mathematical optimization. the ibm ilog system is of practical interest due to the implementation of opportunities to reduce delivery costs, achieve reliability of supply, reliable operation of vehicles transporting petrochemical products, plan supply chain infrastructure, and optimize investments. the core of the decision optimization center is ilog cplex, which performs mathematical optimization calculations. the cplex cp module facilitates task solutions such as constraint programming, tasks for optimizing scheduling and resource plans. cplex parameters are numerous, and they may be divided into the following categories: general parameters (algorithm selection, logging level, etc.), triggering and reprocessing, simplex, barrier and network algorithm parameters, mip parameters (integer tasks). also, supply chains energy efficiency is facilitated by rational management of information flows a convenient visual view of data, a quick transition between numerous information directories. this is provided by means of visual programming visual basic for application (vba) of the ms access environment. logical-informational modeling of production organization processes of a petrochemical complex may be considered within the framework of the idef notation languages. we propose the development of scientific and technical mechanism at petrochemical enterprise by synthesizing such organizational and technical solutions as resource-saving technologies, production automation, infrastructure support, dcor-model and kpi system corresponding to auxiliary processes of the dcor-model (figure 1). the model is implemented by means of the all fusion process modeler program (case tool bpwin). the resulting model demonstrates how system, process or organization works. idef0 models both supply chain organization processes and quality process models. it is a software tool for transforming an idef0 model into a dynamic idef2 model and executing it for modeling and supply chain management; software tool for converting idef0 model to resource model; software tool for converting idef0 model to organizational model. in addition, supply chains energy-saving is facilitated by computer algorithms construction that provide economic and mathematical modeling using analytical programs excel, statistica. as part of the study, number of electronic resources were developed and registered. shinkevich, et al.: computer analysis of energy and resource efficiency in the context of transformation of petrochemical supply chains international journal of energy economics and policy | vol 11• issue 3 • 2021 531 1. an algorithm for economic and statistical modeling of enterprises scientific and technological development is focused on resource conservation, which includes stages of constructing production function of innovative goods volume and services from the cost of capital and labor in science. the model was built in order to develop a mechanism for modeling resource conservation in the petrochemical industry 2. an algorithm for constructing a model of a resource-saving function using independent multicomponent variables adequate to the digital economy is based on production function that takes into account the digital specifics of capital and labor resources 3. methodology for energy-resource-efficient reconstruction of an oil refinery based on pinch analysis takes into account external heat losses, containing a list of stages of the pinch analysis and recommendations for the reconstruction of a chemical technology system using software products 4. logical and informational models of business processes organization and production, and technological processes use the idef0 methodology, reflecting the detailing of the production process based on the scor model. for development of these provisions we consider it necessary to deepen the study of resource conservation issues towards efficient energy consumption within the framework of supply chain management for petrochemical products. the study is based on performance results systematization of large petrochemical enterprise pjsc “nizhnekamskneftekhim.” first, prices analysis for energy resources used by the enterprise for 2012-2018 is carried out, since the structure of the enterprise’s costs is determined by prices for resources (figure 2). the price dynamics is unstable. the most noticeable jump in prices was recorded in 2015 for fuel, when the price increase was 29.93%. the overall picture is characterized by an increase in energy prices by 2017, which undoubtedly determined the structure and value of the enterprise’s costs and becomes an objective reason for energy consumption rationalization in the supply chains of the company’s petrochemical products. figure 2: annual increase in energy prices in the supply chains of petrochemical products of pjsc “nizhnekamskneftekhim” figure 1: unified model of auxiliary processes for resource saving project preparation in the petrochemical industry second, energy costs and energy intensity dynamics of petrochemical products production was assessed (figure 3). there is a low dependence between the indicators: if in 2013 high values of energy consumption share in production costs and energy intensity were recorded, then in 2015 there was a clear gap between the indicators. on average, over the period under study, the rate of increase in energy consumption share was 0.45%, energy intensity 0.28%. in general, for 2012-2017, energy consumption share remained practically unchanged it increased by 2.39%, while energy intensity returned to the level of 0.13 rub./rub. despite the enterprise implementation of a set of measures aimed at energy saving, it should be noted that there is an unrealized internal potential for resource-saving development: the production and logistics subsystem of the enterprise is capable of reducing the share of energy costs in the cost price to 17%, and energy consumption to 0.12 rubles./rub. third, cost structure assessment (figure 4) revealed the prevailing share of heat energy consumption (53.2% in 2018). at the same time, the overall dynamics of energy resources for 2012-2018 decreased by 14% (or 8.6 percentage points), the share of fuel decreased slightly by 2.8% (0.4 percentage points). this is due to the introduction of advanced energy-saving technologies, processes automation, restructuring of consumed energy resources towards electric energy the share of which increased from 24% in 2012 to 33% in 2018 (an increase of 37.5%). shinkevich, et al.: computer analysis of energy and resource efficiency in the context of transformation of petrochemical supply chains international journal of energy economics and policy | vol 11• issue 3 • 2021532 figure 4: structure dynamics of energy costs of pjsc “nizhnekamskneftekhim”, % (inner ring 2012, outer ring 2018) figure 3: dynamics of prodcution energy costs and energy intensity of pjsc “nizhnekamskneftekhim” figure 5: dynamics of economic indicators of pjsc “nizhnekamskneftekhim”, % fourth, the economic indicators of pjsc “nizhnekamskneftekhim” activity have been studied (figure 5). when the cost of petrochemical products is steadily growing, then the return on costs, on the contrary, has an abrupt tendency to change. this is determined by the ratio of growth rate of profit and cost. in 2018, a positive change in indicator was recorded due to a significant increase in the company’s profit by 16369.80 million rubles. the presented analysis of economic indicators dynamics and energy efficiency indicators of pjsc “nizhnekamskneftekhim” makes it possible to state an increase in prices for energy resources, which determines the costs growth for energy supply of the enterprise. the energy consumption share in the cost of petrochemical products is also growing, but there is a clear change in the consumed resources from thermal energy to electrical energy. the presence of unrealized internal potential for improving energy efficiency determines the relevance of computer analysis of energy factors and indicators of economic efficiency dependence in the production of petrochemical products. 3. methods and models computer analysis of energy and resource efficiency in petrochemical supply chains was implemented using economic and mathematical modeling, including: 1. the production function of cobb-douglas, which allows to formalize the mathematical dependence of energy efficiency on two factors costs and labor intensity 2. a predictive model that allows, based on the constructed production function, to determine the predicted values of energy productivity 3. factor analysis, which allows classifying the indicators of enterprise development, taking into account energy efficiency. the construction of an economic and mathematical model makes it possible to assess the dependence of an effective indicator on a number of independent variables. the classical production function describes the dependence between result on capital and labor investments. the two-factor cobb-douglas production function, taking into account adaptation to the subject of our study, has the form: y = a0*k a1*la2 (1) where y is energy output (energy productivity), rubles/rubles, k – costs for 1 rub. products sold (revenue), kopecks, l – labor intensity, a0 – coefficient of neutral technical progress; a1 – coefficient of elasticity of factor k; a2 – coefficient of elasticity of factor l. the construction of a production function is implemented by us using ms excel tools and covers the following stages: • sequential logarithm of variables y, k and l • implementation of the linest function, where the arguments are the logarithms of dependent and independent variables • assessment of deviations of calculated values ycalc. from actual yfact . • assessment of significance of the obtained production function according to the fisher criterion: if the fisher table criterion is exceeded over the calculated one, the adequacy of the constructed production function is stated with a probability of 95%. based on the constructed model, it is proposed to predict indicators by determining the trend values of independent variables and their substitution into the function of dependence of energy efficiency on capital and labor investments. at the third stage, factor analysis is carried out, which makes it possible to classify by type a number of performance indicators of pjsc “nizhnekamskneftekhim”: shinkevich, et al.: computer analysis of energy and resource efficiency in the context of transformation of petrochemical supply chains international journal of energy economics and policy | vol 11• issue 3 • 2021 533 х1 – costs for 1 rub. products sold (revenue), kopecks; х2 – energy costs, х3 – the share of energy costs in the cost price, х4 – return on costs, х5 – energy output (energy productivity), х6 – return on assets, х7 – labor intensity, х8 – coefficient of labor force acceptance, х9 – coefficient of retirement of labor. determination of number of factors is carried out on the basis of the kaiser criterion factors with an intrinsic value of more than 1. the selected indicators characterize development of related aspects of the enterprise and reflect the efficiency of not only the production system of the enterprise, but also the supply chains of the products manufactured by it. since the construction of the model covers dissimilar indicators, the problem arises at different dimensions of variables. this problem is solved by standardizing the initial data, when the arithmetic mean of the normalized data is 0, and the variance is 1: yij = (хij – хср.j)/ sj, (2) where yij is the standardized value; sj is the sample variance of the j-th variable; хij – initial values of variables; хср.j – the average value of the j-th variable. taking into account factor loads, it is proposed to introduce an indicator for assessing the energy and resource efficiency of petrochemical supply chains, which has the form: ieesc = σ (eigi * fi) (3) where i is the number of selected factors; eigi – eigenvalue of the i-th factor; fi is the actual value of the factor, calculated by the formula: fi = σ (ri * xi), (4) where ri is the value of coefficient correlation between the variable and the selected factor; xi is the actual value of the variable. 4. results and discussions a reliable economic and mathematical dependence of energy productivity on capital and labor costs has been built in the form of the cobb-douglas production function, which determines the leverage on the energy efficiency of petrochemical supply chains. rational energy efficiency management of petrochemical supply chains should take into account not only energy costs, but also a number of other factors. undoubtedly, the functioning of the logistics system of an enterprise is affected by the efficiency of personnel, well-constructed routes for the movement of vehicles (both within the enterprise and with external links in the supply chain), facts of underload, which as a result affects the volume of fuel consumption. in this regard, we have selected indicators that reflect the capital and labor intensity of production of pjsc “nizhnekamskneftekhim” for 2013-2018. a model for managing energy output of petrochemical products production is proposed, presented in the form of a production function: y = 411,3*k-0,892*l0,013, where y is energy output (energy productivity), rubles/rubles, k – costs for 1 rub. products sold (revenue), kopecks, l – labor intensity. evaluation of model according to fisher’s criterion includes a comparison between tabular and calculated values of the coefficients (figure 6). calculated value of the fisher’s f-criterion exceeds the tabular one: f-criterion (calculated) = 9.85> f-criterion (tabular) = 9.55. thus, production energy efficiency is largely determined by unit costs level, since the coefficient of elasticity for this variable is higher than for labor intensity. it should be noted that the strong, but negative impact of unit costs indicates that energy efficiency will increase with additional costs. a predictive model allows you to determine trends in energy productivity and tools to influence energy efficiency in order to increase it. in order to predict the energy efficiency of supply chains for petrochemical products, a trend line of energy level output was built, taking into account the predictor variables k and l. polynomials of the dependent and independent variables were constructed (table 1) and a possible decrease in the energy output of production was revealed, all other things being equal. calculation of energy efficiency by substituting the predicted values of k and l into obtained production function confirms the negative trend in energy resources efficiency use by the pjsc “nizhnekamskneftekhim” enterprise (figure 7). figure 6: deviation of the original data from the calculated value of energy efficiency of nizhnekamskneftekhim shinkevich, et al.: computer analysis of energy and resource efficiency in the context of transformation of petrochemical supply chains international journal of energy economics and policy | vol 11• issue 3 • 2021534 of human resources, which brings an additional positive effect in the energy-saving of the production and logistics system. the visual distribution of factor loads is shown in figure 8. based on factors eigenvalues, we propose to formalize the dependence of the factors in the form of an indicator of the energy and resource efficiency of petrochemical supply chains. since we take into account the total energy costs in the factor model, it is advisable to reduce the resulting indicator value by 100,000: ieesc = (7,96 * fen + 1,03* fec) / 100 000, ieesc (2014) = 1,37, ieesc (2018) = 0,29. the use of indicator in practice also allows one to judge about the decrease in energy efficiency of pjsc “nizhnekamskneftekhim.” in this regard, we believe that the models we have proposed reflect the latent relationships between the private indicators of enterprise’s performance and are practically significant sets of variables, a systematic approach to managing allowing the enterprise to minimize the impact of external factors and stabilize energy efficiency of the production and logistics system. table 2: factor loadings of variables variables symbol energy factor (fen) economic factor (fec) costs per 1 rub. products sold х1 ˗0,837 ˗0,547 energy costs х2 0,993 0,117 the share of energy costs in the prime cost х3 0,806 0,592 return on costs х4 0,845 0,535 energy efficiency (energy performance) х5 0,923 0,384 fund profitability х6 0,370 0,929 labor intensity х7 ˗0,879 ˗0,477 labor force acceptance rate х8 0,695 0,719 labor retirement rate х9 0,242 0,970 expl.var 5,355 3,645 prp.totl 0,595 0,405 table 1: predicting production function variables vtariable polynomial equation prognosis 2019 2020 costs per 1 rub earnings k y = 0,3137×2 – 2,7445x + 91,959 88,12 90,08 labor intensity l y = 0,0043×2 – 0,2146x + 1,596 0,30 0,15 energy efficiency y y = -0,0539×2 + 0,4081x + 7,048 7,26 6,86 figure 7: predicting energy efficiency (2019-2020) by applying a production function figure 8: plot of factorial loads after rotation thus, the constructed economic and mathematical model is a tool for managing energy efficiency of petrochemical supply chains. despite the negative forecasts, we believe that the implementation of energy-saving programs by the enterprise will prevent the predicted decrease in energy efficiency. also, despite the relatively low share of fuel in energy costs, it is necessary to focus on rational routing of supplies of products of pjsc “nizhnekamskneftekhim.” the indicators of development of pjsc “nizhnekamskneftekhim” were aggregated by factors that formed the basis for determining energy efficiency indicator of the supply chain of petrochemical products. as a result of using the statistica package (module factor analysis), the variables x1-x9 are standardized according to formula (2) and aggregated by two factors (the optimal number of factors was identified by the kaiser criterion). as a result, 2 types of variables were formed according to the principle of high factor loads: the energy factor, which combined the indicators of energy consumption and labor intensity of production, and the economic factor, which covers the indicator of the efficiency of management of the company’s fixed assets and personnel (table 2). an inverse relationship was found between the energy factor fen and variable costs per 1 ruble. revenue and labor intensity. accordingly, the value of the energy factor fen will grow with decrease in unit costs and decrease in labor intensity of operations (mainly due to the automation of processes). it is noteworthy that employee turnover rates have a positive effect on the economic factor of fec. this relationship can be interpreted as the renewal shinkevich, et al.: computer analysis of energy and resource efficiency in the context of transformation of petrochemical supply chains international journal of energy economics and policy | vol 11• issue 3 • 2021 535 5. conclusion diagnostics of energy consumption by production and logistics system of pjsc “nizhnekamskneftekhim” revealed ambiguous trends in implementation of the energy saving policy. despite this, it should be emphasized that the company’s achievements in curbing energy consumption in the context of stable price increases. currently, a key factor in development of the enterprise is the impact of the current crisis situation on production a sharp drop in demand for some types of petrochemical products, at the same time, a sharp increase in demand for disinfectants. the performance of petrochemical supply chains spanning links from other regions is under attack due to restrictions on interregional transportation. it is possible to overcome the destabilization of enterprise development by adapting production, assortment policy and organizing supplies to crisis phenomena to restructuring demand. accordingly, a modernized (taking into account these changes) approach to energy conservation of production and logistics system is required. as regards to the transport subsystem, it is important to observe the rule of efficient loading and optimal routes. the indicated, undoubtedly, is of interest for future scientific research. an analytical review of research works of domestic and foreign scientists, the subject of which is energy conservation, made it possible to reveal the poor knowledge of the interdependence between energy and economic factors at the microeconomic level. when assessing the energy and resource efficiency of the petrochemical supply chain, we took into account not only the production system of the pjsc nizhnekamskneftekhim enterprise, but also the logistics aspect. in particular, we are talking about the transportation of petrochemical products and fuel costs for transportation, which directly affects the energy efficiency of the supply chain. we believe that the adaptation of production and logistics system of pjsc “nizhnekamskneftekhim” to global economic challenges necessitates continuous improvement of managing energy consumption mechanism and solving a number of organizational, economic and technological problems. the tools for improving this mechanism are proposed in this study and are reduced to the possibilities of forecasting and managing the energy and resource efficiency of petrochemical supply chain based on: • the production function, expressed as the dependence of the energy output of production on the cost per 1 ruble. revenue and labor intensity of production • factor model and the proposed indicator of energy resource efficiency of petrochemical supply chains. in our opinion, the practical application of conducted computer analysis results will help to identify the internal unrealized potential of energy efficiency in the supply chain of petrochemical products, and to ensure the competitiveness of products in the global petrochemical market. 6. acknowledgments the research was carried out within the framework of the grant of the president of the russian federation for state support of leading scientific schools of the russian federation, project number nsh2600.2020.6. the study was carried out within the framework of the state assignment of the southwestern state university, project code – 0851-2020-0034. references ayres, r., lindenberger, d., warr, b. (2013), the underestimated contribution of energy to economic growth. structural change and economic dynamics, 27, 79-88. bing, j., rui, l. (2011), economic analysis of energy efficiency in china’s economy. actual problems of economics, 124(10), 367-372. bobkov, v.i., fedulov, a.s., dli, m.i., meshalkin, v.p., morgunova, e.v. (2018), scientific basis of effective energy resource use and environmentally safe processing of phosphorus-containing manufacturing waste of ore-dressing barrows and processing enterprises. clean technologies and environmental policy, 20(10), 2209-2221. brahmana, r.k., ono, h. (2020), energy efficiency and company performance in japanese listed companies. international journal of energy technology and policy, 16(1), 24-40. brunoroa s., bizzarria, g., ferrari, l. (2019), energy efficient industrial parks cooperation: the case study of fabbrico and rolo in reggio emilia, italy. international journal of smart grid and clean energy, 8(3), 257-262. dellano-paz, f., calvo-silvosa, a., antelo, s.i., soares, i. (2015), the european low-carbon mix for 2030: the role of renewable energy sources in an environmentally and socially efficient approach. renewable and sustainable energy reviews, 48, 49-61. dunlop, t. (2019), mind the gap: a social sciences review of energy efficiency. energy research and social science, 56, 101216. farrou, i., androutsopoulos, a., botzios-valaskakis, a., goumas, g., andreosatos, c., gavriil, l., perakis, c. (2020), energy efficiency in steam using industries in greece. international journal of sustainable energy, 39(6), 556-582. kalenoja, h., kallionpää, e., rantala, j. (2011), indicators of energy efficiency of supply chains. international journal of logistics, 14(2), 77-95. kvon, g.m., prokopyev, a.i., shestak, v.a., larionova, a.a., shikh, e.v. (2019), features of cost advantages from implementation of energysaving projects. international journal of energy economics and policy, 9(3), 53-58. locmelis, k., bariss, u., blumberga d. (2019), energy efficiency obligations and subsidies to energy intensive industries in latvia. environmental and climate technologies, 23(2), 90-101. marchi, b., zanoni, s. (2017), supply chain management for improved energy efficiency: review and opportunities. energies, 10(10), 1618. meshalkin, v.p. (2009), energy-saving technology performance and efficiency indexes. chemical engineering transactions, 18, 953-958. meshalkin, v.p. (1997), computer-aided design of the resource-saving refinery processes. proceedings of european congress on chemical engineering, 4, 3055-3058. meshalkin, v.p., belozerskii, a.y., men’shova, i.i., bobkov, v.i., dli, m.i. (2019), optimizing the energy efficiency of a local process of multistage drying of a moving mass of phosphorite pellets. doklady chemistry, 486(1), 144-148. moshev, e.r., meshalkin, v.p. (2014), computer-based logistics support system for the maintenance of chemical plant equipment. theoretical foundations of chemical engineering, 48, 855-863. panarin, v., meshalkin, v.p. (2008), new energy-saving technologies in the chemical industry. energy for sustainable future, 2, 287-290. shi, g.m., bi, j., wang, j.n. (2010), chinese regional industrial energy shinkevich, et al.: computer analysis of energy and resource efficiency in the context of transformation of petrochemical supply chains international journal of energy economics and policy | vol 11• issue 3 • 2021536 efficiency evaluation based on a dea model of fixing non-energy inputs. energy policy, 38(10), 6172-6179. shinkevich, m.v., mashkin, n.a., ishmuradova, i.i., kolosova, v.v., popova, o.v. (2020), management of sustainable consumption of energy resources in the conditions of digital transformation of the industrial complex. international journal of energy economics and policy, 10(5), 454-460. thiede, s., bogdanski, g., herrmann, c. (2012), a systematic method for increasing the energy and resource efficiency in manufacturing companies. procedia cirp, 2, 28-33. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 1 • 2022188 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(1), 188-192. mitigating emissions in india: accounting for the role of real income, renewable energy consumption and investment in energy festus victor bekun* faculty of economics administrative and social sciences, istanbul gelisim university, istanbul, turkey. *email: fbekun@gelisim.edu.tr received: 18 september 2021 accepted: 23 november 2021 doi: https://doi.org/10.32479/ijeep.12652 abstract accomplishing environmental sustainability has become a global initiative whilst addressing climate change and its effects. thus, there is a necessity for innovation on part of economies as they seek energy for sustainable development. thus, we explore the case of india a highly industrialized and heavy emitter of carbon emission. to this end, this study explores the effect of renewable energy, non-renewable, economic growth, and investment in the energy sector on co2 emission in the indian economy. canonical cointegration regression (ccr), fully modified least squares (fmols) and dynamic least squares (dols) were used to access the long-run elasticity of the variables as well as granger causality analysis to detect the direction of causality relationship among the highlighted variables. empirical regression shows a negative relation between co2 emission and renewable energy. thus, suggesting that renewable energy serves as a panacea for sustainable development in the face of economic growth trajectory. however, there was a positive relationship between co2 emission and both non-renewable and real gdp growth. on the granger analysis, we observe a one-way causality among renewable energy consumption and co2 emission, economic development, and energy investment. these outcomes have far-reaching policy direction of environmental sustainability target in indian economy. keywords: environmental sustainability, carbon reduction, renewable energy, fossil-fuel energy jel classifications: c32, c23, q40, q45 1. introduction accomplishing environmental sustainability has become a global initiative whilst addressing climate change and its effects. on the other hand, non-renewable energy consumption has a driven production gain for many years (adedoyin et al., 2020). however, the reduction of fossil-fuel sources and the problem of anthropogenic climate change has a wide emphasis on sustainable energy development. with the advent of technologies and the development of environmental conservation, clean energy choices are progressively important substitutes. however, clean energy solutions remain relatively underdeveloped in both developing and advanced markets, although they are increasingly call for a worldwide change to sustainable and low-carbon energy sources. this disposition is being resonated by the intergovernmental panel on climate change (ipcc) on topical studies on the climate-led urban development debate was how the transition from a nonrenewable source in the form of fossil fuel energy sources to sustainable energy (renewables) in the form of wind, photovoltaic and hydro energy would foster economic growth in emerging markets (solarin et al., 2021). nevertheless, the analysis of the impact of sustainable and non-renewable energy sources on economic growth renders insights on sustainable energy and inclusive growth strategies as posited by apergis and payne (2012). this journal is licensed under a creative commons attribution 4.0 international license bekun: mitigating emissions in india: accounting for the role of real income, renewable energy consumption and investment in energy international journal of energy economics and policy | vol 12 • issue 1 • 2022 189 over the years, many studies have tried to identify the impact of renewable energy utilization, fossil fuel utilization, and sustainable development on environmental degradation. the bulk literature has not had a concerted agreement in the literature which this study seeks to bridge this gap. belaid and youssef (2017) explore the complex causal relationship involving co2, electricity generation use, fossil-based electricity consumption, and sustainable growth in algeria through 1980-2012. autoregressive global lag cointegration approach was utilized. empirical findings support the presence of long-term linkages between parameters. they discover that, in the long term, income activity and non sustainable electricity usage hurt the development of the climate, while the use of renewable energy has a useful impact on the climate. additionally, ito (2017) used panel data from 42 advanced states from the time frame of 2002-2011 to analyze scientifically the correlation connection co2 pollution, clean and non renewable energy use as well as sustainable development. their findings show that non-renewable energy used has a detrimental effect on sustainable development in developed nations. they notice that the use of green energy leads favorably to sustainable development in the future. boontome et al. (2017) examined the causal involvement regarding fossil fuel, clean energy, emission, and sustainable development in thailand from 1971 to 2013 utilizing the cointegration and causality methods. they identified the presents of cointegration involving the variables. from the causal involvement, it was observed that a one-way direction was identified involving fossil fuel and emission. their studies exposed that; fossil fuel raises emission in thailand. additionally, inglesi-lotz and dogan (2018) answered the discrepancies in the documentation by evaluating the factors (renewable and non-renewable capacity, income and trade openness) on co2 emission for the 10 largest oil producers in sub-saharan africa for the duration 1980 to 2011 by utilizing rigorous cross-dependent panel approximation approaches. the long-term association among the factors was established. rises in non-renewable energy usage boost emissions, although the reverse is true for sustainable energy. as respects to the orientation of the causal interaction, they noted the unidirectional causality of pollution, employment, trade, and non renewable energy to sustainable sources of energy. more recently, bekun et al. (2019) used structured panel evidence from the 1996-2014 entire cycle for chosen eu-16 members. the kao test demonstrates the co-integration of greenhouse gas emissions, productivity growth, renting of oil and gas, sustainable energy, and non-renewable energy use. the panel pooled mean group-autoregressive autoregressive distributive lag model (pmg-ardl) indicates a strong, long-term correlation between the country’s natural resource rent and carbon dioxide emissions. insinuating that overreliance on the rent of natural resources impacts the protection of the environment of panel states as preservation and maintenance choices are overlooked. their research shows that non-renewable energy use and business output boost greenhouse gas emissions, while sustainable energy use decreases carbon dioxide emissions1. 1 for brevity’s sake more literature on the growth-energy growth nexus see ozturk (2010) furthermore, chen et al. (2019a) analyzed the connection regarding per capita carbon dioxide (co2) emissions, gross domestic product (gdp), sustainable energy, non renewable, output, and foreign trade for china from the span 1980-2014. they concluded that there was a long-term association between these factors. a further interesting aspect was that china has no environmental kuznets curve (ekc) among output and carbon emission. their long-term forecasts indicate that fossil fuel and gdp increase pollution, while clean energy and international exchange hurt carbon emission. short-term granger causality analysis shows a bi-directional causality from international trade, co2 emissions, and fossil fuel to clean energy. the result shows that green energy use is a crucial approach to rising co2 pollution across the period. furthermore, the goal of this study is to examine the effects of clean energy as well as fossil-fuel-based energy usage on environmental sustainability targets in india by adding investments in energy in the empirical framework of this present study. this study is built on a carbon-income function. the additional variables incorporated help this study underscores the determinant of carbon emission for the case of india. the incorporation of additional variables aid in circumventing for omitted variable bias in the econometrics modeling. the choice of india is motivated by first, been one of the major growing energy-dependent states in the world. second, india’s balance of energy is largely controlled by global fossil fuel sources. nevertheless, india’s per capita usage of clean energy is much below that of most emerging countries (ohlan, 2015, ohlan and ohlan, 2016). the same is expected to rise significantly in the foreseeable period, through the quest for a better superiority of life as well as the capacity for exponential growth of the industrial segment in current policies (i.e., build asia, national industrial zones, technological asia, and venture india). growth of energy production in the area, and on the other hand, is unlikely to continue with intensified competitiveness. as a consequence, the state’s reliance on importing resources is predicted to rise even additional in the coming years. any loss of fossil fuel supplies due to an unpredictable geographical condition could lead to extreme energy shortages, which could, as a result, hinder india’s socio-economic growth. it is on this premise this study leverages on fmols, dols, and canonical cointegrating regression (ccr) for the indian clean energy and fossil fuel usage economic growth by exploring the long-term elasticity and causality relationship between the highlighted variables. the remainder of this study is structured as: section 2 offers the data and method employed while section 3 renders the discussion of empirical results. section 4 concludes the study with policy direction. 2. methodology this current study explores the effect of both clean and nonrenewable energy usage on co2 emission for the case of india. to do this, data from the world bank indicators were used. pollutant in the form of co2 emission is used for environmental degradation while gdp growth in (2010 us) has been used as a measure for economic growth and investment in the energy sector (investment in energy with private involvement (current us$) and bekun: mitigating emissions in india: accounting for the role of real income, renewable energy consumption and investment in energy international journal of energy economics and policy | vol 12 • issue 1 • 2022190 growth of the economy (gdp per capita (constant 2010 us$). the study data spans from 1990 to 2016 which is determined by the accessibility of data. 2.1. formulation of model to explore the effect of sustainable energy usage and nonrenewable energy consumption on co2 emission in a carbonincome function, the follow model is fitted as: co2t=f (rect, nrect, gdpt, iect) (i) here co2 presents carbon dioxide emissions in metric kg per, gdp growth, rec represents renewable energy consumption (% of total final energy consumption), nec denotes fossil fuel energy consumption (% of total), gdp= gdp per capita (constant 2010 us$) and iec= investment in energy with private participation (current us$). there exist few studies in the extant literature on the relationship between energy consumption and emissions level (see khoshnevis yazdi and shakouri, 2017; nguyen and kakinaka, 2019), the current study focuses on the indian economy to explore the determinants of co2 emissions. more specifically this study incorporates investments in the energy sector to substitute trade transparency and urbanization which distinguishes it from the studies of (khoshnevis yazdi and shakouri, 2017). utilizing the double log-linear modification of the eq variables. (1) the econometric definition of the time series is specified as: lnco2t=β0+β1lnrect+β2lnnrect+β3lngdpt+β4lniect+µt (ii) where ln denotes logarithm transformation of betas to achieve elasticity of the outlined variables. 3. empirical results and discussion this section discusses and describes all empirical findings in a stylized manner. table 1 demonstrates that the co2 has the maximum level over the span undergoing study. both sequences show negative skews apart from emissions and gdp, while pearson’s pairwise correlation reveals that co2 emission are closely related to economic development and other macroeconomic variables under consideration for stationarity purposes, the dickey and fuller (adf) (dicker and fuller, 1981) was utilized to check the stationarity structure among the factors used in this analysis. the cointegration technique was implemented to determine the long-term equilibrium relationship between the variables in the eqs. (2). johansen cointegration test equilibrium (cointegration) is used to determine the cointegration properties. while the fmols, dols, and ccr were used to verify the long-term elasticity of the variables. subsequently, granger causality analysis was utilized to verify the causal interaction of the variables. table 2 presents the stationarity test. the stationarity test is necessary to ascertain the integration properties of variables under review. this is pertinent to avoid working with variables integrated of order 2. as such variables will translate into spurious regression and by extension misleading inferences (bekun and agboola, 2019). from table 2 we confirm that our study variables are integrated of order 1. i.e., after first differencing. subsequently, we proceed to explore the equilibrium properties of the series as seen in table 3. the johansen cointegration test shows that the null hypothesis of no cointegration was rejected. thus indicating 2 cointegration table 1: descriptive statistics and correlation metrix analysis lnco2 lngdp lniec lnnrec lnrec mean 0.1069 6.9287 21.329 4.1851 3.8366 median 0.0911 6.8868 21.217 4.1833 3.90648 maximum 0.2562 7.6500 24.263 4.3437 4.0716 minimum –0.0508 6.3552 16.410 3.9846 3.5309 std. dev. 0.0992 0.4022 1.6030 0.1027 0.1761 skewness 0.1118 0.2063 –0.5598 –0.2381 –0.3881 kurtosis 1.63464 1.8250 4.5433 2.0685 1.6618 lnco2 lngdp lniec lnnrec lnrec correlation analysis lnco2 1 lngdp –0.9123*** 1 lniec –0.494*** 0.542*** 1 lnnrec –0.886*** 0.982*** 0.594*** 1 lnrec 0.841*** –0.985*** –0.547*** –0.964*** 1 ***=0.01, **=0.05 and *=0.10 table 2: unit root test statistics (level) lnco2 lngdp lnrec lnnrec lniec πτ –0.4474 2.8418 1.1731 –2.0601 –2.5154 πϑ –2.7396 –2.4748 –1.8322 –2.8044 –2.9580 statistics (1st difference) lnco2 lngdp lnrec lnnrec lniec πτ –5.7643*** –4.8977*** –3.3439** –4.9050*** –8.0448*** πϑ –5.6246*** –5.4344*** –3.5334* –5.1156*** –7.9385*** ***=0.01, **=0.05 and *=0.10.; thus, πτ is with constant, πϑ is with constant and trend bekun: mitigating emissions in india: accounting for the role of real income, renewable energy consumption and investment in energy international journal of energy economics and policy | vol 12 • issue 1 • 2022 191 vectors. thus, suggesting cointegration among the variables over the sampled period. this study applied a battery of regression techniques namely, the canonical cointegrating regression (ccr), fully modified least squares (fmols) and dynamic least squares (dols) were employed to access the long-run elasticity of the variable which is presented in table 4 above. form the estimation it was verified that; renewable energy consumption was 1% negatively significant in all the three estimations. thus, a 1% increase in renewable energy consumption will decrease emissions by 1.24%, 1.15% and 1.25% respectively. furthermore, all the three-estimation showed a positive significant for non-renewable energy consumption. thus, a 1% increase in the utilization of non-renewable energy will increase emission of 0.71%, 1.08% and 0.84% respectively. moreover, the estimations indicated that gdp had 1% negatively significant level with emissions. thus, 1% increase in gdp will decrease emission by 0.91%, 0.94% and 0.95% respectively in the long run and all the estimation affirms the findings of bekun et al. (2019). lastly, there was a 5% negatively significant at ccr and fmols in respect to investment in the energy sector. thus, a 1% increase in investment in the energy sector will decrease emission by 0.0081% in ccr and 0.0082% in fmols. from the table above, the estimations show that all the variables affect emission both in positive or negative in the long run. after confirming the long-run elasticity of the variables, there was a need to check the causality association of the variables by employing the granger causality analysis. the analysis of granger causality reported in table 5 shows that a one-way directional causality was identified between renewable energy utilization and emission, sustainability development and investment in the energy sector, and sustainable development and renewable energy utilization. these outcome resonates with the finding of gyamfi et al. (2020) and also give credence to the need for energy diversification to cleaner energy technologies to foster sustainable development targets. 4. concluding remarks the purpose of this study is to examine how the indian economy emission is affected by renewable energy consumption, nonrenewable energy consumption alongside economic growth and investment in the energy sector between 1990 and 2016. our study data were sourced from the world bank indicators database. india is among the emerging 7 nations (e7) which means the nation’s attention is shifting to industrialization with a lot of human activities which will result in producing more emission which stems from anthropogenic activities which in turn affect the environment in the long run. the majority of nations have therefore adopted initiatives and innovation into mitigating the reduction of emission by strict adherence to the kyoto procedure whereby india is not exempted from these strides for a cleaner and more habitable ecosystem. to this end, this study employed the canonical cointegrating regression (ccr), fully modified least squares (fmols), and dynamic least squares (dols) to access the long-run elasticity of the variable as well as the granger causality analysis to identify the causality relationship of the variables. the regression from ccr, dols and fmols are in harmony that renewable energy significantly decreases emission by 1.24%, 1.15% and 1.25% respectively, non-renewable energy consumption increases emission by 0.71%, 1.08%, and 0.84% respectively and gdp decreases emission by 0.91%, 0.94% and 0.95% respectively. all these three variables that is renewable energy, non-renewable energy and gdp estimations are in confirmations to the study of bekun et al. (2019). moreover, investment in financial development had a 0.0081% in ccr and 0.0082% in fmols decreasing impact on emission in the long run. nevertheless, granger causality test shows a unidirectional table 5: granger causality analysis null hypothesis f-statistics p-value lngdp≠lnco2 1.566 (0.2312) lnco2≠lngdp 0.004 (0.9953) lniec≠lnco2 0.140 (0.8699) lnco2≠lniec 0.722 (0.4967) lnnrec≠lnco2 2.421 (0.1121) lnco2≠lnnrec 1.192 (0.3223) lnrec≠lnco2 1.003 (0.3829) lnco2≠lnrec 3.401* (0.0516) lniec≠lngdp 1.226 (0.3126) lngdp≠lniec 4.389** (0.0249) lnrec≠lngdp 0.296 (0.7460) lnrec≠lngdp 2.403 (0.1138) lngdp≠lnrec 0.247 (0.7831) lngdp≠lnrec 2.715* (0.0883) lnnrec≠lniec 0.490 (0.6186) lniec≠lnnrec 0.015 (0.9843) lnrec≠lniec 1.042 (0.3693) lniec≠lnrec 0.648 (0.5326) lnrec≠lnnrec 1.199 (0.3203) lnnrec≠lnrec 0.842 (0.4440) ***=0.01, **=0.05 and *=0.10. while≠denote does not “granger cause” table 4: ccr, dols and fmols variables ccr dols fmols lngdp –0.9119*** –0.9400*** –0.9478*** p-value (0.0000) (0.0009) (0.0000) lnrec –1.2397*** –1.1447*** –1.2518*** p-value (0.0000) (0.0037) (0.0000) lnnrec 0.7097*** 1.0838** 0.8366*** p-value (0.0017) (0.0282) (0.0054) lniec –0.0081** –0.0024 –0.0081** p-value (0.0432) (0.8224) (0.0142) constant 8.3856*** 6.5367** 8.1495*** p-value (0.0000) (0.0127) (0.0000) r-square 0.957 0.9836 0.9567 adj r-square 0.949 0.9545 0.9492 ***=0.01, **=0.05 and *=0.10 table 3: johansen test to cointegration hypothesis no. of ce (s) fisher stat (from trace) eigenvalue p-value r ≤ 0 97.982*** 0.827203 (0.0001) r ≤ 1 50.580** 0.641350 (0.0271) r ≤ 2 22.894 0.358380 (0.2513) r ≤ 3 10.913 0.205607 (0.2169) r ≤ 4 4.6982 0.159710 (0.3302) ***=0.01, **=0.05 and *=0.10 bekun: mitigating emissions in india: accounting for the role of real income, renewable energy consumption and investment in energy international journal of energy economics and policy | vol 12 • issue 1 • 2022192 causality among renewable energy consumption and emission, sustainability development and investment in energy sector and sustainability development and renewable energy consumption. given the above-highlighted results, from a policy standpoint, indian economy needs to adopt measures such as incentives for carbon reduction, tax advantages, and financial aid to businesses manufacturing such infrastructures for renewable energy. furthermore, there is a need for a paradigm shift from the traditional energy consumption mix which is based on fossilfuel to renewables. renewables have been outlined as more environmentally friendly to environmental sustainability targets as well as investment in energy from public-private partnerships in the energy sector. this traction will translate into a green environment and economic growth. references adedoyin, f.f., gumede, m.i., bekun, f.v., etokakpan, m.u., balsalobrelorente, d. (2020), modelling coal rent, economic growth and co2 emissions: does regulatory quality matter in brics economies? science of the total environment, 710, 136284. apergis, n., payne, j.e. (2012), renewable and non-renewable energy consumption-growth nexus: evidence from a panel error correction model. energy economics, 34, 733-738. bekun, f.v., agboola, m.o. (2019), electricity consumption and economic growth nexus: evidence from maki cointegration. engineering economics, 30(1), 14-23. bekun, f.v., alola, a.a., sarkodie, s.a. (2019), toward a sustainable environment: nexus between co2 emissions, resource rent, renewable and nonrenewable energy in 16-eu countries. science of the total environment, 657, 1023-1029. belaid, f., youssef, m. (2017), environmental degradation, renewable and non-renewable electricity consumption, and economic growth: assessing the evidence from algeria. energy policy, 102, 277-287. boontome, p., therdyothin, a., chontanawat, j. (2017), investigating the causal relationship between non-renewable and renewable energy consumption, co2 emissions and economic growth in thailand. energy procedia, 138, 925-930. chen, y., wang, z., zhong, z. (2019a), co2 emissions, economic growth, renewable and non-renewable energy production and foreign trade in china. renewable energy, 131, 208-216. chen, y., zhao, j., lai, z., wang, z., xia, h. (2019b), exploring the effects of economic growth, and renewable and non-renewable energy consumption on china’s co2 emissions: evidence from a regional panel analysis. renewable energy, 140, 341-353. gyamfi, b.a., bein, m.a., bekun, f.v. (2020), investigating the nexus between hydroelectricity energy, renewable energy, nonrenewable energy consumption on output: evidence from e7 countries. environmental science and pollution research, 27(20), 2532725339. inglesi-lotz, r., dogan, e. (2018), the role of renewable versus nonrenewable energy to the level of co2 emissions a panel analysis of sub-saharan africa’s βig 10 electricity generators. renewable energy, 123, 36-43. ito, k. (2017), co2 emissions, renewable and non-renewable energy consumption, and economic growth: evidence from panel data for developing countries. international economics, 151, 1-6. khoshnevis yazdi, s., shakouri, b. (2017), renewable energy, nonrenewable energy consumption, and economic growth. energy sources part b, 12, 1038-1045. nguyen, k.h., kakinaka, m. (2019), renewable energy consumption, carbon emissions, and development stages: some evidence from panel cointegration analysis. renewable energy, 132, 1049-1057. ohlan, a., ohlan, r. (2016), generalizations of fuzzy information measures. switzerland: springer international publishing. ohlan, r. (2015), the impact of population density, energy consumption, economic growth and trade openness on co2 emissions in india. natural hazards, 79, 1409-1428. ozturk, i. (2010), a literature survey on energy-growth nexus. energy policy, 38(1), 340-349. solarin, s.a., bello, m.o., bekun, f.v. (2021), sustainable electricity generation: the possibility of substituting fossil fuels for hydropower and solar energy in italy. international journal of sustainable development and world ecology, 28(5), 429-439. world bank. (2019), world development indicators. available from: http:// www.databank.worldbank.org/data/reports.aspx?source=worlddevelopmentindicators [last accessed on 2020 feb 02]. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020280 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 280-287. the influence of crude oil prices volatility, the internet and exchange rate on the number of foreign tourist arrivals in indonesia heppi millia1*, pasrun adam2, zainuddin saenong1, muh. yani balaka1, yuwanda purnamasari pasrun3, la ode saidi2, wali aya rumbia1 1department of economics, universitas halu oleo, kendari, indonesia, 2department of mathematics, universitas halu oleo, kendari, indonesia, 3department of information system, universitas sembilanbelas november, kolaka, indonesia. *email: milliaheppi@gmail.com received: 13 june 2020 accepted: 08 september 2020 doi: https://doi.org/10.32479/ijeep.10083 abstract this paper seeks to examine the influence of crude oil prices volatility, the internet, and exchange rate on the number of foreign tourist arrivals in indonesia. using a time-series dataset from 1995 to 2018 and employing an autoregressive distributed lag (ardl) model plus an error correction model (ecm-ardl), our research shows that in the long run, the internet has a positive influence on the number of foreign tourist arrivals. every 1% rise in the internet, the number of foreign tourist arrivals rises by 0.49%. however, crude oil prices volatility and exchange rates do not significantly affect the number of foreign tourist arrivals. in the short run, there is a negative influence of crude oil price volatility on the number of foreign tourist arrivals. meanwhile, the exchange rate positively affects the number of foreign tourist arrivals, meaning that the appreciation (depreciation) of the idr exchange rate against the usd causes the number of foreign tourist arrivals to go down (up). keywords: crude oil price volatility, the internet, exchange rate, foreign tourist arrivals, ardl model jel classifications: c32, e310, f310, o330 1. introduction crude oil is an important commodity in the world economy because crude oil is needed by all countries as input (raw material) in the production process. in this case, it functions to run production machinery, transportation tools, and machine for power generation (muthalib et al., 2018). the need for crude oil brings world demand shock. this increase in demand can raise crude oil prices. however, the price of crude oil can also fall as a result of economic crisis. since the beginning of the 21st century, international oil prices have surged and fluctuated widely. significant changes in oil price have affected many countries (liu et al., 2020). changes in the price of crude oil can trigger changes in production cost in industrial sectors including tourism industry. large oil price changes as a result of rising and falling crude oil prices can make crude oil price volatility high (becken, 2011). crude oil price volatility is a measure of risk in crude oil trading and investments in the financial markets where crude oil is the basic benchmark in derivative trading, for instance option instruments (put option and call option). furthermore, currencies and the internet also play an important role in the economy. currency becomes a means of transaction in international trade both in real and financial sectors. meanwhile, the internet is a worldwide communication network that serves to send and transfer information between its users in all economic activities (saidi et al., 2020) including activities in the tourism industry sector. with regards to the role of crude oil, currency and the internet in the world economy, the discussion about the relationship between this journal is licensed under a creative commons attribution 4.0 international license millia, et al.: the influence of crude oil prices volatility, the internet and exchange rate on the number of foreign tourist arrivals in indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020 281 crude oil prices, crude oil prices volatility, exchange rates, the internet and the number of tourist arrivals have been the concern of academics both from the theoretical side and the empirical side. in theory, crude oil price volatility and exchange rate can influence the number of tourist arrivals through inflation. an increase in oil price volatility can increase the state of uncertainty in economic activity in every country (yang et al., 2002; rentschler, 2013). the increase in state of uncertainty can lead to delays in investment by investors and companies that ultimately lower total production (rafiq et al., 2009; trang et al., 2017; eyden et al., 2019). the decline in total production can cause aggregate supply to drop which then raise the price of produced goods (including the price of goods in the tourism industry sector) and inflation (bulman and simon, 2003; dritsakis, 2004; pangannavar, 2014). so, crude oil price volatility can lead to high inflation (gokmenoglu and fazlollahi, 2015; hung, 2020). furthermore, exchange rates and the internet can also affect the number of foreign tourist arrivals in a country. exchange rates can affect the number of foreign tourist arrivals via interest rate channels and inflation. according to the uncovered interest rate parity theory, if the domestic currency exchange rate strengthens (appreciates), then the domestic interest rate can fall (pilbeam, 2006; adam et al., 2017; saenong et al., 2020) which can afterward encourage inflation (saidi et al., 2019). high inflation can raise travel costs, accommodation, and production prices of the tourism industry which in turn can reduce the number of foreign tourist arrivals in the country of tourist destination (al-mulali et al., 2019). thus, an increase in crude oil price volatility and the domestic currency exchange rate can decrease the number of foreign tourists in a country of tourist destination. internet technology can make it easy for potential tourists to get information about interesting tourist attractions to visit. for companies in the field of tourism, internet technology can be used to promote tourism objects in the form of beautiful natural resources and art of local culture. moreover, from the efficiency side, according to meltzer (2014), zengin and arici (2017) and world bank (2016), internet use can reduce the operational costs of companies in the field of tourism so that the costs of visiting can also decrease. knowledge of attractive tourism objects and affordable visit costs can influence the attitude or decision of potential tourists to make a visit to tourist spots. these two potentially raise the number of foreign tourists coming into a country. a number of empirical studies have been conducted to investigate the influence of oil prices on the number of foreign tourist arrivals (cao et al., 2017; hassani et al., 2020). studies of the influence of oil price volatility on economic activity have also been undertaken (rafiq et al., 2009; itō, 2010; rentschler, 2013; al-asasi, 2017; junior, 2018). nevertheless, these studies are nowhere near enough (rafiq and salim, 2014). according to our best knowledge, no research study has investigated whether or not crude oil prices volatility could have an impact on the number of foreign tourist arrivals. furthermore, several studies looking at the effect of exchange rates on foreign tourist arrivals have been carried out (vita, 2014; wamboye et al., 2020). they found that there is an exchange rate effect on the number of foreign tourist arrivals. likewise, studies on the effect of the internet on the number of foreign tourist arrivals have been carried out by, among others, agiomirgianakis et al. (2018) and the results of their study indicated that there the internet affects the number of foreign tourist arrivals. in indonesia, a research concerning the influence of exchange rate on the number of foreign tourists has been conducted by faidzin and cahyono (2017). in their study, however, exchange rate was not found to impact the number of foreign tourist arrivals in indonesia. meanwhile, the study looking at the internet influence on the number of foreign tourist arrivals in indonesia has never been reported in the literature. in this study, we use annual time-series data over the period of 19952018. this data period differs from that used by faidzin and cahyono (2017), while it worth noticing that variation in data period between two or more studies could lead to a substantial difference in findings (adam et al., 2015). indonesia is a developing country where the tourism sector is important to be developed. since 1978, the indonesian government has been paying attention to further the tourism industry with the aim of increasing foreign exchange, expanding employment, and promoting indonesian culture. various efforts have been made to develop the tourism sector such as promotion, provision of facilities, and improvement of service quality (soebagyo, 2012). these efforts appear to pay off, making indonesia a country that has competitiveness in the tourism sector. indonesia has become one of the tourist destinations in the world and was ranked 70th in 2013 and 42nd in 2017 (ollivaud and haxton, 2019). since crude oil prices, exchange rate and the internet also become factors that can have an impact on how tourism development is directed, the policy for the provision of crude oil for domestic use, domestic currency rates stabilization, and the internet use in the tourism industry should get more attention. to take policy measures, the government certainly needs data and information that can be obtained through surveys or preliminary studies. therefore, the current study is of great importance to carry out. to fill the lacuna in research as mentioned above, the purpose of this study is to examine the effect of crude oil price volatility, the internet and exchange rate on the number of foreign tourist arrivals in indonesia. to test this effect, we employ an autoregressive distributed lag (ardl) model. 2. literature review as stated earlier, the development of tourism industry sector has attracted the attention of researchers and policymakers in many countries including indonesia. the advances in various sectors of tourism industry such as tourist sites, arts and culture, hospitality, transportation, restaurants, travel agencies, and other services sectors are assumed to have attracted more foreign tourists to visit. as a result, the number of foreign tourist arrivals is growing which ultimately increases the foreign exchange as well as promotes economic growth. for this reason, researchers have studied factors that can influence the number of foreign tourist arrivals including commodity prices such as crude oil and exchange rate (sabon et al., 2018) and also the internet (agiomirgianakis et al., 2018). in this section, we review several empirical studies on the effect of oil prices, exchange rate, and the internet on the number of foreign tourist arrivals in several countries. millia, et al.: the influence of crude oil prices volatility, the internet and exchange rate on the number of foreign tourist arrivals in indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020282 a few of researchers have described the symmetry and asymmetry effects of oil prices on the number of foreign tourist arrivals as either positive or negative. yet, from literature research, we have not found any study looking at the effect of crude oil price volatility on the number of foreign tourist arrivals. huang et al. (2018) in their study in the united states and in several european countries (austria, italy, germany, greece, the netherlands, spain, portugal, sweden, and the united kingdom) found that there is a positive influence of oil prices on the number of tourist arrivals. their findings were the results of the convergent cross mapping (ccm) tests on monthly data from january 1996 to december 2015. becken and lennox (2012) in the conclusion of their study in new zealand stated that sharp increases in oil prices have a negative influence on the number of tourist arrivals. al-mulali et al. (2019) examined the asymmetry effect that oil prices have on the number of foreign tourist arrivals in malaysia. their findings showed that in the short run the increase in oil prices negatively affects the number of foreign tourist arrivals. meanwhile, the effect of exchange rate on the number of foreign tourist arrivals was investigated by, among others, othman et al. (2018), kosnan et al. (2012), nugroho et al. (2017) and gibtiah et al. (2018). othman et al. (2018) used a set of yearly panel data from 149 countries for the period 1995-2012. in addition to the exchange rate as an exogenous variable, they also included other variables such as the country’s revenue from tourism and the number of hotel rooms. the gravity model test results indicated that revenue affects the number of demand in foreign tourists, while exchange rate and the amount of hotel room inventory do not show the effect. kosnan et al. (2012) examined the number of foreign tourist arrivals in malaysia using panel data from 20 countries and annual time series data from 1998 to 2009. the factors that become the center of attention are distance, cost of living, and exchange rate. the test results using the gravity model showed the distance, living costs, and the exchange rate negatively affect the number of tourists coming to malaysia. nugroho et al. (2017) investigated the impact of exchange rates on the demand of foreign tourists in bali. using the logistic regression model, their research showed that exchange rate has no significant effect on the number of foreign tourist arrivals in bali. gibtiah et al. (2018) examined the influence of exchange rate, living cost, and friendly culture on the number of japanese tourist arrivals in palembang indonesia. they collected data, by interviewing 120 respondents. the structural equation model test results showed a positive effect of the exchange rate and friendly culture on the number of tourist arrivals, whereas the effect of living cost is not found. tavares and leitao (2016) investigated the exchange rate influence and income of the country of origin on the number of foreign tourist arrivals in brazil. the results of the gravity model test indicated that exchange rate and income of the country of origin positively impact the number of foreign tourist arrivals. ramos and rodrigues (2013) studied the influence of the internet, length of stay, living cost in tourism area, and travelling cost to tourism area on the number of foreign tourist arrivals in 18 european countries (austria, belgium, cyprus, denmark, finland, france, germany, greece, ireland, italy, the netherlands, norway, portugal, spain, sweden, switzerland, turkey, and the uk). the test results of panel data against the countries’ panel data with time series from 1993 to 2007 showed that all exogenous variables positively affect the number of foreign tourist visiting the countries. sun et al. (2019) outlooked the internet influence on the number of tourist arrivals in china using the granger causality analysis and monthly data over the period of january 2011 to april 2017. the test results showed that the internet could increase the number of tourist arrivals. 3. data and methodology 3.1. data we use annual time series data which include data for crude oil prices, the internet, and the exchange rate for the period from 1995 to 2018. the proxy for crude oil prices is the price of west texas intermediate (wti) crude oil in usd per barrel. the proxy for the internet is internet users, and we use the percentage of internet users per 100 populations for its unit of measurement. the proxy for the exchange rate is idr/usd in rupiah per usd. the timeseries data for wti crude oil prices are obtained from the eia website, while for the internet and the exchange rate are sourced from the world bank website. 3.2. methodology we use vot, oil, ius, exr, and tra notations to declare crude oil price volatility, crude oil price, the internet, exchange rate, and the number of foreign tourist arrivals respectively. oil, ius, exr, and tra variables are the logarithmic forms of the corresponding time-series data. vot volatility variable is a measure of the risk of crude oil prices in the wti international crude oil trade (see misra, 2018). vot time-series data are generated using the garch(1.1) model (see bahmani-oskooee and xi, 2015) as follows 1t t toil a boil u-= + + 1 ~ (0, )t t th iidn h-w 2 1t t th w du eh -= + + where a, b, w, d, and e are the parameters of the regression equations, and ut is an error. the ht variable is the conditional variance of the error ut against ωt−1 where ωt−1 is the set of events in the form of information at time t-1 with t = 1995, 1996,…, 2018. furthermore, t tvot h= is the crude oil price volatility. the long run relationship between crude oil price volatility (vot), the internet (ius), the exchange rate (exr) and the number of foreign tourist arrivals (tra), is specified with multiple linear regression equations in (1) t t t t ttra c vot ius exra b g e= + + + + (1) by referring to the specification of the relationship model in equation (1), we assume that the volatility of crude oil prices, the internet, the exchange rate and the number of foreign tourist arrivals are cointegrated. the parameters α, β, and γ are the cointegration parameters or known as the long run coefficients of millia, et al.: the influence of crude oil prices volatility, the internet and exchange rate on the number of foreign tourist arrivals in indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020 283 crude oil prices volatility, the internet and exchange rates against the number of foreign tourist arrivals, while c is the intercept and εt is the error that is normally distributed, independent (unautocorrelated) and homoscedastic. we employ the autoregressive distributed lag (ardl) model to test the effect of the crude oil prices volatility, the internet, and the exchange rate on the number of foreign tourist arrivals. the ardl model formula with the lag length p, q, r and s written as ardl(p, q, r, s) is as follows (pesaran and shin, 1999; heij et al., 2004) 0 1 0 p q t i t i j t j i j tra c tra votq a= = = + + +å å 1 0 0 r s k t k l t l t k l ius exrb g e= = + +å å (2) where c0, ( 1, 2, ..., )i i pq = , ( )0,1 , , j j qa = ¼ , ( )0,1 , , ,k k rb = ¼ ( 0,1 , , )l l sg = ¼ are the parameters of the regression equation and ε1t is the error or residual that is independent one another and homoscedastic. the ardl model in equation (2) will produce a long run cointegration equation in equation (1) if each variable of crude oil price volatility, the internet, the exchange rate and the number of foreign tourist arrivals reaches equilibrium in such a way that 0 1 1 p ii c c q = = -å , 0 1 1 q jj p ii a a q = = = å å , 0 1 1 r kk p ii b b q = = = å å and 0 1 1 s ll p ii g g q = = = å å . to test the effect of crude oil prices volatility, the internet and the exchange rates on the number of foreign tourist arrivals using equation (2), we follow the following a procedure as follows: (i) testing for stationarity of all variables, (ii) testing for cointegration (if one or all variables are stationary at first difference), and (iii) estimating the model accompanied by testing for error assumption and stability of the regression parameters. in the first step, we perform a stationarity test of all variables employing the perron test with break date (perron, 1989; brooks, 2014), hereafter expressed as pb. the pb test uses the adf equation. for example, to test for stationarity of the tra variable, the adf equation with break date is as follows: ( ) ( )1 1 2t t t b td tra tra d t t dm-= y + +æ +æ + 2 1 ( ) p i t i t i t d tral j e= + +å (3) where 1 2, , , , m ly æ æ and ( 1, 2, , )i i pj = ¼ in equation (3) are the parameters of the regression equation. furthermore, ε2t is the error, and t is the trend, tb is the break date, and dt is the dummy variable which is defined as b b 0 t 1 tt if t d if t <ì = í ³î , 1995,1 996, , 2018.t = ¼ variable d(trat) is the first difference form of trat where d(trat) = trat – trat–1 = tra – tra(−1). the hypothesis of the stationary test is formulated as h0: time series is not stationary versus h1: time series is stationary. in the second step, we perform a cointegration test between the crude oil price volatility, the internet, the exchange rate, and the number of foreign tourist arrivals. we employ the ardl bound cointegration test (pesaran et al., 2001). in the ardl bound cointegration test, one or all the regressors in the model are assumed to be non-stationary at second difference or not i(2) process, but all the regressors are stationary at level or first difference or compound of both. meanwhile, sam et al. (2019) state that the dependent variable could be non-stationary at first difference or not i(1) process. the ardl bound model formula is 1 1 0 1 0 ( ) ( ) ( ) p q t i t i j t j i j d tra c d tra d votq a = = = + + +å å 1 1 0 0 ( ) ( ) r s k t k l t l k l d ius d exrb g = = + +å å 1 1 2 1 3 1 t t ttra vot iust t t-+ + + 4 1 2t texrt e+ (4) in equation (4), ( 1, 2, 3, 4)i it = is the parameter of the regression equation. to test for cointegration, the hypothesis formula is 0 1 2 3 4: h t t t t¹ ¹ ¹ (there is no cointegration between variables) versus h1: there is i(i = 1,2,3,4) such a way that ti ¹ 0 (there is cointegration between variables). to test the hypothesis, we employ the f-test with the following criteria: (i) if the f-statistic is greater than the upper bound critical value i(1) then the hypothesis h0 is rejected (h1 accepted), or in other words, there is a cointegration between the volaitility of crude oil prices, the internet, the exchange rate and tourist arrival; (ii) if the f-statistic value is smaller than the lower bound critical value i(0) then the hypothesis h0 is accepted (h1 is rejected), and; (iii) in other cases, the hypothesis test does not make any conclusion. in the third step, we estimate the error correction model (ecmardl). the ecm-ardl(p-1, q-1, r-1, s-1) model formula (heij; 2004) as follows ( ) ( ) ( )0 0 0 1( )t t t t td tra d vot d ius d exr eca b g p -= + + + + 1 1 * * 1 0 ( ) ( ) p q i t i j t j i j d tra d votq a = = + +å å 1 1 * * 2 1 1 ( ) ( ) r s k t k l t l t k l d ius d exrb g e = = + +å å (5) in pesaran and shin (1999), equation (5) is the ecm-ardl model with restricted intercept and no trend (case 2). the coefficient π is the error correction coefficient and the variable ect is the error correction variable. the ecm-ardl model is called the one-way relationship short-run model of the crude oil price volatility, the millia, et al.: the influence of crude oil prices volatility, the internet and exchange rate on the number of foreign tourist arrivals in indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020284 internet, and the exchange rate to the number of foreign tourist arrivals. as the completeness of testing the effect of crude oil prices volatility, the internet and the exchange rate on the number of foreign tourist arrivals, we test the classical assumptions (autocorrelation, homoscedastic, and error normality) and the stability of the ardl(p, q, r, s) model parameters. for that purpose, we employe the breusch-godfrey lm, the breuschpagan-godfrey, and the jarque bera tests to test assumptions autocorrelation, homoscedasticity, and normality respectively. afterwards, to test the stability of the parameters of the ardl model, we employ the cusum test and the cusum square test (brown et al., 1975). 4. results and discussion 4.1. results the use of the ardl model to test an effect does not require variable stationarity testing requirements. however, since one of the variables involved in this model should not be stationary at second difference or i(2) process. therefore, before we proceed, we first need to test for stationarity of all the variables employing the pb test. the purpose is to ensure that not any of the four variables involved in the model is i(2) process. the stationarity test results are summarized in table 1. we can see that statistical values in table 2, the crude oil prices volatility variable, and the number of tourist arrival variable are all stationary at first difference. meanwhile, the internet and exchange rate variables are stationary at level and also at first difference. next, we test for cointegrating between the variables: the crude oil price volatility, the internet, the exchange rate, and the number of foreign tourist arrival. as stated in the methodology subsection above, we employ the ardl bound cointegration test. this test is preceded by the determination of the ardl model lag length. based on the akaike information criteria (aic), we obtain the lag length p = 3, q = 0, r = 2 and s = 3. so, the ardl bound test is based on the ardl(3,0,2,3) model. from the calculation results, we obtain an f-statistic value of 4,828. meanwhile, the upper bound critical value i(1) at the 5% significance level is 4.306. because the f-statistic value is higher than the upper bound critical value (1), then we conclude that at the 5% significance level, there is cointegration between the volatility of crude oil prices, the internet, the exchange rate, and the number of foreign tourist arrivals. this result also gives a signal that in the long run there is a relationship between crude oil price volatility, the internet, exchange rate, and the number of tourist arrivals. however, this conclusion needs to be based on the significance of the long run parameters in equation (1). afterwards, we estimate the long run coefficients of the ardl(3,0,2,3) model and the short run coefficients of the ecm-ardl(2,0,1,2) model. the estimation results of all model parameters are presented in table 2. in panel a, it appears that the long run coefficient of the internet is 5% so that we conclude that at a significance level of 5%, there is a positive long run influence of the internet on the number of tourist arrivals in indonesia. every 1% of the internet rises, the number of foreign tourist arrivals rises by 0.49%. furthermore, in panel b it appears that the coefficients of crude oil prices volatility and exchange rate are significant. in other words, there is a negative short run influence of the volatility of crude oil prices on the number of foreign tourist arrivals. at the same time, there is also a positive short run influence of the exchange rate on the number of foreign tourist arrivals. this conclusion is said to be valid as all model assumptions are satisfied, both classical assumption for residual (autocorrelation, homoscedasticity, and normality) and stability assumption of the ardl model parameters as shown by figure 1. 4.2. discussions the present study finds that in the long run, the internet has an influence on the number of foreign tourist arrivals. this finding is aligned with the theory stated in the introduction (meltzer, 2014; world bank, 2016; zengin and arici, 2017). it also agrees with that of agiomirgianakis et al. (2018). meanwhile, in the short run, the study finds an influence of crude oil price volatility (despite being negative) on the number of foreign tourist arrivals, bringing this study to confirm the theory put forward by yang et al. (2002), rentschler (2013), rafiq et al. (2009), trang et al. (2017), eyden et al. (2019), bulman and simon (2003), dritsakis (2004) and pangannavar (2014). table 1: unit root test with break date of perron variable intercept intercept and trend test statistic break date test statistic break date vot −3.4448 2005 −3.6431 2015 d(vot) −5.7818* 2001 −5.7754* 2001 ius −5.1014* 2015 −6.6184* 2011 d(ius) −7.0118* 2001 −6.7082 2001 exr −21.6340* 2014 −18.3887* 2014 d(exr) −7.2166* 2000 −7.0520* 2000 tra −0.0287 2010 −2.0476 2002 d(tra) −6.3062* 2006 −8.6085* 2003 *means significant at 1% significance level table 2: estimation of long run and short run coefficients constant and variable independent coefficient t-statitics p-value panel a : long run coefficient, dependent variable: tra c 4.4917 2.1375 0.0650 vot −0.4876 −0.3889 0.7075 ius 0.4085 2.7939 0.0234 exr 0.4989 0.9277 0.3807 panel b: short run coefficient, dependent variable: d(tra) d(tra(-1)) −0.4743 −2.6102 0.0311 d(tra(-2)) −0.3717 −1.9598 0.0857 d(vot) −0.2807 −1.0641 0.3183 d(vot(-1)) −0.7032 −4.5858 0.0018 d(vot(-2)) −0.3874 −2.4850 0.0378 d(exr) 0.4859 2.2628 0.0535 d(exr(-1)) 0.2293 3.1247 0.0141 ec(-1) −0.4231 −6.0172 0.0003 in sequence, p-value for the breusch-godfrey serial correlation lm test, the breuschpagan-godfrey test, and the jarque berra test are 0.191, 0.117, and 0.959 millia, et al.: the influence of crude oil prices volatility, the internet and exchange rate on the number of foreign tourist arrivals in indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020 285 similarly, in the short run, the exchange rate is found to positively affect the number of foreign tourist arrivals. this finding is particularly supported by the theories expressed by pilbeam (2006) and al-mulali et al. (2019). it is also in line with that of vita (2014), tavares and leitao (2016), gibtiah et al. (2018), and wamboye et al. (2020). however, it contradicts that of kosnan et al. (2012), faidzin and cahyono (2017), nugroho et al. (2017). these studies did not report the existence of influence from exchange rate to the number of foreign tourist arrivals. this discrepancy could be caused by variation in data period used (adam et al., 2015) especially for the same research location and also by variation in socio-cultural and economic conditions of a country where research is conducted (ozturk, 2010). furthermore, the present study reveals the positive influence of the internet on the number of foreign tourist arrivals. it, therefore, is consistent with ramos and rodrigues (2013) and sun et al. (2019) who also reported in their studies the influence of the internet on the number of foreign tourist arrivals. with these findings, the indonesian government in particular needs to take policy with regard to crude oil energy industry, domestic currency exchange stability, and development of internet technology. in the energy field, the government should continue to subsidize households to stabilize crude oil prices so that crude oil prices can be depressed and do not cause inflation. 5. conclusions crude oil is a mineral resource that is needed by all countries in the world. it is used to run production machinery, transportation tools, and electricity-generating machinery. meanwhile, the internet and exchange rate are also important assets in the economy. the internet is a technology used to send and receive information in economic activities, while exchange rate is a unit price of transactions in international trade. on the other hand, tourism industry has become very strategic to support a country’s economy. therefore, factors that influence the private sector including crude oil prices volatility, the internet, and exchange rate are important to know. the objective of the present study is to examine the effect of crude oil prices volatility, the internet, and exchange rate on the number of foreign tourist arrivals in indonesia. to test this influence, we use the annual time series data on crude oil prices, the internet, exchange rate, and the number of foreign visitor arrival covering the period from 1995 to 2018. to analyze the data, we employ the ardl model and the ecm-ardl model. the cointegration test result shows that there is a cointegration between the price of crude oil prices volatility, the internet, the exchange rate, and the number of foreign tourist arrival. meanwhile, the result of the ardl model estimation indicated a positive long run effect of the internet on the number of foreign tourist arrivals in which every 1% rise in the internet led to an increase of 0.49% in the number of foreign tourist arrivals. furthermore, based on the estimation results of the ecm-ardl model, we conclude that in the short run, the prices of crude oil volatility negatively impact the number of tourist arrivals. as for the exchange rate, it is found to positively affect the arrivals of foreign tourists, meaning that if the exchange rate of the idr appreciates (depreciates) against the usd, the number of foreign tourist arrivals declines (increases). references adam, p., nusantara, a.w., muthalib, a.a. (2017), foreign interest rates and the islamic stock market integration between indonesia and malaysia. iranian economic review, 21(3), 639-659. adam, p., rianse, u., cahyono, e., rahim, m. (2015), modeling of the dynamics relationship between world crude oil prices and the stock market in indonesia. international journal of energy economics and policy, 5(2), 550-557. agiomirgianakis, g., bertsatos, g., tsounis, n. (2018), asymmetric responses in the tourism demand function. the journal of economic asymmetries, 18, 1-4. al-asasi, b.o., taylan, o., demirbas, a. (2017), the impact of oil price volatility on economic growth. energy sources, part b: economics, planning, and policy, 12, 847-852. al-mulali, u., gholipour, h.f., al-hajj, e. (2019), the nonlinear effects of oil prices on tourism arrivals in malaysia. current issues in tourism, 23, 942-946. bahmani-oskooee, m., xi, d. (2015), exchange rate volatility and domestic consumption: evidence from japan. economic systems, figure 1: stability test results of ardl(3,0,2,3) model parameters millia, et al.: the influence of crude oil prices volatility, the internet and exchange rate on the number of foreign tourist arrivals in indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020286 36, 326-335. becken, s. (2011), oil, the global economy and tourism. tourism review, 66(3), 65-72. becken, s., lennox, j.a. (2012), implications of a long-term increase in oil prices for tourism. tourism management, 33(1), 133-142. brooks, c. (2014), introductory econometrics for finance. 3rd ed. cambridge, united kingdom: cambridge university press. brown, r.l., durbin, j., evans, j.m. (1975), techniques for testing the constancy of regression relationships over time. journal of the royal statistical society, series b (methodological), 37(2), 149-192. bulman, t., simon, j. (2003), productivity and inflation, research. australia: discussion paper, no. 2003-10, bank of australia. cao, z., li, g., song, h. (2017), modelling the interdependence of tourism demand: the global vector autoregressive approach. annals of tourism research, 67, 1-13. dritsakis, n. (2004), a causal relationship between inflation and productivity: an empirical approach for romania. american journal of applied sciences, 1(2), 121-128. eyden, r.v., difeto, m., gupta, r., wohar, m.e. (2019), oil price volatility and economic growth: evidence from advanced economies using more than a century’s data. applied energy, 233-234, 612-621. faidzin, n., cahyono, h. (2017), pengaruh kurs rupiah per dollar amerika terhadap jumlah wisatawan mancanegara (inbound) dan jumlah devisa parawisata di indonesia tahun 2006: m1-2015: m2. jurnal pendidikan ekonomi, 5(3), 1. available from: https://www. jurnalmahasiswa.unesa.ac.id/index.php/jupe/article/view/21984. gibtiah, g., desiana, l., aryanti, a. (2018), analisis moslem friendly tourism, living cost, culture dan kurs valuta asing terhadap minat wisatawan muslim dalam pengambilan keputusan untuk berkunjung ke jepang. nurani, 18(1), 45-60. gokmenoglu, k.k., fazlollahi, n. (2015), the interactions among gold, oil, and stock market: evidence from s and p500. procedia economics and finance, 25, 478-488. hassani, h., ghodsi, m., huang, x., silva, e.s. (2020), is there a causal relationship between oil prices and tourist arrivals? journal of applied statistics, 2020, 1-12. heij, c., de-boer, p., franses, p.h., kloek, t., van-dijk, h.k. (2004), econometric method with applications in business and economics. new york: oxford university press. huang, x., silva, e., hassani, h. (2018), causality between oil prices and tourist arrivals. stats, 1, 134-154. hung, n.t. (2020), analysis of the time-frequency connectedness between gold prices, oil prices and hungarian financial markets. international journal of energy economics and policy, 10(4), 51-59. ito, k. (2010), the impact of oil price volatility on macroeconomic activity in russia. coruña: economic analysis working papers, no. 2010, 5, colegio de economistas de a coruña. junior, t.c., goodness, c.a. (2018), the effects of oil price uncertainty on economic activities in south africa. cogent economics and finance, 6, 1-17. kosnan, s.s.a., ismail, n.w. (2012), determinants of international tourism in malaysia: evidence from gravity model. jurnal ekonomi malaysia, 47(1), 131-143. liu, d., meng, l., wang, y. (2020), oil price shocks and chinese economy revisited: new evidence from svar model with sign estrictions. international review of economics and finance, 69, 20-32. meltzer, j.p. (2014), the internet, cross-border data flows and international trade. asia and the pacifific policy studies, 2(1), 90-102. misra, p. (2018), an investigation of the macroeconomic factors affecting the indian stock market. australasian accounting, business and finance journal, 12(2), 71-86. muthalib, a.a., adam, p., rostin, r., saenong, z., suriadi, l.o. (2018), the influence of fuel prices and unemployment rate towards the poverty level in indonesia. international journal of energy economics and policy, 8(3), 37-42. nugroho, i.a., gunawan, s., awirya, a.a., nurman, p. (2017), the effect of exchange rate fluctuations on bali tourism sector. jurnal ekonomi dan pembangunan, 25(1), 15-26. ollivaud, p., haxton, p. (2019), making the most of tourism in indonesia to promote sustainable regional development. paris, france: oecd economics department working papers, no. 1535. p1-41. othman, m.h., mohamad, n., arifin, g.m.m. (2018), malaysia’s tourism demand: a gravity model approach. journal of business and social development, 6(1), 39-50. ozturk, i. (2010), literature survey on energy-growth nexus. energy policy, 38, 340-349. pangannavar, a.y. (2014), manipulation theory of inflation: a research study on components of general price rise. journal of indian economy, 1(2), 66-82. perron, p. (1989), the great crash, the oil price shock and the unit root hypothesis. econometrica, 87(6), 1361-1401. pesaran, m.h., shin, y. (1999), an autoregressive distributed-lag modelling approach to cointegration analysis. in: strom, s., editors. econometrics and economic theory in the 20th century: the ragnar frisch centennial symposium. cambridge: cambridge university press. p371-413. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied economics, 16, 289-326. pilbeam, k. (2006), international finance. 3rd ed. new york: palgrave macmillan. rafiq, s., salim, r. (2014), does oil price volatility matter for asian emerging economies? economic analysis and policy, 44(4), 417-441. rafiq, s., salim, r., bloch, h. (2009), impact of crude oil price volatility on economic activities: an empirical investigation in the thai economy. resources policy, 34, 121-132. ramos, c.m.q., rodrigues, p.m.m. (2013), research note: the importance of online tourism demand. tourism economics, 19(6), 1443-1447. rentschler, j.e. (2013), oil price volatility, economic growth and the hedging role of renewable energies. washington, dc: policy research working paper, no.6603, world bank. sabon, v.l., perdana, m.t.p., koropit, p.c.l., pierre, w.c.d. (2018), strategi peningkatan kinerja sektor pariwisata indonesia pada asean economic community. esensi jurnal bisnis dan manajemen, 8(2), 164-176. saenong, z., muthalib, a.a., adam, p., rumbia, w.a., millia, h., saidi, l.o. (2020), symmetric and asymmetric effect of crude oil prices and exchange rate on bond yields in indonesia. international journal of energy economics and policy, 10(2), 95-100. saidi, l.o., adam, p., rahim, p., rosnawintang, r. (2019), the effect of crude oil prices on economic growth in south east sulawesi, indonesia: an application of autoregressive distributed lag model. international journal of energy economics and policy, 9(2), 194-198. saidi, l.o., heppi, m., adam, p., purnamasari, y., arsadsani, l.o. (2020), effect of internet, money supply and volatility on economic growth in indonesia. international journal of advanced science and technology, 29(03), 5299-5310. sam, c.y., mcnown, r., goh, s.k. (2019), an augmented autoregressive distributed lag bounds test for cointegration. economic modelling, 80, 130-141. soebagyo. (2012), strategi pengembangan parawisata di indonesia. jurnal liquidity, 1(2), 153-158. sun, s., wei, y., tsui, k.l., wang, s. (2019), forecasting tourist arrivals with machine learning and internet search index. tourism management, 70, 1-10. millia, et al.: the influence of crude oil prices volatility, the internet and exchange rate on the number of foreign tourist arrivals in indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020 287 tavares, j.m., leitão, n. (2016), the determinants of international tourism demand for brazil. tourism economics, 2016, 1-12. trang, n.t.n., tho, t.n., hong, d.t.t. (2017), the impact of oil price on the growth, inflation, unemployment and budget deficit of vietnam. international journal of energy economics and policy, 7(3), 42-49. vita, g.d. (2014), the long-run impact of exchange rate regimes on international tourism flows. tourism management, 45, 226e-233e. wamboye, e.f., nyaronga, p.j., sergi, b.s. (2020), what are the determinant of international tourism in tanzania? world development perspectives, 17, 100175. world bank. (2016), enabling digital development: how the internet promotes development. washington dc: international bank for reconstruction and development/the world bank. available from: https://www.openknowledge.worldbank.org/handle/10986/23347. yang, c.w., hwang, m.j., huang, b.n. (2002), an analysis of factors affecting price volatility of the us oil market. energy economics, 24(2), 107-119. zengin, b., arici, s. (2017), the effect social media usage forms of occomodation businesses on consumer’s purchassing intentions. journal of business research turk, 9(4), 375-399. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 3 • 2023262 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(3), 262-270. impact of quantum movement theory on energy policy cooper r. wade1,2*, olusegun s. tomomewo1 1institute for energy studies, grand forks, north dakota 58202 usa, 2grid power, little rock, arkansas 72205 usa. *email: cooper.wade@und.edu received: 21 january 2023 accepted: 27 april 2023 doi: https://doi.org/10.32479/ijeep.14241 abstract the federal energy regulatory commission (ferc) has been tasked with ensuring that the united states of america maintains a reliable electric grid that provides its citizens with affordable power and energy security. this responsibility of regulating electric energy delivery comes with the ability to charge and collect interstate commerce tax. in this ability, is the separation of state and federal regulatory of electricity transactions, which is a contested topic in the u.s. supreme court. the reason for this is that ferc is trying to enforce interstate commerce tax control over any equipment that poses the potential to generate electricity. they’re utilizing the 1880’s understanding of direct current (dc) electricity which moves through the “flow of electrons,” and therefore this gives them direct authority over all generators interconnected to the grid. using the quantum movement theory of alternating current established in 2023, this notion of a flow of electrons does not occur on the grid, and therefore restricts the jurisdiction and the taxing ability of ferc (wade and tomomewo, 2023). this change would increase the implementation of distributed energy resources (ders) and save transmission operators, electric utilities, and ultimately consumers up to $500 million per year over the next several decades. keywords: interstate commerce tax, ferc, electron theory, quantum movement theory, energy policy, distributed energy resources jel classifications: g43, h21, k23 1. introduction the energy industry globally is the backbone for keeping the world moving in ways including but not limited to transportation, communication, commerce, security, health, etc. in 2010, globally the world spent over $6.4 trillion on energy where 19% or $1.2 trillion was spent on energy in north america alone (u.s. energy information administration, 2021) (enerdata, 2011). according to the united states energy information administration, over 37.7% of energy consumed in the united states is through the electric grid (u.s. energy information administration, 2021). this trillion-dollar industry provides a critical service to communities around the world as well as in the united states and must maintain reliability in order to provide this service. the u.s. electrical infrastructure is recognized as one of the largest and most complex machines in the world, where the u.s. department of energy is tasked with maintaining its reliability, efficiency, and affordability to maintain energy security (bressand, 2013) (u.s. department of energy, 2021). in order to accomplish this, there is a complex hierarchy of jurisdictional authorities ranging from federal, regional, state and local levels to effectively manage the electric grid. this structure begins at the top with the u.s. department of energy establishing reliability and operational standards through ferc and the north american electric reliability corporation (nerc) (u.s. department of energy, 2015). regional jurisdiction is achieved through regional transmission operators (rtos) and independent system operators that maintain macroscopic grid performance (u.s. department of energy, 2015). the next tier consists of transmission and distribution utilities, where in 35 u.s. states, the electric utilities are regulated through the implementation of public utility commissions (pucs) (hlinka, 2021). lastly, consumers or end-users are at the bottom of the spectrum, which includes ders (u.s. department of energy, 2015). der implementation is growing at an increasing rate due to many factors including renewable energy scalability, reliability this journal is licensed under a creative commons attribution 4.0 international license wade and tomomewo: impact of quantum movement theory on energy policy international journal of energy economics and policy | vol 13 • issue 3 • 2023 263 interests, micro-grid technology improvements, the need for improved localized power quality, demand response, operational efficiencies, etc. in 2015 the u.s. had 264 mw of ders in operation, and the current growth rate it is expected to achieve 387 mw of operating ders by 2025 (kellison, 2020). as der saturation increases operationally on the u.s. electric grid, this creates an operational efficiency need to streamline the implementation of ders. currently, ders are regulated through local jurisdictions such as the respective electric utilities and pucs, where in this manner the localized need is regulated by the localized authorities having jurisdiction. no one is better familiar with the localized needs and resources of the grid than the localities themselves. there have been numerous attempts throughout the recent century to regulate ders directly through ferc control. this in effect would create unnecessary regulatory procedural inefficiencies and result in fewer ders being implemented, thus counterintuitive to the very mission of achieving affordable, efficient, and reliable electricity. the basis for this argument used by ferc is relying on the idea of where electrons flow on the grid rather than the energy itself when applied to the topic of interstate commerce. the quantum movement theory of alternating current provides a quantum physics basis for understanding that electrons don’t flow in an alternating current environment, and therefore ferc should redirect its claim to regulating energy that traverses state lines (wade and tomomewo, 2023). this theory provides a scientific basis as to why ferc should not gain direct control of ders, where this article discusses the legal implications of both sides. 2. background der from the terminology using the word “distributed” is in reference to smaller generators that are distributed throughout the grid in various methods. the location and configuration of these ders can be classified as a few different things depending upon the customer and interconnection method. in general, to be classified as a distributed generation resource the generator has a nameplate rating of <20 mw ac according to nerc (north american electric reliability corporation, 2016). in most instances these generation resources are <10 mw ac. this is mostly due to voltage and conductor sizing limitations to be able to feasibly handle much more distribution of power at voltages ranging from 5kv (5,000v) to 34.5kv (34,500kv) (u.s. department of energy, 2015). an example of a typical electric grid structure of a substation and distribution circuit is shown in figure 1. this single line diagram indicates the inbound transmission feeder to the primary bus at the substation on the left side of the diagram indicating common voltages of 69kv, 115kv, 138kv, or 230kv. the inbound power then passes through a transformer to be stepped down to lower distribution voltages commonly resulting in 12.5kv, 13.8kv, or 34.5kv. on the low side of the transformer at distribution medium voltages you have multiple distribution feeders that branch out to deliver power to the various customers on those circuits. on the secondary side of the transformer, it can be seen that there is a shunt or disconnecting means branching from the secondary bus, another for the distribution circuit as a whole, and lastly at the customer’s load which consists of 4 inductive motor loads, electronic loads, and static loads. according to the north american electric reliability corporation, a der can be classified into two different categories of retail distributed energy resources (r-der) and utility distributed energy resources (u-der) (north american electric reliability corporation, 2016). r-der is a generation resource interconnected behind the meter at a customer’s facility at either single or three phase service and is unlimited by generation nameplate capacity, whereas u-der is interconnected along the distribution circuit or at the substation secondary bus not located behind the meter and therefore not offsetting customer site load and is generally ranging in nameplate capacity from 0.5mw ac (500kw) to 20mw ac (20,000kw) (north american electric reliability corporation, 2016). in the r-der scenario the primary purpose of the der is to offset the demand and energy located at the customers facility, whether it is a home or business. in the u-der scenario the owners of those ders are usually either utilities or investors that are serving utilities that have located the der in a place that needs that amount of power. this scenario is like the r-der strategy except the metering point can be viewed as the primary bus of the substation, which figure 1: diagram of typical distribution substation with transmission feeds (left) and distribution feeds (right) that serve residential and commercial customers (north american electric reliability corporation, 2016) figure 2: figure 1 with u-der and r-der generator integration methods (north american electric reliability corporation, 2016). wade and tomomewo: impact of quantum movement theory on energy policy international journal of energy economics and policy | vol 13 • issue 3 • 2023264 is at transmission voltage. ideally, the energy generated by the u-der would never (or be less likely) to impact the transmission system by entering the primary bus within the substation. the very nature of ders in either r-der or u-der techniques is to place generation where it is needed most. this leads to the composite load model created by the north american electric reliability corporation that is shown in figure 3. this illustration shows how u-der and r-der need to be evaluated with consideration of substation secondary bus generation and load values. there are several ways to evaluate a der on a substation which can be at the distribution feeder breaker and the main breaker for the secondary bus of the substation. in a conceptual model like what is shown in figure 3, imagine you have an r-der that has a nameplate capacity of 1mw ac and a distribution circuit minimum load of 1.5mw ac. in this scenario, the generation from the r-der should never make it to the distribution circuit feeder breaker and onto the secondary bus, because the load is always greater than the generation supply. this is a simple loadflow analysis understanding for electrical engineering. the same understanding applies to u-ders interconnected under a dedicated feeder breaker on to the substation secondary bus shown in figure 3. in this scenario, imagine that the minimum load on the main breaker of the secondary bus is 5mw ac and the u-der nameplate capacity is 4mw ac. using basic engineering principles and understanding of electric current, it can be concluded that the electricity should not move through the transformer and touch the primary bus. this would mean that the electric current would be moving against the overall macro direction of electric movement and therefore back-feeding. a der is in itself a complex machine interconnected to a complex system, and like the entire energy industry has to comply with policies and regulations set in place. in many ways, policy is what drives the development of energy resources. this has been recognized in recent decades with a higher adoption of customer owned generation rather than primarily large, centralized generators owned and/or operated by electric utility providers. this is largely driven by the technological developments in renewable energy and storage technology as well as the financial feasibility for customers to own their own source of power generation. this change in electricity delivery has created new challenges that the regulatory authorities such as the u.s. department of energy, federal energy regulatory commission, north american electric reliability corporation, state public service commissions, regional transmission operators, independent system operators, and electric utilities will have to adapt to. the primary reason that ders are a challenge for policy regulators and electric utilities is due to the change in the movement of electricity. traditionally, electric energy was operated and managed by electric utilities and strategized in a way that electric energy is generated at a large power station, transmitted at high voltages over longer distances, transformed to lower voltages and distributed to local homes and business at their required service levels. in this sense, electricity flowed in “one direction” from the generator to the ultimate end user. the energy transition began to pick up speed in the 1990’s when homeowners and businesses found it to become common place to install a backup generator on their home ran from either diesel or natural gas. as prices lowered and it thus became more feasible to have reliable backup power, more and more individuals began utilizing them. as rates for electric demand increased over time, large businesses found it more and more enticing to utilize behind-the-meter power generation to lower their demand charges. this practice is commonly known as peak shaving or demand shedding and consists of the customer lowering their overall peak demand in a way that allows them to save money on their electric utility bills. around the turn of the century in the early 2000’s, solar started emerging as an acceptable power generation resource that businesses could implement for peak demand shaving purposes as well as public relations claims (u.s. department of energy, n.d.). the current market has reached a time where customer owned generation is becoming more commonplace and therefore states began establishing net-metering policies to allow customers to generate their own energy and be a net-zero electric user from the grid on an annual basis. this new rate schedule defining compensation for customer owned generation and federal tax incentives for renewable energy gave solar and wind a boost for quicker adoption rates among consumers. from 2010 to 2020 alone, the national renewable energy laboratory reported decreased costs for turnkey residential solar projects by over 64% and commercial projects by over 69% (feldman et al., 2021). as energy storage continues to decrease as well, this is driving the rapidly increasing deployment of ders in the united states (kellison, 2020). with this background in development, it can be seen why there is a concern between the traditional notion of “one direction” of power now transitioning to a “two direction” movement of power. 3. quantum movement theory the quantum movement theory of alternating current was developed during 2021-2022 by cooper r. wade and established figure 3: figures 1 and 2 modified to show the composite load model, which is the recommended method for evaluating cumulative consumer generation and load (north american electric reliability corporation, 2016) wade and tomomewo: impact of quantum movement theory on energy policy international journal of energy economics and policy | vol 13 • issue 3 • 2023 265 in 2023 (wade and tomomewo, 2023). this theory established two equations that allow the movement of electrons to be quantified based upon the macroscopic movement of energy in any system, more effectively with regards to this research is applying this theory to the impact of electron movement due to energy generated by ders. the two equations developed allow insight into: (1) the number of electrons moved given a specific amount of energy and (2) the distance these electrons traveled given the same amount of energy. equation 1 shown below will result in the amount of electrons moved given a specific amount of energy in an electric environment: e iq fn = 2 (1) equation 2 shown below will result in the distance that the electrons moved given a specific amount of energy in an electric environment: d iqaw fd em a = 2 � (2) the variables indicated in the previous equations are shown in table 1 with their respective constant values and corresponding units. a previous study conducted two examples utilizing this theory for the following scenario with a current of 20 amps of alternating current moving through a 12-gauge copper conductor at a frequency of 60 hertz. the amount of electrons necessary to move this amount of energy was found to be 1.0402515 × 1018 electrons oscillating through a cross-sectional area of a wire. the distance traveled by these same electrons was found to be 4.063322 × 10-6 cm that the oscillating electrons traveled in either direction inside of the conductor given the specific energy moved. this theory directly supports and promotes the notion that electrons don’t flow. this theory provides a significant mathematical breakthrough that allows anyone the ability to calculate the movement of electrons in both direct current and alternating current by modifying the respective frequency. when performed, the results demonstrate electron behavior and allow researchers to interpret electron movement in various environments. the concept of a “flow” of electrons as previously mentioned and discussed further in the following sections, is proven incorrect by equations 1 and 2 developed by the quantum movement theory. it is only logical that the policies used to regulate the electric energy industry in the united states are appropriately based upon the science of how electric energy moves. 4. federal and state jurisdiction in the early 1900’s, the united states federal government determined that due to the growing gas and electric utility industries they needed to set in place an appropriate regulatory structure. the federal power act established the framework to set in place federal regulation of the electric grid in the united states on june 10, 1920 (federal power act, 1920) this federal regulation of the electric industry was passed onto the responsibility of the federal power commission until being transferred into the federal energy regulatory commission in 1977 (greer, 2022) (greenfield, 2018). the purpose of their incorporation according to the federal power act is to regulate the interstate commerce of electricity and charge an interstate commerce tax for such electricity as established in parts ii and iii of the federal power act (federal power act, 1920). in 1935, the federal power act was revised to more explicitly draw the line between federal and state jurisdictions of electric power delivery and outlined ferc’s jurisdiction as the following in section 201 (b) (1): “authority to regulate ‘the transmission of electric energy in interstate commerce’ and ‘the sale of electric energy at wholesale in interstate commerce’” (dennis et al., 2016). further continued in section 201 (b) (1), the united states congress explicitly excluded the following electric grid infrastructure from federal regulation: 1. “facilities used for the generation of electricity 2. facilities used for local distribution of power to retail customers 3. facilities used for transmission of electricity strictly in intrastate commerce, and 4. transmissions of electricity to be used entirely by the transmitter” (dennis et al., 2016). and lastly clarifying once again in section 201 (a): “[f]ederal regulation. ..extend [s] only to those matters which are not subject to regulation by the states” (dennis et al., 2016). it can be clearly and explicitly seen based on the previous three cited statements from section 201 of the federal power act of 1930 that the federal government has no jurisdiction over electricity that doesn’t cross state lines. throughout the decades since the passing of the federal power acts of 1920 and 1930, the lines separating federal and state jurisdiction over the regulation of electric infrastructure has become less black and white and more grey. when these laws and regulations are written there are always special case scenarios that can be reviewed and granted depending upon application. this has happened several times in the last century, which has contested the jurisdictional boundary. there have been a large amount of ferc proceedings, briefings, federal court rulings, and supreme table 1: variables and values symbol variable value/units i current amps q coulombs 1c=6.241509 × 1018 electrons a surface area of conductor cm2 w atomic weight grams (g) f frequency 60 hertz dm material density g/cm 3 ea free electrons 1 electron/atom (e/a) d distance to be calculated (cm) en number of electrons to be calculated wade and tomomewo: impact of quantum movement theory on energy policy international journal of energy economics and policy | vol 13 • issue 3 • 2023266 court cases that have influenced the jurisdictional boundary. early on, ferc has tried to expand its regulatory jurisdiction such as in 1951 in federal court for wisconsin-michigan power co. v. fpc, where ferc: “rejected an argument that it did not have authority over certain wholesale energy sales because the energy only traversed facilities used for local distribution in the state where the energy was consumed. ferc explained that ‘nothing in the [fpa] makes our jurisdiction. over sales of electric energy dependent upon the nature of the facilities involved in effecting the sale’” (peskoe, 2018). this continues explicitly in a ferc proceeding in 1965 for indiana and michigan electric co. (33 fpc 739), where ferc: “rejected similar argument, holding that ‘there is nothing in the power act that makes commission jurisdiction over sales dependent on whether the facilities used are local distribution facilities” (peskoe, 2018). in these examples ferc has maintained that their jurisdiction is based upon the type of sale, being wholesale energy, and not based upon the transfer of electricity over a state border. this directly goes against what congress mandated in 1920 and 1935 in the federal power act. this has been challenged many times over the years by electric utilities, public service commissions, regional transmission operators, and industry associations, where ferc has been able to maintain its posture on regulating wholesale electricity. in 2010, this jurisdictional debate was directly challenged in ferc docket el10-64-000 by the petition to intervene from the sacramento utilities district where they argued: “sales of energy by a der should not be subject to ferc’s jurisdiction because they are not ‘in interstate commerce.’ the utility argued that ‘as a physical matter sales of power over lower voltage distribution wires are unlikely, on account of impedance, to enter the [interstate] bulk power system.’ it cautioned that ‘a decision asserting commission jurisdiction over all distributionlevel power sales to utilities would necessarily bring within the commission’s regulatory reach literally millions of homeowners, farmers or businesses. who sell power to their local utility’” (peskoe, 2018). the petition was denied, but their argument is justified. if ferc is using the concept of having a unified and interconnected electric grid as a vague reason to extend their regulating reach to become further within state borders and impact every consumer with a generation source, then they must do it from a systems operation approach. the argument that generation from someone’s home will impact the greater electric grid and become interstate commerce is highly improbable of occurring. ferc has ascertained that since it is technically possible for electricity from a der to make it into a wholesale energy transaction then it should have jurisdiction over all of the consumers that could impact the interstate system. the california public utilities commission clarifies ferc’s intentions to regulate ders in the same docket: (docket no. el10-64-000, 2010). “the commission’s fpa authority to regulate sales for resale of electric energy and transmission in interstate commerce by public utilities is not dependent on the location of generation or transmission facilities, but rather on the definition of, as particularly relevant here, wholesale sales contained in the fpa” (132 ferc 61,047, 2010). it is made clear that overtime the envelope has been continuously pushed for ferc to take on more and more regulatory authority from the state’s control. the next question that arises is, “on what basis does ferc determine that ders have a large impact to the bulk transmission system and therefore interstate commerce?” this what forms the base that is the problem being addressed in this research and outlined in the following section. 5. policy problem currently, ferc has used the argument of regulating “any wholesale electricity” transaction, while not considering the “in interstate commerce” clause, to achieve the jurisdictional authority to regulate any wholesale electricity transaction between utilities even if it is within the same state border. this is a continuing argument and very relevant to the increased development and installation of ders on the electric grid. if ferc was responsible for regulating ders of any type including r-der and u-der, then this would be a massive inhibitor to constructing ders. from the simplest perspective there would at least be applied interstate commerce taxes and longer approval timelines which increase development and operations costs. this prompts the question, “how does ferc justify regulating ders when they’re designed for localized power distribution and interconnected on medium voltage distribution lines?” the reasoning that is used by ferc can be summarized in two major points: 1. the electric grid is one large, interconnected grid including distribution, transmission, and generation 2. the “flow of electrons” or “electron flow” from ders can go anywhere. point (1) that is mentioned, is technically true. the modern electric grid is one large interconnected complex machine. point (2) is incorrect by nature, whereas electrons in an alternating current system do not “flow” in fact there is no “flow of electrons”, but rather an oscillation. legal research conducted during this evaluation has found 323 times that ferc/fpc has recognized the “flow of electrons” or “electron flow” in any sense during a court case, docket, or briefing. this statement relating the “flow of electrons” to the electric grid became common place during the late 1800’s when most of the electric grid consisted of direct current power generation, delivery, and consumption rather than alternating current. however, the modern electric grid consists primarily of alternating current compatible components, and the correct argument should be used to regulate such components. since the location of the “flow of electrons” is the determining factor that indicates whether electricity from a der impacts the bulk electric system in interstate commerce, this is the focal point of this research. to summarize, the problem is that the determining factor being used to justify ferc jurisdictional boundary is relying on the wade and tomomewo: impact of quantum movement theory on energy policy international journal of energy economics and policy | vol 13 • issue 3 • 2023 267 “flow of electrons”. quantum movement theory applied to electrical concepts does not allow for any “flow of electrons” in an alternating current electric grid. there is power flow that occurs 24/7 on the electric grid from ders, however the purpose of ders is to serve local areas at medium voltages. there are scenarios where der power generation can exceed the localized load, but this is not a design standard for ders to transmit power over long distances. if they do, then that amount that traverses a state border would be subject to interstate commerce tax. to reiterate, the design purpose of a der is to serve a localized area and in current scenarios should not continuously export to the transmission system. the current ferc jurisdiction as it stands does not represent wholesale electricity transactions, but actually wholesale transactions between utilities including intrastate commerce. spreading the impact to include all r-der and u-der would greatly impact development and installation of new generation assets. individual consumers such as homeowners and businesses would not want the added requirements, timeframes, and cost implications (taxes and other indirect cost factors) that would follow with doing so. figure 4 illustrates a flowchart that shows the jurisdictional boundary as it currently stands. in essence, what this indicates is if the der does not offset consumption for a specified consumer within the utility it is interconnected to then it is subject to ferc authority (excluding purpa qualified facilities). under this representation all consumer owned ders that are designed to offset consumption would avoid federal regulation, which includes homes and businesses. purpa facilities are different and are outlined in the public utilities regulatory policies act of 1978, which is where the acronym purpa comes from (united states congress, 1978). a purpa qualifying facility is one that is either a cogeneration facility generating electricity and another form of useful thermal energy or a small power production facility consisting of a renewable generation source located within a mile of the load source where the generation amount does not exceed the load up to 80 mw ac (federal energy regulatory commission, n.d.). these facilities are able to get. fast-tracked approval for implementation and are granted avoided cost rates (generally wholesale) from the interconnected utility. these facilities are able to get special treatment and avoid ferc authority. this is not seen as a “sale for re-sale” of electricity, which has been the common concern for classifying net metered ders under ferc regulation. the argument is that overgeneration is considered wholesale power due to the fact that the utility is delivering it to another customer even when the “transaction” was not at wholesale rates. if ferc receives the jurisdictional boundary they are seeking by using the “electron flow” argument, then they will regulate any consumer owned power generation source no matter if they export to the distribution grid or not. this situation is represented well on march 26, 1941, in supreme court case, connecticut light and power co. v. federal power commission (324 u.s. 515), where connecticut light and power co. states: (324 u.s. 515, 1945). “federal jurisdiction was to follow the flow of electric energy, an engineering and scientific, rather than a legalistic or governmental, test…every facility from generator to the appliance for consumption may thus be called one for transmitting such interstate power. by this test the cord from a light plug to a toaster on the breakfast table is a facility for transmission of interstate energy if any part of the load is generated without the state. it has never been questioned that technologically generation, transmission, distribution and consumption are so fused and interdependent that the whole enterprise is within the reach of the commerce power of congress, either on the basis that it is, or that it affects, interstate commerce, if at any point it crosses a state line” (324 u.s. 515, 1945). this argument relies heavily on the “uncertainty” of electron movement and doesn’t place much weight on the dependency for energy movement between states to necessitate jurisdictional claim over it. in 2019, there were over 2,000,000 commercial and industrial solar arrays installed and operating that were either u-der or r-der in style, and if this jurisdictional change were to be implemented then all of these home and business owners would be subject to federal energy regulations (merchant, 2019). that is just for solar alone and does not include any other gridinteractive generation source that consumers may have installed. the original intent of congress under the federal power act was not to regulate individual end customers, but to regulate wholesale market transactions, whereas this jurisdictional change would directly go against that. the interstate commerce act was passed on february 4, 1887, which preemptively gave the federal government power “’to regulate commerce with foreign nations, and among the several figure 4: flowchart indicating whether a specified der is subject to state or federal regulation (peskoe, 2018). wade and tomomewo: impact of quantum movement theory on energy policy international journal of energy economics and policy | vol 13 • issue 3 • 2023268 states’” including taxing authority (united states senate, n.d.). it wasn’t until 1920 that the federal power commission was established to regulate and tax electricity in interstate commerce. interstate commerce taxes are assessed once a year or per quarterly basis depending on operator via wholesale energy transaction data provided by transmission owners/operators per ferc’s rules and regulations. this is done through the submittal of data from electric utilities to their respective rtos/isos and each submits a ferc form 1, which are evaluated by ferc. it is then verified which tax rate will be charged per gwh reported of wholesale. transactions across all rtos/isos in order to reach the actual amount of taxes needing to be collected versus the budgeted amount. figure 5 contains the interstate commerce tax data for every gwh reported to be sold in wholesale transactions from 2010 to 2020 compared to the cumulative gwh generated in the united states. it is to be noted that detailed data for years 2013 and 2014 that matched the format and granularity for years 20102012 and 2015-2020 was unable to be retrieved from ferc. from 2010 to 2020 there has been both an increase in the proportion of taxed energy versus total generation as well as the cumulative taxes collected. during this timeframe of 11 reporting years, cumulative interstate commerce taxes have increased by over 42% and the proportion of taxed energy vs. total generated energy has increased by over 12% during this time, while total energy production has maintained relatively the same over this period. if proposed jurisdictional changes take place, it will be a significant increase in the amount of data processing that will occur through ferc and therefore increase taxes paid by der owners. based on the estimates in figure 6 it is clear that taxes will continue to soar and exponentially more so if jurisdictional shifts occur towards the regulation of ders. 6. conclusion the application of this research is to show what behavior the electron as a particle is having within an alternating current electric grid, which will assist in determining the solution to this policy issue. the hypothesis is that given a cumulative der generation load that is lower than the cumulative substation load as measured on the substation secondary bus, then the overall movement of electricity will be an importing of electricity from the transmission system and not a net-export of electricity onto the transmission system. this would result in no net energy flow onto the grid and therefore no electron movement onto the grid. it would force those using the “electron flow” or “flow of electron” argument to change the basis for their reasoning or succumb to the understanding that electricity works differently than how it is currently being outlined. even in the event of a net-exporting of energy to occur onto the transmission system, then the magnitude that there is electron movement occurring is insignificantly small. policy and regulations have huge implications on the energy industry with regards to the development of technology and speed of deployment. the current policies set in place at both the federal and state levels are not perfect but work to address issues at their given level without needing to move further up the food chain. with ders this could not be more true, because as the world grows into an increasingly carbonless world, energy plays a huge role in that. every year, more consumers and companies are setting and establishing renewable energy or carbon neutrality goals. solar, wind, and energy storage technologies would not have grown as much as they have without proper policy to support them. figure 6 demonstrates the policy structure that allowed this to happen. cohesively, the federal government was able to set goals and incentives at the federal level to get this accomplished, and the state level governments adapted and implemented policies that worked for their localized needs and interests. whereas figure 7 represents the structure where ferc takes control over der generation. if that is the case, then ferc has essentially gone from overseeing only large energy transactions to now including the smallest energy transactions. the question has to be asked, “what role does the state have left to play in this?” in this scenario, there wouldn’t be much reason to maintain any state regulation since their authority has essentially been stripped with the exception of maintaining some control over consumer rate regulation to ensure market fairness. figure 5: chart indicating interstate commerce tax collected for years 2015-2020, with forecasted amounts for years 2030, 2040, and 2050 based on historical increases at a 95% confidence interval. figure 6: chart indicating federal and state jurisdiction over the electric industry at its current status. wade and tomomewo: impact of quantum movement theory on energy policy international journal of energy economics and policy | vol 13 • issue 3 • 2023 269 in summary, the “electron flow” or “flow of electrons” argument is incorrect based upon the hypothesis of this research, whereas the focus should be turned to the flow of electrical energy. with ders, the flow of electrical energy is also up for debate given the nature of ders to be to provide localized power generation not intended for long distance transmission and delivery. either way, the notion of ders transmitting across state lines in wholesale transactions is unlikely and unintended. the policy debate at hand is between who should regulate ders, the federal or local authorities having jurisdiction. it is reasonable to expect ders to continue to gain saturation on the grid as well as market share. due to this, ferc wants to increase controllership over these resources more so than the current level of control. their current control extends only to ders actively participating in wholesale markets and the ability to develop standards and procedures for ders to follow nationally. in this method, ferc establishes guidelines that states, local jurisdictions, grid operators, and electric utilities adopt according to their local/regional need. this process is currently not in need of repair and shouldn’t be subjected to unnecessary regulatory inefficiencies by assigning ferc direct authority over all ders. as discussed, the argument being used to support the federal claim of deserving control over all ders is incorrect in nature and is based upon a law written when the understanding was that electric energy moves via a flow of electrons as the grid was previously lead by direct current technology rather than alternating current. the quantum movement theory provides clarity and understanding for what is occurring inside of an electrified conductor (wade and tomomewo, 2023). this theory refutes the claim by federal regulators to assert authority over localized power generation within the states’ borders. therefore, the basis for federal regulation should be shifted to managing energy resources rather than the quantum particles serving as the building blocks that allow the system to operate. either way, the consensus remains the same. as the world progresses and technological breakthroughs continue to change, these types of discussions should be welcomed. depending upon perspective, this argument can appear pointless, however this is a valuable part of the energy industry in the united states. the ability to discuss recurring issues overtime provides the energy industry with a structure of “checks and balances” that allow policies and regulatory authorities to adapt as the needs change overtime. in this manner, industry can continue to have these debates which helps further ensure that the decisions being made are the correct ones for u.s. taxpayers. this article serves as a part of this recurring “checks and balances” as the industry continues to develop together. no policy is perfect in any scenario and every policy remains relative to the time of enactment. 7. acknowledgment c. r. wade thanks the support of his family, friends, educators, and colleagues in this endeavor to further expand the knowledge base of quantum physics in electrical systems and the implications thereof on energy policy. references 132. ferc 61,047. (2010), available from: https://www.dwt.com/files/ uploads/documents/advisories/10-10_caiso_0715.pdf amendment to motion to intervene of the sacramento utility district, docket no. el10-64-000 (2010). available from: https://casetext. com/case/sacramento-municipal-utility-district-v-us-5. bressand, a. (2013), in: goldthau, a., editor. the handbook of global energy policy. united states: wiley blackwell. connecticut light and power co. federal power commission (324 u.s. 515). (1945), available from: https://supreme.justia.com/cases/ federal/us/324/515 dennis, j., kelly, s., nordhaus, r., smith, d. (2016), federal/ state jurisdictional split: implications for emerging electricity technologies. united states: lawrence berkeley national laboratory. available from: https://www.energy.gov/sites/prod/ files/2017/01/f34/federal%20state%20jurisdictional%20split-implications%20for%20emerging%20electricity%20technologies. pdf enerdata: intelligence + consulting. (2011), world energy expenditures. available from: https://www.enerdata.net/publications/executivebriefing/world-energy-expenditures.html#:~:text=more%20than%20 us%246%2c000bn,and%20in%20some%20cases%20first federal energy regulatory commission. (2022), purpa qualifying facilities. available from: https://www.ferc.gov/qf federal power act. (1920), available from: https://www.energy.gov/sites/ prod/files/2019/10/f67/federal%20power%20act_2019_508_0.pdf feldman, d., ramasamy, v., fu, r., ramdas, a., desai, j., margolis, r. (2021), u.s. solar photovoltaic system and energy storage cost benchmark: q1 2020. united states: national renewable energy laboratory. available from: https://www.nrel.gov/docs/ fy21osti/77324.pdf greenfield, l.r. (2018), an overview of the federal energy regulatory commission and federal regulation of public utilities. united states: federal energy regulatory commission. available from: https://www.ferc.gov/sites/default/files/2020-07/ferc101.pdf figure 7: chart indicating what federal and state jurisdiction would look like if ferc’s authoritative jurisdiction is changed to regulate ders wade and tomomewo: impact of quantum movement theory on energy policy international journal of energy economics and policy | vol 13 • issue 3 • 2023270 greer, m. (2022), state regulations, policies, and updates on states with retail choice. available from: https://www.sciencedirect.com/ science/article/pii/b9780128213650000232 hlinka, m. (2021), us utility commissioners: who they are and how they impact regulation. s&p global: market intelligence. available from: https://www.spglobal.com/marketintelligence/en/ news-insights/blog/us-utility-commissioners-who-they-are-andhow-they-impact-regulation kellison, b. (2020), the next five years will see massive distributed energy resource growth: the momentum is clear, despite covid-19 impacts in 2021. united kingdom: wood mackenzie. available from: https://www.woodmac.com/news/editorial/dergrowth-united-states/#:~:text=the%20report%20also%20finds%20 that,a%20new%20peak%20in%202025 merchant, e. (2019), us surpasses 2 million solar installations as industry looks to ‘dominate’ the 2020s. united states: greentech media. available from: https://www.greentechmedia.com/articles/ read/u-s-solar-installations-top-2-million north american electric reliability corporation. (2016), reliability guideline: modeling distributed energy resources in dynamic load models. available from: https://www.nerc.com/comm/ pc_reliability_guidelines_dl/reliability_guideline_-_modeling_der_ in_dynamic_load_models_-_final.pdf peskoe, a. (2018), the case against direct ferc regulation of distributed energy resources. united states: harvard law school. available from: http://eelp.law.harvard.edu/wp-content/uploads/ the-case-against-direct-ferc-regulation-of-distributed-energyresources-pdf u.s. department of energy. (2021), a reliable, affordable clean power sector is here. it’s time to invest in the future. available from: https://www.energy.gov/articles/reliable-affordable-clean-powersector-here-its-time-invest-future u.s. energy information administration. (2021), u.s. energy consumption by source and sector, 2021. available from: https:// www.eia.gov/energyexplained/us-energy-facts/images/consumptionby-source-and-sector.pdf united states congress. (1978), h.r.4018-public utility regulatory policies act. available from: https://www.congress.gov/bill/95thcongress/house-bill/4018 united states department of energy. (2022), the history of solar. available from: https://www1.eere.energy.gov/solar/pdfs/solar_ timeline.pdf united states department of energy: office of electricity delivery and energy reliability. (2015), united states electricity industry primer. available from: https://www.energy.gov/sites/prod/files/2015/12/f28/ united-states-electricity-industry-primer.pdf united states senate. (2022), the interstate commerce act is passed. available from: https://www.senate.gov/artandhistory/history/ minute/interstate_commerce_act_is_passed.htm wade, c., tomomewo, o. (2023), quantum movement theory of alternating current. american journal of energy research, 11(1), 31-37. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 2 • 2023526 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(2), 526-536. analysis of the effect of energy prices on stock indexes during the epidemic crisis shafa guliyeva* azerbaijan state university of economics (unec), azerbaijan. *email: shafa_guliyeva@unec.edu.az received: 15 december 2022 accepted: 10 march 2023 doi: https://doi.org/10.32479/ijeep.14052 abstract petroleum and natural gas, which are among the most used energy sources in the world, have a significant impact on financial markets and macroeconomic indicators as they are used as raw materials in many fields. for this reason, us, england, japan, russia, turkey, brazil, and india, as energy importers and developing countries, may be affected positively or negatively by changes in energy prices. the main purpose of this study is to examine the correlation between brent oil, crude oil (wti), and natural gas (ng) prices and moscow stock exchange index (rtsi), borsa istanbul index (xu100), bovespa brazilian stock exchange index (bvsp), indian national stock exchange nifty 50 index (nsei), standard and poor’s 500 index (s and p 500), london stock exchange (ftse 100), and тokyo stock exchange (n225). in the study, weekly data between february 16, 2020 and december 26, 2021 were examined. vector autoregressive (var) model was used to examine the correlation between the variables included in the analysis, and the direction of the correlation between the variables was determined by the granger causality test. according to the results of the var model, brent oil and crude oil prices have significant effects on the indices included in the analysis; however, natural gas price does not have a significant effect on indices, brent oil, and crude oil prices. on the other hand, the results of the granger causality test confirm the findings of the var analysis. granger causality test results reveal that in granger’s sense, only bvsp and nsei are the cause of brent oil price, rtsi, bvsp, nsei, xu100, s and p 500, ftse 100, and n225 are the cause of wti, and wti is the cause of nsei. keywords: brent oil, crude oil, natural gas, stock market i̇ndex, var analysis, granger causality jel classifications: b26, c58, g14, g15, o16 1. introduction stocks reflect enterprises’ potential profitability. therefore, oil shocks’ influence on the stock market is a helpful economic indicator. since asset prices reflect organisations’ future net earnings, it’s important to lessen the effects of present and future oil shocks on stocks and returns before they happen (jones et al., 2004 p. 13). in the simplest sense, energy, which is the basis of life, is vital for the survival and development of humanity (fouquet, 2011 p. 1). with the mechanisation of production and the production of steam-powered machines, the need for energy has continuously increased, and economic growth and prosperity have become more dependent on energy (ghosh, 2002 p. 125). it is necessary to consume energy at a certain level in order to achieve rapid economic development (özdemir, 2012 p. 61). energy is one of the most important factors that directly or indirectly determines the production level, national and international competitiveness, budget balances, current account deficits, and economic growth levels of countries (esen, 2013 p. 48, 49). in this respect, for the continuity of economic growth, it is important to provide timely, low-cost, high-quality, reliable energy sources (bayraktutan et al., 2012 p. 30). determining the factors affecting stock prices will enable the investor to make the right investment decisions. if the factors affecting the stock prices are determined correctly, the success of the investments to be made will be higher. factors affecting stock prices are macroeconomic, enterprise-specific, and this journal is licensed under a creative commons attribution 4.0 international license guliyeva: analysis of the effect of energy prices on stock indexes during the epidemıc crisis international journal of energy economics and policy | vol 13 • issue 2 • 2023 527 other (dizdarlar and derindere, 2008 p. 113). macroeconomic factors: interest rates, inflation, exchange rates, money supply, economic growth, industrial production index, gold prices, foreign trade balance, foreign portfolio investments, and energy price changes (güngör and yerdelen, 2015 p. 149). microeconomic factors: capital structure, profit distribution policies, corporate governance, intellectual capital, insider trading, and financial ratios (demir, 2001 p. 110). other factors are psychological factors, political factors, seasonal changes, and speculation (kaya et al., 2015 p. 167). the effect of energy prices on national economies and financial markets varies depending on whether the country is an energy importer or exporter. countries that import the majority of energy can be adversely affected by changes in energy prices. for this reason, the long and short-term correlations between energy prices (oil and natural gas) and stock market indices of four developing countries were examined in this study. in this direction, the study is important as it will help the investors who are present and who aim to invest in the brent oil, crude oil, and natural gas prices, and moscow stock exchange index, borsa istanbul index, bovespa brazilian stock exchange index, indian national stock exchange nifty 50 index, standard and poor’s 500 index, london stock exchange, and тokyo stock exchange in the decision-making process. the study consists of four parts. in the first part of the study, a literature review related to the studies on this subject was made. in other words, studies on the effects of volatility in energy resource prices on the stock market indices of developed and developing countries have been conducted. in the second part of the study, information is given about the definition of the variables to be analysed and the methods to be used in the analysis. in the third part of the study, the findings obtained as a result of the analysis of dependent and independent variables are included and interpreted. in the conclusion part, which constitutes the fourth chapter, a general evaluation of the study was made. 2. literature review in this section, studies on energy price changes and stock market indices are discussed, and the results of the studies examined in this direction are presented. the number of academic studies is increasing day by day due to the importance of energy and the volatility of its prices. price fluctuations in one market can rapidly propagate other markets. in recent decades, there has been much research effort to study the relationship between gold, crude oil, and the stock markets (gujarati, 2013; jain and biswal, 2016; coronado et al., 2018; tursoy and faisal, 2018; shabbir and kousar, 2020; shaikh, 2021), and discover evidence from developed or emerging markets yielding various results. (samanta and zadeh, 2012; partalidou et al., 2016; raza et al., 2016; arfaoui and rejeb, 2017; wei and guo, 2017; karhan and aydın, 2018; pandey and vipul, 2018; alio et al., 2019; singhal et al., 2019; kumar et al., 2019; majidli and guliyev, 2020; kumar et al., 2021; kumau et al., 2020; gherghina et al., 2020; humbatova et al., 2020; karakuş, 2021). some of the empirical studies employed vector autoregressive model (var) (ding et al., 2016; chkili, 2022; grabias, 2022; nairobi et al., 2022; kelesbayev et al., 2022). however, not a single study was able to explain the specific relationship between gold, crude oil, and the stock market (uthumrat, 2022 p. 350-356.). in recent decades, there has been much research effort to study the relationship between the effect of energy prices on stock ındices in the period of covid-19, and relationship between oil prices and stock ındustry ındex prices akbulaev and rahimli (2020). suleymanli et al. (2020) akbulaev et al. (2022). between 2001 and 2010, managi and okimoto (2013) used markovswitching var (ms-var) analysis to detect the existence of a relationship between oil, energy company stocks, and interest in the united states. as a result of the analysis, they found a positive relationship between oil prices and stocks. dhaoui and khraief (2014) used the egarch method to examine whether the stock returns of the usa, switzerland, france, canada, england, japan, singapore, and australia countries were affected by oil shocks between january 1991 and september 2013. as a result of the analysis, they found that returns were significantly affected, with decreased returns and increased volatility. they stated that this was due to the risk of an increase in oil prices and the uncertainty in the market. benkraiem et al. (2018) examined whether there is a relationship between s&p 500 monthly price data and oil and natural gas prices in the usa between january 1999 and september 2015 using the qardl-ecm method. they discovered an unstable long-and short-term relationship as a result of the analysis, despite the fact that the amounts were insignificant, and emphasised that energy prices were the driving force for stock market returns. alsufyani and sarmidi (2020) examined the relationship between commodity energy prices and the stock market in saudi arabia between the years 2007 and 2017 using the garch-x method. as a result of the analysis, they determined that energy prices did not affect the stock market and that there were other macroeconomic factors affecting the stock market. chien et al. (2021) analysed the relationship between the covid-19 pandemic, oil prices, us geopolitical risk index, stock market indices, and the granger causality test in the usa, europe, and china. as a result of the analysis, a 1% severity of the pandemic has caused a decrease of around 10% in the productivity index, 0.9% in oil demand, 0.67% in the stock market, 1.12% in gdp growth, and 0.65% in the electricity demand index. they found out why. çevik et al. (2020) investigated the relationship between oil prices and stock market returns between 1990 and 2017 using the egarch method. as a result of the analysis, they determined that oil prices significantly affect stock returns. özcan and karter (2020) used the bostrap rolling windov causality test to investigate the relationship between oil prices and the bist100 index between 2001 and 2020. according to the analysis’ findings, there is causality from oil prices to the bist100 index in six periods and in three periods if oil prices from the guliyeva: analysis of the effect of energy prices on stock indexes during the epidemıc crisis international journal of energy economics and policy | vol 13 • issue 2 • 2023528 bist 100 are correct, and it would be beneficial for investors to monitor changes in oil prices. dursun and ozcan (2019) constructed a panel data collection using 2005-2017 quarterly oecd data. a multiple structural break cointegration study demonstrated a long-term cointegration between electricity, natural gas, and oil price indices and oecd stock market indices. energy prices and stock indexes move in the same way. granfger’s causality research shows a link between stock market indices and oil and natural gas prices, but not electricity costs. kuzu (2019) analysed the spillover effects of exchange rates, government debt securities, and oil prices on the bist 100 index, using the data from january 2, 2005, to may 31, 2018, and the egarch model. the results of the analysis showed that there is a significant average volatility spillover effect between the government debt securities and the stock market, and this effect is bidirectional. corbet et al. (2020) discussed sectoral volatility spillovers in terms of the covid-19 outbreak, specific to energy companies. as a result, they found significant spillover effects from oil prices on renewable energy and coal prices. rakshit and neog (2021) investigated the effects of volatility in exchange rates, oil prices, and covid-19 cases on the returns and volatility of stock markets and found that the volatility in exchange rates had a negative effect on the returns of stock markets in brazil, chile, india, mexico, and russia. they are determined. wang et al. (2021) examined the volatility spillovers between stock markets, exchange rates, and oil prices and suggested that volatility spillovers peaked at the beginning of the covid-19 outbreak and then declined. hung and vo (2021) focused on the spillover effects between the s&p 500 index, oil, and gold prices. they benefited from wavelet coherence and the diebold-yilmaz index. as a result of their study, they determined that return spreads are more intense during the covid-19 period. ajmi et al. (2021), using the bekk-garch model, discussed the volatility spillovers between the us stock market, oil, and gold during the covid-19 period and determined that the intensity of the spreads between the markets increased during the pandemic period. amar et al. (2021) investigated the spreads and co-movements between commodity and stock prices during the covid-19 period. using econometric methods such as the dieboldnd co-movements between commodity and stock prices during the covid-19 period. using econometric methods such as the diebold–ylmaz index, the researchers stated that the spreads between the markets included in the study changed according to time, and the highest spread levels were reached during the covid-19 period. kök and nazlolu (2022) analysed the study’s annual data for brazil, russia, india, china, south africa, and turkey using the stock market index, oil price, and international energy security risk index score covering the period of 1994-2018. as a result of the research, it has revealed the importance of financial markets in terms of energy security risk in the energy-finance relationship for brics-t countries. in their study, gül and suyadal (2022) examined the dynamic interdependence relationships between 11 stock markets before and during the covid-19 pandemic. the research findings show that the relationships between the stock markets have increased during the covid-19 pandemic. when the literature is examined, the general opinion is that there is an interaction between energy prices and stock market indices, or from stock market indices to energy prices. for this reason, during the pandemic period of february 16, 2020-december 26, 2021, which is thought to be an interaction in the research, brent oil, crude oil (wti), and natural gas (ng) prices, the moscow stock exchange index (rtsi), the borsa istanbul index (xu100), and the bovespa brazilian index the presence of the effect will be investigated in the boston stock exchange index (bvsp), indian national stock exchange nifty 50 index (nsei), standard and poor’s 500 index (s and p 500), london stock exchange (ftse 100), and tokyo stock exchange (n225) indices. 3. dataset and econometric method 3.1. dataset in this study, the correlation between brent oil, crude oil (wti), and natural gas (ng) prices and the indicators of four important capital markets was examined. these four capital market indicators include rtsi-moscow stock exchange index, xu100-borsa istanbul index, bvsp-brazilian stock exchange index, nseiindian stock exchange index (in us dollars), s&p 500-standard and poor’s 500 index, ftse 100-london stock exchange, and n225-тokyo stock exchange. to investigate the correlation between brent oil, crude oil (wti), and natural gas (ng) prices and rtsi-moscow stock exchange index, xu100-borsa istanbul index, bvsp-brazilian stock exchange index, nsei-indian stock exchange index, s&p 500-standard and poor’s 500 index, ftse 100-london stock exchange, and n225-тokyo stock exchange. 97-week data for the period of february 16, 2020-december 26, 2021, when large price fluctuations were observed in energy prices, were used. vector autoregressive model was used to examine the correlation between the variables, and the direction of the correlation between the variables was determined by the granger causality test. in this study, all analyzes were carried out with the help of the eviews 12 software package. table 1 presents the coding and description of the data included in the analysis. 3.2. methodology this section describes the methods used to choose the right model in studying the correlation between energy prices and stock market indices. an ordinary time series analysis may be appropriate if all the variables are stationary; however, if they are not stationary, a cointegration analysis, vector error correction (vec) model, or vector autoregressive (var) model may be the appropriate model to test this correlation. therefore, this section begins with an explanation of stationarity tests. after the stationarity tests, the var model and the granger causality test are explained. guliyeva: analysis of the effect of energy prices on stock indexes during the epidemıc crisis international journal of energy economics and policy | vol 13 • issue 2 • 2023 529 3.2.1. stationarity tests stationarity is one of the most critical properties of time series data. with non-stationary series, it is possible to conclude the analysis with a “spurious regression.” on the other hand, having non-stationary data does not always mean that the correlation between these variables causes spurious regression. if the variables are cointegrated in their level form, the regression results will show their long-run equilibrium correlations. there are several methods of testing whether the variables satisfy the stationarity condition. one of the methods of testing the stationarity of the said variables is the unit root test. the presence of a unit root in the variables proves that there is no stationarity. in this study, the augmented dickey-fuller test, which is obtained from the dickey-fuller test, was used as a unit root test. the following three equations can be used in the traditional dickeyfuller test (syzdykova and azretbergenova, 2021:50): ∆𝑦𝑡 = 𝛽1 * 𝑦𝑡 -  1 + 𝜀𝑡 ∆𝑦𝑡 = 𝛽0 + 𝛽1 * 𝑦𝑡 -  1 + 𝜀𝑡 ∆𝑦𝑡 = 𝛽0 + 𝛽1 * 𝑦𝑡 -  1 + 𝛽2 * 𝑇𝑟𝑒𝑛𝑑 + 𝜀𝑡 in all three tests, the hypothesis is as follows: h0 : 𝛽1 = 0 the variable has a unit root, the variable is not stationary. h1 : 𝛽1 < 0 the variable has no unit root, the variable is stationary. 3.2.2. vector autoregressive model the possibility of endogeneity can bias traditional multilinear model estimates. at this point, the vector autoregressive (var) model is a suitable model designed to deal with endogeneity problems. in the var model, all variables are considered endogenous and their effects on each other are taken into account. in these models, an equation is created for each variable. in these equations, each variable becomes the dependent variable, and the lagged values of the dependent variable and the lagged values of the independent variables are added to the equation. in the end, there will be as many equations as the number of variables. thus, the effect of each variable on other variables can be tested. the var model will use the following systems of equations for the two variables (syzdykova and azretbergenova, 2021: 50): y a y xt i t i m i t i t i m � � � �� � � � � �0 1 1 1 � � � (1) x a y xt i t i m i t i t i m � � � �� � � � � �0 1 1 1 � � � (2) var analysis requires determining the optimal lag length. in the above equations, m refers to the optimal lag. depending on the information criteria, the appropriate lag length is selected. the information criteria used in this study are likelihood ratio (lr), final prediction error (fpe), hannan-quinn (hq), schwarz (sic), akaike (aic). the lower the information criteria of the model, the more appropriate the lag length used in that model. however, information criteria alone are not sufficient to decide the optimal lag length. serial correlation is a very critical problem in var analysis, as the var model includes the lagged value of the dependent variable. therefore, before determining the optimal lag, model results with that lag should be tested for serial correlation. the appropriate lag length can only be chosen after it has been found that the error terms are not serially related. 3.2.3. vector error correction model, vecm after proving the existence of a long-term relationship between the series, it is necessary to show the short-term movements of the variables that are related in the long-term. the short-term analysis of the var model is done with the vector error correction mechanism. the error correction model allows one to distinguish between the long-term equilibrium between the variables and the short-term dynamics and determine the short-term dynamics. for this purpose, an error correction term reflecting the adjustment to the long-term equilibrium is added between the explanatory variables by taking the first-order differences of the non-stationary variables (lebe and akbaş, 2014:67). if there is a cointegration relationship between the variables, shortand long-term causal relationships can be examined in terms of vecm. within the scope of this model, even if the series are not stationary, the causality relationship between the variables is questioned without any difference, so information loss about the series is prevented. if the series consisting of x and y variables are assumed to be dependent variables, respectively, vecm models can be expressed with the help of equations (3) and (4) below (turan, 2018: 205). � � � � � � � �� � � � � � �lny a x y vectt i t i k i t t t i k 1 1 1 1 1 1 1 1 � � � � (3) � � � � � � � �� � � � � � �ln x a x y vectt i t i k i t t t i k 2 2 1 1 2 1 1 2 1 � � � � (4) in equations (3) and (4), k represents the optimal delay length, and vect represents the error correction term. the coefficient in front of the vect term indicates the vector error correction coefficient and expresses the speed of adaptation of the post-shock imbalances to the equilibrium level over time. if the vect coefficient is negative, between 0 and 1, and is statistically significant, it will be understood that the established vecm model is correct and the longterm causal relationship between the variables is valid. diagnostic analysis based on several tests is required to determine whether the established vecm model is robust. the diagnostic tests mentioned above include autocorrelation, varying variance, and normality tests. the existence of serial correlation between the residuals of the model established up to a certain lag length is examined by an autocorrelation test. the autocorrelation test is based on the lm test statistic. if the probability value for all delay values is greater than 5%, it can be concluded that there is no autocorrelation. this shows that the model is a good one. another method used to measure the robustness of the model is the variable variance test. the changing variance test is based on the chi-square test statistic. if the probability of the chi-square test statistic calculated for the guliyeva: analysis of the effect of energy prices on stock indexes during the epidemıc crisis international journal of energy economics and policy | vol 13 • issue 2 • 2023530 model is greater than 1%, it is understood that there is no problem of varying variance. finally, the established vecm model’s residues should follow the multivariate normal distribution (mert and alar, 2019: 273). the normality test is based on the jarquebera test statistic. if the probability of the jarque-bera test statistic is greater than 1%, it is understood that the model satisfies the normality condition. as a result, in a well-established vecm model, the vect coefficient should be negative, between 0 and 1, statistically significant, there should be no autocorrelation and varying variance problems in terms of the residuals of the model, and the residuals of the model should be in accordance with the normal distribution (tayyar, 2021: 273-274). although the cointegration relationship shows long-term relationships between the variables, it does not indicate whether the variables used are internal or external. in terms of establishing the vecm model, it is very important whether the variables are internal or external (salam & yldrm, 2014: 203). for this reason, the equation accuracy of the model can be determined by applying the weak externality test to each series. the weak externality test is based on the chi-square test statistic. by giving a constraint to the related variable, its connection with other series is eliminated in the cointegration relationship. if the chi-square probability value of the variable is less than 1% or 5%, it is understood that the relevant variable is an endogenous variable (tayyar, 2021: 273-274). 3.2.4. granger causality test the significant side in regression analysis is the dependence of one variable on other variables. however, this does not always mean that there is causality between these variables. in other words, causality or the direction of the effect cannot be proved by the existence of a correlation between the variables (gujarati, 2013: 652). the granger causality test consists of estimating the following regression systems (syzdykova and azretbergenova, 2021: 51): y y a xt i t i m i t i i i m � � �� � � � � �� �1 1 0 (5) y y xt i t i i m i t i i i n � � �� � � � � �� � � 1 0 (6) using these models, the granger causality test reveals not only the significance of the correlation between variables but also the direction of the correlation between these variables. 4. empirical results to determine whether there is a multicollinearity problem between the variables used in the study, first of all, the correlation between the variables is examined. table 2 below shows the correlation matrix between independent variables. 4.1. unit root test to test the stationarity in the data, study incorporated the augmented dicky-fuller test. the results statistics are as follows: as seen in table 2, according to the above test statistics, all variables are non-stationary at level. as we can see, brent has a t-statistic of −8.65 with a p-value near zero at the first difference level. this means that the study cannot proceed with regression with the variable brent’s first difference. ng have a −10.31 value of the t-statistic, which is also highly significant and shows the first differential is better. like these two, our variable wti is also stationary at the first difference. as per the above results, all variables based on stock market indices are also significant with respect to the first difference. 4.2. descriptive statistics in this study, the data have been described with the help of descriptive analysis. as we know, the variables incorporated into the study have a unit root problem at level; therefore, the data were initially converted into the first differential for further analysis. descriptive statistics explain the mean, median, maximum, minimum, standard deviation, skewness, and kurtosis of the data. but the main thing that is explained is the jarque-bera statistic. it shows the normality of the data. as per the below results, all variables’ data are normally distributed because the probability values of the jarque-bera statistic were significant. sampling periods and descriptive statistics regarding sampling are given in table 3. according to the price averages, bovespa brazilian stock exchange index (bvsp) has negative averages with a score of −91.32990 and london stock exchange with a score of −0.199794 on the basis of the sample period. that is, it has a higher negative return in terms of returns than other countries. тokyo stock exchange (n225) 55.72134 and indian national stock exchange nifty 50 index (nsei) 54,36289, with the highest average, has higher returns for the sample period compared to other countries. standard and poor’s 500 index (s&p 500) 14.84536 and borsa istanbul index (xu100) 7.106804 averages table 1: dataset information variable description brent brent oil futures wti crude oil wti futures ng natural gas futures rtsi rtsi (irts) moscow-moscow stock exchange ındex bist100 bist 100 (xu100) ıstanbul-borsa ıstanbul ındex bvspo bovespa (bvsp)-bovespa brazilian stock exchange ındex nsei nifty 50 (nsei)-indian national stock exchange sp500 s&p 500 (spx)-standard and poor’s 500 ındex ftse100 ftse 100 (ftse)-london stock exchange n225 nikkei 225 (n225)-тokyo stock exchange table 2: augmented dickey‑fuller test statistic variable t-statistic p‑value stationary level brent −8.654948 0.0000 1st difference ng −10.31618 0.0000 1st difference wti −8.035219 0.0000 1st difference rtsi −9.658492 0.0000 1st difference bist100 −8.523583 0.0000 1st difference bvspo −8.816050 0.0000 1st difference nsei −7.163876 0.0000 1st difference sp500 −11.71144 0.0001 1st difference ftse100 −10.83087 0.0000 1st difference n225 −7.723180 0.0000 1st difference guliyeva: analysis of the effect of energy prices on stock indexes during the epidemıc crisis international journal of energy economics and policy | vol 13 • issue 2 • 2023 531 are seen to have medium returns. moscow stock exchange index (rtsi) 0.732474, crude oil (wti) 0.225052, brent oil (brent) 0.198763 and natural gas (ng) 0.018814 averages seem to have the lowest returns. since the high standard deviation, which is another important definitional indicator, indicates an increase in volatility, it is seen that this indicator is ranked from high risk to low risk in brazil, japan, england, india, the usa, russia, and turkey on the basis of the stock market index. in terms of risk score, it is seen that russia’s score is at the highest level of volatility. in addition, jarque bera test statistics obtained from skewness and kurtosis statistics show that all series have normal distributions except for the turkey and russia data. according to the standard deviation indicators, it is ranked from the ones with both high volatility and high risk to the least. it would be important to state that brent oil (3.304206), crude oil (3.266174), and natural gas (0.247618), which are the main energy sources known for their sudden price increases or decreases especially during economic, financial, war, and epidemic crises, have the lowest risk with their standard deviations. 4.3. correlation analysis table 4 presents the correlation analysis result table. in this section, we discuss the correlation analysis of our data. brent is strongly correlated with the rts index, and both are directly related to table 3: descriptive statistics based on first difference of variables variable dbrent dng dwti drtsi dbist100 dbvspo dnsei dsp500 dftse100 dn225 mean 0.198763 0.018814 0.225052 0.732474 7.106804 −91.32990 54.36289 14.84536 −0.199794 55.72134 median 0.430000 0.032000 0.470000 7.110000 13.60000 −73.00000 133.6500 28.20000 4.560000 74.22000 maximum 9.180000 0.519000 6.830000 111.6800 134.0000 8144.000 1289.650 301.2000 427.1600 2836.600 minimum −11.42000 −1.315000 −9.550000 −266.2700 −193.1900 −15609.00 −1209.750 −406.1000 −1096.440 −3318.700 sd 3.304206 0.247618 3.266174 59.19468 52.85827 4073.209 393.8338 105.2938 205.0327 825.2497 skewness −0.522792 −1.760721 −0.823189 −1.425213 −0.982526 −1.104221 −0.385984 −1.084831 −1.945342 −0.488255 kurtosis 4.310279 10.82018 3.900287 7.728323 5.359342 5.906119 4.503449 6.959664 12.51440 6.152467 jarque-bera 11.35740 297.2880 14.23102 123.1979 38.10452 53.84610 11.54419 82.39493 427.0472 44.02029 probability 0.003418 0.000000 0.000812 0.000000 0.000000 0.000000 0.003113 0.000000 0.000000 0.000000 sum 19.28000 1.825000 21.83000 71.05000 689.3600 −8859.000 5273.200 1440.000 −19.38000 5404.970 sum sq. dev. 1048.107 5.886197 1024.117 336384.9 268223.7 1.59e+09 14890088 1064332. 4035689. 65379557 observations 97 97 97 97 97 97 97 97 97 97 table 4: correlation matrix variable dbrent dng dwti drtsi dbist100 dbvspo dnsei dsp500 dftse100 dn225 dbrent 1 dng 0.0846 1 dwti 0.9441 0.0693 1 drtsi 0.6361 −0.0062 0.6232 1 dbist100 0.2192 −0.1701 0.2364 0.4135 1 dbvspo 0.5062 0.0268 0.4814 0.6253 0.4933 1 dnsei 0.4144 0.0649 0.4130 0.6263 0.4595 0.6848 1 dsp500 0.4935 0.1347 0.4913 0.5912 0.4179 0.7290 0.6660 1 dftse100 0.5490 −0.0562 0.5128 0.7642 0.5018 0.7086 0.6060 0.7519 1 dn225 0.3487 0.0964 0.3386 0.5932 0.4083 0.6141 0.6300 0.6679 0.7124 1 table 5: variance inflation factors (vif ındex) variables and vif coefficient uncentered centered variable variance vif vif c 22.12289 1.010313 na dbrent 18.74304 9.282673 9.248857 dng 363.8313 1.014153 1.008271 dwti 19.13658 9.271177 9.226914 table 6: unrestricted cointegration rank test (trace) hypothesized eigenvalue trace statistic 0.05 critical value prob.** no. of ce (s) none* 0.558555 307.7303 239.2354 0.0000 at most 1* 0.525815 229.2308 197.3709 0.0005 at most 2 0.311269 157.5997 159.5297 0.0634 at most 3 0.299913 121.8009 125.6154 0.0835 at most 4 0.283212 87.57202 95.75366 0.1600 at most 5 0.208537 55.60644 69.81889 0.3940 at most 6 0.135120 33.15470 47.85613 0.5483 at most 7 0.107538 19.21894 29.79707 0.4773 at most 8 0.082449 8.296846 15.49471 0.4342 at most 9 0.000379 0.036365 3.841466 0.8487 trace test indicates 2 cointegrating eqn (s) at the 0.05 level. *denotes rejection of the hypothesis at the 0.05 level. **mackinnon-haug-michelis (1999) p-values table 7: unrestricted cointegration rank test (maximum eigenvalue) hypothesized eigenvalue max‑eigen statistic 0.05 critical value prob.** no. of ce (s) none* 0.558555 78.49944 64.50472 0.0014 at most 1* 0.525815 71.63115 58.43354 0.0016 at most 2 0.311269 35.79878 52.36261 0.7520 at most 3 0.299913 34.22885 46.23142 0.5099 at most 4 0.283212 31.96558 40.07757 0.3049 at most 5 0.208537 22.45174 33.87687 0.5727 at most 6 0.135120 13.93576 27.58434 0.8270 at most 7 0.107538 10.92210 21.13162 0.6551 at most 8 0.082449 8.260481 14.26460 0.3528 at most 9 0.000379 0.036365 3.841466 0.8487 max-eigenvalue test indicates 2 cointegrating eqn (s) at the 0.05 level. *denotes rejection of the hypothesis at the 0.05 level. **mackinnon-haug-michelis (1999) p-values guliyeva: analysis of the effect of energy prices on stock indexes during the epidemıc crisis international journal of energy economics and policy | vol 13 • issue 2 • 2023532 each other. brent is also moderately directly proportional to bvspo, nsei, sp500, ftse500, and n225, but only weakly correlated with bist100. ng has a very weak association with some indices. ng has no significant association with rtsi, bvspo, nsei, ftse100, or n225, but the variable has a weakly significant association with bist100 and sp500. the ng index has a direct relationship with the sp500 index and an inverse relationship with the bist100 index. wti has a strong and positive relationship with rtsi. wti is positively related to the bist100, bvspo, nsei, sp500, ftse100, and n225 indices. wti is weakly related to the bist100 index, and its relationship with the other 5 indices is moderate. but here the question is: does there exist any statistically significant association between these oil prices and market indices? to test this phenomenon, the study will analyse the data using the var and vec models. 4.4. testing for multicollinearity before starting any regression analysis, the study tested the model for multicollinearity. to study the multicollinearity, we used the variance inflation factors (vif) index. there are different schools of thought about the vif value for multicollinearity, but we go with the common thought. if the vif value is <10, it means there is no table 8: lag order selection criteria var lag order selection criteria endogenous variables: brent ng wti rtsi bist100 bvspo nsei sp500 ftse100 n225 lag logl lr fpe aic sc hq 0 −5187.958 na 5.63e+36 112.9991 113.2732 113.1097 1 −4428.898 1336.606 3.41e+30 98.67170 101.6869* 99.88865* 2 −4331.945 149.6444 3.91e+30 98.73794 104.4942 101.0612 3 −4251.102 107.2056 7.19e+30 99.15439 107.6517 102.5840 4 −4107.397 159.3249 4.14e+30 98.20428 109.4427 102.7402 5 −3952.995 137.6189 2.64e+30 97.02164 111.0011 102.6639 6 −3762.423 128.4289* 1.35e+30* 95.05268* 111.7732 101.8012 *indicates lag order selected by the criterion table 9: vector autoregressive model results statistics output and variable brent ng wti rtsi bist100 bvspo nsei sp500 ftse100 n225 r-squared 0.974097 0.966539 0.974198 0.950041 0.962341 0.943222 0.985518 0.976600 0.912345 0.959774 adj.r-squared 0.971085 0.962648 0.971197 0.944232 0.957961 0.936619 0.983834 0.973879 0.902152 0.955096 sum sq. resids 728.0609 4.095312 764.0154 266391.1 224751.2 1.19e+09 11454324 879950.0 2651285. 51874394 s.e. equation 2.909609 0.218220 2.980587 55.65582 51.12129 3719.447 364.9518 101.1532 175.5816 776.6535 f-statistic 323.4107 248.4133 324.7030 163.5404 219.7621 142.8661 585.2272 358.9180 89.51166 205.1904 log likelihood −235.3972 15.85907 −237.7351 −521.6605 −513.4169 −929.2684 −704.0766 −579.6131 −633.1055 −777.3338 akaike aic 5.080355 −0.100187 5.128558 10.98269 10.81272 19.38698 14.74385 12.17759 13.28053 16.25431 schwarz sc 5.372332 0.191791 5.420536 11.27467 11.10470 19.67896 15.03583 12.46957 13.57250 16.54628 mean dependent 56.83412 2.994773 53.79763 1421.877 1334.686 107003.3 13704.27 3784.499 6554.477 25907.04 sd dependent 17.11099 1.129110 17.56248 235.6765 249.3321 14774.08 2870.317 625.8690 561.3112 3665.099 determinant resid covariance (dof adj.): 4.36e+30, determinant resid covariance: 1.31e+30, log likelihood: −4739.625, akaike information criterion: 99.99228, schwarz criterion: 102.9121 table 10: vector error correction model results error correction: d (brent) d (ng) d (wti) d (rtsi) d (bist100) d (bvspo) d (nsei) d (sp500) d (ftse100) d (n225) cointeq1 −0.496842 −0.046765 −0.365810 0.518457 1.944733 −110.2825 26.32373 −8.674123 −16.02876 −78.99497 (0.15420) (0.01119) (0.15609) (2.90900) (2.59037) (199.883) (19.1680) (5.09822) (9.94251) (39.7440) (−3.22210) (−4.18104) (−2.34363) (0.17823) (0.75075) (−0.55174) (1.37331) (−1.70140) (−1.61215) (−1.98759) c 0.198763 0.018814 0.225052 0.732474 7.106804 −91.32990 54.36289 14.84536 −0.199794 55.72134 (0.32021) (0.02323) (0.32413) (6.04085) (5.37918) (415.078) (39.8045) (10.5870) (20.6467) (82.5327) (0.62073) (0.81003) (0.69432) (0.12125) (1.32117) (−0.22003) (1.36575) (1.40223) (−0.00968) (0.67514) r-squared 0.098517 0.155413 0.054657 0.000334 0.005898 0.003194 0.019466 0.029570 0.026629 0.039924 adj. r-squared 0.089028 0.146523 0.044706 −0.010189 −0.004566 −0.007299 0.009145 0.019355 0.016383 0.029818 sum sq. resids 944.8505 4.971403 968.1426 336272.5 266641.7 1.59e+09 14600237 1032859. 3928220. 62769323 s.e. equation 3.153695 0.228759 3.192331 59.49547 52.97881 4088.046 392.0290 104.2698 203.3462 812.8528 f-statistic 10.38191 17.48106 5.492586 0.031764 0.563633 0.304412 1.885989 2.894772 2.599012 3.950532 log likelihood −248.0384 6.456891 −249.2195 −532.9589 −521.7061 −943.2614 −715.8461 −587.3839 −652.1729 −786.5799 akaike aic 5.155430 −0.091895 5.179783 11.03008 10.79806 19.48992 14.80095 12.15224 13.48810 16.25938 schwarz sc 5.208517 −0.038808 5.232869 11.08317 10.85115 19.54301 14.85404 12.20533 13.54119 16.31247 mean dependent 0.198763 0.018814 0.225052 0.732474 7.106804 −91.32990 54.36289 14.84536 −0.199794 55.72134 sd dependent 3.304206 0.247618 3.266174 59.19468 52.85827 4073.209 393.8338 105.2938 205.0327 825.2497 determinant resid covariance (dof adj.): 1.30e+31, determinant resid covariance: 1.06e+31, log likelihood: −4840.948, akaike information criterion: 100.4319, schwarz criterion: 101.2282 guliyeva: analysis of the effect of energy prices on stock indexes during the epidemıc crisis international journal of energy economics and policy | vol 13 • issue 2 • 2023 533 issue of multicollinearity, but if the vif value is higher than10, it means multicollinearity exists. as seen in table 5, the above results are based on the ordinary least squares method. in the above analysis, first the study regresses the model by taking any one index as a dependent variable and brent, ng, and wti as independent variables. the ordinary least squares method was used to detect the vif index values for regressors. the vif values indicate that all our variables are free from the issue of multicollinearity. 4.5. testing for cointegration before going for var or vecm, the study tested the data for cointegration equations. the below results are based on johnson’s cointegration test. the cointegration test will reveal whether or not there are any cointegrated equations. if any cointegrated equation exists, it means that the data follow a long-term trend, and we can regress the vector error correction model. as we already tested the data for unit root and unit root exists in the data, it is better to use var models with lag selections to eliminate the issue of unit root. as per the below analysis, at most two cointegrating equations can be studied with the help of johnson’s cointegration test. therefore, we will use both var and vecm methods to test the relationship between oil market prices and stock market indices (as seen in tables 6 and 7). 4.6. vector autoregressive model (varm) this work is based on studying the relationship between crude oil, natural gas, and petroleum products using seven different stock market indices. the study uses var and vecm methods to test the relationship between oil prices and indices. in this section, we will discuss the lag selection criteria and vector autoregressive analysis. as seen in table 8, as per the above analysis, there are different criteria to select the lanes. these lag selection criteria are lr, fpe, aic, sc, and hq. lr, fpe, and aic criteria explain that the lag selection should be six or higher, but in this study, our data is based on limited observations; therefore, we consider the sc and hq criteria for lag selection. we can accept one lag based on the above analysis. in var, we will do analysis with lag 1, and for vecm, we will use lag min 1, e.g., zero lags (table 9). as seen in table 9, as per the above analysis, the brent oils are positively related, with the rts index having a p-value near zero. it means we can conclude the results as the brent is highly significantly related with rts index at 0.01 level of significance. moreover, the relationship between these variables is positive. natural gas and crude oil are also positively related to the rts index, with both being significant at the 0.01 level. the association between brent oil, crude oil, and natural gas with the bist100 index is also highly significant and directly proportional to this index. the p-value of these three regressors is significant at the 0.01 level. brent oil, crude oil, and natural gas variables all have a positive relationship with the bvspo index. as per the above results, these variables are also highly significant for the nse index, sp500, ftse 100, and n225, as the p-values of all regressors were almost zero. as a result, we can conclude that all of the regressors are statistically significant at the 0.01 level and have a positive association. 4.7. vector error correction model (vecm) after performing the analysis with the var method, the study incorporated vecm as a robustness analysis because there is cointegration, which indicates that a long-term trend is applicable. to test the model under long-term trends, the study uses vecm. below are results based on a vector error correction model (table 10). as per the above analysis, brent oil is significantly associated with market indices at the 0.05 level of significance. the equation based on brent oil can explain 9.85% of the total population. the overall significance of the model is good, with an f-statistics value of 10.38. natural gas is also significant at the 0.05 level, and the model based on natural gas can explain 15.54% of the population. the second model based on natural gas has overall significance with an f-statistic value of 17.48. moreover, the model based on crude oil is significant only at a 0.1 level. as per the two analyses, the var and vecm explain the significant association between brent oil, crude oil, and natural gas with stock market indices. 4.8. granger causality test after performing the analysis with var and vecm, the study also tested the causal relationship between the indicators. the results presented below are based on the granger causality test, which was run in eviews. as per the below results, the bist100 index has a positively significant causal relationship with brent oil at a 0.05 level of significance. moreover, the nse index positively causes the brent oil price, and the sp500 index also has a causal association with brent oil prices. both causal relationships are significant. according to the granger causality test results shown in table 11, while the natural gas price is not the cause of brent oil (p-values higher than 1%, 5%, and 10%, “0.0151”), it is seen that brent petroleum natural gas is the cause (p < 10%, “0.0954”). similarly, while natural gas prices are not the cause of crude oil prices (p > 1%, 5%, and 10%, “0.2121”), crude oil prices are the cause of less (p < 10%, “0.0757”). while the price of crude oil is the cause of brent oil (p < 10%, “0.0630”), it is seen that brent oil is not the cause of crude oil (p-value is higher than 1%, 5%, and 10%, “0.5811”). when table 12 is examined, it is seen that while the rtsi index belonging to the country with oil resources is the cause of brent petroleum (p < 10%, “0.0762”), brent petroleum is not the cause of the rtsi index (p-value higher than 1%, 5%, and 10% “0.22029”). while bist100 index is the reason for brent oil (p < 5%, “0.0495”), brent oil is not the reason for bist100 index (p-value is higher than 1%, 5%, and 10%, “0.6705”). it is seen that the bvspo index is not the cause of brent oil (p-value table 11: granger causality test of the relationship between energy prices null hypothesis f‑statistic prob. ng→brent 2.20787 0.1407 brent→ng 2.83783 0.0954 ng→wti 1.57869 0.2121 wti→ng 3.22541 0.0757 wti→brent 3.54082 0.0630 brent→wti 0.30653 0.5811 guliyeva: analysis of the effect of energy prices on stock indexes during the epidemıc crisis international journal of energy economics and policy | vol 13 • issue 2 • 2023534 higher than 5%, “0.2193”), and brent oil is not the cause of the bvspo index (p-value higher than 1%, 5%, and 10%, “0.6859”). while the nsei index is the strongest cause of brent oil (p < 1%, “0.0002”), brent oil is not the cause of the nsei index (p-value is higher than 1%, 5%, and 10%, “0.8028”). while the sp500 index belonging to the country that owns the oil resources is the strong cause of the brent petroleum (p < 1%, “0.0006”), it is seen that the brent petroleum is not the cause of the sp500 index (p-value higher than 1%, 5%, and 10%, “0.7242”). likewise, it is seen that the ftse100 and n225 indices, brent oil, and brent oil are not the cause of the ftse100 and n225 indices (p-values higher than 1%, 5%, and 10%). “ftse100: 0.9730, brent: 8.e-05, n225: 6.e05, brent: 0.4661,” for example. as seen in table 13, the p-value of the test statistics for the rtsi belonging to the country with natural gas resources is 0.0496, which is <5% significance level. the rtsi index is the cause of the natural gas price. the p-value of the test statistics for natural gas is 0.0089, which is <1% significance level. therefore, the null hypothesis that natural gas and rtsi are the causes is accepted. while it is not the reason for the natural gas price of the bist100 index of the natural gas-importing country (p-value higher than 1%, 5%, and 10%, “0.5798”), it is seen that the natural gas price is the reason for the bist100 index (p < 1%, “0.0090”). while the bvspo index is the cause of the natural gas price (p < 10%, “0.0995”), the natural gas price is not the cause of the bvspo index (p-value is higher than 1%, 5%, and 10%, “0.9890”). while the nsei index is the reason for the natural gas price (p < 10%, “0.0692”), the natural gas price is not the reason for the nsei index (p-value is higher than 1%, 5%, and 10%, “0.1949”). while the sp500 index is the reason for the natural gas price (p < 10%, “0.0825”), the natural gas price is not the reason for the sp500 index (p-value is higher than 1%, 5%, and 10%, “0.6007”). while it is not the reason for the natural gas price of the ftse 100 index (p-value higher than 1%, 5%, and 10%, “0.3432”), it is seen that the natural gas price is not the reason for the sp 500 index (p < 1%, “0.0011”). it is seen that the n225 index is not the cause of the natural gas price, and the natural gas price is not the cause of the n225 index (p-values higher than 1%, 5%, and 10% “0.2868” and “0.4417”). examining table 14, the rtsi index is the cause of the wti price (p < 10%, 0.0979). however, it seems that the wti price is not the cause of the rtsi index (p-value higher than 1%, 5%, and 10%, “0.1750”). it is the reason for the wti price of the bist100 index (p < 10%, “0.0710”). it seems that the wti price is not the cause of the bist100 index (p-value higher than 1%, 5%, and 10%, “0.6714”). it is seen that the wti price of the bvspo index (p-value higher than %, 5%, and 10%, “0.2092”) and wti are not the cause of the bvspo index (p-value higher than 1%, 5%, and 10%, “0.7885”). while the nsei index is the cause of the wti price (p < 1%, “0.0011”), it is seen that the wti price is not the cause of the nsei index (p-value higher than 1%, 5%, and 10%, “0.9949). the strong reason for the wti price of the sp500 index belongs to the country that owns this oil resource (p < 1%, or “0.0016”). however, it seems that the wti price is not the cause of the sp500 index (p-value higher than 1%, 5%, and 10%, “0.8309”). why does the wti price of the ftse 100 index change? (the p-value is higher than 1%, 5%, and 10% (“0.7918”). the wti price appears to be the strong cause of the ftse 100 index (p < 1%, “0.0001”), while the n225 index is the strong cause of the wti price (p < 1%, “0.0020”). it seems that the wti price is not the cause of the n225 index (p-value higher than 1%, 5%, and 10%, “0.5798”). as a result, it can be said that the granger causality test results confirmed the findings of the var analysis during the covid-19 pandemic. table 12: granger causality test of the relationship between brent oil prices and stock indices null hypothesis f‑statistic prob. rtsi→brent 3.21441 0.0762 brent→rtsi 1.64452 0.2029 bist100→brent 3.96073 0.0495 brent→bist100 0.18219 0.6705 bvspo→brent 1.52897 0.2193 brent→bvspo 0.16460 0.6859 nsei→brent 15.5201 0.0002 brent→nsei 0.06270 0.8028 sp500→brent 12.4966 0.0006 brent→sp500 0.12524 0.7242 ftse100→brent 0.00115 0.9730 brent→ftse100 17.1354 8.e-05 n225→brent 17.7753 6.e-05 brent→n225 0.53568 0.4661 table 13: granger causality test of the relationship between natural gas and stock market indices null hypothesis f‑statistic prob. rtsi→ng 3.95474 0.0496 ng→rtsi 7.13336 0.0089 bist100→ng 0.30864 0.5798 ng→bist100 7.11022 0.0090 bvspo→ng 2.76849 0.0995 ng→bvspo 0.00019 0.9890 nsei→ng 3.37802 0.0692 ng→nsei 1.70467 0.1949 sp500→ng 3.08032 0.0825 ng→sp500 0.27576 0.6007 ftse100→ng 0.90765 0.3432 ng→ftse100 11.2688 0.0011 n225→ng 1.14776 0.2868 ng→n225 0.59700 0.4417 table 14: granger causality test of the relationship between crude oil prices and stock indices null hypothesis f‑statistic prob. rtsi→wti 2.79530 0.0979 wti→rtsi 1.86729 0.1750 bist100→wti 3.33554 0.0710 wti→bist100 0.18107 0.6714 bvspo→wti 1.59909 0.2092 wti→bvspo 0.07240 0.7885 nsei→wti 11.2549 0.0011 wti→nsei 4.1e-05 0.9949 sp500→wti 10.5796 0.0016 wti→sp500 0.04587 0.8309 ftse100→wti 0.07007 0.7918 wti→ftse100 16.5976 0.0001 n225→wti 15.5635 0.0002 wti→n225 0.30872 0.5798 guliyeva: analysis of the effect of energy prices on stock indexes during the epidemıc crisis international journal of energy economics and policy | vol 13 • issue 2 • 2023 535 5. conclusion the relationship between energy and capital market indicators is very important for investors as it can affect their diversification decisions. in this study, the correlation between brent oil, crude oil, and natural gas prices and moscow stock exchange index, borsa istanbul index, bovespa index, indian stock exchange index, standard and poor’s 500 index, london stock exchange, and тokyo stock exchange has been studied. in the study, weekly data between 16.02.2020 and 26.12.2021 were examined. vector autoregressive model was used and the direction of the correlation between variables was determined by the granger causality test. brent oil prices also have a positive causal relationship with the ftse 100 index and the n225 index. the causal impact is significant at a level of 0.05. natural gas has a positive effect on the rts index and is significant at both the 0.05 and 0.01 levels. natural gas also has a positive effect on the bist100 index and is significant at the 0.05 level. the causal association between natural gas and the ftse 100 index is also positively significant. these results are also similar to our previous var and vecm analyses. the nse index, sp500 index, and n225 index positively cause the price of crude oil, as these variables are significant at the 0.01 level of significance. finally, crude oil has a positive influence on the ftse 100 index, which is statistically significant at the 0.01 level. in line with all the above analyses, e.g., correlation, var, vecm, and granger causality analysis, there was a significant association studied between brent oil, crude oil, and natural gas prices with stock market indices. as a result of the analysis, in summary (i) causality in the price of brent oil and crude oil natural gas, crude oil brent oil price at 10% accuracy level; (ii) causality to brent oil price of russia, turkey, india and usa stock market indexes; the causality of the brent oil price only to the turkish stock exchange; (iii) causality to natural gas from the russian, brazilian, indian, and us stock exchanges; causality from natural gas to stock market indices in russia, turkey, and england; (iv) causal to crude oil from stock market indices of russia, turkey, india, usa and japan; it can be said that there is only one causal link between crude oil and the british stock exchange index. there is a causal relationship between stock markets and energy prices. as a result of this study, it shows that oil and natural gas, which are the main energy sources, and capital market investors should follow both the oil and natural gas price changes and the movements in the stock market indices during the pandemic crisis periods as well as during the economic and financial crisis periods. although the results provided valuable information about the relationships between stock market indices and oil and gas prices, it would be useful to analyze normal periods and compare the results with the findings in this study. references ajmi, h., arfaoui, n., saci, k. (2020), volatility transmission across international markets amid covid-19 pandemic. studies in economics and finance, 38(5), 926-945. akbulaev, n., mammadli, e., bayramli, g. (2022), the effect of energy prices on stock indices in the period of covid-19: evidence from russia, turkey, brazil, and india. international journal of energy economics and policy, 12(3), 262-269. akbulaev, n., rahimli, e. (2020), statistical analysis of the relationship between oil prices and industry index prices. international journal of energy economics and policy, 10(2), 324-331. alio, f.c., okolo, v.o., egbo, o.p., ezeaku, h.c. (2019), energy prices and the nigerian stock market. international journal of energy economics and policy, 9(6), 33-37. alsufyani, m., sarmidi, t. (2020), the inter-relationship between commodity energy prices and stock market volatility in saudi-arabia. journal of nusantara studies (jonus), 5(1), 270-293. amar, a.b., belaid, f., youssef, a.b., chiao, b., guesmi, k. (2021), the unprecedented reaction of equity and commodity markets to covid-19. finance research letters, 38, 101853. arfaoui, m., rejeb, a.b. (2017), oil, gold, us dollar and stock market interdependencies: a global analytical insight. european journal of management and business economics, 26(3), 278-293. bayraktutan, y., uçak, s., & bicil, i̇.m. (2012). yükselen piyasalarda elektrik tüketimi büyüme ilişkisi: nedensellik analizi. çukurova üniversitesi sosyal bilimler enstitüsü dergisi, 21(1), 241-254. benkraiem, r., lahiani, a., miloudi, a., shahbaz, m. (2018), new insights into the us stock market reactions to energy price shocks. journal of international financial markets, institutions and money, 56, 169-187. çevik, n.k., cevik, e.i., dibooglu, s. (2020), oil prices, stock market returns and volatility spillovers: evidence from turkey. journal of policy modeling, 42(3), 597-614. chien, f.s., sadiq, m., kamran, h.w., nawaz, m.a., hussain, m.s., raza, m. (2021), co-movement of energy prices and stock market return: environmental wavelet nexus of covid-19 pandemic from the usa, europe, and china. environmental science and pollution research, 28, 32359-32373. chkili, w. (2022), the links between gold, oil prices and islamic stock markets in a regime switching environment. eurasian economic review, 12, 169-186. corbet, s., goodell, j.w., günay, s. (2020), co-movements and spillovers of oil and renewable firms under extreme conditions: new evidence from negative wti prices during covid-19. energy economics, 92, 104978. coronado, s., rodriguez, r.j., rojas, o. (2018), an empirical analysis of the relationships between crude oil, gold and stock markets. the energy journal, 39, 193-208. demir, y. (2001), hisse senedi fiyatını etkileyen işletme düzeyindeki faktörler ve mali sektör üzerine i̇mkb’de bir uygulama. süleyman demirel üniversitesi i̇ktisadi ve i̇dari bilimler fakültesi dergisi, 6(2), 109-130. dhaoui, a., naceur, k. (2014), empirical linkage between oil price and stock market returns and volatility: evidence from international developed markets. economics discussion papers. p1-30. ding, z., liu, z., zhang, y., long, r. (2016), the contagion effect of international crude oil price fluctuations on chinese stock market investor sentiment. applied energy, 187, 27-36. dizdarlar, h.i., derindere, s. (2008), hisse senedi endeksini etkileyen faktörler: i̇mkb 100 endeksini etkileyen makroekonomik göstergeler üzerine bir araştırma. yönetim dergisi, 19(61), 113-124. dursun, a., özcan, m. (2019), enerji fiyat değişimleri ile borsa endeksleri arasındaki ilişki: oecd ülkeleri üzerine bir uygulama. muhasebe ve finansman dergisi, 82, 177-198. esen, ö. (2013), sürdürülebilir büyüme bağlaminda türkiye’nin enerji açiği sorunu: 2012-2020 dönemi enerji açiği projeksiyonu (yayımlanmamış doktora tezi). erzurum: atatürk üniversitesi sosyal bilimler enstitüsü i̇ktisat anabilim dali. fouquet, r. (2011), a brief history of energy. united kingdom: edward elgar publications. fuat, l., yusuf, a. (2014), türkiye’nin konut talebinin analizi: 1970-2011. guliyeva: analysis of the effect of energy prices on stock indexes during the epidemıc crisis international journal of energy economics and policy | vol 13 • issue 2 • 2023536 atatürk üniversitesi i̇ktisadi ve i̇dari bilimler dergisi, 28(1), 57-83. gherghina, ș.c., armeanu, d.ș., joldeș, c.c. (2020), stock market reactions to covid-19 pandemic outbreak: quantitative evidence from ardl bounds tests and granger causality analysis. international journal of environmental research and public health, 17(18), 6729. ghosh, s. (2002), electricity consumption and economic growth in india. energy policy, 30(2), 125-129. grabias, i.p. (2022), interdependence between wti crude oil prices and the us equity market. international journal of energy economics and policy, 12(2), 226-232. gujarati, d. (2013), basic econometrics. 5th ed. united states of america: tatamcgraw-hill education pvt. ltd. gül, y., suyadal, m. (2022), covid-19’un pay piyasaları arasındaki getiri ve volatilite yayılımlarına etkisi. pamukkale üniversitesi sosyal bilimler enstitüsü dergisi, 50, 350-368. güngör, b., yerdelen, k.c. (2015), dinamik panel veri analizi ile hisse senedi fiyatını etkileyen faktörlerin belirlenmesi. kaü i̇i̇bf dergisi, 6(9), 149-168. humbatova, s.i., ahmadov, f.s., seyfullayev, i.z., hajiyev, n.g.o. (2020), the relationship between electricity consumption and economic growth: evidence from azerbaijan. international journal of energy economics and policy, 10(1), 436-455. hung, n.t., vo, x.v. (2021), directional spillover effects and timefrequency nexus between oil, gold and stock markets: evidence from pre and during covid-19 outbreak. international review of financial analysis, 76, 101730. jain, a., biswal, p.c. (2016), dynamic linkages among oil price, gold price, exchange rate, and stock market in india. resources policy, 49, 179-185. jones, d. w., leiby, p. n., and paik, i. k. (2004). oil price shocks and the macroeconomy: what has been learned since 1996. the energy journal, 25(2). karakuş, r. (2021), petrol ve doğalgaz fiyatları ile hisse senedi fiyatları ilişkisi: bi̇st sinai sektöründe ampirik bir araştırma. i̇şletme araştırmaları dergisi, 13(3), 2072-2083. karhan, g., aydın, h.i̇. (2018), petrol fiyatlari, kur ve hisse senedi getirileri üzerine bir araştırma. akademik araştırmalar ve çalışmalar dergisi,10(19), 405-413. kaya, v., çömlekçi, i̇., kara, o. (2015), hisse senedi getirilerini etkileyen makroekonomik değişkenler 2002-2012 türkiye örneği. dumlupınar üniversitesi sosyal bilimler dergisi, 35, 167-176. kelesbayev, d., myrzabekkyzy, k., bolganbayev, a., baimaganbetov, s. (2022), the impact of oil prices on the stock market and real exchange rate: the case of kazakhstan. international journal of energy economics and policy, 12(1), 163-168. kumar, s., choudhary, s., singh, g., singhal, s. (2021), crude oil, gold, natural gas, exchange rate and indian stock market: evidence from the asymmetric nonlinear ardl model. resources policy, 73, 102194. kumar, s., pradhan, a., tiwari, a., kang, s.h. (2019), correlations and volatility spillovers between oil, natural gas, and stock prices in india. resources policy, 62, 282-291. kök, d. & nazlıoğlu, e. h. (2022). enerji arz güvenliği, petrol fiyatları ve pay piyasalarında nedensellik i̇lişkisi: brics-t örneği . ekonomi politika ve finans araştırmaları dergisi, 7 (1), 220-237. kuzu, s. (2019), devlet iç borçlanma senetleri, döviz, petrol piyasalarının hisse senedi piyasası üzerine ortalama ve oynaklık yayilma etkileri. bingöl üniversitesi sosyal bilimler enstitüsü dergisi, 9(17), 443-461. majidli, f., guliyev, h. (2020), how oil price and exchange rate affect non-oil gdp of the oil-rich country-azerbaijan? international journal of energy economics and policy, 10(5), 123-130. managi, s., okimoto, t. (2013), does the price of oil interact with clean energy prices in the stock market? japan and the world economy, 27, 1-9. mert, m., çağlar, a.e. (2019), eviews ve gauss uygulamalı zaman serileri analizi. 1. baskı. ankara: detay yayıncılık. nairobi, n., ambya, a., russel, e., paujiah, s., pratama, d.n., wamiliana, w., usman, m. (2022), analysis of data inflation energy and gasoline price by vector autoregressive model. international journal of energy economics and policy, 12(2), 120-126. özdemir, a. (2012), küreselleşme sürecinde anahtar rol: enerji politikaları. ankara: asomedya. özcan, g., & karter, ç. (2020). türkiye’de petrol fiyatları ve hisse senedi fiyatları arasındaki nedensellik i̇lişkisi: boostrap rolling window yaklaşımı. pamukkale journal of eurasian socioeconomic studies, 7(2), 105-114. pandey, v., vipul, v. (2018), volatility spillover from crude oil and gold to brics equity markets. journal of economic studies, 45(2), 426-440. partalidou, x., kiohos, a., giannarakis, g., sariannidis, n. (2016), the impact of gold, bond, currency, metals and oil markets on the usa stock market. international journal of energy economics and policy, 6(1), 76-81. rakshit, b., neog, y. (2021), effects of covid-19 pandemic on stock market returns and volatilities: evidence from selected emerging economies. studies in economics and finance, 39, 549-571. raza, n., shahzad, s.j.h., tiwari, a.k. (2016), asymmetric impact of gold, oil prices and their volatilities on stock prices of emerging markets. resources policy, 49, 290-301. sağlam, b.b., yıldırım, k. (2014), doğrudan yabancı yatırımlar ve ücretler: türkiye ekonomisi için bir uygulama. hacettepe üniversitesi i̇i̇bf dergisi, 32(1), 191-209. samanta, s.k., zadeh, a.h.m. (2012), co-movements of oil, gold, the u.s dollar, and stocks. modern economy, 3, 111-117. shabbir, a., kousar, s., batool, s.a. (2020), impact of gold and oil prices on the stock market in pakistan. journal of economics, finance and administrative science, 25(50), 279-294. shaikh, i. (2021), on the relation between pandemic disease outbreak news and crude oil, gold, gold mining, silver and energy markets. resources policy, 72, 102025. singhal, s., choudhary, s., biswal, p.c. (2019), return and volatility linkages among international crude oil price, gold price, exchange rate and stock markets: evidence from mexico. resources policy, 60, 255-261. suleymanli, j.e., rahimli, e.m., akbulaev, n.n. (2020), the causality analysis of the effect of oil and natural gas prices on ukraine stock ındex. international journal of energy economics and policy, 10(4), 108-114. syzdykova, a. & azretbergenova, g. (2021). bıtcoın fiyatının altın ve ham petrol fiyatları i̇le i̇lişkisinin analizi . in traders international trade academic journal, 4(1), 43-58. tayyar, a.e. (2021), elektrik üretimi-ekonomik büyüme-çevre kirliliği: türkiye için vecm analizi. sosyoekonomi, 29(47), 267-284. turan, z. (2018), türkiye’de tarımsal mal ticaretinin ve hayvancılığın ekonomik büyüme üzerindeki etkisi (1990-2014). international journal of disciplines economics and administrative sciences studies, 4(8), 200-209. tursoy, t., faisal, f. (2018), the impact of gold and crude oil prices on stock market in turkey: empirical evidences from ardl bounds test and combined cointegration. resources policy, 55, 49-54. uthumrat, w. (2022), dynamic relationship between the return of gold, crude oil, and the stock exchange of thailand based on a vector autoregressive model. international journal of energy economics and policy, 12(4), 350-356. wang, d., li, p., huang, l. (2021), time-frequency volatility spillovers between major international financial markets during the covid-19 pandemic. finance research letters, 46, 102244. wei, y., guo, x. (2017), oil price shocks and china’s stock market. energy, 140, 185-197. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 1 • 2023 235 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(1), 235-240. causality between selected energy companies’ price indexes and barel oil prices nigar huseynli* azerbaijan state university of economics (unec), baku, azerbaijan; phd candidate sakarya university, sakarya, turkey. *email: nigar.f.huseynli@gmail.com received: 25 august 2022 accepted: 28 december 2022 doi: https://doi.org/10.32479/ijeep.13579 abstract energy production and consumption have an important place in the world. due to the increase in demand, it reveals the result of the valuation of the companies in this sector. the main purpose of this study is to analyze the relationship between brent oil prices in the world and the index prices of energy companies, which are among the world’s most important and top 10 companies. the research covers the period between january 2011 and july 2022. the time series was created by considering the data in the selected time period on a monthly basis. co-integration analysis was applied to the series and the relationship between the variables was tried to be determined. short-term relationships were examined by applying the var model. at this stage, causality was carried out with granger causality analysis. as a result of the analysis, it was concluded that brent oil prices, which were formed as a result of events in the world, had an effect on the index prices of two important energy companies, exxon mobile and gazprom. in other words, there is a causal relationship between these variables. this bilateral causality relationship between brent oil prices and exxon mobile is realized unilaterally with the other two energy companies. in short, there is a granger causality relationship between these variables. keywords: energy sector, barel oil price, oil price, energy company jel classifications: q41, d53, g13 1. introduction oil is an important input used in all economic activities of any country. people are being pushed to consume more because of globalization, increased international commerce volume, and extensive internet use. they all want to attain absolute growth, whether it’s in the food, textile, or other areas. for this expansion to occur, every country needs energy resources (huseynli and huseynli, 2022). the world is dominated by the oil industry. the most important source of energy on this planet, the lifeblood of industrialized nations, often the cause of wars, oil has built skyscrapers in the deserts of some countries, even though it has crashed many economies (bhattacharya and sachdev, 2021). from an economic point of view, production, imports, and exports are interrelated and are important points for economic growth. in this sense, energy demand depends on the economic growth rate and standard of living of each country, as well as on the development of the industry (stoenoiu, 2021). so, energy is the lifeblood of technological and economic development (huseynli, 2022). when global fuel prices are analysed, it is seen that there is a high level of volatility. from 2008 to 2019, since the financial crises, the price of brent crude oil showed extreme changes and shocks. the main reasons for these are financial crises, global political instability and supply-demand fluctuations. according to brown and yücel (2002), increases in gasoline prices have several detrimental effects on the economy, including a reduction in consumer spending, an increase in production costs, a reduction in the trade surplus, changes in the demand for money and the ensuing monetary policy, and finally, market volatility and an unstable economic environment. this journal is licensed under a creative commons attribution 4.0 international license mailto:nigar.f.huseynli@gmail.com huseynli: causality between selected energy companies’ price indexes and barel oil prices international journal of energy economics and policy | vol 13 • issue 1 • 2023236 a study by alkahteeb (2019) examined the effect of oil price on india’s economic growth. as a result of the study, it has been revealed that oil price, capital formation and inflation cause economic growth in the long run. ayo et al. (2021) examined the issues related to production cost, energy recovery levels and economic fortunes of refinery operations in ghana and proposed a conceptual framework to improve the energy efficiency of tema oil refinery (tor). from a theoretical point of view, the relationship between energy or especially oil prices and economic indicators is in most cases a non-linear relationship (lee and chang, 2007). there are studies in the literature on the relationship between the energy market and financial markets, in particular oil prices. in this study, the relationship between the world brent oil prices in the period january 2011-july 2022 and the index prices of energy companies, which are among the most important and largest companies in the world, were examined. 2. literature review 2.1. energy companies and barel oil prices commercial products created to create value for their customer or user have a price. oil is both an important product and an important production cost. for this reason, the increase in oil prices naturally increases the production costs. as oil prices increase, there will be cost inflation and an increase in inflation will reduce economic growth (gisser and goodwin, 1986). the increase in oil prices does not only increase production costs, but also affects all prices in the economy. a study by cunado and perez de gracia (2005) examined the relationship between oil price increases and inflation from 1975 to 2002. as a result of the study, it has been determined that there are negative effects on economic growth and inflation, but mostly in the short term. a study by tang et al. (2010) analyzed the relationship between variables in china from 1998 to 2008. korhonen and ledyaeva (2010) stated that the increase in oil prices will be positive for oil exporting countries at first, but this situation will be observed as economic uncertainty when trade relations are taken into account. as a result of the study by cong and shen (2013), it was determined that a 1% increase in the energy price index could decrease the stock market index by 0.54% and the increase in industry value added by 0.037%. as a result of their study, managi and okimoto (2013) found that after 2007 there was a positive link between crude oil prices and new energy stocks. in another study by cunado et al. (2015), oil prices were investigated in japan, korea, india and indonesia for the period 1997-2014. as a result of the study, surprisingly, it was revealed that the increases in oil prices did not significantly affect the economies of these countries. as a result of the study by horng and tsai (2016), it was found that the volatility of the thai and malaysian stock markets took the effect of the positive and negative values of the volatility of the global energy index and the global material index. as a result of his study, dutta (2017) found that the new energy stock market is highly sensitive to the impact of the crude oil price volatility index. reboredo and ugolini (2018) found in their study that crude oil plays an important role in the dynamic shifts of new energy stocks for the united states. in a study conducted by afşar et al. (2019), the effect of oil price fluctuations on the current account balance for bric countries and turkey was investigated. nasreen et al. (2020) analyzed the dynamic linkage of crude oil prices and new energy stocks. according to the study by zhou and geng (2021), crude oil demand shock and supply shock have little impact on any new energy market volatility, but the impact of crude oil risk shocks on china and us new energy market volatility is 2%, respectively. 44 and 3.14%. 2.2. studies related to price indices of energy companies and barrel petrol prices in a study by kaneko and lee (1995), the relationship between many variables such as inflation rate, production amount, oil prices, money supply and stock returns in the usa and japan was analyzed. in a study by basher and sadorsky (2006), the relationship between the stock returns of 21 developing countries and oil prices between december 1992 and october 2005 was analyzed using the international multi-factor model. as a result of the study by boyer and filion (2007), it was found that the canadian energy stock is positively related to the canadian stock market return, crude oil and natural gas prices, which supports the market theory. cong et al. (2008) analyzed the relationship between the chinese stock market and oil prices between january 1996 and december 2007. as a result of the study by ravichandran and alkhathlan (2010), it has been determined that oil price change has an impact on gcc stock market returns in the long run. in a study by kapusuzoğlu (2011) the relationship between bist100, 50 and 30 indices and brent oil prices between january 2000 and january 2010 was analyzed using johansen and juselius cointegration and granger causality tests. as a result of the study by negi et al. (2011), it has been proven that there is a long-term relationship between oil prices and stock market prices for both countries. in a study conducted by ünlü and topçu (2012), the effect of oil prices on borsa istanbul between january 1990-february 2001 and march 2001-december 2011 was examined using cointegration and causality analysis. in a study by aydogan and berk (2012), the relationship between the bist100 index and crude oil prices and global financial liquidity conditions was examined by dividing the years between january 1992 and november 2011 into three sub-periods. in a study by güler and temel nalın (2013), oil prices and weekly closing prices of bist100, bist industrial and bist chemical, petroleum and plastic indices were analyzed by granger causality method between february 1997 and november 2012. in a study conducted by özmerdivanli (2014), daily data for the period 2003:01-2014:02 for oil prices and bist 100 index variables were used to investigate the relationship between oil prices and stock prices. cointegration and granger causality tests were used in the study. huseynli: causality between selected energy companies’ price indexes and barel oil prices international journal of energy economics and policy | vol 13 • issue 1 • 2023 237 according to maghyereh et al. (2019) examined the link between oil prices and new energy stocks and found that there is a significant return and risk transfer relationship from crude oil to new energy stock markets. pham (2019) found that the link between crude oil prices and different categories of new energy stocks is heterogeneous. in a study by demirkale and ebghaeı (2020), the mutual sensitivities and interaction degrees of oil prices and bist100, bist industry, bist chemical, petrol and plastic, dollar/tl, interest rate variables were analyzed. according to the results of a study by attarzadeh and balcilar (2022), it was determined that oil and clean energy markets have bidirectional volatility spillovers. 3. research methodology 3.1. data set a set of data is required to perform the analysis. the data required for the time series includes a period of approximately 12 years on a monthly basis. by carrying out the study, it was tried to measure whether there is a causal relationship between brent oil prices and the index price values of the three selected companies that have the most important share in this sector. in the study, the granger method was preferred to measure causality. before proceeding to the granger analysis, tests such as the adf test and the var model were performed. 3.2. analysis method in this research, the causality between brent oil prices and the index price values of three selected pollutants, which are among the top 10 energy companies, has been examined. it has been tried to measure how the price increases in oil prices, which cover the most important part of production and consumption, affect the values of companies in this sector. the variables used in the study were analyzed monthly between 01: 2011-06:2022. the information required for the analysis was taken from investing.com. vector auto regression (var) analysis, which is one of the time series analysis methods, was preferred in the study. in this analysis, cointegration analysis, causality analysis and variance decomposition techniques were also applied. var analysis is a model used in time series that are stationary at the same level. in this study, the var model was preferred because the time series were first-order stationary. after the necessary tests were carried out, granger analysis was started. dual granger causality will show the presence and direction of causality, if any, between the variables. however, it will give us neither the length of time required for the causal effect to occur nor the true qualitative nature of the relationships. according to granger (1988), “x is y’s granger causality if y’s prediction is more useful when using x’s historical data than when x’s historical data is not used”. after this identification is verified, it is formatted as x→y. granger (1969) developed this approach for causality testing based on two main econometric links. if xt helps predict yt, a variable xt is said to be a granger-causal variable for another time series variable yt. the granger causality test is one of the best-known criteria for assessing predictive causality between the elements that make up a system. the granger test is based on the idea that knowing the past dynamics of the causative element should help predict the future dynamics of the causative agent, because by definition the latter is partially defined or delimited by the former (zanin, 2021). 4. analysis and results before applying granger and other types of analysis, the price movements of the oil prices of the companies examined as an example over the 11-year period are included in the tables 1-3 with the table names suitable for them. as can be seen from the tables, prices do not show stability and they are in a dynamic movement according to years (figures 1-4). before establishing granger analysis and var model, it is necessary to test the stationarity of the data. according to the unit-root test results, it was observed that the given time series are not stationary. if there is no stationarity between the data, the analysis may cause the spurious regression result to be estimated. this result may show that there are relationships between the variables that do not exist in reality. figure 1: 10-year change in exxon mobil stock prices figure 2: 10-year change in gazprom stock prices huseynli: causality between selected energy companies’ price indexes and barel oil prices international journal of energy economics and policy | vol 13 • issue 1 • 2023238 as a result of the stationarity test performed in the analysis, all four variables; brent oil prices, index price of exxon mobil, index price of gazprom and index prices of korea electric company are not stationary in terms of level. the fact that the t statistics values are lower than the test critical values and the probability values are greater than 0.05 show that there is no stationarity situation table 1: level values of series exxon mobil price index gazprom price index korea electric terminal price index brent oil prices t-statistics possibility t-statistics possibility t-statistics possibility t-statistics possibility adf testing statistics −2.613997 0.2749 −2.208774 0.4805 −1.588381 0.7928 −3.027919 0.1285 test critical values 1% −4.025924 −4.027463 −4.025924 −4.026429 5% −3.442712 −3.443450 −3.442712 −3.442955 10% −3.146022 −3.146455 −3.146022 −3.146165 table 3: appropriate delay length lag logl lr fpe aic sc hq 0 −2512.293 na 7.63e+11 38.71220 38.80043 38.74805 1 −1874.128 1227.241* 53173425* 29.14043* 29.58158* 29.31968* 2 −1861.369 23.75145 55933035 29.19029 29.98437 29.51295 3 −1850.928 18.79310 61036962 29.27582 30.42283 29.74189 4 −1836.048 25.86854 62305564 29.29304 30.79299 29.90252 5 −1827.269 14.72186 70002891 29.40414 31.25700 30.15702 6 −1818.213 14.62859 78519569 29.51097 31.71676 30.40726 *indicates the appropriate lag length for the relevant test. table 4: granger causality test hypotheses f-value probability value (p) decision at 5% significance level the price index changes of gazprom company are the reason for the changes in the price index values of exxon mobile company 6.740435 0.0344 acceptable the price index changes of korea electric are the reason for the changes in the price index values of exxon mobile. 7.533690 0.0231 acceptable the change in brent oil prices is the reason for the change in the price index values of exxon mobile. 17.57256 0.0002 acceptable the price index changes of exxon mobile are the reason for the changes in the price index values of gazprom. 5.046585 0.0802 rejected changes in the price index of the korea electric company are the reason for the changes in the price index values of the gazprom company 3.059780 0.2166 rejected the change in brent oil prices is the reason for the change in the price index values of gazprom company 10.43995 0.0054 acceptable the price index changes of exxon mobile are the reason for the changes in the price index values of korea electric. 2.226787 0.3284 rejected the price index changes of gazprom company are the reason for the changes in the price index values of korea electric company 0.846336 0.6550 rejected the change in brent oil prices is the reason for the change in the price index values of korea electric company. 3.115042 0.2107 rejected the price index changes of exxon mobile are the reason for the change in brent oil price values. 7.120328 0.0284 acceptable changes in gazprom's price index are the reason for the change in brent oil price values. 4.431483 0.1091 rejected the price index changes of korea electric are the reason for the change in brent oil price values. 7.856874 0.0197 acceptable table 2: level values of first order series exxon mobil price index gazprom price index korea electric terminal price index brent oil prices t-statistics possibility t-statistics possibility t-statistics possibility t-statistics possibility adf testing statistics −12.18684 0.0000 −9.276502 0.0000 −10.78293 0.0000 −9.581375 0.0000 test critical values 1% −4.026429 −4.027959 −4.026429 −4.026429 5% −3.442955 −3.443704 −3.442955 −3.442955 10% −3.146165 −3.146604 −3.146165 −3.146165 huseynli: causality between selected energy companies’ price indexes and barel oil prices international journal of energy economics and policy | vol 13 • issue 1 • 2023 239 as it can be understood from the table 1. this is true for all four variables, and in this case, the h1 hypothesis is accepted. as stated before, the adf test was applied to ensure the stationarity, which is one of the important conditions for the analysis, and it was concluded that the data were stationary in the first order. information about the first-order stationarity result is given in table 2. the fact that the probability values are less than 0.05 also indicates the validity of the h1 hypothesis. after the time series were made stationary at the same level, the var model was established and the appropriate lag numbers of the series were determined with the help of akaike (aic), ll, lr, fbe, sc and hq information criteria. the appropriate lag numbers in table 3 indicate that these time series have the appropriate lag number in the first length. after the stationarity test of the data, the establishment of the var model and the determination of the appropriate lag numbers, the transition to the granger model was made. granger results between brent oil prices, exxon mobil price index, gazprom price index and korea electric price index are shown in table 4. according to the results of the granger analysis, a causal relationship was found between the variables, either bilaterally or unilaterally. table 4 shows that there is a bidirectional causality between brent oil prices and exxon mobile values. a unilateral causality relationship was obtained between the other remaining variables. as a final result, we know that there is a causal relationship between bremt oil prices and exxon mobile and gazprom company. in other words, there is granger causality between these variables. these indicators obtained as a result of econometric analysis show that there is a relationship between these variables. 5. discussion and conclusion energy production and consumption has an important place in the world. due to the increase in demand, it reveals the result of the valuation of the companies in this sector. the main purpose of this study is to analyze the relationship between brent oil prices in the world and the index prices of energy companies, which are among the most important and largest companies in the world. the research covers the period between january 2011 and july 2022. the time series was created by considering the data in the selected time period on a monthly basis. co-integration analysis was applied to the series and the relationship between the variables was tried to be determined. short-term relationships were examined by applying the var model. at this stage, dual causality was carried out with granger causality analysis. as a result of the analysis, it was concluded that brent oil prices, which were formed as a result of events in the world, had an effect on the index prices of two important energy companies, exxon mobile and gazprom. in other words, there is a causal relationship between these variables. this bilateral causality relationship between brent oil prices and exxon mobile is realized unilaterally with the other two energy companies. in short, there is a granger causality relationship between these variables. the results obtained from the study are similar to the results of the study conducted by basher and sadorsky (2006). in other words, according to the study by basher and sadorsky, it has been revealed that the increase in oil prices affects stock returns positively when they use daily and monthly data, and the decrease in oil prices affects stock returns positively when they perform the analysis with weekly and monthly data. another study, cong et al. (2008) also show the same results in their studies. as a result of the study, it was revealed that oil price shocks do not have an effect on stock returns. likewise, as a result of the study conducted by ünlü and topçu (2012), it was found that there was a cointegration relationship between the bist100 index and crude oil prices in the march 2001-december 2011 period, and there was a unidirectional causality relationship from the crude oil variable to the bist100 index. according to the results of the study conducted by güler and temel nalın (2013), it has been determined that there is no causality relationship between oil prices and indices. references afşar, b., cura, f., mıhoğlu, a. (2019), petrol fiyatlari ile cari açik ilişkisi: bric ülkeleri ve türkiye karşilaştirmasi. uluslararası ekonomi ve siyaset bilimleri akademik araştırmalar dergisi, 3(7), 1-13. alkahteeb, t.t.y., sultan, z.a. (2019), oil price and economic growth: the case of indian economy. international journal of energy figure 4: 10-year change in brent oil prices figure 3: 10-year change in korea electric stock prices huseynli: causality between selected energy companies’ price indexes and barel oil prices international journal of energy economics and policy | vol 13 • issue 1 • 2023240 economics and policy, 9(3), 274-279. attarzadeh, a., balcilar, m. (2022), on the dynamic connectedness of the stock, oil, clean energy, and technology markets. energies, 15(5), 1893. aydogan, b., berk, i. (2015), crude oil price shocks and stock returns: evidence from turkish stock market under global liquidity conditions. international journal of energy economics and policy, 5(1), 54-68. ayo, d., arthur, j.l., adinkrah-appiah, k. (2021), economic benefits of energy efficiency to the petroleum refineries in ghana: a case of tema oil refinery (tor). open journal of energy efficiency, 10(4), 121-135. basher, s.a., sadorsky, p. (2006), oil price risk and emerging stock markets. global finance journal, 17(2), 224-251. bhattacharya, s., sachdev, b.k. (2021), can renewable energy reduce the demand for crude oil: an analysis? international journal of multidisciplinary research and growth evaluation, 2(6), 94-98. boyer, m.m., filion, d. (2007), common and fundamental factors in stock returns of canadian oil and gas companies. energy economics, 29(3), 428-453. cong, r.g., wei, y.m., jiao, j.l., fan, y. (2008), relationships between oil price shocks and stock market: an empirical analysis from china. energy policy, 36(9), 3544-3553. cunado, j., de gracia, f.p. (2005), oil prices, economic activity and inflation: evidence for some asian countries. the quarterly review of economics and finance, 45(1), 65-83. cunado, j., jo, s., de gracia, f.p. (2015), macroeconomic impacts of oil price shocks in asian economies. energy policy, 86, 867-879. demirkale, ö., ebghaeı, f. (2020), ham petrol fiyatlari ile makroekonomik ve finansal göstergeler arasindaki karşilikli ilişkinin var modeli ile analizi: türkiye üzerine bir uygulama. finans ekonomi ve sosyal araştırmalar dergisi, 5(4), 688-698. dutta, a. (2017), oil price uncertainty and clean energy stock returns: new evidence from crude oil volatility index. journal of cleaner production, 164, 1157-1166. gisser, m., goodwin, t.h. (1986), crude oil and the macroeconomy: tests of some popular notions: note. journal of money credit and banking, 18(1), 95-103. granger, c.w.j. (1969), investigating causal relations by econometric models and cross-spectral methods. econometrica, 37(3), 424-438. granger, c.w.j. (1988), causality, cointegration, and control. journal of economic dynamics and control, 12(2-3), 551-559. güler, s., temel nalin, h. (2013), petrol fiyatlarinin i̇mkb endeksleri üzerindeki etkisi. international journal of economic and social research, 9(2), 79-97. horng, w.j., tsai, y.c. (2016), an impact of global energy index and global material index volatilities in southeast asia two stock markets: empirical study of thailand and malaysia markets. in: international conference on mathematical, computational and statistical sciences and engineering (mcsse 2016), pp.456-461. huseynli, b. (2022), examining the relationship between brand value, energy production and economic growth. international journal of energy economics and policy, 12(3), 298-304. huseynli, b., huseynli, n. (2022), econometric analysis of the relationship between renewable energy production, traditional energy production and unemployment: the case of azerbaijan. international journal of energy economics and policy, 12(4), 379-384. kaneko, t., lee, b. (1995), relative importance of economic factors in the u.s. and japanese stock markets. journal of the japanese and international economies, 9(3), 290-307. kapusuzoğlu, a. (2011), relationships between oil price and stock market: an empirical analysis from istanbul stock exchange (ise). international journal of economics and finance, 3(6), 99-106. korhonen, i., ledyaeva, s. (2010), trade linkages and macroeconomic effects of the price of oil. energy economics, 32(4), 848-856. lee, c.c., chang, c.p. (2007), the impact of energy consumption on economic growth: evidence from linear and nonlinear models in taiwan. energy, 32(12), 2282-2294. maghyereh, a.i., awartani, b., abdoh, h. (2019), the co-movement between oil and clean energy stocks: a wavelet-based analysis of horizon associations. energy, 169, 895-913. managi, s., okimoto, t. (2013), does the price of oil interact with clean energy prices in the stock market? japan and the world economy, 27, 1-9. nasreen, s., tiwari, a.k., eizaguirre, j.c., wohar, m.e. (2020), dynamic connectedness between oil prices and stock returns of clean energy and technology companies. journal of cleaner production, 260, 121015. negi, p., chakraborty, a., mathur, g. (2011), long term price linkages between the equity markets and oil prices: a study of two big oil consuming countries of asia. middle eastern finance and economics, 14, 141-151. özmerdivanli, a. (2014), petrol fiyatlari ile bist 100 endeksi kapaniş fiyatlari arasindaki ilişki. akademik bakış dergisi, 43, 1-12. pham, l. (2019), do all clean energy stocks respond homogeneously to oil price? energy economics, 81, 355-379. ravichandran, k., alkhathlan, k.a. (2010), impact of oil prices on gcc stock market. research in applied economics, 2(1), 1-12. reboredo, j.c., ugolini, a. (2018), the impact of energy prices on clean energy stock prices. a multivariate quantile dependence approach. energy economics, 76, 136-152. stoenoiu, c.e. (2021), retrospective analysis of the evolution of industrial production in relation to energy consumption. in: 2021 international conference on electromechanical and energy systems (sielmen). united states: ieee. p.249-252. tang, w., wu, l., zhang, z. (2010), oil price shocks and their short-and long-term effects on the chinese economy. energy economics, 32(suppl 1), s3-s14. zanin, m. (2021), simplifying functional network representation and interpretation through causality clustering. scientific reports, 11(1), 1-12. zhou, l., geng, j.b. (2021), dynamic effect of structural oil price shocks on new energy stock markets. frontiers in environmental science, 9, 636270. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 4 • 202240 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(4), 40-47. investigating the nexus between crude oil price and stock prices of oil exploration companies k. abhaya kumar1, prakash pinto2, iqbal thonse hawaldar3*, saheem shaikh1, shravan bhagav1, b. padmanabha4 1department of mba, mangalore institute of technology and engineering, moodabidri, karnataka, india, 2department of business administration, st. joseph engineering college, mangalore, karnataka, india, 3department of accounting and finance, college of business administration, kingdom university, bahrain, 4department of mba, sahyadri college of engineering and management, mangalore, karnataka, india. *email: thiqbal34@gmail.com received: 01 march 2022 accepted: 24 may 2022 doi: https://doi.org/10.32479/ijeep.13070 abstract in emerging economies, examining the linkage between different markets has become crucial. we have examined the linkage between crude oil and indian oil exploration companies’ equity prices. the augmented dickey-fuller method is used to test the stationarity of the series. the granger causality test, vector autoregression (var) and correlation methodologies are used to examine the causality between the markets. the p-values of granger causality tests are <0.05, which confirms that the crude oil price causes the price movements of indian oil exploration equities. the var (2) model confirmed that the prices of hoce, oil and ongc follow the first and second lag, reliance and petronet equities follow the first lag of international crude price. the impulse response function shows a positive response of indian oil exploration equity returns for the positive shocks of crude oil return. the findings of this study may help the traders and investors in the equity market, energy equity investors. keywords: energy equity, causality, oil price, vector auto regression, impulse response function jel classifications: g21; g30 1. introduction the nexus between the oil market and other financial markets have become many academicians’ interests in recent decades. numerous studies have found the relationship between the oil market and other financial markets. changes in oil prices lead to fluctuations in economies; the oil shocks affect multiple countries’ economies (atif et al., 2022; meher et al., 2020; blanchard and gali, 2007). kumar et al. (2021) found the impact of dynamic crude oil prices on the price of natural rubber in india. amin (2015) found the nexus between the oil price and electricity policy changes in bangladesh. alamgir and amin (2021) found a positive relationship between oil price and asian stock market indices. kumar et al. (2021) examined the relationship between crude oil price and indian tyre equity prices; the multivariate garch models revealed a negative relationship between the oil and tyre equity prices. india is the third-largest oil consumer globally, after usa and china. the amount of crude oil extracted in india is insufficient to meet the domestic demand. hence, a massive volume of crude is imported from foreign countries. according to iea (india energy outlook 2021), the primary energy demand is expected to double to 1,123 million tonnes because of the expected growth in gdp to usd 8.6 trillion by 2040. india has low conventional energy resources than its required energy needs, driven by a vast population and a rapidly increasing economy. as an alternative, india can harness the enormous potential of solar energy as it receives sunshine most of the year. it also has vast potential in the hydropower sector, which is being explored across states in the this journal is licensed under a creative commons attribution 4.0 international license kumar, et al.: investigating the nexus between crude oil price and stock prices of oil exploration companies international journal of energy economics and policy | vol 12 • issue 4 • 2022 41 northeast. however, an expensive amount of capital investment is the hurdle to the growth of such alternative sources. for oil exploration, the government has planned to invest us$2.86 in upstream oil and gas production (alamgir and amin, 2021). these strong fundamentals ensure good growth and a future for india’s oil exploration sector. however, the global oil market is not stable. using the granger causality test and vector auto regression (var) model, we examine the relation between oil prices and indian oil exploration companies’ stock prices. 2. literature review many studies revealed that the indian stock market and stock prices react to different issues (meher et al., 2021; kumar et al., 2020; hawaldar, 2016; iqbal, 2014). earning announcements (iqbal and mallikarjunappa, 2009; iqbal et al., 2007), risk and return (iqbal 2015; 2011) and oil prices (atif et al., 2022) affects stock prices significantly. long et al. (2021) have used the var methodology to examine the relationship between money supply, inflation and output in vietnam and china. var model is applied to analyse the relationship between the crude oil market and pandemic covid-19 (shaikh, 2021). to understand the spillover across equity markets between china and southeast asian countries, hung (2019) applied var and bekk models. kilian and zhou (2020) have applied the var model to understand the oil price shocks in the demand and supply of oil in the market. to examine the volatility transmission between crude oil, gasoline, heat oil and carbon emissions, bunnag (2015) has used var and vecm models. to examine the nexus between crude palm price, soybean oil price and crude oil price, songsiengchai et al. (2018) have used var and granger causality test. the nexus between crude oil price volatility and stock indices movement in india and china was examined using wavelet analysis (mishra and debasish, 2022). researchers found the relation between global crude oil price and equity market both in indian and chinese economies. barbaglia et al. (2020) stated that the volatility spillover exists between the energy, equity, and bioenergy markets. the study’s interaction between oil and currency exchange markets was evident (butt et al., 2020). an unconditional causal relationship was found between oil price and exchange rates in malaysia by (butt et al., 2020). volatility and correlation spillover was evident from the oil market to the indian industrial sectors (kumar and maheswaran, 2013). a couple of times in the past, the business dailies in india have reported that depreciated oil prices are taking the tyre sector stocks up (shyam, 2019). a study by bagchi (2017) found asymmetric volatility responses for negative and positive innovations, and a further negative relationship was observed between returns and volatility of crude oil and sensex. a study by dutta (2018) revealed a long-term correlation between the stock market and oil market volatilities. further, granger causality found a short-term lead-lag relationship between the usa’s oil and stock markets. the causal relationship between crude oil price, exchange rate and rice price study (adam et al., 2018) revealed only a short-term relationship between the selected variables. oil price volatility in the context of covid-19 was studied by bourghelle et al. (2021). the study revealed that the pandemic has negatively impacted the whole economy. the covid 19 pandemic reduced global demand for crude oil, increased uncertainty, and triggered a severe economic recession in most developed and emerging countries (meher et al., 2020). this led to a supply shock as the pandemic resulted in an oil trade war between the major oil-producing nations (saudi arabia and russia). these shocks led to extremely high levels of oil price volatility. the empirical study of fuentes and herrera (2020) stated that the crude oil, gold market, green energy stocks and s and p 500 indices show a unidirectional relationship. empirical studies by saeed et al. (2020), liu and hamori (2020), and yu-ling hsiao et al. (2019) also found some evidence of a linkage between energy stock prices and the oil market. many causal studies have used the granger causality test, var and vecm models to summarise this section. numerous studies from various economies have found nexus between crude oil and the equity market. studies have appeared from the indian perspective concerning causality between crude oil prices and sensex, crude oil prices and tyre equities, crude oil prices, and currency exchange rates. however, a specific study regarding the nexus between oil prices and oil exploration companies’ stock prices has not appeared. this work aims to address the topic. those few questions left unanswered necessitated the following research agenda worthwhile. this work aims to add to the exciting literature segment on the linkage between the crude oil market and equity market in india by examining the causal relationship of crude oil prices with indian oil exploration companies’ equities. 3. methodology this empirical study analyses the nexus between the oil market and indian oil exploration companies’ stock prices. based on market capitalisation top five oil exploring companies are selected they are reliance industries (reliance), oil and natural gas corporation (ongc), petronet lng (petronet), oil india (oil) and hindustan oil exploration company (hoec). from the official website of yahoo finance, the daily closing price data of crude oil and indian oil exploring companies’ equities are gathered for the period from march 10, 2010 to december 31, 2021. after adjusting the missing values in the oil and equity price series using the v-look up the function of the microsoft excel package, we could finalise 2443 daily observations for each price series. we have applied pearson correlation, granger causality test, and var model to examine the causal relationship between the indian oil exploration equities with crude oil prices. the general equation of pearson’s correlation model is presented in equation 3.1. augmented dicky-fuller (adf) tests are performed to check the stationarity of the series. if the price series are not stationary, log-returns of the series are taken to make such series stationary. r n cop oee cop oee n cop cop n oee oee � � �� �� � � � � � � � � � ( ( )( ) [ ( ) ][ ( ) 2 2 2 22 ] (3.1) profillidis and botzoris (2019) opined that a causal test could only examine the causal relationship between two variables. the general equation of the causality test of granger (1969) is kumar, et al.: investigating the nexus between crude oil price and stock prices of oil exploration companies international journal of energy economics and policy | vol 12 • issue 4 • 202242 presented in equation 3.2. in equation 3.1, the variable cop is the crude oil price, oee is the price of indian oil exploration equities determinant and commodity price, and r is the correlation coefficient. y y y yt t t p p t� � � � � ��� � �� � �� � � � �1 1 2 2 2 (3.2) equation 3.2 resembles the autoregressive process, where yt is the price of indian oil exploration equity, α is the intercept, εt is the error term, and β1, β2, β3 are the slope parameters of the auto r(p) process. equation 3.2 is augmented by introducing the lag values of crude oil price (xt) and the resulting equation presented below. y y y y x x t t t p p t n n t � � � � � ��� � �� � ���� � � � � � � � � � � � � 1 1 2 2 2 1 1 1 (3.3) in equation 3.3, x is the price of crude oil in the international market, and n is the lag length for which the past values of crude oil prices are statistically significant. the general equation of the bivariate var (1) model is presented in equation 3.4. oee oee oee cop co t oee oee t oeek t k oeek t oeek � � ��� � � ��� � � � � � � � 0 1 1 1 pp ut k oeet� � (3.4) cop cop cop oee oe t cop cop t copk t k copk t oeek � � ��� � � ��� � � � � � � � 0 1 1 1 ee ut k oeet� � (3.5) where (oee) in equation (3.3) is the equity price of oil exploration companies, dependent on its past values, past values of crude oil price, and (uoeet) is the white noise error term. similarly, the cop in equation (3.2) is the crude oil price, which functions its past values and past values of oil exploration equity prices (oee) and ucopt is the white noise error term. the term “t” in the above two equations is the time index. this study accommodates the above seven endogenous variables in the model: six selected oil exploring companies’ equity price series and crude oil spot price series. 4. data analysis and discussion the price line chart of crude oil prices and indian oil exploration companies’ equities are shown in figure 1. the equity price series of petronet and reliance shows an upward trend during the study period. the crude spot series shows a mixed trend, and the equity price series of oil, ongc and hoec resemble the price series of the crude spot. we have witnessed crude oil trading with a negative value in the new york mercantile exchange (nymex) due to the oil crisis during the covid pandemic. this is evident from a sharp fall in crude spot prices and all selected stock prices of oil exploration companies during the beginning of 2020. the descriptive statistics of crude oil spot and indian oil exploration companies’ stock prices are presented in table 1. in panel b of table 1, the mean return of all the series is equal to zero, the standard deviations of those series are greater than zero. this indicates that the returns on crude and indian oil exploration equities were highly volatile during the study period. the minimum price of crude during the study was us$ 10.01; this was reported during the covid pandemic in 2020. most economies were in lockdown at the beginning of 2020, resulting in an increased crude inventory in the international market. this resulted in crude trading with negative values too in the futures market of the nymex platform. this is evident from an extremely high value of kurtosis (63.74) for crude returns compared to the kurtosis of indian exploration equity returns. negative skewness for the return series of crude, oil and ongc indicate a longer left tail that is the extreme losses during the study period. the positive skewness reported in table 1 is evidence of good profits for the equities of hoec, petronet and reliance during the study period. the jarque-bera test statistics imply that the series is not normally distributed. the test for stationarity of the series is done using adf methodology; the unit root test results are presented in table 2. the p values for the unit root tests for the price series are greater than 0.05, and the absolute value of the t-statistic of adf is less than the critical values at 1%, 5% and 10%. these statistical values confirm that the price series of crude and oil exploration equities are not stationary. the logged returns of crude prices and select stock prices of indian oil exploration companies are computed using the log function r p pji t ij t ij t , , , ( )� � ln 1 . where, pij,t and pij,t-1 are the closing prices of crude oil and indian oil exploration equity returns for day’s t and yesterday t-1, respectively. the probability values of the adf test for the returned series of crude price and indian oil exploration equities are <0.05, the absolute values of the t-statistic of adf tests are greater than the t-statistic for 1%, 5% and 10% critical values. this confirms that the return series of crude price and indian oil exploration equities are stationary. the return series are plotted in figure 2, in which the log-returns are reverting to zero, and the series is not showing an upward or downward trend. the correlation analysis and granger causality test analysis are presented in table 3. the oil and ongc company’s stock prices positively correlate with a crude price; the correlation coefficients are 0.67 and 0.57, respectively. the equity prices of petronet and reliance are negatively, and the price of hoec equity is moderately positively correlated with crude price. the second half of table 3 presents the granger causality test results; the null hypothesis is that the crude price does not granger cause the oil exploration equities in india. the probability values of the granger causality test for both return and price series of all oil exploration equities are less than or equal to 0.05. the probability values of all the correlation coefficient estimations are <0.05; the same is not presented in the table. hence, with a 95% confidence level, we can confirm that the price of crude oil in the international market will cause the prices of indian oil exploration equities. this empirical study examines the nexus between crude price and indian oil exploration equities. with a default lag length of 2, the var model was estimated. post estimation, the function lag length criteria are used to identify the optimal lag length for the kumar, et al.: investigating the nexus between crude oil price and stock prices of oil exploration companies international journal of energy economics and policy | vol 12 • issue 4 • 2022 43 var model. based on akaike information criteria (aic), schwarz criteria (sc) and hanna quinn (hq) information criteria, the optimal lag for the model is identified as 2. hence, this var (2) model estimated 78 coefficients with six endogenous variables, of which 19 coefficients were statistically significant with a 95% confidence level. only the coefficients on this objective are presented in table 4. other significant coefficients are presented as var equations in 4.1–4.5. figure 1: price series of crude oil spot and indian oil exploring companies’ equities. source: authors processing table 1: descriptive statistics of crude oil and indian oil exploration company equities statistic crude hoec oil ongc petronet reliance panel a: price series mean 69.01 100.38 212.81 171.44 149.53 862.36 maximum 113.93 286.40 330.60 303.43 288.25 2731.85 minimum 10.01 24.40 70.35 60.00 38.03 334.88 sd 22.27 57.10 54.83 44.69 78.82 601.36 skewness 0.12 0.84 −0.60 −0.15 0.16 1.31 kurtosis 1.85 3.12 2.77 3.38 1.32 3.53 jarque−bera 139.39 290.68 152.29 24.40 297.41 730.83 observations 2443.00 2443.00 2443.00 2443.00 2443.00 2443.00 panel b: return series mean 0.00 0.00 0.00 0.00 0.00 0.00 maximum 0.32 0.23 0.15 0.13 0.10 0.14 minimum −0.60 −0.26 −0.13 −0.17 −0.09 −0.13 sd 0.03 0.04 0.02 0.02 0.02 0.02 skewness −2.31 0.10 −0.07 −0.05 0.31 0.37 kurtosis 63.74 7.29 7.74 8.90 4.97 7.60 jarque-bera 377535.60 1878.39 2285.73 3548.70 432.64 2207.60 observations 2442.00 2442.00 2442.00 2442.00 2442.00 2442.00 source: authors’ computations kumar, et al.: investigating the nexus between crude oil price and stock prices of oil exploration companies international journal of energy economics and policy | vol 12 • issue 4 • 202244 figure 2: return series of crude oil spot and indian oil exploring companies’ equities. source: authors processing table 2: unit root test results of crude oil and indian oil exploration company equities price series price series variable critical value t-statistic probability variable critical value t-statistic probability crude adf test −1.65 0.46 crude adf test −40.11 0.00 1% level −3.43 1% level −3.43 5% level −2.86 5% level −2.86 10% level −2.57 10% level −2.57 hoec adf test −2.42 0.14 hoec adf test −47.02 0.00 1% level −3.43 1% level −3.43 5% level −2.86 5% level −2.86 10% level −2.57 10% level −2.57 oil adf test −1.93 0.32 oil adf test −37.07 0.00 1% level −3.43 1% level −3.43 5% level −2.86 5% level −2.86 10% level −2.57 10% level −2.57 ongc adf test −1.79 0.39 ongc adf test −38.17 0.00 1% level −3.43 1% level −3.43 5% level −2.86 5% level −2.86 10% level −2.57 10% level −2.57 petronet adf test −1.32 0.62 petronet adf test −52.05 0.00 1% level −3.43 1% level −3.43 5% level −2.86 5% level −2.86 10% level −2.57 10% level −2.57 reliance adf test 0.93 1.00 reliance adf test −21.26 0.00 1% level −3.43 1% level −3.43 5% level −2.86 5% level −2.86 10% level −2.57 10% level −2.57 source: authors’ computations kumar, et al.: investigating the nexus between crude oil price and stock prices of oil exploration companies international journal of energy economics and policy | vol 12 • issue 4 • 2022 45 oil crude hoec crude oil � � �� �� � �� �� � �� �� � � 0 05 1 0 03 1 0 03 2 0 06 1 . . . . �� �� � �� �� � �� �� � �� � 0 09 2 0 07 1 0 05 1 . . . oil ongc reliance (4.1) hoec crude hoec crude � � �� �� � �� � � � �� � 0 12 1 0 04 1 0 07 2 . . . (4.2) ongc crude crude oil ongc � � �� �� � �� � � � �� �� � � 0 09 1 0 08 2 0 06 1 0 08 . . . . 11� � (4.3) ( ) ( ) 0.03 1 0.08 1 0.06 ( 2) petronet crude petronet petronet = × − − × − − × − (4.4) reliance crude� � �� �0 06 1. (4.5) table 4 proves that the international price of crude oil causes the price movements of indian oil exploration equities. there are three values presented in each cell: coefficient, standard error, and t-statistic. the coefficients presented in bold letters are the statistically significant coefficients with a 95% confidence level. the regression coefficients for the equities of hoec, oil and ongc are statistically significant for the first and second lag of crude return. this confirms that the crude prices of the previous 2 days will cause today’s prices of hoec, oil and ongc. the equity price of hoec depends on its previous lag as well. the oil price will be influenced by the past 2 days’ crude oil price, its price past 2 days, and the first lag of hoec, ongc and reliance equity prices. the regression coefficients of ongc confirm that the first lag of oil and its price will cause its price movements in addition to the crude oil price. the coefficients of petronet table 3: results of correlation analysis and granger causality tests correlation of crude oil with indian oil exploration equities crude does not granger cause oil exploration equity price variable price series return series price series return series hoec 0.34 0.056 0.00 0.00 oil 0.67 0.072 0.02 0.00 ongc 0.56 0.080 0.00 0.00 petronet −0.63 −0.004 0.05 0.05 reliance −0.36 0.046 0.01 0.00 source: authors’ computations figure 3: impulse response of indian oil exploration equity returns to the crude oil return. source: authors processing table 4: var estimates lag crude hoec oil ongc petronet reliance crude (−1) −0.116 0.117 0.045 0.086 0.027 0.058 −0.020 −0.023 −0.013 −0.014 −0.013 −0.012 (−5.725) (5.120) (3.485) (6.292) (2.107) (4.836) crude (−2) −0.088 0.073 0.025 0.081 0.005 0.011 −0.021 −0.023 −0.013 −0.014 −0.013 −0.012 (−4.282) (3.158) (1.937) (5.869) (0.379) (0.909) source: authors’ estimation kumar, et al.: investigating the nexus between crude oil price and stock prices of oil exploration companies international journal of energy economics and policy | vol 12 • issue 4 • 202246 and reliance confirm that the first lag of crude oil price will cause the price and return of these equities. the impulse response of indian oil exploration equity returns for crude oil return shocks is plotted in figure 3. a positive crude return shock would increase oil exploration equity returns in india, and we found that a positive crude oil disturbance would increase india’s oil exploration equity prices. the red and blue lines in figure 3 are 95% confidence interval and response to shock, respectively. 5. conclusion examining the linkage between commodities markets with other economies’ markets has become the interest of many researchers today. the stock markets have become more volatile in recent decades. numerous studies have evidenced the positive or negative impact of macros like oil price, interest rate, inflation rate and currency exchange rates on the financial markets. in such markets, examining and understanding the influence of such macros on the market of a particular sector is essential. this study has examined the nexus between international crude prices and indian oil exploration equity prices. the var (2) model found that the past 2 days’ price of crude oil would influence the price of hoec, oil and ongc equities. the correlation coefficients and the granger causality test statistics confirmed the linkage between oil price and oil exploration equities. further, the previous day’s price of crude would influence the price of petronet and reliance. these findings are supported by the impulse response of indian oil exploration equity returns to the positive international crude oil returns shock. further, using multivariate volatility models, one can examine the portfolio hedging feasibility of crude oil futures to oil exploration equity portfolios. these causal studies help investors and analysts decide on their buy, sell, or hold decisions in the equity markets. references adam, p., ode saidi, l., tondi, l., ode arsad sani, l. (2018), the causal relationship between crude oil price, exchange rate and rice price. international journal of energy economics and policy, 8(1), 90-94. alamgir, f., amin, s.b. (2021), the nexus between oil price and stock market: evidence from south asia. energy reports, 7, 693-703. amin, s.b. (2015), the macroeconomics of energy price shocks and electricity market reforms: the case of bangladesh, durham university. available from: http://www.etheses.dur. ac.uk/11241/%0ause atif, m., rabbani, m.r., bawazir, h., hawaldar, i.t., chebab, d., karim, s., abbas, a. (2022) oil price changes and stock returns: fresh evidence from oil exporting and oil importing countries. cogent economics and finance, 10(1), 2018163. bagchi, b. (2017), volatility spillovers between crude oil price and stock markets : evidence from bric countries. international journal of emerging markets, 12(2), 352-365. barbaglia, l., croux, c., wilms, i. (2020), volatility spillovers in commodity markets : a large t-vector autoregressive approach. energy economics, 85, 104555. blanchard, o.j., gali, j. (2007), the macroeconomic effects of oil shocks: why are the 2000s so different from the 1970s? in national bureau of economic research no. 15467. bourghelle, d., jawadi, f., rozin, p. (2021), oil price volatility in the context of covid-19. international economics, 167, 39-49. bunnag, t. (2015), volatility transmission in oil futures markets and carbon emissions futures. international journal of energy economics and policy, 5(3), 647-659. butt, s., ramakrishnan, s., loganathan, n., chohan, m.a. (2020), evaluating the exchange rate and commodity price nexus in malaysia : evidence from the threshold cointegration approach. financial innovation, 6(22), 1-10. dutta, a. (2018), oil and energy sector stock markets: an analysis of implied volatility indexes. journal of multinational financial management, 44, 61-68. fuentes, f., herrera, r. (2020), dynamics of connectedness in clean energy stocks. energies, 13(14), 1-18. granger, c.w.j. (1969), investigating causal relations by econometric models and cross-spectral methods. econometrica-journal of the econometric society, 37(3), 424-438. hawaldar, i.t. (2016), the cross-sectional variations in portfolio returns: evidence from bahrain bourse. british journal of economics, finance and management sciences, 12(2), 1-11. hung, n.t. (2019), return and volatility spillover across equity markets between china and southeast asian countries. journal of economics, finance and administrative science, 24(47), 66-81. iqbal, t.h. (2011), relevance of capital asset pricing model-a review. journal on banking financial services and insurance research, 1(2), 85-97. iqbal, t.h. (2014), seasonal analysis of abnormal returns after quarterly earnings announcements. international journal of accounting and financial reporting, 4(2), 501-519. iqbal, t.h. (2015), empirical testing of capital asset pricing model on bahrain bourse. asian journal of finance and accounting, 7(2), 107-119. iqbal, t.h., mallikarjunappa, t. (2009), indian stock market reaction to the quarterly earnings information. indian journal of finance, 3(7), 43-50. iqbal, t.h., mallikarjunappa, t., nayak, p. (2007), stock price adjustments to quarterly earnings announcement: a test of semi-strong form of efficiency. gyan management, 1(2), 25-42. kilian, l., zhou, x. (2020), the econometrics of oil market var models. federal reserve bank of dallas, working papers, 2020(2006). kumar, a., pinto, p., hawaldar, i.t., spulbar, c.m., birau, f.r. (2021), crude oil futures to manage the price risk of natural rubber: empirical evidence from india. agricultural economics-czech, 67(10), 423-434. kumar, a., soni, r., hawaldar, i.t., vyas, m., yadav, v. (2020), the testing of efficient market hypotheses: a study of indian pharmaceutical industry. international journal of economics and financial issues, 10(3), 208-216. kumar, d., maheswaran, s. (2013), correlation transmission between crude oil and indian markets. south asian journal of global business research, 2(2), 211-229. kumar, k.a., pinto, p., hawaldar, i.t., ramesh, k.g. (2021), can crude oil futures be the good hedging tool for tyre equities? evidence from india. international journal of energy economics and policy, 11(6), 523-537. liu, t., hamori, s. (2020), spillovers to renewable energy stocks in the us and europe: are they different? energies, 13(12), 3162. long, p.d., hien, b.q., ngoc, p.t.b. (2021), money supply, inflation and output: an empirically comparative analysis for vietnam and china. asian journal of economics and banking, 3(1), 1-13. meher, b.k., hawaldar, i.t., mohapatra, l., sarea, a.m. (2020), the impact of covid-19 on price volatility of crude oil and natural gas kumar, et al.: investigating the nexus between crude oil price and stock prices of oil exploration companies international journal of energy economics and policy | vol 12 • issue 4 • 2022 47 listed on multi commodity exchange of india. international journal of energy economics and policy, 10(5), 1-10. meher, b.k., hawaldar, i.t., spulbar, c., birau, r. (2021), forecasting stock market prices using mixed arima model: a case study of indian pharmaceutical companies. investment management and financial innovations, 18(1), 42-54. mishra, s., debasish, s.s. (2022), exploring the relationship between crude oil price volatility and stock indices movement using wavelet analysis: evidence from india and china. vilakshan-ximb journal of management, 19(1), 69-86. profillidis, v.a., botzoris, g.n. (2019), econometric, gravity, and the 4-step methods. in: modeling of transport demand. netherlands: elsevier. saeed, t., bouri, e., vo, x.v. (2020), hedging strategies of green assets against dirty energy assets. energies, 13(12), 3141. shaikh, i. (2021), on the relation between the crude oil market and pandemic covid-19. european journal of management and business economics, 30(3), 331-356. shyam, a. (2019), lower oil prices could put tyre companies on the fast track. the economic times. p3-5. availabler from: https:// www.economictimes.indiatimes.com/markets/stocks/news/ lower-oil-prices-could-put-tyre-companies-on-the-fast-track/ articleshow/67376148.cm… songsiengchai, p., sidique, s.f., djama, m., azman-saini, w.n.w. (2018), a cointegration analysis of crude palm oil price in thailand. e3s web of conferences, 52. yu-ling hsiao, c., lin, w., wei, x., yan, g., li, s., sheng, n. (2019), the impact of international oil prices on the stock price fluctuations of china’s renewable energy enterprises. energies, 12(24), 4630. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 2 • 2023 545 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(2), 545-552. impact of oil and non-oil tax revenue on economic growth in nigeria adegbola olubukola otekunrin1, samuel adeniran fakile2, damilola felix eluyela3*, ademola andrew onabote4,5, okoye nonso john6, sarah ifeanyichukwu2,6 1department of accounting, bowen university, iwo, osun state, nigeria, 2department of accounting and finance, landmark university, omu aran, nigeria, 3tasmanian school of business and economics, university of tasmania, australia, 4department of economics, landmark university, omu aran, nigeria, 5landmark university sdg 8 group, omu aran, nigeria, 6department of banking and finance, nnamdi azikiwe university, awka, anambra state, nigeria. *email: eluyela.damilola@lmu.edu.ng received: 08 january 2022 accepted: 05 january 2023 doi: https://doi.org/10.32479/ijeep.12781 abstract this study examined the impact of oil and non-oil tax revenue on economic growth in nigeria. few works have covered oil and non-oil taxation and the relationship of petroleum profit tax (ppt), company income tax (cit), value added tax (vat) and custom and excise duties tax (ced) on real gross domestic product of nigeria. the study adopted ex-post facto research design, and data were drawn from the annual reports of central bank of nigeria and federal inland revenue services publications. error correction model was employed to analyse the data collected after subjecting the series to unit root test and cointegration test. the result of the study showed that ppt with coefficient of 31.71067 and p = 0.0004 and ced with coefficient of 1.786145 and p = 0.0206 had appositive significant relationship with economic growth, while cit with coefficient of −14446.50 and p = 0.0066 and vat with coefficient of −23.33177 and p = 0.0001 had a negative significant relationship with economic. the study recommends that taxation is appropriately controlled to boost economic growth, lower inflation, and create jobs in the country. more attention to channelling of ppt and ced revenue collections to infrastructural developments will bring about economic growth of the country. keywords: economic growth, gross domestic product, non-oil tax, oil tax, revenue jel classification: o47, h71 1. introduction every accountable and competent government has a primary responsibility to provide appropriate public goods and basic infrastructure to improve the level of living of its population. nigeria, like many other countries, is reliant on revenue production to support its population’s basic and infrastructure demands. taxation is one of the available sources of revenue for delivering essential services to the majority of people in a given location. (olufemi et al., 2018). the demand for tax payments has been a worldwide phenomenon since it affects every economy, regardless of national differences. as a result, a tax is an imposed monetary contribution to the government that is mandated by law. (ican, citn) to put it differently, every tax must be based on a legally binding statute. tax revenue in nigeria can be divided into two categories: oil and non-oil tax revenue. oil tax revenues are derived through taxes imposed on the earnings and profits of oil corporations operating in nigeria. petroleum profit tax (ppt) and royalty from oil extraction economic rentals are two examples. non-oil tax revenues, on the other hand, are revenues derived from taxes other than oil-related activities, such as corporate income tax (cit), personal income tax (pit), value added tax (vat), and so on (yahaya and yusuf, 2019). the agricultural industry was the basis of the nigerian economy before the discovery of oil in oloibiri, bayelsa state, nigeria (abomaye-nimenibo et al., 2018). according to the world bank (2013), before oil, nigeria’s agriculture industry generated nearly this journal is licensed under a creative commons attribution 4.0 international license otekunrin, et al.: impact of oil and non-oil tax revenue on economic growth in nigeria international journal of energy economics and policy | vol 13 • issue 2 • 2023546 95% of the country’s foreign exchange revenues, over 60% of its employment potential, and around 56% of its gross domestic earnings. following the discovery of oil, nigeria’s petroleum industry grew to become the country’s largest. oil accounted for almost 90% of foreign exchange earnings and about 80% of federal revenue and adds to the nigerian economy’s rate of growth. the oil boom of the 1970s led to a neglect of the country’s agricultural and manufacturing sectors in favour of the oil industry. oil has undoubtedly contributed significantly to nigeria’s revenue creation and economic progress, but the country’s overdependence on the oil sector, as well as the urgent need for diversification, have become major concerns. (abomaye-nimenibo et al., 2018). since independence, the nigerian state has struggled with economic growth, with several policies aimed at reviving the economy failing to provide real results. unemployment, high death rate due to a poor health-care system, brain drain due to insufficient educational funding, lack of essential infrastructure, high inflation, insecurity, and other concerns continue to plague nigeria. the occurrence of all of these critical challenges, as well as the recent drop in crude oil prices on the global market, necessitates a look at the impact of tax revenue on economic growth (ewa et al., 2020). because of its overdependence on the oil sector, nigeria’s economy has suffered substantial economic losses over the years. this has necessitated the urgent need for economic diversification to boost economic growth. the most pressing issue is determining the best balance between a tax system that is business and investment friendly while also generating enough income for the delivery of public services, which makes the economy more appealing to investors (abomaye-nimenibo et al., 2018). taxation is necessary for the government to provide essential services to citizens, and citizen neglect results in a significant loss of money and the government’s incapacity to provide basic infrastructure that enhances the citizens’ standard of living. this is reflected in a statistic from the nigeria bureau of statistics (nbs), which estimates nigeria’s employed population at 69.5 million as of september 2018. however, the individual taxpaying population is projected to be 19 million, implying that around 50.5 million nigerians are employed but not paying taxes. the low tax-to-gdp ratio can be attributed to a low degree of compliance. when compared to south africa, where the tax-togdp ratio is more than 25%, this is even more concerning. the tax-to-gdp ratio in nigeria is among the lowest in the world. in 2018, it was estimated to be 6.3% according to the organisation for economic cooperation and development (oecd). developed countries like usa has a tax estimate of 24.5% in 2019 according to oecd. developed countries that have a higher compliance rate and better management have been able to use their resources to provide important services for their residents’ welfare. tax-togdp ratios in countries such as the united states, france, and denmark are high, owing to strong taxpayer compliance and good tax administration. other studies such as (abomaye-nimenibo et al., 2018; mohammed et al., 2020; yahaya and yusuf, 2019) have expended significant effort on existing literature focusing on non-oil tax revenue and economic growth using a related approach (linear regression). however, this study therefore, seeks to close the knowledge gap by examining the extent to which both oil tax revenue (petroleum profit tax) and non-oil tax revenue (companies income tax, personal income tax, value added tax) impacts economic growth in nigeria using a different approach (auto regressive). using empirical data to determine the impact of taxation on economic growth in nigeria is a timely research project, as there is a pressing need to investigate the relationship between petroleum profit tax, corporate income tax, customs and excise levies, and economic growth in nigeria. this study will not only ensure that the country’s income base is improved, but it will also position the government to take full advantage of the new millennium global tax reform system. the study would be beneficial to tax policy makers, researchers, and the public. this study therefore seeks to answer the following questions. 1. what is the significant relationship between petroleum profit tax and economic growth in nigeria? 2. what is the significant relationship between companies and excise duty tax and economic growth in nigeria? 3. what is the significant relationship between personal income tax and economic growth in nigeria? 4. what is the significant relationship between value added tax and economic growth? to address the above stated questions, annual time series data were collected for the period 1980 to 2019 from the central bank of nigeria (cbn) statistical bulletin, and federal inland revenue services (firs) tax statistics for the reference period in order to test the following research null hypotheses formulated: • h01: there is no significant relationship between petroleum profit tax and economic growth in nigeria • h02: there is no significant relationship between companies’ income tax and economic growth in nigeria • h03: there is no significant relationship between custom and excise duty tax and economic growth in nigeria • h04: there is no significant relationship between value added tax and economic growth in nigeria. 2. literature review the nigerian tax system dates back to 1904, when the personal income tax was implemented in northern nigeria prior to the colonial masters’ unification of the country. it was eventually adopted in the western and eastern regions through native revenue ordinances in 1917 and 1928, respectively. among other amendments in the 1930s it was later incorporated into direct taxation ordinance no. 4 of 1940 (bukie and adejumo, 2011). in essence, nigeria’s tax system is based on british tax rules and has undergone a number of adjustments in recent years. different governments have continued to improve the system since then. the recent amendment to the companies and allied matters act 2016, which gave birth to the companies and allied matters act (cama) 2020, has made a significant improvement to the country’s tax system. the joint tax board and the federal inland revenue services are the two main bodies in charge of tax administration in nigeria. the joint tax board was founded in 1961 to provide guidance otekunrin, et al.: impact of oil and non-oil tax revenue on economic growth in nigeria international journal of energy economics and policy | vol 13 • issue 2 • 2023 547 and coordinate various aspects of tax revenue, as well as to ensure uniformity in both the execution of the personal income tax act 1993 and the tax incidence on persons across nigeria. the federal board of inland revenue, on the other hand, was founded in 1990 with the authority to manage corporate income taxes. the federal inland revenue service (firs), which was founded in 1993 and is responsible for income tax assessment, collection, accounting, and administration, is the main operator of this entity. the three tiers of government (federal, state, and local government) enforce tax revenue under current nigerian law, with each domain specifically defined in the taxes and levies (authorized list for collection) decree, 1998 (appah, 2010). multiple taxation by the three tiers of government, however, remains a problem in nigeria, posing a significant obstacle and increasing welfare costs. the low productivity of the nigerian tax system has been a source of worry for successive governments. this can be attributed to flaws in the tax administration and collecting system, complicated legislation, and general apathy especially on the part of those outside the tax net. 2.1. concept of taxation the word ‘tax’ is derived from the latin word ‘taxo’, that is to estimate the value or compute the value (lewis et al., 1975). as a result, tax is defined as a regular and obligatory payment made by citizens to the government in exchange for the use of government services (agunbiade et al., 2020). according to world bank (2000), taxes are the forced transfer of income from the rest of the economy to the government. chibu and njoku (2015), emphasize that taxes are an important source of revenue for all economies, and that they are typically utilized to close the gap between the rich and the poor. tax income is recognized as the most essential financial source for governmental public expenditures among the many ways the government might create cash. (fregnall-hughes, 2014). taxation is the process of forcing communities or groups of people to contribute in a certain amount and in a certain way for the administration and growth of society. (ogundele, 1999). taxation is a non-penal levy imposed by the government on the profits, income, or consumption of its citizens through its agent. (ojong et al., 2016). because the government has particular tasks to undertake for the benefit of people it rules, taxation is considered as a burden that every citizen must incur in order to sustain his or her government. (bruno and emmanuel, 2019). akintoye and tashie (2013) asserted that people’s willingness to pay taxes is critical and cannot be overlooked. they urged that the government pay attention to citizens’ willingness to pay taxes and improve on it. according to adams (2012), taxation is the most important source of revenue for modern governments, accounting for 90% or more of their total revenue. however, this is not the situation in nigeria, where tax money has historically accounted for a minimal part of total government revenue. this is because bulk of revenue needed is derived from oil (ayuba, 2014). the provision of basic infrastructure is critical for any society’s growth. this explains why the government is so concerned about finding a channel through which cash can be made accessible to meet the society’s aims (fagbemi, 2010). the main objective of taxation is to raise revenue to meet government expenditure and to redistribute wealth and management of the economy (ojong et al., 2016). anyanwu (1993) pointed out that there are three basic objectives of taxation. these are to raise revenue for the government, to regulate the economy and economic activities and to control income and employment. taxes generally have allocation, distributional and stabilization function (nzotta, 2007). according to musgrave and musgrave (2006). the distributional function is concerned with the distribution of income and wealth in order to guarantee that it adheres to what society views to be a fair or just allocation. the stabilization function aims to achieve a high level of employment, a tolerable degree of price stability, and a suitable rate of economic growth while accounting for trade and balance of payment consequences. the decision of the pattern of production, the goods that should be produced, who should produce them, the interaction between the private and public sectors, and the point of social balance between the two sectors are all part of the tax allocation function. 2.2. oil and non-oil tax revenue oil and non-oil tax revenue are the two main types of tax revenue that a country like nigeria collects. petroleum profit tax (ppt), royalty, and gas tax are all included in the oil tax revenue. on the other hand, non-oil tax revenue is revenue from direct and indirect sources paid by other sectors of the economy other than the oil sector. direct taxes are those that are imposed directly on a person or a company, and the individual or company is expected to pay the tax as recommended by the notification, known as an assessment notice. (abomaye-nimenibo et al., 2018). direct taxes are personal income tax (pit), company income tax (cit), capital gains tax, withholding tax and education tax. while, the indirect taxes are taxes in which the burden of the taxes are distributed among the taxpayers who pays the tax knowingly or unknowingly. tax burden is collected from the taxpayers proportionally, progressively, or regressively. indirect taxes are value added tax (vat) and custom and excise duties. 2.3. economic growth economic growth simply refers to an increase in the value of a country’s goods and services produced over time, and it may be used to measure a country’s size. (yahaya and yusuf, 2019). economic growth is defined by dwivedi (2004) as a sustained increase in the nation’s per capita output through time, or as the net national product over time. it indicates that the pace of rise in total output must be greater than the rate of population growth, resulting in an improvement in citizens’ living standards. according to olapade and olapade (2010), a rise in economic activity is referred to as “growth.” economic growth is defined as a rise in the value of a country’s goods and services over a period of time. (ewa et al., 2020). gross domestic product is used to measure this increase in economic growth. as a result, it is likely that a country’s economic expansion will not result in economic progress in the short, medium, or long term. (hadjimichael et al., 2014) economic growth refers to the monetary values of commodities produced in a country over a period of time by its population, regardless of their nationality. gdp can be calculated using the current basic price (nominal gdp), the constant basic price (real gdp), or the current market price. because it accounts for changes in the price level of goods and services produced inside the country at a given time, real gdp has been a good measure otekunrin, et al.: impact of oil and non-oil tax revenue on economic growth in nigeria international journal of energy economics and policy | vol 13 • issue 2 • 2023548 of economic growth. the study used real gdp as a proxy for economic growth as a result of this. 2.4. petroleum profit tax the colonial lords first imposed a petroleum profit tax in 1957, but it only became effective and operational in 1958, when nigeria began exporting crude oil to the world market. petroleum profit tax, as defined by the petroleum profit tax act of 1959, is a liability incurred when a corporation sells chargeable oil and gas. under the rules of the ppta in nigeria, disposal includes delivery of chargeable oil to refineries; the tax is levied on the company’s earnings from petroleum operations. petroleum exploration, development, production, and sales are all included in the act’s definition of a petroleum operation. 2.5. companies income tax profits of all incorporated entities in nigeria accruing in, derived from, brought into, or received in nigeria are subject to corporate income tax. (yahaya and yusuf, 2019). non-residents’ revenue (private and public limited firms) derived from doing business in nigeria is subject to this type of tax. (appah, 2010). the company’s income act of 1979, which oversees the assessment and collection procedures and has its roots in the income tax management act of 1961, established companies’ income tax. a number of other revisions have been enacted as acts or degrees. 2.6. custom and excise duty tax importers of certain commodities must pay customs duty, which is an important source of revenue for the federal government (buyonge, 2008). customs and excise duties are a large portion of non-oil revenue and has been a significant source of revenue both before and after the discovery of oil in nigeria, contributing significantly to national development over the years. customs duties are the sum of all duties collected by the customs and excise department on imports and exports. excise taxes are levied by the government at various rates on certain commodities produced in a country. (abomaye-nimenibo et al., 2018). 2.7. value added tax according to abata, (2014) vat, or value-added tax, is a type of consumption tax in which the tax burden is carried by the consumer. he added that the tax burden is transmitted from the producer to the middlemen (wholesaler and retailer), who then pass it on to the consumer. as a result, vat cannot be avoided unless individuals refrain from purchasing and consuming value added tax goods and services. the vat system in nigeria is a multi-step system in which vat is collected at each stage of the manufacturing process, from the manufacturer to the consumer . vat is currently set at 7.5%. 2.8. benefit received theory this idea believes that the taxpayer and the state have an exchange relationship since the state delivers certain commodities and services to society’s members. as a result, society members should contribute to the cost of these supplies in proportion to their benefits. (bhartia, 2009). this notion is found in the cit, vat, and pit relationships with economic growth, where the non-oil tax levies reflect the advantages obtained in the consumption of social goods. knut wicksell (1896) and erik lindahl were the first to propose this notion (1919). tax progressivity, company taxes, and property or wealth taxes have all been studied using this idea. 2.9. prior studies from 1993 to 2012, akwe (2010) looked at the impact of non-oil tax revenue on nigerian economic growth. secondary data from the central bank of nigeria’s statistical bulletin for 2012 was used (cbn). the ordinary least squares regression was used to analyse the data. the test’s findings indicate that non-oil tax revenue has a favourable impact on nigeria’s economic growth. according to the report, the government should intensify its efforts at all levels to increase non-oil tax collection, particularly from the informal sector, because this rise has the potential to grow the economy. it was also advised that the federal inland revenue service (firs) and other relevant tax authorities’ administrative machinery be reinforced in order to eliminate deficiencies and internal control failures in the assessment and collection of nonoil taxes in nigeria. yahaya and yusuf (2009) looked into the impact of non-oil tax revenue on nigerian economic growth. ex-post facto research was used in this study. after running the series via unit root and co-integration tests, the data was analyzed using auto regressive distributive lag (ardl). cit had a positive significant association with economic growth, while vat had a positive insignificant relationship with economic growth, according to the study’s findings. according to the report, the government should focus on raising cit revenue by strengthening tax compliance standards to reduce tax evasion and avoidance. more emphasis on channelling vat and ced income collections to infrastructural development will result in the country’s economic progress. using economic growth as the dependent variable and petroleum profit tax (ppt), company income tax (cit), and customs and excise duties (ced) as the independent variables, abomayenimenibo et al. (2018) empirically examine the tax revenue and economic growth in nigeria from 1980 to 2015. the study’s analysis was conducted out utilizing the multiple regression analysis approach. the major analytical methodology used with econometric software (e-views 9.0) was the ordinary least square (ols) method of econometrics. bukie and adejumo (2011) used time series data covering the years 1970-2011 to investigate the impact of tax income on economic growth in nigeria. the study used the ordinary least square (ols) regression technique to discover that tax income has a beneficial impact on nigeria’s economic growth. domestic investment, labour force, and foreign direct investment all have a favourable and significant impact on nigeria’s economic growth, according to the findings. olugbemi et al. (2019) investigated the impact of tax income on nigerian economic growth. to determine the elements that influence tax revenue and economic growth in nigeria, an exploratory approach was used. to determine the relationship between dependent and independent variables, a multiple regression model was used to analyse the data collected for this project. using gdp as an index economy, the results demonstrated otekunrin, et al.: impact of oil and non-oil tax revenue on economic growth in nigeria international journal of energy economics and policy | vol 13 • issue 2 • 2023 549 a favourable link between tax revenue and economic growth. according to the report, public monies should be appropriately employed to favourably impact the nigerian economy’s growth. 2.10. gaps in literature the government has to reform tax administration and employ revenue earned more efficiently to promote the country’s economic growth, according to the literature evaluated in this study. it’s also worth noting that the country’s over reliance on the oil sector has led to a neglect of the non-oil economy. it was also demonstrated that a lack of fundamental facilities in society causes citizens to avoid or delay paying taxes since they perceive the money is being wasted. as a result, the government is advised to provide basic infrastructure in order to promote inhabitants’ well-being. 3. methodology the study examined the impact of oil and non-oil tax revenue on economic growth in nigeria. the expost facto research design was adopted for the study. this is on the basis that the required data cannot be manipulated because they have already existed. economic growth was measured using real gross domestic product (rgdp) while the oil tax revenue (independent variable) was proxied by petroleum profit tax and non-oil tax revenue was proxied by company income tax (cit), value added tax (vat) and custom and excise duty tax (ced). the study used annual time series secondary data obtained from central bank of nigeria (cbn) statistical bulletins for the period of 39 years (1980-2019) the study error correction model technique to investigate the hypotheses formulated for the study. this technique was adopted after subjecting the series in the model of the study to unit root test and co-integration test. 3.1. model specification this study adopted an economic model previously used by yahaya and yusuf (2019) to examine impact of non-oil tax revenue on economic growth in nigeria. the work examined companies income tax; value added tax and custom and excise duty tax. the model was presented as; gdp cit vat cedt = + + + +β β β β µ0 1 1 2 1 3 1 1 this study modifies the model by adding another variable suitable for this study. thus, the model was modified as; gdp ppt cit ced vatt t t= + + + + +β β β β β µ0 1 2 3 1 4 1 1 where; gdp = gross domestic product ppt= petroleum profit tax cit= companies income tax ced= custom and excise duty tax vat= value added tax t = time β0 = constant β1 + β2 + β3 + β4 = coefficient of parameters of taxation µ = error t-erm (stochastic term) a prior expectations β0>0,β1>0,β2>0,β3>0,β4>0 4. results and discussion the data collected for the study were subjected to descriptive statistics and presented for better understanding of the nature and distribution of the series. the results of unit root test, cointegration test and regression analysis were also presented as well as discussion of findings. table 1 shows result from descriptive statistics. the descriptive statistics presents the mean, median, standard deviation, coefficient of skewness, coefficient of kurtosis and coefficient of variation of the variables ppt, cit vat and ced. the discrepancies between the means and the medians of the variables is a reflection of the degrees of skewness of the respective variables. the results of the jarqu-bera test and the associated asymptotic significance probabilities of 46.5 (p < 0.000), 27.6 (p < 0.000), 14.2 (p < 0.00), 5.07 (0.08) and 20.3 (p < 0.000) for gdp ppt, cit, vat and ced respectively indicate that only vat data are approximately normally distributed. the coefficients of skewness also speak volumes of the deviation of the respective variable, expect vat, from normality as a normal distributed variable should had a coefficient of skewness that is zero or significantly close to zero. in terms of the spread of the data about the mean, the variables that are least dispersed to the most dispersed are cit, ppt, vat, ced and gdp, sing the standard deviation. however, in terms of total variation, the ordering of the variables from least to highest is gdp, cit, ppt, vat and ced it is pertinent to note that the dispersion of the observations about the mean (captured by the standard deviation) is slightly different from the variation of the observations about the mean using coefficient of variation. the coefficient of variation can also be used to infer the precision of the estimates. in this context, the order of precision of the variables in ascending order is: ced, vat, ppt, cit and gdp. but the basis of comparison in this manner is constrained by the differences in the variables. furthermore, all the variables are leptokurtic (table 1). table 2 shows result from stationarity test. results of the stationarity tests show that none of the variables was stationary at level; however, all the five variables, gross domestic product (gdp), petroleum profit tax (ppt), company income tax (cit), value added tax (vat) and (ced) were all significant at first difference (table 1). 4.1. cointegration test in table 3, results of the cointegration test indicate that the asymptotic significant probabilities associated with the null table 1: descriptive statistics statistics gdp ppt cit vat ced mean 369550.1 15648.52 166.3022 125467.4 187849.4 median 26909.00 3827.900 35.30000 55000.00 177700.0 maximum 2812300. 89100.00 802.9647 438300.0 876514.0 minimum 939.4122 403.0000 0.000000 1616.000 1728.200 sd 694026.9 21761.13 252.4217 146348.1 192851.5 observations 35 35 35 35 35 source: authors computation (2021) otekunrin, et al.: impact of oil and non-oil tax revenue on economic growth in nigeria international journal of energy economics and policy | vol 13 • issue 2 • 2023550 hypotheses that: there is no cointegration equation, at most one, at most two, and at most 4 cointegration equations were p < 0.001, p < 0.001, p < 0.001, 0.059 and 0.0152 respectively. thus, while we may reject the hypotheses that there is no cointegrating equation, there is at most one cointegration equation, at most 2 cointegrating equations and there are at most 4 cointegrating equations we cannot reject the hypotheses that there are at most three cointegrating equations. the implication is that there are three cointegrating equations and thus, there is a long-run relationship between the variables (table 2). 4.2. estimated equation d(gdp) = c(1)* (gdp (−1) + 10.5898507651*ppt (−1) + 237.07*cit (−1) 47.3*0vat (−1) + 2.254*ced (−1) +1120567.99781) + c(2)*d(gdp (−1)) + c(3)*d (gdp(−2)) + c(4)*d (ppt (−1)) + c(5)* d (ppt(−2) + c(6)*d (cit (−1)) + c(7) *d (cit(−2)) + c(8)*d (vat (−1) + c(9)*d (vat(−2) + c(10)*d(ced (−1)) + c(11)*d (ced (−2) + c(12) 4.3. long run estimation results of the error correction model present the long run equilibrium relations. the cointegration equation is estimated as: gdp + 112.06 +10.59 ppt (−1) + 237 cit (−1) − 47.32 vat (−1) + 2.354 ced (−1) = 0; thus, gdp = – 112.06 − 10.59 ppt (−1) − 23.7 cit (−1) + 47.32 vit (−1) −2.34 ced (−1) the estimated vecm results in table 4 indicate that a unit change in petroleum profit tax will lead to 1059% change in the level of gdp and thus the economic growth of nigeria. in the same vein, a unit change in company income tax will cause a 2370% change in the gdp, a unit change in value added tax will cause a 4732% change in the gdp, while a unit change in ced will cause a 235.4% change in the ced. the results further show that three of the explanatory variables (petroleum profit tax, company income tax and custom and excise duty tax) have negative long-run relationships with the economic growth (gdp), while value added tax (vat) had a positive relationship (table 3). furthermore, it was observed that petroleum profit tax (ppt), company income tax (cit) and value added tax (vat) significantly influence economic growth (gdp) in the long run while ced had no significant influence on economic growth (table 3). based on the results of the stationarity tests, which indicated that all, the variables were stationarity first difference, the study employed the vector error correction model in data analysis. 4.4. short run estimation following the long-run coefficients of the cointegration equations, the short-run coefficients were estimated through the error correction model (ecm) component (table 5). the ecm estimations in the cointegration equation show that the coefficients of all the regressors have the hypothesized (a priori) signs. two of the variables, petroleum profit tax and company income tax, had statistically significant short run influence on economic growth (gdp) at the ninety-nine percent and ninetyfive percent confidence levels respectively; and like the longrun relationships, both variables had a positive short-run effect on economic growth. furthermore, the coefficient of the error correction term (ect) is −0.5912 and this coefficient had a calculated t of −5.572 and a p value of (p < 0.001). thus, the speed of adjustment after short-run fluctuations is 59.12%. the value indicates the speed of restoration of the system to equilibrium after a previous deviation. d(gdp) = c (1)*(gdp (−1) + 10.5898507651*ppt (−1) + 23707.1701216*cit (−1) 47.3018563285*vat (−1) + 2.25443464447*ced (−1) + 1120567.99781) + c(2)*d(gdp (−1)) + c(3)*d(gdp(−2)) + c(4)*d(ppt (−1)) + c(5)*d(ppt(−2)) + c(6)*d(cit (−1)) + c(7)*d(cit(−2)) + c(8) *d(vat (−1)) + c(9)*d(vat(−2)) + c(10)*d(ced (−1)) + c(11)*d(ced(−2)) + c(12) lastly, results of the error correction model show that that the explanatory variables (petroleum profit tax, company income tax, value added tax and ced) explain about 69.12% of the variation table 4: estimated vector error correction model dependent variable npi variable coefficient standard error t statistic significant p remark gdp (−1) 1.000 ppt (−1) 10.59 2.29 4.619 0.0010 significant cit (−1) 23.7 64.6 36.65 vat (−1) −47.32 1.698 −27.85 0.062 ns ced (−1) 2.354 0.790 2.855 0.0752 ns c 112.05 source: authors computation (2021) table 2: results of stationarity tests variable p-value at level p-value at 1st difference remark gdp 0.071 0.0086 stationary at 1st difference ppt 0.146 0.000 stationary at 1st difference cit 1.00 0.024 stationary at 1st difference vat 0.996 0.000 stationary at 1st difference ced 0.994 0.000 stationary at 1st difference source: authors computation (2021) table 3: cointegration test hypothesized number eigenvalue trace statistic value critical asymp. value prob. none * 0.9123 184.91 69.82 0.000 at most 1* 0.8268 104.56 47.86 0.000 at most 2* 0.5585 26.98 21.12 0.007 at most 3 0.3421 13.82 14.26 0.059 at most 4* 0.1634 5. 889 3.8415 0.0152 source: authors computation (2021) otekunrin, et al.: impact of oil and non-oil tax revenue on economic growth in nigeria international journal of energy economics and policy | vol 13 • issue 2 • 2023 551 in the dependent variable (economic growth) as shown by the adjusted coefficients of variation (table 6). diagnostic tests were also performed. firstly, a test for serial correlation was performed on the residuals using breusch-godfrey test. the results indicate an asymptotic probability value on 0.1633 for the chi-square statistic. thus, we cannot reject the null hypothesis that the stochastic error terms are not serially correlated. the results are consistent with the computed value of the durbin watson statistic of 1.9233 (table 7) which lies between the range du and 4-du where du is the upper value of the durbin watson statistic. the non-correlation of the stochastic error terms is an indication that the results are not spurious. 5. discussion of findings the results indicate that there is significant direct (positive) relationship between the level of economic growth (dependent variable) and petroleum profit tax and custom and excise duty tax and that there is a significant negative relationship between economic growth (dependent variable) and value added tax and companies’ income tax. the implication is that increase in petroleum profit tax and custom and excise duty leads to increase in the level of economic growth. both ppt and ced has a positive significant relationship. it therefore means that petroleum profit tax and custom and excise duty tax can be used to control economic growth. the study also revealed that increase in value added tax rate lead to decrease in the level of economic growth and increases in and company income tax lead to decrease in the level of economic growth. thus, instability in the realisation of petroleum profit tax, company income tax, custom and excise duty tax and value added tax stimulate disequilibrium in the level of economic growth in nigerian. the results are consistent with those of bukie and adejumo (2011), oshiobugie and akpokerere (2019), ewa et al. (2020), kingsley (2014), ojong et al. (2016), akwe (2010), yahaya and yusuf (2009), ojong et al. (2016), bukie and adejumo (2011), oshiobugie and akpokerere (2019), ewa et al. (2020), kingsley (2014). however, the results are inconsistent with that of asaolu et al. (2018) in that they did not find any significant relationship between petroleum profit tax and economic growth. 6. conclusion and recommendation in the course of the study, annual time series data were accessed and analysed to examine the impact of individual types of oil tax revenue (ppt) and non-oil tax revenue (cit, vat and ced) on economic growth (real gdp) in nigeria over the period 19802019. based on the findings of the study, it was concluded that ppt and ced has positive impact on economic growth in nigeria, while vat and cit had significant but negative impact on the real gross domestic product of nigeria for the study period. based on the findings, this study makes the following recommendations. the government should make sure that taxation is appropriately controlled in order to boost economic growth, lower inflation, and table 5: estimated vector error correction model error correction d (gdp) d (ppt) d (cit) d (vat) d (ced) coin eq1 −0.5912 −0.0066 −1.10e04 −0.0061 0.1008 (0.101) (0.0021) (4.3 e06) (0.0108) (0.0185) [−5.878] [−3.154] [−2.557] [−0.569] [−0.438] d (gdp (−1) −0.481 −0.0016 −3.85e-05 −0.0123 0.0249 (0.114) (0.0024) (4.9e06) (0.0122) (0.0211) [−4.201] [−0.683] [−7.9006] [−1.005] [1.1839] r-squared 0.8020 0.891009 0.9106 0.5415 0.89149 adj r-squared 0.6912 0.83106 0.86151 0.2893 0.83182 sum sq resids 2.30e+12 9.89e+08 4189.9 2.64e+10 7.83-e+10 s.e. equation 339382 7031.5 14.4740 36330 62551 f-statistic 7.3661 14.8637 18.5306 2.14698 14.93832 log likelihood −445.406 −321.34 −123.40 373.8996 −391.2861 akaike aic 28.5876 20.8342 8.4626 24.1187 25.2054 schwarz sc 29.1372 21.3839 9.0122 24.6684 25.7550 source: authors computation (2021) table 7: breusch-godfrey serial correlation lm test f statistic 1.2486 prob (f2 23) 0.3056 obs r squared 3.6238 prob. chi-square (2) 0.1633 durbin watson 1.9233 table 6: estimated vector error correction model error correction coefficient std. error t-statistic prob. c (1) −0.644019 0.115576 −5.572274 0.0000 c (2) −0.464260 0.133412 −3.479899 0.0022 c (3) −1.340249 0.325484 −4.117717 0.0005 c (4) 31.71067 7.594860 4.175281 0.0004 c (5) 11.64562 5.816487 2.002173 0.0583 c (6) −14446.50 4788.413 −3.016971 0.0066 c (7) 14541.90 4617.144 3.149544 0.0048 c (8) −23.33177 4.832181 −4.828414 0.0001 c (9) −20.80166 4.169682 −4.988789 0.0001 c (10) 1.786145 0.713346 2.503899 0.0206 c (11) 1.911082 0.769534 2.483429 0.0215 c (12) 546641.0 118852.5 4.599321 0.0002 r-squared 0.716518 mean dependent var −107.7709 adjusted r-squared 0.568028 s.d. dependent var 603023.8 s.e. of regression 396334.8 akaike info criterion 28.89319 sum squared resid 3.30e+12 schwarz criterion 29.43738 log likelihood −464.7377 hannan-quinn criter. 29.07630 f-statistic 4.825354 durbin-watson statson 1.803706 prob (f-statistic) 0.000981 otekunrin, et al.: impact of oil and non-oil tax revenue on economic growth in nigeria international journal of energy economics and policy | vol 13 • issue 2 • 2023552 create jobs in the country. the nigerian government should reform its tax system to meet the demands of the twenty-first century. if economic growth must be achieved in nigeria, then the federal government as a matter of urgency, needs to restructure the tax system in nigeria. tax revenue should also be used effectively and judiciously to offer essential services to nigeria’s taxpaying population. the government should also take steps to diversify the economy, rather than focusing solely on the oil industry. the revenue collected from taxes, particularly the petroleum profit tax and custom and excise duty tax, should be used to build the domestic economy, specifically the agro-allied industry and the manufacturing sector. the government should educate citizens about the importance of paying taxes and not evading them through public awareness campaigns and education. nigeria’s tax regulatory authority must establish strategies to close gaps in tax rules that taxpayers exploit to avoid paying taxes. finally, the government should prudently use tax income to provide essential services such as good housing, roads, water, stable power supply, education, primary health care and this will aid the growth of numerous economic sectors, hence boosting economic growth. references abata, m.a. (2014), the impacts of tax revenue on nigerian economy. journal of policy and development studies, 9(1), 109-123. abomaye-nimenibo, w. a. s., michael, j. e., & friday, h. c.(2018), an empirical analysis of tax revenue and economic growth in nigeria from 1980 to 2015. global journal of human social science, 18(3), 8-33. adereti, s.a, sanni, m.r, adesina, j.a. (2011), value added tax and economic growth of nigeria. european journal of humanities and social sciences, 10(1), 456-471. akintoye, i.r., tashie, g.a. (2013), the effect of tax compliance on economic growth and development in nigeria, west-africa. british journal of arts and social sciences, 11(2), 222-231. anyanwu, j.c. (1993), monetary economics: theory, policy and institutions. onitsha: hybrid publishers. appah, e. (2010), the problems of tax planning and administration in nigeria: the federal and state governments experience. international journal of labour and organisational psychology, 4(1-2), 1-14. ayuba, a.j. (2014), impact of non-oil tax revenue on economic growth: the nigerian perspective. international journal of finance and accounting, 3(5), 303-309. bhartia, h.l. (2009), public finance. 14th ed. new delhi: vikas publishing house pvt ltd. bruno, o.o., emmanuel, a.o. (2019), tax revenue and the nigerian economy. international journal of academic management science research, 3(2), 61-66. bukie, h., adejumo, t.o. (2011), the effects of tax revenue on economic growth in nigeria. international journal of humanities and social science invention, 2(6), 16-26. chigbu, e.e., akujuobi, l.e., appah, e, (2012), an empirical study on causality between economic growth and taxation in nigeria. current research journal of economic theory, 4(2), 29-38. dandago, k.i., alabede, j.o. (2001), taxation and tax administration in nigeria. kano, nigeria: triumph publishing company limited. dwivedi, d.n. (2004), managerial economics. new delhi: vikas publishing house pvt ltd. ewa, u.e., adesola, w.a., essien, e.n. (2020), impact of tax revenue on economic development in nigeria. international business research, 13(6), 1-12. fagbemi, t.o. (2010), an empirical study of the relationship between culture and personal income tax evasion in nigeria. european journal of social sciences, 12(1), 12-32. hadjimichael, f.m., kemeny, t., lanahan, l. (2014), economic development: a definition and model for investment. available from: https://www.edu.gov/tool lewis, c.t., short, c., andrews, e.a., freund, w. (1975), a latin dictionary founded on andrews’ edition of freund’s latin dictionary revised and enlarged edition. oxford: clarendon press. mohammed, j.i., karimu, a., fiador, v.o., abor, j.y. (2020), oil revenues and economic growth in oil-producing countries : the role of domestic financial markets. resources policy, 69, 101832. nzotta, s.m. (2007), tax evasion problems in nigeria: a critique nigeria account. journal of management accounting research, 40(2), 40-44. ogundele, a.e. (1999), elements of taxation. 1st ed. lagos: libri service. ojong, c.m., anthony, o., arikpo, o.f. (2016), the impact of tax revenue on economic growth : evidence from nigeria. iosr journal of economic and finance, 7(1), 32-38. olufemi, a.t., jayeola, o., oladele, a.s., naimot, a.o. (2018), tax revenue and economic growth in nigeria. scholedge international journal of management and development, 5(7), 72-85. olushlola, o.k., oliver, b.u., okon, m.e., osang, o.d. (2020), tax revenue and economic growth in nigeria: an econometric approach. iiard international journal of economic and business management, 6(2), 52-60. the sun nigeria. (2016), diversification of nigeria’s economy urgentbuhari. available from: https://www.sunnewsonline.nigeria’sgdp unegbu, a.o., irefin, d. (2011), impact of vat on economic development of emerging nations. arabian journal of business and management review. 1(9), 15-25. world bank. (2000), east asia: recovery and beyond. washington, d.c: the world bank. world bank. (2013), nigeria economic report (no.1). washington, dc: world bank. yahaya, k.a., yusuf, k. (2019), impact of non-oil tax revenue on economic growth in nigeria. the journal of accounting and management, 9(2), 56-69. . international journal of energy economics and policy | vol 5 • issue 4 • 20151042 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2015, 5(4), 1042-1049. relationships among co2 emissions, economic growth and foreign direct investment and the environmental kuznets curve hypothesis in turkey mesut balıbey* faculty of economics and administrative sciences, tunceli university, tunceli, turkey. *email: mbalibey@tunceli.edu.tr abstract this study examines the causal relationships between economic growth, carbon dioxide emission and foreign direct investment (fdi) and evaluates the environmental kuznets curve (ekc) hypothesis for turkey in 1974-2011. firstly, the causality relationships investigated by using the johansen cointegration test, the granger causality test, impulse-response and variance decomposition analysis of vector autoregression model (var) model. the causality relationships display that fdi (lfdi) and economic growth (lgdp) have a significant effect on carbon dioxide emissions (lco2). moreover, impulse-response functions and variance-decompositions of var model support these relationships among lgdp, lco2 and lfdi. secondly, the study investigates the validity of the ekc hypothesis in turkey for the period 1974-2011 by using regression model approach for the various ekc model forms such as linear, quadratic, and cubic. consequently, economic growth leads to degradation of environment and depletion of natural resources. it must be the major aim to obtain a sustainable economic growth by less co2 emissions and consuming less energy. moreover, the policy makers may take account exogenous impacts such as foreign investments to plan energy policies, and to maintain economic growth against global climate warming. keywords: co2 emission, economic growth, environmental kuznets curve hypothesis, granger causality, johansen cointeration, impulse-response jel classifications: c58, c51, q43, q56 1. introduction environmental pollution and protecting the environment have been one of the most global issues which have the priority in international political agenda. according to the kyoto protocol, countries have taken precautions to preserve the environment. the kyoto protocol adapted in 1997 contains an international strategy to restrict greenhouse gas emissions. the protocol’s main aid is to succeed the reduction in the emissions of greenhouse gases by establishing quantified limitation and reduction obligations to the organization for economic cooperation and development (oecd) member states and east european countries. increasing concentrations of greenhouse gases in the world is accepted as a significant factor affected changing of the climate conditions. because, a small changing in the climate conditions may cause economic losses and natural disasters. greenhouse gas emission reduction affects various sectors in the world economy, such as energy sectors, transport, production processes and industry. increasing economic activity of countries represents the level of energy consumption and carbon dioxide (co2) emissions (kuo et al., 2014; stern, 2004; lieb, 2002). in the 1980s, environmental issues such as global warming, descending biodiversity and ozone layer depletion led to debates about the effects of environmental degradation on economic growth of the world’s countries. therefore, there has been a need to clarify the relationships among economic growth, environmental pollution and other factors. the primary aim of this study is to reexamine the causality relationships between foreign direct investment (fdi), economic growth and carbon dioxide emission (co2) by using johansen cointegration test, the vector autoregression model (var) or vector error correction (vec) model, granger causality test of var or vec model, impulse-response functions and variance decompositions of the model. secondly, the study aims to test the balıbey: relationships among co2 emissions, economic growth and foreign direct investment and the environmental kuznets curve hypothesis in turkey international journal of energy economics and policy | vol 5 • issue 4 • 2015 1043 ekc hypothesis by using ols regression model approach for turkey for the period of 1974-2011. 2. theory and literature review most empirical studies are related to testing of hypothesis namely the ekc. the ekc hypothesis was introduced by grossman and krueger’s (1991) study on environmental effects of the north american free trade aggrement (nafta) in 1990s, and 1992 world bank report. according to the ekc hypothesis, environmental quality or emissions of pollutants are related to economic growth. the ekc hypothesis supports that at the beginning of economic development of the country, environmental degradation will increase until a specific income level “turning point” is reached, and environmental quality will begin to improve as growing income (selden and song, 1994). after the turning point, environmental quality indicators begin to indicate decreases in pollution and environmental degradation. this relationship in some cases means that the environmental impact indicator is an inverted u-shaped curve of income per capita (lieb, 2002; stern, 2004; selden and song, 1994; kuo et al. 2014). a generalized ekc is plotted in figure 1 (yandle, 2002). from figure 1, the ekc hypothesis actually summarizes an essentially dynamic process of change, as income of an economy increases over time, firstly, emission levels increase, reaches a peak point and then starts decreasing after a threshold level (turning point) of income (dinda, 2004). the ekc hypothesis analysis used in the literature is identified by various forms such as linear (1) quadratic (2) and cubic (3) as the follow: y xit it it= + +β β ε0 1 , i=1,2,…n (1) y x xit it it it= + + +β β β ε0 1 2 2 , i=1,2,…n (2) y x x xit it it it it= + + + +β β β β ε0 1 2 2 3 3 , i=1,2,…n (3) where; i=1, 2,…n, countries t=1,…t, time yit=co2 emissions per capita β0=estimated parameters xit=gdp per capita εit=error term the values of the parameters, if the ekc hypothesis is valid, should be, for β1 and β3 positive and for β2 negative. the squared term in model indicates the u-shape behaviour while the cubic term of model explains monotonically rising pollution (n-curves turn). if the cubic term (β3) is insignificant, it can be removed from model (3). if quadratic term (β2) is also not significant in quadratic model (2), model will returns linear form (1). in brief, cubic form produces various results such as a monotonically increasing or decreasing pollution-income relationship, an inverted u-shape (i.e., the ekc), a u-shape, a n-shape (first rising, then falling, and finally rising again), an inverted n-shape or an insignificant (i.e., flat pollution-income relationship) (lieb, 2002; stern, 2004). if β1 is negative and statistically significant but β2 is statistically insignificant, there are indicators that display an certain improvement with rising per capita income. if β1 is positive and statistically significant but β2 is statistically insignificant, these are indicators that indicate an certain deterioration as incomes increase. these consist per capita carbon dioxide emissions (co2). it is possible that these indicators will show the ekc but at much higher per capita turning points. in addition, if β1 is positive and statistically significant and β2 is negative and statistically, the estimated ekc has a maximum turning point per capita income level calculated by y* = (−β1/2β2) (neumayer, 2003; neumayer, 2004). on the other hand, fdi is considered as an important driving force of economic development for countries. in recent years, fdi inflows have raised questions such as if there is a causal relationship between fdi, economic growth and environmental deterioration. therefore, several studies have implemented on the relationships among fdi, economic growth, energy intensity and co2 emissions, and testing of the ekc hypothesis, estimate of the ekc. for example, saidi and hammami (2015) examined the impact of economic growth and co2 emissions on energy consumption for a global panel of 58 countries using dynamic panel data model estimated by means of the generalized method of moments (gmm) for the period 1990-2012. they found that significant positive impact of co2 emissions on energy consumption. leitao (2014) investigated the correlation between economic growth, carbon dioxide emissions, renewable energy and globalization for the period 1970-2010 by using time series methods (ols, gmm, unit root test, vec model and granger causality) for portuguese economy. he found that carbondioxide emissions and renewable energy are positively correlated with economic growth. moghadam and lotfalipour (2014) investigated the impact of financial development on environmental quality in iran by using the auto regression model distributed lag over the period from 1970 to 2011, and they examined short-term and longfigure 1: the environmental kuznets curve balıbey: relationships among co2 emissions, economic growth and foreign direct investment and the environmental kuznets curve hypothesis in turkey international journal of energy economics and policy | vol 5 • issue 4 • 20151044 term relationships among the variables. they found that financial development accelerated the degradation of the environment. omri et al. (2014) investigated the causality relationships between co2 emissions, fdi, and economic growth using dynamic simultaneous-equation panel data models for a global panel of 54 countries over the period 1990-2011. they showed that there was an evidence of bidirectional causality between fdi inflows and economic growth for all countries and between fdi and co2 for all the panels, except europe and north asia. they also indicated that there was unidirectional causality relationship from co2 emissions to economic growth, with the exception of the middle east, north africa, and sub-sahara panel. shaari et al. (2014) examined the effects of fdi and economic growth on co2 emission by using panel data analysis by data the period of 1992 to 2012 from 15 developing countries. they showed a cointegration relationship between variables, and found that fdi didn’t has any effect on co2 emissions. sahinoz and fotourehchi (2014) investigated the relationship between fdi in turkey and co2 emissions for the voladility of pollution haven hypothesis between 1974 and 2011. chen and huang (2013) examined the relationship between carbon dioxide (co2) emission per capita and economic growth in next eleven (n-11) over the period 1981-2009 by using panel unit roots, cointegration in heterogeneous panels and panel causality tests. they presented that there were positive long-run relationship among co2 emissions, electric power consumption, energy use and gdp, and there was a bi-directional causality between co2 emission and electric power consumption. ozturk et al. (2013) examined short-run and long-run relationship and causality between energy consumption and economic growth for the period 1960-2006 in turkey. they employed johansen and juselius cointegration methods and vec model (vecm). the findings of study indicated that there was not short-term causality relationship between energy consumption and gdp, and there was an unidirectional long-run causality from per capita gdp to per capita energy consumption. ozturk and acaravci (2013) investigated the causal relationships between financial development trade, economic growth, energy consumption and carbon emissions in turkey for 1960-2007 period. they indicated that an increase in foreign trade to gdp result, an increase in per capita carbon emissions and financial development variable has no significant effect on per capita carbon emissions in the longrun. shahbaz et al. (2013) investigated relationships between co2 emissions, energy intensity, economic growth and globalization for the period of 1970-2010 in turkey. they used unit root test and cointegration approach in the presence of structural breaks. they displayed that there was a cointegration relationship between the series, and energy intensity and economic growth increased co2 emissions. farhani and rejeb (2012) examined the relationships between ec, gdp and co2 emissions for 15 mena countries by using the panel unit root tests, panel cointegration methods and panel causality test covering the annual period 1973-2008. they found that there was no causality relationship between gdp and ec; and between co2 emissions and ec in the short run. however, in the long run, there was a unidirectional causality relationship from gdp and co2 emissions to ec. ozturk and uddin (2012) investigate the long-run granger causality relationship between energy consumption, carbon dioxide emission and economic growth in india over the period 1971-2007. the most important result is that there is feedback causal relationship between energy consumption and economic growth in india which implies that the level of economic activity and energy consumption mutually influence each other; a high level of economic growth leads to a high level of energy consumption and vice versa. the value of the error correction term confirms the expected convergence process in the long-run for carbon emissions and growth in india which implies that emission reduction policies will hurt economic growth in india if there are no supplementary policies which seek to modify this causal relationship. kaplan et al. (2011) examined the causal relationship between energy consumption and economic growth in turkey for the period 1971-2006. they used demand model and production model based on vector error correction model. the study indicated that energy consumption and economic growth had a cointegration relationship and there was bidirectional causality relationship between energy consumption and economic growth. kim et al. (2010) considered the linkage between carbon dioxide emissions and economic growth in korea. they presented that the causality relationship between carbon dioxide and growth by using granger causality test. choi et al. (2010) investigated the debates over the excistence of the ekc, and used var/vecm models for the period 1971-2006 in china, korea and japan. they found that korea, china and japan showed very different ekc results. ozturk and acaravcı (2010) investigated causal relationships between economic growth, carbon emissions, energy consumption and employment ratio in turkey. they used autoregressive distributed lag bounds testing of cointegration for the period 1968-2005, and presented an evidence of a long-term cointegration relationship between variables. akbostancı et al. (2009) investigated the relationship between environmental quality and income for turkey in 1968-2003 at two levels by using cointegration techniques and pm10 and so2 measurements in turkish provinces. they showed that the results of time series and panel data analyses do not support the ekc hypothesis. soytas and sarı (2009) investigated the long term granger causality relationship between economic growth, carbon dioxide emissions and energy consumption in turkey. they found that the lack of a long term causal relationship between income and emissions could be implying that to reduce carbon emissions. halicioglu (2008) examined empirically dynamic causality relationships between carbon emissions, energy consumption, income, and foreign trade in turkey by using the time series data for the period 1960-2005. the study indicated that income was the most significant variable in explaining the carbon emissions in turkey which is followed by energy consumption and foreign trade. mazzanti et al. (2006) presented new empirical evidence on trends concerning emission-related indicators in italy. they investigated the related ekc literature critically. they used two panel datasets concerning (a) 1990-2000 emissions at province level (b) and sectoral disaggregated namea emissions sources over 19902001 in analysis. the findings of study displayed mixed evidence in support of the ekc hypothesis. they found that it doesn’t exist an ekc dynamic, but many ekc dynamics, differing by period of observation, country/area, emissions/environmental pressures, balıbey: relationships among co2 emissions, economic growth and foreign direct investment and the environmental kuznets curve hypothesis in turkey international journal of energy economics and policy | vol 5 • issue 4 • 2015 1045 sectors. lieb (2002) presented the empirical evidence about that economic growth had been promoted as a method of improving the environment. selden and song (1994) investigated ekcs for four emissions series: so2, co2 etc. they showed that the turning point for emissions was to be higher than that for ambient concentrations. grossman and krueger (1991) estimated ekcs for so2 dark matter (fine smoke), and suspended particles using the gems data set. they found that the turning points for sulfur oxide (so2) and dark matter were at around $4000-5000. 3. empirical analysis 3.1. preliminary analysis of data this study considers time series data set of the world bank database. the yearly data consists of fdi, gdp per capita used as a proxy of economic growth and co2 emissions (metric tons per capita) for the sample period from 1974 to 2011. all variables were transformed into logarithms namely lco2, lfdi and lgdp. all empirical tests had been carried out by using the eviews-8. the time series of co2, fdi and gdp are presented in figure 2. from figure 2, it has been seen that all variables are nonstationary. stationary series can be described as one series with a constant mean, constant variance and constant autocovariance for each lag during time1. the augmented dickey fuller (adf) test, phillipsperron (pp) test and kwiatkowski-phillips-schmidt-shin (kpss) test are used to determine the stationary of time series of lco2, lfdi, lgdp. table 1 presents the results of the adf test, pp test and kpss test. according to table 1, the results of the stationary tests indicate that all variables are stationary at first level in adf, pp and kpss tests. in other words, all variables are integrated of order one i (1). 3.2. the johansen cointegration test, the granger causality test of the var/vec model, impulseresponse functions and variance-decompositions because the variables are integrated with order i (1), it is tested whether there is a long term relationship among these variables by using the johansen cointegration test. if cointegration relationship exists among lco2, lfdi and lgdp, vecm approach will be used to determine long term relationships among variables. since the results of the johansen cointegration analysis depend on the lags of the model, prior to the cointegration test, the lag order selection criteria for standard var are presented in table 2. according to table 2, one lag lenght is more appropriate for the model. in the vec model, all variables are endogenous, and the equation of vecm system is specified as follows: y l y yt t t= + +ϕ δ ε( ) / (1) where, y=(co2t, fdit, gdpt), φ(l) is the coefficient matrices for lag operators l, and δ is the cointegrating vectors capturing 1 after being differentiated once is said to be integrated of order 1. it has been showed by i (1). in table 1, variables integrated of order i (1) are presented by d (.). the long-run relationships among the variables in the system. in addition, the results of the johansen cointegration analysis with one lag order are indicated in table 3. from table 3, the results display the rejection of null hypothesis that there isn’t any cointegration relationship between variables, and there is only a cointegration equation according to trace and maximum eigenvalue statistics at 5% significant level. according to the results of vec (1) granger causality in table 4, there does not exist any causality relationship between lco2, lfdi and lgdp. carbondioxide emissions, fdi and economic growth are not related in long term. furthermore, var granger causality test is applied also, and the results are displayed in table 5. from table 5; it can be said that there is bidirectional causality relationship from fdi (lfdi) to carbon emissions (co2) at 5% figure 2: co2 emissions, foreign direct investment and gdp balıbey: relationships among co2 emissions, economic growth and foreign direct investment and the environmental kuznets curve hypothesis in turkey international journal of energy economics and policy | vol 5 • issue 4 • 20151046 significant level. similarly, there is a unidirectional causality relationship from lgdp to lco2. the causality relationships displays that fdi (lfdi) and economic growth (lgdp) have a significant effect on carbon dioxide emissions (lco2). in addition, both lco2 and lgdp have a significant causal effect on lfdi at 5% significant level. however, both fdi (lfdi) and carbon dioxide emissions (lco2) do not have any causal effect on economic growth (lgdp). accordingly, the impulse-response functions of impact of variables by one standard deviation shock on each other are plotted for ten quarter horizon in figure 3 for var (1) model. the impulse-response functions of impact of variables by one standard deviation shock on each other are plotted for ten quarter horizon in figure 3 for var (1) model. it can be seen from these figures that one standard deviation shock in fdi (lfdi) has a positive significant impact on carbon dioxide emission (lco2), and that one standard deviation shock in economic growth (lgdp) has a negative minor effect on carbon dioxide emission (lco2). moreover, one standard deviation shock in economic growth (lgdp) and carbon dioxide emission (lco2) have a positive significant effect on fdi (lfdi). furthermore, the variance decomposition results of var (1) model are presented in table 6. according to table 6, the variance decomposition results indicate %100 of lco2 variance can be expained by current lco2 in the first period, and the percentage is continuing at the end of the tenth periods by 84.16%. at the end of the tenth periods, fdi (lfdi) and economic growth (lgdp) affect the variation in the forecast error of carbon emissions (lco2) by 15.80% and 0.03% respectively. the variance decompositions of fdi at the end of the tenth periods display that 49.87% of lfdi variance can be explained by current lfdi. in addition lco2 significantly contributes by 48.77% to variance of lfdi. however, the contribution of lgdp to lfdi variance is only 1.36% level. furthermore, the variance decompositions of economic growth (lgdp) present that 44.71% of the forecast error variance of table 1: the results of unit root tests tests lco2 dlco2 lfdi dlfdi lgdp dlgdp adf –0.623087 –5.839374* –0.755011 –8.637102* 0.093386 –5.857395* pp –0.549143 –6.080549* –0.222207 –9.399018* 0.295239 –5.854142* kpss 0.733171 0.081123* 0.697916 0.354492* 0.734588 0.080526* *indicates the refusal of unit root null hypothesis in the significance level at %5. (mckinnon critical value is [–2.943427], kwiatkowski critical value is [0.463000]), adf: augmented dickey fuller, pp: phillips-perron, kpss: kwiatkowski-phillips-schmidt-shin, lco2: carbon dioxide emissions, fdi: foreign direct investment, gdp: gross domestic product table 2: the results of unit root tests lag logl lr fpe aic sc hq 0 27.36402 na 4.99e-05 –1.392230 –1.258914 –1.346209 1 107.5922 142.1184* 8.54e-07* –5.462410* –4.929148* –5.278328* 2 110.8422 5.200052 1.20e-06 –5.133841 –4.200632 –4.811697 3 112.3751 2.189841 1.90e-06 –4.707149 –3.373993 –4.246943 *indicates lag order selected by the criterion, lr: sequential modified lr test statistic (each test at 5% level), fpe: final prediction error, aic: akaike information criterion, sc: schwarz information criterion, hq: hannan-quinn information criterion table 3: the results of johansen cointegration test hypothesis variables: lco2, lfdi, lgdp null alternative eigenvalue trace statistic critical value 5% p-value r=0 r=1 0.435306 29.62094* 24.27596 0.0097 r≤1 r≥2 0.192720 9.047993 12.32090 0.1663 r≤2 r≥3 0.036563 1.340953 4.129906 0.2887 r=0 r=1 0.435306 20.57294* 17.79730 0.0186 r≤1 r≥2 0.192720 7.707039 11.22480 0.1941 r≤2 r≥3 0.036563 1.340953 4.129906 0.2887 *r value indicates the number of cointegrating vectors. (*) indicates rejection at the 5% critical value, lco2: carbon dioxide emissions, fdi: foreign direct investment, gdp: gross domestic product table 4: vec granger causality/block exogeneity wald tests excluded chi-square df probability dependent variable: d (lco2) d (lfdi) 2.184325 1 0.1394 d (lgdp) 0.230166 1 0.6314 all 2.212405 2 0.3308 dependent variable: d (lfdi) d (lco2) 0.069318 1 0.7923 d (lgdp) 0.150732 1 0.6978 all 0.151145 2 0.9272 dependent variable: d (lgdp) d (lco2) 1.766753 1 0.1838 d (lfdi) 0.316883 1 0.5735 all 2.382403 2 0.3039 vec: vector error correction, lco2: carbon dioxide emissions, fdi: foreign direct investment, gdp: gross domestic product table 5: var granger causality/block exogeneity wald tests excluded chi-square df probability dependent variable: lco2 lfdi 4.223234 1 0.0399 lgdp 2.979391 1 0.0843 all 6.731664 2 0.0345 dependent variable: lfdi lco2 14.78222 1 0.0001 lgdp 15.67529 1 0.0001 all 17.18603 2 0.0002 dependent variable: lgdp lco2 0.824190 1 0.3640 lfdi 1.242881 1 0.2649 all 1.263442 2 0.5317 var: vector autoregression model, lco2: carbon dioxide emissions, fdi: foreign direct investment, gdp: gross domestic product balıbey: relationships among co2 emissions, economic growth and foreign direct investment and the environmental kuznets curve hypothesis in turkey international journal of energy economics and policy | vol 5 • issue 4 • 2015 1047 economic growth (lgdp) is explained by current economic growth (lgdp) at the end of the tenth periods. in addition, lco2 and lfdi contribute at 47.57% and 7.72% levels for variance of economic growth (lgdp) respectively. 3.3. statistical model estimation for testing of the ekc hypothesis as mentioned earlier, the ekc hypothesis explains an inverted u-shaped relationship between economic growth (gdp) and environmental quality (co2). in econometric analysis, this relationship could be described as quadratic form. there is also a possibility that this relationship would be a linear relationship, if economic growth (gdp) is proportional to carbon dioxide emission (co2), or, that this relationship takes a cubic form in econometrics namely the n-shaped curve relationship. for this purpose, to evaluate if the two variables actually have the these forms of relationship described in literature, a statistical regression analysis by least square method can be performed. finally, it will also help to determine whether the relationship between economic growth (gdp) and carbon dioxide emission (co2) is statistically significant in different forms. the results of the three models for ekc hypothesis are presented in table 7. all model parameters display the results to be statistically significant at 5% level. the ekc emissions reversal at higher incomes is clearly present in the data, with appropriate signs on the model coefficients. firstly, the quadratic term (lgdp2) of quadratic model is negative and statistically significant at 5% level, and the linear term (lgdp) is positive and statistically significant also. in this case, the estimated the ekc has a maximum turning point per capita income level calculated as lgdp* = (−lgdp/2lgdp2) = (12.72614/2[–0.674319])= –4,290739 (neumayer, 2003; neumayer, 2004). in cubic model, the cubic term (lgdp3) is also statistically significant and positive, indicating an n-shaped curve. this would indicate that emissions would begin to rise again once a second income turning point is passed. the estimated models have r-squares (r2) values above 0.95. the results suggest a strong inverted u-shaped relation between carbon emissions (co2) and economic growth (gdp). in the cubic model, the parameters are also statistically significant, indicating an n-shaped relation. both an inverted-u shaped and an n-shaped ekc mean that a higher income level and a faster economic development lead to a clearer display of the trend in pollution-income relations (yang et al., 2010). 4. conclusion and remarks this study aims to investigate the causal relationships between economic growth, carbon dioxide emission and fdi, and to evaluate the ekc hypothesis for turkey in 1974-2011. firstly, the causality relationships between the variables are examined by econometric methods. for this purpose, the methodology used in the study includes unit root tests based on adf, pp and kwiatkowski-phillips-schmidt-shin (kpss) tests, the johansen cointegration test, the granger causality test in a var, impulseresponse and variance decomposition analysis of var model. the findings obtained display that a long term relationship exists among economic growth (gdp), carbon dioxide emission (co2) and fdi. table 6: the variance decompositions of var (1) model period se lco2 lfdi lgdp variance decomposition of lco2 1 0.049812 100.0000 0.000000 0.000000 2 0.067372 95.06175 4.914045 0.024200 3 0.080913 91.29985 8.661361 0.038790 4 0.092300 88.92124 11.03400 0.044763 5 0.102252 87.37725 12.57668 0.046072 6 0.111156 86.31758 13.63741 0.045003 7 0.119250 85.55172 14.40553 0.042753 8 0.126694 84.97439 14.98564 0.039971 9 0.133599 84.52444 15.43853 0.037033 10 0.140049 84.16432 15.80152 0.034167 variance decomposition of lfdi 1 0.651444 0.667665 99.33233 0.000000 2 0.736822 9.418898 90.39904 0.182067 3 0.799867 18.61078 80.98436 0.404859 4 0.856808 26.14138 73.25572 0.602897 5 0.909618 32.08342 67.14539 0.771188 6 0.959077 36.81708 62.26700 0.915917 7 1.005704 40.65849 58.29836 1.043154 8 1.049892 43.83291 55.00969 1.157402 9 1.091949 46.49817 52.23999 1.261850 10 1.132125 48.76651 49.87472 1.358776 variance decomposition of lgdp 1 0.044006 53.02676 0.428369 46.54487 2 0.061442 50.17797 2.887877 46.93416 3 0.075042 48.69788 4.490782 46.81134 4 0.086702 47.94562 5.490560 46.56382 5 0.097135 47.57014 6.154891 46.27496 6 0.106705 47.40127 6.629428 45.96930 7 0.115628 47.35372 6.989880 45.65640 8 0.124045 47.38191 7.277282 45.34081 9 0.132055 47.45977 7.515243 45.02499 10 0.139727 47.57142 7.718161 44.71042 se: standard error, var: vector auto regression, lco2: carbon dioxide emissions, fdi: foreign direct investment, gdp: gross domestic product figure 3: (a and b) the impulse-response functions of vector autoregression (1) model b a balıbey: relationships among co2 emissions, economic growth and foreign direct investment and the environmental kuznets curve hypothesis in turkey international journal of energy economics and policy | vol 5 • issue 4 • 20151048 the results of the granger causality test of vec model display that any causality relationship does not exist in long run while the results of the granger causality test of var model support that there is bidirectional causality relationship from fdi (lfdi) to carbon emissions (co2) at 5% significant level. in addition, there is a unidirectional causality relationship from economic growth (lgdp) to carbon dioxide emissions (lco2). in brief, the causality relationships show that fdi (lfdi) and economic growth (lgdp) have a significant effect on carbon dioxide emissions (lco2). in addition, both lco2 and lgdp have a significant causal effect on lfdi. moreover, impulse-response functions and variance-decompositions of var model support these relationsips among lgdp, lco2 and lfdi. carbon dioxide emission (co2) contributes for the variation in the forecast error of all other variables. furthermore, fdi significantly affects variance of carbon dioxide emission (co2). according to impulse-response functions, the shocks in foreign direct investment (lfdi) have a positive significant impact on carbon dioxide emission (lco2) while the shocks in economic growth (lgdp) have a negative minor effect on carbon dioxide emission (lco2). moreover, one standard deviation shock in economic growth (lgdp) and carbon dioxide emission (lco2) have a positive significant effect on foreign direct investment (lfdi). the findings indicate that in the long run foreign direct investment has an effect on co2 emission. therefore, any increase in fdi have cause any problem to the environment. an increase in economic growth is negatively related with the environment as it can contribute for decreasing of co2 emissions. the findings are very important in the environmental policies. therefore, the countries should find the alternative energy such as natural gas that there is no effect on the environment. secondly, the study examined the validity of ekc hypothesis in turkey for the period 1974-2011 by using regression model approach. for this purpose, the various ekc model forms such as linear, quadratic, and cubic are estimated. all parameters of the three models for ekc hypothesis are statistically significant at 5% level. the ekc emissions reversal at higher incomes is clearly present in the data, with appropriate signs on the model coefficients. firstly, the quadratic term (lgdp2) of quadratic model is negative and statistically significant at 5% level, and the linear term (lgdp) is positive and statistically significant also. in this case, the estimated the ekc has a maximum turning point per capita income level. in cubic model, the cubic term (lgdp3) is also statistically significant and positive, indicating an n-shaped curve. that means that emissions would begin to rise again once a second income turning point is passed. consequently, economic growth leads to degradation of environment and depletion of natural resources despite increasing life quality. the findings are significant in the environmental policies. therefore, it must be the major aim to obtain a sustainable economic growth by less co2 emissions and consuming less energy. furthermore, the policy makers may take account exogenous impacts such as foreign investments to plan energy policies, and to maintain economic growth for global climate warming. references akbostancı, e., türüt-aşık, s., tunç, g.i̇. (2009), the relationship between income and environment in turkey: is there an environmental kuznets curve?. energy policy, 37(3), 861-867. chen, j.h., huang, y.f. (2013), the study of the relationship between carbon dioxide (co2) emission and economic growth. journal of international and global economic studies, 6(2), 45-61. choi, e., heshmati, a., cho, y. (2010), an empirical study of the relationships between co2 emissions, economic growth and openness. iza discussion paper, 5304, 1-27. dinda, s. (2004), environmental kuznets curve hypothesis: a survey. ecological economics, 49, 431-455. farhani, s., rejeb, j.b. (2012), energy consumption, economic growth and co2 emissions: evidence from panel data for mena region. international journal of energy economics and policy, 2(2), 71-81. grossman, g.m., krueger, a.b. (1991), environmental impacts of a north american free trade agreement. national bureau of economic research working paper, 3914. cambridge, ma: nber. halicioglu, f. (2008), an econometric study of co2 emissions, energy consumption, income and foreign trade in turkey. energy policy, 37, 1156-1164. kaplan, m., ozturk, i., kalyoncu, h. (2011), energy consumption and economic growth in turkey: cointegration and causality analysis. romanian journal of economic forecasting, 2(31), 31-41. kim, s.w., lee, k., nam, k. (2010), the relationship between co2 emissions and economic growth: the case of korea with nonlinear evidence. energy policy, 38, 5938-5946. kuo, c.k., kanyasathaporn, p., lai, s. (2014), the causal relationship between gdp, energy consumption and co2 emissions in hong kong. production research journal, 46-47(3), 127-138. leitao, n.c. (2014), economic growth, carbon dioxide emissions, renewable energy and globalization. international journal of energy economics and policy, 4(3), 391-399. lieb, c.m. (2002), the environmental kuznets curve: a survey of the empirical evidence and of possible causes. university of heidelberg department of economics discussion paper series, 391, 1-60. table 7: the estimations of regression models dependent variable: lco2 independent variables linear model coefficients quadratic model coefficients cubic model coefficients c (constant) –8.854106** (0.286932) [0.0000] –58.49850** (7.040325) [0.0000] –10.6747** (281.2797) [0.0163] lgdp 1.149412** (0.033515) [0.0000] 12.72614** (1.641321) [0.0000] 240.4722** (98.21036) [0.0197] lgdp2 –0.674319** (0.095595) [0.0000] –27.17071** (11.42491) [0.0232] lgdp3 1.027006 (0.442818) [0.0265] r2 0.970301 0.987736 0.989411 adjusted r2 0.969476 0.987035 0.988477 f-statistic 1176.149 1409.432 1058.971 prob (f-statistic) 0.000000 0.000000 0.000000 **indicates statistically significant at level 5%, ( ) indicates standard error, [ ] indicates p-values, lco2: carbon dioxide emissions, fdi: foreign direct investment, gdp: gross domestic product balıbey: relationships among co2 emissions, economic growth and foreign direct investment and the environmental kuznets curve hypothesis in turkey international journal of energy economics and policy | vol 5 • issue 4 • 2015 1049 mazzanti, m., montini, a., zoboli, r. (2006), economic dynamics, emission trends and the ekc hypothesis new evidence using namea and provincial panel data for italy. universita degli studi di ferrara. p1-36. moghadam, h.e., lotfalipour, m.r. (2014), impact of financial development on the environmental quality in iran. chinese business review, 13(9), 537-551. neumayer, e. (2003), are left-wing party strength and corporatism good for the environment? a panel analysis of 21 oecd countries, 19801998. ecological economics, 45(2), 203-220. neumayer, e. (2004), national carbon dioxide emissions: geography matters. area, 36(1), 33-40. omri, a., nguyen, d.k., rault, c. (2014), causal interactions between co2 emissions, fdi, and economic growth: evidence from dynamic simultaneous-equation models. economic modelling, 42, 382-389. ozturk, i., acaravci, a. (2010), co2 emissions, energy consumption and economic growth in turkey. renewable and sustainable energy reviews, 14(9), 3220-3225. ozturk, i., uddin, g.s. (2012), causality among carbon emissions, energy consumption and growth in india. economic research, 25(3), 752-775. ozturk, i., kaplan, m., kalyoncu, h. (2013), the causal relationship between energy consumption and gdp in turkey. energy and environment, 24(5), 727-734. ozturk, i., acaravci, a. (2013), the long-run and causal analysis of energy, growth, openness and financial development on carbon emissions in turkey. energy economics, 36, 262-267. saidi, k., hammami, s. (2015), the impact of co2 emissions and economic growth on energy consumption in 58 countries. energy reports, 1, 62-70. selden, t.m., song, d. (1994), environmental quality and development: is there a kuznets curve for air pollution? journal of environmental economics and management, 27, 147-162. soytas, u., sari, r. (2009), energy consumption, economic growth, and carbon emissions: challenges faced by an eu candidate member. ecological economics, 68(6), 1667-1675. sahinoz, a., fotourehchi, z. (2014), foreign direct investments and pollution emissions: “pollution haven hypothesis” test for turkey. socio-economy, 1, 187-210. shaari, m.s., hussain, n.e., abdullah, h., kamil, s. (2014), relationship among foreign direct ınvestment, economic growth and co2 emission: a panel data analysis. international journal of energy economics and policy, 4(4), 706-715. shahbaz, m., ozturk, i., afza, t., ali, a. (2013), revisiting the environmental kuznets curve in a global economy. renewable and sustainable energy reviews, 25, 494-502. stern, d.i. (2004), the rise and fall of the environmental kuznets curve. world development, 32(8), 1419-1439. yandle, b., vijayaraghavan, m., bhattarai, m. (2002), the environmental kuznets curve. perc research study, 02-1, 1-24. yang, h., zhou, y., abbaspour, k.c. (2010), an analysis of economic growth and ındustrial wastewater pollution relations in china. consilience the journal of sustainable development, 4(1), 60-79. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 3 • 2023384 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(3), 384-395. managing electricity consumption on campus: the effect of online learning from home vera pujani1, fajril akbar2, refdinal nazir3* 1department of management, universitas andalas, padang 25162, indonesia, 2department of information system, universitas andalas, padang 25162, indonesia, 3department of electrical engineering, universitas andalas, padang 25162, indonesia. *email: refdinalnazir@eng.unand.ac.id received: 07 january 2023 accepted: 23 april 2023 doi: https://doi.org/10.32479/ijeep.14147 abstract this paper analyzes the effect of online learning from home (olfh) during the covid-19 pandemic on electricity consumption and the quality of the learning process quality. this study identifies the reduction of electricity consumption on campus during olfh, which can be utilized to maintain the quality of the learning process. the electricity consumption data was analyzed from the direct measurement using the electricity consumption realtime monitoring system. again, the data analyzed of the online learning process quality was obtained from the student survey via google forms. the results of monitoring electricity consumption before and during olfh showed that the most significant decrease in electricity consumption occurred in classroom buildings, with a decrease value of 68.74%. meanwhile, the lowest reduction of electricity consumption occurred in the rectorate building, with its reduced value of 19.02%. a student survey showed that most respondents were satisfied with the transition from face-to-face learning to olfh during the covid-19 pandemic. however, this study also identified negative aspects of olfh. reducing electricity consumption during olfh will cost saving for the university. the cost saving can be used to implement programs to address the deficiencies of olfh and improve its infrastructure so that the quality of the learning process is maintained. keywords: electricity consumption, covid-19, online learning from home, campus building, electricity consumption monitoring system jel classifications:  m150, o320, o440 1. introduction the covid-19 outbreak at the end of 2019 in wuhan, china, the coronavirus has spread to 230 countries worldwide. more than 600 million people are infected, and 6.5 million are dying because of the virus (worldometer, 2021). however, the spread of its plague has begun to be controlled today. thanks to the vigorous vaccination efforts carried out by countries worldwide. however, the heavy burden felt while fighting against the covid-19 outbreak has still not been erased from people’s minds. the covid-19 pandemic has harmed almost all sectors of human life, especially the productive sector, such as the industrial sector, the tourism sector, the trade sector, the infrastructure sector, the transportation sector, etc. growth in these sectors will result in a decline in economic development. on the other hand, the pandemic has also decreased world energy demand and reduced energy consumption in all productive sectors(jiang et al., 2021; tamilselvan et al., 2022). in general, during the covid-19 pandemic, businesses will experience a decline in production, leading to a decrease in energy consumption. it also dropped the number of tourist visits in the tourism sector due to travel restriction policies in almost all countries, both domestic and foreign tourism. a decrease in the number of tours will impact a decline in the number of flight routes, land and sea transportation routes, and the number of guest this journal is licensed under a creative commons attribution 4.0 international license pujani, et al.: managing electricity consumption on campus: the effect of online learning from home international journal of energy economics and policy | vol 13 • issue 3 • 2023 385 visits to hotels. the condition will lead to a decrease in energy demand in this sector. it also occurred in the industrial sector due to the decline in economic growth during the covid-19 pandemic, which caused a decrease in market demand for goods from industrial products. a drop will follow the reduction in industrial products in energy demand. in contrast with the business industry, some countries’ educational activities were still running during the covid-19 pandemic. however, in several countries, learning activities had to be stopped altogether. most educational institutions control the spread of the covid-19 pandemic by shifting the face-to-face learning process to online learning from home (olfh). in other words, the education sector continues its business despite the questionable process quality. however, some institutions do not have internet facilities, especially in developing countries, stopping all learning activities from controlling the spread of covid-19 (andrei et al., 2021). the scope of study in this article is focused on universities switching from face-to-face learning to olfh to control the spread of covid-19 on a university campus. in terms of electricity consumption during olfh, there will be a shift in the need for electrical energy from university buildings to homes, as discussed in the literature (andrei et al., 2021; kawka and cetin, 2021). the amount of consumption in educational institution buildings will decrease, while in homes, there will be an increase in energy consumption. this article analyzes the effect of olfh during the covid-19 pandemic on electricity consumption and the quality of the learning process in the university. the electricity consumption data, before and during oflh, was obtained from the direct measurements of the electricity consumption real-time monitoring system. at the same time, the data for learning process quality were collected from an online survey of 149 students. in this study, several programs are formulated to stimulate olfh to maintain the quality of the learning process at the university. as the object of study, universitas andalas campus in padang, indonesia, was chosen. 2. literature review in general, the educational institution’s response when the covid-19 pandemic occurred was to switch from face-to-face lectures to olfh (apec, 2021). the change was not too difficult to implement for an institution that has already implemented online learning as e-learning or blended learning. in contrast with the universities that already have information technology (it) facilities but have not utilized them for online learning processes, it will require a lot of funds and human resources to develop online learning systems quickly. it cannot be carried out for universities that do not provide it facilities. some campuses have disrupted all campus academic activities during the covid-19 pandemic. in most developing countries, all students cannot reach distance learning due to limitations in internet access, especially in remote areas (kawka and cetin, 2021). in addition, the inability to have electronic equipment/gadgets/digital devices for conducting online lectures and poor internet connections, it facilities, online teaching materials, and it skills make it difficult for lecturers and students to implement online learning. another way to implement the learning process during the covid-19 pandemic is diverting face-to-face lectures to one-way lectures via radio and television (tadesse and muluye, 2020). however, many low-income families still do not have radio, television, and other devices to access learning resources from their homes, so the learning process cannot be carried out effectively. in addition, to help low-income families, governments in several developing countries have made zero-fee policies on internet educational resources, free online learning resources, and broadcast teaching. 2.1. the electricity consumption patterns in campus buildings the electricity consumption on campus depends on the electrical equipment used and activities requiring electricity (pujani et al., 2019). electrical equipment used in campus buildings can be grouped into cooling and/or heating, lighting, computer equipment, laboratory equipment, and other equipment. air conditioning (ac) is only needed for campus buildings in the tropics, whereas air cooling and heating are required for areas with four seasons. in general, the buildings on campus, based on user activities, can be distinguished into central library buildings, department/faculty buildings, rectorate buildings, student dormitory buildings, sports buildings, and buildings for other purposes. electrical equipment and user activities carried out in each campus building will determine the electricity consumption pattern in each building. each campus building will have different types of electrical equipment installed and electricity consumption patterns. for example, the department building where practicum activities, lecturer academic activities, and administrative activities happen is equipped with the dominant electrical equipment, such as lights, air conditioners, computers, laboratory equipment, and other electrical equipment. meanwhile, the central library building only has electrical equipment for reading activities and seminars, such as air conditioners, lights, and other electrical equipment. the impact of the covid-19 pandemic on electricity consumption patterns in campus buildings is strongly influenced because there is a change in activity patterns that usually occur in that buildings. the consumption pattern in lecture buildings sharply drops when the online learning process is at home. it happened because almost all learning activities moved from campus to home. meanwhile, the electricity consumption pattern in the rectorate building may not experience a significant decrease because administrative and management activities must continue during the covid-19 pandemic. indifferent when a total lockdown is implemented on campus. in general, the electricity consumption pattern in campus buildings during covid-19 is determined mainly by changes in activity patterns in each building. according to a study (kawka and cetin, 2021), in the united states, during the covid-19 pandemic, there was a shift in pujani, et al.: managing electricity consumption on campus: the effect of online learning from home international journal of energy economics and policy | vol 13 • issue 3 • 2023386 electricity consumption from business buildings, campuses, or offices to residential buildings. it happened because, during the covid-19 pandemic, the house was used as a temporary office, lecture hall, restaurant, and entertainment center. thus, the consumption pattern of campus buildings will tend to decrease during a pandemic. in contrast, the electricity consumption pattern in lecturers’ and students’ homes will tend to increase (andrei et al., 2021). the percentage decrease in electricity consumption in university buildings and the percentage increase in the homes of lecturers and students is proportional to the decline and growth in the use of computers in the university and households, respectively. on the other hand, online learning from home can reduce energy consumption for round-trip transportation of the academic community from home to campus. 2.2. impact of covid-19 pandemic on education funding regarding education financing, covid-19 has significantly impacted university finances (jiang et al., 2021). this business activity relies heavily on tuition fees from domestic and international students to fund learning activities, including research. as more domestic and international students choose to take time off during the pandemic, university revenues have fallen. in contrast, expenses have increased due to the expansion of investments in online education systems to costs associated with disinfecting campus facilities. however, transferring the learning process from face-to-face to online learning at home is an attractive solution for students to continue attending lectures comfortably during the covid-19 pandemic so that the student’s movement can be reduced. in some universities that have started partial online courses or blended learning, investment development in online learning infrastructure is not very significant. meanwhile, university costs will also decrease due to reduced electricity consumption because of online learning. from the perspective of students and lecturers, some argue that the online learning system is a cheap learning model in terms of transportation and accommodation costs (tamilselvan et al., 2022). students do not need accommodation costs near campus because all learning activities have moved to their homes. likewise, transportation costs for lecturers and students will decrease drastically because the frequency of trips from home to campus is minimal during the covid-19 pandemic. however, the financing of electricity and internet bills in the homes of students and lecturers will increase. 2.3. the quality of olfh processes at universities radu et al. (2020) from vasile alecsandri university of bacau, romania, have conducted a study through a survey regarding the impact of the covid-19 pandemic on the quality of the learning process in the faculty of engineering and the faculty of physical education and sports. the survey results showed that most students were satisfied with switching from face-toface to online learning during the lockdown period. however, this study also identified negative aspects of online learning during the covid-19 pandemic. it includes a lack of adequate infrastructure for some students, a lack of effective communication and interaction between students and lecturers, an impossible practical application, and a lack of motivation to learn. it also declared that the opportunity to cheat in exams is relatively high, the tendency to decrease physical and mental health, and sedentary lifestyle patterns. according to (maatuk et al., 2022), students believe that e-learning can positively contribute to their learning during the covid-19 pandemic. however, it can reduce the workload on the faculty and increase the course load on students. the main obstacle to e-learning was the low quality of public internet services during the pandemic. faculty members agreed that e-learning helped enhance students’ computer skills, although it required significant investment development costs. universities must provide internet services for students and lecturers with sufficient computer hardware to implement e-learning. a modern electronic library and dedicated classrooms with all necessary equipment and tools are also required to implement e-learning instead of coming to the main campus. holding regular online training and seminars is very important for lecturers to support the implementation of e-learning. 2.4. the online learning infrastructure universitas andalas developed the e-learning system before the covid-19 pandemic as a learning support facility. it was built using moodle™ with hardware installed and configured in the data center on the limau manis campus. the architecture of the existing elearning system can be seen in figure 1. the elearning server is located at limau manis main campus with dedicated internet access. meanwhile, students access elearning using their internet access. server hardware is provided by the campus data center located at universitas andalas campus, indonesia. with 15 faculties and 1 postgraduate program, they provide four servers with a capacity of 2 cpu cores, 4 gb ram, and 200 gb storage to serve campus e-learning services. different things happened during the pandemic. at that time, universitas andalas had to upgrade their server hardware to 10 servers with 500 gb storage capacity each, including practicum. it is in line with the olfh policy implemented by the government for all educational institutions. figure 2 shows the traffic usage of one of the existing e-learning servers. it showed a significant increase from july, with total traffic of 1 gb to 15 gb in august 2019. it was affected by olfh policy during that month. figure 1: e-learning system at universitas andalas pujani, et al.: managing electricity consumption on campus: the effect of online learning from home international journal of energy economics and policy | vol 13 • issue 3 • 2023 387 3. methods 3.1. real-time electricity consumption monitoring system a real-time monitoring system for electricity consumption has been investigated and developed since 2019 on several samples of buildings that are the object of study. the system is built with a client/server architecture using web technology as an interaction between application users and the system. figure 3 shows the energy monitoring system’s architecture, consisting of 3 parts: the client, servers, and sensors. with web-based applications connected to the internet, application users can access applications from computers or mobile devices that support web communication. energy data is taken from sensors in 4 functionally different buildings: lecture, library, faculty, and rectorate. the server section consists of 3 servers. a web server that serves web service requests from users and processes data stored at the database server. the database server provides the data of sensor readings and data that the web will publish. meanwhile, the simple network management protocol (snmp) server will serve the needs of sending data from each sensor. the communication process between the snmp server and the power meter as a sensor device can be seen in figure 4. the communication between the snmp server and the power meter uses one of the snmp protocols, a protocol in the application layer in the osi model. as a protocol that is widely used for monitoring needs, one of the communication modes used is the snmp poll mode. as shown in figure 4, in snmp poll mode, the snmp manager will send a “get request” code to the snmp agent located on the power meter. it will be replied to with “get response” code from the snmp agent. every snmp poll is equipped with an object id (oid) to ensure that the data sent is as required. all requested oids are registered in the same management information base (mib) in snmp manager and snmp agent. the snmp poll process will be conducted every 5 minutes. the web application that is built is the implementation of the php language that is integrated with the laravel® framework. with the support of mysql® as database management, every data obtained is stored in the database and used for web application (dashboard) needs. for graphic visualization, canvasjs® is used, and adminlte® is used to display a more interactive application that is integrated with the laravel® framework. in addition, the database is also processed to issue information on energy and other variables per day. 3.2. student survey the survey’s primary purpose is to determine students’ perceptions of the effects of online lectures during the covid-19 pandemic on financing, infrastructure readiness, and the quality of the learning process quality. the survey was conducted using a student sample of 149 students, consisting of 108 students (72.5%) from the electrical engineering department, 21 students (14.1%) from the management department, and 20 students (13.4%) from the information systems department. the number of samples was dominated by undergraduate students, as many as 137 students (91.9%), while the master’s program students were only 12 respondents (8.1%). the student survey was carried out in march 2022. the survey was conducted using the google forms platform. the questions in the survey are grouped into three categories. the first category of questions focused on knowing the c o n d i t i o n o f s t u d e n t f i n a n c i n g d u r i n g o n l i n e l e c t u r e s consisted of 6 questions. the second category focused on the condition of the infrastructure supporting online lectures, which included five questions. meanwhile, the third category contains questions regarding the quality of the learning process during online lectures, which consist of 10 questions. based on 21 questions in the survey would give an overview of the quality of olfh and the external factors that impact it. the questions were inspired by the literature of katić et al. (2021) and radu et al. (2020). 4. results and discussion 4.1. the impact of olfh and owfh on campus electricity consumption the results of electricity consumption data were analyzed by dividing it into four different types of campus buildings with different purposes. it compares the data before and during olfh. a recording was carried out from august 2019 to february 2020, defined as before the pandemic. it also defines august 2020 to february 2021 as during the pandemic. the duration of recording and analysis is adjusted in odd semesters of academic activities (andalas, 2019, 2020). meanwhile, the type of buildings sampled as objects of study is very significant in contributing to the total energy consumption of the campus. in addition, each building provides a different role from one another in carrying out academic activities. a sample of 4 groups of these buildings can represent the fundamental role of figure 2: e-learning of engineering faculty’s server traffic usage during 2019 pujani, et al.: managing electricity consumption on campus: the effect of online learning from home international journal of energy economics and policy | vol 13 • issue 3 • 2023388 the campus in organizing educational activities. the buildings sampled in this study are the dean’s office of engineering faculty, the classroom, the central library, and the rectorate building. in the next section, we will try to highlight the impact of each building. 4.1.1. impact on faculty engineering buildings the faculty engineering buildings consist of department and dean buildings. activities carried out in department buildings are lab sessions, research, lectures with a limited audience, and other supporting academic activities. figure 5 shows the results of a comparative analysis of electricity consumption before and during the covid-19 pandemic on the odd semester. a comparison of weekly electrical energy consumption from faculty buildings is shown in figure 5a, while figure 5b compares electricity consumption per month. at the beginning semester, the 1st and 2nd weeks (figure 5a), the electricity consumption in faculty buildings is almost the same. it could be because, based on the academic calendar in those weeks, lectures and practicum activities had not yet started (andalas, 2019). as shown by figure 5b, in october and november, there was the highest decrease in electricity consumption because of the pandemic. it also a policy requires owfh (online work from home) during the pandemic during these months (rector, 2020a, 2020b). 4.1.2. impact on classroom buildings the building group of classrooms consisted of b, c, d, and g buildings. the activities carried out in these buildings were entirely lecture activities. figure 6 shows electricity consumption before and during olfh at classroom buildings. as demonstrated in figure 6a, the weekly electricity usage during the pandemic is almost the same as during a lecture break. this condition occurred because, during olfh, lecture activities switched to online meetings, so practically no activities were carried out in this building. it is relatively a small consumption of electricity in this building. it is an essential building requirement for night lighting and pumping water. figure 6b. shows a comparison of monthly electricity usage in lecture buildings before and during figure 4: the server communication mode with sensor(huawei, 2007) figure 3: the system architecture of electricity consumption monitoring at universitas andalas (pujani et al., 2019) figure 5: the comparison of electricity consumption before and during olfh in the engineering faculty buildings. (a) electricity consumption per-week. (b) electricity consumption per month 0 2000 4000 6000 8000 10000 12000 14000 0 2 4 6 8 10 12 14 16 18 20 22 24 26 kw h week before pandemic(aug.'19-jan.'20) during pandemic(aug.'20-jan.'21) 49712.351 43989.664 46979.69 46131.676 47215.56 40681.984 30977.547 28759.295 24815.188 23675.809 33042.759 33223.928 0 10000 20000 30000 40000 50000 60000 jannuary december november october september august kwhb a pujani, et al.: managing electricity consumption on campus: the effect of online learning from home international journal of energy economics and policy | vol 13 • issue 3 • 2023 389 olfh. from october to november, the comparison of electrical energy consumption between during and before the pandemic was lowest in october (rector, 2020a, 2020b). 4.1.3. impact on central library building activities in the central library building include lending service, reading service, and library administration. in addition, at the universitas andalas library building, seminar room facilities are also provided, usually used every saturday. electrical equipment that is very dominant in consuming electrical energy in this building is air conditioning (ac) and lights. figure 7 shows the analysis of electricity consumption in library buildings before and during the olfh. in general, there has been a significant decrease in electricity consumption in the main library building during the olfh. the most significant decline occurred in october and november, or weeks 11 to 16, as shown by figure 7a and b. the decrease in energy consumption from library buildings during covid-19 was mainly due to reduced student visits to the central library and the university’s owfh policy(rector, 2020a, 2020b). 4.1.4. impact on rectorate building the rectorate building is the center of administration and management activities of the entire campus. this building includes office work, financial, and student administration activities. in addition, this building is also the center of campus management. figure 8 compares electricity consumption before and during the olfh at the rectorate building. as shown in figure 8, there is a decrease in electricity consumption during the covid-19 pandemic in this building, and it is not too significant if we compare it with the other buildings. figure 6: the comparison of electricity consumption before and during olfh in the classroom buildings group. (a) electricity consumption per-week. (b) energy consumption per month figure 7: the comparison of electricity consumption before and during olfh in the central library building. (a) electricity consumption per-week. (b) electricity consumption per month figure 8: the comparison of electricity consumption before and during olfh at the rectorate building. (a) electricity consumption perweek. (b) electricity consumption per month 0 500 1000 1500 2000 2500 3000 3500 0 2 4 6 8 10 12 14 16 18 20 22 24 26 kw h week before pandemic (aug.'19-jan.'20) during pandemic (aug.'20-jan.'21)_ 10616.2 12926.451 14174.017 12918.224 8834.003 6643.815 3639.049 3331.674 3482.593 3537.412 3315.49 3357.477 0 2000 4000 6000 8000 10000 12000 14000 16000 august september october november december january kwhb a 0 1000 2000 3000 4000 5000 6000 0 2 4 6 8 10 12 14 16 18 20 22 24 26 kw h week before pandemic (aug'19-jan'20) during pandemic (aug'20-jan'21) 15999.426 17586.397 19472.345 18784.448 19511.02 18870.48 12037.469 10013.778 5882.533 5588.64 10678.358 9889.778 0 5000 10000 15000 20000 25000 january december november october september august kwh a b 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 kw h week before pandemic (nov.'2019-feb.'2020) during pandemic (nov.'2020-feb'2021) 29407.608 31769.046 29997.504 29255.398 25655.4 25270.866 24219.466 22373.233 0 5000 10000 15000 20000 25000 30000 35000 feb jan. dec. nov. kwh a b pujani, et al.: managing electricity consumption on campus: the effect of online learning from home international journal of energy economics and policy | vol 13 • issue 3 • 2023390 4.2. effects of olfh on quality learning process 4.2.1. impact on students’ living costs the results of the effects of lectures online during olfh on students’ cost of living are shown in table 1. as shown in table 1, 69 respondents (46.3%) stated that they had an increment in living costs during online learning, and 34 respondents (22.8%) indicated a decline in living costs. 87 respondents (58.4%) stated that telephone and internet bills were the cause of this problem, followed by component electricity bills, which were declared by 76 respondents (51%). meanwhile, 70 respondents (47%) said there was a decrease in costs in transportation costs. 4.2.2. the supporting factors of olfh table 2 shows the survey results on the condition of supporting facilities during olfh. as shown in table 2, most of the respondents stated that their supporting facilities for implementing online learning were in good condition. supporting equipment for online learning, such as laptops/mobile phones/tablets/personal computers, are usable. likewise, supporting media for online lectures, such as virtual meetings, online classes, and messenger, are sufficiently available. in addition, the ability to operate supporting equipment and applications from online learning is quite good. however, according to most respondents, internet speed needed to be increased to improve the implementation of quality lectures. this section discusses the results of a survey on the effects of olfh on learning process quality. the survey was conducted by asking ten questions about the motivation and quality of the online learning process during olfh. questions 1 and 2 relate to student motivation for implementing olfh during the covid-19 pandemic. the results are shown in figures 4 and 9. as can be seen from the answers to questions 1 and 2, students’ motivation to participate in olfh during the covid-19 pandemic is relatively high. for questions 3 to 10, each respondent can choose more than one answer. question 3 regarding the factors that support olfh, as shown in figure 10. 50.3% of respondents stated that students agree with online learning because lectures and exams can be carried out more flexibly. in addition, 30.9% of respondents noted that the implementation of olfh ran smoothly due to the free internet package support from the government and the convenience of attending lectures from home. question 4 of the survey asks respondents for their opinion on the advantages of olfh. 75.8% of respondents stated that the benefit of olfh is that learning and teaching activities can be carried out flexibly, as shown by figure 11. at the same time, 47% of respondents agree that online courses can improve digital student abilities. question 5 asks the respondent’s opinion about the lack of olfh. 67.8% of respondents stated that olfh must provide a good internet connection and adequate supporting equipment, as shown by figure 12. as many as 59.7% of respondents stated that they could not interact face-to-face with lecturers and students during olfh. meanwhile, 52.3% of respondents said that learning with the internet causes learning motivation to decrease. figure 13 shows the survey results from the answers to question 6. 47% of respondents stated that olfh resources are interactive and easy to use. 42.3% of respondents noted that the content and sources of olfh are relevant and qualitative. meanwhile, 34.9% said that the content and sources of olfh were suitable for developing student skills related to job opportunities. the answer to question 7 is shown in figure 14. as shown in the figure 14, 85.2% of respondents think that the most effective and quality form of online learning is virtual meeting learning, and 11.4% of respondents choose an online class. meanwhile, only 3.3% of respondents chose to use messenger. table 1: results of the survey on the effects of online learning during olfh on students’ living cost type of student living cost greatly increased (%) increase (%) constant (%) decrease (%) greatly decreased (%) transportation fee 4 (2.7) 15 (10) 26 (17.4) 70 (47) 34 (22.8) accommodation fee 6 (4) 30 (20.1) 54 (36.2) 39 (26.2) 20 (13.4) meal cost 8 (5.4) 50 (33.6) 45 (30.2) 31 (20.8) 15 (10.1) electric bill 29 (19.5) 76 (51) 33 (22.1) 7 (4.7) 4 (2.7) telephone and internet bill 87 (58.4) 43 (28.9) 15 (10) 2 (1.3) 2 (1.3) total living cost 13 (8.7) 69 (46.3) 23 (15.4) 34 (22.8) 10 (6.7) table 2: the survey results for the supporting factors condition of online learning the item for online lecture supporting infrastructure very good (%) good (%) neutral (%) bad (%) very bad (%) the ability of online learning devices to be connected to the internet network 24 (16.1) 56 (37.6) 55 (36.9) 13 (8.7) 1 (0.7) availability of online learning support equipment (hp/tablet/laptop/computer) 25 (16.8) 77 (51.7) 35 (23.5) 11 (7.4) 1 (0.7) ability to operate online learning support equipment (hp/tablet/laptop/computer) 37 (24.8) 96 (64.4) 14 (9.4) 2 (1.3) 0 availability of adequate online lecture support media (virtual meeting, online class, messenger): 31 (20.8) 68 (45.6) 45 (30.2) 5 (3.3) 0 information traffic conditions on the campus internet network that support the implementation of online learning 6 (4) 36 (24.2) 86 (57.7) 17 (11.4) 4 (2.7) impact on the quality of the learning process pujani, et al.: managing electricity consumption on campus: the effect of online learning from home international journal of energy economics and policy | vol 13 • issue 3 • 2023 391 question 8 asks the respondent’s opinion about the advantages of online exams. as shown by figure 15, 72.5% of respondents stated that the benefit of online exams is the high flexibility in implementation (it can be taken from anywhere). meanwhile, 59.1% of respondents noted that the advantage of online exams is that it reduces the high sense of stress while doing it. question 9 asks the respondent’s perception of the drawbacks of the online exam. as shown by figure 16, 78.5% of respondents stated that the lack of online exams is very vulnerable to a poor internet connection. meanwhile, 40.3% of respondents said that the lack of online exams is a higher opportunity for cheating. question 10 asks the respondent’s opinion about the learning model at regular times. as shown by figure 17, 30.9% of respondents prefer a balanced learning model between online and face-to-face. 20.8% of respondents want learning to be conducted online only. meanwhile, 16.1% of respondents want to be mixed online and face-to-face learning with more online learning. 5. discussion as previously explained, all samples of campus buildings experienced a reduction in electricity consumption due to implementing olfh during the covid-19 pandemic. the effect of olfh on electricity consumption varies in each type of building. its influenced mainly by the activities carried out in each building. this study selected campus buildings with different activities, as shown in table 3. it has a lot of activities in the engineering faculty buildings. meanwhile, in the classroom buildings, only lecturing activities have been done in these building. how significant the effect of olfh during the covid-19 pandemic on electricity consumption depends on the function and intensity of activities that occurred in the building. the level of electricity consumption reduction for each activity is shown in table 4. as shown in table 4, lecture and practicum activities conducted online causes a decrease in electricity consumption with high levels. it is in line with government policy to organize olfh during the emergency period of the spread of covid-19 (secretary, 2020). meanwhile, more administrative activities are still carried out offline to maintain service quality so that the level of reducing electricity consumption is the smallest. table 5. shows a comparison of total electricity consumption before and during olfh for each building on the odd semester. as shown in table 5, the most considerable reduction in energy consumption due to olfh during the covid-19 pandemic occurred in classroom buildings, reaching 68.74%. it happened because there was no activity during the olfh in this building, so the level of reduction of its electricity consumption was the highest. however, the lowest decrease in electricity consumption occurred in the rectorate building, with a decrease value of 19.02%. as an administration and management center, daily activities in the rectorate building continue during olfh. however, the intensity of activity in this building was limited, and some employees were diverted to work from home (wfh), strongly disagree 1% disagree 13% neutral 26% agree 48% strongly agree 12% q1: do you agree with the policy of changing from face to face learning to olfh during the covid-19 pandemic ? strongly disagree 3% disagree 28% neutral 29% agree 33% strongly agree 7% q2: do you agree that olfh during the covid-19 pandemic has a positive impact ? figure 9: respondents’ answers to question 2 20.0% 50.3% 13.4% 18.1% 30.9% 30.9% 0 10 20 30 40 50 60 other reasons online lectures and exams are more flexible free from strict face-to-face lecture rules no need for a place to live near campus the convenience of attending lectures from home availability of assistance for zero fee internet package from the government respondent (%) question 3: the things that most support the implementation of olfh in your opinion ? figure 10: respondents’ answers to question 3 pujani, et al.: managing electricity consumption on campus: the effect of online learning from home international journal of energy economics and policy | vol 13 • issue 3 • 2023392 mainly due to an increase in the components of the living cost, such as electricity bills, internet bills, and meal costs. the increase in electricity and internet bills is understandable due to the rise in electricity, telephone, and internet usage at home due to learning activities at home. the internet cost spike has been anticipated with the government’s policy to provide free internet packages to students (secretary, 2020). the policy was implemented in 2020 and 2021, giving each student a free internet data package of 15 gb monthly. conversely, according to most respondents, transportation costs decreased during olfh, as shown in table 1. likewise, most respondents said accommodation costs on campus fell during olfh. overall, the increase and decrease in the cost of living component during online lectures during olfh were almost balanced. even if there were an increase in the total cost of living, it was not significant. moreover, the government has also assisted with student tuition fees during the covid-19 pandemic (ministry, 2020). based on the respondent’s response, the it infrastructure supporting the online class was adequate and in good condition. the availability of students’ online learning equipment, such as hp/tablet/laptop/computer, is excellent. however, 8.1% of respondents stated that the availability of its supporting tools was not good, as shown in table 2. likewise, 9.4% of respondents said that their tools could not be appropriately connected to internet access. since these two conditions are relatively small in number, they can be resolved case by case. 57.7% of respondents perceived campus internet speed as moderate conditions. increasing internet bandwidth to the campus data center is necessary to optimize learning process quality during olfh. as discussed earlier, the student survey results showed that most respondents were well-received about switching from face-toface learning to olfh during the covid-19 pandemic. whereas during the post-covid-19 pandemic, the learning method that was more in demand by respondents was a balanced mix of face-to-face lectures and online lectures. overall, the majority of respondents have the perception that olfh during the covid-19 pandemic has provided benefits for students, including: a. learning and teaching activities implemented flexibly b. can improve students’ digital abilities c. online lecture content and resources are more interactive and easy to use d. online exams can reduce stress compared to onsite exam. on the other side, the perception of the majority of respondents stated that online learning has some drawbacks, among the reasons being: a. cannot communicate and interact directly between lecturers and students b. implementation of online lectures and their exams must require a qualified internet connection and equipment c. cause motivation and enthusiasm to learn to be reduced d. opportunities for cheating and plagiarism are higher in online exams. the significant reduction in electricity consumption in campus buildings due to olfh during the covid-19 pandemic is a table 3: the variety and intensity of activities conducted in the campus buildings activities variation buildings eng. faculty classroom library rectorate lectures low high na na seminar/meeting medium na high medium lending service low na high na reading service low na high na final project/research high na na na practicum high na na na academic activity high na na na administration high na low very high na: not available table 4: the electricity consumption reduction level for each activity activities electricity consumption reduction level high medium low lecture activities v seminar/meeting v lending service v reading service v final project/research v practicum v academic activities v administration v table 5: the comparison of electricity consumption of buildings before and during olfh on the odd semester buildings electricity consumption on odd semester (kwh) electricity consumption reduction before pandemic during pandemic kwh % eng. faculty 274710.925 174494.526 100216.399 36.48 classroom 66112.71 20663.695 45449.015 68.74 central library 110224.116 54090.556 56133.560 50.93 rectorate 120429.556 97518.965 22910,591 19.02 0.0% 22.8% 31.5% 18.8% 47.0% 75.8% 0 10 20 30 40 50 60 70 80 respondent (%) question 4: what are the advantages of olfh in your opinion ? figure 11: respondents’ answers to question 4 especially when the campus lockdown policy was enforced (rector, 2020a, 2020b). according to most respondents, as shown in table 1, the results show that olfh has increased the cost of living. the increase was pujani, et al.: managing electricity consumption on campus: the effect of online learning from home international journal of energy economics and policy | vol 13 • issue 3 • 2023 393 0.0% 19.5% 59.7% 19.5% 67.8% 52.3% 0 10 20 30 40 50 60 70 80 other reasons the quality of learning media is poor and difficult to use. unable to communicate and interact face to face unable to do activities practically requires an internet connection & supporting equipment sufficient causes motivation and enthusiasm to learn to be reduced respondent (%) question 5: what are the disadvantages of olfh ? figure 12: respondents’ answers to question 5 2.0% 22.8% 29.5% 34.9% 47.0% 42.3% 0 5 10 15 20 25 30 35 40 45 50 other reasons students are more daring to ask questions and express opinions to the lecturer students are more daring to express their opinions in discussion forums suitable for developing student skills related to job opportunities interactive and easy to use relevant and qualitative respondent (%) question 6 : what makes online resources and content useful in your opinion ? figure 13: respondents’ answers to question 6 0.0% 3.3% 0.0% 11.4% 85.2% 0 10 20 30 40 50 60 70 80 90 other reasons messengger (what’sapp, email, facebook) media sharing networks (youtube, block) online class (microsoft teams, moodle, google clasroom, e-learning)p virtual meeting (zoom, skype, video call, google meet} respondent (%) question 7 :the supporting media for olfh which in your opinion are the most effective and of high quality are: figure 14: respondents’ answers to question 7 source of cost savings for the university. these cost savings can be used to implement programs that can correct deficiencies in the online lecture process, which have been identified from the student survey results. the programs to increase learning in olfh during the covid-19 pandemic include: a. organizing an international conference regarding how to maintain the quality of the learning process during olfh b. developing an interactive video module as a practicum substitute for olfh c. making a policy in reduction of tuition fees for final-year students. in addition, olfh infrastructure improvements have also been made to maintain the quality of the learning process. their infrastructure improvements are in the form of e-learning server capacity upgrades. this upgrade includes an increase in internal memory from 2gb to 4gb, an increase in the processor from 2 cores to 4 cores, and an increase in the server hard disk from 100 gb to 500 gb. pujani, et al.: managing electricity consumption on campus: the effect of online learning from home international journal of energy economics and policy | vol 13 • issue 3 • 2023394 0.7 32.2 34.2 30.2 72.5 59.1 0 10 20 30 40 50 60 70 80 other reasons can improve students' digital skills lower level of complexity of online exam on-line exams are faster than face-to-face exams to increase the high flexibility of exam execution reducing high stress during exams respondent (%) question 8: advantages of taking exams oline in your opinion ? figure 15: respondents’ answers to question 8 2.7% 26.2% 24.8% 28.9% 40.3% 78.5% 0 10 20 30 40 50 60 70 80 90 other reasons examination assessment is more subjective lack of practical application in exam materials lack of interaction between lecturers and students during theexam higher chance of cheating bad internet connection respondent (%) question 9 : disadvantages of conducting online exams are : figure 16: respondents’ answers to question 9 6. conclusion this paper has analyzed the effect of switching from faceto-face lectures to olfh during the covid-19 pandemic on electricity consumption and the quality of learning in university. the results have shown a significant drop in electricity consumption in all groups of buildings on campus on odd semesters. the most significant percentage decrease in electricity consumption occurred in the classroom buildings, with a reduction of 68.74%. a minor percentage decrease in electricity consumption during olfh occurred in the rectorate building, with a decline of only 19.02%. the survey results showed that most students were satisfied with switching from face-to-face olfh during the lockdown period. however, this study also identified negative aspects of olfh during the covid-19 pandemic. it stated that online lectures and exams require a good internet connection and adequate equipment. it also cannot communicate interactively between lecturers and students, can decrease motivation and enthusiasm for learning, and opens opportunities for cheating and plagiarism during online exams and independent assignments. it also finds that reducing electricity consumption during the covid-19 pandemic saves campus operational costs. the saving cost can be used to implement programs to support the deficiencies of online learning and improve it infrastructure so that the quality of the learning process is maintained. 20.8% 17.4% 30.9% 16.1% 14.8% 0 5 10 15 20 25 30 35 online only a mix of online and face-to-face, but more online a balanced mix of online and face-to-face a mix of online and face-to-face, but more face-to-face face-to-face only respondent (%) question 10: after attending online lectures during the covid-19 pandemic, for normal lectures, the lecture model that you prefer are : figure 17: respondents' answers to question 10 pujani, et al.: managing electricity consumption on campus: the effect of online learning from home international journal of energy economics and policy | vol 13 • issue 3 • 2023 395 7. acknowledgments the authors would like to thank universitas andalas for the financial support of this work through pdu krp1gb krp1gb funding no. t/8/un.16.17/pp.energi-krp1gb/lppm/2020. references andalas, u. (2019), academic calendar 2019/2020. indonesia: universitas andalas. available from: https://akademik.unand.ac.id/ akreditasi/item/209-kalender-akademik-tahun-2018-2019 andalas, u. (2020), academic calender 2020/2021. indonesia: universitas andalas. available from: https://akademik.unand. ac.id/images/kalender%20akademik%20ta%202020-2021%20 -%20ok.pdf andrei, h., diaconu, e., gheorghe, a., bizon, n., mazare, a., ionescu, l., stanculescu, m., porumb, r., seritan, g., andrei, p. (2021), energy consumption, pandemic period and online academic education: case studies in romanian universities. in: conference 2021 7th international symposium on electrical and electronics engineering. p1–6. apec, human resources development working group. (2021), education response to covid-19 in the asia-pacific region challenges and solutions. singapore: apec. available from: https://www.apec.org/docs/default-source/publications/2021/11/ education-response-to-covid-19-in-the-asia-pacific-region/221_ hrd_education-response-to-covid-19-in-the-asia-pacific-region. pdf?sfvrsn=16456019_2 huawei, t. co., ltd. (2007), what is snmp ? available from: https:// support.huawei.com/enterprise/en/doc/edoc1100086963 jiang, p., van fan, y., klemeš, j.j. (2021), impacts of covid-19 on energy demand and consumption: challenges, lessons and emerging opportunities. applied energy, 285, 116441. katić, s., ferraro, f.v., ambra, f.i., iavarone, m.l. (2021), distance learning during the covid-19 pandemic. a comparison between european countries. education sciences, 11(10), 595. kawka, e., cetin, k. (2021), impacts of covid-19 on residential building energy use and performance. building and environment, 205, 108200. maatuk, a.m., elberkawi, e.k., aljawarneh, s., rashaideh, h., alharbi, h. (2022), the covid-19 pandemic and e-learning: challenges and opportunities from the perspective of students and instructors. journal of computing in higher education, 34(1), 21-38. ministry. (2020), regulation of the minister of education and culture concerning standards for operational unit costs of higher education at state universities within the ministry of education and culture. kementrian pendidikan dan kebudayaan, repulik indonesia. available from: https://peraturan.bpk.go.id/home/ details/163756/permendikbud-no-25-tahun-2020 pujani, v., akbar, f., nazir, r. (2019), management review of energy consumption: the energy saving opportunity in university buildings. in: proceedings of the 2019 5th international conference on industrial and business engineering. p110-116. radu, m.c., schnakovszky, c., herghelegiu, e., ciubotariu, v.a., cristea, i. (2020), the impact of the covid-19 pandemic on the quality of educational process: a student survey. international journal of environmental research and public health, 17(21), 7770. rector. (2020a), circular letter no. 26 in 2020 concerning the implementation of the work from home system (work from home) for state civil apparatuses in the universitas andalas. indonesia: universitas andalas. available from: https://repo.unand. ac.id/40133/1/edaran%20no%2026%20thn%202020.pdf rector. (2020b), circular letter no. 29 in 2020 concerning implementing the work system for state civil apparatus in the universitas andalas environment. indonesia: universitas andalas. available from: https://repo.unand.ac.id/40136/1/edaran%20no%2029%20 thn%202020.pdf secretary, g. (2020), regulation of the secretary-general number 14 in 2020 concerning technical guidelines for internet data quota assistance in 2020. kementrian pendidikan dan kebudayaan, repulik indonesia. available from: https://lldikti3.kemdikbud. go.id/v6/wp-content/uploads/2020/09/19092020_salinan-persesjennomor-14-tahun-2020-merged.pdf tadesse, s., muluye, w. (2020), the impact of covid-19 pandemic on education system in developing countries: a review. open journal of social sciences, 8(10), 159-170. tamilselvan, m., srinivasan, p., kumar, m., maity, b., agrawal, n. (2022), electricity demand and co emissions during the covid-19 pandemic: the case of india. international journal of energy economics and policy, 12(3), 161-169. worldometer, c.v. (2021), coronavirus cases: [electronic]. available from: https://www.worldometers.info/coronavirus tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(3), 251-260. international journal of energy economics and policy | vol 11 • issue 3 • 2021 251 natural resources depletion, renewable energy consumption and environmental degradation: a comparative analysis of developed and developing world amjad ali1,2*, marc audi1, yannick roussel1 1european school of administration and management, france, 2lahore school of accountancy and finance, university of lahore, city campus, lahore, pakistan. *email: chanamjadali@yahoo.com received: 21 november 2020 accepted: 13 february 2021 doi: https://doi.org/10.32479/ijeep.11008 abstract this article investigates the impact of renewable energy consumption and natural resource depletion on environmental degradation from 1990 to 2014. the analysis of this study is distributed into three parts, developing country analysis, developed country analysis and complete sample analysis. an insignificant relation has found between natural resource depletion and environmental degradation in the case of complete sample analysis and developing country analysis, but vica-versa in developed countries. fossil fuel energy consumption has a positive and significant impact on environmental degradation in developing countries. renewable energy consumption has negative impact on environmental degradation in the case of complete sample analysis and developed country analysis, but visa-versa in developing countries. economic growth positively and significantly effecting environmental degradation in all the three cases, this mean for higher economic growth we have to bear some environmental degradation. but it is the need of the hour that we should find some threshold between economic growth and pollutant emissions, so that a healthy environment can be safe for coming generations. so, for a healthy environment, fossil fuel consumption should be reduced and consumption of renewable energy with merchandised trade and urbanization can be encouraged. keywords: environmental degradation, natural resources, economic growth, renewable energy jel classifications: q57, q26, f43, q20 1. introduction the burning of biomass and combustion of fossil fuels is attached to human activities, generate greenhouse gasses that disturb the global climate and atmosphere. few last few decades the human activities witnessed different extension which creates the rapid urbanization and high pace of industrialization, this ultimately increase the energy consumption and damage to the environment. thus, the study of energy consumption, economic growth and environmental degradation become an important topic from all perspectives i.e. energy consumption, economic and environmental policies at national and international levels. there are numerous empirical and theoretical studies which explore the association of energy consumption and pollutant emissions across the world (selden and song, 1994; agras and chapman, 1999; ang, 2007; ang, 2008; halicioglu, 2009; apergis and payne, 2010; ghosh, 2010; jayanthakumaran et al., 2012; akpan and akpan, 2012; ozcan, 2013; lau et al., 2014; long et al., 2015; xu and lin, 2015; alshehry and belloumi, 2015; robaina-alves et al., 2016; alam et al., 2016; zhao et al., 2017; yeh and liao, 2017; zhang et al., 2017; jebli and youssef, 2017; bildirici, 2017; riti et al., 2017; mikayilov et al., 2018; chaudhary and bisai, 2018; rauf et al., 2018; liu and bae, 2018; song et al., 2018; bano et al., 2018). but still no consensus has been developed by these studies. therefore, the main focus of this article is to find the relationship of natural resources depletion, renewable energy consumption and this journal is licensed under a creative commons attribution 4.0 international license ali, et al.: natural resources depletion, renewable energy consumption and environmental degradation: a comparative analysis of developed and developing world international journal of energy economics and policy | vol 11 • issue 3 • 2021252 environmental degradation, a comparison among the developed and developing countries. to the best of our knowledge, this study is a healthy contribution towards respective literature. during the present era, natural resource depletion is faster than the resource replenishment (hook et al., 2010). the availability of a resource decides its value, more depleted resource has higher value. natural resource depletion has several types i.e. slash-and-burn agricultural practices, mining for fossil fuels and minerals, deforestation, aquifer depletion, soil erosion, pollution or contamination of resources, and overconsumption, excessive or unnecessary use of resources. the measurement of a natural resource depletion is very complex to quantify like a house, car or bread, because there is no suitable unit of measurement which decide how to deal with collective nature of ecosystems and possible extent of duplication (boyd, 2007). some social scientists and economists believe that measurement includes the attached benefits of natural resource for public and natural recovery of that resource. but still no unanimous global consensus is available for its measurement. while talking about deforestation, it is considered so extensive for having environmental impact i.e. less biodiversity, rising soil erosion, change in water cycle and emissions of carbon in the atmosphere. so, natural resource depletion is often considered a major contributor of global warming as well. recently, green economy, green job and green growth have become very famous terms among the environmentalists, economists and other social scientists. the way to a green economy prefers renewable energy resources instead of mineral and depletable energy resources. pigou (1932) and coase (1960) mention that over use of environmental goods leads to potential environmental externalities and if imbalance is severe, a solid public policy is required to correct for future generations. it is private ownership and free market forces which increase the negative gap between economic growth and environmental depletion (hotelling, 1931). during the 20th century, the rising greenhouse gasses among developed and developing nations urge the world to think about it seriously. the figure 1 shows that major contributors of gasses emissions are developing countries and this share is increasing day by day, in the presence of new international emissions control policies. the creation of the world health organization is stepping stone towards the solution of this issue. the rising combustion of energy is considered one the main driving forces towards higher greenhouse gasses emissions. till the last decade of the 20th century greenhouse gasses emissions are rising tremendously throughout the world, although number of international binding agreements are existed to control environmental degradation i.e. kyoto protocol etc. the local level pollutants create environmental issues across nations and times, and the behavior of free riders may cause the environment long lasting losses (arrow et al., 1995), thus environmental degradation is considered a universal phenomenon. but more than 60% population of the world is living in developing countries and these countries have higher poverty, unemployment rate, income inequality and low national output as well. these socioeconomic targets can be achieved with the help of economic activities and energy consumption is the main driving forces of all types of economic activities. higher output depends upon higher fossil fuel energy consumption and fossil fuel higher energy consumption is attached with higher environmental degradation (ekpo, 2013). figure 1 explains that human activities are the prime factor of rising greenhouse gasses in the atmosphere since last 150 years. solomon et al. (2008) point out that rising human activities are attached with higher energy demand. the energy demand in the production process is an important as other inputs (kraft and kraft, 1978; bhattacharyya, 1995; heil and selden, 2001). more than 30% emissions are produced by industrial sector only and most of the developing countries are under the conditions of limited energy supply. the limited supply of fossil fuel energy consumption with limited use of renewable energy consumption create environmental pollution and the growing concern about global warming, attract the interest of policy makers towards environmental degradation (figure 2). 2. literature review greenhouse gasses are creating an adverse impact on the quality of ecosystem in general and human life specific. so, it becomes necessary to examine the main roots of environmental figure 1: major contributors of emissions source: paris agreement status of ratification, 2019 figure 2: greenhouse gas emissions by economic sector source: paris agreement status of ratification, 2019 ali, et al.: natural resources depletion, renewable energy consumption and environmental degradation: a comparative analysis of developed and developing world international journal of energy economics and policy | vol 11 • issue 3 • 2021 253 degradation and prepare some suitable remedies. following the volume of carbon emission in ecosystem, previous literature considers it, as main indicators to aggregate greenhouse gasses. to date, extensive body of literature is available which examine the connection of economic growth, energy consumption and pollutant emission, but here in literature review purpose, we have selected recent and most relevant studies. friedl and getzner (2003) investigate the connection of economic development and carbon dioxide emissions in the case of small opened and industrial country i.e. austria, data from 1960 to 1999 has been used for empirical analysis. a cubic relationship has been found between economic development and co2 emissions. the findings indicate that emission projections of single country support the policy changes under the kyoto protocol. ang (2007) explores the causality among total output, consumption of energy and pollutant emissions in france from 1960 to 2000. the outcomes present the evidence of the long run relationship amon the pollutant emissions, consumption of energy and output in france. the outcomes of causality support the idea that it is level of economic growth which causes energy use and growth of pollutant emission over the long run in france. in another study, halicioglu (2009) focuses on dynamic causal link of pollutant emission, consumption of energy, level of income and international trade in turkey from 1960 to 2005. the findings of this study are consistent with the findings of ang (2007). ozturk and acaravci (2010) explore the causality among the employment ratio, consumption of energy, pollutant emission and level of economic growth in turkey over the time period 19682005. for this purpose, autoregressive-distributed-lag-bounds testing approach of co-integration and granger-causality-test has been used. the empirical outcomes highlight long-run association is existed among the selected indicator in turkey. the findings of this study show that environmental kuznets do not exist in turkey over the selected time period. the overall outcomes display that policies of energy conservation, i.e. rationing for consumption of energy and control over the emissions of carbon; put negative impact over growth of real output in turkey. al-mulali and sab (2012) analyses the impact of pollutant emission and consumption of energy on financial development and gdp in 30 sub-saharan nations over the period of 1980 to 2008. the results highlight that consumption of energy has vital contribution in the level of growth and financial development. the results recommend that african economies should focus on productivity of energy by raising its efficiency, encourage projects of energy conservation and savings and utilize outsourcing of energy infrastructure. arouri et al. (2012) investigate association among real gdp, consumption of energy, and pollutant emission, a sample of 12 mena has been selected over the period 1981to 2005. for this purpose, advance bootstrap panel stationarity tests and cointegration have been used. the results of this study show that consumption of energy has positive long-run impact on pollutant emission and real gdp has nonlinear influence on pollutant emission. camarero et al. (2013) examine the level of environmental degradation convergence among the oecd nations from 1960 to 2018. the methodology developed by phillips and sul (2007) has been used for this purpose. the outcomes of the study reveal that with the passage of time there is evidence of convergence of environmental degradation among the oecd nations as like the level of development among these countries. dogan and seker (2016) explore the link among real income, nonrenewable and renewable consumption of energy and openness of trade on pollutant emission. environmental kuznets curve model has been tested for some selected european nation from 1980 to 2012, advance panel methods have been applied for empirical analysis. the outcomes of the analysis reveal that liberalization of trade and energy production by renewable resources diminish emissions of carbon in environment, whereas non-renewable energy has vice-versa impact. the findings of this study show a bidirectional causal relationship between pollutant emission and consumption of renewable and unidirectional causal relationship from real income to pollutant emission, from pollutant emission to nonrenewable energy, and from liberalization trade to pollutant emission. 3. the model the link between renewable resources and environmental conditions is attached to ricardian rent theory, as the prices of scare renewable resources are higher that the less cost depletable resources (ricardo, 1891). lower level of environmental degradation is attached to a higher living standard, so every nation is trying to improve environmental conditions with less carbon emissions. this study is examining the effect of natural resources depletion and consumption of renewable energy on degradation of environment from 1990 to 2014. the world development indicator and some national sources have been used for data collection. based on a detailed review of literature, our model follows govindaraju and tang (2013), shahbaz et al. (2013), ali and audi (2016) and audi and ali (2018), our model functional form becomes as: co fit it it it it it it2 = (nrd ,fec ,rnc ,ecog ,urb ,trade ) (1) here co2 = environmental degradation nrd = natural resource depletion fec = fossil fuel energy consumption rnc = renewable energy consumption ecog = economic growth urb = urbanization trade = merchandise trade i = ith country (1, 2, 3,… 66) t = time period (1990 to 2014). 4. discussion of results this section is comprised of estimated results and discussion, this study uses panel least square method for examining the effect of ali, et al.: natural resources depletion, renewable energy consumption and environmental degradation: a comparative analysis of developed and developing world international journal of energy economics and policy | vol 11 • issue 3 • 2021254 natural resource depletion, and consumption of renewable energy on environmental degradation among selected developed and developing countries. this study distributes its analysis into three parts, complete sample analysis, developed country analysis and developing country analysis. the results of descriptive statistic of all three cases are presented in appendixes table a-e. the descriptive statistic of complete sample analysis shows that selected variables have mean value between 2.745632 and 74.36373 and median and maximum value range 0.828648-81.22369 and 220.4074-0.00000 respectively. the data are positive skewed except consumption of energy through fossil fuel and economic growth, all indicators have kurtosis value in positive. the descriptive statistic of developed country analysis shows that selected variables have mean value between 0.662743-78.45416 and median and maximum value range 0.168449-81.92648 and 208.1709-0.00000 respectively. the data are positive skewed except consumption of energy through fossil fuel and economic growth, all indicators have kurtosis value in positive. the descriptive statistic of developing country analysis shows that selected variables have mean value between 3.927667 and 71.33698 and median and maximum value range 1.996871-79.61963 and 220.4074-0.00000 respectively. the data are positive skewed except consumption of energy through fossil fuel and economic growth, all indicators have kurtosis value in positive. the descriptive statistic results of all three cases reveal that our selected data fulfill all the requirements of the panel least square. the outcomes of the correlation matrix of all three cases have been given in appendixes table b, table d, and table f. the outcomes in table b of complete sample analysis reveal that natural resource depletion has inverse and insignificant correlation with degradation of environment. the estimated results show a positive and significant correlation between fossil fuel energy consumption and degradation of environment. renewable consumption of energy, urbanization and merchandise trade have significant inverse correlation with degradation of environment. economic growth has positive and insignificant correlation with degradation of environment in case of complete sample analysis. fossil fuel energy consumption, economic growth and urbanization are positively and significantly correlation to natural resources depletion; renewable energy consumption has positive and insignificant correlation with natural resources depletion; merchandise trade has negative and insignificant correlation with natural resource depletion. consumption of energy through fossil fuel and consumption of energy through renewable sources have negative and significant correlation; economic growth and urbanization have positive, but insignificantly correlated to consumption of energy through fossil fuel; merchandise trade is positively and significantly correlated to fossil fuel energy consumption. economic growth is positively and significantly correlated to renewable energy consumption; urbanization has positive but insignificant correlation with renewable energy consumption; merchandise trade has negative and significant correlation with renewable energy consumption. the results explain that urbanization and merchandise trade are positively and significantly correlated to economic growth; urbanization is also positively and significantly correlated to merchandise trade. the results of the correlation matrix of developed country analysis have been given in appendix table d. the results show that natural resource depletion, consumption of energy by renewable resources, urbanization and merchandise trade are negatively and significantly correlated to environmental degradation; while fossil fuel energy consumption has positive and significant correlation with environmental degradation in developed countries. fossil fuel energy consumption, urbanization and merchandise trade have negative and significant correlation with natural resources depletion; renewable energy consumption has positive significant correlation with natural resources depletion whereas economic growth has positive and insignificant correlation with natural resource depletion. renewable energy consumption has significant and positive correlation with fossil fuel energy consumption; economic growth and urbanization are positively and significantly correlated to fossil fuel energy consumption; whereas fossil fuel energy consumption is negatively and insignificantly correlated to merchandise trade. economic growth and merchandise trade are negatively and insignificantly correlated to renewable energy consumption; urbanization is positively and significantly correlated to renewable energy consumption. the estimated outcomes show that urbanization and merchandise trade are positively and significantly correlated to economic growth; urbanization and economic growth in the case of developed countries. the results of the correlation matrix of developing country analysis have been given in appendix table f. natural resources depletion, fossil fuel energy consumption and economic growth have positive and significant correlation with environmental degradation; renewable energy consumption, urbanization and merchandise trade have negative and significant correlation with environmental degradation. fossil fuel energy consumption, economic growth and urbanization have positive and significant correlation with natural resource depletion; renewable energy consumption has negative and significant correlation with natural resources depletion; whereas merchandise trade has positive and insignificant correlation with natural resource depletion. fossil fuel energy consumption has negative and significant correlation with renewable energy consumption; economic growth and merchandise trade have positive and significant correlation with fossil fuel energy consumption; urbanization has positive and insignificant correlation with fossil fuel energy consumption. economic growth and urbanization have insignificant negative correlation with renewable energy consumption; merchandise trade has negative and significant correlation with renewable energy consumption. urbanization has positive but insignificant correlation with economic growth; merchandise trade has positive and significant correlation with economic growth. urbanization has positive and significant correlation with merchandise trade in the case of development. the comparative analysis of correlation matrices of complete analysis, developed country analysis and developing country analysis show that natural resources depletion has negative but insignificant correlation with environmental degradation incomplete sample analysis; natural resource depletion has negative and significant correlation with environmental degradation in developed country analysis; whereas natural ali, et al.: natural resources depletion, renewable energy consumption and environmental degradation: a comparative analysis of developed and developing world international journal of energy economics and policy | vol 11 • issue 3 • 2021 255 resources depletion has positive and significant correlation with environmental degradation in developing countries. fossil fuel energy consumption has positive and significant correlation with environmental degradation in all the three cases. renewable energy consumption has negative and significant correlation with environmental degradation in all the three cases. economic growth has insignificant correlation with environmental degradation in the case of complete sample analysis and developed country analysis; whereas there is positive and significant correlation between environmental degradation and economic growth in the case of developing countries. the estimated results show that urbanization and merchandise trade have negative and significant correlation with environmental degradation in the complete sample analysis, developed country analysis and developing country analysis. the overall correlation matrix shows that mostly selected variables have significant correlation with environmental degradation in the three cases over the selected time period. the estimated panel least square of complete sample analysis has been given in the table 1. natural resource depletion has an insignificant impact on environmental degradation in case of complete sample. fossil fuel energy consumption has a positive impact on environmental degradation in the case of complete sample analysis. fossil fuel is the easiest and cheapest method of energy production, but it is attached with higher amount of greenhouse gases (ulgiati and pimentel, 1997; youngquist, 1997; pimentel and kounang, 1998; croysdale, 2001; pimentel et al., 2001; fuel’s gold, 2002; lieberman, 2002; hodge, 2002). so, a 1% increase in fossil fuel energy consumption in the world increases environmental degradation (0.014351) percent in the world. renewable energy consumption has a negative and significant impact on environmental degradation. renewable energy resources and their use has become very vital for lower environmental degradation. the advancement and development of renewable energy resources are considered environment friendly, less costs and long lasting (dincer and rosen, 1998; dincer and dost, 1996; norton, 1991). our study finds that 1% increase in renewable energy consumption reduces environmental degradation by (0.027552) percent. economic growth has positive and significant impact on environmental degradation. kraft and kraft (1978) mention that in the starting stages of economic development, there is a direct positive relationship between environmental degradation and economic growth. our results show that 1% increase in economic growth increases environmental degradation by (0.027885). urbanization has a positive and significant impact on environmental degradation. following the theory of urban population, urban population is attached to higher education and better life conditions. moreover, urban population cares healthier environment as compare to rural population. so, urbanization has negative impact on environmental degradation, our study finds that 1% increase urbanization decreases environmental degradation by (0.066083) percent. merchandise trade has a negative and significant impact on environmental degradation. following trade theory, the importing countries prefer the quality of product, unhealthy production process reduces the benefits of exporting countries. so, for getting the higher benefits from exports, the exporting countries use healthier and environment friendly methods of production, which lower the overall environmental degradation in societies. our results show that 1% increase in merchandise trade, decreases environmental degradation by (0.014573) percent. the estimated results of the developed country analysis have been presented in table 1. natural resource depletion has a positive and significant impact on environmental degradation. natural resources are the main source of maintaining the eco-system, so an increase in natural resources depletion, changes the share of greenhouse gases in the ecosystem. an immediate impact of higher natural resource depletion will increase the environmental degradation, our study finds that 1% increase natural resource depletion, increases environmental degradation by (0.161392) percent. fossil fuel energy consumption has a negative and significant impact on environmental degradation in the case of developed countries. this shows that developed countries are in the position of kuznet environmental degradation inverted u-shaped relationship between fossil fuel energy consumption and environmental degradation. our results reveal that 1% increase in fossil fuel, decreases environmental degradation by (0.012986) percent in the case of developed countries. renewable energy consumption has a negative and significant impact on environmental degradation in the case of developed countries. renewable energy sources are one of the main growing sources of energy production and it is considered environmentally friendly. our study finds that 1% increase in renewable energy consumption brings (0.061456) percent decrease in environmental degradation in the case of developed countries. economic growth has positive and significant impact on environmental degradation in developed countries. the estimated results show that 1% increase in economic development increases environmental degradation by (0.022032) percent. this shows that for higher economic growth specific amount of environmental degradation has to be faced. urbanization has a negative and significant impact on environmental degradation in developed countries. following the world urbanization prospects (2011), the urban population in developed countries cares more their surroundings and environment. all the developed countries have more than 80% urban population, this is the main reason that rising urbanization reduces the environmental degradation. our study finds that 1% increase in urbanization decreases environmental degradation by (0.048953) percent. merchandise trade has a negative and significant impact on environmental degradation. after the emergence of world trade organization, all the trading goods must be banned which production process is not environment friendly. so, rising trade discourages trade of unfriendly trading goods, this further reduces the environmental degradation in developed countries. our findings show that table 1: panel least square; dependent variables: co2 variables whole sample developed countries developing countries nrd 0.002917 0.161392*** 0.003471 fec 0.014351*** −0.012986*** 0.065496*** rnc −0.027552*** −0.061456*** 0.022768*** ecog 0.027885*** 0.022032** 0.020619*** urb −0.066083*** −0.048953*** −0.070439*** trade −0.014573*** −0.018665*** −0.008835*** c 13.55205*** 16.09054*** 8.125993*** ***,**,*present significance level 1%, 5% and 10% respectively ali, et al.: natural resources depletion, renewable energy consumption and environmental degradation: a comparative analysis of developed and developing world international journal of energy economics and policy | vol 11 • issue 3 • 2021256 1% increase in merchandise trade decreases environmental degradation by (0.018665) percent. the estimated panel least square of developing country analysis has been given in the table 1. our estimates show that natural resource depletion has a positive, but insignificant impact on environmental degradation in developing countries. fossil fuel energy consumption has a positive and significant impact on environmental degradation in developing countries. the estimated results show that 1% increase in fossil fuel energy consumption increases environmental degradation by (0.065496) percent. renewable energy consumption has a positive and significant impact on environmental degradation. renewable energy resources are getting much attention in the process of energy production, but unlike the developed countries, renewable energy consumption has a positive impact on environmental degradation. this shows that renewable energy consumption in developing countries is not as efficient as like in developed countries, so it is enhancing environmental degradation in developing countries. our results show that 1% increase renewable energy consumption, increase environmental degradation by (0.020619) percent in the case of developing countries. developing countries are in the early stage of economic development, so there is a positive and significant impact of economic growth on environmental degradation in the case of developing countries. our results show that 1% increase in economic growth, (0.020619) percent increase has been occurred in environmental degradation in the case of developing countries. like the developed countries, urbanization has a negative and significant impact on environmental degradation in developing countries. our study finds that 1% increase in urbanization, (0.070439) percent decrease in environmental degradation has been occurring in the case of developing countries. merchandised trade has a negative and significant impact on environmental degradation in developing countries, this effect is same like in developed countries. our findings show that 1% increase in merchandised trade, (0.008835) percent decrease is occurring in environmental degradation in the case of developing countries. the overall results show that fossil fuel consumption and renewable energy consumption are positively contributing in environmental degradation, whereas urbanization and merchandised trade have a negative impact on environmental degradation. panel causality results of the all three cases have been given in table 2. the results show that unidirectional causality is running from natural resources depletion to environmental degradation in the case of complete sample analysis and developed country analysis. whereas there is no causal relationship between natural resources depletion and environmental degradation in the case of developing country analysis. unidirectional causality is running from fossil fuel consumption to environmental degradation in the case of complete sample analysis and developing country analysis. bidirectional causality is running between fossil fuel energy consumption and environmental degradation in the case of developed country analysis. bidirectional causality is running between renewable energy consumption and environmental degradation in the case of complete analysis and developed country analysis. but unidirectional causality is running from renewable energy consumption to environmental degradation in the case of developing countries. unidirectional causality is running from economic growth to environmental degradation in the case of complete sample analysis and developing country analysis, whereas bidirectional causality is running between economic growth and environmental degradation in the case of developed country analysis. unidirectional causality is running from urbanization to environmental degradation in the case of complete sample analysis and developing country analysis, but bidirectional causality is running between urbanization and environmental degradation in the case of developed countries. unidirectional causality is running from merchandised trade to environmental degradation in all the three case i.e. complete sample analysis, developed country analysis and developing country analysis. there is no causal relationship between fossil fuel consumption and natural resource depletion in the case of complete sample analysis and developing country analysis, but bidirectional causality is running between these two in the case of developed country analysis. no causality is existed between renewable energy consumption and natural resources depletion in the case of compete sample analysis, but bidirectional causality is running between these two in the case of developed countries analysis whereas unidirectional causality is running from renewable energy consumption to natural resources depletion in the case of developing countries analysis. there is no causal relationship between economic growth and natural resource depletion in the case of complete sample analysis and developing country analysis, but unidirectional causality is running from natural resources depletion to economic growth in the case of developed country analysis. no causality is running between urbanization and natural resource depletion in the case of complete sample analysis and developing country analysis, but these two have bidirectional causality in the case of developed country analysis. unidirectional causality is running from natural resources depletion to merchandised trade in the case of complete sample, bidirectional causality is existed between these two in the table 2: panel pairwise granger causality tests complete sample developed countries developing countries nrd→co2 nrd→co2 nrd→co2 fec→co2 fec→co2 fec→co2 rnc→co2 rnc→co2 rnc→co2 ecog→co2 ecog→co2 ecog→co2 urb→co2 urb→co2 urb→co2 trade→co2 trade→co2 co2→trade fec→nrd fec→nrd fec→nrd rnc→nrd rnc→nrd rnc→nrd ecog→nrd nrd→ecog ecog→nrd urb→nrd urb→nrd urb→nrd trade→nrd trade→nrd trade→nrd rnc→fec rnc→fec rnc→fec ecog→fec ecog→fec ecog→fec urb→fec urb→fec urb→fec fec→trade fec→trade fec→trade ecog→rnc ecog→rnc ecog→rnc urb→rnc urb→rnc urb→rnc trade→rnc rnc→trade trade→rnc urb→ecog urb→ecog urb→ecog trade→ecog trade→ecog trade→ecog urb→trade urb→trade urb→trade →: bidirectional causaity, →: unidirectional causality, →=no causality ali, et al.: natural resources depletion, renewable energy consumption and environmental degradation: a comparative analysis of developed and developing world international journal of energy economics and policy | vol 11 • issue 3 • 2021 257 case of developed country analysis, no causal relationship between merchandised trade and natural resource depletion in the case of developing countries. bidirectional causality is running between renewable energy consumption and fossil fuel energy consumption in all the three types of analysis. bidirectional causality is running between economic growth and fossil fuel energy consumption in the case of complete sample analysis and developed country analysis, but unidirectional causality is running from economic growth in fossil fuel energy consumption in the case of developing country analysis. no causality is running between urbanization and fossil fuel energy consumption in the case of complete sample analysis and developing country analysis, whereas bidirectional causality is running between these two in the case of developed country analysis. unidirectional causality is running from merchandised trade to fossil fuel energy consumption in the case of complete sample analysis and developed country analysis, but there is no causal relationship existed between these two in the case of developing country analysis. bidirectional causality is running between economic growth and renewable energy consumption in the case of complete sample analysis and developed country analysis, whereas unidirectional causality is running from economic growth to renewable energy consumption in the case of developing countries. no causality is existed between urbanization and renewable energy consumption in the case of complete sample analysis and developing country analysis, but bidirectional causality is running between these two in the case of developed country analysis. no causality is running between merchandised trade and renewable energy consumption in the case of complete sample analysis and developing country analysis, but unidirectional causality is running from merchandised trade to renewable energy consumption in the case of developed country analysis. bidirectional causality is running between urbanization and economic growth in all the three types of analysis. unidirectional causality is running from economic growth to merchandised trade in the case of complete sample analysis and developing country analysis, but bidirectional causality has existed between these two in the case of developed country analysis. no causality is existed between urbanization and merchandised trade in the case of complete sample analysis and developing country analysis, whereas bidirectional causality has existed between these two in the case of developed country analysis. overall causality results show that most of the variables have a unidirectional causal relationship with environmental degradation in the case of complete sample analysis and developing country analysis, whereas most of the variables have a bidirectional causal relationship with environmental degradation in the case of developed country analysis. this reveals that selected variables have strong predicating power to explain environmental degradation in the case of developed and developing countries. 5. conclusions and policy implications this paper has examined the impact of renewable consumption of energy and natural resources depletion on environmental degradation from 1990 to 2014. this study uses environmental degradation as dependent variable, whereas economic growth, natural resources depletion, fossil fuel consumption of energy, renewable energy consumption, urbanization and merchandise trade has been used as explanatory variables. this study has used 66 developed and developing countries for empirical analysis, among them, 38 are developing countries and 28 are developed countries, the selection is based international monetary fund’s world economic outlook database and list of countries is given in the appendix. the analysis of this study is distributed into three parts, developing country analysis, developed country analysis and complete sample analysis. the study finds insignificant impact of natural resource depletion in the case of complete sample analysis and developing country analysis. natural resource depletion is increasing environmental degradation in the case of developed countries, so for better environmental conditions, the developed nations should reduce natural resource depletion. moreover, the developing countries natural resource depletion are done by developed countries, so developing countries have an insignificant relationship between natural resources depletion and environmental degradation (lieberman, 2002; hodge, 2002). fossil fuel consumption of energy has a significant and positive effect on environmental degradation in the complete sample analysis and developing country analysis. so, for the improvement of environmental conditions in developing countries should reduce fossil fuel consumption, but there may be other factors which increase environment degradation in developed countries, as there is an inverse relationship between environmental degradation and fossil fuel consumption of energy. the renewable consumption of energy has negative influence on environmental degradation in the case of complete sample analysis and developed country analysis. this show that developed countries should enhance energy production with the help of renewable resources as these sources are environmentally friendly and less costly. the developing countries have a positive association amid renewable consumption of energy consumption and environmental degradation, this shows that developing country’s renewable energy production is less efficient, so it is increasing environmental degradation. this means that developing countries should use, efficient methods of renewable energy consumption method as like the developed countries, so that environmental degradation can be reduced. economic growth has a positive and significant effect on degradation of the environment in all the three types of analysis, this mean for higher economic growth we have to bear some environmental degradation. but it is the need of the hour that we should find some threshold between economic growth and environmental degradation, so that a healthy environment can be safe for coming generations. urbanization and merchandise trade have a negative and significant effect on the environment. so, for a healthy environment, economies should promote urbanization and free trade among countries. the results of causality test reveal that most of the selected explanatory variables have a significant effect on environmental ali, et al.: natural resources depletion, renewable energy consumption and environmental degradation: a comparative analysis of developed and developing world international journal of energy economics and policy | vol 11 • issue 3 • 2021258 degradation. so, for a healthy environment, fossil fuel consumption should be reduced and renewable energy consumption with urbanization and merchandised trade can be encouraged. references agras, j., chapman, d. (1999), a dynamic approach to the environmental kuznets curve hypothesis. ecological economics, 28, 267-277. akpan, g.e., akpan, u.f. (2012), electricity consumption, carbon emissions and economic growth in nigeria. international journal of energy economics and policy, 2, 292-306. alam, m.m., murad, m.w., noman, a.h.m., ozturk, i. (2016), relationships among carbon emissions, economic growth, energy consumption and population growth: testing environmental kuznets curve hypothesis for brazil, china, india and indonesia. ecological indicators, 70, 466-479. ali, a., audi, m. (2016), the impact of income inequality, environmental degradation and globalization on life expectancy in pakistan: an empirical analysis. international journal of economics and empirical research (ijeer), 4, 182-193. al-mulali, u., sab, c.n.b. (2012), the impact of energy consumption and co2 emission on the economic growth and financial development in the sub saharan african countries. energy, 39, 180-186. alshehry, a.s., belloumi, m. (2015), energy consumption, carbon dioxide emissions and economic growth: the case of saudi arabia. renewable and sustainable energy reviews, 41, 237-247. ang, j.b. (2007), co2 emissions, energy consumption, and output in france. energy policy, 35, 4772-4778. ang, j.b. (2008), economic development, pollutant emissions and energy consumption in malaysia. journal of policy modeling, 30, 271-278. apergis, n., payne, j.e. (2010), renewable energy consumption and economic growth: evidence from a panel of oecd countries. energy policy, 38, 656-660. arouri, m.e.h., youssef, a.b., m’henni, h., rault, c. (2012), energy consumption, economic growth and co2 emissions in middle east and north african countries. energy policy, 45, 342-349. arrow, k., bolin, b., costanza, r., dasgupta, p., folke, c., holling, c.s., jansson, b.o., levin, s., mäler, k.g., perrings, c., pimentel, d. (1995), economic growth, carrying capacity, and the environment. ecological economics, 15, 91-95. audi, m., ali, a. (2018), determinants of environmental degradation under the perspective of globalization: a panel analysis of selected mena nations. bano, s., zhao, y., ahmad, a., wang, s., liu, y. (2018), identifying the impacts of human capital on carbon emissions in pakistan. journal of cleaner production, 183, 1082-1092. ben jebli, m., ben youssef, s. (2017), renewable energy consumption and agriculture: evidence for cointegration and granger causality for tunisian economy. international journal of sustainable development and world ecology, 24, 149-158. bhattacharyya, s.c. (1995), internalising externalities of energy use through price mechanism: a developing country perspective. energy and environment, 6, 211-221. bildirici, m.e. (2017), the effects of militarization on biofuel consumption and co2 emission. journal of cleaner production, 152, 420-428. boyd, j. (2007), nonmarket benefits of nature: what should be counted in green gdp? ecological economics, 61, 716-723. camarero, m., castillo, j., picazo-tadeo, a.j., tamarit, c. (2013), ecoefficiency and convergence in oecd countries. environmental and resource economics, 55, 87-106. chaudhary, r., bisai, s. (2018), factors influencing green purchase behavior of millennials in india. management of environmental quality: an international journal, 29, 798-812. coase, r.h. (1960), the problem of social cost. in: classic papers in natural resource economics. london: palgrave macmillan. p87137. croysdale, d. (2001), belatedly, dnr concedes our air is clean: the daily reporter. dincer, i., dost, s. (1996), a perspective on thermal energy storage systems for solar energy applications. international journal of energy research, 20, 547-557. dincer, i., rosen, m.a. (1998), a worldwide perspective on energy, environment and sustainable development. international journal of energy research, 22, 1305-1321. dogan, e., seker, f. (2016), determinants of co2 emissions in the european union: the role of renewable and non-renewable energy. renewable energy, 94, 429-439. ekpo, h.e. (2013), promoting inclusive growth in nigeria: issues of policies reform, people, expectation and private sector responses. public lecture delivered on 13th june, 2013. friedl, b., getzner, m. (2003), determinants of co2 emissions in a small open economy. ecological economics, 45, 133-148. fuel’s gold. (2002), fuel’s gold: adm’s million-dollar soft money donations help the ethanol tax break survive. available from: http://www.commoncause.org/publications/fuelsgold_toc.htm. [last accessed on 2002 sep 18]. ghosh, s. (2010), examining carbon emissions economic growth nexus for india: a multivariate cointegration approach. energy policy, 38, 3008-3014. giampietro, m., ulgiati, s., pimentel, d. (1997), feasibility of large-scale biofuel production. bioscience, 47, 587-600. govindaraju, v.c., tang, c.f. (2013), the dynamic links between co2 emissions, economic growth and coal consumption in china and india. applied energy, 104, 310-318. halicioglu, f. (2009), an econometric study of co2 emissions, energy consumption, income and foreign trade in turkey. energy policy, 37, 1156-1164. heil, m.t., selden, t.m. (2001), carbon emissions and economic development: future trajectories based on historical experience. environment and development economics, 6, 63-83. hodge, c. (2002), ethanol use in us gasoline should be banned, not expanded. oil and gas journal, 100, 20. höök, m., li, j., oba, n., snowden, s. (2011), descriptive and predictive growth curves in energy system analysis. natural resources research, 20, 103-116. hotelling, h. (1931), the economics of exhaustible resources. journal of political economy, 39, 137-175. jayanthakumaran, k., verma, r., liu, y. (2012), co2 emissions, energy consumption, trade and income: a comparative analysis of china and india. energy policy, 42, 450-460. kraft, j., kraft, a. (1978), on the relationship between energy and gnp. the journal of energy and development, 3, 401-403. lau, l.s., choong, c.k., eng, y.k. (2014), carbon dioxide emission, institutional quality, and economic growth: empirical evidence in malaysia. renewable energy, 68, 276-281. lieberman, b. (2002), the ethanol mistake: one bad mandate replaced by another: competitive enterprise institute. available from: http:// www.nationalreview.com/comment/comment-lieberman031202. shtiml. [last accessed on 2002 sep 17]. liu, x., bae, j. (2018), urbanization and industrialization impact of co2 emissions in china. journal of cleaner production, 172, 178-186. long, x., naminse, e.y., du, j., zhuang, j. (2015), nonrenewable energy, renewable energy, carbon dioxide emissions and economic growth in china from 1952 to 2012. renewable and sustainable energy reviews, 52, 680-688. ali, et al.: natural resources depletion, renewable energy consumption and environmental degradation: a comparative analysis of developed and developing world international journal of energy economics and policy | vol 11 • issue 3 • 2021 259 mikayilov, j.i., galeotti, m., hasanov, f.j. (2018), the impact of economic growth on co2 emissions in azerbaijan. journal of cleaner production, 197, 1558-1572. norton, b.g. (1991), thoreau’s insect analogies: or why environmentalists hate mainstream economists. environmental ethics, 13, 235-251. ozcan, b. (2013), the nexus between carbon emissions, energy consumption and economic growth in middle east countries: a panel data analysis. energy policy, 62, 1138-1147. ozturk, i., acaravci, a. (2010), co2 emissions, energy consumption and economic growth in turkey. renewable and sustainable energy reviews, 14, 3220-3225. phillips, p.c., sul, d. (2007), transition modeling and econometric convergence tests. econometrica, 75, 1771-1855. pigou, a.c. (1932), the effect of reparations on the ratio of international interchange. the economic journal, 42, 532-543. pimentel, d., kounang, n. (1998), ecology of soil erosion in ecosystems. ecosystems, 1, 416-426. pimentel, d., mcnair, s., janecka, j., wightman, j., simmonds, c., o’connell, c., wong, e., russel, l., zern, j., aquino, t., tsomondo, t. (2001), economic and environmental threats of alien plant, animal, and microbe invasions. agriculture, ecosystems and environment, 84, 1-20. rauf, a., zhang, j., li, j., amin, w. (2018), structural changes, energy consumption and carbon emissions in china: empirical evidence from ardl bound testing model. structural change and economic dynamics, 47, 194-206. ricardo, d. (1891), principles of political economy and taxation. united kingdom: g. bell and sons. riti, j.s., song, d., shu, y., kamah, m. (2017), decoupling co2 emission and economic growth in china: is there consistency in estimation results in analyzing environmental kuznets curve? journal of cleaner production, 166, 1448-1461. robaina-alves, m., moutinho, v., costa, r. (2016), change in energyrelated co2 (carbon dioxide) emissions in portuguese tourism: a decomposition analysis from 2000 to 2008. journal of cleaner production, 111, 520-528. selden, t.m., song, d. (1994), environmental quality and development: is there a kuznets curve for air pollution emissions? journal of environmental economics and management, 27, 147-162. shahbaz, m., solarin, s.a., mahmood, h., arouri, m. (2013), does financial development reduce co2 emissions in malaysian economy? a time series analysis. economic modelling, 35, 145-152. shahbaz, m., van hoang, t.h., mahalik, m.k., roubaud, d. (2017), energy consumption, financial development and economic growth in india: new evidence from a nonlinear and asymmetric analysis. energy economics, 63, 199-212. solomon, k.r. (2008), effects of ozone depletion and uv‐b radiation on humans and the environment. atmosphere-ocean, 46, 185-202. song, m., peng, j., wang, j., zhao, j. (2018), environmental efficiency and economic growth of china: a ray slack-based model analysis. european journal of operational research, 269, 51-63. xu, b., lin, b. (2015), how industrialization and urbanization process impacts on co2 emissions in china: evidence from nonparametric additive regression models. energy economics, 48, 188-202. yeh, j.c., liao, c.h. (2017), impact of population and economic growth on carbon emissions in taiwan using an analytic tool stirpat. sustainable environment research, 27, 41-48. youngquist, w. (1997), geodestinies: the inevitable control of earth resources over nations and individuals, no. 333.85 y79g. oregon, us: national book. zhang, j., zeng, w., wang, j., yang, f., jiang, h. (2017), regional lowcarbon economy efficiency in china: analysis based on the supersbm model with co2 emissions. journal of cleaner production, 163, 202-211. zhao, x., zhang, x., li, n., shao, s., geng, y. (2017), decoupling economic growth from carbon dioxide emissions in china: a sectoral factor decomposition analysis. journal of cleaner production, 142, 3500-3516. table a: descriptive statistic of complete sample lco2 nrd fec rnc ecog urb trade mean 11.35301 2.745632 74.36373 23.17951 3.157721 25.71431 70.53699 median 11.12274 0.828648 81.22369 15.26307 3.414654 23.65385 63.43954 maximum 16.14687 43.65421 100.0000 94.98880 34.50000 74.56980 220.4074 minimum 6.562064 0.000000 3.780881 0.000000 −34.80864 2.867021 13.75305 sd 1.688643 5.052347 21.82053 22.86331 4.839223 13.02636 34.43644 skewness 0.066495 3.719332 −1.079306 1.229378 −1.123729 0.568445 1.151944 kurtosis 3.031526 19.95435 3.421963 3.699989 18.13292 3.241124 4.658931 jarque-bera 1.283476 23566.38 331.7829 449.3133 16091.38 92.85771 554.1217 sum 18721.11 4530.293 122402.7 38246.19 5210.239 42428.61 116386.0 sum sq. dev. 4699.296 42092.72 783243.0 861983.1 38616.41 279812.5 1955497 observations 1649 1650 1646 1650 1650 1650 1650 appendixes table b: correlation matrix of complete sample variables lco2 nrd fec rnc ecog urb trade lco2 1.000000 nrd −0.030261 1.000000 fec 0.465343*** 0.068002*** 1.000000 rnc −0.479868*** 0.029212 −0.905958*** 1.000000 ecog 0.013751 0.143885*** 0.026408 0.049562** 1.000000 urb −0.564737*** 0.109122*** 0.029510 0.026688 0.070928** 1.000000 trade −0.284119*** −0.009299 0.152551*** −0.234920*** 0.060638*** 0.213674*** 1.000000 ***,**,*present significance level 1%, 5% and 10% respectively. ali, et al.: natural resources depletion, renewable energy consumption and environmental degradation: a comparative analysis of developed and developing world international journal of energy economics and policy | vol 11 • issue 3 • 2021260 table f: correlation matrix of developing countries variables lco2 nrd fec rnc ecog urb trade lco2 1.000000 nrd 0.056704* 1.000000 fec 0.525524*** 0.169668*** 1.000000 rnc −0.457281*** −0.142218*** −0.965798*** 1.000000 ecog 0.077338** 0.095036*** 0.055485* −0.005238 1.000000 urb −0.548379*** 0.110936*** 0.031260 −0.052422 0.044887 1.000000 trade −0.208439*** 0.048308 0.223631*** −0.299810*** 0.071114** 0.293726*** 1.000000 ***,**,*present significance level 1%, 5% and 10% respectively. table d: correlation matrix of developed countries variables lco2 nrd fec rnc ecog urb trade lco2 1.000000 nrd −0.076659** 1.000000 fec 0.236281*** −0.121049*** 1.000000 rnc −0.458658*** 0.511049*** −0.705458*** 1.000000 ecog −0.034954 0.012424 0.068933* −0.021170 1.000000 urb −0.585457*** −0.068220* 0.084280** 0.140012*** 0.079084** 1.000000 trade −0.503436*** −0.043973 −0.030118 −0.027952 0.118733*** 0.129119*** 1.000000 ***,**,*present significance level 1%, 5% and 10% respectively table c: descriptive statistic of developed countries lco2 nrd fec rnc ecog urb trade mean 11.72516 0.662743 78.45416 15.08113 2.112794 24.08287 74.70251 median 11.21516 0.168449 81.92648 9.013570 2.395094 22.66940 67.65734 maximum 15.57160 10.06595 98.52626 61.37896 11.44974 53.04243 208.1709 minimum 8.923993 0.000000 29.77475 0.608264 −13.99821 5.412514 16.01388 sd 1.380310 1.383562 15.86426 13.46952 3.109870 11.87727 34.68962 skewness 0.676691 4.078147 −1.073002 1.422437 −1.082657 0.393413 1.019593 kurtosis 3.155462 22.20307 3.451572 4.915821 6.790323 2.352440 3.909653 jarque-bera 54.12785 12695.75 140.2698 343.1072 555.7748 30.28753 145.4177 sum 8207.611 463.9199 54917.91 10556.79 1478.956 16858.01 52291.75 sum sq. dev. 1331.774 1338.056 175920.6 126818.2 6760.231 98607.69 841155.7 observations 700 700 700 700 700 700 700 table e: descriptive statistic of developing countries lco2 nrd fec rnc ecog urb trade mean 11.08131 4.280393 71.33698 29.14674 3.927667 26.91641 67.46766 median 11.03136 1.996871 79.61963 20.67226 4.465166 24.88514 59.44135 maximum 16.14687 43.65421 100.0000 94.98880 34.50000 74.56980 220.4074 minimum 6.562064 0.011899 3.780881 0.000000 −34.80864 2.867021 13.75305 sd 1.838072 6.114472 24.92197 26.28026 5.671801 13.69427 33.94109 skewness 0.069214 2.910549 −0.841241 0.773166 −1.364520 0.596533 1.276772 kurtosis 2.650774 12.83265 2.670846 2.476796 16.74007 3.419692 5.390610 jarque−bera 5.586034 5168.243 115.8490 105.4850 7767.727 63.31535 484.3261 sum 10527.25 4066.373 67484.78 27689.40 3731.283 25570.59 64094.27 sum sq. dev. 3206.206 35480.05 586943.7 655428.8 30528.69 177968.9 1093246. observations 950 950 946 950 950 950 950 list of selected countries argentina, australia, austria, azerbaijan, bangladesh, belarus, belgium, benin, brazil, bulgaria, cambodia, cameroon, canada, chile, china, colombia, costa rica, cote d’ivoire, croatia, denmark, ecuador, egypt, el salvador, finland, france, germany, greece, hungary, india, indonesia, iran, ireland, israel, italy, jamaica, japan, jordan, kuwait, macedonia, malaysia, mexico, morocco, netherlands, new zealand, nigeria, norway, oman, pakistan, peru, philippine, poland, portugal, romania, russian federation, saudi arabia, south africa, spain, sri lanka, sweden, switzerland, thailand, tunisia, turkey, ukraine, united kingdom, united states. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 3 • 2023374 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(3), 374-383. electricity consumption and population growth in south africa: a panel approach nyiko worship hlongwane*, olebogeng david daw school of economics, north-west university, south africa. *email: nyikowh@gmail.com received: 25 march 2022 accepted: 15 march 2023 doi: https://doi.org/10.32479/ijeep.13044 abstract this study investigates the relationship between population growth and electricity consumption in south africa for the period from 2002 to 2021 collected from statssa. the study utilises seemingly unrelated regression model and dumitrescu and hurlin (2012) causality tests to analyse the relationship between the variables. empirical results revealed that there is a negative statistically significant relationship between population growth and electricity consumption in south africa. the results further reveal one-way causality running from population growth to electricity consumption. the study recommends that the government and policy makers must implement policies aimed at increasing renewable electricity generation to match the gap between electricity demand and growing population thereby reducing constant loadshedding in south africa. keywords: electricity consumption, population growth, seemingly unrelated regression model, eskom, south africa jel classifications: c33, h20, o04, o25 1. introduction electricity is the backbone of an economy to grow in most societies today. south africa has been marred with continuous loadshedding that has resulted from poor electricity generation that fails to meet the overgrowing electricity demand. the impact of loadshedding has resulted in some of the households having to find alternative sources of energy such as wood fuel in the rural areas, gas, and solar systems. this has also resulted in electricity consumption declining as people switch to alternative sources of energy. lenoke (2017), khobai and le roux (2017), khobai (2018a), hlongwane and daw (2021), stungwa et al. (2022) has conducted a study on electricity consumption but their studies was much focusing on the relationship between electricity consumption and economic growth. electricity consumption is predicted to rise over next few decades. increasing demand for electricity poses a problem to south africa’s administration because it relates to a significant reliance on expensive fuel imports. the study of primary factors of electricity consumption in south africa will contribute to a better understanding and description of the nature of aggregate electricity consumption, as well as an endeavour to build a solid electricity policy. 1.1. overview of the study there are insufficient studies focusing on the relationship between population growth and electricity consumption in south africa and the significance of this study is to investigate on that nexus. electricity infrastructure is divided into three sub-sectors: generation, transmission, and distribution. in terms of generation, eskom is the market leader in the production of power. eskom generates, transmits, and distributes electricity in south africa to industrial, mining, commercial, agricultural, mining, commercial, agricultural, and residential clients, as well as municipalities, which redistribute electricity to companies and homes within their jurisdictions (ratshomo and nembahe, 2019). in addition, the utility acquires power from independent power producers (ipps) under different agreement schemes, as well as electricity generating facilities located outside of the country’s boundaries. electricity is the backbone of the south african economy, and it is a critical industry that generates employment and value by this journal is licensed under a creative commons attribution 4.0 international license hlongwane and daw: electricity consumption and population growth in south africa: a panel approach international journal of energy economics and policy | vol 13 • issue 3 • 2023 375 extracting, processing, and delivering energy commodities and services across the country. south africa’s consistent economic expansion, along with an increased emphasis on industrialisation and a mass electrification initiative to provide power to deep rural regions, has resulted in a sharp increase in electricity consumption in recent years. modise and mahotas (2020); ratshomo and nembahe (2019) and gabrielle (2020) summarizes that residential was accountable for 8%, commerce and public services 14%, agriculture 6%, transport sector 19%, industry sector 52% and 1% was not specified in terms of electricity consumption in south africa in 2016. residential sector accounted for 72% of electricity consumption in south africa according ratshomo and nembahe (2019). population has been increasing but electricity consumption has not been increasing enough to match with the population. figure 1 below shows the sum of population growth and electricity consumption in nine provinces in south africa. figure 1 above shows the sum of population growth and electricity consumption by province from 2002 to 2021. according to figure 1, gauteng has the highest electricity consumption followed by kwazulu-natal, mpumalanga, and western cape province in terms of total gigawatt hours consumed. this is because gauteng is the main tertiary and industrial hub of south africa and holds a lot of population as compared to other provinces. in terms of the sum of population, gauteng has the highest number, followed by kwazulu-natal, eastern cape, western cape, and limpopo province. in south africa we have a problem of high electricity consumption and high population growth, hence the significance of this study is to investigate the relationship between population growth and electricity consumption in south africa. this will enable the policy makers, government, and eskom to know how much electricity they should generate to meet the increasing consumption from the growing population. 2. literature 2.1. theoretical literature the theoretical that underpins the investigation is presented in this section of the study. this study focuses on the growth theories in greater depth. malthus (1798) believed that population increase will outpace the earth’s ability to produce food, resulting in humanity’s destitution. solow (1956) underlined in a research that contributed to economic growth theory that a country with faster population growth rates will have lower levels of capital and income per worker in the long run. according to kremer (1993), population expansion leads to economic growth. more people in the country equals more geniuses, scientists, and engineers, which lead to quicker technical advancement (stungwa and daw, 2021). this study, however, tries modifying the growth theories by making electricity consumption depend on population growth and economic growth in south africa to investigate the nature of relationship that exists among the variables. 2.2. a review of developing countries mohanty and chaturvedi (2015) examine the weather electricity energy consumption on economic growth in indian using the annual data spanning 1970-1971 to 2011-2012. using granger causality test and engle-granger technique, their study suggested that electricity energy consumption has a positive relationship on economic growth in the short run and long run. athukorala and wilson (2010) investigate it the short run dynamics and long run equilibrium relationship between the residential electricity demand and the factors influencing demand, like capita income, price of electricity, price of kerosene oil and price of liquefied petroleum gas using an onion data for sri lanka for the period of 1960 to 2007. the main findings of the paper were that increasing the price of electricity is not the most effective tool to reduce electricity consumption. niu et al. (2013) analyzed the causality between electricity consumption and human development and assesses the changing trend of electricity consumption. they have started employed panel data from 1990 to 2009 for 50 countries divided into four groups according to the income. for human development indicator, per capita gdp, consumption expenditure, urbanization rate, life expectancy at birth and the adult literacy rate was selected. the result from the study demonstrated long run bidirectional causality existing between electricity consumption and five indicators. the study further suggested, to enhance human development, the electricity should be incorporated into the basic public services construction to improve the availability of electricity for low-income residents. ouédraogo (2010) examined the direction of causality between electricity consumption and economic growth in burkina faso for the period of 1968 to 2003. the bounce test yields evidence of cointegration between electricity consumption gdp and capital 0 50000000 100000000 150000000 200000000 250000000 300000000 e as te rn c ap e f re e s ta te g au te ng k w az ul un at al li m po po m pu m al an ga n or th w es t n or th er n c ap e w es te rn c ap e sum of population by province 2002-2021 0 500000 1000000 1500000 e as te rn c ap e f re e s ta te g au te ng k w az ul un at al li m po po m pu m al an ga n or th w es t n or th er n c ap e w es te rn c ap e sum of electricity consumption by province 2002 -2021 figure 1: sum of population and electricity consumption by province from 2002 to 2021 source: author’s own compilation using data from statssa hlongwane and daw: electricity consumption and population growth in south africa: a panel approach international journal of energy economics and policy | vol 13 • issue 3 • 2023376 formation when electricity consumption and gdp are used as dependent variables. the start argued that electricity is a significant factor in socio economic development in burkina faso, therefore energy policies must be implemented to ensure that electricity generates few potential negative impacts. bangladesh one of the largest populous countries in the world is being overwhelmed by an access demand of energy from the households, hence, debnath et al. (2015) investigated the bottom up approach towards modelling the aggregate energy demand of right households of bangladesh from 2010 to 2015. the energy demand pathway model demonstrated a significant rise in energy demand. lionel (2013) investigated the relationship between electricity supply and economic development in nigeria using an annual time series data from 1970-2009. the paper employed error correction model for empirical analysis of the study. the results showed that per capita gdp, lagged electricity supply, technology, cut it down at the significant variables that influence economic development in nigeria. electricity supply has an influence in economic development in nigeria, but its impact is very low. jamil and ahmad (2010) investigated the relationship between electricity consumption, electricity prices and economic growth in pakistan. the study employed annual time series data spanning for the period from 1960 to 2008. the study employed a vector error correction model (vecm) and granger causality test to analyse the relationship between the variables in pakistan. empirical results revealed short run positive relationship between electricity consumption and economic growth in pakistan. granger causality results revealed unidirectional causal relationship from economic growth to electricity consumption that indicates economic growth stimulates electricity consumption in the long run. the researchers recommend that it is essential for pakistan policymakers to plan and increase infrastructure development to meet increasing electricity demand. the researchers also recommend that government should adopt policies to sustain electricity supply. hussain et al. (2016) forecasted electricity consumption in pakistan. the study borrowed available annual time series data spanning for the period from 1980 to 2011. the study employed holt-winter and autoregressive integrated moving average (arima) models to forecast electricity consumption in pakistan. the empirical results revealed that electricity demand is higher in the household sector than in other sectors and that electricity generation would be lesser than the increase in electricity generation. the researchers recommend that policymakers should focus on shortand longterm projects such as renewable sources of electricity to balance the supply-demand gap in pakistan. da silva et al. (2016) investigated electricity supply security and the future role of renewable energy sources in brazil. the researchers found that hydroelectricity generation is the backbone of electricity supply in brazil. the recent drought exposed the exposed vulnerability of electricity supply and drew significant immediate attention to address power outages. the researchers highlight that brazil faces considerable increases in electricity consumption and policy makers should focus on renewable energy sources to balance energy supply and reduce dependence on hydroelectric power. osman et al. (2016) conducted a study on electricity consumption and economic growth in the gcc countries. the study borrowed available annual panel data spanning from 1975 to 2012. the study employed panel estimation techniques to analyse the relationship between the variables. empirical results revealed positive results between the variables both in the short and long run period. the researchers recommend that if these countries adopt or implement policies that conserve electricity, this will have negative impact on economic growth of these countries. salahuddin and alam (2016) conducted a study on information and communication technology, electricity consumption and economic growth in oecd countries. the study borrowed available annual panel data spanning for the period from 1985 to 2012. the study employed panel estimation techniques to analyse the relationship between the variables. empirical results revealed that electricity consumption boost economic growth. based on empirical results, the researchers recommend the adaption of technologies that promotes efficiency electricity consumption to reduce hazards arising from electricity consumption. zhang et al. (2017) investigated electricity consumption and economic growth in china. the study utilises available literature spanning from 1978 to 2016 that focuses on electricity generation and economic growth. the study reveals that vector error correction model (vecm) and vector autoregressive (var) model are the most employed models in the analysis. the study revealed that there is interaction between electricity consumption and economic growth. the researchers stresses that due to employment of different models, the results are not the same. the researchers recommend that china should increase the renewable sources of electricity to balance the strain on electricity supply and maintain environmentally friendly status. ouedraogo (2017) modelled sustainable long-term electricity supply-demand in africa. the study employed the systembased approach developed by schwartz in the context of long-range alternative planning. the results revealed that despite the increase in the electricity generation, the demand for electricity will still be prevailing by 2030 and 2040 implying the insufficient in electricity supply. the researchers suggest that energy efficiency policies should be implemented to reduce the high energy consumption levels in africa. shahbaz et al. (2017) conducted a study on the dynamics of electricity consumption, oil price and economic growth on a panel global perspective. the study borrowed available annual panel data for 157 countries spanning from 1960 to 2014. the study employed panel estimation techniques to analyse the relationship between the variables. empirical results revealed a short run positive relationship of electricity consumption on economic growth. the researchers reveals that more vigorous policies on electricity to be implemented to attain sustainable long run economic growth. the study recommends electricity conversion policies to trigger economic growth. belaid and youssef (2017) conducted a study on environmental degradation, renewable and non-renewable electricity consumption on economic growth in algeria. the study borrowed annual time series data spanning from 1980 to 2012. the study employed an autoregressive distributed lad model and granger causality test to analyse the relationship between the variables in algeria. empirical results revealed a unidirectional long run causality between the variables. the study recommends hlongwane and daw: electricity consumption and population growth in south africa: a panel approach international journal of energy economics and policy | vol 13 • issue 3 • 2023 377 that investment in renewable electricity will boosts economic growth that will help fight unemployment in algeria. dey and tareque (2019) investigates the electricity consumption and gross domestic product nexus in bangladesh. the study borrowed the available time series data spanning from 1971 to 2014. the study employs an autoregressive distributed lag model to analyse the relationship between bangladesh’s electricity consumption and economic growth. empirical results revealed a positive relationship between electricity consumption and economic growth both in the short and long run period. the researchers recommend that electricity generation and conservation policy will be effective in bangladesh. shahbaz (2015) examined the impact of electricity shortage on sectoral gdp such as agriculture, industrial and service sectors in the case of pakistan for the period of 1991 to 2013. the ordinary least squared (ols) was used for empirical analysis of the study. the results from the study demonstrated that electricity shortage is inversely linked with it agricultural sector output, and the result further showed that industrial the sector output is inversely affected by electricity shortage. ha and ngoc (2021) revisits the relationship between energy consumption and economic growth in vietnam. the study borrowed available annual time series data spanning for the period from 1971 to 2017. the study employs an asymmetric autoregressive distributed lag model to analyse the relationship between the variables. the empirical results revealed that the negative impacts are greater than the positive impacts both in the short and long run of electricity consumption on economic growth in vietnam. the researchers recommend that the government should encourage enterprises and people to use intelligent equipment and low electricity consumption machines while adopting renewable energy sources as an alternative. 2.3. a review of developed countries kahouli (2018) investigated the causal relationship between electricity consumption, co2 emissions, research and development stocks and economic growth of mediterranean countries. the study borrowed annual panel data spanning for the period from 1990 to 2016. the study employed panel estimation techniques to analyse the relationship between the variables. the empirical results revealed that electricity consumption boosts economic growth in the mediterranean countries. the researchers recommend that policymakers should implement policies of electricity that are environmentally friendly. bekhet and bt othman (2011) investigated the relationship between electricity consumption, consumer price index, gross domestic product, and foreign indirect investment for period of 1971 to 2009. the vector error correction model was employed to estimate the causal relationship between electricity consumption with respective independent variables. the results demonstrated that electricity consumption what is the cointegrated with all their respective independent variables. the results further showed that there long-run causality from electricity consumption to fdi, gdp growth and inflation was found to be significant. in greece, marques et al. (2014) investigated the relationship between electricity generation and economic growth. data from august 2004 to october 2013 were used in the study. to examine the relationship between the variables, researchers used a vector error correction model. the findings showed that convectional fossil fuels have a short-term positive impact on economic growth. other findings revealed that there is no link between renewable energy and economic growth in the short and long term. to boost economic growth, the study suggests that greek technology be integrated into renewable electricity generation. marques et al. (2016) investigated the relationship between the mix of electricity generation and economic growth in france. from january 2010 to november 2014, the study used monthly time series data. the relationship was investigated using an autoregressive distributed lag model. according to empirical findings, nuclear energy promotes economic growth in france, whereas renewable energy is detrimental to economic growth. according to the researchers, policymakers in france should be aware that any reduction in nuclear power is harmful to economic growth. kirikkaleli et al. (2021) conducted a study on nuclear energy consumption and economic growth in the united kingdom. the study employed annual time series data spanning from 1998 to 2017. the study employed a toda yamamoto causality and wavelet coherence test to analyse the relationship between the variables. the empirical results revealed that there is a positive correlation between nuclear energy consumption and economic growth in the united kingdom. furthermore, the study highlight that it is critical for the united kingdom policymakers to create developmentfocused techniques and processes to build the economy from environmentally sustainable sources. al-bajjali and shamayleh (2018) investigated the determinants of electricity in jordan for the period from 1986 to 2015. the study employed a vecm model and found that gdp, population growth, urbanization, structure of economy and aggregate water consumption are positive statistically significant determinants of electricity consumption. zaman et al. (2012) conducted a study on the determinants of electricity consumption function in pakistan for the period from 1975 to 2010. the study employed a vecm granger causality test and found that population growth, income and investment have positive relationship with electricity consumption. huang (2015) investigated the determinants of household electricity consumption in taiwan from 1981 to 2011. the study employed quantile regression and found that household income and household size have a positive significant relationship with electricity consumption. bedir et al. (2013) conducted a study on the determinants of electricity consumption among the dutch dwellings and found that household activities such as household size, dwelling type, use of dryer, washing cycles and several showers explains the variation in electricity consumption. kwakwa (2018) investigated the determinants of electricity consumption in ghana for the period from 1971 to 2014. the study employed an ardl model and found that population, urbanization, education, and industrialisation positively affect electricity consumption while income negative impact electricity consumption. sharma and kautish (2019) investigated the macroeconomic determinants and electricity consumption in india for the period from 1980 to 2015. the study employed an nardl model and found that gdp has a positive impact on electricity consumption in india. kwakwa (2017) conducted hlongwane and daw: electricity consumption and population growth in south africa: a panel approach international journal of energy economics and policy | vol 13 • issue 3 • 2023378 a study on electricity consumption in egypt analysing the long-run effects. the study employed a fully modified ols model on the data for the period from 1971 to 2012 and found that income, urbanisation, financial development, trade, and education positively impact electricity consumption. ubi et al. (2012) conducted an econometric analysis of the determinants of electricity supply in nigeria for the period from 1970 to 2009. the study employed an ecm model and found that technology, government funding and the level of power loss were statistically significant determinants of electricity supply in nigeria. louw et al. (2008) conducted a panel study on the determinants of electricity demand for newly electrified low-income african households. the results from the study found that income, wood fuel usage, iron ownership and credit obtained were significant in determining the consumption levels within these households. 2.4. a review of south africa bekun et al. (2019) investigated the relationship between energy consumption, carbon emissions and economic growth in south africa. the study borrowed available annual time series data spanning for the period from 1960 to 2016. the study employed granger causality test to analyse the relationship between the variables in south africa. the results revealed a positive relationship between electricity consumption and economic growth in south africa. the researchers recommend that the electricity conservation policies harm economic growth. khobai (2018b) investigated causal linkages between renewable electricity generation and economic growth in south africa. the study utilised quarterly time series data spanning from first quarter in 1997 to fourth quarter in 2012. the study employed a vector error correction model and granger causality tests to analyse the relationship between the variables. the empirical results reviewed a unidirectional causality running from electricity generation to economic growth and that electricity generation from renewable energy source enhances economic growth. the researchers recommend that the south african government should make appropriate effort to select energy policies that do not negatively affect economic growth. bhattacharya et al. (2016) analyses the relationship between renewable energy consumption on economic growth in 38 oecd countries. the study covered the period from 1991 to 2012 and employed a full modified ordinary least squares method to analyse the relationship between the variables. the results from the study revealed that renewable energy sources and non-renewable energy consumption had a negative effect on economic growth in south africa. menyah and wolde-rufael (2010) analysed the relationship between energy consumption, pollutant emissions and economic growth in south africa. the study covered the period from 1965 to 2006 and employed a modified granger causality and ardl model to analyse the relationship between the variables. the results revealed that energy consumption is negatively related to economic growth in south africa. from the literature above, majority of the studies that were conducted focused on the relationship between electricity consumption and economic growth, and there is limited to insufficient studies that focuses on the relationship between population growth and electricity consumption in south africa. this study therefore investigates the relationship between population growth and electricity consumption by utilising economic growth as an intermittent variable. 3. methodology 3.1. model specification the study investigates the relationship between population growth and electricity consumption in nine provinces in south africa by utilising gross domestic expenditure as intermittent variable to formulate a multivariate model. the variables are transformed into logarithms to have the same unit of measurement and avoid problems of spurious regressions. these variables were adopted from the study conducted by al-bajjali and shamayleh (2018) and zaman et al. (2012) on the determinants of electricity consumption in jordan. the study utilises a simple linear model given in the equation 1 below: lelc lpop lgdpt lpop t lgdp t t= + + +α α α ε0 (1) whereby, lelc represents the logged electricity consumption, lpop is the logarithm of population growth, lgdp is the logarithm of gross domestic product, εt and α0 is the error term and constant. 3.2. data sources the study utilises the annual time series data spanning for the period from 2002 to 2021 for electricity consumption, population and gross domestic product collected from quantec and statistics south africa (statssa). 3.3. data analysis the study employs a basic linear seemingly unrelated regression (sur) model developed by moon and perron (2006) to analyse the relationship between population growth and electricity consumption in south africa. suppose that yit is a dependent variable, ' ,1 ,2 , 1(1, , , ., )−= …it it it it kix x x x is a k i – vector of explanatory variables observational unit i, and uit is unobservable error term, where the double index it denotes the tth observation of the ith equation in the system, t denotes the time dimension. the classical linear sur model is a system of linear regression equations as given below: y xit t t= +β µ'1 1 1 (2) y xnt n nt nt= +β µ' (3) whereby, i=1,….,n and t=1,…,t denote l=k1+…+kn this study however modifies the simple sur model to a multivariate regression with parameter restrictions since this study employs more variables as proposed by moon and perron (2006). in this modification, ' ' ' 1 2[ , , , ' ]= …t t t ntx x x x and a (β)=diag (β1,…, βn) to be (l×n) block diagonal matrix. the multivariate sur model can therefore be rewritten as given below: y a x ut t t= ( ) +β ' (4) where the coefficient a(β) satisfies: vec a gβ β( )( ) = (5) hlongwane and daw: electricity consumption and population growth in south africa: a panel approach international journal of energy economics and policy | vol 13 • issue 3 • 2023 379 for some (nl×l) full rank matric g. in a special case where k1=…=kn=k we have 1( , , )= … ⊗n kg diag i i i where ij denotes the j’th column of the n×n identity matrix in. in the errors of ut are assumed to be iid overtime with mean zero and homoscedastic variance ∑= e xt t( , )'µ µ . we assume that ∑ is positive definite and denote by σij the (i, j) th element of ∑ that is σij = ( , ) '∝ ∝t t x . 3.4. the dumitrescu-hurlin causality test dumitrescu and hurlin (2012) provide an extension of granger (1969) causality test designed to detect causality in panel data. the underlying regression is: , , , , 1 1 1, , 1, , α γ β ε− − = = = + + + = … = … ∑ ∑ k k i t i ik i t k ik i t k i t k k y y x with i n and t t (6) whereby, xi,t and yi,t are the observations of two stationary variables for individual i period t. coefficients are allowed to differ across individuals but are assumed to be time invariant. the lag order of k is assumed to be identical for all individuals, and the panel must be balanced. as given in granger (1969), the procedure to determine the existence of causality is to test for significant effects of past values of x on the present value of y. the null hypothesis is therefore defined as: 0 1: 0 1, ,β β=…= = ∀ = …i ikh i n (7) which correspond to the absence of causality for all individuals to the panel. the dh test assumes there can be causality for some individuals but not necessarily for all. thus, the alternate hypothesis is: 1 1 1: 0 1, ,β β=…= = ∀ = …i ikh i n (8) 1 10 .. 0 1, , β β≠ …… ≠ ∀ = + …i ikor or i n n where n1 ∈ (0, n–1) is unknown. if n1=0, there is causality for all individuals in the panel. n1 must be strictly smaller than n, otherwise, there is no causality for all individuals, and h1 reduces to h0. in opposition of the above notion, dumitrescu and hurlin (2012) proposes the following procedure: run the n individual regressions implicitly encloses in equation 5, perform f tests of the k linear hypothesis βi1=…=βik=0 to retrieve the individual wald statistic wi, and finally compute the average wald statistic w :1 w n w i n i= = ∑ 1 1 (9) lopez and weber (2017) emphasizes that the test is designed to detect causality at panel level and rejecting h0 does not exclude noncausality for some individuals. following monte carlo simulations, dumitrescu and hurlin (2012) show that w is asymptotically well behaved and can genuinely be used to investigate panel causality. under the assumption that the wald statistics wi are independent and identically distributed across individuals, it can be shown that the standardized statistic z when t→∞ first and then n→∞ (sometimes interpreted as t should be large relative to n) follows a standard normal distribution: ( ) ( ) 0,1 2 , = × − → → ∞ n d z w k n k t n (10) the testing procedure of the null hypothesis finally based on z and z . if these are larger than the standardized critical values, then lopez and weber (2017) highlight that the null hypothesis (ho) must be rejected and conclude that granger causality exists. for large n and t panel datasets, z can be reasonably considered and for large n but relatively small t datasets, z should be favoured. the study therefore continues to provide the results and interpretations as shown in section 4 below. 4. results and interpretation the study performed a panel unit root test as shown in table 1 above by employing the levin, lin, and chu test, im, pesaran, and shin test and adf-fisher test. the results shows that lelc and lgdp are integrated of i(1) while lpop is integrated of i(0). the study therefore continues to perform the panel cointegration test as shown in table 2 below to determine long run relationships among the variables. table 2 above shows the cointegration results of pedroni (1999) and kao (1999). the results of pedroni (1999) are separated into two sections: within the dimension and between dimensions. the null hypothesis of pedroni (1999) stress that there is no cointegration between the variables. within the dimension, panel rho-statistic, pp-statistic and adf-statistic are all significant at 1% level of significance. as a result, the null hypothesis cannot be accepted and the conclusion the conclusion that cointegration exists is reached. because the four tests were a tie, the study cannot establish that there is cointegration without testing the between dimensions. the results of the between dimensions confirms presence of cointegration since the group rho-statistic (0.0783) is statistically significant. the group pp-statistic and adf-statistic are also significant at 1% level of significance. the table 1: unit root test variable llc ips adf-fisher constant constant and trend constant constant and trend constant constant and trend lelc −2.41460*** −2.76476*** −1.34980* −0.77465 24.6673 23.7009 lpop −8.60690*** 7.21015 −5.13018*** 6.15673 61.1092*** 3.08208 lgdp −5.24503*** 8.69102 −0.96851 9.46007 27.3829* 2.28978 dlelc −7.00055*** −8.96537*** −6.13912*** −6.88326*** 72.3898*** 74.7454*** dlgdp 3.83358 5.50667 −3.35001*** −2.70020*** 50.1112*** 43.8120*** source: author’s own computation hlongwane and daw: electricity consumption and population growth in south africa: a panel approach international journal of energy economics and policy | vol 13 • issue 3 • 2023380 the study performed the sur model to show long run relationship among the variables in the model as given in table 4 above when lelc is a dependent variable explained by lpop and lgdp. the results shows that there is a negative statistically significant relationship between population growth and electricity consumption in south africa. a 1% increase in population growth in south africa, will significantly result in electricity consumption declining by 0.09%, ceteris paribus. these results are inconsistent with the studies conducted by al-bajjali and shamayleh (2018), zaman et al. (2012) and huang (2015) that found a positive relationship between population growth and electricity consumption. this means that an increase in population growth in south africa has a detrimental effect on electricity consumption. this may be a result of people in south africa using alternative sources of energy. the recent load shedding affecting south africa since 2009 has resulted in the people switching to alternative sources of energy such as paraffin, firewood, gas, solar and biogas for their daily activities. therefore, policies that results in increase in electricity consumption might have a detrimental effect on the environment and people resulting call to switch to greener energy as eskom is heavily reliant on non-renewable sources of energy. the results further shows that there is a positive statistically significant relationship between economic growth and electricity consumption in south africa. a 1% increase in economic growth in south africa, will significantly result in electricity consumption increasing by 0.01, ceteris paribus. these results are consistent with the studies conducted by huang (2015), albajjali and shamayleh (2018) and zaman et al. (2012) that found that economic growth has a positive relationship with electricity consumption. this entails that increase in economic growth result in an increase in electricity consumption since firms will be expanding the scale of their activities and industries requiring more electricity to cater for increasing demand in electricity. this calls for policy makers and the government to implement policies that results in an increase in renewable electricity generation to match with the growing electricity demand from economic growth. the durbin-watson statistic is greater than the r-squared which means the regression is not spurious. the r-squared is 0.45%, meaning 45% of the variation in electricity consumption is explained by population growth and economic growth in south africa. the adjusted r-squared is 0.41, meaning that 41% is adjusted for the degrees of freedom. the study therefore continues to perform the cross-section dependence as shown in table 5 below. table 2: panel cointegration test method pedroni residual cointegration test statistic probability h1: common ar coefs. (within dimensions) panel v-statistic −0.342178 0.6339 panel rho-statistic −2.664407 0.0039 panel pp-statistic −9.403298 0.0000 panel adf-statistic −8.329954 0.0000 h1: individual ar coefs. (between dimension) group rho-statistic −1.416709 0.0783 group pp-statistic −10.30917 0.0000 group adf-statistic −7.184155 0.0000 kao residual cointegration test t-statistic probability h0: no cointegration adf −3.520705 0.0002 residual variance 0.000673 hac variance 0.000116 source: author’s own computation table 3: durbin-watson test estimated models dw-statistics conclusion fixed effects model 2.300624 no autocorrelation random effects model 2.099321 no autocorrelation seemingly unrelated regression 2.060358 no autocorrelation source: author’s own computation table 4: cross-section seemingly unrelated regression on electricity consumption, population, and economic growth variables coefficients std. error t-statistics probability lpop −0.086142 0.211732 -3.963758 0.0001 lgdp 0.012592 0.005352 2.352653 0.0199 intercept 0.578315 0.145299 3.980178 0.0001 r-squared adjusted r-squared durbin-watson stat prob (f-statistic) 0.449260 0.412787 2.060358 0.000000 source: author’s own computation results of kao (1999) also confirms that there is cointegration within the variables in the model since the adf probability value is significant at 1% implying the rejection of the null hypothesis of no cointegration. the study therefore continues to perform the durbin-watson test to detect autocorrelation as shown in table 3 below. the study begins by using the dw statistics to check for autocorrelation of the residuals sequence of fixed effects model (fem), random effects model (rem) and cross-section seemingly unrelated regression (sur). the results are presented in table 3 above and the dw statistics for fem, rem and sur are >2, implying that there is no presence of autocorrelation in the residuals when fem, rem and sur are used to investigate the relationship between total population, economic growth, and electricity consumption in the nine south africa provinces. after some diagnostic tests, the results of the fem and rem models cannot be accepted due to presence of heteroskedasticity and non-normal residuals, therefore, the study will employ the cross-section seemingly unrelated regression to analyse the relationship between electricity consumption, total population, and economic growth in south africa. hlongwane and daw: electricity consumption and population growth in south africa: a panel approach international journal of energy economics and policy | vol 13 • issue 3 • 2023 381 table 5: cross-section dependence on sa provinces test statistics d.f. probability breusch-pagan lm 1.877601 36 1.0000 pesaran scaled lm −4.021363 0.0001 bias-corrected scaled lm −4.286069 0.0000 pesaran cd 0.006560 0.9948 source: author’s own computation figure 2: histogram normality test source: author’s own compilation table 6: pairwise dumitrescu hurlin panel causality tests pairwise dumitrescu hurlin panel causality test lags: 1 null hypothesis w-stat zbar stat. probability lpop does not homogeneously cause lelc lelc does not homogeneously cause lpop 2.80584 1.11709 2.69216 −0.05989 0.0071 0.9522 lgdp does not homogeneously cause lelc lelc does not homogenously cause lelc 0.61155 1.09725 −0.88527 −0.11070 0.3760 0.9119 lgdp does not homogenously cause lpop lpop does not homogenously cause lgdp 12.6464 2.57784 18.3071 2.25045 0.0000 0.0244 source: author’s own computation the study performed cross-sectional dependence test as shown in table 5 above. when there is presence of cross-sectional dependence across the panels, this impact on the efficiency of estimators and leads to biased results. the null hypothesis is that there is no cross-sectional dependence among residuals of the variables in the model. the results of breusch and pagan (1980) are reliable since it is good and powerful when time period (t) is greater than the cross-sectional dimension (n), while the pesaran (2015) is perfect when either n is big or small (stungwa and daw, 2021). the probability values of the breusch-pagan lm (1.0000) and pesaran cd (0.9948) are >5% implying that we fail to reject the null hypothesis cross-sectional dependence and concluding that there is cross-sectional independence between the cross-sectional units. this entails that the south africa provinces are independent of each other when it comes to the relationship between electricity consumption, population growth and economic growth. the study continues to perform the residual normality test as shown in figure 2 below. the study performed the residual normality test as shown in figure 2 above. the value of the jarque-berra is 1.272486 and its corresponding probability value is 0.529277 meaning that we fail to reject the null hypothesis that the residuals are normally distributed. this means that the results from the model are reliable since the residuals are normally distributed that is consistent with the prior expectations of a normal ols regression model. the study continues to perform the dumtrescu hurlin causality test as shown in table 6 below to check for causal relationships among the variables in the model. the study performed the pairwise dumitrescu hurlin panel causality test as shown in the table 6 above to check for causal relationship among the variables. the study employed 1 lag to check is the effect of the previous year on explanatory variables have an impact in the presence results of the electricity consumption in south africa. the results reveals that there is unidirectional causality running from population growth to electricity consumption since the probability values is 0.0071 which is significant at 1% level of significance. these results are consistent with the study that was conducted by al-bajjali and shamayleh (2018) that found that population granger causes electricity consumption. the results show bidirectional causality between economic growth and population growth in south africa since the probability values are 0.0000 and 0.0244 which are statistically significant at 1% and 5% level of significance, respectively. this means that policies that affect economic growth and population growth will have causal effect on each other. the results reveal absence of causality between economic growth and electricity consumption since the probability values (0.3760 and 0.9119) are insignificant at 1%, 5% and 10% level of significance. this means that policies that affect economic growth will not have causal effect on electricity consumption and vice versa. the study therefore continues to give the conclusion and recommendations of the study as shown in section 5 below. hlongwane and daw: electricity consumption and population growth in south africa: a panel approach international journal of energy economics and policy | vol 13 • issue 3 • 2023382 5. conclusion and recommendations the study examined the relationship between population growth and electricity consumption using economic growth as an intermittent variable and discovered that population growth and economic growth are significantly related to electricity consumption in south african provinces in both negative and positive ways, respectively. the study employed a seemingly unrelated regression model using panel data spanning the years 2002-2021. the panel unit root test was used in the study to establish the order of cointegration and to assist prevent the problem of spurious regressions. the study used the cross-section dependence diagnostic test and discovered that the provinces are independent of one another, avoiding misleading findings and inefficient parameters. the residual normality test findings indicated that the residuals are normally distributed, which is compatible with the expectations of a normal ols model. the policy recommendations of this study are therefore as follows: firstly, the negative statistically significant relationship between population growth and electricity consumption calls for the policy makers, the government and eskom to speed up policies that increase renewable electricity consumption. this will help reduce reliance on non-renewable electricity consumption and leading to households altering to environmentally friendly sources of energy such as wind and solar. the government must increase investment in the wind farms in the eastern cape province and solar in the northern cape and limpopo provinces to take advantage of the abundant wind and higher temperature to generate electricity. secondly, the one-way causality from population growth to electricity consumption calls for the government, eskom and policy makers must audit on electricity consumption to reduce people who are illegally connected to the grid municipalities who does not pay for their electricity bills to comply and pay their debts. this will help reduce the problem of heavy debts on eskom, reducing financial problems and allowing eskom the opportunity to be able to produce electricity that matches with a growing population. thirdly, the positive relationship between economic growth and electricity generation calls for the policy makers to implement policies that result in an increase in electricity generation to match the growing demand in electricity consumption because of economic growth. the electricity is the backbone of an economy, electricity is needed to grow the economy. an increase in economic growth means the expansion of the activities of firms, households, and other sectors in the economy. most of the sectors in the economy depends on electricity for caring their daily activities such as in the primary, secondary and tertiary sectors. this growing in electricity demand because of economic growth then needs to be accounted for by an increase in electricity generation to avoid problems of constant load shedding that has recently marred the south african economy. fourthly, bidirectional causality between population growth and economic growth calls for the policymakers to revise policies aimed at increasing population growth. policies that will have an impact on population growth will also have a causal effect on economic growth. if the government implement policies that increase population growth, this will result in a causal effect on economic growth in south africa. this is what solow growth model allude when a countries are having the same population growth, saving rate and capital accumulation, then they have the same steady state, so they will converge. solow (1956) then alludes to say along the convergence path, a poorer country then grows faster. in conclusion, the study’s main objective was to investigate the relationship between population growth and electricity consumption in south africa by utilising economic growth as an intermittent variable. the objective was accomplished by the discovery of a negative relationship between population growth and electricity consumption and a positive relationship between economic growth and electricity consumption. this study therefore recommends that in future, the research should consider investigating the relationship between population growth and electricity consumption by employing the panel models and more variables such as unemployment, electricity generation and sectorial analysis to discover new knowledge in the field. references al-bajjali, s.k., shamayleh, a.y. (2018), estimating the determinants of electricity consumption in jordan. energy, 147, 1311-1320. athukorala, p.w., wilson, c. (2010), estimating short and long-term residential demand for electricity: new evidence from sri lanka. energy economics, 32, s34-s40. bedir, m., hasselaar, e., itard, l. (2013), determinants of electricity consumption in dutch dwellings. energy and buildings, 58, 194-207. bekhet, h.a., bt othman, n.s. (2011), causality analysis among electricity consumption, consumer expenditure, gross domestic product (gdp) and foreign direct investment (fdi): case study of malaysia. journal of economics and international finance, 3(4), 228-235. bekun, f.v., emir, f., sarkodie, s.a. (2019), another look at the relationship between energy consumption, carbon dioxide emissions, and economic growth in south africa. science of the total environment, 655, 759-765. belaid, f., youssef, m. (2017), environmental degradation, renewable and non-renewable electricity consumption, and economic growth: assessing the evidence from algeria. energy policy, 102, 277-287. bhattacharya, m., paramati, s.r., ozturk, i., bhattacharya, s. (2016), the effect of renewable energy consumption on economic growth: evidence from top 38 countries. applied energy, 162, 733-741. breusch, t.s., pagan, a.r. (1980), the lagrange multiplier test and its applications to model specification in econometrics. the review of economic studies, 47(1), 239-253. da silva, r.c., de marchi neto, i., seifert, s.s. (2016), electricity supply security and the future role of renewable energy sources in brazil. renewable and sustainable energy reviews, 59, 328-341. debnath, k.b., mourshed, m., chew, s.p.k. (2015), modelling and forecasting energy demand in rural households of bangladesh. energy procedia, 75, 2731-2737. dey, s.r., tareque, m. (2019), electricity consumption and gdp nexus in bangladesh: a time series investigation. journal of asian business and economic studies, 27, 35-48. dumitrescu, e.i., hurlin, c. (2012), testing for granger non-causality in heterogeneous panels. economic modelling, 29(4), 1450-1460. hlongwane and daw: electricity consumption and population growth in south africa: a panel approach international journal of energy economics and policy | vol 13 • issue 3 • 2023 383 gabrielle, d. (2020), the south african power sector energy insight. in: a.r.p.o.e.a.e., editors. growth. p1-11. granger, c.w. (1969), investigating causal relations by econometric models and cross-spectral methods. econometrica, 37, 424-438. ha, n.m., ngoc, b.h. (2021), revisiting the relationship between energy consumption and economic growth nexus in vietnam: new evidence by asymmetric ardl cointegration. applied economics letters, 28(12), 978-984. hlongwane, n.w., daw, o.d. (2021), the challenges and opportunities of electricity generation on economic growth in south africa: an ardl approach. germany: university library of munich. huang, w.h. (2015), the determinants of household electricity consumption in taiwan: evidence from quantile regression. energy, 87, 120-133. hussain, a., rahman, m., memon, j.a. (2016), forecasting electricity consumption in pakistan: the way forward. energy policy, 90, 73-80. jamil, f., ahmad, e. (2010), the relationship between electricity consumption, electricity prices and gdp in pakistan. energy policy, 38(10), 6016-6025. kahouli, b. (2018), the causality link between energy electricity consumption, co2 emissions, r&d stocks and economic growth in mediterranean countries (mcs). energy, 145, 388-399. kao, c. (1999), spurious regression and residual-based tests for cointegration in panel data. journal of econometrics, 90(1), 1-44. khobai, h. (2018a), electricity consumption and economic growth: a panel data approach for brazil, russia, india, china and south africa countries. international journal of energy economics and policy, 8(3), 283-289. khobai, h. (2018b), the causal linkages between renewable electricity generation and economic growth in south africa. germany: university library of munich. khobai, h., le roux, p. (2017), the relationship between energy consumption, economic growth and carbon dioxide emission: the case of south africa. international journal of energy economics and policy, 7(3), 102-109. kirikkaleli, d., adedoyin, f.f., bekun, f.v. (2021), nuclear energy consumption and economic growth in the uk: evidence from wavelet coherence approach. journal of public affairs, 21(1), e2130. kremer, m. (1993), the o-ring theory of economic development. the quarterly journal of economics, 108(3), 551-575. kwakwa, p.a. (2017), electricity consumption in egypt: a long‐run analysis of its determinants. opec energy review, 41(1), 3-22. kwakwa, p.a. (2018), an analysis of the determinants of electricity consumption in benin. journal of energy management and technology, 2(3), 42-59. lenoke, m. (2017), the impact of load shedding on the economic growth of south africa. south africa: north-west university. lionel, e. (2013), the dynamic analysis of electricity supply and economic development: lessons from nigeria. journal of sustainable society, 2(1), 1-11. lopez, l., weber, s. (2017), testing for granger causality in panel data. the stata journal, 17(4), 972-984. louw, k., conradie, b., howells, m., dekenah, m. (2008), determinants of electricity demand for newly electrified low-income african households. energy policy, 36(8), 2812-2818. malthus, t.r. (1798), an essay on the principle of population. printed for j. johnson. st. paul’s church-yard, london: 1-126. marques, a.c., fuinhas, j.a., menegaki, a.n. (2014), interactions between electricity generation sources and economic activity in greece: a vecm approach. applied energy, 132, 34-46. marques, a.c., fuinhas, j.a., nunes, a.r. (2016), electricity generation mix and economic growth: what role is being played by nuclear sources and carbon dioxide emissions in france? energy policy, 92, 7-19. menyah, k., wolde-rufael, y. (2010), energy consumption, pollutant emissions and economic growth in south africa. energy economics, 32(6), 1374-1382. modise, d., mahotas, v. (2020), department of energy: south african energy sector. pretoria: department of energy. p.1-12. mohanty, a., chaturvedi, d. (2015), relationship between electricity energy consumption and gdp: evidence from india. international journal of economics and finance, 7(2), 186-202. moon, h.r., perron, b. (2006), seemingly unrelated regressions. in: the new palgrave dictionary of economics. vol. 1. london: palgrave macmillan. p9. niu, s., jia, y., wang, w., he, r., hu, l., liu, y. (2013), electricity consumption and human development level: a comparative analysis based on panel data for 50 countries. international journal of electrical power and energy systems, 53, 338-347. osman, m., gachino, g., hoque, a. (2016), electricity consumption and economic growth in the gcc countries: panel data analysis. energy policy, 98, 318-327. ouédraogo, i.m. (2010), electricity consumption and economic growth in burkina faso: a cointegration analysis. energy economics, 32(3), 524-531. ouedraogo, n.s. (2017), modeling sustainable long-term electricity supply-demand in africa. applied energy, 190, 1047-1067. pedroni, p. (1999), critical values for cointegration tests in heterogeneous panels with multiple regressors. oxford bulletin of economics and statistics, 61(s1), 653-670. pesaran, m.h. (2015), testing weak cross-sectional dependence in large panels. econometric reviews, 34(6-10), 1089-1117. ratshomo, k., nembahe, r. (2019), the south african energy sector report 2019. p1-39. salahuddin, m., alam, k. (2016), information and communication technology, electricity consumption and economic growth in oecd countries: a panel data analysis. international journal of electrical power and energy systems, 76, 185-193. shahbaz, m. (2015), measuring economic cost of electricity shortage: current challenges and future prospects in pakistan. germany: university library of munich. shahbaz, m., sarwar, s., chen, w., malik, m.n. (2017), dynamics of electricity consumption, oil price and economic growth: global perspective. energy policy, 108, 256-270. sharma, r., kautish, p. (2019), dynamism between selected macroeconomic determinants and electricity consumption in india: an nardl approach. international journal of social economics, 46, 805-821. solow, r.m. (1956), a contribution to the theory of economic growth. quarterly journal of economics, 70, 65-94. stungwa, s., daw, o.d. (2021), infrastructure development and population growth on economic growth in south africa. germany: university library of munich. stungwa, s., hlongwane, n.w., daw, o.d. (2022), consumption and supply of electricity on economic growth in south africa: an econometric approach. international journal of energy economics and policy, 12(1), 266-274. ubi, p.s., effiom, l., okon, e.o., oduneka, a.e. (2012), an econometric analysis of the determinants of electricity supply in nigeria. international journal of business administration, 3(4), 72-82. zaman, k., khan, m.m., ahmad, m., rustam, r. (2012), determinants of electricity consumption function in pakistan: old wine in a new bottle. energy policy, 50, 623-634. zhang, c., zhou, k., yang, s., shao, z. (2017), on electricity consumption and economic growth in china. renewable and sustainable energy reviews, 76, 353-368. . international journal of energy economics and policy | vol 7 • issue 3 • 2017282 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(3), 282-286. a review on carbon emissions in malaysian cement industry b. bakhtyar1*, tarek kacemi2, md atif nawaz3 1school of economic, finance and banking, college of business, universiti utara malaysia, 06010 sintok, kedah darulaman, malaysia, 2school of economic, finance and banking, college of business, universiti utara malaysia, 06010 sintok, kedah darulaman, malaysia, 3school of economic, finance and banking, college of business, universiti utara malaysia, 06010 sintok, kedah darulaman, malaysia. *email: bakhtyar11@gmail.com abstract cement production is an energy and carbon-intensive process. hence, they are a noteworthy contributor to global anthropogenic co2 emissions. the cement industry has always been among the greatest co2 discharge sources with 900 kg co2 released with each production ton of cement. malaysia massive amount of biogenic wastes, palms oil fuel ash, rice husk ash, sawdust ash/ash from timber. around 0.3 million ton of palm oil fuel ash is produced every year in malaysia, yet there are no noteworthy employments uses of these ashes. disregarding malaysia technical and financial benefits, till date these ashes, are only used for landfill purposes. excessively dependent on this energy will lead to an expansion in co2 emission that consequently responsible for the global warming. researchers discover by substituting fossil fuels with alternative fuels will lead to lessening in carbon dioxide emissions. hence, we suggest that by eliminating legal, economic obstructions, co2 mitigation strategies can be applied on the extensive scale of the cement industry to a globally acceptable emission targets in each nation. furthermore, the relatively small number of participants signifies that an agreement for the cement market in malaysia can probably be reached easily between the parties in decreasing co2 emissions. keywords: carbon emission, cement industry, energy consumption jel classifications: q01, q53, q54 1. introduction world cement production has been growing relentlessly over many decades signifying around 2.31 gt in 2005. cement production addressed an extension of almost 300% from the 1970 s production levels and two-fold the aggregate production in 1990 (zhu, 2011). cement manufacturing, cement production is an energy and carbon-intensive process. consequently, cement production is a noteworthy contributor to global anthropogenic co2 emissions (bakhtyar et al., 2017). furthermore, the cement industry has always been among the greatest co2 discharge sources as 900 kg co2 released to the environment for producing one ton of cement (benhelal et al., 2013). 10 years of yearly increments of 4%, on average, was reduced to about 1% in 2012 and 2013, and further reduction in following years of 2014 as the growth in global co2 emissions practically slowed down, expanding by only 0.5% in 2014 (benhelal et al., 2012). not only co2 generation due to fossil fuels ignition in the cement production but carbon dioxide is also likewise delivered as by-product during disintegration reactions. according to olivier et al. (2015), in the 2014 year, emissions from fossil-fuel raging and common procedures (production of cement clinker, metals, and chemicals) come to 35.7 billion tons co2 in 2015, an aggregate sum of globally discharged co2 transmitted of 36.2 billion tons virtually the identical level as in 2014 (olivier et al., 2015). manufacturing cement involves blending small amounts of gypsum and anhydrite with finely ground clinker. co2 emission is discharged into the air amid the production of clinker and directly connected with the amount of clinker created. clinker is formed through a synthetic conversion process called calcination in which calcium carbonate isolated in a super-heated kiln producing lime and co2. according to ke et al. (2013), the direct co2 emissions from the calcination process in cement making are usually called cement process co2 emissions. cement production emits carbon dioxide co2 both directly and indirectly. in 2000, the cement industry released around 1.4 gt co2 (direct and indirect), which represented for ~5% of the worldwide anthropogenic co2 bakhtyar, et al.: a review on carbon emissions in malaysian cement industry international journal of energy economics and policy | vol 7 • issue 3 • 2017 283 emissions or 3% of the global anthropogenic greenhouse gas emissions (zhu, 2011). while, utilizing blended cement can lessen the amount of co2 discharged says (davis, 2002). malaysia mostly relies on nonrenewable energy such as fossil fuel and coal to generate the production activities yet if the economy is too dependent on this energy, it will cause an expansion in co2 emission that consequently responsible for the global warming (chik and rahim, 2014). cement and concrete association of malaysia as the standard writing organization for cement has effectively required the advancement and adjustment of the new euro standard for cement in bolstering the improvement of blended cement. in this new cement standard, an aggregate of 27 types of cement will now be allowed to produced with 26 types are blended cement and only ordinary portland cement (opc) being just a single of the 27 sorts of cement delivered in malaysia. furthermore, malaysian government’s aspiration is to achieve a 40% voluntary reduction of co2 emission by 2020 in the low carbon society blueprint project toward transforming malaysia into a low carbon nation (bakhtyar, 2017, and yuzuru and siong, 2013). 2. direct carbon emissions in cement factories direct emissions are emanations from sources that are possessed or controlled by the reporting organization. for instance, emanations from fuel burning in a cement kiln are direct emissions of the company owning (or controlling) the kiln. according to vanderborght and brodmann (2001), direct co2 emissions result from the accompanying sources: calcination of limestone in the raw materials, conventional fossil kiln fuels, alternative fossilbased kiln fuels, biomass kiln fuels, and nonkiln fuels in cement plants. likewise, ali et al., 2011, summarize emissions of co2 in a cement industry mainly come directly from the combustion of fossil fuels and calcination of the limestone into calcium oxide. cement is known as the “glue” that holds the concrete and is utilized extensively in construction globally (international energy agency, 2007). cement industries with 25 billion tons of cement are delivered yearly everywhere worldwide and globally produced about 2.282 billion ton/year (lai, 2015). cement production is an energy-escalated process and energy consistently addresses to 20-40% of total production costs. the most extensively used is portland cement type that contains 95% cement clinker. furthermore, cement manufacturing is the most astounding potential savings for co2 emissions as cement records for nearly one-fourth of total direct co2 emissions in industry. while cement production in malaysia is around 20 million ton for each year and this segment of industry took about 12% of total energy in malaysia (madlool et al., 2011). the regular electrical power consumption of a modern cement plant is around 110-120 kwh per ton of cement (alsop, 2005). thermal energy represents around 20-25% of the cement production cost. cement additives quality improver polymer (caqip) is created from an integrated polymer, palm oil waste for production of sustainable cement, and waste materials from petrochemical. according to (lai, 2015), this caqip has substantially improved the productivity, quality, decrease co2 outflow, crushing and clinking energy and improved production of sustainable cement and concrete in malaysia. in the manufacture of opc and sustainable cement, industrial scale trial in local cement plants dosage up 0.01-0.69% caqip have significantly enhanced efficiency, 8.327.5% saving effectiveness, 24.73-86.36% clinking energy, and 7.70-21.57% crushing energy. furtermore, the carbon dioxide and others dangerous gasses emission lessened to 21.90-90.0% by supplanting clinker with waste material such as out-spec clinker (50-100%), limestone waste (5-25%), and fly ash (25-35%). according to gazipur (2011), around 0.3 million ton of palm oil fuel ash (pofa) is produced every year in malaysia, yet there are no noteworthy employments uses of these ashes as these are only dumped into environment consequently leading to disposal problem later. similar complications have been emerged by slag, rice husk ash, and sawdust ash/ash from timber as well. a colossal amount of biogenic wastes palms, oil fuel ash, rice husk ash, and sawdust ash/ash from timber produced in the developing countries like malaysia for instance. industrial by-product like slag is generated both from the developed as in developing countries. these biogenic wastes that contain a high amount of silicon dioxide inamorphous form verified as pozzolanic materials that are useful in cement production. pofa is an agro waste ash that contains a lot of silicon dioxide and has high potential to be utilized as a cement substitution. in creating high-quality cement, pofa can be used as a pozzolanic material in improving durability, reducing cost with less usage of cement. accordingly, this pozzolanic characteristic, rice husk ash to a significant degree is a reactive pozzolanic material and it is appropriate to use in lime-pozzolan blends and portland cement as a supplement. hence, this other industrial by-product (slag) and the biogenic waste pofa, rice husk ash, and sawdust ash/ash from timber) that accessible in malaysia will make a critical and dynamic in decreasing the co2 amount. truth be told, disregarding malaysia technical and financial benefits, till date these ashes, are only used for landfill purposes. 3. indirect carbon emissions in cement factories cement production uses much electricity for raw materials preparation, cement grinding, and catering for other electrical instrumentations (ke et al., 2013). amid the cement production process, co2 is emitted by four different sources. combustion of fossil fuel in pyro--handling unit, produces 40% of total emanations, while another 10% is in consequence of crude materials transportation and electricity generating consumed by electrical engines and facilities. while the most noteworthy proportion of emissions that about 50% is discharged in the decomposition of caco3 and mgco3 to produce cao and mgo as the core chemical responses in the process (mahasenan et al., 2003). co2 outflows in cement industry mostly from ignition of fossil fills and calcination of the limestone into calcium oxide. roughly 50% of co2 discharges originated from the combustion of fuels, and half of them are originated from the calcination of bakhtyar, et al.: a review on carbon emissions in malaysian cement industry international journal of energy economics and policy | vol 7 • issue 3 • 2017284 the limestone (ali et al., 2011). indirect emissions are emissions that result because of the activities of the reporting company, however, happen at sources possessed or controlled by another corporation. for instance, emissions from the generation of network electricity ran through by a cement company will qualify as indirect (wbcsd, 2011). utilization of electricity that is generated by burning fossil fuels is considered as energy-related co2 emissions and transmitting co2 indirectly. the share of co2 emissions from the power utilization is 5%, and the co2 emissions are indirect since they are the aftereffect of the power utilization to work the plant (zhu, 2011). this figure can vary from <1% to more than 10% as the efficiency at which it is used in the local electricity blend (müller and harnisch, 2008). furthermore, co2 outflows result not only from furnace operations, as well as from upstream and downstream processes, and (indirectly) from cement grinding (wbcsd, 2011). the mechanical energy required to grind the limestone, or blend the mix, is provided by electrical motors. accordingly, the co2 emanations identified with the grinding are mostly indirect and referred to the use of electricity. not only that cement production also relates to indirect greenhouse gas discharges from different sources such as external creation of electricity devoured by cement producers, production of clinker purchased from various manufacturers, transport of inputs (crude materials, fuels), and outputs (cement, clinker) by third parties and production and preparing of routine and option fuels by third parties. cement production sometimes requires transports for the arrangement of crude materials and fuels in addition to the dispersion of products (cement, concrete, and clinker). occasionally, clinker is transferred to another site for grinding. if the transports (such as conveyor belts, road, and rail) are carried out by independent third parties, then the related emissions qualify as indirect. indirect co2 emission reductions can be fulfilled by decreasing energy consumption in cement manufacturing (ali, et al., 2011). three components that determine the related co2 emissions (procedure efficiency, electrical engines and drive systems efficiency and the co2 intensity of the fuel mix in creating the electricity), the electric energy efficiency improvements can be accomplished through several approaches such as executing best accessible technologies and non-technical measures (müller and harnisch, 2008). grinding processes are major power consumers in cement plants, utilizing modern highly-efficient engine or enhancing the proficiency of engine framework can bring in a remarkable decrease in electricity utilization and related indirect co2 emissions. the present day grinding technologies can diminish the electricity request of the crude and finishing grinding operation as well as that of coal processing for fuel planning, prompting to decreases in indirect co2 emissions (zhu, 2011). else, reduction in fossil fuel reliance also gives a chance to lessen the co2 emission to the environment indirectly says (grosse-daldrup and scheubel, 1996, and benhelal et al., 2013). these fuels, for the most part, include biomass residues (agricultural and nonagricultural) and waste (petroleum, miscellaneous, chemical, and hazardous). according to the international energy agency statistics (2010), electricity and heat generation sector was responsible for 41% of the worldwide co2 emanations in 2008. it is mostly because of ignition of coal, the most carbon-intensive fossil fuel, stressing it’s partake in worldwide emissions. 4. emitted carbon from chemical reactions (clinker) fuel combustion emissions of co2 related to cement production are of approximately in total, 8% of global co2 emissions (olivier et al., 2015). during the cement production, clinker is scorched at about 1450°c. consequently, ecological contamination and global warming are constantly expanding and, natural resources, and energies are being shrunk day-to-day. the cement-based methodology and the clinker-based methodology are to calculate co2 emissions from delivering cement. the cement-based approach represents changes in co2 emissions in cement production by incorporating modifications (blended) to the cement manufacturing process while the clinker-based approach, calculates co2 emissions based on the volume and composition of clinker produced and the amount of cement kiln dust not recycled to the kiln (davis, 2002). these days, for the concrete production, much of the regularly utilized cement is opc as the cost of cement are persistently increasing, and natural resources like clinker are diminishing (gazipur, 2011). the utilization of added substances and substitutes to opc clinker has been one of the most standout measures in decreasing the specific co2 emissions 0.75 of a longterm clinker proportion is desirable. f, a low clinker proportion implies the reduced co2 emissions as less calcination is needed in creating the cement. for malaysia, the proportion of the clinker ratio is 0.89 (müller and harnisch, 2008). clinker production is the most energy escalated step, speaking to around 80% of the energy used in cement manufacturing. hence, by upgrading the energy efficiency in the clinker production process can lessen the energy consumption, related expenses, and co2 emissions. clinker substitution is the most financially savvy approach to reducing co2 emissions from cement production and has other environmental advantages. the supplementary materials cast off as clinker substitutes include blast furnace slag, fly ash from coal combustion, other natural and manufactured pozzolans. the thermal energy ingesting of per unit cement produced decreases with the expanded ratio of clinker substitutes in the blended cement (zhu, 2011). experts of clinker substitutes could significantly upgrade the procedure in organizations and local governments to boost the recovery and advance the entire industrial streams particularly in heavy industries can be very favorable to supply clinker substitutes. coal ashes with exorbitant carbon content (5% or more) diminish the cement strength, which is a noteworthy issue for quality and on the co2 balance, unusable coal ashes (5-20%) are proportionate to a power plant of a much lower productivity (müller and harnisch, 2008). in the generation of co2 the and internal separation process, co2 detachment is done inside the bakhtyar, et al.: a review on carbon emissions in malaysian cement industry international journal of energy economics and policy | vol 7 • issue 3 • 2017 285 cement process, and almost 66% of the total co2 could be stored straight away without any capture process. 5. discussion for cement fabricating, 300 mt cement clinker (about 15%) can be substituted by slag, fly ash, and pozzolans (international energy agency, 2007). fly-ash may likewise be utilized directly in the cement kiln as a replacement for clay or bauxite, and these additionally help in reducing resource consumption and co2 emissions. notwithstanding, there is a range of other types of cement that utilize an assortment of clinker substitutes to reduce clinker expenses and co2 emissions. these different feed stocks for cement have properties like cement and therefore can be replaced for clinker either in the cement or the kiln as an option to the feedstock blend. dependent on the case, either the conventional or the advanced alternatives to portland cement will prompt to noteworthy reductions of co2 stretching out from 20% to 80% (müller and harnisch, 2008). cement is conveyed from a feedstock of clay, limestone, and sand and hence which give the four key fixings requisite of alumina, lime, silica, and iron. another arrangement which as of now exists involves supplanting a part of the clinker in the cement with other cementations materials. preferably such substitutes would not require any further calcination and would be incorporated after the kiln so that no thermal processing would be necessary. blending such materials would spare 40% of the energy required for calcination, and additionally 50% of the co2 taking place from the reaction. in this manner, each ton of clinker substitute included would decrease the co2 emissions by 90% (müller and harnisch, 2008). in benhelal et al.’s, 2013, work, strategies of co2 reduction such as fuel and energy saving, carbon separation and storage, and utilizing alternative materials are carried out and have been reviewed by academic researchers and companies to directly or indirectly decrease co2 emissions in cement industry. first, utilizing wastederived fuel in cement plant seems to be an environmental since it simultaneously reduces emissions from both cement plants and landfills. furthermore, if waste-derived fuel is not utilized in cement process as the main or partial source of energy, it ought to be demolished by incinerators or must be sent to the landfills, generating further co2 in addition to co2 produced by the fossil fuel that has not been replaced. second, if there should be an occurrence of energy saving approaches, moving to more efficient process for instance from wet to dry process with calciner, demonstrates the best outcomes since possibly reduces up to 50% of requisite energy and lessens almost 20% of co2 emissions in the process with the carbon detachment and storage, a feasible way to avoid release of co2 . third, the most cost-effective ways are to capture co2 from the flue gasses and store it away in the soil or ocean. this can reduce carbon emissions by as much as 65-70%. by reducing clinker/ cement ratio with the expansion of different added substance, co2 emissions can be reduced substantially (ali et al., 2011). industrial wastes such as fuels, raw materials, and clinker substitutes can be utilized in alleviating co2 emissions that root from cement plants and landfills. regardless, economic and technical challenges can still play a remarkable obstacle against implementing such processes in the cement plant. obstructions for the utilization of clinker substitutes remain in some markets. the legitimate systems in some developing countries require composition-based cement standards, constraining the use of clinker substitutes. this is particularly imperative since composite cement with a low clinker ratio is the second-rate in quality, but rather may have a slower reactivity and a more drawn out setting time. nevertheless, the expanded setting time is a detriment to a blasting economy where short construction time for buildings is of great importance. furthermore, benhelal et al., 2013, recommend that further research need to be conducted to ensure the utilization of the alternative materials are applicable and suitable for a solid cement production, even though the alternative materials were proved chemically can be used in the cement production. in 2006, malaysia consumed 20 mt of cement and had a clinker ratio of 0.89 t/t co2 , which is higher than the world average. hence, simulations have been created for malaysia by müller and harnisch (2008), with respect the cement production by 2020 and the likelihood of restricting the related co2 emissions using conventional methods such as more efficient plants, the utilization of clinker substitute, and biomass-based fuels. with the assumption of the co2 factor of the cement industry in malaysia was 0.77t co2 /=t cement in 2006 that prompted to worldwide emissions of 15 mt co2 /year, and the share of biomass-based fuels in the blend can presumably be expanded to 4% or higher however it is constrained because of the nation’s relatively high population density. thus, the clinker factor can likely be brought down to 0.82 t/t. furthermore, by upgrading existing plants and also of efficient new plants in the year 2020 in malaysia, the average specific heat consumption of cement kilns might be decreased to around 3,250 mj/t, hence lead to the reduction situation to an achievable decline of the co2 intensity to 0.68t co2 /t cement by 2020. 6. conclusion cement manufacturing is an energy intensive industry consuming about 12-15% of total industrial energy use. in any case, it set up that the substituting fossil fuels with alternative fuels may play a major role in the decrease of carbon dioxide emissions. these measures will reduce environmental impacts without deterring the overall of quality cement production. sizeable amounts of discharge of emissions into the atmosphere because of burning fossil fuels to supply energy requirements of these industries. for these reasons, particular attention is needed for the clinker production to reduce co2 emissions. although vital methodologies approach described above have high potential to subside co2 emissions in worldwide cement industry, however, economic and legal difficulties still play as striking deterrents against across the board execution of such methodologies implementation. thus, by eliminating such obstructions, co2 mitigation strategies can be applied on the extensive scale of the cement industry to a globally acceptable emission targets in each nation. in this way, a persistent move bakhtyar, et al.: a review on carbon emissions in malaysian cement industry international journal of energy economics and policy | vol 7 • issue 3 • 2017286 should make by the researchers with the support from the government along with the compliance from the industry. a specific agreement could be reached to equip malaysian plants with waste heat recovery generation (muller and harnisch, 2008). furthermore, the relatively small number of participants, an agreement for the cement market in malaysia can probably be reached between the parties to guarantee the move to lower technologies which empower the decrease of emissions. furthermore, in future, different sorts of blended cement will gradually supplant opc as the main cement type in malaysia. both the malaysian government organizations and also the private part shall keep on supporting the preference for more sustainable and eco-friendly blended cement, as opposed to utilizing the ordinary opc which generates a much higher amount of co2 and is less sustainable. besides, approaches to expand further, the share of biomass must be found. the energy from biomass plays a significant role in energy demand worldwide, supplying 10% of the total energy demand (karstensen, 2006). hence, the proper direct smoldering of the biogenic waste can utilize as option fuel in the cement industry without issues or performance deterioration. references ali, m.b., saidur, r., hossain, m.s. (2011), a review on emission analysis in cement industries. renewable and sustainable energy reviews, 15(5), 2252-2261. alsop, p. (2005), the concise guide to cement manufacture. international cement review, 22(2), 140-145. bakhtyar, b., fudholi, a., hassan, k., azam, m., lim, c.h., chan, n.w., sopian, k. (2017), review of co2 price in europe using feed-in tariff rates. renewable and sustainable energy reviews, 69, 685-691. bakhtyar, b. (2017), asian and global financial crises. effect on malaysia co2 emission. international journal of energy economics and policy, 7(2), 236-242. benhelal, e., zahedi, g., hashim, h. (2012), a novel design for green and economical cement manufacturing. journal of cleaner production, 22(1), 60-66. benhelal, e., zahedi, g., shamsaei, e., bahadori, a. (2013), global strategies and potentials to curb co2 emissions in cement industry. journal of cleaner production, 51, 142-161. chik, n.a., rahim, k.a. (2014), sources of change in co2 emissions from energy consumption by industrial sectors in malaysia. 9th perkem proceeding. p163-174. lai, f.c. (2015), innovative cement additives quality improvers in sustainable cement and concrete. sains malaysiana, 44(11), 1599-1607. davis, g. (2002), general reporting protocol. california climate action registry. grosse-daldrup, h., scheubel, b. (1996), alternative fuels and their impact on refractory linings. world cement, 27(3), 94-98. international energy agency. (2007), tracking industrial energy efficiency and co2 emissions. paris, france: organisation for economic co-operation and development. international energy agency statistics. (2010), co2 emissions from fuel combustion highlights. paris: organisation for economic cooperation and development. gazipur, b. (2011), necessity and opportunity of sustainable concrete from malaysia’s waste materials. australian journal of basic and applied sciences, 5(5), 998-1006. karstensen, k.h. (2006), cement production in vertical shaft kilns in china: status and opportunities for improvement. report to the united nations industrial development organization. ke, j., mcneil, m., price, l., khanna, n.z., zhou, n. (2013), estimation of co 2 emissions from china’s cement production: methodologies and uncertainties. energy policy, 57, 172-181. madlool, n.a., saidur, r., hossain, m.s., rahim, n.a. (2011), a critical review on energy use and savings in the cement industries. renewable and sustainable energy reviews, 15(4), 2042-2060. mahasenan, n., smith, s., humphreys, k., kaya, y. (2003), the cement industry and global climate change: current and potential future cement industry co2 emissions. in: greenhouse gas control technologies-6th international conference. vol. 2. elsevier. p9951000. müller, n., harnisch, j. (2008), a blueprint for a climate friendly cement industry. report for the wwf-lafarge conservation partnership. gland, switzerland: wwf. olivier, j.g.j., janssens-maenhout, g., muntean, m., peters, j.a.h.w. (2015), trends in global co2 emissions: 2015 report. pbl netherlands environmental assessment agency, the hague; european commission, joint research centre (jrc). institute for environment and sustainability (ies). vanderborght, b., brodmann, u. (2001), the cement co2 protocol: co2 emissions monitoring and reporting protocol for the cement industry. world business council for sustainable development. wbcsd. (2011), co2 and energy accounting and reporting standard for the cement industry. world business council for sustainable development. yuzuru, m., siong, h.c. (2013), low carbon society scenarios malaysia 2030. japan: university teknologi malaysia. zhu, q. (2011), co2 abatement in the cement industry. iea clean coal centre. research report ccc/184. ole_link1 tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 1 • 2023144 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(1), 144-153. the causal impact of solid fuel use on mortality – a crosscountry panel analysis muhammad irfan1, michael p. cameron2*, gazi hassan2 1school of economics and management, xiamen university malaysia, malaysia, 2school of accounting, finance, and economics, university of waikato, new zealand. *email: mcam@waikato.ac.nz received: 20 august 2022 accepted: 19 december 2022 doi: https://doi.org/10.32479/ijeep.13498 abstract biomass consumption causes indoor air pollution which impairs health and environment. in this paper, we examine the causal relationship between biomass fuel consumption and measures of life expectancy and infant and child mortality. using 13 years of cross-country panel data which covers 105 countries over the period 2000-2012, we applied fixed effect model and instrumental variable regression. we find that solid fuel combustion causes increase in infant and child mortality and decreases in male and female life expectancy. a back-of-the envelope calculation suggests that, if the solid fuel consumption gap between low-income and lower-middle income countries were reduced by 50%, infant and child mortality in the lowincome countries decrease by 16.5 and 29.8 per thousand respectively, and life expectancy would increase by 1.0 and 1.5 years for males and females respectively. our findings suggest that governments, particularly of developing countries, should focus efforts to reduce solid fuel use. keywords: solid fuels; indoor air pollution; child mortality; life expectancy; causal relationship jel classifications: i15; q53; o13 1. introduction today, pollution is chiefly responsible for more deaths than aids, tuberculosis, obesity, malaria, child and maternal malnutrition, alcohol, road accidents, or wars (landrigan et al., 2018). globally in 2015, an estimated 9 million premature deaths and 14 million years lived with disability were attributed to pollution (landrigan et al., 2018). furthermore, millions are facing serious diseases such as lung infection, asthma, tuberculosis (tb), sinus problems, cardiovascular diseases, and cancer (mishra, 2003b; kim et al., 2011; lakshmi et al., 2012). the consumption of solid fuels remains higher in rural areas than urban areas (irfan et al., 2018) and higher in low-income and middle-income countries than in developed countries, and the deaths due to indoor air pollution are therefore highest in rural areas of lower and middle-income countries (landrigan et al., 2018). adverse health effects are concentrated among poor families (duflo et al., 2008), and especially women and children, because women usually cook food for their families and children under age 5 usually accompany their mothers (edwards and langpap, 2012). children and infants are particularly vulnerable because their underdeveloped immune system is less able to fight against infections. moreover, infants have limited energy stores that may be insufficient to compensate for the reduced feeding that accompanies respiratory illness (berman, 1991). premature deaths and diseases due to indoor air pollution place a great burden on national budgets, increasing medical expenditures, and reducing the overall productivity of the economy (landrigan and fuller, 2014; zhu et al., 2018). pollution also damages the environment, and the excessive use of firewood as a cooking source depletes forests (arnold et al., 2006; mcneill, 2006). worryingly, the overall consumption of solid fuel by households is expected to continue increasing until 2030 (edwards and langpap, 2012). currently, almost three billion people in low-income and middleincome countries do not have access to clean or modern energy this journal is licensed under a creative commons attribution 4.0 international license irfan, et al.: the causal impact of solid fuel use on mortality – a cross-country panel analysis international journal of energy economics and policy | vol 13 • issue 1 • 2023 145 sources, and hence depend upon solid fuels such as firewood, biomass, crop residues, coal, and charcoal (landrigan et al., 2018). when these solid fuels are burned, they emit a multitude of complex chemicals including formaldehyde, nitrogen dioxide, carbon monoxide, cilia toxic, polycyclic aromatic hydrocarbons (pah), and other inhalable particulates (torres-duque et al., 2008), leading to adverse effects on health and the environment. despite the substantial collective and individual damages of indoor air pollution, the use of solid fuels is common, especially in developing countries. the prevention of indoor air pollution has not gained the urgency it deserves in international forums (duflo et al., 2008). a possible reason of this lack of attention is the lack of awareness of the scope of the problem (landrigan and fuller, 2014). although a positive association between solid fuel consumption and child mortality (or, more generally, a negative association between solid fuel consumption and health) has been found in many studies (e.g. mishra, 2003a; bloom et al., 2005 and acharya et al., 2014), these studies have failed to establish causal effects, as they have been based only on cross-sectional or panel data. the main objective of this paper is to attempt to fill this significant research gap by investigating the causal relationship between indoor air pollution and both mortality and life expectancy. this investigation is important so that policy makers can get a better understanding about the adverse health effects of solid fuel consumption and form appropriate policies to reduce the consumption of solid fuels. the remainder of the paper is structured as follows. section 2 discusses the relevant literature, section 3 discusses the data and variables, and section 4 presents the methods that we employ. in section 5 we discuss the results, then section 6 concludes the paper. 2. literature review an extensive literature is available regarding the impacts of indoor air pollution on health, including review articles such as pandey et al. (1989), bruce et al. (2000), ezzati and kammen (2002), smith (2002), larson and rosen (2002), dherani et al. (2008), kim et al. (2011), and oluwole et al. (2012). despite these numerous reviews, there remains a severe lack of cross-country empirical research in particular. among studies at the individual level, edwards and langpap (2012) investigated the impact of firewood consumption on the health of women and of children aged under 5 years in guatemala, as well as the consequences of cooking inside the home. they applied probit and two-stage least squares (2sls) regression analysis on living standards measurement survey data (for the year 2000), and found that firewood consumption was positively associated with the probability that a child had a respiratory disease. in a study in bangladesh using primary data from 49 households, khalequzzaman et al. (2007) first measured the amount of harmful gases (carbon dioxide, carbon monoxide, nitrogen dioxide, dust, and volatile organic compound) that were emitted from the energy sources used for cooking. they found that solid fuels such as fuelwood and crop residues were the main emitters of harmful gases, and concluded that these gases were affecting children’s health negatively. in other words, consumption of solid fuels (fuelwood, crop residues) were putting children’s health at risk. mishra (2003b) examined the effect of biomass combustion on children aged under 5 years in zimbabwe. they used zimbabwe demographic and health survey 1999 data, and logistic regression on the probability of suffering from acute respiratory infections (ari). they concluded that fossil fuel combustion was significantly and negatively associated with children’s health. likewise, studies in nepal acharya et al. (2014) and in south africa barnes et al. (2009) have found positive associations between ari and solid fuel consumption among children under 5 years. using panel data from india, upadhyay et al. (2015) similarly found a negative association between solid fuel consumption and children’s health. imelda (2018) used a quasi-experiment to establish the causal relationship between kerosene use and infant mortality in indonesia. they used three rounds of the indonesian demographic and health survey for the years 2002, 2007, and 2012. having segregated the regions based on subsidy given on lpg, they found that the infant mortality rate was lower in regions where households had shifted from kerosene to lpg use. the study concluded that the lpg subsidy program saved 600 infants death annually in indonesia. however, the study data were based on repeated cross-sections rather than panel data, and only considered the impact of kerosene consumption on health. this suggests that there may be enormous health benefits to the public provision of modern fuel consumption (xue, 2018). children and infants are not the only vulnerable group that may be heavily impacted by indoor air pollution. the impact of solid fuel consumption on the health of elderly people (>60 years) was examined by mishra (2003a) in india. he found that the probability of being an asthma patient was two times higher for elderly people living in households using solid fuels than those residing in homes that use clean cooking fuels. in contrast to individual or household-level analyses, crosscountry investigations of these relationships are much less common, including investigations of the relationship between life expectancy and solid fuel consumption. pope et al. (2009) found a negative relationship between air pollution and life expectancy in the united states and in canada, stieb et al. (2015) found an inverse association between air pollution and life expectancy. likewise, chen et al. (2013) found that air pollution was significantly and negatively associated with life expectancy in northern china. they used data from 1981 to 2000 for 90 cities and applied ordinary least squares and regression discontinuity approaches to explore the relationship between life expectancy and total suspended particulates. they concluded that a 100 μg/m3 increase in total suspended particulates leads to a decline of 3 years in life expectancy at birth. however, they did not estimate the effects on life expectancy separately for males and females. if men and women face differential exposure to air pollution, then the impact on their life expectancies will differ. for example, traditional biomass combustion is a major cause of total suspended particulates and has a chronic impact on the life irfan, et al.: the causal impact of solid fuel use on mortality – a cross-country panel analysis international journal of energy economics and policy | vol 13 • issue 1 • 2023146 expectancy of women and children (zahnd and kimber, 2009). women in developing countries are more at risk from iap because of cooking responsibilities. the study bearing the most similarity to our paper is bloom et al. (2005), who used cross-country data for 162 countries to investigate the health impacts of solid fuel combustion on life expectancy and child mortality. they concluded that biomass combustion was positively associated with child mortality and negatively associated with life expectancy. however, because of the cross-sectional nature of their study, it does not demonstrate the causal effect of solid fuel consumption on health. our study builds on bloom et al. (2005), by using panel data and adopting an instrumental variables approach to demonstrate causal, rather than correlational, effects. we also estimate the causal effects on life expectancy separately by gender. although our results do not differ qualitatively from those of the earlier studies, their robustness and the plausible attribution of causality makes them more suitable for policy applications, as suggested by barnes et al. (2009) and landrigan et al. (2018). 3. data and variables most extant cross-country studies of the relationship between indoor air pollution and health outcomes have used cross-sectional data, whereas we employ panel data. panel data has many advantages over time series and conventional cross-sectional data (hsiao et al., 2003). panel data or longitudinal data usually gives the researcher a larger number of data points (n by t), increasing the degrees of freedom and reducing the collinearity among explanatory variables. it allows models to be employed that will control for the impact of time-invariant omitted variables, potentially uncovering dynamic relationships, and generating more accurate predictions. because of these advantages, panel data models have become increasingly popular among applied researchers (hsiao et al., 2003). annual data on gross domestic product (gdp), education, population, forest area, and countries’ profile variables were obtained from the world bank’s world development indicators (wdi),1 and child and infant mortality rates data were obtained from the world health organization (who).2 data on household fuel consumption and production at country level, including both clean and solid fuels, were obtained from the un statistics division energy statistics database.3 the energy sources data were available only for the period 2000 to 2012, which restricts our analysis to that time period. the nature and structure of the variables can be seen in table 1. we have unbalanced panel data on fuel consumption and health for 157 countries, although this falls to 105 in our preferred instrumental variables (iv) specification due to lesser availability of gas production and forest cover data, which are our instruments (described below). 1 https://databank.worldbank.org/data/reports.aspx?source=worlddevelopment-indicators 2 http://www.who.int/gho/en/ 3 https://unstats.un.org/unsd/energy/edbase.htm the main independent variable, “percentage of solid fuel consumption”, was constructed as the proportion of total energy consumption originating from household consumption of fuelwood, charcoal, and dry animal dung. annual household energy consumption data were not all expressed in the same units; therefore, we first converted them into terajoules.4 in the iv regression (described in the following section), we include the percentage of forested area and total combined production of liquefied natural gas (lng), liquefied petroleum gas (lpg), and natural gas (in terajoules) as instrumental variables. the proportion of energy derived from solid fuel consumption was treated as the endogenous variable. table 1 shows the summary statistics of the variables overall, as well as separately for low-income, lower-middle income, uppermiddle income, and high-income countries.5 as anticipated, household consumption of solid fuel is higher in low-income and lower-middle income countries, and the rates of infant mortality and child mortality are also higher in those countries. per capita gdp and the exploration of oil and gas are also lower in lowincome and lower-middle income countries, as is the percentage of the population living in urban areas. we faced some data limitations. for example, some other important variables were not included in the model, which may affect mortality and life expectancy such as access to clean drinking water, sanitation, calorie consumption, mother’s health (for infant and child mortality), number of hospitals and doctors, other medical facilities, and technological advancement over time. we note that many of these variables are likely to be correlated with (log of) gdp per capita, which is included in the model along with country fixed effects and time dummies. this would create a problem of ‘bad controls’ (angrist and pischke, 2008), if these other variables were also included in the model. moreover, country fixed effects will pick up country-specific time invariant differences, and general time trends and time-specific global shocks such as some improvements in technology will be captured by time fixed effects. in addition to avoiding bad controls, the more parsimonious specification also reduces problems of multicollinearity and over-fitting. 4. methodology our hypothesis is that increasing solid fuel consumption at household level causes indoor air pollution and is therefore a source of higher infant and child mortality and lower life expectancy at birth. we do not have cross-country data on indoor air pollution, and so our models begin with a reduced form specification that links solid fuel consumption directly to health impacts. hence, in order to examine the impact of using biomass fuels on child mortality and life expectancy, we applied panel data models. in total we ran four models with different dependent variables: (1) 4 we used an online calculator for this conversion (https://www.convertunits. com/from/tons/to/terajoule) 5 the world bank classifies these categories based on mainly gross national income (gni). for details see: https://datahelpdesk.worldbank.org/ knowledgebase/articles/378833-how-are-the-income-group-thresholdsdetermined irfan, et al.: the causal impact of solid fuel use on mortality – a cross-country panel analysis international journal of energy economics and policy | vol 13 • issue 1 • 2023 147 infant mortality per thousand population; (2) child mortality per thousand population; (3) male life expectancy at birth; and (4) female life expectancy at birth. explanatory variables included the proportion of energy derived from solid fuel consumption, male and female primary school enrolment (gross),6 log of gross domestic product per capita, and the proportion of the population living in urban areas. the general panel specification of our models is: y x z a k u t tit it it i t it� � � � � � ���� �1 2 1 2 3, , , , .. (1) where: yit is the dependent variable for country i in time period t (in our case, the dependent variable is one of: infant mortality; child mortality; or life expectancy for the whole population or for one of the genders); xit represents a vector of other independent variables for country i in time period t; zit represents solid fuel consumption for country i in time period t; ai is a vector of country fixed effects; kt is a vector of time fixed effects; β1 and β2 represent the coefficient for the independent variables; and uit is the idiosyncratic error term. a particular issue for our reduced form specification is that solid fuel consumption may depend on various excluded and included variables such as taste preference, consumption habits, gender of 6 the number of children enrolled in primary schools, divided by the population of that age group and multiplied by 100. the variable is taken from wdi database. the household head, household income, household size, education level, access to fuels, and other demographic variables (o’neill and chen, 2002; mekonnen and köhlin 2009; jan et al., 2012; lee, 2013; irfan et al., 2021a). thus, the independent variable will be correlated with the error term in the panel regression model, leading to an endogeneity problem. to overcome this, we apply an iv approach. our selected instruments are: (1) percentage of forest area in the country; and (2) annual production of natural gas (including lng and lpg). both variables can be expected to affect the endogenous variable (solid fuel consumption), and are plausibly exogenous (i.e. have no direct effect on infant and child mortality or life expectancy). households located near to forested areas are expected to consume more firewood (jumbe and angelsen, 2011), while forested areas are not expected to directly affect mortality or life expectancy in a material way. in 2015, the total number of fatalities due to forest fires across 31 countries7 was only 18,400, which is certainly too small to have an appreciable impact on country-level mortality and life expectancy (world fire statistics, n.d.). likewise, wildfires in indonesia were associated with roughly 15,600 fetal, infant, and child mortalities were noted in 1997 (jayachandran, 2009). however, deaths due to wildfire or forest fires have reduced significantly over time due to better equipment for firefighting and advancements in weather forecasting (doerr and santín, 2016). similarly, a country that has gas reserves is expected to consume less solid fuels because of the increased availability (and lower domestic price) of natural gas, lng, and lpg. while production of gas is not expected to have an appreciable direct effect on 7 armenia, austria, belarus, bulgaria, croatia, czech republic, estonia, finland, france, great britain, hungary, italy, kazakhstan, kyrgyzstan, latvia, liechtenstein, lithuania, moldova, mongolia, netherlands, new zealand, poland, romania, russia, singapore, slovenia, sweden, switzerland, ukraine, usa, and vietnam. table 1: summary statistics, by country income class variables country income class all countries n low income n lower middle n upper middle n rich n percentage of solid fuel consumption 30.71 (19.03) 299 10.09 (17.02) 505 1.82 (6.88) 599 0.32 (0.63) 619 7.69 (15.69) 2022 infant mortality rate per thousand population (0-27 days) 74.00 (21.28) 299 44.72 (22.44) 506 24.37 (18.96) 606 7.02 (5.51) 624 31.40 (28.56) 2035 child mortality rate per thousand population (1-59 months) 118.94 (40.86) 299 61.05 (36.07) 506 31.1 (29.46) 606 8.31 (6.49) 624 44.48 (46.64) 2035 female primary school enrolment (gross) 75.96 (42.25) 299 89.84 (35.92) 506 84.20 (42.74) 606 91.72 (31.74) 624 86.69 (38.24) 2035 male primary school enrolment (gross) 87.78 (42.91) 299 93.42 (93.42) 506 86.13 (43.86) 606 92.37 (32.03) 624 90.09 (38.64) 2035 log of gdp per capita (usd) 5.95 (0.50) 297 7.03 (0.69) 500 8.31 (0.65) 601 10.02 (0.75) 617 8.16 (1.60) 2015 total population (millions) 15.54 (15.60) 298 59.90 (186.43) 506 48.84 (190.62) 606 14.60 (24.51) 624 36.20 (141.63) 2034 percentage of urban population 26.99 (10.25) 298 41.24 (17.01) 506 59.77 (15.12) 606 75.70 (18.71) 624 55.24 (23.72) 2034 percentage of forest area of total area 21.86 (15.30) 299 29.92 (23.90) 506 38.27 (25.09) 606 28.33 (22.27) 624 30.73 (23.35) 2035 log of lng, lpg, and natural gas production (terajoule) 4.55 (4.57) 73 7.24 (7.15) 301 9.49 (5.64) 428 9.45 (5.50) 499 8.68 (6.07) 1301 standard deviations are in parentheses. irfan, et al.: the causal impact of solid fuel use on mortality – a cross-country panel analysis international journal of energy economics and policy | vol 13 • issue 1 • 2023148 mortality or life expectancy. the adverse impact of fracking sites could be correlated with infants’ health (mortality, low birth weight). however, the impact radius of fracking sites is only 1 km, and so the effect is expected to be minimal. for instance, informal estimates suggest only 29,000 of around 4 million birth occurs within 1 kilometer of active fracking sites in the united states (currie et al., 2017). furthermore, global data related to number of fatalities among those employed in gas extraction are not available; however, some studies have tried to estimate the number of deaths at a regional level. the total number of deaths from 1969 to 1996 in oil and gas related occupations in seven countries8 was 8,386 (hirschberg et al., 2004) and in the united states of america from 2003 to 2013 the corresponding number was 1,189 (mason et al., 2015). again, these numbers are too small to have an appreciable impact on country-level mortality. moreover, gas extraction related mortality is more likely to affect adults than children. while we are satisfied about the exogeneity of our instruments, we also accept the alternative view that they may not fully meet the exogeneity criteria. to check the robustness of our iv results, we also undertake the ‘plausibly exogenous’ bound estimation developed by (conley et al., 2012). this method allows for statistical inference when a potential instrumental variable (iv) may be “close to,” but not necessarily precisely, exogenous. specifically, the conley et al. (2012) method involves performing a sensitivity analysis of the coefficients when a small direct impact (referred to as γ) of the ivs on the dependent variable is allowed for. the (conley et al., 2012) method allows two types of bounds testing for inference for iv: (1) the union of confidence interval (uci) approach; or (2) the γ-local-to-zero (ltz) approach. we used the local-to-zero (ltz) approximation, as the uci approach is not applicable when multiple instruments are used. the ltz approach generates bounds of the coefficient of interest when the parameter γ is assumed to be drawn from n (0, δ2) distribution, and the interpretation of the results of this sensitivity analysis is that if the iv-point estimates in the structural equation fall outside the bounds, then the results would be doubtful, but not otherwise. this sensitivity analysis is increasingly being employed when the exogeneity of ivs is doubtful, such as in dang (2013), roychowdhury (2017), and tran et al. (2021). moreover, there could be some cause for concern that our instruments are influenced by gdp and are therefore not exogenous in that way. to allay these concerns, we also checked the correlation between the instruments and the log of gdp per capita. table a1 in the appendix shows that one instrument (log of natural gas, lng, and lpg) is significantly and positively associated with log of gdp per capita. we also ran the first stage regression without log of gdp per capita, and the results are presented in table a2. the results are not sensitive to the exclusion of log of gas production or log gdp per capita. furthermore, the suitability of the instruments was further tested for joint significance of endogenous (anderson-rubin wald test, stockwright lm s statistic) under-identification (anderson canonical correlation lagrange multiplier statistics), over-identification 8 afghanistan, brazil, egypt, mexico, philippines, russia, and south korea. (sargan test), and weak identification (cragg-donald wald f-statistic). the results of these tests are included in table a3 in the appendix. 5. results and discussion we applied the hausman test to identify whether random effects or fixed effects is the appropriate model specification. the test suggests that the fixed effect models are the appropriate specification. hence, table 2 presents the results of the fixed effects models. in all models, the percentage of solid fuel consumption is statistically significant with the expected sign. solid fuel consumption is significantly and positively associated with both infant and child mortality. specifically, a one-percentage point higher proportion of household solid fuel use at the national level is associated with a 0.27 per thousand population higher infant mortality rate and a 0.53 per thousand population higher child mortality rate. a one-percentage point higher proportion of solid fuel use is also associated with 0.051 to 0.059 years lower life expectancy, with a slightly larger coefficient for women than men. these findings are consistent with the earlier results of bloom et al. (2005), albeit our results utilise panel rather than cross-sectional data. the coefficients on control variables are mostly as expected except male education. however, while female education has a negative association with both infant and child mortality, male education is positively associated with both variables. our findings in this respect are the exact opposite to those of bloom et al. (2005), who found that female education was positively and male education negatively associated with infant and child mortality (however, their coefficients were statistically insignificant whereas ours are significant). similarly, we find that female education is positively associated with life expectancy, but male education is negatively associated with life expectancy. here again, our results are completely opposite to the findings of bloom et al. (2005). higher female education (but not male education) has been previously found to be associated with lower solid fuel consumption (pundo and fraser, 2006; acharya et al., 2014), which may explain our results. moreover, mother’s education play an important role in improving child’s health (chakrabarti, 2012). alternatively, the endogeneity of solid fuel consumption may be causing these unexpected results. as expected, per capita gdp and urbanization were both significantly negatively associated with infant and child mortality, and significantly positively associated with life expectancy. these findings are consistent with the earlier cross-sectional analysis of bloom et al. (2005). higher income countries generally provide people with better access to higher quality medical facilities and have more robust health systems, and people in urban areas typically have better access to medical care. our iv regression analysis (see below) is run on a smaller sample of 105 countries for which we have data on the instrumental variables. we ran all fixed effect models with this smaller sample and the results are similar (table a4 in the appendix). as previously noted, the proportion of household solid fuel use is likely to be endogenous. we applied the anderson-rubin wald irfan, et al.: the causal impact of solid fuel use on mortality – a cross-country panel analysis international journal of energy economics and policy | vol 13 • issue 1 • 2023 149 and stock-wright lagrange multiplier s-statistic test to confirm this in our models. our first two exogenous variables (percentage of land that is forested and the log of natural gas, lng, and lpg production) are statistically significant predictors of the endogenous variable (percentage of solid fuel consumption), as can be seen in table 3, which presents the first-stage estimation from the iv regression. the first stage clearly satisfies the relevance restriction. as noted above, we also tested for underidentification, over-identification, and weak identification. the results of these tests are included in table a3 in the appendix. the results of these tests confirm that that our instruments are strong and valid. both the relevance and exclusion restrictions are therefore satisfied and our estimators are consistent (alva et al., 2014; behncke, 2012). moreover, the tests results support our instrumental variable approach and demonstrate the suitability of our chosen instruments. finally, table 4 presents the iv model (two-stage least squares) results. although the sample size reduces from 157 and 154 to 105 (due to the unavailability of data on the instruments for some countries), the results support our hypothesis that solid fuel consumption causes increases in child and infant mortality and decreases in life expectancy at birth. the coefficients in the iv regression are larger than in the fixed effect models (table 2), which suggests that we may also be reducing the measurement table 2: fixed effect model results infant mortality rate child mortality rate male life expectancy female life expectancy percent of solid fuel use 0.268*** (0.019) 0.534*** (0.038) −0.051*** (0.004) −0.059*** (0.005) female primary sch. enrolment −0.324*** (0.030) −0.601*** (0.061) 0.038*** (0.007) 0.038*** (0.008) male primary sch. enrolment 0.296*** (0.029) 0.548*** (0.060) −0.034*** (0.007) −0.034*** (0.007) log of gdp per capita −5.490*** (0.474) −7.771*** (0.971) 0.261** (0.113) 0.179 (0.122) urban % of population −0.560*** (0.067) −0.850*** (0.137) 0.073*** (0.016) 0.106*** (0.018) _cons 108.760*** (5.068) 157.606*** (10.375) 58.853*** (1.203) 62.701*** (1.292) year fixed effects yes yes yes yes r2 (overall) 0.66 0.65 0.57 0.59 n 2,007 2,007 1,950 1,950 number of countries 157 157 154 154 *p<0.1; ** p<0.05; ***p<0.01 country level clustered standard errors are in parentheses. table 3: first stage instrumental variable regression results for all models percentage of solid fuel consumption coefficients percentage of forest land of total land 0.707*** (0.113) log of natural gas, lng, lpg production –0.441*** (0.090) female primary sch. enrolment –0.040 (0.029) male primary sch. enrolment 0.033 (0.028) log of gdp per capita –2.342*** (0.403) urban % of population –0.610*** (0.065) year fixed effect yes number of countries 105 n 1289 *p<0.1; **p<0.05; ***p<0.01. country level clustered standard errors are in parentheses the estimates are generated by using stata command plausexog by clarke (2014) figure 1: γ-local-to-zero (ltz) approximation bounds tests for instruments validity irfan, et al.: the causal impact of solid fuel use on mortality – a cross-country panel analysis international journal of energy economics and policy | vol 13 • issue 1 • 2023150 error in the solid fuel consumption variable. our results imply that a one-percentage point increase in the proportion of household solid fuel consumption leads to a statistically significant increase in infant mortality of 1.599 per thousand population and a statistically significant increase in child mortality of 2.89 per thousand population. to get a sense of the size of these effects, the difference between the mean upper-middle income country and the mean low-income country in proportion of solid fuel use is 28.89% points in our sample. ceteris paribus, this difference in solid fuel use would cause the infant mortality rate in low-income countries to be higher by 46.2 per thousand, and the child mortality rate in low-income countries to be higher by 83.5 per thousand, compared with upper-middle income countries. solid fuel consumption also causes lower life expectancy at birth, with a one-percentage point increase in the proportion of household solid fuel consumption lowering male life expectancy at birth by 0.098 years and female life expectancy at birth by 0.144 years. again, considering the difference between the mean upper-middle income country and the mean low-income country, in low-income countries males are losing 2.8 years and females are losing 4.5 years of life expectancy at birth in low-income countries compared to upper-middle income countries. other results are similar to the panel model in table 2, except that male and female education becomes statistically insignificant in the model of male life expectancy, and urbanisation becomes insignificant in the models of infant and child mortality. we further report the results of the sensitivity analysis, following conley et al. (2012) in figure 1 (the corresponding regression results are included in the appendix, table a5). the ltz approximation bounds do not encompass the zero line (with 95% confidence) only for very small values of δ, with somewhat greater confidence for mortality rates than for life expectancy. however, the bounds are relatively narrow, so that suggests that our results may be sensitive to violations of the exclusion restriction. as a whole, we interpret these results as showing the vulnerability of our results to violations of the exclusion restriction. as a result, further research should endeavor to identify alternative or additional instruments. 6. conclusion almost half of the population in developing countries, and up to 90% of the rural population, depends upon solid fuels such as firewood, charcoal, coal, crop residues, and animal dung for cooking and heating purposes (bloom et al., 2005). when these solid fuels burn they emit harmful gases, that not only affect child mortality directly but is also associated with water pollution, ocean pollution and climate change (holdren, 1991). our empirical results confirm this relationship using cross-country panel data. we found that countries where the proportion of solid fuel use by households was higher had higher infant and child mortality and lower life expectancy at birth. importantly, our iv regression results demonstrated that these effects are plausibly causal – increases in solid fuel use cause higher infant and child mortality and lower life expectancy. nevertheless, our results are vulnerable to violations of the assumption of exogeneity of our instruments. we argue that they are exogenous, although there is no way to directly test this assertion, and further investigation of alternative instruments that perform better on the conley et al. (2012) sensitivity analysis should be undertaken. the effects that we identify are economically meaningful in terms of size. these results suggest a straightforward policy response. child and infant mortality can be lowered, and life expectancy at birth increased, by reducing household use of solid fuels for cooking and heating. how large could the health gains from reducing solid fuel consumption be? a simple backof-the-envelope calculation provides an indication. if the solid fuel consumption gap between low-income and lower-middle income countries was reduced by 50% (10.31% points), infant and child mortality in the low-income countries would decrease by 16.5 and 29.8 per thousand population9 respectively, and life expectancy at birth for males and females would increase by 1.01 and 1.5 years respectively. according to united nations data,10 low-income countries had 103.397 million children aged under five years in 2015. assuming one-sixtieth of those were infants (aged under one month), the reduction in child and infant deaths (combined) from reducing the solid fuel consumption gap between low-income countries and lower-middle income countries by half is approximately 2.85 million infant and child deaths averted per year. similarly, if the solid fuel consumption gap between lower-middle income countries and the upper-middle income countries was reduced by 50% (4.13% points), infant and child mortality in the lower-middle income countries would decrease by 6.61 and 9 coefficients of infant and child mortality from causal regressions (table 4) are multiplied by the reduced gap. 10 https://esa.un.org/unpd/wpp/download/standard/population/ table 4: instrumental variable regression results models infant mortality rate child mortality rate male life expectancy female life expectancy percent of solid fuel use 1.599*** (0.155) 2.892*** (0.272) −0.0982*** (0.0279) −0.144*** (0.0292) female primary sch. enrolment −0.132*** (0.0431) −0.226*** (0.0757) 0.0120 (0.00774) 0.0180** (0.00811) male primary sch. enrolment 0.117*** (0.0417) 0.199*** (0.0732) −0.00818 (0.00748) −0.0141* (0.00785) log of gdp per capita −2.742*** (0.706) −2.831** (1.241) 0.363*** (0.127) 0.222* (0.133) urban % of population 0.152 (0.128) 0.249 (0.225) 0.0773*** (0.0231) 0.0945*** (0.0242) year fixed effects yes yes yes yes r2 0.502 0.461 0.757 0.739 n 1,289 1,289 1,289 1,289 number of countries 105 105 105 105 *p<0.1; **p<0.05; ***p<0.01. country level clustered standard errors are in parentheses. irfan, et al.: the causal impact of solid fuel use on mortality – a cross-country panel analysis international journal of energy economics and policy | vol 13 • issue 1 • 2023 151 11.95 per thousand population respectively. lower-middle income countries have 319.752 million children. therefore, the reduction in child and infant mortality (combined) from reducing the solid fuel consumption gap between lower-middle income countries and upper-middle income countries by half is approximately 3.5 million infant and child deaths averted per year. these back-of-the-envelope calculations suggest that there are significant potential mortality reductions and health gains available that can be obtained by reducing solid fuel consumption in lowincome and middle-income countries. however, achieving these potential health gains will require direct policy intervention. as irfan et al. (2021a) recently noted for pakistan, income growth or development alone will not be sufficient to switch households, particularly households in rural areas, to cleaner fuel use. in addition, various studies such as hutton et al. (2007), malla et al. (2011), isihak et al. (2012), and irfan et al. (2021b) have explored interventions to reduce the adverse impact of indoor air pollution in developing countries. however, our results only demonstrate that there are substantial benefits in reducing solid fuel use (and even then, we have demonstrated only the benefits in terms of direct health gains and not those resulting from environmental quality improvements). governments will need to weigh these potential benefits of reducing solid fuel consumption against the costs of doing so. the costs are especially salient for low-income and middle-income countries, where government budget constraints may be especially severe. there may also be a role for the international community in reducing mortality from indoor air pollution. interventions in low-income countries that are demonstrated to have a high benefit-cost ratio, but where government budget constraints prevent investment, may need to be subsidized or provided by international donors. given the substantial potential health gains, and the high and unequal health burden currently arising from indoor air pollution, urgent action is required. references acharya, p., mishra, s.r., berg-beckhoff, g. (2014), solid fuel in kitchen and acute respiratory tract infection among under five children: evidence from nepal demographic and health survey 2011. journal of community health, 40(3), 515-521. alva, m., gray, a., mihaylova, b., clarke, p. (2014), the effect of diabetes complications on health-related quality of life: the importance of longitudinal data to address patient heterogeneity. health economics, 23(4), 487-500. angrist, j.d., pischke, j.s. (2008), mostly harmless econometrics: an empiricist’s companion. princeton: princeton university press. available from: https://www.press.princeton.edu/books/ paperback/9780691120355/mostly-harmless-econometrics arnold, j.e.m., köhlin, g., persson, r. (2006), woodfuels, livelihoods, and policy interventions: changing perspectives. world development, 34(3), 596-611. barnes, b., mathee, a., bruce, n., thomas, e. (2009), household energy, indoor air pollution and child respiratory health in south africa. journal of energy in southern africa, 20(1), 4-13. behncke, s. (2012), does retirement trigger ill health? health economics, 21(3), 282-300. berman, s. (1991), epidemiology of acute respiratory infections in children of developing countries. reviews of infectious diseases, 13(supplement_6), s454-s462. bloom, d.e., zaidi, a.k.m., yeh, e. (2005), the demographic impact of biomass fuel use. energy for sustainable development, 9(3), 40-48. bruce, n., perez-padilla, r., albalak, r. (2000), indoor air pollution in developing countries: a major environmental and public health challenge. bulletin of the world health organization, 78(9), 1078-1092. chakrabarti, a. (2012), determinants of child morbidity and factors governing utilization of child health care: evidence from rural india. applied economics, 44(1), 27-37. chen, y., ebenstein, a., greenstone, m., li, h. (2013), evidence on the impact of sustained exposure to air pollution on life expectancy from china’s huai river policy. proceedings of the national academy of sciences u s a, 110(32), 12936-12941. conley, t.g., hansen, c.b., rossi, p.e. (2012), plausibly exogenous. the review of economics and statistics, 94(1), 260-272. cooper, j.a. (1980), environmental impact of residential wood combustion emissions and its implications. journal of the air pollution control association, 30(8), 855-861. currie, j., greenstone, m., meckel, k. (2017), hydraulic fracturing and infant health: new evidence from pennsylvania. science advances, 3(12), e1603021. dherani, m., pope, d., mascarenhas, m., smith, k.r., weber, m., bruce, n. (2008), indoor air pollution from unprocessed solid fuel use and pneumonia risk in children aged under five years: a systematic review and meta-analysis. bulletin of the world health organization, 86(5), 390c-398c. doerr, s.h., santín, c. (2016), global trends in wildfire and its impacts: perceptions versus realities in a changing world. philosophical transactions of the royal society b biological sciences, 371(1696), 20150345. duflo, e., greenstone, m., hanna, r. (2008), indoor air pollution, health and economic well-being’, s.a.p.i.en.s. surveys and perspectives integrating environment and society. available from: https://www.journals.openedition.org/sapiens/130 [last accessed on 20121 feb 13]. edwards, j.h.y., langpap, c. (2012), fuel choice, indoor air pollution and children’s health. environment and development economics, 17(4), 379-406. ezzati, m., kammen, d.m. (2002), the health impacts of exposure to indoor air pollution from solid fuels in developing countries: knowledge, gaps, and data needs. environmental health perspectives, 110(11), 1057-1068. hirschberg, s., burgherr, p., spiekerman, g., dones, r. (2004), severe accidents in the energy sector: comparative perspective. journal of hazardous materials, 111(1), 57-65. holdren, j.p. (1991), population and the energy problem. population and environment, 12(3), 231-255. hsiao, c., hammond, p., holly, a. (2003), analysis of panel data. cambridge: cambridge university press. available from: https://www.ebookcentral.proquest.com/lib/waikato/detail. action?docid=218160 hutton, g., rehfuess, e., tediosi, f. (2007), evaluation of the costs and benefits of interventions to reduce indoor air pollution. energy for sustainable development, 11(4), 34-43. imelda. (2018), indoor air pollution and infant mortality: a new approach. aea papers and proceedings, 108, 416-421. irfan, m., cameron, m.p., hassan, g. (2018a), household energy elasticities and policy implications for pakistan. energy policy, 113, 633-642. irfan, m., hassan, g., cameron, m.p. (2021a), can income growth alone increase household consumption of cleaner fuels? evidence from irfan, et al.: the causal impact of solid fuel use on mortality – a cross-country panel analysis international journal of energy economics and policy | vol 13 • issue 1 • 2023152 pakistan, economics and policy of energy and the environment, 2021(2), 121-146. irfan, m., cameron, m.p., hassan, g. (2021b), interventions to mitigate indoor air pollution: a cost-benefit analysis. plos one, 16(9), e0257543. isihak, s., akpan, u., adeleye, m. (2012), interventions for mitigating indoor-air pollution in nigeria: a cost-benefit analysis. international journal of energy sector management, 6(3), 417-429. jan, i., khan, h., hayat, s. (2012), determinants of rural household energy choices: an example from pakistan. polish journal of environmental studies, 21(3), 635-641. jayachandran, s. (2009), air quality and early-life mortality evidence from indonesia’s wildfires. journal of human resources, 44(4), 916-954. jumbe, c.b.l., angelsen, a. (2011), modeling choice of fuelwood source among rural households in malawi: a multinomial probit analysis. energy economics, 33(5), 732-738. khalequzzaman, m., kamijima, m., sakai, k., chowdhury, n.a., hamajima, n., nakajima, t. (2007), indoor air pollution and its impact on children under five years old in bangladesh. indoor air, 17(4), 297-304. kim, k.h., jahan, s.a., kabir, e. (2011), a review of diseases associated with household air pollution due to the use of biomass fuels. journal of hazardous materials, 192(2), 425-431. lakshmi, p.v.m., virdi, n.k., thakur, j.s., smith, k.r., bates, m.n., kumar, r. (2012), biomass fuel and risk of tuberculosis: a casecontrol study from northern india. journal of epidemiology and community health, 66(5), 457-461. landrigan, p.j., fuller, r., acosta, n.j.r., adeyi, o., arnold, r., basu, n.n., baldé, a.b., bertollini, r., bose-o’reilly, s., boufford, j.i., breysse, p.n., chiles, t., mahidol, c., collseck, a.m., cropper, m.l., fobil, j., fuster, v., greenstone, m., haines, a., hanrahan, d., hunter, d., khare, m., krupnick, a., lanphear, b., lohani, b., martin, k., mathiasen, k.v., mcteer, m.a., murray, c.j.l., ndahimananjara, j.d., perera, f., potočnik, j., preker, a.s., ramesh, j., rockström, j., salinas, c., samson, l.d., sandilya, k., sly, p.d., smith, k.r., steiner, a., stewart, r.b., suk, w.a., van schayck, o.c.p., yadama, g.n., yumkella, k., zhong, m. (2018), the lancet commission on pollution and health. the lancet, 391(10119), 462-512. landrigan, p.j., fuller, r. (2014), environmental pollution: an enormous and invisible burden on health systems in low-and middle-income counties. world hospitals and health services, 50(4), 35-40. larson, b.a., rosen, s. (2002), understanding household demand for indoor air pollution control in developing countries. social science and medicine, 55(4), 571-584. lee, l.y.t. (2013), household energy mix in uganda. energy economics, 39, 252-261. malla, m.b., bruceb, n., batesc, e., rehfuessd, e. (2011), applying global cost-benefit analysis methods to indoor air pollution mitigation interventions in nepal, kenya and sudan: insights and challenges. energy policy, 39(12), 7518-7529. mason, k.l., retzer, k.d., hill, r., lincoln, j.m. (2015), occupational fatalities during the oil and gas boom-united states, 2003-2013. morbidity and mortality weekly report, 64(20), 551-554. mcneill, j.r. (2006), population and the natural environment: trends and challenges. population and development review, 32(s1), 183-201. mekonnen, a., köhlin, g. (2009), determinants of household fuel choice in major cities in ethiopia. available from: https://www. gupea.ub.gu.se/handle/2077/21490 [last accessed on 2017 feb 02]. mishra, v. (2003a), effect of indoor air pollution from biomass combustion on prevalence of asthma in the elderly. environmental health perspectives, 111(1), 71-78. mishra, v. (2003b), indoor air pollution from biomass combustion and acute respiratory illness in preschool age children in zimbabwe. international journal of epidemiology, 32(5), 847-853. oluwole, o., otaniyi, o.o., ana, g.a., olopade, c.o. (2012), indoor air pollution from biomass fuels: a major health hazard in developing countries. journal of public health, 20(6), 565-575. o’neill, b.c., chen, b.s. (2002), demographic determinants of household energy use in the united states. population and development review, 28, 53-88. pandey, m.r., boleij, j.s., smith, k.r., wafula, e.m. (1989), indoor air pollution in developing countries and acute respiratory infection in children. the lancet, 333(8635), 427-429. pope, c.a., ezzati, m., dockery, d.w. (2009), fine-particulate air pollution and life expectancy in the united states. new england journal of medicine, 360(4), 376-386. pundo, m.o., fraser, g.c. (2006), multinomial logit analysis of household cooking fuel choice in rural kenya: the case of kisumu district. agrekon, 45(1), 24-37. smith, k.r. (2002), indoor air pollution in developing countries: recommendations for research. indoor air, 12(3), 198-207. stieb, d.m., judek, s., brand, k., burnett, r.t., shin, h.h. (2015), approximations for estimating change in life expectancy attributable to air pollution in relation to multiple causes of death using a cause modified life table. risk analysis, 35(8), 1468-1478. torres-duque, c., maldonado, d., pérez-padilla, r., ezzati, m., viegi, g., forum of international respiratory studies (firs) task force on health effects of biomass exposure. (2008), biomass fuels and respiratory diseases. proceedings of the american thoracic society, 5(5), 577-590. upadhyay, a.k., singh, a., kumar, k., singh, a. (2015), impact of indoor air pollution from the use of solid fuels on the incidence of life threatening respiratory illnesses in children in india. bmc public health, 15(1), 300. world fire statistics. ctif-international association of fire services for safer citizens through skilled firefighters (no date). available from: https:// www.ctif.org/world-fire-statistics [last accessed on 2018 aug 20]. xue, y. (2018), health returns to modern heating: evidence from china. applied economics, 50(10), 1059-1073. zahnd, a., kimber, h.m. (2009), benefits from a renewable energy village electrification system. renewable energy, 34(2), 362-368. zhu, b., pang, r., chevallier, j., wei, y.m., vo, d.t. (2018), including intangible costs into the cost-of-illness approach: a method refinement illustrated based on the pm2.5 economic burden in china. the european journal of health economics, 20, 501-511. irfan, et al.: the causal impact of solid fuel use on mortality – a cross-country panel analysis international journal of energy economics and policy | vol 13 • issue 1 • 2023 153 appendix table a4: fixed effect models for 105 countries models infant mortality rate child mortality rate male life expectancy female life expectancy percent of solid fuel use 0.759*** (0.0329) 1.460*** (0.0586) −0.135*** (0.00727) −0.163*** (0.00770) female primary sch. enrolment −0.195*** (0.0341) −0.333*** (0.0608) 0.0103 (0.00753) 0.0176** (0.00798) male primary sch. enrolment 0.173*** (0.0331) 0.295*** (0.0591) −0.00668 (0.00732) −0.0138* (0.00776) log of gdp per capita −4.945*** (0.475) −6.588*** (0.848) 0.266** (0.105) 0.172 (0.111) urban % of population −0.318*** (0.0781) −0.554*** (0.139) 0.0548*** (0.0173) 0.0825*** (0.0183) constant 86.87*** (6.118) 123.3*** (10.92) 61.88*** (1.353) 66.48*** (1.434) year fixed effects yes yes yes yes r2 0.68 0.65 0.77 0.74 n 1,277 1,277 1,277 1,277 number of countries 105 105 105 105 *p<0.1; **p<0.05; ***p<0.01. country level clustered standard errors are in parentheses. table a2: first stage instrumental variable regression results for all models without gdp percentage of solid fuel consumption coefficients percentage of forest land of total land 0.751*** (0.114) log of natural gas, lng, lpg production −0.454*** (0.090) female primary sch. enrolment −0.038 (0.029) male primary sch. enrolment 0.031 (0.028) urban % of population −0.613*** (0.066) year fixed effects yes n 1300 number of countries 105 *p<0.1; **p<0.05; ***p<0.01. country level clustered standard errors are in parentheses. table a5: results of conley test for checking exclusion restriction variables infant mortality rate child mortality rate male life expectancy female life expectancy percent of solid fuel use 0.884*** (0.324) 2.560*** (0.492) −0.716*** (0.154) −0.444*** (0.139) female primary sch. enrolment −0.769*** (0.108) −0.909*** (0.167) −0.0646 (0.0584) 0.0881** (0.0368) male primary sch. enrolment 0.689*** (0.105) 0.802*** (0.162) 0.0692 (0.0569) −0.0706** (0.0356) log of gdp per capita −6.876*** (0.893) −7.044*** (1.294) 1.664*** (0.394) 2.339*** (0.335) urban % of population −0.121*** (0.0340) −0.0746 (0.0526) −0.0126 (0.0185) 0.0141 (0.0157) constant 92.95*** (10.20) 95.60*** (15.64) 58.16*** (5.022) 54.14*** (4.209) year fixed effect yes yes yes yes observations 1290 1290 1290 1290 ***p<0.01, **p<0.05, *p<0.1. standard errors in parentheses. table a3: tests for instruments’ validity statistical tests model 1 infant mortality model 2 child mortality model 3 male life expectancy model 4 female life expectancy under identification test (anderson canon. corr. lm statistics) 81.141*** 81.141*** 81.141*** 81.141*** over-identification test (sargan statistics) 1.638 1.557 1.153 0.014 weak identification test (cragg-donald wald f statistic) 42.893 42.893 42.893 42.893 *p<0.1; **p<0.05; ***p<0.01. cragg-donald wald f statistic is greater than 10% maximum relative bias (19.93) which means our instruments are not weak. instrument 1: percentage of forest area, instrument 2: log of annual natural gas, lng, lpg production. table a1: association between log of gdp and instrumental variables log of gdp per capita coefficients percentage of forest land of total land −0.003 (0.005) log of natural gas, lng, lpg production 0.012** (0.006) constant 7.920*** (0.223) year fixed effect yes n 1,290 number of countries 106 *p<0.1; **p<0.05; ***p<0.01. country level clustered standard errors are in parentheses tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020272 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 272-279. evaluation of gas industry competitiveness in the foreign market natalya s. shcherbakova1*, yulia a. nazarova1, olga s. kirichenko2,3, oleg a. gorunov3, andrey v. dubrovsky2 1peoples’ friendship university of russia, (rudn university) moscow, russia, 2financial university under the government of the russian federation, moscow, russia; 3gubkin russian state university of oil and gas (national research university), moscow, russia. *email: shcherbakova-ns@rudn.ru received: 25 june 2020 accepted: 20 september 2020 doi: https://doi.org/10.32479/ijeep.10275 abstract the evaluation of the russian oil and gas companies’ competitiveness in the foreign market under the tough market conditions is of particular importance as it is crucial to retain company’s current position and market share. the article makes qualitative and quantitative evaluation of russian companies in the global gas market. to analyze the competitiveness of the gas industry company in the foreign market, the authors used a dynamic method of evaluating competitiveness coupled with a swot analysis. the dynamic evaluation method offers an opportunity to identify the basic factors that influenced the level of competitiveness of the entity under study and, accordingly, determine the main reserves for increasing its competitiveness. based on the study conducted, recommendations were made on the increase in competitiveness in the current situation of unstable demand and volatile energy prices. by analyzing the pjsc gazprom level of competitiveness, as well as its external and internal environment, indicators were identified the regulation of which will lead to the progressive development of the organization and increase in its competitiveness. the practical relevance of the study lies in the possibility to use both the research outcome and the proposed methods in a development strategy for the gas industry company. keywords: advantages, competitiveness management, swot-analysis, oil and gas companies jel classifications: l10, f23, n70 1. introduction with the rapid humankind development and its exponential growth, the world faced the challenge of finding new sources of energy that could at least partially replace coal and wood. gas and oil became such sources as they are currently the main sources of energy and important commodities in the export market of many countries of the world. natural gas plays an important role in global power consumption, as gas is relatively affordable and environmentally friendly. most (83.4%) of the world’s gas resources are concentrated in twelve countries (figure 1), while 64.4% of global reserves belong to five of them (bp, 2019). gas suppliers export two types of goods: both liquefied (lng) and unliquified natural gas. lng is natural gas artificially liquefied by cooling it to –160°c to facilitate its storing and transporting. if traditional gas is piped, then lng can be transported by sea vessels, but its further application needs maritime gasification terminals. russia is the largest natural gas supplier in the world market in 2018, the country exported 247.9 billion cubic meters (figure 2), which is 26.3% of the global total gas export. in 2018, the russian federation exported 193.8 billion cubic meters to european countries through pipeline and 6.8 billion cubic meters of lng, which accounts for 80.9% of russian exports. this journal is licensed under a creative commons attribution 4.0 international license shcherbakova, et al.: evaluation of gas industry competitiveness in the foreign market international journal of energy economics and policy | vol 10 • issue 6 • 2020 273 according to pjsc gazprom, in 2018 the share of russian gas in european consumption reached 36.7%. more than 11% of russian gas goes to the cis countries. exports of liquefied natural gas from the russian federation accounts for 10% of total exports (24.9 billion cubic meters). a significant increase (over 60%) in 2018 was due to the putting into operation of new facilities the yamal lng plant. the major importers of russian lng: japan (9.4 billion cubic meters), taiwan (3.2 billion cubic meters), south korea (2.6 billion cubic meters). despite their first place in the export of natural gas and significant volumes of deliveries, russian companies face many problems in the global gas market. table 1 depicts the key indicators of russian vertically integrated companies in the oil and gas industry. pjsc gazprom is distinguished by its best performance, ranking 43rd in the list of global companies. pjsc lukoil is also one of the hundred leading oil and gas companies, occupying 98th place. the positions of surgutneftegas and tatneft are much weaker the companies are ranked 335 and 577 respectively. data analysis for 2008-2018 showed that the volumes of gas exported by russia are closely related to emerging economic crises (for example, 2009 and 2014). in the short term, the global oil and gas market is inelastic, that is, a decrease in supply leads to a sharp increase in prices, while producing reserves reports by oil producers, on the contrary, leads to a sharp decrease in prices. a huge problem for the oil and gas market and global economic development is a sharp drop and boom in price quotations (figure 3). in march 2020, the united states recorded negative oil prices, when some manufacturers had to pay extra for unloading oil depots. the oil and gas market has always been under the influence of geo-economic and geopolitical confrontation. especially over the past several years, the market is experiencing constant shocks associated with the sanctions and restrictions, which strongly affect the activities of many large exporting countries, including russia. another striking feature of the market is cross-border trade it is associated with an uneven distribution of resources in the world and specificities of the national economies, since the availability of reserves does not imply their active exploitation. current trends indicate that in recent years the us has been actively increasing oil exports. according to the analytical report and forecasts of the international energy agency (iea), the market situation may change due to the ever-increasing volumes of oil table 1: key financial indicators of russian vertically integrated oil companies in comparison with leading foreign companies in the oil and gas industry, 2017 (billion dollars) rating position company country revenue profit assets market value 11 royal dutch shell netherlands 321.8 15.2 410.7 306.5 13 exxonmobil usa 230.1 20.4 348.8 344.1 21 chevron usa 139.4 10.2 256.4 248.1 26 total france 155.8 8.4 257 168 27 sinoptec china 326.6 8 249.9 138.6 30 petrochina china 282.4 4.1 381.1 220.2 36 bp great britain 251.9 4.3 275.3 152.6 43 pjsc gazprom* russia 112.2 12.2 316.8 57.8 73 pjsc rosneft russia 94.8 3.9 214.2 69 91 equinor (ex. statoil) norway 65.1 4.9 115.4 90.2 95 eni italy 75.5 3.9 143.1 70.7 98 lukoil russia 99.9 7.2 92 60.4 335 surgutneftegas russia 19.8 3.3 74.5 17.2 577 tatneft russia 11.9 2.1 19.2 25.6 *gazprom neft data not shown. source: compiled by the authors according to the analytical center under the government of the russian federation (2018) figure 1: share of total proves reserves by countries source: compiled by the authors according to the bp, 2019 figure 2: export of natural gas of the russian federation (2008-2018) source: compiled by the authors according to the bp, 2019 shcherbakova, et al.: evaluation of gas industry competitiveness in the foreign market international journal of energy economics and policy | vol 10 • issue 6 • 2020274 supplies from the united states over the next years, which may cause a rapid transformation of global oil markets. it is expected that by 2024 the united states will export more oil than russia, and will approach saudi arabia in terms of export volumes. the main competitors of the russian federation in the lng market are qatar, algeria and nigeria, which supply in total 47.5 billion cubic meters of liquefied gas to europe. according to forecasts, over the next 5 years the united states, together with iraq, brazil, norway, guyana and other major countries will provide about 70% increase in global oil supplies. that is, oil importers are now becoming exporters, demand growth is slowing, third world countries (such as indonesia, trinidad and tobago) are developing and starting to export energy, and an increase in lng supplies from the us to europe is supplanting other market players. russian companies mainly specialize in the extraction, export, primary processing of raw materials and their supply abroad and to domestic markets. foreign companies developing in other areas, such as petrochemicals, have higher rates due to different added value and marginality, and in addition they also become resistant to fluctuations in the market. under harsh conditions of lowering price indicators and demand in the oil and gas market, it is especially important for russian companies to search for ways to increase their competitiveness in the foreign market so as not to lose their market share. 2. literature review in 2003, mark melitz published a model of international trade with heterogeneous companies. its ideas were based on assumptions of heterogeneity of companies, horizontal differentiation of goods and imperfect competition. the author emphasized that the most competitive companies have lower costs of entering foreign markets, as a result of which markets witness redistribution in favor of such companies. melitz presented a hierarchy of companies depending on their participation or non-participation in globalization processes. according to this hierarchy, the most competitive are the companies that directly invest in foreign companies, the less competitive are those that operate in both the foreign and domestic markets, and even less competitive firms operate only in the domestic market (melitz, 2003). the need for diversification, including geographical, in the current crisis context is addressed in the article by kirichenko et al. (2020). the authors argue that in conditions of instability in global oil prices, a quantitative evaluation of the degree of company diversification becomes the basis of strategic planning; while the largest foreign and russian companies in the oil and gas industry are preparing their development strategies taking into account the diversification of both types of activities and markets. the need for diversification is confirmed by a qualitative analysis of the activities of russian and foreign energy companies. the start of the russian companies’ integration in the global oil and gas market is discussed in articles by liuhto (2002) and vahtra and liuhto (2006). the authors analyze the growth of russian companies’ investments in projects in other countries. liuhto considers the activities of the two largest russian corporations gazprom and lukoil; liuhto and majuri’s paper (2014) notes that from 2000 to 2013 the volume of direct investments from russia grew from $ 20 billion up to 500 billion dollars. vahtra also writes that the main drivers of the international growth of the russian economy are natural resources companies. in many respects, modern events in the oil and gas industry are related to the topic considered by brunekreeft and guliyev (2009). the authors describe the problems of european energy policy, which include the security of gas supply and the competitiveness of the gas market. the authors think that the security of gas supplies is at risk due to the high and ever-growing dependence of european imports on a limited number of large foreign suppliers, in particular sonatrach, statoil and gazprom. the article examines the possible contradictions between the goals of ensuring supply security and competition, explores the scenarios of the european countries’ response to their dependence on a small number of large foreign suppliers. the competitiveness of russian oil and gas companies in the case of gazprom and rosneft is analyzed in an article by olsen (2013). the author focuses on the government’s role in the international expansion of russian oil and gas companies. locatelli (2014) и boussena and locatelli (2017) in their works note that pjsc gazprom needs to change its traditional export strategy due to growing competition in the european union market and the threat of a new market player emergence imports of liquefied natural gas from the united states. according to the author, the company has to decide whether it should start a price war in order to passively adapt to the impending competition and its role as a “residual supplier” to the eu gas market, or whether it should take advantage of the current price uncertainty. this article explores the possibilities of long-term strategic operations of gazprom, in addition to its simple participation in a price war. it is argued that gazprom may become a key player in the eu gas market. figure 3: global prices for oil, natural gas and lng 1998-2018 source: compiled by the authors according to the bp, 2019 shcherbakova, et al.: evaluation of gas industry competitiveness in the foreign market international journal of energy economics and policy | vol 10 • issue 6 • 2020 275 specific features of the russian oil and gas companies’ operations in the european market are discussed in the book by vlček and jirušek (2019). the authors present the behavioral patterns of the russian gas giant gazprom in the south-eastern european region. the paper by romanova (2016) also analyzes foreign energy policy in terms of geopolitics, the use of legal and technocratic instruments both by state bodies and gazprom. the evaluation of the russian oil and gas companies’ competitiveness is getting more topical bearing in mind the problems in the international market: 1. a drop in gas demand in the european market 2. increased competition between natural gas, coal and renewable energy 3. the transition from national markets to integrated market zones 4. expanding possibilities of europe to diversify imports 5. change in the pricing system in the gas market (kulagin et al., 2016); but any changes in the international market can be apprehended not only in terms of negative influence on the positions of russian oil and gas companies. problems in traditional markets should open the way to the progress of alternative activities. thus, the implementation of the strategically important project “the power of siberia” opens up a new market for the asiapacific region for russia. bradshaw and waterworth (2020) note that the development of significant natural gas reserves in china is associated with geological and technical problems; the demand growth prospects indicate that china may need to expand its lng imports or a second pipeline from russia. the article by bondarenko et al. (2020) analyzes the development prospects of petrochemical companies. the authors evaluate the competitiveness of petrochemical companies in the russian federation and abroad for the current period and until 2030 in accordance with the industry development strategy and draw conclusions about the existing growth potential. the main competitive advantage of russia in the field of petrochemicals is that it has a rich raw material base, since natural resources are the main component of petrochemical production. thus, taking into account present-day challenges in the international oil and gas market, companies need to clearly understand their competitive advantages and be able to evaluate competitiveness in the foreign market in order to turn any problems into future development prospects. 3. methodology of the research to analyze the competitiveness of pjsc gazprom within the framework of this study, it is proposed to apply a dynamic method for evaluating the competitiveness of an enterprise in the foreign market, together with the construction of a swot analysis matrix. the companies’ case proves that most of the market entities successfully developing in the long term owe much to a competent market evaluation, therefore, as part of this study it is proposed to focus on the full model of swot analysis as an example of evaluating the competitiveness of an enterprise. it is worth remembering that the competitiveness of an enterprise is a relative indicator. therefore, the basis for comparison should be similar indicators of competitiveness of the key competing enterprises, which will be used in the dynamic method of evaluating competitiveness, and which will make it possible to efficiently evaluate the competitiveness of an enterprise both in dynamics and in statics. many researchers consider this method the best in terms of the correlation between the reliable results obtained and the labor-intensiveness of their application. the main aspect of the dynamic method is the calculations for several previous periods (3-4), not just for the reporting one. the obtained during the analysis time series significantly increase the reliability of enterprise competitiveness evaluation. the decomposition of the competitiveness indicator obtained by applying the mathematical model of the dynamic method in the context of objects of comparison in combination with an analysis of their dynamics allows us to draw conclusions regarding the main reason for the current level of competitiveness (low sampling efficiency or high activity efficiency of the analyzed enterprise, etc.). then such an analysis of the company’s competitiveness enables identifying the main factors that influence the competitiveness rate of the organization under study. and this, therefore, allows us to determine the main reserves for increasing the competitiveness of the analyzed enterprise. the mathematical model of the dynamic method of evaluating the competitiveness of the gas industry company is shown in table 2. the competitiveness coefficient has the following criteria: the higher с, the greater the level of competitiveness of the analyzed enterprise will have in relation to the selection of competitors. if с > 1, then the competitiveness of the analyzed enterprise will be higher than that of the sample of competitors. if с = 1, then the competitiveness of the analyzed company will be equal to the competitiveness of the sample. with 0 <с <1, the competitiveness of the analyzed company will be lower than the sample of competitors. the first step in evaluating competitiveness by applying a dynamic method is to define matching objects. the objects of comparison with pjsc gazprom will be the main competitors in the foreign market the largest oil and gas companies, whose sales territory covers the whole world. the following most successful players on the world stage over the past 4 years are included in the sample of competitors based on the monitoring of the companies’ international activities in the fuel and energy industry: 1. “exxonmobil” (usa) 2. “royal dutch shell” (netherlands-great britain) 3. “petrochina” (china) 4. british petroleum (great britain) 5. chevron (usa) 6. total (france). thus, the calculation of the competitiveness coefficients for pjsc gazprom in the foreign market will be carried out in comparison shcherbakova, et al.: evaluation of gas industry competitiveness in the foreign market international journal of energy economics and policy | vol 10 • issue 6 • 2020276 with the average value of the total indicators for a sample of the above mentioned competing enterprises. the source of information for calculating competitiveness indicators is the financial statements of companies (revenue, net profit, current assets and short-term liabilities) published on their official websites. all reporting is carried out under international standards (gaap and ifrs) in united states dollar terms. the financial statements of pjsc gazprom are also presented under international financial reporting standards (all data for comparison were converted into us dollars at the average central bank rate for each reporting year). it is believed preferable to use annual reporting information to evaluate and analyze the competitiveness of high-tech enterprises, because such data is not subject to seasonal fluctuations that occur when using reports for shorter periods. thus, a dynamic competitiveness analysis of the pjsc gazprom in the global market will be carried out on the basis of annual reports for 2015-2018. 4. the results of research the final calculation results are presented in the table 3. the analysis of the calculations (table 3) suggests that throughout the analyzed period of 2015-2018 the competitiveness indicator of pjsc gazprom in comparison with the key competitors of the fuel and energy industry in the world market was consistently >1 (1.81> c> 1.23), which indicates the high competitive status of the company compared to its key competitors in the foreign market. imagine the dynamics of the pjsc gazprom level of competitiveness in the international arena in 2015-2018-2018 (figure 4). 5. interpretation of results analyzing figure 4, it can be noted that the competitiveness of pjsc gazprom was subject to fluctuations in 2017, but in general it is positive with respect to the sample of competitors in the foreign market. figure 5 shows the decomposition of the rate of pjsc gazprom international competitiveness according to the sources of this indicator for 2015-2018: operating efficiency coefficient, strategic positioning coefficient, financial condition ratio (indicators c (r), c (i) and c (l) respectively). the analysis of evaluation results allows noting that the situation in the international market is partly similar to the situation in the domestic market. of all the coefficients that form the overall competitiveness coefficient of the analyzed enterprise, only the strategic positioning coefficient in 2017-2018 turned out to be below the normative table 2: the mathematical model of the dynamic method formula decoding the formula c=r (a)/r (s)* i (a)/i (s)* l (a)/l (s) r (a) the operational efficiency of the organization under study r (s) the operational efficiency of the sample i (a) the index of change in revenue of the organization under study i (s) revenue change index for a sample of competitors l (a) liquidity of the studied organization l (s) liquidity for a sample of competitors r (a) = s (a)/e (a) s (a) revenue of the studied company for the reporting period (sales) e (a) costs of the studied company for the reporting period (expenses) r (s)= s (s)/e (s) s (s) revenue from a sample of competitors for the reporting period e (s) costs for the selection of competitors for the reporting period i (a) = s (a)/s (0a) s (0a) the revenue of the organization under study for the previous period i (s) = s (s)/s (0s) s (0s) the revenue from a sample of competitors for the previous period l (a) = ca (a)/cl (a) cl (a) current liabilities of the organization (current liabilities) ca (a) current assets of the organization under study (current assets) l (s) = ca (s)/cl (s) cl (s) short-term liabilities of a sample of competitors ca (s) current assets of a sample of competitors source: compiled by the authors according to voronov, 2014 table 3: pjsc gazprom competitiveness indicators in comparison with the main competitors in the world market indicator calculation 2015 2016 2017 2018 с с(r)*с(i)*с(l) 1.8174 1.8833 1.2314 1.6966 с(r) r (a)/r (s) 1.1285 1.1738 1.0851 1.1634 r (a) s (a)/e (a) 1.1528 1.1950 1.1327 1.2284 s (a) 99,563 92,592 112,865 132,648 e (a) 86,363 77,484 99,642 107,987 r (s) s (s)/e (s) 1.0216 1.0180 1.0438 1.0558 s (s) 209,130 182,334 227,275 276,059 e (s) 204,711 179,103 217,732 261,459 с(i) i (a)/i (s) 1.0414 1.0667 0.9779 0.9676 i (a) s (a)/s (0a) 0.6768 0.9300 1.2189 1.1753 s (a) 99,563 92,592 112,865 132,648 s (0a) 147,100 99,563 92,592 112,865 i (s) s (s)/s (0s) 0.6499 0.8719 1.2465 1.2146 s (s) 209,130 182,334 227,275 276,059 s (0s) 321,763 209,130 182,334 227,275 с(l) l (a)/l (s) 1.5466 1.5042 1.1604 1.5071 l (a) ca (a)/cl (a) 1.8797 1.6830 1.3397 1.7028 ca (a) 65,471 49,005 59,815 67,939 cl (a) 34,831 29,118 44,647 39,898 l (s) ca (s)/cl (s) 1.2154 1.1188 1.1545 1.1298 ca (s) 62,250 59,587 66,203 66,117 cl (s) 51,218 53,257 57,341 58,519 с(a) r (a)*i (a)*l (a) 1.4667 1.8703 1.8498 2.4583 с(s) r (s)*i (s)*l (s) 0.8070 0.9931 1.5022 1.4490 source: calculated and compiled by the authors shcherbakova, et al.: evaluation of gas industry competitiveness in the foreign market international journal of energy economics and policy | vol 10 • issue 6 • 2020 277 table 4: matrix of events based on a comparison of internal and external factors of pjsc gazprom power-capabilities power-threats 1. the search and development of new natural resources will allow pjsc gazprom to strengthen its position and increase its share in the global energy market 2. increased sales in alternative natural gas markets 3. the construction of new pipelines and the reconstruction of old ones will allow the company to win new markets 1. pjsc gazprom needs to develop plans taking into account the risk of changes in the political and, as a consequence, tax situation (the removal of tax exemptions for new fields) 2. construction of new pipelines bypassing troubled transit countries (will ensure the reliability of gas supplies to consumers the main competitive advantage of the company) weakness-capabilities weakness-threats 1. with additional revenue, pjsc gazprom will be able to use it to search for and develop new energy deposits 2. the company needs to sell inefficient non-core assets redistributing funds to highly efficient core assets 1. it is necessary to develop new fields and construct pipelines 2. creation of new funds for future financing of these deposits 3. the company should improve efficiency and establish tighter control over costs by strengthening control over the managerial departments of the enterprise at all levels source: compiled by the authors value (<1). the other coefficients throughout the analyzed period remained higher than the standard value. at the same time, it is worth mentioning a sharp decrease in the values of all component coefficients in 2017. but in 2018, the overall ratio returned to approximately the initial value of 2016, which was mainly due to a sharp increase in the financial condition coefficient. as in the analysis of the pjsc gazprom competitiveness in the domestic market, the strategic positioning coefficient has the smallest strength of all three components (c) of the coefficients over the entire period: which once again confirms the existence of substantial reserves for increasing the overall rate of the company’s competitiveness relying on an increase in this indicator value. figure 6 depicts the dynamics of the pjsc gazprom competitiveness in the context of comparing objects: the resource efficiency coefficient of pjsc gazprom (c (a)) and the resource use efficiency coefficient for a sample of international competitors (c (s)). analyzing the changes in the pjsc gazprom competitiveness in the foreign market in comparison with the objects of comparison c (a) and c (s) presented in figure 6, we can state that in the analyzed period there is a tendency to increase the pjsc gazprom efficiency of resources use (this coefficient since 2015 has increased more than 1.5 times). a positive trend in 2015-2017 was also observed in the whole sample of global competitors, but according to the results of 2018, when the company showed a sharp increase in this indicator, the sample of competitors demonstrated a decrease in this indicator. pjsc gazprom, in particular, has enjoyed a stable increase in coefficient c (a) mainly due to an increase in the company’s revenue change index (i (a)) (revenue in 2018 increased by more than 25% compared to 2015). a similar situation was throughout the sample from 2015 to 2017; an increase in the resource use efficiency by a sample of competitors c (s) was also due to an increase in the index of change in revenue for the sample (i (s)). as in the domestic market, according to the analysis, the competitiveness of pjsc gazprom in comparison with the main oil and gas companies competing in the world market can be generally described as high, but it advisable to pay attention to the fluctuations of this indicator in 2017. summing up the outcome of the dynamic analysis of the pjsc gazprom competitiveness in relation to the leading international competitor companies in the fuel and energy sector,we should note figure 4: dynamics of the competitiveness level of pjsc gazprom in the foreign market in 2015-2018 source: compiled by the authors based on table 3 data figure 5: the dynamics of the pjsc gazprom competitiveness in the foreign market in 2015-2018 according to sources source: compiled by the authors based on table 3 data figure 6: dynamics of pjsc gazprom's competitiveness in the foreign market for objects of comparison c (a) and c (s) source: compiled by the authors based on table 3 data shcherbakova, et al.: evaluation of gas industry competitiveness in the foreign market international journal of energy economics and policy | vol 10 • issue 6 • 2020278 that the main factor for fluctuations in the overall competitiveness coefficient in the foreign market is the operational efficiency of the company, and the basic reserve for increasing the rate of international competitiveness, as well as in the domestic market, is to increase the coefficient of strategic positioning. this, in turn, can be achieved by increasing the volumes of production and sale of energy resources, which, taking into account the current situation in the oil and gas market, is unrealistic; therefore, the emphasis on increasing the volumes of production should be revised towards the sale of processed products, as well as an analysis of the technological possibilities of entering new markets (for example, through the development of natural gas liquefaction facilities). 6. conclusions by analyzing the level of competitiveness of pjsc gazprom, as well as its external and internal environment, indicators were identified, the regulation of which will lead to the progressive development of the organization and increase in its competitiveness. based on the identified factors, we will design gazprom development measures according to a set of four of combinations: power with capabilities, power with threats, weaknesses with capabilities and weaknesses with threats (table 4). the key reserve for increasing competitiveness, identified in the course of the dynamic analysis of gazprom, is the increase in sales volumes to improve the index of changes in the company’s revenue (one of the sources of the company’s competitiveness). this, in turn, can be achieved as follows. to increase sales, pjsc gazprom is proposed to influence the marketing management system and the sales management system. it is recommended to include a number of events in the draft marketing policy of the company: • strengthening the position of russian gas supplied by pjsc gazprom to the eu countries (currently the european market is the most profitable) and concluding long-term cooperation agreements with them. to this end, pjsc gazprom is recommended to diversify export routes and minimize transit risks • increased exports to china (given the rate of chinese economy development in the future this market may become the most profi]) • -strengthening pjsc gazprom’s position in the global lng (liquefied natural gas) market through the implementation of new lng production projects in russia and the sale of this energy carrier in the countries of the asia-pacific region (as this is one of the key growth centers for global lng trade). liquefied natural gas is convenient in transportation and storage and is in great demand in japan and south korea. the conclusion of lng supply agreements with these countries, given the level of their economic development, could significantly increase the company’s sales • entering the north american market; for this, it is recommended that pjsc gazprom enter into a cooperation with american partners in the development of new energy production sites • improving the contractual base of the company and introducing new forms of trade (for example, selling large quantities of gas products through gas auctions) • developing a discount system. as for the foreign market, it is recommended to provide discounts on long-term contracts to increase the flexibility of export policy • conducting an effective advertising campaign (to stimulate demand and effectively promote the company’s energy in the market). in order to develop the sales management system of pjsc gazprom, it is recommended to create competitive advantages at the stage of receiving and processing orders, packaging and preparing products for shipment to customers, shipping products to a vehicle and transporting them to the place of sale or destination. as well to improve the sales network, it is recommended to tighten control over the organization of settlements on transport and loading operations. in the future, with the increase in sales volumes and, as a result, increased profits, pjsc gazprom is suggested to make contributions to the following funds: of development and improvement of processes for the provision of oil transportation (increase the chances of entering new markets), conduct of research and development work (for the innovative development of technologies and the creation of new engineering inventions, with the help of which the level of operational activity can be increased), of development of new places energy production (will give the company new sources of raw materials), as well as to direct part of the profit for financial assistance and social services (to maintain the image). given the fact that pjsc gazprom is a high-tech enterprise in order to increase the rate of competitiveness special emphasis must be placed on introducing innovations. for this, the company is recommended to develop and implement innovative technologies in the following areas: 1. gas business • searching and exploring hydrocarbon deposits, including the development of unconventional resources • increasing the efficiency of existing deposits • developing hydrocarbon resources on the continental shelf • developing new deposits • improving the efficiency of main gas transportation and diversifying methods of gas supply to consumers • increasing the efficiency of gas storage • improving the efficiency of gas and gas-condensate processing • producing liquefied natural gas • selling and using gas. 2. oil business • producing oil • oil refining and petrochemicals producing. shcherbakova, et al.: evaluation of gas industry competitiveness in the foreign market international journal of energy economics and policy | vol 10 • issue 6 • 2020 279 organizational innovation is also important for increasing the competitiveness of a knowledge-based enterprise. thus, pjsc gazprom can recommend the implementation of the following organizational innovations: • developing a knowledge management system • introducing a production management system • introducing quality management systems • increasing operational efficiency, disseminating lean manufacturing principles • introducing a productive asset management system based on an assessment of the technical condition and risks • systemic informatization and automation of production and business processes • introducing a life cycle management system for products (objects) based on modern digital technologies • improving the organizational structure and business processes, including the optimization of the structure of production and technological chains. the implementation of these organizational innovations of pjsc gazprom will pursue the following aims: • reducing the time for preparation, adopting and implementing management decisions (in terms of reducing operating time costs) • reducing uncertainty (increasing the reliability and objectivity of the initial information for decision-making) during the preparation and adoption of decisions • increasing the quality of managerial decisions (a decrease in the losses of pjsc gazprom due to incorrect decisions) • increasing labor productivity, which will be the result of improving management methods, implementing modern quality control systems, introducing corporate knowledge management systems • increasing investment attractiveness of pjsc gazprom, formed by the company’s efficiency. 7. acknowledgment the publication has been prepared with the support of the “rudn university program 5-100.” references analytical center under the government of the russian federation. (2018), oil companies’ efficiency. energy bulletin. available from: https://www.ac.gov.ru/archive/files/publication/a/17636.pdf. bondarenko, t., borodin, a., zholamanova, m., panaedova, g., belyanchikova, t., gurieva, l. (2020), investments to the petrochemical sector: the value of the competitiveness of petrochemical companies. entrepreneurship and sustainability issues, 7(3), 2510-2525. boussena, s., locatelli, c. (2017), gazprom and the complexity of the eu gas market: a strategy to define. post-communist economies, 29(4), 549-564. bp. (2019), statistical review of world energy. available from: https:// www.bp.com/content/dam/bp/business-sites/en/global/corporate/ pdfs/energy-economics/statistical-review/bp-stats-review-2019full-report.pdf. bradshaw, m., waterworth, a. (2020), china’s dash for gas: local challenges and global consequences. eurasian geography and economics. available from: https://www.tandfonline.com/action/ showcitformats? brunekreeft, g., guliyev, f. (2009), gas supply security and the competitiveness on the european gas market. in: jepma, c.j., editor. gas market trading. groningen: energy delta institute. available from: https://www.ssrn.com/abstract=2188099. kirichenko, o.s., komzolov, a.a., nazarova, y.a., shcherbakova, n.s., kirichenko, t.v. (2020), diversification of russian oil and gas upstream companies. international journal of energy economics and policy, 10(3), 112-118. kulagin, v.a., melnikova, s.i., galkina, a. a., osipova, e.d., kozina, e.o. (2016), prospects for russian gas in the european market in the context of changing market conditions, regulatory environment and eu energy policy. international organizations research journal: education, science, new economy, 2016. available from: https://www.cyberleninka.ru/article/n/perspektivyrossiyskogo-gaza-na-evropeyskom-rynke-v-kontekste-izmeneniyarynochnyh-usloviy-regulyatornoy-sredy-i-energeticheskoy. liuhto, k.t. (2002), russian gas and oil giants conquer markets in the west. journal of east-west business, 7(3), 31-72. liuhto, k.t., majuri, s.s. (2014), outward foreign direct investment from russia: a literature review. journal of east-west business, 20(4), 198-224. locatelli, c. (2014), the russian gas industry: challenges to the gazprom model. post-communist economies, 26(1), 53-66. melitz, m.j. (2003), the impact of trade on intra-industry reallocations and aggregate industry productivity. econometrica, 71(6), 16951725. olsen, m. (2013), the future of national oil companies in russia and how they may improve their global competitiveness. vol. 35. united states, houston journal of international law. romanova, t.a. (2016), is russian energy policy towards the eu only about geopolitics? the case of the third liberalisation package. geopolitics, 21(4), 857-879. vahtra, p., liuhto, k. (2006), an overview of russia’s largest corporations abroad. journal of east-west business, 11(3-4), 23-40. vlček, t., jirušek, m. (2019), comparison with russian operations in the sector of natural gas: the case of gazprom. in: russian oil enterprises in europe. cham: palgrave macmillan. p211-232. voronov, d.s. (2014), enterprise competitiveness: assessment, analysis, ways to improve. ekaterinburg: publishing house of ural state technical university. p221. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 5 • 2022 117 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(5), 117-123. relationship between geopolitical risk in major oil producing countries and oil price tin hei alpha yuen1*, wai kee thomas yuen2 1university of hong kong, hong kong, 2hong kong shue yan university, hong kong. *email: alphayuen2012@gmail.com received: 05 june 2022 accepted: 19 august 2022 doi: https://doi.org/10.32479/ijeep.13373 abstract this study has applied granger causality tests and dynamic ordinary least squares (dols) models to examine the relationship between geopolitical risk in major oil-producing countries and the crude oil price before and after the 2008 financial crisis. the granger causality tests show that the geopolitical risk of saudi arabia, russia, the united states and china granger cause changes in crude oil prices. the dols models show that the series in the model are cointegrated. the coefficients for the geopolitical index of canada, russia and china are significant before the 2008 financial crisis sample period. however, the dols model shows that the coefficients for all geopolitical indexes are insignificant after the 2008 financial crisis sample period. the general public and investors generally precept major oil exporters like russia and saudi arabia as the major players in the oil market. however, after the 2008 financial crisis, the discrepancy in the economic needs of the major oil-producing countries has reduced their ability to co-operate crude oil prices. this study also discovered that china plays a significant role in the oil market. keywords: oil prices, oil production, granger causality test, dynamic ordinary least squares model, geopolitical risks jel classifications: q41, q02, f51, h56 1. introduction according to the u.s. energy information administration (2021), the world’s top five largest oil producers in 2020 are the united states, saudi arabia, russia, canada and china respectively. these five predominant oil-producing countries occupied over 50% of the total global oil production in 2020. the oil production in these five countries is significant to the oil supply and the world oil price (u.s energy information administration, 2021). as such, i contribute to the growing literature on the effect of geopolitical risk on oil price by examining the association between the variables in major oil-producing countries. while most previous literature focuses on evaluating the relationship between the world geopolitical risk and the world oil price, no previous literature examines how the geopolitical risk in major oil producers affects the world oil price. consequently, in this essay, i would like to evaluate the effect of geopolitical events in major oil-producing countries on the world oil price by examining the relationship between the country-specific geopolitical risk index of the top five oil-producing countries and the world crude oil price by conducting granger causality test and dynamic ordinary least squares (dols) analysis. 2. literature review geopolitical risk is defined as the risk associated with wars, terrorist acts, and tensions between states that affect the normal and peaceful course of international relations (caldara and iacoviello, 2018). the consequence of geopolitical events on the commodity market has long been realised by economists and has been a popular research field over the past decades across the globe. mitsas et al. (2022) have observed that geopolitical risk dramatically raises the price of most commodity futures, including oil, gold, platinum, and silver, as a consequence of the supply shock from geopolitical events. ding et al. (2021) have also discovered this journal is licensed under a creative commons attribution 4.0 international license yuen and yuen: relationship between geopolitical risk in major oil producing countries and oil price international journal of energy economics and policy | vol 12 • issue 5 • 2022118 that commodity price would typically drove up by the increase in geopolitical risk as commodities are commonly used by investors as a hedging tool against geopolitical uncertainty. nevertheless, the effect of geopolitically risk typically has a stronger effect in the short run while the commodities’ price tends to return to a stable level over a longer period. on the other hand, murray (2018) has used the s&p goldman sachs commodity index and the geopolitical risk index to examine the relationship between geopolitical risk and the commodity price using granger causality and vector autoregressive analysis. surprisingly, there is no granger causality between the general commodity price index and the geopolitical risk. the only granger causality found is between the geopolitical risk index and the price of livestock commodities. nevertheless, by completing separate tests for the time period prior and after the global financial crisis in 2008, he observed the difference between the granger causality effect prior and after the crisis. while geopolitical risk has a granger causality on both the price of livestock and precious metal commodities, there is no evidence of any granger causality on any categories of commodities after the global financial crisis, suggesting the global financial crisis in 2008 may have eliminated the causality between geopolitical risk and commodities’price. for precious metals, one key sub-category of commodity, yilanci and kilci (2021) discovered the causality effect from geopolitical risk to the price of precious metals, including gold, silver, platinum and palladium, and suggested the occurrence of the causality effect as the consequence of the hedging properties of precious metals against raising risk on stock and bond market during economic uncertainty. cryptocurrencies, for instance, bitcoins, are not traditional commodities, but the rising trading volume has made them one of the most popular commodities nowadays. kyriazis (2021) has examined the effect of the change in the level of the geopolitical risk on cryptocurrencies and surprisingly discovered that the level of geopolitical risk has an extremely strong predictive power on the price and volatility of cryptocurrencies, notably bitcoins, suggesting cryptocurrencies as a better hedging tool than traditional commodities like gold and silver. for energy, which is another predominant sub-category of commodities, liu et al. (2021) discovered that geopolitical risk would positively impact energy volatility significantly in the long run, and one standard deviation increase in the geopolitical risk would raise the volatility of crude oil, heating oil and natural gas by 13.24%, 28.01% and 15.30% respectively. they also discovered that the geopolitical threat rather than the actual geopolitical event is the reason for the impact of geopolitical risk on energy volatility. while geopolitical risk has a uniform impact on the volatility of energy commodities, gursoy (2021) has examined the relationship between geopolitical risk and the price of nonrenewable energy using the lee-strazicich unit root test and the hatemi-j asymmetric causality analysis and discovered the price of oil as the only energy commodity in a one-way positive symmetrical causality relationship with geopolitical risk, suggesting the uniqueness of oil price in being affected by the change in geopolitical risk. for oil, kyrazis (2021); mitsa et al. (2022); gursoy (2021); su et al. (2019); duan et al. (2021) have all discovered the positive relationship between the level of geopolitical risk and the oil price based upon qualitative evidence from different econometric methods. selmi et al. (2020) stated that a strong positive relationship between geopolitical risk and the oil price is anticipated, especially when major oil exporters or importers are at war. when major oil exporters get into wars, the world oil supply increases uncertainly. as the world oil demand rises with an uncertain supply, oil producers who are incapable of producing enough oil have to guarantee that sufficient oil is stockpiled to cover operations, resulting in the oil price rise. additionally, su et al. (2019) have also discovered that high geopolitical risk would raise the oil price as a consequence of the shortage in supply, in particular when geopolitical events occur in oil-exporting countries. li et al. (2020) have identified three predominant channels of how geopolitical risk affects the world crude oil prices. the first important channel they identified is the impact on oil production and demand by geopolitical events, which would significantly affect the oil price, consistent with the rationale suggested by su et al. (2019) and selmi et al. (2020). the second channel they pointed out is the effect on investor sentiment by geopolitical risk as the hedging properties of commodities and financial speculation by investors would significantly impact the oil price. the third channel they identified is the impact on energy conversion by geopolitical risks, which would affect the crude oil price to a large extent. consistent with other commodities, duan et al. (2021) have also suggested through wavelet-based analysis that the effect of geopolitical risk on the oil price solely occurred in the short and medium run, while geopolitical events would not affect the oil price in the long run. in addition to the price, liu et al. (2019) have examined the effect of geopolitical events on oil volatility by adding geopolitical risk to the garch-midas-gprs model, discovering that geopolitical risk would significantly impact the oil volatility, in particular for oil future. huang et al. (2021) have used nonlinear granger causality tests and a dcc-mvgarch model based on high-frequency data to examine the correlation between geopolitical risk and oil prices and further discovered that geopolitical risk mainly affects the oil market by affecting its volatility rather than its return. most literature examined the relationship between geopolitical risk and oil price using global data. however, selmi et al. (2020) have pointed out that the consequence of geopolitical risk on the oil price is countries-specific and different countries tend to be affected by the level of geopolitical risk differently. ozcelebi and tokmakcioglu (2020) have employed the time-varying parameter structural vector autoregression models to examine the asymmetric impacts of the geopolitical risk on the world oil price based on the county-specific gpr index of four bric countries, which are russia, china, india and brazil. while the tests indicate the change in the level of geopolitical risk would result in a subsequent change in the world oil price in the same direction for all four countries, the magnitude of the effect is not identical. it is suggested the correlation between the geopolitical risk and oil price is highest in china and lowest in yuen and yuen: relationship between geopolitical risk in major oil producing countries and oil price international journal of energy economics and policy | vol 12 • issue 5 • 2022 119 india. additionally, ozcelebi and tokmakcioglu have also identified that the difference between the impact of geopolitical events on the oil price is not notable among oil-exporting and importing countries. demier et al. (2019) have also examined the impact of geopolitical risk on different regional markets, including dubai and tapis, and discovered that the impact of geopolitical events on the oil price is not uniform in different regional markets. the research results in specific regional markets are not capable of being applied to others. nevertheless, they also pointed out that geopolitical risk mostly affects the volatility of the oil price rather than the oil price itself. salisu et al. (2021) have further contributed to the effect of geopolitical risk in the oil market by examining the effect of geopolitical threat and real act on the oil market separately. they surprisingly discovered that increase in geopolitical risk is not necessarily resulting in higher tail risk in the oil market. while threat did increase the tail risk, real acts would decrease the tail risk in the oil market. 3. data this study evaluates the relationship between geopolitical risk and oil price. in this study, the monthly country-specific geopolitical risk index created by caldara, dario and matteo iacoviello (2022) is used as the proxy for the geopolitical risk in the five major oils producing countries, namely the united states, saudi arabia, russia, canada and china. the data was downloaded from https://www.matteoiacoviello.com/gpr.htm on april 10, 2022. the geopolitical risk index tracks the sum of newspaper articles reviewing rising geopolitical risks divided by the sum of all published newspaper articles per month based upon automated text searches on the electronic archives of 10 newspapers from the united states and canada, which are the chicago tribune, the daily telegraph, the financial times, the globe and mail, the guardian, the los angeles times, the new york times, usa today, the wall street journal, and the washington post. crude oil futures serve as the proxy for the crude oil price. west texas intermediate (wti) crude oil futures are used as the proxy for the crude oil price, and the monthly data is downloaded from www.investing.com. the study’s timeframe is selected between january 1985 to february 2022 according to the availability of country-specific geopolitical risk indexes. table 1 reported the descriptive statistics of all variables. comparing the mean of the country-specific geopolitical risk index, the geopolitical risk index of the united states is significantly greater than other countries. however, it only reflects that geopolitical risk events are mentioned at a higher frequency in the newspaper in the united states, rather than indicating that the united states has a higher geopolitical risk than the other four nations. the kurtosis values of the geopolitical risk index of canada, russia, saudi arabia and the united states are extremely high, indicating that their distribution is more peaked than the normal distribution and tends to have heavy tails. china is the only one of the top five oil-producing nations that has a geopolitical risk index of normal kurtosis value, indicating the geopolitical risk index of china has a distribution that is closer to the normal distribution. considering the standard deviation and sample variance of the geopolitical risk index of the five nations, the united states has significantly higher values compared to the other four nations, indicating that the geopolitical risk of the united states is less stable than other top oil-producing countries. all five country-specific geopolitical risk indexes have shown a positively skewed distribution, indicating that most of the values are crowded around the left tail of the distribution. 4. methodology murray (2018) has identified that the positive relationship between commodities’ price and geopolitical risk was eliminated after the occurrence of the global financial crisis in 2008. this study works with three basic time series, the period prior to the 2008 global financial crisis between january 1985 to june 2008, the period after the 2008 global financial crisis from january 2009 to february 2022 and the full sample period between january 1985 to february 2022. consequently, the time series before and after the global financial crisis are evaluated in order to identify the effect of the global financial crisis on the relationship between oil price and geopolitical risk. granger causality test and dols are conducted to evaluate the relationship between the country-specific geopolitical risk indexes of the top five oil-producing countries and the crude oil price, according to granger (1969), a variable (country-specific geopolitical risk index of a certain nation) is said to granger cause another variable (crude oil price) if past and present values of the index aid in forecasting the crude oil price. following the standardised procedure from ghosh (2002); oxley and greasley (1998); obadi and korecek (2018); foresti (2006), augmented table 1: descriptive statistics gpr_can gpr_ru gpr_sa gpr_usa gpr_chn wti mean 0.223 0.760 0.216 2.304 0.400 44.635 standard error 0.008 0.020 0.016 0.059 0.012 1.362 median 0.181 0.666 0.130 2.058 0.333 32.610 standard deviation 0.160 0.428 0.348 1.249 0.249 28.762 sample variance 0.026 0.183 0.121 1.561 0.062 827.276 kurtosis 29.917 13.072 56.102 31.162 2.664 -0.401 skewness 4.331 2.461 6.727 4.594 1.512 0.836 minimum 0.057 0.205 0.017 0.751 0.070 10.420 maximum 1.724 4.345 3.572 13.229 1.521 140.000 observations 446.000 446.000 446.000 446.000 446.000 446.000 “gpr_can,” “gpr_ru,” “gpr_sa”,“ gpr_usa”,“ gpr_chn”,“ wti” represent the country-specific geopolitical risk index of canada, russia, saudi arabia, the united states, china and the wti crude oil futures respectively. wti: west texas intermediate yuen and yuen: relationship between geopolitical risk in major oil producing countries and oil price international journal of energy economics and policy | vol 12 • issue 5 • 2022120 dickey fuller unit root tests are performed to ensure the stationarity of the series in order to meet the prerequisites of conducting granger causality tests. for the augmented dicky fuller unit root test, if the null hypothesis is rejected, it represents that there is a unit root present, and the data series is stationary. according to the result of the unit root test, the first difference form of the oil price, which is stationary, is used to replace the nonstationary oil price series in performing the granger causality test. the granger causality test would be carried out as: wti wti wti gpr gprt t t t t t� � � � � �� � � �� � � � � �0 1 1 2 2 1 1 2 2 (1a) gpr gpr gpr wti wti ut t t t t t� � � � � �� � � �� � � � �0 1 1 2 2 1 1 2 2 (1b) f-test statistics would be used to test the hypothesises. equation 1a refers to the hypothesis that the country-specific geopolitical risk index of that particular nation is said to granger cause the crude oil price. equation 1b refers to the hypothesis that the crude oil price is said to granger cause the country-specific geopolitical risk index of that certain nation. in addition to testing the granger causality, dols is also carried out to examine the long-run cointegration relationship between the country-specific geopolitical risk indexes of the five predominant oil-producing countries and the crude oil price. the crude oil price is the dependent variable, and the five country-specific geopolitical risk indexes are the independent variables. dynamic ordinary least squares estimates regression models based on cointegrated variables and solve the bias of regression caused by the asymptotic endogeneity and serial correlation (saikkonen, 1992; stock and watson, 1993). the equation is shown below: wti gpr can gpr ru gpr sa gpr usa t t t t t � � � � � � � � � � � � 1 2 3 4 ( _ ) ( _ ) ( _ ) ( _ ) 55 ( _ )gpr chn t t�� (2) where t = time period a cointegration test is performed following the standardised procedure to validate the model. in this study, the hansen parameter instability cointegration test initiated by hansen (1992) is conducted to test the null hypothesis of cointegration. 5. empirical results and discussion 5.1. augmented dickey-fuller test table 2 presents the results of the augmented dicky fuller test. the country-specific geopolitical risk indexes are stationary, but the crude oil price is non-stationary. as a result, the stationary first difference in oil price is used instead in granger causality test. 5.2. granger causality table 3 presents the pairwise granger causality tests for the observations in the full sample period between january 1985 and february 2022. in the full sample period, both the country-specific table 3: pairwise granger causality tests (full sample period) pairwise granger causality tests sample: 1985m01 2022m02 lags: 2 dwti (first difference in oil price) null hypothesis: obs f-statistic prob. gpr_sa does not granger cause dwti** 443 4.42469 0.0125 dwti does not granger cause gpr_sa 0.15096 0.8599 gpr_chn does not granger cause dwti** 443 4.5288 0.0113 dwti does not granger cause gpr_ chn* 2.8027 0.0617 gpr_can does not granger cause dwti 443 0.98449 0.3745 dwti does not granger cause gpr_can 0.59429 0.5524 gpr_ru does not granger cause dwti 443 1.85698 0.1574 dwti does not granger cause gpr_ru 1.35937 0.2579 gpr_usa does not granger cause dwti 443 1.23845 0.2908 dwti does not granger cause gpr_usa 0.86371 0.4223 *significant at 10%, **significant at 5% geopolitical risk indexes of china and saudi arabia would granger cause the oil price at the 5% significance level. in the full sample period, out of the five major oil-producing countries, surprisingly, only the geopolitical risk of saudi arabia and china are influential to the crude oil price, suggesting that the geopolitical risk of major oil-producing nations may not be instrumental to the crude oil price. in fact, while china, the united states, saudi arabia, canada and russia are predominant oil producers, only saudi arabia and russia are predominant oil exporters, suggesting that major oil-producing countries may not be significant to the oil supply as many of them tend to self-consume their oil production, for instance, china and the united states. while saudi arabia is the second biggest oilproducing nation behind the united states, saudi arabia is the biggest net oil-exporting nation, so its significant impact on the oil supply rationalises the enormous influence of its geopolitical risk. china has seldom been included in the discussion of the oil price, and most people neglect the influence of china in the oil market. in addition to being one of the top oil-producing nations, china is also one of the biggest net oil importers due to the high oil demand in china, rationalising the strong influence of the geopolitical risk in china on the oil price. the result also suggests that both the geopolitical risk of predominant oil importers and exporters are significant to the oil price, so the geopolitical situation in net oil importers like china should also be strongly considered in the oil market analysis. table 4 presents the pairwise granger causality tests of the observations prior to the global financial crisis in 2008. table 5 table 2 : augmented dickey-fuller test variable adf test t-stat p-value gpr‑can –9.430286 0 gpr‑ru –6.485417 0 gpr‑sa –6.103759 0 gpr‑usa –6.662178 0 gpr‑chn –3.222129 0.0194 wti –1.973224 0.2988 dwti –16.99153 0 dwti is the first difference form of wti yuen and yuen: relationship between geopolitical risk in major oil producing countries and oil price international journal of energy economics and policy | vol 12 • issue 5 • 2022 121 presents the pairwise granger causality tests of the observations after the global financial crisis in 2008. prior to the global financial crisis in 2008, russia and saudi arabia were the only two nations in which their geopolitical risk indexes granger caused the oil price at the 5% significance level. at the 10% significance level, china would also granger cause the oil price. after the global financial crisis, saudi arabia and the united states are the only two nations where their geopolitical risk indexes granger cause the oil price at the 5% significance level. while the geopolitical risk of china has been influential to the crude oil price prior to the 2008 global financial crisis, it has not been that influential since the crisis occurred. in fact, even though china’s oil demand has reclaimed its upward trend after the 2008 global financial crisis, matsumoto (2012) stated that the oil demand of china has decreased significantly from the second half of 2008 to early 2009. he also stated that china’s oil demand started to decelerate in 2011 due to the slower economic growth in china. while china remains one of the biggest oil importers across the globe, china’s oil demand has decreased during the financial crisis and decelerated after the crisis due to slower economic growth, lowering china’s influence on the oil price, rationalising why the geopolitical risk of china did not granger cause the oil price after the financial crisis. comparing the period before and after the 2008 global financial crisis, it is surprising to see the influence of russia’s geopolitical risk on the oil price disappear. while the recent 2022 surge in oil price may prove that russia’s control over oil price is still high, statistics show that the geopolitical risk of saudi arabia and the united states should be the two nations that influence the oil price the most in recent years. since the 2008 global financial crisis, the geopolitical risk of the united states has been increasingly influential to the oil price as a consequence of the significant rise in oil production in the united states. from 2009 to 2019, the united states has doubled its share of world oil production from 8.91% to 17.9% by increasing its oil production at a much quicker rate than its main competitors, for instance, russia and saudi arabia (kutlu, 2020). 5.3 dols table 6 presents the result of hansen parameter instability test for the three dynamic ordinary least squares models. all three cointegration tests failed to reject the cointegration null hypothesis, validating that the series are cointegrated. table 7 presents the results for the three dynamic ordinary least squares (dols) models for the full sample period, the period prior to the 2008 global financial crisis, and the period after the 2008 global financial crisis, respectively. in dols models, the observation is consistent with murray (2018), in which the statistically significant relationship between geopolitical risk and the oil price has all been eliminated after the 2008 global financial crisis, proving the significance of 2008 global financial crisis in affecting the effect of geopolitical risk on the commodity market. in the full sample period, the coefficient for geopolitical risk indexes of china and canada are significant at the 5% significance level, while the coefficient for the geopolitical risk index of russia is significant at 10% significance level. for the period prior to the 2008 global financial crisis, the coefficient for the geopolitical risk indexes of china and russia are significant at the 5% significance level. the dols model shows that saudi arabia failed to establish a long-run relationship with the oil price in all three sample periods. it seems that the geopolitical risk in saudi arabia tends to cause the failure of opec in manipulating the oil price in the long run. canada and russia are both major net oil-exporting nations across the globe, and the geopolitical risk of both nations tends to have a negative relationship with the oil price, referring that a higher level of geopolitical risk in these nations would tend to lower the oil price. this result differs from the public perception that higher geopolitical risk in oil-exporting countries tends to impact the world oil supply and raise the oil price. one possible explanation is that high geopolitical risk may cause the countries to increase the supply and export of oil so as to improve trade surplus and accumulate foreign reserves to define the increasing geopolitical risk. nevertheless, the high geopolitical risk does not always refer to wars or terrorist acts. consequently, while war would affect table 4: pairwise granger causality tests (period prior to the 2008 global financial crisis) pairwise granger causality tests sample: 1985m01 2008m06 lags: 2 dwti (first difference in oil price) null hypothesis: obs f-statistic prob. gpr_sa does not granger cause dwti** 279 5.57018 0.0043 dwti does not granger cause gpr_sa 0.24008 0.7867 gpr_chn does not granger cause dwti* 279 2.94836 0.0541 dwti does not granger cause gpr_chn 1.2629 0.2845 gpr_can does not granger cause dwti 279 1.30345 0.2733 dwti does not granger cause gpr_can 0.02322 0.9771 gpr_ru does not granger cause dwti** 279 4.39683 0.0132 dwti does not granger cause gpr_ru 0.38973 0.6776 gpr_usa does not granger cause dwti 279 0.75715 0.47 dwti does not granger cause gpr_usa 0.17573 0.8389 *significant at 10%, **significant at 5% table 5: pairwise granger causality tests (period after the 2008 global financial crisis) pairwise granger causality tests sample: 2009m01 2022m02 lags: 2 dwti (first difference of oil price) null hypothesis: obs f-statistic prob. gpr_sa does not granger cause dwti** 158 4.08071 0.0188 dwti does not granger cause gpr_sa 0.10064 0.9043 gpr_chn does not granger cause dwti 158 1.98038 0.1415 dwti does not granger cause gpr_chn 1.82069 0.1654 gpr_can does not granger cause dwti 158 2.0201 0.1362 dwti does not granger cause gpr_can 1.17441 0.3118 gpr_ru does not granger cause dwti 158 0.70498 0.4957 dwti does not granger cause gpr_ru 1.39393 0.2512 gpr_usa does not granger cause dwti** 158 4.84344 0.0091 dwti does not granger cause gpr_usa 1.69987 0.1861 *significant at 10%, **significant at 5% yuen and yuen: relationship between geopolitical risk in major oil producing countries and oil price international journal of energy economics and policy | vol 12 • issue 5 • 2022122 the oil supply and demand in the nation, a high geopolitical risk in major oil-exporting countries should not always be interpreted as an adverse impact on the world oil supply and resulting in a rise in the oil price. as one of the largest net oil importers globally, china is influential in the oil price during the full sample period and prior to the 2008 global financial crisis. according to the models, china’s influence on the oil market disappeared after the 2008 global financial crisis due to decelerated oil demand from slower economic growth, which is consistent with the result of the granger causality tests. the result from the models indicates that the geopolitical risk of china has established a long-run relationship with the oil price in the two sample periods, referring that higher geopolitical risk in china would tend to raise the oil price, indicating that higher geopolitical risk in china would raise the oil demand of china. the increase in the geopolitical risk of china usually comes from territory conflict with neighbouring nations and also the relationship with the united states in recent years. a potential military conflict with neighbouring nations, which would raise the geopolitical risk, would raise china’s oil demand and the oil price as china is one of the major oil importers. while the relationship between china and the united states is at its all-time low, china is purchasing more oil from the united states despite the high price to fulfil the trade deal signed between the two nations. consequently, the increase in geopolitical risk in china has actually raised its oil demand and thus established a long-run relationship with the oil. 6. conclusion the granger causality tests show that saudi arabia and china’s geopolitical risk influences the crude oil price in the full sample period. the geopolitical risk of saudi arabia, russia and china granger cause change in oil prices before 2008 financial crisis sample period. after the 2008 financial crisis sample period saudi arabia and usa granger cause the change in crude oil prices. the dols models show the series in the model are cointegrated. the coefficients for the geopolitical index of canada, russia and china are significant for the full sample period. before 2008 financial crisis sample period, the coefficients for the geopolitical index of canada, russia and china are significant. however, the dols model shows that the coefficients for all geopolitical indexes are insignificant after the 2008 financial crisis sample period. the general public and investors generally precept major oil exporters like russia and saudi arabia as the major players in the oil market. however, after the 2008 financial crisis, the major oil-producing countries’ discrepancy in economic needs has reduced their influential power. thus, the geopolitical risk of major production countries does not significantly affect crude oil prices. with reference to murray (2018) ‘s research on the effect of 2008 global financial crisis on the relationship between commodities’ price and geopolitical risk, this study would also like to confirm that the relationship between oil price and geopolitical risk has changed after the 2008 global financial crisis. this study has discovered the significance of china in the oil market, which is different to the general public’s perception. nevertheless, this study indicated that china, as one of the major crude oil-producing nations and one of the biggest net oil importers, has a strong relationship between its geopolitical risk and oil price both in the short run and the long run based on the results from granger causality tests and the dols models respectively. on the other hand, while granger causality tests have indicated the short-run effect of the geopolitical risk of saudi arabia in the oil price, the dynamic ordinary least squares models have indicated that the geopolitical risk of saudi arabia has failed to establish a long-term relationship with the oil price. table 6: hansen parameter instability lc statistic stochastic deterministic excluded prob.* trends (m) trends (k) trends (p2) 1985m01 to 2022m02 0.001785 5 0 0 >0.2 1985m01 to 2008m06 0.002753 5 0 0 >0.2 2009m01 to 2022m02 0.007552 5 0 0 >0.2 table 7: dynamic ordinary least squares (dols) sample period dependent variable: wti gpr_can gpr_ru gpr_sa gpr_usa gpr_chn α β1 β2 β3 β4 β5 1985m01 to 2022m02 40.9236** (4.465772) –105.012** (–2.038009) –17.6951* (–1.673641) 7.3603 (0.573798) 6.9084 (1.049211) 56.7344** (4.389495) 1985m01 to 2008m06 25.7476** (2.834975) 19.7042 (0.450546) –22.2733** (–2.131507) 9.0025 (0.965078) –3.4208 (–0.611491) 74.8887** (3.417242) 2009m01 to 2022m02 97.7796** (3.923413) –65.7414 (–0.663845) 3.19229 (0.163172) –31.5489 (–0.769618) –0.4096 (–0.020723) –19.7273 (–0.939955) r2 adjusted r2 s.e. 1985m01 to 2022m02 0.3248 0.2928 24.16157 1985m01 to 2008m06 0.3650 0.3160 17.18181 2009m01 to 2022m02 0.1925 0.0738 21.0133 **, *denote 5% and 10% significance levels correspondingly, t-statistics is indicated in parenthesis yuen and yuen: relationship between geopolitical risk in major oil producing countries and oil price international journal of energy economics and policy | vol 12 • issue 5 • 2022 123 references caldara, d., iacoviello, m. (2018), measuring geopolitical risk. international finance discussion papers, no. 1222. demirer, r., gupta, r., ji, q., tiwari, a.k. (2019), geopolitical risks and the predictability of regional oil returns and volatility. opec energy review, 43(3), 342-361. ding, q., huang, j., zhang, h. (2021), the time-varying effects of financial and geopolitical uncertainties on commodity market dynamics: a tvp-svar-sv analysis. resources policy, 72, 102079. duan, w., khurshid, a., rauf, a., khan, k., calin, a.c. (2021), how geopolitical risk drives exchange rate and oil prices? a wavelet-based analysis. energy sources part b: economics planning and policy, 16(9), 861-877. foresti, p. (2006), testing for granger causality between stock prices and economic growth. germany: university library of munich. ghosh, s. (2002), electricity consumption and economic growth in india. energy policy, 30(2), 125-129. granger, c.w. (1969), investigating causal relations by econometric models and cross-spectral methods. econometrica: journal of the econometric society, 37(3), 424-438. gürsoy, s. (2021), analysis of the energy prices and geopolitical risk relationship. uluslararası ekonomi siyaset i̇nsan toplum bilimleri dergisi, 4(2), 69-80. hansen, b.e. (1992), testing for parameter instability in linear models. journal of policy modeling, 14(4), 517-533. huang, j., ding, q., zhang, h., guo, y., suleman, m.t. (2021), nonlinear dynamic correlation between geopolitical risk and oil prices: a study based on high-frequency data. research in international business and finance, 56, 101370. kutlu, o. (2020), u.s. oil production up 134% in last 11 years. ankara: anadolu agency. available from: https://www.aa.com.tr/en/ economy/us-oil-production-up-134-in-last-11-years/1896901 [last accessed on 2022 may 20]. kyriazis, ν.a. (2021), the effects of geopolitical uncertainty on cryptocurrencies and other financial assets. sn business and economics, 1(1), 1-14. liu, j., ma, f., tang, y., zhang, y. (2019), geopolitical risk and oil volatility: a new insight. energy economics, 84, 104548. liu, y., han, l., xu, y. (2021), the impact of geopolitical uncertainty on energy volatility. international review of financial analysis, 75, 101743. mitsas, s., golitsis, p., khudoykulov, k. (2022), investigating the impact of geopolitical risks on the commodity futures. cogent economics and finance, 10(1), 2049477. mitsumoto, t. (2012), decelerated china’s oil demand. ieej: japan: the institute of energy economics. murray, d. (2018), geopolitical risk and commodities: an investigation. global commodities applied research digest, 3, 95-106. obadi, s.m., korecek, m. (2018), the crude oil price and speculations: investigation using granger causality test. international journal of energy economics and policy, 8(3), 275. oxley, l., greasley, d. (1998), vector autoregression, cointegration and causality: testing for causes of the british industrial revolution. applied economics, 30(10), 1387-1397. ozcelebi, o., tokmakcioglu, k. (2022), assessment of the asymmetric impacts of the geopolitical risk on oil market dynamics. international journal of finance and economics, 27(1), 275-289. saikkonen, p. (1992), estimation and testing of cointegrated systems by an autoregressive approximation. econometric theory, 8(1), 1-27. salisu, a.a., pierdzioch, c., gupta, r. (2021), geopolitical risk and forecastability of tail risk in the oil market: evidence from over a century of monthly data. energy, 235, 121333. selmi, r., bouoiyour, j., miftah, a. (2020), oil price jumps and the uncertainty of oil supplies in a geopolitical perspective: the role of opec’s spare capacity. international economics, 164, 18-35. stock, j.h., watson, m.w. (1993), a simple estimator of cointegrating vectors in higher order integrated systems. econometrica journal of the econometric society, 61(4), 783-820. su, c.w., qin, m., tao, r., moldovan, n.c. (2021), is oil political? from the perspective of geopolitical risk. defence and peace economics, 32(4), 451-467. u.s. energy information administration (eia). (2021), frequently asked questions (faqs)-u.s. united states: energy information administration (eia). available from: https://www.eia.gov/tools/ faqs/faq.php?id=709&t=6 [last accessed on 2022 may 20]. yilanci, v., kilci, e.n. (2021), the role of economic policy uncertainty and geopolitical risk in predicting prices of precious metals: evidence from a time-varying bootstrap causality test. resources policy, 72, 102039. . international journal of energy economics and policy | vol 6 • issue 3 • 2016374 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2016, 6(3), 374-380. uncertainty of oil proved reserves and economic growth in iran elaheh asadi mehmandosti1*, fatemeh bazzazan2, mir hossein mousavi3 1department of economics, alzahra university, tehran, iran, 2department of economics, alzahra university, tehran, iran, 3department of economics, alzahra university, tehran, iran. *email: elahehasadi@alzahra.ac.ir abstract the relationship between the oil and the level of economic activity is a fundamental empirical issue in macroeconomics. also, a part of major debates between the pessimists and the optimists approaches about economic growth is how uncertainty of proved reserves of nonrenewable energy resources as a one of main inputs, effects on the economic growth; in other words, on the base of some optimistic new economic growth models, the uncertainty through positive shocks positively effects on the economic growth. so, to find some evidences about it, in this research we try to find experimentally direct effects of uncertainty of oil proved reserves on macroeconomics of iran by using annually data from 1980 to 2013 by using multivariate generalized auto-regressive conditional heteroskedasticity in-mean vector auto-regression (var) model. we find that uncertainty in oil proved reserves has not had statistically significant effect on aggregate output and the responses to positive and negative shocks are symmetric. keywords: uncertainty, oil proved reserves, time allocation of resources, vector auto-regression multivariate generalized auto-regressive conditional heteroskedasticity-in-mean vector auto-regression jel classifications: c32, e10, q32 1. introduction oil is one of the strategic goods in the world and also one of the principal factors of production and economic growth especially after industrial revolution. moreover, iran has 4th rank of owning oil proved reserves in the world and as oil export income has high share in the annual gross domestic production (gdp), iran has an economic depending to oil. in addition, as oil is a major factor in the production and is non-renewable, there are many doubts about future economic growth of iran; so, to ensure long term economic growth and intergenerational justice, time allocation of non-renewable energy resources must be attend. furthermore, economists in the world have two pessimistic and optimistic approaches about economic growth. in 1798, malthus (1798) suggested that neither technological progress nor the human ingenuity would be sufficient to overcome obstacles of population growth. he criticized the prevailing idea that nature would never limit growth. this view had already been expressed by the french philosopher nicolas de condorcet in 1794 (malthus, 1798). the british classical economists likewise argued that in principle nature could limit growth, but such natural constraint would not be reached in any meaningful time frame. the most famous scholar who took this stance was mill (1862). in 1862 he argued that social institutions and increases in social welfare would slow down population growth. since the 1890s the debate increasingly considered the depletion of non-renewable resources as a major obstacle for growth. in this context, the former us president roosevelt (1908) promoted the conservation movement. research was deepened by hotelling in 1931 and barnett and morse in 1963, who took an optimistic view. barnett and morse (1963) assumed that technological development would produce substitutes for scarce resources, reduce the relative prices of these goods and expand the total amount of economic reserves. even so, they considered how the depletion of non-renewable resources could impede economic growth and what the optimal rate of depletion would be. although they allowed for the possibility of scarce natural resources, scarcity was an idea only considered validity in theory. in fact most companies chose a higher rate of depletion, because they simply sought short-term profit maximization. however, the situation was not that serious as barnett and morse (1963) showed because the price of most minerals as well as agricultural products had fallen, not risen. the debate that continued, there were scholars who argued a more mehmandosti, et al.: uncertainty of oil proved reserves and economic growth in iran international journal of energy economics and policy | vol 6 • issue 3 • 2016 375 pessimistic view. the most cited publication of this phase was the limits to growth (meadows, 1972), published by scholars at the massachusetts institute of technology. they argued that the economy would soon stagnate and finally collapse because many critical non-renewable resources would be exhausted in the near future. although most of their predictions have not come to pass, it is worth looking at their arguments as they had a deep impact on the debate. according to them population grows exponentially, whereas resources and food supply grow linear at lower rates. hence (1) an insufficient supply of food for an increasing world population will be one limiting factor on growth in the near future. another limiting factor will be (2) the depletion of natural resources. as a result raw materials will become extremely expensive and the depletion of non-renewable resources will lead to a sudden collapse of economic development instead of a smooth transition. pollution will further limit the availability of natural resources (meadows, 1972). in contrast, the optimists emphasized the short-term occurrence of over-consumption. simon (1996) pointed out that in the short-run, it is indeed possible that supply will fall short; but in the long-run, increased price levels will boost production. for instance, rising food prices will make the application of new technologies profitable and agricultural output will be amplified (kahn, 1976 and 2005). in fact, the price of resources indicates the underlying mechanism of scarcity rather than depletion. for oil the situation is likewise: a distinct pattern of fluctuating oil prices and new discoveries in the past demonstrate a strong correlation between oil demand and supply, because increased oil prices encourage oil companies to invest in exploring for oil, at deeper and less accessible layers. although an unexpected demand shock cannot be covered in the short-run, market mechanisms will balance supply and demand in the longrun, albeit at eventually higher prices (simon, 1996). in addition, the optimists argued that non-renewable resources as input in economic activities will lose their importance in the long-run. this pattern of adaptation can, for example, be illustrated by the unexpected diminishing importance of coal in developed countries. simon (1996) stressed that the depletion of natural resources need not conflict with economic growth, because (1) a rising price will stimulate the search for new deposits and (2) increase the profitability of currently more expensive renewable resources. during the next phase dasgupta and heal (1974) discussed whether it is possible to maintain sustained economic growth in light of diminishing non-renewable resources. similarly solow (1974) and stiglitz (1974) showed that market economies may not lead to sustainable outcomes, i.e. market forces could lead to over consumption of non-renewable resources and hence limit growth. anderson (1987) argued that even technological change could not impede this outcome. only if capital accumulation can be substituted for non-renewable resources, can consumption levels be maintained in the long-run (hartwick, 1977). a more optimistic perspective is the idea that investments into new technologies could decrease the costs of renewable energy and hence make the substitution of non-renewable resources feasible (dasgupta and stiglitz, 1981). during the last decades new economic growth models showed the effects of technological change and substitution on sustainable development. though non-renewable resources are by definition finite, either in terms of supply or by relative pricing, there is no reason to argue that economic growth will be limited. barro and sala-i-martin (1995) showed how sustained growth is possible. for example, as schmalensee et al. (1998) has shown, pollution measured by per capita emissions has peaked in some oecd countries. likewise there are scenarios that predict a falling demand for oil after the year 2030 (iea (international energy agency), 2003) partly due to the substitution by cheaper renewable energy sources. salo and tahvonen (2001) emphasized that an unexpected demand shock cannot be covered in the short run, but supply will adjust to its demand in the long-run. still there are scholars who argued that development in the long-run will reach a steady state. daly (1991) assumed that sooner or later only renewable resources could be consumed, but a comparison with reality shows that the short-term occurrence of his predicted ‘cycle-stage’ seems unlikely. a more efficient employment of oil due to new technologies as well as the input of substitutes have compensated for overall increases in consumption. the pessimists acknowledged that technological progress and substitution could possibly compensate for increased demand and usage rates of nonrenewable resources; however, these effects were not been taken sufficiently in to account (tahvonen, 2000). the experience with oil proved the pessimistic assumptions to be misleading; instead of decreasing oil reserves due to its depletion, oil reserves have actually increased during the last decades (bp statistical review of world energy report, 2015; radler, 2006). in the future it is possible that energy will continue to be produced from non-renewable resources as this is for several reasons: (1) the rate of depletion will change over time due to the development of new technologies, (2) there will be new discoveries of reserves, (3) consumer behavior will change over time and (4) the structural framework of the global economy will change due to such things as the implementation of various environmental regulations. however, amount of proved reserves of non-renewable resources are also stochastic and thus, amount of input of non-renewable energy and its changes can be seen as a one stochastic variable in the production function. in other words, examples of random negative shocks in the proved reserves are earthquakes, hurricanes, and war, while a random positive shock can be the discovery of an unexpected field and increasing of rate of depletion due to the development of new technologies. nevertheless, the debate between the pessimists and the optimists is mostly about how technological progress, human mind, uncertainty about the actual amount of reserves of resource and future prospects of oil prices, costs of production, and substitution cheaper renewable energy will affect on economical growth and whether they can overcome obstacles for future economic growth or not. to investigate empirically the facts, there are vast literatures that examine empirically effects of different factors including uncertainty, depleting non-renewable resource, technological progress, human capital, and substitution cheaper renewable energy on economic growth. as an illustration, tilton (1996) in his paper analytically considered both optimistic and pessimistic approaches about future economic growth by including major factors such as depleting non-renewable resource, uncertainty about the proved reserves of non-renewable energy resources, mehmandosti, et al.: uncertainty of oil proved reserves and economic growth in iran international journal of energy economics and policy | vol 6 • issue 3 • 2016376 and technological progress. also, pasqual and souto (2003) investigated on long term growth rate and managing natural resources under uncertainties and proved that intergenerational distribution of the resources is key to ensure long term growth rate. in continue, gerlagha and keyzerb (2004) studied path of long term economic growth by considering restrictions of intergenerational and uncertainties of nonrenewable resources and showed that integration of economics depend to initial reserves of resources. also, martinet (2007) in their paper studied long term growth including non-renewable resources and technological progress by using control of variable approach. for more to see, stamford da silva (2008) and schilling and chiang (2011). in this paper, we move the empirical literature forward by examining a part of major debates between the pessimists and the optimists approaches about economic growth which is how uncertainty about the actual amount of proved reserves of nonrenewable resources effects on the economic growth and thus, whether for intergenerational justice, time allocation of nonrenewable energy resources must be attend or not. it is mentioned that uncertainty of oil proved reserves includes random negative shocks such as earthquakes, hurricanes, and war, and random positive shock includes the discovery of an unexpected field and increasing of rate of depletion due to the development of new technologies. in this way, we try to find the direct effects of oil proved reserves uncertainty on real economic activity as well as the response of real gdp growth to oil reserves shocks by using annually data for the iran as a country which has 4th rank of owning amount of oil proved reserves in the world. the model is based on a structural vector auto-regression (var) that is modified to accommodate generalized auto-regressive conditional heteroskedasticity (garch) in-mean errors, as detailed in engle and kroner (1995), grier et al. (2004), shields et al. (2005), and elder and serletis (2010). as a measure of uncertainty about the impending oil proved reserves, we utilize the conditional standard deviation of the forecast error for the change in the proved reserves of oil. our principal result is that uncertainty about the proved reserves of oil in the country has not had a significant effect on real gdp over the post-1980 period, including both positive (technology growth and discovering unexpected reserves) and negative (war) shocks, even after controlling for lagged oil proved reserves and lagged real output. we also conduct impulse-response analysis. consistent with much of the literature, our impulse-responses are not estimated very precisely (we report one standard error confidence bands), but we find some evidence that accounting for uncertainty about oil reserves tends to alter the estimated response of real output to an oil reserves shock. in particular, the responses to positive and negative are symmetric. there are a few notification in interpreting our results. our proxy for uncertainty is the conditional variance of oil proved reserves. this proxy reflects the dispersion in the forecast error generated by an econometric model applied to historical data and may not capture other forwardlooking components of uncertainty that are not parameterized in the model. it may also be correlated with some other factor that is driving our result. auto-regressive conditional heterskedasticity (arch-) based measures of uncertainty, however, have been very common, at least since their seminal application by engle (1982) to inflation uncertainty. the paper is organized as follows. section 1 provides a brief description of the empirical model and addresses estimation issues. section 2 presents the data and draws on the large empirical literature dealing with identification issues in structural var. sections 3 assess the appropriateness of the econometric methodology by various information criteria, and discuss the empirical results. the final section concludes. 2. the empirical model as indicated above and same as elder and serletis (2010), we measure uncertainty about oil proved reserves as the standard deviation of the one-step-ahead forecast error, conditional on the contemporaneous information set. the standard deviation of this forecast error is a measure of dispersion in the forecast, and as such, is a measure of uncertainty about the impending realization of the proved reserves of oil. such time-series measures of uncertainty have been very common, at least since engle (1982) and bollerslev (1986) applied univariate arch and garch models to measure inflation uncertainty. we follow same method with elder and serletis (2010). our empirical model is a multivariate annually garchin-mean model in real gdp growth and the change in the proved reserves of oil and was first developed in elder (1995, 2004). the operational assumption is that the dynamics of the structural system can be summarized by a linear function of the variables of interest plus a term related to the conditional variance. according to the basic garch framework which was extended by engle et al. (1987), the conditional mean, yt to depend on the conditional variance, δt 2 . following it and imposing some restriction, the conditional mean is as follow: by c y l h et i t i t ti p = + + +−=∑ γ λ( )1 (1) dim (b) = dim (γi) = (n*n) et |ωt-1 ~ iid n (0, ht), where 0 is the null vector, λ (l) is a matrix polynominal in the lag operator, ωt-1 denotes the available information set in period t-1, which includes variables dated t-1 and earlier. the system is identified by imposing a sufficient number of exclusion restrictions on the matrix b, and assuming that the structural disturbances, et are uncorrelated. this specification allows the matrix of conditional standard deviations, denoted ht , to affect the conditional mean. testing whether oil proved reserves uncertainty affects real economic activity is a test of restrictions on the elements of λ(l) that relate the conditional standard deviation of oil reserved, given by the appropriate element of ht , to the conditional mean of yt that is, if oil proved reserves uncertainty has positively affected output growth, then we would expect to find a positive and statistically significant coefficient on the conditional standard mehmandosti, et al.: uncertainty of oil proved reserves and economic growth in iran international journal of energy economics and policy | vol 6 • issue 3 • 2016 377 deviation of oil in the output equation. in our application, the vector yt includes real output growth and the change in the proved reserves of oil. in other words, y oil y e e e h h t t t t oil t y t t oil =       =       = ∆ ∆ ∆ ∆ ∆ln ln ; ; ln , ln , ln ∆∆ ∆ ∆ ln , ln ln , ; oil t y y th       b b c oil y oil i i i =         =         = 1 0 1 11 12 ∆ ∆ ∆ γ ln c c ³ ³ ; ln ln ( ) ( ) ³³ ³ l 21 22 22 0 ( ) ( ) ( ) ; ( ) ( ) . i i jl         =         λ λ the conditional variance ht is modeled as multivariate garch on the base of elder (2004), which shows that imposing a common identifying assumption in structural vars greatly simplifies the variance function written in terms of the structural disturbances. that is, given the zero contemporaneous correlation of structural disturbances, the conditional variance matrix ht is then diagonal, substantially reducing the requisite number of variance functions parameters. so, the variance function is as follow: diag h c f diag h g e et v j t j kk g t k t kj f ( ) ( ) ( )= + + ′− = − −= ∑∑ 11 (2) were diag is the operator that extracts the diagonal from a square matrix. if we impose the additional restriction that the conditional variance of yi,t depends only on its own past squared errors and its own past conditional variances, the parameter matrices fj and gk are also diagonal. given the focus of this paper, this assumption is not restrictive, and it can be relaxed if we have particular interest in how the lagged uncertainty of one variable may interact with the conditional variance of another. we therefore estimate the variance function given by equation (2), with f = g = 1. the multivariate garch-in-mean var, equations (1) and (2), can be estimated by full information maximum likelihood (fiml), which avoids pagan’s (1984) generated regressor problems associated with estimating the variance function parameters separately from the conditional mean parameters, as in lee et al. (1995). the procedure is to maximize the log likelihood with respect to the structural parameters b, c c f andgi v j k, , , , , ,γ λ where l n b h e h et t t t t= − + − − ′ − ( )ln( ) ln ln ( ). 2 2 1 2 1 2 1 2 2 1π we set the pre sample values of the conditional variance matrix h0 to their unconditional expectation and condition on the pre sample values y0, yt–1,..., yt–p+1 to ensure that ht is positive definite and et is covariance stationary, the following restrictions are imposed: cv is element-wise positive, f and g are element-wise non negative, and the eigen values of (f + g) are less than one in modulus. provided that the standard regularity conditions are satisfied, fiml estimates are asymptotically normal and efficient, with the asymptotic covariance matrix given by the inverse of fisher’s information matrix. this procedure is computationally intensive, as it estimates all the structural parameters simultaneously, unlike the conventional procedures for a homoskedastic var. in a homoskedastic var, the reduced-form parameters are typically estimated by ols and the structural parameters are recovered in a second stage either by a cholesky decomposition or a maximum likelihood procedure applied to the reduced-form covariance matrix, requiring numerical optimization over as few as n (n − 1)/2 free parameters in b. such simplified estimation schemes are not possible with this model, however, in part because the information matrix is not block diagonal. impulse responses are calculated as described in elder (2003). the monte carlo method used to construct the confidence bands is described in hamilton (1994 p. 337), adopted to our model. that is, the impulse responses are simulated from the maximum likelihood estimates (mles) of the model’s parameters. confidence intervals are generated by simulating 1,000 impulses responses, based on parameter values drawn randomly from the sampling distribution of the mles, where the covariance matrix of the mles is derived from an estimate of fisher’s information matrix. 3. data and identification we use annually data for the iran over the period from 1980 to 2013, including both positive (technology growth and discovering unexpected reserves) and negative (war) shocks, a total of 33 observations. we estimate our model using of real gdp and amount of proved reserves of oil; so, we have two variables the real gdp (yt) and the proved reserves of oil (ot). furthermore, we use data for nominal gdp and gdp deflator or real gdp, which are used to calculate gdp deflator, from reports of central bank of iran. also, we use bp statistical review of world energy (2015) annual data on oil proved reserves and basic year was 2004. figures 1 plot the logged levels and the first differences of real gdp and the proved reserves of oil (ln yt and ∆ln yt/ln ot and ∆ln ot series) respectively, for iran. a battery of unit root and stationary tests are conducted in table 1 in the natural logs of real gdp and the oil proved reserves. in particular, we use the augmented dickey–fuller (adf) test (dickey and fuller, 1981) and the dickey–fuller gls test (elliot et al., 1996), assuming both a constant and trend, to determine whether the series have a unit root. moreover, given that unit root tests have low power against trend stationary alternatives, we also use the kpss test (kwiatkowski et al., 1992) to test the null hypothesis of stationarity. as shown in table 1, the null hypothesis of a unit root cannot be rejected at conventional significance levels by both the adf and df-gls test statistics in approximately all data. moreover, the null hypothesis of stationarity in the different methods of kpss test has not shown same results for the same series; however, it can be approximately rejected at conventional significance levels. we thus conclude that real gdp and the oil proved reserves are nonstationary, or integrated of order one, i(1). in panel table 1 also, we repeat the unit root and stationarity tests using the first differences of the logs of the series. clearly, all of tests have not shown same results for the same series; however, the mehmandosti, et al.: uncertainty of oil proved reserves and economic growth in iran international journal of energy economics and policy | vol 6 • issue 3 • 2016378 table 1: unit root and stationary tests log levels first differences of log levels adf( ) df gls− ( ) kpss( )ηµ λ kpss( )ητ λ adf( ) df gls− ( ) kpss( )ηµ λ kpss( )ητ λ a. real gdp −3.866 −2.300 0.587 0.132 −2.326 −2.523 0.121 0.094 b. oil proved reserves −2.402 −2.478 0.728 0.074 −5.979 −6.058 0.060 0.058 %cv −3.553 −3.190 0.463 0.146 null hypotheses of the adf and df-gls tests are mostly rejected and the null hypothesis of the kpss test cannot be mostly rejected, suggesting that the logarithmic first differences are stationary, or integrated of order zero, i(0). due to the presence of unit roots in the logged levels, in the next section we estimate all models using the first differences of the logarithms of the series. 4. empirical evidence we estimate a multivariate garch-in-mean var with one lag, using annually observations on the log change in the proved reserves of oil and the log change in real gdp over 1980 to 2013 for the iran. it must be mentioned that different lags considered and only in the one lag the model integrated. the point estimates of the conditional mean and conditional variance-covariance function parameters of the multivariate garch in-mean var are reported in table 2 for and provide less support for the specification. the primary coefficient of interest relates to the effect of oil proved reserves uncertainty on real gdp. this is the coefficient on the conditional standard deviation oil proved reserves changes in the output growth equation, which is reported in the λ (l) matrix in table 2. the null hypothesis that the true value of this coefficient is zero is not rejected at the 5% level in the period, thus providing evidence to not support the hypothesis that positive oil proved reserves uncertainty tends to increase real economic activity. hence, uncertainty about the proved reserves of oil has not tended to increase real gdp over our sample and that effect is statistically not significant at conventional. on the base of variance-covariance function, there is evidence of arch in both real gdp and oil proved reserves. at a annually frequency, the volatility process for the proved reserved of oil is apparently persistent, as most of the coefficient are significant. table 2: parameter estimates for iran model: equations (1) and (2) with p=1, f=1 , and g=1 a. conditional mean equation b c=       = − −    1 0 0 945 1 067 0 1 82 223 16 542 1 285 1 364. ( . ) ; . ( . ) . ( . )   ; γ 1 0 807 2 229 5 255 0 836 0 113 0 535 3 459 1 053 = − − − −    . ( . ) . ( . ) . ( . ) . ( . )    =      ; ( ) . . ( . ) λ l 0 000 0 001 0 783 b. conditional variance-covariance structure c fv =       = 57 988 51 920 103 305 3 663 0 999 32303 0 315 . ( . ) . ( . ) ; . ( ) . (11 689 0 000 0 164 2 492. ) ; . . ( . )       =      g to assess the effect of incorporating oil proved reserves uncertainty on the dynamic response of real gdp to an oil reserves shock, we plot the associated impulse responses in figure 2, simulated from the mles of the model’s parameters. the impulse responses are based on an oil shock equal to the annualized unconditional standard deviation of the change in the proved reserves of oil. we choose a shock of this magnitude to make the impulses comparable to those of standard homoskedastic var. we simulate the response of real output to both a positive and negative oil reserves shock, to investigate whether the responses to positive and negative shocks are symmetric or asymmetric. we also report one-standard error bands. consider first the top panel of figure, which reports the response of real output to a positive oil reserves shock. the impulse response indicates that, accounting for the effects of oil proved reserves uncertainty, an oil reserves shock tends to increase real gdp growth immediately in the iran, inducing a upward revision in the annualized growth rate of real gdp. however, in the next period decreased under zero and after was going to be stable around zero. also, the dynamic effect of the positive shock to the real gdp is not relatively persistent. figure 1: iran (a) logged real gdp and its growth rate. (b) logged oil proved reserves and its rate of change ba mehmandosti, et al.: uncertainty of oil proved reserves and economic growth in iran international journal of energy economics and policy | vol 6 • issue 3 • 2016 379 in order to quantify the dynamic response of real gdp to oil reserves shocks, in the second panel of figure we report the impulse response of real gdp to a negative oil reserves shock. clearly, our model estimates this effect very imprecisely, as the response of real gdp is well within one standard error of zero at all horizons. hence, in our model the responses to positive and negative shocks are symmetric, in that the effect of a positive shock is not different from that of a negative shock. 5. conclusion a part of major debates between the pessimists and the optimists approaches about economic growth is how uncertainty about the actual amount of proved reserves of nonrenewable resource as a one of the principal factors in the production effects on the economic growth. in this paper, we examine the effects of oil proved reserves uncertainty on real economic activity in the iran, in the context of a dynamic multivariate framework in which a structural var has been modified to accommodate multivariate garch-in-mean errors, as in elder and serletis (2010). in this model, oil proved reserves uncertainty is the conditional standard deviation of the one-period-ahead forecast error of the change in the proved reserves of oil. our main empirical result is that uncertainty about the proved reserves of oil has not had a significant effect on real output at the 5% level in our sample. we also find some evidence that the responses to positive and negative shocks are symmetric, in that the effect of a positive shock is not different from that of a negative shock. further research might investigate by defining different proxy to measure oil reserves uncertainty. finally, our results do not provide some support evidence that uncertainty about oil proved reserves may ensure economic growth; so, time allocation of non-renewable energy resources to ensure economic growth and intergenerational justice must be attended. references anderson, c. (1987), the production process: inputs and wastes. journal of environ-mental economics and management, 14, 1-12. barnett, h., morse, c. (1963), scarcity and growth: the economics of natural resources availability. baltimore: published for the resource for the future, the johns hopkins press. pxv, 288. barro, r., sala-i-martin, x. (1978), economic growth. new york: mcgraw hill. bollerslev, t. (1986), generalized autoregressive conditional heteroskedasticity. journal of econometrics, 31, 307-327. daly, h. (1991), steady state economics. washington, d.c: island press. dasgupta, p., heal, g. (1974), the optimal depletion of natural resources. review of economic studies, symposium. p3-28. dasgupta, p., stiglitz, j. (1981), resource depletion under technological uncertainty. econometrica, 49, 85-104. dickey, d., fuller, w. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica, 49,1057-1072. elder, j. (1995), macroeconomic and financial effects of monetary policy and monetary policy uncertainty, ph.d. dissertation, university of virginia. elder, j. (2003), an impulse-response-function for a vector autoregression with multivariate garch-in-mean. economics letters, 79, 21-26. elder, j. (2004), another perspective on the effects of inflation volatility, journal of money, credit, and banking, 36, 911-28. elder, j., serletis, a. (2010), oil price uncertainty. journal of money, credit and banking, 42, 1137-1159. elliott, g., rothenberg, t.j., stock, j.h. (1996), efficient tests for an autoregressive unit root. econometrica, 64, 813-836. engle, r.f. (1982), autoregressive conditional heteroscedasticity with estimates of the variance of uk inflation. econometrica, 50, 987-1008. engle, r.f., kroner, k.f. (1995), multivariate simultaneous generalized arch. econometric theory, 11, 122-150. engle, r.f., lilien, d.m., robins, r.p. (1987), estimating time varying risk premia in the term structure: the arch-m model. econometrica 55(2), 391. gerlagha, r., keyzerb, m. (2004), path-dependence in a ramsey model with resource amenities and limited regeneration. journal of economic dynamics and control, 28, 1159-1184. grier, k.b., henry, o.t., olekalns, n., shields, k. (2004), the asymmetric effects of uncertainty on inflation and output growth. journal of applied econometrics, 19, 551-565. hamilton, j.d. (1994), time series analysis. princeton, nj: princeton university press. p337. hartwick, j. (1977), international equity and the investing of rents from exhaustible resources. american economic review, 67, 972-974. hotelling, h. (1931), the economics of exhaustible resources. journal of political economy, 39, 137-175. international energy agency (iea). (2003), energy to 2050. scenarios for a sustainable future. paris: oecd/iea. kahn, h. (1976), the next 200 years: a scenario for america and the world. new york: morrow. p4-11. kahn, j.r. (2005), the economic approach to environmental and natural resources. mason, oh: thomson southwestern. figure 2: impulse responses for iran mehmandosti, et al.: uncertainty of oil proved reserves and economic growth in iran international journal of energy economics and policy | vol 6 • issue 3 • 2016380 kwiatkowski, d., philips, p.c.b., yonocheo, s., schmidt, p. (1992), testing the null hypothesis of stationarity against the alternative of a unit root: how sure are we that economic times series have a unit root? journal of econometrics, 54, 159-178. lee, k., ni, s., ratti, r.a. (1995), oil shocks and the macroeconomy: the role of price variability. the energy journal, 16, 39-56. malthus, t. (1798), an essay on the principle of population as it affects the future improvement of society. london: ward lock. martinet, v.l. (2007), sustainability of an economy with an exhaustible resource: a viable control approach. resource and energy economics, 29, 17-39. meadows, d.l. (1972), the limits to growth. london: pan books ltd. mill, j.s. (2002), principles of political economy. new york: appleton. pagan, a. (1984), econometric issues in the analysis of regressions with generated regressors. international economic review, 25, 221-247. pasqual, j., souto, g. (2003), sustainability in natural resource management. ecological economics, 46, 47-59. radler, m. (2006), oil production, reserves increase slightly in 2006. oil and gas journal, 104(47), 20-23. roosevelt, t. (1908), conservation as a national duty, opening address at the conference of governors. washington, dc. salo, s., tahvonen, o. (2001), oligopoly equilibria in nonrenewable resource markets. journal of economic dynamics and control, 25(5), 671-702. schilling, m., chiang, l. (2011), the effect of natural resources on a sustainable development policy: the approach of non-sustainable externalities. energy policy, 39, 990-998. schmalensee, r., stoker, t., judson, r. (1998), world carbon dioxide emissions: 19502050. the review of economics and statistics, 80, 15-27. shields, k., olekalns, n., henry, ó.t., brooks, c. (2005), measuring the response of macroeconomic uncertainty to shocks. the review of economics and statistics, 87(2), 362-370. simon, j. (1996), the ultimate resource2. princeton: princeton university press. solow, r.m. (1974), intergenerational equity and exhaustible resources. review of economic studies, symposium on the economics of exhaustible resources. p29-46. stamford da silva, a. (2008), growth with exhaustible resource and endogenous extraction rate. economic modelling, 25, 1165-1174. stiglitz, j.e. (1974), growth with exhaustible natural resources: efficient and optimal growth paths. review of economic studies, symposium on the economics of exhaustible resources, 123-137. tahvonen, o. (2000), economic sustainability and scarcity of natural resources: a brief historical review. washington, dc: resources for the future. tilton, j.e. (1996), exhaustible resources and sustainable development. resources policy, 22, 91-97. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 6 • 2021 479 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(6), 479-488. structural transformation versus environmental quality: the experience of the low-income countries in sub saharan africa atif awad* department of finance and economic, college of business administration, university of sharjah, sharjah, uae. *email: aawoad@ sharjah.ac.ae received: 16 may 2021 accepted: 25 september 2021 doi: https://doi.org/10.32479/ijeep.11516 abstract structural transformation has been recognized as a critical mechanism for improving living standards for developing countries in africa. however, the growing evidence indicates that such change is associated with considerable damage to the environment quality and, hence, challenging sustainable development. the present study investigates industrialization’s influence on the environment quality for 20 low-income countries in sub-saharan africa during 1980-2018. we employed two measurements for environmental quality, which are co2 and nitrous dioxide emissions. likewise, the study applied the fully modified ols and the dynamic ols as the most modern and suitable techniques related to the panel data analysis. overall, the fmol and dols results show that industrialization has an insignificant influence on environmental quality. the results also show that these countries’ population size is the main driver for environmental quality changes. this finding implies that these countries should continue in their current efforts regarding promoting the industrial sector without wondering about sustainable development. keywords: ekc, industrialization, low-income countries, fmol, dols jel classifications: q560, q580, o140, o550 1. introduction since the beginning of the new millennium, the figures show that african economies have been growing at a somewhat speedy rate (unctad, 2012). the achieved growth was reflected in an improvement on several factors such as trade, fdi, and progress in the physical infrastructure (african union’s agenda 2063, 2015; african development bank, 2015; african transformation report, 2014; unctad, 2012; imf, 2013). unfortunately, evidence suggests that the present trend of growth is neither inclusive nor sustainable. several interrelated factors have been identified as primary sources for this failure. however, bypassing industrialization, a major stage in the structural change and development process, is recognized as a critical explanation(unctad, 2012; opokua and boachieb, 2020). theoretically, structural change is said to occur, as described by kuzents(1966) and others, through the gradual movement and shift of an economy via two stages. in the first stage, from agriculture to the industrial sector, the second stage is industrial to the services sector. however, unlike other regions’ experiences, in africa, the economy jumps directly from agriculture to informal economic activities in the service sector(unctad, 2012; opokua and boachieb, 2020). the industrial and manufacturing sector is recognized as the sector able to create new and sustainable job opportunities. thus, with the absence of manufacturing, sustainable and inclusive growth will be unattainable in africa (zamfir, 2016; page, 2011; gui-diby and renard, 2015;world bank, 2014; africa growth initiative, 2016; opokua and boachieb, 2020). recently, african policymakers have responded to the growth-exclusiveness outcomes by establishing structural transformation basics. thus, today we can see several initiatives have been emerged to support the importance of creating a fundamental change in the structure of the africa economy (unctad and unido, 2011). this journal is licensed under a creative commons attribution 4.0 international license awad: structural transformation versus environmental quality: the experience of the low-income countries in sub saharan africa international journal of energy economics and policy | vol 11 • issue 6 • 2021480 nonetheless, by shifting the economy’s structure toward the industrial sector, structural transformation is a double-edged sword. it is well recognized that structural change is essential and preconditions for improving living standards and generating sustained growth. however, it is not sufficient to achieve sustainable development because such change is more likely to reflect high costs on ecological systems. the other countries’ experience shows that the transformation from an agriculture-based economy to an industrial one is associated with considerable destruction to the environment (fischer-kowalski and haberl, 2007). that is to say, despite the importance of structural change and industrialization for job creation and poverty alleviation; however, it also might create undesirable consequences on the quality of the environment and hence sustainable development. in this respect, stern (2009) argued that due to climate change disasters and rising temperatures, achieving sustainable development is challenging. given the significance of industrialization in accomplishing sustainable development goals, on the one hand, and the potential negative impact of automation on such goals, on the other hand, it is imperative to explore the consequence of industrialization on the environmental quality of developing countries in africa. although numerous empirical studies tried to explain the critical factors determining a group of african countries’ ecological systems, industrialization’s potential and explicit role in explaining this phenomenon has been ignored(will be discussed in the next section). to the best of our knowledge, only two studies by lin et al. (2016) and opokua and boachieb (2020) addressed this matter straightforwardly for a group of african economies. the present study utilized the panel cointegration technique for 20 lowincome economies in sub sharhan africa (ssa) over the period 1980-2018 to explore the industrialization process’s influence on the environment quality. more specifically, this study’s main objectives are first; to analyze the ekc’s validity in low-income countries in sub sharah africa using an extended version of the ipat version. the secondary objectives comprise identifying the key factors that affect the quality of the environment in africa by utilizing appropriate techniques such as panel cointegration, fully modified ols(fmols), and dynamic ols (dols) techniques. this article aims to discover the experience of low-income countries in ssa with this matter, and it adds to the present works in three significant ways. firstly, as we said, since so far, only two studies accounted for the role of industrialization in explaining environmental quality in africa, the present study will add a new contribution to the field and open the door for further studies. second, instead of dealing with african countries as a homogenous group, as lin et al. (2016) and opokua and and boachieb (2020), the present study will limit the analysis to the low-income countries the continent. as per the world bank (2020) classification, the 53 economies in the continent are classified into 23 low income,21 lower middle income,6 upper median income, and the remaining three as high income. it is well recognized that the structure of the economy and the level of development vary across countries. thus, as unctad (2012) suggested, the challenge of attaining sustainable development is different in economies at varying stages of development. thirdly, the current study applies the most modern and suitable long-run panel techniques in the field of panel cointegration procedures offered by pedroni (1999). for robustness checking, the current study utilized two indicators for the degree of environmental quality, namely, co2 and nitrous dioxide emissions, and two analysis techniques, which are fmols besides dols. besides, we also consider the influence of trade and fdi within the environmental quality -industrialization nexus. this study’s outcomes are essential for these countries’ policymakers in their current efforts to achieve, in a simultaneous way, structure transformation and social and environmental sustainability. in the subsequent section, related empirical literature will be summarized. the data, estimation technique, and methodology procedures are displayed in section 3. the obtained results will be highlighted and discussed in section 4. the final section includes the conclusion of the study in addition to policy implications and recommendations. 2. literature review following the influential work of grossman and krueger (1991), empirical analyses on the influence of various human actions and behavior on the environment’s quality are growing extensively. however, most of these studies focused on developed counties’ experiences and ignored that of emerging economies. despite these growing studies, the relationship between growth in per capita gdp and environmental pollution remains complicated. indeed, the ekc suggests some demonstrative instruments for shedding light on the interrelationship between economic activities and their environmental quality consequence. the ekc indicates that in the first stage of development, the per capita income increases will be associated with deterioration in the environment at an increasing rate. however, over time and once the economy moves to a relatively high development level, there will be a gradual improvement in the environment. grossman (1995) interpreted the inverted ‘u-shaped’ form in the ekc hypothesis through the three effects, which are scale, composition, and technology influences. the scale consequence denotes that there will be a massive demand for all resources in general and natural resources, particularly at the beginning of the development process journey. the direct and indirect utilization of natural resources will be converted into the production of various manufactured products. at this stage, the economy is expected to witness a considerable amount of industrial waste that creates significant damage to the environment. second, to sustain and boost per capita gdp growth, policymakers neglect the deterioration in environmental quality. the whole ecological degradation begins to spread with a rise in the production process (per capita gdp growth). however, with continuous increases in the per capita income, the industrial component of an economy starts experiencing a transformation, and thus, the composition of an economy begins altering. however, once the economy reaches a specific level of per capita income during this stage, the public and policymakers’ attention will shift towards a clean environment. therefore, the emerging industrial sector has to adopt more friendlyenvironment tools and equipment in the production process. this is once the industries sectors begin to integrate technologies for expanding energy efficiency, and thus less and less damage to the environment will occur. the growing empirical results regarding the growth-environment nexus have yielded mixed results. besides, most of these studies awad: structural transformation versus environmental quality: the experience of the low-income countries in sub saharan africa international journal of energy economics and policy | vol 11 • issue 6 • 2021 481 are focused on advanced economies; thus, their outcomes are not consistent and untrustworthy with poor developing countries (carson, 2010; stern, 2003). likewise, even the few empirical studies related to africa derived mixed outcomes, which creates a challenge for leaders since it will manifest dissimilar policy consequences. the inconsistency of the findings was attributed to various factors including, model specifications(linear, quadratic, and cubic), environment measurement, the additional explanatory variables that included, and the method of estimation employed, which depends on the structure of the data (time series/panel, cross-section). likewise, the mixed outcomes were attributed to geographic location and the chosen period of the study. according to wagner (2008), numerous critical econometric drawbacks have been neglected in previous studies related to the environmental kuznets curve. recently, katz (2015) analyzed the correlation between freshwater use and income growth, and he discovered that the finding is substantially dependent on selecting datasets and employed econometric methods. this is why, even for similar economies or panels of economies, the obtained results are mixed (shahbaz and sinha, 2020). in the present study, since previous empirical work in this matter is significantly tremendous, we will limit the review on the empirical studies on ekc that focused on the africa continent only1. more specifically, in reviewing previous studies in africa, we divided these studies into two groups, a single country-oriented analysis and a group of countries-oriented research. second, we will review empirical studies, regardless of the location of the country/countries covered, that incorporated, in an implicit way, industrialization as one of the critical explanations for environmental quality. this work will be classified into two groups; the first group comprises studies using several versions from the decomposition techniques. the second group contains studies that incorporated a proxy for industrialization variables in a linear, quadratic, or cubic form. due to the unavailability of sufficient time-series data for most african countries, most of the studies, as mentioned earlier, are cross-section or panel data. however, recently and with the relative improvement in the data collection, some singles based studies started to emerge. for instance, kohler (2013) analyzes ekc’s validity for south africa during 1960-2009 using the ardl technique. the results of the quadratic specification detected the existence of inverted ushaped. moreover, shahbaz et al. (2013) examine the validity of ekc hypotheses for south africa during 1960-2008 using the ardl technique. the author implemented two specifications, linear and quadratic. while the linear specification results show monotonically increasing, the results detected the exitance of an inverted u-shaped quadratic one. besides, nasr et al. (2015) examine the validity of ekc hypotheses for south africa (1911-2010) by utilizing the eck’s cubic form. the results of the co-summability technique show inverted n-shaped. likewise, farhani et al. (2014a) inspected the strength of ekc hypotheses for tunisia during 1971-2008) using the eck’s quadratic form. the results of the ardl method show existence of inverted u-shaped. 1 for comprehensive and recent literature survey in this matter, see shahbaz and sinha, 2020). similarly, kivyiro and arminen (2014) examine the validity of ekc hypotheses for 6 sub-saharan countries during 1971-2010 using the quadratic specification. the findings show that while inverted u-shaped is verified in three economies, no evidence of ekc hypotheses is revealed in the remaining three countries. moreover, shahbaz et al. (2015) explore the validity of ekc hypotheses for 13 african countries (1980-2012) by applying the eck’s quadratic specification. the results of the johansen cointegration method show mixed findings across these countries. namely, the ekc shape is confirmed as inverted u, u-shaped, monotonically increasing, and no ekc in some countries. regarding cross-countries studies, farhani and shahbaz (2014) inspect the validity of the ekc hypotheses for 10 mena economies during 1980-2009 using the quadratic specification. the results of both fmols, as well as dols detected the existence of inverted u-shaped. farhani et al. (2014b) reinvestigated the ekc hypotheses for 10 mena economies during 1990-2010 by implementing a quadratic form. the results of both fmols and panel dols confirm the presence of inverted u-shaped. besides, osabuohien et al. (2014) analyze the validity of ekc hypotheses for 50 african economies (1995-2010) through applying pdols on quadratic specification. the results show the presence of an inverted u-shaped. likewise, oshin and ogundipe (2014) examine the strength of the ekc hypotheses for 15 west african countries (1980-2012) using the quadratic specification. the author applies three methods of estimations, pooled ols, random effect, and fixed effect. interestingly, the study revealed that the ekc hypotheses’ validity depends mainly on the estimates’ technique. similarly, jebli et al. (2015) examine ekc postulations’ strength for 24 sub-saharan africa economies during the 1980-2010 period by applying ekc’s quadratic form. the results of both ols and fmols confirm the existence of u shape. besides, zoundi (2017) inspects ekc’s validity for 25 african economies during 1980-2012 via ekc’s quadratic form. the author implements five different estimation methods: dols, system gmm, dynamic fixed effect, mg, and pmg. while the results of gmm confirm the presence of u-shaped, the remaining methods fail to detect any form of ekc. using the stirpat framework, awad and abougamos (2017a) examine the validity of ekc hypotheses of 54 economies in africa during 1980–2014. the results show evidence that supports the presence of an inverted-u shaped. within the stochastic impacts by regression on population, affluence, and technology (stirpat) framework, awad and abougamos (2017b) examine the validity of ekc hypotheses in 20 countries in the mena region during 1980–2014. using panel data and a semi-parametric panel fixed effects regression, the results show evidence supports an inverted-u-shaped presence. likewise, awad and warsame (2017) inspect the validity of ekc hypotheses for 54 economies in africa during 1990-2014. the study fails to find any evidence that supports the ekc hypothesis. concerning preceding empirical studies that addressed industrialization’s influence on the environment quality, as we mentioned previously, we classified these studies into two groups. the first group comprises studies that used several versions of the decomposition techniques. the second group contains studies that awad: structural transformation versus environmental quality: the experience of the low-income countries in sub saharan africa international journal of energy economics and policy | vol 11 • issue 6 • 2021482 incorporated a proxy for industrialization variables in a linear, quadratic, or cubic specification of the ekc. several version forms of the decomposition technique were employed in most of these studies. for instance, akbostanci et al. (2008) tried to identify the source of the co2 emissions of the turkish manufacturing sector during 1995–2001. the log mean divisia index (lmdi) method was utilized to decompose the variations in the co2 emissions of the manufacturing industry into five elements; changes in activity, activity structure, sectoral energy intensity, sectoral energy mix, and emission factors. the results demonstrated that the chief sources of the variation in co2 emissions were total industrial activity and energy intensity. likewise, tunc et al. (2009) tried to recognize the factors contributing to changes in co2 emissions for the turkish economy during 1970–2006 via utilizing the lmdi method. the result shows that the primary sources of co2 emissions are economic activity. roinioti and koroneos (2017) and khan et al. (2019) arrive at a similar finding for the case of greece and pakistan economy, respectively. likewise, cherniwchan (2012) examines the role of observed industrialization on the environmental quality for 157 economies over 1970–2000. the results demonstrate that the process of manufacturing is a substantial determinant of observed changes in emissions. lu et al. (2015) arrive at a similar finding for the case of jiangsu, the chinese province. likewise, chunxu et al. (2016) analyzes carbon emissions due to energy consumption based on china’s sectors from 1996 to 2014 by utilizing the lmdi method. one more time, the carbon emissions were decomposed into four categories: energy structure, energy intensity, economic structure, and economic output effect. the results detected that the chief factor driving carbon emissions was the economic output, and the industry sector was the top contributor to carbon emissions. concerning the second group of the studies, few studies incorporated a proxy for industrialization in linear, quadratic, or cubic specification. for instance, xu and lin (2015) examine automation and urbanization’s role in explaining co2 emissions for provincial panel data in china from 1990 to 2011. an inverted u-shaped nonlinear relationship has been confirmed between industrialization and co2 emissions. besides, lin et al. (2016) utilize the stirpat framework and panel cointegration for five african economies from 1980 to 2011. the authors decompose growth into agricultural-based growth and industrial-based growth. the fmols technique’s results failed to identify any significant relationship between co2 emissions and agriculturalbased development or industrial-based growth. also, dogan and inglesi-lotz (2020) tried to inspect the economic structure’s impact on seven european countries’ environmental quality from 1980 to 2014. the fmols results show the u-shaped relationship between industrialization and growth in these countries. likewise, ha le (2020) examined the impact of several factors on greenhouse gas emissions for a sample of 16 economies in south and east asia during 1995-2012. the author employs four types of emission: ghg, co2, ch4, and n2o, and utilizes two estimations; prais-winsten regression with panel corrected standard error (pcse) and feasible general ols (fgols). the results show that the influence of industrialization on the environment depends on environmental measurement. more specifically, while industrialization activities tend to harm the co2, its effect on the remaining three environmental measures is favorable. likewise, opokua and boachieb (2020) examined industrialization’s environmental impact in 36 selected african economies during 1980–2014. using various measures for the environment quality, the pooled mean group (pmg) technique indicates the insignificant impact of industrialization on the environment depend on utilized measurement for the environment. namely, the results show that manufacturing has a statistically negligible consequence on all pollution measurements except for nitrous oxide emissions that appear adversely affected by industrialization. from the reviewed literature, it is clear that there is a lack of consensus over the relevance of the ekc to the continent in general and the impact of the structural transformation. most importantly, the previous studies’ review confirms the lack of sufficient empirical research that accounted for industrialization’s expected role in explaining the critical determinants of the environmental quality for the developing countries in africa. as we said previously, the challenge of accomplishing sustainable development is different in countries at varying development levels. 3. methodology 3.1. model, variables, and data this section aims to illustrate the model, data, and framework utilized to build the empirical analysis of industrialization’s environmental quality impact. to display the theoretical links among manufacturing, income per capita, and environmental quality, we firstly specified the quality of the environmental (eq) as a function of industrialization (ind) and real per capita gdp (y)and its square (y2) as shown in the general form below: eq=f(ind, y, y2) (1) equation 1 demonstrates the fundamental role of economic growth in affecting the environment’s status; thus, the ekc was combined into our investigation. it was crucial to select an appropriate measure for the quality of the environment as it was a vital factor in this study’s interpretation. the ecological consequence of industrialization could take various types of pollution. in the present study, we employed two environmental quality measures following preceding studies: co2 and nitrous oxide emissions. the utilization of these two indicators because the first, although data related to the environmental quality, is massive; however, for poor countries in africa and during the study period, data are available for only these two variables. second, using more than one indicator provides the sound of robustness for the analysis. following the recent empirical research on the environmental quality, we added to equation 1 an additional three explanatory variables that may contribute directly to the ecological quality or indirectly through its impact on industrialization. the variable that contributed directedly is population growth, as hypothesized in the ipat framework (rosa and dietz, 2012; chertow, 2000). the second two variables that indirectly contribute are a foreign direct investment, as hypothesized in the pollution haven hypothesis and halo effect hypothesis (copeland, 2005; eskeland and harrison, 2003; temurshoev, 2006), and trade as postulated in the porter awad: structural transformation versus environmental quality: the experience of the low-income countries in sub saharan africa international journal of energy economics and policy | vol 11 • issue 6 • 2021 483 hypothesis (porter and van der linde, 1995; ren et al., 2014; seker et al., 2015; zhang and zhou, 2016; sapkota and bastola, 2017). after adding these variables, equation 1 can be shown as follows eq=f(ind, y, y2, p, t, fdi) (2) where p refers to population, t for trade, and fdi for foreign direct investment. the log liner specification for eq 2 can be write down as follows: 2 1 2 3 4 5 6 7 it it it it it it it i logeq logind logy logy logp t fdi t α α α α α α α δ = + + + + + + + (3) here, eq signifies the co2 emissions (kt), i denotes the country (19 economies), and t signifies time (1980-2018). for robustness, as we said previously, equation 3 was re-estimated employing an alternative air pollution measure, which is nitrous dioxide emissions; ind is industry, value added (2010 us$). gdp (y) is the gdp per capita (us$ 2010). p is the total population, and t is the trade-in terms of exports plus imports scaled by the gdp. fdi is the foreign direct investment as a percentage of gdp. except for trade and fdi variables, all the remaining variables have been converted into the natural logarithmic form (shahbaz et al., 2013a). statistical features for the data are presented in table 1. data related to entire variables are gathered from the world development indicators. the data covered 20 african economies (see the list of these economies in appendix a1) for 1980-2018. variables measurement and definition are displayed in table a2 in the appendix. the results of the correlation matrix, as shown in table 1, reflect a relatively high correlation between the variable of interest, which is the industry, with each pollution measurement (lco2 and lnit). however, this outcome is not robust because, as we know, the correlation is different from causation. 3.2. estimation approaches this section seeks to explain the stages that will be implemented toward the study’s objective. as per previous empirical works that deal with panel data, we have to test the data’s statistical features to construct the cross-sectional dependence test. in the second step, which depends on the first step’s outcomes, we perform the unit root test, followed by specific panel cointegration testing. in the final step, if we identify a long relationship between the variables, we completed the long-run analysis by utilizing the fomols and the dols. according to shahbaz et al. (2017), unobserved frequent shocks that become an essential component of the error terms(et) will lead to the presence of cross-sectional dependence in crosscountries data. ignoring this test and procedure in the examination may lead to unreliable et of the estimated coefficients (driscoll and kraay, 2001). in the present study and following previous work in this field and for robustness purposes, we will implement four different types of cross-sectional dependence tests. once we perform the cross-sectional dependence tests, the next step is to examine the integration between the variables via panel unit root tests. since several unit root test is available, selecting the specific unit root test depends mainly on the first step(i.e., cross-sectional dependence). if the unit root results show the nonexistence of integration at order two i(2), we have to move to the third step, the panel cointegration tests. if the test results show cointegration evidence between the selected variables, we move to the final step to perform our principal analysis and get our key objectives. the common and traditional estimation technique of panel data such as random effects, fixed effects, and gmm may manifest ambiguous and untrustworthy coefficients if employed on cointegrated panel data (awad, 2019; shahbaz et al., 2017). besides, there is a possibility of an endogeneity problem in our eq2 that might due to either omitted variables and reverse causality. on the one hand, some of the control variables may have been overlooked in eq2. therefore, our findings are most likely to be biased if the omitted variables are associated with the industrialization variable. on the other hand, it is also possible that the environment quality will influence industrialization, reflecting reverse causality. eq2 has been estimated to overcome these problems using two techniques: fully modified ordinary least squares (fmols) dynamic ordinary least squares. (dols). pedroni has developed these two techniques (2000, 2001) that are commonly used in the literature. it is well recognized that panel dols and fmols techniques reduce the endogeneity and autocorrelation between independent variables and et, thus producing efficient results. for this reason, we follow the panel fmols and dols methods whose basic procedures are given in eqs. (4) and (5), where a/eq refer to explanatory/dependent variable in eq. (3).  ^ 2 1 1 1 1 ( ) ˆ( ) n t fmols it ii t t it i ititt a a n a a eq t β = = =   = − ×       − − ∆     ∑ ∑ ∑ (4) ^ ~ 1 1 1 1 n t t dols it it it iti t t a qa n eaβ = = =    =        ∑ ∑ ∑ (5) whether the fmols or dols method is favored, the empirical evidence is conflicting (harris and sollis, 2003). on the one hand, table 1: correlation matrix lco2 lnit lp ly t fdi lind lco2 1 0.62 0.68 0.38 0.28 0.28 0.71 lnit 0.62 1 0.75 0.15 0.12 0.13 0.78 lp 0.68 0.75 1 –0.16 –0.03 0.23 0.83 lyy 0.38 0.15 –0.16 1 0.32 0.06 0.27 t 0.28 0.12 –0.03 0.32 1 0.38 0.05 fdi 0.28 0.13 0.23 0.06 0.38 1 0.22 lind 0.71 0.78 0.83 0.27 0.05 0.22 1 source: author calculation table 2: cross-sectional dependence result factors bp ps bcs cd lco2 2999.81a 144.14a 143.85a 46.57a lnit 11051.58a 220.16 219.35a 81.70a lind 2401.35a 113.54a 113.13a 28.81a ly 2785.65a 133.65a 132.85a 14.28a t 960.07a 39.56a 39.24a 15.39a lp 7232.45a 361.64a 360.64a 85.03a fdi 1158.212a 49.66a 49.41a 27.85a source: author calculation. a signifies significance at the 1% level awad: structural transformation versus environmental quality: the experience of the low-income countries in sub saharan africa international journal of energy economics and policy | vol 11 • issue 6 • 2021484 table 3: the results of the panel root test variables levin, lin and chu cadf-fisher chi-square test level difference level difference c c + t c c + t c c + t c c + t lco2 5.21 (0.000) 1.50 (0.93) –7.95 (0.000) –7.30 (0.000) 7.33 (1.000) 2.72 (0.99) –10.94 (0.000) –10.08 (0.000) lnit 1.37 (0.93) 0.48 (0.68) –10.11 (0.000) –7.42 (0.000) 2.00 (0.79) –0.65 (0.48) –16.21 (0.000) –14.56 (0.000) lind 1.65 (0.96) –0.07 (0.48) –8.18 (0.000) –7.81 (0.000) 5.16 (1.000) 0.85 (0.81) –8.50 (0.000) –6.03 (0.000) ly 2.04 (0.97) –1.98 (0.023) –17.85 (0.000) –17.22 (0.000) 3.46 (1.000) –0.15 (0.84) –19.95 (0.000) –18.20 (0.000) t –2.75 (0.002) –4.07 (0.000) –22.37 (0.000) –20.87 (0.000) –2.77 (0.003) –3.56 (0.000) –21.91 (0.000) –16.98 (0.000) lp –1.84 (0.03) 6.41 (1.000) 1.24 (0.89) 8.70 (1.000) 4.82 (1.000) –3.24 (0.002) –4.90 (0.000) –5.80 (0.000) fdi –3.81 (0.000) –6.31 (0.000) –27.36 (0.000) –23.64 (0.000) –3.90 (0.000) –6.99 (0.000) –28.63 (0.000) –26.35 (0.000) source: author calculation. * **indicates significance at the 1%. table 4: pedroni residual cointegration test dependent variable lco2 lnit value value value value alternative hypothesis: common ar coefs. (within-dimension) panel v-statistic 0.55 –2.54*** –1.84 –3.88*** panel rho-statistic 0.53 1.40 1.01 –0.86 panel pp-statistic –2.05** –2.89*** –4.25*** –10.73*** panel adf-statistic –2.88*** –3.99*** –4.25*** –9.88*** statistic statistic alternative hypothesis: individual ar coefs. (between-dimension) group rho-statistic 2.38 1.56 group pp-statistic –3.01*** –10.69*** group adf-statistic –3.38*** –7.05*** source: author calculation. ***, ** indicates rejection of the null hypothesis of no cointegration at the 1% and 5%, respectively the fmols method and by default overcome the autocorrelation issue, but it is non-parametric. on the other hand, although the dols method remains a parametric test, its powerlessness rests in the degree of freedom matter due to leads and lags (maeso-fernandez et al., 2006). 4. results and discussion table 2 represents the results of the cross-sectional independence tests. the products detect the existence of cross-sectional dependency for each selected variable. we carry on by carrying out panel unit root tests that take into account the dependency in our cross-sectional. the llc statistic of levin et al. (2002) and the cadf statistic of pesaran (2007) are the two tests that consider such dependency (awad, 2019). the results of these tests are reported in table 3. the results indicate that all the variables are i(1). this finding implies that emissions measurement, industrialization, economic growth, population, trade, and fdi have a unique integration order for each panel. cadf-fisher chi-square test therefore, and for each panel, we inspected the cointegration relationship between the variables. the pedroni (1999, 2004) panel cointegration tests are displayed in table 4. the results suggest that out of the seven pedroni tests, five statistics confirmed the existence of cointegration in each specification. however, as pedroni (1999) proposed, panel adf and group adf are the leading statistics for small samples. in other words, if the results are controversial, as in our case, the panel adf and group adf statistics could be the benchmark. consequently, based on the adf and group adf results, we can conclude that the long relationship is confirmed for each specification. table 5 reports the estimated long-run coefficients from the fmols and the dols approach. prior to discussing the findings, we verified the possible multicollinearity problem between the variables in each model. tables a3 and a4 in the appendix show the variance inflation factors (vif) test implemented in each description. the results show that of such a problem in our analysis2. now is the time to move forward and to look for the fmols and dols outcomes. 2 we tested the potential collinearity problems amongst the regressors by using the coefficient variance decomposition (cvd) test. the results, which are not reported here, show the nonexistenceof any collinearity problem in our reults. the results of both fmols and dols are identical, which indicates the robustness of our analysis. the results tell us that our primary variable of interest, which is the industry, has a statistically insignificant impact on the two emitted pollutants’ two measures. the negligible effect of industrialization on the environment could be due to the region’s low industrial activity level. indeed, aggregate data on the industry value add in sub-saharan africa show a decreasing trend over time. for instance, while both sub saharan africa (ssa)and south asia (sa) have the same rate of growth in the industry value added as per 2000(10%), by 2017, sa registered a growth rate of 24% and for ssa remain below 10%. as we mentioned previously, unlike the experience of other regions, in africa, the economy jumps directly from agriculture to informal economic activities in the service sector. according to opoku and yan (2019), the industrial sector’s contribution to africa’s growth is either low or non-existent. likewise, according to gui-diby and renard (2015), industrialization has not yet occurred in africa. similarly, the africa growth initiative (2016) has explained that africa’s industrial improvement and drive have been lagged for more than 40 years. according to zamfir (2016), africa’s share in global manufacturing is tiny. this study’s outcome seems, and to some extent, consistent with previous studies that addressed this matter in africa, namely the work by lin et al. (2016) and opokua and boachieb (2020). lin et al. (2016) use the exact estimation awad: structural transformation versus environmental quality: the experience of the low-income countries in sub saharan africa international journal of energy economics and policy | vol 11 • issue 6 • 2021 485 table 5: fmols and dols technique explanatory variables lco2 lint fmols dols fmols dols lind 0.012 (0.84) 0.13 (0.27) 0.001 (0.99) 0.094 (0.94) ly –5.98** (0.014) –7.53** (0.05) –7.67** (0.02) –6.25** (0.03) ly2 0.56*** (0.005) 0.72** (0.04) 0.64** (0.02) 0.53** (0.03) lp 1.11*** (0.000) 0.97*** (0.000) 0.57*** (0.000) 0.57*** (0.000) t 0.001 (0.50) 0.0007 (0.80) 0.003 (0.15) 0.002 (0.17) fdi 0.002 (0.72) 0.003 (0.83) 0.01 (0.11) 0.009 (0.94) source: author calculation. the p values are in ( ) ** and ***denotes significance at the 5% and 1% level of significance, respectively. (fmols) and arrive at the same conclusion on the insignificant impact of industrialization on environment quality for five african countries. our finding is also consistent with the outcome of opokua and boachieb’s (2020) result when co2 is utilized but differs when environmental quality is proxied by nitrous dioxide emissions. concerning the impact of per capita gdp, and it is a quadratic term, the results show that while per capita gdp is negative and statistically significant, its quadratic term appears positive and statistically significant. this suggests the presence of a “u”shaped relationship between the two environmental measurements and income in the low-income economies in africa. following hasanov et al. (2019), to confirm that the results are consistent with reality, we calculated the turning point using both estimation methods’ average results. the estimated turning point value is approximately equal to 5.5. this turning point value is lower than the whole countries’ average income in our study (table 6). this finding implies that for poor countries in africa, it is expected that the growth process will continue to generate more damage to the environment as long as per capita income below the computed turning point. however, once this group of countries moves beyond that average, the growth process will generate minor damage to the environment. our findings are consistent and contradict studies that were reviewed previously within the africa context. the results indicate that the population is a leading and significant driver for the selected countries’ emissions. as proposed by the stirpat framework, population growth is a considerable factor driving environmental problems comprising climate change. the increase in the population can cause damage to the environment in several ways. the pressure on the limited land resources will force the society to either destroy imperative forest resources or overexploitation arable land. likewise, natural resources and climate are expected to be affected negatively due to population growth that will reflect more production and consumption. numerous analyses have been conducted on the potential influences of the population on the environment (lin et al., 2015; ray and ray, 2011). finally, both specifications indicate that neither the pollution haven hypothesis and the halo effect hypothesis nor porter hypothesis is valid for developing countries in africa. 5. conclusion and policy implications the leaders in africa have implemented several types of strategies to improve living standards and achieve sustainable growth. although most of these countries witnessed and, to some extent, positive growth in per capita gdp, the poverty rate and the unemployment rate started to increase and expand. this led to a significant shift in the policymakers’ mindset in the continent to implement a new strategy to allocate resources toward a more inclusive growth pattern. the structural transformation of the economy from agriculture, a and raw material-based economy, to a more industrialized economy, has been recognized as an essential tool in this strategy. however, evidence and the experience of the other countries show that industrialization is associated with environmental damage. thus, it seems that there is a trade-off between automation and ecological quality. the present study employed panel data techniques to investigate the potential impact of industrialization on the environment quality for 19 developing countries in sub-saharan africa during 19802018. the present study employed two indicators of environmental quality as well as the method of estimation. more specifically, for environmental quality, the current studies used co2 and nitrous dioxide emissions. besides, the fmols, as well as the dols, was utilized in the analysis. the results seem to bring good news for the developing countries in africa since no significant impact for the industrialization of the environment quality has been detected. this finding implies that current observed efforts in the industrialization process should continue without considering it has a potentially adverse impact on these countries’ environment. the environmental issue should be handled through topics related to population behavior. table 6: descriptive statistic lco2 lnit lp lyy t fdi lind mean 6.776232 8.199746 16.05668 6.132878 50.28451 1.978924 20.35469 median 6.743951 8.154916 15.99539 6.160502 47.96138 0.815095 20.38805 maximum 9.163794 11.91689 18.34517 6.963822 108.8148 34.46370 23.07601 minimum 4.988253 5.880378 13.99892 5.299806 19.68416 –28.62426 17.91588 std. dev. 0.818717 1.242315 0.807418 0.360884 17.52620 3.981784 1.088331 no of obs 456 456 456 456 456 456 456 source: author calculation awad: structural transformation versus environmental quality: the experience of the low-income countries in sub saharan africa international journal of energy economics and policy | vol 11 • issue 6 • 2021486 this study’s results are considerable and provide imperative policy implications for the countries inspected in the panels and regional economic blocks, and environmental organizations. our results also crucial for future studies, as it is expected that our research may open additional research directions. other studies are still required for in-depth analysis and investigation for this matter. future studies may, for example, with the africa context, compare the outcome of the industrialization on the environment between this group of countries (low income) and other groups such as the middle-income group. likewise, future studies may address the same issue by looking for low-income countries’ experiences in different regions. similarly, further studies may employ an alternative proxy for industrialization or add more explanatory variables or another specification. references african development bank. (2015), afdb group’s long term strategy. available from: http://www.afdb.org/en/consultations/ closedconsultations/afdb-groups-long-term-strategy [last accessed on 2020 jun 01]. african transformation report. (2014), african transformation report: growth with depth. ” available from: http://africantransformation. org/wp-content/uploads/2014/02/2014-african-transformationreport.pdf [last accessed on 2020 jun 06]. african union’s agenda 2063. (2015), agenda 2063 vision and priorities. available from: http://agenda2063.au.int/en/vision [last accessed on 2020 jun 01]. akbostanci, e., türüt-asik, s., ipek. t.g. (2009), the relationship between income and environment in turkey: is there an environmental kuznets curve? enpol engineering, 37, 861-867. awad, a. (2019), does economic integration damage or benefit the environment? africa’s experience. energy policy, 132, 991-999. awad, a., hoda, a. (2017b), income-carbon emissions nexus for mena countries: a semi-parametric approach. international journal of energy economics and policy, 7(2), 152-159. awad, a., hoda, r.)2017a), a semi-parametric panel data analysis on the urbanization-carbon emissions nexus for mena countries. renewable and sustainable energy reviews, 78, 1350-1356. awad, a., warsam, m. (2017), climate changes in africa: does economic growth matter? a semi-parametric approach. international journal of energy, environment, and economics, 7(1), 1-8. carson, r.t. (2010), the environmental kuznets curve: seeking empirical regularity and theoretical structure. review of environmental economics and policy, 4, 3-23. cherniwchan, j. (2012), economic growth, industrialization, and the environment. resource and energy economics, 34(4), 442-467. chertow, m.r. (2000), the ipat equation and its variants. journal of industrial ecology, 4, 13-29. copeland, b.r. (2005), policy endogeneity and the effects of trade on the environment. agricultural and resource economics review, 34(1), 1-15. dogan, e., inglesi-lotz, r. (2020), the impact of economic structure to the environmental kuznets curve (ekc) hypothesis: evidence from european countries. environmental science and pollution research, 27, 12717-12724. driscoll, d., kraay, a. (2001), trade, growth, and poverty. the world bank policy research working paper, no. 2615. washington, dc: world bank. eskeland, g.s., harrison, a.e. (2003), moving to greener pastures? multinationals and the pollution haven hypothesis. journal of development economics, 70(1), 1-23. farhani, s., chaibi, a., rault, c. (2014a), co2 emissions, output, energy consumption, and trade in tunisia. economic modelling, 38, 426-434. farhani, s., mrizak, s., chaibi, a., rault, c. (2014b), the environmental kuznets curve and sustainability: a panel data analysis. energy policy, 71, 189-198. farhani, s., shahbaz, m. (2014), what role of renewable and nonrenewable electricity consumption and output is needed to initially mitigate co2 emissions in mena region? renewable and sustainable energy reviews, 40, 80-90. fischer-kowalski, m., amann, c. (2011), beyond ipat and kuznets curves: globalisation as a vital factor in analysing the environmental impact of socio-economic metabolism. population and environment, 23,7-47. grossman, g.m. (1995), pollution and growth: what do we know? in: goldin, i., winters, l.a., editors. the economics of sustainable development. cambridge, united kingdom: cambridge university press. p19-45. grossman, g.m., krueger, a.b. (1991), environmental impacts of a north american free trade agreement. national bureau of economic research. working paper no. w3914. gui-diby, l., renard, m.f. (2015), foreign direct investment inflows and the industrialization of african countries. world development, 74, 43-57. ha le, t. (2020), drivers of greenhouse gas emissions in south-east and east asia: evidence from panel data analysis. in: han, p., hesar, f., kimura, f., editors. energy sustainability and development in asean and east asia. 1st ed. milton park, abingdon-on-thames: routledge. hasanov, f., mikayilov, j., mukhtarov, s., suleymanov, e. (2019), does co2 emissions-economic growth relationship reveal ekc in developing countries? evidence from kazakhstan. environmental science and pollution research, 26, 30229-30241. imf. (2013), jobs and growth: analytical and operational considerations for the fund. available from: https://www.imf.org/external/np/pp/ eng/2013/031413.pdf [last accessed 2020 jun 03]. jebli, m.b., youssef, s.b., ozturk, i. (2015), the role of renewable energy consumption and trade: environmental kuznets curve analysis for sub-saharan africa countries. african development review, 27(3), 288-300. katz, d. (2015), water use and economic growth: reconsidering the environmental kuznets curve relationship. journal of cleaner production, 88, 205-213. khan, a., jamil, f., huma, n. (2019), decomposition analysis of carbon dioxide emissions in pakistan. sn applied sciences, 1, 1012. kivyiro, p., arminen, h. (2014), carbon dioxide emissions, energy consumption, economic growth, and foreign direct investment: causality analysis for sub-saharan africa. energy, 15(74), 595-606. kohler, m. (2013), co2 emissions, energy consumption, income and foreign trade: a south african perspective. energy policy, 63, 1042-1050. kuznets, s. (1966), modern economic growth. new haven, ct: yale university press. lean, h.h., smyth, r. (2010), co2 emissions, electricity consumption and output in asean. applied energy, 87(6), 1858-1864. levin, a., lin, c., chu, c.j. (2002), unit root test in panel data: asymptotic and finite sample properties. journal of economics, 108, 1-24. lin, b., omoju, o, n., okonkwo, j., megbowon, e. (2016) is the environmental kuznets curve hypothesis a sound basis for environmental policy in africa? journal of cleaner production, author queries??? aq1: kindly provide jel classifications aq2: kindly note “mckinsey global institute, 2010” not listed in reference list aq3: kindly note “unea, 2013” not listed in reference list aq4: kindly provide physical table for table a2 aq5: kindly provide these author details in the reference list aq6: kindly cite reference in the text part aq7: kindly cite table a1 in the text part awad: structural transformation versus environmental quality: the experience of the low-income countries in sub saharan africa international journal of energy economics and policy | vol 11 • issue 6 • 2021 487 133(1), 712-724. maeso-fernandez, f., osbat, c., and schnatz, b. (2006), towards the estimation of equilibrium exchange rates for transition economies: methodological issues and a panel cointegration perspective, journal of comparative economics, 34, 499-517. nasr, a.b., gupta, r., sato, j.r. (2015), is there an environmental kuznets curve for south africa? a co-summability approach using a century of data. energy economics, 52, 136-141. opokua, e., boachieb, m. (2020) the environmental impact of industrialization and foreign direct investment. energy policy, 137, 111178. osabuohien, e.s., efobi, u.r., gitau, c.m.w. (2014), beyond the environmental kuznets curve in africa: evidence from panel cointegration. journal of environmental policy and planning, 16(4), 517-538. oshin, s., ogundipe, a.a. (2014), an empirical examination of environmental kuznets curve (ekc) in west africa. euro-asia journal of economics and finance, 3(1), 16. pedroni, p. (1999), critical values for cointegration tests in heterogeneous panels with multiple regressors. oxford bulletin of economics and statistics, 61(s1), 653-670. pedroni, p. (2000), fully modified ols for heterogeneous cointegrated panels. advances in economics, 15, 93-130. pedroni, p. (2004), panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the ppp hypothesis. economic theory, 20, 597-625. pesaran, m.h. (2007), a simple panel unit root test in the presence of cross-sectional dependence. journal of applied economics, 27, 265-312. porter, m., van der linde, c. (1995), green and competitive: ending the stalemate. brighton, massachusetts: harvard business review. p119-134. ren, s., yuan, b., ma, x., chen, x. (2014), international trade, fdi (foreign direct investment) and embodied co2 emissions: a case study of chinas industrial sectors. china economic review, 28, 123-134. roinioti, a., koroneos, c. (2017), the decomposition of co2 emissions from energy use in greece before and during the economic crisis and their decoupling from economic growth renewable and sustainable energy reviews, 76,448-459. rosa, e.a., dietz, t. (2012), human drivers of national greenhouse-gas emissions. nature climate change, 2, 581-586. shahbaz, m., nasreen, s., ahmedd, k., hammoudeh, s. (2017), trade openness-carbon emissions nexus: the importance of turning points of trade openness for country panels. energy economics, 61, 221-232. shahbaz, m., sinha, a. (2020), environmental kuznets curve for co2 emissions: a literature survey. journal of economic studies, 20(3), 317-339. shahbaz, m., solarin, s.a., sbia, r., bibi, s. (2015), does energy intensity contribute to co2 18 emissions? a trivariate analysis in selected african countries. ecological indicators, 50(19), 215-224. shahbaz, m., tiwari, a.k., nasir, m., (2013), the effects of financial development, economic growth, coal consumption, and trade openness on co2 emissions in south africa. energy policy, 61, 1452-1459. stern, d.i. (2003), the environmental kuznets curve. international society of ecological economics rensselaer polytechnic institute, troy, united states. temurshoev, u. (2006), pollution haven hypothesis or factor endowment hypothesis: theory and empirical examination for the us and china. available from: http://ideas.repec.org/p/cer/pape rs/ wp292.html. http://www.cerge-ei.cz/pdf/wp/wp292.pdf tunc, g., asık, s., akbostanc, e. (2009), a decomposition analysis of co2 emissions from energy use: turkish case. energy policy, 37, 4689-4699. unctad. (2011), technology and innovation report 2011: powering development with renewable energy technologies. united nations publication. sales no. e.11.ii.d.20. new york, geneva: unctad. unctad. (2012), economic development in africa: structural transformation and sustainable development in africa. available from: http://unctad.org/en/publicationslibrary/aldcafrica2012_ embargo_en.pdf [last accessed on 2020 jun 05]. unido. (2011), green industry: policies for supporting green industry. vienna: unido. wagner, m. (2008), the carbon kuznets curve: a cloudy picture emitted by bad econometrics? resource and energy economics, 30(3), 388-408. world bank. (2014), africa’s pulse: decades of sustained growth is transforming africa’s economies. washington, dc: world bank. available from: http://www.worldbank.org/en/region/afr/publication/ africas-pulsedecades-of-sustained-growth-is-transforming-africaseconomies [last accessed on 2020 apr 15]. xu, b., lin, b. (2015), how industrialization and urbanization process impacts on co2 emissions in china: evidence from nonparametric additive regression models. energy economics, 48, 188-202. xu, s.c., he, a.x., long, r.y., chena, h. (2016), factors that influence carbon emissions due to energy consumption based on different stages and sectors in china. journal of cleaner production, 115(1), 139-148. zamfir, i. (2016), africa’s economic growth: taking off or slowing down? members’ research service. directorate-general for parliamentary research services, european parliament. zoundi, z. (2017), co2 emissions, renewable energy and the environmental kuznets curve, a panel 21 cointegration approach. renewable and sustainable energy reviews, 72, 1067-1075. awad: structural transformation versus environmental quality: the experience of the low-income countries in sub saharan africa international journal of energy economics and policy | vol 11 • issue 6 • 2021488 appendixes table a1: list of the low-income countries in africa benin madagascar burundi malawi burkina faso mali chad mozambique central african republic niger congo, dem. rep. rwanda ethiopia sierra leone gambia, the tanzania guinea togo guinea-bissau uganda table a3: variance inflation factors, dependent variable l co2 variable coefficient uncentered variance vif lp 0.020654 4.241493 lyy 5.881338 695.0213 t 3.06e-06 1.551459 ly2 0.039730 690.1430 fdi 2.69e-05 1.610652 lind 0.008011 7.190250 source: author calculation table a4: variance inflation factors, dependent variable lnit variable coefficient uncentered variance vif lp 0.040738 4.195345 lyy 11.42899 671.9985 t 5.42e-06 1.388022 ly2 0.077741 664.8192 fdi 5.57e-05 1.571421 lind 0.016573 7.115771 source: author calculation table a2: variables definition and measurement variable definition and measurement co2 emission carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. they include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring nitrous oxide emissions (thousand metric tons of co2 equivalent) nitrous oxide emissions are emissions from agricultural biomass burning, industrial activities, and livestock management industry, value added (constant 2010 us$) industry corresponds to isic divisions 10-45 and includes manufacturing (isic divisions 15-37). it comprises value added in mining, manufacturing (also reported as a separate subgroup), construction, electricity, water, and gas. value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. it is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. the origin of value added is determined by the international standard industrial classification (isic), revision 3. data are in constant 2010 u.s. dollars population, total the total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship gdp per capita (constant 2010 us$) gdp per capita is gross domestic product divided by midyear population. gdp is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. foreign direct investment, net inflows (% of gdp) foreign direct investment are the net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor. it is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital, as shown in the balance of payments. this series shows net inflows (new investment inflows less disinvestment) in the reporting economy from foreign investors and is divided by gdp trade (% of gdp) trade is the sum of exports and imports of goods and services measured as a share of gross domestic product 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. . international journal of energy economics and policy | vol 6 • issue 3 • 2016 581 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2016, 6(3), 581-587. economic and technical feasibility of metering and sub-metering systems for heat accounting luca celenza1, marco dell’isola2, giorgio ficco3, marco greco4*, michele grimaldi5 1university of cassino and southern lazio, italy, 2university of cassino and southern lazio, italy, 3university of cassino and southern lazio, italy, 4university of cassino and southern lazio, italy, 5university of cassino and southern lazio, italy. *email: m.greco@unicas.it abstract the energy efficiency directive 2012/27/eu (eed) requires that final users in multi-apartment buildings supplied by common central heating source should be provided by 31 december 2016 with accounting systems, as long as technical feasibility and reasonable costs in relation to the potential energy savings can be demonstrated. such systems would reflect users actual thermal energy consumption. the typical configuration of italian multiapartment buildings implies quite expensive installation costs and sometimes even prevents the installation for technical reasons. coherently with eed, in such cases alternative cost-efficient methods for heat accounting should be adopted, such as indirect methods. this study assesses the economic and technical feasibility of the most common heat accounting systems. in this paper, after a brief analysis of the different approaches adopted in eu member states, the authors present a cost/benefit analysis that considers the main capital and running costs of individual heat accounting systems with respect to the potential energy savings achievable. keywords: energy efficiency, heat accounting, cost efficiency jel classifications: o31, o33 1. introduction the european directive 2012/27/eu (european parliament, 2012) on energy efficiency directive (eed) considers individual metering of heat consumption a remarkable potential driver of energy efficiency. according to the article 9.3 of eed, multiapartment buildings supplied by a district heating network or by a common central heating/cooling source should be provided by 31 december 2016 with individual meters capable to effectively measure the consumption of heat or cooling or hot water for each unit where technically feasible and cost-efficient. according to the eed, individual direct heat meters (hms) should be preferentially installed. nevertheless, under certain circumstances, the use of individual hms might be technically complicated and costly in relation to the potential energy savings. in such cases, alternative cost-efficient methods for heat accounting should be adopted, such as indirect methods. the modest diffusion of allocation services (especially in countries with moderate climate) avoided the development of studies regarding costs and benefits associable to real individual consumptions. in italy, almost 5.5 million apartments are potentially subject to the requirements of eed, of which only 2% are already equipped with direct hms or indirect heat cost allocators (hcas) (felsmann et al., 2015). however, such estimation is quite approximate, as in a subset of them both direct and indirect heat metering might result technically or economically unfeasible. table 1 shows the characteristics of italian residential buildings (istat, 2011). unfortunately, the typical configuration of heating plants in italian multi-apartment buildings rarely allows an easy installation of direct hms and such installation is often quite expensive or even technically unfeasible (e.g., in historical buildings). when hms are not economically or technically feasible, the eed allows the installation of indirect systems, such as hcas, which are particularly useful in buildings with architectural or structural constraints (authors, 2015a). noticeably, indirect systems do not carry out a direct and accurate measurement of thermal energy consumptions, since they give back a dimensionless estimation of heat consumption through some parameters strongly correlated with it. such estimation can be therefore used to share heating/cooling celenza, et al.: economic and technical feasibility of metering and sub-metering systems for heat accounting international journal of energy economics and policy | vol 6 • issue 3 • 2016582 costs of the entire building among single users, incentivizing tenants to reduce their own energy consumption also through operational rating energy diagnosis instead of asset rating one (authors, 2015b). in italy, decree 102/14 implemented the eed and confirmed the mandatory installation of heat accounting systems by 31 december 2016. the decree identified suitable existing standards and technical recommendations to accomplish the goal and delegated the authority for electricity, gas, and water to set appropriate regulations for service, quality and safety of district heating and of individual heat accounting. in this respect, the national standard uni 10200:2015 provides specific information about the design and management of heat accounting systems, expressly quoting both direct and indirect meters. eu member states are implementing the eed quite differently one from another. in some countries, such as germany and austria, almost every building is obliged to install individual metering and sub-metering systems, with few specific exceptions. in other countries, such as great britain, a technical and economical assessment is to be performed for each building. finally, in other countries, such as france and sweden, the commitment to introduce individual heat accounting systems is quite limited, as their economic efficiency is still considered unsatisfactory. eu commission is oriented to suggest the member states to implement specific actions for individual heat accounting and informative billing in order to maximize energy savings in the residential sector. such actions should be considered in view of the building characteristics and of their economic efficiency. buildings can be classified according to the following three types: • viable buildings, whose characteristics suggest that technical and economic feasibility is likely to be satisfactory in most cases; • exempted buildings, whose characteristics suggest that technical and economic feasibility is likely to be not efficient in most cases; • an open class of buildings which cannot be classified neither as viable nor exempted, which need an individual assessment of technical and economic feasibility. the assessment of the economic efficiency of individual heat accounting systems requires an in-depth estimation of the related capital and running costs and of expected benefits in terms of energy savings potentially achievable from the installation of individual metering and sub-metering systems. to this aim, table 2 shows capital and running costs of direct hms and indirect hcas and of the needed thermostatic valves available for the german (felsmann and schmidt, 2013) and uk (olloqui and duckworth, 2014) markets. noticeably, available costs of german market do not include costs for thermostatic valves, whereas for uk market such information is available. to date, several studies provided estimations of energy savings in different building typologies across several european countries (table 3). nevertheless, such estimations are extremely variable and range from 8% to 40%, due to different experimental contexts, which include different automation levels of temperature control, the usage of home displays, the frequency of consumption readings, the type of user and of building. furthermore, existing studies are in most cases referred to central europe climate, which is very different from the mediterranean one. in italy, only a few systematic analyses have been conducted to estimate the expected benefits and, to the best of our knowledge, none of them has been described in literature. in this paper, after a brief analysis of the main features of direct and indirect heat metering and sub-metering systems, a cost-benefit table 1: residential buildings in italy (source: istat) construction date total (millions) social housing (millions) single-family buildings (millions) total multi-apartment buildings (millions) type of heating source (%) none individual central <1945 6.60 0.12 2.39 4.21 35 40 15 1945-1955 4.33 0.11 0.99 3.34 25 40 35 1956-1965 5.71 0.17 1.09 4.62 10 40 50 1966-1975 5.14 0.22 1.15 3.99 10 60 30 1976-1985 3.32 0.18 0.80 2.53 10 80 10 1986-2001 2.16 0.12 0.80 1.37 5 90 5 >2001 1.20 0.09 0.42 0.78 5 90 5 total 28.47 1.03 7.64 20.83 19 55 26 table 2: capital and running costs of different direct hms and indirect hcas in germany and uk in case of individual heat measurement and informative accounting description capital (one-off) cost running cost per year cost per heating element cost per apartment cost per building cost per radiator cost per apartment cost per building germany hm €314.00 €21.00 €23.80 €67.50 hca €39.00 €126.00 €5.20 €75.10 uk hm €257.83 hm installation €77.35 €837.952 €90.24 hca1 €51.57 €837.952 €90.24 thermostatic valve1 €64.46 1installation costs not included, 2for napt ≤8; €1,031.33 for 9< napt<32; €1,224.70 for 33< napt<64; €2,578.32 for napt >65. hm: heat meters, hca: heat cost allocators celenza, et al.: economic and technical feasibility of metering and sub-metering systems for heat accounting international journal of energy economics and policy | vol 6 • issue 3 • 2016 583 analysis of the economic efficiency of such systems is presented and discussed. for the reader’s convenience, an appendix table 1 including all the acronyms used in this article is available at the end of the paper. 2. direct and indirect systems for heat accounting as discussed above, thermal energy consumptions can be estimated through direct or indirect devices. direct thermal energy meters, also known as hms allow a “true” direct thermal energy measurement and enable accurate measurements of actual consumptions. hms are regulated by the european directive on measuring instruments mid (european parliament, 2004), which guarantees the conformity in both a metrological and legal perspective and recognizes the importance of the technical standard en 1434 (cen, 2007a) and of the technical recommendation oiml r75 (2002). three typologies of indirect measuring devices are available, as summarized in table 4: • hca, regulated by en 834 (cen, 2013) and en 835 (cen, 1994); • insertion time counters compensated with the average temperature of the heat transfer fluid (itc-tc), regulated by uni 11388 (uni, 2015a); • insertion time counters compensated with the actual degreedays of the building unit (itc-ddc), regulated by uni 9019 (uni, 2013). table 5 shows the technical feasibility of direct hms and indirect hcas and itcs accounting systems in buildings in which a central heating system with vertical or horizontal configuration is available, coherently with the technical standard uni 10200 (uni, 2015b). it turns out that heat accounting with direct hms is not always technically feasible and rarely results cost-efficient. this mainly table 3: average, minimum and maximum expected benefits in some european countries reference member state eb (%) average min max (felsmann et al., 2015; oschatz, 2004) germany 20.2 9 30 (routledge and williams, 2012) uk 20 15-17 30 (siggelsten and hansson, 2010) sweden n.a. 10 40 (gullev and poulsen, 2006) denmark n.a. 15 17 (gorzycki, 2014) poland 15 8 33 (biron, 2015) france 20 19.8 n.a. (european commission, 2013) eu n.a. n.a. 30 eb: expected benefit table 4: technical characteristics of direct and indirect devices for heat accounting characteristics direct system indirect systems hm hca itc-tc itc-ddc technical standard mid+en 1434 en 834 uni 11388 uni 9019 control volume for the thermal balance heating plant of the apartment heated zone1 regulated zone2 regulated zone3 accuracy high medium medium medium costs medium-high medium medium-high medium-high unit kwh allocation unit (dimensionless) metrological conformity “ce” + “m” metrology marking (mid) initial verification by manufacturer (mid) subsequent verification (dm 155/2013) “ce” marking no duty of initial verification no duty of subsequent verification 1heating elements not included, 2heating elements and heating plant included, 3heating elements, heating plant and perimeter walls included. hm: heat meters, hca: heat cost allocators table 5: technical feasibility of direct and indirect devices for heat accounting heating element central heating plant with vertical mains direct systems indirect systems hm hca itc radiator poor1 optimal optimal convector poor1 good optimal fan coil poor1 not feasible poor underfloor heating panel poor1,2 not feasible poor2 wall or ceiling heating panel poor1,2 not feasible poor hot air nozzle optimal not feasible not feasible heating element central heating plant with horizontal pipes (ring) direct systems indirect systems hm hca hm radiator optimal3 poor4 good good convector optimal3 poor4 good good fan coil optimal3 poor4 not feasible poor underfloor heating panel optimal3 poor4 not feasible good3 poor4 wall or ceiling heating panel poor not feasible not feasible poor4 hot air nozzle optimal not feasible not feasible 1uneconomicalm, 2feasible if the fluid can be intercepted, 3when flow and return pipes are available in specific modules, 4when flow and return pipes are embedded in walls. hm: heat meters, hca: heat cost allocators celenza, et al.: economic and technical feasibility of metering and sub-metering systems for heat accounting international journal of energy economics and policy | vol 6 • issue 3 • 2016584 happens in the case of retrofit interventions on existing building, due to the configuration of the central heating plant (e.g., in the presence of vertical mains) or in the case of architectural constraints (e.g., in historical buildings). conversely, indirect devices can be installed in most existing buildings but are lacking in a metrological and legal perspective, which are crucial for the fairness of economic transactions and for consumer’s protection. on the whole, heat metering and sub-metering systems in multi-apartment buildings can be classified according to three configurations of the central heating plant (figure 1): (a) with horizontal pipes (ring configuration) equipped with individual hms; (b) with vertical mains equipped with hcas; (c) with vertical mains equipped with itc-tc or itcddc. figure 1: typical configurations of heat accounting systems with heat meters (a), heat cost allocators (b), and insertion time counters (c) c ba celenza, et al.: economic and technical feasibility of metering and sub-metering systems for heat accounting international journal of energy economics and policy | vol 6 • issue 3 • 2016 585 3. cost-benefit analysis of heat metering and sub-metering systems the european standard en 15459 (cen, 2007b) is explicitly quoted in the eu guidance note on eed (european commission, 2013) and in article 9, par. 5 recital (b) and (c) of decree 102/2014 as an applicable methodology for the economic assessment of the efficiency of individual metering and sub-metering systems in buildings. in fact, the above-mentioned standard can be used, even partially, for the evaluation of the economic feasibility of energy saving choices in buildings and for the comparison of different options of energy saving in buildings (i.e., system type, fuel type). en 15459 (cen, 2007b) resorts to the following parameters: (i) the real interest rate rr, i.e., the market interest rate compensated with the inflation rate ri; (ii) the discount rate rd(p); (iii) the present value factor fpv(n), that is the multiplicative coefficient of costs/ revenues in order to obtain the corresponding value referred to the initial year. the above described parameters are calculated by means of equations (1), (2) and (3), respectively: r r r rr i i = − +1 100/ (1) r p rd r p ( ) / = +       1 1 100 (2) f n r rpv r n r ( ) = − + −1 1 100 100 ( ) / (3) the economic efficiency of the investment can be therefore assessed from the calculation of the global cost of the investment cg(τ) corresponding to calculation period τ (4) or, as an alternative, from the evaluation of the yearly cost (5): c c c j r i v jg i j i a i d fτ τ τ( ) = + •( )−         ∑ ∑ =1 , ,( ) ( ) ( ) (4) a n f npv ( ) = ( ) 1 (5) where: ri is the annual inflation rate (which can depend from the i-th year); p is the number of years; τ is the calculation period in years; ci is the initial investment cost; ca,i(j) is the annual costs for component or j-th system of the i-th year (nominal value), including the management costs and the costs occurred for replacements; rd (i) is the discount rate for the i-th year; vf,τ(j) is the final value of the j-th component or system j-th at the end of the calculation period τ. here below, a sensitivity analysis of cost-efficiency of both direct (hms) and indirect (only hcas) heat metering and sub-metering systems is presented, taking into account capital expenditure (capex) and operational expenditure (opex) costs for the uk market as listed in table 6. in such analysis the following assumptions are invoked: • investment and operational costs as in table 2 for the uk market; • an average sized apartment of 80 m2; • a mean number of radiators for each apartment ncs=5; • calculation period τ=10 years; • expected benefit eb ranging 10-40% of the energy costs; • real interest rate (inflation rate included) rr=4%; • energy rate te (€/kwh) of heating, obtained from the gas mean rate tgas=0.80 €/sm 3 and considering the conventional gross heat value of natural gas ghv=38.52 mj/sm3 (aeegsi, 2016). furthermore, costs consequential to the installation of individual accounting devices (e.g., supply and installation of circulating pumps and inverters, of thermostatic valves and so on) and to the necessary adjustment of the heating plant itself have been neglected. in figure 2, the net present value (npv) trend along 10 years is depicted as a function of the primary energy need eph at typical figure 2: net present value with calculation period τ=10 years as a function of eph: (a) direct heat meters, (b) direct heat cost allocators b a table 6: capex and opex of the direct (hms) and indirect (hcas) accounting systems in the uk (for a typical building of 12 apartments each with average heated surface of 80 m2, 5 heating elements for each apartment) device capex opex hm individual €8,920.97 €1,082.89 hca €7,992.78 €1,082.89 capex: capital expenditure, opex: operational expenditure, hm: heat meters, hca: heat cost allocators celenza, et al.: economic and technical feasibility of metering and sub-metering systems for heat accounting international journal of energy economics and policy | vol 6 • issue 3 • 2016586 conditions at different expected benefit eb ranging 10-40% for a building of 12 apartments. it is evident that when the expected benefit decreases (both for hms and for hcas) also the eph at which the investment turns cost-efficient decreases. such value ranges 85-325 kwh/m2 for hms and 80-315 kwh/m2 for hcas when eb=10% and eb=40%, respectively. similarly, in figure 3, the npv trend along 10 years as a function of the pay-back period (pbp) is depicted for different eph at fixed eb=25% (surely optimistic) for a building of 12 apartments. from figure 3 it is possible to find out that as eph decreases also npv decreases. thus, the investment always results not cost-efficient when eph < 100 kwh/m 2. moreover, pbp is lower than 10 years only for eph>120 kwh/m 2. finally, in figure 4 the trend of the eph value at which the investment turns cost-efficient after 10 years is shown when the number of apartments in the building varies. from the figure 4 it is evident that such value is strongly affected by the number of apartments only for small buildings (i.e. two-family houses and napt < 8). 4. conclusions the cost benefit analysis of heat metering and sub-metering systems underlines some critical aspects of the implementation of the directive 2012/27/eu for energy efficiency. the sensitivity analysis, in fact, shows a significant dependence of the economic efficiency of such systems on the energy performance of the building (i.e., its primary energy needs) and on its dimensions, besides on capital and running costs and on the expected benefits. when a data acquisition system capable to continuously read individual heat consumption in real time is available, the following results applies for both hm and hca: • when eb decreases, the primary energy need eph of the building at which the investment turns cost-efficient decreases; • similarly, when the eph decreases, the economic efficiency of the investment decreases as well (always resulting not cost-efficient when eph<100 kwh/m 2) and pbp is lower than 10 years only when eph>120 kwh/m 2; • the limit of eph, beyond which heat metering and submetering systems are cost-efficient, depends on the number of apartments, especially in small buildings. noticeably, authors’ evaluations are based on earlier studies that carried out similar evaluations in different markets of european countries and at different climatic conditions. thus, future researches should carry out a precise survey of the capital and operational costs, and an experimental characterization of the expected benefits in different european markets and at different conditions, especially at mediterranean climate ones. acknowledgments the authors wish to thank aeegsi, the national authority for electricity, gas and water and enea, the italian agency for new technologies, energy and sustainable economic development, for their powerful support in developing this research. references aeegsi, autorità per l’energia elettrica il gas e il sistema idrico. (2016), prezzi e tariffe. available from: http://www.autorita.energia.it/it/ prezzi.htm. [last retrieved on 2016 may 17]. celenza, l., dell’isola, m., ficco, g., palella, b. i., riccio, g. (2015), heat accounting in historical buildings. energy and buildings, 95, 47-56. ficco, g., iannetta, f., ianniello, e., d’ambrosio alfano, f. r., dell’isola, m. (2015), u-value in-situ measurement for energy figure 3: pay-back period as a function of eph: (a) direct heat meters, (b) indirect heat cost allocators figure 4: energy needs lower limit for a variable number of flats and expected benefit=25% b a celenza, et al.: economic and technical feasibility of metering and sub-metering systems for heat accounting international journal of energy economics and policy | vol 6 • issue 3 • 2016 587 diagnosis of existing buildings. energy and buildings, 104, 108-121. biron, p. (2015), implementation of eed articles 9-11 into french law. dgec ministère de l’écologie, du développement durable et de l’énergie. heat cost allocation and billing workshop paris, 5-6 may; 2015. cen, european committee for standardization. (1994), en 835, heat cost allocators for the determination of the consumption of room heating radiators. appliances without an electrical energy supply, based on the evaporation principle. brussels. cen, european committee for standardization. (2007a), en 1434-1, heat meters – part 1: general requirements. brussels. cen, european committee for standardization. (2007b), en 15459:2007, energy performance of buildings economic evaluation procedure for energy systems in buildings. cen, european committee for standardization. (2013), en 834, heat cost allocators for the determination of the consumption of room heating radiators. appliances with electrical energy supply. brussels. decreto legislativo 4 luglio 2014, n. 102. (2014), gazzetta ufficiale della repubblica italiana. p165. european commission. (2013), guidance note on directive 2012/27/eu on energy efficiency, amending directives 2009/125/ec and 2010/30/ ec, and repealing directives 2004/8/ec and 2006/32/ec. brussels. european parliament. (2004), directive 2004/22/eu. official journal of the european union, l135, 1-80. european parliament. (2012), directive 2012/27/eu. official journal of the european union, l315/1, 1-56. f e l s m a n n , c . , s c h m i d t , j . ( 2 0 1 3 ) , a u s w i r k u n g e n d e r verbrauchsabhängigenabrechnung. in: abhängigkeit von derenergetischengebäudequalität. dresden. felsmann, c., schmidt, j., mróz, t. (2015), effects of consumptionbased billing depending on the energy qualities of buildings in the eu. dresden. gorzycki, r. (2014), experiences of the housing cooperative, robotnicza spółdzielnia mieszkaniowa ursus”, located in warsaw, in the range of heat metering. workshop on the implementation of eed articles 9-11 in relation to individual metering and billing of heating/cooling/ hot water consumption. warsaw. gullev, l., poulsen, m. (2006), the installation of meters leads to permanent changes in consumer behaviour. news from dbdh, 3, 20-24. istat, istituto nazionale di statistica. (2011), censimento popolazione e abitazioni. available from: http://ww.dati-censimentopopolazione. istat.it/index.aspx. [last retrieved 2016 may 17]. oiml, international organization of legal metrology. (2002), oiml r 75-1, heat meters part 1: general requirements. paris: international organization of legal metrology. olloqui, e., duckworth, a. (2014), decc heat networks individual heat metering viability test tool general specification. london. oschatz, b. (2004), heiz kostener fassungim niedrig energie haus. berlin: bbsr heft. p118. routledge, k., williams, j. (2012), district heating – heat metering cost benefit analysis. garston. siggelsten, s., hansson, b. (2010), incentives for individual metering and charging. journal of facilities management, 8(4), 299-307. uni, ente nazionale italiano di unificazione. (2013), uni 9019:2013, sistemi di contabilizzazione indiretti basati sul totalizzatore di zona termica e/o unità immobiliare per il calcolo dell’energia termica utile tramite i tempi di inserzione del corpo scaldante compensati dai gradi-giorno dell’unità immobil. milano. uni, ente nazionale italiano di unificazione. (2015a), uni 10200:2015, impianti termici centralizzati di climatizzazione invernale e produzione di acqua calda sanitaria criteri di ripartizione delle spese di climatizzazione invernale ed acqua calda sanitaria. milano. uni, ente nazionale italiano di unificazione. (2015b), uni 11388: 2015, sistemi di contabilizzazione indiretta del calore basati sui tempi di inserzione dei corpi scaldanti compensati dalla temperatura media del fluido termovettore. milano. table 1: acronyms acronym definition aeegsi italian regulatory authority for electricity gas and water (autorità per l’energia elettrica il gas e il sistema idrico) capex capital expenditure cen european committee for standardization (comité européen de normalisation) cg (τ) cost of the investment corresponding to calculation period τ eb expected benefit eed european directive 2012/27/eu on energy efficiency eph primary energy need fpv (n) present value factor hms heat meters hcas heat cost allocators istat italian national institute of statistics (istituto nazionale di statistica) itc-ddc insertion time counters compensated with the actual degree-days of the building unit itc-tc insertion time counters compensated with the average temperature of the heat transfer fluid mid european directive 2004/22/eu on measuring instruments ncs mean number of radiators for each apartment npv net present value oiml international organization of legal metrology (organisation internationale de métrologie légale) opex operating expenditure pbp pay-back period rd (p) the discount rate ri inflation rate vf,τ (j) is the final value of the jth component or system j-th at the end of the calculation period uni italian committee for the unification (ente nazionale italiano di unificazione) appendix . international journal of energy economics and policy | vol 6 • issue 3 • 2016594 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2016, 6(3), 594-601. sustainable economic growth: an empirical study for the asia-pacific economic cooperation forum josé dávalos* escuela superior politécnica del litoral, facultad de ciencias sociales y humanísticas, guayaquil-ecuador. *email: jldavalo@espol.edu.ec abstract this study analyses the validity of environmental kuznets curve (ekc) hypothesis for the asia-pacific economic cooperation forum (apec), within the period 1992-2012. three econometric models are performed, which use different environmental quality indicators as dependent variable. model 1: uses carbon dioxide (co2) total emissions in apec, model 2: uses co2 emissions generated from coal consumption, and model 3: uses co2 emissions generate from petroleum consumption. pedroni and kao co-integration approach are applied for testing long-run relationship between variables for each model. fully modified ordinary least squares method is employed for determining the elasticities of the long-run relationships. the analysis finds that an ekc is held under model 1, and 3, but for model 2 the relation between the variables does not show an inverted u shape behavior. additionally descriptive analysis and model 2 suggest that coal consumption has been increasing in last years, because of the effect in co2 emissions; even more in this specific indicator, economic activity is leading to an unsustainable growth scenario in apec. keywords: environmental kuznets curve, carbon dioxide emissions, economic growth jel classifications: q5, q56 1. introduction over the last two decades it has been observed the growing interest in the issues of scientific research with environmental background. one of the main motivations is the study of the consequences that brings development, measured in its various forms, on the health of planet earth. to study these effects with their causes, it can serve as an important recommendation tool for policy makers that address to create a sustainable scenario for future generations. one can say that one of the main problems in the issue of environmental pollution is the air pollution, which translates to creating a greenhouse effect. in air pollution they are involved a variety of gases, taking the name of greenhouse gases, where the main actor is carbon dioxide (co2), which has been attributed to be the cause of more than 50 % of greenhouse effect (ozturk and acaravci, 2010). the causes of greenhouse gas emissions can be many, since the use of appliances and burning trash, to large farming and industrial production, so it is reasonable to expect that economic activity will present one of the main causes of pollution, hence it can be said that the solution is not to stop such economic activities, because it means the growth of nations, but rather seek the methods by which the growth of nations is maintained with sustainable levels of contamination. kuznets (1955) tested the relationship between income levels and inequality hypothesis in per capita terms. under the assumption that higher income levels represent more development, it was observed that low levels of inequality levels were high, while with high levels of development, inequality tended to decline. this behavior took the name of kuznets curve (kc), and is recognized by its inverted “u” shape. if we take the kc hypothesis, this time not applied to a measure of inequality, but an indicator of environmental degradation, and obtain similar behavior (inverted u-shape) then an environmental kc (ekc) hypothesis can be validate. shafik and bandyopadhyay (1992), selden and song (1994), grossman and krueger (1994), holtz-eakin and selden (1995), stern et al. (1996), panayatou (1997) were some dávalos: sustainable economic growth: an empirical study for the asia-pacific economic cooperation forum international journal of energy economics and policy | vol 6 • issue 3 • 2016 595 of the researchers who first developed the concept of the ekc, applied to a variety of specific issues such as estimating demand elasticities of environmental quality, effects of international trade, implementation case environmentally efficient technologies, improvements in government policies, etc. 2. the ekc across asia-pacific countries the asia-pacific economic cooperation (apec) is an organization that currently has 21 member states (australia, brunei darussalam, canada, chile, people’s republic of china, chinese taipei, usa, philippines, hong kong, indonesia, japan, republic of korea, malaysia, mexico, new zealand, papua new guinea, peru, singapore, russia, thailand and vietnam). apec aims to increase opportunities of an inclusive, sustainable and secure balanced economic growth through regional economic integration of its members (apec, 2015). it was created in 1989 by australian initiative in response to multiple new blocks that have been marked new trends in economic cooperation and integration in the world, such as the consolidation of the european union or the signing of trade agreements, such as nafta in america. the forum includes both developed economies and developing economies. in recent decades it has been reported a large increase in economic activity carried out by asian countries, as china controlled its own 11% of world trade in 2013 (wto, 2015), other economies such as south korea and japan are highly industrialized, in addition the sum of the gross domestic product (gdp) of the 21 forum members equal about 56% of total world production. as mentioned above, the link between economic activity and environmental quality of the countries where it is carried out is currently of great interest, and also is the aim of this study. many research has taken asia-pacific countries as objects of study, and in the last 5 years have seen the implementation of a variety of econometric and analytical techniques that offer different points of view to researchers. regarding southeast asia, indonesia relatively recent studies of narayan and narayan (2010) and saboori and sulaiman (2013a) provide results do not support the hypothesis of an ekc. for malaysia, saboori et al. (2012), saboori and sulaiman (2013a), shahbaz et al. (2013) and lau et al. (2014) find sufficient evidence to prove the validity of the ekc using co2 as an indicator of environmental degradation. in contrast, other studies as mugableh (2013) or saboori and sulaiman (2013b), which includes disaggregated variables of energy consumption, have no empirical evidence that holds an ekc. for the philippines, narayan and narayan (2010) and saboori and sulaiman (2013a), using different methodologies, show no evidence to prove the existence of a ekc. similarly to thailand, narayan and narayan (2010) shows that the evidence does not support one ekc. in contrast saboori and sulaiman (2013a) determine that the evidence is sufficient to validate the ekc in singapore and thailand. al-mulali et al. (2015) argues that the evidence is not sufficient to prove the ekc hypothesis in vietnam. for other asia-pacific countries, such as south korea and japan onafowora and owoy (2014) proves that there is sufficient evidence to validate the ekc hypothesis in both countries. in the case of china, we can say that is one of the countries that most studies have been conducted for, finding much evidence in favor of ekc (jalil and feridun, 2011; jayanthakumaran and liu, 2012; wang et al., 2016), and also evidence that prevents assert the existence of a ekc (onafowora and owoy, 2014; ozturk, 2015; kang et al., 2016). in the other hand for russia, pao et al. (2011) and ozturk (2015) determine that there is not an ekc. for american pacific nations, in the case of canada, plassmann and khanna (2006) and hamit-haggar (2012) find results in favor of ekc. narayan and narayan (2010) finds that in mexico the existence of a ekc is validated, while in chile and peru it cannot be validate. in contrast onafowora and owoy (2014) argues that in mexico there would be no ekc. the aforementioned studies have used different methodologies, different indicators of environmental degradation, and at different periods of study. the technique of autoregressive model with distributed lags (ardl) has been perhaps the most common method applied to the analysis of individual countries. however, in countries like china, with the aim of buil studies based on their political or natural divisions, panel model methods are applied (table 1). considering that most recent studies using co2 as an indicator of environmental degradation, in the present study that fact is replicated, further disaggregation of two main sources of co2 emissions is taken, as is the co2 from the petroleum consumption, and co2 emissions from coal consumption. 3. data and variables in the present study 4 series are taken: (1) co2 emissions from petroleum consumption, (2) co2 emissions from coal consumption, (3) total co2 emissions from energy consumption, (4) real gdp at 2005 dollars adjusted for purchase power parity. series 1, 2 and 3 are taken from the database of the u.s. energy information administration (www.eia.gov) and are measured in millions of metric tons. series 4 is taken from penn wordl table 8.01, measured in millions of dollars. in order to obtain better comparable series, they are transformed in per capita terms, additionally expressed in their natural logarithm in order to estimate elasticities (table 2). all series are evaluated within 1992-2012 period. brunei and papua new guinea are excluded from the analysis, since the unavailability of certain data of some series would cause an unbalanced panel. 4. methodology 4.1. econometric specification an ekc generally can be expressed as: e = f(y,y2,w), where e denotes an environmental quality indicator, y and y2 represent the level of income and its square respectively, and w is a set of additional variables which the researcher has evidence affect on environmental quality, either positively or negatively. in the present study three indicators of environmental quality are used, and the variable gdp per capita represents levels of income, on the other hand additional regressors variables are not included. given the notation for panel data, three models are specified, one for each environmental indicator, as follows: 1 developed by robert, c.f., inklaar, r. and timmer, m.p. (2015), “the next generation of the penn world table” forthcoming american economic review. available for download at www.ggdc.net/pwt. http://www.rug.nl/research/ggdc/data/pwt/v81/the_next_generation_of_the_penn_world_table.pdf dávalos: sustainable economic growth: an empirical study for the asia-pacific economic cooperation forum international journal of energy economics and policy | vol 6 • issue 3 • 2016596 2 2 0 1 2model 1: it it it itlco lgdp lgdp u= + + +α α α (1) 2 2 0 1 2model 2: β β βit it it itlco c lgdp lgdp e= + + + (2) 2 2 0 1 2model 3: it it it itlco p lgdp lgdp= + + +γ γ γ ε (3) where, αj, βj, γj for j = 0, 1, 2 are the elasticities to be estimated, and uit, eit, εit are random error term. the ekc hypothesis is validity when α1 > 0, β1 > 0, γ1 > 0 and α2 < 0, β2 < 0, γ2 < 0. if the elasticitities have the expected signs, then the models (1), (2) and (3) will present an inverted u-shape. 4.2. panel unit root detection in the present study, following farhani et al. (2014), with the aim of verifying the stationary properties and intregración variables, three statistical test (1) are used levin, lin, and chu t-statistics (levin et al., 2002), (2) breitung (2001) t-statictics, and (3) im, pesaram and shin w-statistic (im et al., 2003). while levin et al. (2002) t-statistics and the breitung (2001) t-statistics propose a null hypothesis of unit root presence, it is that it follow a common process on that root; im et al. (2003) test proposed under the null hypothesis of unit root presecia following an individual process. table 3 shows the detailed formulas used for the different tests. 4.3. testing for co-integration the recent literature on studies of the ekc has been used extensively the model ardl (pesaran et al., 2001) bound testing approach, because the possibility of an individually comparative analysis between shortand long-run of the countries concerned. however, when it comes to data panels, say, groups of countries or economic blocs, recent studies apply based on co-integration panel methods either proposed by pedroni (1999) (hamit-haggar, 2012; farhani et al. 2014; al-mulali and ozturk, 2015; al-mulali et al. 2015) and kao (1999) co-integration test (al-mulali et al., 2015). in this study both co-integration test suggested by pedroni (1999; 2004) and kao (1999) are applied. pedroni (1999; 2004) co-integration test shows seven test divided into two dimensions. within dimension has the following panel statistics: v-statistic, rho-statistic, pp-statistic and augmented dickey-fuller (adf)-statistic; between dimension has the following group statistics: rho-statistic, pp-statistic and adfstatistic. if the p value of most of these statistics are significant, then we can say that the analyzed variables holds a long-run table 1: literature review summary in asia-pacific countries country study period methodology indicator inverted u-shape? canada plassmann and khanna (2006) 1975-1999 johansen co-integration-ols model co2 yes hamit-haggar (2012) 1990-2007 pedroni co-integration-fmols co2 yes chile narayan and narayan (2010) 1980-2004 pedroni co-integration – panel model co2 no china jalil and feridun (2011) 1975-2005 ardl co2 yes jayanthakumaran and liu (2012) 1990-2007 panel model and simultaneous equations so2 yes onafowora and owoy (2014) 1970-2010 ardl co2 no ozturk (2015) 1980-2013 generalized method of moments co2 yes kang et al. (2016) 1997-2012 spatial panel model co2 no wang et al. (2016) 1990-2012 semi parametric panel model analysis co2 no indonesia narayan and narayan (2010) 1980-2004 pedroni co-integration – panel model co2 no saboori and sulaiman (2013a) 1971-2009 ardl co2 no japan onafowora and owoy (2014) 1970-2010 ardl co2 yes korea onafowora and owoy (2014) 1970-2010 ardl co2 yes malaysia saboori et al. (2012) 1980-2009 ardl co2 yes saboori and sulaiman (2013a) 1971-2009 ardl co2 yes saboori and sulaiman (2013b) 1971-2009 ardl co2 no mugableh (2013) 1971-2012 ardl co2 no shahbaz et al. (2013) 1971-2011 ardl co2 yes lau et al. (2014) 1970-2008 ardl co2 yes mexico narayan and narayan (2010) 1980-2004 pedroni co-integration – panel model co2 yes onafowora and owoy (2014) 1970-2010 ardl co2 no peru narayan and narayan (2010) 1980-2004 pedroni co-integration – panel model co2 no philippines narayan and narayan (2010) 1980-2004 pedroni co-integration – panel model co2 no saboori and sulaiman (2013a) 1971-2009 ardl co2 no russia pao et al. (2011) 1990-2007 johansen co-integration-ols model co2 no ozturk (2015) 1980-2013 generalized method of moments co2 no singapore saboori and sulaiman (2013a) 1971-2009 ardl co2 yes thailand narayan and narayan (2010) 1980-2004 pedroni co-integration – panel model co2 no saboori and sulaiman (2013a) 1971-2009 ardl co2 yes vietnam al-mulali et al. (2015) 1981-2011 ardl co2 no ols: ordinary least squares, ardl: autoregressive distributed lag, fmols: fully modified ordinary least squares, co2: carbon dioxide table 2: variable transformations variable symbol unit of measurement natural logarithm of per capita co2 emissions from petroleum consumption lco2p metric tons natural logarithm of per capita co2 emissions from coal consumption lco2c metric tons natural logarithm of total per capita co2 emissions from energy consumption lco2 metric tons natural logarithm of real gdp per capita lgdp u.s.d. dollars squared natural logarithm of real gdp per capita lgdp2 u.s.d. dollars gdp: gross domestic product, co2: carbon dioxide dávalos: sustainable economic growth: an empirical study for the asia-pacific economic cooperation forum international journal of energy economics and policy | vol 6 • issue 3 • 2016 597 relationship, so there is co-integration. farhani et al. (2014) provides a review of the seven statistical formula proposed above. kao (1999) co-integration test is performed through the combined application of a df test and adf test for unit root based on residuals. assuming the residual 1ˆ ˆit it ite e vρ −= + under a regression equation yit = αi + βxit + eit for i = 1,…,n, t = 1,…,t, estimated by fixed effects, it can be obtained: *2 11 2 ˆ( 1) n t iti t df e e t t sρ ρ −= == − = ∑ ∑ (4) table 3: panel unit root test summary test statistics parameters hyphotesis breitung (2001) 2 1 2 1 n(1, 0) n *' * i i ii ub n *' * i i ii y x x a'ax − = − = = → ∑ ∑  σ σ from the equation yit = μi + βit+ xit where, xit k p ik i,t-k it= + = + ∑ 1 1 α x µ e(δyit) = βi, where δyit is white noise σ ∆i i ie y 2 1 2= −( )² , ,i i1 ity y y ′= …  ∆ ∆ x y yi i i t= …  ′ −0 1, , , y ay y yi i i * it ** 1= = …   ′ , , x bx x xi * i i * it *= = …    ′ 1, , such that= e y xit * it *,( ) 0 t=time series dimention n=total cross section units 1 0 1 h : 0 p ik k + = − =∑α (unit root) levin et al. (2002) 2 * * * ˆˆ ( ) n(1, 0)n mt mt t ts std t −− = →    δ ε δ σ δ µ σ t = time series dimension * mtµ =mean adjustment * mtσ =estandar deviation adjustment ˆ ˆ( ) t std =δ δ δ where δ̂ and ˆ( )std δ are taking by stamating: 1 1ˆit it ite v − −= + δ ε and, 2 2 1 1 2 1 ˆˆ ( ) i n t it it i t p e v nt − = = +    = −      ∑ ∑    ε δσ h0: δ = 0 (unit root) im et al. (2003) { }( ) (1, 0) ( ) nt t tbar t n t bar e t z n var t − − = →     1 1 n nt iti t bar t n = − = ∑  where, , 1 ' 1/ 2 , 1 , 1ˆ ( ) ' i t i it it i i y m y t y m y − − − = τ ∆ σ and 2 1 ˆ ' i i it y m y t = − τ∆ ∆σ 1 '( )'t t t t tm i −= −τ τ τ τ τ τt = (1,1,…,1) t δyi = (δyi1, δyi2,…,δyit)’ yi,−1 = (yi0, yi1,…, yi, t−1)’ and it is an identity matrix of dimensions t×t h0: unit root all test equation are according with the notatition used in the original papers. dávalos: sustainable economic growth: an empirical study for the asia-pacific economic cooperation forum international journal of energy economics and policy | vol 6 • issue 3 • 2016598 and if we derive    1 2ˆv yy yx xx σ − = −∑ ∑ ∑ y 2 10 ˆ ˆˆ ˆ ,v yy yx xxσ −= −ω ω ω statistic (5) can be built. * 0 2 2 0 2 2 6 2 (0,1) 3 2 ˆ ˆ ˆ ˆ ˆ0ˆ 1 v adf v t v v v v n t df n σ σ σ σ σ σ + = → + (5) in a same way if one takes into account a residual equation of the form: 1 1 ˆ ˆ ˆ p it it j it j itp j e e e vρ ϕ− − = = + +∑ ∆ (6) statistic (7) can be constructed, on which the test co-integration is evaluated. the null hypothesis can be presented as: h0: ρ = 0. 0 2 2 0 2 2 ˆ ˆ ˆ ˆ 6 2 (0,1) 3 2 10ˆ ˆ v adf u v v v v n t adf n σ σ σ σ σ σ + = → + (7) 4.4. fully modified ordinary least squares (fmols) model having tested the existence of co-integration for the variables of the three econometric specifications, a regression is applied by fmols in line of pedroni (2000). fmols is considered as an efficient estimation method, and offers other advantages, for example it can provide consistent estimators and can eliminate the correlation between the co-integration equation and stochastic regressor innovation as al-mulali et al. (2015) noted. 5. empirical analysis and results as a descriptive analysis five ratios are performed (table 4) in order to observe the participation and behavior of co2 emissions made by of apec countries member. figure 1a shows the evolution of the share who of co2 emissions from the consumption of petroleum and from coal consumption relative to the total co2 emissions in apec, it is observed that approximately from 1999, the co2 emissions caused by petroleum consumption has been decreasing. on the other hand roughly from the same year co2 emissions from the consumption of coal has meant greater weight within the total co2 emissions in apec, for example in 1999, a 41.47% of total co2 emissions in apec were due to coal consumption, in 2011 the figure was 51.40%. in contrast to 1999 when a 40.07% of total co2 emissions was due to petroleum consumption, while in 2011 the same proportion dropped to 31.34%. this seems to show greater intensive use of sources different from petroleum in apec, such as coal, with sharply rising trends. the literal figure 1b shows that co2 emissions from petroleum consumption does not exceed 1% of total global co2 emissions during the study period. on the other hand for 2011 co2 emissions from the consumption of apec coal was equivalent to almost 33% of global co2 emissions. literal figure 1c shows globally the share of apec co2 emissions relative to global emissions. in this aspect there is a growing trend, and throughout the study period more than 50% of global co2 emissions were produced by apec members; by 2011 this figure reached a considerable 63.86%. descriptively the input that within apec generates more co2 emissions is coal, while total co2 emissions made by member countries highly contribute to global emission levels. 5.1. panel unit root and co-integration test panel unit root test reveals that all the variables are not stationary at levels, taking in consideration the presence of individual stochastic intercept and trend. since all variables are stationary at first differences, then all variables are integrate of degree one i(1), so the pedroni and kao co-integration test can be performed. table 5 shows test details. co-integration test ensures that exists an long-run relationship for each case of study (table 6). having ensured the existence of cointegration, the three models are estimated by fmols (table 7). estimated model 1 shows that data supports and ekc, meaning that for an increase of 1% in the gdp2, table 4: descriptive ratios ratios 2 2 pet co emissions from petroleum consumption made by apec apec total co emissions made by countries in apec = 2 2 coal co emissions from coal consumption made by apec apec total co emissions made by countries in apec = 2 2 pet co emissions from petroleum consumption made by apec world total global co emissions = 2 2 coal co emissions from coal consumption made by apec world total global co emissions = 2 2 apec total co emissions made by countries in apec world total global co emissions = apec: asia-pacific economic cooperation forum table 5: panel unit root test results test levels first difference levin, lin and chu t lco2 −2.15856 −8.24620*** lco2p −1.58323 −12.6722*** lco2c −1.25479 −12.8990*** lgdp −1.33934 −6.19789*** lgdp2 −0.87369 −6.19626*** im, pesaram and shin w-stat lco2 −0.89458 −10.7874*** lco2p −2.84733 −10.6073*** lco2c 1.19006 −12.4606*** lgdp 0.57526 −6.97100*** lgdp2 1.40822 −6.96158*** breitung t-statistics lco2 1.38792 −8.24620*** lco2p 0.81088 −5.84711*** lco2c 1.72899 −6.18701*** lgdp −1.51210 −4.57727*** lgdp2 −1.47126 −4.55783*** all tests consider individual intercept and trend for each variable, ***significance level at 1%. gdp: gross domestic product dávalos: sustainable economic growth: an empirical study for the asia-pacific economic cooperation forum international journal of energy economics and policy | vol 6 • issue 3 • 2016 599 figure 1: ratios behavior across time, (a) carbon dioxide (co2) from petroleum versus co2 from coal (within asia-pacific economic cooperation forum [apec]), (b) co2 emitted by petroleum and coal consumption (within apec) against global co2 emissions, (c) influence of total co2 emissions of apec in global co2 emissions c ba table 6: co-integration test results cases lco2=f (lgdp, lgdp 2) lco2c=f (lgdp, lgdp 2) lco2p=f (lgdp, lgdp 2) pedroni co-integration test within dimension panel v-statistic 3.936650*** −1.376843 2.280060** panel rho-statistic 1.309713 1.116521 1.470787 panel pp-statistic −2.319541** −2.596653*** −1.274924 panel adf-statistic −2.054045** −2.739713*** −2.786685*** between dimension group rho-statistic 2.279301 1.349947 2.933348 group pp-statistic −4.425428*** −4.952845*** −2.402021*** group adf-statistic −4.454357*** −5.639495*** −3.586924*** kao co-integration test adf −2.812177*** −3.316323*** −2.19522** residual variance 0.003419 0.253849 0.004107 hac variance 0.004845 0.256623 0.004127 deterministic trend and intercept have been assume for pedroni co-integration test. *** and ** are significance levels at 1% and 5% respectively. adf: augmented dickey-fuller, hac: heteroskedasticity and autocorrelation consistent, gdp: gross domestic product, co2: carbon dioxide dávalos: sustainable economic growth: an empirical study for the asia-pacific economic cooperation forum international journal of energy economics and policy | vol 6 • issue 3 • 2016600 will decrease the total co2 emissions 0.123044% in average. for model 3 the reporter sing of the gdp2 is negative, so an increase of 1% in gdp2, will decrease the co2 emissions (of petroleum consumption) 0.123044% in average. in contrary form model 2 shows an ekc cannot be held, it means that increases of gdp bring increases in co2 emissions (of coal consumption) levels. 6. conclusions the apec is a block of contrasts. several of its members are the most developed economies in the world, that have reached upper living standards (such as u.s.a., canada, korea or japan), in the other hand some members are developing economies with high industrialization levels that still have low living standards (such as mexico, malaysia, indonesia, philippines or taiwan). the present analysis based on the ekc approach has considerated air pollution as the interest matter. using total co2 emissions as environmental quality indicator, there are sufficient statistic evidence that ensures the existence of an ekc in apec for the period 1992-2012. taking into consideration that there is no a previous panel study for apec, we can argue that this results are consistent with plassmann and khanna (2006), hamit-haggar (2012), jalil and feridun (2011), ozturk (2015), onafowora and owoy, (2014), saboori et al. (2012), saboori and sulaiman (2013a), shahbaz et al. (2013), lau et al. (2014), narayan and narayan (2010) since they have investigated and found ekc in some apec members in an individual form. despite an ekc exists for the total co2 emissions, when only co2 emissions generate by coal consumption is taken as dependent variable, the characteristic inverted “u” shape of ekc is not held, it means that the increasing levels of gdp (as an economic activity proxy) lead to proportional increasing levels of environmental degradation, and this degradation is linked to unsustainable coal consumption stage. policy makers have to take in consideration the trend of coal consumption, and focus on the develop of renewables energy sources, it could be the way that environmental degradation for co2 emissions start to slow down, in addition it reach a less dependent levels of the coal, even more when it is an highly polluting agent and nonrenewable mineral. references al-mulali, u., ozturk, i. (2015), the effect of energy consumption, urbanization, trade openness, industrial output, and the political stability on the environmental degradation in the mena (middle east and north african) region. energy, 84, 382-389. al-mulali, u., saboori, b., ozturk, i. (2015), investigating the environmental kuznets curve hypothesis in vietnam. energy policy, 76, 123-131. al-mulali, u., tang, c.f., ozturk, i. (2015), estimating the environment kuznets curve hypothesis: evidence from latin america and the caribbean countries. renewable and sustainable energy reviews, 50, 918-924. asia-pacific economic cooperation. (2015), asia-pacific economic cooperation official. available from: http://www.apec.org/. breitung, j. (2001), the local power of some unit root tests for panel data. in: baltagi, b.h.t., fomby, b., hill, r.c., editors. nonstationary panels, panel cointegration, and dynamic panels, advances in econometrics. vol. 15. amsterdam: jai press. p161-177. farhani, s., mrizak, s., chaibi, a., rault, c. (2014), the environmental kuznets curve and sustainability: a panel data analysis. energy policy, 71, 189-198. grossman, g.m., krueger, a.b. (1994), economic growth and the environment. quarterly journal of economics, 110(2), 353-377. hamit-haggar, m. (2012), greenhouse gas emissions, energy consumption and economic growth: a panel cointegration analysis from canadian industrial sector perspective. energy economics, 34(1), 358-364. holtz-eakin, d., selden, t.m. (1995), stoking the fires? co2 emissions and economic growth. journal of public economics, 57(1), 85-101. im, k.s., pesaran, m.h., shin, y. (2003), testing for unit roots in heterogeneous panels. journal of econometrics, 115(1), 53-74. jalil, a., feridun, m. (2011), the impact of growth, energy and financial development on the environment in china: a cointegration analysis. energy economics, 33(2), 284-291. jayanthakumaran, k., liu, y. (2012), openness and the environmental kuznets curve: evidence from china. economic modeling, 29(3), 566-576. kang, y.q., zhao, t., yang, y.y. (2016), environmental kuznets curve for co2 emissions in china: a spatial panel data approach. ecological indicators, 63, 231-239. kao, c. (1999), spurious regression and residual-based tests for cointegration in panel data. journal of econometrics, 90(1), 1-44. kuznets, s. (1955), economic growth and income inequality. the american economic review, 45(1), 1-28. lau, l.s., choong, c.k., eng, y.k. (2014), investigation of the environmental kuznets curve for carbon emissions in malaysia: do foreign direct investment and trade matter? energy policy, 68, 490-497. levin, a., lin, c.f., chu, c.s.j. (2002), unit root tests in panel data: asymptotic and finite-sample properties. journal of econometrics, 108(1), 1-24. mugableh, m.i. (2013), analysing the co2 emissions function in malaysia: autoregressive distributed lag approach. procedia economics and finance, 5(13), 571-580. narayan, p.k., narayan, s. (2010), carbon dioxide emissions and economic growth: panel data evidence from developing countries. energy policy, 38(1), 661-666. onafowora, o.a., owoye, o. (2014), bounds testing approach to analysis of the environment kuznets curve hypothesis. energy economics, 44, 47-62. ozturk, i. (2015), sustainability in the food-energy-water nexus: evidence table 7: long-run estimations fmols method inverted u shape? model 1 lco2=3.004295lgdp−0.123044lgdp 2 ...............(6.916316)*** (−5.148474)*** yes model 2 lco2c=−3.477867lgdp+0.262781lgdp 2 .....................(1.809123)* (2.640056)*** no model 3 lco2p=3.865664lgdp−0.187931lgdp 2 ..................(1.809123)*** (2.640056)*** yes between parenthesis are t-statistics, *** and * are significance levels at 1% and 10% respectively. fmols: fully modified ordinary least squares, gdp: gross domestic product, co2: carbon dioxide dávalos: sustainable economic growth: an empirical study for the asia-pacific economic cooperation forum international journal of energy economics and policy | vol 6 • issue 3 • 2016 601 from brics (brazil, the russian federation, india, china, and south africa) countries. energy, 93, 999-1010. ozturk, i., acaravci, a. (2010), co2 emissions, energy consumption and economic growth in turkey. renewable and sustainable energy reviews, 14(9), 3220-3225. panayatou, t. (1997), demystifying the environmental kuznets curve: turning a black box into a policy tool. environment and development economics, 2(04), 465-484. pao, h.t., yu, h.c., yang, y.h. (2011), modeling the co2 emissions, energy use, and economic growth in russia. energy, 36(8), 5094-5100. pedroni, p. (1999), critical values for cointegration tests in heterogeneous panels with multiple regressors. oxford bulletin of economics and statistics, 61(s1), 653-670. pedroni, p. (2000), fully modified ols for heterogenous co-integrated panels. review of economics and statistics, 15(4), 93-130. pedroni, p. (2004), panel co-integration: asyntotic and finite sample properties of pooled time series tests with an application to the ppp hypothesis. econometric theory, 20(03), 597-625. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. plassmann, f., khanna, n. (2006), household income and pollution: implications for the debate about the environmental kuznets curve hypothesis. the journal of environment and development, 15(1), 22-41. saboori, b., sulaiman, j. (2013a), co2 emissions, energy consumption and economic growth in association of southeast asian nations (asean) countries: a cointegration approach. energy, 55, 813-822. saboori, b., sulaiman, j. (2013b), environmental degradation, economic growth and energy consumption: evidence of the environmental kuznets curve in malaysia. energy policy, 60, 892-905. saboori, b., sulaiman, j., mohd, s. (2012), economic growth and co2 emissions in malaysia: a co-integration analysis of the environmental kuznets curve. energy policy, 51, 184-191. selden, t., song, d. (1994), environmental quality and development: is there a kuznets curve for air pollution emissions? journal of environmental economics and management, 27(2), 147-162. shafik, n., bandyopadhyay, s. (1992), economic growth and environmental quality: time series and cross-country evidence. vol. 904. washington, dc: world bank publications. shahbaz, m., solarin, s.a., mahmood, h., arouri, m. (2013), does financial development reduce co2 emissions in malaysian economy? a time series analysis. economic modeling, 35, 145-152. stern, d.i., common, m.s., barbier, e.b. (1996), economic growth and environmental degradation: the environmental kuznets curve and sustainable development. world development, 24(7), 1151-1160. wang, y., han, r., kubota, j. (2016), is there an environmental kuznets curve for so2 emissions? a semi-parametric panel data analysis for china. renewable and sustainable energy reviews, 54, 1182-1188. world trade organization. (2015), world trade report 2014. switzerland. available from: https://www.wto.org/english/res_e/booksp_e/ world_trade_report15_e.pdf. . international journal of energy economics and policy | vol 7 • issue 5 • 2017 271 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(5), 271-278. system aspects of fuel and energy balance formation irina vladimirovna osinovskaya* institute of management and business, department of energy complex management, tyumen industrial university, 625000, tyumen, volodarskogo street 38, russia. *email: osinovskaya79@mail.ru abstract this article reveals the importance of the fuel and energy balance (feb) for ensuring the country’s energy security. the role of the fuel and energy complex (fec) in the russian economy is shown. feb is considered as a possible efficient tool for managing the development of the fec and, as a consequence, ensuring the country’s energy security. the necessity to develop the methodological foundations of the feb formation is substantiated. proposals have been made concerning the expediency of building the process of forming the feb on the basis of systemic contours. the author’s interpretation of the term “systemic contour” is disclosed in the context of solving the issues on the formation of feb. it is proposed to single out several major systemic outlines that reflect the situation of the world’s energy and political systems, the social, economic, political and energy systems of the country, as well as in the fec and other subsystems. particular attention is paid to the issues of information support for the formation of feb, taking into account the spatial coverage of the subsystems included in the consolidated feb of the country. the need for attention on the part of the state to address the issue of forming unified information and analytical space and an early warning system is underlined. the emphasis is placed on the fact that it is these information systems that will allow timely monitoring of the changes in the subsystems of the fec, and also taking appropriate proactive measures to stabilize the situation in the short and long term. keywords: fuel and energy balance, complex, formation, system, state, information, strategy, energy security jel classifications: l10, l94, l71 1. introduction the fuel and energy balance (feb) is a balanced system of quantitative characteristics that characterize the state and level of development of the fuel and energy complex (fec) at a certain point in time. stable and progressive development of the fec contributes to the implementation of strategic goals at the state level regarding the preservation of the country’s energy security. the level of economic development of the country today still depends on the level of the fec development. according to a. novak, despite the sanctions and reduction of prices for the main energy carriers, all fuel and energy industries worked in 2016 steadily and improved their performance. the total inflow of investments into the tec amounted to 3.7 trillion rubles, growth about 6%. all power engineering developed ahead of the economy. for the first time in many years, the commissioning of new fields began (results of the fec in 2016, 2017). today the fec is one of the most stable operating production complexes of the russian economy. it accounts for about 30% of russia’s gdp, 50% of the country’s tax revenue, and 30% of exports. the structure of the fec is shown in figure 1. oil production with condensate in russia and the world for the period from 1970 to 2015 is presented in table 1 (eder et al., 2016). in 2015 russia reached the highest level of oil production in the newest history of the country 534 million tons, or 12.2% of the world production. however, it is only 93% of the oil production in 1987. the stable trend in the change in the structure of oil production in russia is an increase in the share of gas condensate production, which is associated with an active involvement of high-condensate gas in the western siberia. and such trends are observed in all subsystems of the russian fec, which will directly lead to a gradual change in the structure of the energy balance in the prospective period. osinovskaya: system aspects of fuel and energy balance formation international journal of energy economics and policy | vol 7 • issue 5 • 2017272 investigating the state of the fec for today and its impact on the structure of the energy balance, it is necessary to identify the role of alternative energy sources. despite the fact that for many years the most part of the energy component for russia will be based on traditional energy carriers, it is necessary to more actively solve the tasks to achieve innovative development of non-traditional energy sources. today, the situation in the world is developing in the field of alternative energy sources, and if russia does not follow the trend of innovative development, then there is a risk of lagging behind the leading countries in the world. the report of the national rating agency development of alternative energy in russia notes that the electric power industry based on renewable energy sources (res) in russia currently does not play a significant role in the country’s energy system, providing less than 1% of the total electricity generation. nevertheless, the government of the russian federation defined the main directions of the state policy, within the framework of which it is envisaged to expand the using of res in the sphere in order to increase the energy efficiency of the electric power industry (razvitie alternativnoy energetiki v rossii (development of alternative power industry in russia, 2016). table 2 presents the overall results of renewable energy projects. figure 1: structure of the fuel and energy complex table 1: oil production with condensate in russia and the world (1970-2015) year in the world ussr/cis rsfsr/russia opec oil prices on the world market, usd/bbl. total mt. share in the world, % total mt. share in the world,% total mt. share in the world, % urals brent 1 2 3 4 5 6 7 8 9 10 1970 2.355 353 15.0 285 12.1 1132 48.0 1980 3.088 603 19.5 547 17.7 1287 41.7 38.3 39.8 1985 2.792 608 21.8 542 19.4 772 27.6 25.9 27.6 1990 3.168 570 18.0 516 16.3 1159 36.6 20.3 21.0 1995 3.278 355 10.8 307 9.4 1317 40.2 16.4 16.2 2000 3.618 396 10.6 323 8.9 1511 41.8 27.4 28.3 2005 3.938 580 14.8 470 12.1 1691 42.9 50.2 54.6 2010 3.979 663 17.0 505 13.1 1671 42.0 77.9 79.6 2011 4.012 665 16.6 511 12.7 1711 42.6 108.0 110.0 2012 4.119 669 16.2 518 12.6 1782 43.3 110.6 111.7 2013 4.127 677 16.4 523 12.7 1734 42.0 107.9 108.7 2014 4.229 677 16.0 527 12.5 1733 41.0 97.6 97.8 2015 4.362 682 15.6 534 12.2 1807 41.4 51.2 53.5 osinovskaya: system aspects of fuel and energy balance formation international journal of energy economics and policy | vol 7 • issue 5 • 2017 273 the long-term forecast for the types of generating capacities is presented in table 3. this forecast shows that in the long-term perspective, for virtually all types of generating capacity, russia will continue to have a growth trend, and it will fit into world trends. a significant increase is projected for wind power generation (21.7%), as well as geothermal energy (11%). in russia, the use of geothermal sources is quite a promising direction, which is due to the low cost of energy produced by geothermal power plants. the economic potential of russia’s geothermal resources is 115 million tce/year, the use of which may amount to 10% in the total energy supply balance (alkhasov et al., 2016). thus, the development of the country’s energy within the framework of the forecast trends will lead directly to a change in the structure of the feb in the long-term period. the importance of the state of the fec for the economy of the country predetermines the urgency of comprehensive consideration and development of various aspects of forming the feb as the main tool that allows analyzing, forecasting and planning the development of energy. the identification and analysis of the current trends in the functioning of the components of the feb will allow to establish disproportions in the development of individual fuel and energy sectors, the need and priority of issues requiring state support. the forecasted febs compiled while taking into account the revealed tendencies and regularities will allow increasing the level of program-targeted development planning in the whole fec of the country and its components, individual energy consumption subsystems. in addition, a comprehensive work on the analysis of retrospective febs and prospective ones will create an early warning system at the state level to identify energy threats. it should be noted that the methodological aspects of table 2: the general results of the selection of res indicator 2014 2015 forecast total 2016 2017 2018 2019 results of the selection of solar power plants, megawatts (mw) quotas 120 140 200 255 285 270 1250 selected 35 140 199 250 270 270 1184.2 mw y = -5.2679x 2 + 72.304x + 38.5 r² = 0.9453 y = -12.161x 2 + 131.3x 81.1 r² = 0.9981 0 50 100 150 200 250 300 2014 2015 2016 2017 2018 2019 quotas: selected: results of the selection of wind power plants, mw quotas 51 50 200 400 500 1201 selected 51 50 90 191 results of the selection of small hydropower projects, mw quotas 18 26 124 124 141 159 592 selected 21 50 70.44 general results of selection of renewable energy projects, mw quotas 138 217 374 574 811 929 3043 selected 35 191 249 366 285 320 1445.64 mw osinovskaya: system aspects of fuel and energy balance formation international journal of energy economics and policy | vol 7 • issue 5 • 2017274 the analysis and the formation of forecasted febs are a rather complex issue, since it affects virtually all levels of management: from the fec to industries and the state with a sufficiently wide spatial coverage. the system vision and systematic approach to the formation of consolidated febs will make it possible to turn energy balances into an effective tool for managing the energy security of the country, and not as a tool for creating a statistical base that captures the values of indicators that reflect the correspondence between the arrival and consumption of fuel and energy resources, and also sources of their receipt and directions of use. 2. reviewing references currently, the role and importance of the feb seem to be increasing at federal and regional level. in this regard, both individual scientists and scientific society in general are starting to take an active part in solving various issues concerning the formation and use of the feb as an efficient means of systemic table 3: forecast by types of generating capacity before 2040, gigawatts (gw) region/country history projections average annual percent change, 2012-40 2011 2012 2020 2025 2030 2035 2040 world total installed generating capacity by region and country non-oecd europe and eurasia 411 418 462 468 480 494 499 0.6 russia 230 233 267 267 272 277 275 0.6 other 180 185 194 201 208 217 225 0.7 total non-oecd 2.587 2.748 3.628 3.946 4.271 4.627 4.988 2.2 total world 5.202 5.440 6.577 6.981 7.422 7.925 8.455 1.6 world installed liquids-fired generating capacity by region and country non-oecd europe and eurasia 20 21 20 19 18 17 17 −0.8 russia 3 3 4 4 4 3 3 −0.1 other 17 17 16 15 15 14 13 −0.1 total non-oecd 161 165 178 171 164 157 151 −0.3 total world 394 395 388 366 348 332 320 −0.8 world installed natural-gas-fired generating capacity by region and country non-oecd europe and eurasia 147 151 165 167 176 184 187 0.8 russia 107 109 118 113 116 119 117 0.3 other 40 42 47 54 59 65 70 1.8 total non-oecd 593 624 749 822 908 1.012 1.111 2.1 total world 1.370 1.423 1.597 1.717 1.870 2.052 2.252 1.7 world installed coal-fired generating capacity by region and country non-oecd europe and eurasia 111 110 112 109 110 112 111 0.0 russia 49 49 53 51 54 56 56 0.5 other 62 61 59 58 57 55 55 −0.4 total non-oecd 1.076 1.146 1.344 1.358 1.359 1.376 1.406 0.7 total world 1.715 1.782 1.947 1.947 1.936 1.946 1.970 0.4 world installed nuclear generating capacity by region and country non-oecd europe and eurasia 40 40 53 59 58 58 58 1.3 russia 24 24 33 38 34 33 32 1.1 other 17 17 20 21 24 25 26 1.6 total non-oecd 68 69 127 164 227 265 304 5.4 total world 369 373 414 461 532 570 602 1.7 world installed hydroelectric and other renewable generating capacity by region and country non-oecd europe and eurasia 92 95 112 114 117 124 127 1.0 russia 47 48 59 61 64 66 66 1.1 other 44 47 53 53 54 57 60 0.9 total non-oecd 690 745 1.230 1.431 1.613 1.818 2.017 3.6 total world 1.353 1.466 2.231 2.491 2.736 3.025 3.311 3.0 world installed wind-powered generating capacity by region and country non-oecd europe and eurasia 2 4 8 8 8 9 9 3.4 russia 0 0 4 4 4 4 4 21.7 other 2 3 4 4 4 5 5 1.1 total non-oecd 67 89 248 306 365 423 480 6.2 total world 220 269 569 656 750 867 961 4.7 world installed geothermal generating capacity by region and country non-oecd europe and eurasia 0 0 2 2 2 2 2 11 russia 0 0 2 2 2 2 2 11 other 0 0 0 0 0 0 0 total non-oecd 4 4 11 16 26 30 34 7.8 total world 10 10 22 28 41 46 52 5.9 table is based on the materials of international energy outlook 2016 with projections to 2040, may 2016, u.s. energy information administration office of energy analysis u.s. department of energy washington, dc 20585. for the formation of the table, the «h» application was used (appendix h contains summary tables of reference case studies for installed electric power capacity by fuel and regional electricity generation) osinovskaya: system aspects of fuel and energy balance formation international journal of energy economics and policy | vol 7 • issue 5 • 2017 275 management of the country’s fec and energy security. issues regarding the formation of a feb were studied already back in 1937 by a group of scientists including weitz et al. (1937). a significant contribution to the systemization of knowledge on the formation of the feb was made by s.d. feld. in his work, he presented a methodology for the formation of a unified energy balance (feld, 1964). some methodical issues regarding the accounting of nonconventional sources of hydrocarbons in the prospective feb are regarded in the work by alymov and ilyinsky (2012). the feb is regarded as a tool for analysis, forecasting and indicative planning of power industry development in works by bashmakov (2007). information assurance in the formation of the feb is presented in works by belova and litvak (2012). strategic aspects of power industry development and their interrelation with the feb are presented in a collective scientific work by bushuev et al. (2016). general issues of the systems and systemic research theory are considered in works by volkova and denisov (2006), voskoboynikov (2013). methodical basis for forecasting including the one based on the systemic approach which can be applied in feb forecasting is presented in works by andronova et al. (2008), makarov (2010) and lyubimova (2010). foreign literature quite often covers issues regarding the development of russia’s fec and its impact on the country’s energy security taking into account global trends (keun-wook, 2012; henderson, 2015). thus, for instance, in his work, j. henderson studies the key factors defining the prospects in oil extraction and export by russia, as well as analyzes the fundamentals of oil extraction in russia taking into account the current low oil prices (henderson, 2015). energy security issues are regarded in works by buchan (2014), buchan and keay (2016). 3. materials and methods 3.1. forecasting the feb based on the systemic approach taking into consideration the matter of the systemic approach and the increasing complexity of forecasting objects, including both fec subsystems and various constituents of the energy balance, as well as factors influencing its dynamic characteristics and intensity of their change, mobility, the author considers it reasonable to be based on the existing general power industry forecasting scheme used in russia when developing methodological aspects in feb forecasting. the retrospective analysis of the methodical base of feb formation has shown that it was based on the results of works by a.a. makarov and a.g. vigdorchik and involved the “normative” energy consumption calculation method with subsequent energy balancing of particular kinds of fuel and uniting them into a summary balance (makarov and vigdorchik, 1979). later, a method was developed to draw summary balance of primary energy resources and corresponding simulation models, which transferred report data in a unified feb form developed in assistance with domestic scientists from the energy research institute of the russian academy of sciences and united nations economic commission for europe (official website of energy research institute, 2017, https://www.eriras.ru/data/34). deploying systemic contours within feb forecasting will facilitate prompt tracking of various changes taking place in the country’s and regions’ economy at all levels, as well as the stability of their energy security. when fulfilling the objectives set by the analysis, forecasting, and planning, the author interprets a systemic contour as a multitude of subsystems and elements within the same contour interacting with each other and forming a particular unity. energy balance is a basic category in economic and energetic analysis which demonstrates a country’s capabilities to provide for external and internal demand and facilitates outlining general development trends for particular kinds of fuel, types of power industries and user sectors. it is one of the main tools which allow carrying out general analysis of resourcing, production, consumption, and external trade of energy carriers. the structure of energy balances regarding both the resources and sources of use is rather inert (markovich and salikhov, 2007). in this regard, it is reasonable to use the systemic approach and the term “system” because the formation of feb involves quite a great number of systems and subsystems of various levels which are interrelated and interinfluencing. the forecasting object is rather complex and not at all clear, but it definitely has all the attributes of integrity and unity. figure 2 presents an enlarged view of systemic contours forming during the achievement of various energy security management objectives based on the feb. practical use of the above mentioned approach based on the formation of systemic contours to achieve energy security management objectives through building energy balances both for the entire country and each region is not possible due to the absence of appropriate information assurance. 3.2. information assurance for fulfillment of methodological principles of feb formation based on systemic contours information assurance plays a key role in a country’s systemic energy security management through formation of feb. and it implies only not the formation of an information statistics field for each feb section, but also the creation of a unified centralized database. such an information system would allow accumulating all information necessary for the formation of feb both at regional and federal level, including information assurance for forecasting at all levels of systemic contours. several research works focus on the formation of a unified information system which would accumulate and systematize data necessary for building feb and monitoring it. in their works, s.d. korovkin, i.d. ratmanova, l.v. schavelev, i.a. levenets osinovskaya: system aspects of fuel and energy balance formation international journal of energy economics and policy | vol 7 • issue 5 • 2017276 consider an opportunity to create a corporate information and analysis system for a region’s feb aiming at arrangement and integration of information based on its sources and consumers of fuel and energy resources in order to improve fec management (korovkin et al., 2005). the author suggests forming an information and analysis system which would assure the formation, within each systemic contour, of an early warning system which allows responding to any changes promptly and thus ensure dynamic characteristics of feb constituents. information must comply with the following key requirements: reliability, topicality, sufficiency, and promptness. such a system is to be based on hundreds of indicators, which would cover various feb aspects and factors influencing it. building such a system is quite a complicated process, and it is hardly possible without ideological and financial support from the government. moreover, it is necessary to note that part of forecasts regarding feb formation are based on global trends in power industry, politics, development of global markets, etc. that is why the issue regarding the acquisition of authentic and reliable information obtained from global sources and necessary for such forecasts is rather topical at the moment. in his work, al-zayer a. fuad noted the importance of international cooperation in the formation of an information field within global power industry. international cooperation in this aspect focuses on improving the quality of data about the power industry, as well as satisfying the increasing need in such detailed information (al-zayer, 2017). 4. results during the research, the author attempted to emphasize the importance of using the feb as an active tool in a country’s energy security management and not as a tool to analyze the current situation. to make it happen, it is necessary to improve the quality aspect of feb formation through building a methodological basis aiming at forming systemic contours which would facilitate structuring different subsystems influencing the feb taking into account the spatial regional scope. according to experts, “the main issue in feb development is incompleteness and low quality of statistical information. it is necessary to develop a method which could be widely used. moreover, there is no coherent system for federal and territorial febs”. to develop coherent forecasting of febs at country and regional level, a unified social and economic bases is needed, i.e. forecasts regarding the social and economic development of the country and regions (interview “minenergo sees no need to build feb at municipal level”, 2016). in this regard, it is suggested to form an information and analysis system which would provide feb analysis, forecasting, and planning with necessary, topical, relevant, and authentic information. another result of the research was detecting the need to form an early warning system to prevent any deviations from forecast and target feb values in order to take prompt management actions to ensure stable energy security in the country. an early warning system implies analyzing the most current data about changes in global economy, global energetic system, industry and markets based on the main economic and industry indicators which allow forecasting crucial moments in the global energy market. figure 2: enlarged representation of systemic contours: subsystem. 1 – fossil fuels; subsystem; 2 – non-fossil fuels; subsystem 3 – nuclear power industry; subsystem n – other subsystems outlined within the feb analysis, forecasting, and planning, e.g., based on fec branches; sta – science and technology advance osinovskaya: system aspects of fuel and energy balance formation international journal of energy economics and policy | vol 7 • issue 5 • 2017 277 5. discussion issues regarding the formation of forecast febs have been discussed rather actively lately – in the scientific world, at federal level, by industry analysts and experts. publications by i.a. bashmakov, executive director at the center for energy efficiency (cenef) emphasizes the necessity and possibility to use a unified region’s feb being the main tool of development and monitoring of energy efficiency improvement programs (bashmakov, 2012). scientific and practical works related to the formation of forecast feb, forecasting of energy consumption and research of a country’s energy efficiency have been performed at the energy research institute (eri) since it was founded, and have always been among top priority objectives (official website of energy research institute, 2017). however, a number of publications note that insufficient attention is paid to the issues related to the formation of a unified forecast feb by the state. it is not obligatory to build feb at regional level, and it is to be used only as an information basis to assess the current situation in the retrospective period for groups of particular kinds of energy resources in order to form single-product balances. recently, this topic has been developed by the associate members of the russian academy of sciences s.p. filippov, a.n. kurashev and e.v. mokhina, and has been involved in the solution of various practical objectives. the most important among them were the preparation of supporting materials for the preparation of the energy strategy of russia for the period up to 2030, the formation of feb of subjects of the russian federation complying with the country’s feb, and the analysis of the energy efficiency trends in the russian economy and its particular sectors (filippov, 2010). here, one should mention that, in order to achieve the latter objective, it was necessary to build feb at global level. but it is still an occasional need in feb which is spatially limited (a certain number of regions taking part in the scientific project). 6. conclusion in conclusion, one should mention that the above mentioned suggestions on the development of methodological aspects of feb formation are presented only briefly, without detailed explanation of aspects such as the systemic contours formation algorithm, which systems and subsystems will represent each contour, which set of indicators will characterize each system (subsystem), etc. although long-term forecasting issues are mentioned, the article hardly regards methodical issues concerning the formation of these forecasts. the formation of an early warning system for feb monitoring has been mentioned just superficially. the author intends to discuss this and reveal it within subsequent research of the formation of high-quality febs with their corresponding characteristics. at the same time, the goal of this article stated by the author, aiming at covering the trends in the development of methodological aspects of feb formations has been achieved. an integral system of formation of a unified feb with highquality information and analysis assurance will facilitate prompt development of fec branches and, thus, ensure energy security in the country. and both scientific research and practical use of the obtained results must be supported both at regional and federal level through the creation of a corresponding updated normative base, as well as provision of grants for such research. it is reasonable to agree with s.v. alymov who notes that methodological principles of feb formation, besides the general system requirements, must also ensure: • interaction of the feb with investment programs; • possible diversification of fuel and energy within the balance structure; • harmonization of the rates at which conventional resources are replaced by alternative ones; • accounting of regional aspects of balance formation, accounting of technological capabilities and innovation constituent of the feb, etc. (alymov, 2012). references alkhasov, a.b., alkhasova, d.a., aliev, r.m., ramazanov, a.s.h. (2016), kompleksnoe osvoenie geotermalnykh resursov [comprehensive development of geothermal resources]. south of russia: ecology, development, 11(1), 149-158. alymov, s.v. (2012), methody prognozirovaniya toplivnoenergeticheskogo balansa strany s uchetom netraditsionnykh istochnikov uglevodorodnogo syrya [methods of forecasting country’s fuel and energy balance taking into account nonconventional sources of hydrocarbons]. saint petersburg: author’s abstract from dissertation in support of candidature for ph.d. degree in economics. available from: http://www.engec.unecon.ru/ sites/default/files/avtoref/avtoreferat_alymov_s.v.pdf. [last accessed on 2014 sep 25]. alymov, s.v., ilyinsky, a.a. (2012), metodicheskie voprosy ucheta netraditsionnykh istochnikov uglevodorodov v perspektivnom toplivno-energeticheskom balanse [methodical issues regarding accounting of non-conventional sources of hydrocarbons in prospective fuel and energy balance]. gas industry, 5, 14. al-zayer, f.a. (2017), better data better decisions. the joint organizations data initiative (jodi): increasing energy data transparency through international cooperation. available from: http://www.unece.org/fileadmin/dam/energy/se/pp/unfc_egrc/ egrc8_apr_2017/28_april/6-fuad-al-zayer.pdf. [last accessed on 2017 may 10]. andronova, i.v., plenkina, v.v., osinovskaya, i.v. (2008), prognozirovanie sotsialno-ekonomicheskikh yavleniy [forecasting social and economic phenomena]. tyumen: tsogu (tyumen state oil and gas university). p216. bashmakov, i.a. (2007), toplivno-energeticheskii balans kak instrument analiza, prognoza i indikativnogo planirovaniya razvitiya energetiki [fuel and energy balance as a tool for analysis, forecasting, and indicative planning of power industry development]. energy policy, 2, 16-25. bashmakov, i.a. (2012), energeticheskie balansy rf i subyektov rf kak osnova razrabotki i monitoringa programm povysheniya energoeffektivnosti [energy balances of the rf and rf subjects as basis for development and monitoring of energy efficiency improvement programs]. energy council, 4(23). available from: http://www.energosovet.ru/bul_stat.php?idd=310. [last accessed osinovskaya: system aspects of fuel and energy balance formation international journal of energy economics and policy | vol 7 • issue 5 • 2017278 on 2016 mar 27]. belova, o.v., litvak, v.v. (2012), razrabotka modeli toplivnoenergeticheskogo balansa obyekta [developing a fuel and energy balance model of an object]. power industry: efficiency, reliability, security, 2012, 315-317. buchan, d. (2014), europe’s energy security caught between shortterm needs and long-term goals. available from: https://www. oxfordenergy.org/publications/europes-energy-security-caughtbetween-short-term-needs-and-long-term-goals. [last accessed on 2016 nov 16]. buchan, d., keay, м. (2016), europe’s long energy journey towards an energy union. oxford: oxford university press. p256. bushuev, v.v., gromov, a.i., belogoryev, a.m., mastepanov, a.m. (2016), energetika rossii: poststrategicheskii vzglyad na 50 let vpered [power industry of russia: post-strategic outlook 50 years from now]. moscow: iac energiya. p96. eder, l.v., filimonova, i.v., provornaya, i.v., mamaxatov, t.m. (2016), osobennosti razvitiya neftyanoy promyshlennosti rossii na sovremennom etape [current peculiarities of development of oil industry in russia]. drilling and oil, 12. available from: http://www. burneft.ru/archive/issues/2016-12/3. [last accessed on 2016 jul 01]. energy research institute of the russian academy of sciences. (2017), available from: https://www.eriras.ru/data/25/rus. [last accessed on 2017 feb 15]. fec results for 2016. (2017). available from: http://www.ruscable. ru/news/2017/04/07/itogi_tek_za_2016_god. [last accessed on 2017 may 11]. feld, s.d. (1964), edinyi energeticheskiy balans narodnogo khozyaystva [unified energy balance in national economy]. moscow: publisher ekonomika. p312. filippov, s.p. (2010), prognozirovanie energopotrebleniya s ispolzovaniem kompleksa adaptivnykh imitacionnykh modeley [forecasting energy consumption using a complex of adaptive simulation models]. bulletin of the russian academy of sciences. power industry, 4, 8. henderson, j. (2015), key determinants for the future of russian oil production and exports. oxford institute for energy studies. available from: https://www.oxfordenergy.org/publications/keydeterminants-for-the-future-of-russian-oil-production-and-exports. [last accessed on 2016 oct 12]. keun-wook, p. (2012), sino-russian oil and gas cooperation the reality and implications. oxford: published by the oxford university press for the oxford institute for energy studies. p498. korovkin, s.d., ratmanova, i.d., schavelev, l.v., levenets, i.a (2005), sistema vedeniya toplivno-energeticheskogo balansa kak sreda dlya podderzhki prinyatiya resheniy po upravleniyu toplivnoenergeticheskim kompleksom regiona [fuel and energy balance management system as a medium used to maintain decisionmaking when managing region’s fuel and energy balance]. news bulletin of ivanovo state power engineering university, 4. available from: http://www.ispu.ru/files/60-63.pdf. [last accessed on 2016 jul 10]. lyubimova, e.v. (2010), otrazhenie mnozhestvennosti metodik postroeniya energeticheskogo balansa pri energeticheskikh issledovaniyakh (na primere irkutskoy oblasti) [presenting a multitude of methods of building an energy balance in energy research (based on the irkutsk oblast)]. news bulletin of novosibirsk state university. series: social and economic sciences, 10(2). available from: http://www.nsu.ru:8080/rs/mw/link/media:/22715/14.pdf. [last accessed on 2015 mar 17]. makarov, a.a. (2010), metody i rezultaty prognozirovaniya razvitiya energetiki rossii [methods and results of forecasting power industry development in russia]. bulletin of the russian academy of sciences]. power industry, 4, 12. makarov, a.a., vigdorchik, a.g. (1979), toplivno-energeticheskij kompleks. metody issledovaniya optimalnyx napravlenij razvitiya [fuel and energy complex. research methods finding optimal ways of development]. moscow: nauka. p279. markovich, l.g., salikhov, m.r. (2007), energeticheskiy balans rossii: analiz i otsenka [russia’s energy balance: analysis and assessment]. economic survey, 3. available from: http://www.perspektivy.info/ history/energeticheskij_balans_rossii_analiz_i_ocenka_2007-08-31. htm. [last accessed on 2016 dec 17]. minenergo ne vidit neobkhodimosti formirovaniya teb na urovne munitsipalitetov [minenergo sees no need to build feb at municipal level]. (2016), analytical center for the government of the russian federation. available from: http://www.ac.gov.ru/ events/010601.html. [last accessed on 2017 jul 01]. razvitie alternativnoy energetiki v rossii (development of alternative power industry in russia). (2016), report by the national rating agency. available from: http://www.ra-national.ru. [last accessed on 2016 jun 22]. volkova, v.n., denisov, a.a. (2006), systems theory. moscow: higher school. voskoboynikov, a.e. (2013), sistemnye issledovaniya: bazovye ponyatiya, printsipy i metodologiya [systemic research: basic terms, principles, and methodology]. knowledge. skill, 6. available from: http://www.zpu-journal.ru/e-zpu/2013/6/voskoboinikov_systemsresearch. [last accessed on 2017 jun 05]. weitz, v.i., probst, a.e., rusakovsky, e.a. (1937), problema edinogo energeticheskogo balansa narodnogo khozyaystva v tretey pyatiletke [issue regarding the energy balance in national economy in the 35 year plan]. planned economy, 34, 9-10. . international journal of energy economics and policy | vol 7 • issue 2 • 2017 243 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(2), 243-249. the re-analysis of the relationship between government’s income and expenditure in an oil-based economy with tvpfavar approach (iran as the case of study) jaber akbari1*, sadegh bakhtiari2, morteza sameti3, homayoun ranjbar4 1department of economics, isfahan (khorasgan) branch, islamic azad university, isfahan, iran, 2department of economics, isfahan (khorasgan) branch, islamic azad university, isfahan, iran, 3department of economics, isfahan (khorasgan) branch, islamic azad university, isfahan, iran, 4department of economics, isfahan (khorasgan) branch, islamic azad university, isfahan, iran. *email: akbari.economy@yahoo.com abstract oil incomes play important roles in the budget structure and government expenditures of oil-dependent economies. the existence of such an economic structure has made the causal relationship between government’s incomes and expenditures a debatable issue for economic decision-makers. in the previous studies, the relationship between the two variables of iran’s incomes and expenditures was considered linearly, while the nature of these two variables is non-linear. due to the limitations of econometric techniques, the non-linear investigation of these variables has not been carried out thus far. models with changeable parameters over time have solved this problem. so in the present study by applying tvp favar method in matlab software and employing seasonal data from 1989 to 2015, attempt has been made to accurately explore the relationship between government’s incomes and expenditures. the results of the study demonstrated that the coefficients of income expenditure over time have a non-linear fluctuation mode. therefore, simultaneous fiscal policy hypothesis is confirmed for iran. keywords: oil shocks, income-expenditure relationship, government, tvp-favar jel classifications: c13, c18, h50, h20 1. introduction iran, as a member of opec, both affects and is affected by world oil markets. transient increases in oil incomes caused government’s expenditures to increase and remain at a higher level. even with lowering prices and oil incomes, government’s expenditures are resistant to reduction. unexpected changes in oil prices on the international volatile markets have always influenced economic planning (due to the dependence of budget on oil and the high proportion of government in the economy). given such economic structures as well as limitations of econometric techniques, the causal relationship between government incomes and expenditures have remained a debatable issue for economic decision-makers, since in the previous studies the relationship between the two variables of income and expenditure was considered to be linear. that is, a coefficient for the entire period is estimated and based on that coefficient, causality has been determined. but the nature of these two variables’ relationship is non-linear i.e., the ratio between these two variables can be changed at any time. however, due to limitations of econometric techniques, studying this issue nonlinearly has not been done yet. models with changeable parameters over time solved this problem. so in this paper, by employing tvpfavar method, an accurate exploration of government’s income-expenditure relationship has been carried out. in fact, it is of importance for policy makers to understand the relationship between government’s income and expenditure, to prevent continual budget deficit. if the presumed income expenditure hypothesis for iran holds true; implementing policies to stimulate government income can offset the budget deficit. accordingly, this research study aims to identify the relationship between government’s incomes and expenditures by using tvpfavar patterns. this study is written in five sections. following the introduction which was just discussed, in the akbari, et al.: the re-analysis of the relationship between government’s income and expenditure in an oil-based economy with tvpfavar approach (iran as the case of study) international journal of energy economics and policy | vol 7 • issue 2 • 2017244 second part, the literature of the study which includes theoretical foundations, principles and empirical literature and innovation, will be reviewed. and the third part introduces the model and its analysis. finally in the fourth section, conclusions and political recommendations are presented. 2. literature review 2.1. theoretical foundations overall, four main hypotheses about the relationship between income and expenditure exist: • the first hypothesis income-expenditure hypothesis: according to this hypothesis, there is a one-way relation from the expenditure to the income. this view is based on the effect of exogenous shocks, such as war, sanctions and tense economic situation, atmosphere of political instability and natural disasters, on increasing government expenditures and consequently raising taxes as a source of government income. according to this hypothesis, the government spends at first and then decides how to meet the costs through higher taxes, if necessary. if the permanent or temporary increases in government expenditures sooner or later lead to higher taxes, a causal relationship will be established between the incomes and the expenditures of the government. people like peacock and wiseman (1961) confirm this theory and believe that certain situations such as political or economic crises that lead to an increase in government’s expenditures will eventually force the government to raise taxes. according to this hypothesis, to deal with budget deficit, the government must reduce its expenditures, especially in the absence of crises. this assumption is in line with the barro’s tax smoothing theory and ricardian equivalence framework. this means that from a rational tax payer’s point of view increasing the expenditures at present time (with no fiscal illusion) is equal raising taxes in the next period (saunoris and payne, 2010). in economy literature, the income-expenditure hypothesis is presented in the form of two models by carneiro et al. (2004) and hoover and shefrin (1995). carneiro et al. (2004) express the income-expenditure hypothesis in a simple hypothetical economic model for a poor mono-product country. the assumptions of this model are as follows: • the economy in this country has a major part which is the agricultural part specializing in producing (y) and exports x amount of this product. therefore, it can be written: αy = x where 0<α<1. without the reduction of generality, it is assumed that the; a = 1. • in view of the fact that the hypothetical economy of this poor country lacks the financial market, it can be assumed that investment with respect to inelastic interest rates and savings is an ascending function of the production level. in other words, can be written: i=i s=s(y) . the amount of the exports of the product depends on the global price (p) (which reflects the supply and demand shocks), foreign income level (yf) and exchange rate (π): x = x(p, yf, π). • the amount of imports (z) is an ascending function of domestic income (y) and descending function of the exchange rate: z = z(y, π). • in this economy, fixed exchange rate system applied by the central bank, thus: =π π . • the objective of monetary policy by the central bank is to provide price stability and reduce inflation. to achieve these objectives, the central bank uses fixed interest rate and credit control policies. in the other words: r=r v= y m . where, r is the rate of interest, and v is the velocity of money. therefore, money market equilibrium can specify price level: m p =l(y,r) . it is assumed that government has two major income sources: taxes on exports and imports. therefore, government income can be written as follows: t = t(x)+t(z). due to the lack of transparency, poor governance, corruption, mismanagement and inelastic demand for public services, government expenditure in a poor country with a weak economy, is always above the level needed to balance short-term funding ( g ). based on this assumption we can write: g>g . the mentioned model specifies the equilibrium level of endogenous variables g, r, m, i, x, y, z, s, p, t. this pattern is a reversal pattern and is solved by placing the equations in each other. the important point is that government expenditures are specified prior to the incomes of government. in other words, the level of government expenditures determines the level of its incomes. we can conclude that government expenditure is a granger cause for government incomes. therefore, this model is as a special explanation for income-expenditure hypothesis. • the second hypothesis government income-expenditure hypothesis: the hypothesis that has been emphasized by friedman and wagner states that there is a one-way relationship between government’s incomes and expenditures. that’s to say, the increase in government’s incomes leads to an increase in expenditures and consequently imbalances the budget. according to this hypothesis, governments adjust their expenditures with their income level. according to the traditional beliefs that prevailed in the eighties which were accepted by many economic policy makers, such a policy will not necessarily reduce the budget deficit, as the control of income level will limit the growth of government expenditure (hoover and shefrin, 1992). friedman argues that the government should cut taxes to reduce the deficit, as controlling the tax level will limit the growth of government’s expenditures. this hypothesis has been confirmed by many economists. friedman believes in the positive causal relationship between government’s incomes and expenditures, but buchanan and wagner (1977) believe that while cutting taxes, this relationship is negative (saunoris and payne, 2010). akbari, et al.: the re-analysis of the relationship between government’s income and expenditure in an oil-based economy with tvpfavar approach (iran as the case of study) international journal of energy economics and policy | vol 7 • issue 2 • 2017 245 income-expenditure hypothesis can be expressed in the following mathematical model: g =f(r ) g =f( r ) t t j t t j − −∆ ∆ where, gt and rt are government expenditures and incomes respectively. according to freedman’s (increasing government incomes will influence government expenditures) ′f >0, while based on buchanan and wagner ′f >0 (by increasing government incomes, government’s expenditures will be reduced). • the third hypothesis simultaneous fiscal policy hypothesis: this hypothesis suggests a two-way causality between government incomes and expenditures i.e., government taxes and government expenditures may change at the same time. another hypothesis which is presented by musgrave et al. (1981) is simultaneous fiscal decisions hypothesis. according to this hypothesis, the government decides on incomes and expenditures simultaneously, and a causal two-way relationship exists between government’s incomes and expenditures. here, the optimal amount of incomes and expenditures is specified on the basis of the equality of the benefits and final expenditures of government programs (aslan and tasdemir, 2009). to evaluate the hypothesis of simultaneity, hoover and shefrin (1992) offered the mutual cost-benefit model that will be explained in the following. suppose that the level of welfare with the state of tax decreased rapidly, but due to increased government expenditures, welfare increases with a decreasing rate. the ultimate benefits and ultimate tax expenditures are variable. taxes and expenditures route will be chosen in a way that the expected welfare be at maximum level. thus, the equation of maximizing the expected welfare can be written: 2 2 2 0 1 1 1 1 1 1 1 1 1 max e ( g bg )-( t + et ) b 2 2 2 t , g   ε − η −    in which b1 = r(b0+g1−t1) and the amount of b0 is known, ε and η variables are white noise random shocks with a mean value of ε and η the amount of which can be assumed zero in long-term time series. levels of expenditures and taxes are determined from the equality of the expected ultimate costs and expected ultimate benefits. therefore, the first conditions are: ε η − − − − − b(g ) r (b +g t )=0 +e(t )+r (b +g t )=0 1 2 0 1 1 1 2 0 1 1 according to the above, it is clear that there is a two-way causal relation between the t and g. • the fourth hypothesis the neutral fiscal policy hypothesis. according to this hypothesis, none of the three above-mentioned assumptions explains the relationship between government’s incomes and expenditures. and this relationship is determined by long-term economic growth. in fact, this assumption implicitly represents the institutional separation between government’s incomes and expenditures. the fourth hypothesis states that if decisions about incomes and expenditures are to be made by two separate entities, there is no causal relationship between government’s incomes and expenditures. this hypothesis is confirmed in several studies (baghestani and mcnown, 1994; wildavsky, 1988). this assumption has been examined in the form of fixed-share pattern by hoover and shefrin (1992). based on the assumption of this model, government considers expenditure and tax rates as a fixed share of gdp and there is no need to coordinate the given share. for example, suppose: g= y+ t=by+ α ε η . where y is gdp and ε and η are white noise random shocks. by dividing these two equations by y we have: g = + y t =b+ y α ε′ η′ . according to the above equations, there is no causal relationship between the g and t. this is because intervention in expenditure system is applied through changes in the share of production costs (a) will have no effect on t/y, as the intervention in the fiscal system which is applied through b will not affect g/y either (saunoris and payne, 2010). due to heavy dependence of incomes and expenditures on oil, the above hypotheses are considerable of investigation. 2.2. empirical backgrounds and previous studies among the previous studies on the relationship between government’s income and expenditure, the following ones are worth mentioning. in a study entitled “the causality and integration test between government’s income and expenditure: considering structural breaks,” mehrara and rezaee (2015) analyzed the granger causality relationship between the incomes and expenditures of the government on the 1979-2012 data. they utilized lütkepohl and hausman test and found that the long term relation between the variables of the pattern indicate that there is a causal long term unidirectional relation between iran government incomes and their expenditures. komeijani and nazari (2015) in a study entitled “investigating the effect of oil incomes on the expenditures of iran government through auto regressive patterns with distribution lags” explored the effect of oil incomes on the expenditures by iran government from 1975 to 2012. they utilized the auto-regression model with distribution lags and showed that both in short and in long term oil incomes have a positive effect on government expenditure. this finding also proved the assumption of income-expenditure relation in line with friedman’s theory. ebaidalla (2013) in a study entitled “the causality between government expenditures and national income, evidence from sudan” examined the causality between the income and akbari, et al.: the re-analysis of the relationship between government’s income and expenditure in an oil-based economy with tvpfavar approach (iran as the case of study) international journal of energy economics and policy | vol 7 • issue 2 • 2017246 expenditures of sudan government using the annual data of 19702008. he used error correction method and granger causality and concluded that in the short and in the long run the direction of causality is from expenditure towards income. saysvmbat and kkoilovang (2013) in their study which was entitled “the causality relation between income and expenditure in laos” investigated the causal relation between the incomes and expenditures of laos’s government from 1980 to 2010. they employed vector error correction model and showed that there is a long term unidirectional causal relation between government’s income and expenditures. the direction of this causal relation was from expenditures towards the incomes which is in line with the assumption of expenditure-income but in the short run there is no causality. these findings justifies the expenditure-tax policy of laos. elyasi and rahimi study (2011) which is entitled “the causality between incomes and expenditures in iran’s government) analyzed the causality between government’s incomes and expenditures from 1963 to 2007. they used error correction model. utilizing granger causality test, they concluded that the causality is from expenditures towards incomes. they consider external troubles such as natural disasters and political conditions as the causes of this phenomenon and suggested a reduction in government expenditures to compensate for budget deficit. overall, in the previous studies the relation between income and expenditure variables is considered to be linear which generally shows as causal unidirectional relationship. however, due to coefficient changes, in practice the relation between these two variables is nonlinear i.e., the coefficient of these two variables can change annually. this can shed some doubts on the findings of the previous studies. therefore, in the present study this relation will be reanalyzed using the model with changeable parameters over time. 3. research methodology and the theoretical backgrounds of the prediction method as for the scientific essence and target, the present study is applied research. the nature of our data is seasonal time series and as a result the utilized patterns are time series pattern and are presented in the tvp and tvpfavar econometrics formats. the sample of this study consists of the seasonal data of iran from 1989 to 2015 and are taken from the central bank of the islamic republic of iran. in what follows the theoretical backgrounds of tvp and tvpfavar will be discussed. according to stock and watson (2008), the main shortcoming of the previous calculation methods was that they could not make the right predictions in the course of time and some models could make proper predictions at boom times and some others at recession times. it resulted in the appearance of models with changeable parameters over time and markov chain monte carlo models (mcmc) which could predict sizable models with la large number of variables in the course of time. in these model the stimulation coefficient could change through time. due to changes in circumstances, structural breakdowns and cycle shifts, the previous models were not sufficient for analyzing parameters under such conditions. in addition, the number of variables and predictors can be many. the increase in the number of variables will lead to the creation of big models. in such models, whenever there are m variables in the t time period, there will be 2mt prediction models (koop and korobilis, 2011; khezri, 2015). many studies have been carried out in the format of structural models using tvp methods. following these methods, favar models became frequent in identifying factors affecting dependent variables in different time periods in a way that the combination of tvp and tvp favar models provided economic and political analysts with powerful tools. the general structure of tvpfavar model in korobilis (2009) studies is as follows. yit = λ0it+λitft+γitrt+εit t pt t 1 f 1t pt t t t 1 t p ff f = + + + r r r −− − −      φ φ ε          …   it assumes that each εit follows the incidental fluctuations of a variable and f ft tvar ( )=ε ∑   possesses a multivariable-fluctuation process like what was discussed in premieri (2005). finally the 0it it it 1t pt, , , ,λ λ γ φ φ  coefficients are allowed to promote in accordance with the incidental step for i = 1,…m. all the other assumptions are similar to the assumptions of favar. in a nutshell, similar to many models utilized in applied macro economy, the bayesian inference in tvp_favar proceeds by having an mcmc algorithm which includes blocks of different samples and similar algorithms. suppose that xt for t = 1,…, t is a n×1 vector of variables for predicting unobservable variables in the model. in addition, yt will be a s×1 vectro in the model which is comprised of the growth of growth domestic product, the growth of monetary units, the relationship between the government’s income and expenditure, interest and exchange rates. the tvp favar model is as follows: y f t t t t t t t pt t 1 t t,1 t,p t t t 1 t p x = y + f +u yy y =c +b +…+b + f f f −− − − λ λ      ε            in the above equation, λ t y is the regression coefficients, λ t f is the loading factor and ft is the factor. (bt,1,…bt,p) are var coefficients. ut and εt are the distribution errors with a normal distribution of zero average and qt and vt covariances. according to the assumptions of the literature of the models’ factors, it is assumed that vt is diametric. loading coefficients λ λ λ t t f ' t y ' ' = ,( ) ( )   and model coefficients βt = var. akbari, et al.: the re-analysis of the relationship between government’s income and expenditure in an oil-based economy with tvpfavar approach (iran as the case of study) international journal of energy economics and policy | vol 7 • issue 2 • 2017 247 c ,vec , vec ' t ' t,1 ' t,p β … β( ) ( )( ) are extracted in line with a fluctuation step process per time: λt=λt−1+vt βt=βt−1+ηt where there are ηt~n (0,rt) and vt~n (0,wt). equation 18 is called tvp-favar model. all the errors in the above function uncorrelated with each other and with time. therefore, they have a structure which is as follows: t t t t t t t t u v 0 0 0 =n 0 , 0 q 0 0 00 0 w r0 0 0                ε     υ         η     4. model estimation 4.1. the analysis of data durability in this section, the durability of the analyzed data is analyzed through augmented dickey fuller test in tables 1 and 2. before going to the results of augmented dickey fuller test, the timeseries nature of the data is demonstrated. table 3 shows that the variables of government income and expenditure are both durable. since the analyzed variables are at a durable level, there is no need to consider the long term relationship between these variables. in what follows, the var model is calculated and the optimum pause is determined. before considering var model, the optimum pause is identified and finally the causality between the income and the expenditure of the government is investigated. according to the information indices, in the present study the optimum pause is determined to be 6 (table 1). in the following granger causality test will be used to show the granger relation among the variables of the present study. the results of this test are presented in table 2. based on the results of table 2 which reveals that the granger causality relation holds between the variables of income and expenditure, it can be inferred that in each equation the significance level is below 5%. therefore, it can be said that there is a twoway relationship between the variables of this study and the two variables of this study are capable of being analyzed in a var equation. but since in a var equation, the possibility of coefficient estimation is equal to the number of optimum pauses, it is not possible to estimate all the coefficients for all time periods. consequently, tvp model will be employed to help reaching this goal. 4.2. calculating the relation between income and expenditure through time according to the explanations presented in the previous sections, ordinary least squares and the vector regression itself is not capable of calculating the relation between the government income and expenditure because these models are linear and can estimate only one coefficient in the whole period while determining the incomeexpenditure relations requires the use of estimation coefficients in each period. the tvp model provides us with such a capability (non-linear model). since tvpfavar models are among the nonstructural models, in modeling this method only the theoretical backgrounds which are related will be used and it is not possible to identify how the variables of the study are related to each other. therefore, the modeling of tvp is generally as follows: tc tr =c +b tc tr + +b tr tc t t t t,1 t 1 t 1 t,p t p t p                 − − − − …    + t ε as the above equation shows, in tvp method, in each period the coefficients between tr and tc can be calculated. the estimation of the coefficients through time makes it possible to calculate the income-expenditure relations according to these coefficients. the flow of these coefficients is displayed in figure 1. according to figure 1, the coefficients of the income-expenditure relations are fluctuating and nonlinear through time in a way that in most time periods the relationship between the two variables is positive. in other words, in most time periods the government has more expenditures than its incomes. at the beginning of the period the slope of the figure is ascending but at the end it is descending. therefore, the assumption of the simultaneity of fiscal policy and the existence of a two way relation between the variables of income and expenditure is proved. table 1: the optimal lag of the model (var lag order selection criteria) lag logl lr fpe aic sc hq 0 −1091.931 na 10884744 21.87863 21.93073 21.89971 1 −982.6717 211.9636 1326051 19.77343 19.92974 19.83670 2 −973.2281 17.94276 1189419 19.66456 19.92508* 19.77000 3 −967.4601 10.72860 1148430 19.62920 19.99393 19.77681 4 −966.9179 0.986847 1231298 19.69836 20.16729 19.88814 5 −958.2448 15.43796 1122345 19.60490 20.17803 19.83686 6 −948.6579 16.68136* 1004864* 19.49316* 20.17050 19.76729* 7 −946.7234 3.288543 1048925 19.53447 20.31602 19.85078 8 −942.5475 6.932053 1047443 19.53095 20.41671 19.88943 lr: sequential modified lr test statistic (each test at 5% level), fpe: final prediction error, aic: akaike information criterion, sc: schwarz information criterion, hq: hannan-quinn information criterion, *according to the index (lr), is significant at 95% confidence level. akbari, et al.: the re-analysis of the relationship between government’s income and expenditure in an oil-based economy with tvpfavar approach (iran as the case of study) international journal of energy economics and policy | vol 7 • issue 2 • 2017248 5. conclusion in the previous studies the relationship between the variable of income and expenditure in iran’s government has been assumed to be linear. it means that the estimation has been carried out for the whole period and the causality has not been identified. based on the nature of these two variables, the relation them is nonlinear i.e., the relation between these variables is changeable in the course of time. however, due to the limitation of econometrics methods, this issue has not been examined non-linearly by far. the models with changeable parameters over time have solved this problem. therefore, in the present study tvp favar model was used to examine the seasonal data from 1989 to 2015. in order to fathom the exact relationship which exists between government incomes and expenditures. according to the outcome of the model, the coefficient of the relation between income and expenditure is fluctuating in a way that in most time periods the relationship between income and expenditure is positive. in other words, in most time periods the government has more expenditures than its incomes and the bidirectional relation between government incomes and expenditures is proved. the assumption of the simultaneity of fiscal policy is therefore proved. it means that there is a causal relation between government’s incomes and expenditures. that’s to say that government expenditures change synchronously and the change in each variable will cause a change in another variable. hence, economic policy makers can make use of this relation between government’s income and expenditures to prevent the continuous budget deficits, the policies of resource and consumption management should be established simultaneously and that control unidirectional policies are not compatible with the behavior of the examined variables in particular and the economic structure of iran (as an oil-dependent economy) in general. references aslan, m., tasdemir, m. (2009), is fiscal synchronization hypothesis relevant for turkey? evidence from cointegration and causality tests table 2: granger causality between income-expenditure variables var granger causality/block exogeneity wald tests dependent variable: pay excluded chi-square df p tr 22.74821 6 0.0009 all 22.74821 6 0.0009 dependent variable: tr excluded chi-square df p pay 17.70747 6 0.0070 all 17.70747 6 0.0070 table 3: the results of augmented dickey-fuller test statistic variable name status statistical amount critical amounts at 1% level at 5% level at 10% level pay with the intercept and slope −4.71 −4.04 −3.45 −3.15 tr with the intercept and slope −4.96 −4.04 −3.45 −3.15 figure 1: coefficient changes in income-expenditure relations through time in tvp method akbari, et al.: the re-analysis of the relationship between government’s income and expenditure in an oil-based economy with tvpfavar approach (iran as the case of study) international journal of energy economics and policy | vol 7 • issue 2 • 2017 249 with endogenous structural breaks. journal of money, investment and banking, 12, 14-25. baghestani, h., mcnown, r. (1994), do revenue or expenditures respond to budgetary disequilibria? southern economic journal, 61(2), 311-322. buchanan, j.m. (1967), the fiscal illusion. public finance in democratic process: fiscal institutions and individual choice. chapel hill: university of north carolina press. buchanan, j., wagner, r. (1977), democracy in deficit: the political legacy of lord keynes. new york: academic press. carneiro, f.g., faria, j.r., barry, b.s. (2004), government revenues and expenditure in guinea-bissau. africa regions working paper, no. 65. ebaidalla, e.m. (2013), causality between government expenditure and national income: evidence from sudan. journal of economic cooperation and development, 34(4), 61-76. elyasi, y., rahimi, m. (2011), the causality between revenue and government expenditure in iran. energy policy, 36, 1164-1168. hoover, d., shefrin, s.m. (1992), causation, spending, and taxes: sand in the sandbox or tax collector for the welfare state? american economic review, 82(1), 225-248. khezri, m. (2015), the analysis of the dynamics of inflation in iran’s economy and inflation modeling using dynamic models. p.h.d. thesis, tarbiat modarres university of iran. komeijani, a., nazari, m. (2015), investigating the effect of oil incomes on the expenditures of iran government through auto regressive patterns with distribution lags. the bimonthly of iran’s economy empirical studies, 5(2), 55-90. koop, g., korobilis, d. (2011), forecasting inflation using dynamic model averaging. international economic review, 53, 867-886. korobilis, d. (2009), assessing the transmission of monetary policy shocks using dynamic factor models. working paper, series 35-09, rimini centre for economic analysis. mehrara, m., rezaee, a. (2015), a test on the long term relations between the incomes and expenditures of the government: a focus on structural break. journal of parliament and strategy, the 22nd year, 82(1), 337-387. musgrave, r. (1966), principles of budget determination. in: cameron, h., henderson, w., editors. public finance selected reading. new york: random house. p15-27. peacock, a.t., wiseman, j. (1961), the growth of public expenditure in the united kingdom. london: oxford university press. primiceri, g.e. (2005), time varying structural vector auto regressions and monetary policy. review of economic studies, 72(3), 821-852. saunoris, j.w., payne, j.e. (2010), tax more or spend less? asymmetries in the uk revenue-expenditure nexus. journal of policy modeling, 32(4), 478-487. saysombath, p.h., kyophilavong, t.h. (2013), the casual link between spending and revenue: the lao pdr. international journal of economic and finance, 5(1), 111-117. stock, j., watson, m. (2008), phillips curve inflation forecasts. working paper, no. 14322. wildavsky, a.b. (1988), searching for safety. ohio: bowling green state university, social philosophy & policy center. p253. . international journal of energy economics and policy | vol 7 • issue 2 • 2017 1 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(2), 1-8. assessment of energy poverty in new european union member states: the case of bulgaria, croatia and romania nela vlahinić lenz1, ivana grgurev2 1university of rijeka, faculty of economics, rijeka, croatia, 2energy institute hrvoje požar, zagreb, croatia. *email: nela.vlahinic.lenz@efri.hr abstract energy poverty has become a rising issue in european union (eu), especially in new member states, but still there is no uniform methodology in defining energy poverty and policy measures. the aim of our paper is to assess and compare the number of energy poor households in three new eu member states based on quantitative indicators like the number of energy poor households that use financial measures related to energy sector and the number of households that spend more than 10% of their income on energy. our results show that the number of energy poor population increased in the period 2009-2014 in all three countries according to the level of monthly (bulgaria and romania) and guaranteed minimum allowances (croatia), while the share of heating allowances decreased only in romania, but is still very high. in all three countries the problem of energy poverty is present in 4 to 5 deciles. additionally, the share of the population who consider that they cannot keep their homes warm is the biggest problem in bulgaria (45%), then in romania (14%) and croatia (10%). keywords: energy poverty, bulgaria, croatia, romania jel classifications: q48, i32 1. introduction due to global economic recession that has started in 2007, volatile energy prices and low energy efficiency in residential buildings, the number of households in european union (eu) that are facing energy poverty is increasing. they are known as energy/fuel poor households. however, at the european and global scale there is an inconsistent use of terminology (thomson and snell, 2013), with the term energy poverty sometimes used interchangeably with fuel poverty, whilst at other times it is used to conceptualise a more extreme set of circumstances (thomson, 2013). sometimes energy and fuel poverty are considered as different concepts with energy poverty referring to the lack of access to modern energy services in developing countries (bazilian et al. [2010]; birol (2007) and sagar [2005]), and fuel poverty referring to “a problem of affordability rather than access, which is present in some of the world’s most developed countries” (househam and musatescu, 2012). however, the energy sources covered by the term fuel poverty are broader than those considered in the energy poverty references in the internal electricity and gas market legislation (ec, 2010). although these terms are not sinonimous, we decide to use energy poverty terminology since it is widely used in scientific literature. according to ec (2015), many eu member states do have measures in place to protect vulnerable households, but nearly 11% of eu’s population, mostly in new member states of central eastern and southeastern europe is in a situation where they are not able to adequately heat their homes at an affordable cost. this paper focuses three newest eu member states: bulgaria, croatia and romania that have been burdened with similar problems arisen from low gdp p/c, non-market history and low electricity and gas prices until few years ago due to high cross-sectors energy subsidies. however, energy market liberalization became a global process and it resulted in higher energy prices, while the recession decreased disposable income of households. after the years of lobbying by a number of international organizations, academics and political groups, the notion of “energy poverty” finally entered in the legislation of the eu. the institutional framework was presented within the third energy lenz and grgurev: assessment of energy poverty in new eu member states: the case of bulgaria, croatia and romania international journal of energy economics and policy | vol 7 • issue 2 • 20172 package, in directives on concerning common rules for the internal market in electricity and natural gas supply (directives 2009/72/ ec and directive 2009/73/ec). member states shall define the concept of vulnerable customers which may refer to energy poverty and to the prohibition of disconnection of electricity and gas to such customers in critical times. defining the concept became a legal obligation for all member states by the end of 2015. furthermore, member states should ensure the necessary energy supply for vulnerable customers. in doing so, an integrated approach, such as in the framework of social policy, could be used and measures could include social policies or energy efficiency improvements for housing. however, energy poverty is a broader concept and since it refers not only to vulnerable consumers, different metrics to define and measure is required. in 2011 bulgaria has adopted the energy strategy (og 43/11) till 2020 in which one of the reason for energy efficiency improvement is combating energy poverty. according to the strategy, the reduction in energy consumption in households that are affected by this problem is the appropriate tool for reducing energy poverty. with amendments to the law on energy sector (og 107/03, last amended in 98/14), the concept of vulnerable customers entered in the bulgarian legislation. vulnerable customer is a customer from the household category who is a beneficiary of targeted allowance for electricity, heat or natural gas under the law on social assistance. the definition implied the placement of energy poverty problem in the area of social policy, and not energy. according to the law on social assistance (og 56/98, last amended in 120/02), vulnerable households are entitled to targeted allowance for electricity, heat or natural gas (for heating) in a specific monetary amount. financial assistance is awarded during the winter months and contributes to only short-term problem solving, moreover facilitates individuals only a survival. unfortunately, regardless of the adoption of the national action plan for energy efficiency 2014-2020 and the national programme for the reconstruction of buildings 20052020, energy efficiency is not placed into service for reducing energy poverty as the only long-term solution. croatia adopted energy strategy in 2009 (og 130/09) and defined the concept and status of vulnerable customer for the first time in the energy act (og 120/12, 14/14,95/15,102/15) following by the law on electricity market (og 22/13,95/15,102/15) and the law on gas market (og 28/13, 14/14). vulnerable customer is an energy final customer from household category who because of its social status and/or health conditions is entitled to energy supply under special conditions. final customer from household category, who meets the condition of poverty, is entitled to a social minimum energy consumption determined by the conditions of supply in the housing in which he lives, number of family members and their health and economic status. in september 2015 government adopted the decision according to which the vulnerable customer is a customer from household category who is a beneficiary of minimum guaranteed social allowance and/or disability allowance. aside from directives on the internal market for electricity and natural gas, croatia transposed the provisions of the directive on energy efficiency (2012/27/ec) which are incorporated in the law on energy efficiency and the appropriate national energy efficiency action plan for the period from 2014 to 2020. according to the law on energy efficiency og 127/14 some measures to increase energy efficiency might be implemented as a priority for vulnerable customers. in addition, potential financial sources for the implementation of energy poverty measures are listed in the air protection act (og 130/11, 47/14), and in the poverty reduction strategy. romanian energy strategy which was adopted in 2011, states that energy prices for vulnerable customers must be beyond the regulation domain. also, it states that the social tariffs for natural gas, electricity and heat must be replaced by direct social benefits. vulnerable customer is defined in the law on electricity and natural gas (og 123/12) as household customers at risk of social exclusion because of its older age, health or low-income and who is, in order to prevent risk, a beneficiary of social protection measures, including financial ones. in addition to the law on electricity and natural gas (og 123/12), the term vulnerable customer is defined in the emergency regulation on measures of social protection during the winter (og 70/11, 27/13) for the purpose of social assistance, as a household (individual/family) who cannot provide to cover all costs of heating and whose income is within the predefined limits. less than a third of eu countries officially recognize energy poverty and only a few have an official definition in their national legislation. since there is no official definition of energy poverty on eu level and no uniform methodology and policy measures for reducing energy poverty, it is obvious that much more needs to be done to develop an internationally consistent measurement framework and to put in place data collection systems that will enable regular reporting. assessment of energy poor households represents an important first step in dealing with the problem. we are aware that the issue of energy poverty could be analyzed and measured in a multidimensional framework; however we choose a more narrow approach. the aim of our paper is to assess and compare the number of energy poor households in three new eu member states based on quantitative indicators like the number of energy poor households that use financial measures related to energy sector. since it is a first step in tackling the problem of energy poverty, we hope that this paper gives a small contribution to addressing this issue by using comparative analysis of three less developed eu countries. 2. energy poverty and energy prices: empirical framework since energy prices strongly influence the occurrence of energy poverty, the following analysis focuses the development of energy prices and energy mix of households in bulgaria, croatia and romania. figures 1 and 2 shows the development of electricity and natural gas prices for a household that consumes 2500-5000 kwh/year, which represents an average household consumption in the period from 2007 to 2014 in selected countries. lenz and grgurev: assessment of energy poverty in new eu member states: the case of bulgaria, croatia and romania international journal of energy economics and policy | vol 7 • issue 2 • 2017 3 data show that bulgaria constantly had the lowest level of electricity prices for households compared to croatia and romania, but also compared to the eu average. during the period, prices in bulgaria grew on average by only 2% annually although it was a time of high prices of primary energy sources like gas and oil. contrary to bulgaria, electricity prices in romania significantly fluctuated over the years. for example, large price drop of almost 10% in 2009, and an increase of 23% in 2013 were recorded. compared with prices in romania and bulgaria, prices in croatia are the highest and they grew on average by 5% per year. in all three countries electricity prices for households decreased in 2014 because of the large price drop on the wholesale market. in all three countries the process of electricity market liberalization took place as a part economy-wide structural adjustment programs and influenced the level of prices that have become more cost reflective. as a legacy of non-market economy till the beginning of 90s, state-owned and highly bundled monopolies were strongly subsidized from the state budget, while electricity and other energy prices were artificially low. however, liberalization and privatization in energy sector created different macroeconomic environment and increased electricity prices. similar pattern can be seen in gas sector as well (figure 2). data show that the prices of natural gas increased by 50% in bulgaria, by 65% in croatia, while decreased by 8% in romania in comparison with 2007. unlike the prices of electricity, natural gas prices are the highest in bulgaria and not only among observed countries, but also in comparison with the eu average as well. the increase in gas prices in most eu countries that are strongly import-dependent on russia, was the reality till the end of 2014. changing prices of energy impacted the structure of final energy consumption of households in the mid-term run and therefore it would be interesting to see broader structural changes. when faced with growing prices of certain energy source, households are prone to change the energy source if they are able to. consequently, final energy consumption changes over time. figure 3 presents the structure of final energy consumption in households by energy sources in bulgaria (marked by b), croatia (marked by c) and romania (marked by r) in the period 2005-2012. according to the presented data, electricity is the most important energy source in bulgaria (40%) followed by firewood (32%). district heating is also represented (15%), as well as coal (10%). natural gas comprises only 2% in the overall structure. the reason for high electricity consumption lies in its low price. in fact, in several bulgarian cities the newly constructed gas distribution network led to increase in natural gas prices that became too expensive for many households. as a result, most of the people who were connected to the distribution network, ceased to use gas for heating during the winter months. on the other hand, because of an underdeveloped gas network, large share of the total households has no access to natural gas as an energy source. also, many households have switched from district heating to electricity because the heat prices were no longer subsidized (peneva, 2014). energy prices in romania influence the structure of final energy consumption in households as well. data show that firewood has the largest share (44%) followed by natural gas (28%). electricity is used only 12%. due to the cessation on subsidizing the heat price, district heating consumption decreased and currently amounts only 13% of the total energy consumption. households in croatia mostly use electricity (30%) and slightly less gas (28%). district heating participates 8% in total consumption due to the fact that only a small number of cities are connected to heating systems. during the analyzed period, share of gas and district heating decreased due to the rising prices accompanied with the fall in disposable income of households. the result is the return of traditional biomass use and growing share of firewood in final energy consumption (23%). 3. data and methodology the assessment of energy poverty is based on several indicators. first we calculate the number of energy poor population who are beneficiaries of various social policy measures that are related to energy sector. the number of beneficiaries (families and single people) is placed in the ratio with the total number of households. then we calculate the share of households energy expenditures in their total income in order to see how many households spend more than 10% on energy, which represents the margin for energy poor household (boardman, 1991). the third indicator is the share of household expenditures on energy in the total income. figure 1: electricity prices in bulgaria, croatia and romania in the period 2007-2014, vat included source: eurostat database, 2015 figure 2: natural gas prices in bulgaria, croatia and romania in the period 2007-2014, vat included source: eurostat, 2015 lenz and grgurev: assessment of energy poverty in new eu member states: the case of bulgaria, croatia and romania international journal of energy economics and policy | vol 7 • issue 2 • 20174 households are divided with regard to income into the decile classes. the decile classes are formed by dividing the basic set on ten equal parts by calculating the average net income per household, classifying households by income from the lowest to the highest and by classifying the households from the basic set into the corresponding decile. thus, the households that have the lowest annual net income are in the first decile, while households that are in the tenth decile have the highest annual net income. subsequently, the total expenditure on energy by decile is set into the ratio with total household income. additionally, we also use the eu-silc (eu-statistic on income and living conditions) indicator that shows the share of the population who cannot keep their homes warm. data are collected from national statistics published by national statistical institute of all three countries and they cover the period from 2009 till 2013/2014. the share of households in bulgaria covered by the social policy measures aimed to mitigate the energy poverty is based on budget survey published by the ministry of labor and social affairs and ordinance on the terms and conditions for allocation of targeted assistance for heating (og 49/08). these measures include monthly and heating allowance. estimation of the energy poor population in croatia is based on statistical data of the ministry of social policy and youth. according to the law, the beneficiaries of the guaranteed minimal allowance are the poorest part of the croatian population and they represent the minimum number of potential energy poor residents. these measures include guaranteed minimum allowance and heating allowance. the estimates for romania are based on statistical reports provided by romanian ministry of labor, family, social affairs and the elderly. the share of households covered by social policy measures aimed to mitigate the energy poverty is calculated for romania by using measures that include guaranteed monthly allowance and heating allowance according to the law on minimum wage (og 416/01). 4. results and discussion estimated results on the energy poor population in three analyzed countries are presented in following figures. the data for bulgaria, the less developed country according to gdp p/c, are shown in figure 4. approximately 2% of the total number of households in bulgaria was beneficiaries of monthly allowance in 2014, which represents the simplest form of social assistance. almost 10% of the population was beneficiaries of heating allowance during the winter. the data also show that the number of beneficiaries for heating allowance has increased during the last 3 years, and the number of monthly allowance beneficiaries has increased during the whole analyzed period. similar trends of rising number of energy poor population could be seen in croatia as well. however, croatia is the most developed among the analyzed countries and these shares are considerably lower in comparison with bulgaria and romania, but still they are increasing over the analyzed period. the data on croatia are presented in the figure 5. approximately 3.4% of the total number of households in croatia was beneficiaries of monthly allowance and 2.9% of heating allowances in 2013. during the analyzed period, the number of monthly allowance beneficiaries has grown, as well as the number of heating allowance beneficiaries. the estimation for romania is shown in the figure 6. although romania is more developed than bulgaria (and less than croatia), the share of energy poor population is much higher than in other analyzed countries. on the basis of the total number of households, about 3.4% were beneficiaries of monthly allowance and 14.5% of heating allowance. during the observed period the number of guaranteed minimum allowance beneficiaries increased slightly, while the number of heating beneficiaries decreased but it is still on a very high level that indicates energy poverty as a big social problem. the second step in assessing the energy poverty is to calculate the share of households’ expenditure on energy in relation to total disposable income by decile classes. due to data availability these shares are calculated for bulgaria in 2013, croatia in 2011 and romania in 2013. the limit of energy poverty is set to 10% figure 3: structure of final energy consumption in bulgaria, croatia and romania, 2005-2012 source: authors according to odysee mure base, 2015 lenz and grgurev: assessment of energy poverty in new eu member states: the case of bulgaria, croatia and romania international journal of energy economics and policy | vol 7 • issue 2 • 2017 5 and marked by red line. the share of households above the red line is considered to be energy-poor. figure 7 shows the share of household expenditure on energy in bulgaria, figure 8 presents the share of household expenditure on energy in croatia, while figure 9 presents this share in romania. the results are in a way unexpected because they indicate that in croatia, the most developed country with the least energy poor population, there are the most households that spend on energy more than 10% of their income. according to presented data, in all three countries there are energy poor households in 4-5 deciles, but the problem is the most pronounced in croatia. although net income in croatia is higher than income in bulgaria and romania, prices of electricity and natural gas for households in croatia are also higher and reach the average level in eu. one of the indicators analyzed in the framework of the eu-silc is the proportion of the population who cannot keep their homes warm. this indicator refers to the ability to pay for adequate heating of living space. it should be noted that the indicator is calculated on the basis of the survey in accordance with the perception by the residents and it is not the objective calculation of the thermal comfort in households. the survey results for all three analysed countries are presented in the figure 10. according to eu-silc data, about 45% of households in bulgaria consider that they cannot keep their home warm. comparing these data with the previously assessed indicators, it can be seen that this percentage is much higher than the share of households that receive heating allowance (10%). in croatia, there is also a difference between the number of households receiving some form of social assistance aimed to address the energy poverty problem (3%) and the actual number of energy-poor households according to this last indicator (10%). in romania, the share of the households which expressed the inability to adequately heat their homes is the same as the share of the household which receives heating allowance during the winter (about 14%). these results should be analyzed in a wider context of energy markets liberalization that has led to increase in energy prices in all countries. due to liberalization, energy prices for households are not regulated any more, as they used to be in the past. till recently the most of new member states have still retained the distorted price structure, which was the legacy of a system in which domestic consumption of electricity was subsidized at the expense of industrial and commercial consumption. however, the situation changed and today energy prices have become costreflective, which strongly influence the number of households that are beneficiaries of some kind of allowances related to energy. according to presented data, it could be concluded that cost-reflective tariffs in three analyzed countries have resulted in restrictions of comfort, inadequate heating in households and high share of income spent on energy bills in new eu member states. there is no doubt that these problems should be tackled by european commission and national authorities since they have become serious economic and social issues. 5. conclusion the analysis shows that the number of energy poor population increased in the period 2009-2014 in all three selected countries according to the level of monthly (bulgaria and romania) and guaranteed minimum allowances (croatia), while the share of heating allowances decreased only in romania, though from very high level of over 20-14%. the second step was to calculate the share of households’ expenditure on energy in relation to total disposable income by decile classes. the limit of energy poverty is set to 10%. according to our results, in all figure 4: the share of energy poor population in bulgaria, 2009-2014 source: authors according to data from www.mlsp.government.bg figure 5: share of energy poor population in croatia, 2009-2013 source: authors according to data from www.mspm.hr figure 6: share of energy poor population in romania, 2009-2014 source: authors according to data from www.mmssf.ro lenz and grgurev: assessment of energy poverty in new eu member states: the case of bulgaria, croatia and romania international journal of energy economics and policy | vol 7 • issue 2 • 20176 figure 7: share of household expenditure on energy in bulgaria source: authors according to national statistics institute bulgaria, 2015 figure 8: share of household expenditure on energy in croatia source: authors according to croatian bureau of statistics, 2012 figure 9: share of household expenditure on energy in romania source: authors according to national institute for statistics romania, 2013 lenz and grgurev: assessment of energy poverty in new eu member states: the case of bulgaria, croatia and romania international journal of energy economics and policy | vol 7 • issue 2 • 2017 7 three countries the problem of energy poverty is present in 4-5 deciles, although is the most pronounced in croatia due to higher electricity and natural gas prices in comparison with bulgaria and romania. another indicator has been analyzed that shows the share of the population who consider that they cannot keep their homes warm and results show that the energy poverty is the biggest problem in bulgaria where 45% of households consider that they cannot keep their home warm, 14% in romania and 10% in croatia. the overview of measures in each country shows that there is no uniform approach and that tackling the problem of energy poverty still remains within social policy since financial allowances are based only on households’ income. all observed countries need systematic and long-term approach in dealing with this problem that should include indirect measures like improving energy efficiency. 6. acknowledgment this work has been fully supported by croatian science foundation under the project ip-2013-11-2203. references air protection act, croatia, og 130/11, 47/14. annual statistic report on applicable social welfare rights, ministry of social croatia: policy and youth; 2005-2013. available from: http://www.mspm.hr. bazilian, b., sagar, a., detchon, r., yumkella, k. (2010), more heat and light. energy policy, 38(10), 5409-5412. birol, f. (2007), energy economics: a place for energy poverty in the agenda? the energy journal, 28(3), 1-6. boardman, b. (1991), fuel poverty: from cold homes to affordable warmth. london: belhaven press. croatian bureau of statistics. (2012), results of household budget survey 2008 – 2011. available from: http://www.dzs.hr. emergency regulation on measures of social protection during the winter, romania, og 70/11, 27/13. energy act, croatia, og 120/12, 14/14, 95/15, 102/15, available at: http:// www.zakon.hr/z/368/zakon-o-energiji. energy strategy of the republic of bulgaria. bulgaria, og 43/11, available at: http://www.mi.government.bg/files/useruploads/files/ epsp/23_energy_strategy2020%d0%95ng_.pdf. e n e rg y s t r a t e g y o f t h e r e p u b l i c o f c r o a t i a , c r o a t i a , o g 130/09. available from: http://narodne-novine.nn.hr/clanci/ sluzbeni/2009_10_130_3192.html. energy strategy of the republic of romania. available from: http:// www.minind.ro/energie/strategia_energetica_actualizata.pdf. european commission. (2015), energy poverty and vulnerable consumers in the energy sector across the eu: analysis of policies and measures, policy report. available from: https://www.ec.europa. eu/energy/sites/ener/files/documents/insight_e_energy%20 poverty%20-%20main%20report_final.pdf. eurostat database. available from: http://www.ec.europa.eu/eurostat. househam, i., musatescu, v. (2012), improving energy efficiency in low-income households and communities in romania: fuel poverty draft assessment report. united nations development programme, romania. available from: http://www.undp.ro/libraries/ projects/ee/assesment%20report%20on%20fuel%20poverty%20 -%20%20draft.pdf. law on electricity and natural gas, romania, og 123/12. available at: http://www.electrificarecfr.ro/elegi/legi/l123.pdf. law on electricity market, croatia, og 22/13,95/15,102/15. available at: http://www.zakon.hr/z/377/zakon-o-tr%c5%bei%c5%a1tuelektri%c4%8dne-energije. law on energy sector, bulgaria, og 107/03, 98/14. available at: https:// www.me.government.bg/bg/library/zakon-za-energetikata-256c25-m258-1.html. law on gas market, croatia, og 28/13, 14/14. available at: http://www. zakon.hr/z/374/zakon-o-tr%c5%bei%c5%a1tu-plina. law on minimum wage, romania, og 416/01. available at: http://www. cdep.ro/pls/legis/legis_pck.htp_act_text?idt=28801. law on social assistance, bulgaria, og 56/98, 120/02. available at: http://pomosti.oneinform.com/zakon-za-socialno-podpomagane/. law on social assistance, croatia, og 157/13, 152/14, 99/15, 52/16 available at: http://www.zakon.hr/z/222/zakon-o-socijalnoj-skrbi. ministry of economy, bulgaria. available from: http://www. mi.government.bg. figure 10: share of population that cannot keep its home adequately warm, 2010-2013 source: eurostat database, 2015 lenz and grgurev: assessment of energy poverty in new eu member states: the case of bulgaria, croatia and romania international journal of energy economics and policy | vol 7 • issue 2 • 20178 ministry of labor and social policy of bulgaria. (2016), report of the ministry of labor and social policy budget 2009-2015. available from: http://www.mlsp.government.bg. ministry of labor, family, social protection and elderly of romania. (2015), statistic report in domain of social inclusion 2009 2014. available from: http://www.mmuncii.ro. national institute for statistics of romania. (2013), report on living in romania income and consumption in 2013. available from: http://www.media.hotnews.ro/media_server1/document-2014-079-17640607-0-coordonate-ale-nivelului-trai-romania-2013.pdf. national statistical institute of republic of bulgaria. (2013), household budgets in the republic of bulgaria. available from: http://www. nsi.bg. odysee mure database. available from: http://www.odyssee-mure.eu. ordinance on the terms and conditions for allocation of targeted assistance for heating, bulgaria, og 16/08, available at: http://pomosti. oneinform.com/celeva-pomist-za-otoplenie/. peneva, t. (2014), energy poverty: the bulgarian case. washington, dc: international association for energy economics. sagar, a.d. (2005), alleviating energy poverty for the world’s poor. energy policy, 33(11), 1367-1372. thomson, h. (2013), fuel poverty measurement in europe: a rapid review of existing knowledge and approaches. kendal uk: eaga charitable trust. thomson, h., snell, c. (2013), quantifying the prevalence of fuel poverty across the european union. energy policy, 52c, 563-572. . international journal of energy economics and policy | vol 7 • issue 5 • 2017 263 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(5), 263-270. increase of social impact due to the development of the renewable energy industry in russia yulia alexandrovna nazarova1, natalya yuryevna sopilko2*, rimma shoidorzhievna bolotova3, natalya sergeevna shcherbakova4, vladimir borisovich alexeenko5 1peoples’ friendship university of russia (rudn university), 6 miklukho-maklaya street, 117198, moscow, russia, 2peoples’ friendship university of russia (rudn university), 6 miklukho-maklaya street, 117198, moscow, russia, 3peoples’ friendship university of russia (rudn university), 6 miklukho-maklaya street, 117198, moscow, russia, 4peoples’ friendship university of russia (rudn university), 6 miklukho-maklaya street, 117198, moscow, russia, 5peoples’ friendship university of russia (rudn university), 6 miklukho-maklaya street, 117198, moscow, russia. *e-mail: sheremett73@gmail.com abstract the article is providing highlights on the development prospects of the renewable energy industry in russia from the point of view of increasing the social impact on jobs creation. the branch of renewable energy is considered as one of the directions reducing unemployment in the regions of russia. the peculiarities of the industry development in russia, related to the existing regulatory and legal framework and the structure of the national electric power market, are singled out. as a result of the study, methodological approaches in assessing the social effect from the development of the renewable energy industry in russia are formulated. also a forecast of the number of created jobs is made, taking into account the implementation of projects in the wholesale and retail electric power markets and isolated power systems. the compiled statistical and expert data allow to develop scenarios for commissioning capacities in the industry. the proposed approaches and scenarios make it possible to estimate the number of created jobs regionally and analyze the impact of these places on the level of unemployment in the regions of russia. regions have been identified where the development of the renewable energy sector will have a significant positive social effect. quantitative assessment of the social effects of the industry development can help to work out mechanisms of state support for renewable energy, for performing technical and economic calculations for projects and regional programs in the field of renewable resources and energy sources. the results can be used to formulate criteria for regional competitive selection, to formulate schemes for the territorial development of the electric power industry. keywords: renewable energy industry, social effect, unemployment level, russian regions, jobs creation jel classifications: j21, j60, l72 1. introduction the development of the renewable energy industry leads to economic, social and environmental effects from its use. at the same time, it is essential to solve the unemployment problem, which is especially important for many russian regions, considering the shortage of jobs (republic of dagestan, ingushetia, sakha (yakutia), etc.) among social effects. despite the fact that since 2000 the unemployment rate has been tending to decrease (10.6% in 2000, 7.3% in 2010), the crisis in the economy is evident. so, in 2014 the unemployment rate reached 5.2%, but in 2015 it rose to 5.6% and after a small fall in 2016 (to 5.4%) as of january 2017, the unemployment rate in russia is 5.6% or 4.3 million people (according to rosstat). evaluation of the role of the renewable energy development in terms of social benefits is one of the priorities in solution of the unemployment problems in russia. on the one hand, the construction of industry facilities is economically feasible in remote and hard-to-reach areas where it is difficult to find work for the population. on the other hand, newly commissioned renewable energy facilities, especially when accompanied with the organization of equipment production, can defuse the tense situation of shortage of work in such regions as the north caucasus federal district. nazarova, et al.: increase of social impact due to the development of the renewable energy industry in russia international journal of energy economics and policy | vol 7 • issue 5 • 2017264 the need for the development of renewable energy is fairly controversial for russia. with the existing low prices for natural gas and oil, developed infrastructure of the gas industry and traditional generation, the economic viability of building renewable energy sources (res) facilities is often questioned by many experts. nevertheless, the beginning of the development of the renewable energy sector has already been initiated, which is one of the opportunities in solving the unemployment problem in the regions. the effect assessment of the renewable energy on solving problems of unemployment in the russian regions is possible due to the adoption of the regulatory framework for the support of renewable energy in the wholesale and retail markets, as well as the need to justify incorporation of projects based on res in regional development programs and energy supply schemes. according to world statistics, in 2015, 8.1 million people were employed in the sector (excluding large hydro-generation), which is 5% more than in 2014, when renewable energy industry employed 7.7 million people (renewable energy and jobs 2016). despite the fact that the dynamics of growth in the number of people employed in the renewable energy sector has slowed down, the total number of jobs created in the industry is on the rise. at the same time, countries of asia are playing an increasing role with share increased to 60%. such countries as china, brazil, the united states, india, japan and germany are the leaders in volume of employed in the renewable energy sector. the number of people employed in various sectors of the renewable energy sector according to statistics is presented in table 1. according to the data in the table, the dynamics of employment in technologies based on the use of res are different. the largest employer is the solar energy industry, where 2.8 million people were employed in 2015, and the growth tendency is 11% compared to 2014. however, there has been a significant increase in japan and the us, stabilization in china, a decline in the european union. the number of jobs in wind energy reached 1.1 million people, which is more by 5% in 2014 due to the input power in china, the us and germany (renewable energy and jobs 2016). in bioenergy, employment amounted to 1.7 million people, including 822 thousand people in biomass processing projects and 382 thousand people in biogas utilization projects. nevertheless, compared to 2014, there was a 6% decrease in the number of employed because of the increased level of mechanization in some countries and a reduction in the production of biofuels in others. practical data suggest that in some renewable energy sectors more jobs are created per mw of installed capacity than in traditional energy, as during the construction phase as well as during the operation of the generating facility (rutovitz and harris 2012). the possible number of jobs created in the energy sector is presented in table 2. the development of renewable energy in the world has led to an increase in the number of studies on employment issues and the impact of the renewable energy industry on reducing the number of unemployed. among modern foreign studies, the work of f. ulrich, w. lehr et al. on the impact of renewable energy on the labor market and employment in germany (ulrich et al., 2012) was mentioned. the number of jobs created in wind energy is estimated as a result of domestic investment and exports, and jobs for the operation and maintenance of existing wind turbines. in addition to direct employment in wind energy, the creation of jobs is estimated in related industries, and the regional influence of wind energy on employment is also considered. the works of cebotari and benedek (2017) assess the influence of res on the development of innovations in the regions. in their opinion, the realization of solar energy projects does not directly affect the “classical” indicators such as employment and local government revenue for the settlements of northwestern romania, but it is necessary to assess their impact on innovation and technological development on the whole. it is important to emphasize that the insignificant impact of res projects on employment refers to the local level, and not to the region as a whole. the study says that res projects usually involve highly qualified personnel who come from regional centers and do not live directly at the site of the res project. the adas experts analyzed the opportunities for social development in the rural regions of the uk under the influence table 1: volume of people employed in the renewable energy sector and related industries. thousand people number of employed in country technology res based china brazil usa india japan bangladesh germany france other eu countries total in the world sun energies (photovoltaic modules) 1652 4 194 103 377 127 38 21 84 2772 liquid biofuels 71 821 277 35 3 23 35 47 1678 wind power 507 41 88 48 5 0.1 149 20 162 1081 energy of the sun (thermal installations) 743 41 10 75 0.7 10 6 19 939 solid biomass 241 152 58 49 48 214 822 biogas 209 85 9 48 4 14 382 energy of water 100 12 8 12 5 12 4 31 204 energy of geothermal sources 35 2 17 31 55 160 energy of the sun (concentrated solar energy) 4 0.7 5 14 total 3523 918 769 416 388 141.1 355 170 644 8079 nazarova, et al.: increase of social impact due to the development of the renewable energy industry in russia international journal of energy economics and policy | vol 7 • issue 5 • 2017 265 of wind energy, hydro and bioenergy projects (renewable energy and its impact on rural development and sustainability in the uk, 2003). the study shows that the greatest number of jobs is created when implementing bioenergy projects (on average 29, of which 25 are created directly in the project implementation area, and 1 work place assumes part-time employment). the number of jobs created is lower in hydroand wind-power engineering (respectively 2 and 6 workplaces with part-time employment). the work emphasizes that for rural areas where employment opportunities are extremely limited, including agriculture and forestry, even a small number of new jobs can have a significant impact on the development of the region. the focus on the study of socio-economic effects from the development of the renewable energy industry was made in the work of del rio and burguillo (2008). among the effects, the authors singled out: the diversification of energy sources, the opportunities for regional and rural development, the creation of localized industry and jobs. the study is aimed at creating a theoretical basis for identifying the impact of the renewable energy on regional sustainability with the possibility of applying results for different territories. many researchers in the field of renewable energy pay special attention to the effects from its development (kammen et al., 2004; alvarez et al., 2009; dai et al., 2016; barbosea et al., 2016; dvorak et al., 2017). among the russian studies in the field of social effects from the development of renewable energy can be noted the works of kopylov (2015), bezrukikh and bezrukikh (2014), grechukhina et al. (2016), where they pay special attention to the already implemented projects in the field of renewable energy in various countries. these days, russia has not gained an experience in implementing projects in this area. therefore, this study is of a predictive nature, and its purpose is to assess the possible benefits from implementing renewable energy projects in the regions of russia, based on existing goals and indicators for the development of res in the wholesale and retail electricity and capacity markets, supported by existing regulatory documentation. 2. methodology of the research social effects from the development of renewable energy, such as the creation of jobs in the renewable energy and in related industries, should be evaluated in several stages (nazarova et al., 2017). at the first stage, a large-scale valuation is carried out on the basis of the existing normative legal documentation and strategic goals in the input powers industry. also, the peculiarities of the economic model of the operation of res facilities in russia should be taken into account, which is fundamentally different for the wholesale and retail electricity market, for isolated power systems. support measures such as establishing long-term tariffs for the purchase of electricity for the payback period, inclusion of res projects in federal and regional target programs, ensuring priority loading of generating objects of res in the operational dispatch management system are provided for isolated power systems. in retail markets, the main element of support is the obligation of grid companies to purchase electricity from qualified res facilities at regulated tariffs in order to compensate for losses. at the same time, the federal budget compensates the costs of technological connection to electric grids for facilities with a capacity of less than 25 mw. for qualified renewable generation facilities in the wholesale electricity and capacity market (wecm), a mechanism is provided for the sale of electricity under a purchase and sale agreement, as well as capacity sales under a capacity contract (cc), which is the generator’s obligation to build, commission and to bring a new generation to the wecm in the future. the government of the russian federation determined the procedure for competitive selection of construction projects for generating facilities based on res, rules for calculating the price for the capacity of generating facilities for res that provide return on invested capital, as well as targets for commissioning of generating facilities for res up to 2024, target indicators of the localization degree and limit values for capital and operating costs. taking into account the above-mentioned peculiarities of the structure of the russian branch of renewable energy, the number of jobs created can be assessed according to the formula 1: table 2: number of jobs per 1 mw of installed capacity technology term of construction construction period production of equipment operation period coal 5 7.7 3.5 0.1 gas. oil and diesel fuel 2 1.7 1.0 0.08 nuclear power 10 14.0 1.3 0.3 biomass 2 14.0 2.9 1.5 small hydropower engineering 2 15 5.5 2.4 wind power onshore 2 2.5 6.1 0.2 wind power offshore 4 7.1 11 0.2 solar power engineering 1 11 6.9 0.3 geothermal power engineering 2 6.8 3.9 0.4 solar thermal power engineering 2 8.9 4.0 0.5 tidal energy 2 9.0 1.0 0.3 nazarova, et al.: increase of social impact due to the development of the renewable energy industry in russia international journal of energy economics and policy | vol 7 • issue 5 • 2017266 p = ((p +p )*ym (p *(ym +ym) ))c i i i-1π +i n i n = =∑ ∑1 1 ∋ (1) where: i – number of the target year of the period under evaluation, i = 1, 2, 3 etc.; n – number of years in the period under evaluation; рс – number of jobs created during the construction of a renewable energy object; рп – number of jobs created in the production of equipment for the res facility in related industries; рэ – number of workplaces created when operating a renewable energy object; ум – the value of the installed capacity of the renewable energy object, determined by the formula: 1 2 3 ym (ym ; ym ; ym )i = ∑ (2) where: i – number of the target year of the period under evaluation, i = 1, 2, 3 etc.; ум1 – the amount of installed capacity of renewable energy objects in the wecm; ум2 – value of installed capacity of res in the retail market; ум3 – value of the installed capacity of renewable energy objects in isolated power systems. at the stage of the integrated estimation for definition of the predicted value of the established capacity as an initial information can be used: 1. existing legal and regulatory framework (for wecm); 2. expert review (for the retail market and isolated energy systems). to determine the specific indicators for the number of jobs created in renewable energy and related industries can be used analytical and information reports irena, ren21, np “council of market participants in res” and others. the second stage of the assessment can be carried out at the regional level and include the assessment of social effects from the implementation of specific res projects. as projects planned for implementation, it is reasonable to consider objects that have passed the competitive selection at wecm or won in regional competitions. the results of competitive selection at the wecm are published annually by np “market council”. at the final stage of the study, the results obtained are summarized and the conclusions formulated about the impact of res projects on solving unemployment problems at the country and region level. 3. the results of research the installed capacity of facilities operating on the basis of renewable energy in 2015-2016 is determined on the basis of the data of the np “market council” and np “council of market participants of renewable energy” about qualified renewable energy facilities. the installed capacity of the facilities for the period 2017-2024, corresponds to the target indicators of the regulatory documentation, and is presented in table 3. according to vygon consulting, the potential for developing renewable energy projects in the retail market is estimated at around 3,000 mw with an aggregate investment of $ 8 billion. the development potential for res until 2020 in isolated power systems is up to 1,000 mw (mainly solar and wind power projects) according to the estimation of the ministry of energy. the number of jobs created was estimated on the basis of specific indicators per 1 mw for different sectors according to the irena study (for european countries, usa and south africa). it was done during the construction period, including the production of equipment and installation and start-up work: • jobs in wind energy 12.5 people/mw; • jobs in solar energy 33.2 people/mw; • jobs in small hydropower 20.4 people/mw; • jobs in bioenergy 7.7 people/mw; • the average for the four renewable energy sectors is 20.3 people/mw for the period of operation of renewable energy facilities: • jobs in wind power engineering 0.4 people/mw; • jobs in solar energy 0.5 people/mw; • jobs in small hydropower 1,2 people/mw; • jobs in bioenergy 5.5 people/mw; • the average for four renewable energy sectors 1 person/ mw. considering the available basic data for the wecm, the number of jobs created up to 2024 will be about 100,000 and by res sectors is shown in table 4. assuming that 3000 mw of installed capacity will be introduced in the retail market, the number of jobs allocated to the four res (wpp, spp, shpp and bioenergy) sectors can reach 60,950. for isolated power systems, this amount can be 21,700 when 1000 mw of solar and wind power are put into operation. by 2024, about 6,000 jobs can be created for the operation of renewable energy facilities (table 5), including: • in wecm 2521; • in the retail market 2950; • in isolated power systems 428. starting in 2013, a number of renewable energy facilities were built in russia in regions with high unemployment: • small hydroelectric power plant “kokadoy” (chechen republic, 135 thousand unemployed); • buribaevskaya and bugulchanskaya solar power plants (republic of bashkortostan, more than 100 thousand unemployed); nazarova, et al.: increase of social impact due to the development of the renewable energy industry in russia international journal of energy economics and policy | vol 7 • issue 5 • 2017 267 • perevolotskaya solar power station and sakmarsk solar photovoltaic power plant. a.a. vlazneva (orenburg region, more than 46 thousand unemployed); • small hydropower stations “lyaskel” and “kalliokoski” (republic of karelia, more than 26 thousand unemployed). the results of competitive selection held in 2013-2016, give an idea of the regions that are interesting from the point of view of the development of res. in addition, in august 2016, the territorial planning scheme of the russian federation in the energy sector was adopted, where the commissioning of capacity in wind energy by regions of russia is forecasted for the period up to 2030 (table 6). the information presented in table 6 gives the possibility to assess the impact of projects in renewable energy on the problem of creating jobs in the regions. given the ambiguity of the presented projecting data, two scenarios were formed: scenario 1 “realistic” implementation of res projects takes place, according to the selection on a competition basis. regions of project implementation are defined. when assessing the input capacities and, respectively, the created workplaces, information is used based on the competitive selection results, held in 2013-2016. thus, the renewable energy resources introduced for the period up to 2020 are taken into account. scenario 2 “optimistic” the implementation of res projects takes place according to the results of competitive selection, but the forecast for the construction of wind power plant (wpp) is taken into account in accordance with the rf territorial planning scheme in the energy sector for the period until 2030. regions of project implementation are defined. when assessing the input capacity and, accordingly, the created workplaces, information is used based on the results of the competitive selection held in 2013-2016, and the forecast up to 2030 for the wpp. thus, the res capacities commissioned for the period up to 2020 by ses and mini-hpps are taken into account, and by 2030 by wes. table 7 provides an assessment of the created jobs in renewable energy for the construction period of the facility, taking into account the production of equipment and commissioning, as well as the period of operation. 4. discussion the unemployment rate in the regions under consideration, according to the state statistics service, as of 2016, is presented in table 8. taking into account the forecast of created jobs in the regions where res projects are implemented (table 7), an assessment of the reduction in the unemployment rate in the regions of russia under consideration is made (table 8). table 3: the installed capacity of renewable energy at the wecm for the period up to 2024. mw power stations based on renewable energy sources 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 total wind power plants (wpp) 3.3 0 200 400 500 500 500 500 500 150.2 3253.4 solar power plants (spp) 55.5 70.3 250 270 270 270 162.6 162.6 0 0 1510.9 small hydroelectric power plants (shpps) 8.3 10.8 124 0 49.8 109.2 35.6 35.6 35.6 35.6 444.6 total 66.9 81.1 574 670 819.8 879.2 698.2 698.2 535.6 185.8 5208.9 source: order of the government of the russian federation dated february 28. 2017 no. 354-s table 4: creation of jobs at the wecm for the period up to 2024 people power stations based on renewable energy sources 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 total wpp 40 2500 5000 6250 6250 6250 6250 6250 1878 40668 spp 1841 2334 8300 8964 8964 8964 5398 5398 50163 shpps 170 221 2530 1016 2228 726 726 726 726 9069 total 2051 2555 13330 13964 16230 17442 12375 12375 6976 2604 99900 table 5: creation of jobs in the renewable energy sector for the operation of power generation facilities 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 creation of workplaces for operation of renewable energy sources at the wecm wpp 1 1 78 232 424 616 808 1000 1192 1249 spp 27 61 181 312 442 572 651 729 729 729 shpps 10 23 175 175 235 369 412 455 499 542 total in wepm 38 85 434 718 1101 1556 1870 2184 2420 2521 creation of workplaces for the operation of res facilities in the retail market 369 738 1106 1475 1844 2213 2581 2950 creation of workplaces for the operation of renewable energy sources in isolated power systems 53 107 160 214 267 321 374 428 total for three sectors 38 85 856 1562 2368 3245 3981 4717 5375 5898 nazarova, et al.: increase of social impact due to the development of the renewable energy industry in russia international journal of energy economics and policy | vol 7 • issue 5 • 2017268 5. conclusions the following results were obtained as a result of the study: • a methodology for assessing the social effect, expressed in creating jobs and reducing the level of unemployment in russia from the implementation of projects based on renewable energy is proposed; • a forecast of the number of jobs created in the renewable energy sector of russia, taking into account the implementation of projects at the wecm, the retail market and isolated power systems is made; • scenarios for the introduction of capacities based on res by regions of russia are formulated; • the impact of res projects on the level of unemployment in the regions of russia is assessed taking into account the scenarios for capacity development. the proposed methodology was used to assess the social effect of the development of the renewable energy industry in russia with the parameters determined by the existing regulatory and legal documentation and competitive selection of res projects that took place in 2013-2016, which made it possible to assess the prospects for implementing res projects as one of the directions solving the problems of unemployment in russia at the regional level. according to our estimates, in the res industry will be created for the period until 2024: 9,900 jobs in the implementation of projects at the wecm; 60,950 jobs when implementing projects in the retail market; 21,700 jobs when implementing projects in isolated power systems. in addition, 6000 permanent jobs will be created for the operation of the constructed res facilities. at the same time, it should be noted that the number of jobs is estimated not only for the period of construction of new res facilities taking into account the creation of localized production of equipment, but includes the period of operation of the constructed generating capacities, which creates additional permanent jobs for the lifetime of the res facility, which can reach 20-25 years. a quantitative assessment of the social effects of renewable energy development can serve as a reference point for developing mechanisms for state support for renewable energy, for carrying out technical and economic calculations for projects and regional programs in the field of renewable resources and energy sources. the results can be used to formulate criteria for regional competitive selection, to formulate schemes for the territorial development of the electric power industry and to take decisions on the implementation of projects based on res. 6. acknowledgement this paper was financially supported by the ministry of education and science of the russian federation (the agreement no. 02.a03.21.0008). table 6: planned volumes of installed capacity of renewable energy sources at the wecm of the russian federation according to the results of competitive selection in 2013-2016. mw the subject of the russian federation wpp wpp* spp shpp altai region 20 astrakhan region 30 100 90 belgorod region 15 volgograd region 100 transbaikal region 40 irkutsk region 15 kaliningrad region 200 karachay-cherkess republic 300 5.6 krasnodar region 460 1000 leningrad region 300 lipetsk region 45 murmansk region 400 nizhny novgorod region 350 omsk region 110 40 orenburg region 30 150 290 republic of adygea 150 441 altai republic 20 republic of bashkortostan 64 the republic of buryatia 70 the republic of dagestan 10 republic of kalmykia 51 150 70 the republic of karelia 49.8 he republic of khakassia 5.198 samara region 75 saratov region 1000 40 stavropol region 115 15.04 ulyanovsk region 80 chelyabinsk region 60 total 801 4501 1184.2 70.4 *according to the territorial planning scheme of the russian federation in the energy sector until 2030. adopted by the russian federation government decree no. 1634-r dated august. 2016 the general decrease in unemployment in the group of regions under consideration will be from 3% to 5.76%. under scenario 1, the least impact (up to 1%) on the unemployment problem from implementation of renewable energy projects is in the altai territory, the irkutsk region, the karachay-cherkess republic, the republic of dagestan. the biggest impact (from 5% to 20%) is the implementation of renewable energy projects to reduce unemployment in such regions as: astrakhan region, lipetsk region, orenburg region, republic of adygea, republic of altai, republic of buryatia, republic of kalmykia, stavropol territory. under scenario 2, the least impact (up to 1%) on the unemployment problem from implementation of renewable energy projects is in the altai territory, the irkutsk region, and the republic of dagestan. the biggest impact (from 5% to 30%) is the implementation of renewable energy projects to reduce unemployment in such regions as: astrakhan region, kaliningrad region, karachay-cherkess republic, krasnodar territory, leningrad region, lipetsk region, murmansk region, nizhny novgorod region, orenburg region, republic of adygea, republic of altai, republic of buryatia, republic of kalmykia, stavropol territory. nazarova, et al.: increase of social impact due to the development of the renewable energy industry in russia international journal of energy economics and policy | vol 7 • issue 5 • 2017 269 table 7: estimation of the number of jobs created in the regions of russia as a result of the implementation of renewable energy projects. people the subject of the russian federation wpp wpp* spp shpp scenario 1 scenario 2 altai region 674 674 674 astrakhan region 387 1288 3031 3418 4320 belgorod region 505 505 505 volgograd region 3368 3368 3368 transbaikal region 1347 1347 1347 irkutsk region 505 505 505 kaliningrad region 2577 2577 karachay-cherkess republic 3865 121 121 3986 krasnodar region 5927 12884 5927 12884 leningrad region 3865 3865 lipetsk region 1516 1516 1516 myrmansk region 5154 5154 nizhny novgorod regio 4509 4509 omsk region 1417 1347 1347 2765 orenburg region 387 1933 9768 10154 11701 republic of adygea 1933 5682 1933 5682 altai republic 674 674 674 republic of bashkortosta 2156 2156 2156 the republic of buryatia 2358 2358 2358 the republic of dagestan 337 337 337 republic of kalmykia 657 1933 2358 3015 4290 the republic of karelia 1077 1077 1077 the republic of khakassia 175 175 175 samara region 2526 2526 2526 saratov region 12884 1347 1347 14231 stavropol region 3873 325 4199 4199 ulyanovsk region 1031 1031 chelyabinsk region 2021 2021 2021 total 10320 57991 39887 1523 51730 99401 *according to the territorial planning scheme of the russian federation in the energy sector until 2030. adopted by the rf government decree no. 1634-s dated august 1. 2016 table 8: possibilities to reduce unemployment as a result of implementation of res projects in the regions of russia the subject of the russian federation unemployment rate, people reduction of unemployment (scenario 1), % reduction of unemployment (scenario 2), % altai region 99,645 0.68 0.68 astrakhan region 39,968 8.55 10.81 belgorod region 32,537 1.55 1.55 volgograd region 87,987 3.83 3.83 transbaikal region 57,592 2.34 2.34 irkutsk region 110,160 0.46 0.46 kaliningrad region 31,468 8.19 karachay-cherkess republic 30,937 0.39 12.89 krasnodar region 159,480 3.72 8.08 leningrad region 44,297 8.73 lipetsk region 23,621 6.42 6.42 murmansk region 34,334 15.01 nizhny novgorod region 76,281 5.91 omsk region 75,652 1.78 3.65 orenburg region 50,005 20.31 23.40 republic of adygea 18,231 10.60 31.17 altai republic 11,880 5.67 5.67 republic of bashkortostan 115,975 1.86 1.86 the republic of buryatia 43,504 5.42 5.42 the republic of dagestan 146,163 0.23 0.23 republic of kalmykia 15,347 19.64 27.96 the republic of karelia 30,183 3.57 3.57 the republic of khakassia 16,309 1.07 1.07 samara region 71,865 3.52 3.52 saratov region 63,657 2.12 22.36 stavropol region 78,336 5.36 5.36 ulyanovsk region 29,721 3.47 chelyabinsk region 130,464 1.55 1.55 total 1,725,599 3.00 5.76 nazarova, et al.: increase of social impact due to the development of the renewable energy industry in russia international journal of energy economics and policy | vol 7 • issue 5 • 2017270 references alvarez, g.c., jara, r.m., julián, j.r.r., bielsa, j.i.g. (2009), study of the effects on employment of public aid to renewable energy sources. madrid: universidad rey juan carlos. barbosea, g., wiser, r., heeterb, j., mai, t., bird, l., bolinger, m., carpenter, a., heath, g., keyser, d., macknick, j., mills, a., millstein, d. (2016), a retrospective analysis of benefits and impacts of u.s. renewable portfolio standards. energy policy, 96, 645-660. bezrukikh, p., bezrukikh, p. (2014), ob indikatorakh sostoyaniya energetiki i efektivnosti vozobnovlyaemoy energetiki v usloviyakh ekonomicheskogo krizisa [on indicators of the state of energy and efficiency of renewable energy in the conditions of economic crisis]. voprosy economiki, 8, 92-105. cebotari, s., benedek, j. (2017), renewable energy project as a source of innovation in rural communities: lessons from the periphery. sustainability, 9(4), 169-185. dai, h., xie, x., xie, y., liu, j., masui, t. (2016), green growth: the economic impacts of large-scale renewable energy development in china. applied energy, 162, 435-449. del rio, p., burguillo, m. (2008), assessing the impact of renewable energy deployment on local sustainability: towards a theoretical framework. renewable and sustainable energy reviews, 5, 1325-1344. dvorak, p., martinat, s., horst, d., frantal, b., tureckova, k. (2017), renewable energy investment and job creation; a cross-sectoral assessment for the czech republic with reference to eu benchmarks. renewable and sustainable energy reviews, 69, 360-368. grechukhina, i.a., kudryavtseva, o.v., yu, y.e. (2016), evaluation of the development of the renewable energy markets in russia. economy of region, 12(4), 1167-1177. kammen, d.m., kapadia, k., fripp, m. (2004), putting renewables to work: how many jobs can the clean energy industry generate. berkeley: rael report, university of california. kopylov, a. (2015), economika vie [economics of res]. moscow: grifon. p289-302. lehr, u., nitsch, j., kratzat, m., lutz, c., edler, d. (2008), renewable energy and employment in germany. energy policy, 1, 108-117. nazarova, y.a., sopilko, n.y., orlova, a.f., bolotova, r.s.h., gavlovskaya, g.v. (2017), evaluation of development prospects of renewable energy source for russia. international journal of energy economics and policy, 7(3), 1-6. renewable energy and its impact on rural development and sustainability in the uk. (2003), newcastle: adas consulting ltd, university of newcastle. renewable energy and jobs. (2016), renewable energy and jobs, international renewable energy agency. abu dhabi: irena. rutovitz, j., harris, s. (2012), calculating global energy sector jobs: 2012 methodology. broadway: institute for sustainable futures, uts. ulrich, p., distelkamp, m., lehr, u. (2012), employment effects of renewable energy expansion on a regional level-first results of a model-based approach for germany. sustainability, 4, 227-243. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 3 • 2023 279 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(3), 279-291. the environmental kuznets curve and renewable energy consumption: a review haider mahmood1*, muhammad shahid hassan2, soumen rej3, maham furqan4 1department of finance, college of business administration, prince sattam bin abdulaziz university, 173 alkharj 11942, saudi arabia, 2department of economics and statistics, dr. hassan murad school of management, university of management and technology, lahore, pakistan, 3university of petroleum and energy studies, india, 4school of public policy, oregon state university, corvallis, or 97331, usa. *email: haidermahmood@hotmail.com received: 23 january 2023 accepted: 27 april 2023 doi: https://doi.org/10.32479/ijeep.14270 abstract renewable energy consumption (rec) would reduce pollution and a large pool of literature has probed the environmental kuznets curve (ekc) including rec in a panel or a country-specific model. the present study reviewed 69 empirical studies and found that 57 out of 69 studies validated the ekc but 12 studies did not confirm the ekc. out of these, 64 studies found that rec reduced emissions. in the country-specific analyses, 18 out of 25 studies validated the ekc and 24 out of 25 studies substantiated that rec reduced emissions. in the panel studies, 39 out of 44 studies validated the ekc and 40 out of 44 studies found that rec reduced emissions. comparatively, panel studies reported more evidence of the ekc compared to country-specific studies. however, country-specific studies reported more evidence of the positive environmental effect of rec. the results of logistic regression show that the chance of the validity of the ekc is 4.82 times more in the studies if rec reduced emissions in a model. thus, future studies on ekc testing should include rec in the model. in comparison, panel studies carry more chance of confirmation of the ekc than country-specific studies. keywords: renewable energy consumption, the environmental kuznets curve, the panel studies, country-specific studies jel classifications: o44, p18, q20 1. introduction the issue of pollution emissions and global warming is hot in the present environmental and energy economic literature. renewable energy consumption (rec) would reduce emissions from economic activities and increase carbon productivity. but, the generation of renewable sources of energy and technologies needs a lot of research and development (r&d) activities and investment, which may be supported by public finance. moreover, the economic growth of any country may demand and generate the renewable energy market (apergis and payne, 2010). here, we cannot ignore the discussions of the environmental kuznets curve (ekc). fossil fuel would be used more during the 1st phase of economic growth, which would damage the environment (grossman and kreuger, 1991). thus, the government of a country may impose pollution taxes to avoid such damages. here, government regulators are policy suppliers. later, the communities require a clean atmosphere after a threshold point of growth, and the community is a policy demander for a clean environment. this demand forces the government of a country to make tight environmental regulations and to support the r&d activities to generate renewable energy projects (komen et al., 1997). thus, a technique effect may emerge at this stage to support the rec in the economy and rec would help in tracing the 2nd phase of the ekc. the initial cost of installation of renewable energy projects might be high. thus, the government might support renewable energy projects by providing tax incentives and subsidies. moreover, the increasing rec may also increase the competitiveness of a country this journal is licensed under a creative commons attribution 4.0 international license mahmood, et al.: the environmental kuznets curve and renewable energy consumption: a review international journal of energy economics and policy | vol 13 • issue 3 • 2023280 in the international market (jordan‐korte, 2011). thus, producers might shift to rec to reduce social costs (owen, 2006), to get taxincentive, and to avoid pollution tax on their production. from the policy perspective to promote rec, green certificate policies can be used to promote renewable portfolio standards. this policy motivates power suppliers to buy renewable energy (re) plants (wang et al., 2020). further, subsidies and renewable energy certificates can be provided for re investment (ozge et al., 2020; ge et al., 2019). thus, investment in renewable technology would increase re generation (genus and iskandarova, 2020). moreover, an optimum pricing policy should be designed by providing subsidized to have long-run stable returns from the re producers (wang et al., 2016). overall, the market mechanism is very important to accelerate rec at a large scale (yu et al., 2019). however, re production may cause congestion to the power system and an optimum re production plan should be provided to reduce the congestion (reza et al., 2017). moreover, administrative problems and market obstacles would slow down the process of re transition (liu et al., 2018), which should be resolved. r&d and innovations in new technologies of re are essential for renewable energy transition (ret) in an economy to replace the old energy technologies. however, ret also needs time to diffuse in the industry and the whole economy. moreover, social and market acceptance are required to diffuse the new technologies (wüstenhagen et al., 2007). the adoption of new energy needs an educational program to diffuse (negro et al., 2012) and academic research should support the innovation process to be generalized. the process of development of new energies is started with academic research and the government of any country would play a significant role to accelerate the innovation for cleaner technologies. afterward, knowledge transfer is required to diffuse technologies among all stakeholders (gallagher et al., 2012). nevertheless, a lack of energy infrastructure and political reasons may become a hurdle in the way of ret (tsoutsos and stamboulis, 2005). however, economies of scale may foster the process of adaptation to new technologies. moreover, entrepreneurs would implement new technologies and may support technology diffusion. in addition, the financial market would also finance new green technology projects (tamazian et al., 2009). the theoretical literature on rec motivates a lot of empirical studies in testing the role of rec in tracing the ekc. some review studies conducted in the ekc literature on some macroeconomic indicators of pollution (saini and sighania, 2019; liobikienė, 2020; leal and marques, 2022; chang et al., 2017). isa et al. (2015) reviewed the relationship between growth and energy use. other studies focused on the scientific aspects of re i.e., re trading and generation (huang and li, 2022), re integration in smart grids (godoy simões et al., 2019), uncertainty in predicting methods for re power (li et al., 2021), the role of re in generation expansion planning (dagoumas and koltsaklis, 2019), sustainable re supply chain (fontes and freires, 2018), bayesian networks in re system (borunda et al., 2016), technology diffusion in re technology (rao and kishore, 2010), optimized methods to renewable energy (banos et al., 2011), and re policy mechanisms (cheng and yi, 2017). however, a comprehensive review study is missing to present a complete role of rec in emissions and shaping the ekc, which is the main motivation behind this review study. 2. rec and global co2 emissions trends to capture the snapshot of the rec and emissions relationship, we collect the global data from bp (2022) and global carbon atlas (2022). figure 1 shows that the rec trend is upward but still the percentage of rec in primary energy consumption (pec) is meager in figure 2. figure 3 shows the scatterplot of rec and territorial emissions nexus. a positive relationship shows that rec could not help to reduce total territorial emissions. however, figures 4 and 5 show a minute negative effect of rec on per-person emissions and territorial emissions per unit of gross domestic product (gdp). thus, rec helped to increase carbon productivity and to reduce per capita emissions. figure 6 shows the scatterplot of the positive relationship between rec and consumption-based emissions. thus, rec is increasing total consumption-based emissions. however, figures 7 and 8 show a negative impact of rec on per-person emissions and figure 1: primary energy consumption and renewable energy consumption trends mahmood, et al.: the environmental kuznets curve and renewable energy consumption: a review international journal of energy economics and policy | vol 13 • issue 3 • 2023 281 figure 2: percentage of renewable energy consumption in primary energy consumption figure 3: renewable energy consumption and territorial emissions relationship figure 4: renewable energy consumption and per person territorial emissions relationship figure 6: renewable energy consumption and consumption emissions relationship figure 5: renewable energy consumption and territorial emissions per gross domestic product unit relationship consumption-based emissions per unit of gdp. thus, rec helped to increase carbon productivity in terms of consumption-based emissions and reduced per capita consumption-based emissions as well. the above figures expose a complex relationship between rec and emissions, which motivates a lot of literature to capture the exact relationship in different regions of the globe. section 3 presents a comprehensive review of the literature in this regard. 3. literature review 3.1. the testing of the ekc including rec in country-specific analysis first, we discuss the studies investigating the ekc in countryspecific analyses and table 1 shows a summary. for instance, ohler (2015) investigated the us from 1990 to 2008 and found that rec could not decrease co2 emissions. moreover, the ekc was mahmood, et al.: the environmental kuznets curve and renewable energy consumption: a review international journal of energy economics and policy | vol 13 • issue 3 • 2023282 not validated. benavides et al. (2017) investigated austria from 1970 to 2012 using the autoregressive distributive lag (ardl) and found that rec reduced methane emissions (ch4). moreover, the ekc was validated. paweenawat and plyngam (2017) investigated thailand from 1986 to 2012 by using the ardl technique and found that rec did not reduce co2 emissions in the manufacturing sector. in addition, the ekc was also corroborated. shahbaz et al. (2017) investigated the us economy from 19602016 by using ardl and found that biomass energy, exports, and imports reduced co2 emissions. moreover, the ekc was also substantiated. dogan and ozturk (2017) investigated the us from 1980 to 2014 by using ardl and found that rec reduced co2 emissions. non-rec increased emissions and the ekc was not validated. solarin et al. (2017) studied china and india from 1965 to 2013 by using ardl and found that hydroelectricity consumption reduced co2 emissions. urbanization increased emissions and the ekc was validated in both countries. el-aasar and hanafy (2018) examined the egyptian economy from 1971 to 2012 by using the ardl technique and found that rec reduced ghg emissions. however, the ekc was not corroborated, and trade openness also did not affect ghg emissions. bekhet and othman (2018) examined malaysia from 1971 to 2015 and found that rec reduced co2 emissions. however, the ekc was not confirmed in malaysia. in another study, gill et al. (2018) examined malaysia from 1970 to 2011 by using the ardl framework and found that rec decreased co2 emissions. however, the ekc was not found valid in their analysis. dong et al. (2018) investigated china considering ardl, fmols, and dols in a sample period ranging from 1993-2016 and confirmed the evidence of the ekc hypothesis. rec also reduced emissions. sinaga et al. (2019) investigated malaysia from 1978 to 2016 using ardl and found that hydroelectricity reduced co2 emissions. moreover, the ekc was also validated. sasana and aminata (2019) investigated indonesia from 1990 to 2014 using regression analysis and noticed that rec decreased co2 emissions. nevertheless, the ekc was not substantiated, and economic growth, population, and primary energy accelerated co2 emissions. saudi et al. (2019) applied the ardl for the malaysian economy from 1980 to 2017 and substantiated the ekc. they further found that rec significantly reduced carbon emissions in malaysia. stadniczeńko (2020) explored poland from 1980 to 2018 by using the ardl technique and found that rec reduced co2 emissions. the ekc was also validated. in koc and bulus’s (2020) study, we see that gdp significantly left an n-shaped influence on emissions in south korea. they considered the ardl approach from 1971 to 2017 and further exposed that rec reduced emissions. ridzuan et al. (2020) analyzed malaysia from 1978 to 2016 by using ardl and found that rec, crops, and fisheries reduced co2 emissions. the ekc was also validated. sarkodie et al. (2020) investigated china from 1961 to 2016 by using ardl and found that fossil fuels increased co2 emissions. rec reduced emissions and the ekc was corroborated. sharif et al. (2020) investigated turkey from 1965 to 2017 and validated the ekc by using ardl and found that rec reduced ecological footprint. muchran et al. (2021) tested the inverted u-shaped relationship in the indonesian economy. they considered the ardl from 1980 to 2018 and confirmed the ekc. the empirical findings further concluded that rec reduced carbon emissions. nguyen et al. (2021) utilized the ardl from 1980-2018 and found a u-shaped influence of per capita gdp growth on carbon emissions while rec reduced emissions in vietnam. the validity of the ekc was also tested by salari et al. (2021) for 50 us states. after using the system gmm technique over the period from 1997 to 2016, they concluded that per capita gdp had an inverted u-shaped effect on carbon emissions while energy consumption in aggregated and disaggregated forms significantly enhanced carbon emissions. rec was significantly reducing emissions. besides them, murshed et al. (2021) utilized the ardl, fmols, and dols estimators over the sample from 1980 to 2015 and found the ekc in bangladesh. further, hydropower consumption as a proxy for rec significantly curtailed emissions. afterward, pata (2021) utilized fmols and dols from 19802016 and substantiated the validity of the ekc in the us. the results further uncovered that rec played a facilitating role in reducing pollution. murshed et al. (2022a) investigated argentina figure 8: renewable energy consumption and per person consumption emissions relationship figure 7: renewable energy consumption and per person consumption emissions relationship mahmood, et al.: the environmental kuznets curve and renewable energy consumption: a review international journal of energy economics and policy | vol 13 • issue 3 • 2023 283 table 1: the ekc testing in the country-specific analyses authors journal sample period geographical sample technique pollution proxy the ekc is validated or not the effect of rec on pollution ohler (2015) the energy journal 1990–2008 the us panel regression co2 no reducing benavides et al. (2017) ijeep 1970–2012 austria ardl ch4 yes reducing paweenawat and plyngam (2017) economics bulletin 1986–2012 thailand ardl co2 yes no effect shahbaz et al. (2017) energy economics 1960–2016 the us ardl co2 yes reducing dogan and ozturk (2017) espr 1980–2014 the us ardl co2 no reducing solarin et al. (2017) rser 1965–2013 china and india ardl co2 yes reducing el-aasar and hanafy (2018) ijeep 1971–2012 egypt ardl co2 no reducing bekhet and othman (2018) energy economics 1971–2015 malaysia ardl co2 no reducing gill et al. (2018) eds 1970–2011 malaysia ardl co2 no reducing dong et al. (2018) jcp 1993–2016 china ardl, fmols, and dols co2 yes reducing sinaga et al. (2019) ijeep 1978–2016 malaysia ardl co2 yes reducing sasana and aminata (2019) ijeep 1990–2014 indonesia multiple regression model co2 no reducing saudi et al. (2019) ijeep 1980–2017 malaysia ardl co2 yes reducing stadniczeńko (2020) ijeep 1980–2018 poland ardl co2 yes reducing koc and bulus (2020) espr 1971–2017 south korea ardl co2 yes reducing ridzuan et al. (2020) resources, conservation and recycling 1978–2016 malaysia ardl co2 yes reducing sarkodie et al. (2020) science of the total environment 1961–2016 china ardl co2 yes reducing sharif et al. (2020) sustainable cities and society 1965q1– 2017q4 turkey ardl ecological footprint yes reducing muchran et al. (2021) ijeep 1980–2018 indonesia ardl co2 yes reducing nguyen et al. (2021) ijeep 1980–2018 vietnam ardl co2 no reducing salari et al. (2021) economic analysis and policy 1997–2016 50-us states system generalized method of movement co2 yes reducing murshed et al. (2021) espr 1980–2015 bangladesh ardl, fmols, dols co2 and ghg yes reducing pata (2021) espr 1980–2016 the us fmols and dols co2 and ecological footprints yes reducing murshed et al. (2022a) espr 1971–2014 argentina ardl co2 yes reducing bouyghrissi et al. (2022) espr 1980–2017 morocco ardl co2 yes reducing ijeep: international journal of energy economics and policy, espr: renewable and sustainable energy reviews, espr: environmental science and pollution, ghg: greenhouse gas, eds: environment, development and sustainability, jcp: journal of cleaner production, ekc: environmental kuznets curve, rec: renewable energy consumption, ardl: autoregressive distributive lag, fmols: fully modified ordinary least square, dols: dynamic ordinary least square from 1971 to 2014 by using ardl and found that rec and innovation reduced co2 emissions. globalization increased emissions and the ekc was validated. bouyghrissi et al. (2022) investigated morocco from 1980 to 2017 by using ardl and found that rec reduced, and foreign direct investment (fdi) and financial development increased co2 emissions. the ekc was also validated. 3.2. the testing of the ekc including rec in the panel analyses after discussion of the ekc studies in a single country, we reviewed the studies investigating the ekc in a panel and table 2 displays these studies. for instance, sharma (2011) examined 69 countries from 1985 to 2005 by using the gmm approach and found that rec and urbanization reduced co2 emissions. mahmood, et al.: the environmental kuznets curve and renewable energy consumption: a review international journal of energy economics and policy | vol 13 • issue 3 • 2023284 table 2: the ekc testing in the panel analyses authors journal sample period geographical sample technique pollution proxy the ekc is validated or not the effect of rec on pollution sharma (2011) applied energy 1985–2005 69 countries gmm co2 yes reducing burke (2012) australian journal of agricultural and resource economics 1960–2006 105 countries binomial dependent variable modeling co2 yes reducing ben jebli et al. (2015) african development review 1980–2010 24 ssa economies cointegration and causality tests co2 no no effect halkos and psarianos (2016) environmental economics and policy studies 1990–2011 43 countries gmm co2 no reducing dogan and seker (2016) renewable energy 1980–2012 15 eu countries dols co2 yes reducing jebli et al. (2016) ecological indicators 1980–2010 25-oecd countries fmols and dols co2 yes reducing al-mulali et al. (2016) ecological indicators 1980–2010 7 regions in the globe dols co2 yes, except for ssa and mena reducing, except ssa and mena zaghdoudi (2017) economics bulletin 1990–2015 oecd fmols and dols co2 yes reducing hasnisah et al. (2019) ijeep 1980–2014 13 asian countries fmols and dols co2 yes no effect ng et al. (2019) international journal of business and society 1990–2013 25 oecd countries fmols and dols co2 yes reducing majeed and luni (2019) pakistan journal of commerce and social sciences 1990–2017 166 countries fixed effects (fe) and random effect (re) co2 no reducing baležentis et al. (2019) resources, conservation and recycling 1995–2015 27 eu nations fmols and dols ghg yes reducing lau et al. (2019) economic modelling 1995–2015 18 oecd countries gmm co2 yes reducing zafar et al. (2019) resources policy 1990–2016 g-7 and n-11 bootstrap panel cointegration method co2 yes reducing salim et al. (2019) applied economics 1980–2015 selected asian developing countries ardl co2 yes reducing sharif et al. (2019) renewable energy 1990–2015 74 economies fmols and cross-sectional dependence (cd) tests co2 yes reducing ehigiamusoe (2020) the singapore economic review 1990–2016 asia pmg co2 yes reducing florea et al. (2020) agricultural economics 2000–2017 11 european economies ardl ghg no reducing dong et al. (2020) the world economy 1995–2015 120 countries gmm co2 yes reducing elshimy and el-aasar (2020) environment, development and sustainability 1980–2014 arab world ardl carbon footprint yes reducing hanif et al. (2020) environment, development and sustainability 1990–2017 16 oecd and 14 non-oecd nations re co2 yes reducing vural (2020) resources policy 1980–2014 8 ssa nations dols co2 yes reducing kamoun et al. (2020) journal of the knowledge economy 1990–2013 13 oecd countries gmm net savings from emissions yes reducing (contd...) mahmood, et al.: the environmental kuznets curve and renewable energy consumption: a review international journal of energy economics and policy | vol 13 • issue 3 • 2023 285 authors journal sample period geographical sample technique pollution proxy the ekc is validated or not the effect of rec on pollution danish et al. (2020) sustainable cities and society 1992–2016 brics fmols and dols ecological footprints yes reducing aydogan, and vardar (2020) international journal of sustainable energy 1990–2014 e-7 fmols and dols co2 yes no effect ahmad et al. (2021) economics of innovation and new technology 1990–2014 26 oecd nations fmols co2 yes reducing nathaniel et al. (2021a) studies of applied economics 1990–2016 mena nations fmols and dols ecological footprint yes reducing khan et al. (2021) applied economics 1987–2017 rcep countries cs-ardl co2 yes reducing tian et al. (2021) structural change and economic dynamics 1995–2015 g-20 countries fmols and dols co2 yes reducing nathaniel et al. (2021b) espr 1990–2017 g7 amg co2 yes no effect xue et al. (2021) sustainability 1990–2014 south asia fe, re, gmm, and amg ecological footprint yes reducing mehmood (2022) espr 1990–2017 pakistan, india, bangladesh, sri lanka cs-ardl co2 yes reducing jun et al. (2022) economic research-ekonomska istraživanja 1995–2019 top-10 carbon emitter countries cs cointegration co2 yes reducing jena et al. (2022) espr 1980–2016 china, india, and japan pmg co2 and ecological footprint yes reducing saqib et al. (2022) frontiers in environmental science 1995–2019 e-7 countries cs-ardl and amg co2 yes reducing sarwat et al. (2022) espr 1990–2014 brics countries fmols, dols, and panel quantile regression co2 yes reducing yu-ke et al. (2022) renewable energy 1995–2019 42-high polluting countries pmg transport and production -based emissions yes reducing yang et al. (2022) renewable energy 1995–2018 e-7 countries mmqr co2 yes reducing murshed et al. (2022b) energy sources, part b 1995–2015 south asia amg ecological footprint yes reducing djellouli et al. (2022) renewable energy 2000–2015 africa pmg co2 no reducing afshan et al. (2022) renewable energy 1990-2017 oecd mmqr ecological footprint yes reducing gao et al. (2023) resources policy 1990–2021 top-31 carbon emitting countries pmg carbon emissions from industrial production yes reducing saqib et al. (2023) espr 1990–2020 g-7 countries cs-ardl, amg ecological footprint yes reducing jahanger et al. (2023) sustainable energy technologies and assessments 1990–2020 top-10 manufacturing countries mmqr ghg yes reducing amg: augmented mean group, mmqr: method of moments of quantile regression, brics: brazil, russia, india, china, and south africa, pmg: pooled mean group, ekc: environmental kuznets curve, rec: renewable energy consumption table 2: (continued) https://www.sciencedirect.com/journal/sustainable-cities-and-society https://www.sciencedirect.com/journal/sustainable-cities-and-society mahmood, et al.: the environmental kuznets curve and renewable energy consumption: a review international journal of energy economics and policy | vol 13 • issue 3 • 2023286 however, total energy usage and trade increased emissions. moreover, the ekc was also validated. burke (2012) investigated 105 countries from 1960 to 2006 by using binomial dependent variable modeling and found that rec reduced co2 emissions. moreover, the ekc was validated. ben jebli et al. (2015) investigated 24 sub-saharan africa (ssa) economies from 1980 to 2010 by panel cointegration and found that rec could not reduce co2 emissions. exports increased and imports reduced emissions. moreover, the ekc was not validated. halkos and psarianos (2016) investigated 43 economies from 1990 to 2011 by using the gmm approach and found that rec decreased co2 emissions. however, the ekc was not substantiated. dogan and seker (2016) tested the ekc by considering the rec in their study. they used dols for 15 european economies from 1980 to 2012 and founded the ekc. they further confirmed that rec mitigated carbon emissions. jebli et al. (2016) employed fmols and dols from 1980 to 2010 and found the ekc in 25 organization for economic co-operation and development (oecd) countries. they also described that carbon emissions were reduced because of rec. al-mulali et al. (2016) investigated 7 regions in the globe from 1980 to 2010 by using dols and discovered that rec reduced co2 emissions in all regions except ssa and mena. the ekc was also validated in all regions except ssa and mena. zaghdoudi (2017) explored oecd countries from 1990-2015 and found that rec and oil prices reduced emissions. the ekc was substantiated in these economies. hasnisah et al. (2019) examined asia from 1980 to 2014 by using fmols and dols techniques and found that rec reduced emissions and corroborated the ekc. nevertheless, non-rec increased co2 emissions. ng et al. (2019) examined 25 oecd countries from 1990-2013 and found that rec reduced emissions and substantiated the ekc. however, non-rec increased emissions. majeed and luni (2019) investigated 166 economies globally and found that rec from all sources helped in reducing co2 emissions. however, the ekc was not validated. baležentis et al. (2019) explored 27 eu economies from 1995-2015 by using fmols and dols panel techniques and found that biomass and other rec reduced ghg emissions. in addition, the ekc was substantiated. lau et al. (2019) examined 18 oecd economies from 1995 to 2015 by using the gmm and corroborated that nuclear power reduced co2 emissions. moreover, the ekc was also found valid in their analyses and non-rec increased emissions. zafar et al. (2019) examined g-7 and n-11 economies from 1990 to 2016 by using the bootstrap approach and found that rec reduced emissions and corroborated the ekc. the banking sector reduced carbon intensity in g-7 and increased in n-11. moreover, capital formation increased emissions. salim et al. (2019) explored asian developing economies from 1980 to 2015 by using the ardl technique and found that rec, urbanization, and trade liberalization reduced co2 emissions. moreover, non-rec and population increased emissions, but the ekc was substantiated. sharif et al. (2019) investigated 74 economies from 1990 to 2015 by using fmols and cd-tests and found that rec and financial development reduced co2 emissions. non-rec increased emissions and the ekc was validated. ehigiamusoe (2020) examined asia from 1990 to 2016 by using the pmg and found that rec, fdi, and trade reduced emissions. non-rec increased emissions, but the ekc was substantiated. florea et al. (2020) analyzed 11 european economies in the years 2000–2017 and found that rec reduced ghg emissions. however, the ekc was not substantiated. dong et al. (2020) examined 120 world economies from 1978 to 2016 using gmm and found that rec reduced emissions and corroborated the ekc. elshimy and el-aasar (2020) investigated the arabian economies from 1980 to 2014 by using ardl and found that rec reduced carbon footprint. moreover, non-rec and livestock increased carbon footprint, but the ekc was substantiated. hanif et al. (2020) investigated 16 oecd economies from 1990 to 2017 and found that human capital increased rec, which would help in reducing co2 emissions. moreover, the ekc was also validated. vural (2020) explored 8 ssa economies from 1980 to 2014 and found that rec reduced co2 emissions. moreover, nonrec and trade increased emissions, but the ekc was corroborated. kamoun et al. (2020) explored 13 oecd countries from 1990 to 2013 using gmm and found that rec increased net saving adjusted from emissions and non-rec reduced it. moreover, the ekc was also corroborated. afterward, danish et al. (2020) examined the ekc in brics economies. they considered fmols and dols approaches from 1992 to 2016 and confirmed the validity of ekc for economies as a whole and as individuals. they also provided evidence of the negative effect of rec in curtailing ecological footprint. aydogan and vardar (2020) tested the ekc in seven emerging economies from 1990 to 2014 and found a significant ekc. the results also presented a mitigating effect of rec on co2 emissions. ahmad et al. (2021) explored 26 oecd nations from 1990 to 2014 by using fmols and found that rec and fdi reduced co2 emissions. the ekc was also substantiated. nathaniel et al. (2021a) explored mena economies from 1990 to 2016 and found that rec and urbanization reduced ecological footprint. the ekc was also corroborated. khan et al. (2021) investigated the regional comprehensive economic partnership (rcep) economies from 1987 to 2017 and found that rec and innovative technologies reduced co2 emissions and the ekc was substantiated. tian et al. (2021) examined the ekc in g-20 economies. they applied fmols and dols methods over the period from 1995 to 2015 and substantiated the ekc. rec also reduced emissions. nathaniel et al. (2021b) investigated g7 nations from 1990 to 2017 and found that rec did not reduce but nuclear power decreased emissions. the ekc was substantiated. xue et al. (2021) investigated south asia from 1990 to 2014 and found that rec reduced ecological footprint. fdi and non-rec increased ecological footprint, but the ekc was validated. mehmood (2022) explored south asia using cd-ardl from 1990 to 2017 and concluded that the ekc was corroborated, and rec reduced carbon emissions. jun et al. (2022) investigated the ekc in top-ten carbon-emitting nations. they employed cs-ardl from 1995 to 2019 and established the ekc. they further exposed that rec had a negative impact on carbon emissions. jena et al. (2022) explored the ekc in china, india, and japan from 1980 to 2016 by taking renewable energy as a control variable mahmood, et al.: the environmental kuznets curve and renewable energy consumption: a review international journal of energy economics and policy | vol 13 • issue 3 • 2023 287 and substantiated the ekc. the results also concluded that rec curtailed emissions. saqib et al. (2022) examined the ekc by taking renewable energy as a controlling factor. they utilized csardl and amg methods for e-7 countries from 1995 to 2019 and supported the ekc. they further disclosed that rec condenses emissions. according to sarwat et al. (2022), gdp growth had a significant and inverted u-shaped impact on emissions in brics economies from 1990 to 2014. the study further exerted a negative effect of rec on emissions. using pmg estimators from 1995 to 2019, yu-ke et al. (2022) found that rec reduced emissions in 42 countries. trade openness reduced carbon emissions while industrial production significantly enhanced emissions. the ekc was also substantiated. yang et al. (2022) investigated e-7 countries from 1995 to 2018 using mmqr and found that rec reduced emissions in lower quantiles and substantiated the ekc. murshed et al. (2022b) investigated south asia from 1995 to 2015 using amg and found that intra-regional trade, rec, and fdi reduced the ecological footprint. the ekc was also corroborated. djellouli et al. (2022) investigated africa from 2000-2015 using pmg and found that rec reduced co2 emissions and fdi increased emissions. but the ekc was not substantiated. afshan et al. (2022) investigated oecd economies from 1990-2017 using mmqr and found that rec and innovation reduced ecological footprint. the ekc was also validated. gao et al. (2023) tested the role of renewable energy in the ekc model of top-polluted economies from 1990-2021 and substantiated the ekc. moreover, rec reduced pollution. saqib et al. (2023) investigated the ekc in g-7 nations by taking rec in a model. using cs-ardl and amg techniques from 1990 to 2020, the study substantiated the ekc hypothesis. besides this, rec reduced ecological footprint. jahanger et al. (2023) studied the top 10 manufacturing countries from 1990 to 2020 by using mmqr and found that rec, technology, and energy efficiency reduced ghg emissions. the ekc was also validated. 4. analyses and discussions table 3 shows a summary of the validity of the ekc in the 69 reviewed studies. 57 out of 69 studies validated the ekc and 12 studies could not find the validity of the ekc. out of these, 64 studies reported that rec helped to reduce emissions and 5 studies reported the insignificant effect of rec on emissions. in the country-specific studies, 18 out of 25 studies validated the ekc and 7 studies did not validate the ekc. out of these, 24 studies found that rec reduced emissions and 1 study found an insignificant effect of rec on emissions. in the panel studies, 39 out of 44 studies confirmed the ekc and 5 studies could not find the validity of the ekc. out of these, 40 studies found that rec helped to reduce emissions and 4 studies found the insignificant effect of rec on emissions. in comparison, 88.6% of panel studies found the validity of the ekc and 72% of country-specific studies reported the validity of the ekc. alternatively, 96% of country-specific studies reported that rec reduced emissions. however, 90.9% of panel studies could find that rec reduced emissions. thus, the ekc in panel studies is more pronounced than in country-specific studies and the positive environmental contribution of the rec is more evident in country-specific studies compared to the panel studies. table 4 shows logistic regression estimates to test the effect of rec on the validity of the ekc. the dependent variable carries 1 if the ekc is validated and 0 otherwise. the independent variable carries 1 if the rec reduced emissions and 0 otherwise. all results show positive effects. if rec reduced emissions, then the chance of the validity of the ekc is increasing. the results from a sample of all studies show that chance of the validity of the ekc is 4.82 times (e1.5724) more than the non-validity of the ekc if rec reduced emissions in a model. in comparison, the coefficient of panel studies is much higher than the coefficient of country-specific studies. thus, the chance of the validity of the ekc is more in the panel studies (e2.1857 = 8.98 times) compared to country-specific studies (e0.8873 = 2.43 times) if rec reduced emissions in a model. 5. conclusion rec would reduce emissions to shape the ekc. the present study discusses the theoretical argument for the relationship between rec and the ekc. moreover, we conducted a review of the 69 empirical studies investigating the ekc hypothesis in country-specific and panel analyses. we find that 57 out of 69 studies validated the ekc but 12 studies did not confirm the ekc. moreover, 64 studies found that rec reduced emissions and 5 studies substantiated the insignificant effect of rec on emissions. in the country-specific analyses, 18 out of 25 studies proved the ekc and 7 studies could not validate the ekc. further, 24 studies substantiated that rec reduced emissions and 1 study could not find this evidence. in the panel studies, 39 out of 44 studies validated the ekc and 5 studies did not confirm the ekc. moreover, 40 studies reported that rec reduced emissions and 4 studies found an insignificant effect of rec on emissions. overall, 88.6% of panel studies reported the validity of the ekc and 72% table 3: summary of the ekc and rec results studies the ekc is valid no. of studies rec reduce emissions no. of studies all studies yes 57 yes 64 no 12 no 5 country specific studies yes 18 yes 24 no 7 no 1 panel studies yes 39 yes 40 no 5 no 4 ekc: environmental kuznets curve, rec: renewable energy consumption table 4: logistic regression: the ekc is validated as a dependent variable studies coefficient (p-value) all studies rec reduce emissions 1.5724 (0.0000) country-specific studies rec reduce emissions 0.8873 (0.0480) panel studies rec reduce emissions 2.1957 (0.0000) ekc: environmental kuznets curve, rec: renewable energy consumption mahmood, et al.: the environmental kuznets curve and renewable energy consumption: a review international journal of energy economics and policy | vol 13 • issue 3 • 2023288 of country-specific studies substantiated the ekc. in contrast, 96% of country-specific studies found that rec reduced emissions and 90.9% of panel studies could validate it. therefore, panel studies reported greater evidence of the ekc, and the positive environmental effects of the rec are reported more by countryspecific studies. we also tested the effect of rec on the ekc by using logistic regression in a full sample of 69 studies and found that the chance of the validity of the ekc is 4.82 times more in the studies if rec reduced emissions in a model. in the same way, the chance of the validity of the ekc is 8.98 times more in the panel studies and 2.43 times more in the country-specific studies, if rec reduced emissions in a model. comparatively, the chance of the ekc is found more in the panel studies compared to country-specific studies. moreover, rec has been proven to be an important component of the ekc model. thus, we recommend future ekc studies to include rec in the model. 6. funding this study was sponsored by the prince sattam bin abdulaziz university via project number 2023/rv/03. references afshan, s., ozturk, i., yaqoob, t. (2022), facilitating renewable energy transition, ecological innovations and stringent environmental policies to improve ecological sustainability: evidence from mmqr method. renewable energy, 196, 151-160. ahmad, m., khan, z., rahman, z.u., khattak, s.i., khan, z.u. (2021), can innovation shocks determine co2 emissions (co2e) in the oecd economies? a new perspective. economics of innovation and new technology, 30(1), 89-109. al-mulali, u., ozturk, i., solarin, s.a. (2016), investigating the environmental kuznets curve hypothesis in seven regions: the role of renewable energy. ecological indicators, 67, 267-282. apergis, n., payne, j.e. (2010), renewable energy consumption and economic growth: evidence from a panel of oecd countries. energy policy, 38(1), 656-660. aydogan, b., vardar, g. (2020), evaluating the role of renewable energy, economic growth and agriculture on co2 emission in e7 countries. international journal of sustainable energy, 39(4), 335-348. baležentis, t., streimikiene, d., zhang, t., liobikiene, g. (2019), the role of bioenergy in greenhouse gas emission reduction in eu countries: an environmental kuznets curve modelling. resources, conservation and recycling, 142, 225-231. banos, r., manzano-agugliaro, f., montoya, f.g., gil, c., alcayde, a., gómez, j. (2011), optimization methods applied to renewable and sustainable energy: a review. renewable and sustainable energy reviews, 15(4), 1753-1766. bekhet, h.a., othman, n.s. (2018), the role of renewable energy to validate dynamic interaction between co2 emissions and gdp toward sustainable development in malaysia. energy economics, 72, 47-61. ben jebli, m., ben youssef, s., ozturk, i. (2015), the role of renewable energy consumption and trade: environmental kuznets curve analysis for sub-saharan africa countries. african development review, 27(3), 288-300. benavides, m., ovalle, k., torres, c., vinces, t. (2017), economic growth, renewable energy and methane emissions: is there an environmental kuznets curve in austria? international journal of energy economics and policy, 7(1), 259-267. borunda, m., jaramillo, o.a., reyes, a., ibargüengoytia, p.h. (2016), bayesian networks in renewable energy systems: a bibliographical survey. renewable and sustainable energy reviews, 62, 32-45. bouyghrissi, s., murshed, m., jindal, a., berjaoui, a., mahmood, h., khanniba, m. (2022), the importance of facilitating renewable energy transition for abating co2 emissions in morocco. environmental science and pollution research, 29(14), 20752-20767. bp (2022), bp statistical review of world energy 2022. available from: https://www.bp.com/statisticalreview [last accessed on 2022 dec 25]. burke, p.j. (2012), climbing the electricity ladder generates carbon kuznets curve downturns. australian journal of agricultural and resource economics, 56(2), 260-279. chang, r.d., zuo, j., zhao, z.y., zillante, g., gan, x.l., soebarto, v. (2017), evolving theories of sustainability and firms: history, future directions and implications for renewable energy research. renewable and sustainable energy reviews, 72, 48-56. cheng, q., yi, h. (2017), complementarity and substitutability: a review of state level renewable energy policy instrument interactions. renewable and sustainable energy reviews, 67, 683-691. dagoumas, a.s., koltsaklis, n.e. (2019), review of models for integrating renewable energy in the generation expansion planning. applied energy, 242, 1573-1587. danish, ulucak, r., khan, s.u.d. (2020), determinants of the ecological footprint: role of renewable energy, natural resources, and urbanization. sustainable cities and society, 54, 101996. djellouli, n., abdelli, l., elheddad, m., ahmed, r., mahmood, h. (2022), the effects of non-renewable energy, renewable energy, economic growth, and foreign direct investment on the sustainability of african countries. renewable energy, 183, 676-686. dogan, e., ozturk, i. (2017), the influence of renewable and nonrenewable energy consumption and real income on co2 emissions in the usa: evidence from structural break tests. environmental science and pollution research, 24, 10846-10854. dogan, e., seker, f. (2016), determinants of co2 emissions in the european union: the role of renewable and non-renewable energy. renewable energy, 94, 429-439. dong, k., dong, x., jiang, q. (2020), how renewable energy consumption lower global co2 emissions? evidence from countries with different income levels. the world economy, 43(6), 1665-1698. dong, k., sun, r., jiang, h., zeng, x. (2018), co2 emissions, economic growth, and the environmental kuznets curve in china: what roles can nuclear energy and renewable energy play? journal of cleaner production, 196, 51-63. ehigiamusoe, k.u. (2020), the drivers of environmental degradation in asean+ china: do financial development and urbanization have any moderating effect? the singapore economic review, https:// doi.org/10.1142/s0217590820500241. el-aasar, k.m., hanafy, s.a. (2018), investigating the environmental kuznets curve hypothesis in egypt: the role of renewable energy and trade in mitigating ghgs. international journal of energy economics and policy, 8(3), 177-184. elshimy, m., el-aasar, k.m. (2020), carbon footprint, renewable energy, non-renewable energy, and livestock: testing the environmental kuznets curve hypothesis for the arab world. environment, development and sustainability, 22(7), 6985-7012. florea, n.m., badircea, r.m., pirvu, r.c., manta, a.g., doran, m.d., jianu, e. (2020), the impact of agriculture and renewable energy on climate change in central and east european countries. agricultural economics, 66(10), 444-457. fontes, c.h.d.o., freires, f.g.m. (2018), sustainable and renewable energy supply chain: a system dynamics overview. renewable and mahmood, et al.: the environmental kuznets curve and renewable energy consumption: a review international journal of energy economics and policy | vol 13 • issue 3 • 2023 289 sustainable energy reviews, 82, 247-259. gallagher, k.s., grübler, a., kuhl, l., nemet, g., wilson, c. (2012), the energy technology innovation system. annual review of environment and resources, 37(1), 137-162. gao, j., hassan, m.s., kalim, r., sharif, a., alkhateeb, t.t.y., mahmood, h. (2023), the role of clean and unclean energy resources in inspecting n-shaped impact of industrial production on environmental quality: a case of high polluting economies. resources policy, 80, 103217. ge, w., qi, z., yan, l., benjamin, c.m., xunzhang, p. (2019), corrective regulations on renewable energy certificates trading: pursuing an equity-efficiency trade-off. energy economics, 80, 970-982. genus, a., iskandarova, m. (2020), transforming the energy system? technology and organisational legitimacy and the institutionalisation of community renewable energy. renewable and sustainable energy reviews, 125, 109795. gill, a.r., viswanathan, k.k., hassan, s. (2018), a test of environmental kuznets curve (ekc) for carbon emission and potential of renewable energy to reduce green house gases (ghg) in malaysia. environment, development and sustainability, 20(3), 1103-1114. global carbon atlas. (2022), available from: https://w w w. globalcarbonatlas.org/en/co2-emissions [last accessed on 2022 dec25]. godoy simões, m., harirchi, f., babakmehr, m. (2019), survey on time‐domain power theories and their applications for renewable energy integration in smart‐grids. iet smart grid, 2(4), 491-503. grossman, g.m., krueger, a.b. (1991), environmental impacts of the north american free trade agreement. nber. working paper 3914. halkos, g., psarianos, i. (2016), exploring the effect of including the environment in the neoclassical growth model. environmental economics and policy studies, 18(3), 339-358. hanif, n., arshed, n., aziz, o. (2020), on interaction of the energy: human capital kuznets curve? a case for technology innovation. environment, development and sustainability, 22(8), 7559-7586. hasnisah, a., azlina, a.a., che, c.m.i. (2019), the impact of renewable energy consumption on carbon dioxide emissions: empirical evidence from developing countries in asia. international journal of energy economics and policy, 9(3), 135. huang, w., li, h. (2022), game theory applications in the electricity market and renewable energy trading: a critical survey. frontiers in energy research, 10, 1009217. isa, z., alsayed, a.r., kun, s.s. (2015), review paper on economic growth-aggregate energy consumption nexus. international journal of energy economics and policy, 5(2), 385-401. jahanger, a., ozturk, i., onwe, j.c., joseph, t.e., hossain, m.r. (2023), do technology and renewable energy contribute to energy efficiency and carbon neutrality? evidence from top ten manufacturing countries. sustainable energy technologies and assessments, 56, 103084. jebli, m.b., youssef, s.b., ozturk, i. (2016), testing environmental kuznets curve hypothesis: the role of renewable and non-renewable energy consumption and trade in oecd countries. ecological indicators, 60, 824-831. jena, p.k., mujtaba, a., joshi, d.p.p., satrovic, e., adeleye, b.n. (2022), exploring the nature of ekc hypothesis in asia’s top emitters: role of human capital, renewable and non-renewable energy consumption. environmental science and pollution research, 29(59), 88557-88576. jordan‐korte, k. (2011), government promotion of renewable energy technologies a comparison of promotion instruments and national and international renewable energy market development in germany, the united states, and japan. wiesbaden: gabler. jun, w., mughal, n., kaur, p., xing, z., jain, v., cong, p.t. (2022), achieving green environment targets in the world’s top 10 emitter countries: the role of green innovations and renewable electricity production. economic research-ekonomska istraživanja, 35(1), 5310-5335. kamoun, m., abdelkafi, i., ghorbel, a. (2020), the impact of renewable energy on sustainable growth: evidence from a panel of oecd countries. journal of the knowledge economy, 10(1), 221-237. khan, z., murshed, m., dong, k., yang, s. (2021), the roles of export diversification and composite country risks in carbon emissions abatement: evidence from the signatories of the regional comprehensive economic partnership agreement. applied economics, 53(41), 4769-4787. koc, s., bulus, g.c. (2020), testing validity of the ekc hypothesis in south korea: role of renewable energy and trade openness. environmental science and pollution research, 27(23), 29043-29054. komen, r., gerking, s., folmer, h. (1997), income and environmental rd: empirical evidence from oecd countries. environment and development economics, 2, 505-515. lau, l.s., choong, c.k., ng, c.f., liew, f.m., ching, s.l. (2019), is nuclear energy clean? revisit of environmental kuznets curve hypothesis in oecd countries. economic modelling, 77, 12-20. leal, p.h., marques, a.c. (2022), the evolution of the environmental kuznets curve hypothesis assessment: a literature review under a critical analysis perspective. heliyon, 8(11), 11521. li, j., luo, y., yang, s., wei, s.y., huang, q. (2021), review of uncertainty forecasting methods for renewable energy power. high voltage energy, 47, 1144-1157. liobikienė, g. (2020), the revised approaches to income inequality impact on production-based and consumption-based carbon dioxide emissions: literature review. environmental science and pollution research, 27(9), 8980-8990. liu, s., bie, z., lin, j., xi, w. (2018), curtailment of renewable energy in northwest china and market-based solution. energy policy, 123, 494-502. majeed, m.t., luni, t. (2019), renewable energy, water, and environmental degradation: a global panel data approach. pakistan journal of commerce and social sciences, 13(3), 749-778. mehmood, u. (2022), examining the role of financial inclusion towards co2 emissions: presenting the role of renewable energy and globalization in the context of ekc. environmental science and pollution research, 29(11), 15946-15954. muchran, m., idrus, a., badruddin, s., tenreng, m., kanto, m. (2021), influence of the renewable and non-renewable energy consumptions and real-income on environmental degradation in indonesia. international journal of energy economics and policy, 11(1), 599-606. murshed, m., alam, r., ansarin, a. (2021), the environmental kuznets curve hypothesis for bangladesh: the importance of natural gas, liquefied petroleum gas, and hydropower consumption. environmental science and pollution research, 28(14), 17208-17227. murshed, m., mahmood, h., ahmad, p., rehman, a., alam, m.s. (2022a), pathways to argentina’s 2050 carbon-neutrality agenda: the roles of renewable energy transition and trade globalization. environmental science and pollution research, 29(20), 29949-29966. murshed, m., nurmakhanova, m., al-tal, r., mahmood, h., elheddad, m., ahmed, r. (2022b), can intra-regional trade, renewable energy use, foreign direct investments, and economic growth mitigate ecological footprints in south asia? energy sources, part b: economics, planning, and policy, 17(1), 2038730. nathaniel, s.p., adeleye, n., adedoyin, f.f. (2021a), natural resource abundance, renewable energy, and ecological footprint linkage in mena countries. studies of applied economics, 39(2), 1-16. nathaniel, s.p., alam, m.s., murshed, m., mahmood, h., ahmad, p. (2021b), the roles of nuclear energy, renewable energy, and mahmood, et al.: the environmental kuznets curve and renewable energy consumption: a review international journal of energy economics and policy | vol 13 • issue 3 • 2023290 economic growth in the abatement of carbon dioxide emissions in the g7 countries. environmental science and pollution research, 28(35), 47957-47972. negro, s.o., alkemade, f., hekkert, m.p. (2012), why does renewable energy diffuse so slowly? a review of innovation system problems. renewable and sustainable energy reviews, 16(6), 3836-3846. ng, c.f., choong, c.k., ching, s.l., lau, l.s. (2019), the impact of electricity production from renewable and non-renewable sources on co2 emissions: evidence from oecd countries. international journal of business society, 20(1), 365-382. nguyen, t., dang, b.h., tran, t.d.n., su, t.o.h. (2021), the role of renewable energy consumption and fdi in testing the existing of environmental kuznets curve in vietnam. international journal of energy economics and policy, 11(1), 293-301. ohler, a.m. (2015), factors affecting the rise of renewable energy in the us: concern over environmental quality or rising unemployment? the energy journal, 36(2), 97-115. owen, a.d. (2006), renewable energy: externality costs as market barriers. energy policy, 34(5), 632-642. ozge, o., benjamin, f., marit, h., paul, r.k. (2020), capacity vs energy subsidies for promoting renewable investment: benefits and costs for the eu power market. energy policy, 137, 111166. pata, u.k. (2021), renewable and non-renewable energy consumption, economic complexity, co2 emissions, and ecological footprint in the usa: testing the ekc hypothesis with a structural break. environmental science and pollution research, 28(1), 846-861. paweenawat, s.w., plyngam, s. (2017), does the causal relationship between renewable energy consumption, co2 emissions, and economic growth exist in thailand? an ardl approach. economics bulletin, 37(2), 697-711. rao, k.u., kishore, v.v.n. (2010), a review of technology diffusion models with special reference to renewable energy technologies. renewable and sustainable energy reviews, 14(3), 1070-1078. reza, h., hedayat, s., mehdi, a.j. (2017), stochastic planning and scheduling of energy storage systems for congestion management in electric power systems including renewable energy resources. energy, 133, 380-387. ridzuan, n.h.a.m., marwan, n.f., khalid, n., ali, m.h., tseng, m.l. (2020), effects of agriculture, renewable energy, and economic growth on carbon dioxide emissions: evidence of the environmental kuznets curve. resources, conservation and recycling, 160, 104879. saini, n., sighania, m. (2019), environmental impact of economic growth, emission and fdi: systematic review of reviews. qualitative research in financial markets, 11(1), 81-134. salari, m., javid, r.j., noghanibehambari, h. (2021), the nexus between co2 emissions, energy consumption, and economic growth in the us. economic analysis and policy, 69, 182-194. salim, r., rafiq, s., shafiei, s., yao, y. (2019), does urbanization increase pollutant emission and energy intensity? evidence from some asian developing economies. applied economics, 51(36), 4008-4024. saqib, n., sharif, a., razzaq, a., usman, m. (2023), integration of renewable energy and technological innovation in realizing environmental sustainability: the role of human capital in ekc framework. environmental science and pollution research, 30, 6372-16385. saqib, n., usman, m., radulescu, m., sinisi, c.i., secara, c.g., tolea, c. (2022), revisiting ekc hypothesis in context of renewable energy, human development and moderating role of technological innovations in e-7 countries. frontiers in environmental science, 10, 1077658. sarkodie, s.a., adams, s., owusu, p.a., leirvik, t., ozturk, i. (2020), mitigating degradation and emissions in china: the role of environmental sustainability, human capital and renewable energy. science of the total environment, 719, 137530. sarwat, s., godil, d.i., ali, l., ahmad, b., dinca, g., khan, s.a.r. (2022), the role of natural resources, renewable energy, and globalization in testing ekc theory in brics countries: method of moments quantile. environmental science and pollution research, 29(16), 23677-23689. sasana, h., aminata, j. (2019), energy subsidy, energy consumption, economic growth, and carbon dioxide emission: indonesian case studies. international journal of energy economics and policy, 9(2), 117-122. saudi, m.h.m., sinaga, o., jabarullah, n.h. (2019), the role of renewable, non-renewable energy consumption and technology innovation in testing environmental kuznets curve in malaysia. international journal of energy economics and policy, 9(1), 299-307. shahbaz, m., solarin, s.a., hammoudeh, s., shahzad, s.j.h. (2017), bounds testing approach to analyzing the environment kuznets curve hypothesis with structural beaks: the role of biomass energy consumption in the united states. energy economics, 68, 548-565. sharif, a., baris-tuzemen, o., uzuner, g., ozturk, i., sinha, a. (2020), revisiting the role of renewable and non-renewable energy consumption on turkey’s ecological footprint: evidence from quantile ardl approach. sustainable cities and society, 57, 102138. sharif, a., raza, s.a., ozturk, i., afshan, s. (2019), the dynamic relationship of renewable and nonrenewable energy consumption with carbon emission: a global study with the application of heterogeneous panel estimations. renewable energy, 133, 685-691. sharma, s.s. (2011), determinants of carbon dioxide emissions: empirical evidence from 69 countries. applied energy, 88(1), 376-382. sinaga, o., alaeddin, o., jabarullah, n.h. (2019), the impact of hydropower energy on the environmental kuznets curve in malaysia. international journal of energy economics and policy, 9(1), 308-315. solarin, s.a., al-mulali, u., ozturk, i. (2017), validating the environmental kuznets curve hypothesis in india and china: the role of hydroelectricity consumption. renewable and sustainable energy reviews, 80, 1578-1587. stadniczeńko, d. (2020), development and challenges for the functioning of the renewable energy prosumer in poland: a legal perspective. international journal of energy economics and policy, 10(5), 623-630. tamazian, a., chousa, j.p., vadlamannati, k.c. (2009), does higher economic and financial development lead to environmental degradation: evidence from bric countries. energy policy, 37(1), 246-253. tian, x.l., bélaïd, f., ahmad, n. (2021), exploring the nexus between tourism development and environmental quality: role of renewable energy consumption and income. structural change and economic dynamics, 56, 53-63. tsoutsos, t.d., stamboulis, y.a. (2005), the sustainable diffusion of renewable energy technologies as an example of an innovation focused policy. technovation, 25(7), 753-761. vural, g. (2020), how do output, trade, renewable energy and nonrenewable energy impact carbon emissions in selected sub-saharan african countries? resources policy, 69, 101840. wang, h., su, b., mu, h., li, n., gui, s., duan, y., jiang, b., kong, x. (2020), optimal way to achieve renewable portfolio standard policy goals from the electricity generation, transmission, and trading perspectives in southern china. energy policy, 139, 111319. wang, h., zheng, s., zhang, y., kai, z. (2016), analysis of the policy effects of downstream feed-in tariff on china’s solar photovoltaic industry. energy policy, 95, 479-488. wüstenhagen, r., wolsink, m., bürer, m.j. (2007), social acceptance of renewable energy innovation: an introduction to the concept. energy policy, 35(5), 2683-2691. mahmood, et al.: the environmental kuznets curve and renewable energy consumption: a review international journal of energy economics and policy | vol 13 • issue 3 • 2023 291 xue, l., haseeb, m., mahmood, h., alkhateeb, t.t.y., murshed, m. (2021), renewable energy use and ecological footprints mitigation: evidence from selected south asian economies. sustainability, 13(4), 1613. yang, q., huo, j., saqib, n., mahmood, h. (2022), modelling the effect of renewable energy and public-private partnership in testing ekc hypothesis: evidence from methods moment of quantile regression. renewable energy, 192, 485-494. yu, s., zheng, y., li, l. (2019), a comprehensive evaluation of the development and utilization of china’s regional renewable energy. energy policy, 127, 73-86. yu-ke, c., hassan, m.s., kalim, r., mahmood, h., arshed, n., salman, m. (2022), testing asymmetric influence of clean and unclean energy for targeting environmental quality in environmentally poor economies. renewable energy, 197, 765-775. zafar, m.w., zaidi, s.a.h., sinha, a., gedikli, a., hou, f. (2019), the role of stock market and banking sector development, and renewable energy consumption in carbon emissions: insights from g-7 and n-11 countries. resources policy, 62, 427-436. zaghdoudi, t. (2017), oil prices, renewable energy, co2 emissions and economic growth in oecd countries. economics bulletin, 37(3), 1844-1850. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 2 • 202230 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(2), 30-38. building energy consumption prediction using neural-based models adrian-nicolae buțurache1*, stelian stancu2 1economic cybernetics and statistics doctoral school, bucharest university of economic studies, bucharest, romania, 2department of informatics and economic cybernetics, bucharest university of economic studies, bucharest, romania. *email: ad.buturache@yahoo.ro received: 13 november 2021 accepted: 20 january 2022 doi: https://doi.org/10.32479/ijeep.12739 abstract in the recent years digital transformation became one of the most used approaches in building energy consumption optimization. increased interest in improving energy sustainability and comfort inside buildings has created an opportunity for digital transformation to build predictive tools for energy consumption. by retrofitting or implementing new construction technologies nowadays the quantity and quality of the operational data collected has reached unprecedented levels. this data must be consumed by implementing powerful predictive tools that will provide the needed level of certainty. adopting six sigma’s define, measure, analyze, improve, control (dmaic) cycle as predictive analytics framework will make this paper accessible for both professionals working in energy industry and researchers that are developing models, creating the premises for reducing the gap between research and real-world business, guiding the use of data. moreover, the selected strategy for preprocessing and hyperparameter selection is presented, the final selected models showing scalability and flexibility. at the end the architectures, performance and training time are discussed and then coupled with the thought process providing a way to weigh up the options. building energy consumption prediction, it is a relevant and actual topic. firstly, on european level, meeting the targets set by the new european green deal for buildings sector is relying heavily on digitization and therefore on predictive analytics. secondly, on romania level, the liberalization of the energy market created an unpreceded energy price increase. the negative social impact might be diminished not only by the price reduction, but also by understanding how the energy is consumed. keywords: machine learning, artificial neural networks, building energy prediction, six sigma jel classifications: o13, o14, o31, q47, c45, r11 1. introduction energy consumption prediction represents one of the main concerns of the modern world. since the industrial revolution, energy consumption has gained another dimension. our lifestyles and energy consumption habits are increasingly interdependent, encompassing demands for electricity, steam, or hot or chilled water. the cost of energy is increased by the environmental costs associated with the pollution generated by the entire conversion process, from raw resources to refined end-user products. prediction models are essential in energy management and planning. buildings’ energy consumption can be improved in three ways: system improvement, device improvement, and behavior improvement. system and device improvement are closely related to technological advances while behavior is driven by education and awareness. all three development directions should be guided by coherent laws and regulations that are eventually aligned on a global scale. going forward, two main approaches to potentially improve construction have been identified: new buildings should be more efficiently designed than existing buildings and existing buildings should be retrofitted to reduce energy consumption. traditional grid solutions are limited to electrical power distribution, while smart grids represent an evolution of the traditional grid, enabling a two-way interaction this journal is licensed under a creative commons attribution 4.0 international license buțurache and stancu: building energy consumption prediction using neural-based models international journal of energy economics and policy | vol 12 • issue 2 • 2022 31 between suppliers and customers (vrablecová et al., 2018). the main aim is to optimize in real time how energy is delivered to customers. a smart grid must monitor, learn, predict, and drive actions. one of the major challenges in renewable energy is to sustain the continuous supply of power from various production sites in the desired quantity when required. smart grid solutions play a key role in the successful deployment of green energy technologies. energy management systems are responsible for cost minimization and quality optimization and are crucial for smart grid operations. in the last 170 years, the growth rate of global energy consumption has been around 2.4% per year, with no indications that it will decrease (jarvis et al., 2012). during the last 50 years, events such as the rise in oil prices in the 1970s, nuclear accidents, global climate change, renewable and sustainable energy technology breakthroughs, and the rapid growth of emerging economies through industrialization have made energy consumption reduction an important research field, particularly since the demand shows no signs of slowing down (u.s. energy information administration, 2019). the international energy agency (iea) reports that buildings represent the largest energy-consuming sector and that this sector continues to increase annually (international energy agency, 2013, 2018; u.s. energy information administration, 2020). models for predicting energy consumption are divided into two major classifications: based on model type and based on model prediction time horizon. model type can be physical, statistical, machine learning or hybrid, while the model prediction time horizon can be short, medium, or long. the major advantage of machine learning and statistical models is their flexibility. physical modeling can be detailed and precise, but at the same time, it is only appropriate for specific use cases (reimann et al., 2018). building demand for electricity depends on various parameters of the building itself, such as glazing percentage and properties, building fabrics, occupancy pattern, number of floors, level of internal gains, and building purpose (korolija et al., 2013). energy consumption prediction for the medium and long term represents one of the core information sources for strategic and tactical decisions concerning areas such as development directions, capital investment, revenue analysis, or capacity management. the new european green deal is targeting improvements in the way the energy is consumed in the buildings sector. the council of european union highlights two important areas: renovation of the existing buildings to increase their efficiency and ecodriven design for the new buildings to be built. european union renovation wave and innovation fund represents two frameworks made to enable professionals to tackle the challenges on the way to a decarbonized europe. for the already existing buildings and for the new to be built these two frameworks provide the tools, including regulations and financing, to optimize and decrease energy consumption. on top of them are the nextgenerationeu and investeu funds that acts like a binder since are aiming areas like: lead on energy efficient artificial intelligence solutions, data share across eu, usage of technologies to make buildings more energy efficient. the access on energy must be viewed from three different perspectives. first one is related to the infrastructure and its existence, the second is related to the capability of producing the quantity of energy needed and the third is related to the possibility of the end customer to buy the energy. the access on electricity and adoption of the latest technologies is a measure of wellbeing. a healthy and sustainable development will reduce the gaps between different social classes. through digitization and predictive analytics, the existing and limited resources available can be shared in a more even and cheap way, both acting like enablers. up to 90% of the total energy used during a building’s life cycle is used during building operations. of this percentage, up to 20% could be saved through the adoption of a proactive attitude toward energy control and fault detection (ramesh et al., 2010; teke and timur, 2014), in other words by introduction of predictability. this article is providing an overview on the use of neural-based model on predictive analytics of building energy consumption. the focus is on modeling, by identifying and highlighting the theoretical and practical considerations of neural-based algorithms for building energy consumption prediction. in the end, the outcome of the best performing models are compared in terms of resources spent for training and generalization capacity. building energy consumption optimization represents a relevant and actual topic considering all the initiatives started at european level. the guidelines for the upcoming 10 years are clear, and the premises are that this topic will remain relevant and actual at least until 2050. 2. literature review artificial neural networks (anns) represent one of the most used machine learning models for energy consumption prediction (amasyali and el-gohary, 2018). data analysis on a house built to testing new technologies for improving energy efficiency, indoor air quality, and sustainable construction highlighted the benefits of a straightforward approach (biswas et al., 2016). ffnn models were used to predict energy consumption based on weather data gathered over 3 months. energy consumption and hvac equipment data were recorded with a five-minute timestamp. during the data collection process, the house was unoccupied, and the impact of the occupant’s behavior was not included in the data. two ann models based on levenberg-marquardt and owo-newton algorithms were deployed to predict total energy consumption. input data and network topology were the same for both models: three neurons in the input layer, seven neurons in the hidden layer, and one neuron in the output layer. this simple model architecture proved sufficiently powerful to predict energy consumption with coefficients of determination between 0.87 and 0.91. comparison of multiple machine learning techniques showed that ann can perform better than linear regression and support vector machines on long-term prediction. in total, 4 years of data including independent variables such as ambient temperature, installed power capacity, resident electricity consumption, and gross domestic product were used (ekonomou, 2010). in the same long-term energy consumption paradigm and the same types of models, ann, linear regression, and least-squares svm were compared using gross electricity generation, installed capacity, total subscribership, and population as independent variables (ekonomou, 2010). another comparison between machine learning buțurache and stancu: building energy consumption prediction using neural-based models international journal of energy economics and policy | vol 12 • issue 2 • 202232 techniques—this time for short-term prediction, with 15-minute resolution data for day-ahead prediction—proved the superiority of ann over other techniques, such as linear regression, support vector machine, rbf kernel, and nearest neighbor ball tree (chae et al., 2016). a deep learning approach can be tried using lstm algorithms (marino et al., 2016). standard lstmand lstmbased sequence-to-sequence (s2s) architectures were tested on two benchmark datasets, the first with a resolution of 1 h and the second with a resolution of one minute. both datasets were gathered from a single residential customer. s2s architecture performed better on both datasets, while standard lstm architecture was unable to forecast accurately on the dataset with one-minute resolution data. a more extensive analysis was made using lstm (sülo et al., 2019). a bayesian regularization neural network approach was proposed as a simplified approach for predicting a commercial building’s energy consumption (kim et al., 2019). since the data quantity is limited, the authors predict that overfitting is likely to occur. another simplified approach is sensitivity analysis, which has also proven useful in reducing the number of independent variables used in the analysis. comparison of arima, ffnn, dnn, conventional recurrent neural networks (crnns), and lstm for short-, medium-, and long-term prediction revealed that arima, crnn, and lstm are close in terms of performance for short-term predictions, while for mediumand long-term predictions, rnn and lstm outperformed all other models (nugaliyadde et al., 2019). to overcome the varying nature of renewable energy sources, an artificial neural network-based predictive model for optimizing and energy usage schedules can reduce the effects experienced by customers (finck et al., 2019). moreover, compared with a conventional approach, such as the proportional-integral controller, selected flexibility indicators are improved. there is no single best algorithm for energy consumption prediction exists. however, a review of the existing work led strong expectations for the selected path. although ffnn and lstm are completely different models, they still appear in many comparatives analyzes. neural-based modeling approach enable researchers to study building energy consumption without having priori experience in this field. being scalable and flexible these models outperform existing models. furthermore, the key is to understand neural-based modeling fundamentals, industry needs and, in the end, to refine the models to meet the professionals’ expectations. on a macro level the enablers for these neuralbased solutions and any other type of data analytics are all the frameworks proposed on european level where the regulations and fundings are driving digital transformation. on a micro level, the incremental adoption of these solutions will depend on the quality of the results delivered. 3. theoretical fundamentals 3.1. feed forward neural networks anns have the advantage of providing robustness for non-linear problems and offer the possibility of scaling the solution. ann represents a mathematical model of the human nervous system (kumar et al., 2013). ffnns consist of simple calculation units called “neurons” operating in parallel. neurons are organized in layers. each layer can contain one or more neurons. the input layer the same as the output layer represents the only two areas of the network in which interaction with the outside environment is possible. the input layer is used to feed the network with data. the output layer contains the predictions made by the network. consecutive layers are connected, and each connection has a synaptic weight attached. synaptic weights express the importance of a given input at a given time (figure 1). the learning algorithm represents the procedure whereby the synaptic weights are adjusted to minimize the objective function (figure 2). the synaptic weights can be said to store the knowledge. under the supervised learning paradigm, predicted values are compared with real values during the training process. based on the resulting error, all synaptic weights are updated. the function used to determine the difference between actual and predicted values is called the “cost” or “loss”. inside the neuron, u is calculated—the sum of the dot product of every pair as in equation (1). figure 1: feed forward neural network schema figure 2: artificial neuron mathematical abstraction buțurache and stancu: building energy consumption prediction using neural-based models international journal of energy economics and policy | vol 12 • issue 2 • 2022 33 u=w1x1+w2x2+w3x3+b (1) on the summation of the dot product can be added a bias, b, necessary to add robustness and to avoid getting blocked in a local minimum. the activation function is used to trigger or not trigger the neuron once the weighted sum of the inputs exceeds a limit. non-linearity is thus introduced into the neuron output. this feature is important in actual case scenarios since most of the studied problems rely on non-linear data. going forward with the logic, a non-linear model can build non-linear decision boundaries, which will lead to a better model fitting. the rectified linear unit (relu) activation function performs the following operation: f(x) = max (0,x) (2) by its nature, it is more computationally efficient than sigmoid or tanh activation functions. relu overcomes the vanishing gradient problem, enabling speed and performance (glorot et al., 2010). rectified linear units have become popular among machine learning practitioners, with convolutional neural networks used simultaneously for image recognition (kusuma and afiahayati, 2018). the output of the neuron, y is calculated by passing the summation of the dot product through the activation function. the result can or cannot activate the neuron, based on the threshold. y=f(u)=f(w1x1+w2x2+w3x3+b) (3) 3.2. feed forward neural networks recurrent neural networks are neural networks designed for sequential data and predict the next step of the sequence with respect to the sequence’s previous steps. crnns are discretetime dynamical systems that possess an input, an output, and a hidden layer (pascanu et al., 2013). one of their main limitations is attributable to the vanishing and exploding gradients (bengio et al., 1994). the synaptic weight that connects hidden layers of consecutive states (i.e. t-3, t-2, t-1, t, where t is the current state) is the same. if it is too small, the gradient becomes increasingly lower until it vanishes. if it is too large, the gradient becomes increasingly larger until it explodes. this is an effect of the training conducted with gradient-descent based algorithms and computations completed by backpropagation through time (bptt) (werbos, 1990). bptt is similar to the backpropagation (rumelhart et al., 1986) used for ffnns. the main difference is that the gradient is calculated individually for each time step of the rnn, and at the end, the resulting gradients are added. another weakness is due to the information morphing, which reveals the network’s inability to maintain relevant information if the analyzed context contains several time steps (i.e., relevant information occurring at time step t-15 may be lost until the current state t is calculated). to surpass the issues related to the conventional rnn, another type of gradient-based method called lstm was introduced by hochreiter and schmidhuber (1997) (figure 3). this solution proposes adding gating functions to the state dynamics. these functions enable the network’s ability to remember information from the earlier stages. lstm is equipped with three gates: the input, output, and forget gates. compared with the conventional recurrent neural network, which has only one neural network in each cell, lstm has four. the cell’s gates—input, output, and forget—determine which information is passed or blocked and are composed of the neural networks mentioned above. all three gates possess sigmoid-activated neural networks with outputs of 0 and 1. sigmoid t e t � � � � � 1 1 (4) tanh t = e e e +e z t t t � � − − − (5) where t represents the current state. when the value in the gate is 0, the information passing is blocked; when the value in the gate is 1, the information can pass through the gate in its entirety. long-term memory cells are described using the following equations: ft=σ (xtu f+ht–1w f) (6) it=σ (xtu i+ht–1w i) (7) c = tanh x u +h wt t g t 1 g  −� � (8) c = ã f c +i ct t t-1 t t � � (9) ot=σ (xtu o+ht–1w o) (10) ht=tanh (ct) it (11) the first equation is the forget gate and is used to decide how much of the information will be ignored and how much will be stored in the current cell state. equations (7) and (8) control how much of the new computed information will be written in the cell state ct. ct  is the vector of the new candidate values for the current state cell. the current state calculation is a function of the previous cell state, ct-1, multiplied by (taking the decision on what to forget from the previous state). to this is added ct but only after multiplication with the input gate. this multiplication basically allows only a certain amount of the input information to be part of the current state (9). at the end, the output is composed figure 3: lstm cell buțurache and stancu: building energy consumption prediction using neural-based models international journal of energy economics and policy | vol 12 • issue 2 • 202234 of (10) and (11), representing the output gate and the hidden state output. the output gate determines what information is used for prediction and determines what information is sent to the next layer. both ffnns and lstms can be trained using gradient-descentbased algorithms. more generally, gradient-descent-based algorithms are used to find the local minimum or maximum of a differentiable function. to search for the maximum, the steps taken to find the solution are proportional to the gradient. to search for the minimum, the steps taken are opposite to the gradient. adam, derived from adaptive moment estimation, is a method for stochastic optimization based on adaptive estimates of low-order moments for first-order gradient-based optimization of stochastic objective functions (kingma and ba, 2014). for a given objective function j(ѳ) parametrized by the model’s parameters ѳ, the update equation can be written as follows: � � � � t t t t v m� � � 1 − � � (12) m = m 1 ² t t 1 t  − (13) v = v 1 ² t t 2 t  − (14) mt=β1mt-1+(1–β1)gt (15) v = ² v +(1 ² )gt 2 t 1 2 t 2 − − (16) where mt  = compute bias-corrected first moment estimate, vt  = compute bias-corrected first moment estimate, = update biased first moment estimate, vt = update biased second raw moment estimate, and β1 t and β2 t = exponential decay rates for the moment estimates at time step t and t-time step. both ffnns and lstm are supervised learning algorithms. supervised learning is achieved under the certainty that the target is known and can be split into two main sub-classes: classification and regression (fawcett and provost, 2013). after preprocessing all data sets, the retained independent variables had targets associated represented by the energy consumption. energy consumption is a numeric and continuous variable, meaning that all models prepared are built to be part of the regression sub-class. 4. methodology the study’s entire methodology was aligned with the dmaic framework (figure 4). dmaic is the initialism for define, measure, analyze, improve, control and is six sigma’s process improvement methodology, ensuring quantifiable and sustainable results. between these five phases, feedback loops are set to ensure that project results meet business needs and that expectations are realistic (beemaraj and prasath, 2013). usually, in real-world applications, six sigma-based projects become the mandatory step between baseline and improved operations. during the define phase, the problem statement and the project’s goal are defined. during the measure phase, the issues related to data quality and quantity were assessed. for example, information on the number of floors was missing in proportion of 75.5%. if this study’s purpose had been to predict the energy consumption at floor level for each building, this would have been impossible. most of the time was spent on understanding and preparing the data. if the data quantity and quality are not suited to the project’s scope, then the project must be stopped, its scope adjusted, or the project should be continued without the scope being refined but at a high risk of culminating in no meaningful insights. the data used in this study were made available by ashre through a competition carried out on kaggle.com (ashrae, 2019). the scope of this study is to predict the energy consumption of 1430 buildings clustered in 16 sites. all buildings are labeled based on their primary use: education, lodging/residential, office, entertainment/public assembly, other, retail, parking, public services, warehouse/storage, food sales and service, religious worship, healthcare, utility, technology/science, manufacturing/ industrial, and services (table 1). as part of the data preprocessing step, five of the seventeen primary use categories were retained while the remaining twelve were merged under the other category. the primary use categories ultimately used table 1: data available by site and primary use (thousands) site id education entertainment/public assembly lodging/residential office public services other total per site 0 258.5 43.6 237.2 203.7 na 165.5 908.4 1 192.7 8.7 87.6 140.2 17.5 na 446.9 2 535.3 183.8 105.3 210.6 52.684 96.488 1184.3 3 787.7 385.7 96.3 200.1 741.9 157.1 2369.1 4 557.3 62.1 29.6 na 50.5 46.8 746.6 5 428.9 157.5 8.7 96.3 43.7 43.7 779.1 6 113.8 26.3 96.4 69.9 8.7 na 315.3 7 102.7 na na na na na 102.7 8 na 196.2 na 55.6 227.9 88.1 567.9 9 551.9 148.2 166.4 140.2 17.5 43.8 1068.2 10 109.4 34.5 26.2 37.3 na 28.7 236.5 11 42.6 na na na na na 42.6 12 175.1 17.2 na 78.7 8.7 35.1 314.8 13 201.8 52.5 87.5 613.5 43.9 237.1 1236.5 14 227.1 87.5 78.9 330.1 61.1 105.2 890.0 15 293.2 101.8 199.6 126.8 43.1 43.1 807.6 buțurache and stancu: building energy consumption prediction using neural-based models international journal of energy economics and policy | vol 12 • issue 2 • 2022 35 in the study were: education, entertainment/public assembly, lodging/ residential, office, public services and other (table 2). the available data are categorized according to source into three categories: weather data, building data, and energy consumption data. weather data are gathered from each site’s location and consist of the following variables: site id, timestamp, air temperature, cloud coverage, precipitation depth, dew temperature, sea level pressure, wind direction, and wind speed (table 3). in terms of missing data, six out of thirteen independent variables required data imputation. removal of the records with missing data was not an option owing to the limited quantity of data. missing data can be caused by faults in data acquisition, errors in measurement, insufficient resolution of data sampling, and lack of data acquisition hardware. the computational method used for handling missing data is the nearest neighbor. the nearest neighbor is a univariate imputation schema and relies on the start and end points of the gaps within the data to estimate what is in between. this method was selected from among two other methods—linear and cubic spline interpolation. for the data used during this research, the nearest neighbor performed better. relying on the theoretical foundations and existing research papers, two models were identified as suitable for energy consumption prediction: ffnn and lstm (figure 5). the selection of the hyperparameters had two dimensions. the first was represented by the model’s ability to generalize and the second by the speed of training and testing. based on the mathematics behind anns, categorical data cannot be used in any format other than numeric data. during the preprocessing step, categorical data were transformed into numerical data through encoding. from the timestamp data, date and time information were extracted: year, month, day, hour, weekend, working days, working hours. at the end of the preprocessing step, a data set consisting of 68 variables, including dependent variables, was obtained (figure 6). selection of the number of neurons in the hidden layer and the use of a single hidden layer were part of an optimization process aimed at finding the balance between the model’s ability to generalize and the time required for training. data modeling and final architecture selection are part of dmaic’s measure and improve phases. the optimization process can be visualized as a feedback loop between these two phases. the three metrics used for evaluation are: mean absolute error (mae), coefficient of determination (r2) and training time (tt). the average of the absolute error, equation (17), is used for comparing different models on the same dataset, while r2, equation (18), it is a measure of how well the model can explain the variability in the output, this metric making the research eligible for comparisons with other models since r2 does not depend on the dataset used. n i i i=1 1 mae = y n ŷ∑ (17) table 2: count of building by site and primary use site id education entertainment/public assembly lodging/residential office public services other total per site 0 30 5 27 24 19 0 105 1 22 1 19 16 0 2 60 2 61 21 12 24 11 6 135 3 92 44 11 23 18 85 273 4 66 9 4 0 6 6 91 5 49 18 1 11 5 5 89 6 13 3 11 8 0 1 36 7 12 0 0 0 0 0 12 8 0 24 0 7 11 28 70 9 63 17 19 16 5 2 122 10 14 4 3 5 4 0 30 11 5 0 0 0 0 0 5 12 29 2 0 9 4 1 45 13 23 6 10 70 27 5 141 14 26 10 9 38 12 7 102 15 41 15 28 18 6 6 114 table 3: weather data summary air temp. cloud coverage precip. depth dew temp. sea level pressure wind dir. count 139773 139770 139773 139773 139773 139773 mean 14.4 2.9 0.7 7.3 1016.2 179.3 std 10.6 3.0 6.8 9.8 7.4 111.8 min -28.9 0 0 -35 968.2 0 25% 7.2 0 0 0.6 1012.1 80 50% 15 2 0 8.3 1016.4 190 75% 22.2 6 0 14.4 1020.4 280 max 47.2 9 343 26.1 1045.5 360 missing data before imputation (%) 0% 49% 0% 36% 8% 4% count=total number of data points; std=standard deviation; min=minimum value; 25%=first quartile; 50%=median value; 75%=third quartile; max=maximum value buțurache and stancu: building energy consumption prediction using neural-based models international journal of energy economics and policy | vol 12 • issue 2 • 202236 n i i2 i=1 n 2 i ii=1 (y y ) r = 1 (y – ) – ˆ– y ˆ∑ ∑ (18) where ŷ and yi represents the predicted value and actual value. training time it is a measure of the resources spent on training. training time depends on the hardware and software setup used. for this research the setup consists of a dell precision 7350 equipped with intel core i5-8400h @ 2.5 ghz cpu, 32 gb ram, nvidia quadro p2000 gpu, windows 10, and python 3.6.10. all the algorithms were implemented using keras and tensorflow on the backend. 5. results and discussion ffnn architecture allows training that is twice as fast with an average of 2188 s and r2 equal to 0.8424 over all primary use categories, while lstm’s average training time is 4402 s and average r2 is equal to 0.8461 (figure 7). due to their configurability and scalability neural-based models possess the capability of learning and generalizing from different datasets having different patterns. the mean absolute error, coefficient of determination and training time depend on the figure 4: dmaic methodology figure 6: final ffnn and lstm architectures used for prediction figure 5: ffnn and lstm schema figure 8: average mae comparison by primary use figure 7: average r2 comparison by primary use primary use and site. this may also be linked to how the data are gathered and the extent to which the collected data can explain the phenomena. when the method for dealing with the missing data was selected, the impact of removing the rows or columns containing empty records was assessed. data removal was not an option since these two approaches led to inferior results, while data imputation provided better results. given that lstm is a type of neural network built to model time series, the available optimizations are more generous for problems requiring prediction of energy consumption than in the case of ffnn. ffnn, on the other hand, excels in speed compared to lstm, being least sophisticated. however, lstm’s mechanisms in place for capturing the short and long-term dependencies by default is require more training time (figure 8). given that buțurache and stancu: building energy consumption prediction using neural-based models international journal of energy economics and policy | vol 12 • issue 2 • 2022 37 smart grid systems’ control systems work optimally in real time and computational resources are limited, ffnn models may be preferable. the selection of two fixed architectures and completion of a total of 192 predictions proved that both ffnn and lstm are flexible and scalable. in a real-world business case the focus must be on minimizing the mae (figure 9). 6. conclusion the increased predictability of problems related to the production, distribution, and consumption of electrical energy offers a good foundation for increasing the adoption of energy obtained from renewable sources, economical optimization by introducing flexible pricing policies, and reducing electricity consumption. at the same time, six sigma dmaic methodology ensures that the initial setup for the problem statement and needs, goals, and possible blocking points in a clear and simple yet powerful framework. modeling real-world data using anns under a six sigma dmaic cycle—a robust data mining framework—proved to be successful in terms of performance and training speed. moreover, the flexibility and scalability have been proven by maintaining the level of performance for extreme scenarios in which the available data consisted of either thousands or millions of records. increasing the performance of the models it is a matter of having more data with better quality. also, a finer discretization of the primary use will bring together use cases likely to have the same patters. comparing the results by the primary use can be highlighted the fact that one model can capture the phenomena better than the other one, with the mention that on a bigger resolution (e.g., prediction by primary use and building) both models may have better and closer performance. although one solution might look initially the best before deploying it into production a rigorous validation process must be conducted. by selecting r2 as one of the metrics comparisons with other similar research papers can be made and a benchmark may be set. moreover, by listing all models’ parameters, software and hardware configuration will allow other researchers to perform the same experiments. comparing the results with those obtained by other researchers was not possible due to the way the metrics are typically selected; specifically, the metrics allow a comparison of models that are trained using the same data set, but do not allow a comparison of models trained on different data sets. in this regard, the use of the coefficient of determination, the complete description of the models’ parameters, and the software and hardware configuration will allow other researchers to use this article for comparative studies. the performance of the models might be increased by adding exogenous variables, such as wind speed, wind shear, ambient temperature and pressure, dew point temperature and humidity. the freshly approved romanian recovery and resilience plan provides 41% of the total amount for green transition and 21% for digital transition. in the key of this achievement researchers will be able to continue their work. references abdeljaber, o., avci, o., kiranyaz, s., boashash, b., sodano, h. and inman, d. (2017), 1-d cnns for structural damage detection: verification on a structural health monitoring benchmark data. neurocomputing, 275, 1308-1317. al-ali, a.r. (2016), internet of things role in the renewable energy resources. energy procedia, 100, 34-38. ashton, k. (2009), that “internet of things” thing: in the real world things matter more than ideas. rfid journal, 22(7), 97-114. bengio, y., simard, p., frasconi, p. (1994), learning long-term dependencies with gradient descent is difficult. ieee transactions on neural networks, 5(2), 157-166. botea, r. (2020), energiile regenerabile au acoperit 42% din consumul de energie al româniei, cu 10 puncte procentuale peste media europeană. available from: https://www.zf.ro/eveniment/energiileregenerabile-au-acoperit-42-din-consumul-de-energie-al-romanieicu-10-puncte-procentuale-peste-media-europeana-18764797 [last accessed on 2020 oct 19]. chen, l., lai, x. (2011), comparison between arima and ann models used in short-term wind speed forecasting. in: ieee, 2011 asiapacific power and energy engineering conference. wuhan, china, 25-28 march 2011. cho, k., van merriënboer, b., gulcehre, c., bougares, f., schwenk, h., bengio, y. (2014), learning phrase representations using rnn encoder-decoder for statistical machine translation. in: proceedings of the 2014 conference on empirical methods in natural language processing (emnlp). doha, qatar, 25-29 october 2014. chollet f. (2017), deep learning with python. greenwich, ct: manning publications. ding, m., zhou, h., xie, h., wu, m., nakanishi, y., yokoyama, r. (2019), a gated recurrent unit neural networks based wind speed error correction model for short-term wind power forecasting. neurocomputing, 365, 54-61. eldali, f., hansen, t., suryanarayanan, s., chong, e. (2016), employing arima models to improve wind power forecasts: a case study in ercot. in: ieee, 2016 north american power symposium (naps). denver, co, 18-20 september 2016. end to end machine learning school. (2020), convolution in one dimension for neural networks. available from: https://e2eml. school/convolution_one_d.html [last accessed on 2020 dec 20]. european commission. (2020), eu climate policies and the european green pact. available from: https://ec.europa.eu/clima/policies/euclimate-action_ro [last accessed on 2020 oct 20]. european court of auditors. (2019), wind and solar energy for electricity generation: significant action is needed to achieve eu targets. available from: https://op.europa.eu/webpub/eca/special-reports/ wind-solar-power-generation-8-2019/ro/index.html#h2table5 [last figure 9: average tt comparison by primary use buțurache and stancu: building energy consumption prediction using neural-based models international journal of energy economics and policy | vol 12 • issue 2 • 202238 accessed on 2020 dec 19]. fawcett, t., provost, f. (2013), data science for business. newton, ma: o’relly. fukuoka, r., suzuki, h., kitajima, t., kuwahara, a., yasuno, t. (2018), wind speed prediction model using lstm and 1d-cnn. journal of signal processing, 22(4), 207-210. hanski, j., uusitalo, t., vainio, h., kunttu, s., valkokari, p., kortelainen, h., koskinen, k. (2018), smart asset management as a service deliverable 2.0. available from: http://doi.org/10.13140/ rg.2.2.31027.94244 [last accessed on 2020 oct 19]. hochreiter, s., schmidhuber, j. (1997), long short-term memory. neural computation, 9(8), 1735-1780. ibm. (2019), ibm spss modeler crisp-dm guide: crisp-dm help overview. available from: https://www.ibm.com/support/ knowledgecenter/ss3ra7_sub/modeler_crispdm_ddita/clementine/ crisp_help/crisp_overview.html [last accessed on 2020 oct 19]. kingma, d., ba, j. (2015), adam: a method for stochastic optimization. in: 3rd international conference for learning representations, san diego, ca, 7-9 may 2015. kiranyaz, s., avci, o., abdeljaber, o., ince, t., gabbouj, m., inman, d.j. (2020), 1d convolutional neural networks and applications: a survey. mechanical systems and signal processing, 151, 107398. krishna, p.g., ravi, k.s., kishore, k.h., veni, k.k., rao, k.n.s., prasad, r.d. (2018), design and development of bi-directional iot gateway using zigbee and wi-fi technologies with mqtt protocol. international journal of engineering and technology, 7(28), 125-129. le cun, y., boser, b., denker, j.s., henderson, d., howard, r.e., hubbard, w., jackel, l.d. (1990), handwritten digit recognition with a back-propagation network. in: touretzky, d. editor. advances in neural information processing systems (nips 1989), denver, co, 27-30 november 1989. burlington: morgan kaufmann. liu, y., ding, s., jia, w. (2020), a novel prediction method of complex univariate time series based on k-means clustering. soft computing, 24, 16425-16437. mcculloch, w.s., pitts, w. (1943), a logical calculus of the ideas immanent in nervous activity. bulletin of mathematical biophysics, 5, 115-133. neon neue energieökonomik. (2020), open power systems data: load, wind and solar, prices in hourly resolution. available from: https:// data.open-power-system-data.org/time_series/2020-10-06 [last accessed on 2020 oct 19]. pant, p., garg, a. (2016), forecasting of short term wind power using arima method. international journal for research in applied science and engineering technology, 4(3), 356-361. pascanu, r., gulcehre, c., cho, k., bengio, y. (2014), how to construct deep recurrent neural networks. in: iclr, 2nd international conference on learning representations. banff, canada, 14-16 april 2014. rumelhart, d., hinton, g.e., williams, r.j. (1986), learning representations by back-propagating errors. nature, 323, 533-536. sava, j.a. (2020), onshore wind energy capacity in romania 2008-2019. available from: https://www.statista.com/statistics/870766/onshorewind-energy-capacity-in-romania [last accessed on 2020 dec 21]. singh, v. (2020), 10 benefits of using cloud storage. available from: https://cloudacademy.com/blog/10-benefits-of-using-cloud-storage [last accessed on 2020 oct 19]. wang, j., hu, j. (2015), a robust combination approach for short-term wind speed forecasting and analysis combination of the arima (autoregressive integrated moving average), elm (extreme learning machine), svm (support vector machine) and lssvm (least square svm) forecasts using a gpr (gaussian process regression) model. energy, 93, 41-56. yun, m., yuxin, b. (2010), research on the architecture and key technology of internet of things (iot) applied on the smart grid. in: ieee, 2010 international conference on advances in energy engineering, beijing, china, 19-20 june 2010. zhang, a., lipton z.c., li, m., smola, a.j. (2020), dive into deep learning. available from: https://d2l.ai/chapter_convolutionalneural-networks/index.html [last accessed on 2020 dec 20]. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 4 • 2023 555 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(4), 555-562. effects of co2, renewables and fuel prices on the economic growth in new zealand geeta duppati1, aviral tiwari2, neha matlani3* 1prince mohammad bin fahd university, khobar, saudi arabia, 2rajagiri business school, kochi, india, 3research fellow, singapore management university, singapore. *email: neha.matlani@yahoo.com received: 10 august 2022 accepted: 29 april 2023 doi: https://doi.org/10.32479/ijeep.13463 abstract this study investigates the impact of green policy initiatives on economic growth in the form of reduction in co2 emissions, fossil fuel consumption, and an increase in renewable energy in new zealand for the period 1980-2019. our study addresses two questions: first, whether new zealand managed to achieve economic growth while simultaneously decreasing emissions and increasing renewables? and second, whether the new zealand gdp per capita is sensitive to the changes in fuel prices at the international level. our study provides empirical insights on green policy initiatives, which will help refine early mitigation actions and support a transparent public debate about longer-term desirable and feasible mitigation pathways. we use a range of time series estimation techniques after the pre-diagnostic’s tests. the johansen cointegration test confirm long-term cointegration in the series. our results from vecm suggests that the new zealand economic growth and co2 emissions are sensitive to the changes in the renewables, fossil fuels, brent and australian coal prices in the long run. while our results from the error correction term indicate that renewables have the flexibility and potential to correct the short-run inconsistencies in economic growth at a significant speed and ensures equilibrium in the long run. but the brent and the australian coal are likely to cause discrepancies in the short term and after which the error corrections in the long-term equilibrium are unlikely to happen. we also undertake impulse response function for forecasting the effects of economic growth, co2 emissions, renewables, fossil fuels, brent and australian coal on one another. our results of economic growth on co2 emissions, show differential short and long-run effects. in comparison, a negative co2 emissions shock lasts for a brief period and triggers a very marginal short-term positive effect on economic growth and indicates that worsening or improving co2 emissions will play an essential role in determining the level of economic growth in new zealand. therefore, it is crucial to execute policies that ensure a negative shock in co2 emissions with long-term consequences on the economic growth with reduced emissions. our study provides essential insights into the effectiveness of green initiatives on the economic growth of new zealand. keywords: climate change, carbon emissions, economic growth, renewable energy jel classifications: o56, p18, q41, q43, q47, q54 1. introduction new zealand was a party to the united nations framework convention on climate change (unfcc) and a signatory to the kyoto protocol. it assumed a responsibility emissions reduction target for the first commitment period from 2008-2012 to reduce greenhouse gas emissions to their 1990 levels1. further, it 1 https://environment.govt.nz/what-government-is-doing/internationalaction/nz-united-nations-framework-convention-climate-change/ reiterated its commitment to the kyoto protocol by signing the doha amendment agreement on november 30, 2015, described as the second commitment period. new zealand aims to reduce emissions to 30% below 2005 levels by 2030. therefore, it is vital to understand the green policy initiatives and their effects on co2 emissions, changes in the energy mix, and economic growth. our study addresses two questions: first, whether new zealand achieved economic growth while simultaneously decreasing emissions and increasing renewables? furthermore, second, this journal is licensed under a creative commons attribution 4.0 international license duppati, et al.: effects of co2, renewables and fuel prices on the economic growth in new zealand international journal of energy economics and policy | vol 13 • issue 4 • 2023556 whether the new zealand gdp per capita is sensitive to the changes in fuel prices at the international level. therefore, we provide empirical insights on green policy initiatives that will help refine early mitigation actions and support a transparent public debate about longer-term desirable and feasible mitigation pathways (sims et al., 2016). urban population agglomeration and industrialization describe a higher contribution to climate change and rising carbon emissions. (raihan and tuspekova, 2023). global forums warn the adversaries of not reducing the greenhouse gas emissions on climate change. therefore, urgent action by all the nations for saving the planet earth is vital. emphasis is on setting up targets globally, at the national level for carbon emissions is one aspect of these green efforts to reduce carbon emissions. the kyoto protocol international treaty of 1997 came into force in 2005 as the united nations framework convention on climate change (unfcc). it urged the signatories to reduce the emission of six greenhouse gases in 41 countries plus the european union to 5.2% below 1990 levels. the signatories assumed mandatory emissionreduction targets, depending on the unique circumstances of each country. at the same time, restrictions on emissions to developing countries, signatories to the unfcc are relaxed. new zealand has announced an unconditional target of –5% (below 1990 levels) by 2020, equivalent to a 2013-2020 qelro (quantified emission limitation and reduction objectives) of 96.8 on 1990 emissions. new zealand will apply the kyoto protocol framework of rules to its target to ensure actions are transparent and have integrity. new zealand’s conditional copenhagen target range of reducing emissions between 10 and 20% by 2020 remains on the table, pending meeting those conditions (ets 2012). new zealand government considers emissions trading scheme as a critical instrument for decreasing greenhouse gas emissions. carbon pricing is used an instrument for reducing greenhouse gas emissions by utilizing the emissions trading system (ets) and carbon tax methods (rontard and hernández, 2022). emission units, sometimes called “carbon credits,” are traded between participants in the scheme. an emission unit can either represent one metric tonne of carbon dioxide or any other greenhouse gas equivalent. the primary unit of trade is created by the new zealand government and allocated to organizations and individuals participating in the scheme. “emissions trading” is a marketbased approach for reducing emissions of greenhouse gases. the ets puts a price on emissions by charging specific sectors of the economy for the greenhouse gases they emit. those that emit greenhouse gases into the atmosphere have to surrender nzus or other eligible emission units to the government. while those that remove greenhouse gases from the atmosphere or new zealand may earn nzus from the government. for example, owners of forests that absorb greenhouse gases or export products containing hydrofluorocarbons. national emission trading programs are mixed in the asia pacific region. the carbon emissions trading system (ets) is an important policy tool recognised by international community to achieve carbon-neutrality goals and promote carbon emission reduction by using a market mechanism (tan et al., 2022). although the tokyo metropolitan government has been operating a trading scheme for indirect co2 emissions since 2010, japan has no plans to initiate a national emission trading system. likewise, australia abandoned its long-planned national ets after a change in the government. while new zealand’s small ets has been operating since 2008 and south korea’s emission policy has been in force since 2015 (wb, 2015). extant literature identifies that the renewable energy development in new zealand is less compared to other countries like japan due to barriers that are specific to hydro, solar, geothermal, and wind. in contrast, environmental and resource consent issues are significant factors in development (kelly, 2011). a study from suomalainen et al. (2015) provides insights on the trade-offs of developing wind power in different parts of new zealand. this study provides valuable evidence on wind resource availability in critical periods of the year, such as dry seasons. it thereby enables identifying sites that can most optimally balance price volatility while potentially also maximizing profits to investors. while literature also shows that installing wind energy projects will support domestic energy demand and reduce the consumption of fossil fuels to produce energy (jin et al., 2021). prior studies on the long-term association between the gdp and co2 emissions (vidyarthi, 2013, zou, 2018; and leitao 2014). some studies show energy-induced growth (leitao, 2014; emir and bekun, 2019; duppati et al., 2023), while few studies show that reducing emissions by cutting down fossil fuels would restrict economic growth (soytas and sari, 2009), upgradation of technologies (chang et al., 2015; akram et al., 2020) or by increasing renewables in the energy mix (zafar et al., 2019). atkins et al., (2010), contributes to the literature by conducting carbon emissions pinch analysis (cepa), which extends the standard thermal and mass pinch analysis to the realm of macroscale (i.e. economy-wide) emissions targeting and planning. this methodology takes growing demand into consideration, as well as a carbon pinch study of the new zealand electricity companies. our study adds to the literature, the experience of new zealand on the effects of co2 emissions, renewables, fossil fuels, brent and australian coal on the economic growth. we show that the crossover points in the brent and australian coal has implications for cleaner economic growth in new zealand. a negative shock in brent has a positive effect on renewables and a negative impact on fossil fuels and co2 emissions. these effects lead us to believe that the economic growth in new zealand is sensitive to the changes in the oil and coal commodity prices and, therefore, can be moderated by reducing the dependencies on coal consumption and increase the renewable energies potentials. our study provides empirical insights on green policy initiatives, which will help refine early mitigation actions and support a transparent public debate about longer-term desirable and feasible mitigation pathways. the rest of the paper proceeds as follows: section 2 provides a brief outline of the data and methodology used. we present our results in section 3 and we present our discussion and concluding remarks in section 4. duppati, et al.: effects of co2, renewables and fuel prices on the economic growth in new zealand international journal of energy economics and policy | vol 13 • issue 4 • 2023 557 2. data and methodology this paper examines the effects of climate change policy initiatives on economic growth in new zealand for the period 1980 to 2019 following its commitment for reducing carbon emissions in international forums by using before and after method. we use time series data of new zealand. seven variables are selected for the model. economic growth is the log of gross domestic product (gdp) expressed as billion $us/annum. carbon emissions ((×10^6 tonnes co2e/annum) are log transformed. renewable energy and fossil fuels consumption are expressed as fraction of the total energy consumption. total energy consumption is expressed in exojoules/annum. brent represents the price of the brent oil benchmark in usd per barrel. australia coal price are expressed. the natural gas is the price of the natural gas prices (us) in usd per million british thermal units. the australian coal price is the price of the south african coal in usd per metric ton. the data of the brent, us-natural gas and australian gas is dawn from the global economy database. the data for the period 1980 to 2019 on the gdp, carbon emissions, renewables and non-renewables are obtained from multiple sources: the oecd (data.oecd.org), nz ministry of business, innovation, and employment, world bank data (data.worldbank.org) and bp statistical review. 2.1. time series estimation approaches 2.1.1. pre-diagnostics tests in order to examine the long-term association of co2 per capita emissions, fossil fuels, renewables, prices of brent and australian coal on the gdp per capita of new zealand in vector error correction model (vecm) framework, we undertake some pre-diagnostics tests like, testing the stationarity of the variables included in the vecm analysis and the cointegration of the series. this is important for drawing valid conclusions and to avoid a spurious regression phenomenon. we therefore conduct a unit root test for each variable before the analysis. this paper adopts the augmented dickey-fuller (adf) tests. the proposed null hypothesis for the series is nonstationary, or the series has a unit root. for all cases if critical value (which is based on mackinnon, 1996) exceeds the calculated value in absolute terms (less in negative terms) null hypothesis will not be rejected implying that that series is nonstationary (tiwari, 2012). these tests involve the testing of coefficient associated with 1 year past value of dependent variable. differencing a series using differencing vecm is as follows: operations produce other sets of observations such as the first-differenced values, the seconddifferenced values and so on (asari et al., 2011). we expect the series in the first difference to be stationary. if the variables used in this study are nonstationary and having same order of integration, we undertake cointegration analysis. johansen approach is one widely used method of conducting cointegration tests. prior literature finds this approach particularly promising as it is based on the well-established likelihood ratio principle and precludes the limitations of single equation cointegration procedures (arzie, 1996; dickey et al., 1991) and its superiority over other single and multivariate techniques (gonzalo, 1994). we therefore use johansen and juselius (1990). these procedures use two tests to determine the number of cointegration vectors: the first test is trace (λtrace) statistics and the second one is maximum eigenvalue (λtrace) statistics. the trace statistics tests the null hypothesis that the number of cointegrating relations is r against of k cointegration relations, where k is the number of endogenous variables. the maximum eigenvalue test tests the null hypothesis that there are r cointegrating vectors against an alternative of r +1 cointegrating vectors. critical value for estimation has been obtained from mackinnon, haug, and michelis (1999) which differs slightly from those provided by jj. for both tests if the test statistic value is greater than the critical value, the null hypothesis of r cointegrating vectors is rejected in favor of the corresponding alternative hypothesis. if the series are found to be cointegration then we apply the vector error correction model (vecm) for testing the long-term relationships and in the absence of cointegration we adopt grange causality tests to check the causal relationships between the variables. the regression structure for vecm estimation is given below: 1 1 1 1 1 0 0 0 γ α β γ δ− − − = = = ∆ = + + ∆ + ∆ × +∑ ∑ ∑ n n n t t i t t i i i p e i i yiz (1) 2 2 1 1 1 0 0 0 n n n t t i t t i i i p e i i yizα β γ δ− − − = = = ∆× = + + + ∆× +∑ ∑ ∑ (2) the cointegration rank in the vecm indicates the number of cointegrating vectors. for instance, a rank of two indicates that two linearly independent combinations of the non-stationary variables will be stationary. a negative and significant coefficient of the ecm (i.e. et-1 in the above equations) indicates that any short term fluctuations between the independent variables and the dependent variable will give rise to a stable long run relationship between the variables (asari et al., 2011). 3. empirical analysis and discussion 3.1. unit root tests the results presented in the table 1 tests the null hypothesis that there is a unit root. the unit root adf test support the table 1: results of the augmented dickey-fuller unit root test variables t-statistics probability result gdp per capita 2.0265 0.9884 nonstationary d.gdp per capita −3.5331*** 0.0008 stationary co2 per capita 0.6503 0.8524 nonstationary d.co2 per capita −9.9324*** 0.0001 stationary fossil fuels per capita 1.037 0.9184 nonstationary d.fossil fuels per capita −9.0834*** 0.0001 stationary renewables per capita −0.2063 0.6052 nonstationary d.renewables per capita −9.7748*** 0.0001 stationary brent 0.1353 0.7195 nonstationary d.brent −5.8388*** 0.0001 stationary australia coal 0.2322 0.7454 nonstationary d.australia coal −6.7801*** 0.0001 stationary ***significant at 1% using t-stat approach. gdp: gross domestic product duppati, et al.: effects of co2, renewables and fuel prices on the economic growth in new zealand international journal of energy economics and policy | vol 13 • issue 4 • 2023558 null hypothesis in the levels where the test statistics for all the variables is less than the 5% critical values, suggesting the data as non-stationary. therefore, the null hypothesis that there is a unit root should be accepted. while the results obtained from the first difference tests, indicate that the test statistics is higher than the critical values at 5% level and therefore do not support the null hypothesis and accept the alternate hypothesis that there is no unit root in the data series and therefore the data is stationary. the table 1 shows all the variables non-stationary at levels and are stationary in first differences. we then perform the optimal vector autoregressive (var) lag order selection criteria and obtain in this paper is two. to proceed for cointegration first step is selection of appropriate lag length. therefore, we have carried out a joint test of lag length selection for exports and import function separately, which suggests (basing upon sic) we should take one lag of each variable2. 3.2. co-integration tests it is important to test the long-run relationships between the economic growth and the explanatory variables. co-integration is therefore an important tool for modelling the long-run relationships in time series data. we perform johansen co-integration test, because the variables are all stationary in the first-order differential sequence and co-integration relationship is likely to exist. the null hypothesis is no co-integrating equation among the variables and the alternate hypothesis implies that at least one co-integrating relationship exists. in other words, the test begins from r = 0 where there is no co-integration amongst the variables and accepts the first null hypothesis that is not rejected. in the table 2 below, the trace statistics at r = 0 of 125.12 exceeds its critical value of 95.75, we reject the null hypothesis of no co-integrating equation. likewise, the trace statistics at r = 1 of 79.20 exceeds the critical value of 69.81 and the same is the case with the r = 2. we reject the null hypothesis that there is one co-integration relationship between gdp per capita and the climate change adaptation initiatives at 5% level of significance. while the trace statistics at r = 3, r = 4 and r = 5 are less than their critical values so we cannot reject the null hypotheses at 2 results of lag length selection can be obtained by request to the authors. these ranks. we, therefore, the johansen co-integration test results shows a long-term association among the gdp, energy consumption renewables and fossil fuels, commodity prices and carbon emissions. further, analysing the normalized co-integration coefficients in the vecm allows us to understand how the long-term relationship holds for the co2 emissions, renewables, fossil fuels and fuel prices on the gdp per capita. the results are displayed in the table 3. we anticipate a stable equilibrium relationship to exist as we identified 2 co-integrating equations. in the first equation the results are normalized on the gdp per capita. the co2 emissions and renewables have negative association with the gdp per capita at 1% and 5% levels of significance. while the fossil fuels and brent have a positive association with gdp per capita at 1% level of significance. the second panel of table 3 presents the long run cointegration of the second equation showing long run association of fossil fuels, renewables, and fuel commodity prices with co2 emissions. these long run equilibrium relationships are examined by normalising the co2 emissions. our results indicate that the fossil fuels, renewables and brent oil prices have negative association with co2 emissions, at 1% level of significance, while the australian coal has negative association at 1% level. it is evident that the changes in the carbon emissions are substantially associated to fossil fuels, renewables, brent and the australian coal prices in the long run and can predict the changes in the co2 emissions in new zealand. it is evident from table 3 that in all cases, there is strong evidence for the presence of one cointegration vector i.e., stable long run relationship exists among the variables in two equations. we now present long run cointegrating equation in table 4. it is evident from table 4 that there exists cointegration between the endogenous and dependent variables as shown under cointegration equation one and two. for the first cointegration equation our interpretation of the coefficients is that a 1% increase in fossil fuels and australian coal will lead to 57.73% and 48.57% decrease in the gdp per capita, and a 1% increase in renewables and brent will increase the gdp per capita by 217.51% and 21.02% in the long run. these results table 2: results of the johansen co-integration test panel a: unrestricted cointegration rank test (trace) maximum rank number of ce (s) eigen value trace statistics 5% critical value probability** r=0 none* 0.7109 125.1229 95.7537 0.0001 r=1 at most 1* 0.6762 79.2028 69.8189 0.007 r=2 at most 2 0.3348 37.4798 47.8561 0.3253 r=3 at most 3 0.3093 22.3912 29.7971 0.2773 r=4 at most 4 0.1434 8.6956 15.4947 0.3943 r=5 at most 5 0.0771 2.9701 3.8415 0.0848 panel b: unrestricted cointegration rank test (maximum eigen value) r=0 none* 0.7109 45.9200 40.0776 0.0098 r=1 at most 1* 0.6762 41.7231 33.8769 0.0047 r=2 at most 2 0.3349 15.0886 27.5843 0.7412 r=3 at most 3 0.3094 13.6955 21.1316 0.3905 r=4 at most 4 0.1434 5.7255 14.2646 0.6487 r=5 at most 5 0.0771 2.9701 3.8415 0.0848 trace test indicates, and maximum-eigen value test indicates supports the rejection of the hypothesis at 5% level of significance duppati, et al.: effects of co2, renewables and fuel prices on the economic growth in new zealand international journal of energy economics and policy | vol 13 • issue 4 • 2023 559 suggests that the gdp per capita is sensitive to the changes in the renewables, fossil fuels, brent and australian coal prices. while for the second cointegration equation coefficients suggest that a 1% increase in fossil fuels, renewables and brent will lead to 71.73%, 67.72% and 16.25% decrease in the co2 emissions, and a 1% increase in australian coal will increase the co2 emissions per capita by 19.45% in the long run. these results suggests that the gdp per capita in the first equation and co2 emissions in the second cointegration equation are sensitive to the changes in the renewables, fossil fuels, brent and australian coal prices. it is evident from table 5 that cointegration coefficient i.e., error correction term of renewables is negative and significant at 1% level, while brent and australian coal are positive and significant at 1% levels for equation 1. further the equation 2, indicates the error correction term of co2 emissions as negative and significant at 1% level while brent and australian coal are positive and significant at 1% levels. a negative and significant value of error correction term indicates that in the next period any disturbance in the corresponding dependent variable will get corrected by the amount of the coefficient value. conversely, a positive and significant value of the error correction term indicates that any disturbance in the dependent variable will diverge from the equilibrium by the amount of the coefficient value. for example, when dependent variable is renewables corresponding to it value of error correction term is –0.5618, it implies that any previous periods deviations from the long run equilibrium is corrected in the current period at an adjustment speed of 5.61% in the next year. further, our results also show that one year lag value of gdp per capita has positively significant impact on the gdp per capita itself at 5% level. while two year lag value of australian coal has positive and significant impact on the co2 emissions at 5% level 9although results are not displayed, they may be obtained from the authors). 3.3. post-diagnostics tests to determine the robustness of the model, diagnostic tests are implemented in table 6. we examine whether there are any issues associated with normality, autocorrelation, serial correlation, and heteroscedasticity, we perform post diagnostics test. we have carried out diagnostic checks analysis employing lm test for serial correlation, and j-b test of normality of residuals (tiwari, 2012). results of diagnostic checks are reported in the following table 6. impulse response functions summarize the impact of one variable on another as shown in the figure 1. in essence, they assume a theoretical/hypothetical shock to one variable and display how this shock propagates throughout the other variables. the figure 1 table 3: cointegrating equation of climate change initiatives on economic growth (gross domestic product per capita) gdp per capita co2 fossil renewables brent aus-coal 1. cointegrating equation 1 −2.4954 (0.2936) 8.49903*** −2.3671 (0.2384) 9.9282*** −0.4851 (0.2321) 2.090** 0.1954 (0.0435) 4.4936*** 0.0003 (0.0559) 0.0049 2. cointegrating equation 1 0 0.5772 (0.1345) [4.2901]*** −2.1752 (0.4281) [5.0808]*** −0.2103 (0.0868) [2.4211]** 0.4858 (0.1118) [4.1203]*** 0 1 0.7173 (0.0569) [12.5912]*** 0.6772 (0.1813) [3.7358]*** 0.1626 (0.0368) [4.4201]*** −0.1946 (0.0473) [4.1098]*** ***rejection of the hypothesis at the 0.01, **at 0.05 level. z-statistics are provided in square brackets. normalized cointegrating coefficients (se in parentheses). null hypothesis is no cointegration among the variables. source: author’s calculation. se: standard error table 4: long run results of cointegration equation analysis dependent variables endogenous variables fossil renewables brent aus-coal cointegration equation 1 gdp per capita 1 0 −0.5772*** [−4.1957] 2.1751*** [4.969] 0.2102** [2.3677] −0.4857*** [−4.2501] cointegration equation 1 co2 0 1 −0.7173*** [−12.3137] −0.6772*** [−3.6537] −0.1625*** [−4.3225] 0.1945*** [4.0197] ***,** and *significant at 1%, 5%, and 10% level respectively. source: author’s calculations. t-values are given in the squared brackets [ ] and coefficients are presented in the top row table 5: vector error correction model engle-granger causality analysis error correction d (gdp per capita) d (co2) d (fossil) d (renewables) d (brent) d (aus-coal) cointegration equation 1 −0.0779 [−1.1118] −0.2549 [−1.4963] −0.3149 [−1.3203] −0.5618*** [−3.1322] 1.9083** [2.1657] 2.6744*** [3.0922] cointegration equation 2 −0.0637 [−0.3887] −1.0549** [−2.6453] −0.9187 [−1.6455] −0.4815 [−1.1471] 5.2051** [2.5241] 5.8565** [2.8933] c 0.0069 [1.5898] 0.0073 [0.6912] 0.0110 [0.7403] 0.0043 [0.3848] 0.0329 [0.5989] 0.0538 [0.9983] r2 0.5316 0.6331 0.4686 0.7254 0.5769 0.5722 adjusted r2 0.2336 0.3996 0.1304 0.5507 0.3077 0.3000 f-statistic 1.7840 2.7115 1.3858 4.1517 2.1433 2.1022 ***,** and *significant at 1%, 5%, and 10% level respectively, “d” denotes first difference, in “[ ]” t-values. source: authors calculation duppati, et al.: effects of co2, renewables and fuel prices on the economic growth in new zealand international journal of energy economics and policy | vol 13 • issue 4 • 2023560 presents 10 years forecasts of error correction impulse responses. it is evident from figure 1a that any innovation in the gdp will have negative impact/response of nearly 0.0 to –0.1 on the co2 emissions, fossil fuels and –0.1 to < –0.2 for renewables. however, the impact lasts for only one and a half year and then turn towards positive direction for co2 emissions and fossil fuels to above 0.00, while the negative impact on renewables continues to drop further for a period of four years and then become persistent for six years period. figure 1b presents responses of the gdp per capita, fossil fuels, renewables, brent and australian coal to one s.d. shock/ innovation in the co2 per capita emissions. a one s.d. shock (innovation) causes co2 emissions to drop from 0.04 to.02 in one and half year and with some fluctuations between third and fifth year, it then rises upwards and goes beyond 0.04 in the tenth year. the fossil fuels follow similar pattern of the co2 emissions while the have marginal effects with minimum drops around fifth year but moves upwards and remains on –0.2 level. while the gdp per capita drops below -0.02 towards the end of the 10th year. figure 1c presents responses of the gdp per capita, co2 emissions, renewables, brent and australian coal to one s.d. shock/innovation in the fossil fuels. a one s.d. shock (innovation) causes fossil fuels to drop from 0.6 to.04 in one and half year and with some fluctuations between third and fifth year, it then rises upwards and goes beyond 0.06 and plateaus there from fifth year until the tenth year. the co2 emissions follow similar pattern of the fossil fuels. while the gdp per capita drops from 0.02 to below -0.02 in fifth year and continues to drop further nearly to nearly -0.03 towards the end of seventh year and reaches nearly −0.04. figure 1d presents responses of the gdp per capita, fossil fuels, co2 emissions, brent and australian coal to one s.d. shock/innovation in the renewables. a one s.d. shock (innovation) causes renewables to drop from 0.04 to.02 in one and half year and with some fluctuations between third and fifth year, it then rises upwards and goes beyond 0.04 in the tenth year. the fossil fuels follow similar pattern of the co2 emissions drops around fifth year but moves upwards and remains on −0.2 level. while the gdp per capita drops below -0.02 towards the end of seventh year and table 6: diagnostic checks for analysing the effectiveness of nz climate change policy initiatives tests df rao f-statistics p vec residual serial correlation lm tests lag 1 36 0.6702 0.8955 lag 2 36 1.7622 0.0310 lag 3 36 0.7589 0.8067 vec residual jb normality tests df jarque-bera probability component 1 2 0.4369 0.8038 component 2 2 2.7372 0.2545 component 3 2 8.1084 0.0173 component 4 2 0.7945 0.6721 component 5 2 0.6748 0.7137 component 6 2 4.9114 0.0858 joint 182 173.9868 0.6522 source: authors calculation. vec: vector error correction figure 1: vecm forecast error-correction impulse responses. (a) response of gdp per capita to innovations. (b) response of co2 emissions to innovations. (c) response of fossil fuels to innovations. (d) response of renewables to innovations. (e) response of brent to innovations. (f) response of australian coal to innovations. note: (a) response of nz gdp per capita to generalised one sd innovations; (b) response of nz co2 emissions per capita to generalised one sd innovations; (c) response of nz fossil fuels per capita to generalised one sd innovations; (d) response of nz renewables per capita to generalised one sd innovations and (e) response of brent to generalised one sd innovations. dc b f a e duppati, et al.: effects of co2, renewables and fuel prices on the economic growth in new zealand international journal of energy economics and policy | vol 13 • issue 4 • 2023 561 gradually rises upwards towards the tenth year and reaches −0.02. figure 1e presents a one s.d. shock (innovation) causes brent to drop from 0.2 to 0.1 in three years’ time and but then gradually recovers and increases and settles above 0.1 towards the end of the 10 year. the australian coal shows inverse response to one sd shock in brent. when the australian coal drops the fossil fuels and co2 emissions rises and gdp per capita rises, while renewables drop to nearly −0.01. 4. discussion and conclusions our impulse response functions show the impact of one variable on another graphically. we find that a positive shock to gdp per capita causes an initial decrease in co2 emissions for a short period of fewer than two years and rebounds and increases in the longer term for nearly eight years. these responses imply that the impact of economic growth on co2 emissions in new zealand is multifaceted, with differentiated short and long-run effects. in the short run (approximately up to 2 years after the gdp per capita shock), higher levels of economic growth will result in decreased co2 emissions. however, the effect is positive in the long run. these impulse response effects suggest that economic growth is clean with reduced emissions in the short run, but economic growth leads to increased co2 emissions over time. we observe some exciting findings when we consider the impact of a negative co2 shock in figure 1b. a negative shock in co2 emissions lasts for a brief period of two years and has a very marginal shortterm positive impact on the economic growth (gdp per capita). subsequently, a positive shock in co2 emissions causes economic growth to drop moderately (nearly two years). these responses lead us to believe that worsening or improving co2 emissions will play an essential role in determining the level of economic growth in new zealand. therefore, it is crucial to execute policies that ensure a negative shock in co2 emissions and are long-lasting and aligns with prior evidence (dong et al., 2018). thus, they have positive longer-term consequences on economic growth in a clean environment with reduced emissions. these responses pose a vital insight and challenge for policymakers. we observe some thought-provoking findings when we consider the impact of a negative shock on renewables in figure 1d. a negative shock in renewables lasts for a brief period of two years and causes a positive impact on economic growth (gdp per capita). subsequently, a positive shock in renewables triggers economic growth to drop moderately. this effect on the economic expansion continues even after a bounce in renewables following a positive shock. these responses lead us to believe that the impact of renewables on the economic growth in new zealand is complicated with differentiated in the short run but has positive effects in the long run. therefore, it is essential to note that the positive outcome from renewable sources involves more extended gestation periods. these findings address the first question raised in this paper, i.e., whether new zealand achieved economic growth while simultaneously decreasing emissions and increasing renewables? revisiting the current policies and desirable actions by policymakers are of vital importance. when we consider the impact of a negative shock on brent in figure 1e we observe some challenging findings. a negative shock in brent lasts for nearly three years and causes a positive effect on the economic growth (gdp per capita) for 2 years, and then it declines in the third year but rebounds when the negative shock remains persistent. further, it is essential to note that a small shock in brent makes australian coal stretch substantially. the crossover points in the brent and australian coal has implications for economic growth. further, negative shock in brent has a positive effect on renewables and a negative impact on fossil fuels and co2 emissions. these effects lead us to believe that the economic growth in new zealand is sensitive to the changes in the oil and coal commodity prices and, therefore, can be moderated by reducing the dependencies on coal consumption and increase the renewable energies potentials. we find a stable equilibrium association (negative) between economic growth and co2 emissions, economic growth, and renewables at 1% and 5% significance levels. at the same time, fossil fuels and brent have a positive association with economic growth at a 1% level of significance. we also find a long-run association (negative) between co2 emissions and fossil fuels, renewables, and brent at a 1% level of significance and a positive association between co2 emissions and australian coal in the long run. further, the error correction term suggests that renewables have the flexibility and potential to correct the shortrun inconsistencies in economic growth at a significant speed that adjusts deviation from the equilibrium in the long run. at the same time, brent and australian coal are likely to cause discrepancies in the economic growth in the short term. after that, the error corrections in the long-term equilibrium are unlikely to happen. our results inform policymakers to develop policies that increase investment in the renewable energy sector by giving investors tax relief and financial incentives. renewable energy consumption helps in attaining a cleaner environment by decreasing carbon emissions. therefore, our study provides important insights into the effectiveness of green initiatives on the economic growth of new zealand. policymakers must now consider how to achieve cleaner economic growth in new zealand. references akram, r., chen, f., khalid, f., ye, z., majeed, m.t. (2020), heterogeneous effects of energy efficiency and renewable energy on carbon emissions: evidence from developing countries. journal of cleaner production, 247, 119122. asari, f.f.a.h., baharuddin, n.s., jusoh, n., mohamad, z., shamsudin, n., jusoff, k. (2011), a vector error correction model (vecm) approach in explaining the relationship between interest rate and inflation towards exchange rate volatility in malaysia. world applied sciences journal, 12(3), 49-56. atkins, m.j., morrison, a.s., walmsley, m.r. (2010), carbon emissions pinch analysis (cepa) for emissions reduction in the new zealand electricity sector. applied energy, 87(3), 982-987. chang, y., huang, r., ries, r.j., masanet, e. (2015), life-cycle comparison of greenhouse gas emissions and water consumption for coal and shale gas fired power generation in china. energy, 86, 335-343. dong, k., sun, r., jiang, h., zeng, x. (2018), co2 emissions, economic growth, and the environmental kuznets curve in china: what roles can nuclear energy and renewable energy play? journal of cleaner production, 196, 51-63. duppati, et al.: effects of co2, renewables and fuel prices on the economic growth in new zealand international journal of energy economics and policy | vol 13 • issue 4 • 2023562 duppati, g., younes, b.z., tiwari, a.k., hunjra, a.i. (2023), timevarying effects of fuel prices on stock market returns during covid-19 outbreak. resources policy, 81, 103317. emir, f., bekun, f.v. (2019), energy intensity, carbon emissions, renewable energy, and economic growth nexus: new insights from romania. energy and environment, 30(3), 427-443. gulagi, a., bogdanov, d., breyer, c. (2017), a cost optimized fully sustainable power system for southeast asia and the pacific rim. energies, 10(5), 583. ipcc. (2014), climate change 2014 synthesis report, summary for policymakers, intergovernmental panel on climate change. available from: http://www.ipcc.ch/pdf/assessment-report/ar5/syr/ ar5_syr_final_spm.pdf leitao, n.c. (2014), economic growth, carbon dioxide emissions, renewable energy and globalization. international journal of energy economics and policy, 4, 391-299. nzes new zealand energy strategy. (2011), developing our energy potential, ministry of economic development. available from: https://www.mbie.govt.nz/dmsdocument/142-nz-energy-strategylr-pdf [last accessed on 2023 may 19]. raihan, a., tuspekova, a. (2023), towards net zero emissions by 2050: the role of renewable energy, technological innovations, and forests in new zealand. journal of environmental science and economics, 2(1), 1-16. rontard, b., hernández, h.r. (2022), political construction of carbon pricing: experience from new zealand emissions trading scheme. environmental development, 43, 100727. sims, r., barton, b., bennett, p., isaacs, n., kerr, s., leaver, j., reisinger, a., stephenson, j. (2016), transition to a low-carbon economy for new zealand. available from: https://www.researchbank. ac.nz/handle/10652/3594 [last accessed on 2023 may 19]. soytas, u., sari, r. (2009), energy consumption, economic growth, and carbon emissions: challenges faced by an eu candidate member. ecological economics, 68(6), 1667-1675. suomalainen, k., pritchard, g., sharp, b., yuan, z., zakeri, g. (2015), correlation analysis on wind and hydro resources with electricity demand and prices in new zealand. applied energy, 137, 445-462. tan, x., sun, q., wang, m., se cheong, t., shum, y.w., huang, j. (2022), assessing the effects of emissions trading systems on energy consumption and energy mix. applied energy, 310, 118583. tiwari, a.k. (2012), an error-correction analysis of india-us trade flows. journal of economic development, 37(1), 29. vidyarthi, h. (2013), energy consumption, carbon emissions and economic growth in india. world journal of science, technology and sustainable development, 10, 278-287. zafar, m.w., zaidi, s.a.h., sinha, a., gedikli, a., hou, f. (2019), the role of stock market and banking sector development, and renewable energy consumption in carbon emissions: insights from g-7 and n-11 countries. resources policy, 62, 427-436. zhao, j., patwary, a.k., qayyum, a., alharthi, m., bashir, f., mohsin, m., hanif, i., abbas, q. (2021), fueling the future with green economy: an integration of its determinants from renewable sources. energy, 238, 122029. zou, x. (2018), vecm model analysis of carbon emissions, gdp, and international crude oil prices. discrete dynamics in nature and society, 2018, 5350308. . international journal of energy economics and policy | vol 8 • issue 3 • 2018 209 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(3), 209-215. performance of the electrical energy index in the light of institutional changes in the brazilian electricity sector caio corrêa costa1*, andré luís da silva leite2, nivalde josé de castro3 1business school, federal university of santa catarina – ufsc, florianopolis, brazil, 2business school, federal university of santa catarina – ufsc, florianopolis, brazil, 3federal university of rio de janeiro – ufrj, rio de janeiro, brazil. *email: caio.costa@ufsc.br abstract this study aims to analyze the performance of the electrical energy index (iee) in the perspective of institutional changes in brazilian electricity sector. the research focused its efforts in analyze the impact of provisional measure no. 579 of september 11, 2012 (converted into law no. 12783/2013) on the stocks of the electric power sector, represented here by the respective sector index in bmf and bovespa. the research results reveal that from the release of provisional measure no. 579 by the end of the observed time interval (april 2015), the iee didn’t recovered from the reversal trend caused by this measure, which once was a growth trend but instantly became a stagnation/decay trend. keywords: brazilian electricity sector, capital markets, electrical energy index, laws and regulations, provisional measure no. 579/2012 jel classifications: g38, k23, l51, q40, q48 1. introduction sectors of the economy that have a great impact on society tend to present strong state interference both directly and indirectly. the electrical energy sector would not be left out of this list of sectors where the state has strong interference in decision making and trading. this interference is justified since the electrical energy is considered as a basic service (public utility) and its performance interferes directly in the life of the brazilians in general. government action in the brazilian economy is essential for the country’s development, but it is possible to affirm that it takes place in a cyclical way, as sometimes the state acts more actively, investing heavily in infrastructure, roads, hydroelectric power plants, creating companies and developing economy sectors, but at other times, especially in times of fiscal crisis, delegates such activities to private initiative (filardi et al., 2014). in this institutional context (in which the electric energy sector is settled), taking into account the last years, an event that caused a huge impact in the electric energy sector was the publication of provisional measure no. 579, of september 11, 2012 (brasil, 2012; brasil, 2013). this government action had an immediate impact on the market, causing a sharp drop in shares of energy sector companies. from this point of view, this study aims to analyze the performance of the electrical energy index (iee) in the perspective of institutional changes in brazilian electricity sector. 2. theoretical background 2.1. institutional environment and regulation of the electrical energy sector to understand the structure of the institutional environment settled in the electric sector, it is necessary to approach some important concepts, such as the concept of regulation and in what extent regulatory risks interferes in decision making and trading in each sector of the brazilian economy. the concept of regulation is presented in several different readings by various authors. these concepts present some similarities and also some differences. taffarel (2015) brings a broad and direct concept of regulation, based on the idea of several authors. the author says that we can understand the regulation as a kind of field of action or intervention of the state, directly or indirectly, costa, et al.: performance of the electrical energy index in the light of institutional changes in the brazilian electricity sector international journal of energy economics and policy | vol 8 • issue 3 • 2018210 on the economic agents, aiming to reach the equilibrium of a given system. according to dodge (2003), regulation is necessary to protect industries and consumers from potential negative effects in an economic environment where there is no competition. the possible effects that a non-competitive scenario can bring forth are: artificially inflated prices for consumers or low prices for producers, illegal monopolization of an industry or even the formation of cartels. in a perspective more closely related to the electrical energy sector, regulation is also necessary when market failures or characteristics of a given sector creates a natural monopoly. durana (2006) tries to attribute common characteristics of sectors of the economy that are considered to be of public utility and where the natural monopoly often prevails. below are the main similarities between these sectors according to the author: • utilities generally have interconnected (networked) structures that requires the use of public goods and rights; • these industries create/generate a product or service in one place, and then distribute it over the entire network where it is delivered to numerous end users; • the activities of these sectors can be divided into three segments: production, transmission and distribution. in some cases these segments are vertically integrated; • they usually present high costs in relation to the need to develop/build an extensive physical structure (high costs related to infrastructure); • these sectors have significant gains in economies of scale, the average cost of production of a given good decreases drastically as the quantity produced increases. in this scenario, it is responsibility of the regulatory institutions do not to allow market failures such as abuse of conditions and prices by the companies involved. the main justification for the regulation of public utilities was the existence of market failures, mainly the possibility of market power abuse by the monopolists. regulation by the state was meant to correct these distortions by simulating competitive conditions. the protection of the public interest provided, then, the rationale for government intervention in the market place so as to minimize the economic inefficiencies that would result if the markets were left “free” (durana, 2006. p. 30). state through the regulation process intends to reach a balance between the interests of society and the interests of the companies involved, thus making the decisions taken are satisfactory for both parties (taffarel et al., 2015). 2.2. provisional measure no. 579/2012 the provisional measure no. 579/2012 was published on september 11, 2012, which according to the federal government had the objective of reducing the price of the electrical energy tariff in brazil. this reduction in the price of electrical energy tariff promised by the government was around 20.2%. the regulatory agency of the electricity sector in brazil (aneel) justifies the foundation of this law as essential for new investments related to the quality and continuity of services. aneel says that the main objective of this change of legislation is “to provide security and conditions for agents to make the necessary investments to maintain and continue to provide the service they hold. minimize unnecessary interventions” (aneel, 2014). on the other hand, castro and brandão (2013) understand that the real motivations on the part of the government for the publication of provisional measure no. 579/2012 (converted into law 12,783/2013) were: • high tariff prices practiced in the regulated market; • end of the power plants contracts, representing approximately 40% of the hydroelectric energy in brazilian market (34% in 2015 and 6% in 2017) and transmission lines equivalent to 66% of the national total; • insecurity related to the effectiveness of a bidding in an oligopolistic sector; • end of the old energy contracts as of december 31, 2012. it was understood that the best decision for energy policy would be to extend the contracts of energy companies. in order to extend these contracts, the government would set new terms for new 30year contracts (castro and brandão, 2013). costellini and hollanda (2014) point out that these measures proposed and implemented through provisional measure no. 579/2012 can be considered as a watershed (before and after mp 579) in the brazilian electricity sector. many of the impacts we see today in the industry came from this governmental interference. as a result of this change of legislation where the electricity energy contracts were renewed, it was up to the energy companies to adapt to the new requirements and rules imposed by the federal government, requirements and new rules that caused a huge financial impact on the companies. 3. method and data the most relevant data collected to build and ground the analysis that this article proposes to make are the historical quotations of the iee. therefore, the time horizon of the iee quotations adopted in the survey was from april 2009 to april 2015. historical quotations of other sectors indexes will also be used in order to compare their respective performances with the performance of the iee. these indexes will be the consumption index (icon), financial index (ifnc) and industrial index (indx). in addition, indicators usually used in the capital markets such as relative price, daily, weekly or monthly return, and volatility will support the evaluation of the performance of the iee. 4. analysis and results this chapter presents how was the situation of the electric sector in bmf and bovespa (including growth expectations, variation costa, et al.: performance of the electrical energy index in the light of institutional changes in the brazilian electricity sector international journal of energy economics and policy | vol 8 • issue 3 • 2018 211 in the period, future projections) before the provisional measure no. 579/2012, and compare with the situation of the sector after the release of provisional measure no. 579/2012 (brasil, 2012; brasil, 2013), evaluating the same indicators growth expectation, variation in the period, future projections, among others. 4.1. the iee and the provisional measure no. 579/2012 as soon as the provisional measure no. 579 was announced and with the instantaneous support of the eletrobras group (whose largest shareholder is the federal government), there was an immediate impact on the price of eletrobras stocks in the brazilian capital market and consequently a large impact on the iee. in order to analyze this impact and other factors, it follows graph 1 with the quotation of the iee from april 2009 to april 2015. analyzing graph 1, it was noticed that during this 6-year period (april/2009–april/2015), the iee showed a positive oscillation of 67.65%, rising from 17,200 points on april 01, 2009 and reaching 28,836 points on april 15, 2015 (the last day considered for analysis in the survey). it is important to note that in certain moments prior to provisional measure no. 579/2012, the iee price reached a positive variation >100% in relation to the period of the beginning of the survey (april 1st, 2009), surpassing 35,000 points in the first half of 2012, as can be seen in graph 1. it is possible to observe a sharp drop in the electric energy index since september 2012, totally changing the expectation and projection of growth of the iee from this point forward. clearly, the direct influence that the provisional measure no. 579/2012 had on the iee was observed instantaneously, from the point previously mentioned (september 2012 onwards). examining graph 1, it is possible to notice that from this point of september 2012 until the final period considered, april 2015, the iee did not recover from the trend reversal provoked by mp 579, which before the measure was a growth trend and after the measure became a trend of stagnation/decline. graph 2 shows the situation of the electric energy index prior to the publication of provisional measure no. 579/2012. in graph 2, during this period of more than 3 years taking into account as previous to mp 579, april/2009–july/2012, the electric energy index showed a positive variation of 97.92%, rising from 17,200 points in april 1, 2009 and reaching 34,008 points on july 16, 2012 (last day taken into account as prior to mp 579 for graphical analysis purposes only). it is possible to notice the constant growth of the iee from 2009 until the middle of july/august 2012. in the total period of time researched (april/2009–april/2015) the iee reached a maximum price of 36,391 points, on may 11, 2012. this price of 36,391 points represents a positive change of 111.58% in relation to the beginning of the period observed (17,200 points on april 1, 2009). due to the arguments and data that were exposed in the previous paragraphs, it is clear the growth trend in the electric energy index in the period from 2009 to the first half of 2012. this growth trend ended with provisional measure no. 579/2012, as can be seen in graph 3. graph 3 shows that during this period of <3 years taking into account as post-provisional measure 579, from july/2012 to april/2015, the electric energy index showed a negative oscillation of −15.21%, starting in 34,008 points on july 16, 2012 and reaching 28,836 points on april 15, 2015 (the period from july 16, 2012 to april 15, 2015, taken into account as the period subsequent to provisional measure no. 579/2012 is a period used only for graphical analysis). it is interesting to note the trend inversion in relation to graph 2 (iee quotation before mp 579), where it presented a clear growth outlook for the electric energy index. on the other hand, graph 1: quotation of the electrical energy index from april/2009 to april/2015 % variation 67,65% nominal variation 11.636 costa, et al.: performance of the electrical energy index in the light of institutional changes in the brazilian electricity sector international journal of energy economics and policy | vol 8 • issue 3 • 2018212 in graph 3, it is possible to see clearly that there is no prospect of growth that could be equivalent to that of the first half of 2012, taking into account that after mp 579 the electric energy index was never able to reach the quotations of the mentioned period. after provisional measure nº 579/2012, the maximum quotation reached by the iee was 31,478 points, on september 03, 2014. this maximum quotation after mp 579 represents a negative oscillation of -7.44% in relation to the beginning period of graph 3 (july 16, 2012). the minimum quotation after mp 579 was 21,750 points, reached on march 10, 2014. this minimum quotation after mp 579 represents a negative oscillation of −36.04% in relation to the same period of the beginning of the graph, mentioned in the paragraph above. taking into account the year of 2015 until the last date considered in the research (april 15, 2015), the electric energy index ranges from 25,000 to 28,000 points. 4.2. iee x other indexes in this section of chapter 4, the fluctuation of other indexes for the same period considered for the iee (april 2009–april 2015) will be discussed. in addition to the iee, the other indexes taken into account in this analysis are: • icon – consumer goods index: it is the indicator of the stocks of the companies representing the sectors of cyclical and non-cyclical consumer goods (bmf and bovespa, 2015). • indx – industrial index: this index was developed to measure the performance of the most representative stocks of the industrial sector, an important segment of the brazilian economy (bmf and bovespa, 2015). • ifnc – financial index: this index is intended to be the indicator of the shares of companies representing the sectors of financial intermediaries, financial services, pension and insurance services (bmf and bovespa, 2015). graph 2: quotation of the electrical energy index before mp 579 % variation 97,72% nominal variation 16.808 graph 3: quotation of the electrical energy index (iee) after mp 579 % variation −15,21% nominal variation −5.172 costa, et al.: performance of the electrical energy index in the light of institutional changes in the brazilian electricity sector international journal of energy economics and policy | vol 8 • issue 3 • 2018 213 graph 4 brings the fluctuation in the quotations of these four indexes (iee, icon, indx, ifnc) during the observation period considered in this research, from april 1, 2009 to april 15, 2015. all the indexes demonstrated positive oscillation in this 6-year time horizon, as referred to in graph 4, but in different proportions. the consumer goods index showed the highest increase in this period, having a similar appreciation in 2009, 2010 and 2011 and growing exponentially in 2012, 2013, 2014 and 2015, reaching a positive oscillation close to 300% in relation to the beginning of the period. the financial index and the industrial index presented similar performances throughout the observed time. this can be seen from the similar highs and lows that the two indexes had together during most of the years, as shown in graph 4. it is understood that there may be some kind of correlation between the ifnc and the indx. at the end of the analyzed period, the financial index appreciated slightly more than 150% and the industrial sector index slightly <150%. the iee showed similar performance in comparison to the other three indexes in the 1st years, but with some differences, as the iee increased in a slightly lower level in the beginning of graph 4. the iee was in a growing trend of performance, where in 2011 and the first half of 2012 reached the level of appreciation of ifnc and indx. however, this growing trend has completely reversed in the second half of 2012 (as can be seen in graph 4.), as a consequence of the publication of provisional measure no. 579/2012. from this point on, the growth of the index lost “breath” and was no longer able to keep up with the appreciation levels of other indexes. 4.3. risk, return and volatility of the iee in order to have a more in-depth analysis of the performance of the iee, it is necessary to take into account some commonly used indicators in stock valuation in the capital markets. the indicators referred and which will be addressed in this section of the survey are: risk, return and volatility. the term risk is most often used erroneously only with a negative connotation, and is generally used as a sense of “risk of loss.” however, in the financial market this is not exactly what the term “risk” means. jorion (1998) points out that although the term risk sometimes is used as “danger of loss,” finance theory defines it as “dispersion of unexpected results due to fluctuations in financial variables.” thus, positive and negative fluctuations should be seen as sources of risk. extraordinary actions, both good and bad, should be observed with caution. it is interesting to highlight the relationship between risk and return in the capital markets in general. according to the concept of risk brought in the theory of finance, where risk is seen as uncertainty in relation to the results, in both positive and negative oscillations, it is possible to infer that higher risk stocks have a higher expectation of return. hull (2001) defines that the expected return by investors on a particular stock depends on some variables, among these variables the risk level of this stock stands out. the higher the risk, the greater the expectation of return required by investors. taking into account this uncertainty regarding the level of risk of an asset and the expectation of return in relation to it, a tool that is widely used in the capital markets to precisely measure this relationship between risk and return is volatility. according to hull (2001), the volatility of a stock can be understood as the measurement of uncertainty in relation to the returns provided by this stock. still according to hull (2001), the volatility of a stock can be estimated through the historical data of this stock, for this it is considered a fixed interval of time (it can be daily, weekly or monthly). graph 4: electrical energy index x other indexes label iee – blue icon – red indx – green ifnc – orange costa, et al.: performance of the electrical energy index in the light of institutional changes in the brazilian electricity sector international journal of energy economics and policy | vol 8 • issue 3 • 2018214 in order to estimate the volatility of the iee in the period studied, two formulas will be used: the relative price formula and the daily return formula. hull (2001) defines the relative price as being: relative price formula: si si−1 in the above formula, si represents the stock price at the end of the defined period (i = 0, 1,.. n). the daily, weekly or monthly return is defined by the following formula: daily, weekly or monthly return formula si ui=ln si 1     − for the construction of table 1, a monthly observation interval of the iee was considered from april 2009 until april 2015. for this, the first quotation of each month was taken into account. the analysis of the monthly return and relative price table of the iee demonstrates the difference between the pre-mp579 returns and the post-measure returns. prior to publication of provisional measure no. 579/2012 (considered from april 2009 to august 2012 in table 1) there was a sum of positive returns of 0.70848. following the edition of the measure (considered from september 2012 through april 2015 in table 1) the trend reversed completely, coming out of a sum of the positive returns as mentioned above for a sum of negative returns of −0.21231. the sum of the returns of the whole period (april 2009 to april 2015) shows a positive return of 0.46717. it is important to observe that this sum of the returns at the end of the observed period could be much higher if the iee had continued with the growth trend that had been presenting until august 2012, but that came to an end a month later with the referred institutional change. as previously analyzed, the sum of the returns from the iee pre-mp579 is positive and post-mp579 is negative, meaning that provisional measure nº 579/2012 influenced the return. volatility, however, is lower than before, which on the one hand is a sign of lower risk but also that there is lower transaction volume, which stems from the fact that a higher degree of uncertainty leads to fewer transactions, due to the fact that the brazilian electricity sector has become less attractive to investors. 5. conclusion previously to provisional measure no. 579/2012, the iee was showing a clear perspective of growth, reaching historical maximums only a few months before the publication of such measure. however, after the release of the mp 579, there was an instant reversal of trend. what was once a growth perspective quickly turned into a declining/stagnating trend. in this scenario until the year of 2015, the iee was never able to reach the level of the prices of the period prior to such measure. given the content presented in this research, it is understood that government interventions, through the change of regulatory policies, have an intense impact on the sector targeted by this regulation and the companies that operate in it, since the regulatory risk causes insecurity to the investors. references aneel. (2014), agência nacional de energia elétrica. análise de impacto regulatório. brasília-df: aneel. bmf and bovespa. (2014), bolsa de mercadorias e futuros and bolsa de valores de são paulo. são paulo–sp: metodologia do índice bm & fbovespa energia elétrica. bmf and bovespa. (2015), bolsa de mercadorias e futuros and bolsa de valores de são. available from: http://www.bmfbovespa.com.br/. [last accessed on 2015 mar 05]. brasil. (2012), medida provisória nº 579, de 11 de setembro de 2012. available on: http://www.planalto.gov.br/ccivil_03/_ato20112014/2012/mpv/579.htm/. [last accessed on 2015 jan 28]. brasil. (2013), lei n 12.783. de 11 de janeiro de 2013. available from: http://www.planalto.gov.br/ccivil_03/_ato2011-2014/2013/ lei/l12783.htm/. [last accessed on 2015 feb 11]. castro, n.j., brandão, r. (2013), questões sobre a renovação das concessões de distribuição. rio de janeiro: universidade federal table 1: monthly return and relative price of iee date (first date of each month) quotes relative price monthly return april/09 17200 may/09 19115 1.11134 0.10556 june/09 19794 1.03550 0.03489 july/09 20646 1.04302 0.04212 august/09 21222 1.02792 0.02754 september/09 21249 1.00128 0.00128 october/09 22234 1.04635 0.04531 november/09 22214 0.99908 −0.00092 december/09 23322 1.04989 0.04868 january/12 32559 1.09088 0.08699 february/12 32459 0.99694 −0.00307 march/12 34438 1.06096 0.05918 april/12 35767 1.03859 0.03786 may/12 35981 1.00597 0.00595 june/12 33701 0.93664 −0.06545 july/12 35337 1.04854 0.04740 august/12 34932 0.98856 −0.01151 sum of returns before mp 579 0.70848 september/12 33093 0.94734 −0.05409 october/12 29957 0.90524 −0.09955 november/12 29455 0.98325 −0.01689 december/12 27521 0.93434 −0.06792 january/13 29278 1.06385 0.06189 february/13 28049 0.95801 −0.04290 march/13 27180 0.96902 −0.03147 april/13 27739 1.02058 0.02037 january/15 26473 0.95890 −0.04197 february/15 25475 0.96229 −0.03844 march/15 26284 1.03177 0.03127 april/15 28250 1.07480 0.07214 sum of returns after mp 579 −0.21231 sum of returns total 0.49617 elaboration based on data from the electrical energy index (iee). iee: electrical energy index costa, et al.: performance of the electrical energy index in the light of institutional changes in the brazilian electricity sector international journal of energy economics and policy | vol 8 • issue 3 • 2018 215 do rio de janeiro–ufrj. costellini, c., hollanda, l. (2014), setor elétrico: da mp 579 ao pacote financeiro–fgv energia. são paulo: fundação getúlio vargas–fgv. dodge, l.w. (2003), the political effects of ideas and markets on china’s economic reforms: the case of electric power. santa barbara, ca: university of california–ucla. durana, m.d.i. (2006), electricity sector liberalization in: the european union: the political economy of regulatory reform. baltimore, maryland: johns hopkins university. filardi, f., leite, a.l.d.s., torres, a.a.g. (2014), análise de resultados de indicadores de gestão e de regulação após a privatização: estudo de caso da light serviços de eletricidade. revista de administração usp, 49(1), 18-32. hull, j.c. (2001), fundamentals of futures and options markets. 4th ed. usa: prentice hall. jorion, p. (1998), value at risk: a nova fonte de referência para o controle do risco de mercado. são paulo: mcgraw-hill. taffarel, m. (2015), análise das relações entre perfil e intensidade das medidas regulatórias e o risco das ações de empresas do setor de energia elétrica brasileiro. curitiba, pr: pontifícia universidade católica do paraná. taffarel, m., silva, w.v., clemente, a., veiga, c.p., del corso, j.m. (2015), the brazilian electricity energy market: the role of regulatory content intensity and its impact on capital shares risk. international journal of energy economics and policy, 5(2), 288-304. . international journal of energy economics and policy | vol 7 • issue 3 • 2017102 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(3), 102-109. the relationship between energy consumption, economic growth and carbon dioxide emission: the case of south africa hlalefang khobai1*, pierre le roux2 1department of economics, nelson mandela metropolitan university, south africa, 2department of economics, nelson mandela metropolitan university, south africa. *email: hlalefangk@gmail.com abstract this paper investigates the relationship between energy consumption, carbon dioxide (co2) emission, economic growth, trade openness and urbanization for south africa. the annual data for the period between 1971 and 2013 is employed. the results of johansen test of co-integration show that there is a long run relationship between energy consumption, co2 emission, economic growth, trade openness and urbanization in south africa. the results for the existence and direction of vector error correction model (vecm) granger causality indicates that there is bidirectional causality flowing between energy consumption and economic growth in the long run. the vecm results further found a unidirectional causality flowing from co2 emissions, economic growth, trade openness and urbanization to energy consumption and from energy consumption, co2 emissions, trade openness and urbanization to economic growth. these results posit a fresh perspective for creating energy policies that will boost economic growth in south africa. keywords: energy consumption, economic growth, carbon dioxide emission, south africa jel classifications: o13, q43 1. introduction the world has experienced major changes in economic and environmental scopes in south africa due to the great reform and economic transition in the past two decades. south africa has experienced increasing demand in energy following the increase in economic growth post-apartheid era. the country’s energy intensity is above average which indicates that much energy is required to produce a single unit of gross domestic product (gdp). however, south africa’s energy utilization is characterized by high dependence on low-cost and abundantly available coal. a large amount of crude oil is imported into the country while a small amount of renewable energy is used. table 1 shows the trends of the total energy supply from 2003 to 2006. it can be seen from table 1 that coal dominates the energy supply while hydroelectricity contributes the least to energy supply. however, coal was subjected to a mix of trends since 2003. its contribution decreased by 4.5% from 2003 to 2004, and increased by 3.6% from 2004 to 2005; from 2005 to 2006, it fell again by 5.9%. in general, the contribution of coal has decreased by 6.8% for the entire period. the contribution of hydroelectricity has increase by 0.1% since 2003. crude oil has experienced an increase of 7.8% since 2003 while gas supply increased by 1.7%. the nuclear contribution dropped from 3.1% in 2003 to 1.9% in 2006. the renewables have decreased from 9.4% in 2003 to 7.6% in 2006. coal and crude oil remain the major primary energy suppliers in south africa despite their effects on air quality, human health, wildlife and climate change. south africa is the ranked number six among the world’s largest recoverable coal reserves (department of energy, 2009). it is 12th highest carbon dioxide (co2) emitter in the world and number one greenhouse gas emitter in africa (usaid, 2016). the increasing concern of the greenhouse gas emission has motivated many researchers to investigate relationship the between energy consumption, co2 emission and economic growth in different countries and regions. however, this relationship has been rarely examined in south africa despite the fact that south africa’s energy consumption and carbon emission increased more than double in the last two decades. while there are studies carried in the international literature to investigate khobai and le roux: the relationship between energy consumption, economic growth and carbon dioxide emission: the case of south africa international journal of energy economics and policy | vol 7 • issue 3 • 2017 103 the relationship between energy consumption, co2 emission and economic growth, they do not focus on south africa (saidi and hammami, 2015; arouri et al., 2012; linh and lin, 2014; vidyarthi, 2013). the studies which were done in south africa focused on energy consumption and economic growth (okafor, 2012; wolde-rufael, 2009 and odhiambo, 2010). the only south african study that covered energy consumption, economic growth and pollutant emissions was done by menya and wolde-rufael (2010). our study differs from menya and wolde-rufael (2010)’s study in that we included trade openness and urbanization as the additional variables to form a multivariate framework. the remainder of the study is organized as follows: section 2 studies the review of the empirical literature. section 3 presents the data and methodology used in the study followed by the discussion of the findings in section 4. section 5 concludes the study with some policy implications. 2. literature review the relationship between economic growth and energy consumption had been researched extensively over the past three decades. however, the results concerning the direction of causality between these variables are still mixed. the results range from no causality to unidirectional or bidirectional causality. the difference is caused by different methodologies applied, different countries’ data applied and the particular period of the study. the pioneers of the studies on energy consumption and economic growth are kraft and kraft (1978). their study considered the case of usa for the period 1947 to 1974. the results from sims granger-causality supported a unidirectional causality flowing from gross national product to energy consumption. this implies that energy conservation policies can be introduced without causing any harm to economic growth. shyamal and rabindra (2004) undertook a study to investigate the causal relationship between energy consumption and economic growth in india covering the period 1950-1996. the study utilized engle-granger co-integration to estimate the long run relationship between these variables and the standard granger-causality to find the direction of causality. the results supported a unidirectional causality flowing from energy consumption to economic growth. the results from engle-granger co-integration detected a one-way causality flowing from economic growth to energy consumption in the long term. the combination of standard granger-causality and the engle-granger approach revealed bidirectional causality between energy consumption and economic growth. saidi and hammami (2015) conducted a study to assess the link between energy consumption and economic growth in tunisia. the annual data was used for the period between 1974 and 2011. the johansen technique results suggested that there is a long run relationship between economic growth and energy consumption. the granger-causality results found a bidirectional causality flowing between energy consumption and economic growth in tunisia. tang et al. (2016) investigated the long run relationship between energy consumption and economic growth for the period between 1971 and 2011. the results from co-integration technique revealed existence of co-integration among the variables. the grangercausality results suggested a one-way causality running from energy consumption to economic growth in vietnam. this implies that vietnam is an energy-intensive country and there is a need to implement renewable energy policy to provide sufficient supply as this will speed up economic growth. albiman et al. (2015) conducted a study to determine the relationship between energy consumption, environmental pollution and per capita economic growth in tanzania for the period between 1975 and 2013. the study investigated the causality relationship by employing the more robust causality technique of toda and yamamoto’s non-causality test. the findings revealed a unidirectional causality flowing from economic growth and energy consumption to environmental pollution through co2 emissions. vidyarthi (2013) carried out a study to investigate the long term and causal relationship between energy consumption, economic growth and carbon emissions in india. the data used in this study covered a period from 1971 to 2009. to determine the co-integration between the selected variables, the johansen co-integration technique was employed while the vector error correction model (vecm) granger-causality test was used to find the direction of causality between the variables. the johansen cointegration technique results established a long term relationship between energy consumption, carbon emissions and economic growth. the long term causality results validated a unidirectional causality flowing from energy consumption and co2 emissions to economic growth while the short term causality revealed mixed results: a unidirectional causality flowing from energy consumption to carbon emission; carbon emission to economic growth and; economic growth to energy consumption. table 1: total primary energy supply-tj: 2003-2006 variables 2003 % 2004 % 2005 % 2006 % coal 3,227,600 72.7 3,573,343 68.2 3,651,726 71.8 3,721,156 65.9 crude oil 615,689 13.7 1,016,664 19.4 724,774 14.2 1,214,122 21.5 gas 50,218 1.1 84,152 1.6 153,078 3.0 160,318 2.8 nuclear 138,142 3.1 145,801 2.8 123,193 2.4 109,375 1.9 hydro 2890 0.1 2890 0.1 4199 0.1 11,069 0.2 nuclear 422,979 9.4 418,058 8.0 430,427 8.5 428,396 7.6 total 4,507,518 5,240,908 5,089,397 5,644,436 source: department of energy (2009) khobai and le roux: the relationship between energy consumption, economic growth and carbon dioxide emission: the case of south africa international journal of energy economics and policy | vol 7 • issue 3 • 2017104 another study that used a trivariate framework is by dehnavi and haghnejad (2012) which aimed to determine the relationship between energy consumption, pollution and economic growth for a selected panel of eight organization of the petroleum exporting countries. the study used a panel data technique for the period 1971-2008. the granger-causality identified a two-way causality between co2 emissions and energy consumption and a one-way causality flowing from economic growth to energy consumption and pollution in the long term. the short run results observed that economic growth granger-causes co2 emission while energy consumption granger-cause co2 emission and economic growth. a multi-country study was conducted by vidyarthi (2014) to investigate the relationship between energy consumption, carbon emissions and economic growth for five south asian countries: bangladesh, india, pakistan, nepal and sri lanka. the study used pedroni’s co-integration to determine the long term relationship among the variables and panel vecm granger-causality to find the direction of causality between the variables. in using data for the period between 1972 and 2009, the study found that there exists a long term relationship between energy consumption, carbon emissions and economic growth in all these countries. the vecm granger-causality suggested bidirectional causality between energy consumption and economic growth, a unidirectional causality flowing from carbon emissions to economic growth and energy consumption in the long term. the short term results identified a unidirectional causality flowing from energy consumption to carbon emissions. another multi-country study was carried out by ahmed and azam (2016) who served to examine the nexus between energy consumption and economic growth for 119 countries all over the world. the countries were categorized as follows; 30 high income oecd, 13 high income non-oecd, 65 middle income and 11 low income countries. the granger-causality results detected feedback hypothesis for 18 countries (5 high income oecd, 2 high income non-oecd, 10 middle income oecd and 1 low income). it was further established that there is a growth hypothesis in 25 countries which comprises of 4 high income oecd, 3 high income non-oecd, 14 middle income and 4 low income countries. conservation hypothesis was revealed for 6 high income oecd, 6 high income non-oecd, 27 middle income and 1 low income countries. finally, there was no causality established in 15 high income oecd, 2 high non-oecd, 14 middle income and 5 low income countries. moubarak and lin’s (2014) research aimed to determine the long term and short run relationship between renewable energy consumption and economic growth in china. the data used in the study covered the period 1977-2011. co2 emissions and labor were used as additional variables to form a multivariate framework. the results from the autoregressive distributed lag technique and the johansen co-integration test found that there is a long term relationship between the selected variables. the granger-causality test suggested a two-way causality flowing between renewable energy consumption and economic growth in the long-term. the causality results further established a unidirectional causality flowing from labor to renewable energy consumption. there was no causality found between carbon emissions and renewable energy consumption in the long term and short term. this implies that renewable energy has not been exploited in china to mitigate co2 emissions. pablo-romero and de jesús (2016) conducted a study to examine the link between energy consumption and economic growth using the hypothesis postulated for the energy-environmental kuznets curve. a panel data of 22 latin american and caribbean countries were employed covering the period between 1990 and 2011. their findings showed existence of a u-shaped relationship between energy consumption and economic growth. linh and lin (2014) contribute to the most recent studies that assessed the dynamic relationship between energy consumption and economic growth using multivariate framework by adding the variables foreign direct investments and co2 emissions. this vietnam study used data for the period between 1980 and 2010. the co-integration findings show that there is a long term relationship between economic growth, energy consumption, foreign direct investments and co2 emissions. the grangercausality results established bidirectional causality between foreign direct investment and income in vietnam. this implies that an increase in vietnam’s income has a potential of attracting more capital from overseas. kais and sami (2016) investigated the impact of energy consumption and economic growth on co2 emissions in 58 countries covering the period between 1990 and 2012. the countries were divided into three regional subgroups as follows: european and north asian region, latin american and caribbean region and sub-saharan region. the results posit that energy consumption has a positive impact on co2 emissions all panels. it is further revealed that economic growth has a positive and a statistically significant impact on co2 emissions european and north asian region and north africa and sub-saharan africa. streimikiene and kasperowicz (2016) served to determine the nexus between energy consumption and real gdp by incorporating fixed capital and total employment to form multivariate framework. the study used data for 18 european union countries for the period from 1995 to 2012. it was established that economic growth, energy consumption and gross fixed capital move along in the long run. the findings from the fully modified ordinary least squares (fmols) and dynamic ordinary least squares estimators indicated a positive relationship between economic growth, energy consumption and gross fixed capital. arouri et al. (2012) examined the link between energy consumption, co2 emission and economic growth for 12 middle east and north african countries spanning the period 1981-2005. the bootstrap panel unit root tests and co-integration techniques were applied. the findings indicated a long run positive relationship between energy consumption and co2 emissions. furthermore, real gdp showed a quadratic relationship with co2 emissions for the entire region. saidi and hammami’s (2015) study serves to investigate the impact of economic growth and co2 emissions on energy consumption for khobai and le roux: the relationship between energy consumption, economic growth and carbon dioxide emission: the case of south africa international journal of energy economics and policy | vol 7 • issue 3 • 2017 105 58 countries. dynamic panel data model for the period between 1990 and 2012 was estimated using the generalized method of moments (gmm). the findings show that co2 emission have a positive and significant impact on energy consumption for four global panels. the results further show that economic growth has a positive effect on energy consumption. wang et al. (2016) detected the causal link between urbanization, energy consumption and co2 emissions for the association of southeast asian nations countries covering the period between 1980 and 2009. the findings from the pedroni panel co-integration tests evidenced existence of a long run relationship among the variables. employing the fmols, it was established that all else the same, a 1% rise in urbanization leads to co2 emissions increasing by 0.20%. the granger-causality results suggested a unidirectional short run causality flowing from urbanization to energy consumption and from urbanization to co2 emissions. it was further detected that urbanization and energy consumption granger-cause co2 emissions in the long run. ozturk and al-mulali (2015) investigate whether better governess and corruption control help to form the inverted u-shaped relationship between income and pollution in cambodia for the period of 1996-2012. the outcome from the gmm and the two-stage least squares revealed that gdp, urbanization, energy consumption, and trade openness increase co2 emission while the control of corruption and governess can reduce co2 emission. it is fundamental to note that the environmental kuznets curve hypothesis was not confirmed in cambodia. okafor (2012) and odhiambo (2010) employed energy consumption and economic growth nexus in south africa. odhiambo (2010) applied the granger-causality test while okafor (2012) employed hsiao’s granger-causality test. the results of odhiambo’s (2010) study validated a one-way causality flowing from energy consumption to economic growth while okafor’s (2012) results suggested a unidirectional causality flowing from energy consumption to economic growth. menyah and wolde-rufael’s (2010) research investigated the relationship between economic growth, pollutant emissions and energy consumption. their study added labor and capital to form a multivariate model and used south african data for the 1965-2006 period. a modified version of the grangercausality test and bounds test approach to co-integration were applied to analyze the direction of causality and long term relationships between the variables. a long term relationship was established between the variables. the granger-causality results showed unidirectional causality flowing from pollutant emissions to economic growth. it also found a unidirectional causality from energy consumption to co2 emission and from energy consumption to economic growth. al-mulali et al. (2015) investigate the influence of disaggregated renewable electricity production by source on co2 emission in 23 selected european countries for the period of 1990-2013. the pedroni cointegration results indicated that co2 emission, gdp growth, urbanization, financial development, and renewable electricity production by source were cointegrated. moreover, the fully modified ordinary least-square results revealed that gdp growth, urbanization, and financial development increase co2 emission in the long run, while trade openness reduces it. from the empirical literature, it can be realized that no study was done to investigate the relationship between energy consumption, economic growth and co2 emission incorporating trade openness and urbanization as controlling variables in south africa. therefore, this current study endeavors to fill that gap. 3. methodology 3.1. model specification this study analyses the relationship between energy consumption, co2 emissions and economic growth by adding trade openness and urbanization as intermittent variables to form a multivariate framework. to address the issue of heteroskedasticity, all the variables are converted into logarithm form. the log linear quadratic form is used to analyze the relationship between energy consumption, co2 emissions and economic growth using the following model; lec lco lgdp lto lubn t lco t lgdp t lto t lubn t t = + + + + + α α α α α ε 1 2 2 (1) lec represents the natural log of energy consumption per capita lgdp indicates the natural log of real gdp (using constant prices of 2010), lco2 is the natural log of co2 emissions, lto denotes natural log trade openness and lubn represents natural log of urbanisation. furthermore, α1 and εt represent the constant and an error term, respectively. 3.2. data sources the study employs annual time-series data covering the period between 1971 and 2013 for energy consumption, economic growth, co2 emissions, trade openness and urbanization. different sources have been used to gather data of the mentioned variables. real gdp (using constant prices of 2010) was collected from the south african reserve bank. the data for co2 emissions, energy consumption and urbanization were collected from word development indicators while data for trade openness was sourced from united nations and trade development. 3.3. data analysis 3.3.1. unit root test the unit root test is used to determine whether or not the variables energy consumption, co2 emission, economic growth, trade openness and urbanization are stationary series. this study employs two unit root tests; augmented dickey–fuller (adf) unit root test by said and dickey (1984) and another one by phillips and perron (1988) termed phillips-perron (pp) unit root test. when the variables are found to be integrated of the same order, co-integration between the variables will be tested. 3.3.2. co-integration test the long run relationship between energy consumption, co2 emissions, economic growth, trade openness and urbanization is estimated using the johansen co-integration technique (johansen, 1988; johansen and juselius, 1990). this technique involves the estimation of a vecm to determine the likelihood-ratios. it works khobai and le roux: the relationship between energy consumption, economic growth and carbon dioxide emission: the case of south africa international journal of energy economics and policy | vol 7 • issue 3 • 2017106 in a way that there are at most n−1 cointegrating vectors if there are n variables which all have unit roots. the vecm model employed in this study is as follows: ∆ = + ∆ + ∝ + = − −∑ −y yt i k i t y t t kθ θ β ε 0 1 1 1 ' (2) where, δ is the difference operator, yt is (lec, lco2, lgdp, lto, lubn), θ is stands for the intercept and ε is the vector of white noise process. the johansen technique comprises of two likelihood ratio tests namely; the maximum eigenvalue and the trace test. the number of co-integrating vectors in the system is determined by the number of significant non zero eigen values. 3.3.3. granger-causality the presence of co-integration implies that there is a causality but it does not show the direction of causality among the variables. to estimate causality between energy consumption, co2 emission, economic growth, trade openness and urbanization, the vecm is employed. the empirical equations of the vecm grangercausality are presented as follows: ∆ ∆ ∆ ∆lec lec lco lgdpt t i t i t i i s i r i q = + + +− − − === ∑∑α α α α10 11 12 2 13 111 ∑∑ ∑ ∑+ + + +− − − − −α α ψ ε14 1 15 1 1 1 1 ∆ ∆ltr lubn ectt i i t t i i u t t (3) ∆ ∆ ∆ ∆ lco lco lec lgdp t t i t i i r i q t i 2 20 21 2 22 11 23 2 = + + + + − − == − ∑∑α α α α α 44 11 25 1 2 1 2 ∆ ∆ ltr lubn ect t i i t i s t i i u t t − −= − − − ∑∑ ∑+ + +α ψ ε (4) ∆ ∆ ∆ ∆ lgdp lgdp lec lco t t i t i i r i q t i = + + + + − − == − ∑∑α α α α α 30 31 32 11 33 2 344 11 35 1 3 1 3 ∆ ∆ ltr lubn ect t i i t i s t i i u t t − −= − − − ∑∑ ∑+ + +α ψ ε (5) ∆ ∆ ∆ ∆ltr ltr lec lcot t i t i t i i s i r i q = + + +− − − === ∑∑∑α α α α40 41 42 43 2 111 ++ + + +− − − − −∑ ∑α α ψ ε44 1 45 1 5 1 5 ∆ ∆lgdp lubn ectt i i t t i i u t t (6) ∆ ∆ ∆ ∆ lubn lubn lec lco t t i t i i r i q t i i = + + + + − − == − = ∑∑α α α α 50 51 52 11 53 2 11 54 1 55 1 5 1 5 s t i i t t i i u t t lgdp ltr ect ∑ ∑ ∑ − − − − −+ + + α α ψ ε ∆ ∆ (7) where, ect, co2t, gdpt, trt, ubnt, represent energy consumption, co 2 emissions, gdp, trade openness and urbanization, respectively. εit (for i = 1, 2, 3, 4, 5) represents serially uncorrelated random error terms. ectt−1 (error correction term) represents the co-integrating vectors. the adjustment coefficient is ψ and it shows how much disequilibrium is corrected (jamil and ahmed, 2010). to find the long term causality flowing from the dependent variable(s) to the dependent variable, the coefficient of the ect (ψ) should be significant. from equation 3, the causality from co2, gdp, tr, ubn to ec can be tested. from equation 4, the causality from ec, gdp, tr, ubn to co2 can be estimated while from equation 5, the causality from ec, co2, tr, ubn to gdp can be tested. the causality from ec, co2, gdp, ubn to tr can be estimated from equation 6 and from equation 57, the causality from ec, co2, gdp, tr to ubn can be tested. the wald test on differenced and lagged differenced terms of the dependent variables is employed to estimate the short run causality. 4. findings 4.1. unit root tests the time series properties of the variables are tested using the adf test by dickey and fuller (1984) and pp test by phillips–perron (1988). the results are presented in table 2. the results at level form show that all the five variables are nonstationary at the 5% level of significance, whereas at first difference the variables are stationary. this implies that energy consumption, economic growth, co2, trade openness and urbanization are integrated of order one. 4.2. co-integration the presence of a similar order of integration, as reported by adf and pp unit root tests, endorses the application of the johansen co-integration test. but prior to estimating co-integration among the variables, the optimum lag is determined. the results are table 2: unit root tests variables adf unit root test pp unit root test levels 1st difference levels 1st difference lco2 −1.6661 −5.9022* −1.8363 −5.8988* lenc −1.9875 −6.2656* −1.8922 −6.2663* lgdp −1.7242 −4.4481* −1.0698 −4.2660* lto −2.1026 −5.4221* −2.0581 −5.4427* lubn −1.7675 −2.0591*** −1.3083 −1.3742*** source: own calculation. *,***represent 1% and 10% significance levels, respectively. adf: augmented dickey–fuller, pp: phillips–perron, co2: carbon dioxide, gdp: gross domestic product khobai and le roux: the relationship between energy consumption, economic growth and carbon dioxide emission: the case of south africa international journal of energy economics and policy | vol 7 • issue 3 • 2017 107 illustrated in table 3. the study selects the optimum lag to be 2, according to the schwarz information criterion and akaike information criterion. co-integration among the variables is explored using the johansen co-integration test and the results are presented in table 4. the johansen co-integration test exhibits that for r = 0, the λ max statistics is 36.135, which is greater than the 95% critical value of 33.877. on the other hand, maximal trace statistics is 79.054, which is greater than the 95% critical value of 69.819. this implies that the null hypothesis r = 0 is rejected at 5% level of significance. but the results for r ≤ 1, r ≤ 2, r ≤ 3 and r ≤ 4 shows that the null hypotheses cannot be rejected. as a result, the trace test and the maximum eigen test detected the existence of a single cointegrating vector. therefore, the study concludes that there is a long run relationship between energy consumption, co2 emissions, economic growth, trade openness and urbanization in south africa. 4.3. granger-causality the direction of causality between the variables is estimated using the vecm and the findings of both long and short run causalities are presented in table 5. when energy consumption was used as the dependent variable, the lagged error term was found to negative and significant. this shows that there is one-way causality flowing from co2 emissions, economic growth, trade openness and urbanization to energy consumption in the long run. similar results were established when economic growth was used as the dependent variable. this implies that there is existence of a one way causality flowing from energy consumption, co2 emissions, trade openness and urbanization. generally, it can be realized that there is bidirectional causality flowing between energy consumption and economic growth. this shows increasing economic growth is essential for the improvement of the energy industry which in turn helps boost economic growth in south africa. the short run results exhibit no short run causality flowing between energy consumption, economic growth, co2 emissions, trade openness and urbanization. the absence of a short run causality flowing from energy consumption to economic growth means that environmentally friendly policies such as energy conservation, efficiency improvements measures and demand-side management policies can be implemented in south africa without adversely affecting economic growth. 4.4. variance decomposition tables 6-8 present variance decomposition results for co2 emissions, energy consumption and economic growth, respectively. table 6 illustrates that in the 10th year, one standard deviation shock in energy consumption, economic growth, trade openness and urbanization, reveals 8.10%, 6.97%, 11.45% and 4.61% of the forecast error variance of co2 emissions, respectively. a greater percentage of 68.88 of variation in economic growth becomes self-explanatory after 10 periods. the variance decomposition approach findings in table 7 posit that a 62.09% portion of energy consumption is contributed by its own innovative shocks. a one standard deviation shock in co2 emission explains energy consumption by 13.06% while economic growth, trade openness and urbanization support energy consumption by 9.08%, 12.09% and 3.68%, respectively. table 3: selection order criteria lag logl lr fpe aic sc hq 0 402.7047 na 1.59e-15 −19.88523 −19.6741 −19.80890 1 724.3525 546.8014 5.82e-22 −34.71763 −33.4509 −34.25964* 2 756.1016 46.03614* 4.42e-22* −35.05508* −32.7329* −34.21544 3 771.8888 18.94460 8.24e-22 −34.59444 −31.2167 −33.37315 source: own calculation. *indicates lag order selected by the criterion. lr: sequential modified lr test statistic (each test at 5%), fpe: final prediction error, aic: akaike information criterion, sc: schwarz information criterion, hq: hannan-quinn information criterion table 4: johansen co-integration h1: alternative hypothesis h0: null hypothesis λmax test λmax test (0.95) trace test trace test (0.95) r=1 r=0 36.135 33.877 79.054 69.819 r=2 r≤1 16.262 27.584 42.919 47.856 r=3 r≤2 12.232 21.132 26.658 29.979 r=4 r≤3 9.661 14.256 14.425 15.495 r=5 r≤4 4.764 3.841 4.764 3.841 source: own calculation table 5: vecm dependent variable types of causality short run long run ∑δlgdp ∑δlenc ∑δlco2 ∑δlto ∑δlubn ectt−1 δlgdp ……. 0.3189 0.1391 0.1027 1.0345 −0.005* δlenc 0.0086 ………. 0.1464 0.1783 0.3882 −0.066* δlco2 0.6474 0.1554 …………. 0.2462 1.8034 0.170* δlto 2.5025 1.5289 0.6362 ………. 0.8510 0.003 δlubn 0.3142 0.6291 0.3651 0.1978 ………. −0.106 source: own calculation. co2: carbon dioxide, gdp: gross domestic product, ect: error correction term, vecm: vector error correction model. *represent 1% significance level, respectively khobai and le roux: the relationship between energy consumption, economic growth and carbon dioxide emission: the case of south africa international journal of energy economics and policy | vol 7 • issue 3 • 2017108 table 8 illustrate the results of variance decomposition of economic growth. the results exhibit that only 3.83% of the variation in economic growth is self-explanatory, while co2 emissions accounted for a larger forecast error variance. co2 emission explain 78.60% of the forecast error variance after 10 periods. the other variables account for the remaining percentages: energy consumption (7.27%), trade openness (3.00%), and urbanization (7.30%). 5. conclusion the study analyses the relationship between energy consumption, economic growth and co2 emissions by incorporating trade openness and urbanization as the control variables to form a multivariate framework. the johansen co-integration technique and the vecm were used to estimate the long run relationship and the direction of causality among the variables. the findings of the johansen co-integration test demonstrate an existence of one co-integrating equation. this shows that there is a long run relationship between energy consumption, economic growth, co2 emission, trade openness and urbanization in south africa. the vecm results detect bidirectional causality flowing between energy consumption and economic growth. this shows that an energy-led growth hypothesis exists in south africa. the results further proved existence of a one-way causality flowing from co2 emissions, trade openness and urbanization to economic growth and energy consumption. the findings of the variance decomposition analysis show that the share of energy consumption in explaining economic growth is minimal. the results of this study indicate that policies aiming at reducing energy consumption and controlling for co2 emissions in south africa could slow down growth. this implies that any energy conservation measures undertaken should consider the adverse impact on economic growth. south africa has been found to be one of the highest co2 emitters in the world. it is therefore important that in finding ways of proving energy services, south africa table 6: variance decomposition of co2 emissions period se co2 ec gdp to ubn 1 0.019628 100.0000 0.000000 0.000000 0.000000 0.000000 2 0.026562 91.89339 4.589901 2.555510 0.156643 0.804559 3 0.030665 85.57634 7.246649 3.083585 1.711180 2.382247 4 0.033072 81.11732 7.874258 2.950823 4.377137 3.680463 5 0.034440 77.54523 8.121085 2.866657 7.083195 4.383833 6 0.035192 74.98575 8.241193 2.966109 9.158480 4.648468 7 0.035647 73.16568 8.270247 3.379795 10.47951 4.704775 8 0.036017 71.67708 8.243090 4.221844 11.17391 4.684075 9 0.036394 70.26940 8.180441 5.471839 11.43646 4.641854 10 0.036795 68.87592 8.099492 6.966451 11.44830 4.609839 co2: carbon dioxide, gdp: gross domestic product table 7: variance decomposition of energy consumption period se ec co2 gdp to ubn 1 0.015500 77.83988 22.16012 0.000000 0.000000 0.000000 2 0.020594 82.72739 14.97301 1.759080 0.098657 0.441873 3 0.023183 78.77644 14.16628 2.991576 2.271403 1.794303 4 0.024914 74.54362 14.05594 3.103013 5.430711 2.866717 5 0.025942 71.44868 13.85322 3.219925 8.080770 3.397404 6 0.026544 69.00323 13.72646 3.641936 10.01734 3.611028 7 0.026959 67.00582 13.60893 4.468539 11.24390 3.672818 8 0.027317 65.26040 13.45389 5.732366 11.87785 3.675495 9 0.027673 63.62673 13.26384 7.340313 12.10238 3.666734 10 0.028034 62.09049 13.05784 9.086054 12.08886 3.676760 co2: carbon dioxide, gdp: gross domestic product table 8: variance decomposition of economic growth period se gpd ec co2 to ubn 1 0.009458 3.194818 12.13791 84.66727 0.000000 0.000000 2 0.014698 1.655402 9.026458 87.64497 0.526282 1.146883 3 0.018176 1.123524 8.384503 85.92335 1.553330 3.015294 4 0.020480 0.884926 8.298630 83.73153 2.353602 4.731316 5 0.022015 0.850080 8.192801 82.10033 2.838178 6.018612 6 0.023039 1.127241 8.004994 80.94399 3.083956 6.839818 7 0.023719 1.715172 7.777171 80.10167 3.148813 7.257179 8 0.024172 2.477627 7.560666 79.46727 3.103363 7.391073 9 0.024471 3.232140 7.389231 78.97630 3.031177 7.371148 10 0.024663 3.830934 7.274707 78.59727 2.998905 7.298182 co2: carbon dioxide, gdp: gross domestic product khobai and le roux: the relationship between energy consumption, economic growth and carbon dioxide emission: the case of south africa international journal of energy economics and policy | vol 7 • issue 3 • 2017 109 should pay attention to the environmental impact associated with different uses of energy. it is recommended that policy makers should advocate for renewable energy such as wind and solar to ensure sustainable growth of the economy. references ahmed, m., azam, m. (2016), causal nexus between energy consumption and economic growth for high, middle and low income countries using frequency domain analysis. renewable and sustainable energy reviews, 60, 653-678. albiman, m.m., suleiman, n.n., baka, h.o. (2015), the relationship between energy consumption, co2 emissions and economic growth in tanzania. international journal of energy sector management, 9(3), 361-375. al-mulali, u., ozturk, i., lean, h.h. (2015), the influence of economic growth, urbanization, trade openness, financial development, and renewable energy on pollution in europe. natural hazards, 79(1), 621-644. arouri, m.e., youssef, a., mhenni, h., rault, c. (2012), energy consumption, economic growth and co2 emissions in middle east and north african countries. energy policy, 45, 342-349. dehnavi, j., haghnejad, a. (2012), energy consumption, economic growth, and pollution in selected opec countries: testing the environmental kuznets curve hypothesis. journal of academic research economics, 4(2), 149-167. department of energy. (2009), energy information management. digest of south african energy statistics. pretoria, south africa: process design and publications. jamil, f., ahmed, p. (2010), the relationship between electricity consumption, electricity prices and gdp in pakistan. energy policy, 38, 6016-6025. johansen, s. (1988), statistical analysis of cointegration vectors. journal of economics dynamic and control, 12, 231-254. johansen, s., juselius, k. (1990), maximum likelihood estimation and inference on cointegration with applications to the demand for money. oxford bulletin of economics and statistics, 52, 169-210. kais, s., sami, h. (2016), an econometric study of the impact of economic growth and energy use on carbon emissions: panel data evidence from fifty eight countries. renewable and sustainable energy reviews, 59, 1101-1110. kraft, j., kraft, a. (1978), on the relationship between energy and gnp. journal of energy development, 3, 401-403. linh, d.h., lin, s. (2014), co2 emissions, energy consumption, economic growth and fdi in vietnam. managing global transitions, 12(3), 219-232. menyah, k., wolde-rufael, y. (2010), energy consumption, pollutant emissions and economic growth in south africa. the journal of energy economics, 32, 1374-1382. moubarak, m., lin, b. (2014), renewable energy consumption economic growth nexus in china. renewable and sustainable energy reviews, 40, 111-117. odhiambo, n.m. (2010), energy consumption, prices and economic growth in three ssa countries: a comparative study. journal of energy policy, 38, 2463-2469. okafor, h.o. (2012), testing the relationship between energy consumption and economic growth: evidence for nigeria and south africa. journal of economics and sustainable development, 3(11), 111-124. ozturk, i., al-mulali, u. (2015), investigating the validity of the environmental kuznets curve hypothesis in cambodia. ecological indicators, 57, 324-330. pablo-romero, m.d.p., de jesús, j. (2016), economic growth and energy consumption: the energy-environmental kuznets curve for latin america and the caribbean. renewable and sustainable energy reviews, 60, 1343-1350. phillips, p.c.b., perron, p. (1988), testing for unit roots in time series regression. biometrika, 75, 335-346. said, s.e., dickey, d. (1984), testing for unit roots in autoregressive moving-average models with unknown order. biometrika, 71, 599-607. saidi, k., hammami, s. (2014), energy consumption and economic growth nexus: empirical evidence of tunisia. american journal of energy research, 2(4), 81-89. shyamal, p., rabindra, n.b. (2004), causality between energy consumption and economic growth in india: a note on conflicting results. journal of energy economics, 26, 977-983. streimikiene, d., kasperowicz, r. (2016), review of economic growth and energy consumption: a panel cointegration analysis for eu countries. renewable and sustainable energy reviews, 59, 1545-1549. tang, c.f., tan, b.w., ozturk, i. (2016), energy consumption and economic growth in vietnam. renewable and sustainable energy reviews, 54, 1506-1514. usaid. (2016), greenhouse gas emissions in south africa. available from: http://www.users/cqwanzcho/downloads/ghg%20 emissions%20fact%20sheet%20south%20africa%20-%207-516%20usaidsacomm_rev08-26-16_clean%20(1). [last accessed on 2017 feb 20]. vidyarthi, h. (2013), energy consumption, carbon emissions and economic growth in india. world journal of science, technology and sustainable development, 10(4), 278-287. vidyarthi, h. (2014), an econometric study of energy consumption, carbon emissions and economic growth in south asia: 1972-2009. world journal of science, technology and sustainable development, 11(3), 182-195. wang, y., chen, l., kubota, j. (2016), the relationship between urbanization, energy use and carbon emissions: evidence from a panel of association of southeast asian nations (asean) countries. journal of cleaner production, 112, 1368-1374. wolde-rufael, y. (2009), energy consumption and economic growth: the experience of african countries revisited. journal of energy economics, 31, 217-224. . international journal of energy economics and policy | vol 6 • issue 2 • 2016222 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2016, 6(2), 222-233. energy efficiency and sustainable development: an analysis of financial reliability in energy service companies industry gianpaolo iazzolino1*, rossella gabriele2 1department of mechanical, energy and management engineering, university of calabria, building 46/c, 87036 rende (cs), italy, 2department of mechanical, energy and management engineering, university of calabria, building 46/c, 87036 rende (cs), italy. *email: gp.iazzolino@unical.it abstract the aim of this study is twofold: (i) at first, the authors would like to analyze the financial reliability of energy service companies (esco) industry in italy by using the z” score model by altman et al. (1995) and (ii) secondly, observing the trend of z’’ values from the year 2010 to the year 2014, they would try to connect these changes to specific business behaviors. an empirical research on a sample of 68 italian escos has been carried out. by analyzing balance sheet indicators, the authors identify the causes that entail the transition of firms from a specific solvency situation to another. findings show that in most cases z’’ score increased over the years thanks to the acquisition of white certificates, that represents an efficient instrument to promote energy saving. research results allow to hope in a future development of esco industry. keywords: financial reliability, energy service companies, z-score, italian companies jel classifications: c20, g33, m41 1. introduction by sustainable growth strategies we mean the firm behaviors that in the long run tend to legitimize the social, environmental and economic expectations of both internal and external stakeholders (donaldson and preston, 1995). sustainable development represents a key element of environmental safety and it is one of the most debated topic of the last years. the need to reconcile economic growth with a fair distribution of resources in a new development model began to appear from the seventies, after becoming conscious of the fact that the concept of classic development would have caused the collapse of natural systems. among all the definitions of sustainable development, one of the most important was given by the brundtland commission (world commission on environment and development): “the development that meets the needs of the present without compromising the ability of future generations to meet their own needs.” this paper focuses on the topic of energy sustainability. many studies were carried out in the literature: zajicek et al. (2016) discuss the u.s. energy sector in the context of economic growth, employment conditions, manufacturing competitiveness, and trade deficits in order to expand the use of domestic energy resources to improve competitiveness in the global goods market and reduce dependency on foreign oil. the concept of energy sustainability is strictly connected to the concept of sustainable development by a tridimensional approach which considers production side (promotion of renewable energy sources), utilization side (energy efficiency) and environmental impact. energy efficiency improvements are in many countries a key part of the strategy to reduce energy consumption and to tackle global warming (gonzález and ventosa, 2015). iazzolino and gabriele: energy efficiency and sustainable development: an analysis of financial reliability in energy service companies industry international journal of energy economics and policy | vol 6 • issue 2 • 2016 223 energy efficiency can be defined as the ability to carry out normal actions of energy operation with less energy than it was used previously, reducing consumptions and obtaining an immediate saving, not only at a monetary level. as enea (italian agency for new technologies, energy and sustainable development) states, doing energy efficiency can be translated in “doing more with less,” thanks to a reliable and aware behavior in using energy and reducing waste. therefore, “energy efficiency” indicates a series of actions in programming, planning and realizing that allow to consume less energy, offering services being equal. in this context the role of energy service companies (escos) can be introduced. they are companies specialized in energy services with a great availability of know-how, technologies and capital strongly pointed to the realization of energy requalification projects (dayton et al., 1998; singer and lockhart, 2002). escos offer a service that includes finding of financial resources linked to the intervention, realization of energetic diagnosis, feasibility studies, design and realization of interventions and their future maintenance and efficiency control. in order to do this, these companies typically resort to the mechanism of the third party financing (tpf), which allows them to benefit from the results of the intervention, based on achieved energetic saving. in this way escos can offer service to the client (private or public) at zero cost. however, it is not always so simple to start this type of projects. the greatest stop could be the lack of financial sources, especially in current years characterized by an evident economic crisis, during which it is very difficult to find capitals. hence, it could be happen that escos do not have available capital to finance their projects and must necessarily turn to banks to obtaining such resources. nevertheless, lending institutions grant loans only if they are sure that granted capital will be turned within established terms. the paper is organized as follows: section 2 presents literature analysis on topics of (i) financial reliability and (ii) escos; section 3 describes research methodology; section 3 illustrates the sample of companies used in the research; section 5 shows the results of escos’ financial reliability and section 6 presents results discussion and considerations on the variation of reliability on considered time horizon; in the end, last section of paper illustrates conclusions, including limits and possible developments for future studies. 2. literature review 2.1. financial reliability analysis three different groups of models for credit risk evaluation can be identified: (i) structural credit risk models; (ii) reduced form models; and (iii) methodologies taken from the field of artificial intelligence and operational research (hybrid models). structural credit risk models rely on the notion of claim priority and limited liability, which allows a firm’s equity and debt to be viewed as contingent claims that partition the asset value of the firm. many applications and improvements have been proposed (iazzolino, fortino, 2012, iazzolino et al., 2013b). some difficulties in implementation motivates an alternative approach known as reduced-form (the second group), which considers corporate default as an event governed by an exogenous shock that is not based on the firm’s asset value failing to cover its debt obligation. the third group, hybrid approach, uses discriminant analysis, logistic regression, artificial neural networks and mars and hence provides an alternative in handling credit scoring tasks. lee et al. (2006) demonstrated the effectiveness of credit scoring using mars, revealing that they outperform other approaches in terms of credit scoring accuracy. very recently, mars has been modified by constructing a penalized residual sum of squares as a tikhonov regularization problem, providing an alternative modelling technique named cmars (alp et al., 2011; weber et al., 2012). a hybrid model integrating rough set theory with support vector machines technique has been proposed by ching-chiang et al. (2010). another model that is proposed as a credit risk evaluation tool for business loan applications is data envelopment analysis model (dea). in particular, the model incorporates uncertainty to predict the loan applicant’s relative creditworthiness condensed in a single score reflecting a potential borrower’s future loan performance (bruni et al., 2014; iazzolino et al., 2013a). kuosmanen and johnson (2010) establish linkages between least-squares regression and dea models, contributing to the integration of the non-parametric regression approaches towards a unified framework of prediction of credit default. dea approach is also used for other aims like energy efficiency, as dogan and tugcu (2015) demonstrate adopting input oriented dea based on the charnes, cooper and rhodes model to estimate technical and super efficiency scores of g-20 countries in terms of electricity production for certain periods. as specifically regards the model based on financial indicators, we can distinguish the univariate and the multivariate models. the seminal works in this field were beaver (1966) and altman (1968). beaver (1966) started up the univariate models, concluding that cash flow to debt ratio was the best single ratio predictor. univariate models often overlap with qualitative models. many models have been generated that put in connection ebit and interest expenses: the most known is the model by damodaran (2002). the multivariate models, among which the first contribution was given by altman (1968), are based on the concept that the identification of the point of probable insolvency (cut-off) depends on the weighting of different indicators, selected within the set of the most significant financial risk indicators. altman’s z is one of the best known, statistically derived predictive models used to forecast a firm’s impending bankruptcy (moyer, 2005). the z-score uses various accounting ratios iazzolino and gabriele: energy efficiency and sustainable development: an analysis of financial reliability in energy service companies industry international journal of energy economics and policy | vol 6 • issue 2 • 2016224 and market-derived price data to predict financial distress and future bankruptcy and the original formula was developed on a sample of 66 manufacturing firm. however, in response to requests for a measure to predict the likelihood of bankruptcy for non-manufacturing firms, altman developed the z” model, (altman and hotchkiss, 2006). for many years after the publication, altman’s formula was the prevalent statistical technique applied to the default prediction models. it was used by many authors (altman et al., 1977; micha, 1984; piesse and wood, 1992; lussier, 1995; altman et al., 1995). in recent years, advanced techniques such as neural networks (altman and sabato, 2007), genetic programming (huang et al., 2004; varetto, 1998) and support vector machine (xu et al., 2009) have been proposed in the empirical literature. these techniques are based on data mining techniques, i.e., the design and development of algorithms that allow computers to predict behaviour based on empirical data and are able to model extremely complex functions, providing an alternative to conventional techniques. 2.2. esco and energy efficiency escos are important agents to promote energy efficiency improvements, especially in those countries experiencing increased competition and privatization in the electric utility business (vine et al., 2003). an esco is a company that fulfils all the following requirements: it provides integrated energy services to their customers (mainly large energy users, but also utilities), which may include implementing energy-efficiency projects (and renewable energy projects), frequently on a turn-key basis. in particular, they include a wide range of activities, such as energy analysis and audits, energy management, project design and implementation, maintenance and operation, monitoring and evaluation of savings, provision of services like lightning or space heating (bertoldi et al., 2006). an esco provides performance and savings guarantees, and its remuneration is directly tied to the energy savings achieved. therefore, the company risks its payments on the performance of equipment and services implemented. it typically finances, or assists in arranging financing for the installation of an energy project it implement by providing a savings guarantee. it also retains an on-going operational role in measuring and verifying the savings over the financing term. many studies examine the growth and potential market for the esco industry in the united states (goldman et al., 2002; vine et al., 1999). goldman et al. (2002), for example, analyses a database of 1500 case studies of energy-efficiency projects, estimating that esco industry revenues in the us increased at an average annual growth rate of 24% in the last decade. other studies (bertoldi et al., 2003; biermann, 2001; fraser, 1996; murakoshi et al., 2000; poole and geller, 1997; vine, 2005) try to recreate esco industry development in many countries, identifying the origin of these companies in the early eighties for most of them, including italy. however, persistent barriers inhibit many cost-effective energy efficiency projects and prevent the full development of the esco industry internationally. some major barriers are: lack of information and understanding of the opportunities that energy efficiency offer; lack of culture for project financing; public procurement rules that prevent the use of escos; burdensome administrative procedures that allow only very large projects to be carried out; limited understanding of energy efficiency and performance contracting by financial institutions (westling, 2003a; 2003b). although some researchers are optimistic about the future of the esco industry, others argue that several types of strategic actions are needed for fostering the development of the esco industry internationally. for example, to move in this direction europe commission joint’s research centre plans to create a comprehensive list of esco in the european union, including a description of their projects, capabilities, and illustrative case studies (bertoldi et al., 2003). other actions are to ensure that escos provide a qualified and reliable service and to create more information for financial institutions in order to develop funding sources. by the way, esco often need working capital for marketing and project preparation and development. referring to performance contracting, three broad options for financing energy efficiency improvements can be distinguished: (i) esco financing, that refers to financing with internal funds of the esco and may involve use of its own capital or funding through other debt or lease instruments; (ii) energy-user/customer financing, that usually involves financing with internal funds of the user/customer backed by an energy savings guarantee provided by the esco and finally (iii) third-party financing (tpc), that is the most used source of financing energy efficiency projects in which project financing comes from a third party, e.g. a finance institution, and not from internal funds of the esco or of the customer. large escos with deep pockets and hence high credit rating have started to prefer tpf to their own funds because their costs of equity financing and long-term financing are often much greater than what can be accessed in the financial markets. in addition, if an esco arranges tpf, then its own risk is smaller. this would allow for lower cost of money and hence for the same level of investment more money would be assigned to the project. prevision of companies insolvency and, consequently, of financial reliability in the brief and long term is a theme that became more important in the current context, characterized by serious economic problems. however, studies that examine the level of financial reliability of italian escos do not exist in the literature. in this paper altman z’’ model is applied on a sample of italian esco in order to assess their level of solvency. the model, that is an enhancement of altman z score model, is based on iazzolino and gabriele: energy efficiency and sustainable development: an analysis of financial reliability in energy service companies industry international journal of energy economics and policy | vol 6 • issue 2 • 2016 225 a fundamental financial review derived from a quantitative risk model (altman et al., 1995). 3. research objectives and methodology the aim of the research is two fold: (i) to analyze the financial reliability of italian escos by using the z’’ score model (altman, 1995) and the trend analysis from the year 2010 to 2014; (ii) to deeply analyze the indicators that generated the change in rating and to identify the specific organizations’ behaviors related to these changes. objective n. 1 is presented in section 4 (research results), whereas objective n. 2 is analyzed in section 5, which focuses on the discussion. as regards the first aim of research, insolvency level of organizations has been assessed through altman z’’ score model (revised version of 1995), because it is more suitable for the sample considered in this paper. therefore, the z’’ score is calculated by the following formula: z’’ = 3.25 + 6.56 x1 + 3.26 x2 + 6.72 x3 + 1.05 x4 where: x1 = working capital/total assets x2 = retained earnings/total assets x3 = operating income/total assets x4= book value equity/total liabilities. altman and hotchkiss (2006) identify three classification areas of insolvency risk, considering z’’ value, that are represented in figure 1. figure 2 shows in detail the correspondences between z’’ values and ratings assigned to obligations by international agency standard and poor’s. the safe zone includes all situations in which insolvency risk is null; an elevate risk is identified by the distress zone, whereas the grey zone represents situations of uncertainty, for which become difficult to forecast future trend of financial reliability of the company. z’’ value has been calculated punctually on considered years, focalizing attention on the variation of firms’ number belonging to three zones, in order to understand if they improved their score or not. finally, relating to the second objective of research, we tried to link the causes of score variations to typical firms’ behaviors. 4. dataset to analyze financial reliability of escos, this study utilizes a sample extracted from aida bureau van dijk database, which includes all balance sheets of small, medium and large italian companies. the sample is characterized by 68 escos, shown in table a1 in appendix. the companies have been classified based on following characteristics: • size • localization • sector. as regards the first point, the majority of firms considered in the sample ranks as micro (38%) and small (31%) firms, with a turnover lower than 10 thousands euros and with a number of employees lower than 50. the chart represented below shows companies’ size (figure 3). figure 1: classification area of risk 38% 31% 15% 16% companies size micro companies small companies medium companies large companies figure 3: companies size figure 2: correspondences between z'' values and ratings source: adapted by altman and hotchkiss (2006) iazzolino and gabriele: energy efficiency and sustainable development: an analysis of financial reliability in energy service companies industry international journal of energy economics and policy | vol 6 • issue 2 • 2016226 escos are located especially in north-italy (26 companies in lombardy) and they appear almost absent in the regions of southitaly, as shown in figure 4. escos act their energetic requalification projects in different sectors, which are indicated by ateco codes in the figure 5. the chart shows that the majority of firms belongs to sector m (45.59%). sectors f and d are relevant. 5. results of financial reliability analysis (objective 1) table a2, represented in the appendix of the paper, highlights z’’ score values for each company on every considered year, from 2010 to 2014. the minimum absolute value of index z’’ (−4.86) is achieved on 2010, the first year of time horizon, whereas the maximum one is obtained on year 2014 and it is equal to 585.06. the average z’’ score trend for every year is illustrated in the figure 6. the average score has a constant trend on all the years from 2010 to 2013, then it shows a peak in 2014. in particular, referring to rating classes in figure 2, the score swings from safe zone (null risk area) and grey zone (uncertain risk area). in effect: • on 2010 the average score is 5.91 that corresponds to the rating class bbb which belongs to the grey zone. however, it is a matter of a value that gets close to the null risk zone rather than the high risk area. • on 2011 the average score is 6.26 that corresponds to the rating class bbb which belongs to the safe zone, that is the null risk area. • on 2012 the average score is 6.22 that corresponds to the rating class bbb which belongs to the grey zone. as it happened for 2010, it is a matter of a value that gets close to the null risk zone rather than the high risk area. • on 2013 the average score is 6.95 that corresponds to the rating class a which belongs to the safe zone, that is the null risk area. • on 2014 the average score is 15.61 that corresponds to the rating class aaa which belongs to the safe zone, that is the null risk area. table a3 in appendix resumes both achieved z’’ score and rating class for each year and for each company. starting from 2012 the number of firms belonging to the safe zone is increased, especially from 2013 to 2014. consequently, firms characterized by a high insolvency risk decrease over the years, whereas those belonging to the grey zone increase if comparing the year 2010 with the year 2014 but they decrease if comparing 2014 with previous years. observing the first and the last column in table 1, we can evaluate in percentage the number of companies in the three risk area from the first considered year to the last one. escos financial reliability improved from the year 2010 to the year 2014 as the number of firms belonging to the safe zone increases whereas that belonging to the distress zone decreases. as regards the grey zone, the number of companies remains almost constant over the years. 26 8 7 6 5 5 4 4 1 1 1 sample localization figure 4: sample localization 0 5 10 15 20 25 30 35 m f d g c n j 31 17 9 5 4 1 1 operating sectors legenda • m professional, scientific e technical activities • f building • d provision of electric energy, gas, vapor and conditioned air • g wholesale and retail • c manifacturing activities • n rental, travel agencies, companies support services • j communication and information services figure 5: operating sectors of energy service companies iazzolino and gabriele: energy efficiency and sustainable development: an analysis of financial reliability in energy service companies industry international journal of energy economics and policy | vol 6 • issue 2 • 2016 227 the passage from a certain risk zone to another depends on the value of index z’’, that in turn is linked to the values of balance sheet indicators described in section 2. to identify the causes that allow the transition of firms from the safe zone to the distress zone and vice versa on period 2010-2014 we have observed variation of balance sheet indicators, finding in most cases that: • the reduction of z’’ score and the consequent passage from the safe zone to the distress zone is mainly due to the increase of short-term debts, due to an increase of notes and accounts payable • the increase of z’’ score and the consequent passage from the distress zone to the safe zone is mainly due to the increase of accounts receivable. 6. results discussion and identification of firms’ behaviors (objective 2) the application of z’’ score model allows to characterize escos industry in italy from the financial reliability point of view. by the way, evaluating this index for every year it is possible to identify for each company their own rating class. as described in previous section, while the presence of companies in distress zone decreases by 16.78% compared to the year 2010, companies in the safe zone increases by 14.71%. in particular: 1. the safe zone acquires 15 companies (11 from distress and 4 from grey) 2. the distress zone loses 18 companies (11 from safe and 7 from grey). moreover, from the analysis of average z’’ score we can state that esco industry belongs on average to the null risk area. in effect, starting from 2010 to 2013, the average score remains more or less constant, but on the year 2014 it becomes subjected to a positive increase of 8.65% compared to the previous year. positive or negative variation causes that have been found on considered time horizon have been studied by detailed balance sheet analysis by which we identified a relationship between score’s increase and credits’ increase. reduction of z’’ is mainly due to the increase of financial and commercial debts instead. these results can be justified by some behaviors that an esco typically assumes. 6.1. rating growth due to increase of accounts receivable the increase of accounts receivable have a positive impact on score growth and on rating. the item “accounts receivable” is strictly connected to the achievement of “white certificates,” that represent the most important and efficient instrument to incentivize energy saving in italy and the mainframe of any sustainable energy strategy to contrast the threats of climate change. in the past few years, italy, france and great britain have embarked on implementing tradable certificate schemes to improve energy efficiency, so-called “tradable white certificate” schemes. in this system, electricity and gas suppliers or distributors are obliged to undertake the promotion of energy efficiency among final uses, and to show that they implement, each year, interventions designed to save an amount of energy that is a given percentage of the energy they supply or distribute. this amount is certified through certificates (the ‘‘white certificates’’) that are generated when the obligated parties themselves, or other actors, introduce energy saving measures. such certificates can be exchanged and traded on the market. obligated parties unable to submit their share of certificates are subject to pecuniary sanctions exceeding the estimated market value of the missing certificates. the application of the mechanism of whc involves in any case an increase of the investments in new technologies for energy utilisation. the low target scenario implies for the year 2020 an increase of 7% in investments in energy demand technologies for the residential and service sectors relative to the business-as-usual scenario, while the average unit cost of the energy system is decreased. for the more ambitious medium and high scenarios, investments in technology grow much more: for the year 2020 by 30% and 80% respectively. therefore, even when there is a trade-off between cost of saving and value of the energy saved, there will be a displacement from expenditure for fuels to investment in new technology, which in itself is likely to have a positive effect on the economy as a whole. figure 6: average z'' score from 2010 to 2014 table 1: number of escos in every risk zone from 2010 to 2014 (%) risk area year 2010 2011 2012 2013 2014 safe zone 32.35 30.88 35.29 35.29 47.06 grey zone 14.71 17.65 23.53 23.53 16.18 distress zone 52.94 51.47 41.18 41.18 36.76 escos: energy service companies iazzolino and gabriele: energy efficiency and sustainable development: an analysis of financial reliability in energy service companies industry international journal of energy economics and policy | vol 6 • issue 2 • 2016228 recent developments in european energy policy reveal a growing interest in creating markets aiming to boost energy efficiency cost-effectively. more in-depth descriptions are provided in lagniss and praetorius (2006), farinelli et al. (2005). 6.2. rating reduction due to the increase of shortterm debts balance sheet analysis conducted on the dataset highlights that the increase of short-term debts strongly influences score reduction and rating, because it entails the increase of total debts hence the reduction of variable x4. in particular, short-term debts may be classified in two groups: • notes payable • accounts payable. the increase of the former can be explained by the fact that escos often resort to the tpf, that expects to require financial sources to lending institutes (i.e., banks) to realize energetic requalification projects. figure 7 illustrates the relations existing in this type of performance contracting. hence it is clear that in most cases escos, and not clients, directly establish contractual agreements with banks. when the esco is the borrower, the customer is safeguarded from financial risks related to the project technical performance because the savings guarantee provided by the esco is either coming from the project value itself or is appearing on the balance sheet of the esco. both public and private customers can benefit from off-balance sheet financing because the debt service is treated as an operational expense and not a capital obligation. for highly leveraged companies this is important because the obligation not showing up on the balance sheet as debt means that company borrowing capacity is freed up (dixon, et al., 2010). accounts payables are mainly due to the purchase of equipment, that are expected in esco interventions. by the way esco does not produces internally all the materials and machinery that are necessary to the requalification project, but it chooses to buy them externally preferring a buy strategy to a make one. 7. limits, future development and conclusions the main aim of the study is to provide a general description of the degree of financial reliability of escos in italy, in order to give also a measure of their work on the territory. escos represent one of principal instrument to promote energy efficiency in final uses. through the plan and the realization of specific energetic requalification projects, escos support their own clients in achieving social and economic objectives. the energetic requalification interventions as power factor compensation, routine or emergency maintenance, realization of plants build according to rules, entail evident economic savings in bill and decrease environmental impact of production processes by reducing waste and noxious emissions and utilizing optimally the resources. however, to carry out all activities of core business escos do not always have the possibility to manage their own work only by their capital, but they are forced to turn to lending institutes that grant them necessary financial sources. several possible funding sources should be investigated: private banks and lending institutions; financial institutions that are already familiar with energy performance contracting; multi-lateral funders and donor agencies (vine, 2005). hence, it is important to identify as far as possible the exact degree of reliability of such companies as banks agree to activate the funding only once assured of their solvency. for this reason, research methodology takes into account 68 companies on italian territory, whom balance sheet have been extracted from aida bureau van dijk database. first of all, starting from altman revised model (1995), a mapping of dataset has been carried out based on z’’ score value; in this way each company has been placed in a specific risk area for every year, from 2010 to 2014. then, we put attention on the variation of score value between the first and the last year of time horizon, observing as consequence the movement of many firms from a specific risk zone to another one. the increase of companies that pass from a situation characterized by an elevate insolvency risk (distress zone) to a state of financial safety (safe zone) has been major than that of companies that have been subjected to the inverse passage. financial reliability of such companies has been grown over the years, showing an important improving of financial conditions that allow the possibility to obtain funds to apply energetic requalification projects. finally, we tried to identify the main causes related to the improvement and to the worsening of financial reliability conditions through a detailed balance sheet analysis from which we demonstrated that the increase of accounts receivables (related to white certificates) positively influence z’’ score, whereas the source: adapted from bertoldi, 2006 figure 7: third party financing with energy service companies borrowing iazzolino and gabriele: energy efficiency and sustainable development: an analysis of financial reliability in energy service companies industry international journal of energy economics and policy | vol 6 • issue 2 • 2016 229 increase of total debts contributes to a reduction of the score and, consequently, to an increase of insolvency level. the results of research could be improved if considering a sample with a larger size. another limit of the study can be identified in the decision to choose altman model as statistic prevision method. early scholars criticized altman’s formula as having a poor record as predictor despite altman’s explanation for a bankrupt (hayes et al., 2010). in a test of altman’s z grice and ingram (2001) found inconsistent results because the formula was not suitable for predicting distress in contemporary firms. in general, the result of research shows that in recent years escos have been subjected to a strong improvement in their financial situation, achieving a higher probability in obtaining necessary resources. findings let us imagine in a possible development of this industry. moreover, companies operating in energy efficiency certificates market are able to obtain more credits than others, achieving a high rating. in conclusion, this study provides an important description of escos industry in italy from a financial point of view, because it does not only highlights the importance of their work that promotes sustainable development on territory but tries to give an contribute related to a sector that is still new in italy. references alp, o.s., büyükbebeci, e., çekitç, a.i., özkurt, f.y., taylan, p., weber, g.w. (2011), cmars and gam and cqp – modern optimization methods applied to international credit default prediction. journal of computational and applied mathematics, 235(16), 4639-4651. altman, e.i. (1968), financial ratios, discriminant analysis and the prediction of corporate bankruptcy. journal of finance, 23, 589-609. altman, e.i., haldeman, r.g., narayanan, p. (1977), zeta-analysis: a new model to identify bankruptcy risk of corporations. journal of banking and finance, 1(1), 29-54. altman, e.i., hartzell, j., peck, m. (1995), emerging markets corporate bonds: a scoring system. new york: salomon brothers inc. altman, e.i., hotchkiss, e. (2006), corporate financial distress & bankruptcy. 3rd ed. hoboken, nj: john wiley & sons. altman, e.i., sabato, g. (2007), modelling credit risk for smes: evidence from the us market. abacus, 43(3), 332-357. beaver, w.h. (1966), financial ratios as predictors of failure. empirical research in accounting: selected studies. journal of accounting research, 4, 71-111. bertoldi, p., berrutto, v., renzio, m., adnot, j., vine, e. (2003), how are eu escos behaving and how to create a real esco market? proceedings of the 2003 eceee summer study, european council for an energy-efficient economy, paris, france. p909-916. bertoldi, p., rezessy, s., vine, e. (2006), energy service companies in european countries: current status and a strategy to foster their development. energy policy, 34(14), 1818-1832. biermann, a. (2001), escos in the liberalised domestic uk energy markets-barriers to establishing escos and possibilities to overcome them in the uk energy markets. vol. 2. proceedings of the 2001 eceee summer study, european council for an energy-efficient economy, paris, france. p437-446. bruni, m.e., beraldi, p., iazzolino, g. (2014), lending decisions under uncertainty: a dea approach. international journal of production research, 52(3), 766-775. ching-chiang, y., der-jang, c., ming-fu, h. (2010), a hybrid approach of dea, rough set and support vector machines for business failure prediction. expert systems with applications, 37(2), 1535-1541. damodaran, a. (2002), investment valuation: tools and techniques for determining the value of any asset. new york: john wiley and sons. dayton, d., goldman, c., pickle, s. (1998), the energy services company (esco) industry: analysis of industry and market trends. vol. 6. proceedings of the 1998 aceee summer study, american council for an energy-efficient economy, washington, dc. p29-45. dixon, r.k., mcgowan, e., onysko, g., scheer, r.m. (2010), us energy conservation and efficiency policies: challenges and opportunities. energy policy, 38(11), 6398-6408. dogan, n.o., tugcu, c.t. (2015), energy efficiency in electricity production: a data envelopment analysis. international journal of energy economics and policy, 5(1), 246-252. donaldson, t., preston, l. (1995), the stakeholder theory of corporation: concepts, evidence and implications. academy of management review, 20(1), 65-91. farinelli, u., johansson, t.b., mccormick, k., mundaca, l., oikonomou, v., ortenvik, m., patel, m., santi, f. (2005), white and green: comparison of market based instruments to promote energy efficiency. journal of cleaner production, 13, 1015-1026. fraser, m. (1996), what makes the canadian esco industry unique? vol. 10. proceedings of the 1996 summer study on energy efficiency in buildings, american council for an energy efficient economy, washington, dc. p39-45. goldman, c., osborn, j., hopper, n., singer, t. (2002), market trends in the us esco industry: results from the naesco database project, lbnl-49601. berkeley, ca: lawrence berkeley national laboratory. gonzález, j.f., ventosa, i.p. (2015), energy efficiency policies and the jevons paradox. international journal of energy economics and policy, 5(1), 69-79. grice, j.s., ingram, r.w. (2001), tests of the generalizability of altman’s bankruptcy prediction model. journal of business research, 54(1), 53-61. hayes, s.k., hodge, k.a., hughes, l.w. (2010), a study of the efficacy of altman’s z to predict bankruptcy of specialty retail firms doing business in contemporary times. economics & business journal: inquiries & perspectives, 3(1), 122-134. huang, z., chen, h., hsu, c.j., chen, w.h., wu, s. (2004), credit rating analysis with support vector machines and neural networks: a market comparative study. decision support systems, 37(4), 543-558. iazzolino, g., fortino, a. (2012), credit risk analysis and the kmv-black and scholes model: a proposal of correction and an empirical analysis. investment management and financial innovations, 9(2), 167-181. iazzolino, g., bruni, m.e., beraldi, p. (2013a), using dea and financial ratings for credit risk evaluation: an empirical analysis. applied economics letters, 20(14), 1310-1317. iazzolino, g., migliano, g., gregorace, e. (2013b), evaluating intellectual capital for supporting credit risk assessment: an empirical study. investment management and financial innovations, 10(2), 44-54. kuosmanen, t., johnson, a.l., (2010), data envelopment analysis as nonparametric least-squares regression. operations research, 58(1), 149-160. lagniss, o., praetorius, b. (2006), how much market do market-based instruments create? an analysis for the case of ‘white’ certificates. energy policy, 34(2), 200-211. lee, t.s., chiu, c., chou, y.c., lu, c.j. (2006), mining the customer credit using classification and regression tree and multivariate adaptive regression splines. computational statistics and data iazzolino and gabriele: energy efficiency and sustainable development: an analysis of financial reliability in energy service companies industry international journal of energy economics and policy | vol 6 • issue 2 • 2016230 analysis, 50, 1113-1130. lussier, r.n. (1995), a non-financial business success versus failure prediction model for young firms. journal of small business management, 33(1), 8-20. micha, b. (1984), analysis of business failures in france. journal of banking and finance, 8(2), 281-291. moyer, s.g. (2005), distressed debt analysis: strategies for speculative investors. fort lauderdale, fl: ross publishing. murakoshi, c., nakagami, h., sumizawa, t. (2000), exploring the feasibility of esco business in japan: demonstration by experimental study. vol. 5. proceedings of the 2000 summer study on energy efficiency in buildings, american council for an energy efficient economy, washington, dc. p231-241. piesse, j., wood, d. (1992), issues in assessing mda models of corporate failure: a research note. british accounting review, 24(1), 33-42. poole, a., geller, h. (1997), the emerging esco industry in brazil. washington, dc: american council for an energy efficient economy. singer, t., lockhart, n. (2002), iea dsm task x-performance contracting, country report: united states. paris, france: international energy agency. varetto, f. (1998), genetic algorithms applications in the analysis of insolvency risk. journal of banking and finance, 22(10), 1421-1439. vine, e., nakagami, h., murakoshi, c. (1999), the evolution of the us energy service company (esco) industry: from esco to super esco. energy-the international journal, 24(6), 479-492. vine, e., hamrin, j., crossley, d., maloney, m., watt, g. (2003), public policy analysis of energy efficiency and load management in changing electricity businesses. energy policy, 31(5), 405-430. vine, e. (2005), an international survey of the energy service company (esco) industry. energy policy, 33, 691-704. xu, x., zhou, c., wang, z. (2009), credit scoring algorithm based on link analysis ranking with support vector machine. expert systems with applications, 36(2), 2625-2632. weber, g.w., batmaz, i., koksal, g., taylan, p., ozkurt, f.y. (2012), cmars: a new contribution to nonparametric regression with multivariate adaptive regression splines supported by continuous optimization. inverse problems in science and engineering, 20(3), 371-400. westling, h. (2003a), performance contracting. summary report from the iea dsm task x within the iea dsm implementing agreement. paris, france: international energy agency. westling, h. (2003b), energy performance contracting will improve climate and business. proceedings of the 2003 eceee summer study, european council for an energy-efficient economy, paris, france. p1041-1047. zajicek, e.k., karagiannis, n., wilhoit, t. (2016), could the u.s. energy sector become new engine for growth? international journal of energy economics and policy, 6(1), 113-119. table a1: esco considered in the research esco a2a calore e & servizi fostini s.r.l. adria energy e.s.co s.r.l. g.m.t. s.p.a. aice s.c. a r.l. geetit s.r.l. amga calore & impianti s.r.l. global power service s.p.a. area engineering s.r.l. hera comm s.r.l. aura energy s.r.l. innowatio s.p.a. avvenia s.r.l. interesco srl axopower s.r.l. jpe 2010 azzero co2 s.r.l. menowatt ge s.p.a. bartucci spa meridionale impianti s.p.a. bit energia s.r.l. nesco north energy service company s.r.l. c.e.i. s.p.a. calore energia impianti newen s.r.l. carbotermo s.p.a. nrg. it s.r.l. casadei & pellizzaro s.r.l. om.e.g. srl centoraggi societa’ cooperativa oros p&r srl e oros progetti srl centro calor s.r.l. pagano e ascolillo energy and technology s.p.a. co.meta societa’ cooperativa consortile polo tecnologico per l’energia s.r.l. cofely italia s.p.a. ranzato impianti s.r.l. consul system s.p.a. restiani s.p.a. cremonesi consulenze s.r.l. sangalli technologies esco s.r.l. cristoforetti servizi energia s.p.a. saras ricerche e tecnologie s.p.a. dedalo esco s.p.a. sea servizi energia ambiente s.r.l. diddi dino e figli s.r.l. seaside s.r.l. e.on energia s.p.a. sime energia s.r.l. energest s.r.l. siram s.p.a. energon esco s.p.a. sof s.p.a. energynet s.r.l. solgen s.r.l. e.s.co. berica s.r.l. studio botta & associati srl e.s.co. comuni s.r.l. studio mps engineering s.r.l. esco italia s.r.l. tea servizi s.r.l. e.s.co. primiero s.r.l. tep energy solution ets life s.r.l. tera energy s.r.l. eureka e.s.co. s.r.l. ulteria s.r.l. fedabo s.p.a. universal sun s.r.l. escos: energy service companies appendix iazzolino and gabriele: energy efficiency and sustainable development: an analysis of financial reliability in energy service companies industry international journal of energy economics and policy | vol 6 • issue 2 • 2016 231 table a2: z’’ score of every company on every year of time horizon company z’’ (2010) z’’ (2011) z’’ (2012) z’’ (2013) z’’ (2014) a2a calore e & servizi 4.14 4.4 4.18 4.35 3.08 adria energy e.s.co s.r.l. 7.87 10.38 11.58 7.99 10.14 aice s.c. a r.l. 11.4 5.54 3.48 3.36 3.34 amga calore & impianti s.r.l. 2.12 2.97 3.8 4.05 4.23 area engineering s.r.l. 5.07 4.13 4.67 3.4 6.33 aura energy s.r.l. 3.45 3.69 2.42 6.64 5.57 avvenia s.r.l. 14.57 14.8 13.07 14.65 16.8 axopower s.r.l. 4.49 4.01 3.79 4.03 4.17 azzero co2 s.r.l. 4.58 3.74 2.94 4.46 5.43 bartucci spa 13.23 12.36 11.51 13.75 11.3 bit energia s.r.l. 10.7 13.64 12.12 10.19 11.06 c.e.i. s.p.a. calore energia impianti 6.56 4.88 5.53 5.58 6.33 carbotermo s.p.a. 4.83 5.39 5.54 5.55 5.76 casadei & pellizzaro s.r.l. 8.65 9.33 12.52 10.69 9.31 centoraggi societa’ cooperativa 4.17 15.41 11.33 18.86 11.42 centro calor s.r.l. 3.79 2.64 2.08 1.89 1.15 co. meta societa’ cooperativa consortile 3.56 2.64 2.8 3.6 4.11 cofely italia s.p.a. 5.29 6.7 6.27 4.83 5.28 consul system s.p.a. 8.3 6.1 7.23 9.28 7.51 cremonesi consulenze s.r.l. 3.17 3.08 5.43 4.68 5.63 cristoforetti servizi energia s.p.a. 4.34 4.28 3.68 4.2 4 dedalo esco s.p.a. 3.69 0.76 1.6 0.6 0.61 diddi dino e figli s.r.l. 4.69 4.57 8.36 7.8 8.14 e.on energia s.p.a. 2.41 2.99 4.82 5.04 5.14 energest s.r.l. 18.33 13.25 16.85 16.65 14.36 energon esco s.p.a. 3.38 4.99 5.7 6.03 6.89 energynet s.r.l. 5.75 6.77 7.91 4.18 4.62 e.s.co. berica s.r.l. 1.55 3.29 3.98 3.48 3.41 e.s.co. comuni s.r.l. 6.38 4.34 3.4 4.73 3.66 esco italia s.r.l. 7.17 3.04 3.27 4.35 6.1 e.s.co. primiero s.r.l. 24.35 14.05 8.26 4 4.3 ets life s.r.l. 7.99 8.87 8.96 9.49 9.49 eureka e.s.co. s.r.l. −1.83 5.39 4.19 14.32 6.37 fedabo s.p.a. 3.86 5.98 5.64 7.51 8.32 fostini s.r.l. 4.35 4.65 4.89 4.93 5.43 g.m.t. s.p.a. 4.13 5.02 4.73 4.87 7.3 geetit s.r.l. 5.2 2.41 3.44 3.56 2.83 global power service s.p.a. 4.13 5.17 5.82 6.13 6.72 hera comm s.r.l. 3.78 4.2 4.13 4.3 4.5 innowatio s.p.a. 8.12 13.21 13.25 16.04 12.37 interesco srl 4.05 4.83 4.09 2.87 1.23 jpe 2010 5.18 4.43 6.22 23.66 6.35 menowatt ge s.p.a. 4.65 4.22 6.03 3.78 3.56 meridionale impianti s.p.a. 6.77 8.38 8.02 10.09 10.16 nesco north energy service company s.r.l. 4.12 3.6 12.5 14.12 585.06 newen s.r.l. 2.24 2.82 4.88 3.34 4.1 nrg. it s.r.l. 17.72 20.56 3.66 5.77 8.13 om.e.g. srl 0.64 1.62 6.88 17.52 65.95 oros p&r srl e oros progetti srl 3.15 6.07 5.89 5.72 6.71 pagano e ascolillo energy and technology s.p.a. 3.54 3.72 4.87 5.47 5.83 polo tecnologico per l’energia s.r.l. 5.23 4.44 5.15 4.03 4.02 ranzato impianti s.r.l. 2.49 3.16 3.42 4.97 5.06 restiani s.p.a. 3.36 3.35 3.72 4.38 4.28 sangalli technologies esco s.r.l. 3.05 3.06 3.9 10.46 6.47 saras ricerche e tecnologie s.p.a. 7.64 6.62 6.79 8.95 7.35 sea servizi energia ambiente s.r.l. 5.53 7.22 9.81 5.93 6.68 seaside s.r.l. 10.36 11.9 6.65 6.62 6.69 sime energia s.r.l. 2.42 2.52 2.47 2.59 2.44 siram s.p.a. 5.82 4.72 4.87 6.11 6.3 sof s.p.a. 4.4 4.31 3.68 4.35 4.31 solgen s.r.l. 3.95 3.84 4.69 3.47 3.79 studio botta & associati srl 12.46 5.24 6.49 5.26 6.47 studio mps engineering s.r.l. −4.86 2.65 3.72 5.12 4.52 tea servizi s.r.l. 12.03 22.01 9.27 6.9 4.45 (contd...) iazzolino and gabriele: energy efficiency and sustainable development: an analysis of financial reliability in energy service companies industry international journal of energy economics and policy | vol 6 • issue 2 • 2016232 company z’’ (2010) z’’ (2011) z’’ (2012) z’’ (2013) z’’ (2014) tep energy solution 6.49 7.09 8.37 9.52 9.14 tera energy s.r.l. 9.65 9.83 13.31 10.28 11.1 ulteria s.r.l. 4.25 3.98 4.2 3.92 5.49 universal sun s.r.l. 3.73 6.37 5.14 3.55 3.07 escos: energy service companies table a2: (contd....) esco 2010 2011 2012 2013 2014 z’’ rating z’’ rating z’’ rating z’’ rating z’’ rating a2a calore e & servizi 4.14 ccc+ 4.4 b4.18 b4.35 b3.08 cccadria energy e.s.co s.r.l. 7.87 aa 10.38 aaa 11.58 aaa 7.99 aa 10.14 aaa aice s.c. a r.l. 11.4 aaa 5.54 bb 3.48 ccc 3.36 ccc 3.34 ccc amga calore & impianti s.r.l. 2.12 d 2.97 ccc3.8 ccc+ 4.05 ccc+ 4.23 barea engineering s.r.l. 5.07 bb4.13 ccc+ 4.67 b3.4 ccc 6.33 bbb aura energy s.r.l. 3.45 ccc 3.69 ccc 2.42 d 6.64 bbb+ 5.57 bb avvenia s.r.l. 14.57 aaa 14.8 aaa 13.07 aaa 14.65 aaa 16.8 aaa axopower s.r.l. 4.49 b4.01 ccc+ 3.79 ccc+ 4.03 ccc+ 4.17 bazzero co2 s.r.l. 4.58 b+ 3.74 ccc 2.94 ccc4.46 b5.43 bb bartucci spa 13.23 aaa 12.36 aaa 11.51 aaa 13.75 aaa 11.3 aaa bit energia s.r.l. 10.7 aaa 13.64 aaa 12.12 aaa 10.19 aaa 11.06 aaa c.e.i. s.p.a. calore energia impianti 6.56 bbb+ 4.88 b+ 5.53 bb 5.58 bb 6.33 bbb carbotermo s.p.a. 4.83 b+ 5.39 bb 5.54 bb 5.55 bb 5.76 bb+ casadei & pellizzaro s.r.l. 8.65 aaa 9.33 aaa 12.52 aaa 10.19 aaa 9.31 aaa centoraggi societa’ cooperativa 4.17 b15.41 aaa 11.33 aaa 18.86 aaa 11.42 aaa centro calor s.r.l. 3.79 ccc+ 2.64 ccc2.08 d 1.89 d 1.15 d co. meta societa’ cooperativa consortile 3.56 ccc 2.64 ccc2.8 ccc3.6 ccc 4.11 ccc+ cofely italia s.p.a. 5.29 bb 6.7 a6.27 bbb 4.83 b+ 5.28 bb consul system s.p.a. 8.3 aaa 6.1 bbb7.23 a+ 9.28 aaa 7.51 aacremonesi consulenze s.r.l. 3.17 ccc3.08 ccc5.43 bb 4.68 b 5.63 bb cristoforetti servizi energia s.p.a. 4.34 b4.28 b3.68 ccc 4.2 b4 ccc+ dedalo esco s.p.a. 3.69 ccc 0.76 d 1.6 d 0.6 d 0.61 d diddi dino e figli s.r.l. 4.69 b 4.57 b 8.36 aaa 7.8 aa 8.14 aa e.on energia s.p.a. 2.41 d 2.99 ccc4.82 b+ 5.04 bb5.14 bbenergest s.r.l. 18.33 aaa 13.25 aaa 16.85 aaa 16.65 aaa 14.36 aaa energon esco s.p.a. 3.38 ccc 4.99 bb5.7 bb+ 6.03 bbb6.89 a energynet s.r.l. 5.75 bb+ 6.77 a7.91 aa 4.18 b4.62 b e.s.co. berica s.r.l. 1.55 d 3.29 ccc 3.98 ccc+ 3.48 ccc 3.41 ccc e.s.co. comuni s.r.l. 6.38 bbb 4.34 b3.4 ccc 4.73 b 3.66 ccc esco italia s.r.l. 7.17 a+ 3.04 ccc3.27 ccc 4.35 b6.1 bbbe.s.co. primiero s.r.l. 24.35 aaa 14.05 aaa 8.26 aaa 4 ccc+ 4.3 bets life s.r.l. 7.99 aa 8.87 aaa 8.96 aaa 9.49 aaa 9.49 aaa eureka e.s.co. s.r.l. −1.83 d 5.39 bb 4.19 b14.32 aaa 6.37 bbb fedabo s.p.a. 3.86 ccc+ 5.98 bbb5.64 bb 7.51 aa8.32 aaa fostini s.r.l. 4.35 b4.65 b 4.89 b+ 4.93 b+ 5.43 bb g.m.t. s.p.a. 4.13 ccc+ 5.02 bb4.73 b 4.87 b+ 7.3 a+ geetit s.r.l. 5.2 bb2.41 d 3.44 ccc 3.56 ccc 2.83 cccglobal power service s.p.a. 4.13 ccc+ 5.17 bb5.82 bb+ 6.13 bbb6.72 ahera comm s.r.l. 3.78 ccc+ 4.2 b4.13 ccc+ 4.3 b4.5 b innowatio s.p.a. 8.12 aa 13.21 aaa 13.25 aaa 16.04 aaa 12.37 aaa interesco srl 4.05 ccc+ 4.83 b+ 4.09 ccc+ 2.87 ccc1.23 d jpe 2010 5.18 bb4.43 b6.22 bbb23.66 aaa 6.35 bbb menowatt ge s.p.a. 4.65 b 4.22 b6.03 bbb3.78 ccc+ 3.56 ccc meridionale impianti s.p.a. 6.77 a8.38 aaa 8.02 aa 10.09 aaa 10.16 aaa nesco north energy service company s.r.l. 4.12 ccc+ 3.6 ccc 12.5 aaa 14.12 aaa 585.06 aaa newen s.r.l. 2.24 d 2.82 ccc4.88 b+ 3.34 ccc 4.1 ccc+ nrg. it s.r.l. 17.72 aaa 20.56 aaa 3.66 ccc 5.77 bb+ 8.13 aa om.e.g. srl 0.64 d 1.62 d 6.88 a 17.52 aaa 65.95 aaa oros p&r srl e oros progetti srl 3.15 ccc6.07 bbb5.89 bbb5.72 bb+ 6.71 apagano e ascolillo energy and technology s.p.a. 3.54 ccc 3.72 ccc 4.87 bb+ 5.47 bb 5.83 bb+ polo tecnologico per l’energia s.r.l. 5.23 bb4.44 b5.15 bb4.03 ccc+ 4.02 ccc+ ranzato impianti s.r.l. 2.49 d 3.16 ccc3.42 ccc 4.97 bb5.06 bbrestiani s.p.a. 3.36 ccc 3.35 ccc 3.72 ccc 4.38 b4.28 btable a3: sample rating on every observation year (contd...) iazzolino and gabriele: energy efficiency and sustainable development: an analysis of financial reliability in energy service companies industry international journal of energy economics and policy | vol 6 • issue 2 • 2016 233 esco 2010 2011 2012 2013 2014 z’’ rating z’’ rating z’’ rating z’’ rating z’’ rating sangalli technologies esco s.r.l. 3.05 ccc3.06 ccc3.9 ccc+ 10.46 aaa 6.47 bbb+ saras ricerche e tecnologie s.p.a. 7.64 aa 6.62 bbb+ 6.79 a8.95 aaa 7.35 aasea servizi energia ambiente s.r.l. 5.53 bb 7.22 a+ 9.81 aaa 5.93 bbb6.68 aseaside s.r.l. 10.36 aaa 11.9 aaa 6.65 a6.62 bbb+ 6.69 asime energia s.r.l. 2.42 d 2.52 ccc2.47 d 2.59 ccc2.44 d siram s.p.a. 5.82 bb+ 4.72 b 4.87 b+ 6.11 bbb6.3 bbb sof s.p.a. 4.4 b4.31 b3.68 ccc 4.35 b4.31 bsolgen s.r.l. 3.95 ccc+ 3.84 ccc+ 4.69 b 3.47 ccc 3.79 ccc+ studio botta & associati srl 12.46 aaa 5.24 bb6.49 bbb+ 5.26 bb 6.47 bbb+ studio mps engineering s.r.l. −4.86 d 2.65 ccc3.72 ccc 5.12 bb4.52 b tea servizi s.r.l. 12.03 aaa 22.01 aaa 9.27 aaa 6.9 a 4.45 btep energy solution 6.49 bbb+ 7.09 a+ 8.37 aaa 9.52 aaa 9.14 aaa tera energy s.r.l. 9.65 aaa 9.83 aaa 13.31 aaa 10.28 aaa 11.1 aaa ulteria s.r.l. 4.25 b3.98 ccc+ 4.2 b3.92 ccc+ 5.49 bb universal sun s.r.l. 3.73 ccc 6.37 bbb 5.14 bb3.55 ccc 3.07 cccescos: energy service companies table a3: (contd....) . international journal of energy economics and policy | vol 7 • issue 3 • 2017 364 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(3), 364-369. annulment of oil licences in nigeria’s upstream petroleum sector: a legal critique of the costs and benefits olusola joshua olujobi1, olabode adeleke oyewunmi2* 1department of business management, covenant university, nigeria, 2department of business management, covenant university, nigeria. *email: olabode.oyewunmi@covenantuniversity.edu.ng abstract owing to various reasons, tenable and untenable, successive governments in nigeria have annulled licenses duly granted to identifiable upstream petroleum operators. with due sense of circumspect, when irregularities manifest in the process and the grant of substantive licences, such does not vest in the government an unfettered right to annul the licence. there are evidences of such occurrence in spite of established procedures regulating annulments, commonly referred to as revocation or cancellation. this paper is a critique of the annulment of oil licenses and the associated contractualregulatory dimensions. the validity of the federal government’s actions also comes to the fore, particularly in the light of renewed drive to attract investments into the upstream sector. thus, as some benefits are accruable to the players, it is also important to appraise the consequential costs attributable to undue annulment of oil licenses. the paper adopts a descriptive analytical method of available facts, expounds requisite statutory provisions and utilizes judicial precedents to highlight the context of the study. it is imperative that the federal government adheres to established procedures on oil license annulment, as a contrary posture will amount to several negative outcomes. keywords: oil, upstream, nigeria, licence, annulment, contracts, regulations jel classifications: k32, k12, k2, k42, p28 1. introduction the recent decline of global oil prices (2015-2017) has not diminished the significance of oil and gas revenues to nigeria’s socio-economic and political well-being. earnings from oil, gas and associated products remain the mainstay of nigeria’s economy but there are current efforts to diversify the national revenue base. this progression can only be effectively achieved by leveraging the sanctity of established processes and practices that are integral for the sustainability of nigeria’s oil and gas industry. the seemingly customary practice of revoking, cancelling or annulling various species of oil agreements is no longer tenable and is evidently inconsistent with industry best practices. it apparent that such a posture clearly contradicts the desire and efforts to secure long-term financing of upstream projects. the reasons for adopting annulment is usually hinged on intrinsic right, albeit unilaterally, to review and revaluate subsisting agreements, notwithstanding the pending contractual obligations (akinrele, 2016). the considerable losses, financial and otherwise associated with breaches in procedure needs to be urgently addressed, if all the stakeholders (internal and external) are to derive optimal benefits. moreover, the multifaceted collateral damage associated with oil and gas activities is well documented (oyewunmi and oyewunmi, 2016) but the nigerian state can ill-afford to perpetuate a negative perception on issues of due commercial compliance. evidently, such unfavourable outlook, coupled with other impediments, has hampered sustained investments into the upstream petroleum sector. a concerted and holistic policy driven approach will contribute in measurable respects to mitigating negative outcomes in this regard. the upstream license award process is complex, competitive, capital intensive, potentially profitable and involves multiple interests (atsegbua, 2004). in nigeria, the right to participate in the upstream sector is usually granted on the basis of licences or leases. this will typically refer to the; oil exploration license (oel), oil prospecting licence (opl) and oil mining lease (oml); all of which vary in terms of tenure, geological coverage and permissible activity (nlerum, 2007-2010). hence, owing to the olujobi and oyewunmi: annulment of oil licences in nigeria’s upstream petroleum sector: a legal critique of the costs and benefits international journal of energy economics and policy | vol 7 • issue 3 • 2017365 multiple layers of risk associated upstream sector, the principal actors need to fulfill their reciprocal obligations, failing which will culminate in added costs and consequential losses for both parties. annulment of oil licences is comparable to the proverbial double ‘edged sword’ with divergent outcomes, subject to the decisions made by the contracting parties relative to a given set of circumstances. on the one hand, the enabled statutory governmental agency must ensure that annulments are effected based on the express provisions of applicable laws. thus, it will not suffice to annul oil licences merely on policy inclinations or other extraneous matters not under consideration during the award process. whilst on the other hand, the licensee may bear the burden (annulment) of not adequately fulfilling the terms and conditions underpinning the grant of a licence. this is in spite of the fact that considerable levels of investment have been committed towards commercializing the grant coverage area. the principle of privity to all intents and purpose provides a veritable benchmark for effective regulation of contractual interactions. the primary statute, requisite award rules and guidelines; and the express, implied and customary licence terms, are integral to determining the validity of annulment. in the light of varying contractual complexities, this paper entails a legal critique of costs and benefits connected with the irregular or arbitrary annulment of oil licences in nigeria. the paper addresses a sensitive and somewhat controversial subject matter, especially in the light of the myriad of interests competing for a share of the common wealth of the nigerian state. in the process of securing specific allocations, there are bound to be some breaches or omissions by the certain players or stakeholders. the following paragraphs, constitute conceptual clarifications, legal framework for investment guarantees, statutory overview, judicial critique and conclusion. 2. conceptual clarifications: award of licences and annulments an oel encapsulates the express consent granted by a competent authority to execute specific undertakings within a delineated geographical area. hence, failure or omission to secure the requisite consent renders subsequent actions by an affected party illegal or wrongful. in a more concise sense, it entails an authority to do something, subject to the stipulated terms and conditions. a licence as opposed to ownership vests limited or qualified legal interest, coupled with the fact that it is also revocable subject to a contract duly signed, sealed and delivered by the respective parties. licensing in the upstream petroleum sector refers to authorization given by the federal government to upstream petroleum companies to carry out certain activities as expressed and implied by the licence. according to section 2(1) (c) petroleum act 2004, licenses in the oil sector are commonly referred to as concessions or leases and are usually granted in wide and extensive terms, that is, "to explore, acquire, produce and to dispose of petroleum." hence, it is erroneous to construe, that the federal government as the original titleholder, has transferred the unqualified degree of title to a licensed operator. moreover, the applicable laws of nigeria do not recognize the private ownership of oil and other mineral resources, which further attests to the limitation on oil exploration rights or interests and by implication affirming the dominant role of government in the scheme of oil development affairs. the minister of petroleum usually awards oel in accordance to section 2(1) of the petroleum act, laws of the federation of nigeria. it empowers the licensee to venture into petroleum activities in the area encompassed by the licence. in addition, the licensee is statutorily enabled to commence exploration activities not later than 3 months after issuance of the licence. by virtue of the provisions of the act, oel expires on december 31st of the year following the date of issue, but it may be recommenced for another year. as regards the opl, the minister for petroleum may grant such pursuant to section 2(1) (b) of the act. it offers the holder of the licence the power to delve into activities oil within the area covered by the license. the petroleum minister in accordance with section 2(1) (c) petroleum act awards an oil-mining lease (oml). an oml is exclusive to the holder of an opl who has met all the provisions stipulated on his license; has found oil in market able magnitudes and achieved minimum oil production benchmark of, 10,000 barrels of oil per day relative to the licensed area for prospecting. under paragraphs 8, 9, 10, 11, 12 and 13 of the 1st schedule, petroleum act, the holder of oil mining lease enjoys all the rights of an opl holder. this is inclusive of; exclusive rights to explore, acquire, operate, and remove and to sell the crude oil found and explore in the area subject to the terms of the lease or the concession. the act, also the vests in the minster of petroleum; powers over the allotment of licenses for prospecting, mining exploration of oil without deploying the requisite oversight controls for regulating the process of such allotments. it is noteworthy that under nigeria’s constitution and established administrative law principles clearly indicate that; where the law stipulates a specific process for exerting a right, the processes must be stringently complied with in the exercise of such power. thus, adopting an alternative approach is illegal especially if the law relates to repudiation of the proprietary right of citizens. successive administrations, have allocated oil licenses covering exploitation of oil resources, without instituting effective procedures that regulate such a complex and multifaceted process. such a posture has evidently provided ample opportunity for entrenching unethical and corrupt practices on the part of some operators, as well as notable regulatory authorities. during the military rule, most licenses were awarded without due process by the heads of state. in 1999, the former president chief olusegun obasanjo annulled eleven oil blocks awarded to theformer military officers by the previous governments. 67 licenses were granted betweenjanuary 1, 2005-december 31, 2011 with $506 million outstanding unpaid signature bonuses to the federal government account. 7 discretionary allocations reviewed, $183 million was alleged outstanding and due to the national treasury (ribadu, 2016). the likelihood of abuse is predominant during award of oil licenses, and more so as the process is often based on direct negotiations with prospective operators. auctions procedures are imperative in the selection of the most competent operators for production. olujobi and oyewunmi: annulment of oil licences in nigeria’s upstream petroleum sector: a legal critique of the costs and benefits international journal of energy economics and policy | vol 7 • issue 3 • 2017 366 pre-qualification process ensures that companies that participate in tender process are competent to execute the contract. fraud may also arise where criteria for pre-qualification is structured to single out certain operators. instructively, the adoption of ‘right of first refusal’ option accorded to specific participants in the bidding process may breed corruption and other rent-seeking activities that are detrimental to the myriad of stakeholders. government officials and regulatory authorities can exploit such gaps to extract bribes from the bidding companies. also captured is infringement of due process by disclosing sensitive facts to one of the bidders in advance in exchange for favour and other rent seeking behaviour. furthermore, abuse occurs; when the licensee violates the terms of the licence, under quoting volumes and government officials are culpable of not delivering monitoring and oversight functions, as they ought to. consequently, renegotiations and amendments are inevitable in a contractual regime bedevilled with compliance practices or incidents. it also negatively affects the expected revenues attributable to anticipated production activities over a given period. 3. investment guarantees in nigeria: overview of legal framework successive nigerian governments have often expressed the desire to attract foreign investment to the upstream sector. the efforts in this regard have without a doubt yielded a notable number of laws, even though the level of harmonization is subject to ongoing debate. a non-exhaustive list of such laws includes; investment and securities act, 2004; nigerian investment promotion commission decree; national office for technology acquisition and promotion act, 2004; companies and allied matters act, 2004; the nigerian content development act, 2010, foreign exchange monitoring miscellaneous provisions act c 2004, industrial inspectorate act cap.18, laws of federation of nigeria, 2004, and 1995, the privatisation decree, 1999. it is a fact that such legal frameworks irrespective of the good intentions underpinning such, have not sufficed to mitigate the investments risks in nigeria. what is more fundamental towards sustaining the required investments is the recurring issue of consistent levels of implementation. in addition, the issue of policy review needs to be frontally addressed, subject to unfolding realities. hence, such a posture will contribute towards; creation of viable investments opportunities and climate; ensure fairness and equity; promote rule of law and probity, and ultimately entrench a culture of due process in the award of licences for upstream players. the petroleum act failed to explain the specific attributes of an oil license, especially in terms of whether it vests exclusive rights on the holder. it gives extensive right to the lessee to search for oil, to utilize oil-mining lease, and to refine the oil. the “without restrictedness” connotes that on no account will any other stakeholder be awarded a privilege to search for crude on the field covered by the earliest license granted until after it expiry. in effect, such a license may be annulled if it is transferred for value without the consent of the minister of petroleum and energy resources. alternatively, oil-prospecting license offers the licensee specific privileges. it gives the right, the privilege to search, dig for oil within the scope of the licence. lessee may transfer the license with the consent of the minister of petroleum and energy resources with the right to dispose of oil won during the prospecting activities in the sector. these privileges are exclusive it offers rights that are profitable and commercially significant to the licensee. the minister cannot suomotu terminate the contractual oil licence without following due process. any indiscriminate annulment amounts to a breach of contract and by implication contravenes section 44 of the 1999 constitution of nigeria that guarantees inviolability of right to property anywhere in nigeria. furthermore, any alteration of the sum of royalty payable by the licensee; or any other terms not in the licence that was introduced subsequently after the agreement has been executed and prescribed statutory fees have been paid; or any other reasonable commercial considerations that were not anticipated by the parties, is an expropriation of the licensee’s exclusive possessory right. an annulment of the oil license, while there is a subsisting oil licence contract makes the federal government liable for breach of contract and infringement of the licence’s right to property. 4. annulment ofoil licences: a statutory overview the unilateral revocation of oil licenses on the part of the federal government, before the expiration period and without any merit, is to all intents and purposes a breach of contract. it further entails, a confiscation of value, depriving the licensed operators their rights and benefits accruable to them in the course of their undertaking. the government’s action in this regard has increased licensees’ investment risk exposure in the sector. this is coupled with the fact that such infringes the statutory guaranteed and exclusive rights allocated to licensees under the requisite laws and regulations governing such matters. the federal government will usually be inclined to annul subsisting oil licences as part of ongoing efforts to combat corruption in the oil and gas sector. it centres on expediency for the adoption of such an option, especially where beneficiary companies have failed or neglected to pay statutory application fees. moreover, as formal agreements governing the entire undertaken are sill being finalized, a window of opportunity may exist to annul contractual obligations. by virtue of the provision of paragraph 23(1) of the first schedule to the petroleum act, the minister of petroleum may annul any oil licence if the licensee is being manage by a citizen or a company registered in any country other than nigeria and where the laws do not permit nigerians to run petroleum concessions on certain conditions which in the opinion of the minister of petroleum and energy resources is similar with the terms upon which such concessions are given to citizens of such foreign investor in nigeria. also, in paragraph 24 of the same first schedule to the petroleum act further provides that the minister of petroleum and energy resources can annul opl or oil mining lease to oml, if in his estimation, the concerned licensee or lessee is not carrying on its operations regularly and in a business-like tactics worthy of oil field practice, or refused to adhered to the provisions of the act or any other procedures or failed to honoured his duties as stated in the license or lease or failure to pay outstanding royalties, if olujobi and oyewunmi: annulment of oil licences in nigeria’s upstream petroleum sector: a legal critique of the costs and benefits international journal of energy economics and policy | vol 7 • issue 3 • 2017367 demanded for or not by the minister within the time stated or in accordance with act or has refused to make available such details on his activities as the head of petroleum inspectorate demand. the licensee or lessee shall become liable for all liabilities suffered before the actual date of such cancellation. according to etikerentse (2004) on the effectiveness of the power of revocation of petroleum licence, he said that: “the significance attached to the cancellation powers of the grantor in this issue has been taken away to a great extent by the very fact that in nearly all petroleum operations in nigeria now, the government through nigerian national petroleum corporation has participation interests. nigerian national petroleum corporation’s officials have a say in the manner the processes are carried out and they would therefore be aware of any non-payments that warrant of annulment. annulment would thus affect both parties to the joint venture and the nigerian national petroleum corporation’s inspectorate, being the actual organ saddled with effecting any annulment, would be most unwilling to carry out that order that would indirectly affect its alter ego.” evidences abound of instances when the federal government had cancelled licences awarded by the previous governments. notably, in 2011, eni and shell petroleum companies were alleged to have paid $1.1 billion for oil block opl 245. the payment was allegedly made to the federal government, who then passed it on to malabu company owned a former nigerian oil minister who during his tenure in office, had awarded the oil block to his own company. the halliburton case is also worthy of mention as the company officials conceded that its nigerian subsidiaries sometime in 2006; offered bribes of $2.4 million dollars to tax officials for favourable tax rebate worth more than $14 million. the company’s licence was consequently annulled as the matter is currently pending at the federal high court. the unilateral annulment has also brought to the fore legal and policy inconsistencies touching on the validity of annulment process, as well as the associated contractual consequences. it thus suffices to say that the implementation of the extant legal framework is weak, as there is need for concerted effort to achieve the desired outcomes in upstream sector. 5. judicial critique: oillicence annulment in nigeria in the decided case of; mr. obikoya and sons nigeria limited v. the lagos state governor, the court stated that any law that governs mandatory acquisition of the citizen property right; such must be interpreted firmly against the acquiring party to the benefits of the title holders of the acreage or the party in possession of the property in question. the petroleum act, the principal legislation regulating oil search and production, stipulates the procedure by which the minister for petroleum can revoke oil license where foreigner is controlling the license. paragraph 23(1) (a) of schedule 1 to the petroleum act amongst others provides for revocation; where in the minister’s opinion, the lessee or other stakeholders fail to honour the act or fail to fulfills his expected duties in paragraph 24 (1) and lastly to pay royalties even if not demanded by the minister. however, the minister can only exercise such power after satisfying the prerequisiteas stated under paragraphs 25-29 of the schedule. paragraph 25 inter alia states that the minister must notify the licensee the grounds for the revocation. licensees are to be to giving the reasons and where the minister is contented with the reasons, he may summon the licensee to make amendment in respect of licence or other issues within the shortest time as enshrined in paragraph 26 of the act. where the leaseholders fail to give cogent reasons, or amend the complaint within the time framed, the minister may then annul the license as stated under paragraph 27 of the petroleum act. the revocation exercise by the federal government contravened the “due process” and doctrine of “natural justice.” section 36(5) and section 44(1) 1999 of the constitution (as amended); provides for fair hearing on matters of individuals’ civil rights and civil obligations. it also nullifies compulsory acquisition of private property except in accordance with the law. failure of the federal government to conform to the statutory procedure for revocation of oil licences renders such revocation null and void. it is trite law that, before licensees’ proprietary rights can be varied or revoked such licensees must be accorded the full privileges of fair hearing. in lagos state development and property corporation v. foreign finance corporation, it was opined that a holder of administrative authority must give the person who is going to suffer injury by the use of such administrative authority reasonable trial. it is a mandatory prescribed procedure and non-compliance renders the action or process a nullity. the supreme court declared that in the exercise of revocation power, the potential party must be given an opportunity to be heard, as the exercise may touch on their exclusive right. for instance, when government official is exercising the powers conferred under section 28 of the land use act 1978 to annul the certificate of occupancy issued through the power of cancelation he or she is expected to act with reasonable fair hearing and to respect fundamental human rights of the parties to such contract. also, in ude v. nwara, the court held that where the law gives powers with the effect of extinguishing exclusive rights it is expected of those exercising such powers to strictly adhere to the provisions of the law. anybody who performs public duty are expected to comply with the rule of law; to exercise their discretion judiciously and in conformity with the enabling statute. upstream petroleum companies who held the licenses that had been annulled by the federal government alleged denial of fair hearing. the committee of inquiry established by the federal government to consider the procedure for the award of the grant and it was on the findings of the committee of inquiry that the federal government cancelled the licenses of concerned companies without prior notices. furthermore, even when the concerned upstream companies failed to pay up the outstanding prescribed statutory fees; that do not give the right to annul the licenses contrary to the provision of the olujobi and oyewunmi: annulment of oil licences in nigeria’s upstream petroleum sector: a legal critique of the costs and benefits international journal of energy economics and policy | vol 7 • issue 3 • 2017 368 enabling law. an infringement of any covenant in oil licence agreement only establishes basis for annulment but may not definitely result to annulment. as decided in nwara (supra), an infringement of terms in an oil licence agreement is a mere ground for forfeiture. it is thus evident that the annulment by the federal government was not consistent with the petroleum act and the 1999 constitution of nigeria (as amended). therefore, the annulment was illegal, null and void. in a more recent case, federal government revoked, the opl 323 that had been allotted to the korea national oil corporation in august 2005. nigerian government alleged that the korean national oil company is yet to pay the balance of $231 million signature bonus on the two oil blocks allocated to it. the revocation was executed while the court had granted an order of interim injunction against the attorney general of the federation and the president, federal republic of nigeria restraining them from the revocation of opl pending the determination of the substantive matter before the court. the federal government instituted an action at the federal high court, abuja with an application for a stay of execution stating the reasons it has not obeyed subsisting court orders that rendered void the annulment of opls 321, 323 respectively. the court decided that the annulment of the two oel of the foreign conglomerate company by the federal government was illegal, particularly on the grounds that federal government did not have the legal powers to revoke oel. hence, it suffices to say that the minister of petroleum and energy resources is the appropriate authority in this regard. the legal interpretation of schedule 4 of the petroleum act is fundamental to the holistic appreciation of the legal essence as well as the associated consequences oil licence annulments. it provides, that any licence or lease granted under an enactment repealed by the petroleum act shall continue in force notwithstanding the repeal, but shall be subject to the petroleum act and to any regulations made thereunder except on matter of; duration of the licence or lease, rent and royalties payable in respect thereof. it is implicit here that the, obligations of the parties have been frozen in specific respects subject to the statutory exposition in this regard. however, the following judicial authorities, though with contrasting outcomes provides further insight on the contractualregulatory dimensions of survival and sanctity of oil license agreements. firstly, under consideration is the case texaco petroleum company limited and california asiatic oil company v. the government of libya, where the principle of sanctity of contract was considered in holding that the concession amounted to a binding obligation under international law. thus, the libya government was bound to honour its contractual undertakings. however, in the cases of libyan american oil company v. the government of libya and british petroleum company v. the government of libya, the arbitrators relied on the existence of the new international economic order of may 1, 1974, a resolution favourably disposed to the sovereign rights of states to control and exercise ownership over their natural resources. hence, the implication of the resolution, being to mitigate the expansive effects of the doctrine of sanctity of contracts, relative to natural resource concessionary arrangements. 6. conclusion investments in nigeria’s upstream petroleum sector ought to be from a strategic perspective, subject to the enabling legislations. this necessitates informed manoeuvring to ensure positive and sustainable outcomes or returns. license fees and licensing regimes in the nigerian upstream petroleum sector ought to be reviewed and renewed in conformity with the current contextual realities. perhaps, contracting parties should be more innovative in deploying ”freezing clauses” in licence agreements. this will help to manage losses attributable unilateral annulments, which is not uncommon to developing climes that rely heavily on oil revenues. also important are issues of the enactment of a whistle blowers protection act, as such will promote increased transparency, and serve as a barometer to foster broader compliance levels. in addition, long over-due petroleum industry bill will complement the associated laws, rules, guidelines, codes, policies and initiatives in promoting operational efficiency and enhanced governance structures. these amongst other efforts at re-engineering nigeria’s oil and gas industry will foster accountability and healthy competition (oyewunmi and olujobi, 2016). it is also important to state that the effective harmonization of existing laws will help to mitigate regulatory overlaps and ensure improved consistency of issues on annulment and other related matters. it is recommended that erring upstream petroleum companies should be blacklisted, and rules or guidelines must be designed to mitigate corrupt practices at the pre-qualification stage. the guidelines for pre-qualification and for tendering for oil licences ought to be advertised in not less than three national dailies. in addition, independent and non-partisan observers must be present in all the stages of the tendering from pre-qualification of companies, the bidding stage and the grant of contracts. upstream petroleum companies bidding for petroleum licences or that maintain oil licences should duly disclose their actual titleholders. this probity and openness requirements may discharge public suspicious of government’s officials of benefiting illegally from the award of oil licences and oil blocks. on a final note, the federal government should set the tone by timeously publishing specifics of all licence annulments. this posture of reciprocal accountability will serve as a veritable benchmark to test the viability or otherwise of this option whilst also recognizing the importance of the wider societal corporate interest. references akinrele, a. (2016), the current impact of global crude oil prices on nigeria-an overview of the nigerian petroleum and energy sector. journal of world energy law and business, 9(5), 314-345. atsegbua, l. (2004), oil and gas in nigeria: theory and practice. benin: filers lane. p213. british petroleum company v. the government of libya. (1974), 53 international law reports, no. 297. companies and allied matters act cap 20. (2004), laws of the federation of nigeria. constitution of the federal republic of nigeria. (1999), cap. 23 laws of the federation of nigeria. etikerentse, g. (2004), nigerian petroleum law. london: macmillan. p60-115. olujobi and oyewunmi: annulment of oil licences in nigeria’s upstream petroleum sector: a legal critique of the costs and benefits international journal of energy economics and policy | vol 7 • issue 3 • 2017369 foreign exchange (monitoring miscellaneous provisions) act cap f34 lfn. (2004). industrial inspectorate act cap.18, lfn. (2004). investment and securities act cap.124 lfn. (2004). libyan american oil company v. the government of libya. (1981), international legal. materials, no. 1. vol. 20. p1-87. lagos state development and property corporation v. foreign finance corporation. (1987), 1 nigerian weekly law report (pt. 50), 413. national office for technology acquisition and promotion act cap n62 laws of the federation of nigeria. (2004). nlerum, f.e. (2007-2010), reflections on participation regimes in nigeria’s oil sector. nigerian current law review, 5, 146-162. ude, v.n. (1993), 2 nigerian weekly law report (pt 278) 638 at 664. obikoya and sons limited v. governor of lagos state. (1987), 1 nigerian weekly law report (pt.50), 385. oyewunmi, o.a., olujobi, o.j. (2016), transparency in nigeria’s oil and gas industry: is policy re-engineering the way out?international journal of energy economics and policy,5(4), 630-636. oyewunmi, o.a., oyewunmi, a.e. (2016), managing gas flaring and allied issues in the oil and gas industry: reflections onnigeria. mediterranean journal of social sciences, 7(4), 643. petroleum act, cap. p10 lfn (2004). ribadu, n. (2016), oil subsidy report. available from: http:// www.247ureports.com/full-text-of-nuhu-ribadus-oil-subsidy-report/ http//247ureports.com/full-text-of-nuhu-ribadus-oil-subsidy-report. texaco petroleum company limited and california asiatic oil company v. the government of libya. (1979), 53 international law reports no. 398. the nigerian content development act. (2010). the nigerian investment promotion commission decree. (1995). ole_link1 . international journal of energy economics and policy | vol 7 • issue 2 • 2017360 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(2), 360-366. development of economical and geographical image of eastern siberia as a subject and an object of strategic investments in oil and gas complex albert leonidovich feldman1*, lada avenirovna podolyanets2 1school of petroleum and gas engineering, siberian federal university, 82, svobodny pr., krasnoyarsk 660041, russia, 2saint petersburg mining university, 21st line of vasilyevsky island, 2, saint-petersburg 199106, russia. *email: albertfl@yandex.ru abstract in modern conditions of long-term reduction of the country’s income, and, respectively, searches of financing of regions optimum structuring of regional space, use of historically developed spaces-regions as one of the sources of social and economic development by the way of increase in volumes and soundness of investments is very important. the article represents the east siberian region as historically developed economical and geographical space and transformation of its image in modern geo-economic conditions. meridional location of the region united by common baikal-angara-yenisei water system should be taken into account at planning of development of separate economic sectors in its territory for the purpose of achievement of both all-federal purposes and purposes of regional development. the youngest and most dynamic sector in the territory of the region is oil and gas that provides an opportunity for creation of general federal and regional strategy for its further development. it is necessary to use the existing regional system of oil product supply while implementation of federal programs and plans of vertically integrated oil company in oil and gas industry in the territory of the region and to build operating structures not only for the west-east line, but also for the north-south. keywords: regional economy, regional space, east siberian oil and gas complex, oil product supply jel classifications: o18, r12 1. introduction s t r u c t u r i n g o f t h e g e o g r a p h i c a l s p a c e , i n c l u d i n g i t s component economic space is the most important stage of transition from raw export economy to the balanced self-sufficient economy of new industrialization and regional development (jean and savona, 1997). location and content of production structures is deeply influenced by a mental image, map of the territory, its position and coordinates (neklessa, 1997). that is the structure of oil product supply in the east siberian region was formed under the influence of its spatial integrity, which is established and historically proved (tsagareli, 1995). it is the meridional extent and structuring around the baikalangara-yenisei water system (miroshnikova, n. d.). in the absence of own oil processing facilities, the oil products were delivered to the territory of the region by rail using the transsiberian railway. a basis of the oil product supply system in the beginning of 20th century was a construction of warehouses for oil and oil products in the main zone. in august, 1900 “nobel brothers oil production partnership” organized the first such warehouse in the city of achinsk near the railway station. similar warehouse was organized in krasnoyarsk also near the railway station. main warehouse and headquarters of the partnership in eastern siberia were located in irkutsk (feldman et al., 2016a). under the conditions of world war i the government of russia reconsidered the economic activity management structure in the country. by the end of 1914 the first governmental body for regulation of procurement and delivery of fuel-osotop (special fuel committee) was created. it got such name in august, 1915 after numerous reorganizations (mastobayev et al., 2006). the special committee created a policy for development of the system of oil product supply for the territories and obtained the right of distribution of orders, establishment of marginal prices and carrying out of requisitions. at first the soviet system kept the existing state control mode, but under the conditions of the feldman and podolyanets: development of economical and geographical image of eastern siberia as a subject and an object of strategic investments in oil and gas complex international journal of energy economics and policy | vol 7 • issue 2 • 2017 361 beginning of the civil war and worsening economic breakdown the council of people’s commissars (cpc) in 1918 issued decree about nationalization of the oil industry (history of ussr, 1967). for the purpose of management of the industry cpc founded the main oil committee (glavkoneft) as a part of the supreme soviet of the national economy with which district oil committees were founded. in the days of the new economic policy an establishment engaged in sale of oil and oil products was neftetorg founded in january, 1922 and further transformed into neftesindikat. after transition of national economy to the planned one neftesindikat in 1928 was dissolved and all petroleum depots were transferred to the all-union association soyuzneft which became a basis for glavneftesbyt (torochkov et al., 1978). in the territory of eastern siberia the west siberian department of soyuzneftesbyt and the east siberian department with headquarters in irkutsk were the establishments which dealt with oil product supply (feldman, 2015). old petroleum depots were recreated and new petroleum depots were built along the trans-siberian long distance railway. in 1928 the kanskaya and uzhurskaya oil depots were formed, in 1929 zaozyornovskaya and uyarskaya oil depots were created. in december, 1929 zlobinskaya (krasnoyarskaya) oil depot was founded (feldman et al., 2016). the new stage of development of oil product supply of eastern siberia started in december, 1934 when krasnoyarsk region was formed. there was an expansion of oil-product network of the region. particular attention was paid to riverside distribution tank farms for the purpose of maximum use of yenisei river system and its inflows. in march, 1936 in the village of kuragino an oil depot was created. oil products were supplied using the river tuba. in june, 1936 the minusinsk oil depot was founded. at first oil products were delivered by river transport, later also by rail transport. in october, 1939 in the far northern part of krasnoyarsk district igarskaya oil depot was founded (“krasnoyarsknefteprodukt” pjsc, 2004). thus, the zlobinskaya (krasnoyarskaya) transshipment water-railway oil depot was supplemented with a network of water-distribution and deep oil depots according to the meridional arrangement along the north-south axis, with an opportunity to reach the northern sea route (nsr) and intraregional development which was guided by all-federal projects for the east-west line. in parallel with development of oil product supply system, other components of the oil and gas complex (ogc) were also developed. in 1930s the works aimed at search for hydrocarbon raw materials in the southern areas of krasnoyarsk district were started. in the second half of 20th century these works were transferred to the northern areas. it is interesting that the first field of industrial production of natural gas was made exclusively to cover internal needs of the region, namely the taimyr peninsula and the norilsk industrial district (chernysh et al., 2000). along with an intensification of works aimed at search for hydrocarbon raw materials there was a development of petrochemical and oil processing component of the oil and gas company. in 1957 in the city of krasnoyarsk the synthetic rubber production plant was put into operation. even earlier in the neighbouring irkutsk region in 1949 the angarsk petrochemical plant was commissioned (later pa angarsknefteorgsintez). in 1956 it commissioned first primary distillation system. by the early 1990s the association consisted of 12 plants with oil refining efficiency of 72.73% (1989) and actually set fresh feed rate of 23,056 million tons/year (melnikova et al., 1997). in 1972 near the city of achinsk construction of the achinsk refinery started. in october 1983 it became one of currently operating plants of minneftekhimprom of the ussr. design fresh feed rate of the first stage was 6.9 million tons per year. with an opportunity of commissioning of the second stage and increase in design capacity up to 12 million tons of raw materials per year (chernysh, 2006). in 1979 the resolution # 265 “on measures for intensification of oil and gas exploration works in eastern siberia” was adopted by the central committee of the communist party of the soviet union and the council of ministers of the ussr. in compliance with it in august, 1979 spa “yeniseigeofizika” was organized; it included all geophysical expeditions in the territory of krasnoyarsk region. the purpose of the new union was investigation of deep geological structure of the territory of krasnoyarsk region, division of the territory into districts in view of prospects of oil-and-gas content, carrying out regional prospecting works with the purpose of identification and preparation for deep drilling of oil and gas potential structures. by 1985 58 objects with the total prospective area of 9,400 sq. km were prepared. opening in the late 1980s of the vankorskoye field and the yurubcheno-tokhomskoye oil-andgas area was a result of these works. since 1970s and until the end of 1980s the system of oil product supply reached the peak of its development. the state establishment “krasnoyarsknefteprodukt” was carrying on the business in the territory of krasnoyarsk region (including the khakass autonomous region, the evenki and taimyr autonomous areas) and the republics of tuva, it was operating 38 petroleum storage depots and 250 gas stations (feldman et al., 2016b). commissioning of the 1st and 2nd stages of the yenisei (abalakovskaya) transshipment water-railway petroleum storage depot intended for satisfaction of requirements for oil products needs of the norilsk industrial district was very important. feasibility reports for construction of trunk oil pipelines from the achinsk refinery under construction in three directions were made: 1. to the yenisei oil depot; 2. to the minusinsk oil depot and further to kyzyl (republic of tuva); 3. kansk-taishet (irkutsk region) (feldman and podolyanets, 2016). thus by the beginning of 1990s the east siberian ogc was created. 2. methods the ogc is considered as a component developing in time and space of the east siberian region. its historical and social and economic component is supplemented with the geographical and geopolitical (geoeconomic) characteristic (meridional extent and structuring around the baykalo-angaro-eniseyskoy water system). during the work on article methods of theoretical generalization and forecasting, the logical analysis, comparative-historical generalizations are used. the attention to researches in the field of economy, geoeconomy, geopolitics, geography, history, regional economy is paid. as initial information acts, program documents and decisions on development of oil branch of the government of the russian federation, general court and administration of krasnoyarsk krai, data of social and feldman and podolyanets: development of economical and geographical image of eastern siberia as a subject and an object of strategic investments in oil and gas complex international journal of energy economics and policy | vol 7 • issue 2 • 2017362 economic statistics (goskomstat, management of statistics on krasnoyarsk krai), materials of scientific conferences are attracted. 3. results at the moment, contrary to logic of spatial development of the region the prevailing direction of creation of the production structures is west-east or east-west. so, the commercial operation of the vankorskoye field which was started in 2009 was supported by construction of vankor-purpa oil pipeline (figure 1) to the main pipe of transneft with its further pumping to the east: to china and nakhodka. the following options for using the regional infrastructure were rejected. 1. by way of oil pipeline construction in the direction of the port of igarka with further use and development of igarka, dudinka and dickson ports for oil transportation by the nsr further, using the network of northern oil depots, it would be possible to expand transportation of oil products also through the nsr for supply of the arctic regions (khatanga, etc.) and for export (feldman et al., 1997). 2. by way of construction of the oil pipeline to the achinsk refinery. with partial processing of the extracted oil and transfer of oil products at the yenisei oil depot by the nsr. further development of the ogc of krasnoyarsk region is planned as development of the yurubcheno-takhomsky oil and gas accumulating area with construction of the oil pipeline kuyumbataishet with further direction to china and nakhodka port. thus being technologically and logistically developed fields belong to the west siberian ogc and the far east export oil and gas logistic direction being created (export of crude oil, oil processing and petro chemistry). what we have now is creation of production structures of the ogc of the east siberian region being formed just along the west-east and the east-west lines with obvious export orientation for the raw materials (in this case crude oil). accordingly the main activities in the territory of the region are carried out by the companies with transnational business activities, interests and sources of financing. they receive financial resources figure 1: arrangement of the oil pipeline to vankor-purpa and main users of this main oil pipeline feldman and podolyanets: development of economical and geographical image of eastern siberia as a subject and an object of strategic investments in oil and gas complex international journal of energy economics and policy | vol 7 • issue 2 • 2017 363 at the global markets from transnational financial institutions and develop oil and gas infrastructure in line with interests (logic) of the global market. according to this logic involvement of regional infrastructure, construction of advanced refining complexes is an additional cost, decrease in capitalization of the companies, increase in loan debt for the projects which main objective is exportation of raw materials with the minimum costs. as a result the effect for the regional industry and the budget in principle can’t be significant as a matter of fact it is minimal. at the moment there are no finished projects aimed at oil refining in krasnoyarsk region except for the achinsk refinery which was commissioned in 1983. and as early as the soviet period the petrochemical complex was started to be created in the region for future oil and gas projects (vankorskoye and other fields were commissioned in the soviet period), but it was ruined in 1990s. supplies of material resources from the east siberian fields are generally integrated into the latitudinal schemes of supplies from the yamal peninsula where the production projects of the region’s vertically integrated oil companies are located. that is, according to the program of complex development of the fields of yanao and the north of krasnoyarsk region till 2020 the vankorskaya group of fields will have the common with yamal transport network, common power supply system (urengoy regional power station, etc.) and common social infrastructure. as for development of processing industry of krasnoyarsk region, oil and gas projects generally didn’t exert their influence on its development both in respect of increase in output and in respect of upgrade. during the period of development of the vankorskoye field the purchasing amount for material resources by “vankorneft” in 2010-2012 made 120-140 billion rubles a year. at the same time the orders for the entities of the region made 7-14 billion rubles a year, i. e., no more than 6-10% of all purchases of the company (kryukov et al., 2013). generally the development of the fields is made using foreign equipment (bukharova and samusenko, 2016). the reason for that is that domestic equipment can’t provide the necessary level of efficiency. the multi-national federal companies build in the region its own wholesale and retail oil product business (khantemirov, 2016). the final purpose is complete dominance at the regional market with replacement of local players and reformatting of the regional system of oil product supply (part of it is reallotted to them, and the rest is liquidated). this newly created oil product supply system as a part of the federal companies will be servicing as their core business at the west-east line for the purpose of minimization of costs and maximization of profit. within this model the calls to increase participation of the regional entities in oil and gas projects will not help, because it is in conflict with the logic of the developing above described system. the offers to expand the list of project participants, investors by domestic vertically integrated oil companies also will not help. all the offered measures for support of development of eastern siberia, in general, and particularly krasnoyarsk region, are provided in accordance with this model. therefore it is necessary to develop the north-south and south-north model not instead but in parallel. its main provisions are as follows. to use creatively the previous experience of the projects providing economical, geographical and geopolitical integrity of the territories of russia. certainly, it is the project of ogc and its major component oil product supply system of the east siberian region. it will help to provide long term growing region economy with inexpensive fuel, creating rational transport and logistics routes of supply. it is necessary to return to plans of construction of oil pipelines in the east siberian region. the project of achinskminusinsk-kyzyl refinery in case of its implementation can be continued in the direction of mongolia for supply of low-cost oil products, supporting joint russian-mongolian projects in other fields of economy. thus, this country, which is so important for the east siberian region, will be integrated in the north-south line towards russia (mutovin and feldman, 2016). achinsk-yeniseisk (abalakovo) refinery will help to organize regular and inexpensive supply of oil products for northern and arctic districts of the region and will contribute to activation of the nsr. in case of implementation of the achinsk-kansk-taishet (irkutsk region) refinery the western, central and eastern parts of krasnoyarsk region will qualitatively improve their oil products supply. the large urban center krasnoyarsk will receive an optimum transport scheme for their delivery, including removal of the krasnoyarsk (zlobinskaya) petroleum storage depot out of the city (the problem is still exist) (16). it is necessary to create the regional logistic (wholesale and retail) center based on the large enterprise of the oil product supply system which is owned by the region (today it is “krasnoyarsknefteprodukt” public joint stock company) with inclusion of group of transshipment and distribution petroleum storage depots in this center (feldman et al., 2016). important question for implementation of projects are sources of its financing which owing to features of the russian structure of management and property are difficult to access. nevertheless, it is possible to offer the following options based on the soviet and russian projects, successful foreign experience and current russian and world trends. 1. experience of norway and brazil. by 60th years of the 20th century norway had no oil and gas industry at all. by 70th years the plan for its creation was developed. in its basis active participation of the state. requirements to use of local goods and services at implementation of projects on oil extraction were legislatively defined. in general during the period from the middle of the 70th to the middle of the 90th years of the 20th century the share of the norwegian goods and services reached 90% of all deliveries. in 1972 the government structures connected with oil production were reorganized into the norwegian oil management which created the statoil company the national oil company, the conductor of commercial interests of the state. for influence on deliveries of goods and services in 1972 in the ministry of the industry the department controlling activity of the oil companies in the sphere of contracts and deliveries was created (noreng, 2004). now annual volumes of services grow in oil and gas sector of norway by 4 times quicker, than oil and gas extraction. similar approach is applied in brazil the government established the requirement according to which from 40 to 85% of operational costs of the companies of oil and gas business have to is the share of local suppliers of goods and services. 2. from the second half of the 90th years of the 20th century within state programs and in circles of expert community feldman and podolyanets: development of economical and geographical image of eastern siberia as a subject and an object of strategic investments in oil and gas complex international journal of energy economics and policy | vol 7 • issue 2 • 2017364 the latitudinal models of development of the country were developed. it was intended to direct international trade and transport flows through the territory, air and sea space of the russian federation. originally from the west to the east. the task was to integrate into the international system of latitudinal transport corridors with the following projects: • nsr • the trans-siberian and baikal-amur railway lines with branches to japan (with construction of the bridge through the island of sakhalin), china and korea. however, these plans initially came up against the opposition of the eu, which began to promote its projects, the main one being the traceca corridor, the main intention of which was the revival of the great silk road from europe to china. with the help of this corridor it was planned to send european cargoes from the ports of bulgaria, romania and ukraine by ferries through the black sea to the caucasus, then by rail and road to baku, then by ferry across the caspian to turkmenistan and by rail to china. although the time in transit, taking into account the time of transshipment in the black and caspian seas, was 2 times more than through the trans-siberian railway, the project continued to be implemented. he changed direction from east to west and is now known as the great silk road. the reason is that china became the main source of the commodity mass for transportation instead of europe. since the main stream only affects russia to a small extent, the development of russian regions will not be carried out, moreover, the financial, infrastructure, human, technological resources will be “attracted” to the route, distracting them from the russian regions. therefore, the compensatory mechanism “north-south” is needed. 1. an extremely expensive annual event for russia is the northern delivery, most of which is fuel. at the same time, the price for transportation of fuel is 1.5 2.5 times higher than its cost, according to former head of the presidential administration s. ivanov. on average, the northern delivery assumes an annual delivery of 7 million tons of liquid petroleum products and 23 million tons of coal. financing of the northern delivery, transferred from the federal budget to the regional level, despite the fact that the debts of the regions in the rf reached 2.4 trillion. rub., becomes extremely difficult. the development of the transport and fuel system in the east siberian region will significantly reduce the cost of the northern delivery, reduce the prime cost of most types of products produced in the siberian-far eastern regions and regions of the far north. in the future, we can assume the consolidation of the population in these territories. 2. out of direct financial resources, it is possible to propose the use of the mechanism of public-private partnership at the regional level in combination with the production sharing agreement, with the receipt of funds allocated by the federal budget for import substitution purposes in these regions. the funds allocated in accordance with the strategy of social and economic development of russia to 2020 and up to 2030 can also be used. 4. discussion the image of the east siberian region, proposed in our article, is subject to the impact of alternative projects. one group of authors includes kuznetsov et al., who in the article “spatial opportunities and limitations of the modernization of the russian economy: an example of the north-western macroregion” outlines the results of the study of the role of space in modernizing the economy of this region. they pose the problem in such a way that a special interdisciplinary scientific methodology is needed the geospatial paradigm. in our opinion, today there was a need for this methodology, when an important component is socio-economic development. in this paradigm, geographic and economic factors have an impact on geospace. the concept of space is connected with the concept of region. but they consider the socio-economic space through the prism of classical economic theory. we propose to optimize the old image of economic geography and fit it into the existing market conditions. another group of authors includes works in which the concept of the region is explored. so, tatarkin in the article: “social and economic status of the middle region of russia”, introduced the notion of the middle region on the basis of a geographical criterion and on its basis, conducts economic and mathematical modeling. v. yu. burov in the report at the 2nd international scientific conference “siberian bridgehead 17-18.02.2016 year” operated the concept “baikal subregion” in the composition of buryatia, irkutsk region and transbaikal region. in his opinion, this region should strive for integration with the far eastern district and with china. k.s chumlyakov in the article “infrastructural security of the raw macro-region of the russian federation” (journal of problems of economics and management of the ogc, no. 6, 2015) analyzes the inland situation of the west siberian macro region of the russian federation. it includes the republic of khakassia and the western districts of the krasnoyarsk territory. this territory, which is characterized by a high concentration of fuel, energy, mineral resources and other resources, should be actively involved in the organization of commodity exchange through the formation of a transcontinental logistics infrastructure for the export of raw materials. these authors justify the blurring of the east-siberian region along the west-east line for transit and raw infrastructure projects. and we consider the region through the historical-geographicgeopolitical aspect and on this basis we determine the region. we offer a basic, historically developed image. the concept image is a category that is considered to be largely geopolitical, “the security of modern russia is a matter of timely modeling of targeted geographic images.” (“foreign policy and security of contemporary russia”: a chrestomathy in 2 volumes). geoeconomics extends the use of geographic images, as it operates with financial and economic flows and virtual spaces. the construction of geographical images becomes an urgent task of the present day. in our opinion, it is necessary to actualize the space in the economic sense, to make it one of the sources of economic development. this study also raises issues of prospective generation of financial revenues. in the opinion of the authors, at the first stage of implementation the costs for the northern delivery will be reduced, and the constant risks of fuel crises in these regions are reduced. the task of the second stage will be the justification of feldman and podolyanets: development of economical and geographical image of eastern siberia as a subject and an object of strategic investments in oil and gas complex international journal of energy economics and policy | vol 7 • issue 2 • 2017 365 the organizational, economic and territorial-regional development of the production of oil products of various types for the domestic and foreign markets. the results of the second stage research will be presented in the next article. figure 2: direction of transport arteries along the line north-south feldman and podolyanets: development of economical and geographical image of eastern siberia as a subject and an object of strategic investments in oil and gas complex international journal of energy economics and policy | vol 7 • issue 2 • 2017366 5. conclusion today the production, economic, transport and logistic interactions created over the past decades and being created along the westeast and east-west line not only support exportation of the raw materials from the country, but also create around them importdependent technological infrastructure (krasnoyarsk region in figures, 2015). all this promotes dissolution, shrinking and disappearance of the image of eastern siberia as a complete region having economical, geographical and geopolitical tradition and a sense of existence. we see a creation of a new economical and spatial image for the benefit of the foreign states and powerful multinational corporations which are based on their territory. it is necessary not just to declare “import substitution” tasks, but to advance, design the corresponding images of the territory of eastern siberia which will create objective needs and will become a basis for development and production for the processing industry. in general, the key transport corridor of russia along the westeast line passing through the territory of eastern siberia has to be added with a key regional transport corridor along the northsouth line (figure 2). it will intensify the dynamics of regional development and will help to start implementation of the only correct internal shift of the country in modern conditions to the east and not to far east for the purpose of supporting china, but to the east siberian region, equidistant both from europe and the european part of russia and from big china and the asia-pacific region in general. the transport routes passing from the west to the east and from the east to the west will provide additional dynamics to internal development of the baikal-angara-yenisei region along the northsouth line with connection to the international markets by the nsr. references bukharova, e.b., samusenko, s.a. (2016), economy of krasnoyarsk region: system of regional economic security in a down economy. krasnoyarsk: siberian federal university. p226. chernysh, m.e. (2006), development of oil-processing industry in the soviet union: historical fragments. moscow: nauka. chernysh, v.f., krinin, v.a., nazimkov, g.d., nakoryakov, v.d. (2000), search and exploration of oil and gas fields in krasnoyarsk region and the republic khakassia. krasnoyarsk: business intelligence. 182. chumlyakov, k.s. (2015), infrastructural security of the raw macro-region of the russian federation. journal of problems of economics and management of the oil and gas complex, 6, 41-46. feldman, a.l. (2015), creation of effective oil product supply management structures in krasnoyarsk region. current issues of science and education, 1. [data views 06.02.2017]. available from: https://www.science-education.ru/ru/article/view?id=17623. feldman, a.l., gorodishcheva, a.n., feldman, l.a., lyalina, p.a. (2016), designing and organization of logistic centers as a part of oil product supply system of the east siberian region. naukovedeniye, 8(4), 1-9. feldman, a.l., gorodishcheva, a.n., lyalina, e.p. (2016a), formation of oil product supply system of eastern siberia at the end of 19th and at the beginning of 20th century (using the example of krasnoyarsk region). issues of social and economic development of siberia, 2, 37-45. feldman, a.l., gorodishcheva, a.n., lyalina, p.a. (2016b), development trends of the system of oil products supply of the krasnoyarsk region throughout the second half of the 20th century. fundamental researches, 3, 643-647. feldman, a.l., ivanov, v.m., gromovykh, s.a., feldman, a.l. (1997), use of a network of northern oil depots of “krasnoyarsknefteprodukt” pjsc for creation of a stable system of oil products supply for the regions of the far north and the arctic region. transport and storage of oil products, 7, 18-22. feldman, a.l., podolyanets, l.a. (2016), plans for creation of oil pipelines in the east siberian region. modern science: current issues of theory and practice, 10, 37-42. feldman, a.l., podolyanets, l.a., feldman, l.a. (2016), problems of city oil depots using the example of functioning of the krasnoyarsk (zlobinskaya) oil depot. naukovedeniye, 8(4), 55. history of ussr. (1967), from ancient time till now: 2 series. great october socialist revolution and civil war in the ussr 1917-1920. vol. 7, 12. moscow: nauka. p751. jean, c., savona, p. (1997), geoeconomics. moscow: ad marginem. khantemirov, r. (2016), overview of the russian market of oil products. na analytics of commodity markets, 4, 1-4. krasnoyarsk region in figures. (2015), statistic review: krasnoyarskstat. krasnoyarsk: the territorial body of the federal state statistics service for the krasnoyarsk territory. p207. k r a s n o y a r s k n e f t e p r o d u k t p j s c . ( 2 0 0 4 ) , 7 0 ye a r s o f krasnoyarsknefteprodukt, 1934-2004. krasnoyarsk: platina. p17. kryukov, v.a., nefedkin, v.i., semykina, i.o. (2013), in what direction the vector of development of the siberia macroregion is changing. makroregion siberia: issues and prospects of development. krasnoyarsk: siberian federal university. p181-235. kuznetsov, s.v., mezhevich, n.m., lachinsky, s.s. (2015), spatial opportunities and limitations of the modernization of the russian economy: an example of the north-western macroregion. economy of the region, 3, 25-38. mastobayev, b.n., mutallapov, n.g., prokhorov, a.d., dmitriyeva, t.v., korobkov, g.e. (2006), development of oil product supply system of russia. st. petersburg: nedra. p25-28. melnikova, s.a., kandelaki, t.l., tankayev, r.u., avramenko, n.v. (1997), oil processing and petrochemistry in the russian federation. moscow: infotek-consult. p500. miroshnikova, t.i. (n. d.), for 190-anniversary of foundation of the yenisei province. archives of krasnoyarsk region. [data views 06.02.2017]. available from: http://www.xn7sbbimrdkb3alvdfgd8eufwc.xnp1ai. mutovin, s.i., feldman, a.l. (2016), history of oil product supply in the republic of tyva. modern science: current issues of theory and practice, 10, 37-42. neklessa, a.i. (1997), post-modern world in the new system of coordinates. vol. 2. moscow: vostoc. p35-51. noreng, o. (2004), norway: economic diversification and the petroleum industry 10th annual energy conference of the emirates centre for strategic studies and research. abu dhabi, uae, september. p26-27. tatarkin, a.i. (2005), social and economic status of the middle region of russia. spatial economy, 4, 21-39. torochkov, i.m., beyder, p.y., balayan, r.d., matskin, l.a. (1978), organization of oil product supply. moscow: nedra. tsagareli, d.v. (1995), technical development of oil product supply system. moscow: information center mathematics. p8-13. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 6 • 2021328 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(6), 328-334. factors affecting tax incentives of energy companies listed on the indonesia stock exchange tjia siauw jan*, zainal muttaqin, lastuti abubakar faculty of law, universitas padjajaran, bandung, indonesia. *email: tsiauwjan.unpad@gmail.com received: 01 feburary 2021 accepted: 10 august 2021 doi: https://doi.org/10.32479/ijeep.11134 abstract this study aims to determine and explain the effect of company size, profitability, leverage, capital intensity, and inventory intensity on tax revenue for the tax amnesty program at energy companies listed on the indonesia stock exchange. this research is a research that uses an associative approach. the sample in this study were 13 energy companies listed on the idx in the 2013-2017 period which were determined by the saturation sampling method. this study uses descriptive statistics, multiple linear regression test for panel data models, hypothesis testing (t-test and f-test) and coefficient of determination as research analysis techniques. the results obtained show that partially the capital intensity, leverage and company size affect tax revenue from the tax amnesty program, while inventory intensity and profitability do not affect tax revenue from the tax amnesty program. furthermore, company size, inventory intensity, capital intensity, profitability and leverage simultaneously affect tax revenue from the tax amnesty program. this means that tax revenue for the tax amnesty program at energy companies is influenced by company size, inventory intensity, capital intensity, profitability and leverage. keywords: company size, inventory intensity, capital intensity, profitability, leverage, tax amnesty jel classifications: h23, h27 1. introduction indonesia’s national economic growth in recent years has tended to experience a slowdown. the economic slowdown has an impact on decreasing state revenues from the taxation sector, which also results in a lack of liquidity provision in indonesia, even though this liquidity is very important to increase national economic growth (sayidah and assagaf, 2019). hence, tax amnesty implemented in indonesia includes the elimination of payable taxes, administrative sanctions and tax penalties by determining the existence of a ransom in a predetermined amount, which is calculated based on net assets either in the form of a declaration or repatriation (ibrahim et al., 2018). in energy sector contexts, tax incentives are also useful for improving energy efficiency performance (villca-pozo and gonzales-bustos, 2019; kraal, 2019; hymel, 2006). theoretically, alex radian stated that if tax revenue has not been able to achieve sufficient revenue it will result in disruptions in the provision of public services and also allow the government not to have many opportunities to spend financing and investment and provide unexpected funds (radian, 1980; gunadi, 2007). tax revenue in indonesia has increased every year, which can be seen from figure 1. however, table 1 shows that tax revenue from 2013 to 2017 did not reach the predetermined revenue target (tax shortfall). table 1 shows that the tax revenue target has never been achieved in the last few years prior to the implementation of the tax amnesty program in 2017. according to stella (1991), the most important goal of a tax amnesty is to increase income in a short period of time (darussalam, 2014). the key to the tax amnesty program lies in the scope of the tax amnesty, attractive rates, guaranteed confidentiality, simplicity in its implementation, this journal is licensed under a creative commons attribution 4.0 international license jan, et al.: factors affecting tax incentives of energy companies listed on the indonesia stock exchange international journal of energy economics and policy | vol 11 • issue 6 • 2021 329 and massive outreach to the public, including energy companies to participate in this program (dippenaar, 2018; ogunlana and goryunova, 2017). lisa and hermanto (2018) explain that the tax amnesty program is about the factors that affect the willingness to pay taxes, which shows that tax amnesty has a good understanding of tax awareness, understanding of tax regulations, and the effectiveness of the taxation system. in addition, husnurrosyidah and nuraini (2016) studied the impact of tax amnesty and tax sanctions on tax compliance, and the results all had a positive impact on tax compliance. meanwhile, etisya’s (2017) research shows that tax amnesty has a significant positive effect on tax awareness and a good understanding of the effectiveness of the taxation system, but does not have a significant effect on knowledge and understanding of tax regulations. several studies have highlighted the relationship between tax amnesty and performance in energy companies (ibrahim et al., 2018; heffron, 2018; salgado et al., 2019; cansino et al., 2010; abidin et al., 2020). based on the description, the purpose of this study is to obtain empirical evidence regarding the effect of company size, inventory intensity, capital intensity, profitability and leverage partially and simultaneously on the tax amnesty program at energy companies listed in indonesia stock exchange. 2. theoretical background and hypotheses 2.1. the effect of company size on tax amnesty of energy companies listed in indonesia stock exchange in energy companies company size is measured based on the total assets owned by each company and is used as a measure of company scale. companies that are included in a large corporate scale will have abundant resources that can be used for certain purposes. based on agency theory, the resources owned by the company can be used by managers to maximize the manager’s performance compensation, namely by reducing corporate tax costs to maximize company performance. derashid and zhang (2003), mulyani et al. (2018) concluded that company size has an effect on tax amnesty of energy companies listed in indonesia stock exchange in manufacturing sector. this explains that companies that are included in large-scale companies pay lower taxes than small-scale companies, this is because largescale companies have more resources that can be used for tax planning by adopting effective accounting practices and political lobbying to reduce corporate tax. langedijk et al. (2014) argues that small-scale companies cannot be optimal in tax planning due to a lack of experts in taxation (schratzenstaller et al., 2017). when the company’s tax planning activities are not optimal, it will cause the company to lose the opportunity to receive tax incentives which can reduce the tax imposed on the company. h1: firm size has an effect on tax amnesty of energy companies listed in indonesia stock exchange table 1: 2012‑2017 tax revenue year target realization % shortfall 2013 1072 985 92 87 2014 1294 1055 82 239 2015 1539 1283 83 256 2016 1283 1147 89 136 2017 1424 1316 92 108.1 figure 1: tax revenue 2012-2017 source: hirschmann (2020) jan, et al.: factors affecting tax incentives of energy companies listed on the indonesia stock exchange international journal of energy economics and policy | vol 11 • issue 6 • 2021330 2.2. effect of profitability on tax amnesty of energy companies listed in indonesia stock exchange the agency theory will spur managers to increase company profits. when the profits earned get bigger, the income tax amount will automatically increase according to the increase in company profits. companies with a high level of profitability can pay higher taxes than companies with low profitability. the reason is that corporate income tax will be imposed based on the amount of income received by law no. 36 of 2008 article 1 explains that income tax is imposed on tax subjects who receive or earn income in the tax year. lanis et al. (2017) state that companies that have high profitability will pay higher taxes than companies that have a lower level of profitability. lanis et al. (2017) also stated, profitability is described by roa. the higher roa level of the company causes higher taxes, because the basis for the imposition of income tax is the income earned and received by the company. by using financial data of companies listed in china, sun et al. (2020) link value added tax incentives to increased profitability of the new energy industry. akhtar et al. (2012) also found a relationship between the burden and financial performance of the energy sector in pakistan. h2: profitability has an effect on tax amnesty of energy companies listed in indonesia stock exchange 2.3. the effect of the level of debt on the tax amnesty according to phuong et al. (2020), energy companies use debt with the aim that the profits earned by the company that are greater than the cost of assets and sources of funds. the level of debt is the size of a company’s liabilities arising from past transactions and must be paid in cash, goods and services in the future. in this case, debt is inversely proportional to profit so that if debt is greater, profit will be smaller with the addition of interest expense. accounts payable can be used by managers to reduce corporate tax costs by utilizing debt interest costs. darmadi and zulaikha (2013) explain that loan interest, both paid and unpaid at maturity, is an expense that can be deducted from income. research conducted by derashid and zhang (2003) found that debt affects tax amnesty. this explains that the use of debt to finance the company’s operational activities will result in fixed costs, namely interest. interest costs can be deducted from taxes, so that the use of debt as a company operational expense will directly affect the amount of company tax, including in energyrelated industry (jeffrey and perkins, 2015). h3: the level of debt affects the tax amnesty of energy companies listed in indonesia stock exchange 2.4. effect of fixed asset intensity on tax amnesty of energy companies listed in indonesia stock exchange the intensity of the company’s fixed assets illustrates the amount of company investment in the company’s fixed assets. in agency theory, depreciation can be used by managers to reduce the company’s tax burden. managers will invest the company’s idle funds to invest in fixed assets, with the aim of getting a profit in the form of depreciation which can be used as a tax deduction. by taking advantage of depreciation, managers can improve company performance to achieve the desired manager performance compensation. derashid and zhang (2003) found that the variable asset intensity has a negative effect on tax amnesty. this suggests that companies that have a large proportion of fixed assets will pay lower taxes, because companies benefit from depreciation attached to fixed assets which can reduce the company’s tax burden. h4: the level of fixed asset intensity affects the tax amnesty of energy companies listed in indonesia stock exchange 2.5. effect of inventory intensity on tax amnesty of energy companies listed in indonesia stock exchange inventory intensity describes how the firm invests its wealth in inventory. the amount of inventory intensity can cause additional costs, including storage costs and costs arising from damage to goods (zhang et al., 2015). the costs incurred on having large inventories should be excluded from the cost of the inventory and recognized as an expense in the period in which the costs are incurred. additional costs for a large inventory will cause a decrease in company profits. in agency theory, managers will try to minimize the additional burden due to the large inventory so as not to reduce company profits. on the other hand, managers will maximize the additional costs they have to bear to reduce the tax burden. the way that the manager will use is to charge additional inventory costs to reduce the company’s profit so that it can reduce the company’s tax burden (darmadi and zulaikha, 2013). if the company’s profit decreases, it will cause a decrease in taxes paid by the company so that taxes will decrease. h5: the level of inventory intensity affects the tax amnesty of energy companies listed in indonesia stock exchange 2.6. theoretical framework the agency theory will spur managers to increase company profits. when the profits earned get bigger, the income tax amount will automatically increase according to the increase in company profits. the manager as an agent in the agency theory will try to minimize the amount of tax so as not to reduce the manager’s performance compensation as a result of eroding corporate profits by the tax burden. derashid and zhang (2003), andriansyah et al., (2021) explain that companies included in large-scale companies pay lower taxes than small-scale companies, this is because large-scale companies have more resources that can be used for tax planning. by adopting effective accounting practices and political lobbying to lower corporate taxes. according to law no. 36 of 2008 article 1 explains that the income received by the tax subject (company) will be subject to income tax, so that the greater the income received by the company, the greater the income tax imposed on the company or vice versa. derashid and zhang (2003) explain that the use of debt to finance the company’s operational activities will result in fixed jan, et al.: factors affecting tax incentives of energy companies listed on the indonesia stock exchange international journal of energy economics and policy | vol 11 • issue 6 • 2021 331 costs, namely interest. interest costs are tax deductible, so that the use of debt as a company operating expense will directly affect corporate taxes. derashid and zhang (2003) state that companies that have a large proportion of fixed assets will pay lower taxes, because companies benefit from depreciation attached to fixed assets which can reduce the company’s tax burden. the costs incurred on having large inventories should be excluded from the cost of the inventory and recognized as an expense in the period in which the costs are incurred. the additional cost of having a large inventory will cause a decrease in company profits so that taxes will decrease. based on the explanation stated above, the conceptual framework of the independent and dependent variables in seeing the influence between the variables either simultaneously or partially can be done in figure 2. 3. research methods the population in this study are all energy companies listed on the indonesia stock exchange from 2013 to 2017. sampling was carried out by purposive sampling method with the criteria of publishing annual audited financial data as of december 31 during 2013-2017 on the indonesia stock exchange (bei) and the energy company was not delisted during the observation period. so that the samples obtained in this study were 13 samples. the data analysis model used in this study is a multiple linear regression analysis model for panel data using eviews 7 software. panel data is a combination of cross section data and time series data. cross section data observes the value of one or more variables taken from several sample units or subjects in the same time period. time series data observe the value of one or more variables over a period of time. so that the panel data equation which is a combination of cross section and time series equations can be written as follows: yit= α+β1x it + β2x it + β3x it + β4x it + β5x it + εit note: yit= tax amnesty (tax rate) for energy company i year t; α= constant; x1it = energy company size i-year t; x2it = profitability of energy company i-year t; x3it= energy company debt level i-year t; x4it = energy company fixed asset intensity i-year t; x5it= energy company inventory intensity i-year t; β1.β5= regression coefficient; ε= standard error 4. results and discussion the chow test is used to choose between which fixed effect model or common effect model should be used (table 2). based on the results of the model specification test using the chow test, it can be seen that the chi-square probability value is 0.0001. this value is below 0.05, this means that h0 is rejected and ha is accepted. so that the chosen model is the fixed effect model (fem). after the fixed effect model (fem) model is selected, it is necessary to do another test, namely the hausman test to determine whether it is better to use a fixed effect model (fem) or a random effect model (rem). furthermore, the hausman test is used to select the best model, whether the fixed effect model (fem) or the random effect model (rem). the hypothesis in the hausman test is that if the random effect model is rejected, the conclusion should be to use the fixed effect model. because the random effect model (rem) is likely correlated with one or more independent variables. conversely, if ha is rejected, then the model that should be used is random (table 3). based on the results of the model specification test using the hausman test, it can be seen that the random cross-section probability value is 0.0032. this value is less than 0.05, this means that h0 is rejected and ha is accepted. so that the chosen model is the fixed effect model (fem) (table 4). the normality test used in this study is by analyzing and comparing the probability value with an error rate of 0.05 from the normality test data processed using the eviews7 application program. the results of the residual normality test show a p = 0.183633> 0.05, this means that the residuals are normally distributed, so that it meets the criteria for normality assumptions. table 2: cross‑section fixed effects test (chow test) effects test statistic d.f. prob. cross-section f 3.2132 (12.37) 0.0018 cross-section chi-square 39.1954 12 0.0001 company size (x1) profitability (x2) debt rate (x3) fixed asset intensity (x4) inventory intensity (x5) tax amnesty figure 2: conceptual framework source: hirschmann (2020) table 3: correlated random effects ‑ hausman test test summary chi‑square statistic chi‑square. d.f prob. cross-section random 18.125212 5 0.00029 table 4: normality test results series: standardized residuals sample 2014‑2018 observation 65 mean −1.18e-16 median −0.053608 maximum 0.411571 minimum −0.427178 std. dev. 0.204970 skewness −0.263022 kurtosis 2.014697 jarque-bera 3.378761 probability 0.183633 jan, et al.: factors affecting tax incentives of energy companies listed on the indonesia stock exchange international journal of energy economics and policy | vol 11 • issue 6 • 2021332 furthermore, the multicollinearity test is used to detect any relationship between variables in this study by looking at the correlation coefficient between each variable, if it is greater than 0.8 then there is multicollinearity in the regression model, but if the correlation coefficient between each variable is smaller from 0.8, there is no multicollinearity in the regression model (table 5). the test results show that there is no independent variable relationship with a value of more than 0.8. so it can be concluded that the variable data in this study does not have multicollinearity. furthermore, the heteroscedasticity test used in this study was the glejser test (table 6). based on the picture above, prob. each independent variable is greater than 0.05. where is prob. firm size (x1) is 0.8823> 0.05, prob. profitability of 0.5861> 0.05, prob. debt level of 0.1333> 0.05, prob. fixed asset intensity is 0.1738> 0.05, and inventory intensity is 0.3837> 0.05. hence prob. each independent variable> 0.05 then it does not have a heteroscedasticity problem. the autocorrelation test was tested with the durbin-watson (dw) test. based on tests carried out with the help of eviews software, the durbin watson value is 2.2138. based on the number of independent variables used in this study (k = 5) and the number of observations (n = 65), the value of dl = 1.4378 and du = 1.7673 is obtained. it can be concluded that the model does not occur autocorrelation, with the criteria du <d <4-du or 1.7673 <2.2138 <2.237. so that the regression model is feasible to use to see the energy company tax listed on the indonesia stock exchange based on the input of the independent variable company size, profitability, debt level, fixed asset intensity, and inventory intensity. furthermore, the data can be analyzed using multiple regression analysis of the panel data model. following are the results of data processing using eviews 7 (table 7). the results of research obtained regarding the effect of company size on tax amnesty of energy companies listed in indonesia stock exchange are in line with kraal (2019) that there is an effect of company size on tax amnesty of energy companies. the partial hypothesis test results show that the t-statistic value for the firm size variable is 6.636 and the t-table with prob = 5% is known to be 2.001. thus, the t-statistic is greater than t table (6.636> 2.001) and the probability value is 0.000<0.05 which means that the hypothesis is accepted. the positive value of the statistics indicates an increase in company size followed by an increase in tax amnesty. company size can be defined as a scale in which the company can be classified as large and small according to various ways, one of which is the size of its assets. the greater the total assets shows that the company has good prospects in a relatively long period of time. in relation to the effect of company profitability on tax amnesty of energy companies, the results of the study show that profitability has no effect on tax amnesty of energy companies listed in indonesia stock exchange. this can be seen from the statistical smaller than t-table (0.252649 <2.001) and the probability value 0.7701 (0.7701> 0.05), which means that the hypothesis is rejected. this shows that in terms of profitability, it does not affect tax amnesty for energy companies listed on the indonesia stock exchange. this study is not in line with lanis et al. 2017) and derashid and zhang (2003) who state that profitability affects tax amnesty. but in line with research conducted by ardyansah and zulaikha (2014) which states that profitability has no effect on tax amnesty of energy companies listed in indonesia stock exchange because this can be influenced by income that should not be included as a tax object but is included as a tax object, for example dividend income with an ownership level of 25% or more and other operating income. the results of the research obtained regarding the effect of the level of debt on tax amnesty of energy companies listed in indonesia stock exchange show the partial hypothesis test results that the-statistic value is 2.797590 and t table with prob = 5% is known to be −2.001. thus -statistic is smaller than -table (−2.797590 <−2.001) and the probability value is 0.0098 (<0.05), meaning that the hypothesis is accepted. the negative value of the statistics indicates an increase in the level of debt followed by a decrease in tax amnesty. this is in line with derashid and zhang (2003) and darmadi and zulaikha (2013). in terms of the effect of fixed asset intensity on tax amnesty of energy companies listed in indonesia stock exchange, the results of the study show that the intensity of fixed assets has an effect on tax amnesty of energy table 5: multicollinearity test x1 x2 x3 x4 x5 x1 1.000000 0.223482 0.268655 0.027294 0.09966 x2 0.222484 1.000000 0.213821 0.297698 0.081896 x3 0.288622 0.213821 1.000000 0.026814 0.025915 x4 0.026294 0.297698 0.028721 1.000000 0.054125 x5 0.079669 0.081896 0.025015 0.054125 1.000000 table 6: heteroscedasticity test variable coefficient std. error t-statistic prob c 0.064660 0.081885 0.789644 0.4337 x1 −0.006598 0.044447 −0.148442 0.8823 x2 −0.006041 0.011049 −0.546755 0.5861 x3 0.060380 0.039515 1.528031 0.1333 x4 0.182364 0.132056 1.380964 0.1738 x5 0.046402 0.052765 0.879410 0.3837 table 7: model estimation results variable coefficient std. error t-statistic prob. c −0.375308 0.145215 −3.272469 0.0020 x1 0.563533 0.072711 6.636426 0.0000 x2 0.003193 0.021064 0.252649 0.7701 x3 −0.137627 0.055096 −2.797590 0.0098 x4 −0.533375 0.235754 −2.307507 0.0253 x5 −0.173380 0.104817 −1.539173 0.1270 effect specification cross-section fixed r-square 0.700911 mean dependent var −1.504718 adjusted r-square 0.592729 s.d. dependent var 0.277239 s.e. of regression 0.176928 akaike info criterion −0.396541 sum squared resid 1.471265 schwarz criterion 0.205597 log likelihood 3.088760 hannan-quinn criter. −0.158959 f-statistic 6.359033 durbin-watson stat. 2.213848 prob (f-statistic) 0.000000 jan, et al.: factors affecting tax incentives of energy companies listed on the indonesia stock exchange international journal of energy economics and policy | vol 11 • issue 6 • 2021 333 companies listed in indonesia stock exchange which shows the same results as research conducted by derashid and zhang (2003), and darmadi and zulaikha (2013). where t.stat <t-table (2.307507 <−2.001) and a probability value of 0.0253 (<0.05) means that the hypothesis is accepted. the negative value of the statistics shows an increase in fixed assets followed by a decrease in tax amnesty. the results also show that inventory intensity has no effect on tax amnesty of energy companies listed in indonesia stock exchange with the t-statistic being greater than t-table (−1.539173 <−2.001) and the probability value of 0.1270 (greater than 0.05). it means that the hypothesis is rejected. this shows that in spatial terms inventory intensity has no effect on tax amnesty of energy companies listed in indonesia stock exchange. finally, testing the effect of company size, profitability, debt level, fixed asset intensity and inventory intensity simultaneously on tax amnesty of energy companies listed in indonesia stock exchange. the test is carried out using the fixed effect test with the results revealing an f-statistic of 6.359033 with a probability level of 0.0000, while the f-table amounting to 2.37. based on these results, it can be seen that f-stat. is greater than f-table (6.359033>2.37). thus, the hypothesis is accepted. hence, it can be concluded that the variable company size, profitability, level of debt, intensity of fixed assets and intensity of inventory simultaneously have a significant effect on tax amnesty of energy companies listed in indonesia stock exchange. this means that each total asset that describes the size of a company, the level of profitability in generating profits, the level of debt in financing, asset turnover and inventory turnover is closely related to tax amnesty. it is very useful for measuring how much tax burden the company will pay. then with a level of relationship of 59.27% which means there are 40.73% explained by other factors not examined in this study such as independent commissioners, affiliated company transactions, corporate governance, and audit quality. 5. conclusion findings regarding the influence of company size, profitability, level of debt, intensity of fixed assets and intensity of inventories on tax amnesty of energy companies listed in indonesia stock exchange from 2013 to 2017 with a sample size of 13 companies stated that company size has a significant effect on the direction tax amnesty of energy companies listed in indonesia stock exchange is positive, profitability has no effect on tax amnesty of energy companies listed in indonesia stock exchange, debt levels have a significant effect in a negative direction on tax amnesty of energy companies listed in indonesia stock exchange, fixed asset intensity has a significant effect in a negative direction on tax amnesty of energy companies listed in indonesia stock exchange, inventory intensity has no effect on tax amnesty of energy companies listed in indonesia stock exchange, firm size, profitability, level of debt, fixed asset intensity, and inventory intensity together have an effect on tax amnesty of energy companies listed in indonesia stock exchange. this illustrates that the company is more stable and able to generate profits compared to companies with small total assets. with the company’s ability to generate high profits, it will affect the tax amnesty because the tax burden also increases. furthermore, profitability in this study uses the measurement of the comparison of profit before tax with total assets, where the tax expense is obtained from taxable income, namely profit before tax after fiscal correction. with the existence of fiscal corrections can increase or decrease taxable income due to the occurrence of fixed differences (fixed differences) between recognition in commercial financial accounting and tax accounting (tax regulations), which can cause profit before tax to decrease but the tax burden to increase. therefore, managers in carrying out their tax planning should know that in taxation there are costs that can and some cannot be reduced by gross income. this result is theoretically in accordance with agency theory, namely the relationship between agent and principal, the relationship between owner/shareholder (principal) and manager (agent) is how the company manager uses debt in financing the companys operational activities. if the company uses debt in the composition of the financing, it will incur interest expenses that must be paid so that it will be a deduction from taxable income. this is beneficial for the company because tax payments are lower so that net income can increase, with increasing net profit the agent will get compensation from the principal for the work that has been done. practically, the findings suggest managers in tax planning to take advantage of depreciation to reduce the amount of corporate tax burden. managers can invest the company’s idle funds to invest in fixed assets, with the aim of getting a profit in the form of depreciation which can be used as a tax deduction so that tax amnesty decreases. another practical implication relates to the need for managers in carrying out tax planning to know that there is no tax incentive that comes from costs for companies that have a large amount of merchandise inventory. this is in accordance with the income tax law article 10 paragraph 6 concerning the valuation and allowable use of supplies based on cost only. references abidin, m.z., rosdiana, h., salomo, r.v. (2020), tax incentive policy for geothermal development: a comparative analysis in asean. international journal of renewable energy development, 9(1), 53-62. akhtar, s., javed, b., maryam, a., sadia, h. (2012), relationship between financial leverage and financial performance: evidence from fuel and energy sector of pakistan. european journal of business and management, 4(11), 7-17. andriansyah, a., sulastri, e.s., satispi, e.s. (2021), the role of government policies in environmental management. research horizon, 1(3), 86-93. cansino, j.m., pablo-romero, m.d.p., román, r., yñiguez, r. (2010), tax incentives to promote green electricity: an overview of eu-27 countries. energy policy, 38(10), 6000-6008. darmadi, i.n.h., zulaikha, z. (2013), analisis faktor yang mempengaruhi manajemen pajak dengan indikator tarif pajak efektif (studi empiris pada perusahaan manufaktur yang terdaftar di bursa efek indonesia pada tahun 2011-2012) (doctoral dissertation, fakultas ekonomika dan bisnis). darussalam, d. (2014), tax amnesty dalam rangka rekonsiliasi nasional. inside tax, 26, 14-19. derashid, c., zhang, h. (2003), effective tax rates and the “industrial policy” hypothesis: evidence from malaysia. journal of international accounting, auditing and taxation, 12(1), 45-62. jan, et al.: factors affecting tax incentives of energy companies listed on the indonesia stock exchange international journal of energy economics and policy | vol 11 • issue 6 • 2021334 dippenaar, m. (2018), the role of tax incentives in encouraging energy efficiency in the largest listed south african businesses. south african journal of economic and management sciences, 21(1), 1-12. etisya, m. (2017), dampak program tax amnesty terhadap kemauan membayar pajak (studi pada himpunan pengusaha muda indonesia (hipmi) di jember) (doctoral dissertation, universitas muhammadiyah jember). gunadi. (2007), rumitya menggapai rencana penerimaan pajak. bisnis indonesia, 20 agustus 2007. heffron, r.j. (2018), the application of distributive justice to energy taxation utilising sovereign wealth funds. energy policy, 122, 649654. hirschmann, r. (2020), tax revenue in indonesia 2000-2017. available from: https://www.statista.com/statistics/670985/indonesia-taxrevenue husnurrosyidah, h., nuraini, u. (2016), pengaruh tax amnesty dan sanksi pajak terhadap kepatuhan pajak. equilibrium: jurnal ekonomi syariah, 4(2), 1-10. hymel, m. (2006), united states experience with energy-based tax incentives: the evidence supporting tax incentives for renewable energy. loyola university chicago law journal, 38, 43. ibrahim, m.a., myrna, r., irawati, i., kristiadi, j.b. (2018), tax policy in indonesian energy sectors: an overview of tax amnesty implementation. international journal of energy economics and policy, 8(4), 234. jeffrey, c., perkins, j.d. (2015), the association between energy taxation, participation in an emissions trading system, and the intensity of carbon dioxide emissions in the european union. the international journal of accounting, 50(4), 397-417. kraal, d. (2019), petroleum industry tax incentives and energy policy implications: a comparison between australia, malaysia, indonesia and papua new guinea. energy policy, 126, 212-222. langedijk, s., nicodème, g., pagano, a., rossi, a. (2014), debt bias in corporate taxation and the costs of banking crises in the eu (no. 50). directorate general taxation and customs union, european commission. lanis, r., richardson, g., taylor, g. (2017), board of director gender and corporate tax aggressiveness: an empirical analysis. journal of business ethics, 144(3), 577-596. lisa, o., hermanto, b. (2018), the effect of tax amnesty and taxpayer awareness to taxpayer compliance with financial condition as intervening variable. international research journal of management, it and social sciences, 5(2), 227-236. mulyani, s., kusmuriyanto, k., suryarini, t. (2018), analisis determinan tax avoidance pada perusahaan manufaktur di indonesia. jurnal rak (riset akuntansi keuangan), 2(2), 53-66. ogunlana, a.o., goryunova, n.n. (2017), tax incentives for renewable energy: the european experience. the european proceedings of social and behavioural sciences, 19, 508-513, phuong, n.t.t., hung, d.n., van, v.t.t., xuan, n.t. (2020), effect of debt structure on earnings quality of energy businesses in vietnam. international journal of energy economics and policy, 10(3), 396401. radian, a. (1980), resource mobilization in poor countries: implementing tax policies. vol. 1. piscataway, new jersey: transaction publishers. salgado, m.a.h., tarelho, l.a., matos, m.a.a., rivadeneira, d. (2019), palm oil kernel shell as solid fuel for the commercial and industrial sector in ecuador: tax incentive impact and performance of a prototype burner. journal of cleaner production, 213, 104-113. sayidah, n., assagaf, a. (2019), tax amnesty from the perspective of tax official. cogent business and management, 6(1), 1659909. schratzenstaller, m., krenek, a., nerudová, d., dobranschi, m. (2017), eu taxes for the eu budget in the light of sustainability orientation a survey. jahrbücher für nationalökonomie und statistik, 237(3), 163-189. stella, p. (1991), an economic analysis of tax amnesties. journal of public economics, 46(3), 383-400. sun, c., zhan, y., du, g. (2020), can value-added tax incentives of new energy industry increase firm’s profitability? evidence from financial data of china’s listed companies. energy economics, 86, 104654. villca-pozo, m., gonzales-bustos, j.p. (2019), tax incentives to modernize the energy efficiency of the housing in spain. energy policy, 128, 530-538. zhang, h., zheng, y., zhou, d., zhu, p. (2015), which subsidy mode improves the financial performance of renewable energy firms? a panel data analysis of wind and solar energy companies between 2009 and 2014. sustainability, 7(12), 16548-16560. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(1), 93-100. international journal of energy economics and policy | vol 11 • issue 1 • 2021 93 determinants of energy consumption in newly industrialised countries of asia karen fernandes, y. v. reddy* goa business school, goa university, taleigao, goa, india. *email: yvreddy@unigoa.ac.in received: 05 august 2020 accepted: 15 november 2020 doi: https://doi.org/10.32479/ijeep.10725 abstract this study focuses on identifying the factors that lead to energy consumption in select newly industrialized countries of asia such as china, india, indonesia, malaysia, philippines and thailand. gdp, exchange rate, industrialization, urbanization and trade openness are the select factors identified and such data is obtained for a period from 1980 to 2018. to check for stationarity, adf unit root test and pp unit root test is employed where all variables are found to be stationary at first difference. ols regression is applied to identify which factor has an impact on energy consumption. besides, johansen cointegration test to establish long run relationship and vecm is employed, where all variables were found to be integrated in the long run however vecm indicated that for china and malaysia energy consumption is able to achieve equilibrium after a shock in the previous period. to determine causal links between variables, toda yamamoto causality test is applied. results indicate that industrialization, exchange rate, financial development and trade openness causes energy consumption in china. however, in india and thailand only industrialization causes energy consumption. gdp causes energy consumption in indonesia and trade openness causes energy consumption in malaysia. keywords: energy consumption, ols regression, vecm, toda yamamoto causality jel classifications: o13, o20, q43 1. introduction the consumption of energy is due to certain factors which directly or indirectly have an impact of energy consumption of a country. it is necessary to identify and study those factors that have an impact on energy use for a country so as to formulate appropriate energy policies and to control such factors accordingly. the factors identified as those that affect energy consumption based on literature review are economic growth (gdp), industrialisation, exchange rate, financial development and trade openness. economic growth measured by gross domestic production (gdp) refers to the total output of an economy. an increase in gdp indicates that the economic growth of a country is robust. high economic growth implies more energy requirements to sustain economic activities. when a country is an emerging economy, it moves from dependence on agriculture to the industry and services. the rapid spread of industries would lead to increase in demand for various forms of energy to support output. exchange rate refers to the rate at which domestic currency can be exchanged for foreign currency. an increase in exchange rate would discourage import of energy thereby reducing energy consumption since emerging countries are not self -sufficient in energy resources. financial development refers to the availability of finance especially with reference to the private sector. increase in financial development will encourage energy demand as an economy will be able to incur energy cost. trade openness is the ratio of trade to gdp of a country. higher the trade openness of a country, higher energy consumption of a country. majority studies have focused on identify whether specific individual variables have an impact on energy consumption and which leads to the omission of important variables which may have a significant impact on energy consumption. this study makes a this journal is licensed under a creative commons attribution 4.0 international license fernandes and reddy: determinants of energy consumption in newly industrialised countries of asia international journal of energy economics and policy | vol 11 • issue 1 • 202194 multivariate attempt to identify which variables have a significant impact on energy consumption for china, india, indonesia, malaysia, philippines and thailand. this will assist individual countries to monitor identified variables in order to achieved desired policy outcomes with respect to energy consumption and related environmental issues. variables under study have been selected based on availability of data and literature review. data is collected from the year 1980 to 2018 and therefore the period of the study is 38 years. 2. review of literature researchers have identified and examined the various possible factors that lead to energy use in a context of time series and panel studies for countries. in case of asean countries, (shah et al., 2015) examined the linkages among energy consumption, foreign direct investment, financial development and trade using techniques such as ardl testing approach and granger causality test. results indicated that there exists a long-run relationship among the variables and short-run unidirectional causality running from fdi inflows to energy consumption while (hassan, 2018) advocated that economic growth, energy access and urbanization have significant effects on energy demand. according to (çoban and topcu, 2013) greater financial development leads to more energy consumption however (obadi and korček, 2015) employed logarithmic mean divisia index decomposition technique and found that energy intensity effect was the major factor influencing energy consumption. (nasreen and anwar, 2014) explored the causal relationship between economic growth, trade openness and energy consumption in asian countries and identified economic growth and trade openness to have a positive impact on energy consumption while (sadorsky, 2010) examined the impact of financial development on energy consumption for emerging economies and concluded that the relationship is positive and statistically significant. (zeren and koc, 2014) investigated the relationship between energy consumption and financial development for newly industrialised countries and found bidirectional causality in only positive shocks for india and turkey while for thailand, positive shocks of financial development are cause of energy consumption. in south america, (sadorsky, 2012) examined the relationship between energy consumption, output and trade and concluded that there exists a short run bidirectional relationship between energy consumption and exports, output and exports/import and a long run causal relationship between trade and energy consumption. (kahouli, 2017) examined the short and long run causality relationship among economic growth, energy consumption and financial development for south mediterranean countries and found short-run unidirectional causal relationships existing at least once for each country (except egypt). in case of the organisation of the islamic conference countries, (gamoori et al., 2017) investigated the relationship between foreign investment, financial development (fd) and foreign trade with energy consumption and identified foreign trade, investment and financial development to had a positive significant effect on energy consumption while in case of the oecd (dedeoǧlu and kaya, 2013)found bidirectional causalities between exports, imports and gdp on energy consumption. granger causality from exports to energy consumption was found by a study conducted by (sadorsky, 2011) on the middle east. energy consumption is influenced by economic growth and financial development, both in the short and the long run, but population impacts energy consumption only in the long run according to a study conducted by (islam et al., 2013) who explored the existence of a long run relation among energy use, aggregate production, financial development and population while (shahbaz et al., 2015) advocated that urbanization affluence, capital stock and trade openness leads to increases in energy consumption. recently (ridzuan et al., 2020) analysed the macroeconomic indicators that influence malaysia’s electrical consumption and found that economic progression and urbanization that lead to increase in electrical consumption, whereas financial deepening and higher inflation leads to reduction. in case of india, (mahalik and mallick, 2014) using ardl approach to cointegration concluded that ec is positively and significantly impacted by urban population however negatively and significantly impacted by financial development, economic growth and proportion of industrial output while (shahbaz et al., 2016) identified acceleration of globalization and financial development is negatively related to energy consumption however economic growth and urbanization lead to increased energy demand. (bashir et al., 2019) investigated the causality between human capital, energy consumption, co2 emissions, and economic growth for indonesia and found that in the short-run, there is causal evidence between co2 emission and energy consumption. in vietnam (morelli and mele, 2020) used toda-yamamoto test and johansen and juselius approach to study the relationship among per capita gdp, co2 emissions, and energy use and concluded that economic growth leads to energy consumption. similarly in pakistan besides economic growth (komal and abbas, 2015) found a positive impact of urbanization and financial development on energy consumption and negative impact of energy prices on energy consumption. in turkey, (dumrul, 2019) using johansen cointegration test fmols and dols test concluded that financial development and economic growth have a positive effect on energy consumption. (shahbaz and lean, 2012) assess the relationship among energy consumption, financial development, economic growth, industrialisation and urbanisation in tunisia and found that long run bidirectional causalities between financial development and energy consumption, financial development and industrialisation, industrialisation and energy consumption. (rafindadi and ozturk, 2017) investigated whether financial development, trade openness and economic growth add to the energy consumption and found that all three variables lead to energy consumption in south africa. in germany, (rafindadi, 2014) predicted the effects of financial development and trade openness on the german energy consumption using bayerhank combined cointegration test, ardl bounds test and vecm granger causality test and concluded that financial development, capital use and trade openness decline energy demand. 3. data and methodology energy consumption (ec) is measures in million tonnes of oil equivalent and is sourced from bp statistical review. to identify which factors impact energy consumption, the select factors for fernandes and reddy: determinants of energy consumption in newly industrialised countries of asia international journal of energy economics and policy | vol 11 • issue 1 • 2021 95 this study include economic growth which is measured by real gdp per capita in constant 2010 usd sourced from world bank indicators database. exchange rate data is sourced from the websites of unctadstat, oecd and world bank. financial development (fd) is measured in terms of domestic credit to private sector (% of gdp) and is sourced from world bank indicators. industry (including construction), value added (% of gdp) trade openness is the ratio of trade to gdp of a country and is therefore measured by trade (% of gdp) sourced from world bank indicators. unit root tests are conducted to find out if a variable is time invariant i.e. whether the mean, variance and autocovariance of the variable are the same in different lags. augmented dickey fuller test and philip perron test (phillips and perron, 1988) is employed to check for stationarity of variables. from the table 1, both tests indicate that variables are stationery at first difference. the results of correlation in table 2 indicates that gdp, financial development and trade openness are highly positively correlated with energy consumption in case of china. the same is the case for india in addition to exchange rate. in case of indonesia gdp and exchange rate are highly positively correlated. the same is the case of malaysia where financial development is also positively correlated. correlation results for philippines indicates a negative correlation for industrialization and energy consumption however gdp and financial development is positively correlated. moreover the energy consumption of thailand is positively correlated with all variables under study. china_ec_log = 0.69752351574*china_ gdp_log−0.313664397653*china_industr ialisation_−0.223745440422*china_log_ exchange_rate−0.329203130314*china_log_ fd+0.229742822948*china_trade_openess_ log+0.330564482897 (1) india_ec_log = 0.138310413329*india_ exchange_rate_log+0.45259347386*india_in dustrialisation_−0.0355207050584*ind ia_log_fd+0.737692257873*india_log_ gdp−0.0702699455952*india_trade_op_ log−1.77462719673 (2) table 1: results for unit root test country variable adf unit root test pp unit root test test statistic level test statistic 1st difference test statistic level test statistic 1st difference china energy consumption (0.9710) (2.816)** 0.0556 (3.024)* gdp (2.872) (4.180)** (1.9517) (3.4636)** exchange rate (1.7374) (5.5256)** (1.8097) (5.5009)** financial development (2.6129) (5.6639)** (2.5974) (5.8228)** industrialization (1.9126) (4.0487)** (1.8581) (3.9791)** trade openness (1.4273) (5.4014)** (1.4490) (5.3906)** india energy consumption (1.7546) (6.4913)** (2.0012) (6.4909)** gdp (0.6546) (5.1698)** (0.5184) (15.6573)** exchange rate (1.0622) (4.8409)** (1.2199) (4.8665)** financial development (4.5987)** (2.4128) (1.5489) (5.4927)** industrialisation (2.3180) (2.6003)* (2.019) (5.8330)** trade openness (1.3536) (4.9075)** (1.8429) (4.9388)** philippines energy consumption (1.5967) (4.4506)** (2.0274) (4.4599)** gdp (0.2246) (8.6989)** (0.8991) (4.1915)** exchange rate (2.0790) (4.5691)** (2.0830) (4.5772)** financial development (2.5844) (3.9152)** (1.9900) (3.8850)** industrialisation (2.1501) (6.9745)** (2.0887) (6.9645)** trade openness (0.9051) (4.6678)** (1.2376) (4.7044)** malaysia energy consumption 0.8531 (3.4273)* 0.0967 (7.6755)** gdp (1.8.73) (5.0777)** (2.0088) (5.0777)** exchange rate (2.4899) (4.7440)** (1.9856) (4.6548)** financial development (2.9353) (5.5405)** (2.9156) (5.5312)** industrialisation (1.4361) (6.5976)** (1.4861) (6.6300)** trade openness (0.1810) (4.2758)** (0.1811) (4.1009)** indonesia energy consumption (0.3268) (5.1994)** (0.2581) (5.1344)** gdp (2.2718) (4.6402)** (1.9531) (4.6362)** exchange rate (1.8444) (6.5069)** (1.8059) (6.5069)** financial development (2.4036) (4.4939)** (2.2735) (4.4703)** industrialisation (1.1799) (5.4061)** (1.7634) (5.3416)** trade openness (2.6748) (8.3524)** (2.6327) (8.8411)** thailand energy consumption (0.0368) (4.4436)** (0.4861) (4.4095)** gdp (1.9539) (3.5696)** (1.4622) (3.5910)** exchange rate (1.3460) (4.7029)** (1.6063) (4.6432)** financial development (2.3015) (3.4219)* (1.7774) (3.4219)* industrialisation (1.3004) (6.5642)** (1.3104) (6.5383)** trade openness (0.8383) (5.0298)** (1.0209) (5.7275)** *indicates significance at 10% significance level. **indicates significance at 5% significance level. h0: variable is not stationery (has a unit root). h1: variable is stationery (does not have a unit root) fernandes and reddy: determinants of energy consumption in newly industrialised countries of asia international journal of energy economics and policy | vol 11 • issue 1 • 202196 table 3: results of ols regression dependent variable: energy consumption coefficient se t-statistic prob. china gdp 0.697524 0.039543 17.63940 0.0000** industrialisation −0.313664 0.250092 −1.254196 0.2186 exchange rate −0.223745 0.044105 −5.073069 0.0000** financial development −0.329203 0.145613 −2.260810 0.0305** trade openness 0.229743 0.056921 4.036205 0.0003** constant 0.330564 0.521134 0.634318 0.5302 r-squared 0.993299 india gdp 0.737692 0.079907 9.231929 0.0000** industrialisation 0.452593 0.205526 2.202124 0.0348** exchange rate 0.138310 0.030645 4.513341 0.0001** financial development −0.035521 0.083067 −0.427617 0.6717 trade openness −0.070270 0.047646 −1.474831 0.1497 constant −1.774627 0.345719 −5.133154 0.0000 r-squared 0.993964 indonesia gdp 0.559986 0.131830 4.247785 0.0002** industrialisation 0.597530 0.236679 2.524645 0.0166** exchange rate 0.213003 0.037711 5.648312 0.0000** financial development 0.069118 0.037324 1.851853 0.0730 trade openness −0.051914 0.138570 −0.374645 0.7103 constant −2.401055 0.367800 −6.528153 0.0000 r-squared 0.979848 malaysia gdp 1.061029 0.059576 17.80963 0.0000** industrialisation 0.102322 0.339966 0.300977 0.7653 exchange rate 0.091623 0.109669 0.835448 0.4095 financial development −0.043932 0.068679 −0.639674 0.5268 trade openness 0.274255 0.116960 2.344865 0.0252** constant −2.869976 0.495932 −5.787036 0.0000 r-squared 0.981068 philippines gdp 0.433738 0.072213 6.006376 0.0000** industrialisation −0.696052 0.170250 −4.088417 0.0003** exchange rate −0.040097 0.038908 −1.030563 0.3102 financial development 0.161312 0.043238 3.730760 0.0007** trade openness 0.285208 0.074572 3.824593 0.0006** constant 0.036113 0.351600 0.102710 0.9188 r-squared 0.959037 thailand gdp 1.059659 0.054081 19.59384 0.0000** industrialisation −0.188792 0.110925 −1.701974 0.0982 exchange rate 0.243879 0.043983 5.544859 0.0000** financial development 0.128935 0.031483 4.095362 0.0003** trade openness 0.291784 0.067551 4.319494 0.0001** constant −3.071457 0.167377 −18.35053 0.0000 r-squared 0.997942 **5% level of significance table 2: results for correlation ec china ec india ec indonesia ec malaysia ec philippines ec thailand gdp 0.987065 0.991081 0.957242 0.980850 0.773138 0.994677 industrialization −0.085809 0.533567 0.495878 0.267888 −0.700328 0.771328 exchange rate 0.615978 0.933498 0.960813 0.836903 0.695094 0.731504 financial development 0.909008 0.905934 0.393648 0.711091 0.820790 0.877992 trade openness 0.800247 0.932795 −0.007690 0.586957 0.587869 0.966438 source: researchers compilation fernandes and reddy: determinants of energy consumption in newly industrialised countries of asia international journal of energy economics and policy | vol 11 • issue 1 • 2021 97 indonesia_ec_log = 0.559986187182*indonesia__ gdp_log+0.213003141631*indonesia_exchange_ rate_+0.597529946157*indonesia_industr ialisat+0.0691177829398*indonesia_log_ fd−0.0519144752016*indonesia_trade_op log−2.40105492863 (3) malaysia_ec_log = 0.102321970337*malaysia__ industrialisat+0.0916229067461*malays ia_exchange_rate_l+1.0610289205*malaysia_ gdp_log−0.0439322878018*malaysia_log_ fd+0.27425514624*malaysia_trade_op log−2.86997569294 (4) philippines_ec_log = −0.0400968777434*philippines_exchange_ rat+0.433738314966*philippines_gdp_ log−0.696052281808*philippines_indust rialis+0.161311823803*philippines_log_ fd+0.285208415197*philippines_trade openes+0.0361129753543 (5) thailand_ec_log = 0.243878920341*thailand_ exchange_rate_l+1.05965892383*thailand_gdp _log−0.188791518478*thailand_industrialisati+0 .128934537752*thailand_ log_fd+0.291784230579*thailand_trade_op log−3.07145728454 (6) table 3 indicates ols regression where in case of china, economic growth, exchange rate, financial development and trade openness have a significant impact on energy consumption. a 1% increase in gdp and trade openness leads to 0.69% and 0.23% resp. increase in energy consumption. a 1% increase in exchange rate and financial development will each cause a decrease in energy consumption by 0.22% and 0.33% resp. in case of india, gdp, industrialization and exchange rate have a significant impact on energy consumption. a 1% increase in economic growth, industrialization and exchange rate will each lead to an increase in energy consumption by 0.73%, 0.45% and 0.14% resp. the same is in the case of indonesia where a 1% increase in gdp, industrialization and exchange rate will each increase energy consumption by 0.55%, 0.59% and 0.21% resp. gdp and trade openness have a significant impact on energy consumption of malaysia where a 1% increase in the variables will cause energy consumption to increase by 1.06% and 0.27% resp. gdp, industrialization , financial development and trade openness have a significant impact on the energy consumption of philippines. a 1% increase in gdp financial development and trade openness will each cause energy consumption to increase by 0.43%, 0.16% and 0.28% resp. while industrialization will decrease energy consumption by 0.69%. gdp, exchange rate, financial development and trade openness has a significant impact on energy consumption of thailand. a 1% increase in these variables will lead to an increase in energy consumption by 1.05%, 0.24%, 0.12% and 0.29% resp. table 4 indicating johansen’s cointegration test reveals that the variables under study are integrated in the long run towards equilibrium which is supported by trace statistic and max eigen value. vecm indicates the speed at which energy consumption returns to equilibrium after a change in the independent variables viz. gdp, industrialization, exchange rate, financial development and trade openness. vecm results in table 5 indicate that incase of china and malaysia there exists a long run relationship among the variables. for china, energy consumption is corrected towards long run equilibrium by 85% each year while for malaysia energy consumption is corrected towards long run equilibrium by 11% each year. the toda yamamoto causality test is considered to be an advanced causality test as pretests for unit root and cointegration is not a prerequisite. this test follows the method of adding extra lags intentionally in the estimation. the usual strategy that one tests some economic hypothesis conditioned on the estimation of a unit root, a cointegrating rank, and a cointegrating vector(s) may suffer from severe pretest biases (toda and yamamotob, 1995). table 6 indicates which variable causes table 4: johansen’s cointegration test country hypothesised number of cointegrating equations eigen value trace statistic critical value at 5% (p value) max eigen statistic critical value at 5% (p value) china none 0.913320 235.9224 95.75366 (0.0000) 85.59369 40.07757 (0.0000) at most 1 0.830164 150.3287 69.81889 (0.0000) 62.05225 33.87687 (0.0000) india none 0.780068 148.8716 95.75366 (0.0000) 56.03415 40.07757 (0.0004) at most 1 0.658735 92.83742 69.81889 (0.0003) 39.77850 33.87687 (0.0088) indonesia none 0.746577 135.7644 95.75366 (0.0000) 50.78977 40.07757 (0.0022) at most 1 0.615253 84.97460 69.81889 (0.0019) 35.34123 33.87687 (0.0332) malaysia none 0.662928 116.7574 95.75366 (0.0009) 40.23602 40.07757 (0.0480) at most 1 0.594869 76.52141 69.81889 (0.0132) 33.43115 33.87687 (0.0564) philippines none 0.718112 136.0521 95.75366 (0.0000) 46.85115 40.07757 (0.0075) at most 1 0.617659 89.20094 69.81889 (0.0007) 46.85115 33.87687 (0.0311) thailand none 0.982123 273.9532 95.75366 (0.0000) 140.8488 40.07757 (0.0001) at most 1 0.839631 133.1044 69.81889 (0.0000) 64.05970 33.87687 (0.0000) source: authors compilation fernandes and reddy: determinants of energy consumption in newly industrialised countries of asia international journal of energy economics and policy | vol 11 • issue 1 • 202198 graph 1: china graph 2: india graph 3: indonesia graph 4: malaysia graph 5: philippines energy consumption with respect to each country under study. industrialization, exchange rate, financial development and trade openness causes energy consumption in china. however, in india and thailand only industrialization causes energy consumption. in indonesia, gdp causes energy consumption and trade openness causes energy consumption in malaysia. the energy consumption of the philippines is not caused by any of the select factors. the inverse roots of ar characteristic polynomial i.e. the reciprocal of the roots indicates stability. if all inverse roots lie within the unit circle, the process is stationary. the inverse roots of graph 1 which indicates stability for china, graph 2 for india, graph 3 for indonesia, graph 4 for malaysia, graph 5 for philippines and graph 6 for thailand are situated within the circle which indicates stability. fernandes and reddy: determinants of energy consumption in newly industrialised countries of asia international journal of energy economics and policy | vol 11 • issue 1 • 2021 99 exchange rate have a significant impact on energy consumption. in addition energy consumption is caused due to industrialization and gdp for india and indonesia resp. according to toda yamamoto causality test. the government of india has stressed upon encouraging domestic production and consumption through ‘make in india initiatives and encouraging exports which leads to industrialization. gdp and trade openness have a significant impact on energy consumption of malaysia and there exists a long run relationship between the variables according to vecm which is in line with (islam et al., 2013; shahbaz et al., 2015). moreover toda yamamoto causality test suggests that trade openness causes energy consumption. the 11th five year plan (2016-2020) has focused on increasing exports to improve the country’s trade balance. besides, the government has aimed to promote productivity and investment to increase sustainable economic growth in other words green growth. in case of the philippines, gdp, industrialization, financial development and trade openness have a significant impact on the energy consumption. by 2022, the development plan of the philippines focuses on alleviating the country to upper middle income by lowering poverty and unemployment rates in rural areas through inclusive growth (manila2018.dof.gov.ph). gdp, exchange rate, financial development and trade openness has a significant impact on energy consumption of thailand. however, toda yamamoto causality test indicates that industrialization causes energy consumption of thailand. the 12th national economic and social development plan focuses on promoting its industrial sector through advanced science, technology and innovation thereby generating economic value added (eva) as well as enhancing the potential of existing production and service base by strengthening connectivity in the manufacturing sector. besides, the development plan aims to expand thai outward investment and making the financial sector more efficient and competitive. therefore it is evident that the energy consumption needs of all countries under study will increase in the future as analysis indicate that the various select factors have a significant impact on energy consumption. therefore there is a need to invest in discovering renewable sources of energy to sustain economic development. references chin, j. (2018), available from: http://niti.gov.in/index.php/annualreports. annual report, niti ayog, government of india. (2020), available from: https://www.thestar.com.my/business/business-news/2018/10/18/ table 5: vector error correction model ect coefficient se t-statistic prob. china −0.853437 0.276379 −3.087925 0.0075** india 0.181179 0.090903 1.993095 0.0557 indonesia −0.067305 0.155462 −0.432936 0.6712 malaysia −0.107820 0.049879 −2.161634 0.0390** philippines −0.040591 0.168186 −0.241348 0.8110 thailand −0.017373 0.017753 −0.978585 0.3359 **5% level of significance table 6: toda yamamoto causality test country industrialisation causes ec gdp causes ec exchange rate causes ec financial development causes ec trade openness causes ec china 0.0009** 0.0751 0.0000** 0.0024** 0.0096** india 0.0144** 0.7024 0.5918 0.1187 0.7076 indonesia 0.4850 0.0469** 0.6960 0.2536 0.0613 malaysia 0.4264 0.1015 0.9957 0.1679 0.0418** philippines 0.4719 0.5742 0.4814 0.8553 0.4471 thailand 0.0290** 0.4108 0.5983 0.9993 0.8259 **5% level of significance graph 6: thailand 4. conclusion economic growth (gdp), exchange rate, financial development and trade openness has a significant impact on energy consumption for china. since the 13th five year plan which ends in the year 2020 focuses on expanding exports, increasing outbound and inbound investment as well as strengthening the domestic currency and the gdp of the country, energy will have increased. a positive sign is that the 14th five year plan had stressed upon the need to cap carbon emissions and reducing coal consumption (non-renewable energy consumption) in addition to expanding non-fossil fuel (hydro power and nuclear energy) energy generation by 20% of energy mix. (chinadialogue.net). long run relationship among the variables also exists where energy consumption of china is able to correct itself towards long run equilibrium by 85% after a shock in the previous period. according to toda yamamoto causality test, industrialization, exchange rate, financial development and trade openness causes energy consumption in china. in india and indonesia, results suggest that gdp, industrialization and fernandes and reddy: determinants of energy consumption in newly industrialised countries of asia international journal of energy economics and policy | vol 11 • issue 1 • 2021100 highlights-of-11th-malaysia-plan-mid-term-review. bashir, a., thamrin, k.m.h., farhan, m., mukhlis, m., atiyatna, d.p. (2019), the causality between human capital, energy consumption, co2 emissions, and economic growth: empirical evidence from indonesia. international journal of energy economics and policy, 9(2), 98-104. çoban, s., topcu, m. (2013), the nexus between financial development and energy consumption in the eu: a dynamic panel data analysis. energy economics, 39, 81-88. dedeoǧlu, d., kaya, h. (2013), energy use, exports, imports and gdp: new evidence from the oecd countries. energy policy, 57, 469-476. dumrul, y. (2019), estimating the impact of the financial development on energy consumption: a co-integration analysis. international journal of energy economics and policy, 8(5), 294-299. gamoori, a., jorjorzadeh, a., mehrabani, f. (2017), investigation the links between foreign investment, economic growth and energy usage : organization of the islamic conference countries. international journal of energy economics and policy, econjournals, 7(2), 304-309. hassan, s. (2018), long run energy demand and its determinants: a panel cointegration analysis of the association of southeast asian nations-5. international journal of energy economics and policy, 8(4), 270-279. islam, f., shahbaz, m., ahmed, a.u., alam, m.m. (2013), financial development and energy consumption nexus in malaysia: a multivariate time series analysis. economic modelling, 30(1), 435-441. kahouli, b. (2017), the short and long run causality relationship among economic growth, energy consumption and financial development: evidence from south mediterranean countries (smcs). energy economics, 68, 19-30. komal, r., abbas, f. (2015), linking fi nancial development, economic growth and energy consumption in pakistan. renewable and sustainable energy reviews, 44, 211-220. mahalik, m.k., mallick, h. (2014), energy consumption, economic growth and financial development: exploring the empirical linkages for india. the journal of developing areas, 48(4), 139-159. morelli, g., mele, m. (2020), energy consumption, co2 and economic growth nexus in vietnam. international journal of energy economics and policy, 10(2), 443-449. nasreen, s., anwar, s. (2014), causal relationship between trade openness, economic growth and energy consumption: a panel data analysis of asian countries. energy policy, 69, 82-91. obadi, s.m., korček, m. (2015), investigation of driving forces of energy consumption in european union 28 countries. international journal of energy economics and policy, 5(2), 422-432. philippine development plan. (2017-2022), abridged version. available from: http://www.neda.gov.ph/philippinedevelopmentplan-2017-2022. phillips, p.c.b., perron, p. (1988), testing for a unit root in time series regression. biometrika, 75(2), 335-346. rafindadi, a.a. (2014), econometric prediction on the effects of financial development and trade openness on the german energy consumption: a startling revelation from the data set. international journal of energy economics and policy, 5(1), 182-196. rafindadi, a.a., ozturk, i. (2017), dynamic effects of financial development, trade openness and economic growth on energy consumption: evidence from south africa. international journal of energy economics and policy, 7(3), 74-85. ridzuan, a.r., kamaludin, m., ismail, n.a., razak, m.i.m., haron, n.f. (2020), macroeconomic indicators for electrical consumption demand model in malaysia. international journal of energy economics and policy, 10(1), 16-22. sadorsky, p. (2010), the impact of financial development on energy consumption in emerging economies. energy policy, 38(5), 2528-2535. sadorsky, p. (2011), trade and energy consumption in the middle east. energy economics, 33(5), 739-749. sadorsky, p. (2012), energy consumption, output and trade in south america. energy economics, 34(2), 476-488. shah, i., abidin, z., haseeb, m., azam, m., islam, r. (2015), foreign direct investment, financial development, international trade and energy consumption : panel data evidence from selected asean countries. international journal of energy economics and policy, 5(3), 841-850. shahbaz, m., lean, h.h. (2012), does financial development increase energy consumption? the role of industrialization and urbanization in tunisia. energy policy, 40(1), 473-479. shahbaz, m., loganathan, n., sbia, r., afza, t. (2015), the effect of urbanization, affluence and trade openness on energy consumption: a time series analysis in malaysia. renewable and sustainable energy reviews, 47, 683-693. shahbaz, m., mallick, h., kumar, m., sadorsky, p. (2016), the role of globalization on the recent evolution of energy demand in india : implications for sustainable development. energy economics, 55, 52-68. the 12th national economic and social development plan. (2017-2021), available from: https://www.data.thailand.opendevelopmentmekong. net/library_record/12. toda, h.y., yamamoto, t. (1995), statistical inference in vector autoregressions with possibly integrated processes. journal of econometrics, 66(1-2), 225-250. u.s. china economic and security review commission. (2017), the 13th five-year plan, katherine koleski, research director and policy analyst, economics and trade. available from: https:// www.chinadialogue.net/en/pollution/9048-13th-five-year-planin-focus. zeren, f., koc, m. (2014), the nexus between energy consumption and financial development with asymmetric causality test: new evidence from newly industrialized countries. international journal of energy economics and policy, 4(1), 83-91. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 1 • 202314 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(1), 14-21. the role of consumer attitude and renewable energy towards environmental friendly policies in the intention to comply with the paid plastic environmental friendly policy anton atno parluhutan sinaga1*, sunday ade sitorus2 1methodist university of indonesia, medan, indonesia, 2hkbp nommensen university, medan, indonesia. *email: antonmethodist@gmail.com received: 28 august 2022 accepted: 22 december 2022 doi: https://doi.org/10.32479/ijeep.13612 abstract the purpose of this study is to determine the effect of consumer attitudes and renewable energy on the intention to comply with the paid plastic environmentally friendly policy in north sumatra province through the environmental friendly policy variable made by the government as a moderator variable. in this study the variables used are exogenous variables, namely consumer attitudes and renewable energy, while the endogenous variables are intention to comply with the paid plastic eco-friendly policy in north sumatra province and the moderator variable is environmentally friendly policies made by the government. in this study, the data taken were adult population data in north sumatra province in 2020 who used as much as of plastic 4,177,004 souls. the research method used in this study is a quantitative descriptive research method using data analysis, namely path analysis using pls 3.0 software. based on the results of the research analysis, the conclusion of this study is partially that only consumer attitude variables affect the intention to comply with paid plastic environmentally friendly policies in north sumatra province and consumer attitudes and renewable energy variables affect environmentally friendly policy variables. simultaneously, consumer attitudes and renewable energy variables affect the intention to comply with the paid plastic environmentally friendly policy in north sumatra province with the environmental friendly policy variable as the moderator variable. through the results of the research that has been stated above, the adults of north sumatra will have the intention to obey and obey all environmentally friendly policies that are carried out, such as creating renewable energy, these policies are very useful so that the people of north sumatra are protected from the dangers of environmental damage and disasters, nature that will happen if you still use energy from fossils that can pollute the land, sea and air. keywords: consumer attitude, renewable energy, intention to comply with environmentally friendly policies, environmentally friendly policies jel classifications: e42, e60, e71 1. introduction in the era of free trade or globalization, economic actors in various parts of the world are required to conduct trade between countries without setting impeding boundaries, such as the abolition of boundaries that hinder the economy, such as the imposition of strict import and export tariffs, the determination of export and import taxes, as well as the determination of high tariffs on certain products from various countries, which has already occurred in the range of 2020-2021 when the trade war between the united states and china occurred. in addition, in carrying out free trade activities an agreement appears that will allow a country to reduce carbon emissions, where these carbon emissions cause global warming, as well as environmental damage due to excessive use of fossil energy. reducing carbon emissions is one of the environmentally friendly policies in order to maintain world harmony and harmony, preserve the world’s environment, and keep mankind from doing things that can cause increased global warming, thereby causing this journal is licensed under a creative commons attribution 4.0 international license sinaga and sitorus: the role of consumer attitude and renewable energy towards environmental friendly policies in the intention to comply with the paid plastic environmental friendly policy international journal of energy economics and policy | vol 13 • issue 1 • 2023 15 climate change as a result of the use of materials from natural sources. fossils that can damage various joints of the environment, not only the land, but also the sea and air (hanif et al., 2019). the use of fossil energy today is very worrying for the world’s population, not only residents in urban areas, but also very worried about the population in rural areas, where this fossil energy causes pollution, not only soil pollution, but can also cause sea and air pollution, where the use of fossil energy this contributes 70% to global warming and climate change (khan et al., 2019). governments in various parts of the world are united and want to do something to prevent global warming and climate change by forming the paris agreement cooperation, where this agreement explains that each country is required to reduce the level of carbon emissions or the greenhouse effect in accordance with the targets set in their respective countries. -each country, in order to limit the increase in temperature by 2°c (atinkut et al., 2020). to prevent climate change, each country must implement environmentally friendly policies, where this policy can be carried out by increasing the use of renewable energy and reducing the use of energy or fuels from animals and fossils, where energy or fossil fuels can pollute the air and make earth’s temperature increases every year (white et al., 2019).there are still many countries that are egocentric and don’t pay attention to the agreement to reduce carbon emissions, where there are still countries that don’t care about the impacts caused by global warming and climate change, where the earth’s temperature will rise, there are unclear seasonal changes in various places countries, as well as the melting of the ice surface in the north pole and in the greenland area, so that it will have an impact on massive sea level rises that will endanger some of the islands in the world (prakash et al., 2019). with the impact that is very detrimental to the world’s population, it is necessary to have a strong commitment and prevent egocentricity to save the world and also save humanity from extreme disasters that will hit the world if environmentally friendly policies, such as creating renewable energy that does not pollute the soil, air and sea is implemented and executed well and comprehensively. indonesia is one of the countries that follow this paris agreement, where indonesia must comply with every item of this agreement to prevent things that are detrimental to the indonesian population, where the government must slowly implement this environmentally friendly policy and must gradually abandon the use of natural materials. non-environmentally friendly fuels, such as fuel oil and natural gas. environmentally friendly policies that are slowly being implemented are the conversion from the use of kerosene to gas, the elimination of the use of gasoline, slowly reducing the consumption of fossil fuels, such as diesel and will replace them with environmentally friendly fuels, such as fuel from palm oil (bio fuel) and fuel from plastic that does not pollute the environment (ekasari and zaini, 2020). plastic is one of the necessities that indonesian people need to wrap something, as a packaging material for food and non-food products and also serves for food storage. in a function that is already very good, there are parties who abuse plastic by throwing plastic in the wrong place, throwing plastic carelessly, resulting in pollution of the existing environment, as has been seen in indonesia, the emergence of floods, landslides and plastic waste pollution which made the government initially come up with the idea to prevent such pollution, then paid plastic was applied to consumers who wanted to wrap something using plastic or packaging when going shopping at traditional markets and supermarkets. at first this policy was widely supported by environmental organizations, but the attitude of consumers who did not agree with the policy so that the government did not implement it directly, but the policy was handed over to the regions, so that the regions had implemented it, and some did not apply it. this is because it still follows the desires and wishes of the community that paid plastic policies are very detrimental to people with low incomes. due to the very attitude of consumers to spend money to pay for the use of plastic in shopping centres and other places, this policy cannot be applied in various regions or regions, where this policy can be applied to people who have empathy and awareness that the use of paid plastic will prevent the occurrence of environmental damage, so that the role of consumers becomes very important to create a healthy climate and an undamaged environment, so that the environment becomes clean and beautiful, and free from plastic waste pollution. for example, jakarta is one of the provinces in indonesia that implements a paid plastic policy when consumers are going to buy something by wrapping goods or giving packaging to products, where this policy can be implemented properly because of the attitude of consumers who are aware of the cleanliness and environmental sustainability of jakarta so that the capital city can be clean and tidy and not polluted with plastic waste and prevent environmental damage. in addition, paid plastic can be a substitute for fossil energy to prevent climate change, where paid plastic is used to limit the use of single-use plastics, where the role of plastic as a counterweight to the use of renewable energy can prevent and reduce carbon emissions, so this paid plastic is a temporary solution for prevention of damage to nature and the environment caused by human activities that pollute the land, sea and air. north sumatra province has several shopping places, where consumers who always shop at shopping centres in the north sumatra province need a place to put groceries such as plastic. during the period of 2020, the population of north sumatra province was around 14,703,532, where the number of adults was around 4,177,004 people who often shopped and used plastic as a place to wrap something or product packaging. north sumatra province is one of the provinces that implement a paid plastic policy in the territory of indonesia, where the average consumer attitude with the existence of this paid plastic application tends not to support efforts to prevent increasing global warming and climate change, where there are still some residents in the sumatra region. north sumatra, so that they do not have full intention and awareness to comply with environmentally friendly policies through paid plastic policies, so it can be said that the adult population in the north sumatra region does not yet have the awareness to balance fossil energy into renewable energy through paid plastic policies made by the government, so that later can prevent north sumatra province from things that can damage the regional environment in north sumatra province. the purpose of this study is to determine the effect of consumer attitudes and renewable energy on the intention to comply with the paid plastic environmentally friendly policy in north sumatra sinaga and sitorus: the role of consumer attitude and renewable energy towards environmental friendly policies in the intention to comply with the paid plastic environmental friendly policy international journal of energy economics and policy | vol 13 • issue 1 • 202316 province through the environmental friendly policy variable made by the government as a moderator variable. 2. literature review 2.1. consumer attitude consumer attitude is the willingness of consumers to increase the consumption of goods and services in order to use products appropriately and efficiently (al-harahsheh et al., 2019). the attitude of consumer behavior describes an effort to obtain goods and services by paying attention to aspects that will make him always able to take an attitude in the process of obtaining these goods and services (ahmad et al., 2021). consumer attitude is a study conducted to find out the actions of consumers whether they want to consume the product or not (bugge et al., 2019). consumer attitude is something that needs to be studied so that later the business that will be developed can make consumers behave to use the product as well as possible (kasayanond et al., 2019). consumer attitudes, product use policy is an effort made in an effort to buy and use the resulting product so that the product is known by consumers, so that it can be a thorough consideration for consumers whether the product is useful and can be used for consumers or not (rich, 2018). the factors that influence consumer attitudes in paying plastic environmentally friendly policies are as follows: condition of goods due to policy, consumer interest, consumer response to policy, social influence, awareness in consumers’ minds of policy (van riel et al., 2021). 2.2. renewable energy renewable energy is a natural energy source and is able to renew itself continuously and is used for wider purposes because it does not include materials that damage the environment (popovic et al., 2019). renewable energy is a natural energy source and can be used continuously and cannot be used up because it is very beneficial for the community (agyeman and badugu, 2017). renewable energy comes from nature, where this energy comes from available sources from nature, it can be from plants, semiused goods, to goods that are free and found in nature (nadia et al., 2021). renewable energy is a basic need for humans that comes from nature, is free and is everywhere and is used to prevent natural destruction (arafah et al., 2018; destek and aslan, 2017; destek and sinha, 2020). renewable energy is an energy that is intended for the benefit of society, where this energy is needed to overcome problems that exist on earth, such as natural damage and global warming, and climate change (spranz et al., 2018). renewable energy is an alternative energy that is intended to replace fossil energy that disturbs and damages the environment, and can be renewed for the greater benefit and for the benefit of mankind (yacob et al., 2019). the factors that affect the need for renewable energy are as follows: old energy cannot be renewed, excessive consumption of fossil energy, high population growth, large energy subsidies, the existence of alternative energy sources (zutshi et al., 2016). 2.3. environmentally friendly policy environmentally friendly policy is a policy that is regulated so that later it can be used to prevent problems related to the emergence of seeds of damage in the environment (khansa and widiastuti, 2022). environmentally friendly policy is a policy that is made to prevent environmental damage by implementing processes that produce from various sources in nature (andaç and güzel, 2017). environmentally friendly policy is a policy that leads to environmental preservation, where this policy is carried out to prevent ecosystem damage that will lead to environmental destruction (ćwiąkała-małys and mościbrodzka, 2019). environmentally friendly policies can be utilized not only by the government, but also by humans and society in their daily lives, so that in implementing these policies the community can create a beautiful and sustainable environment and prevent natural damage (hwang and choi, 2018). the factors that influence environmentally friendly policies are as follows: environmental conditions, things that can harm society and the environment, quality of the environment, public awareness of environmental sustainability (urbinati et al., 2019). 2.4. intention to comply with policy the intention to comply with the policy is something that the community realizes is important to be obeyed in order to achieve the benefit and the policy is indeed appropriate for the benefit of the community (kim and yun, 2019). the intention to comply with the policy is a right that is carried out to submit to a policy that is indeed beneficial to the community (yacob et al., 2019). intention to comply with policies is a human psychology to obey the rules and something that is made to improve the welfare of mankind (lee et al., 2018). people who have the intention to comply with a government policy must have the attention and attitude to always obey the existing rules and also to what is the object of a policy that has been set (mohd et al., 2018). the factors that influence the intention of the community to comply with government policies are as follows: what the community wants, something that the community needs, desire to improve community welfare, desire to facilitate services to the community (tomşa et al., 2021). 3. research methods the research method used is descriptive quantitative. quantitative descriptive method is a method used by analyzing and describing all the constraints and obstacles as well as problems in research in order to find a solutive solution. the data analysis is carried out by using the path analysis method using pls (kock, 2018). path analysis is a data analysis used to determine the direct and indirect effects between several variables. in this study, the variables used are exogenous variables, namely consumer attitudes and renewable energy, while the endogenous variables are variables intention to comply with the paid plastic eco-friendly policy in north sumatra province and the moderator variable is environmentally friendly policies made by the government (pişirir et al., 2020). in this study, the data taken were adult population data in north sumatra province in 2020 who used as much as of plastic4,177,004 souls, and analysis of the data using path analysis through the pls 3.0 program. the population of this study is paid plastic users who are sourced from the adult population in north sumatra province in 2020 amounting to 4,177,004 people, the sampling technique in this study uses the simple random sampling method, simple random sampling method is a research method carried out by determining sinaga and sitorus: the role of consumer attitude and renewable energy towards environmental friendly policies in the intention to comply with the paid plastic environmental friendly policy international journal of energy economics and policy | vol 13 • issue 1 • 2023 17 how many samples from the universe of the population are selected randomly each sample has an equal chance of being selected as a sample, the number of samples can be calculated by the slovin formula namely (usakli and kucukergin, 2018). n = n/(1 + (n × e²)) n = 4,177,004/(1 + (4,177,004 × 0.05²) n = 399 samples. 4. research results to find out the output results via pls, it can be explained in the following bootstrapping model figure 1: information: exogenous variables: consumer attitudes (sk) and renewable energy (et). endogenous variables: intention to comply with environmentally friendly policies (nuptkrl). moderator variable: environmentally friendly policy (krl). 4.1. convergent validity convergent validity data processing is a test carried out to obtain results that state the results of the data processing can be said to be valid, the condition for the outer loading value is greater than a significance of 0.7 (pişirir et al., 2020), the results of data processing from the convergent validity test can be seen in table 1: based on table 1, it can be concluded that the results of data processing or the outer loading value of several variables are greater than 0.70, it can be concluded that the distribution of the results of data processing through the convergent validity test of several variables can be said to have a valid data distribution and is suitable for use for other data processing. 4.2. average variant extracted (ave) the results of the ave analysis data processing can be seen in table 2. based on table 2, it can be explained that the results of data processing for the average variant extracted value have a value greater than 0.5, which means that the distribution of data from existing variables has accurate data acceleration, so it is necessary to continue with further data testing. 4.3. composite reliability test for the results of testing the data from the composite reliability test, it can be seen in table 3: based on table 3, it can be explained that the value of the data processing results from the composite reliability test results is >0.6, which means that all variables have a high level of reliability and are feasible for further testing. 2,402 sk sk1 sk2 sk3 sk4 sk5 krl krl1 krl2 krl3 krl4 et et1 et2 et3 et4 et5 tuptkrl tuptkrl1 tuptkrl2 tuptkrl3 tuptkrl1 2,405 4,732 4,504 6.542 -1,243 0.752 0.718 0.8440.8370.792 0.743 0.764 0.746 0.708 0.754 0.855 0.853 0.736 0.873 0.832 0.775 0.737 0.827 figure 1: model bootstrapping sinaga and sitorus: the role of consumer attitude and renewable energy towards environmental friendly policies in the intention to comply with the paid plastic environmental friendly policy international journal of energy economics and policy | vol 13 • issue 1 • 202318 4.4. path coefficient test path coefficient test is the result of data testing to find out how strong the direct or indirect influence is between variables (kurniawan and wahyuningsih, 2018). the path coefficient test results can be seen in the r2 value or r square value which can be analyzed according to tables 4-8: based on table 5, it can be explained that the r square value of the consumer attitude variable is 83.2, which means that the percentage change in consumer attitudes of 83.2% can be explained by the intention variable to comply with environmentally friendly policies and the remaining 16.8% can be explained by other variables not explained in this study. based on table 5, it can be explained that the r square value of the renewable energy variable is 80.8, which means that the percentage of the amount of renewable energy produced is 62.8% which can be explained by the intention to comply with environmentally friendly policies and the remaining 37.2% can be explained by other variables that are not explained in this study. based on table 6, it can be explained that the r square value of the consumer attitude variable is 83.5, which means that the percentage of changing consumer attitudes of 83.5% can be explained by the environmental friendly policy variable and the remaining 16.5% can be explained by other variables not described in this study. based on table 7, it can be explained that the r square value of the renewable energy variable is 80.6, which means that the percentage of the amount of renewable energy created is 80.6% which can be explained by the environmental friendly policy variable and the remaining 19.4% can be explained by the variable. others not described in this study. based on table 8, it can be explained that the r square value of the environmentally friendly policy variable is 83.3, which means that the percentage of improvement in environmentally friendly policies of 83.3% can be explained by the intention to comply with environmentally friendly policies and the remaining 16.7%. can be explained by other variables that are not explained in this study. 4.5. hypothesis testing to explain the results of hypothesis testing can be seen in table 9. based on table 9, it can be explained that only the consumer attitude variable affects the intention to comply with the paid table 1: convergent validity test variable indicator outer loading consumer attitude (x1) sk 1 0.775 sk 2 0.746 sk 3 0.708 sk 4 0.754 sk 5 0.737 renewable energy (x2) et1 0.855 et 2 0.853 et 3 0.736 et 4 0.873 et 5 0.832 intention to comply with environmentally friendly policies (y) tuptkrl 1 0.743 tuptkrl 2 0.752 tuptkrl 3 0.718 tuptkrl 4 0.827 environmentally friendly policy (z) krl 1 0.764 krl 2 0.792 krl 3 0.837 krl 4 0.844 source: data processing results with pls 3.0, 2022 table 2: ave test variable ave consumer attitude (x1) 0.640 renewable energy (x2) 0.556 intention to comply with environmentally friendly policies (y) 0.623 environmentally friendly policy (z) 0.722 source: data processing results with pls 3.0, 2022 table 3: composite reliability test variable composite reliability consumer attitude (x1) 0.863 renewable energy (x2) 0.866 intention to comply with environmentally friendly policies (y) 0.872 environmentally friendly policy (z) 0.747 source: data processing results with pls 3.0, 2022 table 4: test of r square variable x1 against y variable r square consumer attitude (x1) 0.832 intention to comply with environmentally friendly policies (y) 0.811 source: data processing results with pls 3.0, 2022 table 5: test of r square variable x2 against y variable r square renewable energy (x2) 0.628 intention to comply with environmentally friendly policies (y) 0.621 source: data processing results with pls 3.0, 2022 table 6: test of r square variable x1 against z variable r square consumer attitude (x1) 0.835 environmentally friendly policy (z) 0.810 source: data processing results with pls 3.0, 2022 table 7: test of r square variable x2 against z variable r square renewable energy (x2) 0.806 environmentally friendly policy (z) 0.623 source: data processing results with pls 3.0, 2022 table 8: r square test of variable z against y variable r square environmentally friendly policy (z) 0.833 intention to comply with environmentally friendly policies (y) 0.825 source: data processing results with pls 3.0, 2022 sinaga and sitorus: the role of consumer attitude and renewable energy towards environmental friendly policies in the intention to comply with the paid plastic environmental friendly policy international journal of energy economics and policy | vol 13 • issue 1 • 2023 19 plastic environmentally friendly policy in north sumatra province and the consumer attitude variable and renewable energy partially affect the environmentally friendly policy variable. simultaneously, consumer attitudes and renewable energy variables affect the intention to comply with the paid plastic environmentally friendly policy in north sumatra province with the environmental friendly policy variable as the moderator variable. 5. discussion based on the results of the t-test for the consumer attitude variable, it can be seen that the t-test value of 6.542 is greater than the significance value of 0.05, consumer attitudes affect the intention to comply with paid plastic environmentally friendly policies in north sumatra province,explained that the intention to comply with any environmentally friendly policy by the government of a country can be seen from the attitude of consumers in responding to the policy, if the policy is very useful, then consumers as citizens in a region or country will obey, obey and follow the policy (rich, 2018). on the other hand, if the policy is not useful and tends to harm consumers (society), then consumers will not obey, obey and follow the policy. in addition, the results of the t-test for consumer attitudes can be seen that the t-test value of 4.504 is greater than a significance value of 0.05, consumer attitudes affect environmentally friendly policies, research. this study explains that consumer attitudes in supporting environmentally friendly policies can be seen from the intention to always obey and obey the policy, this environmentally friendly policy will prevent and protect the community from environmental damage, such as floods, landslides, and other natural disasters. the results of the t-test regarding consumer attitudes can be seen that the t-test value of 4.732 is greater than a significance value of 0.05, which means that consumer attitudes affect the intention to comply with paid plastic environmentally friendly policies in north sumatra province with environmentally friendly policy variables as moderator variables (he et al., 2019; jaelani et al., 2017). the good attitude of consumers to comply with environmentally friendly policies can be seen from the willingness to obey and obey the policies implemented to prevent global warming. based on the results of the t-test for renewable energy variables, it can be seen that the t-test value of -1.243 is smaller than the significance value of 0.05, which means that the renewable energy variable affects the variable of intention to comply with paid plastic environmentally friendly policies in north sumatra province (al-harahsheh et al., 2019). renewable energy that is created and is part of an environmentally friendly policy does not make consumers as citizens of a country or region to comply with environmentally friendly policies, because this renewable energy takes a long time to be managed and created perfectly to meet alternative energy needs, so that currently consumers are not too sure that renewable energy will benefit society (kim and yun, 2019). in addition, the results of the t-test for renewable energy variables, the t-test value of 2.402 is greater than the significance value of 0.05, which means that the renewable energy variable affects the environmental friendly policy variable, environmentally friendly policies that are useful for finding alternative energy are highly adhered to and adhered to by consumers as citizens, consumers will always follow what the policy is to protect residents and consumers to prevent environmental damage and climate change (hwang and choi, 2018). the results of the t-test for renewable energy variables, the t-test value of 2.540 is greater than the significance value of 0.05, which means that the renewable energy variable affects the intention to comply with the paid plastic environmentally friendly policy in north sumatra province with the environmentally friendly policy variable as a variable. moderator, renewable energy and environmentally friendly policies become a single unit, this policy affects the ability of a country or region to protect its citizens from natural damage that will harm the citizens of that country, so that citizens as consumers of renewable energy users will tend to be obedient and obedient and will follow all environmentally friendly policies made by the state (nadia et al., 2022). 6. conclusion based on the results of the research analysis, the conclusion of this study is partially that only consumer attitude variables affect the intention to comply with paid plastic environmentally friendly policies in north sumatra province and consumer attitudes and renewable energy variables affect environmentally friendly policy variables. simultaneously, consumer attitudes and renewable energy variables affect the intention to comply with table 9: hypothesis testing hypothesis influence t-statistics p-value results h1 influence of consumer attitudes towards the intention to comply with environmentally friendly policies 6.542 0.000 received h2 effects of renewable energy towards the intention to comply with environmentally friendly policies -1,243 0.203 rejected h3 influence of consumer attitudes towards environmentally friendly policies 4,504 0.000 received h4 effects of renewable energy towards environmentally friendly policies 2,402 0.002 received h5 influence of consumer attitudes on the intention to comply with environmentally friendly policies with environmentally friendly policy variables as moderating variables 4,732 0.001 received h6 effects of renewable energy on the intention to comply with environmentally friendly policies with environmentally friendly policy variables as moderating variables 2.045 0.000 received source: data processing results with pls 3.0, 2022 sinaga and sitorus: the role of consumer attitude and renewable energy towards environmental friendly policies in the intention to comply with the paid plastic environmental friendly policy international journal of energy economics and policy | vol 13 • issue 1 • 202320 the paid plastic environmentally friendly policy in north sumatra province with the environmental friendly policy variable as the moderator variable. through the results of the research that has been stated above, the adults of north sumatra will have the intention to obey and obey all environmentally friendly policies that are carried out, such as creating renewable energy, these policies are very useful so that the people of north sumatra are protected from the dangers of environmental damage and disasters. nature that will occur if they still use fossil fuels that can pollute the land, sea and air. references agyeman, c.m., badugu, d. (2017), predicting consumers purchasing intentions of a product ; a critical analysis of willingness-to-pay as the antecedent. international journal of research in economics and social sciences (ijress), 7(2), 71-84. ahmad, f., ahmad, s., zaindin, m. (2021), sustainable production and waste management policies for covid-19 medical equipment under uncertainty: a case study analysis. computers and industrial engineering, 157, 107381. al-harahsheh, m., al-nu’airat, j., al-otoom, a., al-hammouri, i., aljabali, h., al-zoubi, m., al’asal, s. (2019), treatments of electric arc furnace dust and halogenated plastic wastes: a review. journal of environmental chemical engineering, 7(1), 102856. andaç, t., güzel, a. (2017), attitudes of families with children towards eco-friendly designed furniture: kayseri sample. bioresources, 12(3), 5942-5952. arafah, w., nugroho, l., takaya, r., soekapdjo, s. (2018), marketing strategy for renewable energy development in indonesia context today. international journal of energy economics and policy, 8(5), 181-186. atinkut, h.b., yan, t., arega, y., raza, m.h. (2020), farmers’ willingness-to-pay for eco-friendly agricultural waste management in ethiopia: a contingent valuation. journal of cleaner production, 261, 121211. bugge, m.m., fevolden, a.m., klitkou, a. (2019), governance for system optimization and system change: the case of urban waste. research policy, 48(4), 1076-1090. ćwiąkała-małys, a., mościbrodzka, m. (2019), an analysis of field preferences of an educational system. wroclaw review of law administration and economics, 9(1), 26-45. destek, m.a., aslan, a. (2017), renewable and non-renewable energy consumption and economic growth in emerging economies: evidence from bootstrap panel causality. renewable energy, 111, 757-763. destek, m.a., sinha, a. (2020), renewable, non-renewable energy consumption, economic growth, trade openness and ecological footprint: evidence from organisation for economic co-operation and development countries. journal of cleaner production, 242, 118537. ekasari, a., zaini, s.m. (2020), moral norm and theory of planned behavior: the intention to use eco-friendly reusable bag. indonesian journal of sustainability accounting and management, 4(1), 56. hanif, i., raza, s.m., gago-de-santos, p., abbas, q. (2019), fossil fuels, foreign direct investment, and economic growth have triggered co2 emissions in emerging asian economies: some empirical evidence. energy, 171, 493-501. he, l., zhang, l., zhong, z., wang, d., wang, f. (2019), green credit, renewable energy investment and green economy development: empirical analysis based on 150 listed companies of china. journal of cleaner production, 208, 363-372. hwang, j., choi, j.k. (2018), an investigation of passengers’ psychological benefits from green brands in an environmentally friendly airline context: the moderating role of gender. sustainability, 10(1), 10010080. jaelani, a., firdaus, s., jumena, j. (2017), renewable energy policy in indonesia: the qur’anic scientific signals in islamic economics perspective. international journal of energy economics and policy, 7(4), 193-204. kasayanond, a., umam, r., jermsittiparsert, k. (2019), environmental sustainability and its growth in malaysia by elaborating the green economy and environmental efficiency. international journal of energy economics and policy, 9(5), 465-473. kaya, m. (2018), current weee recycling solutions. in: waste electrical and electronic equipment recycling: aqueous recovery methods. netherlands: elsevier ltd. khan, s.a.r., sharif, a., golpîra, h., kumar, a. (2019), a green ideology in asian emerging economies: from environmental policy and sustainable development. sustainable development, 27(6), 1063-1075. khansa, a.d.t., widiastuti, t. (2022), kausalitas pertumbuhan ekonomi, energi terbarukan dan degradasi lingkungan pada negara organisasi kerjasama islam. jurnal ekonomi syariah teori dan terapan, 9(1), 118-130. kim, t., yun, s. (2019), how will changes toward pro-environmental behavior play in customers’ perceived value of environmental concerns at coffee shops? sustainability (switzerland), 11(14), 11143816. kock, n. (2018), minimum sample size estimation in pls-sem: an application in tourism and hospitality research. applying partial least squares in tourism and hospitality research, 2018, 1-16. kurniawan, d., wahyuningsih, t. (2018), analysis of student difficulties in statistics courses. international journal of trends in mathematics education research, 1(2), 53-55. lee, j., bhatt, s., suri, r. (2018), when consumers penalize not so green products. psychology and marketing, 35(1), 36-46. mohd, j., kadir, a., nurul, n., hassan, n.m., noor, n., aziz, a. (2018), investigating students’ attitude and intention to use biodegradable drinking straw in emerging country. international journal of science and research, 9, 418-425. nadia, e.n., beatrice, c.d., atour, t. (2021), luxury hotels’ eco-friendly activities & customers’ preferences and willingness to pay for green hotels. journal of advanced management science, 8, 7-14. pişirir, e., uçar, e., chouseinoglou, o., sevgi, c. (2020), structural equation modeling in cloud computing studies: a systematic literature review. kybernetes, 49(3), 982-1019. popovic, i., bossink, b.a.g., van der sijde, p.c. (2019), factors influencing consumers’ decision to purchase food in environmentally friendly packaging: what do we know and where do we go from here? sustainability, 11(24), 1-22. prakash, g., choudhary, s., kumar, a., garza-reyes, j.a., khan, s.a.r., panda, t.k. (2019), do altruistic and egoistic values influence consumers’ attitudes and purchase intentions towards eco-friendly packaged products? an empirical investigation. journal of retailing and consumer services, 50, 163-169. spranz, r., schlüter, a., vollan, b. (2018), morals, money or the master: the adoption of eco-friendly reusable bags. marine policy, 96, 270-277. tomşa, m.m., romonţi-maniu, a.i., scridon, m.a. (2021), is sustainable consumption translated into ethical consumer behavior? sustainability, 13(6), 13063466. urbinati, a., chiaroni, d., toletti, g. (2019), managing the introduction of circular products: evidence from the beverage industry. sustainability, 11(13), 3650. usakli, a., kucukergin, k.g. (2018), using partial least squares structural equation modeling in hospitality and tourism: do researchers sinaga and sitorus: the role of consumer attitude and renewable energy towards environmental friendly policies in the intention to comply with the paid plastic environmental friendly policy international journal of energy economics and policy | vol 13 • issue 1 • 2023 21 follow practical guidelines? international journal of contemporary hospitality management, 30(11), 3462-3512. van riel, a.c.r., andreassen, t.w., lervik-olsen, l., zhang, l., mithas, s., heinonen, k. (2021), a customer-centric five actor model for sustainability and service innovation. journal of business research, 136, 389-401. white, k., hardisty, d.j., habib, r. (2019), the eluvise green consumer. harvard business review, 2019, 125-133. yacob, p., wong, l.s., khor, s.c. (2019), an empirical investigation of green initiatives and environmental sustainability for manufacturing smes. journal of manufacturing technology management, 30(1), 2-25. zutshi, a., creed, a., holmes, m., brain, j. (2016), reflections of environmental management implementation in furniture. international journal of retail and distribution management, 44(8), 840-859. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(1), 22-30. international journal of energy economics and policy | vol 13 • issue 1 • 202322 the effect of energy consumption and renewable energy on economic growth in indonesia sodik dwi purnomo1*, nur wani2, suharno2, arintoko2, herman sambodo2, lilis siti badriah2 1faculty of economics and business, wijayakusuma university purwokerto, indonesia, 2faculty of economics and business, jenderal soedirman university, indonesia. *email: sodikdwipurnomo@yahoo.com received: 04 september 2022 accepted: 24 december 2022 doi: https://doi.org/10.32479/ijeep.13684 abstract the economic growth in indonesia showed a stable trend while the growth in energy consumption showed a declining trend. however, previous studies had revealed the existence of positive and significant relationship between energy consumption and economic growth. this study aims to analyse the effect of oil, gas, and biomass fuel consumption, road infrastructure, life expectancy, and average length of education on economic growth in indonesia during the year of 1990-2019. this study used quantitative approach with linear regression as data analysis method. the data used are time series data from the period of 1990-2019. the result of this study showed that oil, gas, and biomass fuel consumption, as well as average length of education have a positive and significant effect, while road infrastructure and life expectancy have no effect on economic growth in indonesia for the year of 1990-2019. this study recommends: (1) energy reserves should be improved by increasing the number of energy sources and developing more infrastructure in order to support and boost the supply of energy, (2) quality of educations should be upgraded by giving out scholarships as well as improving the educators and physical infrastructure. keywords: economic growth, renewable energy, infrastructure, human capital jel classifications: o13, o15, o18, o47, q42, q43 1. introduction economic development, in addition to increasing the national income, is also intended to increase productivity. furthermore, economic development also aims to reach a high economic growth, maintain economic stability, and a fair income distribution. a high economic growth would be able to improve the public welfare since it could mean an increase in work force (haryanto, 2013). sukirno (2011) stated that economic growth is one of the goals that needs to be achieved by a country. this is because economic growth is a quantitative measure that reflects the yearly economic developments of a country in comparison to the previous year (nugroho, 2014). according to united nations development programs, by the end of 1999s, human development is indicated by economic growth. economic growth is closely related to the increase in goods and services produced within the society, which means that the more goods and services produced, the better the social welfare within that society, and hence the better the quality of their human resources. this could then be one of the indicators for economic growth, as could be seen from the amount of gross domestic product (todaro, 2000). according to mankiw (2007), economic growth reflects a country’s national output that determines the rate of their living standard. in practice, a high economic growth could be one of the main goals for national development in developing countries. economic growth could be seen as closely related to the increase in production of goods and services in society. a higher production of goods and services would be able to improve the social welfare. this journal is licensed under a creative commons attribution 4.0 international license purnomo, et al.: the effect of energy consumption and renewable energy on economic growth in indonesia international journal of energy economics and policy | vol 13 • issue 1 • 2023 23 figure 1 shows the economic growth in indonesia for the year 2010-2019. it could be seen from the chart that the economic growth in indonesia for the past 10 years indicates a stable trend in the range of 5%. taking the average from that time period, the economic growth in indonesia is around 5.48%. however, looking from the point of view of the growth in energy consumption in indonesia which includes oil, gas, electricity, and biomass fuels, the trend shows a significant decline. in the past 10 years, the average growth of energy consumption in indonesia is around 0.9% (oil), 10.50% (gas), 6.31% (electricity), and −3.86% (biomass), as shown in figure 2. referring to figures 1 and 2, it could be seen that economic growth has a stable trend in the range of 5%, while energy consumption growth showed a declining trend. however, previous empirical study by lolos (2002), mahadevan (2007), pradhan (2010), apergis and payne (2010), rezki (2011), adhikari and chen (2013), nnaji et al., (2013), susanto (2013) ishida (2013), ouedraogo (2013), purbaningrum (2014), iyke (2014), fariz (2015), nazer and handra (2016), zuldarepa (2017), akandy (2017), fauzi (2017), ula and affandi (2019), and setiawan et al. (2019) showed that energy consumption has a positive effect on economic growth. the effort to improve economic growth within all sectors, such as: production, distribution of products and services, and consumption, requires some form of energy resources which could be in the form of oil, gas, electricity, and biomass fuel. stern (2003) explained that the consumption of energy is a mean to propel economic industrialisation and a mean to accumulate complementary or substitutionary capital for development in order to produce economic outputs. in this study, energy would be differentiated into 4 types, namely: oil, gas, electricity, and biomass fuel. the distinction between those variables is based on, firstly, the difference in unit, secondly, the difference in usage where oil is mostly used in transportation and industrial sector and gas in household sector. the excessive use of fossil energy such as oil, gas, and coal could have a negative effect towards the environment (international panel on climate change, 2007). to handle such problem, the government in south east asian region should find an alternative source of energy to replace the environmentally damaging energy sources. such alternative energy sources could be in the form of solar, wind, water, biomass, or other type of fuel that is more environmentally friendly. biomass energy is a form of renewable energy that still has not been explored further in indonesia. previous empirical studies done by ula and affandi (2019), apergis and payne (2010), and soytas and sari (2006) showed a positive correlation between the consumption of renewable energy and economic growth. the study done by tugcu et al. (2012) looked into the effect of renewable and non-renewable energy on economic growth in the g7 countries. the result of their study showed a positive correlation between renewable energy consumption and economic growth. frondel et al. (2010) focused their study on the implication of the use of renewable energy which is to create more employment and effective market operation in germany. furthermore, inglesi-lotz (2016) concluded that that there is a great advantage from the government policy in promoting the use of renewable energy by building the market for it while keeping the good environmental condition. therefore, more analysis is needed on the effect of energy consumption and renewable energy on economic growth. with the increase in the number of industries in every year, there is also an increase in demand for energy. energy is also considered to be one of the most critical resources. it is highly needed in carrying out economical activities in indonesia, both in consumption and production activities in various economic sectors. as a natural resource, energy needs to be utilized as efficiently as possible for source: badan pusat statistik, 2019 figure 2: energy consumption growth in 2010-2019 (percentage) source: badan pusat statistik figure 1: economic growth in indonesia for the year 2010-2019 purnomo, et al.: the effect of energy consumption and renewable energy on economic growth in indonesia international journal of energy economics and policy | vol 13 • issue 1 • 202324 the sake of the public welfare and needs to be managed according to the principles of sustainable development (elinur et al., 2010). in addition to analysing the effect of energy consumption on economic growth in indonesia, this study also adds several control variables such as average length of education, life expectancy, and road infrastructure. according to kuncoro (2010), physical economic capital could become more productive when a country has a sufficient human capital. agents of developments could be more productive if they have the suitable knowledge, physical health, and skills in order to boost economic growth. it has been widely acknowledged that human capital is one of the most important factors in economic growth (brata, 2002). this is supported by several studies. uppun (2011) showed that human development in terms of the quality of human capital could affect the economic growth. the availability of good quality human resources is an important requirement in the growing suistainable economic development (sri, 2010). todaro (2000) stated that improvement in human quality could be achieved through several policies, which means that educational development could shape the direction of economic development in the future. the development in health sector is also acknowledged to instill a culture of healthy lifestyle as well as increasing the scope and quality of healthcare services. for lower income residents, the improvement in human quality could be done by teaching practical skills, suppressing the rate of population growth through the implementation of family planning movement, balancing the spread of population density, and improving the economic growth. the public welfare is directly proportional to the public need for a good quality education. the higher the education level of a person, the more productive they are, and hence improving both individual and national income. improving individual income would also improve the consumption ability and therefore improving the economic growth. life expectancy could be an indicator for the success of development in healthcare sector. an improvement in life expectancy could reflect the public socio-economic condition, health, and environment. otherwise, a decline in socio-economic condition of one period in a society could result in the decline of life expectancy (badan pusat statistik [bps], 2018). health and wellbeing could be seen as one of the most basic need of every person and without them the productivity of a country could be disturbed. the development of infrastructure could boost economical welfare and economic growth by increasing the efficiency of economic activities. restoration of infrastructures could contribute in improving productivity and is hoped to help supporting long term economic growth. infrastructures has a crucial role in improving economic growth since a higher economic growth could be seen in places with sufficient availability of infrastructure. any unavailability of infrastructure is one of the obstacles in achieving a rapid economic growth. maqin (2011) stated that infrastructure has a statistically significant and strong impact on economic growth. based on the reasoning above, the effect of energy consumption, infrastructure development, and human development on economic growth should be proved in the form of research. it is hoped that a study that utilises time-series data analysis would be able to find the effect of the four variables on the rate of economic growth in indonesia. 2. research method this study is a type of quantitative study because the data used is in the form of numbers (supranto, 2000: 65). this study is an empirical study to analyse the effect of energy consumption, renewable energy, economic infrastructure, and human capital on economic growth in indonesia. the data used in this study is a secondary data from the period of 2000-2019 in indonesia. the data was collected from relevant research bodies such as bps, ministry of state-owned corporations, and other relevant bodies. table 1 shows the operational definition used in this study. before conducting the multiple linear regression on eviews application to determine the magnitude of effect of independent variables on the dependent variables, a stationarity test and cointegration test need to be run first. stationarity test is aimed to see whether the mean data variance is constant over time and the variance between two or more time series data depends only on the lag between the two or more time periods (gujarati and porter, 2011). classical assumption tests on the regression model used were done in order to find out whether the regression model is a suitable model or not. the classical assumption tests used in this study are normality test, multicollinearity test, heteroscedasticity test, and autocorrelation test (gujarati and porter, 2011). the analysis of the effect of energy consumption, renewable energy, economic infrastructure, and human capital on economic growth in indonesia by using the multiple linear regression method was done with the help of eviews application. the equation for the multiple linear regression used in this study is as follows: egi = β0 + β1ofci + β2gct + β3eci + β4bct + β5eii-1 + β6lei + β7alet + e note: eg = economic growth β0 = constant β1,2,3,4,5,6,7 = regression constant ofc = oil fuel consumption gc = gas consumption ec = electricity consumption bc = biomass consumption ei = economic infrastructure le = life expectancy ale = average length of education e = standard error i = time series purnomo, et al.: the effect of energy consumption and renewable energy on economic growth in indonesia international journal of energy economics and policy | vol 13 • issue 1 • 2023 25 3. results and discussion the data analysis done to find out the effect of energy consumption, renewable energy, economic infrastructure, and human capital on economic growth in indonesia during the period of 1990-2019 using the multiple linear regression method with the help of eviews application was initiated by conducting the stationarity test. unit root stationarity test is the first test that needs to be done before conducting the regression analysis of the data. the aim of this stationarity test is to see whether the mean data variance is constant over time and the variance between two or more time series data depends only on the lag between the two or more time periods. the result of the stationarity test was summarised into the table below. table 2 shows that all variables give a probability value smaller the level of significant (α = 5%). this means that the data on the model could be concluded as stationary and therefore the analysis using ordinary least squares (ols) could be conducted. the normality test is done to find out whether or not the residual follows a normal distribution (gujarati and porter, 2011). residuals are said to be normal if the probability of normality produced are greater than or equal to the level of significant (α = 5%). the analysis result showed the value of probability of 0.4517 which is greater than the level of significant (α = 5%). therefore, the residual of the model could be said to be normally distributed, hence the assumption of normality is achieved. heteroscedasticity test is used to find out whether or not the residual has a homogeneous variety (gujarati and porter, 2011). the heteroscedasticity test used in this study is the glejser test. the criteria for this test stated that if the probability found from glejser test is greater than or equal to the level of significant (α = 5%), therefore the residual could be concluded to have a homogeneous variety. the analysis result showed that the probability value of obs*r-squared is 0.0839 which is greater than the level of significant (α = 5% atau 0.05). this means that the residual could be said to have a homogenous variety. multicollinearity test is used to find out whether or not there is a correlation between the independent variables. the linear regression analysis does not allow for any correlation among the independent variables. the multicollinearity test was done by looking at the value of vif for every independent variable. the criteria for this test stated that if the value of vif is <10 then that means there is no symptom of multicollinearity (suliyanto, 2011:76). the summary for multicollinearity test for this study could be seen in the table below. table 3 shows that all independent variables used in this study has a vif value of <10. this means that the model used in this study has no symptom of multicollinearity. the autocorrelation test is used to find out whether or not there is a correlation between the residual error in the period t-1 (gujarati and porter, 2011). based on the output of autocorrelation test, the value of durbin-watson (dw) was obtained to be 2.157921. this value is then compared to the db table for n = 29 and number of variable (k) = 7, and the value found are du = 2,0520 and dl = 0,9004. this showed that there is no autocorrelation in this model. table 4 showed a summary of the output for the multiple linear regression using the ols model. this model has been acknowledged as the best linear unbiased estimator (blue) which means it has gone through the classic assumption test such as normality, multicollinearity, heteroscedasticity, and autocorrelation test. 3.1. the effect of oil fuel consumption on economic growth the oil fuel consumption has a positive and significant effect on economic growth in indonesia for the period of 1990-2019. it is consistent with the result of the study done by bloch et al. (2015) and adjave et al. (2016) which stated that there is a positive correlation between oil fuel energy and economic growth. the higher the consumption of oil fuel in a country, the higher their economic growth would be. this means that the fulfilment of table 1: definitions of operational research variables s. no. variable definition unit 1. economic growth gross domestic regional product in indonesia percent 2. oil fuel consumption the amount of energy consumed by the population both in industrial and non-industrial sector kiloliter 3. gas consumption the amount of energy consumed by the population both in industrial and non-industrial sector tons 4. electricity consumption the amount of energy consumed by the population both in industrial and non-industrial sector megawatt 5. biomass consumption the amount of energy produced to be consumed by all sectors ton 6. economic infrastructure the length of asphalt road built by the government kilometer 7. life expectancy average life expectancy of the population of indonesia years 8. average length of education average length of education of the population of indonesia years table 2: summary of stationarity test s. no. variable stationary level level significance note 1. economic growth (y) 0.0065 stationary 2. oil fuel consumption (x1) 0.0190 stationary 3. gas consumption (x2) 0.0001 stationary 4. electricity consumption (x3) 0.0033 stationary 5. biomass consumption (x4) 0.0208 stationary 6. economic infrastructure (x5) 0.0192 stationary 7. life expectancy (x6) 0.0489 stationary 8. average length of education (x7) 0.0441 stationary source: data processing result, 2020 purnomo, et al.: the effect of energy consumption and renewable energy on economic growth in indonesia international journal of energy economics and policy | vol 13 • issue 1 • 202326 supply of oil fuel energy would contribute in the continuity of economic wheel. this is because oil fuel is the most used energy source by the household sector which still use kerosene of up to 484,392 kilo liter in 2019, the commercial sector which use kerosene, petroleum, premium, and diesel fuel of up to 370,865 kilo liter, and the transportation sector which use premium, petroleum, diesel, and avtur of up to 67,964,176 kilo liter, while the other sectors use up to 1,835,518 kilo liter. the same goes to the research done by razzaqi et al. (2012), which studied the relationship between energy and economic growth in indonesia, turkey, malaysia, iran, egypt, and bangladesh, whose result showed that there is a long term and short-term relationship in all countries except in indonesia. another study was done by fariz (2015) in indonesia as one of the energy exporter countries and the result showed that the economic growth is affected by oil fuel energy consumption. 3.2. the effect of gas consumption of economic growth the consumption of gas has a positive and significant effect on economic growth in indonesia for the period of 1990-2019. this is consistent with the study done by rezki (2011) and kurnia (2019) which stated that gas consumption has a great contribution on economic growth, where gas consumption has a positive and significant effect on economic growth. it is also consistent with the study done by ozturk and al mulali (2015) which found that the gas consumption affects the economic growth positively and in long term. this is because the majority of the sectors that produce a certain product or output needs gas as their fuel. the consumption of gas then become an important factor since it is the second main energy source after oil fuel in various sector because the supply of gas is still abundant in almost every country. according to erdo et al. (2019), the thing that needs to be looked into the most is how to increase investment in gas energy projects to produce more supply of energy. gas is one of the energy solutions that is environmentally friendly and could help reduce pollution. the use of gas fuel has spread across various sectors such as used as fuel in small industries, as fuel for motor vehicles, and as fuel for household, hotels, and restaurants. 3.3. the effect of electricity consumption on economic growth electricity consumption has a positive and significant effect on economic growth in indonesia for the period of 1990-2019. this result is consistent with the study done by shandra (2012), silvia et al. (2013), and thaker et al. (2019) which stated that electrical energy consumption has a positive effect on economic growth. in order to maintain the supply of energy, there is a need for other sources of energy to be developed which means a large capital is needed as well as a collaboration in developing a sustainable energy supply. the president of republic of indonesia in 2017 has also instructed all ministry and governmental bodies to support the development of electric cars. the use of electric vehicles is increasing every day, both for two-wheeled and four-wheeled vehicles. in fact, almost every country in europe, america, australia, and china has introduced the use electric vehicles. various vehicle rental companies around the globe has also started to use electric vehicles, which means that the world has agreed to support the development of clean energy as transportation mode. the use of clean energy should be implemented sooner and with a set of rules and regulations. aside of transportation vehicles, in indonesia, there is an ongoing campaign of conversion from gas energy to electrical energy as conveyed by pt pln (persero) which target a conversion of one million gas fuelled stove into electrically inducted stove. the ministry of energy and mineral resources has also encouraged the people to make the transition from gas stove to electric stove to achieve energy efficiency of 17% by 2025. for now, in indonesia, in order to improve the supply of electricity, the ministry of energy and mineral resources has collaborated with several countries such as denmark to analyse the best scenario for indonesia in terms of the most affordable electrical system. the use of electricity is still dominated by the household sector, which mostly is only used for daily needs and not for productivity. therefore, it can be defined that there is only a oneway relationship between electricity consumption and economic growth. table 3: summary of multicollinearity test s. no. independent variable vif value 1. oil fuel consumption (x1) 2.6183 2. gas consumption (x2) 1.1996 3. electricity consumption (x3) 1.5303 4. biomass consumption (x4) 1.4302 5. economic infrastructure (x5) 1.4204 6. life expectancy (x6) 1.9051 7. average length of education (x7) 2.4444 table 4: summary of regression result s. no. independent variable coefficient thitung ttable prob 1. oil fuel consumption (x1) 0.1324 3.0520 2.0738 0.0061*** 2. gas consumption (x2) 0.3804 2.3746 2.0738 0.0272** 3. electricity consumption (x3) 0.0139 2.0869 2.0738 0.0493** 4. biomass consumption (x4) 0.7605 3.5553 2.0738 0.0019*** 5. economic infrastructure (x5) −0.0002 −0.0309 2.0738 0.9757 6. life expectancy (x6) 0.3545 1.8634 2.0738 0.0764 7. average length of education (x7) 1.2765 2.9451 2.0738 0.0077*** r-squared =0.7852 fhitung =10.9675 ftable =2.3970 source: data processing result, 2020. *significant at 10%, **significant at 5%, ***significant at 1% purnomo, et al.: the effect of energy consumption and renewable energy on economic growth in indonesia international journal of energy economics and policy | vol 13 • issue 1 • 2023 27 3.4. the effect of biomass consumption on economic growth consumption of biomass energy has a positive and significant effect on economic growth in indonesia for the period of 19902019. this result is consistent with the studies done by ula and affandi (2019), akinlo (2008), bhattacharya et al. (2016), huang et al. (2008), and streimikiene (2016). the results of their studies show that the consumption of renewable energy contributes positively to economic growth, because there are several sectors that regularly use biomass energy as fuel to produce goods or their output. therefore, it could be said that the higher the use of biomass energy in producing an item, the higher the economic growth in indonesia. biomass energy in indonesia is only used in the industrial sector and the household sector. in 2019, the industrial sector used 42,862 thousand tons, while the household sector used 7,490 thousand tons of biomass energy. this could then be said to be the reason that biomass consumption has a positive effect on economic growth. although the use of biomass energy has been going on for hundreds of years, ever since the humans switched to oil and natural gas, the use of biomass energy has begun to shift. however, in the last few years, the development of biomass energy has been kickstarted, such as the development of biomass power plants in various regions in indonesia, as stated in the minister of energy and mineral resources regulation number 7, year 2014 concerning the purchase of electricity from biomass and biogas power plants by pt. pln (persero). some of the drawbacks of this energy are in the large costs of processing tools. also, the encouragement from the government for the potential of this energy has also been minimal. the processing of biomass energy is still considered to be minimal because it requires considerable research, so it is necessary to develop and increase the investment in the field of renewable energy so that its use could be maximized and hence give a positive impact on economic growth as well as a sustainable environment. in indonesia, in the effort to increase the consumption of renewable energy, the ministry of energy and mineral resources (2019) has collaborated with several countries such as japan develop a sustainable renewable energy in indonesia. this is fully supported by the government which therefore encourages the millennial generation to create renewable energy businesses and innovations, so that the increase in renewable energy could one day replace fossil energy consumption without reducing the level of a country’s economy. 3.5. the effect of economic infrastructure on economic growth economic infrastructure has no effect on economic growth in indonesia for the period of 1990-2019. this result is consistent with the study done by sumadiasa et al. (2016) which stated that road length infrastructure has no effect on economic growth. it is also supported by the study done by iriyena et al. (2019) which concluded that road length has no effect on economic growth. the economic infrastructure such as length of road has no direct effect on economic growth because it takes time to build asphalt roads and hence it could be the reason that it indirectly has no effect. however, road infrastructure should still be developed and improved to increase connectivity by increasing the access to potential areas such as industrial areas/special economic zones, agriculture, plantations, tourism in strategic areas, national and regional tourism, ports, airports, opening isolated, remote, underdeveloped areas, borders, as well as outermost and small island area. for similar reasons, the government has also been encouraging more and more programs in developing infrastructure. the presence of infrastructure can open new access or make it easier to reach new areas which can increase new economic activities. infrastructure development in indonesia seeks to connect and provide access between indonesian regions in order to create a logistics network and link production centres, such as from agricultural and fishermen production to small industries. road infrastructure development in indonesia from 1990 to 2019 was constrained by the monetary crisis in 1997-1998 which led to the delay in construction of 19 toll roads of 762 km in 19951997. road construction in indonesia at that time was stagnating, as proven by the building of only 13.3 km of road in 1997-2001. from the year of 2001 to 2004, 4 new toll roads were built with a total length of 41.80 km. in 2005 a new toll road regulatory agency was formed to act as the indonesian toll road regulator, accompanied by the continuation of 19 toll road construction projects that were delayed in 1997 (ministry of pupr, 2019). many of the road infrastructure development in the villages outside java island during 1990-2000 was still stagnant. the community still uses footpaths such as in certain vilaages in kalimantan, sulawesi, nusa tenggara, maluku and papua. the construction of asphalt roads to these remote areas had begun in 2000 and is still on going until now in order to connect indonesian regions and establish a logistics network. the result of this study, however, is in contrast to the study done by warsilan and noor (2015) which stated that infrastructure plays a positive role in economic growth. likewise, the study done by putri (2014) shows that domestic investment, capital expenditure, labor and infrastructure has a significant and positive effect on economic growth in indonesia. 3.6. the effect of life expectancy on economic growth life expectancy has no effect on economic growth in indonesia for the period of 1990-2019. this is consistent with the study done by handayani et al. (2016) and nurwijayati (2017) which stated that life expectancy has no effect on economic growth. this means that a long life-expectancy without accompanied by any useful skills or expertise would become a burden for a country instead. additionally, there is a lack of job opportunities for the elderly who are still able and willing to work. life expectancy is the estimated average number of years that a person has from birth to death. this indicator is used to determine the level of public health because it could reflect the length and quality of life of a person. the length of life of a person without the support of good health would result in them being a burden instead. according to the central statistics agency (2019), the average growth in life expectancy from 1990 to 2019 was 0.5%/year. this purnomo, et al.: the effect of energy consumption and renewable energy on economic growth in indonesia international journal of energy economics and policy | vol 13 • issue 1 • 202328 shows that the life expectancy of new-born babies is improving because of the advancement in public health. however, the growth in the number of elderly people is also getting higher every year. based on the data from the ministry of health in 2019, the growth of the elderly population from 1990 to 2019 was 9.70%. the increasing number of elderly people has become a concern for the government considering that the elderly is part of the population that is unproductive and could be a burden for the family and government, especially those who have certain health or mental disorders due to chronic diseases, accidents, crime and other causes. although life expectancy in indonesia has increased, on the other hand, the death rate in indonesia caused by noncontagious diseases is also high. between 1990 and 2016, 82% of the total deaths were caused by non-contagious diseases. this also has an impact on economic growth, where life expectancy cannot affect economic growth if the population is dominated by elderly people who have low health quality and if the country has a high mortality rate. the high life expectancy in indonesia has not been able to have a positive effect on economic growth. economic growth is determined by talents, abilities, quality, capacity and a set of skills, cultures, values, goals and motivation as well as the political structure of the institution (jighan, 2010; 67). according to putri (2014), in the current modern era, the slow and low-energy attitude is no longer appropriate because, economically, any slow action has high cost consequences. this leads to an argument that the community has a slow and low-energy attitude at work so that means that the productivity of the community is low. 3.7. the effect of average length of education on economic growth the average length of education has a positive and significant effect on economic growth in indonesia for the period of 19902019. this result is consistent with the study by hasanah (2016), nurwijayati (2017) and muda et al. (2019) which stated that the average length of education has a significant effect on economic growth. education, measured from the average length of education, is one of the important indicators that shows the quality of the population of a country. generally, in developed countries, their population already has a high awareness of the importance of education and mastery of science and technology. this could be seen from the very high rate of participation of education in developed countries. limited funding requires prioritization of various options in the field of education that are appropriate in the long run to drive economic growth. one of the motivations to develop the education level in an effort to build a country’s economy is that the higher the education, the better the people’s knowledge rationality in thinking. this could cause people to take more rational steps in decision makings. education could provide society with the technical knowledge necessary to lead and run modern enterprises and to develop a more modern small and micro businesses. the good and useful skills and knowledge obtained through education could become an incentive to innovate. the higher a person’s education level and the longer their experience in schools or courses, the higher the knowledge and skills that they have, and hence the higher their productivity. the average length of education has been increasing every year which indicates that the quality of human resources in indonesia is getting better and could compete well with other countries (hasiani et al., 2015). 4. conclusions the economic growth in indonesia showed a stable trend while the growth in energy consumption showed a declining trend. however, previous studies had revealed the existence of positive and significant relationship between energy consumption and economic growth. the result of this study showed that oil, gas, and biomass fuel consumption, as well as average length of education have a positive and significant effect, while road infrastructure and life expectancy have no effect on economic growth in indonesia for the year of 1990-2019. this study recommends: (1) energy reserves should be improved by increasing the number of energy sources and developing more infrastructure in order to support and boost the supply of energy, (2) the government should further develop integrated biomass processing industry in areas with high industrial waste, or in agricultural areas, and (3) the quality of educations should be upgraded by giving out scholarships as well as improving the educators and physical infrastructures. references adhikari, d., chen, y. (2013), energy consumption and economic growth: a panel cointegration analysis for developing countries. review of economics and finance, 3, 68-80. akandy, p.a. (2017), analisis pengaruh konsumsi energi non renewable resources terhadap pertumbuhan ekonomi di indonesia pada periode 1980-2014. jurnal ilmiah mahasiswa feb universitas brawijaya, 5(2), 1-15. akinlo, a.e. (2008), energy consumption and economic growth: evidence from 11 sub-sahara african countries. energy economics, 30(8), 2391-2400. apergis, n., payne, j.e. (2010), renewable energy consumption and economic growth: evidence from a panel of oecd countries. energy policy, 38(1), 656-660. adjaye, j. a., byrne, d., alvarez, m. (2016), economic growth, fossil fuel and non-fossil consumption: a pooled mean group analysis using proxies for capital. energy economics, 60, 345-356. bhattacharya, s.r., paramati, s,r., ozturk, i., bhattacharya, s. (2016), the effect of renewable energy consumption on economic growth: evidence from top 38 countries. applied energy, 162, 733-741. bloch, h., rafiq, s., salim, r. (2015), economic growth with coal, oil and renewable energy consumption in china: prospects for fuel substitution. economic modelling, 44, 104-115. brata, a.g. (2002), pembangunan manusia dan kinerja ekonomi regional di indonesia. jurnal ekonomi pembangunan, 7(2), 113-122. central statistics agency (2019), statistical yearbook of indonesia 2019. indonesia. elinur, e., priyarsono, d.s., tambunan, m., dan firdaus, m. (2010), perkembangan konsumsi dan penyediaan energi dalam perekonomian indonesia. indonesian journal of agricultural economics, 2(1), 97-119. erdo, s., gedikli, a., mustafa, k. (2019), a note on time-varying causality between natural gas consumption and economic growth in turkey. purnomo, et al.: the effect of energy consumption and renewable energy on economic growth in indonesia international journal of energy economics and policy | vol 13 • issue 1 • 2023 29 resources policy, 64, 101504. fariz, m. (2015), pengaruh konsumsi energi terhadap pertumbuhan ekonomi di indonesia. jurnal ilmiah mahasiswa feb universitas brawijaya, 3(2), 1-16. fauzi, r. (2017), pengaruh konsumsi energi, luas kawasan hutan dan pertumbuhan ekonomi terhadap emisi co2 di 6 (enam) negara anggota asean. pendekatan analisis data panel ecolab, 11(1), 1-5. frondel, m., ritter, n., schmidt, c.m., vance, c. (2010), economic impacts from the promotion of renewable energy technologies: the german experience. energy policy, 38(8), 4048-4056. gujarati, d.n., porter, d.c. (2011), basic econometrica. 5th ed. new york: mc graw hill. handayani, p.n.r., bendesa i.k.g., dan yuliarmi, n. (2016), pengaruh jumlah penduduk, angka harapan hidup, rata-rata lama sekolah, dan pdrb per kapita terhadap pertumbuhan ekonomi di provinsi bali. jurnal ekonomi dan bisnis universitas udayana, 5(10), 3449-3474. haryanto, t.p. (2013), pengaruh pengeluaran pemerintah terhadap pertumbuhan ekonomi kabupaten/kota di provinsi jawa tengah tahun 2007-2011. economics development analysis journal, 2(3), 148-159. hasanah, f. (2016), analisis pengaruh aglomerasi industri, angkatan kerja dan human capital investment terhadap pertumbuhan ekonomi kabupaten/kota di provinsi jawa tengah tahun 2012-2014. jurnal pendidikan dan ekonomi, 5(4), 283-291. hasiani, f., maulida, y., sari, l. (2015), analisis kualitas sumber daya manusia dan pengaruhnya terhadap pertumbuhan ekonomi di kabupaten pelalawan. jurnal online mahasiswa fekon, 2(2), 1-15. huang, b.n., hwang m.j., yang c.w. (2008), causal relationship between energy consumption and gdp growth revisited: a dynamic panel data approach. ecological economic, 67(1), 41-54. international panel on climate change. (2007), the physical science basis. contribution of working group i to the fourth assessment report of the intergovernmental panel on climate change. available from: http://web.archive .org/web/200702031644/http ://www.ipcc. ch/ spm2feb07.pdf. iriyena, p., naukoko, a.t., siwu h.f.d. (2019), analisis pengaruh infrastruktur jalan terhadap pertumbuhan ekonomi di kabupaten kaimana 2007-2017. jurnal berkala ilmiah efisiensi, 19(2), 49-59. ishida, h. (2013), causal relationship between fossil fuel consumption and economic growth in japan: a multivariate approach. international journal of energy economics and policy, 3(2): 127-136. iyke, b.n. (2014), electricity consumption, inflation, and economic growth in nigeria: a dynamic causality test. vol. 23. germany: munich personal repech archive. p15-28. jhingan, m. l. (2010), ekonomi pembangunan dan perencanaan. raja grafindo persada, jakarta; jakarta. kuncoro, m. (2010), dasar-dasar ekonomika pembangunan. upp stim ykpn: yogyakarta. kurnia, m.i., sasana, h., septiani, y. (2019), analysis of the causality of co2 emissions, consumption of fossil fuels, electricity consumption, and economic growth in indonesia in 1990-2019. afebi economic and finance review (aefr), 4(2), 113-120. lolos, s., papapetrou, e., hondroyiannis, g. (2002), energy consumption and economic growth: assessing the evidence from greece. energy economics, 24(4), 319-336. mahadevan, r., asafu-adjaye j. (2007), energy consumption, economic growth and prices: a reassessment using panel vecm for developed and developing countries. energy policy, 35(4), 2481-2490. mankiw, n.g., liza, f., nurmawan, j., hardini, w., barnadi, d., saat, s. (2007), makroekonomi edisi keenam. jakarta (id): penerbit erlangga. maqin, a. (2011), pengaruh kondisi infrastruktur terhadap pertumbuhan ekonomi di jawa barat, trikonomika, 10(1), 10-18. ministry of pupr. (2019), ministry of public works and public housing book 3 infrastructure development. jakarta: directorate of settlement environmental health development. ministry of energy and mineral resources. (2019), handbook of energi & economic statistik of indonesia 2019, jakarta. muda, r., koleangan, r., dan kalangi, j.b. (2019), pengaruh angka harapan hidup,tingkap pendidikan dan pengeluaran perkapita terhadap pertumbuhan ekonomi di sulawesi utara tahun 2003-2017. jurnal berkala ilmiah efisiensi, 19(1), 44-55 nazer, m., handra, h. (2016), urban household energy consumption analysis in indonesia: periode of 2008 and 2011. jurnal ekonomi dan pembangunan indonesia, 16(2), 141-153. nnaji, c.e., chukwu, j.o., nnaji, m. (2013), electricity supply, fossil fuel consumption, co2 emissions and economic growth: implications and policy options for sustainable development in nigeria. international journal of energy economics and policy, 3(3), 262-271. nugroho, b.s. (2014), pertumbuhan ekonomi dan ketimpangan pendapatan antar kecamatan. journal of economics and policy, 7(1), 46-59. nurwijayati, n. (2017), pengaruh indikator komposit pembangunan manusia terhadap pertumbuhan ekonomi kabupaten/kota provinsi diy. jurnal pendidikan dan ekonomi, 6(6), 520-529. ouedraogo, n.s. (2013), energy consumption and economic growth: evidence from the economic community of west african states (ecowas). energy economics, 36(13), 637-647. ozturk, i., al mulali, u. (2015), natural gas consumption and economic growth nexus: panel data analysis for gcc countries. renewable and sustainable energy reviews, 51, 998-1003. pradhan, r.p. (2010), transport infrastructure, energy consumption and economic growth triangle in india: cointegration and causality analysis. journal of sustainable development, 3(2), 167-173. purbaningrum, s.p. (2014), audit energy dan analisis peluang penghematan konsumsi energy listrik pada rumah tangga. media mesin, 15(1), 26-33. putri, i.p. (2014), pengaruh investasi, tenaga kerja, belanja modal, dan infrastruktur terhadap pertumbuhan ekonomi pulau jawa. journal of ekonomics and policy, 7(2), 100-202. razzaqi, s., bilquees, f., sherbaz, s. (2012), dynamic relationship between energy and economic growth. the pakistan development review, 50(4), 437-458. rezki, j.f. (2011), energy consumption and economic development in south east asia. jurnal ekonomi dan pembangunan indonesia. 12(1), 31-38. inglesi-lotz, r. (2016), the impact of renewable energy consumption to economic growth: a panel data application. energy economics, 53(1), 58-63. setiawan, a., david, p., michael, k.e. (2019), effect of fossil fuel consumption on indonesia gross domestic products and its reciprocal relationship between both of them. jurnal teknologi mineral dan batubara, 15(3), 213-223. shandra, y. (2012), konsumsi dan investasi serta pertumbuhan ekonomi sumtera barat. jurnal kajian ekonomi, 1(1), 113-139. silvia, e.d., wardi, y., aimon, h. (2013), analisis pertumbuhan ekonomi, investasi, dan inflasi di indonesia. jurnal kajian ekonomi, 1(2), 224-243. sri, w. s. (2010). pengaruh domestik bruto (pdb) dan indeks pembangunan manusia (ipm) terhadap angka kemiskinan di indonesia. jurnal ekonomi pembangunan, 8(2), 357-366. soytas, u., sari, r. (2006), energy consumption and income in g-7 countries. journal of policy modeling, 28(7), 739-750. stern, d. (2003), energy and economics growth. encyclopedia of energy elsavier, 1(1), 27-42. streimikiene, d. (2016), review of economic growth and energy purnomo, et al.: the effect of energy consumption and renewable energy on economic growth in indonesia international journal of energy economics and policy | vol 13 • issue 1 • 202330 consumption: a panel cointegrationanaly for eu countries. renewable and sustainable energy reviews, 59(2), 1545-1549. sukirno, s. (2011), introduction to macroeconomic theory. jakarta: pt. king grafindo persada. suliyanto, s. (2011). ekonometrika terapan teori dan aplikasi dengan spss. andi: yogyakarta. sumadiasa, i.k., tranawati, n.m., wirathi, i.g.a.p. (2016), analisis pengaruh pembangunan infrastruktur jalan, listrik dan pma terhadap pertumbuhan pdrb provinsi bali tahun 1993-2014. e-jurnal ekonomi pembangunan universitas udayana, 5(7), 925-947. supranto, s. (2000), statistik (teori dan aplikasi), edisi keenam, jakarta: erlangga. susanto, j., dan laksana, d.h. (2013), uji kausalitas antara konsumsi energi dan pertumbuhan ekonomi di asean. buletin ekonomi, 11(1), 1-86. thaker, m.a.m.t., thaker, h.m.t., amin, m.f., pitcay, a.a. (2019), electricity consumption and economic growth: a revisit study of their causality in malaysia. etikonomi, 18(1), 1-12. todaro, m.p. (2000), economic development. 7th ed. new york: addition wesley longman, inc. tugcu, c.t., ozturk, i., aslan, a. (2012), renewable and non-renewable energy consumption and economic growth relationship revisited: evidence from g7 countries. energy economics, 34(6), 1942-1950. ula, t., affandi, a. (2019), dampak konsumsi energi terbarukan terhadap pertumbuhan ekonomi: studi di asia tenggara. journal of economic science (jecs), 5(2), 64-72. uppun, p. (2013). pengaruh kualitas sumber daya manusia terhadap pertumbuhan ekonomi di kabupaten mamasa (doctoral dissertation, universitas hasanuddin). warsilan, w., noor, a. (2015), peranan infrastruktur terhadap pertumbuhan ekonomi dan implikasi pada kebijakan pembangunan di kota samarinda. mimbar, 31(2), 359-366. zuldarefa, f. (2017), analisis pengaruh konsumsi energi dan co2 terhadap pertumbuhan ekonomi indonesia tahun 1981-2014, jurnal ilmiah mahasiswa feb universitas brawijaya, 5(1):1-15. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020460 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 460-468. small hydropower development potential in chechen republic i. a. kerimov1,2*, m. ya. gaysumov1, s. v. badaev1, a. a. batukaev1 1grozny state oil technical university named after academician m.d. millionshchikov, russia, 2schmidt institute of physics of the earth of the russian academy of sciences, moscow, russian federation. *email: i.akerimov@yahoo.com received: 24 june 2020 accepted: 10 september 2020 doi: https://doi.org/10.32479/ijeep.10491 abstract the aim of this study is to examine the issues of energy development and hydroelectric potential utilization of the rivers in the chechen republic. one gives a brief description of the river network and performs the hydroelectric potential’s calculations of large and small rivers. one estimates the hydroelectric potential at about 4.86 billion kwh. the share content of hydroelectric resources constitutes 3682.7 kwh/1 km2 of the territory. we attribute special attention to the potential assessment of rivers within the mountainous part of the territory. the estimated gross potential of mountain rivers alone is 2.4 billion rubles kwh, and technical 0.55 billion kwh. one note that the development of small hydropower is an important factor of improvement in regard to the socio-economic conditions of the population’s life and territory’s energy security. keywords: hydropower, potential of small rivers, distributed power generation, ecology, sustainable development, hydroelectric power stations, chechen republic jel classifications: o13, p28, p48, q42, r11 1. introduction hydropower technologies are off-the-shelf technologies and are currently applicable on a significant scale. despite the fact that today the main role of hydropower within the global energy supply is to ensure centralized generation of electricity, one can master some technologies at the point of use, when hydroelectric power stations operate in isolation and supply autonomous systems with electricity, in many cases throughout the rural and remote areas. as long as the generating capacities and consuming facilities are geographically as close as possible, there is no need to transport energy and to build transport electric power systems. this can provide consumers and neighbors with their own energy in accordance with the reciprocation scheme, in contrast to traditional types of generation, whose energy one must deliver hundreds of kilometers away. the attractiveness of a particular energy supply option also depends on the broader economic, environmental and social aspects, as well as on the contribution that technology makes in order to provide the appropriate energy supply (for example, peak demand for electricity) or imposes additional costs on the energy system (for example, integration costs). in general, hydroelectric power is a recognized and highly advanced technology, but there are still possibilities for further improvement by operations optimization, mitigation or reduction of environmental impacts, adaptation to new social and environmental requirements, and implementation of more reasonable and cost-effective technological solutions (asarin, 2013; gaisumov and kerimov, 2018; russian federation, 2012, hydro minds-tool). if the energy conversion efficiency of large turbine units has already reached its maximum value, then new promising technologies have appeared in the field of small-scale power generation. these technologies include: variable speed rate technology, fish-friendly turbines, hydrokinetic turbines, and new technologies for using low (<15 m) or very low (<5 m) water pressure, previously unused for traditional technology applications. this journal is licensed under a creative commons attribution 4.0 international license kerimov, et al.: small hydropower development potential in chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020 461 2. characteristics of the fluvial network the territory of the chechen republic has characteristics with a relatively high availability of surface water resources, which are mainly concentrated in rivers, lakes and water storage basins. the distribution of surface water is very irregular throughout the territory. it is due to the nature of the terrain and the rainfall distribution, the sharp predominance of evaporation over rainfalls in steppe and semi-desert areas. not only the altitude, but also the direction of mountain ranges, the orientation of slopes, and the nature of landforms have a great influence on the land forms (gaisumov and kerimov, 2018, russian soviet federative socialist republic, 1987). the southern part of the republic the mountainous regions and the chechen sloping plain have a widely branched and dense network of rivers and streams. terek-sunzha elevation and zaterechnaya lowland, that locate to the north of the terek, have no discharge. the total number of rivers is 3198, the total length is 6508.8 km. the vast majority of rivers (more than 97%) are small currents of water <10 km long. the number of main rivers (more than 10 km long) is about 100 (renewable energy and climate change mitigation 2011, gaisumov and kerimov, 2018). the largest rivers by length are the rivers: terek (218 km), sunzha (205 km), argun (125 km), belka (83.2 km), dzhalka (82.5 km), martan (61 km), gehi (57 km), aksai (57 km), fortanga (34.7 km), assa (32.4 km). orographic, physical and climatic features influence on the formation and distribution of the hydrographic pattern. all the rivers of chechnya belong to the basin of river terek, with the exception of the rivers aksay, yaman-su and yaryk-su, which belong to the basin of river aktash. the rivers terek, argun, and assa , as rivers of glacial nutrition, have not only spring water rises associated with melting of snow within their basins, but also a high-water season in the second half of summer, during the melting of the glaciers in the caucasian mountain range (figure 1). increased autumn rains in the mountains also cause water rises. the lowest water level in mountain rivers is in winter. the seasonal distribution of annual mountain rivers flow has characteristics of approximately the following ratio: in summer (june-august) the run-off is around 55%, in spring and autumn – 35%, in winter (december-february) – 10%. this hydrological regime of rivers is favorable for irrigation, but it makes it difficult for hydroelectric power stations to operate evenly. with the exception of terek, assa and argun, all other rivers in the mountainous and foothill parts of the republic have nourishment of spring and rain waters. the most significant of them are – sunzha, fortanga, gekhi and martan they originate in the zone of the rocky ridge, and figure 1: map of hydrographic network in the chechen republic kerimov, et al.: small hydropower development potential in chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020462 shalazhi, valerik, goita, dzhalka, gums and others – from the springs of the pasture mountain range and the black mountains. long-term hydrological observations show that the rivers with spring and rain supply become very shallow by the summer, due to the absence of a second flood. smaller rivers of the sunzha river basin with nourishment of the ground water, have a more stable flow. these rivers do not react well to rainfalls in the mountains or melting of glaciers in the high mountain area. the main river of chechen republic is terek. the total length of river terek is 590 km, and the basin area is about 44 thousand km2, the length of chechen republic is 218 km. the riverbed in the territory under study is meandering, full of shoals and islands, that often change their size and shape due to washouts and aggradations. the place, where terek receives its largest feeder is river sunzha, and there its lower course of a river begins. away to the north-east, already outside the republic, it flows into the caspian sea (table 1). sunzha river is the last right feeder of river terek, its length from source to estuary is 265 km, its catchment area constitutes 12,200 km2. the source of river sunzha locates in the area of the black mountains within the western part of the forward branches of the lesysty mountain ridge. the springs, ground water and rainfalls feed sunzha and its feeders on the upper reaches. in the area from the town karabulak to the city grozny the several feeders flow into into the river sunzha, where the largest ones are: assa, fortanga, salaga, gekhi, martin, goyta. from grozny to the railway bridge that crosses river sunzha below the city gudermes, a number of feeders flow into it, the largest of which are rivers argun and belka with the feeders hums and hulhulau. argun river, the largest tributary of the sunzha river, forms from the confluence of two rivers – chanta-argun and sharo-argun, and is a right feeder of river sunzha. the chanta-argun river originates on the northern mountain slope of the main caucasus mountain range, at the altitude of about 3000 m. in the upper reaches of the river on both sides there are many glaciers’ feeders. the river sharo-argun originates in the glaciers of the tushet mountain range at the altitude of more than 3000 m. the regime of river argun ,as well as the rivers of its components (chanta-argun and sharo-argun), has all the features of a mountain river with mixed nutrition, with low horizons and expenditures in winter and with summer floods. it has more water than sunzhu. the length of river argun reaches 148 km, the total area of the basin is 3370 km2, and the average height of the basin is 1900 m. the mountain slope of the river is different: in the upper current: 0.080-0.100°; in the middle current: 0.015-0.020°; in the lower current: 0.003-0.006°. the congealation and ice conditions of the chechen rivers depend not only on winter temperatures, but also on the speed of their current flow. on the rivers of the highland zone (upper assa, chanty-argun, sharo-argun), despite the relatively low winter temperatures, there is no formation of solid ice, due to the high flow speed; only in some places there are formations of ice edge around the coast (landfast ice). the average long-term river flow on the territory of chechen republic: terek – 9.21 km3, sunzha 1.41 km3. river argun has a regulated stream flow near the village of duba-yurt and in accordance with the calculations, its average flow is 0.52 km3 (ivanov, 2015; federation, 2009). rivers of chechen republic have characteristics of high water turbidity, due to the presence of easily eroded rocks in the riverbeds. for example, the sediment runoff of river sunzha in grozny is 1.14 kg/m3, river braguna is 1.67 kg/m3, river argun in dubayurt is 1.36 kg/m3, and river michik in gudermes is 3.55 kg/m3. one can identify the amount of sediment loads, their granulometric composition and distribution by their water regime (table 2). 3. hydroelectric potential in study of the hydroelectric power of rivers, one distinguishes the following categories of hydroelectric potential: • gross theoretical hydropower potential, or potential hydropower resources; • technical hydroelectric potential, or technically usable hydroelectric resources , is that part of the gross theoretical hydroelectric potential of a river flow that can technically be under the use or is already in operation; • economic hydroelectric potential part of the technical hydroelectric potential, the use of which is cost-effective. the main hydro resources of chechen republic mainly concentrate within the large rivers: terek, sunzha, argun, assa and others. rivers of the deep rock canyons make it possible to build efficient table 1: characteristics of the fluvial network on the territory of chechen republic interval length, km number of rivers total length, km average length of rivers, km % for the total number of rivers up to 1 km 1893 936.39 0.49 59.19 1-2 668 942.06 1.41 20.89 2-3 255 617.60 2.42 7.97 3-4 108 373.27 3.46 3.38 4-5 68 303.21 4.46 2.13 5-6 30 163.04 5.43 0.94 6-7 34 220.88 6.50 1.06 7-8 22 164.58 7.48 0.69 8-9 10 86.01 8.60 0.31 9-10 10 93.02 9.30 0.31 10-25 77 1164.80 15.13 2.41 25-50 13 411.90 31.68 0.41 50-100 7 484.70 69.24 0.22 minimum 100 3 547.30 182.43 0.09 total 3198 6508.76 2.04 100 kerimov, et al.: small hydropower development potential in chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020 463 hydroelectric complexes. one determines the potential hydro resources of the territory in accordance with the data of average annual expenditures and potential hydro energy (asarin 2013; ivanov, 2015; polovinkin and fomichev, 2014; casila, 2019; zema et al., 2016). the average long-term runoff of rivers in chechen republic is 12.7 million m3. let’s examine the calculation of the theoretical hydroelectric potential for the i-th section of the river which locates between points a and b (figure 2). one determines the hydroelectric potential of the i-th section of the river pi (kw) by the ratio: p g q hi i i= ⋅ ⋅ ⋅ρ , (1) where g acceleration of gravity, m/s2; ρ water density, kg/m3 qi – the average value of the average annual water flow on the i-th section of the river, m3/s; hi – the height difference between the water level of water storage basin and the level of turbine’s location (the fall of the i-th section of the river), m. approximately, the last formula, where g and ρ are constants, we can represent as follows: p h q qi i= ⋅ ⋅ +9 81 21 2. ( ) / , (2) where q1 and q2 – the average annual water flow at point a and point b (figure 2), m3/s. if there is a longitudinal profile of the entire river and data on its flow, one can determine the potential capacity from the source to the mouth of the river (control station) by the following formula: p q hi i n i= ⋅ = ∑9 81 1 . (3) the size of the technical potential depends on the amount of losses, some of which are unavoidable and more or less constant, the other (main) part depends on the hydrological, topographic and other natural conditions that form the run-off. this part of the loss is not constant, and its value can vary widely. the limits of fluctuations in the size of permanent losses are small, and their average value may reflect the order of magnitude inherent in all hydroelectric power stations. their value consists of head losses in supply channels, in pressure pipelines, etc. (2-10%); from flow losses through distributors, gates of water-retaining constructions (1%); from mechanical losses within the conversion of hydraulic energy into electrical energy (11-13%). therefore, the upper limit on the use of gross hydroelectric potential cannot exceed 86%. one estimates the gross hydroelectric potential of chechen republic at about 4.86 billion kwh. the share content of hydroelectric resources constitutes 3682.7 kwh/1 km2 of the territory. the gross potential of separate mountain rivers is 2.4 billion rubles. kwh and technical – 0.55 billion. kwh. the economic hydroelectric potential depends on the natural economic conditions of the construction in small hydroelectric power stations, and therefore, estimated by the method proposed in the studies (asarin, 2013, ivanov, 2015) as 0.55 of the technical potential, for mountain rivers constituted 0.302 billion rubles. kw·h. the development of only 10% of the small rivers hydroelectric potential in the mid-mountain and high-mountain zones will allow to supply up to 70% of the electricity needs in chechen republic (table 3). one can use the rich energy resources of argun river basin in a more effective way. in 2007-2008 the ministry of industry and energy of the czech republic concluded an agreement on the development of argun hpp cascade and infrastructure facilities with the firm “rico group” (republic of slovenia). in accordance with the research data, we identified the several options for the usage of argun river’s hydroelectric potential. in accordance with the calculations results, we selected an option that includes the construction of 10 priority hpps with such energy indicators as: the total capacity of 681 mwatts, the annual output of the cascade up to 1.5 billion cubic meters. kwh/year (kerimov and debiev, 2010, kerimov et al., 2011). currently, we have built only the kokadoyskaya hpp with a table 2: the average monthly usage of water consumption in m3/s of major rivers in chechen republic (basins of terek, (1987), cadastre, s.w. (n.d.) rivers months annual run-offi ii iii iv v vi vii viii ix x xi xii terek stanitsa kargalinskaya 130 133 166 213 324 460 538 510 349 241 198 159 285 sunja town karabulak city grozny selo braguny 1.9 2.0 2.5 3.0 3.5 4.8 2.5 2.1 2.0 2.0 1.8 1.8 2.5 16.9 17.3 24.5 35.9 42.9 56.5 46.6 35.7 305 26.5 23.1 19.7 31.3 43.1 42.5 58.6 83.0 11.5 156 143 112 85.5 70.2 58.2 49.2 84.7 argun selo duba-yurt 16.2 15.2 18.7 30.4 55.3 85.4 91.0 71.8 50.4 36.3 25.4 19.3 43.0 figure 2: for calculation of the hydroelectric potential kerimov, et al.: small hydropower development potential in chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020464 capacity of 5 mw (originally there was a plan to build a hpp with a capacity of up to 30 mwatts with a production of up to 87 gw/year). 3.1. small hydropower in russian federation, small hydroelectric power includes damless hydroelectric power station (dhps), whose capacity does not exceed 30 mwatts, and the capacity of a single hydroelectric unit is <10 mwatts. one can divide such hpps, in turn, into: microhpps (with a capacity of 1.5-100 kw) and small hpps (with a capacity from 100 kw to 30 mw). currently, there are more than 300 small hydroelectric power stations with a total capacity of about 1300 mw that operate on the territory of russian federation. these small hydro power plants differ by design solutions and technical level – from manually controlled to fully automated stations that operate without on-duty personnel. these hpps provide power to individual consumers isolated from the electric power systems, but most of them have connection to the local power systems. in order to create such capacities, technical solutions that are fundamentally different from the traditional ones developed for larger hpps are possible, as well as: • construction of river intakes; • the creation of water storage basins, the flooding of which does not exceed the maximum preflood level; • external structural arrangement of hydroelectric power stations; • the energy use of natural changes in the water flow. • the required conditions for the small hydropower development: • decentralized, low-volume energy consumption; small industries, individual farms and enterprises, rural population; • low-voltage distribution network and, obviously, within the regional micro-power supply system; • the average length of the planning period, the use of local materials and labour. recently, new technologies for the usage of small river flows (with a flow rate of 3-5 m3/s for small dam hpps) have appeared. there are already hydroelectric installations that receive electricity from ultra-small flows (low-potential, from 20 l/s), with large capacity capabilities (up to 100 kw), and also from artificially created flows of so-called “kinetic hydro-ring” (polovinkin and fomichev, 2014; bjorn_lytskjold, astrid vosko, 2005, russian federation, 2012; hydrominds-tool). the new technological solutions are rapidly erected, easy to operate and use a wide range of river depths, from 0.15 m and above, with the only condition that the flow speed must be at least 0.8 m/s. the sediment transport and their sedimentation in the reservoirs create problems that require the comprehension, as they have a number of negative impacts on the performance of hpp. that means: depletion of the reservoir storage capacity over time, increased downstream degradation, increased risk of inundation upstream from the reservoirs, production losses due to reduced energy conversion efficiency of turbines, increased frequency of repairs and maintenance; reduced turbine service life and uninterrupted power generation. one can eventually deal with the problem of sedimentation through the use of established technologies. the extension of the program to support the development of renewable energy after 2024 will allow the construction of small hydroelectric power plants (hpps) with a total capacity of about 1 gw in russian federation by 2035 (table 4) (federation, 2009). in accordance with jsc “mnto inset” s-petersburg (www. inset.ru), the use of damless hydroelectric power stations (dhps) that use water pressure is possible on the rivers terek and sunzha with a total capacity of up to 100 mw. if there is a very large reservoir in relation to the size of a hydroelectric power station (or very constant river flows), hpps can generate electricity almost continuously in the course of year, i.e. function as a base load power plant. otherwise, if the potential of hydroelectric power significantly exceeds the storage capacity of the reservoir, then the hydroelectric power plant sometimes has name of energy-limited hydroelectric power station. an energylimited hydroelectric power plant will use up its “fuel reserves” by continuously functioning at level of its nominal capacity during a year. in this case, the use of the reservoir capacity ensures the generation of hydroelectric power in those periods of time that are most important from the perspective of the power system, rather than in those periods of time that belong solely to the river flows. since the demand for electricity changes during the day and table 3: main technical indicators of the argun hpp cascade no name of hpp accumulation volume, m≥ area of accumulation, ha volumetric water discharge, m3/s fall head, m. capacity, mwatt annual output, gw 1 chiri-yurt 48×106 255 2×60 29.3 32.2 142 2 duba-yurt 145×106 519 2×60 44.7 49 169 3 zones 22×106 79 2×45 90 74 201 4 nihaloy 25×106 100 2×40 106.7 78 215 5 cockadoy 25×106 145 2×35 46.8 30 87 6 itum-kale 210×106 425 2×35 156.8 106 243 7 ulus-kert 33×106 134 2×27.5 74.1 37.2 81.2 8 nezhiloy-ahk 60×106 132 2×27.5 116.4 58 130.3 9 sharo-argun 75×106 210 2×25 97.2 44 87.9 10 hima 89×106 220 2×20 445 160 185.7 total 668.4 1542.1 kerimov, et al.: small hydropower development potential in chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020 465 night, during the week and seasons, the generation of electricity from a hydroelectric storage plant can refer to those periods of time when the needs of the power system are greatest. part of this time will relate to the periods of peak demand for electricity. operation of hydroelectric power stations in such a way as to generate electricity during periods of high demand has the name of peak mode (as opposed to base-load regime). however, even if there is a water storage basin, hydroelectric power generation will still have limitations by its size, the rated electric capacity of the hydroelectric power plant, as well as recreational activities or environmental protection. the production of hydroelectric power in peak mode can lead, if there is a water discharge directly into the river, to rapid fluctuations in the river flow, the area covered by water, the depth and speed of the current (kasamba, 2015). 4. economical effectiveness the contracts for design, procurement and construction of hpp become the most popular form of the construction work in large hydropower projects. the main contractors in a number of countries face many difficulties during the construction phase of hydropower projects and it results in significant schedule delays and cost overruns. one of the reasons is the low capacity of subcontractors. an important factor for any main contractor in the implementation of hydropower projects is the subcontractor who participates in the implementation of the hydropower project. the main contractors attempt to examine the risks associated with the identification and control of subcontractors and with the construction delay of hydroelectric power stations. for example in (berkun, 2010; bui, 2019, mai and wang, 2017, nogueira,1993; sachin, 2012; nunes and genta, 1996), by the results’ summary of international research that relate to hydroelectric projects in combination with analytical characteristics of the hydroelectric power projects development in countries with tropical monsoon, subtropical, subequatorial, temperate continental climate with forests on mountain-forest soils, with steppes turning into semi-deserts, covered with glaciers, identified the risk types of subcontractors for the process timeout of a hydroelectric project. there was a development of questionnaire with 18 risk elements, which then passed to experts in the field of hydropower project management. in accordance with the risk model, we identified 11 main risk elements, that one can divide into 3 groups (table 5). (berkun, 2010; bui, 2019; lópez-gonzález, 2019; mai and wang, 2017; nogueira, 1993; sachin, 2012; nunes and genta, 1996). hydroelectric power has characteristics of the highest conversion coefficient in relation to all known energy sources (a coefficient of about 90% in transmission “from water to wires”) it has a very high payback rate for electricity and is a predictable and pricecompetitive technology. it currently provides approximately 16% of global electricity production and 86% of all electricity from renewable sources. the service life of small hpps is quite long, some stations have been operating for more than 70 years, and modern small hpps can have an even longer time of operation. thus, they can provide electricity for a long time without harm to the environment. numerous calculations have proved that investments in small hydropower are not subject to risks, they are reliable for several decades (renewable energy and climate change mitigation 2011, berkun, 2010; federation, 2009; international hydropower association. (n.d.)). the hydropower projects often require a large initial investment, but they have the advantage of very low maintenance costs and a long operational life. in general, there are two main groups of costs: construction costs, which are usually the largest costs for a hydroelectric project; and costs for electromechanical equipment. for power plants designed for maximum power generation (base load) and/or with a certain regulation, the power coefficients range from 30% to 60%. for peak load power plants-the power factor is in the same range and for river systems-in a wide range (20-95%) in accordance with the geographical and climatological conditions, technology and operational characteristics. according to the ibrd, with an average power factor of 44%, initial investment in the construction of small hydroelectric power plants ranges from 1,800 to 3,800 us dollars per 1 kw of capacity (for fall heads from 2.3 m to 13.5 m) and from 1,000 to 3,000 us dollars per 1 kw (for fall heads from 27 m to 350 m). at the same time, the service cost of hpp is low. the capital expenditures include: construction of dams, canals, stations; equipment for power generation (turbine, generator, transformer, table 4: projects for the construction of small hpps in the north caucasus region name small hydro power plant capacity, mwatt av. annual output, mln. kwh period of payback*, years stage of project’s realization* kabardino-balkaria adyr-su 24.5 92.5 9 study of financial feasibility zaragizhskaya 15.0 65.5 8 the same verkhnebalkarskaya 14.7 76.0 7 the same adyl-su, two-stage cascade 14.4 60.3 10 feasibility study design* rd kurminskaya 15.0 57.5 9 the same shinazskaya 1.4 7.0 8 construction and assembly operationsarakulskaya 1.4 6.0 amsarskaya 1.0 4.0 republic of north ossetia – alania fiagdonskaya 4.0 22.0 6 feasibility study design* total 91.4 390.8 *calculations are preliminary and subject to clarification. source: www.ne-fund.ru http://www.ne-fund.ru kerimov, et al.: small hydropower development potential in chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020466 power lines); development of project documentation, cost of land, commissioning. typically, equipment used with low fall pressure and low power generation is expensive and accounts for 40-50% of the total investment. since we talk about the cost of civil construction, it is impossible to give exact figures with regard to the cost of each object. dams, channels, and intake units will constitute the different percentages of the total investment for different facilities. much depends on the topographical and engineering-geological conditions, as well as on the construction technology and the materials under use (figure 3). in accordance with the ministry of energy of the russian federation, the cost of 1 kw·h produced at a small hpp in russian federation within the centralized power system is 40-60 kopecks, within the autonomous system-1.1-2.3 rubles, respectively, the payback of the small hydro power plant is 7-8 years (asarin, 2013; ivanov, 2015; federation, 2009). the costs directly related to the construction of hpp constituted 35% of this amount, while the cost of equipment for power generation – 50%. high investment costs are the biggest barrier to large-scale development of small hydropower. however, despite this fact and a long payback period (7-10 years), small hpps are costeffective due to their long service life (more than 70 years) and low maintenance costs. as a rule, the cost of maintenance and repair without the replacement of expensive equipment is approximately 3 to 4% of capital investment for small and micro-hydro power. 4.1. small hydropower and sustainable development of the region the power plants that use fossil fuels to generate electricity are the main source of greenhouse gases (ghgs). one can effectively replace these installations by nuclear power, hydroelectric power, and other less important options such as biomass, hydrogen, wind power, and solar power. one must produce hydrogen either from natural gas or from electrolysis, and it can become a significant source of greenhouse gases. in accordance with the data from the international commission on large dams (icold) and the world bank, there are ten environmental impact categories. these are impacts on the natural environment (flora, fauna, and aquatic fauna), social/ economic/cultural aspects (relocation), land, dam construction, deposition of water storage basins, downstream hydrology, water quality, tidal barriers, climate, and human health (berkun, 2010, bui, 2019, milton and geiger, 2015). the artificial reservoirs are also a source of significant pollution, especially greenhouse gases (methane and co2). they also cause a major political concern, especially in semi-arid areas, by the decrease of river speed and the sediment increase, that result in significant changes in the downstream regions. as the population increases and the quality of life increases, there is an additional load in relation to the social infrastructure and its intrusion into the physical resource base. however, the choice between costs and benefits is inevitable when the economy, demographics, politics, and environment meet in the same ecosystem (berkun, 2010; bui, 2019; milton and geiger, 2015). historically, economic development has close link with the increase of energy consumption and greenhouse gas emissions, and renewable energy can help reduce this relationship by promotion of the sustainable development. the hydropower essentially offers opportunities to promote socio-economic development, access to energy, advanced energy supply, climate change mitigation, and reduction of negative impacts on the environment and human health. the wide range of hydroelectric power potential, its flexible nature, the ability to accumulate (if there is a reservoir) and the ability to function independently or within the networks of different sizes makes it possible to provide a wide range of services. for example, in china, small hpps are one of the most successful examples in agricultural electrification, with more than 45,000 small hpps that operate with a total capacity of more than 55,000 mw and an annual capacity of 160 twh, with consumers of more than 300 million people (international hydropower association. (n.d.)). the development of small hydro-power also exists in various us states (milton and geiger, 2015; nunes and genta, 1996). figure 3: the cost of 1 kw of capacity in accordance with the ibrdtable 5: results of engineering, procurement and construction risks identification (epc) factors elements of risk engineering • risk due to poor quality of technical design • risk due to poor quality of construction plans • risk due to negative survey data • risk due to poor examination of technical and drawing design purchase • risk due to uncertain and unclear terms of the purchase/sale agreement • risk due to poor purchase of materials, supplies, equipment and machinery • risk due to poor equipment installation and commissioning construction • risk due to a quality team of construction project control • risk due to building safety • risks due to poor quality of investor management • risks due to poor quality management of the epc main contractor • risks due to unclear circular guidance of quality management laws • risk due to poor subcontractors • risk due to poor construction from the epc main contractors kerimov, et al.: small hydropower development potential in chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020 467 like all other options for regulation of energy consumption and water management, hydroelectric projects have negative and positive environmental and social outputs. from an environmental perspective, hydroelectric power can have a significant impact on the environment at the local and regional levels by influence on the ecology of rivers, mainly as a result of changes in their hydrological indicators and violations of the ecological process constancy in relation to sediment transport and fish migration through the construction of dams, embankments and weirs. at the same time, the degree of change in the physical, chemical, biological and ecosystem characteristics of the river depends mainly on the type of hpp. although the projects of river hpp do not change the river flow regime, the creation of a water storage basin in order to accumulate the hydroelectric power causes serious environmental changes as a result of the ecosystem’s transformation in relation to the fast-flowing river into an artificial lake with still water (lópez-gonzález, 2019). the issue of whether hydroelectric power plants can contribute to the acceleration of socio-economic development depends to a large extent on how one shares and distributes the services and income produced among the different stakeholders. hpps can also have a positive impact on local residents and the regional economy, not only by generation of electric power, but also by support of many other water-dependent activities, such as irrigation, tourism, and others. we should note that large power and heat stations focus on the energy supply of cities and industrial enterprises. small settlements and farms scattered among mountain gorges have no electricity or the quality of electricity is poor. one uses approximately 80% of household electricity consumption in mountain regions for room illumination and household appliances. currently, the main energy source materials for the population of these areas are wood, natural gas, oil products, etc. 5. conclusion nowadays, the development of hydroelectric power, as well as small ones, is an important factor for the improvement of the socio-economic living conditions of the population in mountain regions and contributes to the solution of environmental problems in general. despite all its disadvantages, the advantages of small hpps over large ones are known – they have much lower financial and material costs during their construction, lower environmental risk, and proximity to the consumer, which is very significant in mountain conditions. due to the high level of adaptability to cycling up and down demand in the network, a small hydroelectric power station is the preferred element of any integrated power system. we should note that large power and heat stations focus on the energy supply of cities and industrial enterprises. small settlements and farms scattered among mountain gorges have no electricity or the quality of electricity is poor. the construction of small hpp usually uses local materials and labor resources. surface runoff on the territory of chechen republic has a significant volume and the use of its hydroelectric potential will solve a number of economic and social problems. the generation of electricity and its distribution nature will support the development of productive forces in the republic and contribute to energy security both on the territory of the republic and at the regional level. references asarin a.e. (2013), potential of small hpps in the cis countries. assessments and reality. small-scale power generation, 1(2), 16-19. basins of terek. (1987), state water cadastre. section 1 surface water series 3 multiannual data part 1 rivers and channels. vol. 1. russian soviet federative socialist republic. p230-240. berkun, m. (2010), hydroelectric potential and environmental effects of multidam hydropower projects in turkey. energy for sustainable development, 14(4), 320-329. bjorn-lytskjold, a.v. (n.d.), calculating potential for small hydro power plants using gis. norwegian water resources and energy directorate. available from: http://www.ginorden.org/events/ gikonferanser/ginorden2005/folder.2005-09-22.0156715982/ folder.2005-09-26.8958437228/session_1calculating_potensial_for_ small_power_plants_bjorn_lytskjold.pdf/at_download/file. bui, d.m. (2019), research on subcontractor risk of epc hydropower project in vietnam. world journal of engineering and technology, 7, 54-67. cadastre, s.w. (n.d.), electronic catalog of rivers in russian federation. available from: http://www.textual.ru/gvr/index.php. casila, j.d. (2019), potential of the molawin creek for micro hydro power generation: an assessment. sustainable energy technologies and assessments, 32, 111-120. federation, d.o. (2009), energy strategy of the russian federation for the period up to 2030. approved, no. 1715. available from: https:// www.minenergo.sov.ru/aboutminen/energostrategy. gaisumov, m.y., kerimov i.a. (2018), hydroelectric potential of chechen republic and problems of its development. sustainable development of caucasian mountain territories, 1, 326-332. international hydropower association. (n.d.), methodology for evaluation of the hydropower projects compliance with the criteria of sustainable development. available from: http:// www.hydrosustainability.org/getattachment/88626c6e-f889455d954bd0f34e299867/russian-protocol.aspx. ivanov, t.s., badenko v.l., oleshko v.a. (2015), results of the hydroelectric potential assessment of russian rivers by regions in russian federation. izvestiya all-russian vedeneev hydraulic engineering research institute, 276, 57-70. kasamba, c.n. (2015), analysis of flow estimation methods for small hydropower schemes in bua river. energy and power engineering, 7, 55-62. kerimov, i.a., debiev, m. (2018), green energy as a factor of sustainable development in chechen republic. sustainable development of mountain territories, 2(36), 235-245. kerimov, i.a., gaisumov, m. (2011), program of energy development in chechen republic for 2011-2030. science and education in chechen republic: state and prospects of development. materials of the allrussian scientific and practical conference dedicated to the 10th anniversary of the academy of sciences. p338-63. lópez-gonzález, a.f.m. (2019), long-term sustainability assessment of micro-hydro projects: case studies from venezuela. energy policy, 1, 120-130. mai, s.h., wang, j.q. (2017), research on quality risk of epc hydropower kerimov, et al.: small hydropower development potential in chechen republic international journal of energy economics and policy | vol 10 • issue 6 • 2020468 projects in vietnam. world journal of engineering and technology, 5, 299-308. milton, e.g., wade, s.w., wade, d.w. (2015), wade wyoming small hydropower handbook. wyoming: university of wyoming. p64. nogueira, m.f. (1993), the use of small hydroelectric power plants in the amazon. renewable energy, 3(8), 907-911. nunes, v., genta, j. (1996), micro and mini hydroelectric power assessment in uruguay. renewable energy, 9(1-4), 1235-1238. polovinkin, v.n., fomichev, a. (2014), energy reserves and resources. world energy of the xxi century. vol. 2. saint petersburg: st. petersburg state maritime technical university. p254. renewable energy and climate change mitigation. (2011), ipcc special report. summary for policymakers. cambridge, england: cambridge university press. p431. russian federation. (2012), (scientific center for applied research of rae ees of russian federation). electronic resource mode of access. available from: http://www.panthernet.ru/ru/projects-ru/ energyinvest-2012. russian soviet federative socialist republic. (1987), state water cadastre. section 1 surface water. series 3 multiannual data. part 1 rivers and channels. vol. 1. moscow: russian soviet federative socialist republic. p230. zema, d.a., nicotra, a., tamburino, v., zimbone, s.m. (2016), a simple method to evaluate the technical and economic feasibility of micro hydro power plants in existing irrigation systems. renewable energy, 85, 498-506. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. tx_1~at/tx_2~at international journal of energy economics and policy | vol 12 • issue 4 • 202232 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(4), 32-39. what drives environmental disclosure? evidence from mining companies listed on the indonesia stock exchange kumba digdowiseiso*, bambang subiyanto, retno setioningsih faculty of economics and business, university of national, jakarta, indonesia. *email: kumba.digdo@civitas.unas.ac.id received: 17 march 2022 accepted: 11 june 2022 doi: https://doi.org/10.32479/ijeep.13170 abstract this study aims to analyse the effects of environmental performance, profitability, and leverage on the environmental disclosure in mining industry sector companies listed on the indonesia stock exchange. the sample of this study was 15 mining companies which were selected by using a purposive sampling technique. we collected the company’s annual report over the period 2014–2021. the results showed that environmental performance had a positive and significant effect on environmental disclosure. in this case, the corporate performance rating program (proper) rating was able to prove that there was a significant influence between the global reporting initiative (gri) as a form of its responsibility and the extent of environmental disclosure. in addition, profitability produced a negative and significant effect on environmental disclosure. the company considered that it was no longer necessary to carry out environmental disclosure when the company has made a profit annually because the company’s environmental performance was good. finally, leverage had a negative and significant effect on environmental disclosure. thus, when the leverage of the company reached the maximum point, the company chose to pay off the debt, instead of conducting environmental disclosure. keywords: environmental performance, environmental disclosure, profitability, leverage, indonesia jel classifications: q500, q510, q560 1. introduction companies generally make profit as the main goal for the interests of shareholders. however, companies should not only focus their attention on generating profits, but they also have some responsibilities for the surrounding environment as the environmental consequences arise from their operational activities (totok, 2014). in the last few years, there have been problems regarding pollution and environmental damage due to the company’s operating activities. take the example of how are you indonesia (hayi, ltd.) located in south cimahi district, west java that has been proven to pollute the environment in the citarum watershed through the disposal of liquid waste from textiles. according to the ministry of environment and forestry (moef), hayi, ltd. received a sentence from the panel of judges to pay material compensation of usd 830,000. this act of environmental pollution is an extraordinary crime because it has a direct impact on public health, economy and ecosystem damage and has a widespread impact for the future (moef, 2020). the next case was moef sealed the former mining pit of cahaya energi mandiri (cem, ltd.) and multi harapan utama (mhu, ltd.), which is located in city of samarinda and tenggarong, respectively. the two ex-mining holes have formed a pool of water with a depth of almost 30 m. the negligence of the company, which did not immediately rehabilitate it, has resulted in the death of children’s lives with as many as 13 victims in 10 mining company areas (moef, 2016). based on the environmental complaint reports, in 2019, moef received a total of 470 reports based on environmental and forestry categories. in 2020, there was an increase in complaints by 275 reports, followed by a rise in charges by 710 reports in 2021. therefore, the problem of pollution and environmental damage in indonesia is very worrying for the survival of the community. this journal is licensed under a creative commons attribution 4.0 international license digdowiseiso, et al.: what drives environmental disclosure? evidence from mining companies listed on the indonesia stock exchange international journal of energy economics and policy | vol 12 • issue 4 • 2022 33 in line with this view, protecting the environment is a human duty and one of the company’s obligations. according to chrysanti and noviarini (2015), companies have a big responsibility in protecting the environment because the environment plays a major role in the future given the depletion and deteriorating natural resources in indonesia. in indonesia, one of the newest regulations on the environment has been stipulated in law no. 32 of 2009 concerning environmental protection and management. this law regulates an integrated systematic effort to preserve environmental functions and prevent environmental pollution, which includes planning, utilization, control, maintenance, supervision and law enforcement. it also regulates the prohibition of polluting, importing hazardous and toxic objects, entering waste into environmental media, clearing land by burning, and so on. however, the company makes a minimum disclosure regarding reports of all environmental activities that can be reported in the annual report (ciriyani and putra, 2016). in principle, such a regulation on environmental disclosure is already contained in the financial accounting standards requirements no. 1 of 2019 where the financial statements are reports that show the results of management’s responsibilities related to the use of available resources that have been entrusted to them. several entities provide financial reports containing environmental reports although such reports have been presented outside the financial statements. but, this rule can be one example of corporate environmental disclosure. here, information regarding responsibility for the environment can also be disclosed in a sustainability report. purwanto and nugroho (2020) stated that environmental disclosure is one of the processes carried out by companies in disclosing information related to the responsibility for the company’s operational activities and to the impacts that arise on the social conditions of society and the environment. it can create harmony between the company, nature and humans. besides, it can improve the company’s good image so that the company is able to survive in its survival. one of the government programs to assess a company’s environmental performance is by utilizing the socalled corporate performance rating program (proper). it is a program of corporate responsibility efforts in controlling pollution or environmental damage and managing waste, hazardous and toxic materials that have an impact on people’s lives based on the applicable laws and regulations. moef has determined the proper measurement by giving five (5) colours starting from the best color, namely gold, then green, blue, red to black in a row as a bad rating. this rating assesses the environmental performance of a company in the context of conservatism so that it can control the environmental impact of the company’s operations. figure 1 shows that there is an increasing number of proper participants annually. this indicates a good action, namely increasing the blue colour rating. companies rated green experienced a significant decline from 2017 to 2018, before it rose again in 2020 and 2021. however, there were still few companies that obtained a gold colour rating. proper also stated the percentage of a company’s compliance with its environmental responsibilities. in the period 2017-2018, the percentage of obedience was 85% and then increased to 92% in 2018-2019 period. in the period 2019-2020, the percentage of obedience was 87%, then there was a decrease in obedience over the period 2020-2021 by 2%. several factors affecting environmental disclosure indicate that there is a contradiction between the results of previous studies and other studies. for example, according to clarkson et al. (2008), noviani and suardana (2019), and sari et al. (2019), environmental performance has a positive effect on environmental disclosure. however, purwanto and nugroho (2020) argue that it has no influence. furthermore, studies conducted by andrikopoulos and kriklani (2013) and clarkson et al. (2011) state that profitability has a positive effect on environmental disclosure, while akbaş and canikli (2019) argues that profitability has a negative influence to environmental disclosure. different results are also found in the studies of dibia and onwuchekwa (2015) and kalash (2020) where profitability has no effect on environmental disclosure. the last factor studied in this research is leverage. kalash (2020) states that leverage has a positive effect on environmental disclosure while dibia and onwuchekwa (2015), ohidoa et al. (2016), van de burgwal and vieira (2014), and akbaş and canikli (2019) prove that leverage has no effect on environmental disclosure. aside from the research gap, the analysis of the annual report data of the mining companies over the period 2014-2021 shows that there is a business phenomenon, namely between profitability and environmental disclosure (figure 2). companies that possess a higher profitability have not made a complete environmental disclosure according to the global reporting initiative (gri). in principle, gri is an institution that issues guidelines in environmental disclosure that increases the company’s responsibility to the environment in the long term. therefore, research related to environmental disclosure needs to be re-done to determine the level of corporate responsibility for the survival of the community in the future. on the basis of the business phenomenon and research gap described above, the authors assume that there is a problem regarding environmental disclosure so that it needs to be investigated further considering issues related to the environment. thus, to analyse figure 1: trend on proper over the period 2017-2021 source: authors’ calculation digdowiseiso, et al.: what drives environmental disclosure? evidence from mining companies listed on the indonesia stock exchange international journal of energy economics and policy | vol 12 • issue 4 • 202234 empirical evidence about the effect of environmental performance, profitability and leverage on environmental disclosure, this research was conducted. the rest of the paper is organized as follows: section ii depicts literature review on the determinants of environmental disclosure. section iii presents the data and methodology used in this research. section iv reports empirical results and discussions based on the econometric model. we also provide concluding remarks as the next section. 2. literature review in this study, we use legitimacy theory as a focal point to explain the nexus between public and corporate, where community belief should be in line with company expectations (dowling and pfeffer, 1975). according to ghozali and chariri (2007), it is a status of a company that exists when the company’s value system aligns with the social value system. it emphasizes that the company must protect the company’s operational activities so that the company exists within the limits and the norms applied in the society. legitimacy can be expressed as the company’s recognition of the community which aims to gain trust, develop and maintain the company in the future (deegan, 2002). thus, legitimacy theory focuses on the company and society within the social contract. in this context, companies are required to pay attention to their environment because social expectations will always change in the future (deegan, 2002). lindblom (1994) states that if the company’s legitimacy is being questioned, the company should implement an aggressive strategy that must be informed to its shareholders. one of which is related to the changes in the company’s activities and performance drastically. however, the company can choose to gradually change the views of its stakeholders without altering the actual behaviour of the company. for example, turning its attention on the issues involved and encouraging emotional engagement (guthrie and abeysekera, 2006). legitimacy theory requires companies to show attitudes and behaviours that are in accordance with social norms in the company’s operational activities (guthrie and abeysekera, 2006). this action can be achieved if the company makes environmental disclosures and reports it through an annual report and/or sustainability report. disclosure is useful as management considerations regarding social values or attracting the attention of the community regarding the negative impacts of operational activities (lindblom, 1994). several previous studies conducted an assessment of the voluntary disclosure of annual reports and assessed that the reporting of environmental and social information was a method used by companies to respond to the public demands (guthrie and abeysekera, 2006). now, the problems that occur in the business environment are increasingly being considered by companies in carrying out their operational activities. to overcome this, the company tries to disclose more detailed information which aims to improve the reputation of the company (gray et al., 2001). environmental disclosure is a form of the company’s concern for the environment and reports it through an annual report. it is a sustainable matter that is widespread for all group of companies to improve their annual reports and hence, overcome environmental problems (sahay, 2004). the responsibility of environmental disclosure can be seen by how many companies implement obligations stated on the standards of global reporting initiative (gri), in which those must be reported in their annual financial reports (van de burgwal and vieira, 2014; purwanto and nugroho, 2020). environmental disclosure is very important because it is used for consideration in making social, economic or political decisions for the community, investors and the government. the company is obliged to report the implementation related to the environment as a form of the company’s concern for the environment and society. this is because environmental disclosure is mandatory for companies which has been regulated in law no. 40 of 2007 concerning limited liability companies (pt). in addition to the annual reports, companies are also required to report social and environment sides for which the company is responsible. therefore, environmental disclosure is very crucial as the public can assess activities carried out by the company in maintaining the social environment that have been presented in the annual report (deegan, 2002). environmental performance has become a very popular issue for stakeholders in the company because the company’s operational activities may have a harmful impact on the environment (hackston and milne, 1999; monteiro and aibar-guzman, 2010). the government and society also emphasize on companies to pay attention to their environmental responsibilities and disclose environmental information (lu and abeysekera, 2014). according to akbaş and canikli (2019), negative environmental impacts resulting from economic development such as climate change and global warming, natural disasters, and pollution have become the center of attention of governments and civil society organizations. this condition further increases the pressure on the company. assessment of environmental performance in indonesia can be seen through the environmental management rating program (proper) by the moef. proper can influence companies to comply with applicable regulations in a bid to create a superior environment (i.e. environmental excellence). proper participants are selective, aimed at companies whose operations have a major impact on the environment. proper has a rating figure 2: business phenomenon between profitability and environmental disclosure source: authors’ calculation digdowiseiso, et al.: what drives environmental disclosure? evidence from mining companies listed on the indonesia stock exchange international journal of energy economics and policy | vol 12 • issue 4 • 2022 35 from best to worst with marked gold, green, blue, red and black colours (table 1). according to brigham and houston (2022), profitability is a summary of the net results of the company’s operational activities in a certain period of time. further, they state that profitability can be determined by calculating financial ratios to analyse the financial position, results of operations and the level of profit of a company. this can assess the progress of a company and is needed by the stakeholders in considering decision making. in principle, profitability can be calculated with several return and margin ratios such as return on assets (roa), return on equity (roe), return on investment (roi), gross profit margin (gpm), and net profit margin (npm) (rokhmawati, 2016). in this research, we use roa as a proxy indicator to measure profitability as it indicates the ability of a company generates profit from the assets used. meanwhile, according to brigham and houston (2022), leverage compares between total liability and total assets of the company. it shows how much the company uses funds through debt as fixed costs in an effort to level up profitability. the use of debt in the company will make the company provide more information to meet the demands of investors and creditors as creditors always monitor the funds lent to the company. the leverage ratio consists of debt to equity ratio (der) and debt to total asset ratio (dar) (brigham and houston, 2022). in this study, we utilize der that can be calculated simply by dividing the company’s total debt (including short-term liabilities) by shareholder equity. the lower this ratio, the higher the level of corporate funding provided by shareholders and the greater the protection for creditors (i.e., margin of protection) in the event of asset depreciation or major losses. companies that have good environmental performance tend to make environmental disclosures as a form of obedience to the law. according to clarkson et al. (2008), companies that are able to show their environmental performance will get a good signal from the surrounding environment. the purpose of the company reporting the environmental disclosure report is so that the public or stakeholders know that the company has carried out its responsibilities to the environment well so that it is able to attract sympathy and improve the company’s image in the eyes of the community and the company will be considered legitimate and responsible. therefore, our first hypothesis is that environmental performance has a positive and significant effect on environmental disclosure. based on the legitimacy theory, companies will always get pressure from the community so that companies pay more attention to environmental problem arising from their operations. companies with high levels of profitability will easily cope with public pressure because they have resources that can be used to make environmental disclosures compared to companies with low levels of profitability (ningtiyas and riharjo, 2018). this makes it easier for them to gain legitimacy from the community. in line with this argument, kipngetich (2019) states that profitability can affect environmental disclosure so that it can improve company performance. this resulted in environmental disclosure which can be trusted as a management approach to reduce social pressure and respond to social needs (hackston and milne, 1996). thus, our second hypothesis is that profitability has a positive and significant effect on environmental disclosure. according to brigham and houston (2022), leverage has a positive effect on environmental disclosure because companies will continue to increase the environmental disclosure actions when the company’s funding is in high-risk conditions. such actions can facilitate company to convince investors and creditors. however, the higher the leverage, the higher the risk of the company which can affect the company’s net income (kipngetich, 2019). debt will cause interest to be paid by the company so that the company will reduce costs, especially costs for making environmental disclosures. besides, the company has a great responsibility to creditors when the company’s leverage is high so that creditors will monitor the company closely. this makes management more careful in reporting their performance. hence, our third hypothesis is that leverage has a negative and significant effect on environmental disclosure. 3. data and empirical framework in this study, the authors selected 15 mining companies as a sample. from a total population of 47 companies, the authors determine it based on the following criteria: (1) mining companies listed on the indonesia stock exchange during the 2014-2021 period; (2) mining companies that publish the annual reports completely over the period 2014-2021; (3) mining companies must experience profit over the period 2014-2021; and (4) mining companies should include the company performance rating assessment program (proper) in their annual report. the authors use the dependent variable of environmental disclosure as the object of analysis. as a metric of environmental disclosure, we utilize the environmental disclosure score contained in the annual report of the sample companies. a score is given to table 1: proper category color information gold the company consistently demonstrates environmental excellence in the production and service processes and has ethics and responsibility towards the community in doing business green the company manages the environment better than the management required by regulations (beyond compliance through the implementation of an environmental management system and utilizes resources efficiently and carries out social responsibility well blue the company carries out environmental management in accordance with predetermined requirements or in accordance with applicable laws and regulations. red the company carries out environmental management but has not complied with the requirements specified in the legislation black companies that intentionally commit acts or omissions that result in environmental pollution or damage and violate the regulations that have been regulated in the applicable laws and/or do not carry out administrative sanctions source: moef (2019) digdowiseiso, et al.: what drives environmental disclosure? evidence from mining companies listed on the indonesia stock exchange international journal of energy economics and policy | vol 12 • issue 4 • 202236 each item of environmental activity disclosure contained in the annual report. to find out the extent of environmental disclosure, the researchers adopted previous studies such as syahputra et al. (2019) and purwanto and nugroho (2020) who developed a checklist of gri-g4 indicators with the environment category consisting of 12 indicators with 34 items (table 2). according to syahputra et al. (2019) and purwanto and nugroho (2020), the calculation of the environmental disclosure index is carried out by assigning a score to each disclosure item, then divided by a maximum score of 34. on environmental performance, we utilize the environmental management rating program (proper) in companies by adopting the assessment of syahputra et al. (2019) and purwanto and table 2: gri-g4 disclosure indicators for environmental category indicators/aspects information ingredient g4-en 1 materials used by weight or volume g4-en 2 percentage of materials used which are recycled input materials energy g4-en 3 energy consumption in the organization g4-en 4 energy consumption outside the organization g4-en 5 energy intensity g4-en 6 reducing energy consumption g4-en 7 reducing energy requirements for products and services water g4-en 8 total water intake by source g4-en 9 water sources significantly affected by water withdrawal g4-en 10 percentage and total volume of water recycled and reused biodiversity g4-en 11 operational sites owned, leased, managed within, or adjacent to, protected areas and areas of high biodiversity value outside protected areas g4-en 12 description of the significant impact of activities, products and services on biodiversity in protected areas and areas with high biodiversity value outside protected areas g4-en 13 protected and restored habitat g4-en 14 total number of species on the iunc red list and species on the national protected species list with habitats in areas affected by operations, by level of extinction risk emission g4-en 15 direct greenhouse gas (ghg) emissions (scope 1) g4-en 16 indirect energy greenhouse gas (ghg) emissions (scope 2) g4-en 17 other indirect greenhouse gas (ghg) emissions (scope 3) g4-en 18 greenhouse gas (ghg) emission intensity g4-en 19 reducing greenhouse gas (ghg) emissions g4-en 20 emissions of ozone depleting substances (bpo) g4-en 21 nox, sox and other significant air emissions effluent and waste g4-en 22 total water discharged by quality and purpose g4-en 23 total weight of waste by type and method of disposal g4-en 24 the total number and volume of spills is significant g4-en 25 the weight of the waste considered hazardous according to the provisions of the basel convention attachments i, ii, iii, and viii transported, imported, exported, or processed, and the percentage of waste transported for international shipments g4-en 26 the identity, size, protected status, and biodiversity value of water bodies and associated habitats that are significantly affected by the organization’s wastewater and runoff products and services g4-en 27 the degree of mitigation of the impact on the environmental impact of products and services g4-en 28 percentage of products sold and their packaging reclaimed by category obedience g4-en 29 the monetary value of the significant fine and the total amount non-monetary sanctions because disobedient to environmental laws and regulations transportation g4-en 30 significant environmental impacts of transporting products and other goods and materials for the organization’s operations, and transporting personnel work etc g4-en 31 total environmental protection expenditure and investment by type top suppliers for the environment g4-en 32 percentage of new suppliers screened using environmental criteria g4-en 33 actual significant negative environmental impacts and potential in the supply chain and actions taken troubleshooting mechanism environment g4-en 34 number of complaints about environmental impacts that were filed, handled, and resolved through the official complaint mechanism source: syahputra et al. (2019) and purwanto and nugroho (2020) digdowiseiso, et al.: what drives environmental disclosure? evidence from mining companies listed on the indonesia stock exchange international journal of energy economics and policy | vol 12 • issue 4 • 2022 37 nugroho (2020). they use proper to analyse the extent to which the company guarantees compliance with regulations based on its level. the annual report of 15 selected mining companies can not only produce the proper rating, but it also gives an insight on profitability ratio as measured by return on assets (roa), and leverage ratio as gauged by debt to equity ratio (der). with regards to table 3, it is clear that on average, the number of environmental disclosure is quite low. however, environmental performance, on average, is categorized as well. profitability and leverage are also, on average, quite moderate. in estimating the effects of environmental performance, profitability, and leverage on environmental disclosure, we utilize the fixed effects (fe) regression in a static panel dataset since the previous hausman and chow test indicate that fe is more suitable than random effects (re) and pooled least squared (pls) models, respectively. therefore, the following benchmark model at crosscompany level will be used: edit=β0+β1epit+β2proit+β3levit+ui+ɵt+ɛit (1) where the subscript i denotes the province, t denotes observation period, which is 2014-2021, and εit is the corresponding error term. the main interest throughout this article lies in the coefficient β1, β2, and β3, which measures the impacts of environmental performance, profitability, and leverage on tourism, respectively. in the models, we also incorporate the company and period fixed effects to control the issue of time-invariant (ui) and time-variant (ɵt) unobserved factors, respectively. such a method is expected to reduce cross-sectional dependence due to spatial effects and unobserved common factors. hence, in the fixed effects (fe) model, we incorporate both income group and period fixed effect. specifically, the inclusion of ui will at least tackle some unobserved preferences of societies in a certain company, and may thus simultaneously determine the degree of environmental disclosure. 4. empirical results and discussion the regression results are listed in table 4, which shows various determinants of environmental disclosure. it is important to note that environmental performance was significantly and positively correlated with environmental disclosure. the estimated coefficient implies that a one additional point increases in ep will increase environmental disclosure by 15.11 points, ceteris paribus respectively. however, there were a significant and negative association between profitability and leverage and environmental disclosure. precisely, it indicates that a one additional point increases in pro and lev will respectively decrease environmental disclosure by 63.45 and 8.75 points, holding other variables fixed. companies that have a good environmental performance tend to disclose more environmental information to the public. in this study, the proper rating of mining companies is able to prove that there is a positive influence of the global reporting initiative (gri) as a form of responsibility on the disclosure of environmental information. our result is somehow consistent with the theory of legitimacy in which companies unveil the environmental information in their annual report to minimize the occurrence of the legitimacy gap. by doing so, they must comply with the laws and regulations related to the corporate social obligations. therefore, our study corroborates the results of clarkson et al. (2008), noviani and suardana (2019), and sari et al. (2019) which state that environmental performance has a positive effect on environmental disclosure. regarding on profitability, in order to carry out environmental disclosure, companies must spend larger costs which can affect the profitability. for example, a company builds a place for captive breeding of extinct animals or for processing waste to be environmentally friendly. based on this argument, companies will prefer to fulfil their obligations to their investors and creditors rather than incur costs for environmental disclosure. hence, our result confirms the findings of dewi and yasa (2017) where profitability has a negative effect on environmental disclosure. however, the findings do not corroborate the legitimacy theory where companies with high levels of profitability have more resources, particularly in conducting environmental disclosure, when compared to companies with low levels of profitability (dibia and onwuchekwa, 2015; ningtiyas and riharjo, 2018). moving to the discussion of debt, companies that have a high level of leverage tend to use their resources to pay off their debts as they will always be supervised by its stakeholders. increasing debt will be considered as a step back for managements because it can increase the risk of financial distress (dibia and onwuchekwa, 2015). in this case, managements tend to conceal the company’s performance on environmental aspects to their stakeholders. thus, our results are in line with the findings of dibia and onwuchekwa (2015) where leverage has a negative effect on environmental disclosure. however, we cannot confirm theory of legitimacy table 3: summary of statistics on environmental disclosure equation variables obs. mean std. deviation min max environmental performance 120 3.59 0.67 3 5 profitability 120 0.11 0.11 2 x 10-4 0.46 leverage 120 0.77 0.60 0.19 3.38 environmental disclosure 120 29.12 19.36 5.88 64.71 source: authors’ calculation table 4: fixed effects (fe) regression on environmental disclosure equation independent variables (1) environmental performance 15.11*** (2.94) profitability −63.45*** (17.91) leverage −8.75*** (3.30) company fe yes year fe yes observation 120 group 15 within r-squared 0.42 number of parentheses are robust standard error. asterisks denote: ***significant at 1%; **significant at 5% level; *significant at 10% level digdowiseiso, et al.: what drives environmental disclosure? evidence from mining companies listed on the indonesia stock exchange international journal of energy economics and policy | vol 12 • issue 4 • 202238 where the higher the leverage, the higher the company to execute environmental disclosure as it makes easier for them to gain legitimacy from the community (dowling and pfeffer, 1975). 5. conclusion in this study, we investigated the determinants of environmental disclosure in the mining companies listed on the indonesia stock exchange (idx) over the period 2014-2021 by applying the fixed effects (fe) regressions. we found that environmental performance had a positive and significant effect on environmental disclosure. meanwhile, both profitability and leverage had a negative and significant effect on environmental disclosure. our study is bound by certain limitations. first, our study does not capture the certain indicators of profitability and leverage. the relative importance of difference metrics will assist policymakers to identify and facilitate the design of efficient policies. thus, a comprehensive measure of fundamental factors can evaluate precisely the impact of profitability and leverage on environmental disclosure. second, the within r-squared of the model is about 0.42 which means that 42 percent of the environmental disclosure variables can be explained by environmental performance (x1), profitability (x2), and leverage (x3), while the remaining 58 percent is explained by other unknown factors that were not included in this study. hence, the need to incorporate several control variables such as firm size and age, and concentration of ownership can add the variation of model. 6. acknowledgments the authors convey a big gratitude to fellow colleagues from department of management and accounting, university of national for the inputs and comments during our seminar. references akbaş, h.e., canikli, s. (2019), determinants of voluntary greenhouse gas emission disclosure: an empirical investigation on turkish firms. sustainability, 11(1), 1-24. andrikopoulos, a., kriklani, n. (2013), environmental disclosure and financial characteristics of the firm: the case of denmark. corporate social responsibility and environmental management, 20(1), 55-64. brigham, e.f., houston, j.f. (2022), fundamentals of financial management: concise. boston, ma, united states: cengage limited. chrysanti, a., noviarini, d. (2015), the influence of corporate governance perception index, profit management, and industrial type to environmental disclosure. jurnal ilmiah wahana akuntansi, 10(2), 108-123. ciriyani, n.k., putra, i.m.p. (2016), pengaruh ukuran perusahaan, profitabilitas, dan umur perusahaan pada pengungkapan informasi lingkungan. e-jurnal akuntansi, 17(3), 2091-2119. clarkson, p.m., li, y., richardson, g.d., vasvari, f.p. (2008), revisiting the relation between environmental performance and environmental disclosure: an empirical analysis. accounting, organizations, and society, 33(4-5), 303-327. clarkson, p.m., overell, m.b., chapple, l. (2011), environmental reporting and its relation to corporate environmental performance. abacus: a journal of accounting, finance, and business studies, 47(1), 27-60. deegan, c. (2002), the legitimizing effect of social and environmental disclosures: a theoretical foundation. accounting, auditing and accountability journal, 15(3), 282-311. dewi, i.a.p., yasa, g.w. (2017), pengaruh ukuran perusahaan, profitabilitas, tipe industri, dan kinerja lingkungan terhadap environmental disclosure. e journal akuntansi, 20(3), 2362-2391. dibia, n.o., onwuchekwa, j.c. (2015), determinants of environmental disclosures in nigeria: a case study of oil and gas companies. international journal of finance and accounting, 4(3), 145-152. dowling, j., pfeffer, j. (1975), organizational legitimacy: social values and organizational behavior. the pacific sociological review, 18(1), 122-136. ghozali, i., chariri, a. (2007), teori akuntansi. semarang: badan penerbit universitas diponegoro. gray, r., javad, m., power, d.m., sinclair, d.a.r. (2001), social and environmental disclosure and corporate characteristics: a research note and extension. journal of business, finance and accounting, 28(3-4), 327-356. guthrie, j., abeysekera, i. (2006), content analysis of social, environmental reporting: what is new? journal of human resource costing and accounting, 10(2), 114-26. hackston, d., milne, m.j. (1996), some determinant of social and environment disclosure in new zealand companies. accounting, auditing and accountability journal, 9(1), 77-108. kalash, i. (2020), environmental disclosure: determinants and effects on financial performance? an empirical evidence from turkey. sosyoekonomi, 28(46), 95-115. kipngetich, r.m. (2019), effect of liquidity management on the financial performance of insurance companies in kenya. doctoral dissertation, university of nairobi. lindblom, c.k. (1994), the implications of organizational legitimacy for corporate social performance and disclosure. new york: critical perspectives. lu, y., abeysekera, i. (2014) stakeholders’ power, corporate characteristics, and social and environmental disclosure. journal of cleaner production, 64(1), 426-436. ministry of environment and forestry. (2016), kementerian l h k lakukan penyegelan lubang tambang di kalimantan timur yang memakan korban. available from: https://www.menlhk.go.id/site/ single_post/533/kementerian-l-h-k-lakukan-%20penyegelan-lubangtambang-di-kalimantan-timur-yang-memakan-korban [last accessed on 2022 mar 20]. ministry of environment and forestry. (2019), kriteria proper. available from: https://www.proper.menlhk.go.id/proper/kriteria [last accessed on 2022 mar 20]. ministry of environment and forestry. (2020), pt hayi akan bayar ganti rugi lingkungan rp 12 milyar. available from: http:// www.ppid.menlhk.go.id/berita/siaran-pers/5556 [last accessed on 2022 mar 10]. monteiro, s.m.d., aibar-guzman, b. (2010), determinants of environmental disclosure in the annual reports of large companies operating in portugal. corporate social responsibility and environmental management, 17(4), 185-204. ningtiyas, r.y., riharjo, i.b. (2018), pengaruh ukuran perusahaan dan kinerja keuangan terhadap environmental disclosure pada perusahaan manufaktur yang terdaftar di bei. jurnal ilmu dan riset akuntansi, 7(6), 1-21. noviani, n.k.d., suardana, k.a. (2019), pengaruh ukuran perusahaan, political cost dan kinerja lingkungan terhadap environmental disclosure dalam laporan tahunan. e-jurnal akuntansi, 28(3), 1904-1919. digdowiseiso, et al.: what drives environmental disclosure? evidence from mining companies listed on the indonesia stock exchange international journal of energy economics and policy | vol 12 • issue 4 • 2022 39 ohidoa, t., omokhudu, o.o., oserogho, i.a.f. (2016), determinants of environmental disclosure. international journal of advanced academic research, 2(8), 49-58. purwanto, a.p., nugroho, p.i. (2020), factors influencing environmental disclosure in consumer goods industry and mining companies. international journal of social science and business, 4(1), 1-9. rokhmawati, a. (2016), manajemen keuangan. jakarta: cv budi utama. sahay, a. (2004), environmental reporting by indian corporations. corporate social responsibility and environmental management, 11(1), 12-22. sari, w.h., agustin, h., mulyani, e. (2019), pengaruh good corporate governance dan kinerja lingkungan terhadap pengungkapan lingkungan. jurnal eksplorasi akuntansi, 1(1), 18-34. syahputra, d., helmy, h., mulyani, e. (2019), analisis pengungkapan lingkungan berdasarkan global reporting initiatives (gri) g4. jurnal eksplorasi akuntansi, 1(2), 678-693. totok, m. (2014), corporate social responsibility. bandung: alfabeta. van de burgwal, d., vieira, r.j.o. (2014), environmental disclosure determinants in dutch listed companies. revista contabilidade and finanças, 25(64), 60-78. . international journal of energy economics and policy | vol 8 • issue 1 • 2018122 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(1), 122-127. formation of the price mechanism for energy resources in russia and the countries of the european union olga ergunova1, vladislav lizunkov2, viktor blaginin3, ekaterina politsinskaya4, olga i. shaykina5* 1department of foreign economic activity, ural state economic university, yekaterinburg, russian federation, 2yurga institute of technology of national research tomsk polytechnic university, yurga, russian federation, 3department of regional, municipal economy, ural state economic university, yekaterinburg, russian federation, 4yurga institute of technology of national research tomsk polytechnic university, yurga, russian federation, 5national research tomsk polytechnic university, tomsk, russian federation. *email: nikol_2507@mail.ru abstract the current research focuses on the solution to the challenge of finding balance in different energy resources pricing trends. our research shows that increase in gas price leads to corresponding growth in electricity cost, but the effect of replacement has not occurred yet. the burden on population is growing as cross-subsidization is gradually being canceled in order to increase the production competitiveness. it has been found out that households in russia pay less nowadays than in the ussr, less than europeans for gasoline, electricity and diesel at present. if we bring the cost of electricity in proportion to the corresponding level of the soviet time, it will cost about 0.1825 € per kwh, which quite corresponds to european prices and newly confirms the validity of the author’s calculations. two theoretically possible directions for the development of russian energy system based on innovations in energy consumption and production have been defined. keywords: european union, energetics, price, energy supplies, competitiveness of production, direction of development jel classifications: c62, n70, o13, p48 1. introduction at all times energy sector has determined the development of not only economics but mankind as a whole thus contributing to the fundamentals of so-called energy security. the quality and quantity of the consumed energy resources defined labor efficiency (productivity) as well as areas and rate of core productions development. at the same time there is a “use of resources rule” in the economic theory: profits are maximized by continually added resources until the marginal revenue product is equal to the marginal revenue cost: mrp = мrс. the “use of resources rule” leads to demand of a firm for each resource. the change of resource price leads to both substitution effect when a firm substitutes expensive resources for cheaper ones and output effect when a firm increases output of the product if the price of the resource goes down or reduces output when the price of the resource goes up. market uses price mechanism to inform about demand change for each economic resource. price dynamics is closely connected to elasticity of the resource demand at a certain price. this elasticity characterizes change of demand for the resource if its price changes. energy sector is one of the most significant and at the same time one of the most difficult spheres of russia-european union (eu) relations. the eu needs hydrocarbons supply, and russia needs revenues from energy resources sale (eu buys more than 50% of russian oil exports and more than 60% of russian natural gas exports). this has a serious impact on the traditional alignment of forces in their economic relations. as a rule, the eu gets superior in the economic relations with russia, trying to impose its own level playing field both through bilateral documents and in multilateral forums. although the eu made similar attempts in the energy sector, its efforts remained rather restrained. the reaction of the russian federation was extremely tough. ergunova, et al.: formation of the price mechanism for energy resources in russia and the countries of the european union international journal of energy economics and policy | vol 8 • issue 1 • 2018 123 at the same time, governments of european countries attach great importance to the development of alternative energy technologies. in 1997, the eu, in the white paper on renewable energy sources, set the goal to double the use of renewable energy sources from 6% (the 2000 level) to 12% by 2010. three main sectors where an increase in the share of renewable energy use will make it possible to significant change the current situation were determined as follows: power supply; buildings heat and cold supply; production of biofuels. these three sectors contribute greatly to sustainability, reliability and competitiveness of the energy supply. but industrial base, demands, growth barriers and legislative base required for each sector differ drastically. considering these principles, it would be curious to analyze the dynamics of the price for the main energy carrier in the russian federation, namely, gas and identify changes in the energy sector which might take place if gas price and net costs change in the russian federation and european market. 2. literature review in the world economic literature, the theoretical framework for analyzing the problems of regulating national energy sectors and world energy markets is rather extensive, as they represent the basic infrastructure sector of the world economy. this is due to the fact that the problems of regulation encompass such areas as industrial organization theory, public sector economics, economic regulation theory and natural monopolies theory which can be attributed to the above-mentioned economic regulation theory as well as a number of other theories and disciplines. the monographs of a. koch, m. atton, j. vickers, m. crew, p. kleindorfer, s. brown and d. sibley and others are devoted to theoretical analysis of regulatory problems and related issues. as already noted, it is possible to identify 2 different approaches in the state policy aimed at increasing economic welfare. on the one hand, we define development and implementation of measures for competition development and antimonopoly policy, which we have considered above, and, on the other hand regulation can be pointed out. the main approach is applied to those areas of production activities where competition is potentially effective, while additional approach is applicable to the areas where the market turns out to be ineffective (natural monopolies, negative externalities, contradictions between short-term commercial interests of the business and long-term strategic plans for social and economic development, etc.). in as early as the 1960s, american economists h. averch and l. johnson_ftn1 discovered the effect that was later on called averch–johnson effect. the essence of the effect is that at a given rate of return, regulated companies tend to expand the volume of their profits by artificial capital accumulation, namely, the denominator in the rate of return formula. the k/l ratio is overstated by the regulated company, and its output can be implemented at a lower cost using less capital and more effort. so, h. averch and l. johnson came to the following conclusion: rate of return regulation leads to inefficient operation of the company and does not necessarily lead to an increase in output and a drop in price (averch and johnson, 1962). the ineffectiveness of regulating the capital rate of return was also described by r. greenwald (greenwald, 1980), m. brennan, e. schwartz and other researchers (brennan and schwartz, 1982). modern ideas of natural monopolies and economic regulatory institutions allow the introduction of one or another type of competition to ensure the effective operation of the naturally allocated monopoly sector. the forms of competition, used as regulators of natural monopolies, go beyond the generally accepted typology (korolkova, 2000). the theory includes the following types of market environments compatible with natural monopoly and forcing it to operate in socially desirable regimes: • the model of contestable market, which was proposed by w. baumol, j. panzar and r. willing, • competition for the market model as referred to natural monopoly was formulated in the late 1960s and early 1970s by h. demsetz (demsetz, 1968), j. stigler (stgler, 1971), and r. posner (posner, 1974); • yardstick competition model. the essence of this concept is that regulators auction off a monopoly franchise (gas deregulat on report, 2006). public-private partnerships are often created as a result of this form of competition (electricity deregulat on report, 2006). 3. methods in the world economy, the method of price caps has started to be used since the second half of the 80s when the privatization of a number of natural monopoly firms took place in england. price cap regulation was first proposed by s. littlechild to control the prices of british telecom, the company that was privatized in 1984. as a result, in the 80’s the practice of price caps started to gain recognition in the united states. later on, price cap regulation was used in other countries as well. the main principle of the price cap approach is to set an upper boundary of the price that the regulated company can charge. the firm is allowed to set a price less or equal to the cap and to retain all of the resulting profits. as far as the restriction imposed on the firm is not tied to its costs and is not dependent on them, so the price cap serves as a mechanism that generates incentives to reduce costs. this model presupposes quite a long period between the reviews of the price caps. the duration of this period is clearly fixed in advance (usually the lag is 4–5 years). in a multicommodity situation, the object of regulation is the company’s total revenue divided by its cumulative output. the firm is allowed to change prices for products with the only condition that the average income does not exceed the established limit. this simplifies the calculation procedure, since it is not necessary to calculate the actual costs for the production of each type of product (jiménezpreciado et al., 2017). the price cap is calculated on the basis of a pre-established exogenous correction for the firm. frequently, such a correction ergunova, et al.: formation of the price mechanism for energy resources in russia and the countries of the european union international journal of energy economics and policy | vol 8 • issue 1 • 2018124 is the consumer price index rp minus the performance factor x, expressed as a percentage: pt+l=pr(rp-x) here pt is the base price for the previous period of time (month, year), pt+l is the price for the next period of time. this mechanism is called rp-x regulation. the value of x is determined on the basis of quantitative estimates of such factors as long-term demand, amount of capital investment, amount of profit from other (unregulated) activities, probability of cost reduction and productivity growth, as well as need for investment. the main advantage of the price cap model is that it is less prone to cost inefficiency and a tendency to overestimate the capital intensity than rate of return regulation model. producers are guaranteed to maintain the benefits of improving efficiency within the period between x reviews. natural monopoly gets incentives to increase production efficiency. in addition, the regulation procedure becomes much simpler and cheaper: the costs of collecting and analyzing information on the financial and economic activities of the regulated enterprise are significantly reduced. despite obvious advantages, the rp-x regulation has its own flaws (shepherd, 1999), including, in particular: (1) regulating authorities are often unable to determine accurately the value, (2) regulated firms tend to reduce the quality of products (quality control is necessary), (3) failure to respect a normal investment schedule (investments are made only at the beginning of the regulatory period). 4. data and estimation techniques according to official data, gas will provide the largest increase in electricity production in the 20-year term (scheme and program for the development of the unified energy system of russia for 2013–2019 approved by the ministry of energy order on july 19, 2013). according to gazprom, the average cost of gas production in the second quarter of 2016 was 1224 rubles per 1000 cubic meters (an increase of 81% as compared to the prices in the 2nd quarter of 2015), in the third quarter of 2015 was 802 rubles per 1000 cubic meters ($27.63), which is 38% higher than the average level of 2014–581 rubles ($19.14). the cost price in us dollars increased by 44%. the cost price of oil production is also steadily increasing, ranging from $15 to $25 per barrel (transportation costs included) for the third quarter of 2016. huge increase in cost price in 2015-2016 was caused by 272 rubles met rise from 237 to 509 rubles per 1000 m3 of gas and an increase in production costs. undoubtedly, high domestic price for oil and gas affects the growth of costs in russia, thus reducing the competitiveness of production (chart 1). gas price increase leads to corresponding growth in electricity cost, but at the same time the effect of replacement which is expected according to theoretical postulates, has not occurred yet. this may partly be due to government regulation of the industry implying relatively low tariffs for the population, which is possible by virtue of cross-subsidization at the expense of production works. 5. empirical results we have calculated how this state policy affects the electricity prices growth for the population (table 1). data for 2012 and price growth calculations are made by the author in november-december 2012. the average salary is given according to rosstat data for march 2012. the table shows that electricity price has grown 75 times compared to the soviet period. for instance, diesel fuel has risen in price 429 times, wages have increased by 182 times. only vodka price has risen less than electricity price. so, electricity costs are almost the same as accessible alcoholic beverages. as it follows from the above data, there is an actual decrease in electricity tariffs, compared to the tariffs in the ussr. moreover, the regulated tariffs for electricity that existed in the ussr did not contain an investment component. at the same time, the burden on population is growing and will grow in future as cross-subsidization is gradually being canceled in order to increase the production competitiveness. the increase in electricity prices is caused by the need to invest in the generation and development of the grid economy until domestic prices for consumers, other than the population, come around the european level with a discount of 10–15%. according to the ministry of economic development, this period will last until 2017–2018. in addition, the commissioning of new capacities until 2018 as well as large-scale investments in the power grid facilities will affect the increase in electricity prices. as a result, the electricity prices will undergo quite a high growth about 11% until 2016, and by 8–8.5% annually in 2017–2018. it turned out that households in russia pay less nowadays than in the ussr, less than europeans for gasoline, electricity chart 1: growth of gas and electricity costs in russia, 2011-2015, % ergunova, et al.: formation of the price mechanism for energy resources in russia and the countries of the european union international journal of energy economics and policy | vol 8 • issue 1 • 2018 125 and even diesel at present. it is understandable that prices for gas are at the same level as in europe (karacaer-ulusoy and kapusuzoglu, 2017). if we now bring the cost of electricity in proportion to the corresponding level of the soviet time (table 2), it will cost about 7.3 rubles per kilowatt-hour, which corresponds to 0.1825 €/kwh, which corresponds to european prices and newly confirms the validity of the author’s calculations. so, it is quite possible that tariffs will grow both for households and for both small and large business. if the practice of cross subsidization is maintained and the cost of electricity for both the population and business grows at the same rate, then the tariff for the population will sooner or later reach 4 rubles. but small business by then will have to pay 8 rubles per kilowatt, which will be one of the highest electricity tariffs in the world. 6. concluding remarks such prospects make it logical to replace the energy resource i.e., building their own generation facilities for consumers-households and for businesses. this approach is becoming more and more economically justified than centralized energy supply in the russian federation. and this trend will intensify due to the significant decrease in the cost parameters of generation (table 3). theoretically, it is possible and logical to switch to other types of fuel (kapitonov, 2012a) for example, to cheaper coal, as russia table 1: prices for some products according to statistical data and price lists (1970, 1985 and 2012) name of product price of goods, ruble price growth 1970-2012 1970 1985 10.2012 electricity, kwh 0.04rub. 0,04rub. 3,00rub. 75,0 diesel fuel, l 0.07rub. 0.11rub. 30.09rub. 429.9 gasoline ai-92. l 0.15rub. 0.17rub. 28.86rub. 192.4 bakery, kg 0.23rub. 0.27rub. 32.00rub. 139.1 sausage products, kg 2.22rub. 2.69rub. 330.00rub. 148.6 potatoes, kg 0.13rub. 0.15rub. 15.00rub. 115.4 zhigulevskoe beer, l 0.47rub. 0.51rub. 50.00rub. 106.4 vodka, 0.5 l 2.87rub. 4.12rub. 150.00rub. 52.3 copper wire, kg 1.81rub. 1.81rub. 409.00rub. 226.0 average salary 145.00rub. 190.00rub. 26 440.00rub. 182.3 source: data for 1970-1985 energy and industry of russia, no. 22 (162) november 2010: front page: electricity, vodka and beer cost the same in russia table 2: cost of gasoline, diesel, electricity and gas in the eu and in russia, 2012 countries gasoline, 95, € (10.12.2012) diesel, € (10.12.2012) electricity, € per 1 kw/h up to 3500 kw/year (01.05.2012) gas, € per 1 m3, consumption up to 1400 m3 (±25%) austria 1.392 1.390 0.1988 0.0702 belgium 1.656 1.501 0.2134 0.0574 bulgaria 1.248 1.268 0.0829 0.0428 czech republic 1.501 1.465 0.2850 0.0541 denmark 1.584 1.460 0.1480 0.1146 estonia 1.264 1.334 0.2982 0.0414 finland 1.603 1.529 0.0989 n/d france 1.650 1.481 0.1566 0.0583 germany 1.597 1.460 0.1412 0.0574 greece 1.683 1.433 0.2541 n/d hungary 1.421 1.494 0.1265 0.0568 ireland 1.584 1.554 0.1708 0.0506 italy 1.758 1.700 0.1920 0.0700 latvia 1.337 1.337 0.2031 0.0394 lithuania 1.392 1.309 0.1187 0.0433 luxembourg 1.330 1.234 0.1200 0.0516 malta 1.520 1.400 0.1707 n/d netherlands 1.811 1.511 0.1695 0.0727 poland 1.346 1.365 0.2208 0.0466 portugal 1.754 1.517 0.1488 0.0609 romania 1.218 1.235 0.1689 0.0285 slovakia 1.515 1.441 0.1095 0.0465 slovenia 1.484 1.402 0.1677 0.0670 spain 1.374 1.354 0.1447 0.0525 sweden 1.661 1.679 0.1959 0.1226 england 1.645 1.744 0.2098 0.0419 russia 0,7215 0,75225 0,075 0,09555 source: eu-25 data: european energy agency/european energy portal http://www.energy.eu/, in russia: rbc-rosstat http://quote.rbc.ru/news/macro/2012/11/23/33826363.html, federal tariff service data, http://www.fstrf.ru/tariffs/analit_info, calculations of the author, made at a rate of 40 rubles per 1 euro. eu: european union ergunova, et al.: formation of the price mechanism for energy resources in russia and the countries of the european union international journal of energy economics and policy | vol 8 • issue 1 • 2018126 has significant coal deposits. these two theoretically possible directions for the development of the national energy system of the russian federation are indirectly confirmed by data on commissioned capacities in the eu, where there is a gradual transition of the eu countries mainly to alternative energy sources and to some extent to coal (table 4). this transition is logical, as large energy-consuming industries need powerful power production plants and for this purpose new, more environmentally friendly and economical coal-fired power plants with introduced innovations in combustion and cleaning process are being introduced. it is possible to deliver coal from many regions; its deposits are also present in the eu itself. as for private households and enterprises that do not consume much energy, it is possible to switch to alternative energy (kapitonov, 2012b). this concept is confirmed by the theoretical transition of the developed countries to the so-called 6th technological order. russia has already missed the fifth technological order, but if it does not realize the necessity of the new transition now, it will irretrievably fail to gain high profits from energy supplies today, the money which could be directed to the advanced modernization of the economy to enter the sixth order tomorrow (kapitonov, 2012c). we can see the ongoing transformation of the global energy security system into a local-regional system based on innovations in energy consumption and production. both general theoretical postulates and practical steps taken by countries confirm this fact. the new system is maximally self-sufficient, based on energy saving, energy efficiency, applies innovative technologies for energy production, transportation and combustion of fuel; uses renewable energy sources in order to develop and conserve significant amounts of natural resources for future generations. the new regional-oriented energy security system leaves aside the mutual dependence of the supplier and consumer in the context of global energy security, focusing primarily on local-regional aspects of energy efficiency and energy security. 7. acknowledgments the research is carried out at tomsk polytechnic university within the framework of tomsk polytechnic university competitiveness enhancement program grant. references averch, h., johnson, l. (1962), behaviour of the firm under regulatory constraint. american economic review, 52, 1052-1069. brennan, m., schwartz, e. (1982), concistent regulatory policy under uncertainty. the bell journal of economics, 13, 506-521. demsetz, h. (1968), why regulate utilities? journal of law and economies, 11, 55-66. electricity regulation report. (2006), global-2006: energy market research reports: uk, london. available from: http://www.energymarket-research.info/free_energy_market_research_reports. shtml. pdf. [last retrieved on 2017 oct]. enerdata. (2012), available from: http://www.dhi.nic.in/writereaddata/ content/indian_mission_plan_2012-2022.pdf. [last accessed on table 3: existing and prospective cost benchmarks in the field of renewable energy in the world, average values indicators capital investments, $/kw cost of production, $ cent/kwh 2005 2030 2005 2030 biomass 1000–2500 950–1900 3.1–10.3 3.0–9.6 geothermal power engineering 1700–5700 1500–5000 3.3–9.7 3.0–8.7 traditional hydropower engineering 1500–5500 1500–5500 3.4–11.7 3.4–11.5 small hydropower engineering 2500 2200 5.6 5.2 solar photoenergetics 3750–3850 1400–1500 17.8–54.2 7.0–32.5 solar thermal power engineering 2000–2300 1700–1900 10.5–23.0 8.7–19.0 tidal energy 2900 2200 12.2 9.4 ground wind energy 900–1100 800–900 4.2–22.1 3.6–20.8 marine wind power 1500–2500 1500–1900 6.6–21.7 6.2–18.4 npp 1500–1800 3.0–5.0 coal fired hydroelectric power station 1000–1200 1000–1250 2.2–5.9 3.5–4.0 gas fired hydroelectric power station 450–600 400–500 3.0–3.5 3.5–4.5 source: international energy agency (iea), 2010 table 4: projects of capacities in europe, planned for commissioning in 2012-2022 year planned (gwt) authorized for construction (gwt) under construction (gwt) gas coal res residual atom gas coal res residual atom gas coal res residual atom 2012 4 2 12 1 2 6 0,5 9 2,5 0,2 2013 2 0.5 12 0.2 8 2 10 2.5 0.5 0.2 2014 7 2 14 0.4 2 0.5 0.2 0.5 2 0.5 0.1 0.1 2015 5 1.8 12 1 1 0.5 0.1 0.5 2 0.5 0.5 2016 7 32 4 0.8 0.2 1 0.5 0.1 0.5 0.5 2017 2 1 3 1 0.3 1 0.1 2018 3 1 3.2 1.5 0.1 1 2019-2022 0.2 14 14 2.5 0.2 0.2 source: enerdata, 2012 ergunova, et al.: formation of the price mechanism for energy resources in russia and the countries of the european union international journal of energy economics and policy | vol 8 • issue 1 • 2018 127 2017 jul]. gas regulation report. (2006), global-2006: energy market research reports: uk, london. available from: http://www.energy-marketresearch.info/free_energy_market_research_reports.shtml.pdf. [last retrieved on 2017 oct]. greenwald, r. (1980), admissible rate bases, fair rates of return and the structure of régulation. finance, 35, 359-368. international energy agency (iea). (2010), world energy outlook. available from: http://www.worldenergyoutlook.org/media/ weo2010.pdf. [last accessed on 2017 jun]. jiménez-preciado, a.l., cruz-aké, s., venegas-martínez, f. (2017), persistency of price patterns in the international oil industry, 20012016. international journal of energy economics and policy, 7(1), 9-18. kapitonov, i.a. (2012a), economics and safety of innovation-oriented energy sources introduction in russia and abroad. international economics, 4,  74-85. kapitonov, i.a. (2012b), ecological and economic problems and prospects for the transition to the sixth technological order in the world and in russia. bulletin of economic integration, 1,  86-91. kapitonov, i.a. (2012c), innovation-oriented energy basis for the formation of national competitiveness in the conditions of the world transition to the sixth technological order. bulletin of economic integration, 2,  58-62. karacaer-ulusoy, m., kapusuzoglu, a. (2017), the dynamics of financial and macroeconomic determinants in natural gas and crude oil markets: evidence from organization for economic cooperation and development/gulf cooperation council/organization of the petroleum exporting countries. international journal of energy economics and policy, 7(3), 167-187. korolkova, e.i. (2000), natural monopoly: regulation and competition. lecture 3. power engineering: regulation and competition. economic journal of the higher school of economics, 4, 528-551. posner, r. (1974), theories of economic régulation. the bell journal of economics, 5, 335-358. scheme and program for the development of the unified energy system of russia for 2013-2019 approved by order of the ministry of energy on july 19, 2013, 319. shepherd, w.c. (1999), the economics of industrial organization. illinois: waveland press. stgler, g. (1971), the theory of economic régulation. the bell journal of economics, 2, 3-21. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(5), 485-497. international journal of energy economics and policy | vol 10 • issue 5 • 2020 485 effect of oil revenues on government size in selected oil-exporters with an emphasis on iran’s economy davood danesh jafari, hamid nazemian, javid bahrami, mohammad hassan kheiravar* department of economics, faculty of economics, allameh tabataba’i university, tehran, iran. *email: m_kheiravar@atu.ac.ir received: 29 april 2020 accepted: 13 july 2020 doi: https://doi.org/10.32479/ijeep.10110 abstract as a huge source of wealth, oil can serve as the engine of, or a barriers to, economic growth in oil-rich countries. the important issue is how to manage oil revenues while taking into account the welfare of future generations as a foundation of sustainable development. on one hand, oil-exporters can lay the groundwork for sustainable development by allocating these revenues to infrastructural projects; on the other hand, they can create rents through corruption or mismanagement and thus create a strong barrier to the growth of macroeconomic indicators (sala-i-martin and subramanian, 2003). oil revenues have a significant role in iran’s economy and are the main source of government expenditures. oil accounts for the bulk of the country’s exports. one of the issues highlighted in iran’s 2025 vision is to cut the country’s dependence on oil revenues and finance spending through tax revenues, while allocating oil rents to efficient and productive investments. therefore, the present research uses generalized method of moments (gmm) and autoregressive distributed lag (ardl) to examines the effect of oil revenues on government expenditures and size in selected oil-exporting countries during 1980-2015 with an emphasis on iran’s economy. the results suggest that oil revenues, with a lag, have a significant positive effect on government expenditures and size in the selected oil exporters. moreover, in the case of iran, increase in oil revenues have significant short-run and long-run effects on government size. keywords: oil revenues, government size, generalized method of moments, oil-exporting countries, iran’s economy jel classification: q43 1. introduction access to natural resources is a major factor in the output and economic development of countries. therefore, resource-rich countries have an advantage in economic and political spheres. however, it is clear that the mere abundance of natural resources cannot bridge the existing gap beween a country and the world’s powerful economies. how to use the revenues from extracting natural resources, including oil, has always been a of interest to experts in economics, politics, and social sciences. the performance of resource-rich countries suggests that vast amounts of valuable natural resources can improve economic processes and contribute to economic development, but can also have devastating effects on the economy. for a country like norway, the wealth generated through oil sales has been a blessing, bringing about economic prosperity and welfare to the people. however, in countries like iraq and iran, a vast amount of foreign currency from oil and gas exports are injected into the economy beyond its capacity and become central to economic policies; as a result, not only does it increase government expenditures, but also expands government interventions in the economy and disrupts market performance. in most of these countries, these revenues are directly injected into the public sector to support government spending instead of being invested on infrastructures and institutions that would accelerate economic development. as evidence suggests, this process eventually leads to expansion of state power, state-owned monopoly, lack of competition, and suboptimal allocation of resources. this, in turn, places the economy in the hands of politicians, and oil and other natural resources are used as means of consolidating political power (sala-i-martin and subramanian, 2003). this journal is licensed under a creative commons attribution 4.0 international license jafari, et al.: effect of oil revenues on government size in selected oil-exporters with an emphasis on iran’s economy international journal of energy economics and policy | vol 10 • issue 5 • 2020486 this article is organized in four parts. the first part is the introduction; the second part presents the theoretical framework and a review of the literature; the third part provides the methods and the results, and the last part presents the conclusion and recommendations. 2. literature review 2.1. theoretical framework 2.1.1. different perspectives on government size and role in the economy government size and role has been a controversial topic among economists and political leaders since the classical period and adam smith’s theories in the 18th century. however, economic ideas and policies have changes significantly in the last century. in the classical school, market creates equilibrium and efficiency, and self-interest is pursued by taking into account the interests of the society. presence of the government in the economy limits freedom, prevents equilibrium, and reduces productivity. government is present only in cases of market inefficiency, such as lack of economic freedom, inequality and insecurity, violation of human rights and personal freedoms, monopolization, and unhealthy activities with no regard for social justice or antidiscrimination laws (naderan, 2002). the neo-classical perspective is quite different. especially with the evolution of economic theories in the 20th century, the government is allowed to interfere to correct deviation in the performance of economic actors through fixed taxes and transfer payments. market failure and imperfect competition justify government intervention. provision of public goods such as the legal system, national defense, public transportation, education, or addressing market failious such as monopolies, externalities as well as incomplete information and unfair distribution also justify government intervention. market is the top priority. only in the case of deviation from efficient distribution of resources does the government intervene. the government serves as the public defendant to maximize the welfare of the society (dadgar, 2001). in the 20th century, the old doctrine of economic liberalism, like other schools, was modernized and adapted to the new socioeconomic environment. economists acknowledged that the government plays a new role in the current state of world affairs; that is, it can use means other than economic mechanisms to remove obstacles and solve problems. this new school holds that freedom of natural prices is the best and most effective tool for regulating the economy and that government intervention can be detrimental. however, it also holds that government intervention is, at times, necessary to create the suitable environment for free and natural economic activity within limited, rational frameworks (khabazi et al., 2014). john maynard keynes, the prominent british economist, started a new chapter in the history of economic thought, especially with regards to theories of state intervention in economic affairs (al-qudair, 2005). regardless of the many components of the traditional economics model and the multitude of organizational and policy factors that had been carefully examined by economists, keynes managed to revive the relationship between economics and government policies. his explanation of the modern capitalist downturn with an imperfect market and a growing public sector lead to a new approach. perhaps the most important aspect of keynes’s scientific endeavor was his conceptualization of a new role for the government. keynes is the first capitalist economist who analyzed the importance and the growing capability of public sector in capitalism. according to the official theory, the role of the government in a market economy is to safeguard—i.e., enforce contracts, balance the budget, and maintain the stability of the currency. the new dimensions of the public sector and the new institutional organization of the private sector (especially the focus on production and the growth of trade unions) show that the economy can no longer simply play a passive role. keynes realized that state power enables the government to bring about economic prosperity by regulating tax policies and its costs (garrett and rhine, 2006). therefore, keynes’ work can be interpreted as a serious attempts to explain the importance of the state as a major actor in the economic environment and to recognize its new role, thus justifying the positive intervention of the government in the economy for a more optimal allocation of resources (khabazi et al., 2014). therefore, there is a disagreement between conventional perspectives on the role and size of the government. the degree of state intervention lies on a spectrum running from free market on one end to centralized planning on the other end. today, however, there are few instances of state intervention in one of these extremes, and often there are mixed economies. there is an extensive literature on state intervention in the economy. those who believe in the minimal role of the state argue that the state is allowed to intervene only where the private sector does not have the incentive or efficiency to invest, i.e., where the private sector fails. this includes public goods such as roads, public transportation, education, and health, but the state is not allowed in sectors of the economy that would lead to inefficient allocation of resources, disrupt market performance, or reduce welfare. therefore, despite the important role of the state in creating balance between the interests of the public and the private sector, it is only allowed to intervene in the economy where it does not create market imbalance or disrupt the market and simply create the infrastructure and policies needed to improve market performance. it must also be noted that greater government presence in the economy increases rent-seeking activities and reduces economic growth (heitger, 2001). 2.1.2. government size generally, there is a wide range of perspectives on government intervention from free market to centralized planning. in practice, however, countries have a mixed economy with a preference for one of these two extremes. government size is a measure of the role of the state budget in the economy. according to the latest world bank statistics, government size in different countries is not merely a product of their level of development. for example, government size is higher than 40% in developed countries such as france, uk, and italy, while in other developed countries such as singapore, canada, and the us, it is 13%, 18%, and 14% jafari, et al.: effect of oil revenues on government size in selected oil-exporters with an emphasis on iran’s economy international journal of energy economics and policy | vol 10 • issue 5 • 2020 487 respectively. therefore, what determines the level of development is not government size, but government spending. in iran, budget and off-budget interventions have played a critical role in the development process. these interventions can disrupt market efficiency and competition. the history of iran’s commodity, currency, credit, and energy markets has been a prime example of these inefficiencies. nevertheless, excessive government size negatively affects economic growth (gwartney et al., 1998) in two ways: (1) the bigger the size of the government, the more it will need to raise taxes and borrow to cover its costs, which reduces its financial resources as well as the private sector’s incentive to invest; (2) according to the law of diminishing returns, the bigger the government, the larger will be its activities, which leads to suboptimal allocation of resources in the economy; and (3) the public sector is slower than the private sector in responding to new information and the use of technologies, which lowers economic growth (bergh and karlsson, 2010). as a result, government size has always been of interest to economists and policymakers. there are various measures for determining government size, but two measures are most commonly used by researchers: share of government purchases (excluding transfer payments) in gdp, and government expenditures as a percentage of gdp (guerrero and parker, 2007; pajouyan, 2012). here, we use the ratio of government expenditures to gdp as the measure of government size. in iran, calculation of government expenditures includes current payments and development payments (ownership of capital assets) and excludes the budget of state-owned corporations, banks, and non-profit institutions. 2.1.3. comparison of government size in different countries as discussed earlier, a commonly measures of government size is the ratio of government expenditures to gdp. a review of the statistics of different countries in 2015 reveals that iran is ranked 9th in the world in the ratio of government expenditures to gdp (17.2%). the highest values largely belonged to advanced european economies such as finland (58%), france (57%), and denmark (56%). for the us and the uk, this ratio is 35% and 40% respectively. among neighboring developing countries, turkey has a ratio of 38%, which is more than twice the ratio for iran. comparison of economic regions shows that the ratio of government expenditures to gdp in iran is less than the average ratio of eu countries (47%), advanced economies (39%), emerging and developing economies (31.4%), latin america (35%), and even middle east and north africa (35.5%) (figure 1). these numbers suggest that the ratio of government expenditures to gdp shows iran to be a small government (economic review department report, 2016). 2.1.4. government size in iran in iran, government size has fluctuated in the last three decades and has been constantly affected by oil revenues, the iran-iraq war and post-war reconstructions, and economic sanctions. these effects are especially noticeable in the government’s dependence on oil revenues. studies show that government expenditures have increased with rising oil revenues and have decreased with drops in oil revenues. being affected by oil shocks has always lead to instability in iran’s economy and has resulted in excessive state interventions. fluctuations in government size in iran can be explained by examining the trend of expenditures as a percentage of gdp from 1989, i.e. the beginning of the 8-year war, to the present. in 1989 at the start of the fifth government (first development plan), government size was 20.2%, which decreased to 16.1% in 1992 at the start of the next government. however, in iran, government size has fluctuated in the last three decades and has been constantly affected by oil revenues, the iran-iraq war and post-war reconstructions, and sanctions. these effects are especially noticeable in the government’s dependence figure 1: government expenditures as a percentage of gdp in 2015 jafari, et al.: effect of oil revenues on government size in selected oil-exporters with an emphasis on iran’s economy international journal of energy economics and policy | vol 10 • issue 5 • 2020488 on oil revenues. studies show that government expenditures have increased with rising oil revenues and have decreased with drops in oil revenues. being affected by oil shocks has always lead to instability in iran’s economy and has resulted in excessive state interventions. fluctuations in government size in iran can be explained by examining the trend of expenditures as a percentage of gdp from 1989, i.e., the beginning of the 8-year war, to the present. between 1989 and 1992 during the terms of the fifth and sixth governments (the first development plan), government size decreased from 20.2% to 16.1% with some fluctuations. afterwards, however, government size increased mainly due to the increase in current and development expenditures, reaching 23% in 1997. during the terms of the seventh and eighth governments, government size fluctuated, but decreased from 23% to 20% over the 8 year period. until 1999, negative oil shocks and reduction in oil revenues lead to a proportional decrease in government size, while the subsequent economic boom increased government spending. however, his ratio decreased since the increase in gdp was greater than government expenditures. during the terms of the ninth and tenth governments, government expenditures dramatically increased, especially in the development sector in 2005, reaching the highest level in 2006 with a ratio of 26%. there were some fluctuations afterwards, but since 2011, economic and political sanctions has led to a significant decrease in oil revenues and, as a result, in the ratio of government expenditures to gdp. the financial resources of the government decreased with the drop in oil revenues, and despite the economic recession during this period, the decline in government expenditures was mainly due to the reduction in gdp, with this ratio reaching its lowest value in the last three decades in may 2013 (13%) (figure 2). 2.1.5. oil revenues and government size oil is one of the main sources of energy that has always played a critical role in the global economy and macroeconomic indicators, especially in oil-exporting countries. almost no activity is possible without energy and, at the moment, the global economy cannot continue to function without it. the unique role of oil revenues in the economies of oil exporters can be observed in the structure of their budgets and social programs. the governments of oil-rich countries gain a considerable share of their revenues through ownership and sales of this depletable resource. many economists argue that the use of oil revenues for current expenditures have adverse impacts on the economy like the dutch disease or the voracity effect (akinlo, 2012). in addition, large and unpredictable fluctuations in oil prices can make it difficult for oil exporters to determine the appropriate level of spending (habibi, 1998; eltony, 2002). plenty of studies have shown that resource-rich countries tend to have a much slower growth than resource-poor countries. this has been empirically proven as well and has been analyzed in a large body of research. there are also very poor countries that have abundant natural resources. therefore, understanding the roots of these failures can have significant implications for development in these countries (sachs and warner, 1995, 1999, 2001). economic growth slows down in economies that lack a strong legal-political institutional infrastructure and looks at oil as a source of revenue and economic consumption (tornell and lane, 1999). in these countries, a rise in oil revenues increases current expenditures, but with a drop in oil prices, the government cannot decrease its current expenditures immediately (villafuerte and lopez-murphy, 2010). therefore, it first offsets a portion of the drop in oil revenues by reducing its expenditures and development costs, but faces budget deficit in the medium-term, which leads to more borrowing and adverse impacts such as increased money supply and inflation (emami and adibpour, 2012). the problem is solved when these countries view oil as a source of wealth rather than revenue and invest the oil income on human and physical capital (gylfason, 2001). in general, oil rents create opposite forces in the economy, the sum of which is determined by the institutional infrastructure of the country and by the management of these revenues. if the management of oil revenues is led and supervised by an efficient structure, we can expect the economy to grow and macroeconomic variables to improve. however, in an state with poor institutional infrastructure and extensive bureaucracy, oil revenues lead to the resource curse and have adverse impacts on the economy. therefore, oil revenues play an important role in the economy of oil-exporting countries, especially iran, where oil revenues are the main source of government expenditures and have the largest share of exports. in recent years, oil and gas has accounted for about 60% of government revenues and 80% of exports in these economies. given the importance of oil revenues and their impact on welfare programs, it is important to examine their impact on government size. oil revenues affect government expenditures, the structure of the economy, and government behavior in iran (pazoki, 2012). however, regardless of the rise in oil prices and government revenue in recent years, iran is faced with many problems in carrying out economic projects. given that iran is the third largest oil producer among opec countries, its economy is largely dependent on oil and greatly affected by oil price shocks. rising oil prices in recent years has led to an increase in oil revenues and government expenditures. however, there have been international pressures to limit iran’s oil exports and investments in oil-related projects, and these sanctions have had negative impacts on iran’s oil industry. therefore, oil revenues act as a key variable that determine government spending for current and development costs (mehrara, 2008). as the main recipient of oil revenues, the iranian government must distribute oil revenues within the economic structure and pay various types of subsidies. given the importance of these issues, the present study investigates the effects of oil revenues on the size of government in selected oil-exporting countries with an emphasis on iran’s economy. trends in the last 27 years indicate fluctuations in government size in iran. the reason for this ebb and flow is entirely related to government spending. government size has been affected by changes in oil prices and spending of oil revenues (falahi, 2011).statistical analysis show jafari, et al.: effect of oil revenues on government size in selected oil-exporters with an emphasis on iran’s economy international journal of energy economics and policy | vol 10 • issue 5 • 2020 489 authors aim method time period result bachmeier (2008) examining the role of monetary policy in the transmission of oil shocks to the us economy var model 1986-2003 oil shocks have had a negative effect on stock returns reyes-loya and reyes (2008) examining the relationship between government expenditures, tax revenues, oil revenues, and industrial production index in mexico arima model 1990-2007 there is an inverse relationship between oil-related revenues and tax revenue from non-oil sources chun (2010) exploring the impact of oil revenue on the national defense spending of five oil-exporting countries (iran, saudi arabia, kuwait, venezuela, and nigeria) measuring elasticity of demand 1997-2007 in each of these countries, the demand for military spending is largely inelastic, meaning that attempts to limit defense spending by tinkering with oil revenues are likely to fail mehrara et al. (2010) studying the non-linear relationship between oil revenues and real output growth of the iranian economy ecm model 1959-2007 the response of economic growth to oil revenue growth in low regimes of oil revenues is greater than in high regimes of oil revenues hassani and nojoomi (2010) examining the factors that determine iran’s oil revenues ardl model 1970-2008 factors such as oil production, oil price, and oil proved reserves have long-run effects on iran oil export revenues. the effects of variables such as domestic oil consumption and world oil production are negative farzanegan (2011) analyzing the dynamic effects of oil shocks on different categories of the iranian government expenditures var model 1959-2007 iran’s military and security expenditures significantly respond to a shock in oil revenues (or oil prices), while social spending components do not show significant reactions to such shocks shahnazi et al. (2011) examining the effect of oil revenues on government fiscal policy uzawa-lucas model optimal policy requires making use of subsidies to invest in human and physical capital. human capital can be financed by oil revenues and income tax, and physical capital can be financed by oil revenues alone. government size depends on oil revenues: as the share of oil revenues in gdp or the ratio of oil revenue to physical capital increases, government size increases and vice versa garkaz et al. (2012) examining the relationship between oil revenues and government expenditures wavelet analysis 1996-2007 there is a significant positive relationship between oil revenues and government expenditures in the long run hamdi and sbia (2013) examining the dynamic relationships between oil revenues, government spending, and economic growth in the kingdom of bahrain panel var model 1960-2010 oil revenues are the principal source for growth and the main channel which finances government spending aregbeyen and kolawole (2015) examining the relationships among oil revenue, government spending, and economic growth in nigeria ols model 1980-2012 oil revenue granger caused both total government spending and growth, while there was no-causality between government spending and growth in the country. thus, government should increase spending on capital projects and intensify efforts at increasing output in the oil sub-sector in order to boost economic growth in nigeria ahmad and masan (2015) examining the dynamic relationships between oil revenue, government spending, and economic growth in oman var model 1971-2013 there is a long-run relationship between the real gdp, the real government expenditure, and the real oil revenues. government expenditure appears to be the main source for long-run economic growth, and in the short run, variations in government expenditure are generally derived by oil revenue shocks ghadiri (2000) analyzing the determinants of economic growth in iran ardl model 1971-1996 fiscal policies and oil revenues encourage economic growth, while monetary policies have negative impacts on economic growth farhangi and shirkavand (2011) examining the effect of oil revenues on economic management process in iran statistical analysis 1994-2004 oil revenues have adverse effects on iran’s economy and have led to inefficient economic management in the country arsalani (2011) investigating the role of oil price and oil revenues in iran’s economy and their relationships with macroeconomic variables 1963-1999 when oil price rises, foreign exchange earnings from oil increases, leading to an increase in the government budget mehnatfar (2004) examining the factors that increase current costs of iran’s government ols model 1959-2001 tax revenues and oil revenues significantly increase government expenditures table 1: a review of relevant studies (contd...) jafari, et al.: effect of oil revenues on government size in selected oil-exporters with an emphasis on iran’s economy international journal of energy economics and policy | vol 10 • issue 5 • 2020490 authors aim method time period result mehrara and oskoui (2006) examining the dynamic effects of oil shocks on economic variables in four oil-exporting countries (iran, indonesia, kuwait, and saudi arabia) svar model 1960-2003 the degree of outsourcing oil revenues is higher in saudi arabia and kuwait than iran. moreover, oil price shocks are the most important source of gdp fluctuations in saudi arabia and iran. iranian and saudi economies are more dependent on, and susceptible to, oil revenues than the other two economies renani et al. (2006) investigating the relationship between financial decentralization and government size in iran statistical analysis 1989-2003 financial decentralization of expenditures is negatively related to the size of the central government, but positively related to the size of provincial governments. moreover, estimation of the parameters of the control variables show that the effect of oil and gas revenues on government size is insignificant esmailnia (2012) examining the effect of oil shocks on government expenditures in iran’s economy var model 1965-1999 military and social security expenditures have a significant positive response to oil revenue (or oil price) shocks. other social expenditures do not significantly respond to shocks. moreover, iran’s military activities are highly sensitive to unexpected negative shocks. therefore, sanctions aimed at limiting iran’s oil export capacity can have significant effects on iran’s military spending, but no significant effect on education healthcare, and cultural expenditures emam et al. (2013) effects of oil revenues on spending behavior and government size in iran gmm model 1971-2011 there is a significant positive relationship between oil revenues and government size in iran. oil revenues have significant positive effects on military and cultural spending, while education, healthcare, and social security expenditures are not affected by oil shocks. since about 49% of government expenditures are military expenditures, this is the sector that is most affected by oil shocks mohammadi and barat (2013) examining the effect of shocks from reduction in oil revenues on government spending and money supply in iran var model 1970-1990 oil revenue shocks have significant effects on development and current expenditures of the government as well as the money supply zonouzi et al. (2014) examining the effect of oil revenues on good governance in selected opec member countries panel model 1996-2011 oil revenues have a significant negative effect on good governance, suggesting the negative impact of oil revenues on corruption control, political stability, and accountability. oil revenues also have a negative effect on government effectiveness and the quality of laws and a positive effect on the rule of law, but these effects are not significant komijani and nazari (2015) examining the effect of oil revenues on government expenditures in iran var model 1974-2011 oil revenues have significant positive effects on government expenditures (total, consumption, and development), both in the short and long run table 1: (continued) that government size fluctuated within a specific interval from 1989 to 2005 (16%-23%). however, with rising oil prices and a shift in the approach to spending oil revenues, government expenditures in the budget has grown since 2005. in 2006, government size reached its highest level in 27 years at 26%. in 2013, sanctions and the reduction in oil revenues led to a decline to record lows in government expenditures in the development sector. although there was an economic recession in this period, the decline in government expenditures has mainly been due to the reduction in gdp. 2.2. literature and empirical evidence a review of literature review and relevant studies are presented in table 1. 3. methodology and results 3.1. analysis and results for selected oil-exporting countries this section examines the relationship between oil revenues and government size in selected oil-exporting countries. 3.1.1. stationarity test the first step in time series estimation is testing for stationarity of the variables, as non-stationary series in econometrics estimations lead to spurious regression and the results will not be reliable or interpretable. unlike time series data, panel data cannot be tested for stationarity using the dickey–fuller test or augmented dickey– jafari, et al.: effect of oil revenues on government size in selected oil-exporters with an emphasis on iran’s economy international journal of energy economics and policy | vol 10 • issue 5 • 2020 491 fuller test (ashrafzadeh and mehregan, 2010). for panel data, the levin-lin-chu test (llc), the im-pesaran-shin test (ips), fisheradf, the phillips–perron test, the choi test, the breitung test, and the hardi test have been proposed. in this research, llc is used to test for stationarity of the variables with the following hypotheses: • h0: variable contains a unit root • h1: variable is stationary. if the absolute value of the test statistic is less than the absolute value of critical values and/or the test probability is less the 0.05, the null hypothesis is rejected and the variable is stationary. the results of this test are provided in table 2. the results of the llc test indicate that the probability of the test statistic is <0.05 for all the variables. this suggests that the null hypothesis is rejected and the variables are stationary. therefore, the log of all the variables are stationary at the level of data, and the results of model estimation are reliable enough for interpretation. 3.1.2. results of model estimation the generalized method of moments (gmm) is one method for estimating model parameters in the dynamic panel data approach that can be used for time series, cross-sectional, and panel da-ta. gmm accounts for the dynamic adjustments of the dependent variable. a dependent variable with lagged values causes a correlation between explanatory variables (regressors) and error terms, and thus using ordinary least squares (ols) will lead to biased and inconsistent results. gmm can solve this problem by using instrumental variables. the following dynamic model is the mathematical expression of gmm: ´ 1 it it it i t ity y x   −= + + +∅ + (1) where y is the dependent variable, x is the vector of explanatory variables, η denotes individual and country fixed effects, ∅ is the fixed effect of time, ε is the error term, i denotes country, and t denotes time. in equation 1, it is assumed that error terms are not correlated with individual and country fixed effects and lagged values of the dependent variable. if η is correlated with some of the explanatory variables, one way to remove individual and country fixed effects is through first-order differencing; otherwise, using the fixed effects model will lead to biased estimators from coefficients. therefore, equation 1 is converted to the following: ´ 1it it it t ity y x  −∆ = ∆ + ∆ + ∆∅ + ∆ (2) in this equation, the lagged difference of the dependent variable (∆yit-1) is correlated with the first order difference of error terms (∆εit). there is also the problem of endogeneity for some of the explanatory variables, which is not accounted for in the model. therefore, it is necessary to use instrumental variables to address this problem. the following moment is true about equation 2: ( ) 0 ; 2; 3, 4, ,u s ite y s t t− ∆ = ≥ = … (3) ( ) 0 ; 2; 3, 4, ,u s ite x s t t− ∆ = ≥ = … (4) the following matrix of instrumental variables is used to estimate the parameters of equation 2: ( )1 2 2 1 2 2, , , , , , ,i i i it i i itz diag y y y x x x− −= … … (5) the estimators of gmm ̂ are defined as follows: 1)ˆ ( n nb za z b b za z y −= ′ ′ ′ ′ (6) after estimating the coefficients, it is necessary to use the sargan test to examine the validity of the instrumental variables that are incorporated into the model and test for over-identification of the equation. in addition, the order of autocorrelation in error terms must be determined, since first-order differencing is effective only when autocorrelation in error terms is not of the second order. the sargan test (1958) has an asymptotic x2 distribution, which is defined as: ´ 1 1 ˆ ˆ( ) n i i i i s z z h z z − = ′ ′= ∑ (7) in this test, ˆˆ y x = − , ̂ is a k×1 matrix of estimated coefficients, is a matrix of instrumental variables, and h is a square matrix with (t-q-1) dimensions, where t is the number of observations and is the number of explanatory variables in the model. if the null hypothesis of the test is not rejected, the instrumental variables are valid and sufficient. otherwise, more appropriate instrumental variables must be defined for the model (baltagi, 2005). table 3 shows the results of model estimation for the effect of oil revenues on government size using arellano-bond dynamic panel data model in selected oil-exporting countries over the period 1980-2015. estimation is done in stata. the results of estimating the first model show that government size (government expenditures as a percentage of gdp) with one lag and a coefficient of 0.623 has a significant positive effect on government size in the next period. that is, an increase in government size in the previous period significantly increases government size in the current period. oil revenues with a coefficient of −0.031 have no significant effect on government size in the selected oil-exporting countries. that table 2: the results of unit root test using llc variable proxy test conditions test statistic p value log of government size lgovsize with intercept and trend −3.32 0.0004* log of oil revenues loilrev with intercept and trend −1.80 0.0359** log of economic openness lopen without intercept and trend −3.11 0.0009* log of income per capita lypc with intercept and trend −2.00 0.0224** source: present research calculations; * and ** indicate significance at the 0.01 and 0.05 levels jafari, et al.: effect of oil revenues on government size in selected oil-exporters with an emphasis on iran’s economy international journal of energy economics and policy | vol 10 • issue 5 • 2020492 table 3: the results of estimating the first model: effect of oil revenues on government size in selected oil-exporting countries (dependent variable: government size) variable proxy coefficient t-statistic p value intercept c 0.186 0.83 0.407 log of government size with one lag lgovsize(-1) 0.623 16.92 0.000* log of oil revenues loilrev −0.031 −1.14 0.254 log of oil revenues with one lag loilrev(−1) 0.057 2.18 0.0029* log of economic openness lopen −0.056 −1.76 0.079** log of income per capita lypc −0.118 −3.39 0.001* sargan test statistic: 449; sargon test probability: 0.2976; wald chi-squared test statistic: 456; wald test probability: 0.000. source: present research calculations; * and ** indicate significance at 0.01 and 0.1 respectively table 4: the results of augmented dickey-fuller test (adf) variable proxy test conditions test statistic p value result government size lgovsize dlgovsize without intercept and trend without intercept and trend 0.28 −4.18 0.7634 0.0001* i(1) oil revenues loilrev dloilrev without intercept and trend without intercept and trend 0.24 −6.09 0.7521 0.0000* i(1) economic openness lopen dlopen without intercept and trend without intercept and trend −0.97 −4.41 0.2864 0.0001* i(1) income per capita lypc dlypc without intercept and trend without intercept and trend −3.26 −4.11 0.0910 0.0146** i(1) source: present research calculations; * and ** indicate significance at 0.01 and 0.05 respectively is, current oil revenues have no significant effect on government expenditures and size in the selected oil-exporting countries. oil revenues with one lag and a coefficient of 0.057 have a significant positive effect on government size in the current period. in oil-exporting countries, rising oil revenues in the previous period affect government expenditures in the next period through the budget, and these governments adjust their future expenditures based on their current oil revenues. therefore, increase in oil revenues have a significant positive effect on government expenditure and size. economic openness with a coefficient of −0.056 has a significant negative effect on government size in the selected oil-exporting countries at the 0.1 significance level. also income per capita with a coefficient of −0.118 has a significant negative effect on government size. the results of sargan test for examining the validity of the instrumental variables used in the arellano-bond panel data model suggest that these variables are indeed valid (p = 0.2976). 3.2. results from iran’s economy this section examines the relationship between oil revenues and government size in iran. 3.2.1. stationarity test it is again necessary to test for stationarity before estimating the model. the augmented dickey-fuller test is used and the results are provided in table 4. as the data in table 4 show, government size, oil revenues, economic openness, and income per capita are not stationary at the level of data and are stationarized through differencing. therefore, all the variables have a cointegration degree of one, and ardl is used to examine short-run and long-run relationships as well as cointegration of the variables. 3.2.2. short-run model of the effect of oil revenues on government size in model estimation using ardl, first the dynamic model (shortrun) must be estimated (table 5). the optimal variable lag is ardl(0,0,0,1) based on the schwarz-bayesian criterion. as the data in table 5 show, government size with one lag and a coefficient of 0.15 has a positive effect on government size in the current period, but the effect is not statistically significant. oil revenues and income per capita with coefficients of 0.14 and 0.48 respectively have significant positive effects on government size in the short run. that is, rising oil revenues and income per capita significantly increase government expenditures and government size. the results also show that economic openness with a coefficient of −0.60 has a significant negative effect on government size in the short run. in estimation of time series models, serial autocorrelation, nonnormal distribution of the residuals, incorrect functional form, and heterogeneity of variance are major problems that undermine the results. normal distribution of residuals, serial autocorrelation, homogeneity of variance, and functional form are examined using the jarque-bera test, the breusch-godfrey test, the breusch-pagangodfrey test, and the ramsey test respectively. table 6 provides the results of diagnostic testing of these classical assumptions. the results of the breusch-godfrey lm test show that the null hypothesis for lack of serial autocorrelation is true, as the probability of the test statistic is >0.05 (0.3442). the results of ramsey’s test for functional form indicate that the probability of the test statistic is >0.05 (0.1331); thus, the null hypothesis is true and the model has correct functional form. jafari, et al.: effect of oil revenues on government size in selected oil-exporters with an emphasis on iran’s economy international journal of energy economics and policy | vol 10 • issue 5 • 2020 493 percent increase in economic openness decreases government size by 0.71 in the long run. therefore, increase in trade and economic openness decreases government size in iran. 3.2.4. error correction model the short-run fluctuations of the variables can be examined using an error correction model and their long-run relationships can be discussed. the results of estimating the error correction mod-el (ecm) are provided in table 8. the data show that the coefficient of the error correction term is -0.84 and statistically significant. therefore, we can conclude that the speed of adjustment toward a long-run relationship is very high in the estimated model. therefore, the model quickly adjusts itself toward a long-run relationship. 3.2.5. structural stability test the structural stability and robustness of the estimated coefficients of the model are examined using cusum and cusumsq tests. the results are provided in figures 3 and 4. as these the results of cusum test show, the cumulative sum of recursive residuals fall inside the critical bounds. therefore, the estimated model has no structural breaks and the coefficients are stable during the studied period. the results of cusumsq test show that the cumulative sum of recursive residuals fall inside the critical bounds and, therefore, the estimated model does not have a structural break. 4. conclusion and implications as a strategic commodity, oil plays a significant economic and political role. world’s economy has experienced considerable fluctuations in oil prices in the last half the 20th century. oil price volatility has had direct and indirect effects on many macroeconomic variables in oil-exporting countries, thus posing new challenges to officials in these countries by creating macroeconomic instability. rising oil prices stimulates the economy of these countries from both demand and supply sides— from the demand side through the state budget and from the supply side by affecting public and private investments—which, in turn, accelerate or decelerate their economic growth. the sum of these effects is referred to as the net effect of oil revenues on table 5: the results of estimating the short-run model of the effect of oil revenues on government size variable ardl(0,0,0,1) coefficient t-statistic p-value c 14.41 4.35 0.0002* lgovsize(-1) 0.15 1.23 0.2281 loilrev 0.14 1.87 0.0712*** lypc 0.48 1.90 0.0668*** r2=0.96; r 2̅=0.96; f statistic=199; p value=0.000. source: present research calculations; * and *** indicate significance at 0.01 and 0.1 respectively table 6: diagnostic testing test statistic p value breusch-godfrey lm test for serial correlation 1.10 0.3442 ramsey’s test for functional form 1.54 0.1331 jarque-bera test of normality 0.56 0.7524 breusch-pagan-godfrey test for homogeneity 0.77 0.5506 source: present research calculations table 7: the results of estimating the long-run model of the effect of oil revenues on government size in iran variable coefficient t-statistic p value c 17.04 8.49 0.0000* loilrev 0.17 2 0.0539*** lopen −0.71 −12.9 0.0000* lypc 0.57 1.76 0.0874*** source: present research calculations; * and *** indicate significance at 0.01 and 0.1 respectively table 8: the results of estimating the error correction model variable coefficient t-statistic p value ecm(−1) −0.84 −24.6 0.0000 source: present research calculations the jarque-bera test is used to examine the distribution of residuals. given that the probability of the test statistic is >0.05 in each model (0.7524), the null hypothesis is true and the error terms are normally distributed. finally, results of the breusch-pagan-godfrey test for homogeneity of variance show that the probability of the test statistic is >0.05 (0.5506), indicating that the null hypothesis is true and the model has homogeneity of variance. 3.2.3. long-run model of the effect of oil revenues on government size bounds testing is used to test for the presence of long-run relationships between the variables. this approach provides an upper and a lower bound, and test statistics higher than the upper bound critical value confirm the presence of a long-run relationship. the results of bounds testing indicate that the lower and upper bounds are 3.23 and 4.35 respectively at the 0.01 significance level, and the f-statistic is 4.52. thus, the f-statistic is greater than the upper bound and the presence of long-run relationships and cointegration is confirmed. the results of estimating the long-run model are provided in table 7. the results of estimating the long-run model show that oil revenues with a coefficient of 0.17 have a significant positive effect on government size in iran at the 0.05 significance level. that is, one percent increase in iran’s oil revenues increases government size by 0.17 in the long run. therefore, oil revenues increase government size in iran. income per capita with a coefficient of 0.57 has a significant positive effect on government size in the long run at the 0.1 level. that is, one percent increase in income per capita increases government size by 0.57 in the long run. therefore, income per capita increases government size in iran. economic openness with a coefficient of −0.71 has a significant negative effect on government size in the long run. that is, one jafari, et al.: effect of oil revenues on government size in selected oil-exporters with an emphasis on iran’s economy international journal of energy economics and policy | vol 10 • issue 5 • 2020494 figure 4: the results of the cusumsq test figure 3: the results of cusum test figure 2: government size in iran jafari, et al.: effect of oil revenues on government size in selected oil-exporters with an emphasis on iran’s economy international journal of energy economics and policy | vol 10 • issue 5 • 2020 495 the economy. oil revenues make up a large portion of government revenues and government expenditures. therefore, government size in oil-exporting countries is affected by oil revenues. oil and gas exploration has been the source of many of the rapid socioeconomic changes that have occurred in iran over the last century. oil has been woven into the fabric of iran’s economy and oil production and revenues have been the main agent of change, whether positive or negative. it scope beings at the level of government expenditures and political power and continues by affecting the balance of payments, domestic demand, growth of financial and monetary markets, and eventually, economic growth. current economic statistics also confirm the dominant role that the oil industry still plays in iran’s economic structure, and today, like most countries that produce hydrocarbon resources, oil revenues are the main drivers of the economy in iran. these revenues usually have two different, but related, roles in the iranian economy. first, as a key source of foreign exchange, oil revenues enable the country to import various capital, intermediate, and consumption goods. secondly, they make up a considerable portion of government revenues and are used to finance current and development expenditures. given the impact of the export of crude oil and oil products on iran’s economy and the financing of a major portion of public spending through oil revenues, the performance of the oil sector is of special importance. one of the most important issues facing the country’s financial system is the dependence of tax revenues and other sources of government earnings on oil revenues. that is, rising oil revenues increase direct and indirect revenues, allowing the government to expand its size. the lack of discipline in iran’s public sector as a structural problem has always exacerbated this issue. therefore, if oil revenues are not properly managed, they can undermine the macroeconomics, budgeting structure, and governance of the country, thus resulting in waste of resources. the economic situation of many other oil-rich economies confirms this notion, which is extremely alarming. oil revenues has often led to the resource curse, revenues which will not last for a very long time. these revenues must benefit future generations, but they are often not devoted to sustainable development. to avoid such a fate for this unprecedented opportunity, special, and sometimes, creative policies are required. despite these adverse effects, proper management of oil exploration, extraction, and exports can accelerate economic growth and the country’s development (gylfason, et al. 1999). in order to stabilize economic and social developments upon oil and gas sectors, revenues must be managed in such a way as to reinforce other sources of wealth. of course, given that the future value of hydrocarbon resources is largely uncertain due to being non-renewable, managing these revenues is a critical and complicated challenge. addressing this challenge requires developing meticulous policies that can serve as a useful guide for investing or saving oil revenues so that, eventually, implementation of these policies would increase the efficiency of macroeconomic management in the face of various opportunities and barriers. moreover, national policies in the oil and gas sectors require a proper framework to facilitate sustainable management of revenues from these natural resources. these policies generally aim to reduce any adverse effect on the economy by providing the details of how to manage predicted oil revenues and integrate them into existing government systems. they require the highest standards of transparency and accountability in management of hydrocarbon revenues and must recommend the appropriate institutional and governance structures to allow for optimal use of these revenues. in this article, a model was proposed to examine the effect of oil revenues on government size in selected oil-exporting countries with several variables, including oil revenues, economic openness, income per capita, and government expenditures as a percentage of gdp (a measure of government size). first, the levin-lin-chu (llc) unit-root test was performed to test for stationarity. the results showed that were stationary at the level of data (p = 0.05). in the next step, the generalized method of moments (gmm) was used to estimate the relationship between oil revenues and measures of macroeconomic stability in selected oil-exporting countries. the results suggested that oil revenues with a lag and a coefficient of 0.057 have a significant positive effect on log of government size; that is, rising oil revenues in selected oil-exporting countries positively affect government size with a 1-year lag. also the results of the sargan test showed that the instrumental variables incorporated into the arellano-bond panel data model were valid. as for iran’s economy specifically, the results of stationarity test showed that all the variables contained a unit root and were stationarized by differencing. thus, the variables were i(1) stationary. subsequently, short-run and long-run relationships between the variables were examined using the autoregressive distributed lag (ardl) approach. the results of short-run estimation of the effect of oil revenues on government size in iran showed that oil revenues have a significant positive effect on government size (0.14). in fact, in the short run, increase in oil revenues increases the current size of the government. the results of long-run model estimation showed that log of oil revenues has a significant positive effect on government size (0.17). the coefficient of the error correction term was −0.84 and was statistically significant. this suggested that the speed of error adjustment toward a long-run relationship was very high and the model quickly adjusts itself to a long-run relationship. in addition, the results of cusum and cusumsq showed that the sum of sum of recursive residuals fall inside the critical bounds and, therefore, the estimated model had no structural break and the estimated coefficients were stable in the studied period. nonetheless, it must be recognized that dependence of the government on oil revenues and the fluctuations and uncertainties of the oil market are major challenges that iran as an oil ex-porter faces. iran’s forex reserves account was established at the beginning of the third development plan to prevent or reduce the negative effects of strong fluctuations in the global price of crude oil on the economy and government budgets. however, the balance of the foreign exchange reserves and frequent withdrawals indicate the reality that oil price fluctuations can still threaten iran’s macroeconomic jafari, et al.: effect of oil revenues on government size in selected oil-exporters with an emphasis on iran’s economy international journal of energy economics and policy | vol 10 • issue 5 • 2020496 stability. one of the goals of iran’s 2025 vision is for the country to become the strongest economic, technological, and scientific power in the middle east. an important issue highlighted in this document is to reduce the country’s dependence on oil revenues for financing current spending and instead use tax revenues, and to allocate oil revenues to efficient and productive investments. below are the implications of the present findings for practice: 1. a portion of oil revenues must be allocated to development projects to increase and expand the economic infrastructure of the country. of course, these investments must be done in areas where the private sector is not allowed, capable, or willing to get involved 2. since it is impossible to suddenly cut oil revenues from the budget, it is better to finance the current expenditures of the country through tax revenues 3. there must be a transition from an economy that is entirely dependent on oil revenues to a knowledge-based economy that benefits from the oil industry. given the fluctuations in oil prices and oil revenues, it seems that the discourse on “economy without oil” should not merely be a slogan, but rather guide the behavior and economic policies of the country 4. fundamental measures and changes need to be made within the government’s structure to reduce its expenditures, since a drop in oil revenues leads to serious budget deficits with grave consequences for the economy. references ahmad, a., masan, s. (2015), dynamic relationships between oil revenue, government spending and economic growth in oman. international journal of business and economic development, 3(2), 93-115. akinlo, a.e. (2012), how important is oil in nigeria’s economic growth? journal of sustainable development, 5, 165-179. al-qudair, k.h.a. (2005), the relationship between government expenditure and revenues in the kingdom of saudi arabia: testing for cointegration and causality. jkau: economics and administration, 19(1), 31-43. aregbeyen, o., kolawole, b. (2015), oil revenue, public spending and economic growth relationships in nigeria. journal of sustainable development, 8(3), 1-10. arsalani, a. (2011), effect of oil price on macroeconomic variables in iran from 1963 to 2000. doctoral dissertation, faculty of economics. iran: university of tehran. ashrafzadeh, h., mehregan, n. (2010), econometyrics; panel datya. tehran: tehran university publications. bachmeier, l. (2008), monetary policy and the transmission of oil shocks. journal of macroeconomics, 30, 1735-1755. baltagi, b. (2005), econometric analysis of panel data. 3rd ed. london: john wiley & sons ltd. bergh, a., karlsson, m. (2010), government size and growth: accounting for economic freedom and globalization. public choice, 142(1-2), 195-213. chun, c.k.s. (2010), do oil exports fuel defense spending? strategic studies institute (ssi). united states: army war college. dadgar, y. (2001), literature on the role of government in economy. culture of thought, 2, 7-21. economic review department report. (2016), chamber of commerce. tehran, iran: economic review department report. eltony, n.m. (2002), oil price fluctuations and their impact on the macroeconomic variables of kuwait: a case study using var model for kuwait. available from: https://www.arbiapi.org/wps9908. pdf. emam, v.g., karimi, m., mousavi, s. (2013), explaining the effects of oil revenues of spending behavior and government size in iran. in: proceedings of the 1st national conference on oil and economic development, faculty of economics. tehran: allameh tabatabaei university. emami, k., adibpour, m. (2012), oil income shocks and economic growth in iran. economic modelling, 29(5), 1774-1779. falahi, m. (2011), the relationship between economic growth and government size in selected opec countries: a multivariate analysis using panel data techniques. value economy, 8(2), 79-94. farhangi, a., shirkavand, s. (2008), effect of oil revenues on economic management process in iran: 1974-2001. iranian journal of knowledge management, 21(80), 93-104. farzanegan, m.r. (2011), oil revenue shocks and government spending behavior in iran. energy economics, 33(6), 1055-1069. garkaz, m., azma, f., jafari‏, r. (2012), relationship between oil revenues and government expenditure using wavelet analysis method: evidence from iran. economics and finance review, 2(5), 52-61. garrett, t.a., rhine, r.m. (2006), on the size and growth of government. federal reserve bank of st. louis review, 88(1), 13-30. ghadiri, a. (2000), analysis of the determinants of economic growth in iran, master’s thesis. iran: shahid beheshti university. guerrero, f., parker, e. (2007), the effect of federal government size on long-term economic growth in the united states, 1792-2004. unr economics working paper series, working paper no. 07-002. gwartney, j.d., lawson, r., holcombe, r.g. (1998), the size and function of government and economic growth. washington, d.c: joint economic committee study. gylfason, t. (2001), natural resource, education and economic development. european economic review, 45, 847-859. gylfason, t., herbertsson, t., zoega, g. (1999), a mixed blessing: natural resources and economic growth. macroeconomic dynamics, 3, 204-225. habibi, n. (1998), fiscal response to fluctuating oil revenues in oil exporting countries of the middle east. cairo: erf working paper no. 0136. hamdi, h., sbia, r. (2013), dynamic relationships between oil revenues, government spending and economic growth in an oil-dependent economy. economic modelling, 35, 118-125. hassani, m., nojoomi, a. (2010), an ardl model of factors determining iran’s oil export revenues (1971-2008). international review of business research papers, 6(5), 17-35. heitger, b. (2001), the scope of government and its impact on economic growth in oecd countries. russia: institute of world economics. heydari, h., parvin, s., fazeli, m. (2010), the relationship between government size and economic growth; a case study: opec countries at the persian gulf margin. value economy, 3, 43-66. khabazi, m., janati, m.a., ghasemi, m. (2014), the effect of oil revenues on government size and economic growth in selected countries (iran, norway, saudi arabia). european online journal of natural and social sciences, 3(4), 1212-1222. komijani, a., nazari, r. (2015), effect of oil revenues on government expenditures in iran. empirical studies of iran’s economy, 2, 55-90. mehnatfar, y. (2004), factors affecting current government expenditures in iran: 1959-2001. iranian journal of socioeconomics research, 15, 79-108. mehrara, m. (2008), the asymmetric relationship between oil revenues and economic activities: the case of oil-exporting countries. energy policy, 36(3), 1164-1168. mehrara, m. (2009), reconsidering the resource curse in oil-exporting countries. energy policy, 37(3), 1165-1169. jafari, et al.: effect of oil revenues on government size in selected oil-exporters with an emphasis on iran’s economy international journal of energy economics and policy | vol 10 • issue 5 • 2020 497 mehrara, m., maki, m., tavakolian, h. (2010), the relationship between oil revenues and economic growth, using threshold methods (the case of iran). opec energy review, 34(1), 1-14. mehrara, m., oskoui, k.n. (2006), dynamic effects of oil price shocks on macroeconomic variables. iranian journal of commerce, 40, 1-32. mohammadi, h., barat, a. (2013), effect of shocks from drop in oil revenues on government expenditures and money supply in iran. iranian energy economics journal, 2(7), 129-145. naderan, e. (2002), the government in liberal schools: the role of government in economy. pajouyan, j. (2012), public finances and government policy. tehran: payame noor publications. pazoki, a. (2012), effect of oil shocks on government expenditures in iran. master’s thesis, faculty of economics. tehran: tehran branch of iau. renani, m., sameti, m., farazmand, h. (2006), the relationship between financial decentralization and government size in iran. iranian journal of economics research, 26, 125-151. reyes-loya, m.l., blanco, l. (2008), measuring the importance of oil-related revenues in total fiscal income for mexico. energy economics, 30(5), 2552-2568. sachs, j.d., warner, a.m. (1991), natural resource abundance and economic growth. nber working paper no. 5398. sachs, j.d., warner, a.m. (1995), natural resource abundance and economic growth. nber working paper no. 5398. sachs, j.d., warner, a.m. (2001), natural resources and economic development the curse of natural resources. european economic review, 45, 827-838. sala-i-martin, x., subramanian, a. (2003), addressing the natural resource curse: an illustration from nigeria. cambridge, ma: nber working paper no. 9804. shahnazi, r., renani, m., dalali, e.r., khoshakhlagh, r., vaez, m. (2011), optimal fiscal policy with oil revenues. iranian economic review, 15(29), 73-88. tornell, a., lane, p.r. (1999), the voracity effect. the american economic review, 89(1), 22-46. villafuerte, m., lopez-murphy, p. (2010), fiscal policy in oil producing countries during the recent oil price cycle. fiscal affairs department. imf working paper draft. no. wp/10/28. zonouzi, j., shahbazi, k., parnak, r. (2014), effect of oil revenues on good governance in selected opec member countries. iranian journal of economic development policy, 2(4), 117-156. . international journal of energy economics and policy | vol 7 • issue 3 • 2017146 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(3), 146-151. consequences of oil and food price shocks on the ecuadorian economy jesser roberto paladines amaiquema1*, alexander ruben paladines amaiquema2 1department of economics, faculty of business studies, universidad técnica de machala, ecuador, 2department of sociology, faculty of social sciences, universidad técnica de machala, ecuador. *email: jesserpaladines@gmail.com abstract in this study, i investigated the short run impact on macroeconomics variables in ecuador, economic growth and inflation specifically, due to world oil price and global food price shocks, considered these last two, as external variables. the model used to explain the dynamic of variables was the structural vector auto-regression, with annual data from 1980 to 2015. i concluded that oil price shocks affect positively to economic growth in ecuador during two consecutive years, and then it returns to its natural state gradually. no enough statistically significant evidence was found, to conclude the global food index affect economic growth or inflation in ecuador. inflation neither showed significant response to oil price shocks. considering the small sample in this study, due to unavailability of domestic economic data, the model resulted stable, and it is in line with arguments from other authors. oil price shocks are a very important variable to keep watching, as ecuador still depends on it, any government macroeconomic policy should be focus to it. keywords: oil price, food price, structural vector auto-regression, impulse-response function, forecast error variance decompositions, ecuador jel classifications: c32, 040, f20 1. introduction though there is a current trend from many years ago to start using renewable sources of energy, the crude oil is still the focus of many studies, due to the relationship between the oil price, and some macro-economic variables. researchers as (hamilton, 1996; bernanke, et al., 1997; kilian, 2008; mork, 1989; papapetrou, 2001; lee and ni, 2002; paladines, 2017) have demonstrated that fluctuations on oil prices have influence in the domestic economy. in the last years, oil price was about $100 per barrel, which was considerably higher than the last decade. the market of oil affects everything that is related to it, as transportation, heating bill, etc. henceforth, oil prices are responsible for diminish the real economic growth, as many studies have demonstrated (galesi and lombardi, 2009; abbott et al., 2009; headey and fan, 2008). crude oil importing countries depend on oil prices, as high oil prices could shock the economy, increasing domestic prices and diminish output (doğrul and soytas, 2010). these countries must forecast oil prices increases as this may lead to instability. (mork, 1989; hamilton, 1996; rodriguez and sanchez, 2004; burbidge and harrison, 1984; berument, et al., 2010). exporting crude oil countries, as ecuador, the aim of this study, which is a net oil exporter, benefits of higher oil prices, that is as kilian (2005) explained, translated into more money to expend, but the inefficient use of this revenue may cause a long recession, difficult to overcome, as it is happening right now in venezuela. higher prices can lead to inflation but from different mechanisms o channels (huseynov and ahmadov, 2013). but this mechanisms are difficult to capture, without a fully specified model (bjørnland, 2000), but according to some authors like (jones et al.; 2004; tang et al., 2010; brown and yüce, 2002), have identified a few of these transmission channels, that would include the supply side effect, wealth transfer effect, inflation, real balance, sector adjustment and the unexpected effect. one of these channels that is the inflation, it is accepted that may be transmitted through three different channels, the first one is the amaiquema and amaiquema: consequences of oil and food price shocks on the ecuadorian economy international journal of energy economics and policy | vol 7 • issue 3 • 2017 147 cost channel; higher oil prices can lead to higher cost production for oil import countries, as this increase in oil prices generate high inflation, in concordance with (kilian, 2005), and may reduce output (chuku et al., 2011). similarly, in exporting oil countries, higher oil prices can lead to higher cost production, in spite, the energy price is subsidized by government in oil exporting countries, the imported goods used for production do increases, or are components of the consumer price index (cpi) (hooker, 2002; tang, et al., 2010). the second channel is the impact on exchange rate, as oil price increases the local currency for an oil exporting country can appreciate. but the opposite can exist when oil price falls, devaluation on the local currency is highly to happen due to overpressure on inflation. and the third one is the fiscal channel, in spite of being an oil exporting country, if government exceeds its capacity of purchase, can trigger inflation easily, during high oil prices, due to the dependency on oil (farzanegan, 2011). all this background deserves that we watch carefully fluctuations of oil prices, in order to study the shocks that can impact on the economy. in this investigation i use the structural vector autoregressive (svar) to analyze the impact on ecuadorian macroeconomic variables due to changes in oil prices. this study involves the following macroeconomic variables from ecuador; inflation, measured as changes in cpi, economic growth measured as changes in real gross domestic product (gdp) per capita, world oil price and global food index. all series are annual from 1980 to 2015. impulse response functions (irfs) and forecast error variance decompositions (fevds) are explored to evaluate the short run dynamic among variables. 2. literature review the study of effect of the oil price on macroeconomic variables dates from 1970s. hamilton (1996) concluded that us recessions after wwii were preceded by increases in the oil price, determined a correlation between the impact of oil prices and recessions on the us economy. and more recently brown and yüce (2002) concluded related results. recessions was also studied by blanchard and gali (2007) that characterized the macroeconomic performance of a set of industrialized economies in the aftermath of the oil price shocks of the 1970s and of the last decade, using a six-variable var model. they found a significant role of oil prices in the economic downturns. besides they concluded these impacts may be reducing with time due to the flexibility of the labor market. the most relevant literature about oil price shock on macroeconomic variables for this study, was kilian (2008) who showed evidence that the recent increase in crude oil prices was driven primarily by global aggregate demand shocks helps explain why this oil price shock so far has failed to cause a major recession in the u.s. using a svar model decomposing the real oil price. investigations like (rodriguez and sanchez, 2004) in line with (kilian, 2005; hooker, 2002) who concluded that oil price shocks on economic recession in g7 countries. similar to du et al. (2010) and gómez-loscos et al. (2011) that determined a direct relationship between the same variables. (lescaroux and mignon, 2008). (berument, et al., 2010) concluded the price of oil could be considered as bad for oil importing countries but good for oil exporting countries, as it was demonstrated as well, by aydın and acar (2011) who concluded there is a negative effect on gdp in terms of variations in the price of oil in turkey. in line with burbidge and harrison (1984), who argued based on a var model, that oil price has adverse effects on the macroeconomic variables in five organization for economic co-operation and development (oecd) countries. above literature can be confirmed besides by taghizadeh-hesary et al. (2013) evaluated the impact of oil price shocks on oil producing and consuming economies; the study used a simultaneous equation framework for different countries with business relations. as expected, the results showed that oil producers (iran and the russian federation) benefit from oil price shocks; similar to (huseynov and ahmadov, 2013), who confirm that a rise in oil prices is a positive shock which boosts the domestic economy, but in general leads to higher inflation. oil price increases are expected to affect net oil importers countries negatively, through rising import bills leading to inflation, reducing output and unemployment (bacon and kojima, 2008). similar to chang and wong (2003) indicated that impact of oil volatilities on gdp, inflation and unemployment have been significant. cuñado and pérez de gracia (2005) concluded that oil prices have a significant effect on both economic activity and price indexes although the impact is limited to the short-run for some asian countries. and tang et al. (2010) who studies short and long run effects of oil price in china; by using svar model, he showed that increases of oil price negatively affect output and investment but positively affect inflation and interest rate. other works by bjørnland (1998) concluded that for germany, uk and us, an adverse oil price shock has had a negative effect on output in the short run, but, for the us it was in the long run. similar works about impact on output to oil prices shocks in saudi arabia, indonesia, iran, kuwait were mehrara and oskui (2007), who using a svar, concluded that, oil price shocks are shown to be the main source of output fluctuations in saudi arabia and iran. but in kuwait and indonesia, output fluctuations were mainly found due to aggregate supply shocks. moreover, their results show that oil price shocks in saudi arabia steadily expand prices while such impact on the long run prices in iran, kuwait and indonesia is not approved. structural var models allow to forecast scenarios based on hypothetical future structures, as it was demonstrated by baumeister and kilian (2016) who studied the causes of the steep decline in the brent price of oil between june and december 2014. their analysis shows that more than half of this decline was predictable in real time as of june 2014. amaiquema and amaiquema: consequences of oil and food price shocks on the ecuadorian economy international journal of energy economics and policy | vol 7 • issue 3 • 2017148 3. methodology the svar model, introduced by sims (1980) have been used widely, two of them are the most important works used in these study, which are the studies by kilian (2008) and alom (2013), who used a svar, for studying the impact on macro-economic variables due to shocks in oil price. this paper uses a svar model to measure the impact on macroeconomic variables for changes in supply and oil prices, as there is enough evidence confirming the correlation between the variables studied by kilian (2008), for example (fueki, 2016; lorusso and pieroni, 2015; roach, 2014; lanteri, 2014; lamazoshvili, 2014; bjørnland, 2000; alom, 2013). in this work, domestic economic variables used to explain oil price shocks were: the real gdp per capita and inflation, both from ecuador, all data is annual from 1980 to 2015, data was obtained from el instituto nacional de estadísticas y censos (www.ecuadorencifras.gob.ec). it also can be said, that it is a small sample as kilian (1998). inflation was calculated from the log-differenced of the cpi of ecuador and the real gdp per capita was calculated in logdifferenced, in order to express the economic growth. following kilian (2008) work, who postulated a recursive structure such that, the form error et, can be decomposed according to ( )e at t= − 0 1ε , taking the following scheme: e 0 0 0 e e e t t prod t rea t rpo 11 21 22 31 32 33 ≡             =     ∆ α α α α α α      ε ε ε t oil supplyshock t aggregatedemandshock t oil-specificcdemandshock             i developed a structural var with variables similar to (alom, 2013; khan, 2011; omojolaibi, 2013; taghizadeh-hesary et al., 2013), with world oil price and world food index, as exogenous variables. in order to have a consistent model, i determined a recursive identification scheme, assuming that a matrix is an identity, while b matrix is upper triangular, capturing contemporaneous relationships. the impact matrix with the restrictions imposed can be seen below: e e e e e 0 0 0 0 0 t t rpo t fin t gdp t inf 11 21 22 31 ≡                 = α α α α α332 33 51 52 53 54 t worldoil price t world foo 0α α α α α ε ε               dd index t realgdpper capita shock t inflation shock ε ε                 this scheme follows an order from exogenous to endogenous, related to the respective responses of variables to temporary shocks. four restrictions according to theory were applied, which its estimation suggest that, the first and second row, these are, the oil supply and the world food index shocks, they are place on top because they are considered macro variables. oil price does not respond to innovations to the other macroeconomic variables in the period t. (lee and ni, 2002). food price responds to oil price shocks, although there is no evidence that the food index may be impacted by oil price shocks (baumeister and kilian, 2014), this variable may affect domestic variables in ecuador. it is expected that a positive shock in food index, impacts on inflation positively and a positive shock in oil price, would cause a positive impact on economic growth of ecuador. the third row, it is the ecuador economic growth, proxied by the real gdp per capita, it’s assumed this variable it is only affected by itself, oil price and food index, according to jiménez-rodríguez (2007) and alom (2013). and finally, inflation receives contemporaneous effects of all the remaining variables in the system, similar to (alom, 2013; khan, 2011; jiménez-rodríguez, 2007). i assumed oil price shocks could affect cpi indirectly. oil price, refers to the real oil price, this is measure as the average price in dollars for equal weights of oil according to brent, dubai and wti prices. both, oil price and food index, were obtained from the oecd (www.oecd.org). time series in logs were used, from 1980 to 2015. 4. findings 4.1. unitary root test there are important differences between stationary and nonstationary time series. changes in stationary series are necessarily temporary, over time, the effects of shocks will dissipate and the series will return to their mean level in the long run. while a non-stationary series necessarily has permanent components. the mean and variance of a non-stationary series are time dependent (enders, 2015). a var can be estimated with non-stationary variables in level and the resulting impulse responses in the shortand medium-run are then reliable estimators of the true impulse responses. this holds also with cointegrated variables. this result comes from the fact that the var in level takes implicitly account of the cointegrated relationships. similarly, as pointed out by sims et al. (1990), the common practice of transforming models into stationary representations by first-differencing or using cointegration operators is often unnecessary even if data appear likely to be integrated (at least asymptotically). variables were tested by both the dickey-fuller augmented test and the phillips-perron test (phillips and perron, 1998), these tests showed that only oil price, has a unit root in levels. 4.2. svar analysis the main and unique objective of this paper is to study the impact of oil price shocks on the economic growth and inflation in ecuador, using the irf. it was chosen 4, as the lag length, in order to remove residual correlation properly, given by the akaike information criterion. amaiquema and amaiquema: consequences of oil and food price shocks on the ecuadorian economy international journal of energy economics and policy | vol 7 • issue 3 • 2017 149 table 1 shows the coefficients of the svar model, according to the order of variables in the two matrixes. 4.3. impulse-response function (fir) since the individual coefficients in the estimated var models are often difficult to interpret, practitioners often estimate the fir (gujarati and porter, 2010). (pesaran and shin, 1998) they propose a type of impulse generalized response that consists in constructing a set of orthogonal innovations (shocks), such that they do not depend on the ordering in the var. it is important to remind that for software limitation, it is just calculated a positive one unit standard deviation shock to oil prices. as i studied the impact on macroeconomic variables due to shocks to oil market, the following graph does no show impacts on oil prices, as it was discussed before. the result about the impact on gdp to shocks to oil price, are almost the same as paladines (2017), and similar to (taghizadeh-hesary et al. 2013; du et al., 2010; gómez-loscos et al., 2011; lescaroux and mignon, 2008; berument, et al., 2010; chang and wong, 2003), gdp reaches its peak in 2nd year; after that results suggest that gdp declines gradually. the gdp response to world food index shocks, shows a negative effect, this is according to theory, until the 5th year, then it returns to zero, but it is not statistically significant all the 10 periods forecast, similar to alon (2011), the impact on inflation due to shocks in oil and food prices, both have positive effects as (huseynov and ahmadov, 2013) and later negative effects, but still it is not statistically significant (figure 1). 4.4. analysis of fevd the prediction of error variance decompositions are also popular tools for interpreting var models (lütkepohl and krätzig, 2004). the variance decomposition offers a slightly different method for examining the dynamics of a var system. they give the proportion of the movements in the dependent variables that are due to their own shocks, to shocks of other variables. a shock to the variable ith will directly affect that variable, but will be transmitted to all other variables in the system through the dynamic structure of the var (brooks, 2008). when analyzing the table 1, it is observed that the variability of the economic growth of ecuador can be explained until 22% approximately the oil price shocks, but food index, could explain until 11% of its variability. oil price and food price are shock 1 and shock 2 respectively. domestic inflation is not almost explained by oil price shocks, but a positive shock in the world food index could affect it by 13% approximately, but according to the irf respective, these results cannot be definite (table 2). 4.5. diagnostic tests as the var technique is relatively flexible and dominated by the endogeneity of the variables, it is not customary to analyze the estimated regression coefficients and their statistical significance; nor is the goodness of the fit (r2, it is usual to verify that the absence of serial correlation of the residuals of the individual equations of the model and the normal multivariate distribution of the variables is observed. sometimes the variables are expected to reflect behaviors consistent with the expected some researchers perform additional tests, such as the stability of the model, the joint significance of the variables considered, their direction of causality, the cointegration of the residuals of the individual regressions and the decomposition of variance of the forecast error (dv) (arias and torres, 2004). figure 1: response-impulse functions with ± 2 s.e table 1: svar results estimated a matrix 1.000000 0.000000 0.000000 0.000000 −0.087912 1.000000 0.000000 0.000000 0.009797 −0.083635 1.000000 0.000000 −0.018392 −3.304943 10.48118 1.000000 estimated b matrix 0.242940 0.000000 0.000000 0.000000 0.000000 0.083687 0.000000 0.000000 0.000000 0.000000 0.018574 0.000000 0.000000 0.000000 0.000000 0.501514 svar: structural vector autoregressive table 2: variance decomposition period s.e. shock 1 shock 2 gdp 1 0.019858 0.089463 12.42324 2 0.026685 22.02441 7.301726 3 0.027271 22.08870 7.371997 4 0.028322 22.25212 8.434969 5 0.029683 24.30358 11.93930 inflation 1 0.580793 1.958429 12.24329 2 0.591269 2.201948 11.85744 3 0.612331 5.030766 12.92291 4 0.616520 5.084973 13.63427 5 0.620564 5.024468 13.65459 amaiquema and amaiquema: consequences of oil and food price shocks on the ecuadorian economy international journal of energy economics and policy | vol 7 • issue 3 • 2017150 4.5.1. normalily it is necessary the normality of the underlying data of the generated processes, for example to establish forecast intervals (the forecast errors used in the construction of forecast intervals are weighted sums of the ut). non-normal residuals may indicate that the model is not a good representation of the processes of the generated data. for this reason, testing this distribution assumption is desirable (lütkepohl and krätzig, 2004). the normality test by the structural factorization method, showed a p-value of 0.1189 for the jarque-bera (jb) statistic, this result means i cannot reject the null hypothesis that residuals are multivariate normal, but this result it is taken with carefully, as the jb statistic follows an asymptotic distribution. 4.5.2. autocorrelation results from the lm test of autocorrelation of residuals, suggest in non-rejection of the null hypothesis of non-autocorrelation until the 4th lag. so, i can conclude the absence of correlation among residuals. 4.5.3. heteroskedasticity the test of white without cross-terms, which null hypothesis is the absence of heteroskedasticity in the var, is not rejected in this model, the test showed a p-value of chi-square, equals to 0.2340. 4.5.4. stability model the estimated var is stable (stationary) if all roots have modules <1 and lie within the unit circle. if the var is not stable, certain results (such as standard impulse response errors) are not valid (eviews, 2016). according to the table 3, i can conclude that the model is dynamically stable. 5. conclusion the dynamic relationship between the two global variables, oil price and the food index, with the domestic variables that are the economic growth, proxied by the real gdp per capita, and inflation of ecuador, are very important issues, to take into account for economic policies. this research was carried out, taking annual data from 1980 to 2015, and using level of the variables, i tried to explain the behavioral of these ones, using two econometric tools as, the fir and the dv, in base of a svar model, i concluded a short run relationship among variables, according to the restrictions used in the model. since the stability tests of the svar were significant, the model is good specified. results from the fir indicate that, a positive shock in oil prices, the economic growth of ecuador if affected positively and other results were inconclusive, as there was no much statistically significant evidence, to prove correlation between oil production with both gdp and inflation, like wise no significant relationship was found between oil price shocks and inflation. the most change in economic growth in ecuador can be explained by oil price shocks by 24% approximately. as fir did not show significant values with inflation, the dv lacks of veracity. although this model could be improved later by adding more data this paper accomplished its purpose to explain any short run relationship among the variables studied, in spite this was a small sample. references abbott, p., hurt, c., tyner, w. (2009), what’s driving up food prices. washington, dc: farm foundation. alom, f., ward, b., hu, b. (2013), macroeconomic effects of world oil and food price shocks in asia and pacific economies: application of svar models? opec energy review, 37(3), 327-372. alom, f. (2011), economic effects of oil and food price shocks in asia and pacific countries: an application of svar model. nzares conference. arias, e., torres, c. (2004), banco central de costa rica. obtenido de. available from: http://www.bccr.fi.cr/investigacioneseconomicas/ metodoscuantitativos/modelos_var_y_vecm.pdf. aydın, l., acar, m. (2011), economic impact of oil price shocks on the turkish economy in the coming decades: a dynamic cge analysis. energy policy, 39(3), 1722-1731. bacon, r., kojima, m. (2008), oil price risks. viewpoint: public policy for the private sector; note no. 320. available from: https://www. openknowledge.worldbank.org/handle/10986/11151. baumeister, c., kilian, l. (2014), do oil price increases cause higher food prices? economic policy, 29(80), 691-747. baumeister, c., kilian, l. (2016), understanding the decline in the price of oil since june 2014. journal of the association of environmental and resource economists, 3(1), 131-158. bernanke, b., gertler, m., watson, m., sims, c., friedman, b. (1997), systematic monetary policy and the effects of oil price shocks. brookings papers on economic activity, 1, 91-157. berument, m., ceylan, n., dogan, n. (2010), the impact of oil price shocks on the economic growth of selected mena1 countries. the energy journal, international association for energy economics, 1, 149-176. bjørnland, h. (1998), the economic effects of north sea oil on the manufacturing sector. scottish journal of political economy, 45(5), 553-585. bjørnland, h.c. (2000), the dynamic effects of aggregate demand, supply and oil price shocks a comparative study. the manchester school, 68(5), 578-607. blanchard, o., gali, j. (2007), the macroeconomic effects of oil shocks: why are the 2000s so different from the 1970s? nber working paper 13368. p77. brooks, c. (2008), introductory econometrics for finance. 2nd ed. estados unidos, new york: cambridge university press. brown, s., yüce, m. (2002), energy prices and aggregate economic activity: an interpretative survey. the quarterly review of economics and finance, 42(2), 193-208. table 3: stability test root modulus 0.856327-0.172954i 0.873619 0.856327+0.172954i 0.873619 0.205494-0.618241i 0.651498 0.205494+0.618241i 0.651498 −0.388256-0.508515i 0.639789 −0.388256+0.508515i 0.639789 0.220959-0.435324i 0.488191 0.220959+0.435324i 0.488191 amaiquema and amaiquema: consequences of oil and food price shocks on the ecuadorian economy international journal of energy economics and policy | vol 7 • issue 3 • 2017 151 burbidge, j., harrison, a. (1984), testing for the effects of oil-price rises using vector autoregressions. international economic review, 25(2), 459-484. chang, y., wong, j. (2003), oil price fluctuations and singapore economy. energy policy, 31(11), 1151-1165. chuku, c., usenobong, a., ndifreke, s. (2011), oil price shocks and the dynamics of current account balances in nigeria. opec energy review, 35(2), 119-139. cuñado, j., pérez de gracia, f. (2004). oil prices, economic activity and inflation: evidence for some asian countries. faculty working papers. p1-36. dickey, d., fuller, w. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica, 49(4), 1057-1072. doğrul, h., soytas, u. (2010), relationship between oil prices, interest rate, and unemployment: evidence from an emerging market. energy economics, 32(6), 1523-1528. du, l., yanan, h., wei, c. (2010), the relationship between oil price shocks and china’s macro-economy: an empirical analysis. energy policy, 38(8), 4142-4151. enders, w. (2015), applied econometric time series. 4th ed. chichester, west sussex: john wiley & sons. eviews. (2016), eviews. obtenido de. available from: http://www. eviews.com/help/helpintro.html#page/content/var-views_and_ procs_of_a_var.html. farzanegan, m.r. (2011), oil revenue shocks and government spending behavior in iran. energy economics, 33(6), 1055-1069. fueki, t.e. (2016), identifying oil price shocks and their consequences role of expectations and financial factors in the crude oil market. bank of japan working paper series. p1-25. galesi, a., lombardi, m. (2009), external shocks and international inflation linkages: a global var analysis. european central bank, working paper series no. 1062. p45. gómez-loscos, a., montañés, a., gadea, m. (2011), the impact of oil shocks on the spanish economy. energy economics, 33(6), 1070-1081. gujarati, d., porter, d. (2010), econometría. mexico: mcgraw hill. hamilton, j. (1996), this is what happened to the oil price-macro economy relationship. journal of monetary economics, 38(2), 215-220. headey, d., fan, s. (2008), anatomy of a crisis: the causes and consequences of surging food prices. agricultural economics, 39(1), 375-391. hooker, m. (2002), are oil shocks inflationary? asymmetric and nonlinear specifications versus. journal of money, 34(2), 540-561. huseynov, s., ahmadov, v. (2013), oil windfalls, fiscal policy and money market disequilibrium. william davidson institute working paper no. 1051. p40. jiménez-rodríguez, r. (2007), the industrial impact of oil price shocks: evidence from the industries of six oecd countries. banco de españa research paper (wp-0731). p1-51. jones, d., leiby, p., paik, i. (2004), oil price shocks and the macroeconomy: what has been learned since 1996. the energy journal, 25(2), 1-32. khan, m. (2011), macroeconomic effects of global food and oil price shocks to the pakistan economy: a structural vector autoregressive (svar) analysis. the pakistan development review, 50(4), 491-511. kilian, l. (2005), the effects of exogenous oil supply shocks on output and inflation: evidence from the g7 countries. centre for economic policy research no. 5404. kilan, l. (1998), small-sample confidence intervals for impulse response functions. review of economics and statistics, (80), 218-230. kilian, l. (2008), exogenous oil supply shocks: how big are they and how much do they matter for the u.s. economy? review of economics and statistics, 90(2), 216-240. lamazoshvili, b. (2014), effects of oil shocks on oil-importing developing economies: the case of georgia and armenia. eerc working paper series (e14/06). p1-33. lanteri, n. (2014), determinantes de los precios reales del petróleo y su impacto sobre las principales variables macroeconómicas: eu, españa, noruega y argentina. economía: teoría y práctica, 41, 45-70. lee, k., ni, s. (2002), on the dynamic effects of oil price shocks: a study using industry level data. journal of monetary economics, 49(4), 823-852. lescaroux, f., mignon, v. (2008), on the influence of oil prices on economic. opec energy review, 32, 343-380. lorusso, m., pieroni, l. (2015), causes and consequences of oil price shocks on the uk economy. ceerp working paper no. 2. p1-31. available from: http://www.ceerp.hw.ac.uk/repec/hwc/wpaper/002. pdf. lütkepohl, h., krätzig, m. (2004), applied time series econometrics. themes in modern econometrics. new york and melbourne: cambridge university press. p33-167. mehrara, m., oskoui, k. (2007), the sources of macroeconomic fluctuations in oil exporting countries: a comparative study. economic modelling, 24(3), 365-379. mork, k. (1989), oil and the macroeconomy when prices go up and down: an extension of hamilton’s results. journal of political economy, 97(3), 740-744. omojolaibi, j. (2013), does volatility in crude oil price precipitate macroeconomic performance in nigeria? international journal of energy economics and policy, 3(2), 143-152. paladines, j. (2017), oil price and real gdp growth of ecuador: a vector autoregressive approach. journal of economics and political economy, 4(1), 71-78. papapetrou, e. (2001), oil price shocks, stock market, economic activity and employment in greece. energy economics, 23(5), 511-532. pesaran, h., shin, y. (1998), generalized impulse response analysis in linear multivariate models. economics letters, 58(1), 17-29. phillips, p., perron, p. (1988), testing for a unit root in time series regression. biometrika, 75(2), 335-346. roach, k. (2014), a structural analysis of oil price shocks on the jamaican macroeconomy. monetaria, 2(2), 217-252. available from: http:// www.cemla.org/pdf/monetaria/pub-mon-ii-02-02.pdf. rodriguez, j., sanchez, m. (2004), oil price shocks and real gdp growth: empirical evidence from some oecd countries. working paper series no. 0362, european central bank. p64. taghizadeh-hesary, f., yoshino, n., abdoli, g., farzinvash, a. (2013), an estimation of the impact of oil shocks on crude oil exporting economies and their trade partners. frontiers of economics in china, 8(4), 571-591. sims, c.a. (1980), macroeconomics and reality. econometrica 48, 1-48. sims, c.a., stock, j.h. watson, m.w. (1990). inference in linear time series models with some unit roots. econometrica, 58, pp. 113-144. tang, w., wu, l., zhang, z. (2010), oil price shocks and their short-and long-term effects on the chinese economy. energy economics, 32(1), 3-14. . international journal of energy economics and policy | vol 6 • issue 1 • 2016128 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2016, 6(1), 128-133. reconstructing renewable energy: making wind and solar power dispatchable, reliable and efficient eric l. prentis* college of business & public management, wenzhou-kean university, wenzhou, china. *email: eric.prentis@gmail.com abstract this paper is important because it explains how to create a grid-scale energy storage system (ess) that makes, for the first time, wind and solar renewable energy—dispatchable, reliable and efficient. existing and recent discoveries in battery technology are analyzed, with the most appropriate recommended for use in the new ess. additionally, an innovative time-shifting ess design approach is presented that decouples electricity production from use, considerably improving total wind and solar power peak average capacity contribution values. this minimizes the need for expensive standby natural-gas combustion turbine peaker plants—thereby decreasing costs by 75%. furthermore, this advanced ess improves performance by making the interconnection grid more reliable and better able to handle changing customer demands, relieves transmission congestion, and decreases unscheduled power outages—and also provides ancillary services; thereby improving system-wide benefits by 30-to-40%, further reducing effective ess costs, perhaps to zero. keywords: renewable energy, efficiency, dispatchable, grid-scale energy storage system jel classifications: g31, g38, h44, k23 1. introduction the u.s. energy information administration’s (eia) annual energy outlook 2015 (2015) projects that total renewable energy generation will increase 72%, from 525 billion kilowatt-hours (kwh) in 2013, to 900 billion kwh in 2040. wind and solar renewable energy will account for nearly two-thirds of the growth. u.s. department of energy: office of scientific and technical information, (2015), wind vision predicts that by 2050, wind power will provide 35% of total u.s. electricity generating capacity. in 2014, the u.s. installed 61.9 megawatts (mw) of energy storage, an increase of 40% from 2013, comprising 180 individual installations, averaging 344 kilowatts (kw) per energy storage facility. energy storage installations have a total market size of $128 million dollars and are expected to grow to 220 mw in 2015, reaching 850 mw by 2019, a continued growth of 40% per year, resulting in cumulative energy storage installations of 2.5 gw. ninety percent of energy storage systems (esss) are grid-scale, installed in front of the meter. because the electricity produced by wind and solar renewable energy depends on unstable weather conditions, which change unexpectedly, wind and solar power generation is intermittent and variable. using the current battery technology and the existing ess design approach, requires a substantial number of standby, natural-gas combustion turbine (ngct) peaker plants to be kept in reserve, ready to produce electricity when required. ngct peaker plants are expensive and costs will continue to rise—as wind and solar power interconnection grid capacity percentages increase—if the existing electric ess design approach and battery technology continue to be used (prentis, 2015a). about 97% of the battery storage market on the interconnection grid currently uses rechargeable lithium-ion (lit-ion) batteries (gtm research and the energy storage association, 2015). in addition, rechargeable li-ion batteries are presently the dominant battery chemistry technology, used worldwide, in billions of cell phones, laptop computers and electric vehicles. however, what is appropriate to power mobile consumer electronics is not the best choice for a stationary, grid-scale esss. prentis: reconstructing renewable energy: making wind and solar power dispatchable, reliable and efficient international journal of energy economics and policy | vol 6 • issue 1 • 2016 129 li-ion batteries have a relatively high cost for raw materials and a low 1,000 charge-discharge cycle durability. consequently, li-ion batteries, when being deeply discharged, daily, need replacement about every 3 years, and therefore, cannot last the 30 years necessary to be cost effective in a grid-scale ess. li-ion batteries have fully recharging/discharging cycle times of about 2 hours (h). consequently, “long duration” esss are only capable of delivering energy for 2-4 h. this makes li-ion batteries impractical for a grid-scale ess, which should have about 6 h of energy storage to supply energy during both morning and evening peak demand periods. additionally, rechargeable li-ion batteries pose a safety hazard, resulting from using a flammable electrolyte that is kept under pressure. in response to safety concerns, the boeing company recently warned passenger airlines on the dangers of transporting bulk shipments of li-ion batteries that can explode, in a chain reaction, because of “thermal runaway,” possibly destroying the airplane during flight. in addition, the federal aviation administration conducted tests and warned that fire-retardant chemicals, on airplanes, may be incapable of extinguishing fires that result from li-ion battery “thermal runaway.” consequently, li-ion batteries can be dangerous, overheat and catch fire—similar to what can happen to extremely corrosive sodium-sulfur (na-s) batteries that have 300-350°c operating temperatures. fire safety hazards, high raw material costs, low durability and slow recharging/discharging cycle times make li-ion batteries technically unsuited for a cost-effective, 6 h grid-scale ess. research into advanced battery technologies is ongoing; the most promising are discussed next. 2. literature review prospective advantages of lithium-air (li-o2) and lithium-sulfur (li-s) warrant continued research (bruce, et al., 2012). new li-o2 research, still in the development stage, has theoretical energy density per kilogram comparable to gasoline, has shown improved recharging efficiency and increased ability to be charged and discharged (mit technology review, 2015). li-s batteries are demonstrated to be practical, have an energy density three-to-four times that of li-ion batteries, use less expensive raw materials, but need to increase the 1,500 charge-discharge cycle durability, to be cost-effective for grid-scale energy storage applications. lithium-titanate (li-ti) batteries are modified li-ion batteries that charge in about 10 minutes. voltage (v) is 2.4 v versus 3.7 v for li-ion. energy density is 90 wh/kg versus 200 wh/kg for li-ion, with durability cycles of 9,000, resulting in an expected life of 20+ years. li-ti batteries have proven their practicality in the electric-transport industry—used by honda and mitsubishi for electric vehicles. li-ti batteries may be competitive with li-ion batteries for an ess application, but also use expensive materials in their manufacture, including lithium and hard to get cobalt, which is mined mainly in african conflict zone countries—making li-ion and li-ti impractical, when compared to competing battery choices. magnesium-ion (mg-ion) batteries, in comparison with li-ion, are made from materials less costly to acquire, significantly increase energy density and offers improvements in safety. most encouraging, toyota is investing in mg-ion battery technology. however, mg-ion battery chemistry is not yet perfected. magnesium reacts with other materials, interfering with ion movements through the electrolyte. in addition, accelerated dendritic growths significantly reduce the mg-ion’s chargedischarge cycle durability (wan and prendergast, 2014). nickel-hydrogen (ni-h2) battery technology is proven, with many space-age satellite applications, most notably the orbiting hubble space telescope. ni-h2 batteries have advantages— high-reliability, light weight, safety, are maintenance free, have high durability with frequent charge-discharge cycles of 50,000 (liu et al., 2005). ni-h2 batteries, unfortunately, have many disadvantages, including: low energy density of about 60 wh/ kg, low voltage at 1.5 v, a high self-discharge rate, and require high pressure storage. in addition, ni-h2 batteries are made from exotic materials, making them very expensive. consequently, high cost prohibits ni-h2 battery use in an efficient grid-scale ess. economic analysis of the advanced grid-scale ess, presented in this paper, supports incorporating a new battery technology. the innovative time-shifting ess design approach that decouples electricity production from use, is offered that explains how best to use the new battery technology to make, for the first time, intermittent and variable renewable solar and wind energy— dispatchable, reliable, efficient, standardized, modular, flexible, transportable, easily-sited and grid-integrated. 3. data and methodology 3.1. new al-ion battery technology a new discovery on aluminium-ion (al-ion) batteries (lin, et al. 2015) offers clear advantages for an ess. independent research on basic al-ion material-science advances, presented in the literature, is extensive, beginning in 2011 (jayaprakash, et al. 2011), (xiong, et al. 2011), (wang, et al., 2013), (mon, 2013). when compared to lithium-ion batteries, al-ion batteries are low cost—using aluminium, graphite and chloride versus lithium, cobalt and ethylene carbonate materials for li-ion, and are safe, environmentally friendly and easy to decommission—in comparison to li-ion batteries that require treatment like hazardous waste. al-ion batteries demonstrate long lasting durability, up to tens-ofthousands of cycle times versus 1,000 cycles for li-ion. al-ion batteries have ultrafast charging times of one minute, producing a 60/h charging and discharging rate—the “c” rate of current—when compared to li-ion batteries, which may take 2 h to charge— resulting in a very low “1/2c” rating for li-ion—which then requires costly buffering with capacitors. al-ion batteries, with a lower cost and a high “60c” rating, require less buffering, allowing for better solutions when designing the al-ion ess. al-ion batteries can be bent and folded into many shapes in their flexible polymer-coated pouch, and have a long life, lasting prentis: reconstructing renewable energy: making wind and solar power dispatchable, reliable and efficient international journal of energy economics and policy | vol 6 • issue 1 • 2016130 30 years in an ess, with daily charge-discharge cycles. the energy density is reported by a co-author to have already doubled in the lab, to 80 wh/kg, and generates two volts of electricity, which should increase by improving the graphite cathode material. at 80 wh/kg, 4 kwh is 50 kg, operating at 60 c charge/discharge rate, produces 240 kw of power. three thousand kw (3 mw) of power requires 625 kg of al-ion batteries. making the al-ion ess dispatchable for 6 h may require six times 625 kg, equaling 3,750 kg of al-ion batteries, for each 3 mw of power from renewable energy. the al-ion ess is categorized by both power capacity and energy capacity, and would be rated at a 3 mw power capacity, with 6-h storage capacity, equivalent to an energy capacity of 18 mwh, with an expected 90% round-trip efficiency. currently, on the texas interconnection grid, esss are used only to smooth and stabilize intermittent and variable renewable energy, in real time. the existing ess design approach is a restrictive application, and would not derive the best use of the al-ion battery technology. the al-ion battery technology will be used in the new ess timeshifting design approach that decouples electricity production from use, which is described next. 3.2. new ess time-shifting design approach the innovative time-shifting al-ion ess design approach decouples electricity production from use, by first producing renewable energy electricity—then delivering the electricity to the al-ion ess—and only then supplying electricity from the al-ion ess to the interconnection grid, 24 h later. electricity is never delivered, in real time, directly from the renewable energy source to the interconnection grid, as is the current ess smoothing and stabilizing practice for renewable energy intermittent and variable real-time supply. the unique al-ion ess design approach presented permits the decoupling of wind and solar electricity generation—from when and where the renewable resource power is produced, to when and where the power is needed—which are major new advantages. consequently, the improvement in how the new al-ion battery technology is used, results in a cost-effective change in application procedure—where electricity is available for transmission, daily, independent of the prevailing wind’s speed or the sun’s intensity. the innovative ess is a major change from using energy storage only to smooth and stabilize renewable energy power, in real time. over a 24-h period, wind and solar power generation is used only to recharge al-ion batteries in the ess—never supplying electricity directly to the interconnection grid, until the next day. time shifting wind electricity supply—from low demand at night to peak-loads during the day—is arbitraging the high and low cost of daily electricity generation (lamont, 2013). stored electricity is reliably available, used when wanted, without the need for conventional reserve capacity (prentis, 2014a). this paper’s new al-ion renewable ess is best implemented using a turnkey operation, which is presented next. 3.3. al-ion ess turnkey operation the new al-ion ess is assembled at the manufacturing plant, filling a 53-foot long shipping container, housing 3,750 kg of al-ion batteries, hvac, and a computer operating system to control grid congestion and energy market interface connection requirements. then, the prepackaged al-ion ess shipping container is trucked to the renewable energy site, as a complete assembly—able to be used on arrival at its destination location—by placing it on a prewired and preinstalled concrete pad, ready for turnkey operation. modular construction of the al-ion batteries allows for plug-in replacement if individual battery packs fail. maintenance for the al-ion ess is minimal. the al-ion ess is flexible and easily scalable. if more than 3 mw of power capacity and 18 mwh of energy capacity are generated each day; additional outfitted shipping containers are installed at the site. this al-ion ess concept approach moves away from the expensive custom design, fixed site transformation process—used by blattner energy, an engineering, procurement and construction company, on the 20 mw lee/dekalb li-ion ess in northern illinois, completed in february 2015 (energy storage association, 2015)— to a much less expensive standardized flow design, transportable transformation process (prentis, 1987). going from a proprietary design method to a standardization modular design requires open data communication and common software specifications for different parts suppliers, thereby having available interoperable components to speed products to market. as a result, recurring engineering system integration will no longer be needed—reducing unit costs, improving reliability and power output, and allowing data to be easily shared—so the al-ion ess works in concert with the existing interconnection grid system. this important advancement ends the need for reinventing a renewable energy system integration protocol. the electric reliability council of texas (ercot) is the independent system operator (iso) administering the texas interconnection grid, and supplies the capacity, demand and reserves report data for this research (electric reliability council of texas (ercot), 2015). the u.s. energy information administration (eia) (2013) reports on the capital costs for electricity plants used in this research (prentis, 2015b). the results of the al-ion ess economic analysis are presented next, starting with an analysis of the existing ess design approach. 4. empirical results 4.1. existing ess design approach ercot assesses the effective load carrying capacity (elcc) of non-coastal wind at 12% and elcc for coastal wind at 56% of prentis: reconstructing renewable energy: making wind and solar power dispatchable, reliable and efficient international journal of energy economics and policy | vol 6 • issue 1 • 2016 131 total rated wind capacity, which can be relied upon at the time of peak demand. the elcc for solar power is estimated at 80%. the total installed wind capacity in the texas interconnection grid is 11,379 mw for non-coastal wind and 1,680 mw for coastal wind installations. the peak average capacity contribution (pacc) values for wind power is 12% times 11,379 mw for non-coastal wind and 56% times 1,680 mw for coastal wind. consequently, only 2,306 mw of wind power can be currently relied upon to meet resource adequacy requirements, at peak demand. for solar power, the pacc is 80% times 303 mw, equaling 242 mw. the pacc total value for wind and solar is 2,548 mw. typically, because wind and solar power elccs are low, expensive ngct peaker plants are required to be available as reserve capacity to supply power at peak demand. adding to this problem, wind and solar power elccs decline as wind and solar percentages of total system capacity increase. 4.2. innovative time-shifting, al-ion ess design approach for the new al-ion ess design approach, wind turbine capacity factors are reported to be at least 50%, which should be the minimum elcc attainable, because renewable energy resources are operated over a 24-h period—capturing peak wind production periods, with energy storage in the al-ion ess cumulative—and then dispatched to meet system reliability needs the next day. consequently, the elcc for non-coastal wind is set at 50%. to be conservative, the elccs for coastal wind and solar are set only 5% higher, at 61% and 85%, respectively. ercot’s pacc for wind and solar power, using an al-ion ess, is 50% times 11,379 mw, plus 61% times 1,680 mw, plus 85% times 303 mw, equaling 6,972 mw. consequently, 4,424 mw of expensive ngct peaker plants would no longer be needed for reserve capacity. ngct peaker plants’ overnight capital and fixed operation and maintenance (om) costs are $980,340/mw times 4,424 mw, totaling $4.34 billion dollars. eia reports, from 2002 to 2015, average natural gas (ng) prices are $4.25 dollars per thousand cubic feet (mcf), making an efficient ngct peaker plant fuel costs $42.15/mwh. variable non-fuel om costs are $15.45/mwh. ng fuel and variable non-fuel om costs total $57.60/mwh—however, at the high end, older inefficient ngct peaker plants’ fuel and variable non-fuel om costs may be twice this amount—multiplied times 4,424 mw times 6 h/day times 365 days/year times 30 years, equals $16.74 billion dollars. ngct peaker plant costs total $21.08 billion dollars, over a useful life of 30 years. the al-ion ess has no fuel or variable om costs, meaning if overnight capital and fixed om costs are less than $8,273,155/mw, the al-ion esss is economical. the weighted average system price for grid-scale ess currently in use in 2014 is $2,064,000/mw. a savings of $21.08 billion dollars divided by $2,064,000/mw equals 10,213 mw, which would then be the power available at peak times, up from 2548 mw presently, an increase of 401%. an extra 7,665 mw is available for pacc when using the advanced al-ion ess design approach, at only 25% of the cost of expensive ngct peaker plants. ngct peaker plants and al-ion batteries have useful lives that are about equal, 30 years, making depreciation of capital costs comparable. one can think of the al-ion batteries being the consumable fuel, and the depreciation charge, over its 30 year useful life, the fuel cost. eia reports that capital costs for ngct peaker plants, in us dollars per kw, are about half that of onshore wind, a sixth that of offshore wind, and quarter that of solar photovoltaic. however, capital costs for renewable energy are dropping quickly. for example, in report entitled, “financing the future of energy,” authored by the university of cambridge and pwc, commissioned by the national bank of abu dhabi (parkinson, 2015), predicts that future investments in electric power will be almost entirely in renewable energy. coal, ng, oil and nuclear fuels will find it difficult to compete. acwa power—which is a $23 billion saudi energy firm—bid to supply electricity from a new 200 mw solar facility, at a very competitive us$0.0584 dollars per kwh, without subsidies. combining this inexpensive solar renewable energy source, with a cost-effective al-ion ess, would further reduce costs, making the new electric solar power system and al-ion ess a clear winner versus existing renewable energy generation and existing ess design, using lithium-ion battery technology. additionally, the brattle group (2014) says 30-40% of the systemwide benefits from interconnection grid-scale esss are attributed to system reliability, and transmission and distribution functions. for example, the easily-sited al-ion ess may be located at congested nodes on the grid to reduce locational marginal prices (liu, et al. 2014). this further reduces effective al-ion ess costs, perhaps to zero. in addition, the smallest ngct peaker plants are about 50 mw, and therefore, are less flexible than an al-ion ess, which is more adaptable, able to be deployed in 3 mw increments and then scaled-up over time. from an operations and environmental standpoint, ngct peaker plants take minutes to dispatch, have significant standby costs, produce considerable co2 emissions and are single purpose. in comparison, al-ion batteries take only seconds to dispatch, and therefore can respond much faster to interconnection grid changes, have low standby costs, produce zero direct co2 emissions and are applicable to ancillary services; thereby adding another important capability to the constant need to balance electrical supply with demand. all of these reasons, plus much lower costs for the al-ion ess, will insure that expensive ngct peaker plants are replaced by the new al-ion ess, for interconnection grid capacity services. additionally, the al-ion ess compares favorably with competing, alternative technology esss. for example, the al-ion ess is easily sited, safe, environmentally friendly and has a small space prentis: reconstructing renewable energy: making wind and solar power dispatchable, reliable and efficient international journal of energy economics and policy | vol 6 • issue 1 • 2016132 requirement—in comparison with pumped-storage hydroelectricity, which requires considerable land space availability and water resources—and when compared to compressed air energy storage, which needs an existing large underground geological storage facility, such as a salt mine. when the al-ion ess design approach becomes policy, and is fully implemented; it will materially transform and modernize the electric power industry. 5. discussion economic analysis of a new, grid-scale, renewable ess design concept, using al-ion battery technology and a time-shifting ess design approach is presented in this paper. the new grid-scale ess design approach explains how best to use the al-ion battery technology to make—for the first time—intermittent and variable solar and wind renewable energy—dispatchable, reliable, efficient, standardized, modular, flexible, transportable, easily-sited and grid-integrated. the innovative, time-shifting al-ion ess decouples electricity production from use, first producing renewable energy electricity—then delivering the electricity to the al-ion ess— and only then supplying electricity from the al-ion ess to the interconnection grid, 24 h later. ercot and eia data are used to make an economic justification for al-ion battery use in timeshifting, grid-scale esss. energy density is less crucial in a stationary ess than in portable electronics and electric vehicles that use rechargeable lithium-ion (lit-ion) batteries. the advanced al-ion ess makes use of inexpensive materials, high cycle durability for long life and low capital costs, an ultrafast charging and discharging time, safety—to be easily sited and decommissioned—and flexibility, to fit a shipping container and be placed at the site for operation. in addition, the al-ion ess is portable, for ease of construction and transport, and is modular, for high reliability and ease of maintenance. the al-ion ess will use grid-integrating optimizing software, making the al-ion ess dispatchable. al-ion batteries fit all of these innovative ess time-shifting design approach requirements. because of time-shifting, stored electricity is now dispatchable daily, from the al-ion ess, when needed, not when produced by intermittent and variable wind and solar renewable energy. the iso grid scheduler knows in advance the amount of al-ion ess stored power available to supply the interconnection grid, the next day, and can easily plan for conventional power plant reserve capacity—in the unlikely event it is deemed necessary. thus, there is no longer the need to closely match intermittent and variable renewable energy electrical supply with variable electricity demand—resulting in a more reliable electric power system (prentis, 2014b). the al-ion ess is calculated to cost only 25% of expensive ngct peaker plants currently in use on the interconnection grid, over its 30 years expected life. total savings come from time-shifting wind and solar power, thereby using the power more efficiently. in addition, al-ion batteries are expected to be much less costly than li-ion batteries, now being used on interconnection gridscale esss. therefore, al-ion ess costs should further decline, over time. total wind and solar pacc values are considerably improved, significantly reducing the need for expensive standby ngct peaker plants—thereby reducing costs by 75% and making the al-ion ess dispatchable and efficient. in addition, this advanced al-ion ess improves performance by making the interconnection grid more reliable and better able to handle changing customer demands, relieves transmission congestion and decreases unscheduled power outages—and also provides ancillary services, thereby increasing system-wide benefits by 30-to-40%—further reducing effective al-ion ess costs, perhaps to zero. 6. conclusion and policy implications a creative, cost-effective, time-shifting, grid-scale al-ion ess for wind and solar renewable energy electricity generation is explained in this paper. the innovative time-shifting al-ion ess design approach decouples electricity production from use, by first producing renewable energy electricity—then delivering this electricity to the al-ion ess—and only then supplying electricity from the al-ion ess, to the interconnection grid, 24 h later. electricity is never delivered directly from the renewable energy sources, to the interconnection grid, in real time, as is the current ess smoothing and stabilizing practice. the innovative al-ion ess time-shifting design concept permits the decoupling of wind and solar electricity generation, from when and where the renewable resource power is produced, to when and where the power is needed, which are major new advantages over the existing ess approach. the interconnection grid-scale, low maintenance al-ion timeshifting ess is valuable, not only to deal with the unpredictable changes in weather, but as importantly, to deal with the continual changes in electrical demand. the advanced al-ion time-shifting ess improves performance by making the interconnection grid more reliable and better able to handle varying customer demands, relieves transmission congestion and decreases unscheduled power outages. in addition, the time-shifting, al-ion ess provides ancillary services; thereby improving system-wide benefits by 30-to-40%, further reducing effective ess costs, perhaps to zero. having abundant, dispatchable, reliable, efficiently produced electricity, available from renewable energy, is the goal fulfilled in this paper. the new, grid-scale al-ion time-shifting ess presented is economically efficient and universally advantageous—for power generation suppliers, consumers and the environment. when the al-ion ess design approach becomes policy, and is fully implemented; it will materially transform and modernize the electric power industry. prentis: reconstructing renewable energy: making wind and solar power dispatchable, reliable and efficient international journal of energy economics and policy | vol 6 • issue 1 • 2016 133 references bruce, p.g., freunberger, s.a., hardwick, l.j., tarascon, j.m. (2012), li-o2 and li-s batteries with high energy storage. nature materials, 11(1), 19-29. electric reliability council of texas (ercot). (2015), report on the capacity, demand and reserves (cdr) in the ercot region, 2016-2025, may 4, 2015. available from: http:// www.ercot.com/content/gridinfo/resource/2015/adequacy/cdr/ capacitydemandandreservereport-may2015.pdf. energy storage association. (2015), blattner energy completes construction of one of the largest battery storage projects in the world, february 12, 2015. available from: http://www.energystorage.org/ news/esa-news/blattner-energy-completes-construction-one-largestbattery-storage-projects-world. gtm research and the energy storage association. (2015), u.s. energy storage monitor 2014 year in review, february 20, 2015. available from: https://www.greentechmedia.com/research/us-energy-storagemonitor. jayaprakash, n., das, s.k., archer, l.a. (2011), the rechargeable a l u m i n i u m i o n b a t t e r y. c h e m i c a l c o m m u n i c a t i o n s , 4 7 , 12610-12612. lamont, a.d. (2013), assessing the economic value and optimal structure of large-scale electricity storage. ieee transactions on power systems, 28(2), 911-921. lin, m., gong, m., lu, b., wu, y., wang, d., guan, m., angell, m., chen, c., yang, j., hwang, b., dai, h. (2015), an ultrafast rechargeable aluminium-ion battery. nature, 520(7547), 325-328. liu, m., lee, w., lee, l.k. (2014), financial opportunities by implementing renewable sources and storage devices for households under ercot demand response programs design. ieee transactions on industry applications, 50(4), 2780-2787. liu, s., dougal, r.a., weidner, j.w., gao, l. (2005), a simplified physics-based model for nickel hydrogen battery. journal of power sources, 141, 326-339. mit technology review. (2015), researchers solve key challenges with energy-dense lithium-air batteries, january 27, 2015. available from: http://www.technologyreview.com/news/534446/advance-doublesthe-longevity-of-high-energy-electric-car-batteries/. mon, r. (2013), a new structured aluminium-air secondary battery with a ceramic aluminium ion conductor. rcc advances, 3(29), 11547-11551. parkinson, g., (2015), renew economy, even at $10/barrel, oil can’t match solar on cost, march 2, 2015. available from: http://www. reneweconomy.com.au/2015/even-at-10barrel-oil-cant-match-solaron-cost-37540. prentis, e.l. (1987), operations management taxonomy. journal of operations management, 7(1), 63-78. prentis, e.l. (2014a), deregulation & privatization: texas electric power market evidence. review of business and finance studies, 5(2), 117-126. prentis, e.l. (2014b), u.s. electrical system reliability: deregulated retail choice states’ evidence and market modeling. international journal of energy economics and policy, 4(4), 588-598. prentis, e.l. (2015a), evidence on u.s. electricity prices: regulated utility vs. restructured states. international journal of energy economics and policy, 5(1), 253-262. prentis, e.l. (2015b), texas interconnection grid: economic optimal capacity utilization rate evidence. international journal of energy economics and policy, 5(3), 686-692. the brattle group. (2014), the value of distributed electricity storage in texas: proposed policy for enabling grid-integrated storage investments, november 2014. available from: http://www.brattle. com/system/news/pdfs/000/000/749/original/the_value_of_ distributed_electricity_storage_in_texas.pdf?1415631708. u.s. energy information administration (eia). (2013), capital cost for electricity plants: updated capital cost estimates for utility scale electricity generating plants, april 12, 2013. available from: http:// www.eia.gov/forecasts/capitalcost/. u.s. energy information administration (eia). (2015), annual energy outlook 2015. available from: http://www.eia.gov/forecasts/aeo/ index.cfm. u.s. department of energy: office of scientific and technical information. (2015), wind vision: a new era for wind power in the united states, march 2015. available from: http://www.energy. gov/sites/prod/files/wv_executive_summary_overview_and_key_ chapter_findings_final.pdf. wan, l.f., prendergast, d. (2014), the solvation structure of mg ions in dichloro complex solutions from first-principles molecular dynamics and simulated x-ray absorption spectra. journal of the american chemical society, 136(41), 14456-14464. wang, w., jiang, b., xiong, w., sun, h., lin, z., hu, l., tu, j., hou, j., zhu, h., jiao, s. (2013), a new cathode material for super-valent battery based on aluminium ion intercalation and deintercalation. scientific reports, 3, 3383. xiong, l., xu, y., tao, t., du, x., li, j. (2011), double roles of aluminium ion on surface-modified spinel limn1,97tl0.03o4. journal of materials chemistry, 21(13), 4937-4944. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(3), 367-373. international journal of energy economics and policy | vol 13 • issue 3 • 2023 367 the effects of environmental cost, environmental disclosure and environmental performance on company value with an independent board of commissioners as moderation imam hidayat1*, tubagus ismail2, muhamad taqi3, agus sholikhan yulianto4 1phd scholar, university of sultan ageng tirtayasa, indonesia, 2department of accounting, faculty of economics and business, university of sultan ageng tirtayasa, indonesia, 3department of accounting, faculty of economics and business, university of sultan ageng tirtayasa, indonesia, 4department of accounting, faculty of economics and business, university of sultan ageng tirtayasa, indonesia. *email: imam_accounting@yahoo.com received: 08 january 2023 accepted: 21 april 2023 doi: https://doi.org/10.32479/ijeep.14159 abstract company value is one of the most important indicators to increase the company’s competitiveness in the midst of very tight business competition. this study aims to determine the effects of environmental cost, environmental disclosure, environmental performance on company value with an independent board of commissioners as moderation partially and simultaneously. this research was conducted on the indonesia stock exchange in 2018-2021. purposive sampling was used as the sampling method and 14 companies were obtained. multicollinearity test and heteroscedasticity test were used as the classical assumption test. eviews 9 software with panel data regression analysis was used to test the hypothesis. based on the results of the study, it was found that environmental costs have a negative effect on company value, environmental disclosure has no effects on company value, environmental performance has no effects on company value, environmental costs have negative effects on value companies with an independent board of commissioners as moderation, environmental disclosure has no effect on company value with an independent board of commissioners as moderation, and environmental performance has no effects on company value with an independent board of commissioners as moderation. keywords: environmental cost, environmental disclosure, environmental performance, company value, an independent board of commissioners jel classifications:  m0, m2, m4, h0 1. introduction the development of the industrial world cannot be separated from the expansion of business operations carried out by business actors in order to grow their business to increase the value of the companies they manage on the other hand, the impact of competition among companies related to the value of the company occurs because many companies deliberately ignore the environment in which the business is establishedby ignoring the side effects of the production activities they cause. there are several cases regarding the environment in indonesia, with the latest case involving pt. toba pulp lestari, tbk (inru). based on the indonesian peasant union (spi) in 2021, pt. toba pulp lestari, tbk cut down the forest that threatens lake toba, causing siltation of lake toba, the damaged of the forest because they are almost gone as air reservoir, biological wealth is lost and the asahan river is polluted which causes fish population to reduce and even die. communities around the pt. toba pulp lestari, tbk did not get even the slightest benefit but they experienced loss as a result of damaged road infrastructure, land disputes, air pollution, deforestation, improper waste disposal in accordance with amdal, and other social impacts such as the criminalization of 70 indigenous people around current biology. this journal is licensed under a creative commons attribution 4.0 international license hidayat, et al.: the effects of environmental cost, environmental disclosure and environmental performance on company value with an independent board of commissioners as moderation international journal of energy economics and policy | vol 13 • issue 3 • 2023368 that is pt. toba pulp lestari, tbk which does not perform environmental performance well, but only seeks profit for the company. a similar action is taken by sampoerna agro tbk’s (hmsp) subsidiary, pt national sago prima (nsp), which polluted the air by burning 3,000 hectares of forest in pt nsp’s concession area in meranti regency, riau. forest fires cause smoke to pollutethe air in the burning area which stops the activities of the surrounding community. the ministry of environment and forestry (klhk) filed an appeal to the supreme court (ma). after conducting the trial, pt nsp was found guilty of deliberately burning the forest. as a result of their actions, pt nsp had to pay a fine of rp 1.07 trillion to carry out land restoration actions. this condition makes investors interested and encourages the market believe not only in the company’s performance but also in the company’s promising future in terms of its good company value. based on the identification of the problems described above and considering the many factors that are thought to affect firm value, this research is limited to environmental cost, environmental disclosure and environmental performance on company value with an independent board of commissioners as moderation in manufacturing companies listed on the indonesia stock exchange. 2. literature review a theory can be interpreted as a series of interconnected concepts that serve to systematically and in-depth describe an issue or event. a systematic description explains variables and aims to describe and explain the phenomenon. 2.1. legitimacy theory the legitimacy theory explains how a company carries out its operating activities continuously in accordance with the norms and values that apply in society. (spence, heleich, and stapp, 1973) argues that legitimacy is a company management system that is oriented towards taking sides with the community (society), the environment, government, individuals, and community groups. according to (dura and purnaningsih, 2018). legitimacy is important for organizations, boundaries are imposed by social norms and values, and reactions to these limits encourage the importance of analyzing organizational behavior with respect to the environment. according to sari (2013) the legitimacy theory is a company activity that is limited by a corporate social contract that reports its social activities will be recognized and accepted by the community. according to sari (2013), legitimacy theory states that an organization can only survive if the community around the organization believe that the organization operates based on a value system compatible with those owned by the community. according to suchman’s system of standards, values, beliefs, and definitions (2015), legitimacy can be considered as an entity’s efforts to convince various parties that the actions that have been taken are needed, appropriate or in accordance with those standards. 2.2. contingency theory contingency theory was first introduced by lawrence and lorsch (1967) and then used by kazt and rosenzweig (1973). this theory stated that there is no best way to achieve conformity between organizational and environmental factors to obtain good performance for an organization. contingency theory argues that the design and system of controls depend on the organizational context in which the controls are implemented (fisher, 1998). according to raybun and thomas (1991) contingency theory states that the selection of an accounting system by the management depends on differences in the pressures of the company’s environment. according to sari, (2006) contingency theory is a theory that can be used to study the organizational design, performance and behavior as well as studies related to strategic arrangements. contingency theory assumes that leadership is a process of a leader’s ability to exert influence depending on the group task situation and the levels of leadership style, personality and approach appropriate to the group. a person does not become a leader because of his personality traits, but rather because of various situational factors and the interaction between the leader and the situation, fiedler in manaley, usman and devega (2013). 2.3. the value of the company company value is a condition that the company has achieved as a sign of public’s trust in the company. high corporate value is an achievement for the company because it can bring prosperity and profitability for shareholders and make the market believe not only in the company’s performance but also in future prospects. investors believe thatthe value of the company is an important concept that the market uses as an indicator to judge the company as a whole. firm value, which is closely related to rizka’s share price (2019), is an investor’s perception of the company’s level of success. if a company were to be sold, its value would be determined by the sale price that potential purchasers would be prepared to make, according to husnan (2000). the company’s goal is to pay attention to the welfare of the owner of the company by optimizing the value of the company. 2.4. environmental accounting the concept of environmental accounting has been developing since the 1970s in europe. in the mid-1990s the international accounting standards committee (iasc) developed the concept of international accounting principles, including the development of environmental accounting and human rights audits. in addition, industry standards are also growing and professional auditors such as the american institute of certified public auditors (aicpa) issue universal principles on environmental audits. the background of the importance of environmental accounting basically demands full awareness of companies and other organizations that have benefited from the environment. it is important for companies or other organizations to increase their efforts to consider environmental conservation in a sustainable manner. companies are encouraged to use environmental hidayat, et al.: the effects of environmental cost, environmental disclosure and environmental performance on company value with an independent board of commissioners as moderation international journal of energy economics and policy | vol 13 • issue 3 • 2023 369 accounting concepts to minimize the environmental problems. many large industrial and service companies are now implementing environmental accounting. the aim is to improve the efficiency of environmental management by assessing environmental activities from the standpoint of environmental costs and economic benefits. 2.5. environtemtal cost environmental costs include from all the most tangible costs (such as waste disposal), to measure uncertainty and they are basically related to important elements of good management decision-making such as products, processes, systems, or facilities rohelmy et al. (2015). hansen and mowen (2007) state that environmental costs are those that result from or may result from poor environmental quality. thus, environmental costs relate to the creation, detection, improvement, and prevention of environmental degradation. 2.6. environtemtal disclosure environmental disclosure is the disclosure of information related to the environment in the company’s annual report, suratno et al. (2006). disclosure is the provision of useful data to those who need it. when associated with the annual report, disclosure means an annual report that must provide information clearly and accurately describe economic events that affect the operating results of the business unit. the information disclosed must be useful and not confusing in order to assist the users of the annual report in helping to make economic decisions (by ghozali and chariri [2010]). according to hendriksen and breda (2004) disclosure is the presentation of information needed to achieve optimum operations in an efficient capital market. this implies that sufficient information must be provided to enable prediction of trends in future dividends and the variability and covariability of future returns in the market. the emphasis should be on the preferences of experienced investors and financial analysts. 2.7. environtemtal performance environmental performance is the company’s performance in creating a good environment suratno et al. (2006). environmental performance is the company’s performance to create a green environment in accordance with the expectations of stakeholders. environmental performance is one of the investments for companies to achieve business success. in line with the legitimacy theory, if the company’s environmental performance is good,public opinion of the company will have a positive opinion of it, and vice versa. when the public has positive opinion of the company, the public also views the company positively. 2.8. an independent board of commissioners independent commissioners are members of the board of commissioners who are not affiliated with management, other members of the board of commissioners and controlling shareholders. they are also free from business relationships or other relationships that may affect their ability to act independently or act solely in the interests of the company amelia and hernawati (2016). independent commissioners are in the best persons to carry out the monitoring function in order to create a good corporate governance company. 3. research methodology 3.1. research approach this study uses quantitative data, descriptive and associative research to describe whether events are true or false and to explain the relationship between the variables studied by interpreting data collected, processed, analyzed, and presented. we can conclude that this study was intended to do so. hypothesis. this study examines the causal relationship of each variable, including independent, dependent, and moderating variables. in addition, this research was conducted through a causal comparative study. 3.2. place and time of research this study uses secondary data though online downloading the annual report and sustainability reports of manufacturing companies listed on the idx in the period 2018-2021 via the internet. the downloaded data is of course data that has been published on the indonesia stock exchange website. 3.3. research variables the dependent variable in this study is firm value. in this study, there are three independent variables, namely: environmental cost, environmental disclosure, environmental performance. the moderating variable in this study is the independent board of commissioners. an independent board of commissioners is a member of the board of commissioners who is not affiliated with management, other members of the board of commissioners and the controlling shareholder. he is also free from business relationships or other relationships that may affect his ability to act independently or act solely in the interests of the company. the following table 1 gives an explanation of the operational definition of the variables used in the study. 3.4. sampling method in this study, not all of the research population will be the object of research, so sampling techniques must be carried out. this research uses non-probability sampling technique and purposive sampling method. purposive sampling is a method of determining the sample by using certain criteria and reviews as the data source. 3.5. data retrieval method this study uses secondary data, annual report data and sustainability report data that researchers indirectly obtained from the official website www.idx.co.id which has been published by the indonesia stock exchange. 3.6. data analysis method panel data regression analysis method is commonly used in quantitative data analysis with the help of software eviews version 9. panel data regression analysis is also useful in knowing the whether relationship between the dependent and the independent variable is negative or positive and estimating the value of the dependent variable which is influenced by the magnitude of the increase or decrease of the independent variable. hidayat, et al.: the effects of environmental cost, environmental disclosure and environmental performance on company value with an independent board of commissioners as moderation international journal of energy economics and policy | vol 13 • issue 3 • 2023370 1. descriptive statistics test the meanstandard deviation, maximum and minimum analysis were the analysis tool used. descriptive statistics provide a very important numerical measure for sample data. the eviews 9 program was used to conduct descriptive statistical tests. 2. estimation of panel data regression to estimate the regression model using panel data, it is necessary to go through 3 strategies that can be used, and they are as follows: a. common effects model (cem) y xit k kit it k n � � � � �� � �0 1 b. fixed effects model (fem) y x x xit it it it it it� � � � �� � � � �0 1 1 2 2 3 3 c. random effects model (rem) y x x xit it it it it it� � � � �� � � � �0 1 1 2 2 3 3 3. selection of panel data estimation model techniques the following is a test scheme in determining the panel data regression model to be used in panel data regression analysis (figure 1). 4. research results and discussion 4.1. description of research object this is a type of quantitative research that performs statistical testing of secondary data. based on the criteria that have been set in sampling, this study uses a sample of manufacturing companies in indonesia from 2018 to 2021. from the information above, 201 manufacturing companies that will be used as data sources for analysis are obtained. the selection process used is as follow in table 2. based on the sampling criteria above, it can be seen that 14 companies can be sampled during the observation period. a total of 56 data were collected over the 4-year research observation period (from 2018 to 2021). the summary of the general description of the company is as follows in table 3. 4.2. data presentation 1. stock closing price the closing price of shares is obtained from the official website of the indonesia stock exchange, namely www.idx.co.id. 2. number of shares outstanding the number of outstanding shares is obtained from the official website of the indonesia stock exchange, namely www.idx.co.id. 3. total equity total equity used in this study was obtained from the statement of financial position of each company that became the research sample. 4. total debt the total debt used in this study was obtained from the statement of financial position of each company as the research sample. table 2: sample selection criteria s. no criteria total 1. manufacturing companies listed on the indonesia stock exchange for the period 2018-2021. 201 2. manufacturing companies that do not consistently publish annual reports in the research year of 2018-2021 (59) 3. manufacturing companies that do not consistently publish sustainability reports in the research year of 2018-2021 (33) 4. manufacturing companies that suffered losses during the research period of 2018-2021 (63) 5. manufacturing companies that are not registered as participants in the environmental management performance rating program (proper) from the ministry of environment between 2018 and 2021 (32) total sample company 14 research period (years) 4 number of research data samples 56 table 1: operational definition s. no variables definition measurements scale 1 the value of the company firm value is an investor’s perception of value where this is often associated with the company’s stock price. q emv d ebv d � � � ratio 2 environmental costs environmental costs in this study are independent variables that are proxied using the ratio between total environmental costs and total net profit after tax. ec � �biayalingkungan lababersihsetelahpajak ratio 3 environmental disclosure disclosure is the provision of useful data to those who need it. ed � �itempengungkapanlingkungan totalselurnhitempengungkapan ratio 4 environmental performance environmental performance is one of the investments for companies to achieve business success. proper score ratio 5 an independent board of commissioners an independent board of commissioners is a member of the board of commissioners who is not affiliated with management. komisris independen komisaris independen anggotadewankomisar � � iis� �100% ratio hidayat, et al.: the effects of environmental cost, environmental disclosure and environmental performance on company value with an independent board of commissioners as moderation international journal of energy economics and policy | vol 13 • issue 3 • 2023 371 5. total environmental cost total environmental costs used in this study were obtained from the annual reports of each company as the research sample. 6. total net profit total environmental costs used in this study were obtained from the annual reports of each company as the research sample. 7. environmental disclosure score the environmental disclosure score used in this study was obtained from the sustainability reports of each company as the research sample. 4.3. data calculation based on the results of the tests that have been carried out and described above, the following conclusions can be drawn (table 4). 5. conclusion based on the results of statistical tests and based on the discussion described in the previous chapter, the conclusions of this study are as follows: 1. environmental costs have a negative and significant effect on firm value as evidenced by the p-value of 0.0000 <0.05 significance level and the t arithmetic value > t table (2.742077 > 2.00758). 2. environmental disclosure has no effect on firm value as evidenced by the p-value of 0.3037 > the significance level of 0.05 and the t value < t-table (1.043941 < 2.00758). 3. environmental performance has no effect on firm value as evidenced by the p-value 0.2031 > a significance level of 0.05 and the value of t count < t table (1.297187 < 2.00758). 4. the independent board of commissioners has no effect on firm value as evidenced by the p-value 0.7031 > 0.05 significance level and the t count < t table (0.384333 < 2.00758). 5. the independent board of commissioners is able to moderate environmental costs, which can be proven by a p-value of 0.0087 < 0.05 significance level and t arithmetic value > t table (2.780603 > 2.00758). 6. the independent board of commissioners is not able to moderate environmental disclosure which can be proven by a p-value of 0.1489 > a significance level of 0.05 and a t count < t table (1.476054 < 2.00758). 7. the independent board of commissioners is not able to moderate environmental disclosure which can be proven by a p-value of 0.1489 > a significance level of 0.05 and a t count < t table (1.476054 < 2.00758). 8. the independent board of commissioners is not able to moderate environmental performance which can be proven by a p-value of 0.2729 > a significance level of 0.05 and a t count < t table (1.114017 < 2.00758). 6. suggestions based on the conclusions and limitations above, the author suggests the following: 1. for company in this era of development that has seen a significant increase in environmental activities, companies, especially manufacturing companies, are expected to conduct further research on the effects of environmental cost, environmental disclosure and environmental performance in order to increase company value. companies should be aware of the importance of environmental sustainability in the era of development that has implemented green accounting. companies must apply environmental accounting according to established standards to ensure that environmental sustainability is maintained. and the independent board of commissioners should provide direction and extra supervision to the management to implement and run environmental accounting table 4: conclusion of test results hypothesis conclusion h1: environmental cost has an effect on firm value accepted h2: environmental disclosure affects company value rejected h3: environmental performance has an effect on company value rejected h4: independent board of commissioners has an effect on company value rejected h5: independent board of commissioners moderates environmental cost to company value accepted h6: independent board of commissioners moderates environmental disclosure on corporate values rejected h7: independent board of commissioners moderates environmental performance on company values rejected table 3: company sample list s. no code company name 1 asii pt. astra international tbk 2 dlta pt. delta djakarta tbk 3 hmsp pt. h.m sampoerna tbk 4 icbp pt. indofood cbp sukses makmur tbk 5 indf pt. indofood sukses makmur tbk 6 intp pt. indocement tunggal perkasa tbk 7 issp pt. steel pipe industry of indonesia tbk 8 kaef pt. kimia farma tbk 9 klbf pt. kalbe farma tbk 10 myor pt. mayora indah tbk 11 sido pt. sido muncul tbk 12 smgr pt. semen indonesia tbk 13 ultj pt. ultra jaya milk tbk 14 unvr pt. unilever indonesia tbk figure 1: panel data regression model selection scheme hidayat, et al.: the effects of environmental cost, environmental disclosure and environmental performance on company value with an independent board of commissioners as moderation international journal of energy economics and policy | vol 13 • issue 3 • 2023372 in order to increase the value of the company in the eyes of the public and investors. 2. for further researchers a. for further research, it is expected to add the number of variables that will be used. b. further research is expected to use more years of observation and more samples in order to better describe the actual situation. c. further research can be carried out in different sectors such as the mining sector or the property sector. references  aisiyah, r.n. (2018), pengaruh environmental performance terhadap economic performance. journal of multidisciplinary studies, 2, 1-11. al-tuwaijiri, s.a., christensen, t.e., huges, k.e. (2004), the relations among environmental disclosure, environmental performance, and economic performance: a simultaneous equations approach. accounting, organizations and society, 29, 447-471. al-tuwaijri, s.a., christensen, t.e., hughes k.e. 2nd. (2005), the relations among environmental disclosure, environmental performance, and economic performance: a simultaneous equations approach. ssrn electronic journal. amaliyah, f., herwiyanti, e. (2019), pengaruh kepemilikan institusional, dewan komisaris independen, dan komite audit terhadap nilai perusahaan sektor pertambangan. jurnal akuntansi, 9(3), 187-200. amelia, w., hernawati, e. (2016), pengaruh komisaris independen, ukuran perusahaan dan profitabilitas terhadap manajemen laba. neo~bis, 63. angraeni, s. (2020), pengaruh environmental performance, environmental cost dan environmental disclosure terhadap nilai perusahaan. riset akuntansi, 8(235), 245. aniela, y. (2018), peran akuntansi lingkungan dalam meningkatkan kinerja lingkungan dan kinerja keuangan perusahaan. berkala ilmiah mahasiswa akuntansi, 1(1), 15-19. apip, m., sukomo, faridah, e. (2020), pengaruh environmental performance dan environmental disclosure terhadap economic performance. jurnal wawasan dan riset akuntansi, 7, 62-77. rizka, a. (2019), pengaruh leverage, profitabilitas dan ukuran perusahaan terhadap nilai perusahaan pada perusahaan otomotif yang terdaftar di bursa efek indo. skripsi universitas muhammadiyah sumatera utara, 8, 244-252. handayani, a.r. (2010), pengaruh environmental performance terhadap environmental disclosure dan economic performance serta enviromental disclosure terhadap economic performance. indonesia: skripsi undip. p1-109. ariesanti, a. (2017), the relations among enviromental performance. the indonesian journal of accounting research, 20, 99-116. azzahra, a.s., nasib, w. (2019), pengaruh firm size dan leverage ratio terhadap kinerja keuangan pada perusahaan pertambangan. jwem stie mikroskil, 9, 13-20. basuki, a.t., prawoto, n. (2016), analisis regresi dalam penelitian ekonomi dan bisnis. jakarta. jakarta: pt raja grafindo persada. buana, v.a., nuzula, n.f. (2017), pengaruh environmental cost terhadap profitabilitas dan nilai perusahaan. jurnal administrasi bisnis s1 universitas brawijaya, 50(1), 46-55. paramitha, b.w., rohman, a. (2014), pengaruh karakteristik perusahaan terhadap environmental disclosure. e jurnal akuntansi s1 undip, 3(3). cristofel, c., kurniawati, k. (2021), pengaruh enterprise risk management, corporate social responsibilty dan kepemilikan institusional terhadap nilai perusahaan. jurnal akuntansi bisnis, 14(1), 1-12. dananjaya, p.m., mustanda, i.k. (2016), pengaruh keputusan investasi, keputusan pendanaan, dan kebijakan dividen terhadap nilai perusahaan. e-jurnal manajemen, 5. daromes, f.e., kawilarang, m.f. (2020), peran pengungkapan lingkungan dalam memediasi pengaruh kinerja lingkungan terhadap nilai perusahaan. jurnal akuntansi, 14(1), 77-101. dewi, a.s., sari, d., abaharis, h. (2018), pengaruh karakteristik dewan komisaris terhadap kinerja perusahaan manufaktur di bursa efek indonesia. jurnal benefita, 3, 445. dewi, l.c., nugrahanti, y.w. (2017), pengaruh struktur kepemilikan dan dewan komisaris independen terhadap nilai perusahaan (studi pada perusahaan industri barang konsumsi di bei tahun 2011–2013). kinerja, 18(1), 64-80. dianawati, c.p., fuadati, s.r. (2016), pengaruh csr dan gcg terhadap nilai perusahaan: profitabilitas sebagai variabel intervening. jurnal ilmu dan riset manajemen, 5(1), 1-20. dura, j., purnaningsih. (2018) pengaruh profitabilitas, likuiditas, solvabilitas, dan ukuran perusahaan terhadap audit report lag pada perusahaan yang terdaftar di bursa efek indonesia. jurnal ilmiah bisnis dan ekonomi asia, 11(1), 64-70.  eksandy, heriyanto, a.d.f. (2017), metode penelitian akuntansi dan keuangan. tangerang: universitas muhammadiyah tangerang. epi, y. (2017), pengaruh ukuran perusahaan, struktur kepemilikan manajerial dan manajemen laba terhadap kinerja perusahaan property dan real estate yang terdaftar pada bursa efek indonesia. riset dan jurnal akunta,  1(1), 1-7. ermaya, h.n.l., mashuri, a.a.s. (2020), the influence of environmental performance, environmental cost and iso 14001 on financial performance in non-financial companies listed on the indonesia stock exchange. neraca: jurnal akuntansi terapan 1(2), 74-83. fisher, g.j., (1998), contingency theory, management control systemand firm outcomes: past results and future directions. behavioural research in accounting, 10(supplement), 47-64. ghozali, i., chariri, a., (2007), teori akuntansi. semarang: badan penerbit undip. hansen/mowen., (2007), akuntansi manajerial. buku 2. edisi 8. salemba empat.jakarta. hendriksen dan van breda., (2004), accounting theory. mc graw hill:international edition. husnan, s., (2000), manajemen keuangan teori dan penerapan (keputusan jangka panjang) buku 1. yogyakarta: bpfe. kast, f., rosenzweig, j., (1973), contingency views of organization and management, science research associates, chicago, il. lawrence, p.r., lorsch, j.w., (1967), organization and environment: managing differentiation and integration. irwin, homewood. rayburn, j.m., rayburn, l.g., (1991), contingency theory and the impact of new accounting technology in uncertain hospital environments. accounting, auditing, accountability journal, 4(2), 55-75. rohelmy, f.a., zahroh z.a., dan r. rustam hidayat, (2015), efektivitas penerapan biaya lingkungan dalam upaya meminimalkan dampak lingkungan (studi pada pt. emdeki utama). jurnal administrasi bisnis (jab), 2(2), 2015. sari, r.n., ainuddin, r.a. dan tengku abdullah, t.a. (2006), kesan padanan antara perakaunan pengurusan strategik dengan strategi perniagaan terhadap prestasi firma. jurnal pengurusan, 25, 87-109. sari. 2013, “pengaruh pengungkapan csr terhadap nilai perusahaan dengan profitabilitas sebagai variabel pemoderasi”. e-jurnal akuntansi universitas udayana 5.3. spence, j.t., heleich, r., stapp, j. 1973, a short version of the attitudes toward women scale (aws). bulletin of the psychonomic society 2(4): 219-20. hapsoro, d., ambarwati, a., wicaksono, c.a. (2020), relationship analysis of eco-control, company age, company size, carbon emission hidayat, et al.: the effects of environmental cost, environmental disclosure and environmental performance on company value with an independent board of commissioners as moderation international journal of energy economics and policy | vol 13 • issue 3 • 2023 373 disclosure, and economic consequences. the indonesian journal of accounting research, 23(2), 293-324. harahap, s.s. (2011), teori akuntansi. jakarta: pt raja grafindo persada. harjito, d.a., martono. (2014), manajemen keuangan. yogyakarta: ekonisia.  hermiyetti, dondokambey, g.y. (2012), analisis perlakuan akuntansi dan pengalokasian biaya lingkungan pada pt aspex kumbong. jurnal infestasi, 8(1), 63-80. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 1 • 2023 1 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(1), 1-6. the concept of waste management on economic development in the european union azwardi azwardi*, alghifari mahdi igamo, wahyu aji wijaya department of economic and development, faculty of economics, sriwijaya university, indonesia. *email: azwardi@fe.unsri.ac.id received: 02 september 2022 accepted: 20 december 2022 doi: https://doi.org/10.32479/ijeep.13667 abstract this study aims to analyze whether the circular economy variables which include per capita municipal waste production, municipal waste recycling rate, packaging waste recycling rate by type of packaging, bio-waste recycling, and e-waste recycling rates have an effect on economic development. measured by gdp per capita (gross domestic product) in european union countries. the methodology in this study uses panel data with estimates using the common effect model, fixed effect model, random effect model and uses the best testing method, namely the chow, hausman, and lagrange multiplier tests in 28 countries in the european union for the period 2000-2020. the results showed that the final model used was the fixed effect model. overall the concept of a circular economy which includes the level of recycling of municipal waste, the level of recycling of packaging waste by type of packaging, recycling of bio-waste, recycling of e-waste and added value in the euro currency has a significant and positive effect on economic development as measured through per capita income, while waste production per capita is inversely proportional to that it has no significant and positive effect on economic development in european union countries. it can be concluded that the application of the circular economy concept can ensure economic growth while reducing the use of natural resources and ensuring great environmental protection. keywords: waste management, circular economy, economic development, sustainable development jel classifications: q01, q53, o10 1. introduction in the circular economy, the amount of waste is minimized through the careful design of new products and industrial processes in which materials are continuously circulated in closed-loop systems (fischer and pascucci, 2013). waste has become a very important issue in all countries. it has been estimated that approximately 80% of all materials and consumer goods are wasted and more than 30% of processed foods are wasted once they enter the food supply chain (scheel et al., 2020). the circular economy concept promotes environmental protection and social welfare (jawahir and bradley, 2016) and enables economic growth in line with sustainable development. a circular economy can reduce the environmental damage of the entire system and promote new value creation. the european commission has estimated that the transition to a circular economy will bring additional economic benefits of €600 billion annually to manufacturing in the european union (korhonen et al., 2018). current linear production methods consume energy at all stages of production. it is based on the “extract-produce-usedump” model and represents an unsustainable model of production. enable the economic system. amount of waste. the idea behind the circular economy concept came from recognizing the negative environmental impact of linear production methods. this paper determines the application of the circular economy concept in the context of contemporary economic development at two levels. the first level covers the theoretical considerations of the circular economy that modern economies around the world need to achieve resource and economic sustainability. the second, at the applied level, examines the impact of economic development in european union member states in relation to implementing a circular economy and achieving sustainable economic development. using the eurostat index, researchers explored the relationship between this journal is licensed under a creative commons attribution 4.0 international license azwardi, et al.: the concept of waste management on economic development in the european union international journal of energy economics and policy | vol 13 • issue 1 • 20232 gross domestic product income and per capita waste generation in selected member states of the european union, with it determined the use of secondary raw materials, and the extent to which added value in a circular economy would lead to an increase in gross domestic product. 2. literature review ghisellini et al., (2016) explains the term circular economy has been studied since the 1970s. pierce and turner examine the impact of natural resources on economic systems and their impact on linear, open-ended perspectives. experimental results show an important contribution. economic and ecological aspects must coexist and be balanced (geissdoerfer et al., 2017). the economy as a closed loop to avoid the negative impacts of waste, create new jobs, and achieve resource efficiency and dematerialization of the industrial economy. initially, the circular economy concept was based on the 3rs (reduce, reuse, recycle), but more recently it has moved to the 6rs (reuse, recycle, redesign, remanufacture, reduce, recover) (jawahir and bradley, 2016). in addition to exploiting limited natural resources, the circular economy ensures a wide range of mechanisms for creating new value. a circular economy can be defined in many ways. here are some of the most cited definitions of the circular economy. “at the heart of the circular economy is a (closed) cycle of resource and energy consumption in multiple phases” (franklin-johnson et al., 2016). another definition is “a spiral cycle economy, h. a system that minimizes material and energy flows and damage to the environment without limiting economic growth or social and technological progress” (geng et al., 2009). george et al., (2015) states that “the goal of the circular economy is to create the highest value products, components and materials over time.” as one of the key principles of the circular economy released allow all materials. because those near or at the end of their life cycle can be used again as input for manufacturing the next generation of products (tukker, 2015; van weelden et al., 2016). consumer engagement plays a key role in implementing a circular economy (sijtsema et al., 2020). however, the circular economy concept implies systemic change based on innovation and the use of new technological systems, as well as changes in the environment. nature and methods include politics, society, business models, and financing methods (domenech and bahnwalkowiak, 2019). the last goal is to construct a system that allows materials, product components and output to be recycled in such a way that their highest value is preserved for the longest time. at the same time, resources must be able to be redesigned and desegregated into the economic complex or used as natural food. the advantage connected with the new business model are purely numerical. mayer et al., (2019) assessing improved resource use efficiency saves him 17-24% of raw materials and his €630 million in costs in europe. based on product-based modeling, it is estimated that applying circular economy concepts could increase eu gdp by 3.9% by 2030. the idea of applying circular economy concepts is prevalent in european union documents and legislation, but different judgement have been expressed by experimenters (clift and druckman, 2015; haupt et al., 2017; kovanda, 2014). most exploration on the usage of circular economy concepts focuses on concrete products or parts of manufacturing processes (huysman et al., 2017). science of some elements of the manufacturing cycle has increased significantly in recent years (cullen and allwood, 2013; graedel et al., 2015; reck and graedel, 2012), making it possible to apply circular economy concepts to specific companies. improved ability to do so or industry (lieder and rashid, 2016; pauliuk et al., 2012). a comprehensive assessment of circularity along the national or macro level is almighty abnormal (haas et al., 2015; hashimoto et al., 2004). some previous exploration have focused on finding innovations in strategies and business models in the circular economy driven by new ventures. it is intended to complement well-known theories of sustainable innovation. furthermore, it contributes to the possibility of operationalizing circular business models through pre-defined frameworks (bigliardi and filippelli, 2021). a concept known as a circular deck also emerged/this concept helps companies analyze, generate ideas and grow their business into a circular ecosystem full of potential innovations (konietzko et al., 2020). the european union keep up to strive to get a circular economy in order to achieve greater sustainability. the european commission has adopted a series of measures affiliated to the circular economy. this includes banning the use of single-use plastics, improving legislation on waste prevention and production of critical raw materials (european commission), and better monitoring of eu 28 circular economy indicators (meyer, 2012). uni europe adopted a circular economy strategy and action plan in 2015, aimed at a more successful implementation of the circular economy in the economy (geissdoerfer et al., 2017). strategies and actions for implementing the circular economy concept lays out the steps necessary to implement recycling and waste management schemes in the european union. it also mentions measures to effectively “close the loop” in the economic cycle and the handling of products throughout the product life cycle, from production to consumption to disposal. european regulations aim to reduce the generation and management of high quality waste, save energy and consume less resources by 2030. with this strategy, the eu has adopted a new legal framework in which investments support the transformation of the economy towards a circular economy in order to harden the economy, increase competitiveness and secure coming economic growth. this strategy will ensure that developed countries move further away from economies that discard linear products. in this way waste is reduced while avoiding the use of natural resources in the production process itself. waste trading is liberalized in the sense that it can be more facilitated through virtual means and used as support for awareness campaigns aimed at building eco-industrial parks (hartley et al., 2020). ribić et al., (2017) although the problem of the recycling -type economy is increasing, croatia has no framework or policies yet. the design framework focuses on how to manage waste in croatian capital and the concept of the circulation economy. (geng et al., 2009) discuss the need for transition from linear economy to circulation economy. trica et al., (2019) states that the circulation economy is one of her ways to hit resource effectiveness. andabaka azwardi, et al.: the concept of waste management on economic development in the european union international journal of energy economics and policy | vol 13 • issue 1 • 2023 3 (2018) accent the advantages of relate a circulating economic principle to the croatian economy and the transition to the economic model. robaina et al., (2020) shows the importance of shifting from linear economy to circulatory economy. in addition, krlec analyzes the topic of the circulatory economy and explains the application and advantages of implementing manufacturing and waste management using general methods. pimenta, (2022) is examining what means to realize the concept of a recycling economy at the eu level, including croatia. since this concept is also attracting attention from legislators and policy proppons, it has influenced governments and international organizations at local, region, international, and international levels to promote new economic concepts (bocken et al., 2017; geisendorf and pietrulla, 2018). 3. methods there is no adequate research on the impact of economic development on the implementation of a circular economy. therefore, to achieve sustainable economic development the author uses this study which includes the following variables gdp per capita, value-added eur, municipal waste generation per capita (kg), recycling rate of municipal waste (%), recycling rate of packaging waste by type of packaging (%), recycling of bio-waste (kg per capita), recycling rate of e-waste. the panel data regression equation model can be seen in the following equation: gdpit = β0 + β1 (mwgit) + β2 (rrmit) + β3 (rrpit) + β4 (rrbit) + β5 rre (phit) + β6 (vait) + eit data for each eu member state (28) for the period 2000-2020 is obtained from eurostat. this research refers to the study conducted by (van langen et al., 2021; skrinjarić, 2020; trica et al., 2019). the purpose of circular economies is how well they live up to expectations and how much impact they have on a number of european countries. in addition, the methodology is designed to enable the evaluation of the sustainability of the circular economy model using indicators and verifying the influence of environmental factors. this study uses panel data regression analysis with 3 output models, namely the common effect model, fixed effect model, and random effect model. in selecting the output of the three models, it is necessary to test the best model using the chow test, hausman test, and lm test. 4. results and discussion 4.1. summary data of waste management and economic development in table 1, the countries with the highest average gdp are luxembourg, ireland, and the netherlands. statistical data on the volume of municipal waste per capita, countries that have the highest per capita waste generation are denmark (773 kg/capita), luxembourg (694 kg/capita) and cyprus (660 kg/capita). this data already shows a correlation between gdp and the volume of waste. positive examples with respect to this indicator include the czech republic (340 kg/capita), romania (318 kg/capita), and poland (306 kg/capita). a very important indicator is also the recycling rate, which shows that although certain countries produce large amounts of waste, they also have high recycling rates by packaging waste by type of packaging such as, belgium (78%), netherlands (67%), and denmark (65%). it can be seen from what is explained above that the indicator is not the only relevant one. according to huysman et al., (2017) using indicators to measure the effectiveness of various possibilities for processing plastic waste in a circular economy. this measure takes into account the flow of plastic waste and its technical quality, and monitors consumption resources through cumulative exergy extraction. saidani et al., (2019) research is linked to the circular economy by highlighting the remaining 37 major challenges, such as effective uptake by industry. moraga et al., (2019) provides a classification framework for categorizing circular economy indicators based on what (ce strategy) and how (environmental measurement). howard et al., (2019) provides a framework for developing circular economy indicators related to the core objectives and principles of the circular economy. looking at the circular economy and economic growth, we can see the economic drivers underlying the development of the circular economy at the eu level (busu, 2019). trica et al., (2019) conduct a study on the economic drivers of sustainable circular economy development, building on insights from the economic literature in this area. d’adamo et al., (2020) examine the relationship between recycling, gdp and population. they conclude that gdp and population growth will lead to increased recycling. he built a circular economy model with two kinds of economic resources, pollution input and recycling input. their results point to several factors that play important roles in economic development. these factors are the level of pollution caused by using the pollutant, the costs incurred by using the pollutant, the recycling rate, and the recycling of inputs relative to the marginal product. an assessment of the sustainability of circular economy models can be performed by monitoring various environment-related indicators and determining the model’s impact on economic growth in the european union (walker et al., 2018). in line with this, it is important to analyze measurable indicators and improve implementation concepts to strengthen circular economy implementation (haas et al., 2015; walker et al., 2018). 4.2. analysis of panel regression the results of this article show that the common effect, fixed effect, and random effect models can be seen in table 2: from the output results above, there are significant differences in results between the three models. in the common effects model, it is found that the environmental variable has a positive and significant relationship below 5% except for added value with a negative relationship to per capita income in european union countries. in the fixed effect model, all variables have coefficients and a positive directional relationship with per capita income, only the municipal waste generation per capita variable has no significant effect on per capita income as indicated by a probability value above 5% (0.654). in the third model all variables have a positive directional relationship and have a significant effect on per capita income, except for municipal waste generation per capita which has no significant effect. the three panel data regression azwardi, et al.: the concept of waste management on economic development in the european union international journal of energy economics and policy | vol 13 • issue 1 • 20234 models also have a relatively high r-squared value, the average r-squared level is above 52%, or it can be said that the variation in the income per capita variable can be explained by the circular economy variable of 52%. the panel data regression method requires testing the best model test using the chow test, which is to determine whether the common effect model is better than the fixed effect model and vice versa. hausman test to see if the random effect model is better than the fixed effect model and vice versa. lm test to see whether the common effect model is better to use than the random effect model. the results of the three tests can be seen in table 3. table 3 above can be seen that in the chow test the probability value is 0.0000 or <0.05, it can be said that the prob f value is less than 0.05 then ho is rejected and h1 is accepted, so it can be concluded that from the results of the chow test the best model is obtained, namely the estimation with fixed effects. for the second test, namely the hausman test, it can be seen that the cross section random probability value is 0.0001 or < 0.05, it can be said that ho is rejected and h1 is accepted so that the best model table 1: important indicator of waste management and economic development in eu country gdp per capita value add (million eur) municipal waste generation (per capita per year) recycling rate of municipal waste (%) recycling rate of packaging (%) recycling rate of bio waste (kg per capita) recycling rate of e-waste (%) austria 32147.6 2222.4 581.1 59.5 66.5 198.7 39.5 belgium 30023.8 1915.2 451.3 53.6 78.4 96.4 32.5 bulgaria 10981.0 267.6 525.7 22.8 57.2 8.8 68.3 croatia 15085.7 407.2 386.5 15.6 55.5 7.9 63.0 cyprus 23619.0 198.4 660.4 9.8 48.2 5.3 17.8 czechia 21300.0 1109.2 340.9 16.9 67.8 15.0 33.6 denmark 31990.5 1953.4 773.7 44.4 64.8 128.8 43.4 estonia 17319.0 164.8 376.6 20.8 54.4 13.5 36.9 finland 28919.0 1564.6 501.0 36.1 55.3 54.9 37.5 france 27219.0 14697.6 529.0 35.4 58.3 85.0 26.6 germany 30485.7 28380.0 610.8 62.4 70.8 103.0 36.5 greece 19981.0 1186.8 470.9 15.1 50.3 10.9 26.2 hungary 16504.8 804.2 417.4 19.8 49.5 16.0 39.3 ireland 38909.5 931.2 654.9 31.8 58.6 26.7 40.9 italy 26247.6 14380.1 520.1 31.1 60.0 61.6 28.3 latvia 14523.8 180.7 359.6 14.6 51.0 11.2 25.6 lithuania 16481.0 241.2 421.6 19.7 54.2 34.5 36.9 luxembourg 66395.2 253.9 694.2 45.3 63.6 129.7 35.9 malta 22309.5 281.2 628.0 9.6 31.6 16.0 12.4 netherlands 33852.4 3536.3 562.8 49.7 68.7 144.2 33.6 poland 15481.0 2494.8 306.6 16.7 45.7 12.7 27.9 portugal 20014.3 1233.3 475.1 20.7 52.6 49.8 32.9 romania 12671.4 1685.4 318.6 7.2 46.8 10.4 18.3 slovakia 17204.8 573.1 317.1 14.0 56.2 18.1 41.2 slovenia 21357.1 238.2 470.0 31.5 59.5 28.3 27.9 spain 23785.7 11464.7 533.1 31.1 59.0 81.6 25.6 sweden 31628.6 3107.2 456.1 45.2 63.9 59.2 56.7 united kingdom 28009.5 18176.4 531.1 33.2 56.7 60.4 32.5 source: data processed, e-views table 2: panel data regression results variable common fixed random coefficient prob coefficient prob coefficient prob c 4.9498 0.0000 6.8719 0.0000 7.1831 0.0000 mwg 0.5838 0.0000 0.0286 0.6454 0.1033 0.0796 rrm 0.0858 0.0107 0.1319 0.0000 0.1275 0.0000 rrp 0.2733 0.0000 0.2446 0.0000 0.2415 0.0000 rrb 0.0887 0.0000 0.0299 0.0562 0.0345 0.0248 rre 0.0160 0.6073 0.1323 0.0000 0.1074 0.0000 va −0.0283 0.0007 0.1464 0.0007 0.0524 0.0210 r-squared 0.6383 0.9146 0.5278 f-statistic 130.2835 135.0535 82.5149 prob (f-statistic) 0.0000 0.0000 0.0000 source: data processed, e-views table 3: best model test model chow test hausman test lm test prob 0.0000 0.0001 0.0000 source: data processed, e-views azwardi, et al.: the concept of waste management on economic development in the european union international journal of energy economics and policy | vol 13 • issue 1 • 2023 5 based on the hausman test is an estimate with fixed effect or it can be said that the fixed effect model is more appropriate to use than the hausman test. with a random effects model. in both tests, we can conclude that the best model used in this study is to use the fixed effect model estimation. table 4 describes if 1% increase in gdp per capita means an average increase of about 0.14 eur in value added, 0.028 kg of waste per capita, 0.013% in municipal waste recycling rate, about 0.0024% in packaging waste recycling rate, approximately 0.002 kg/capita in bio-waste recycling, and 0.0013% in e-waste recycling rates. based on the estimation results, it can be concluded that the greater the gdp, the greater the volume of municipal waste per capita. in 2018, luxembourg had the highest gdp (78,900 eur per capita), as well as having the highest volume of waste at 803 kg/capita. in 2017, the country with the highest rate of use of secondary raw materials was the netherland and had lower levels of waste volume among the countries observed in the higher gdp range. the relationship between circular economy and higher gdp is evidenced by the fact that all developed countries like germany, austria, netherlands, denmark and sweden have larger numbers in circular economy and higher gdp. the results display that the developed countries of the european union generate more waste, but also provide except pointer of circular economy implementation. on the other hand, in order to achieve better results in the world’s developing countries, more financial resources need to be invested in activities such as research and development, new technology development and innovation. it is also essential that environmental activists become more involved in activities that promote a circular economy (sijtsema et al., 2020). achieving these two goals of hers will improve the implementation of sustainable economic development in eu member states. 5. conclusion this research theme will determine the application of the circular economy concept in eu member states from 2000 to 2020 and how the implementation of the circular economy affected economic growth. the most common linear economic model is based on the belief that resources are limitless and that there is infinite space for waste disposal. such models are clearly unsustainable and must be changed. the circular economy concept remains a poorly understood concept by all economic stakeholders and the general public. the transition to a circular economy requires not only changes in single activities, but systemic changes in industry, social elements, energy, transport, agriculture, etc. since each economic sector has its own principles and limits, and each country in the european union is unique, transitioning to a circular economy requires different approaches and timeframes. from the results of this study, it can be concluded that there is a link between economic development and circular economy indicators. the application of circular economy concepts cannot just wait for government intervention or subsidies. businesses and citizens can also take their own initiatives towards the transition, starting with waste sorting, recycling, and energy conservation. by adopting the concept of circular economy, companies can address inefficiencies in their business organization such as resource scarcity, taxation and externalities more. a circular economy model can generate income and create new jobs that most countries, especially croatia, need. a circular economy model successfully combines economic and environmental benefits and contributes to the further development of entrepreneurship. by using waste as a resource and applying circular economy principles, we can reach new milestones in economic development. we need to continue to stimulate our citizens both economically and educationally, and the transition to a circular economy, including infrastructure issues and technological advances. addressing this will require greater social engagement, cooperation at local and national levels, adoption of new business models, support of industrial clusters for by-product trading, and new urban management systems, which will require this will take some time. recommendations for further research will certainly be put forward to investigate whether the republic of croatia is ready to move towards a circular economy and which countries can be used as examples of better practice. from this we can conclude that, in addition to investments in information, education and technology dissemination, it is also necessary to: by applying the concept of circular economy, it develops and strongly promotes entrepreneurship at both medium and large scale. references andabaka, a. (2018), challenges of circular economy in croatia. international journal of multidisciplinarity in business and science, 4(5), 115-126. bigliardi, b., filippelli, s. (2021), investigating circular business model innovation through keywords analysis. sustainability (switzerland), 13(9), 13095036. bocken, n.m.p., olivetti, e.a., cullen, j.m., potting, j., lifset, r. (2017), taking the circularity to the next level: a special issue on the circular economy. journal of industrial ecology, 21(3), 476-482. busu, m. (2019), adopting circular economy at the european union level and its impact on economic growth. social sciences, 8(5), 8050159. clift, r., druckman, a. (2015), taking stock of industrial ecology. in: taking stock of industrial ecology. germany: springer nature. p.1-362. table 4: final model using fixed effect model correlation value add municipal waste generation per capita (kg) recycling rate of municipal waste % recycling rate of packaging waste (%) recycling of bio-waste (kg per capita) recycling rate of e-waste (%) coefficient 0.146439 0.028635 0.131883 0.244563 0.029896 0.132328 prob <0.05 >0.05 <0.05 <0.05 <0.05 <0.05 source: data processed, e-views azwardi, et al.: the concept of waste management on economic development in the european union international journal of energy economics and policy | vol 13 • issue 1 • 20236 cullen, j., allwood, j. (2013), mapping the global flow of aluminum: from liquid aluminum to end-use goods. environmental science and technology, 47, 304256s. d’adamo, i., gastaldi, m., rosa, p. (2020), recycling of end-oflife vehicles: assessing trends and performances in europe. technological forecasting and social change, 152, 119887. domenech, t., bahn-walkowiak, b. (2019), transition towards a resource efficient circular economy in europe: policy lessons from the eu and the member states. ecological economics, 155, 7-19. fischer, a., pascucci, s. (2013), institutional incentives in circular economy transition: the case of material use in the dutch textile industry. journal of cleaner production, 155, 48. franklin-johnson, e., figge, f., canning, l. (2016), resource duration as a managerial indicator for circular economy performance. journal of cleaner production, 133, 589-598. geisendorf, s., pietrulla, f. (2018), the circular economy and circular economic concepts-a literature analysis and redefinition. thunderbird international business review, 60(5), 771-782. geissdoerfer, m., savaget, p., bocken, n.m.p., hultink, e.j. (2017), the circular economy-a new sustainability paradigm? journal of cleaner production, 143, 757-768. geng, y., zhu, q., doberstein, b., fujita, t. (2009), implementing china’s circular economy concept at the regional level: a review of progress in dalian, china. waste management, 29(2), 996-1002. george, d.a.r., lin, b.c., chen, y. (2015), a circular economy model of economic growth. environmental modelling and software, 73, 60-63. ghisellini, p., cialani, c., ulgiati, s. (2016), a review on circular economy: the expected transition to a balanced interplay of environmental and economic systems. journal of cleaner production, 114(7), 11-32. graedel, t.e., harper, e.m., nassar, n.t., reck, b.k. (2015), on the materials basis of modern society. proceedings of the national academy of sciences of the united states of america, 112(20), 6295-6300. haas, w., krausmann, f., wiedenhofer, d., heinz, m. (2015), how circular is the global economy? an assessment of material flows, waste production, and recycling in the european union and the world in 2005. journal of industrial ecology, 19(5), 765-777. hartley, k., van santen, r., kirchherr, j. (2020), policies for transitioning towards a circular economy: expectations from the european union (eu). resources conservation and recycling, 155, 104634. hashimoto, s., moriguchi, y., saito, a., ono, t. (2004), six indicators of material cycles for describing society’s metabolism: application to wood resources in japan. resources conservation and recycling, 40, 201-223. haupt, m., vadenbo, c., hellweg, s. (2017), do we have the right performance indicators for the circular economy? insight into the swiss waste management system. journal of industrial ecology, 21(3), 615-627. howard, m., hopkinson, p., miemczyk, j. (2019), the regenerative supply chain: a framework for developing circular economy indicators. international journal of production research, 57(23), 7300-7318. huysman, s., de schaepmeester, j., ragaert, k., dewulf, j., de meester, s. (2017), performance indicators for a circular economy: a case study on post-industrial plastic waste. resources conservation and recycling, 120, 46-54. jawahir, i.s., bradley, r. (2016), technological elements of circular economy and the principles of 6r-based closed-loop material flow in sustainable manufacturing. procedia cirp, 40, 103-108. konietzko, j., bocken, n., hultink, e.j. (2020), a tool to analyze, ideate and develop circular innovation ecosystems. sustainability (switzerland), 12(1), 12010417. korhonen, j., honkasalo, a., seppälä, j. (2018), circular economy: the concept and its limitations. ecological economics, 143, 37-46. kovanda, j. (2014), incorporation of recycling flows into economy-wide material flow accounting and analysis: a case study for the czech republic. resources conservation and recycling, 92, 78-84. lieder, m., rashid, a. (2016), towards circular economy implementation: a comprehensive review in context of manufacturing industry. journal of cleaner production, 115, 36-51. mayer, a., haas, w., wiedenhofer, d., krausmann, f., nuss, p., blengini, g.a. (2019), measuring progress towards a circular economy: a monitoring framework for economy-wide material loop closing in the eu28. journal of industrial ecology, 23(1), 62-76. meyer, b. (2012), macroeconomic modelling of sustainable development and the links between the economy and the environment. gws research report. p.1. available from: https://www.gws-os.com/ discussionpapers/gws-researchreport12-1.pdf moraga, g., huysveld, s., mathieux, f., blengini, g.a., alaerts, l., van acker, k., de meester, s., dewulf, j. (2019), circular economy indicators: what do they measure? resources conservation and recycling, 146, 452-461. pauliuk, s., wang, t., müller, d.b. (2012), moving toward the circular economy: the role of stocks in the chinese steel cycle. environmental science and technology, 46(1), 148-154. pimenta, c.c.d.c. (2022), la economía circular como eje de desarrollo de los países latinoamericanos. ciencia latina revista científica multidisciplinar, 5(6), 14623-14638. reck, b.k., graedel, t.e. (2012), challenges in metal recycling. science, 337(6095), 690-695. ribić, b., voća, n., ilakovac, b. (2017), concept of sustainable waste management in the city of zagreb: towards the implementation of circular economy approach. journal of the air and waste management association, 67(2), 241-259. robaina, m., villar, j., pereira, e. (2020), the determinants for a circular economy in europe. environmental science and pollution research, 27(11), 12566-12578. saidani, m., yannou, b., leroy, y., cluzel, f., kendall, a., saidani, m., yannou, b., leroy, y., cluzel, f., kendall, a. (2019), a taxonomy of circular economy indicators. journal of cleaner production, 207, 542-559. scheel, c., aguiñaga, e., bello, b. (2020), decoupling economic development from the consumption of finite resources using circular economy. a model for developing countries. sustainability (switzerland), 12(4), 1291. sijtsema, s.j., snoek, h.m., van haaster-de winter, m.a., dagevos, h. (2020), let’s talk about circular economy: a qualitative exploration of consumer perceptions. sustainability (switzerland), 12(1), 12010286. skrinjarić, t. (2020), empirical assessment of the circular economy of selected european countries. journal of cleaner production, 255, 120246. trica, c.l., banacu, c.s., busu, m. (2019), environmental factors and sustainability of the circular economy model at the european union level. sustainability (switzerland), 11(4), h11041114. tukker, a. (2015), product services for a resource-efficient and circular economy-a review. journal of cleaner production, 97, 76-91. van langen, s.k., vassillo, c., ghisellini, p., restaino, d., passaro, r., ulgiati, s. (2021), promoting circular economy transition: a study about perceptions and awareness by different stakeholders groups. journal of cleaner production, 316, 128166. van weelden, e., mugge, r., bakker, c. (2016), paving the way towards circular consumption: exploring consumer acceptance of refurbished mobile phones in the dutch market. journal of cleaner production, 113, 743-754. walker, s., coleman, n., hodgson, p., collins, n., brimacombe, l. (2018), evaluating the environmental dimension of material efficiency strategies relating to the circular economy. sustainability (switzerland), 10(3), 10030666. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 3 • 2023102 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(3), 102-110. the causal relation between energy consumption, carbon dioxide emissions, and macroeconomic variables in somalia zakarie abdi warsame1,3*, maria mohamed ali1, liban bile mohamud2, farhia hassan mohamed1 1faculty of economics, simad university, mogadishu, somalia, 2somalia national bureau of statistics, somalia, 3kasmotute insttitute for technology, logistics and economics research (kitler), somalia. *email: zakariye1968@gmail.com received: 20 january 2023 accepted: 05 april 2023 doi: https://doi.org/10.32479/ijeep.14262 abstract this study investigated the relationship between energy consumption, carbon dioxide emissions, and macroeconomic variables in somalia with data spanning from 1990 to 2019 using ardl model. the study found a negative long-run relationship between carbon dioxide emissions and energy consumption in somalia, suggesting that improving access to clean energy can reduce the gradual rise of carbon dioxide emissions. the study also found that rising industrial value-added had a significant positive impact on energy consumption. furthermore, findings from cholesky’s variance decomposition showed that 13.13% of future fluctuations in energy consumption are due to shocks in carbon dioxide emission, 33.63% of future fluctuations in carbon dioxide emissions are due to shocks in energy consumption, 40.63% of future fluctuations in industrialization are due to shocks in energy consumption and 41.23% of future fluctuations in population are due to shocks in energy consumption. there was evidence of a bidirectional causality between: energy consumption and population. the study suggests adding renewable energy technologies to the energy portfolio. this would help reduce reliance on unstable energy sources and reduce the chance that changes in commodity prices will interrupt the energy supply, which eventually would help reduce the effects of climate change. keywords: energy consumption, industrialization, trade openness, somalia and ardl jel classifications: p18, o14, q53 1. introduction energy consumption and related services to meet social and economic development and improve human health and welfare are increasing due to the requirement to meet basic human needs and productivity (edenhofer et al., 2011). the energy development of a country is closely related to the economic development of the country. a country’s economic growth is directly influenced by its ability to provide energy to its citizens. achieving the millennium development goals (mdgs) depends heavily on access to energy. it is undoubtedly evident that energy inadequacies have a close association with poverty indicators, such as illiteracy, life expectancy, infant mortality, fertility rates, and rapid urbanization in developing countries like somalia; this is because rural residents migrate to urban areas in search of better living conditions and social amenities (lipton and ravallion, 1995). due to the limited energy supply in somalia, the rapid growth of the urban population is currently being hampered by energy insecurity. around 80-90% of all energy consumption in somalia comes from wood and charcoal (african development bank, 2015). electricity provision in somalia has been the primary responsibility of the country’s thriving private sector since the collapse of the central government in 1991. as of right now, the total production capacity is around 106 megawatts. while most utilities still use gasoline power plants to generate electricity, hybrid systems that take advantage of renewable sources like solar and wind are attracting more and more attention and funding. recent research by the african development bank found that somalia has the greatest resource potential for coastal wind power in africa, with the capacity to produce between 30,000 and 45,000 megawatts. solar panels could generate more than 2,000 kwh/m2 of energy. this journal is licensed under a creative commons attribution 4.0 international license warsame, et al.: the causal relation between energy consumption, carbon dioxide emissions, and macroeconomic variables in somalia international journal of energy economics and policy | vol 13 • issue 3 • 2023 103 around one-sixteenth of the population, by some estimates, has access to modern power. somalia has more expensive taxes than its neighbors, kenya and ethiopia (u.s. agency for international development). somalia consumed 12,100,621,000 btu (0.001 quadrillion btu) of energy in 2017, representing 0.00% of global energy consumption. the country produced 156,621,000 btu (0.00 quadrillion btu), covering 1% of its annual energy consumption (somalia energy statistics-worldometer, n.d.). despite this, since 1960, carbon dioxide emissions from the combustion of fossil fuels have tripled. concerns have grown due to the realization that human-caused carbon dioxide emissions significantly contribute to climate change. emissions of carbon dioxide and models of economic performance may be critical for understanding the connections between population growth and financial performance. rapid economic growth and demographic expansion contribute to environmental deterioration (chandia et al., 2018). several economic and legal factors are making the environmental situation around the world worse. these factors operate in different areas and have varying degrees of impact and consequences. they include a macroeconomic policy that encourages the overuse of natural resources, an investment policy that prioritizes using natural resources, and a sectoral policy that needs improving, especially in the fuel and energy industry (shpak et al., 2022). somalia’s co2 emissions are relatively low compared to other countries due to its limited industrialization and low per capita energy consumption. somalia’s energy sector is primarily based on fossil fuels, with oil accounting for about 95% of the country’s total energy consumption. however, due to the ongoing civil conflict and lack of infrastructure, energy access is limited, and the country’s total co2 emissions remain low. according to the (world bank, n.d.), somalia’s co2 emissions in 2018 were estimated to be 0.06 metric tons per capita, which is significantly lower than the global average of 4.8 metric tons per capita. however, it is important to note that somalia, like other developing countries, is vulnerable to the impacts of climate change, including sea-level rise, droughts, and floods. besides, conservation policies can greatly affect how well the economy does because every economy depends a lot on how much energy is used. so, testing macroeconomic and environmental variables in the real world is important, as it is crucial to clarifying policy implications and recommendations. since per capita income is associated with energy consumption, economic growth can also be identified as the primary cause behind the increase in energy consumption over the last decade (asumadu-sarkodie and owusu, 2016a). nevertheless, no consensus has been achieved about the pattern of the causal link between rising macroeconomic output and energy consumption in somalia. in light of this, the study investigates the relationship between macroeconomic variables, carbon dioxide emissions, and energy consumption in somalia. the research makes an effort to address the gap in the literature on energy-emissions economic analysis, which has been spotty and scarce in somalia. in order to assess how each random innovation affects energy usage, carbon dioxide emissions, and increased macroeconomic output the research estimates the variance decomposition using cholesky’s approach. finally, reliable estimation methods based on auto regressive distributive lag ardl, and granger causality test are used to provide more extensive scheme suggestions from somalia’s energy consumption. the paper is structured as follows: section 2 reviews the relevant literature, section 3 describes the research methodology and data, section 4 presents the study’s findings, and section 5 concludes with policy implications. 2. literature review the literature provides ample documentation of the dynamic causal connection between energy consumption and environmental pollution. the primary objective of these investigations was to describe temporal relationships, but bivariate models were used extensively. there appears to be no consensus regarding the dynamic causal relationship between energy consumption and environmental pollution. possible causes of inconclusive results include misspecification of estimated models, bias from omitted variables, or failure to select true lag lengths (which are very sensitive to granger causality). table 1 represents a few of the existing literature examined in the study with their subsequent econometric method, the length of the data employed, and the findings of their study. 3. methodology the study examines the causal nexus between energy consumption, carbon dioxide and macroeconomic variables in somalia. a time series data spanning from 1990 to 2019 were employed from world bank, sesric and world data. six study variables were used in the study which include ec-energy-consumption (kilogram of oil equivalent per capita); co2-carbon dioxide emissions (kt); totrade openness; ind-industry, value added (constant 2015 us$), which is a proxy for industrialization; gdppc-rgdp per capita (constant 2015 us$); and pop-population. a linear representation of the relationship between energy consumption, carbon dioxide and macroeconomic variables in somalia is showed in eq. (1): inec f inco into inind inpop ingdppct t t t t t= ( , ), , ,2 (1) where inect, inco2t, intot, inindt, lnpopt and lngdppct represent a natural logarithmic transformation of co2, to, ind, pop and gdppc for a more stable data variance. the empirical specifications for the model can be quantified as: warsame, et al.: the causal relation between energy consumption, carbon dioxide emissions, and macroeconomic variables in somalia international journal of energy economics and policy | vol 13 • issue 3 • 2023104 inec inco into inind inpop ingdpc t t t t t t t � � � � � � � � � � � � � � 0 1 2 3 4 5 2 (2) where inect is the dependent variable, while inco2t, intot, inindt, inpopt and ingdppct are the explanatory variables in year t, εt is the error term, and β0, β1, β2, β3, β4 and β5 are the elasticities to be estimated. the first step in testing for cointegration is investigating the order of integration of the variables. we apply augmented dickey-fuller (adf) and philips-perron (pp) stationarity tests to determine if the series are cointegrated. once the series become stationary, we select the lag order and investigate whether there are cointegrating relationships between variables. to examine the long run relationship among the model variables, there are several tests of cointegration. the first one that has been extensively used and discussed in the literature is the popular engle and granger test which is applicable only for same order integrated variables. subsequently, many other approaches have been developed some of which are the error correction cointegration technique of johansen which is more general and flexible than the engle and granger approach, phillips and ouliaris test, johansen and juselius test, the structural error correction model (ecm) proposed by (boswijk, 1994), and the test suggested by (banerjee et al., 1998a) which is based on the t-test for the null hypothesis. however, these standard approaches have been criticized as being highly unreliable in small samples, inconsistent with different order integrated variables, lead to significantly misleading results and biased against the rejection of null hypothesis (no-cointegration) which requires an adjustment for critical values (shahbaz et al., 2015). hence, in order to increase the power of test, more robust cointegration technique is employed which is autoregressive distributed lag (ardl) bounds testing approach. following the empirical work of (sarkodie and adams, 2018) the ardl cointegration equation can be written as: � � � � � � � � � � � � inec inco into inind inpop in t t t t t � � � � � � 0 1 1 2 1 3 1 4 1 5 2 ggdppc inec inco into t i q t k i p t k i p t k � � � � � � � � � � � � � � � � 1 0 1 0 2 0 32 � � � �� � � � � � � � � � � � � � � � � i p t k i o p t k i p t k t inind inpop ingdppc 0 4 5 0 6 � � � � kk (3) where α0 is the constant, α1–α6 are the coefficient of the shorttun variables, β1-β5 are the elasticities of long-run parameters, q indicates the explained’s optimal lags, p shows the optimal lags of the explanators, δ is the first difference sign showing short run variables and εt is the error term. the ardl cointegration approach begins with bound testing, which is then regressed using ordinary least squares (ols). the null hypothesis (h0): β1 = β2 = β3 = β4 = β5 = β6 = β7 = β8= 0 implies variables are not cointegrated in the long-run whereas the alternative hypothesis (h1): β1 ≠ β2 ≠ β3 ≠ β4 ≠ β5 ≠ β6 ≠ β7 ≠ 0 implies variables are cointegrated in the long-run. the wald-f statistics and critical values were employed to test the null hypothesis. if the wald-f statistics exceed the upper bound critical values, the null hypothesis is rejected, indicating that the variables are linked in the long run and vice versa. 4. results and discussion 4.1. descriptive analysis and correlation matrix we examined the characteristics of the data series using descriptive statistics presented in table 2. results in table 2 report the mean of energy consumption (2.48), carbon dioxide (12.79), trade table 1: summary of the related literature reference time period econometric approach dv iv findings (asumadu-sarkodie and owusu, 2017) 1960-2013 vecm euse co2, fid, ind, gdppc, pop ec↔fd, ec↔ind, ec↔pop, co2↔fd, co2↔gdppc (warsame, 2023) 1990-2019 ardl co2 fdi, rec, gdppc, pg, k co2→pg, rec→pg (shahbaz et al., 2015) 1980-2012 vecm co2 ec, fp, tsva co2↔ec, tsva↔co2, fp→co2, fp→ec, fp→tsva (rafindadi and ozturk, 2015) 1971-2012 ardl ngc gdp, lf gdp does not granger-cause ngc (warsame and sarkodie, 2021) 1985-2017 nardl defo ec, rgdpc, and pg pg↔gdp, gdp→pg, gdp→ec (warsame et al., 2022) 1990-2017 ardl ed rec, pop. iq, rgdpc, and k no causality is observed from renewable energy to environmental degradation and vice versa. (lin et al., 2015) 1980-2011 vecm co2 gdp, ec, and pop weak long-run causality from ec to co2 (asumadu-sarkodie and owusu, 2016b) 1980-2012 vecm co2 gdp, ec, and pop co2↔ec, gdp↔ec, pop→co2 (cerdeira bento and moutinho, 2016) 1960-2011 ardl co2 gdp, reep, nreep, and int gdp→reep, nreep→reep (mohiuddin et al., 2016) 1971-2013 vecm co2 ec and gdp ec→co2 (chen et al., 2019) 1980-2014 ardl co2 gdp, r, n, and t long-run causality from gdp, the square of gdp, rec, n, and t to co2. (salahuddin et al., 2015) 1980-2012 fmols co2 gdp, ec, and fd long-run causality from gdp to co2 (dong et al., 2018) 1993-2016 vecm co2 gdp, ff, nu, and re long-run causality among co2, ff, nu, and rec warsame, et al.: the causal relation between energy consumption, carbon dioxide emissions, and macroeconomic variables in somalia international journal of energy economics and policy | vol 13 • issue 3 • 2023 105 openness (1.44), industrialization (7.86), population (6.57), and gdp per capita (2.47). besides, industrialization and population have the highest maximum values of 8.27, and 6.85 respectively. energy consumption, population, and gddpc are positively skewed while co2, trade openness, and industrialization are negatively skewed. furthermore, the correlation of the sampled variables presented in table 3 shows that carbon dioxide, trade openness, industrialization, population, and gdp per capita are negatively correlate with energy consumption in somalia. 4.2. unit root test testing the unit root properties is a prerequisite in time series modeling, specifically ardl. hence, augmented dickey-fuller (adf) and philips perron (pp) tests were utilized to circumvent spurious regression results. the unit root analysis reported in table 4 shows lnec is stationary at level [i (0)], whereas the remaining series has unit root. however, table 4 shows that most of the series are integrated at first difference [i (1)] while only lnec is integrated at [i (0)]. since none of the variables are stationary at second difference i (2), we proceeded to estimate the bounds test cointegration. 4.3. cointegration test results of the bounds test presented in table 5 examine the presence of long-run co-integration between energy consumption and the explanator variables. however, the results show the wald f-statistics (13.06530) is above the upper bound critical value (3.38) at 5% significance level. this infers the variables are cointegrated in the long run. 4.4. ardl long-run and short-run results with diagnostics the long-run estimations of the ardl method are presented in table 6, with some diagnostic test statistics. the results show a negative long-run significant relationship between carbon dioxide emission and energy consumption in somalia. in other words, carbon dioxide emissions are negatively related to energy consumption in the long run, which has a policy implication in somalia. it is likely that reducing carbon dioxide emissions through the adoption of renewable and clean energy technologies will eventually improve energy consumption in somalia in the long run. this finding is in line with the findings of (asumadusarkodie and owusu, 2017). the impact of rising industrial value added also has significant positive impact on energy consumption. the rise in industrial activities requires more energy to contribute to the gross domestic product. a 1% rise in industrial value-added increases energy consumption by 1.34% in the long run. population is found to be negatively related to energy consumption in the long run. this implies that a 1% increase in population leads a decrease of 2.040% to energy consumption in the long run. this contradictory finding may be attributable to the fact that a large proportion of the somali population resides in rural areas and is typically unable to obtain oil or fuel. finally, the study found that variables of trade openness and gdppc are insignificant in the long run. our results indicating that an increase in industrial value-added leads to increased energy consumption are in line with the findings of (lovins, 1990), (shahbaz and lean, 2011). table 2: descriptive statistics of variables stats lec lco2 lto lind lpop lgdppc mean 2.483004 12.785123 1.435547 7.862481 6.571825 2.474741 median 2.483861 2.795866 1.411702 7.910259 6.566554 2.461671 maximum 2.764392 2.863323 2.027635 8.265808 6.852656 2.622711 minimum 2.357120 2.690196 0.750508 7.434153 6.341225 2.340999 sd 0.076813 0.043834 0.463578 0.272687 0.165930 0.089644 skewness 1.392708 −0.514309 −0.011466 −0.143373 0.179796 0.129722 jarque-bera 31.04760 1.446313 3.062268 2.508708 2.246811 1.833647 p-value 0.000000 0.485218 0.216290 0.285260 0.325171 0.399787 table 3: correlation matrix lec lco2 lto lind lpop lgdppc lec 1 lco2 −0.0042 1 lto −0.7191 0.3411 1 lind −0.7721 0.2503 0.9797 1 lpop −0.8085 0.2914 0.9754 0.9821 1 lgdppc −0.6198 0.5987 0.9138 −0.8959 0.8948 1 table 4: unit root variables t-statistics at level adf pp lnec −7.4709*** −6.2445*** lnco2 −2.6578 −2.3435 lnto −1.1355 −2.9312 lnind −2.2516 −2.2305 lnpop −2.9307 −2.5392* lngdppc −2.3044 −2.5738 at first difference δinco2 −3.4250* −3.4618* δinto −4.5596*** −4.5596*** δinind −5.9256*** −5.8817*** δinpop −4.4759*** −1.6335 δingdppc −5.6156*** −5.6063*** ***, **, *indicate the significance level at 1%, 5%, and 10%. δ denotes first difference operator. the t-statistics reported are the intercept and trend table 5: f bounds test f-statistic level of significance (%) bounds test critical values i (0) i (1) 13.06530 1 3.06 4.15 5 2.39 3.38 10 2.08 3 warsame, et al.: the causal relation between energy consumption, carbon dioxide emissions, and macroeconomic variables in somalia international journal of energy economics and policy | vol 13 • issue 3 • 2023106 our results indicating the negative effect of population increase on energy consumption are corroborated by numerous studies such as (kunvitaya and dhakal, 2017), (ohlan, 2015), and (otsuka, 2018) who conclude that population density has a negative impact on energy consumption. diagnostic check results show no serial correlation, heteroscedasticity, model misspecification, and normality problems in the ardl model. also, the coefficients of the ardl model are found stable over the sample period according to the cusum and cusum-square tests, and test results are presented in figures 1 and 2, respectively. the short-run elasticities are computed as the estimated coefficients of the first differenced variables. the short-run results are reported in table 7. carbon dioxide exerts negative impact on energy consumption marginally. in short-run, energy consumption will decline by 1.4% due to a 1% increase in carbon dioxide emission. the effect of trade openness on energy consumption is negative and highly significant. this indicate that a 1% increase in trade openness leads a decrease of 0.39% to the energy consumption in the short run. the economic activities in industrial sector are positively associated with energy consumption. it is found that 1% increase in industrial value added will cause 0.46% energy consumption rise. findings also revealed that population rise is positively affects energy consumption as 1% increase in population leads an increase of 47% to the energy consumption in the short run. the impact of economic growth on energy consumption is positive and highly significant. a 1% rise in economic growth will increase energy consumption by 1.04%. the significance of error correction term implies that change in the response variable is a function of disequilibrium in the cointegrating relationship and the changes in other explanatory variables. the coefficient of ectt-1 shows speed of adjustment from short-run to long-run and it is statistically significant with negative sign. (banerjee et al., 1998b) noted that significant lagged error term with negative sign is a way to prove that the established long-run relationship is stable. the deviation of energy consumption from short-run to the long-run is corrected by 12.65% each year. table 6: long run results and diagnostics variables coefficient c 51.3108 (3.3227)** lnco2 ‒5.2763 (‒1.9771)* lnto ‒0.1054 (‒1.2831) lnind 1.3428 (2.2224)* lnpop 2.0407 (‒2.7432)** lngdppc ‒0.3539 (‒0.6727) reset test 0.6933 (0.5105) serial correlation 2.6739 (0.1478) heteroskedasticity 20.6589 (0.6927) normality 0.7342 (0.6927) ***, **,* indicate significance levels at 1%, 5%, and 10%. the t-statistics are reported in (..), p-values are in [..] table 7: short run ecm results variables coefficient δinect-1 −0.69332 (−7.8215) *** δinco2 −1.429 (−8.8308) *** δinco2t-1 1.2672 (−8.8308) *** δinto −0.3945 (−9.6429) *** δintot-1 −0.2419 (−5.8585) *** δinind 0.4623 (9.3141) *** δinpop 47.8542 (6.9768) *** δinpopt-1 −106.015 (−8.4944) *** δinpopt-2 29.5116 (7.3079) *** δingdppc 1.0412 (−6.9478) *** δingdppct-1 1.0603 (7.8346) *** δingdppct-2 0.6323 (6.5418) *** ectt-1 −0.6583 (−12.6511) *** ***, **,* indicate significance levels at 1%, 5%, and 10%. the t-statistics are reported in (..), p values are in [..] figure 1: assessing parameter stability using cusum test figure 2: assessing parameter stability using cusum square test warsame, et al.: the causal relation between energy consumption, carbon dioxide emissions, and macroeconomic variables in somalia international journal of energy economics and policy | vol 13 • issue 3 • 2023 107 4.5. granger causality test in order to determine the direction of causality between variables, we conducted the granger causality test shown in table 8. from co2 to energy consumption, trade openness to co2, population to co2, gdppc to industrialization, and gdppc to population we observed unidirectional causation. there are bidirectional causal relationships between population and energy consumption, industrialization and co2, industrialization and trade openness, population and trade openness, gdppc and trade openness, and population and industrialization. 4.6. variance decomposition this section estimates the response of variables to random innovation affecting the variables in the var using the cholesky’s method of variance decomposition. evidence from table 9 a shows that 13.13% of future fluctuations in lnec are due to shocks in lnco2, 11.43% of future fluctuations in lnec are due to shocks in lnto, 5.46% of future fluctuations in lnec are due to shocks in lnpop, 3.92% of future fluctuations in lnec are due to shocks in lnind, and 0.99% of future fluctuations in lnec are due to shocks lngdppc. as a policy implication for somalia, carbon dioxide emissions affect energy consumption in the future more than trade openness population, industrialization, and gdp per capita. evidence from table 9 b shows that almost 33.63% of future fluctuations in lnco2 are due to shocks in lnec, 18.73% of future fluctuations in lnco2 are due to shocks in lnto, 16.3% of future fluctuations in lnco2 are due to shocks in lnpop, 3.36% table 8: pairwise granger causality null hypothesis obs f-statistic prob. inco2 does not granger cause inec 28 3.69957 0.0405 inec does not granger cause inco2 28 1.22018 0.3136 into does not granger cause inec 28 2.04205 0.1526 inec does not granger cause into 28 1.17761 0.3259 inind does not granger cause inec 28 1.0382 0.3701 inec does not granger cause inind 28 2.03355 0.1537 inpop does not granger cause inec 28 2.56318 0.0989 inec does not granger cause inpop 28 8.37181 0.0019 ingdppc does not granger cause inec 28 0.0409 0.9600 inec does not granger cause ingdppc 28 2.40318 0.1128 into does not granger cause inco2 28 5.47321 0.0114 inco2 does not granger cause into 28 2.13027 0.1417 inind does not granger cause inco2 28 5.33058 0.0125 inco2 does not granger cause inind 28 3.47038 0.0482 inpop does not granger cause inco2 28 11.7016 0.0003 inco2 does not granger cause inpop 28 1.1926 0.3215 ingdppc does not granger cause inco2 28 1.90639 0.1714 inco2 does not granger cause ingdppc 28 0.25898 0.7741 inind does not granger cause into 28 2.98343 0.0705 into does not granger cause inind 28 4.64893 0.0202 inpop does not granger cause into 28 3.75578 0.0388 into does not granger cause inpop 28 3.04342 0.0672 ingdppc does not granger cause into 28 6.79864 0.0048 into does not granger cause lngdppc 28 3.48718 0.0476 inpop does not granger cause inind 28 15.0648 0.0000 inind does not granger cause inpop 28 11.6456 0.0003 ingdppc does not granger cause inind 28 11.7177 0.0003 inind does not granger cause ingdppc 28 0.40083 0.6744 ingdppc does not granger cause inpop 28 19.0959 0.0000 inpop does not granger cause ingdppc 28 0.44707 0.6449 table 9: variance decomposition a) variance decomposition of lnec period s.e. inec inco2 into inind inpop ingdppc 1 0.037776 100 0 0 0 0 0 2 0.047324 81.74989 7.120279 5.224611 0.222687 5.273605 0.408927 3 0.0576 73.40587 13.42851 6.978587 1.376377 4.473519 0.337144 4 0.061162 71.62573 12.35961 9.294517 2.411826 3.967663 0.340651 5 0.06209 69.58832 12.11219 11.04883 2.903981 4.01573 0.330948 6 0.062742 68.16538 12.45138 10.86428 3.179632 4.819499 0.519825 7 0.063678 66.25832 13.11106 11.0774 3.383104 5.332493 0.83762 8 0.064282 65.38054 13.30776 11.45954 3.603291 5.278576 0.970297 9 0.064652 65.20435 13.20886 11.5053 3.827624 5.28394 0.969932 10 0.064878 65.07637 13.12598 11.42653 3.922963 5.459732 0.988424 b) variance decomposition of lnco2 period s.e. lnec lnco2 lnto lnind lnpop lngdppc 1 0.018160 18.98679 81.01321 0.000000 0.000000 0.000000 0.000000 2 0.020924 14.54022 61.0513 0.217973 0.549562 22.00749 1.633451 3 0.028213 32.85115 42.86229 3.161401 0.315152 19.37486 1.435139 4 0.035320 39.48501 32.50462 7.579748 0.598448 17.79076 2.041415 5 0.039651 36.96935 29.0155 15.33211 0.614804 15.64264 2.425601 6 0.041208 35.52213 27.68793 19.21259 0.737222 14.48418 2.355943 7 0.041704 35.06113 27.03512 19.77435 0.837832 14.93328 2.358295 8 0.042176 34.5351 26.63378 19.3365 1.069199 15.7669 2.658517 9 0.042800 34.04188 26.10001 18.98674 1.554874 16.23534 3.081156 10 0.043420 33.62897 25.68895 18.72736 2.298263 16.29576 3.360701 c) variance decomposition of lnto period s.e. lnec lnco2 lnto lnind lnpop lngdppc 1 0.060317 0.097471 14.91304 84.98949 0.000000 0.000000 0.000000 2 0.085146 0.368801 9.412168 66.19750 13.24972 5.954974 4.816833 3 0.115074 7.745887 9.552816 38.76711 22.19934 13.21844 8.516404 (contd...) warsame, et al.: the causal relation between energy consumption, carbon dioxide emissions, and macroeconomic variables in somalia international journal of energy economics and policy | vol 13 • issue 3 • 2023108 of future fluctuations in lnco2 are due to shocks in lngdppc, and 2.3% of future fluctuations in lnco2 are due to shocks in lnind. as a policy implication for somalia, energy consumption affects carbon dioxide emissions in the future more than trade openness, gdp per capita, industrialization, and population. moreover, evidence from table 9 c shows that, almost 32.88% of future fluctuations in lnto are due to shocks in lnind, 23.33% of future fluctuations in lnto are due to shocks in lnco2, 15.14% of future fluctuations in lnto are due to shocks in lnec, 8.8% of future fluctuations in lnto are due to shocks in lnpop, and 7.02% of future fluctuations in lnto are due to shocks in lngdppc. as a policy implication for somalia, industrialization affects trade openness in the future more than carbon dioxide emission, energy consumption, population, and gdp per capita. evidence from table 9 d shows that almost 40.63% of future fluctuations in lnind are due to shocks in lnec, 25.21% of future fluctuations in lnind are due to shocks in lnto, 7.74% of future fluctuations in lnind are due to shocks in lnco2, 6.97% of future fluctuations in lnind are due to shocks in lnpop, and 0.92% of future fluctuations in lnind are due to shocks lngdppc. as a policy implication for somalia, energy consumption affects industrial value added in the future more than trade openness, carbon dioxide emissions, population and gdp per capita. in addition, evidence from table 9 e shows that almost 41.23% of future fluctuations in lnpop are due to shocks in lnec, 28.24% of future fluctuations in lnpop are due to shocks in lnto, 4.84% of future fluctuations in lnpop are due to shocks in lnind, 4.69% of future fluctuations in lnpop are due to shocks in lnco2, and 2.03% of future fluctuations in lnpop are due to shocks in lngdppc. as a policy implication for somalia, energy consumption table 9: (continued) c) variance decomposition of lnto period s.e. lnec lnco2 lnto lnind lnpop lngdppc 4 0.144888 10.07868 13.33237 25.56425 28.80558 12.84684 9.372283 5 0.173012 12.94577 14.73421 18.10619 33.18196 11.59211 9.439766 6 0.199343 15.71125 16.61490 1,364,181 34.92462 10.33313 8.774288 7 0.217774 16.50086 19.00609 11.50073 35.44629 9.461863 8.084161 8 0.228622 16.27145 21.09667 10.77755 35.15938 9.075692 7.619251 9 0.234828 15.65524 22.70668 11.27476 34.13013 8.942591 7.290592 10 0.239247 15.13880 23.32543 12.83254 32.88161 8.797875 7.023740 d) variance decomposition of lnind period s.e. lnec lnco2 lnto lnind lnpop lngdppc 1 0.053802 51.95368 4.218534 11.05033 32.77745 0.000000 0.000000 2 0.060476 44.20283 12.19904 15.10017 26.56296 1.932907 0.002093 3 0.064266 39.18167 14.51023 14.33457 25.18027 5.842866 0.960392 4 0.070585 32.61441 16.41487 18.64761 20.87722 9.686311 1.759578 5 0.073798 29.86625 16.04012 23.38977 19.10734 9.757484 1.839036 6 0.076304 28.64037 15.04378 26.54260 18.29666 9.735596 1.740986 7 0.080212 29.57774 13.70947 27.97173 17.74547 9.406054 1.589534 8 0.087632 33.72539 11.63210 26.98443 17.65156 8.635057 1.371463 9 0.097614 38.05545 9.435389 25.74610 17.89929 7.743952 1.119817 10 0.107793 40.63962 7.738617 25.20531 18.52484 6.970276 0.921331 e) variance decomposition of lnpop period s.e. lnec lnco2 lnto lnind lnpop lngdppc 1 0.000978 29.95410 1.919819 0.520289 5.368368 62.23743 0.000000 2 0.002540 30.70284 2.044221 2.673434 4.960494 58.34512 1.253891 3 0.004913 30.93122 3.410568 10.14105 4.050014 48.75990 2.707250 4 0.007649 30.04796 4.415351 17.55936 3.410027 41.14973 3.417574 5 0.010448 30.31854 4.905000 22.67687 3.106397 35.39828 3.594918 6 0.013174 31.73386 5.126825 25.85679 3.013320 30.82603 3.443170 7 0.015830 33.94238 5.233862 27.49914 3.148990 27.06262 3.113004 8 0.018444 36.54531 5.213597 28.14391 3.512493 23.86276 2.721928 9 0.021002 39.06284 5.026007 28.29266 4.093843 21.17509 2.349561 10 0.023450 41.23321 4.689210 28.24065 4.843619 18.96360 2.029716 f) variance decomposition of lngdppc period s.e. lnec lnco2 lnto lnind lnpop lngdppc 1 0.028245 4.146526 1.049299 9.764113 0.530419 63.62860 20.88105 2 0.042112 4.609519 9.749053 36.46300 4.197690 32.40336 12.57737 3 0.043942 4.401092 11.99666 37.00492 4.043623 30.58769 11.96601 4 0.045385 6.503746 11.98368 37.32893 4.278083 28.67907 1122649 5 0.047393 9.273601 12.79228 36.77025 4.248973 26.59928 10.31562 6 0.050663 15.24251 12.42754 34.66226 5.191256 23.27877 9.197672 7 0.05405 19.39081 10.93782 33.07414 7.875717 20.45694 8.264568 8 0.056983 20.93201 10.10655 32.07623 10.71740 18.49593 7.671884 9 0.059722 21.76906 10.19500 30.18350 13.45841 17.06708 7.326937 10 0.062256 22.65140 10.90741 27.98759 15.46832 15.91398 7.071297 warsame, et al.: the causal relation between energy consumption, carbon dioxide emissions, and macroeconomic variables in somalia international journal of energy economics and policy | vol 13 • issue 3 • 2023 109 affects industrialization in the future more than trade openness, industrialization, carbon dioxide emissions, and gdp per capita. finally, evidence from table 9 f shows that almost 27.99% of future fluctuations in lngdppc are due to shocks in lnto, 22.65% of future fluctuations in lngdppc are due to shocks in lnec, 15.91% of future fluctuations in lngdppc are due to shocks in lnpop, 15.47% of future fluctuations in lngdppc are due to shocks in lnind, and 10.91% of future fluctuations in lngdppc are due to shocks in lnco2. as a policy implication for somalia, trade openness affects population in the future more than energy consumption, population, industrialization and carbon dioxide emissions. 5. conclusion and policy implications the study examined the causal relationship between energy consumption, carbon dioxide emissions, and macroeconomic variables in somalia with a data spanning from 1990 to 2019 using the ardl model. the summary of findings are as follows: the results show a negative long-run significant relationship between carbon dioxide emission and energy consumption in somalia. we can say that energy policies aimed at improving access to clean energy consumption in somalia will reduce the gradual rise of carbon dioxide emission in somalia. the impact of rising industrial value added also has significant positive impact on energy consumption. the rise in industrial activities requires more energy to contribute to the gross domestic product. a 1% rise in industrial value-added increases energy consumption by 1.34% in the long run. population is found to have a negative long-term relationship with energy consumption. in the long term, a 1% increase in population results in a 2.040% decrease in energy consumption. this contradictory finding may be attributable to the fact that a large proportion of the somali population resides in rural areas and is typically unable to obtain oil or fuel. further, the study found that variables of trade openness and gdppc are insignificant in the long run. carbon dioxide emission and trade openness are adversely affected to the energy consumption in the short run. contrary to this, industrialization, population and gddpc increase energy consumption in somalia. ecm’s significant error coefficient confirms the existence of a long-run relationship between the variables. with regards to granger-causality, there was evidence of a bidirectional causality between: population to energy consumption, industrialization to co2, industrialization to trade opennes, population to trade openess, gdppc to trade opennes, and population to industrialization. moreover, there was evidence of a unidirectional causality running from co2 to energy consumption, trade opennes to co2, population to co2, gdppc to industrialization, and gdppc to population. evidence from the cholesky’s method of variance decomposition shows that 13.13% of future fluctuations in energy consumption are due to shocks in carbon dioxide emissions, 33.63% of future fluctuations in carbon dioxide emissions are due to shocks in energy consumption, 32.88% of future fluctuations in trade openness are due to shocks in industrialization, 40.63% of future fluctuations in industrialization are due to shocks in energy consumption, 41.23% of future fluctuations in population are due to shocks in energy consumption, and 27.99% of future fluctuations in gdppc are due to shocks in trade openness. several policy implications can be drawn based on empirical findings concerning energy consumption in somalia. to begin with, diversification of somalia’s economic productivity through enhanced technological advancement; innovation; value added to raw materials, goods, and services will broaden the financial base leading to high levels of per capita gdp. furthermore, diversification of somalia’s energy sector throughout the incorporation of renewable energy technologies into the energy portfolio will reduce reliance on volatile energy sources (fuel, oil, and gas) and the likelihood of interruptions in energy supply due to commodity price volatility, thereby contributing to climate change mitigation efforts. references african development bank. (2015), somalia energy sector needs assessment and investment programme. abidjan: african development bank. available from: https://www.afdb.org asumadu-sarkodie, s., owusu, p.a. (2016a), the potential and economic viability of solar photovoltaic power in ghana. energy sources, part a: recovery, utilization, and environmental effects, 38(5), 709-716. asumadu-sarkodie, s., owusu, p.a. (2016b), energy use, carbon dioxide emissions, gdp, industrialization, financial development, and population, a causal nexus in sri lanka: with a subsequent prediction of energy use using neural network. energy sources. part b economics, planning and policy 11(9):889-899. asumadu-sarkodie, s., owusu, p.a. (2017), the causal nexus between energy use, carbon dioxide emissions, and macroeconomic variables in ghana. energy sources, part b: economics, planning and policy, 12(6), 533–546. banerjee, a., dolado, j.j., mestre, r. (1998a), error-correction mechanism tests for cointegration in a single-equation framework. journal of time series analysis, 19(3), 267-283. banerjee, a., dolado, j.j., mestre, r. (1998b), error-correction mechanism tests for cointegration in a single-equation framework. journal of time series analysis, 19(3), 267-283. boswijk, h.p. (1994), testing for an unstable root in conditional and structural error correction models. journal of econometrics, 63(1), 37-60. cerdeira bento, j.p., moutinho, v. (2016), co2 emissions, non-renewable and renewable electricity production, economic growth, and international trade in italy. renewable and sustainable energy reviews, 55, 142-155. chandia, k.e., gul, i., aziz, s., sarwar, b., zulfiqar, s. (2018), an analysis of the association among carbon dioxide emissions, energy consumption and economic performance: an econometric model. carbon management, 9(3), 227-241. chen, y., wang, z., zhong, z. (2019), co2 emissions, economic growth, renewable and non-renewable energy production and foreign trade warsame, et al.: the causal relation between energy consumption, carbon dioxide emissions, and macroeconomic variables in somalia international journal of energy economics and policy | vol 13 • issue 3 • 2023110 in china. renewable energy, 131, 208-216. dong, k., hochman, g., zhang, y., sun, r., li, h., liao, h. (2018), co2 emissions, economic and population growth, and renewable energy: empirical evidence across regions. energy economics, 75, 180-192. edenhofer, o., madruga, r.p., sokona, y., seyboth, k., matschoss, p., kadner, s., zwickel, t., eickemeier, p., hansen, g., schlömer, s., von stechow, c. (2011), renewable energy sources and climate change mitigation: special report of the intergovernmental panel on climate change. in: renewable energy sources and climate change mitigation: special report of the intergovernmental panel on climate change. united kingdom: cambridge university press. p1-1075. kunvitaya, a., dhakal, s. (2017), household energy requirements in two medium-sized thai cities with different population densities. environment and urbanization, 29(1), 267-282. lin, b., omoju, o.e., okonkwo, j.u. (2015), impact of industrialisation on co2 emissions in nigeria. renewable and sustainable energy reviews, 52, 1228-1239. lipton, m., ravallion, m. (1993), poverty and policy. handbook of development economics, 3, 2551-2657. lovins, a.b. (1990), the effect of urbanization and industrialization on energy use in emerging economies: implications for sustainable development. population and development review, 16, 95. mohiuddin, o., asumadu-sarkodie, s., obaidullah, m. (2016), the relationship between carbon dioxide emissions, energy consumption, and gdp: a recent evidence from pakistan. cogenteng engineering, 3, 1. ohlan, r. (2015), the impact of population density, energy consumption, economic growth and trade openness on co2 emissions in india. natural hazards, 79(2), 1409-1428. otsuka, a. (2018), population agglomeration and residential energy consumption: evidence from japan. sustainability, 10(2), 469. rafindadi, a.a., ozturk, i. (2015), natural gas consumption and economic growth nexus: is the 10th malaysian plan attainable within the limits of its resource? renewable and sustainable energy reviews, 49, 1221-1232. salahuddin, m., gow, j., ozturk, i. (2015), is the long-run relationship between economic growth, electricity consumption, carbon dioxide emissions and financial development in gulf cooperation council countries robust? renewable and sustainable energy reviews, 51, 317-326. sarkodie, s.a., adams, s. (2018), renewable energy, nuclear energy, and environmental pollution: accounting for political institutional quality in south africa. science of the total environment, 643, 1590-1601. shahbaz, m., khraief, n., jemaa, m.m.b. (2015), on the causal nexus of road transport co2 emissions and macroeconomic variables in tunisia: evidence from combined cointegration tests. renewable and sustainable energy reviews, 51, 89-100. shahbaz, m., lean, h.h. (2011), does financial development increase energy consumption? the role of industrialization and urbanization in tunisia. energy policy, 40, 473-479. shpak, n., ohinok, s., kulyniak, i., sroka, w., fedun, y., ginevičius, r., cygler, j. (2022), co2 emissions and macroeconomic indicators: analysis of the most polluted regions in the world. energies, 15(8), 15082928. somalia energy statistics-worldometer. (n.d.), available from: https:// www.worldometers.info/energy/somalia-energy [last accessed on 2023 feb 15]. somalia power africa u.s. agency for international development. (n.d.), available from: https://www.usaid.gov/powerafrica/somalia [last accessed on 2023 feb 15]. warsame, a.a., sarkodie, s.a. (2021), asymmetric impact of energy utilization and economic development on environmental degradation in somalia. environmental science and pollution research,  29(16), 23361-23373. warsame, a.a., sheik-ali, i.a., mohamed, j., sarkodie, s.a. (2022), renewables and institutional quality mitigate environmental degradation in somalia. renewable energy, 194, 1184-1191. warsame, z.a. (2023), the significance of fdi inflow and renewable energy consumption in mitigating environmental degradation in somalia. international journal of energy economics and policy, 13(1), 443-453. world bank. (n.d.), co2 emissions (kt)-somalia data. available from: https://www.data.worldbank.org/indicator/en.atm.co2e. kt?locations=so [last accessed on 2023 mar 04]. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 3 • 2023 7 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(3), 7-14. contract structure of production sharing agreement by international oil company in exploration of petroleum resources in developing countries sha iqul hassan1, yusuff jelili amuda1, mohsin dhali1*, saghir munir mehar2 1prince sultan university, saudi arabia, 2mna management group, canada. *email: mdhali@psu.edu.sa received: 04 january 2023 accepted: 01 april 2023 doi: https://doi.org/10.32479/ijeep.14142 abstract presently, there is little focus on the contractual agreement, particularly on the production sharing agreement by the international oil companies in the exploration of petroleum resources of developing countries. the primary objective of this paper is to critically explore the contract structure of production sharing agreement by the international oil companies in the exploration and development of petroleum resources in developing countries. content analysis was used as the methodology of the study after examining several literatures. the findings indicate that the contract structure of the production sharing agreement (psa) between national oil companies (noc) and international oil companies (ioc) plays a significant role in the cost and risk of exploration and development of oil. in addition, it is noted that the joint committee of the noc and ioc plays a paramount role in monitoring the operations of psa between the noc and ioc. hence, from the gross oil production, the noc gets its share as profit while ioc gets its share income tax. as an instrument of contract structure in the oil and gas sector, psa needs further entrenchment between ioc and noc to avoid likely issues that can emanate between the two parties in the face of current developments. keywords: petroleum resources, contract structure, production sharing agreement, energy, oil jel classifications: k120, q40, q48. 1. introduction the exploration and development of petroleum resources present enormous opportunities for the economic growth of many developing countries. at the same time, it offers various risks, constraints, and technical challenges for these countries too (waterworth and bradshaw, 2018). typically, many developing countries suffer from the resource curse, among other related issues, when dealing with the production of petroleum resources, compared to countries less rich in oil (rosser, 2006) due to their over-dependence on oil as a form of national revenue (badeeb et al., 2017; ross, 2012). evidence of the poor economic performance of some oil-rich developing countries has given their huge return on oil profit (waterworth and bradshaw, 2018). a critical issue that continues to inhibit the economic development of these countries despite their resource wealth. for international oil companies, issues associated with risks that are non-technical and uncertain are of concern, serving as a barrier to investment (aven, 2016; waterworth and bradshaw, 2018), while for national oil companies in developing countries, it is the uncertainty in the future the demand for oil, and the projected availability of technological resources that is to mitigate climate change and facilitate the transition to renewable energy (solano-rodriguez et al., 2019). in addition, rentier states among developing countries that are fiscally reliant on petroleum resources revenue are known to experience severe institutional and political-economic shortfalls associated with the windfall nature of resource rent. they are also often susceptible to conflict this journal is licensed under a creative commons attribution 4.0 international license hassan, et al.: contract structure of production sharing agreement by international oil company in exploration of petroleum resources in developing countries international journal of energy economics and policy | vol 13 • issue 3 • 20238 over the resources revenue (barma, 2021). furthermore, neither these countries nor their private organizations are endowed with adequate experience and capital for the development of their petroleum resources. this lack of technical expertise and capital in the oil and gas sector among developing countries, as examined in the case of lebanon, results in brain drain, lack of a pool of scientists and researchers in specific units, inadequate institutional environment, inability to make public investments in relevant research and infrastructure (dirani and ponomarenko, 2021) in the face of the long-term, capital-intensive project which includes geological gap (da hora et al., 2019). for these reasons, developing countries liaise with international oil companies based on an agreed contract structure for the exploration and development of petroleum resources. meanwhile, the main issues for both parties in their contractual structure are the amount of risks to share and the distribution of revenue (hurst, 1989). contract structure is the framework that determines the contractual relationship between an international oil companies (ioc) and national oil companies (noc), otherwise known as a principalagent agreement for the purpose of exploring petroleum resources in the oil and gas sector of a host country with stipulated terms of the agreement, condition and regulation between the major partners. however, despite this structural arrangement, many developing countries endowed with petroleum and natural resources still experience some level of constraints in dealing with ioc for several reasons, which have been highlighted above. for the purpose of emphasis, developing countries are usually faced with the inability to independently exploit these resources as it requires a large amount of capital and technical expertise for the whole process. thereby issuing the right to perform such task to the ioc through the issuance of the license for the payment of tax under a number of terms of contracts such as production sharing agreement, concession, service agreement, and joint venture with bidding methods of negotiation and competitive bidding (bindemann, 1999). further, oil-rich developing countries with little capital and expertise and ioc are often faced with contractual challenges due to the dynamic nature of oil exploration and development either as a result of uncertainty in the quantity of reserves, the future price of oil, or geological constraints, among other issues. usually, in contract theory, the agreement between the “principalagent” is traditionally examined from the principal’s perspective, who needs to ensure that the agent acts appropriately in line with the contract terms. under this note, the study shall examine the production-sharing agreement as one primary form of contract structure between noc and ioc in developing countries. it also investigates the continuous interplay between the ioc and noc and deep further examines the investment pool in the industry in light of current development. several studies have provided an in-depth understanding of the economic analysis of production-sharing agreement (bindemann, 1999; dirani and ponomarenko, 2021; peters and kumer, 2011). other studies have also investigated the historical development, changes, and reformation of the psa, particularly in the case of indonesia (dirani and ponomarenko, 2021). while zebaria studied the production-sharing contract in the case of iraq (zebaria, n.d.). in addition, ngoasong also investigated the business practice of international companies in the oil and gas sector and their response to local content policies in developing countries (ngoasong, 2014). however, limited literature is available to explore production-sharing agreement as the instrument of the contract between international and national companies in light of current developments in the energy sector. this study attempts to fill this gap. 2. contract structure of production sharing agreements in the petroleum industry: a concise overview the need for a contract structure between ioc and noc would remain in academic discourse, specifically when dealing with the energy sector. both parties (noc-ioc) involved in the exploration and development of petroleum resources among developing countries understand the deeper meaning behind a contract structure, considering the risk and profit that may emanate from the investment and the synergy in their interest. in recent times, discourse about the structural sharing of production between international oil companies and national oil companies in the exploration and development of petroleum resources in developing countries has dominated the masterpiece. this is triggered by the fact that the sector is not only seen as a backbone for economic growth and development but also plays a significant contribution to job creation, poverty alleviation, enhancement of the gross domestic product (gdp), and improvement of all-round social well-being of the people in these developing countries. in some quarters, perhaps, it is believed that no extractive industry has been more volatile than oil, being the primary source of energy for modern industrialization. an initiative driven by endless cycles of spikes in demand precipitates an influx of actors, an oversupply of oil, and eventual price collapse. as the supply of oil grew in the pre-and post-world war ii eras, vast reserves were found in developing countries and former colonies, which gave rise to an essential dilemma over the ownership of the oil in the ground. a significant development in the oil and gas sector. one of the most exciting aspects of the petroleum industry is that it has several sectors or segments. the petroleum industry comprises three segments: (1) upstream sectors (exploration, development, and production of crude oil or natural gas); (2) midstream sectors; (3) downstream sectors (oil tankers, refiners, retailers, and consumers) (jafarinejad, 2022). based on the classification, there are also the following types of classification of morphological categories depending on the purpose and methods: (1) empirical; (2) morphological-semantic; (3) semantic-pragmatic. in addition, the oil industry was subdivided into four major companies. they include national oil companies (nocs), international oil companies (iocs), operator companies, and service companies. given this overview, the petroleum industry in developing countries seeks the exploitation of their petroleum resources with the demand for capital and technical expertise for the success of this project. hassan, et al.: contract structure of production sharing agreement by international oil company in exploration of petroleum resources in developing countries international journal of energy economics and policy | vol 13 • issue 3 • 2023 9 this brings the need for collaboration with an international oil company to provide these resources. in pursuance of this project, there is a need for both parties to reach an agreement structured in the interest of all actors. this agreement can be established in different forms of contract depending on developing countries’ national objectives and the interest of the ioc. notable among these contractual structures is the production-sharing agreement. 2.1. common features of production sharing agreements and petroleum fiscal system the production-sharing agreement remains the most dominant form of contract for the exploration and development of petroleum resources in developing countries (bindemann, 1999; olleik et al., 2021). in this form of contract, the state remains the principal owner of petroleum resources. still, it interacts with an ioc that provides her with both financial and technical expertise for the process of development and exploration. usually, the state is represented by either the government or one of its units, particularly the national oil company. on the other hand, the ioc is entitled to a certain percentage of the extracted oil as compensation for service rendered and risk taken in the production process. in addition, psa has four key features. first, the ioc is responsible for paying royalties to the government on total production. after which, the ioc is entitled to a predetermined amount to recover the cost. the quantity of production left (profit oil) is distributed between ioc and the government at a predetermined ratio. afterward, the ioc is obliged to pay tax on its income from oil profit (bindemann, 1999; daniel et al., 2010). the government, the principal owner of the resources, has the privilege to partake in several areas of the project. furthermore, psa provides an avenue for both parties to dialogue in the form of a joint committee with the responsibility to monitor and manage the process of operation. two unique features distinguish psa from other forms of contracts. first, the government is the sole owner of the equipment and its installations. second, the ioc is responsible for the entire risk of operations. in the case whereby no oil is discovered, the ioc bears all the risk as established in the contract structure. however, this agreement varies between the government and ioc, depending on how the contract is structured. for example, under the psa in indonesia, when it is discovered that the oil and gas field is sufficient for commercial purposes, the state is responsible for all costs of exploration and production. in the case of peru, the risk burden in the process of exploration and production is shouldered by the company with a considerable compensation of oil revenue compared to the terms of the contract in indonesia (dirani and ponomarenko, 2021). some of these companies are chevron pacific indonesia, pertamina ep, cnooc, exxonmobil cepu limited, and pertamina hulu mahakam. however, zebaria argued that in the case of iraq, it establishes a maximum level of oil production and recovery for international oil companies (zebaria, n.d.). making it an attractive contract structure for both parties. especially when noc uses local content legislation or policy to deal with the ioc. for example, in the case of nigeria, there is a nigeria content bill, while kazakhstan relies on kazakh content law (ngoasong, 2014). 2.2. developing countries adopting the use of production sharing agreement this flexible nature of the agreement and negotiation process also makes psa a unique contract structure. although the productionsharing agreement first began in indonesia in 1966 before being adopted by other oil-rich developing countries. around the world today, the production-sharing agreement is commonly applied in many developing countries such as china, peru, indonesia, qatar, egypt, syria, guatemala, malaysia, jordan, libya, bangladesh, angola, and jordan (babusiaux, 2004). solano-rodríguez et al. argued that the majority of the developing countries in the caribbean and latin america also fit into psa (solanorodriguez et al., 2019). it is also widely adopted in central asia and the caucasus region (radon, 2005). however, under psa, oil produced cannot be processed or sold by ioc; the noc processes and sells the share of the oil extracted (brunnschweiler and poelhekke, 2021). despite the differences among developing countries adopting psa, what remains predominant is that the state government is the rightful owner of the petroleum resources while also granting the right to control and manage the exploration and development process to ioc. yet, the interest of individual states differs and are influenced by certain conditions and circumstances (radon, 2005). notwithstanding, generally, the psa formula is often embedded in the contract structure and is usually present in the government’s policy and legislation. the prominent constructs for measurement are variable scales and fixed percentages which determine the sharing of oil profit between ioc and noc. variable scales: the rate of distribution differs depending on one or more variables such as prices, rate of return, “r” factor (income/ disbursements), and production, among others. fixed-rate: the share that resonates with the existing psa governments differs between 40% and 85%. table 1 below shows an example of sharing formula under psa. if daily average production as stipulated in the time period was 45,000 bbls per day government profit share = [(30%*25,000) + 35% (20,000)]/45,000 government profit share = 32.2% source: committee of experts on international cooperation in tax matters (2020). meanwhile, the ioc, on its share of profit oil, needs to pay income tax. at times, this share of profit allocated to the ioc is included table 1: percentage of government profit share based on daily production rate daily production rate (thousands bbls/day) government profit share (%) 0-25 30 >25-50 35 >50-75 40 >75-100 55 >100 60 hassan, et al.: contract structure of production sharing agreement by international oil company in exploration of petroleum resources in developing countries international journal of energy economics and policy | vol 13 • issue 3 • 202310 in the production sharing formula (through tax oil) and can be paid in kind. this is usually specified in the psa fiscal clauses. 2.3. developing countries adopting the use of production sharing agreement the histories of international oil companies (iocs) can be traced as far back as the late 19th century during the time of their establishment. in the beginning, they acted similarly to other corporations, with the exception that they were also engaged in the production of petroleum resources. for example, until 1911, in the united states, the majority of the iocs emerged from the dissolution of standard oil, which was, at this period, the leading oil corporation. as for the iocs, they are commonly regarded as supermajor. in fact, globally, the supermajors are the six biggest oil companies that are publicly traded. it is worth فخ mention that since the 1990s, these supermajor companies have undergone different forms of changes due to mergers and acquisitions, which are subject to forces in the market. globally, it is estimated that the supermajors companies are in charge of 6% of oil as compared to nocs, who are in charge of 88%, respectively. table 2 below: shows the six supermajors companies national oil companies (noc), on the other hand, are state-owned agencies or corporations that also deal in petroleum resources. alfalih asserts that (nocs) are oil firms owned by host countries having a more significant portion of shares in the oil sector and whose objective is to act in the interest of the country they represent (al-falih, 2011). colen et al. further corroborated that the common mandate of noc is usually to permit and provide assess foreign investors, as well as co-owners and service providers, to its petroleum resources (colen et al., 2016). looking at current development, in the majority of the countries with large oil deposits, nocs have commonly been utilized to organize and control its operation. according to al-fattah, presently, the majority of the developing countries which dominate the oil and gas sector, such as saudi aramco, kuwait oil company, and the iraqi national oil company, could all retrace their cradle back to partnerships established with international investors in the petroleum industry for the development of domestic resources right at the beginning of century (al-fattah et al., 2013). darko confirms that these international agreements for drilling oil and gas are becoming hypercompetitive, technology-driven, and exponentially highercost businesses (darko, 2014). in addition, it is evident that the producers in the petroleum sector show many stakes, and public expectations are disturbed by over-reliant on oil income which is volatile and uncertain, considering the increase in oil prices as these are crucial for creating an economy that is sustainable towards a long-term human development (dietsche et al., 2013). studies by yergin posited that during the 1990s, two primary forces were driving oil exploration and development in developing countries (yergin, 1992). the first factor was the interest of the (iocs) to control and incorporate upstream and downstream assets in order to avoid excess production to gain price stability. second, the powerful nations of this period were concerned with organizing a world order under their control and influence. therefore, as part of geopolitical concerns to counter the russian empire’s expansion and also to secure the energy supply of the royal navy, which incentivize great britain to embark on oil exploration in persia (yergin, 1992). during this period, ioc was privileged to sign a number of concession agreements with many governments, given its technological prowess and expertise for the exploration and development of oil. for a certain period of time, the ioc is responsible for upfront expenses in exchange for an agreed share of profit; at the same time, the government receives royalty from her. although this remains the contract structure for many years, both ioc and noc still have some gray areas influencing their relationship, which shall be further examined. 3. international oil company and national oil company: point of divergence several factors have been put forward to explain the rapport between ioc and noc. the critical point of divergence between international oil company and national oil company can be captured broadly in terms of access to capital, standard technology, breadth of capabilities as well as partnerships, and local engagement efficiency. 3.1. access to capital and finance the primary motivating element of the investment agreement between ioc and noc is access to capital and finance. given that capital and finance is the backbone of any investment. as such, its pool is tantamount to economic efficiencies, viability, and policy decision-making. based on this, the noc oil project depends on state-backed capital and having access to equity and debt in global capital markets. unlike the iocs that acquire their capital from publicly floated firms with access to liquid stock markets, banks, and bond buyers. 3.2. standard technology the technology standard is another noticeable divergence between the ioc and noc. standard technology in iocs is usually characterized by inclining towards minimal expenses in the areas of randd, which reduces costs under challenging environments targeted for development. comparatively, given the current state of table 2: the six supermajors’ companies name location (country) revenue (billions of dollars) reserve size in billions of barrels exxonmobil texas –united states 383 72 royal dutch shell the hague –netherlands 368 20 bp/amoco london –united kingdom 308 18 total sa paris –france 229 10.5 chevron california –united states 204 10.5 conocophillips texas –united states 198 8.3 source: unctad (2017) hassan, et al.: contract structure of production sharing agreement by international oil company in exploration of petroleum resources in developing countries international journal of energy economics and policy | vol 13 • issue 3 • 2023 11 standard technology in noc, there has been tremendous progress in randd innovation and technology. equally, this has, in recent times, culminated and paved the way for an increase in randd budgets in developing countries. this actually has its own effect in the sense that it encompasses the activities that these companies undertake in developing, designing, and enhancing their product or perhaps to innovate and introduce new products, goods, and services in the oil industry (al-fattah et al., 2013). 3.3. breadth of capabilities and partnerships another point of contrast between the ioc and noc is the concept of comprehensiveness of capabilities and partnerships. it is a common phenomenon to observe iocs having a long history of partnerships in multiple environments and governments of different countries, nocs, oilfield services companies (ofscs), and other iocs and similarly coming to terms with new partners. while in contrast, the noc principally focuses on domestic operations. gallagher and birch noted that in most cases, nocs establish alliances with iocs, independents and ofscs as required, thereby expanding businesses globally (gallagher and birch, 2009). pointing to this, for instance, was the agreement between chevron and aramco of saudi arabia for developing and exploring massive oil wells. similarly, both aramco of saudi arabia and total entered a joint venture deal to construct the al-jubail refinery to process large volumes of oil. in the artic, an agreement was also struck between exxonmobil and rosneft, among other colossal oil investment deals. 3.4. engagement efficiency as aforementioned, in general, the majority of the international oil companies have a deep-rooted societal engagement at multiple levels to make deals with developing countries with poor institutional infrastructure using psa as it appears convenient for them due to the risk exposure for the lack of transparency, legal uncertainty, and of political instability in the host country. al-fattah noted that, in essence, iocs develop models with local engagement by necessity (al-fattah, 2013; garcia et al., 2014). while on the other way round, noc mainly operates in their domestic market and has little need for local overseas engagement even though they have access to resources globally. essentially the fiscal policy demands that the nocs are responsible for the ownership and management of the supply chain of petroleum resources from upstream to downstream in the host country (ike and lee, 2014). 3.5. international oil company and national oil company: the meeting point the point of convergence between international oil companies and national oil companies is having increasingly equal unrestricted access to capital markets. meanwhile, among some developing countries, the increase in the issuance of external sovereign bond has also been reflected in the increase in debt sustainability with grave concern that could be worsened by external or domestic shocks, including slippages in the management of public funds. in advanced economies, the majority of companies have firmly embarked on using their financial window to finance share buy-backs, higher acquisitions, and dividends (mudford and stegemeier, 2003). most of the time, there is usually an overlap between ioc and noc in the area of shared operations because iocs often train local workers to help developing countries advance and improve their workforce, which is often inadequate (wef, 2019). this is considered a significant factor contributing to gdp growth but does not reflect the essential aspects of sustainability and well-being. it has also contributed to the improvement of nocs workers to become qualified domestic operators by utilizing iocs’ expertise with healthier agreements, acquiring and providing small-size companies the opportunities to have technical skills, as well as developing skilled workers and expertise via partnerships on a global scale. the point of convergence between international oil companies and national oil companies is also having in-house research and development capabilities. both ioc-noc interactions often result in the commencement of cross-national investments as well as building and establishing institutional knowledge and skills in major areas of technical expertise. this interaction between nocs and iocs is usually established in a unique and mutually productive avenue for the exchange of knowledge, technology, and skills. such education and training create a new experience for businesses and opportunities to operate at a level that contributes to national development, thereby increasing human capital, stimulating domestic firms, and helping these participants in the diversification of their economy. the noc-ioc corporations focus on developing and promoting the local economy by leveraging the upstream sector. for illustration, large oil importers have the opportunity to profit from the development of domestic renewable energy sources, which will, in turn, lead to developments in energy supply, security, and external balances. this reflects the urgent requirement why these countries are beginning to introduce environmental sustainability objectives into their strategies and policy for national development and to as well comprehend the resource consequences of achieving and reaching the sustainable development goals by 2030. the iocs also play an important role in national development objectives, often described as corporate social responsibility (csr). jaffe confirms the concept of csr strategies as requirements for operational activities that include the delivery of goods outside tax for the host country and the mitigation of risk (jaffe, 2020). this is also supported by al-fattah et al., 2013 who sees csr as a mutual objective between national and commercial development needs, organizing projects with the appropriate government stakeholders and other community participants (al-fattah et al., 2013). 4. current pool of investment and prospect in oil growth of developing countries despite the fall in oil prices between 2014 and 2016, investment in the petroleum industry continues to increase, picking from the drop experienced in the past years. a number of developing countries such as angola, timor-leste, libya, venezuela, qatar, iran, darussalam, united arab emirates, russia, nigeria, saudi arabia, azerbaijan, bahrain, gabon, kuwait, trinidad and tobago, hassan, et al.: contract structure of production sharing agreement by international oil company in exploration of petroleum resources in developing countries international journal of energy economics and policy | vol 13 • issue 3 • 202312 colombia, kazakhstan, brunei darussalam, algeria, and oman are seeking to exploit their new founded petroleum resources to drive revenue. the economic situation in some countries is reinforced by the increase in the production of oil as a result of these new oilfields contributing to stream coupled with more efficient extraction strategies and policies. in several developing countries, it is projected that mild economic expansion will likely occur because of the increase in oil production. for example, in libya, there is a record of stable growth due to the regain in the production of petroleum resources. similarly, in nigeria, as the production of oil increased with the improvement of the private sector, growth is estimated to have picked up to 2.1% in 2019. meanwhile, in 2018, growth in gdp remained at 1.6%, where it is projected to reach 2.7% in 2019 and 2.9% in 2020, respectively. in gabon, the economy is estimated to improve by 2.5% in 2019 and 2.8% in 2020, reflected by the increase in the production of oil. in addition, growth acceleration in chad is estimated to climb from 3.8% in 2019 to 5.5% in 2020. the export of oil and gas in other exporting countries declined due to the ongoing repair of oilfields in kazakhstan, while in azerbaijan, economic activities progressed due to the increase in the production of natural gas and the operationalization of the southern gas corridor. further, in turkmenistan in april 2019, the continuation of gas exportation to russia also contributed to the prospect of economic growth (filatova et al., 2021; wef, 2019). more than that, a sharp recovery from the breakdown of oil prices in 2014/15 still remains fragile due to instability and insecurity in these countries. apart from that, the factual prospect in assessing demands in the future, it is understood that there is an exposure to risk in decisions and policies linked with stranded losses and assets. furthermore, there is room for the increase and expansion of renewable energy. the international renewable energy agency (irena) projected that over the period between 2015 and 2050, global assets could possibly be stranded due to the transition into a new form of energy which will aggregately result in the use of trillion dollars, with a minimum of roughly $5 trillion buildings and equipment. in the upstream energy sector, there is an additional amount of $4 trillion, which is approximated to be about 45-85% of the total value of the present upstream oil producers. also included is an additional amount of $900 billion in assets that deal with the production of power and about $240 billion in industrial assets (irena, 2018). in addition, top energy analytical firms estimate that in the next 20 years, there will be a steady increase in the demand for hydrocarbon and a steady rise in the price of oil which is a short-term indicator of an accumulation of the investment for new projects (yakovlevicha et al., 2019). the following summarizes the prospect of oil growth among developing countries. 4.1. wealth fund management petroleum resource producers must carefully manage revenues from current oil sales to have a buffer against potential losses and invest in a diverse portfolio of long-term assets with the majority of long-term oil and gas produced. therefore, countries such as oman, united arab emirates, iran, bahrain, kazakhstan, qatar, angola, colombia, saudi arabia, libya, venezuela, russia, gabon azerbaijan, brunei darussalam, kuwait, nigeria, and timor-leste have commenced their establishment of sovereign wealth funds and programs to help in their process of transition. in march 2018, more than 78 commodity-based sovereign wealth funds were in existence, with more than $7.4 trillion in the global gross product in assets (wef, 2019). this would inevitably shape the continuous interaction between noc and ioc regarding their future contract structure. this is because noc is structuring its national interest and objective to sustainable development in the face of dire and current challenges in the oil and gas industry. 4.2. economic diversification in the words of al-fattah, key priorities that have strengthened economic resilience and have enhanced the prospect of long-term development between the iocs and nocs include investments in both education and infrastructure and providing the means to promote the importance of economic diversification (al-fattah et al., 2013). united nations further asserted that there had been economic diversification in the last decades via strategic investments in training and skill development, infrastructure, and technology (united nations department for economic and social affairs, 2020). this has helped to reduce the weight on external balances due to the decline in commodity-related profit, creating fresh employment opportunities and promoting an easy route to transit to a cleaner energy mix. 4.3. transparency in risk-sharing agreements notwithstanding, developing petroleum resources needs substantial physical and human capital investments. however, developing countries that are very much interested in considering future investment in the petroleum industries must adequately and openly establish that these risks are well defined in contractual agreements and transparently shared with the ioc. this, for the majority of developing countries, would serve as a significant issue, which predominantly relies on international investors and firms to embark on exploration projects that are expensive in order to commence with the fundamentals aspect of such sectors (united nations department for economic and social affairs, 2020). the consequences could be far greater than the cost to be shared if both parties assumed full responsibilities using the proper contract structure. 5. results and discussion the study’s main objective is to explore the contract structure of production sharing agreement between the ioc and noc in the exploration and development of petroleum resources in developing countries. we find that psa remains the most dominant contract structure between noc and ioc in developing countries. in addition, evidence suggests that both parties have a strong common interest in exploring and developing petroleum resources for profit maximization. this factor, among others, has continued to shape their interaction during negotiations before any agreement that further leads to renegotiation. furthermore, both noc and ioc have their unique contribution to the development of petroleum resources which can be described as symmetric cooperation for hassan, et al.: contract structure of production sharing agreement by international oil company in exploration of petroleum resources in developing countries international journal of energy economics and policy | vol 13 • issue 3 • 2023 13 the common interest. from a historical standpoint, the concession contract by happenstance remained the leading form of contract structure until psa overtook it as the host government began to realize the need to control and benefit more from their petroleum resources. although there are a number of gray areas which define their point of divergence and convergence in terms of capital, technical expertise, resource allocation, and distribution in their contract structure, the use of production-sharing agreements as a contractual mechanism has helped to facilitate ease this practice with many rooms for improvement considering the present and future challenges confronting the global production of oil due to its effect on the environment. despite this challenge, the study still anticipates that the exploration and development of petroleum resources among developing countries would remain in the future with the pool of investment in the industry despite the global movement to transit to clean energy. at this junction, it is critical to expand the scope and content of psa to accommodate this new development, as most developing countries have seen the need to adopt the production sharing agreement due to its flexibility and power vested in state ownership and control. even though most of these agreement might vary from country to country yet, it does not change the fundamental nature of the system and structure, as the ownership of resources and equipment usually belongs to the host government. given the benefit from oil revenue, most oil-producing developing countries have seen the need to be prepared with this revenue for future energy challenges through their sovereign wealth investment, while others are lacking behind. in addition, it is likely to see some oil-rich developing countries less dependent on foreign capital and expertise looking at this wealth growth and increase in expertise in the development of petroleum resources under the umbrella of the energy transition. the transition to a renewable energy source is considered one of the biggest challenges facing the petroleum industry. however, this study argues that such a challenge can be mitigated and controlled with an appropriate strategic approach and the commitment of noc and ioc to diversify their revenue and investment into renewable sources of energy to remain relevant and sustainable. history shows that although there has been a new form of energy since the 18th and 19th century with the transition to a new source of energy, the newly discovered alternative does not completely overwrite the old source from biofuel to fossil fuel and renewable in contemporary discourse. therefore, in the best interest of the noc and ioc, such an issue must be critically examined as the world is moving to net zero by 2050. for the time being, the contract structure using production sharing agreement between ioc and noc will steadily improve. it will develop further into a more sophisticated agreement in the lens of global environmental policy that will have a tremendous effect on the system of production of petroleum resources and the business model of leading companies in the oil and gas sector, as posited by this study. this challenge does not seem to be over in the near future, but it will instead transform into something bigger under a contractual structure in which psa would remain highly relevant. more importantly, host countries must clearly define their national interest in the energy sector to formulate policies appropriately. in the same vein, ioc must be ready to identify the national interest of the host countries towards their development to serve as a winwin package for all parties. 6. conclusion the issues and challenges associated with the exploration and development of petroleum resources in developing countries will remain long-term friction between ioc and noc, as identified by this study. although, over the years since 1966, there have been massive changes and adjustments in the contractual system between the two parties. production sharing agreement has been one of the most common systems of contract between ioc and noc in recent years due to its robust advantage for noc, although it differs among developing countries. several factors influence the exploration and production of petroleum resources in developing countries. states’ fiscal policy and regulation, reward and risk, control and monitoring, national interest, institutional shortfall, and lack of capital and technical expertise, among others are the common factors identified as influencing the exploration and development of petroleum resources in developing countries. in the nearest future, most of these factors are still likely to remain, although they may differ among countries. whether or not psa would remain the most dominant form of contract between ioc and noc, even though it will continue to experience a number of reforms considering the global push for renewable energy consumption. both noc and ioc have shared some common interests and diverged in others, yet, for the interest of all parties, it is imperative to reform their contract structure to accommodate the new development and challenges. notably issues dealing with climate change and environmental challenges due to global concern for the survival and protection of nature and humanity. 7. acknowledgement the authors would like to acknowledge the support of prince sultan university for paying the article processing charges (apc) of this publication. references al-falih, k. (2011), addressing the real sustainability challenge. i n t h e s e c o n d i n t e r n a t i o n a l e n e rg y f o r u m n o c i o c forum. available from: https://www.chrome-extension:// efaidnbmnnnibpcajpcglclefindmkaj/https://www.ief.org/_resources/ files/events/2nd-noc-ioc-forum/khalid-al-falih-keynote-speech.pdf al-fattah, s.m. (2013), the role of national and international oil companies in the petroleum industry. usaee working paper no. 13-137. al-fattah, s.m., aramco, s., abdullah, k. (2013), national oil companies: business models, challenges, and emerging trends. corporate ownership and control, 11(1), 727-736. aven, t. (2016), risk assessment and risk management: review of recent advances on their foundation. european journal of operational hassan, et al.: contract structure of production sharing agreement by international oil company in exploration of petroleum resources in developing countries international journal of energy economics and policy | vol 13 • issue 3 • 202314 research, 253(1), 1-13. babusiaux, d. (2004), oil and gas exploration and production: reserves, costs, contracts (technip). institut francas du petrole publication. available from: https://www.books.google.com.sa/books?id=xgl7 oxjakdcc&printsec=frontcover&hl=ar&source=gbs_ge_summary _r&cad=0#v=onepage&q&f=false badeeb, r.a., lean, h.h., clark, j. (2017), the evolution of the natural resource curse thesis: a critical literature survey. resources policy, 51, 123-134. barma, n.h. (2021), do petroleum rents fuel conflict in developing countries? a case study of political instability in timor-leste. energy research and social science, 75, 102018. bindemann, k. (1999), production-sharing agreements gran economic analysis. united kingdom: oxford institute for energy studies. brunnschweiler, c.n., poelhekke, s. (2021), pushing one’s luck: petroleum ownership and discoveries. journal of environmental economics and management, 109, 102506. colen, l., persyn, d., guariso, a. (2016), bilateral investment treaties and fdi: does the sector matter? world development, 83, 193-206. da hora, m.a.b.p., asrilhant, b., accioly, r.m.s., schaeffer, r., szklo, a., hawkes, a. (2019), decision making to book oil reserves for different brazilian fiscal agreements using dependence structure. energy strategy reviews, 26, 100377. daniel, p., keen, m., mcpherson, c. (2010), the taxation of petroleum and minerals: principles, problems and practice. 1st ed. london: routledge. darko, e. (2014), short guide summarising the oil and gas industry lifecycle for a non-technical audience. available from: https:// www.partnerplatform.org/eps-peaks dietsche, e., dodd, s., haglund, d., henstridge, m., jakobsen, m., sindou, e., slaven, c. (2013), extractive industries, development and the role of donors. available from: https://www.eldis.org/ document/a66736 dirani, f., & ponomarenko, t. (2021). contractual systems in the oil and gas sector: current status and development. energies, 14, issue 17, 14175497 filatova, i., nikolaichuk, l., zakaev, d., ilin, i. (2021), public-private partnership as a tool of sustainable development in the oil-refining sector: russian case. sustainability, 13(9), 5153. gallagher, k.p., birch, m.b.l. (2009), do investment agreements attract investment? evidence from latin america. in: the effect of treaties on foreign direct investment: bilateral investment treaties, double taxation treaties, and investment flows. united kingdom: oxford university press. garcia, r., lessard, d., singh, a. (2014), strategic partnering in oil and gas: a capabilities perspective. energy strategy reviews, 3(c), 21-29. hurst, c. (1989). transnational oil companies and natural gas in developing countries: the implications of the fiscal regime. energy policy, 17(5), 501-510. ike, c.b., lee, h. (2014), measurement of the efficiency and productivity of national oil companies and its determinants. geosystem engineering, 17(1), 1-10. irena. (2018), global energy transformation: a roadmap to 2050. available from: https://www.irena.org jafarinejad, s. (2022), control and treatment of sulfur compounds specially sulfur oxides (sox) emissions from the petroleum industry: a review. chemistry international, 2(4), 242-253. jaffe, a.m. (2020), stranded assets and sovereign states. national institute economic review, 251, r25-r36. mudford, b., stegemeier, d. (2003), analyzing the sensitivity of production sharing contract terms using simulation. in: paper presented at the spe hydrocarbon economics and evaluation symposium, dallas, texas. ngoasong, m.z. (2014), how international oil and gas companies respond to local content policies in petroleum-producing developing countries: a narrative enquiry. energy policy, 73, 471-479. olleik, m., auer, h., nasr, r. (2021), a petroleum upstream production sharing contract with investments in renewable energy: the case of lebanon. energy policy, 154, 112325. peters, m.s., kumer, a. (2011), an insight into production-sharing agreements: how they prevent states from achieving maximum control over their hydrocarbon resources. international research center for energy and economic development (iceed), 37(1/2), 285-295. radon, j. (2005), the abcs of petroleum contracts: license-concession agreements, joint ventures, and production-sharing agreements. in: a reporter’s guide to energy. available from: https://www. gmec-ee.com/wp-content/uploads/2013/08/the-abcs-of-petroleumcontractspdf ross, m.l. (2012), the oil curse. in: the oil curse. united states: princeton university press. rosser, a. (2006), the political economy of the resource curse: a literature survey. https://opendocs.ids.ac.uk/opendocs/ handle/20.500.12413/4061 solano-rodriguez, b., pye, s., li, p.h., ekins, p., manzano, o., vogt-schilb, a. (2019), implications of climate targets on oil production and fiscal revenues in latin america and the caribbean. energy and climate change, 2, 100037. https://doi.org/10.1016/j. egycc.2021.100037 united nations department for economic and social affairs. (2020), world economic situation and prospects 2020. united nations. united nations department for economic and social affairs. waterworth, a., bradshaw, m.j. (2018), unconventional trade-offs? national oil companies, foreign investment and oil and gas development in argentina and brazil. energy policy, 122, 7-16. wef. (2019), the speed of the energy transition gradual or rapid change? available from: https://www.weforum.org yakovlevicha, b., sergeevich, k.k., mikhailovichc, p.v. (2019), investment strategies of international oil and gas companies. international journal of innovation, creativity and change, 8(5), 63-69. yergin, d. (1992), the prize: the epic quest for oil, money and power. free press. available from: https://books.google.com. sa/books?hl=en&lr=&id=wiutwbtux2oc&oi=fnd&pg=pr3 &dq=the+prize:+the+quest+for+oil,+money,+and+power.+& ots=_4b_v2a_21&sig=y06objtvbnv2ne7r_i1ezelrkks&redir_ esc=y#v=onepage&q=the%20prize%3a%20the%20quest%20 for%20oil%2c%20money%2c%20and%20power.&f=false zebaria, d. (n.d.), oil production sharing contracts (pscs) with a focus on iraqi kurdistan region oil contracts. available from: https:// www.ijicc.net/images/vol_13/iss_4/13410_zebari_2020_e_r.pdf [last accessed on 2022 oct 12]. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2022, 12(4), 61-66. international journal of energy economics and policy | vol 12 • issue 4 • 2022 61 development and climate change in oic countries: examining causality between economic development, energy consumption, and emissions mohammad iqbal irfany1*, muhamad mulya tarmizi2, resfa fitri3, neneng hasanah4 1,3,4faculty of economics and management, ipb university, indonesia, 2faculty of islamic economics, institut ummul quro al-islami, indonesia. *email: iqbal.irfany@apps.ipb.ac.id received: 28 february 2022 accepted: 20 may 2022 doi: https://doi.org/10.32479/ijeep.13058 abstract oic countries experience a fast and stable socio-economic development over the last decades. however, in the same time environmental degradation have also escalated as a consequence of its development. a central question raises whether oic countries can push socio-economic growth without reducing environmental quality, or whether this region can implement emission reduction strategies without impeding their growth potentials. in this regards, this study examines the econometric relationships between emissions and socio-economic including output, population, emission intensity, investment, and urbanization. employing panel data from 49 oic countries from 1990 to 2019, the results show that gdp per capita, population, emission intensity, value-added industries, and proportions of urban communities significantly affect per capita co2 emissions. it is suggested that climate change mitigation in emissions by oic countries needs to be carried out both in the short and long term in reducing their dependence on fossil energy use both in production and consumption side, including the environmentally friendly technologies. keywords: oic countries, development, co2 emission jel classifications: q50, q54, q56, o11, o13 1. introduction oic countries experience a fast and stable socio-economic development over the last decades. however, in the same time environmental degradation have also escalated as a consequence of such development. even comparing with emerging economies, oic countries are considered among main contributors of world co2 emissions. unsustainable natural resource management, unstustainable industrial growth, unstustainable agricultural practices, and rising middle-income class consumption are attributed to this rising co2 emissions. the increasing trend of co2 emissions generates debatable issues in oic countries. a central question is whether oic countries can push socio-economic growth without reducing environmental quality, or whether this region can implement emission reduction strategies without impeding their growth potentials. in this regard, this study examines the econometric relationships between emissions and socio-economic figures including output, energy intensity, investment and urbanization. previous studies investigated the relationship green house gas emissions and socio-economic development. these studies, mainly co2 emissions, ranged from cross or panel studies (e.g. selden and song, 1994; coondoo and dinda, 2002; dinda and coondoo, 2006; baek et al., 2008; bernard et al., 2011; choi et al., 2010; martínez-zarzoso and maroutti, 2011) to more specific regional or national studies (e.g. akbostanci et al., 2009; zhang and cheng, 2009; zaman, 2010; tiwari, 2011; nasir and rehman, 2011). apart from computation of co2 emissions, previous studies also this journal is licensed under a creative commons attribution 4.0 international license irfany, et al.: development and climate change in oic countries: examining causality between economic development, energy consumption, and emissions international journal of energy economics and policy | vol 12 • issue 4 • 202262 investigated the determinants of environmental degradation, for instance shafik (1994), which differentiates them into structural and policy drivers, which are as follows: (1) endowment, e.g. location and climate; (2) income, which reflects the structure of production, private consumption, and urbanization; and (3) exogenous factors, particularly related to technology; and (4) respective policies, which reflects public decisions on the provisions of environmental public goods. specifically, the objectives of this study are as follows. first, we will do a descriptive and historical analysis of carbon dioxide gas emissions, economic growth and other control variables in oic countries. second, we will examine the existence and direction between socio-economic growth, energy consumption and co2 emissions by employing panel data analysis. we further ask whether income, population, emission intensity, urbanization, industrialization and other possible control variables matter. third, we will examine descriptive analysis and panel regression result to have a valid conclusions. 2. literature review the effect of economic growth on environmental degradation has been widely discussed in journals. arfanuzzaman (2016) mentions that there is a relationship between per capita income, the human development index and the environmental index in bangladesh. the results of this study indicate that economic growth will tend to reduce the quality of the environment which will eventually reduce the environmental performance index of bangladesh. in addition, research on economic growth and the use of renewable energy consumption on the level of co2 emissions was also conducted in china, dong et al, (2018). the estimation results in this study indicate that there is a positive relationship between economic growth and the level of carbon dioxide gas emissions, but the consumption of natural gas and renewable energy reduces the level of carbon dioxide gas emissions. this study recommends that china, which seeks to reduce co2 emissions, needs to substitute more environmentally friendly fuels for its production machines. environmental kuznets curve (ekc) hypothesis argues that severe environmental degradation is often found in developing countries, and the majority have low per capita income (see for instance lau 2014). the ekc hypothesis explains that in countries with low per capita income, that many of them are found in preindustrial or agrarian countries, will gradually adopt agricultural and other industrial mechanization so that resource use increases due to technology, so that pollution increases. in the long term, economic growth that results in environmental degradation also makes the country aware of expectations for life expectancy, cleaner water, improved air quality and cleaner habitats, so that environmental improvement is also a priority in economic development. figure 1 shows the transition from pre-industrial countries to industrial economies and post-industrial economies will form a relationship in a curve that forms an inverted u between a country‘s per capita income and environmental degradation (fodha and zaghdoud 2015). research on the impact of urban population growth and energy consumption was conducted by dash and behera (2017) in south asian and southeast asian countries using data from 17 countries. using a data period of 1980-2012 and dividing countries into three sub-groups including high, middle, and low income by panel data analysis, the results of this study indicate that in the long term, energy consumption, fdi, urban population levels, and levels of co2 emissions have a positive and significant long-term relationship across all groups of countries. 3. data and estimation strategies we use panel data of 49 oic countries from 1990 to 2019 of co2 emissions (in metric ton per capita), real per capita gdp (in constant 2000 usd), co2 intensity (in kg), urban population (in percentage to total population), fossil energy consumption (in percentage to total energy consumption), and industry value added (in percentage to total value added). all data are taken from world development indicators (wdi) and emission database for global atmospheric research (edgar). to analyze the causality between co2 emissions, energy consumption and economic development, we employ a number of estimation techniques. first, we estimate a log linear specification to measure long-run causality between emission, energy consumption and output, which can be expressed as follows: 0 1 2 3 4 5 6 2 2 _ _ _ α α α α α α α ε = + + + + + + + it it it it it it it it lnco cp lngdpcap lnpop lnco int p fossil p urban p industry where lnco2cpit lngdpcapit lnpopit lnco2intit refers to per capita co2 emissions, per capita output, population, and co2 intensity (all in natural logarithm), p_fossil, p_urban p_industry represent percentage of fossil energy consumption to total energy consumption, percentage of urban population to total population, and percentage of industry value added to total value added, respectively. finally, εt represents the error terms assumed to be i.i.d (0, σ2). figure 1: environmental kuznets curve source: fodha and zaghdoud (2015) irfany, et al.: development and climate change in oic countries: examining causality between economic development, energy consumption, and emissions international journal of energy economics and policy | vol 12 • issue 4 • 2022 63 3.1. development of fossil energy consumption and carbon dioxide emissions in oic countries oic countries are well-known as among the largest oil producers in the world. this has consequences for the consumption of fossil energy which is quite large even as the main energy source in economic activity. this is shown by a graph of the average percentage of fossil energy consumption to the total energy consumption of oic countries. figure 2 shows the trend that since 1990, the average proportion of fossil energy use to total energy consumption in oic countries tends to increase until 2019. the average proportion of fossil energy use is around 77–79% of total energy consumption in the country. from 1990 to 2019, it seems that the commitment of oic countries to use clean and environmentally friendly energy has not been seen. the proportion of the use of fossil energy as the main energy source for economic activities in oic countries will certainly have a direct impact on the accumulation of carbon dioxide gas emissions released into the air and have an impact on accelerating global warming. the use of fossil energy that tends to increase in the economic activities of oic countries can also be seen as a consequence of industrialization in this region. in general, the development of industrialization in oic countries, which is represented by the role of industry in the value added of oic countries, can be seen in figure 3. figure 3 shows that the role of industry in the economy of oic countries is quite large in compiling the added value/gdp of oic countries. the role of industry sector as an economic driver for oic countries, which accounts for around 30% of value added/gdp from 1990 to 2019, is a major economic buffer in the economic activities of oic countries. however, industrialization that occurs in oic countries is directly proportional to the increase in the proportion of fossil energy use to the total energy consumption of oic energy. this shows that the use of fossil energy is also used for industrial purposes in the production of goods/services. increasing industrial and community activities in oic countries that depend on the use of fossil energy, will have an impact on increasing co2 emissions. the development of fossil energy as the main energy source can be seen from the development of carbon per capita co2 of oic countries in the period 1990 to 2019 (figure 4). it can be seen that average of per capita co2 emission of oic countries tends to increase over time, as a consequence of increasing industrial and community activities as previously shown. indeed it is argued that the trend of increasing average per capita co2 emissions from 1990 to 2019 is an unavoidable consequence of oic countries due to their high dependence on fossil energy as the main energy source for all economic activities. oic countries which are dominated by developing countries will indeed worsen environmental quality degradation as a result of 73 74 75 76 77 78 79 80 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18 20 19 % o f t o t a l c o n s u m p t io n figure 2: average fossil energy consumption (percentage of total energy consumption) source: the world bank, world development indicators (2019) 0 5 10 15 20 25 30 35 40 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18 20 19 pe rc en ta ge to to ta l v al ue a dd ed figure 3: average of industry (including construction) value added to total value added source: the world bank, world development indicators (2019) irfany, et al.: development and climate change in oic countries: examining causality between economic development, energy consumption, and emissions international journal of energy economics and policy | vol 12 • issue 4 • 202264 economic activity, although it will greatly depend on geographical factors of an oic country which is high in natural resources that are sensitive to climate and low adaptive capacity to the environment. investigating oic countries, existing climate models predict worsening of environmental and climatic conditions in this region which poses serious socio-economic consequences especially for the disadvantaged and poor populations (sesric, 2019). it is also reported that the majority of oic member countries are characterised by poor environmental performance and a high level of vulnerability to temperature change (sesric 2019), as shown ini figure 5. qatar is that the best playing and most environmentally property country, followed by turkmenistan, balkan nations and brunei darussalam. on the other hand, twenty four oic member countries are hierarchal among the formeost vulnerable and lowest performing countries within the world. 4. estimation results the relationship between the use of fossil energy and other socio-economic variables on the level of carbon dioxide gas emissions is estimated by panel data regression analysis. to see the robustness of extimation techniques, we employ several panel data models including the fixed effect model, random effect model, autoregressive fixed effect model, and autoregressive random effect model to estimate the coefficient of the effect of fossil energy variables and other variables on carbon dioxide gas emissions per capita of oic countries. the estimation results can be seen in table 1. estimation results show that per capita gdp (lngdpcap) significantly and positively affects per capita co2 emissions in all models. the increase in the income of the people of oic countries directly increases per capita co2 emissions. per capita gdp with a positive sign indicates that economic activities that increase gdp per capita have a negative impact on the environment, i.e. the increase in per capita co2 emissions. in this regards, as a major oil-producing country, in order to drive industrial machines as the economic driving force, oic countries need to pay attention to environmental impacts in line with the expansion of economic activity. this finding confirmed the environmental kuznet curve hypothesis that suggests that increasing income (affluence) of lowand middleincome countries will respond positively to increased environmental degradation, whereas high-income countries will respond negatively to environmental degradation. oic countries that are generally middle-income through this model are proven to support the environmental kuznet curve hypothesis when an increase in gdp per capita will also increase environmental degradation. population (lnpop) has a positive and significant impact on per capita co2 emissions, i.e. the increase in the population tends table 1: estimation results dependent variable: lnco2cpit variables fixed effect model random effect model autoregressive fixed effect model autoregressive random effect model lngdpcapit 0.488048*** 0.2898457*** 0.2233272*** 0.14376658** (0.000) (0.000) (0.000) (0.000) lnpopit 0.099137*** 0.0335425 0.1887202*** 0.1649583*** (0.002) (0.269) (0.004) (0.000) lnco2intit 0.116925*** 0.1603105*** 0.0750658*** 0.0952762*** (0.000) (0.000) (0.000) (0.000) p_fossil 0.001908* 0.0030019** 0.0026004*** 0.0031423*** 0.096 (0.011) (0.001) (0.000) p_urban 0.010114*** 0.0203993*** 0.0063447** 0.01184*** (0.000) (0.000) (0.011) (0.000) p_industry 0.004430*** 0.0074805*** 0.0010521 0.0031832*** (0.001) (0.000) (0.236) (0.001) hausmann test 250.16 prob : 0.000 n 1519 1519 1519 1519 adjusted r-sq 0.3208 0.2917 0.0622 0.2725 *significant at 10%, **significant at 5%, ***significant at 1%, p value source: edgar (2019) 0 1 2 3 4 5 6 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18 20 19 t on c o 2 figure 4: average of co2 emission per capita of oic countries irfany, et al.: development and climate change in oic countries: examining causality between economic development, energy consumption, and emissions international journal of energy economics and policy | vol 12 • issue 4 • 2022 65 increase per capita co2 emissions. this indicates that the increase in public consumption, especially in fossil energy, will increase carbon dioxide gas emissions. this is in line with the co2 intensity variable which also has a positive and significant effect on the level of carbon dioxide gas emissions. co2 intensity, represented by lnco2int, has a positive impact on per capita co2 emissions. this means that the higher emission intensity contributes to pollution. in oic countries, the intensity of co2 emissions from the use (production) of energy tend to increase the level of co2 emissions. this finding suggest that oic countries still have structural challenges to decrease co2 intensities overtime in order to decrease the level of emissions. the oic member countries need to implement a more carbon-efficient energy mix of their energy system. fossil fuels as the main energy source will increase per capita co2 emissions, as suggested by positive estimation of p_fossil coefficient. as it was previously known that the average proportion of fossil energy use to total energy consumption is around 70%, this shows that oic is very dependent on fossil energy to meet its main energy needs, but on the other hand it has an impact on increasing per capita co2 emissions and global warming. the rate of urbanization, represented by p_urban, has a positive and significant impact on per capita co2 emissions in oic countries. in addition to the problem of dependence on heavydependence on fossil energy which can increase carbon dioxide gas emissions, the rate of urbanization is also another factor that increases per capita co2 emissions of oic countries. a possible explanation is that regional (rural-urban) inequality and the need for employment has led to a high rate of urbanization, resulting in a high level of economic activity in the city, especially production machines which have side effects on per capita co2 emissions in oic regions. industrial activity, represented by the p_industry, has a positive and significant impact on the level of carbon dioxide gas emissions in oic countries. this shows that industrial activities in oic countries, representing the production activities, are still very dependent on the use of energy that emits co2 emission. the oic countries, which many of them are oil-producing countries, of course also directly use oil as fuel for production activities. this also means that oic countries still have several challenges towards a more sustainable production activities. 5. conclusion and recommendations to date, energy sources of oic countries are heavily dependent on fossil energy as the main energy source in driving economic activity. industrial and community activities that depend on the use of fossil energy directly will increase the accumulation of co2 emissions. the increase in industrial activity that drives the economic growth of oic countries has an impact on environmental degradation. co2 missions that accumulate in the air will certainly have an impact on global warming so that in the long term it will cause serious damage to the lives of living things and economic resources. in addition to the economic aspect, another control variable that also affects carbon dioxide gas emissions is the increasing number of urban population due to urbanization. climate change mitigation, particularly related to reducing co2 missions by oic countries, needs to be carried out both in the short and long term. in this regards, oic countries need to reduce their dependence on fossil energy as the main energy source in socio-economic activity. the use of environmentally friendly energy and products is more than an option that needs to be done in climate change mitigation. in production or industrial activity, the production technology needs to be more environmentally efficient. apart from the use of renewable energy in production process, green technology adoption from developed countries to oic countries, needs to be done to gradually replace “dirty” production process. more over, the imposition of a carbon tax (apart from gradual reduce in fossil fuel subsidy) can be another important ways to be realized as compensation for environmental degradation that occurs due to increased co2 emissions. these actions need to be taken in an effort in climate change mitigations in the future. the continuous rate of ghg gases, mainly co2 emissions allowed by the oic countries will have a serious impact on the environment and will require greater costs to improve the environment. economic growth which is the goal of oic countries also needs to calculate the impact of environmental damage and calculate compensation costs for environmental improvements due to expansion of economic activity in order to promote a green growth strategy. finally, further researches on climate mitigation and adaptation for the case of oic countries need to be carried in order to promote a more sustainable growth in this region. references akbostanci, e., turut-asik, s., tunc, g.i. (2009), the relationship between income and environment in turkey: is there an environmental source: adapted from sesric (2019) figure 5: environmental performance and environmental vulnerability of oic, non-oic and developed countries irfany, et al.: development and climate change in oic countries: examining causality between economic development, energy consumption, and emissions international journal of energy economics and policy | vol 12 • issue 4 • 202266 kuznets curve? energy policy, 37(3), 861-867. arfanuzzaman, m. (2016), impact of co2 emission, per capita income, and hdi on environmental performance index: empirical evidence from bangladesh. journal of environment and pollution research, 4(2), 61-73. bernard, j.t., gavin, m., khalaf, l., voia, m. (2011), the environmental kuznets curve: tipping points, uncertainty and weak identification. create working paper. choi, e., heshmati, a., cho, y. (2010), an empirical study of the relationships between co2 emissions, economic growth and openness. iza discussion paper no. 5304. coondoo, d., dinda, s. (2002), causality between income and emission: a country group-specific econometric analysis. ecological economics, 40, 351-367. dash, d.p., behera, s.r. (2017), the effect of urbanization, energy consumption, and foreign direct investment on the carbon dioxide emission in the ssea (south and southeast asian) region. renewable and sustainable energy reviews, 70, 96-106. dinda, s., coondoo, d. (2006), income and emission: a panel data-based cointegration analysis. ecological economics, 57, 167-181. dong, k., sun, r., dong, x. (2018), co2 emissons, natural gas and renewables, economic growth: assessing the evidence from china. science of the total environment, 640, 293-302. fodha, m., zaghdoud, o. (2010), economic growth and pollutant emissions in tunisia: an empirical analysis of the environmental kuznets curve. energy policy, 38(2), 1150-2256. lau, l.s., choong. c.k., eng, y.k. (2014), investigation of the environmental kuznets curve for carbon emissions in malaysia: do foreign direct investment and trade matter? energy policy, 68, 490-497. martínez-zarzoso, i., maruotti, a. (2011), the impact of urbanization on co2 emissions: evidence from developing countries. ecological economics, 70(7), 1344-1353. nasir, m., rehman, f.u. (2011), environmental kuznets curve for carbon emissions in pakistan: an empirical investigation. energy policy, 39, 1857-1864. sesric. (2019), oic environment report 2019. retrieved from: https:// www.sesric.org/files/article/675.pdf [last accessed on 2020 jan 02]. shafik, n. (1994), economic development and environmental quality: an econometric analysis. oxford economic papers, new series, special issue on environmental economics, 46, 757-773. the world bank. (2019), world development indicators. fossil fuel energy consumption. retrieved from https://data.worldbank.org/ indicator/eg.use.comm.fo.zs tiwari, a.k. (2011), energy consumption, co2 emission, and economic growth: evidence from india. journal of international business and economy, 12(1), 85-122. zaman, k. (2010), trade liberalisation, financial development and economic growth: evidence from pakistan (1980-2009). journal of international academic research, 10(2), 2010. zhang, x.p., cheng, x.m. (2009), energy consumption, carbon emissions, and economic growth in china. ecological economics, 68, 2706-2712. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 3 • 2023408 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(3), 408-417. renewable energy communities in the energy transition context enzaemilia cavallaro*, maria rosaria sessa, ornella malandrino department of business sciences, management and innovation systems, via giovanni paolo ii, 132, fisciano (sa) 84084, italy. *email: enzaemilia.cavallaro@gmail.com received: 23 january 2023 accepted: 27 april 2023 doi: https://doi.org/10.32479/ijeep.14230 abstract economic, social, and environmental sustainability is becoming increasingly important in territorial development policies in europe and internationally. among the sustainable development goals, the theme of the energy transition is particularly important, which translates not only into a move away from energy from fossil fuels in favor of renewable ones but also into an improvement in energy efficiency linked to energy production and greater awareness of energy consumption by citizens. to achieve a paradigm of sustainable development, combating the problem of resource scarcity and biodiversity loss, as well as the unsustainability of today’s consumption and production systems, the renewable energy communities can be a suitable model to support urban space redevelopment projects. actions that aim to recover the pre-existing building heritage to give new life to abandoned areas are increasingly necessary for the protection of the environment. this encourages the propensity to act responsibly, promoting virtuous circles for the territories and communities of reference. this work aims to analyze and understand the actual development of the eco-friendly model of energy communities, understanding its real benefits. in particular, the case study of the energy community of east naples is reported which, through the involvement of citizens and businesses of the territory, can produce, consume and exchange energy with a view to self-consumption and collaboration. keywords: energy community, renewable energy, transition, urban areas, italy jel classifications: q2, q4, p28 1. introduction issues related to sustainability, already central to the political agenda of the european union, have acquired increasing importance within the priorities of the various actors in the economic sector, pushing them to redefine their objectives toward a direction of greater environmental sustainability. thanks to the growing awareness of the importance of environmental, social, and governance issues, one of the objectives set by almost all business organizations are to find stable solutions that allow them to improve their performance in these areas. it is necessary to overcome or integrate the conventional business model based on maximizing economic well-being, with objectives aimed at other issues such as environmental protection, enhancement of natural resources, equity, inclusion, solidarity, and social cohesion. the transformation of companies and organizations towards environmental, social, and governance (esg) criteria requires an evolution in the relationship with the resources necessary both for production and for the management of production processes or the provision of services, for example, saving in the use of fossil fuels through efficiency by companies (elliott et al., 2006) is one of the ways to integrate esg into business logic. in an energy market full of variables and pitfalls, the pressure of the energy crisis has accelerated the ecological transition, given the sense of urgency that pushes to increase the use of renewables and reduce consumption. in today’s economic and environmental scenario, energy efficiency is an absolute priority, and the elimination of any waste assumes a “double value”, economic and environmental. this twofold interpretation of this journal is licensed under a creative commons attribution 4.0 international license cavallaro, et al.: renewable energy communities in the energy transition context international journal of energy economics and policy | vol 13 • issue 3 • 2023 409 economic activities, which is necessarily considered, finds full coexistence in the phenomenon known as the energy community. their creation is an opportunity to experiment with a model of energy capitalization of the territory (magnaghi, 2013). the territory energy is an integrated model in which the entire territory is involved producing local energy, through interventions calibrated on the local availability of resources and respectful of the patrimonial values of the territory, overcoming upstream the environmental criticalities that arise from an approach oriented to the intensive exploitation of resources. the characteristics of energy communities, the involvement of inhabitants/producers in the identification and appropriate use of energy resources with participatory techniques aimed at promoting the growth of awareness of place (magnaghi, 2013), reinforce the concept that “there is no green economy without green society” (bonomi, 2020). in this interpretation, the construction of the energy community, as a community of inhabitants in which citizens are not simply “users” who derive economic benefits from joining the community but take an active role as protagonists in the definition and management of the transition process of their territory towards a horizon of self-sustainability, turns out to be a possible solution to the current economic and environmental instability. to face the evolution that is expected for energy communities, towards active components of innovative forms of local development, it is necessary to support a precise regulatory framework. the energy transition process requires, to be carried out, actions that combine an increase in energy production from renewable sources, a reduction in greenhouse gas emissions, and a reduction in energy demand. to give substance to the paris agreement1, the transition to renewable sources must, first of all, take shape in the local dimension, acting on territorial contexts with appropriate and locally defined solutions based on the specificities of the places. therefore, the objectives of this research are (1) to analyze the state of the art of the energy community in italy, understanding its real benefits in terms of eco-efficiency; (2) present savings, in terms of consumption, through the adoption of this model, which translates into economic, environmental and social benefits, paying particular attention to the virtuous case of the renewable energy communities (cer) of east naples, promoter in its context of the ecological transition process and the enhancement of the territorial area of reference. 2. materials and methods 2.1. rec: an overview of the literature the change in today’s production and consumption systems towards more sustainable and eco-efficient forms is now more stringent than ever. environmental issues pose not only economic actors but society, facing the challenge of contemporaneity: rethinking their way of acting with a view to sustainability, for the benefit of the ecosystem. the energy transition towards more suitable forms that allow a reduction in consumption and a lower impact on the 1 the document produced by cop 21 in 2015, the paris agreement, identifies a limit to be imposed on global warming to avoid its most serious consequences, i.e. to limit the temperature increase within 2°c compared to the pre-industrial period. environment, is one of the processes implemented by today’s society in response to the environmental crisis. in the literature there is growing attention to community energy, considering that, both in the academic and policy fields, the preventive interest of society towards new forms of energy sharing, to the transition towards sustainable use of the same, is considered propaedeutic. being a concept of recent development, it emerges from the literature that the notion of community energy (similarly energy community), is not established in detail, so the concept cannot be identified as unitary, being accessible to multiple interpretations, connoting it with a widely acceptable flexible meaning. this would facilitate the spread of the concept of an energy community, functioning as a bridge concept that facilitates the treatment and dialogue concerning the theme between subjects and their different interests (star and griesemer, 1989). at the beginning of 2000, following some studies by english-speaking authors, the notion of community energy refers to a site of energy sharing by components to address issues related to climate change, the use of renewable resources, and sustainability (pellizzoni, 2018). centralized energy installations thus give way to a new way of consuming energy, using the opportunity to hold individual citizens and business forces accountable, directing them towards collaborative forms to bypass the political conflict over energy issues and rebuild the social and natural foundations that capitalism and the market need but are unable to reproduce (dardot and laval, 2014). over the years, the field of investigation of energy communities changes considerably and brings with it the succession of different terminologies adopted to identify the phenomenon. alongside community energy, expressions such as rec (walker and devine-wright, 2008) collective and politically motivated renewable energy projects (becker and kunze, 2014), energy democracy (szulecki, 2018), sustainable energy communities (romero-rubio and de andrés díaz, 2015). despite the different terminology used, the intrinsic meaning is shared community energy identifies initiatives in which the community itself benefits from the collaboration that is established between the participants in terms of energy, obtaining advantages regarding the generation, management, acquisition, and consumption of the same. these initiatives have a positive impact on the community through the development of renewables promoted and the significant reduction of energy consumption, in a context of social cohesion and innovation. according to burchell et al. (2014), six distinct but interrelated meanings of the activity carried out by energy communities can be identified: a local or location-related activity; an interest-based activity; a collaborative, community-managed process with locally distributed benefits in an equitable manner; an activity at the intermediate level between the individual and that of large organizations or the state; an agency actor; an experimental niche (pellizzoni, 2018). whatever definition is given to the notion of community energy, there is no doubt that the benefits of this new model of energy sharing are multiple and disparate. they can be deduced both from the texts of the articles and from the policy documents, which illustrate a broader vision of the community, as a social form capable of responding simultaneously to the limits of the activities carried out at the macro level and to those of individual action on consumer decisions (pellizzoni, 2018). this means that the characteristics of the community such as the sense of identity, cavallaro, et al.: renewable energy communities in the energy transition context international journal of energy economics and policy | vol 13 • issue 3 • 2023410 the sharing of places, values, visions, and interests, solidarity, the ability to participate and mobilize collectively, and resilience, give it the appointment of an ideal site to explore alternative ways to the production, use, and sharing of energy, from a technological, organizational and economic point of view. energy communities represent a new model that promotes the link between energy choices and economic, environmental, and social perspectives (torabi moghadam et al., 2020). the community becomes a place where the willpower of all social actors, located in a specific area, to share the will to self-produce and self-consume energy from renewable energy sources is expressed. 2.2. the regulation of cers: regulatory aspects in europe and italy in recent decades, the european union has committed itself to fight climate change by adopting strategies aimed at achieving a 40% reduction in greenhouse gas emissions, to achieve climate neutrality in 2050, making the eu economy sustainable (barroco et al., 2020). the energy sector is the most responsible for greenhouse gas emissions into the atmosphere, especially in the production of heat and electricity. for this reason, policies to combat climate change are aimed at the energy sector and are aimed at promoting the energy transition, i.e., the transition from a system based on fossil fuels to one with low emissions thanks to the use of renewable sources. many national and european sustainability policies call, in a circuital way, to collectivize renewable energy resources, to influence and optimize their production and consumption, promoting the energy transition. among the most important actions promoted at the international and european levels, to outline the most suitable governance mechanism to follow, there are the 2030 agenda and the green new deal. some of the objectives promoted by the agenda, give importance to the energy issue, conveying the possibility of being able to take advantage of the sustainable model of the energy communities to profoundly change the organization of energy systems and the relationships between subjects, constituting real synergistic and sustainable systems in which all citizens consciously use energy. in particular, the sdgs that include the theme are goal 7 and goal 11, which respectively commit to ensuring access to affordable, reliable, sustainable, and modern energy systems for all and to making cities and human settlements inclusive, safe, durable, and sustainable. these objectives, which translate into concrete actions, could act as a reference point for communities in the energy transition, helping them to experiment with innovative resources and mechanisms, coming to define an integrated system aimed at meeting both energy and anthropic quality priorities. the new global policies, in this way, favor new technologies and mechanisms (e.g., distributed storage, demand-response, electric vehicles) contributing to the emergence of new players in the energy sector, bringing profound transformations to the traditional model, giving space to decentralized production even in locations accessible to the grid (berka and dreyfus, 2021). at the european level, the green new deal (or new green pact), is a binding law for all eu countries, with the aim not only of combating climate change and promoting the energy transition, but also any transformation of the productive fabric towards the circular economy. with directive 2018/2001/eu (known as renewable energy directive ii, redii) and directive 2019/944/eu for the internal market in electricity (also called internal energy market directive, iem), the european union introduced its policy to promote the spread of the use of renewable sources, thus sensitizing society’s consciences towards the energy transition, which translates into significant benefits for the entire ecosystem. article 2 of the redii directive defines the “cer as an ‘a legal entity based on open and voluntary participation, autonomous and effectively controlled by shareholders or members that are in the vicinity of renewable energy production facilities that are developed by the community’.” members can be natural persons, small and mediumsized enterprises, or local authorities, including municipalities, the main objective is to provide environmental, economic, or social benefits to the local area in which it settles. to facilitate the spread and formation of energy communities, article 22 of the redii directive requires eu member states to address obstacles to the realization of the model and to remove any unjustified regulatory barriers, to protect the rights and obligations of members acting as final customers of the community. that article also required individual states to ensure the production, consumption, storage, and sale of renewable energy, as well as collaboration between the energy distribution system operator and the communities themselves, to facilitate the passage of energy within the cers. in redii the definition of “renewable energy consumer cars acting collectively” is introduced, i.e., a group of at least two renewable energy consumer cars that are located in the same building or condominium, thus meaning a final customer who is a producer and consumer of renewable electricity, which in turn can store or sell, provided that these activities do not constitute their main commercial or professional activity (european parliament and council, 2018.). in this way, becoming part of an energy community or in a collective self-consumption scheme, can guarantee advantages of different natures to the citizens involved and to the territory, acting as a springboard towards self-sustainability and energy efficiency. the iem directive introduces the innovative figure of the “active customer” or prosumer, referring to the user who is not limited to the passive role of consumer (consumer), but to the one who actively takes part in the different phases of the production process of the resource (producer). the prosumer, being a subject that owns its energy production plant of which it consumes only a part, feeds the remaining share into the network, and exchanges it with physically close consumers, accumulating it in a special system and returning it to the consumption units at the most appropriate time. he is therefore an active protagonist in the management of energy flows and can enjoy not only relative autonomy but also economic benefits: this sharing model allows for to reduction of the energy supply costs of the various subjects that participate in it. in italy, the transposition of the european redii directive resulted in the enactment of legislative decree 162/2019 (converted with law no. 8/2020 of 28 february 2020) and the related implementing measures (resolution 318/2020/r/ eel of arera and ministerial decree 16 september 2020 of mise) and legislative decree 199/2021, fully implementing the project designated by the eu on the promotion of the use of energy from renewable sources, experimenting immediately, cavallaro, et al.: renewable energy communities in the energy transition context international journal of energy economics and policy | vol 13 • issue 3 • 2023 411 the model of renewable energy communities and the related collective self-consumption. the regulation seeks to collect data and elements so that the directives are fully implemented nationally, as well as directing useful investments to allow the pursuit of the objectives established in the national integrated energy and climate plan (pniec). from the milleproroghe decree, it is clear that ‘collective self-consumption means that carried out by a plurality of consumers, located inside a building in which there are one or more plants powered exclusively by renewable sources. the provision relating to energy communities provides that the participating subjects must produce energy for their consumption with plants powered by renewable sources with a total power not exceeding 200 kw. to share the energy produced, users can use existing distribution networks and use forms of virtual self-consumption. for consumers/producers of this shared energy to be able to access the incentives provided for by the decree, the plant must be new, i.e., installed after 1 march 2020. the incentive rate will be cumulative with tax deductions, where available, and will be established in different values, according to the type below (barroco et al., 2020): a) shared energy in the context of collective self-consumption (same building or condominium): 100 €/mwh b) shared energy within renewable energy communities (same medium/low voltage electrical substation): 110 €/mwh however, to facilitate the dissemination and implementation of the cer model, a series of legal and economic enabling conditions are necessary. the legal nature that a cer can assume differs in terms of governance structure, decision-making process, and responsibilities and the legal forms with which it can be established are varied: cooperatives according to the provision of article 2551, recognized and non-recognized associations, foundations, social enterprises according to legislative decree. 112/2017, benefit companies, third-sector bodies, etc. the wide category of legal vestments that a community can assume has the purpose of promoting and encouraging its constitution, allowing its members to establish the most desirable legal case. the law does not specify the renewable technology to be adopted, but the one that lends itself to better exploiting the advantages of the provision is undoubtedly photovoltaics. article 42-bis of the european directive 2018/2001, defines the treatment of energy produced and shared as follows (pisello et al.,2020): (i) the energy produced may only be shared using the existing distribution network; (ii) shared energy is equal to the minimum, in each hourly period, between the electricity produced and fed into the grid by renewable energy installations and the electricity withdrawn by associated final customers; (iii) energy is shared for instant self-consumption also through storage systems built near buildings/condominiums. the relationships of end customers who take part in the form of energy collaboration envisaged by the cer are governed by a private law contract, which identifies a delegated subject as responsible for the shared energy distribution. this subject could be an external consultant or the condominium administrator to whom customers delegate the management of payment and collection items to the sellers and the energy services manager (gse), playing a fundamental role in accessing the forms of incentive provided. resolution 318/2020/r/eel of 4 august 2020 of the regulatory authority for energy, networks, and the environment (arera), an active part of this implementation process, established the requirements for access to incentives and calculation models to determine the fees to be paid by the gse to self-consumers and members of the energy communities. with the aforementioned resolution, arera designated the regulatory model to be applied to the cers, identifying the benefits that the participants bring to the network and the tariff components that consequently must not be applied to them. the introduction of law 8/2020, has meant that the energy communities have become a real “extended” collective self-consumption scheme, from which to draw both electro-energy and social benefits, in fact with the construction of new plants powered by renewable sources, the cers can give answers to collective needs, for example in the fields of welfare, of local development, of the fight against energy poverty (de vidovich et al., 2021). on 8 may 2021, law no. 53 of 22 april 2021, better known as the “european delegation law 2019–2020”, came into force, with which the parliament and the senate of the republic delegated the government to implement some european directives, including the red ii directive and the iem directive. according to article 5 of the aforementioned law, the government is required to follow a series of principles with the overall transposition of the european directive. in particular, regarding cers (and collective self-consumption schemes), the government is invited to identify incentive measures for the promotion of renewable energy communities aimed at encouraging the participation of local communities in the construction of plants, enhancing the existing electricity grid and maximizing the local use of the related energy production, with consequent lower use of the electricity grid deriving from diffuse generation, without prejudice to the application of general system charges on energy taken from the public grid by final customers and on energy produced and shared using the existing distribution network. to that end, provide that renewable energy installations in collective own consumption configurations and energy communities are guaranteed equal and non-discriminatory access to all relevant regulatory or regulatory support schemes, in particular self-consumption valorization mechanisms and mechanisms for recognizing the avoided costs for the electricity system that such self-consumption entails, however, avoiding distortive effects on the market and providing for simplified mechanisms according to which the share of shared energy, as it is self-consumed locally, is separated a priori and does not fall within the items subject to supply by third-party sellers2. further steps in terms of legislation on cers were taken with legislative decree no. 199/2021 on “implementation of directive 2018/2001/eu of the european parliament and of the council of 11 december 2018 on the promotion of the use of energy from renewable sources”, published in the official gazette on 30 november 2021, and entered into force on 15 december of the same year. article 3 of the legislative decree, in line with the indications of the pniec, establishes the objective pursued, to bring at least 30% of the overall share of energy from renewable 2 https://www.gazzettaufficiale.it/atto/serie_generale/caricadettaglioatto/ originario?atto.datapubblicazionegazzetta=2021-04-23&atto. codiceredazionale=21g00063 (last accessed:2023.01.28). https://www.gazzettaufficiale.it/atto/serie_generale/caricadettaglioatto/originario?atto.datapubblicazionegazzetta=2021-04-23&atto.codiceredazionale=21g00063 https://www.gazzettaufficiale.it/atto/serie_generale/caricadettaglioatto/originario?atto.datapubblicazionegazzetta=2021-04-23&atto.codiceredazionale=21g00063 https://www.gazzettaufficiale.it/atto/serie_generale/caricadettaglioatto/originario?atto.datapubblicazionegazzetta=2021-04-23&atto.codiceredazionale=21g00063 cavallaro, et al.: renewable energy communities in the energy transition context international journal of energy economics and policy | vol 13 • issue 3 • 2023412 sources on gross final consumption and to reduce greenhouse gas emissions by at least 55% by 2030. article 14 of the legislative decree transposing the red ii then defines the specific criteria for coordination between the measures introduced by the national recovery and resilience plan (pnrr) and the sectoral incentive instruments how the benefits of the pnrr will be granted are regulated. in paragraph i.e., it is specified that “in implementation of the measures mission 2, component 2, investment 1.2 ‘promotion of renewables for energy communities and selfconsumption’ are defined criteria and methods for the granting of zero-interest financing up to 100% of eligible costs, for the development of the energy community, as defined in article 31, in small municipalities through the construction of res production plants, also combined with energy storage systems”. the pnrr provides zero-interest loans to encourage the spread of selfproduction and collective self-consumption methods, providing for the disbursement of 2.2 billion euros to be allocated to the development of energy communities. the first line of investment aims to increase the share of renewable energy by accelerating the development of energy communities, guaranteeing them support. a key point of the national program – divided into six missions – is represented by the national ecological and digital transition, which suffers from tangible shortages, and is confronted with the decisive phases of the green transition in access to energy sources and consumption. to do this, the pniec aims to define an organic and synergistic strategy on the five dimensions of energy. these are energy efficiency, renewable energy, greenhouse gas emission reductions, interconnections, and research and innovation. the national pniec 2021–2030 has already been prepared and notified to the european commission, outlining a future update of the long-term objectives and strategy, reflecting the changes that will take place in the meantime at the european level. table 1 shows the main targets, including: • 30% of gross final energy consumption must come from res (32% is the eu target); • 22% of gross final energy consumption in transport must come from res (14% is the eu target). the 55% reduction in co2 emissions by 2030 (data still to be updated in the document stopped at 33% initially expected). the plan, therefore, provides for the promotion of cers to support the economies of small municipalities where self-consumption is particularly difficult. through appropriate information tools, we try to increase the degree of development, the establishment and management of communities, as well as the enhancement of energy production. central is the issue of energy poverty and how energy communities are an adequate tool to combat and promote a conscious and sustainable use of energy resources. over time, the state has tried to provide italy with legal instruments suitable to accommodate the new models of use, production, and energy consumption, with the common intention of implementing a new energy policy that ensures the full environmental, social, and economic sustainability of the territory, preparing guidelines to accompany the energy transition and beyond. 3. data analysis: consumption and benefits 3.1. the state of the art of cers in italy according to the legambiente3 2022 renewable communities report, in italy between renewable energy communities and collective self-consumption configurations, 35 are operational, 41 are planned and 24 are being established. the energy communities that are being born are extremely heterogeneous in the social, environmental, and geographical contexts in which they develop (from friuli-venezia giulia to sicily, from metropolitan areas to mountains, from small towns to large areas), for the actors involved (municipalities, companies, third sector bodies, citizens) and their motivations. what unites their constitution is undoubtedly the desire to seek sustainable and responsible ways of producing, consuming, and using energy, in addition to the incentives that come from it in economic terms. concerning impacts, four macro-categories of benefits can be identified (giusti, 2022): 3 https://legambiente.it/wp content/uploads/2021/11/comunitarinnovabili-2022_report.pdf (last accessed: 2023.01.28). table 1: main energy and climate objectives of the eu and italy for 2020 and 2030 aspect of energy and climate goals 2020 goals 2030 eu italy eu italy renewable energies share of energy from renewable energy in gross final energy consumption 20% 17% 32% 30% share of energy from renewable energy in gross final energy consumption in transports 10% 10% 14% 21,6% share of energy from renewable sources in gross final energy consumption for heating and cooling +1.3% annual (approximate) +1.3% annual (approximate) energy efficiency reduction in primary energy consumption compared with the 2007 primes scenario −20% −24% −32.5% (approximate) −43% (approximate) reduction of final consumption through energy efficiency mandatory schemes −1.5% annual (without transport) −1.5% annual (without transport) −0.8% annual (with transport) −0.8% annual (with transport) ghg emissions ghg reduction versus 2005 for all ets-constrained installations −21% −43% ghg reduction versus 2005 for all non-ets sectors −10% −13% −30% −33% overall reduction of greenhouse gases compared to 1990 levels −20% −40% source: own processing on italian government, 2021 https://legambiente.it/wp%20content/uploads/2021/11/comunita-rinnovabili-2022_report.pdf https://legambiente.it/wp%20content/uploads/2021/11/comunita-rinnovabili-2022_report.pdf cavallaro, et al.: renewable energy communities in the energy transition context international journal of energy economics and policy | vol 13 • issue 3 • 2023 413 • technical-energetic: the electricity system benefits from considerable positive effects deriving from the collective action of producers and consumers who, by aggregating collectively in local energy projects, contribute to the reduction of network losses, to the improvement of voltage profiles as well as the lower stress of the distribution network, with a consequent increase in self-consumption and selfsufficiency indicators. • environmental: with the cer model, there is a proportional increase in the production and share of renewable energy consumption at a local level. legambiente quantifies in 17.2 gw the new renewable capacity expected by 2030 through the establishment of renewable energy communities and self-consumption models (equal to about 30% of the pniec targets) that would allow a reduction in co2eq emissions by 2030 estimated at 47.1 million tons (considering the average consumption of 2700kwh of italian families). to these direct benefits can be added the indirect effect of increasing awareness of the use of energy resources by members. • social: social impacts can be seen both in the process of construction and operation of the erc (increase in participation in the decision-making process), and in the allocation of the value generated that can be partly used to remunerate members, but also to provide services to members, to affect the cost of bills or to finance initiatives identified by the community as priorities (fight against energy poverty, education projects, provision of welfare services, support for local development). in this way, the fight against energy poverty can be addressed directly, for example by reducing the energy expenditure of households in difficulty, or indirectly, by providing tools and information for proper management of household equipment. • direct and indirect economic impact on local development trajectories: the direct benefits were given by the savings in the bill of households, deriving from a conscious use of energy. the indirect benefits are associated with the possibility that the coordination between the subjects of the territory experienced within the ercs and the collaboration with other relevant local actors (pa, companies, etc.), can trigger virtuous processes of shared construction of strategies and actions for local development. even the politecnico di milano has investigated the benefits deriving from energy communities a report on smart grids has provided three classifications of advantages (chiaroni and frattini, 2014): 1. benefits for energy users: the active participation of the population in the various sustainable projects would bring greater awareness of the need to adopt and implement renewable technologies, increasing their acceptability by citizens. this would lead to the optimization of energy expenditure, with an economic advantage in terms of economies of scale, given by community participation in the project from which a reduction in per capita cost results. 2. benefits for the electricity system: with greater use of renewable sources, our country would decrease its energy dependence on foreign supply sources, ensuring greater stability and reliability of the system. 3. benefits for the territory: the production of energy from renewable sources brings benefits to the environment, considering the reduction of pollutants released into the atmosphere, and promoting and raising awareness of a green image of the territory. it is also important to consider the resulting increase in the employment rate resulting from new installations that produce jobs in the long term. 4. benefits for the consumer: the energy community model is characterized by a collegial approach to energy management since it involves a plurality of energy users. such an approach would therefore make it possible to achieve a series of benefits compared to individual ones, the main ones referring to those concerning the synergies obtained from the union of several energy users. another study by seyfang et al. (2012) also highlighted that the key factors for the success of energy communities are: 1. group: a group of members that synergistically and in an organized and cohesive way, acts for a common purpose, and overcomes adversity. 2. project: an idea supported by relevant knowledge and skills, financial and material resources; 3. community: benefits from the implementation of projects. 4. support network: adequate information on the population of renewable energy and energy communities, represents concrete support for the realization of sustainable projects. 5. policy: without a policy framework to support ercs, their development is not desirable. the examples of energy communities show that renewable technologies are now ripe to give life to communities, but also that the obstacles concern the involvement of the population and the political-regulatory support for these projects. as reported, the benefits, advantages, and components that coexist in the creation of communities to pursue energy efficiency, with a view to self-consumption and collaboration, are many. however, achieving climate and energy goals does not only come through energy communities. it must be considered that, although sustainable development has also entered the italian political agenda, translating into a series of interventions, the consequences generated by the covid-19 pandemic, and the most recent conflict in ukraine, have also accelerated the energy crisis, undermining the sustainability of the industrial system and the country. as figure 1 shows, in the italian production system, there is an exponential increase in disbursements for the supply of electricity, as well as gas, which reflects the inevitable consequences on all industrial companies. in this scenario, it is necessary to think about a major restructuring in energy management in all fields. in italy, industry uses almost half of the electricity with 44% of consumption, followed by the service sector, with 30% of consumption, the domestic sector with 23%, and the agriculture sector, which represents just over 2% of electricity consumption. analyzing in detail the consumption of electricity in industry, we note the sectors most dependent on the availability and costs of electricity: metallurgy, food industries, manufacture of chemicals, metals, plastics, paper, and many others. these are large, mediumsized, small, and very small enterprises that generate employment cavallaro, et al.: renewable energy communities in the energy transition context international journal of energy economics and policy | vol 13 • issue 3 • 2023414 and contribute significantly to the economy and social well-being. the challenge lies in finding more and more ways to ensure “green” electricity independently, without depending too much on foreign countries and the risks of shortage of the same and price increases that would bring supply difficulties to the industry and would put at risk the prospects of sustainability of the country. after the promising beginning of 2010, and until 2015, the growth of renewable sources did not continue the expected development in the following years, as can be seen from the following terna chart (figure 2). as many as 161.7 twh, equal to 58%, were produced in 2020 from traditional imported thermal sources, mainly oil and gas which, together with electricity imported from other countries, bring our electricity dependence to exceed 70%. pnrr resources should be useful to improve and make the country’s energy system resilient, investing in research, photovoltaics, and all renewable energy sources. precisely because of the great unknowns that characterize future energy prospects, the international news agency bloomberg, among the best-known in the world, hypothesizes three possible scenarios (figure 3). in 2019, 83% of the world’s energy is mainly produced from fossil energy sources and only 12% from renewable sources, and 5% from nuclear power. in a vision of the implications in 2050, the scenarios that can be hypothesized according to bloomberg are three: 1. a grey perspective, with a reduction, not entirely significant, in the use of fossil fuels from 83% to 52%; the increase from 12% to 42% of renewable sources and the stability of nuclear energy to 5%. 2. a green perspective, fully focused on the transition to renewable energy, with a use of 85%, a considerable reduction of fossil fuels to 10%, and stability of nuclear power to 5%. 3. the third red perspective, so defined because there would be a development of new generation nuclear power, respectful of the environment, up to represent 66% of energy sources, with a substantial part equal to 27% of renewable sources and 7% of residual fossil fuels. given the implications that are expected in the future, the most appropriate strategies to be adopted would be to increase investment in renewable energy to guide the transition to green sources, avoiding the impoverishment of the country and contributing to the rebirth of the ecosystem; turning research towards nuclear power to increase its use rate. given this, the diffusion of energy communities, therefore, seems fundamental, considering the benefit in terms of reducing the costs incurred by figure 1: energy consumption by the industrial sector source: https://www.collaudo.terna.it/it/sistemaelettrico/statistiche/evoluzione-mercato-elettrico/consumi-energia-elettrica-settore cavallaro, et al.: renewable energy communities in the energy transition context international journal of energy economics and policy | vol 13 • issue 3 • 2023 415 the electricity system by about 10–20% (chiaroni and frattini, 2014). support of an adequate regulatory framework, which appropriately considers the benefits inherent in the model and the impacts it would bring on network operators, would favor this diffusion. 3.2. focus on east naples’s energy community the vision of the energy community, as an active and integrated component of a territorial community of self-government with the growth of forms of community democracy (bolognesi and magnaghi, 2020), goes far beyond the only technical-administrative purpose linked to the energy saving of the inhabitants, it is rather a much more articulated process, of a socio-political nature, which develops together energy wealth, self-production capacity of the local energy system and enhancement of the heritage that becomes a common good. with the retrieval of european directives on community energy, the first energy communities arose in italy, in the legal form of third sector bodies, social enterprises, and community enterprises, to promote the cer model and spread its underlying ideological vision. one of the first examples of the energy and solidarity community (so defined), in the national panorama that fully embodies the socio-environmental purpose of the model, is that of east naples, established in 2020 in the district of san giovanni a teduccio. thanks to the precious contribution figure 2: production (gwh) by source source: https://www.collaudo.terna.it/it/sistema-elettrico/statistiche/evoluzione-mercato-elettrico/produzione-energia-elettrica-fonte source: 4https://www.rinnovabili.it/energia/politiche-energetiche/zero-emissioni-al-2050-bnef-strade figure 3: three possible bloomberg’s prospects for 2050 cavallaro, et al.: renewable energy communities in the energy transition context international journal of energy economics and policy | vol 13 • issue 3 • 2023416 of legambiente campania, which has provided the community with all the technical skills for its development, and to the famiglia di maria foundation, with the support of fondazione con il sud which co-financed this virtuous project. the family of mary foundation is a philanthropic institution of catholic origin that in the nineteenth century ran an orphanage in the neighborhood; today it is a secular educational institution that collaborates with the social services of the municipality and manages a socio-educational center in san giovanni a teduccio. legambiente campania and fondazione con il sud believed in the realization of this project, starting the process of establishing an energy community that led, in fact, to the redevelopment of the area. the famiglia di maria foundation, in the same way, promoter of the idea, represents an important educational and cultural garrison within the district of san giovanni a teduccio, welcoming everyday children who live a difficult reality, offering them canteen, after-school and various training activities, also carrying out projects with families. fondazione con il sud has installed a photovoltaic system on the roof of the foundation’s main building, which benefits 20 families of consumers who use the energy produced sustainably. the plant consists of 166 photovoltaic panels that generate a total power of 53 kw, with a storage system to store the unused energy produced (bernardoni et al., 2022). thanks to self-production and internal distribution of energy, community members can enjoy significant advantages in terms of reducing costs in the bill, drawing considerable economic benefits; environmental benefits deriving from the use of energy produced from renewable sources; and cultural benefits as being part of an energy community, on the one hand, increases citizens’ awareness of the problems environmental (de vidovich et al., 2021) and on the other hand, represents a tool for spreading values and a civic sense that can be applied in other areas of social and economic life. with the help and mediation of the fondazione famiglia di maria, an important “community work” was made possible, which led to the creation of the rec, although the site in which it stands is a neighborhood characterized by strong mistrust. the activism and the desire for redemption have led the community, from the three families that made up the first founding nucleus, to sensitize other families in the neighborhood, up to involving the 20 families currently members. the birth of the erc represents an important result for the famiglia di maria foundation, a form of social redemption with a symbolic value, as well as economic, to combat energy poverty. the adhesion by the families of the district of san giovanni a teduccio to the energy and social community does not bring with it only economic benefits but represents an active engine of cultural change in an entire neighborhood. a challenge that legambiente defines as “revolutionary”, with important repercussions not only environmental but also social, is a concrete opportunity for the regeneration of the suburbs. for the reasons explained above, it is called “energy and solidarity community”, becoming an opportunity for people and for the territory to be promoters of the ecological transition, which also keeps within the change of society itself. in this way, attention is generated toward the environment and towards a community that will provide a chain of mutual aid to feed good practices (bernardoni et al., 2022). in italy, there are over two million families in conditions of energy poverty, which with the self-production and sharing of energy from renewables, and through interventions that reduce the consumption of homes, could improve their living conditions. environment, solar energy, and educational equality are the components that define the energy community born in naples and that guarantee a fairer future for the current and future generations, promoting, in fact, sustainable development. 4. conclusions energy, like other natural resources, is a limited solution, so it is necessary to find suitable solutions to decouple economic growth from the consumption of resources. renewable energy communities, as a consolidation of a spontaneous process of involvement of social actors along the entire energy chain, can be protagonists of the sustainable transition of the contemporary energy system. their impact in terms of local self-consumption and distortion of the rules of operation of the energy market identifies suitable components for the energy transition. the diffusion of cers represents a great opportunity to experiment with new energy models based on the self-organization of members and on the enhancement of the resources available to the territories. the cers have above all great social value as well as economic and environmental, as they can represent models of synergy and cooperation spread throughout the national territory, helping to experiment with innovative solutions in the management of the common good, in the implementation of new local development policies and the experimentation of new welfare models. the proposed changes must be confronted with market and regulatory challenges. the directives and national transposition have created an enabling environment and the prerequisite for making cers attractive to public and private investments. the cultural resistance and inertia of the system cannot be removed by law so that cers can evolve from a niche of radical innovation to a new energy regime in contemporary europe. the theoretical model must adapt to the nascent concrete cases, starting from the ability to penetrate urban systems, facilitated by self-consumption schemes, which remains a great challenge for any ecological transition policy. in this perspective, an important role must be played by business networks, associative networks, universities, and research centers, foundations of banking origin, which will be able to carry out specific training courses on the energy transition dedicated to organizations, such as the support of subjects specialized in the energy sector. the different degree of development of the energy communities compared to other european realities, will bring heterogeneity in the development paths of the renewable energy communities, but an advancement of their state of the art cannot be excluded, with the adoption of more detailed common rules at the supranational level. the energy sector is facing a great transformation process, encouraged by the digital revolution that is encouraging the opening of new forms of energy management, control, and trading. the scenarios that can be envisaged for the energy sector can be different and radical, the desirable one is a prosperous energy future, with significant growth processes for energy companies and a greater diffusion of renewable supply sources, which can cavallaro, et al.: renewable energy communities in the energy transition context international journal of energy economics and policy | vol 13 • issue 3 • 2023 417 support and counteract the possibility of a decline in current energy systems, caused by disintermediation and customer behavior. the energy communities will play a key role in the future ‘golden age’ of energy, a framework of stable rules, a strong simplification of authorization procedures, and inclusive operating models with wide freedom of action for prosumers would be useful tools so that they can quickly establish themselves throughout the national territory and, in this way, contribute significantly to the planned objectives. all this must be combined with the rational exploitation of resources, compatible with environmental constraints, which respects the territories, encouraging the development of ‘ethical’ initiatives. if it were possible to coordinate the production and consumption of energy from renewable sources, the activities of the energy communities, and all circular economy actions such as the reuse of different types of waste (energy recovery) and the use of energy that normally without the use of specific technologies (cogeneration-refrigeration), a mix of virtuous actions would be generated. the latter, if used simultaneously, could implement a strategy that fully respects the decarbonization objectives, with a view to efficiency and sustainability, able to protect and enhance the environment, and that can reduce the dependence on imports from third countries. being an energy community means embarking on a path that starts from the community dimension to adopt new ways of producing and consuming energy. this strengthens the link with the environment with the use of renewable sources, for the realization of a sustainable economic and social system for present and future generations. energy community means reciprocity, collaboration, exchange, synergy, and values at the base of the analyzed model that become inspiring principles of living together. references barroco, f., borghetti, a., cappellaro, f., carani, c., chiarini, r., d’agosta, g. (2020), energy communities in italy a guide-to-guide citizens in the new market. sweden: enea. becker, s., kunze c. (2014), transcending community energy: collective and politically motivated projects in renewable energy (cpe) across europe. people place and policy online, 3, 180-191. berka, a., dreyfus, m. (2021), decentralisation and inclusivity in the energy sector: preconditions, impacts and avenues for further research. renewable and sustainable energy reviews, 138, 110663. bernardoni, a., borzaga, c., sforzi, j. (2022), renewable energy communities. social enterprise. doi: 10.7425. bolognesi, m., magnaghi, a. (2020), towards energy communities. territorial sciences, special issue “living in the territory at the time of covid”. pp. 142-150, doi: 10.13128 bonomi, a. (2020), territory as a social construction at the time of covid. spatial science, territorial sciences, special issue “living in the territory at the time of covid”. pp. 118-125, doi: 10.13128 burchell, k., rettie, r., & roberts, t. c. (2014). community, the very idea!: perspectives of participants in a demand-side community energy project. people, place and policy, 8(3), 168-179. chiaroni, d., frattini, f., franzo, s. (2014), smart grid report. prospects for the development of energy communities in italy. italy: energy and strategy group politecnico di milano. isbn: 9788898399048 dardot, p., laval, c. (2014), the new way of the world: on neoliberal society. london: verso books. de vidovich, l., tricarico, l., matteo, z. (2021), community energy map. a survey of the first experiences of renewable energy communities. italy: franco angeli. p1-141. elliott, r.n., langer, t., nadel, s. (2006), reducing oil use through energy efficiency: opportunities in the industrial sector. environmental quality management, 15, 81-91. energy policies. available from: https://www.rinnovabili.it/energia/ politiche-energetiche/zero-emissioni-al-2050-bnef-strade [last accessed on 2023 jan 03]. energy market statistics. available from: https://www.collaudo.terna.it/it/ sistema-elettrico/statistiche/evoluzione-mercato-elettrico/consumienergia-elettrica-settore [last accessed on 2023 jan 10]. energy market statistics. available from: https://www.collaudo.terna. it/it/sistema-elettrico/statistiche/evoluzione-mercato-elettrico/ produzione-energia-elettrica-fonte [last accessed on 2023 jan 10]. european parliament and council. (2018), directive 2018/2001 on the promotion of the use of energy from renewable sources. belgium: european parliament and council. giusti, a. (2022), energy communities: the protagonists of the ecological transition. legal daily-law journal-issn 2784-8906 magnaghi, a. (2013), spatial forms and dimensions of new demand for urbanity. spatial science, 356-359. magnaghi, a. (2013), the territory energy factory: an experimental integrated project. netherlands: wolters kluwer. pellizzoni, l. (2018), community energy. a critical survey of the literature. energy and innovation between global flows and local circuits. trieste: edizioni università di trieste. p17-41. pisello, a.l., piselli, c., pioppi, b. (2020), a new model for the national and european. aicarr journal, 65(6), 42-47. report on renewable energy communities. available from: https:// www.legambiente.it/wp-content/uploads/2021/11/comunitarinnovabili-2022_report.pdf [last accessed on 2023 jan 08]. romero-rubio, c., de andrés díaz, j.r. (2015), sustainable energy communities: a study contrasting spain and germany. energy policy, 85, 397-409. seyfang, g., park, j.j., smith, a. (2012), community energy in the uk. working paper 3s. norwich: university of east anglia. p11. star, s.l., griesemer, j.r. (1989), institutional ecology, ‘translations’ and boundary objects: amateurs and professionals in berkeley’s museum of vertebrate zoology, 1907-39. social studies of science, 19(3), 387-420. szulecki, k. (2018), conceptualising energy democracy. environmental policy, 27, 21-41. text of law. available from: https://www.gazzettaufficiale.it/ a t t o / s e r i e _ g e n e r a l e / c a r i c a d e t t a g l i o a t t o / o r i g i n a r i o ? a t t o . d a t a p u b b l i c a z i o n e g a z z e t t a = 2 0 2 1 0 4 2 3 & a t t o . codiceredazionale=21g00063 [last accessed on 2023 jan 08]. torabi moghadam, s., di nicoli, m.v., manzo, s., lombardi, p. (2020), integrating energy communities in the transition to a low-carbon future: a methodological approach. energies, 13, 1597. walker, g., devine-wright, p. (2008), community renewable energy: what should it mean? energy policy, 36, 497-500. . international journal of energy economics and policy | vol 7 • issue 2 • 2017 185 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(2), 185-192. applying the capital asset pricing model in identifying the electricity retail price in ho chi minh city, vietnam nguyen minh ha1*, nguyen duy hoang2 1ho chi minh city open university, vietnam, 2ho chi minh city power corporation, vietnam. *email: ha.nm@ou.edu.vn abstract this paper applies the capital asset pricing model to calculate the expected return rate equivalent to electricity retail price in ho chi minh city (hcmc), with observed 1464 h of hcmc power corporation. the study suggests the model of calculate the electricity retail price so that government has more tools to adjust the electricity prices in electricity market, and recommends an electricity retail price list of 12 levels, with the minimum sale price of 965 vnd1/kwh and maximum sale price of 1675 vnd/kwh. specifically, with current electricity sale price of 1447 vnd/kwh, the hcmc power corporation reaches the highest return rate of 11.7% and the return rate fluctuates from −12% to 11.7% (price of 1447 vnd/kwh with rf = 6%). the sensitive analysis shows that from rf = 12% above, the return rate always reaches the maximum point at price of 1313 vnd/kwh (it is an average cost to produce 1 kwh). keywords: capital asset pricing model, electricity retail price, electricity market jel classification: q4 1 vnd is vietnamese currency, and exchange rate between vnd/usd is now about 22,500 vnd/usd. 1. introduction electricity retail tariffs in vietnam are currently approved by the prime minister based the appraisal results of the ministry of industry and trade for the suggestion of vietnam electricity (evn). in the structure of electricity retail tariffs, electricity regulatory authority of vietnam (erav) has regulated the tariff as follows: (i) to increase the price for production load and to decrease the price for households; (ii) to support the price for low-income households and poor households (for first 50 kwh/month); (iii) to be applicable multi-tariffs. all the above characteristics showed the existence of compensation and subsidy between different customer groups through electricity prices. accordingly, each customer is charged at different rates (đàm, 2012). in vietnam, the electricity price is determined based on the basis of production cost, transmission cost, distribution cost and reasonable profits for business (ngô, 2012), in which the most importance is the average retail price and retail prices for end-users. however, the method of determining the electricity retail tariff is now mainly based on statistical cost accounting of the sold goods cost of evn, with the aim to cover losses disregard to the cause and measures to reduce costs. the adjustment is just focused on the increasing prices that are not interested in reducing the price. to develop a competitive electricity market is the most effective solution to make the electricity price transparency. according to rothwell and gómez (2003), the implementation of the restructuring and deregulation of the power sector is to reduce electricity prices through cost savings. to reach the efficient pricing in electricity retail sector and generate optimal benefit for both retailer company (retco) and customers, the appropriated models which concerned with risk recovery are needed. efficient retail price is necessary to ensure that the electricity will be used in the most optimal way and both producer and customer will get the maximization of their benefit. on top of that, consumer will be satisfied due to the improvement of transparency in electricity pricing. in this paper, the electricity retail price will be studied and determined through the capital asset pricing model (capm). this method will be concerned as the efficient tool to determine the ha and hoang: applying the capm model in identifying the electricity retail price in ho chi minh city, vietnam international journal of energy economics and policy | vol 7 • issue 2 • 2017186 retail electricity price for the end-users. the rest of the paper is structured as follow: in section 2 overview of the deregulation of vietnamese power sector and fundamental of capm approach. spot market modeling algorithm where the market clearing price (mcp) is generated, is analyzed in section 3. data analysis is shown in section 4. conclusions and recommendations are given in section 5. 2. literature review 2.1. competitive electricity market and deregulation of power sector in vietnam over the years, the power sector throughout the world has experienced important changes due to deregulation and restructuring (rothwell and gómez, 2003). the vertically integrated state-owned power company (pc) is being changed to a new structure which separated generation, transmission and distribution. in the wholesale market, power plants will compete to sell electricity. for the retail market, customers can choose services from various retail companies with the most reasonable price and good quality service. power transmission and distribution still need to be regulated by the authorities. this model ensures openness, non-discrimination for the components to participate in the market in stages: generators, retailers and customers. to withdraw the monopoly in vietnamese power sector, to improve transparency in electricity pricing, to reduce amount outstanding of state enterprises, and to improve economic efficiency, deregulation has to be considered. the cost-based power pool model has been chosen for vietnamese power sector. under the cost-based model, generator will bid at their marginal costs (mc) or actual or estimated variable production costs of supply. the system marginal price can be verified by short-run mc which is consisted of operating, maintenance and fuel cost of the marginal plant. since the market is being formed. the state-owned vietnam electricity (evn) still dominates vietnam’s electricity sector, directly and indirectly controlling most generation, transmission, distribution, bulk power and retail power supply activities. evn plays the following key roles in the pilot market. 2.1.1. system operator (so)/market operator (mo) evn’s national load dispatch center (nldc) is charged with the roles of so/mo in the market. the nldc is therefore responsible for thermal and hydro scheduling and dispatching. in addition the nldc is also responsible for hydro resources management which includes reservoir operations, flood control and irrigation. 2.1.2. single buyer (sb) evn acts as the sb and trader for wholesale electricity in the market. the evn sb procures the energy its needs to supply evn pcs from evn’s generation companies and submits about 75% of the energy bids to the mo via the power pool web site. 2.1.3. evn generator companies (gencos) evn remains the owner and operator of the generation units declared by the government as strategically important generators. these units have been identified as the three largest multipurpose hydroelectric complexes in the country. in addition, under its current re-structuring plan evn has retained majority ownership (over 51%) of all equitized generation units, giving evn control over most of the existing generation in the country. evn owned and controlled generators are capable of offering their bids directly into the market via the power pool web based portal. 2.1.4. transmission owner/operator evn also owns and operates transmission company responsible for the 500 kv, 220 kv and some 110 kv transmission assets. this includes oversight of interconnections agreements between new ipps and bots and evn. 2.1.5. distribution owner/operator the 05 distribution companies (retcos) responsible for distribution asset management (up to 110 kv), procuring power from evn at the internal price and in turn, selling the power to their franchise customers at tariffs approved by the prime minister. in 2011, vietnam introduced its competitive generation market (cgm) in pilot form, which moved to full operation in 2012. under the cgm, generators compete in an hourly spot market to sell power to a sb, the electric power trading corporation which is a dependent unit within evn. currently, pcs hold a monopoly over sales to all electricity customers in their service areas. under the power sector reform roadmap approved by the prime minister, large customers will be allowed to purchase directly from generators from 2015 onwards. from 2022, with the start of full retail competition, all customers will be allowed to choose their electricity supplier and pcs will no longer hold a monopoly over electricity sales. they will continue to be the monopoly owner and operator of the distribution network in their service areas and will charge a fee for use of this network by other suppliers. in conclude, vietnam electricity market will be formed and developed in three phases as follows: (i) cgm (2009-2015), (ii) competitive wholesale market (2016-2025), (iii) competitive retail market (after 2025). 2.2. capm a capm is a simple relationship that links the return on particular stock with the return on portfolio made up of the entire market (hull, 2003). the capm model is widely used as measure of risk in the portfolio investment. e(rj−rf) = βj × e(rm−rf) (1) where, e(rj−rf) is called the expected excess rate of return of asset j. e(rm−rf) is called the expected excess rate of return of the market portfolio. βj is normalized covariance between j th asset and total portfolio returns. ( , ) ( ) j m j m cov r r var r  = (2) as e(rf) = rf: ha and hoang: applying the capm model in identifying the electricity retail price in ho chi minh city, vietnam international journal of energy economics and policy | vol 7 • issue 2 • 2017 187 e(rj)−rf = βj × e(rm−rf) (3) under the capm, the expected return e(rj) of any asset j satisfies: e(rj) = rf + βj × e(rm−rf) (4) rj is return of any asset j, rm is rate of market return, rf is risk free rate of return. where, • if βj = 0 then expected return of asset j is risk free rate of return, • if βj = 1 then asset j has the risk of market and expected return equal to rm, • if βj > 1 then the risk of asset j is higher than that of market and expected return higher than rm, • if βj < 1 then the risk of asset j is less than that of market and expected return less than rm. the capm model can be appropriately used for retcos who invest the payment received from end users in gencos in competitive market (karandikar et al., 2007). in model, risk will be considered as variance and for any capital the total variance of return must be minimized. the price change will affect the estimation of asset returns, thus the retcos will recalculate their projected price, which will be offered to the customer, until both demand and supply are matched. the capm model can be appropriately used for determining the retail tariff in order to regulate retcos in competitive market (karandikar et al., 2007). the expected rate of return of retailer from one generator is determined using capm model is as follows: e(rg) = β[e(rm)−rf] + rf (5) where, e(rg) is expected rate of return from generator, β is normalized co-variance between profit from generator and total profit of retailer, e(rm) is expected rate of market return of each portfolio i.e., each generator and is a ratio of generator mean profit and mean of total profit, rf is risk free rate of return. in case that β is almost zero, then the asset is completely uncorrelated with the market. accordingly, in this case, the expected return is the risk free rate. if e(rj) < rf, the asset may face the high risk. under this circumstance, retcos will accept the lower expected value by concern some forms of insurance. for conclusion, the retcos can quantify their business risk by applying capm model for the different tariffs. 3. methodology in the spot market, the gencos have to bid their price and quantity of their generated electricity to the electricity pool. ho chi minh city (hcmc) power corporation will get fixed rate of return, controlled by erav, while they purchase from volatile market which the price can be change all the time and hardly to be predicted. the calculation in this study as follows: • step 1 – generating the spot price: the time length in this study is 1464 h in the period of may and june of 2013 from may 01, 2013 to june 30, 2013 in the area of hcmc. the data needed are load demand and power supply for hcmc during 2 months period of may and june in 2013. • step 2 – determination of β which is normalized co-variance between profit from generator supply power for hcmc and total profit of evnhcmc: using the calculated mcp and proposed retail tariff to determine the expected return in each hour of 1464 h of each unit of generator. divide the variance of rate of return of market by covariance of expected return of generators and profit of evnhcmc. • step 3 – using capm to calculate the expected rate of return of evnhcmc. • step 4 – data analysis to determine the appropriate electricity retail tariff for regulate pcs in power competitive market. 3.1. data collection the load for this study is varying hour to hour. the maximum load is 3047.8 mw, the minimum is 0 mw, and the average is 2,288.7 mw. figure 1 gives the total load variation for the 1464 h. for generating the spot market, the supply and demand curves have to be generated. as for supply curve generating, the power plants and generators data are required, such as power plant capacity, force outage rate, spinning reserve, and short-run mc (fuel cost, fixed and variable operating and maintenance cost), etc. (pasapong and charles, 2011). power plant selection to supply power for hcmc has to meet followings criteria: • hcmc is in the southern of vietnam; therefore, the power plants are dispatched to supply power for hcmc in the state of optimum power flow • these plants must be in the list of plans that are participate in the cgm. figure 1: hourly load of ho chi minh city in may and june/2013 source: evnhcmc (2013) ha and hoang: applying the capm model in identifying the electricity retail price in ho chi minh city, vietnam international journal of energy economics and policy | vol 7 • issue 2 • 2017188 as the result, the 6 plants with 21 generators are selected which are shown in table 1. this list is also the investment portfolio of evnhcmc. 3.2. mcp generating the following spot market algorithms shortly describe how the model will be worked. starting from the 1st of may to 30th of june in year 2013, the following steps were performed: • at the beginning of each simulated hour, the model will uses the demand data between evnhcmc and gencos • the model permits each generating unit the offer only one bid into the system or the pool. each generator will use their srmc as the offered price • the model then builds the stair-step supply curve ranked according to the plants’ merit order and the industry supply at each hourly basis. according with the auction approach and the actual dispatch schedule that happening in may and june in 2013 provided by evn, the mcp at the given hour will be equal to the srmc of last generator who allocate their electricity to the pool and make the total load demand equal to the supply offer. for example, on the 1st h where the load needed is 1532.9 mw, the selected generator, who has been selected as the last bidder in the system at that hour, is phu_my_21_gt22 (code name: g10). thus, the mcp of the system at 1st h will be equal to g10 srmc which is 580 vnd/kwh (figure 2). the generators (from g3 to g9) could not run at full load due to periodically maintenance so the last selected generator is g10. hence, as for remaining 1463 h, the process will be continued as same as the 1st h process. the results reveal that the mcp varies from 612 to 3359 vnd/kwh (figure 3). 3.3. proposal of retail tariff and calculating β retail tariff is set by government based on following costs: generation cost, transmission cost, distribution cost and auxiliary services fee. in this paper, the determined average generation cost of 1 kwh is 1.019vnd; adding up with generation cost, transmission cost, distribution cost and auxiliary services fee defined are as follows: • transmission cost = 73 vnd/kwh • distribution cost = 216 vnd/kwh • auxiliary services fee = 5 vnd/kwh average retail price for 1 kwh = 1.019 + 3 + 216 + 5 = 1.313 vnd/kwh. evnhcmc has invested in 21 generators; the average cost for all 21 generators is 6.2 usc/kwh. follow with this cost per kwh, the range of proposed fixed retail price will start from 965 vnd to 1675 vnd (table 2). this assumption with ±5% of average retail price is based on the decision by government that allowing evn to adjust the retail price if the proposed increase/decrease price is lower than 5% of current price. table 1: the description of selected generators (arranged with respect to merit order) code name generator plant type bid capacity (mw) bid price (vnd/kwh) accumulation power (mw) g1 phu_my_1_gt11 phu my 1 ccgt 365 580 365 g2 phu_my_1_gt12 phu my 1 365 580 730 g3 phu_my_1_gt13 phu my 1 365 580 1095 g4 da_nhim_h1 da nhim hydropower 41,5 589 1136.5 g5 da_nhim_h2 da nhim 41,5 589 1178 g6 da_nhim_h3 da nhim 41,5 589 1119.5 g7 da_nhim_h4 da nhim 41,5 589 1261 g8 phu_my_4_gt41 phu my 4 ccgt 245 603 1506 g9 phu_my_21_gt21 phu my 2.1 ccgt 245 612 1751 g10 phu_my_21_gt22 phu my 2.1 245 612 1966 g11 phu_my_21_gt24 phu my 2.1 245 612 2241 g12 phu_my_21_gt25 phu my 2.1 245 612 2486 g13 nhon_trach_2_gt5 nhon trach 2 ccgt 385 819 2871 g14 nhon_trach_2_gt6 nhon trach 2 385 819 3256 g15 phu_my_4_gt42 phu my 4 ccgt 245 827 3501 g16 nhon_trach_1_gt11 nhon trach 1 ccgt 230 883 3731 g17 nhon_trach_1_gt12 nhon trach 1 230 883 3961 g18 ham_thuan_h1 ham thuan hydropower 150 1.015 4111 g19 ham_thuan_h2 ham thuan 150 1.918 4261 g20 da_mi_h1 da mi hydropower 87 3.539 4348 g21 da_mi_h2 da mi 87 3.539 4435 source: evn (2013). evn: vietnam electricity figure 2: the process to determine market clearing price on the 1st h ha and hoang: applying the capm model in identifying the electricity retail price in ho chi minh city, vietnam international journal of energy economics and policy | vol 7 • issue 2 • 2017 189 then, calculating expected profit of generator(s) and evnhcmc’s profit as follows: • expected profit of 1 generator = (mcp – cost for running of 1 kwh) × capacity of generator • expected profit evnhcmc = (retail price × power demand) – (mcp × power supply). for example, with the price of 965 vnd/kwh and the information provided for generator g1 is: • expected profit of g1 = (612–580) × 365 = 11.680.000 vnd • expected profit of evnhcmc = (965 × 1532.9) – (612 × 1.537) = 538.337.175 vnd. doing above calculations for the rest of 1463 h with 11 retail prices indicating in table 2. then calculating β of 21 generators: ( , ) ( ) j m j m cov r r var r  = and expected return of the market erm. average profit of generators average profit of evnhcmcm er = 4. data analysis after load demand, selected generators and mcp are determined, the capm model can be used to find the effective rate of retail price for retailer to gain the highest of evnhcmc’s return. according to different offered fixed retail price, β of different generators (figure 4 and table 3) and expected return of retailer from each generator are determined. in present case, risk free rate of return is assumed 6%, 8%, 10%, and 12%. table 4 is shown β results while tables 5-8 are represented expected rate of return and average value for all generators at different fixed retail price at each assumed risk free rate. generators g20 and g21 of da mi hydropower has the highest bid price of 3.539 vnd/kwh so they have not been chosen to dispatch; therefore, no revenue for generator to calculate β. as for g16 has β = 0. thus, the expected rate of return of g16 unit will be risk-free rate. the result shows that with current electricity sale price of 1447 vnd/kwh, the hcmc power corporation reaches the highest return rate of 11.7% and the return rate fluctuates from −12% to 11.7% (price of 1,447 vnd/kwh with rf = 6%). the sensitive analysis shows that from rf = 12% above, the return rate always reaches the maximum point at price of 1313 vnd/kwh (it is an average cost to produce 1 kwh). 5. conclusions and recommendations 5.1. conclusions to perform preliminary analysis of efficient electricity retail price in competitive market by using quantitative methods is the main figure 3: the market clearing price for all 1464 h figure 4: β of different generators table 2: proposed fixed retail price of evnhcmc 1 2 3 4 5 6 7 8 9 10 11 12 retail price (vnd/kwh) 965 1.016 1.069 1.125 1.185 1.247 1.313 1.378 1.447 1.519 1.595 1.675 evnhcmc: vietnam electricity ho chi minh city table 3: expected profit of g1 and evnhcmc in 1st h with the price of 4.6 usc/kwh hour gen capacity (mw) bid price (vnd/kwh) mcp (vnd/kwh) expected profit of g1 (103 vnd) demand (mw) supply (mw) evnhcmc’s profit ($) 1 g1 365 580 612 11.680 1.532,9 1.537 538.337 evnhcmc: vietnam electricity ho chi minh city, mcp: market clearing price ha and hoang: applying the capm model in identifying the electricity retail price in ho chi minh city, vietnam international journal of energy economics and policy | vol 7 • issue 2 • 2017190 ta bl e 4. β o f d if fe re nt g en er at or s r et ai l p ri ce v n d /k w h β1 β2 β3 β4 β5 β6 β7 β8 β9 β1 0 β1 1 96 5 −0 .5 85 99 −1 .2 24 54 −0 .5 47 15 −0 .7 35 48 −0 .7 72 98 −0 .6 63 39 −0 .7 52 58 −0 .8 78 53 −0 .4 31 46 −0 .4 31 85 −0 .4 36 23 1. 01 6 −0 .0 21 41 −0 .0 31 74 −0 .0 18 82 −0 .0 24 05 −0 .0 25 35 −0 .0 19 91 −0 .0 24 35 −0 .0 28 91 −0 .0 15 65 −0 .0 15 61 −0 .0 20 79 1. 06 9 −1 .0 73 42 −1 .9 90 89 −0 .9 91 7 −1 .3 56 52 −1 .4 28 72 −1 .2 14 69 −1 .3 91 64 −1 .8 12 14 −0 .7 22 95 −0 .7 23 52 −0 .7 38 28 1. 12 5 −1 .3 54 89 −2 .4 97 87 −1 .2 48 42 −1 .6 98 93 −1 .7 84 32 −1 .5 23 13 −1 .7 40 09 −2 .3 71 33 −0 .8 93 58 −0 .8 94 61 −0 .8 97 96 1. 18 5 −1 .5 28 4 −2 .6 65 43 −1 .4 03 4 −1 .8 96 95 −1 .9 81 6 −1 .7 00 16 −1 .9 35 67 −2 .7 85 86 −0 .9 91 68 −0 .9 92 92 −0 .9 93 02 1. 24 7 −1 .6 02 55 −2 .5 88 68 −1 .4 65 67 −1 .9 62 72 −2 .0 33 89 −1 .7 57 54 −1 .9 91 2 −3 .0 62 58 −1 .0 26 58 −1 .0 27 8 −1 .0 26 32 1. 31 3 −1 .5 60 17 −2 .2 98 53 −1 .4 20 18 −1 .8 79 −1 .9 25 47 −1 .6 79 42 −1 .8 90 66 −3 .1 57 67 −0 .9 88 18 −0 .9 89 11 −0 .9 86 8 1. 37 8 −1 .4 05 5 −1 .8 77 12 −1 .2 72 26 −1 .6 59 34 −1 .6 76 07 −1 .4 78 41 −1 .6 51 94 −3 .0 40 07 −0 .8 79 74 −0 .8 80 18 −0 .8 77 56 1. 44 7 −1 .1 52 92 −1 .3 86 28 −1 .0 36 22 −1 .3 27 67 −1 .3 15 2 −1 .1 77 06 −1 .3 02 84 −2 .7 00 78 −0 .7 09 76 −0 .7 09 61 −0 .7 07 08 1. 51 9 −0 .8 38 68 −0 .9 02 46 −0 .7 46 61 −0 .9 35 51 −0 .9 01 69 −0 .8 23 26 −0 .8 99 69 −2 .1 60 45 −0 .5 01 43 −0 .5 00 85 −0 .4 98 65 1. 59 5 −0 .5 16 24 −0 .4 90 56 −0 .4 52 94 −0 .5 51 57 −0 .5 09 7 −0 .4 79 59 −0 .5 14 4 −1 .4 95 06 −0 .2 89 54 −0 .2 88 8 −0 .2 87 08 1. 67 5 −0 .2 42 15 −0 .1 92 81 −0 .2 06 31 −0 .2 42 02 −0 .2 06 19 −0 .2 04 78 −0 .2 12 87 −0 .8 32 78 −0 .1 11 78 −0 .1 11 18 −0 .1 09 95 r et ai l p ri ce v n d /k w h β1 2 β1 3 β1 4 β1 5 β1 6 β1 7 β1 8 β1 9 β2 0 β2 1 96 5 −0 .4 32 44 −9 .4 88 87 −9 .4 76 03 −1 .0 14 93 0 0. 63 56 4 0. 88 76 2 1. 28 97 8 − − 1. 01 6 −0 .0 15 68 −0 .3 48 01 −0 .3 45 67 0. 00 18 91 0 0. 01 71 0. 84 59 1. 26 48 3 − − 1. 06 9 −0 .7 24 83 −1 6. 29 22 −1 6. 24 5 −1 .2 05 7 0 0. 20 27 1 0. 80 14 7 1. 23 85 3 − − 1. 12 5 −0 .8 96 13 −2 0. 97 05 −2 0. 91 42 −1 .4 53 39 0 0. 51 29 2 0. 75 40 9 1. 21 08 − − 1. 18 5 −0 .9 94 8 −2 3. 79 91 −2 3. 73 41 −1 .2 49 43 0 0. 59 52 2 0. 70 35 1. 18 15 7 − − 1. 24 7 −1 .0 30 13 −2 5. 10 83 −2 5. 03 68 −0 .9 27 04 0 0. 59 73 9 0. 64 94 1. 15 07 7 − − 1. 31 3 −0 .9 91 93 −2 4. 66 64 −2 4. 59 28 −0 .6 07 39 0 0. 56 72 9 0. 59 14 7 1. 11 82 9 − − 1. 37 8 −0 .8 83 39 −2 2. 53 96 −2 2. 46 93 −0 .3 49 85 0 0. 52 27 8 0. 53 24 7 1. 08 57 7 − − 1. 44 7 −0 .7 12 96 −1 8. 96 3 −1 8. 90 16 −0 .1 50 64 0 0. 46 78 7 0. 46 93 1 1. 05 15 7 − − 1. 51 9 −0 .5 03 89 −1 4. 45 62 −1 4. 40 84 −0 .0 10 06 0 0. 40 46 5 0. 40 16 1 1. 01 56 2 − − 1. 59 5 −0 .2 91 07 −9 .7 31 04 −9 .6 99 13 0. 07 61 89 0 0. 33 39 9 0. 32 89 9 0. 97 78 3 − − 1. 67 5 −0 .1 12 41 −5 .4 99 74 −5 .4 82 77 0. 11 36 01 0 0. 25 62 8 0. 25 11 0. 93 80 9 − − ha and hoang: applying the capm model in identifying the electricity retail price in ho chi minh city, vietnam international journal of energy economics and policy | vol 7 • issue 2 • 2017 191 table 5: expected return for each generator at risk free rate 6% retail price v nd/kwh erg1 erg2 erg3 erg4 erg5 erg6 erg7 erg8 erg9 erg10 erg11 erg12 erg13 erg14 erg15 erg16 erg17 erg18 erg19 erevnhcmc 965 −0.58 −1.24 −0.44 0.04 0.03 0.07 0.04 −0.30 −0.17 −0.14 −0.16 −0.15 0.19 0.38 0.10 0.06 0.02 0.01 −0.02 −0.12 1.016 0.04 0.04 0.05 0.06 0.06 0.06 0.06 0.05 0.05 0.05 0.05 0.05 0.07 0.07 0.06 0.06 0.06 0.01 −0.02 0.05 1.069 −0.59 −1.11 −0.43 0.07 0.07 0.10 0.07 −0.32 −0.14 −0.11 −0.14 −0.13 0.61 0.78 0.12 0.06 0.05 0.01 −0.01 −0.05 1.125 −0.59 −1.10 −0.43 0.09 0.09 0.12 0.09 −0.32 −0.13 −0.10 −0.12 −0.12 0.87 1.05 0.13 0.06 0.03 0.01 −0.01 −0.02 1.185 −0.54 −0.95 −0.39 0.11 0.11 0.13 0.11 −0.29 −0.11 −0.08 −0.10 −0.09 1.06 1.23 0.13 0.06 0.02 0.02 −0.01 0.02 1.247 −0.46 −0.76 −0.33 0.12 0.12 0.14 0.12 −0.24 −0.08 −0.06 −0.07 −0.07 1.18 1.34 0.11 0.06 0.02 0.02 −0.01 0.06 1.313 −0.37 −0.55 −0.25 0.13 0.12 0.14 0.12 −0.18 −0.05 −0.03 −0.04 −0.04 1.21 1.34 0.09 0.06 0.03 0.02 −0.01 0.09 1.378 −0.27 −0.36 −0.18 0.12 0.12 0.13 0.12 −0.12 −0.02 0.00 −0.01 −0.01 1.15 1.25 0.08 0.06 0.03 0.03 −0.01 0.11 1.447 −0.17 −0.21 −0.11 0.11 0.11 0.12 0.11 −0.07 0.01 0.02 0.01 0.01 1.00 1.08 0.07 0.06 0.03 0.03 0.00 0.12 1.519 −0.09 −0.09 −0.04 0.10 0.10 0.10 0.10 −0.02 0.03 0.04 0.03 0.03 0.79 0.85 0.06 0.06 0.04 0.04 0.00 0.11 1.595 −0.02 −0.01 0.01 0.08 0.08 0.08 0.08 0.02 0.05 0.05 0.05 0.05 0.56 0.59 0.06 0.06 0.04 0.04 0.00 0.10 1.675 0.03 0.04 0.04 0.07 0.07 0.07 0.07 0.04 0.06 0.06 0.06 0.06 0.35 0.36 0.05 0.06 0.04 0.04 0.00 0.08 for the price at 1.447vnđ/kwh. the average rate of return is maximum. table 6: expected return for each generator at risk free rate 8% retail price vnd/kwh erg1 erg2 erg3 erg4 erg5 erg6 erg7 erg8 erg9 erg10 erg11 erg12 erg13 erg14 erg15 erg16 erg17 erg18 erg19 erevnhcmc 965 −0.55 −1.19 −0.40 0.07 0.07 0.10 0.07 −0.26 −0.14 −0.11 −0.13 −0.12 0.40 0.58 0.14 0.08 0.03 0.01 −0.02 −0.07 1.016 0.06 0.06 0.07 0.08 0.08 0.08 0.08 0.07 0.07 0.08 0.07 0.07 0.10 0.10 0.08 0.08 0.08 0.01 −0.02 0.07 1.125 −0.54 −1.03 −0.39 0.15 0.14 0.17 0.14 −0.25 −0.09 −0.07 −0.09 −0.08 1.31 1.49 0.18 0.08 0.04 0.02 −0.02 0.06 1.185 −0.49 −0.88 −0.34 0.17 0.17 0.18 0.17 −0.21 −0.07 −0.04 −0.06 −0.05 1.56 1.73 0.17 0.08 0.03 0.02 −0.01 0.11 1.247 −0.41 −0.68 −0.28 0.18 0.18 0.19 0.18 −0.16 −0.04 −0.02 −0.03 −0.03 1.70 1.86 0.15 0.08 0.03 0.03 −0.01 0.15 1.313 −0.31 −0.48 −0.20 0.18 0.18 0.19 0.18 −0.10 −0.01 0.01 0.00 0.00 1.73 1.86 0.13 0.08 0.03 0.03 −0.01 0.18 1.378 −0.22 −0.31 −0.13 0.18 0.17 0.18 0.17 −0.04 0.02 0.03 0.02 0.03 1.62 1.72 0.11 0.08 0.04 0.04 −0.01 0.19 1.447 −0.13 −0.16 −0.06 0.16 0.16 0.16 0.16 0.01 0.04 0.05 0.05 0.05 1.40 1.48 0.09 0.08 0.04 0.04 0.00 0.19 1.519 −0.05 −0.05 −0.01 0.14 0.13 0.14 0.14 0.05 0.06 0.07 0.06 0.06 1.10 1.15 0.08 0.08 0.05 0.05 0.00 0.17 1.595 0.01 0.02 0.04 0.12 0.11 0.11 0.11 0.07 0.07 0.08 0.07 0.07 0.78 0.81 0.07 0.08 0.05 0.05 0.00 0.14 1.675 0.05 0.06 0.06 0.10 0.09 0.09 0.09 0.08 0.08 0.08 0.08 0.08 0.48 0.49 0.07 0.08 0.06 0.06 0.00 0.12 * for the price at 1.378vnđ/kwh. the average rate of return is maximum. table 7: expected return for each generator at risk free rate 10% retail price vnd/kwh erg1 erg2 erg3 erg4 erg5 erg6 erg7 erg8 erg9 erg10 erg11 erg12 erg13 erg14 erg15 erg16 erg17 erg18 erg19 erevnhcmc 965 −0.51 −1.15 −0.37 0.11 0.11 0.13 0.11 −0.22 −0.11 −0.08 −0.10 −0.09 0.61 0.79 0.18 0.10 0.04 0.01 −0.03 −0.03 1.016 0.08 0.08 0.09 0.10 0.10 0.10 0.10 0.09 0.09 0.10 0.09 0.10 0.12 0.13 0.10 0.10 0.10 0.02 −0.03 0.09 1.069 −0.50 −0.99 −0.35 0.17 0.17 0.19 0.17 −0.21 −0.07 −0.04 −0.07 −0.06 1.30 1.47 0.21 0.10 0.08 0.02 −0.02 0.08 1.125 −0.49 −0.96 −0.34 0.20 0.20 0.22 0.20 −0.19 −0.06 −0.03 −0.05 −0.04 1.75 1.93 0.23 0.10 0.05 0.02 −0.02 0.14 1.185 −0.44 −0.80 −0.29 0.22 0.23 0.24 0.22 −0.13 −0.03 0.00 −0.02 −0.01 2.05 2.22 0.22 0.10 0.04 0.03 −0.02 0.20 1.247 −0.36 −0.61 −0.23 0.24 0.24 0.25 0.24 −0.08 0.00 0.02 0.01 0.01 2.23 2.38 0.19 0.10 0.04 0.04 −0.02 0.25 1.313 −0.26 −0.42 −0.16 0.24 0.24 0.24 0.24 −0.01 0.03 0.05 0.04 0.04 2.24 2.37 0.16 0.10 0.04 0.04 −0.01 0.27 1.378 −0.17 −0.25 −0.09 0.23 0.23 0.23 0.23 0.04 0.06 0.07 0.06 0.06 2.09 2.19 0.13 0.10 0.05 0.05 −0.01 0.28 1.447 −0.09 −0.11 −0.02 0.21 0.20 0.20 0.20 0.08 0.08 0.09 0.08 0.08 1.80 1.88 0.11 0.10 0.05 0.05 −0.01 0.26 1.519 −0.01 −0.02 0.03 0.18 0.17 0.17 0.17 0.11 0.09 0.10 0.09 0.09 1.41 1.46 0.10 0.10 0.06 0.06 0.00 0.23 1.595 0.04 0.05 0.06 0.15 0.14 0.14 0.14 0.12 0.10 0.10 0.10 0.10 0.99 1.02 0.09 0.10 0.07 0.07 0.00 0.19 1.675 0.08 0.08 0.09 0.12 0.12 0.12 0.12 0.12 0.10 0.10 0.10 0.10 0.61 0.62 0.09 0.10 0.07 0.07 0.01 0.15 *for the price at 1.378vnđ/kwh. the average rate of return is maximum. table 8: expected return for each generator at risk free rate 12% retail price vnd/kwh erg1 erg2 erg3 erg4 erg5 erg6 erg7 erg8 erg9 erg10 erg11 erg12 erg13 erg14 erg15 erg16 erg17 erg18 erg19 erevnhcmc 965 −0.48 −1.10 −0.34 0.14 0.14 0.17 0.14 −0.19 −0.08 −0.05 −0.07 −0.07 0.82 1.00 0.22 0.12 0.04 0.01 −0.03 0.02 1.016 0.10 0.10 0.11 0.12 0.12 0.12 0.12 0.11 0.12 0.12 0.11 0.12 0.15 0.15 0.12 0.12 0.12 0.02 −0.03 0.11 1.069 −0.46 −0.93 −0.31 0.21 0.21 0.23 0.21 −0.15 −0.04 −0.01 −0.03 −0.02 1.64 1.82 0.25 0.12 0.10 0.02 −0.03 0.15 1.185 −0.38 −0.73 −0.24 0.28 0.29 0.29 0.28 −0.06 −0.01 0.04 0.02 0.02 2.55 2.72 0.26 0.12 0.05 0.04 −0.02 0.29 1.247 −0.30 −0.54 −0.18 0.30 0.30 0.30 0.30 0.01 0.04 0.06 0.05 0.05 2.75 2.90 0.23 0.12 0.05 0.04 −0.02 0.34 1.313 −0.21 −0.35 −0.11 0.30 0.30 0.30 0.30 0.07 0.07 0.09 0.08 0.08 2.75 2.88 0.19 0.12 0.05 0.05 −0.01 0.37 1.447 −0.04 −0.07 0.02 0.25 0.25 0.25 0.25 0.16 0.11 0.12 0.11 0.12 2.20 2.27 0.14 0.12 0.06 0.06 −0.01 0.34 1.519 0.02 0.02 0.06 0.22 0.21 0.21 0.21 0.17 0.12 0.13 0.12 0.12 1.72 1.77 0.12 0.12 0.07 0.07 0.00 0.29 1.595 0.07 0.08 0.09 0.18 0.17 0.17 0.17 0.17 0.12 0.13 0.12 0.13 1.21 1.24 0.11 0.12 0.08 0.08 0.00 0.23 1.675 0.10 0.11 0.11 0.15 0.14 0.14 0.14 0.15 0.12 0.12 0.12 0.12 0.74 0.75 0.11 0.12 0.09 0.09 0.01 0.18 *for the price at 1.313vnđ/kwh. the average rate of return is maximum. ha and hoang: applying the capm model in identifying the electricity retail price in ho chi minh city, vietnam international journal of energy economics and policy | vol 7 • issue 2 • 2017192 objective for this study. capm which is used for determining the expected return from the 21 generators, that evnhcmc has invested in. the necessary data which is needed for using in capm is the mcp for each hour. the mcp varies due to the demand and power supply for hcmc, while the fixed price is applied for retail price of evnhcmc. fortunately, vietnam has operated the cgm that is generating mcp for this study. the study suggests the model of calculate the electricity retail price so that government has more tools to adjust the electricity prices in electricity market, and recommends an electricity retail price list of 12 levels, with the minimum sale price of 965 vnd/kwh and maximum sale price of 1675 vnd/kwh. for evnhcmc, the retco, the risk from mcp in electricity market has to be considered and added to the retail price thanks to applying capm. as the result from capm, erav may to fix the retail price at 1313 vnd/kwh for evnhcmc gaining the highest return. for the meaning of β: at the price of 965vnd/kwh, g19 (unit of ham thuan hydropower h2) gains the highest β at 1.29. that means if the market returns increases 1 times then profit of g19 increases 1.29 times. meanwhile, at the price of 965 vnd/kwh, g13 (unit of thermal power gt5 nhon trach 2) gains the smallest β at −25.11. that means if the market profit increases 1 times then g13 profit decreases 25.11 times. conclusion, if β > 0, then the expected profit of units has the same direction as the market returns. if β < 0, then the expected profit of units has the opposite direction of the market returns. β = 0, the expected rate of return of generator will be risk-free rate (in case of unit g16). in this study, the price of 1016 vnd/kwh makes the β equal 0. regarding the relationship between β, mcp and retail price: the higher mcp, the higher profit for generators, the lower profit for evnhcmc. the higher retail price, the higher profit for evnhcmc, still the profit for generator unchanged. β of generators is correlated with mcp and inversely correlated with retail prices. for the expected rate of return of evnhcmc: the expected rate of return of evnhcmc varies from −12% to 11.7%. sensitivity analysis shows that the highest rate of return is 36.5% at 1313 vnd/ kwh with rf = 12%. in scenario with rf = 12% or over, the expected rate of return of evnhcmc always peaked at 1313 vnd/kwh which is the average cost to produce 1 kwh of electricity. 5.2. recommendations recommendations for the future work are suggested as follows: there are only 1464 h considered as the time length in this study. thus, the future study should be considered more hour period in order to generate more accurate result. in this study, the mcp is generated with the auction approach. in reality, evn has the software to stimulate all the process to generating the spot prices. to approach this software is expected to have more concrete results. study on other prices and charges that make up retail prices such as wholesale price, transmission and distribution charge, etc. references đàm, x.h. (2012), bỏ bù chéo giá điện: các hệ quả và giải pháp khắc phục trong dự thảo luật sửa đổi bổ sung một số điều của luật điện lực. hull, j.c. (2003), options, futures, and other derivatives. singapore: pearson education. karandikar, r.g., khaparde, s.a., kulkarni, s.v. (2007), quantifying price risk of electricity retailer based on capm and raroc methodology. electrical power and energy systems, 29, 803-809. ngô, t.l. (2012), chính sách điều tiết giá những hàng hóa quan trọng, thiết yếu và những kiến nghị. tham luận diễn đàn kinh tế mùa thu, 2012, 1-8. pasapong, g., charles, o.p.m. (2011), electricity retail price in competitive market using the risk-adjusted capital asset pricing model (capm): a case of thailand. pea-ait education cooperation project. p1-7. rothwell, g., gómez, t. (2003), electricty economics: regulation and deregulation. hoboken, nj: wiley-interscience. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. tx_1~at/tx_2~at international journal of energy economics and policy | vol 8 • issue 4 • 2018 13 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(4), 13-20. study of fuel oil supply and consumption in indonesia akhmad1*, amir2 1faculty of economics and business, university of muhammadiyah, makassar, indonesia, 2faculty of economics and business, university of muhammadiyah, makassar, indonesia. *email: akhmad09@yahoo.co.id abstract the consumption of fuel oil (bbm) in indonesia for the last 10 years is increasing along with the increase in economic growth and the number of population. the increase in fuel oil consumption is not accompanied with the increase in domestic oil production. the research aimed to find out factors influencing fuel oil supply and consumption and forecasting the supply and consumption in indonesia in the future. the research used time series data for 1997-2016. the research used econometrics model with simultaneous equation system. the model of simultaneous equation system built was consisted of 11 structural equations and 2 identic equations. the result of analysis indicated that factors influencing the supply of fuel oil were world oil price and the supply of oil in the previous year. in addition, factors influencing the consumption of fuel oil were fuel oil price and fuel oil consumption in the previous year. the result of forecasting indicates that fuel oil consumption in indonesia up to 2025 is increasing in average of 4.07% for gasoline, 2.99% for kerosene, and 3.19% for diesel per year. in addition, the price of fuel oil in indonesia was estimated to increase in average of 3.76% for gasoline, 3.87% for kerosene, and 3.19% for diesel, whereas, import of fuel oil increased in average of 4.83% per year. keywords: time series, simultaneous equations, supply and consumption of fuel oil jel classifications: c32, q4, q47 1. introduction the consumption of energy in indonesia for the last 10 years indicates an increase in average of 7-8% per year along with the increase in population and better economic growth. the condition requires better energy availability to support the economic activities and social dynamics of the society. however, there are various challenges and obstacles to fulfill the need of energy, among others, crude oil production that tends to increase while the acceleration in renewable new energy development that is expected to become the new backbone of national energy is not maximal. the condition causes indonesia to be vulnerable to global energy market since some of the consumption, especially petroleum products, are fulfilled through import (the ministry of energy and mineral resources, 2016). indonesia as an archipelago state and has a large number of population needs high movement/transportation. transportation sector service is the most important basic need for the society to support the fulfillment of the basic needs, such as clothing, food, and house. the role of transportation is closely related to the need of energy, 90% of the energy is in form of fuel oil (bbm). national energy board (2016) stated that the consumption of fuel oil in transportation sector in indonesia tends to grow by 8.6% per year, higher than the household consumption of 3.7%, power plants of 4.6% and smaller than the growth in industrial consumption of 9.1%. the reserve of fossil-based fuel oil, which is the non-renewable resource, is very limited of 4.7 billion barrel. the reserve is sufficient for consumption for 15 years if no new oil wells found through exploration and no energy diversification conducted. consumption of fuel oil energy for transportation sector is dominated by road transportation, which is 88% of total fuel oil consumption in transportation sector, particularly diesel and gasoline. along with the increase in the number of motor vehicles, better quality fuel oil is needed both fossil-based and renewable non-fossil based fuel, which is biofuel or environmentally friendly bioenergy. the growth of transportation sector is estimated to be high in the future. the number of vehicles is increasing every year (6-8%), especially motor bike and car as well as the growth of travel, especially travel by private vehicles causing the high rate akhmad and amir: study of fuel oil supply and consumption in indonesia international journal of energy economics and policy | vol 8 • issue 4 • 201814 of growth in fuel oil demand (the secretary of national energy board, 2016). with the diminishing reserve of fossil energy and the increase in energy consumption, it threatens the economic development of indonesia. therefore, various efforts need to be conducted to encourage the use of efficient energies along with an intensive search of new fossil energy resources and the development of renewable alternative energy resources (elinur, 2010). the main cause of inefficiency in energy utilization is cheap energy policy by the government of indonesia. tambunan (2006) stated that cheap energy policy through large subsidies has negative impacts. first, the high dependency on crude oil energy resources. low price is disincentives for energy diversification as well as conservation effort (elinur, 2012). second, fuel oil subsidy in apbn (state budget) threatens the fiscal sustainability of the government (akhmad, 2014). third, the less optimum of other energy resources utilization, such as natural gas and coal that have larger reserve than crude oil or new and renewable energies (kuncahyo et al., 2013). fourth, the rampant of fuel oil smuggling abroad causing higher demand level than the actual need. fifth, the rampant of mixing fuel oil activity that harm the state and general consumers. sixth, price signal distorts investment feasibility in the downstream sectors of oil and gas. other indicators indicating the waste in energy utilization in indonesia is energy intensity. energy intensity is a comparison between the amount of energy consumption to pdb (gross domestic product) per capita. the more efficient a country is, the smaller its intensity. to date, energy subsidies applied by the government causes energy waste since the use is less optimal. it is reflected in the relatively high energy intensity, which is 482 toe (ton-oil-equivalent) per a million usd. it means, to produce a value added (gross domestic product) of usd 1 million, indonesia would need energy of 482 toe. meanwhile, malaysia only need 439 toe/million usd and the average intensity of 100 energy of developed countries joined in the organization for economic co-operation and development (oecd) is only 164 toe/million usd. it indicates a large potential of energy savings in indonesia (bureau of statistics, 2015). factors influencing fuel oil consumption are: the length of road (xiao et al., 2007), the number of vehicles (kenworthy and laube, 2002; fwa, 2005), the behavior of road users (directorate general of land transportation, 2008), vehicle speed (caroline, 2007; nanang et al., 2008; rodrigue, 2004; taylor and linsay, 2004), and type of machine (taylor and linsay, 2004). in addition, fuel oil consumption is also influenced by the number of population, land use, and population density (kenworthy and laube, 2002; verameth et al., 2007). hassan et al. (2018) found that industrial growth in sub-saharan africa is highly depended on the supply of energy thus policies on energy preservation effort give negative impact on industrial growth. fuel oil availability issue for indonesia is very important to fulfill the need of the society and to improve economic growth. therefore, government needs to maintain balance between economic growth and the availability of fuel oil as one of requirements to achieve developed and sustainable economic development. thus, it is interesting to conduct a study to analyze the supply and consumption of fuel oil in indonesia. therefore, the research aimed to find out factors influencing the supply and consumption of bbm in indonesia and forecast the supply and consumption of bbm in indonesia in the future. 2. data and research method the research used time series data in the period of 1997-2016. data used consisted of data of fuel oil supply, fuel oil price, fuel oil consumption and government revenue and expenditures. data was obtained from bureau of statistics, the ministry of energy and mineral resources, the ministry of finance, and central bank of indonesia. the research used econometrics model with simultaneous equation system. the model of simultaneous equation system built consisted of 13 equations where 11 equations were structural equations and 2 equations were identity equations. the model was divided into four blocks, namely: (1) block of fuel oil supply, (2) block of fuel oil price, (3) block of fuel oil consumption, and (4) block of government revenue and expenditures. 2.1. block of bbm supply equation 2.1.1. domestic fuel oil production domestic fuel oil production was influenced by the world oil price, increase in crude oil input for oil refineries, the capacity of oil refineries, and the domestic fuel oil production in the previous year. the equation of domestic fuel oil production was formulated as follows: bbmdt = a0+a1poilwt+a2timtt+a3kkmt+a4lpbbmdt-1+u1 (1) the sign of expected estimated parameter: a1, a2, a3 >0 and 0<a4<1. 2.1.2. import of fuel oil import of fuel oil was influenced by the final consumption of fuel oil, the number of land transportation, the domestic fuel oil production, rupiah exchange rate, and import of fuel oil in the previous year. the equation of import of fuel oil was formulated as follows: ibbmt = b0+b1 cbbmt+b2jtdit+b3 pbbmdt+b4ntrpt +b5libbmt-1+u2 (2) the sign of expected estimated parameter: b1, b2, >0; b3,b4<0 and 0<b5<1. 2.1.3. fuel oil supply fuel oil supply is the domestic fuel oil production added with import of fuel oil and subtracted by export of fuel oil. the formula of fuel oil supply as follows: ybbmt = pbbmdt+ibbmt−xbbmt (3) akhmad and amir: study of fuel oil supply and consumption in indonesia international journal of energy economics and policy | vol 8 • issue 4 • 2018 15 2.2. block of fuel oil price 2.2.1. the equation of domestic crude oil price the price of domestic crude oil was influenced by the final consumption of fuel oil, fuel oil supply, government expenditure for fuel oil subsidies, world crude oil price, and domestic crude oil price in the previous year. the equation of domestic crude oil price is formulated as follows: r p b b m t t = c 0 + c 1 c b b m t + c 2 y b b m t + c 3 g s b b m t +c4poilwt+c5lrpbbmtt-1+u3 (4) the sign of expected estimated parameter: c1, c4>0; c2, c3<0, and 0<c5<1. 2.2.2. the equation of gasoline price the price of gasoline was influenced by gasoline consumption, fuel oil supply, government expenditure for fuel oil subsidies, world crude oil price, and price of gasoline in the previous year. the equation of gasoline price is formulated as follows: rpbent = d0+d1cbent+d2ybbmt+d3gsbbmt+d4poilwt+d5 lrpbent-1+u4 (5) the sign of expected estimated parameter: d1, d4>0; d2, d3<0, and 0<d5<1. 2.2.3. the equation of kerosene price kerosene price was influenced by kerosene consumption, fuel oil supply, government expenditure for fuel oil subsidies, world crude oil price, and kerosene price in the previous year. the equation of kerosene price is formulated as follows: rpmtt = e0+e1cmtt+e2ybbmt+e3gsbbmt+e4poilwt+e5lrp mtt-1+u5 (6) the sign of expected estimated parameter: e1, e4>0; e2, e3<0, and 0<e5<1. 2.2.4. the equation of solar oil price solar oil price was influenced by the consumption of solar oil, fuel oilsupply, government expenditure for fuel oil subsidies, world crude oil price, and solar oil price in the previous year. the equation of solar oil price is formulated as follows: rpdst = f0+f1cdst+f2ybbmt+f3gsbbmt+f4lpoilwt+f5lrp dst-1+u6 (7) the sign of expected estimated parameter: f1, f4>0; f2, f3<0, and 0<f5<1. 2.3. block of bbm consumption equation 2.3.1. gasoline consumption gasoline consumption was influenced by gasoline price, gross domestic product, fuel oil supply and gasoline consumption in the previous year. the equation of gasoline consumption is formulated as follows: cbent = g0+g1rpbent+g2pdbt+g3ybbmt+g4lcbent-1+u7 (8) the sign of expected estimated parameter: g1<0; g2, g3>0 and 0<g4<1. 2.3.2. kerosene consumption kerosene consumption was influenced by kerosene price, gross domestic product, fuel oil supply, and kerosene consumption in the previous year. the equation of kerosene consumption is formulated as follows: cmtt = n0+h1rpmtt+h2pdbt+h3ybbmt+h4lcmtt-1+u8 (9) the sign of expected estimated parameter: h1<0; h2, h3>0 and 0<h4<1. 2.3.3. solar oil consumption solar oil consumption was influenced by solar oil price, gross domestic product, fuel oil supply, and solar oil consumption in the previous year. the equation of solar consumption is formulated as follows: cdst = i0+i1rpdst+i2pdbt+i3ybbmt+i4lcdst-1+u9 (10) the sign of expected estimated parameter: i1<0; i2, i3>and 0<i4<1. 2.4. block of government revenues and expenditures 2.4.1. government revenues government revenue was influenced by domestic fuel oil production, import of fuel oil, tax, government revenues in the previous year. the equation of government revenue is formulated as follows: trgt = j0+j1pbbmdt+j2tibbmt+j3taxt+j4ltrgt+u10 (11) the sign of expected estimated parameter: j1, j2, j3>0 dan 0<j4 1. 2.4.2. government expenditures the equation of government expenditure was formed in identity equation. the equation of government expenditure was the sum of non-subsidy government expenditure added with government expenditure for fuel oil subsidies and government expenditure of non-subsidy fuel oil, and it is formulated as follows: tget = gnst+gsbbmt+gsnbbmt (12) 2.4.3. expenditure of fuel oil subsidies expenditure of fuel oil subsidies was influenced by government revenue, rupiah exchange rate against the usd in the previous year, final consumption of fuel oil and expenditure of fuel oil subsidies in the previous year. the equation of expenditure of bbm subsidy is formulated as follows: gsbbmt = k0+k1tget+k2lntrpt-1+k3cbbmt+k4lgsbbmt-1+u11 (13) the sign of expected estimated parameter: k1, k3>0; k2<0 dan 0<k4<1. akhmad and amir: study of fuel oil supply and consumption in indonesia international journal of energy economics and policy | vol 8 • issue 4 • 201816 2.5. identification of model and model estimation method the model of fuel oil supply and consumption in indonesia developed in the research was a simultaneous equation model where the behavior of its variable was determined simultaneously. the identification of model was determined based on order condition as a requirement of necessity and rank condition as a requirement of sufficiency. according to koutsoyiannis (1977), juanda (2009), the formulation of identification of structural equation model based on order condition is determined by: (k−m)>(g−1) (14) where: k: total variables in the model, which is endogenous and predetermined variables m: the number of endogenous and exogenous variables included in one certain equation in a model. g: total equation in a model, which is the number of endogenous variables in a model. based on the order condition, if: (k-m)>(g-1): the equation is stated as over identified (k-m)=(g-1): the equation is stated as exactly identified (k-m)<(g-1): the equation is stated as unidentified. the result of identification for each structural equation should be exactly identified or over identified. therefore, due to the simultaneity the parameter estimators with ordinary least square method were inconsistent and bias thus alternative estimation method was needed (juanda, 2009). in this research, model estimation method used was 2sls (two stage least square) since the method is suitable for over identified simultaneous equation and it could be used in a relatively small number of sample and it is insensitive to model modification (re-specification), both for structural analysis and simulation and forecasting analysis. data processing was conducted using computer software program of sas version 9.1. 2.6. model simulation and forecasting after model was validated and fulfilled the statistic criteria, the model could be used as a basic model of simulation and forecasting. some scenarios of simulation to be conducted in the study were: (1) an increase in world oil price by 10%, (2) a decrease in fuel oil subsidy expenditures by 20%, (3) the combination of an increase in world oil price by 10% and a decrease in bbm subsidy expenditure by 20%. method used in the forecasting was stepwise auto-regression (stepar) method, which is the combination of time trend model and auto-regressive model. stepwise auto-regression method is a forecasting method that firstly conducts forecasting on exogenous variables using linear trend. after the values of exogenous variables are obtained, forecasting on the development of endogenous variables was conducted using energy consumption and supply model in indonesia economy that has been built. 3. research results model specification used in the research had been modified several times since there were found several estimation results that inconsistent to the theory and several parameter estimations that insignificant. in the end, a model was obtained with result performance of parameter estimation that was representative to describe the phenomenon of fuel oil supply and consumption in indonesia. model estimation using 2sls (two stage least square) method resulted factors influencing the endogenous variables in the model, where there were 11 structural equations from 4 blocks and it showed good result as a whole. 3.1. result of estimation of fuel oil supply model the result of model estimation of fuel oil production (table 1) indicates that: world oil price had negative and significant influence on domestic fuel oil production. it indicates that if world oil price increases the domestic fuel oil production will decrease. in addition, the fuel oil production in the previous year had positive and significant influence on domestic fuel oil production. variable of the addition of crude oil input for refineries and the capacity of oil refineries had positive but insignificant influence. the value of elasticity of domestic fuel oil production on world oil price was 0.1859. it means that the domestic fuel oil production is irresponsive to world oil price. if world oil price increases by 1% the domestic fuel oil production will decrease by 0.1859%, ceteris paribus. the result of model estimation on import of fuel oil obtained that fuel oil consumption and import of fuel oil in the previous year had positive and significant influence on import of fuel oil. meanwhile, domestic fuel oil production and rupiah exchange rate against usd had negative and significant influence on import of fuel oil. the elasticity of fuel oil consumption to import of fuel oil was 0.2120. it means that the import of fuel oil was irresponsive to fuel oil consumption. if the consumption of fuel oil increases by 1% the import of fuel oil will increase by 0.2120%. the elasticity of fuel oil production and rupiah exchange rate to import of fuel oil was −0.3413 and −0.3019, respectively. it means that fuel oil production and rupiah exchange rate were irresponsive to import of fuel oil. if fuel oil production and rupiah exchange rate in the previous year increases by 1% the import of fuel oil will decrease by 0.3413% and 0.3019%, respectively. 3.2. result of estimation of fuel oil price model the result of model estimation on domestic crude oil price obtained that: domestic crude oil price was positively and significantly influenced by fuel oil subsidies, world crude oil price and domestic crude oil price in the previous year, whereas fuel oil consumption and fuel oil supply had positive but insignificant influence. the result of elasticity calculation indicates that all variables were irresponsive to domestic crude oil price. the result of model estimation on gasoline price obtained that domestic gasoline price was negatively and significantly influenced by supply of fuel oil and positively and significantly influenced by government fuel oil subsidies and gasoline price akhmad and amir: study of fuel oil supply and consumption in indonesia international journal of energy economics and policy | vol 8 • issue 4 • 2018 17 in the previous year, whereas world oil price had positive but insignificant influence. moreover, final consumption of fuel oil had negative but insignificant influence. the result of elasticity calculation indicates that all variables were irresponsive to domestic gasoline price. the result of model estimation on kerosene price obtained that domestic kerosene price was positively and significantly influenced by kerosene price in the previous year; whereas world oil price and fuel oil subsidies had positive but insignificant influence. in addition, final consumption of kerosene and supply of fuel oil had positive but insignificant influence. the result of elasticity calculation indicates that all variables were irresponsive to domestic kerosene price (table 2). the result of model estimation on diesel price obtained that domestic diesel price was positively and significantly influenced by diesel price in the previous year. whereas, government fuel oil subsidies had negative and significant influence. in addition, world oil price had positive but insignificant influence. further, final consumption of diesel and supply of fuel oil had negative but insignificant influence. the result of elasticity calculation indicates that all variables were irresponsive to domestic diesel price. 3.3. result of estimation of fuel oil consumption model result of model estimation on gasoline consumption obtained that gasoline consumption was positively and significantly influenced by gasoline consumption in the previous year and negatively and significantly influenced by gasoline price. in addition, gross domestic product, supply of fuel oil had positive but insignificant table 1: results of estimation equation of fuel oil supply 1. equation of domestic fuel production (pbbmd) variables estimates p>(t) elasticity variable name f value r2 intercept 271074.5 0.0251 intercept 32.09 0.8004 poilw −343.5142 0.0345 −0.1859 world oil prices timt 0.045999 0.4917 0.4143 increase in crude oil inputs for refineries kkm 1.697810 0.3011 0.3730 refinery capacity lpbbmd 0.451925 <0.0001 domestic fuel production the previous year 2. equation of import of fuel oil (ibbm) intercept −50506.71 0.2206 intercept 99.11 0.8770 cbbm 0.320033 0.1120 0.2120 final consumption of fuel oil jtdi 0.24649 0.0304 0.2706 number of land transportation pbbmd −0.54619 0.0304 −0.3413 domestic fuel production ntrp −0.012028 0.5815 −0.3019 rupiah exchange rate against usd libbm 0.831304 <0.0001 import of fuel oil the previous year table 2: estimation results of fuel oil price 1. the equation of domestic crude oil price (rpbbmt) variables estimates p>(t) elasticity variable name f value r2 intercept 63894.889 0.6038 intercept 832.09 0.9604 cbbm −0.075999 0.7917 −0.1143 fuel oil consumption ybbm −0.697810 0.4211 −0.1430 supply of fuel oil gsbbm −0.547832 0.0211 −0.3142 government expenditure on fuel subsidies poilw 0.604110 0.0111 0.4941 world oil prices lrpbbmt 0.151925 0.0232 the price of domestic crude oil the previous year 2. gasoline price equations (rpben) intercept −12506.19 0.4406 intercept 68.45 0.7964 cben −0.432033 0.6220 −0.1120 consumption of gasoline ybbm −0.134649 0.0304 −0.3206 supply of fuel oil gsbbm −0.326649 0.0211 −0.3201 government expenditure on fuel subsidies poilw 0.432028 0.9815 0.1309 world oil prices lrpben 0.831304 <0.0001 gasoline consumption the previous year 3. the equalization of kerosene price (rpmt) intercept 950619.7 0.2206 intercept 55.43 0.7775 cmt −0.241033 0.7321 −0.0132 kerosene consumption ybbm −0.186641 0.4404 −0.2706 supply of fuel oil gsbbm −0.124321 0.2132 −0.1231 government expenditure on fuel subsidies poilw 0.000028 0.3215 0.2214 world oil prices lrpmt 0.442301 <.0001 kerosene price of previous year 4. solar oil price equation (rpds) intercept 66506.99 0.2206 intercept 31.54 0.6978 cds −0.773044 0.7120 −0.0220 consumption of diesel oil ybbm −0.996649 0.1704 −0.1806 supply of fuel oil gsbbm −0.543650 0.0121 −0.3214 government expenditure on fuel subsidies poilw 0.000028 0.2015 0.0019 world oil prices lrpds 0.831304 <0.0001 diesel oil prices the previous year akhmad and amir: study of fuel oil supply and consumption in indonesia international journal of energy economics and policy | vol 8 • issue 4 • 201818 influence. the result of elasticity calculation indicates that all variables were irresponsive to domestic gasoline consumption (table 3). the result of model estimation on kerosene consumption obtained that kerosene consumption was positively and significantly influenced by kerosene consumption in the previous year, whereas, gross domestic product, supply of fuel oil had positive but insignificant influence. in addition, kerosene price had negative but insignificant influence. the result of elasticity calculation indicates that all variables were irresponsive to domestic kerosene consumption. the result of model estimation on diesel consumption obtained that diesel consumption was positively and significantly influenced by diesel consumption in the previous year and significantly and negatively influenced by diesel price. in addition, gross domestic product and supply of fuel oil had positive but insignificant influence. the result of elasticity calculation indicates that all variables were irresponsive to domestic diesel consumption. 3.4. result of estimation of government revenue and expenditure model the result of model estimation on government revenue parameters obtained that government revenue was positively and significantly influenced by total tax and government revenue in the previous year. whereas, fuel oil production and total import of fuel oil had positive but insignificant influence on government revenue. the result of elasticity calculation indicates that all variables were irresponsive to government revenue (table 4). the result of model estimation on government fuel oil subsidies obtained that government fuel oil subsidies was positively and significantly influenced by government expenditures on fuel subsidies in the previous year. whereas, total government expenditures, rupiah exchange rate in the previous year and fuel oil consumption had positive but insignificant influence on government fuel subsidies. the result of elasticity calculation indicates that all variables were irresponsive to government fuel subsidies. 3.5. policy simulation policies applied by the government as well as the changes in external factors occurred could bring positive and negative impacts table 3: estimation results of oil fuel consumption 1. gasoline consumption equation (cben) variables estimates p>(t) elasticity variable name f value r2 intercept −65434.86 0.0238 intercept 111.09 0.8324 rpben −0.324388 0.0017 0.1414 the price of gasoline pdb 0.986710 0.2211 0.1733 gross domestic product ybbm 0.321340 0.3214 0.2132 supply of fuel oil lcben 0.851925 <0.0001 gasoline consumption the previous year 2. kerosene consumption equation (cmt) intercept 28894.88 0.0908 intercept 13.09 0.5904 rpmt 0.332421 0.7917 0.0143 the price of kerosene pdb 0.123010 0.4021 0.1420 gross domestic product ybbm 0.231431 0.2132 0.3212 supply of fuel oil lcmt 0.851925 <0.0001 kerosene consumption the previous year 3. solar oil consumption equation (cds) intercept 804321,82 0.1038 intercept 79.09 0.8804 rpds 0.321229 0.0417 0.0143 price of diesel oil pdb 0.543211 0.3211 0.1730 gross domestic product ybbm 0.321321 0.2101 0.2311 supply of fuel oil lcds 0.851925 <0.0001 diesel fuel consumption the previous year table 4: result of estimated government revenue and expenditure 1. government revenue equation (trg) variables estimates p>(t) elasticity variable name f value r2 intercept 8544.88 0.4532 intercept 17.09 0.6604 pbbmd 0.321432 0.3917 0.2143 domestic fuel production tibbm 0.327810 0.3221 0.1730 total imports of fuel oil tax 2.043221 0.0213 0.0221 tax ltrg 0.432543 <0.0001 government revenue the previous year 2. spending equation fuel subsidies alone government (gsbbm) intercept 72194.93 0.1038 intercept 244.54 0.8704 tge 0.231210 0.7917 0.0143 total government expenditures lntrpt−1 0.321431 0.1611 0.1921 rupiah exchange rate against usd previous year cbbm 0.123212 0.1205 0.1120 oil fuel consumption lgsbbm 0.851925 <0.0001 government expenditure on fuel subsidy the previous year akhmad and amir: study of fuel oil supply and consumption in indonesia international journal of energy economics and policy | vol 8 • issue 4 • 2018 19 on every endogenous variables included in a simultaneous equation system. therefore, simulation conducted in the research consisted of: (1) a decrease in the fuel oil subsidies by 20%; (2) an increase in world oil price by 10%; and (3) the combination of a decrease in fuel oil subsidies by 20% and an increase in world oil price by 10%. the result of simulation is displayed in table 5. the result of the first simulation indicates that if the government decreases the fuel subsidies by 20%, the price of gasoline, kerosene and diesel would increase above 2%, in average, whereas the consumption of gasoline, kerosene, and diesel decreases by 0.02%, in average. further, the result of the second simulation indicates that if the world oil price increases by 10%, the price of gasoline, kerosene and diesel increases by 0.5%, in average, whereas, domestic fuel oil consumption only decreases by 0.02%. further, the result of the third simulation, which was the combination of a decrease in fuel oil subsidies by 20% and an increase in world oil price by 10%, causes the price of gasoline, diesel, and kerosene increases by 2.5%, in average, whereas consumption of gasoline, diesel, and kerosene decreases by 0.03%. 3.6. forecasting fuel oil consumption and supply in indonesia for period of 2018-2025 forecasting fuel oil consumption, supply and price in indonesia economy needed to be conducted to obtain an illustration about the future condition thus it can be used in economic-energy planning and development in indonesia. forecasting was conducted from 2018 to 2025. the limit of forecasting in 2025 was referred to the blue print of energy development in indonesia that has been set up to 2025. the result of forecasting indicates that fuel oil consumption in indonesia up to 2025 will increase by 3.91%, 2.99%, and 3.81% per year, for gasoline, kerosene, and diesel, respectively. moreover, the price of fuel oil in indonesia was estimated to increase by 2.45%, 1.58%, and 2.09% per year for gasoline, kerosene and diesel, respectively. whereas, import of fuel oil increases by 5.49%, in average (table 6). 4. conclusion and policy implications the result of model estimation obtained that factors influencing the supply of fuel oil were world oil price and fuel oil supply in the previous year. factors influencing the price of fuel oil were fuel oil consumption and world oil price. whereas, factors influencing fuel oil consumption were fuel oil price and fuel oil consumption in the previous year. the result of simulation indicates that if the government increases the fuel oil subsidies by 20%, the price of gasoline, kerosene table 5: the result of simulation variables basic value change (%) simulation 1 simulation 2 simulation 3 domestic fuel production 3085605,4 0,001 0,005 0,005 import of fuel oil 1262374,2 −0,003 −0.095 0,096 supply of fuel oil 3245981,15 −0,016 −0,005 −0,018 domestic crude oil price 239580,6 0,303 0,589 0,696 gasoline price 60762,21 2,068 0,561 2,403 kerosene price 14354,21 2,301 0,504 2,505 price of diesel oil 27424,23 2,409 0,604 2,724 gasoline consumption 4311867,55 −0,021 −0,018 −0,034 consumption of kerosene 562027,8 −0,026 −0,014 −0,034 consumption of diesel oil 249839,35 −0,021 −0,025 −0,039 government revenue 9636651,3 −0,228 −0,103 −0,313 government expenditures 7809321,73 −0,204 1,102 −1,202 expenditure subsidies on fuel oil 1169541,21 −20,00 0,127 −20,00 table 6: results of forecasting pricing and consumption of indonesian fuel variables name unit 2018 2025 growth (%) domestic fuel production thousand barrels 266.237,87 273.235,73 0,38 import of fuel oil thousand barrels 225.735,58 322.546,03 5,49 supply of fuel oil thousand barrels 491.973,45 595.781,76 3,01 domestic crude oil price rupiah./barrels 266.719,40 336.732,32 3,75 gasoline price rupiah/barrels 989.278,75 1.159.278,90 2,45 kerosene price rupiah./barrels 859.260,90 954.460,75 1,58 price of solar oil rp./barrels 957.260,40 1.097.268,55 2,09 gasoline consumption thousand barrels 401.867,55 511.888,50 3,91 consumption of kerosene thousand barrels 62.027,80 75.027,80 2,99 consumption of solar oil thousand barrels 149.839,35 189.839,75 3,81 government revenue billion rupiah 956.366,30 1.004.566,50 0,72 government expenditures billion rupiah 977.366,20 1.017.367,40 0,58 expenditure subsidies on fuel oil billion rupiah 369.541,21 377.540,35 0,31 akhmad and amir: study of fuel oil supply and consumption in indonesia international journal of energy economics and policy | vol 8 • issue 4 • 201820 and diesel increases above 2%, whereas the consumption of gasoline, kerosene and diesel decreases about 0.02%, in average. further, the result of simulation indicates that if the price of world oil price increases by 10%, the price of gasoline, kerosene and diesel increases by 0.5%, in average, whereas the domestic fuel oil consumption decreases by 0.02%. the result of the third simulation, which was the combination of a decrease in fuel oil subsidies by 20% and an increase in world oil price by 10%, caused the price of gasoline, diesel, and kerosene increases by 2.5%, in average, whereas consumption of gasoline, diesel, and kerosene decreases by 0.03%. the result of forecasting indicates that fuel oil consumption in indonesia up to 2025 increases by 4.07%, 2.99%, and 3.19% per year, for gasoline, kerosene, and diesel, respectively. moreover, the price of fuel oil in indonesia was estimated to increase by 3.76%, 3.87%, and 3.19% per year for gasoline, kerosene and diesel, respectively. whereas, import of fuel oil will increase by 4.83%, in average. as time goes by, fuel oil consumption experiences an increase due to the increase in the number of population and vehicles as well as the need of fuel oil in other sectors. on the supply side, the reserve of fossil energy, especially oil is decreasing thus the government need to increase investment in production and processing aspects as well as conversion in the use of fuel oil-based energy by industrial sectors to other types of energy. in addition, government needs to try to shift the use of non-renewable resource energy to renewable resource energy, such as the utilization of energy from water and wind, biofuel (biomass, biodiesel, biogas, and so on), and other sustainable energy resources. references akhmad. (2014), the impact of compensation for fuel price increase against poverty in indonesia. academica journal of political science and social sciences faculty of social, tadulako university, 6, 21-30. caroline, s. (2007), advanced traffic control system impacts on environmental quality in a large city in a developing country. journal of the eastern asia for tranportation studies, 7, 255-267. central bureau of statistics. (2015), indonesia energy statistics. jakarta: central bureau of statistics. directorate general of land transportation ministry of transportation. (2008), general planning of massar transportation development in java island. jakarta: directorate general of land transportation ministry of transportation. elinur, d.s., priyarsono, m., tambunan m., firdaus, m. (2010), development of energy consumption and supply in indonesian economy. indonesian journal of agricultural economics, 2(1), 237-250. elinur. (2012), analysis of consumption and supply of energy in indonesian economy. doctoral dissertation. graduate school, bogor agricultural university. fwa, t.f. (2005), sustainable urban transportation planning and development issue and chalenges for singapore. department of civil engineering of singapore. hassan, s., ismail, a.d., muhammad, r.d. (2018), energy consumption and manufacturing performance in sub-saharan africa: does income group matter? international journal of energy economics and policy, 8(1), 1-4. juanda, b. (2009), econometrics modeling and assumptions. bogor (id): pt penerbit ipb press. kenworthy, j., laube, f. (2002), urban transport patterns in a global sample of cities and their lingkages to transport infrastucture, landuse, economics and environment, 8, 5-19. koutsoyiannis, a. (1977), theory of econometrics: an introductory exposition of econometric methods. 2nd ed. london: the macmillan press ltd. kuncahyo, p., fathallah, a.z., semin, s. (2013), analysis of potential prediction of biodiesel raw materials as diesel fuel gas supplement in indonesia. journal of engineering pomits, 2(1), 1-10. ministry of energy and mineral resources. (2006), handbook of energy and economic statistic of indonesia. jakarta: center for data and information on energy and mineral resources. ministry energy and mineral resources. nanang, p.m., jacub, c., driejana, r., tamin, z. (2008), background for optimization of feul consumtion at congested network using hydrodynamic traffic theory. proceeding pstpt international simposium. national energy council. (2016), indonesia energy outlook 2016. jakarta: secretary general of the national energy council. rodrigue, j.p. (2004), transportation and the environment. usa: department of economics and geography hafstra university. secretariat of national energy council. (2016), outlook energy indonesia 2016. jakarta: secretariat of national energy council. tambunan, m. (2006), the second high cycle of world oil (energy) price crisis: challenges and option. washington, usa: global dialogue on natural resources. taylor, b., linsay, b. (2004), public attitudes to transport issue. finding from the british social attitudes surveys. verameth, v., miyamoto, k., rujopakam, v. (2007), an empirical study of land use/transport interaction in bangkok with operation model application. journal of the eastern asia society for transportation studies, 7, 1250-1265. xiao, l., daimon, h., marimoto, a., koike, h. (2017), a study and traffic behavior on high income people in asia developing countries. journal of the eastern asia society for transportation studies, 7, 1222-1235.  . international journal of energy economics and policy | vol 7 • issue 3 • 2017 95 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(3), 95-101. energy efficiency standards and labels for cold appliances in jordan alwiyah abd alfattah1, ahmad sakhrieh2,3*, ahmed al-ghandoor4 1department of mechanical engineering, the university of jordan, amman 11942, jordan, 2department of mechanical engineering, the university of jordan, amman 11942, jordan, 3department of mechanical and industrial engineering, american university of ras al khaimah, uae, 4department of industrial engineering, the hashemite university, zarqa, 13115, jordan. *email: ahmad.sakhrieh@aurak.ac.ae abstract in the last few years, jordan has experienced an expansion in the number of electrical appliances. in order to reduce energy consumption in the residential sector, jordan has to consider implementing minimum energy efficiency standards (mees) for electrical appliances in the coming years. this study provides background on the benefits of, and steps needed to support introduction of ees and labeling in jordan. furthermore, this study attempts to predict the amount of energy that will be saved in the residential sector by implementing mees for the cold electrical appliances (refrigerators and freezers). this study concentrates on cold electrical appliances because it was found that cold appliances are about 32.7% of total household electrical energy consumption in jordan. four scenarios for replacing the old appliances have been suggested and analyzed. it was found that the net saving from 2011 to 2020 will be approximately 4451.17 gwh. the associated co2 emission reduction during the 10 years is expected to reach 2221 (1000 ton). in addition, the reduction of customer bills will reach 320 million jd based on the worst scenario. keywords: energy efficiency, standard, appliances, jordan jel classification: q4 1. introduction the minimum energy efficiency standard (mees) is a tool for improving the energy efficiency of appliances and equipment. mees sets the minimum levels of energy efficiency which a product must meet to be sold in the jordanian marketplace. an energy efficiency label contains information which is attached to manufactured products indicating the product’s energy efficiency rating or estimated annual energy use in order to provide consumers with the necessary data to make an informed purchase. improved appliance efficiency is important for personal financial reasons e.g., lowering electricity consumption. also, improved efficiency is important for environmental reasons; because it reduces the consumption of electricity which in turn reduces air pollution by minimizing greenhouse gas emissions. lawrence berkeley national laboratory’s (lbnl) energy efficiency standards (ees) group has performed technical and economic analyses of refrigerator-freezer for the u.s. department of energy (doe) since 1979. these analyses formed the bases of the efficiency standards established by doe in 1989 and 1997 (which became effective in 1993 and 2001, respectively). refrigerator-freezers manufactured after july 2001 typically consume about 30% less energy than the maximum energy use allowed under the 1993 efficiency regulations (meyers et al., 2003). in 2008, lbnl completed an updated study of the historic and projected impacts of u.s. residential appliance standards. in 2005, doe confined its updated analysis for the two most popular product classes of refrigerators: top-mount refrigerator or freezers without through-the-door (ttd) features and sidemounted refrigerator-freezers with ttd feature. depending on assumptions regarding the impact that standards would have on market efficiency, amended standards at the 2005 energy star levels were estimated to yield between 2.4 to 3.4 quads from 2005 to 2030, with an associated economic impact to the u.s economy from a burden or cost of $1.2 billion to a benefit or saving of $3.3 billion. the energy independence and security alfattah, et al.: energy efficiency standards and labels for cold appliances in jordan international journal of energy economics and policy | vol 7 • issue 3 • 201796 act of 2007 (eisa, 2007), signed into law on december 19, 2007, required that the doe published a final rule no later than december 31, 2010, to determine whether to amend the standards in effect for refrigerators, refrigerator-freezers, and freezers manufactured on or after january 1, 2014 (meyers et al., 2004). the situation of the global refrigerator market was analyzed. it was found that germany offers the most lead market advantages in the refrigerator-producing industry, followed by korea and italy (cleff and rennings, 2016). brennan and palmer (2013) examine how an energy efficiency resource standards compares to policies oriented to meeting objectives, such as reducing greenhouse gas emissions, correcting for consumer error in energy efficiency investment, or reducing peak demand absent real-time prices. energy consumption of household appliances has become a target for energy efficiency improvements. electricity consumption increased significantly in the past few years. in 2010, total electricity consumption in jordan reached 12,843 gwh (ministry of energy and mineral resources, 2010), which is 7.42% higher than the preceding year. consumption of household appliance in this same year (5219 gwh) is about 41% of the total electricity consumption as shown below in figure 1. immediate benefits for energy saving can be realized by improving building efficiency and appliance standards, while solving the jordan’s energy challenges is a long-term proposition. in jordan, a study has been conducted in 2008 in order to analyze the historical, current and future fuel and electricity consumption within the residential sector. it was shown that the electricity and fuel demand were expected to rise approximately 100% and 23%, respectively within 10 years. consequently, associated greenhouse gas (ghg) emissions resulting from residential sector are predicted to rise by 59% for the same period (al-ghandoor et al., 2008). most households in jordan do not employ efficient appliances. the study demonstrated that significant potential energy and environmental benefits are a result of adopting high efficiency standards. the worst scenario expected the net saving of 61.4 million us$ per annum, will be achieved in 2018 (al-ghandoor et al., 2009). consequently, the associated co2 emissions reduction will be approximately 180 million ton per year. this study will present the potential of implementing mees on annual saving of electricity from cold appliances in the residential sector according to field survey conducted in amman and zarqa. the impact of implementing mees will investigate and expect significant impact in the future electricity consumption and associated ghg emission for residential sector in jordan. furthermore a cost-benefit analysis of implementing mees for these appliances and its environmental impact will be conducted. the calculation is based on the growth of energy consumption in residential sector during 2010-2020. 2. methodology the data necessary for the study are the electricity consumption and pollution values of jordanian household appliances. the historical electrical energy consumption for residential sector for the period 1985-2010, were used to predict future electricity consumption in the residential sector using polynomial curve fitting for 10 years period (2011-2020). the electrical energy data for the period 1985-2010 was obtained from the ministry of energy and mineral resources (memr, 2010). as shown in table 1, the electrical energy consumption in the residential sector has increased year by year along with the total electricity consumption of the country. co, co2 and nox values were obtained from the department of statistic (dos, 2009). these data are summarized in table 2. it is clear that all mentioned pollutants are increasing every year. a questionnaire was used to obtain the third part of the data, i.e. house appliances data. house owners provided estimates for typical usage of each household appliance. the sample size is step in the planning of the survey. the selected confidence interval was 95%, it means that if we repeat the survey 100 times we would expect the answer to any question to vary between the chosen margin of error in 95 out of 100 times. response percentage, the percentage of people who give a particular answer to a question in a survey, was 85% and the margin error value was ±5%. the size of the total population for the target sample of this study of amman and zarqa city population was 3,350,700. according to the numbers shown above, the calculated figure 1: electrical energy consumption percentage in jordan table 1: electrical energy consumption for residential sector in jordan year total energy consumption (gwh) residential energy consumption (gwh) 1985 2151 655 1990 3089 874 1995 4785 1411 2000 6133 1981 2005 8712 2989 2010 12843 5219 table 2: co, co2 and nox emissions in jordan fuels emission (ton metric 000/year) year co2 nox co 2006 20766.9 127.0 537.4 2007 20712.4 130.1 566.9 2008 21387.7 135.0 598.0 2009 21996.2 140.5 630.0 alfattah, et al.: energy efficiency standards and labels for cold appliances in jordan international journal of energy economics and policy | vol 7 • issue 3 • 2017 97 sample size was 196 surveys. the sample was taken randomly from different areas and house types (e.g. floor) and different social situations. the total collected surveys were 210. using matlab a fourth degree polynomial is found to be the best curve to predict electricity consumption in the future years with an adjusted r2 of 0.995. this curve has the formula: y=636.05+6.65x+10.77x2−0.72x3+0.02x4 (1) 3. analysis figure 2 shows the contribution of home appliances in energy consumption in amman and zarqa as obtained from the survey data. the used electrical energy inside houses depends on the lifestyle, the family size and the size and age of appliances. the energy consumption of the appliances in household is reflected directly on the electricity bill. the power consumption in wattage of different electrical appliances is used to compare the cost of running different appliances. the following formula was used to estimate the annual energy consumed by a specific appliances: aec=(appliance watt) (hour per day) (day per year) in order to evaluate electricity saving and the environmental impact resulting from implementing mees, four different scenarios are suggested for each appliance. • scenario 1: the market share for the new efficient models of class a, b and c will take a yearly constant of 25% and 75% for ordinary models. • scenario 2: the market share for the new efficient models of class a, b and c will take a yearly constant of 50% and 50% for ordinary models. • scenario 3: the market share for the new efficient models of class a, b and c will take a yearly constant of 75% and 25% for ordinary models. • scenario 4: the market share for the new efficient models of class a, b and c will take full share. the market share of the efficient models for classes a, b and c is divided to 40%, 40%, and 10%, respectively. table 3 represents the considered market share percentages for all classes for each scenario. each scenario will be applied for cold appliances electricity consumption in jordan. as a first step, energy consumption analysis was performed for different home appliances. it was found that refrigerators and freezers are in the first place. followed by lighting, air conditioning, space heating (electric heater), water cooling (cooler) and water heating (electric boiler) respectively. in this study we will apply mees for cold appliances (refrigerator, freezer) as they are the main electricity consumers in the residential sector in jordan. energy efficiency classes are divided to 5 main classes a, b, c, d and e. each class has an energy efficiency index or ratio. the index or ratio range is dependent on the appliance type. defining the class make it possible to compare energy consumption of energy efficient and normal appliances. energy efficiency classes and energy efficiency ratio or index are shown in table 4. energy saving can be calculated for each appliance according to the following formula: energy saving={(et−e0)+(e0*r)} cp*ms*sf (2) where, et is the predicted electricity consumption for year t, e0 is the electricity consumption for the base year (2010), cp is the contribution percentage, ms is the market share, sf is the safety factor and r is the replacement factor. the first part of equation (et−e0) represents the increase in the electricity consumption from the base year (2010) due to the increase of electrical appliances. the second part (e0*r) represents the consumed energy by the replaced appliances due to damaging, ending of the life cycle or increasing the concerning about mees effect on the electrical utility bill. the replacement factor assumed to be increased by 10% every year to reach 100% at the end of 2020 that is mean all figure 2: energy consumption of appliances from total residential energy consumption table 3: market share percentage for all classes for each scenario scenario efficient model (%) ordinary model (%) class a class b class c scenario 1 10 10 5 75 scenario 2 20 20 10 50 scenario 3 30 30 15 75 scenario 4 40 40 20 75 table 4: proposed energy efficiency classes and energy efficiency index/ratio value of cold appliances energy efficiency class energy efficiency index% (eei) for refrigerator/freezer a i<55 b 55<i<75 c 75<i<90 d 90<i<100 e 100<i<110 european commission, 2010 alfattah, et al.: energy efficiency standards and labels for cold appliances in jordan international journal of energy economics and policy | vol 7 • issue 3 • 201798 old appliances will be replaced by the new one have one of the three selected energy efficiency class a, b or c. the input data are summarized in table 5. the potential of saving amount indicated using saving factor. the saving factor value changed according to appliance efficiency class and appliance type. the saving factor formula for refrigerator and freezer is shown as follows: sf=(aecc−aeca)/aeca (3) where, aecc is the annual energy consumption for specific energy class, aeca is the annual energy consumption average in jordan. ( )n1aec aec / na = ∑ (4) where, n is the number of appliances. that is given from the collected data. the annual energy consumption for specific energy class can be determined from its related energy efficiency index [6]. aecc=(eei)(v) (5) where, aecs is the annual energy consumption standard, v is in the net internal volume of storage space in the cabinet, in l. the average volume for refrigerator according to surveyor is about 710 l. v=base area*high (6) implementing the minimum energy efficiency will not only affect electricity consumption but also environmental impact (e.g. gaseous emission such as nitrogen oxides, sulphur oxides and greenhouse gases). in this research, only greenhouse gas emissions, represented by carbon dioxide are considered. the projected reduction in co2 emissions can be calculated based on direct relationship between electricity generation and co2 emission: higher rate of energy consumption means more co2 release to atmosphere. table 6, shows the emitted gases for unit electricity generation in jordan for the previous period 2002-2009. the emission of co2 coefficient of electricity generation was calculated based on the weighted average of all power generation per fuel type divided annual co2 emission over the annual generated electricity of all plants in jordan during 2010 and assumed to be constant to the next 10 years shown in table 7. ( )fuel type1 fuel type 1 coe electricity generated cof / electricity generated = ×∑ ∑ (7) where cof is the emission co2 factor for each fuel type was used in electricity generation. the total reduction in co2 emission given by the formula: tcoe=es×coe (8) the reduction amount in electricity bill associated to the reduction on energy consumption and the energy prices which are changes according to the global fossil fuel price. the prices also different according to the energy consumption in households, in this study the energy prices are assumed to be fixed and constant for the next 10 year. the average price for the different household energy consumer ranges considered 72 fills/kwh. su=es×p (9) where, su is saving in utility bills, p is energy price (fills/kwh). 4. results 4.1. reduction in electrical energy consumption in this research mees were implemented for cold appliances (refrigerator, freezer and combination) in jordanian residential sector based on the collected data. these appliances accounted for about 32.7% of household electricity energy consumption in jordan. the majority of cold appliances used in jordanian residential sector were old as noticed during survey. the resulted saving amount is the minimum amount which can be saved due to implementing mees for household appliances. figure 3 shows the amount of saved energy for the years 2011-2020 for the four scenarios. through the years, the amount of saved energy will be increase due to increase number of houses which table 5: input data symbol description value y0 base year 2010 e0 energy consumption at base year 5219 gwh/year t life span (study period) 10 year p average electricity price 72 fills/kwh coe co2 emission 0.49 co2 kg/kwh table 6: fossil fuel emission for unit electricity generation fuels emission (ton metric 000/year) co2 nox co 2002 17742.2 108.9 433.7 2003 18600.0 113.7 457.7 2004 19493.0 118.2 483.3 2005 20107.0 122.2 509.5 2006 20766.9 127 537.4 2007 20712.4 130.1 566.9 2008 21387.7 135 598 2009 21996.2 140.5 630 table 7: co2 emission for unit electricity generation year total (gwh) co2 emission (ton metric 000/year) kg/kwh 2002 8132.0 17742.2 2.18 2003 7994.6 18600.0 2.33 2004 8967.9 19493.0 2.17 2005 9654.0 20107.0 2.08 2006 11120.2 20766.9 1.87 2007 12999.1 20712.4 1.59 2008 13768.0 21387.7 1.55 2009 14207.8 21996.2 1.54 2010 14682.8 alfattah, et al.: energy efficiency standards and labels for cold appliances in jordan international journal of energy economics and policy | vol 7 • issue 3 • 2017 99 used efficient appliances, moreover the number of old appliances replacing by efficient model will be increased. implementing mees based on scenarios 1, 2, 3 and 4 till the year of 2020 will save about 4451.7, 8903.4, 13,355.1 and 17,806.8 gwh, respectively, at the end of year 2020. these calculation will be effective for the next 10 year, after that new calculation have to be made because the awareness of people on efficient model and how it will affect their utilities and bills. the saving energy by applying different scenarios was increased during the years based on the calculation. scenario 4 represents the highest saving percentage in respect to all other scenarios by the end of. the market share of each scenario divided over the energy efficiency class a, b and c are by 40%, 40% and 20% respectively, in order to enhance the number of efficient model in the market. 4.2. reduction in co2 emission in addition to the evaluation of the impact of implementing mees on energy consumption, the environmental impacts were evaluated as represented by co2 emission. co2 emission due to electricity generation in jordan increases gradually. co2 emission was increased by 54% from year 2002 to 2009 due to increasing electricity demand. if electric energy consumption remained at the same level without adopting mees, co2 emission would reach 2.6 times of that of 2009. co2 emission will grow at lower rate if mees according to the four scenarios is implemented. co2 emission percentage due to electricity generation in jordan was calculated based on used fuel mix in electricity generation. co2 emission produced is approximately 0.499 co2 kg/kwh. table 8 presents average co2 emission factor and fraction of electricity generation for each source in jordan. using efficient cold appliances will reduce emitted gasses as a result of reducing electricity consumption. table 9 presents the predicted future reduction of co2 emission for the four scenarios. the contribution on reducing co2 emission was 50.1% from total reduction for each scenario. the annual co2 reduction would be about 454, 907, 1361 and 1814 ton metric 1000/year for scenario 1, 2, 3 and 4, respectively, by year of 2020. 4.3. reduction in electrical utility bill since it is expected that electrical energy consumption would reduce when implementing mees for the future sold appliances in the market and when replacing old models by efficient models, electrical utility bill would reduce. the electricity price increases due to the increase of global fossil fuel prices. in this work the electricity cost was assumed constant at rate 72 fills/kwh. figure 4 shows the effect of implementing mees on electricity bills according to the four suggested scenarios. table 10 shows the annual reduction in utility bill by implementing mees were the total saving at the end of 2020 for the scenario 1, 2, 3 and 4 were about 320.5, 641.0, 961.6 and 1282.1 million respectively. 5. conclusions this study presented a polynomial fitting regression for electricity consumption in the jordanian residential sector. figure 3: annual electrical energy saving by implementing minimum energy efficiency standards for cold appliances for four scenarios table 8: average co2 emission factor and fraction of electricity generation for each source in jordan (2010) source co2 emission (kg/mj of fuel) electricity generation (gwh) total consumption (ktoe) total consumption (tj) co2 emission (106 kg) diesel 0.067 435.5 106.0 4438.0 297.3 hfo 0.075 3628.2 883.0 36969.4 2772.7 natural gas 0.038 9339.5 2273.0 95166.0 3616.3 renewable 0.000 2.65 0.7 30.6 0 total 13406.2 3262.7 136604.0 6686.4 alfattah, et al.: energy efficiency standards and labels for cold appliances in jordan international journal of energy economics and policy | vol 7 • issue 3 • 2017100 the developed model has been proved to be adequate with r2 and adjusted-r2 of 99.6% and 99.5% respectively. the energy consumption has been increasing because of increasing numbers of the used electrical appliances in households and the ever increasing population and incoming people from other countries due to the political situation. therefore, the implementation of mees effect was studies and a calculation was made for the cold appliances, most energy consuming appliances inside the household. implementing mees for jordanian cold appliances was found to be very beneficial for the government, environment and customer. at worst scenario, it is found that the net saving from 2011-2020 was approximately 4451.7 gwh by the end of year 2020, the associated co2 emission reduction during the 10 years increase gradually to reach 454 (1000 ton) in 2020. in addition, the reduction of customer bills was reaching 65.4 million jd in 2020. energy consumption could increase much more than this study due to the political situation, which will lead to increase in kingdom’s population in an unexpected manner therefore, implementing the mees for the electrical household appliances in jordan, should be carried out so as to reach the desired energy saving once the standards are implemented. inefficient products will be pushed out of the market and replaced by efficient products. the standard indirectly will also reduce the amount of environmental pollution. the customer will pay higher purchase prices for appliances, but will get lower electricity bills. table 9: environmental impact by implementing minimum energy efficiency standards for cold appliances scenario 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 scenario 1 35 68 104 143 185 230 279 333 391 454 a 15 30 45 62 80 100 122 145 170 198 b 14 27 41 57 73 92 111 133 156 181 c 6 11 17 24 31 38 46 55 65 75 scenario 2 70 137 208 285 369 460 559 666 782 907 a 31 60 91 124 161 201 244 290 341 396 b 28 54 83 114 147 183 222 265 311 361 c 12 23 35 47 61 76 93 110 130 151 scenario 3 106 205 312 428 554 690 838 998 1172 1361 a 46 89 136 187 241 301 365 435 511 593 b 42 82 124 170 220 275 334 398 467 542 c 18 34 52 71 92 115 139 166 195 226 scenario 4 141 273 416 571 738 920 1117 1331 1563 1814 a 61 119 181 249 322 401 487 580 681 791 b 56 109 166 227 294 366 445 530 622 722 c 23 45 69 95 123 153 185 221 259 301 table 10: the annual saving amount (million jd) by implementing mees for cold appliances of the four scenarios scenario 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 total scenario 1 5.1 9.8 15.0 20.6 26.6 33.2 40.3 48.0 56.4 65.4 320.5 scenario 2 10.2 19.7 30.0 41.2 53.3 66.4 80.6 96.0 112.8 130.9 641.0 scenario 3 15.2 29.5 45.0 61.8 79.9 99.6 120.9 144.1 169.2 196.3 961.6 scenario 4 20.3 39.4 60.0 82.4 106.5 132.8 161.2 192.1 225.5 261.8 1282.1 mees: minimum energy efficiency standards figure 4: the saving on the utility bills amount (million jd) by implementing minimum energy efficiency standards for cold appliances alfattah, et al.: energy efficiency standards and labels for cold appliances in jordan international journal of energy economics and policy | vol 7 • issue 3 • 2017 101 references al-ghandoor, a., al-hinti, i., jaber, j.o., sawalha, s.a. (2008), electricity consumption and associated ghg emissions of the jordanian industrial sector: empirical analysis and future projection. energy policy, (36), 258-267. al-ghandoor, a., jaber, j.o., al-hinti, i., mansour, i.m. (2009), residential past and future energy consumption: potential savings and environmental impact. energy policy, (13), 1262-1274. brennan, t.j., palmer, k.l. (2013), energy efficiency resource standards: economics and policy. utilities policy, 25, 58-68. cleff, t., rennings, k. (2016), are there first mover advantages for producers of energy-efficient appliances? the case of refrigerators. utilities policy. doi: 10.1016/j.jup.2016.03.004. department of statistic. (2009), environmental statistics. amman, jordan: department of statistic. department of statistic. (2009), annual environmental statistics. amman, jordan: department of statistic. energy independence and security act (eisa). 110th congress; 2007. meyers, s., mcmahon, j.e., mcneil, m., liu, x. (2003), impacts of us federal energy efficiency standards for residential appliances. energy, 28(8), 755-767. meyers, s., mcmahon, j.e., mcneil, m., liu, x. (2004), realized and prospective impacts of u.s. energy efficiency standards for residential appliances: 2004 update, lawrence berkeley national laboratory, report no. lbnl-56417. ministry of energy and mineral resources. (2010), annual report. amman, jordan: ministry of energy and mineral resources. ministry of energy and mineral resources. (2010), energy balance. amman, jordan: ministry of energy and mineral resources. ministry of energy and mineral resources. (2010), sectors energy consumption distribution. amman, jordan: ministry of energy and mineral resources. 1565_burakov.indd international journal of energy economics and policy | vol 6 • issue 1 • 2016 65 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2016, 6(1), 65-75. elasticity of energy intensity on a regional scale: an empirical study of international trade channel dmitry burakov* department of monetary relations and monetary policy, russian federation, financial university under the government of russian federation, moscow, russia. *email: dbur89@yandex.ru abstract this study examines the relationship between energy intensity in different world regions. to explain relationship between them we test a hypothesis of international trade channel and determine degree of sensitivity of national economy’s energy intensity to actions of major competitors in export market. based on data of energy intensity for more than 150 countries for the period from 1980 to 2011, using regression analysis, we built a number of unrestricted vector autoregression models refl ecting relationship between energy intensity of different regions, and relationship between groups of economies, primary source of exports for which is fuel or engineering sector. to characterize elasticity of energy intensity in sampled countries, we use variance decomposition and impulse response techniques. the study shows the presence of a stable relationship between energy intensity for different regions of the world. testing interlinkages between energy intensity of economies exporting raw materials (e.g. oil) and engineering production, for trade channel, confi rms its existence. the sensitivity of economies exporting raw materials to shocks in energy intensity tends to be signifi cantly lower than in economies exporting consumer goods. keywords: energy intensity, elasticity of energy intensity, credit market jel classifi cations: f14, o13, q43 1. introduction energy is an important factor for economic and social development, which ensures reliable functioning of economic and public relations, helps to achieve welfare of the world community. in regard to economic relations, energy is essential to maintain continuity of reproduction in conditions of modern technology. lack of energy or its ineffi cient use has negative implications for economic development. one of the common indicators of energy effi ciency is energy intensity. the energy intensity of the economy refl ects amount of power needed to ensure stability of economic operations. at the same time, energy is an indirect manifestation of technology’s effectiveness as a production factor. the problem of energy effi ciency as a result of production factors’ usage signifi cantly increased in the 1970s, and has attracted increased attention from authorities, experts and research community. even so, the problem of energy intensity of the economy remains relevant today. reduction in energy intensity is the keynote of public policy of most countries in the world. the problem of energy stagnation preservation of steadily high levels of consumption relative to gross domestic product (gdp), still exists. the energy intensity of economy can be considered in light of technological factor of production, its effi ciency. the classic model of production factors and competitive advantages (for example, the hecksher-ohlin model) states that the structure of exports and imports of the national economy directly, ceteris paribus, depends on existing competitive advantages when using factors of production. in conditions of perfect competition, with no barriers of market entry, the optimal functioning of institutions, and taking into account transaction costs, exported products should and will have a comparative advantage in relation to competitors. the same is true for imports. thus, the classical model of international trade states that in a free market (absence of institutional and political barriers), elasticity of demand and supply for goods and services in international markets must tend to maximum values. a high level of competitive pressure should stimulate producers to the most effi cient use of production factors. otherwise, non-maximizing burakov: elasticity of energy intensity on a regional scale: an empirical study of international trade channel international journal of energy economics and policy | vol 6 • issue 1 • 201666 behavior is fraught with loss of competitive advantages. in other words, ineffi cient use of factors of production is fraught with the loss of a niche in the international market, reducing a share of exports and an increasing pressure of cheaper imports in the domestic market (in this case, the policy of exchange rate should be thought of as a barrier). with regard to energy intensity of the economy, this theory states that taking into account geographical features, transportation and other transaction costs, consumption of energy should have signifi cant elasticity and technology, as a factor of production, determining energy intensity, to respond to competitors’ actions in a manner of reaction to external technological shocks. unfortunately, in practice, the hecksher-ohlin theorem has proved, in certain cases, unviable due to unrealistic assumptions, which include full rationality of agents, maximizing behavior, lack of barriers to market entry, perfect information, stable risk aversion, no protectionism in the actions of national authorities etc. therefore, an assumption about absolute elasticity of production factors also cannot be considered as realistic. however, the field of international economic relations is developing rapidly. depending on the specialization of economies in relation to various industries, there exist regional centers that are in competition with each other taking into account the spatial aspect. competition between players is enhanced, which requires not only actions on maintaining comparative advantages, such as well managed exploitation of production factors (labor, land, capital, information), but also their development through technology upgrades, and, consequently, a reduction in energy intensity. however, in practice, protectionist measures of national authorities begin to play an increasing role, establishing import quotas, import tariffs, implementing methods of unfair competition, which generally reduce effi ciency of the national economy, making it more closed, less market-oriented. these actions also infl uence on elasticity production factors, in particular on energy intensity. another consequence of such market imperfections lie in rising energy consumption, conserving an economy in the current technological state, which leads to lower economic growth, quality of life and level of prosperity. thus, it can be assumed that in the presence of dependence on export operations (if share of exports in gdp is at least 30%), the need for maintaining competitive advantages dictates the necessity of reducing energy intensity of gdp. the degree of sensitivity of exports to technological shocks on international markets at the same time may depend on the presence of protectionist policies, manipulating exchange rate in order to devaluate national currency, geographic features, and structure of exports. another important point for this study is to determine relationship between sectoral specialization of the national economy and elasticity of energy intensity (energy elasticity). in other words, one could assume that sensitivity of some industries in international markets to shocks in energy consumption is higher than in others and pace of changes is signifi cantly higher. the basis of this assumption is still a same thesis about comparative advantages due to the natural barriers that protect the industry. for example, in case of economies dependent on oil exports, geographical position, specifi cs of transportation, could create in some cases a quasi-monopolistic position, which may substantially reduce sensitivity to actions of competitors, which could potentially lead to reduction in energy intensity, thereby reducing net costs of oil production. in absence of such barriers, sensitivity of an economy that depends on exports should be signifi cantly higher. moreover, we can assume that in current conditions, the question of energy intensity of gdp, its elasticity to changes in international markets, lies not so much in maintaining competitive advantages, but in the survival of the national economy in the long term. and this exactly determines relevance of the present study. the question of determining relationship between energy intensity of economies worldwide in a regional breakdown presence or absence and its degree (sensitivity of energy intensity of individual economies to shocks of international markets), should allow to shed light on current status of international market for goods and services in the context of energy effi ciency, as well as to determine patterns of energy elasticity for various types of economies. given the above, the aim of this study is to test hypotheses about relationship between energy effi ciency of economies on a regional scale and to determine elasticity’s level of their energy intensity in the context of international trade. the paper is organized as follows: section 2 reveals existing theory and presents a literature review on the issue. section 3 presents methods used to test the hypotheses. section 4 presents the results of hypotheses’ empirical testing and identifi es areas of further research. section 5 presents concluding remarks of this research. 2. literature review the issue of energy intensity of gdp is well researched. there is a large number of studies on energy effi ciency, methods of its measurement, comparative analysis of energy effi ciency. much attention is paid to relationships between energy effi ciency and economic growth of the economy; upgrading technological factor of production and changes in energy intensity. (jorgenson, 1984; rezitis and ahammad, 2015). most of the studies conclude that there is signifi cant relationship between economic growth and the level of energy intensity of production (florax et al., 2011). the same is true for the impact of technology modernization on energy effi ciency, provided signifi cant energy intensity of gdp. these results allow us to assume that the role of energy in economies of most countries of the world to be high (mulder and de groot, 2004). concerning subject of our research, existing literature on the issue could be divided into several blocks. the fi rst block of literature discusses relation between energy intensity of gdp and technological factor of production and burakov: elasticity of energy intensity on a regional scale: an empirical study of international trade channel international journal of energy economics and policy | vol 6 • issue 1 • 2016 67 provisions of international trade theories. so, most of the studies reveal lack of conformity between energy effi ciency trend and provisions of hecksher-ohlin theorem. among the potential causes of impairment monopolistic or oligopolistic competition, territorial, geographic factors, low quality of institutions (absence of incentives to improve energy efficiency) are pointed out (hillman and bull, 1978; burakov, 2015). the second block of literature deals with the question of exports elasticity to competitive pressure on international markets. in these studies, sensitivity of energy intensity of gdp to shocks of international markets is analyzed. thus, studies of li (2010), jacobsen (2013), demonstrate presence of energy-intensive industries’ elasticity to actions of competitors at the level of national economies, creating a system of incentives to modernize production technology in order to reduce production costs. however, these incentives can be blocked under different causes, including low weight of energy in net costs of production, policy of export/import tariffs, and fi xed exchange rate in times of currency wars and so on (havlik, 1998; srinivasan and archana, 2009). the third literature block includes cross-country studies of energy effi ciency, identifi es trends and linkages between different economic sectors at the global level. e.g., mulder and de groot (2011; 2012), using data of energy intensity in sample economies for 25 years, carried out a comparative analysis of energy effi ciency and determined its degree in the context of particular industries. also a detailed comparative analysis of national economies’ effi ciency and energy intensive industries are presented in florax et al. (2011). for example, in gunay and ceylan (2010) a comparative study of energy effi ciency is presented and potential of turkey, compared with countries of the eurozone is assessed. in the study by amador (2011), comparative analysis of energy effi ciency of 30 countries over a 10-year period is conducted and changes in a trend of energy effi ciency is analyzed through the classical set of factors of international trade theory. all the studies of this literature block highlight a problem of lowering energy intensity in a number of countries, stating that interlinkages of energy intensity between different sectors exist, however energy elasticity does not solely explain growth rates of gdp, or economy’s output (nilsson, 1993; eichhammer and mannsbart, 1997; howarth et al., 1998; markandya et al., 2006). in some cases, authors even come to conclusion that labor effi ciency (effort level) as a production factor nowadays play a more signifi cant role rather than energy and technologies due to increasing imperfect competition on international markets (miketa, 2001; miketa and mulder, 2005; huntington, 2010; mulder and de groot, 2012). the fourth block of literature is devoted to the study of energy elasticity sensitivity of changes in energy consumption to changes in gdp. most of research is concentrated around analysis of national economic patterns and energy elasticity (liu and ang, 2007; phoumin and kimura, 2014). the most commonly used factor in determining and explaining energy elasticity is energy price and associated prices of oil and gas. a key conclusion of this research block on our issue is identifi cation of a low price elasticity of energy consumption: in case of a rise in electricity prices, a reduction in demand is either minimal or absent (e.g. bernstein and griffi n, 2006). regarding a hypothesis of our research cross-country regional analysis of interlinkages between energy intensities of gdp and dependence of elasticity on the type of exported goods, just a few works close to our subject of research were found. however, all the above-mentioned papers encapsulate essential parts of argumentation and theoretical provisions necessary to conduct our research. 3. methodology of research for verifi cation of the hypotheses, we use unrestricted vector autoregression (var) model to refl ect a statistically signifi cant relationship between energy intensity of economies at a regional scale. the sample includes 156 developed and developing countries, characterized by different levels of energy intensity of gdp. we do not set ourselves a task to conduct a comparative analysis of energy effi ciency, but to identify the relationship between changes in it. the sampling period is 31 years from 1980 to 2011. the main source of information is data from united states energy information administration. in the absence of data for some periods, we turn to national statistical offi ces to ensure the completeness and comparability of time series. to measure energy intensity of national economy, we use data on total primary energy consumption per dollar of gdp (btu per 2005 u.s. dollars [purchasing power parity]). the sample of regions includes western europe, eastern europe, southeast asia, middle east, sub-saharan africa, and latin america. to determine energy intensity on a regional we average data on energy intensity of countries in the region with the aim of obtaining aggregated regional trend. obtained data are used to construct unrestricted var model, which allows refl ecting the presence or absence of correlation between energy intensity of regional economies. in process of constructing the model, variables of regional trends are tested for presence of unit root in time series with the augmented dickey-fuller test. next, using obtained time-series sample, we construct a var model and test it for presence of heteroscedasticity and serial correlation of residuals. for heteroscedasticity of residuals, white test is used. null hypothesis states that the residuals are homoscedastic. serial correlation is tested with the residual autocorrelation lm test. the null hypothesis of the test is that there is no serial correlation in the residuals up to the specifi ed order. in addition, normality test is used. the resulting model refl ects presence or absence of linkages between regional trends. the second part of the study is devoted to identifi cation of presence/absence and degree of elasticity of energy intensity in sampled countries depending on the type of exported goods. to conduct the study we form two samples of countries. the first sample includes largest countries-exporters of oil; the burakov: elasticity of energy intensity on a regional scale: an empirical study of international trade channel international journal of energy economics and policy | vol 6 • issue 1 • 201668 second exporters of engineering products. data for time series is obtained from the same sources. for analysis of relationships, we built two unrestricted var models, which were also tested for stationary (using second difference), serial correlation and heteroscedasticity. to assess the degree of elasticity we use techniques of variance decomposition and impulse response function. 4. empirical findings results of augmented dickey-fuller test for regional model show that time series used in the study are not stationary. therefore the null hypothesis of non-stationary could not be rejected, but after second differencing of the variables, the t-bar test statistics are well less than the corresponding critical values at 5% signifi cation level, which indicate that the null hypothesis of non-stationary should be rejected and the alternative hypothesis of stationary be accepted (table 1). after differencing the variables and confi rming that time series used for var model are stationary we turn to identifying the optimal lag structure for our model (table 2). value of each information criterion speaks in favor of choosing two lags as an optimal number for the model. after determining that time series used to construct the model are stationary, setting the optimal number of lags for the model, we can proceed to the construction of the model itself (table 3). before we start analysis of the obtained results, it is necessary to ensure that serial correlation and heteroscedasticity are absent, as well as to ensure that the model meets the requirement of normality and stability. for this, we conduct tests of the residuals, the results of which are presented in table 4. as can be seen from the data presented in this table 4, the model we have built meets the requirement of normality, is characterized by stability and absence of serial correlation as well as heteroscedasticity. the results of the var models built, refl ecting presence or absence of statistically signifi cant correlation between energy intensity of economies at the regional scale, allow drawing several important conclusions. firstly, according to classical international trade theory, the relationship between energy intensities of economies on a regional scale exists. positive values of diagnostic tests of the regression model allow us to argue that false results caused by the effect of autocorrelation do not exist and the model cannot be thought of as spurious. secondly, regression model refl ects existence of statistically signifi cant dependencies in case of not all regions, which also speaks in favor of international trading channel on the one hand. on the other hand, according to hecksher-ohlin theorem, elasticity of production factors (including energy as a technological factor) should be present in all situations determined by the existence of trade relations. elasticity values should tend to maximum. this theorem gets only partial confi rmation according to constructed regression model. a possible explanation for lack of statistically signifi cant correlation between energy intensity of economies on a regional scale may be due to imperfections of international market for goods and services on the one hand, and internal imperfections of institutional nature on the other. thirdly, we can assume that there are alternative endogenous variables that explain changes in a trend of energy intensity in the region. this model does not serve determining regression equation, which allows explaining structure of the trend in energy intensity completely, nor does it attempt to predict changes in this trend. among the alternative variables one could point out intra-regional links between the region’s economies, structure of gdp, level of human capital, development of science-intensive production techniques to reduce capital intensity of production and others. fourthly, existing regional correlation of energy intensities is partly explained by structure of export-import operations, as well as participation of other regions’ economies in development of the energy sector and the economy. for example, changes in energy intensity in countries of the middle east have a signifi cant impact on the eastern, western europe, south asia and latin america (value of t statistics correspond to the criterion of statistical signifi cance at 5% confi dence level). a possible explanation may table 1: results of unit root test variable t statistics p value adf test at level with intercept and trend western europe −4.24 0.109 eastern europe −3.69 0.367 sub-saharan africa −2.84 0.193 south asia −2.04 0.554 latin america −2.41 0.068 middle east −1.85 0.654 adf test at 2nd difference with intercept and trend western europe −5.24 0.009 eastern europe −5.62 0.005 sub-saharan africa −6.44 0.000 south asia −7.18 0.000 latin america −6.42 0.000 middle east −6.19 0.001 adf: augmented dickey–fuller table 2: optimal lag selection criteria lag logl lr fpe aic sc hq 0 −1180.329 na 2.55e+29 84.73780 85.02327 84.82507 1 −1137.445 64.32656 1.66e+29 84.24606 86.24437 84.85696 2 −1059.347 83.67649* 1.22e+28* 81.23906* 84.95020* 82.37359* *indicates lag order selected by the criterion. lr: sequential modifi ed lr test statistic (each test at 5% level). fpe: final prediction error, aic: akaike information criterion, sc: schwarz information criterion, hq: hannan-quinn information criterion burakov: elasticity of energy intensity on a regional scale: an empirical study of international trade channel international journal of energy economics and policy | vol 6 • issue 1 • 2016 69 be due to changes in energy intensity of middle east economies due to changes in energy prices (oil), which is the main export commodity. the change in oil prices affects domestic consumption and the energy intensity of production in the importing countries with increasing energy prices, growing domestic consumption (with a lag) leads to higher energy intensity in other countries. in addition, a signifi cant dependence of regions’ energy intensity is seen in case of latin america, western and eastern europe, south asia and sub-saharan africa. the explanation of the statistically signifi cant interlinkages is, in our opinion, in export operations. most of exports of latin america (and africa) is food products, where latin america is opposed to asia, africa and europe. a surprising feature of the results is lack of dependence of african region’s energy intensity from other regions. this feature is explained on the one hand by territorial remoteness of the region, climatic characteristics, and the structure of economies that are not too energy-intensive, which follows general principles of the theory of international trade. if our assumptions about the international trade channel of infl uence on energy intensity of economies at the regional scale are correct, then these assumptions could be confi rmed by presence of energy elasticity’s impact on degree of correlation between sampled countries. the sample of countries is formed in such a way, so that to test patterns of elasticity of energy intensity of table 3: unrestricted var model of cross-country relationship of energy intensity on a regional scale variable d(eastern_ europe,2) d(latin_ america,2) d(middle_ east,2) d(south_ asia,2) d(sub_ saharan_ africa,2) d(western_ europe,2) d(eastern_europe(-1),2) −0.356905 0.206054 0.172839 −0.022654 −0.073350 0.189832 (0.19326) (0.09016) (0.25313) (0.05596) (0.10097) (0.09660) [−1.84672] [2.28531] [0.68280] [−0.40480] [−0.72643] [2.01520] d(eastern_europe(-2),2) −0.477671 −0.155735 −0.457269 −0.118191 −0.193488 −0.213438 (0.18342) (0.08557) (0.24024) (0.05311) (0.09583) (0.09168) [−2.60419] [−1.81990] [−1.90336] [−2.22529] [−2.01903] [−2.32812] d(latin_america(-1),2) 1.533237 0.023762 0.932412 0.207372 0.113479 0.672804 (0.53028) (0.24740) (0.69455) (0.15355) (0.27705) (0.26504) [2.89135] [0.09605] [1.34246] [1.35051] [0.40959] [2.53845] d(latin_america(-2),2) 1.078727 −0.494300 0.054513 0.119859 0.018385 −0.452173 (0.41633) (0.19423) (0.54529) (0.12055) (0.21752) (0.20809) [2.59106] [−2.54492] [0.09997] [0.99425] [0.08452] [−2.17300] d(middle_east(-1),2) 0.885411 0.263749 0.184649 0.116699 0.019929 0.253858 (0.19424) (0.09062) (0.25441) (0.05624) (0.10148) (0.09708) [4.55842] [2.91056] [0.72580] [2.07489] [0.19639] [2.61486] d(middle_east(-2),2) −0.115693 −0.126110 −0.367053 −0.137098 −0.095033 0.143300 (0.18394) (0.08581) (0.24092) (0.05326) (0.09610) (0.09194) [−0.62897] [−1.46958] [−1.52356] [−2.57405] [−0.98888] [1.55870] d(south_asia(-1),2) −1.903523 −1.419570 −0.798446 −1.056143 0.239828 −1.389004 (0.70562) (0.32919) (0.92420) (0.20432) (0.36866) (0.35268) [−2.69768] [−4.31226] [−0.86393] [−5.16906] [0.65054] [−3.93844] d(south_asia(-2),2) −2.300689 −0.840694 −1.317366 −0.540969 0.247682 −0.595230 (0.68983) (0.32183) (0.90352) (0.19975) (0.36041) (0.34479) [−3.33515] [−2.61223] [−1.45803] [−2.70824] [0.68722] [−1.72636] d(sub_saharian_africa(-1),2) −0.680842 −0.418264 −1.264230 −0.063494 −0.816125 −0.633580 (0.46412) (0.21653) (0.60790) (0.13439) (0.24249) (0.23198) [−1.46694] [−1.93167] [−2.07968] [−0.47245] [−3.36564] [−2.73122] d(sub_saharian_africa(-2),2) 1.985314 0.763081 1.913982 0.321079 0.034191 0.407403 (0.43778) (0.20424) (0.57340) (0.12677) (0.22873) (0.21881) [4.53491] [3.73617] [3.33796] [2.53285] [0.14949] [1.86188] d(western_europe(-1),2) −2.387753 −1.066336 −2.491786 0.073962 −0.002967 −1.610367 (0.54537) (0.25443) (0.71431) (0.15792) (0.28494) (0.27258) [−4.37824] [−4.19103] [−3.48838] [ 0.46836] [−0.01041] [−5.90778] d(western_europe(2),2) 0.931983 0.974775 0.881618 0.699331 0.339859 0.600718 (0.56637) (0.26423) (0.74181) (0.16400) (0.29591) (0.28308) [1.64555] [3.68913] [1.18846] [4.26425] [1.14854] [2.12208] c 32.16083 −6.563987 −11.84519 −20.37299 −11.37931 5.568610 (72.4475) (33.7992) (94.8899) (20.9781) (37.8512) (36.2105) [0.44392] [−0.19421] [−0.12483] [−0.97116] [−0.30063] [0.15378] var: vector autoregression table 4: results of model’s diagnostic testing type of test results lags lm-stat p value var residual serial correlation lm test 1 43.45706 0.1835 2 29.16504 0.7832 3 41.83999 0.2321 stability condition test all roots lie within the circle var satisfi es stability condition heteroscedasticity test (white) 0.2931 normality test 0.7513 var: vector autoregression burakov: elasticity of energy intensity on a regional scale: an empirical study of international trade channel international journal of energy economics and policy | vol 6 • issue 1 • 201670 economies depending on export for compliance with theoretical positions of classical hecksher-ohlin theorem. for building models of sampled countries in order to verify trade channel and its impact on elasticity of energy intensity of countries in the sample, we have selected countries that are the main competitors from export structure point of view. in the fi rst model, countries competing in the extraction and delivery of oil as a key energy source are represented. in the second model, countries competing in the supply of fi nal consumption goods (mostly machinery industry) are included. the algorithm for constructing these models is identical to the previous one. it involves testing for presence of unit root, transformation of time series in the second difference to resolve the problem (tables 5 and 6). further, optimal values of the time lag for regression models are determined (tables 7 and 8). the models themselves, refl ecting correlation of energy intensity depending on actions of competing countries are presented in tables 9 and 10. diagnostic testing results of models for the presence of heteroscedasticity, serial correlation, test for normality and stability are presented in tables 11 and 12. assessment of the degree of energy elasticity of sampled economies, depending on the action of competitors on international markets for oil, goods and services presented using the tools of variance decomposition and impulse response (graphs 1a-f, 2a-f, 3a-f, and 4a-f). the results of the var models developed, confi rm the correlation between energy intensity of sampled economies, as in case of countries that export mainly energy and in case of countries exporting industrial consumer goods. in case of countriesexporters of oil, statistically signifi cant correlations exist due to territorial proximity, elimination of high transportation costs (as in the case of russia and norway), or of a common pool of consumers (as in the case of russia and venezuela, which is actively entering the market of eastern europe). at the same time, in the case of, for example, russia there is no statistically signifi cant dependence of its energy intensity from technology investments in countries of the middle east (e.g. saudi arabia and uae) due to geographical distance. the dependence of norway from major players of oil market remains. an explanation for this peculiarity lies in the quasi-monopolistic position of russia as supplier of oil in the region, naturally protected on one side by the effect of scale of oil supply (from norway) and low transportation costs (from the middle east). this, in turn, leads to decreased elasticity of energy intensity of the russian economy to shocks on the international energy market and the deterioration of the oil industry. in case of geographical proximity of competitors on one side and a shared pool of consumers on the other (saudi arabia and uae) sensitivity to shocks increases energy effi ciency. analysis of energy elasticity of countries-oil exporters allows making several conclusions. firstly, in presence of limited competition and a quasi-monopolistic position on the market, sensitivity to shocks of international market tends to zero, or is of a minor value and reveal itself with a signifi cant time lag (in case of russia, for example, only at the 4th period; the same is true for saudi arabia sensitivity to shocks in the long run is almost unchanged). secondly, in case of geographical proximity, competitive pressure on the market forces players to react on actions of competitors, reducing production costs by investing in technologies of oil extraction and refi nery (in case of saudi arabia and the uae). thirdly, in absence of competitive advantages and presence of tough competition (russia and norway), countries are forced to respond to energy intensity shocks with a lag period of 1-2 and in a very signifi cant range. analysis of responses by the countries in the sample confi rm identifi ed patterns. turning to analysis of the model, describing energy intensity elasticity of economies, exporting consumer goods, we can draw the following conclusions. first, a hypothesis about existence of relationship between energy intensity of sampled economies is confi rmed due to presence of statistically signifi cant correlations between the countries. e.g., there exist a strong relationship between energy intensities of germany and china, the usa, spain and holland. in addition, a signifi cant impact on energy intensity of the us economy has a chinese trend. explanation of these interlinkages may be found in strong competition between the us, china and germany in various markets for goods and services. specifi cs of china is that the trend of its energy intensity does not table 5: results of unit root test for oil-exporting countries variable t statistics p value adf test at level with intercept and trend saudi arabia −2.85 0.188 russian federation −2.11 0.520 united arab emirates −2.31 0.418 qatar −1.81 0.670 venezuela −1.88 0.636 norway −3.48 0.058 adf test at 2nd difference with intercept and trend saudi arabia −6.43 0.000 russian federation −7.91 0.000 united arab emirates −7.16 0.000 qatar −9.41 0.000 venezuela −9.71 0.000 norway −7.31 0.000 adf: augmented dickey–fuller table 6: results of unit root test for manufacturing export countries variable t statistics p value adf test at level with intercept and trend usa −3.60 0.058 china −0.76 0.956 germany −2.03 0.559 france −2.50 0.325 spain −2.92 0.169 netherlands −3.22 0.097 adf test at 2nd difference with intercept and trend usa −5.28 0.001 china −7.44 0.000 germany −9.37 0.000 france −5.59 0.000 spain −8.86 0.000 netherlands −7.30 0.000 adf: augmented dickey–fuller burakov: elasticity of energy intensity on a regional scale: an empirical study of international trade channel international journal of energy economics and policy | vol 6 • issue 1 • 2016 71 depend on other countries in the sample. this result is explained by the presence of comparative competitive advantages in the use of labor as a factor of production, reducing possible effects on the chinese economy. a sensitivity analysis of countries in the sample to technological shocks that affect the energy intensity of gdp allows allocating the following features. first, low elasticity is inherent to countries that have a competitive advantage in the framework of table 7: optimal lag selection criteria for oil-exporting countries lag logl lr fpe aic sc hq 0 −1420.501 na 7.19e+36 101.8929 102.1784 101.9802 1 −1348.493 108.0121 5.86e+35 99.32092 101.8277* 99.93183 2 −1295.631 56.63755* 2.61e+35* 98.11651* 101.3192* 99.25105* lr: sequential modifi ed lr test statistic (each test at 5% level). fpe: final prediction error, aic: akaike information criterion, sc: schwarz information criterion, hq: hannan-quinn information criterion table 8: optimal lag selection criteria for manufacturing export countries lag logl lr fpe aic sc hq 0 −1140.825 na 1.52e+28 81.91606 82.89734 82.00333 1 −1100.800 60.03709 1.21e+28 81.62858 83.62688 82.23948 2 −1030.607 75.20702* 1.57e+27* 79.18620* 82.20153* 80.32074* lr: sequential modifi ed lr test statistic (each test at 5% level). fpe: final prediction error, aic: akaike information criterion, sc: schwarz information criterion, hq: hannan-quinn information criterion table 9: unrestricted var model of cross-country relationship of energy intensity for oil-exporting countries variable d(saudi_ arabia,2) d(russia,2) d(united_ arab_ emirates,2) d(qatar,2) d(norway,2) d(venezuela,2) d(saudi_arabia(-1),2) −0.826284 −0.170586 1.763550 −1.131395 −0.101294 −0.106971 (0.26437) (0.33107) (0.28865) (0.64946) (0.12879) (0.27362) [−3.12549] [−0.51526] [6.10975] [−1.74205] [−0.78648] [−0.39095] d(saudi_arabia(-2),2) −0.075446 −0.304098 1.157584 −1.242975 −0.268155 −0.140668 (0.30740) (0.38496) (0.33563) (0.75517) (0.14976) (0.31815) [−0.24543] [−0.78996] [3.44901] [−1.64594] [−1.79060] [−0.44214] d(russia(-1),2) 0.050865 −0.312557 0.346238 0.117718 0.258528 −0.225594 (0.20255) (0.25365) (0.22115) (0.49760) (0.09868) (0.20964) [0.25112] [−1.23222] [1.56563] [0.23657] [2.61994] [−1.07612] d(russia(-2),2) −0.172165 −1.052301 −0.614680 −0.357589 0.218454 −0.614791 (0.23751) (0.29743) (0.25931) (0.58347) (0.11571) (0.24581) [−0.72489] [−3.53803] [−2.37041] [−0.61287] [1.88801] [−2.50106] d(united_arab_emirates(-1),2) −0.072248 0.161494 −0.509373 0.532044 0.008496 0.260652 (0.17407) (0.21799) (0.19006) (0.42764) (0.08480) (0.18016) [−0.41504] [0.74083] [−2.68009] [1.24414] [0.10018] [1.44675] d(united_arab_emirates(-2),2) −0.273213 0.062751 −0.240731 0.124978 0.111642 −0.180425 (0.11124) (0.13930) (0.12145) (0.27327) (0.05419) (0.11513) [−2.45615] [0.45047] [−1.98213] [0.45734] [2.06015] [−1.56718] d(qatar(-1),2) −0.025555 −0.074618 −0.031972 −0.265284 −0.147855 −0.084272 (0.09834) (0.12315) (0.10737) (0.24158) (0.04791) (0.10178) [−0.25987] [−0.60592] [−0.29778] [−1.09811] [−3.08625] [−0.82800] d(qatar(-2),2) −0.014468 0.172968 −0.062339 0.289711 −0.035773 0.029333 (0.10325) (0.12929) (0.11273) (0.25364) (0.05030) (0.10686) [−0.14013] [1.33778] [−0.55301] [1.14221] [−0.71121] [0.27451] d(norway(-1),2) 0.077425 1.147199 −1.346619 2.220011 −0.805764 1.156541 (0.42838) (0.53645) (0.46771) (1.05237) (0.20869) (0.44336) [0.18074] [2.13849] [−2.87917] [2.10954] [−3.86100] [2.60858] d(norway(-2),2) 0.404326 0.839206 0.093490 0.330439 −0.336213 1.285753 (0.50932) (0.63782) (0.55609) (1.25123) (0.24813) (0.52714) [0.79385] [1.31573] [0.16812] [0.26409] [−1.35499] [2.43911] d(venezuela(-1),2) 0.178154 0.437371 −1.817894 1.189869 −0.241868 −0.184729 (0.30102) (0.37697) (0.32866) (0.73951) (0.14665) (0.31155) [0.59183] [1.16023] [−5.53115] [1.60900] [−1.64929] [−0.59293] d(venezuela(-2),2) 0.066003 1.183208 −0.282184 1.850497 −0.213837 0.643888 (0.43158) (0.54047) (0.47121) (1.06025) (0.21026) (0.44668) [0.15293] [2.18923] [−0.59885] [1.74534] [−1.01704] [1.44150] c −51.81977 51.90932 −29.81161 −21.78037 −64.23873 10.92664 (145.838) (182.632) (159.230) (358.274) (71.0485) (150.940) [−0.35532] [0.28423] [−0.18722] [−0.06079] [−0.90415] [0.07239] var: vector autoregression burakov: elasticity of energy intensity on a regional scale: an empirical study of international trade channel international journal of energy economics and policy | vol 6 • issue 1 • 201672 export-import transactions (such as china), or countries whose gdp does not depend signifi cantly on exports (as in the case of the united states and france export share less than 30%). secondly, in cases of economies that are heavily reliant on exports (e.g., the netherlands), sensitivity to changes in energy intensity (technological shocks) tends to be high, and reaction occurs within 1-2 periods. third, on average, countries exporting consumer goods are more responsive to changes in international markets (expressed through technological shocks) than countries that export oil. variance decomposition of the two samples shows that, on average, the response in the fi rst sample (oil exporters) occurs after 4-6 periods (with the exception of countries with a low energy elasticity), while, reaction to technological shocks of countries exporting consumer goods occurs with a lag of 1-3 periods. this result confi rms our assumption about a higher sensitivity table 10: unrestricted var model of cross-country relationship of energy intensity for manufacturing export countries variable d(china,2) d(france,2) d(germany,2) d(spain,2) d(usa,2) d(netherlands,2) d(china(-1),2) −0.254451 0.110341 0.105300 0.090578 0.031424 0.268896 (0.20897) (0.06889) (0.04934) (0.04556) (0.07204) (0.08397) [−1.21766] [1.60168] [2.13432] [1.98795] [0.43622] [3.20212] d(china(-2),2) 0.038419 0.106855 −0.025158 −0.009328 0.138679 0.112511 (0.17854) (0.05886) (0.04215) (0.03893) (0.06155) (0.07175) [0.21518] [1.81538] [−0.59680] [−0.23960] [2.25312] [1.56813] d(france(-1),2) −1.761863 −0.383745 −0.772653 −0.042688 −0.176686 −0.190097 (0.94605) (0.31189) (0.22336) (0.20628) (0.32613) (0.38017) [−1.86234] [−1.23040] [−3.45921] [−0.20694] [−0.54176] [−0.50003] d(france(-2),2) −1.570775 0.365377 0.361713 0.480917 −0.649575 0.983176 (1.07526) (0.35449) (0.25387) (0.23445) (0.37068) (0.43210) [−1.46083] [1.03072] [1.42480] [2.05122] [−1.75240] [2.27534] d(germany(-1),2) 1.940901 −0.212446 −0.794480 0.543077 −0.234250 −0.010816 (0.87372) (0.28804) (0.20628) (0.19051) (0.30120) (0.35111) [2.22142] [−0.73755] [−3.85138] [2.85068] [−0.77772] [−0.03081] d(germany(-2),2) 0.625334 −0.181126 −0.423527 0.205164 −0.056646 −0.708988 (0.91867) (0.30286) (0.21690) (0.20031) (0.31670) (0.36917) [ 0.68069] [−0.59805] [−1.95266] [1.02423] [−0.17887] [−1.92048] d(spain(-1),2) −0.678678 −0.014833 −0.364513 −0.386597 −0.335335 −0.579673 (0.85141) (0.28069) (0.20102) (0.18564) (0.29351) (0.34214) [−0.79712] [−0.05284] [−1.81334] [−2.08246] [−1.14250] [−1.69423] d(spain(-2),2) −1.872148 0.150102 0.461050 −0.462302 −0.359663 −0.078446 (0.85400) (0.28154) (0.20163) (0.18621) (0.29440) (0.34318) [−2.19221] [0.53314] [2.28662] [−2.48271] [−1.22167] [−0.22858] d(usa(-1),2) 0.323341 −0.281083 0.003633 0.218068 −0.546308 −0.554621 (0.65679) (0.21653) (0.15507) (0.14321) (0.22642) (0.26393) [0.49231] [−1.29815] [0.02343] [1.52273] [−2.41284] [−2.10136] d(usa(−2),2) 0.000359 0.057893 0.579845 −0.241848 −0.279448 −0.167368 (0.67635) (0.22297) (0.15968) (0.14747) (0.23316) (0.27179) [0.00053] [0.25964] [3.63118] [−1.63996] [−1.19853] [−0.61579] d(netherlands(-1),2) 0.344824 −0.003784 0.582067 −0.210818 0.048885 −0.168971 (0.83110) (0.27399) (0.19622) (0.18122) (0.28651) (0.33398) [0.41490] [−0.01381] [ 2.96637] [−1.16336] [0.17063] [−0.50593] d(netherlands(-2),2) 0.096747 −0.553355 −0.279843 −0.234655 0.472684 −0.513454 (0.76235) (0.25132) (0.17999) (0.16622) (0.26281) (0.30635) [0.12691] [−2.20175] [−1.55477] [−1.41168] [1.79861] [−1.67602] c 41.23731 1.678408 −5.789537 −16.42414 10.07712 −7.478694 (100.579) (33.1583) (23.7467) (21.9306) (34.6729) (40.4183) [0.41000] [0.05062] [−0.24380] [−0.74892] [0.29063] [−0.18503] var: vector autoregression table 11: results of model’s diagnostic testing for oil-exporting countries type of test results lags lm statistics p value var residual serial correlation lm tests 1 38.94815 0.3385 2 33.12311 0.6062 3 40.07817 0.2941 stability condition all roots lie within the circle. var satisfi es stability condition heteroscedasticity test (white) 0.3369 normality test 0.6993 var: vector autoregression table 12: results of model’s diagnostic testing for manufacturing export countries type of test results lags lm statistics p value var residual serial correlation lm tests 1 45.21587 0.1396 2 38.49125 0.3574 3 35.30519 0.5014 stability condition all roots lie within the circle. var satisfi es stability condition heteroscedasticity test (white) 0.2904 normality test 0.9307 var: vector autoregression burakov: elasticity of energy intensity on a regional scale: an empirical study of international trade channel international journal of energy economics and policy | vol 6 • issue 1 • 2016 73 of economies that export consumer goods due to availability of substitute products on markets for consumer goods. 5. discussion and conclusion this study is devoted to the issue of energy elasticity at the regional scale. we have posed a question, whether dependence of energy intensity of one regions from others does exist at global (regional) scale. the second task is closely related with an attempt of testing energy elasticity dependence on the channel of international trade. the hypothesis is that in conditions of competitive pressure, a technological shock (reducing energy intensity), ceteris paribus, should lead to a similar reduction in energy intensity in countries-competitors. verification of the first hypothesis graph 1: (a-f) variance decomposition (energy elasticity of oil-exporting countries to competitors’ shocks in energy intensity) a d e f b c graph 2: (a-f) variance decomposition (energy elasticity of manufacturing export countries to competitors’ shocks in energy intensity) d e f ba c burakov: elasticity of energy intensity on a regional scale: an empirical study of international trade channel international journal of energy economics and policy | vol 6 • issue 1 • 201674 confi rmed existence of dependencies between energy intensities of different economies at the regional level. verifi cation of the second hypothesis also confi rmed existence of energy intensity’s sensitivity to technological shocks in international markets for sampled countries. in this case, energy elasticity of countries-oil exporters is signifi cantly lower and the reaction pace is slower in contrast to consumer goods’ exporting countries. confi rmation of these hypotheses provides space for further research. in particular, perspective areas of research are defi nition of intra-regional dependencies of energy intensity. also development of indicators to assess energy intensity’s elasticity is of great importance as well as development of strategies for managing elasticity of energy effi ciency at the national level, especially in case of energy market anemia and energy stagnation in a number of countries. references amador, j. (2011), energy content in manufacturing exports: a crosscountry analysis. banco de portugal working papers. april. bernstein, m., griffi n, j. (2006), regional differences in the priceelasticity of demand for energy. national renewable energy laboratory. subcontract report nrel/sr-620-39512. february. burakov, d.v. (2015), energy effi ciency in rent-seeking economies: is credit capable of breaking the energy curse? international journal of energy economics and policy, 5(3), 677-685. eichhammer, w., mannsbart, w. (1997), industrial energy effi ciency: indicators for a european cross-country comparison of energy effi ciency in the manufacturing industry. energy policy, 25, 759-772. florax, r., mulder, p., de groot, h. (2011), improving energy effi ciency through technology trends, investment behaviour and policy design. cheltenhamn: edward elgar publishing. p352. gunay, e., ceylan, d. (2010), energy efficiency trends and policies: cross-country comparison in europe. ecomod paper, no. 259600038. havlik, p. (1998), export competitiveness of central and eastern europe, in: ‘the competitiveness of transition economies’, oecd. p72-92. hillman, a., bull, w. (1978), energy, the heckscher-ohlin theorem, and u.s international trade. american economic review, (3), 96-106. howarth, r.b., schipper, l., duerr, p.a., strøm, s. (1991), manufacturing energy use in8 oecd countries. energy economics, 13, 135-142. huntington, h.g. (2010), structural change and u.s. energy use: recent patterns. energy journal, 31, 25-39. jacobsen, h. (2013), export of energy technology: the case of denmark. mpra paper no. 51796, november. jorgenson, d.w. (1984), the role of energy in productivity growth. energy journal, 5, 11-26. li, l. (2010), an empirical analysis of relationship between export and energy consumption in shandong province. international journal of business and management, 5(3), 214-216. liu, n., ang, b.w. (2007), factors shaping aggregate energy intensity trend for industry: energy intensity versus product mix. energy economics, 29, 609-635. markandya, a., pedroso-galinato, a., streimikiene, d. (2006), energy graph 3: (a-f) impulse responses for oil exporting countries a c e f d b graph 4: (a-f) impulse responses for manufacturing export countries a c d e f b burakov: elasticity of energy intensity on a regional scale: an empirical study of international trade channel international journal of energy economics and policy | vol 6 • issue 1 • 2016 75 intensity in transition economies: is there convergence towards the eu average? energy economics, 28(1), 121-145. miketa, a. (2001), analysis of energy intensity developments in manufacturing sectors in industrialized and developing countries. energy policy, 29, 769-775. miketa, a., mulder, p. (2005), energy-productivity across developed and developing countries in 10 manufacturing sectors: patterns of growth and convergence. energy economics, 27, 429-453. mulder, p., de groot, h. (2004), decoupling economic growth and energy use. an empirical cross-country analysis for 10 manufacturing sectors. tinbergen institute discussion paper. march. mulder, p., de groot, h. (2010), energy intensity across sectors and countries. empirical evidence 1980-2005. cpb netherlands bureau for economic policy analysis. cpb discussion paper no. 171. march. mulder, p., de groot, h. (2012), structural change and convergence of energy intensity across oecd countries, 1970–2005. energy economics, 34(6), 1910-1921. nilsson, l. (1993), energy intensity in 31 industrial and developing countries, 1950-88. energy, 18, 309-322. phoumin, h., kimura, s. (2014), analysis on price elasticity of energy demand in east asia: empirical evidence and policy implications for asean and east asia. eria discussion paper series. april. rezitis, a., ahammad, s. (2015), the relationship between energy consumption and economic growth in south and southeast asian countries: a panel vector autoregression approach and causality analysis. international journal of energy economics and policy, 5(3), 704-715. srinivasan, t., archana, v. (2009), india in the global and regional trade: determinants of aggregate and bilateral trade flows and firms’ decision to export. indian council for research of international economic relations. working paper no. 232. february. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 2 • 202392 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(2), 92-99. using generalized linear model to determine the impact of oil price fluctuations on the egyptian public budget hamdy ahmad aly alhendawya1, mohammed galal abdallah mostafaa1*, sozan galal elkananib2, neveen mohsen ahamed zakic3, mousa gowfal selmeya1 1department of economic, faculty of commerce, mansoura university, egypt, 2department of economic, higher institute of administrative science, belqas, egypt. 3department of applied statistics and insurance, faculty of commerce, mansoura university, egypt. *email: drmohammed2008@yahoo.com received: 15 november 2022 accepted: 14 february 2023 doi: https://doi.org/10.32479/ijeep.14029 abstract oil is regarded as one of the most significant energy sources in the world due to the enormous impacts it has on the level of the economy as a whole in both developing and developed countries and for both producing and importing countries. so, this study aims to know the effects of fluctuations in oil prices on the egyptian public budget during the period from 2000 to 2022. for this purpose, the study used the glm (generalized linear model) model, which is one of the first studies to use this model in economics. the study concluded that oil price fluctuations negatively affect the public budget, which means that there is a positive relationship between oil price fluctuations and the general budget deficit in egypt as a result of egypt being one of its importing countries. therefore, the rise in oil prices leads to an increase in the public budget deficit, and its low prices may contribute to a decrease in this deficit. keywords: oil price, public budget, egypt, generalized linear model jel classifications: e39, c5, h6 1. introduction oil is an essential element in all different economic operations and activities due to the important role it plays in operating machinery and equipment, as it helps convert raw production materials into outputs that meet different needs. in economic sectors, petroleum products are used for their activities and operations or to transfer their production from manufacturers to markets. oil is not only the best-selling product in the world, but it is also the most important source of energy for economic activity. changes/ fluctuations in oil prices have always become a research problem. also, the impact of oil prices on the main macroeconomic variables such as energy subsidies, economic growth, inflation and unemployment is an economic problem that must be addressed (peng and drakeford, 2020; mostafa, 2021; mostafa and mater, 2021; mostafa and selmy, 2022). fluctuations in oil prices occur mainly due to imbalances between demand and supply, which result from the interaction of many factors that directly affect the global oil market (such as global production capacities-global economic growth-opec productionchange in crude oil stocks and market structure) or indirectly (such as future expectations in the oil market and the state of uncertainty). other reasons that lead to fluctuation in the global price of oil include fluctuations in production due to political factors such as wars and conflicts, as well as economic sanctions that are imposed on some countries, especially oil-producing countries, which may sometimes have a greater impact on oil prices than economic factors and lead to its volatility. ascending and descending. in addition to environmental problems, issues of technological progress, and the dominance of a few major exporters and importers of the global oil market. likewise, the lack and unavailability of information on some aspects such as the elasticity of income demand and this journal is licensed under a creative commons attribution 4.0 international license mostafa, et al.: using generalized linear model to determine the impact of oil price fluctuations on the egyptian public budget international journal of energy economics and policy | vol 13 • issue 2 • 2023 93 prices in the long term, and the reactions of opec countries and other countries that are likely to affect the supply of oil, resulting in a state of uncertainty regarding the supply of oil and the future production plans of the countries of the organization and the producing countries the other (jawad, 2013). moreover, the global collapse in oil demand due to the covid-19 pandemic has put pressure on the budgets of oil exporting countries, while the excess demand for oil during the first and second oil crises in 1973 and 1979 had a detrimental effect on the budgets of importing countries (zulfigarov and neuenkirch, 2020). hence, the prospects for recovery in oil prices are highly uncertain. whereas, oil futures contracts are expected to witness a slow and partial recovery (imf, 2021). moreover, escalating geopolitical tensions between russia and ukraine and in the middle east are adding to oil supply concerns, and this is contributing to rising inflation and concerns about economic recovery (world economic forum, 2022). from here, we find that the fluctuation in oil prices has great economic repercussions, and these repercussions cause effects on the economy in general through many channels, including the budget deficit channel, the transportation costs channel, the external debt channel, etc. (imf, 2021; peng and drakeford, 2020). oil prices greatly affect transportation costs in general, including marine transportation. where the rise in oil prices leads to an increase in the costs of maritime transport and the increase in the costs of international trade in developing countries, and reduces the importance of competitive advantages resulting from low costs, which works to move and change production sites. especially since 2004, the flexibility of container transport prices has increased to changes in oil prices, which means that its impact has become greater, because of its significant impact on the high cost of fuel for ships, and then the high shipping costs. as for the general budget channel, we find that the studies that dealt with the impact of fluctuations in oil prices on it were divided into two types. the first of which is (abimanyu, 2016; akhmedov, 2019; saud et al., 2020; laan et al., 2021) and believes that the fluctuation in oil prices positively affects the public budget, and this happens either to oil-exporting countries on the one hand, as this fluctuation is due to the rise in oil prices. oil, as it is expected that the state’s revenues will increase from its export process, which positively affects the budget or the importing country, in the event of a decrease in oil prices, as this contributes to achieving a surplus in the funds directed to finance the purchase of oil, which positively affects the general budget. and the second type is like a study (imf, 2015; afangideh et al., 2018; al shukri, 2021; sun et al., 2022) and considers that the fluctuation in oil prices negatively affects the general budget, and this is either for the exporting countries in the event of a decrease in prices oil or to importing countries, in case of high prices. in the recent period, especially after the corona pandemic in 2020, interest has increased in searching for the effects caused by fluctuations in oil prices on the economies of different countries. this study is distinguished from others in that it is one of the few studies that focus on the general budget, especially in egypt as an importing country that depends on oil on the one hand, and that it is one of the first studies to use the glm model and apply it in the economy on the other hand. accordingly, these fluctuations in oil prices raise many questions about the challenges and opportunities that could face the general budget in egypt as a result. hence, the main objective of this study is to analyze and measure the impact of fluctuations in international oil prices on the general budget in egypt during the period (1990-2022). this study has been divided into five sections as follows: section (i): introduction and literature review. section (ii) data and methodology. section (iii): data and methodology. section (iv) empirical result and discussion. section (v) conclusion. 2. literature review 2.1. studies dealing with the positive impact of oil price fluctuations on the general budget of exporting and importing countries there is no doubt that the downward fluctuations in oil prices have positive effects on the budgets of oil-importing countries as a result of the surplus achieved by these countries from the funds directed to purchase oil, in addition to the fact that the decline in oil prices exerts other indirect effects on the public budget through the decrease in subsidies directed to energy materials and the decrease in costs transport, low inflation rates and other indirect effects on the general budget. this matter does not stop at this point, but the previous effects result in positive social effects that exert positive effects on the general budget. on the contrary, for oil-exporting countries, the positive effects occur in the event of a rise in oil prices, as this contributes to an increase in the revenues generated from the oil export process, which leads to positive effects on the public budget. many studies have discussed the positive effects of fluctuations in oil prices on the public budget, and among these studies is a study (abimanyu, 2016; saud et al., 2020), which showed that there is a positive relationship between fluctuations in oil prices and public expenditures in the short term, while this relationship is negative in the long run. in kazakhstan, a study (akhmedov, 2019) showed that the rise in oil prices during the period (2011-2013) led to unprecedented levels of government revenues. the effect of the additional revenue generated by the increase in oil prices depends critically on the wise management of these oil resources (lakuma, 2020). on the other hand, the decline in oil prices always benefits the importing economies as an incentive to align domestic prices with international prices, as well as gradually raising taxes, which increases the state’s public revenues (laan etal., 2021). 2.2. the negative impact of oil price fluctuations on the public budget the negative effects of oil price fluctuations on the public budget occur either in the case of low prices for oil-exporting countries or in the case of high prices for oil-importing countries. mostafa, et al.: using generalized linear model to determine the impact of oil price fluctuations on the egyptian public budget international journal of energy economics and policy | vol 13 • issue 2 • 202394 the decline in oil prices constitutes a triple macro-financial shock for exporting countries as a result of: a significant loss of revenues received by the state, a negative economic impact on domestic non-oil activity, and increased spending pressures arising from the policy response to the effects of covid-19 (imf, 2015). a study (kandil and markovski, 2020; al shukri, 2021) concluded that fluctuations in global crude oil prices negatively affect exporting countries through the public budget channel and the public debt channel. in the united arab emirates, the decline in oil prices at $35.6 in 2020; this led to a sharp deterioration in the public budget surplus, in light of the oil price estimate in the public budget at $67.1. the decline in the global price of crude oil, which began in mid2014, had major repercussions in all countries of the middle east, not only for net oil exporters, but also for net oil importers, such as egypt, jordan and lebanon, which are linked in one way or another to the oil-producing gulf countries. the drop in oil prices represents a second major shock to the region in the early twenty-first century-as it imposes constraints on public finances, specifically lower public revenues (beck and richter, 2021). in nigeria, a study (afangideh et al., 2018) revealed that crude oil prices and terrorism have a significant negative impact on government revenues in the short and long term. as the study (adedokun, 2018) demonstrated, there is a negative relationship between oil revenues and total government expenditures in the short term, and it is also clear that oil shocks greatly affect political variables in the short term and transmit effects on other macroeconomic variables in the long term. (raouf, 2021) confirmed the impact of oil shocks on current and capital government spending. it was found that oil price shocks as a result of its high prices affect government capital expenditure positively in oil-exporting countries and negatively in oilimporting countries. in china, when the price of crude oil changes, public investment in the public utility sector decreases (sun et al., 2022). in addition, the study showed that fluctuations in oil prices are among the important factors affecting the performance of the public budget. this study concluded that there are two different effects of these fluctuations on the oil-exporting countries: the first is positive through increasing their financial returns and achieving financial surpluses in the financial budget when oil prices rise. as for the second, it is considered negative due to the decrease in their financial returns and the accompanying increase in the general budget deficit, when oil prices drop. 3. data and methodology 3.1. data table 1 shows the variables used in the study. figure 1 shows data on the oil price and the public budget deficit ratio to the gdp in egypt during the period from 2000 to 2022. 3.2. methodology to determine the impact of oil price fluctuations on the egyptian public budget, generalized linear regression models were used. the generalized linear model (glm) is seen as a regression model, in which the dependent variable follows one of the probability distributions that belong to the exponential family, and these models are less restrictive than the traditional regression models. the generalized linear models are based on a set of assumptions, which are as follows (murphy et al., 2000; al-hosary and mohammed, 2017): 1. the dependent variables are not required to follow a normal distribution, but they are supposed to follow an exponential distribution 2. in generalized models, heteroskedasticity is allowed 3. in the generalized models, the relationship is not required to be linear between the dependent variable and the independent variables, but it is assumed that there is a linear relationship between the link function and the independent variables, and then some non-linear models can be reconciled using the generalized linear models 4. random errors are independent and are not required to follow a normal distribution 5. parameters are estimated using the maximum likelihood estimation method as well as the ordinary least squares (ols) method. the generalized linear model differs from the linear regression model in that the expected value of the response variable is replaced by a link function (g(µ)=ƞ), where ƞ is a linear combination of explanatory variables, and the main objective of using the link function is to make the error variance more stable. the general picture of generalized linear models is as follows (murphy et al., 2000; al-hosary and mohammed, 2017): y g xi i i i= +( )β ε where: xi: the set of independent variables that affect the value of the dependent variable. g: is the link function, and it is a function used to show the relationship between the expected value of the response variable and the explanatory variables. ε: it is the random error and represents the unexpected variables. yi: is the dependent variable, which is a random variable that follows one of the exponential family distributions: • normal distribution • gamma distribution • poisson distribution • binomial distribution • negative binomial distribution • inverse gaussian distribution • tweedie distribution. table 1: variables and source of data variables kind source budget defecit dependent variable egyptian central bank oil price independent variable statista database source: author mostafa, et al.: using generalized linear model to determine the impact of oil price fluctuations on the egyptian public budget international journal of energy economics and policy | vol 13 • issue 2 • 2023 95 components of the generalized linear model (al-hosary and mohammed, 2017): the generalized linear model consists of three components (): 1. random component: it means the distribution followed by the dependent variable y, as it is assumed in generalized models that the dependent variable follows one of the exponential distributions. 2. systematic component: that is, the linear predictor (ƞ) linear predictor, which means the set of features (β) and the set of explanatory variables (x1, x2,…., xp), and then η β= xi t represents the regular element. 3. link function: it is a function used to link the random component to the regular component, and it is used to clarify the relationship between the expected value of the dependent variable and the linear predictor, and the linking function is denoted by the symbol g (.). � � � = ( ) = ∴ ( ) = g x x g i i i t i i i i t i µ β η µ β  where g(⋅): link function xi: vector of independent variables x x x xi i ip i=           1 2 ) : : xi t : transpose of vector of independent variables x x xi ip i t 1, , :…  β: vector of parameters β β β =           1  p � � � hence, it is important to address both the exponential distributions and the exponential dispersion distributions briefly, as well as addressing what the linking function is; this is as follows: 1. exponential family distribution assuming that we have a random variable y with one parameter, θ, it is said that this distribution follows one of the exponential distributions if the probability function can be written for it in the following form (al-hosary and mohammed, 2017): + = −c y f y y bi i i i i i i( )] ( ; ) exp[ ( ) ( )θ θ θ ɵ: natural parameter exponential distributions include a set of probability distributions as follows: a. poisson distribution assuming that we have a discrete random variable (y) with parameter (λ), then this variable follows a poisson distribution if its probability function is as follows: f y y e y i i i i i i ; ! λ λ λ( ) = − the probability function of the poisson distribution can be put on the general form of the probability function of exponential distributions, as follows (al-hosary and mohammed, 2017): f y y y f y y y i i i i i i i i i i i i ; ! ; exp log log λ λ θ λ λ λ λ ( ) = ( ) = ( )− − ( )  − hence f y b c y y i i i i i i i i i ; ! λ λ θ θ λ θ ( ) = = ( ) ( ) = = ( ) ( ) = − ( ) log exp log figure 1: egyptian economic data source: statista data base and egyptian central bank mostafa, et al.: using generalized linear model to determine the impact of oil price fluctuations on the egyptian public budget international journal of energy economics and policy | vol 13 • issue 2 • 202396 b. binomial distribution assuming that we have a discrete random variable (y) with parameter ( ri ), this variable follows a binomial distribution if its probability function is as follows (al-hosary and mohammed, 2017): f y r n y r ri i i i i y i n yi i i;( ) =       −( ) − 1 the probability function of a binomial distribution can be put in the general form of the probability function of exponential distributions, as follows: f y r n y r ri i i i i y i n yi i i;( ) =       −( ) − 1 f y r n y y r n r yi i i i i i i i i;( ) =      + ( )+ −( )+     exp log log log log1 1 1−          ri f y r y r r n r n yi i i i i i i i i ;( ) = −      + −( )+         exp log log log 1 1      hence = −      log τ τ θi i 1 1 b n r ni i i i iθ θ( ) = − −( ) = + ( ) log log exp1 1 c y n yi i i ( ) =      log 2. exponential dispersion family exponential dispersion distributions differ from exponential distributions in that the former contains a ϕ scale parameter (constant) (also called dispersion parameter) in addition to the natural parameter of the distribution (θ), and then the distribution is said to follow one of the exponential dispersion distributions if the probability function can be written in the following form (al-hosary and mohammed, 2017): f y y b a c yi i i i i i i; , ( ) ,θ φ θ θ φ φ( ) = − ( ) + ( )         exp examples of such distributions are: a. normal distribution suppose we have a random variable connected (y) with two parameters ( , )µ θi i 2 , then this variable follows a normal distribution if its probability density function is as follows(alhosary and mohammed, 2017): f y ei i yi i ; ,µ σ πσ µ σ2 2 2 1 2 2 2( ) = − −( ) the probability density function of the normal distribution can be put in the general form of the probability function of the exponential dispersion distributions as follows (al-hosary and mohammed, 2017): f y e f y y i i y i i i i i ; , ; , µ σ πσ µ σ πσ µ σ2 2 2 2 2 1 2 2 2 2( ) = ( ) = − ( )− − −( ) exp log −−( )        ( ) = − ( )− + − µ σ µ σ πσ σ µ σ i i i i i if y y y 2 2 2 2 2 2 2 2 2 2 ; , exp log −−         ( ) = ⋅ −      − − µ σ µ σ µ µ σ i i i i i if y y y 2 2 2 2 2 2 2 1 2 2 2 ; , exp 11 2 2 2 log πσ( )         hence = µ θi i b i i iθ µ θ ( ) = = 2 2 2 2 a( )φ σ= 2 = − ( ) = − ( )y y c yi i i 2 2 2 2 2 1 2 2 2 1 2 2 σ πσ φ πφ φlog log( ) , b. gamma distribution assuming that we have a continuous random variable (y) with two parameters (α, n), then this variable follows a gamma distribution if its probability density function is as follows (al-hosary and mohammed, 2017): y f y ei i i i a iα λνλ α λ α − −( ) =1 ; , ( )r the probability density function of the gamma distribution can be put in the general form of the probability function of exponential dispersion distributions as follows (al-hosary and mohammed, 2017): y f y ei i i i yi iα α λλ α λ α − −( ) =1 ; , ( )γ suppose: λi=α/µi y f y ei i i i yi iα α λλ α λ α − −( ) =1 ; , ( )γ f y y i i i y i i i ; , ( ) ( )λ α α α α µ α α α µ ( ) = − − + − −    exp log log log log γ 1 f y y i i i i i yi i ; , ( )λ α α µ α α α( ) = − −      + − +     −exp log log log log 1 γ(( )]α mostafa, et al.: using generalized linear model to determine the impact of oil price fluctuations on the egyptian public budget international journal of energy economics and policy | vol 13 • issue 2 • 2023 97 hence b i i iθ µ θ( ) = ( ) = − −( )log log a a ( )φ = 1 = − + − ( )( ) ( ) ,α α α α φ1 log log logy c yi iγ c. negative binomial distribution: assuming that we have a random variable connected (y) with a marker (ri), this variable follows a negative binomial distribution if its probability density function is as follows (al-hosary and mohammed, 2017): f y r y n y r ri i i i i i n i yi i;( ) = + −      −( ) 1 1 the probability density function of a negative binomial distribution can be put in the general form of the probability function of exponential dispersion distributions as follows (al-hosary and mohammed, 2017): f y r y n y r r f y r y n i i i i i i n i y i i i i i i; ; ( ) = + −      −( ) ( ) = + − 1 1 1 exp log yy n r y r supose i i i i i      + ( )+ −     )log log(1 = −log( )1 r θ so e rθ = −1 . = − ∴1 e rθ f y r y n y n e yi i i i i i i;( ) = + −     + −( )+    exp log log log 1 1 θ 1 1− −( )( )e θ f y r y n y n e yi i i i i i i;( ) = + −     + −( )+        exp log log 1 1 θ θ hence =θ θi i b n ei iθ θ( ) = −( )log 1 a( )φ =1 = + −      ( )log y n y c yi i i i 1 ,φ 4. results and discussion 4.1. test of goodness of fit for the data in the beginning, test of goodness of fit for the data is made for the data to find out the probability distributions of the dependent variable (the general budget deficit), based on the kolmogorovsmirnov, anderson-darling test, and the results are as follows: it is clear from table 2 that the data on the dependent variable (the general budget deficit) according to (kolmogorov-smirnov, anderson-darling) follows a log-gamma distribution at the significant level (0.2), (0.1), and (0.05) and (0.02) and (0.01). we note from table 3 that the analysis of the linear regression model can be performed depending on the gamma distribution by linking the independent variables to the expected value of the dependent variable through the log link function. 4.2. test of goodness of fit for whole model the researcher conducted the omnibus test to see if the model is significant or not, as shown in the table 4. we note from table 4 that the model is significant at 5% and 10%. 4.3. model parameters estimation estimates of the model parameters and standard errors were obtained for the model with the value of the statistic and its significance as in the table 5. table 3: model information model information dependent variable budget deficit probability distribution gamma link function log source: spss v. 23 output table 4: omnibus test omnibus testa likelihood ratio χ2 df significant 123.102 21 0.001** source: spss v. 23 output **significance at α= 5% ; 10% table 2: test of goodness of fit for the data to find out the probability distributions of the dependent variable (the general budget deficit) log-gamma kolmogorov–smirnov sample size 22 statistic 0.18912 p 0.05618 α 0.2 0.1 0.05 0.02 0.01 critical value 0.1513 0.17302 0.19221 0.21493 0.23059 reject? yes yes no no no anderson–darling sample size 22 statistic 1.7302 α 0.2 0.1 0.05 0.02 0.01 critical value 1.3749 1.9286 2.5018 3.2892 3.9074 reject? yes no no no no source: easy fit program output mostafa, et al.: using generalized linear model to determine the impact of oil price fluctuations on the egyptian public budget international journal of energy economics and policy | vol 13 • issue 2 • 202398 the previous table shows that oil price fluctuations have a negative impact on the egyptian public budget, meaning that there is a positive relationship between oil price fluctuations and budget deficit in egypt, and these effects are significant at α = 5%. this is due to the fact that fluctuations in oil prices raise a wide controversy because of their important effects, given that egypt is an oil importer (for crude oil and petroleum derivatives), and therefore it is more vulnerable to the shocks that occur in its prices, especially in light of the recent decisions that were taken regarding the gradual reduction to support energy within the framework of its reform program since 2016. this happens through several channels, including. *the fluctuations in international oil prices negatively affect the industry in egypt, and this means that the occurrence of a positive shock or the increase in oil prices led to a decrease in the growth rate of industrial output, in proportion to the nature of the inverse theoretical relationship between the two variables in an oil-importing country such as egypt that suffers from there is a gap between production and domestic consumption of oil. there is no doubt that the negative impact of industrial output leads to an increase in the budget deficit as a result of the subsidies that the state may direct to support this sector and the reduction that may be witnessed in taxes collected from this sector. **fluctuations in oil prices increase lead to a rise in the prices of energy materials and then a rise in the rate of inflation, which in turn leads to an increase in public spending directed to social support in order to overcome the negative effects that may be caused by inflation. ***rising transportation costs and demanding higher wages, which may lead to an increase in public expenditures on the one hand, and a decrease in public revenues on the other hand. the estimated model is as follows: log μy = (12.342) + (9.544) x1 where μy: expected value for budget deficit x: oil price 5. conclusion and policy implications the study is an attempt to contribute to the debate about the impact of fluctuations in international oil prices on the public budget, as it is one of the important issues raised at all global, regional and local levels, which is still a matter of great controversy, especially after the succession of fluctuations in recent years. where most of the applied studies in this field focus on the oil-exporting countries, as well as focus on the impact on economic growth in general without more focus on the egyptian public budget. at the level of the egyptian economy, these fluctuations in oil prices raise a wide controversy because of their important effects as an oil-importing country, and therefore it is more vulnerable to the shocks that occur in its prices, especially in light of the recent decisions that were taken regarding the gradual reduction of energy subsidies within the framework of its program the reformist reform movement since 2016. thus, these fluctuations are likely to affect many aspects of the egyptian economy, the most important of which are: transportation costs, the value of oil imports, subsidies for oil products, inflation and other important variables. this study aimed to analyze and measure the impact of fluctuations in international oil prices on egyptian public budget during the period (2000-2022) using generalized linear model (glm). to achieve this goal, the theoretical background of the relationship between oil prices and the general budget was addressed, and previous literature was reviewed. the study concluded that oil price fluctuations negatively affect the public budget, which means that there is a positive relationship between oil price fluctuations and the general budget deficit in egypt as a result of egypt being one of its importing countries. therefore, the rise in oil prices leads to an increase in the public budget deficit, and its low prices may contribute to a decrease in this deficit. based on the foregoing, therefore, the study recommends that hedging against uncertainty regarding fluctuations in international oil prices is an important element in order to maintain economic stability in egypt and then the stability of the general budget by facing fluctuations in oil prices in the event of a rise, and trying to maximize benefit from them. in the event of a decline in the short term, work on developing a multi-pronged plan in the long term. references abimanyu, y. (2016), oil price, government revenue, export value, and economic growth: indonesia case. kajian ekonomi dan keuangan, 20(3), 1-10. adedokun, a. (2018), the effects of oil shocks on government expenditures and government revenues nexus in nigeria (with exogeneity restrictions). future business journal, 4(2), 219-232. afangideh, u., ujunwa, a., ukemenam, a. (2018), oil prices, armed conflict and government revenue in nigeria. international journal of emerging markets, 13(5), 1196-1210. akhmedov, e. (2019), the impact of oil price shocks on selected kazakhstan’s macroeconomic indicators. journal of international studies, 12(4), 258-271. al shukri, h. (2021), analysis of crude oil price fluctuations and their impact on the sustainability of public debt in iraq for the period (2000-2019). journal of sustainable studies, 3(4), 401-447. al-hosary, m., mohammed, a. (2017), the use of generalized linear table 5: parameter estimation parameter estimates parameter b se wald χ2 df significant r2 intercept 12.342 0.7506 497.981 1 0.000 0.42 oil price 9.544 2.526 14.268 1 0.002 source: spss v. 23 output. se: standard error mostafa, et al.: using generalized linear model to determine the impact of oil price fluctuations on the egyptian public budget international journal of energy economics and policy | vol 13 • issue 2 • 2023 99 models in auto insurance pricing complementary. journal of administrative research, 35, 53-105. beck, m., richter, t., editors. (2021), oil and the political economy in the middle east: post-2014 adjustment policies of the arab gulf and beyond. england: manchester university press. imf. (2015), the commodities roller coaster: a fiscal framework for uncertain times. united states: imf fiscal monitor. imf. (2021), special series on fiscal policies to respond to covid-19. fiscal affairs. united states: international monetary fund. jawad, m. (2013), an econometrics analysis of oil price volatility. international journal of econometrics and financial management, 1(1), 20-30. kandil, m., markovski, m. (2020), oil prices: challenges and a way forward for the united arab emirates. cairo: economic research forum. laan, t., suharsono, a., viswanathan, b. (2021), fuelling the recovery: how india’s path from fuel subsidies to taxes can help indonesia. international institute for sustainable development (iisd), available from: https://www.iisd.org/gsi/policy-briefs/fuelling-recovery-howindias-path-fuel-subsidies-taxes-can-help-indonesia lakuma, c. (2020), oil wealth in uganda: analysis of the macroeconomic policy framework. in: langer, a., ukiwo, u., mbabazi, p., editors. oil wealth and development in uganda and beyond: prospects, opportunities, and challenges. leuven: leuven university press. p127-148. mostafa, m., mater, m. (2021), using artificial neural networks to recognize the determinants of economic growth: new approach evidence from developing countries. indian journal of economics and business, 20(2),1-24. mostafa, m.g.a. (2021), the impact of energy subsidy reform on economic growth in egypt over the period from 2013 to 2020. international journal of energy economics and policy, 11(4), 31-42. mostafa, m.g.a., selmey, m.g.s.g. (2022), determinants of energy consumption in egypt “new approach”. international journal of energy economics and policy, 12(2), 175-180. murphy, k.p., brockman, m.j., lee, p.k. (2000), using generalized linear models to build dynamic pricing systems. in: casualty actuarial society forum, winter. cas monographs series, p107-139. peng, j., lee, z., drakeford, b. (2020), dynamic characteristics of crude oil price fluctuation-from the perspective of crude oil price influence mechanism. energies, 13(17), 1-19. raouf, e. (2021), oil prices shocks and government expenditure. international journal of energy economics and policy, 11(5), 78-84. saud, d., mohammed, a., talib, h. (2020), the impact of oil price fluctuations on the fiscal deficit and surplus of the public budget in iraq for the period 2004-2019. palarch’s journal of archaeology of egypt egyptology, 17(5), 1334-1345. sun, z., cai, x., huang, w. (2022), the impact of oil price fluctuations on consumption, output, and investment in china’s industrial sectors. energies, 15, 3411. world economic forum. (2022), why do oil prices matter to the global economy? an expert explains. switzerland: world economic forum. zulfigarov, f., neuenkirch, m. (2020), the impact of oil price changes on selected macroeconomic indicators in azerbaijan. economic systems, 44(4), 100814. . international journal of energy economics and policy | vol 8 • issue 3 • 201858 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(3), 58-66. estimation and analysis of wind electricity production cost in morocco ijjou tizgui1, fatima el guezar2, hassane bouzahir3*, alessandro n. vargas4 1laboratory of engineering systems and information technologies, national school of applied sciences, po box 1136, ibn zohr university, agadir, morocco, 2laboratory of engineering systems and information technologies, faculty of sciences, po box 8106, ibn zohr university, agadir, morocco, 3laboratory of engineering systems and information technologies, national school of applied sciences, po box 1136, ibn zohr university, agadir, morocco, 4universidade tecnológica federal do paraná utfpr cornélio procópio, brazil. *email: hbouzahir@yahoo.fr abstract the goal of this investigation is to evaluate, analyze and compare the cost of energy produced at nine wind farms in morocco, namely tarfaya, fem el oued, essaouira, tangier i, haouma, koudia al baïda, laayoune, tetouan i and tetouan ii. we report the economic factors that influence the wind energy cost. then, we give an easy and precise economic methodology to estimate it. the conducted analysis reveals that the minimum cost is attained at koudia al baïda park which is equal to 0.0164 €/kwh. the good result is obtained also at essaouira, tetouan i and fem el oued with a cost <0.03 €/kwh. the parks where the energy cost is between 0.03 €/kwh and 0.04‎ €/kwh are haouma, tarfaya, tetouan ii and tangier i. the park that generates energy with more than 0.04‎ €/kwh is laayoune. the sensitivity analysis reveals that for the studied wind farms, the variables which have a greatest effect on the estimated wind energy cost are the interest rate, the produced energy and the project lifetime. the estimated energy cost is not very sensitive to the variation on operation and maintenance costs. the obtained results show also that for all the studied wind farms, the obtained costs of producing one kwh of energy are less than the purchase tariff of electricity in morocco and compare favorably with solar energy production cost in morocco. thus, wind energy is economically beneficial in morocco, which is due to the important wind resources and the available concessional finance. keywords: investment cost, operation and maintenance cost, annualized cost, interest rate, capital recovery factor, levelized cost of energy jel classifications: e4, q4 1. introduction1 until a decade ago, 98.9% of moroccan energy needs come from fossil fuel with oil price at the time at around 77 €/mwh. in 2010, this country set a national plan for renewable energy with an ambitious target which is to extract 42% of its energy from renewable energy by 2020 and 52% by 20302. according to moroccan investment development agency3, morocco has invested approximately 34 billion € to achieve this plan development, 1 to unify the monetary units in this work, we note that we converted all monetary units to euro (€) by considering the following exchange rates: €/ usd=1.3 and mad/€=11. 2 according to the international energy agency, available at “www.iea.org”, (accessed on 03 september 2017). 3 moroccan investment development agency, available at “www.invest.gov. ma”, (accessed on 17 september 2017). of which 78% is conditional upon international mechanisms to finance climate, like the green climate fund. wind is a promising resource of electricity in morocco, particularly in its north, north-east and south. the average wind speed is 5.3 (m/s) at more than 90% of the kingdom territory. according to the moroccan wind atlas presented in figure 1, wind speed varies between 9.5 and 11 m/s at height of 40 m in essaouira, tangier and tetouan. it varies between 7.5 and 9.5 m/s in tarfaya, dakhla, taza and laayoune4. thus, the country onshore wind potential is estimated to be 25 gw, where 6 gw will be installed by 2030. morocco wants to bring the installed capacity of wind energy, from 280 mw in 4 according to: renewables now, available at “www.renewablesnow.com”, (accessed on 28 june 2017). tizgui, et al.: estimation and analysis of wind electricity production cost in morocco international journal of energy economics and policy | vol 8 • issue 3 • 2018 59 figure 1: moroccan wind atlas figure 2: morocco wind program. pei: integrated wind energy program tizgui, et al.: estimation and analysis of wind electricity production cost in morocco international journal of energy economics and policy | vol 8 • issue 3 • 201860 2010 to 2000 mw in 2020. to meet this aim, this developing country has launched a wind energy plan that aims to produce an annual energy of 6600 gwh by 2020. figure 2 shows the achieved wind farms and other under development at morocco. the kingdom invested 2.87 billion €. that will enable it to save annually 1.5 million tons of fuel and to match the sum of 577 million €. the last 850 mw was contracted in january, 2016 and is now under construction in five projects. its commissioning is expected between 2017 and 2020. in its tender for 850mw, morocco has announced an average wind energy cost of 23 €/ mwh and a lowest at around 19.2 €/mwh5. this new cost in the world is reinforced by the strong wind resource in morocco and available concessional finance. indeed, to support its energy plan, morocco has created an energy investment company (sie) with a capital of 90.9 million €. its funding benefits from the resources mobilized under the frame of the energy development fund with 153.8 million € as a contribution of the hassan ii fund for economic and social development and a donation from the kingdom of saudi arabia (384.6 million €) and uae (230.7 million €). an economic evaluation is essential before, during and after any energy project. it can be used to decide on energy purchases, to select on the competing technologies, to finance an energy project, to control costs, to analyze benefits or to make a decision. for that, calculating the levelized cost of energy (lcoe) per kwh is very interesting. it takes into account all costs during the system lifetime6. estimating lcoe is useful to assure expenses are paid and benefits are collected. lcoe is often used to compare competing energy producing technologies. in this study, it will be used to evaluate, analyze and compare the energy cost at nine wind farms in morocco. for specific areas and different wind turbines technology, several studies have been made by authors to analyze the wind energy economics notably the energy production cost. for instance, marafia and ashour (2003) have analyzed the cost of energy at two parks in qatar. they have compared on one hand the cost of energy generated by wind and gas turbines and on another hand the cost of energy generated by onshore and offshore wind turbines. the results have proved that the cost of energy output from a wind turbine is 0.0289 €/kwh which is low compared with 0.0342 €/kwh for energy produced by a gas turbine. for offshore wind turbines, the cost of energy is less about 8% compared with onshore one. in iran, mohammadi et al. (2016) have compared the cost of electricity delivered by four types of wind turbines in order to select the most appropriate economical turbine. the lowest value that they have obtained is 0.044 €/kwh, which is lower than the electricity price in iran (0.1 €/kwh). saeidi et al. (2013) have evaluated the energy cost produced by a vertical axis wind turbines. they have shown that this type of turbines generates more energy, especially at areas with low turbulence and low wind speed. that proved a reduction of 0.046 €/kwh in energy cost. we 5 according to: ecomena, echoing sustainability in mena, available at “www.ecomena.org”, (accessed on 15 june 2017). 6 a wind energy system is expected to operate for a limited duration which is called lifetime. also cite mostafaeipour (2013) who has conducted an economic assessment of three small wind turbines by analyzing their costs and benefits. fazelpour et al. (2017) have conducted an economic assessment in order to evaluate the energy cost in four sites and propose the suitable turbines that maximize the benefit for each one. at three towns in the south of morocco (tan-tan, laayoune and dakhla), zejli et al. (2004) have compared the cost of sea-water desalinated by vapor compression powered by wind turbines and reverse osmosis. the obtained lcoe by wind turbine is 0.05 €/kwh, which shows that using wind energy is the most interesting solution. basing on the literature, section 2 focuses on reporting the factors that influence the wind energy cost. in fact, before any wind project, it is very important for an engineer to know those factors. furthermore, an overview on methodology to estimate the wind energy cost is presented. thus, the methodology summarized in this section can be considered as a guide for an engineer outside the economy field that wants to estimate the wind energy cost for making a decision. section 3 of this work. concerns the description of nine wind farms in morocco, namely tarfaya, fem el oued, essaouira, tangier i, haouma, koudia al baïda, laayoune, tetouan i and tetouan ii. to assess the cost of the delivered energy at those parks, the available data and many economics assumptions are presented. afterwards, section 4 gives an evaluation, analysis and comparison of energy cost at the cited wind farms. to determine the effects of varying the key assumptions on lcoe, we carry out the sensitivity analysis by changing the values of interest rate, operation and maintenance costs, energy output and projects lifetime. moreover, we deal with comparing the cost of wind and solar energies in morocco. 2. methodology on estimation of wind energy production cost the purpose of this section is to analyze the most important economic indicators that influence directly the wind electricity cost and give an overview on methodology followed in the literature to estimate the net present cost (npc), the total annualized cost and finally the lcoe. figure 3 summarizes the methodology to estimate the wind energy production cost. 2.1. economic factors influencing the wind energy cost the wind electricity cost is strongly influenced by the investment cost, the operation and maintenance cost and the financing cost. those factors are defined in the following part. 2.1.1. investment cost the investment cost or initial capital cost (ic) is any cost from the project idea until the operation date. ic depends on the used technology and site. as stated by johnson (2006) and manwell et al. (2009), ic involves the turbine and its component purchase, its transportation and installation (foundation construction, installing the turbine, connection to the grid, testing, and commissioning). tizgui, et al.: estimation and analysis of wind electricity production cost in morocco international journal of energy economics and policy | vol 8 • issue 3 • 2018 61 it includes also, indirect costs such as the purchase of land, roads to access the site and legal fees. the investment cost distribution differs from one author to another. for example, for installing a small wind turbine in us. bortolini et al. (2014) have considered the investment cost distribution reported in figure 4. as one can note, the cost of the wind turbines makes more than 70% of the whole cost of wind farm project. recently, the wind turbine price has increased because of its size growth (increase in height, blades and rotor diameter), which increases its weight and the cost of its installation (transportation, tower and foundation). however, the international renewable energy agency has stated that compared to 2016 levels, wind turbine prices will decline by 27% in 2025 (irena 2016). as specified by hemami (2012) and manwell et al. (2009), a typical cost for an onshore wind turbine is 769.23 €/kw of its rated power, and for offshore wind turbine is 1230.77 €/kw. other initial costs are in general taken to be 40% of the wind turbines price. 2.1.2. financing cost the cost of wind electricity is also impacted by financing costs, which are defined by manwell et al. (2009) to be the costs that have been burned at the beginning to finance the equipments purchase and installation. the wellspring of capital might be a bank or speculators. the money lenders will expect a return on the credit. in the case of a bank, the return is called interest. over the project life, the cumulative interest can add up to an important amount of the total costs. 2.1.3. operation and maintenance cost operation and maintenance cost (o&m) starts when the wind project is delivering electricity. it is the cost of repairing turbines damages and keeping it operating under safe conditions during the project lifetime. in other word, o&m gathers the costs of requiring monitoring and maintenance to optimize performance from specialized wind technicians and operators (corrective maintenance, preventive maintenance, insurance, lease, taxes, salary, insurance, running, etc). fazelpour et al. (2017), mohammadi et al. (2016) and minaeian et al. (2017) have defined o&m as a percentage m of ic by: o&m = m ic (1) m ranges generally from 1.5% to 3% and it increases with the age of the turbine. for old wind turbines, it is approximately equal to 3% and for modern machine it varies between 1.5% and 2%7. in an economic evaluation of a wind project in morocco8, m was taken to be 2%. 7 according to: wind measurement international, available at “www. windmeasurementinternational.com”, (accessed 01 october 2017). 8 sahara wind, available at “www.saharawind.com” (accessed on 17 september 2017). figure 3: methodology to estimate the wind energy production cost figure 4: investment cost distribution tizgui, et al.: estimation and analysis of wind electricity production cost in morocco international journal of energy economics and policy | vol 8 • issue 3 • 201862 2.2. npc ramli et al. (2016) and al-sharafi et al. (2017) have defined the npc of a system as the total cost of installing and operating the system over its lifetime. the same authors have calculated the npc using the following formula: npc = ic+o&m (2) siyal et al. (2016) have defined npc as a life cycle cost of a wind energy system. for them, total npc of a wind energy system is the sum of initial investment cost, operation and maintenance cost and salvage cost. they have used this equation to estimate npc. npc = ic+o&m+sc (3) where, sc is the salvage cost of the wind energy system, which is the cost of decommissioning a wind energy system, transport and sell its components to another power supplier. 2.3. total annualized cost as we cited previously, npc is the total cost of a wind energy system over lifetime. to convert it into total annualized cost, it is important to note that in economic field, money today has not the same value as tomorrow. this difference is due to the interest rate, which is used to convert from one-time costs to annualized costs (ac). 2.3.1. annual interest rate in the economic assessment, it is supposed that all costs escalate at the same rate. the annual real interest rate (i) can be defined as the yearly yield that a lender anticipates from borrowers. it can be calculated as follows: i i f f = − + ' 1 (4) where i’ is the annual nominal interest rate, and f is the annual inflation rate. 2.3.2. capital recovery factor (crf) the crf is a ratio used to convert total npc value into total annualized cost over a number of years n (system lifetime) and at a specified interest i. as reported by hemami (2012), crf can be calculated as follows. ( ) ( ) ( ) 1 , 1 1 n n i i crf i n i + = + − (5) a period of n = 20 years is often assumed for an economic assessment. by improving the wind turbine design, a lifetime of 30 years was utilized in us economic studies. but that demands a major annual maintenance of wind turbines to replace key parts. haghighat mamaghani et al. (2016) have estimated ac using the following equation: ac = npc*crf (6) to estimate ac, drew et al. (2015) annualized just ic, because they have estimated the o&m costs for 1 year, they have used the following equation: ac = ic*crf+o&m (7) 2.4. levelized production cost of energy hosseinalizadeh et al. (2017) and haghighat mamaghani et al. (2016) have defined the levelized cost of energy as the average cost per kwh of the produced wind electricity. lcoe is obtained by dividing ac by the annual electricity generation et (in kwh/year). it is given by: lcoe ac et = (8) in other word, lcoe is the minimum price needed to break-even. a project is economically feasible when lcoe is less than the local electricity price. recently, lcoe has recently decreased because of the significant advancement in the technology, markets competition and the economies of scale. that is due also to the wind turbine size growth (increase in height, blades and rotor diameter) which allows a greater energy generation (because wind speed increases with height and the produced energy is proportional to the swept area). 2.5. sensitivity analysis for a complete economic assessment of a wind energy project, it is very important to include sensitivity analysis for estimation of the output variable. in fact, there is a degree of uncertainty in the assumed economic variables and any change in this inputs impacts dramatically the output parameter value. each variable must be varied around the original case in order to visualize its influence. several studies that assess the wind energy economics perform a sensitivity analysis of the calculated parameter. for example, to assess the sensitivity analysis of lcoe in essaouira wind power project9, o&m costs and the discount rate have been increased by 10% and 2% respectively. athanasia (2012) has conducted a sensitivity analysis of cost and income of electricity by varying the tax rate and the project lifetime. he has concluded that the cost of electricity increases as the tax rate increases and the project lifetime decreases. siyal et al. (2016) have analyzed the influence of initial capital, interest rate and selling price of electricity on the cost of produced wind energy, the net present value and the payback period. the obtained results show that the cost of electricity increases as the interest rate and the initial investment cost increase. to visualize the sensitivity of the calculated net present value, johnson and solomon (2010) have varied the interest rate, electricity prices, produced electricity and other costs. liu et al. (2016) have performed the sensitivity analysis of lcoe by changing values of initial investment, interest rates, o&m costs and wind turbine power and diameter. we cite also neij (1999) who has analyzed the impact of varying the progress ratio on the cost of generated wind energy. his results show that this variable has significant impact on the calculated energy cost. 3. wind energy cost assessment at nine moroccan wind farms in this study we selected nine onshore moroccan wind farms for which the needed details of an economic evaluation are available. those farms are named tarfaya, fem el oued, essaouira, 9 clean development mechanism project (2004), design document form (cdm pdd). tizgui, et al.: estimation and analysis of wind electricity production cost in morocco international journal of energy economics and policy | vol 8 • issue 3 • 2018 63 tangier i, haouma, koudia al baïda, laayoune, tetouan i and tetouan ii. table 1 gives the geographical coordinates and the commissioning dates of the studied parks, whereas table 2 presents the technical characteristics of the installed wind turbines at the studied farms. an economic evaluation by calculating lcoe for each park is the goal of this section. 3.1. economic analysis data and assumptions to carry out the economic assessment, the available data and the assumptions differ from one author to another. for our case: • the total investment capital including all costs (turbines purchase, site, land preparation, consultancy, design, equipment, transportation and project management, etc.) is available. it is reported in table 3. • the yearly produced wind energy is also available. it is reported in table 3. • the normal interest rate is i = 2.25% and the inflation rate is 2.1% (for january, 201710). • the following information was supposed.1112 • the lifetime of the studied turbine is taken to be n = 20 years (marafia and ashour, 2003, mohammadi et al. 2016). • to estimate o&m over the project lifetime, we use equation (1). as per (fazelpour et al. 2017), m is taken to be 2% of the wind turbine cost. 10 trading economics, available at: “www.tradingeconomics.com” (accessed on 07 september 2017). 11 wiki eolienne, the wind power collaborative project, available at: “https:// eolienne.f4jr.org” (accessed on 20 september 2017). 12 the wind power, wind energy market intelligence, available at “www. thewindpower.net” (accessed on 24 june 2017). • to estimate npc, we use equation (2). in this study we don’t take into account the salvage cost, because we estimate that the remaining value of a wind power system can be used to cover the cost of decommissioning the farm. • to calculate ac, we use equation (6). • the purchase tariff of electricity in morocco is 0.0830 ‎€/kwh (zejli et al., 2004). 4. results and discussion 4.1. analysis and comparison of the estimated lcoe we developed an excel calculation tool for the evaluation of the lcoe. using the mentioned values of normal interest rate, inflation rate and turbines lifetime, the annual real interest rate and the crf are 4.84% and 0.0792 respectively. basing on the available data and assumed value of m, the estimated o&m, npc and ac are presented in table 4. table 4 shows also the obtained results for lcoe per kwh at the studied wind farms. this cost is affected by the sites characteristics and the installed technologies. the wind park that produces energy with less cost is koudia al baïda (0.0164‎ €/kwh) followed by essaouira, tetouan i and fem el oued (with 0.0227 €/kwh, 0.0234 €/kwh and 0.0245 €/kwh respectively). the parks where the lcoe is between 0.03 ‎€/kwh and 0.04‎ €/kwh are haouma, tarfaya, tetouan ii and tangier i. the park that generates energy with more than 0.04 €/kwh is laayoune. figure 5 illustrates the estimated lcoe for each park. we observe that the highest cost of kwh is obtained at laayoune farm which is equal to 0.0459 €/kwh, while table 1: geographical coordinates and the commissioning date of the studied parks11 wind farm geographical coordinates commissioning date tarfaya 27.715871, −12.946883 december, 2014 fem el oued 27.015034, −13.388821 2013 essaouira 31.413263, −9.802698 march, 2007 tangier i beni mejmel 35.760841, −5.688281 april, 2009 dhar saadane 35.592920, −5.574541 april, 2010 haouma 35.80772, −5.490889 2013 koudia al baïda 35.79292, −5.461139 august 2000 (50.4 mw)/2001 (3,5 mw) laayoune 27.15642, −13.34039 october, 2011 tetouan i 35.605864, −5.438227 may, 2005 tetouan ii 35.614724, −5.430151 december 2008 (5 t*)/june 2009 (6 t) *: t=turbine table 2: technical data of installed wind turbines at the studied farms12 wind farm turbine model number of turbines rated power (kw) hub height (m) tarfaya swt-2.3-101 131 2300 80 fem el oued swt-2.3-101 22 2300 80 essaouira g52/850 71 850 --tangier i beni mejmel g52/850 39 850 65 (127 t), 55 (19 t) and 49 (19 t) dhar saadane 126 haouma swt-2.3-93 22 2300 80 koudia al baïda v42/600 e40/500 84 7 600 500 --laayoune g52/850 6 850 --tetouan i g52/850 12 850 44 tetouan ii g80/2000 11 2000 60 (6 t) and 67 (5 t) ---: data not available tizgui, et al.: estimation and analysis of wind electricity production cost in morocco international journal of energy economics and policy | vol 8 • issue 3 • 201864 the lowest value is observed at koudia al baïda park which is equal to 0.0164 ‎€/kwh. thus, we conclude that in terms of lcoe, the park of koudia al baïda is more promising. the private sector and the government can keep and expand the investment in this park. in general, all studied farms generate a benefit because for all of them, the lcoe is less than the electricity price which is 0.0830 ‎€/kwh in morocco. this is clearly beneficial for investors and government. 4.2. sensitivity analysis to perform the sensitivity analysis of the estimated lcoe at the studied parks, we change individually the interest rate, the o&m costs, the energy output and the projects lifetime. figure 6 illustrates the sensitivity analysis of lcoe by varying the interest rate over the interval [1%, 10%]. from this figure, we can say that the lcoe depends strongly on the interest rate variation. we note that an increase in the interest rate generates an increase in the lcoe and a decrease of the interest rate results a decrease in lcoe. figure 7 presents the effect of o&m cost variation on the lcoe. for all parks, as it can be seen, o&m costs have the lower effect on the lcoe. we vary the o&m costs over the range of [−60%, +60%] but we don’t note any significant change on lcoe. figure 8 clarifies the dependence of the lcoe on the energy output. for the studied farms, we vary the produced energy by a margin of ±10, 20, 30%. it is clear that lcoe drops with the increase of the energy output. figure 9 shows the impact of varying the studied projects lifetime between 15 and 30 years. we note that an extend in a project lifetime leads the cost of energy production. in contrast, lowering the projects lifetime causes a great increase in lcoe. figure 5: estimated lcoe for each park (‎in €/kwh) figure 6: effect of varying interest rate on the lcoe table 3: investment cost and yearly energy output at the studied parks11 available data tarfaya fem el oued essaouira tangier i haouma koudia al baïda laayoune tetouan i tetouan ii ic (million €) 450.0000 61.6000 59.0909 250.0000 72.7273 46.0000 9.0909 11.0000 35.0909 et (mwh/year) 1187724.6 202700 210000 526500 192000 226000 16000 38000 77000 table 4: estimated o&m, npc, ac and lcoe for the studied parks costs tarfaya fem el oued essaouira tangier i haouma koudia al baïda laayoune tetouan i tetouan ii o&m (million €) 9.0000 1.2320 1.1818 5.0000 1.4545 0.9200 0.1818 0.2200 0.7018 npc (million €) 459 62.8320 60.2727 255.0000 74.1818 46.9200 9.2727 11.2200 35.7927 ac (million €) 36.3333 4.9736 4.7710 20.1852 5.8721 3.7141 0.7340 0.8881 2.8333 lcoe (€/kwh) 0.0306 0.0245 0.0227 0.0383 0.0306 0.0164 0.0459 0.0234 0.0368 tizgui, et al.: estimation and analysis of wind electricity production cost in morocco international journal of energy economics and policy | vol 8 • issue 3 • 2018 65 4.3. comparison of wind and solar energies lcoe in morocco in morocco, wind energy is more attractive and competitive with other energy sources. in fact, its cost compares favorably with the solar energy one. for example, according to world bank13 the energy generated by the solar farm noor i costs 0.2050 €/kwh, and 0.1506 €/kwh in case of concessional financing. it costs 0.1590 €/kwh 13 the world bank, ibrd. ida, available at: “www.worldbank.org” (accessed on 03 september 2017). for noor ii and 0.1464 €/kwh for redstone. indeed, for installing the same capacity of 2000 mw of wind and solar energies, morocco has invested in solar energy more than wind energy (3.13 billion € for wind energy plan and 8.12 billion € solar energy plan), that is due to the expensive solar energy technologies, its maintenance and operation costs. by 2020, the generated wind energy will be 6600 gwh, while, the generated solar energy will be just 4500 gwh. that explains a good capacity factor of wind energy systems comparing with solar systems. thus, in morocco, wind is economically more appropriate for producing energy. figure 7: effect of varying o&m on the lcoe figure 8: effect of varying the energy output on the lcoe figure 9: effect of varying the project lifetime on the lcoe tizgui, et al.: estimation and analysis of wind electricity production cost in morocco international journal of energy economics and policy | vol 8 • issue 3 • 201866 5. conclusion this paper summarizes the most important economic factors that affect the energy cost and summarized the method of determining the levelized cost of electricity. then, a case study of nine wind parks in morocco, namely tarfaya, fem el oued, essaouira, tangier i, haouma, koudia al baïda, laayoune, tetouan i and tetouan ii is achieved. the following results can be extracted from the evaluation, analysis and comparison of energy cost at the cited wind farms. • the minimum lcoe is attained at koudia al baïda park which is equal to 0.0164 €/kwh. the good result is obtained also at essaouira, tetouan i and fem el oued with a lcoe <0.03 €/kwh. • the parks where the lcoe is between 0.03 €/kwh and 0.04 €/kwh are haouma, tarfaya, tetouan ii and tangier i. the park that generates energy with more than 0.04 €/kwh is laayoune. • for all the studied wind farms, the obtained costs of producing one kwh of energy are less than the purchase tariff of electricity in morocco (0.0830 €/kwh). moroccan government should encourage investors to continue investment at those parks considering that the current wind energy projects are expected to operate for a limited duration. that will help the country to become more independent in the energy field and make investors and government generating an enormous profit in addition to fuel saving and emissions reduction. • from the sensitivity analysis, we conclude that for the studied wind farms, the variables which have a greatest effect on lcoe are the interest rate, the produced energy and the project lifetime. the lcoe is not very sensitive to the o&m costs variation. • due to important wind resource and investment in wind technology manufacturing, the wind energy cost in morocco compares favorably with the solar energy cost. thus, in morocco, wind is economically more appropriate for producing energy. 6. acknowledgments the authors would like to thank the national centre for scientific and technical research (cnrst) of morocco for sponsoring this study. references al-sharafi, a., sahin, a.z., ayar, t., yilbas, b.s. (2017), technoeconomic analysis and optimization of solar and wind energy systems for power generation and hydrogen production in saudi arabia. renewable and sustainable energy reviews, 69, 33-49. athanasia, a. (2012), economics of wind energy. modern energy review, 4(2), 209-236. bortolini, m., gamberi, m., graziani, a., manzini, r., pilati, f. (2014), performance and viability analysis of small wind turbines in the european union. renewable energy, 62, 629-639. drew, d.r., barlow, j.f., cockerill, t.t., vahdati, m.m. (2015), the importance of accurate wind resource assessment for evaluating the economic viability of small wind turbines. renewable energy, 77, 493-500. fazelpour, f., markarian, e., soltani, n. (2017), wind energy potential and economic assessment of four locations in sistan and balouchestan province in iran. renewable energy, 109, 646-667. haghighat mamaghani, a., avella, e.s.a., najafi, b., shirazi, a., rinaldi, f. (2016), techno-economic feasibility of photovoltaic, wind, diesel and hybrid electrification systems for off-grid rural electrification in colombia. renewable energy, 97, 293-305. hemami, a. (2012), wind turbine technology. usa: cengage learning. hosseinalizadeh, r., sadat, r.e., alavijeh, a.s., ghaderi, s.f. (2017), economic analysis of small wind turbines in residential energy sector in iran. sustainable energy technologies and assessments, 20, 58-71. international renewable energy agency. (2016), the power to change: solar and wind cost reduction potential to 2025. abu dhabi: international renewable energy agency. johnson, g.l. (2006), wind energy systems. manhattan, ks: electronic edition. johnson, n.h., solomon, b.d. (2010), a net-present value analysis for a wind turbine purchase at a small us college. energies, 3(5), 943-959. liu, c., wang, y., zhu, r. (2016), assessment of the economic potential of china’s onshore wind electricity. resources, conservation and recycling, 121, 33-39. manwell, j.f., mcgowan, j.g., rogers, a.l. (2009), wind energy explained: theory, design and application. 2nd ed. washington, usa: wiley. marafia, a.h., ashour, h.a. (2003), economics of off-shore/on-shore wind energy systems in qatar. renewable energy, 28(12), 1953-1963. minaeian, a., sedaghat, a., mostafaeipour, a., akbar, a.a. (2017), exploring economy of small communities and households by investing on harnessing wind energy in the province of sistanbaluchestan in iran. renewable and sustainable energy reviews, 74, 835-847. mohammadi, k., mostafaeipour, a., sedaghat, a., shamshirband, s., petković, d. (2016), application and economic viability of wind turbine installation in lutak, iran. environmental earth sciences, 75(3), 1-16. mostafaeipour, a. (2013), economic evaluation of small wind turbine utilization in kerman, iran. energy conversion and management, 73, 214-225. neij, l. (1999), cost dynamics of wind power. energy, 24(5), 375-389. ramli, m.a.m., hiendro, a., al-turki, y.a. (2016), techno-economic energy analysis of wind/solar hybrid system: case study for western coastal area of saudi arabia. renewable energy, 91, 374-385. saeidi, d., sedaghat, a., alamdari, p., alemrajabi, a.a. (2013), aerodynamic design and economical evaluation of site specific small vertical axis wind turbines. applied energy, 101, 765-775. siyal, s.h., mentis, d., howells, m. (2016), mapping key economic indicators of onshore wind energy in sweden by using a geospatial methodology. energy conversion and management, 128, 211-226. zejli, d., benchrifa, r., bennouna, a., zazi, k. (2004), economic analysis of wind-powered desalination in the south of morocco. desalination, 165, 219-230. international journal of energy economics and policy vol. 1, no. 2, 2011, pp.32-46 issn: 2146-4553 www.econjournals.com electricity consumption and economic growth: trivariate investigation in botswana with capital formation solarin sakiru adebola1 college of arts and science, room 250, economics building, universiti utara, malaysia. phone: +60122436814 e-mail: sakiru1424@yahoo.co.uk, s92027@student.uum.edu.my abstract: this study investigates the relationship between electricity consumption and real gross domestic product in botswana (the world’s largest producer of diamonds). the study includes capital formation in a trivariate system for the period covering 1980-2008. zivot and andrews (1992) unit roots test; bound test for cointegration, and granger causality test are employed. unidirectional causality is found from electricity consumption to real gross domestic product is in line with study of altinay and karagol (2005) among others. the long run estimate reinforce the granger causality tests by indicating that electricity consumption is positively associated with real gross domestic product in the long run. further findings suggest unidirectional causality from capital formation to real gross domestic product. the implication is that botswanabeing a highly energy dependent countrywill have the performance of its capital formation on the economy partly determined by adequate electricity. keywords: economic growth, electricity consumption, bound test, causality, structural break, botswana jel classification: q43; c32; o55 1. introduction electricity plays an essential role in modern life, bringing benefits and progress in various sectors, including transportation, manufacturing, mining and communication sectors. electric power is vital for economic growth and quality of life not only because it fosters the productivity of capital, labour and other factors of production, but also that increased consumption of energy, particularly commercial energy like electricity signifies high economic status of a country (jumbe, 2004). these facts have attracted authors to investigate the role of electricity in different countries. starting with the pioneering work of kraft and kraft (1978), most authors have utilised causality tests to investigate the relationship between electricity consumption and economic development. further advances in time series techniques and availability of long time series data on electricity have stimulated further research in this area (see tang, 2008; altinay and karagol, 2005; shiu and lam, 2004; narayan and singh, 2007). in recent times, some authors have decided to focus on african countries (see akinlo, 2009; kouakou, 2011; odhiambo, 2009a, b; jumbe, 2004; wolde-rufael, 2006; squalli, 2007). conspicuously from all these studies is that botswana-the largest producer of diamond in the world was not included. this is despite the fact that botswana remains one of the countries in africa with consistent electricity deficit, which reached its peaked in 2008 at 1174.83 kilo-watts (kwh) per capita (which is due to declining electricity generation and persistent increase in electricity consumption). botswana is a country, which depends on imported electricity to the tune of 80% (eia, 2011; jefferis, 2008). besides, the electricity usage among household insufficiently increased from 10% in 1991 to 25% in 2001. rural access to electricity was merely 40.75% in 2008. given the unfavourable conditions, the government’s “vision-2016 plan” aims at 100% electrification to support the broader development goals of access to education and health, as well as employment opportunities, to the rural 1 the author is a phd research candidate at the universiti utara, malaysia electricity consumption and economic growth: trivariate investigation in botswana with capital formation 33 and the disadvantaged population (afdb, 2009). capital investment is seen as bedrock to achieve this vision. thus, botswana power corporation (bpc) proceeded in 2007 and 2008, to invest 343.4 million pula and 17.3 million pula, respectively in electricity infrastructure (lekaukau, 2007; rakhudu, 2008). besides, the study notes that with the exception of odhiambo (2009b) and ouédraogo (2009) most of these studies on african countries employ bivariate analysis. however, akinlo (2009) argues that this may create omitted variable bias. in addition, studies on african countries have ignored structural breaks in testing for the unit root tests. the seminal work of perron (1989) has shown that structural change can substantially reduce the power of unit root tests. in other words, failure to allow for an existing break leads to bias that reduces the ability to reject a false unit root null hypothesis. therefore, bias resulting from unit root test will affect the inferences made from the subsequent cointegration test and ultimately the causality tests. against these backdrops, the study intends to investigate the relationship between electricity consumption and real gross domestic product in botswana for the period 1980-2008. the study will provide for capital investment in a trivariate system. furthermore, the study intends to utilise zivot and andrews (1992) method to endogenously determine structural breaks while conducting the unit root tests. the rest of the paper is organized as follows. section 2 provides an overview of electric power in botswana and section 3 cover a brief review of literature related to energy consumption and economic growth. section 4 outlines the methodology used in the study. following, section 5 provides the empirical findings of the research and the last section concludes the study. 2. overview of electric power in botswana botswana is a landlocked country located in southern africa sharing border with namibia (1,360 km), south africa (1,840 km) and zimbabwe (813 km). the size of botswana is 581,730 sq km with landmass accounting for 566,730 sq km and water accounting for 15,000 sq km (cia, 2011). from a humble beginning as an agrarian economy at independence in 1966, the discovery of diamonds in 1967 transformed the country’s economy, culminating into becoming the world’s leading diamond producer (mfdp, 2003). for the review period 2001-2005, diamonds accounted for the largest portion of the country’s total foreign exchange revenues. the economic growth per capita was high at 7.540% in 2002 and despite the global downturn; the botswana was still able to grow at 3.278% and 1.579% in 2007 and 2008, respectively. in 2007, the growth of manufacturing value added was 17.476%. the youth literacy was high at 95.100% in 2008 (wdi, 2010). key to botswana maintaining its successful development path is the energy sector. botswana’s energy demand was about 3660 gigawatt hour (gwh) in 2008 (peak load of 500 megawatt), which is projected to grow at about 6% per annum reaching 5300 gwh by 2017 (peak load of 850 megawatt) and 6890 gwh by 2026 (peak load of 1130 megawatt). however, the deepening energy crisis across the southern africa sub-region is a major impediment to botswana’s economic growth plans, poses a threat to stability, and requires a major concerted effort at the national and regional levels to address the energy challenge (afdb, 2009). generally, in the southern african region, the main source of electricity is coal-fired power. in botswana, the case is not different. as shown in table 1, the percentage of coal-fired power has been increasing over the years. for instance, the contribution of coal-fired power was 78.172% in 1990 and rose to 95.277% and 99.464% in 1985 and 2007, respectively (wdi, 2010). the other source of electricity has been majorly through small-scale oil–sourced power. the preference for coal-fired power over the oil-sourced power has been majorly due to costs differences as the latter is far more expensive. it is estimated that coal-fired power costs 6-8 us cent per kwh, while oil-sourced power costs around 25-35 cent per kwh (jefferis, 2008). this indicates that botswana electricity tariffs are still relatively low by world – and african – standards. besides, botswana, like several other countries in the southern africa sub region relies on inexpensive, abundant, and reliable electricity from south africa. in recent years, around 80% of electricity is imported, of which 70% is from the national electric utility of south africa-eskom. the domestic supply of around 20% comes from botswana power corporation (bpc), which is the sole electricity company over the entire country and has a mandate of supplying the country with power. in 2008 alone, botswana imported about 2440 gwh (67% of its power requirements) from eskom, while its own small 25-year-old coal power plant (morupule a, 4 x 33 mw) provided about 22% (afdb, 2009). in addition, the bpc controls the international journal of energy economics and policy, vol. 1, no. 2, 2011, pp.32-46 34 network of transmission and distribution lines to transport electricity from the power station, or point of import to eventual consumers. based on the recommendation of a steering committee by the government on the need to privatise, decentralised bpc, the electricity supply act of 1973 was amended in 2007 to permit independent electricity suppliers (marandu, 2010). table 1. botswana electricity sources year coal oil 1981 78.172 21.828 1985 95.277 4.723 1990 88.079 11.921 1995 97.983 2.017 2000 97.149 2.851 2005 99.382 0.618 2006 99.424 0.576 2007 99.464 0.536 source: world development indicators (2010) with these sources, generation of electricity has been falling over the years. for instance, fig. 1 shows that net electricity generation fell from 760.004 kwh per capita (generation) in 1992 to 542.6519 kwh per capita in 2001 and further fell to 308.674 kwh per capita in 2008. one reason for this is that bpc supply has been declining slowly, presumably reflecting the aging of the power station and the resulting maintenance needs (jefferis, 2008). on the other hand, electricity consumption has been rising over time. the electricity consumption was 762.687 kwh per capita (electricity) in 1992; 1156.209 kwh per capita in 2001; and in the year 2008, the figure rose to 1483.508 kwh per capita. this has resulted into electricity deficit exacerbating over the years, as it was 2.682 kwh per capita in 1992, 613.557 kwh per capita in 2001, and 1174.83 kwh per capita in 2008. in order to solve this problem, the rural electrification programme was accelerated with the connection of 72 villages over the period september 1999 to december 2001. for the financial year 2006/07, the government set aside funds to electrify villages (marandu, 2010). more recently, the rural electrification plan is being addressed by implementing two main projects namely, the 100 villages and the 30 villages electrification projects. the 100 villages electrification project is funded by the government of botswana through a loan from swedish and norwegian banks amounting to us dollar 89 million (motsepe, 2009). hence, between 2004 and 2007, rural access to electricity doubled to 44%, though short of the 60% target under the national development plan (afdb, 2009). 0 1,000 2,000 3,000 4,000 5,000 1980 1984 1988 1992 1996 2000 2004 2008 rgdp electricity generation fig. 1 trend in electricity consumption, electricity generation and rgdp, 1980–2008 electricity consumption and economic growth: trivariate investigation in botswana with capital formation 35 the efforts will be futile if the targetelectricity does not have any correlation or positive impact on the economy. however, fig. 1 indicates that electricity has been very close to the real economic activities-real gross domestic product per capita (rgdp). it is shown that in the years 1992, 2001 and 2008; rgdp rose from us 2622.549 dollars, to us 3333.276 dollars, and further to us 4299.7492 dollars, respectively (wdi, 2010; eia 2011). this association does indicate whether economic growth is dependent on energy consumption or vice versa. causality running from rgdp to electricity implies that botswana is not entirely dependent on energy for its economic growth, while causality running from electricity consumption to economic growth, for example, implies that economic growth is dependent on energy consumption. therefore, econometrics methods are required to examine the relationship between electricity and rgpd in botswana. before investigating the nexus econometrically, we review some existing literatures on the subject matter. 3. review of related studies the investigation of the relationship between energy consumption and economic growth started with the seminal work of kraft and kraft (1978) on usa (see ozturk, 2010 for a detailed survey of literature on energy-growth nexus). subsequently, numerous authors specifically concentrated on the relationship between electricity consumption and economic development (see ghosh, 2002; jamil and ahmad, 2010; ho and siu, 2007; shiu and lam, 2004; narayan and singh, 2007). although with conflicting results, most of these works have several similarities. an obvious similarity is the utilisation of causality tests to investigate the relationship. this is even applicable to multi-country studies (see; narayan and prasad, 2008; acaravci and ozturk, 2010; ozturk and acarvci, 2011; narayan and smyth, 2009; yoo, 2006; chen, kuo and chen, 2007). the other similarity is that unidirectional causality running from gross domestic product to energy consumption is interpreted to mean that a country is not exclusively dependent on energy for its economic growth, and that power conservation policies can be undertaken with insignificant or no adverse effects on economic growth (odhiambo, 2010). on the other hand, unidirectional causality running from real gross domestic product electricity consumption is interpreted to mean that a country is not entirely dependent on energy for its economic growth, and that energy conservation policies can be implemented with modest or no undesirable effects on economic growth (narayan and singh, 2007; odhiambo, 2009a). the studies on africa are also characterised by conflicting results and utilisation of causality tests. for example, on nigeria, akinlo (2009) investigates the causality relationship between energy consumption and economic growth for period 1980-2006, using granger causality test, johansen and juselius (1990) cointegration test. the results show that real gross domestic product and electricity consumption are cointegrated and there is unidirectional granger causality running from electricity consumption to real gross domestic product. using the data from 1971 to 2008, kouakou (2011) investigates the causal relationship between the electric power industry and the economic growth of cote d’ivoire. the findings reveal bidirectional causality between per capita electricity consumption and per capita gross domestic product in the short run, but a unidirectional causality from electricity to gross domestic product in the long run. in another study with similar findings, odhiambo (2009a) examines the relationship between energy consumption with economic growth in tanzania for the period 1971-2006. the study utilises the granger causality tests, but unlike akinlo (2009), the study employs bounds testing approach for cointegration. furthermore, energy is proxy by total energy consumption per capita and electricity consumption per capita. generally, odhiambo (2009a) observe that there is a stable long run relationship between each of the proxies of energy consumption and economic growth. more importantly, the results of the causality test, on the other hand, show that there is unidirectional causal flow from total energy consumption to economic growth. jumbe (2004) examines relationship between electricity consumption and respectively, overall gross domestic product, agricultural gross domestic product and non-agricultural gross domestic product using malawi data for period 1970-1999. with residual-based cointegration, the results suggest that electricity consumption is respectively, cointegrated with gross domestic product and nonagricultural gross domestic product, but not with agricultural gross domestic product. the granger causality tests suggest bidirectional causality between electricity consumption and gross domestic product, but a unidirectional causality running from non-agricultural gross domestic product to international journal of energy economics and policy, vol. 1, no. 2, 2011, pp.32-46 36 electricity consumption. further, jumbe (2004) examines the elasticity of the variables, with the findings indicating that the impact of electricity consumption is only significant in the long run. there are also multi-country studies on africa. these include wolde-rufael (2006) who considers 17 african countries for the period 1971-2001 in investigating the long run and causal relationship between electricity consumption per capita and real gross domestic product per capita. the paper adopts the bound test for cointegration; in addition to the causality test propose by toda and yamamoto (1995). the findings reveal unidirectional causality flowing from electricity consumption per capita to real gross domestic product per capita for benin congo, dr and tunisia. on the other hand, the results suggest unidirectional causality flowing from real gross domestic product per capita to electricity consumption per capita cameroon, ghana, nigeria, senegal zambia and zimbabwe. wolde-rufael (2006) reports bidirectional causality on egypt, gabon and morocco, while no causality on algeria, congo rep. kenya, sudan and south africa. another multi-country work that includes african countries is squalli (2007). in contrary to wolde-rufael (2006), squalli (2007) notes unidirectional causality from economic growth to electricity consumption for algeria; and a bidirectional relationship between economic growth to electricity consumption for nigeria. beyond the similarity of using causality tests, it is obvious to note that the studies are based on bivariate analysis. this creates the danger of omitted variable bias that could result from the use of bivariate analysis (akinlo 2009). hence, odhiambo (2009b) provide for omitted variable by including employment in a study of south for the period 1971 to 2006. the findings suggest that there is bidirectional causality between electricity consumption and economic growth in south africa. moreover, the study shows that employment in south africa granger causes economic growth. the other study with a trivariate system is ouédraogo (2009) who investigates the nexus on burkina faso by adding capital formation to the system, for the period 1968-2003. using granger causality, the findings reveal that there is a bidirectional relationship between electricity consumption and real gross domestic product in the short-run and the long run. besides, there is also evidence of a positive feedback relationship between gross domestic product and capital formation. however, the study shows no causal relationship between electricity consumption and capital formation. from the foregoing reviewed literatures on africa, it is pertinent to note that there is no previous study on botswana despite the electricity situation cum the efforts and targets of the authorities in the country. moreover, literatures on africa does not provide for structural breaks. only a handful of literatures (odhiambo, 2009b; ouédraogo, 2009) utilise a trivariate system. thus, the methodology discussed in the next section provide for all these deficiencies. 4. methodology and data 4.1 model in investigating the relationship between electricity consumption and output growth, the study follows a neo-classical one-sector aggregate production model proposed by ghali and el-sakka (2004) that treats capital, labour, and energy(in our case, electricity) as separate inputs. this implies that: (1) where rgdp is the aggregate output of real gdp; capital is the capital stock; labour is the level of employment; electricity is total electricity consumption, and the subscript t denotes the time period. the study computes per capita form of the variables by dividing through by labour and then taking the logarithmic form of (1). this results in: (2) where the dot above each variable indicates that each variable is in per capita form. the constant parameters and  measures the marginal effect of capital and electricity, respectively on output. the production function (1) suggests that long-run movements of the variables may be related (ghali and el-sakka, 2004). furthermore, for short-run dynamics in factor-input behaviour, the specification in (2) would suggest that past changes in variables such as capital and electricity could contain useful information for predicting the future changes of output, ceteris paribus (lorde, waithe and francis, 2010). in other words, causality tests can be utilised to examine the relationship among the variables. electricity consumption and economic growth: trivariate investigation in botswana with capital formation 37 4.2 data this study uses annual data for the period 1980-2008. the study sources its real gross domestic product and gross capital formation data from the world bank’s world development indicators (wdi) 2010. the annual data of real gross domestic product per capita (rgdp) and gross capital formation (which was subsequently divided by population figure from wdi to arrive at the per capita figures) are in us dollars (2000=100). studies such as wolde-rufael (2009) ouédraogo (2009), apergis and payne (2009), narayan and smyth (2008) utilised capital formation (capital) to proxy the stock of physical capital. the electricity consumption figure is obtained from the energy information administration (eia) website and subsequently divided by population figure from wdi to arrive at the electricity consumption per capita in kwh (electricity). all the variables are expressed in natural logarithmic form. 4.3 stationarity test traditionally, unit root tests are investigated using augmented dickey-fuller test or adf as developed by said and dickey (1984) and phillip and perron (1988) test or pp, which control for serial correlation. however, perron (1989) shows structural change can substantially reduce the power of unit-root tests and proposes a unit root model, with an exogenous structural break. exogenous structural break has been, in turn criticised on the basis that it leaves room for arbitrarily selection of dates. hence, zivot and andrews (1992) propose a variation of perron (1989) original test by assuming that the exact time of the break point is unknown. instead, a data dependent algorithm is used to proxy perron (1989) subjective procedure to determine the break points. zivot and andrews (1992) developed three models to test for unit root. in this study, we employ the first two of the three zivot and andrews (1992) methods, which are specified below: )4( )(: )3( )(: 1 1 1211 1 1 1211 tjt k j jt b t abb t tjt k j jt a t aaa t yydttybmodel yydutyamodel                where )(tdu is 1 and  ttdtt )( * if tt  , 0 otherwise. t tb and tb represents a possible break point. the null hypothesis is  = 0 while the alternative hypothesis is <0 implying that the series is a trend-stationary process with a one-time break occurring at an unknown point in time. zivot and andrews (1992) considers all points as a potential break-date (tb) and runs a regression for every possible break-date sequentially. hence, the break-date (tb) eventually selected represents the date, which minimizes the one-sided t-statistic from amongst all possible break points (tb). generally, model a allows for a change in the level of the series, while model b allows for a change in the slope of trend of a series. 4.4 cointegration sequel to the stationarity test is the cointegration test in which the study utilises bound tests of the autoregressive distributed lag (ardl) approach as articulated by pesaran and shin (1999) and extended by pesaran, shin and smith (2001). there are several reasons for the adoption of this technique. as against the conventional johanssen cointegration method that uses system of equation to estimate long run relationship, ardl employs a single reduced form equation. moreover, the approach does not require pre-testing variables, hence it could be implemented regardless of whether the underlying variables are i(0), i(1), or fractionally integrated, thereby reducing the task of establishing the order of integration amongst the variables. moreover, the long and short-run parameters of the model are estimated simultaneously. as a result, the inability to test hypotheses on the estimated coefficients in the long run associated with the engle-granger method is avoided. procedurally, ardl involves investigating the existence of a long run relationship using the following unrestricted error correction models (uecms): international journal of energy economics and policy, vol. 1, no. 2, 2011, pp.32-46 38 (5) (6) (7) in the three specifications above  represents first difference operator, electricity is the per capita electricity consumption, rgdp is the per capita gross domestic per capital and capital is capital formation per capita. hence, a joint significance test, which implies no cointegration (h0: 0: is conducted on (5), (6) and (7). the f-test is considered in determining whether a long-run relationship exists among the variables through testing the significance of the lagged levels of the variables. if the computed fstatistic exceeds the upper critical value, then there is cointegration. if the f-statistic falls within the two bounds of critical values then the test becomes inconclusive. finally, if the f-statistic is below the lower critical value, it implies no cointegration. 4.5 causality test granger (1988) integrated the concept of cointegration into causality. with cointegrated variables, granger (1988) stated that causal relations among variables can be examined within the framework of the ecm. while the short run dynamics are captured by the individual coefficients of the lagged terms, the error correction term contains the information of long run causality. hence, significance of each explanatory variable lags depict short run causality. on the other hand, a negative and statistical significant error correction term is assumed to signify long run causality. the equations are stated below: (8) (9) (10) where ect stands for the error correction term, which is derived from the long run cointegration relationship and must be significant for long run causality to exist. moreover,  must produce a negative sign for causality to exist in the long run. electricity consumption and economic growth: trivariate investigation in botswana with capital formation 39 4.6 diagnostic test the study conducts diagnostics tests such as breusch-godfrey test to check the null hypothesis of no autocorrelation, as against the use of durbin watson test, which loses its power in the presence of a lagged dependent variable. besides, the study adopts the jarque and bera (1980) tests popularly called the jarque and bera tests for the normality test, which encompasses other forms of detecting normalityskweness and kurtosis. in fact, it is a weighted average of the squared sample moments corresponding to skweness and excess kurtosis. under the null hypothesis, it is distributed as chisquared with two degree of freedom (verbeek, 2004). in testing for the functional form of the equation, the study employs the ramsey (1969) reset test (regression equation specification error tests), which tests whether additional terms of the regressors variables are significant in the auxiliary regression. the significance of these additional variables indicates that the model is misspecified (see gujarati, 2003). the diagnostics tests include autoregressive conditional heteroscedasticity (arch) test for heteroscedasticity. in testing for the stability of parameters and regressions, the study utilises the brown, durbin and evans (1975) tests popularly known as cumulative sum (cusum) and cumulative sum of squares (cusumsq) tests, which are based on the recursive regression residuals. the cusum and cusumsq statistics are updated recursively and plotted against the model’s break points. thus, the coefficients of a given regressions are stable if the plots of the statistics fall within critical bounds of 5% significance. generally, cusum and cusumsq tests are conducted through graphical representation. the study selects cusum and cusumsq tests ahead of other forms of stability tests because cusum and cusumsq tests overcome shortcomings of the other stability tests. for example, chow (1960) introduce chow test that requires a priori knowledge of structural breaks in the estimation period, which may not be known hence need to be determined arbitrarily. the chow test ignores the difference on the account of intercepts, slopes or both (gujarati, 2003) and it is only valid under homoscedasticity (wooldridge, 2009). armed with all the foregoing methods, the study provides the empirical findings in the following section. 5. results and findings the results for the adf and pp unit root tests for rgdp, capital and electricity are reported in table 2. the adf and pp tests produce identical outcomes. the null hypothesis that the variables are nonstationarity cannot be rejected for any of the series at level, but when the data are first differenced, the null that the series contain unit root can be rejected for all variables with rgdp at 10%. this implies that rgdp, capital and electricity are i(1). however, the results may not be valid because of structural breaks. therefore the study proceeds with a method that incorporates structural break. table 2. adf and pp tests for unit roots variables levels first differences adf pp adf pp rgdp -1.980 -2.321 -2.742* -2.754* capital -0.907 -0.471 -4.068*** -4.043*** electricity -0.971 -1.700 -4.201*** -8.381*** the lag selection of the adf is based on aic with a lag length of 1. the pp test is estimated based on bartlett kernel with newey-west bandwidth. generally, the specification of the tests include intercept only; critical values are based on mackinnon (1996) and the null hypothesis is that of no stationarity. *, *** imply stationarity at 10% and 1% level of significance, respectively. international journal of energy economics and policy, vol. 1, no. 2, 2011, pp.32-46 40 the results of the zivot and andrews (1992) model a and model b unit root tests in the presence of one unit root are reported in table 3. coincidentally, the findings are similar to the unit root tests without structural breaks. thus, we are unable to reject the null hypothesis of unit root at the 10% level or better, confirming that the series are at least i(1). the break dates for rgdp intercept and slope are 1987 and 1989, respectively. on the break dates for capital, the study notes 1988 and 1993 for the intercept and slope, respectively. lastly, the break dates for intercept and slope of electricity are 1989 and 1992 respectively. the periods correspond to the time (17 august 1992) in which the southern african development community (an establishment championed by the biggest economy in africa and botswana’s largest supplier of electricity-south africa) was formed. table 3. zivot–andrews test for unit roots variables model a model b z-a break z-a break rgdp -4.686 1987 -4.141 1989 capital -4.726 1988 -4.001 1993 electricity -4.795 1989 -3.566 1992 the critical value for 1% and 5% levels are -5.340, -4.800 and -4.420, -4.800 for model a and b from zivot and andrews (1992). for easy comparism to the adf test the optimal lag is set to 1. the two models contain deterministic components. the null hypothesis is no stationarity in the presence of endogenous structural break. the results of the bounds test for cointegration, together with critical values of pesaran and pesaran (1997) are reported in table 4. the bounds test indicates that there is a cointegration relationship. at 10% significance level, we reject null hypothesis of no cointegration, when the rgdp is the dependent variable. however, when capital and electricity are the dependent variables, there is no cointegration. the existence of cointegrating relationship among rgdp, capital and electricity suggests that there must be granger causality in at least one direction, but it fails to signify the direction of temporal causality among the variables. table 4. bounds tests for cointegration dependent variable f-statistics 10% i(0) 10% i(1) 5% i(0) 5% i(1) 1 i %(0) 1% i(1) rgdp 4.634* 3.182 4.126 3.793 4.855 5.288 6.309 capital 2.210 3.182 4.126 3.793 4.855 5.288 6.309 electricity 1.742 3.182 4.126 3.793 4.855 5.288 6.309 *, **, *** imply 10%, 5%, and 1% level of significance respectively. the critical values are for the model with intercept but no trend, as contained in case ii of pesaran and pesaran (1997). the null hypothesis is no cointegration. in table 5, the study examines short-run and long run granger causality and the long run estimates. long run causality is found from electricity to rgdp, but with no feedback from rgdp. this unidirectional result is similar to the findings of odhiambo, (2009a) on tanzania and kouakou (2011) on cote d’ivoire. according to nayaran and prasad (2007), this implies that reducing electricity consumption could lead to a fall in income. the long run estimates of the ardl reinforce the granger causality tests by suggesting that electricty is positively and significantly associated with rgdp in the long run. in particular, for every 1% increase in electrcity, there is 1.06% increase in rgdp, at 5% significance level. these results have a lot of significance on the botswana economy. it implies that the country is highly energy dependent. this is not surprising, as botswana requires substantial electricity for its diamond mining. electricity consumption and economic growth: trivariate investigation in botswana with capital formation 41 table 5. causality and long run estimates variable granger causality results long run estimates ∆rgdp ∆capital ∆electricity ect(-1) rgdp capital electricity ∆rgdp 6.939** 1.778 -1.767* -0.338 1.063** ∆capital 8.272** 0.878 ∆electricity 2.030 0.542 for the equation with ∆rgdp as dependent variable, the optimal lag selection is 1, 3 and 3, respectively. the unrestricted var is utilised in computing the causality with ∆capital and ∆electricity as the dependent variables. in this case the maximum lag is set to 3. generally, the null hypothesis is no granger causality. the chi-square statistics are reported for the variables, while the t-statistic is reported for the ect. *, **, *** imply 10%, 5%, and 1% level of significance respectively. the lack of feedback from rgdp may mean that the focus of the economy on the electricity sector has not been adequate and misfit in botswana. in other words as regular growth of electricity supply is germane in boosting economic output; however, additional income or economic growth does not translate into adequate capital investment in electricity sector, and thus does not stimulate additional electricity consumption. the results on capital confirm this finding as there is no causality flowing from capital to electricity. the study notes further that in the long run, capital granger causes rgdp with a short run feedback. the long run estimates suggest capital has negative and insignificant impact on rgdp implying that there is somewhat a relationship between capital and electricity. thus, we interpret this to mean that capital formation will have adequate impact on the economy if there is adequate electricity in the economy. table 6. diagnostics tests test statistics lm test f-test serial correlation chsq(1) = 0.064 [0.800] f (1, 15) = 0.037 [0.850] functional form chsq(1) = 0.233 [0.630] f(1, 15) = 0.135 [0.718] normality chsq(2) = 1.276 [0.528] n/a heteroscedasticity chsq(1) = 1.784 [0.182] f(1, 24) = 1.768 [0.196] the study applies a number of diagnostic tests to the ardl estimates in table 6. the tests suggest that no autocorrelation in the disturbance of the error term. the reset test indicates that the model is correctly specified and no functional form problem. the model passes the jarque-bera normality tests, signifying that the errors are normally distributed. moreover, the arch test denotes that the errors are homoskedastic and independent of the regressors. given that neither the cusum nor the cusumsq test statistics exceed the bounds of the 5% level of significance, the regression equation appears stable over the period of estimation. international journal of energy economics and policy, vol. 1, no. 2, 2011, pp.32-46 42 -5 -10 -15 -20 0 5 10 15 1988 1993 1998 2003 2008 fig. 2 plot of cumulative sum of recursive residuals -0.5 0.0 0.5 1.0 1.5 1988 1993 1998 2003 2008 fig. 3 plot of cumulative sum of square of recursive residuals forecasting electricity gap for vision 2016 in order to investigate whether botswana is likely to achieve vision 2016 (conceived in 1997) of 100% electrification by 2016, the study forecasts the electricity gap for the period 2009 to 2016 using exponential smoothing technique in table 7. exponential smoothing method is a very popular scheme to produce smoothed and forecasted time series (pyo and choi, 2009). specifically, the study utilises the one parameter (double) technique. this method applies a single smoothing method (using the same parameter) on the level and trend components of the variable and is appropriate for series with a linear trend. obviously, from table 7, electricity situation is likely to worsen if the current trend is sustained. therefore, vision 2016 may not be achieved based on the current situation. on the forecasting accuracy we used the one parameter (double) exponential smoothing technique because, of all the five methods of exponential smoothing considered; this method produces the smallest alpha in all cases. in fact, it is within bowerman and o’connell (1979) suggested range of 0.01 to 0.30 in the case of electricity (at 0.296) and closest to the range in the case of generation (at 0.368). the lower the value of alpha, the less responsive the forecast is to sudden change. as our two values are well below the benchmark value of 0.5, we argue that the forecasts are accurate. in fig. 4, the study graphically examines how the actual and forecasted series moves together. the forecasted series for electricty is electrictysm, while generationsm is the forecast for generation. evidently, the figure shows that the forecasted figures move in tandem with the actual values. electricity consumption and economic growth: trivariate investigation in botswana with capital formation 43 table 7. forecasts of electricity gap, 1997–2016 electricity generation gap year actual forecast actual forecast 1997 958.385 535.480 -45.309 1998 946.372 618.063 -119.022 1999 1033.191 616.134 -137.724 2000 1085.017 607.818 -164.651 2001 1156.209 542.652 -168.969 2002 1130.334 562.063 -10.347 2003 1344.766 583.178 -12.565 2004 1328.015 513.359 -7.019 2005 1371.904 496.452 -18.023 2006 1384.040 524.981 -31.959 2007 1442.064 358.270 -2.682 2008 1483.508 308.674 -59.193 2009 1537.262 299.120 -156.778 2010 1584.278 258.838 -172.084 2011 1631.293 218.557 -397.962 2012 1678.309 178.275 -422.906 2013 1725.324 137.993 -328.309 2014 1772.340 97.712 -417.057 2015 1819.355 57.430 -477.198 2016 1866.371 17.149 -613.557 for generation, the alpha is; single parameter technique, 0.914; one parameter (double) technique, 0.368; holt-winters-no seasonal (two parameters), 0.930; holt-winters-additive technique, 1.000; and holt-winters-multiplicative technique, 1.000. for electricity the alpha is; single parameter technique, 0.987; one parameter (double) technique, holt-winters-no seasonal (two parameters), 0.550; holt-winters-additive technique, 0.610; and holt-winters-multiplicative, 0.580. 200 400 600 800 1,000 1,200 1,400 1,600 1980 1984 1988 1992 1996 2000 2004 2008 electricty electricitysm generationsm generation fig. 4 actual and forecasts of electricity gap, 1980-2008 international journal of energy economics and policy, vol. 1, no. 2, 2011, pp.32-46 44 6. conclusion the study investigates the relationship between electricity consumption per capita and real gross domestic product per capita in botswana. the study includes capital formation in a trivariate system for the period of 1980 -2008. choosing botswana is ideal, as no published study has conducted research on the largest diamond producing country, before now. this is in the face of the country’s persistent electricity deficit and large electricity dependence on south africa. unlike any previous study on africa, we provided for structural breaks in testing for unit roots using the zivot and andrews (1992) to endogenously determine structural breaks before proceeding to the bound test for cointegration and the granger causality tests in addition to providing the long run estimates. the results suggest long run causality from electricity consumption to real gross domestic product, but with no feedback from real gross domestic product. this unidirectional causality is in line with of odhiambo, (2009a) on tanzania and kouakou (2011) on cote d’ivoire. the long run estimate reinforces the granger causality tests by indicating that electricity consumption is positively and significantly associated with real gross domestic product in the long run. summarily, this may be interpreted to mean that botswana is a highly energy dependent country. this is not surprising as the economy depends on electricity for its mining activities. thus, improving electricity could improve income generation. further results suggest that unidirectional causality from capital formation to real gross domestic product, with the coefficient of capital formation being negative and insignificant in the long run. thus, we interpret this to mean that capital formation will have adequate impact on the economy if there is adequate electricity supply in the economy. besides, the findings on forecasting suggest that if the current situation is sustained, then the problem of electricity gap is likely to worsen in botswana. from the foregoing, it is obvious that electricity policy that focuses on securing the long term supply will naturally spur sustainable growth of economic activities. in this regard, we urge the authorities in botswana to intensify the issue of diversification of electricity sources and management. solar energy is described as a viable alternative to other sources of electricity. one additional benefit of solar energy is that it is cheaper to generate locally. diversification into solar energy will reduce the dependence of botswana dependence on eskom. on the issue of electricity management, it is pertinent that the privatisation of bpc should be accelerated, especially in the area of generation in which private generation companies will be allowed in the electricity supply market in botswana. this will not only provide an avenue for the much-needed private capital in the electricity sector, but also foster competition in the electricity supply market that would allow large consumers to select their own supplier. references acaravci, a., ozturk, i. (2010), electricity consumption-growth nexus: evidence from panel data for transition countries. energy economics 32, 604-608. afdb, (2009), environmental and social impact assessment executive summary. african development bank -morupule "b" power project, p-bw-fa0-001. retrieve from http://www.afdb.org/en/projects-and-operations/project-portfolio/project/p-bw-fa0-001/ on may 25, 2011 akinlo, a.e., (2009), electricity consumption and economic growth in nigeria: evidence from cointegration and co-feature analysis. journal of policy modeling, 31(5), 681-693 altinay, g., karagol, e. (2005). electricity consumption and economic growth: evidence from turkey. energy economics 27, 849-856. apergis, n., payne, j.e. (2009), energy consumption and economic growth in central america: evidence from a panel cointegration and error correction model. energy economics, 31(2), 211-216. bowerman, b., o’connell, r. (1979), time series and forecasting: an applied approach. new york, duxbury press. brown, r., durbin, j., evans, j.m., (1975), techniques for testing the constancy of regression relationships over time. journal of the royal statistical society 37, 149-172. chen, s.t., kuo, h.i., chen, c.c. (2007), the relationship between gdp and electricity consumption in 10 asian countries. energy policy, 35, 2611–2621. chow, g. (1960), tests of equality between sets of coefficients in two linear regressions. econometrica 28(3), 591-605. electricity consumption and economic growth: trivariate investigation in botswana with capital formation 45 cia, €(2011), central intelligence agency world fact book. retrieve from www.cia.gov/library/publications/the-world-factbook/geos/bc.html on may 25, 2011 eia, (2011), us energy information admininstration dataset. retrieve from http://www.eia.gov/cfapps/ipdbproject/iedindex3.cfm?tid=2&pid=2&aid=2&cid=bc,&syid=1 980&eyid=2009&unit=bkwh on may 25, 2011 ghali, k.h., el-sakka, m.i.t., (2004), energy use and output growth in canada: a multivariate cointegration analysis. energy economics 26, 225-238. ghosh, s., (2002), electricity consumption and economic growth in india. energy policy, 30(2), 125129. granger, c.w.j., (1988), causality, cointegration and control. journal of economic dynamics and control 12, 551-559. gujarati, d., (2003), basic econometrics. fourth edition. mcgraw hill publishing company ho, c.y., siu, k.w., (2007), a dynamic equilibrium of electricity consumption and gdp in hong kong: an empirical investigation. energy policy, 35(4), 2507-2513. jamil, f., ahmad, e., (2010), the relationship between electricity consumption, electricity prices and gdp in pakistan. energy policy 38, 6016-6025. jarque, c., bera, a. (1980), efficient tests for normality, homoscedasticity and serial independence of regression residuals. economics letters, 6, 255-259. jefferis. k., (2008), summary of economic developments. bifm economic review 1st quarter, 2008 johansen, s., juselius, k. (1990), maximum likelihood estimation and inference on cointegration with application to the demand for money. oxford bulletin of economics and statistics, 52, 169-210. jumbe, c.b.l., (2004). cointegration and causality between electricity consumption and gdp: empirical evidence from malawi. energy economics, 26, 61-68. kouakou a.k., (2011), economic growth and electricity consumption in cote d’ivoire: evidence from time series analysis. energy policy, 39, 3638-3644 kraft, j., kraft, a. (1978), on the relationship between energy and gnp. journal of energy and development 3, 401-403. lekaukau. c., (2007). board of directors chairman’s address. botswana power corporation annual report 2007, 11 lorde, t., waithe, k., francis, b. (2010), the importance of electrical energy for economic growth in barbados. energy economics, 32, 1411-1420. marandu, e., (2010), pro-poor policies for rural electrification in botswana: a rights-based perspective. international social science journal, 60, 371-387. mfdp, (2003), national development plan 9. ministry of finance and development planning (bostwana) government press. 2003. mmewr, (2003), preliminary investigation on electricity supply industry restructuring. ministry of minerals, energy and water resources. motsepe. a., (2009), director rural’s address. botswana power corporation annual report 2009, 21 narayan, p.k., prasad, a. (2008), electricity consumption-real gdp causality nexus: evidence from a bootstrapped causality test for 30 oecd countries. energy policy 36, 910-918. narayan, p.k., singh, b. (2007), the electricity consumption and gdp nexus for the fiji islands. energy economics, 29, 1141-1150. narayan, p.k., smyth, r. (2005), electricity consumption, employment and real income in australia evidence from multivariate granger causality tests. energy policy 33, 1109-1116. narayan, p.k., smyth, r. (2009), multivariate granger causality between electricity consumption, exports and gdp: evidence from a panel of middle eastern countries. energy policy, 37(1), 229-236. narayan, p.k., smyth, r., (2008), energy consumption and real gdp in g7 countries: new evidence from panel cointégration with structural breaks. energy economics 30, 23312341. odhiambo, n.m., (2009a), energy consumption and economic growth nexus in tanzania:an ardl bounds testing approach. energy policy 37, 617-622. odhiambo, n.m., (2009b), electricity consumption and economic growth in south africa: a trivariate causality test. energy economics, 31(5), 635-640. international journal of energy economics and policy, vol. 1, no. 2, 2011, pp.32-46 46 odhiambo, n.m., (2010), energy consumption, prices and economic growth in three ssa countries: a comparative study. energy policy 38 (2010) 2463–2469 ouédraogo, i.m., (2010), electricity consumption and economic growth in burkina faso: a cointegration analysis. energy economics, 32, 524-531. ozturk, i. (2010). a literature survey on energy-growth nexus. energy policy, 38(1), 340-349. ozturk, i., acaravci, a. (2011), electricity consumption and real gdp causality nexus: evidence from ardl bounds testing approach for 11 mena countries," applied energy, 88(8), 28852892. perron, p. (1989), the great crash, the oil price shock, and the unit root hypothesis. econometrica, 57, 1361-1401. pesaran, m.h., and shin, y. (1999), autoregressive distributed lag modelling approach to cointegration analysis, in: s.strom (ed.), econometrics and economics theory: the ragnar frisch centennial symposium, chapter 11, cambridge university press. pesaran, m.h., pesaran, b. (1997), working with microfit 4.0: interactive econometric analysis. oxford university press, oxford. pesaran, m.h., shin, y., smith, r.j., (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics 16, 289-326. phillips, p., perron, p. (1988), testing for a unit root in time series regressions. biometrika, 75, 335-346. pyo, s., choi, y. (2009), a fast handover scheme using exponential smoothing method. international journal of computer science and network security, 9(2), 61-64. rakhudu. e., (2008), board of directors chairman’s address. botswana power corporation annual report 2008, 14 ramsey, j., (1969), tests for specification errors in classical linear least squares regression analysis. journal of the royal statistical society, 31(2), 350-371. said, e., dickey, d. (1984), testing for unit roots in autoregressive moving average models of unknown order. biometrika, 71, 599-607. shiu, a., lam, p.l. (2004). electricity consumption and economic growth in china. energy policy 32, 47-54. squalli, j., (2007). electricity consumption and economic growth: bounds and causality analyses of opec members. energy economics 29, 1192-1205. tang, c.f., (2008), a re-examination of the relationship between electricity consumption and economic growth in malaysia. energy policy, 36(8), 3077-3085. toda, h., yamamoto, t. (1995), statistical inferences in vector autoregressions with possibly integrated processes. journal of econometrics, 66, 225-250. verbeek, m., (2004), a guide to modern econometrics second edition. west sussex, john wiley sussex. wolde-rufael, y., (2006). electricity consumption and economic growth: a time series experience for 17 african countries. energy policy 34, 1106-1114. wolde-rufael, y., (2009), energy consumption and economic growth: the experience of african countries revisited. energy economics 31(2), 217-224. wooldrigde, j., (2009), introductory econometrics: a modern approach, fourth edition. austrialia, south-western college publishing. world bank, (2010), world development indicators on cd-rom, washington, dc. yoo, s., (2005), electricity consumption and economic growth: evidence from korea. energy policy, 33(12), 1627-1632. yoo, s., (2006), the causal relationship between electricity consumption and economic growth in asean countries. energy policy 34, 3573-3582. yoo, s., kwak s. (2010), electricity consumption and economic growth in seven south american countries. energy policy, 34(18), 181-188. zivot, e., andrews, d. (1992), further evidence of the great crash, the oil-price shock and the unit-root hypothesis. journal of business and economic statistics 10, 251-270. . international journal of energy economics and policy | vol 8 • issue 2 • 2018 81 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(2), 81-88. prediction of hydropower energy price using gómes-maravall seasonal model arash jamalmanesh1#, mahdi khodaparast mashhadi2*, ahmad seifi3, mohammad ali falahi4 1phd candidate of economics, international campus, ferdowsi university of mashhad, iran, 2department of economics, faculty of economics and administrative sciences, ferdowsi university of mashhad, iran, 3department of economics, faculty of economics and administrative sciences, ferdowsi university of mashhad, iran, 4department of economics, faculty of economics and administrative sciences, ferdowsi university of mashhad, iran. *corresponding author: email: m_khodaparast@um.ac.ir abstract the present research is aimed at investigating the possibility of predicting average monthly electricity prices and presenting a model for predicting electricity price in iranian market considering unique characteristics of electricity as a commodity. for this purpose, time series data on average monthly electricity price during 2006–2015 was used. firstly, unit root test was used to investigate stationarity of time series of electricity price. then, using gómes-maravall model, an arima model was estimated for predicating electricity price in iranian market using energy purchase data from a hydropower plant. the model was run utilizing seats (signal extraction in arima time series) and tarmo (“time series regression with arima noise, missing observations, and outliers”) programs. for this purpose, energy purchase data from three karun river hydropower plants (khuzestan province, iran) was used. keywords: electricity prices, hydropower, seasonal gómes-maravall model jel classifications: q41, q43 # this research has been conducted in the phd thesis of arash jamalmanesh at the international campus, ferdowsi university of mashhad, iran. 1. introduction in many countries, structure of power industry is evolving from an exclusive environment to a competitive one. however, different countries are experiencing different models of restructuring of power industry toward privatization of this industry and making it competitive. despite the differences between electrical energy and other commodities, which root in unique characteristics of this type of energy such as inability to store it in large amounts, the main idea behind the process of making competitive the power industry is to consider the electric energy as a commodity which can be traded via bilateral or multilateral agreements or electricity market. with the restructuring of electricity market from a governmental monopoly to competitive market where average price is determined by market forces, modeling and prediction of price has been accompanied with uncertainty and become particularly important for stakeholders of electricity market. in order to perform modeling and prediction in such a competitive market, one should consider characteristics of electricity as a commodity, such as storage limitations, low elasticity, seasonal nature of supply and demand, and the necessity of a continuous balance between supply and demand. today, electricity market exhibits further harmony with other markets such as ancillary services market, thereby remarkably complicating decision-making toward enhanced profitability for market’s stakeholders. success in the novel competitive electricity market requires possessing an acceptable deal of skill in estimation based on scientific criteria. players of energy market are uncertain about the profit to be gained from long-term energy delivery contracts in the future, because there are chances that production, demand, and prices change compared to the contract requirements; as such, energy suppliers and consumers may act better should they perform more accurate predictions. with increasing the demand for electricity, the motivation toward optimized use of resources jamalmanesh, et al.: prediction of hydropower energy price using gómes-maravall seasonal model international journal of energy economics and policy | vol 8 • issue 2 • 201882 and economic competitions lead companies and economic firms toward investing on and participation in electricity industry. in a competitive electricity system, customers are free to select sellers. accordingly, more customers can be attracted by providing better services and cheaper energy, bringing about more profits for energy producers and sellers while presenting more interests to the customers. energy sellers or suppliers are representatives who sell energy to customers; they may not be original producers, but rather have bought shares of plant productions. in such a case, prediction of electricity prices offered by electricity market for purchasing the electricity generated by plants or supplied by energy suppliers become very important. meanwhile, being engaged with production limitations in terms of water input and seasonal changes, hydropower plants consider predicting trend of prices in longer runs. in order to predict and model the behavior of electricity prices in shortand mid-term using time series data on electricity prices and considering particular characteristics of electricity, numerous econometric tools and artificial intelligence-based methods (e.g. neural networks) have been adopted. in most of modeling practices, various possible methods have been used for estimating the models followed by comparing the methods based on statistics indicating the power of predictions. in the present research, however, box-jenkins and gómes-maravall model are investigated and compared using seasonal data. electricity price follows a seasonal pattern, because the demand for electricity depends on the level of economic activity in different days, weeks, and months in a year and also on weather conditions. when the demand for electricity decreases, producers tend to use the units with minimal final production cost. during summer or peak hours, however, the units of higher final cost are also brought in service. prices tend to move along an average price determined by the competitive market forces. in electricity market, the production unit with the lowest efficiency will be the last unit to respond to the demand for electricity. moreover, as an effective factor in determining prices, air temperature follows a periodic pattern which returns to the average price. this pattern is commonly used to explain the autocorrelation of electricity price time series. as such, some sort of mean reversion model is expected for electricity prices. there are limiting values in electricity price time series. the solution which makes the model able to predict these data is to include the variable of time scattering variable into the mean reversion model. these models can further take into account intense fluctuations in the values of variables, making them suitable for modeling electricity price data which can be influenced by network interruptions, meteorological factors, sudden rise of demand, and production fluctuations. fluctuations in electricity prices are commonly not stable, so that the prices reverse to the mean rapidly. arima and seasonal arima models introduce effect of the information received from common and uncommon states into the model. some of the received information are of the type of normal events and result in smooth changes in prices; these changes are explained by the mean reversion model. some other received information is uncommon and lead to fluctuations in prices. these models express market prices as a function of preceding prices and previous error terms. 2. research background analysis of seasonal changes in economic time series has a background almost identical to that of the theory of macroeconomics. however, despite such a great deal of background, only little consensus can be seen in empirical research on the way to deal with seasonal nature of fluctuations in economic variables. considering the studies performed so far, advances have been achieved in reducing electricity price prediction error. in the following, some of the most important studies on price predication time series are briefly reviewed. samer et al. (2001) predicted demand for electricity using singlevariable arima models. in this paper, once finished with making the data reliable, the demand for electricity was predicted using different arima models such as ma and ar at various orders. finally, ar(1) model was selected as the best model for this purpose. darbellay and marek (2000) predicted short-term demand for electricity in czech republic. in this paper, the demand was firstly predicted using a nonlinear model (artificial neural networks), followed by predicting the same demand using a linear model (arima). it was finally concluded that, short-term demand for electricity follows a linear model, so that the artificial neural network may not be regarded as a better model for predicating the demand for electricity. darbellay and slama (2000) presented a combination of artificial neural network and arima as an optimum solution for predicting time series, and claimed that, the combination of artificial neural network model (as a nonlinear model) and arima (as a linear model) may perform better than either of the models alone when it comes to the prediction of time series. finally, they proved their hypothesis by adopting several experimental datasets. the method was originally devised for seasonal adjustment of economic time series (i.e., removal of the seasonal signal), and the basic references are cleveland and tiao (1976), box et al. (1978), burman (1980), hillmer and tiao (1982), bell and hillmer (1984), maravall and pierce (1987). these approaches are closely related to each other, and to the one followed in this program. in fact, as already mentioned, seats developed from a program built by burman for seasonal adjustment at the bank of england (1982 version). some researchers have been using neural networks, time series (arma models) or a combination of both to forecast electricity prices in electricity market. the following researchers can be mentioned: areekul et al. (2010), bowerman and richard (1987), nogales et al. (2002), senjyu (2010), sun and meng (2006), tiao and tasay (1983), voronin and partanen (2013), zhang (2003). gómez and maravall (1994), gómez (1998), estimated and interpolated nonstationary series with the kalman filter. jamalmanesh, et al.: prediction of hydropower energy price using gómes-maravall seasonal model international journal of energy economics and policy | vol 8 • issue 2 • 2018 83 3. theoretical foundations and pricing in competitive electricity market there are two distinctive approaches in electricity market: (1) electricity trading via optional electricity exchanges (e.g. new zeeland market) and forced electricity exchange (e.g. uk and australia). the main advantage of the forced market is transparency across the market which is practiced to confine market power of giant producers. in a governmental monopoly, electricity prices are set upon governmental orders and are functions of supply costs as well as industrial and social policies adopted by governments. for most part, these prices remain either unchanged or change very slightly and predictably in mid and short runs. following the restructuring of electricity market in many countries, electricity price is determined in competitive market and under the effect of market forces via interaction of complicated electricity supply and demand functions. producers and purchasers compete for trading the produced and needed electricity in the market, offering their proposed prices for different hours to the market operator. demand for electricity depends on the level of economic activities and weather conditions. trading methods in an electricity market include: electricity exchange, bilateral deals, and multilateral deals. in an electricity exchange, all of the sellers and buyers are required to participate in the market and present their purchase/sell offerings. this entity matches cumulative supply and demand curves to determine an equilibrium point for the market. similar to any other exchange, sales can be either oneway or two-way. in a one-way sale, sellers offer their production level and prices (supply curve), while consumers indicate their needed quantities only. in a two-way sale, both sellers and purchasers are sensitive to price, so that they offer not only the production/consumption quantities, but also the desired price. in bilateral deals, given that consumers opt for the cheapest producers, market efficiency is enhanced. depending on the market mechanisms, the market may be either one-way or two-way. in a one-way market, independent system operator (iso) considers the predicted load as a reference. this load prediction is performed both by consumers (across the area under their control) and operator (for the entire network). with this approach, the load is specified when launching uc software. for this level of load, the iso specifies the quantity of reserve and other ancillary services for each hour. figure 1 shows how the market is closed in this model. there is another variant of electricity market wherein energy suppliers and consumers provide not only quantities, but also proposed prices. in such markets, competition is promoted both at production and consumption levels. in two-way markets, the subject matter of maximizing social welfare is highlighted, because in such a case, each party has set load supply strategies by means of the price parameter (figure 2). pricing is performed via any of the following three methods either in electricity exchange market or by iso. in a pre-pricing method, price of the commodity is set before delivering the good, with the players agreeing on a quantity of electricity to be delivered at a predetermined price at a given time in future. in post-pricing method, price of the commodity is determined upon delivery; producers and consumers can alter their proposals up to a given time, and the market is settled in the course of offering processes. the third method is a combination of the two above-mentioned methods. in instantaneous (cash) market, electricity price is determined at the last day before delivery, with any change between predicted and actual values of consumption which may end up with a difference between the predetermined and instantaneous prices being compensated via the second mechanism. in a combined market, system price is set before the delivery, and any imbalance is purchased by iso in a market known as adjustment market in real-time. in this case, market closing point is where social welfare is maximal. producers who can offer their products at lower prices than the competitors will be selected sooner and with a larger deal of chance. in a case where consumers also propose prices for fulfilling their needs, naturally, those who are ready to pay the figure 1: balance in a one-way market with predetermined demand figure 2: balance in a two-way market jamalmanesh, et al.: prediction of hydropower energy price using gómes-maravall seasonal model international journal of energy economics and policy | vol 8 • issue 2 • 201884 largest cost for the same commodity will enjoy priority. in such a case, both producers and consumers are well satisfied with the deal. electricity supply and demand shall be balanced continuously. electricity production and consumption are performed at exactly the same time, and no storage facility for this commodity exists across the grid. given that supply and demand fluctuations cannot be smoothed using inventory, electricity prices in cash market are highly unstable. moreover, electricity prices are set locally, with no possibility for arbitrage deals on electricity. electricity is a non-storable commodity, so that demand fluctuations may abruptly fluctuate its price. 4. time-series modeling approach one of the well-known models for the purpose of this research is autoregressive (ar) integrated moving average (arima) model. in a general case, this method was expressed as arima (p, d, q) by box-jenkins, where p is ar order of the model, q is the order of ma, and d is differential order of the model (to make the model stationary). in case one element is equal to zero, the model is denoted as either ar or ma. for instance, ma(1) is the same as arima (0, 0, 1). in this method, once finished with determining the differential order and orders of ar and ma processes, model parameters are found. given highly subjective nature of the box-jenkins methodology, time-series analyzers have introduced and adopted other criteria for identification and recognition of orders in arima models. penalty function statistics (e.g. akaike information criterion (aic), bayesian information criterion, and hannan quinn criterion) have been used in the literature on the analysis of time series for presenting an accurate yet economic model in terms of the count of parameters. all of these functions possess a residual sum of squares (rss) minimization component along with a penalty element which is a combination of the number of estimated coefficients along with the number of observations1. the criteria used to determine lag length in non-seasonal modeling are solely dependent on the parameters q and p. in different configurations of arima model, there are only rare cases where the values of q, d, and p exceed 1, and even this small domain covers many feasible cases in the prediction. autocorrelation function (acf) and partial acf (pacf) are used to determine the values of p and q. 4.1. seasonal time series modeling – seasonal ar integrated ma (sarima) in seasonal time series econometrics literature, there are two approaches to the modeling of seasonal time series. commonly known as conventional method, the first approach is based on 1 these sample functions are defined as follows: bcs = log (rss/t) + [log (t) × k/(t)], bqc = log (rss/t) + [2 log (log (t))×k/(t)] and aic = log (rss/t) + [2 k/(t)]. where k is the number of estimated coefficients (1+p+q+p+q), rss is residual sum of squares, and t is the number of observations. lag length with optimal minimal is determined by minimizing the above functions. however, finding the solution is somewhat difficult considering the large number of p, q, p, and q parameters. the assumption that, seasonal component of a time series is assumed to be non-stochastic and independent of non-seasonal components. in contrast, the second approach assumes that the seasonal component is random and independent of non-seasonal components. such that, for example, price of a product in the current period not only is a function of the product price in the preceding month, but also of that in the same month in the past year. therefore, in order to predict a variable (price or any other variable of interest), not only the prices in the neighboring months (seasons) shall be incorporated into the model, but also the prices at the same month(s) in the previous years(s) shall be further examined. the most well-known seasonal arima model is the multiplicative model known as box-jenkins (1976) model. 4.2. monthly time series data modeling box-jenkins approach can be used as tool for providing reliable predictions for policy-setting. similar to non-seasonal time series, values of p, q, p, and q were determined using acfs and torques of the arma (p, q) (p, q)s process. as an example, autocorrelation behavior of a general seasonal process is expressed as arma (0, 1) (0, 1)s with s = 4, 12 where s refers to the type of the time series period. in this seasonal process, the interrupting component is assumed to be white noise, with the absolute values of the two parameters θ1 and θ1 being smaller than 1. xt = (1−θ1b) (1−θ1b s)εt (1) therefore, acfs of the time series xt are as follows: ρ θ θ ρ θ θ1 1 s= − + = − +/ ( ), / ( )1 11 2 1 1 2 (2) ρ ρ ρ ρ θ θ θ θs s+1 s 1 1− = = = + +1 1 1 2 1 2 1 1/ ( )( ) (3) for example, in a time series with s = 4, acfs are non-zero for the lags of 1, 3, 4, and 5 only. comparing acfs of the two processes ma (1) and ma(1)s can be interesting. for the two models, these functions are observed to be ρ θ θ1 1 1 2 1= − +( )/ and ρ θ θs = − +( )1 121 , respectively, which are exactly the two first acfs of the process sarma (0, 1) (0, 1)s. multiplication of these two torques (i.e., ρs−1=ρs+1=ρsρ1,) gives mutual effects of these two periods. parameters of a seasonal model are estimated in a similar way to that followed for an annual time series model. the coefficients can be estimated via either maximum likelihood method (conditional and deterministic) or least squares (linear and nonlinear) method. 4.3. validation and model characterization criteria in order to evaluate the estimated model and statistically validate it, one could use white noise test on its residual component. in this hypothetical tests, acf and pacf shall exhibit no significant difference from zero. variance (standard deviation) of kρ̂ can calculated using bartlett’s approximation. for the seasonal timeseries model airma(0,0,1)(0,0,1)12, bartlett’s approximation of the variance of kρ̂ is as follows: ( ) ( )2 2 2 2k 1 11 12 13ˆ ˆ ˆ ˆvar =(1+2 + + + /t; k>13ˆρ ρ ρ ρ ρ (4) jamalmanesh, et al.: prediction of hydropower energy price using gómes-maravall seasonal model international journal of energy economics and policy | vol 8 • issue 2 • 2018 85 for s = 4, the above approximation becomes: ( ) ( )2 2 2 2k 1 3 4 5ˆ ˆ ˆ ˆvar = (1+2 + + + /t; k>5ˆ ρ ρ ρ ρ ρ (5) under null hypothesis (i.e., the studied phenomenon is white noise), all of the autocorrelation factors become zero and standard deviation of kρ̂ is equal to 1 t . in addition, another method for controlling and evaluation of adequacy of a general boxjenkins model is to analyze the residuals obtained from the estimated model (7.1). in this approach, partly resembling diagnosis investigations on time-series models with odd periods, acfs and sample acfs are used. also in the seasonal time series data, box and pierce’s sample function q and loung-box sample function q* were used, as defined below: k 2 i t i=1 ˆq=t' r ( )∑ ε (box and pierce) (6) k * ' ' 1 2 i t i=1 ˆq =t'(t +2) (t +1) r ( )−∑ ε (loung-box) (7) where t′ = t−(d+s.d) and t is the number of observations in the main time series, s is the number of seasons per year (or the number of months per year, 4 or 12), and d and d are the number of annual and monthly differentiation of the studied time series to arrive at a stationary process zt (or filtered xt). the parameter ri 2 is the squared sample correlation at lag i for the residuals of the estimated model (7.1). it is obvious that, if d = d = 0, then t´ = t; this is the sample function used to identify annual data. both of these sample functions can be used for identification studies. however, it can be proved that, q* exhibits better performance in this respect, so that this statistic is generally recommended for checking adequacy of the model. the larger the value of 2i tˆr ( )ε and hence q*, the further autocorrelation will be the residuals. then, q* shows that the estimated model is inadequate and the obtained residual is not white noise. that is, there are still some information in lε̂ which are of particular trend and should be considered in the autocorrelation or ma component of previous values of zt. monthly seasonal time series parameters were estimated similar to the quarterly time series using conditional maximum likelihood method. complexity of modeling this data arises from identifying different types of unit roots that this process may have. 5. gómes-maravall model seats stands for signal extraction in arima time series; this is the model introduced by gómes and maravall for predicating seasonal data with missing data points. in this research, the gómes model was used to predict electricity price in energy market. this model uses monthly data and sarima to predict time series based on actual time series. this model enjoys numerous advantages. firstly, the data are studied based on monthly seasonal changes, e.g. it compares all octobers and uses the results for time-series prediction. secondly, missing data points may not interrupt the estimation flow. one of the most important advantages of this model is to assign larger weights to the most recent data during the period considered for prediction (gómez and maravall, 1998). in the present research, monthly data during 2006–2015 periods were used for estimating the models using gómes model. the program falls into the class of so-called arima-model-based methods for decomposing a time series into its unobserved components (i.e., for extracting from a time series its different signals). the program starts by fitting an arima model to the series. let xt denote the original series, (or its log transformation), and let: zt = δ(b)xt (8) represent the “differenced” series, where b attitudes for the lag operator, and δ(b) stand for the differences taken on xt in order to achieve stationarity. in seats, δ ∇ ∇b d s d( ) = (9) where d s ds1 b , and (1 b )= − = −∇ ∇ represents seasonal differencing of period s. the model for the differenced series zt can be expressed as φ θb z z (b)at( ) −( ) = (10) where z is the mean of zt, at is a white-noise series of innovations, ordinarily distributed with zero mean and variance σ2, ϕ(b) and θ(b) are ar and ma polynomials in b, correspondingly, which can be conveyed in multiplicative form as the produce of a regular polynomial in b and a seasonal polynomial in bs, as in ϕ(b) = ϕr (b)ϕs (b s) (11) θ(b) = θr (b)θs (b s) (12) putting together 1–5, the complete model can be written in detailed form as φ φ θ θr s s d s d t r s s tb b x b b a +c( ) ( )∇ ∇ = ( ) ( ) (13) and, in concise form, as φ(b) xt = θ(b) at+c (14) where φ(b) = ϕ(b)δ(b) represents the complete ar polynomial, including all unit roots. notice that, if p denotes the order of ϕ(b) and q the order of θ(b), then the order of φ(b) is p = p+d+d×s. the ar polynomial ϕ(b) is allowed to have unit roots, which are typically estimated with considerable precision. unit roots in ϕ(b) would be present if the series were to contain a nonstationary cyclical component, or if the series had been under differenced. they can also perform as nonstationary seasonal harmonics. the program decomposes a series that follows model (10) into several components. the decomposition can be multiplicative or additive. since the former becomes the second by taking logs, we shall use in the discussion an additive model, such as: jamalmanesh, et al.: prediction of hydropower energy price using gómes-maravall seasonal model international journal of energy economics and policy | vol 8 • issue 2 • 201886 xt = ∑ixit (15) where xit represents a component. the components that seats considers are: xpt = the trend component, xst = the seasonal component, xct = the cyclical component, xut = the irregular component. broadly, the trend component represents the long-term evolution of the series and displays a spectral peak at frequency 0; the seasonal component, in turn, captures the spectral peaks at seasonal frequencies. besides capturing periodic fluctuation with period longer than a year, associated with a spectral peak for a frequency between 0 and (2π/s), the cyclical component also captures shortterm variation associated with low-order ma components and ar roots with small moduli. finally, the irregular component captures erratic, white-noise behavior, and hence has a flat spectrum. the components are determined and fully derived from the structure of the (aggregate) arima model for the observed series, which can be directly identified from the data. the program is mostly aimed at monthly or lower frequency data and the maximum number of observations is 600. 6. run the models and result tramo (“time series regression with arima noise, missing observations, and outliers”) performs estimation, forecasting, and interpolation of regression models with missing observations and arima errors, in the presence of possibly several types of outliers. seats (“signal extraction in arima time series”) performs an arima-based decomposition of an observed time series into unobserved components. the two programs were developed by victor gomez and agustin maravall. used together, tramo and seats provide a commonly used as a program for seasonally adjusting a series. typically, individuals will first “linearize” a series using tramo and will then decompose the linearized series using seats. the parameters of the gomez-maravall model are estimated in table 1 that is derived from the implementation of this model. refer to gómez and maravall (1996) for the interpretation of table 1. after run the model and specify the parameters of model, the eviews software provides the price forecast for 24-month period, as shown in figure 3. 6.1. electricity price for hydropower plants to estimate the electricity price of the karun 1 and 3 dams, we use the forecasted results of the electricity price for masjedsoliman hydropower plant. the electricity price for these three power plants is close and there is no significant difference. as a result, ordinary least squares method is used to estimate these prices. to do this, we consider electricity prices for the karun 1 and 3 dam as a function of the price of the masjedsoliman hydropower plant. first, for the karun 3 hydroelectric power station we have: p = + .p +t t k3 msjd tα β ε (16) then for the karun 1 power plant: p = + .p +t t k1 msjd tα β ε (17) the predicted results are presented in table 2. using the above models, the results of which are reflected in table 2, the estimated values of electricity purchasing price from khuzestan hydroelectric power plants (by iranian electricity market) are presented in the following table 3. 7. conclusions in most of modeling practices, various possible methods have been used for estimating the models followed by comparing the methods based on statistics indicating the power of predictions. in the present research, however, gómez and maravall (1996) model are investigated and compared using seasonal data. prices tend to move along an average price determined by the competitive market forces. in electricity market, the production figure 3: 2-year forecast of electricity prices using the gomez maravall model table 1: the results of the gomez-maravall model in predicting electricity prices index 1 index 2 index 3 index 4 index 5 mq=12 imean=1 lam=-1 d=1 bd=1 p=0 bp= 0 q=1 bq=1 ireg=0 itrad=0 ieast=0 idur=0 m=36 qm=24 aio=2 int1=1 int2=120 rsa=0 seats=2 va=3.50 pc=0.143 noadm=1 bias=1 maxbias=0.5 smtr=0 thtr=-0.4 rmod=0.5 source: research results jamalmanesh, et al.: prediction of hydropower energy price using gómes-maravall seasonal model international journal of energy economics and policy | vol 8 • issue 2 • 2018 87 unit with the lowest efficiency will be the last unit to respond to the demand for electricity. moreover, as an effective factor in determining prices, air temperature follows a periodic pattern which returns to the average price. this pattern is commonly used to explain the autocorrelation of electricity price time series. as such, some sort of mean reversion model is expected for electricity prices. the solution which makes the model able to predict these data is to include the variable of time scattering variable into the mean reversion model. these models can further take into account intense fluctuations in the values of variables, making them suitable for modeling electricity price data which can be influenced by network interruptions, meteorological factors, sudden rise of demand, and production fluctuations. fluctuations in electricity prices are commonly not stable, so that the prices reverse to the mean rapidly. arima and seasonal arima models introduce effect of the information received from common and uncommon states into the model. some of the received information are of the type of normal events and result in smooth changes in prices; these changes are explained by the mean reversion model. some other received information is uncommon and lead to fluctuations in prices. these models express market prices as a function of preceding prices and previous error terms. short-term electricity prices are highly unstable due to inability to store the electricity, inelasticity of demand with respect to prices, and supply limitations, particularly during peak consumption periods. instantaneous (cash) instability of electricity prices may change due to weather conditions and the forces contribuxting to supply and demand. however, time series of mid-term prices, such as monthly average price, exhibit more stable trend and are seemingly more suitable for predictive models, especially in hydropower plants where loner-term seasonal changes are common. we used two programs were developed by victor gomez and agustin maravall. we used a commonly program, tramo and seats for seasonally adjusting a series. typically, individuals will first “linearize” a series using tramo and will then decompose the linearized series using seats. we used gómes-maravall model, an arima model was estimated for predicating electricity price in iranian market using energy purchase data from a hydropower plant. the model was run utilizing seats (signal extraction in arima time series) and tarmo (“time series regression with arima noise, missing observations, and outliers”) programs. for this purpose, energy purchase data from three karun river hydropower plants (khuzestan province, iran) was used. references areekul, p., swenjyu, t., toyama, h., yona, a. (2010), a hybrid arima and neural network model for short-term price forecasting in deregulated market. ieee transactions on power systems, 1: 524530. bell, w.r., hillmer, s.c. (1984), issues involved with the seasonal adjustment of economic time series. journal of business and economic statistics, 2, 291-320. bowerman, b., richard, t.o. (1987), time series forecasting. 2nd ed. boston, usa: duxbury press. burman, j.p. (1980), seasonal adjustment by signal extraction. journal of the royal statistical society a, 143, 321-337. cleveland, w.s., tiao, g.c. (1976), decomposition of seasonal time series: a model for the census x-11 program. jasa, 71: 581-586. darbellay, g.a., marek, s. (2000), forecasting the short term demand for electricity do neural network stand a better chance? international journal of forecasting, 16, 71-83. gómez, v. (1998), three equivalent methods for filtering finite nonstationary time series. working paper sgape 98003, ministerio de economía y hacienda, madrid. 4th coming in the journal of business and economic statistics. gómez, v., maravall, a. (1994), estimation, prediction and interpolation for nonstationary series with the kalman filter. journal of the american statistical association, 89, 611-624. gómez, v., maravall, a. (1996), programs tramo and seats; instructions for the user, working paper 9628, servicio de estudios, banco de españa. gómez, v., maravall, a., peña, d. (1999), missing observations in arima models: skipping approach versus additive outlier approach. journal of econometrics, 88, 341-364. hillmer, s.c., tiao, g.c. (1982), an arima-model based approach to seasonal adjustment. journal 01 the american statistical association, table 2: results of electricity price estimates for karun 1 and 3 dams r2ma (1)tβcdepended variables 0.990.57841.0063801electricity price of karun 1 0.990.71711.0191286electricity price of karun 3 source: research results table 3: predicted price of electricity purchased from hydropower plants of khuzestan province hydropower plants karun 1karun 3masjedsolimanmonths 465,386466,296454,923januaryfirst year 471,238472,159460,643february 477,080478,013466,354march 483,112484,056472,250april 489,369490,326478,367may 496,064497,034484,911june 502,188503,169490,897july 509,145510,140497,698august 520,764521,782509,056september 512,859513,861501,328october 529,357530,392517,456november 536,405537,454524,345december 565,592566,698552,876januarysecond year 550,020551,095537,654february 582,781583,920569,678march 563,753564,855551,078april 570,994572,110558,156may 578,311579,442565,309june 585,923587,069572,750july 593,691594,852580,343august 599,149600,320585,678september 594,117595,279580,760october 618,120619,329604,223november 626,631627,857612,543december source: research results jamalmanesh, et al.: prediction of hydropower energy price using gómes-maravall seasonal model international journal of energy economics and policy | vol 8 • issue 2 • 201888 77, 63-70. maravall, a., pierce, d.a. (1987), a prototypical seasonal adjustment model. journal 01 time series analysis, 8, 177-193. nogales, fj., contreras, j., conejo, a.j., espinola, r. (2002), forecasing next-day electricity price by time series models. ieee transactions on power systems, 17(2), 342-348. samer, s., elie, b., george, n. (2001), univar ate modeling and forecasting of energy consumption: the case of electricity in lebanon. energy, 2(6), 1-14. senjyu, t. (2010), next day price forecasting in deregulated market by combination of artificial neural network and arima time series models. 5th ieee conference on industrial electronics and applications. p1451-1456. sun, w.e.i., lu, j., meng, m. (2006), application of time series based svm model on next-day electricity price forecasting under deregulated power market. proceedings of the 5th international conference on machine learning and cybernetics, dalian. p13-16. tiao, g.c., tasay, r.s. (1983), consistency properties oí least squares estimates of autoregressive parameters in arma models. the annals ol statistics, 11, 856-871. voronin, s., partanen, j. (2013), forecasting electricity price and demand using a hybrid approach based on wavelet transform, arima and neural networks. international journal of energy research, 1(3), 331-338. zhang, g.p. (2003), time series forecasting using a hybrid and neural network model. neurocomputing, 50, 159-175. . international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2016, 6(2), 202-207. international journal of energy economics and policy | vol 6 • issue 2 • 2016202 pollutant emissions, energy consumption and economic growth in nigeria philip o. alege1, oluwasogo s. adediran2, adeyemi a. ogundipe3* 1department of economics and development studies, college of business and social sciences, covenant university, ota, ogun, nigeria, 2department of economics and development studies, college of business and social sciences, covenant university, ota, ogun, nigeria, 3department of economics and development studies, college of business and social sciences, covenant university, ota, ogun, nigeria. *email: ade.ogundipe@covenantuniversity.edu.ng abstract the study investigates the direction of causal relationships among emissions, energy consumption and economic growth in nigeria using annual time series data for the period 1970-2013. the johansen maximum likelihood cointegration tests indicate an existence of a unique cointegrating vector, and the normalized long run estimates shows that fossil fuel enhances carbon emissions whereas, clean energy source (electricity) mitigate the atmospheric concentration of carbon dioxide (co2) emissions. similarly, the wald exogeneity granger causality test indicates an existence of unidirectional causation running from fossil fuel to co2 emissions and gross domestic product (gdp) per capita. alternatively, non-fossil energy (electric power) causes more proportionate change in gdp per capita but our result could not establish any causal link between electric power and carbon emissions. finally, charting a channel towards ensuring sustainable environment and economic development involves a progressive substitutability of clean energy sources for fossil consumption. keywords: carbon dioxide emissions, energy consumption, johansen cointegration, granger causality jel classifications: c22, o13, q53 1. introduction every developed and developing economy of the world desire a certain level of economic growth and sustainable development, but climate change and global warming as a common and controversial environmental issues in this modern age poses threat to achieving this objective. this is because a sizable portion of the world’s energy consumption need is met through fossil fuels. therefore, increase in global trade and a rapid surge in economic activities around the world have caused a significant increase in carbon dioxide (co2) emission. as heavy use of energy and other natural resources cause environmental deterioration, also the gas emissions from fossil consumption increases the amount of co2 which harms the environment as well as inflicting irreparable damages on the atmosphere. this in turn leads to extremely risky climate changes such as drought, floods and rising sea levels. the global impacts are already apparent in increasing the frequency of extreme weather events, heightening storm intensity and reversing ocean currents. these changes, additionally, have significant impacts on the functioning of ecosystems, the viability of wildlife, and the wellbeing of humans. meanwhile, the predictions by the assessment report of the intergovernmental panel on climate change (ipcc) in 2007, has established that africa is more vulnerable to global warming and climate change. this is evident in subsequent decline of water availability from 50% to 30% of population access and a decline of about 20% in agricultural yields across the continent in the last few years. therefore, the complex nature of the relationship between pollutant emissions, energy consumption and economic growth process has been a subject of inquiry among scholars and policy analysts since energy is considered as an important driving force of economic growth. an understanding of this tripartite relationship in nigeria and other african countries becomes important in charting a pathway towards ensuring sustainable development. why is nigeria a suitable case study? and why should nigeria be bothered? nigeria as the giant of africa has been on the focus alege, et al.: pollutant emissions, energy consumption and economic growth in nigeria international journal of energy economics and policy | vol 6 • issue 2 • 2016 203 of the world for its spectacular gdp growth as well as high energy demand growth in recent years. for instance, statistical evidence from nigerian economic outlook (2014) has shown that the nigerian economy has consistently grown by an average of over 6% in the last few years. the economy grew at 5.3% in 2011; 4.2% in 2012, exceeded 5.5 in 2013 and 7.4% in 2014. but in spite of this impressive consistent growth, the supply of electricity in nigeria has remained irregular. this has ultimately led to the shift to alternative sources of power that has largely required burning of fossil fuels and subsequent increase in emission level. therefore, there is no doubt that the current emission profile of nigeria poses a significant challenge to the country’s economic growth. evidence from existing literature shows a number of empirical and theoretical studies on the environment-growth nexus that focused in developing and developed countries (e.g. hansen and king 1996; devlin and hansen 2001; akinlo 2008; odhiambo 2009; ziramba 2009; wolde-rufael and menyah 2010; onakoya et al., 2013; oyedepo 2013; olarinde et al., 2014; dinh and shih-mo, 2015), these studies have offered plausible results and explanations for this nexus. ironically, they might have suffered from the problem of omitted variables. secondly, there is still lack of specific study for nigeria that has employed modern time series econometrics of cointegration and causality to test the causal relationship between pollutant emissions, energy consumption and economic growth in a more coherent framework. therefore, pertinent to this methodological flaw, this study aims at filling this gap by investigating the causal relationship between pollutant emissions, energy consumption and economic growth in a multivariate modelling framework while including an indicator for dirty and clean energy sources. this is to show how environmental degradation and other crucial variables affect growth process in nigeria. from an econometric argument, we include these variables because they are relevant and their exclusion may not only bias the estimates, but also make them inconsistent lukepohl (1982). furthermore, since a multivariate modelling framework gives more information than a bivariate framework, the causal inference drawn may be relatively more reliable loizides and vamvoukas (2005). the granger causality test examines the causal relationship between pollutant emissions; energy consumption and economic growth within a multivariate johansen’s cointegration and errorcorrection framework. in addition to the analysis of granger causality, this study also considers the individual and block exogeneity of the explanatory variables. this will enhance the robustness of the results. the remainder of this paper is organised as follows. the next section briefly presents some stylized facts on energy consumption demand and economic growth in nigeria. in section three, we give an overview of the literature on environment-energygrowth nexus. section four is concerned with methodology and the empirical model. section 5 gives the empirical analysis and results; and section 6 addresses the conclusion and policy recommendations. 2. some stylized facts on energy consumption demand and economic growth in nigeria the nigerian economy has experienced phenomenal growth over the last one decade with the growth rate averaging about 6% in the last few years. being the most populous nation in africa with an estimated population of over 160 million, this rapid growth has enlisted this country as the fastest growing economy among developing nations. however, with this strong economic growth, nigeria demand for energy is increasing just as pollutant emissions (figure 1). this is because an attempt to achieve higher growth rate and development is usually at the expense of the environment. according to olarinde et al., (2014), nigeria`s gdp per capita growth rate in 2011 was 249.52% higher than 1980 value. although in 2011 the co2 emission per capita experienced a decline with a growth rate of –50.42% of 1980 value, this was not enough to reduce the level of carbon intensity. the country’s carbon intensity experienced a marginal increase of about 12.11% of 1980. this is not surprising, given that manufacturing share of the country’s gdp was significantly higher than other sectors’, with services sector which is expected to be environmental-friendly accounting for only 26.6% of the gdp in 2010 fiscal year (table 1). then, it is also of note that the magnitude of emission of carbons in the country’s atmosphere varied among the sectors and type of energy used. for instance in 2009, as explained by shuaibu and oyinlola (2013), total co2 emissions from combustion fuels stood at 41.2% while electricity and heat generated 8.2%. the manufacturing and construction sectors emitted 3.1% while the energy industry stood at 4.5%. while, the transport sector was the highest emitter of co2 with almost 24% with the road sector component dominating. other sectors cumulating emission stood at 2%. 3. an overview of the literature on environment-energy-growth nexus the seminal work of kraft and kraft (1978) presented the premier study on the causal relationship between economic growth and energy consumption, thereafter, several studies have attempted to investigate the causal link in the recent time (soytas et al., 2007; odhiambo 2009; akpan and akpan, 2012; ogundipe and apata, figure 1: trend of energy consumption, co2 emission and growth source: shuaibu and oyinlola (2013) alege, et al.: pollutant emissions, energy consumption and economic growth in nigeria international journal of energy economics and policy | vol 6 • issue 2 • 2016204 2013; shahbaz et al., 2013; onakoya et al., 2013; olarinde et al., 2014; shahbaz et al., 2014; apergis and ozturk, 2015, al-mulali et al., 2015). even though this link has been extensively studied in nigeria, most of these studies mainly focus on testing the validity of the environmental kuznets curve (ekc) (e.g., omotor, 2008; odularu and okonkwo 2009; olusanya 2012; and bozkurt and akan 2014), and do not consider investigating the causal link of environment-energy-growth nexus in the same framework. though, literature abound on the empirical examination of the nexus in advanced economies (ozturk and acaravci 2010; acaravci and ozturk 2010) but an evaluation is expedient for the nigerian economy. however, since fossil-fuel energy use is the main source of global warming, incorporating energy consumption and other growth relevant factors such as human capital and institution in the growth framework can enhance a better understanding of the issues surrounding the effect of global warming. in view of this, recent studies that attempted to investigate the causal relationship between pollutant emissions, energy consumption and economic growth seems to be inconsistent concerning the direction of causality. for instance, soytas et al., (2007) in the u.s.a., found that income does not granger cause carbon emissions in the short-run but that there is a long-run causal link between energy use and carbon emissions. apergis and payne (2009), used a panel cointegration and panel causality tests in investigating some group of countries in south america and discovered that energy use had a positive and a statistically significant impact on emissions while, energy consumption and economic growth cause emissions in the short-run, but in the long-run, there was evidence of a feedback between energy consumption and emissions, but no feedback between real output and pollutant emissions. for a group of commonwealth of independent states, apergis and payne (2009), found that both energy consumption and economic growth cause co2 emissions in the short-run, but there appears to be bidirectional causality between energy consumption and co2 emissions in the long run. for west african countries, olarinde et al. (2014), using a fixed effects panel regression model examined the relationship between co2 emission and economic growth and found that in the long run, there is an n-shape relationship between income and co2 emissions and that the ekc hypothesis is not supported for west africa. in the case of nigeria, shuaibu and oyinlola (2013), while relying on zivot-andrews unit root test and gregory-hansen cointegration test, established that due to structural shifts, there is no causal link between co2 emission and energy consumption to economic growth. consequently, in china, ang (2009) found that more energy use, higher income and greater trade openness tend to cause more co2 emissions. but in a multivariate causality study for china, zhang and cheng (2009) found a unidirectional granger causality running from gdp to energy consumption to carbon emissions in the long-run but neither carbon emissions nor energy consumption leads to economic growth. the foregoing conflicting evidences and results have major implications for reducing co2 emissions and economic growth. in a case of unidirectional granger causality, which runs from co2 emissions to economic growth, where rise/fall in co2 emissions leads to rise/fall in economic growth, then an energy strategy that encourages reduction of co2 emissions could lead to an ultimate decrease in economic growth. by implication, economic growth could be sacrificed in order to reduce co2 emissions. likewise, if causality runs from economic growth to co2 emissions, where rise/fall in economic growth cause rise/ fall in co2 emissions, then, an energy policy that reduces co2 emissions may have no negative effect on economic growth. this implies that, it may be possible to reduce co2 emissions without necessarily harming economic growth. but in a case of no causality running in any direction, then, the neutrality hypothesis is not rejected, and reducing co2 emissions may not affect economic growth. in contrast, in case of a bidirectional causality running between the two; economic growth leads to more co2 emissions, and then this may increase the environmental degradation. 4. methodology 4.1. model the study adopts the standard ekc specification developed by grossman and krueger (1991) in investigating the environmental pollution impact of north america free trade agreement (nafta). the model has been extended and applied to developing africa economies by extant studies such as ogundipe et al. (2014); ogundipe et al., (2015); and oshin and ogundipe (2014) to ascertain the effect of income on environmental quality. an expended ekc model for the study is presented thus: table 1: structure of output, gdp per-capita and rate of co2 emission for selected countries in west africa (2009-2010) country gdp per capita (us $) agric % of gdp industry % gdp manufacturer % of gdp services % of gdp co2 emission growth rate nigeria 5.05 32.7 40.7 2.6 26.6 5.55 ivory coast 0.37 22.9 27.4 19.2 49.7 2.5 ghana 5.47 30.2 18.6 6.5 51.1 18.98 senegal 1.24 16.7 22.1 12.8 61.1 –1.54 liberia 6.04 61.3 16.8 12.7 21.9 –5.59 burkina faso 4.86 33.3 22.4 13.6 44.4 –1.49 benin –0.35 32.2 13.4 7.5 54.4 8.92 togo 1.33 43.5 23.9 10.1 43.5 3.27 average 4.33 33.6 22.9 8.39 43.4 7.29 source: olarinde et al., (2014) alege, et al.: pollutant emissions, energy consumption and economic growth in nigeria international journal of energy economics and policy | vol 6 • issue 2 • 2016 205 lco ly ly lfc lhc lpc ist t t t t t t t t 2 0 1 2 2 3 4 5 6 = + + ( ) + + + + + β β β β β β β µ the description of the variables is as follow: lco2t: co2 emissions (kiloton) lyt: gdp per capita (2005 constant us$) lfct: fossil fuel energy consumption lhct: human capital (proxied by total school enrolment) lpct: electric power consumption (kwh) istt: institutions (average of four indicators provided by wgi government effectiveness, regulatory quality, rule of law and control of corruption) 4.2. data source the study adopted an annual time series data for the period 1970 to 2013 for nigeria. the data for gdp per capita, co2 emissions, electric power consumption, fossil fuel consumption, and school enrolment (proxy for human capital) were obtained from the world development indicators (2014) of the world bank while the data for institutions were sourced from the world governance indicators (2014) of the world bank. 4.3. estimation procedure the analyses in this paper are carried out in three phases. the estimation process began by conducting the unit root test using augmented dickey-fuller (adf) and philip perron (pp) tests. this becomes expedient to avoid spurious regression. secondly, we estimated the johansen maximum likelihood cointegration test and the vector error correction model (vecm) to obtain the long run estimates and ascertain the long-run sustainability of the model respectively. finally, we conducted the block wald exogeneity granger causality test in order to ascertain the direction of causal relationship among the variables in the model. 4.4. discussion of results the estimation process began by examining the time series properties of the variables in the model. for the purpose of ensuring a robust analysis, the adf and the philip perron (pp) tests were employed. according to the tests, the series all became stationary at first difference, it implies that we failed to reject the null hypothesis of no unit root at i (0); hence, the series were integrated at order i (1) (tables 2 and 3). having satisfied the sufficient condition of integration at order i (1) for the series, the study proceeds to estimate the johansen cointegration tests. the johansen likelihood test is preferred to the engle-granger two step procedure as the former enable a simple straightforward analysis and capable of generating the long-run coefficient estimates. two prominent tests are conducted in the johansen cointegration analysis the trace and the maximum eigen-value tests. the trace and the maximum eigen-value tests indicate one and two number of cointegration ranks respectively. the cointegrating vector is ascertained at points where the test statistics is less than the critical values. as aforementioned, the johansen technique presents the long-run estimates. it is worthy to note that the approach is a multivariate analysis in which all variables are regarded as endogenous, and in order to ascertain the relationship among the variables, we simply normalised the explanatory variables with the coefficient of the dependent variable. the normalised long run model shows that at gdp per capita and the squared of gdp per capita varies inversely and directly with co2 emissions respectively, hereby refuting the ekc hypothesis. consequently, fossil fuel influences co2 significantly and positively. the result reveals that a percent change in fossil fuel consumption leads to about 20% change in atmospheric co2 concentration. to put succinctly, fossil fuel exerts a fairly large positive elastic variation on carbon emissions. the evidence portrays the present reality in nigeria, as inadequate supply of cleaner energy sources has limited the substitutability of fossil fuel. fossil fuel is consumed practically in all social and economic facets of human activities, ranging from automobiles, household and business power generating purposes. on the other hand, electric power consumption (a cleaner energy source) varies significantly and negatively with co2 emissions. this implies that substituting cleaner non-fossil energy for fossil fuel significantly improves environmental quality. also, the indicator of human capital and institutions does not influence co2 significantly. this might not be unconnected with the weak quality of regulatory enforcement in nigeria, the bureaucratic inefficiencies in the electricity sectors had left everyone to the use of dirty energy sources. having established the existence of cointegration, the study proceeds to estimate the vecm. the model incorporates the error adjustment mechanism into the system of equations. this ensures that immediate errors in the model are corrected in the successive periods. in order to attain a meaningful error correction, the ecm is expected to be negative, its absolute value must lie between 0 and 1 and the t-statistic must be significant. the estimated result shows an error correction coefficient of –0.0158, implying that about 2% of short run errors are corrected as the model attains its long run equilibrium. the low absolute value of the ecm coefficient indicates that errors (deviations) are weakly restored in the model. table 4 presents the result of the block exogeneity granger causality test. the test result shows evidence supporting a unidirectional causality from fossil fuel to co2 emissions (lfc∃lco2) and gdp per capita (lfc∃ly). that is, changes in fossil fuel consumption granger causes a change in the level co2 emissions and gdp per capita. this implies that dirty growth accounts for significant proportion of nigeria growth experience. on the other hand, a unidirectional causality runs from electric power consumption to gdp per capita (lep∃ly) but the study found no evidence of causality between electric power consumption and co2 emissions. these evidences suggest that cleaner energy sources (electricity) do not contribute to environmental degradation and thus suitable towards attaining a sustainable environment. finally, the wald causality test provides insight on the exogeneity status of explanatory variables, the rejection of the null hypothesis indicates that fossil fuel, electric power consumption and education are truly exogenous to the model. alege, et al.: pollutant emissions, energy consumption and economic growth in nigeria international journal of energy economics and policy | vol 6 • issue 2 • 2016206 5. conclusion and recommendations the study investigates the direction of causal relationship among pollutant emissions, energy consumption and economic growth in nigeria using annual time series data for the period 19702013. the study adopted the maximum likelihood johansen cointegration technique; the normalized long run estimates show that fossil fuel consumption enhances the level of environmental degradation in nigeria by increasing more than proportionately the concentration of co2 emissions. conversely, electric power consumption varies inversely with carbon emissions, implying that as adoption of cleaner energy source (electricity) increases, the atmospheric concentration of carbon emissions dwindle. the result from the wald exogeneity causality test indicate an evidence supporting a unidirectional causality running from fossil fuel to co2 emissions, gdp per capita and the squared of gdp per capita. also a unidirectional causal relation exists from electric power consumption and indicator of human capital gdp per capita and co2 emissions, respectively. the foregoing evidence reveals that, though, the consumption of dirty fuel sources enhance per capita income but its increasing use jeopardizes the sustainable environment agenda by increasing the accumulation of co2 concentration. alternatively, electric power consumption table 2: unit root test variables augmented dickey–fuller philip perron with a time trend without a time trend with a time trend without a time trend ly –0.0711 (3) 0.1242 (3) –0.2987 (3) –0.3838 (3) lco2 –2.4148 (3) –2.332 (3) –2.4086 (3) –2.3107 (3) lpc –2.8425 (3) –1.0369 (3) –2.9050 (3) –0.6833 (3) lfc –2.2459 (3) –3.1663 (3) –2.2368 (3) –3.1615 (3) lhc –2.5282 (3) –2.2906 (3) –1.8825 (3) –2.0872 (3) list –2.1434 (3) –0.5734 (3) –6.2700 (3) –2.3486 (3) ↑ly –6.4045 (3)*** –5.7812 (3)*** –6.4020 (3)*** –5.9044 (3)*** ↑lco2 –6.8411 (3)*** –6.9034 (3)*** –6.8188 (3)*** –6.8791 (3)*** ↑lpc –8.5202 (3)*** –8.6315 (3)*** –8.7256 (3)*** –8.8516 (3)*** ↑lfc –5.8626 (3)*** –5.3733 (3)*** –5.8503 (3)*** –5.3605 (3)*** ↑lhc –3.3731 (3)*** –3.2839 (3)*** –3.4639 (3)*** –3.3668 (3)*** ↑ist –20.4210 (3)*** –20.5864 (3)*** –26.2548 (3)*** –23.6888 (3)*** source: computed using e-views 7.0, lag lengths (in parenthesis) are determined by aic, ***: significance at 1% level table 3: maximum likelihood cointegration tests cointegration rank trace test maximum eigen test statistics critical value probability* statistics critical value probability* none* 175.6081 139.2753 0.0001 56.9581 49.5868 0.0073 at most 1 118.6500 107.3466 0.0073 40.1915 43.4198 0.1078 at most 2 78.4585 79.3415 0.0581 23.7425 37.1636 0.6811 at most 3 54.7160 55.2458 0.0556 19.1633 30.8151 0.6178 at most 4 35.5527 35.0109 0.0437 17.0058 24.2520 0.3363 at most 5 18.5469 18.3977 0.0477 10.9629 17.1477 0.3146 at most 6 7.5841 3.8415 0.0059 7.5841 3.8415 0.0059 normalized cointegration equation lco2+161.388 (0.74) ly–12.460(–0.74) ly 2–20.181(–6.12) lfc+0.297 (0.09) lhc+23.646 (7.98) lep–2.636(–1.47) ist+4.712trend error correction coefficients variable ↑(lco2   ) ↑(ly) ↑(ly  2    ) ↑(lfc) ↑(lhc) ↑(lpc) ↑(ist) ecm (–1) –0.0158 –0.0091 –0.1238 0.0073 0.0069 0.0057 –0.0194 t-statistics* –1.6155 –2.2305 –2.3363 1.3448 2.0827 0.5918 –0.9861 source: computed using e-views 7.0, 95% critical value, the lag structure of var is determined by aic, t-values are given in parentheses, *: significance at 5% level table 4: block exogeneity granger causality test dependent variables f-statistics t-statistics short-run long-run ↑(lco2   ) ↑(ly) ↑(ly  2    ) ↑(lfc) ↑(lhc) ↑(lpc) ↑(ist) ectt‑1 ↑(lco2) 0.9821 0.8913 0.2821 0.0515* 0.0430* 0.2818 0.2882 –1.6155* ↑(ly) 0.1911 0.8621 0.3881 0.0918* 0.9911 0.0432* 0.8139 –2.2305* ↑(ly  2) 0.2917 0.3872 0.8768 0.0895* 0.9281 0.1821 0.3819 –2.3363* ↑(lfc) 0.8971 0.1823 0.1277 0.9821 0.6517 0.1291 0.9821 1.3448 ↑(lhc) 0.8392 0.8910 0.8720 0.7821 0.7810 0.7819 0.3667 2.0827* ↑(lep) 0.1871 0.5711 0.7631 0.2863 0.9721 0.7829 0.3765 0.5918 ↑(ist) 0.2876 0.6891 0.3681 0.7681 0.1821 0.8611 0.3767 –0.9861 source: computed using e-views 7.0, *: significance at 5% level alege, et al.: pollutant emissions, energy consumption and economic growth in nigeria international journal of energy economics and policy | vol 6 • issue 2 • 2016 207 granger causes gdp per capita but has no causal link with co2, the finding from the johansen long run estimates corroborates this fact which implies that cleaner energy sources is capable of charting an appropriate platform towards attaining a sustainable environment and economic development. references acaravci, a., ozturk, i. (2010), on the relationship between energy consumption, co2 emissions and economic growth in europe. energy, 35(12), 5412-5420. akinlo, a.e. (2008), energy consumption and economic growth: evidence from 11 subsahara african countries. energy economics, 30, 2391-2400. akpan, g.e., apkan, u.f. (2012), electricity consumption, carbon emissions and economic growth in nigeria. international journal of energy economics and policy, 2(4), 293-308. al-mulali, u., saboori, b., ozturk, i. (2015), investigating the environmental kuznets curve hypothesis in vietnam. energy policy, 76, 123-131. ang, j.b., (2009), co2 emissions, research and technology transfer in china. ecological economics, 68, 2658-2665. apergis, n., ozturk, i. (2015), testing environmental kuznets hypothesis in asian countries. ecological indicators, 52, 16-22. apergis, n., payne, j.e., (2009), co2 emissions, energy usage, and output in central america. energy policy, 37, 3282-3286. bozkurt, c., akan, y. (2014), economic growth, co2 emissions and energy consumption: the turkish case. international journal of economics and policy, 4(3), 484-494. devlin, n., hansen, p. (2001), health care spending and economic output: granger causality. applied economics letters, 8, 561-564. dinh, h., shih-mo, l. (2015), dynamic causal relationships among co2 emissions, energy consumption, economic growth and fdi in the most populous asian countries. advances in management and applied economics, 5(1), 69-88. grossman, g., krueger, a. (1991), environmental impacts of a north america free trade agreement, natural bureau of economy. research working paper no. 3194, cambridge: nber. hansen, p., king, a. (1996), the determinants of health care expenditure: a cointegration approach. journal of health economics, 15(1), 127-137. kraft, j., kraft, a. (1978), on the relationship between energy and gnp. journal of energy and development, 3, 401-403. loizides, j., vamvoukas, g. (2005), government expenditure and economic growth: evidence from trivariate causality testing. journal of applied economics, viii(1), 125-152. lütkepohl, h. (1982), non-causality due to omitted variables. journal of econometrics, 19, 367-378. nigerian economic outlook (aeo). (2014), africa development bank group publication. available from: http://www.afdb.org/en/ countries/west-africa/nigeria/nigeria-economic-outlook/. odhiambo, n.m., (2009), electricity consumption and economic growth in south africa: a trivariate causality test. energy economics, 31, 635-640. odularu, g.o., okonkwo, c. (2009), does energy consumption contribute economic performance? empirical evidence from nigeria. journal of economics and international finance, 1(2), 044-058. ogundipe, a., apata, a. (2013), electricity consumption and economic growth in nigeria. journal of business management and applied economics, 11(4), 1-14. ogundipe, a.a., alege, p.o., ogundipe, o.m. (2014), income heterogeneity and environmental kuznets curve in africa. journal of sustainable development, 7(4), 165-180. ogundipe, a.a., olurinola, i.o., odebiyi, j.t. (2015), examining the validity of ekc in western africa: different pollutant option. environmental management and sustainable development, 4(2), 69-90. olarinde, m., martins, i., abdulsalam, s. (2014), an empirical analysis of the relationship between co2 emissions and economic growth in west africa. america journal of economics, 4(1), 1-17. olusanya, s.o. (2012), long-run relationship between energy consumption and economic growth: evidence from nigeria. journal of humanities and social sciences, 3(3), 40-51. omotor, d.g. (2008), causality between energy consumption and economic growth in nigeria. pakistan journal of social sciences, 5(8), 827-835. onakoya, a.b., onakoya, a.o., jimi-salami, o., odedairo, b.o. (2013), energy consumption and nigerian economic growth: an empirical analysis. european scientific journal, 9(4), 25-40. oshin, s., ogunipe, a.a. (2014), an empirical examination of environmental kuznets curve (ekc) in western africa. euro-asia journal of economics and finance, 3(1), 18-28. oyedepo, s.o. (2013), energy in perspective of sustainable development in nigeria. sustainable energy, 2, 14-25. ozturk, i., acaravci, a. (2010), co2 emissions, energy consumption and economic growth in turkey. renewable and sustainable energy review, 14(9), 3220-3225. shahbaz, m., ozturk, i., afza, t., ali, a. (2013), revisiting the environmental kuznets curve in a global economy. renewable and sustainable energy reviews, 25, 494-502. shahbaz, m., sbia, r., hamdi, h., ozturk, i. (2014), economic growth, electricity consumption, urbanization and environmental degradation relationship in united arab emirates. ecological indicators, 45, 622-631. shuaibu, m.i., oyinlola, m.a. (2013), energy consumption, co2 emissions and economic growth in nigeria. paper presented at the 2013 naee international conference, lagos, nigeria. soytas, u., sari, r., ewing, b.t. (2007), energy consumption, income, and carbon emissions in the united states. ecological economics, 62, 482-489. wolde-rufael, y., menyah, k. (2010), energy consumption, pollutant emissions and economic growth in south africa. energy economics, 32(2010), 1374-1382. world development indicators (wdi). (2014), world bank publication. available from: http://www.data.worldbank.org/data-catalog/worlddevelopment-indicators. zhang, x.p., cheng, x.m. (2009), energy consumption, carbon emissions, and economic growth in china. ecological economics, 68, 27062712. ziramba, e., (2009), disaggregate energy consumption and industrial production in south africa. energy policy, 37(6), 2214-2220. . international journal of energy economics and policy | vol 8 • issue 2 • 2018102 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(2), 102-110. the impact of oil revenue shocks on the volatility of iran’s stock market return sina davoudi1*, alireza fazlzadeh2, firouz fallahi3, hossein asgharpour4 1ma in financial management, management department, faculty of economics, management, and business, university of tabriz, iran, 2associate professor, management department, faculty of economics, management, and business, university of tabriz, iran, 3associate professor, management department, faculty of economics, management, and business, university of tabriz, iran, 4associate professor, management department, faculty of economics, management, and business, university of tabriz, iran. *email: cna.davoudi@outlook.com abstract the aim of this study was to examine the impact of oil revenue shocks on the volatility of tehran’s stock market return, by applying generalized auto regressive conditional heteroscedasticity (garch) model with seasonal data from january 1993 to march 2014. after calculating the volatility stock returns via garch models, we employed auto regressive distributed lag (ardl) model to estimate the oil shocks effects. the population is consisted of all active companies in tehran’s stock market during the period of this research. study results showed that oil shocks are associated with positive effects on the stock market volatility, representing that this shocks are one of the main motivators of stock price index growth in iran’s case. more ever, exchange rate and liquidity had same effects on the stock market return through increasing the volatility. on the other hand our results indicated that there were no relations between consumer price index and stock market volatility. other result of this study refers to effects of sanctions imposed by the us and europe, which elicits the increase of stock market volatility from the day they have been taken place. keywords: oil revenue, stock market returns volatility, sanctions, exchange rate, consumer price index, portfolio management jel classifications: m21, g11, e10 1.introduction previous studies and investigations indicate that fluctuations in total revenues, whether as a result of rise and falls and economic instabilities, or international sanctions, can create serious challenges for market participants. for example, oil prices and related shocks can lead to stagnation in stock markets and, consequently, to fluctuations in revenues which can in turn be a moderator of consumer prices and a prospect for growth and development. the rise in oil prices in exporting countries yields a higher income for them as well. since minimizing the risk of the intended portfolio is one of the most important duties of the policy makers, investors and, ultimately, financial managers, paying attention to the impacts of fluctuations and shocks from markets and other external factors, such as oil price changes, exchange rates, and imposition of sanctions have become more and more significant, all of which are demonstrated through the revenues of governments on the macro level. based on statistical evidence and the study of the outcome of sanctions imposed by the united nations, eu and the us on iran’s economy, oil revenues in iran have encountered various fluctuations over the past two decades. on the other hand, studies on the iranian stock market in the last two decades indicate that fluctuations in the stock market and, consequently, the volatility of this market’s return are significant. the main question is what connection can be discovered between stock return volatility in the stock market and oil revenues fluctuations. the purpose of the present study is to investigate the impacts of fluctuations in oil revenues of the country alongside official exchange rate, price index, liquidity supply, and sanctions on iranian stock market fluctuations in order to create a field for selection and management of the portfolio with the least risk of oil revenue shocks. in this regard, after presenting the introduction, the theoretical foundations and the theoretical origins of the issue concerning the impacts of macroeconomic variables on stock return volatility in different countries will be presented. afterwards, previous domestic and foreign studies will davoudi et al.: the impact of oil revenue shocks on the volatility of iran’s stock market return international journal of energy economics and policy | vol 8 • issue 2 • 2018 103 be reviewed and the methodology of the research and the model estimation will be presented. in conclusion, the summaries and suggestions will be presented for the article. 2. theoretical basics the importance of examining the impact of oil market shocks on the iranian economy as the third largest producer in the organization of petroleum exporting countries in 2010 and the fifth largest exporter according to the latest statistics of the organization of petroleum exporting countries (opec) in 2014, is due to the large volume of oil export revenues and the annual government budget, in a way that fluctuation in the world oil prices and, consequently, changes in government revenues from oil sales play a major role in the country’s economic performance and the iranian stock market (table 1 and chart 1). it is believed that stock returns are determined by some macroeconomic variables such as macro revenues of governments, interest rates, currency, liquidity, and inflation. several studies have been conducted to demonstrate the effect of economic forces on stock returns in different countries. for example, the arbitrage pricing theory, first proposed by stefan ross in 1976, was later used by chen et al. (1986) to illustrate the impact of some macroeconomic variables on stock return of capital markets in the united states. their findings indicated that industrial productions and changes in the risk and periodical structure have positive relationship with expected stock returns. however, the relationship between the predicted and unpredicted inflation ratio and the expected stock returns is significantly negative. chen et al. (1986) proposed the arbitrage pricing theory as a substitute for capital asset pricing model. the process of the capital asset pricing model starts with the question of how investors cannot create an effective portfolio, while arbitrage pricing theory observes the risk issues and its measurement from a completely different point of view and does not pursue effective investment portfolios; it argues on the basis that stock prices are moderated as shareholders seek for arbitrage profits. in other words, the capital asset pricing model was in fact a simplified version of the arbitrage pricing theory which assumed that only a systematic factor affects the yield of securities (bodie et al., 2011). the experiments performed on the arbitrage pricing model indicated that it overtakes the capital asset pricing model (chen, 1983). with such an understanding of the arbitrage pricing theory, the relationship between stock return and the factors of such a model and its ability to predict the future can be estimated through modeling based on economic factors and assuming that the stock market has a reasonable performance. 2.1. the concept of return volatility uncertainty is unpredictable changes in an economic variable and as such changes cannot be predicted in the future, it can have great impacts on other economic variables; therefore, it cannot be treated as a lateral issue, but should be addressed in a context, aspects of which would be accepted as pervasive reality and to create proper theory and mechanism to compete with it (morad pour olaadi et al., 1999). uncertainty is often defined as standard deviation of variance which has a specific meaning in each example and subject. for example, in relation to stock returns, standard deviation is indicative of risk. volatility refers to the degree of uncertainty or risk of changes in the value of any type of securities. high volatility means that the value of securities, for example, and the stock price can fluctuate in a greater range, meaning that, the stock price can vary considerably in both directions over a short period of time, but changes in value do not occur at a constant rate over time. the stock return alone encompasses information content and most of the actual and potential investors practice it in their predictions and financial analyses (gha’emi and tousi, 2005). 2.2. oil revenues as a result of total demand and global fluctuations in oil prices the vast majority of opec member countries are almost oneproduct exporters in their export sectors; in other words, oil revenues are considered as the main source of export income, or at least as one of the most important sources of export income in such countries; they may feel direct effect of oil prices due to great dependence on oil. oil exports provide a large part of foreign and government revenues and budgets for these countries, and uncertainty in the changes in their incomes through oil pricing plays a key role in the development of these countries and their financial markets. it can be demonstrated through evidence that, apart from the years when oil prices have fallen sharply, in other years, the cost of oil production is less than 10% of the oil price; in fact, 90% of the revenue from oil production is net or profits (sameti et al., 2009). since the mentioned revenue is deposited to the treasury account and is distributed in accordance with the government’s attitude, it is important to examine its changes over time alongside with the change in the rate of other macroeconomic variables, such as exchange rate, liquidity growth rate, and so on. in addition, the share of oil revenues in the general government budget was more than 80%, which has been fluctuating between 60-80% in recent years (behboudi et al., 2009). in the following, the approaches and mechanisms affecting oil revenues and its fluctuations will be analyzed theoretically. to this end, the mechanisms affecting oil revenues from the two perspectives of oil price fluctuations and total demand will be examined. 2.2.1. oil price oil price volatility is a significant issue for oil-exporting countries. the relationship among macroeconomics, stock market, and oil price fluctuations has been investigated widely in the past. researchers such as jones and kaul (1996) and sadorsky (1999) were true investigators of the relationship between oil price fluctuations and stock returns percentage and demonstrated that fluctuations in oil prices were one of the most important determinants of the stock market returns. in general, oil price fluctuations have direct or indirect impact on the stock market performance. the direct impact could be explained by the fact that the upward movement of oil price creates uncertainty in the financial markets, which in turn, leads to a fall in stock prices. the indirect impact could be explained in this way that an increase in oil price fluctuations results in a decrease in production and stock davoudi et al.: the impact of oil revenue shocks on the volatility of iran’s stock market return international journal of energy economics and policy | vol 8 • issue 2 • 2018104 prices and returns causing the inflation to increase. economic theoreticians believe that the price of each asset is determined by its expected cash flows; therefore, any factor that can change the expected cash flows has a significant effect on the asset price, and as a consequence, any increase in oil price fluctuations results in an increase in costs, changes in cash flows and in a larger scale, cause the investors’ capital value to decrease. in conclusion, any increase in oil price fluctuations will be accompanied by a decrease in stock value. 2.2.2. total demand in all the opec member countries, oil revenue forms most of the government budget and a high dependence in the government’s budget on oil revenues can be observed; in this regard, in the absence of designing mechanisms for stabilizing the government budget, the oil shocks of the budget will affect the activity of economic agencies and stock return volatility in the short and long term. the total demand of the iranian oil has undergone lots of ups and downs due to global sanctions on this vital industry which has had impacts on macroeconomic indexes over the past years. oil exporters are not immune from the consequences and impacts of oil crises, just like oil consuming countries. according to economic theories, changes in the price of crude oil affects the economy through the two channels of supply and demand. the effect of the supply side can indicate that oil is the raw material of various productions; therefore, rising oil prices will reduce demand for oil. the demand side influences the economy through consumption and investment as well. consumption is indirectly influenced by changes in oil prices due to its positive relationship with disposable income. with rising oil prices, a transfer of income will be witnessed from importing to exporting countries; therefore, consumption in oilimporting countries will decrease. furthermore, rising oil prices will have an adverse impact on investment by increasing the cost of companies. in addition to the effects the changes in the price of crude oil through supply and demand might have, it also influences the economy through the exchange rate and inflation (shahbazi et al., 2013). 2.3. effective macroeconomic variables on the iranian stock market return 2.3.1. exchange rate there must be accordance in the trade between products and goods in the world with the values that are accepted and approved by all the countries. this value is nothing but the national currency of the country of origin (and the so-called currency of the trading country as its national money). in fact, goods and services are priced and traded in international trade in terms of the mentioned currency. undoubtedly, the price (credit) of the currency and its fluctuations depend on a condition which is not the subject of the current study, but in the business environment of the economic agencies, the process of supply-production and distribution of companies’ products are influenced by exchange rate fluctuations. when the level of risk and uncertainty increases in macro variables such as the exchange rate, the flow of capital and savings will move towards centers of the economy where the impact of the turbulence is less felt (mehrabian and chegni, 2013). the uncertainty of exchange rate fluctuations is considered as a kind of risk (uncertainty) for each agency, which can affect the company’s performance framework (brown, 2001). determining the exact exchange rate in a floating exchange rate system is typically difficult since the balance is determined by the supply and demand of the market; accordingly, any change in the exchange rate will affect buyers’ and sellers’ predictions (hu and motwani, 2014). 2.3.2. consumer price index (cpi) chen et al. in 1986 used eugene fama’s article titled “stock returns, real activity, inflation, and money” for defining and explaining the inflation. in this article, according to the theory and definition of fama, the index of goods price and consumer services were used to measure inflation, which was divided into two predictable and unpredictable components. this index measures the cost of purchasing fixed goods that represents consumer purchasing power. this basket of goods is fixed every year (fisher, 1930); cpi is normally used to know about inflation rate. the cpi is one of the most important tools for economic planners to determine the country’s economic situation at different times and to guide determining monetary and financial policies; it is however considered as one of the main measures of inflation. investors pay more attention to the inflation percentage because the net benefits of their investment depend on the percentage of inflation. in other words, whenever the distance between investment and operating costs increases, the amount that an investor obtains as a gain in investment has less purchasing power and, therefore, the real return on investment will be less than expected (saeedi and kouhsarian, 2009). 2.3.3. the liquidity supply the government sells oil resources exclusively and transfers the currencies from this exchange to the central bank in order to receive national currency in return, some of which will be converted into monetary base. therefore, it seems that the volume of money in the economy is largely affected by oil revenue fluctuations. if the central bank does not succeed in neutralizing (aborting) the mentioned effects, the volume of liquidity can also be affected equally; such a situation would mean that the central bank loses the control of the money supply and fails at making decisions. the obvious difference between the growth rate of liquidity in the first program of economic development and the performance rate of liquidity growth during the years of the mentioned program through 1989-1993 is a clear evidence for the issue (mohammadi and baratzadeh, 2013). 2.3.4. sanctions (eu and us) the sanction hypothesis was first stated by galtung in 1967 to express dissatisfaction and restrain some countries from certain behaviors. in the year 2000, chan and drury expanded this theory and described sanctions as a way of sending messages to other countries in order to have similar behavior with the target country. lindsay (1986) believes that the four possible objectives of economic sanctions davoudi et al.: the impact of oil revenue shocks on the volatility of iran’s stock market return international journal of energy economics and policy | vol 8 • issue 2 • 2018 105 are: compliance, subversion, domestic symbolism, deterrence and international symbolism. the sanctions literature evaluates the effectiveness of unilateral and multilateral sanctions, as well as the cost of sanctions for both sides. hufbauer et al. (1990) and farmer (2000) have conducted some studies in this field; some researchers such as hufbauer generally do not consider sanction policies to be effective after the cold war. others, such as cortright and lopez (2002), believe that sanctions can be an effective tool of foreign policy when a country pursues a specific objective. the strategic position of iran through the course of history has been a source of pressure and sanctions against this country. economic sanctions has affected the economy of iran from several directions, including a decline in oil revenues, the rise in the exchange rate and its volatility, the multi-currency exchange system, a decline in economic security, and formation of barriers to foreign direct investment. 3. literature review in some cases, the existing literature explains and clarifies the negative relationship between oil and stock prices. several theoretical views describe the negative relationship between oil prices and market movements. from the microeconomic point of view, rising oil prices have an adverse effect on the profit of companies which oil is either their direct or indirect cost of production. if companies could not fully transfer this increase in their total cost of production to consumers, the company’s profits and dividends per share as the main stimuli for determining the stock price will decrease (al-fayoumi, 2009). however, by reviewing recent studies, the main issue is many researchers believe that the effect of fluctuations in oil prices has indirect impact on the stock market which occurs by macroeconomic indicators; therefore, it is expected that as in oil-exporting countries the income of the country increases, the increase in oil price fluctuations would have a positive effect (bjorland, 2009). hosseini nasab et al. (2011) in an article titled “the effect of oil price fluctuations on the stock return in tehran stock exchange: wavelet analysis and markov switching model”, examined the effect of oil market shocks on stock return in tehran stock exchange during the period march 1997 to august 2010. according to the results of the article, in the downturn and flourishing phase the stock market returns had severe fluctuations and in the flourishing phase the stock market returns met mild fluctuations; however, the effect of oil price fluctuations on the stock market returns was positive. furthermore, in the downturn phase, the stock returns had mild fluctuations and the effect of oil price fluctuations on stock market returns was negative; this was in a way that, the rise in oil prices has been a factor in continuing the recession in tehran stock exchange. arouri et al. (2012) investigated the fluctuations in oil prices for european countries and the us through the vargeneralized auto regressive conditional heteroscedasticity (garch) approach, and while acknowledging the superiority of this model in examining the transfer of fluctuations comparing to other previous models of econometrics, discovered an indirect fluctuation transfer from global oil markets to european stock markets as well as a direct transfer to the us. abbasi and shafaghat (2012) in their study compared the effect of oil price volatility on the stock market index of iran as an oil exporter country and germany as a european industrial pole, and used the var-garch method to examine the comparisons. according to the results of the current study, the oil price fluctuations have more permanent effects on the market index of iran, and play a more significant role in the trend of the stock market index in the long-term. chortareas and noikokyris (2014), in a study titled “oil shocks, stock market prices, and the u.s. dividend yield decomposition”, investigated the effects of oil supply and demand shocks in the u.s. by using the methodology of campbell and vuolteenaho, known as good and bad beta. the results indicated that there is a positive relationship between the rising of oil price and dividend yield. yahyazadehfar et al. (2012) used a frequency domain model in his dissertation titled “impacts of oil shocks on stock returns: an application of frequency domain method” to investigate the immediate and permanent effects of oil price fluctuations. the results of the research indicated that the midterm impacts of oil shocks on stock returns are positive; oil shocks with short-term impacts do not have a significant effect on stock returns, and the exchange rate had a negative and significant impact on stock returns. bouri (2015), in a study titled “the returns and fluctuations between oil price and lebanon stock market during the crisis” examines the volatility of the returns in the relationship between lebanon’s oil price and stock market using the newly developed var-garch model, with data from january 30, 1998 to may 30, 2014. the results, in contrary to previous studies, indicate that there is a transition and return volatility from oil prices to stock markets of oil-exporting countries. experimental results for the entire period demonstrate that the effects of oil price returns to lebanon’s stock market are unstable, while the mutual relationship between lebanon’s oil prices and its stock market has increased during the crisis, but it has declined significantly in the post-crisis period. several field studies have been conducted with regard to the relationship between macroeconomic variables and oil prices, while many studies have concentrated on stock returns in developed economies through financial theoretical basis due to oil price shocks. a few of the mentioned studies have investigated the relationship between revenue changes from oil sales and stock returns in developing countries; nevertheless, studies focusing on the relationship between stock returns and stock market fluctuations with the volatility of oil revenues in iran, using time series analysis and seasonal data, are few. 4. methodology 4.1. data analysis methodology e-views and microfit software were used for analyzing the data. after collecting the field data, the analysis was carried out davoudi et al.: the impact of oil revenue shocks on the volatility of iran’s stock market return international journal of energy economics and policy | vol 8 • issue 2 • 2018106 through econometric method using time series and co-integration technique with ardl model and pesaran’s bound test based on estimation approach and unrestricted error correction model. the research territory in the present study includes all companies active in tehran stock exchange in the test period. companies active in stock exchange are those effective companies whose prices were calculated in dividend per share index. if during the test years, some companies have withdrawn from the stock board, the indexes calculated by the stock exchange have been adjusted accordingly. data concerning the theoretical foundations review and subject literature have been collected through desk studies and internet searching. the test index for estimating volatility includes the total index of iranian stock exchange during the period of 1993-2013 so that the stock fluctuations returns of all active companies in the iranian stock exchange are considered in the present study. since the impacts of some oil shocks appear in a period shorter than 1 year, the data used in this article is episodic; therefore, if annual data are used, the mentioned impacts will be ignored in the model. data related to exchange rate, cpi, liquidity supply, and iran’s oil revenues have all been extracted by the help of the central bank’s site www.cbi.ir. additionally, in the present study, by relying on the previous studies (kazerouni et al., 2016), impacts of the sanctions on stock returns fluctuations in iran will be analyzed from two aspects of the european and american sanctions during a 20-year period (3/20/1993 to 3/21/2013). the required tests for data analysis are conducted by software; final tables have been added, results of which are presented in chapter 5. 4.2. model estimation according to the studies carried out in the present research, as well as explanations and definitions of variables conducted in the chapter 2, the multivariate regression model was used to investigate the effect of each of the independent variables on the dependent variables (stock return fluctuations). r ln pt pt-1 t =     *100 (1) lvol=f(lo,lp,lex,lm,ext,mod) lvol: stock return volatility logarithm, lo: virtual variable of oil revenues shock, so that if the oil income changes more than 10% comparing to the previous period, it is indicative of oil shock and number one is selected by the virtual variable, otherwise the zero number is considered for the variable. lp: logarithm of cpi. lx: logarithm of the unofficial market exchange rate. lm: liquidity logarithm. ext and mod, european and the us sanctions respectively: the virtual variable has been used to calculate these variables, so that if sanctions were imposed on the side of the eu or the united states, number one, and in other situations number zero have been replaced. t pt r ln *100 pt-1  =    (2) in which rt is the return of the stock price index, pt is the index value in the current period, and pt-1 is its value in the previous period (damodaran, 1996). the first step in estimating the stock returns volatility index is examining the durability of this variable, using the generalized right tail augmented dickey-fuller (rtadf) test. the results of the study on stock returns durability are presented in table 2: the study results of the static stock return variable using adf test statistic indicate that this variable is static and therefore the collective rank of this variable is zero. in order to estimate the stock returns volatility, first the best arima pattern (p, d, q) has to be selected. in order to get to this objective, regarding the results of the correlation graph analysis, it is indicated that p = 3 and q = 3. in addition, concerning the fact that the stock return variable is in the durable level, so d = 0. using the resulting p as the stock return interruption and q as the lag of the interruption sentences, the arima model is estimated. the coefficients which are statistically less significant than other variables are deleted based on the box and jenkins methodology, and the model is re-estimated; this process is repeated so that all the model variables are statistically significant (box and pierce, 1970). as the results of table 3 demonstrate, all variables are statistically significant. in order to use arch models, the variance through the random sequence should not be constant and has to be a function of the behavior of error sentences. arch family models can explain the conditional variance trend according to their previous information, but it should be noted that volatility can only be estimated through garch methods when the existence of conditional heteroskedasticity is confirmed by the arch test; therefore, in this section, the conditional heteroscedasticity test of interruption sentences is examined using the lm-arch test. the results of table 4 demonstrate that the zero hypothesis of the lm test, which indicates the absence of heteroskedasticity variance, cannot be repudiated; therefore, the interruption sentences of the estimation model do not have the problem of heteroscedasticity variance. as a conclusion, using this model and the eviews software, the stock returns volatility can be extracted, table 1: the value of iran’s oil exports during the 4-year period (2011-2014) $ billions opec members 2011 2012 2013 2014 algeria 77.668 77.12 69.659 040.60 angola 67.31 93.71 69.562 63.908 ecuador 22.322 23.765 24.848 266.01 iran 144.874 107.409 91.793 98.981 iraq 83.226 94.39 89.742 85.298 kuwait 102.052 118.917 115.084 104.165 libya 19.060 61.26 46.018 15.186 nigeria 93.676 95.360 95.118 83.897 qatar 112.912 132.985 136.767 131.716 saudi arabia 364.699 388.401 375.873 372.829 emirates 302.036 349.481 378.660 380.347 venezuela 92.811 97.34 88.962 80.663 source: opec database. opec: organization of petroleum exporting countries davoudi et al.: the impact of oil revenue shocks on the volatility of iran’s stock market return international journal of energy economics and policy | vol 8 • issue 2 • 2018 107 which can be used as stock returns fluctuations in investigations. chart 2 displays the stock market return volatility during the studied period. in order to select the optimal p and q in the garch (p, q) process, there are different criteria used; schwarz criteria (sc) criteria has been applied in the present study: ivanov and kilian (2005) have demonstrated that the most appropriate criterion for selecting optimal lag for models with a sample size less than 120 is the schwartz criterion. at this stage, regarding the minimum value of the schwarz criterion, the optimal lag of garch (p,q) is selected. according to the results of table 5, by considering the garch (1,1) as the criterion for the estimation of stock returns volatility, the time series of stock returns volatility is estimated. considering the difference in the total variables degrees, ardl is used to examine dynamic, longterm, and error correction relationships. the ardl dynamic model is estimated (table 6) with lags determined by schwartz-bayesian using the system. the results of the selection of the ardl model are displayed in table 7. in order to ensure that the estimation regressions are not inaccurate, dickey-fuller test is required to table 2: generalized dickey-fuller test results for stock return variables variable y-intercept y-intercept and trend result statistical test critical quantity on level 5% probability statistical test critical quantity on level 5% probability r −6.37 −2.89 0.00 −6.38 −3.46 0.000 durable source: research findings table 3: estimation of stock return volatility after applying the jenkins box method variable coefficient standard deviation t-statistics p value c 4.66 0.01 276.93 0.000 ar (1) 0.24 0.10 2.42 0.01 source: research findings table 4: the results of the heteroscedasticity variance test statistical test statistical quantity probability value f statistic 0.132 0.716 2 0.135 0.712 source: research findings chart 1: percentage share of iranian oil exports among opec countries (2014) source: organization of petroleum exporting countries database be carried out confirming the variance of the variables (tables 8 and 9). 4.3. long-term pattern estimation after ensuring the existence of classical assumptions, a long-term relationship, and coefficient stability test, the long-term results are presented. the results of the long-term estimation of the ardl method have been presented in table 10 with a maximum of three lags and based on the schwartz-bayesian criterion. as it is demonstrated in table 10, all variables are significant at 95% confidence level except for the price index variable. the liquidity variable has a positive and significant relationship with the stock return volatility; that is, if liquidity increases by one percent, stock returns volatility increases by 0.99%. the exchange rate variable also has a positive and significant relationship with stock return volatility; that is, if the exchange rate increases by one percent, the stock returns volatility increases by 0.71%. the shock variable of oil revenues causes stock return volatility to increase as well; meaning that an oil revenue shock results in a 0.17 % increase in stock market volatility. european and american sanctions variables also have positive and significant effects on stock return volatility in the studied period and lead to a 0.45% and 0.38% increase in stock return volatility respectively. 5. conclusion in present study, it is attempted to measure the effectiveness of the index of companies active in the stock market of the uncertainty caused by the volatility of iranian crude oil revenues. we concluded that by estimating econometric models and especially impulse response functions, the uncertainty caused by oil revenue shocks on the returns of the total stock market index has a direct and positive effect, and if in some cases the mentioned effect is negative its effect is imperceptible. in agreement with the results of the research, the effect of exchange rate changes was observed to be significant as well. the cpi and its effects on the stock returns fluctuations were discovered to be insignificant. in addition, more variables were added to improve the model. the liquidity supply and economic sanctions were also examined along with the previous variables in order to determine their clarification effect in the studied model. as a conclusion, these three variables caused stock return volatility to increase by 0.55%, 0.45% (europe), and table 5: selecting optimal p and q in the garch process (p, q) p&q (1&0) (0&1) (1&1) (1&2) (2&1) (2&2) schwarz criteria −1.23 −1.25 −1.35 −1.33 −1.29 −1.21 source: research findings davoudi et al.: the impact of oil revenue shocks on the volatility of iran’s stock market return international journal of energy economics and policy | vol 8 • issue 2 • 2018108 source: research findings chart 2: displays the stock market return volatility during the studied period. table 6: dynamic relation davoudi et al.: the impact of oil revenue shocks on the volatility of iran’s stock market return international journal of energy economics and policy | vol 8 • issue 2 • 2018 109 0.38% (us) respectively. in the end, considering the identification of effective variables on stock returns, suggestions are being made to improve the current situation of the economy, capital markets, and economic agencies. references abbasi, q., shafaghat, m. (2012), a comparative study of the impacts of oil price fluctuations on stock market index in oil-exporting and oil-importing countries (study on iran and germany). national conference of accounting, management, and investment. golestan, gorgan, iran: university of applied science and technology. al-fayoumi, n.a. (2009), oil prices and stock market returns in oil importing countries: the case of turkey, tunisia and jordan. european journal of economics, finance and administrative sciences, 16(2), 86-101. arouri, m.e.h., jouini, j., nguyen, d.k. (2012), on the impacts of oil price fluctuations on european equity markets: volatility spillover and hedging effectiveness. energy economics, 2(34), 611-617. behboudi, d., motafaker azad, m., rezazadeh, a. (2009), investigating the effects of oil price volatility on gross domestic product in iran. energy economics review quarterly, 6(20), 1-33. bjorland, c.h. (2009), oil price shocks and stock market booms in an oil exporting country. scottish journal of political economy, 2, 232-254. bodie, z., kane, a., marcus, a.j. (2011), investment and portfolio management. boston: mcgraw-hill/irwin, p289-292. bouri, e. (2015), return and volatility linkages between oil prices and the lebanese stock market in crisis periods. energy,89, 365-371. box, g.e., pierce, d.a. (1970), distribution of residual autocorrelations in autoregressive-integrated moving average time series models. journal of the american statistical association, 65(332), 1509-1526. brown, g.w. (2001),managing foreign exchange risk with derivatives. journal of financial economics, 60(2), 401-448. table 8: dickey-fuller test results, generalized for variables level variable y-intercept y-intercept and trend result statistical test critical quantity on level 5% probability statistical test critical quantity on level 5% probability lvol −5.45 −2.89 0.000 −5.90 −3.46 0.000 durable lex −0.58 −2.89 0.867 −2.34 −3.46 0.403 non-durable lm −0.57 −2.89 0.869 −2.05 −3.47 0.561 non-durable lp −0.70 −2.89 0.839 −2.58 −3.47 0.287 non-durable source: study results table 9: dickey‑fuller test results generalized for first order difference of variables variable y-intercept y-intercept and trend result statistical test critical quantity on level 5% probability statistical test critical quantity on level 5% probability dlex −8.17 −2.89 0.000 −8.12 3.46− 0.000 durable dlm −3.39 −2.90 0.014 −3.40 −3.47 0.058 durable dlp −5.34 −2.89 0.000 −5.32 −3.46 0.000 durable source: study results table 7: dynamic model results (lvol dependent variable) variable coefficient t-statistic results lvol(−1) 0.634 8.62 significant lm 0.016 2.92 significant lex 0.011 2.38 significant lp −0.132 −1.78 insignificant lp (−1) 0.282 2.82 significant lp (−1) −0.157 −2.90 significant lo 0.0028 2.43 significant ext −.0074 0.91 insignificant mod −0.0064 −1.53 insignificant c −.0280 −1.49 insignificant f=28.14 r2=0.78 source: research findings table 10: results of long-term relationship (dependent variable lvol) variable coefficient t-statistics results lm 0.99 2.14 significant lex 0.71 2.40 significant lp −0.157 −0.080 insignificant lo 0.17 2.23 significant ext 0.45 2.44 significant mod 0.38 2.78 significant c −1.946 −2.31 significant source: research findings davoudi et al.: the impact of oil revenue shocks on the volatility of iran’s stock market return international journal of energy economics and policy | vol 8 • issue 2 • 2018110 chan, s., drury, a., editors. (2000), sanctions as economic statecraft: theory and practice. england: springer. chen, n.f. (1983), some empirical tests of the theory of arbitrage pricing. journal of finance, 38, 1393-1414. chen, n.f., roll, r., ross, s.a. (1986), economic forces and the stock market. journal of business, 21(9), p383-403. chortareas, g., noikokyris, e. (2014), oil shocks, stock market prices, and the us dividend yield decomposition. international review of economics and finance, 29, 639-649. cortright, d., lopez, g.a. (2002), introduction: assessing smart sanctions: lessons from the 1990s. smart sanctions: targeting economic statecraft. lan-ham, md: rowman and littlefield. p1-22. damodaran, a. (1996), corporate finance. new york: wiley. farmer, r.d. (2000), costs of economic sanctions to the sender. the world economy, 1(23), 93-117. fisher, i. (1930), the theory of interest. vol. 43. new york: macmillan freeman. galtung, j. (1967), on the effects of international economic sanctions: with examples from the case of rhodesia. world politics, 3(19), 378-416. gha’emi, m., tousi, s. (2005), investigating factors affecting stock returns of companies accepted in tehran stock exchange. vol. 17, 18.  iran: management message press, p159-175. hosseini nasab, s., khezri, m., rasouli, a. (2011), determining the impacts of oil price fluctuations on stock returns in tehran stock exchange: wavelet analysis and markov switching. energy economics review quarterly, 8(29), 31-60. hu, x., motwani, j.g. (2014), minimizing downside risks for global sourcing under price-sensitive stochastic demand, exchange rate uncertainties, and supplier capacity constraints. international journal of production economics, 147, 398-409. hufbauer, g.c., schott, j.j., elliott, k.a. (1990), economic sanctions reconsidered: history and current policy. vol. 1. usa: peterson institute. ivanov, v., kilian, l. (2005), a practitioner’s guide to lag order selection for var impulse response analysis. studies in nonlinear dynamics and econometrics, 9(1), 1219-1253. jones, c. m., kaul, g. (1996), oil and the stock markets. the journal of finance, 51(2), 463-491. kazerouni, a., asgharpour, h., khezri, a. (2016), “investigating the effects of economic sanctions on business between iran and major foreign trade partners during the period of 1992-2013”. quarterly journal of business researches, 20(79), 1-34. lindsay, j.m. (1986), trade sanctions as policy instruments: a reexamination. international studies quarterly, 2(30), 153-173. mehrabian, a., changi, i. (2013), the effect of exchange rate fluctuations on iranian stock price index. quarterly of applied economics, 4, 65-78. mohammadi, h., baratzadeh, a. (2013), the impacts of shocks from oil revenue decrease on the government spending and liquidity in iran. energy economics review quarterly, 2(7), 129-145. morad pour oladi, m., ibrahimi, m., abbasioun, v. (1999), a study on the uncertainty of actual exchange price on private sector investment. quarterly of iranian economic research, 10(159), 35-176. sadorsky, p. (1999), oil price shocks and stock market activity. energy economics, 21(5), 449-469. saeedi, p., kouhsarian, a. (2009), investigating the relationship of inflation indexes (cpi & ppi) and stock returns in tehran stock exchange. journal of economic research, 89, 109-128. sameti, m., khanzadi, a., yazdani, m. (2009), the effects of oil revenues and its injection into the economy on income distribution: a case study of iran. quarterly journal of quantitative economics, former economic studies, 6(4), 51-72. shahbazi, k., rezaee, e., salehi, y. (2013), the impacts of oil price shocks on stock returns in tehran stock exchange: svar approach. scientific research quarterly of financial knowledge of securities analysis, 6(18). . international journal of energy economics and policy | vol 8 • issue 6 • 2018284 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(6), 284-291. household cooking energy situation in nigeria: insight from nigeria malaria indicator survey 2015 ebenezer megbowon1*, peter mukarumbwa1, sola ojo2, olawuyi seyi olalekan1 1department of agricultural economics and extension, faculty of science and agriculture, university of fort hare, south africa, 2department of business administration and management, the federal polytechnic, ado-ekiti, nigeria. *email: megbowontoyin@gmail.com received: 11 august 2018 accepted: 19 october 2018 doi: https://doi.org/10.32479/ijeep.6913 abstract the lingering electricity energy crisis in nigeria which is beyond the control of most households necessitates making decision and choice on alternative energy pathways for households’ sustenance and welfare. this study assessed households’ energy situation with respect to choice of cooking fuel and cooking energy poverty status in nigeria. further investigation was sought to isolate the main factors influencing households’ choice of individual fuels as main cooking fuels using data from nigeria’s malaria indicator survey of 2015 with the application of descriptive and multivariate probit analyses. findings revealed that wood and kerosene fuels remain the major fuels utilized by most households in nigeria for cooking purposes. meanwhile, level of education, household size, wealth status and regional factors are significant predictors driving choices of fuels among households, though the impact of these factors differs across the highlighted choices. based on these findings, mass enlightenment campaign on the safe use of clean energy is recommended while the need for economic diversification by rural households to aid their wealth status is also emphasized. also, there is need to gear up corporate social responsibilities by the available private establishments in ensuring rural accessibility, availability and affordability of modern and cleaner fuel (such as lpg). keywords: cooking energy choice, multivariate probit model, nigeria jel classifications: d10, i30, q40 1. introduction the energy sector is widely acknowledged to be indispensable for the smooth sailing of any economy; it is a vital element in human life and a pivotal input for social and economic development (brew-hammond, 2010). this suggests that a sustainable, secure, sufficient, affordable and accessible supply of fuel as well as affordable use of energy is very crucial for the growth and sustainability of modern societies. hence, it is central to addressing many of today’s development challenges which are centered on human health, inequality, unemployment, education, climate change, food security and general household welfare (bazilian et al., 2012; varun and bhat, 2009). the motivation for and satisfaction derived from energy demand is not the same for economic agents (household and productive users) (bhattacharyya and timilsina, 2009), while households use energy for cooking, heating, lighting and, cooling systems to obtain the greatest degree of satisfaction, businesses on the other hand demand and use it as part of production input which account for business economic profitability or loss. hence, this account for differentials in its demand, availability, affordability and use. despite these differences energy use type and pattern have development implications. energy use at the household level remains a serious challenge which many developing countries have continued to grapple with (hou et al., 2017), this is so because it has continued to reflect poor access to clean energy, hence energy poverty. it often this journal is licensed under a creative commons attribution 4.0 international license megbowon, et al.: household cooking energy situation in nigeria: insight from nmis 2015 international journal of energy economics and policy | vol 8 • issue 6 • 2018 285 highlight heavy reliance on alternative energy options-solid fuels (mainly biomass and coal) which are not environmentally sustainable and energy efficient and when used does have harmful effect on the health and productivity of those in the household (iea, 2017). its’ health hazards affect the vulnerable (females and children) the most because of many hours spent while cooking near exposed fire-flames (hou et al., 2017). an annual premature death of 2.8 million people was recently reported due to smoky environments caused by burning solid biomass in inefficient stoves and or from combustion of kerosene or coal for cooking (iea, 2017). furthermore, overreliance on traditional energy sources like wood and agricultural residues has been identified as a leading cause of deforestation (bisu et al., 2016). access to clean reliable and modern energy sources is a daunting task confronting the african continent at large (baiyegunhi and hassan, 2014). in nigeria, the situation is paradoxical in nature, in that despite enormous natural resources that could be utilized for energy generation purposes, the ranking of the country as the 6th largest oil exporting nation and an estimated 187 trillion standard cubic meters of liquid natural gas reserve, which is the largest reserve in africa and 9th largest reserve in the world according to (iea, 2014), yet the country is still faced with energy crises that have been existing for more than a decade, remain unabated and with no of the crises in sight. these crises include shortage of supply where the demand for electricity far exceeds currently installed and generation capacities, frequent power outage, inadequate and delayed maintenance of facilities and occasional collapse of national grid among others. these energy crises without doubt have links with population expansion, security issues, poor investment, corruption, and inconsistent and lack of continuity in energy sector initiatives by various governments. these crises have implications for household welfare, industrialization, employment generation and economic growth and development in general. for instance, world bank (2018) reported a national electricity access of 59.3% and low per capita consumption for nigeria of 144.5 kwh per capita in 2016 and 2014 respectively. aside, household sector which is the largest consumer of electricity energy in nigeria, and also play a dominant role in energy-related sustainability and conservative issues have to result in the reliance and usage of various alternative options that are readily available to meet their various electricity energy demand especially cooking which account for about 80% of the total domestic energy consumption (oyedepo, 2012; gujba et al., 2015). providing solution to electricity issues in the country is out of the scope of this study, rather the study focused on households alternative energy use in the face of persistent energy challenges. paucity of studies that offer comprehensive nationwide analysis on the dynamics of household cooking energy situation in the country in nigeria using most current information where possible, which could reflect the effect of time and relevant government policies and also needed for energy planning in the country motivated this study. hence, in light of the above facts, the aim of this paper is to answer the following research question; 1. what is the pattern and trends of households cooking energy situation and is any improvement observed? 2. which current socioeconomic statuses explains the use of specific cooking energy options by households. it is envisioned that this study will assist in the formulation of effective energy policies that could have positive impact on household behavior with respect to cooking energy in nigeria. the rest of the paper is organized as follows; section 2 contains literature review while section 3 focuses on the research methodology and data. section 4 presents the results and discussion while section 5 is the conclusion. 2. literature review energy is consumed at the household level for purposes of cooking, heating, lighting and powering machines where necessary (ogwumike and ozughalu, 2012). energy type consumed by households for cooking, heating and lighting can broadly be categorised into traditional, transitional or modern energy sources. hence, conceptually, it is the type of energy consumed that determines whether a household is energy poor or not, although there are no universally accepted definition of energy poverty. household energy poverty is therefore conceptualized as a situation where there is inadequate access to sustainable, cleaner and modern energy sources (iea, 2017; sesan, 2012; bouzarovski, et al., 2016). these cleaner energy sources are fuels which are more environmentally sustainable, energy efficient and when used does not have any harm on the health of those in the households (iea, 2017), and they include improved biomass, gas, biogas, solar cooker and electricity (iea, 2017; ekouevi and tuntivate, 2012). contrariwise, households who can only access or use traditional energy sources and non-clean fuel are regarded as being energy poor. this entails the use of energy sources which are of very low technological-based such as firewood (traditional biomass), charcoal, kerosene, plant residue and animal waste (iea, 2017; ekouevi and tuntivate, 2012). in addition, household is considered energy poor when it has to spend more than 10% of its disposable income to meet it energy need (teller-elsberg et al., 2016; ismail and khembo, 2015). various theories have been postulated in order to explain household energy choices in energy poverty studies. the theory of ‘energy ladder model’ has been extensively used in such studies. the theory states that households gradually climb an energy ladder in three phases. they begin with traditional energy sources and transitioning to commercial fuels and eventually to the use of advanced fuels such as electricity (bisu et al., 2016). the transition through these three stages is guided by household income and fuel prices. the model assumes a linear progression pattern of households as they move along the imaginary energy ladder, switching completely from traditional fuels as their income increase. however, the energy transition theory has been criticized by various recent studies that have found out that as household income increases, traditional fuels are not discarded completely rather they are used conjointly with other energy sources and that income alone does not influence household fuel use, thus negating the energy ladder model. the weakness of the “energy ladder” model led to proposition of alternative models like the fuel stacking model (masera et al., 2000). the “fuel stacking” model assumes that the transition of households to clean energy is not megbowon, et al.: household cooking energy situation in nigeria: insight from nmis 2015 international journal of energy economics and policy | vol 8 • issue 6 • 2018286 linear, rather households just increase number of energy sources used without necessarily forgoing completely the old ones (bisu et al., 2016). here, energy use patterns of households is guided by many factors which include cultural, social, economic and even personal preferences and not only income (bisu et al., 2016). other theories used in literature include the poverty-environment and the theory of utility maximization in consumer behaviour (joshi and bohara, 2017; ogwumike and ozughalu, 2016). empirically, this study acknowledge the existence of several studies (including ogwumike et al., 2014; oyekale, 2012; mensah and adu, 2015, karimu, 2015; rahut et al., 2016; rahut et al., 2017; nlom and karimov, 2015; makonese et al., 2018) that have examined the factors influencing household cooking fuel choice at both local and national perspectives. these studies applied different analytical techniques with majority applying chi-square analyses, multiple regression, multivariate probit regression, seemingly unrelated bivariate probit regression, multinomial probit, ordered probit model and multinomial logit in this regard. evidences from these literatures shown that specific choice of household main cooking fuel is influenced by both households’ economic and non-economic factors. the economic factors include income and expenditure of household, and prices of fuel. while on the other hand, non-economic factors include socio-economic characteristics such age, gender, household size, education, distance to fuel source, type of dwelling, location and distance to fuel source. however, the dimension and extent of influence of these factors on household’s choice of fuel type vary across type of fuel source. this study further observed while majority of studies carried out in nigeria were found to have been carried out in a few local government areas, not even regional let alone the whole country as a whole, the four studies (oyekale, 2012; ogwumike and ozughalu, 2012; ogwumike et al., 2014, and ogwumike and ozughalu, 2016) that looked at it from a nationwide perspective utilized data for 2008, 2004 and 2004 respectively. one most recent study by ifegasan et al., (2016) where 2013 nationwide survey data was used has a flawed methodological approach. the multiple regression approach used by ifegbasan et al., (2016) in addressing their study&#39;s research question on whether socio-economic characteristics predict household choice on the type of fuel being used for cooking is inconsistent and inappropriate because there is no clear conceptualization of the response variable. besides in similar studies like this response variables are categorical, this violates the criteria of multiple regression/ols that response variable should be continuous. type of cooking fuel in ifegbasan et al., (2016) are not in continuous form, hence the application of multiple regression and subsequent inferences are flawed. yet, comprehensive current and nationally representative information where possible in this regard that could reflect the effect of time and relevant government policies is however needed in understanding the dynamics of household cooking energy situation in the country for better energy and environmental planning. 3. materials and methods 3.1. study area, data source and sampling nigeria is a west african country located approximately between latitudes 40 and 140 north and longitude 30 and 150 east (ifegbesan et al., 2016). nigeria is bordered by benin to the west, cameroon to the east, niger republic on the northern side and the atlantic ocean on the southern side. the country consists of 36 states as well as a federal capital territory (fct) which are divided into six geopolitical zones south-south, south-west, north central, north east, north west and south east. the country’s population is estimated to be 191 million (un, 2017). the study used the nigeria malaria indicator survey (nmis) data that were collected from october 2015 through november 2015. the nmis was implemented by national malaria elimination programme (nmep), the national population commission (npopc), and the national bureau of statistics. the population and housing census of the federal republic of nigeria (nphc) conducted in 2006 by the npopc was used as the sample frame for the 2015 nmis. samples were selected using stratified two-stage cluster design consisting of 329 clusters. a two-stage sampling strategy was adopted for the 2015 nmis. in the first stage, nine clusters (eas) were selected from each state, including the fct. in the second stage, 25 households were selected in each cluster by equal probability systematic sampling. details of the sampling procedure can be found in (nmep et al., 2016). the sample selection was done in such a way that it was representative of each state. 7,745 household were successfully interviewed, yielding a response rate of 99% (nmep et al., 2016). this study utilized information on demographic and socioeconomic characteristics of households and type of cooking energy. 3.2. analytical techniques 3.3.1. descriptive analysis descriptive analysis was used to describe the pattern and trend of household usage of cooking fuel sources and consequently cooking energy poverty. basically, frequencies, percentages, tables and charts were used. 3.3.2. multivariate probit regression the factors influencing choice of main cooking fuel are not uniform among different households. to this effect, a multivariate probit model was employed to analyse the determinants of household’s cooking energy choices. the study focused on four main specific cooking fuels (lpg, kerosene, charcoal, and wood fuels) which together accounts for about 94.9% of total cooking fuel used in the study area. the rational for analysing the individual fuel energy option was to avoid the aggregation problem. one advantage of the multivariate probit model is that, unlike single-equation probit and logit, and multinomial logit models, it simultaneously analyses the choice of energy types thus allowing for non-zero covariance across cooking energy types. estimating the models independently may generate biased and inconsistent coefficients, though, as the error terms are likely to be correlated across activities. as dependent variables, we use dummies for usage of a specific type of cooking fuel, specifically kerosene, wood, natural gas, and charcoal. households that use a type of fuel for as main fuel for cooking are scored 1 and those that do not use such as main fuel are scored 0. following (rahut et al., 2017), the multivariate model for determining factors that influence household cooking energy choice is stated as follows; megbowon, et al.: household cooking energy situation in nigeria: insight from nmis 2015 international journal of energy economics and policy | vol 8 • issue 6 • 2018 287 y x eim m im im * *= + (1) y 1 if yim = >im and if otherwise * 0 0 where y represents the dependent variable which is the four main cooking fuels (m = 1, 2, 3, 4) used by the ith household (i = 1,…., 7745). x is the vector of explanatory variables that influences choice of cooking fuel by ith household, α is the vector of unknown parameters, and e is the vector of unobserved error term. the explanatory variables are described in table 1. the variables were recoded where necessary in order to carry out this analysis. 4. results and discussion 4.1. socio-economic characteristics of respondents table 2 presents the socio-economic characteristics distribution of the households. the result shows that 84.53% of the household heads are males, educational distribution of household head reveal that while a higher proportion (34.15%) of the respondents have no education, 19.7 and 29% attained primary and secondary education respectively. geopolitical distribution of respondents shows that there is almost an equal representation of respondent in the survey. majority (59.12%) of the respondents live in the rural settlements, while 40.88% live in the urban settlement. in terms of wealth status, 31.1% of the aggregated respondents are considered to be in poor category while 21.6% are in the moderately poor category and 47.3% are found to be in the non-poor category. 4.2. pattern and trends of households cooking energy situation most national censuses on household surveys have only recently integrated questions relating to household energy usage. it is therefore difficult to draw solid conclusions on a time series trend of household energy use over a longer period of years. however, in an attempt to only spot-light the trend of use of cooking fuel types, this study utilized available information from demographic and health surveys carried out in nigeria between 2003 and 2015. a comparative distribution of household choice of fuel for cooking in this regard is presented in figure i. from the figure i, it can be deduced that there has not been significant positive development in the use of improved energy sources (for instance, electricity and lpg) for cooking. wood and kerosene also are clearly revealed as the main choice of fuel energy for cooking by most households in nigeria over the years represented. although, there are slight changes in the proportion of household using these two sources of energy sources as major fuel for cooking, the continual dominant nature and use of wood fuel for cooking is worrisome. this questions the effort, determination and investment by the nigerian government in improving the standard of living of the people through poverty reduction (energy poverty inclusive) and providing a sustainable environment. in the same vein, it can further be deduced that the non-usage of lpg as seen in figure 1 could be as a result of fear of possible inferno, poor knowledge of reduced pollution advantage, a high table 1: specification of multivariate probit regression explanatory variables variables description type of data gender 1 if male, 0 if otherwise dummy age age of household head continuous household size number of people in the household nominal education 1 if higher degree, 0 otherwise dummy number of children number of children<5 years in the household nominal location 1 if rural, 0 otherwise dummy region 1 if northern, 0 otherwise dummy electricity access 1 if having access, 0 otherwise dummy wealth status 1=poorest; 2=poorer; 3=middle, 4=richer; 5=richest categorical table 2: demographic and socioeconomic characteristics of respondents gender of head frequency (%) male 6547 (84.53) female 1198 (15.47) age of household head (years) ≤30 1659 (21.42) 31–50 3499 (45.18) 51–70 1963 (25.35) ≥71 624 (8.06) educational attainment of head no education 2645 (34.15) primary 1528 (19.73) secondary 2253 (29.09) higher 1286 (16.6) household size 1–5 4950 (63.91) 6–10 2363 (30.51) above 10 432 (5.58) access to electricity yes 4247 (54.84) no 3498 (45.16) wealth index poorest 1058 (13.66) poorer 1351 (17.44) middle 1676 (21.64) richer 1844 (23.81) richest 1816 (23.45) location urban 3166 (40.88) rural 4579 (59.12) geopolitical region north central 1385 (17.88) north east 1200 (15.49) north west 1547 (19.97) south east 1002 (12.94) south south 1281 (16.54) south west 1330 (17.17) source: computed by authors megbowon, et al.: household cooking energy situation in nigeria: insight from nmis 2015 international journal of energy economics and policy | vol 8 • issue 6 • 2018288 initial cost associated with acquisition of lpg gas ancillaries (i.e., cooker, gas cylinder, re-filling of the gas cylinder as needs demand) which is considered high considering the minimum wage in the country and the traditional perception of high cost and that usage of lpg gas is meant for the rich in the society. this can be further deduced from current price of lpg which is estimated to be about 23.7% of current minimum wage in nigeria. figure ii presents a comparative distribution of cooking energy poverty status by geographical locations (i.e., urban and rural) with respect to geopolitical zones of households. it is clearly shown that among urban households, cooking energy poverty is prevalent in the south west and south east geographical regions of the country accounting 66.33% and 55.47% respectively. this is so because rural-urban migration is higher in these regions. thus several households end up not having access to cleaner cooking fuels. contrarily, the south east and the northern regions have higher proportion of households in the rural area that are cooking energy poor as shown in the figure ii. it is however puzzlingly to note that the northern region collectively is the most wood deficient in the country; where deforestation and desertification is prevalent and which threaten the living conditions of the inhabitants in these areas, yet as noted by sa’ad and bugaje, (2016) the region have the highest prevalence of traditional biomass usage than any other region in the country. 4.3. determinants of cooking fuel type multivariate probit regression result the result of the multivariate probit regression model on factors influencing choice or usage of specific cooking fuel by respondents in the study area is presented in table 3. the variables used in this result were subjected to test of multicollinearity in order to avoid a spurious and misleading results. the multicollinearity test examined the appropriateness and reliability of the choice of variables included in the multivariate probit model through the variance inflation factor (vif) statistics and tolerance level. from the multicollinearity test conducted none of the variables have a vif >10. also, the average vif of 1.69 for the model depicts an overall tolerance of about 59.2%, which is a favourable indication that multicollinearity is not a serious problem in the fitted model. the findings from the fitted model revealed that the coefficient of gender of household head (base reference-male) is negative and significant with respect to the usage of charcoal and firewood as main cooking fuels. this indicates that having a man as the head of the households reduces the probability of a household using charcoal or firewood as cooking fuel energy options. alternatively, the result does imply that usage of the two significant solid fuels (charcoal and firewood) increases with having female as the head. this is not unexpected in developing africa countries context where female are decision makers with respect to cooking which is a part of house chores, and are often saddled with the duty to collect firewood from the forest for their cooking activities. additionally, the low economic status of female headed households compare to male headed ones make such households to be utilizing less expensive fuel (charcoal) for cooking, even if such fuel is dangerous to human health. this further point out to the vulnerability to poverty and lower standard of living nature of women and consequently such households they head. generally, female heads and consequently their households are economically vulnerable because of poor access to employment opportunities and resources. this finding agrees with other studies such as (ogwumike et al., 2014; rahut et al., 2017). also, the coefficient of age of household head is negative and significant with respect to the use of kerosene, but positive and significant for firewood. this result implies that probability of using kerosene as cooking fuel decreases as the age of household head increases when other variables are held constant while it increases for firewood. this result is similar to the findings of (baiyegunhi and hassan, 2014) who all reported a shifting to firewood consumption or preference for firewood as the age of the household head increases. this arises due to reduction in income of the head when he or she is no longer economically active coupled with the fact that such household head might not have any other source of income, either through remittances, pension or other income sources. the reality of low or no and unstable income (for pensioners) which is prevalent in nigeria is seen to have lowered the standard of living of households with older heads. other reason for high preference for firewood by households with older heads is due to the old habit or conservatism associated with older people. in this case, old folks may have become accustomed to the use of traditional fuel energy source(s) and thus are less willing to change towards modern reality of energy usage (mensah and adu, 2015). likewise, from table 3, while a negative and significant relationship between household size and use of lpg and kerosene as main cooking fuels was observed, the relationship was positive for usage of wood as main cooking energy. the result suggests a reduction in the probability of a household using lpg and kerosene for cooking as household size increases. this is majorly due to figure 1: trends in type of main cooking fuel use source: generated by authors. nb: lpg and natural gas were categorized together in 2003, same as firewood and straw figure 2: cooking energy poverty by geopolitical zone and location source: generated by authors from nigeria malaria indicator survey, 2015 megbowon, et al.: household cooking energy situation in nigeria: insight from nmis 2015 international journal of energy economics and policy | vol 8 • issue 6 • 2018 289 the amount of energy required for cooking for large number of persons and the consequent cost implication associated with it, which is higher for larger households. it is expected that larger household will prefer to use firewood because it requires a large amount of fuel energy in aggregate to meet the family needs. in line with the submission of (pundo and fraser, 2006), it is comparatively affordable to use firewood for large family than kerosene and charcoal because its rate of consumption per unit of time is low. again, the cheapness of firewood would require that households with large family size use huge amount of it for their cooking activities. suffix to say that, this positive and significant estimated coefficient for family size was not unexpected and it is in line with (karimu, 2015). the findings from table 3 also shows a negative and significant relationship between education and kerosene, charcoal and wood fuels but a positive and significant relationship with lpg. this indicates that, increase in education attainment increases the chances of a household using lpg as main cooking fuel while on the other hand, it reduces the likelihood of using kerosene, charcoal and wood as main coking fuels as expected, ceteris paribus. a positive and higher return to education can be deduced in this regard; that is, positive returns on employment opportunities, income and standard of living generally resulting to economic affordability of better and clean fuel energy options for cooking and other domestic uses. this is supported by the studies from (bisu et al., 2016; mensah and adu, 2015). likewise, the coefficient of under 5 years in table 3 is positive and significant for kerosene fuel preference but negative for firewood usage. this thus implies that households with more children under the age of 5 years are more likely to use kerosene fuel energy and less likely to use solid wood fuel as main cooking energy. this is because of the inability of the mothers in rural area to collect firewood at this nursing stage. this inability arose from more time used to attend to other pressing house chores especially as it pertains to taking care of the little children most often in cases where there are no older children in the house to assist. hence, it becomes imperative and a justification for the use of kerosene as an alternative fuel energy which is more easily accessible. furthermore, the result in table 3 shows that there is a significant and negative relationship between rural dwelling and usage of kerosene and charcoal as main cooking fuel choices; this does imply that, living in rural areas reduces households’ chances of using kerosene or charcoal for cooking. the result is however positive for the use of firewood which by extension suggests that rurality significantly increases the probability of the using of wood for cooking. this is mainly due to easy accessibility of firewood in the rural areas unlike urban areas where development in all forms has led to major deforestation; thus, various forms of improved cooking fuel energy are available to choose from, thus, the significant use of firewood is not unexpected. this finding is similar to the submission of (ogwumike et al., 2014) where urban sector (location variable) was found to be negatively related to household firewood consumption. likewise, there is a negative relationship between rural dwelling and usage of kerosene as main cooking fuel which also suggests that living in rural areas reduces household chances of using kerosene for cooking. this is largely a result of little supply of kerosene fuel energy, distance, low economic benefit of supply of kerosene to rural areas and mostly, the easy accessibility and availability of alternative fuel energy options in the rural areas. it is also seen from the table 3 that the geopolitical variable (northern region) is positive and significantly related to usage of charcoal and firewood as main cooking fuel but negatively related to use of kerosene for cooking. this is expected considering the high poverty rate in the northern part of nigeria. oyekale (2012) buttressed on this that, when the households are struggling to meet basic needs for food, demand for improved energy sources for cooking will never be an importance. this positive relationship with use of solid fuels as noted by (sa’ad and bugaje, 2016) could also be as a result of the belief by northern households that the food cooked on woods would be testier than the one cooked with aluminum pots in a kerosene stoves; hence, the preference by majority of the northern households for firewood fuel energy source. the coefficient of electricity access is positive and significantly related to kerosene fuel. this suggests that households are more likely to combine both kerosene and electricity for cooking. however, the use and preference for kerosene as cooking table 3: multivariate probit estimates of factors influencing choice of cooking energy fuel variables lpg kerosene charcoal wood coef. std. err. coef. std. err. coef. std. err. coef. std err. constant −5.1135 0.3696 −2.5533 0.1475 −2.5053 0.1926 1.1462 0.1089 gender 0.0399 0.0963 −0.0019 0.0520 −0.2192** 0.0839 −0.1348* 0.0479 age −0.0006 0.0025 −0.0072* 0.0013 −0.0019 0.0020 0.0089* 0.0011 household size −0.0589* 0.0198 −0.0763* 0.0105 0.0115 0.0117 0.0710* 0.0077 education 0.6326* 0.0728 −0.2128* 0.0493 −0.3357* 0.0821 −0.1551* 0.0466 number of children −0.0548 0.0481 0.0810* 0.0248 0.0064 0.0314 −0.0476** 0.0195 residence (rural) 0.0776 0.0866 −0.1072** 0.0459 −0.5714* 0.0788 0.3267* 0.0394 northern region −0.0799 0.0807 −0.6626* 0.0465 0.9059* 0.0726 0.1896* 0.0397 access to electricity −0.1379 0.1349 0.1008** 0.0604 0.1285 0.0887 −0.0524 0.0467 wealth status 0.8027* 0.0786 0.7155* 0.0324 0.1682* 0.0369 −0.5806* 0.0225 log likelihood −6697.7315 wald χ2 (36) 3548.29 prob.>χ2 0.0000 number of obs. 7745 source: computed by authors from stata 12 megbowon, et al.: household cooking energy situation in nigeria: insight from nmis 2015 international journal of energy economics and policy | vol 8 • issue 6 • 2018290 fuel energy option despite having access to electricity is as a result of the deplorable and unreliable state of the power sector in nigeria till date and kerosene being a relatively clean and fairly accessible fuel energy source was opted for as a back-up plan for inconsistent electricity supply. lastly, the coefficient of wealth status shows a positive relationship with all the cooking fuels considered except for firewood which is significant negatively. the implication of the significant relationship between lgp, kerosene and wealth is that non-poor households who are mostly found in urban areas have a higher probability of using lpg or kerosene as the main cooking fuel energy sources majorly due to affordability and availability. this further attests to the fact that firewood which is cheap and readily available in the rural areas is mostly used by rural and agrarian households who are generally conceptualized to fall within the poorer category of households. from this, it can be implied that lpg is more of a luxury item than necessities in nigeria. this however ought not to be so considering the abundance of natural gas resources and endowment in nigeria. this finding is also in line with (rahut et al., 2016). it can be inferred that the effects of each of the fitted explanatory variables differs across the choice and use of specific cooking fuel; hence, the significant explanatory variables fitted in the multivariate probit model explain the variation in the preference and use of alternative fuel energy options across different categories of households in nigeria. 5. conclusions this paper provided a nationwide information about current patterns and trends of households cooking fuel energy use as well as households’ energy poverty using the survey data from nmis 2015. multivariate probit model was further employed to analyse the determinants of households’ use of main cooking fuel choices. the descriptive analysis of trends and patterns of household energy choice clearly show that the proportion of households using wood and kerosene is still very high in the country and consequently cooking energy poverty situation is high as well. this dependence on wood harvesting negatively affects the environment because it links into drivers of deforestation, reduced crop productivity and increasing desertification rates especially in the north of nigeria. this trend implies there is need for urgent action by the government in promoting access to modern fuels for cooking. the result of the multivariate probit model revealed that gender, age, household size, education, number of children, location (rural or urban), access to electricity, region and wealth status significantly affect households’ energy choices. based on these findings, the following policy statements are suggested: there is need for enlightenment on the long term economic and environmental costbenefits of lpg usage, pricing, and appropriate safety measures in the process of using lpg for cooking. there should be intensive, monitored and sustainable development programme targeted at rural areas in nigeria and most especially in northern geopolitical region of the country. these programmes should include massive deployment of infrastructures which will aid easy access to cleaner cooking fuel energy for households use. the nigerian government could partner with the private sectors in the distribution of low cost technology accessories and ancillary materials needed for the use of lpg for cooking in the country. as well as in investments in renewable energy sources such as biogas, improved biomass, solar and energy efficient stoves as obtainable in the developed countries. this could be seen as public-private sector initiative or private sectors’ corporate and social responsibilities to assisting the government in the fight against households’ energy poverty. such investment today is needed to improve access to and affordability of modern and more efficient clean fuel and at the same time achieve a pollution free environment which in the long run will have a positive spill-over effects on health and general well-being of the populace. references african development bank group. (2014). west africa monitor quarterly, 3, 14-15. baiyegunhi, l.j.s., hassan, m.b. (2014), rural household fuel energy transition: evidence from giwa lga kaduna state, nigeria. energy for sustainable development, 20(1), 30-35. bazilian, m., nussbaumer, p., rogner, h., brew-hammond, a., foster, v., pachauri, s., kammen, d. (2012), energy access scenarios to 2030 for the power sector in sub-saharan africa. utilities policy, 20(1), 1-16. bhattacharyya, s.c., timilsina, g.r. (2009), energy demand models for policy formulation. a comparative study of energy demand models. washington d.c: world bank policy research working paper no. 4866. bisu, d., kuhe, a., iortyer, h. (2016), urban household cooking energy choice: an example of bauchi metropolis, nigeria. energy, sustainability and society, 6(1), 15. bouzarovski, s., herrero, s.t., petrova, s., ürge-vorsatz, d. (2016), unpacking the spaces and politics of energy poverty: pathdependencies, deprivation and fuel switching in post-communist hungary. local environment, 21(9), 1151-1170. brew-hammond, a. (2010), energy access in africa: challenges ahead. energy policy, 38(5), 2291-2301. ekouevi, k., tuntivate, v. (2012), household energy access for cooking and heating: lessons learned and the way forward. a world bank study. washington, dc: world bank. gujba, h., mulugetta, y., azapagic, a. (2015), the household cooking sector in nigeria: environmental and economic sustainability assessment. resources, 4(2), 412-433. hou, b.d., tang, x., ma, c., liu, l., wei, y.m., liao, h. (2017), cooking fuel choice in rural china: results from microdata. journal of cleaner production, 142, 538-547. iea. (2014), africa energy outlooka special report in the 2014 world energy outlook series. paris: iea. iea. (2017), energy access outlook 2017: from poverty to prosperity. world energy outlook special report. available from: http://www. iea.org/energyaccess. ifegbesan, a.p., rampedi, i.t., annegarn, h.j. (2016), nigerian households’ cooking energy use, determinants of choice, and some implications for human health and environmental sustainability. habitat international, 55, 17-24. ismail, z., khembo, p. (2015), determinants of energy poverty in south africa. journal of energy in southern africa, 26(3), 66-78. joshi, j., bohara, a.k. (2017), household preferences for cooking fuels and inter-fuel substitutions: unlocking the modern fuels in the nepalese household. energy policy, 107, 507-523. karimu, a. (2015), cooking fuel preferences among ghanaian households: an empirical analysis. energy for sustainable megbowon, et al.: household cooking energy situation in nigeria: insight from nmis 2015 international journal of energy economics and policy | vol 8 • issue 6 • 2018 291 development, 27, 10-17. makonese, t., ifegbesan, a.p., rampedi, i.t. (2018), household cooking fuel use patterns and determinants across southern africa: evidence from the demographic and health survey data. energy and environment, 29(1), 29-48. masera, o.r., saatkamp, b.d., kammen, d.m. (2000), from linear fuel switching to multiple cooking strategies: a critique and alternative to the energy ladder model. world development, 28(12), 2083-2103. mensah, j.t., adu, g. (2015), an empirical analysis of household energy choice in ghana. renewable and sustainable energy reviews, 51, 1402-1411. national malaria elimination programme (nmep), national population commission (npopc), national bureau of statistics (nbs), icf international. (2016), nigeria malaria indicator survey 2015. abuja, nigeria, and rockville, maryland, usa: nmep, npopc, and icf international. nlom, j.h., karimov, a.a. (2015), modeling fuel choice among households in northern cameroon. sustainability, 7(8), 9989-9999. ogwumike, f.o., ozughalu, u. (2012), energy consumption, poverty and environmental linkages in nigeria: a case of traditional and modern fuels for cooking. in: adenikinju, a., iwayemi, a., iledare, w., editors. green energy and energy security: options for africa. ibadan: atlantis books. pp.235-254. ogwumike, f.o., ozughalu, u.m. (2016), analysis of energy poverty and its implications for sustainable development in nigeria. environment and development economics, 21(3), 273-290. ogwumike, f.o., ozughalu, u.m., abiona, g.a. (2014), household energy use and determinants : evidence from nigeria. international journal of energy economics and policy, 4(2), 248-262. oyedepo, s.o. (2012), energy and sustainable development in nigeria: the way forward. energy, sustainability and society, 2(1), 1-17. oyekale, a.s. (2012), assessment of households’ access to electricity and modern cooking fuels in rural and urban nigeria: insights from dhs data. life science journal, 9(4), 1564-1570. rahut, d.b., behera, b., ali, a. (2016), household energy choice and consumption intensity: empirical evidence from bhutan. renewable and sustainable energy reviews, 53, 993-1009. rahut, d.b., mottaleb, k.a., ali, a. (2017), household energy consumption and its determinants in timor-leste. asian development review, 34(1), 167-197. sa’ad, s., bugaje, i.m. (2016), biomass consumption in nigeria: trends and policy issues. journal of agriculture and sustainability, 9(2), 127-157. sesan, t. (2012), navigating the limitations of energy poverty: lessons from the promotion of improved cooking technologies in kenya. energy policy, 47, 202-210. sher, f., abbas, a., awan, r.u. (2014), an investigation of multidimensional energy poverty in pakistan: a province level analysis. international journal of energy economics and policy, 4(1), 65-75. teller-elsberg, j., sovacool, b., smith, t., laine, e. (2016), fuel poverty, excess winter deaths, and energy costs in vermont: burdensome for whom? energy policy, 90, 81-91. varun, p.r., bhat, i.k. (2009), energy, economics and environmental impacts of renewable energy systems. renewable and sustainable energy reviews, 13(9), 2716-2721. world bank. (2018), database world development indicators access to electricity (% of population). available from: https://www.data. worldbank.org/indicator/eg.elc.accs.zs. [last accessed on 2018 jul 16]. world bank. (2018), database world development indicators electric power consumption (kwh per capita). available from: https://www. data.worldbank.org/indicator/eg.use.elec.kh.pc. [last accessed on 2018 jul 16]. . international journal of energy economics and policy | vol 7 • issue 2 • 2017374 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(2), 374-383. prospects for the use of associated gas of oil development as energy product mikhail shmerovich barkan1, anton vladimirovich kornev2* 1saint-petersburg mining university, 2, 21 line, st. petersburg 199106, russia, 2saint-petersburg mining university, 2, 21 line, st. petersburg 199106, russia. *email: kornev_opi@mail.ru abstract the paper analyzes the scope of associated petroleum gas (apg) losses and estimates the emissions of harmful substances into the atmosphere when apg is burned in flare devices. the technique of industrial monitoring of atmosphere air for industrial facilities of oil development is proposed. the purpose of this work is to create industrial systems for using the resource and energy potential of associated gas of oil development while minimizing a negative impact on the environment under the terms of self-repayment. keywords: emissions of harmful substances, oil and gas separation, absorption drying, mono-ethanolamine, atmospheric air pollution monitoring jel classifications: q34, q43, q52, q53 1. introduction the industrial practice gives evidence of large-scale negative consequences associated with the uncontrolled pollution of the atmosphere with associated gas of oil development and oil products as a result of flare devices operation (korzhubaev, 2009; korzhubaev, 2012; hughes, 2013). the index of flaring (deflation) of associated petroleum gas (apg) in flare devices should not exceed 5% of the volume of the produced associated gas. in order to achieve this result, it is necessary to introduce systems for its targeted use that will significantly reduce emissions of harmful substances into the atmosphere. it should be noted that the absolute volumes of apg and combustion gases are quite big. according to various estimates, they can amount to 10-11 billion m3 per year. therefore, it can be argued that the use of apg is economically and environmentally appropriate (korzhubaev, 2009; korzhubaev, 2012; hughes, 2013; aksenov, 2016; krivov, 2013; korzhubaev, 2012). recommended measures to improve associated gas utilization technologies assume the following cycle of operations: • gathering and processing system management of apg for supply to would-be customers; • gathering and compressing apg with subsequent injection into compressed cylinders in order to provide industrial facilities with an energy source for internal needs (heat supply, hot water supply, maintenance of the technological process). we should consider in parallel the possibility of implementing modern technologies for demineralization of oilfield water and its use in recycling water supply or alternative technologies to maintain the reservoir pressure in oil development. the main types of man-caused impacts in oil development given in table 1 are related to boreholes drilling, construction and assembling operations carried out within the areas allocated for producing wells, arrangement of processing areas and line facilities, and the installation of oil-storage pits. at the same time, there is a serious possibility that oil products and polluting substances enter the environment as a result of implementation of auxiliary processes and separate operations. the main factors influencing the environment during the development of oil fields are the operational emission of combustion gases in flare devices of the central processing facility, as well as exhaust gases from diesel engines of drilling units. other 45_ijeep barkan barkan and kornev: prospects for the use of associated gas of oil development as energy product international journal of energy economics and policy | vol 7 • issue 2 • 2017 375 factors influence in smaller quantities such as evaporation of light hydrocarbon fractions with leakage of equipment, spillages on the ground of well-bore fluids, oilfield and refinery water, treated oil, reactants followed by percolation into the cenozoic water-bearing horizons and drainage along the lower areas towards the surface and permanent watercourses (korzhubaev, 2009; aksenov, 2016; krivov, 2013; eder, 2016; stern, 2006; flanner et al., 2007; sims, 2008). 2. methods initial treatment (processing) of oil in oil pumping plants (opf) is its dehydration and desalination in order to reduce ballast (water) during transportation, as well as degassing to reduce the vapor pressure. the scheme of the oil and gas separation process is shown in figure 1. there are mechanical, thermo-chemical and electrochemical methods of demulsification in industrial practice. the mechanical method of demulsification is carried out according to a two-stage scheme in the sludge tanks of stages i and ii. when implementing the process of chemical demulsification, industrial demulsifiers are used, the supply and dosage of chemical agents to which is produced in package plants. dehydration and desalting of oil are carried out in field-assisted electric dehydrators. it can be seen from the scheme that in order to ensure oil and gas separation an excessive heat supply is needed for demulsification processes; fresh water is needed for desalination. the characteristics of intermediate stocks (table 2) make it possible, if necessary, to determine the volume of apg, set the conditional productivity and predict the capacity of the gas-fired supply system. 3. results based on the initial characteristics of raw materials and volumes of oil produced, it is possible to determine the volume of apg produced by the enterprise. table 3 shows the characteristics of a typical composition of raw feedstock. table 4 gives an approximate component composition of apg and its main properties. let us calculate the emissions of harmful substances into the atmosphere as a result of the combustion of apg. the conditional daily production rate of the enterprise is 12001300 tons. according to the gas-oil ratio, it is possible to determine the total volume of produced oil gas per day by specifying the conditional productivity: v = q⋅qt = 1249⋅10.85 = 135,551.65 m 3/day (1) where, q – conditional daily oil production, t/day; qt – amount of oil gas per ton of oil produced, t/day. apg emissions are calculated using the methodology for calculating emissions of harmful substances into the atmosphere when flaring apg in flare devices in accordance with applicable standards and regulations (“on approval of the methodology for calculating emissions of harmful substances into the atmosphere during the flaring of associated petroleum gas at flare devices.” order of the state committee for ecology of russia no. 199, 1998). based on the initial data of the component composition of apg, we determine the molecular weight of each component and calculate the mass fraction. for ideal gases, the numerical values of the molar and volume fractions are the same. table 1: impact of oil production facilities on components of the environment (korzhubaev, 2009; aksenov, 2016; krivov, 2013; eder, 2016; stern, 2006; flanner et al., 2007; sims, 2008) component of the environment source of impact characteristic of impact atmosphere flange coupling of oil pipelines, shutoff and control valves, pumps, pressure vent valve, etc.; oil traps; oil based fluid pouring into oil tankers emissions of hydrocarbons into the atmosphere flare devices nitrogen oxide, nitrogen dioxide machinery and equipment carbon monoxide, sulfur dioxide, pure carbon black, benzpyrene, hydrogen sulphide, methane hydrosphere drilling operations crude oil and refined products orchestrated water course (refinery water) highly mineralized oilfield water unorchestrated water course (overland flow); disturbance situations chemical agent, synthetic surface active substance, suspended matters rock sphere boreholes drilling; formation of excavated material landscape change; destruction, soil contamination leakage and oil spillage soil contamination with oil products and chemicals; soil salinization bioenvironment contaminated soils depletion in numbers and group composition of mesofauna contaminated water direct impact on the epidermis of animals; toxic and narcotic action of paraffin hydrocarbons barkan and kornev: prospects for the use of associated gas of oil development as energy product international journal of energy economics and policy | vol 7 • issue 2 • 2017376 the formula for calculating the mass fraction is: i i i i i 14 k k k 1 m m 39.8 m  = χ ⋅ χ ⋅ = = χ ⋅∑ , (2) where χ – molar fraction; m – molecular weight. the design data of apg: • mass flow: wg = 835.9 kg/h; • volume flow rate: wv = 469.6 m/h = 0.13 m/s; • density at standard conditions: ρ = 1.78 kg/m3; • molar mass: 39.8 kg/kmol. let us recalculate the entire component composition into mass fractions taking into account the formula (2), and determine the mass flow of the components (table 5). figure 1: an approximate scheme of oil and gas separation (solovyanov, et. al. 2013; kirillov 2014; pyatibratov 2014) table 2: characteristics of intermediate stocks (solovyanov et al., 2013; ferencz, 2012; leontev, 2012) name of intermediate stocks quality drivers required for verification rate as received dehydrated oil water content, % 0.3 density, g/cm3 0.9260 viscosity, mpa 208.92 content of chloride salts, mg/dm3 50 oilfield water density, g/cm3 1.128 basic sediment, % 0.0216 ion composition of water, g/l cl− 378.82 hco−3 0.15 ca2+ 12.63 mg2+ 11.43 na++k+ 209.62 oil products content, mg/dm3 45 content of chloride salts, mg/dm3 168,573 barkan and kornev: prospects for the use of associated gas of oil development as energy product international journal of energy economics and policy | vol 7 • issue 2 • 2017 377 the flare stack is a pipe with a passage diameter of 500 mm, and a height of 27.5 m/s. let us determine the exit velocity:  = = = ⋅ = w s w r m/s v v 2π 0 13 3 14 0 25 0 663 2 . . . . (3) the stoichiometric reaction of combustion is written as: 2 2 2 2 c h s n o ko kn kn co 2 h o 2 so 2 n 2 c h s n o mo n h n co n h o + n so n n + = + + (4) the volume flow rate of combustion products: a v v cp (273 t ) w w v 273 + = ⋅′ , (5) where, vcp – the amount of combustion products formed during stoichiometric combustion of 1 m3 of apg in a humid air atmosphere, (m3/m3) which can be determined by the formula: vcp = c + s + 0.5 (h + n + m ∙ (kh + kn)) (6) where, c, s, h, n and kh, kn correspond to the conditional molecular formulas of apg and moist air, respectively. the mass content of the jth chemical element in apg ωj (wt%) is calculated according to the formula:    j i i j i = ⋅∑ , (7) where, ωij – the content (wt%) of chemical element in the i th component of apg; ωi – the mass content of the i th component in apg (“on approval of the methodology for calculating emissions of harmful substances into the atmosphere during the flaring of apg at flare devices.” order of the state committee for ecology of russia no. 199, 1998). the calculated mass contents of elements in apg are presented in table 6. the number of atoms of the jth element kj (table 7) in the conditional molecular formula of the associated gas is calculated by the formula: k m m j j j a = ⋅ ⋅0 01.  , (8) table 3: typical raw feedstock composition (krivov, 2013; pavlov et al., 1987) name of raw feedstock products quality drivers required for verification rate as received oil-in-place water content, % 78-80 density, g/cm3 1.0875 viscosity, mpa 66.5 content of chlorides, mg/dm3 157,152 basic sediment, % 0.0550 sulphur content, % 2.16 gas-oil ratio at 20°c, m3/t 10.85 oilfield water density, g/cm3 1.145 exponent of hydrogen ion activity, ph 6.3-6.5 hco−3 0.045-0.052 ca2+ 14.1-14.5 mg2+ 4.8-4.99 na++k+ 114-115 table 4: approximate component composition of associated petroleum gas and its properties (averaged data) (korzhubaev, 2012; krivov, 2013; sviridova, 2015; churakaev, 1983) component/ parameter content, %/value component content, % mass flow, kg/h 830.0-835.9 i-c4h10 2.89-3.73 density at standard conditions, kg/m3 1.75-1.78 n-c4h10 8.11-8.35 molar mass, kg/kmol 39.8 i-c5h12 2.98-3.55 co2 0.8-1.59 n-c5h12 2.01-2.56 h2s 0.35-0.54 n-c6h14 1.80-2.32 n2 5.89-6.67 n-c7h16 0.48-0.65 ch4 6.13-6.92 n-c8h18 0.14-0.17 c2h6 32.16-34.21 h2o 4.6-5.1 c3h8 21.8-23.6 table 5: recalculation of the component composition into mass fractions fractional analysis, % molar mass, g/mol mass fraction, % mass flow of the component, kg/h concentration, g/m3 co2-1.59 44.01 1.76 14.70 31.30 h2s 0.54 34.08 0.46 3.87 8.23 n2-6.67 28.01 4.69 39.24 83.57 ch4-6.92 16.04 2.79 23.31 49.64 c2h6-34.21 30.07 25.85 216.05 460.07 c3h8-23.6 44.1 26.15 218.59 465.47 i-c4h10-3.73 58.12 5.45 45.53 96.96 n-c4h10-8.35 58.12 12.19 101.93 217.04 i-c5h12-3.55 72.15 6.44 53.79 114.55 n-c5h12-2.56 72.15 4.64 38.79 82.61 n-c6h14-2.32 86.17 5.02 41.99 89.41 n-c7h16-0.65 100.21 1.64 13.68 29.13 n-c8h18-0.17 114.23 0.49 4.08 8.68 h2o 5.1 18.02 2.31 19.30 41.10 99.96 99.87 total c3h8+ 1,144.95 barkan and kornev: prospects for the use of associated gas of oil development as energy product international journal of energy economics and policy | vol 7 • issue 2 • 2017378 the conditional molecular formula of apg is as follows: c2.465h6.727s0.005n0.133o0.083 (9) at the air humidity of 60% and 20°c, the moisture content d = 0.01 kg/kg. then the number of atoms of chemical elements in the conditional molecular formula of moist air can be determined according to the formulas given in table 8. the molecular formula of moist air is as follows: o0.433n1.570h0.032 (10) the stoichiometric reaction of combustion taking into account the performed calculations: c = n c co 2.465 6.727 0.005 0.133 0.083 0.433 1.570 0.032 2 h s n o +mo n h o 2 ++n h o+n so +n n h o 2 s 2 n 2 2 2 2 o (11) m is the molar stoichiometric coefficient according to the condition of the complete saturation of the valency (the complete oxidation reaction); it is calculated by the following formula: m k v k v j j j j j j = − ⋅ ′ ⋅ ′ = − ⋅ − ⋅ − ⋅ + ⋅ ⋅ ∑ ∑ 4 2 465 1 6 727 2 0 005 2 0 083 2 0 43 . . . . . 33 1 0 032 19 709 − ⋅ = . . , (12) where v j ' and vj – valency of the elements j and j’ which are the part of humid air and apg; k j ' and kj – number of atoms of elements in the conditional molecular formulas of moist air and gas. the theoretical amount of moist air required for complete combustion of 1 m3 of apg is 19.709 m3. let us determine the amount of separate combustion products: n 2 co = c = 2 465. (13) n h o 2 = 0.5 ∙ (h + mkh) = 0.5 ∙ (6.727 + 19.709 ∙ 0.032) = 3.679 (14) n so 2 = s = 0.005 (15) n n 2 = 0.5 (n + mkn) = 0.5 (0.133 + 19.709 ∙ 1.570) = 15.538 (16) hence the amount of combustion products formed during the stoichiometric combustion of 1 m3 of apg in an atmosphere of moist air: vcp = 2.456 + 0.005 + 0.5 (6.727 + 0.133 + 19.709 (0.032 + 1.570)) = 21.678 m3/m3 (17) the specific permissible discharge of carbon dioxide is calculated by the formula: q m q 2 2 4 4 co co co ch ch co c m q m = ⋅ − −      = ⋅ − ⋅ − g m 44 011 2 465 39 8 5 10 . . . 44 2 16 043 2 10 28 011 2 693 . . .− ⋅       = − (18) the specific permissible discharge of water vapor: 4 2 2 4 chh h o h o g ch 4 q(h mk ) q 0.5 m m m (6.727 19.709 0.032) 5 10 0.5 18.016 1.665 39.8 16.043 −  − = ⋅ ⋅ −     + ⋅ ⋅ = ⋅ ⋅ − =   (19) table 6: mass content of elements in apg fractional analysis content of chemical elements in components (reference data) the mass content of elements in apg component mass fraction, % c h s n o c h s n o co2 0.02 27.29 72.71 0.0048 0.0128 h2s 0.0046 5.92 94.08 0.0003 0.0044 n2 0.05 0.0469 ch4 0.03 74.87 0.0209 0.0070 c2h6 0.26 79.89 20.11 0.2065 0.0520 c3h8 0.26 81.71 18.29 0.2137 0.0478 i-c4h10 0.05 82.66 17.34 0.0450 0.0094 n-c4h10 0.12 82.66 17.34 0.1008 0.0211 i-c5h12 0.06 83.23 16.75 0.0536 0.0108 n-c5h12 0.05 83.24 16.76 0.0386 0.0078 n-c6h14 0.05 83.73 16.27 0.0421 0.0082 n-c7h16 0.02 84.01 15.99 0.0137 0.0026 n-c8h18 0.00 84.12 15.88 0.0041 0.0008 h2o 0.02 11.19 88.81 0.0026 0.0205 99.87 0.7438 0.1704 0.0044 0.0469 0.0333 apg: associated petroleum gas table 7: number of atoms of the jth element element mj kj element mj kj c 12.011 2.465 n 14.008 0.133 h 1.008 6.727 o 16 0.083 s 32.066 0.005 barkan and kornev: prospects for the use of associated gas of oil development as energy product international journal of energy economics and policy | vol 7 • issue 2 • 2017 379 the specific permissible discharge of nitrogen: q m n mk m q m n n h g no no 2 2= ⋅ + −       = ⋅ + ⋅ ( ) . ( . . . 2 28 016 0 133 19 709 1 570)) . . . 39 8 3 10 30 008 21 872 3 − ⋅       = − (20) the specific permissible discharge of sulfur dioxide: q m s m so co g 2 = 2 ⋅ = ⋅ =64 054 0 005 39 8 0 008. . . . (21) based on the analysis of the gas flow, the coefficient of underburning ku = 0.0006. the specific permissible discharge of hydrocarbons (on conversion to methane), as well as the sulfur compounds contained in gas such as hydrogen sulphide and mercaptan, are determined by the general formula: q c c x x h u h y y k= ⋅ ⋅0 01. ω (22) the emissions of hydrocarbons (on conversion to methane):   ( )ch i i ch m /m 44 277∑ = ⋅ =∑ (23) qch4 = 0.01∙0.0006∙277 = 0.001662 kg/kg (24) mch4 = 0.278∙0.001662∙835.9 = 0.386 g/s (25) the mass content of hydrogen sulfide is 0.46%. then: qh s2 = 0.0006 ∙ 0.01 ∙ 0.046 = 0.00000276 kg/kg (26) m h s 2 = 0.278 ∙ 0.00000276 ∙ 835.9 = 0.000641 g/s (27) let us determine the maximum emissions of harmful substances (g/s): qgi = 0.278 ∙ qi ∙ wg (28) the calculated values of the maximum and total emissions of harmful substances into the atmosphere during the combustion of apg are given in table 9. 4. discussion transportation of oil gas is impossible for long distances because water vapor and heavy hydrocarbons condense when the temperature decreases because they form liquid, ice and hydrate plugs. proceeding from this, the processing of this gas should be carried out in an industrial complex designed for oil and gas separation of oil-in-place. the technological cycle assumes the following stages of processing: • compression; • drying; • stripping; • acid gas removal (churakaev 1983; kochi, 2013). when these operations are over, the dried and stripped gas can be transported under high pressure for long distances. liquefied gases are formed from unstable gasoline gas in the form of a propane-butane mixture or technically pure separate hydrocarbons and gasoline. liquefied gases are widely used as raw materials for the petrochemical industry; they are used as motor fuel, as well as household fuel for gasification of settlements, enterprises, livestock farms, etc. the main consumer of liquefied gases is petrochemical production. ethane, propane, n-butane, as well as gasoline and hexane, serve as raw materials for the production of ethylene which in turn produces ethyl alcohol, glycerin, ethylene glycol, dichloroethane, ethyl chloride, etc. further processing of these substances gives varnishes, solvents, dyes, detergents, synthetic rubber, polyethylene, and polypropylene. butane is used to produce synthetic butadiene rubber; isobutane and isopentane are used for the production of isoprene rubber which is close to natural. gasoline is used in oil refineries (oil refinery plant) as a compounding additive that improves the properties of gasoline. liquefied gases, due to the ability to be in table 8: number of atoms of the jth element of moist air element o n h kj (0.421+1.607d) (1+d) 1.586 (1+d) 3.215d (1+d) table 9: results of calculations of emissions of harmful substances into the atmosphere during the combustion of associated petroleum gas substance specific permissible discharge at sootless flaring, kg/kg maximum emission of harmful substances, g/s gross emissions of harmful substances, g/t co 2×10−2 4.647 146.55 n2 3×10 −3 0.697 21.98 benzo (a) pyrene 2×10−2 0.464×10−8 1.46×10−7 so2 0.008 1.859 58.63 co2 2.693 625.80 19735.23 h2s 2.76·10 -6 0.000641 0.02 ch4 1.662·10 -3 0.386 12.17 barkan and kornev: prospects for the use of associated gas of oil development as energy product international journal of energy economics and policy | vol 7 • issue 2 • 2017380 a gaseous state under normal conditions and to switch to a liquid state at relatively low excess pressures, are very convenient for the use as a household fuel. a complicated pipeline network is not required for their transportation; they can be delivered to certain areas in cylinders and special tanks. liquefied gases are widely used for cutting metals (churakaev, 1983; kochi, 2013). thus, dried and stripped apg can be used at power plants that allow reducing emissions into the atmosphere, especially when switching from solid or liquid fuel to gas. the produced gas can also be transported to nearby industrial facilities. the part of the processed gas can be sent for sale to petrochemical enterprises and a consumer. when the temperature of gas that contain maximum of water vapor decreases, then condensation of the part of water vapor takes place. to reduce the temperature at which condensation of water vapor occurs, it is necessary to dry it. for industrial implementation, it is recommended to dry the gas with liquid absorbers, since its advantages are small investments and operating costs. the scheme of the process of gas drying with liquid absorbers is shown in figure 2 (ferencz, 2012; churakaev, 1983; kochi, 2013; etvud, 2005). at diethylenglycol dehydration (deg), wet gas goes to the lower scrubbing part of the absorber (1) where it is freed from suspended hydrocarbon condensate and water. then it passes through the central tube of the draw-off tray and contacts with deg or teg absorber water solution flowing from above. gas, being on bubble trays, rises from tray to tray, the number of which depends on the design of the absorber and can be from 5 to 12; then gas is dried and goes to the upper scrubbing part of the column where the entrained drops of absorber are retained. above the absorber, the dried gas goes to the destination. as the solution of the absorber flows down (from tray to tray), it is increasingly saturated with water, then it is gathered on a draw-off tray (stretching) of the absorber. the absorber operates under the same pressure, under which gas is sent to the dryer. to ensure the self-flow of the regenerated absorbent from the stripping tower or stripper (4) through heat exchangers (2) and the refrigerator (6) into the intermediate tank, the desorber is placed on a shell of 4-5 m high and the absorbent is sent from the tower to the next stage – regeneration. on exit from the absorber, the saturated absorbent successively passes the heat exchanger (2), the evaporator (3) in which absorbed gases are extracted from it, then it is passed by the second heat exchanger (2) and goes to the stripping tower at a temperature close to the boiling point (4). in the desorber, water vapor from the absorber solution is distilled. gases and vapors of water released from the solution are emitted from the top of the tower into the atmosphere. sometimes water vapor condenses and then is sent to the upper tray for a cold irrigation. the stripping tower has 10-16 bubble-cap plates or valve type plates and one draw-off tray mounted 0.6-1.0 m below of the lower sieve tray. the absorbent gathered on the draw-off tray passes by gravity through a remote heater called a reboiler (5), and merges into the bottom of the column. in the heater, the absorber solution is heated by water vapor or another heat carrier. the absorbent inlet is at the bottom for better heat transfer, and the outlet is at the top. thus, the heater is always filled with the absorber and the entire mass of the circulating absorbent passes through it bottom-upwards. the regenerated absorber gathered in the lower part of the desorber (4) passes through the heat exchanger (2) where it gives off heat to the saturated absorber, then it passes through the cooler 6 to the intermediate tank 7 from which it is sent for irrigation. the desorber, as a rule, operates under atmospheric pressure or the pressure that is slightly higher (0.011-0.012 mpa). in some devices, the absorber is regenerated under vacuum. the industrial practice of removing so2 and co2 impurities from apg involves the precipitation of acidic components with the help of solutions of mono-ethanolamines (mea). mea absorbs h2s and co2 along with the formation of sulfides, disulfides, carbonates and bicarbonates: 2rnh2 + h2s <=> (rnh3)2s, (29) (rnh3)2 + h2s <=> 2rnh3hs, (30) 2rnh2 + co2 + h2o <=> (rnh3)2co3, (31) (rnh3)2 co3 + co2 + h2o <=> 2rnh3hco3, (32) 2rnh2 + co2 <=> rnhcoonh3r. (33) r is a residual in these equations ch2-ch2-oh. the course of reactions is from left to right at the temperature of 20-40°c and the increased pressure; and the course of reactions figure 2: the scheme of the process of gas drying with liquid absorbers (ferencz 2012; churakaev, 1983; kochi, 2013; etvud, 2005): 1 – absorber; 2 – heat exchangers; 3 – evaporator; 4 – stripping tower (strip column); 5 – reboiler; 6 – refrigerators; 7 – intermediate tank; 8 – pump. flows: i – raw gas; ii – dry gas; iii – weathering gas; iv – water vapor; v – regenerated absorbent; vi – fresh absorbent; vii – gas condensate barkan and kornev: prospects for the use of associated gas of oil development as energy product international journal of energy economics and policy | vol 7 • issue 2 • 2017 381 is from right to left with the increase in temperature to 105-130°c and with the pressure close to the atmospheric one (kirillov, 2014; ferencz, 2012; leontev, 2012; pavlov et al., 1987). chemical reactions are carried simultaneously with the physical process of absorption. the driving force of absorption (diffusion) is the difference between the partial pressures of h2s or co2 in the gas phase and mea solution. h2s and co2 molecules overcoming the resistance of the liquid film react chemically with mea. the resulting products are removed very quickly from the interfacial area and they are distributed uniformly and fully in the solution. therefore, the partial pressures of the absorbed acid gases in the solution do not increase but remain at the same level. since the vapor pressure ratings of co2 and h2s equilibrated with mea are close to zero (or even zero), the absorption of acid gases with the solution is possible until mea is chemically reactive with these gases. the basic scheme of the gas treatment unit for the solution of mea is shown in figure 3. in the gas treatment unit with mea solution, the gas containing acidic components is sent to the lower absorber zone (2) in which it contacts the mea solution. the process has counter-current flow; the gas flows bottom-upwards, the mea solution is from the top downward. absorption is carried out at pressures from 0.2 to 7.0 mpa. the absorber has 16-30 bubble plates. the purified gas from the top of the absorber goes to the desorber 7 where it is released from the drops of the mea solution. the solution saturated with sulfides, disulphides, carbonates and bicarbonates goes to the amine flash drum 3 from the bottom of the absorber. there hydrocarbon gases and some of the acid gases are released from the solution. individual point monitoring must meet the following criteria: • to characterize for sure a pollution bubble (the pollution bubble is determined by the results of the dispersion calculations and subsequent analysis); • to characterize the level of impact within the specific zone on people health and on the environment as a whole; • to allow characterizing the contributions of the main sources of pollution. the method of conducting observations (at a control point or by flare plume monitoring) is determined in each specific case and depends on the location of the emission sources and their type, as well as the composition of the pollutants emitted. table 10: recommended schedule for compliance control with emission quota for an industrial facility using associated petroleum gas control point production, shop floor, shop area name of the harmful substance number of planned measurements in a period of time controlled parameters on the boundary of spz oil-separator amount of hydrocarbons incomplete programme mass fraction of saturated hydrocarbons (in total), unsaturated hydrocarbons (in total) and aromatic hydrocarbons (benzene, toluene, ethylbenzene, xylenes, styrene) with their joint presence in the atmospheric air, workplace air and industrial emissions boiler (if any) sulphur dioxide once year mass fraction of sulfur dioxide in waste gases from boilers, thermal power plants, state district power stations and other fuelburn systems – carbon dioxide once year mass fraction of carbon dioxide from sources of burning of organic fuel – nitrogen oxides once year mass fraction of nitrogen oxides in operational emissions of boiler houses, thermal power plants and state district power plants on the boundary of a settlement amount of hydrocarbons incomplete programme mass fraction of saturated hydrocarbons (in total), unsaturated hydrocarbons (in total) and aromatic hydrocarbons (benzene, toluene, ethylbenzene, xylenes, styrene) with their joint presence in the atmospheric air, workplace air and industrial emissions spz: sanitary protection zone figure 3: gas treatment unit with the solution of mono-ethanolamine (churakaev, 1983; etvud, 2005): 1, 3, 10 – separators; 2 – absorber; 4 – tank; 5, 9 – refrigerators; 6 – heat exchanger; 7 – desorber; 8 – reboiler; 11 – pumps. flows: i – raw gas; ii – purified gas; iii – acid gases barkan and kornev: prospects for the use of associated gas of oil development as energy product international journal of energy economics and policy | vol 7 • issue 2 • 2017382 an observation program is developed for each point that includes a list of substances to be monitored, the composition of means and methods of measurement or calculation, frequency and time limits. to monitor the norms of maximum permissible discharges, the values of ground level concentration were determined at points on the boundary of the sanitary protection zone in the direction of the nearby residential development, and on the boundary of the settlement zone. a potentially implemented schedule for compliance control with emission quota is presented in table 10. in concordance with the incomplete program, observations are made according to a staggered schedule: tuesday, thursday, saturday – at 7:00, 10:00, 13:00, monday, wednesday, friday – 15:00, 18:00, 21:00. 5. conclusion the incidence of losses of apg that is burned in flare devices is determined; as a result, a significant amount of pollutants (co, co2, nox, and so2) are emitted into the atmospheric air. based on the analysis of the existing practice, recommendations are formulated for the targeted use of apg with the change-over of boiler rooms designed for the use of natural gas produced as a result of processing of the apg. the implementation of such measures will make it possible to eliminate the irrevocable losses of natural energy carriers under the terms of selfrepayment. the paper can be summarized as follows: 1. ecological and economic feasibility of using irreversibly lost associated gas of oil production is beyond doubt. 2. the processes associated with the operation of flare devices in oil production and refining facilities lead to irreversible environmental violations, primarily due to the burning of the atmosphere and its simultaneous large-scale pollution. 3. the implementation of integrated technologies for the use of associated gases should be a high-priority task for oil companies. references aksenov, a.n. (2016), analiz ukazaniy po vzimaniyu platy za vybrosy zagryaznyayushchikh veshchestv pri szhiganii ili rasseivanii png i primeneniye ikh na praktike (analysis of instructions on charging fees for emissions of pollutants during combustion or dispersal of apg and their application in practice). neft, gaz i pravo: analitika. kommentarii. praktika, 3, 21-25. churakaev, a.m. (1983), pererabotka neftyanykh gazov. uchebnik dlya rabochikh (processing of oil gases. textbook for workers). moscow: nedra. p279. eder, l.v. (2016), dobycha i utilizatsiya poputnogo neftyanogo gaza kak napravleniye kompleksnogo osvoyeniya nedr: rol gosudarstva i biznesa, tekhnologiy i ekologicheskikh ogranicheniy (extraction and utilization of associated petroleum gas as a direction of integrated development of mineral resources: role of government, business, technologies and environmental constraints). burenie i neft, 10, 8-15. etvud, t. (2005), skhema predotvrashcheniya vybrosov v atmosferu organicheskikh letuchikh komponentov na ustanovke osushki gaza (scheme for preventing atmospheric emissions of organic volatile components in the gas drying plant). neftegazovyye tekhnologii, 10, 15-16. ferencz, t. (2012), adsorbtsionnaya osushka gaza pered transportirovkoy (adsorption drying of gas before transportation). neftegazovye tekhnologii, 10, 58-62. flanner, m.g., zender, c.s., randerson, j.t. (2007), present-day climate forcing and response from black carbon in snow. journal of geophysical research, 112(d11), 17-24. hughes, d. (2013), izobiliye netraditsionnykh vidov topliva v novuyu eru energetiki. chast 7 (abundance of unconventional fuels in a new era of energy. part 7). neftegazovye tekhnologii, 12, 25-38. kirillov, v.a. (2014), tekhnologiya pererabotki poputnykh neftyanykh gazov maloresursnykh i malonapornykh neftyanykh mestorozhdeniy v metanovodorodnyye smesi i tovarnyy prirodnyy gaz (technology of processing of associated petroleum gases of low-resource and lowpressure oil fields into methane-hydrogen mixtures and commercial natural gas). neft. gaz. novatsii, 8, 68-75. kochi, k.v. (2013), ispolzovaniye poputnogo neftyanogo gaza s uchetom novykh resheniy (use of associated petroleum gas taking into account new solutions). ekologiya proizvodstva, 3, 26-30. korzhubaev, a.g. (2009), analiz tendentsiy v neftyanom komplekse rossii (analysis of trends in the oil complex of russia). eko, 10, 85-103. korzhubaev, a.g. (2012), negasimoye plamya png. sostoyaniye i perspektivy kvalifitsirovannogo ispolzovaniya poputnogo neftyanogo gaza v rossii (unquenchable flame of apg. status and prospects for the qualified use of associated petroleum gas in russia). neft rossii, 7, 58-61. korzhubaev, a.g. (2012), utilizatsiya poputnogo neftyanogo gaza osnova povysheniya tekhnologicheskoy effektivnosti prirodopolzovaniya (utilization of associated petroleum gas is the basis for increasing the technological efficiency of natural resource use). mineralnyye resursy rossii, 3, 42-47. krivov, r.a. (2013), ekonomicheskoye stimulirovaniye ratsionalnogo ispolzovaniya poputnogo neftyanogo gaza (economic incentives for the rational use of associated petroleum gas). ekologiya proizvodstva, 12, 14-22. leontev, s.a. (2012), opredeleniye optimalnykh usloviy separatsii pri podgotovke poputnogo neftyanogo gaza (determination of optimal separation conditions in the preparation of associated petroleum gas). izvestiya vuzov. neft i gas, 2, 57-59. pavlov, k.f., romankov, p.g., noskov, a.a. (1987), primery i zadachi po kursu protsessov i apparatov khimicheskoy tekhnologii (examples and tasks about processes and devices of chemical technology). 10th ed. leningrad: khimiya. p576. prikaz goskomekologii rossii ot 8 aprelya 1998 g. no. 199 ob utverzhdenii metodiki rascheta vybrosov vrednykh veshchestv v atmosferu pri szhiganii poputnogo neftyanogo gaza na fakelnykh ustanovkakh (on approval of the methodology for calculating emissions of harmful substances into the atmosphere during the flaring of associated petroleum gas at flare devices. order of the state committee for ecology of russia no. 199). st. petersburg. april 8, 1998. p27. pyatibratov, p.v. (2014), povysheniye effektivnosti zakachki neftyanogo poputnogo gaza v usloviyakh sistemy podgotovki nefti s dvukhstupenchatoy separatsiyey (increasing the efficiency of pumping of oil associated gas in the terms of oil treatment system with a two-stage separation). territoriya neftegas, 11, 40-44. sims, p. (2008), effektivnoye snizheniye vybrosov, zagryaznyayushchikh barkan and kornev: prospects for the use of associated gas of oil development as energy product international journal of energy economics and policy | vol 7 • issue 2 • 2017 383 atmosferu (effective reduction of pollutant emissions). neftegazovyye tekhnologii, 3, 76-78. solovyanov, a.a., tetelmin, v.v., yazev, v.a. (2013), poputnyy neftyanoy gaz. tekhnologii dobychi, strategii ispolzovaniya: uchebnoe posobie (associated petroleum gas. production methods, utilization strategies: textbook). dolgoprudny: intellect. p208. stern, n. (2006), the economics of climate change. cambridge, uk: cambridge university press. p610. sviridova, o.s. (2015), ispolzovaniye png: organizatsionnyye, ekonomicheskiye i pravovyye problemy i puti ikh resheniya (chast 2) (use of apg: organizational, economic and legal problems and ways to solve them (part 2)). neft, gaz i biznes, 4, 37-40. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 1 • 2023128 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(1), 128-134. comparative analysis of strategies for innovative development of the fuel and energy complex: the experience of the eu countries makpal zholamanova1*, nurbakhyt nurmukhametov2, mikhail tolmachev3, kassymkhan sarsen4, altyn amerkhanova5 1department of finance, gumilyov eurasian national university, satbaeva st. 2, nur-sultan 010000, kazakhstan, 2department of economics, nao s. seifullin kazakh agrotechnical university, ave. zhenis 62, nur-sultan 010005, kazakhstan, 3department of business analysis, financial university under the government of the russian federation, 49 leningradsky prospekt, 125993, moscow, russian federation, 4department of economic, l.n. gumilyov eurasian national university, kazakhstan, 5department of management njsc, l.n. gumilyov eurasian national university, 000005, kaymakam street, 11, nur-sultan, republic of kazakhstan. *email: makpalzh@mail.ru received: 30 august 2022 accepted: 20 december 2022 doi: https://doi.org/10.32479/ijeep.13628 abstract most european countries do not have large reserves of natural resources and depend on imported energy resources. in this regard, the government of the european union has approved a new energy policy aimed at developing a “green” economy and combating dependence on non-renewable resources. currently, the european union is a leader in the development of renewable energy sources. many states have achieved success in this industry, their experience can be used in other countries where alternative energy is not so widespread. this study analyzes and compares existing strategies for the innovative development of the fuel and energy complex of eu member states. the process of formation of the eu energy policy and its distinctive features were studied. the example of italy, germany, poland, spain, and finland was used to study in detail the impact of the new energy policy approved by the eu government. the prospects for the introduction of alternative energy sources in the geographical and climatic conditions of kazakhstan have been assessed. synthesizing the information obtained, a list of tips for the successful development of alternative energy in the republic of kazakhstan was proposed. keywords: european union, kazakhstan, green economy, fuel and energy complex, renewable energy, natural resources jel classifications: q20, q30, q42, q50 1. introduction the european union has enormous economic potential. driven by the interests of public safety and energy security, european states have modified the fuel and energy balance in favor of petroleum products and clean natural gas over coal. however, the eu is dependent on energy imports due to a shortage of its own natural resources (pavlenko, 2020). nevertheless, the eu is actively developing alternative energy, increasing the supply of “green” electricity every year. as of 2019, the eu is a leader in the fight against climate change at the global level. conventional energy, which occupies the bulk of the fuel and energy complex of the eu countries, is gradually being replaced by alternative energy. due to the gradual depletion of fossil fuels, the strong dependence of some countries on imported energy resources, greenhouse gas emissions, and overall levels of pollution, the eu energy policy is aimed at the transition to renewable energy sources. this journal is licensed under a creative commons attribution 4.0 international license zholamanova, et al.: comparative analysis of strategies for innovative development of the fuel and energy complex: the experience of the eu countries international journal of energy economics and policy | vol 13 • issue 1 • 2023 129 depending on the geographical location and amount of natural resources, different ways of reducing dependence on nonrenewable sources are applied. for example, sukhotina and tomashevskaya (2019) point out that germany leads in energy consumption but is the largest producer of alternative energy in the eu. the united kingdom, as part of the eu, ranked third on the list of total energy consumption, with most ocean energy projects continuing to be implemented in the united kingdom. since environmental protection and reduction of pollutant emissions is a global task (tulchynska et al., 2021), the rich experience of european countries can be used in other regions to improve the fuel and energy complex. kazakhstan has a large territory, so it is necessary to use the potential of the state to expand energy production from alternative sources. this paper presents an analysis and comparison of the energy sector of european countries, identifying the best strategies for the geographical and climatic conditions of kazakhstan. the features of the fuel and energy complex of some eu countries depending on climatic conditions, in particular, italy, germany, poland, spain, and finland are highlighted. identified the most effective solutions to improve the fuel and energy complex of kazakhstan and justified the need to disseminate renewable energy sources. 2. literature review the question of natural resources and the possibility of obtaining energy in an environmentally friendly way has been the subject of study by many scientists from all european countries. many studies are currently examining the impact of the eu’s new energy strategy. hewitt et al. (2019) examined the drivers of the eu’s european energy policy using examples from germany, belgium, france, italy, spain, poland, sweden, and the united kingdom. the researchers presented a broad sample of the energy strategies of different countries. the authors compared the activities of states with high dependence on energy imports (italy, belgium, and spain), countries with high coal consumption (poland, germany, and the uk), and countries whose energy dependence has been decreasing in recent years (france, sweden). the comparison is also made from the perspective of the largest production of electricity from renewable sources. the countries that generate the largest share of electricity using photovoltaic systems include: germany, spain, and italy. wind power is most common in germany, great britain, and spain. hydropower is in sweden, france, and italy. countries with less developed renewable energy sources include poland. tagliapietra et al. (2019) determined under what conditions a fullscale energy transition toward renewable energy and zero-carbon emissions would be economically and technologically feasible. the topic of sustainable development of eu member states is addressed in wieczorek-kosmala et al. (2021). by conducting an empirical analysis of the financial performance of energy companies, the authors identified factors for the sustainable performance of the energy sector in europe. polzin and sanders (2020) explored the possibility of europe completely abandoning conventional energy, identifying a mismatch between the available funding for green projects and the required investments to achieve zero carbon emissions by 2050. an assessment of the impact of energy reforms conducted by angheluta et al. (2019). the article numerically assesses the progress of european countries on the way to achieving the reduction of harmful emissions into the atmosphere and increasing the production of energy from renewable sources. a comparative analysis of renewable energy data in transportation, electricity, heating, and cooling is presented. studies have shown that in all states there is an increase in the use of renewable resources in all sectors. an important point is the security of the energy system. kovacic and di felice (2019) compared the discrepancy between the political program and the current level of reliability of european countries’ power systems. the authors noted that this point is often mentioned in energy programs, but in reality, it is often ignored. a proposal was made to strengthen control over the security of eu energy complexes. opportunities for kazakhstan’s transition to renewable energy are considered in the article by nazarova et al. (2020). the prospects for the development of alternative energy sources in the republic of kazakhstan, in particular wind, solar, biogas, and hydropower, were determined. the authors identified the main requirements for the implementation of the listed types and assessed the benefits of the transition to the use of renewable resources. prospects for the development of the spread of “green” energy sources are also considered in the article by zhunusova and omarbakiev (2018). the researchers believe that in the climatic and geographical conditions of kazakhstan the most efficient production of electricity based on solar and wind installations. it is determined that hydropower can produce 25 times more energy than the use of gas, oil, and coal. nevertheless, in order to successfully implement a renewable energy policy, a number of legal and organizational measures must be taken. 3. methodology the methodological approach of this article is based on methods of analysis and comparison of the existing energy policies of different eu countries, depending on the current situation of their fuel and energy complex. the synthesis method was also used, which allowed to generalize the information obtained for the introduction of alternative energy in the republic of kazakhstan. a detailed review of the history of the formation of european energy policy is necessary the study was conducted in three stages. the first stage of the article examined the history of the formation of european energy policy. the main stages of the formation of the eu energy system and the consequences of the adopted directives were defined. the main objectives of the european government for the coming years are outlined. zholamanova, et al.: comparative analysis of strategies for innovative development of the fuel and energy complex: the experience of the eu countries international journal of energy economics and policy | vol 13 • issue 1 • 2023130 at the second stage, the fuel and energy complexes of different eu countries were analyzed, and the peculiarities of each state were highlighted. the energy systems of italy, germany, poland, finland, and spain are examined in detail. the strengths and weaknesses of each state were identified, their ways of resisting dependence on energy imports and the spread of alternative energy were studied. the third stage studied the prospects for introducing renewable energy sources in kazakhstan. based on the experience of european countries, proposed ways to accelerate the development of alternative energy. the need to use solar, hydro, wind, and bioenergy is justified. this issue is considered from the perspective of balancing the economy of the country and employment. it is indicated what actions should be avoided in the new energy policy. 4. energy policy of the european union the history of eu energy policy is divided into three periods, which focused on energy security, free competition in the domestic market, and the fight against climate change. in 1951 the european coal and steel community was created, at that time the main source of energy of eu countries was coal. in 1957, the european atomic energy community was approved. these were the first steps toward a common energy policy based on supranational powers. subsequently, in the 1980s and 1990s, directives were issued to liberalize the european energy market in order to develop its competitiveness. in addition, the first energy package, a collection of directives on gas and electricity in 1996 and 1998, respectively, was released. as a result, eu member states were to open their energy markets to strengthen their competitiveness, security of supply, and protection of nature. however, the actions taken did not solve the issue of the lack of a legal framework and the absence of a common energy policy. it was not until 2005 that the european council adopted a common european energy policy and approved the second energy package, overturning the previous one. this gave an impetus to the creation of program-targeted documents aimed at improving the sustainability of the energy economy, security of supply, etc. reforms aimed at liberalizing the gas and electricity sector were carried out. between 2006 and 2007, new energy policy goals were set to combat climate change, improve energy security and enhance the competitiveness of member states. the status of european energy policy was strengthened by the lisbon treaty, which was signed in 2007 and entered into force in 2009. this gave the european parliament and the council the ability to pass legislation in the field of energy. according to the treaty, the main objectives are: developing the energy market, managing the european oil, gas, electricity, and gas network, strengthening the security of energy supply, improving energy efficiency, expanding the range of “green” energy technologies. in this case, the environmental aspect was brought to the forefront. the third energy package, adopted in 2009, implies new changes in the sale and transportation of gas and electricity. the energy companies have not been able to operate the transmission network and produce or sell energy at the same time since then and have to be separated. thus, it has served to promote fair competition in the market and reduce the cost of energy for consumers. the eu government has worked hard to ensure the security of the energy supply and a free energy market, achieving its goals. subsequently, there was an increase in the number of reforms affecting the development of green energy. the european council 2011 adopted an 80-95% emissions reduction target by 2050, and in 2014 a framework on energy and climate change was proposed to be implemented by 2030. in 2016. the european commission issued a set of regulatory proposals, clean energy for all europeans. thus, three goals were set: to achieve the highest energy efficiency and global leadership in the field of alternative energy, as well as to create favorable conditions for consumers, in particular, it concerns the cost of energy resources. in 2019, the foundations of the new energy policy were finalized, the package “clean energy for all europeans” was finally formed. the strategy of carbon neutrality was approved, a complete shift from fossil fuels to cleaner energy. one of the main intentions was to increase energy production from renewable sources to 32% by 2030 (knodt, 2018; lehotay, 2020). the effectiveness of the reforms carried out varies greatly from country to country. ossowska and janiszewska (2020) identified four groups of eu member states, depending on the level of sustainable energy consumption. the first class denotes a favorable situation, the second rather favorable, the third rather unfavorable, and the fourth unfavorable. the first group includes the nordic countries: denmark, finland, and sweden; the share of energy production by renewable energy sources in these countries was 35%, 41%, and 51%, respectively. although denmark and sweden are among the most energy-dependent eu countries, and the energy efficiency index is rather low, the governments of these countries successfully provide the population with the required amount of energy by expanding alternative sources. natural conditions allow extensive use of hydropower in coastal areas and hydropower in mountainous areas. the second group includes italy, the czech republic, latvia, estonia, greece, croatia, portugal, and romania. these countries have the best energy efficiency levels. the third group includes austria, ireland, germany, spain, france, belgium, bulgaria, lithuania, hungary, slovakia, and slovenia. the energy situation in these countries is more difficult. most of these countries are failing to cope with the reduction of harmful emissions into the atmosphere. there is also no positive trend in overcoming energy dependence. the last group includes malta, the netherlands, luxembourg, cyprus, and poland. the reasons for this are the lack of natural resources in some of the states and the predominance of oil in energy consumption. poland has its own coal reserves, but the use of this resource inevitably leads to an increase in carbon dioxide emissions, which contradicts the regulations of the european commission. let’s look at some individual cases. 4.1. refusal to import energy resources: the italian experience in italy, there is a growing trend to switch to renewable sources, while germany and poland are failing to meet their goals. using italy as an example, we can trace how the country is successfully zholamanova, et al.: comparative analysis of strategies for innovative development of the fuel and energy complex: the experience of the eu countries international journal of energy economics and policy | vol 13 • issue 1 • 2023 131 overcoming dependence on fossil fuels, guided by the adopted eu programs. in 2000, italy’s energy system was based on imported energy resources. according to hafner and raimondi (2020), the share of the total demand for fossil fuels was 88%. by 2018, it had fallen to 74%. oil demand was 50%, and by 2018 it had dropped to 16%. the volume of alternative energy sources has increased from 7% to 20%. consequently, greenhouse gas emissions have decreased, and energy efficiency has increased markedly. italy plans to eliminate the use of coal for energy production by 2025 and to achieve zero carbon emissions by 2050. in 2021, the italian government approved the italian long-term strategy to reduce harmful emissions. this process involves the ministry of environment, land and sea, the ministry of infrastructure and transport, the ministry of economic development, the ministry of agricultural, food, and forestry policies, as well as numerous research centers. the emission reductions in each sector follow a certain scenario. industrial production must switch to renewable fuels and use carbon capture and storage technology. the transportation sector must eliminate harmful emissions by introducing electrification and green fuels. agriculture commits to reducing waste by offsetting emissions and applying the principles of a circular economy. this also includes carbon sequestration (gaeta et al., 2021). the example of italy shows that the task of protecting the environment while improving energy efficiency can only be solved comprehensively. 4.2. radical energy reforms: the german experience in the case of germany, there is a mismatch between goals and reality in some sectors. in 1990, there was large-scale consumption of fossil fuels, which was associated with a lack of interest in switching to renewables. in addition, a large share of the population was employed in conventional energy. nuclear power plants were legally exempt from liability insurance. soon a radical change toward alternative energy began. the diversification of the “green” energy industry began, and a decision was made to phase out nuclear power. in 1991, the german government passed the “feedin act”, which led to the formation of a “green tariff”. utilities, according to the new law, were obliged to buy electricity generated by alternative sources. this decision had a favorable effect on the development of “green” energy. the number of investments in this sector increased, which led to the expansion of the production of alternative sources of electricity. in 2000, the renewable energy act was introduced, providing financial support for producers of decentralized electricity. german citizens, in particular farmers and rural residents, supported this law. subsequently, a number of bills were passed providing for the development of alternative energy. the energy strategy “energiewende” was approved, aimed at environmental protection, development of a “green” economy and alternative energy technologies, combating monopolization of the energy sector, overcoming dependence on imported natural resources, and preventing risks in the operation of nuclear power plants. a tax on carbon dioxide producers was introduced. this strategy was supposed to improve the environmental situation in the fields of heat and electricity supply, as well as in the transport system. for example, the attempt to replace non-renewable resources in the automobile industry with renewable ones ended in failure. the success of alternative sources of heating has also been unsuccessful. the large-scale introduction of green energy sources has not resulted in significant emission reductions. since the nuclear power industry in germany has been decommissioned, coal-fired thermal power plants have made up for the lack of electricity. this is not the whole list of obstacles faced by the german government. nevertheless, germany is among the leaders in the level of investment in alternative energy and the volume of solar, wind, and biogas installations. in addition, the state has one of the highest rates of electricity supply reliability (kunze and lehmann, 2019; rechsteiner, 2020). undoubtedly, germany has achieved the highest results in the production of electricity from alternative sources. nevertheless, the state is still dependent on imported natural resources, which directly hinders the development of other parts of the fuel and energy complex. in addition, the current energy policy has led to a high cost of electricity, which causes considerable dissatisfaction among the population. the price of electricity is expected to fall after 2023 because of the expiration of the contracts signed between the government and the producers of “green” electricity, which meant supplying energy from renewable sources at a fixed price. 4.3. obstacles to the transition to renewable energy sources: polish experience the polish government does not support the eu’s carbon-neutral policy because coal is the country’s dominant energy source, accounting for 80% of its consumption. in addition, the coal industry employs about 88,000 polish citizens on an interregional level (hafner and raimondi, 2020). going back to the question of employment, abandoning coal would lead to job losses, but this judgment is controversial. ortega-izquierdo and río (2020) point out that between 2008 and 2016, the spread of alternative energy in the eu created more than 2.5 million jobs. by smoothly switching to alternative sources, poland can offset the number of positions in the coal sector by creating new ones related to renewable energy. in order to remove public opposition and dissatisfaction with energy substitution, germany intends to pay compensation in those regions where there is the most pronounced dependence on coal production. this factor should be taken into account, since in kazakhstan the coal industry is one of the key industries, and the use of coal in thermal power plants is 80% (drozd et al., 2020). 4.4. leadership in maritime technological innovation: the finnish experience finland’s fuel and energy complex is rich in natural resources, but the government is striving to expand the use of environmental resources. there are some obstacles to this task. finland’s energy policy is currently focused on short-term increases in cost-effective renewable energy production. for the long term, a number of issues about subsidizing projects need to be resolved. for example, there is currently a debate about further subsidies for wind power. to support alternative energy, finland has also obliged carbon dioxide zholamanova, et al.: comparative analysis of strategies for innovative development of the fuel and energy complex: the experience of the eu countries international journal of energy economics and policy | vol 13 • issue 1 • 2023132 producers to pay taxes, but unlike germany, this system has not been as effective (paukku, 2021). finland has not yet developed the alternative energy generation sector, but the country is leading the way in maritime technological innovation. recently, the most significant finnish project is intens, which covers the digitalization and decarbonization of water transport. the project name implies integrated energy solutions for smart and green shipping. intens technologies enable physics-based machine learning to predict onboard energy consumption, which directly improves ship energy efficiency. new design methods in the field of shipbuilding are proposed. the use of artificial intelligence helps to optimize the shipbuilding process at an early stage, allowing to anticipate and prevent possible costs (zou and hänninen, 2021). the use of smart technology is not the only way to improve the environmental and economic performance of waterborne transportation. financial monitoring of companies in the port sector is necessary, which will help preserve the environment, prevent the outflow of money into the shadow economy, and prevent the use of transport for smuggling. there is a high probability of oil spills, uncontrolled emissions of harmful substances, accidents during transportation of dangerous cargoes, etc. application of a risk-oriented approach may improve the financial stability of ports. it is necessary to impose fines in case of outflow of resources into the shadow economy sector, non-compliance with environmental protection rules, smuggling. financial monitoring is an effective element of the management system to identify and prevent possible problems (oneshko and ilchenko, 2017). taking into account the above information, kazakhstan can improve the efficiency of water transport, in particular on the caspian sea. 4.5. unstable development of solar energy: the spanish experience spain has enormous photovoltaic potential among eu countries due to its favorable climate conditions. in the 2000s, spain became the european leader in the number of solar panel installations, which contributed to the creation of new jobs in the renewable energy sector. this progress was greatly influenced by the regulatory framework and government subsidies during a period of economic growth. since 2007, spain has pursued an aggressive policy to stimulate solar energy production. at that time, the cost of photovoltaic systems was low, and investment flows from the construction sector shifted to the photovoltaic solar energy sector. credit opportunities were made available for the development of the solar energy sector, and the banking system provided support. this led to a disproportionate increase in photovoltaic power generation, which grew by 300% per year. the situation changed due to the economic crisis in spain in 20082012, which led to the reduction of feed-in tariffs for solar energy production and, eventually, to the stagnation of the photovoltaic market. since 2009, the number of spanish energy companies in the sector has declined due to the impact of government policies. in 2012, with the introduction of regulatory reforms to address tariff deficits and the instability of the electricity system, this process accelerated. after carrying out numerous reforms to improve the energy industry, a new period of photovoltaic upswing began in 2016. by 2018, the number of energy companies was close to the number that existed in 2007. however, the development of solar energy has not significantly accelerated due to decreased government support and worsening economic conditions in the country. given spain’s current energy policy, the elimination of the feed-in tariff system for the alternative energy market could also hinder progress in reducing harmful emissions. consequently, spain risks falling behind other eu member states in the process of achieving carbon neutrality, as approved by the green economy strategy at the supranational level (blanco-díez et al., 2020; fernández-gonzález et al., 2021). 4.6. prospects for the introduction of alternative energy in kazakhstan kazakhstan has great potential for the introduction of renewable energy sources, including hydropower, wind, solar, and biomass. however, to date, except for the partial application of hydropower, other options have not been properly developed. the presence of huge reserves of natural resources is one of the main reasons for the low rate of development of alternative energy. kazakhstan, unlike most european countries, does not depend on imported energy resources and is able to maintain the energy sector from its own reserves. the second reason is the low interest of the government in the development of green energy, which leads to low involvement in the expansion of renewable technologies and the lack of adequate funding. the southeastern region successfully combines simultaneous power generation from hydroelectric power plants and wind farms. these power plants complement each other in terms of seasonal electricity generation, i.e., primarily from wind farms during colder periods of the year and from hydroelectric power plants during warmer periods. the use of solar panels in the southern regions can also have a favorable effect on increasing the share of electricity production and improve the environmental background. nevertheless, kazakhstan lags behind the eu in this industry due to the lack of solar panel production (kurmanov, 2019). using the experience of european countries, kazakhstan can accelerate the development of alternative energy. following the example of germany and italy, it is necessary to gradually reform the energy sector. partnership with scientific institutions of eu countries will contribute to the further development of “green” technologies. the introduction of renewable energy sources will improve not only the environment but also the economy of the state. 5. discussion and conclusion the widespread distribution of alternative energy sources would undoubtedly improve the environmental situation in the world. nevertheless, such a strategy is a real challenge for countries whose economic potential is small. in addition, a green economy policy is inherently linked to the redistribution of jobs. european countries, whose fuel and energy complex is inherently linked to high levels of coal consumption, are not making radical changes in energy policy. this can lead to large-scale job losses. the abrupt transition to renewable energy sources is unprofitable for some countries. for this reason, poland has no intention of zholamanova, et al.: comparative analysis of strategies for innovative development of the fuel and energy complex: the experience of the eu countries international journal of energy economics and policy | vol 13 • issue 1 • 2023 133 abandoning the coal industry in the near future. nevertheless, there is a solution to this issue. the number of jobs can be compensated by new vacancies in the alternative energy sector. at the same time, the country may not have much potential for the expansion of solar and wind energy due to its geographical location. blanco-díez et al. (2020) point to a high rate of job growth in spain’s bioenergy sector, which exceeds that of solar and wind energy. it is clear that the process of re-training conventional energy professionals in the case of a complete transition to renewable sources requires significant effort and funding for the training program. to achieve high results, attention must be paid to training workers with the required qualifications. britchenko and saienko (2017) note that the process of training a specialist has a serious philosophical basis and requires the study of the level of mental and physical qualities of the person. considering the unstable energy market in spain and the sharp fluctuations of functioning companies, it should be concluded that it is necessary to maintain the performance of the enterprise. khan et al. (2021) consider this issue from the side of maintaining the reputation of the company and the relationship with the consumer. for the successful development of renewable energy in kazakhstan, first of all, it is necessary to support the government at the financial and legislative level. the german energy system has achieved tremendous development in the production of electricity from alternative sources and can rightfully be considered a benchmark. drawing a parallel between spain and germany, we can consider an important factor that has led to the stalling of the development of the renewable energy sector. the reduction of subsidies and feed-in tariffs in spain led to a decline in the generation of energy from alternative sources, while the strong support of germany contributed to the rapid development of all sectors of “green” energy. unlike germany, kazakhstan has its own natural resources and does not need to import oil, natural gas, coal, and other natural resources. the unpopularity of renewable sources is largely due to the fact that it is economically unprofitable for the republic to reform its energy system. however, ignoring environmental protection will inevitably lead to an increase in population morbidity. samoilenko (2018) believes that the adopted law of the republic of kazakhstan “on the support of renewable energy sources” should be improved and directed to the regulation of alternative energy, and renewable energy sources should be introduced into the economic turnover. the use of alternative forms of energy is not limited to the use of solar, wind, and tidal energy. it is possible to effectively use biofuels in the transport and communication complex of the country. the paper mentioned that the efficiency of water transport can be achieved by using high-tech technologies with the introduction of artificial intelligence, but this is not the only option. there are solar-powered ships around the world. the power produced by solar batteries cannot supply the energy system of big ships. that’s why only small ships can use this technology. however, the use of biofuel can solve this problem. sorokina and cherkaev (2021) analyze the prospects of biofuel development in kazakhstan and compare methods of production of biodiesel, bioethanol, and biogas. the authors determined that the use of this resource can replace the traditional fuel to run the engines of ships and road transport. the fuel and energy complex of any country includes the coal, peat, oil and gas, nuclear, and electric power industries. this paper does not cover the entire list. the greatest focus is on electricity production, partially affecting the oil, gas, coal, and nuclear industries of european nations. the eu’s new energy policy aims to completely reduce carbon dioxide emissions and overcome dependence on energy imports. most countries have been successful in meeting their targets, but some states have to work harder to achieve carbon neutrality while stabilizing their economies. nevertheless, eu policies are at the forefront of environmental conservation. following the eu example, kazakhstan can successfully implement a new energy policy. studying the history of eu energy policy development will help prevent earlier mistakes made in other countries. the example of spain shows that it is extremely important to control the level of financial support for alternative energy projects, preventing overfunding or underfunding. drawing on germany’s experience, it is necessary to control electricity prices. the transition to alternative energy can be a serious challenge for kazakhstan’s economy. nevertheless, it is a necessary step to improve the environmental situation in the country and around the world. renewable energy sources are inherently linked to improving the quality of life and safety of the population, and with the right strategy can increase the economy of the state. references angheluta, s., burlacu, s., diaconu, a., curea, c.s. (2019), the energy from renewable sources in the european union: achieving the goals. european journal of sustainable development, 8(5), 57-65. blanco, m., ferasso, m., bares, l. (2021), evaluation of the effects on regional production and employment in spain of the renewable energy plan 2011-2020. sustainability, 13(6), 3587. blanco-díez, p., díez-mediavilla, m., alonso-tristán, c. (2020), review of the legislative framework for the remuneration of photovoltaic production in spain: a case study. sustainability, 12(3), 1214. britchenko, i., saienko, v. (2017), the perception movement economy of ukraine to business. economic studies journal, 26(4), 163-181. drozd, v., spanova, b., te, a., kogay, g., ten, t. (2019), trends in the development of heat and power resources of kazakhstan. engineering and construction bulletin of the caspian sea, 2(28), 56-61. fernández-gonzález, r., arce, e., garza-gil, d. (2021), how political decisions affect the economy of a sector: the example of photovoltaic energy in spain. energy reports, 7, 2940-2949. gaeta, m., businge, c.n., gelmini, a. (2021), achieving net zero emissions in italy by 2050: challenges and opportunities. energies, 15(1), 46. hafner, m., raimondi, p. (2020), priorities and challenges of the eu energy transition: from the european green package to the new green deal. russian journal of economics, 6(4), 374-389. hewitt, r.j., bradley, n., compagnucci, a.b., barlagne, c., ceglarz, a., cremades, r., mckeen, m., otto, i. m., slee, b. (2019), social innovation in community energy in europe: a review of the evidence. frontiers in energy research, 7(31), 1-27. khan, r., saienko, v., tolchieva, h. (2021), dependence of the company’s zholamanova, et al.: comparative analysis of strategies for innovative development of the fuel and energy complex: the experience of the eu countries international journal of energy economics and policy | vol 13 • issue 1 • 2023134 reputation and the quality of customer relations. economic studies journal, 2, 159-176. knodt, m. (2018), eu energy policy. in: heinelt, h., münch, s., editors. handbook of european policies. ch. 12. united kingdom: edward elgar publishing limited. kovacic, z., di felice, l.j. (2019), complexity, uncertainty, and ambiguity: implications for european union energy governance. energy research social science, 53, 159-169. kunze, c., lehmann, p. (2019), the myth of the dark side of the energiewende. the european dimension of germany’s energy transition, cham: springer international publishing, 255-263. kurmanov, z. (2019), energy development in kazakhstan based on the use of renewable energy sources. available from: https://old. kazatu.edu.kz/assets/i/science/sf15-energo-121.pdf [last accessed on 2022 sep 21]. lehotay, v. (2020), road to the european energy union. journal of agricultural and environmental law, 15(28), 260-288. nazarova, u., oteshova, a., niyazbaeva, a., mingazova, o., nusratullin, i. (2020), kazakhstan experience in implementing ecoinnovations. moscow economic journal, 3, 201-215. oneshko, s., ilchenko, s. (2017), financial monitoring of the port industry companies on the basis of risk-oriented approach. investment management and financial innovations, 14(1), 191-199. ortega-izquierdo, m., del río, p. (2020), an analysis of the socioeconomic and environmental benefits of wind energy deployment in europe. renewable energy, 160, 1067-1080. ossowska, l., janiszewska, d. (2020), toward sustainable energy consumption in the european union. energy policy journal, 23(1), 37-48. paukku, e. (2021), how could finland promote renewable-energy technology innovation and implementation? clean energy, 5(3), 447-463. pavlenko, i. (2020), assessment of the energy reliability of the countries of the european union. economics and management organization, 1(37), 28-38. polzin, f., sanders, m. (2020), how to finance the transition to low-carbon energy in europe? energy policy, 147, 111863. rechsteiner, r. (2020), german energy transition (energiewende) and what politicians can learn for environmental and climate policy. clean technologies and environmental policy, 23, 305-342. samoilenko, a. (2018), development of renewable energy in the republic of kazakhstan: a look at international experience. young scientist, 11, 238-241. sorokina, e., cherkaev, g. (2021), prospects for the production of biofuels in the republic of kazakhstan for the development of shipping. vol. 01. saint petersburg, russia: proceedings of the krylov state research center. p266-268. sukhotina, a., tomashevskaya, e. (2019), modern trends in the development of the fuel and energy complex of the european union and its impact on the world market of energy resources. russian economic bulletin, 2(4), 79-84. tagliapietra, s., zachmann, g., edenhofer, o., glachant, j.m., linares, p., loeschel, a. (2019), the european union energy transition: key priorities for the next five years. energy policy, 132, 950-954. tulchynska, s., popelo, o., marhasova, v., nusinova, o., zhygalkevych, z. (2021), monitoring of the ecological condition of regional economic systems in the context of sustainable development. journal of environmental management and tourism, 12(5), 1220-1228. wieczorek-kosmala, m., marquardt, d., kurpanik, j. (2021), drivers of sustainable performance in european energy sector. energies, 14(21), 7055. zhunusova, g., omarbakiev, l. (2018), the modern structure of energy resources and the possibility of developing alternative sources in kazakhstan. current research in the modern world, 9(1), 130-137. zou, g., hänninen, s. (2021), integrated energy solutions to smart and green shipping: 2021 edition. available from: https://cris.vtt.fi/ en/publications/integrated-energy-solutions-to-smart-and-greenshipping-2021-edit [last accessed on 2022 sep 21]. tx_1~at/tx_2~at international journal of energy economics and policy | vol 7 • issue 6 • 2017 39 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(6), 39-47. financial development, economic growth and renewable energy consumption in russia: a vector error correction approach dmitry burakov1*, max freidin2 1department of financial markets & banks, financial university under the government of the russian federation, moscow, russia. 2department of marketing, belarusian state agricultural academy, mogilev region, gorki, belarus. *email: dbur89@yandex.ru abstract this article aims to explore the causal relationship between financial development, economic growth and renewable energy consumption on the example of russia. using data from 1990 to 2014, we build the vector error correction model to determine the nature of short-term and long-term relationships between the variables. to determine causality and its direction, we use the granger causality test vec in domain. the results of the vec model show that the system of variables corrects its previous period disequilibrium at a speed 22,98% in one year. based on the results of the wald test, we find no statistically significant causality running from renewable energy consumption to either economic growth or financial development. the results of granger causality test show that there is bi-directional causality between economic growth and financial development in russia, while renewable energy consumption does not granger cause economic growth or financial development. although economic growth does granger cause changes in renewable energy consumption. keywords: renewable energy, economic growth, financial development, vector error correction model jel classifications: d53, o40, q42, q43 1. introduction energy is one of the main sources of economic growth of the national economy. energy consumption is an integral part of the production process of most modern consumer goods. however, the current industrial structure of most countries is based on the use of non-renewable energy sources. in condition of a growing demand for energy and their limitations, the question of their effective utilization, on the one hand, and the shift to wider use of renewable energy sources on the other side, takes its place. for example, according to the eia, the modern supply is unstable from an economic point of view, not to mention the social side and the environmental one. according to forecasts (apergis and danuletiu, 2014), primary energy demand will continue to grow until 2030 at a rate of 1.5% per year. while fossil fuels will be the main source of energy, the active use of fossil fuels with the increasing growth of consumption will lead to an increase in co2 emissions in several times that will only exacerbate problems of environmental and energy security. this, in turn, will lead to a revision of the strategy of energy development and could lead to a paradigm shift from the use of non-renewable energy to renewable energy for not polluting the environment. renewable energy sources are those sources that generate energy, such as wind, geothermal, solar activity, biomass, etc. unlike the modern energy sources, generating environmental pollution, clean energy sources are secure and inexhaustible. in this lies the reason for the steadily growing demand for them. for example, the growing demand for clean sources of energy in the world is sustained around 8% per year. especially, this trend is observed in developed and rapidly developing countries, such as usa, eu and china (iea, 2009). as noted above, energy resources are one of the main factors of economic growth. to date, economic growth in most countries of the world is unstable because of dependence on fossil sources of energy (oil, gas, coal). the instability is called to life by the fact that in the case of the imported energy sources, significant dependence appears on changes of prices on world markets, a negative shock in which may lead to a significant deterioration in the export position burakov and freidin: financial development, economic growth and renewable energy consumption in russia: a vector error correction approach international journal of energy economics and policy | vol 7 • issue 6 • 201740 and the position on domestic markets and households’ welfare. thus, increased active use of renewable energy contributes not only to ensuring environmental, but to energy security and independence from the world market. this proves the importance of learning about clean energy sources as one of the key areas to strengthen and ensure stable economic growth of the national economy. a logical continuation of the previous theses, then, is the assumption about the existence of the relationship between energy consumption, financial development and economic growth of the national economy. this issue attracts quite a lot of attention from researchers. the rationale behind this connection stems from the fact that energy consumption is one of the key determinants of economic performance in terms of impact on the volume and cost of production. the growth of the national economies of developing countries, accompanied by population growth leads to increased energy consumption. an example is the rapidly growing countries of asia (india, china). thus, the increase in economic growth leads to financial development and ceteris paribus can lead to reduction in energy consumption on the one hand and the shift to safer renewable sources of energy, on the other. the reason for this is global competition and the sensitivity of world markets to price shocks in the medium term. the decrease in capital intensity of production, the production of environmentally friendly products leads to an increase in demand for national products. considering the need to ensure stable and accelerated development of the national economy of russia, the desire to “get off the oil needle” and increase the share of national product of russia on the world market, the active development of alternative, clean energy sources, their use in the national economy should be a priority to ensure not only energy security, but also a key element of a growth strategy. for these purposes, the existing economic growth, contributing to the development of the financial sector should lead to the active use of financial resources for the implementation of clean, renewable energy sources, or through the lending and investment in this sector, either through government programs support or venture funding. therefore, being aware of the importance of energy security, we set ourselves a task to analyze the relationship between the use of clean energy sources, economic growth and financial development for the presence of causal relationships, and testing the hypothesis of active support by the financial sector of “green” energy projects. this study aims to determine the presence of a causal relationship between the share of renewable energy in the production of the national economy, economic growth and financial development in the long term, as well as to determine the presence and the vector of the causal relationships between the above variables in the short term. the study is conducted on the example of russia. the paper is organized as follows. section 2 presents an overview of the major and most influential studies on the relationship between renewable energy, economic growth and financial development, as well as the formulation of the hypothesis and its novelty. section 3 presents an overview and description of used research methods. section 4 presents the description and explanation of the obtained results of the study. section 5 presents the final provisions and suggestions for application of findings. 2. literature review the literature on the issue of the relationship between energy consumption, economic growth and financial development is a diverse array of research, both of national and international scale. in the famous article on “economic growth-energy” nexus,, ozturk (2010) describes the current state of the directions of studies on the relationship between renewable energy consumption and economic growth, in terms of causal relationships as a set of different hypotheses. according to the “growth hypothesis” there is a direct causal relationship running from renewable energy to economic growth. then, conservative policy on the use of renewable resources can lead to negative effect on economic growth. according to the “conservation hypothesis”, the causal relationship is reversed: allows for the existence of unidirectional causality running from economic growth to renewable energy consumption. in this case, the policy of prohibition of renewable energy consumption has no significant effect on economic growth. according to the “feedback effect” hypothesis there exists a bidirectional causality between energy consumption and economic growth. this allows for the possibility of the influence of each variable on the other through various channels. according to the “neutrality hypothesis” causality between economic growth and renewable energy consumption does not exist, which makes the protection policy of renewable energy is insignificant (ozturk, 2010). conventionally, all the existing studies can be divided between the above stated hypotheses. depending on the empirical sample, different studies present different results. for example, some researchers using cross-country and within-country (regional) samples, find bi-directional causality between economic growth and renewable energy consumption, which confirms the hypothesis of a “feedback effect” (apergis and payne, 2010; fang, 2011; rafindadi and ozturk, 2017; tugcu, 2013). other studies show that there is a unidirectional causality from energy consumption to economic growth, allowing the authors to conclude that the impact of energy consumption on economic growth exist, supporting the growth hypothesis (fotourehchi, 2017, bhattacharya et al., 2016; esso, 2010; fang, 2011; leitão, 2014; payne, 2010). the study by ocal and aslan (2013) on the example of turkey gives the arguments in favor of the conservation hypothesis, describing the dependence of renewable energy from economic growth. also worthy of noting is the number of studies in which were received ambivalent, mixed results in determining the direction of causality between the different proxies to measure economic growth and energy consumption. these include the papers by bowden and payne (2010), jebli et al. (2016), pao and fu (2013b), tugcu et al. (2012) yildirim et al. (2012). among the works that speak in favor of the hypothesis of absence of causality between the studied variables one should highlight the papers by menegaki (2011) and payne (2010), giver different proxies used to measure renewable energy consumption. speaking on the relationship between renewable energy consumption and consumption in general and financial development, we conditionally can distinguish several directions of research results. some studies confirm the existence of burakov and freidin: financial development, economic growth and renewable energy consumption in russia: a vector error correction approach international journal of energy economics and policy | vol 7 • issue 6 • 2017 41 causality running from energy consumption to financial market development. for example, al-mulali and sab (2012) investigated the effect of energy consumption on economic growth and financial markets development on the example of the 19 countries for the period 1980 to 2008. the results showed that energy consumption is statistically significant and affects the development of the financial sector and economic performance. islam et al. (2013), based on the use of vec models, tested the relationship between the growth of financial market, economic growth, population and energy consumption on the example of malaysia. as a result of the study, the authors came to the conclusion about the existence of a causal relationship in the long run. energy consumption affects financial development and economic growth also in the short term. shahbaz et al. (2013a) studied the relationship between energy consumption and economic growth, including such variables as financial development and trade on the example of china during 1971-2011 using ardl model. the results of the study showed that the consumption, financial market development and trade are positively related to economic growth. the study on the example of indonesia by shahbaz et al. (2013b) concluded that the growth of national gdp and consumption leads to higher co2 emissions, while financial development and liberalization suppress them. in other words, they found evidence that financial development facilitates the spread of renewable clean energy. çoban and topcu (2013) investigated the issue of causality on the example of the eurozone countries for the period 1990-2011. the results of the study showed that financial development has significant impact on energy consumption among the old eu members. chang (2015) on the sample of 53 countries for the period 1999-2008 investigated the nonlinear impact of financial markets on consumption and income. income growth leads to increased energy consumption in the case of developing countries. in developed countries, the increase is of short-term nature. in low-income countries, the energy consumption grows with the development of financial markets (in the case of bank loans). if as a proxy are used data on indices of the securities market, enrgy consumption decreases with the development of financial markets in developed countries, but growing in developed countries. ozturk and acaravci (2013) investigated long-term relation between energy, economic growth, openness and financial sector development on the example of turkey for the 1960-2007. the results showed the presence of a long-term relationship between the variables. the development of the financial sector has no statistically significant influence on the emission of carbon in the long term. ali et al. (2015) investigated the relationship between financial development and energy consumption on the example of nigeria, using ardl approach. the results showed that the variables sampled are in cointegration, and therefore have a long-term relationship. in the short term, financial development and economic growth have a negative impact on energy consumption. in the long run, financial development has a little negative impact on energy consumption. yazdi and shakouri (2017) investigate the relationship between economic growth, renewable energy consumption, energy consumption, financial development, and trade openness over the period 1979-2014 in case of iran, using ardl approach and granger causality test. results of the study show that renewable energy consumption has a negative impact on economic growth in the short run and the long run. also the authors find unidirectional causality from renewable energy consumption to economic growth. zeren and koc (2014) study the relationship between energy consumption and financial development on example of 7 developing countries for period 1971-2010. results show that financial development and energy consumption may affect each other in positive and negative way. tugcu et al. (2012) investigate the long-run and causal relationships between renewable and non-renewable energy consumption and economic growth using ardl approach for g7 countries for 1980-2009. results show bidirectional causality for all countries in case of classical production function, mixed results are found for each country when the production function is augmented. given the above, we can note the absence of detail studies on the relationship between renewable energy consumption, financial development and economic growth on the example of russia, which determines the novelty of the research. among the studies on the relationship between the energy sector and the financial sector in russia can be mentioned the study by burakov (2015), where relationship between energy efficiency of the russian economy and bank lending of green projects is studied. 3. materials and methods 3.1. research methods to test the hypothesis about relationship between renewable energy consumption, economic growth and financial development, we use econometric techniques to analyze time series. the algorithm of the ongoing study is determined by several key stages. first and foremost, one should test sampled variables on stationarity or order of cointegration, since the time series must have the same order, as can be seen from equation (1). secondly, it is necessary to determine presence/absence of correlation in long term between the variables in the equation. to check this assumption, we use a johansen cointegration test. in a case of a long-term relationship on the one hand and condition of stationarity of sampled time series in the first order i(1) on the other, it is possible to use vec model. in case of confirmation of presence of cointegration between the variables of the sample, residuals of the equilibrium regression can be used to estimate error correction model. also based on vec model it is possible to identify short-term relationships between sampled variables. for this purpose, we use the wald test. to determine causal linkages between variables we use granger causality test. the final stage of constructing a model is to conduct diagnostic tests to determine validity of the model. these include testing for heteroscedasticity, serial correlation, normality and stability of the model. 3.1.1. unit root test for the analysis of long-term relationships between the variables, johansen and juselius (1990) admit that this form of testing is only possible after fulfilling the requirements of stationarity of the time series. in other words, if two series are co-integrated in order d (i.e., i (d)) then each series has to be differenced d times to restore stationarity. for d=0, each series would be stationary in levels, while for d=1, first differencing is needed to obtain stationarity. a series is said to be non-stationary if it has non-constant mean, burakov and freidin: financial development, economic growth and renewable energy consumption in russia: a vector error correction approach international journal of energy economics and policy | vol 7 • issue 6 • 201742 variance, and auto-covariance over time (johansen and juselius, 1990). it is important to cover non-stationary variables into stationary process. otherwise, they do not drift toward a long-term equilibrium. there are two approaches to test the stationarity: augmented dickey and fuller (adf) test (1979) and the phillipsperron (p-p) test (1988). here, test is referred to as unit-root tests as they test for the presence of unit roots in the series. the use of these tests allows to eliminate serial correlation between the variables by adding the lagged changes in the residuals of regression. the equation for adf test is presented below: 1 2 1 3 1t t t ty t ay y− −∆ = + + + ∆ +∑β β δ ε (1) where εt is an error term, β1 is a drift term and β2 is the time trend and ∆ is the differencing operator. in adf test, it tests whether a=0, therefore the null and alternative hypothesis of unit root tests can be written as follows: h0: a = 0 (yt is non-stationary or there is a unit root). h1: a < 0 (yt is stationary or there is no unit root). the null hypothesis can be rejected if the calculated t value (adf statistics) lies to the left of the relevant critical value. the alternate hypothesis is that a < 0. this means that the variable to be estimated is stationary. conversely, we cannot reject the null hypothesis if null hypothesis is that a = 0, and this means that the variables are non-stationary time series and have unit roots in level. however, normally after taking first differences, the variable will be stationary (johansen and juselius, 1990). on the other hand, the specification of p-p test is the same as adf test, except that the p-p test uses nonparametric statistical method to take care of the serial correlation in the error terms without adding lagged differences (gujarati, 2003). in this research, we use both adf and p-p test to examine the stationarity of the sampled time series. 3.1.2. johansen co-integration test to test for presence of cointegration we apply the johansen test using non-stationary time series (values in levels). if between variables does exist a cointegration, the first-best solution would be using vecm model. an optimal number of lags according to akaike information criterion for providing johansen test is determined in var space. to conduct johansen test, we estimate a var model of the following type: 1 1 ... t t p t p t ty a y a y bx-= + + + + ε (2) in which each component of yt is non-reposeful series and it is integrated of order 1. xt is a fixed exogenous vector, indicating the constant term, trend term and other certain terms. εt is a disturbance vector of k dimension. we can rewrite this model as: 1 1 1 1 p t t i t t t i y y v y bx − − − = ∆ = + ∆ + + ε∑π (3) where, , 1 1 p p i i j i j i a i a = = + = − ∆ = −∑ ∑π (4) if the coefficient matrix π has reduced rank r < k , then there exist k × r matrices α and β each with rank r such that π = αβ′ and β′yt is i(0). r is the number of cointegrating relations (the cointegrating rank) and each column of β is the cointegrating vector. the elements of α are known as the adjustment parameters in the vec model. johansen’s method is to estimate π matrix from an unrestricted var and to test whether we can reject the restrictions implied by the reduced rank of π (johansen, 1991). 3.1.3. vector error correction model granger (1988) suggested the application of vector error correction methodology (vecm) in case if the variables are cointegrated in order to find short-run causal relationships. vecm, therefore, enables to discriminate between long-run equilibrium and short-run dynamics. in this sense, we employ following vecms to estimate causal linkages among the variables: 0 1 2 3 1 1 1 1 1 k n m t i t i t i i i i t ln l a a lnl a lns a lny ect v − − − = = = − ∆ = + ∆ + ∆ + ∆ + + ∑ ∑ ∑ λ 0 1 2 3 1 1 1 1 2 k n m t i t i t i i i i t ln s lns lnl lny ect v − − − = = = − ∆ = + ∆ + ∆ + ∆ + + ∑ ∑ ∑β β β β φ 0 1 2 3 1 1 1 1 3 k n m t i t i t i i i i t ln y lny lnl lns ect v − − − = = = − ∆ = + ∆ + ∆ + ∆ + + ∑ ∑ ∑η η η η χ where, l – renewable energy consumption, s – economic growth, y – einancial development (granger, 1988). providing regression analysis of the sampled variables by modeling vecm allows us to determine the existence of substantial and statistically significant dependence not only on the values of other variables in the sample, but also dependence on previous values of the variable. however, vec model must meet the requirements of serial correlation‘s absence, homoscedasticity of the residuals and to meet the requirement of stability and normality. only in this case the results can be considered valid. 3.1.4. granger causality test the last stage to determine the relationship and its direction is the use of granger causality test. so, rejection of the null hypothesis of granger test (h0), according to which: b1 = b2 = ..... = bp = 0 (5) burakov and freidin: financial development, economic growth and renewable energy consumption in russia: a vector error correction approach international journal of energy economics and policy | vol 7 • issue 6 • 2017 43 in favor of the alternative hypothesis (h1) suggests that changes in renewable energy consumption granger cause changes in russian economic growth and financial development (granger, 1969). 3.2. materials and data processing we test the hypothesis on example of russian data for the period 1990 to 2014. the base period is one year. unfortunately, use of monthly and quarterly values of variables for the analysis is hindered due to availability of only yearly data for renewable energy consumption in russia. using vecm, we set ourselves a task to determine sensitivity of economic growth and financial development to shocks in renewable energy consumption as a share of total final energy consumption. data on financial development is obtained from the statistical database of the central bank of russia (www.cbr.ru). financial development is measured as a share of bank loans (broad money) to national gdp in constant 2000 us dollars. data on economic growth is obtained from the statistical database of federal service of state statistics (www.gks.ru). data on renewable energy consumption is derived from world bank database (www.data.worldbank.org). to conduct time-series analysis, all variables were transformed into logarithms. to study sensitivity and causal linkages between the variables in the sample in short-and long-run, we turn to regression analysis, which involves the construction of vec model of certain type based on stationary time series, testing the model for heteroscedasticity of the residuals, autocorrelation as well as stability and normality. based on the model, we study causal linkages between variables in the short run by applying granger causality test in vec domain. 4. results and discussion the first step in testing hypotheses is to test variables for the presence of unit root. for this purpose, we use standard tests adf and p-p test. results of unit root testing are presented in table 1. as can be seen from the test results of the variables for the presence of unit root in their differentiation to the first order, we can reject the null hypothesis of unit root in each of the variables. thus, the condition of stationarity at i(1) is performed, which gives us reason to test variables for cointegration. however, it is necessary to determine the optimal time lag. building a var model involves determining the optimal number of lags. in our case, the akaike information criterion equals 1. consequently, we built a model based on the use of time lag of 1 year to determine the relationship in the short run. the results of the diagnostic testing of var model for heteroscedasticity of residuals, autocorrelation, serial cross-correlation, and stability are presented in table 2. as can be seen from table 2, the model is stable, heteroscedasticity and serial correlation of residuals in the model are absent. the model is used to determine the level of sensitivity of control variables to shocks in renewable energy consumption in the short run and we use it to test for stable long-run relationship, applying johansen cointegration test. results of johansen co-integration test are presented in table 3. johansen test results show the presence of cointegration between a number of equations, which allows presuming the existence of a long-term relationship between them. starting from the results of the cointegration test, we can proceed to the construction of vecm model to reveal presence or absence of long-term and short-term relations between variables. the results of the model, showing the relationship between the variables are presented in table 4. as can be seen from the table, the value of error correction term c(1) is negative in sign and statistically significant. this suggests the existence of long-run relationship between the variables of the sample. in other words, we can assume that renewable energy consumption, economic growth and financial development have similar trends of movement in the long term. the c (1) shows speed of long run adjustment. in other words, this coefficient shows how fast the system of interrelated variables would be restored back to equilibrium in the long run or the disequilibrium would be corrected. given statistical significance at 5% level (p-value being less than 5%) and negative meaning, the system of variables corrects its previous period disequilibrium at a speed of 22,98% in one year (given optimal lag meaning of one year for ecm). it implies that the model identifies the sizeable speed of adjustment by 22,98% of disequilibrium correction in 1 year for reaching long run equilibrium steady state position. high speed of adjustment of relations between variables towards equilibrium is understandable. the reason for the existence of the relationship between the variables of the sample, and, namely, renewable energy consumption, economic growth and financial development is the internal processes of the relationship. in particular, economic growth leads to increased demand for credit resources, which leads to increased financial development of the national economy. in this case, we can assume that a causal relationship is bi-directional. on the other hand, economic growth leads to increased energy consumption overall, however, this in no way suggests that economic growth leads to increased use of renewable energy sources. a possible reason for long-term relationship between economic growth in the case of russia and renewable energy may be tougher competition on world markets and the need to reduce the cost of production of finished goods. in case of financial development, the question of a causal relationship with renewable energy can be of different nature. table 1: results of individual unit root test variables adf pp statistic p** statistic p** levels intercept 5.39865 0.4521 6.70331 0.5138 intercept and trend 1.74693 0.8160 1.33419 0.8021 first-difference intercept 32.7125 0.0000** 39.2509 0.0000** intercept and trend 22.6734 0.0012** 34.1103 0.0000** **denotes statistical significance at the 5% level of significance burakov and freidin: financial development, economic growth and renewable energy consumption in russia: a vector error correction approach international journal of energy economics and policy | vol 7 • issue 6 • 201744 on the one hand, financial sector development can promote the implementation of green technologies in the energy sector. on the other hand, the development of alternative sources of energy can contribute to economic growth and, thereby, contribute to financial development. to identify short-term relationship between the variables we refer to the wald test results. this test allows to determine the interrelationship between variables in the short term. in other words, under the null hypothesis of this test, the response of error correction term to explanatory variables equals zero, i.e. the sensitivity of resulting variable to changes (shocks) in explaining are not observed. results of wald test for the model are presented in table 5. as can be seen from the results of the wald test in the short term there is no statistically significant relationship between changes in renewable energy consumption and economic growth in russia. based on the results of the wald test, we detect no statistically significant causality. a possible reason for absence of causality in the short term is a significant dependence of the russian economy from fossil energy sources, the dependency of russian economy on oil and gas resources, their relative prevalence in historically formed technological structure of the economy. it is important to note that the share of renewable energy in total final energy consumption in russia is not more than 4%, which allows to speak of insignificance of renewable energy sources as a factor of influence on economic growth. feedback from economic growth is also unlikely due to presence of the falling trend of renewable energy consumption in russia over the investigated 25 years. the second result also shows absence of causality running from financial development to renewable energy consumption. the absence of causality between financial development and renewable energy allows us to speak about the absence of significant incentives in the financial market of russia to massive investment in green energy. this fact probably can be explained by the fact that russia is an exporter of energy and most of the exports are energy resources. in this context, the lower costs of production through the transition to environmentally friendly sources of energy do not seem to be a pressing need. the last stage of analysis are the test results for causality in the granger causality in the vec environment. the results of granger causality test are presented in table 6. table 2: results of unrestricted var model diagnostic testing type of test results lags lm-statistics p-value var residual serial correlation lm test 1 11.09531 0.0832** 2 32.25085 0.0031 3 47.19086 0.0002 stability condition test all roots lie within the circle var satisfies stability condition heteroscedasticity (white test) 0.1905* var residual cross correlation test no autocorrelation in the residuals **denotes acceptance of null hypothesis (ho: there is no serial correlation). *denotes acceptance of null hypothesis of homoscedasticity table 3: results of johansen co-integration test hypothesized no. of ce (s) eigenvalue trace statistics 0.05 critical value p* none * 0.786213 41.09763 31.70702 0.0146* at most 1 0.279981 12.10985 17.80567 0.1933 at most 2 0.096307 1.607931 4.220348 0.0979 trace statistics indicate 1 cointegrating equation at the 0.05 level. *denotes statistical significance at the 5% level of significance table 4: results of vector error correction model coefficient number coefficient meaning standard error t-statistic p c(1) −0.229864* 0.071376 −2.630810 0.0476* c(2) 0.024309 0.176172 0.210988 0.6234 c(3) 0.132439 0.209985 0.197604 0.5671 c(4) 0.158962 0.189317 0.180934 0.5295 c(5) 0.080645 0.136129 0.103931 0.5032 *denotes statistical significance table 5: wald test results for short run relationship test statistic value df probability test statistic value df probability t-statistic 0.0246 23 0.6198 t-statistic 0.485723 23 0.3419 f-statistic 1.0241 (1, 23) 0.6198 f-statistic 0.9825 (1, 23) 0.3419 chi-square 1.0241 1 0.2546 chi-square 0.9825 1 0.5136 null hypothesis: c (3)=0 (economic growth) null hypothesis: c (4)=0 (financial development) *denotes statistical significance and rejection of ho: no short-run relationship burakov and freidin: financial development, economic growth and renewable energy consumption in russia: a vector error correction approach international journal of energy economics and policy | vol 7 • issue 6 • 2017 45 the granger test results confirmed our assumptions. renewable energy sources do not have a statistically significant impact neither on economic growth nor on financial development. the same is true for feedback. economic growth does not granger cause of economic growth and financial development. the only identified bi-directional causality between economic growth and financial development. as we can note, the only uni-directional causality runs from economic growth to renewable energy consumption. the final stage of the analysis of the model is to determine the extent of its validity. for this, it is necessary to conduct some diagnostic tests, including tests for heteroscedasticity of the residuals, serial correlation, stability and normality of the model. the results of these tests are presented in table 6. as can be seen from table 7, the model is characterized by the fulfillment of all requirements homoscedasticity and absence of serial, auto and partial correlation. in figures 1-3 we present test results for normality and stability (cusum and cusum square test). as can be seen from the data of figures 1-3, the model meets the requirement of normality. 5. conclusion this article aims to explore the causal relationship between financial development, economic growth and renewable energy consumption on the example of russia. using data from 1990 to 2014, we build the vector error correcting model to determine the nature of short-term and long-term relationships between the variables. to determine causality and its direction, we use the granger causality test vec in domain. we test the hypothesis on example of russian data for the period 1990 to 2014. the base table 6: results of granger causality test excluded chi-square df p dependent variable: renewable energy consumption economic growth 3.193318 1 0.0218* financial development 0.249123 1 0.6177 all 0.210331 2 0.4438 dependent variable: economic growth renewable energy consumption 0.006066 1 0.8160 financial development 8.967673 1 0.0253* all 0.699304 2 0.1336 dependent variable: financial development renewable energy consumption 0.011233 1 0.9156 economic growth 9.768316 1 0.0107 all 4.851795 2 0.1370 *denotes statistical significance and rejection of ho: no granger causality table 7: results of diagnostic testing test type value probability characteristic p-value heteroscedasticity test: breusch-pagan-godfrey f-statistic 8.697 prob. f (6,17) 0.4421 obs*r2 6.421 prob. chi-square (6) 0.3217 scaled explained ss 4.378 prob. chi-square (6) 0.8798 heteroskedasticity test: arch f-statistic 2.483 prob. f (1,21) 0.9109 obs*r2 0.013 prob. chi-square (1) 0.8875 breusch-godfrey serial correlation lm test f-statistic 2.198 prob. f (1,18) 0.7812 obs*r2 0.167 prob. chi-square (1) 0.8067 autocorrelation/partial correlation lag ac pac q-statistics p 1 −0.012 −0.012 0.0045 0.917 2 0.157 0.157 0.2538 0.784 figure 1: results of normality test burakov and freidin: financial development, economic growth and renewable energy consumption in russia: a vector error correction approach international journal of energy economics and policy | vol 7 • issue 6 • 201746 period is one year. to conduct time-series analysis, all variables were transformed into logarithms. to study sensitivity and causal linkages between the variables in the sample in short-and long-run, we turn to regression analysis, which involves the construction of vec model of certain type based on stationary time series, testing the model for heteroscedasticity of the residuals, autocorrelation as well as stability and normality. based on the model, we study causal linkages between variables in the short run by applying granger causality test in vec domain. the results of the vec model show that the system of variables corrects its previous period disequilibrium at a speed 22,98% in one year. based on the results of the wald test, we find no statistically significant causality running from renewable energy consumption to either economic growth or financial development. the results of granger causality test show that there is bi-directional causality between economic growth and financial development in russia, while renewable power does not granger cause the economic growth or financial development. although economic growth does granger causes changes in renewable energy consumption. references ali, h., yusop, z., hook, l. (2015), financial development and energy consumption nexus in nigeria: an application of autoregressive distributed lag bound testing approach. international journal of energy economics and policy, 5(3), 816-821. al-mulali, u., sab, c.n.b. (2012), the impact of energy consumption and co2 emission on the economic and financial development in 19 selected countries. renewable and sustainable energy reviews, 16(7), 4365-4369. apergis, n., danuletiu, d. (2014), renewable energy and economic growth: evidence from the sign of panel long-run causality. international journal of energy economics and policy, 4(4), 578-587. apergis, n., payne, j.e. (2010), the renewable energy consumptiongrowth nexus in central america. applied energy, 88, 343-347. bhattacharya, m., paramati, s.r., ozturk, i., bhattacharya, s. (2016), the effect of renewable energy consumption on economic growth: evidence from top 38 countries. applied energy, 162, 733-741. bowden, n., payne, j.e. (2010), sectorial analysis of the causal relationship between renewable and non-renewable energy consumption and real output in the u.s., energy sources, part b: economics. planning and policy, 5, 400-408. burakov, d. (2015), energy efficiency in rent seeking economies: is credit capable of breaking the energy curse? international journal of energy economics and policy, 5(3), 677-685. chang, s.c. (2015), effects of financial developments and income on energy consumption. international review of economics and finance, 35, 28-44. çoban, s., topcu, m. (2013), the nexus between financial development and energy consumption in the eu: a dynamic panel data analysis. energy economics, 39, 81-88. dickey, d., fuller, w. (1979), distribution of the estimators for autoregressive time series with a unit root. journal of american statistical association, 74, 427-431. esso, j.l. (2010), the energy consumption-growth nexus on seven subsahara african countries. economic bulletin, 30, 1191-1209. fang, y. (2011), economic welfare impacts from renewable energy consumption: the china experience. renewable sustainable energy review, 15, 5120-5128. fotourehchi, z. (2017), renewable energy consumption and economic growth: a case study for developing countries. international journal of energy economics and policy, 7(2), 61-64. granger, c.w.j. (1969), investigating causal relations by econometric models and cross-spectral methods. econometrica, 37(3), 424-438. granger, c.w.j. (1988), some recent development in a concept of causality. journal of econometrics, 39, 199-211. gujarati, d. (2003), basic econometrics. 4th ed. london: mc graw-hill. iea. (2009), world energy outlook. paris, france: international energy agency. islam, f., shahbaz, m., ahmed, a.u., alam, m.m. (2013), financial development and energy consumption nexus in malaysia: a multivariate time series analysis. economic modelling, 30, 435-441. jebli, m.b., youssef, s.b., ozturk, i. (2016), testing environmental kuznets curve hypothesis: the role of renewable and non-renewable energy consumption and trade in oecd countries. ecological indicators, 60, 824-831. johansen, s. (1991), estimation and hypothesis testing of cointegration vectors in gaussian vector autoregressive models. econometrica, 59(6), 1551-1580. johansen, s., juselius, k. (1990), maximum like hood estimation and inference on co-integration with applications to the demand for money. oxford bulletin of economics and statistics, 52, 169-210. leitão, n.c. (2014), economic growth, carbon dioxide emissions, renewable energy and globalization. international journal of energy economics and policy, 4(3), 391-399. menegaki, a.n. (2011), growth and renewable energy in europe: a random effect model with evidence for neutrality hypothesis. energy economics, 33, 257-263. ocal, o., aslan, a. (2013), renewable energy consumption-economic growth nexus in turkey. renewable and sustainable energy figure 2: results of cusum test figure 3: results of cusum square test burakov and freidin: financial development, economic growth and renewable energy consumption in russia: a vector error correction approach international journal of energy economics and policy | vol 7 • issue 6 • 2017 47 reviews, 28, 494-499. ozturk, i. (2010), a literature survey on energy-growth nexus. energy policy, 38(1), 340-349. ozturk, i., acaravci, a. (2013), the long-run and causal analysis of energy, growth, openness and financial development on carbon emissions in turkey. energy economics, 36, 262-267. pao, h.t., fu, h.c. (2013b), the causal relationship between energy resources and economic growth in brazil. energy policy, 61, 793-801. payne, j.e. (2010), survey of the international evidence on the causal relationship between energy consumption and growth. journal of economic studies, 37, 53-95. phillips, p.c.b., perron, p. (1988), testing for unit root in time series regression. biometrica, 5, 335-346. rafindadi, a.a., ozturk, i. (2017), impacts of renewable energy consumption on the german economic growth: evidence from combined cointegration test. renewable and sustainable energy reviews, 75, 1130-1141. shahbaz, m., adnan, h.q., tiwari, a., leitao, n. (2013a), economic growth, energy consumption, financial development, international trade and co2 emissions in indonesia. renewable and sustainable energy reviews, 25, 109-121. shahbaz, m., khan, s., tahir, m.i. (2013b), the dynamic links between energy consumption, economic growth, financial development and trade in china: fresh evidence from multivariate framework analysis. energy economics, 40, 8-21. tugcu, c.c., ozturk, i., aslan, a. (2012), renewable and non-renewable energy consumption and economic growth relationship revisited: evidence from g7 countries. energy economics, 34(6), 1942-1950. tugcu, t. (2013), disaggregate energy consumption and total factor productivity: a cointegration and causality analysis for the turkish economy. international journal of energy economics and policy, 3, 307-314. yazdi, s., shakouri, b. (2017), renewable energy, nonrenewable energy consumption, and economic growth. energy sources, part b: economics, planning, and policy, in press. doi: 10.1080/15567249.2017.1316795. yildirim, e., sarac, s., aslan, a. (2012), energy consumption and economic growth in the usa: evidence from renewable energy. renewable and sustainable energy review, 16, 6770-6774. zeren, f., koc, m. (2013), the nexus between energy consumption and financial development with asymmetric causality test: new evidence from newly industrialized countries. international journal of energy economics and policy, 4(1), 83-91. international journal of energy economics and policy vol. 1, no. 2, 2011, pp. 47-58 issn: 2146-4553 www.econjournals.com total factor productivity and energy intensity in indian manufacturing: a cross-sectional study1 santosh kumar sahu department of humanities & social sciences, iit bombay mumbai, 400076, india. email: santoshkusahu@gmail.com krishnan narayanan department of humanities & social sciences, iit bombay mumbai, 400076, india. email: knn@iitb.ac.in abstract: in recent climate change negotiations and debates, energy use pattern, efficiency and productivity cannot be overlooked and hence it is necessary to focus on these ascepts for indian manufacturing industries. the objective of the paper is to estimate the transcendental logarithmic production function and analyse the relationship between energy intensity and total factor productivity (tfp). the estimation of tfp is based on four inputs model; labour, capital, material and energy. the findings suggest that labour and material inputs play major role as compared to the capital and energy input. further, estimates suggest that age of the firm, export intensity and disembodied technology import are positively related to the tfp, where as ownership, energy intensity, embodied technology import and r&d intensity are negatively related to tfp of the indian manufacturing industries. i̇n addition, energy efficient firms also found to have high levels of tfp. this implies the need for fostering energy efficiency at firm level in indian manufacturing. keywords: production function, total factor productivity, energy intensity, indian manufacturing industries jel classification: d24, q4, b3 1. introduction in the early phases of industrialization, the productivity in the indian manufacturing sector was limited by the government policies, e.g., the reservation of production (a large amount of production items for small-scale sector), high custom tariff distorting resource allocation and prohibiting indian industry’s ability to compete in the international market, shutting down industries in response to normal competitive market forces and various types of distortion created by the structure of domestic trade taxes and excise duties. however, the situation has gradually changed since 1991 due to the liberalization policies. over the years several measures were under taken by the government of india for boosting up the industrial productivity. it has been more than two decades since india initiated the industrial liberalization. one of the important objectives of policy reforms was to improve the efficiency of industrial sectors, as productivity and efficiency growth are the key factors for the development of any industry. in this respect, this study focuses on estimating total factor productivity using transcendental logarithmic specification of production function, and further estimates the determinants of productivity for the indian manufacturing industries using a cross 1 this paper was presented in the workshop on “economic reforms and the evolution of productivity in indian manufacturing” during 18-19th march, 2011 held at iit bombay.we gratefully achknowledge commets and suggestions given by prof. b. n. goldar and the anonymous referees of the journal. the errors that remain are our own. international journal of energy economics and policy, vol. 1, no. 2, 2011, pp.47-58 48 sectional data for the year 2008-09 collected from the center for monitoring indian economy (cmie). the rest of the paper is organized as follows: section-2 deals with the review of literature on productivity and substitution possibilities, section-3 focuses on the model specification and econometric estimation, section-4 deals with the empirical analysis of the estimation and section-5 concludes the finding of the study. 2. review of literature there are a wide range of studies focused on trends in total factor productivity growth in indian industries. in addition, a large number of studies also focus on the substitution possibility between energy, capital and labour for any industry context. the debate is based on the issue whether energy-capital, energy-labour are substitutes or complementary to each other. in the recent decades, several methodologies have been developed and applied to examine changes in productivity and technical change. a number of studies have estimated total factor productivity of indian economy using statistical indices within the standard growth accounting framework such as mongia and sathaye (1998, 1998a) and ahluwalia (1991). ahluwalia (1991) attempts to analyses the long-term trends in total productivity and partial productivity in the organized manufacturing sector in india for 1959-60 to 1985-86. the study also explored the role of factor input growth and the growth in value added. the analysis conducted at a detailed level of disaggregation for 63 constituent industry groups at the three-digit level and also for the four “use-based” sectors of manufacturing, i.e., intermediate goods, consumer non-durables, consumer durables and capital goods. for almost all of the 63 industries, capital intensity showed a strong and significant positive growth for fewer industries accounting for 64 percent of the valued added in manufacturing. there were a few industries which even experienced a decline in labour productivity. study by pradhan and barik (1999) attempts to open a solution channel by considering tfpg as a result of interaction between economies of scale and technical change. thus, it seeks to lay emphasis on proper management of scale economies and technical change for producing a desired tfpg. the study estimates tfpg using a translog cost function. the empirical findings of the exercise on data of aggregate manufacturing sector and eight selected industries of india indicate that both scale economies and technical change have registered a declining trend in recent years in the process of a declining tfpg. goldar (2000) found that the growth rate in employment in the organized manufacturing sector in india for 1990-91 to 1997-98 was 2.69 percent per annum which was well above the growth rate of 0.53 percent per annum achieved in the 1980s. he attributed two major reasons for this growth in employment: slowdown in growth of real wages in the 1990s and faster growth of small and medium-sized factories in organized manufacturing; which are more labour intensive as compared to large-sized factories. he also highlighted that the increase in employment in the organized manufacturing sector, which took place in the 1990s, was accounted for by private sector factories. nagaraj (2004) pointed out that faster employment generation in organized manufacturing was restricted mainly to the first half of the 1990s. as the boom went bust, there was a steep fall in employment in the second half of the 1990s. relative cost of labour did not seem to matter in employment decisions, as the wage-rental ratio declined secularly. according to him, about 1.1 million workers, or 15 percent of the workers in the organized manufacturing sector in the country, lost their jobs between 1995-96 and 2000-01. roy et al. (1999) report the analysis of productivity growth and input trends in six energy intensive sectors of the indian economy, using growth accounting framework and econometric methods. the econometric technique estimates rates and factor price biases of technological change using a translog production model with an explicit relationship defined for technological change. estimates of own-price responses indicate that raising energy prices would be an effective carbon abatement policy for india. at the same time, they found as with previous findings on the us economy, such policies in india could have negative long run effects on productivity in these sectors. inter-input substitution possibilities are relatively weak, so that such policies might have negative short and medium term effects on sectoral growth. the study provides information relevant for the analysis of costs and benefits of carbon abatement policies applied to india and thus contribute to the emerging body of modeling and analysis of global climate policy. total factor productivity and energy intensity in indian manufacturing: a cross-sectional study 49 assuming a translog specification of a four input (klem) production function, mongia et al. (2001) use growth accounting framework to decompose the growth of output into growth of inputs and a residual; representing the productivity growth. a major finding of the paper is overall productivity growth in the industries was quite low during 1973-1994. however, there were significant deferences in productivity growth across industries during this time. these differences can to a large extent be explained by the nature and timing of policy changes in individual sectors. using the growth accounting framework, they estimated the total productivity growth (tpg) for five energy intensive industries in india. the results show that total productivity growth in these industries during 19731994 was insignificant, although productivity growth varied across industries. it was significantly positive in the fertilizer industry, positive but low in aluminum and cement, and negative for iron & steel and paper industry. productivity growth was not uniform over time either. the partial productivity growth of capital and energy appear to be significant determinants of total productivity growth. these in turn were crucially affected by capacity utilization. the analysis of results for two sub-periods, 1973-1981 and 1981-1994, shows that changes in technologies and production conditions triggered or induced by policy reforms helped increase productivity growth significantly in the cement and fertilizer industry. the effect of policy changes was less significant in the case of aluminum industries because of lumpiness of investment and because of the inherent nature of the technology. however, the removal of market constraints and the addition of a modern plant did raise the growth rate in the second sub-period significantly. productivity growth was adversely affected in the case of iron and steel and paper industries, where due to lack of a clear long-term perspective, the positive effects of policy reforms were overwhelmed by institutional and market conditions, at least temporarily. according to the study, the policy reforms did not go far enough to significantly affect productivity growth in india's energy intensive manufacturing sectors. berndt et al. (1998) show that electricity is a weak substitute for both capital and labour in major alabama industries and regulatory constraints are binding due to inelastic electricity demand. mahmud (2000) finds very little substitution between energy and other inputs but weak substitution between electricity and gas in pakistan manufacturing. chang (1994) finds little difference between translog and constant elasticity production functions in taiwanese manufacturing and reports that energy and capital are substitutes. yi (2000) finds substitution varies across translog and leontief production functions in swedish manufacturing industries. ma et al. (2009) measures technological change, factor demand and inter-factor and inter-fuel substitutability measures for china. they use individual fuel price data and a two-stage approach to estimate total factor cost functions and fuel share equations. both inter-factor and inter-fuel substitution elasticities are calculated and the change in energy intensity is decomposed into its driving forces. their results suggest that energy is substitutable for capital regionally and for labour nationally. capital substitutes for energy more easily than labour does. energy intensity changes vary by region but the major drivers seem to be ‘‘budget effect’’ and the adoption of energy-intensive technologies, which might be embodied in high-level energy-using exports and sectors, capital investment and even old technique and equipment imports. they conclude that, after decomposing energy intensity, the budget effect and technological changes are the two major driving forces of the changes in energy intensity nationally. the variations in budget effect across regions are most likely related to the differences in regional economic growth and industrial structure. further, they find that the technological changes or innovative activities can be embodied in capital investment, equipped labour, export goods and even sectoral shifts. based on the above discussion, we can observe that most of the research focuses on estimating productivity using different functional form and/or analyzing the substitution possibility between different inputs. this paper is an attempt to estimate the total factor productivity (tfp) of indian manufacturing industries for 2008, with four inputs i.e. capital, labour, material and energy. in addition there is an attempt to find out factors that determine tfp other than the four inputs. specifically, this study also tries to look at the relationship between the energy intensity and tfp. 3. methodology and econometric specification tfpg measures the amount of increase in total output which is not accounted for the increase in total inputs and thus measures shift in output due to the shift in the production over time, holding all inputs constant [abramovitz (1956); denison (1962, 1967, 1985); hayami et al. (1979)]. this in turn international journal of energy economics and policy, vol. 1, no. 2, 2011, pp.47-58 50 implies an upward/downward shift in production/cost function, thereby leading to an increase in output. it has been widely acknowledged in the economic literature that industrial growth, no matters how impressive, will not be sustainable without improvement in productivity. tfpg can be measured by (i) growth accounting approach; (ii) econometric (parametric) approach (i.e. by estimating production function or cost function); (iii) non-parametric approach (i.e. through data envelopment analysis (dea)). one of the approaches to compute the production function is using the translog production function. this has both linear and quadratic terms with the ability of using more than two inputs. this function can be approximated by second order taylor series (christensen et al. 1971). this study uses the translog production function with four inputs (klem). industrial energy demand for energy is essentially a derived demand as the firm’s demand for energy is an input is derived from the demand for the firm’s output (berndt & wood, 1975). limited number of studies focuses on estimating production function for more than three inputs and taking energy as one of the important input for the production process of industries. this study is an attempt to estimate the production function using cross-section firm-level data for the indian manufacturing industries. further, there is an attempt to investigate the determinants of total factor productivity using firm specific variables other than labour, capital and material. the four-input translog production function can be written in terms of logarithms as follows:         2 0 2 2 2 1ln ln ln ln ln ln ln2 1ln ln ln ln ln ln ln ln ln2 1 1ln ln ln ln2 2 k l e m kk kl ke km ll le lm ee em mm lnq k l e m k k l k e k m l l e l m e e m m                               (0.1) where, q is the gross manufacturing output, k is stock of capital good, l is labour input, m is material input and e is energy input. α0 is the intercept or the constant term. βk, βl, βm, and βe are the first derivatives. βkk, βll, βmm, and βee are the cross second derivatives. net fixed capital has been taken as the measure of capital input, wages and salaries is taken as the labour input, cost of material is taken as the material input and cost of energy (from difference sources of energy consumed by the industries) is taken as the energy input in estimating equation (0.1). we follow a two-step estimation procedure. the first step involves estimating equation (0.1) using ols. once the ols estimates are computed ^ q is generated from the regression output of (0.1). where, ^ q measures the total factor productivity2 of the industries. then, the second step of the study involves estimating ols using ^ q as the dependent variable with the firm specific variables for indian manufacturing to find out the determinants of total factor productivity. the second equation takes the following functional form: ^ 1 2 3 4 5 6 7 8 1 9 2 10 3 11 4 12 5 13 6 14 7 15 8 16 9 17 10 18 11 19 12 20 13 21 14 22 15 23 16 24 17 25 18 i q age mne ei eti rdi expi deti id id id id id id id id id id id id id id id id id id u                                                      (0.2) where, age is age of the firm. age of the firm is computed as the difference of year of data used to the incorporated year of the firm. age is one of the major variables which may reflect the productivity of any firm. we assume older the age of the firm higher the productivity. mne is the ownership of the firm. ownership of any firm may affect of the performance of the firm, as foreign firms might have higher efficiency in production as compared to the domestic ones. this variable is 2 “technological progress or the growth of total factor productivity is estimated as a residual from the production function”[statscan 13-568: 50-51, cross cited from lipsey and carlaw (2001)] total factor productivity and energy intensity in indian manufacturing: a cross-sectional study 51 constructed as a dummy capturing 1 for the domestic firms and 0 for the foreign firms. energy intensity (ei) is one of the important factors contributing the production process. energy intensity of the firm is calculated as a ratio of cost of energy used (various sources of energy) to net sales of the firm. several previous studies have shown that importing firms are better performers or more productive than non-importing firms (sachs and warner, 1995). generally higher importing firms receive technological transfers as well as better inputs because of access and exposure to foreign sources, which can potentially help the importing firms to enhance their productivity and export performance. embodied technology intensity (eti); disembodied technology intensity (deti) and efficient use of energy (cost minimizing) can increase the productivity of any firm. we hypothesize that higher the productivity of firm, lesser the energy intensity. embodied technology intensity is calculated as a ratio of expenditure on import of capital goods to net sales of the firm and disembodied technology intensity is calculated as the ratio of royalty, and technical fees payments to net sales of the firm. export intensity (expi) of the firm is calculated as the ratio of export to net sales of the firm. the learning by exporting hypothesis, which claims that exporting to foreign market produces many positive learning effects by exposing the domestic firms to advanced technological innovations from international buyers and competitors and helps them to improve their productivity. this hypothesis for indian industries is confirmed by sharma & mishra (2011) where they found a positive and significant impact of productivity on export. hence the export intensity is assumed be a determinant of productivity. it is well established in the related literature that research and development (r&d) intensity is an important determinant of productivity and export performance of firms. in this concern the pioneering study of griliches (1979) has shown in the r&d capital stock model that this factor has a direct effect on the performance of firms. empirical evidences reported by lichtenberg and siegal (1989) and hall and mairesse (1995) also provides strong support to griliches’s view. to capture the r&d activities of firms, the study considers the ratio of r&d expenditure to the firm’s net sales. this variable is a measure of r&d intensity of firms and it is expected to have a positive impact on firms’ productivity. further to investigate the inter-industries difference of total factor productivity; we have defined 18 industries dummies (id1, id2…id18) from 19 sub-industries. data for the empirical investigation is collected from the cmie prowess data base for 2008. the sample size is 2541 for 19 sub-industries in indian manufacturing. 4. empirical results this section of the study presents the empirical estimates of indian manufacturing. table 1 presents the descriptive statistics of select variables of the sample of firms. the sample size for the analysis is 2541 firms drawn from indian manufacturing industries for the year 2008-09. mean output is calculated to be ` 7700.49 million with a higher standard deviation of 7133.29. the mean of capital, labour, energy and material inputs are calculated to be 401.90, 30.67, 26.04, and 372.33 respectively. this study is a two stage estimation of determinants of productivity for the indian manufacturing. therefore, as stated in section-3, the firm specific variables are also included at the second stage estimation. the variables include age of the firm, energy intensity, embodied technology import intensity, disembodied technology import intensity, r&d intensity and export intensity of the firm. from table-1 we can observe that the mean age of the firms is 31 years. the mean energy intensity, embodied technology import intensity, r&d intensity, export intensity and disembodied technology import intensity are calculated to be 0.07, 0.004, 0.003, 0.151, and 0.081 respectively. table-2 gives the estimation result of the translog production function. from the results we can see that the elasticity of capital is positively related to the output and statistically significant at 1%. this implies the higher the capital input of a firm higher is the output of the firm. the coefficient of the labour input carries a positive sign with the productivity and highly significant. this indicates that increase in labour input also increases the output of the firm. energy input is considered as the third input in the tfp model. this variable carries a positive sign and significant at 1% level. hence increase in energy consumption is increasing the output of firms. the fourth input of the model is the material used for production. this variable carries a positive relationship with the output of the firm. detailed result of equation (0.1) is given in table-2. international journal of energy economics and policy, vol. 1, no. 2, 2011, pp.47-58 52 table 1. descriptive statistics of selected variables variable mean std. dev. min max output 770.49 7166.29 0.01 270582.40 capital 401.90 2956.63 -12182.80 107932.30 labour 30.67 202.16 0.00 8069.15 energy 26.04 138.40 0.01 3399.91 material 372.33 3227.14 0.00 101494.60 age of the firm 31.42 44.39 1.00 118.00 energy intensity 0.074 0.23 0.00 8.00 embodied technology import intensity 0.004 0.09 0.00 4.53 r&d intensity 0.003 0.02 0.00 1.19 export intensity 0.151 0.24 0.00 1.09 disembodied technology import intensity 0.081 0.16 0.00 4.66 number of observations 2541 source: own estimates from cmie, prowess data for 2008 table 2. estimation result of the translog production function for indian manufacturing variables coefficients standard error t statistics βk 0.174 0.020 8.660*** βl 0.220 0.026 8.470*** βe 0.065 0.022 3.030*** βm 0.515 0.020 25.540*** βkk 0.000 0.000 3.370*** βkl 0.040 0.007 5.570*** βke -0.049 0.007 -7.010*** βkm 0.009 0.006 1.450 βll 0.000 0.000 -0.590 βle 0.000 0.006 -0.070 βlm -0.046 0.007 -6.520*** βee 0.000 0.000 -0.560 βem 0.049 0.005 10.410*** βmm 0.000 0.000 0.200 α0 1.415 0.058 24.490 r2 0.835 prob > f 0.000*** root mse 0.493 number of observations 2541 source: own estimates from cmie, prowess data for 2008 note: ***: statistically significant at 1% once the tfp is estimated based on a translog specification, we tried to calculate the mean tfp for 19 sub-industries. in addition, the mean energy intensity is also calculated for the full sample. from the result we can see that, the diversified manufacturing reported to be higher tfp as compared to all other industries and the agricultural product industries have the least tfp. figure-1 presents the result where the horizontal line represents the mean tfp and the bars represent the tfp for each industry. we can observe from the figure that, only nine sub-industries out of 19 sub-industries have tfp greater than the mean tfp. the ranking of the sub-industries in terms of tfp are given in table-3. total factor productivity and energy intensity in indian manufacturing: a cross-sectional study 53 table 3. mean total factor productivity and energy intensity in indian manufacturing symbol used sub-industries number of observation mean total factor productivity mean energy intensity ranking based on tfp* ranking based on energy intensity* id1 food products 6 4.81 0.07 14 13 id2 agricultural products 87 3.18 0.07 1 12 id3 petrochemical 31 5.55 0.03 18 3 id4 other food products 54 5.03 0.05 15 8 id5 beverages and tobacco products 159 4.75 0.04 11 6 id6 textile 321 4.53 0.11 10 17 id7 lather and lather products 14 4.15 0.03 5 5 id8 wood and wood products 14 3.58 0.08 3 15 id9 paper and paper products 83 4.30 0.11 7 18 id10 chemical and chemical products 390 4.49 0.09 9 16 id11 rubber and plastics products 165 4.22 0.05 6 10 id12 non-metallic mineral products 129 4.80 0.15 12 19 id13 basic metal and metal products 283 5.19 0.06 16 11 id14 machinery and machinery products 129 4.49 0.02 8 1 id15 heavy machinery 115 4.80 0.02 13 2 id16 electronics 93 4.14 0.03 4 4 id17 transport equipments 181 5.32 0.04 17 7 id18 other miscellaneous manufacturing products 36 3.30 0.05 2 9 id19 diversified manufacturing 28 6.42 0.08 19 14 total 2318 4.63 0.07 source: own estimates from cmie, prowess data for 2008 note: *: ranking of the variable takes higher value for higher tfp and higher energy intensity. mean tfp of full sample, lies between rank 10 and 11, whereas mean energy intensity lies between rank 12 and 13. as this study also tried to look at the energy intensity of the firms, and in the second stage regression, energy intensity is considered as a determinant of productivity, we tried to look at the mean energy intensity of the 19 sub-industries and the mean energy intensity of the full sample. table-3 gives the result of this exercise. table-3 also gives the ranking of the sub-industries based on the energy intensity of the firms. figure-2 presents the mean energy intensity of each sub-industries and mean energy intensity of the full sample. the horizontal line parallel to the x-axis in figure-2 gives the mean energy intensity. from the figure we can observe that the non-metallic mineral product industries are higher energy intensives as compared to all other 18 sub-industries and the machinery and machinery product industries are the least energy intensives. further, we can observe that seven out of 19 industries are above the mean energy intensity. however, as compared to the mean tfp the fluctuation is higher in case of the energy intensity for the sub-industries. the next attempt of this paper is to investigate the determinants of tfp using firm specific variables other than labour, capital and material. hence, we have tried the estimation of the determinants of inter-firm differences in the productivity. international journal of energy economics and policy, vol. 1, no. 2, 2011, pp.47-58 54 figure 1. comparison of mean tfp of full sample with 19 sub-industries sample figure 2. comparison of mean energy intensity of full sample with 19 sub-industries sample it is now interesting to check whether the energy intensity and the tfp of the indian manufacturing industries have any relationship among themselves. in this connection we have tried to check the correlation coefficients between the energy intensity and the tfp at firm level. for a detail analytical purpose, we have classified the sample in the following sub-classifications, (i) classification based on the ownership pattern of the firms, (ii) classification based on the aggregate industries total factor productivity and energy intensity in indian manufacturing: a cross-sectional study 55 classification (as in cmie), and (iii) classification based on the energy intensity. initially we have tried the correlation and further we have also calculated the rank correlation coefficient between the set of variables. the result of this exercise is given in table-4. from the table we can observe that, except for non-metallic mineral product and for the diversified manufacturing industries rest all the subindustries classification turned out to be negatively related to the tfp. however, a detail observation in between the sub-groups, for example between the ownership of the firms (either foreign or domestic) gives the result that the domestic firms are highly correlated with the tfp as compared to the foreign firms. in the aggregate industries classification, we can also see that there is inter-industries difference in correlation coefficients. to check whether there is any relation between energy intensity and tfp we further divided the data into two groups. one group contains firms those energy intensity is greater than the mean of the energy intensity of the sample (here defined as the less energy efficient firms) and firms those energy intensity is less than that of the energy intensity of the full sample (defined as the energy efficient firms). the correlation result shows that, firms those are highly energy efficient are bearing a higher significant level in the correlation coefficient as compared to the less energy efficient firms. table 4. correlation coefficient of energy intensity and tfp across groups sl no description of the sample sample size correlation coefficient rank correlation coefficient 1 full sample 2318 -0.152 0.230 2 foreign 89 -0.002 0.303 3 domestic 2229 -0.151 0.230 4 food products 6 -0.807 0.770 5 agricultural products 87 -0.127 0.252 6 petrochemical 31 -0.593 0.600 7 other food products 54 -0.305 0.593 8 beverages and tobacco products 159 -0.316 1.000 9 textile 321 -0.251 0.801 10 lather and lather products 14 -0.251 0.864 11 wood and wood products 14 -0.481 0.947 12 paper and paper products 83 -0.020 0.830 13 chemical and chemical products 390 -0.162 0.857 14 rubber and plastics products 165 -0.018 0.927 15 non-metallic mineral products 129 0.081 0.867 16 basic metal and metal products 283 -0.048 0.913 17 machinery and machinery products 129 -0.288 0.946 18 heavy machinery 115 -0.272 0.934 19 electronics 93 -0.140 0.953 20 transport equipments 181 -0.269 0.877 21 other miscellaneous manufacturing products 36 -0.489 0.973 22 diversified manufacturing 28 0.218 0.860 23 highly energy efficient 1886 -0.161 0.240 24 less energy efficient 432 -0.080 0.362 table-5 gives the detailed result of the estimates of equation (0.2). from the estimate of determinants of productivity (tfp) we can observe that, age of the firm is positively significant with the tfp of the firms. this suggests that older firms are more productive as compared to the younger ones. the positive relation between the age of the firm and the tfp is as expected earlier and supports our hypothesis. energy intensity has turned out to be negatively related to the tfp. this result suggests that lesser energy intensive firms (higher energy efficiency firms) are more productive as compared to the higher energy intensive firms. this is as according to our hypothesis, as firms international journal of energy economics and policy, vol. 1, no. 2, 2011, pp.47-58 56 minimize energy input in producing output and energy is a derived demand for the industries, the higher energy efficient firms are more productive when compared to the less energy efficient firms. table 5. estimates of determinants of total factor productivity for indian manufacturing variables coefficients standard error t statistics age 0.003 0.001 4.030*** mne dummy -0.659 0.188 -3.500*** ei -4.461 0.677 -6.590*** eti -3.687 1.622 -2.270*** rdi 3.791 1.282 2.960*** expi 0.417 0.155 2.700*** deti 2.160 0.225 9.580*** id1 -1.161 0.776 -1.500 id2 -3.168 0.376 -8.430*** id3 -1.205 0.452 -2.670*** id4 -1.336 0.402 -3.320*** id5 -1.558 0.353 -4.410*** id6 -1.743 0.342 -5.090*** id7 -2.415 0.568 -4.250*** id8 -2.944 0.565 -5.210*** id9 -1.852 0.379 -4.880*** id10 -1.988 0.339 -5.870*** id11 -2.225 0.353 -6.300*** id12 -1.502 0.363 -4.140*** id13 -1.213 0.342 -3.540*** id14 -2.008 0.360 -5.580*** id15 -1.699 0.364 -4.670*** id16 -2.598 0.373 -6.960*** id17 -1.171 0.351 -3.340*** id18 -3.146 0.435 -7.230*** α 6.867 0.377 18.240*** f( 26, 2291) 17.150 prob > f 0.000*** r2 0.163 adj r2 0.154 number of observations 2541 source: own estimates from cmie, prowess data for 2008 note: ***: statistically significant at 1% the embodied technology import intensity has a negative relationship with the tfp of the firms. this result suggests that firms those import lesser embodied technology are more productive. research and development intensity of the firms are positively related to the tfp of the firms. hence, higher the research and development expenditure of the firm higher productive they are. the export intensity has also turned out with a positive relation with the tfp of the firms. hence, export oriented firms are also more productive. as against the result of the embodied technology import, the disembodied technology import intensity of the firms is found to be positively related to the tfp of the firms. this result suggests that firms importing higher disembodied technology are less productive as compared to their counterparts. total factor productivity and energy intensity in indian manufacturing: a cross-sectional study 57 to capture the industry specific characteristics in the inter-firm differences in tfp, we have created 18 dummies in equation (0.2). except food products industries all other industry dummies have turned out to be significant. as the coefficient of the constant has also turned out to be significant we can interpret the dummy coefficients and compared to the diversified manufacturing (the excluded industry in dummy). in addition to the industry dummy the mne dummy is too significant in the result. hence in addition to the constant coefficient the result suggests that the foreign owned firms are higher productive as compared to the domestic firms. the result of the dummied (17, except the food products industries) conform the estimation result. further, we can observe that the tfp is higher for the diversified manufacturing (as the benchmark) as compared to all other sub-industries. 5. conclusion the objective of the paper is to estimate the translog production function and analyze the determinants of inter-firm differences in the level of tfp. we used a two-stage regression using ols to estimate the translog production function for four inputs for the indian manufacturing industries for the year 2008. further, the determinants of tfp were carried out using firm specific characteristics and energy intensity. the findings of the paper suggest that labour and material inputs play major role as compared to the capital and energy input. age of the firm, ownership, energy intensity, embodied and disembodied technology imports, research and development and exports were considered as the possible determinants of the tfp in the second stage regression. the finding of the estimates suggest that age of the firm, export intensity and disembodied technology import are positively related to the tfp, whereas ownership, energy intensity, embodied technology import and r&d intensity are negatively related to the tfp of the firms for indian manufacturing. energy efficient firms also have high levels of tfp. from the mean tfp we can observe that the diversified manufacturing industries has higher tfp as compared to other eighteen sub-industries and the agricultural product industries turned out to have the least tfp for indian manufacturing. beyond measuring the tfp, this work attempts to understand the determinants of tfp for the indian manufacturing industries and compares across subindustries. one more value addition of the paper is that it takes energy as the fourth input in the production function. in recent climate change negotiations and debates, energy cannot be overlooked and there is a necessary to focus on productivity and energy use in indian industries, more specifically in the manufacturing industries. the results have vital policy implications. one specific implication is the need to foster energy efficiency at firm level in all the manufacturing industries in india. the government could think of introducing fiscal incentives for achieving higher energy efficiency. references abramovitz, m., 1956. resources and output trends in united states since 1870. american economic review 46, 1-23. ahluwalia, i. j., 1991. productivity and growth in indian manufacturing – trends in productivity and growth. oxford university press new york, new delhi. berndt, a. h., keith, r., and henry, t., 1998. electricity substitution: some local industrial evidence. energy economics 20, 411-419. berndt, e. r., and watkins, g. c., 1981. energy prices and productivity trends in the canadian manufacturing sector 1957-76: some exploratory results. a study prepared for the economic council of canada. berndt, e. r., and wood, d. o., 1975. technology, prices and the derived demand for energy. the review of economics and statistics 57, 259-268. biesebroeck, j. v., 2005. firm size matters: growth and productivity growth in african manufacturing. economic development and cultural change 53, 545-583. catsany, l., lopez-bazo, e., moreno, r., 2007. decomposing differences in total factor productivity across firm size. research institute of applied economics, working paper no. 5 chang, k., 1994. capital-energy substitution and the multi-level ces production function. energy economics 16 (1), 22-26. christensen, l. r., jorgenson, d., and lau, l. j., 1971. conjugate duality and the transcendental logarithmic production function. econometrica 39 (4), 255-256. international journal of energy economics and policy, vol. 1, no. 2, 2011, pp.47-58 58 denison, e. f., 1962. the source of growth in the united sates, and alternative before us. committee of economic development, new york. denison, e. f., 1967. why growth rates differ. post war experience in nine western countries. the brooking institution. the brooking institution, washington, d. c. denison, e. f., 1985. trends in american economic growth: 1929-1982. the brooking institution, washington, d. c. goldar, b. n., 1986. productivity growth in indian industry. allied publishers pvt. ltd., new delhi goldar, b. n., 2000. employment growth in organized manufacturing in india. economic and political weekly 35 (14), 1191-1195. griliches, z., 1979. issues in assessing the contribution of r&d to productivity growth. bell journal of economics 10, 92-116. hall, b. h., & mairesse, j., 1995. exploring the relationship between r&d and productivity in french manufacturing firms. journal of econometrics 65(1), 263-293. hayami, y., vemon, w. r., and herron, m. s., 1979. agricultural growth in japan, taiwan, korea and philippines. the university press of hawaii, honolulu. lichtenberg, f. r., & siegel, d., 1989. the effects of leveraged buyouts on productivity and related aspects of firm behavior. center for economic studies, working papers no. 89-5, u.s. census bureau. lipsey, r. g., & carlaw, k. i., 2001. what does total factor productivity measure?. downloaded from www.csls.ca/ipm/1/lipsey-carlaw-e.pdf. ma, h., oxley, l., and gibson, j., 2009. substitution possibilities and determinants of energy intensity for china. energy policy 37 (5), 1793-1804. mahmud, s., 2000. the energy demand in the manufacturing sector of pakistan: some further results. energy economics 22, 641-648. mongia, p., and sathaye, j., 1998. productivity trends in india’s energy intensive industries: a growth accounting analysis. lawrence berkeley national laboratory, working paper no. 41838, berkeley, california. mongia, p., and sathaye, j., 1998a. productivity growth and technical change in india’s energy intensive industries a survey. lawrence berkeley national laboratory, working paper no. 41840, berkeley, california. mongia, p., schumacher, k., sathaye, j., 2001. policy reforms and productivity growth in india's energy intensive industries. energy policy 29, 715-724. nagaraj, r., 2004. fall in organised manufacturing employmenta brief note. economic and political weekly 24, 33873390. pradhan, g., barik, k., 1999. total factor productivity growth in developing economies a study of selected industries in india. economic & political weekly 34, m92-m97. roy, j., sathaye, j., sanstad, a., mongia, p., and schumacher, k., 1999. productivity trends in india’s energy intensive industries. the energy journal 20 (3), 33-61. sharma, c., & mishra, r. k., 2011. does export and productivity growth linkage exist? evidence from the indian manufacturing industry. international review of applied economics, 1-20. yi, f., 2000. dynamic energy-demand models: a comparison. energy economics 22, 285-297. zoltan, a., morek, r., and yeung, b., 1996. productivity growth and firm-size distribution. milken institute. . international journal of energy economics and policy | vol 7 • issue 2 • 2017152 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(2), 152-159. income-carbon emissions nexus for middle east and north africa countries: a semi-parametric approach atif awad*, hoda abugamos department of finance & economic, college of business administration, university of sharjah, sharjah, uae. *email: aawoad@sharjah.ac.ae abstract it is widely accepted that middle east and north africa (mena) region is significantly impacted by climate change. evidence suggests that the region is positioned at the second place after north america in carbon emission. this study attempts to further examine the impacts of income on carbon emissions in mena region through investigation of the existence of an environmental kuznets curve. within the stochastic impacts by regression on population, affluence and technology framework, this is the first study in mena region to explore the income-carbon emissions nexus; using panel data together with a semi-parametric panel fixed effects regression. our data set is referred to a panel of 20 countries in mena region spanning the period 1980-2014. with this information, we find evidence to support an inverted-u shaped relationship between income and co2 emissions in the region. these findings suggest that environmental degradation may be reversible and environmental quality may be recoverable alongside the economic growth process in the region. keywords: per capita income, carbon emissions, stochastic impacts by regression on population, affluence and technology environmental kuznets curve, mena region jel classifications: q01, q28, q52, q51 1. introduction it is widely accepted that middle east and north africa (mena) region is significantly impacted by climate change (wodon et al., 2014; al-rawashdeh et al., 2014). according to the international energy agency (2014), the region is positioned at the second place after north america in carbon emission and documented by 9 metric tons of co2 per person; which is higher than the average value in africa (1.1), asia (3.7), europe (7.1), and even higher than that worldwide (4.6). empirical studies addressing this issue in the region agree that energy use and/or consumption and economic growth are the key sources of co2 emissions (arouri et al., 2012; al-rawashdeh et al., 2014; herrala and goel, 2012; méon and sekkat, 2004). at one hand, the pattern of economic growth and structure change in the economy of the region may be responsible, at least partly, for the deterioration of the environmental quality. at the other hand, the extensive use of energy in the region which has been attributed to high subsidies on petroleum products may encourage an exaggerated and inefficient use of fossil energy. studies show that eleven out of twenty countries in the world which subsidize gasoline consumption are from mena region (brown, 2011). recently, and for two reasons, environmental degradation and income nexus has received increased attention and emerged as one of the most attractive empirical topics of immense interest among economists and policy makers. first, due to the aggravation of pollution problems, policy makers in the region seek to identify the exact relationship between income and environmental quality in order to prepare the required appropriate policy. if the relationship between income and environmental degradation is found to be a monotonously (linear) positive relationship, then environmental quality will continue to deteriorate with income development. only when income enters a stage of stagnation, the tendency towards environmental degradation would slow down. therefore, policy makers should re-think about the pattern of economic growth to avoid environmental deterioration. however, if results show a monotonously negative relationship between income and environmental degradation, then environmental quality will continue to improve even with the continuation of the growth awad: income-carbon emissions nexus for mena countries: a semi-parametric approach international journal of energy economics and policy | vol 7 • issue 2 • 2017 153 process. hence, policy makers should continue promoting the process of development to maintain the quality of the environment. in contrast, if a non-monotonous (nonlinear) relationship is found between development and environmental quality, environmental degradation may be reversible and environmental quality may be recoverable. theoretically, the existence of such a nonmonotonous and nonlinear curve (analogous to an inverted u-shaped curve) may link income per capita to environmental quality indicators such as carbon dioxide and/or sulphur dioxide emissions as termed by the environmental kuznets curve (ekc) hypothesis. the ekc hypothesis states that in the early stages of socioeconomic growth, environmental quality deteriorates with the increase of gas emissions. however, as the economy continues growing beyond a certain threshold (the turning point), emissions begin to decline and environmental quality starts to improve; forming an approximately inverted u-shaped curve. validity of the ekc hypothesis indicates that income versus environmental protection dilemma can be resolved. in the context of developing countries, finding evidence in support of this hypothesis might have promising implications for sustainable development in the future (wang et al., 2016). the second reason, which is a main concern for economists and econometricians, is related to the appropriate theoretical model that can be used to describe income and environmental quality nexus as well as the relevant estimated method. with regard to the theoretical framework, previous studies frequently employ either ad hoc model or ipat (i.e., population, affluence and technology) theoretical model as proposed by ehrlich and holdren (1971). however, the ipat model is considered purely a simple function form; parsimoniously indicating that anthropogenic environmental impact is associated with multiple driving forces. thus, it cannot -individuallydetermine the extent to which each factor affects the environment (zhua et al., 2012; liddle and lung, 2010). concerning the estimation method, most of the preceding studies employ a parametric panel fixed effects technique to estimate the impact of income on co2 emissions. however, using this technique usually yields biased estimators as a result of failure to consider relevant explanatory variables and therefore; leads to potential functional form misspecification (wang et al., 2015). the present study seeks to fill the gap in the literature concerning the income co2 emissions nexus in mena region in two principal fashions. first, and to avoid the limitations of ipat mentioned previously, the present study employs the stochastic impacts by regression on population, affluence and technology (stirpat) model. according to york et al. (2010) the stirpat model could precisely specify the functional form of the relationship between anthropogenic gas emissions and economic growth. second, and instead of using the parametric fixed panel; a method that is extensively used in the previous studies, we employ the semi-parametric regression developed by baltagi and li (2002). according to wang et al. (2016) the semi-parametric regression is a consistent estimation method for a dynamic partially linear panel data model with fixed effects. in contrast to the parametric panel fixed effects regression, the semi-parametric panel fixed effects regression is more flexible; which enables addressing of the potential functional form misspecification (desbordes and verardi, 2012; wang et al., 2015). furthermore, it partially avoids dimensionality problems by combining features of parametric and non-parametric techniques. a further advantage of the semiparametric panel fixed effects regression is the possible inclusion of a concise economic interpretation of the results. to the best of the authors’ knowledge, this is the first empirical study in mena region, to investigate the ekc hypothesis by employing the semiparametric regression within the stirpat model. the remaining of the paper is organized as follows. section 2 briefly describes the empirical evidence from the literature. sections 3 and 4 examine the models, estimation methods and data sources used to test the ekc hypothesis. empirical results and related discussion are presented in section 5. the final section; section 6 contains concluding comments and policy implications. 2. literature review according to oscan (2013) there are three empirical research strands examining the above-mentioned topics in the environmental economics literature. the first strand focuses on the environmental pollutants and income nexus, and seeks to examine the validity of the ekc hypothesis. the first empirical study regarding the ekc is attributed to grossman and krueger (1991). thereafter, numerous researchers have tested the ekc hypothesis and arriving to mixed findings (agras and chapman, 1999; dinda and coondoo, 2006; fiedl and getzner, 2003; galeotti et al., 2009; selden and song, 1994; saboori et al., 2012; shahbaz et al., 2013; holtz-eakin and selden, 1995; stern, 2004; he and richard, 2010; al-mulali et al., 2015; ozturk and al-mulali, 2015; al-mulali et al., 2016). the second strand comprises studies exploring the growth -energy nexus. these studies date back to the seminal work of kraft and kraft (1978). again, after that, numerous researchers have tested the growth energy nexus and arriving to mixed findings (belloumi, 2009; akarca and long, 1980; bentzen and engsted, 1993; pao, 2009; erol and yu, 1987; ghosh, 2010; yu and hwang, 1984). however, all the studies that tend to employ a bivariate model are criticized due to the omitted variables bias and also because they fail to get consensus results. nevertheless, to avoid this problem, recent studies have started to examine the nexus of energy consumption and economic growth in a multivariate framework (gurgul and lach, 2011; 2012; altinay and karagol, 2004; al-iriani, 2006; apergis and payne, 2009; narayan and smith, 2008; oh and lee, 2004; stern, 2000; yang, 2000; ozturk, 2010). however, analyzing the growth environment nexus and growth energy nexus in a bivariate framework suffers from omitted-variables bias as stated by saboori and soleyman (2011). the third stream of research has emerged as reflected by the fact that today numerous studies have gathered both nexuses in a single framework (ang, 2007; soytas et al., 2007; hamit-haggar, 2012; ozturk and acaravci, 2012; esteve and tamarit, 2012; tiwari et al., 2013; toda and philips, 1995; soytas et al., 2007; akbostanci et al., 2009; halicioglu, 2009; jalil and mahmud, 2009; soytas and sari, 2009; tamazian and rao, 2009; zhang and cheng, 2009; he and richard, 2010; lean and smyth, 2010; narayan and narayan, 2010). recently, the above mentioned multivariate framework has been extended further by including, for example, the impacts of foreign trade and awad: income-carbon emissions nexus for mena countries: a semi-parametric approach international journal of energy economics and policy | vol 7 • issue 2 • 2017154 urban population, and human development (hd) into the nexus, in order to avoid omitted variable bias in the econometric estimation (halicioglu, 2009; and zhang and cheng, 2009). in the present study and to conserve space, we would only review some selected studies related to mena region. however, to our knowledge, there are only few studies that analyze economic growth co2 emissions nexus in mena region. most importantly, even among these few studies, no consensus exists in regards to the impact of income on carbon emission in the region. so, we classify these studies into country-based studies and panel or cross countries-based studies. based on the country level analysis, fodha and zaghdoud (2010) investigate the validity of the ekc hypothesis for tunisia using two indicators for pollutant emissions (so2 and co2), during the period 19612004. employing the johansen approach for cointegration, as well as granger causality test, the study arrives to an evidence in support for ekc hypothesis when co2 has been used as a proxy for pollutant emissions. in contrast, a monotonically increasing relationship with gross domestic product (gdp) is found to be more appropriate for co2 emissions. the causality results support the argument that the relationship between income and pollution in the country is one of the unidirectional causality with income causing environmental changes and not vice versa; both in the short-run and long-run. alkhathlan and javid (2013) examine the relationship among economic growth, carbon emissions and energy consumption at the aggregate and disaggregate levels for saudi arabia during the period 1980-2011. for the aggregate energy consumption model, the authors use the total energy consumption per capita and co2 emissions per capita based on the total energy consumption. for the disaggregate analysis, they use oil, gas and electricity consumption models along with their respective co2 emissions. the results of the autoregressive distributed lag technique show that the estimated long-term income elasticities of carbon emissions is higher than the estimated short-term income elasticities of carbon emissions; which imply that over time, per capita carbon emissions increase with the rise in per capita incomes in saudi arabia. this result indicates that there is a monotonically increasing relationship between carbon emissions and per capita income in saudi arabia. therefore, the ekc hypothesis does not hold for these three models. likewise, al-rawashdeh et al. (2014) examine whether or not the ekc relationship exists between economic growth and two environmental pollution indicators (so2 and co2) based on a country level analysis using time series data for all of the 22 mena countries in the region. under a country level, the results suggest an evidence of so2 ekc for algeria, tunisia, yemen, morocco, turkey and libya. regarding co2, the findings also support an inverted u-shaped pattern associated with the ekc hypothesis for tunisia, morocco, turkey and jordan. in analyzing mena region as a panel, the results show that there is no ekc evidence for so2 and co2 emissions, but there is only a monotonically increasing linear relationship between income and co2 emissions. m’henni (2005) tests for the ekc hypothesis in tunisia over the period from 1980 to 1997. the author employs the generalized method of moments and examines the following pollutants: co2 emissions, fertilizers’ concentration and the number of cars in traffic which serve to calculate an index for environmental quality. the results show that there is no evidence to confirm the ekc for any of these pollutants. based on the cointegration analysis, again, chebbi et al. (2009) examine the same issue for tunisia and arrive to different results. more specifically, they detect a positive linkage between trade openness and per capita emissions and a negative linkage between economic growth and per capita pollution emissions in the long-run. akbostanc et al. (2009) examine the relationship between co2, so2 and (particulate matter 10 micrometers or less in diameter) emissions. they examine the ekc in turkey at both national level, as well as at provinces level (58 provinces). they find a monotonic and increasing relationship at the national level. however, at the level of provinces, they discover an n-shaped curve; implying the absence of evidence in support for the ekc. with regard to the panel or cross countries-based studies, al-mulali (2011) examines the impact of oil consumption on the economic growth of mena countries during the period 1980-2009. the author regress gross domestic product on both oil consumption (in term of thousands of barrels per day) and total carbon dioxide emissions from the consumption of energy. after employing both pedroni and kao cointegration tests, the author employs engle-granger panel causality technique to examine the direction of the relationship. the results detect the existence of a long-run relationship between the variables. in addition, the causality test reveals the presence of a bi-directional relationship between the variables in both short and long run. likewise, arouri et al. (2012) employ cointegration techniques on data related to economic growth, energy consumption and emissions of co2 for 12 countries in mena region during the period 1981-2005. the main objective of these techniques is to, first, test for the ekc hypothesis in mena region for co2. second, to investigate the existence of ekc for each country. finally, to explore the nature of the causality relationship between economic growth, energy consumption and emissions of co2. the results show that in the long-run, energy consumption has a positive significant impact on co2 emissions in mena region. more interestingly, the results show that real gdp exhibits a quadratic relationship with co2 emissions. taken together, the findings support an inverted u-shaped pattern associated with the ekc hypothesis for mena region. in addition, co2 emissions increase with real gdp, stabilize, and then decrease. at the country-level, however, the results show that ekc is not verified for the studied countries; except for jordan. although the estimated long-run coefficients of income and its square satisfy the ekc hypothesis in most studied countries, the ekc turning points are very low in some cases and very high in other cases, hence providing rather poor evidence in support of the ekc hypothesis. for the causality relationship, the results show that in the short-run, the evidence suggests existence of positive causality from energy consumption to co2 emissions. however, in the long run, the evidence suggests existence of bidirectional relationship between the variables. based on these findings, the authors suggest that future reductions in co2 emissions per capita might be achieved at the same time as gdp per capita continues to grow in mena region. awad: income-carbon emissions nexus for mena countries: a semi-parametric approach international journal of energy economics and policy | vol 7 • issue 2 • 2017 155 likewise, omri (2013) examines the nexus between co2 emissions, energy consumption and economic growth using simultaneous-equations models with panel data of 14 mena countries over the period 1990-2011. the study reveals existence of a bidirectional causal relationship between economic growth and co2 emissions for the region as a whole. the author suggests that degradation of the environment has a causal impact on economic growth, and that a persistent decline in environmental quality may exert a negative externality on the economy through affecting human health; and thereby may reduce productivity in the long-run. meanwhile, farhani et al. (2013) empirically parallels two panel. the first panel; denoted as panel a, pursues the studies of halicioglu (2009), jalil and mahmud (2009), and jayanthakumaran et al. (2012) which experiment the introduction of energy consumption and trade into the environmental function. the second panel; panel b, develops the work of hossain (2011) which tries to propose urbanization as a mean to evade omitted variable bias. the study includes 11 mena countries over the period 1980-2009. the authors employ panel fully modified ordinary least squares (fmols) and dynamic ols (dols) as well as causality test. the empirical results show consistency in light of the ekc biography based on the cointegrated and causal relationships. the results imply that an increase in energy use, together with higher gdp and greater trade openness tend to reveal more co2 emissions. furthermore, the addition of urbanization in the environmental function enhances the final results and positively affects the pollution level. regarding the causality test, for panel a, it is found that real gdp and energy consumption cause co2 emissions in the short-run panel causality. this implies that in the absence of energy conservation policies due to the economic development, these countries consume more energy; which may result in more pollution for the environment. in the log-run, there are two causal relationships among the variables running from all variables to co2 emissions and to energy consumption. for panel b, the results indicate that real gdp, energy consumption and urbanization exert a causal significant effect on co2 emissions, and trade openness exerts a causal significant effect on urbanization in the short-run. moreover, farhani et al. (2014) examine the existence of long-run equilibrium relationships for two different ekc specifications for 10 mena countries over the period 1990-2010. in the first one, co2 emissions variable has been regressed on per capita real gdp, energy consumption, trade openness, manufacture value added and modified hd index (hdi). in the second model, genuine saving index is regressed on hdi, energy consumption, trade openness, manufacture value added and the role of law. the two models have been estimated using two recent techniques; namely panel fmols and dols. the results of the first specification; namely ekc, show that there is an inverted u-shaped relationship between environmental degradation and income; while for the second specification; namely modified ekc, the findings show that there is an inverted u-shaped relationship between sustainability and hd. a study by arouri et al. (2012) has implemented recent bootstrap panel unit root tests and cointegration techniques to investigate the relationship between carbon dioxide emissions, energy consumption, and real gdp for 12 mena countries over the period 1981-2005. the results detect evidence in support of the ekc hypothesis in mena region. more specifically, the results demonstrate that the level of co2 emissions first increases with income, then stabilizes, and then declines. in contrast, ozcan (2013) tests the ekc hypothesis for 12 mena countries during the period 1990-2008; by employing a cointegration approach. the results provide evidence contrary to the ekc hypothesis. the review of the extant studies that examine mena region demonstrates the absence of any consensus in regards to the nature of the relationships between income and carbon emission as described by the ekc hypothesis. the conflicting results of these studies may be attributed to country-specific policies, the use of different energy consumption and income measures, the econometric methodology, omitted variable bias, model specifications or the varying time spans of the studies. however, most importantly, all these studies, however, have weaknesses that this study aims to address. they mainly involve the use of ad-hoc model specifications which are not based upon solid theoretical models. as a result, the findings of the present study may prove beneficial and relevant value-added for policy-makers seeking to implement appropriate policies that can maintain environmental quality within the region. 3. theoretical framework and methodology to address the limitation of ipat, we employ a stochastic version of ipat designated stirpat; which provides a relative quantitative framework to explore the environmental impact of income progress (dietz and rosa, 1997). the model specification is i =ap a t i i b i c i d i ε (1) in equation 1, i denotes environmental impact, p, a, and t stand for population, affluence, and technology factors respectively. explanatory variable coefficients to be estimated are represented by a, b, c, and d; ε represents random error; and subscript i denotes the panel unit; which refers to 20 mena countries in the present study. to test the existence of the ekc, york et al. (2010) incorporate a quadratic term of the per capita gdp factor into the stirpat model. following previous studies, we derive extended versions of the stirpat model to test for the presence of an inverse u-shaped curve relationship between per capita gdp and carbon emission. in this model, all variables except urbanization are converted into natural logarithmic form for direct interpretation as elasticities. accordingly, within the ekc hypothesis framework, the augmented model is estimated as lnce = + lnp + lna + lnel + ur + la +t + ti i 1 it 2 it 3 it 4 it it 2 t it α β β β β β ε (2) where countries are indexed by i and time periods by t; ceit is the amount of co2 emissions of country i in year t; a is gdp per capita; p is the total population; ei is energy intensity; ur is the level of urbanization; αi represents a country-specific effect that is constant with time, and a time specific effect tt may be used to account awad: income-carbon emissions nexus for mena countries: a semi-parametric approach international journal of energy economics and policy | vol 7 • issue 2 • 2017156 for time-varying omitted variables and stochastic shocks that are common to all countries. energy intensity may be interpreted as a proxy for technology level which may damage the environment (zarzoso et al., 2007), whereas time-specific effect is sometimes interpreted as the effect of technical progress in carbon emission control overtime (stern, 2002). meanwhile, anderson and cavendish (2001) point out that prior studies paid little attention to the role of technical progress in air pollution abatement. ignoring this determinant could drastically underestimate possibilities for countries to decrease pollution levels with economic growth. with regard to urbanization, we follow wang et al. (2016) and we add urbanization variable as an essential part in the investigation of income carbon emission nexus. this is because; some possible effects of urbanization on the environmental quality are somewhat and independently debated in three relevant theories. the first is the ecological modernization theory; which claims that environmental problems may rise from low to intermediate stages of development. nonetheless, extra modernization can reduce such inverse impacts; as societies start to recognize the significance of environmental sustainability. the second is the urban environmental transition theory; where an increase in affluence of cities often leads to an increase in manufacturing activities; leading to massive industrial pollution-related issues as air and water pollution. however, such inverse impacts decrease in affluent cities as a result of advanced environmental regulations, technological progress and structural improvement in the economy. the third is the compact city theory; where high urban density allows cities to accomplish economies of scale of urban public infrastructure, and decrease car usage, travel length, allocation losses of electricity supply, and minimize energy consumption and co2 emissions (burton, 2000; capello and camagni, 2000; burton et al., 2004; newman and kenworthy, 1989). within the aforementioned framework, we first examine the existence of income and carbon emission ekc; using parametric panel fixed effects regression. a more flexible method is used to explore this topic is the semi-parametric panel fixed effects model of baltagi and li (2002); which does not place an ex-ante restriction on the shape of the relationship curve between income and carbon emission and can therefore address potential functional form misspecification (wang et al., 2015). in the present study, the semi-parametric model for testing the relationship between income and carbon emission may be described as lnceti = αi+β1lnpit + β2lnelit+β3uit+f(lait)+tt+εit (3) where the functional form f (.) in the model is unspecified because the income variable is a non-linear input to the model. unobserved heterogeneous effects can be removed at the first difference: lnceit−1-lnceit−1 = β1(lnpit-lnpit−1) + β2(lnelit-lnelit−1) + β3(uit-uit−1) + [f(lait)-f(lait−1)] + tt−tt−1 + εit−εit−1 (4) to consistently estimate the first difference model, the following series of differences are derived to respectively estimate [f (urit)-f (urit−1)] in line with baltagi and li (2002). pk(lait, lait−1)=[p k(lait)-p k(lait−1)] (5) where, pk (ur) and pk (ln a) are the first k terms of a sequence of function (p1 (ur), p2 (ur),…) and (p1 (ln a), p2 (ln a),…), respectively. in practice, a typical example of pk series could be a spline; corresponding to piecewise polynomials with pieces depicted by a sequence of smooth knots. once β coefficients are estimated, the values of unit-specific intercepts αi can be calculated. thus, equation 5 can be reduced to u =lnce lnp lnel u =f(la )+ it ^ it 1 ^ it 2 ^ it 3 ^ it i ^ it it β β β α ε (6) the curve f (.) can be easily estimated by performing spline regression uit on the urit variable in equation 6. we execute a b-spline regression model of order k=4. 4. data and variables we investigate whether there is an evidence of a non-monotonic relationship between income and carbon emission; as postulated by the ekc hypothesis, for a balanced panel of 20 mena countries and data spanning 1980-2014. all data for the analysis was collected from the world bank development indicators. for this dataset, we apply, and for the first time, parametric and semiparametric panel fixed effects models. all underlying variables with their descriptive statistics are listed in table 1. it should be noted that all variables except urbanization are converted into natural logarithmic form. 5. results and discussion empirical results for per capita gdp co2 emissions nexus are given in table 2. column 1 of the table presents results of the parametric fixed effects regression estimator within the per capita gdp co2 emissions ekc hypothesis framework. the findings reveal that the elasticity of co2 emission with respect to energy use is highly significant at the 1% level, and its sign is positive. a 1% increase in energy use leads to 0.6% increase in carbon emission. the estimated coefficients for both; urbanization and population variables are not significant and have unexpected signs. the affluence variable and its quadratic term are both highly significant and they have the expected signs. findings from the parametric fixed effects model confirm the presence of the income co2 emissions ekc hypothesis. column 2 presents estimates of control variables in the semi-parametric panel fixed effects model. unlike the parametric fixed, the semi-parametric results detect insignificant impact for the energy use variable. in contrast to the parametric fixed effects model, the population variable is positive and highly significant at the 1% level. the results of the semi-parametric panel data model suggest that only population variable is the main source for carbon emission in mena region. the partial fit for the per capita gdp and co2 emissions nexus in the semi-parametric panel fixed effects model is represented in figure 1. the plot seems to confirm the existence of an ekc between income and co2 emissions in the region. the relationship appears more obviously inversely u-shaped; co2 emissions increase with real gdp, stabilize, and then start to decrease. the awad: income-carbon emissions nexus for mena countries: a semi-parametric approach international journal of energy economics and policy | vol 7 • issue 2 • 2017 157 curve develops gradually to be largely flat; suggesting that it is approaching the turning point. once income reaches the turning point, carbon emission begins to fall. thus, from the results of the two panel regression methods, we confirm the presence of the income co2 emissions ekc hypothesis, and it is more pronounced in the semi-parametric fixed effects model. 6. conclusion and policy implication the present study seeks to examine the impacts of income on carbon emission in mena region through investigation of the existence of an ekc. within the stirpat framework, this is the first study in mena region to explore the income and carbon emission nexus; using panel data together with semi-parametric panel fixed effects regression. our data set is referred to a panel of 20 countries in mena region spanning the period 1980-2014. with this information, we find evidence to support an inverted u-shaped relationship between income and co2 emissions in the region. one possible justification for our findings is related to the fact that in the region, there are several initiatives of renewable energy which are taken in consideration in algeria, the kingdom of saudi arabia and other mena countries like the pioneering project of masdar sustainable city. these initiatives are expected to improve the situation in the next years. overall, our results suggest that environmental degradation may be reversible and environmental quality may be recoverable alongside the development process in the region. reference agras, j., chapman, d. (1999), a dynamic approach to the environmental kuznets curve hypothesis. ecological economics, 28(2), 267-277. akarca, a.t., long, i.t.v. (1980), on the relationship between energy and gnp: a re-examination. journal of energy and development, 5, 326-331. akbostanci, e., turut-asik, s., tunc, i.g. (2009), the relationship between income and environment in turkey: is there an environmental kuznets curve? energy policy, 37(2), 861-867. al-iriani, m.a. (2006), energy-gdp relationship revisited: an example from gcc countries using panel causality. energy policy, 34(17), 3342-3350. alkhathlan, k., javid, m. (2013), energy consumption, carbon emissions and economic growth in saudi arabia: an aggregate and disaggregate analysis. energy policy, 62, 1525-1532. al-mulali, u. (2011), oil consumption, co2 emission and economic growth in mena countries. energy, 36, 6165-6171. al-mulali, u., adebola, s.s., ozturk, i. (2016), investigating the presence of the environmental kuznets curve (ekc) hypothesis in kenya: an autoregressive distributed lag (ardl) approach. natural hazards, 80(3), 1729-1747. al-mulali, u., tang, c.f., ozturk, i. (2015), estimating the environment kuznets curve hypothesis: evidence from latin america and the caribbean countries. renewable and sustainable energy review, 50, 918-924. al-rawashdeh, r., jaradat, a.q., al-shboul, m. (2014), air pollution and economic growth in mena countries: testing ekc hypothesis. environmental research, engineering and management, 4, 54-65. altinay, g., karagol, e. (2005), electricity consumption and economic growth: evidence for turkey. energy economics, 27, 849-856. anderson, d., cavendish, w. (2001), dynamic simulation and environmental policy analysis: beyond comparative statics and the environmental kuznets curve. oxford economics papers, 53, 721-746. ang, j.b. (2007), co2 emissions, energy consumption, and output in table 1: descriptive statistics of variables variables definition mean minimum maximum ln ce carbon dioxide emissions, metric tons per capita 1.55 −2.38 4.22 ln a gdp per capita (constant 2005 us$) 8.36 6.08 11.05 ln el energy use (kg of oil equivalent) per $1,000 gdp (constant 2011 ppp) 4.75 3.71 5.70 ln p population, total 15.98 13.07 18.31 ur urban population (% of total) 69.58 20.93 99.16 gdp: gross domestic product table 2: estimates for income-co2 emissions models variables parametric model semi-parametric model constant −14.84* (1.19) ln a 2.55* (0.27) ln el 0.60* (0.05) 0.09 (0.20) ln p −0.03 (0.03) 0.61* (0.13) ur −0.002 (0.003) −0.01 (0.013) ln a2 −0.09* (0.02) country dummies yes yes year dummies yes yes adjusted r2 0.76 0.66 observed 415 401 cluster-robust standard errors in parentheses. superscripts *denote statistical significance at 1% levels points on graph are estimated partial residuals for carbon emission. maroon curve represents fitted values for adjusted effects of other explanatory variables in the model, and 95% confidence bands are indicated by shading areas figure 1: partial fit of per capita gross domestic product and co2 emissions nexus awad: income-carbon emissions nexus for mena countries: a semi-parametric approach international journal of energy economics and policy | vol 7 • issue 2 • 2017158 france. energy policy, 35, 4772-4778. apergis, n., payne, j.e. (2009), co2 emissions, energy usage, and output in central america. energy policy, 37, 3282-3286. arouri, m.e., youssef, a., m’henni, h., rault, c. (2012), energy consumption, economic growth and co2 emissions in middle east and north african countries. energy policy, 45, 342-349. baltagi, b.h., li, d. (2002), series estimation of partially linear panel data models with fixed effects. annals of economics and finance, 3, 103-116. belloumi, m. (2009), energy consumption and gdp in tunisia: cointegration and causality analysis. energy policy, 37, 2745-2753. bentzen, j., engsted, t. (1993), shortand longrun elasticities in energy demand: a cointegration approach. energy economics, 15, 9-16. brown, l.r. (2011), world on the edge: how to prevent environmental and economic collapse. new york: norton and company. burton, e. (2000), the compact city: just or just compact? a preliminary analysis. urban studies, 37, 1969-2001. burton, e., jenks, m., williams, k. (2004), the compact city: a sustainable urban form? washington, dc: taylor & francis. capello, r., camagni, r. (2000), beyond optimal city size: an evaluation of alternative urban growth patterns. urbanization studies, 37, 1479-1496. chebbi, h., olarreaga, m., zitouna, h. (2009), trade openness and co2 emissions in tunisia. in: proceedings of the erf16 th annual conference. november. p7-9. desbordes, r., verardi, v. (2012), refitting the kuznets curve. economic letter, 116, 258-261. dietz, t., rosa, e.a. (1997), effects of population and affluence on co2 emissions. proceeding of the national academy of science of the usa, 94, 175-179. dinda, s., coondoo, d. (2006), income and emissions: a panel based cointegration analysis. ecological economics, 57, 167-181. ehrlich, p.r., holdren, j.p. (1971), impact of population growth. science, 171, 1212-1233. erol, u., yu, e.s.h. (1987), on the causal relationship between energy and income for industrialized countries. journal of energy and development, 13(1), 113-122. esteve, v., tamarit, c. (2012), threshold cointegration and nonlinear adjustment between co2 and income: the environmental kuznets curve in spain, 1857-2007. energy economics, 34(6), 2148-2156. doi: 10.1016/j.eneco.2012.03.00. farhani, s., shahbaz, m., arouri, m. (2013), panel analysis of co2 emissions, gdp, energy consumption, trade openness and urbanization for mena countries. mpra paper 49258. farhani, s., mrizak, s., chaibi, a., rault, c. (2014), the environmental kuznets curve and sustainability: a panel data analysis. energy policy, 71, 189-198. fiedl, b., getzner, m. (2003), determinants of co2 emissions in a small open economy. ecological economics, 45, 133-148. fodha, m., zaghdoud, o. (2010), income and environmental degradation in tunisia: an empirical analysis of the environmental kuznets curve. energy policy, 38, 1150-1156. galeotti, m., manera, m., lanza, a. (2009), on the robustness of robustness checks of the environmental kuznets curve hypothesis. environment and research economic, 42(4), 551-574. ghosh, s. (2010), examining carbon emissions economic growth nexus for india: a multivariate cointegration approach. energy policy, 38, 3008-3014. grossman, g., krueger, a. (1991), environmental impacts of a north american free trade agreement. national bureau of economics research working paper, no. 3194. cambridge: nber. gurgul, h., lach, ł. (2011), the role of coal consumption in the economic growth of the polish economy in transition. energy policy, 39, 2088-2099. gurgul, h., lach, ł. (2012), the electricity consumption versus economic growth of the polish economy. energy economics, 34(2), 500-510. halicioglu, f. (2009), an econometric study of co2 emissions, energy consumption, income and foreign trade in turkey. energy policy, 37, 1156-1164. hamit-haggar, m. (2012), greenhouse gas emissions, energy consumption and economic growth: a panel cointegration analysis from canadian industrial sector perspective. energy economics, 34, 358-364. he, j., richard, p. (2010), environmental kuznets curve for co2 in canada. ecological economics, 69(5), 1083-1093. herrala, r., goel, r.k. (2012), global co2 efficiency: country-wise estimates using a stochastic cost frontier. energy policy, 45, 762-770. holtz-eakin, d., selden, t.m. (1995), strokingthe fires: co2 emissions and economic growth. journal of public economy, 57(1), 85-101. hossain, m.s. (2011), panel estimation for co2 emissions, energy consumption, economic growth, trade openness and urbanization of newly industrialized countries. energy policy, 39, 6991-6999. international energy agency. (2014), world energy investment outlook report. france: international energy agency. jalil, a., mahmud, s.f. (2009), environment kuznets curve for co2 emissions: a cointegration analysis. energy policy, 37, 5167-5172. jayanthakumaran, k., verma, r., liu, y. (2012), co2 emissions, energy consumption, trade and income: a comparative analysis of china and india. energy policy, 42, 450-460. kraft, j., kraft, a. (1978), on the relationship between energy and gnp. journal of energy and development, 3, 401-403. lean, h.h., smyth, r. (2010), co2 emissions, electricity consumption and output in asean. applied energy, 87, 1858-1864. liddle, b., sidney, l.s. (2010), age-structure, urbanization, and climate change in developed countries: revisiting stirpat for disaggregated population and consumption-related environmental impacts. population and environment, 31, 317-343. m’henni, h. (2005), economic development, adjustment and environmental quality: the case of tunisia for a contingent valuation study. mediterranean journal of economics, agriculture and environment, ivn(2), 342-349. méon, p.g., sekkat, k. (2004), does the quality of institutions limit the mena’s integration in the world economy? the world economy, 27, 1475-1498. narayan, p.k., narayan, s. (2010), carbon dioxide emissions and economic growth: panel data evidence from developing countries. energy policy, 38, 661-666. narayan, p.k., smyth, r. (2008), energy consumption and real gdp in g7 countries: new evidence from panel cointegration with structural breaks. energy economics, 30, 2331-2341. newman, p., kenworthy, j. (1989), cities and automobile dependence: a sourcebook. monograph. uk: gower. oh, w., lee, k. (2004), causal relationship between energy consumption and gdp: the case of korea 1970-1999. energy economics, 26, 51-59. omri, a. (2013), co2 emissions, energy consumption and economic growth nexus in mena countries: evidence from simultaneous equations models. energy economics, 40, 657-664. oscan, b. (2013), the nexus between carbon emissions, energy consumption and economic growth in middle east countries: a panel data analysis. energy policy, 62, 1138-1147. ozcan, b. (2013), the nexus between carbon emissions, energy consumption and income in middle east countries: a panel data analysis. energy policy, 62, 1138-1147. ozturk, i. (2010), a literature survey on energy-growth nexus. energy policy, 38(1), 340-349. ozturk, i., acaravci, a. (2012), the long-run and causal analysis of energy, awad: income-carbon emissions nexus for mena countries: a semi-parametric approach international journal of energy economics and policy | vol 7 • issue 2 • 2017 159 growth, openness and financial development on carbon emissions in turkey. energy economics, 36, 262-267. ozturk, i., al-mulali, u. (2015), investigating the validity of the environmental kuznets curve hypothesis in cambodia. ecological indicators, 57, 324-330. pao, h.t. (2009), forecast of electricity consumption and economic growth in taiwan by state space modelling. energy, 34, 1779-1791. saboori, b., soleymani, a. (2011), co2 emissions, economic growth and energy consumption in iran: a cointegration approach. international journal of environment and society, 2(1), 44-53. saboori, b., sulaiman, j., mohd, s. (2012), economic growth and co2 emissions in malaysia: a cointegration analysis of the environmental kuznets curve. energy policy, 51, 184-191. selden, t.m., song, d. (1994), environmental quality and development: is there a kuznets curve for air pollution emissions? journal of environmental economics and management, 27(2), 147-162. shahbaz, m., ozturk, i., afza, a., ali, a. (2013), revisiting the environmental kuznets curve in a global economy. renewable and sustainable energy reviews, 25, 494-502. soytas, u., sari, r. (2009), energy consumption, economic growth, and carbon emissions: challenges faced by an eu candidate member. ecological economics, 68, 2706-2712. soytas, u., sari, r., ewing, b.t. (2007), energy consumption, income, and carbon emissions in the united states. ecological economics, 62, 482-489. stern, d.i. (2000), multivariate cointegration analysis of the role of energy in the u.s. macro economy. energy economics, 22, 267-283. stern, d.i. (2002), explaining changes in global sulfur emissions: an econometric decomposition approach. ecological economics, 42, 201-220. stern, d.i. (2004), the rise and fall of the environmental kuznets curve. world development, 32, 1419-1439. tamazian, a., rao, b.b. (2009), do economic, financial and institutional developments matter for environmental degradation? evidence from transitional economies. eeri research paper series no. 02/2009. tiwari, a.k., shahbaz, m., hye, m.q.a. (2013), the environmental kuznets curve and the role of coal consumption in india: cointegration and causality analysis in an open economy. renewable and sustainable energy reviews, 18(3), 519-527. toda, h.y., philips, p.c.b. (1993), vector auto regressions and causality. econometrica, 61, 1367-1393. wang, y., han, r., kubota, j. (2016), is there an environmental kuznets curve for so2 emissions? a semi-parametric panel data analysis for china. renewable and sustainable energy reviews, 54, 1182-1188. wang, y., zhang, x., kubota, j., zhu, x., lu, g. (2015), an empirical study of the environmental kuznets curve for environmental quality in gansu province. ecological indicators, 56, 96-105. wodon, q.a., liverani, g.j., bougnoux, n. (2014), climate change and migration: evidence from the middle east and north africa. washington, dc: the world bank. yang, h.y. (2000), a note on the causal relationship between energy and gdp in taiwan. energy economics, 22(3), 309-317. york, r., rosa, e.a., dietz, t. (2010), ecological modernization theory: theoretical and empirical challenges. in: redclift, m.r., woodgate, g., editors. the international handbook of environmental sociology. 2nd ed. cheltenham, uk: edward elgar. yu, e.s.h., hwang, b.k. (1984), the relationship between energy and gnp: further results. energy economics, 6(3), 186-190. zarzoso, i.m., morancho, a.b., lage, r.m. (2007), the impact of population on co2 emissions: evidence from european countries. environmental resources economics, 38, 497-512. zhang, x.p., cheng, x.m. (2009), energy consumption, carbon emissions, and economic growth in china. ecological economics, 68, 2706-2712. zhua, h., you, w., zeng, z. (2012), urbanization and co2 emissions: a semi-parametric panel data analysis. economic letter, 117, 848-850. . international journal of energy economics and policy | vol 8 • issue 4 • 2018338 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(4), 338-346. investigating volatility in saudi arabia crude oil prices and its impact on oil stock market shu tong1, mohammed majdy m. baslom2*, hussain zaid h. alsharif3, 1business school, hunan university, changsha, china, 2business school, hunan university, china, & ministry of education, saudi arabia, 3business school, hunan university, changsha, china, & ministry of education, saudi arabia. *email:baslom.m@hotmail.com abstract this study is the evidence of a research that was carried out to investigate the impact of oil price volatility on oil stock markets in the context of saudi arabia. prior studies have measured the impact of crude oil price (cop) volatility on stock market performance but not much attention has been paid on saudi arabia. this study was an attempt to fill this research gap by finding any linkages between crude oil price and saudi stock market performance. the study also aimed to identify such structural changes in the crude oil market during a given time period caused by varying factors such as old and new financial investors, emergence of new markets, socio-political events and fluctuation in demand-supply ratios causing changes in the crude oil price significantly. often it has been observed that when new participants enter the oil market, there are structural changes in the process of crude oil price setting, much similar to the process in any kind of financial markets. the role of opec in setting oil prices shall also be studied during the course of this study. prior studies have revealed that lack of opec spare capacity has caused serious large imbalances in the crude oil prices worldwide as opec historically has been a major policy maker on the supply side. in order to carry out such a study, different models/methods can be used including markov regime switch method and garch and granger causality method. however, the choice of model will depend on properties/variables. keywords: oil price, demand supply ratios, volatility, stock market jel classifications: e39, j20, r53 1. introduction crude oil is one of the most important raw materials of most industrialized nations. it generates heat, drives machinery, vehicles and airplanes. almost all chemical products, such as plastics, detergents, paints, and even medicines can be produced by the components of crude oil. hence, oil has a great impact on the world economy and therefore oil price is the most important concern of world economists. there was a drastic change in crude oil prices (cops) after the 1973 oil sanctions imposed by the organization of arab petroleum exporting countries. until that time, the us oil prices had started showing low volatility across big time intervals due to an indigenous regulatory structure of the oil industry (hamilton, 1983). however, after 1973, a nonlinearity and unprecedented volatility could be seen which was characteristic of the demandsupply disruptions caused by various factors like growth of the asian markets and increase in energy consumptions, competition among the oil exporting nations resulting in a decline in oil prices to maintain their position and attempt to bring stability in their oil revenues. a good example of the decline in oil prices and how the oil prices affect the country’s terms of trade can be seen in the case of canadian economy. canada is among the net oil exporter nations, with oil being its major source of domestic income. though oil and gas extraction in canada accounts for only 6% of canadian gross domestic product (gdp), it amounts to about 30% of its total business investment. but in 2014, with the decline in the oil price, and in the absence of any alternative fiscal remedy, the canadian gdp fell down by 2%. as a remedial measure, the bank of canada decreased interest rates twice in 2015 to help the economy adjust to lower oil prices. this example shows that there are several such structural factors that can potentially change the direction of the oil based economy. a positive direction is however taken in us by introducing technological innovation in the shale oil extraction. the novel techniques adopted in the us would slowly spread in other parts of the world which could boost oil production and contribute to bring stability in oil prices. however, there are two principal tong, et al.: investigating volatility in saudi arabia crude oil prices and its impact on oil stock market international journal of energy economics and policy | vol 8 • issue 4 • 2018 339 channels by which volatility in oil prices can affect stock market prices (narayan and narayan, 2010). first, oil volatility can make an impact on production costs, affecting both earnings and stock dividends. second, oil prices can also make an impact on inflation rate and the real interest rate (huang et al., 1996). gogineni (2010) reported a positive effect on stock prices when there is a change in aggregate demand for crude oil, but a negative affect when there is a change in aggregate supply. in net oil importing countries, e.g., canada, an increase in oil price also affects exchange rates and inflation which may cause central banks to raise interest rates. however, once the capacity of producing crude oil increases, the competitive fringe enters in among the nations which have no relation with its capacity to produce crude oil. the competitive fringe is mainly for commercial reasons and for keeping a control of the oil market. this can happen in two ways: first, by reducing the production costs; second, by reducing the gap between oil price volatility. both these elements play a major role in the oil price decline and will be discussed in this study. evidence will be drawn that when a nation depends on crude oil revenue there are bound to be price fluctuations leading to high instabilities to the nation’s economy. likewise, with the emergence of new technologically advanced resources such as shale oil in the united states and ecofriendly policies has further led to depreciations in cops. this will also be discussed in this study. 1.1. crude oil situation in saudi arabia historically, saudi arabia has relied heavily on crude oil as a main source of revenue, which accounts for nearly 70% of the country’s budget revenues. however, with the collapse in crude oil prices resulting in budget deficit in 2013, the saudi government has set several measures to revamp the economy. one of the alternatives is also to reorient the economy and break its dependence on oil revenues. the crude oil situation has so weakened in saudi arabia that the government is seriously contemplating to partially privatize state-owned oil and gas major, saudi aramco with a minimum of 5% of its shares listed in the tadawul saudi stock exchange (walid, 2018). the year 2017 for saudi arabia was an economic nightmare. the economy was in decline with gdp deteriorated to a mere 0.7% consumer inflation on its worst ever negative figure (alekhina and yoshino, 2018); credit growth on decline for the whole year, and like – all partly due to the lower oil prices and the government’s subsequent decision to cut off salaries and government expenditures. the drop in crude oil prices also proved kingdom’s worst economic slowdown since global financial crisis. however, with oil markets improving in last few months of 2017, and government spending in q4 2017, few demand indicators have started to improve. the pmi index started to move up consistently, while non-oil gdp growth also was on the up move. the year 2018 has begun on a positive note, with the international monetary fund (imf) increasing its estimate of gdp growth to 1.6% from 1.1% earlier. in energy context, the term volatility is defined as “the pace at which prices rise or fall sharply within a period of time” (ogiri et al., 2013). another aspect of price volatility is that there occur huge losses or gains to oil producing, oil importing and oil exporting nations, particularly when their economies are dependent on the oil leading to economic instability. similarly, oil volatility also results in huge losses or gains to independent investors when they are confronted with greater uncertainty of the oil stock market (salisu and fasanya, 2012). during the last two decades, oil prices have fluctuated sharply with up to 60% decrease in prices. such a sharp decline has also affected the macro-economic variables such as the energy and stock market. the developing countries have in the past faced huge disasters such as what happened after the second world war when oil volatility played a major role in the us recession because the sharp increase in crude oil prices had a negative correlation with the us real gnp growth (hamilton, 1983). moreover, the crash of the stock market in 1987, the invasion of kuwait by iraq in 1992, the currency disaster in east asia in 1997 are a few other examples of world’s financial crises which are directly or indirectly linked with oil prices. recently the gulf unrest can also be attributed to volatility of oil prices and its impact on oil stock market. moreover, the volatility in oil price is also responsible for extra space storage (exr) affecting the stock market. recently, the global financial markets are facing severe crises related to asset value loss and share price fluctuations leading to stock market declines. a need is therefore felt to investigate and estimate factors of cop volatility and the impact on oil stock market performance in saudi arabia. the rational of taking a study of this nature is that no due attention has been given to saudi arabia crude oil price situation and its impact on saudi stock market. 1.2. saudi oil stock exchange (tadawul) the saudi stock exchange, or tadawul as it is called, has 180 listed companies including merely four oil companies, despite being the dominant sector. the tadawul all share index (tasi) determines the stock market index tracking the performance of all companies listed on the saudi stock exchange. tadawul is currently open only to domestic investors and gcc-nationals. direct foreign access is unavailable and investors can invest only through exchange-traded funds and swaps via member trading firms. in 2015, capital market authority (cma), the regulator of the saudi capital market, permitted foreign institutional investors to invest in saudi stocks and a regulatory framework would be finalized to facilitate foreign presence in saudi stock exchange. the conditions for such foreign investors who wanted to participate in the saudi stock exchange were kept very stringent, e.g., only established institutional foreign investors were allowed to invest provided they have been in business for at least 5 years and possess assets worth value at least $5 billion. the door was closed for individual investors. after the inclusion of saudi arabia in msci and ftse indices later in 2018, foreign institutional investments would be on rise in saudi equity markets. another landmark event would be the aramco ipo in 2018. the reason for taking such policy initiative was that tasi had been facing a consistent volatility every year having fallen by 15%, and a negative average annual return of −3.7% ever since tong, et al.: investigating volatility in saudi arabia crude oil prices and its impact on oil stock market international journal of energy economics and policy | vol 8 • issue 4 • 2018340 2014 when oil prices started to fall. saudi arabia’s tadawul index is not only the region’s largest equities market, but it is also one of the most diverse, consisting of close to 180 stocks across a range of sectors. while financials and materials combine to comprise over half the market, listed companies span a variety of sectors, such as telecom services and real estate, making it more representative of the real economy compared to regional peers. while saudi arabia constitutes more than 50% of the s and p pan arab composite large midcap index with an average daily liquidity of us$885 million, sell-side coverage remains low and is limited to approximately 55% of listed entities saudi arabia’s stock market is retail investor dominated, constituting over 70% of daily trading activity. one of the key pillars of the saudi arabian government’s plan is the privatization of state assets, the proceeds of which it would use to fund non-oil investments. for instance, the government is set to partially privatize aramco-saudi arabia’s national oil company-this year, in what could be the world’s biggest initial public offering. a dual listing in riyadh and an international stock exchange is currently expected. additionally tadawul all share index (tasi) tasi’s possible inclusion to ftse and msci indices would also help the index to improve. in 2017, tasi performed better than most of its gcc peers, except kuwait and bahrain. while oil price volatility played a part in affecting equity market performance, the rise in geopolitical tensions also played a significant role in stock performance. one of the major landmark events for saudi arabian equity market to look forward to in 2018 would be its possible inclusion in ftse and msci emerging market benchmark indices. the formal inclusion in these indices would lead to global asset management firms to increase their exposure to saudi arabian equities in order to align their portfolios to these benchmarks. while the possible inclusion of saudi arabia in the benchmark indices has been on the cards since 2015, it is only now that the developments are accelerating towards actual inclusion. in case of ftse indices, during its review in september 2017 country classification annual review, the index provider refrained from adding saudi arabia, while also expecting that it expects the country to soon meet the criteria to be promoted from unclassified status to secondary emerging market. the inclusion of saudi arabia is expected to lead to passive fund inflows, presuming saudi arabia has 2.7% weight in the index, as per analyst estimates. the estimated weight is excluding possible aramco listing, which could increase saudi arabia’s weight in the index to close to 5%. with respect to msci, in june 2017, saudi arabia was added to its watch list for a potential upgrade in june 2018. if the upgrade materializes, the actual inclusion of saudi arabia in the msci emerging market index would happen in two phases – in may 2019 and august 2019. the inclusion of saudi arabia is expected to lead to active fund inflows in to its equity market up to an estimated usd 9 billion; presuming saudi arabia has 2.4% weight in the index, as per msci indications. the weight would be distributed across 32 saudi stocks, excluding aramco. with aramco, saudi arabia’s weightage would nearly double to close to 5% in the benchmark index. saudi arabia has been vying for inclusion in benchmark indices since 2015, as part of larger plan of diversification of the economy and ensuring a vibrant capital market as a key feature of the economy. it has taken a series of steps to pursue its goals. the market was opened to qualified financial investors (qfis) to directly take stake in listed equities, in 2015. the permitted stake, in individual companies and in the market as whole, has been gradually increased. the qualification criteria, such as minimum assets under management (aum), have also been progressively relaxed. qfis have been now allowed to participate in ipos. while qfis have been allowed to take stakes in saudi arabian listed companies up to 49% of equity, the actual percentage holding has been quite low so far. the inclusion in benchmark indices would lead to net inflows of funds in to saudi equities, similar to the inflows witnessed in case of uae and other gcc countries at the time of their inclusion in benchmark indices. last, but not the least, steady oil prices are seen as critical to the share sale. saudi arabia is spearheading production cuts among opec and other oil exporters in order to shrink global crude stockpiles, which supports prices. 1.3. oil price volatility and risk factors during past few decades energy and oil sectors have contributed drastically in the economic growth of oil exporting and importing countries. it is not the oil reserves or the number of oil wells under the possession by an oil producing nation, but the oil prices that now are the determining risk factors to minimize or maximize the economic stature of any country. the oil price volatility also affects macroeconomic factors such as direct earnings and growth rates, equity risk premiums, inflation, transportation polices and discount rates which concurrently affect cash flows in stock valuation models. this phenomenon is aptly supported by capital asset pricing model theory which postulates a positive relation between risk and the oil prices and its impact in the stock market behavior (al shubiri and jamil, 2018). the main argument of this theory is that volatility in oil prices affects oil importers as well as oil exporters. in the case of oil importers, the oil price shocks affect only the production costs; but oil exporter countries not only have to face the oil price fluctuations directly on their revenues but suffer indirectly over their overall government budget revenues (mohanty et al., 2013). thus energy price volatility not only causes macro-economic fluctuations, but also affects the fiscal and monetary matters of a country’s economy. owing to high energy density and convenience of extraction, transportation and refining, oil has been a major source of energy of many nations. until the 1990s, opec was playing a major role in determining oil pricing, which was mainly dependent on supply factors. but gradually, because of the rapid economic growth in asia, the energy sector multiplied and began to be controlled by non-opec oil suppliers in countries like india and china which had maximum energy consumption. due to an increased demand in oil there was a diversification in the supply side. eventually opec lost control in price determination as well as in keeping a control on oil exports. with this change in demand-supply coordination, there also arose a risk of oil price volatility (yoshino and alekhina, 2016), tong, et al.: investigating volatility in saudi arabia crude oil prices and its impact on oil stock market international journal of energy economics and policy | vol 8 • issue 4 • 2018 341 particularly in those oil exporting nations where oil occupied a significant share in total export and contributed to the government budget. moreover, the oil market volatility is much more grievous than other commodities due to low price elasticity in oil supply and demand. this results in a wider fluctuation in the oil prices, directly impacting the oil exporters’ economies, as they depend much on oil export revenues. any untoward happening becomes a major factor of deterioration of economy as was in the case of brent crude oil prices that resulted in the fall of the gdp of an energy exporting country (figure 1). this shows how the country’s gdp is affected with the rise and fall in the brent oil price during the period 1993-2016. similarly, figure 2 shows how socio-political events worldwide were responsible for oil price fluctuations. the illustration is an evidence to show how prices of three different oil grades (opec, brent and urals) are highly correlated and face the same impact of the events (figure 2). this is also an indication how a decline in oil prices can put severe pressure on any government’s budget and macro-economy of an energy exporting country. in such a situation, risk management becomes more imperative. it becomes necessary to identify such means that allow nations to regain their economy by bringing in coordination between risk factors and oil prices. 2. literature review there are studies that have examined the oil price volatility and its impact on stock markets of nigeria, vietnam, oman, malaysia, indonesia, russia, india and other european and american countries (jones and kaul,1996; sadorsky,1999; papapetrou, 2001; maghyereh, 2004; olomola and adejumo, 2006; park and ratti, 2008; yoshino and alekhina, 2016; narayan and narayan, 2012; arouri and nguyen, 2010; asaolu and ilo, 2012; cong et al., 2008; ito, 2012; ono, 2011; berk and aydogan, 2012; ogiri et al., 2013; al shubiri and jamil, 2018; abidin, and haseeb, 2018). all these studies have utilized simple regression models and reported that the stock returns for major countries of the world were negatively impacted by oil prices. their findings suggest that oil prices and stock returns have a negative relationship in short-term. in other words, these studies are the evidence of the phenomenon that higher oil prices lead to lower stock returns. in order to study the figure 1: nominal gross domestic product and brent oil rice 1993-2016 source: federal reserve economic data figure 2: opec basket, brent crude, and urals oil prices, 2000-2014 showing impact of the worldwide events data source: us energy information administration and institute of energy economics, japan ieej tong, et al.: investigating volatility in saudi arabia crude oil prices and its impact on oil stock market international journal of energy economics and policy | vol 8 • issue 4 • 2018342 causality from the stock market returns to the oil market and vice versa, these studies also used various models such as var model, regime-switching model, johansen test and vector-error-correction model. these studies have also not used the methods identified for the current study, which is another rational for carrying out an empirical study of this nature. the relationship between oil prices and stock markets is although a much researched area but not much attention has been paid on oil price volatilities and the stock market returns. in the saudi context, the reason was that prior studies did not differentiate oil-exporting countries from oil-importing countries when volatility in oil prices was discussed (hammoudeh and aleisa, 2004). had that difference been maintained, the impact scenario of oil stock markets in terms of profitability too would have been different. hence, the main focus in the current study will be to investigate the effect of oil price volatility on stock prices and profits in developing economies (basher, 2006). however, there is a contrary view too (park and ratti, 2008) which suggests that both consumers’ and the oil firms’ behaviors affect the oil price changes which subsequently also affect the oil stock market. such issues will also be discussed in the study appropriately. hamilton (1983) significantly drew attention to energy price changes and its impact on the us economy on a number of occasions including recessions during the period 1948-1972. the relationship of oil price shocks and us stock markets is also reported by sadorsky (1999), papapetrou (2001), guo and kliesen (2005), ekong and ebong (2016), eze, (2016) and hsu and chin-chang (2017) who unanimously seem to agree that there is a negative impact of oil prices on stock market prices. however, huang et al. (1996) supported a causal impact of oil prices on stock prices and so did narayan and narayan (2010) who reported a positive long-term impact of oil prices on stock prices. hence, there exists a difference of opinion among the authors and critics as findings of one study would be refuted by the findings of the other. for this reason, a few of these studies about relationship between oil and stock market prices seem to be inconclusive and debatable. for instance, studies (prajitno, 2011; kaul and seyhun, 1990; sadorsky, 1999; sawyer and nandha, 2006; katircioglu, 2017 and okere and ndubuisi, 2017) show that high oil price volatility is responsible for creating unstable economic conditions and lowering the stock market prices. on the contrary, various other studies, for instance, jones and kaul (1996) have found evidence that international stock prices would not be affected by oil price volatility. other studies (ferderer, 1997; huang et al., 1996) have contended that in the event of oil price rise, there may be an inflation and economic recession in oil-importing countries whereas yang et al. (2002) assert that in oil-exporting countries the fall in the oil prices might be a result of political and social instability. the lehman crisis of 2008 and subsequent impact of it once again resulted in a renewed interest in oil price fluctuations and their role in macro-economic issues (hamilton 2009; hamilton 2013; yoshino and taghizadeh-hesary, 2014) and its linkages with oil shocks and price volatility. other studies (peersman and van robays, 2012; taghizadeh-hesary et al., 2016; aydoğan et al., 2017; okere and ndubuisi, 2017; ullah, et.al. 2017) found evidences of linkages between oil prices and stock markets and identified such economies that witnessed both good and bad results of oil price shocks. these studies reiterated the fact that the correlation between oil volatility and its impact on stock market depends much on the fact whether the country is an oil-exporter or an oil-importer. other studies like nguyen and bhatti (2012) and olamide et al. (2017) that examined the nexus between oil prices and stock market performance in nigeria; khai et al. (2017) that studied the impact of world crude oil prices on the vietnamese stock market have used annual time series data using the regression analysis methods. although vietnam is a crude oil exporter and a refined-oil importer, it never witnessed any shocks on its stock market until 2008, but rather grew rapidly despite regression felt in other parts of the globe. however, during the economic crisis of 2008-2012, the vietnamese oil stock market also crashed and exposed the nexus between oil prices and stock market prices. hammoudeh and aleisa (2004), in another empirical study, examined the nexus between oil prices and stock markets in gcc countries and concluded that the saudi market is the only market in the region that is predictable about future oil prices. similarly, bashar (2006) had also studied the impact of oil price change on gcc stock markets and found the saudi and omani markets enjoying the predictive power in the increase of oil price. studies on saudi arabia were found in much less number except a few that scantily discussed the issue of oil volatility and its regressive impact on oil stocks. exceptionally a study by aleisa and dibooğlu (2002) attempted to study the shocks due to oil price fluctuations in saudi arabia. their findings revealed the varying impact of real and nominal shocks. the real shocks, it was found, made a stronger influence on exchange rates in saudi arabia while nominal shocks managed the price level movement. in a similar study on gcc countries, abdelaziz et al. (2008) found that net exporting countries experienced a positive impact in the form of price rise which resulted in the increase of real national income and higher export earnings. on the contrary, this study found a negative impact in the form of high oil prices, inflation, higher input costs and reduced demand in net importing countries. these studies are the evidence that a rising volatility in crude oil prices (cops) has proved a challenge to policy makers across countries. these studies however measured the impact of cop volatility on stock market performance, but remained confined to a limited geographical region and failed to make any generalization. these are also a few studies based on oil exporting countries like saudi arabia. hence, this study aims to fill this gap in the existing literature by trying to establish the linkages between oil price and stock market performance in saudi arabia. this section on previous studies was only suggestive in order to provide evidence of the work already carried out in the subject of the current study. the main objective of this review was to prepare platform for the study. 3. theoretical framework the aim of this study is to empirically examine the relationships between crude oil prices, its volatility and the oil stock market. tong, et al.: investigating volatility in saudi arabia crude oil prices and its impact on oil stock market international journal of energy economics and policy | vol 8 • issue 4 • 2018 343 figure 3 is a technical roadmap to illustrate the theoretical framework that would be ideally suitable to this kind of study. the framework shows the key objectives along with the proposed constructs and properties for this study, as well as the methods that may be used for the study and their functions. 4. data sources and methodology for this study, annual time series panel data over the period ranging from 2007 to 2017 was used. the study eventually converted the data into a natural logarithmic equation so as to obtain elasticity of oil prices with respect to the other variables such as the volatility and the oil stock market. these variables suggested in this study were also used by some previous studies including syed and sadorsky (2006), narayan and narayan (2012); aydoğan et al., 2017 and taghizadeh-hesary et al. (2016) who have examined the relationship between crude oil prices, volatility and oil stock markets. the analytical method for this study was the regression analysis because it used 10 year time series variables. therefore, to avoid a spurious regression and study their properties and model the relationship between non-stationary series, it was necessary to examine all variables through their time plots, unit root tests and co-integration analysis. the methods suggested to be used in this study were mentioned in the theoretical framework (figure 3) and also listed in the table 1. these methods are also used in various studies including syed and sadorsky (2006), who investigated the impact of oil price volatility on emerging stock market; narayan and narayan (2012) who employed the garch method to testify cops and found that oil shocks are influenced by a long-term volatility; ciner (2001) who used granger causality test and the var model and found a statistically significant but nonlinear relationship between real stock returns and oil prices; abdalla (2012) too used the bivariate vargarch model to examine the impact of oil price fluctuations on stock market returns in saudi arabia. last, but not the least, taiwo et al. (2012) used co-integration, unit root test and error correction model (ecm) to examine the relationship between cop, stock price and macroeconomic growth to include that growth rate of gdp was significantly affected by growth rate in both oil prices and stock prices. 5. results and discussions this study has used weekly data on crude oil prices obtained from data stream 2007/01/07 to 2017/12/25. the methods used for this study were fully tested and relevant to such studies including markov switching model based, detrended moving average method, garch and granger causality method, autoregressive conditional duration model and dynamic analysis (moving windows) method. the variety of methods was used with the purpose to triangulate the data and verify their validity. this also figure 3: theoretical framework of the study table 1: methods/models and their functions testing method functions and objectives detrended moving average method fractal analysis of oil and stock time series temporal historical evolution of crude oil market in relation with oil stock market markov regime switch method to detect structural break in both time series structural detection of structural breaks in crude oil market and energy stock market garch and granger causality method to check the spillover effect on oil market spillover the relationship between crude oil price volatility and stability of energy stock market autoregressive conditional duration model to check the var or recurrence interval of risk risk management what are best risk management practices for both markets dynamic analysis (moving windows) method to establish a trading strategy for hedging out oil production risk and study its impact on stock market trading positive/negative effects of risk management on trading of oil tong, et al.: investigating volatility in saudi arabia crude oil prices and its impact on oil stock market international journal of energy economics and policy | vol 8 • issue 4 • 2018344 enabled to check the responses reaction of one model by the other and assisted in examining the dynamic behaviour of the financial and economic variables. the markov switching nonlinear model is amongst all the most popular time series models. one of the qualities of this type of model is that it involves multiple equations to characterize the time series patterns in different regimes. furthermore, the switching features of this model are governed by an unobservable state variable. this model is also different from the structural change models because it can adjust frequent changes occurring at random point of time while the structural changes models only adjust occasional and exogenous changes. therefore, markov switching model was found to be suitable to describe the correlated data that exhibit distinctive dynamic time series patterns. moreover, the weekly time series data about the variables of the crude oil sector under study exhibited a nonlinear associationas a result of which the switching regression was seen as: r gr fdvt st st t g oil g j st t h global f tf k = + + +−= −=∑ ∑τ δ ϕ ε1 1 . (1) where ε δt stn~ ( , )0 2 , the term τst represents the crude oil sector specific intercepts while δst 2 is the variance of error term for each regression. whereas, δst g represents the impact of crude oil impact on the stock market. moreover, the term st is unobserved latent variable that takes the value 1 to 2. following the empirical literature on the issue, two regimes have been specified for the state of the economy. the first regime can be considered as a stable regime while second regime is in the state of recession. the probability matrix for the unobserved latent state variable adopts the following markov chain process p p p p p = − − 11 1 22 1 11 22 (2) while the p p st and p p s stt 11 1 1 1 22 2 1 2= − =    = = − =    ; to examine the effect of changes in the oil prices on the probabilities of different regimes while taking global factors as a constant, the transition probability matrix was assumed to be taken initially constant and then time-varying following the hamilton specification. the likelihood function of unobserved latent variables, therefore, could be specified as follows. f r s i n i r c gr t t t t t st g j st t g oil f k st ( ,� := = − − − − − = − = ∑ ∑ ω 1 1 11 2 1 2πσ δ ϕ ffdv i t h global f −                                   . σ 2 (3) where the parameters of the models are ni= (σi, δi, φi, φiσi) while is the σi can be interpreted as information available at time (t). therefore, the volatile probabilities matrix in the regression is specified as follows ( ) 11 1 22 1 11 1 22 t t t t p p p t p p − = − (4) furthermore, the regime switching possibilities are time-varying while global factors and oil prices are given. in that case, the transition probabilities can be specified as in equation (5) and in equation (6). { } { } . 1 1 1 1 . 1 1 1 1 1 11 1 µ µ oil global f t t t oil global f t t exp r v p exp r v     − − − − + + = + + + (5) { } { } . 2 2 1 2 1 . 2 2 1 2 1 22 1 oil global f t t t oil global f t t exp r v p exp r v       − − − − + + = + + + (6) the results of constant markov switching model indicate that oil price shocks have been impacted greatly with different degrees of significance at different intervals. the weekly stock indices in the crude all prices are computed on continuously compounded basis , , 1 l 0 n *1 0ij tij ij t p r p −   =     while pij,t and pij,t−1 are weekly closing stock prices in sector i in week j. the results in table 2 indicate that oil prices are significantly positive in the stable regime one as wel las in regime two, which is considered to be a recessionary regime. the impact of global factors is also found significantly negative for both regimes. it implies that the crude oil stock returns are significantly influenced by the uncertainties generated by global factors. therefore, the volatility in both regimes tends to be high and significant. moreover, the significant probabilities of the values of p11 and p22 indicate that transition between specified regimes for ksa economy is stable and persistent. the results obtained and presented above partially contradict kilian and park (2009), apergis and miller (2009), basher et al. (2012), lin et al. (2014), but are consistent with those of wang et al. (2013). this phenomenon existed probably due to similar data timespan but the researcher noted a relatively low length of significant responses in the results obtained. this leads to the argument that this phenomenon might have existed because of capturing a recent year data in the sample. the present research findings would be helpful for forecasting future performance of stock market returns. this study has analysed country-specific characteristics in the crude oil market, therefore one could infer information and intuition about future market trends. the study would also assist individual firms in the decision-making process, to decide whether they should hedge the risks or not. for the investors, this study would provide useful information about how to make a diversified portfolio., it tong, et al.: investigating volatility in saudi arabia crude oil prices and its impact on oil stock market international journal of energy economics and policy | vol 8 • issue 4 • 2018 345 is also expected that such factors could be identified that lead to volatility in oil prices and make a significant impact on energy stock market. these factors will be considered as determinants of oil volatility and said to have a causal relationship between oil prices and oil stock markets. the future studies will also reveal results like structural breaks and spillover effects in oil market. however, to obtain the desired results, the stationarity of the time series will be needed to be tested before the required estimation. the tests suggested and models suggested in table 1 should be ably supported by ‘panel unit root tests’ to examine all hypotheses of the study. it is also estimated that such a study will also help to recommend best risk management practices and setting new benchmarks for oil stock market stability as well as oil trading strategies in the event of high volatility. 6. conclusion and recommendations saudi arabia is contemplating a massive public share offering for aramco, the world’s biggest oil company, on a big international stock exchange. aramco is now expected to move forward with a listing on the saudi stock exchange, with plans for an international listing boosting the market capitalization of the entire saudi stock exchange. a rebound in oil prices following the 2014 collapse of the crude market has somewhat curbed the need for such a large ipo is a positive step towards brining stability in oil market. moreover, the saudi government has extended the fiscal balance program to 2023 with the aim of balancing the budget by 2020 and focus on reviving near term economic growth. even imf has suggested to the saudi government to recalibrate the pace of fiscal reforms, so as to allow the economy to adjust to the changes introduced. accordingly, the government has revised the program with gradual movement to fiscal rebalancing by 2023. the fuel price related reforms have also been spread out over 2018 to 2023 period, with only jet fuel, benzene, diesel and electricity price revisions expected in 2018. also, as part of the program, the government has put a cap on debt-to-gdp ratio of 30% and total reserves drawdown to usd 250 bn. the saudis framed the purge as a crackdown on corruption, though some analysts said it was likely a move by bin salman to consolidate power as he embarks on an ambitious effort to reshape saudi arabia’s economy. following 3 years of soft oil prices, the saudis have drained budget surpluses and now need to return to economic growth. saudi arabia has been making a push to attract foreign investors by opening up its capital markets as the kingdom attempts to diversify the economy and reduce its dependence on oil revenue. foreign ownership has languished, however, as investors have focused on the government’s austerity push and recent domestic political changes rather than market reforms. announcements from msci and ftse russell suggest the country could be promoted to emerging markets status this year, something that will likely draw global investors. references abdalla, s.a.s. (2012), modelling stock returns volatility: empirical evidence from saudi stock exchange. international research journal of finance and economics, 1(85), 9-20. abdelaziz, m., chortareas, g., cipollini, a. (2008), stock prices, exchange rates, and oil: evidence from middle east oil-exporting countries. topics in middle eastern and african economies, 10, 1-27. abidin, i.s.z., haseeb, m. (2018), malaysia-gcc bilateral trade, macroeconomic indicators and islamic finance linkages: a gravity model approach. academy of accounting and financial studies journal, 22, 1-7. al shubiri, f.n., jamil, s.a. (2018), the impact of idiosyncratic risk of banking sector on oil, stock market and fiscal indicators of sultanate of oman international journal of engineering business management, 10(1), 1-8. aleisa, e.a., dibooğlu, s. (2002), sources of real exchange rate movements in saudi arabia. journal of economics and finance, 26(1), 101-110. alekhina, v., yoshino, n. (2018), impact of world oil prices on an energy exporting economy, monetary policy no. 828 (march 2018). tokyo: asian development bank institute. apergis, n., miller, s.m. (2009), do structural oil-market shocks affect stock prices? energy economics, 31(4), 569-575. arouri, m.e.h., nguyen, d.k. (2010), oil prices, stock markets and portfolio investment: evidence from sector analysis in europe over the last decade. energy policy, 38, 4528-4539. asaolu, t.o., ilo, b.m. (2012), the nigerian stock market and oil price: a co-integration analysis. arabian journal of business and management review, 1(5), 28-36. aydoğan, b., tunç, g., yelkenci, t. (2017), the impact of oil price volatility on net-oil exporter and importer countries’ stock markets. eurasian economic review, 7(2), 231-253. bashar, a.z. (2006), wild oil prices, but brave stock markets. the case of gcc stock markets, operational research, 6, 145-162. basher, s., haug, a., sadorsky, p. (2012), oil prices, exchange rates and emerging stock markets. energy economics, 34(1), 227-240. berk, i., aydogan, b. (2012), crude oil price shocks and stock returns: evidence from turkish stock market under global liquidity conditions (no. 12/15). ewi working paper. ciner, c. (2001), energy shocks and financial markets: nonlinear linkages. studies in non-linear dynamics and econometrics, 5, 203-212. cong, r.g., wei, y.m., jiao, j.l., fan, y. (2008), relationships between oil price shocks and stock market: an empirical analysis from china. energy policy, 36, 3544-3553. ekong, n.p., ebong, d.w. (2016), on the crude oil price, stock market table 2: the results of constant markov switching model crude oil sector parameters prob. regime one τ −0.024 0.880 δ1 0.138* 0.001 φ1 −0.021** 0.041 σ1 0.586* 0.004 regime two τ −0.067 0.678 δ1 0.340** 0.012 φ1 −0.074** 0.078 σ1 1.569* 0.006 p11 0.786 7.67d p22 0.876 17.9d log-likelihood −1104.47 q10 7.567 0.567 q2 10 5.234 0.789 τi is the constant term, the δi is the coefficients of the crude oil, φi is the global factors while σi is the volatility. the p11and p22 is the switching probabilities and dis constant expected regime duration. the **indicate the significance at 1%, 5% and 10% respectively. the q10 and q210 are the tests of autocorrelation tong, et al.: investigating volatility in saudi arabia crude oil prices and its impact on oil stock market international journal of energy economics and policy | vol 8 • issue 4 • 2018346 movement and economic growth nexus in nigeria evidence from cointegration and var analysis. asian journal of economic modelling, 4(3), 112-123. eze, t.c. (2016), re-examination of wagners hypothesis: implications for the dwindling oil revenue in nigeran economy. asian development policy review, 4(3), 74-90. ferderer, j.p. (1997), oil price volatility and the macroeconomy. journal of macroeconomics, 18(1), 1-26. gogineni, s. (2010), oil and the stock market: an industry level analysis. financial review, 45(4), 995-1010. guo, h., kliesen, k.l. (2005), oil price volatility and us macroeconomic activity. review, 87, 669-683. hamilton, j.d. (1983), oil and the macroeconomy since world war ii. the journal of political economy, 91(2), 228-248. hamilton, j.d. (2009), causes and consequences of the oil shock of 2007-08,” working papers no. 215-283. massachusetts, ma: economic activity economic studies program, the brookings institution. hamilton, j.d. (2013), historical oil shocks. in: parker, r.e., whaples, r., editors. routledge handbook of major events in economic history. new york: routledge taylor and francis group. p239-265. hammoudeh, s., aleisa, e. (2004), dynamic relationships among gcc stock markets and nymex oil futures. contemporary economic policy, 22(2), 250-269. hsu, t.k., chin-chang, t. (2017), explore the impact of the trading value, the oil price and quantitative easing policy on the taiwan and korea stock market return with quantile regression. asian economic and financial review, 7(1), 15-26. huang, r.d., masulis, r.w., stoll, h.r. (1996), energy shocks and financial markets. journal of futures markets, 16(1), 1-27. ito, k. (2012), the impact of oil price volatility on the macroeconomy in russia. the annals of regional science, 48(3), 695-702. jones, c.m., kaul, g. (1996), oil and the stock markets. the journal of finance, 51(2), 463-491. katircioglu, s. (2017), investigating the role of oil prices in the conventional ekc model: evidence from turkey. asian economic and financial review, 7(5), 498-508. kaul, g., seyhun, h.n. (1990), relative price variability, real shocks, and the stock market. the journal of finance, 45(2), 479-496. khai, h.v., sang, l.m., nguyet, p.t.a. (2017), the impact of world crude oil prices on the vietnamese stock market. southeast asia review of economics and business, 1(1), 106-115. kilian, l., park, c. (2009), the impact of oil price shocks on the u.s. stock market. international economic review, 50(4), 1267-1287. lin, c., fang, c., cheng, h. (2014), the impact of oil price shocks on the returns in china’s stock market. emerging markets finance and trade, 50(5), 193-205. maghyereh, a. (2004), oil price shocks and emerging stock markets: a generalized var approach. international journal of applied econometrics and quantitative studies, 1-2, 27-40. mohanty, s.k., akhigbe, a., al-khyal, t.a., bugshan, t. (2013), oil and stock market activity when prices go up and down: the case of the oil and gas industry. review of quantitative finance and accounting, 41(2), 253-272. narayan, p.k., narayan, s. (2010), modelling the impact of oil prices on vietnam’s stock prices. applied energy, 87(1), 356-361. narayan, s., narayan, p.k. (2012), do the us macroeconomic conditions affect asian stock markets? journal of asian economics, 23, 669-679. nguyen, c.c., bhatti, m.i. (2012), copula model dependency between oil prices and stock markets: evidence from china and vietnam. journal of international financial markets institutions and money, 22(4), 758-773. ogiri, h.i., amadi, s.n., uddin, m.o., dubon, p.p. (2013), oil price and stock market performance in nigeria: an empirical analysis. american journal of social science and management, 4(1), 20-41. okere, k., ndubuisi, p. (2017), the role of stock market development on economic growth in opec countries: does oil price movement matter? fresh evidence from nigeria. asian journal of economic modelling, 5(2), 194-207. olamide t.o., onolemhemhen, r.t., isehunwa, o. (2017), crude oil price volatility and its impact on nigerian stock market performance (1985-2014). international journal of energy economics and policy, 7(5), 302-311. olomola, p.a., adejumo, a.v. (2006), oil price shock and macroeconomic activities in nigeria. international research journal of finance and economics, 3, 28-34. ono, s. (2011), oil price shocks and stock markets in brics. the european journal of comparative economics, 8(1), 29-45. papapetrou, e. (2001), oil price shocks, stock market, economic activity and employment in greece. energy economics, 23(5), 511-532. park, j., ratti, r.a. (2008), oil price shocks and stock markets in the us and 13 european countries. energy economics, 30(5), 2587-2608. peersman, g., van robays, i. (2012), cross-country differences in the effects of oil shocks. energy economics, 34(5), 1532-1547. prajitno, o. (2011), the effect of the oil price volatility on the us stock market. thesis of department of economics. erasmus university rotterdam. sadorsky, p. (1999), oil price shocks and stock market activity. energy economics, 21(5), 449-469. salisu, a.a., fasanya, i.o. (2012), comparative performance of volatility models for oil price. conference proceeding of the 5th annual naee/ iaee (nigeria/international association for energy economics) international conference. sawyer, k.r., nandha, m. (2006), how oil moves stock prices. available at ssrn 910427. syed, b., sadorsky, p. (2006), day-of-the-week effects in emerging stock markets. applied economics letters, 13, 621-628. taghizadeh-hesary, f., yoshino, n., abadi, m.m.h., farboudmanesh, r. (2016), response of macro variables of emerging and developed oil importers to oil price movements. journal of the asia pacific economy, 21(1), 91-102. taiwo, m., abayomi, t., damilare, o. (2012), crude oil price, stock price and some selected macroeconomic indicators: implications on the growth of nigeria economy. research journal of finance and accounting, 3(2), 42-48. ullah, g.m.w., islam, a., alam, m.s., khan, m.k. (2017), effect of macroeconomic variables on stock market performance of saarc countries. asian economic and financial review, 7(8), 770-779. walid, m. (2018), saudi arabia could be emerging markets’ next rising star. available from: https://www.lazardassetmanagement.com/us/ en_us/research-insights/investment-research/saudi-arabia-couldbe-ems-next-rising-star. wang, y., wu, c., yang, l. (2013), oil price shocks and stock market activities: evidence from oil-importing and oil-exporting countries. journal of comparative economics, 41(4), 1220-1269. yang, c.w., hwang, m.j., huang, b.n. (2002), an analysis of factors affecting price volatility of the us oil market. energy economics, 24(2), 107-119. yoshino, n., alekhina, v. (2016), impact of oil price fluctuations on an energy exporting economy: evidence from russia. journal of administrative and business studies, 2(4), 156-166. yoshino, n., taghizadeh-hesary, f. (2014), monetary policy and oil price fluctuations following subprime mortgage crisis. international journal of monetary economics and finance, 7(3), 157-173. yoshino, n., taghizadeh-hesary, f. (2016), monetary policy and the oil market. japan: springer. . international journal of energy economics and policy | vol 8 • issue 5 • 2018 273 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(5), 273-280. is groningen effect still present in russia: a vector error correction approach alexander bass* department of financial markets and banks, financial university under the government of the russian federation, moscow, russia. *email: alexbass1947@gmail.com abstract in this article we aim to test the groningen effect on the example of russia. according to the groningen effect, a boom in the resource sector leads to deterioration in other sectors of the national economy due to appreciation of the national currency. this leads to, given the openness of the economy and elasticity of global markets’ prices, to a decline in manufacturing sector and a rise in the services sector. the hypothesis is tested on the example of russia. to test the hypothesis, we examine the impact of oil prices’ dynamics (brent) on different sectors of russian economy, including manufacturing, real estate services, transport and communication services over the period 1990–2016. to test the hypothesis, we use vector error correction approach and granger causality test. the results of the study show that all the sampled variables are cointegrated in the long-run, detecting dependence of the russian economy on oil. short-run effects estimation show that the groningen effect is absent in the russian economy. pairwise granger causality test confirms absence of the dutch disease as well. keywords: oil prices, gross domestic product sectors, groningen effect, cointegration, causality, dutch disease jel classifications: e01, o11, o13, q41, q43 1. introduction the rationale behind the dutch disease states that an oil boom leads to a negative effect, stemming from appreciation of the national currency, affecting economic development. dutch disease or the groningen effect states that a fast growth of oil/ gas (or other mineral resources) export leads to an increase in inflation and unemployment, a decline in manufacturing and pace of economic growth. so, the rise of oil prices in 1970s and 1980s led to the similar result in saudi arabia, nigeria and mexico. the negative effect and its negative externalities are achieved through different channels. a sudden burst of export revenues in oil sector leads to an additional inflow of foreign currency, which in turn leads to appreciation of the national currency. the last diminishes competitive position of the goods, produced in the manufacturing sector, which leads to a decline in output and export of the goods. another possible consequence of a surge in the manufacturing sector may be rising unemployment. herewith a rise in import may be observed, which leads to declining gross domestic product (gdp). moreover, a rise of income creates additional demand on both tradable goods and non-tradable goods. as tradable goods are under international competitive pressure, additional demand doesn’t significantly affect their price in case of a small open economy, while non-tradable goods, that doesn’t participate on global markets suffer rising prices on them, which increases inflation pressure in the national economy. a rise in revenues of the services sector, which doesn’t participate in the global competition, stimulates the growth. this effect may maintain the level of gdp growth, masking a decline in output of the manufacturing sector. hence, one of the main symptoms of the dutch disease is rising services sector, while manufacturing is in decline. in the long-run, a shift of investments and resources takes place, migrating from manufacturing sector to resources and services sector, showing returns above average. moreover, dependency on resources rent affects incentives and willingness to invest in manufacturing. russia, being one of the largest oil producers and exporters, may be subject to the dutch disease. one of the main symptoms of the bass: is groningen effect still present in russia: a vector error correction approach international journal of energy economics and policy | vol 8 • issue 5 • 2018274 dutch disease is steadily declining output of the manufacturing sector and growing services sector. as can be seen from figure 1, the symptoms are present in case of russia. during 2003–2016 the share of manufacturing sector in russian gdp has shrunk from 17% of total value added to 13.5%. on the other hand, the share of services sector (e.g., real estate operations) has risen up to 18% of total value added from 10.5%. another disturbing aspect of the dutch disease is pronounced through declining share of wholesale and retail trade, which indicates total economic activity for tradable goods. therefore, we aim to test the dutch disease presence in russian economy through examining causal and cointegration relationship between oil prices (brent) dynamics and value added by sampled economic sectors in russia. the remainder of the paper is organized as follows: section 2 provides an overview of relevant literature; section 3 describes econometric modeling techniques and data used; section 4 presents an analysis of empirical results; section 5 presents the conclusion of the study. 2. literature review to test the stated hypothesis, we refer to the relevant literature on the issue. as can be seen from table 1, “resource curse” hypothesis is well tested on different examples, including both developed and developing countries, resources-rich and resources poor countries, transition economies and so on. dutch disease, being a main tested subject in this paper, presents itself a specific case of resource curse problem, aimed at pointing out causes and consequences of oil boom in the national economy and its effects on economic development and economic growth in various sectors of the national economy. a brilliant overview of different approached to the dutch disease, its consequences and validity of the hypothesis is presented in papers by corden (1984) and wright and czelusta (2004). evolution of approaches and conventional views on the dutch disease is closely linked with the empirical observations. double oil hike in the 1970-s showed that in some cases a boom in the energy sector (in our case, oil sector) leads to extremely abnormal level of extracted rent in the oil segment of the national economy at the cost of declines and deterioration in other sectors of economy, especially in manufacturing sector. another effect of the dutch disease manifests itself in rising services sector. all these empirical observations found themselves best captured in the dutch disease hypothesis. table 2 presents overview of main empirical and theoretical findings, concerning the dutch disease hypothesis. as can be seen form table 2, relevant literature source may be divided in several groups. one group emphasizes and advocates importance and existence of the dutch disease or natural abundance disease in this or that way. the results of empirical investigations, presented in the second group show that dutch disease is absent in the sampled states. ambiguity of results and reasons to explain absence or presence of the dutch disease in the sampled countries is explained by institutional and political factors, which lies at heart of the papers in the third group. concerning russian case, perifanis and dagoumas (2017) find strong evidence on the oil dependence of the russian economy; however, they do not find firm established proof of the dutch disease. ito (2017) also found no strong evidence of rising oil prices affecting decline in manufacturing output. despite these results, we use a vector error correction (vec) approach on the data for the period 1990–2016, using data for sampled sectors of the national economy. 3. materials and methods 3.1. research methods to test the hypothesis about relationship between shocks in oil prices and different economic sectors of russian economy, we use econometric techniques to analyze time series. the algorithm of the ongoing study is determined by several key stages. first and foremost, one should test sampled variables on stationarity or order of cointegration, since the time series must have the same order, as can be seen from equation (1). secondly, it is necessary to determine presence/absence of correlation in long term between the variables in the equation. to check this assumption, we use a johansen cointegration test. in a case of a long-term relationship on the one hand and condition of stationarity of sampled time series in the first order i (1) on the other, it is possible to use vec model. figure 1: russian gross domestic product sectoral decomposition bass: is groningen effect still present in russia: a vector error correction approach international journal of energy economics and policy | vol 8 • issue 5 • 2018 275 author sample methodology results of the study alexeev and conrad (2009) large endowment of oil long-term economic growth regression analysis the claims of a negative effect of oil and mineral wealth on the countries’ institutions as well as on some other factors potentially affecting economic growth do not appear to be valid alexeev and conrad (2010) relationship between “point-source” resource abundance and economic growth, quality of institutions, investment in human and physical capital, and social welfare, transition economies cross-country regression analysis author find little evidence of a natural resource curse for all countries. only the “voice and accountability” measure of institutional quality is negatively and significantly affected by oil wealth. in the economies in transition, there is some evidence that natural resource wealth is associated with lower primary school enrollment and life expectancy and higher infant mortality compared to other resource rich countries bjornland (1998) norway, the uk, energy booms (oil, gas) – manufacturing output restrictred var analysis there is only weak evidence of a dutch disease in the uk, whereas manufacturing output in norway has actually benefited from energy discoveries and higher oil prices bjorvatn et al.(2012) political fractionalization -“resource curse” nexus, 30 oil-rich countries regression analysis authors find that the income effect of resource rents is moderated by the political power balance. with a strong government, resource wealth can generate growth even in an environment of poorly developed institutions, while adding oil revenues to a weak government may have damaging effects on the economy boschini et al. (2007) resource curse – institutional quality nexus, resources-rich countries regression analysis countries rich in minerals are cursed only if they have lowquality institutions, while the curse is reversed if institutions are sufficiently good. furthermore, if countries are rich in diamonds and precious metals, these effects both positive and negative are larger brunnschweiler (2008) natural resource curse hypothesis testing ols, 2 sls regression analysis in both ols and 2 sls regressions, the positive resource effects are particularly strong for subsoil wealth. results also show no evidence of negative indirect effects of natural resources through the institutional channel brunnschweiler and bulte (2008) resource abundance hypothesis testing regression analysis in multiple estimations that combine resource abundance and dependence, institutional and constitutional variables, authors find that resource abundance, constitutions and institutions determine resource dependence, resource dependence does not affect growth, and resource abundance positively affects growth and institutional quality cotet and tsui (2010) cross-country analysis, oil rent development nexus panel regression analysis exploiting cross-country variations in the timing of oil discoveries and the size of initial oil in place, authors find that, contrary to the oil-curse hypothesis, there is little robust evidence of a negative relationship between oil endowment and economic performance, even after controlling for initial income eggoh et al. (2011) relationship between energy consumption and economic growth, 21 cointegration and causality analysis there exists a long-run equilibrium relationship between energy consumption, real gdp, prices, labor and capital for each group of countries as well as for the whole set of countries. decreasing energy consumption decreases growth and vice versa, and that increasing energy consumption increases growth, and vice versa, and that this applies for both energy exporters and importers gokmenoglu et al. (2015) turkey, industrial production, gdp, inflation and oil prices nexus, 1961–2012 cointegration, causality analysis johansen co-integration results confirm a long-run relationship among these variables and granger causality test illustrates the unidirectional relationship from oil price to industrial production hutchison (1984) the united kingdom, the netherlands, norway cointegration and vec modeling results do not provide much support for the hypothesis, either for the short or longer-term horizons. only for norway do impulse response functions indicate a short-run adverse effect on manufacturing arising from the energy boom table 1: literature review (contd..) bass: is groningen effect still present in russia: a vector error correction approach international journal of energy economics and policy | vol 8 • issue 5 • 2018276 author sample methodology results of the study larsen (2006) denmark, sweden. dutch disease hypothesis testing structural break techniques norway was in a favorable position to find oil. an educated populace could start an intensely technological extraction that also gave birth to expertise build-up and innovative research. to the extent that developed countries share these qualities, it may be possible that developed countries are less likely to contract the curse. however, norway is a special case in its fervently egalitarian society that cultivates strong social norms. this may have prevented pressure from vested interests in rent seeking and allowed a centralized second, norway’s oil policy was patient, realistic, and modest prasad et al. (2007) fiji islands, 1970-2005, relationship between real gdp and oil prices time series analysis main finding is that an increase in oil has a positive, albeit inelastic, impact on real gdp, inconsistent with the bulk of the literature van wijenbergen (1984) gulf countries disequilibrium analysis higher oil revenues can be likened to a transfer putting pressure on non-oil traded goods prices and drawing resources out of the t sector. the slope of the wage indexation line determines whether classical unemployment or repressed inflation results wright and czelusta (2004) developed and developing countries, resource production economic growth description, correlation analysis the resource-curse hypothesis seems anomalous as development economics, since on the surface it has noclear policy implication but stands as a wistful prophecy: countries afflicted with the “original sin” of resource endowments have poor growth prospects. the danger of such ostensibly neutral ruminations, however, is that in practice they may influence sectoral policies. min-erals themselves are not to blame for problems of rent-seeking and corruption. instead, it is largely the manner in which policymakers and businesses view minerals that determines the outcome yaduma (2017) oecd and non-oecd oil-exporting countries, share of oil rents in gdp/per capita oil reserves aggregate/per capita income arellano–bond difference gmm method results provide evidence of the curse in non-oecd countries employing aggregate and per-capita measures of genuine income perifanis and dagoumas (2017) russian federation, oil prices gdp, industrial production index, unemployment, government expenditure, oil production var analysis, impulse response analysis authors find strong evidence on the oil dependence of the russian economy; however, they do not find firm established proof of the dutch disease rivero et al. (2017) bolivia, resource dependence economic growth, real exchange rate, 2000–2015 production function analysis, var/svar analysis results show empirical support that a positive shock in natural resource dependence increases the boom sector in natural resources and generates positive innovations in domestic demand. positive shocks in dependence on natural resources generate positive effects on real growth of economic activity ito (2017) russian federation, testing dutch disease regression analysis manufacturing output in russia is positively associated with the price of oil, though the response following an oil-price shock is marginal in the short run; manufacturing output rises slightly even in case of the appreciation of real effective exchange rate; fdi inflows contribute to the growth of manufacturing output, but not significant; an increase in government expenditures crowds out the manufacturing sector; and the government has a tight fiscal policy in response to a rise in manufacturing output fdi: foreign direct investment, gdp: gross domestic product table 1: (continued) bass: is groningen effect still present in russia: a vector error correction approach international journal of energy economics and policy | vol 8 • issue 5 • 2018 277 in case of confirmation of presence of cointegration between the variables of the sample, residuals of the equilibrium regression can be used to estimate error correction model. also based on vec model it is possible to identify short-term relationships between sampled variables. for this purpose, we would use the wald test. the final stage of constructing a model is to conduct diagnostic tests to determine validity of the model. these include testing for heteroscedasticity and serial correlation, normality and stability of the model. another tool for detecting presence or absence of the dutch disease in russian economy is pairwise granger causality test. 3.1.1. unit root test for the analysis of long-term relationships between the variables, johansen and juselieus (1990) admit that this form of testing is only possible after fulfilling the requirements of stationarity of the time series. in other words, if two series are co-integrated in order d (i.e., i (d)) then each series has to be differenced d times to restore stationarity. for d = 0, each series would be stationary in levels, while for d = 1, first differencing is needed to obtain stationarity. a series is said to be non-stationary if it has non-constant mean, variance, and auto-covariance over time (johansen and juselius, 1990). it is important to cover non-stationary variables into stationary process. otherwise, they do not drift toward a long-term equilibrium. there are two approaches to test the stationarity: augmented dickey and fuller (adf) test (1979) and the phillipsperron (p-p) test (1988). here, test is referred to as unit-root tests as they test for the presence of unit roots in the series. the use of these tests allows to eliminate serial correlation between the variables by adding the lagged changes in the residuals of regression. the equation for adf test is presented below: ∆yt=β1+β2t+ ayt-1+δ3∑∆yt-1+εt (1) where εt is an error term, β1 is a drift term and β2t is the time trend and is the differencing operator. in adf test, it tests whether a = 0, therefore the null and alternative hypothesis of unit root tests can be written as follows: ho: a = 0 (yt is non-stationary or there is a unit root). h1: a < 0 (yt is stationary or there is no unit root). the null hypothesis can be rejected if the calculated t value (adf statistics) lies to the left of the relevant critical value. the alternate hypothesis is that a < 0. this means that the variable to be estimated is stationary. conversely, we cannot reject the null hypothesis if null hypothesis is that a = 0, and this means that the variables are non-stationary time series and have unit roots in level. however, normally after taking first differences, the variable will be stationary (johansen and juselius, 1990). on the other hand, the specification of p-p test is the same as adf test, except that the p-p test uses nonparametric statistical method to take care of the serial correlation in the error terms without adding lagged differences (gujarati, 2003). in this research, we use both adf and p-p test to examine the stationarity of the sampled time series. 3.1.2. johansen co-integration test to test for presence of cointegration we apply the johansen test using non-stationary time series (values in levels). if between variables does exist a cointegration, the first-best solution would be using vec methodology (vecm) model. an optimal number of lags according to akaike information criterion for providing johansen test is determined in var space. to conduct johansen test, we estimate a var model of the following type: yt=a1yt-1+.+apyt-p+bxt+ϵt (2) in which each component of yt is non-reposeful series and it is integrated of order 1. xt is a fixed exogenous vector, indicating the constant term, trend term and other certain terms. εt is a disturbance vector of k dimension. we can rewrite this model as: ∆ = + ∆ + +∏ ∑− −= − y y v y bxt t i t ti p t1 11 1  (3) where, ∏ ∑ ∑= − ∆ = −= = +a i aii p i jj i p 1 1 , (4) if the coefficient matrix ∏ has reduced rank r < k, then there exist k × r matrices α and β each with rank r such that ∏ =αβ‘ and β‘yt is i(0). r is the number of cointegrating relations (the cointegrating rank) and each column of β is the cointegrating vector. the elements of α are known as the adjustment parameters in the vec model. johansen’s method is to estimate ∏ matrix from an unrestricted var and to test whether we can reject the restrictions implied by the reduced rank of ∏ (johansen, 1991). 3.1.3. vecm granger (1988) suggested the application of vecm in case if the variables are cointegrated in order to find short-run causal relationships. vecm, therefore, enables to discriminate between long-run equilibrium and short-run dynamics. in this sense, we employ following vecms to estimate causal linkages among the variables: ∆ = + ∆ + ∆ + ∆ + = − = − = − = ∑ ∑ ∑ ∑ lnl a a lnl a lnm a lnr i k t i i n t i i m t i i s 0 1 1 1 2 1 3 1 aa lnt ect vt i t4 1 1∆ + +− − table 2: results of individual unit root test variables adf p-p statistic prob.** statistic prob.** levels intercept 12.545 0.792 9.142 0.6743 intercept and trend 16.343 0.376 18.895 0.1434 first-difference intercept 42.991 0.0000** 51.483 0.0000** intercept and trend 33.116 0.0010** 63.435 0.0000** **denotes statistical significance at the 5% level of significance. adf: augmented dickey and fuller, p-p: phillips-perron bass: is groningen effect still present in russia: a vector error correction approach international journal of energy economics and policy | vol 8 • issue 5 • 2018278 ∆ = + ∆ + ∆ + ∆ + = − = − = − = ∑ ∑ ∑ ∑ lnm lnm lnl lnr i k t i i n t i i m t i i s β β β β0 1 1 1 2 1 3 1 ββ φ3 1 2∆ + +− −lnt ect vt i t ∆ = + ∆ + ∆ + ∆ + = − = − = − = ∑ ∑ ∑ ∑ lnr lnr lnl lnm i k t i i n t i i m t i i s η η η η0 1 1 1 2 1 3 1 ηη χ3 1 3∆ + +− −lnt ect vt i t ∆ = + ∆ + ∆ + ∆ + = − = − = − = ∑ ∑ ∑ ∑ lnt lnt lnl lnm i k t i i n t i i m t i i s    0 1 1 1 2 1 3 1 3 1 4∆ + +− −lnr ect vt i t where l international oil prices (brent), m value added by manufacturing sector, r value added by real estate services sector, t value added by transportation and communication services sector (granger, 1988). providing regression analysis of the sampled variables by modeling vecm allows us to determine the existence of substantial and statistically significant dependence not only on the values of other variables in the sample, but also dependence on previous values of the variable. however, vec model must meet the requirements of serial correlation‘s absence, homoscedasticity of the residuals and to meet the requirement of stability and normality. only in this case the results can be considered valid. 3.2. materials and data processing we test a hypothesis of relationship between oil prices shocks and value added by various economic sectors of an economy on example of russian data for the period 1990–2016. the base period is one quarter. using vecm, we set ourselves a task to determine sensitivity of different economic sectors in russia to shocks in international oil prices. data on value added by sampled economic sectors is obtained from federal service of state statistics (www.gks.ru). data on world prices of oil is obtained from the statistical database of nasdaq (www.nasdaq.com). to conduct time-series analysis, all variables were transformed into logarithms. to study sensitivity and causal linkages between the variables in the sample in short-and long-run, we turn to regression analysis, which involves the construction of vec model of certain type based on stationary time series, testing the model for heteroscedasticity of the residuals, autocorrelation. to test casual linkages between the sampled variables we use pairwise granger causality test. 4. results and discussion the first step in testing hypotheses is to test variables for the presence of unit root. for this purpose, we use standard tests adf and p-p test. results of unit root testing are presented in table 2. as can be seen from the test results of the variables for the presence of unit root in their differentiation to the first order, we can reject the null hypothesis of unit root in each of the variables. thus, the condition of stationarity at i(1) is performed, which gives us reason to test variables for cointegration. however, it is necessary to determine the optimal time lag. building a var model involves determining the optimal number of lags. in our case, the akaike information criterion equals 1. consequently, we built a model based using time lag of 4 quarters to determine the relationship in the short run. the results of the diagnostic testing of var model for heteroscedasticity of residuals, autocorrelation, serial cross-correlation, and stability are presented in table 3. as can be seen from table 4, the model is stable, heteroscedasticity and serial correlation of residuals in the model are absent. the model is used to determine the level of sensitivity of control variables to shocks in oil prices in the short run and we use it to test for stable long-run relationship, applying johansen cointegration test. results of johansen co-integration test are presented in table 4. johansen test results show the presence of cointegration between a number of equations, which allows presuming the existence of a long-term relationship between them. starting from the results of the cointegration test, we can proceed to the construction of vec model to reveal presence or absence of long-term and short-term relations between variables. the results of the model, showing the relationship between the sampled variables are presented in table 5. table 3: results of unrestricted var model diagnostic testing type of test results var residual serial correlation lm test lags lm-stat p-value 1 9.2543 0.3954 2 6.4531 0.9437 3 5.5973 0.8593 4 11.3483 0.4392 stability condition test all roots lie within the circle. var satisfies stability condition heteroscedasticity (white test) 0.6703* var residual cross correlation test no autocorrelation in the residuals **denotes acceptance of null hypothesis (ho: there is no serial correlation). *denotes acceptance of null hypothesis of homoscedasticity bass: is groningen effect still present in russia: a vector error correction approach international journal of energy economics and policy | vol 8 • issue 5 • 2018 279 as can be seen from the table 5, the value of error correction term c(1) is negative in sign and statistically significant. this suggests the existence of long-run relationship between the variables of the sample. in other words, we obtained evidence that brent oil prices and sampled economic sectors of russia are cointegrated, so that they have similar trends of movement in the long term. the c(1) shows speed of long run adjustment. in other words, this coefficient shows how fast the system of interrelated variables would be restored back to equilibrium in the long run or the disequilibrium would be corrected. given statistical significance at 5% level (p-value being <5%) and negative meaning, the system of variables corrects its previous period disequilibrium at a speed of 39.53% in four quarters (given optimal lag meaning of four quarters for ecm). it implies that the model identifies the sizeable speed of adjustment by 39.53% of disequilibrium correction in four quarters for reaching long run equilibrium steady state position. yet, we find no evidence of existence of the short-run effects coming from world oil prices to manufacturing, trade and services sector. on the one hand, long-run trends of economic sectors and oil prices are cointegrated. and dependency in the long-run exist between them, given the fact that russian economy is heavily dependent on oil revenue. yet, short-run effects on sampled sectors are absent due to the fact that russian is not a small open economy, as stated in neoliberal economic models for different states, and also due to the fact that natural currency appreciation/depreciation effects are softened by trade tariffs and protectionist policies, as well as central bank’s monetary policy. overall, the obtained results are consistent with existing empirical and theoretical results of the previous studies (e.g., ito, 2017; perifanis and dagoumas, 2017), finding no statistical or significant evidence on the presence of the dutch disease in russia. the final stage of the analysis of the model is to determine the extent of its validity. for this, it is necessary to conduct some diagnostic tests, including tests for heteroscedasticity of the residuals and serial correlation in the model. the results of these tests show that residuals are homoscedastic and serial correlation is absent. another test to check for the presence of the dutch disease is pairwise granger causality test. the results of the test are presented in table 6. as can be seen from table 6, results of pairwise granger causality test also reject the hypothesis of manufacturing sector being affected by oil prices dynamics in russia. 5. conclusion in this paper we aim to test the dutch disease presence in russian economy through examining causal and cointegration relationship between oil prices (brent) dynamics and value added by sampled economic sectors in russia. dutch disease or the groningen effect states that a fast growth of oil/gas (or other mineral resources) export leads to an increase in inflation and unemployment, a decline in manufacturing and pace of economic growth. table 4: results of johansen co-integration test hypothesized number of ce(s) eigenvalue trace statistics 0.05 critical value prob.* none* 0.9912 78.6345 29.7970 0.0002* at most 1 0.3864 12.8531 15.4947 0.5324 at most 2 0.0536 2.4345 3.8414 0.1934 at most 3 0.0312 0.9453 2.1253 0.1124 trace statistics indicate 1 cointegrating equation at the 0.05 level. *denotes statistical significance at the 5% level of significance table 5: results of ecm coefficient number coefficient meaning standard error t-statistic prob. c(1) −0.3953 434.254 3.8922 0.0009* c(2) −0.3523 0.435 7.5742 0.4509 c(3) −0. 0114 3.194 9.2471 0.8167 c(4) 0.0272 5.367 8.2149 0.7582 c(5) 0.7823 2.158 9.9134 0.9544 с(6) 574.3213 413.475 2.0166 0.0021 *denotes statistical significance. vecm: vector error correction model table 6: results of pairwise granger causality test null hypothesis observations f-statistic p-value oil prices dynamics does not granger cause manufacturing’s value added 108 0.42153 0.6608 manufacturing’s value added does not granger cause oil prices dynamics 108 2.14166 0.6020 oil prices dynamics does not granger real estate services sector’s value added 108 0.47790 0.9467 real estate services sector’s value added does not granger cause oil prices dynamics 108 0.56583 0.5296 oil prices dynamics does not granger cause trade sector’s value added 108 1.06645 0.2225 trade sector’s value added does not granger cause oil prices dynamics 108 0.51841 0.6259 oil prices dynamics does not granger cause t and c’s value added 108 1.58988 0.3600 t and c’s value added does not granger cause oil prices dynamics 108 0.65272 0.3392 *denotes acceptance of null hypothesis bass: is groningen effect still present in russia: a vector error correction approach international journal of energy economics and policy | vol 8 • issue 5 • 2018280 concerning russian case, perifanis and dagoumas (2017) find strong evidence on the oil dependence of the russian economy; however, they do not find firm established proof of the dutch disease. ito (2017) also found no strong evidence of rising oil prices affecting decline in manufacturing output. despite these results, we use a vec approach on the data for the period 1990–2016, using data for sampled sectors of the national economy. to test the hypothesis about relationship between shocks in oil prices and different economic sectors of russian economy, we use econometric techniques to analyze time series. it is necessary to determine presence/absence of cointegration in long term between the variables in the equation. to check this assumption, we use a johansen cointegration test. in a case of a long-term relationship on the one hand and condition of stationarity of sampled time series in the first order i(1) on the other, it is possible to use vec model. in case of confirmation of presence of cointegration between the variables of the sample, residuals of the equilibrium regression can be used to estimate error correction model. the final stage of constructing a model is to conduct diagnostic tests to determine validity of the model. these include testing for heteroscedasticity and serial correlation, normality and stability of the model. another tool for detecting presence or absence of the dutch disease in russian economy is pairwise granger causality test. johansen test results show the presence of cointegration between a number of equations, which allows presuming the existence of a long-term relationship between them. based on these results we construct a vec model, where the value of error correction term c(1) is negative in sign and statistically significant. this suggests the existence of long-run relationship between the variables of the sample. in other words, we obtained evidence that brent oil prices and sampled economic sectors of russia are cointegrated, so that they have similar trends of movement in the long term. yet, we find no evidence of existence of the short-run effects coming from world oil prices to manufacturing, trade and services sector. results of pairwise granger causality test also reject the hypothesis of manufacturing sector being affected by oil prices dynamics in russia. references alexeev, m., conrad, r. (2009), the elusive curse of oil. the review of economics and statistics, 91(3), 586-598. alexeev, m., conrad, r. (2010), the natural resource curse and economic transition. economic systems, 35(4), 445-461. bjornland, h.c. (1998), the economic effects of north sea oil on the manufacturing sector. scottish journal of political economy, 45(5), 553-585. bjorvatn, k., farzanegan, m.r., schneider, f. (2012), resource curse and power balance: evidence from oil-rich countries. world development, 40(7), 1308-1316. boschini, a.d., pettersson, j., roine, j. (2007), resource curse or not: a question of appropriability. scandinavian journal of economics, 109(3), 593-617. brunnschweiler, c.n. (2008), cursing the blessing? natural resource abundance, institutions and economic growth. world development, 36(3), 399-419. brunnschweiler, c.n., bulte, e.h. (2008), the resource curse revisited and revised: a tale of paradoxes and red herrings. journal of environmental economics and management, 55(3), 248-264. corden, m.w. (1984), booming sector and dutch disease economics: survey and consolidation. oxford economic papers, 36(3), 359-380. cotet, a., tsui, k.k. (2010), resource curse or malthusian trap? evidence from oil discoveries and extractions, working papers 201001, ball state university, department of economics. dickey, d., fuller, w. (1979), distribution of the estimators for autoregressive time series with a unit root. journal of american statistical association, 74, 427-431. eggoh, j.c., bangake, c., rault, c. (2011), energy consumption and economic growth revisited in african countries. energy policy, 39(11), 7408-7421. gokmenoglu, k., azin, v., taspinar, n. (2015), the relationship between industrial production, gdp, inflation and oil price: the case of turkey. procedia economics and finance, 25, 497-503. granger, c.w.j. (1988), some recent development in a concept of causality. journal of econometrics, 39, 199-211. gujarati, d. (2003), basic econometrics. 4th ed. london: mc graw-hill. hutchison, m.m. (1994). manufacturing sector resiliency to energy booms: empirical evidence from norway, the netherlands, and the united kingdom. oxford economic papers, 46(2), 311-329. ito, k. (2017), dutch disease and russia. international economics, 151, 66-70. johansen, s. (1988), statistical analysis of co-integration vectors. journal of economics dynamic and control, 12, 231-254. johansen, s., juselius, k. (1990), maximum like hood estimation and inference on co-integration with applications to the demand for money. oxford bulletin of economics and statistics, 52, 169-210. larsen, e.r. (2006), escaping the resource curse and the dutch disease? american journal of economics and sociology, 65(3), 605-640. perifanis, t., dagoumas, a. (2017), an econometric model for the oil dependence of the russian economy. international journal of energy economics and policy, 7(4), 7-13. prasad, a., narayan, p.k., narayan, j. (2007), exploring the oil price and real gdp nexus for a small island economy, the fiji islands. energy policy, 35(12), 6506-6513. rivero, r.a.b., ramirez, m.a.n., caba, l.f.e. (2017), natural resources, tradable and non-tradable sector: an exemplification with bolivia, a boom-tradable and non-tradable model. international journal of energy economics and policy, 7(5), 68-82. van wijenbergen, s. (1984), inflation, employment, and the dutch disease in oil exporting countries: a short-run disequilibrium analysis. quarterly journal of economics, 99(2), 233-250. wright, g., czelusta, j. (2004), the myth of the resource curse. challenge, 47(2), 6-38. yaduma, n. (2017), investigating the oil curse in oecd and nonoecd oil-exporting economies using green measures of income. environment, development and sustainability. https://doi. org/10.1007/s10668-017-0013-y. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 3 • 2023 507 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(3), 507-511. the effect of crude oil price and inflation on algae export in indonesia dzulfikri azis muthalib1, abd azis muthalib2*, ahmad muhlis nuryadi3, arifuddin4, la ode muhammad harafah5, murdjani kamaluddin6, la ode sahili7, muh. irfandy azis8, rince tambunan9 1universitas muhammadiyah, kendari, indonesia, 2faculty of economics and business universitas halu oleo, kendari 93232, indonesia, 3universitas muhammadiyah, kendari, indonesia, 4faculty of economics and business universitas halu oleo, kendari 93232, indonesia, 5faculty of economics and business universitas halu oleo, kendari 93232, indonesia, 6faculty of economics and business universitas halu oleo, kendari 93232, indonesia, 7sekolah tinggi ilmu ekonomi enam-enam, kendari 93121, indonesia, 8universitas borneo tarakan 77124, indonesia, 9sekolah tinggi ilmu ekonomi enam-enam, kendari 93121, indonesia. *email: azis61288@gmail.com received: 09 january 2023 accepted: 02 may 2023 doi: https://doi.org/10.32479/ijeep.14145 abstract the aim of this study is to test and analyze the long-term and short-term effects of crude oil prices and inflation on algae export in indonesia. the effects were tested using multiple cointegration regression and error correction models. furthermore, annual time series data from 2012 to 2021 was used in this study and the results of the analysis show that in the long term, crude oil price and inflation have a positive effect on algae export. while in the short term, only crude oil price positively influences its exportation. keywords: crude oil price, inflation, algae export, cointegration model, error correction model jel classifications: c32, e31, f410 1. introduction algae is one type of chlorophyll-containing plant and it is classified as a low-level plant that does not have true roots, stems, or leaves but rather it has what resembles a stem, called a thallus. algae can grow in shallow water with sandy, slightly muddy, or mixed bottom conditions. to grow, this plant usually attaches to a certain substrate, such as coral, mud, sand, stone, or other hard objects. therefore, farmers in some countries use media made of hard objects to plant algae (riyastini, 2022). economically, this plant has many benefits, including in the fields of pharmacy, agriculture, textiles, and food processing and coastal communities cultivate this commodity to improve their household economy. in connection with the improvement of welfare through algae cultivation, the government of algae-producing countries has also developed various cultivation methods, including in countries such as latin america (robledo and hayashi, 2019), indonesia (riyastini, 2022), and fiji (lal and vuk, 2010). the development of these cultivation methods is intended to increase production to meet both domestic and export needs. accordingly, the development of algae cultivation in indonesia is carried out only in areas where the commodity can thrive, such as aceh, north sumatra, jakarta, west java, central java, east java, bali, east nusa tenggara, west nusa tenggara, north sulawesi, central sulawesi, south sulawesi, maluku, and papua regions (reza et al., 2020). this development has contributed to the increase in production quantity and also exports. statista (2021) reported that indonesian algae production has shown an this journal is licensed under a creative commons attribution 4.0 international license muthalib, et al.: the effect of crude oil price and inflation on algae export in indonesia international journal of energy economics and policy | vol 13 • issue 3 • 2023508 increasing trend from 6.52 million metric tons in 2012 to 11.32 million metric tons in 2015 and then decreased to 9.66 million metric tons in 2019. nonetheless, the quantity of 2012-2019 still shows an increasing trend. the increased production level in 2019 made indonesia the second-highest algae-producing country in the world, with the highest being china. the export volume in indonesia also shows a fluctuating and increasing trend from 110134.3 usd in 2012 to 222613.8 usd in 2021. although the quantity shows an increasing trend, it does not mean that farmers do not experience obstacles in the cultivation process. these obstacles include the scarce supply of materials used which in turn causes the commodity’s price to increase (reza et al., 2020; saragi et al., 2021). study on the determinants of algae export is still limited in number. in indonesia, this study has only been conducted by denatika (2012) and saragi et al. (2021). the focusing factors are the exchange rate and gdp, but the studies employed different methods of analysis. furthermore, there has not been a study that reports the long-term and short-term effects of crude oil prices and inflation on algae export in indonesia. therefore, the aim of this study is to examine the long-term and short-term effects of crude oil prices and inflation on algae export in indonesia. to analyze the data, multiple regression cointegration models and an error correction model (ecm) were used. the two models were intended to test for the long-term and short-term effects respectively. 2. literature review as stated in the introduction, a study on the effect of crude oil prices and inflation has not been conducted. therefore, in this literature review section, only theories related to the relationship between the price of crude oil and export, as well as the relationship between inflation and export will be discussed. the indonesian country region consists of islands with a total coast length of 99,093 km, and these coastal waters have the potential for algae cultivation, as various species of algae can be cultivated in this area. according to the ministry of marine and fishery, 2019, the indonesian coastal waters have 782 algae species consisting of 196 green algae (chlorophyceae), 452 red algae (rhodophyceae), and 134 brown algae (phaeophyceae) (kementerian kelautan dan perikanan, 2019). this is a potential for the development of algae cultivation and based on this potential, according to the theory of absolute advantage, indonesia can produce enough of this commodity for exportation purposes (salvatore, 2013). oil plays an important role in the world economy, as an input in production. in manufacturing industries, oil is used to run production machines that process raw materials into finished products. likewise, in the algae industry, crude oil is used to run production machines that process raw algae into food and pharmaceuticals. in algae cultivation, farmers use crude oil to run their marine vehicles when they travel to the cultivation site. in such conditions, the rise in the price of crude oil will burden the production costs of both the manufacturing and the algae industry. economically, oil is a production factor not only in the manufacturing industry but also in the algae industry. in the context of crude oil as a production factor, faria et al. (2009) developed a mathematical model to explain the relationship between crude oil price and export using the douglas production function: y=(ωn)α oβ where ω is technology, n represents workforce, and o is the price of crude oil, while α and β are constants. the model development shows that the price of crude oil and export have a positive relationship. to prove the correctness of the model development conclusions, faria et al. (2009) used china’s export data and the monthly west texas intermediate (wti) crude oil price for the period from 1992.1 to 2005.12. the analysis, which was conducted using the autoregressive distributed lag (ardl) model, shows that crude oil prices have a positive effect on export. the effects of oil prices on exports can also be explained using the wealth effect theory as follows. indonesia is a crude oil-producing country and some of its products are exported abroad, but this country is no longer a member of the organization of petroleum exporting countries (opec) since 2008. according to the wealth effect theory, when indonesia exports oil to other countries, the country receives a wealth transfer from the importing country. with this wealth transfer, consumption expenditure will increase, which will in turn increase the gdp and economic growth (cologni and manera, 2008; abel et al. 2020). the relationship between economic growth and export can be bidirectional and positive. according to the export-led growth hypothesis, exports can drive economic growth, and vice versa, and based on the theory of comparative advantage, economic growth can positively affect exports (dodaro, 1993). furthermore, inflation can significantly impact exports through domestic interest rates and the domestic currency exchange rate against foreign currencies. as a result of monetary policy, the indonesian government through the central bank has set an inflation threshold. therefore, if inflation rises above the threshold, the central bank will raise interest rates to curb inflation. this increase in interest rates can affect exports, especially algae export, because of the exchange rate. based on the interest rate parity theory, domestic interest rates (r) are equal to the sum of international interest rates (r*) and the change in the domestic currency exchange rate against foreign currency. then, if the foreign currency is the us dollar (usd) and the domestic currency is idr, mathematically the interest rate parity theory is expressed by the equation: r r idr usd � � � � � � � � * � where � idr usd � � � � � � changes in the idr/usd exchange rate. therefore, if the increase in domestic interest rates is greater than the increase in international interest rates or (r–r*) > 0, then the muthalib, et al.: the effect of crude oil price and inflation on algae export in indonesia international journal of energy economics and policy | vol 13 • issue 3 • 2023 509 domestic interest rates will increase the � idr usd � � � � � � value or the idr domestic currency exchange rate will depreciate (pilbeam, 2006). in international trade theory, when the domestic currency depreciates, domestic goods will become cheap and can be sold abroad, and this can increase exports (ali et al., 2014). 3. data and methodology 3.1. data three variables were used in this study, namely: the crude oil price and inflation as the independent variables, and export as the dependent variable. the time series data for wti crude oil price was collected, while inflation was used to collect consumer price index time series data (the base year 2010), and the export variable was used to collect the algae export time series data. the time series data spans from 2012 to 2021 and the unit price for crude oil was usd per barrel, while the unit for algae export was usd. furthermore, the crude oil price data, consumer price index data, and algae export data were obtained from the energy information administration (eia) website, the world bank website, and the indonesian central bureau of statistics website respectively. 3.2. methodology the natural logarithm of crude oil price, inflation, and algae exports were represented by oil, inf, and exi respectively. to test the long-term effect of crude oil price and inflation on algae export, the cointegration model (asteriou and hall, 2021) was used with the equation: exi oil inf ut t t t� � � �� � �0 1 (1) equation (1) is a multiple regression equation where α0, α1, and α2 are the parameters of the regression equation, and ut is an error. error ut has assumptions, such as no autocorrelation, homoscedastic, and normally distributed. another assumption is that the variables oil and inf are not multicollinear, and are exogenous to exi. following this, to test the short-term effect of crude oil price and inflation on algae export, the model used is the ecm model (asteriou and hall, 2021) with the equation: d (exit)= β0+β1 d (oilt)+β2 d (inft)+π ect+ut (2) where β0, β1, and β2 are the parameters of the regression equation. variable d (exit) is the first differentiable variable of exit with exit=exi(0)–exi(1). coefficient π is negative and is called the error correction coefficient, meanwhile, ect is called the ecm model error correction variable. accordingly, in order to examine the long-term and short-term effects of crude oil prices and inflation on algae exports, several testing steps were carried out. the first step was to test the stationarity of the three variables of crude oil price, inflation, and algae export. the stationary test used was the phillips-perron test or simply the pp test (phillips and perron, 1998). the second step involves testing the cointegration between the crude oil price, inflation, and algae export. in this test, the engle-granger cointegration test (engle and granger, 1987) was employed and this test can only be used if the three variables, which are the crude oil price, inflation, and export, are stationary at the first difference. the steps for the engle-granger cointegration test are (i) estimate the regression equation (1) and suppose the result is: 0 1 2ˆ ˆ ˆα α α= + +y oil inf (3) (ii) generate time series ect using equation (3), where ect fulfilled equation (4) as follows. 0 1 2ˆ ˆ ˆα α α= − − +t t t tec y oil inf (4) furthermore, the stationarity test ect was performed with the pp test. if ect is stationary at the level or integrated at order 0, i(0) then it can be concluded that the crude oil price, inflation, and algae export are cointegrated or have a long-term relationship. the third step is to test the residual (error) assumptions ut, the multicollinearity assumption, and the exogeneity of the oil and inf variables. meanwhile, the autocorrelation, heteroskedasticity, and error normality were tested using the breusch-godfrey serial correlation lm (bgslm), arch, and jarque bera (jb) tests respectively. the variance inflation factor (vif) test was used to test the multicollinearity between oil and inf. the two independent variables in the model (1) do not have multicollinearity if the vif value is <10 (rawlings et al., 1998: cohen et al., 2003; doane and seward, 2011). following this, the exogeneity of the oil and inf variables was tested using the durbin-wu-hausman (dwh) test, also known as the j-statistic test. the dwh test was distributed as a chi-square with degrees of freedom df=2 (number of independent variables). the hypotheses of the dwh test are: h0: oil and inf are exogenous against exi but the alternative hypothesis indicated that: h1: oil and inf are endogenous against exi (davidson and mackkinon, 1993; ihs-markit, 2020). 4. results and discussion 4.1. results the first step in examining the long-term and short-term effects of crude oil price and inflation on algae export is to test the stationarity of all the variables using the pp test as presented in table 1. based on the data, the three variables are stationary at the first difference. table 1: results of the pp test variables level first difference intercept intercept and trend intercept intercept and trend oil −2.103300 −0.446651 −1.866325 −3.683547** inf −21.89444* −1.153438 −0.091908 −3.904522** exi −1.944209 −2.570089 −3.158795** −2.466065 *, ** significant at 1%, 10% muthalib, et al.: the effect of crude oil price and inflation on algae export in indonesia international journal of energy economics and policy | vol 13 • issue 3 • 2023510 the second step is to test the co-integration between crude oil price, inflation, and algae export by testing the stationarity of the ec variable using the pp test, as shown in table 2. the ec error correction variable was found to be stationary at the level, indicating that crude oil price and inflation are co-integrated with algae export. in other words, crude oil price and inflation have a long-term relationship with algae export. furthermore, the third step is to estimate the long-term cointegration model parameters in equation (1), and the ecm model in equation (2) using the ordinary least squares method, the estimation results are presented in table 3. in panel a, the long-term coefficient of crude oil price and inflation is positive and significant at a 1% significance level. this means that both the crude oil price and inflation have a positive impact on algae export in the long term. in panel b, the short-term coefficient of inflation is positive, but only the coefficient of crude oil price is significant. in other words, the crude oil price affects algae export in the short term but inflation does not. the final step is to test the model assumptions. from the p-value of the bgsclm, arch, and jb tests listed in table 3, it was found that the error model does not have autocorrelation, is homoscedastic, and is normally distributed. following this, the vif calculation results are shown in table 4. the vif values of the two variables, oil, and inf, are less than 10, indicating that there is no multicollinearity in the multiple regression model between crude oil price, inflation, and algae export. furthermore, the dwh test statistic (j-statistic) is 0, which is less than its critical value at a 5% significance level of 5,991. this shows that variables oil and inf are exogenous to exi. 4.2. discussion the data analysis shows that, partially, the crude oil price has a positive and significant effect on algae export in both the long and short terms. the long-term coefficient of the crude oil price variable is 0.658244, which means that for every 1 usd increase in crude oil price, algae export increases by 0.658244 usd. this result is in line with the theory presented by faria et al. (2009). the result is also consistent with the combination of the wealth effect theory (cologni and manera, 2008; abel et al., 2020) and the comparative advantage theory (dodaro, 1993) where it was stated that an increase in crude oil price leads to an increase in export. partially, inflation also affects algae export in the long term and the coefficient of the inflation variable is 2.612401. therefore, the effect of inflation on economic growth is positive, where for every 1 unit increase in the consumer price index (inflation), algae export increases by 2.612401 usd. this finding is in accordance with the combination of the interest rate parity theory presented by pilbeam (2006) and the trade theory presented by ali et al. (2014), where it was concluded that inflation drives export. lastly, according to the results, this study recommends that the indonesian government pay more attention to changes in crude oil prices and inflation when exporting algae. an increase in crude oil price and inflation indicates that algae export activities can be carried out. this is also aimed at increasing foreign exchange. 5. conclusion algae is a type of chlorophyll-containing plant that grows in coastal waters. this plant is found in almost all coastal waters of the islands in indonesia since indonesians use coastal areas for algae cultivation. due to its economic benefits, the government has been developing different cultivation methods for this plant with the aim of increasing production, as an export commodity. two previous studies have examined the effect of economic growth on algae export in indonesia. this study is a continuation of those studies, with its focus on the factors of crude oil price and inflation, which theoretically have a positive correlation with export. furthermore, in this study, the analysis models used are the multiple cointegration regression and the ecm models, each of which is useful for testing long-term and short-term effects. first, the model requirements were tested, which involves testing the stationarity of variables, crude oil price, inflation, and algae export, and the results showed that the variables were stationary in the first difference. a cointegration test was also performed, where the crude oil price and inflation were cointegrated with algae export. additionally, parameter estimation, which was carried out using the least squares method, showed that in the long and short term, crude oil price positively affects algae export. this means that an increase in crude oil price proportionally increases algae export. in the long term, inflation also positively affects algae export, meaning that an increase in inflation drives export. however, in the short term, only crude oil price positively affects algae export. table 3: estimating long and short‑term coefficients model (1) and model (2) intercept and variable independent coefficient t-statistics p-value a. long-term effect, dependent variable: exi c −3.551804 −1.145882 0.2895 oil 0.658244 3.546385 0.0094 inf 2.612401 5.087683 0.0014 f-statistic 0.004446 b. the short-term effect, dependent variable: d (exi) ec (−1) −1.232028 −3.230522 0.0232 d (oil) 0.440840 3.110576 0.0265 d (inf) 4.086888 1.680641 0.1537 c −0.051015 −0.502901 0.6364 the p values of the test statistics based on the chi-square of bgsclm, arch, and jb are 0.0966, 0.4271, and 0.734081, respectively table 2: pp test results for cointegration variables level intercept intercept and trend ec −3.784231* −2.868480 *significant at 1% table 4: vif values variable coefficient variance vif oil 0.034451 1.878596 inf 0.263657 1.878596 vif: variance inflation factor muthalib, et al.: the effect of crude oil price and inflation on algae export in indonesia international journal of energy economics and policy | vol 13 • issue 3 • 2023 511 references abel, a.b., bernanke, b.s., croushore, d. (2020), macroeconomics. 10th ed. new york: pearson education inc. ali, a.a., johari, f., alias, m.h. (2014), the effect of exchange rate movements on trade balance: a chronological theoretical review. economics research international, 2014, 1-7. asteriou, d., hall, s.g. (2021), applied econometrics. 4th ed. london: red globe press. cohen, j., cohen, p., west, s.g., aiken, l.s. (2003), applied multiple regression/correlation analysis for the behavioral sciences. 3rd ed. london: lawrence erlbaum associates publisher. cologni, a., manera, m. (2008), oil prices, inflation and ınterest rates in a structural cointegrated var model for the g-7 countries. energy economics, 30, 856-888. davidson, r., mackinnon, j.g. (1993), estimation and inference in econometrics. new york: oxford university press. denatika, d.p. (2012), analisis faktor-faktor yang mempengaruhi ekspor rumput laut dan kajian trend volume ekspor rumput laut indonesia ke china(periode tahun 1999-2011), unpublished undergraduate thesis. bogor: institut pertanian bogor. available from: https://c:/users/user/downloads/adoc.pub_analisis-faktorfaktor-yang-mempengaruhi-ekspor-ru.pdf doane, d.p., seward, l.e. (2011), applied statistics in business and economics. 3rd ed. new york: mcgraw-hill companies, inc. dodaro, s. (1993), exports and growth: a reconsideration of causality. the journal of developing areas, 27(2), 227-244. engle, r.f., granger, c.w.j. (1987), cointegration and error corrections representation: estimation and testing. econometrica, 55(2), 251-276. faria, j.r., molick, a.v., albuquerque p.h., leon-ledesma, m. (2009), the effect of oil price on china’s exports. china economic review, 20, 793-805. ihs-markit. (2020), eviews 12 user guide ii. irvine: ihs global inc. avalaible from: https://cdn1.eviews.com/eviews%2012%20 users%20guide%20ii.pdf kementerian kelautan dan perikanan. (2019), pedoman umum pemberdayaan rumput laut di indonesia. available from: https:// jdih.kkp.go.id/peraturan/a8ca8-1-kepmen-kp-2019-ttg-pedumpembudidayaan-rumput-laut-1.pdf lal, a., vuk v. (2010), the historical development ofseaweed farming, including roles of men and women, and prospects for its future development in fiji. spc women in fisheries information bulletin, 21, 11-16. phillips, p.c.b., perron, p. (1998), testing for a unit root in time series regression, biometrika, 75, 335-346. pilbeam, k. (2006), international finance. 3rd ed. london: palgrave macmillan. rawlings, j.o., pantula, s.g., dickey, d.a. (1998), applied regression analysis: a research tool. 2nd ed. new york: springer-verlag inc. reza., made, s., baso, a. (2020), analysis of the development of the export seaweed processing industry in south sulawesi. international journal of environment, agriculture and biotechnology, 5(4), 850-856. riyastini, i.a.p. (2022), seaweed for community, seaweed for conservation. denpasar: dinas perikanan dan kelautan. available from: https://diskelkan.baliprov.go.id/seaweed-for-communityseaweed-for-conservation robledo, d., alemañ, a.e., hayashi, l. (2019), development of seaweed cultivation in latin america: current trends and future prospects. phycologia, 58(5), 462-471. salvatore, d. (2013), international economics, 11th ed. danvers, united state: john wiley and son inc. saragi, a.k., burhanuddin, b., herawati, h. (2021), determinant analysis of indonesian seaweed trade. journal of integrated agribusiness, 4(1), 77-87. statista. (2021), production volume of seaweed in indonesia from 2011 to 2019. avalilable from: https://www.statista.com/statistics/1083216/ indonesia-production-volume-of-aweed international journal of energy economics and policy vol. 1, no. 4, 2011, pp.95-106 issn: 2146-4553 www.econjournals.com pulses production systems in term of energy use efficiency and economical analysis in iran alireza koocheki department of agronomy, faculty of agriculture, ferdowsi university of mashhad, mashhad, iran. e-mail: akooch@ferdowsi.um.ac.ir reza ghorbani department of agronomy, faculty of agriculture, ferdowsi university of mashhad, mashhad, iran. e-mail: reza-ghorbani@um.ac.ir farzad mondani department of agronomy, faculty of agriculture, ferdowsi university of mashhad, mashhad, iran. e-mail: fa_mo300@stu-mail.um.ac.ir yaser alizade department of agronomy, faculty of agriculture, ferdowsi university of mashhad, mashhad, iran. e-mail: yaseralizade5@gmail.com rooholla moradi, corresponding author department of agronomy, faculty of agriculture, ferdowsi university of mashhad, mashhad, iran. e-mail: roholla18@gmail.com, tel: +989364019319 abstract: energy analysis of agroecosystems seems to be a promising approach to assess environmental problems and their relations to sustainability. the aim of the present study was to compare bean, lentil, irrigated and dryland chickpea farms in terms of energy efficiency, energy productivity, benefit to cost ratio and the amount of renewable energy use. data were collected from 18 bean, 27 lentil, 24 irrigated chickpea and 46 dryland chickpea growers, using a face-to-face questionnaire during 2010. the results revealed that the total energy requirement were for bean 23666.8 mj ha-1, for lentil 14114.79 mj ha-1, for irrigated chickpea 15756.21 mj ha-1, and for dryland chickpea 2630.12 mj ha-1. the average energy input consumed in studied crops including direct, indirect, renewable and non-renewable energies in bean, lentil, irrigated chickpea and dryland chickpea farms were 67%, 33%, 30% and 70%, respectively. energy use efficiency was 1.81 for bean, 1.79 for lentil, 1.21 for irrigated chickpea and 2.78 for dryland chickpea. the benefit to cost ratios in bean, lentil, irrigated chickpea and dryland chickpea farms were 6.18, 6.15, 3.71 and 8.10, respectively. based on the results of the present study, dryland chickpea was the most efficient in terms of energy. between studied irrigated crops, bean was the most efficient both in terms of energy and economical benefit. keyword: energy productivity, net return, bean, chickpea, lentil jel classifications: o13, q1, q4 pulses production systems in term of energy use efficiency and economical analysis in iran 96 1. introduction pulses are a staple food of poor rural and urban areas especially in developing countries while they are major cash crops in developed countries. among pulses, bean (phaseolus vulgaris l.), lentil (lens culinaris l.), and chickpea (cicer arietinum l.) are the most important pulses worldwide. the cultivated area in iran was about 697000 hectares, the share of chickpea, lentil and bean are 61.13%, 21.94% and 14.26%, respectively (maj, 2009). khurasan razavi province (iran) is one of the pulse producing areas with cultivating area about 13500 ha where pulses are a main source of raw food material for many rural and urban families. today’s agricultural production relies greatly on the consumption of non-renewable energies such as fossil fuel (erdemir, 2006). consumption of fossil energy results in direct negative environmental effects through release of co2 and other burning gases (gallaher et al., 2009). nevertheless, great amounts of inexpensive fossil energy have indirect negative impacts on the environment such as less diversified nature etc. energy, economics, and the environment are commonly dependent together (refsgaard et al., 1998; pimentel et al., 1994). moreover, there is a close relationship between agriculture and energy. the productivity and profitability of agriculture depend upon energy consumption at the present. thus, looking for agricultural production methods with higher energy productivity is today as typical as it was some 20 years ago (refsgaard et al., 1998). in agroecosystems, energy requirements are classified into four groups: direct and indirect, non-renewable and renewable. direct energy is required to perform many tasks such as land preparation; irrigation, threshing, harvesting and transportation of agricultural inputs and farm products (singh, 2000). indirect energy contains the energy consumed in constructing, packaging and carrying fertilizers, biocides and machinery (ozkan et al., 2004). non-renewable energy includes diesel, chemicals, fertilizers and machinery, and renewable energy consists of human labor, water, seeds and farmyard (mohammadi et al., 2008). extensive use of direct and renewable energy enhances in energy supply and use efficiency is able to make a valuable contribution to meet sustainable energy development targets (streimikiene et al., 2007). energy consumption in agriculture has increased year by year while more intensive energy use has led to some important human health and environmental problems. it is necessary to reduce fossil energy inputs in agricultural systems. it would help to reduce agricultural carbon dioxide emissions. thus, efficient use of energy inputs has become important in terms of sustainable farming (karimi et al., 2008, rathke and diepenbrock, 2006), and is one of the principal requirements of sustainable agriculture. energy use in agriculture section has been growing in reaction to population rise, limited supply of arable land, and a demand for higher standards of living (ghasemi mobtaker et al., 2010). continuous demand in increasing food production resulted in intensive use of chemical fertilizers, pesticides, agricultural machinery and other natural resources. therefore, efficient use of energy in agriculture will also reduce environmental problems, prevent destruction of natural resources, and support sustainable agriculture as an economical production system (erdal et al., 2007). an input to output of energy analysis is used in determining the effects of production systems on environment and efficient use of energy (franzluebbers and francis, 1995). the rate of energy used in agriculture depends on environmental factors such as soil and climatic conditions, amount of inputs and techniques employed in production (fao, 2005). in developing countries like iran, agricultural growth is essential for nurturing, the economic improvement and meeting the ever-higher demands of the growing population (beheshti-tabar et al., 2010). commercial farming has replaced subsistence farming as the dominant mode of agricultural production in iran, within the past 30 years. the agricultural section is iran’s second chief employment provider and is an important contributing part to the gross domestic product (gdp). the share of agriculture in gdp was 10.87% in 2009 (maj, 2009). in recent years, with increasing world energy prices, the iranian organizations have taken steps to decrease fuel and energy consumption. rationing subsidized petrol and diesel for consumers and taking measures to enhance the efficiency of energy use to slow down the growing energy demands in all sectors of economy have been implemented. nowadays, people are getting more aware of the implications of such policies in energy use in iran (beheshti-tabar et al. 2010). many studies investigated input and output energy, and economic analysis to determine the energy efficiency of crop production, such as chickpea, irrigated and dryland wheat, barley in iran (ghasemi mobtaker et al., 2010 ;salami and ahmadi 2010; ghorbani et al., 2011), dry bean and international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.95-106 97 canola in turkey (ozkan et al., 2004; unakitan et al., 2010), rice in malaysia (bockari gevao et al., 2005), and maize and sorghum in the united states (mohammadi et al., 2008). however, no studies are published on the energy and economical analysis of pulses production in iran. because of worldwide use of pulses for food and feed, extensive knowledge is needed about energy consumption in their production systems and thereby it could enhance energy use efficiency. thus the aims of this study were (i) to determine the total amount of input-output energy used in three major pulse production systems (bean, lentil and irrigated and dryland chickpea), (ii) to analysis energy and economical use efficiency per hectare for the production of pulse systems and, (iii) to compare bean, lentil and irrigated and dryland chickpea production systems in term of energy use efficiency and economical analysis in khorasan razavi province, iran. 2. material and methods 2.1. description site study the present study was conducted in khorasan razavi province which is located northeast of iran, within 30024 and 38017 north latitude and 55017 and 61015 east longitude. total area of the province is 12842000 ha and the total farming area of bean, lentil and chickpea is 13486 ha consisting of 916 ha bean, 2245 ha lentil, 2108 ha irrigated chickpea and 8217 ha dryland chickpea. in order to determine the relation between pulse yield and energy consumption, required data were collected from growers by using a face to face questionnaire during 2010. in addition to the data obtained by surveys, previous studies of related organizations such as food and agricultural organization (fao) and ministry of agriculture of iran (maj) were also utilized during this study. the number of operations involved in the pulse production systems, and their energy requirements influence the final energy balance. a random sampling method was used, and the sample size was calculated using equation (unakitan et al., 2010). (1) where n is the required sample size, n is population volume, s is standard deviation, sx is standard deviation of sample mean (sx = d/z) , d, the permissible error in the sample size, was defined to be 10% of the mean for a 95% confidence interval and z is the reliability coefficient (1.96, which represents 95% reliability). based on the calculation the sample size were 18 for bean, 27 for lentil, 24 for irrigated chickpea and 46 for dryland chickpea farms. 2.2. energy analysis energy efficiency of agricultural system was evaluated by the energy ratio between output and input (alam et al., 2005). human labor, machinery, diesel oil, fertilizer, pesticides and seed amounts and output yield values of bean, lentil, irrigated chickpea and dryland chickpea have been used to estimate the energy ratio. energy equivalents shown in table 1 were used for estimation. the sources of mechanical energy used on the selected farms included tractors and diesel oil. the mechanical energy was computed on the basis of total fuel consumption (l ha-1) in different farm operations. therefore, the energy consumed was calculated, using conversion factors and expressed in mj ha-1 (tsatsarelis, 1991). basic information on energy inputs and also yield of bean, lentil, irrigated chickpea and dryland chickpea were transferred into excel spreadsheets, and analyzed by spss program. energy use efficiency, energy productivity, specific energy and net energy were calculated based on inputs and output energy equivalents (bockari gevao et al., 2005; ghorbani et al., 2011). (2) (3) 22 2 )1( n ssn sn x    ) ( ) ( efficiency useenergy 1 1    hamjinputenergy hamjoutputenergy ) ( ) ( crops ty productivienergy 1 1    hamjinputenergy hakgoutput pulses production systems in term of energy use efficiency and economical analysis in iran 98 (4) net energy = energy output (mj ha-1) energy input (mj ha-1) (5) indirect energy included energy embodied in seeds, chemical fertilizers (npk), herbicide (treflan and basagran), pesticide (diazinon), fungicide (carboxin) and machinery while direct energy covered human labor, diesel, electricity and water used in pulse production. non-renewable energy includes diesel, electricity, chemical pesticides, chemical fertilizers and machinery, and renewable energy consists of human labor, seeds and water. 2.3. economical analysis the economic inputs of pulses production systems contained variable costs. the variable costs of production included current costs (for example: chemicals, fuel, human labor and electricity). the economic output of pulse production systems includes grain and straw yield. all prices of input and output were market prices (average prices of the year 2010). gross and net return, total cost of production, benefit to cost ratio and productivity was calculated according to the following equations (bockari gevao et al., 2005; banaeian et al., 2011): gross return = grain and straw yield (kg ha-1) × grain and straw price ($) (6) net return = gross return ($ ha-1) total cost of production ($ ha-1) (7) benefit to cost ratio = gross return ($ ha-1) / total cost of production ($ ha-1) (8) productivity = pulse yield (kg ha-1) / total cost of production ($ ha-1) (9) table 1. energy equivalent of inputs and outputs in agricultural production particulars unit energy equivalent (mj unit−1) ref. a. inputs 1. human labor h 1.95 (taylor et al., 1993) 2. machinery h 62.7 (alam et al., 2005; ozkan et al., 2004) 3. diesel fuel l 56.30 (taylor et al., 1993) 4. chemical fertilizers (a) nitrogen kg 75.46 (taylor et al., 1993) (b) phosphate kg 13.07 (taylor et al., 1993) (c) potassium kg 11.15 (demircan et al., 2006; kousar et al., 2006; sartori et al., 2005) 5. chemicals (a) herbicides l 238.3 (taylor et al., 1993; kitani, 1999) (b) basagran l 187.8 (taylor et al., 1993; kitani, 1999) (c) pesticide l 101.2 (taylor et al., 1993; kitani, 1999) (d) fungicide kg 181.9 (taylor et al., 1993) 6. electricity kwh 3.6 (taylor et al., 1993) 7. water for irrigation m3 1.02 (ozkan et al., 2004; yamane, 1967) 8. seeds (bean) kg 14.9 (taylor et al., 1993) 9. seeds (chickpea) kg 14.7 (kitani 1999) 10. seeds (lentil) kg 14.7 (taylor et al., 1993) b. outputs 1. bean grain yield kg 14.9 (topak et al., 2005) 2. bean straw yield kg 12.5 (topak et al., 2005) 3. chickpea grain yield kg 14.7 (kitani, 1999) 4. chickpea straw yield kg 12.5 (kitani, 1999) 5. lentil grain yield kg 14.7 (taylor et al., 1993) 2. lentil straw yield kg 12.5 (taylor et al., 1993) ) (ut crops ) (input energy specific 1 1    hatputo hamjenergy international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.95-106 99 3. results and discussion 3.1. structures of farms structures of farms where pulse was produced and all essential cultural practices were determined and presented in table 2. chemicals were sprayed 3.3, 2.4, 2.8 and 1 times on bean, lentil, irrigated chickpea and dryland chickpea farms, respectively. irrigation operations were performed on average 13.7, 4.3 and 6.1 times in bean, lentil and irrigated chickpea farms. land preparation and soil tillage were frequently accomplished by a massey ferguson 28,575 hp tractor along with moldboard plow, disc harrows, land leveler (for irrigated), and chisel (for dryland). the average farm sizes were in bean 1.2 ha, in lentil 0.7 ha, in irrigated chickpea 1.1 ha and in dryland chickpea 2.9 ha. about 79.6% of total land in chickpea production was dryland and only 20.4% was used as irrigated. winter wheat, barley, cotton, corn, sorghum, tomato and alfalfa were grown along with pulse in the studied farms. the number of tractors per farm was 0.3 ha-1. other agronomic practices are shown in table 2. table 2. management practices for bean, lentil and irrigated and dryland chickpea practices/operations bean lentil irrigated chickpea dryland chickpea names of varieties derakhshan, naze robat, gachsaran jam, kermanshahi, karaj 12-60-31 jam, kermanshahi, karaj 12-60-31 land preparation tractor used: 285 mf 75 hp moldboard plow, disc harrows, land leveller moldboard plow, disc harrows, land leveller moldboard plow, disc harrows, land leveller chisel land preparation period april february february october average tilling number 2.2 2.2 2.2 1.2 planting period may march march november fertilization period (before planting) april february february ___ fertilization period (top dressing) may april april ___ average number of fertilization 2.2 1.2 1.5 ___ irrigation period may-september march-june march-july ___ average number of irrigation 13.7 4.3 6.1 ___ spraying period april-july march-may march-may may average number of spraying 3.3 2.4 2.8 1 harvesting period august-september may –june june-july may –june 3.2. input energy total energy used in different production processes for producing bean, lentil, irrigated chickpea and dryland chickpea are shown in tables 3, 4, 5 and 6. the main factors resulting in excessive energy use in irrigated chickpea were application of diesel fuel and irrigation water. however, the share of energy use of total energy for diesel and machinery were higher in dryland farms. but, the amount of energy used in different farming practices such as machinery, electricity and fertilizer in irrigated farms was higher than that of dryland farms. salami and ahmadi (2010) reported that diesel energy engrossed 37.9% of total energy, followed by chemical fertilizer 29.6% during production period in chickpea in kurdistan province of iran. asakereh et al. (2010) showed that the total energy input in organic lentil was 5062 and in non-organic lentil was 6196.5 mj ha-1 in kurdistan county of iran. pulses production systems in term of energy use efficiency and economical analysis in iran 100 table 3. energies consumed in bean farms energy quantity per unit area (ha) total energy equivalent (mj) percentage of total energy input (%) input human labor 525.90 1031.45 4.30 machinery 24.45 1533.10 6.51 diesel fuel 81.35 4086.20 17.26 nitrogen 23.00 1735.60 7.33 phosphate (p2o5) 92.00 1202.40 5.10 potassium (k2o) 25.00 275.80 1.21 herbicides 1.50 357.51 1.50 pesticide 2.00 202.40 0.87 fungicide 0.50 90.95 0.38 electricity 1400 5040.0 21.29 water for irrigation 7000 7140.0 30.16 seed 65.0 964.50 4.09 total energy input 23666.8 100.00 outputs bean grain yield 1217.50 18140.80 42.26 bean straw yield 1982.50 24781.30 57.73 total energy output 42922.00 table 4. energies consumed in lentil farms energy quantity per unit area (ha) total energy equivalent (mj) percentage of total energy input (%) input human labor 441.15 860.24 6.09 machinery 20.15 1263.40 8.96 diesel fuel 68.45 3438.24 24.36 nitrogen 23.00 1735.60 12.29 phosphate (p2o5) 46.00 601.22 4.25 potassium (k2o) 25.00 278.75 1.98 herbicides 1.00 238.00 1.68 pesticide 2.00 202.40 1.44 fungicide 0.50 90.95 0.64 electricity 520 1872.00 13.27 water for irrigation 2600 2652.00 18.79 seed 60.00 882.00 6.25 total energy input 14114.79 100.00 outputs bean grain yield 696.60 10240.02 40.50 lentil straw yield 1203.40 15042.50 59.50 total energy output 25282.52 table 5. energies consumed in irrigated chickpea farms energy quantity per unit area (ha) total energy equivalent (mj) percentage of total energy input (%) input human labor 434.55 847.37 5.37 machinery 21.55 1351.18 8.57 diesel fuel 72.85 3659.25 23.23 nitrogen 23.00 1735.60 11.01 phosphate (p2o5) 46.00 601.22 3.81 potassium (k2o) 25.00 278.75 1.77 herbicides 1.00 238.00 1.52 pesticide 2.00 202.40 1.28 fungicide 0.50 90.95 0.58 electricity 700 2520.00 16.00 international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.95-106 101 water for irrigation 3500 3570.00 22.66 seed 45.00 661.50 4.20 total energy input 15756.21 100.00 outputs chickpea grain yield 453.50 6666.45 34.86 chickpea straw yield 996.50 12456.25 65.14 total energy output 19122.70 table 6. energies consumed in dryland chickpea farms energy quantity per unit area (ha) total energy equivalent (mj) percentage of total energy input (%) input human labor 103.00 200.85 7.64 machinery 9.00 564.30 21.45 diesel fuel 29.00 1456.67 55.38 nitrogen phosphate (p2o5) potassium (k2o) herbicides 1.00 187.80 7.14 pesticide fungicide electricity water for irrigation seed 15.00 220.50 8.39 total energy input 2630.12 100.00 outputs chickpea grain yield 144.70 2127.09 29.06 chickpea straw yield 415.30 5191.25 70.94 total energy output 7318.34 3.3. output energy grain and straw yield in bean, lentil, irrigated chickpea and dryland chickpea farms were calculated and presented in tables 3, 4, 5 and 6. energy use efficiency in dryland chickpea was nearly 2.4 times more than irrigated chickpea, which could be due to using low input energy in dryland systems. therefore, our results indicate that the energy was used most efficiently in dryland chickpea, followed by bean, lentil and irrigated chickpea. among irrigated production systems, bean farms showed the highest energy use efficiency. it seems that high energy efficiency for bean was due to its high output compared to lentil and irrigated chickpea. in another study conducted by topak et al. (2009), the total energy output and energy efficiency for bean was 37250 mj ha-1 and 1.11, respectively. salami and ahmadi (2010) showed that the energy use efficiency was 1.04 in chickpea in kurdistan province of iran. mean grain yield in dryland farms was 68.18% lower than that in irrigated farms. while chickpea yield was lower in dryland farms, the energy output-input ratio was higher. in another study in iran, reported by ghorbani et al. (2011), the total energy requirement in wheat low-input systems was 9354.2 mj ha-1, whereas in wheat high-input systems it was 45367.6 mj ha-1 and energy ratio in low-input systems was 3.38, however, it was 1.44 in high-input systems. 3.4. energy production the total energy input consumed could be classified as direct (73.1%, 62.5%, 67.2% and 63.0%), indirect (26.9%, 37.5%, 32.8% and 37.0%), renewable (38.6%, 31.1%, 32.2% and 16.0%) and non-renewable (61.4%, 68.9%, 67.8% and 84.0%) energy in bean, lentil, irrigated chickpea and dryland chickpea, respectively (table 7). the share of direct energy from total energy used in the studied crops was higher than indirect energy. although, the share of direct energy in dryland chickpea farms (63.0%) was low, energy use efficiency was higher than other crops due to lack of irrigation and not using fertilizer. total energy input in dryland chickpea systems were 83.3% lower than irrigated systems. in other words, total energy input needed in dryland chickpea system was 16.7% compared to the irrigated systems. pulses production systems in term of energy use efficiency and economical analysis in iran 102 our results indicated that the share of renewable energy from the total energy used in investigated crops was lower than non-renewable energy. renewable energy in bean was higher than in other crops. it is necessary to reduce the share of non-renewable energy for achieving high energy efficiency in agricultural production systems. due to the highly mechanized agricultural systems in most area of iran, fuel consumption has risen by 10% in recent years (beheshti-tabar et al., 2010). reducing consumption of diesel fuel and fertilizer (especially nitrogen) has major effect in decreasing total energy consumption. saving in diesel by changing tillage, harvest system, and other agronomic operations could enhance field energy efficiency. moreover, using direct and local marketing crops improves profitability for growers and reduces energy needed for their transport. ghorbani et al. (2011) reported that the share of non-renewable energy (76%) in comparison with renewable energy (24%) was higher in irrigated and dryland wheat production systems in iran. beheshti-tabar et al. (2010) stated that with higher yields and improved agricultural practices in the wheat irrigated systems, the unit of land used per unit of output, reduced by 32% in 2006 compared to 1990. it can be inferred that improvement in irrigation efficiency together with the promotion of targeted application of fertilizers can have a significant effect on energy efficiency in iran agriculture. advances in irrigation will also alleviate the effect of droughts on energetic parameters. employment of more productive cultivars along with more intense crop management will cause higher outputs, and consequently lead to a higher energy ratio (ghorbani et al., 2011). table 7. total energy input in the form of direct, indirect, renewable and non-renewable energies in bean, lentil, irrigated chickpea and dryland chickpea farms. bean lentil irrigated chickpea dryland chickpea type of energy (mj ha-1) % a (mj ha-1) % a (mj ha-1) % a (mj ha-1) % a direct energyb 17297.66 73.09 8822.49 62.50 10596.63 67.25 1657.52 63.02 indirect energyc 6369.08 26.91 5292.30 37.50 5159.58 32.74 972.6 36.98 renewable energyd 9139.95 38.62 4394.24 31.13 5078.87 32.24 421.35 16.02 non-renewable energye 14526.80 61.38 9720.55 68.87 10677.34 67.76 2208.77 83.98 total energy input 23666.75 14114.79 15756.21 2630.12 3.5. energy productivity and specific energy energy input and output, energy use efficiency, specific energy, energy productivity and net energy are summarized in table 8. the highest energy use efficiency was 2.78 for dryland chickpea and the lowest was 1.21 for irrigated chickpea. average energy productivity of bean, lentil, irrigated chickpea and dryland chickpea were 0.051, 0.049, 0.029 and 0.055 kg mj-1, respectively. this means that 0.051, 0.049, 0.029 and 0.055 outputs were obtained per unit energy in bean, lentil, irrigated chickpea and dryland chickpea, respectively. calculation of energy productivity rate is documented in the literature for tomato (1.0) (esengun et al., 2007), cotton (0.06) (yilmaz et al., 2005) and sugar beet (1.53) (erdal et al., 2007). our results indicated that specific energy was higher in irrigated chickpea than other studied crops. also, net energy was 19255.2 mj ha-1 in bean which is higher than other crops. canakci and akinci (2006) reported that specific energy was 16.2 for sesame, 11.2 for cotton, 5.2 for wheat, 3.9 for maize, 1.1 for tomato, 0.98 for melon and 0.97 for water-melon in turkey. development of low-input systems with using minimum rate of fossil energy while maintaining high output of food would help to reduce carbon dioxide emissions (rathke and diepenbrock, 2006). better knowledge of fossil energy use in agricultural systems is needed in order to develop agronomic practices that allow utilizing limited energy resources more efficiently (dalgaard et al., 2001). it seems that production of nitrogen fertilizer represents the largest component of energy consumption for production among all chemical fertilizers (mclaughlin et al., 2000). traditionally, legumes have been viewed as excellent sources of nitrogen in agriculture (kinzig and socolow, 1994). crop rotations with legumes, capable for fixing atmospheric nitrogen, can maintain production levels with reduced reliance on energy intensive mineral fertilizers (rathke and diepenbrock, 2006). international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.95-106 103 table 8. energy input-output ratio in bean, lentil, irrigated chickpea and dryland chickpea farms. items unit bean lentil irrigated chickpea dryland chickpea energy input mj ha-1 23666.75 14114.79 15756.21 3630.12 energy output mj ha-1 42922.00 25282.52 19122.70 7318.34 energy use efficiency 1.81 1.79 1.21 2.78 specific energy mj kg-1 19.45 20.26 34.74 18.18 energy productivity kg mj-1 0.051 0.049 0. 029 0.055 net energy mj ha-1 19255.25 11167.73 3366.49 4688.22 table 9. economic analysis in bean, lentil, irrigated chickpea and dryland chickpea farms. cost and return components bean (value) lentil (value) irrigated chickpea (value) dryland chickpea (value) grain yield (kg ha-1) 1217.50 696.60 453.50 144.70 grain sale price ($) 0.557 0.620 0.620 0.620 straw yield(kg ha-1) 1982.50 1203.34 996.50 415.30 straw sale price ($) 0.077 0.077 0.077 0.077 gross return ($ ha-1) 830.24 524.34 357.67 121.58 gross return ($ kg-1) 0.26 0.28 0.25 0.22 gross return ($ mj-1) 0.019 0.021 0.019 0.017 total cost of production ($ ha-1) 134.42 85.18 96.48 15.18 total cost of production ($ kg-1) 0.042 0.045 0.066 0.027 total cost of production ($ mj-1) 0.003 0.003 0.005 0.002 net return ($ ha-1) 695.82 439.15 261.19 106.40 net return ($ kg-1) 0.22 0.23 0.18 0.19 net return ($ mj-1) 0.016 0.017 0.017 0.014 benefit to cost ratio 6.18 6.15 3.71 8.10 productivity (kg $-1) 9.06 8.18 4.70 9.53 3.6. economical indices production costs and gross product values are shown in table 9. total costs of production in bean were higher than other investigated crops. results of our study indicated that the total cost of production in bean, lentil, and irrigated chickpea were higher than dryland chickpea. it seems that this was due to intensive use of fuel, fertilizer, water for irrigation and electricity in irrigated chickpea. large quantities of locally available non-commercial energies, such as seed, manure and animal energy, and commercial energies directly and indirectly in form of diesel, electricity, fertilizer, chemicals, irrigation water and machinery are applied in agriculture. efficient use of these inputs helps to achieve higher production and improvement of economy stability, profitability and competitiveness of agriculture sustainability (singh et al., 2002). moreover, in recent decades, fossil resources consumption has enormously increased to achieve higher yield. utilization of fossil energies threatens soil fertility and weakens the economic independence of farmers. therefore, any positive change in energy consumption leading reducing them will bring a positive effect in agricultural ecosystems (zahid et al., 2010; schneider and smith, 2009). 4. conclusions the objective of this study was to perform an energy input-output analysis of iranian farmers’ pulse production systems. results indicate that diesel fuel, water for irrigation, machinery and electricity energies constituted the major part of energy inputs used in irrigated farms. high amount of diesel fuel consumption is due to intensive use of machinery for operations such as soil preparation, cultural practices, harvest and transportation. this is somewhat because of the small average size of pulse farms. nevertheless, our results revealed that water for irrigation was not used efficiently in the studied farms. it seems to be due to the fact that farmers applying unsuitable irrigation methods according to the scientific principles. bean, lentil and irrigated chickpea consumed a total energy of 23666.7, 14114.8 and 15756.2 mj ha-1, which was mainly due to the application of diesel fuels, water for irrigation and electricity. total energy input consumed in dryland chickpea was 2630.1 mj ha-1, which was mainly due to diesel fuel and machinery energy. with the exception of bean, the energy input in form of diesel fuels, water pulses production systems in term of energy use efficiency and economical analysis in iran 104 for irrigation and electricity had the first, secondary and third share within the total energy inputs in lentil and irrigated chickpea. energy use efficiency was 1.81 in the bean, 1.79 in the lentil, 1.21 in the irrigated chickpea and 2.78 in the dryland chickpea. although net return per ha in dryland chickpea was less than irrigated one, energy efficiency and benefit to cost ratio in dryland were much higher than irrigated systems, meanwhile, there was at least a minimum crop production in areas with water deficiency. in terms of energy use efficiency, dryland chickpea farms reflected more than 1.5, 1.6 and 2.3 times the rate compared to irrigation investigated farms, subsequently a growing trend towards higher sustainability. attaining minimum production with high energy efficiency in present market where crop prices rise rapidly and as moria et al. (2010) predicted will grow even higher in future. this seems to be essential for governments and policy makers to prevent the growth of a vulnerable food market and low income individuals. therefore, there is a need to follow a new policy persuading farmers to undertake energy efficient practices that increase crop yield without destructive natural resources. based on results of the present study, dryland chickpea was most efficient in terms of energy. other positive aspects of dryland farming in iran are reducing erosion by covering soil and minimum or no consumption of biocides and chemical synthetic fertilizers which cause lower using energy input and also more environmental friendly production systems (ghorbani et al., 2011). among the investigated irrigation crops, bean was the most efficient in terms of energy and economical benefit. references alam, m. s., alam, m.r., islam k. k. (2005). energy flow in agriculture: bangladesh. american journal of environmental sciences, 1, 213-20. asakereh, a., shiekhdavoodi, m. j., safaieenejad, m. (2010). energy consumption pattern of organic and conventional lentil in iran a case study: kurdistan county. asian journal of agricultural sciences, 2, 111-116. banaeian, n., omid, m., ahmadi, h. (2011). energy and economic analysis of greenhouse strawberry production in tehran province of iran. energy conversion and management, 52, 1020-1025. beheshti-tabar, i., keyhani, a., rafiee, s. (2010). energy balance in iran’s agronomy (1990-2006). renewable and sustainable energy reviews, 14,849-55. bockari gevao, s. m., wan ishak, w. i., azmi, y., chan, c. w. (2005). analysis of energy consumption in lowland rice-based cropping system of malaysia. sci technol, 27, 819-26. canakci, m., akinci, i. (2006). energy use pattern analyses of greenhouse vegetable production. energy, 31,1243-1256. dalgaard, t., halberg, n., porter, j. r. (2001). a model for fossil energy use in danish agriculture used to compare organic and conventional farming. agriculture, ecosystems and environment, 87, 51-65. demircan, v., ekinci, k., keener, h. m., akbolat, d., ekinci, c. (2006). energy and economic analysis of sweet cherry production in turkey: a case study from isparta province. energy conversion and management, 47, 1761-9. erdal, g., esengun, k., erdal, h., gunduz, o. (2007). energy use and economical analysis of sugar beet production in tokat province of turkey. energy, 32, 35-41. erdemir, g. (2006). energy use on organic farming: a comparative analysis on organic versus conventional apricot production on small holdings in turkey. energy conversion and management, 47, 3351-3359. esengun, k., erdal, g., gunduz, o., erdal, h. (2007). an economic analysis and energy use in staketomato production in tokat province of turkey. renewable energy, 32,1873-81. food and agriculture organization of the united sikim agzova nations (fao). (2005). agriculture production. http://faostat.fao.org/faostat. accessed 01 august 2010 franzluebbers, a. j., francis, c. a. (1995). energy output-input ratio of maize and sorghum management systems in eastern nebraska. agriculture, ecosystems and environment, 1995, 53:271-8. gallaher, m., delhotal, k., petrusa, j. (2009). estimating the potential co2 mitigation from agricultural energy efficiency in the united states. energy efficiency, 2, 207-220. international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.95-106 105 ghasemi mobtaker, h., keyhani, a., mohammadi, a., rafiee, s., akram, a. (2010). sensitivity analysis of energy inputs for barley production in hamedan province of iran. agriculture, ecosystems and environment, 137, 367-372. ghorbani, r., mondani, f., amirmoradi, s., feizi, h., khorramdel, s., teimouri, m., sanjani, s., anvarkhah, s., aghel, h. (2011). a case study of energy use and economical analysis of irrigated and dryland wheat production systems. applied energy, 88, 283-288. karimi, m., beheshti-tabar, i., khubbakht, g. m. (2008). energy production in iran’s agronomy. american-eurasian journal agricultural environ science, 4, 172-177. kinzig, a. p., socolow, r. h. (1994). human impacts on the nitrogen cycle. physics today, 47, 24-31. kitani, o. (1999). cigr handbook of agricultural engineering. vol. v., energy and biomass engineering. asae publication: st joseph: mi. kousar, r., makhdum, s. a., yagoob, s., saghir, a. (2006). economics of energy use in cotton production on small farms in district sahiwal, punjab, pakistan. journal of agricultural social sciences, 2, 219-221. maj (ministry of agriculture of the i.r. of iran). (2009). planning and economics department, statistics bank of iranian agriculture. <http://www.maj. ir/english/statistic/default.asp?p=statistic>. accessed 07 august 2010 mclaughlin, n. b., hiba, a., wall, g. j., king, d. j. (2000). comparison of energy inputs for inorganic fertilizer and manure based corn production. can j agric eng, 42, 2.1-2.14. mohammadi, a., tabatabaeefar, a., shahin, s., rafiee, s., keyhani, a. (2008). energy use and economical analysis of potato production in iran, a case study: ardabil province. energy conversion and management, 49, 3566-70. moria, s., katob, m., idoc, t. (2010). gisela-gis-based evaluation of land use and agriculture market analysis under global warming. applied energy, 87, 236-42. ozkan, b., akcaoz, h., & fert, c. (2004). energy input-output analysis in turkish agriculture. renewable energy, 29, 39-51. ozkan, b., akcaoz, h., & fert, c. (2004). energy input–output analysis in turkish agriculture. renewable energy, 29, 39-51. ozkan, b., kurklu, a., & akcaoz, h. (2004). an input-output energy analysis in greenhouse vegetable production: a case study for antalya region of turkey. biomass and bioenergy, 26,189-95. pimentel, d., herdendorf, m., eisenfeld, s., olander, l., & carroquino, m. (1994). achieving a secure energy future: environmental and economic issues. ecological economics, 9, 201-19. rathke, g. w., & diepenbrock, w. (2006). energy balance of winter oilseed rape (brassica napus l.) cropping as related to nitrogen supply and preceding crop. european journal of agronomy, 24, 35-44. refsgaard, k., halberg, n., & kristensen, e. s. (1998). energy utilization in crop and dairy production in organic and conventional livestock production systems. agricultural systems, 57, 599-630. salami, p., & ahmadi, h. (2010). energy input and output in a chickpea production system in kurdistan, iran. african crop science journal, 18, 51-57. sartori, l., basso, b., bertocco, m., & oliviero, g. (2005). energy use and economic evaluation of a three year crop rotation for conservation and organic farming in ne italy. biosystems engineering, 91, 245-56. schneider, u. a., & smith, p. (2009). energy intensities and greenhouse gas emission mitigation in global agriculture. energy efficiency (2009) 2:195–206 singh, h., mishra, d., & nahar, n. m. (2002). energy use pattern in production agriculture of a typical village in arid zone india-part i. energy conversion and management, 43, 2275-86. singh, j. m. (2000). on farm energy use pattern in different cropping systems in haryana, india. germany: int. inst. of management university of flensburg. sustainable energy systems and management, master of science. streimikiene, d., klevas, v., & bubeliene, j. (2007). use of eu structural funds for sustainable energy development in new eu member states. renewable and sustainable energy reviews, 116, 1167-87. taylor, e. b., o’callaghan, p. w., & probert, s. d. (1993). energy audit of an english farm. applied energy, 44, 315-35. pulses production systems in term of energy use efficiency and economical analysis in iran 106 topak, r., acar, b., & ugurlu, n. (2009). (analysis of energy use and input costs for irrigation in field crop production: a case study for the konya plain of turkey. journal of sustainable agriculture, 33, 757-771. topak, r., süheri, s., kara, m., & çalisir, s. (2005). investigation of the energy efficiency for raising crops under sprinkler irrigation in semi-arid area. applied engineering in agriculture, 21, 761768. tsatsarelis, c. a. (1991). energy requirements for cotton production in central greece. journal of agricultural engineering research agric eng res, 50, 239-46. unakitan, g., hurma, h., & yilmaz, f. (2010). an analysis of energy use efficiency of canola production in turkey. energy, 35, 3623-3627. yamane, t. (1967). elementary sampling theory. englewood cliffs. nj (usa): prentice-hall inc. yilmaz, i., akcaoz, h., & ozkan, b. (2005). an analysis of energy use and input costs for cotton production in turkey. renewable energy, 30,145-55. zahid, h., azam, k. m., & irfan, m. (2010). water energy and economic analysis of wheat production under raised bed and conventional irrigation systems: a case study from a semi-arid area of pakistan. soil and tillage research, 109, 61-67. . international journal of energy economics and policy | vol 8 • issue 4 • 2018 139 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(4), 139-146. an empirical analysis of short run and long run relationships between energy consumption, technology innovation and economic growth in saudi arabia yusuf opeyemi akinwale* department of economics, college of business administration, imam abdulrahman bin faisal university, dammam, saudi arabia. *email: yoakinwale@iau.edu.sa abstract this study investigates the shortand long-run relationships between energy consumption, technology innovation and economic growth in saudi arabia. the direction of causality between them was also determined using granger causality. the data covers the period between 1980 and 2015, and autoregressive distributed lag (ardl) was used for analysis as the series consist of the mixture of i(0) and i(1) order of integration. the results reveal that the variables are cointegrated which establish the existence of long run relationships between them. in the long-run, technology innovation has a negative effect on energy consumption while economic growth has a positive effect on energy consumption. similar result was found in the short run. the results of the granger causality show a unidirectional causality runs from technology innovation and economic growth to energy consumption. the results of this study support intensive investment in r&d and technology innovation by saudi government and private companies as well as the implementation of energy efficiency and conservation policies to reduce energy demand, as this would not hamper the economic growth of saudi arabia. government should fully explore the use of renewable energy sources and technologies such as solar and wind to bring about sustainable development in the country. keywords: energy consumption, technology innovation, economic growth, saudi arabia, conservation policies, autoregressive distributed lag, vision 2030 jel classifications: b13, c01, o32, q43, q54, q58 1. introduction energy has been recognised as growth agent in every sector of economy across the world. it is an essential input in production and plays a vital role in the socio-economic and technological growth and development of a nation (heinberg, 2003). energy access is also important in all aspects of human development as it is a sine-qua-non to certain basic activities, such as heating, lighting, refrigeration and the running of household appliances, which would ordinarily not be possible without energy (ogundari et al., 2017; iwayemi, 2008). the level of energy consumption by the citizens of a country has been used as a yardstick for determining the country’s energy poverty status as country with a low energy consumption per capita are relatively termed energy poor (sambo, 2008; akinwale et al., 2015). many studies (ozturk, 2010; tang and tan, 2013; shahbaz et al., 2013; khan et al., 2016; ameyaw et al., 2017) have shown the positive relationship between energy consumption and economic growth. despite the importance of energy consumption, the negative impact of its usage, specifically fossil fuel energy, in recent years cannot be undermined. carbon emission from energy has contributed largely to the degradation of ozone layers, thus, there is a global effort towards ameliorating the level of greenhouse gas emissions so as to save the entire universe from the devastating consequences (akinwale and ogundari, 2017). technological innovation becomes an integral method of generating a sustainable modern energy system as the energy path taken by most industrialised and emerging countries to become industrialised has been classified unsustainable in the current period (sohag et al., 2015; akinwale, 2017). this technological innovation cannot occur unconsciously within the country; rather it must be a coordinated action by the stakeholders (olaopa et al., 2018; akinwale and surujlal, 2017). policy interventions are akinwale: an empirical analysis of short run and long run relationships between energy consumption, technology innovation and economic growth in saudi arabia international journal of energy economics and policy | vol 8 • issue 4 • 2018140 required to drive technology innovation in a low-carbon energy system towards achieving a sustainable economic development (ockwell and mallett, 2013; akinwale, 2017). whether a country would implement energy conservation policy or not depend on the long run relationship between energy consumption, economic growth and technology innovation. if there is neither long-run nor causality from energy consumption to economic growth, then conservation policy could be easily implemented, otherwise restricting energy consumption could affect economic growth (nasreen and anwar, 2014). the saudi energy sector is growing rapidly so as to keep pace with the increase in electricity demand in the country. the yearly consumption rose at a rate of 7–9%, which is largely due to the fully subsidised energy price and increased in population. the electricity consumption per capita stood at 9,444.22 kwh while total energy consumption per capita stood at 6,937.23 kg as at year 2014 (world bank development indicators (2017). world data on energy usage). figure 1 shows the energy consumption per capita between 1980 and 2014, and it could be seen that the energy consumption has considerably increased over time. the total installed electricity generation capacity in saudi arabia is approximately 45,000 mw with total reliance on oil and natural gas plants (alrashed and asif, 2014). while oil accounted for an approximate of 57%, natural gas accounted for the rest. residential sector accounted for approximately half of the total electricity consumption, whereas industrial sector accounted for nearly 18% of the electricity consumption in the country (alrashed and asif, 2015). most of the residential houses are not adequately insulated in a way that would reduce energy consumption, and the consumers are less concerned with energy wastage because of its accessibility and low cost. there are recent arguments in literature on the link between energy consumption, technology innovation and economic growth within and across countries. while some studies (romer, 1990; sohag et al., 2015; pradhan et al., 2017) opine that technology innovation is a catalyst to economic growth and crucial for improving energy efficiency by reducing energy use as it provides opportunities for the economy to switch from depletable sources to renewable energy to meet energy demands; others (inekwe, 2015; tuna et al., 2015) reveal that it is either economic growth that leads to technology innovation or there exists no significant relationship between them, and that technology innovation has not been able to reduce the energy consumption (khan et al., 2016) but rather increase the level of energy consumption. though, technological innovation reduces energy consumption slightly but it might not reduce a great share of the energy used (sohag et al., 2015). for example, if the price of energy drops as a result of energy efficiency, the reduced price might encourage economic agents to use more energy (greening et al., 2000). there are also diverse opinions of the impact of economic growth (income) on energy consumption and which one granger causes the other (yoo, 2006; payne, 2010; akinwale et al., 2013; khan et al., 2016). based on the lack of consensus in literature and the unavailability of studies that combine the three variables in a single model in the saudi arabia’s economy, this study therefore investigates the shortand long-run as well as the causal direction between energy consumption, technology innovation and economic growth. examining this relationship in the saudi arabia’s economy is timely as the government is currently engaging in various activities to achieve her “transformation agenda 2020” and “vision 2030.” 2. literature review this section reviews relevant literature on technology innovation, energy consumption and economic growth though the studies which combine the three variables are limited. jin and zhang (2014) examine china’s potential transition from its energyintensive status quo to an innovation-oriented growth prospect using endogenous growth model which incorporate technological innovation and its interaction with fossil energy use and the environment. they reveal that a small amount of capital installation will incentivize investment in physical capital rather than r&d-related innovation, and this leads to accumulation of energy-consuming capital resulting into an intensive use of fossil energy otherwise known as energy-intensive growth pattern. however, when the mechanism of r&d related innovation was introduced into the economy, the economic system embarked on r&d for innovation until the dynamic benefit of r&d is equalized with that of capital investment. thus, the economy evolves along an innovation-oriented balanced growth path where consumption, physical capital and technology all grow, whereas fossil energy consumptions drop and environmental quality improves. pradhan et al. (2017) investigate the granger causal relationships between innovation, economic growth, ict infrastructure and some other macroeconomic variables using panel data from 32 high income oecd countries from 1970 to 2016. they found that all of these variables are cointegrated with innovation implying long run relationship among them. there is bidirectional causality between innovation, economic growth and ict infrastructures in the long run as well as various short run. kim (2011) examines the contributions of r&d stock to economic growth using the r&d-based cobb-douglas production function during the years 1976–2009 in south korea and finds that r&d activities create the most efficient methods to raise competitiveness in the corresponding economy, which ensures stable and continuous economic growth. cameron (1996) reviews the empirical evidence on the link between innovation and economic growth, whereby factors such as r&d spending, patenting, and innovation counts figure 1: energy consumption per capita (kg of oil equivalent) in saudi arabia source: world bank development indicators (2017) akinwale: an empirical analysis of short run and long run relationships between energy consumption, technology innovation and economic growth in saudi arabia international journal of energy economics and policy | vol 8 • issue 4 • 2018 141 are used as measures of innovation. the study concludes that innovation makes a significant impact on economic growth and that there are significant spillovers between countries, firms and industries, and to a lesser extent from government-funded research. the study of goel and ram (1994) reveals a positive impact of research and development (r&d) outlays on economic growth. kirchhoff et al. (2007) reveal that university r&d encourages the formation of new firms which creates employment and positively impacts on gross domestic product (gdp). hasan and tucci (2010) investigate the relationship between innovation and the economy and find that there is an increase in economic growth for countries that increase their level of patenting. akinwale et al. (2012) investigate the impact of r&d and innovation, labour and capital on economic growth in nigeria using least square method between 1977 and 2007. the results reveal that gross expenditure on r&d has negative and significant impact on economic growth, and they infer that the level of r&d spending and innovation support of government is still relatively low. moreso, it is not enough to increase spending on r&d and innovation when there are weak institutions, high corruption practices, low interaction between the academia and the industry, uncoordinated industrial clusters, among others. they therefore suggest strong “political will” of government to create an enabling environment for innovation. tuna et al. (2015) examine the relationship between r&d expenditures and economic growth in turkey and their result reveals no long run relationship and no causality between them. inekwe (2015) also reveals in his study that the effect of r&d spending on growth is insignificant in lower income economies while it is positive for upper middle-income economies. tang and tan (2013) explore the nexus of electricity consumption, economic growth, energy prices and technology innovation in malaysia, and they found that electricity consumption and its determinants are cointegrated. the empirical results also reveal that income positively affects electricity consumption, while energy prices and technology innovation negatively affect it in the long run. the granger causality results further shows that technology innovation granger-cause economic growth and electricity consumption; and that electricity consumption and economic growth granger-cause each other both in the short and in the long run. sohag et al. (2015) investigate the effects of technological innovation on energy use in malaysia by extending the marshallian demand framework using an autoregressive distributed lag (ardl) bounds testing approach for the sample period 1985–2012. the results confirm both shortand long-run theoretical predictions that technology innovation reduces energy use while gdp per capital increases energy use. this suggests that technological innovation is an important factor in reducing energy use and improving energy efficiency in malaysia without impairing economic growth. moreover, wong et al. (2013) establish that oecd countries are able to enjoy greater energy efficiency gains due to their sizeable technological innovation compared to other developing countries. khan et al. (2016) also investigate the impact of technological innovations, economic growth, energy price on energy use at aggregate and disaggregate levels for the economy of pakistan using an extended marshallian demand function for the period 1971–2013, and the variables are cointegrated which indicates long run relationship among the variables. the results fail to confirm the negative relationship between technology innovation and aggregate energy use, and in fact technology innovation seems to be the main driver of energy demand in pakistan, except for petroleum products and electricity, highlighting the existence of rebound effect. the result also reveal that elasticity of energy demand with respect to real gdp per capita and energy price are insignificant implying income and price variations do not affect energy consumption in the long-run in pakistan. since price is also a factor influencing demand from the marshallian demand function, the impact of energy price on energy consumption is also observed. the empirical results are mixed in various studies. studies such as zhou and teng (2013) in china, altinay (2007) in turkey, khan et al. (2016) in pakistan, find no significant price elasticity of energy demand indicating inelastic energy demand. however, studies such as tang and tan (2013) in malaysia; fei and rasaiah (2014) in ecuador, south africa and canada find significant impact of price elasticity of energy price signalling that energy demand would reduce as price increases and vice versa. there are also numerous studies with differing results on the relationship between energy consumption and economic growth. while some studies (shahbaz et al., 2013; acaravci et al., 2015; akinwale and muzindutsi, in press) suggest unidirectional causality from energy consumption to economic growth, other studies (yoo, 2006; lean and smyth, 2010; akinwale et al., 2013; ameyaw et al., 2017) reveal the reverse case. meanwhile, there are some studies (tang and tan, 2013; nasreen and anwar, 2014; mezghani and haddad, 2017) that also show bidirectional causality between them, whereas few studies (apegris and payne, 2009; ozturk and acaravci, 2013) show no causality. thus, there is no consensus on the energy-growth nexus in the literature. some of the differing results at many instances are due to the omission of important variables, methodological differences and peculiarities of the economy (ozturk, 2010; payne, 2010; akinwale and grobler, in press). this study therefore extends beyond bivariate model by examining energy consumption, technology innovation, energy price and economic growth in saudi arabia. 3. methodology 3.1. data and sample period annual time series data covering the period 1980–2015 on energy consumption per capita (in kg), gdp per capita (constant at 2010 us$), technological innovation (total patent application in the country i.e. both residents and non-residents) and consumer price index were collected from the 2017 update of world bank’s world development indicator as published through the online database of world bank. the variables used in the models are: ec for energy consumption per capita, gdp for real gdp per capita, tin for technological innovation and p as consumer price index. since data on energy price is not readily available and most energy prices of various products are distorted due to large subsidy, this warrants the use of consumer price index as energy price in many studies (lean and smyth, 2010; tang and tan, 2013; khan et al., 2016) akinwale: an empirical analysis of short run and long run relationships between energy consumption, technology innovation and economic growth in saudi arabia international journal of energy economics and policy | vol 8 • issue 4 • 2018142 so the study also adopts cpi as proxy for energy price. the choice of the starting period was constrained by the availability of data on technological innovation. 3.2. method and model specification this study followed what was used by tang and tan (2013) among other studies which is basically on the theory of marshallian demand function. energy demand can be derived from this marshallian demand function, and can be written as a function of income and price as follows: ect=f(yt,pt) (1) where ect is energy consumption, yt is income or economic growth and pt is the energy prices. for the purpose of this research, equation (1) is then extended by incorporating technology innovation as an additional variable that influence energy demand/consumption. further to this, yt would be replaced by gdpt and tint would be used for technological innovation. thus, the new empirical model for energy consumption in saudi arabia is written as follows: ect=f(gdpt, pt, tint) (2) after natural logarithm of equation 2 is taking, then the new model is: ect=β0+β1lngdpt+β2lnpt+β3lntint+ԑt (3) from equation 3 above, ln denotes the natural logarithm, lnect is per capita energy consumption, lngdpt is per capita real income, lnpt is the price, and lntint is technology innovation. the error term ԑt is assumed to be spherically distributed and white noise (tang and tan, 2013). the expected signs for the coefficients of real income, energy price and technology innovation are β1>0, β2<0, and β3<0 respectively. few studies such as khan et al. (2016) also believe that β3 can be >0 as the elasticity of energy demand with respect to technology innovation may be positive or negative depending on the nature of technology innovation, and its relative effect on production and consumption. before the data could be used to determine the existence of long run and causality direction of the variables, it is necessary to determine the order of integration of each variable. this is done with the use of unit root testing. granger and newbold (1974) stated that using non-stationary data in causality tests can yield spurious causality results. hence, unit root tests are used to investigate if trending data should be first differenced or be differenced at higher order to render the data stationary. this study use augmented dickey fuller (adf) and phillips-perron (pp) tests to check the stationarity of the data. a preliminary analysis of trend, stability and variability of the variables was also conducted using diagnostics statistics. to investigate the existence of a long run equilibrium relationship between energy consumption and its determinants, an ardl model is used to test the presence of cointegration among the variables. ardl was chosen for this study because of the advantages it has over other tests of long run. this includes its ability to combine a mixture of variables that are stationary at level, i(0) and those that are stationary at first difference, i(1) (tang and tan, 2013; akinwale and muzindutsi, in press). thus, ardl can be used irrespective of whether the explanatory variables are purely i(0), purely i(1), or mutually cointegrated, but it cannot be used when variables are stationary at the second difference, i(2) (pesaran and shin, 1998). it is also found that the ardl bounds testing approach is more efficient when the samples is small (pesaran and shin, 1998). the ardl model is therefore expressed thus: ∆ ∆ ∆ ∆ ∆ lec lec lgdp ¸ lt t j t jj n j t jj n jj n t j j p = + + + + −= −= = − ∑ ∑ ∑ α γ β δ 0 0 0 0 iin lec lgdp lp t jj n t t t t t z −= − − − − ∑ + + + + 0 1 1 2 1 3 1 4 1 ϕ εϕ ϕ ϕ + (4) where: ∆lect is the change in the natural log value of energy consumption at time t; ∆lgdpt represents the change in the natural log value of gdp at time t; ∆pt is the change in the natural log value of price at time t and ∆ltint is the change in the natural log value of trade openness. α0 is the intercept, n is number of lags and εt is the error term. coefficients βj, γj, ɵj and δj represent the short-run dynamics of the model; while φ1, φ2, φ3, and φ4, are used to test for the long-run relationship known as bound cointegration test. based on equation 4, the following hypothesis was therefore set to test for co-integration: null hypothesis (h0) for no co-integration: φ1=φ2=φ3=φ4=0 alternative hypothesis (h1) for co-integration φ1≠0, φ2≠0, φ3≠0, φ4≠0 if the null hypothesis of no cointegration is rejected the alternative of cointegration or inconclusiveness is considered on the basis of comparison between f-statistic (calculated) and critical values provided by pesaran et al. (2001). if the estimated f-value is greater than the upper critical value then there is a cointegrating relationships between the variables but if the estimated f-value lies between the lower and upper critical values the result remained inconclusive unless additional information is provided. however, if the estimated f-value is lesser than the lower critical value, the h0 cannot be rejected and this suggests that there is no cointegration between the variables. as the existence of cointegration is established between the variables, then error correction model is estimated to obtain the short run and long run parameters. while short run causal effects is indicated by the f-statistic on the explanatory variables, the long run causal relationship is denoted by the t-statistic on the coefficient of the lagged error-correction term (ect) (narayan and smyth, 2006; belloumi, 2014; akinwale and grobler, in press). this is expressed in equation 5 as follows: ∆ ∆ ∆ ∆ ∆ ec ec lgdp p ltin t j t jj n j t jj n j n j t j j = + + + + −= −= = − ∑ ∑ ∑ α γ β δ 0 0 0 0 θ tt jj n t−= −∑ + +0 1λectt ε (5) where ectt−1 is the error correction term and λ is the coefficient of ect which measures the speed of adjustment to the equilibrium. 4. results analysis 4.1. analysis of unit root tests the existence of unit root at second difference i(2) signifies non stationary of the variable which could lead to spurious results. in akinwale: an empirical analysis of short run and long run relationships between energy consumption, technology innovation and economic growth in saudi arabia international journal of energy economics and policy | vol 8 • issue 4 • 2018 143 order to ascertain the absence of unit root in the variables used in the model, unit root test was conducted using the standard adf and pp unit root tests. the results of the unit root tests are presented in table 1. the results show that gdp and energy consumption are stationary at first difference, technology innovation is stationary at level and first difference whereas price is stationary at second difference. consequently, price was removed from the model so as to avoid spurious result. after the removal of consumer price index, then the model consist of the mixture of i(0) and i(1) series, suggesting that ardl is the appropriate model to test for cointegration. 4.2. bounds tests and long run analysis akaike information criteria selected lag 2 as the optimal lag for the model, and the results of bounds cointegration tests are presented in table 2. these results show that the estimated f-value (7.2) is greater than the upper critical value (6.36) at 1% level of significance. this implies that the null hypothesis which states that there is no cointegration is rejected; hence, there is a long run relationship between energy consumption, technology innovation and economic growth in saudi arabia as shown in table 2. the direction and the significance of the long run relationship between the variables are shown by equation 6. the results show that while technology innovation has a negative long run effect on energy consumption, gdp growth has a positive long run effects on energy consumption. lec = −21.7780–0.0052 ltin+3.0945 lgdp (6) the result also indicates that technology innovation does not have significant impact on energy consumption whereas gdp growth has a statistically significant impact on energy consumption at 10% level of significance. the negative effect of technology innovation implies that 1% improvement in technology would reduce energy consumption by 0.0052. this means that technology innovation would lead to a reduction of energy consumption in saudi arabia though this is not statistically significant. this might be due to the present low level of innovation and technology at the residential sector as well as the industry such as poor insulation of the houses and factories. the positive effect of gdp on energy consumption specifies that 1% increase in gdp growth would lead to 3.09% increase in energy consumption. this means that saudi arabia residents tend to consume more energy as the economy grows, and the impact is statistically significant. these results are in line with the results obtained in the studies of sohag et al. (2015) and ameyaw et al. (2017) among others. these results suggest that saudi arabia can benefit immensely in the long run by strengthening her technology innovation as well as engage in conservation policies as these would reduce the energy consumption in the long run without affecting economic growth. 4.3. analysis of short run relationship and error correction modelling the result of the error correction model and short run relationship is presented in table 3. the ectt−1 coefficient is negative as required and it is statistically significant at 1% significant level. this ectt−1 coefficient (−0.1275) also implies that a short run deviation from the long run disequilibrium is corrected by 12.75% towards a long run equilibrium path each year. this sign and significance of ect signify that there is at least a long run causality running from technology innovation and economic growth to energy consumption. this further establishes the existence of long run relationship between the variables. table 3 also shows that in the short run, gdp has a positive impact on energy consumption whereas technology innovation has a negative impact on energy consumption. moreso, gdp is statistically significant at 10% while technology innovation is not statistically significant. this is similar to the results obtained in the long run, and this is clearly depicting that increase in economic growth would increase energy consumption while the development of new technology innovation or improvement on the existing ones would decrease energy consumption. 4.4. analysis of granger causality tests table 4 presents the results of the pairwise granger causality tests conducted to further examine the short run relationship between the variables. the results show that there is unidirectional causality from technology innovation and gdp to energy consumption, as well as from gdp to technology innovation. these results are also consistent with findings of lean and smyth (2010), tang and tan (2013), akinwale et al. (2013) and sohag et al. (2015) among others. this result indicates that technology innovation is very important to the reduction of energy demand by households and firms in saudi arabia. innovation regarding household appliances, bulbs, heating and cooling system among others would reduce the household energy consumption which accounted for more than 50% of the energy used in ksa. also, technology innovation which would make most of the industrial machine and equipment energy efficient should also be given priority by the government and the private sector. this technology innovation is expected to bring about a drastic reduction in energy consumption, which would lead to reduction in carbon emission. the unidirectional causality of gdp to energy consumption signifies that an increase in economic growth would encourage energy consumption at a faster rate. thus, government is encouraged to implement conservation and energy efficient policies without any fear of harming economic growth. this conservation policy will also engender the reduction in energy demand which would lead to the reduction of the quantity of carbon emitted into the environment. table 1: results of unit root tests variable adf pp order of integrationlevels first difference levels first difference lec −0.9039 −3.6376** −0.2410 −9.0089*** i (1) ltin −5.4710*** −6.7490*** −5.1048*** −6.7490*** i (0) lgdp −2.2293 −4.3570*** −2.4377 −4.6755*** i (1) lp 0.3355 −2.0885 1.3647 −1.9726 i (2) ***,**,*indicate 1%, 5% and 10% level of significance, respectively, adf: augmented dickey fuller, pp: phillips-perron akinwale: an empirical analysis of short run and long run relationships between energy consumption, technology innovation and economic growth in saudi arabia international journal of energy economics and policy | vol 8 • issue 4 • 2018144 renewable energy sources and technologies should be fully harnessed by the government since there is abundance of sun and wind in saudi arabia. the result of unidirectional causality from gdp to technology innovation implies that the growth in the economy will lead to the advent of more technology innovation, though a feedback effect was expected for this. however, the present low level of technology innovation, when compared with some emerging and developed economies might warrant this. 4.5. analysis of diagnostic tests the adequacy of the model has been validated through various diagnostic tests, including breusch-godfrey serial correlation lm test, jarque-berra test, heteroskedasticity test, cusum of squares and cusum tests. table 5 shows that the null hypotheses for no presence of autocorrelation and heteroscedasticity cannot be rejected. also, the residuals are found to be normally distributed. furthermore the cusum of squares in figure 2 also shows that the relationship between the variables is stable over the period, though figure 3 shows that cusum shortly goes out of the bound in 2009 but falls back within the bound in a very short time. this could be as a result of the aftermath of global financial crisis in 2008, which saudi arabia was able to absorb within a short time due to the nature of their financial system. summarily, the diagnostic tests confirm the validity of the specified model. 5. conclusion this study examines the relationship between energy consumption, technology innovation and economic growth in saudi arabia. this study becomes important considering the current efforts of the saudi government in transforming the economy towards the achievement of vision 2030, and also the limited studies relating to these three variables in saudi arabia. the results of adf and pp tests show that the series consist of both i(0) and i(1) making ardl bound testing approach the most suitable method of analysis for this model. ardl bound test shows that energy consumption, technology innovation and economic growth are cointegrated, hence establishes the existence of long run relationships between them. the ect also corroborates the long run relationship between the variables, as it has the required negative sign and significant at 1% level of significance. the results of both long run and short run relationships are similar as they both reveal that while technology innovation has a negative relationship with energy consumption; economic growth has a positive relationship with energy consumption. furthermore, the results of pairwise granger causality show that there is unidirectional causality running from technology innovation and gdp to energy consumption, as well as unidirectional causality running from gdp to technology innovation. the empirical results from this study provide some managerial implications for the policy makers. the long run causality running from technology innovation to energy consumption and the table 2: ardl bounds test test statistic value k f-statistic 7.2003 2 critical value bounds significance i0 bound i1 bound 10% 3.17 4.14 5% 3.79 4.85 2.5% 4.41 5.52 1% 5.15 6.36 ardl; autoregressive distributed lag table 3: short run analysis and error correction model variable coefficient std. error t-statistic prob. d (tin) −0.065287 0.038680 −1.687866 0.1062 d (gdp) 0.394634 0.203782 1.936547 0.0664 ectt−1 −0.127526 0.030028 −4.246845 0.0002 table 4: pairwise granger causality results null hypothesis f-statistic d (lgdp) does not granger cause d (lec) 3.68942** d (lec) does not granger cause d (lgdp) 2.57285 d (ltin) does not granger cause d (lec) 2.95330* d (lec) does not granger cause d (ltin) 2.39085 d (ltin) does not granger cause d (lgdp) 1.62801 d (lgdp) does not granger cause d (ltin) 3.66198** ***,**,* indicate 1%, 5% and 10% level of significance, respectively table 5: diagnostic test results item applied test p value decision serial correlation lm test 0.1643 no serial correlation normality jacquebera 0.8415 variables are normally distributed heteroscedasticity breusch pagan godfrey 0.2073 no heteroscedasticity figure 2: cusum of squares at 5% level of significance figure 3: cusum at 5% level of significance akinwale: an empirical analysis of short run and long run relationships between energy consumption, technology innovation and economic growth in saudi arabia international journal of energy economics and policy | vol 8 • issue 4 • 2018 145 negative relationship between them implies that development of new technology innovation and the improvement on the existing ones would reduce the level of energy demand in saudi arabia which would further lead to reduction in carbon emission. furthermore, the long run causality running from gdp to energy consumption and the positive relationship between them indicates that the expansion in economic activity in saudi arabia would exacerbate the extent of energy demand by the households and firms; thus, the adoption of energy conservation policies by the government would not impair economic growth in realising vision 2030. the policy makers are therefore required to make policy that would continue to encourage government investment in r&d that would generate technology innovation and at the same time create an enabling environment for the private sectors to invest in r&d which would generate technology innovation so as to reduce the extent of energy consumption. this study also suggests that government can successfully implement energy efficient and conservation policies as these will not hamper economic growth of the saudi economy but rather improve the quality of the environment. alternative energy through renewable energy sources and technologies such as solar and wind should be fully explored by the government to create sustainable economic development. references acaravci, a., erdogan, s., akalin, g. (2015), the electricity consumption, real income, trade openness and foreign direct investment: the empirical evidence from turkey. international journal of energy economics and policy, 5(4), 1050-1057. akinwale, y. (2017), descriptive analysis of building indigenous low-carbon innovation capability in nigeria. african journal of science, technology innovation and development, 1-14. doi: 10.1080/20421338.2017.1366131. akinwale, y., dada, a., oluwadare, a., jesuleye, o., siyanbola, w. (2012), understanding the nexus of r&d, innovation and economic growth in nigeria. international business research, 5(11), 187-196. akinwale, y., grobler, w. (in press). education, openness and economic growth in south africa: empirical evidence from vecm analysis. the journal of developing areas, 49, 1057-72. akinwale, y., ilevbare, o., ogundari, i. (2015), utilising renewable energy technologies for electricity poverty reduction in southwest nigeria: technology adoption and psychosocial perspectives. international akinwale, y., jeseleye, o., siyanbola, w. (2013), empirical analysis of the causal relationship between electricity consumption and economic growth in nigeria. british journal of economics, management and trade, 3(3), 277-295. akinwale, y., muzindutsi, p. (in press), electricity consumption, trade openness and economic growth in south africa: an ardl approach. journal of economic cooperation and development. akinwale, y., ogundari, i. (2017), exploration of renewable energy resources for sustainable development in nigeria: a study of the federal capital territory. international journal of energy economics and policy, 7(3), 240-246. akinwale, y., surujlal, b. (2017), a techno-economic policy framework to enhance the contribution of marginal oil and gas field to nigeria’s economic growth: a petroleum innovation system approach. international journal of economics and finance studies, 9(1), 132-147. alrashed, f., asif, m. (2015), an exploratory residents’ views towards applying renewable energy systems in saudi dwellings. energy procedia, 75, 1341-1347. altinay, g. (2007), short-run and long-run elasticities of import demand for crude oil in turkey. energy policy, 35(11), 5829-5835. ameyaw, b., oppong, a., abruquah, l., ashalley, e. (2017), causality nexus of electricity consumption and economic growth: an empirical evidence from ghana. open journal of business and management, 5, 1-10. apegris, n., payne, j. (2009), energy consumption and economic growth in central america. evidence from a panel co-integration and error correction model. energy economics, 31, 211-216. belloumi, m. (2014), the relationship between trade, fdi and economic growth in tunisia: an application of autoregressive distributed lag mode. economic systems, 38, 269-287. cameron, g. (1996), innovation and economic growth. centre for economic performance. discussion paper, no. 277. consumption, exports and gdp: evidence from a panel of middle eastern countries. energy policy, 37, 229-236. fei, q., rasiah, r. (2014), electricity consumption, technological innovation, economic growth and energy prices: does energy export dependency and development levels matter? energy procedia, 61, 1142-1145. goel, r., ram, r. (1994), research and development expenditures and economic growth: a cross-country study. economic development and cultural change, 42(2), 403-411. granger, c., newbold, p. (1974), spurious regressions in econometrics. journal of econometrics, 2(2), 111-120. greening, a., greene, d., difiglio, c. (2000), energy efficiency and consumption-the rebound effect-a survey. energy policy, 28(6), 389-401. hasan, i., tucci, c. (2010), the innovation-economic growth nexus: global evidence. research policy, 39(10), 1264 -1276. heinberg, r. (2003), the party’s over: oil, war and the fate of industrialized societies, new society publishing, british columbia. available from: http://www.unep.fr/scp/rpanel/pdf/assessing_ biofuels_full_report.pdf. [last accessed on 2017 nov 20]. inekwe, j. (2015), the contribution of r&d expenditure to economic growth in developing countries. social indicators research, 124(3), 727-745. iwayemi, a. (2008), investment in electricity generation and transmission in nigeria: issues and options. international association for energy economics, 38-42. available from: https://www.iaee.org/documents/ newsletterarticles/iwayemi.pdf. jin, w., zhang, z. (2014), quo vadis? energy consumption and technological innovation. ccep working paper 1412, august 2014. crawford school of public policy , the australian national university. journal of renewable energy technology, 6(3), 224-244. khan, g., ahmed, a., kiani, a. (2016), dynamics of energy consumption, technological innovations and economic growth in pakistan. journal of business and economics, 8(1), 1-21. kim, j. (2011), the economic growth effect of r&d activity in korea. economy journal, 12, 25-44. kirchhoff, b., catherine, a., newbert, s., hasan, i (2007). the influence of university r&d expenditures on new business formations and employment growth. entrepreneurship theory and practice, 31(4), 543-559. lean, h., smyth, r. (2010), on the dynamics of aggregate output, electricity consumption and exports in malaysia: evidence from multivariate granger causality tests. applied energy, 87, 1963-1971. mezghani, i., haddad, h. (2017), energy consumption and economic growth: an empirical study of the electricity consumption in saudi akinwale: an empirical analysis of short run and long run relationships between energy consumption, technology innovation and economic growth in saudi arabia international journal of energy economics and policy | vol 8 • issue 4 • 2018146 arabia. renewable and sustainable energy reviews, 75, 145-156. narayan, p., smyth, r. (2009), multivariate granger causality between electricity nasreen, s., anwar, s. (2014), causal relationship between trade openness, economic growth and energy consumption: a panel data analysis of asian countries. energy policy, 69, 86-91. ockwell, d., mallett, a. (2013), low carbon innovation and technology transfer. in: urban, f., nordensvärd, j., editors. low carbon development: key issues. abingdon: earthscan, routledge. p109128. ogundari, i., akinwale, y., adepoju, a., atoyebi, m., akarakiri, j. (2017), suburban housing development and off-grid electric power supply assessment for north-central nigeria. international journal of sustainable energy planning and management, 12, 47-64. olaopa, o., akinwale, y., ogundari, i. (2018), governance institutions for sustainable energy resources management in nigeria. in: asuelime l., okem, a., editors. the political economy of energy in sub-saharan africa. london and new york: routledge taylor and francis groupd. ozturk, i. (2010), a literature survey on energy-growth nexus. energy policy, 38, 340-349. ozturk, i., acaravci, a. (2013), the long-run and causal analysis of energy, growth, openness and financial development on carbon emissions in turkey. energy economics, 36, 262-267. payne, j. (2010), a survey of the electricity consumption-growth literature. applied energy, 87, 723-731. pesaran, m., shin, y. (1998), an autoregressive distributed-lag modelling approach to cointegration analysis. econometric society monographs, 31, 371-413. pesaran, m., shin, y., smith, r. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. pradhan, r., arvin, m., bahmani, s., bennett, s. (2017), the innovationgrowth link in oecd countries: could other macroeconomic variables matter? technology in society, 51, 113-123. romer, p. (1990), endogenous technological change. journal of political economy, 98(5), 71-102. sambo, a. (2008), matching electricity supply with demand in nigeria. international association for energy economics (iaee) newsletter, fourth quarter. available from: https://www.iaee.org/documents/ newsletterarticles/408sambo.pdf. shahbaz, m., khan, s., tahir, m. (2013), the dynamic links between energy consumption, economic growth, financial development and trade in china: fresh evidence from multivariate framework analysis. energy economics, 40, 8-21. sohag, k., begum, r., abdullah, s., jafaar, m. (2015), dynamics of energy use, technological innovation, economic growth and trade openness in malaysia. energy, 90, 1497-1507. tang, c., tan, e. (2013), exploring the nexus of electricity consumption, economic growth, energy prices and technology innovation in malaysia. applied energy, 104, 297-305. tuna, k., kayacan, e., bektas, h. (2015), the relationship between research and development expenditures and economic growth: the case of turkey. procedia social and behavioral sciences, 195, 501-507. wong, s., chang, y., chia, w. (2013), energy consumption, energy r&d and real gdp in oecd countries with and without oil reserves. energy economics, 40, 51-60. yoo, s. (2006), the causal relationship between electricity consumption and economic growth in the asean countries. energy policy, 34, 3573-3582. zhou, s., and teng, f. (2013), estimation of urban residential electricity demand in china using household survey data. energy policy, 61, 394-402. alrashed, f., asif, m. (2014), trends in residential energy consumption in saudi arabia with particular reference to the eastern province. journal of sustainable development of energy, water and environment systems, 2(4), 376-387. . international journal of energy economics and policy | vol 8 • issue 1 • 2018128 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(1), 128-136. decision making model of electric power fulfillment in lampung province using soft system methodology m. yusuf s. barusman1*, appin purisky redaputri2 1faculty of economics, bandar lampung university, lampung, indonesia, 2faculty of economics, bandar lampung university, lampung, indonesia. *email: yusuf.barusman@ubl.ac.id abstract at present, lampung province is experiencing electric power deficit. this study aims to investigate the criteria and decision making alternative solution of electricity distribution management, to determine alternative possibilities of decision-making, and decision alternative priority. method used in this study is soft system methodology by using analytical hierarchy process, multi criteria decision making, weighted sum method and weighted product method. the result has two criteria, which are internal and external, with three sub-criteria in each existing criteria. among others are budget availability, human resources readiness, and implementation technique for internal criteria, population growth, economic growth and political intervention for external criteria. moreover, some decision making alternatives are building additional power plants, transmission lines, renting additional power plant and independent power producer (ipp) and excess power. there are 30 possibilities decision making model. and alternatives that become priority which are building transmission line and building additional power plant constructions. keywords: decision making, alternative priority, soft system methodology jel classifications: d7, q41, q42 1. introduction imbalance of electric power supplies and public needs cause the presence of electric power deficit. one of electric power deficit is occurring in sumatra island is in lampung province. based on national electric company (nec) data in 2014 (pln, 2014), it is known that the growth of electricity demand in lampung province is adequately high, around 15% each year. electricity ratio in lampung reaches only around 76% so that it electricity development is still needed to increase electric power supplies, power quality as well as its reliability. at the end of 2015, lampung is having the worst deficit of electric power condition, which reached 79,4-189,3 mw in november. therefore, a study needs to be conducted to investigate criteria and decision making solution alternative of electricity distribution management, to determine decision making alternative possibilities of electricity needs fulfillment based on existing criteria and to determine priority of decision alternative on what must be done to conduct electric power fulfillment in lampung province. there are many studies discussed about the electricity, maqin and sidharta (2017) discussed about the relationship of economic growth with human development and electricty consumption; rodrigues et al. (2017) discussed about the efficiency of power transmissiona and distribution of electricity; mylnikov and kuetz (2017) discussed production management system of electricity. 2. methodology this study uses soft system methodology (ssm) approach because it needs complex approach system with unstructured problem and it keeps developing that has certain purpose. the ssm has been developed over the past four decades by a team of academics from the university of lancaster led by checkland in order to deal with unstructured problems (checkland, 1981; 2000; checkland and winter, 2006). ssm initially is used to help solving complex problem and involving many stakeholders in management field. checkland’s ssm (checkland, 2000) presents as being a powerful holistic approach that is highly developed. it delivers effective levers of organizational change as it enables participants to engage barusman and redaputri: decision making model of electric power fulfillment in lampung province using soft system methodology international journal of energy economics and policy | vol 8 • issue 1 • 2018 129 in a continuous learning process that enhances the willingness to collaborate in achieving the desired outcome and is inclusive of the cultures of both the participants and the end users. ssm is developed by management technicians in lancaster university to help solving problems related to efficiency and effectiveness involving modern technology with high complexity in human organization. checkland (2000), and checkland and scholes (1999) have attempted to transform these ideas from systems theory into a practical methodology that is called ssm. checkland’s premise is that systems analysts need to apply their craft to problems of complexity that are not well defined, and that ssm attempts to understand the wicked and fuzzy world of complex organizations. this is achieved with the core paradigm of learning (checkland, 2000). the 7-stage ssm implementation of checkland thought really dominated this soft method, even when it is used, checkland’s idea cannot be left. the checkland’s seven stages are entering the problem situation, expressing the problem situation, formulating root definitions of relevant systems, building conceptual models of human activity systems, comparing the models with the real world, defining changes that are desirable and feasible, taking action to improve the real world situation (checkland, 2000). this approach is used when technical approach is not able to explain varied phenomena faced entirely and accurately. therefore, it can be concluded that ssm is a holistic approach in viewing real and conceptual aspects in society. ssm sees each matter occurring as human activity system because the series of human activities can be named as a system, which is each activity relates to each other and forms a bond. soft systems approach is considered as a very productive methodology to learn each human activity that is organized in achieving certain goals. in this study, the first analysis instrument used is analytical hierarchy process (ahp). it aims to investigate criteria and decision-making solution alternative of electricity distribution. it is also appropriate due to complex and unstructured problem faced by nec. ahp is a supporting model of decision that is developed by saaty (1980; 1992). this decision-supporting model will parse multi factor problems or multi criteria problems that are complex into a hierarchy. according to saaty and vargas (2012), a hierarchy is defined as a representative of a complex problem in a multi-level structure where the first level is a goal, followed by level of factor, criteria, sub criteria, and continuously to the bottom until the last level of alternative as shown in figure 1. with hierarchy, a complex problem can be parsed into groups that then are arranged into a form of hierarchy, so the problem will be seen more structured and systematic. ahp is often used as a problem solving method compared to other methods because of some reasons as the following: structure that has a hierarchy, as a consequence of the chosen criteria, to the deepest sub criteria; considering validity to the limit of inconsistent tolerance from varied criteria and alternatives selected by decision maker; and considering durability of decisionmaking sensitivity analysis output. 2.1. ahp stages in ahp method, steps done are as the following: 1. defining problems and determining desirable solutions. 2. making a hierarchy structure that is started by main goal. after setting the main goal as the top level, then, hierarchy level that is in the lower level, which is suitable criteria, is arranged to consider or to evaluate alternatives that we give and to determine the alternatives. each criterion has different intensity. the hierarchy is then followed by sub criteria (if it is needed). 3. creating a paired comparison matrix that illustrates relative contribution or the effect of each element on the goal or upper criteria. to start the paired comparison process, a criterion from the top level is selected, for example, k and then from the lower level, the element that will be compared, for example, e1, e2, e3, e4, e5. 4. defining paired comparison so that it can be obtained the number of all evaluations as many as n [(n−1)/2] item, with n is the number of elements that are compared. 5. importance intensity 1 = both elements are equally important, both elements have great effect. 3 = one element is slightly more important than the other element, experience and evaluation slightly support one element compared to the other element. 5 = one element is more important than the other element, experience and evaluation strongly support one element compared to the other element. 7 = one element is absolutely more important than the other element; one element is strongly supported and is dominantly seen in practice. 9 = one element is absolutely more important than the other element, evidence that supports one element toward the other element has the highest confirmation level that might strengthen it. 2, 4, 6, 8 = values between two values of considerations that are adjacent, this value is given if there are two compromises in between two opposite selections = if for activity i, it gets one number compared to activity j, then j has the opposite value compared to i. 6. calculating eigen value and testing its consistency. if inconsistent, then, data collecting is repeated. 7. repeating the steps for the entire hierarchy levels. 8. calculating eigen vector from each paired comparison matrix that is a weight for each element to determine priority of elements in the lowest hierarchy level to goal achievement. 9. checking the consistency of hierarchy. what is measured in ahp is the consistency ratio by looking at the consistency ratio. expected consistency is the one nearly perfect in order to produce decision that is nearly valid. even though it is difficult to achieve, consistency ratio is expected to be ≤10%. the next ssm analysis instrument is multi criteria decision making (mcdm). it is a method that helps in conducting decision making on some alternatives of decision taken with some criteria consideration (zimmermann, 1987; jones, et al., 1986). according to many authors (zimmermann, 1987; pohekar and ramachandran, 2004) mcdm is divided into multi-objective decision making and multi-attribute decision making (madm). although madm methods may be widely diverse, many of them have certain aspects in common (chen and hwang, 1992; tzeng and huang, 2011) which are: 1. alternative; alternative is objects that are different and have opportunity to be chosen by decision maker. barusman and redaputri: decision making model of electric power fulfillment in lampung province using soft system methodology international journal of energy economics and policy | vol 8 • issue 1 • 2018130 2. attribute; attribute is often named as decision criteria. 3. conflict between criteria; some criteria generally have conflict between one to another, for example profit criteria will have conflict with cost criteria. 4. decision weight, decision weight shows relative importance from each criterion, w = (w1, w2, w3,…, wn) 5. decision matrix, a matrix of decision x that is measured as m x n, contains of elements xij representing rating from alternative a: i = 1, 2, 3, m toward criteria cj;j = 1, 2, 3,…, n the last tool used is weighted sum method (wsm) and weighted product method (wpm). the wsm is the simplest available method, applicable to singledimensional problems, due to the fact that it follows an intuitive process. in the background of this method, the additive utility hypothesis is applied, which implies that the overall value of every alternative is equivalent to the products’ total sum. in problems with the same units’ ranges across criteria, wsm is easily applicable; however, when the units’ ranges vary, for example when qualitative and quantitative attributes are employed, the problem becomes difficult to handle, as the aforementioned hypothesis is violated, and hence, normalisation schemes should be employed. it is common practice to use wsm along with other methods, for instance ahp, because of the method’s plain nature. for the case of n criteria and m alternatives, the optimum solution to the problem is obtained by the following equation: 6 1 * | maxwsm i ij j i j a a a w =    =     ∑ i = 1, 2, 3, 4 where i1,…, m, a*wsm represents the weighted sum score, aij is the score of the ith alternative with respect to the jth criterion and wj is the weight of the j th criterion (kolios et al., 2016). the wpm is very similar to the wsm. the main difference is that instead of addition in the model there is multiplication. each alternative is compared with the others by multiplying a number of ratios, one for each criterion. each ratio is raised to the power equivalent to the relative weight of the corresponding criterion. in general, in order to compare alternatives ap and aq (where m ≥ p, q ≥ 1) the following product (triantaphyllou and sanchez, 1997) has to be calculated: 1 jwn p pj q qjj a a r a a =     =        ∏ if the ratio r(ap/aq) is greater than or equal to one, then the conclusion is that alternative ap is more desirable than alternative aq (for the maximization case). the best alternative is the one which is better than or at least equal to all other alternatives. the wpm is sometimes called dimensionless analysis because its structure eliminates any units of measure. thus, the wpm can be used in single and multi-dimensional decision making problems. all analysis instruments, their function and data collecting method can be seen in figure 2. all analysis instruments above are used for the final goal which is decision making. robbins et al., (2014) stated that decision is a choice made from alternative. decision making process is series of stages consisting of a number of steps including identifying problem, selecting an alternative, and evaluating decision. the process that found this decision making model is a management technology. management technology basically gives contribution in solving learning problems so that learning process can achieve learning goal effectively and efficiently. the result from the study of decisionmaking model then can be applied in management information system. management information system is a system that is integrated between human and machine that is able to give such information to support the running of the operation, the running of management, and the function of decision making in an organization (davis, 2005). to conduct data analysis, data collecting is initially needed. in this study, in order to get deeper data, questionnaire distribution, focus group discussion, and in depth structured interview are done with practitioners of electricity distribution in nec of lampung and related external parties. there are five main interviewees who are representatives from nec, government, electricity association, and consumer protection agencies. 3. results and discussion presently, electricity condition in lampung depends on several factors: the ability of electrical power (reliability of power source supply, power transfer from palembang (south sumatra) both from the number of transferred power and the reliability of its transmission), good voltage condition that is affected by isolator, material type of conductor, diameter of conductor, length of conductor, usage load capacity or power used by community that is affected by culture and economic growth. at this moment, the peak load of lampung reaches ±850 mw with the last peak load in april 2016 as much as 847.5 mw and maximum of 861 mw, capacity of electric power plant in lampung as much as ±500 mw and sumatera interconnection power transfer as much as ±350 mw with transfer minimum of 270 mw and maximum of 360 mw. therefore, lampung electricity condition now can be said mediocre. in this condition, when the main plant unit is having disturbance or maintenance, lampung electricity then becomes deficit. considering the deficit electricity condition, lampung distribution nec conducts varied means for improvement such as electricity distribution management in lampung that is known as lampung sub system, setting rolling blackouts pattern with schedule based on several things which are separation between priority customers and other customers, the number of power produced by power plant and the one that can be distributed, the number of electricity load that must be reduced, electricity distribution based on feeders order in an area and blackout frequency. besides setting blackouts pattern, lampung nec will add power supply, rent a 160 mw power plant, and build transmission in eastern route. voltage improvement is then done, it relates to power transfer through transmission lines from sumatera interconnection, some have been installed with capacitor used to improve voltage in barusman and redaputri: decision making model of electric power fulfillment in lampung province using soft system methodology international journal of energy economics and policy | vol 8 • issue 1 • 2018 131 transmission line, because the longer the distance the smaller the voltage will be. however, it is only small part of it due to limited budget. all means of capacity addition, in its implementation, constrained few things, so that it has not been able to handle electric power deficit effectively. therefore, it is necessary to make a decision-making model of electrical power fulfillment in lampung province. 3.1. decision making model of electric power fulfillment in lampung province using ahp based on the result of interview and focus group discussion with the previous interviewees, it can be arranged ahp hierarchy as the following: from the hierarchy above, there are three (3) hierarchy levels, one (1) goal, which is the electricity fulfillment of lampung community sustainably, two (2) criteria, which are internal and external factors, six (6) sub criteria which are budget availability, hr readiness, implementation technical, population growth, economic growth, and political intervention, and four (4) alternatives which are building additional power plant, renting additional power plant, ipp and excess power and building transmission lines of sumatera interconnection system as shown in figure 3. the table 1 is the definition of each existing criterion, sub criterion and alternative: based on the ahp hierarchy above, questionnaire filled by 5 interviewees from varied fields both from internal and external of pln is made. moreover, the result of the questionnaire is processed by using application of expert choice, so it produces calculation as the following for each criterion, sub criterion, and alternative, as shown in table 2. the study found that in order to achieve the sustainable electricity fulfillment, the decision alternative with the biggest priority is based on internal factors with weight of 0.676, compared with pln external factors (0.324), budget availability is a sub criterion with the biggest weight which is 0.362 compared with sub criterion of human resource readiness with the weight 0.323 and sub criterion of implementation technique with the weight 0.313. moreover, alternative with the biggest weight is building additional power plant (0.090) compared with renting additional power plant (0.029), ipp and excess power (0.039) and building transmission lines (0.078). from the existing weight data, evaluation and evaluation definition are made for each criterion as shown in table 3: to get possibilities of decision making, the weighting result of expert choice above, range is made in accordance with evaluation and definition from each measurement criteria as shown in table 4: therefore, qualitatively, it can be interpreted as the following as in table 5. table 1: definition of criteria criteria, sub criteria, and alternatives definition internal criteria that affect the fulfillment of lampung electricity in internal of pt pln (limited company) external criteria that affect the fulfillment of lampung electricity outside pt pln (limited company) budget availability the amount of budget available in pln to fulfill the needs of lampung community electricity human resource readiness the ability of pln human resource technique in implementing the existing alternative implementation technique easiness of existing alternative implementation completion in fulfilling lampung electricity needs population growth the number of population growth in lampung economic growth the capacity increasing process of lampung economic production that is realized in the form of regional income increase where the existence of economic growth is an indicator the success of economic development political intervention how big the political importance affects/involves in electricity fulfillment problem in lampung building addition power plant the building of new power plant coming from new energy and is renewed by using existing potential in lampung in order to add electricity needs of lampung community renting additional power plant the implementation of power plant renting from the third party to add the needs of electricity of lampung community cooperation with private electricity (ipp and excess power) the implementation of electrical power produced by private party, with difference which ipp is independent power producer, a private party that intentionally builds power plant and produces electrical power and it is sold entirely to pln, while excess power is where there is a private party that has its own power plant and has excessive power so the electrical power is sold to pln building transmission lines of sumatera interconnection system adding transmission eastern lines that connect menggala – seputih banyak, so it adds the reliability of sumatera electricity system interconnection barusman and redaputri: decision making model of electric power fulfillment in lampung province using soft system methodology international journal of energy economics and policy | vol 8 • issue 1 • 2018132 table 3: criteria, evaluation and definition criteria evaluation definition budget availability very adequate budget is enough and excessive adequate budget is enough less adequate budget is not enough human resource readiness very ready very good technical ability ready good technical ability less ready poor technical ability implementation technique very easy implementation of electricity power fulfillment is very easy easy implementation of electricity power fulfillment is easy difficult implementation of electricity power fulfillment is not easy population growth very rapid population growth is very rapid rapid population growth is rapid less rapid population growth is less rapid economic growth very rapid economic growth is very rapid rapid economic growth is rapid less rapid economic growth is less rapid political intervention very strong political intervention affects very strongly strong political intervention affects strongly weak political intervention affects weakly table 2: result of expert choice calculation goal level 1 (criterion) level 2 (sub criterion) alternatives priority to fulfill electricity of lampung sustainably (l:.1000) percent internal (l: .676) 70.7 internal (l: .676) percent budget availability(l: .362) 23.6 budget availability(l: .362) building additional power plant 0.09 renting additional power plant 0.029 ipp & excess power 0.039 building transmission line 0.078 percent human resource readiness (l: .323) 21.8 human resource readiness (l: .323) building additional power plant 0.08 renting additional power plant 0.037 ipp & excess power 0.03 building transmission line 0.071 percent implementation technic (l: .315) 25.3 implementation technic (l: .315) building additional power plant 0.078 renting additional power plant 0.051 ipp & excess power 0.046 building transmission line 0.078 percent external (l: .324) 29.3 external (l: .324) percent population growth (l: .253) 8 population growth (l: .253) building additional power plant 0.026 renting additional power plant 0.014 ipp & excess power 0.01 building transmission line 0.03 percent economic growth (l: .363) 11.2 economic growth (l: .363) building additional power plant 0.043 renting additional power plant 0.017 ipp & excess power 0.017 building transmission line 0.035 percent political intervention (l: .384) 10.1 political intervention (l: .384) building additional power plant 0.025 renting additional power plant 0.015 ipp & excess power 0.015 building transmission line 0.046 barusman and redaputri: decision making model of electric power fulfillment in lampung province using soft system methodology international journal of energy economics and policy | vol 8 • issue 1 • 2018 133 the table 5 is some decision making models that can be taken in the best condition, what alternative that can be taken in condition of each existing criterion. however, if we analyzed the possibility there will be many chances of decision-makings. besides there are many possibilities for decision-making model, to determine the priority of alternative decision-making model in the fulfillment of electrical power in lampung province, to determine alternative priority of decision making of electricity power fulfillment in lampung province, expert choice calculation has weight value that is then conversed into ordinal scale from 1 to 10 with the value of very important to very unimportant, as what can be seen from the table 6: therefore, value change is obtained from the weight of expert choice calculation result along with its ordinal scale are as shown in table 7: to select the best alternative, the methods wsm (kolios et al., 2016) and wpm (chen and hwang, 1992) are used. wsm and wpm method are as shown table 8: 6 1 * | maxwsm i ij j i j a a a w =    =     ∑ i = 1, 2, 3, 4 and 6 1 * | max ( ) jwwpm i ij i j a a a =    =     π i = 1, 2, 3, 4 table 5: decision making model in the best condition criteria budget availability human resource readiness implementation technique population growth economic growth political intervention alternative building additional power plant very adequate very ready very easy less rapid rapid weak renting additional power plant less adequate ready easy less rapid less rapid weak ipp and excess power adequate less ready very easy less rapid less rapid weak building transmission lines very adequate very ready very easy less rapid rapid strong ipp: independent power producer table 6: evaluation range description highly very important very important important adequately important little important little unimportant adequately unimportant unimportant very unimportant highly very unimportant alternative range 0.091–0.1 0.081–0.09 0.071–0.08 0.061–0.07 0.051–0.05 0.041–0.05 0.031–0.04 0.021–0.03 0.011–0.02 0.001–0.01 weight range 0.91–1 0.81–0.9 0.71–0.8 0.61–0.7 0.51–0.6 0.41–0.5 0.31–0.4 0.21–0.3 0.11–0.2 0.01–0.1 ordinal value 10 9 8 7 6 5 4 3 2 1 table 4: evaluation range description very adequate/ready/easy/rapid/strong adequate/ready/easy/rapid/strong less adequate/ready/easy/rapid/strong range 0.0667–0.1 0.0334–0.0667 0–0.0333 table 7: weighting and its ordinal scale alternative weight building aditional power plant renting aditional power plant ipp and excess power building transmission linecriteria internal weight os (wj) weight os (a1j) weight os (a2j) weight os (a3j) weight os (a4j) budget availability 0.362 4 0.090 9 0.029 3 0.039 4 0.078 8 human resource readiness 0.323 4 0.080 8 0.037 4 0.030 3 0.071 8 implementation technique 0.315 4 0.780 8 0.051 6 0.046 5 0.078 8 external population growth 0.253 3 0.026 3 0.014 2 0.010 1 0.030 3 economic growth 0.363 4 0.043 5 0.017 2 0.017 2 0.035 4 political intervention 0.384 4 0.025 3 0.015 2 0.015 2 0.046 5 os: ordinal scale barusman and redaputri: decision making model of electric power fulfillment in lampung province using soft system methodology international journal of energy economics and policy | vol 8 • issue 1 • 2018134 where ai is the-i th alternative (i = 1, 2, 3, 4), aij is the ordinal scale of the-ith alternative and the-jth criteria (j = 1, 2, 3, 4, 5, 6), and wj is the ordinal scale of the weight of the-jth the criteria. the results are presented in table 8. from the calculation result of exponential comparison above, it can be known that in fulfilling nec electricity in lampung sustainably, there are some alternatives of decision making according to wsm and wpm calculation. wsm raises two alternative decisionmaking with the same priority which are building a transmission line and building an additional power plant. for that we need other analysis tools that can show us the main priority in fulfilling the electricity needs in lampung, by using wpm. the results with wpm are that with the existence of the peak load growth projection as much as 9.2% in 2022, building transmission line especially from areas with a surplus supply of electricity such as southern sumatra is an alternative solution for the short term. the transmission line will be connected from aceh to lampung. and then for the medium and long term, building an additional power plant becomes an alternative solution that must be done. pln lampung should use energy source potential in lampung, both water energy, geothermal energy. 4. conclusion there are four hierarchy levels of structured problem that can be found with ahp, first is goal which is the fulfillment of electricity in lampung community sustainably, second: two criteria which are internal and external factors, third: six sub criteria, which are budget availability, human resource readiness, implementation technique, population growth, economic growth, and political intervention, and fouth: four alternatives which are building additional power plant, renting additional power plant, ipp and excess power, and building transmission lines of sumatera interconnection system. afterwards, analysis of decision making model possibilities is done, and it is obtained that there are 30 possibilities of decision making model in fulfilling electricity needs in lampung based on the calculation of mcdm that can be chosen in varied dynamic conditions. moreover, according to wsm calculation, there are two alternative decision-making with the same priority which are building a transmission line and building an additional power plant. for that we need other analysis tools that can show us the main priority in fulfilling the electricity needs in lampung, by using wpm. according to wpm calculation, building transmission line especially from areas with ahp to inves�gate criteria and solu�on alterna�ve of decision making interview and focus group discussion mcdm to conduct decision making towards some decision alterna�ves that must be taken in some criteria that will be considera�on ques�onnaire and interview mpe to search decision alterna�ve priority ques�onnaire and interview data analysis instrument func�on data collec�ng method figure 2: analysis instruments level 1 level 2 level 3 goal criteria 1 criteria 2 criteria 3 criteria 5criteria 4 criteria 6 alterna�ve 1 alterna�ve 2 alterna�ve 3 alterna�ve 4 figure 1: a three level hierarchy (adapted from saaty and vargas, 2012. p. 3) table 8: the calculation of wsm and wpm for the four alternatives methods building additional power plant renting additional power plant ipp and excess power building transmission line wsm 141 (p1) 74 (p3) 67 (p4) 141 (p1) wpm 1.55×1017 (p2) 55×109 (p3) 3.3×109 (p4) 2.97×1017 (p1) (pi) means priority i=1, 2, 3, 4. wsm: weighted sum method, wpm: weighted product method, ipp: independent power producer barusman and redaputri: decision making model of electric power fulfillment in lampung province using soft system methodology international journal of energy economics and policy | vol 8 • issue 1 • 2018 135 a surplus supply of electricity such as southern sumatra is an alternative solution for the short term. and then for the medium and long term, building an additional power plant becomes an alternative solution that must be done. based on the entire study results above, pln is able to conduct improvement in lampung electricity condition with several existing alternatives especially building transmission line. in addition to continuing the existing transmission, later if sumatera has been connected as a whole and has a reliable transmission, electricity can be distributed from anywhere on the sumatera island. besides building a transmission line, pln also needs to build an additional power plant for the electricity reliability of the local area. 5. acknowledgment the authors would like to thank nec indonesia (pln) for providing the data and giving permission to use it. we would also like to thank nec management, stakeholders, and the local government of lampung province for providing the time during the focus group discussion of this study. references checkland, p. (1981), systems thinking; systems practice. new york: john wiley & sons. checkland, p. (2000), systems thinking, systems practice, including a 30-year retrospective. chichester: john wiley and sons ltd. checkland, p., winter, m. (2006), process and content: two ways of using ssm. journal of the operational research society, 57(12), 1435-1441. checkland, p., scholes, j. (1999), soft systems methodology in action. new york: john wiley & sons ltd. chen, s.j., hwang, c.l. (1992), fuzzy multiple attribute decision making: methods and applications, lecture notes in economics and mathematical systems, no. 375. berlin: springer verlag. davis, g.b. (2005), management information systems. massassusset, ma: blackwell publishing. jones, a., kaufmann, a., zimmermann, h.j. (1986), fuzzy sets theory and applications. dordrecht: d. reidle publishing company. kolios, a., mytilinou, v., minguez, el., salonitis, k. (2016), a comparative study of multiple criteria decision making methods under stochastic inputs. energies, 9, 1-21. maqin, r.a., sidharta, i. (2017), the relationship of economic growth with human development and electricity consumption in indonesia, international journal of energy economics and policy, 7(3), 201-207. mylnikov, l., kuetz, m. (2017), electric power supply subsystem and its role in solving production system management and planning issues, international journal of energy economics and policy, 7(5), 191-200. pln. (2014), statistik pln 2014. available from: http://www.pln.co.id/ wp-content/uploads/2012/01/statistik-pln-2014_for-website-10juni-2015.pdf. [last retrieved on 2016 jul 01]. pohekar, s.d., ramachandran, m. (2004), application of multicriteria decision making to sustainable energy planninga review. goal criteria sub criteria alternative building additional power plant cooperating with private electricity agencies (ipp & excess power) building transmission line system of sumatera interconnection renting additional power plant electricity of lampung community is fulfilled sustainably human resource readiness implementation technique economic growth political intervention population growth eksternal internal budget availability figure 3: ahp model of electric power fulfillment in lampung province alternative explanation: goal → electricity of lampung community is fulfilled sustainably criteria → internal and external sub criteria → budget availability, human resource readiness, implementation technique, population growth, economic growth, political intervention alternative → building additional power plant, renting additional power plant, cooperating with private electricity agencies (ipp and excess power), building transmission line system of sumatera interconnection barusman and redaputri: decision making model of electric power fulfillment in lampung province using soft system methodology international journal of energy economics and policy | vol 8 • issue 1 • 2018136 renewable and sustainable energy reviews, 8, 365-381. robbins, s.p., decenzo, d.a., coulter, m., anderson, i. (2014), fundamental of management. 7th ed. toronto: pearson education inc. rodrigues, l.f., madeira de souza, m.a., paula dos santos dias, t. (2017), performance assessment of brazilian power transmission and distribution segments using data envelopment analysis, international journal of energy economics and policy, 7(3), 14-23. s a a t y, t. l . ( 1 9 8 0 ) , t h e a n a l y t i c h i e r a r c h y p r o c e s s . new york: mcgraw-hill. saaty, t.l. (1992), decision making for leaders. pittsburgh: rws publications. saaty, t.l., vargas, l.g. (2012), models, methods, concepts and applications of the analytic hierarchy process. 2nd ed. new york: springer verlag. tzeng, g.h., huang, j.j. (2011), multiple attribute decision making methods and applications. new york: crc press. triantaphyllou, e., sanchez, a. (1997), a sensitivity analysis approach for some deterministic multi-criteria decision making methods. decision sciences journal, 28(1), 151-194. zimmermann, h.j. (1987), fuzzy sets, decision making, and expert systems. boston: kluwer academic publishers. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 4 • 2023 1 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(4), 1-8. energy operations for resident and its implications for economic growth: indonesia’s new capital city as a case study rosyadi rosyadi1*, zamruddin hasid2, purwadi purwadi3 1department of economics and development studies, faculty of economics and business, universitas tanjungpura, indonesia, 2department of economics, faculty of economics and business, universitas mulawarman, indonesia, 3department of management, faculty of economics and business, universitas mulawarman, indonesia. e-mail: rosyadi@ekonomi.untan.ac.id received: 27 february 2023 accepted: 10 june 2023 doi: https://doi.org/10.32479/ijeep.14182 abstract the topic of “ikn” is not just a discourse. this is good news for indonesia which is trying to be free from prosperity conflicts, which so far have only been concentrated in one area. what is more crucial is that the struggle for economic resources is also always won by regions that have inclusive grdp growth, competitive workers, and solid infrastructure facilities, especially in java. this is because regions such as kalimantan, their economic prospects are sinking because the transformation of consumption and purchasing power is not working. therefore, this paper initiates the relationship between population, electricity, water production, and regional/grdp growth in the center of ikn and 4 buffer zones. systematics in data extraction uses panel regression which presents time-series data (8 periods). valuable insights conclude some important findings. the population has been proven to increase electricity in ppu, paser, balikpapan and samarinda. positive causality also indicates the effect of population on water production in ppu and balikpapan. however, it also influences positively. on the other hand, electric power has a positive impact on economic growth in ppu, while in paser, water production actually increases economic growth. population as the only variable that has no effect on economic growth in all cases. only kukar has all the opposite variables and has a negative effect. finally, preparations towards a fair ikn development perspective consider long and short term policy packages. keywords: populations, electricity, clean water, regional growth, new ikn jel classifications: j11, l94, l95, r11 1. introduction 1.1. background the government’s decision to change the capital city of indonesia from jakarta to east kalimantan is the right idea (azmy, 2021; salya, 2022; shimamura and mizunoya, 2020; sugihartati et al., 2020). via the regulations contained in law number: 3 of 2022 which exposes the “national capital” is seen as an expansive leap. specifically, east kalimantan’s position as a new administrative center located in the sepaku-penajam paser utara (ppu) area, has great expectations of resolving 4 primary polemics: economic expansion, protection against natural disaster vulnerabilities, environmental degradation, and population growth uncontrollable. so far, the government’s obsession with accelerating regional arrangement and equity between regions in indonesia has often been hindered by the low quality of human resources and suboptimal access to infrastructure that connects the network to the outermost islands (hasid et al., 2023). the island of java is no exception, which has complete facilities, inclusive investments, transportation accommodations, and a variety of supporting public needs. the irony is that, for example, those who live on the island of borneo are quite distorted by the integration of development which sucked up the government budget in the old capital city. at the same time, the overcrowded human routine on the island of java also presents problems that never stop, for example: a decrease in the level of happiness in life, a decline in welfare due to this journal is licensed under a creative commons attribution 4.0 international license rosyadi, et al.: energy operations for resident and its implications for economic growth: indonesia’s new capital city as a case study international journal of energy economics and policy | vol 13 • issue 4 • 20232 fast-moving levels of competition and slower-moving employment opportunities, triggering crimes and criminal acts, pollution, health threats, clean water crises, and other concrete matters that urge the implementation of relocation (busari et al., 2022). figure 1 represents a map of the new capital or what is called “ikn.” in line with the review above, that the ikn is located in the ppu regency. meanwhile, 4 buffer zones in ikn were selected based on their respective roles. first, ikn is concentrated in ppu, in the sepaku area to be precise. in that context, ppu became indonesia’s new government system (ministry of national development planning of the republic of indonesia, 2021). second, paser regency is an essential target for accommodating urbanization from outside kalimantan and is promoted for the development of residential areas. third, balikpapan was chosen as a logistics-based metropolis, where this city has a lot of warehouses and strategic sea lane connections in east kalimantan. balikpapan also provides services that can meet the needs of millions of people. fourth, the administrative point of east kalimantan continues to rotate in samarinda city. besides that, samarinda is also claimed to be the beginning of east kalimantan civilization, so that tourism planning for samarinda city is ensured to still adhere to local principles that have been rooted for hundreds of years (ilmi et al., 2022). fifth, kutai kartanegara (kukar) is pursued as a suburb that is separated from the three buffer zones to stimulate food security. in principle, the oriented kukar selection solution encourages the success of plantation cultivation, food crops and forestry, and fisheries. jiuhardi et al. (2022) emphasizes that changing the status of agricultural land from fertile to barren is a “bad signal” reflecting the destruction of the food supply for generations. there is an aggressive transition from agriculture to industry, services and real estate on the island of java which also contributes to the greenhouse gas effect (priyagus, 2021). according to gaveau et al. (2014) and karjoko et al. (2020), although east kalimantan is highlighted globally by excessive natural exploitation such as: new reserves of coal, gas and oil, it remains a priority of the “lungs of the world” because when compared to other areas, the proportion of protected forest in east kalimantan still relatively awake. on the one hand, the ikn agenda in 2024 is projected to support universal mobility. even so, there are still striking deficiencies and must receive substantive attention, where the commitment of stakeholders to develop an energy generation foundation that exceeds the ideal composition. the urgency in reforming energy manufacturing cannot be separated from the harmonization of devices, technology, and network maintenance costs that bridge new life interactions. constraints in water, gas and electricity generators have not been maximized in east kalimantan. poor land-river infrastructure makes it more difficult and isolates energy commodities from one area to another (lestari et al., 2022). in addition, hayakawa et al. (2020), suharso and ahyudanari (2020), and wijaya et al. (2020) show that transportation costs are expensive and spatial distances are far apart, also draining time and finances. 1.2. existing situation even though the ikn has been inaugurated, the population conditions in east kalimantan have not changed drastically. it is projected that there will be a prominent demographic trend in the upcoming 2024 period. initially, around 2,000 domestic residents entered the new ikn and this number is predicted to increase sharply again if immigrants from abroad join them. in fact, in 2045, around 1.7 million to 1.9 million people will migrate to east kalimantan (info tempo, 2022). now, to be precise, in 2021, indonesia’s population density has exceeded 142 people/km2 and that figure is still below east kalimantan, where the population density is only 30 people/ km2 (central bureau of statistics of the republic of indonesia, 2022). at the east kalimantan level, the densest population cluster is in balikpapan: 1,357 people/km2, while samarinda is ranked (source: creations of the authors) figure 1: design of ikn and key areas rosyadi, et al.: energy operations for resident and its implications for economic growth: indonesia’s new capital city as a case study international journal of energy economics and policy | vol 13 • issue 4 • 2023 3 2: 1,160 people/km2, and ppu is ranked 4: 62 people/km2. uniquely, the population density in kukar and paser is relatively stable. figure 2 captures the demographic dynamics of those living in ppu, paser, balikpapan, samarinda, and kukar which appear to be unbalanced. overall, those who choose to live in urban areas are skilled workers and not some non-permanent residents. take for example samarinda and balikpapan, which on average are inhabited by almost half the population of east kalimantan. within 8 periods, the average population in samarinda was the highest compared to the others or ranked 1: 830,167 people. then, kukar with the largest area is ranked 2: 745,664 people, while balikpapan is ranked 3: 660,061 people, paser is ranked 4: 277,258 people, and ppu is ranked 5: 166,885 people. in other words, the certainty that some ppu areas will become ikn is a viable option referring to demographic aspects. it’s just that, when the peak of the spread of the coronavirus 2019 (covid-19) entered indonesia in early 2020, it disrupted the ikn development work. this also includes disruption to human activities, including infection and casualties in east kalimantan. at its peak, thousands of lives were lost due to contamination by covid-19 in kukar and samarinda in 2020 (roy et al., 2021). from the components of electricity and clean water as summarized in figures 3 and 4, it implies that energy channels are still limited. too to facilities, this constraint is triggered by the intensity of the generators for generating water and electricity that are not yet modern. in fact, the basic procedures that enable efficient use of natural resources and lead to economic prosperity in a region. the development of electric power between regions in east kalimantan is very disparity. this is a dilemma that is reflected by the electricity capacity created from the main generating source which is dominated by samarinda. during 2015-2022, as a government corridor, samarinda is able to generate electricity to customers reaching an average of 847,243 kw (rank 1). then, the power plant from balikpapan city (rank 2), has generated power with an average of 219,561 kw, but kukar, which is passed by most of the mahakam river (rank 3), only extracts electrical energy of 70,013 kw. the ppu is in rank 4: 63,698 kw and paser (rank 5): 51,673. furthermore, figure 4 explains the productivity of water energy in ikn. geographically, the largest coastline in east kalimantan which is in balikpapan, makes it easy for this city to be traversed by sea transportation and that is related to power plants that take advantage of ocean currents, ocean waves, and sea tides or differences in sea layer temperature to explore renewable energy. interestingly, although there are weaknesses in clean water reserves, balikpapan is the first largest supplier of water energy: an average of 1,460.88 per second which outperforms kukar (rank 2): an average of 1,375.63/s, samarinda is ranked 3: average 1,243.38/s, paser which is only in rank 4: average 246.32/s, and ppu (rank 5): average is 144.43/s. publication by kencanawati and mustakim (2017) reveals that a program called “water treatment plant (wtp)” from several dams in balikpapan has sanitized clean water needs for households. wtp is very central to the human life cycle. the diagram below reports on the economic growth performance of electricity and water supply based on gross regional domestic product (grdp) in the ikn from 2015 to 2022. in the 5 projects that are currently in the management stage, the electricity and water sectors are in a positive pattern. in detail, the macroeconomic structure in terms of electricity and water in the ikn area, the majority are high above the average constant growth based on other pillars. statistically, the economic growth of both illustrates an average of 13.3% for samarinda (rank 1). an impressive growth score was also shown by kukar at rank 2: 11.72%, rank 3: balikpapan achieved 11.14%, rank 4: paser reached 9.3%, and finally ppu was confirmed at 8.67% (figure 5). (source: central bureau of statistics of east kalimantan, 2022) figure 2: information on population in ikn, 2015–2022 (source: central bureau of statistics of east kalimantan, 2022) figure 3: profile of electric power in ikn, 2015-2022 (source: central bureau of statistics of east kalimantan, 2022) figure 4: profile of water production in ikn, 2015-2022 rosyadi, et al.: energy operations for resident and its implications for economic growth: indonesia’s new capital city as a case study international journal of energy economics and policy | vol 13 • issue 4 • 20234 in practice, the classification in electricity and water grdp is divided into two different groups. first, the electricity economy covers the activities of procuring electricity induced by natural and artificial gas, hot steam, fossil, cold air, diesel and the like through permanent pumps or pipes. the dimensions of materials cannot be determined with certainty, including electric utilities. electricity that is run is electricity that is sold, self-used, lost in transmission and distribution, and stolen electricity. as with production data, selling prices and power plant prices are taken from pln on a quarterly basis as well as statistics published annually. the data collection standard also collects electricity subsidy data from government institutions such as the ministry of finance. technically, the clean water sector is identified as an economic factor that empowers river water, rain water, swamp water, or seawater to be processed for distillation into various pipelines and connected to companies and households. the raw materials are assembled from water collection to the purification phase, but it is not limited to the operation of irrigation equipment for agricultural purposes. similar to the concept of electricity held by the state electricity company (pln) and by private companies (non-pln), water treatment consists of: generation, delivery, and distribution of electricity to consumers, which is controlled by regional drinking water companies (pdams) such as: electricity generation by regional owned enterprises (bumd) and electricity sorted by individual businesses or as a union with the aim of profit. the relevance of calculating the two sub-sectors adopts a production approach. output at constant prices applies the revaluation method by multiplying the quantum volume of goods in each period with the basic price per unit of production in 2010, while output at current prices is measured via multiplication between the quantum of goods and the basic price per production unit for a certain period. the gross added value (ntb) on the basis of constant or valid prices both calculates the output in each period with the ntb ratio. 1.3. objectivity and hypothesis the terminology in “ikn motives” dedicates a rational momentum to anticipating the depletion of open space in java which cannot be postponed and demands holistic improvement. unfortunately, the enthusiasm for solving development problems has not been understood by layers of stakeholders, responded with mature execution, ignoring market share, and uncertainty over energy allocation. special records of the combination of electricity and water in ikn need to be tested for quality. progress must be sustainable and adjusted to the quantity of the population, so that it does not become a trap that actually breaks the nature of the establishment of the ikn. the motivation for this paper is structured as follows: • study the relationship between the population of electricity and water production; • investigate the relationship between population, electricity, and water production on grdp growth. figure 6 demonstrates the probability of 5 hypotheses divided into 2 points. the alternative hypothesis (ha) represents that the hypothesis is accepted and the null hypothesis (h₀) proves that the hypothesis is rejected. thus, it makes sense to propose the following hypothesis: • the size of the population indicates an increase in electricity power and water production; • the size of the population, electricity, and water production indicates an increase in grdp growth. 2. research method 2.1. data variance the quantitative database was obtained from a government agency for the province of kalimantan named the central bureau of statistics. data characteristics are secondary in the 2015-2022 period. these data about variables. data tabulation instruments are contained in official documents (websites of all years). the total population is 160 data, where each unit is 32 samples. table 1 details the variable parameters. the four variables have their respective tasks. the population is modified into an independent variable to explain its effect on electricity, water production and economic growth. on the other track, economic growth is evaluated by 2 independent variables: electricity and water production. the only dependent variable is economic growth. 2.2. model to describe the relationship between variables, this study uses panel data regression. in the regression, it involves 4 (source: central bureau of statistics of east kalimantan, 2022) figure 5: economic growth of electricity and water in ikn, 2015-2022 (source: own) figure 6: variable framework rosyadi, et al.: energy operations for resident and its implications for economic growth: indonesia’s new capital city as a case study international journal of energy economics and policy | vol 13 • issue 4 • 2023 5 tests: correlation (r), coefficient of determination (r2), f test (anova), and t test. data input techniques are interpreted via the international business machines–statistical package for the social sciences or abbreviated “ibm-spss.” the analysis procedure is set up into 2 mechanisms. the first track examines the causality of population to electricity and water production. in the second track, it explains the effects of population, electricity, and water production on economic growth. the fundamental equation function is written as follows: yit = δyi,t−1+βxit+μit (1) referring to the equation above, below are two econometric equations that are adjusted based on the variable path: elec_powit = δelec_powit−1+β1popit+μit (2) wat_proit = δwat_proit−1+β2popit+μit (3) econ_groit = econ_groit−1+β3popit+β4elec_powit+β5wat_proit+μit (4) symbols indicator: δ = scalars, xit = 1 × k, β = k × 1, i = 1.,n, t = 1.,t, and μit = μi + vit following a one-way error in the model. 3. findings 3.1. correlation matrix at the degree of probability (ρ) = 99% or 0.01, it is found that there is an agreement between the cases in ppu and balikpapan, where there is a significant two-way impact between the population on electricity (ρ = 0.002; ρ = 0.000) and water production (ρ = 0.003; ρ = 0001), also electricity with water production and vice versa (ρ = 0.009; ρ = 0.001). in samarinda, the population does not have a two-way impact on the production of water and electricity, but instead water production has a significant two-way impact on electricity (ρ = 0.003). surprisingly, it was only in kukar that all the two-way variables were not significantly related. other evidence shows that at the probability level (ρ) = 95% or 0.05 for paser, it can be concluded that population has a significant two-way effect on electricity: ρ = 0.039 and economic growth: ρ = 0.038 (table 2). 3.2. regression estimation over a duration of 8 years, tables 3-7 mention the feasibility of the model, simultaneous causality, and partial causality in the relationship between variables. empirically in the case of ppu, table 1: variable formats variables/code definition expected sign populations (pop) total population of all genders –/+ electric power (elec_pow) electrical power capacity –/+ water production (wat_pro) water capacity per second –/+ economic growth (econ_gro) the percentage growth of grdp at constant prices in the electricity and water division –/+ (source: central bureau of statistics of east kalimantan, 2022) table 2: correlation results ppu (n=32) items pop elec_pow wat_pro econ_gro pop 1 0.911** (0.002) 0.888** (0.003) 0.053 (0.900) elec_pow 0.911** (0.002) 1 0.841** (0.009) −0.183 (0.665) wat_pro 0.888** (0.003) 0.841** (0.009) 1 0.220 (0.601) econ_gro 0.053 (0.900) −0.183 (0.665) 0.220 (0.601) 1 paser (n=32) items pop elec_pow wat_pro econ_gro pop 1 0.732* (0.039) 0.538 (0.169) −0.734* (0.038) elec_pow 0.732* (0.039) 1 0.434 (0.282) −0.567 (0.142) wat_pro 0.538 (0.169) 0.434 (0.282) 1 −0.339 (0.412) econ_gro −0.734* (0.038) −0.567 (0.142) −0.339 (0.412) 1 balikpapan (n=32) items pop elec_pow wat_pro econ_gro pop 1 0.981** (0.000) 0.920** (0.001) −0.570 (0.141) elec_pow 0.981** (0.000) 1 0.931** (0.001) −0.676 (0.066) wat_pro 0.920** (0.001) 0.931** (0.001) 1 −0.570 (0.140) econ_gro −0.570 (0.141) −0.676 (0.066) −0.570 (0.140) 1 samarinda (n=32) items pop elec_pow wat_pro econ_gro pop 1 −0.699 (0.054) −0.553 (0.155) 0.135 (0.750) elec_pow −0.699 (0.054) 1 0.888** (0.003) −0.577 (0.135) wat_pro −0.553 (0.155) 0.888** (0.003) 1 −0.567 (0.143) econ_gro 0.135 (0.750) −0.577 (0.135) −0.567 (0.143) 1 kukar (n=32) items pop elec_pow wat_pro econ_gro pop 1 0.455 (0.257) −0.307 (0.460) 0.101 (0.812) elec_pow 0.455 (0.257) 1 0.515 (0.191) −0.299 (0.472) wat_pro −0.307 (0.460) 0.515 (0.191) 1 −0.125 (0.768) econ_gro 0.101 (0.812) −0.299 (0.472) −0.125 (0.768) 1 (source: own computation in ibm-spss v. 24. **ρ<1% and *ρ<5%) rosyadi, et al.: energy operations for resident and its implications for economic growth: indonesia’s new capital city as a case study international journal of energy economics and policy | vol 13 • issue 4 • 20236 the determination of the population towards electricity and water production is classified as “strong” (r-square = 83%; 78.8%), while there is a “moderate” determination of the 3 factors that influence grdp growth (r-square = 50.8%). based on collectivity, the population has a simultaneous impact on electricity (ρ = 0.002) and water production (ρ = 0.003). there is a failure in the relationship between population, electricity, and water production on grdp growth (ρ = 0.170), so the impact is not simultaneous. other facts reveal that population has a partially positive effect on electricity (ρ = 0.002) and water production (ρ = 0.003), and electricity on water production (ρ = 0.019). especially in table 3, it also tells the effect of population (ρ = 0.083) and water production (ρ = 0.900) which have no impact on grdp growth. in table 4, the reality in paser explains that only the population has a “moderate” determination for electric power (r-square = 53.6%). the increase in population does not guarantee an increase in water production which is marked by a “weak” determination (r-square = 28.9%). this is also confirmed by the “weak” r-square value (33.2%) in population participation, electricity, and water production on grdp growth. this is automatically illustrated by the identity of the simultaneous positive relationship between the population and electricity (ρ = 0.039), but there is a stagnant effect of the population on water production (ρ = 0.169) and the three independent variables on grdp growth (ρ = 0.364) which are not simultaneous. what is encouraging is the relationship between population and electricity (ρ = 0.039) and water production on grdp growth (ρ = 0.038). what is surprising is what happened in balikpapan, where the determinants of population, electricity, and water production on grdp growth are classified as “moderate” (r-square = 48.3%). on the contrary, the massive pattern is reflected by the “near perfect” determination of the population towards electricity (r-square = 96.3%) and the “strong” determination between the population towards water production (r-square = 84.6%). on another occasion, the weak determination between population, electricity, and water production on grdp growth proved to be in line with the simultaneous (ρ = 0.192) and partial (ρ = 0.271; 0.636; 0.141) relationships which did not have a positive impact. in an integrated manner, the population plays a vital role in electric power (ρ = 0.000) and water production (ρ = 0.001). the bright spot referring to table 6 introduces that there is a “weak” determination for all linkages (r-square = 48.9%; 30.6%; 34.7%). the regression output in samarinda presents table 3: regression in ppu (n=32) attributes r-square adjusted r-square f-statistic/prob. standardized coeff. t-statistic/prob. h1(a): pop --> elec_pow 0.830 0.801 29.216 (0.002) 0.911 5.405 (0.002) h1(b): pop --> wat_pro 0.788 0.753 22.350 (0.003) 0.888 4.728 (0.003) h2(a): pop --> econ_gro 0.508 0.311 2.581 (0.170) −1.252 −2.162 (0.083) h2(b): elec_pow --> econ_gro 1.272 2.196 (0.019) h2(c): wat_pro --> econ_gro 0.053 0.131 (0.900) (source: own computation in ibm-spss v. 24) table 4: regression in paser (n=32) attributes r-square adjusted r-square f-statistic/prob. standardized coeff. t-statistic/prob. h1(a): pop --> elec_pow 0.536 0.459 6.937 (0.039) 0.732 2.634 (0.039) h1(b): pop --> wat_pro 0.289 0.171 2.440 (0.169) 0.538 1.562 (0.169) h2(a): pop --> econ_gro 0.332 0.065 1.245 (0.364) −0.518 −1.277 (0.258) h2(b): elec_pow --> econ_gro −0.114 −0.280 (0.790) h2(c): wat_pro --> econ_gro −0.734 2.649 (0.038) (source: own computation in ibm-spss v. 24) table 5: regression in balikpapan (n=32) attributes r-square adjusted r-square f-statistic/prob. standardized coeff. t-statistic/prob. h1(a): pop --> elec_pow 0.963 0.957 156.881 (0.000) 0.981 12.525 (0.000) h1(b): pop --> wat_pro 0.846 0.820 32.956 (0.001) 0.920 5.741 (0.001) h2(a): pop --> econ_gro 0.483 0.276 2.334 (0.192) −1.088 −1.236 (0.271) h2(b): elec_pow --> econ_gro 0.443 0.503 (0.636) h2(c): wat_pro --> econ_gro −0.570 −1.697 (0.141) (source: own computation in ibm-spss v. 24) table 6: regression in samarinda (n=32) attributes r-square adjusted r-square f-statistic/prob. standardized coeff. t-statistic/prob. h1(a): pop --> elec_pow 0.489 0.404 5.742 (0.045) 0.699 2.396 (0.036) h1(b): pop --> wat_pro 0.306 0.190 2.644 (0.155) −0.553 −1.626 (0.155) h2(a): pop --> econ_gro 0.347 0.086 1.327 (0.345) −0.347 −0.441 (0.677) h2(b): elec_pow --> econ_gro −0.259 −0.330 (0.755) h2(c): wat_pro --> econ_gro 0.135 0.333 (0.750) (source: own computation in ibm-spss v. 24) rosyadi, et al.: energy operations for resident and its implications for economic growth: indonesia’s new capital city as a case study international journal of energy economics and policy | vol 13 • issue 4 • 2023 7 only a simultaneous or partial relationship in the population to electricity that has a positive effect (ρ = 0.045; 0.036), while there is no simultaneous correlation between the population and water production (ρ = 0.155) and population, electricity, and water production on grdp growth (ρ = 0.345; 0.677; 0.755; 0.750). in table 7, we articulate the “very weak” coefficient of determination for all linkages, where the r-square is 20.7%, 9.4%, and 9.1%. none of the variables have a simultaneous and partial effect. it is explained by the probability scores in the f-statistic (ρ = 0.257; 0.460; 0.789) and the probability of the t-statistic (ρ = 0.257; 0.460; 0.549; 0.940; 0.812). 4. conclusion and discussion this paper applies causality between the population towards electricity power, water production, and economic growth in the electricity and water sector with the coverage of ikn throughout 8 periods. as a result, imagine 5 points from each region. first, learning at ppu accepts the hypotheses h₁(a), h₁(b), and h₂(b) and denies the hypotheses h₂(a) and h₂(c), so that the final hypothesis is concluded as “population has a positive effect on electric power and production water” and “electricity has a positive effect on grdp growth.” second, learning in paser, accepts the hypotheses h₁(a) and h₂(c) and denies the hypotheses h₁(b), h₂(a), and h₂(b), so that it is concluded that the final hypothesis reads “population has a positive effect on electric power” and “water production has a positive effect on grdp growth.” third, learning in balikpapan, accepts the hypotheses h₁(a) and h₂(b) and denies the hypotheses h₂(a), h₂(b), and h₂(c), so that it is concluded that the final hypothesis reads “population has a positive effect on electric power and production water.” fourth, learning in samarinda, only accepts hypothesis h₁(a) and the rest rejects hypotheses h₂(b), h₂(a), h₂(b), and h₂(c), so that the final hypothesis is concluded as “population has a positive effect on electric power.” fifth, learning in kukar, none of the hypotheses were accepted and denied all the hypotheses put forward, so the final hypothesis reads “population does not affect electricity and water production, then population, electricity and water production also do not have an impact on grdp growth.” in the nuances of electrical energy, this is tied to the demand side or the consumption level of the population. relevant publications on both relationships are highlighted by delong and burger (2015), holdren (1991), hu et al. (2021), muzayanah et al. (2022), and vo and vo (2021) on a global scale, for example at the level of indonesia, england, china, wales, united states, sweden, and nations in southeast asia. not only rapid climate change, human greed is also the root cause of water crises in dry countries, as concrete examples are libya and kenya. in the scenario of the sustainability of the earth, the two are reciprocally related (abughlelesha and lateh, 2013; okello et al., 2015). at first, in the 19th century, water supply companies pioneered and offered water products to consumers, where the availability of water was still abundant and people independently built manual or drilled wells. yet, nowadays, this has changed drastically, and it seems as if the population is being dragged down strongly, where this opportunity is used by companies to continue to consume more hygienic water content. as we enter the era of the industrial revolution, he and gao (2021), imasiku and ntagwirumugara (2020), nepal and paija (2019), and rehman and deyuan (2018) discuss a brilliant new “new civilization” in a different lens. in rwanda, pakistan, south asia, and china, it is noticed that water and electricity supplies are decreasing as an increasing population builds up in metropolitan areas. generally, in the necessities of daily life, humans always deplete water and electricity resources which prolong scarcity. but, the situation was unavoidable. nath (2020), thaker et al. (2019), and shengfeng et al. (2012) examined the dual effect of per capita electricity consumption and real gross domestic product (gdp) in china, malaysia and india. with the modulation of electricity, it brings the proper verifiability of gdp growth. population dependence on water consumption also triggers significant gaps in gdp value added in european union and central asian countries, as well as china (ferasso et al., 2019; hao et al., 2019; turmunkh, 2021; yang and wen, 2018). in the short term, the results are linear, but local aquatic habitats in nature that are consumed expansively can actually worsen the ecology. the discrepancy in this manuscript lies in the dataset which is framed over a period of 8 years. other limitations are also only concentrated in a few cases. in the future, other researchers need to rethink the formulation of a more actual method. follow-up agenda for communities involved in making policy guidelines, to be more pro-active, cooperative, and to protect regulations relevant to energy development from traditional to more modern ways. fighting and banning the excessive use of electricity and water is a constructive measure. besides that, the population density around the new ikn must be surrounded by adequate water and electricity capacity without neglecting efficiency. finally, the authors also warn that in fulfilling future per capita energy in ikn buffer areas, local water and electricity generators can be developed independently. table 7: regression in kukar (n=32) attributes r-square adjusted r-square f-statistic/prob. standardized coeff. t-statistic/prob. h1(a): pop --> elec_pow 0.207 0.075 1.566 (.257) 0.455 1.251 (0.257) h1(b): pop --> wat_pro 0.094 −0.057 0.624 (0.460) −0.307 −0.790 (0.460) h2(a): pop --> econ_gro 0.091 −0.273 0.249 (0.789) −0.320 −0.642 (0.549) h2(b): elec_pow --> econ_gro 0.040 0.080 (0.940) h2(c): wat_pro --> econ_gro 0.101 0.249 (0.812) (source: own computation in ibm–spss v. 24) rosyadi, et al.: energy operations for resident and its implications for economic growth: indonesia’s new capital city as a case study international journal of energy economics and policy | vol 13 • issue 4 • 20238 references abughlelesha, s.m., lateh, h.b. (2013), a review and analysis of the impact of population growth on water resources in libya. world applied sciences journal, 23(7), 965-971. azmy, a.s. (2021), examining the relocation of the capital city of indonesia through the state perspective in political economy. polit journal, 1(1), 26-35. busari, a., rochaida, e., hasid, z., erwin kurniawan, a. (2021), population and economic growth nexus: evidence from indonesia. economic alternatives, 28(4), 697-710. central bureau of statistics of east kalimantan. (2022), publikasi. available from: https://kaltim.bps.go.id/publication.html [last accesed on 2023 feb 07]. central bureau of statistics of the republic of indonesia. (2022), kepadatan penduduk menurut provinsi (jiwa/km2), 2019-2021. available from: https://www.bps.go.id/indicator/12/141/1/kepadatanpenduduk-menurut-provinsi.html [last accessed on 2023 feb 02]. delong, j.p., burger, o. (2015), socio-economic instability and the scaling of energy use with population size. plos one, 10(6), e0130547. ferasso, m., bares, l., ogachi, d., blanco, m. (2021), economic and sustainability inequalities and water consumption of european union countries. water, 13(19), 2696. gaveau, d.l.a., sloan, s., molidena, e., yaen, h., sheil, d., abram, n.k., ancrenaz, m., nasi, r., quinones, m., wielaard, n., meijaard, e. (2014), four decades of forest persistence, clearance and logging on borneo. plos one, 9(7), e101654. hao, y., hu, x., chen, h. (2019), on the relationship between water use and economic growth in china: new evidence from simultaneous equation model analysis. journal of cleaner production, 235, 953-965. hasid, z., mire, m.s., rochaida, e., wijaya, a. (2023), power generation infrastructure and its effect on electric energy consumption: context in indonesia, 2013-2020. international journal of energy economics and policy, 13(1), 52-60. hayakawa, k., isono, i., kumagai, s. (2020), transportation costs in archipelagos: evidence from indonesia. the developing economies, 58(3), 227-241. he, y., gao, s. (2021), electricity water consumption and metropolitan economic growth: an empirical dual sectors dynamic equilibrium model. frontiers in energy research, 9, 795413. holdren, j.p. (1991), population and the energy problem. population and environment, 12(3), 231-255. hu, m., wang, y., xia, b., huang, g. (2021), energy consumption and economic development in guangdong, china: distribution, relationship and causes. available from: https://doi.org/10.21203/ rs.3.rs-160873/v1 [last accessed on 2023 feb 10]. ilmi, z., asnawati, a., judiarni, j.a. sampeliling, a., haribowo, r., za, s.z. (2022), what drives the tourism industry in samarinda? an empirical evidence. geojournal of tourism and geosites, 43(3), 976–985. imasiku, k., ntagwirumugara, e. (2020), an impact analysis of population growth on energy-water-food-land nexus for ecological sustainable development in rwanda. food and energy security, 9(1), e185. jiuhardi, j., hasid, z., darma, s., darma, d.c. (2022), sustaining agricultural growth: traps of socio-demographics in emerging markets. opportunities and challenges in sustainability, 1(1), 13-28. karjoko, l., winarno, d.w., rosidah, z.n., handayani, i.g.a. (2020), spatial planning dysfunction in east kalimantan to support green economy. international journal of innovation, creativity and change, 11(8), 104-260. kencanawati, m., mustakim, m. (2017), analisis pengolahan air bersih pada wtp pdam prapatan kota balikpapan. jurnal transukma, 2(2), 103-117. lestari, d., hasid, z., busari, a., ananda, a.a. (2022), multiplier effect of energy infrastructure on grdp: horizon in 3 production areas in east kalimantan-indonesia. international journal of energy economics and policy, 12(6), 127-136. ministry of national development planning of the republic of indonesia. (2021), buku saku pemindahan ibu kota negara. available from: https://ikn.go.id/storage/buku-saku-ikn-072121.pdf [last accessed on 2023 feb 07]. muzayanah, i.f.u., lean, h.h., hartono, d., indraswari, k.d., partama, r. (2022), population density and energy consumption: a study in indonesian provinces. heliyon, 8(9), e10634. nath, s. (2020), relationship between economic growth and electricity consumption in india: a re-investigation. energy economics letters, 7(1), 23-35. nepal, r., paija, n. (2019), energy security, electricity, population and economic growth: the case of a developing south asian resourcerich economy. energy policy, 132, 771-781. okello, c., tomasello, b., greggio, n., wambiji, n., antonellini, m. (2015), impact of population growth and climate change on the freshwater resources of lamu island, kenya. water, 7(12), 1264-1290. priyagus, p. (2021), does economic growth efficient and environmental safety? the case of transportation sector in indonesia. international journal of energy economics and policy, 11(6), 365-372. rehman, a., deyuan, z. (2018), investigating the linkage between economic growth, electricity access, energy use, and population growth in pakistan. applied sciences, 8(12), 2442. roy, j., hasid, z., lestari, d., darma, d.c., kurniawan, e. (2021), covid-19 maneuver on socio-economic: exploitation using correlation. jurnal pendidikan ekonomi dan bisnis, 9(2), 146-162. salya, s. (2022), moving the national capital (ikn) from the strategic intelligence approach. italienisch, 12(2), 151-159. shengfeng, x., sheng, x.m., tianxing, z., xuelli, z. (2012), the relationship between electricity consumption and economic growth in china. physics procedia, 24(a), 56-62. shimamura, t., mizunoya, t. (2020), sustainability prediction model for capital city relocation in indonesia based on inclusive wealth and system dynamics. sustainability, 12(10), 4336. sugihartati, r., susilo, d., putranto, t.d. (2020), discourse about the government’s political goal to move the capital of indonesia. international journal of innovation, creativity and change, 12(10), 462-480. suharso, a.b.k., ahyudanari, e. (2020), demand analysis at tanah grogot airport east kalimantan. iop conference series: materials science and engineering, 930, 012063. thaker, m.a.m., thaker, h.m.t., amin, m.f., pitchay, a.a. (2019), electricity consumption and economic growth: a revisit study of their causality in malaysia. etikonomi: jurnal ekonomi, 18(1), 1-12. turmunkh, b.e. (2021), the relationship between water pollution and economic growth in central asian countries: a causal analysis using difference-in-difference (did) model. east african scholars journal of economics, business and management, 4(11), 231-242. vo, d.h., vo, a.t. (2021), renewable energy and population growth for sustainable development in the southeast asian countries. energy, sustainability and society, 11(1), 30. wijaya, a., darma, s., darma, d.c. (2020), spatial interaction between regions: study of the east kalimantan province, indonesia. international journal of sustainable development and planning, 15(6), 937-950. yang, j., wen, y.d. (2018), study on the relationship between economic growth and water pollution in jiangxi province-based on ardl model. journal of power and energy engineering, 6(7), 64-75. . international journal of energy economics and policy | vol 8 • issue 3 • 2018 115 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(3), 115-120. do european central bank asset purchase programmes matter for the euro-area stock markets and brent crude market? yih-bey lin1, fu-min chang2, yu-hin leung3, jui-feng lin4, nicholas lee5* 1chaoyang university of technology, taiwan, 2chaoyang university of technology, taiwan, 3chaoyang university of technology, taiwan, 4chaoyang university of technology, taiwan, 5chaoyang university of technology, taiwan. *email: rllee@cyut.edu.tw abstract this paper examines macroeconomic impacts of european central bank (ecb) unconventional policy on euro stock markets and brent crude market respectively. we use actual and confidential asset purchase programmes (apps) data to capture the unconventional effect and apply the vector autoregression (var) model. we find that when the percentage change in ecb apps leads stock market returns in french, england and italy as controlling either the germany or french stock market. controlling both french and germany stock markets simultaneously, we find that the percentage change in ecb apps leads stock market returns only in italy, suggesting that ecb apps for the segments of european stock markets matter. finally, we find the causality from the percentage change in apps to crude oil returns. similar results are obtained when controlling positive percentage change in apps. hence, our results shed valuable lights on conducting conventional monetary policy in times of crisis. keywords: european central bank, asset purchase programme, stock market, crude market, granger causality jel classifications: g15, g14, e52. 1. introduction the european central bank (ecb) launches asset purchase programmes (apps), known as quantitative easing (qe) program, following britain, japan and the united states, to solve the european financial crisis. the inclusion of actual purchases is important because the volumes of official purchases exhibited high volatility and varied significantly among stock markets. on 2 july 2009, the ecb launched its first covered bond purchase programme (cbpp1). it is designed to improve market functioning and the monetary policy transmission mechanism. the aim of the cbpps is not only to improve market liquidity in covered-bond markets, but also eases funding conditions for both banks and non-financial corporations. on 10 may 2010, the ecb started purchasing securities in the context of the securities markets programme (smp). in november 2011, the ecb launched a cbpp2. on 4 september 2014, the ecb announced a purchase programme of covered bonds (cbpp3) and a purchase programme of asset-backed securities (abspp). on 22 january 2015, the ecb decided that asset purchases should be expanded to include a public-sector asset purchase programme (pspp). thus, ecb apps, which combines cbpp1, smp, cbpp2, cbpp3, abspp and pspp, leads to substantial increases in their balance sheets through repurchase agreement (repo) operations. table 1 reports the details related to ecb apps. as central back launching app, two alternative channels, portfolio balance and signaling, can be used to affect real activity (krishnamurthy and vissing-jorgensen, 2011; d’amico et al., 2012; bauer and rudebusch, 2014; sahuc, 2016). through the portfolio balance channel, purchases of longer term securities can lower the long end of yield curve and lead investors to buy assets with greater duration or higher credit risk. this can increase prices for a range of private assets, including home and equity prices. on the other hand, through the signaling channel, asset purchase modifies market expectations about further credit easing in committing to bring down interest rates. the signaling channel suggests that central banks use asset purchase to convey information about future monetary policy to the market. some literature discusses the effects of large-scale asset purchase programmes (lsaps) but mixed results. some literature suggests lin, et al.: do ecb asset purchase programmes matter for the euro-area stock markets and brent crude market? international journal of energy economics and policy | vol 8 • issue 3 • 2018116 that lsaps tend to be more effective on asset prices in periods of high financial distress. neely (2013) and bauer and neely (2014) document that the federal reserve’s lsaps significantly influence international bond yields. in addition, bauer and neely (2014) find some differences in the relative importance of the signaling and portfolio re-balancing channels across major advanced economies. in contrast, some studies show the effects became smaller for later extensions of the apps (meaning and zhu, 2011). ahmed and zlate (2014) find that while capital flows to emerging market economies, it does not systematically increase in response to us unconventional monetary policies. their composition shifts towards more volatile portfolio flows. bowman et al. (2015) find that unconventional monetary policies in the us have a large impact on emerging market economies with substantive cross-country heterogeneity. carpenter et al. (2015) show that there is some segmentation in the markets for these securities. they also find evidences to prove the federal reserve purchases do not only simply affect the yields on the assets purchased, but also induce investors to buy other assets. tillmann (2016) suggests that qe has significant effects on emerging market economies’ financial conditions and plays a sizable role in explaining capital inflows, equity prices and exchange rates. some studies examine the effects of the ecb apps on bond markets. gibson et al. (2016) examine the impact of the ecb’s securities market program (smp) and the ecb’s two cbpps on sovereign bond spreads and covered-bond prices, respectively. they focus on five euro-area stressed countries, including greek, ireland, italy, portugal and spain. their results indicate that the respective apps reduce sovereign spreads and raise covered bond prices. they further find a small negative effect on greek spreads from the smp. on the other hand, few studies examine the effect of apps on equity prices. hau and rey (2006) show that unconventional monetary policy, depreciating currencies, could rebalance the international portfolio. they suggest that higher returns in the home equity market relative to the foreign equity market are associated with a home currency depreciation. georgiadis and gräb (2016) show that the apps announcement boosted equity prices around the world by supporting investor confidence and reducing the risk of deflation and persistent stagnation in the euro area. that is, domestic and global equity prices responded positively to all announcements of ecb unconventional monetary policy measures. conversely, laopodis (2013) find that there is no consistent dynamic relationship between monetary policy and the stock market. gertler and karadi (2013) argue that purchases of securities with some private risk have stronger effects than purchases of government bonds. the european financial crisis seems far from being resolved. the eurozone is not the best currency zone, which will lead to increase tensions within the european monetary union. in response to the crisis, all major central banks have introduced non-standard measures in their monetary policies. however, compared with the federal reserve, bank of england or bank of japan, ecb’s response is clearly more cautious. the main reason to stop the ecb from taking more aggressive measures is that european politicians continue to disagree on this issue. this paper investigates the macroeconomic impact of the percentage change in ecb apps on equity price returns of euroarea stock markets, including greek, ireland, italy, portugal, spain, french, england and germany, as well as brent crude oil return respectively. we use actual purchases to capture effects of the percentage change in apps rather than a zero-one dummy because of the magnitude and the sign of the percentage change in apps on the stock market and brent crude market. it is noted that we use the percentage change in apps to capture the unconventional effect and daily data covered the period from july 1, 2009 to december 31, 2016. we apply the vector auto-regression (var) model to discuss the relationship between the percentage change in ecb apps and stock market returns in the european union (eu) as well as brent crude market. we take both (either) germany and (or) french stock markets returns as exogenous variables because both germany and french economies affect other eu countries significantly. empirical results reveal that when the percentage change in ecb apps leads stock market returns in french, england and italy as taking the germany or french stock market as exogenous variable. when both french and germany stock markets are taken as exogenous variables simultaneously, we find that the percentage change in ecb apps leads stock market returns only in italy. it suggests that ecb apps for the segments of european table 1: details of ecb apps apps duration size objections cbpp1 2 july 2009-30 june 2010 €60 billion to conduct in both the primary and the secondary markets smp may 2010-march 2011 and august 2011-february 2012 €240 billion to conduct interventions in the euro area public and private debt securities markets to ensure depth cbpp2 november 2011-october 2012 €40 billion covered bonds issued in the euro area will be carried out by the euro system by means of direct purchases cbpp3 20 october 2014-now €213,137 million nominal and inflation-linked central government bonds pspp 9 march 2015-now amount to €60 billion nominal and inflation-linked central government bonds and bonds issued by regional and local governments, international organizations and multilateral development banks located in the euro area cspp 8 june 2016-now buy corporate sector bonds abspp 4 september 2014 helps banks to diversify funding sources and stimulates the issuance of new securities source: press releases of the ecb. ecb: european central bank, apps: asset purchase programmes lin, et al.: do ecb asset purchase programmes matter for the euro-area stock markets and brent crude market? international journal of energy economics and policy | vol 8 • issue 3 • 2018 117 stock markets can be effective. finally, we find the causality from the percentage change in apps to crude oil returns. similar results are obtained when controlling positive percentage change in apps. hence, our results for apps and euro stock markets as well as brent crude market shed some lights on the conduction of unconventional monetary policy in times of crisis. the organization of the rest of the paper is as follows. the next section reviews methods and explains the data used, and section 3 summarizes the estimated results. section 4 presents discussions. finally, section 5 concludes the article. 2. methodology and data in order to capture the effects of the changes rate in apps on the euro stock markets, we create a vector auto-regression (var) model as follows: p1 p1 t 10 1p t-p 1p t-p t 1tp=1 p=1 r =c + w r + s gapp +a*x +ε∑ ∑ (1) p1 p1 t 20 2p t-p 2p t-p t 2tp=1 p=1 gapp =c + w r + s gapp +b*x +ε∑ ∑ (2) where, rt represents the return changed on the stock market, gappt, represents a growth rate of apps, and ε1t and ε2t denote the error term respectively. x notes either (both) german or (and) french stock market returns for dax 30 index and the cac40 index as exogenous variables because both germany and french economies affect other eu countries significantly. the optimal length of the lag with p is using by schwarz information criterion (sic). on the other hand, in order to investigate the dynamics of rt and gappt, we employ the granger-causality analysis. if the coefficients of s1p are significant, then gapp causes the stock market returns, implying that the change in apps (gapp) leads returns. it suggests that ecb apps effectively affects the stock market index return. conversely, if the coefficients of are significant, then gapp follows the stock market returns, indicating the change in apps following the stock market returns. it suggests investors self-confidence restored. we discuss some representative indexes, including germany (dax 30 index), england (ftse 100 index), greek (ase index), ireland (overall index), portugal (psi index), italy (ftse mib index), spain (madrid stock exchange general index) and french (cac 40). the data of both stock returns of investigated stock markets and the apps are collected from taiwan economy journal database and ecb website, respectively. the daily data period covers from july 1, 2009 to december 31, 2016 and included totally 1846 observations. table 2 documents the variables description and notations. 3. empirical results this paper first examines the macroeconomic impact of ecb unconventional policy in euro stock markets including french, england, germany, greek, ireland, portugal, italy and spain. we discuss the effects of the growth rate of apps on the stock markets. figure 1 plots price movement of euro stock markets and level in apps. from figure 1, we can see that most of stock markets are growing up during the late apps period. it is noted that italy stock index is more violate; ireland stock index had the opposite performance; the other stock market indexes are growing up quite normal. besides, the unit of vertical axis is million euro dollars for the apps. on the other hand, we turn to look at the percentage change in apps in figure 2. it implies that the ecb played an important role in stabilizing the markets through apps. thus, ecb apps matter for the euro-area stock markets. in this paper, augmented dickey–fuller (adf) test is employed to test the stationarity of the return series. besides, in order to conduct var of the percentage change in apps (gapp) and return series, the optimal length of lag for gapp and their corresponding return should be determined. the descriptive statistics, unit root test and the optimal length of lag are shown in table 3. from table 3, we can see that r_dax and r_as are the highest mean but negative means for r_psi and r_over. specifically, there is the higher return (volatility) in the ireland stock market than other markets. for the unit root test, the return series for all investigated stock markets are significantly at the 1% level. it means the return series data are stationary. the optimal length of lag for gapp and their corresponding return is 4 for all eight cases. next, we discuss the dynamics of the percentage change in apps (gapp) and return series (r) by considering granger causality test. table 4 show the relationship between return r and gapp under given exogenous variables. we provide the chi-square statistics. from table 4, we can see that when we take r_dax as exogenous variable, the percentage change in ecb apps leads stock market returns of r_ft, r_fr and r_it respectively. it means that there exists strengthening integration between international stock markets. on the other hand, it fails to detect the directional causality from stock market return to the percentage change in ecb apps. thus, our findings are not consistent with the argument of laopodis (2013) that there is no consistent dynamic relationship between monetary policy and the stock market. therefore, there table 2: euro stock markets description and notations stock index (country) abbreviation notations for return ase index (greek) ase r_as dax 30 index (germany) daxix r_dax ftse 100 index (england) ftseix r_ft overall index (ireland) overall r_over psi index (portugal) psiix r_psi ftse mib index (italy) itix r_it cac 40 (french) frix r_fr madrid stock exchange general index (spain) spix r_sp lin, et al.: do ecb asset purchase programmes matter for the euro-area stock markets and brent crude market? international journal of energy economics and policy | vol 8 • issue 3 • 2018118 are strong indications that the ecb app had a positive impact on their stock markets. from table 4, when we continue to take r_fr as exogenous variable, we obtain the similar result as controlling r_dax. it is interesting that germany and french stock markets follow the percentage change in apps because of the first two important countries in european. on the other hand, both r_fr and r_dax are taken as exogenous variables simultaneously. we find that the percentage change in ecb apps only leads stock market returns in r_it, implying that an increase in the percentage change in ecb apps increase stock market return in italy. the possible reason is that italy is the third largest economy behind the euro zone and is grantee and political instability, so that the destabilizing status in euro zone have been declined. to investigate the relationship between return r and gapp under given the positive or negative percentage change in apps, we also take r_fr or r_dax as exogenous variable respectively. ecb often uses growing apps during high financial distress periods figure 1: price movement of euro stock markets and level in asset purchase programmes table 4: granger causality test results by adding various exogenous variables r_dax as exogenous variable r_fr as exogenous variable r_dax and r_fr as exogenous variables r→gapp r←gapp r→gapp r←gapp r→gapp r←gapp r_as 4.52 5.39 r_as 4.188 3.69 r_as 4.47 4.04 r_fr 3.17 12.67** r_dax 2.55 15.4*** r_ft 2.35 5.24 r_ft 4.14 20.26*** r_ft 2.01 4.75 r_it 2.97 15.7*** r_it 2.93 20.38*** r_it 2.83 3.83 r_over 3.75 5.96 r_over 3.59 6.32 r_over 3.66 5.35 r_psi 5.04 3.52 r_psi 5.32 6.94 r_psi 4.50 1.98 r_sp 0.74 2.29 r_sp 0.84 4.04 r_sp 0.77 2.97 *,**,***represent significance at the 10%, 5%, and 1% level respectively. a→b means that a leads to b and a←b means that a is behind to b table 3: descriptive statistics, unit root test and the optimal length of the lag variable mean standard deviation skewness kurtosis unit root test sic lag r_dax 0.0005 0.0134 −0.2640 5.2218 −11.79*** −1.9028 4 r_ft 0.0002 0.0139 −0.1170 6.4056 −20.77*** −1.9317 4 r_fr 0.0003 0.0104 −0.1210 5.2295 −21.75*** −1.7875 4 r_psi −0.0001 0.0127 −0.1120 6.9960 −20.51*** −2.3245 4 r_it 0.0001 0.0171 −0.3360 7.1045 −20.44*** −1.3233 4 r_over −0.0004 0.0231 −0.1550 6.5741 −18.3*** −0.6597 4 r_as 0.0005 0.0130 −0.6430 8.2383 −25.83*** −1.9428 4 r_sp 0.0000 0.0157 −0.1380 10.8010 −20.5*** −1.5393 4 *,**,***represent significant at the 10%, 5%, and 1% level respectively. sic: schwarz information criterion lin, et al.: do ecb asset purchase programmes matter for the euro-area stock markets and brent crude market? international journal of energy economics and policy | vol 8 • issue 3 • 2018 119 while as declining apps during less financial distress periods. the empirical results are shown in table 5. from table 5, under given the positive percentage change in apps, we find that the positive percentage change in apps affects r_it, no matter taking r_fr or r_dax as exogenous variable. r_fr is affected by apps by taking r_dax as exogenous variable, which means that french economic had joint relationship to germany in periods of the positive percentage change in apps. under given the negative the positive percentage change in apps, the empirical results reveal that the relationship among all investigated stock markets are not significant, no matter taking either r_fr or r_dax as exogenous variable. 4. discussions table 6 reports the gross domestic product (gdp) for euro nations. we find that italy has the europe’s fourth largest by nominal gdp in 2016. hence, ecb apps for italy stock market is more effective from tables 4 and 5. additionally, we turn to look at the granger causality test results of brent crude oil and the percentage change in apps (gapp) in table 7. the chi-statisitcs are reported. we find the granger causality from gapp to brent crude returns but the reverse relation are not. we further document that similar results occur figure 2: euro stock markets returns and the percentage change in asset purchase programmes table 5: empirical results with positive and negative the positive percentage change in app exogenous variable the positive percentage change in app the negative percentage change in app r_dax r_fr r_dax r_fr r→gapp r←gapp r→gapp r←gapp r→gapp r←gapp r→gapp r←gapp r_as 5.46 3.13 5.46 4.55 1.62 2.34 1.82 2.20 r_dax ---------1.96 7.56 ---------1.86 3.83 r_fr 4.54 9.88** ----------2.34 2.87 ----------r_ft 8.30* 7.60 8.06* 2.49 3.24 3.18 3.20 2.84 r_it 6.64 17.68*** 7.24 10.86** 3.70 4.25 4.02 4.23 r_over 2.97 3.14 3.36 1.95 6.45 3.96 6.85 3.28 r_psi 2.67 2.68 2.70 1.2 1.07 0.83 0.96 0.96 r_sp 2.69 5.60 3.11 1.43 1.03 2.68 0.97 3.27 ***,***represent significance at the 10%, 5%, and 1% level respectively. a→b means that a leads to b and a←b means that a is behind to b. app: asset purchase programme table 6: gdp for euro nations country 1960 (million) 2016 (million) germany 3,477,796.27 united kingdom 72,328.05 2,647,898.65 france 62,651.47 2,465,453.98 italy 40,385.29 1,858,913.16 spain 12,072.13 1,237,255.02 ireland 1,939.33 304,819.02 portugal 3,193.20 204,836.60 greek 4,446.53 192,690.81 gdp datas are obtained from world bank. gdp: gross domestic product lin, et al.: do ecb asset purchase programmes matter for the euro-area stock markets and brent crude market? international journal of energy economics and policy | vol 8 • issue 3 • 2018120 when controling positive percentage change in apps. it suggests ecb can use apps to influence brent crude market return. on the other hand, the percentage change in apps follows brent crude market return. 5. conclusions this study analyzes the macroeconmic impact on euro stock markets and brent crude market through the unconventional monetary policy adopted by the ecb apps, known as qe. we find that although the apps announcements caused global equity prices increasing in domestic but not at all investigated markets. we still believe that global equity prices respond positively to ecb unconventional monetary policy measures. lsaps tend to be more effective on euro stock markets in periods of high financial distress. specifically, we further report that brent crude market returns follow the percentage change in apps, suggesting ecb apps has more effective on brent crude oil asset. on the other hand, we also find that the ecb apps have weak effects on euro stock markets during times of low financial distress. our findings are consistent with lim and mohapatra (2013), suggesting heterogeneity among different types of flows. in other words, they argue that portfolio (especially bond) flows tend to be more sensitive than foreign direct investment to our measured qe effects. our results for apps and euro stock markets and brent crude market shed some lights on the conduction of unconventional monetary policy in times of crisis. evidences reveal that the germany and french stock markets are the key to the entire ecb apps and their economic situations will directly affect the recovery of other countries, in particular for italy stock market and brent crude market. references ahmed, s., zlate, a. (2014), capital flows to emerging market economies: a brave new world? journal of international money and finance, 48, 221-248. bauer, m., neely, c. (2014), international channels of the fed’s unconventional monetary policy. journal of international money and finance, 44, 24-46. bauer, m., rudebusch, g. (2014), the signalling channel for federal reserve bond purchases. international journal of central banking, 10, 233-289. bowman, d., londono, j., sapriza, h. (2015), unconventional monetary policy and transmission to emerging market economies. journal of international money and finance, 55(c), 27-59. carpenter, s., demiralp, s., ihrig, j., klee, e. (2015), analyzing federal reserve asset purchases: from whom does the fed buy? journal of banking and finance, 52, 230-244. d’amico, s., english, w., lopez-salido, d., nelson, e. (2012), the federal reserve’s large-scale asset purchase programs: rationale and effects. the economic journal, 122, 415-446. georgiadis, g., gräb, j. (2016), global financial market impact of the announcement of the ecb’s asset purchase programme. journal of financial stability, 26, 257-265. gertler, m., karadi, p. (2013), qe 1 vs. 2 vs. 3: a framework for analyzing large-scale asset purchases as a monetary policy tool. international journal of central banking, 9, 5-68. gibson, h.d., hall, s.g., tavlas, g.s. (2016), the effectiveness of the ecb’s asset purchase programs of 2009 to 2012. journal of macroeconomics, 47(a), 45-57. gibson, h.d., hall, s.g., tavlas, g.s., (2014), fundamentally wrong: market pricing of sovereigns and the greek financial crisis. journal of macroeconomics, 39, 405-419. hau, h., rey, h. (2006), exchange rates, equity prices, and capital flows. review of financial studies, 19(1), 273-317. krishnamurthy, a., vissing-jorgensen, a. (2011), the effects of quantitative easing on interest rates: channels and implications for policy. brookings papers on economic activity, 42(2), 215-265. laopodis, n.t. (2013), monetary policy and stock market dynamics across monetary regimes. journal of international money and finance, 33(1), 381-406. lim, j., mohapatra, s. (2016), quantitative easing and the post-crisis surge in financial flows to developing countries. journal of international money and finance, 68, 331-357. meaning, j., zhu, f. (2011), the impact of recent central bank asset purchase programmes. bis quarterly review, 2011, 73-83. neely, c.j. (2013), unconventional monetary policy had large international effects. working paper series 2010-018e, federal reserve bank of st. louis. sahuc, j.g. (2016), the ecb’s asset purchase programme: a model-based evaluation. economics letters, 145, 136-140. tillmann, p. (2016), unconventional monetary policy and the spillovers to emerging markets. journal of international money and finance, 66, 136-156. table 7: granger causality test results of brent crude oil and gapp sample condition for gapp r‑oil→gapp r‑oil←gapp none 10.669 17.755** positive 26.598*** 27.569*** negative 1.898 13.277 *,**,***represent significance at the 10%, 5%, and 1% level respectively. a→b means that a leads to b and a←b means that a is behind to b. the optimal length of the lag by sic is 8 for gapp and oil returns of west texas intermediate, dubai crude and brent crude microsoft word 2 ghana adom.docx international journal of energy economics and policy vol. 1, no. 1, 2011, pp. 18-31 www.econjournals.com electricity consumption-economic growth nexus: the ghanaian case philip kofi adom department of economics, university of ghana p.o.box lg 57, legon, accra, ghana email: adomonline@yahoo.co.uk abstract: research into the electricity-economic growth nexus has important implications for energy conservation measures and environmental policy. however, results from the energy-economic growth nexus have been mixed in the literature on ghana. this posses serious problems for the country’s energy policy. much research is thus, required to establish the direction of causality between energy and economic growth. nonetheless, less evidence is available for ghana. it is against this background that this study seeks to investigate the direction of causality between a type of energy, electricity, and economic growth to add to the existing argument in the literature. the toda and yomamoto granger causality test was used to carry out the test of causality between electricity consumption and economic growth from 1971 to 2008. the results obtained herein revealed that there exists a unidirectional causality running from economic growth to electricity consumption. thus, data on ghana supports the growth-led-energy hypothesis. the results imply that electricity conservation measures are a viable option for ghana. keywords: ghana, real gdp per capita, electricity consumption, toda and yomamoto, granger causality test, bounds cointegration jel classifications: q400, q430 1. introduction electricity is a key infrastructural element for economic growth. it is a multitalented ‘energy currency’ that underpins a wide range of products and services that inprove the quality of life, increase worker productivity and encourage entreprenuerial activity. this makes electricity consumption to be positively and highly correlated with real per capita gdp. in ghana, between 2000 and 2008, while real per capita gdp growth averaged 5.5% per annum, annual electricity consumption growth averaged 1.21%. inspite of the fact that real per capita gdp and electricity consumption are positively correlated, it is still not clear the direction of causality between real per capita gdp and electricity consumption. research into the electricity-economic growth nexus has important implications for electricity conservation measures. however, results spanning from the literature on ghana have been mixed (see twerefo et al, 2008; akinlo, 2008; lee, 2005; and wolde-rufael, 2006). this has serious implications for ghana’s energy policy and environmental policy. much research is thus, required to establish the direction of causality between electricity consumption and economic growth. however, there is a dearth of research into the electricity-economic growth nexus in ghana. it is against this background that this study seeks to investigate the direction of causality between electricity consumption and economic growth to add to the existing arguments in the literature using the toda and yomamoto granger causality test from 1971 to 2008. the rest of the paper is organised as follows; chapter two deals with the review of relevant literature and electricity sector and economic growth in ghana; chapter three deals with data and methodolog, chapter four provides empirical results while the last chapter concludes and make policy recommendation. electricity consumption-economic growth nexus: the ghanaian case 19 2. literature review the study of the empirical investigations into the causal relationships between energy consumption and economic growth can be analysed through two lines; the hypothesis criteria (apergis and payne, 2009) and the generation criteria (guttormsen, 2004). the hypothesis approach analyses the causation in light of whether studies concluded that electricity consumption causes economic growth or otherwise or both. along these lines, studies on the empirical investigation into the energyeconomic growth nexus have been grouped into four; the growth-led-energy hypothesis, the energyled-growth hypothesis, the energy-led-growth-led-energy hypothesis, and the neutrality hypothesis. the growth-led-energy hypothesis asserts that economic growth leads to energy consumption. this implies that even severe energy crisis will not retard economic growth, hence energy conservation measures are a viable option. the energy-led-growth hypothesis asserts that energy consumption leads to economic growth. this suggests that severe energy crisis will retard economic growth, hence energy conservation measures are not a viable option. the energy-ledgrowth-led-energy hypothesis asserts that there exists a bidirectional causality between energy consumption and economic growth. lastly, the neutrality hypothesis asserts that there is no causal relationship between energy consumption and economic growth. along the lines proposed by guttormsen (2004), studies on the empirical investigations into energy-economic growth have been classified along three lines; the first generation studies, the second generation studies, and the third generation studies. the first generation studies consists of studies that basically used the traditional vector autoregressive models (sims, 1972) and the standard granger causality test. the main weakness associated with this generation of studies is that they assume the series to be stationary. as a result the second generation of studies proposed cointegration (johansen and juselius, 1990) as the appropriate tool to use in analysing the causal relationship between energy consumption and economic growth. thus, in the second generation of studies, pairs of variables were tested for cointegration relationship and an error correction model was estimated to test for causality (engle and granger, 1987). however, given the possibility of more than one cointegrating vectors, the second generation studies approach was deemed inappriopriaed. this led to the third generation of studies, which proposed a multivariate approach that allowed for more than two variables in the cointegrating relationship. this approach facilitates estimations of systems where restriction on cointegrating relationship can be tested and information on short-run adjustment can be investigated. there are two main problems with the third generation studies. first, the third generation studies impose restrictions that the variables should be integrated of order one. secondly, the variables will have to be cointegrated before a test of causality can be possible. this has led to the fourth generation of studies. these studies use the toda and yomamoto granger causality test, which is based on the autoregressive distributed lag model. in this generation of studies, restrictions are not imposed on the variables. thus, causality is still possible even when variables are integrated of order zero, one or both. in other words, this approach allows for the test of causality even when variables are not cointegrated. in addition to the above, ozturk (2010) in a literature survey on the energy-growth nexus classified the various studies into country-specific and multi-country studies on energy (electricity consumption) and economic growth. the general obervation according to this study is that the results emanating from the multi-country studies and country-specific studies on the causality between energy consumption and economic growth reveals contracdictory results. however, the results from the country-specific studies on the causality between electricity consumption and economic growth reveals that there exists a positive causality which runs from electricity consumption to economic growth but the multi-country studies on the causality between electricity consumption and economic growth shows contracdictory results. the author therefore, recommeded that to avoid the conflicting and unreliable results, current studies on the causality between energy (electricity) consumption and economic growth should use more recent approaches such as ardl bounds cointegration test (pesarran et al, 2001), threshold cointegration models (hansen and seo, 2002), and panel data models. the author also concluded that research papers that use the same methods with the same variables just by altering the data period examined have accounted for the various conflicting results that exist in the literature. as a result, the author advices researchers to desist from such act since such papers do not international journal of energy economics and policy, vol. 1, no. 1, 2011, pp.18-31 20 make any contribution to the existing energy (electricity)-growth literature. below is a table of summary of works on the causality between energy (electricity) consumption and economic growth. table i: summary of works on the energy (electricity)-growth nexus authors / period methodology hypothesis generation kraft and kraft (1978), 1947-1974, standard granger causality growth-led energy u.s.a first generation akarca and long (1980), 1973-1974, standard granger causality growth-led-energy u.s.a first generation yu and hwang ( 1984 ), 1973-1981, standard granger causality growth-led-energy south korea first generation soyatas and sari (2003), 1950-1992, vector error correction model granger causality growth-led-energy, italy, japan, south korea third generation akinlo (2008), 19802003 ardl bounds test neutrality. nigeria, cameroon, ivory coast, kenya, togo fourth generation wolde-rufael (2006), 1971-2001, toda and yomamoto granger causality test growth-led-energy, algeria, congo, egypt, ghana, ivory coast fourth generation akinlo (2008), 19802003 full modified ols energy-led-growth-ledenergy, ghana, gambia, and senegal third generation lee (2005), 1975-2001 vector errror correction model granger causality energy-led-growth, ghana third generation twerefo et al (2008), 1975-2006 vector error correction model granger causality growth-led-energy, ghana third generation fatai et al (2004), 19601999 toda and yomamoto energy-led-growth-ledenergy, philippines fourth generation stern (2000), 1948-1994 cointegration, granger causality energy-led-growth, u.s.a second generation ghali and el-sakka (2004), 1961-1997 cointegration, vec granger causality energt-led-growth-ledenergy, canada third generation ho and siu (2007), 19662002 vec granger causality energy-led-growth, hong kong third generation soytas and sari (2009), 1960-2000 toda and yomamoto causality test neutrality fourth generation payne (2009), 1949-2006 toda and yomamoto causality test neutrality fourth generation masih (1997), 1952-1992 vec granger causality energy-led-growth-ledenergy…..taiwan energy-led-growth. south korea third generation electricity consumption-economic growth nexus authors / period methodology hypothesis generation of study haciciglou (2007), 19682005 granger causality, bounds testing growth-led-electricity, turkey fourth generation tang (2008), 1972-2003 ecm based f-test, ardl growth-led-electricityled-growth, malaysia fourth generation morimoto and hope (2004), 1960-1998 standard granger causality electricity-led-growth, sri lanka first generation shiu and lam (2004), 1971-2000 cointegration, ecm growth-led-electricityled-growth, china second generation odhiambo (2009a), 19712006 ardl bounds test electricity-led-growth fourth generation odhiambo (2009b), 1971-2006 standard granger causality growth-led-electricityled-growth, south africa first generation akinlo (2009), 19802006 vec granger causality electricity-led-growth, nigeria third generation electricity consumption-economic growth nexus: the ghanaian case 21 ghosh (2009), 1970-2006 ardl test growth-led-electricity, india fourth generation ghosh (2002), 1950-1997 standard granger causality growth-led-electricity, indis first generation narayan and smyth (2005), 1966-1999 multivariate granger causality growth-led-electricity, australia third generation twerefo et al (2008), 1975-2006 vec granger causality growth-led-electricity, ghana third generation wolde-rufael (2006), 1971-2001 toda and yomamoto granger causality test growth-led-electricity, cameroon, ghana, nigeria, senegal, zambia, zimbabwe fourth generation as shown in table i above, results spanning from the energy (electricity)-growth nexus have yielded mixed results mainly due to the varying data sets and methodology used and the varying country characteristics. there have been very recent papers on this topical issue, which includes the papers by acaravci and ozturk (2010), and ozturk and acaravci (2011). acaravci and ozturk (2010) using pedroni panel cointegration investigated the causal relationship between electricity consumption per capita and real per capita gdp for selected 15 transition countries from 1990 to 2006. the authors in this paper found nonexistence of level relationship between electricity consumption per capita and real per capita gdp for the selected transition countries and thus, could not run the causality test. in a related study, ozturk and acaravci (2011) using an ardl bounds cointegration approach investigated the relationship and the direction of causality between electricity consumption and economic growth for 11 middle east and north africa countries (mena) from 1990-2006. the authors found no unique evidence of long-run equilibrium relationship between electricity consumption and economic growth in iran, morocco and syria, hence, were eliminated from the sample. however, the study found the existence of level relationship between electricity consumption and economic growth for egypt, israel, oman, and saudi arabia. the test of causality revealed a oneway short-run granger causality from economic growth to electricity consumption in israel. in egypt, oman, and saudi arabia, the causality test revealed the existence of one-way both short and long-run granger causality from electricity consumption to economic growth. generally, the authors concluded that their results suggest that there is weak evidence on the long-run and causal relationship between electricity consumption and economic growth in mena countries. overview of the electricity sub-sector and economic growth electricity generally passes through three-step phases before getting to the final user. first power is produced from generators which are located far from the load centers. power is then transferred to the transmission grid, which comprises transmission lines, transformers, and other components, to the bulk load distribution substations. from the bulk load distribution substations power is delivered to the individual customer sites using distribution lines. in ghana these three-step process are controlled by three different utility companies. the volta river authority (vra) is a state-owned enterprise that is solely responsible for bulk power generation in the country. currently vra operates the akosombo and kpong hydro stations which happen to be the major power generation sources in the country. ghana grid company (gridco) is responsible for transmitting power from bulk power plants to distribution lines while electricity company of ghana (ecg) and northern electrical department (ned), a subsidiary of vra are responsible for distributing power to the final consumer. ecg serves the southern half of the country while ned supplies power to the northern part of the country. the electricity sector has experienced significant growth over a decade now. in 1992, electricity and water sector recorded a growth rate of 12.02% which was 5.43% higher than the previous year. the primary reason, as reported in the budget statement and economic policy for 1993, included expansions in the national electricity grid under the rural electrification programme and the expansion and up-grading of some urban electricity distribution networks. in 2000, the sector witnessed a growth rate of 4.5% which was below the 1992 figure. in terms of the sectors relative contribution to total industrial growth in the country, the electricity sector contributed 10.21% of total international journal of energy economics and policy, vol. 1, no. 1, 2011, pp.18-31 22 industrial gdp in 2000. in 2005, the sector witnessed an increase in growth rate of 12.4% which translated into the sectors increased relative contribution to total industrial gdp of 11.9%. however, in 2007, the sector recorded a decrease in growth rate of -17.4% which caused the sector’s relative contribution to total industrial gdp to fall to 10.2%. (state of the ghanaian economy, 2000-2008). the major reason behind the sectors decreased contribution was mainly due to the serious drought that thumped the ghanaian economy in 2007 which led to plummet in the water level of akosombo, the foremost power house for the country. 3. data and methodology preceeding from the discussion of the empirical literature on energy-growth nexus, the longrun relationship between electricity consumption and economic growth may be specified as below; )1........(....................ttt uyec   where ect is the log of electricity consumption (kwh), yt is the log of real per capita gdp (constant 2000 us$) and ut is the stochastic disturbance term assumed to be white noise. annual time series data from 1971 to 2008 on electricity consumption and real per capita gdp were sourced from the enerdata global energy and co2 data research services and africa development indicators correspondingly. 3.1. unit root test although it has been argued in the literature that the ardl bounds cointegration tests does not require the pre-testing of series for their order of integration, the need for series to pass two conditions necessitates the need to test for the order of integration of the series. first, the ardl bounds cointegration requires that the series in a model should be integrated of an order of either zero or one but not two or more. secondly, the dependent variable should be integrated of order one. in this study the augment-dickey fuller unit root test (adf) and the phillip-perron (pp) unit root test are used to ascertain the order of integration of the series. the adf test is based on the following regression;     k i tittt zztz 1 11100  …………… (2) where t is a linear trend, z is the variable that is being tested for unit root, δ is the first difference operator and t is the gaussian white noise term and k is chosen to achieve white noise residuals. 3.2. ardl bounds cointegration analysis the ardl bounds testing approach compared to the other approaches of cointegration has several distinct advantages. one of the main advantages of the ardl approach in contrast to the engle and granger (1987) and johansen approach (1990) is that the ardl bounds cointegration approach permits to test for cointegration regardless of whether the variables are all i (1) or i (0) or a mixture of the two. secondly, the ardl bounds approach is not sensitive to the size of the sample, therefore, making its small sample properties more superior to the multivariate cointegration approach. lastly, the ardl approach is known to provide unbiased long-run estimates even when some of the variables are endogenous. narayan (2005) and odhianbo (2009) as quoted in amusa et al (2009) demonstrates that even when some of the independent variables are endogenous, the bounds testing approach generally provides unbiased long-run estimates and valid t-statistics. since it is difficult to a priori tell the direction of cointegration between variables, the study in testing for long-run relationships in the variables using the bounds cointegration test, normalised each variable as a dependent variable. thus, the following ardl equations were estimated using ols and a test of significance on the parameters of the lag level variables were conducted. the resulting fstatistic were then compared to the pesaran et al asymptotic critical bounds to determine whether there exist a long-run relationship between the variables. since this is an annual time series, the maximum lag length was set to two. since a priori it is impossible to determine whether real per capita gdp and electricity consumption can be treated as the ‘long-run forcing’ variable explaining electricity consumption and real per capita gdp respectively, this study in testing for level relationship excluded the difference level variables of real per capita gdp and electricity consumption in equations (3) and (4). electricity consumption-economic growth nexus: the ghanaian case 23 )3.........(11211 2 1 2 1 0 ttectecjt i iec i jtiect yecyecec       )4.........(21211 2 1 2 1 1 ttytyjt i iy i jtiy ecyecyy       from equations (3) and (4) the ardl bounds cointegration test involves the test of the following null hypothesis; ;0: 210  ecec ech  0: 211  ecec ech   yecfec | ;0: 210  yy yh  0: 211  yy yh   ecyfy | 3.3. toda and yomamoto granger causality test the study of causality has widely been analysed using the vector error correction model (vecm) and error correction model (ecm). however, toda and yomamoto (1995) have shown that the asymptotic distribution of the test in the unrestricted var has nuisance parameter and nonstandard distribution. also toda and yomamoto (1995), zapata and rambaldi (1997) and rambaldi and doran (1996) have all reported that approaches such as vecm and ecm used to analyse causality are sensitive to the values of the nuisance parameters in finite samples making the results a bit unreliable. as a result, toda and yomamoto (1995) proposed a modification of the granger causality approach. this approach requires estimating a var model in their levels by augmenting the var model with the maximum order of integration, d, of the variables in the model. the method then applies the wald test statistic for linear restrictions to the resulting var (k) model. as shown by toda and yomamoto (1995), the wald statistic for restrictions on the parameters of var (k) has an asymptotic χ2 distribution when a var (k+d) is estimated (zapata and rambaldi, 1997). thus, the main idea is to intentionally over-fit the causality test underlying model wth additional d lags so that the var order becomes (k+d) with k representing the optimal order of the var determined by akaike information criterion. that is when one is uncertain about the order of integration of the variables, augmenting the var model with an extra lag usually ensures that the wald statistic posses the necessary power properties. thus, in applying the toda and yomamoto method, all that is required of one is the maximum order of integration of the variables in the model and the optimal lag order of the var (k) model. this method in contrast to the methods of ecm and vecm does not require pre-testing for cointegration and unit root properties and thus, overcomes the pre-test biased associated with the unit root and cointegration test. also this approach minimises the risk associated with possibly wrongly identifying the order of integration of the series and the presence of cointegration relation (giles, 1997; mavrotas and kelly, 2001). given the superiority that the toda and yomamoto granger causality has over vecm and ecm, this study adopted the toda and yomamoto granger causality to test for the direction of causality between electricity consumption and economic growth in ghana. thus, the study estimated the following model using the seemingly unrelated regression (sur) technique. as argued by rambaldi and doran (1996), the wald test experiences efficiency improvements when sure models are used in the estimation.             max max 1 1 1 1212 1 100 )5.(.......... dk kj k i dk kj tjtjitijtj k i itit yyecectec  )6.....(.......... max max 1 1 1 2212 1 110             dk kj k i dk kj tjtjitijtj k i itit ececyyty  where k is the optimal lag length of the var, dmax is the maximum order of integration of the variables in the var model, ec is the log of electricity consumption, and y is the log of real per capita gdp. to investigate into the causal relationship between electricity consumption and economic growth, the study estimated equations (5) and (6) using the seemingly unrelated regression and tested the following null hypothesis in equations (5) and (6) respectively. 0....: 112110  kh  as against the alternative hypotheses of international journal of energy economics and policy, vol. 1, no. 1, 2011, pp.18-31 24 0....: 11211  kah  0....: 112110  kh  as against the alternative hypotheses of 0....: 112110  kh  failure to reject the null hypothesis in equation (5) would imply that real per capita gdp does not lead to electricity consumption. however, failure to accept the null would imply that real per capita gdp leads to electricity consumption. similarly, in equation (6), failure to accept the null would imply that electricity consumption leads to real per capita gdp. however, failure to reject the null would imply that electricity consumption does not lead to economic growth. in the event that both null hypothesises are accepted, it would imply that neither real per capita gdp and electricity consumption causes the other while failure to accept both null would imply that there exists a bidirectional causality between electricity consumption and real per capita gdp. 4. empirical results the study first tested for unit root in variables using the augmented dickey fuller test and phillip-perron test. the results of the test are shown below in table ii. table ii: unit root test variable/test statistic intercept and no trend intercept and trend none ec-adf -2.711519** -3.662053*** 0.445793 ec-pp -2.072651 -2.469109 1.398986 d(ec)-adf -5.4060*** -5.321561*** -5.44603*** d(ec)-pp -7.691418*** -7.421352*** -5.856158*** y-adf -0.538243 -1.185555 1.186281 y-pp -0.819665 -1.097411 0.247231 d(y)-adf -4.097168*** -2.035976 -4.12844*** d(y)-pp -4.078915*** -6.903395*** -4.121853*** *,**, *** indicates 1%, 10% and 5% levels of significance from table ii above, the test statistics by adf and pp both reveals that the variables are i (1) at the 5% significant level. thus, d, which is the maximum order of integration of the variables is one. 4.1. ardl bounds cointegration test results of the ardl estimates and joint test of significance are as shown in tables iii and iv below. table iii: variable addition test (ols case) dependent variable is dlny list of the variables added to the regression: lny(-1) lnec(-1) 35 observations used for estimation from 1974 to 2008 regressor coefficient standard error t-ratio[prob] con .17168 .37092 .46285[.647] dlny(-1) .40639 .19154 2.1217[.043] dlny(-2) -.019319 .21313 -.090646[.928] dlnec(-1) -.022149 .036798 -.60191[.552] dlnec(-2) -.021731 .037563 -.57852[.568] lny(-1) -.070699 .077234 -.91539[.368] lnec(-1) .026228 .031428 .83453[.411] joint test of zero restrictions on the coefficients of additional variables: electricity consumption-economic growth nexus: the ghanaian case 25 lagrange multiplier statistic chsq( 2)= 1.2410[.538] likelihood ratio statistic chsq( 2)= 1.2635[.532] f statistic f( 2, 28)= .51465[.603] from equations (3) and (4), the following null hypothesis were tested respectively 0: 210  ecech  0: 210  yyh  the resulting f-statistic are denoted as fec(ec|y) = 5.0226 and fy(y|ec) = 0.51465 in equations (3) and (4) respectively. table v shows the bounds cointegration test. table iv: variable addition test (ols case) dependent variable is dlnec list of the variables added to the regression: lnec(-1) lny(-1) 35 observations used for estimation from 1974 to 2008 regressor coefficient standard error t-ratio[prob] con 1.5628 1.4787 1.0569[.300] dlnec(-1) .24103 .14669 1.6431[.112] dlnec(-2) -.15761 .14974 -1.0526[.302] dlny(-1) 1.9185 .76355 2.5126[.018] dlny(-2) 1.4701 .84962 1.7303[.095] lnec(-1) -.38960 .12529 -3.1097[.004] lny(-1) .31218 .30789 1.0139[.319] joint test of zero restrictions on the coefficients of additional variables: lagrange multiplier statistic chsq( 2)= 9.2411[.010] likelihood ratio statistic chsq( 2)= 10.7299[.005] f statistic f( 2, 28)= 5.0226[.014] table v: bounds cointegration test 10% level of significance 5% level of significance f-statistics lower bound upper bound lower bound upper bound fec(ec|y) = 5.0226 fy(y|ec) = 0.51465 2.49 3.38 2.81 3.76 from table v above, the f-statistic from equation (3) exceed the 5% upper critical bound while the f-statistic from equation (4) falls below the lower critical bounds. it can be concluded that the lag level variables y and ec are significant in the electricity consumption equation. thus, there exist a long-run relationship between electricity consumption and real per capita gdp. in other words, real per capita gddp (y) can be treated as the ‘long-run forcing’ variable explaining electricity consumption. however, the lag level varaiables, y and ec are not significant in the real per capita gdp equation. thus, there exist no long-run relationship between real per capita gdp and electricity consumtpion and therefore, electricity consumption cannot be treated as the ‘long-run forcing’ variable explaining real per capita gdp. 4.2. causality test the next stage involved the test of causality between electricity consumption and real per capita gdp. first the study tested for the appropriate oder of the var using the akaike information criterion. results of the test suggest a lag length order of two. also a test of inclusion or exclusion of deterministic variables in the var were conducted. the lr test of deletion of deterministic variables international journal of energy economics and policy, vol. 1, no. 1, 2011, pp.18-31 26 in the var follows the chi-square distribution. results of the test suggest the inclusion of an intercept and a time trend in the var. details of these tests are shown in the tables vi and vii below. table vi: test statistics and choice criteria for selecting the order of the var model based on 34 observations from 1975 to 2008. order of var = 4 list of variables included in the unrestricted var: lnec lny list of deterministic and/or exogenous variables: con t order ll aic sbc lr test adjusted lr test 4 86.0247 66.0247 50.7611 ----- ----- 3 81.4585 65.4585 53.2476 chsq(4)= 9.1325[.058] 6.4465[.168] 2 78.6086 66.6086* 57.4505 chsq(8)= 14.8322[.062] 10.4698[.234] 1 71.6420 63.6420 57.5365* chsq(12)= 28.7655[.004] 20.3051[.062] 0 24.9291 20.9291 17.8764 chsq(16)= 122.1912[.000] 86.2526[.000] nb: aic and sbc in microfit are based on log-likelihood hence the maximum is chosen. table vii: lr test of deletion of deterministic/exogenous variables in the var null hypothesis lr test of restrictions (chsq) maximum value of log-likelihood p-value intercept but no trend 10.0772 74.5430 0.006 no intercept but trend 3.3864 77.8884 0.184 intercept and trend 11.0271 74.0680 0.026 this study first adopted the lr test of block granger non-causality in the var. the lr test of block granager non-causality statistic tests the null hypothesis that the coefficients of the lagged values of the variables assumed to be ‘non-causal’ in the block of equations explaining other variables are zero. the results of the lr test of block granger non-causality are shown in the table viii below; table viii: lr test of block granger non-causality in the var null hypothesis lr statistic decision electricity consumption does not cause real per capita gdp 2.5074 do not reject the null real per capita gdp does not cause electricity consumption 9.0107*** fail to accept the null ***indicates 5% level of significance. the maximum lag length is 2 as shown in table viii above, the lr test of block granger non-causality shows that there exist a unidirectional causality running from real per capita gdp to electricity consumption. having established the optimal lag length to include in the var, the maximum order of integration and inclusion of an intercept and a time trend, the study proceeded to estimate the following var model using the seemingly unrelated regression model.       3 1 3 1 1110 kj kj tjtjjtjt yectec  (6)       3 1 3 1 2110 kj kj tjtjjtjt ecyty  (7) where k = 2 and dmax = 1. results of the estimation of equations (6) and (7) are as shown in tables ix and x below. electricity consumption-economic growth nexus: the ghanaian case 27 table ix: seemingly unrelated regressions estimation. the estimation method converged after 0 iterations dependent variable is lnec. 34 observations used for estimation from 1975 to 2008 regressor coefficient standard error t-ratio[prob] con 1.3649 1.7005 .80260[.429] t -.0013122 .0056366 -.23280[.818] lnec(-1) .85776 .18428 4.6547[.000] lnec(-2) -.39723 .22722 -1.7483[.092] lnec(-3) .16750 .16764 .99921[.327] lny(-1) 2.3465 .89941 2.6089[.015] lny(-2) -.50993 1.3553 -.37624[.710] lny(-3) -1.5100 .97562 -1.5477[.134] r-squared .79376 r-bar-squared .73823 s.e. of regression .19318 f-stat. f( 7, 26) 14.2953[.000] mean of dependent variable 8.3997 s.d. of dependent variable .37758 residual sum of squares .97031 equation log-likelihood 12.2166 dw-statistic 2.1912 system log-likelihood 81.4585 system aic 65.4585 system sbc 53.2476 table x: seemingly unrelated regressions estimation. the estimation method converged after 0 iterations dependent variable is lny. 34 observations used for estimation from 1975 to 2008 regressor coefficient standard error t-ratio[prob] con .78017 .32027 2.4360[.022] t .0043641 .0010616 4.1110[.000] lny(-1) .96366 .16939 5.6890[.000] lny(-2) -.24802 .25525 -.97164[.340] lny(-3) .18140 .18374 .98726[.333] lnec(-1) -.016489 .034706 -.47511[.639] lnec(-2) -.0061151 .042793 -.14290[.887] lnec(-3) -.014059 .031572 -.44531[.660] r-squared .94288 r-bar-squared .92751 s.e. of regression .036383 f-stat. f( 7, 26) 61.3163[.000] mean of dependent variable 5.4787 s.d. of dependent variable .13513 residual sum of squares .034417 equation log-likelihood 68.9807 dw-statistic 1.4142 system log-likelihood 81.4585 system aic 65.4585 system sbc 53.2476 the test of toda and yomamoto granger causality then imposes restrictions on the first k-lags of the variable assumed to be non-causal in the equation. from equations (5) and (6), this study tested for the following null hypothesis based on the wald test respectively; 0: 12110  h as against the alternative hypothesis; 0: 1211  ah and 0: 12110  h as against the alternative hypothesis; 0: 1211  ah results of the wald tests are shown below; international journal of energy economics and policy, vol. 1, no. 1, 2011, pp.18-31 28 table xi: wald test of restriction(s) imposed on parameters in equation 5 the underlying estimated sure model is: lnec con t lnec {1-3} lny {1-3}; lny con t lny {1-3} lnec {1-3}. 34 observations used for estimation from 1975 to 2008 list of restriction(s) for the wald test: a6=0; a7=0 wald statistic chsq( 2)= 10.8149[.004] table xii: wald test of restriction(s) imposed on parameters in equation 6 the underlying estimated sure model is: lnec con t lnec {1-3} lny {1-3}; lny con t lny {1-3} lnec {1-3}. 34 observations used for estimation from 1975 to 2008 list of restriction(s) for the wald test: b6=0; b7=0 wald statistic chsq( 2)= .72479[.696] the sumary of the resulting test are as shown in table xiii below. table xiii: wald statistic null hypothesis wald statistic decision electricity consumption does not cause real per capita gdp 0.72479 do not reject the null real per capita gdp does not cause electricity consumption 10.8149*** fail to accept the null ***indicates 5% level of significance. from the results shown in table xiii, it can be concluded that there exists a unidirectional causality running from real per capita gdp to electricity consumption. thus, data on ghana supports the growth-led–electricity hypothesis. the results obtained herein confirms the conclusions reached by wolde-rufael (2006) and tweredfo et al (2008) but contradicts the conclusions reached by akinlo (2008) and lee (2005). the results obtained herein can be explained in two possible ways. first, electricity as an energy type constitutes the smallest share in terms of national energy consumption in ghana. largely, growth in total energy consumption is heavily dictated by the patterns of biomass and petroleum consumption, with biomas explaining about 70% of the variations in total energy consumption. thus, given the relatively small share of electricity consumption in total energy consumption, electricity consumption is not expected to be a major determinant of energy consumption, hence economic growth. secondly, the most productive sectors (agricultural and service sectors) in the ghanaian economy are less energy intensive. the structure of the distribution of domestic electricity consumption has tilted away from the industrial sector towards the residential sector. coupled with the declining industrial growth, the industrial sectors contribution to national output is now minimal. thus, the industrial sector (the most energy intensive sector), which is preordained to be the channel through which electricity consumption leads to growth is now on the decline. this suggests that even when there are severe energy crisis, the most productive sectors in the economy are less likely to be affected. for instaince, the severe energy crisis experienced in 2006/2007 did not sway the economy from achieving her macroeconomic targets. the economy amidst the energy crisis realised a macroeconomic growth target of about 6.2 percent, which was 0.2 percent higher than the target (budget statement, 2007, ghana). 5. conclusions and policy recommendations the study investigated into the direction of causality between electricity consumption and economic growth using the toda and yomamoto granger causality test from 1971 to 2008. the ardl bounds test of cointegration revealed that there exists a long-run relationship between electricity consumption and real per capita gdp and that real per capita gdp can be treated as the ‘long-run forcing’ variable explaining electricity consumption. electricity consumption-economic growth nexus: the ghanaian case 29 the test of causality between electricity consumption and real per capita gdp based on the toda and yomamoto granger causality test revealed that data on ghana supports the growth-ledelectricity hypothesis. the results herein imply that electricity conservation measures are a viable option for ghana. as a result there would be the need to develop and intensify appropriate electricity conservation measures in the ghanaian economy since this will not retard growth in the economy. acknowledgement i would like to express my heartfelt appreciation to two anonymous referees and the editor whose positive comments and suggestions have perk up the earlier version of this paper. any other error spotted in this work is the fault of the author. references acaravci, a., ozturk, i., (2010), electricity consumption-growth nexus: evidence from panel data for transition countries. energy economics 32(3), 604-608 altinay, g., and karagol, e. (2005), electricity consumption and economic growth: evidence from turkey. energy economics 27, 849-856. akarca,-a.t and long,-t.v (1980), on the relationship between energy and gnp: a reexamination. journal of energy and development, 5, 326-31. akinlo, a.e., (2009), electricity consumption and economic growth in nigeria: evidence from cointegration and co-feature analysis. journal of policy modelling doi:10.1016/j.jpolmod.2009.03 doi:10.1016/j.jpolmod.2009.03.004 akinlo, a.e., (2008), energy consumption and economic growth: evidence from 11 african countries: energy economics 30, 2391–2400. amusa h., amusa k. and mabugu r. (2009), aggregate demand for electricity in south africa. energy policy 37, 4167-4175 apergis, n. and j .e. payne (2009), the emissions, energy consumption, and growth nexus: evidence from the commonwealth of independent states. energy policy 38(1): 650-655 budgement statement, (2007), the republic of ghana. engle, r.f., and granger, c.w.j. (1987), cointegration and error correction representative, estimation and testing: econometrica 55, 251-276 fatai,-k, oxley,-l and scrimgeour,-f.g (2004), modelling the causal relationship between energy consumption and gdp in new zealand, australia, india, indonesia, the philippines and thailand: mathematics and computers in simulation, 64, 431– 45. ghali, k.h., el-sakka, m.i.t., (2004), energy use and output growth in canada: a multivariate cointegration analysis. energy economics 26, 225–238. ghosh, s., (2009), electricity supply, employment and real gdp in india: evidence from cointegration and granger-causality tests. energy policy 37 (8), 2926–2929. ghosh, s., (2002), electricity consumption and economic growth in india: energy policy 30, 125-129 giles, j.a., mizra s. (1998), some pre-testing issues on testing for granger non-causality: econometric working papers, ewp9914. department of economics, university of victoria, canada. granger g.w.j., (1969), investigating causal relations by econometric models and cross-spectral methods: econometrica 37. 424-438 guttormsen, a.g. (2004), causality between energy consumption and economic growth: department of economics and resource management, agriculture university of norway. norway. halicioglu, f., (2007), residential electricity demand dynamics in turkey. energy economics 29 (2), 199–210. hansen, b.e., seo, b., (2002), testing for two-regime threshold cointegration in vector errorcorrection models. journal of econometrics 110, 293–318. ho, c-y., siu, k.w., (2007), a dynamic equilibrium of electricity consumption and gdp in hong kong: an empirical investigation. energy policy 35 (4), 2507–2513. isser. ( 2000-2009), state of the ghanaian economy. university of ghana, legon-accra johansen, s., (1996), likelihood-based inference in cointegrated vector autoregressive models, second ed: oxford university press, oxford. johansen, international journal of energy economics and policy, vol. 1, no. 1, 2011, pp.18-31 30 johansen s, and juselius k. (1990), maximum likelihood estimation and inference on cointegration with applications to the demand for money. oxford bulletin of econonomics and statistics, 52, 169–210. kraft, j., and kraft a. (1978), on the relationship between energy and gnp: journal of energy development, 3, 401-403 lee,-c.c (2005), energy consumption and gdp in developing countries: a cointegrated panel analysis: energy economics, 27, 415–27. masih, a.m.m., masih, r., (1997), on temporal causal relationship between energy consumption, real income and prices; some new evidence from asian energy dependent nics based on a multivariate cointegration/vector error correction approach. journal of policy modeling 19 (4), 417–440. mavrotas g. and kelly r. (2001), old wine in new bottles>testing causality between savings and growth: the manchester school. vol. 69: 97-105 morimoto, r., hope, c., (2004), the impact of electricity supply on economic growth in sri lanka. energy economics 26, 77–85. narayan, p.k., smyth, r., (2005), electricity consumption, employment and real income in australia evidence from multivariate granger causality tests. energy policy 33, 1109–1116. narayan, p.k., (2005), the saving and investment nexus for china: evidence from cointegration tests. applied economics 37, 1979–1990. odhiambo, n.m., (2009a), energy consumption and economic growth nexus in tanzania: an ardl bounds testing approach. energy policy 37 (2), 617–622. odhiambo, n.m., (2009b), electricity consumption and economic growth in south africa: a trivariate causality test. energy economics 31 (5), 635–640. ozturk, i., (2010), a literature survey on energy-growth nexus. energy policy, 38(1), 340-49. ozturk, i., acaravci, a., (2011), electricity consumption-real gdp causality nexus: evidence from ardl bounds testing approach for 11 mena countries. applied energy, 88(8), 2885-2892. payne, j.e., (2009), on the dynamics of energy consumption and output in the us. applied energy 86 (4), 575–577. pesaran, m.h., shin, y.c., and smith, r., (2001), bound testing approaches to the analysis of level relationships: journal of applied econometrics 16, 289–326. pesaran, m.h., and pesaran, b., (1997), working with microfit 4.0: interactive econometric analysis: oxford university press, oxford. pesaran, m.h., and shin, y., (1992), an autoregressive distributed lag modeling approach to cointegration analysis, in strom s. (ed) econometrics and economic theory in the 20th century: cambridge university press, cambridge. rambaldi, a.n. and h.e. doran (1996), testing for granger non-causality in cointegrated systems made easy: working papers in econometrics and applied statistics 88, department of econometrics. sari,-r and soytas, u. (2007), the growth of income and energy consumption in six developing countries: energy policy vol. 35 (2) pp. 889–98. shiu, a., lam, p., (2004), electricity consumption and economic growth in china. energy policy 32, 47–54. sims c. (1972), money, income and causality: american economic review, 62, 540-552 soytas, u., sari, r., (2009), energy consumption, economic growth, and carbon emissions: challenges faced by an eu candidate member. ecological economics 68 (6), 1667–1675. soytas, u., and sari, r, (2003), energy consumption and gdp: causality relationship in g-7 countries and emerging markets: energy economics, vol.25, pp.33-37. stern, d.i., (2000), a multivariate cointegration analysis of the role of energy in the us macroeconomy. energy economics 22, 267–283. tang, c.f., (2008), a re-examination of the relationship between electricity consumption and economic growth in malaysia. energy policy 36 (8), 3077–3085. toda, h.y., yamamoto, t. (1995), statistical inference in vector autoregressions with possibly integrated processes: journal of econometrics 66, 225–250. electricity consumption-economic growth nexus: the ghanaian case 31 twerefo d.k., akoena s.k.k., egyir-tettey f.k. and mawutor g., (2008), energy consumption and economic growth: evidence from ghana. department of economics, university of ghana, ghana wolde-rufael, y., 2006), electricity consumption and economic growth: a time series experience for 17 african countries: energy policy 34, 1106-1114. yu, e.s.h., choi, p.c.y., and choi, j.y., (1988), the relationship between energy and employment: a re-examination: energy systems policy 11, 287–295. yu, e.s.h., and hwang, b.k., (1984), the relationship between energy and gnp: further results. energy economics 6,168–266. zapata, h. o., and a. n. rambaldi (1997), monte carlo evidence on cointegration and causation: oxford bulletin of economics and statistics 52, 285-298. . international journal of energy economics and policy | vol 7 • issue 2 • 2017 127 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(2), 127-131. effective approaches to energy planning and classification of energy systems models farzad rahimi mougouei1*, mahdieh-sadat mortazavi2 1faculty of industrial engineering, golpayegan university of technology, golpayegan, iran, 2faculty of industrial engineering, amirkabir university of technology, tehran, iran. *email: rahimi.farzad@gut.ac.ir abstract a balance between energy supply and demand is one of the challenges faced by policy makers. in fact, the main objective of energy planning is to achieve this balance. energy models can be used for supply and demand future planning of a country or region. in most situations, these methods focus on economic development, energy policy, selection of appropriate resources and technologies for the future and investing in these technologies. this paper discusses the definitions of energy planning and classifies models of energy systems according to various approaches. the paper concludes that overall energy planning requires a balance between supply and demand of energy. however, achieving this balance is possible with the coordination of all energy sectors, proper development and implementation of energy policies and finally guidance and help to the consumer to select the best sources. keywords: energy planning, energy systems modeling, energy management jel classifications: o13, q4 1. introduction as one of the essential needs of humanity, energy has always been one of the most influential factors in economic, social, technical and environmental sectors. hence, achieving an appropriate situation in this area and having proper planning adapted to specific conditions and characteristics of each country are considered two of the priorities of the governments. in recent decades, due to increasing demand for energy and turning to renewable resources instead of fossil fuels various models and methods in predicting and determining the appropriate share of required energy fuels have been developed. according to the latest balance sheet published in iran, in 2012, the primary energy production was equivalent to 2,219.1 million barrels of crude oil, of which only 0.5% was allocated to wind, solar, hydro and nuclear energies, 0.4% to the combustible renewable and the rest, i.e., 99.1%, to the fossil resources. moreover, the final energy consumption mentioned is equivalent to 1,058.6 million barrels of oil 0.71% and 9.93% are provided by combustible renewable resources and by the electricity, respectively. overall, per capita consumption of natural gas and crude oil and their petroleum products are 6 and 1.6 times as much as the global average, while the per capita consumption of renewable resources, coal and electricity is less than that of the global average. the per capita co2 emissions in 2010, was about 4.9 tons in the world while it was 7.7 tons/year in iran (office macro, 2013, the world bank). with regard to these statistics, high energy consumption in iran and consequently emissions from the combustion of fossil fuels need more attention to be paid to the replacement of conventional energy sources and fossil fuels than ever before. construction and operation of a 29.9 mw wind power and 1.6 mw biomass power plant to generate electricity are activities that have taken place in the renewable resources sector in iran. of course, other projects and feasibility studies are in the process of obtaining the necessary permits, too. although several projects in various sectors of renewable sources in the operation have been carried out, their low share cannot meet the demand of the growing population. in addition, the incidence of economic fluctuations affecting fossil resources, population growth and increasing energy demand and raising awareness about the negative effects of fossil fuels on the environment and human health, have made the use of renewable mougouei and mortazavi: effective approaches to energy planning and classification of energy systems models international journal of energy economics and policy | vol 7 • issue 2 • 2017128 resources the focus of attention. renewable energy sources have a higher price stability because they are less vulnerable to price fluctuations; therefore they reduce dependence on resources such as oil, and they will ultimately protect the environment. finally, taking the social and economic well-being of society into account, the quality of energy at the point of consumption, growth in less developed regions and similar cases make the utilization of renewable resources more important. 2. the definition of energy planning despite different definitions of energy planning, all these definitions focus on common points. according to a survey on energy planning and related definitions, a good energy plan has been introduced as a program based on rigorous research on issues related to energy supply and demand, energy prices, technology supply and demand, population growth, environmental, social, technological success in harnessing the energy and influence the political situation of a country (ravita et al., 2014). some definitions of energy planning by other researchers are as follows: • energy planning is an optimal combination of energy sources to satisfy demand (thery and zarate, 2009) • meeting projected energy demand during a given period, by taking the political, social and environmental considerations into account as well as data collected from previous energy plans are the basis for energy planning (cormio et al., 2003) • energy planning includes finding a set of resources and energy conversion equipment to meet the energy demand in a way that is desirable (hiremath et al., 2007) • ensuring the supply as primary goal of energy planning is achievable by careful management of natural resources, diversification of energy sources to reduce energy imports and rational use of energy (kleinpeter, 1995) • the energy planning goal is to determine the optimal mixture of energy sources to meet the energy demand (mourmouris and potolias, 2013). the need to meet the demand in a way desired is the most common point in these definitions. furthermore, considering the amount of supply and planning and rightful management of resources in terms of criteria affecting energy sources is mentioned in most definitions. with regard to the common points, we can see that overall energy planning requires a balance between demand and supply of energy. in fact, to achieve this balance is possible if all the energy sectors are coordinated together, and in addition to correct formulation and implementation of energy policies, help the consumer in better use of resource. 3. energy systems models classification energy modeling dates back to the early 1960s; however, due to the first oil crisis in the world in 1973, the development of these models was followed more seriously (jebaraj, 2006). since then, many methods for planning energy systems with different categories in various fields have been created; however, none of them can be the best classification proposed. in fact, a comprehensive classification scheme or program can provide a good understanding of the differences and similarities between the energy models and can facilitate the process of selecting the most appropriate model to use in the desired position or location. however, to choose a suitable model, study and overview on different methods of classification can be useful. in the following section, energy models are classified based on 6 different approaches, and the specifications and features of each approach are discussed. 3.1. the first approach: classification based on criteria related to models each model is a simplified form of the reality. models of energy systems are designed and created based on different purposes in order to use in different situations. thus, according to the objectives, assumptions and conditions of applying any model will be effective to classify them. at the moment, there are different criteria to classify energy models; an example of a classification distinguishes three important ways to differentiate energy models; namely, the purpose of the models, their structure, and their external or input assumptions (hourcade et al., 1996). another uses six dimensions to classify energy models; (1) top-down versus bottom-up, (2) time horizon, (3) sectoral coverage, (4) optimization versus simulation techniques, (5) level of aggregation, and finally (6) geographic coverage, trade, and leakage (grubb et al., 1993). in addition to the above, other criteria such as mathematical techniques, the degree of complexity of the model and the flexibility of the model were considered for classification. finally, general criteria for the classification of different models are as follows (van beck, 1999): 1. purposes of energy models: general and specific purposes 2. the model structure: internal and external assumptions 3. the analytical approach: top-down versus bottom-up 4. the underlying methodology: econometric, macro-economic, economic equilibrium, optimization, simulation, spreadsheet (tool boxes), back-casting and multi-criteria models 5. the mathematical approach: linear (lp), mixed integer (mip) and dynamic programming 6. geographical coverage: global, regional, national, local, or project 7. sectoral coverage 8. the time horizon: short, medium, and long term 9. data requirements: quantitative, qualitative, synthetic. 3.2. the second approach: classification of jebaraj in a comprehensive study by jebaraj in 2006, all the energy models had been studied by that time. today, his proposed classification is used as a comprehensive approach to the energy models. that is why the proposed approach has been introduced individually and as an integrated approach to energy classification models. in recent years, several papers have been presented on the basis of this approach. jebaraj has studied numerous researches that had been published in different years, and based on the existing review articles, he has provided the following categories: 1. energy planning models: these models are designed to create an integrated energy model to consider all sources of energy 2. energy supply-demand models: these models include models of energy supply, energy demand and a combination of supply and demand as hybrid models mougouei and mortazavi: effective approaches to energy planning and classification of energy systems models international journal of energy economics and policy | vol 7 • issue 2 • 2017 129 3. forecasting models: these models are formulated based on different variables such as population, income, prices, growth factors and technology. the forecasting models’ purpose is to determine the distribution patterns of energy. both fossil fuels and renewable energy resources are considered in these models 4. optimization models: in order to allocate energy demand for each of the renewable resources, formulation of optimization models is done 5. energy models based on neural networks: during the time, using artificial intelligence technologies is more common to solve complex scientific problems in various sectors. the reasons are their being reasonable, flexible and selfexplanatory systems based on artificial intelligence 6. emission reduction models: the destructive effects of pollutants and greenhouse gases caused by fossil fuels leading to develop some models to assess the total amount of these pollutants and the use of renewable sources instead of fossil fuels (jebaraj, 2006). 3.3. the third approach: classification based on analytical approach of models different types of energy models, based on their analytical or conceptual framework, include top-down approach, bottom-up approach and integrated approach that is the combination of the two main approaches. the difference between the two groups is very interesting because they provide different results for one question. in fact, the difference in the results arises from the method or style of decisions, technology adoption and behavior of markets and economic institutions in a given period (van beck, 1999). table 1 compares the characteristics of two main approaches. top-down models including input-output models, econometric models, computable general equilibrium models and systems dynamic, as well as partial equilibrium models, optimization models, simulation models and multi-agent models are as bottomup models (herbst et al., 2012). to overcome the weaknesses and limitations such as lack of technological detail, delivering rather generalized information on the top-down models and lack of macro-effects of the presumed technological change on overall economic activity, structural changes, employment, and prices in bottom-up models, energy modelling is currently moving in the direction of hybrid energy system modelling combining at least one macroeconomic model with at least one set of bottom-up models for each final energy sector and the conversion sector. a high-quality hybrid model system should incorporate at least three properties: 1. technological explicitness 2. microeconomic realism 3. macroeconomic completeness. in addition, considering important issues like the structural changes (inter-sectoral and intra-sectoral) and technological progress require more attention (herbst et al., 2012). 3.4. the fourth approach: classification as supplydemand perspective one of the main tasks of the energy sector is meeting energy demand in various sectors. energy demand is influenced by social, economic, technological and technical factors; therefore, supply of energy needs the development of energy system modeling. energy demand models like other models of energy can be classified by criteria such as objectives, assumptions, technological change and the description of environment. in the general case, the models are grouped in econometric approach, optimization approach and forecasting approach (ravita et al., 2014). energy forecasting as one of the most widely used areas in energy demand has several approaches. types of energy demand forecasting models are: time series models, regression models, econometric models, decomposition models, cointegration models, arima models, artificial systems like experts systems and ann models, grey prediction models, input-output models, fuzzy logic/genetic algorithm models, integrated models like autoregressive, support vector regression and particle swarm optimization models, and bottom up models like markal/times/leap (suganthi and samuel, 2012). in order to meet the energy needs of the different sectors, supply systems will be created. in fact, the supply of useful energy is possible through utilization of primary energy and by diverse table 1: characteristics of top-down and bottom-up approaches (van beck, 1999) top-down models bottom-up models use an “economic approach” use an “engineering approach” give pessimistic estimates on “best” performance give optimistic estimates on “best” performance cannot explicitly represent technologies allow for detailed description of technologies reflect available technologies adopted by the market reflect technical potential the “most efficient” technologies are given by the production frontier (which is set by market behavior) efficient technologies can lie beyond the economic production frontier suggested by market behavior use aggregated data for predicting purposes use disaggregated data for exploring purposes are based on observed market behavior are independent of observed market behavior disregard the technically most efficient technologies available, thus underestimating the potential for efficiency improvements disregard market thresholds (hidden costs and other constraints), thus overestimating the potential for efficiency improvements determine energy demand through aggregate economic indices (gnp, price elasticities), but vary in addressing energy supply represent supply technologies in detail using disaggregated data, but vary in addressing energy consumption endogenize behavioral relationships assess costs of technological options directly assume there are no discontinuities in historical trends assume interactions between energy sector and other sectors is negligible mougouei and mortazavi: effective approaches to energy planning and classification of energy systems models international journal of energy economics and policy | vol 7 • issue 2 • 2017130 energy conversion technologies. other supply models are based on three general approaches including econometrics, optimization and forecasting, as well as the criteria mentioned in the first approach of this study. most popular energy supply models include markal, times, efom, wasp, jasp, message, ideas, ret screen, leap, npep, mesap, nems and energy 2020. these models have been developed by organizations in different parts of the world. all models offer the final consumption of energy or the amount of energy required to estimate the energy demand. therefore, the types of input and output data are mentioned in the classification of these models (kazemi et al., 2013). finally, it can be concluded that energy demand models only consider the demand for each of the sectors. in contrast, energy supply models simulate the demand as a predicted value. in order to obtain a better result, by extracting the positive characteristics of each group, the integrated model of supply and demand is used (kleinpeter, 1995). 3.5. fifth approach: classification as developing countries’ perspective model selection in developing countries should be based on the specific characteristics of such countries. often (especially in econometric and optimization models) standard models for energy systems do not consider enough features and problems of developing countries (bhattacharyya and timilsina, 2010). as most of these models have been created and developed in industrial societies, they cannot meet the characteristics of traditional societies or developing countries. although a number of models are flexible to consider some features (such as fossil energy sources in the model), often local or national models ignore these features. in general, the required data and theoretical foundation of the standard model and lack of ability in terms of the characteristics of a particular country make them inappropriate. poor performance of electricity and fossil fuels, transition from a traditional economy to a modern economy and structural efficiency in society, economy and energy systems are the most important characteristics of developing countries, and need special attention (urban et al., 2007). in addition to these general features, other cases like reliance on fossil energy sources, large informal sector that is sometimes bigger than the formal sector, the urban-rural division and spread of inequality and poverty, structural changes in the economy and the transition from traditional to modern life style, energy supply shortages due to poor performance of power plants, the existence of multiple economic and social barriers to investment and slow technological diffusion make energy systems in developing countries significantly different from these systems in developed countries (bhattacharyya and timilsina, 2010). thus, the energy model in developing countries should be able to consider these features. 3.6. sixth approach: classification in uncertainty and risk conditions since the main aim of energy planning is to match the supply and demand for energy over a given period of time, understanding the energy system that confronts the energy supply and demand is crucial. in addition, uncertainties in any energy system and the possibility of shortage in energy resources necessitate the development of a model by taking the following into account. in order to control the uncertainty in energy planning, a range of different methods such as interval linear programming, fuzzy mathematical programming and random mathematical programming are generated. other techniques under conditions of uncertainty are decision analysis methods daim et al. (2013) and scott et al. (2012). these methods are classified into three, including multi-criteria decision making technique, singleobjective decision-making method and decision support system. each of these techniques, using optimization methods, forecasting methods (including mathematical models and simulation), qualitative and in some cases life-cycle analysis technique and geographic information systems, provides results close to reality compared to other methods (ravita et al., 2014). 4. conclusion in general, the balance between supply and demand is one of the challenges facing policy makers. if all energy sectors are coordinated with each other and energy policies are formulated and implemented correctly, it will be possible to achieve this balance, which is the main objective of energy planning. energy models are used to plan for the future supply and demand of a country or region. finally, in these methods, some cases such as economic activity development, energy policy, material selection, appropriate technology selection and investment on this technology will be considered. references bhattacharyya, s.c., timilsina, g.r. (2010), a review of energy system models. international journal of energy sector management, 4(4), 494-518. cormio, c., dicorato, m., minoia, a., trovato, m. (2003), a regional energy planning methodology including renewable energy sources and environmental constraint. renewable and sustainable energy reviews, 7(2), 99-130. daim, t.u., oliver, t., kim, j. (2013), research and technology management in the electricity industry (methods, tools and case studies). new york: springer. grubb, m., edmonds, j., brink, p.t., morrison, m. (1993), the cost of limiting fossil-fuel co emissions: a survey and analysis. annual review of energy and the environment, 18, 397-478. herbst, a., toro, f., reitze, f., jochem, e. (2012), introduction to energy systems modeling. swiss society of economics and statistics, 148(2), 111-135. hiremath, r.b., shikha, s., ravindranath, n.h. (2007), decentralized energy planning; modeling and application a review. renewable and sustainable energy reviews, 11(5), 729-752. hourcade, j.c., richels, r., robinson, j.b. (1996), estimating the cost of mitigating greenhouse gases. in: bruce, j.p., lee, h., haites, e.f., editors. climate change 1995: economic and social dimensions of climate change. contribution of working group iii to the second assessment report of the ipcc. cambridge: university press. p263-296. jebaraj, i.s. (2006), a review of energy models. renewable and sustainable energy reviews, 10(4), 281-311. kazemi, a., shakoori, g.h., shakiba, s., hossein, z.m. (2013), the perfect model for the allocation of energy resources in iran using analytical hierarchy process. iran energy journal, 16(2), 31-60. kleinpeter, m. (1995), energy planning and policy. england: john wiley & sons ltd. mougouei and mortazavi: effective approaches to energy planning and classification of energy systems models international journal of energy economics and policy | vol 7 • issue 2 • 2017 131 mourmouris, j.c., potolias, c. (2013), a multi-criteria methodology for energy planning and developing renewable energy sources at a regional level: a case study thassos, greece. energy policy, 52(c), 522-530. office macro planning of electricity and energy, ministry of iran. (2013), iran energy balance 2012. tehran: office macro planning of electricity and energy. ravita, d., prasad, r.c., bansal, a.r. (2014), multi-faceted energy planning: a review. renewable and sustainable energy reviews, 38(c), 686-699. scott, j.a., ho, w., dey, p.k. (2012), a review of multi-criteria decisionmaking methods for bioenergy systems. energy, 42(1), 146-156. suganthi, l., samuel, a. (2012), energy models for demand forecasting a review. renewable and sustainable energy reviews, 16(2), 1223-1240. the world bank, co2 emissions (metric tons per capita). available from: http://www.worldbank.org. thery, r., zarate, p. (2009), energy planning: a multicriteria decision making structure proposal. central european journal of operations research, 17(c), 265-274. urban, f., benders, r.m.j., moll, h.c. (2007), modelling energy systems for developing countries. energy policy, 35(6), 3473-3482. van beck, n. (1999), classification of energy models. tilburg: tilburg university & eindhoven university of technology. . international journal of energy economics and policy | vol 8 • issue 5 • 2018342 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(5), 342-346. determination of parity price for gas and electricity in terms of estimation of household incomes and energy costs nadiia pysar1*, victoria dergacheva2 1vasyl stefanyk precarpathian national university, ivano-frankivsk, ukraine, 2igor sikorsky kyiv polytechnic institute, kyiv, ukraine. *email: diserdiser72@gmail.com abstract the paper is concerned with comparing household incomes in ukraine and european countries, estimating households’ gas and electricity costs, as well as determining parity prices for these goods in ukraine for 2016. the calculation of parity prices for electricity and gas was carried out by the share of household’s electricity and gas costs in the respective country to its income level and by the absolute need of the corresponding household for electricity and gas in the respective country. the determination of the parity price for gas and electricity relative to household incomes and energy costs is an attempt to come up with a decision on the need to increase or decrease prices for these goods in ukraine compared to other countries and to assess their relationship to household incomes in order to avoid fuel poverty in ukraine. an investigation of this problem enables to focus on comparing prices and electricity and gas costs with household incomes using a sales comparison approach and determine the need to increase or decrease prices in ukraine to the level of european prices for similar goods. this approach to determining the parity price for energy resources can be used for any other country taken as a basis for analysis and calculation. keywords: energy efficiency, pricing, parity, law of one price, market conditions, liberalization, common energy space jel classifications: b41, r13, o15, n3 1. introduction in the context of formation of the common european energy space, the establishment of parity prices for energy resources is instrumental in the liberalization of the competitive energy market. today, the pricing policy in ukraine is somewhat different from that in europe as ukrainian electricity market goes through the liberalization stages. electricity costs for the ultimate consumer remain clearly regulated. the national energy and public utilities regulatory commission of ukraine imposes tariffs according to the category of electricity consumers along with the weighted average tariff. in europe, the regulation was abandoned with the price imposed by the market as a function of supply and demand. thus, the average electricity prices for european households are approximately 8 times higher than those in ukraine. the policy of european integration primarily means building markets according to european regulations. given the stated goals for reforming ukrainian energy market, prices for electricity, gas and other energy resources shall match market prices. however, given the lowest household incomes in ukraine among all european countries and high energy consumption of households, the increase in energy prices in ukraine to the level of prices for similar goods in european countries can result in “fuel poverty” in ukraine. with this in mind, the investigation and determination of the parity price for gas and electricity in terms of estimating household incomes and energy costs is a necessary and relevant objective given the need to build a socially-oriented market-based economy in ukraine. however, the bringing of residential tariffs to the market level enhances incentives for the introduction of energyefficiency measures. 2. recent literature review among the latest publications in the search for a single price for gas, oil, electricity and assessment of the degree of market pysar and dergacheva: determination of parity price for gas and electricity in terms of estimation of household incomes and energy costs international journal of energy economics and policy | vol 8 • issue 5 • 2018 343 liberalization, it is noteworthy to mention the following researchers: bahmani-oskooee et al. (2015) verified parity prices of the six largest oil-exporting countries by the selection method and fourier analysis. the results support the parity in all six countries, except russia, and indicate nonlinear interconnection of exchange rates in the countries concerned. barrett and li (2002) presents a new approach to analyzing the spatial price based on the estimation of maximum likelihood of the amount distribution model, including price, transfer fee and data on trade flows. this method enables to distinguish between market integration and competitive market equilibrium. the authors (fan and wei, 2006) established the degree of market-based economy in china through the law of one price for the overwhelming majority of goods and services. propose to investigate the degree of market integration by the law of one price by authors (góes and matheson, 2015). according to growitsch and nepal (2009), one of the major objectives of liberalization of european electricity markets is to create competitive and efficient electricity sales markets. in this paper, the author assesses the overall performance of german wholesale electricity market through cointegration analysis and error correction modeling. kulikov and pak (2014) consider the law of one price for 13 eurozone countries using a methodology based on the non-structural linear regression with spatial effects in the geographical measurement of goods and bayesian estimates. lee and park (2015) analyze the goods market in terms of large and unstable deviations from the law of one price as part of flexible prices. dehnavi et al. (2015) investigate the problems of liberalization and competition in gas markets, as well as the problems of price variance from the law of one price. searby (2014) believes that one of the most common standards of value is “fair market value.” he attempts to define the market approach to estimation as the asset value at market prices for comparable assets. the market-based estimation is expressed on the basis of the relevant asset characteristic, for example, its profit, sale or net asset value. gupta (2016) investigates the competition in the oil market and states that businesses in noncompetitive industries have less bearing on the decrease in oil price compared to those in highly competitive industries. olsen et al. (2015) determine the extent to which the law of one price (integration) applies, as well as the role of each individual market in determining prices in 11 major natural gas markets, six from the usa and five from canada. the degree of integration varies with the region. geographically adjacent markets are typically more integrated than those located far from one another. nick and tischler (2014) investigate the degree of gas market integration using the threshold cointegration approach, which corresponds to the law of one price. the above scientific works consider the methodological bases for assessing market liberalization, degree of competition of the energy market and integration into a common energy space through compliance with the law of one price. however, given the importance of research for ukrainian energy market, estimates of parity prices of ukrainian and european energy markets are not presented in scientific discourse. inadequate attention is paid to the methodology for determining the parity price for energy resources. this forms the basis of this paper. performance indices largely depend on the adequacy of statistical data as each country has its own approaches to gathering various statistical data. 3. methodology all energy prices are stated in uah; therefore, the price for gas and electricity in the eu countries was converted into uah at the rate of 1 eur = 32.40 uah. since in the eu energy indices, in particular for gas, are given in kwh, these units were converted into cubic meters by the formula: 1 kwh = 0.09231 cubic meters. comparison of the level of purchasing power in ukraine and the eu countries was carried out through the ratio of indices of average annual household incomes of the selected eu countries and ukraine according to eurostat for 2016 in eur. the investigation of parity prices for gas and electricity offers three approaches: 1. parity by household income, according to which the amount of gas (in cubic meters) that can be purchased for the average monthly salary by each country and the amount of electricity (in kwh) that can be purchased for the annual household income are determined at prices of the respective country. according to this approach, in ukraine and any respective country the parity of prices exists where the product of ukrainian energy resource price for the calculated amount of the energy resource hypothetically purchased for the salary in the respective country is approximately equal to the average monthly salary (to these calculations) in ukraine. if in ukraine the calculated annual parity income relative to the consumed energy resource is lower than the actual one, the price for the corresponding energy resources should be increased, and if higher decreased; 2. parity by share of energy costs at one household income, %. according to this approach, the price for energy resources in ukraine is calculated as the product of share of household energy costs in the respective country to the income of ukrainian household. the higher the share of costs, the higher the estimated price for energy resource and vice versa. hence the need to increase or decrease ukrainian energy costs towards finding parity between countries is assumed; 3. parity by absolute electricity costs of the respective household in the respective country. here, the parity price in ukraine relative to another country is defined as the ratio of absolute household costs of that country to the average amount of electricity consumed by ukrainian household. if the parity price is higher, prices should be increased and vice versa. 4. results and discussion the pricing policy in ukraine is somewhat different from that in europe as ukrainian electricity market has not yet gone through liberalization. therefore, a comparison of ultimate gas and electricity prices in europe and ukraine enables to determine the market need for an increase or decrease in the current price of energy resources in relation to a particular country. despite the increase in prices, the ratio between the cost of “blue fuel” paid by european and ukrainian residents is now significantly different (table 1). given the stated goals of the ukrainian energy pysar and dergacheva: determination of parity price for gas and electricity in terms of estimation of household incomes and energy costs international journal of energy economics and policy | vol 8 • issue 5 • 2018344 ta bl e 1: p ar it y pr ic e fo r ga s an d el ec tr ic it y e ur op ea n co un tr ie s a ve ra ge a nn ua l in co m e of ho us eh ol ds , e u r , 2 01 6 n at ur al ga s pr ic e, e u r /c u m , 20 16 e le ct ri ci ty p ri ce in e ur op ea n co un tr ie s, e u r /k w h, 2 01 6 d if fe re nc e in p ar it y pr ic e fo r ga s by in co m e d if fe re nc e in pa ri ty p ri ce fo r el ec tr ic it y by in co m e p ar it y pr ic es b y sh ar e of e le ct ri ci ty co ns um pt io n, u a h p ar it y pr ic es by s ha re o f g as co ns um pt io n, u a h p ar it y pr ic es by a bs ol ut e el ec tr ic it y co st s, u a h p ar it y pr ic es b y ab so lu te g as co st s, u a h 1 2 3 4 5 6 7 8 9 u kr ai ne 3, 37 8 0. 24 0. 03 1 1 1. 28 6. 87 9 1. 28 6. 87 9 b ul ga ri a 3, 14 7 0. 33 0. 09 0. 67 0. 31 1. 96 0. 28 1. 83 0. 26 l ith ua ni a 5, 64 4 0. 41 0. 12 0. 97 0. 42 0. 83 1. 06 1. 38 1. 77 h un ga ry 4, 72 2 0. 38 0. 12 0. 88 0. 35 1. 19 6. 92 1. 66 9. 67 e st on ia 8, 64 7 0. 35 0. 12 1. 76 0. 64 0. 81 0. 51 2. 07 1. 30 c ro at ia 5, 72 6 0. 39 0. 13 1. 04 0. 39 1. 71 2. 79 2. 90 4. 72 m al ta 13 ,5 72 0. 13 0 0. 93 0. 66 0. 00 2. 67 0. 00 r om an ia 2, 44 8 0. 34 0. 12 0. 52 0. 18 1. 48 5. 69 1. 07 4. 12 sl ov ak ia 6, 95 1 0. 47 0. 15 1. 06 0. 41 1. 03 4. 86 2. 13 10 .0 0 t he c ze ch r ep ub lic 7, 83 8 0. 59 0. 14 0. 94 0. 49 1. 11 4. 45 2. 57 10 .3 2 po la nd 5, 90 5 0. 47 0. 14 0. 89 0. 38 0. 92 2. 66 1. 61 4. 65 t he n et he rl an ds 22 ,7 45 0. 85 0. 16 1. 91 1. 26 0. 36 4. 48 2. 45 30 .1 6 l at vi a 6, 37 4 0. 43 0. 16 1. 05 0. 36 0. 98 1. 15 1. 85 2. 17 fi nl an d 23 ,6 50 0. 16 0. 00 1. 31 0. 99 0. 00 6. 93 0. 00 sl ov en ia 12 ,3 27 0. 59 0. 16 1. 48 0. 68 0. 92 0. 87 3. 36 3. 17 l ux em bo ur g 33 ,8 38 0. 44 0. 17 5. 46 1. 77 0. 32 1. 61 3. 22 16 .1 7 fr an ce 21 ,7 20 0. 71 0. 17 2. 17 1. 14 0. 74 1. 69 4. 76 10 .9 0 c yp ru s 14 ,0 20 0. 16 0. 00 0. 78 1. 16 0. 00 4. 83 0. 00 g re ec e 7, 50 4 0. 69 0. 17 0. 77 0. 39 2. 05 0. 88 4. 56 1. 96 a us tr ia 23 ,6 94 0. 71 0. 2 2. 37 1. 05 0. 66 1. 19 4. 61 8. 34 g re at b ri ta in 21 ,1 36 0. 53 0. 18 2. 84 1. 04 0. 63 2. 76 3. 94 17 .2 9 sw ed en 25 ,2 02 1. 2 0. 2 1. 49 1. 12 1. 59 0. 05 11 .8 3 0. 35 sp ai n 13 ,6 85 0. 9 0. 23 1. 08 0. 53 1. 02 1. 63 4. 14 6. 59 it al y 16 ,2 47 0. 88 0. 23 1. 32 0. 63 0. 60 4. 58 2. 87 22 .0 5 po rt ug al 8, 78 2 0. 87 0. 24 0. 72 0. 33 1. 47 0. 79 3. 81 2. 05 ir el an d 22 ,4 07 0. 72 0. 23 2. 22 0. 87 0. 85 1. 34 5. 67 8. 89 b el gi um 22 ,2 93 0. 56 0. 27 2. 83 0. 74 0. 88 2. 28 5. 78 15 .0 4 d en m ar k 28 ,6 59 0. 78 0. 31 2. 62 0. 82 0. 67 0. 77 5. 66 6. 53 g er m an y 21 ,2 63 0. 68 0. 3 2. 22 0. 63 0. 84 2. 35 5. 31 14 .8 0 c al cu la tio ns o f t he a ut ho r i n ta bl e 1 co ns is t o f a n an al ys is o f t he in fo rm at io n ba se : a llu kr ai ni an in fo rm at io n an d st at is tic al in fo rm at io n of e ur op ea n in st itu tio ns in th e fi el d of n at ur al (2 01 7) , m ea n an d m ed ia n in co m e by h ou se ho ld t yp e (2 01 7) , s oc io -d em og ra ph ic c ha ra ct er is tic s of h ou se ho ld s in u kr ai ne (2 01 7) . e le ct ri ci ty c on su m pt io n by in du st ry , t ra ns po rt a ct iv iti es a nd h ou se ho ld s/ se rv ic es (g w h ) ( 20 17 ), e le ct ri ci ty p ri ce s in e ur op e (2 01 7) . pysar and dergacheva: determination of parity price for gas and electricity in terms of estimation of household incomes and energy costs international journal of energy economics and policy | vol 8 • issue 5 • 2018 345 market reformation, the prices for energy resources should be brought to market prices and the level required to achieve parity of import price. in ukraine, prices are formed with account for the use of gas of different origin. the corresponding volume of domestic gas production covers only 70% of household needs (direct supplies and gas for heat production), with the remaining 30% being imported from other countries. today, part of the business selling gas to households remains unprofitable, and household gas prices are subsidized mainly using small profits from sale of ukrainian gas and other activities. returning prices to the previous level would mean an increase in losses. the increase in the budget and trade balance deficit can only be stopped by leveling household prices. along with the increase in utility prices, it is also necessary to improve the quality of services due to market competition. in ukraine, however, the increase in prices for energy resources due to disproportionate increase in energy prices and household incomes brings about poverty of ukrainian households. in the eu countries, the average ppp gdp is 36,326 us dollars, which is approximately 4 times higher than that in ukraine. in particular, in italy, france and germany the average ppp gdp is respectively 4, 4.5 and 5.3 times higher than that in ukraine [13]. below is a table that is based on the statistical data of references 1420 and characterizes the methodology for determining the parity price for gas and electricity in terms of estimation of household incomes and energy costs. the calculation data in table 1 (columns 4 and 5) enable to obtain information on the price of energy resources in ukraine relative to each country if ukraine had household incomes similar to those in other countries. or, how much household incomes in ukraine should be increased or decreased to achieve similar energy prices parity in order to avoid fuel poverty in ukraine. for example, having compared household incomes in ukraine and luxembourg, we calculated that gas prices relative to this country should be reduced by a factor of 5.5 since household incomes in ukraine are 10 times lower than those in luxembourg, where gas prices are only 1.8 times higher than ukrainian ones. when it comes to poland, we could raise gas prices by 0.11% as polish household incomes exceed ukrainian ones by 1.8 times considering the fact that gas prices in poland are 1.9 times higher than ukrainian ones. according to the second approach (see columns 6, 7 in table 1), it appears that if ukrainian households had the same share of energy costs as in a particular european country, that energy price would be acceptable relative to the ukrainian household incomes. for example, if the share of gas costs in hungarian household incomes is 0.07%, the gas price in ukraine should be 1.19 uah given the same share of gas costs in ukrainian household incomes. in this case, we equated the volume of energy consumption. according to the third approach (columns 8, 9 in table 1), it becomes clear what price for energy resources would be acceptable for ukraine in order to avoid fuel poverty, if ukrainian household income had the amount of energy costs similar to that in other countries. in this case, the comparison considered the prices of energy resources in different countries. for example, if ukrainian households had similar absolute energy costs as the average italian household, ukrainian households would pay 2.87 uah for electricity against 1.28 uah/kwh, i.e. the electricity price relative to italy can be increased by another 1.59 uah. 5. conclusion as a result, the growth of purchasing power parity of ukrainian households is expedient together with the increase in prices. otherwise, ukrainian households are under the threat of ending up in the category of poverty, which will mean an increase in spending on targeted subsidies in ukraine. in addition, the market will face a non-payments crisis, and consequently, a shortage of funds for the purchase of fuel and underinvestment of the industry. increase in energy prices is only one of the prerequisites for creating competitive, transparent and efficient markets. market prices will allow to accumulate adequate resources for upgrading the infrastructure, implementing innovations, as well as increasing domestic production. the government should encourage business initiative as the development of small and medium-sized businesses is a way to achieve simultaneous growth of economy and household incomes while restraining inflation on consumer goods. another tool for reforming the energy market is incentives for energy efficiency, i.e. reducing energy consumption and costs. to consume less and pay more for high quality services is the basis of a rational economy in current conditions. ukraine’s monopolists should be replaced by a whole industry of customer services, which means competition that is required to form a fair price for energy resources. thus, any monetary authority (the national bank of ukraine or any other strategic investor) can use the methodology for calculating the parity price for gas and electricity from the perspective of forecasting social and economic development. it is also important to consider the divergence of difference between the fundamental assessment of a currency pair and its market valuation. the greater the divergence, the higher the grounds for changing the direction of the exchange rate for the respective currency pair. the effectiveness of the parity price model provides for the real exchange rate stabilization in the long-term horizon period, but does not deny the significant short-term deviations from its average equilibrium value for the period under review. as part of antiinflationary monetary policy, methods can be used that are aimed at adapting to inflation rather than attempting to fight against it. these methods include adaptation policy that is implemented through indexation of incomes. the increase in prices caused by inflation inevitably entails a decrease in real household incomes, especially those households who cannot protect themselves from depreciation of money. in this regard, there is a need for full or partial indexation of incomes through the raise in wages of public-sector employees, retirement benefits, cash payments and household savings considering the increase in prices. the indexation itself does not eliminate inflation, but only mitigates pysar and dergacheva: determination of parity price for gas and electricity in terms of estimation of household incomes and energy costs international journal of energy economics and policy | vol 8 • issue 5 • 2018346 its adverse effect, although it can become a formidable inflation factor if implemented in the context of the budget deficit that is financed by money emission. references all-ukrainian information and statistical information of european institutions in the field of natural gas. available from: http://www. nerc.gov.ua/?id=24776.  bahmani-oskooee, m., chang, t., cheng, s.c., wu, t.p. (2015), revisiting purchasing power parity in major oil-exporting countries. macroeconomics and finance in emerging market economies, 8(1-2), 108-116. barrett, c.b., li, j.r. (2002), distinguishing between equilibrium and integration in spatial price analysis. american journal of agricultural economics, 84(2), 292-307. dehnavi, j., wirl, f., yegorov, y. (2015), arbitrage in natural gas markets? international journal of energy and statistics, 3(4), 155018. electricity consumption by industry, transport activities and households/services (gwh). eurostat.  (2017), available from: http://www.ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1& language=en&pcode=ten00094&plugin=1. electricity prices in europe.  (2017), available at: http://www.nerc.gov. ua/?id=19526 european energy market: what is the real price for gas and electricity? (2016), available from: http://www.enref.org/wp-content/ uploads/2016/02/eu-ua_market_study_1.pdf. fan, c.s., wei, x. (2006), the law of one price: evidence from the transitional economy of china, review of economics and statistics, 88(4), 682-697. góes, c., matheson, t.d. (2015), domestic market integration and the law of one price in brazil. working paper no. 15/213. p11. growitsch, c., nepal, r. (2009), efficiency of the german electricity wholesale market. electrical energy systems, 19(4), 553-568. gupta, k. (2016), oil price shocks, competition, and oil and gas stock returns: global evidence. energy economics, 57, 140-153. kulikov, d., pank, e. (2014), law of one price in the euro area: an empirical investigation using nielsen disaggregated price data. p29. available from: http://www.digar.ee/id/nlib-digar:235266. lee, i., park, s.s. (2015), the law of one price revisited: how do goods market frictions generate large and volatile price deviations? mpra paper no. 66470. available from: https://www.mpra.ub.unimuenchen.de/66470. mean and median income by household type. (2017), available from: http://www.appsso.eurostat.ec.europa.eu/nui/show.do?dataset=ilc_ di04&lang=en. nick, s., tischler, b. (2014), the law of one price in global natural gas markets: a threshold cointegration analysis. no 2014-16, ewi working papers. available from: https://www.econpapers.repec.org/ paper/risewikln/2014_5f016.htm. olsen, k.k., mjelde, j.w., bessler, d.a. (2015), price formulation and the law of one price in internationally linked markets: an examination of the natural gas markets in the usa and canada. the annals of regional science, 54(1), 117-142. overview of energy prices for the population in the world’s worst countries; 2016. available from: http://www.edclub.com.ua/ analityka/oglyad-cin-na-energoresursy-dlya-naselennya-v-okremyhkrayinah-svitu-u-2016-roci. provisions on the imposition of special duties on natural gas market actors in order to ensure public interest in the process of functioning of the natural gas market. available from: http://www. zakon3.rada.gov.ua/laws/show/187-2017-%d0%bf. searby, j. (2014), the law of one price market-based analysis. an extract from the asia-pacific arbitration review 2014. available from: https://www.fticonsulting-asia.com/insights/articles/the-lawof-one-price-marketbased-analysis. socio-demographic characteristics of households in ukraine. (2017), state statistics service of ukraine. statistical collection. available from: http://www.ukrstat.gov.ua. . international journal of energy economics and policy | vol 7 • issue 2 • 2017 109 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(2), 109-112. replacing renewable energy in iranian industries using optimal models mohsen jalalimajidi1, s. m. seyedhosseini2* 1department of industrial management, science and research branch, islamic azad university, tehran, iran, 2department of management, science and research branch, islamic azad university, tehran, iran. *email: seyedhosseini@iust.ac.ir abstract in this paper, in order to maximize optimization in iranian industries, an optimal control modeling has been designed, and then optimal paths of replacing fossil fuels by renewable energy over time is plotted in industrial sectors of iran. moreover, a developed optimal control model is presented, and the data used is evaluated. finally, the estimated energy demand in different industrial sectors of iran and the costs of fossil fuel extraction is proposed. keywords: iranian industries, optimization, renewable energy jel classifications: c32, o13, o47 1. introduction energy is an important input for social and economic growth of any country, particularly in industry. the activities within industry and economy are flourishing in each country so the need and demand for energy is consequently increasing. for a long time energy is divided into two categories: renewable and nonrenewable, the latter being exhaustible. it is an essential and emergent need to move toward renewable energy and it is not an easy task to be carried out overnight. it needs to formulate some models able to optimize and use the energy as efficiently as possible. building an energy model will aid to allocate appropriately the widely available renewable energy sources such as solar, wind, bioenergy and small hydropower to see the future energy demand in iran. recently, many models were proposed to meet the need. hence a framework has been developed to examine the renewable energy replacement using optimal control modeling in the industrial sectors of iran. the data are then evaluated to see the result. 2. research methodology chakrvrty et al. (2014) developed a model for determining the optimal path for replacement of fossil fuels with new energies in the energy sector. this model aims at the maximization of social welfare due to the constant supply of fossil fuels. ( ) i i 1 dij(t ) j j i ijrt 1 j ij(t ) ijj 1 j 1 i 1o 0 w max e d d d dt u  = − − = = =      θ θ−       ∑ ∑ ∑∑∫ ∫ (1) ( ) j ij(t ) i ijj 1 d q t u  = = −∑ (2) in the above model i shows the available resources (oil, coal, natural gas and wind and solar energy), j stands for economic sectors (residential, business and public, industry, transportation, agriculture, and electricity) and r represents the discount rate. the inverse demands function for the jth energy, as a control variable, is as follows: i 1 j i ij(t ) i 1 p (t) d d− =   =      ∑ (3) since the process of converting resources (oil, gas, coal, solar and wind energy) is associated with energy dissipation, uij is the ratio of energy delivered to j to the total raw energy contained in a unit of resource i, and is known as the coefficient of performance. the dij is the net energy delivered from the source i to demand j from qij(t) units of the source which is defined as follows: jalalimajidi and seyedhosseini: replacing renewable energy in iranian industries using optimal models international journal of energy economics and policy | vol 7 • issue 2 • 2017110 dij(t) = uijqij(t) (4) q(it) contains estimated and proven reserves of oil, gas and coal, which are considered as a status variable. in the above model, total cost of the conversion and extraction are shown as below: wij = ci + zij (5) in which ci is the final cost of (energy) resource exploitation and zij is the cost of converting energy i according to demand j which equals the sum of operational, repairing and maintenance costs of the equipments used in resource conversion. in this study, it is supposed that renewable energy exploitation cost is zero, but its conversion cost is zb. the continuous-time model with the above infinite time horizon is solved in the frame of optimal control problem. to do this, first the hamiltonian present value for this problem is obtained as follows: ( ) ( ) i ij i 1 d (t ) j j i ij1 j ij ijj 1 j 1 i 10 i j ij(t ) i iji 1 j 1 w h d d d t u d (t) u = − = = − − = = θ θ− − λ ∑ ∑ ∑∑∫ ∑ ∑ (6) λi is scarcity rents variable for energy resources i including (oil, gas and coal). the first condition, which is one of maximum principle conditions, states that the supply of each resource (oil, gas, and coal) is divided by energy demand in different sectors (chatzimouratidis et al, 2008). according to the second condition, the scarcity rent of fossil fuels will be increased through their amounts in the initial period (dessai et al, 2003). the third condition, determines oil, gas, and coal consumption status in different sectors while the forth condition indicates the consumptions status of renewable energy in different parts (coates et al, 2014). in fact, the third condition represents the optimum hostelling condition according to which the average price paid for energy (oil, gas, coal, solar, and wind, etc.) in different parts must exceed the total cost of exploitation, conversion, and fossil fuels scarcity rate in order for that sector to demand fossil fuel (cleland, 2010). the forth condition completes the third one as a transition condition and the moving step from fossil fuel towards renewable energy (martinot et al, 2012). according to this condition, when the average price paid by society in different sectors for energy equals the renewable energy conversion cost, only renewable energy is used, and this results in the reduction of fossil fuels’ demand to zero (fouquet, 2008). in this model, three scarcity variables are mentioned for oil, gas, and coal reserves which, like interest rate, increase consecutively over time. exogenous variable is gross domestic product (gdp) of each year which, using the gdp in base year (y0) and past years gdp growth rate (g) and discounting rate (r), is calculated as follows (energy vortex, 2009): t 1 t 1 y.(1 g) y (1 r) − − + = + (7) to estimate energy demand functions in different sectors, the cobb-douglas functional form was used in this study. e ap y e t k = − α β γ (8) in which e is energy demand in year t, et−k, energy demand in k years ago, γ and a constants, y is income (gdp) in year t, p weighted price of energy carriers in year t, α and β are short term price and income elasticity, and β β γ = −    1 and α α γ = −    1 are long-term income and price elasticity of demands. also in this form, energy demand in each part includes the total demand of (oil, gas, coal, solar, and wind) energy carriers, and the price paid in each part includes the weighted average of paid price in relation to oil, gas, coal, solar, and wind energy. thus, assuming k = 1, the inverse demand function form used in equation model (1) is as follows (knauer et al, 2014).: 1 e p e e( 1) y α θ γ β   =  −  (9) 3. functions of energy demand in different industrials sectors of iran in this part, using dickey-fuller test, the sustainability of demand and cost variables in different industrial sectors of iran is investigated. then, using regression method, the energy demand function in different parts is shown in logarithmic form as follows: ldh = −12.52 − 0.03*lph + 0.47*ly + 0.65*ldh(−1) (−1.74) (0.6) (1.9) (6.1) r2=0.90 dw=1.88 ldp = −17.9 − 0.07*lpp + 0.67*ly + 0.4*ldp (−1) (−2.6) (−1.60) (2.88) (3.89) r2 = 0.75 dw = 1.5 ldi = −7.43 − 0.004*lpi + 0.3*ly + 0.59*ldi(−1) (−1.85) (−1) (2.04) (2.98) r2 = 0.93 dw = 1.82 ldt = −8.54 − 0.002*lpt + 0.33*ly = 0.62*ldt(−1) (−2.18) (−12) (2.26) (3.4) r2 = 0.98 dw = 1.83 lda = −5.63 − 0.11*lpa + 0.34*ly + 0.31*lda(−1) (−0.93) (−2) (1.64) (2.08) r2 = 0.34 dw = 1.93 lde = −8.47 − 0.002*lpe + 0.31*ly + 0.73*lde(−1) (−1.74) (−2) (1.80) (4.99) r2 = 0.98 dw = 1.2 in which ldh, ldp, ldi, ldt, lda and lde respectively stand for energy demand logarithm in different sectors industries, and lph, lpp, lpi, lpt, lpa, and lpe are the logarithm of the paid price for energy in different parts, and ly is the gdp. also ldh−1, ldp−1, ldi−1, ldt−1, lda−1 and lde−1 are energy demand logarithm in (1) production, (2) business and public, (3) small industries, (4) transportation, (5) services, and (6) electricity sectors respectively with an inactivity period. jalalimajidi and seyedhosseini: replacing renewable energy in iranian industries using optimal models international journal of energy economics and policy | vol 7 • issue 2 • 2017 111 the price and income elasticity in different industrials sectors of iran has been calculated using the estimated functions. 3.1. cost functions of oil, gas, and coal exploitation oil production cost is the sum of exploitation, development, and production operational costs. ct is oil production total costs while qot is the amount of oil production. 0.2423 t t tc 1.2(0.46qo 0.7714qo ) −= + (10) functions of gas and coal exploitation costs are respectively as follows: 2 18 3 t t t ttc 63qg 0.0025qg 5.44 10 qg −= − + − (11) 6 2 13 3 t t t ttc 8.9qc 4.99* 10 qc 8.74*10 qc − −= − − + (12) qgt is the amount of natural gas production and qct is the level of coal production (department of energy, 2016). 3.1.1. conversion cost the conversion cost is the total of annual operative and investment costs. for the new energy replacement model, the cost of electricity produced from the conversion of renewable energy, and also the cost of transmitting electricity from power plants to various demand sectors are taken into consideration. the cost of renewable energy as a result the average cost of converting 1 kw/h will be 3800 rail’s (1055 billion rails per pet j). table 1 shows the price and income elasticity in different industrials sectors of iran in 2016. 3.1.2. social welfare cost according to the human development report, the united nations, iran had 1.5% of the global emission of co2 in 2016, and it has 13th rank in releasing carbon dioxide. in this research, by incorporating the social costs resulting from the consumption of fossil fuels in various sectors of the iranian industry, the reduction of social welfare surplus examined. social cost of carbon emissions was 80,000 rail’s per-ton in 2010 that using the price index adjusted to 400,000 rail’s in 2016. 4. replacement of renewable energy instead of fossil energy in different scenarios 4.1. first scenario the results show that with the assumption of constant conversion costs of renewable energy, respectively, public and business sectors after 25 years, transportation sector, after 27 years, the services after 30 years, the power sector after 35 years, production sector after 41 years and small industrials sector after 77 years will change their demand from fossil fuels to renewable energy. 4.2. second scenario assuming a 10% reduction in the cost of renewable energy conversion in every decade, in businesses and public sector after 21 years, in the department of transportation after 23 years, in the services sector after 26 years, in the electricity sector after 30 years, in the production sector after 33 years and in the small industrials sector after 54 years, transition from fossil fuels renewable will take place. according to the second scenario fossil energy demand in different sectors will be zero in 54 years and moving toward renewable energy will be complete. 4.3. third scenario assuming a 30% reduction in the cost of renewable energy conversion in every decade, in public and commercial sector after 18 years, in transportation sector after 20 years, in the services sector after 21 years, in the power sector after 21 years, in the production sector after 25 years and in the small industrials sector after 30 years, transition from fossil fuels to solar and wind power will be done. 4.4. fourth scenario assuming a 50% reduction in the cost of renewable energy conversion, businesses and public sector after 13 years, transportation sector after 16 years, the services sector after 18 years, power sector after 20 years, production sector after 20 years and small industrials sector after 20 years will change their demand from fossil fuels to renewable energy. 5. conclusion this research claims that energy planning processes under sustainable development criteria can maximize the optimization in iranian industries using optimal control models. the analysis of these methodologies and tools is useful to highlight their main advantages and to harness them in the proposal of combined planning methods involving different approaches. findings reveal that estimated energy demand in industrial sectors of iran can be useful for replacement of new energy in future step by step and the programs have to be designed accordingly. references iea (2014), renewable in global energy supply: an iea facts sheet oced. international energy agency, france. knauer, s., fro¨hlingsdorf, m. (2014), renewable energy road map, renewable energies in the 21st century: building a more sustainable future. brussels: commission of the european communities. chatzimouratidis, a.i., pilavachi, p.a. (2008), multicriteria evaluation of power plants impact on the living standard using the analytic hierarchy process. energy conversion and management, 49, 3599-3611. table 1: the price and income elasticity in different industrials sectors of iran sector short-term price elasticity short-term income elasticity long-term price elasticity long-term income elasticity 1 −0.03 0.47 −0.08 1.3 2 −0.07 0.67 −0.11 1.1 3 −0.004 0.2 −0.009 0.48 4 −0.002 0.33 −0.005 0.86 5 −0.11 0.34 −0.15 0.49 6 −0.002 0.31 −0.007 1.1 jalalimajidi and seyedhosseini: replacing renewable energy in iranian industries using optimal models international journal of energy economics and policy | vol 7 • issue 2 • 2017112 department of energy. (2016), available from: http://www.energy.gov/ energy sources.html. dessai, s., lacasta, n.s., vincent, k. (2003), international political history of the kyoto protocol: from the hague to marrakech and beyond. international review for environmental strategies, 4, 183-205. energy vortex-energy dictionary. (2009), base-load energy. available from: http://www.energyvortex.com/energydictionary/ baseload&lowbar;plant.html. fouquet, d., johansson, t.b. (2008), european renewable energy policy at crossroads-focus on electricity support mechanisms. energy policy, 36(11), 4079-4092. martinot, e., dienst, c., weiliang, l., qimin, c. (2012), renewable energy futures: targets, scenarios, and pathways. annual review of environment and resources, 32, 205-239. cleland, d.i., kocaoglu, d.f. (2010), engineering management. new york, ny: mcgraw-hill. coates, j.f., coates,v.t. (2014), next stages in technology assessment topics and tools. technological forecasting and social change, 113, 112-114. tx_1~at/tx_2~at international journal of energy economics and policy | vol 7 • issue 5 • 2017142 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(5), 142-151. do oil industry merger waves reveal any trends? samuel d. barrows* doctorate of business administration candidate 2015-2018, toulouse business school, usa. *email: sam_barrows@yahoo.com abstract the dynamics of the stock prices of oil industry acquirer companies are studied during in-wave and out-wave years between 1998 and 2013. the research question is do oil industry merger waves reveal any trends? this quantitative study focuses on stock returns of acquirer companies over a 4-year horizon for each merger transaction. portfolios created from these transactions provide a comparison between in-wave and out-wave years. three benchmarks are incorporated to provide various economic adjustment factors. six cases are presented whose outcome largely follow other similar studies. the main contribution of the study is the identification of a dynamic during oil industry in-wave years which sees a substantial increase in the brent oil market price, of at least 29% for these in-wave years. this dynamic is not identified previously in the literature. keywords: oil industry mergers, waves, crude oil price, 1998-2013 jel classifications: g15, g34, p18 1. introduction the objective of this study is to explore the stock price performance of oil industry acquirers using various scenarios to determine if any trends can be revealed. one of the market dynamics during the study time frame is the substantial increase in merger transactions during certain years. between 1998 and 2013, using the criteria established in this study, there are 4 years declared as in-wave years as a part of the merger wave dynamic. this study is a quantitative endeavor to explore the acquirer returns relative to the comparative benchmarks for these in-wave years and for the other out-wave years relative to the same benchmarks. the study focus is on the stock price total return performance of acquirer companies over a 4-year horizon for each merger transaction. the first data point in 4-year horizon is the last trading day of the year prior to the transaction in order to provide a price basis before full market expectations. the merger transactions for the acquirers are included in portfolios for in-wave years and out-wave years. portfolios are also created for the benchmarks for the same time periods. this approach utilizes six cases which explore these comparisons and are bulk of the quantitative portion of the study. three hypotheses are included which hone down the discussions to relevant topics for digestion. h1: the brent oil market sees superior returns during in-wave years relative to the benchmark. h2: acquirers see superior returns during in-wave years relative to the global market. h3: acquirers see inferior returns during inwave years relative to the brent oil market. all three hypotheses are confirmed and the study results are consistent with previous established knowledge related to links between merger waves and company performance and between oil price and company performance. a strange dynamic occurs during the oil industry in-wave years which sees a substantial increase in the brent oil market price, of at least 29%, along with a total deal value of $150 billion or more for these in-wave years. this price link is not something found in other literature. it is one of the contributions of this study. the other contributions of the study include confirmation on issues related to merger waves and the link between oil price and oil company performance previously documented. results of studies mostly document lower performance during these in-wave periods (carow, et al., 2004; duchin and schmidt, 2012; haleblian et al., 2012). there are also studies documenting the positive link between oil price and oil company financial performance barrows: do oil industry merger waves reveal any trends? international journal of energy economics and policy | vol 7 • issue 5 • 2017 143 (pirog 2005; baaij et al., 2011; dayanandan and donker, 2011; mohanty et al., 2013). in addition, many of the studies examine mergers and merger wave dynamics (porter, 1980; scharfstein and stein, 1990; chen, 1996; mitchell and mulherin, 1996; rhodeskropf and viswanathan, 2004; bouwman et al., 2009; gorton et al., 2009; maksimovic et al., 2013; doukas and zhang, 2016). 2. literature review during the 1990s, oil companies, hoping to take advantage of rising prices, focus on growth (marko, 2000). other ways of expansion, such as merging with another firm or acquiring a new one may provide an easier route to growth (gorton et al., 2009). these tie-ups can provide a means for continued growth and profitability for the companies (baaij et al., 2011). it is usually quicker and may provide more certain growth (gorton et al., 2009). many of the mergers in the oil industry are horizontal in nature and provide these added economies (maschoff, 1996). mergers are then seen as a valuable mechanism for growth for many oil companies (baaij et al., 2011). these types of industry mergers lead to opportunities to further increase value (gorton et al., 2009). the m&a activity in the oil industry that occur during this time change the breadth and scope for the majority of the major players (baaij et al., 2011). mergers and acquisitions continue to play an important role in shaping business activities, and have become an important business strategy for those companies that focus on growth (gorton et al., 2009). 2.1 merger waves merger transactions tend to group together within various industries (mitchell and mulherin, 1996). this is because merger activity is not a static function and can vary substantially from year to year (rhodes-kropf and viswanathan, 2004). as such, m&a dynamics tend to come in peaks and troughs (haleblian et al., 2012). research confirms that clusters of peak m&a activity exist within industries and these peak time periods are referred to as merger waves (maksimovic et al., 2013). these merger wave time periods see intense activity grouped together within industries (haleblian et al., 2012). there are two common views on the merger wave theory. the first view that is clarified by rhodes-kropf and viswanathan, (2004) is that periods of increased merger activity, also known as waves, are caused by incorrect stock market valuations and these can be both over-valuation and under-valuation, as they both create potential opportunities for exploitation in the merger arena. the second view is that the merger waves are the result of somewhat of a seismic event or shock which impacts the industry or other jolts such as regulatory changes or new financing methods (mitchell and mulherin, 1996). other impact areas can also be included, such as technology implementation or improvements in supply chains, which can create efficiencies which by themselves create value (ahern and harford, 2014). 2.2 in-wave versus out-wave the time during these peak waves is referred to as in-wave while the time outside of these peak periods is referred to as out-wave (duchin and schmidt, 2012). the start of the in-wave periods see large increases in the number of acquisitions (haleblian et al., 2012). there are several views on what constitutes a wave. one study identifies a wave as the 24-month period of highest merger concentration in each decade (harford, 2005). another looks at transactions within an industry that are at least one standard deviation above the study sample mean for the time period under evaluation (maksimovic et al., 2013). still another study looks at the number of mergers that exceed the 95th percentile in a normal distribution over a decade (duchin and schmidt, 2012). regardless of the metrics used, the onset of these in-wave periods is characterized by a large increase in activity (maksimovic et al., 2013). there are studies that quantify the economics of in-wave mergers. one study with a sample size of 9,854 acquisitions from 1980 to 2009 compares transactions after 36 months. it confirms “in-wave acquirers have annualized buy-and-hold abnormal returns that are on average 4.65 to 6.25 percentage point lower than out-wave acquirers” (duchin and schmidt, 2012). another study evaluated 520 acquisitions between 1979 and 1998 and reveals that the in-wave acquirers also tend to underperform the industry. after a 3-year assessment, compared to the value weighted returns for the acquirer’s industry, the mean deficit is 15.71% and the median deficit is 24.43% (carow et al. 2004). 2.3 elective or necessity competition varies within industries (mitchell and mulherin, 1996). rivalry includes more than just sharing markets and access to resources (chen, 1996). companies close in relative size and capability tend to be more competitive with each other and share many of the same beliefs (abrahamson and fombrun, 1994). this impacts the configuration of the industry itself, and the players in that industry (chen, 1996). merger waves do not always happen in-sync across industries, but there is sufficient evidence that m&a activity within an industry is grouped together (mitchell and mulherin, 1996). mergers in response to regulatory, technological, or competitive change in the environment could be deemed as “mergers of necessity” as opposed to “elective mergers” where the participants may feel more freedom not to consummate a merger (duchin and schmidt, 2012). the economics of the “necessity merger” transactions may become of secondary importance (mitchell and mulherin, 1996). making such a merger may become obligatory to stay in the game (duchin and schmidt, 2012). this mentality may exist during the time periods when the corporate strategy may be focused on restructuring and consolidation in order to ensure or solidify a competitive position (mitchell and mulherin, 1996). however, the returns may not be as attractive as a typical “elective merger” (duchin and schmidt, 2012). 2.4 market over-valuation there are two common ingredients in the merger game: the financial markets have ample liquidity and the acquiring company usually has an incorrectly valued stock price (maksimovic et al., 2013). this incorrect valuation is typically an overvaluation and barrows: do oil industry merger waves reveal any trends? international journal of energy economics and policy | vol 7 • issue 5 • 2017144 the in-wave periods are typically characterized by high stock valuations (rhodes-kropf and viswanathan, 2004). because of this, publicly-traded companies are almost twice as likely to participate in m&a activity during in-wave years as opposed to out-wave years since they are able to use their high stock valuations as currency in the merger transactions (maksimovic et al., 2013). acquiring firms tend to use these high stock valuations periods as “acquisition currency” (rhodeskropf and viswanathan, 2004). a study from the mid-1970s to 2004 of 40,000 companies confirms that merger waves typically occur during times of high liquidity and high market valuations (maksimovic et al., 2013). even if the stock is not used as currency, other methods of financing are available if the company has a strong stock valuation and a good reputation (fombrun and shanley, 1990). this allows good access to both capital markets and debt markets (haleblian et al., 2012). this cheap money is an advantage that not all companies enjoy. however, there is a potential downfall to acquiring during high stock valuations, namely potentially lower long-term performance (bouwman et al., 2009). 2.5 merger strategy identifying potential targets is a key part of an overall strategy to deal with industry competitors (porter, 1980). focusing on employee capabilities is of upmost importance including developing professional skillsets related to strategic planning, business analysis, and human resources (grant, 2003). there is a straightforward methodology with regard to broad m&a activities, which is referred to by the acronym of amc. this stands for “awareness, motivation, and capability” (chen, 1996). as these skills are developed, employee confidence increases and may allow staff to move forward on m&a activities (grant, 2003). before merger schemes are envisioned, a strategic analysis of competitors may provide a guide on how to position a company within the industry (subramanian and ishak, 1998). focusing on the overall strategic vision for a company with regard to its placing among the industry competitors and the steps to implement this vision is paramount (porter, 1980). depending on the timing, it may be prudent not to undertake a specific merger if suboptimal market factors exist (haleblian et al., 2012). this awareness may also allow management the ability to reflect on the current situation and possibly wait until more suitable merger candidates arise (porter, 1980). 2.6 early movers or late comers companies likely to move early in a merger wave possess market awareness and often have concerns about their rival’s actions (haleblian et al., 2012). typically, it is the smaller companies that move early as they may become a target themselves (aldrich and auster, 1986). some of these mergers can be defensive where the acquirer looks to pre-empt being a target by moving first (gorton et al., 2009). there is usually a first-mover advantage in the merger game as the early movers usually outperform those who wait (carow et al., 2004). normally it is the smaller and more nimble companies that are seen to move early since they are more likely to be focused on innovating with new technologies or experimenting with new opportunities (haleblian et al., 2012). moving first may be beneficial, but what about waiting? late comers to the merger game may over-pay for synergies since assets could be over-valued during later stages (haleblian et al., 2012). these late comers typically include the larger, more diversified firms that are more complex with bureaucratic processes which may protect them from competitive pressures (march, 1981). being overly bureaucratic might limit the awareness of opportunities and may provide insulation against motivating factors to making acquisitions (haleblian et al., 2012). these late comers may still get in the game, but by then the synergies identified in a potential deal may have been bid up compared to earlier deals (doukas and zhang, 2016). 2.7 herding the acquirers who are late to the game usually see returns that are less than the returns of the early movers (doukas and zhang, 2016). those who join the merger game later may be participating in an activity called “managerial herding” (bouwman et al., 2009). this herding or sharing the blame with other managers is one potential reason for the number of increased transactions during the merger waves (scharfstein and stein, 1990). value-maximizing managers often rely on information from the early-movers, and this information loop continues until it is obvious that the results of these late-movers are inferior to that of the early-movers (persons and warther 1997). managers who move late in this herding process may be able to share the blame for these mergers since their behavior is conforming to their peers (bouwman et al., 2009). studies have shown that in-wave managers are less likely to be terminated following a bad merger compared to out-wave managers (duchin and schmidt, 2012). this is because management can share the blame with their in-wave peers (scharfstein and stein, 1990). there is a common thread in the research that in-wave governance is not as strong as out-wave governance (duchin and schmidt, 2012). 2.8 merger governance there is not widespread agreement that company performance improves with an independent board (bhagat and black, 1999). however, at least one study confirms that independent directors see higher returns related to mergers (byrd and hickman, 1992). there is also evidence that block ownership, where an institution owns at least 5% of the shares is a moderating influence and may lead to fewer mergers that are conducted during the in-wave periods (duchin and schmidt, 2012). implementing proper strategies in order to steer the company through the various competitive battles to achieve long-term stability is becoming ever more important as competition in most industries is becoming more aggressive as companies vie for larger markets (chen, 1996). mergers can be a way forward to if they fit with the overall corporate strategy (rani et al., 2013). barrows: do oil industry merger waves reveal any trends? international journal of energy economics and policy | vol 7 • issue 5 • 2017 145 developing staff capabilities in order to become more effective in implementing corporate strategy will help when playing the merger game (grant, 2003). however, perhaps the most import issue is governance because while the other items contribute to a successful business, governance ensures that the enterprise is on the right track and that proper incentives exist to keep it there (rani et al., 2013). 2.9 oil price link to performance with regard to the connection between crude oil prices and the financial performance of oil companies, there is widespread agreement that the two are connected (pirog 2005; baaij et al., 2011; dayanandan and donker, 2011; mohanty et al., 2013). using general accounting measures for comparison, oil prices are positively related to the financial performance of oil and gas companies (dayanandan and donker, 2011). oil prices impact both a company’s revenue and its profitability (baaij et al., 2011). the profitability of oil companies increases as a result of an increase in oil prices (pirog 2005). hence, there is an oil price risk exposure for oil and gas companies (mohanty et al., 2013). this price risk exposure may not be the same for all companies. “larger oil and gas firms are likely to have lower oil price risk exposures (oil beta) than smaller firms” and oil and gas players deemed with higher growth opportunities are also likely to have less oil beta than other players (mohanty et al., 2013). the measure of systemic risk for a company in relation to general stock market moves is known as market beta (fombrun and shanley, 1990). a profitable player is also normally seen to have lower market risk (market beta), hence, an oil and gas player’s profitability is negatively related to its beta, both for oil and the market (mohanty et al., 2013). mohanty et al., (2013) illustrate the volatility of changing oil prices and the effect on company returns confirming this dynamic by looking at crude oil prices between january 1986 and july 2008. they compute cumulative abnormal returns (car) over a two-day period for both positive changes and negative changes if the daily crude oil price changes are >5%. the study identifies 102 negative moves and 78 positive moves meeting this criteria. based on this, they find that the car readings are higher for the negative changes as compared to the positive changes. negative changes have cars of -1.56% at the company level while at the portfolio level they are -1.46%. positive changes have cars of 0.98% at the company level while at the portfolio level they are 1.02%. an average of the two levels sees a 51% increase for the negative changes as compared to the positive changes (mohanty et al., 2013). 3. methodology the methodology to collect and evaluate the data is based on an empirical and analytic approach. this type of research is focused on using objective knowledge acquired from deductive reasoning using the collection of objective data from independent third-party providers and utilizing quantitative methods. the data providers include the following: thomson reuters, dartmouth college, and the us energy information administration, known as the eia. 3.1 data acquisition the screening of data through the thomson reuters product called eikon provides data on all transactions for public, private and government transactions in the world market place and selection begins from the masrch application in the eikon product (thomson reuters, 2017). transactions are selected from 1998 through 2013. only publicly-traded, commercial m&a transactions which represent over 50% ownership of the target companies in the oil & gas and petrochemicals industries are chosen where each of those transactions exceeds $300 million. private and government transactions are excluded, as are stock buybacks and exchange offers. for more information on the selection of records for the data set, please see table a1 in the appendix. in order to provide a more complete picture of the stock total return dynamics, the first data point in the 4-year horizon is the price on december 31 or the last trading day for the year, the year before the transaction date. this provides a price before the market expectations of the m&a activity are fully digested. monthly prices are then aggregated until the final price in the 4-year horizon is taken 4 years after the initial december 31 date. this is done for each transaction, and included into calendar time portfolios which include monthly returns for all applicable transactions active in the portfolio during that month. similar portfolios are also created for the comparative benchmarks: the crsp global market, the crsp oil industry (of 49 industries), and the brent oil market price (dartmouth, 2017; eia, 2017). the benchmarks along with the portfolios exclude the risk free rate, which is the us one month treasury-bill rate. in the analysis using the total return formula, monthly price changes are measured and compared against the comparative benchmarks in the cases. how the groups perform against the benchmarks is key. are they more volatile or less volatile than the market? this is called beta. 3.2 in-wave calculations there are various methods for calculating in-wave periods. for the purposes of this study, the annual number of deals, the total deals in usd, and average deal size in usd are the selection criteria. if the average of these measurements are one standard deviation above the mean for these items, the years are in-wave. no time restrictions are placed on the selection criteria and the time frame used in the evaluation is from 1990 through 2013. the wider time frame and less restrictive parameters allow for a more realistic gauge of activity. using this criteria, there are 4 years of in-wave activity: 1999, 2000, 2005, and 2010. for more information, please see table a2 for the in-wave criteria and calculations in the appendix. please see figure 1 below using data from thomson reuters (thomson reuters, 2017). 3.3 oil price link to merger waves some studies suggest a strong relationship between the oil price and company share performance in the oil industry (pirog 2005; baaij et al., 2011; dayanandan and donker, 2011; mohanty et al., 2013). but the oil price does not only impact the performance of the barrows: do oil industry merger waves reveal any trends? international journal of energy economics and policy | vol 7 • issue 5 • 2017146 oil companies, according to a direct quote from one study on the oil industry from 1930 to 1990, “changing prices also influenced industry consolidation” (ollinger, 1994). the following graph illustrates this phenomenon. total deals in the oil industry as measured in usd billions is displayed along with the annual price changes in the brent oil market. for more information, please see table a3 oil industry mergers and brent oil price: 1990-2013 in the appendix. please see figure 2 below using data from thomson reuters and eia (thomson reuters, 2017; eia, 2017). there are 4 years in which the total deals in the oil industry meet or exceed $150 billion. those are: $150 billion in 1999, $151 billion in 2000, $197 billion in 2005, and $160 billion in 2010. in each of these years, the change in the brent oil market price from the previous year exceeds 29%. those include: 40% in 1999, 60% in 2000, 42% in 2005, and 29% in 2010. there are other years which have similar upward movements in oil prices, specifically 30% in 1990, 32% in 2004, 34% in 2008, and 40% in 2011. however, there are no other years with total deals at $150 billion or above which has oil price movements <29%. it is interesting to note that these 4 years are the same 4 years identified as in-wave years in section 3.2. that there is a potential link between a substantial rise in oil prices and merger waves in the oil industry is a new connection not previously identified in previous research. 3.4 analytical cases the research question is: do oil industry merger waves reveal any trends? the objective of this study is to evaluate the performance of the acquirers to the comparative benchmarks and assess if certain dynamics or trends are revealed which may give broader meanings. the stock price total return of the acquirers is the dependent variable in this analysis. the independent variable is if the time period is in-wave or out-wave along with the comparative benchmarks. the research is classified as causal and correlational. the intent is to establish a causal connection and quantify the relationship of the stock price total return performance of the acquirers to the merger wave dynamics and to quantify the relationship of oil price movements to these same wave years. to further explore this topic and focus on quantifying the research question, three hypotheses are considered. • h1: the brent oil market sees superior returns during in-wave years relative to the benchmark. • h2: acquirers see superior returns during in-wave years relative to the global market. • h3: acquirers see inferior returns during in-wave years relative to the brent oil market. figure 1: oil industry mergers 1990-2013 figure 2: oil industry mergers and brent oil price: 1990-2013 barrows: do oil industry merger waves reveal any trends? international journal of energy economics and policy | vol 7 • issue 5 • 2017 147 the research approach matches the monthly portfolio to one other factor and is a two-factor version of the three-factor model of fama and french (1993). this method adheres with the strategy that long-run abnormal returns should be calculated as the longrun return of a sample less the long-run return of an appropriate benchmark (barber and lyon, 1997). the first formula is a brent oil market comparison to a steady 1% per month stream. the second formula is an acquirer comparison to the global market. the third formula is an acquirer comparison to the brent oil market. rf rate represents the risk free rate. brent oil market return−rf rate = α + β (1% per month) acquirers return−rf rate = α + β (global market−rf rate) acquirers return−rf rate = α+ β (brent oil market−rf rate the analytic approach utilizes six cases which examine the stock price total return monthly percent changes. the first set of two cases compares the brent oil market to a steady 1% per month stream. the next set of two cases compares the acquirers against the global market. the third set of two cases compares the acquirers against the brent oil market. all sets compare the in-wave and out-wave returns based on comparative benchmarks, and subtracts the risk free rate from all variables except from the steady 1% per month stream. the cases provide the means to gauge the acquirer performance relative to the benchmarks during the in-wave and out-wave years. the expectation is that the in-wave performance is inferior to the out-wave performance for the acquirers. however, if the oil price performance is superior during the in-wave years, the influence that the oil price has on oil company performance has the potential to override the in-wave influence on the oil company performance. for more information, please see the table 1. 4. results a summary of the results of the cases analyzed are included in table 2 below. the alpha readings in four of the cases are negative while only two are positive. the detailed comparisons are discussed in table 2. in case 1, the brent oil market in-wave performance is superior to the comparative benchmark at a 0.01 level, while in case 2, the brent oil market out-wave performance is inferior to the comparative benchmark at a 0.01 level. these results confirm superior performance during the in-wave periods. in case 3, the acquirers’ in-wave performance is superior to the global market at a 0.01 level, while in case 4, the acquirers’ outwave performance is inferior to the global market at a 0.01 level. when comparing both results, acquirers’ performance relative to the global market is superior during the in-wave periods. in case 5, the acquirers’ in-wave performance is inferior to the brent oil market at a 0.10 level. in case 6 the acquirers’ out-wave performance is also inferior to the brent oil market, but at a 0.01 level. however, the alpha reading in case 6 is higher than the alpha reading in case 5 suggesting a relatively better performance during out-wave periods. this implies that the acquirers are not able to capture the gains seen in the brent oil market during the in-wave periods. cases 1 and 2 display adjusted r2 readings of 0.61 and 0.57, respectively. these two readings confirm similar relationships between the two variables during both in-wave and out-wave periods. the moderate correlation to a steady 1% per month stream is interesting and suggests a general oil price increase during both the in-wave and out-wave periods which is the case. cases 3 and 4 for the acquirers and the global market have adjusted r2 readings of (0.01) and 0.61, respectively. the in-wave measurement of (0.01) shows virtually no correlation between the dependent and independent variables, while the out-wave measurement of 0.61 shows a moderate correlation between the dependent and independent variables. cases 5 and 6 for the acquirers and the brent oil market have adjusted r2 readings of 0.55 and 0.83, respectively. case 5 shows a moderate correlation between the variables. case 6 documents a stronger correlation between the variables and shows more of a relationship that would normally be expected between the acquirers and the brent oil market as many studies document the positive connection between crude oil prices and oil company financial performance (pirog 2005; baaij et al., 2011; dayanandan and donker, 2011; mohanty et al., 2013). on the subject of hypothesis testing, five out of the six cases have alpha readings at the 0.01 level with one out of the six cases with an alpha reading at the 0.10 level. this level of certainty confirms that for the purpose of hypothesis testing, the measurements associated with these readings are statistically significant. with regard to the first hypothesis considered, h1: the brent oil market sees superior returns during in-wave years relative to the benchmark, the regressions confirm at a 0.01 level that the brent oil market sees superior returns during in-wave years in comparison to the benchmark. during out-wave years, brent oil prices see inferior returns in comparison to the benchmark, also at a 0.01 table 1: analytical case results analytical cases: all cases minus the risk free rate global market brent oil market 1% per month in-wave years: brent oil market with 1% per month x out-wave years: brent oil market with 1% per month x in-wave years: acquirers with the global market x out-wave years: acquirers with the global market x in-wave years: acquirers with the brent oil market x out-wave years: acquirers with the brent oil market x barrows: do oil industry merger waves reveal any trends? international journal of energy economics and policy | vol 7 • issue 5 • 2017148 level. these results confirm the h1 null hypothesis. using the selected benchmark as a comparison, the brent oil market sees superior returns during in-wave years. the h1 results are further confirmation of the discussion in section 3.3 of the link between oil industry in-wave years and a substantial rise in the crude oil price. the oil industry in-wave years appear to be correlated with a substantial rise, at least 29%, in the brent oil market price. with regard to the second hypothesis considered, h2: the acquirers see superior returns during in-wave years relative to the global market, the regressions confirm at a 0.01 level that the acquirers during in-wave years see superior returns in comparison to the global market. during out-wave years, the acquirers perform inferior to the global market at a 0.01 level. these results confirm the h2 null hypothesis. using the selected benchmark as a comparison, the acquirers see superior returns during in-wave years. the h2 results show that during the study time frame the acquirers are able to take, to some extent, advantage of the rise in oil prices during the in-wave periods. these results confirm other studies which show a positive link between oil price and oil company performance, in terms of both revenue and profitability (baaij et al., 2011), of sole profitability (pirog 2005), and of stock performance (dayanandan and donker, 2011; mohanty et al., 2013). with regard to the third hypothesis considered, h3: the acquirers see inferior returns during in-wave years relative to the brent oil market, the regressions confirm at a 0.10 level that the acquirers during in-wave years see inferior returns in comparison to the brent oil market. during out-wave years, the acquirers also perform inferior to the benchmark at a 0.01 level, but less inferior in relation to the in-wave years. these results confirm the h3 null hypothesis. using the selected benchmark as a comparison, the acquirers see inferior returns during in-wave years. the h3 results are in line with other studies that document inferior performance during merger waves. despite single company variations, it is clear that in-wave mergers perform worse than out-wave mergers (duchin and schmidt, 2012). in-wave acquirers underperform the industry (carow et al., 2004). the in-wave time frame is associated with late-comers and these players may over pay for synergies (haleblian et al., 2012). the research question for this study is: do oil industry merger waves reveal any trends? based on the research methods in this study and the significance of the resultant differences in measurements, a confirmation of the hypothesis is warranted. there are three trends reported in this study: 1. h1: establishes that the link between oil industry in-wave years and a substantial rise in crude oil price is a new trend not previously identified in the research. in conjunction, a substantial rise in oil price, of at least 29% in concert with a jump in the total annual value of deals to at least $150 billion, would signal an in-wave period appears to be a new concept. 2. h2: confirms that the continued trend that a rise in oil price may lead to an improvement in oil company financial performance, in line with other studies (pirog 2005; baaij et al., 2011; dayanandan and donker, 2011; mohanty et al., 2013). 3. h3: confirms that despite the increase in crude oil price, the acquirers perform inferior during the in-wave years when compared to the brent oil market. this is confirmation of a trend where in-wave returns are inferior to out-wave returns as established by other studies (carow, et al., 2004; duchin and schmidt, 2012; haleblian, et al., 2012). 5. conclusions the intent of this study is to identify trends related to oil industry merger waves. in the study, there are four declared in-wave years using the criteria established in this study. one link to the wave periods which is not identified prior to this study is that the in-wave years appear to be coordinated with a substantial rise in oil price, of at least 29%. this phenomenon appears to coincide with the rise of other factors normally associated with in-wave years such as an increase in the number and size of deals (harford, 2005; haleblian et al., 2012; duchin and schmidt, 2012; maksimovic et al., 2013). that there is a potential link between a substantial rise in oil prices and merger waves in the oil industry is a new connection not previously identified in the research and is one of the contributions of this study. studies have already linked a rise in oil price to improved financial performance for oil companies (pirog 2005; baaij et al., 2011; dayanandan and donker, 2011; mohanty et al., 2013). however, when the oil company performance improvement does not match the improvement in oil price then the oil company performance may be viewed as inferior, at least relative to the oil price movement. when it is also linked to merger wave dynamics, the inferior outcome may be viewed as being caused by the wave dynamics as documented by other studies (carow et al., 2004; duchin and schmidt, 2012; haleblian et al., 2012). this may not be entirely true. further research may be needed. references abrahamson, e., fombrun, c. (1994), macro cultures: determinants and consequences. academy of management review, 19(4), 728-755. ahern, k., harford, j. (2014), the importance of industry links in merger table 2: summary of the results of the cases regression statistics table alpha (y intercept) t-statistic beta one adjusted r2 in-wave years: brent oil market with 1% per month 0.67*** 6.98 2.95*** 0.61 out-wave years: brent oil market with 1% per month (0.39)*** (9.38) 0.69*** 0.57 in-wave years: acquirers with the global market 1.26*** 5.83 1.04 (0.01) out-wave years: acquirers with the global market (0.24)*** (12.83) 1.16*** 0.61 in-wave years: acquirers with the brent oil market (0.48)* (1.86) 1.32*** 0.55 out-wave years: acquirers with the brent oil market (0.19)*** (16.89) 0.76*** 0.83 *10%,**5%,***1% denote significance levels barrows: do oil industry merger waves reveal any trends? international journal of energy economics and policy | vol 7 • issue 5 • 2017 149 waves. the journal of finance, 69(2), 527-576. aldrich, h., auster, e. (1986), even dwarfs started small: liabilities of age and size and their strategic implications. research in organizational behavior, 8, 165-198. baaij, m., de jong, a., dalen, j. (2011), the dynamics of superior performance among the largest firms in the global oil industry, 19542008. industrial and corporate change, 20(3), 789-824. barber, b., lyon, j. (1997), detecting long-run abnormal stock returns: the empirical power and specification of test statistics. journal of financial economics, 43, 341-372. bhagat, s., black, b. (1999), the uncertain relationship between board composition and firm performance. the business lawyer, 54(3), 921-963. bouwman, c., fuller, k., nain, a. (2009), market valuation and acquisition quality: empirical evidence. review of financial studies, 22(2), 633-679. byrd, j., hickman, k. (1992), do outside directors monitor managers? evidence from tender offer bids. journal of financial economics, 32(2), 195-221. carow, k., heron, r., saxton, t. (2004), do early birds get the returns? an empirical investigation of early-mover advantages in acquisitions. strategic management journal, 25(6), 563-585. chen, m. (1996), competitor analysis and interfere rivalry: toward a theoretical integration. academy of management review, 21(1), 100-134. dartmouth. (2017), changes in crsp data. available from: available from: http://www.mba.tuck.dartmouth.edu/pages/faculty/ ken.french/data_library.html#research. [last accessed on 2017 feb 02]. dayanandan, a., donker, h. (2011), oil prices and accounting profits of oil and gas companies. international review of financial analysis, 20(5), 252-257. doukas, j., zhang, w. (2016), envy-motivated merger waves. european financial management, 22(1), 63-119. duchin, r., schmidt, b. (2012), riding the merger wave: uncertainty reduced monitoring, and bad acquisitions. journal of financial economics, 107(1), 69-88. eia. (2017), energy information administration. washington, d.c., brent: u.s. department of energy. available from: http://www.eia. gov/dnav/pet/hist/leafhandler.ashx?n=pet&s=rbrte&f=d. [last accessed on 2017 jan 13]. fama, e., french, k. (1993), common risk factors in returns on stocks and bonds. journal of financial economics, 33, 3-56. fombrun, c., shanley, m. (1990), what’s in a name? reputation building and corporate strategy. academy of management journal, 33(2), 233-258. gorton, g., kahl, m., rosen, r. (2009), eat or be eaten: a theory of mergers and firm size. the journal of finance, 64(3), 1291-1344. grant, r.m. (2003), strategic planning in a turbulent environment: evidence from the oil majors. strategic management journal, 24, 491-517. haleblian, j., mcnamara, g., kolev, k., dykes, b. (2012), exploring firm characteristics that differentiate leaders from followers in industry merger waves: a competitive dynamics perspective. strategic management journal, 33, 1037-1052. harford, j. (2005), what drives merger waves? journal of financial economics, 77(3), 529-560. maksimovic, v., phillips, g., yang, l. (2013), private and public merger waves. the journal of finance, 68, 2177-2217. march, j. (1981), decision making perspective-decisions in organizations and theories of choice. in: van, v.a.h., joyce, w.f., editors. perspectives on organization design and behavior. new york: wiley. p205-248. marko, w.a. (2000), upstream companies balancing as and oil portfolios equally. natural gas, 17(1), 2-8. maschoff, d.c. (1996), energy industry mergers and acquisitionsstrategic issues for gas companies. natural gas, 12(8), 2-6. mitchell, m., mulherin, j. (1996), the impact of industry shocks on takeover and restructuring activity. journal of financial economics, 41(2), 193-229. mohanty, s., akhigbe, a., al-khyal, t., bugshan, t. (2013), oil and stock market activity when prices go up and down: the case of the oil and gas industry. review of quantitative finance and accounting, 41(2), 253-272. ollinger, m. (1994), the limits of growth of the multidivisional firm: a case study of the u.s. oil industry from 1930-1990. strategic management journal, 15, 503-520. persons, j., warther, v. (1997), boom and bust patterns in the adoption of financial innovations. review of financial studies, 10, 939-967. pirog, r. (2005), world oil demand and its effects on oil prices, crs report for congress, congressional research service, the library of congress, no: rl32530. porter, m. (1980), competitive strategy: techniques for analyzing industries and competitors. new york: free press. rani, n., yadav, s., jain, p. (2013), impact of corporate governance on short-term performance of mergers and acquisitions. amity global business review, 8, 43-54. rhodes-kropf, m., viswanathan, s. (2004), market valuation and merger waves. journal of finance, 59(6), 2685-2718. scharfstein, d., stein, j. (1990), herd behavior and investment. american economic review, 80, 465-479. subramanian, r., ishak, s. (1998), competitor analysis practices of us companies: an empirical investigation. management international review, 30(10), 7-23. thomson reuters. (2017), thomson reuters eikon product. available from: http://www.thomsonreuters.com/en/products-services/ financial/trading-platforms/thomson-reuters-eikon.html. [last accessed on 2017 mar 13]. http://www.eia.gov/dnav/pet/hist/leafhandler.ashx?n=pet&s=rbrte&f=d http://www.eia.gov/dnav/pet/hist/leafhandler.ashx?n=pet&s=rbrte&f=d http://thomsonreuters.com/ http://www.en/products-services/financial/trading-platforms/thomson-reuters-eikon.html http://www.en/products-services/financial/trading-platforms/thomson-reuters-eikon.html barrows: do oil industry merger waves reveal any trends? international journal of energy economics and policy | vol 7 • issue 5 • 2017150 appendix appendix tables table 1a: selection of records for the data set selection criteria records initial data set from thomson reuters eikon: masrch application for advanced search of mergers and acquisitions >1,000,000 select “completed” in the deal status field >750,000 select date effective between “01-jan-1998 and 01-jan-2014” >500,000 select “oil & gas” and “petrochemicals” in the target industry field >18,000 select “oil & gas” and “petrochemicals” in the acquirer industry field >11,000 select “public. subsidiary. joint venture” in the target public status field >6,900 select “acquisition of assets. acquisition of partial interest. merger. acquisition of majority assets. acquisition of remaining interest. acquisition of certain assets” in transaction field >6,700 select “over 50%” in the % acquired field >4,400 select “over 300 m ($300 million)” in the deal size field 672 select non-blank entries in the acquirer ric field 459 eliminate records with missing acquirer size information 409 eliminate records which generate null or #n/a values when using the total return query 401 eliminate records with same acquirer ric within the same calendar year 364 table 2a: in-wave criteria and calculations year count total amount average deal size count mean+1 standard deviation total amount mean+1 standard deviation average size mean+1 standard deviation % of wave limit in-wave 1990 92 9,698 105 201 135,631 761 22 1991 113 24,696 219 201 135,631 761 34 1992 100 9,394 94 201 135,631 761 23 1993 140 7,709 55 201 135,631 761 28 1994 116 11,078 96 201 135,631 761 26 1995 144 15,234 106 201 135,631 761 32 1996 186 27,232 146 201 135,631 761 44 1997 181 33,790 187 201 135,631 761 47 1998 168 106,783 636 201 135,631 761 82 1999 157 150,120 956 201 135,631 761 105 yes 2000 143 150,555 1,053 201 135,631 761 107 yes 2001 169 140,379 831 201 135,631 761 99 2002 144 68,789 478 201 135,631 761 62 2003 118 46,097 391 201 135,631 761 48 2004 170 41,637 245 201 135,631 761 49 2005 195 196,753 1,009 201 135,631 761 125 yes 2006 184 131,817 716 201 135,631 761 94 2007 212 102,396 483 201 135,631 761 82 2008 217 84,422 389 201 135,631 761 74 2009 182 67,767 372 201 135,631 761 63 2010 219 159,530 728 201 135,631 761 107 yes 2011 187 80,143 429 201 135,631 761 70 2012 215 136,535 635 201 135,631 761 97 2013 170 77,253 454 201 135,631 761 67 barrows: do oil industry merger waves reveal any trends? international journal of energy economics and policy | vol 7 • issue 5 • 2017 151 table 3a: oil industry mergers and brent oil price: 1990-2013 year total deals (usd billion) brent (usd) brent (% gain from 1989 18,25 previous year) 1990 9,70 23,68 30 1991 24,70 20,01 −15 1992 9,39 19,31 −4 1993 7,71 17,04 −12 1994 11,08 15,84 −7 1995 15,23 17,04 8 1996 27,23 20,64 21 1997 33,79 19,12 −7 1998 106,78 12,78 −33 1999 >>150,12<< 17,85 >>40<< 2000 >>150,56<< 28,52 >>60<< 2001 140,38 24,45 −14 2002 68,79 24,96 2 2003 46,10 28,88 16 2004 41,64 38,23 32 2005 >>196,75<< 54,42 >>42<< 2006 131,82 65,15 20 2007 102,40 72,47 11 2008 84,42 96,85 34 2009 67,77 61,49 −37 2010 >>159,53<< 79,51 >>29<< 2011 80,14 111,26 40 2012 136,54 111,65 0 2013 77,25 108,64 −3 tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 3 • 2023334 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(3), 334-341. aspects to consider in the evaluation of photovoltaic system projects to avoid problems in power systems and electric motors narciso castro charris1, vladimir sousa santos1*, juan josé cabello eras2 1department of energy, universidad de la costa, barranquilla, colombia, 2department of mechanical engineering, faculty of engineering, universidad de córdoba, monteria, colombia. *email: vsousa1@cuc.edu.co received: 22 january 2023 accepted: 24 april 2023 doi: https://doi.org/10.32479/ijeep.14265 abstract this paper analyzes the problems in electrical power systems with high penetration of photovoltaic systems, which must be considered in evaluating new projects with these generation sources. the study analyzes the characteristics of photovoltaic systems, their generated effects, and proposals for technological improvements. the features of electric motors and their affectation when they are fed from networks with power quality problems are also described. as a result, the variability in energy production, the difficulties in frequency regulation, the increase in harmonics, and the instability in generating reactive power, are the main problems caused by the massive use of photovoltaic systems. regarding electric motors, it is shown that harmonics and voltage regulation are the power quality problems that most affect their operation. none of the studies conducted analyzes the direct influence that photovoltaic systems can have on the process of electric motors. considering the growth prospects for using photovoltaic systems and the importance of electric motors, it is suggested that the scientific community develop research focused on this problem. keywords: electric motors, electrical systems, photovoltaic systems, power quality, project evaluation jel classifications: q2, q4 1. introduction in recent years, the use of renewable energy sources (res) has increased as one of the main strategies for compliance with the paris 2015 agreement. this agreement aims to reduce greenhouse gas emissions and combat their effects on climate change (unfccc, 2015). from 1990 to the present, res has had an average annual growth of 2% within the global energy supply. figure 1 shows the most significant increase in using photovoltaic solar energy at 37.3% and wind power at 23.6%. the other energy source with significant growth is biogas at 12.3%, solar thermal at 11.5%, and liquid biofuels at 10% (iea, 2018). the generation of electricity has had an annual growth of 2.9% since 1990. in this same period, generating electricity using res has grown slightly, with 3.7%. res is the second largest contributor to electricity production, with 23.8%, behind coal, representing 39.2%. the other contributors to generating electrical energy, as shown in figure 2, are gas at 23.6%, nuclear energy at 10.6%, and oil at 3.8% (iea, 2018). in colombia, as shown in figure 3, the electric power generation matrix comprises 78% hydroelectric plants, 10% thermoelectric plants that operate with gas and coal, respectively, and 8% with other energy sources (ministerio minas y energia and upme, 2016). although clean energy generation predominates in colombia, there are risks to energy security due to the possible absence of rain, which has led to the projection of the diversification of the matrix with non-conventional res (fernc), mainly from photovoltaic generation (upme, 2015). based on the regulatory framework of law 1715 of 2014 (congreso de colombia, 2014) and resolution 030 of 2018 this journal is licensed under a creative commons attribution 4.0 international license charris, et al.: aspects to consider in the evaluation of photovoltaic system projects to avoid problems in power systems and electric motors international journal of energy economics and policy | vol 13 • issue 3 • 2023 335 (ministerio de minas y energía, 2018) and research that demonstrates the energy potential of fernc, it is expected that the development of electricity generation from alternative sources will be promoted in colombia. the expectations of growth in the penetration of fernc, specifically of photovoltaic systems (ps), although it is a good alternative for the current energy and environmental scenario, imply new challenges for the operation of the electrical system. among the challenges implied by the widespread use of fernc, particularly ps, are the variability of energy availability and production depending on weather behavior (rönnberg and bollen, 2016), the bi-directionality of energy transfer (azzouz et al., 2017), frequency regulation (ye et al., 2019), design and selection of protection schemes (brahma and girgis, 2004), deterioration in power quality (liang and andalibbin-karim, 2018), and instability of reactive power generation (sarkar et al., 2018). on the other hand, among the primary energy consumers of the electrical system are electric motors (em). these loads are estimated to consume between 43 and 46% globally and between 60 and 70% in the industrial sector (gómez et al., 2022). em, since their invention, have been designed to operate with balanced sinusoidal voltages close to their nominal value; therefore, any deviation from this condition affects their operation, increasing losses and reducing energy efficiency (sousa santos et al., 2019). the studies presented by (rocha et al., 2022) and (rocha et al., 2022) show that in colombia, there is great energy potential from generation from photovoltaic systems and present the challenges that the country would have for the massive implementation of this source of energy. although these studies evaluate regulatory, social, economic, and technological aspects that must be considered in evaluating this type of project, they do not consider the affectations that may occur in the electrical power system and in electric motors due to quality problems of energy. considering the growth prospects of electric power generation from ps and the importance of em as one of the primary consumers, this article analyzes the challenges that generation with ps implies for the operation of electrical systems and of the em. the paper analyzes the characteristics of the ps, the problems associated with intensive generation from these systems, and proposals for technological improvements developed. in addition, the features of the em and their affectation when they are fed from networks with power quality problems are described. as a result of this study, it is proposed that these aspects be considered in developing new generation projects with photovoltaic systems, specifically in colombia. 2. sf characteristics as shown in figure 4, the ps mainly comprises solar panels, regulators, converters, and batteries that can be complemented with control systems to improve efficiency (mohanty et al., 2016). the photovoltaic solar cell (psc) is the base element of the sf. this device works from the photoelectric effect that occurs in semiconductor materials when energy is transferred from the photon of sunlight to the free electrons of the semiconductors. the number of electrons that can move and generate energy in semiconductors depends on several factors, such as temperature, composition, electric field, and magnetic field (pierret, 1983). the main characteristic of the psc for its application is the currentvoltage (iv) characteristic curve under lighting conditions. within this curve, the most critical parameters are the short circuit current, the open circuit voltage, the current and voltage of the maximum power point, and the form factor or fill factor. the efficiency of the psc has been improved through several parallel layers that allow better capture of photons, prevent light from being reflected, and guide it to penetrate inside the cell. with this alternative, recombination is also avoided, the series resistance figure 2: contribution of energy sources to electricity generation figure 1: annual growth of energy supply from res figure 3: contribution of energy sources to electricity generation in colombia charris, et al.: aspects to consider in the evaluation of photovoltaic system projects to avoid problems in power systems and electric motors international journal of energy economics and policy | vol 13 • issue 3 • 2023336 is minimized, and parallel resistance is increased (tiwari and dubey, 2010). in an sf, in addition to the psc, which is the energy generating element, the converter is the essential equipment since it is the one that delivers energy to the end user, controls the sf, and allows synchronization with the grid. as shown in figure 5, these systems can be classified as standalone photovoltaic systems (sps) and grid-connected photovoltaic systems (cps) (hernández-callejo et al., 2019). the sps can be used without batteries and directly coupled to the load or using batteries with dc self-regulation or with a charge controller with an ac system. the sps also operate with a hybrid sf that includes the possible use of wind turbines, hydro turbines, fuel cells, or diesel generator, among others. the sfrs, can be made up of a bimodal sf with a storage system or directly connected to the user without a storage system. 3. challenges of a massive penetration of ps the main change implied by the increasing use of ps is in the modes of electric power production, which would go from being generated from large units under the control of a network operator to small units connected to the distribution network, whose availability and production it is highly variable depending on the behavior of the weather (rönnberg and bollen, 2016). the main challenges that electrical power systems must face due to the massive use of ps are described below. figure 4: components of a photovoltaic system figure 5: configurations of photovoltaic systems charris, et al.: aspects to consider in the evaluation of photovoltaic system projects to avoid problems in power systems and electric motors international journal of energy economics and policy | vol 13 • issue 3 • 2023 337 the problem of the intermittency of generation from ps is a matter of concern that has been studied, proposing solutions based on hybrid systems that include the storage of pumped hydroelectric energy (basu, 2019; pérez-díaz and jiménez, 2016). another problem of distribution networks with res is that, unlike conventional networks, they have a bidirectional power flow that generates voltage regulation problems. controlled voltage regulation schemes stand out among the methods developed to mitigate this problem (dib et al., 2019). frequency regulation is another challenge in electrical power systems with high penetration of ps due to the variability in their generation. these problems are analyzed in studies where new load frequency control methods are proposed based on artificial intelligence methods that seek faster responses to variations in generation from ps (tungadio and sun, 2019). with the penetration of ps, new challenges have arisen for designing and selecting protection schemes in electrical systems because the fault level changes and the power supply is intermittent. in addition, the unwanted tripping of the overcurrent relays in the distribution feeders can be increased, and their impact can reach the distance relays of the transmission system (telukunta et al., 2018). the massive use of ps has also caused the deterioration of power quality, specifically the increase in harmonics in the points of common coupling (pcc) produced by electronic devices (converters), generating harmonic instability problems for transmission operator networks. various studies have worked on new analysis models and control mechanisms to mitigate these harmful effects (liang and andalib-bin-karim, 2018). reactive power is another parameter that has been affected, with the consequent affectation on voltage regulation and dynamic and transient stability. concerning this other problem, research has been conducted on developing new technologies that allow reactive power to be supplied from the same electronic devices used in the ps (sarkar et al., 2018). 4. effects of ps on the power quality of electrical systems power quality refers to various electromagnetic phenomena that characterize the voltage and current during a particular time in a specific place of the power system. the quality of the energy is affected by electromagnetic distortions that alter the operation of a device, a mechanism, or a system, reducing its useful life. among the main phenomena causing electromagnetic distortions at low frequencies are (ieee std 1159, 2019): • harmonics and interharmonics. • voltage fluctuations. • voltage variations and interruptions of short and long duration. • voltage imbalance. • frequency variation. • low frequency-induced voltages. • direct current signals in alternating current networks. photovoltaic power plants must comply with the requirements of the network to which they are connected, including the established limits of power quality. among the factors that affect the disturbance of photovoltaic energy is the size of the photovoltaic plant, the connection voltage, the short-circuit power at the interconnection point, and the degree of system penetration (ortega et al., 2013). in the case of photovoltaic power plants, the main power quality problems are harmonic content, flicker, voltage variations, and harmonic resonance (chidurala et al., 2016). harmonics, defined as sinusoidal voltages or currents with frequencies that are integer multiples of the system’s fundamental frequency, are among the problems of most concern. harmonic currents increase energy losses in em, overheat the neutral conductor and transformers, and can cause protective devices to malfunction (vita et al., 2016). according to the ieee-519 standard (ieee, 2014) and ieee-1159 (ieee std 1159, 2019), verifying that the harmonics generated by the ps do not exceed the established limits must be done in the pcc. as can be seen in figure 6, the pcc can be in the primary or secondary of the transformer, depending on the connection points of other customers. another characteristic that must be considered with the massive insertion of ps is that the harmonic currents flow from the nonlinear loads (harmonic sources) towards the lowest impedance, generally the primary source. as shown in figure 7, although the impedance of these sources is typically much lower than the impedances of the parallel paths of the loads, the harmonic current is divided according to impedance ratios. higher harmonics will flow to capacitors with low impedance at high frequencies ieee-519 (ieee, 2014). the interaction between the harmonics generated by the ps and the non-linear loads can produce resonance phenomena that are very detrimental to the operation of the electrical system (chidurala et al., 2016). the magnitude and order of the harmonics that photovoltaic units can introduce into the grid will depend to a large extent on the power converter technology. therefore, these components have been studied to improve their performance. recent designs have been based on insulated gate bipolar transistors (igbts) with pulse width modulation (pwm) technology, as they have been shown to produce less harmonic content than thyristorbased converters. in a study where five different converters were evaluated during clear and partly cloudy days, it was possible to demonstrate the influence of the capacity of the converters on the harmonic distortion that can be produced (chicco et al., 2009; langella et al., 2016). in another study where a methodology to measure and evaluate the power quality in ps based on iec standards is applied to a large power plant connected to a medium voltage feeder, it was possible to demonstrate that at low power intervals, the harmonic emission is high (ieee, 2014). interharmonics are also a growing concern. their leading cause is the non-synchronous behavior of electronically connected electrical subsystems: the dc side of the drive and the ac side. some studies have analyzed intercharris, et al.: aspects to consider in the evaluation of photovoltaic system projects to avoid problems in power systems and electric motors international journal of energy economics and policy | vol 13 • issue 3 • 2023338 harmonics emission in a photovoltaic converter, pointing to control with maximum power point tracking (mppt) as a possible cause for frequencies below 100 hz. it is also shown that at more than 100 hz, distorted high-frequency harmonics can have a significant impact. a study conducted in a 96-house distribution system with high sf penetration in the netherlands could identify a high harmonic distortion in the pcc. in this distribution system, the harmonics were produced due to many ps, the typical electronic charges, and the interaction that had the resonance phenomenon (benhabib et al., 2007). in another study in an australian network, the impact of harmonics injected from a network with high sf penetrations was analyzed, which caused an increase in the k-factor of the transformers, causing the overloading and heating of this equipment (chidurala et al., 2016). 5. technological improvements in ps to avoid power quality issues studies on the incidence of ps in the operation of electrical power systems focus on improving the operation of their components and reducing the harmful effects of power quality problems in the electrical system. among the parts of the ps, the power converters are the ones that have received the most attention in various studies that have presented new technological and control strategies that have allowed the improvement of the performance of the ps. one of the control strategies that have been developed is based on status feedback to a dc-dc converter applied for sf regulation purposes. the sf output voltage level is determined by a maximum power point tracking (mppt) algorithm. this control technology provides a suitable duty cycle for switching the dc-dc converter to improve its dynamics concerning the reference voltage generation supplied by the mppt algorithm. the proposed method is tested using computational simulations in the matlab/simulink environment. in addition, an experimental device was used to emulate the simulated results and corroborate the technique’s efficacy (fernandes et al., 2017). a technological solution that has shown excellent reliability against faults is the development of an h-bridge cascade converter applicable to medium voltage and high power. the proposed converter can maintain balanced three-phase network currents during uneven power generation caused by irregular solar irradiation and by different temperatures of each module (yu et al., 2015). another variant that has given good results is the development of a parallel-input, series-output boost converter with dual coupled inductors and a voltage multiplier module. in this technology, the primary windings of two coupled inductors are connected in parallel to share the input current and reduce current ripple. in addition, the converter uses interleaved series connected output capacitors, which enable high voltage gain, reduced output ripple, and reduced switch voltage stress (hu and gong, 2015). the configuration of a multilevel power converter for gridconnected ps has been an effective technology for delivering good quality power. this technology has a modular design and is reusable and scalable. in addition, the converter adds a voltage stabilizer for each module to be installed (duman et al., 2017). the analysis of the principles of classical operation of the converters characterizes the presentation and validation of new designs. another feature of validation is the use of numerical simulations or implementation in novel prototypes. in addition to generation, the operation of an sf is supported by other processes such as monitoring, control, simulation, figure 6: position of the pcc (a) in the transformer’s primary, (b) in the secondary figure 7: the flow of harmonic currents a b charris, et al.: aspects to consider in the evaluation of photovoltaic system projects to avoid problems in power systems and electric motors international journal of energy economics and policy | vol 13 • issue 3 • 2023 339 optimization, fault diagnosis, production stoppage, production start-up, and the operation of all these elements (zhao et al., 2000). to estimate photovoltaic production, it is necessary to anticipate the value of the existing resource, which is irradiance. in forecasting, using artificial neural networks (ann) is widespread. recent research has focused on obtaining short-term forecast models for predicting generation with ps due to the intermittency of solar radiation (gómez rodríguez et al., 2021). one of the problems that have caused the increase in the installation of photovoltaic solar farms is the increase in voltage in the pcc due to the reverse power flow. to regulate the voltage in the pcc, public service companies use the most technology as the voltage source converter with the devices or flexible alternating current transmission systems (facts), aiming to compensate reactive power when there is no generation on the farm (dib et al., 2019). the implementation approach of adaptive ps with mppt has allowed the optimal operation of microgrids in island mode. this strategy enables efficient coordination between all its elements: vf and pq converter control, mppt control, and storage control. it can also be complemented by maintaining the battery unit’s state of charge (soc) (rajesh et al., 2017). hybrid systems composed of ps and a diesel generator have also been studied to minimize costs associated with the consumption of fossil fuels while guaranteeing good energy quality. in a model developed for this purpose, the energy production was programmed through optimization and control techniques to minimize the generator’s fuel costs during operation. the control of the hybrid system was evaluated in two scenarios. in the first, the “continuous” operation control of the generator was analyzed, and in the second, through “on/off” sequences. as analysis criteria, it was considered to minimize the cost of operation of the hybrid system while maintaining the optimal flow of energy, considering the intermittency of energy in the sf, the soc of the battery, and the charging demand. the study’s results demonstrated significant operating savings in this type of system (kusakana, 2015). another alternative to using converters that have proven to have good results is the development of a self-balancing multistage dc-dc boost converter for photovoltaic applications (bhaskar et al., 2017). with this topology, unidirectional energy transfer is guaranteed in scenarios where it is required to increase the voltage without magnetic components (without transformer and inductor). in this case, the output voltage from renewable sources is low and must be expanded using a dc-dc converter for photovoltaic applications. among the advantages of this topology stands out the fact that they are free of magnetic components (without transformer and inductor); the use of continuous input current, capacitors, and low voltage semiconductor devices; modulation capacity; the facility to add a more significant number of levels to increase the voltage gain and the use of only two control switches with alternating operation and simple control. 6. effects of power quality on em em are machines that convert electrical energy into mechanics to drive applications such as pumps, fans, compressors, and conveyors. in em, losses inevitably arise during electromechanical conversion, when a certain amount of energy is irreversibly transformed into heat. figure 8 shows that these are divided into electrical, magnetic, mechanical, and additional losses. electrical losses depend on electrical current squared, so it increases rapidly with increasing load. magnetic losses occur in the steel sheets in the stator and rotor due to hysteresis and eddy current phenomena and vary with flux density and frequency. mechanical losses are due to machine bearings and ventilation system friction. in contrast, additional losses occur mainly due to stray flow, non-uniformity in current distribution, mechanical imperfections in the air gap, and irregular air gap flux density (sousa santos et al., 2019). harmonics and their associated problems in the operation of em have been of interest since the 1920s. in 1929, this phenomenon was addressed as unnecessary noise in electrical devices. in the 1950s, researchers began to address the severe problem of induction machine losses caused by harmonics due to the increasing number of induction machine applications with power supplies based on static frequency converters (rawcliffe and menon, 1952). in the 1960s, additional magnetic power losses in mes due to voltage waves with harmonic frequencies were evaluated (jainy, 1964). studies have shown that each harmonic voltage order has its effects that can be divided into three general categories: (1) insulation voltage; (2) thermal stress; and (3) interruption (gnaciński et al., 2019). regarding the voltage variation, the nema mg-1 standard figure 8: power flow in electric motors charris, et al.: aspects to consider in the evaluation of photovoltaic system projects to avoid problems in power systems and electric motors international journal of energy economics and policy | vol 13 • issue 3 • 2023340 (motors and generators, 2016) establishes that the em will operate correctly under operating conditions with a voltage variation of ±10% and a frequency variation of ±5%. for its part, iec 600034-1 standard (international electrotechnical commission, 2014) allows two different operating ranges: a ±5% variation for continuous operations and a ±10% variation for intermittent operations. the tolerance in the standards is due to the voltage variation’s influence on the operation and efficiency of the em. the voltage variation and frequency variation directly influence the magnetic losses of the induction em (saidur, 2010), which, in turn, represent around 15% of the total losses of the motor operating at full load (bonnett et al., 2016). the worst operating condition of the em is when it is powered at low voltage at a load greater than 70% since the steady state current increases, and consequently, the operating temperature increases. instead, some overvoltage (less than 5%) can decrease em heating as slip falls, and as a result, efficiency can improve, even though the power factor decreases and starting current increases. the voltage variation also directly influences the torque/speed characteristic of the em, such that, with the increase in voltage, the torque and speed also increase, and vice versa (mehazzem et al., 2017). the variable nature of generation in ps and the use of electronic devices in their operation cause power quality problems such as harmonic distortion and voltage deviation that directly affect the operation of em. due to the high incidence that em have, as one of the primary consumers of the electrical system, ps’s influence on their operation should be included. 7. conclusion the analysis based on state-of-the-art shows the challenges that the massive penetration of ps implies for electric power systems and em. the studies demonstrate the affectation that ps has produced in the operation of distribution circuits, mainly due to the variability in the availability and production of energy, the problems of frequency regulation, the generation of harmonics, and the instability of reactive power generation. the article showed how companies in the energy sector and various research centers had directed their efforts toward the technological improvement of ps components to mitigate the problems indicated. the power converter is the most studied component for its crucial function in controlling and synchronizing the energy generated by the sf when coupled with the electrical networks. studies were presented that evaluate the affectation in the operation of the em when it is fed from networks with power quality problems, demonstrating that harmonics and voltage regulation are the power quality problems that most affect their operation. none of the studies presented analyzes the direct influence that ps can have on the operation of em. considering the importance of these charges and the reduction in the energy that can be derived from the ps, this work intends to call the scientific community’s attention to develop research focused on this problem. it is also proposed that the aspects analyzed be considered in developing new generation projects with photovoltaic systems. references azzouz, m.a., farag, h.e., el-saadany, e.f. (2017), real-time fuzzy voltage regulation for distribution networks incorporating high penetration of renewable sources. ieee systems journal, 11(3), 1702-1711. basu, m. (2019), optimal generation scheduling of hydrothermal system with demand side management considering uncertainty and outage of renewable energy sources. renewable energy, 146, 530-542. benhabib, m.c., myrzik, j.m.a., duarte, j.l. (2007), harmonic effects caused by large scale pv installations in lv network. in: 2007 9th international conference on electrical power quality and utilisation. bhaskar, m.s., padmanaban, s., blaabjerg, f. (2017), a multistage dcdc step-up self-balanced and magnetic component-free converter for photovoltaic applications: hardware implementation. energies, 10(5), 719. bonnett, a.h., glatt, h., hauck, s. (2016), effect of power deviations on squirrel-cage induction motors: addressing the impact of voltage and frequency variations. ieee industry applications magazine, 22(6), 39-47. brahma, s.m., girgis, a.a. (2004), development of adaptive protection scheme for distribution systems with high penetration of distributed generation. ieee transactions on power delivery, 19(1), 56-63. chicco, g., schlabbach, j., spertino, f. (2009), experimental assessment of the waveform distortion in grid-connected photovoltaic installations. solar energy, 83(7), 1026-1039. chidurala, a., saha, t.k., mithulananthan, n. (2016), harmonic impact of high penetration photovoltaic system on unbalanced distribution networks-learning from an urban photovoltaic network. iet renewable power generation, 10(4), 485-494. congreso de colombia. (2014), ley 1715 de 2014. diario oficial. available from: http://www.upme.gov.co/normatividad/nacional/2014/ ley_1715_2014.pdf dib, m., ramzi, m., nejmi, a. (2019), voltage regulation in the medium voltage distribution grid in the presence of renewable energy sources. materials today: proceedings, 13, 739-745. duman, t., marti, s., moonem, m.a., kader, a.a.r., krishnaswami, h. (2017), a modular multilevel converter with power mismatch control for grid-connected photovoltaic systems. energies, 10(5), 698. fernandes, d., almeida, r., guedes, t., sguarezi filho, a.j., costa, f.f. (2017), state feedback control for dc-photovoltaic systems. electric power systems research, 143, 794-801. gnaciński, p., hallmann, d., pepliński, m., jankowski, p. (2019), the effects of voltage subharmonics on cage induction machine. international journal of electrical power and energy systems, 111, 125-131. gómez, j.r., sousa, v., cabello eras, j.j., sagastume gutiérrez, a., viego, p.r., quispe, e.c., de león, g. (2022), assessment criteria of the feasibility of replacement standard efficiency electric motors with high-efficiency motors. energy, 239, 121877. gómez rodríguez, m.a., gómez-sarduy, j.r., lorenzo ginori, j.v., fonte gonzález, r., garcía sánchez, z. (2021), electrical generation forecast of photovoltaic systems. first steps by cuban universities. universidad y sociedad, 13(1), 253-265. hernández-callejo, l., gallardo-saavedra, s., alonso-gómez, v. (2019), a review of photovoltaic systems: design, operation and maintenance. solar energy, 188, 426-440. hu, x., gong, c. (2015), a high gain input-parallel output-series dc/dc converter with dual coupled inductors. ieee transactions on power charris, et al.: aspects to consider in the evaluation of photovoltaic system projects to avoid problems in power systems and electric motors international journal of energy economics and policy | vol 13 • issue 3 • 2023 341 electronics, 30(3), 1306-1317. iea. (2018), market report series renewables 2018 analysis and forecast to 2023. france: international energy agency. p211. ieee. (2014), ieee std 519tm-2014: ieee recommended practice and requirements for harmonic control. in: ansi/ieee std. 519. vol. 2014. united states: institute of electrical and electronics engineers. p5-9. ieee std 1159. (2019), ieee std 1159tm-2019: ieee recommended practice for monitoring electric power quality. in: ieee standard 1159-2019 (revision of ieee std 1159-2009). vol. 2014. united states: institute of electrical and electronics engineers. p1-98. international electrotechnical commission. (2014), iec 60034-30-1:2014 rotating electrical machines : efficiency classes of line operated ac motors. 50. united kingdom: international electrotechnical commission. jainy, g.c. (1964), the effect of voltage waveshape on the performance of a 3-phase induction motor. ieee transactions on power apparatus and systems, 83(6), 561-566. kusakana, k. (2015), operation cost minimization of photovoltaic-dieselbattery hybrid systems. energy, 85, 645-653. langella, r., testa, a., meyer, j., moller, f., stiegler, r., djokic, s.z. (2016), experimental-based evaluation of pv inverter harmonic and interharmonic distortion due to different operating conditions. ieee transactions on instrumentation and measurement, 65(10), 2221-2233. liang, x., andalib-bin-karim, c. (2018), harmonics and mitigation techniques through advanced control in grid-connected renewable energy sources: a review. ieee transactions on industry applications, 54(4), 3100-3111. mehazzem, f., nemmour, a.l., reama, a. (2017), real time implementation of backstepping-multiscalar control to induction motor fed by voltage source inverter. international journal of hydrogen energy, 42(28), 17965-17975. ministerio de minas y energía. (2018), resolución creg 030: por la cual se regulan las actividades de autogeneración a pequeña escala y de generación distribuida en el sistema interconectado nacional. p27. https://apolo.creg.gov.co/publicac.nsf/1c09d18d2d 5ffb5b05256eee00709c02/83b41035c2c4474f05258243005a1191/ $file/creg030-2018.pdf ministerio minas y energia, & upme. (2016), guia práctica para la aplicación de los incentivos tributarios de la ley 1715 de 2014. p28. https://www.socialsolar.com.co/wp-content/uploads/2018/09/ incentivos-tributarios.pdf mohanty, p., muneer, t., kolhe, m. (2016), solar photovoltaic system applications. new york city: springer international publishing. rocha, c.m.m., alvarez, j.r.n., castillo, d.a.d., domingue, e.d.f., hernandez, j.c.b. (2022), implementation of the hierarchical analytical process in the selection of the best source of renewable energy in the colombian caribbean region. international journal of energy economics and policy, 12(2), 111-119. rocha, c.m.m., batista, c.m., rodríguez, w.f.a., ballesteros, a.j.f., álvarez, j.r.n. (2022), challenges and perspectives of the use of photovoltaic solar energy in colombia. international journal of electrical and computer engineering (ijece), 12(5), 4521-4528. motors and generators. (2016), pub. l. no. ansi/nema mg 1-2016. available from: https://www.nema.org/docs/default-source/ standards-document-library/ansi_nema-mg-1-2016-contents-andforeword.pdf?sfvrsn=f27547b8_1 ortega, m.j., hernández, j.c., garcía, o.g. (2013), measurement and assessment of power quality characteristics for photovoltaic systems: harmonics, flicker, unbalance, and slow voltage variations. electric power systems research, 96, 23-35. pérez-díaz, j.i., chazarra, m., garcía-gonzález, j., cavazzini, g., stoppato, a. (2015), trends and challenges in the operation of pumped-storage hydropower plants. renewable and sustainable energy reviews, 44, 767-784. pérez-díaz, j.i., jiménez, j. (2016), contribution of a pumped-storage hydropower plant to reduce the scheduling costs of an isolated power system with high wind power penetration. energy 109, 92-104. pierret, r.f. (1983), modular series on solid state devices. volume i: semiconductor fundamentals. boston: addison-wesley publishing company. rajesh, k.s., dash, s.s., bayinder, r., sridhar, r., rajagopal, r. (2017), implementation of an adaptive control strategy for solar photo voltaic generators in microgrlds with mppt and energy storage. in: 2016 ieee international conference on renewable energy research and applications, icrera. p766-771. rawcliffe, g.h., menon, a.m. (1952), a simple new test for harmonicfrequency losses in a.c. machines. journal of the institution of electrical engineers, 4, 119. rönnberg, s., bollen, m. (2016), power quality issues in the electric power system of the future. electricity journal, 29(10), 49-61. saidur, r. (2010), a review on electrical motors energy use and energy savings. renewable and sustainable energy reviews, 14(3), 877-898. sarkar, m.n.i., meegahapola, l.g., datta, m. (2018), reactive power management in renewable rich power grids: a review of gridcodes, renewable generators, support devices, control strategies and optimization algorithms. ieee access, 6, 41458-41489. sousa santos, v., cabello eras, j.j., sagastume gutierrez, a., cabello ulloa, m.j. (2019), assessment of the energy efficiency estimation methods on induction motors considering real-time monitoring. measurement, 136, 237-247. telukunta, v., pradhan, j., agrawal, a., singh, m., srivani, s.g. (2018), protection challenges under bulk penetration of renewable energy resources in power systems: a review. csee journal of power and energy systems, 3(4), 365-379. tiwari, g.n., dubey, s. (2010), fundamentals of photovoltaic modules and their applications. united kingdom: royal society of chemistry. tungadio, d.h., sun, y. (2019), load frequency controllers considering renewable energy integration in power system. energy reports, 5, 436-453. unfccc. (2015), convention on climate change: climate agreement of paris. united states: unfccc. p1-25. available from: https://unfccc. int/process-and-meetings/the-paris-agreement/the-paris-agreement upme. (2015), plan energetico nacional colombia: ideario energético 2050. p184. available from: https://www.upme.gov.co/docs/pen/ pen_idearioenergetico2050.pdf vita, v., alimardan, t., ekonomou, l. (2016), the impact of distributed generation in the distribution networks’ voltage profile and energy losses. in: proceedings-ems 2015: uksim-amss 9th ieee european modelling symposium on computer modelling and simulation. p260-265. ye, y., qiao, y., lu, z. (2019), revolution of frequency regulation in the converter-dominated power system. renewable and sustainable energy reviews, 111, 145-156. yu, y., konstantinou, g., hredzak, b., agelidis, v.g. (2015), operation of cascaded h-bridge multilevel converters for large-scale photovoltaic power plants under bridge failures. ieee transactions on industrial electronics, 62(11), 7228-7236. zhao, y., lu, m.l., yuan, y. (2000), operation and maintenance integration to improve safety. computers and chemical engineering, 24(2-7), 401-407. . international journal of energy economics and policy | vol 7 • issue 5 • 201734 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(5), 34-43. environment–economic growth nexus: a comparative analysis of developed and developing countries#1 ali acaravci1*, guray akalin2 1faculty of economics and administrative sciences, mustafa kemal university, hatay, turkey, 2faculty of economics and administrative sciences, dumlupınar university, kutahya, turkey. *email: acaravci@hotmail.com abstract this study aims to examine the interaction between carbon emissions, income, and trade openness in developed and developing countries for the period from 1980 to 2010 by using recently developed panel data econometric methods. the results are as follows: (i) there is an evidence of the cross-sectional dependence for each variable. (ii) the cross-sectionally augmented and smith et al.’s panel unit root tests are indicate that all variables are stationary at their first difference. (iii) a durbin–hausman cointegration test shows that there exists a long-term relationship between variables. (iv) the results from the common correlated effect estimator presents that there is evidence of the validity of the environmental kuznets curve (ekc) hypothesis in developed countries. (v) the ekc hypothesis is not valid in developing countries. keywords: economic growth, environmental kuznets curve, panel data analysis jel classification: c33, o57, q43, q53, q56 # this paper depends on the results of guray akalin’s master thesis: “enviromental kuznets curve validity of the developed and developing countries-comparative analysis of panel data.” 1. introduction the primary goal of economic activities is to increase human welfare and rapid economic growth is seen as a way to accomplish this goal. however, when production increases the use of resources while the relative cost of production factors diminish, wastes generated by the production and consumption process raise the environmental cost. moreover, population growth, urbanization, and the increasing of use of non-renewable energy can overtake the carrying capacity of the environment. as a result, many environmental problems have begun to emerge that includes climate change; global warming; air, water, and soil pollution; loss of biodiversity; and forest destruction. as environmental problems have become more severe, the nexus between environmental degradation and economic growth becomes an increasingly important issue (tutulmaz, 2015). the environmental kuznets curve (ekc) hypothesis, which implies an inverted-u relationship between environmental degradation and economic growth, has become the center of this research. according to the ekc hypothesis, economic growth is both cause of and solution to environmental degradation. for this reason, testing the ekc hypothesis becomes prominent to economic growth and environmental policies. the ekc hypothesis that inspired from the kuznets curve, has been first proposed and tested by grossman and krueger (1991). they found evidence that the environmental degradation first increases as per capita income rise, but then starts to decrease after turning point in per capita income. their study has been also confirmed by shafik and bandyopadhyay (1992) and panayotou (1993). stern (2004), dinda (2004), shahbaz et al. (2015), ozturk and al-mulali (2015), tang et al. (2016) and gill et al. (2017) have provided extensive review surveys of the studies that tested the nexus between economic growth and environmental pollution. while johansson and kriström (2008) have emphasized that the literature on the ekc is insufficient and this topic needs more empirical investigation. stern (2004) argued that the issues of the ekc should be revisited by using new models and decompositions with different panels and time series data sets. acaravci and akalin: environment–economic growth nexus: a comparative analysis of developed and developing countries international journal of energy economics and policy | vol 7 • issue 5 • 2017 35 however, few scholars as panayotou (1993) believe that the ekc is caused by upgrading from the adjustment of economic structures (tiwari et al., 2013). some of these authors have underlined the roles of three different effects in the ekc (tutulmaz, 2015), that can be listed as scale effects, structural effects and technique effects (grossman and krueger, 1991; stern, 2004; song et al., 2008): (i) scale effect means that using more natural resources in the production process leads to the destruction of nature while technology is constant, which is defined as environmental degradation. (ii) according to the structural effect, economic development passes through stages starting from the preliminary upgrade from an agriculture system to the rapid development of high-grade, industrial structures with high-pollution industries and then finally turns to more information-concentrated industries, which leads to improvements in environmental quality. (iii) in the technique effect that discovered by stokey (1998), economic growth can break through one threshold point after arriving at a certain stage of economic development. hence, at a low-income level, only the high pollution technique can be used but, after crossing the threshold point of economic development, cleaner technologies can be adopted which lowers the degradation in environmental quality. further, another approach to explain the ekc relationship is the income elasticity of demand for environmental quality. the demand for a clean environment increases while real income per capita increases (lopez and islam, 2008). lieb (2002) argued that an increase in income improves the level of education, and this creates awareness about the environment. moreover, an increase in income distribution has positive effects on the environment. finally, he mentions that the policies implemented after the internalization of external effects, substitution between the pollutants, and finally a crisis in the energy sector will affect the shape of the ekc and its turning point. in this context, this study aims to test the ekc hypothesis in developed and developing countries for the period from 1980 to 2010 by using panel data econometric methods. to test the ekc hypothesis, the common correlated effect (cce) estimator, developed by pesaran (2006), has been employed in a multivariate framework which includes carbon emissions, gross domestic product (gdp) per capita, and trade openness rate (% of gdp). the rest of the paper is organized as follows: section 2 summarizes literature on the ekc hypothesis; section 3 describes the model and the data; section 4 explains the methodology and section 5 reports the empirical results; and finally, section 6 concludes the paper. 2. literature review many empirical studies attempt to test the validity of the ekc by using a quadratic or cubic equation. this equation examines the relationship between the per capita incomes with a variety of air pollution indices. a basic reduced (income-reduced) form of an ekc model and interpretation is summarized as by de bruyn and heintz (1999): e y y y zit it it it it it= + + + + +β β β β β ε1 2 3 2 4 3 5 (1) where e represents environmental pressure or environmental pollution; y represents economic development; z is other variables; i and t are country and time indices; and ε is the error term. equation (1) lets us test several forms of environment–economic development/growth relationships that can be described as follows: i) if β2=β3=β4=0, there is a flat pattern (no relationship) between y and e. ii) if β2>0 and β3=β4=0, there is a monotonic increasing relationship (a linear relationship) between y and e. iii) if β2<0 and β3=β4=0, there is a monotonic decreasing relationship between y and e. iv) if β2>0, β3<0 and β4=0, there is an inverted-u-shaped relationship. v) if β2<0, β3>0 and β4<0, there is an inverted n-shaped relationship. vi) if β2>0, β3<0 and β4>0, there is a cubic polynomial or n-shaped relationship. a large number of econometric studies have used equation (1) to test for the emergence of an ekc in a wide variety of incomebased environmental pressure/pollution levels (dinda, 2004). the studies that investigate the relationship between the environment and economic growth have begun in 1990 as a reaction to environmental issues. most of this works have tested the ekc hypothesis. in these studies, different models, methods, data sets, and variables have been used. most studies in this area have been examined by us and are shown in the following table 1. the results of the literature review indicate that there is no consensus on this issue. 3. model and data this paper employs the form of a cubic model in order to test ekc hypothesis that can be introduced as follows: co gdp gdp gdp trit i it it it it it2 1 2 3 2 4 3 5 = + + + + +β β β β β ε (2) where co2, carbon emissions per capita (measured in metric kilograms), is the environmental indicator that is directly related to major issues such as climate change; gdp is the per capita income (constant 2005 usd), and to improve the structure of an econometric model, trade openness rate (% of gdp), tr, is used as a control variable. the annual time series data is taken from the world bank, world development indicators (2014) online for the period from 1980 to 2010 in the form of balanced panel data. the following two samples are used: 40 high-income countries and 33 upper middle-income countries. the 40 high-income countries include antigua and barbuda, australia, austria, bahamas, bahrain, barbados, belgium, canada, chile, cyprus, denmark, equatorial guinea, finland, france, greece, hong kong sar (china), iceland, ireland, israel, italy, japan, korea, luxembourg, macao, malta, the netherlands, new zealand, norway, oman, portugal, saudi arabia, singapore, spain, saint kitts, sweden, switzerland, trinidad, the united kingdom, the united states, and uruguay. the 33 upper middle-income countries include albania, algeria, argentina, belize, botswana, brazil, bulgaria, china, colombia, costa rica, cuba, dominica, dominican republic, ecuador, fiji, gabon, grenada, hungary, jordan, acaravci and akalin: environment–economic growth nexus: a comparative analysis of developed and developing countries international journal of energy economics and policy | vol 7 • issue 5 • 201736 a ut ho rs sa m pl e an d pe ri od m et ho d d ep en de nt v ar ia bl e in de pe nd en t va ri ab le r es ul ts g ro sm an n an d k ru eg er (1 99 1) n af ta c ou nt ri es 19 77 , 1 98 2, 1 98 8 pd a so 2 sp m g d p 1. n re la tio ns hi p fo r s o 2 e k c is n ot v al id 2. d ec re as in g lin ea r r el at io ns hi p fo r s pm sh afi k an d b an dy op ad hy ay (1 99 2) 14 9 co un tr ie s 19 60 -1 99 0 pd a c le an w at er c ity w at er s an ita tio n so 2 t he a m ou nt o f d is so lv ed o xy ge n in th e ri ve r c ha ng es in fo re st a re as d ef or es ta tio n fe ca l c ol if or m in th e ri ve r m id -a ir p ar tic le s c o 2 10 . u rb an w as te g d p 1. e k c is n ot v al id 2. e k c is n ot v al id 3. e k c is v al id (i nv er te du ) 4. e k c is n ot v al id 5. e k c is n ot v al id 6. e k c is n ot v al id 7. e k c is v al id (i nv er te du ) 8. e k c is v al id (i nv er te du ) 9. e k c is n ot v al id 10 . e k c is n ot v al id se ld en a nd s on g (1 99 4) 30 c ou nt ri es 19 79 -1 98 7 pd a so 2 n o 2 sp m c o 2 g d p 1. e k c is v al id (i nv er te du ) 2. e k c is v al id (i nv er te du ) 3. e k c is v al id (i nv er te du ) 4. e k c is v al id (i nv er te du ) pa na ya to u (1 99 7) 30 c ou nt ri es 19 82 -1 99 4 pd a n o 2 pm 10 so 2 d ef or es ta tio n g d p 1. e k c is v al id (i nv er te du ) 2. e k c is v al id (i nv er te du ) 3. e k c is v al id (i nv er te du ) 4. e k c is v al id (i nv er te du ) m oo m aw a nd u nh ru h (1 99 7) 16 c ou nt ri es 19 50 -1 99 2 pd a c o 2 g d p e k c is v al id (i nv er te du ) k au fm an e t a l. (1 99 8) 23 c ou nt ri es 19 74 -1 98 9 pd a so 2 g d p 1. e k c is v al id (i nv er te du ) to rr as a nd b oy ce (1 99 8) 42 c ou nt ri es 19 77 -1 99 1 pd a so 2 m id -a ir p ar tic le s g d p 1. n re la tio ns hi p fo r s o 2 e k c is n ot v al id 2. e k c is n ot v al id d e b ru yn e t a l. (1 99 8) 4 co un tr ie s 19 60 -1 99 3 pd a so 2 c o 2 n o 2 g d p 1. e k c is n ot v al id 2. e k c is n ot v al id 3. e k c is n ot v al id a gr as a nd c ha pm an (1 99 9) 34 c ou nt ri es 19 71 -1 98 9 pd a c o 2 g d p e k c is v al id (i nv er te du ) b ar re t a nd g ra dd y (2 00 0) 32 c ou nt ri es 19 77 , 1 98 2, 1 99 8 pd a so 2 g d p n re la tio ns hi p fo r s o 2 e k c is n ot v al id d ijk gr aa f a nd v ol le be rg h (2 00 1) o e c d c ou nt ri es 19 60 -1 99 7 pd a c o 2 g d p e k c is n ot v al id st er n an d c om m on (2 00 1) 73 c ou nt ri es 19 60 -1 99 0 pd a so 2 g d p e k c is v al id (i nv er te du ) m as on a nd s w an so n (2 00 3) 29 c ou nt ri es 19 76 -1 98 8 pd a c fc g d p e k c is v al id (i nv er te du ) c ol e (2 00 4) 18 o e c d c ou nt ri es 19 80 -1 99 7 pd a so 2 g d p e k c is v al id (i nv er te du ) d in da e t a l. (2 00 0) 33 c ou nt ri es 19 79 -1 99 0 pd a so 2 g d p e k c is v al id (i nv er te du ) a ng (2 00 7) fr an ce 19 84 -2 00 4 t sa c o 2 g d p e k c is v al id (i nv er te du ) ta bl e 1: s el ec te d em pi ri ca l s tu di es o n th e e k c h yp ot he si s (c on td ... ) acaravci and akalin: environment–economic growth nexus: a comparative analysis of developed and developing countries international journal of energy economics and policy | vol 7 • issue 5 • 2017 37 a ut ho rs sa m pl e an d pe ri od m et ho d d ep en de nt v ar ia bl e in de pe nd en t va ri ab le r es ul ts h e an d r ic ha rd (2 00 9) c an ad a 19 48 -2 00 4 t sa c o 2 g d p e k c is n ot v al id n ar ay an a nd n ar ay an (2 01 0) 43 d ev el op in g co un tr ie s 19 80 -2 00 4 pd a c o 2. g d p e k c is v al id in th e m id dl e e as t a nd s ou th a si an c ou nt ri es a ca ra vc i a nd o zt ur k (2 01 0) 19 e ur op ia n c ou nt ri es 19 60 -2 00 5 t sa , a r d l c o 2 e c a nd g d p e k c is v al id in th e it al y an d d en m ar k pa ci ni (2 01 0) 13 8 co un tr ie s 20 07 c sd a c o 2 h d i e k c is v al id (i nv er te du ) sa ng lim su w an (2 01 1) 63 c ou nt ri es 19 90 , 1 99 5, 2 00 0 pd a c o 2 g d p e k c is v al id o n on ly in th e sh or t t er m fa rh an i a nd r ej eb (2 01 2) 15 m en a co un tr ie s 19 73 -2 00 8 pd a c o 2 e c a nd g d p e k c h yp ot he si s is s up po rt ed w ea kl y h an a nd l ee (2 01 3) 19 o e c d c ou nt ri es 19 81 -2 00 9 pd a c o 2 g d p e k c is v al id (i nv er te du ) sh ah ba z et a l. (2 01 3) r om an ia 19 80 -2 01 0 t sa , a r d l c o 2 g d p, e c a nd t r e k c is v al id m am un e t a l. (2 01 4) 13 6 co un tr ie s di vi de d in to fi ve m aj or in co m e gr ou ps pd a c o 2 g d p, t r , s ec to ra l ou tp ut e k c is v al id fo r l ic , l m ic a nd u m ic co un tr ie s e k c is n ot v al id fo r h io e c d a nd h in o e c d c ou nt ri es m en sa h (2 01 4) 6 a fr ic an c ou nt ri es 19 71 -2 00 9 a r d l c o 2 e c a nd g d p e k c o nl y va lid fo r g ha na m en eg ak i a nd t sa ga ra ki s (2 01 5) 33 e ur op ea n m em be r an d ca nd id at e st at e co un tr ie s 19 90 -2 01 0 pd a , a b b r e s, o il, g as , c oa l g d p, e ne rg y in te ns ity , e du ca tio n, te ch on ol og y, d em og ra ph y, s ci en ce e k c is v al id (i nv er te du ) f or b ot h of th e r e s an d c oa l v ar ia bl es e k c is n ot v al id (ı nv er te du ) f or b ot h of th e oi l a nd g as v ar ia bl es a hm ed e t a l. (2 01 6) b ra zi l, in di a, c hi na , s. a fr ic a 19 70 -2 01 3 pe dr on i, fm o l s c o 2 g d p, n sc , u r b a n e k c is n ot v al id d og an a nd t ur ke ku l ( 20 16 ) u sa 19 60 -2 01 0 a r d l c o 2 g d p, f d , t r , u r b a n e k c is n ot v al id o zt ur k et a l. (2 01 6) 14 4 co un tr ie s 19 88 -2 00 8 g m m e co lo gi ca l f oo tp ri nt to ur is m , e ne rg y co ns um pt io n, tr ad e op en ne ss , ur ba ni za tio n th e e k c h yp ot he si s is m or e pr es en t i n th e up pe r m id dl e a nd h ig hin co m e co un tr ie s th an th e ot he r i nc om e co un tr ie s sa id i a nd m ba re k (2 01 7) 19 e m er gi ng c ou nt ri es 19 90 -2 01 3 g m m c o 2 g d p, t r , u rb an e k c is v al id (i nv er te du ) t sa : t im e se ri es a na ly si s, p d a : p an el d at a an al ys is , a r d l : a ut or eg re ss iv e di st ri bu te d la g, c sd a : c ro ss s ec tio n da ta a na ly si s, g m m : g en er al is ed m et ho d of m om en ts , f m o l s: f ul ly m od ifi ed o rd in ar y le as t s qu ar es , a b b : a re lla no b on db ov er es tim at or . g d p: p er c ap ita g d p, e c : p er c ap ita e ne rg y co ns um pt io n, t r : t ra de o pe ne ss , f d : f in an ci al d ev el op m en t, u r b a n : u rb an is at io n, r e s: r en ew ab le e ne rg y so ur ce s, n sc : n at ur al g as c on su m pt io n, h d i: h um an d ev el op m en t in de x, o e c d : o rg an iz at io n fo r e co no m ic c oo pe ra tio n an d de ve lo pm en t, l ic : l ow er in co m e co un tr ie s, l m ic : l ow er m id dl ein co m e co un tr ie s, u m ic : u pp er m id dl ein co m e co un tr ie s, h io e c d : h ig hin co m e o e c d c ou nt ri es , h in o e c d : h ig hin co m e no no e c d c ou nt ri es , n af ta : n or th a m er ic an fr ee tr ad e ag re em en t, m e n a : m id dl e ea st a nd n or th a fr ic a, s o 2: su lf ur d io xi de , s pm : s m ok e an d m id -a ir p ar tic le s, c o 2: c ar bo n di ox id e, n o 2: n itr og en d io xi de , p m 10 : p ar tic ul at e m at te r, c fc : c hl or ofl uo ro ca rb on ta bl e 1: (c on tin ue d) acaravci and akalin: environment–economic growth nexus: a comparative analysis of developed and developing countries international journal of energy economics and policy | vol 7 • issue 5 • 201738 malaysia, mauritania, mexico, panama, peru, seychelles islands, south africa, santa lucia, saint vincent, thailand, tonga, tunis, turkey, and venezuela. these countries were selected according to data available from related income groups. 4. methodology 4.1. testing the cross-sectional dependency conventional panel unit root tests which are also known as firstgeneration like those of hadri (2000), levin–lin–chu (llc, 2002), and im–pesaran–shin (ips, 2003) assume that cross sections are independent and are not able to consider the cross section dependency. this is particularly true of panels with a large cross section dimension (n). in the case of panels where n is small (say 10 or less) and the time dimension of the panel (t) is sufficiently large between sections of panel models, it can cause serious correlations (pesaran, 2004). the cross-sectional dependency in error terms can be caused by several reasons. the first of these neglects spatial and common effect, while the other neglects the relationship between socio-economic networks in the panel model. it does not consider the cross-sectional dependence that occurs due to these reasons and the estimates made by the traditional panel estimator can produce misleading or even inconsistent parameters (chudik and pesaran, 2013). therefore, the cross-dependency should be tested on the basis of both models and variables. if cross-sectional dependence exists in the variables or model, using the first-generation tests may cause the first type of error. for a more reliable econometric estimation approach, researchers must explore cross-sectional dependency in each series and model. breusch and pagan (1980) proposed the following lagrange multiplier test statistic to test for cross-sectional dependency: cd t plm ij j i n i n 1 2 11 1 = = += − ∑∑  (3) where pij is the estimated correlation coefficient among the residuals obtained from individual ordinary least squares (ols) estimations. under the null hypothesis of no cross-sectional dependency with a fixed n (number of cross-sections) and time period t→∞, the statistic has chi-square asymptotic distribution with n(n-1)/2 degrees of freedom. however, this test is not applicable with a large n. to overcome this problem, the lagrange multiplier statistic developed by pesaran (2004) can be used as shown in the following equation: cd n n tplm ij j i n i n 2 1 2 2 11 1 1 1 1= −       −( ) = += − ∑∑ ( ) /  (4) under the null hypothesis of no cross-sectional dependency with first t→∞ and then n→∞, this test statistic is an asymptotic standard normal distribution. even though the cdlm2 test overcomes the drawback of cdlm1, it likely exhibits substantial size distortions when n/t→∞. when n is large and t is small, pesaran (2004) proposed to use of the following cross-sectional dependency test: cd t n n plm ij j i n i n 3 1 2 11 1 2 1 = −       = += − ∑∑ ( ) /  (5) under the null hypothesis of no cross-sectional dependency with t→∞ and n→∞ in any order, the cdlm3 test is asymptotically distributed as standard normal (nazlıoglu et al., 2011). 4.2. panel unit root tests this paper employs two panel unit root tests developed by pesaran (2007) (cross-sectionally augmented dickey–fuller [cadf]) and smith et al. (2004) (hereafter smith bootstrap) in order to investigate the stationarity properties and determine the order of integration of the variables. the most important feature of the cadf panel unit root test is to give reliable results whether n>t or t>n. furthermore, this test is a heterogeneous test and provides separate results for each section (pesaran, 2007). the smith bootstrap panel unit root approach includes five test statistics which are called as t*, lm , max , min , and ws . the t* test is the bootstrap version of the ips panel unit test and is calculated as t n ti i n * = − = ∑1 1 . the lm test has been developed by solo (1984) and tests statistic is calculated as lm n lmi i n = − = ∑1 1 . the max test has been developed by leybourne (1995) and is calculated as max n maxi i n = − = ∑1 1 . the min test is a more powerful variant of the lm statistic and is calculated as min n mini i n = − = ∑1 1 . finally, we examine the ws test developed by pantula et al. (1994). the first test does not consider the cross-sectional dependence. we use bootstrap blocks of m=102. all four tests are constructed with a unit root under the null hypothesis and heterogeneous autoregressive roots under the alternative, which indicates that a rejection should be taken as evidence in favor of stationarity for at least one country (smith et al. 2004). 4.3. panel cointegration and estimating of the long-run coefficients this paper employs durbin-hausman cointegration test in order to investigate the existence of long-run relationship between variables. durbin-hausman test allows the cross-sectional dependency in model and gives reliable results when some of explanatory variables are i(0). this test contains two statistics as follows: the dh-group and the dh-panel statistics. while the dh-group statistic assumes that the autoregressive parameters are heterogeneous and produces results under this assumption; the dh-panel statistic assumes that the autoregressive parameters are homogeneous and produces results under this assumption. in a case when both test statistics reject the null hypothesis; these results indicate the existence of co-integration for the entire panel (westerlund, 2008). once the cointegration relationship is established, the next step is to estimate the long-run parameters. to estimate panel cointegration parameters, various methods have been proposed, acaravci and akalin: environment–economic growth nexus: a comparative analysis of developed and developing countries international journal of energy economics and policy | vol 7 • issue 5 • 2017 39 namely panel ols, panel dynamic ols, and panel fully modified ols. however, none of these consider cross-sectional dependence. to consider the cross-sectional dependence, we use the cce estimator developed by pesaran (2006). moreover, the cce estimator has satisfactory small sample properties even under a substantial degree of heterogeneity and dynamics or relatively small values of n and t (pesaran, 2006). this model’s estimators consider the effects of factors that are not included in the econometric model coupled with a cross section of each unit’s time vector regression equations. the cce estimator assumes that the effects of unobserved common effects and independent variables are stationary and external, but this approach continues to yield consistent estimation and valid inference even when common factors are unit root processes (pesaran, 2006). the cce also allows for individual specific errors to be serially correlated and heteroscedastic. in the model, the common correlated effects pooled statistics are used for the panel and are calculated as follows:  b x m x x m yp i i w i i n i i w i i n = ′       ′ = − = ∑ ∑θ θ 1 1 1 (6) 5. empirical results 5.1. cross-sectional dependence tests results table 2 presents that the null hypothesis of no cross-sectional dependency is rejected for both countries. this provides strong evidence for the existence of cross-sectional dependency across developed and developing countries. this means that, whether developed or developing countries, any development on the environmental–income–trade nexus in one or more countries affects other countries. 5.2. panel unit root tests results as there is cross-sectional dependence in all variables, the stationarity properties of the series will be investigated by the second generation unit root tests. in this study, a cadf panel unit root test developed by pesaran (2007) and a bootstrap panel unit root test developed by smith et al. (2004) has been used to determine the stationarity properties of the variables. cross-sectional dependence in the model has been also found, so cointegration analysis must that take into account cross-sectional dependence is used. the cips panel unit root test results for the developed and developing countries show that the null hypothesis for all variables is accepted at their levels of variables but the null hypothesis for all variables is rejected at their first differences. this means that all variables are stationary at their first differences (table 3). the smith bootstrap panel unit root test results for both the developed countries indicate that the null hypothesis is accepted for all levels of the variables (table 4). the test statistics for the first-differences strongly reject the null hypotheses, which imply that the variables are stationary in the first-difference form. the smith bootstrap unit root test results depend on only the intercept model and intercept-trend model for developing countries indicate that the null hypothesis is accepted for all levels of the variables except for the tr variables. the test statistics for the first-differences strongly reject the null hypotheses, which imply that the variables are stationary in the first-difference form. table 2: cross-section dependence test results for variables and models tests co2 gdp gdp 2 gdp3 tr model developed countries cd lm1 1178.543 (0.000) 1336.885 (0.000) 691.085 (0.000) 695.753 (0.000) 1344.930 (0.000) 1583.734 (0.000) cd lm2 10.090 (0.000) 14.099 (0.000) 5.019 (0.000) 5.162 (0.000) 14.303 (0.000) 20.349 (0.000) cd lm3 2.433 (0.000) 3.806 (0.000) −3.679 (0.000) −3.688 (0.000) 1.536 (0.062) 11.765 (0.000) developing countries cd lm1 713.000 (0.000) 782.046 (0.000) 789.537 (0.000) 785.617 (0.000) 674.793 (0.000) 742.548 (0.000) cd lm2 5.693 (0.000) 7.818 (0.000) 8.048 (0.000) 7.928 (0.000) 4.517 (0.000) 6.602 (0.000) cd lm3 −2.565 (0.005) −2.906 (0.002) −2.921 (0.002) −2.892 (0.002) −1.830 (0.034) −1.494 (0.068) p values are in ( ) table 3: cips panel unit root test results models co2 gdp gdp 2 gdp3 tr developed countries level −2.066 −2.006 −1.937 −1.883 −2.156 1st difference −3.707 −2.869 −2.874 −2.859 −3.415 model contains only intercept; critical value (1%) is −2.23 level −2.272 −1.877 −1.836 −1.807 −2.640 1st difference −3.997 −3.190 −3.212 −3.203 −3.451 model contains constant and trend; critical value (1%) is −2.73 developing countries level −1.860 −1.729 −1.648 −1.641 −2.17 1st difference −3.543 −3.222 −3.081 −3.119 −3.596 model contains only intercept; critical value (1%) is −2.30 level −1.867 −2.112 −2.004 −1.962 −2.405 1st difference −3.667 −3.600 −3.523 −3.491 −3.577 model contains constant and trend; critical value (1%) is −2.81 critical values (1%) are taken from pesaran (2007) table 2b. the maximum lag length is taken as 4 and optimal lag length is determined by the schwarz information criteria acaravci and akalin: environment–economic growth nexus: a comparative analysis of developed and developing countries international journal of energy economics and policy | vol 7 • issue 5 • 201740 5.3. panel cointegration test results and the estimated long-run coefficients the unit root test results present that the integrated degree of the variables is one and this situation indicates a possible long-run cointegrating relationship among the carbon emissions per capita (co2), income per capita (gdp), and trade openness (tr). therefore, a cointegration test is performed at the next stage. the results of the westerlund–durbin–hausman panel cointegration test are presented in table 5. the results show that there is a longrun relationship between the variables for both the developed and developing countries under the assumption of homogeneity in both are heterogeneous. this means that a long-term relationship exists among the non-stationary variables. table 6 presents the results from the cce method for both the developed and developing countries. the results for the developed countries show that the findings are compatible with expectations and the literature. while the coefficients for the gdp3 and tr variables are statistically insignificant, the coefficient for the gdp variable is statistically significant and positive, and the coefficient for gdp2 variable is statistically significant and negative at a 5% level of significance. according to these results, there is evidence for validity of the ekc hypothesis in the developed countries. the level of carbon emissions first increases with income, stabilizes, and then declines. thus, there appears to be an inverted u-shaped relationship between carbon emissions per capita and real gdp per capita in the developed countries. the results for developing countries show that the coefficient of the tr variable is statistically insignificant, the coefficient of the gdp variable is significant and negative, the coefficient of the gdp2 variable is significant and positive, and the coefficient of the gdp3 variable is significant and negative at a 5% level of significance. these results indicate that the ekc hypothesis is not valid in the developing countries. there is an inverse n relationship between environmental pollution and income. the empirical results indicate that trade openness has no statistically significant impact on carbon emissions for both the developed and developing countries. this means that the increase of trade volume does not produce more carbon emissions. 6. conclusions and policy implications since the early 1970s, especially after the united nations conference on the human environment in 1972, the relationship between production and environmental concerns has been handled by different methods in different disciplines. this is because the environment is of vital importance for human life, and they are confronted with serious environmental problems. the most important of these problems are as follows: the risk of going over the environmental pollution assimilation capacity; the difficulty in return of natural balance in the environment; large-scale health problems caused by environmental pollution; rapid depletion of natural resources; global warming and climate change, and the resulting related natural disasters such as floods; the reduction of biodiversity, air pollution, and soil pollution. empirical studies on the environmental pollution–economic growth nexus explore the validity of the ekc hypothesis which states that environmental pollution will increase up to a certain threshold of income growth, and after this threshold, will begin to decrease due to the demand for a clean environment and structural and technological inputs. if the ekc hypothesis is valid, economic growth is both cause of and solution to environmental pollution. this approach is often used when arguing that countries should not compromise economic growth policies to reduce environmental effects. the ekc hypothesis is not valid in cases where economic growth that increased production is the only cause of environmental pollution. this has accelerated the search to replace the neoclassical growth strategy. especially highlighted by the 1992 unced conference in rio de janeiro, a win-win approach to understanding the appropriate account of the ecological paradigm has gained importance in recent years. therefore, the validity of the ekc hypothesis is an important issue in formulating economic growth policies for all countries. in this study, the following two samples are used: (i) 40 highincome countries (oecd members and non-members) and (ii) 33 upper middle-income countries. these countries are selected according to data available from related income groups. the results from the dynamic panel data methods are as follows: (i) the durbin–hausman cointegration test shows that there is a long-term relationship between variables. (ii) the results from the cce estimator indicate that there is evidence of validity of the ekc hypothesis in developed countries. (iii) the ekc hypothesis is not valid in the developing countries. these results show that economic growth is sufficient enough to safeguard environmental quality for developed countries. however, developing countries have not yet reached income levels high enough to be able to derive their turning points. therefore, to reduce environmental pollution that comes with economic growth, developing countries should give importance to r&d activities and institutionalization of environmental awareness. an increase in environmental awareness is imperative and developing and developed countries must not forget the fact that the natural world of tomorrow will be created today. also, our findings show that trade liberalization is not harmful for the environment in developed and developing countries. this means that the increase of trade volume will not produce more carbon emissions. despite the results obtained for the developed countries, we cannot assume that environmental betterment will continue to accompany further growth of per capita income in developed countries. so that, future studies can examine the relationship between economic growth and other pollutants. because, along with the economic growth it may increase the amount of other pollutants. the main contribution of this paper is that we avoid using econometric model that don’t taking into account cross sectional dependency. previous, studies generally use econometric models that assume that cross sections are independent and are not able to consider the cross section dependency. however, in this case, acaravci and akalin: environment–economic growth nexus: a comparative analysis of developed and developing countries international journal of energy economics and policy | vol 7 • issue 5 • 2017 41 ta bl e 4: s m it h bo ot st ra p pa ne l u ni t r oo t t es t r es ul ts d ev el op ed c ou nt ri es l ev el a 1s t d if fe re nc ea co 2 gd p gd p2 gd p3 tr co 2 gd p gd p2 gd p3 tr m ax −0 .7 01 (0 .8 99 ) −0 .3 69 (0 .9 51 ) −0 .4 26 (0 .9 31 ) −0 .4 21 (0 .9 37 ) −1 .3 54 (0 .1 43 ) −4 .4 74 (0 .0 00 ) −2 .6 58 (0 .0 00 ) 2. 80 7 (0 .0 00 ) 2. 76 6 (0 .0 00 ) −4 .2 60 (0 .0 00 ) lm 3. 75 8 (0 .1 06 ) 3. 80 9 (0 .2 07 ) 3. 62 1 (0 .2 88 ) 3. 39 6 (0 .3 72 ) 3. 02 0 (0 .4 53 ) 13 .2 01 (0 .0 00 ) 7. 23 3 (0 .0 00 ) −2 .6 61 (0 .0 00 ) 2. 65 5 (0 .0 00 ) 12 .2 93 (0 .0 00 ) m in lm 2. 14 3 (0 .2 26 ) 1. 56 8 (0 .7 47 ) 1. 51 2 (0 .7 81 ) 1. 42 4 (0 .8 36 ) 2. 44 7 (0 .1 40 ) 12 .5 30 (0 .0 00 ) 6. 71 1 (0 .0 00 ) 7. 23 5 (0 .0 00 ) 7. 08 2 (0 .0 00 ) 12 .1 60 (0 .0 00 ) w s −0 .8 87 (0 .9 08 ) −0 .5 28 (0 .9 77 ) −0 .5 45 (0 .9 73 ) −0 .4 91 (0 .9 83 ) −1 .4 71 (0 .1 99 ) −4 .6 53 (0 .0 00 ) −2 .8 73 (0 .0 00 ) −2 .8 78 (0 .0 00 ) −2 .8 79 (0 .0 00 ) −4 .4 48 (0 .0 00 ) l ev el b 1s t d if fe re nc eb co 2 gd p gd p2 gd p3 tr co 2 gd p gd p2 gd p3 tr m ax −1 .4 53 (0 .9 19 ) −1 .3 28 (0 .8 66 ) −1 .3 62 (0 .8 38 ) −1 .3 51 (0 .8 56 ) −2 .0 32 (0 .2 08 ) −4 .6 06 (0 .0 00 ) −2 .8 96 (0 .0 00 ) −2 .8 67 (0 .0 00 ) −2 .8 28 (0 .0 00 ) −4 .2 05 (0 .0 00 ) lm 4. 83 1 (0 .6 74 ) 3. 92 4 (0 .9 20 ) 3. 97 1 (0 .9 10 ) 3. 92 3 (0 .9 15 ) 5. 53 6 (0 .2 82 ) 14 .0 34 (0 .0 00 ) 8. 20 6 (0 .0 00 ) 8. 07 8 (0 .0 00 ) 7. 82 6 (0 .0 00 ) 12 .4 06 (0 .0 00 ) m in lm 3. 19 5 (0 .8 71 ) 2. 76 8 (0 .9 05 ) 2. 84 5 (0 .8 90 ) 2. 75 8 (0 .9 04 ) 4. 44 6 (0 .2 18 ) 13 .1 49 (0 .0 00 ) 7. 73 1 (0 .0 00 ) 7. 64 3 (0 .0 00 ) 7. 50 5 (0 .0 00 ) 12 .2 45 (0 .0 00 ) w s −1 .9 41 (0 .8 35 ) −1 .8 32 (0 .8 72 ) −1 .8 67 (0 .8 38 ) −1 .8 53 (0 .8 49 ) −2 .3 03 (0 .2 32 ) −4 .9 62 (0 .0 00 ) −3 .2 10 (0 .0 00 ) −3 .1 93 (0 .0 00 ) −3 .1 74 (0 .0 00 ) −4 .5 20 (0 .0 00 ) d ev el op in g co un tr ie s l ev el a 1s t d if fe re nc ea co 2 gd p gd p2 gd p3 tr co 2 gd p gd p2 gd p3 tr m ax −0 .7 09 (0 .9 07 ) −0 .1 92 (1 .0 00 ) −0 .4 26 (0 .9 31 ) −0 .4 21 (0 .9 37 ) −1 .2 42 (0 .1 01 ) −4 .9 00 (0 .0 00 ) −3 .5 73 (0 .0 00 ) 2. 80 7 (0 .0 00 ) 2. 76 6 (0 .0 00 ) −4 .5 09 (0 .0 00 ) lm 2. 75 9 (0 .7 28 ) 1. 00 0 (0 .9 52 ) 3. 62 1 (0 .2 88 ) 3. 39 6 (0 .3 72 ) 3. 57 7 (0 .1 95 ) 14 .6 34 (0 .0 00 ) 10 .5 01 (0 .0 00 ) −2 .6 61 (0 .0 00 ) −2 .6 55 (0 .0 00 ) 13 .0 05 (0 .0 00 ) m in lm 1. 91 2 (0 .4 25 ) 1. 52 0 (0 .8 01 ) 1. 51 2 (0 .7 81 ) 1. 42 4 (0 .8 36 ) 2. 64 4 (0 .0 42 ) 13 .6 80 (0 .0 00 ) 9. 76 8 (0 .0 00 ) 7. 23 5 (0 .0 00 ) 7. 08 2 (0 .0 00 ) 12 .7 58 (0 .0 00 ) w s −0 .8 68 (0 .9 29 ) −0 .3 07 (1 .0 00 ) −0 .5 45 (0 .9 73 ) −0 .4 91 (0 .9 83 ) −1 .5 35 (0 .0 49 ) −5 .1 24 (0 .0 00 ) −3 .8 23 (0 .0 00 ) −2 .8 78 (0 .0 00 ) −2 .8 79 (0 .0 00 ) −4 .7 32 (0 .0 00 ) l ev el b 1s t d if fe fe nc eb co 2 gd p gd p2 gd p3 tr co 2 gd p gd p2 gd p3 tr m ax −1 .7 63 (0 .4 35 ) −1 .5 52 (0 .7 36 ) −1 .5 58 (0 .7 28 ) −1 .5 93 (0 .6 93 ) −2 .1 28 (0 .0 43 ) −4 .9 25 (0 .0 00 ) −3 .8 00 (0 .0 00 ) −3 .8 03 (0 .0 00 ) −3 .7 62 (0 .0 00 ) −4 .5 47 (0 .0 00 ) lm 4. 96 4 (0 .5 74 ) 4. 19 1 (0 .9 23 ) 4. 10 5 (0 .9 36 ) 4. 14 8 (0 .9 34 ) 6. 36 8 (0 .0 42 ) 15 .1 05 (0 .0 00 ) 11 .5 17 (0 .0 00 ) 11 .4 66 (0 .0 00 ) 11 .2 51 (0 .0 00 ) 13 .4 26 (0 .0 00 ) m in lm 1. 81 2 (0 .5 14 ) 3. 14 5 (0 .8 58 ) 3. 21 6 (0 .8 32 ) 3. 37 8 (0 .7 49 ) 5. 19 6 (0 .0 18 ) 14 .0 23 (0 .0 00 ) 10 .7 96 (0 .0 00 ) 10 .7 69 (0 .0 00 ) 10 .6 00 (0 .0 00 ) 13 .1 53 (0 .0 00 ) w s −2 .1 74 (0 .3 36 ) −1 .8 82 (0 .8 62 ) −1 .8 94 (0 .8 54 ) −1 .9 25 (0 .8 11 ) −2 .4 68 (0 .0 22 ) −5 .2 99 (0 .0 00 ) −4 .1 17 (0 .0 00 ) −4 .1 17 (0 .0 00 ) −4 .0 74 (0 .0 00 ) −4 .8 98 (0 .0 00 ) a m od el s co nt ai n on ly c on st an t. b m od el s co nt ai n co ns ta nt a nd tr en d. p v al ue s ar e in ( ). t he m ax im um la g le ng th is ta ke n as 4 , a nd th e op tim al la g le ng th is d et er m in ed b y th e ge ne ra l t o sp ec ifi c ap pr oa ch . p ro ba bi lit y va lu es a re o bt ai ne d fr om 50 00 b oo ts tr ap d is tr ib ut io n acaravci and akalin: environment–economic growth nexus: a comparative analysis of developed and developing countries international journal of energy economics and policy | vol 7 • issue 5 • 201742 table 5: panel cointegration test results variables developed countries developing countries t stat. (nw) p value t stat. (nw) p value durbin-h group stat. 128.629 0.000 1356.295 0.000 durbin-h panel stat. 12.241 0.000 3.908 0.000 table 6: the estimated long-run coefficients for the ekc model variables developed countries developing countries coefficients t stat (nw) coefficients t stat (nw) gdp 50.4683 2.0989 −101.9750 −3.3968 gdp2 −10.5701 −1.7850 29.9381 3.4916 gdp3 0.7278 1.5025 −2.8935 −3.5465 tr 0.0501 0.7160 −0.0872 −1.5952 critical values (5%) ±1.645 ±1.645 ekc: environmental kuznets curve traditional panel estimator can produce misleading or even inconsistent parameters (chudik and pesaran, 2013). while, there is no study in the literature using sample types and econometric models as same as this paper, it is possible to say that our findings are consistent with moomaw and unhruh (1997), ang (2007), shahbaz et al. (2013), mensah (2014), ahmed et al. (2016). on the contrary, our findings are not consistent with he and richard (2009), narayan and narayan (2010), farhani and rejeb (2012), mamun et al. (2014), dogan and turkekul (2016), saidi and mbarek (2017). references acaravci, a., ozturk, i. (2010), on the relationship between energy consumption, co2 emissions and economic growth in europe. energy, 35(12), 5412-5420. agras, j., chapman, d.a. (1999), dynamic approach to the environmental kuznets curve hypothesis. ecological economics, 28(2), 267-177. ahmed, k., shahbaz, m., kyophilavong, p. (2016), revisiting the emissions-energy-trade nexus: evidence from the newly ındustrializing countries. environmental science and pollution research, 23(8), 7676-7691. ang, j.b. (2007), co2 emissions, energy consumption, and output in france. energy policy, 35(10), 4772-4778. barret, s., graddy, k. (2000), freedom growth and environment. environment and development economics, 5(4), 433-456. breusch, t.s., pagan, a.r. (1980), the lagrange multiplier test and ıts applications to model specification in econometrics. journal of the rewiev of economic, 47(1), 239-253. chudik, a., pesaran, m.h. (2013), common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. journal of econometrics, 188(2), 393-420. cole, m.a. (2004), trade, the pollution haven hypothesis and the environmental kuznets curve: examining the linkages. ecological economics, 48(1), 71-81. de bruyn, s.m., heintz, r.j. (1999), the environmental kuznets curve hypothesis. in: van den bergh, c.j.m., editor. handbook of environmental and resource economics. cheltenham, uk: edward elgar. de bruyn, s.m., van den bergh, b.j.c., opschoor, j.b. (1998), economic growth and emissions: reconsidering the empirical basis of environmental kuznets curves. environmental kuznets curves. ecological economics, 25(2), 161-175. dijkgraaf, e., vollebergh, h.r.j. (2001), a note on testing for environmental kuznets curves with panel data nota di lavoro, fondazione eni enrico mattei. dinda, s. (2004), environmental kuznets curve hypothesis: a survey. ecological economics, 49(4), 431-455. dinda, s., coondoo, d., pal, m. (2000), air quality and economic growth: an empirical study. ecological economics, 34(3), 409-423. dogan, e., turkekul, b. (2016), co2 emissions, real output, energy consumption, trade, urbanization and financial development: testing the ekc hypothesis for the usa. environmental science and pollution research, 23(2), 1203-1213. farhani, s., rejeb, j.b. (2012), energy consumption, economic growth and co2 emissions: evidence from panel data for mena region. international journal of energy economics and policy, 2(2), 71-81. gill, a.r., viswanathan, k.k., hassan, s. (2017), is environmental kuznets curve still relevant? international journal of energy economics and policy, 7(1), 156-165. grossman, g.m., krueger, a.b. (1991), environmental impacts of a north american free trade agreement no. w3914, national bureau of economic research. hadri, k. (2000), testing for stationarity in heterogeneous panel data. the econometrics journal, 3(2), 148-161. han, c., lee, h. (2013), dependence of economic growth on co2 emissions. journal of economic development, 38(1), 47-57. he, j., richard, p. (2009), environmental kuznets curve for co2 in canada. cahier de recherche/working paper no. 9, 13. im, k.s., pesaran, m.h., shin, y. (2003), testing for unit roots in heterogeneous panels. journal of econometrics, 115(1), 53-74. johansson, p.o., kriström, b. (2008), on a clear day you might see an environmental kuznets curve. environmental and resource economics, 37(1), 77-90. kaufman, r.k., davidsdottir, b., garnham, s., pauly, p. (1998), the determinants of atmospheric so2 concentrations: reconsidering the environmental kuznets curve. ecological economics, 25(2), 209-220. levin, a., lin, c.f., chu, c.s.j. (2002), unit root tests in panel data: asymptotic and finite-sample properties. journal of econometrics, 108(1), 1-24. leybourne, s.j. (1995), testing for unit roots using forward and reverse dickey-fuller regressions. oxford bulletin of economics and statistics, 57(4), 559-571. lieb, c.m. (2002), the environmental kuznets curve-a survey of the empirical evidence and of possible causes, discussion paper series no. 390, switzerland. lopez, r., islam, a. (2008), trade and the environment. the princeton encyclopedia of the world economy, 24, 22-23. mamun, m.a., sohag, k., mia, m.a.h., uddin, g.s., ozturk, i. (2014), regional differences in the dynamic linkage between co2 emissions, sectoral output and economic growth. renewable and sustainable energy reviews, 38, 1-11. mason, r., swanson, t.a. (2003), kuznets curve analysis of ozonedepleting substances and the ımpact of the montreal protocol. oxford economic papers, 55(1), 1-24. menegaki, a.n., tsagarakis, k.p. (2015), rich enough to go renewable, but too early to leave fossil energy? renewable and sustainable energy reviews, 41, 1465-1477. mensah, j.t. (2014), carbon emissions, energy consumption and output: a threshold analysis on the causal dynamics in emerging african economies. energy policy, 70(14), 172-182. moomaw, w.r., unruh, g.c. (1997), an alternative analysis of apparent ekc-type transitions. ecological economics, 25(2), 221-229. acaravci and akalin: environment–economic growth nexus: a comparative analysis of developed and developing countries international journal of energy economics and policy | vol 7 • issue 5 • 2017 43 narayan, p.k., narayan, s. (2010), carbon dioxide emissions and economic growth: panel data evidence from developing countries. energy policy, 38(1), 661-666. nazlıoglu, s., lebe, f., kayhan, s. (2011), nuclear energy consumption and economic growth in oecd countries: cross-sectionally dependent heterogeneous panel causality analysis. energy policy, 39(10), 6615-6621. ozturk, i., al-mulali, u. (2015) investigating the validity of the environmental kuznets curve hypothesis in cambodia. ecological indicators, 57, 324-330. ozturk, i., al-mulali, u., saboori, b. (2016), investigating the environmental kuznets curve hypothesis: the role of tourism and ecological footprint. environmental science and pollution research, 23(2), 1916-1928. pacini, h. (2010), carbon emissions and development paths: a discussion of the environmental kuznets curve. energy and climate studies, unctad public symposium geneva: united nations. panayotou, t. (1993), empirical tests and policy analysis of environmental degradation at different stages of economic development no. 992927783402676, international labour organization. panayotou, t. (1997), demystifying the environmental kuznets curve: turning a black box ınto a policy tool. environment and development economics, 2(4), 465-484. pantula, s.g., gonzalez-farias, g., fuller, w.a. (1994), a comparison of unit-root test criteria. journal of business and economic statistics, 12(4), 449-459. pesaran, m.h. (2004), general diagnostic tests for cross section dependence in panels, cambridge working papers in economics no. 435, university of cambridge, and cesifo working paper series no. 1229. pesaran, m.h. (2006), estimation and ınference in large heterogeneous panels with a multifactor error structure. journal of econometrica, 74(4), 967-912. pesaran, m.h. (2007), a simple panel unit root test in the presence of cross-section dependence. journal of applied econometrics, 22(2), 265-212. saidi, k., mbarek, m.b. (2017), the ımpact of ıncome, trade, urbanization, and financial development on co2 emissions in 19 emerging economies. environmental science and pollution research, 24(14), 12748-12757. sanglimsuwan, k. (2011), corbondioxide emissions and economic growth: an econometric analysis. international research journal of finance and economics, 67(1), 97-102. selden, t.m., song, d. (1994), environmental quality and development: is there a kuznets curve for air pollution? journal of environmental economics and environmental manamegent, 27(2), 147-162. shafik, n., bandyopadhyay, s. (1992), economic growth and environmental quality: time series and cross country evidence, world development working paper wps 904. washington, dc: world bank. shahbaz, m., dube, s., ozturk, i., jalil, a. (2015), testing the environmental kuznets curve hypothesis in portugal. international journal of energy economics and policy, 5(2), 475-481. shahbaz, m., mutascu, m., azim, p. (2013), environmental kuznets curve in romania and the role of energy consumption. renewable and sustainable energy reviews, 18, 165-173. smith, v., leybourne, s., kim, t.h. (2004), more powerful panel unit root tests with an application to the mean reversion in real exchange rates. journal of applied econometrics, 19(2), 147-170. solo, v. (1984), the order of differencing in arima models. journal of the american statistical association, 79(388), 916-921. song, t., zheng, t., tong, l. (2008), an empirical test of the environmental kuznets curve in china: a panel cointegration approach. china economic review, 19(2008), 381-392. stern, d.i. (2004), the rise and fall of the environmental kuznets curve. world development, 32(8), 1419-1439. stern, d.i., common, m.s. (2001), is there an environmental kuznets curve for sulfur? journal of environmental economics and management, 41(2), 162-178. stokey, n.l. (1998), are there limits to growth? international economic review, 39(1), 1-31. tang, c.f., tan, b.w., ozturk, i. (2016), energy consumption and economic growth in vietnam. renewable and sustainable energy review, 54, 1506-1514. the world bank. (2014), world development indicators online. avaible from: http://www.data.worldbank.org/data-catalog/worlddevelopment-indicators. tiwari, a.k., shahbaz, m., hye, q.m.a. (2013), the environmental kuznets curve and the role of coal consumption in india: cointegration and causality analysis in an open economy. renewable and sustainable energy reviews, 38, 519-527. torras, m., boyce, j.k. (1998), income ınequality and pollution: a reassement of the environmental kuznets curve. ecological economics, 25(2), 147-160. tutulmaz, o. (2015), environmental kuznets curve time series application for turkey: why controversial results exist for similar models? renewable and sustainable energy reviews, 50, 73-81. westerlund, j. (2008), panel cointegration tests of the fisher effect. journal of applied econometrics, 23(2), 193-223. international journal of energy economics and policy vol. 1, no. 3, 2011, pp. 59-68 issn: 2146-4553 www.econjournals.com multivariate cointegration and causality between exports, electricity consumption and real income per capita: recent evidence from japan janesh sami department of economics, banking and finance college of business, hospitality and tourism studies fiji national university, nasinu, fiji islands. email: janesh.sami@fnu.ac.fj abstract: the current literature on the relationship between electricity, exports and economic growth is mixed. this paper examines the relationship between exports, electricity consumption and real income per capita in japan using time series data from 1960-2007. we applied bounds testing procedure developed by pesaran et al., (2001) and found that there is cointegrating relationship between electricity consumption, exports and economic growth. on establishing cointegration, the causal relationship electricity consumption, exports and economic investigation was investigated within a vector error correction model (vecm) framework. we found that in the long run, there is causality from exports and real gdp per capita to electricity consumption. keywords: exports; electricity consumption; real income per capita; japan jel classification: q43, c32 1. introduction energy security is now seen an important perquisite for sustainable economic development. many countries are now implementing a number of measures to ensure energy security and reduce greenhouse gas emissions. special focus of the international community has been drawn to apec region (asia pacific economic cooperation) where world’s some of fastest growing economies are located. these economies are now implementing number of programs to improve efficiency in energy use. these include promotion of good energy practices and encouraging investment in energy efficient technologies. although, today japan is the world’s third largest economy after usa and china, world bank (2010), it has limited amount of energy resources. japan, infact imports about 97% of energy resources from overseas,(ministry of economy, trade and industry, japan, 2010). given its limited energy resources , a report by apec revealed that japan in 2008 imported 99% of oil,98% of its coal and 96% of gas. it has about some 355million tonnes of coal reserves and 20.9 billion cubic metres of gas reserves, apec (2010).furthermore; japan has some 277.671 gw (gigawatt) of installed generating capacity. electricity is generated from thermofuel (70.5%), hydro (6.5%) and nuclear (20.1%), others (2.8%), energy data and modelling center (2009). despite, the limited energy resources, energy consumption in japan’s commercial, residential and transport sector is rising due to a number of factors such as changing life style and higher rate of vehicle ownership. compared to other countries such as germany, france, us, india, uk, china, canada and russia, energy sufficiency ratio in japan is low (ministry of economy, trade and industry, japan, 2010). the japanese government is now implementing a number of measures to achieve energy security and reduce carbon emission. for example, in 2006 basic law on energy policy was enacted. later on, in 2008, the government introduced new national energy strategy in light of global developments. this strategy was heavily focused on achieving energy security. under this strategy, the government targeted to improve energy efficiency to 30%, increase share of electric power generated from nuclear energy to 30-40%, cut down the oil dependency ratio to about 80% and increase domestic investment in oil exploration and related development projects. in 2010, the government further modified the energy international journal of energy economics and policy, vol. 1, no. 3, 2011, pp.59-68 60 plan by adding two important principles that is “energy based economic growth” and “reform of the energy industrial structure”. these two new principles add to already existing principles of energy security, economic efficiency and environmental suitability. the revised strategic energy plan sets out a number of targets for 2030.these includes doubling the energy self sufficiency ratio and energy independence ratio to 36% and 70% respectively, reducing carbon emission by the residential sector by 50% and enhancing energy efficiency in the industrial sector. japan electricity price has been amongst the highest of the developed countries (apec, 2010) and this is possibly explains a series of reforms in the electricity sector. in earlier study by oced (1998) found that japan has highest electricity prices in oced. table 1. electricity power consumption (kwh per capita) for selected asian countries japan india china malaysia singapore phillipines 1971-1975 3,848 105 171 370 1,497 283 1976-1980 4,601 134 243 573 2,315 336 1981-1985 4,985 172 318 786 3,068 341 1986-1990 5,919 242 446 1,031 4,361 339 1991-1995 6,953 328 663 1,621 5,551 359 1996-2000 7,735 389 890 2,533 6,974 468 2001-2005 7,964 438 1,401 3,037 8,041 554 source: wdi (2010) five year average table 1 compares the electricity power consumption (kwh per capita) of selected asian countries. it can be noted from the table that, japan’s electricity power consumption (kwh per capita) is quite high compared to other large economies such india and china. an important implication of this is that japanese government should devise policies to reduce electricity wastage and invest in alternative sources of electricity generation. the recent damage to nuclear power plants due to earthquake can put considerable pressure on the japanese economy to maintain its growth performance. according to international energy agency (2011), the damage to the power sector has been greatest in the areas of tokyo electric power company (tepco) and that of tohoku electric power company (tohoku-epco).the report further found that some 9.7gw of tepco, tohokuepco and japan atomic power nuclear plant capacity was shut down due to the earthquake. rolling blackouts of 3 hours in 5 areas have been announced by tokyo electric power company. in the refining sector, 6 refineries with a capacity of 1.4mb/d (millions of barrels per day) were shut down. these 6 refineries accounted for about 30% of japan’s total refinery capacity, iea (2011). policies to address any possible energy crisis must implement urgently to avoid any adverse effect on the export sector. the electricity industry in japan is controlled by 10 vertically integrated regional companies, dominated by tokyo electric (tepco) and kansai power, thomas (2006). the efforts of the government to liberalise the industry is yet have a major impact. any future electricity shortage can cause serious disruption to production of goods in export sector and hamper economic performance. nuclear power plants have been important source of electricity in japan. though there are some safety issues associated with this form of power generation, nuclear power generation does not produce greenhouse gases and considered an important tool in address in energy supply stability, environmental protection and economic efficiency. further, nuclear energy is recognized now as an important source of electricity.infact, promotion of nuclear energy is one pillars of japan’s energy plan. the recent earthquake however, has raised questions over safety issues with such forms of energy indicating that policies that promote such forms of energy should equally focus on the socio – economic effects. the recent natural disaster in japan that shocked the entire world is yet to show its full effects on the japanese economy, neigbouring asian economics and other developed economies. while some believe that the japanese economy is strong and can rebound quickly, such convincing statements are best evaluated against empirical evidence. in a report by imf (2011) has warned that neigbouring asian economies are likely to be affected through trade channels. it known that damage has been done to nuclear power plants which is an essential source of electricity generation in japan. in light of these developments, it is important to understand the relationship between electricity consumption and economic growth. multivariate cointegration and causality between exports, electricity consumption and real income per capita: recent evidence from japan 61 bulk of earlier papers published in top energy journals has tried to establish the relationship between electricity consumption and economic growth within a bivariate regression, see apergis and payne (2010) for an excellent review. however, in the recent years, the two variable regressions has come under fire from researchers as it is argued that estimated relationship suffers from omitted variable bias and causality tests from bivariate models can be misleading, see lean and smyth (2010) for more discussion on this. furthermore, in a study by wolde-rufael (2009) found that causality results for number of african changed when other variables such as capital and labor were included. since earlier studies examined cointegration and causality within a bivariate framework, this probably explains why even today, the question of how important electricity is for economic growth remains open. we specifically examine the relationship between electricity consumption and economic growth, including exports as an additional variable. exports seem to a very important variable and electricity consumption can influence the performance of the export sector. the objective of this paper is twofold. first of all, we aim to establish if the three variables are cointegrated; implying that they move together in the long run. this would be interesting finding in light of recent development in cointegration literature. it is of interest to know if electricity consumption and real income per capita share a common trend in the long run. secondly, we investigate the causal relationship between exports, electricity consumption and economic growth within a vector error correction model framework. it is expected that by including exports as an additional variable in the analysis, one can get a better picture of causal relationship between electricity consumption and economic growth. if there is uni-directional causality from electricity consumption to economic growth, then growth hypothesis is supported, this would imply that electricity consumption has significant influence on economic growth directly. thus policies that reduce electricity consumption can have adverse impact on economic growth. if there is unidirectional causality from economic growth to electricity consumption, then conservation hypothesis is supported and policies that reduce electricity consumption will not have adverse impact on economic growth. evidence of bidirectional causality between electricity consumption and economic growth supports feedback hypothesis. in this case, policies that reduce electricity consumption shall adversely affect economic growth and these economic fluctuations shall be transmitted back to electricity consumption. finally, if there is no causality between electricity consumption and economic growth, then this implies that electricity conservation policies will not affect economic growth. these findings can be use to policymakers in trade as well as energy. in this study, we employ bound testing procedure to test if there is cointegrating relationship between the variables. the advantage of bound testing procedure is that, it can be applied without knowing the stationary properties of the variables. thus it, spares us from pre-testing for unit roots. moreover, bounds testing procedure is well suited to small size. the rest of the paper is organized as follows: section 2 gives an overview of empirical literature. section 3 explains the data sources and results of unit root tests. section 4 examines the empricial methodology and empricial results. section 5 discusses conclusions and makes some important policy recommendations. 2. review of empricial literature binh (2011) examined the nexus between energy consumption and economic growth in vietnam and found that there is cointegrating relationship between energy consumption and economic growth. he also finds evidence of uni-directional causality running from electricity consumption to economic growth. adom (2011) finds evidence of uni-directional causality running from economic growth to electricity consumption, thus supporting the growth-led energy hypothesis in ghana. payne (2010) surveys the literature on causal relationship between electricity consumption and economic growth and concludes the evidence on causal relationship between electricity consumption and economic growth is mixed. his analysis show that 31.15% of studies supported the neutrality hypothesis, 27.87% of the studies supported conservation hypothesis; 22.95% supported the growth hypothesis; and 18.03% supported the feedback hypothesis. smyth and lean (2010a) examined the causal relationship between aggregate output, electricity consumption, exports, labor and capital in a multivariate model for malaysia by employing modified version of the granger causality test proposed by toda and yamamoto (1995) and dolado and lütkepohl (1996) -tydl. they found evidence in support of bi-directional causality between aggregate output and electricity consumption and exportinternational journal of energy economics and policy, vol. 1, no. 3, 2011, pp.59-68 62 led growth hypothesis in malaysia. smyth and lean (2010b) used time series data from 1970-2008 to study the causal relationship between economic growth, electricity generation, exports and prices. they found evidence of uni-directional causality running from economic growth to electricity consumption. yoo and kwak 2010) find evidence of long run relationship between electricity consumption and economic growth in venezuela and columbia. lorde et al (2010), finds a long run relationship between electricity consumption and economic growth in barbados.chandran, sharma and madhavan (2010) examine the relationship between electricity consumption and growth in malaysia, including price. they find evidence of long run relationship between the variables. smyth and lean (2010c) apply johansen fisher panel cointegration test and finds that there is a long run relationship between carbon dioxide emission, electricity consumption and output in asean countries. ciarreta and zarraga (2010) applies panel data methodology to examine the long run relationship between economic growth and electricity consumption in 12 european countries. their study included energy prices as an additional variable and found evidence that three series move together in the long run. acaravi and ozturk (2010) do not find evidence of cointegration between electricity consumption per capita and real gdp per capita in 15 transition countries. ozturk and acarvci (2011) investigate the short-run and long-run causality issues between electricity consumption and economic growth in the selected 11 middle east and north africa (mena) countries by using autoregressive distributed lag (ardl) bounds testing approach of cointegration and vector error-correction models for 1971-2006 period. the cointegration test results show that there is no cointegration between the electricity consumption and the economic growth in three of the seven countries (iran, morocco and syria). thus, causal relationship cannot be estimated for these countries. however, the cointegration and causal relationship is found for four countries (egypt, israel, oman and saudi arabia). the overall results indicate that there is no relationship between the electricity consumption and the economic growth in most of the mena countries. further evidence indicates that policies for energy conservation can have a little or no impact on economic growth in most of the mena countries. narayan and smyth (2009) find positive effects of electricity consumption and exports on output in a panel of six middle eastern countries.abosedra et al(2009) finds long run relationship between electricity consumption and real gdp. odhiambo (2009) finds that electricity, employment and economic growth in south africa. akinlo (2009) find evidence of long run relationship between electricity consumption and economic growth. ghosh (2007) finds that electricity supply, employment and real gdp in india are cointegrated. narayan and singh (2007) finds that electricity consumption, employment and real gdp are cointegrated in fiji.ho and siu (2007) finds a long run relationship between electricity consumption and gdp for hongkong.mozumder and marathe (2007) found that there is unidirectional causality from per capita gdp to per capita electricity consumption in bangladesh. tang (2008) studied the relationship between electricity consumption and economic growth in malaysia and did not find any evidence of cointegration. yoo (2006) also did not find any evidence of cointegration between electricity consumption and economic growth in asean countries. altinay and karagol (2005) find evidence of uni-directional causality running from electricity consumption to gdp for turkey. lee and chang (2005) find similar evidence for taiwan. narayan and smyth (2005) find that electricity consumption, employment and real income are cointegrated. however, other studies have found evidence of unidirectional running from economic growth to electricity consumption. these include ghosh (2002) for india, hatemi and irandoust (2005) for sweden. other studies have found evidence of uni-directional causality running from electricity consumption. shiu and lam (2004) found that electricity consumption and economic growth in china are cointegrated. yuan et al., (2007) finds that electricity consumption and economic growth are cointegrated. wolde-rufael (2006) finds mixed evidence on causal relationship between electricity consumption and real gdp per capita. squalli (2007) finds evidence of long run relationship between electricity consumption and economic growth for all organization of petroleum exporting countries using bound tests. the author also found evidence of importance of electricity consumption for economic growth in indonesia, iran, nigeria, qatar and venezuela. for a detailed literature survey on energy consumption-economic growth nexus, see the study by ozturk (2010). multivariate cointegration and causality between exports, electricity consumption and real income per capita: recent evidence from japan 63 3. data sources and unit roots tests we sourced data for the study from world development indicators (2010).all variables were transformed into natural logarithm in order to avoid the problem of heteroscedasticity and obtain elasticities. the three variables we used in the study were real income per capita, electricity consumption (kwh per capita) and exports covered for the period 1960-2007.we start our analysis by examining the unit root properties of the data series. a series is said to be stationary if it has a constant mean, variance and auto covariance. while it is known that, bound testing procedure does not require pretesting for unit root, in order to conduct granger causality test the variables must be i(1).while regressing a nonstationary time series on another nonstationary time series may produce a spurious regression, if there is long run relationship between the variables , then such regression may not be spurious but meaningful. regardless , we conduct the unit root test to ascertain the stationary properties for conducting granger causality test and ensure that variables are not i(2)the augmented dickey fuller test corrects for higher order serial correlation through lagged difference terms. on the other hand, a phillips-perron test makes non-parametric correction for residual serial correlation monte carlo studies have indicated that phillips-perron test has greater power than standard adf test (see for example, banerjee et al, 1993; choi,1992). unit root tests the adf test involves estimating the following equations using least squares: (2) (1)             1 1 1 1 t ttitt t ttitt uyyy uyyty where yt is the variable tested for unit root; ρ is the lag length; t is the time trend variable while, ∆ is the difference operator and δ is the constant term. the lag length for estimating the equation is estimated using lag length that minimizes aic. the null hypothesis is that the series is non stationary (it contains unit roots).the test statistics that is computed needs to be compared critical values that provided in mackinnon (1991).on other hand, phillips and perron (1988) test estimating a nonaugmented version of original dickey fuller equation and modifying the t-ratio so that serial correlation does not affect the asymptotic distribution of the test statistics. to conserve space, the results are not reported but can be obtained from the author. regardless, we found all variables are i(1). 4. empirical methodology and results 4.1 cointegration analysis we start our empirical exercise by first establishing if exports and electricity consumption and real income per capita are cointegrated. bound testing procedure developed by pesaran (1995, 1999, and 2001) is used for this purpose. this is considered essential as evidence of cointegrating relationship rules out the possibility of spurious regression. bound testing procedure performs well in studies that have small sample size. another interesting fact about this model is that it can estimate long run and short run components of model simultaneously (narayan and narayan, 2006). furthermore, instead of imposing restriction and deciding on the dependent variable, the ardl method distinguishes between dependent and independent variable through usual f-tests. furthermore, as noted by narayan (2004), the unrestricted equilibrium correction model is likely to have superior statistical properties compared to engle-granger method, as it does not push short run dynamics into the residual terms (pattichis 1999; banerjee et al., 1993; banerjee et al., 1998). in order to test for cointegration using bounds testing procedure, we firstly estimated the following unrestricted error correction model using ordinary least squares. international journal of energy economics and policy, vol. 1, no. 3, 2011, pp.59-68 64 (5) (4) (3) εin x in eδin yβxδin eδin δyδin βαδin x εin x in eδin yβxδin eδin δyδin βαδin e εin x in eδin yβxδin eδin δyδin βαδin y tt-1i t-1it-1it-i n 1i it-i n 1i it-i n 1i it tt-1i t-1it-1it-i n 1i it-i n 1i it-i n 1i it tt-1i t-1it-1it-i n 1i it-i n 1i it-i n 1i it                   in equations above, ∆ is the difference operator; inyt is logged real income per capita; in et is logged electricity consumption (kwh per capita); in xt is logged exports. we then conducted the usual f-test for cointegration .this involves testing the null hypothesis of 00  iiih : against the alternative hypothesis that atleast one of them is not equal to zero. the computed f-statistics from the test is then compared with critical value from narayan (2005). if the computed f-statistics exceeds critical value, then the null hypothesis that there is no long run relationship can rejected at 1% significance level. it can note that if the null hypothesis is rejected at 1% significance level, then it will surely be rejected at 5 % and 10% significance level. we used sbc to select the lag length. table 2. bounds test to cointegration dependent variable without deterministic trend with deterministic trend )inx,ineiny(f tttstats 7.2834*** 5.9974** )inx,inyine(f tttstats 4.2150* 4.1659* )iny,ineinx(f tttstats 0.0671 1.6912 note: acritical values were extracted from narayan (2005). table case ii: restricted intercept and no trend, case iv: unrestricted intercept and restricted trend.*,** and ***indicates significance at 10% ,5% and 1% respectively . the f-test is conducted considering all three variables as possible dependent variable .this approach allows us to identify which variable should be the dependent variable should there be a cointegrating relationship. it also allows us to identify the “long run forcing variables”. following narayan and smyth (2006), we included trend in the unrestricted error correction model. all the result from f-test is presented in table 2. we are able to find the evidence of cointegration relationship between the variables when real gdp per capita as well as electricity consumption per capita is considered the dependent variable. since our objective was to examine cointegration relationship, we do not proceed further except to examine the causal relationship between the three variables. 4.2 granger causality testing according to granger (1987), if a pair of i(1) series are cointegrated, then there must a unidirectional causality running in either way. if the exports, electricity consumption and real income per capita are not cointegrated, the causality can be investigated by estimating vector autoregressive (var) in first differences form. however, since the three variables are non-stationary and become stationary after first differencing and are cointegrated, then granger causality test is conducted with inclusion of lagged error correction term (ect). this ect is obtained from the long run relationship. this requires estimating a vector error correction model as given below. in equations above, ∆ is the difference operator; inyt is logged real income per capita; in et is logged electricity consumption(kwh per capita); in xt is logged exports;ectt-1 is lagged error correction term from cointegrating relationship. for the each of the above equation, the change in the dependent variable is caused by its lags as well as previous period’s disequilibrium in level, ectt-1 .given this specification, the presence of short run and long run causality can easily be investigated. we consider the first equation. multivariate cointegration and causality between exports, electricity consumption and real income per capita: recent evidence from japan 65 (8) (7) (6) tt i tii i tih i tigt tt i tif i tie i tidt tt i tic i tib i tiat ectinxineinyinx ectinxineinyine ectinxineinyiny 313 111 212 111 111 111                   the short-run causal effects can be conducting the f-test of the lagged values of exports and electricity consumption. if exports and electricity consumption are statistically insignificant at say 5% level, then this implied both exports and electricity consumption do not granger cause gdp per capita in the short run. furthermore, the statistical significance of ectt-1 implies presence of long run causality running from exports and electricity consumption to gdp per capita in the long run. the coefficient of lagged ect measures the speed at which dependent variable adjusts to changes in independent variables before converging to its long run level. the estimated coefficient is expected to carry negative sign. table 3 shows that in the long run, there is long run causality running from real gdp per capita to electricity consumption per capita at 5% level. in the short run, there is causality running from exports and electricity consumption per capita to real gdp per capita at 5% and 1% significance level respectively. furthermore, in the short run, there is causality running from real gdp per capita and electricity consumption per capita to exports at 1% significance level. this is indicative of the fact that there causal impact of electricity consumption on exports. we thus think that any disruption in the electricity service can have a causal impact on exports in the short run only. the results also imply that in the short run causality running from real gdp per capita to electricity consumption at 5%.our results differ from narayan and prasad (2008), who found there is no causality between electricity consumption and economic growth in japan. table 3. granger causality results dependent variable sources of causation(independent variables) short run long run ∆iny ∆inx ∆ine ∆iny 4.5382(0.604)** 6.473(0.370)*** -0.052[-0.4222] ∆inx 10.2926(0.113)*** 9.4998(0.147)*** ∆ine 4.0051(0.261)** 2.561(0.464) -0.26755[-2.1322]** note: figures in square brackets are t-statistics, while those in usual brackets are p-values.*** and ** indicates statistical significance at 1% and 5% respectively. 5. conclusions and policy recommendations in this paper, we have examined the relationship between exports, electricity consumption and real income per capita in japan using time series data from 1960-2007.based on our empirical analysis, we are able to find evidence that that exports, electricity consumption and real income per capita are cointegrated. we also found evidence of causality running from real gdp per capita to electricity consumption per capita in the short run as well as in the long run, thus supporting the conservation hypothesis. the government needs to remember the importance of electricity management program to reduce electricity wastage. the government allocates more resources to the development of new sources of energy and ensures sustainability of electricity use. investment in energy infrastructure is important to avoid adverse effects of electricity crisis on real income per capita. promoting further competition the electricity industry can reduce cost of electricity and reduce international journal of energy economics and policy, vol. 1, no. 3, 2011, pp.59-68 66 cost of production, fostering more investment in export sector. we hope future research will examine the relationship between electricity consumption and economic growth using other variables, such labor supply or foreign direct investment. references abosedra, s., a. dah, and s. ghosh, 2008. electricity consumption and economic growth: the case of lebanon. applied energy 86, 429-432. acaravci, a., ozturk, i. 2010. electricity consumption-growth nexus: evidence from panel data for transition countries. energy economics 32, 604-608. adom, p.k. 2011. electricity consumption-economic growth nexus: the ghanaian case. international journal of energy economics and policy 1(1), 18-31. akinlo, a.e. 2009. electricity consumption and economic growth in nigeria: evidence from cointegration and co-feature analysis. journal of policy modeling31, 681-693. altinay, g., karagol, e., 2005. electricity consumption and economic growth: evidence from turkey. energy economics, 27, 849–856. apec energy overview, 2010, the institute of energy economics. japan. banerjee, a., dolado, j.j., mestre, j. 1998. error-correction mechanism tests for cointegration in single-equation framework. journal of time series analysis .19(3), 267-83. banerjee, a, dolado,j.j,galbraith,w.,hendry,d.f. “cointegration, error correction and the econometric analysis of nonstationary data. oxford university press, oxford. binh, p.t. 2011. energy consumption and economic growth in vietnam:threshold cointegration and causality analysis. international journal of energy economics and policy,1,1-17. chandran, v.g.r., s. sharma, and madhavan, k. 2010. electricity consumption-growth nexus: the case of malaysia. energy policy 38, 606-612. chang,t., fang,w, wen,l.f. 2001. energy consumption,employment,output and temporal causality:evidence from taiwan based on cointegration and error-correction modeling techniques. applied economics 33, 1045-1056 chen, s.t., h.i. kuo, and c.c. chen .2007. the relationship between gdp and electricity consumption in 10 asian countries. energy policy 35, 2611-2621. choi,i., 1992. effects of data aggregation on the power of the tests for a unit root.economic letters, 40,397-401 ciarreta, a. and a. zarraga,. 2010. economic growth-electricity consumption causality in 12 european countries: a dynamic panel data approach. energy policy 38, 3790-3796. ghosh, s. 2002, electricity consumption and economic growth in india. energy policy 30, 125129. ghosh, s. 2009, electricity supply, employment, and real gdp in india: evidence from cointegration and granger-causality tests. energy policy 37, 2926-2929. govindaraju c, madhavan k, sharma s. 2010, electricity consumption-growth nexus: the case of malaysia. energy policy, 38:606-12. granger, c. 1988. some recent developments in a concept of causality.journal of econometrics,39,199-212 ho, c.y. and k.w. siu, 2007. a dynamic equilibrium of electricity consumption and gdp in hong kong: an empirical investigation. energy policy, 35, 2507-2513. jain,v., sami, j.2011. capital mobility and saving-investment nexus: empirical evidence from mauritius, malta and maldives, paper presented in tenth international conference on operations and quantitative management held in symbiosis institute of operations management nasik , june 28-30, 2011. jain, v., sami, j. 2011. understanding sustainability of trade imbalance in singapore empirical evidence from cointegration analysis, paper presented in tenth international conference on operations and quantitative management held in symbiosis institute of operations management nasik , june 28-30, 2011. jumbe, c.b.l. 2004. cointegration and causality between electricity consumption and gdp: empirical evidence from malawi. energy economics, 26, 61-68. multivariate cointegration and causality between exports, electricity consumption and real income per capita: recent evidence from japan 67 lean, h.h. and r. smyth. 2010a. on the dynamics of aggregate output, electricity consumption and exports in malaysia: evidence from multivariate granger causality tests. applied energy 87, 1963-1971. lean, h.h. and r. smyth 2010b. multivariate granger causality between electricity generation, exports, prices and gdp in malaysia. energy 35, 3640-3648. lean, h.h. and r. smyth 2010c. co2 emissions, electricity consumption, and output in asean. applied energy 87, 1858-1864. lee, c.c. and c.p. chang. 2005. structural breaks, energy consumption, and economic growth revisited: evidence from taiwan. energy economics, 27, 857-872. hatemi, a., irandoust, m.2005. energy consumption and economic growth in sweden: a leveraged bootstrap approach, 1965–2000. international journal of applied econometrics and quantitative studies 2 (4), 87–98. iea, 2010. world energy outlook, international energy agency, paris. iea, 2011. impact of earthquakes and tsunamis on energy sectors in japan, international energy agency, paris. francis,b. lorde, t, waithe, k. 2010. the importance of electrical energy for economic growth in barbados. energy economics, 32, 1411-1420 morimoto, r. and c. hope. 2004. the impact of electricity supply on economic growth in sri lanka. energy economics 26, 77-85. mozumder, p., a. marathe. 2007. causality relationship between electricity consumption and gdp in bangladesh. energy policy, 35, 395-402. mackinnon, j.g. 1991. critical values for cointegration tests.”in long run economic relationships: readings in cointegration, ed.r.f.engle and c.w.j.granger.oxford: oxford university press. narayan, p.k, narayan, s., 2006. savings behaviour in fiji: an empirical assessment using the ardl approach to cointegration. international journal of social economics, 33(7), 468-480. narayan, p.k., smyth, r. 2005. electricity consumption, employment and real income in australia: evidence from multivariate granger causality tests. energy policy 33, 1109–1116. narayan, p.k., singh, b., 2007. the electricity consumption and gdp nexus for the fiji islands. energy economics 29, 1141–1150. narayan, p.k., a. prasad 2008. electricity consumption-real gdp causality nexus: evidence from a bootstrapped causality test for 30 oecd countries. energy policy 36, 910-918. narayan, p.k., smyth, r., 2009. multivariate granger causality between electricity consumption, exports and gdp: evidence from a panel of middle eastern countries. energy policy 37, 229–236. narayan, p.k, smyth, r., 2006. higher education, real income and real investment in china: evidence from granger causality tests. education economics 14,107-125 mahadevan, r., asafu-adjaye, j., 2007.energy consumption, economic growth and prices: a reassessment using panel vecm for developed and developing countries. energy policy 35, 2481–2490. masih, a.m.m., masih, r., 1997. on the temporal causal relationship between energy consumption, real income and price: some new evidence from asian nics based on a multivariate cointegration/vector error-correction approach. journal of policy modeling 19, 417–440. ministry of economy, trade and industry, 2010. energy in japan 2010, tokyo. odhiambo, n.m. 2009, electricity consumption and economic growth in south africa: a trivariate causality test. energy economics 3111, 635-640. ozturk, i. 2010. a literature survey on energy-growth nexus. energy policy, 38(1), 340-349. ozturk, i., acaravci, a. 2011, electricity consumption and real gdp causality nexus: evidence from ardl bounds testing approach for 11 mena countries," applied energy, 88(8), 2885-2892. pattichis, chalambos a. 1999. price and income elasticities of disaggregated import demand: results from uecms and an application. applied economies 31(9), 1061-71 payne, j.e. 2010, a survey of the electricity consumption-growth literature.applied energy 87, 723-731. pesaran, m. and bahram, pesaran. 1997. microfit 4.0.oxford: oxford university press. international journal of energy economics and policy, vol. 1, no. 3, 2011, pp.59-68 68 pesaran, m.h. and y. shin, 1999, an autoregressive distributed lag modelling approach to cointegration analysis” in econometrics and economic theory in the 20 century: the ragnar frisch centennial symposium edited by s. strom (cambridge university press, cambridge, uk). pesaran, m.h., y. shin, and r. smith. 2001, bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16, 289-326. phillips, peter c.b., bruce hansen.1990.statistical inference in instrumental variables with i(1) processes. review of economic studies 57, no 1:99-125. phillips, peter c.b., pierre perron. 1988. testing for a unit root in time series regression. biometrika 75(4), 335-59 stock,james h., and mark w.watson, 1993. a simple estimator of cointegrating vectors in higher order integrated systems. econometrica 61,no4:783-820 shiu, a., p.l. lam. 2004. electricity consumption and economic growth in china.energy policy 32, 47-54. shiu, a., lam, p., 2004. electricity consumption and economic growth in china. energy policy 32, 47–54. squalli, j. 2007, electricity consumption and economic growth: bounds and causality analyses of opec countries. energy economics 29, 1192-1205. tang, c.f. 2008.a re-examination of the relationship between electricity consumption and economic growth in malaysia. energy policy, 36, 3077-3085. thomas,s.(2006). electricity reform experiences in asia, pacific region, gats and privatisation of the industry, paper presented at world experiences of electricity reforms,colombo, march 10, 2006. wolde-rufael, y. 2006, electricity consumption and economic growth: a time series experience for 17 african countries. energy policy 34, 1106-1114. yoo, s.h. 2005, electricity consumption and economic growth: evidence from korea. energy policy 33, 1627-1632. yoo, s.h. 2006, the causal relationship between electricity consumption and economic growth in the asean countries. energy policy 34, 3573-3582. united nations, united nations statistics division, 2010 world bank, world development indicators, 2010 yoo, s.h. and s.y. kwak 2010, electricity consumption and economic growth in seven south american countries. energy policy, 38, 181-188. yuan, j., c. zhao, s. yu, and z. hu 2007, electricity consumption and economic growth in china: cointegration and co-feature analysis. energy economics 29, 1179-1191. zamani, m. 2007, energy consumption a n d economic activities in iran. energy economics 29, 1135-1140. ziramba, e. 2009, disaggregate energy consumption and industrial production in south africa. energy policy 37, 2214-2220. . international journal of energy economics and policy | vol 6 • issue 1 • 2016 105 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2016, 6(1), 105-112. cost-benefit analysis of renewable power under full subsidy targeting law enforcement conditions in iran mehdi barimani1* 1national academy of science, economical institute, yerevan, armenia. *email: m.barimani@mazrec.co.ir abstract fossil energy extracted resources limitation, on the one hand and fossil energies induced environment pollution, on the other hand, have made renewable energies more attractive, especially for developing countries. thus international programs and policies such as the un programs have been considered in line with global sustainable development playing a special role for renewable energy resources. although, in practice various factors in particular high initial cost and marginal price, not sufficient investment for localization and the associated technologies efficiency enhancement, taking external costs for granted in the economic equations and lack of supportive policies at local, regional and international levels have made renewable energies penetration and development very slow and limited. it is emphasized that rich fossil resources (standing 4th rank in oil reserves and 2nd in gas reserves) existence in iran has been another giant obstacle for renewable energies development in iran. thus executing subsidy targeting policy and article 44 of iranian constitutional law can be a great opportunity for renewable energies development in iran. through economically evaluating the renewable power and comparing it with fossil electricity under full subsidy targeting law enforcement conditions, renewable electricity marginal cost sensitivity analysis and various guaranteed renewable energies resources electricity purchase tariff proposal to the government, the researcher in this study hopes that the private sector investor’s opportunity in this industry and subsequently, renewable electricity share increase in iran energy basket will be provided. keywords: cost-benefit analysis, sensitivity analysis, renewable power, subsidy targeting law, comfar jel classifications: c87, h23, q27, q42 1. introduction at the national level, at least 30 countries around the world already have shares of renewable energy above 20%. some 120 countries have various types of policy targets for long-term shares of renewable energy, including a binding 20% target for the european union by 2020. some countries have long-term policy targets that will put them squarely in the “high renewable” domain by 2030 or 2050, such as denmark (100%) and germany (60%). outside of europe, a diverse group of at least 20 other countries target energy shares in the 2020-2030 time frame that range from 10% to 50%, including algeria, china, indonesia, jamaica, jordan, madagascar, mali, mauritius, samoa, senegal, south africa, thailand, turkey, ukraine, and vietnam (martinot, 2013). several factors have made the penetration and development of renewable energies very slow and limited, especially initial cost, insufficient investment for localization and improvement of the corresponding technologies effectiveness, lack of accounting for foreign costs in economic equations, and lack of supportive policies worldwide, across region and across local places. also, the existence of rich fossilized resources (forth rank of oil resources and second rank of gas resources) in iran has become a larger obstacle for the development of renewable energies in this country. thus the execution of targeted subsidy law (available from: http://www.parliran.ir/index.aspx?siteid=1&pageid=3070) and the execution of the article 44 of the constitutional law (available from: http://www.rc.majlis.ir/fa/content/iran_constitution) could be the most important opportunity for the development of renewable energies in iran. one of the important barriers to implement any such programs for enhancing the use of renewable energy is the limitation of financial resources and lack of government support, which is likely caused by weak economy and fundamental infrastructures deficiencies of countries, which will need to be addressed, first and foremost, by proper governmental policies and deep support from the private investors (world energy council, 1986). barimani: cost-benefit analysis of renewable power under full subsidy targeting law enforcement conditions in iran international journal of energy economics and policy | vol 6 • issue 1 • 2016106 along execution of the article 44 of the iran constitutional law, the improvement of economic structure and the cooperation of the private sector for infrastructure activities is of important and effective actions. the requirement of actualization of this important task in power industry is a structure renewal for establishing competency healthy space, privatization and optimum allocating resources. in iran there have been also carried out the goal of establishing proper space for cooperation of private sector in power industry, several actions such as legal establishment, announcement of regulations and executioner trends. although structure renewal and privatization of power industry are actualized when private sector – besides having satisfaction from obtained benefit – is sure from investment in this sector. in such a situation the execution of supportive tariff-making policy and guaranteed purchase of power by the government could be the most main and important tools for establishing confident conditions for investment and attraction of private sector investment. this policy is of the most main and the most important tools which are used for the development of this era. it should be noted that the protective incentive policy, investment and guaranteed pricing of renewable energy sources are the most important tools in iran for developing the fields, which policy has been used successfully in turkey, canada, germany, denmark, america, spain, and is also used in the countries who intend to support investments in renewable energy sources. these policies and incentives also include the creation of a special for the renewable energy sector (doe report, 2009; dabiri et al., 2013). in this research the researcher have analyzed cost-benefit of the generation of renewable power and have compared it with the fossilized power in the condition of complete execution of targeted subsidy law having accounted for society cost of power generation, sensitivity analysis of finished cost of renewable power and suggestion of guaranteed purchase of power. the researcher hopes that the private sector investor be attracted to this industry and beside the renewable power is increased in the iranian energy basket. this research has been carried out by the consultative opinions of the experts of economic and strategic studies office of the iranian organization of new energies and also experts of power industry, solar thermal power plant, water and wind power plant and steam power plant, small gas plant, large gas plant and combined cycle of fossilized technology. 2. materials and methods cost-benefit analysis methods have been used to evaluate the data in this study. it is customary method in evaluating and measuring the marginal cost of production unit or cost of each energy production unit, which identifies the factors for incentives recommended for guaranteed electricity purchases and the equality of cost-benefit ratio (b/c) for comparison purposes. the equivalent uniform annual cost (euac) and in this case levelized cost of energy (lcoe) is used. in this method all the marginal cost annually are measured with discounted rate (i=10) for the referenced year and then it is distributed during the project’s lifetime. b/c = euab/euac (1) if it is b/c ≥ 1, it is justifiable for private sector investment, and if b/c < 1, it is not justifiable for private sector investment. in this method, lcoe is calculated as follows: lcoe = ac + o&m + pvf/eout (2) the variable terms for the above method of calculation are defined as follows: ac: annual cost of investment ($) o&m: annual cost of maintenance and operation ($) pvf: annual cost of consumption fuel ($) eout: total annual gross electrical energy produced by plant (kwh) ac: annual cost of investment the annual cost of investment, is a uniform cost which has a constant value throughout the plant’s life. to obtain cost of annual investment, at first the investment return coefficient crf should be multiplied by the total cost of the primary investment: ac = crf × c (3) c is the total primary investment amount for engineering, procurement and construction (epc), and crf = i/1(1+i)n, (n is the plant life time and i is the discount rate) (4) o&m: maintenance and operation the cost of maintenance and operation is considered as a percentage of annual cost. pvf: annual cost of fuel consumption the amount of annual cost of fuel is calculated using the following formula: pvf = (w × h/ra × nhv) ×pg (5) w: the plant power (mw) ra: plant efficiency pg: base price of consumed fuel ($) nhv: heat value of net fuel (mw) h: amount of work hours of plant unit in a year (h = cr × 8760) cr: coefficient of accessibility eout: annual gross value of plant production the total annual gross energy production by plant (kwh): eout = w ×cr × 8760 (6) in iran, generally, financial resources and investment funds barimani: cost-benefit analysis of renewable power under full subsidy targeting law enforcement conditions in iran international journal of energy economics and policy | vol 6 • issue 1 • 2016 107 required by the power industry are supplied by the internal resources of the industry, governmental complementary budgets, taking formal loans from the internal banking system, selling valuable papers inside the country, delivering loan and credit from multilateral and bilateral international agencies. in this survey having supportive approach, the investment conditions and financial supply have been considered with banking financial facilities stock equal to 85% and capital delivery stock equal to 15%. considering the loan interest rate is the most important factor in financial decision-making activities, all the calculations, comparisons, and analyses have been carried out in loan different interests (7% interest from national development box of iran and finance, 12% and 17% interest from governmental banks in iran and also 25% interest loan from private banks) (central bank of the islamic republic of iran, 2014). all of the indexes measured in the survey – npb, dpb, irre, npv, irr – have been calculated having the goal of investigation of desired and attractive plans for the private sector investor with the least capital return rate irre=20% (appendixes 1 and 2) (table 1). evaluation calculations and economic comparisons of generated power cost price, suggested tariffs of guaranteed purchase of renewable and fossilized power in the conditions of exact execution of the law of subsidized targeting in 2015 are carried out considering external costs of fossilized power generation. also, to recognize the most important factors affecting on the cost price of renewable power and the value of this effect, the sensitivity analysis of the cost price of the renewable power would be performed. in this article, all the calculations are performed by the economic evaluation software of industrial projects comfar, which is a flexibility program for financial and economic evaluation of industrial capital projects in terms of the national and international standards. 3. the calculations and economic comparison between renewable power and fossilized power the existence of rich fossil resources is a great reason that shows that iran is not developed in renewable energies. thus it is necessary in the analysis and economic calculations related to the technologies of renewable power to carry out its analysis and comparison with fossilized power plants. in calculation of the cost price of the generated power from the fossilized power plants, the fuel price is the most important factor. calculations have been carried out for several kinds of power plants assuming the fuel as natural gas. according to article 1 of the targeted subsidy law, the price of consuming natural gas of the power plants is equal to 75% from export natural gas mean price (parliament of islamic republic of iran). meanwhile, the mean price of natural export gas price has been estimated in 2014, 30 ¢/m3. also it is noted that the rate of dollar would be 24600 rials/$ (central bank of the islamic republic of iran, 2014). to calculate the marginal cost or uniform expense of power generation in fossilized plants, the amount of social cost of power generation would also be considered. the same cost was calculated by the researcher based on energy balance sheet in 2011 (ministry of energy, 2013) for steam plant 0.93 ¢/kwh, gas plant 0.43 ¢/kwh, and combined cycle plant 0.25¢/kwh, respectively. having accounted for the above conditions, the calculations of the marginal costs of power generation, the tariffs of guaranteed purchase and cost-benefit ratio b/c of the power generated from the technology of renewable energy and the generated power from the technology of fossilized energy are represented as follows: in the figure 1 it is seen that in all of the loan interests, the gas small plant is the cheapest option and the cost price of the solar thermal plant is considerably the most expensive one. in the loan interest of 7% to 12% after solar thermal plant, the large gas plant is in the second rank. also in the loan interests the increasing slope of table 1: the manner of calculation of some of the technical-economical parameters tax (income−cost of exploration−capital amortization−loan interest)×tax coefficient annual net energy production (access coefficient×internal consumption −1)×nominal capacity×production coefficient×8760 income tariff×annual net production energy annual amortization investment cost×plant life time/(depreciation coefficient-1) cash flow income − maintenance cost – loan origin rebate – loan interest total investment total primary cost+manufacturing period interest lcoe investment annual cost+annual maintenance and operation costs+(total annual gross energy produced by plant/annual cost of fuel consumption) lcoe: levelized cost of energy figure 1: levelized cost of energy versus interest rates with social cost/comparing interest (%) solar thermal small hydro wind small gas large gas steam combined cycle 7 20.96 9.40 9.42 9.09 14.56 13.18 10.32 12 34.64 12.73 14.13 9.30 14.89 13.95 10.64 17 46.63 15.43 18.26 9.57 15.18 15.00 11.28 25 68.90 20.69 25.94 10.10 15.73 17.14 12.62 barimani: cost-benefit analysis of renewable power under full subsidy targeting law enforcement conditions in iran international journal of energy economics and policy | vol 6 • issue 1 • 2016108 generated power cost is more than from technology of its fossilized analogs. its main reason is the high required amount of cost for renewable technology, so that their loan stock is considerable and it is sensitive versus loan interest. the government could pay attention and support these options of small hydro and wind from the group of renewable and small gas plant from fossilized group. in the figure 2 it is observed that according to all of the amounts of loan interests, the tariffs of the guaranteed purchase of power generated is more expensive than fossilized technology. in this comparison the least tariff corresponds to gas small plants and the most tariffs corresponds to the solar thermal plants. one of the benefit-giving evaluation indexes is cost-benefit ratio b/c. the higher is this ratio, the more is the amount of benefit-giving. considering social cost in the cost price of generating power causes the ratio of revenue to fossilized power cost to decrease. it is evident from figure 3 that generally the renewable power has the highest amount of benefit-giving compared with fossilized power. as it is seen from the calculations, in lower interests, for the investor of private sector the renewable power has the most absorption compared with the fossilized power. therefore, the government should, to support the generation of power by renewable energies, provide and represent the facilities such as loan having low interest (loan with interest of 7% from the national box for development) and also provide the background for entrance of private investor in this field. considering figure 1 the cost price of generated power by gas small plant versus three other fossilized is very low but, regarding figure 3, since, versus other fossilized options the cost-benefit ratio b/c is low, this power plant has not any absorption for the private sector investor. but regarding that these plants can be used as combined cycle and chp and their advantages such as performance increase and dissipated generation of this kind of power plants in generation and delivering power, and regarding low tariff of guaranteed purchase and also its low ascending slope, this kind of power plant could be an appropriate option for the government to support and absorb the investor of the private sector. 3.1. calculation and recommended prices for guaranteed renewable energy in iran in 2013, according to the instructions in paragraph (b) of article 133, iran’s fifth five-year plan and the procedures for determining the power purchase rate of new and cleaner energy sources, the basic rate of purchase of electricity from the resource for contracts guaranteed for purchase for 5 years as follows: guaranteed purchase rate of electricity from renewable energy sources is equal to: the average price of energy converted in to the electricity market per kwh +saving fuel values for liquid combined fuel per kwh +savings the values due to the lack of emissions social cost per kwh base price was calculated for guaranteed purchase rate was determined and communicated for electricity from renewable energy sources at the rate of 17.77 ¢/kwh (renewable energy organization of iran, 2014). following three equations requires finding out the ratio b/c of the technologies: 1. is the production of electricity through wind power plant justified in iran? 2. is the production of electricity through small hydropower plant justified in iran? 3. is the production of electricity through solar thermal power plant justified in iran? it should be noted that the calculation of the electricity production from renewable sources is based on 7% interest loan to finance the foreign exchange reserves, to be considered by the private sector. therefore, to examine the justification of the economic viability tariffs cost of lcoe by the resources, the loan interest figure 2: tariffs versus interest rates without social cost/comparing interest (%) solar thermal small hydro wind small gas large gas steam combined cycle 7 20.96 9.40 9.42 9.09 14.56 13.18 10.32 12 34.64 12.73 14.13 9.30 14.89 13.95 10.64 17 46.63 15.43 18.26 9.57 15.18 15.00 11.28 25 68.90 20.69 25.94 10.10 15.73 17.14 12.62 figure 3: b/c ratios versus interest rates with social cost/comparing interest (%) solar thermal small hydro wind small gas large gas steam combined cycle 7 2.27 1.91 1.84 1.09 1.06 1.15 1.17 12 1.54 1.47 1.31 1.07 1.06 1.12 1.13 17 1.46 1.33 1.25 1.07 1.06 1.13 1.13 25 1.38 1.27 1.20 1.08 1.06 1.15 1.14 barimani: cost-benefit analysis of renewable power under full subsidy targeting law enforcement conditions in iran international journal of energy economics and policy | vol 6 • issue 1 • 2016 109 is set at 7%. with the tariff set by the government, it can be seen that, generating electricity through solar thermal power plant is not economically feasible, although it might be appropriate tariff for the two other options. it’s very important that consideration is given to setting different tariffs for guaranteed purchase of electricity based on the cost of producing electricity through investments in different technologies; hence, different tariffs for different technologies must be used. the same tariffs for different technologies impede balanced development to various renewable energy technologies, as the investors will favor the development of the technology that is more profitable. based on the opinion of the economic and strategic studies expert advisory of the renewable energy organization of iran, the unit cost of electricity generated through renewable sources -lcoe in 2014, with goal of creating economic justifiability in order to encourage private sector investment in this section, different tariffs for different technologies is proposed and the b/c ratio of this resource has been calculated (appendix 3) as table 3: as it can be seen, the proposed electricity tariff by three technologies will be economically feasible. it is hoped that the proposed tariff for solar thermal power plants, which have a relatively high number, with the more power is considered in developing the proposed plant capacity and its future growth, it will result in reduced investment costs and lower energy prices in the future. wind power forecasts dependent on iran’s fifth economic and social development of wind power, the research-based purchase price is expected to be determined based on the high potential of wind power in the value chain of technology and further supported by the government for wind power plants. 3.2. renewable electricity cost principle sensitivity analysis the cost price of produced electricity (lcoe) through renewable energy resources is affected by many factors, known and unknown variables. three main factors affecting it are “discount rate (i), investment cost for epc and net production factor.” net production factor is the ratio of total energy produced by the plant during a specified period (generally a 1-year period) divided by the system peak load and the length of time in hours (generally 8760 h). “sensitivity analysis” has been used to determine the most important factors affecting the cost of electricity generated and the level of its impact. sensitivity analysis repeats the calculations of a financial process by changing the main parameters and comparing the results from the primary data. if a small change in a parameter causes a considerable change in the results, it is said that the plan has high sensitivity with respect to that parameter and that is a sensitive parameter. to investigate the project sensitivity with respect to these changes, the sensitivity geometrical graph methodology is used here (oskounejad, 2008). figures 4-6 are the analyses of sensitivity of cost of the electricity produced through renewable energy resources, with respect to three main components of “discount rate, investment cost for epc and net production factor,” which has been calculated and presented as follows: the following assumptions were used in analyzing sensitivity graphs of figures 4-6: • the cost/price of the production of renewable electricity lcoe of the plants with respect to the component epc has a direct relation and with respect to two other components (discount rate and net production factor) has an indirect relation. • the cost/price of the production of renewable electricity lcoe with respect to component epc, is most sensitive to solar thermal plant, water electricity plant, and wind plant, respectively (according to their epc value). • the cost/price of the production of renewable electricity lcoe with respect to the component of discount rate is most sensitive to solar thermal, wind, and small hydro respectively table 2: b/c ratio of renewable resources tariff in 2014 power plant index wind small hydro solar thermal lcoe (¢/kwh) 9.42 9.40 20.96 tariff (¢/kwh) 17.77 17.77 17.77 b/c 1.80 2.03 0.91 lcoe: levelized cost of energy table 3: the researcher proposed tariff and the ratio b/c proposed tariff in 2014 power plant index wind small hydro solar thermal lcoe (¢/kwh) 9.42 9.40 20.96 tariff (¢/kwh) 17.70 12.70 43.40 b/c 1.84 1.91 2.27 lcoe: levelized cost of energy figure 4: sensitivity graph analyzing wind δi (%) lcoe ($¢/kwh) δ n.p.c (%) lcoe ($¢/kwh) δ epc (%) lcoe ($¢/kwh) 30 8.96 30 9.17 30 9.74 20 9.11 20 9.24 20 9.64 10 9.26 10 9.32 10 9.53 0% 9.42 0 9.42 0 9.42 −10 9.59 −10 9.54 −10 9.31 −20 9.76 −20 9.69 −20 9.21 −30 9.94 −30 9.88 −30 9.10 −40 10.13 −40 10.14 −40 8.99 *i=10%, net production coefficient=30%, epc=1600 $¢/kwh. epc: engineering, procurement and construction, lcoe: levelized cost of energy barimani: cost-benefit analysis of renewable power under full subsidy targeting law enforcement conditions in iran international journal of energy economics and policy | vol 6 • issue 1 • 2016110 (according to their financial calculation). • the cost/price of the production of renewable electricity lcoe with respect to the component of the net production factor, is most sensitive to solar thermal, small hydro and wind respectively. • the cost/price of solar thermal plant with respect of three components varies based on the discount rate, net production factor and epc, respectively. • the cost/price of small hydro power plant with respect to three components varies based on the net production factor, epc, and discount rate, respectively. • the cost/price of wind power plant with respect to three components varies based on the discount rate, net production factor, and epc, respectively. the main reason about high sensitivity of cost/price of the electricity for solar thermal plant with respect to the two components of discount rate and epc, compared to the two other options, is the amount of initial and long term financial investment over the life of the plant. therefore, it is recommended that solar thermal plant to be analyzed more thoroughly, so that by increasing the installation capacity of this kind of plant and the future growth of the related industry, the costs of its investment would be reduced over time and would be set forth as a candidate for cheap electricity in the future. 4. conclusions and suggestions penetration and development of renewable energies have become very slow and limited because of various factors particularly high primary cost and cost price, lack of sufficient investment for localizing and performance improvement of corresponding technologies, lack of accounting for external costs in economic equations, lack of supportive policies worldwide, across region and local. • regarding that the most main factor in the cost price of fossilized power is the cost price of its fuel, so the execution of the law of subsidiary targeting and eliminating subsidy from fossilized energies would be caused the competency advantage of renewable power to increase versus fossilized power. • in achieving steady development, considering external costs in economic transaction is a great task. therefore, in the determination process of power purchase tariffs it is suggested to take into account the social cost in the cost price of fossilized power, however, it would cause the advantage promotion of the renewable power to increase versus fossilized power. • based on determined goals in the 20 years outlook document, 10% of the power required by the country should be supplied via renewable resources. also, in the fifth plan of country development, it has been targeted to use renewable energies as much as 5000 mw (available from: http://www.rc.majlis. ir/fa/law/show/790196; parliament of islamic republic of iran, 2014). these two documents could be a lever to support financial institutions in iran. since the amount of primary cost of investment in renewable power plants is high, development of this infrastructure industry is not possible but by supportive activities of the government. thus the government can carry out the task through banks and the national development box and supply appropriate financial facilities for investing in this sector. • as mentioned, identical tariff for different technologies of renewable power is an obstacle for balanced development of these technologies, since the private sector investor has the tendency to some technology that has less cost and more benefit. this in turn is an obstacle for other options to develop. therefore, considering much difference between the primary cost and investment amount of different technologies of renewable power, the determination and approval of different tariffs for different technologies is a principle action for figure 5: sensitivity graph analyzing small hydro δi (%) lcoe ($¢/kwh) δ n.p.c (%) lcoe ($¢/kwh) δ epc (%) lcoe ($¢/kwh) 30 8.97 30 8.86 30 10.10 20 9.11 20 9.01 20 9.87 10 9.25 10 9.19 10 9.63 0 9.40 0 9.40 0 9.40 −10 9.56 −10 9.66 −10 9.17 −20 9.72 −20 9.98 −20 8.93 −30 9.89 −30 10.40 −30 8.70 −40 10.07 −40 10.96 −40 8.47 *i=10%. net production coefficient=50%, epc=2300 $¢/kwh. lcoe: levelized cost of energy, epc: engineering, procurement and construction figure 6: sensitivity graph analyzing solar thermal δi (%) lcoe ($¢/kwh) δ n.p.c (%) lcoe ($¢/kwh) δ epc (%) lcoe ($¢/kwh) 30 19.92 30 20.30 30 21.81 20 20.25 20 20.48 20 21.52 10 20.60 10 20.70 10 21.24 0 20.96 0 20.96 0 20.96 −10 21.33 −10 21.27 −10 20.67 −20 21.72 −20 21.67 −20 20.39 −30 22.12 −30 22.17 −30 20.10 −40 22.54 −40 22.85 −40 19.82 *i=10%, net production coefficient=50%, epc=2300 $¢/kwh. lcoe: levelized cost of energy, epc: engineering, procurement and construction barimani: cost-benefit analysis of renewable power under full subsidy targeting law enforcement conditions in iran international journal of energy economics and policy | vol 6 • issue 1 • 2016 111 balanced development of different technologies of renewable power. • therefore, the researcher having an approach of economic justifiability and encouraging private investor to invest in renewable power, has calculated and recommended different tariffs for different technologies of renewable power (according to table 3) as: 20.96 ¢/kwh for solar thermal plant, 9.40 ¢/kwh for small water power plant and 9.42 ¢/kwh for wind plant. • the high amount of the primary cost, high investment and financial flow of solar thermal power plant have caused this power plant to have high sensitivity in its cost price versus these two components of discount rate and epc, comparing with the other two options of wind and small water plant. therefore, it is predicted that using researcher’s relatively high recommended tariff for solar thermal power plant, this plant may be accepted by the private sector. also, by increasing the capacity of installation of this kind of power plant the investment costs of it would be decreased and in future it would be a candidate for the generation of cheap power. • regarding wind power plant, the researcher suggested the base price of power purchase, but it is expected that considering high potential of wind plant, recognizing its technology and its value chain in iran, the technology of this plant will receive more support from the side of government. the determination of time period of closing the contract and also applying the stepwise tariff in policy of guaranteed purchase are two other important subjects which are effective in renewable power development. the researcher intends to represent the results of his studies and calculations in another article. refrences central bank of the islamic republic of iran. (2014), key economic indicators. tehran: public relations department. available from: http://www.cbi.ir. dabiri, f., zarei, a., taghavi, l., purhashemi, a. (2013), development and use of renewable energy inefficiently in iran and selected countries, 28th international power system conference, 4-6 november, tehran, iran. doe report. (2009), a comparative study of oecd country for renewable energy technology. available from: http://www.energy. gov/conferences/winter2002/gallery/jacobsson. martinot, e. (2013), renewables global futures report. paris: ren21. p14. ministry of energy. (2013), energy balance of iran_ 2011. tehran: peyeke noor. p554. oskounejad, m. (2008), engineering economy or economic evaluation of industrial projects. 30th ed. tehran: amirkabir university publisher. p420. parliament of islamic republic of iran/research center/law. (2014). available from: http://www.parliran.ir/index.aspx?siteid=1&pageid=3070. parliament of islamic republic of iran/research center/law. (2014). available from: http://www.rc.majlis.ir/fa/law/show/790196. parliament of islamic republic of iran/research center/law. (2014). available from: http://www.parliran.ir/?siteid=1&pageid=220. parliament of islamic republic of iran/research center/law/ constitutional law, article-44. (2014). available from: http://www. rc.majlis.ir/fa/content/iran_constitution. renewable energy organization of iran. (2014), private sectors cooperation office, establishment of non-governmental renewable energy power plants. available from: http://www.privatesectors. suna.org.ir/fa/home. world energy council. (1986), new renewable energy sources. tehran, atlas: wec, energy ministry of iran, kahrobaiyan. p15. appendix 1: calculations of cost price of renewable electricity in investor’s viewpoint in 2014 according to the data from the strategic and economic studies office of renewable energy organization of iran (suna) in 2014 portion of financial bank facilities 85% portion of investor brought 15% rate of bank discount 10% rate of brought discount 10% some calculation consumptions wind solar thermal small hydro investment cost as epc/¢$) kwh) 1600 4700 2300 maintenance and operate cost/¢$) kwh) 0.8 1.3 %2 coefficient of net production (%) 30 30 50 plant life time (year) 20 30 10 cost price components in private section viewpoint wind solar thermal small hydro fuel cost/¢$) kwh) 0.00 0.00 0.00 maintenance and operate cost/¢$) kwh) 0.81 1.30 1.05 constant brought cost/¢$) kwh) 1.07 2.85 1.28 the cost of facilities installments/¢$) kwh) 7.54 16.81 7.07 social cost/¢$) kwh) 0.00 0.00 0.00 cost price – before tax (lcoe)/¢$) kwh) 9.42 20.96 9.40 minimum tariffs/¢$) kwh) 17.90 43.40 12.70 cost price – after tax/¢$) kwh) 10.35 24.10 9.40 lcoe: levelized cost of energy, epc: engineering, procurement and construction barimani: cost-benefit analysis of renewable power under full subsidy targeting law enforcement conditions in iran international journal of energy economics and policy | vol 6 • issue 1 • 2016112 appendix 2: the measurements related to renewable technologies 2014 solar thermal interest (%) loan payment period (years) lcoe ($¢/kwh) tariff ($¢/kwh) irr (%) irre (%) npb-total (years) dpb-total (years) npb-equity (years) dpb-equity (years) benefits cost ratio 7 8.5 20.96 43.40 11.98 22.30 9.16 18.37 11.08 13.20 2.27 12 15 34.64 48.22 13.67 19.99 8.39 14.02 10.01 17.81 1.54 17 15 46.63 61.14 17.71 19.99 6.96 9.78 16.36 18.15 1.46 25 15 68.90 85.43 24.81 20.00 5.49 6.83 16.65 18.51 1.38 small hydro interest (%) loan payment period (years) lcoe ($¢/kwh) tariff ($¢/kwh) irr (%) irre (%) npb-total (years) dpb-total (years) npb-equity (years) dpb-equity (years) benefits cost ratio 7 8.5 9.40 12.70 13.53 20.00 7.93 14.10 10.73 13.12 1.91 12 15 12.73 14.16 15.84 20.00 7.04 10.74 6.85 16.15 1.47 17 15 15.43 17.29 20.50 20.02 5.75 7.77 7.31 16.77 1.33 25 15 20.69 23.15 29.18 20.02 4.39 5.36 8.49 17.48 1.27 wind interest (%) loan payment period (years) lcoe ($¢/kwh) tariff ($¢/kwh) irr (%) irre (%) npb-total (years) dpb-total (years) npb-equity (years) dpb-equity (years) benefits cost ratio 7 8.5 9.42 17.90 12.91 20.02 7.84 13.57 10.61 12.65 1.84 12 15 14.13 20.20 15.51 20.04 6.97 10.54 6.42 10.25 1.31 17 15 18.26 25.10 20.52 20.00 5.69 7.66 6.69 11.26 1.25 25 15 25.94 34.33 29.54 20.00 4.34 5.28 7.28 16.53 1.20 lcoe: levelized cost of energy, epc: engineering, procurement and construction appendix 3: the measurement related to fossilized technologies 2014 under full subsidy targeting law enforcement conditions (the natural gas price # 30 $¢/m3) small gas interest (%) loan payment period (years) lcoe ($¢/kwh) tariff ($¢/kwh) irr (%) irre (%) npb-total (years) dpb-total (years) npb-equity (years) dpb-equity (years) benefits cost ratio benefits-cost ratio (e) 7 8.5 8.31 9.15 17.07 27.86 6.72 9.79 5.64 7.94 1.10 1.09 12 15 8.59 9.44 20.44 34.13 5.87 7.92 4.22 5.13 1.09 1.07 17 15 8.85 9.70 24.66 34.08 5.09 6.47 4.24 5.17 1.09 1.07 25 15 9.32 10.16 32.65 34.62 4.12 4.89 4.21 5.12 1.09 1.08 large gas interest (%) loan payment period (years) lcoe ($¢/kwh) tariff ($¢/kwh) irr (%) irre (%) npb-total (years) dpb-total (years) npb-equity (years) dpb-equity (years) benefits cost ratio benefits-cost ratio (e) 7 8.5 11.13 11.98 19.02 32.80 6.65 8.63 4.82 5.83 1.07 1.06 12 12 11.37 12.22 23.56 38.09 5.91 7.25 4.36 5.02 1.07 1.06 17 12 11.60 12.45 27.49 38.13 5.41 6.43 4.36 5.03 1.07 1.06 25 12 12.05 12.89 34.60 38.35 4.75 5.42 4.35 5.02 1.07 1.06 steam interest (%) loan payment period (years) lcoe ($¢/kwh) tariff ($¢/kwh) irr (%) irre (%) npb-total (years) dpb-total (years) npb-equity (years) dpb-equity (years) benefits cost ratio benefits-cost ratio (e) 7 8.5 12.56 14.23 12.95 20.06 12.13 19.37 2.01 2.01 1.16 1.15 12 15 13.51 15.18 16.71 836.48 10.52 14.03 2.01 2.01 1.14 1.12 17 15 14.43 16.09 20.55 836.48 9.21 11.10 2.01 2.01 1.15 1.13 25 15 16.30 17.96 30.78 836.48 7.84 8.71 2.01 2.01 1.17 1.15 combined cycle interest (%) loan payment period (years) lcoe ($¢/kwh) tariff ($¢/kwh) irr (%) irre (%) npb-total (years) dpb-total (years) npb-equity (years) dpb-equity (years) benefits cost ratio benefits-cost ratio (e) 7 8.5 9.68 10.25 14.51 20.01 10.98 16.11 11.35 15.57 1.18 1.17 12 15 10.33 10.88 16.48 20.08 10.21 13.84 9.31 13.36 1.14 1.13 17 15 10.92 11.48 20.12 20.06 9.16 11.37 9.58 14.25 1.14 1.13 25 15 12.12 12.67 27.12 20.92 7.92 9.03 9.68 14.61 1.15 1.14 lcoe: levelized cost of energy, epc: engineering, procurement and construction tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 2 • 2023166 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(2), 166-174. do the size of oil and gas firms govern their financial performance? with special reference to indian oil and gas firms anis ali*, nadeem fatima college of business administration, prince sattam bin abdulaziz university, al kharj, saudi arabia. *email: ah.ali@psau.edu.sa received: 30 november 2022 accepted: 25 february 2023 doi: https://doi.org/10.32479/ijeep.14051 abstract the amount of profitability, liquidity, solvency, and resource utilization are used to evaluate a corporate organization’s financial performance. the firm’s size is determined by revenue, overall resources, and the availability of capital to execute the business operations. the study tries to get the governance of the financial performance by the size of firms in the indian oil and gas sector. the study is based on secondary data taken from the website of indian oil and gas companies. anova, stacked column chart, and tukey’s homogeneity analysis applied for to get the disparity, variations and growth trend, and homogeneity of relative financial measures of financial performance. in indian oil and gas firms, profitability is governed by the size of the firms negatively and directly while return on resources is negatively but negligibly by the size of the firms. there is no governance of liquidity and solvency by the size of firms in the indian oil and gas industry. the larger manufacturing indian oil and gas companies must increase their managerial and cost effectiveness in order to increase their profitability and absolute profits, while the smaller production indian oil and gas companies must include debt in order to increase their level of activity and absolute profits. keywords: oil and gas, firm size, financial performance, profitability, liquidity, ratio analysis jel classification: q40, q43, m40, m41, l25 1. introduction the financial performance of a business organization is measured by assessing the profit-earning capacity, short-term and long-term playability, and utilization of resources. the financial performance of businesses is governed by various internal and external factors. size is the prominent factor that governs the absolute and relative financial variables of the businesses (ali, 2020b). the size of the business organization is determined by the total resources, activity level, and funds availability to run the operational activities (ali, 2021). the size of the firm is directly and positively related to the growth of absolute measures of the businesses. absolute financial performance i.e. revenue and profits increase directly and proportionately to the increase in the size of the business if other factors remain constant. but, the relative measures of financial performance i.e. profitability, liquidity, solvency, and utilization of the resources of the businesses expected to be stationary. the governance of financial performance by the size of the firm is indicated by fluctuations in the relative financial measurements in accordance with variations in business size. normally, firms enjoy higher relative financial performances by operating their activities at a larger level of production. possibly, enhancement in the relative financial measures is due to fixed cost, semi-fixed cost, quantity discount on the purchase of raw materials, grabbing the larger supply order at the enhanced sale price, or installation of advanced technology of production or processing, etc. one of the industries most important to the growth and development of the economy is the oil and gas sector in india. in india, there is a variety size of oil and gas companies operating their business activities. if the enhancement in the size of the indian oil and gas firms enhances their relative measures of financial performance, it would be progressive enhancements in the absolute measures of financial performance. so, there is a this journal is licensed under a creative commons attribution 4.0 international license ali and fatima: do the size of oil and gas firms govern their financial performance? with special reference to indian oil and gas firms international journal of energy economics and policy | vol 13 • issue 2 • 2023 167 need to study the size of the firms and their impact on their relative financial performance. 2. literature review the financial performance of the firms is governed by the availability of the funds and their composition. dhingra and dev (2016) found that the financial strength of the business organization is governed by the leverage or capital structure of the firm. according to taqi et al. (2020), financial leverage has a favorable impact on profitability. they suggested improving the debt in the capital structure to enhance profitability. the optimum capital structure enhances the profitability of the firm. lopez‐ valeiras et al. (2016) studied that debt has a negative mediating effect on the association between size and financial performance. while, reddy and narayan (2018) indicated that a company’s capital structure is influenced by its liquidity, which is reflected in its continued capacity to meet financial obligations. the firm’s leverage decreases as its liquidity increases and vice versa. however, there is no indication of a major effect of leverage on profitability or capital structure. further, mohammed et al. (2020) carried out a study and found that the profitability of the firm is significantly and negatively correlated with leverage. however, they observed that there is little connection between liquidity and profitability. also, the choice of leverage for a company is crucial since the leverage management style governs the company’s profitability, showing the firm’s ability to survive in the market. additionally, the ratio of debt to equity is crucial, indicating that enterprises must lower their cost of capital to attain the appropriate capital structure, which would improve the financial health of the business. contrarily, kalyani and mathur (2017) studied that sales, operating leverage, and asset growth are important factors in determining profitability provided that roa and assets, financial leverage, sales, and operating leverage are dependent variables. some selected indian oil and gas companies exhibit a significant association between operating leverage and asset growth and net profit ratio. also, meghanathi and chakrawal (2021b) revealed that financial leverage has a substantial positive association with earnings per share (eps), return on equity (roe), and return on asset (roa) but no significant relationship with non-profit ratio (npr). also, the regression analysis indicates that during the study period, leverage had no discernible effects on the profitability of reliance industries ltd. according to baidoo (2022), leverage has a notably negative relationship with profitability, corporate size, the price of crude oil, liquidity, and other important capital structure factors. he suggested utilizing the internal sources of funds in the context of ghanaian major oil and gas companies. alhassan and islam (2021) indicated that debt has a sizable detrimental effect on a company’s profitability. similarly, to this, retained earnings and equity capital are better for businesses than debt financing in the oil and gas industry. to maximize shareholder value, they suggested that oil and gas companies increase equity capital, increase revenues, increase retain earnings, and decrease debt financing. the liquidity in the indian oil and gas companies governs profitability. meghanathi and chakrawal (2021a) found that reliance industries ltd’s liquidity and profitability performance is superior to those of other chosen oil and gas firms in india. also, mistry and vyas (2021) found that profitability is positively affected by the current ratio and the fixed asset turnover ratio while negatively governed by the debt-equity ratio. nurwulandari (2021) observed that while liquidity directly has a negative and negligible impact on company value, it directly has a negative and large impact on profitability, firm size, and capital structure. business value is positively and marginally affected by profitability and firm size. capital structure has a negative and substantial impact and acts as a barrier between the impact of liquidity, profitability, and firm size on company value, directly. ramya and chandran (2018) found that the profitability of businesses depends on the utilization of resources. they suggested the optimum utilization of the business’s resources to enhance profitability. kanagaraj (2021) advocated that profitability is mostly dependent on resource efficiency, cost containment, and market share. it is worthwhile to reduce costs to boost profitability, not just from the standpoint of the investment but also from the investor’s point of view. according to a study by arise and adegbie published in 2021, the financial stability factors of liquidity, profitability, capital adequacy, asset quality, and tangibility of listed oil and gas companies in nigeria were significantly impacted by postbusiness process re-engineering procedures. they encouraged the listed nigerian oil and gas companies to implement business process re-engineering techniques to achieve sound financial stability and overall financial performance in the oil and gas industry. kumar (2019) studied that in comparison to public sector organizations, private sector enterprises have been found to have comparatively high liquidity, high solvency, and low asset management efficiency. private-sector businesses are virtually identical to public-sector businesses in terms of profitability. ali (2022) asserts that compared to larger-scale production of indian oil and gas corporations, smaller-scale production businesses show a superior post-covid-19 relational rise in total revenue, expenditure, earnings, profitability, and liquidity. he suggested improving cost and management efficiency as well as the external funds in capital composition to increase the profitability in greater-scale production companies. sulaiman (2012) discovered that restructuring had a substantial impact on the profitability, liquidity, and solvency position of these businesses, indicating an improvement in managerial effectiveness, adequate capital, stronger operational capability, and assurance of the businesses’ survival. liquidity, profitability, asset productivity, and solvency all affect a firm’s financial health and, consequently, financial distress and financial distress and activity ratio do not correlate statistically significantly (amoa-gyarteng, 2021). pattiruhu and paais (2020) observed that the business size, current ratio (cr), and return on equity (roe) had no positive or noteworthy effects on dividend policy. the impact of debt-to-equity ratio (der) and return-on-assets (roa), in contrast, is favorable and considerable for dividend policy. while the solvency of indian pharmaceutical enterprises is positively and to some extent influenced by the firm’s size (ali, 2020b). kallmuenzer and peters (2018) observed that the micro level of the firm negatively affects its profitability of the firms. abbasi and malik (2015) found a moderatingly favorable effect on expanding companies’ financial success. according to according to ghafoorifard et al. (2014), there is a connection between the firms’ age, size, and financial performance. ali and fatima: do the size of oil and gas firms govern their financial performance? with special reference to indian oil and gas firms international journal of energy economics and policy | vol 13 • issue 2 • 2023168 3. research methodology the study’s secondary data, which covers the financial years 2015-2022, was collected from the websites of the relevant indian oil and gas businesses. profitability ratio (pbt ratio), return on resources ratio (return on assets ratio-roa), liquidity ratio (current ratio), and solvency ratios (debt-equity ratio) are applied to get the profitability on sales, the profitability of total funds, both shortand long-term payment capacity of the indian oil and gas firms. profitability pbt ratio= 100 profitbeforetax totalrevenue � � (1) returnonassets roa ratio= net income total assets � � (2) liquidity(current)ratio= current assets currentliabilities (3) debt equity ratio longtermdebts shareholdersequity � � � � � � � (4) the relative mean financial performance measures of indian oil and gas companies were compared using anova and post hoc analysis (tukeys hsd), which revealed significant differences and homogeneity among the relative financial performance measures. the comparative financial measurements of indian oil and gas firms for the financial years 2015 to 2022 are compared using a clustered column chart. indian oil corporation limited (iocl), bharat petroleum (bp), gas authority of india (gai), hindustan petroleum (hp), chennai petroleum (cp), gujarat gas limited (gg), indraprastha gas limited (ig), mahanagar gas limited (mg) indian oil and gas companies considered for the study. based on average rankings of total revenue, total assets, and working capital (ali, 2021; ali, 2020a) gai, iocl, bp, and hp is the larger production while cp, gg, ig, and mg have smaller production indian oil and gas companies (appendix 1). 3.1. research hypotheses h01: the profitability of the indian oil and gas firms’ is not significantly different. h02: the return on assets of the indian oil and gas firms’ is not significantly different. h03: the liquidity of the indian oil and gas firms’ is not significantly different. h04: the indian oil and gas firms’ solvency is not significantly different. 4. data analysis and results to figure out the effects of the firm’s size on the comparative financial effectiveness of the indian oil and gas firms, the analysis is divided into three categories. 4.1. disparity among the financial performance of indian oil and gas the disparity of profitability based on the total revenue reveals the differences in the earning capacity of the firms. it indicates that the firms with higher profitability maintain the gap between the revenue and its expenses by controlling total cost and or enhancing the sales revenue. return on assets reveals the utilization of the resources of the firms and measures the relational productivity of the resources by the firms. the higher roa indicates the high margin, and high velocity of business activities and reveals the managerial efficiency of the firms, internally. the liquidity ratio refers to the short-term paying capacity and is expected to maintain an optimum balance between the current assets and current liabilities. the debt-equity ratio indicates the solvency or long-term paying capacity of the firms. normally, the debt-equity ratio is expected to maintain an optimum balance between the debts and shareholders’ equities. because the lower debt-equity ratio indicates financial soundness but the firm cannot enjoy the benefits of the leverage. while the higher debt-equity ratio is not favorable when the normal rate of the return of the firm or the industry is lower than the cost of the debt. from table 1 it can be established that there is a significant difference in the profitability, return on resources, liquidity, and solvency of the indian oil and gas firms from 2015 to 2022. 4.2. variations and growth trend of relative financial performances variations and growth trends of relative financial performances reveal the dissimilarity among the financial performances and sustainability of growth of financial performances of firms. 4.2.1. variations and growth trend of profitability (pbt) of indian oil and gas firms variations of profitability reveal the dissimilarity between the margin of the revenue over its expenses while the growth trend reveals the sustainability of profitability over a period. the higher variations between the profitability ratio reveal the significant differences among the cost and managerial efficiency provided that the production and distribution of identical products. figure 1 reveals that there are bi-polar differences in profitability between the smaller and the larger indian and oil gas firms. smaller indian oil and gas firms are more productive than larger indian oil and gas firms which is an indication of improved cost and managerial efficiency. 4.2.2. variations and growth trend of return on assets (roa) of indian oil and gas firms variations of return on resources reveal the dissimilarity between the utilization of resources, velocity of business activities margin of revenue, and total cost while the growth trend reveals the sustainability of utilization of resources, velocity of business activities margin of revenue, and total cost over a period. the higher variations between the roa ratio reveal the significant differences among the cost and managerial efficiency provided that the production and distribution of identical products while lower roa indicates an excess of resources. figure 2 reveals that there are bi-polar differences in roa between the smaller and the larger indian and oil gas firms except for cp (chennai petroleum). smaller indian oil and gas companies have ali and fatima: do the size of oil and gas firms govern their financial performance? with special reference to indian oil and gas firms international journal of energy economics and policy | vol 13 • issue 2 • 2023 169 greater roas than larger indian oil and gas firms, which indicates higher cost and managerial efficiency and optimal resource levels or utilization of resources. 4.2.3. variations and growth trend of liquidity (current ratiocr) of indian oil and gas firms while the growth trend demonstrates the sustainability of the short-term paying capability of the businesses over time, variations in liquidity reflect the relational disparity between the margin of current assets and current liabilities of the business. the larger variations in the cr exemplify the significant disparities in the relationship between the firms’ current assets and current liabilities. the optimum level of cr is preferred while an extremely low and high level of liquidity is avoided due to poor short-term paying ability and negative impact on profitability or blockage of funds in current assets. figure 3 reveals the mutual significant differences among the indian oil and gas companies. the liquidity of the indian oil and gas firms does not vary according to their size. the liquidity of larger indian oil and gas firms, however, demonstrates symmetry, whereas variances are evident in smaller indian oil and gas firms’ production. exceptionally, liquidity is satisfactory in smaller production indian oil and gas companies while enhancements of the short-term paying ability are needed in the indian oil and gas sector companies. 4.2.4. variations and growth trend of solvency (debt-equity ratio) of indian oil and gas firms variations in solvency demonstrate the connection between the business’s debts or long-term loans and stockholders’ equity or cash, whereas the growth pattern indicates the sustainability of the business’s long-term paying capacity over time. the higher variations between the debt-equity ratios reveals the significant table 1: disparity among the financial performance of oil and gas companies h01 hypothesis f* fα** decision: h0 (if f≥f, don’t accept h0) h01.1 there is no significant difference among the profitability of the indian oil and gas companies 77.52397 2.178156 don’t accept h01.2 there is no significant difference among the return on assets of the indian oil and gas companies 8.846924 2.178156 don’t accept h01.3 there is no significant difference among the liquidity of the indian oil and gas companies 28.1775545 2.178156 don’t accept h01.4 there is no significant difference among the solvency of the indian oil and gas companies 7.042194 2.178156 don’t accept *f (fisher’s ratios) and **fα (critical values) calculated using excel’s calculation based on the relative measures of financial performance of indian oil and gas companies (appendix 2-5) source: based on the values given the appendix 2 figure 1: variations and growth trend of profitability of indian oil and gas firms figure 2: variations and growth trend of roa of indian oil and gas firms source: based on the values given the appendix 3 ali and fatima: do the size of oil and gas firms govern their financial performance? with special reference to indian oil and gas firms international journal of energy economics and policy | vol 13 • issue 2 • 2023170 differences among relational margin between the debts or longterm borrowings and shareholders’ funds of the businesses. the optimum level of debt-equity ratio is preferred while an extremely low and high level of solvency is avoided due to negative impact on profitability or blockage of funds in resources of the businesses and poor long-term paying ability. figure 4 reveals the mutual significant differences among the indian oil and gas companies. the solvency of the indian oil and gas firms does not vary according to their size. however, there is symmetry seen in the solvency of larger-scale indian oil and gas companies while the smaller indian oil and gas firms reflect the variability. the capital structure of the major producing indian oil and gas firms includes debts. while the lesser production of indian oil and gas enterprises can be seen to have a bi-polar capital structure. 4.3. homogeneity analysis of relative financial performances the governance of the relative financial performance by the size of the firms is illustrated by homogeneity analysis of the relative financial performance in the context of the size of the firms. 4.3.1. homogeneity of profitability the homogeneity of profitability of firms indicates the similarity of means of profitability ratios. based on the similarity of means of profitability groups can be formed and analyzing the profitability means groups with size and will indicate the governance of profitability by the size. table 2 reveals the grouping of means of profitability ratios of indian oil and gas companies. there is a similarity in the average profitability ratios of larger production indian oil and gas companies. while there are 3 groups (subset, 3 4, and 5) for smaller production oil and gas companies. however, indian oil and gas firms’ smaller-scale production has better profitability than their larger-scale production firms. it indicates the negative governance of the profitability in indian oil and gas companies by the size of the firm. 4.3.2. homogeneity of utilization of resources the homogeneity of return on resources of firms indicates the similarity of means of return on assets ratios. based on the similarity of means of return on assets groups can be formed and analyzing the profitability means groups with size and will indicate the governance of return on resources by size. table 3 reveals the grouping of means of the utilization of resources or return on assets ratios of indian oil and gas companies. there is a similarity (subset 1, and 2) of an average of return on assets ratios of larger production indian oil and gas companies. also, there are 2 groups (subset, 3, and 4) for smaller production oil and gas companies. however, there is a negligible difference between the average of return on assets of indian oil and gas firms’ smaller production and their bigger scale production firms. it indicates the negative but low governance of the return of resources in indian oil and gas companies by the size of the firm. figure 3: variations and growth trend of liquidity of indian oil and gas firms source: based on the values given the appendix 4 figure 4: variations and growth trend of solvency of indian oil and gas firms source: based on the values given the appendix 5 ali and fatima: do the size of oil and gas firms govern their financial performance? with special reference to indian oil and gas firms international journal of energy economics and policy | vol 13 • issue 2 • 2023 171 4.3.3. homogeneity of liquidity the homogeneity of liquidity of firms indicates the similarity of means of current ratios. based on the similarity of means of current ratios groups can be formed and analyzing the liquidity means groups with size and it will indicate the governance of return on resources by the size. table 4 reveals the grouping of means of liquidity ratio or current ratios of indian oil and gas companies. the subsets of the current ratios are not according to the ranks of the size of the indian oil and firms. hence, the liquidity is not governed by the size of the firms in indian oil and gas companies. 4.3.4. homogeneity of solvency the homogeneity of solvency of firms indicates the similarity of means of debt-equity ratios. based on the similarity of means of debt-equity ratios groups can be formed and analyzing the solvency means groups with size and it will indicate the governance of return on resources by the size. table 5 reveals the grouping of means of solvency or debt-equity ratios of indian oil and gas companies. the subsets of the debtequity ratios are not according to the ranks of the size of the indian oil and firms. hence, the solvency is not governed by the size of the firms in indian oil and gas companies. table 2: homogeneity analysis of profitability of indian oil and gas firms (2015–2022) indian oil and gas companies/ranks of size number of years/ sample size subset for alpha=0.05 1 2 3 4 5 cp (5) 8 1.4525 hp (4) 8 3.3513 bp (3) 8 4.2100 4.2100 iocl (2) 8 5.0038 5.0038 gg (6) 8 8.9950 8.9950 gai (1) 8 10.7438 ig (7) 8 21.1313 mg (8) 8 32.1325 significant 0.435 0.112 0.968 1.000 1.000 means for groups in homogeneous subsets are displayed. uses harmonic mean sample size=8.000. tukey’s hsd analysis based on the values given in the appendix 2. cp: chennai petroleum, hp: hindustan petroleum, bp: bharat petroleum, iocl: indian oil corporation limited, gg: gujarat gas limited, gai: gas authority of india, ig: indraprastha gas limited, mg: mahanagar gas limited, hsd: honestly significant difference table 3: homogeneity analysis of utilization of resources return on asset of indian oil and gas firms (2015–2022) indian oil and gas companies/ ranks of size number of years/ sample size subset for alpha=0.05 1 2 3 4 cp (5) 8 1.7300 iocl (2) 8 5.1213 5.1213 hp (4) 8 5.6550 5.6550 bp (3) 8 7.6763 7.6763 7.6763 gai (1) 8 7.7538 7.7538 7.7538 gg (6) 8 8.2850 8.2850 ig (7) 8 13.4413 13.4413 mg (8) 8 14.7263 significant 0.080 0.774 0.107 0.998 means for groups in homogeneous subsets are displayed. uses harmonic mean sample size=8.000. tukey’s hsd analysis based on the values given in the appendix 3. cp: chennai petroleum, hp: hindustan petroleum, bp: bharat petroleum, iocl: indian oil corporation limited, gg: gujarat gas limited, gai: gas authority of india, ig: indraprastha gas limited, mg: mahanagar gas limited, hsd: honestly significant difference table 4: homogeneity analysis of liquidity (current ratios) of indian oil and gas firms (2015–2022) indian oil and gas companies/ ranks of size number of years/ sample size subset for alpha=0.05 1 2 3 4 gg (6) 8 0.5675 cp (5) 8 0.6688 0.6688 iocl (2) 8 0.7813 0.7813 hp (4) 8 0.8125 0.8125 bp (3) 8 0.8525 0.8525 gai (1) 8 1.0238 ig (7) 8 1.2725 mg (8) 8 1.3938 significant 0.122 0.268 0.131 0.763 means for groups in homogeneous subsets are displayed. uses harmonic mean sample size=8.000. tukey’s hsd analysis based on the values given in the appendix 4. cp: chennai petroleum, hp: hindustan petroleum, bp: bharat petroleum, iocl: indian oil corporation limited, gg: gujarat gas limited, gai: gas authority of india, ig: indraprastha gas limited, mg: mahanagar gas limited, hsd: honestly significant difference table 5: homogeneity analysis of solvency (debt‑equity ratios) of indian oil and gas firms (2015–2022) indian oil and gas companies/ ranks of size number of years/ sample size subset for alpha=0.05 1 2 3 mg (8) 8 0.0001 ig (7) 8 0.0087 gai (1) 8 0.1063 0.1063 iocl (2) 8 0.3649 0.3649 0.3649 bp (3) 8 0.4759 0.4759 0.4759 hp (4) 8 0.6138 0.6138 cp (5) 8 0.6908 gg (6) 8 0.7385 significant 0.084 0.052 0.308 means for groups in homogeneous subsets are displayed. uses harmonic mean sample size=8.000. tukey’s hsd analysis based on the values given in the appendix 5. cp: chennai petroleum, hp: hindustan petroleum, bp: bharat petroleum, iocl: indian oil corporation limited, gg: gujarat gas limited, gai: gas authority of india, ig: indraprastha gas limited, mg: mahanagar gas limited, hsd: honestly significant difference 5. discussion and conclusions based on the above disparity it can be explained that there are significant differences in the profitability, return on resources, liquidity, and solvency of the indian oil and gas companies. as per variations and growth trends of relative financial variables, the ali and fatima: do the size of oil and gas firms govern their financial performance? with special reference to indian oil and gas firms international journal of energy economics and policy | vol 13 • issue 2 • 2023172 profitability and return on resources of smaller indian oil and gas companies are an increasing trend and higher than those of larger size manufacturing indian oil and gas firms, indicating better cost, managerial efficiency, and the optimum level of total resources or utilization of resources performances. liquidity is satisfactory in smaller production indian oil and gas companies while enhancements of the short-term paying ability are needed in the indian oil and gas sector companies. the solvency of the major indian oil and gas businesses, however, exhibits symmetry. although symmetric variations can be seen in the lesser producing indian oil and gas companies. the long-term loans in indian oil and gas firms’ capital structures are represented by the larger scale manufacturing firms, whilst the smaller scale production firms show their bi-polar capital structure. homogeneity analysis indicates that the profitability of indian oil and gas firms is governed by the size negatively and directly while the size of the firm governs return on resources negatively but negligibly. the size of the company has no impact on the both short-or long-term payment capacity of indian oil and gas firms. the smaller indian oil and gas firms have better cost and managerial efficiency and resource utilization than the bigger scale producing oil and gas firms. smaller firms can therefore increase their level of activity to enhance absolute earnings, whereas larger indian oil and gas production firms must enhance their cost and administrative efficiencies to improve profitability and resource utilization. the size of the firm does not correlate with the ability to pay in the shortand long-term. long-term debts may be incorporated into the smaller production of indian oil and gas firms to reap the advantages of working with equity. 6. acknowledegement “this study is supported via funding from prince sattam bin abdulaziz university project number (psau/2023/r/1444)”. references abbasi, a., malik, q.a. (2015), firms’ size moderating financial performance in growing firms: an empirical evidence from pakistan. international journal of economics and financial issues, 5(2), 334-339. alhassan, i., islam, k.a. (2021), liquidity management and financial performance of listed oil and gas companies in nigeria. international journal of accounting and finance review, 8(1), 15-25. ali, a. (2020a), do the giant players enjoy profitability? analytical study of pharmaceutical industry of india. journal of talent development and excellence, 12(2s), 3249-3260. ali, a. (2020b), firm size and solvency in indian pharmaceutical sector: a relational co-movement analysis. accounting, 6(7), 1199-1208. ali, a. (2021), firm size and supply chain finance in indian pharmaceutical industry: relational firm analysis of size determinants and cash conversion cycle. accounting, 7(1), 197-206. ali, a. (2022), pre and post covid-19 disparity of financial performance of oil and gas firms: an absolute and relational study. international journal of energy economics and policy, 12(6), 396-403. amoa-gyarteng, k. (2021), corporate financial distress: the impact of profitability, liquidity, asset productivity, activity and solvency. journal of accounting business and management (jabm), 28(2), 104-115. arise, o., adegbie, f. (2021), business process reengineering and financial stability of listed oil and gas companies in nigeria. international journal of science academic research, 2(5), 1541-1549. baidoo, d.a. (2022), factors influencing capital structure: an empirical evaluation of major oil and gas producing companies operating ghana. international journal of finance research, 3(4), 294-311. dhingra, r., dev, k. (2016), determinants of capital structure-a study of oil industry in india. international journal of engineering and management research (ijemr), 6(1), 35-42. ghafoorifard, m., sheykh, b., shakibaee, m., joshaghan, n.s. (2014), assessing the relationship between firm size, age and financial performance in listed companies on tehran stock exchange. international journal of scientific management and development, 2(11), 631-635. kallmuenzer, a., peters, m. (2018), entrepreneurial behaviour, firm size and financial performance: the case of rural tourism family firms. tourism recreation research, 43(1), 2-14. kalyani, s., mathur, n. (2017), impact of capital structure on profitability: with reference to selected companies from oil and natural gas industry of india. inspira journal of modern management and entrepreneurship (jmme), 7(3), 129-137. kanagaraj, m.p., gouwsigan v. (2021), a study on financial performance of indian oil corporation limited. epra international journal of multidisciplinary research (ijmr), 7(7), 62-64. kumar, p. (2019), analysis of financial performance of oil and gas industry in india. think india journal, 22(10), 1869-1875. lopez‐valeiras, e., gomez‐conde, j., fernandez‐rodriguez, t. (2016), firm size and financial performance: intermediate effects of indebtedness. agribusiness, 32(4), 454-465. meghanathi, p., chakrawal, a. (2021a), impact of financial leverage on profitability of reliance industries ltd. journal la bisecoman, 2(5), 15-22. meghanathi, p., chakrawal, a.k. (2021b), an analytical study of liquidity and profitability: analysis of selected oil and gas companies in india. journal of social commerce, 1(1), 34-40. mistry, d., vyas, p. (2021), determinants of profitability of public oil and gas sector in india. journal of finance and accounting, 8(2), 20-35. mohammed, n.f., puat, s.a., amirrudin, m.s., hashim, a. (2020), leverage, liquidity and profitability ratios: accountability of malaysian listed oil and gas firms. humanities social sciences reviews, 8(2), 941-947. nurwulandari, a. (2021), effect of liquidity, profitability, firm size on firm value with capital structure as intervening variable. atestasi jurnal ilmiah akuntansi, 4(2), 257-271. pattiruhu, j.r., paais, m. (2020), effect of liquidity, profitability, leverage, and firm size on dividend policy. the journal of asian finance economics and business, 7(10), 35-42. ramya, s., chandran, rp. (2018), financial analysis and performance of indian oil corporation ltd. international journal for advance research and development, 3(3), 1-5. reddy, y.v., narayan, p. (2018), the impact of liquidity and leverage on profitability: evidence from india. iup journal of accounting research and audit practices, 17(1), 58-77. sulaiman, l.a. (2012), does restructuring improve performance? an industry analysis of nigerian oil and gas sector. research journal of finance and accounting, 3(6), 55-62. taqi, m., khan, r., anwar, i. (2020), financial leverage and profitability: evidence from oil and gas sector of india. gis business, 15(4), 665-687. ali and fatima: do the size of oil and gas firms govern their financial performance? with special reference to indian oil and gas firms international journal of energy economics and policy | vol 13 • issue 2 • 2023 173 appendix tables appendix 1: ranking of indian oil and gas companies based on average of revenue, total assets, and working capital absolute amount/ranks indian oil and gas companies iocl bp gai hp cp gg ig mg average revenue 448,488.26 95,304.8463 258,130.973 241,769.615 34,078.23 8914.725 5189.425 2709.111 r1 1 4 2 3 5 6 7 8 total assets 291,187.29 277,883.47 108,881.55 100,307.49 13,288.18 7372.34 5951.90 3446.88 r2 1 2 3 4 5 6 7 8 working capital −32,131.6 −7761.9675 227.9075 −11,473.675 −2868.98 −756.164 462.7075 347.9638 r3 8 6 3 7 5 4 1 2 average ranks (r4) 3.33 4 2.67 4.67 5 5.33 5 6 overall ranking 2 3 1 4 5.5 7 5.5 8 source: based on financial statements of concerned companies available on the website of moneycontrol.com. cp: chennai petroleum, hp: hindustan petroleum, bp: bharat petroleum, iocl: indian oil corporation limited, gg: gujarat gas limited, gai: gas authority of india, ig: indraprastha gas limited, mg: mahanagar gas limited appendix 2: profitability ratio of indian oil and gas companies years iocl bp gai hp cp gg ig mg 2015 1.43 3.09 7.33 2.00 −1.76 7.05 17.47 25.88 2016 4.42 5.57 6.01 3.18 2.93 4.52 17.09 27.24 2017 7.23 5.39 11.58 4.78 4.92 5.93 22.18 33.21 2018 7.62 4.72 12.68 4.16 4.48 7.45 22.27 35.83 2019 4.73 3.48 12.27 3.37 −0.72 7.78 20.30 33.09 2020 1.56 1.31 10.70 0.95 −8.11 11.63 21.31 35.64 2021 7.77 6.83 10.87 6.04 5.66 17.17 26.15 39.71 2022 5.27 3.29 14.51 2.33 4.22 10.43 22.28 26.46 source: based on financial statements of concerned companies available on the website of moneycontrol.com. cp: chennai petroleum, hp: hindustan petroleum, bp: bharat petroleum, iocl: indian oil corporation limited, gg: gujarat gas limited, gai: gas authority of india, ig: indraprastha gas limited, mg: mahanagar gas limited appendix 3: return on resources ratio of indian oil and gas companies years iocl bp gai hp cp gg ig mg 2015 2.39 7.29 5.74 4.04 −0.35 6.43 14.24 13.89 2016 5.09 9.78 4.33 5.48 7.18 2.51 12.36 13.11 2017 7.37 8.73 6.33 7.91 8.95 3.45 13.97 14.99 2018 7.6 7.96 7.95 7.32 6.44 4.39 13.61 15.87 2019 5.35 6.16 9.35 5.81 −1.39 5.85 13.22 15.87 2020 0.42 2.12 9.66 2.31 −16.39 15.11 15.84 19.22 2021 6.53 13.54 6.67 8.12 1.69 15.09 11.71 13.46 2022 6.22 5.83 12 4.25 7.71 13.45 12.58 11.4 source: based on financial statements of concerned companies available on the website of moneycontrol.com. cp: chennai petroleum, hp: hindustan petroleum, bp: bharat petroleum, iocl: indian oil corporation limited, gg: gujarat gas limited, gai: gas authority of india, ig: indraprastha gas limited, mg: mahanagar gas limited appendix 4: liquidity (current) ratio of indian oil and gas companies years iocl bp gai hp cp gg ig mg 2015 0.99 0.93 1.06 1.16 0.72 0.74 0.87 1.09 2016 0.88 0.89 0.99 1.03 0.74 0.36 1.02 1.46 2017 0.72 0.79 1.09 0.72 0.82 0.37 1.39 1.26 2018 0.67 0.83 1.02 0.78 0.74 0.47 1.52 1.35 2019 0.81 0.99 1.10 0.76 0.68 0.62 1.46 1.43 2020 0.69 0.70 0.97 0.65 0.34 0.79 1.39 1.59 2021 0.73 0.93 0.86 0.70 0.54 0.64 1.32 1.58 2022 0.76 0.76 1.10 0.70 0.77 0.55 1.21 1.39 source: based on financial statements of concerned companies available on the website of moneycontrol.com. cp: chennai petroleum, hp: hindustan petroleum, bp: bharat petroleum, iocl: indian oil corporation limited, gg: gujarat gas limited, gai: gas authority of india, ig: indraprastha gas limited, mg: mahanagar gas limited ali and fatima: do the size of oil and gas firms govern their financial performance? with special reference to indian oil and gas firms international journal of energy economics and policy | vol 13 • issue 2 • 2023174 appendix 5: solvency (debt‑equity) ratio of indian oil and gas companies years iocl bp gai hp cp gg ig mg 2015 0.4816 0.5224 0.2684 0.9272 0.6042 0.7488 0.0693 0.0000 2016 0.2829 0.5039 0.1890 0.5793 0.2300 0.8120 0.0000 0.0000 2017 0.2037 0.4643 0.0788 0.3085 0.0610 1.3931 0.0000 0.0000 2018 0.1699 0.4324 0.0221 0.3687 0.0748 1.1985 0.0000 0.0006 2019 0.3190 0.6432 0.0197 0.4017 0.2324 0.9566 0.0000 0.0000 2020 0.5252 0.6167 0.0821 0.7695 1.3487 0.5575 0.0000 0.0000 2021 0.5014 0.3123 0.1036 0.7481 2.1185 0.1718 0.0000 0.0000 2022 0.4352 0.3117 0.0869 0.8074 0.8571 0.0698 0.0000 0.0000 source: based on financial statements of concerned companies available on the website of moneycontrol.com. cp: chennai petroleum, hp: hindustan petroleum, bp: bharat petroleum, iocl: indian oil corporation limited, gg: gujarat gas limited, gai: gas authority of india, ig: indraprastha gas limited, mg: mahanagar gas limited . international journal of energy economics and policy | vol 8 • issue 6 • 2018128 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(6), 128-134. human capital of transnational corporations in the energy sector yuliya i. bogomolova¹*, elena v. belokurova², vladimir r. meshkov³, evgenii o. pavlov4 ¹institute of international economic relations, moscow, russian federation, ²nizhnevartovsk branch of tyumen industrial university, nizhnevartovsk, russian federation, ³plekhanov russian university of economics, moscow, russian federation, 4jsc “plakart,” moscow, russian federation. *email: j.bogomolova@imes.su received: 15 july 2018 accepted: 30 september 2018 doi: https://doi.org/10.32479/ijeep.6901 abstract for the development of the energy sector, at the present stage, it is necessary to use certain resources. the paper analyzed the application of human capital in the energy sector. to achieve this goal, the authors used the method of offset. it is established that the world energy consumption increases, and the dynamics of the employed population in the energy sector remains within the same norm. it is determined that an important factor for the development of the economy is the gross regional product. as its increase helps to reduce energy intensity. the authors show that human potential is not only a personal characteristic received by the employee independently, but also by the acquired position, which is ensured by the implementation of corporate tools. the paper considers the economic, social and legal provision of such instruments. keywords: labor resources, electrification, energy efficiency, expert evaluation, energy system jel classifications: a10, p48 1. introduction energy is a set of industries that supply the economy with energy resources. it includes all fuel industries and electric power industry with their enterprises and connections ensuring the exploration, development, production, processing and transportation of energy resources, as well as the production and transportation of thermal and electric energy received with their use. for the development of any area, including energy, human resources (human capital) are needed (teleuyev et al., 2017; kapitonov and voloshin, 2017). the transnationalization of human capital is conditioned by the activity and development of supranational tncs as organizations, the basis for the formation and functioning of which are processes of internationalization of production, scientific and technical activities, capital, etc. in modern conditions, tncs are a form of human capital formation, a means of using and realizing the capabilities of each individual. employment in the world’s 100 largest corporations was 5.1 million in 1993, foreign workers accounted for 47.7%, in 2010 8.7 million and 56.1% respectively (del et al., 2015). the data presented indicate a significant increase in the scope of tnc control of the world’s labor resources (vinichenko and shihovtsova, 2016). due to the high degree of development of the production and technological base and the sufficient maturity of the labor relations system, as well as the important place for the social development of the economic entity as one of the bases of its competitiveness, the reproduction processes of the human potential of a large enterprise should not be spontaneous (wang et al., 2018). in this context, the key role of the system of managing the social development of an enterprise as a complex instrument that ensures the stable and regulated nature of the phenomena under consideration is unquestionable (li et al., 2018). in practice, the factor being investigated appears in the form of a cumulative employee of the enterprise. in this regard, it seems that the correct point of this journal is licensed under a creative commons attribution 4.0 international license bogomolova et al.: human capital of transnational corporations in the energy sector international journal of energy economics and policy | vol 8 • issue 6 • 2018 129 view that the human factor can be accumulated and realized only through the development of all employees of the enterprise and their professional joint activities, although formulated with reference to the services sector, is quite relevant for other business entities (shirangi et al., 2018). therefore, the human factor exists in the form of a cumulative employee of a service enterprise. the cumulative employee of a service enterprise is a group of employees engaged in joint work, including a business leader, who constantly work in the same enterprise and expend individual labor as a single unit in order to best meet the growing service needs (atems and hotaling, 2018). thus, the initial thesis is this: the qualitative and quantitative parameters of the cumulative employee of an power enterprise have a major influence on the nature of the functioning of the economic entity, especially in terms of ensuring its stable and long-term sustainable development. in the light of the foregoing, an in-depth review of the positions of various scientists and scientific schools on the problems under consideration seems to be theoretically and practically meaningful. 2. materials and methods proceeding from the notion of potential as a collection of available energetic resources that can be mobilized to achieve the goals of the system, it is suggested to use the offset method for its evaluation (vinichenko and strokova, 2016; kittichaisaree, 2017). still, the system has different potentialities to achieve a certain development strategy in the conditions of existing resource constraints, in particular, human and intellectual capital: , , , min( ; ) 100%i p i posi i p q q pes q = × (1) where pesi– the potential of the economic system in the i th strategic direction; qi,p– the planned state of the system according to the ith vector of strategic objectives; qi,pos– the possible state of the system for the ith direction of strategic development, which is determined by the volume of human and intellectual capital. to measure intellectual capital, we calculate the value of the consumer capital of the country’s economy, which is characterized by the level of competitiveness of its industries: , ,` `` ` `` , , ; t i t ii i e i e i g g ck ck g g = = (2) where – the consumer capital of the ith industry, respectively, in the domestic and foreign markets; gt,i group index of production of the ith industry in terms of technical parameters; ' '', ,; e i e ig g – the group index of the ith industry output by economic parameters, respectively, for the domestic and foreign markets. the indicator of the consumer capital is used for an estimation of a borrowed market share’s speed of change by production of ith branch of own manufacture during time t: (danielewicz-betz, 2016). ` ` ` `( ) ( 1)(1 )i i i i d d ck d t δ δ = − − (3) `` `` `` ``( ) ( 1)(1 )i i i i d d ck d t δ δ = − − (4) where ' '';i id d – respectively, the share of the domestic and foreign market, which deals with the products of its own production of the ith industry. structural (organizational) capital of the economy is characterized by the level of development and use of technological structures and can be determined by the vector of the share of added value received by each branch – v(v1,v2.,vn). the average level of organizational capital (oc) of all sectors of the economy will be calculated as follows: 1 1 ( ) n i ii n ii x v ok x = = × = ∑ ∑ (5) where xi– is the equilibrium output of the i th industry; n – is the number of the economy branches. the prerequisite for the growth of oc is consumer capital. the added value of the ith industry, which is calculated as xi×oki, excluding depreciation and business taxes, is the source of such revenues: xi×oki-ai-ti=wi+ri+pi (6) where ai– depreciation on fixed assets; ti– indirect taxes on business; wi– income of human capital owners; ri– income of borrowed capital owners; pi– income of the capital owners. given this, the amount of human capital of the ith industry will be calculated by the formula: 100%ii i w lk c = × , where 100%i ii i i r p c pk vk + = × + (7) where lki is the human capital of the i th industry; pki; vki– respectively, the volume of own and borrowed capital that is used by the ith industry; – ci– is the measured average capital price. the need to measure the intellectual capital of the microeconomic system is conditioned by the need to assess the level of competitiveness of business entities in market conditions. 3. results and discussion currently, the definition of the human capital of tncs is inherent in its identification with the personnel, human potential, intellectual capital of transnational corporations. the human capital of tncs is the aggregate labor force that represents the entire mass of workers who, to some extent, participate in the activities of the corporation, ensuring its functioning in all forms and stages of the bogomolova et al.: human capital of transnational corporations in the energy sector international journal of energy economics and policy | vol 8 • issue 6 • 2018130 capital movement on the basis of organizational and economic ties, national in form and international in content (wetzel, 2016). but in order to understand how much human capital is needed for the development of the industry, the authors conducted an analysis of consumption, fuses of energy resources, both in the world and in the russian federation. world consumption of electricity increased in 2016, after its stabilization in 2015, but its growth remained below its long-term growth trend. asian countries that are not part of the oecd (india, indonesia, malaysia, thailand and others), due to their dynamic economic development and the electrification of their territory, are the second main region that provoked an increase in electricity consumption. improved energy efficiency has led to a reduction in electricity demand in the united states, for the 6th time in 8 years, as well as to a reduction in demand in japan and its stabilization in the european union. despite the fact that china, which is the world’s largest energy consumer since 2009, has registered a jump in growth in 2016, its energy consumption has seriously slowed down over the last 3 years compared to the trends of 2000–2013 (salim et al., 2017). india continues to make a significant contribution to global energy consumption, and providing a quarter of global growth in 2016. dynamics of strong growth was recorded in turkey and in countries such as indonesia, malaysia and south korea. in contrast, in latin america, such as brazil, colombia and mexico, declined. at the same time, demand in the european union countries remains stable. in figure 1 shows the dynamics of oil production in the world. oil reserves by region are shown in figure 2. the systematization of possible indicators allows the development of criteria that will be used to assess the level of innovation potential of workers. the criteria that are used in practice may vary depending on the characteristics of enterprises (klikauer a universal system of criteria is impossible, but a number of factors that regulate the activities of the vast majority of these enterprises should be determined, which is quite realistic (solaiman, 2017). as a result of expert assessments basic requirements to the criteria and their content were formulated (klikauer, 2016). according to existing requirements, 9 main criteria were selected by expert estimates, on the basis of which was developed a method of complex assessment of the level of innovative potential of enterprise personnel (starr-glass, 2017). they were: intensity of innovation processes (innovations speed); intellectual development of personnel; level of professionalism (competence of personnel); educational level; level of information and communication support; investment in innovation and the achieved technical and technological level of the enterprise; ensuring long-term competitiveness; ensuring financial sustainability and innovation effectiveness; psychological climate. according to the proposed methodology, 9 indices (on a point scale) are evaluated expertly for a particular enterprise, with the maximum development of the planned results (ness and cope, 2016) corresponding to the unit. the dynamics of employment in the russian federation, in the energy sector is presented in table 1. employment of the population is represented as a percentage of the total number of industries. in 2010, primary energy consumption in russia almost reached the level of the pre-crisis peak of 2008, and in 2014 it exceeded it by 3%. according to preliminary estimates for 2015, it fell to almost the level of 2008. in 2007–2014, the most dynamically energy consumption grew in transport and non-energy needs (shuen et al., 2014; buley et al., 2016). in 2015, russia’s gdp remained approximately at the level of 2008 and 1990. primary energy cons umption was lower than in 1990, by 27%. russia is moving to a growth model when slow gdp growth is not accompanied by an increase in energy consumption. many developed countries have been developing for this model for 10–20 years. for the developers of the energy strategy of the russian federation this development seems strange and undesirable. in it, in all scenarios, primary energy consumption continues to grow. the dynamics of energy consumption in russia by main sectors of the economy is presented in figure 3. an important factor is the characteristics of the dynamics of the regional economy. in regions where the gross regional product (grp) grew dynamically, the energy intensity decreased more rapidly, and vice versa. this was due to more dynamic structural shifts in favor of less energy-intensive activities, increased capacity utilization, more dynamic modernization of equipment and buildings due to more intensive implementation of energy efficiency policies and programs (dilaver et al., 2014). also, an important role in the dynamics of primary energy consumption is the growth of their use for non-energy needs. perhaps, when figure 1: dynamics of oil production in the world figure 2: explored world oil reserves by region, % bogomolova et al.: human capital of transnational corporations in the energy sector international journal of energy economics and policy | vol 8 • issue 6 • 2018 131 comparing regions by the energy intensity level of grp, this component of energy consumption should not be taken into account. to do this, it should be more clear than what rosstat is currently doing, it is determined what is included and how the use of energy for non-energy needs is determined (burke and stephens, 2017). another problem is the assignment of energy consumption in interregional transport systems pipelines, railways, airports to consumption of individual regions and a change in the statistics of accounting for these volumes. the third reason is the poor quality of data on fuel consumption in road transport. the dynamics of the world production of energy resources is shown in figure 4. the distribution of energy consumption by sectors of the economy is shown in figure 5. for example, the structure of energy distribution by industry in ugra is described in figure 6. the total volume of electricity consumption and generation in russia as a whole consists of indicators of electricity consumption and production of facilities located in the unified energy system of russia and facilities operating in isolated power systems (taymyr, kamchatka, sakhalin, magadan, chukotka, power systems in central and western yakutia). the actual performance of the energy systems of isolated territories is represented by the subjects of operational dispatch control of these power systems. from january 1, 2017, the consumption and output indicators for ues of russia and ues of the south are formed taking into account the crimean energy system. the maximum consumption of electric power in the ues of russia in 2017 was fixed on 9 january. its value was 151 170 mw, which is 0.1% more than the same indicator in 2016 (mahmood and ahmad, 2018). the increase in electricity and capacity consumption by ues of russia in 2017 is due to the temperature factor: in february 2017, the power system experienced a significant decrease in the outside air temperature relative to the same indicator in 2016 by 4.6°c. the average monthly air temperature, which was lower than in 2016, was also in april–august 2017. the main load for ensuring the demand for electricity in the ues of russia in december 2017 was carried by thermal power plants, the production of which amounted to 62.2 billion kwh, which is 4.7% less than in december 2016. the hydropower plant produced 14.4 billion kwh in the same month (5.6% more than in december 2016), the nuclear power plant output was 18.5 billion kwh (4.0% less than in december 2016), the development of power plants of industrial enterprises 5.5 billion kw • h (0.2% more than in december 2016). the maximum power consumption by ues of russia in december 2017 was 146 526 mw, which is less than the maximum capacity consumption in december 2016 by 3.0%. the decrease in electricity and capacity consumption in december 2017 relative to the same month of 2016 is due to the temperature factor: the average monthly outside air temperature in december 2017 as a whole for the ues of russia was −6.1°c, which is 4.6% higher than the december 2016 temperature from. the branch structure of the power supply potential is shown in the figure 7. the authors considered an example of the use of energy resources in the republic of belarus. the main amount of electricity in the republic is consumed in industry. a feature of the electric power industry in belarus is that almost 100% of all electricity produced is provided by thermal power plants that operate on imported fuel (fuel oil, natural gas). more than 50% of electricity is generated in the minsk and gomel regions (pereira and silva, 2017). but the most powerful thermal power plant in the republic of belarus is lukomlskaya gres with a capacity of 2.4 million kw (2.4 gw) located in the vitebsk region. about 1 gw has capacity berezovskaya gres, the smaller smolevichskaya and vasilevichskaya gres. part of the electricity is generated by chp plants located in large cities (minsk, vitebsk, gomel, etc.) as well as at chp plants at some belarusian enterprises: sugar factories, the belaruskaliy association, the dobrush paper mill. the energy system of the country includes the patriarch of the domestic energy-belgres, which was erected in 1930. it is located in the bowels of peat bogs two dozen kilometers from orsha in the town of orekhovsk, orsha district. and now let’s imagine the amount of energy used in russia (figure 8). these indicators affect, among other things, the number of employed people in a particular sector of the economy. the increase in energy consumption is proportional to the growth of the population of the planet (which continues to increase). following the increase in energy consumption in industrialized countries, which have risen sharply since the 1920s, in developing countries, such growth began in the 1960s, and continues at a similar pace, sometimes even ahead of schedule. the peak of oil production falls on 2000–2025, gas in different countries is in the interval between 2000 and 2040; but by 2100, and according to the optimistic and pessimistic scenario, a significant decline is expected. the reason is that stocks are exhaustible. so, as of 2005, oil has already produced 152 billion tons, proven reserves 179 billion tons; gas already produced 86 trillion. m3, table 1: structure of employment in the energy sector, % activity\year 2005 2006 2007 2008 2009 2010 2011 2014 2016 power engineering 2.9 3.1 2.9 3.0 3.2 3.3 3.2 3.3 3.2 figure 3: dynamics of energy consumption in russia by main sectors of the economy bogomolova et al.: human capital of transnational corporations in the energy sector international journal of energy economics and policy | vol 8 • issue 6 • 2018132 proven reserves of 180 trillion cubic meters. at the same time, we should not forget that all readily available deposits have already been worked out, which means that each newly extracted unit of organic fuel will cost more and more (wang et al., 2016). taking into account the above, starting from 2011 the unsatisfied energy demand is predicted, which will grow and by 2050 will amount to more than 5 million tons of oil equivalent. russia is for the most part a northern country with very significant heating costs, still far behind developed countries in terms of energy efficiency of the economy. the specific energy intensity of the russian economy (in terms of purchasing power parity) is 2.5 times higher than the world average, 2.8 times higher than the average for the oecd countries and 3.5 times higher than the energy intensity of japan’s gdp. the reasons for this situation, apart from the harsh climatic conditions and the territorial factor, are the structure of industrial production formed over a long period of time and the growing technological backwardness of energy-intensive industries and housing and communal services, as well as an underestimation of the cost of energy resources that does not stimulate energy saving (dilaver et al., 2014). the existing energy saving potential in russia is about 40-45% of current energy consumption, or * million tons of equivalent fuel. the application of the algorithm for all industrial instruments, based on the energy company oao nk “rosneft” (table 2). thus, the proposed methods of analysis and evaluation make it possible to really assess the level of social work carried out at the levels of individual directions. all this allows not only to increase the efficiency of reproduction of the human potential of the corporation, but also to strengthen the company’s market positions through the formation of its positive image and increase of investment attractiveness. 4. conclusions the energy complex is developing at an ever-increasing rate. but for the development of a certain industry, including energy, it is necessary to attract human resources. the transnationalization of human capital is carried out in the structure of control, concentration and monopolization of tncs on the basis of: international migration labor and education; international production, scientific and technical, innovative cooperation; international private equity movement; international cooperation, the organization of which is not connected with participation in the capital. figure 4: dynamics of world production of energy resources, billion tons of electricity figure 5: structure of natural gas consumption in russia figure 6: structure of energy distribution by industry in ugra figure 7: branch structure of the power supply potential figure 8: the structure of energy consumption in russia bogomolova et al.: human capital of transnational corporations in the energy sector international journal of energy economics and policy | vol 8 • issue 6 • 2018 133 thus, the human capital of transnational corporations are – controlled, concentrated and monopolized by tncs knowledge, abilities and skills of workers engaged in its global supply system, which is a resource of creation and growth of value, income and a factor of international competitiveness. the monopolization of human capital by transnational corporations has conflicting consequences for national economies. the transnationalization of human capital is a factor in its globalization. the components of global human capital, which is formed under the influence of post-industrial social changes, is the human capital of tncs, regional integration entities, network electronic communities, international and transnational innovation clusters. in practice, the functioning of the system of managing the social development of an enterprise in accordance with the objective logic of the basic functions of management is in the form of planning, organization and control in the sphere of reproduction of the human potential of the business entity. the recently adopted concept of “corporate social policy (csp)” embraces both the processes of social development of the table 2: assessment of the effectiveness of oao nk rosneft, 2016 company csp tools ojsc “rosneft oil company” absolute value scores average monthly calculated salary (thousand rubles) 61.023 8.8 the ratio of the average monthly salary in the company to that in the region (%) 228 10 salary score 9.4 annual labor protection costs per employee (thousand rubles/person) 24.28 10 the number of victims at work to the number of the corporation employees (in per mille) 0.2 10 labor safety assessment score 10 number of employees covered in the reporting year by production training to the number of the corporation employees (%) 75.6 10 the ratio of annual expenses for industrial training to the annual remuneration fund (%) 0.35 2.1 production training score 6.05 "social partnership" instrument number of the trade union members in relation to the number of the corporation employees (%) 24.1 2 the share of employees covered by the collective contract (%) 72.8 7.5 score values of social partnership 4.75 csp score in the production sphere 7.55 salary indexing efficiency (%) 9.5 10 the ratio of the nominal salary index to the consumer price index (in the number of times) 1.1 10 salary indexing scores 10 the amount of annual payments of a social nature per employee (thousand rubles/person) 35.6 6.8 the ratio of the annual social benefit fund to the annual remuneration fund (%) 4.95 4.9 social package scores 5.85 amount of annual expenses for medical and sanatorium-resort services per employee (thousand rubles/person) 9.5 1.9 annual housing costs per participant of the relevant programs (thousand rubles/person) 650 10 annual payments on the pension program per participant (thousand rubles/person) 23.8 2.3 scores of the fundamental social benefits 4.73 csp score in the consumption sphere 6.86 number of employees covered in physical culture and sports by number of employees (%) 47 7 the amount of annual expenses for physical culture and sport per one employee of the corporation (thousand rubles/person) 1.98 3.3 physical culture and sports scores 5.15 number of employees covered by cultural events to the number of employees (%) 41 6 the amount of annual expenses for cultural events per employee (thousand rubles/person) 1.98 4.1 cultural events scores 5.05 number of employees covered by active recreation and tourism to the number of employees (%) 42 6 the amount of annual expenses for active recreation and tourism per one employee of the corporation (thousand rubles/person) 1.99 4 active recreation and tourism scores 5 csp score in the recreation sphere 5.07 the share of environmental expenses in the total social costs of the corporation (%) 58.23 10 the ratio of the environmental expenses to the net profit of the corporation (%) 3.15 5.5 environmental protection scores 7.75 the share of expenses on regional social infrastructure in the total social costs of the corporation (%) 13.7 6.2 the ratio of the expenses regional to the social infrastructure and the net profit of the corporation (%) 0.72 1.75 regional social infrastructure scores 3.98 the share of expenses for the support of small nations and local traditions in the total social costs of the corporation (%) 5.12 8.3 the ratio of the expenses for the support of small nations and local traditions to the net profit of the corporation (%) 0.29 2.75 support for small nations and local traditions scores 5.52 csp score in the sphere of a certain habitat 5.75 csp scores in general (on a 10-score system) 6.31 bogomolova et al.: human capital of transnational corporations in the energy sector international journal of energy economics and policy | vol 8 • issue 6 • 2018134 enterprise and the management system for them. in the light of the foregoing, it can be argued that the categories “social management system of the enterprise” and “csp” (in its management part) are synonymous. managing the reproduction of human potential in the production sector is based on the use of the following tools: labor remuneration; labor protection; production training; social partnership. when managing the reproduction of human potential in the sphere of consumption, such social instruments are used: indexation of wages; providing employees with a decent social package; meeting the needs of staff in basic social goods and services. the main tasks of the methods of analysis and evaluation of the csp are to ensure the measurement of the social management’s results both for each instrument and for their enlarged groups and the system of social management in general. to this end, based on the analysis of rsc data, social reports of leading corporations on the website of the ruie, jsc umc statistics, interviews with employees and experts, we developed the following principal algorithm: two or three key indicators (parameters) are substantiated for each csp tool, which most fully characterize the essence of the tool used; to ensure comparison and reducibility of the above indicators, their specific values are translated into points on a specially developed 10-point scale. the sums of the scores obtained make it possible to assess the effectiveness, firstly, of each instrument separately, secondly, their groups in the sphere of csp, and thirdly, the social management system of the enterprise as a whole. all this allows not only to increase the efficiency of reproduction of the human potential of the corporation, but also to strengthen the company’s market positions through the formation of its positive image and increase of investment attractiveness. references atems, b., hotaling, c. (2018), the effect of renewable and nonrenewable electricity generation on economic growth. energy policy, 112(1), 111-118. buley, n.v., demchenko, t.s., makushkin, s.a., vinichenko, m.v., melnichuk, a.v. (2016), human resource management in the context of the global economic crisis. international journal of economics and financial issues, 6(s8), 160-165. burke, m.j., stephens, j.c. (2017), energy democracy: goals and policy instruments for sociotechnical transitions. energy research and social science, 33(1), 35-48. danielewicz-betz, a. (2016), a sociological perspective on corporations and tool-mediated business communication communicating in digital age corporations. london: palgrave macmillan uk. del, p., pablo-romero, m., sánchez-braza, a. (2015), productive energy use and economic growth: energy, physical and human capital relationships. energy economics, 49(5), 420-429. dilaver, ö., dilaver, z., hunt, l.c. (2014), what drives natural gas consumption in europe? analysis and projections. journal of natural gas science and engineering, 19(1), 125-136. kapitonov, i.a., voloshin, v.i. (2017), strategic directions for increasing the share of renewable energy sources in the structure of energy consumption. international journal of energy economics and policy, 7(4), 90-98. kittichaisaree, k. (2017), regulation of cyberspace and human rights public international law of cyberspace. cham: springer international publishing. klikauer, t. (2016), corporations and hegel’s ethical institutions hegel’s moral corporation. london: palgrave macmillan uk. li, r., huang, h., dong, j. (2018), input factors contribution degree analysis of energy service industry based on economic growth model. international energy journal, 18(1a), 1-10. mahmood, t., ahmad, e. (2018), the relationship of energy intensity with economic growth: evidence for european economies. energy strategy reviews, 20(1), 90-98. ness, i., cope, z. (2016), political economy. the palgrave encyclopedia of imperialism and anti-imperialism. london: palgrave macmillan uk. pereira, g.i., silva, p.p. (2017), energy efficiency governance in the eu-28: analysis of institutional, human, financial, and political dimensions. energy efficiency, 10(5), 1279-1297. salim, r., yao, y., chen, g.s. (2017), does human capital matter for energy consumption in china? energy economics, 67(1), 49-59. shirangi, m.g., volkov, o., durlofsky, l.j. (2018), joint optimization of economic project life and well controls. spe journal, 23(2), 482-497. shuen, a., feiler, p.f., teece, d.j. (2014), dynamic capabilities in the upstream oil and gas sector: managing next generation competition. energy strategy reviews, 3(1), 5-13. solaiman, s.m. (2017), legal personality of robots, corporations, idols and chimpanzees: a quest for legitimacy. artificial intelligence and law, 25(2), 155-179. starr-glass, d. (2017), organizational propensities to share: revisiting talent mobilization and redistribution in multinational corporations. in: machado, c., editor. competencies and (global) talent management. cham: springer international publishing. teleuyev, g.b., akulich, o.v., kadyrov, m.a., ponomarev, a.a., hasanov, e.l. (2017), problems of legal regulation for use and development of renewable energy sources in the republic of kazakhstan. international journal of energy economics and policy, 7(5), 296-301. vinichenko, m.v., shihovtsova, a.i. (2016), the application of data science in hr. materials of the afanasiev readings, 3(16), 71-78. vinichenko, m.v., strokova, s.a. (2016), some approaches to the evaluation of sources of selection of personnel. materials of the afanasiev readings, 2(15), 79-90. wang, c., wei, w., wang, j., liu, f., mei, s. (2018), strategic offering and equilibrium in coupled gas and electricity markets. ieee transactions on power systems, 33(1), 290-306. wang, j., yang, y., sui, j., jin, h. (2016), multi-objective energy planning for regional natural gas distributed energy: a case study. journal of natural gas science and engineering, 28(1), 418-433. wetzel, j.r.m. (2016), corporations and human rights human rights in transnational business: translating human rights obligations into compliance procedures. cham: springer international publishing. . international journal of energy economics and policy | vol 7 • issue 2 • 201726 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(2), 26-33. a study of energy efficiency and mitigation of carbon emission: implication of decomposing energy intensity of manufacturing sector in taiwan yu-kai huang1, jyh-yih hsu2*, lih-chyun sun3 1department of agricultural economics, texas a&m university, college station, texas, usa, 2center for industrial development research, national chung hsing university, taichung, taiwan, 3national policy foundation, taipei, taiwan. *email: cidrnchu01@gmail.com abstract this paper applies the logarithmic mean divisia index (lmdi) approach to examine aggregate energy intensity of the manufacturing sector in taiwan from 1982 to 2014. we decompose aggregate energy intensity into three effects, which are the fuel mixed effect, the sectoral energy intensity effect, and the substructural effect. the results show that aggregate energy intensity is highly correlated with carbon intensity in taiwan. moreover, the aggregate energy intensity is mainly driven by sectoral energy intensity effect. the influence of the substructural effect and fuel mixed effect on improving the aggregate energy intensity has become larger in the recent years. the policy implication of study results suggests that internalizing the costs of carbon emission, creating incentives to invest energy-saving technology, establishing a fair and efficient electricity market are needed in taiwan. keywords: logarithmic mean divisia index, energy intensity, carbon intensity, structural change, fuel mixed effect jel classifications: o1, o2, q4, q5 1. introduction the ipcc (2007) shows that there is a significant relationship between greenhouse gas (ghg) emission and climate change. there are some previous studies (iea, 2012; iea, 2008), which further point out that ghgs are mainly emitted from energy. thus, many countries realized the importance of understanding how effectively energy was consumed in their economies and how to improve energy efficiency (ang, 2006). therefore, most countries have set efficient energy improvement as an important policy goal for tackling the problem of climate change. for example, the european union (eu) intends to save 20% energy consumption by 2020 and 27% or greater by 2030. the us also has called for doubling energy efficiency by 2030. group of twenty has set different targets for improving energy efficiency in certain industries (iea, 2014). in addition, taiwan, whose its carbon emission level ranks 21st in the world (iea, 2015), is not a member of the united nations framework convention on climate change (unfccc). to reduce its emission, the government of taiwan sets a policy target1 for improving energy efficiency more than 20% in 2015 against the level of 2005 and improving at least 50% in 2025. in order to achieve the above policy objective, it is important and necessary to examine energy intensity and its underlying factors. the aim of this paper is to identify the variation trend of energy intensity of the manufacturing sector in taiwan from 1982 to 2014; we decompose energy intensity into the following factors: (1) fuel mixed effect that captures the impact of the energy structure, which hasn’t been examined in previous taiwanese studies; (2) sectoral energy intensity effect, which captures the impact of energy efficiency in the manufacturing sector; and (3) substructural effect, which captures the impact from changes in the manufacturing subsector. lastly, we conclude with corresponding policy implication and strategic measures for improving energy efficiency and mitigating emission. 1 the target is based on “sustainable energy policy framework” issued in 2008. huang, et al.: a study of energy efficiency and mitigation of carbon emission: implication of decomposing energy intensity of manufacturing sector in taiwan international journal of energy economics and policy | vol 7 • issue 2 • 2017 27 the following sections of this paper are organized as a literature review and background introduction in taiwan in section 2. the methodology of the multiplicative index decomposition analysis (ida) model in section 3. description of data is shown in section 4. the result and discussion are shown in section 5. lastly, conclusion and policy implication is in section 6. 2. literature review and background of taiwan 2.1. ida relevant literature review to decompose the energy intensity, there are two methodologies that can be utilized, which are structural decomposition analysis (sda) and ida. the former is based on input-output theorem, and the latter is based on index number theory. hoekstra and van der bergh (2003) summarize the fundamental differences between these two approaches. first of all, since sda uses the input-output framework, and ida uses aggregate sector information, one merit of ida is a lower data requirement which, however, causes it to have a less detailed decomposition of the economic structure than sda. furthermore, sda can capture indirect and direct demands, while ida can only assess the impact of the direct effects. thirdly, sda is able to assess a range of technological effects and final demand effects which are not available for ida. nevertheless, ida is more suitable, when analyzing data at any level of aggregation in term of time series, which is what this study focuses. the evolutions of ida in the previous research can be traced back prior to 1990. ang (2015) states that most decomposition analysis studies were based on the concept of laspeyres index before 1990. thereafter, divisia index was the mainstream method for the ida studies. prior to 2000, arithmetic mean divisia index proposed by boyd et al. (1988) was the major approach applied in decomposition research; however, currently logarithmic mean divisia index (lmdi) has been the most popular method. ang (2004) points out there are two main merits of lmdi: (1) lmdi doesn’t leave an unexplained residue, so it can be perfectly decomposed; and (2) lmdi can deal with the zero data which is an important nature for empirical study (ang and liu, 2007). due to these benefits, the lmdi method has been used widely in decomposition relevant research recently. besides the above advantages of lmdi, there are also some comparative studies pointing out that lmdi is the superior method to apply in decomposing intensity indicators (liu and ang, 2003; ang et al., 2010; ang, 2015). there are several studies using lmdi to decompose carbon emission, energy consumption, carbon intensity and energy intensity in a single country or across countries. the lmdi method was applied to analyze energy and co2 intensity in industrial sectors in thailand (bhattacharyya and ussanarassamee, 2004; bhattacharyya and ussanarassamee, 2005). vinuya et al. (2009) applied lmdi to decompose co2 emission in the usa between 1990 and 2004. gonzález and martinez (2012) analyzed the carbon intensity from 1965 to 2010 in mexico. hasanbeigi et al. (2012) utilized lmdi to analyze the energy intensity of california industries. zhang and guo (2013) identified the factors contributing to the change in rural residential and commercial energy consumption in china by lmdi. marrero and ramos-real (2013) used lmdi to decompose energy intensity in eu-15 countries (except luxembourg) during 1991-2005. emodi and boo (2015) decomposed co2 emission from electricity generation in nigeria by lmdi. obadi and kor (2015) investigated driving forces of energy consumption in eu-28 by lmdi decomposition technique. recent studies have focused on the energy consumption structure (i.e. the fuel mixed effect). shahiduzzaman and alam (2013) analyzed the variation of energy intensity in australia and separated underlying factors, such as the sectoral energy intensity effect, the structural effect, and the fuel mixed effect. lescaroux (2008) discussed the decomposition of energy intensity in manufacturing industries in the usa by the above three effects during 1974-1998 as well. ma and stern (2008) applied the same approach to analyze the variation of energy intensity in china from 1980 to 2003. ida has also been applied to empirical cases in taiwan. hsu and hsu (1998) applied the simple average divisia index to decompose variation of energy intensity by considering the sectoral energy intensity effect and the structural effect during 1961-1990. huang and tsao (2005) analyzed the variation of energy consumption in transport sector during 1990-2003. the divisia index also was applied to identify the key factors influencing taiwan’s co2 emission changes of the industrial sectors (lin et al., 2006), and of highway vehicles (lu et al., 2007). nevertheless, none of the above literature applied the lmdi methodology to examine the variation of energy intensity of the manufacturing sector in taiwan by the three decomposition factors (i.e. the fuel mixed effect, the sectoral energy intensity effect, the subsectoral effect). previous studies didn’t separate the fuel mixed effect from the sectoral intensity effect. in the sense of neoclassical economics, the fuel mixed effect, which captures substitution among different energy sources, presents a move along a production isoquant. on the other hand, the sectoral intensity effect, which captures technological change, presents a shift in the entire isoquants (ma and stern, 2008). the underlying reason of separating fuel mixed effect and sectoral intensity effect is that green energy technology and climate policy have unprecedentedly evolved in the recent years in taiwan. to distinguish the effect influenced by these changes, separating the fuel mixed effect from the sectoral intensity effect is needed. hence, the unique contribution of this paper is not only to fill the above gap but also to provide the latest corresponding strategy for improving energy efficiency and mitigating emission. 2.2. background statement for taiwan 2.2.1. gross domestic product (gdp), the growth rate of economic, energy consumption, and the population in taiwan the gdp per capita, the economic growth rate, the energy consumption and the population are illustrated in figure 1. it indicates that the annual economic growth rate stayed around 4% huang, et al.: a study of energy efficiency and mitigation of carbon emission: implication of decomposing energy intensity of manufacturing sector in taiwan international journal of energy economics and policy | vol 7 • issue 2 • 201728 on average, with exception of the years 2001 and 2009. thus, the gdp per capita increased gradually over the study period. the annual growth rate of energy consumption had a similar pattern with economic growth rate. in addition, the population growth rate declined gradually during the sample period, and it has been almost close to zero in the latest decade. 2.2.2. structural gdp share in taiwan table 1 shows that the economic structure over the study period in taiwan. the gdp share of the agricultural and the transportation sectors had decreased continuously. in contrast, the service sector had risen gradually during the first two decades and remained at around 60% during rest of the study period. the share of the industrial sector declined in the 90’s and raised up again after 2000. in terms of the subsectors level in the manufacturing sector, we can find out that the output share of the “electrical, electronic machinery and precision instruments subsector” grew from 2.7% in 1982 to 14.9% in 2014, which is the most significant increase among all the subsectors during 1982-2014. on the other hand, the gdp share of the most energy-consuming subsector, “petroleum, coal and associated products,” is relatively small, around 0.9-2.1%. another energy-consuming subsector, “chemical materials,” has a gdp share around 1.5-2.1% over the study period. 2.2.3. sectoral energy consumption share in taiwan the share of final energy consumption by the different subsectors and sectors is illustrated in table 2. the industrial sector, the focus in this paper, had the largest share of energy consumption, table 1: the gdp share in the sectors and major subsectors (unit %) sector 1982 1987 1992 1997 2002 2007 2012 2014 agricultural 8.0 5.5 3.6 2.5 1.8 1.5 1.7 1.9 industrial 44.7 47.5 39.1 34.1 32.1 33.9 33.7 35.6 chemical materials 2.1 2.8 1.8 1.9 1.9 1.9 1.5 1.5 non-metallic mineral products 1.6 1.4 1.7 1.1 0.8 1.0 1.0 0.7 electrical, electronic machinery and precision instruments 2.7 4.0 3.8 5.6 8.8 12.5 13.2 14.9 petroleum, coal and associated products 1.3 2.1 1.7 1.6 1.6 1.7 0.9 0.9 electricity and gas supply 4.3 4.0 2.9 2.5 2.2 1.2 1.1 1.8 transportation 4.4 4.6 4.5 4.4 4.1 3.2 3.0 2.9 service 42.9 42.4 52.8 59.0 62.0 61.4 61.6 59.6 total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 source: directorate general of budget, accounting and statistics (2015). gdp: gross domestic product table 2: the share of energy consumption in the sectors and major subsectors (unit %) sector 1982 1987 1992 1997 2002 2007 2012 2014 agricultural 3.4 3.4 2.4 2.0 1.5 0.9 0.9 0.9 industrial 65.1 63.4 59.6 59.2 61.8 65.0 65.3 65.8 chemical materials 6.3 7.8 7.9 7.8 10.0 11.1 10.4 10.1 non-metallic mineral products 9.8 7.7 7.0 5.2 3.7 3.1 3.1 2.8 electrical, electronic machinery and precision instruments 1.1 1.8 1.9 2.8 5.1 7.0 8.7 9.1 petroleum, coal and associated products 19.8 18.1 15.7 16.5 20.0 23.9 24.0 24.9 electricity and gas supply 1.71 3.42 2.87 3.75 3.76 3.58 3.11 3.11 transportation 12.4 13.3 16.4 16.2 14.1 12.4 12.3 12.1 service 19.0 19.9 21.6 22.7 22.6 21.8 21.5 21.3 total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 source: bureau of energy (2015) figure 1: the gross domestic product per capita, the growth rate of economic, the energy consumption and the population source: dgbas (2015), bureau of energy (2015) huang, et al.: a study of energy efficiency and mitigation of carbon emission: implication of decomposing energy intensity of manufacturing sector in taiwan international journal of energy economics and policy | vol 7 • issue 2 • 2017 29 approximately two-thirds of the total, during the past 33 years. in the subsector level, the “petroleum, coal and associated products subsector” consumed around 15.7-24.9% of total energy consumption which was the largest energy consumption subsector. the second large subsector was the “chemical materials subsector,” which consumed around 6.3-11.1% during the study period. 2.2.4. sectoral energy consumption share in taiwan the share of final energy consumption by the different energy sources as shown in figure 2. note that the energy sources shown in figure 2 are recalculated by breaking down the electricity term into its fuel components. the renewable energy shown in figure 2 includes geothermal, solar photovoltaic, wind, conventional hydro, biomass and waste. the hydro illustrated in figure 2 represents pumped hydro. the largest consumption share was from petroleum, but it had decreased continuously from 69% to 39.8%. meanwhile, coal and natural gas grew gradually. the former one ascended from 12.2% to 31.5%, the latter one was more fluctuated but generally increased from 3.8% to 17.5%. it is important to address here that the consumption of nuclear energy had decreased from 19.8% to 8.1%. 2.2.5. the relationship between energy intensity and ghg intensity ang et al. (2010) point out that improving energy efficiency is helpful to reduce ghg. to reexamine this claim in our study, we probed the relationship between energy intensity and ghg intensity during 1990-2013, and the result is shown in figure 3. the trends of these three intensity indicators (energy intensity, co2 intensity, and ghg intensity) were highly correlated. the correlation coefficient between energy intensity and ghg intensity is 0.9630; on the other hand, the correlation coefficient between energy intensity and co2 intensity is 0.9726. this outcome not only echoes the statement of ang et al. (2010), but also indicates that improved energy efficiency, i.e. decreased energy intensity, is an effective way to improve ghg intensity in taiwan. 2.2.6. the cross countries energy intensity comparison figure 4 shows energy intensity comparison among the us, the uk, germany, france, japan, south korea and taiwan. the energy intensity had descended continuously in these selected countries. the uk, germany, france and japan have relatively low energy intensity, which is around 0.09 to 0.16 (toe/thousand usd) over the study period. on the other hand, the us and south korea figure 2: share of the final energy use (1982-2014) source: bureau of energy (2015) figure 3: energy intensity and co2 intensity (1990-2013) source: co2 data is from international energy agency (2015) huang, et al.: a study of energy efficiency and mitigation of carbon emission: implication of decomposing energy intensity of manufacturing sector in taiwan international journal of energy economics and policy | vol 7 • issue 2 • 201730 have relatively high energy intensity, which is around 0.15-0.22 (toe/thousand usd). the energy intensity in taiwan was between these two groups. 3. methodology since lmdi is commonly viewed as the preferred method among the variety of ida methods (ang, 2004), this study applies lmdi as the methodology for decomposing energy intensity. we decompose energy intensity into the following factors: (1) fuel mixed effect, which captures the impact from the energy structure; (2) sectoral energy intensity effect, which captures the impact from energy efficiency in the manufacturing sector; and (3) substructural effect, which captures the impact from changes in the manufacturing sector. the formulation of multiplicative lmdi-i2 with the three decomposition terms (i.e. the fuel mixed effect, the sectoral energy intensity effect, and the substructural effect) is expressed as follows: i e y e y e e e y y y f i s m i im m i im i i i i m i m i i = = = ⋅ ⋅ = ⋅ ⋅ ∑∑ ∑∑ ∑∑ � � � � � � (1) equation (1) indicates that aggregate energy intensity (i) is able to express as the ratio of energy consumption (e) and the overall gdp (y). eim denotes the consumption amount of fuel m in 2 details of the lmdi approach can refer to ang (2005) manufacturing subsector i; yi denotes the gdp in manufacturing subsector i; fm denotes the share of fuel m in the total energy consumption; ii denotes the energy intensity in manufacturing subsector i; si denotes the gdp share of manufacturing subsector i to the total gdp in the manufacturing sector. the multiplicative of the change of energy intensity (dtot) can be obtained as: d i i d d dtot t fm eff str= = ⋅ ⋅ 0 � (2) which represents that the change rate of aggregate energy intensity (dtot) from time 0 to time t is equal to product of the change rate of fuel mixed effect (dfm), the change rate of sectoral energy intensity effect (deff), and the change rate of substructural effect (dstr). each change rate of effects can be calculated by follows: ( ) 0 0 0 0 , exp ln , t im im tt m fm t m i m e e l y yf d f l i i          =          ∑∑ ( ) 0 0 0 0 , exp ln , t im im tt i eff t m i i e e l y yi d i l i i          =          ∑∑ ( ) 0 0 0 0 , exp ln , t im im tt i str t m i i e e l y ys d s l i i          =          ∑∑ where ( ) 0 0 0, / , t tim im t e e l l i i y y      consists of a weight function in terms of logarithmic mean weight function. the logarithmic mean weight function can be calculated by ( ), ln ln ln l          − − = = −      (3) where ∀ α, β>0, α≠β 4. description of data the gdp and the energy balance sheet in taiwan are utilized in this study. the detail descriptions of these data are elaborated as below. 4.1. gdp data the source of gdp data is from the directorate general of budget, accounting and statistics (dgbas). it is the yearly data from 1982 to 2014. the real gdp used in this study is based on the constant price of 2011. in order to easily compare the cross-country data with other research in the future, we exchange the currency unit from the new taiwan dollar to the us dollar by the annual average exchange rate which is also from dgbas. figure 4: energy intensity cross countries comparison source: bureau of energy (2015) note: (1) energy intensity is total primary energy supply/gross domestic product (gdp) (purchasing power parity); (2) gdp is in 2005 usd huang, et al.: a study of energy efficiency and mitigation of carbon emission: implication of decomposing energy intensity of manufacturing sector in taiwan international journal of energy economics and policy | vol 7 • issue 2 • 2017 31 4.2. energy consumption data taiwan’s energy balance sheet, regularly issued by the bureau of energy, is based on the same statistic approach as the organization for economic cooperation and development and the international energy agency. columns of the energy balance sheet present the main end-used energy sources and the associated sub-sources. the main end-used energy sources which are used in this study include seven categories: “coal and associated products,” “crude oil and associated products,” “natural gas,” “biomass and waste,” “electricity,” “solar thermal,” and “heat.” rows of the energy balance sheet are sorted by different subsectors. the manufacturing sector data is used in this study. the kiloliter of oil equivalent is applied as the unit of our energy consumption data, and the duration is as same as that of the gdp data from 1982 to 2014. 5. results and discussion this section presents the decomposition results of energy intensity in the manufacturing sector and then elaborates on corresponding policy implications from our results. 5.1. decomposition of aggregate energy intensity and correlation analysis the decomposition result is shown in figure 5 which indicates that the fuel mixed effect has a relatively trivial influence on aggregate energy intensity in the manufacturing sector, but its effect becomes more apparent in the last 10 years. the larger fuel mixed effect than before could be caused by the increase in use of natural gas and the decrease in the use of petroleum in the recent years in taiwan (figure 2). this almost neutral fuel mixed effect outcome is similar to previous studies (ma and stern, 2008; shahiduzzaman and alam, 2013). on the other hand, the sectoral energy intensity effect is the major factor affecting aggregate energy intensity. it decreased quickly during the 1980s and remained stable in the early 1990s. thereafter, due to the asian financial crisis, the dotcom bubble, and the subprime mortgage crisis, there were deteriorations of the sectoral energy intensity effect in 1997, 2001 and 2008. in view of the substructural effect, since the substructural effect captures more detailed information in the industrial structure, it performed more sensitively. the decreasing trend of the substructural effect has occurred since 2005. as shown in tables 1 and 2, it can be caused by the higher increasing gdp share and relatively lower energy consumption share in the electrical, electronic machinery and precision instruments sector. 5.2. policy implication and discussion according to our decomposition results and high correlation outcome between energy intensity and ghgs intensity (figure 3), we interpret the relevant implication and suggest a corresponding strategy for improving energy efficiency and mitigating emissions in this subsection. 5.2.1. the role of the fuel mixed effect the fuel mixed effect has a trivial influence on the aggregate energy intensity in our results and some previous studies (ma and stern, 2008; shahiduzzaman and alam, 2013). however, there are some plausible reasons to pay more attention to reducing energy intensity further by the fuel mixed effect in the future in taiwan. first, the economic perspective in taiwan is less likely to be as good as the growth rate in the 1980s, so the attribution of improving energy intensity from the sectoral intensity effect will be limited; second, the economy structure is hard to adjust in the short-term so that the improvement of energy intensity from substructural effect would not have a significant change in the short-run. hence, the fuel mixed effect has relatively more room to be improved given some appropriate incentives compared with other effects in taiwan. nevertheless, there is a critical challenge to adjust the fuel structure in taiwan. the government of taiwan is committed to achieving a “zero nuclear policy” by 2025. from figure 2, we can find out that the ratio of nuclear energy has declined gradually since the mid-1980s; however, if the taiwanese government would like to fulfill the commitment of the “zero nuclear policy,” improve energy intensity, and mitigate emission of carbon, the fuel structure needs to switch to natural gas and renewable energy. to achieve this objective, one of the feasible and effective policies is internalizing the cost of emission of carbon. to encourage the manufacturing sector, especially electricity generation, to use less-carbon-intensity fuels, cap and trade scheme should be implemented as soon as possible. to do so, the government of taiwan should accelerate improvement at the emission report and monitor system, develop a carbon emission market in taiwan, and connect with international carbon trading markets. this figure 5: decomposition of aggregate energy intensity (1982-2014) source: estimated by authors note: (1) indices: 1982=1; (2) if index is smaller 1 which indicates that the energy intensity is less than the base year (i.e. energy efficiency is improved; and vice versa) huang, et al.: a study of energy efficiency and mitigation of carbon emission: implication of decomposing energy intensity of manufacturing sector in taiwan international journal of energy economics and policy | vol 7 • issue 2 • 201732 measurement can provide more economic incentives to level up energy efficiency and also replace coal-fired power plants with natural gas-fired or cogeneration power plant. in addition, decentralizing the electricity industry and establishing a fair and efficient electricity dispatching system can help to integrate more decentralized energy resources (small solar and wind turbine power). 5.2.2. provide economic incentives to stimulate energy-saving technological innovation the sectoral intensity effect played a key role in improving aggregate energy intensity in the manufacturing sector during the study period. however, when the economy is in recession, the aggregate energy intensity gets deteriorated. it shows that the energy-saving technology hasn’t developed enough so that the economic growth can’t decouple with energy consumption in taiwan. in order to make economic growth and energy consumption decoupling, it’s necessary to increase investment in energysaving technology. the energy costs, such as electricity, gas, and petroleum, are very low (bureau of energy, 2016). thus, there’s no strong incentive to introduce energy-saving technology. to enhance implementation of energy-saving technology, energy prices should reveal the externality cost of climate change by imposing a carbon or energy tax. therefore, there will be more firms which are willing to involve in altering their production process to a less-carbon-intensity way. 5.2.3. transformation of the industrial structure figure 6 shows the current industrial structure distribution sorted by energy consumption and the gdp. it illustrates that “petroleum and coal associated product,” “chemical materials,” “basic metal” and “electricity and gas supply” are the main high energy intensity subsectors in the industrial sector. due to the essentially different characteristics among these subsectors, a policy-maker cannot apply the same standard of energy intensity to evaluate these distinct subsectors. however, we still can improve the energy efficiency from the above energy-intensive subsectors through implementing appropriate measures: first of all, in order to manage the total amount of emission effectively, the above energy-intensive subsectors should be included in the cap and trade scheme. secondly, the electricity and gas supply firms can increase its added-value by utilizing valuable energy usage data and coordinating with other industries, such as the retail market, transportation sector, and residential sector. thirdly, the “electrical electronic machinery and precision instruments subsector” which is a vital subsector for economic growth and international trade in taiwan is a highly competitive industry across countries. to maintain and enhance high-tech industries competitiveness, the government should create a friendly investment environment through establishing a fundraising platform which can share innovative ideas to potential investors. thus, taiwan can cultivate more high-added-value and innovative start-up companies and make the high-tech industry, a less energy-intensive industry, larger and stronger. 6. conclusion this paper concludes that how different factors influence the energy intensity in the manufacturing sector by lmdi approach during 1982-2014 in taiwan, which is not a member of the unfccc and also needs to reveal its climate policy relevant information and experience. the corresponding policy implication and the strategic measures are discussed in this study. the decomposition results show that the sectoral energy intensity effect is the major factor affecting the aggregate energy intensity. in addition, the substructural effect is more sensitive and fluctuated, and its impact on improving the aggregate energy intensity has gradually become larger recently. likewise, the fuel mixed effect has a relatively slight impact on the aggregate energy intensity during first two decades of our study period, but its influence has become larger in recent years. moreover, our correlation analysis indicates a highly correlated relationship between energy intensity and ghg intensity, and the similar pattern occurs between energy intensity and co2 intensity. it demonstrates that reducing the energy intensity is an effective way to improve the ghg intensity in taiwan. figure 6: the scatter diagram of subsectors based on the energy consumption and the gross domestic product in 2014 source: dgbas (2015), bureau of energy (2015) huang, et al.: a study of energy efficiency and mitigation of carbon emission: implication of decomposing energy intensity of manufacturing sector in taiwan international journal of energy economics and policy | vol 7 • issue 2 • 2017 33 according to our results, the policy recommendations are as follows: • internalize the cost of emission of carbon by carrying out the cap and trade scheme in the major energy-intensive subsectors. • decentralize the electricity industry and establish a fair and efficient electricity dispatching system. • create incentives to increase investment in energy-saving technology through imposing carbon or energy levy or tax. • increase the added-value of traditional utility companies via utilizing their energy data with other industries, such as bundling with retail market, the transportation sector, and residential sector. • establish a fundraising platform which can share innovative ideas to potential investors and cultivate more high-addedvalue and innovative start-up companies. this study provides analytical framework which combines more delicate decomposition analysis with the fuel mixed effect in the manufacturing sector in taiwan, which is not a member of the unfccc, but its emission level cannot be neglected. hence, the empirical results and the corresponding policy implication in taiwan can effectively ease the international carbon leakage problem. in addition, the corresponding policy implication provided by this study are not only helpful to trace and examine the trajectory of energy efficiency performance in taiwan, but also useful to compare the evolution of energy intensity with other countries. 7. acknowledgments we wish to thank the ministry of science and technology (project no. 105-2221-e-005-067) for financial support. references ang, b.w. (2004), decomposition analysis for policymaking in energy: which is the preferred method? energy policy, 32(9), 1131-1139. ang, b.w. (2005), the lmdi approach to decomposition analysis: a practical guide. energy policy, 33, 867-871. ang, b.w. (2006), monitoring changes in economy-wide energy efficiency: from energy gdp ratio to composite efficiency index. energy policy, 34(5), 574-582. ang, b.w., liu, n. (2007), handling zero values in the logarithmic mean divisia index decomposition approach. energy policy, 35, 238-246. ang, b.w. (2015), lmdi decomposition approach: a guide for implement. energy policy, 86, 233-238. ang, b.w., mu, a.r., zhou, p. (2010), accounting frameworks for tracking energy efficiency trends. energy economics, 32, 1209-1219. bureau of energy. (2015), energy balances in taiwan. ministry of economic affairs. taiwan: executive yuan bureau of energy. (2016), energy statistical annual reports. ministry of economic affairs, executive yuan, taiwan. bhattacharyya, s.c., ussanarassamee, a. (2004), decomposition of energy and co2 intensities of thai industry between 1981 and 2000. energy economics, 26, 765-781. bhattacharyya, s.c., ussanarassamee, a. (2005), changes in energy intensities of thai industry between 1981 and 2000: a decomposition analysis. energy policy, 33, 995-1002. boyd, g.a., hanson, d.a., sterner, t. (1988), decomposition of changes in energy intensity: a comparison of the divisia index and other methods. energy economics, 10, 309-312. directorate general of budget, accounting and statistics. (2015), taiwan: national statistics, executive yuan. emodi, n.v., boo, k.j. (2015), decomposition analysis of co2 emissions from electricity generation in nigeria. international journal of energy economics and policy, 5(2), 565-573. gonzález, d., martinez, m. (2012), changes in co2 emission intensities in the mexican industry. energy policy, 51, 149-163. hasanbeigi, a., can, s.r., sathaye, j. (2012), analysis and decomposition of the energy intensity of california industries. energy policy, 46, 234-245. hoekstra, r., van der bergh, j.c.j. (2003), comparing structure and index decomposition analysis. energy economics, 25(1), 39-64. hsu, j.y., hsu, a.c. (1998), analysis of variation trend of energy intensity in taiwan. quarterly journal of taiwan bank, 49(1), 156-196. huang, y.k., tsao, s.m. (2005), decomposition analysis of transportation energy consumption in taiwan. journal of the chinese institute of transportation, 17(2), 175-208. iea. (2008), worldwide trends in energy use and efficiency: key insights from iea indicator analysis. paris, france: international energy agency (iea). iea. (2012), co2 emissions from fuel combustion highlights. paris, france: international energy agency (iea). iea. (2014), energy efficiency policies and measures database. paris, france: international energy agency (iea). iea. (2015), key world energy statistics. paris, france: international energy agency (iea). ipcc. (2007), climate change 2007: mitigation of climate change. working group iii contribution to the ipcc fourth assessment report: summary for policymakers. intergovernmental panel on climate change. lescaroux, f. (2008), decomposition of us manufacturing energy intensity and elasticities of components with respect to energy prices. energy economics, 30(3), 1068-1080. lin, s.j., lu, i.j., lewis, c. (2006), identifying key factors and strategies for reducing industrial co2 emissions from a non-kyoto protocol member’s (taiwan) perspective. energy policy, 34, 1499-1507. liu, f.l., ang, b.w. (2003), eight methods for decomposing the aggregate energy-intensity of industry. applied energy, 76, 15-23. lu, i.j., lin, s.j., lewis, c. (2007), decomposition and decoupling effects of carbon dioxide emission from highway transportation in taiwan, germany, japan and south korea. energy policy, 35, 3226-3235. ma, c., stern, d.i. (2008), china’s change energy intensity trend: a decomposition analysis. energy economics, 30(3), 1037-1053. marrero, g.a., ramos-real, f.j. (2013), activity sectors and energy intensity: decomposition analysis and policy implications for european countries (1991-2005). energies, 6, 2521-2540. obadi, s.m., kor, m. (2015), investigation of driving forces of energy consumption in eu 28 countries. international journal of energy economics and policy, 5(2), 422-432. shahiduzzaman, m., alam, k. (2013), changes in energy efficiency in australia: a decomposition of aggregate energy intensity using logarithmic mean divisia approach. energy policy, 56, 341-351. vinuya, f., difurio, f., sandoval, e. (2009), a decomposition analysis of co2 emissions in the united states. applied economics letters, 17, 925-931. zhang, m., guo, f. (2013), analysis of rural residential commercial energy consumption in china. energy, 52, 222-229. . international journal of energy economics and policy | vol 7 • issue 2 • 2017310 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(2), 310-315. green technology and renewable energy in the system of the steel industry in europe mihail nikolaevich dudin1*, konstantin yurievich reshetov2, victor ivanovich mysachenko3, natalia nikolaevna mironova4, olga vladimirovna divnenko5 1russian presidential academy of national economy and public administration, 119571, vernadsky prosp., 82, moscow, russian federation, 2national institute of business, 111395, yunosti street, moscow, russian federation, 3national institute of business, 111395, yunosti street, moscow, russian federation, 4national institute of business, 111395, yunosti street, moscow, russian federation, 5national institute of business, 111395, yunosti street, moscow, russian federation. *email: dudinmn@mail.ru abstract the purpose of this article is to review the potential applicability of the environmentally friendly metallurgical production technologies and potential replacement of traditional energy sources with renewable energy sources in this sector. the materials presented in this article lead to the following conclusions: (i) the metallurgical production in europe can be considered as one of the most important sectors forming a high added value. simultaneously, the metallurgical production is characterized by relatively high energy consumption and generates a significant contribution to carbon dioxide emissions, (ii) the metallurgical enterprises have to compete not only among themselves but also with other companies engaged in production of the substitute products (e.g. plastic pipes); therefore, the production and technological modernization and environmental optimization of the activity of the metallurgical enterprises in europe is one of the ways to increase the competitiveness and to reduce the expense content, (iii) the use of technologies that virtually eliminate the generation of carbon dioxide in the processing of iron ore allows to reduce the average level of greenhouse gas emissions by an average of 20-25%, (iv) the integration of production technology characterized by very low co2 emissions with the use of solar thermal energy technologies to provide the energy needs of the metallurgical production can significantly reduce the level of energy consumption of the metallurgical plants by an average of 18-31%. keywords: metallurgy, renewable energy, green technology, the greening of production, europe jel classifications: o10, q40, q42, q43 1. introduction the ongoing political transformations in the european union, as well as, probably, the imminent uk’s departure from the european union, will have an impact not only on the geopolitical, but also on the economic processes (protopopov and feyler, 2015; popescu and mursa, 2016; central intelligence agency, 2016). the changing of the boundaries of the united europe will result in the emergence of new challenges for the enterprises of the industrial, service and commercial sectors. first of all, it is necessary to take into account the emergence of the risks in the sphere of european logistics, since the political transformation and the reforming of the borders of the european union will change significantly both the institutional and the cooperative component of the logistic flows. also, it should be kept in mind, that there were some disparities between the production and the marketing specialization of the world markets in the past few decades (popescu and mursa, 2016). in the european union, the metallurgical industry is one of the main trends ensuring the economic growth (central intelligence agency, 2016). at the same time, many european countries were able (and currently are able) to accommodate partially the demand of the steel industry for the raw material with its own ore deposits. however, as recent events have shown, the european steel industry ceases to be economically and investment attractive business, despite the fact that the manufactured products are in demand in the economy and in the social and domestic segment. dudin, et al.: green technology and renewable energy in the system of the steel industry in europe international journal of energy economics and policy | vol 7 • issue 2 • 2017 311 the problem here is that the existing stocks of own raw materials required for steel production are not only insufficient, but unable to completely meet all the demands for raw materials. in particular, the high costs, associated with the import of lacking raw materials, became the key cause of financial instability of some european companies in the steel industry (world steel association, 2016). the second important reason is the replacement of the europeanamerican global vector of development of the global metallurgical industry with the asian one, followed by the changes in the structure of the raw material and sales markets. this led to the manifold growth of the logistic and other costs, related to supply and sales (world steel association, 2016; janovská et al., 2012). the third reason is that the metallurgical industry is the sector characterized by potentially high levels of environmental damage (janovská et al., 2012; jacobson, 2009; wang et al., 2016; li et al., 2016) to the atmosphere, water, flora and ability to reduce the biodiversity. moreover, the environmentally harmful byproducts of the metallurgical production can affect adversely the quality of life of the population and the morbidity rate, and thus can increase the national burden of disease. despite the fact that the european union as a whole can be regarded as the ecologically stable world region, it is worth noting that the further development of the metallurgical industry requires transition to the “green” technology. the “green” technology should be implemented, first, in the metallurgical production and, secondly, in the energy supply of the metallurgical plants. 2. literature and methodology in this article, the researches in the field of international economics, technological shifts and environmental security of the various industries in the globalizing world (the centre for energy policy of the institute of europe, n.d.; dudin et al., 2015; dudin et al., 2017; world energy council, 2013; deutsche energie-agentur gmbh, 2015; united states department of energy, 2016; schwass, 2011; world energy council, 2016; international energy agency, 2015; branker et al., 2011) are used as the methodological basis. moreover, two key trends, defining the greening of the metallurgical production, which can be used by the business entities of other industries geographically localized not only in the european union but also in other countries (kalogirou, 2013; scarlat et al., 2015; gross et al., 2005; mysachenko, 2008), are studied. the first key trend is the “green” technology of metallurgical production. here, the attention should be paid primarily to the technology of electrolysis (using lithium carbonate) of the iron ore in order to minimize carbon dioxide emissions. this technology was developed as the result of scientific exchange between the universities of europe, china and the united states. the second key trend is the reduction of energy consumption and the increase in the energy efficiency of the metallurgical production in the european union through the introduction of the renewable energy technology (wang et al., 2016; li et al., 2016). however, it should be understood that the production technology for the processing of the iron ore, involving the reduction of carbon dioxide emissions (on average by 20-25%), generally, causes no additional scientific and practical problems, and the return on investment in the modification of conventional technology of metallurgical production is <7 years. but, on the other hand, the introduction of renewable energy technology in the metallurgical industry may be accompanied by a number of restrictions. one of the major restrictions is that it is very difficult from a practical point of view to perform the integration of the “green” technology of metallurgical production and the renewable energy technology. the second important restriction is the cost of production (generation) of the energy from the renewable sources. the problem is that the production (generation) of the energy from the renewable sources is characterized by volatility and stochasticity. in particular, when using wind turbines, the wind force and direction are required to be constant (the climate in denmark is characterized by such parameters; therefore, the wind power engineering is foremost developed there, but mainly in the social and domestic sectors). similar problems are relevant also for the use of the solar (radiant) energy; as a rule, the most significant amount of power is generated out of the solar flux at noon, while the parameters of cloudiness are fundamentally important. but the use of energy derived from the solar flux is carried out in the social and domestic sectors in the evening, the use of radiant energy is complicated in the economic sector (particularly, in the metallurgical industry), because the high cost of production and relatively low power allow the use of the solar panels mainly within service and sales areas where the demand for the energy is low (e.g., in the field of tourism services, trade in non-food items, etc.). thus, the scientists, until recently, were required to find the practically applicable renewable energy technology that could be used in energy-intensive sectors of the economy (particularly in the iron and steel industry). the content analysis, carried out as part of this article, allowed to determine that the appearance of the technology of the use of the solar thermal power to reduce the energy consumption of the process of metallurgical product production, based on the environmentally optimal technology (the electrolysis of the iron ore with the use of lithium carbonate) is a reasonable alternative to the traditional energetics. 3. results in the past two decades, the asian region has been leading in the metallurgical production, manufacturing about 70% of the world’s steel and iron. no more than 10% of the global steel and iron market is produced by the european union. however, only in the second half of the 20th century, the volume of rolled metal production increased 4.5 times, and in the period from 2000 to 2015 inclusive it increased additionally almost 2 times. in addition, the entire european union produces about 160 million tons of rolled metal and 93-95 million tons of cast iron, of which at dudin, et al.: green technology and renewable energy in the system of the steel industry in europe international journal of energy economics and policy | vol 7 • issue 2 • 2017312 least 30-40% of products are intended for domestic consumption (central intelligence agency, 2016; world steel association, 2016). when considering the metallurgical products, forming the global export market, it may be noted that the structure of the exports of the iron and steel metallurgy products has undergone significant changes only during the last 5 years (table 1). in 2010, more than 60% of world exports were covered by the products of advantageously low processing (including the ingots and semi-finished products, galvanized sheets, hot-and cold-rolled sheets, steel pipes), and in 2015, about 42% of world exports were covered by the share of products of advantageously high processing (hot-rolled bars, rolled steel, drawn wire, coated sheets, other bars and hot-rolled sheets) (figure 1). it should be noted that the production of the metallurgical products of low processing is characterized by significant environmental emissions, while the production of steel products of high processing is characterized by high energy intensity. on the one hand, in europe (including the countries that form the economic core of the european union) in the period from 1990 to 2015 inclusive, the volume of carbon dioxide emissions due to the use of traditional sources of energy decreased on average by 20% (from 4.4 million tons to 3.7 million tons), but at the same time, according to the data on carbon dioxide emissions in the metallurgical industry, the growth of the emissions can be noted primarily in the segment of low processing products (figure 2). it is obvious that the specific contribution to the generation of carbon dioxide emissions in the european metallurgical production increased mainly due to the segment producing the products of low processing (the share growth of more than 1.3 times). at the same table 1: volumes and structure of the world exports of iron and steel industry products (world steel association, 2016) product type 2010 2011 2012 2013 2014 2015 million tons in % million tons in % million tons in % million tons in % million tons in % million tons in % ingots and semi-finished material 58.7 15.7 57.7 14.8 58.5 14.8 54.1 13.7 54.3 12.1 51.5 12.1 railway track material 3.1 0.8 2.9 0.7 2.6 0.7 3 0.8 2.2 0.5 2.1 0.5 angles, shapes and sections 18.8 5.0 21 5.4 21.8 5.5 22.1 5.6 24.6 5.5 21.7 5.1 concrete reinforcing bars 18.1 4.8 17.5 4.5 21.9 5.5 18.9 4.8 22.2 5.0 18.9 4.4 bars and rods, hot-rolled 11.6 3.1 13.6 3.5 15.4 3.9 18.1 4.6 29.7 6.6 40.7 9.5 wire rod 20 5.3 21.8 5.6 23.2 5.9 24.2 6.1 29.4 6.6 29 6.8 drawn wire 6.9 1.8 7.5 1.9 7.6 1.9 7.7 2.0 8.9 2.0 8.4 2.0 other bars and rods 4.4 1.2 5.4 1.4 4.9 1.2 4.9 1.2 6 1.3 5.3 1.2 hot-rolled strip 4.3 1.1 3.2 0.8 3.1 0.8 3 0.8 3.3 0.7 2.9 0.7 cold-rolled strip 3.7 1.0 3.7 0.9 3.6 0.9 3.5 0.9 4.1 0.9 3.8 0.9 hot-rolled sheets and coils 65.3 17.5 63.4 16.3 64.4 16.2 67.3 17.1 75.8 16.9 77.8 18.2 plates 29.1 7.8 32.9 8.4 31 7.8 29 7.4 34.5 7.7 30.1 7.1 cold-rolled sheets and coils 33.9 9.1 34.4 8.8 32.7 8.2 33 8.4 37.2 8.3 32.8 7.7 electrical sheet and strip 4.3 1.1 4.6 1.2 4.3 1.1 4 1.0 4.2 0.9 4.1 1.0 tinmill products 6.6 1.8 6.4 1.6 6.2 1.6 6.4 1.6 6.7 1.5 6.3 1.5 galvanised sheet 35.1 9.4 36.1 9.3 36.1 9.1 37.1 9.4 40.7 9.1 37.6 8.8 other coated sheet 11.9 3.2 14.5 3.7 15.2 3.8 15.4 3.9 17.9 4.0 16.3 3.8 steel tubes and fittings 36.1 9.7 41.4 10.6 41.6 10.5 39.7 10.1 43.6 9.7 35.3 8.3 wheels (forged and rolled) and axles 0.8 0.2 0.7 0.2 0.8 0.2 0.9 0.2 0.8 0.2 0.8 0.2 castings 0.5 0.1 0.7 0.2 0.7 0.2 0.7 0.2 0.9 0.2 0.8 0.2 forgings 0.7 0.2 0.7 0.2 0.7 0.2 0.7 0.2 0.8 0.2 0.7 0.2 total 374 100 389.9 100 396.4 100 393.8 100 447.7 100 426.9 100 figure 1: the structure of the world exports of iron and steel products, in % of total volume (world steel association, 2016) figure 2: the specific contribution to the generation of carbon dioxide emissions by the metallurgical industry of europe source: central intelligence agency, 2016; janovská, et al., 2012; the centre for energy policy of the institute of europe, n.d.; united states department of energy, 2016; world energy council, 2016 dudin, et al.: green technology and renewable energy in the system of the steel industry in europe international journal of energy economics and policy | vol 7 • issue 2 • 2017 313 time the degree of influence on the environment of the segment producing the products of high processing is substantially less (the share growth of no more than 1.1 times). but in the course of estimation of the power consumption of the european steel production it is worth noting that in the segment of low processing the consumption of the energy resources does not show such a significant rate of growth as compared to the high processing segment (figure 3). it is obvious that the current situation in the european metallurgical industry requires the integrated solutions aimed at both minimization of carbon dioxide emissions and the substitution of traditional energy sources with the renewable energy. 4. discussion the european countries, including the ones forming currently the economic core of the european union, actively introduce the renewable energy technology (protopopov and feyler, 2015; popescu and mursa, 2016; deutsche energie-agentur gmbh, 2015; scarlat et al., 2015; gross et al., 2005; mysachenko, 2008; reshetov, 2015): • the united kingdom ranked third in the world in terms of the total volume of investments in the development of renewable energy and the production of biofuels; • germany is the fourth largest in the world in terms of total installed capacity in the wind power segment and the fifth in the geothermal power industry segment; • france is in the top 10 countries for the production of biofuels. but at the same time in some areas and economic sectors the level of the use of traditional energy sources (hydrocarbons) increases, and the environmental hazards caused by such activities grow steadily. as shown above, this problem is typical for the european metallurgical production and it is quite natural: • first, the renewable energy cannot provide all the energy needs of the economic and socio-domestic sectors (dudin et al., 2015; dudin et al., 2017); • secondly, the reduction of energy consumption of the society in this period economically forms the reserves for its increase in future periods, as the energy reserve is being created for the expansion of business and public activity of the actors (jacobson 2009); • thirdly, the generation and exploitation of renewable energy sources are not accompanied by the release of carbon dioxide, but at the same time the utilization of the equipment and renewable energy systems may potentiate the emission of greenhouse gases, as well as cause other environmental damage (international electrotechnical commission, 2015). at the same time, it should not be forgotten that the decline in carbon dioxide emissions projected by 2050 (at least 45% compared to current levels in 2015 and 2016) is planned to be provided primarily due to both energy conservation and efficiency measures (figure 4). the renewable energy is a solution of the second choice, and the third is the technology of capture and (underground or underwater) storage of carbon dioxide. thus, the ecological trend should be considered at the same time as the limiting condition for the development of the renewable energy sector. it follows here from that the equipment, tools and parts manufactured for the renewable energy sector should be characterized by a capacity for longterm operation in any geo-climatic conditions, or the recycling technology should be used in production of the equipment and components for the renewable energy sector. the second major restriction is the cost of production (generation) of energy from renewable sources. according to the reports, the scientific and technical solutions proposed by the chinese producers, allow to reduce 3-4 times the cost of solar panels and wind turbines (wang et al., 2016; li et al., 2016; world energy council, 2013). but at the same time it should be noted that the average cost of generation of the electrical energy (per 1 kwh) combined with the use of the radiant energy converting technology (photovoltaic and solar thermal power plants) is higher as compared to other sources of energy (e.g., as compared with obtaining of the electric power based on conversion of natural gas or wind power) (figure 5). the reduction of the production cost of the solar power generation using the photovoltaic cells was achieved not through figure 3: the specific contribution of the european metallurgical industry in the consumption of energy resources source: central intelligence agency, 2016; janovská, et al., 2012; the centre for energy policy of the institute of europe, n.d.; united states department of energy, 2016; world energy council, 2016 figure 4: contribution of the main measures and solutions to a reduction of carbon dioxide emissions source: the centre for energy policy of the institute of europe, n.d; world energy council, 2016 dudin, et al.: green technology and renewable energy in the system of the steel industry in europe international journal of energy economics and policy | vol 7 • issue 2 • 2017314 the improvement of the efficiency level (the efficiency of the photoelectric converters is about 16-25%, for comparison, in solar collectors of various modifications the efficiency may range from 10% to 75%), but due to the direct one-step transfer of the solar energy into the electrical energy, which reduces the loss and ensures the efficiency of the conversion (branker et al., 2011). in the course of aggregation of the trend of greening of the metallurgical production and the trend of replacement of traditional sources of renewable energy power, the proposal on the introduction of the iron ore electrolysis using lithium carbonate melt at a temperature of 800°c was formed, and it was also proposed to use solar energy to reduce the energy consumption (the step technology solar thermal electrochemical photo) (wang et al., 2016; li et al., 2016). the idea is that the electrolysis of iron ore using lithium carbonate eliminates the generation of carbon dioxide (the iron ore under electric current decomposes into basic components iron and oxygen, which are collected on two respective electrodes) while the use of solar thermal energy in the process minimizes the energy costs and allows to reduce the consumption of traditional energy sources (hydrocarbons). in other words, the step technology uses the solar thermal energy to melt lithium carbonate and the light energy to perform the electrolysis. in terms of the above-described idea, the preliminary calculations were carried on by a number of researchers, which showed that the electrolysis of iron ore using lithium carbonate melt can reduce carbon dioxide emissions by 20% (minimum) to 25% (maximum) in the metallurgical industry, and can reduce the energy intensity (in the context of traditional energy) by an average of 18% (minimum) to 31% (maximum). the data on potential reduction of carbon dioxide emissions in the european iron and steel production and the reduction of energy intensity of the production are shown in figure 6. 5. conclusions the metallurgical segment in the industry in europe is one of the leading segments creating high added value. in the future, the metallurgical industry products characterized by high restrictions will be in demand in the domestic and foreign markets. but to achieve the goal of the development of steel metallurgy it is required to improve the production technology, to modernize the production capacity and to optimize the logistics processes (supply, sales, internal distribution). it should be understood that the improvement of technology and production and the environmental components should imply the complementary solutions. while solving the issues of improvement of production and processing efficiency and production and ecological optimization, the following should be kept in mind. the market of ferrous metallurgy will certainly grow in the medium term, in this aspect the expert and analytical opinions are not in contradiction. in particular, in the medium term the increase in consumption of the steel metallurgy products is expected in the construction, energy, mechanical engineering sectors. on the other hand, in the long run, many enterprises of metallurgical industry, the functioning of which is characterized by high environmental risks, will be competing not only among themselves but also with the enterprises of the industries producing the substitute products (e.g. the metal-plastic products of industrial and household purpose) and causing less environmental damage. of course, the metal-plastic products are unable to replace completely the steel products, for example, in the construction industry. but at the same time, even now the trend of increasing in the demand for metal-plastic products is apparent in the infrastructure of the municipal and social-domestic sector. in the medium term, the production and technological renovation as well as the environmental optimization of the european iron and steel industry will form the necessary reserves and strategic potential for the diversification of the activities of the metallurgical enterprises in the long term, taking into account the changes in the specifics of the demand for the metallurgical and similar products. figure 5: the average cost of generation of one kilowatt/hour of electric power using the renewable and conventional source: united states department of energy, 2016; schwass, 2011; world energy council, 2016 source: calculated on the basis of the sources (wang et al., 2016; li et al., 2016; world energy council, 2016) figure 6: the expected effects of the introduction of new technologies in the european metallurgical production dudin, et al.: green technology and renewable energy in the system of the steel industry in europe international journal of energy economics and policy | vol 7 • issue 2 • 2017 315 the general aspects of production and technological improvement as well as the greening of the european metallurgical production were studied in this article. the authors plan to reveal the problems of assessment of the risks related to the replacement of the traditional energy sources with the renewable energy sources, as well as the methods of analysis of the effectiveness of the transition to new production technologies in the metallurgical industry. references branker, k., pathak, m.j.m., pearce, j.m. (2011), a review of solar photovoltaic levelized cost of electricity. renewable and sustainable energy reviews, 15(9), 4470-4482. central intelligence agency. (2016), the world fact book (1990-2016). available from: https://www.cia.gov/library/publications/the-worldfactbook/geos/xx.html. [last accessed on 2017 jan 22]. deutsche energie-agentur gmbh. (2015), renewables. made in germany. available from: http://www.renewables-made-in-germany. com/fileadmin/user_upload/technologieausstellung/2015/151119_ renewables_ru.pdf. [last accessed on 2017 jan 11]. dudin, m.n., lyasnikov, n.v., leonteva, l.s., reshetov, k.j., sidorenko, v.n. (2015), business model canvas as a basis for the competitive advantage of enterprise structures in the industrial agriculture. biosciences biotechnology research asia, 12(1), 887-894. dudin, m.n., voykova, n.a., frolova, e.e., artemieva, j.a., rusakova, e.p., abashidze, a.h. (2017), modern trends and challenges of development of global aluminum industry. metalurgija, 56(1-2), 255-258. gross, r., chase, a., howes, j., arnall, a., anderson, d. (2005), uk innovation systems for new and renewable energy technologies: drivers, barriers and systems failures. energy policy, 33(16), 21232137. international electrotechnical commission. (2015), nanotechnology in the sectors of solar energy and energy storage. technology report. available from: http://www.iec.ch/about/brochures/pdf/technology/ iec_tr_nanotechnology_lr.pdf. [last accessed on 2017 jan 25]. international energy agency. (2015). world energy outlook; 2015. available from: http://www.worldenergyoutlook.org/weo2015. [last accessed on 2017 jan 22]. jacobson, m.z. (2009), review of solutions to global warming, air pollution, and energy security. energy and environmental science, 2, 148-173. janovská, k., vilamová, š., besta, p., samolejová, a., švecová, e., vozňáková, i. (2012), analysis of energy demandingness of metallurgical production. metalurgija, 51(2), 277-279. kalogirou, s. (2013), solar energy engineering: processes and systems. 2nd ed. missouri, u.s.a: academic press. p724. li, f.f., wang, b., licht, s. (2016), sustainable electrochemical synthesis of large grain or catalyst-sized iron. journal of sustainable metallurgy, 2(4), 405-415. mysachenko, v.i. (2008), die rolle von investitionen in die strukturellen und technologischen wandel der industrie. journal of russian state trade and economic university, 6, 57-59. popescu, c., mursa, g.c. (2016), correlations between metallurgical, machinery and construction sectors during the latest economic cycle. metalurgija, 55(2), 241-244. protopopov, e.v., feyler, s.v. (2015), analysis of current state and prospects of steel production development. available from: http:// www.iopscience.iop.org/article/10.1088/1757-899x/150/1/012001/ pdf. [last accessed on 2017 jan 27]. reshetov, k.y. (2015), key lines to improve competitiveness of small innovative businesses. modernization innovation research, 6(3), 39-44. scarlat, n., dallemand, j.f., monforti-ferrario, f., banja, m., motola, v. (2015), renewable energy policy framework and bioenergy contribution in the european union an overview from national renewable energy action plans and progress reports (european commission, joint research centre, institute for energy and transport via e. fermi). renewable and sustainable energy reviews, 51, 969-985. schwass, r.d. (2011), world conservation strategy of the international union for the conservation of nature and natural resources (iucn). available from: http://www.eolss.net/sample-chapters/c13/e1-45-0205.pdf. [last accessed on 2017 jan 22]. the centre for energy policy of the institute of europe. (n.d.), available from: http://www.cnews.ru. [last accessed on 2017 jan 27]. united states department of energy. (2016), transparent cost database. available from: http://www.en.openei.org/wiki/transparent_cost_ database. [last accessed on 2017 jan 27]. wang, b., dong, j., gu, d., wu, h., licht, s. (2016), the adoption and mechanism of kio4 for redox-equilibrated stabilization of feo4 as an equalizer in water. ionics, 22(10), 1967-1972. world energy council. (2013), world energy perspective. cost of energy technology. london: world energy council. p17-20, 22-24. world energy council. (2016), world energy focus (perspective 2016-2017). available from: http://www.worldenergyfocus.org/ annual-2016/. [last accessed on 2017 jan 27]. world steel association. (2016), world steel in figures 2016. available from: http://www.worldsteel.org/publications/bookshop/productdetails.~world-steel-in-figures-2016~product~world-steel-infigures-2016~.html. [last accessed on 2017 jan 27]. . international journal of energy economics and policy | vol 7 • issue 5 • 2017 279 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(5), 279-290. development of the methodological approach to the assessment of the innovation position of oil and gas machine-building enterprises in the market miroslava gennadevna glukhova1*, aleksandr andreevich zubarev2 1fsbe institution of higher education “industrial university of tyumen,” tyumen, volodarsky’s street, 38, russia, 2fsbe institution of higher education “industrial university of tyumen,” tyumen, volodarsky’s street, 38, russia. *email: mira_gluhova@mail.ru abstract oil and gas machine building plays a significant role in the development of the russian oil and gas sector. the innovation position of the oil and gas machine-building enterprises depends on the conditions for the development of the external and internal market and the existing potential of enterprises. the development of innovation programs for the production of new equipment and technology is substantiated by the companies’ market strategy and target indicators for the implementation of innovation projects. the article analyzes methodological approaches to the assessment of the innovation potential of enterprises and the innovation climate and identifies their main strengths and weaknesses. the authors substantiate the use of a comprehensive methodological approach to the assessment of the innovation position of the oil and gas machine-building enterprise. the system of estimated indicators of the innovation position of one of the largest russian oil and gas machine-building enterprises in three areas is presented: level of competitiveness, state of the external environment, and innovation potential. the key indicators of innovation-driven growth of the enterprise are substantiated, and the efficiency of innovation investment projects is estimated. the program of the innovation-driven growth of the oil and gas machinebuilding enterprise is developed and the forecast indicators of economic efficiency of its implementation are defined. the use of the comprehensive system of assessing the innovation position of enterprises allows to formulate the justified areas of development of their innovation potential in the market. making informed decisions on the implementation of the innovation program in the context of a highly competitive target market will ensure the efficient development of the enterprise and increase the production potential of oil and gas producing companies. keywords: innovation potential, innovation climate, innovation position, oil and gas machine building, innovation-driven growth jel classifications: o30, o31, o32 1. introduction as the main component of the russia’s fuel and energy complex, the oil and gas sector is the foundation of the national economy. oil and gas machine building is a supporting branch of the oil and gas complex, as it produces the equipment required for drilling, geophysical and geological works, well servicing, extraction, etc. in the context of the increase in the share of reserves in complex, low-permeability reservoirs and significant fluctuations in the world oil prices, an objective need emerges to reduce production costs by using the own innovative technology in the oil and gas industry (zavalny, 2017). establishment of the efficient program of the innovation-driven growth is one of the most important factors for increasing the competitiveness of russian enterprises (concerning the innovation activities and state innovation policy, 1999). saturation of the oil and gas equipment market by representatives of foreign companies in the context of sanctions for imported goods creates special prerequisites for the development of oil and gas machine building by russian producers. favorable prerequisites for the development of the market of russian machine-building industry is the state policy aimed at maintaining and developing the domestic market for manufacturers of equipment for the oil and gas industry (guidance materials for glukhova and zubarev: development of the methodological approach to the assessment of the innovation position of oil and gas machine-building enterprises in the market international journal of energy economics and policy | vol 7 • issue 5 • 2017280 the development of programs for innovation-driven growth for joint-stock companies with state participation, state corporations and federal state unitary enterprises, 2011; recommendations on the development of programs for innovation-driven growth for joint-stock companies with state participation, state corporations and federal state unitary enterprises, 2010). the core attention with regard to the establishment of sanctions by the russian government was paid to the equipment for extraction of hydrocarbon raw materials. however, the market is saturated with imported equipment for the technological operations of exploration, drilling, transportation and refining of oil and gas (figure 1). the current situation has defined the key area of increasing the competitiveness of russian companies – production of innovative equipment and technology that ensure the best performance of producers in the oil and gas industry. due to this, the lack of proper substantiation for the development and implementation of innovation programs is one of the key systemic problems of the machine-building development (semenov, 2011). the economic crisis in 2009 and in 2015 significantly influenced the development of the oil and gas engineering market: the market capacity reduced by 14%, the level of expenses for the development of oil and gas deposits increased, etc. the following problems of a systemic nature are also identified in the strategy of the development of heavy engineering for the period through to 2030: 1. unsatisfactory structure of production capacities of enterprises, high wear of production assets and low technological level of production; 2. acute shortage of creation of new models of equipment due to the low level of investment in r and d; 3. underdevelopment of the market for key components, lack of production of certain types of high-tech components; 4. problem with human resources shortage of prospective talent pool; 5. strong competitive pressure from foreign producers, often based on state support (the energy strategy of russia for the period through to 2030, approved by the decree of the government of the russian federation, dated november 13, 2009). it should also be noted that oil and gas machine-building enterprises depend on the state policy in the field of foreign trade, on the adopted systems of the products certification, as well as direct financial support and other factors. in this regard, the most important innovation priority for machinebuilding enterprises should be the change in the equipment that ensures the growth in labor productivity and the reduction of resource consumption in the geological exploration, production and transportation of hydrocarbons aimed at a radical reduction in the energy intensity of equipment used in the oil and gas industry (gumerova and shaimieva, 2009). the development of equipment goes hand in hand with the development of technology, which allows to obtain effects from innovations measured as the increase in the results of oil and gas production by hundreds or even thousands of percent. at the same time, innovation passivity of many russian enterprises can be noted, in particular: a small share of the output of new products in industrial manufacturing (0.4%), insignificant number of russian industrial enterprises that actively participate in innovation developments (5-7%), low indicators of exports of high-tech products manufactured by russian producers, low patent activity, etc. the costs of manufacturers for r and d make up negligible shares from total investment about one percent, while the leaders of the world machine-building industry allocate 7-9% of revenue for r and d and development of new products (strategy for the development of heavy engineering for the period through to 2020, 2010). overall, the developed countries that carry out approximately 90% of the world’s r and d annually spend 2-2.5% of gross domestic product (gdp) on research and development in engineering; china has been spending almost 1.5% of gdp for these purposes over the past 3 years. despite this, experts predict the growth of the oil and gas machinebuilding market in the medium term with growth rates over 15%, which is due to the following objective reasons (oil and gas engineering has the development potential, 2010): 1. increase in the amount of drilling works in the development new complex deposits, which generates the demand for new modern drilling equipment; 2. high level of wear of a significant share of industrial equipment that requires replacement, which creates the prerequisites for its replacement with more advanced equipment that meets today’s requirements; 3. specific mining, geological and climatic conditions require specialized modern drilling rigs that meet the newest technology for the development of new deposits; 4. application of new drilling technology with more perfect and efficient systems of control, management, cleaning and other processes; 5. growth of the developed deposits in new areas (shelves of the northern seas, the far east, etc.), which leads to an increase in the need for geological exploration, drilling and field development. the following important factors relate to the external reasons preventing the establishment of an innovative production structure: the first is that many market-based business management tools in the rapidly developing russian economy figure 1: structure of the market for oil and gas equipment used for horizontal drilling of oil wells (kaznacheev, 2014) glukhova and zubarev: development of the methodological approach to the assessment of the innovation position of oil and gas machine-building enterprises in the market international journal of energy economics and policy | vol 7 • issue 5 • 2017 281 still yield significantly higher incomes at significantly lower costs of their use, in comparison with the implementation of innovations (loginova, 2007). therefore, many manufacturers are unlikely to prefer replacing marketing funding with investing in the creation and implementation of innovations. the second most important external reason, which forms a rather indifferent attitude of enterprises to the idea of innovation-driven growth, is the possibility of guaranteed sales of their products in the competitive environment, which is 5-6 times less strained by the number of sales entities than in the markets of developed countries, according to experts (engine for the innovative machine, 2007). the implementation of innovations allows to receive goods with higher consumer qualities or with highly competitive price parameters, while such a business model contains real market risks of rejection of the proposed innovative products. this is why most of the machine-building enterprises prefer not to take risks in the situation of lack of critical competition at all and produce products that have long won a stable demand in the market. however, the machinebuilding markets for russian producers, especially for oil and gas equipment, have turned out to be “in the crosshairs” of the world’s largest centers of machine building recently. the third external negative obstacle for the innovation activities of machine-building enterprises is the lack or low capacity of centers of competence the subdivisions of the branch science, developed network of engineering companies in the machine building area, design and engineering centers and development bureaus, developed infrastructure of technology parks, venture funds, etc. that are capable of carrying out the development of innovations and their preparation for implementation in the industry (imamutdinov and medovnikov, 2009). high fluctuations in prices for oil and gas raw materials create special conditions that require radical measures for the innovative transformation of the economy. 2. methods innovation position of an enterprise includes innovation potential and innovation climate of the enterprise. innovation potential is a combination of scientific, technical, technological, infrastructural, financial, legal, sociocultural and other opportunities to ensure the perception and implementation of novelties, i.e., the receipt of innovations (fatkhutdinov, 2008). in addition, innovation potential means a measure of readiness to perform tasks that ensure the achievement of the set innovation goal, i.e., a measure of readiness to implement a project or a program of innovation transformations and the implementation of innovation (gunin, 1999). at the moment, there are several methodological approaches to assessing the structure of innovation potential. the authors consider approaches in the article that consider the innovation potential of an enterprise in terms of: 1. blocks that form the production and economic system of the enterprise; 2. functional zones of the internal environment of the enterprise; 3. financial stability of the enterprise; 4. resources required for the implementation of innovation activities. various authors propose various methods to assess the innovation potential, depending on its structure. the most common is the assessment of innovation potential by blocks that form the production and economic system of the enterprise: product, functional, resource, organizational and management. within the framework of this approach, the innovation potential is assessed according to the following scheme: resource function project. a project or a program refers to the output and implementation of a new product (service), the area of activities. within the framework of this methodological approach, there are two schemes for analyzing the internal environment and assessing the innovation potential: detailed and diagnostic. a detailed analysis of the internal environment and assessment of the innovation potential of the organization is carried out mainly at the stage of justification of innovation and preparation of the project for its introduction and implementation. being highly labor-intensive, it generates systemic and useful information. time constraints, lack of specialists capable of conducting the systemic analysis and lack or inaccessibility of information about the organization (especially in the analysis of the innovation potential of competitors) force using diagnostic approaches to assessing the innovation potential of the organization. a methodological approach that involves the assessment of innovation potential within the financial sustainability of the enterprise includes analysis of indicators such as surplus (or shortage) of the own working capital, surplus (or shortage) of the long-term borrowed sources of stock and cost formation, surplus (or shortage) of the total number of main sources to form stocks and costs. according to the following methodological approach, innovation potential is a combination of various resources. in this regard, the potential is assessed for different types of enterprise resources. comparison of methodological approaches to the assessment of innovation potential allowed to identify differences in the structural elements of the used assessments of the innovation potential (table 1) (ponomareva, 2011a). analysis of existing methodological approaches to the assessment of the company’s innovation potential allowed to identify the core advantages and disadvantages of each of them (table 2) (ponomareva, 2011b). innovation climate is the second most important component of the innovation position of the enterprise. innovation climate is the state of the external environment of the organization that facilitates or undermines the achievement of the innovation goal (24). there are a macro environment (environment of indirect impact) and a micro environment (environment of direct impact) in the structure of the external environment of the organization. macro environment establishes the general conditions of the firm functioning. in most cases, the macro environment is not specific to a particular firm. however, the degree of influence of its state on the innovation activities of firms varies due to differences in both their areas of activities and internal potential. glukhova and zubarev: development of the methodological approach to the assessment of the innovation position of oil and gas machine-building enterprises in the market international journal of energy economics and policy | vol 7 • issue 5 • 2017282 there are several approaches to the structure of the external macro environment of the enterprise. in the first approach, four strategic areas are identified in the macro environment: social, technological, economic and political, which are described by a number of indicators. there areas of external environment are analyzed using pest analysis or step analysis. another methodological approach, proposed by barancheyev, identifies six areas of the external macro environment: economic and financial, scientific and technological, sociopolitical, g e o g r a p h i c a l a n d c o m m u n i c a t i o n a l , m a n a g e m e n t a n d organizational, and regulatory (guidance materials for the development of programs for innovation-driven growth for joint-stock companies with state participation, state corporations and federal state unitary enterprises). approved by the ministry of economic development of russia, 2011; recommendations on the development of programs for innovation-driven growth for joint-stock companies with state participation, state corporations and federal state unitary enterprises, 2010). the key distinguishing feature of barancheyev’s methodological approach is that it takes into consideration the impact of the geographical, communicational, management and organizational areas. however, according to the authors, when analyzing the innovation macroclimate of the oil and gas machine-building enterprise, it is necessary to take into account the state of the fuel and energy complex of the country, which will allow to table 1: comparative characteristics of methodological approaches to the assessment of innovation potential by structural elements methodological approach assessment of the blocks that form the production and economic system of the enterprise identification of functional zones of the internal environment of the enterprise assessment of the financial stability of the enterprise identification of resources required for the implementation of innovation activities product functional production marketing element resource material and equipment material resources labor personnel human resources informational intellectual resources financial finance financial stability financial resources organizational organizational structure infrastructure resources process technology organizational culture organizational culture management table 2: advantages and disadvantages of methodological approaches to the assessment of innovation potential approach advantages disadvantages assessment of the blocks that form the production and economic system of the enterprise comprehensive assessment of the potential through the analysis of all the elements of the internal environment of the enterprise the need to use expert judgment, which is often subjective; indicators relating to other components of the overall potential of the enterprise are often misrepresented as characteristics of innovation potential identification of functional zones of the internal environment of the enterprise takes into consideration the impact of such critical elements as personnel, finance, state of production and marketing in the enterprise, as well as the overall organizational culture does not take into consideration the impact of informational and material resources, the state of the organizational structure, technology and enterprise management system; the need to use expert judgment, which is often subjective assessment of the financial stability of the enterprise availability of quantitative estimation of indicators; simplicity of calculations; based on the assessment of financial resources that play a crucial role in the implementation of innovation activities innovation potential is only assessed from the financial part and does not cover other aspects of the internal environment of the enterprise identification of resources required for the implementation of innovation activities based on the analysis of the crucial resources required for the implementation of innovation activities; infrastructure is assessed in terms of innovation-driven growth of the enterprise based on the analysis of a predominantly resource block and almost does not cover other elements of the internal environment of the enterprise (except for the infrastructure); lack of a unified system of indicators to assess each type of resources glukhova and zubarev: development of the methodological approach to the assessment of the innovation position of oil and gas machine-building enterprises in the market international journal of energy economics and policy | vol 7 • issue 5 • 2017 283 conduct the most qualitative and reliable assessment of the macro environment of the enterprise. the micro environment of the organization is considered as a combination of strategic zones of the nearest environment as the composition of the entities directly interacting with it and having a direct impact on the state of innovation potential. suppliers, consumers, marketing intermediaries, competitors and contact audiences are usually identified in the structure of the external micro environment of the enterprise. porter five forces analysis is one of the methods for assessing the external micro environment of the enterprise, which includes analysis of competitors within the industry, potential (new) competitors, producers of substitute products, suppliers and consumers. each of the identified blocks is assessed by a group of indicators that determine the strength of the influence of the external micro environment on the enterprise. the following methodological approach to the assessment of the innovation microclimate offers an analysis of six strategic zones: 1. economic zone, the market segment: level of competition, relations with consumers and partners; 2. zone of capital formation investment; 3. zone of new technology and scientific information resources; 4. zone of raw materials, fuel, energy, material and equipment resources; 5. zone of labor resources the labor market of specialists, managers, workers; 6. groups of strategic influence (at the level of the industry, city region, district). these strategic zones are assessed using an expert judgment due to the complexity of applying quantitative measures of the assessment of the innovation climate. this leads to a discrepancy in the expert judgments and assessments, which reduces the confidence and reliability of such a method. the authors suggest to assess the innovation position of the oil and gas machine-building enterprise by adjusting the system of indicators that takes into consideration specifics of the scientific and innovation focus, specifics of the industry and availability of quantitative measurement (table 3). it is suggested to assess the innovation position in three main areas: innovation potential, state of the external environment and level of competitiveness (yagudin, 2011). adjustment of indicators is made on the basis of the resource approach, which allows to assess the capabilities of the enterprise and to highlight the specificity of the sectoral demand. as such, each type of resources is represented by objective measurable indicators: intellectual (the number of patents and the ratio of their use), material (depreciation of fixed assets and production capacity utilization), financial (equity ratio), personnel (share of personnel with higher professional education) and infrastructure resources, which are described through the share of personnel employed in the r and d department, since this indicator reflects the availability and scope of this business unit. the state of the external environment is described through objective, measurable quantitative indicators that reflect the favorable nature of the external environment from the point of implementation of innovation projects. the level of competitiveness is described through a set of indicators that reflect the position of the enterprise relative to competitors. 3. results the level of innovation-driven growth of domestic enterprises of oil and gas machine building was analyzed by the example of one of the leading enterprises of this industry in western siberia. the enterprise occupies about 25-30% of the market of packaged modular equipment for oil and gas fields development. the mission of the enterprise is: “to ensure efficient solution of the customer’s tasks by developing and producing modern table 3: proposed comprehensive system of indicators of the innovation position of the oil and gas machine-building enterprise areas of assessment criterion level of competitiveness state of the external environment innovation potential 1 2 3 4 indicators relative market share level of taxation (income tax rate) share of personnel with higher professional education consumer satisfaction dynamics of demand for products (by sales volume) ratio of equipment use share of r and d costs in comparison with the industry average availability of lending, interest rate number of valid patents (relative to the industry leader) expenses for 1 rub. of the marketable output (relative to the industry leader) inflation rate ratio of patent use participation in the industry exhibitions (relative to the industry leader) share of imported machinery products in the domestic market share of personnel involved in the development and implementation of innovation in the enterprise dynamics of income levels of oil extracting companies level of financial capacity (equity ratio) depreciation of fixed assets glukhova and zubarev: development of the methodological approach to the assessment of the innovation position of oil and gas machine-building enterprises in the market international journal of energy economics and policy | vol 7 • issue 5 • 2017284 equipment that complies with russian and international standards” (lenkova, 2013). the core objective of the enterprise is to produce high-quality, competitive products that meet customer’s requirements (osinovskaya and lenkova, 2015). the objectives of the second level include: constant work on improving the quality of the equipment produced and the quality management system, improvement of its efficiency and performance, identification and promotion of the processes leading to the improvement of the enterprise performance. a group of criteria is proposed to assess the first area of “innovation potential,” which reflect the enterprise’s willingness to implement innovation projects. they include the level of financial capacity of the enterprise, which is estimated by the value of the ratio of equity concentration (autonomy). it is also proposed to pay attention to the number of valid patents compared with the number of patents of the industry leader. the ratio of equipment use is estimated from the standpoint of the possibility of producing new types of products and increasing production volumes (maffin and braiden, 2005). it is proposed to analyze indicators reflecting the favorable nature of the external environment from the perspective of implemented innovation projects when assessing the state of the external environment. they include the level of taxation, which is defined based on the income tax rates. the criterion of the dynamics of demand for products is estimated through the forecast of the volume of its realization. the maximum value of the indicator on the scale is taken as the ratio of the total sales volume of the industry leader’s products to the sales volume of the previous year of the analyzed enterprise 181.35%, i.e., an increase in the sales volume that secured the position of a market leader for the enterprise. on the scale for inflation, the average inflation rate for the eu countries is taken as the minimum value, and the maximum inflation rate in russia over the past 10 years is taken as the maximum. the dynamics of the income level of oil extracting enterprises is described by the ratio of the total net profit of the leading oil extracting enterprises of the reporting year to the profit of the previous year. the largest change in net profit for the year among all the largest enterprises is taken as the maximum value of the indicator, and the smallest value is taken as the minimum. it is proposed to analyze the indicators describing the efficiency of the enterprise’s activity in comparison with competitors to assess the last area “level of competitiveness” (glukhova and ponomareva, 2010). consumer satisfaction is calculated according to the method used in the enterprise, using formula (deberdieva, 2015). k1 k2 k3 u=100 + + 100 s d s1   − ×   (1) where, • u is consumer satisfaction with the products of the enterprise, %; • k1 is a number of claims made by the customer during the year against the equipment supplied by the enterprise, pcs; • s is a number of products delivered to the customer during the year, pcs; • k2 is a number of agreements to contracts for the supply of products where deadline for the manufacture of products was broken due to the fault of the enterprise, pcs; • d is a number of contracts concluded for the supply of products, pcs; • k3 is a number of applications (contracts) not concluded with the customer because the products are not manufactured, pcs; • s1 is a total number of applications filed during the year, pcs. the best value of the indicator is 100%, the worst value is 0. costs per 1 ruble of the marketable output relative to the industry leader are found as the ratio of costs per 1 ruble of the marketable output of the analyzed enterprise to the costs per 1 ruble of the marketable output of the industry leader. the best result is 1 or less, i.e., the enterprise’s costs are the same as those of the industry leader or less; the worst result is the ratio of the highest level of costs of the analyzed enterprise to the best level of leader’s costs −1.15. the proposed method for assessing the innovation position takes into consideration the most priority areas of the enterprise’s development, including the level of innovation potential, also focusing on the position of the industry leader and the state of the external environment (ponomareva, 2011a; ponomareva, 2011b). the analysis was carried out for 4 years: 2013, 2014, 2015 and 2016. for this, the quantitative values of the system indicators were first defined and then translated into score (table 4). the enterprise increased its competitiveness level in 2016, which was primarily thanks to an increase in the relative market share, as well as an increase in the number of participations in industry exhibitions relative to the industry leader. the level of innovation potential in 2016 remains at an average level, well below the pre-crisis level. this is largely due to a constant increase in depreciation of fixed assets and a lack of their renewal at the enterprise, as well as to an annually declining level of financial opportunities, which is also caused by the consequences of the recent crisis. after choosing the assessment of the innovation position, the authors developed the program of innovation activities of the oil and gas machine-building enterprise, which assumed specification of the general strategic provisions of innovation activities. the purpose of developing the program of the innovation-driven growth of the enterprise is to identify and systematize the main areas and objectives of the company’s activities in the field of innovation, covering all stages of the innovation cycle, optimize available resources and establish the development indicators for the planned period. the key performance indicators of the program of the innovation-driven growth are provided in accordance with the core objective of the enterprise (table 5). let’s analyze the structure of the enterprise output in order to determine priority investment projects for product innovations (figure 2). the largest share in the production structure is taken by: equipment for measuring the production rate of oil wells, cluster pump glukhova and zubarev: development of the methodological approach to the assessment of the innovation position of oil and gas machine-building enterprises in the market international journal of energy economics and policy | vol 7 • issue 5 • 2017 285 stations and other pump stations of various purposes. to maintain the competitiveness of these types of manufactured equipment, it is necessary to modernize and introduce innovations in their production. according to the algorithm of selection of innovative projects for the program of the innovation-driven growth, during the pre-selection phase the projects were selected for product innovations related to the types of products manufactured at the enterprise that were most in demand and occupied the largest share in the sales structure. as such, after the first stage, innovation projects were selected and an economic evaluation of their efficiency was carried out using dynamic indicators (guidance recommendations on the assessment of the efficiency of investment projects, 1999) (table 6). table 4: assessment of the innovation position of the oil and gas machine building enterprise indicator unit of measurement 2013 2014 2015 2016 value score value score value score value score 1 2 3 4 5 6 7 8 9 10 innovation potential talent pool (proportion of personnel with higher professional education) % 24 3 27 4 28 4 30 4 technical potential (wear of fixed assets) % 35 4 39 4 46 3 49 3 number of valid patents (relative to the industry leader) % 283 5 350 5 383 5 329 5 ratio of patents use % 65 4 71 4 74 4 78 4 share of personnel involved in the development and implementation of innovations at the enterprise % 0.36 2 0.45 2 0.44 2 0.52 2 level of financial capacity (ratio of equity concentration (autonomy)) share 0.5 3 0.31 2 0.19 1 0.17 1 ratio of equipment use % 37.4 4 25.7 4 47.4 3 47.9 3 average value 3.6 3.6 3.1 3.1 state of the external environment level of taxation (income tax rate) % 20 2 20 2 20 3 20 3 dynamics of demand for products (by sales volume) % 131 4 116.9 4 133.1 4 112.7 4 loan availability, annual interest rate % 10.9 4 12 4 18.5 3 13 4 inflation index % 11.9 3 13.3 2 8.8 4 9.1 3 share of imported machine-building products in the domestic market % 85.6 1 66.9 2 64.9 2 63 2 dynamics of income levels of oil extracting companies % 154.4 2 102.7 1 70.7 1 132.1 2 average value 2.7 2.5 2.8 3.0 level of competitiveness relative market share % 60 3 71 4 73 4 93 5 consumer satisfaction % 73.4 4 73 4 68 4 66 4 share of expenditures on r and d in comparison with the industry average % 61 4 53 3 81 5 86 5 costs per 1 ruble of the marketable output (relative to the industry leader) share 1.09 3 1.05 4 1.00 5 1.03 5 participation in industry exhibitions (relative to the industry leader) % 57.1 3 57.1 3 37.5 2 57.1 3 average value 3.4 3.6 4.0 4.4 table 5: key performance indicators of the program of the innovation-driven growth of the oil and gas machine-building enterprise indicator purpose indicators, unit of measurement performance indicators of interaction with external sources of development and innovation number of innovation projects implemented in cooperation with scientific institutes, pcs. number of innovation projects implemented in cooperation with partner universities, pcs. indicators of technological leadership number of valid patents at the year-end, pcs. ratio of patents use, % assessment of the company’s innovation activities in general. indicators of r and d funding and efficiency profitability of innovative products, % share of costs for r and d in revenue, % share of personnel involved in the development and implementation of innovations at the enterprise, % assessment of fixed assets coefficient of equipment use, % wear of fixed assets, % performance indicators of the enterprise revenue, million rub. return on sales, % glukhova and zubarev: development of the methodological approach to the assessment of the innovation position of oil and gas machine-building enterprises in the market international journal of energy economics and policy | vol 7 • issue 5 • 2017286 the discount rate was calculated using the buildup method. the impact of risks on projects was assessed by an expert judgment. the risk-free interest rate amounted to 8%, and the amount of premiums for all types of risks was 3.9%. as such, the discount rate for the calculated innovation investment projects was 11.9%. as can be seen from table 6, three out of the four projects considered for inclusion in the program are cost-effective. following the results of the assessment, the project for the modernization of the dosing unit for chemical reagents is eliminated at the second stage of the project selection by adding the function of preparing the reagents, since it is not cost-effective. as such, following the results of selection of innovation projects, it is recommended to include a project for the modernization of equipment for measuring the production rate of oil wells, development of equipment of high mobility and density, and the modernization of pump stations by installing a high-tech pump as product innovations in the program of the innovation-driven growth of the enterprise. aside from product innovations, it is recommended to include innovations in business processes, measures for the commercialization of technology, personnel development, equipment modernization and interaction with universities and scientific institutes in the program of the innovation-driven growth of the enterprise (table 7). the target values of the key performance indicators for the implementation of the developed program of the innovation-driven growth of the oil and gas machine-building enterprise were defined using the delphi method. the forecast for the implementation of the proposed program of the innovation-driven growth was planned and the economic effect was determined based on the conducted assessment (table 8). results of the assessment indicate the viability of implementing the proposed program of the innovation-driven growth of the oil and gas machine-building enterprise. the presented indicators of costeffectiveness confirm the validity of the proposed methodological approach to the assessment of the innovation position of the enterprise. the comprehensive assessment allowed to expand the choice of managerial decisions, which allow to take various specifics of the strategic position of the enterprise in the industry into consideration to a fuller extent. another advantage of this method is the use of quantitative indicators in the assessment, which ensures greater objectivity of the results obtained. 4. discussion the methodological approach to the assessment of the innovation potential of oil and gas machine-building enterprises proposed by the authors allowed to expand the choice of managerial decisions on the formation of the program of the innovation-driven growth and improve the justification of the formation of strategic decisions. the implementation of the authors’ approach ensures: • formation of justified criteria for assessing the innovation potential and the innovation climate at the oil and gas machinebuilding enterprise; • development of the quality of innovation management at the oil and gas machine-building enterprises; • possibility of achieving high values of the enterprise’s competitiveness in the industry. the proposed methodological approach includes a set of indicators that reflect both external opportunities for development in the market and internal innovation potential. the developed set of indicators can be expanded and supplemented by special criteria reflecting the specifics of the enterprise’s activities in the market (deberdieva, 2015). the authors see the areas of further research in the study of processes of formation of competitive strategies based on the innovation-driven growth of the oil and gas machine-building figure 2: structure of production by the oil and gas machine-building enterprise table 6: indicators of efficiency of innovation investment projects of the oil and gas machine‑building enterprise name of innovation project project success criteria npv internal rate of return profitability index payback period modernization of equipment for measuring the production rate of oil wells by installing a system of total oil metering during its transportation 220,389.8 0.53 1.08 2.9 development of equipment for measuring the production rate of oil wells of high mobility and density 47,624.6 0.28 1.06 3.9 modernization of the dosing unit for chemical reagents by adding the function of reagents preparation −58,630.2 0.79 modernization of pump stations by installing a high-tech innovative pump 261,803.0 0.47 1.07 3.1 npv: net present value glukhova and zubarev: development of the methodological approach to the assessment of the innovation position of oil and gas machine-building enterprises in the market international journal of energy economics and policy | vol 7 • issue 5 • 2017 287 table 7: program of the innovation-driven growth of the oil and gas machine-building enterprise (fragment) area of development measure target year of implementation, years amount of funding, thousand rub performance indicators 1 2 3 4 5 innovations in business processes adjustment of the system of intrafirm planning taking the innovation activities of the enterprise into consideration 2017 12.0 number of commercially viable innovation projects implemented share of personnel involved in the development and implementation of innovations at the enterprise arrangement of the system of continuous monitoring of new technology in the domestic and foreign markets 2017 183.5 … … … product innovations modernization of equipment for measuring the production rate of oil wells by installing a system of total oil metering during its transportation 2018 4,187,042.1 profitability of innovative products share of costs for r and d in revenue revenue number of valid patents npv payback period internal rate of return profitability index development of equipment for measuring the production rate of oil wells of high mobility and density 2018 1,169,051.1 modernization of cluster pump stations by installing a high-tech innovative pump 2018 5,532,533.1 technology commercialization development of procedures for improving the incentive system for creating intellectual property 2019 3.0 number of valid patents ratio of patents use share of personnel involved in the development and implementation of innovations at the enterprise … … … personnel development performance reviews taking innovation activities of the enterprise into consideration 2017 180.0 share of personnel involved in the development and implementation of innovations at the enterprise labor productivity number of commercially viable innovation projects implemented … … … equipment modernization modernization of existing equipment for the production of new types of innovative products 2017 730.0 ratio of equipment use wear of fixed assets share of r and d costs in revenue … … … cooperation with universities, scientific institutes development of procedures for cooperation with partner universities 2017 5.0 number of innovation projects implemented in cooperation with partner universities number of innovation projects implemented in cooperation with scientific institutes number of valid patents number of commercially viable innovation projects implemented conclusion of contracts/agreements on cooperation with new core universities and partner universities 2017 72.0 monitoring and selection of promising r and d applicable for the enterprise in profile universities and scientific institutes 2017 252.0 glukhova and zubarev: development of the methodological approach to the assessment of the innovation position of oil and gas machine-building enterprises in the market international journal of energy economics and policy | vol 7 • issue 5 • 2017288 enterprises, in-depth analysis and detailed study of the influence of various factors on the company’s innovation potential, and building the adapted models for developing managerial decisions for the development of the innovation climate in the industry. 5. conclusion the russian machine-building market for the oil and gas industry has significant potential for sustainable development and growth (gunin, 1999; loginova, 2007). corporate service continues to develop at a number of large oil and gas machine-building enterprises. however, experts define that the key area of the oil and gas machine building development is the development and implementation of innovation equipment and technology that is in demand by oil and gas industry enterprises worldwide (imamutdinov and medovnikov, 2009). in the context of the increasing role of innovations as a factor of economic growth and enterprise competitiveness, the status of innovation management is increasing (grocheva et al., 2015). an innovation component is one of the main components at all levels of enterprise management, which means that innovation management at the current stage of economic development turns into the leading element of enterprise development in the market. identification of innovation opportunities and shortcomings in the innovation-driven growth of the enterprise allows to assess its market potential and identify the expected threats from the external environment. assessment of the innovation position of the enterprise allows to anticipate changes in the cost-effectiveness of the enterprise’s production activities during its innovation planning (borisov and pochukaeva, 2009). it must be noted that the authors consider the innovation opportunity as an area of the enterprise efforts, through which it can achieve a customized, quite often leading position in the markets of certain products. in turn, the threat in the innovation area of activity can be defined as complications arising from an unfavorable trend or specific events that can lead to the product being squeezed out of the market or its access to the market being restricted in the absence of purposeful innovation efforts (osinovskaya et al., 2015). in this regard, the development of the program of the innovation-driven growth of the enterprise should be scientifically grounded and practically applicable. at the moment, the existing methods of the company’s innovation position in the market can be divided into 2 groups: assessment of innovation potential and assessment of the innovation climate. each of these methods offers a set of multipurpose assessment indicators and various approaches to their measurement. each of the methods under study has advantages and disadvantages. the authors proposed a combination of set of assessment indicators for both internal innovation potential and external innovation climate. methodological approaches to measuring the indicators of the innovation position can also be divided into two groups: an expert approach and application of mathematical models to measure the assessment criteria. the expert approach is the most justified in measuring the quality indicators and in the absence of complete and reliable information. mathematical models most often give the most reliable estimate of quantitative criteria of innovationdriven growth of the enterprise. recommendations of the authors are aimed at the use of two approaches that allow to expand the range of the assessed indicators (qualitative and quantitative), as well as to improve the reliability of measuring the criteria that serve as the basis for the formation of the program of the innovation-driven growth of the oil and gas machine-building enterprise. the methodological approach to the assessment of the innovation position of the oil and gas machine-building enterprise in the market recommended by the authors will allow to: 1. expand the range of criteria for assessing the innovation potential of the oil and gas machine-building enterprise; 2. improve justification of the assessment of the influence of the external environment on the innovative capabilities and threats to the enterprise in the market; 3. reasonably define the target indicators of the innovationdriven growth of the enterprise in the industry; table 8: projected effect of the implementation of program of the innovation‑driven growth of the oil and gas machine-building enterprise indicators unit of measurement current year target year growth rate, % number of innovation projects implemented in cooperation with scientific institutes pcs. 9 19 114.6 number of innovation projects implemented in cooperation with partner universities pcs. 0 7 number of valid patents at the year-end pcs. 24 32 33.3 ratio of patents use % 78 91 16.0 profitability of innovative products % 5.6 15.3 173.2 share of costs for r and d in revenue % 3.5 8.2 135.5 share of personnel involved in the development and implementation of innovations at the enterprise % 0.54 2.30 322.2 ratio of equipment use % 44.5 65.2 46.5 wear of fixed assets % 53 35 -33.6 revenue million rub 4013 6,102.4 52.1 return on sales % 4.21 14.2 237.3 glukhova and zubarev: development of the methodological approach to the assessment of the innovation position of oil and gas machine-building enterprises in the market international journal of energy economics and policy | vol 7 • issue 5 • 2017 289 4. improve the quality of development of programs for innovation-driven growth of the oil and gas machine-building enterprise. improving the innovation-driven growth in the field of equipment for oil and gas enterprises will improve the competitiveness of russian enterprises, on the one hand, and ensure the efficiency of hydrocarbon extraction and production of petroleum products in the world market, on the other hand. references b o r i s o v, v. n . , p o c h u k a e v a , o . v. ( 2 0 0 9 ) , i n n o v a t s i o n n o tekhnologicheskoye razvitiye mashinostroyeniya kak faktor innovatsionnogo sovershenstvovaniya obrabatyvayushchey promyshlennosti (innovation and technological development of machine building as a factor of innovation perfection of processing industry). issues of forecasting, 4, 37-45. deberdieva, e.m. (2015), key performance indicators as an instrument of achieving strategic indicators of oil and gas producers. mediterranean journal of social sciences, 3(s3), 19-30. dvigatel dlya innovatsionnoy mashiny (engine for the innovative machine). (2007), editorial article, expert ural no. 27. fatkhutdinov, r.a. (2008), innovatsionnyy menedzhment (innovation management): textbook. 6th ed. st. petersburg: peter. federal law of the russian federation. (1999), ob innovatsionnoy deyatelnosti i o gosudarstvennoy innovatsionnoy politike (concerning the innovation activities and state innovation policy. g l u k h o v a , m . g . , p o n o m a r e v a , e . v. ( 2 0 1 0 ) , k r i t e r i a l n a y a osnova ekonomicheskoy otsenki innovatsionnogo razvitiya neftegazovogo mashinostroyeniya (criterial foundation of economic assessment of innovation-driven growth of oil and gas machine building). innovations in managing the regional and sectoral development: collection of scientific papers. tyumen: tyumsogu. p254-257. grocheva, e.p., naumkin, n.i., shabanov, g.i., shekshaeva, n.n., kupryashkin, v.f., panyushkina, е.n. (2015), practical training in innovative engineering activity. international journal of applied and fundamental research, 2, 44. gumerova, g.i., shaimieva, e.s.h. (2009), otkrytyye innovatsii i otkrytyye tekhnologicheskiye platformy (open innovation and open technological platforms). investment in russia, 3, 42-48. gunin, v.i. (1999), upravleniye innovatsiyami: 17-modulnaya programma dlya menedzherov “upravleniye razvitiyem organizatsii” (managing innovation: a 17-module program for managers “managing the organization development”), module 7. moscow: infra-m. p328. imamutdinov, i.n., medovnikov, d.s. (2009), vysokoye innovatsionnoye ponuzhdeniye (high innovation compulsion). expert, 43, 56-61. kaznacheev, p.p. (2014), sanktsii zamedlennogo deystviya, ili rossiya v neftyanoy lovushke (sanctions of deferred action, or russia in the oil trap). available from: https://www.republic.ru/economics/ sanktsii_zamedlennogo_deystviya_ili_rossiya_v_neftyanoy_ lovushke-1194826.xhtml. lenkova, o.v. (2013), the peculiarities of mission forming in russia’s oil and gas companies. world applied sciences journal, 27(3), 345-348. loginova, e.g. (2007), nekotoryye tendentsii rossiyskogo rynka neftegazovogo oborudovaniya (some trends of the russian market of oil and gas equipment). drilling and oil, 6, 3-5. maffin, d., braiden, p. (2005), manufacturing and supplier roles in product development. international journal of production economics elsevier science publishing company inc., 2, 205. metodicheskiye rekomendatsii po otsenke effektivnosti investitsionnykh proyektov (guidance recommendations on the assessment of the efficiency of investment projects). approved by the ministry of economics of the russian federation, the ministry of finance of the russian federation and gosstroy of the russian federation. no. vk 477. available from: http://docs.cntd.ru/document/1200005634. [last dated on 1999 jun 21]. ministry of economic development of russia. (2011), metodicheskiye materialy po razrabotke programm innovatsionnogo razvitiya aktsionernykh obshchestv s gosudarstvennym uchastiyem, gosudarstvennykh korporatsiy i federalnykh gosudarstvennykh unitarnykh predpriyatiy (guidance materials for the development of programs for innovation-driven growth for joint-stock companies with state participation, state corporations and federal state unitary enterprises), approved by the ministry of economic development of russia, no. zr-of. available from: http://www. economy.gov.ru/minec/activity/ sections/innovations/innovative/ doc20110201_02. [last dated on 2011 jan 31]. neftegazovoye mashinostroyeniye imeyet potentsial dlya razvitiya (oil and gas engineering has the development potential). (2010), rbc: market research. available from: http://www.marketing.rbc. ru/articles/02/04/2010/562949978262890.shtml. osinovskaya, i.v., lenkova, o.v. (2015), the technological development of managerial decisions on the productive capacity of oil producing industrial building structures. international business management, 9(2), 164-168. osinovskaya, i.v., yakunina, o.g., lenkova, o.v. (2015), multiobjective approach in developing oil production enterprise’s production strategy. mediterranean journal of social sciences, 6(s3), 193-202. ponomareva, e.v. (2011a), metodicheskiye osnovy k otsenke innovatsionnogo razvitiya mashinostroitelnogo predpriyatiya (methodological foundations for assessment of innovation-driven growth of a machine-building enterprise). in: proceedings of the 49th international student scientific conference “student and a scientific and technical progress”: economics. novosibirsk: nsu. p127. ponomareva, e.v. (2011b), metodicheskiye podkhody k otsenke innovatsionnogo potentsiala predpriyatiy neftegazovogo mashinostroyeniya i puti ikh razvitiya (methodical approaches to assessment of the innovation potential of oil and gas machinebuilding enterprises and their ways of development). in: development of innovation entrepreneurship in the region: proceedings of the scientific and practical conference of young scientists, graduates and students. tyumen: tyumsogu. p179-184. rekomendatsii po razrabotke programm innovatsionnogo razvitiya aktsionernykh obshchestv s gosudarstvennym uchastiyem, gosudarstvennykh korporatsiy i federalnykh gosudarstvennykh unitarnykh predpriyatiy (recommendations on the development of programs for innovation-driven growth for joint-stock companies with state participation, state corporations and federal state unitary enterprises), approved by the decision of the governmental commission on high technologies and innovations. available from: http://docs.cntd.ru/document/902306418. [last dated on 2010 aug 03]. semenov, v. (2011), neispolzovannyye vozmozhnosti (untapped opportunities), analytical magazine “oil of russia”, special issue “oil service”. p10-12. strategiya razvitiya tyazhelogo mashinostroyeniya na period do 2020 goda (strategy for the development of heavy engineering for the period through to 2020). moscow: 2010. glukhova and zubarev: development of the methodological approach to the assessment of the innovation position of oil and gas machine-building enterprises in the market international journal of energy economics and policy | vol 7 • issue 5 • 2017290 the energy strategy of russia for the period through to 2030, approved by the decree of the government of the russian federation, no. 1715-r. available from: https://minenergo.gov.ru/node/1026. [last dated on 2009 nov 13]. yagudin, s.y. (2011), formirovaniye mekhanizmov otsenki konkurentnogo potentsiala venchurnykh firm v ramkakh strategii innovatsionnogo razvitiya (formation of mechanisms for assessing the competitive potential of venture firms as part of the strategy of innovation-driven growth). issues of statistics, 4, 10-14. zavalny, p.n. (2017), importozameshcheniye neftegazovogo oborudovaniya, kak osnova ekonomicheskoy i energeticheskoy bezopasnosti strany (import substitution of oil and gas equipment as a foundation of economic and energy security of the country). ecological bulletin of russia, 7. available from: http://www.ecovestnik.ru/index.php/2013-07-07-02-13-50/ nashi-publikacii/2508-importozameshchenie-neftegazovogooborudovaniya-kak-osnova-ekonomicheskoj-i-energeticheskojbezopasnosti-strany. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. . international journal of energy economics and policy | vol 8 • issue 6 • 2018 39 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(6), 39-47. reality and prospect of electricity production from renewable energies in arab countries: analytical study (1990–2017) amal rahmane1*, abdelhak bentafat2 1department of economic sciences, faculty of economic and business sciences and management sciences, university of mohamed khider, biskra, algeria, 2department of economic sciences, faculty of economic and business sciences and management sciences, university of kasdi merbah, ouargla, algeria. *email: r.amel70@yahoo.fr received: 25 july 2018 accepted: 04 october 2018 doi: https://doi.org/10.32479/ijeep.6939 abstract this study aims to highlight the status of electricity production from renewable energies in some arab countries due to their potential; that could lead to an increase in the achievement of a significant part of sustainable development if it will be exploited. in addition, this study seeks to highlight the contribution of each renewable energy in producing electricity for every arab country. one of the results of this study is that there is a very strong correlation (0.995) between electricity consumption and production in the considered countries, that means that the increase in electricity consumption is pushing the production to achieve self-sufficiency. moreover, there is a weak and low correlation (−0.420) between the electricity production from renewables and co2 emissions per capita, which means that the increase in the production of electricity from renewables in arab countries reduces co2 emissions per capita, and this is very logical. it should be noted that some arab countries have taken rapid steps towards pioneering electricity production through renewables such as egypt and morocco. keywords: electricity production, renewable energy, arab region jel classifications: o57, q42, q48 1. introduction against the backdrop of the serious and scientifically justified consequences of climate changes such as global warming, flooding … etc, and with the increasing of global fossil fuels’ consumption, renewable energy sources and environmentally friendly energy substitutes, such as wind, solar, biomass and geothermal, have had further importance since they are undepleted sources and do not cause any harmful emissions to the environment. renewable energies have been increasing in the world since 2009, with an annual growth rate of 8–9% registered at record levels by the end of 2016, with a growth rate 8.7% in 2016. in addition, the installed capacity of renewable energies reached a record level of 2006 gw -according to the international renewable energies agency (irena)which is mainly derived from solar power (32%) and wind power (12%). according to the international energy agency (iea) outlook in 2017, the installed capacity of renewable energies will know a growth of 43% in 2022 due to new solar photovoltaic (pv) installations in china and india. by the same report, solar pv will enter a new era in the five coming years because of lower prices, the vitality of markets especially in china, and the improvement of the policies for a large-scale solar energy diffusion (yassaa, 2018). the production of renewable energies is reported to cover only 20% of electricity consumption despite the efforts of some countries to spearhead the production of renewable energies have been recorded. as china is the lead in the production of renewable energies through wind power, the united states of america is the second in power production through the biomass, this journal is licensed under a creative commons attribution 4.0 international license rahmane and bentafat: reality and prospect of electricity production from renewable energies in arab countries: analytical study (1990–2017) international journal of energy economics and policy | vol 8 • issue 6 • 201840 the third place is for germany through its adoption of solar panels. the arab countries are striving to keep pace with the sustainable development of the developed countries that produce electricity from renewable energies, especially if it is known that the ingredients of some arab countries are far superior to those of the developed countries that have pioneered the electricity production from renewable energies. although, a number of arab countries such as jordan and morocco have resorted to the importation of electricity in the past few years, many of these arab countries -north africahave begun to conclude cooperation agreements to produce electricity from renewable energies, such as morocco and algeria due to their potential because of the vast desert areas that can receive huge amounts of sunlight; not to mention, the ingredients of wind energy in other arab countries such as egypt, uae, jordan according to irena. that is what we will try to highlight through this study by answering the following question: what is the reality of electricity production from renewable energies in the arab countries? and what are their future strategies in this area? 2. literature review 2.1. electricity production 2.1.1. electricity as a secondary energy electricity is a form of energy and more accurately an energy vector that has a high flexibility of use. also, it has virtually no competitors in such applications as telecommunications, computing or lighting. it can be easily transported but difficult to store (bonal and rossetti, 2011). electricity is by far the most important of secondary energies. its industrial and commercial development, that has continued since its origins i.e., 120 years, is justified by the intrinsic qualities of this form of energy, in particular the diversity of its modes of production, the flexibility and the convenience of its many uses. its success is measured by its penetration rate, i.e., the share that electricity represents in the final energy’s balance. it reached about 20% worldwide at the end of the twentieth century, but in the most industrialized countries it exceeded 40%. electricity, by its ability to satisfy in every place and at any time multiple energy requirements through a highly branched distribution network, has contributed significantly to the economic boom. its penetration rate could be seen as an indicator of technical development or an index of a country’s standard of living. the electrical system has taken on such importance that it has become strategic and that many governments have wanted to monitor it. but today, this form of energy tends to be considered as an ordinary product to be exchanged freely in the market (naudet et reusso, sans date de pub). 2.1.2. modes of electricity production one of the reported flexibilities of the electrical system is to be able to have means of production fuelled by the most diverse energy sources, whose technical and economic characteristics are sufficiently varied to satisfy all aspects of demand, and whose geographical locations can be very different, imposed either by the energy source or for the good dynamic balance of the network. the modes of production are classified in large categories according to the principle of the transformation of the primary energy used into electricity (naudet et reusso, sans date de pub). the production and distribution of electricity are, at present, key issues in the energy field. the list is long-discussed about them: co2 emissions, reasoned use of electricity, importance of investments to be made to meet demand, place of nuclear power, development of renewable energies, development and regulation of networks, storage of energy, sale price of electricity etc. electricity has the peculiarity of being an instantaneous energy. it is not stored in large quantities. it is, therefore, necessary that at any time its production equals its consumption, although neither is constant. two situations exist. the easiest way is when there is no network. the consumer can only use what he produces. it can still be serviced by storage. when a network exists it is necessary to ensure a complex work of adjustment to maintain to all users a quality electricity: frequency, constant voltage, and no break. the adjustment must always take into account changes in production and consumption. the variations in consumption present a daily cycle and a seasonal cycle (mathis, 2011). in brief, electricity is produced through various primary energy sources that may be depleted or renewable, and each source has its pros and cons. the table 1 can explain that oil is not listed because its uses are secondary in electricity production. 2.1.3. electricity production from renewables 2.1.3.1. electricity production from wind sources wind turbines, modern windmills, transform the mechanical energy of the wind into electrical energy. their benefits compared to windmills are: a better yield, the production of a transportable and usable energy for many applications (mathis, 2011). 2.1.3.2. electricity production from hydraulic sources the principle at work in hydroelectricity involves using the force of water created by a head of water (artificial dam or natural waterfall) to drive a turbine connected to an electricity generator. some hydroelectric dams are equipped with a pumped-storage plant and therefore must have an upper and lower storage reservoir (observ, 2013). hydroelectric installations are classified first according to their nominal power (naudet et reusso, sans date de pub): • micro-hydropower: power <100 kw; • mini-hydropower: power between 100 kw and 2 mw; • small hydropower: power between 2 mw and 10 mw; • large hydropower: power exceeding 10 mw. 2.1.3.3. electricity production from biomass the biomass sector breaks down into four categories: solid biomass (wood, wood waste, bagasse, farming waste and animal rahmane and bentafat: reality and prospect of electricity production from renewable energies in arab countries: analytical study (1990–2017) international journal of energy economics and policy | vol 8 • issue 6 • 2018 41 manure), biogas (from landfills, sewage treatment plants or industrial or farm anaerobic digesters), solid renewable municipal waste and liquid biomass (bioethanol, biodiesel, vegetable oil, etc.). liquid biomass is mainly used as automobile carburation and only marginally for producing electricity (observ, 2013). 2.1.3.4. electricity production from solar sources two quite distinct technologies are used to produce solar power. pv module technology uses one of the properties of (generally silicon) semi-conductors that generates electrical current when it comes into contact with light. the second technology is solar thermal plant (or concentrated solar power plant) technology that concentrates the sun’s rays using mirrors on a focal point to obtain very high temperatures (400–1000°c) to produce water vapour and thus electricity. these concentrating solar power (csp) plants can operate with another energy source (generally natural gas), in which case they are known as hybrid plants. they can also be equipped with storage systems, to continue producing electricity after sundown or in the temporary absence of sunlight during the day (observ, 2013). 2.1.3.5. electricity production from geothermal sources geothermal electricity production entails converting the heat of high-temperature aquifers (150–350°c) using ac turbo generators. if the groundwater temperature is 100–150°c, electricity can be produced by using binary cycle technology, in which case an exchanger transmits the groundwater heat to a fluid (isobutane, isopentane or ammonia) that flashes to a vapour at a lower temperature than that of the water. geothermal power is generally harnessed in volcanic zones and tectonic activity zones (observ, 2013). 2.2. current renewable energy status in arab region 2.2.1. renewable energy potencial in arab region the energy mix in arab region is heavily dependent on fossil fuels. this is especially true for the energy exporting countries, with very low penetration of renewable energy sources. on the contrary, renewables are mostly developed in energy importing countries. historically, hydropower has been the most dominant source. the region is well suited for the development of renewable energy technologies for different applications. as far as solar energy technologies are concerned, most of the countries lie in the socalled sunbelt, with global horizontal irradiance values ranging from 1,600 kwh/m²/y in coastal areas of the mediterranean to 2600 kwh/m²/y in the desert, and direct normal irradiance varying from 1800 kwh/m²/y to more than 2800 kwh/m²/y. this is one of the best areas of the world in terms of solar energy, both for pv and csp applications. the potential for wind is also very high in several countries of the mediterranean, such as morocco, egypt, with more moderate, but still interesting, potential in gcc countries and iraq. other sources, such as biomass or geothermal power, hide a huge potential, but they still remain underexplored (middle east and north africa regional architecture, july 2017). 2.2.2. installed capacity and electricity production from renewables in arab region since 2014, an impressive scale-up of renewable installed capacity has been observed in many arab countries. the total installed capacity of all renewables (including hydro) reached around 14 gw in 2015. excluding hydro, the total installed capacity in 2015 amounted to about 3.0 gw a 150% increase when compared to 2012 where the installed capacity was 1.2 gw excluding hydropower (irena, 2016). in 2016, the renewable energy in the region accounted for 6% of total energy generation, approximately 14gw. mostly, it is in the form of hydropower (4.7%), solar power (0.4%) and wind energy (0.9%) (alevizos, 2017). in 2017, the installed capacity of renewables reached around 15 gw, it is in the form of hydropower (68%), wind energy (14%) and solar power (14%). the rest were for other renewables. in general, the installed capacity of renewables has experienced constant increases during the period 2000–2017 (figures 1 and 2). in detail, morocco continues to lead the region in terms of total installed renewable generation capacity (excluding hydropower). as a result of its long-term efforts and successes in implementing its renewable energy action plan, morocco has increased its share of solar from 35 mw in 2014 to 198 mw in 2015, and wind from 290 mw in 2012 to around 790 mw in 2016. egypt also secured its leading position for the region in wind energy, by commissioning the new 200 mw gulf of el-zayt project on the red sea coast. the total solar pv installed capacity table 1: advantages and disadvantages of primary energies for electricity generation characteristics coal natural gas (combined cycle) nuclear renewable energies size big average very big very small (solar pv) average (ferme wind) big (hydraulic) benefit of the scale factor yes no yes no investment cost big average very big very big for hydraulic average for others length of administrative procedure long long long long construction time average short long short, long for hydraulic operating and maintenance costs average weak average high (low for hydraulics) fuel cost average big weak nil (wind, hydro, solar) big (biomass) production of co2 grande average nil nil security of supply good average good good acceptability by the public bad bad bad bad geopolitical risks nil average nil nil source: furfari, 2012 rahmane and bentafat: reality and prospect of electricity production from renewable energies in arab countries: analytical study (1990–2017) international journal of energy economics and policy | vol 8 • issue 6 • 201842 in egypt reached around 90 mw, predominantly due to the pv rural electrification programme, supported by the uae, and the feed-in tariff (fit) small-scale programme. the uae maintains a prominent regional position in solar installations with a combined 133 mw of operational csp and pv capacities. almost all other arab countries have distributed and utility-scale pv installations. jordan has made a substantial leap, with wind and pv projects growing tenfold since 2014, to reach a total capacity of 216 mw (irena, 2016). however, the most remarkable case is that of sudan. the reason why is that the total installed capacity amounts for 50% of renewable energy share, due to the large hydro capacity, reaching 1.5 gw. nevertheless, there is a sad fact about the renewable capacity in the region. there are many countries, like qatar, kuwait, bahrain and saudi arabia, which have not installed renewable capacity yet. although they may find a huge advantage in these sources, they prefer not to do so, having them unused. as of total power capacity, the renewable capacity ranges between 0.05% and 0.6% in these countries. these arab states do have a strong renewable potential, but they prefer to rely on the fossil fuels or the oil much more than installing the necessary capacity. however, the whole region decided to make this shift and, in the next years, it will experience a huge difference in the energy sector (alevizos, 2017). figure 2: renewable energy technologies in arab region in 2017 source: irena (2018). available from: http://resourceirena.irena.org/gateway/dashboard/?topic=4&subtopic=16. (last retrieved on 2018 july 16). figure 1: installed capacity of renewable energy in the arab region 2000–2017 source: irena (2018). available from: http://resourceirena.irena.org/gateway/dashboard/?topic=4&subtopic=16. (last retrieved on 2018 july 16). rahmane and bentafat: reality and prospect of electricity production from renewable energies in arab countries: analytical study (1990–2017) international journal of energy economics and policy | vol 8 • issue 6 • 2018 43 it is noted in figure 3 that morocco has a competitive advantage in producing electricity from renewables. in general, its electricity production is based on coal as a raw material, followed by wind, and hydroelectric power. the curve shows that tunisia surpassed egypt in generating electricity from renewables in the last 2 years, after the two countries were in strong competition in the first 20 years studied (1990–2010). moreover, the effort of the southern sudan and sudan in producing electricity from renewables can be considered. it is also necessary to mention the delay of some arab countries in the production of electricity through renewables -if not a complete lack of productionsuch as yemen, qatar, oman, libya, kuwait and bahrain. 2.2.3. national renewable energy actions the primary objective in harnessing the renewable energy potential in the region is to meet the increasing demand for energy and water from growing populations. renewables can supply secure, clean energy, providing an efficient solution to climate change by abating harmful greenhouse gas emissions. policy makers and power producers are increasingly eager to invest in renewable energy in arab countries, and a number of high-profile projects and targets have been launched in the region. in general, targets are set at a national level. there is a variety among the region as far as the investment in renewable energy is concerned. there are different plans depending of the deployment year. other countries in the arab region have set targets for 2020 (mid-term goals), while others have set targets for 2030 (long-term goals). in many arab countries, goals have been set in order to meet the domestic demand. the shift towards renewables is based on the most efficient types of this, which is wind and solar energy. arab countries focus on these, because they are the most mature and can give tremendous results. however, countries in the region will increasingly start to look at other types of renewables, such as wasteto-waste energy plants or geothermal power. with the necessary technology, waste-to-waste plants help minimize the negative side of waste, and generate this into electricity (alevizos, 2017). these targets can be summuriezed in the table 2. an important milestone for the deployment of renewable energy in the arab region was the adoption of the “pan-arab strategy for the development of renewable energy 2010–2030.” adopted under the las umbrella at the third arab economic and social development summit in 2013, the strategy sets long-term targets for electricity production from renewables. to reach those targets, the region must scale-up renewable energy development substantially. in addition to electricity, the strategy also sets out regional aims to scale up renewables for heating and cooling, transportation, desalination and rural electrification (irena, 2016). as net energy importers and exporters operate under different circumstances, progress has been uncertain. to support renewable energy, states such as jordan and egypt have introduced fit, tax abatements and power-purchase agreements (ppa). at the same time, however, energy exporter nations (with the exception of the uae) have done little to supplement renewable energy, and continue to count on conventional sources with lower extraction costs to meet the growing demand for electricity. however, the situation appears to be about to change: saudi arabia, in particular, finally seems ready to call tenders for wind and solar panel farms over the coming year. a fall in the cost of technology has enabled some countries to move towards increasingly competitive renewable energy cost-wise. in the meantime, government support source: the world bank, iea statistics© oecd/iea. available from: https://www.iea.org/t&c/termsandconditions/. (last retrieved on 2018 july 20). figure 3: electricity production from renewables excludining hydropower table 2: renewable energy targets by country mw country r.e wind pv csp other total (%) target mw algeria 5.000 13.600 2.000 1.400 22.000 (27) 2030 egypt 7.200 2.300 9.500 (20) 2022 jordan 800 1.000 50 1.850 (10) 2020 morroco 4.200 4.560 1.330 10.090 (52) 2030 tunisia 1.500 1.900 300 3.700 (30) 2030 uae-ad 1.500 1.500 (7) 2020 uae-dubai 5.000 5.000 (25) 2030 ksa 9.500 9.500 (10) 2023 kuwait 4.500 4.500 (15) 2030 source: (apicorp energy research, may 2018). csp: concentrating solar power rahmane and bentafat: reality and prospect of electricity production from renewable energies in arab countries: analytical study (1990–2017) international journal of energy economics and policy | vol 8 • issue 6 • 201844 (as in other parts of the world) will become a fundamental tool to develop the renewable sector in the area (strocchia 2017). to sum uo, tow crucial factors support the transition to renewables in generating electricity, eventhough in slow steps, which are (strocchia, 2017). 2.3. the continual fall in costs in the final analysis, renewable energy will be successful, if costs are competitive. the iea estimated a 30% decrease in the average, global costs for onshore wind energy, whereas pv solar costs slumped 70% between 2010 and 2015. the agency expects a further fall in pv and wind costs of 25% and 15%, respectively, by 2021. these cost savings are mainly a result of technological developments and of the economies of scale due to increased production in asia. constant investments and additional capacities will also result in further cost reductions. nevertheless, other export countries are finding difficulties in starting up their programmes. large oil and gas reserves and contained extraction costs have ensured the demand for hydrocarbons continues to grow in countries such as kuwait, qatar and algeria. this slow progress is due mainly to the uncertainty of their policies and lack of an efficient, legislative framework. kuwait’s declared objective is to achieve 5% of renewable energy by 2020, but it only has the 50 mw csp installation in al-shagaya currently in the pipeline. masdar will construct a 50 mw wind farm in harweel, oman. at the same time, the government has put forward proposals to develop 200 mw of pv energy. other countries, such as qater and bahrain, have made minor investments in renewable energy, but nothing significant is envisaged for the near future. a short time ago, the algerian government announced it wanted to develop approximately 4 gw of pv energy as part of an ambitious programme, which envisages developing 22 gw of renewable energy by 2030. 2.4. new policies to support the development of renewable energy as the nations gradually accelerate their development in the renewable sector, legislation is improving significantly. jordan was the first country to introduce fit in 2012. egypt also has an fit programme, which appears rather muddled at present. it is still too soon to understand the reaction of potential investors and whether they will be able to ensure an adequate return on investments. morocco has no fit policies, even though it launched a similar programme called energipro in 2006. the latter envisaged the opportunity for industrial consumers to invest in renewable energies, whereas the state-owned utility guaranteed it would purchase any surplus power at favourable tariffs. other economic support mechanisms in the region included tax relief, net metering and capital grants. legislation, on the other hand, envisages standards for renewable energy and national objectives. however, the main incentives for private promotors will continue to be the government-backed, long-term, ppa contracts. the latter, together with the competitive prices in the area, will be the main spur. 3. data and research method this study relied upon the analytical descriptive method, where the evolution of electricity production from renewable energies in some arab countries have been described to know the most important renewable source used in these countries. moreover, the analytical method can be explained in using the method of principal component analysis (pca) to analyze and compile the variables of the considered countries that are homogeneous in terms of some studied characteristics. these characteristics are electricity production, electricity production from renewable energies, electricity consumption, gross domestic product (gdp), co2 emissions. this method of analysis helps to draw a parameter to bring down the best image of the homogeneous countries’ grouping in terms of characteristics, and to shorten them into two properties which are the axes of this parameter (table 3). this study relied on the iea data, where the agency provides the information required in it, especially those relating to the production of electricity from renewables in each arab country. it should be noted that the agency does not provide information about djibouti even though this country is considered as an arab one since it has been recently approved by the league of arab table 3: electricity production from renewables in some arab countries in 2015 country country code elc production in 2015 from re in 2015 elc consumption in 2015 gdp (current us) million 2016 co2 emissions* in 2015 algeria dza 68.798 203 50.153 159.049 3.29 saudi arabia sau 338.336 1 292.765 646.438 16.85 bahrain bhr 28.484 0 27.814 32.179 21.83 egypt egy 181.977 15.030 154.205 332.791 2.17 uae are 127.366 296 111.076 348.743 19.68 iraq irq 68.922 2.572 35.585 171.489 3.63 jordan jor 19.014 176 16.127 38.655 3.13 kuwait kwt 67.918 0 43.296 110.876 21.93 lebanon lbn 18.396 479 16.603 49.599 3.88 morocco mar 31.216 6.102 29.939 103.606 1.60 oman omn 32.758 0 28.912 66.293 14.32 qatar qat 41.499 0 36.378 152.452 35.77 sudan sdn 13.047 8.420 10.580 95.584 0.38 tunisia tun 19.676 772 15.437 42.063 2.28 yemen yem 5.326 0 3.114 27.318 0.42 *co2 emissions from fuel combustion only. emissions are calculated using iea’s energy balances and the 2006 ipcc guidelines. source: iea statistics © oecd/iea (2018). available from: https://www.iea.org/t&c/termsandconditions/. (last retrieved on 2018 july 20). gdp: gross domestic product https://www.iea.org/t&c/termsandconditions/ rahmane and bentafat: reality and prospect of electricity production from renewable energies in arab countries: analytical study (1990–2017) international journal of energy economics and policy | vol 8 • issue 6 • 2018 45 states. also, the absence of libya in the analysis due to the lack of statistics on its gdp for the year 2016 from the world bank website as well as syria and the southern sudan. 4. results and discussion 4.1. factorial analysis method data analysis methods can be used for previous information after using the method of factorial analysis to find the level at which we project the picture that summarizes, in the best way, the real situation of any body, that is, less distorted. we can use the method of pca which aims to group items with similar characteristics. following the introduction of these data into the relevant data analysis program xlstat2018, we have been able to obtain the information set out successively as follows: 4.2. correlation matrix between variables through the correlation matrix in table 4, we can deduce some of the correlation coefficients between the studied characteristics. the matrix is diagonal symmetrical with the value “1.” the matrix also resolves many correlation coefficients between the considered elements (characteristics) where values, whether positive or negative, that approach to “zero, 0” can be ignored. the following conclusions can, therefore, be drawn: • there is a positive and very strong correlation (0.995) between the consumption and production of electricity in the studied arab countries, which means that the increase in electricity consumption is pushing the production for more increase to achieve self-sufficiency. • there is a very strong correlation (0.976) between the gdp and the production of electricity in the considered countries. this means that the increase in electricity production is contributing to an increase in gdp, which is very logical. • there is a weak and negative relationship (−0.420) between the production of electricity from renewables and co2 emissions per capita in the considered arab countries, which means that the increase in the production of electricity from renewables reduces co2 emissions for the arab individual, and this is also very logical. 4.3. projection of elements the corresponding figure outlines the projection of elements on the level, and as noted, the cloud of elements has given projections close to the perimeter of the circuit (mathematically [cos a]2), which means that the points are well represented and the quality of the representation is acceptable and has high quality. it also shows that the f1 factor contributes significantly to the representation of countries while the second factor f2 contributes less, and the table in the appendix shows the largest squared of (cos a)2 located in f1, f2, respectively(figure 4). 4.4. projection of variables (countries) we can watch the spread of the cloud points of the considered countries at the level of the generator of two rays f1, f2 and deduce some observations about the studied characteristics. from the figure 5, we can conclude that the studied countries were divided, according to the calculated, data into four major groups, table 4: correlation matrix correlation elc production from re elc consumption gdp co2 elc production 1.000 0.164 0.995 0.976 0.199 from re 0.164 1.000 0.165 0.165 −0.420 elc consumption 0.995 0.165 1.000 0.973 0.210 gdp 0.976 0.165 0.973 1.000 0.228 co2 0.199 −0.420 0.210 0.228 1.000 source: spss v 17 programme outputs, gdp: gross domestic product figure 4: the projection of the studied elements which are electricity production, electricity production from renewable energy, electricity consumption, gross domestic product, and co2 emissions per capita source: spss v17 programme output source: xlstat2018 programme output figure 5: projection of studied arab countries based on the five characteristics studied rahmane and bentafat: reality and prospect of electricity production from renewable energies in arab countries: analytical study (1990–2017) international journal of energy economics and policy | vol 8 • issue 6 • 201846 which took into account the proximity of the projection to f1 axis as it is the most representative. it produces by classification method pca homogeneous core groups in terms of studied characteristics generally which are as follows: • group 1: it is morocco and sudan where there is considerable similarity in terms of characteristics with significant production of electricity from renewables, small amount of co2 emissions per capita in these two countries, and an average gdp. • group 2: qatar, kuwait and bahrain, which are homogeneous in terms of their considered characteristics. they have no electricity production from renewables (production of electricity relies mainly on gas, coal and other depleted sources of energy), large amount of co2 emissions per capita of these countries, and a considered gdp. • group 3: saudi arabia, the united arab emirates is characterized by almost zero electricity production of renewables, large amount of co2 emissions per capita, and an average gdp. • abnormal element: egypt is characterized by a large production of electricity from renewables, very small amount of co2 emissions per capita, and an average gdp. • group 4: other arab countries studied and not previously mentioned are characterized by inconsistencies between the considered characteristics: algeria, iraq, jordan, lebanon, oman, tunisia and yemen. 5. conclusion electricity production in all arab countries is still dependent on fossil fuels, but in recent years there has been a global trend to produce electricity from renewable sources, especially with increasing demand, and the climate change problem with its negative effects. through this study we have found that the arab countries are endowed with great potential of renewable energies, that will enable them to lead the world in the production of electricity if this potential is best exploited. the main results of this study can be summuriezed as follows: • the dependence of many arab countries in electricity production from renewables on hydropower (68%) because many of them have sea views, such as that of north african arab countries in the mediterranean, followed by their dependence on both wind and solar energy in roughly equal proportions estimated at around 14%. • morocco has a competitive advantage in the production of electricity from renewables. its electricity production is generally based on coal as a raw material, but it has recently used a second source which is solar energy. many arab countries, which aspire to improve their electricity production from renewables such as tunisia, egypt, sudan, south sudan, algeria and the uae, cannot be ignored. • the use of renewable energies for electricity production is still very low in some arab countries such as saudi arabia, bahrain and kuwait despite their potential; as a result of their heavy dependence on fossil fuels, especially oil. • the continual fall in costs of renewable energies and the policies made in each arab conutry -according to their nature exporting or importing countrieswill help to facilitate the shift towards electricity production from renewables in the arab region. • the arab region has adopted an ambitious strategy -”panarab strategy for the development of renewable energy 2010–2030” to develop electricity production from renewable sources, setting targets to 2030. • from the analytical study we find that there is a positive and very strong correlation (0.995) between the consumption and production of electricity in the studied arab countries; in addition, there is a weak and negative relationship (−0.420) between the production of electricity from renewables and co2 emissions per capita in the considered arab countries and this is very logical. in the light of these results, some policies could be proposed to improve the use of renewable energies for electricity production in arab countries, which could be listed as follows: • encouraging investment in solar energy, as a large number of arab countries contain deserts, that can be used to establish power plants to attract sunlight such as saudi arabia, algeria, morocco, libya, jordan and other arab countries that have unexploited deserts. in parallel, this can be done through the promotion of patents in this regard, the promotion of scientific research as well as the establishment of research centres and institutes. • the creation of an “arab council for cooperation on renewable energies” and urging it to revitalize the spirit of cooperation among arab countries, and to benefit from the experiences in the production of electricity from renewables since there is currently no special apparatus for such stimulation, except for the registration of some initiatives in the field of renewable energies by the “gcc” as accidental and non-essential. • encouraging arab countries in north africa, in particular, to produce electricity from hydraulic and solar sources, and encouraging them to export such electricity to nearby countries. • enhance all arab countries to adopte renewable energies in the production of electricity in order to reduce co2 emissions, which is considered to be very toxic and which is resulting many environmental and health disadvantages on the arab individual. references alevizos, h. (2017), renewable sources of energy: the pan-arab prospect. (working paper 6). greece: energy and environmental policy laboratory, university of piraeus. apicorp energy research. (2018), renewables in the arab world: maintaining momentum. 3(8). available from: http://www.apicorphttp://www.apicorp-arabia.com/research/energyreseach/2018/ apicorp_energy_research_v03_n08_2018.pdf. [last accessed on 2018 jul 20]. bonal, j., rossetti, p. (2011), energies alternatives. 2nd éd. paris, france: omniscience. furfari, s. (2012), politique et géopolitique de l’énergie. paris, france: technip. irena. (2016), renewable energy in the arab region. overview of developments. abu dhabi, uae: international renewable energy agency. irena. (2018). available from: http://www.resourceirena.irena.org/ rahmane and bentafat: reality and prospect of electricity production from renewable energies in arab countries: analytical study (1990–2017) international journal of energy economics and policy | vol 8 • issue 6 • 2018 47 gateway/dashboard/?topic=4&subtopic=16. [last accessed on 2018 jul 16]. mathis, p. (2011), les energies, comprendre les enjeux. paris, france: quae. middle east and north africa regional architecture. (2017), how can renewable energy help contribute to the development of the mena countries? middle east and north africa regional architecture,  6, 3. naudet, g., paul,r.p. (2008), énergie, électricité et nucléaire. france: edp sciences. p127-132. observ, er. (2013), worldwide electricity production from renewable energy sources. 15th ed. paris, france: inventory. strocchia, g. (2017), arab world steps up renewable energy. available from: https://www.aboutenergy.com/en_it/topics/arab-world.shtml. [last accessed on 2018 jul 18]. the world bank, iea. (2018). available from: https://www.iea.org/t&c/ termsandconditions. [last accessed on 2018 jul 20]. yassaa, n. (2018), ce qui a marqué les activités du cder en 2017. portail algérien des energies renouvelables. available from: https://www.portail.cder.dz/spip.php?article6288. [last accessed on 2018 jul 23]. appendices of both xlstat 2018 and spss v17 programmes factor/variables productionelc fromre consumption elc gdp co2/missing listwise/analysis productionelc fromre consumption elc gdp co2/print univariate initial correlation extraction fscore/format sort blank (10)/plot eigen rotation/criteria mineigen(1) iterate(25)/extraction pc/rotation norotate/save reg (all)/method=correlation. factor analysis component matrixa variables component 1 2 elc consumption 0.992 elc production 0.992 gdp 0.987 from re 0.183 0.856 co2 0.270 −0.827 gdp: gross domestic product. source: xlstat2018 programme outputs. extraction method: principal component analysis. a2 components extracted scree plot squared cosines of the variables variables f1 f2 f3 f4 f5 elc production 0.984 0.001 0.008 0.004 0.002 from re 0.034 0.733 0.233 0.000 0.000 elc consumption 0.985 0.001 0.006 0.007 0.002 gdp 0.975 0.000 0.003 0.022 0.000 co2 0.073 0.683 0.244 0.000 0.000 source: xlstat2018 programme outputs. values in bold correspond for each variable to the factor for which the squared cosine is the largest factor scores studied arab countries f1 f2 f3 f4 f5 dza −0.225 0.092 −0.778 0.086 0.044 sau 5.337 −0.661 −0.913 −0.097 −0.029 bhr −0.840 −1.195 0.587 −0.300 −0.029 egy 2.292 2.780 1.161 −0.193 0.021 are 1.540 −0.930 0.062 0.381 −0.061 irq −0.229 0.472 −0.352 0.228 0.179 jor −1.242 0.066 −0.608 −0.106 −0.028 kwt −0.182 −1.181 0.472 −0.161 0.139 lbn −1.186 0.069 −0.513 −0.054 −0.041 mar −0.702 1.194 0.188 0.070 −0.066 omn −0.795 −0.695 0.059 −0.132 −0.024 qat −0.063 −2.103 1.428 0.162 −0.022 sdn −0.961 1.661 0.546 0.219 −0.039 tun −1.229 0.225 −0.569 −0.087 −0.018 yem −1.517 0.207 −0.772 −0.018 −0.026 source: xlstat2018 programme outputs appendices . international journal of energy economics and policy | vol 9 • issue 4 • 2019 91 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(4), 91-96. empirical scenarios for emission control and economic sustainability of energy input and intervention of agricultural pesticides ahmad qosim1*, anies anies2, henna rya sunoko3 1doctoral program of environmental science, school of postgraduate studies, universitas diponegoro, semarang, indonesia, 2faculty of medicine, universitas diponegoro, semarang, indonesia, 3department of environmental science, school of postgraduate studies, universitas diponegoro, semarang, indonesia. *email:ahmadqosim.pdil.undip@gmail.com received: 14 february 2019 accepted: 11 may 2019 doi: https://doi.org/10.32479/ijeep.7687 abstract the application of pesticides have been out of control, therefore, it is damaging environment due to emissions of vary substances and gases, e.g., co2, so2, po4, and summer smog. this negative impact alone is also going to affect the paddy production. a comprehensive measure must be taken in order to create a sustainable development in agricultural sectors. control on pesticides is one of the best practices to be proposed. this study used a quantitative methodology with a life cycle assessment (lca) approach to test empirically the use of pesticides and to propose various scenarios in the effort of modification of environmentally friendly and low emission agriculture, which includes aspects of greenhouse, acidification, eutrophication, spm smog. by using lca with quantitative measurement using simapro 7, the findings show that ratio of emission rate of the existing condition to the proposed model proved a 34.5% decrease in co2 equivalent (136.4 kg) and 41.6% decrease in so2. as the environmental risks decreases, it is expected that the sustainable agricultural development of paddy commodity can be materialised. some recommendations are given by the researc findings, i.e., distribution system according to the proposed model, recording, monitoring, and legal enforcement towards the sustainable development. keywords: paddy, pesticide control, agricultural sustainability, emission jel classifications:  k32, o13, p18 1. introduction food agricultural organization defines agriculture as a human activity of making use, or exploiting, biological resources to produce cultivated land, industrial raw materials, or energy sources, which also involves environmental management (poisot et al., 2004). rimando (2004. p. 1) defines agriculture as an act of systematically growing plants and cattles/poultries under the management of human. abellanosa and pava (1987. p. 238) furthermore add that such activity is performed to fulfill the human needs. agriculture according to rubenstein (2003: 496) stands for a massive effort to change part of earth surface by way of plant and animal cultivation to fulfill nutrition of food and drink and economic benefit. plant and animal agriculture are some of important knowledge in growing the plants and animal husbandry to fulfill the dietary and other needs and to pursue the economic benefit (bareja, 2017). agriculture is considered as sustainable if it is managed by an ecological concept, a study of correlation between organisms and their environment. sustainable agriculture focuses on economic sustainability by efficient use of energy, minimum ecological footprint, efficient product or commodity packing, widespread local purchase, simple or immediate food supply chain, less processed foods, more community and household gardens, to mention some (kunstler, 2012; mckibben, 2013; palanichamy et al., 2017; zhu et al., 2014). this journal is licensed under a creative commons attribution 4.0 international license qosim, et al.: empirical scenarios of emission control and economic sustainability for energy input and intervention of agricultural pesticides international journal of energy economics and policy | vol 9 • issue 4 • 201992 according to epa, pesticide is substance or organism used for vanquishing, paralysing, modifying, preventing growth and exiling pests. pesticide can be made of either natural or synthetical chemical substance, the combination of the two, or living organisms that act as biological control agents. pesticide used in agriculture is specifically dubbed as crop protection products. this is to differ from the similar products applied to other areas (djojosumarto, 2008). the rapid development of agricultural technology has produced extensive results through the provision and diversity of food sources. on the other hand, agricultural technology cannot be separated from the use of chemical drugs in the form of pesticides. however, the use of pesticides is considered to harm the environment and degrade soil quality in continuous use. with the high dose and frequency of pesticide use, the burden of pesticide contamination on water quality, and soil fertility becomes increasingly high. such changes occurring in soil, water, and air also have potential dangers to living organisms essential to the soil fertility and sustainability of the environment. this is a concern, because the excessive use of pesticides in the medium and long term will cause a burden on environmental degradation, increased emissions, and greenhouse effect (balogh and jámbor, 2017; smagulova et al., 2017). in indonesia, the use of pesticides is very widespread and threatening, including in producing paddy (oryza sativa) as the main staple food source. likewise, paddy is the major food for local community in pati regency, central java province, republic indonesia. therefore, its growth rate has become prominent. efforts to improve paddy productivity by local farmers, however, have tended to depend on pesticides. hence, this study aims to test empirically the use of pesticides and to propose various scenarios in the effort of modification of environmentally friendly and low emission agriculture, which includes aspects of greenhouse, acidification, eutrophication, spm smog, with the research object of paddy field in pati regency, one of the largest rice producing regions in indonesia. this study applied a life cycle assessment (lca) approach to better provide a systematic, factual, and accurate explanation of facts, characteristics, and correlation between phenomena. moreover, by using the lca approach to the sustainable paddy agriculture in pati regency, the distribution model can further be elaborated by involving local government, the surveillance commission on fertiliser and pesticide, and all stakeholders in supervising and controlling the use of pesticide as well as recording, monitoring, and legal enforcement towards the sustainable development. 2. literature review pesticides have become a common term in reference to substances used for exterminating, controlling, exiling, and decreasing crop germs (margni et al., 2002). according to the general guide for pesticide assessment, pesticides contain chemical substances and compounds, tiny organisms, viruses, and other substances, which can be used to protect crops or plants as well as their parts and components. pesticides used for agricultural activities have been specifically referred as products that protect the crops (crop protection products), as they may be separate from the similar products used for other activities (djojosumarto, 2008; soenandar et al., 2010). sudarmo (1991. p. 19-20) mentions vary kinds of pesticide according to their functions and word origins, as follows: (a) akarisida (from latin arka); (b) algicide (from latin alga); (c) avicide (from latin avis); (d) bacteriside (from greek bacterium); (e) fungicide (from greek fungus); (f) herbicide (from latin herba); (g) insecticide (from latin insectum); (h) larvicide (from greek lar); (i) mulluksicide (from greek mulluscus); (j) nematicide (from latin nema); (k) ovicide (from latin ovum); (l) peduculicide (from latin pedis); (m) piscicide (from greek piscis); (n) rodentcide (from greek rodera); (o) predicide (from greek praeda); (p) silvicide (from latin silva); and (q) termicide (from greek termes). uncontrolled application of pesticides can contaminate soil, killing organisms that previously are not the main targets (joko et al., 2017; ramwell et al., 2002). eco-efficiency is an effort to create and added value by performing better practices to fulfill the customers’ need while maintaining, or decreasing, environmental impacts (desimone and popoff, 2000. p. 2-3; kurniawan, 2017). eco-efficiency may be defined as a strategy, which bears in a particular product with a better performance by using efficient energy and natural resources. it is a combination between economic and ecological efficiencies under the principle of “doing more with less”, i.e., producing more goods and services by consuming more efficient energy and natural resources (environment australia, 1999). pati regency, central java province, is a region with huge potential of agriculture, in particular paddy. of the total 150, 360-hectare area, 58,448 hectares are rice fields with technical irrigation. pesticides become the main weapon to control and prevent the pests. as the application has become more widespread, alert must be taken into account for the environmental impacts. pesticides have become prominent method that entails economic value in order to improve agricultural product output and quality nowadays. they are believed to have a significant role in controlling pests (jin et al., 2010). the distribution chain of the pesticides from transportation to storage to application process becomes a series of actiivity that give impact on human health, flora and fauna, agricultural crops, and environmental risk. there must be any effort to minimise these impacts by a model design to guarantee the sustainability of the paddy crops. the model proposed here was approached by the lca. the followings are the previous studies concerning pesticides in agriculture. van hoi et al. (2013) reports the failure of vietnam authority to regulate the pesticide trade. jacquet et al. (2011) and skevas et al. (2013) discuss tax scheme and economic incentives; and pranetvatakul et al. (2011) reveals a grow of 10% of the pesticide use with high external cost in thailand. further study by fan et al. (2015) finds that farmers knowledge correlates with the application of pesticide and policy implication. al zadjali et al. (2013) reports that extension and education of the farmers awareness are important in the pesticide application in oman. likewise, widayati and yusuf (2017) assess the effect of use of pesticide in dieng plateau, central java on the public health, social and economic performance. phung et al. (2012) finds comprehensive risk and benefit of the evaluation of the pesticide registration and management. juraske et al. (2009) discuss the pesticide application on fruits and vegetables. whereas, dijkman et al. (2012) compares the pesticide impacts. the similar qosim, et al.: empirical scenarios of emission control and economic sustainability for energy input and intervention of agricultural pesticides international journal of energy economics and policy | vol 9 • issue 4 • 2019 93 conditions also occur in indonesia, in which government has not effectively executed the surveillance of the overgrowth of the pesticide application. the swot analysis resulted on strategies of the pesticide distribution model for paddy agriculture towards sustainable environment in pati regency, as follows. the first is improved capacity of the surveillance commission on fertiliser and pesticide for the pesticide management to increase rice production. second is improved human resource and number of the extension staff for the pest surveillance at early stages with appropriate pesticide application. third is improved performance of the surveillance commission on fertiliser and pesticide and more advanced technology to increase paddy production. fourth is law enforcement of the ppns performance to decrease the potential environment pollution across the agricultural area. fifth is training for farmers in using the environmental-friendly pesticide practice, cultivation system, and ability to analyse the pest at early stage. sixth is decreased dependence on pesticide use and focused on technological advance with an integrated pest control. seventh is periodical monitoring and evaluation from juridical, technical, and human aspects in line with environmental management to eliminate the pollution. lastly, it is needed the improved technological use in agriculture by a clear and environmental-friendly policy. the major objective of the lca approach is to identify, compare, and evaluate the environmental components through a scenario to be developed to obtain the ultimate scenario de backer et al. (2009). the function unit of the research is according to the range of the research location, i.e., per hectare area with the pesticide emulsion volume of 16 l. 3. methodology this study applied a lca approach with an analytical descriptive method (tien et al., 2007; ingwersen et al., 2012). it aimed at providing a systematic, factual, and accurate illustration of facts, characteristics, and correlation between phenomena to be studied (panichelli et al., 2009). a descriptive method was performed by a quantitative analysis, focusing on research samples obtained from the following villages: srikaton, sukorukun, sriwedari, ngurensiti, bumiayu, dukuhseti, and kembang. 4. results in relation to life cycle inventory, the spraying activity shall give impact on human as the one who performs it. even the impact has already spread over the distribution phase. pesticide results in co2, so2, eutrophication, carsinogenic, and summer smog. a 3-tonne capacity box truck with diesel engine travels at the distance of 212 km, consuming 60-67 kg fuels. to transport the pesticides for a single hectare area, 3-kg pesticides have a ratio of the diesel fuel use of 0.06 kg. the flow diagram already applied to the epa since 2006 is as follow (figure 1). the distribution flow of the pesticides in pati during this study was sampled from the producers that took the headquarters in gresik regency, east java province. the pesticide mixture and spraying process by 78 farmers as the respondents revealed that all of them did not we are protecting gloves and masks. they typically mixed three different pesticides (1 liquid pesticide; 2 powder pesticides) into the sprayer with a dose for 16 l. there were two different volumes of mixing containers used by the farmers to mix the pesticides: 58% of the farmers used 5-l containers and 42% of them used 12-l containers. they used wooden sticks to mix the pesticides without wearing any protection. the pesticides applied to the paddy crops in the morning during the rainy season and in the afternoon during sunny days. most of the respondents (82%) did not wear footwear and most of them (65%) wear casual (not special-purpose) clothes. all the respondents (100%) did not goals : sustainable model of pesticide distribution among farmers in pati regency inventory: distance, energy consumption, transportation mode, fuel consumption, pesticide use, etc. impact : environment (soil, water, air, �ora and fauna), co emission, public health. interpretational evaluation: energy input and intervention of pesticide use showing a total emission and regulation. recommendation : pesticide distribution model by considering emission and regulation, as well as intervention of behaviors towards distribution eco -e�ciency. identi�cation issues : environmental pollution, so2, po4, smog, co2 emissions, government roles in controlling the pesticide distribute, farmer behaviors source: united states environmental protection agency, 2006, with modification and adjustment to research figure 1: model diagram of sustainable model of pesticide distribution according to epa 2006. qosim, et al.: empirical scenarios of emission control and economic sustainability for energy input and intervention of agricultural pesticides international journal of energy economics and policy | vol 9 • issue 4 • 201994 non toxic reduce reuserecycle surveillance commission for fertiliser and pesticide and technical o�ces sop/regulation/pesticide release garbage and waste surveillance commission for fertiliser and pesticide elements (env. dept.) surveillance commission for fertiliser and pesticide and all technical o�ces disseminate lea�ets for public information concerning eligible pestic ides in use, how to use and emergency response to its impacts. pesticice trade/distribution and application pesticide kiosks -waste management mou (spj, medivest, etc.) toxicand hazardouswaste paddy farmers m o n ev, in teg rated tech n ical ed u . rep o rtin g marketing online surveillance commission for fertiliser and pesticide (agriculture dept., trade dept.), extension, evaluation, law enforcement, certi�cation. agriculture extension sta� recommend pesticide provision according to pest analysis ppns + police ministry information and communication+ center district, pub. health. ctr. surveillance commission for fertiliser and pesticide elements source: research findings, 2017 figure 2: pesticide distribution model table 1: emission comparison by lca technical scenarios component greenhouse (co2) (in kg) acidification (so2) (in kg) eutrophication (po4) (in kg) spm smog (smog) (in kg) existing 5029.7 32.7 2.05 22.9 scenario 1 5178.07 31.43 2.11 28.41 scenario 2 5209.70 31.93 2.14 28.86 scenario 3 4113.80 25.00 1.68 22.68 source: data proccessed, 2017. lca: life cycle assessment qosim, et al.: empirical scenarios of emission control and economic sustainability for energy input and intervention of agricultural pesticides international journal of energy economics and policy | vol 9 • issue 4 • 2019 95 wear any protection gloves. the packs of the used pesticides were dumped nearby the paddy crops and then burnt after the harvest time. the spraying equipments were cleaned by 4.5-5.5-l water and the washing water were disposed to the rice fields water tract. the simapro 7.0 revealed co2 emission of 6209.7 kg eq., as the main element of greenhouse effect, so2 31.93 kg as the main element of acid rain, eutrophication by nutrition 2.14 kg, smog due to pesticide spraying 28.86 kg with its negative impact on the environment. the health risk on farmers consisted of symptomatic dizzines (24.46% of the respondents), headache (22.05%), fatigue (17.83%), nausea (26.63%), and skin heating (16.63%). the was a strong correlation of the body protectors and dosage of the applied pesticides to the farmers pain complaints. the health risk of the pesticide distribution was estimated having a contribution to low weight birth in pati regency. children exposed by the unused pesticides was also severe due to pure method of storage. three technical scenarios of the lca approach were discovered along the pesticide distribution in pati regency. the following table 1 is the result of the simapro 7.0 analysis. the table 1 explains that the comparison of the co2 emission to the third scenario resulted in the lowest emission (4113.80 kg co2 eq). compared to the first scenario, it was 1064.27 kg co2 eq lower, a 20% decrease. the lowest rate of so2 was found in the second scenario (25.00 kg so2 eq). whereas, the lowest po4 (1.6 kg) and smog were from the third scenario. the third scenario (scenario 3) proposed a model, which had the lowest emission based on swot (strength, weakness, opportunity, and threat) analysis to get the appropriate strategy. the model and strategy to perform the pesticide distribution towards sustainable environment is as illustrated in the following figure (figure 2). using the lca approach to the sustainable paddy agriculture in pati regency, the distribution model can further be elaborated as follows: a. the government of pati regency is present in the governance of the pesticide distribution across the region by strengthening the surveillance commission on fertiliser and pesticide and other related technical offices, e.g., agriculture, health, environment, and food security; b. the surveillance commission on fertiliser and pesticide develops a standard operational procedure (sop) and disseminates information to the public on the eligible pesticides in use, pesticide governance, and pesticide trade and application through technical education, monitoring and evaluation, and coordination of the existing regulations and rules of law; c. all pesticide distribution levels apply the predetermined sop by recording and reporting all pesticide transports and the management of the wastes, including those generated by the farmers; d. the regency office of agriculture, through its pest surveillance and control division and extension staff, performs an integrated guidance to the farmers and recommends the use of particular pesticides in co-ordination with the surveillance commission on fertiliser and pesticide; e. the civil servant ombudsman (known as ppns in indonesian) contributes to the surveillance of the pesticide distribution to prevent any violation. in doing so, ppns may need for additional help from the police department by rules of law. an online surveillance is also necessary; f. the surveillance of the online transaction must be anticipated by co-operation with the department of communication and information nationwide; g. the regency office of environment and forestry continues to monitor the chemical hazards and toxic substances in cooperation with the waste managers for the disposal of pesticide cartoon packs uncontaminated by the pesticides. the “reduce,” “reuse” and “recycle” principles must apply to the chemical hazards and toxic substances; and h. all the activities are compiled to be data and information to be disseminated publicly through brochures and leaflets. any licensed and registered pesticides must be socialized and recommended according to prescribed dose and the timely application. 5. conclusions the role of the pati regency government in the pesticide distribution had not been fulfilling the need for the environmentbased pesticide control and prevention toward agricultural sustainability. the environmental and health risks exposed by the pesticide distribution in pati regency is necessary to be minimised by calculating the risk factors according to the lca. all concerned parties, either public sector, private sectors, business world, or civil societies are expected to work in concert to materialise the paddy agriculture sustainability. the study recommends institutional strengthening and empowerment, in particular the monitoring commission for fertilizers and pesticides, budget allocation and political support, registration of all agricultural product kiosks, human resources development, standard operation procedure development, legal enforcement, technical guidance of all levels, promotion, monitoring and evaluation, and further studies. references abellanosa, a.l., pava, h.m. (1987), introduction to crop science. cmu, musuan, bukidnon: publications office. p23-64. al zadjali, s., morse, s., chenoweth, j., deadman, m. (2013), disposal of pesticide waste from agricultural production in the al-batinah region of northern oman. science of the total environment, 463, 237-242. balogh, j.m., jámbor, a. (2017), determinants of co2 emission: a global evidence. international journal of energy economics and policy, 7(5), 217-226. bareja, b.g. (2017), what is agriculture, definition of agriculture; 2014. available from: http://www.cropsreview.com/what-is-agriculture. html. [last retrieved on 2017 nov 06]. de backer, e., aertsens, j., vergucht, s., steurbaut, w. (2009), assessing the ecological soundness of organic and conventional agriculture by means of life cycle assessment (lca) a case study of leek production. british food journal, 111(10), 1028-1061. desimone, l.d., popoff, f. (2000), eco-efficiency: the business link to sustainable development. cambridge: mit press. dijkman, t.j., birkved, m., hauschild, m.z. (2012), pestlci 2.0: a second generation model for estimating emissions of pesticides qosim, et al.: empirical scenarios of emission control and economic sustainability for energy input and intervention of agricultural pesticides international journal of energy economics and policy | vol 9 • issue 4 • 201996 from arable land in lca. the international journal of life cycle assessment, 17(8), 973-986. djojosumarto, p. (2008), panduan lengkap pestisida and aplikasinya. jakarta: agromedia. environment australia. (1999), profiting from environmental inprovement in bussiness: an ecoeffiency information tool kit for australian industry. canberra: environment australia. fan, l., niu, h., yang, x., qin, w., bento, c.p., ritsema, c.j., geissen, v. (2015), factors affecting farmers’ behaviour in pesticide use: insights from a field study in northern china. science of the total environment, 537, 360-368. ingwersen, w.w., curran, m.a., gonzalez, m.a., hawkins, t.r. (2012), using screening level environmental life cycle assessment to aid decision making: a case study of a college annual report. international journal of sustainability in higher education, 13(1), 6-18. jacquet, f., butault, j.p., guichard, l. (2011), an economic analysis of the possibility of reducing pesticides in french field crops. ecological economics, 70(9), 1638-1648. jin, f., wang, j., shao, h., jin, m. (2010), pesticide use and residue control in china. journal of pesticide science, 35(2), 138-142. joko, t., anggoro, s., sunoko, h.r., rachmawati, s. (2017), pesticides usage in the soil quality degradation potential in wanasari subdistrict, brebes, indonesia. applied and environmental soil science, 2017, 1-7. juraske, r., mutel, c.l., stoessel, f., hellweg, s. (2009), life cycle human toxicity assessment of pesticides: comparing fruit and vegetable diets in switzerland and the united states. chemosphere, 77(7), 939-945. kunstler, j.h. (2012), vertical farming. cgiar research program on climate change, agriculture and food security (ccafs). kurniawan, r. (2017), effect of environmental performance on environmental disclosures of manufacturing, mining and plantation companies listed in indonesia stock exchange. arthatama journal of business management and accounting, 1(1), 6-17. margni, m., rossier, d., crettaz, p., jolliet, o. (2002), life cycle impact assessment of pesticides on human health and ecosystems. agriculture, ecosystems and environment, 93(1-3), 379-392. mckibben, b. (2013), oil and honey: the education of an unlikely activist. new york: macmillan. palanichamy, n., ing, w.k., danquah, m.k., abu-siada, a., sidhu, a.s. (2017), sustainable economic and emission control strategy for deregulated power systems. international journal of energy economics and policy, 7(5), 102-110. panichelli, l., dauriat, a., gnansounou, e. (2009), life cycle assessment of soybean-based biodiesel in argentina for export. the international journal of life cycle assessment, 14(2), 144-159. panuwet, p., siriwong, w., prapamontol, t., ryan, p.b., fiedler, n., robson, m.g., barr, d.b. (2012). agricultural pesticide management in thailand: status and population health risk. environmental science and policy, 17, 72-81. phung, d.t., connell, d., miller, g., rutherford, s., chu, c. (2012), pesticide regulations and farm worker safety: the need to improve pesticide regulations in viet nam. bulletin of the world health organization, 90, 468-473. poisot, a.s., speedy, a., kueneman, e. (2004), good agricultural practices–a working concept. rome, italy: background paper for the fao internal workshop on good agricultural practices. p27-29. ramwell, c.t., heather, a.i.j., shepherd, a.j. (2002), herbicide loss following application to a roadside. pest management science, 58(7), 695-701. rimando, t.j. (2004), crops science 1: fundamentals of crop science. up hosbernes: university publication office. skevas, t., lansink, a.o., stefanou, s.e. (2013), designing the emerging eu pesticide policy: a literature review. njas-wageningen journal of life sciences, 64, 95-103. smagulova, s.а., adil, j., tanzharikova, a., imashev, a. (2017), the economic impact of the energy and agricultural complex on greenhouse gas emissions in kazakhstan. international journal of energy economics and policy, 7(4), 252-259. soenandar, m., raharjo, a., aeni, m.n. (2010), petunjuk praktis membuat pestisida organik. jakarta: agromedia. sudarmo, s. (1991), pestisida. jakarta, indonesia: agromedia pustaka. tien, s.w., chiu, c.c., chung, y.c., tsai, c.h., chang, c.f. (2007), analysis of production process improvement with life cycle assessment technology˜ example of hdpe pipe manufacturing. asian journal on quality, 8(2), 32-56. van hoi, p., mol, a., oosterveer, p. (2013), state governance of pesticide use and trade in vietnam. njas-wageningen journal of life sciences, 67, 19-26. widayati, t., yusuf, e. (2017), strategies for environmental, economic, and social sustainability of potato agriculture in dieng plateau central java indonesia. journal of environmental management and tourism, 8(1), 259. zhu, z., wang, k., zhang, b. (2014), applying a network data envelopment analysis model to quantify the eco-efficiency of products: a case study of pesticides. journal of cleaner production, 69, 67-73. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 3 • 2023512 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(3), 512-523. impact of financial development and economic growth on energy consumption in developing countries of asia muhammad usman1, kiran rasheed1, faiq mahmood2*, ahsan riaz2, mohsin bashir2 1department of management and administration sciences, university of gujarat, gujarat pakistan, 2lyallpur business school, government college university faisalabad, pakistan. *email: drfaiqmahmood@gcuf.edu.pk received: 20 january 2023 accepted: 05 may 2023 doi: https://doi.org/10.32479/ijeep.14233 abstract this study investigates the impact of financial development and economic growth on energy consumption by controlling variables such as urbanization and globalization in developing countries of asia for the era of 1991-2019. data related to financial development, economic growth, energy consumption and urbanization is collected from world development indicator and data related to globalization is collected from konjunkturforschungsstelle (kof) index of globalization. in this research dynamic seemingly unrelated regression model is applied to test the hypothesis. according to the outcomes of dynamic seemingly unrelated regression model (dsur) the impact of financial development on energy consumption is positively substantial as increase of 1 unit in financial development brings 3.07% rise in energy consumption, the effect of gdp on energy consumption is positively influential as increase of 1 unit in gdp brings 0.29% increase in energy consumption and the influence of globalization is unfavorable but substantial as increase of 1 unit in globalization brings decrease of 15.57% in energy consumption. moreover, the influence of urbanization on energy consumption is positive and considerable, as increase of 1 unit in urbanization brings 11.54% increase in energy consumption. moreover, there is two way connections among gdp and financial development. moreover, asian countries should adopt energy conservation policies. keywords: financial development, energy consumption, dynamic seemingly unrelated regression model, gross domestic products jel classifications: f43, q40, r11, o47, o53 1. introduction energy plays a significant role in growth as well as development of the economy. it is considered fuel for the growth and development of both industry and economy. for the business and social advancement of the country, energy is fundamentally same as other elements of manufacturing. in the past few years, there is rapid growth in asia. from 1985-2009 there has been a growing trend in the gdp of south and east asian countries (perera and lee, 2013). energy consumption is reported higher in south and east asia because energy resources are not utilized carefully. as described by the world bank, gdp and energy consumption are increasing (srivastava and misra, 2007). there are many studies on the association of consumption of energy with different exogenous variables such as financial development and economic growth. recently, a group of researchers document that the social and economic development of the country depends on energy (sahir and qureshi, 2007). financial development is described as the advancement in all the activities of the financial sectors such as an increase in activities of the banking sector, stock or bond market (pradhan et al., 2018). financial development enhances the growth in the economy by raising fdi and encouraging stock exchanges and banking activities (kumar et al., 2016; shahbaz et al., 2013). similarly through development in financial sector, investment resources are available easily that promotes the industrial sector (farhani and solarin, 2017). even in countries that have fewer financial resources, efficient financial system management brings efficient use of financial resources. it also increases economic development (furuoka, 2015). this journal is licensed under a creative commons attribution 4.0 international license usman, et al.: impact of financial development and economic growth on energy consumption in developing countries of asia international journal of energy economics and policy | vol 13 • issue 3 • 2023 513 financial sector enhancement increases energy utilization through different channels such as level and efficiency effects. according to the level effect, financial sectors enable unused resources from non-profitable investments to remunerative investments by appealing home and overseas investments. according to the efficiency effect, financial sectors provide financial capital for effective investments, thus the demand for energy increased due to an increase in effective investment (sadorsky, 2010). similarly, economic growth is affecting the energy’s consumption. growth in the economy is the sign of the growth of the country. it means that the productive capacity of the country is increasing. in the past, numerous studies found out the economic growth’s effect on energy consumption. narayan and smyth (2005) examined that because of growth in real gdp, electricity utilization is also increasing. with the advancement in asian countries, industrial and commercial sectors are growing so electricity is used as a basic source of energy for the expansion of these sectors. so, growth in gdp is increasing the need for energy. likewise, energy consumption is affecting the economic growth. numbers of studies have been performed to find out the cause and effect relationship among economic growth and energy consumption. (akinlo, 2008; zachariadis and pashourtidou, 2007; hondroyiannis et al., 2002; halicioglu, 2007; yoo and kim, 2006; ghosh, 2002; ciarreta and zarraga, 2010; altinay and karagol, 2005; yoo, 2005). moreover, urbanization and globalization are used as control variables in this study. concerning the urbanization stage, people are more likely to use electronic products which in turn positively affect energy consumption (baloch, 2018). urbanization has different essentials that are affecting energy consumption in different ways, such as; man-made environment, expansion in industrial and economic activities, infrastructural changes, and increased transportation activities (poumanyvong et al., 2012; madlener and sunak, 2011). promotion in the urban lifestyle is affecting energy consumption because people use more energy-intensive products due to enhancement in economic and social activities (sadorsky, 2014). similarly, globalization is also influencing energy consumption. globalization may have a direct and inverse impact on energy consumption. because of removing barriers to trade between different countries and investment restrictions, economic growth is increased. by using advanced technology, overseas firms can establish a new business or develop the current business, and energy consumption can be reduced due to advanced technology. on the contrary, energy consumption may increase due to globalization because the goal of foreign firms is to maximize the profit not to conserve the energy. this study will make some imperative contribution to literature by examining the impact of financial development and economic growth on energy consumption. 2. literature review there are different researches on the fd and ec association. komal and abbas (2015) examine the favorable and substantial effect of development of financial sector by using channel of economic growth. outcomes of this research show that increase of 1% in fd brings 0.024 % rise in ec. in saudi arabia mahalik et al. (2017) exposed the association between financial sector advancement and energy consumption for the era 1971–2011. their results show that there is one way causation between fd and ec. similarly in nigeria odusanya et al. (2016) analyzed the relation between fd and ec for the era of (1971-2004). according to their results there is positive and significant association concerning these variables. in addition, komal and abbas (2015) found the association of fd and ec in pakistan by using urbanization and energy price as control variables. according to their results development in financial sector has favorable and vital impact on consumption of energy. furthermore, when financial sector is developed then producers take loan at low cost and purchase advanced technology which consumes less energy (shahbaz et al., 2017). hence, mielnik and goldemberg (2002) established negative connection among fdi and energy’s consumption. imamoglu (2019) suggests that there is direct and definitive impact of financial advancement, trading and economic growth on energy consumption, both in developed and emerging countries. shahbaz and lean (2012) analyze the correlation concerning financial development and energy consumption in tunisia. according to their findings there is direct association among financial sector’s advancement and energy consumption because effect of development of stock market on energy consumption is positive. similarly, granger cause and effect method was used by dan and lijun (2009) for testing the connection among energy consumption and development of financial sector in. similarly, ang (2009) expressed that dcp is an important indicator of financial development because private sector is able to use their funds in a good manner in comparison with public sector. to incorporate the overall credit expansion as the proxy of financial development, overall credit given by sector of banking as well as broad money supply was included. an increase in money supply increases financial depth (gelb, 1989). they found the result that fd does not raise the consumption of energy. xu et al. (2012) examines the link among financial sector advancement and energy consumption throughout the period of 1999-2009 by using panel data set in chinese provinces by applying generalized method of momentum. results demonstrate that there is favorable and significant relationship between the variables. financial development affects consumption of energy through economic growth (bojanic, 2012; calderón and liu, 2003; hassan et al., 2011). fd reduces the ec by attaining effectiveness in its use. as financial development provides access to the financial capital by minimizing the risk of financing and reducing the cost of borrowing. thus, financial development in many ways affects energy demand. for example, consumers get cheaper loan from the banks and purchase energy efficient products which minimize the use of energy. on usman, et al.: impact of financial development and economic growth on energy consumption in developing countries of asia international journal of energy economics and policy | vol 13 • issue 3 • 2023514 the other hand, if they buy high price items such as houses, air conditioners, automobiles and washing machines. than high amount of energy is consumed by these items which can influence the overall energy demand of the country (karanfil, 2009). another research was conducted on eu for examining the impact of fd on ec. according to the results there is strong and substantial effect of fd on ec for the old member countries which is consistent with financial development–energy literature (çoban and topcu, 2013). there is cointegrating association between economic growth, energy consumption, revenues of oil and financial development in iran by using autoregressive–distributed lag bound test (safaynikou and shadmehri, 2014). there is long term connection between economic growth, energy consumption, trade and financial development in countries of south asia such as pakistan, sri lanka, nepal and bangladesh as well as there is no association among these variables in short period of time (siddique and majeed, 2015). the literature leads to the development of following hypothesis: h1: financial development has significant impact on energy consumption. various researches have been done on the association of eg and ec. according to some researchers there are different elements that influence energy consumption such as economic progress and macro-variables. so many studies in past apply these variables to find the impact of eg on energy utilization. for example, method of granger causation was used to check out the effect of economic growth on energy consumption on the data of india. according to the results eg is the cause of ec (chiou-wei et al., 2008). similarly, wolde-rufael (2009) evaluates the correlation between economic growth and energy consumption. this study was conducted on seventeen african countries. according to the results economic progression is the reason of energy depletion which is in the support of growth leads to energy consumption hypothesis. ghali and el-sakka (2004) examined the causative association among energy consumption and economic growth in canada by using the model of vec after applying multivariate cointegration among growth rate, labour, capital and energy consumption. the results suggest that there is reciprocal cause and effect connection among energy consumption and economic growth. there is considerable connection among eg and ec (erdal et al., 2008; hossain and saeki, 2011; imran and siddiqui, 2010; zaman et al., 2011). similarly, another research was conducted in indonesia, pakistan, india, philippines, and singapore for evaluating the association among eg and ec. according to the findings of the study there is cointegration among these variables in india, pakistan and indonesia, but there is no association takes place among these variables in malaysia, singapore and philippines (masih and masih, 1996). the similar research correspondingly established causal movement from ec to eg in india because the nation is depending on energy as well as causality running from eg to ec in pakistan and indonesia which is consistent with the growth leads to energy hypothesis. moreover in india and indonesia causation running from ec to income and reciprocal causation in thailand and philippines (asafu-adjaye, 2000). two directional causation in argentina, in italy and korea it is from eg to ec in turkey, france, germany and japan the causation running from ec to eg (soytas and sari, 2003). as well as there is link among energy use and gdp in turkey and one directional cause and effect relationship runs from gdp to energy consumption which indicates that country is less reliant on energy (lise and van montfort, 2007). there is one directional causation from economic growth to energy consumption in six gulf cooperation council countries (al-iriani, 2006). there is one directional cause and effect association running from eg to ec (kraft and kraft, 1978). similarly another research have been done in low paying, middle paying and high paying countries but findings suggest there is no cause and effect connection among ec and eg in low income countries but find out that economy’s growth affects the energy’s consumption in middle and high income (huang et al., 2008). results are consistent with neutrality hypothesis for low income countries. moreover, cause and effect association between gdp and energy consumption was observed by mozumder and marathe (2007) in bangladesh. according to their findings, there is substantial effect of energy on growth of economy. also causal connection among eg, ec and effluence of environment was examined by chebbi and boujelbene (2008) in tunisia. according to empirical results, there is longitudinal relationship among energy consumption, performance of growth and contamination of environment for the period of 1971-2004. in addition, findings disclosed that there is short term mono directional cause and effect relationship among ec and eg in tunisia. for the era of 1971-2004, loganathan and subramaniam (2010) also examined the viable affiliation among energy consumption and economic growth in malaysia. ardl and ecm was used in this study. according to auto-regressive distributed lag, there is long run association among ec and eg. according to result of ecm there exists reciprocal causality between eg and ec. in eurasian and european countries, tiwari (2011) observed the impact of ec on eg. consumption of hydroelectricity was used as alternative of the sources of reusable energy as well as consumption of coal was used as a substitution of sources of nonrenewable energy for the time period of 1965 to 2009. panel vector autoregressive technique was used in analyzing the influence of energy consumption on economic growth. according to the result there is negative influence of the resources of non–renewable energy on gross domestic product, while there is positive impact of renewable resources of energy on gross domestic product. moreover, another study was conducted in iran to check the granger cause and effect relationship among consumption of usman, et al.: impact of financial development and economic growth on energy consumption in developing countries of asia international journal of energy economics and policy | vol 13 • issue 3 • 2023 515 energy such as electricity, gas and petroleum for the period of 1967-2003. this relationship was observed in manufacturing area. according to the results there is longitudinal mono directional cause and effect association from gdp to energy and there is two directional relationship of cause and effect among gross domestic product and gas as well as the relationship among economic growth and depletion of petrol for entire economy (zamani, 2007). the findings show that in short-run there is no impact of energy consumption on economic growth but in long run it will slow down the growth. in romania, spain and european countries a study have been done for investigating the association of energy consumption, renewable energy, gas, oil and coal with growth of economy for the era of 1990-2010. according to the results, in romania there is mono directional link from reusable energy consumption to economic growth and in spain from consumption of gas to economic growth. but there is no cause and effect association among these variables in european countries (pirlogea and cicea, 2012). further, another study was conducted in south africa for analyzing the association among disaggregates energy consumption and productivity of industry for the era of 19802005. according to the results there is two directional cause and effect relationship among consumption of oil and output of industry (ziramba, 2009). the findings of this result are consistent with neutrality hypothesis. toda-yamamoto long term cause and effect tests were used in us for examining the causative link between consumption of coal and real gdp for the period of 1949-2006. according to these tests there is cause and effect relationship among consumption of coal and real economic growth; mono directional cause and effect relationship from real economic growth to consumption of gas. this relationship is consistent with conservation hypothesis; and one directional cause and effect relationship from consumption of petrol to real economic growth is consistent with the growth hypothesis (aperjis and payne, 2011). growth hypothesis suggests, energy is imperative for growth of economy and proposes that eg is influenced by ec. energy is essential same like other factors of production. squalli (2007) examines the association between eg and ec. findings show that there is unfavorable link related to ec and eg. moreover the research was conducted in barbados for checking the longitudinal link among output growth and use of electricity and also the causal association between them. by using model of neo classical production they established the two directional causation among these variables in the long run but causation runs from energy consumption to output in short run (lorde et al., 2010). the literature thus leads to development of following hypothesis: h2: there is significant effect of economic growth on energy consumption. h3: there is significant effect of energy consumption on economic growth. 3. research methodology we will use the annual data of the developing countries of asia from 1991 to 2019 which are stated in the table 1. in this study we will use different variables to know the impact of fd and eg on ec, such as fd, eg, ec as well as we will include control variables which are urbanization and globalization (table 2). financial development index includes different indices such as financial institutions and financial markets in terms of their access, depth and efficiency. stock and bond markets are including in financial markets. banks, insurance companies, pension funds and mutual funds are included in financial institutions. combination of depth, access and efficiency is called financial development. moreover, depth is defined as a liquidity of markets and size, access is defined as aptitude of corporations and customers to attain financial services and efficiency means to provide financial facilities at minimum cost and with maintainable profit. also we will use gdp per capita for the indication of eg, we will use gdp per capita for ec, energy use (kg of oil equivalent per capita), urban population (% of total population) is used for urban population and kof index of globalization is used as an indicator of globalization. globalization with the economic, social and political dimensions are measured by kof index. data of financial development will be collected from financial development index, data of gdp (per capita), energy consumption, urbanization will be retrieved from world development indicator (wdi). as well as kof index of globalization will be used for data regarding globalization. for empirical analysis dsur model will be used for this study. arnold zellner in (1962) proposed the dynamic seemingly table 1: list of developing countries (sample size) pakistan lebanon korea republic kyrgyzstan india uae samoa mongolia china cambodia kiribati malaysia armenia kazakhstan jordan saudi arabia azerbaijan syrian arab republic myanmar tajikistan philippines sri lanka nepal turkmenistan bangladesh indonesia thailand uzbekistan yemen vietnam table 2: variables measurement and data source variables symbol measurement source energy consumption ec kg of oil equivalent per capita wdi financial development fd financial development index wdi economic growth gdp gdp per capita wdi urbanization urb percentage age of total population wdi globalization glob globalization index kof ec: energy consumption, fd: financial development, gdp: gross domestic product, urb: urbanization, glob: globalization, wdi: world development indicator, kof: konjunkturforschungsstelle usman, et al.: impact of financial development and economic growth on energy consumption in developing countries of asia international journal of energy economics and policy | vol 13 • issue 3 • 2023516 unrelated regressions (dsur). dsur is simplification of linear regression model. there are more than one regression equations. each regression equation has its endogenous and exogeneous variables as every equation is separately predicted. effect of fd and eg on ec will be examined through dsur model. 3.1. effect of financial development and economic growth on energy consumption 0 1it 2 3 4ec α β β β β ε+ + + + += it it it itfd gdp urb glob where, fd = financial development ec = energy consumption gdp = gross domestic product (per capita) urb = urbanization glob = globalization ε = error term. 3.1.1. cross-sectional dependence test csd is an imperative diagnostic that should be examined by researchers before execution of a panel data analysis. this problem arises when we include the countries in our study which are interrelated. we will check the csd of each variable included in this study. 3.1.2. unit root test unit root tests are used for checking the stationarity of the data. adf test is used in this study for checking the stationarity of panel data set. 3.1.3. panel cointegration test cointegration tests are used to check the relationship among variables of given panel data set such as engle-granger, johansen test, phillips-ouliaris test. in this study we will use the engle-granger test of cointegration. the test which is used very extensively is pedroni engle-granger cointegration test for panel data regression analysis, because it takes care of cross-sectional dependence, especially where the countries have the same outlook (either economical, socially, political etc) by allowing considerable heterogeneity. 3.1.4. dsur (dynamic seemingly unrelated regression) arnold zellner in (1962) proposed the seemingly unrelated regressions (dsur). dsur is simplification of linear regression model. there are more than one regression equations. each regression equation has its endogenous and exogeneous variables as every equation is separately predicted. 3.1.5. pairwise dumitrescu hurlin panel causality tests dumitrescu and hurlin (2012) introduced the pairwise dumitrescu hurlin panel causality test. among cross sections, this test permits the coefficients to be heterogeneous. two statistics are used in this technique such as wbar-statistic and zbar-statictic. average of test statistics is used in wbar-statistic and zbar-statictic demonstrates normal distribution. 3.1.6. country wide dynamic ordinary least square model for the valuation of longitudinal analysis of particular country, the dynamic ordinary least square is used in this study. 4. results and discussion 4.1. descriptive statistics in these results of table 3, the mean value of dependent variable (energy consumption) is 1528.753. it means that on average countries consume 1528.753 energy (kg of oil equivalent per capita). the minimum energy that countries consume is 86.65042 (kg of oil equivalent per capita) as well as the maximum energy consumption is 12172.42 (kg of oil equivalent per capita). the value of skewness of energy consumption is 2.758885 which shows that distribution is skewed positively as well the probability value is 0.000 which is significant because the value of probability is 0.000 < 0.05. the mean value of financial development is 24%. it describes that on average financial development is 24%. the maximum financial development is 70% and minimum financial development is 0%. the value of skewness of financial development is 78% which means that distribution is skewed moderately as well the probability value is 0.000 which is significant because the value of probability is 0.000 < 0.05. the mean value of gdp is 3702.320 us.$. it shows that on average growth rate is 3702.320 us.$. the maximum growth rate in countries is 44498.93 us.$. and minimum growth rate is 137.1683 us.$. the value of skewness of gdp is 3.480199 which means that distribution is skewed positively as well the probability value is 0.000 which is significant because the value of probability is 0.000 < 0.05. the mean value of globalization is 50.81425. the maximum globalization is 80.77792 index and minimum globalization is 20.02393 index. the value of skewness of globalization is 0.043517 which means that distribution is almost symmetric as well the probability value is 0.000574 which is significant because the value of probability is 0.000574 < 0.05. on average the urban population is 45.32836%. the maximum urbanization rate is 90% and minimum urbanization rate is 9.18%. the value of skewness of urbanization is 0.485489 which means table 3: descriptive statistics statistical measures ec fd_fd_ix gdp kofgi urb mean 1528.753 0.239 3702.32 50.81 45.32 median 752.7963 0.210 1152.74 50.81 43.55 maximum 12172.42 0.703 44,498.9 80.77 90.00 minimum 86.65042 0.000 137.1 20.02 9.180 sd 2069.430 0.148 7029.0 13.21 21.28 probability 0.000000 0.000 0.00 0.000574 0.000 sum 1100702. 172.7486 2,665,670.0 36,586.26 326,364 sum square deviation 3.08e+09 15.83 3.55e+10 125,639.5 325,664 observation 720 720 720 720 720 ec: energy consumption, fd: financial development, gdp: gross domestic product, urb: urbanization, sd: standard deviation, ix: index, kofgi: konjunkturforschungsstelle index usman, et al.: impact of financial development and economic growth on energy consumption in developing countries of asia international journal of energy economics and policy | vol 13 • issue 3 • 2023 517 that distribution is almost symmetric as well the probability value is 0.000574 which is significant because the value of probability is 0.000574 < 0.05. 4.2. correlation analysis in these results of table 4, association between ec and fd is 0.29, which shows that there is positive but week association among these variables. correlation between ec and eg is 0.86, which indicates the strong positive relationship among these variables. correlation among energy consumption and globalization is 0.32, which specifies the positive but week relationship among these variables. correlation between energy consumption and urbanization is 0.61, which shows that there is moderately positive link among these variables. 4.3. cross-section dependence 4.3.1. cross-sectional dependence (energy consumption) according to findings of table 5, the null hypothesis which is (there is no cross –section dependence) is refused because the probability value is 0.0000 <0.05 which is significant. so it means that there is csd in given data set of energy consumption. 4.3.2. cross-section dependence (financial development) according to findings of table 6, the null hypothesis which is (there is no cross section dependence) is rejected because the probability value is 0.0000 <0.05 which is significant. so it means that there is csd in given data set of financial development. 4.3.3. cross-section dependence (economic growth) according to findings of table 7, the null hypothesis which is (there is no cross section dependence) is rejected because the probability value is 0.0000 <0.05 which is significant. so it means that there is csd in given data set of gdp. 4.3.4. cross-sectional dependence (globalization) according to findings of table 8, the null hypothesis which is (there is no cross section dependence) is refused because the probability value is 0.0000 <0.05 which is significant. so it means that there is csd in given data set of globalization. 4.3.5. cross-section dependence (urbanization) according to findings of table 9, the null hypothesis which is (there is no cross section dependence) is rejected because the probability value is 0.0000 <0.05 which is significant. so it means that there is csd in given data set of urbanization. 4.3.6. unit root test 4.3.6.1. unit root test (energy consumption) table 10 reports the result of adf test. results provide the evidence of refusal of null hypothesis because fisher chi-square table 4: correlation analysis variables ec fd_fd_ix gdp kofgi urb ec 0.29186 0.86544 0.325 0.613 fd_fd_ix 0.291 1 0.36362 0.7219 0.38931 gdp 0.86544 0.36341 1 0.481322 0.58220 kofgi 0.325850 0.72196 0.48132 1 0.59466 urb 0.61347 0.3899 0.582203 0.59204 1 ec: energy consumption, fd: financial development, gdp: gross domestic product, urb: urbanization table 5: cross-section dependence test of energy consumption series: ec null hypothesis: no csd (correlation) test statistic df probability breusch-pagan lm 4197.659 435 0.0000 pesaran scaled lm 126.5490 0.0000 bias-corrected scaled lm 125.8968 0.0000 pesaran cd 20.78967 0.0000 ec: energy consumption, csd: cross-section dependence table 6: cross-section dependence test of financial development null hypothesis: no csd (correlation) test statistic df probability breusch-pagan lm 2930.572 435 0.0000 pesaran scaled lm 83.59073 0.0000 bias-corrected scaled lm 82.93856 0.0000 pesaran cd 42.92620 0.0000 csd: cross-section dependence table 7: cross-section dependence test (economic growth) series: gdp null hypothesis: no csd (correlation) test statistic df probability breusch-pagan lm 9157.995 435 0.0000 pesaran scaled lm 294.7201 0.0000 bias-corrected scaled lm 294.0680 0.0000 pesaran cd 95.50204 0.0000 gdp: gross domestic product, csd: cross-section dependence table 8: cross-section dependence test (globalization) series: kofgi null hypothesis: no csd (correlation) test statistic df probability breusch-pagan lm 9100.690 435 0.0000 pesaran scaled lm 292.7773 0.0000 bias-corrected scaled lm 292.1251 0.0000 pesaran cd 95.27917 0.0000 csd: cross-section dependence table 9: cross-section dependence test (urbanization) series: urb null hypothesis: no csd (correlation) test statistic df probability breusch-pagan lm 8139.085 435 0.0000 pesaran scaled lm 260.1758 0.0000 bias-correcte scaled lm 259.5237 0.0000 pesaran cd 33.65673 0.0000 urb: urbanization, csd: cross-section dependence usman, et al.: impact of financial development and economic growth on energy consumption in developing countries of asia international journal of energy economics and policy | vol 13 • issue 3 • 2023518 value is 0.0000 <0.05. null hypothesis in this test is (the data is non stationary) is rejected. 4.3.6.2. unit root test (economic growth) table 11 reports the result of adf. results provide the evidence of refusal of null hypothesis because fisher chi-square value is 0.0000 <0.05. null hypothesis in this test is (the data is non stationary) is rejected. 4.3.6.3. unit root test (financial development) table 11 reports the result of adf. results provide the evidence of refusal of null hypothesis because fisher chi-square value is 0.0000 <0.05. null hypothesis in this test is (the data is non stationary) is rejected. 4.3.6.4. unit root test (globalization) table 12 reports the result of adf. results provide the evidence of refusal of null hypothesis because fisher chi-square value is 0.03 <0.05. null hypothesis in this test is (the data is non stationary) is rejected. 4.3.6.5. unit root test (urbanization) table 14 reports the result of adf test. results provide the evidence of refusal of null hypothesis because fisher chi-square value is 0.0000 <0.05. null hypothesis in this test is (the data is non stationary) is rejected. 4.4. pedroni residual cointegration test according to the results of table 14, null hypothesis is rejected which is (there is no cointegration) on the basis of four of seven tests because the probability value of panel pp-statistic, panel adf –statistic, group pp-statistic and group adf-statistic is <0.05 except panel v-statistic, panel rho-statistic and group rho-statistic. so it is concluded that there is cointegration among variables of given panel data set. 4.5. panel data long run estimates 4.5.1. dynamic seemingly unrelated regression according to the results of table 15, the impact of fd on ec is positively significant as increase of 1 unit in fd brings 3.07% increase in ec, the impact of gdp on ec is negatively significant as increase of 1 unit in gdp brings 0.29% increase in ec. as well as the effect of globalization is negative but significant as increase of 1 unit in globalization brings decrease of 15.57% in ec. moreover, the effect of urbanization on ec is positive and significant as increase of 1 unit in urbanization brings 11.54% increase in ec. 4.5.2. pairwise dumitrescu hurlin panel causality test according to the results of table 16, there is bidirectional causality running from financial development to energy consumption. likewise, there is bidirectional causality running from gdp to energy consumption. moreover, there is bidirectional relationship among gdp and financial development. 4.5.3. country wide long run estimates for the estimation of long run analysis of single country the dynamic ordinary least square is used in this study. results of table 17 show that the impact of fd on ec is considerable and favourable in countries such as bangladesh, china, pakistan, india, table 10: null hypothesis: unit root (individual unit root process) of economic growth method statistic probability** series: d (ec) adf-fisher’s χ2 220.991 0.0000 adf-choi z-statistic −9.09885 0.0000 series: d (gdp) adf 147.626 0.0000 adf −6.14250 0.0000 gdp: gross domestic product, ec: energy consumption table 11: null hypothesis: unit root (individual unit root process) of financial development series: d (fd_fd_ix) method statistic probability** adf 265.939 0.0000 adf −11.9546 0.0000 fd: financial development table 12: null hypothesis: unit root (individual unit root process) globalization series: kofgi method statistic probability** adf 81.5279 0.0337 adf −0.95576 0.1696 table 13: null hypothesis: unit root (individual unit root process) urbanization series: urb method statistic probability** adf 495.095 0.0000 adf −12.3138 0.0000 urb: urbanization table 14: series: energy_consumption financial development_financial development_ix gross domestic product kofgi urbanization null hypothesis: no cointegration alternative hypothesis: common ar coefs. within-dimension) weighted methods statistic probability statistic probability panel v-statistic 0.148182 0.4411 −2.035861 0.9791 panel rhostatistic 0.496271 0.6901 0.637207 0.7380 panel ppstatistic −4.080452 0.0000 −6.222187 0.0000 panel adfstatistic −3.348459 0.0004 −5.668781 0.0000 alternative hypothesis: individual ar coefficients (between-dimension) methods statistic probability group rhostatistic 3.063499 0.9989 group ppstatistic −4.854447 0.0000 group adf statistic −3.441777 0.0003 usman, et al.: impact of financial development and economic growth on energy consumption in developing countries of asia international journal of energy economics and policy | vol 13 • issue 3 • 2023 519 azerbaijan, kazakhstan, thailand, jordan, cambodia, sri lanka, mynammar, malaysia, philippines, tajikistan, turkmenistan, kyrgyzstan, yemen and kiribati as well as the impact of fd on ec is significant but negative in countries such as uae, armenia, indonesia, lebanon, nepal, saudi arabia, syrian arab republic, samoa and korea republic. the impact of gdp on ec is favourable and significant in countries such as uae, armenia, bangladesh, pakistan, india, kazakhstan, thailand, sri lanka, myanmmar, mongolia, malaysia, nepal, tajikstan, kyrgyzstan, saudi arabia, syrian arab republic, samoa, and korea rep. the impact of gdp on ec is significant but negavtive in countires such as china, azerbaijan, indoneshia, jordan, vietnam, cambodia, lebanan, phillipines, turkemenistan, uzbekistan and yemen. the impact of globalization on ec is significant and favourable in countries such as armenia, bangladesh, azerbaijan, kazakhstan, thailand, jordan, sri lanka, myanmmar, malaysia, nepal, philipines, yemen, saudi arabia, syrian arab republic, samoa, korea republic and kiribati as well as the impact of globalization on ec is considerable but negative in countries such as uae, china, pakistan, india, vietnam, lebanon, mongolia, tajikstan, turkemenistan, uzbekistan and kyrgyzstan. but the impact is negatively insignificant in indoneshia. the impact of urb on ec is positive and significant in countries such as uae, armenia, bangladesh, china, pakistan, india, azerbaijan, indonesia, jordan, cambodia, sri lanka, mongolia, philippines, tajikstan, turkemenistan, uzbekistan, kyrgyzstan, yemen, syrian arab republic, samoa as well as the impact of urb on ec is unfavourable and substantial in countries such as thailand, vietnam, lebanan, myanmmar, nepal, saudi arabia, korea republic. there is positive but insignificant impact of urbanization in kazakhstan and relationship is negatively significant in countries such as malaysia and kiribati. 5. discussion this study examined the effect of financial development and economic growth on energy consumption in developing asian economies for the period of 1991-2014. different econometric techniques are used in this study. before modeling, csd test is applied to check the dependence within cross sections of the given variables. according to cross sectional dependence test there is csd in given data set of all variables because the probability value is “0.000”. so the null hypothesis which is there is no cross sectional dependence is rejected. after checking cross sectional dependence, adf is used to check whether the given variables have unit root or not. results provide the evidence of refusal of null hypothesis because fisher chi-square value is 0.0000 <0.05. null hypothesis in this test is (the data is non stationary) is rejected. dynamic seemingly unrelated regression model is used to find out the impact of fd and eg on ec. according to the results of dynamic seemingly unrelated regression the impact of fd on ec is positively significant as increase of 1 unit in fd brings 3.07% increase in ec. this result is consistent with direct effect, business effect and wealth effect. according to de consumers get cheaper loan from the bank and buy big ticket items such as houses, air conditioners, automobiles and washing machines. so high amount of energy is consumed by these items which can influence the overall energy demand of the country (ozturk and acaravci, 2013). table 15: dynamic seemingly unrelated regression variables coefficient se t-statistic probability c (1) fd 3.071282 0.048666 63.10977 0.0000 c (2) gdp 0.288646 0.004836 59.69209 0.0000 c (3) globalization −15.57513 2.343548 −6.645963 0.0000 c (4) urbanization 11.54356 1.572742 7.339762 0.0000 c (5) constant 544.3358 104.0926 5.229341 0.0000 equation: ec=c (1)*fd_fd_ix+c (2)*gdp+c (3) *kofgi+c (4)*urb+c (5) observations: 720 r2 0.757094 mean dependent variable 1528.753 adjusted r2 0.755735 sd dependent variable 2069.430 se of regression 1022.778 sum squared resident 7.48e+08 durbin-watson statistic 0.198098 equation: gdp=c (1)*ec observations: 720 r2 0.727506 mean dependent variable 3702.320 adjusted r2 0.727506 sd dependent variable 7029.002 se of regression 3669.206 sum squared resident 9.68e+09 durbin-watson stat 0.212789 se: standard error, sd: standard deviation, fd: financial development, gdp: gross domestic product, ec: energy consumption, urb: urbanization table 16: pairwise dumitrescu hurlin panel causality test null hypothesis w-statistic zbarstatistic probability fd_fd_ix does not homogeneously cause ec 30.96 3.58 0.000 ec does not homogeneously cause fd_fd_ix 50.50 6.83 8.e-12 gdp does not homogeneously cause ec 3.95 3.56 0.000 ec does not homogeneously cause gdp 6.39 8.72 0.000 gdp does not homogeneously cause fd_fd_ix 5.42 6.68 2.e-11 fd_fd_ix does not homogeneously cause gdp 4.18 4.05 5.e-05 gdp: gross domestic product, ec: energy consumption, fd: financial development usman, et al.: impact of financial development and economic growth on energy consumption in developing countries of asia international journal of energy economics and policy | vol 13 • issue 3 • 2023520 which energy demand increased (sadorsky, 2011). moreover, we rises when developed stock market provides different channels of financing to the listed corporations and by minimizing the cost of financing. so these corporations invest in new projects which can ultimately increase demand for energy (safaynikou, 2014). this relationship is consistent with the findings of (komal and abbas, 2015; odusanya et al., 2016; shahbaz et al., 2016; imamoglu, 2019; sadorsky, 2011; shahbaz and lean, 2012; islam et al., 2013; bojanic, 2012; calderón and liu, 2002; hassan et al., 2011; kraft and kraft, 1978; karanfil, 2009).their findings suggest that these countries are not taking the advantage of energy efficient technology in the production of goods and services. thus it is suggested that these countries should assign more capital to energy efficient technology and new production procedures to use energy effectively. as well as the impact of eg on ec is positively significant as increase of 1 unit in gdp brings 0.29% increase in energy consumption. this relationship is based on wealth effect. according to we, stock market development is the sign of growth of economy. due to this consumers and businesses get finance for investing in different projects that leads to economy growth and hence increase the energy demand. this relationship is consistent with the findings of (chiou-wei et al., 2008; wolde-rufael, 2009; yavuz and güriş, 2008; suri and chapman, 1998; ghali and el-sakka, 2004; erdal et al., 2008; hossain and saeki, 2011; imran and siddiqui, 2010; zaman et al., 2011; masih and masih, 1996; asafu-adjaye, 2000; soytas and sari, 2003; lise and van montfort, 2007; huang et al., 2008; mozumder and marathe, 2007; chebbi and boujelbene, 2008; loganathan and subramaniam, 2010). according to their findings, there is substantial effect of energy on growth of economy. and their findings suggest that energy is an important source for growth of economy. moreover, the impact of glob on ec is negative but significant as increase of 1 unit in globalization brings decrease of 15.57% in energy consumption. by using advanced technology, foreign firms can setup new business or expand existing business and energy consumption can be reduced due to advanced technology. this relationship is consistent with the study of antweiler (2001). he observed the unfavorable relationship between globalization and energy depletion and found that due to importing cutting edge technology energy demand is reducing. likewise, the effect of urb on ec is positive and significant, as increase of 1 unit in urbanization brings 11.54% increase in energy consumption. in the urbanization stage, energy demand is increasing because of more electronic goods consumed by people (danish and baloch, 2018). urbanization has different essentials that are affecting energy consumption in different ways. for example, man-made environment, expansion in industrial and economic activities, infrastructural changes and increasing transportation (poumanyvong et al., 2012; madlener and sunak, 2011). promotion in urban life style is effecting the energy consumption because people use more energy intensive products due to enhancement in economic and social activities (sadorsky, 2014). urbaniation has intricate connections with energy consumption because of the difficulty of the procedure. table 17: results of country wide long run estimates countries variables fd gdp glob urb uae coefficients −0.24 0.85 −4.13 3.90 probability 0.000 0.000 0.000 0.000 armenia coefficients −0.029 0.280 0.904 0.152 probability 0.000 0.000 0.000 0.50 bangladesh coefficients 3.978 0.067 53.679 0.734 probability 0.000 0.000 0.000 0.0016 china coefficients −0.324 −0.201 −1.450 3.923 probability 0.000 0.000 0.000 0.000 pakistan coefficients 0.423 0.281 −2.719 4.286 probability 0.000 0.000 0.000 0.000 india coefficients 0.038 0.204 −0.209 1.728 probability 0.000 0.000 0.000 0.000 azerbaijan coefficients 0.840 −0.389 0.973 2.081 probability 0.000 0.000 0.000 0.000 indonesia coefficients 0.204 −0.347 −3.039 5.492 probability 0.000 0.000 0.000 0.000 kazakhstan coefficients 0.542 0. 195 1.266 0.623 probability 0.0000 0.0000 0.0003 0.5413 thailand coefficients 0.378 0.255 2.523 −1.431 probability 0.009 0.025 0.026 0.000 jordan coefficients 0.667 −0.348 0.323 1.982 probability 0.000 0.000 0.000 0.000 vietnam coefficients −11.819 0.057 9.204 −6.553 probability 0.000 0.000 0.000 0.000 cambodia coefficients 0.380 −1.265 1.319 3.112 probability 0.000 0.000 0.000 0.000 lebanon coefficients −3.894 2.053 −2.755 −0.624 probability 0.000 0.000 0.000 0.000 sri lanka coefficients 0.217 0.061 0.985 0.641 probability 0.000 0.000 0.000 0.000 myanmar coefficients 1.288 0.114 0.443 −0.076 probability 0.000 0.000 0.000 0.000 mongolia coefficients −6.133 11.442 −6.567 24.512 probability 0.000 0.000 0.000 0.000 malaysia coefficients 1.045 0.184 5.268 −3.818 probability 0.000 0.000 0.000 0.070 nepal coefficients −0.940 0.185 0.908 −0.100 probability 0.000 0.000 0.000 0.002 philippines coefficients 0.494 −0.156 0.083 1.945 probability 0.000 0.000 0.000 0.000 tajikistan coefficients −0.072 0.261 −1.484 2.894 probability 0.000 0.000 0.007 0.000 turkmenistan coefficients 0.309 −0.025 −3.663 5.493 probability 0.000 0.000 0.000 0.000 uzbekistan coefficients −0.190 −0.145 −1.164 3.221 probability 0.000 0.000 0.000 0.000 kyrgyzstan coefficients 0.041 0.426 −1.530 2.719 probability 0.000 0.000 0.000 0.000 yemen coefficients 0.491 −0.197 0.223 1.781 probability 0.000 0.000 0.000 0.000 saudi arabia coefficients −0.285 0.089 5.324 −4.144 probability 0.000 0.000 0.000 0.000 syrian arab republic coefficients −0.228 0.288 −1.364 2.390 probability 0.0081 0.000 0.000 0.000 samoa coefficients −0.146 0.119 0.901 0.165 probability 0.000 0.000 0.000 0.000 korea republic coefficients 1.350 0.009 4.067 −2.453 probability 0.000 0.000 0.000 0.000 kiribati coefficients 0.010 0.326 1.723 −1.098 probability 0.000 0.000 0.000 0.22 gdp: gross domestic product, fd: financial development, urb: urbanization, glob: globalization according to be, businessmen enhance their business as well as producers purchase advance machinery and equipment through usman, et al.: impact of financial development and economic growth on energy consumption in developing countries of asia international journal of energy economics and policy | vol 13 • issue 3 • 2023 521 urbanization includes commercial procedures, societal procedures, spatial procedures and technical procedures. in terms of economic processes, urbanisation is a movement from a less amount of energy-consuming unindustrialized culture to high amount of energy-consuming urban society. economic and manufacturing activities develop in cities, causing an rise in energy consumption (jones, 1989, 1991).in actual, manufacturing production which needs more different and intricate collection of techniques and processes, depends on severe and huge energy consumption. furthermore, pairwise dumitrescu hurlin panel causative association test was used in this study for checking the causative association among the variables. according to the result of pdhpct there is reciprocal causative association running from fd to ec. findings of this relationship are consistent with the findings of (danish and baloch, 2018). their findings suggest that there is feedback effect among fd and ec. it is suggested that fd through the channel of eg increases the energy demand and energy plays vital role in the economic growth and thus economic activities create demand for financial facilities. so due to this energy consumption granger cause financial development. as well as there is two way relationship among eg and ec. the findings are consistent with the study of (loganathan and subramaniam, 2010; ghali and el-sakka, 2004; yavuz and güriş 2008; suri and chapman, 1998; wolde-rufael, 2009; noor and siddique, 2010; apergis and payne, 2009). feedback hypothesis supports the twoway relationship between ec and eg. according to feedback hypothesis, ec and eg are necessary to each other. as well as feedback hypothesis suggests that there is need of energy’s expansionary policies for longitudinal economic growth. likewise, there is two directional connection among eg and fd. fd increases eg through different channels such as level and efficiency effects. according to level effect, financial sectors enable the idle resources from non profitable investments to profitable investments by appealing home and overseas investments due to which economic growth increases. according to efficiency effect financial sectors provide financial capital for effective investments, which increase the economic activities and develop the economy. financial development granger cause economic growth because of increasing the efficacy of capital accretion and due to increase in investment level. it means that by increasing the investment level and efficacy of capital accretion financial development increases economic growth. furthermore, it encourages the adoption of the cutting edge technology. (jalil and ma, 2008; greenwood and jovanovic, 1990; abu-bader and abu-qarn, 2008; ibrahim, 2007; coccorese, 2008; liang and teng, 2006; chukwu and agu, 2009; odhiambo, 2011; al-malkawi et al., 2012). according to demand following hypothesis eg granger cause fd. demand following relationship specifies that economic activities create demand for financial facilities. (fung, 2009; jenkins and katircioglu, 2010) exmine that eg has favourable impact on fd due to output increase. for the estimation of long run analysis of single country, the dynamic ordinary least square is used in this study. according to the results of dols the impact of fd on ec is significant and favourable in some countries and negative in some countries. 6. conclusion this study observed the impact of financial development and economic growth on energy consumption in developing asian economies for the period of 1991-2014. in addition, urbanization and globalization are used as control variables. different econometric methods are used in this study. dsur model is used to test the hypothesis. according to the results of dsur the impact of fd on ec is positively significant. this result is consistent with direct effect, business effect and wealth effect. the impact of gdp on ec is negatively significant. this relationship is based on wealth effect. according to wealth effect, stock market development is the sign of growth of economy. due to this consumers and businesses get finance for investing in different projects that leads to economy growth and hence increase the energy demand. as well as the effect of globalization is unfavorable but significant. by using advanced technology, foreign firms can setup new business or expand existing business and energy consumption can be reduced due to advanced technology. moreover, the effect of urbanization on energy consumption is positive and significant. urbanization has intricate connections with energy consumption because of the difficulty of the procedure. urbanization includes commercial procedures, societal procedures, spatial procedures and technical procedures. furthermore, pairwise dumitrescu hurlin panel causality test was used in this study to find out the causal relationship among the variables. according to the result of dhpcs, there is bidirectional causative relationship running from fd to ec. there is reciprocal effect among fd and ec. as well as there is bidirectional relationship among eg and ec. feedback hypothesis supports the two directional relationship between ec and eg. likewise, there is two directional relationship among eg and fd. fd increases eg through different channels such as level and efficiency effects. according to demand following hypothesis eg granger cause fd. demand following relationship specifies that economic activities create demand for financial facilities. references abu-bader, s., abu-qarn, a.s. (2008), financial development and economic growth: the egyptian experience. journal of policy modeling, 30(5), 887-898. kraft, j., kraft, a. (1978), on the relationship between energy and gnp. journal of energy development, 3(2), 401-403. akinlo, a.e. (2008), energy consumption and economic growth: evidence from 11 sub-sahara african countries. energy economics, 30(5), 2391-2400. al-iriani, m.a. (2006), energy-gdp relationship revisited: an example from gcc countries using panel causality. energy policy, 34(17), 3342-3350. altinay, g., karagol, e. (2005), electricity consumption and economic growth: evidence from turkey. energy economics, 27(6), 849-856. al-malkawi, h.a.n., marashdeh, h.a., abdullah, n. (2012), financial development and economic growth in the uae: empirical assessment using ardl approach to co-integration. international journal of economics and finance, 4(5), 105-115. usman, et al.: impact of financial development and economic growth on energy consumption in developing countries of asia international journal of energy economics and policy | vol 13 • issue 3 • 2023522 ang, j.b. (2009), financial development and the fdi-growth nexus: the malaysian experience. applied economics, 41(13), 1595-1601. antweiler, w., copeland, b.r., taylor, m.s. (2001), is free trade good for the environment american economic review, 91(4), 877-908. apergis, n., payne, j.e. (2009), energy consumption and economic growth: evidence from the commonwealth of independent states. energy economics, 31(5), 641-647. asafu-adjaye, j. (2000), the relationship between energy consumption, energy prices and economic growth: time series evidence from asian developing countries. energy economics, 22(6), 615-625. baloch, m.a. (2018), dynamic linkages between road transport energy consumption, economic growth, and environmental quality: evidence from pakistan. environmental science and pollution research, 25(8), 7541-7552. bojanic, a.n. (2012), the impact of financial development and trade on the economic growth of bolivia. journal of applied economics, 15(1), 51-70. calderón, c., liu, l. (2003), the direction of causality between financial development and economic growth. journal of development economics, 72(1), 321-334. chebbi, h.e., boujelbene, y. (2008), co2 emissions, energy consumption and economic growth in tunisia (no. 725-201649474). in: conference: european association of agricultural economists, 2008 international congress, ghent, belgium. chiou-wei, s.z., chen, c.f., zhu, z. (2008), economic growth and energy consumption revisited-evidence from linear and nonlinear granger causality. energy economics, 30(6), 3063-3076. ciarreta, a., zarraga, a. (2010), economic growth-electricity consumption causality in 12 european countries: a dynamic panel data approach. energy policy, 38(7), 3790-3796. çoban, s., topcu, m. (2013), the nexus between financial development and energy consumption in the eu: a dynamic panel data analysis. energy economics, 39, 81-88. dan, y., lijun, z. (2009), financial development and energy consumption: an empirical research based on guangdong province. in: 2009 international conference on information management, innovation management and industrial engineering. vol. 3. new jersey: ieee. p102-105. erdal, g., erdal, h., esengün, k. (2008), the causality between energy consumption and economic growth in turkey. energy policy, 36(10), 3838-3842. farhani, s., solarin, s.a. (2017), financial development and energy demand in the united states: new evidence from combined cointegration and asymmetric causality tests. energy, 134, 1029-1037. furuoka, f. (2015), financial development and energy consumption: evidence from a heterogeneous panel of asian countries. renewable and sustainable energy reviews, 52, 430-444. gelb, a.h. (1989), financial policies, growth, and efficiency. vol. 202. united states: world bank publications. ghali, k.h., el-sakka, m.i. (2004), energy use and output growth in canada: a multivariate cointegration analysis. energy economics, 26(2), 225-238. ghosh, s. (2002), electricity consumption and economic growth in india. energy policy, 30(2), 125-129. hassan, m.k., sanchez, b., yu, j.s. (2011), financial development and economic growth: new evidence from panel data. the quarterly review of economics and finance, 51(1), 88-104. halicioglu, f. (2007), the financial development and economic growth nexus for turkey (no. 06/2007). eeri research paper series. hondroyiannis, g., lolos, s., papapetrou, e. (2002), energy consumption and economic growth: assessing the evidence from greece. energy economics, 24(4), 319-336. hossain, m.s., saeki, c. (2011), does electricity consumption panel granger cause economic growth in south asia? evidence from bangladesh, india, iran, nepal, pakistan and sri-lanka. european journal of social sciences, 25(3), 316-328. huang, b.n., hwang, m.j., yang, c.w. (2008), causal relationship between energy consumption and gdp growth revisited: a dynamic panel data approach. ecological economics, 67(1), 41-54. imran, k., siddiqui, m.m. (2010), energy consumption and economic growth: a case study of three saarc countries. european journal of social sciences, 16(2), 206-213. imamoglu, h. (2019), the role of financial sector in energy demand and climate changes: evidence from the developed and developing countries. environmental science and pollution research, 26(22), 22794-22811. karanfil, f. (2009), how many times again will we examine the energyincome nexus using a limited range of traditional econometric tools? energy policy, 37(4), 1191-1194. komal, r., abbas, f. (2015), linking financial development, economic growth and energy consumption in pakistan. renewable and sustainable energy reviews, 44, 211-220. lise, w., van montfort, k. (2007), energy consumption and gdp in turkey: is there a co‐integration relationship? energy economics, 29(6), 1166-1178. loganathan, n., subramaniam, t. (2010), dynamic cointegration link between energy consumption and economic performance: empirical evidence from malaysia. international journal of trade, economics and finance, 1(3), 261-267. lorde, t., waithe, k., francis, b. (2010), the importance of electrical energy for economic growth in barbados. energy economics, 32(6), 1411-1420. madlener, r., sunak, y. (2011), impacts of urbanization on urban structures and energy demand: what can we learn for urban energy planning and urbanization management? sustainable cities and society, 1(1), 45-53. mahalik, m.k., babu, m.s., loganathan, n., shahbaz, m. (2017), does financial development intensify energy consumption in saudi arabia? renewable and sustainable energy reviews, 75, 1022-1034. masih, a.m., masih, r. (1996), energy consumption, real income and temporal causality: results from a multi-country study based on cointegration and error-correction modelling techniques. energy economics, 18(3), 165-183. mozumder, p., marathe, a. (2007), causality relationship between electricity consumption and gdp in bangladesh. energy policy, 35(1), 395-402. narayan, p.k., smyth, r. (2005), electricity consumption, employment and real income in australia evidence from multivariate granger causality tests. energy policy, 33(9), 1109-1116. odusanya, i.a., osisanwo, b.g., tijani, j.o. (2016), financial development and energy nexus in nigeria. acta universitatis danubius. œconomica, 12(5), 155-165. ozturk, i., acaravci, a. (2013). the long-run and causal analysis of energy, growth, openness and financial development on carbon emissions in turkey. energy economics, 36, 262-267. perera, l.d.h., lee, g.h. (2013), have economic growth and institutional quality contributed to poverty and inequality reduction in asia? journal of asian economics, 27, 71-86. pirlogea, c., cicea, c. (2012), econometric perspective of the energy consumption and economic growth relation in european union. renewable and sustainable energy reviews, 16(8), 5718-5726. poumanyvong, p., kaneko, s., dhakal, s. (2012), impacts of urbanization on national transport and road energy use: evidence from low, middle and high income countries. energy policy, 46, 268-277. pradhan, r.p., arvin, m.b., nair, m., bennett, s.e., hall, j.h. (2018), usman, et al.: impact of financial development and economic growth on energy consumption in developing countries of asia international journal of energy economics and policy | vol 13 • issue 3 • 2023 523 the dynamics between energy consumption patterns, financial sector development and economic growth in financial action task force (fatf) countries. energy, 159, 42-53. sadorsky, p. (2010), the impact of financial development on energy consumption in emerging economies. energy policy, 38(5), 25282535. sadorsky, p. (2014), the effect of urbanization on co2 emissions in emerging economies. energy economics, 41, 147-153. safaynikou, h., shadmehri, m.t.a., sabahi, a., razmi, m.j. (2017), modelling the effective factors on bank loans default rate using delphi, sem and tobit techniques (evidence from iran). modern applied science, 11(4), 13-22. sahir, m.h., qureshi, a.h. (2007), specific concerns of pakistan in the context of energy security issues and geopolitics of the region. energy policy, 35(4), 2031-2037. shahbaz, m., khan, s., tahir, m.i. (2013), the dynamic links between energy consumption, economic growth, financial development and trade in china: fresh evidence from multivariate framework analysis. energy economics, 40, 8-21. shahbaz, m., lean, h.h. (2012), does financial development increase energy consumption? the role of industrialization and urbanization in tunisia. energy policy, 40, 473-479. shahbaz, m., benkraiem, r., miloudi, a., lahiani, a. (2017), production function with electricity consumption and policy implications in portugal. energy policy, 110, 588-599. siddique, h.m.a., majeed, m.t. (2015), energy consumption, economic growth, trade and financial development nexus in south asia. pakistan journal of commerce and social sciences (pjcss), 9(2), 658-682. soytas, u., sari, r. (2003), energy consumption and gdp: causality relationship in g-7 countries and emerging markets. energy economics, 25(1), 33-37. squalli, j. (2007), electricity consumption and economic growth: bounds and causality analyses of opec members. energy economics, 29(6), 1192-1205. srivastava, l., misra, n. (2007), promoting regional energy co-operation in south asia. energy policy, 35(6), 3360-3368. suri, v., chapman, d. (1998). economic growth, trade and energy: implications for the environmental kuznets curve. ecological economics, 25(2), 195-208. tiwari, a.k. (2011), a structural var analysis of renewable energy consumption, real gdp and co2 emissions: evidence from india. economics bulletin, 31(2), 1793-1806. wolde-rufael, y. (2009), energy consumption and economic growth: the experience of african countries revisited. energy economics, 31(2), 217-224. xu, j.h., fleiter, t., eichhammer, w., fan, y. (2012), energy consumption and co2 emissions in china’s cement industry: a perspective from lmdi decomposition analysis. energy policy, 50, 821-832. yavuz, n.ç., güriş, b., kıran, b. (2008), the month and holy days effects on the volatility of trade deficit: evidence from turkey. journal of economic and social research, 10(2), 67-84. yoo, s.h., kim, y. (2006), electricity generation and economic growth in indonesia. energy, 31(14), 2890-2899. yoo, s.h. (2005), electricity consumption and economic growth: evidence from korea. energy policy, 33(12), 1627-1632. zachariadis, t., pashourtidou, n. (2007), an empirical analysis of electricity consumption in cyprus. energy economics, 29(2), 183-198. zaman, k., khan, m.m., saleem, z. (2011), bivariate cointegration between energy consumption and development factors: a case study of pakistan. international journal of green energy, 8(8), 820-833. zamani, m. (2007), energy consumption and economic activities in iran. energy economics, 29(6), 1135-1140. ziramba, e. (2009), disaggregate energy consumption and industrial production in south africa. energy policy, 37(6), 2214-2220. . international journal of energy economics and policy | vol 8 • issue 3 • 2018 275 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(3), 275-282. the crude oil price and speculations: investigation using granger causality test saleh mothana obadi1*, matej korcek2 1institute of economic research, slovak academy of sciences, slovakia, 2institute of economic research, slovak academy of sciences, slovakia. *email: ekonbadi@savba.sk abstract this paper examines the up normal move of crude oil prices in the last two decades and tries to relate it with the speculative trading of crude oil in the future markets. the speculators were in the centre of attention during the recent large price moves on the oil market. in this paper we attempted to empirically examine the way, oil speculators operate using the methodology of granger causality. we worked with 4 variables the price of oil brent, number of active oil rigs, weekly changes in crude oil stocks and financial positions of investors. our results show that, on the time period we covered, there exist bidirectional granger causality between oil price and investment positioning of money managers. however we also found the existence of strong granger causality running directly and indirectly from the fundamental indicators (number of oil rigs and oil stocks) towards money managers financial positions on the oil markets. this finding suggests that even if financial investors have impact on the price of oil, their actions are fundamentally sound. keywords: granger causality, oil price, speculation jel classifications: q41, q43 1. introduction the unprecedented surge of crude oil prices in the period 2005–2008 and the sharp decline in the next sixth months after that period has not been caused by fundamentals in the oil market. we are aware of the fact that crude oil prices are one of the most volatile among the prices of all primary commodities. but the huge movement that happened in crude oil prices in the periods 2005–2009, 2010–2012 and 2014–2016 cannot be simply explained by supply and demand. many analysts attributed the sharp move of crude oil price to speculators in the futures markets. indeed, the determinants of crude oil prices are not only supply and demand, but also other factors which directly or indirectly affect the supply or demand and in the end the crude oil price. one of these factors is the speculation in the futures markets. while many analysts, traders and producing or importing countries consider the speculation in the futures markets to be a negative factor for crude oil price development, others sees it as a stabilising factor in the crude oil markets. for instance, according to errera and brwon (2002)…”speculations contribute greatly to the efficient pricing of futures contracts. ultimately, the price of a futures contract must be related to its true value true value that is associated with the cash price and carrying charges. speculators acting in their own self-interest cause the prices of futures contracts to be close to their true worth.” what does the speculation mean? it is legal or illegal activity? of course in our point of view the speculation is legal trading activity in the future market while there are some legislation regulating these activities. whether these trading activities are executed within given ethical standards remains questionable. according to errera and brwon (2002) speculation may be thought of as any risky activity undertaken solely for the purpose profit. given the broad definition, speculation may be divided into two categories position trading and spread trading. position trading consists of outright long or short positions in future contracts. the aim of position trading is to profit from changes in the level of prices of futures contracts. spread trading consists of both a obadi and korcek: the crude oil price and speculations: investigation using granger causality test international journal of energy economics and policy | vol 8 • issue 3 • 2018276 long and a short position in different contracts of the same related commodities. the general definition of speculation is provided in kilian and murphy (2013) who note that anyone buying crude oil not for current consumption, but for future use is a speculator from an economic point of view. the objective of this paper is to identify the role of speculation in futures market by empirically examining the way oil speculators operate using the methodology of granger causality. in other words we tried to examine, whether the general knowledge that attributes still greater share of oil price movements to decisions of these so called money managers is valid. this paper is divided into 6 sections. after the introduction, the second section is about the development of crude oil prices in the last years. the literature review is the content of the third section and is followed by the methodology of our analysis and its results which are in the fourth and fifth sections. 2. development of crude oil market in the last years after two decades of relatively quiet period on the oil markets at the end of 20th century, the interest in oil price developments resurfaced as prices started to experience a steady upward trend at the beginning of this millennium. since 2005, this upward movement became more rapid and then, in the course of 2008, oil prices climbed to unprecedented highs of usd 140 per barrel in july, only to fall dramatically in a very short period of time to a low of us 40 per barrel in december 2008. since the end of 2008, oil prices have picked up again, just to lose momentum in 2013 dropping below 30 usd/bbl in january 2015 and prompting opec and russia into actively managing the oil market starting november 2016. the article analyses the development of oil price during the recent 3 years. these years were characterized by opec actively intervening on the oil market after being relatively quiet during the previous period of high oil prices. the cartel shocked the oil market in 2014 when it announced that, despite a surge of the non-opec supply that had already pushed oil prices down, it would not make any reductions in its production, and the oil prices had dropped significantly. in 2015 opec increased production by 1.56 kbl/d and more than offset the lower output growth in oecd countries caused by lower oil price as well as demand growth. aggregate demand growth in 2015 reached 2 mbl/d, and was accompanied with an 2.9 mbl/d increase in supply, resulting in a price drop from 78.44 usd/bl in november 2014 to 37.72 usd/bl at the end of 2015. during the following year, 2016, a gradual supply-demand balancing of the oil market began. demand for oil increased again by 1.6 mbl/d, but production increased by only 0.4 mbl/d. as in 2015, incremental demand came almost exclusively from oil importers, with india (0.3 mb/d) and europe (0.3 mb/d) having unusually strong growth. on the other side, the growth in demand in china (0.4 mb/d) and the us (0.1 mb/d) was quieter compared to previous year. overall expectations for market reaching supply demand balance have been strengthened in november 2016 by an agreement between opec, supplemented by 10 other producers headed by russia, who have agreed to reduce production by 1.8 mbl/d for 6 months beginning january 2017. in response to this announcement, the average monthly oil prices rose by 16% to 54.07 usd/bbl in december 2016. this growth trend slowly continued during the first two months of 2017, when prices reached their average monthly maximum of 54.89 usd/bbl so far this year. however, during this period, oil market participants notified the production recovery on the us oil market, where the average wti marker price has reached 53.4 usd/bbl, which has stimulated shale oil production. the number of active drilling rigs increased to more than double the minimum of the summer 2016 (662 vs. 316), and us production alone increased three months from the beginning of the opec production constraint by 300 kb/d to 9.1 mbl/d (eia has been projecting an increase in production up to a level of 9.9 mb/d by the end of the year). in addition to the increase in us production, a significant part of the production from libya and nigeria returned to the market, previously disrupted by continuing armed unrests, and these countries were not part of a group that was committed to reducing its production under opec and russia agreement. production of libya has increased from an average of 360 kb/d in december 2016 to june 950 kb/d and nigeria’s production has increased by more than 200 kb/d from december’s 1600 kb/d. this increase in supply, together with the fact that also opec countries that have committed to reduce their production in the beginning of 2017 continued to export stocks stored from the previous periods led to the fact that oil stocks in the united states and oecd countries, which have become the most watched variables even slightly increased. the commercial oil stocks reported by eia grew by 105 mbl in 2015. the growth in 2016 was much more modest with increase of only 28 mbl. and during first half of 2017 only 16 mbl growth in crude oil stocks was seen which represented 44% and 72% decline in growth of crude oil stocks during the same period in years 2016 resp. 2015. during this period oil price went through several periods of sudden and heavy moves which were often attributed to changes in trading positions of hedge funds and other money managers. according to fcc reports they were responsible on average for 25% of the open interest of the market dealing with crude oil trading, ranging from 20 to 30% during the observed period. this translates into 867 thousands crude oil contracts (representing 896 million barrel of oil) they were holding on average (with range from 693 thousands to 1060 thousands of contracts). in other words, on average money managers on daily basis operate roughly with 10 days worth of world oil consumption. for our purposes we did not follow the absolute volumes of barrels held by speculators the ratio of long to short positions (l/s ratio) that better describes the expectations of the market participants. during the 2015 the highest price of oil around 67 usd/bbl from may coincide with the l/s ratio of around 4. after then the expectations supported by stocks build ups led to slump in l/s indicator and fall in oil prices to level of 30 usd/bbl. here the momentum changed and oil speculators gradually built up of their long positions to the level where their ratio topped 3:1 and oil price grew moderately to around 50 usd/ bbl. the significant increase of bullishness of oil speculators then came with the opec announcement of cuts and l/s ratio reached its peak value within the observed period of almost 6 at the end of february. however this happened during the first quarter of obadi and korcek: the crude oil price and speculations: investigation using granger causality test international journal of energy economics and policy | vol 8 • issue 3 • 2018 277 2017 during which crude oil stocks increased by 56.5 mbl which was by 9 mbl more than during 2016 and price of oil did not rise. the bearish fundamentals consequently led do sell off and l/s ratio decreased significantly, reaching just 1.46 at the end our observation period. 3. literature review there is no consensus as to the causes of oil price movements in recent years. a number of studies attributed volatility to such supply and demand factors as turmoil in oil-producing countries, reduced production in some major oil fields, and the growth of demand from china, india, and industrializing middle-income countries (jickling and austin, 2011) and recently the rise of shale oil in the usa. a frequent argument has also been that increasing investment flows from financial investors have affected prices (dicker, 2011). other analysts have sharply criticized those claims. before we commence with the review of the scientific literature on this subject we provide quick glimpse into the workings of the oil future market to provide some background on this subject to the reader. crude oil futures contract is an agreement to buy or sell 1000 barrels of oil at some future date at a price set today. thus, the contract gains or losses value as prices fluctuate1. a long position in futures may be described as a bet that prices will rise; a short position is a bet that they will fall. each futures contract has a long and a short side—whatever one trader gains, the other loses. hedgers use futures not to bet on the price, but to avoid price risk. for example, a long contract in effect provides insurance to an oil refinery against an increase in the price of crude oil. if prices rise, the hedger will pay more for oil on the physical (or “spot”) market, but appreciation in the futures position offsets the price increase. thus, the firm can use futures to lock in the price that prevailed when it entered into its position. in practice nearly all contracts are settled for cash, without either party taking or making delivery. a trader may exit the market at any time by simply purchasing an offsetting position. that is, the holder of a long contract purchases a short contract with the same expiration date. most trading is in the contract expiring soonest, called the front month. some authors note that fundamentals and more specifically increased demand from fast growing developing countries which are accounting for larger and larger shares of annual oil consumption growth are playing an important role (for instance helbling et al., 2008). while some large developing countries have been growing rapidly for years, and in some cases decades, a combination of rapid industrialization and higher commodity intensity of growth, coupled with rapid income per capita growth, has increased significantly their oil demand. calvo (2008) argues that excess liquidity and low interest rates have been contributing to the price increases. low interest rates resulting in the expansion of money supply decreased the demand for liquid assets by sovereigns like china, chile or dubai. both effects 1 a contract to buy oil (called a long contract) gains value if the price rises, because the holder is entitled to buy at the old, lower price. conversely, a short contract requires the holder to sell at today’s price, and gains value if prices fall, because the holder may sell at above the market price. would eventually lead to an increase in prices. but not all prices would move at the same time as some prices are more flexible than others. among the most flexible, according to calvo (2008), are the commodity prices. a similar argument has been made by frankel (2005; 2006). in addition to these more fundamental based explanations, some studies have noted that speculation might also be behind the upward movement in commodity prices. the role of speculators in futures markets has always been a source of both interest and controversy in recent years. the traditional speculative stabilizing theory of friedman (1953) suggests that profitable speculation must involve buying when the price is low and selling when the price is high. the traditional theory predicts that irrational speculators or noise traders, who trade on the basis of irrelevant information, will not survive in the market place. such view is for instance confirmed in lombardi and van robays (2011) who found that speculative trading in futures markets may affect spot oil prices significantly, but their overall importance is limited over time. such views are however being challenged by theories of noise trading, herding behaviour and speculative bubbles. shleifer and summers (1990) and delong et al. (1990) for instance show that noise traders might have an impact on prices if they hold large share of assets regardless of their survival in the long run. such views have gained increasing prominence, due to the coincident rise in crude oil prices and the increased numbers of financial participants in the crude oil futures market from 2000 to 2008. indeed, over the last decade, the volume of trading in financial instruments linked to oil (and in general commodities) has increased sharply on both commodity exchanges and over-the-counter markets. for instance, the open futures positions held by financial traders (hedge funds and non-registered participants) grew sharply from about 45,000 contracts in the second half of 2000, to more than half a million futures in the first 8 months of 2008. as a result, the market share of financial traders has more than doubled, from <20% of all open futures and futures-equivalent option positions in 2000 to more than 40% in 2008. to sum it up, the recent literature points towards several factors which may have driven oil prices upwards. however, at the same time, the literature remains inconclusive as to the relative importance of these factors. in particular, there is no consensus as to the relative weight that should be attributed to speculation versus (i.e., supply and demand) fundamentals in driving oil prices (vansteenkiste, 2011). kilian (2009), kilian and murphy (2012), and baumeister and peersman (2012), used data on oil inventories to identify the speculative demand component of the real oil price. their identification strategy rests on the assumption that unobservable shifts in expectations about future oil prices must be reflected in shifts in the demand for above-ground crude oil inventories their main finding is that speculative demand played only a modest role in the real oil price build up of 2003–08. this result was later confirmed by kilian and lee (2013) and eiloth (2009). juvenal and petrella (2011) instead have found a substantial role for financial speculation (adam et al., 2015; aydogan and berk, 2015; wei and chen, 2016; ojikutu et al., 2017; adam et al., 2018). obadi and korcek: the crude oil price and speculations: investigation using granger causality test international journal of energy economics and policy | vol 8 • issue 3 • 2018278 knittel and pindyck (2013), using a reduced-form approach, assessed whether speculation in (mainly) oil futures markets, as a driver of price changes, is consistent with the data on production, consumption, inventory changes, and spot and futures oil prices (given reasonable assumptions about elasticities of supply and demand). they showed that although they could not rule out the possibility that speculation had any effect on oil prices, speculation as an explanation for the sharp changes in prices could be ruled out for the period since 2004. they argued that, unless one believes that the price elasticities of both oil supply and demand are close to zero (a conjecture initially put forward by hamilton, 2009), the behaviour of inventories and futures-spot spreads are simply inconsistent with the view that speculation was a significant driver of spot prices over that period. across their sample, speculation decreased prices on average or left them essentially unchanged and reduced peak prices by roughly 5%. another strand of the literature has instead focused on a narrower definition of speculation which is mainly related to the possible malfunctioning of commodity financial derivative markets (fama, 1998). masters (2008) blamed the oil price spike of 2007–08 on the actions of investors who bought oil futures not as a commodity to use but as a financial asset. he argued that by march 2008, commodity index trading funds holding a quarter of a trillion u.s. dollars’ worth of futures contracts were able to push the spot price up dramatically—however, he did not provide any coherent testable model. alquist and kilian (2010), liu and tang (2010), and tang and xiong (2010) found a structural break in the spot oil price post-2004. the latter attribute it to institutional investors entering the futures market, which then led the spot price to rise higher, moving more closely with the risk premium of the stock market. to rationalize deviations from fundamentals, singleton (2011) explored the impact of active investor flows and financial market conditions on returns in crude oil futures markets. singleton (2011) showed how financial and informational frictions and the associated speculative activity induce prices to drift away from fundamentals and thus showed increased volatility. he found significant empirical support that financial activities are likely to drive the spot oil price away from fundamental values, primarily through investor flows influencing excess returns from holding oil futures contracts of different maturities. various micro studies using confidential data of the commodities future trading commission, however, have struggled to find evidence that non-commercial players have been able to influence oil price movements (beidas-strom and pescatori, 2014). according to ederington et al. (2011) opec plays an important role in terms of world oil supply. in most macro/global models of the oil market opec supply is a crucial ingredient. opec in principle can influence oil prices by managing production quotas (wirl and kujundzic, 2004; kaufmann et al., 2008) and/or capacity utilization (kaufmann et al., 2004; 2008). kaufmann et al. (2004) study the time series behaviour of real oil prices, opec capacity utilization, opec quotas, the degree to which opec exceeds its production quotas and opec stocks of crude oil. the authors study quarterly data for the period 1986 through 2000 and find the opec related variables granger causes oil prices during the sample period. as such it is probably no surprise that announcements by opec of policy changes are greeted by oil markets much like announcements of u.s. federal reserve policy changes are greeted by financial markets. demirer and kutan (2010) used event study tests to examine the effects of opec announcements on crude oil market activity in the u.s. their sample consists of 63 opec press releases from the period 1983 to 2008. the empirical approach involves the measurement of cumulative daily abnormal log price changes in the spot and futures markets at the time of and around the announcements using chosen benchmarks to estimate conditional expected changes. their findings suggested no significant reaction to opec production increases in either the spot or futures markets. opec announcements of production cuts, however, were associated with significantly negative abnormal returns in the spot and futures markets during the period day +2 to +20, where day 0 is the day of the announcement. opec announcements that maintain the aggregate production quota are associated with negative abnormal returns in the spot and futures markets in the day +2 to +20 periods. kilian and murphy (2010) noted that opponents of the view that speculation caused high oil prices during 2003–2008 often cite a lack of noticeable increases in the rate of inventory accumulation during the same period. however, they pointed out that hamilton (2009) argues that speculative trading can, in theory, influence oil prices without any change in inventories if the short-run price elasticity of oil demand is zero. hamilton observed that existing estimates of this elasticity in the literature are close to zero. baumeister and peersman (2009) analyzed changes in oil market dynamics during 1960–2008. the study is motivated by the fact that volatility in crude oil prices increased considerably during this period, while oil production fell substantially. the focus of the study is identifying the source of this puzzle. to this end, they estimated a time-varying parameter bayesian vector autoregressive model with stochastic volatility in the innovation process. the model identified three types of structural shocks that drive oil prices: oil supply shocks, oil demand shocks caused by economic activity, and demand shocks specific to the crude oil market. the shocks were identified via sign restrictions to allow for the immediate impact shocks on both prices and production that can vary with time. the main finding is that the oil price volatility puzzle can be attributed mostly to a substantial decrease in the price elasticity of oil supply and demand after the mid-1980s. thus, market shocks of the same magnitude generated larger and larger price swings due to the steepening of the supply and demand curves. in addition, the analysis indicated that oil prices adjust rather quickly to their long-run equilibrium levels in response to shocks during the entire sample period a study by guera (2008) which included an analysis of the time series response of a shock to investment (measured as a shock to oil rig activity) found only a slight impact on oil price changes, 8% of variation in price changes. most of the studies that examined the relation between oil rig count changes and oil price changes tended to parameterize the model to test whether expected prices influence oil rig activity, but do not allow for feedback from changes in oil rig activity to changes in prices. a good example of this literature is ringlund et al. (2008) who, like guerra, concluded that a shock to oil prices has a significant immediate impact on oil rig activity. obadi and korcek: the crude oil price and speculations: investigation using granger causality test international journal of energy economics and policy | vol 8 • issue 3 • 2018 279 we intend to look into the influence the oil speculation have on the oil markets especially in the short term period. we tried to estimate the causal link between speculative trading, movements of price of brent oil while investigating for the role of supply demand factors regularly reported on weekly basis that are sharply observed by oil traders specifically eia weekly statistics on the movements of storage in the us and number of active oil rigs in the usa. 4. data and methodology this article works with four basic time series: price of brent oil, the ratio of long to short positions of money managers of futures oil contracts, reported on weekly basis by fcc, the number of active oil rigs in usa reported by baker hughes and changes of weekly oil storage reported by eia. the price of oil is represented by closing price of currently traded front month contract for the day when fcc report is published. we examined the period starting in from 2015 till june 2017 which provided us with dataset of 128 observations. we focused on this period, because we intended to find out the importance of american shale revolution and speculation on the price of oil during the period of opec’s effort of active management of the oil markets. in order to examine the relationship among our variables via pairwise granger causality test, we need to make sure our data are stationary. the objective of unit root test is to empirically examine whether a series is stationary. we applied adf unit root test to determine the order of integration of the variables and, therefore, to provide the time-series properties of data. if the series contains a unit root, this means that the series is non stationary. otherwise, the series will be categorized as stationary. our data were used in the form of first differences of their logarithmic transformations and they were stationary. pair wise causality relationship between variables should be tested through the implementation of standard granger causality test. granger’s (1969) concept of “causality” assumes a different meaning with respect to the more common use of the term. the statement(y) granger causes (x) or vice versa, in fact, does not imply that (y) and (x) is the effect or the result of (y) and (x), but represents how much of the current (y) and (x) can be explained by the past values of (y) and (x) and whether adding lagged values of (y and x) can improve the explanation. for this reason, the causality relationship between (y and x) can be evaluated by estimating the following regressions: m n 1 i t-i j t-j t i=1 j=1 lnx= + x + lny +α β λ ν∑ ∑ n n 2 i t-i j t-j t i=1 j=1 lny= + y + x +α γ δ ε∑ ∑ α1 α2 constants; vt εt white noise; i, j lag length; t time period. following this approach, the null hypothesis that (x) does not granger cause (y) in regression (4) and that (y) does not granger cause (y) in regression (5) can be tested through the implementation of a simple f-test for the joint significance of, respectively, the parameters βi and γi. the above equations were estimated using two lags of each variable which should represent and adequate lag-length over which one series could help to predict the other. 5. results testing for granger causality requires data to be stationary. stationarity in strict sense means that probability distributions of data do not change in the course of time (lukáčiková and lukáčik, 2008). for practical research the time series can be considered stationary when their mean, variance and covariance do not depend on time. economic time series often includes trend and are therefore often nonstationary with respect to mean. if this trend is linear simple first differencing the data will restore stationarity. a logarithm transformation of variables is another useful way to obtain stationary data (lukáčik and pekár, 2006). it is important to cover non-stationary variables into stationary process. otherwise, they do not drift toward long term equilibrium (bekhet and yusop, 2009). we used schwarz information criteria to select the lag length. when considering whether to confirm or reject the null hypothesis of unit root existence we used 5% level of significance (table 1). we used data in their stationary form; therefore we proceeded with the simple pairwise granger causality test. we obtained following results. firstly, at 5% level of significance we found that investments of money managers influenced price of oil (at 10% significance level we even observed bidirectional causality) meaning that price speculations actively influenced price of oil and to a lesser extent these investment decisions where driven by the price oil itself which would suggest money managers used trend following techniques in their investment decisions (table 2). however our analysis revealed existence of interesting interrelations of observed variables. the first intuitive, although important, conclusion of our examination is existence of bidirectional causality between number of oil rigs and oil stocks. this can be simply understood as that higher employment of oil rigs will lead to higher oil production and consequently higher stocks. or looking from a different perspective, low oil stocks could be reason for higher drilling effort. the other important finding is the speculations of money managers (expressed by our long to short ratio of future positions) seemed to be granger caused by changes of crude oil stocks. this chain of causalities brought us to conclusion, that the investments of money managers can at least indirectly (via changes in crude oil stocks) granger causes the price of oil. apart from that, we found on 10% level of significance a causality running from number of oil rigs and changes in stocks directly towards oil price which could be identified as further confirmation of our previous results. to sum it up, it can be stated that the price of oil is granger caused by speculation of various investors, but these decisions about these speculations are to large extent driven by the fundamentals table 1: results of adf unit root test variable adf test t-stat p-value brent −12.13562 0.0000 lsratio −8.160941 0.0000 oilstocks −14.10479 0.0000 oilrigs −3.024819 0.0354 source: authors calculations obadi and korcek: the crude oil price and speculations: investigation using granger causality test international journal of energy economics and policy | vol 8 • issue 3 • 2018280 on actual oil markets, which basically confirms the claim that the of financial investors is to help markets to function efficiently. 6. conclusion the price speculators were in the centre of attention during the recent large price moves on the oil market. this is understandable as investment, index and hedge funds become integral part of modern oil trading, even replacing the traditional international oil companies in its role of most important players on this market. in our paper we tried to examine, whether the general knowledge that attributes still greater weight of oil price movements to decisions of these so called money managers is valid. in our article we used the methodology of pair wise granger causality, which enabled us to determine the direction of causality among individual available variables. in this article we worked with 4 variables the price of oil brent, number of active oil rigs, weekly changes in crude oil stocks and financial positions of investors. we chose to focus on the data that are closely observed by market participants on weekly basis, as they represent the most reliable description of fundamentals on the oil market. the results of our calculations show that on the time period we covered that there is bidirectional granger causality between oil price and investment positioning of money managers. this would suggest that money managers are not only causing but also following oil price trends in order to make profit and in this way they exaggerate the range of oil price moves. however we also found the existence of strong granger causality running directly and indirectly from the fundamental indicators (number of oil rigs and oil stocks) towards money managers financial positions on the oil markets. this finding proves that even if financial investors have impact on the price of oil, their actions are fundamentally sound in other words, they basically help to the price of oil to accurately express the immediate state of oil market fundamentals. nevertheless do not infer the moves in oil price are not stronger than they were had the positions of oil speculators were of lesser significance. 7. acknowledgment this paper is supported by the research projects apvv-15-0666 and vega 2/0005/16. source: authors based on various data collected by reuters figure 1: in response to this announcement, the average monthly oil prices rose by 16% to 54.07 usd / bbl in december 2016. figure 2: during the 2015 the highest price of oil around 67 usd/bbl from source: authors based on various data collected by reuters obadi and korcek: the crude oil price and speculations: investigation using granger causality test international journal of energy economics and policy | vol 8 • issue 3 • 2018 281 references adam, p., rianse, u., cahyono, e., rahim, m. (2015), modeling of the dynamics relationship between world crude oil prices and the stock market in indonesia. international journal of energy economics and policy, 5(2), 550-557. adam, p., rosnawintang, r., tondi, l. (2018), the causal relationship between crude oil price, exchange rate and rice price. international journal of energy economics and policy, 8(1), 90-94. alquist, r., kilian, l. (2010), what do we learn from the price of crude oil futures? journal of applied econometrics, 25(4), 539-573. aydogan, b., berk, i. (2015), crude oil price shocks and stock returns: evidence from turkish stock market under global liquidity conditions. international journal of energy economics and policy, 5(1), 54-64. baumeister, c., peersman, g. (2009), sources of the crude oil market volatility puzzle, working paper, bank of canada and ghent university. baumeister, c., peersman, g. (2012), the role of time-varying price elasticities in accounting for volatility changes in the crude oil market. journal of applied econometrics, 28(7), 1087-1109. beidas-strom, s., pescatori, a. (2014), oil price volatility and the role of speculation. imf working paper, wp/14/218, december 2014. bekhet, a.h., yusop, m.y.n. (2009), assessing the relationship between oil prices, energy consumption and macroeconomic performance in malaysia: co-integration and vector error correction model. in international business research, 2(3), 152-175. breitenfellner, a., cuaresma, j.c., keppel, c. (2009), determinants of crude oil prices: supply, demand, cartel or speculation? monetary policy and the economy. calvo, g. (2008), exploding commodity prices, lax monetary policy, and sovereign wealth funds. voxeu. 20 june. available from: http:// www.voxeu.org/index.php?q=node/1244. delong b.j., shleifer, a., summers, l.h., waldman, r.j. (1990), noise trader risk in financial markets. journal of political economy, 98(4), 703-738. demirer, r., kutan, a. (2010), the behavior of crude oil spot and futures prices around opec and spr announcements: an event study perspective. energy economics, 32, 1467-1476. dicker, d. (2011), oil’s endless bid: taming the unreliable price of oil to secure our economy. hoboken, n.j.: john wiley & sons. ederington, l.h., fernando, c.s., lee, t.k., linn, s.c., may, a.d. (2011), factors influencing oil prices: a survey of the current state of knowledge in the context of the 2007-08 oil price volatility. washington, dc: u.s. energy information administration. p20585. einloth, j. (2009), speculation and recent volatility in the price of oil. division of insurance and research. washington, dc: federal deposit insurance corporation. errera, s., brown, s.l. (2002), fundamentals of trading energy futures and options. 2nd ed. usa: penn well corporation. fama, e.f. (1998), market efficiency, long-term returns, and behavioral finance. journal of financial economics, 49(1998), 283-306. fattouh, b., kilian, l., mahadeva, l. (2013), the role of speculation in oil markets: what have we learned so far? the energy journal, 34(3), 1-11. frankel, j.a. (2005), why commodity prices so high? don’t forget low interest rates. financial times. 4/15/05. frankel, j.a. (2006), the effects of monetary policy on real commodity prices. nber working paper number 12713. friedman, m. (1953), the case for flexible exchange rates, in essays in positive economics, chicago: university of chicago press. p157-203. granger, c.w.j. (1969), investigating causal relations by econometric models and cross spectral methods. in econometrica, 37(3), 424-438. guera, s. (2008), long run relationship between oil prices and aggregate oil investment: empirical evidence, working paper, united states association of energy economists. hamilton, j.d. (2009), causes and consequences of the oil shock of 2007-2008, brookings papers on economic activity. brookings. edu: spring. p215-261. hamilton, j.d. (2009), understanding crude oil prices. energy journal, 30, 179-206. helbling, t., mercer-blackman, v., cheng, k. (2008), riding a wave. finance and development march. available from: http://www.imf. org/external/pubs/ft/fandd/2008/03/pdf/helbling.pdf. jickling, m., austin, d. (2011), hedge fund speculation and oil prices. congressional research service. hoboken, new jersey: john wiley & sons, inc. juvenal, l., petrella, i. (2011), speculation in the oil market, working papers 2011-2027, federal reserve bank of st. louis. kaufmann, r.k., bradford, a., belanger, l.h., mclaughlin, j.p., miki, y. (2008), determinants of opec production: implications for opec behaviour. energy economics, 30, 333-351. kilian, l. (2009), not all oil price shocks are alike: disentangling demand and supply shocks in the crude oil market. american economic review, 99(3), 1053-1069. kilian, l., lee, t. (2013), quantifying the speculative component in the real price of oil: the role of global oil inventories, from understanding commodity market fluctuations, imf-oxford conference, washington d.c. march, 2013, and forthcoming in the journal of international money and finance. kilian, l., murphy, d. (2010), the role of inventories and speculative trading in the global market for crude oil, working paper, center for economic policy research and university of michigan at ann arbor. kilian, l., murphy, d. (2012), why agnostic sign-restrictions are not enough: understanding the dynamics of the oil market var models. table 2: pairwise granger causality test results null hypothesis f-statistic p-value l_s_ratio does not granger cause brent 4.10860 0.0188 brent does not granger cause l_s_ratio 2.77311 0.0665 oil rigs does not granger cause brent 2.75550 0.0677 brent does not granger cause oil rigs 0.63058 0.5341 stocks does not granger cause brent 2.60761 0.0780 brent does not granger cause stocks 0.27870 0.7573 oil rigs does not granger cause l_s_ratio 0.15650 0.8553 l_s_ratio does not granger cause oil rigs 0.57489 0.5644 stocks does not granger cause l_s_ratio 4.04758 0.0200 l_s_ratio does not granger cause stocks 0.06423 0.9378 stocks does not granger cause oil rigs 3.42292 0.0359 oil rigs does not granger cause stocks 3.12103 0.0478 source: authors calculations obadi and korcek: the crude oil price and speculations: investigation using granger causality test international journal of energy economics and policy | vol 8 • issue 3 • 2018282 journal of european economic association, 10(5), 1116-1188. knittel, c.r., pindyck, r.s. (2013), the simple economics of commodity price speculation, nber working paper series, no. 18951. lombardi, m.j., van robays, i. (2011), do financial investors destabilize the oil price? ecb working paper no. 1346, june 2011. liu, p., tang, k. (2010), bubbles in the commodity asset class: detection and sources, ssrn elibrary (ssrn). lukáčik, m., pekár, j. (2009), kointegračná analýza v ekonometrii. bratislava: fakulta hospodárskej informatiky. lukáčiková, a., lukáčik, m. (2008), ekonometrické modelovanie s aplikáciami. bratislava: ekonóm. masters, m.w. (2008), testimony before the committee on homeland security and governmental affairs united states senate, the 2008 commodities bubble: assessing the damage to the united states and its citizens, special report. available from: http://www.hsgac. senate.gov//imo/media/doc/052008masters.pdf?attempt=2. ojikutu, o. t., onolemhemhen, r. u., isehunwa, s.o. (2017), crude oil price volatility and its impact on nigerian stock market performance (1985-2014). international journal of energy economics and policy, 7(5), 302-311. reuters eikon is dedicated paid platform providing the data on energy related issues. ringlund, g.b., rosendahl, k.e., skjerpen, t. (2008), does oil rig activity react to oil price changes? an empirical investigation, energy economics, 30, 371-396. shleifer, a., summers, l. (1990), the noise trader approach to finance. the journal of economic perspectives, 4(2), 19-33. singleton, k.j. (2011), investor flows and the 2008 boom/bust in oil prices. stanford, california: graduate school of business, stanford university. tang, k., xiong, w. (2010), index investment and financialization of commodities, nber working papers, national bureau of economic research, inc. u.s. commodity futures trading commission. (2008), available from: http://www.cftc.gov/index.htm. vansteenkiste, i. (2011), what is driving oil futures prices? fundamentals versus speculation. ecb working paper series no. 1371, august 2011. wei, c.c., chen, s.m. (2016), examining the relationship of crude oil future price return and agricultural future price return in us. international journal of energy economics and policy, 6(1), 58-64. wirl, f., kujundzic, a. (2004), the impact of opec conference outcomes on world oil prices (1984-2001), energy journal, 25, 45-62. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(4), 259-269. international journal of energy economics and policy | vol 8 • issue 4 • 2018 259 climate policy integration on the national and regional level: a case study for austria and styria claudia kettner1*, daniela kletzan-slamanig2 1austrian institute of economic research (wifo), arsenal, objekt 20, 1030 vienna, austria, 2austrian institute of economic research (wifo), arsenal, objekt 20, 1030 vienna, austria. *email: claudia.kettner@wifo.at abstract many climate-relevant decisions are taken in other policy areas with only little regard to climate change impacts. in order for climate policy to be successful it has to be integrated in decision-making and legislative processes in basically all policy areas and all levels of government. we analyse the extent of climate policy integration (cpi) in austrian policy-making via in-depth expert interviews, both on the federal level as well as on the regional level using styria as case study. the results show a broad range of perceptions regarding the degree of cpi in austria. the consideration of climate policy issues generally depends on the core competence of the respective institution. moreover, we found widely diverging views on whether cpi in austria is too ambitious or too weak. especially, potential negative impacts of climate policy on competitiveness or employment are seen to hamper a more ambitious implementation of mitigation policies. keywords: climate policy integration, austria, survey jel classifications: c83, q48, q54, q58 1. introduction climate change represents the most exigent environmental problem our societies face. according to a special eurobarometer survey (ec, 2017) 92% of the european population recognise climate change as a serious problem, 74% even consider it as very serious. the rise by 5 percentage points compared to the previous survey in 2015 suggests an increasing consensus about the importance of the issue. for austria specifically, 68% regard climate change as a very serious problem. when asked to name the single most serious problem facing the world, climate change ranks third (after poverty, hunger and lack of drinking water and international terrorism), with 43% of eu citizens (50% of austrian citizens1) considering it as one of the most serious global problems. almost half of the europeans (60% of austrians) report that they have personally taken action to reduce emissions. but four out of ten citizens state that the responsibility for tackling climate change lies mainly with national governments (43%), the eu (39%) and business and industry (38%). moreover, as of 2017 22% of the 1 this figure declined by three percentage points compared to 2015 results. population state that they are personally responsible and one in five say that all actors are responsible for tackling climate change. somewhat divergently, austrians see the main responsibility for tackling climate change with business and industry (49%) followed equally by the eu and the austrian government (45% each). in order to successfully limit climate change it has to be recognised that climate policy is a cross-cutting issue that needs to be firmly integrated into general and sector-specific policy areas that frame economic activity and societal development (kok and de coninck, 2007; ahmad, 2009; mickwitz et al., 2009; kettner et al., 2015). many climate-relevant decisions are taken in conventional areas with only little regard to climate change impacts. the main targets and the general framework for climate policy are defined at eu level. the specific implementation and choice of instruments is, however, mainly decided at the level of member states2. the eu aims at cutting its greenhouse gas (ghg) emissions compared to 1990 by 20% by 2020 and by 2 one exception is the eu ets, the emission trading scheme for industry and energy supply. kettner and kletzan-slamanig: climate policy integration on the national and regional level: a case study for austria and styria international journal of energy economics and policy | vol 8 • issue 4 • 2018260 40% by 2030 respectively (com (2008) 30; com (2014) 15); for 2050 a reduction of 80% is envisaged (com (2011) 112). the corresponding short and medium term targets for austria were defined in the effort sharing decisions (decision 406/2009/ec, com (2016) 482) and imply a reduction target of 16% for 2020 and a proposed reduction of 36% for 2030 compared to 2005 in sectors not included in the eu ets. climate policy in austria is characterised by a wide range of policy instruments including regulatory requirements, economic instruments (mostly subsidies) and awareness-raising campaigns targeting different groups, sectors or activities. given the cross-cutting nature of climate policy the institutional responsibilities are fragmented not only between various ministries (and executing agencies) but also between the federal government and the regional authorities. the provinces (bundesländer) play an important role in climate policy in austria as some climate-relevant issues (e.g., spatial planning, housing subsidies and building regulations) are in their jurisdiction. in order for climate policy to be successful, the objective of reducing greenhouse gas emissions or avoiding rising emissions as unintended side effects of other (non climate) policy interventions has to be integrated in decision-making and legislative processes in basically all policy areas and all levels of government, which is referred to as climate policy integration (cpi) in the literature (e.g., mickwitz et al., 2009; dupont and oberthür, 2011). the assessment of cpi is a rather new research area. applied studies on cpi have been conducted for the eu level as well as for the national level. on eu level a number of studies have addressed cpi in sectoral policies, i.e., energy, water and biodiversity policies as well as in terms of the allocation of eu funds (dupont and oberthür, 2012; dupont and primova, 2011; brouwer et al., 2013; dupont, 2010; hanger et al., 2013; kettner et al., 2012). on the national level, research on cpi so far has concentrated on germany (beck et al., 20093; jacob and kannen, 2015a; b), finland (kivimaa and mickwitz, 20093; lyytimäki, 2011), the netherlands (bommel and kuindersma, 20083; van den berg and coenen, 2012) and denmark (wejs, 2014). these analyses generally show that while climate aspects are widely integrated in – especially high-level – policy strategies at member state level, “political commitment to climate change mitigation has a rather low impact on everyday policy-making” (jacob and kannen, 2015b). federalism generally seems to constrain the integration of climate aspects in other policy areas and coordination between the federal and the regional levels is often insufficient (e.g., steurer and clar, 2014a; jacob and kannen, 2005b). for austria cpi has been assessed by steurer and clar (2014a; b) and niedertscheider et al. (2018). steurer and clar (2014a; b) analysed the integration of climate change mitigation issues in building policies. they discuss the role of federalism for austria’s mitigation performance finding that federalism 3 this study has been conducted in the peer project, where mickwitz et al. (2009) analysed climate policy integration in different eu member states and policy sectors as well as in a selection of case study regions and municipalities using five criteria (inclusion, consistency, weighting, reporting and resources). constrained cpi by adding “a vertical dimension to an already complex horizontal integration” (steurer and clar, 2014a). the federal structure of austria is, however, found to be only one of many factors constraining climate change mitigation in austria. niedertscheider et al. (2018) evaluate the level of cpi in austria since 1990, discussing climate change mitigation measures like the introduction of relevant institutions or legislative acts against the background of other (frequently short-term) drivers of ghgemissions. the analysis suggests that short-term socio-economic events like the financial crisis and climate events such as mild or cold winters exceeded the effects of climate policies on emissions. yet, the effects of policies were more difficult to detect since they happened within longer time-frames and in conjunction with indirect climate change mitigation effects. in this paper we aim at contributing to the research on cpi on member state level focussing on austria. we analyse the degree of cpi in austrian policy-making via in-depth expert interviews. for our survey on cpi at the federal level we contacted representatives from the federal ministries involved in climate policy-related issues or affected by climate policy decisions as well as from special interest groups and other relevant stakeholders. for the analysis of cpi on the regional level we chose styria as case study region and conducted interviews with relevant stakeholders and officials from the regional administration. the objective of the in-depth interviews was to obtain an overall impression from the point of view of various stakeholders regarding the quality of administrative cooperation on climate-related issues as well as the degree of cpi in austria’s policy-making. the paper is structured as follows. in section 2 the methodological approach chosen to analyse cpi in austria and styria is set out. section 3 describes the results on national and provincial level. the final section concludes the paper. 2. methods cpi can be regarded as a continuation and advancement of approaches for environmental policy integration (epi) in the 1980s and 1990s that aimed at contributing to the reduction of environmental problems and guiding the transition to sustainable development (adelle et al., 2009; jordan and lenschow, 2010).4 epi refers to the integration of environmental aspects and policy objectives into sector policies like energy and agriculture (adelle et al., 2009)5. based on the definition for epi by lafferty and hovden (2003) cpi can be defined as6: • the incorporation of the aims of climate change policy objectives into all stages of policy-making in all relevant policy sectors; • complemented by an attempt to aggregate expected consequences for climate change mitigation and adaptation 4 for a discussion of the relation of epi and cpi see adelle and russel (2013). 5 however, this policy-making “principle” has not been unambiguously defined, neither in its normative sense nor in how it can be implemented in the political practice (jordan and lenschow, 2010). 6 this definition is also followed by dupont and oberthür (2011) and mickwitz et al. (2009). kettner and kletzan-slamanig: climate policy integration on the national and regional level: a case study for austria and styria international journal of energy economics and policy | vol 8 • issue 4 • 2018 261 into an overall evaluation of climate policy, and a commitment to minimise contradictions between climate policies and other policies. according to this definition climate policy objectives are given priority in decisions in conventional policy areas7 and the integration should be reflected in general and sector-specific policy strategies as well as applied instruments and ideally in policy outcomes, i.e., a reduction of ghg emissions (mickwitz et al., 2009). key features of policy integration are “policy coherence” and “policy coordination.” policy coherence refers mainly to policy output and outcome8, i.e., the promotion of synergies and mutually reinforcing policy actions (win-win-solutions) such that non-conflicting, consistent incentives are provided by different policies (mickwitz et al., 2009; dupont and oberthür, 2011; kok and de coninck, 2007). policy coordination in turn emphasises the policy process that brings about policy coherence, i.e., the development of policies and programmes (for climate policy and other sectoral areas) that minimise redundancy, incoherence and lacunae (peters, 1998). policy integration can be analysed from different angles, i.e., within or across government levels (figure 1). horizontal cpi focuses on mainstreaming climate policy objectives into other sectoral policy areas on one level of government (e.g., directorates-general on eu level, federal ministries). vertical cpi, in contrast, takes a topdown approach and focuses on mainstreaming throughout multiple levels of government and policy-making (e.g., from eu directives to national implementation to local or regional implementation). in this paper we analyse the extent of cpi in austrian policymaking via the method of expert interviews. in a first step we identified the federal ministries with competencies that affect climate change mitigation (e.g., transport, economic affairs including energy) or are affected by climate policy decisions (e.g., consumer protection). the material linkage between climate policy and other policy areas is inherently more pronounced in some areas such as energy policy than in others like foreign policy. in addition, we included special interest groups (austrian economic chambers, chamber of labour, austrian trade union federation, federation of austrian industries) and other relevant stakeholders (e.g., the austrian environment agency) in the group of interviewees. the objective of the in-depth interviews was to obtain an overall impression from the point of view of various stakeholders in order to evaluate the degree of cpi in austria’s policy-making. table 1 summarises the institutions that were chosen for the interviews. 7 dupont (2010) argues that giving climate policy principles priority over other non-environmental policy areas is justified, while within environmental policy synergies and avoiding conflicts with other environmental objectives should be emphasised. 8 policy output refers to action taken by the administration in pursuance of policy decisions, i.e., the definition of regulation like standards, marketbased incentives, etc., in order to influence the target group’s behaviour. policy outcomes refer to societal consequences of an implemented policy, i.e., the actual, observable change in behaviour, which, however, are less tangible and can also be influenced by other factors as well. for the analysis of cpi on the regional level we chose styria as case study region. the rationale for the selection is that styria is the region in austria that achieved the largest emission reduction in the period 1990 to 20159. as on the national level, the evaluation of cpi on the regional level is based on in-depth interviews with relevant stakeholders and decision-makers (table 2). a total of 23 interviews were conducted between august and december 2017. the distribution between federal ministries, regional administration, special interest groups and other stakeholders is shown in figure 2. the interviews consisted of three parts. the first part dealt with the personnel resources dedicated to climate policy issues in each institution and the internal cooperation in this context. the second part concerned the cooperation with other institutions (administration and stakeholders). the third part included questions concerning cpi and the general relevance of climate policy as compared to other policy objectives. furthermore, questions regarded the consideration of climate effects in designing policy instruments as well as the way in which trade-offs and conflicts are dealt with, i.e., how decisions are reached in cases of 9 latest year available. only three provinces achieved a reduction of co2 emissions over this period (styria, lower austria and vienna). in styria emissions have been reduced most strongly in the household sector, but also in energy supply. see uba (2017). table 1: interview partners at the federal level federal administration bka federal chancellery bmeia federal ministry of europe, integration and foreign affairs bmlfuw federal ministry of agriculture, forestry, environment and water management bmvit federal ministry for transport, innovation and technology bmf federal ministry of finance bmwfw federal ministry of science, research and economy bmask federal ministry of labour, social affairs and consumer protection interest groups iv federation of austrian industries wko austrian economic chambers ak austrian chamber of labour ögb austrian trade union federation relevant stakeholders eaa environment agency austria aea austrian energy agency klien climate and energy funds table 2: interview partners at the regional level regional administration a13 department of environment and spatial planning a15 department of energy, housing and technology a16 department of transport and provincial building infrastructure relevant stakeholders eas energy agency styria kettner and kletzan-slamanig: climate policy integration on the national and regional level: a case study for austria and styria international journal of energy economics and policy | vol 8 • issue 4 • 2018262 conflicting interests. the respective interview outlines are included in the supplementary material. 3. results 3.1. austria 3.1.1. personnel resources personnel resources for climate issues differ strongly between austrian ministries; while in some cases only single persons are in charge of these issues, in other cases whole departments are responsible for climate-related issues. staff members working on climate policy or related issues are employed on different organisational levels (administrative staff, head of department, etc.,). in general, however, more than one department is – at least indirectly – involved in climate policy-making. the variations in personnel resources and the respective hierarchy level that is responsible also reflect the heterogeneous role of the topic for the particular ministries, i.e., it depends on the core responsibilities of the respective ministry – e.g., climate policy as a key area in the environment ministry versus functions only loosely related to or influenced by climate policy like consumer protection for instance. in individual sections of the same ministry the perception regarding the importance of climate policy can differ substantially. also with respect to austrian business/industry and labour organisations (social partners) pronounced differences in the personnel resources for climate policy related issues can be found. this reflects also the diversity in the tasks the respective organisations have to fulfil, ranging from the coordination of opinions among members in the context of legislative consultation procedures to the work as think tank. in addition, it reflects the awareness regarding the importance of climate policy as well as the institution’s perception regarding its role or influence in this issue. 3.1.2. cooperation 3.1.2.1. cooperation within ministries internal cooperation in climate policy-related issues is differently organised in the ministries and departments, i.e., as informal exchange or in institutionalised meetings or processes (e.g., regular jour fixes etc.). the degree of institutionalisation in climate policy cooperation varies between ministries. moreover, climate and energy issues often lie in the competence of different departments or sections. communication and cooperation within the ministries is generally perceived to be good or very good by the officials, with some exceptions (figure 3). 3.1.2.2. cooperation between ministries as a cross-cutting issue, climate policy related matters are in the responsibility of various ministries, which need to cooperate, e.g., for determining the austrian position on eu legislative proposals. in austria, the federal ministry of agriculture, forestry, environment and water management (bmfluw) is legally responsible for climate policy issues, but climate-related issues are distributed across several ministries (energy policy, for instance, lies in the responsibility of the federal ministry of science, research and economy, bmwfw)10. the collaboration of federal ministries is partly related to concrete tasks (statements in legal consultation processes, preparation for council working groups) and informal (in informal meetings or via phone calls, emails, 10 it has to be noted that after the completion of the interviews and following the formation of a new government the allocation of responsibilities between ministries was shifted and ministries are now named differently e.g., the ministry of agriculture, forestry, environment and water management is now the ministry of sustainability and tourism. it was also assigned the responsibility for energy policy. following this rearrangement of competences the aggregation of climate and energy policy in one ministry offers scope for more integrated policy-making. source: own illustration adapted from kettner et al. (2012) figure 1: horizontal and vertical policy integration figure 2: distribution of interviews by institution kettner and kletzan-slamanig: climate policy integration on the national and regional level: a case study for austria and styria international journal of energy economics and policy | vol 8 • issue 4 • 2018 263 etc.,). partly the cooperation occurs in formalised committees (high level group for energy and climate policy, steering group of the austrian integrated climate and energy strategy (ikes), climate council, coordination panel clean energy in transport) and theme-specific technical working groups. cooperation in climate policy issues between the ministries was generally rated as being good by the interviewees (figure 3). nevertheless, the quality of inter-ministerial cooperation was judged differently in individual departments. interests of the ministries are diverging strongly in some areas, which is also reflected in the perceived quality of their cooperation. in addition, some officials, lobbyists and stakeholders considered individual ministries to be strongly influenced by various lobbying interests. conflicting interests were frequently seen to be a source of blockades, resulting e.g., in problems in the implementation of eu directives in austria. between some ministries respondents reported a high level of distrust, hampering everyday collaboration. however, it was frequently stated that the quality of cooperation strongly depends on the persons involved, on the one hand, and that there can be large differences between informal exchanges and contacts under formal, institutionalised circumstances, on the other hand. potential adverse effects on competitiveness and employment are arguments frequently used against climate policy. as regards content, the cooperation between ministries was often rated difficult due to the conflicting interests, while in many cases it was rated good on the personal level. especially at the technical or administrative level, the exchange is found to be strong; on the political level it depends on the individual ministers’ commitment. one respondent felt that the flow of information was not optimal, that information was withheld or decisions were taken in his absence and without involving his ministry respectively. however, the quality of cooperation between the individual ministries was perceived to have altered over time. after the paris agreement (unfccc, 2015) and due to activities on eu level (climate targets, legal framework), climate policy was being increasingly perceived as important and generally moves up on the political agenda. on ministerial level and in actual policy-making, many interviewees felt that climate policy receives only little attention. the lack in commitment by the decision-makers was also seen to translate into a lack of overall coordination or integrated energy and climate policy strategy. regarding the conflicts of interest mentioned, it remains to be seen whether the formal integration of energy policy in the ministry responsible for climate policy (federal ministry of sustainability and tourism) will also improve the integration in actual policymaking and help resolve some of the perceived barriers for climate policy implementation. 3.1.2.3. cooperation between ministries, social partners and other stakeholders in austria industry and labour representatives (ilrs; mostly social partners) are involved in formal processes dealing with climate policy such as the ikes as well as in legislative consultation processes. in addition, many ministry departments also have informal contacts and exchange with the lobbying groups. some stakeholders were found to be closely linked with particular ministries due to overlapping interests or more formal links11. conflicts of interest between climate policy issues and other goals are again most strongly perceived in the areas of competitiveness and employment, i.e., more stringent climate policy might reduce firms’ cost competitiveness and lead to carbon leakage, implying also job losses, as well as in distributional impacts. conflicting or synergetic objectives are reflected in the perceived quality of the cooperation, as well as in the degree of trust between the parties. some respondents thought of interest groups as “gatekeepers” with particular interests, noting that they are caught in their 11 the federal environment agency for instance performs tasks in public interest on behalf of the environment ministry. figure 3: perceived quality of cooperation between federal ministries, interest groups and other stakeholders source: own calculations. for the evaluation of the quality of cooperation, the experts could choose between the categories very good (1), good (2), not so good (3) and poor (4) kettner and kletzan-slamanig: climate policy integration on the national and regional level: a case study for austria and styria international journal of energy economics and policy | vol 8 • issue 4 • 2018264 lobbying work and would communicate only the lowest common denominator of their members, but not deliver any concrete suggestions for solutions. 3.1.2.4. cooperation between business/industry and labour representatives in the context of climate policy, positions of industry and labour representatives may be consistent or diverging. in general, social partners may have similar positions regarding labour and economic growth, i.e., a coalition of social partners “under the keyword jobs” can be perceived. issues without a common basis are often excluded from the discussions between different interest groups and if the positions of the groups do not match, no common statements are drafted. cooperation is more intense between organisations representing the same interests (e.g., business and industry representatives) as compared to cooperation between employers’ and the employees’ organisations. 3.1.3. cpi and weighting of climate targets 3.1.3.1. relevance of climate policy compared to other targets most respondents thought that the general awareness in the administration for climate change has increased during the last years, also as a result of the 2015 paris agreement, even though one interviewee pointed out that climate policy issues today are less relevant than prior to the economic crisis. nevertheless, according to the officials involved directly in climate policy, the awareness in some departments or sections remains low. it was noted that the austrian climate and energy policy agenda to a large extent is determined by the eu; this was often seen positively as important driver for austrian policy-making. some ministries, however, criticised that the eu policy framework has a stronger focus on climate issues, including quantitative targets, as compared to other policy targets such as economic growth. there are considerable differences between the interviewees regarding the perceived relevance given to climate policy targets as compared to other policy targets in austria ranging from too low to exaggerated: on the one hand, other objectives were regarded to be of higher priority and climate issues was considered by tendency to be subordinated to the “core issues” of the ministries. on the other hand, it was stressed that conflicts of interest between climate policy and other policy targets have to be bridged and that all policy goals should have the same relevance without giving priority to climate issues. another respondent noted that generally specific goals were negotiated, without any clear priorisation and no integrated policy approach was taken. according to the majority of officials hence there is scope to increase the weight given to climate policy compared to other policy targets (figure 4). a l l i n t e r v i e w e e s f r o m b u s i n e s s / i n d u s t r y a n d l a b o u r representatives reported that climate policy gained in importance in their institutions, in some it is now also dealt with at management level. the conceived level of relevance varies, however, among the organisations. moreover it was noted that the organisation’s awareness depends on the current level of concern of the represented clientele. compared to the ministry officials and stakeholders, the interest groups, however, perceived that a higher weight is given to climate policy as compared to other policy targets. they called for an integrated, balanced approach to climate policy taking particularly competitiveness and employment concerns into account. the lobbying groups found both, synergies and conflicts between climate policy and other objectives. in the short term conflicts dominate, while in the long term synergies become more relevant. the development of public transport, thermal retrofitting as well as research, development and innovation were named as the most relevant synergetic fields, while competitiveness concerns, employment, distribution and taxes were among the conflicting areas. target conflicts could be solved through technical and socioeconomic innovations as well as research policy, including the promotion of applied research. the stakeholders like the federal environment agency or the austrian energy agency have the most critical view on the relevance of climate policy compared to other policy targets. they noted that so far no national targets have been developed (in addition to those derived from eu legislation), that the integrated energy and climate strategy has still not been published (thus leading to a lack of a comprehensive framework for policy or investment decisions on national level) and that the issue of climate change has no relevance at government level. on the contrary, they stated that while climate policy in principal is embedded in the austrian policy landscape, the importance of the issue has declined markedly since the economic and financial crisis. 3.1.3.2. degree of cpi in austria the different groups of interviewees shared a quite common opinion on the degree of cpi in austria and saw potential for improvement (figure 4). with respect to the perceptions of ministry officials and industry and labour representatives, however, a larger spread is observed. in both groups, at least some of the interviewees stated that climate policy is only poorly integrated into the overall policy landscape in austria, while some thought that the degree of cpi is neither particularly high nor notably low. as a final question the interviewees were asked to name what in their opinion would be a prerequisite for a successful climate policy in austria. the answers largely fell into four categories: first, several respondents emphasised the importance of taking a comprehensive, systemic approach to climate policy, considering synergies as well as conflicts and increasing cpi. a second line of answers regarded the institutional framework – arguing that a state secretary for climate policy or climate protection in constitutional rank would increase the weight given to this issue. most prominent was, however, the demand for drafting the ikes as soon as possible in order to put climate policy targets beyond question and define a comprehensive and long-term framework for national measures. furthermore, the discussions regarding climate policy should be more evidence-based instead of ideological and take into regard the scientific foundation. finally, concerning the implementation of climate policy the actual measures should ensure the achievement of targets. climate policy should also be understood to offer chances, especially when there is a focus on r&d and innovation. but also fiscal instruments were regarded as essential part of the instrument mix. kettner and kletzan-slamanig: climate policy integration on the national and regional level: a case study for austria and styria international journal of energy economics and policy | vol 8 • issue 4 • 2018 265 3.2. case study styria 3.2.1. organisational structure of the regional administration in climate policy issues also for the case study region styria the interview partners were chosen from those departments and units of the public administration that are directly or indirectly involved in climate policymaking on the regional level. climate policy-related issues in this austrian province are generally dealt with in two larger departments, a15 “energy, housing and technology” and a16 “transport and provincial building infrastructure.” the first department comprises competencies on energy issues, housing subsidies as well as climate policy issues in a narrow sense. a16 in turn is responsible for transport related issues (including transport infrastructure and e-mobility) as well as the public building infrastructure in styria. additional climate policy-related issues lie in the responsibility of department a13 “environment and spatial planning.” the personnel resources related to climate policy in the different departments and units vary just as at the federal level, depending on the scope of their work. in some units and departments, only single individuals are directly involved in climate policy issues, while in other cases whole units directly work on climate policy. indirectly, the work of whole departments like transport and building infrastructure is of relevance in terms of climate policy. 3.2.2. cooperation 3.2.2.1. cooperation within departments cooperation within the departments of the styrian administration, on the one hand, arises out of particular occasions such as concrete administrative procedures or the development of regional strategies like the integrated styrian energy and climate strategy 2017 or the development of the styrian adaptation strategy 2012. on the other hand, cooperation takes the form of recurring activities, as in case of the preparation of the provincial energy reports for monitoring the styrian energy strategy 2017 or regular exchange in the form of jour fixes, departmental workshops, etc. cooperation occurs within as well as between different units, for instance when the energy-related criteria for housing subsidies are jointly determined by the unit responsible for housing subsidies and the unit responsible for energy technology. in this context many interviewees pointed out the advantage of bundling a broad range of competencies under a single provincial secretary for cooperation (e.g., between housing and energy issues). the quality of cooperation in the different units and departments generally rated good or even very good by the respondents. some interviewees, however, noted that there were only few points of contact with other units, which resulted in a lower rating (figure 5). 3.2.2.2. cooperation between departments the exchange with other departments is both related to specific tasks and continuous, for instance in form of regular jour fixes with politicians or the jour fixe of the heads of department. in the development of overarching strategies a broad involvement of all relevant departments and units was strived for by the lead department. nevertheless some of the other departments were missing integrative efforts. the joined implementation of measures was generally seen to be consensual and rated good. nevertheless, the respondents that also in the field of climate policy the targets as well as the pace of the implementation of measures were determined on the political level. 3.2.2.3. cooperation with other provinces the officials reported many contacts with their counterparts in other provinces. again, these take both the form of regular meetings such as the meetings of different categories of administrative officials (e.g., meeting of provincial climate protection representatives (“landesklimaschutzbeauftragte” or the meeting of environmental attorneys) as well as working groups on particular issues. the quality of collaboration was generally rated as good, especially on the personal level, although it was reported that often provincial figure 4: perceived weight of climate policy compared to other policy targets and perceived degree of climate policy integration source: own calculations. for the evaluation of the weight of climate policy compared to other policy targets, the experts could choose between the categories “more important” (1), “equally important” (2), “less important” (3) and “not important” (4). with respect to the degree of climate policy integration in austria experts could chose between “very good” (1), “good” (2), “not so good” (3) and “poor” (4) kettner and kletzan-slamanig: climate policy integration on the national and regional level: a case study for austria and styria international journal of energy economics and policy | vol 8 • issue 4 • 2018266 officials have to represent particular political interests. some respondents thought that the level of cooperation has decreased due to changes in the structure of state and provincial administrations. 3.2.2.4. cooperation with the federal state according to the interviewees the frequency and quality of cooperation with the federal state depends strongly on the ministries involved as well as on the nature of the specific task. the contact between the federal administration and the provinces is partly organised via those provincial departments explicitly in charge of climate policy issues that in turn seek expert opinions from other provincial departments (as for the austrian ikes), partly the relevant departments are contacted directly (e.g., in the context of expert working groups) and partly the federal government is gathering comments on specific strategies or legislative proposals. some respondents noted that the federal state primarily acts independently, excluding the provinces from the debate, unless the political support of the federal states was required. contrarily, some ministries would increasingly try to get the provinces on board in order to improve their comparably weak position in political negotiations. on the personal level the contact with the federal administration is, however, rated good, albeit in some cases rare. 3.2.2.5. cooperation with interest groups cooperation between the styrian administration and stakeholders and interest groups takes different forms and intensities, i.e., for some departments the contacts are limited to particular events while others try to involve a broad range of stakeholders in the development of strategies and regulations. often, the views of the interest groups were found to be diverging from the administration’s. however, in cases when the interest groups pursue the same goals, cooperation was rated as good. overall, respondents noted that the quality of cooperation with the interest groups as a whole is difficult to rate and tends to be problematic. 3.2.2. cpi and weighting of climate targets 3.2.2.1. relevance of climate policy compared to other targets the relevance of climate policy issues vis-à-vis other political targets was conceived heterogeneously by the respondents. nevertheless, the majority notes that the weight given to climate issues compared to other goals is a political decision and is very much contingent on the respective context. the interviewees stressed that the relevance given to climate issues differs strongly between the other sectoral policy areas: while progress is made in agriculture (especially with respect to adaptation to climate change) and in the buildings sectors, where austrian provinces have succeeded in defining ambitious standards, climate change is not yet recognised as an issue in tourism or economic policy in styria. as regards transport, the opinions of the respondents were mixed: some noted that the ongoing extension of the road infrastructure is expected to lead to a further increase in transport volumes, that public transport infrastructure is only poorly developed in rural regions of the province, and that so far there are no public investments in battery charging infrastructure for e-mobility. others highlighted progress made in terms of explicit preferential treatment of public via individual motorised transport in some urban areas, implying i.a. a reduction of parking spaces. conflicts were also identified with regard to the current discussion on affordable housing and the corresponding calls for lower thermal quality standards in order to reduce investment costs that would have detrimental effects on long-term energy conservation. one interviewee, however, pointed out that the concept of life cycle analysis is slowly gaining ground. in general, the implementation of mitigation measures, that are planned and ready to be applied, is to a certain extent seen as contingent upon the availability of financial resources. also with respect to air pollution, control conflicts were found and in turn the installation of biomass heating systems has been restricted in areas with high and persisting concentrations of particulate matter. figure 5: perceived quality of cooperation between departments, other administrative entities and stakeholders source: own calculations. for the evaluation of the quality of cooperation, the experts could choose between the categories very good (1), good (2), not so good (3) and poor (4) kettner and kletzan-slamanig: climate policy integration on the national and regional level: a case study for austria and styria international journal of energy economics and policy | vol 8 • issue 4 • 2018 267 in case of target conflicts the different goals are usually weighted in long (inter-departmental) discussions. ultimately the decisionmaking and the balancing of interests fall in the political sphere and tend to be rather intransparent. the division of competencies between the provincial level and the municipal level was noted as a factor constraining mitigation efforts of the province: while energy planning was introduced by the province, the respective adaptation of spatial planning lies in the competence of the municipalities, which tend to follow other interests. overall, the relevance of climate policy as compared to other policy issues was rated low (figure 6) by the vast majority of respondents. or put differently “climate protection is not always actively pursued.” 3.2.2.2. degree of cpi in styria the degree of cpi in styria was generally considered as low. that a single provincial representative is in charge of climate and energy issues was, however, seen as a positive factor for the integration of these policy areas. climate aspects also gain in importance in other policy areas such as agriculture and water management. yet the majority of respondents doubted that currently sufficient action is taken to tackle climate change. it was also noted that concepts for the implementation of additional climate protection measures are available but the necessary funding is not granted. 3.2.2.3. degree of cpi in austria cpi on the federal level is conceived even more critical (figure 6). the failure to issue the integrated climate and energy strategy (ikes) was given as an example for the lack in ambition in federal climate policy. it was noted that only little attention is generally devoted to the topic by policymakers in austria, not only in effective policy-making but also in the respective election campaigns. eu legislation was seen as a pacemaker for austrian climate policy with eu regulation getting continuously more ambitious. the federal structure of austria was mentioned as a factor preventing the swift implementation of eu directives. it was noted that climate policy efforts in austria have slowed down over the last years which was in stark contrast to the increasingly ambitious goals. the integration of agriculture and environment into one ministry added as another explicit factor hampering cpi in austria. climate policy in austria – according to respondents’ views – consists mainly of declarations of intention, but is characterised by a substantial lack in implementation effort. when asked for the prerequisites for a successful climate policy in styria and austria, also on the regional level the respondents emphasised the importance of taking a comprehensive and systemic approach to climate policy-making . just as at the federal level, a timely drafting of the ikes was mentioned as an important framework condition. moreover, many interviewees stressed that the climate policy targets should be taken seriously and put beyond question. this also implies implementing inconvenient measures that go beyond picking the low-hanging fruit. 4. conclusions the key target stipulated by the paris agreement is to limit global warming to well below 2°c compared to pre-industrial levels. mitigating climate change requires a thorough reorganisation of production and consumption patterns which basically translates into net zero emissions by mid-century. successful climate policy requires that the objective of reducing greenhouse gas emissions or avoiding rising emissions as unintended side effects of other (non-climate) policy interventions has to be integrated in decision making and legislative processes in basically all policy areas and all levels of government. the recognition of the cross-cutting nature of climate policy and the consideration of emission impacts of other policy areas are subsumed under cpi. figure 6: perceived weight of climate policy compared to other policy targets and perceived degree of climate policy integration source: own calculations. for the evaluation of the weight of climate policy compared to other policy targets the experts could choose between the categories “more important” (1), “equally important” (2), “less important” (3) and “not important” (4). with respect to the degree of cpi in austria experts could chose between “very good” (1), “good” (2), “not so good” (3) and “poor” (4) kettner and kletzan-slamanig: climate policy integration on the national and regional level: a case study for austria and styria international journal of energy economics and policy | vol 8 • issue 4 • 2018268 in order to assess the degree of cpi in austria on the federal and regional level we conducted a survey among officials in administration as well as representatives from social partners, other special interest groups and stakeholders. the interviews contained questions regarding the personnel resources dedicated to climate policy issues in each institution, the internal and external cooperation as well as the general relevance of climate policy as compared to other policy objectives. the results show a broad range of perceptions regarding the degree of cpi in austria. on the one hand, the consideration of climate policy issues depends on the core competence of the respective institution. on the other hand, we found widely diverging views on whether climate policy in austria is too ambitious or too weak. especially, potential negative impacts of climate policy on competitiveness or employment are seen to hamper a more ambitious implementation of mitigation policies. cooperation is generally rated as good, especially at the personal or informal level. however, conflicts of interest that result from the organisations’ core functions negatively impact on the perceived quality of cooperation. in case of conflicting targets it is widely noticed that “traditional” policy objectives like employment or competitiveness are given priority compared to climate concerns. the failure to effectively integrate climate aspects in other policy areas is reflected in the development of austria’s greenhouse gas emissions. after a slight decline between 2006 and 2014 emissions have been growing again. overall, greenhouse gas emissions amounted to 79.7 mt co2e in 2016 which is one mt above the level of 1990. thus, at present it seems doubtful if austria will be able to meet the 2020 emission reduction target for the non-ets sectors (uba, 2018). a stronger institutional framework for climate policy, e.g., a state secretary for climate policy or climate protection in constitutional rank, could increase the weight given to this issue. most importantly, the publication of an integrated long-term climate and energy policy strategy is required in order to put climate policy targets beyond question and develop a set of concrete measures that ensure the achievement of mitigation targets. regarding the conflicts of interest it remains to be seen whether the formal integration of energy policy in the ministry responsible for climate policy (federal ministry of sustainability and tourism) will improve the integration in actual and help resolve some of the perceived barriers for climate policy implementation. acknowledgement this research was funded by the jubiläumsfonds of the oesterreichische nationalbank (oenb), project number 16765. we would like to thank katharina köberl and susanne markytan for excellent research assistance and franz sinabell for invaluable research guidance. references adelle, c., pallemaerts, m., chiavari, j. (2009), climate change and energy security in europe policy integration and its limits. stockholm. available from https://www.pure.uva.nl/ws/ files/785631/79271_319295.pdf. adelle, c., russel, d. (2013), climate policy integration: a case of déjà vu? environmental policy and governance, 23, 1-12. a h m a d , a . i . ( 2 0 0 9 ) , c l i m a t e p o l i c y i n t e g r a t i o n : to w a r d s operationalization, working papers 73, united nations, department of economics and social affairs. available from: https://www. un.org/development/desa/publications/working-paper/climatepolicy-integration-towards-operationalization. beck, s., kuhlicke, c., görg, c. (2009), climate policy integration, coherence, and governance in germany, ufz-bericht 01/2009. available from https://www.wur.nl/en/show/climate-policyintegration-coherence-and-governance.htm. bommel, s., kuindersma, w. (2008), policy integration, coherence and governance in dutch climate policy. a multi-level analysis of mitigation and adaptation policy, alterra-rapport 1799. available from http://www.content.alterra.wur.nl/webdocs/pdffiles/ alterrarapporten/alterrarapport1799.pdf. brouwer, s., rayner, t., huitema, d. (2013), mainstreaming climate policy: the case of climate adaptation and the implementation of eu water policy. environment and planning c: government and policy, 31, 134-153. com (2008) 30. communication from the commission: 20 20 by 2020-europe’s climate change opportunity. available f r o m h t t p : / / w w w. e u r l e x . e u r o p a . e u / l e g a l c o n t e n t / e n / txt/?uri=celex:52008dc0030. com (2011) 112. a roadmap for moving to a competitive low carbon economy in 2050. available from http://www.eur-lex.europa.eu/ legal-content/en/all/?uri=celex:52011dc0112. c o m ( 2 0 1 4 ) 1 5 . c o m m u n i c a t i o n : a p o l i c y f r a m e w o r k for climate and energy in the period from 2020 to 2030. available from http://www.eur-lex.europa.eu/legal-content/en/ txt/?uri=com%3a2014%3a15%3afin. com (2016) 482. proposal for a regulation on binding annual greenhouse gas emission reductions by member states from 2021 to 2030 for a resilient energy union and to meet commitments under the paris agreement and amending regulation no 525/2013 on a mechanism for monitoring and reporting greenhouse gas emissions and other information relevant to climate change. available from http://www.eur-lex.europa.eu/legal-content/en/ txt/?uri=celex:52016sc0248. decision 406/2009/ec of the european parliament and of the council on the effort of member states to reduce their greenhouse gas emissions to meet the community’s greenhouse gas emission reduction commitments up to 2020. available : from http://www.eur-lex.europa. eu/legal-content/en/txt/?uri=uriserv: oj.l_.2009.140.01.0136.01. eng. dupont, c. (2010), political commitment to climate policy integration at eu level: the case of biodiversity policy. edinburgh europa paper series 2010/05. dupont, c., oberthür, s. (2011), climate policy integration into eu energy policy: achievements and driving forces institute for european studies, brussels. available from: https://www.ies.be/files/ documents/phd/phd%20claire%20dupont%202013.pdf. dupont, c., oberthür, s. (2012), insufficient climate policy integration in eu energy policy: the importance of the long-term perspective. j contemporary euro res, 8(2), 228-247. available : from http:// www.jcer.net/index.php/jcer/article/view/474. dupont, c., primova, r. (2011), combating complexity: the integration of eu climate and energy policies. european integration online papers 15(1). available : from http://www.eiop.or.at/eiop/pdf/2011008.pdf. european commission. (2017), climate change. special eurobarometer kettner and kletzan-slamanig: climate policy integration on the national and regional level: a case study for austria and styria international journal of energy economics and policy | vol 8 • issue 4 • 2018 269 459. brussels: european commission. available : from https://www. ec.europa.eu/clima/sites/clima/files/support/docs/report_2017_ en.pdf. hanger, s., haug, c., lung, t., bouwer, lm. (2013), mainstreaming climate change in regional development policy in europe: five insights from the 2007-2013 programming period. regional environmental change, 15(6), 973-985. jacob, k., kannen, h. (2015a), climate policy integration in federal settings: the case of germany’s building policy, ffureport 01-2015. available from https://www.researchgate.net/ publication/278672899_climate_policy_integration_in_federal_ settings_the_case_of_germany%27s_building_policy. jacob, k., kannen, h. (2015b), integrated strategies for climate policy integration and coherencehe case of germany, ffureport 02-2015. available from https://www.researchgate.net/ publication/278672997_integrated_strategies_for_climate_policy_ integration_and_coherence_the_case_of_germany. jordan, a., lenschow, a. (2010), environmental policy integration: a state of the art review. environmental policy and governance, 20(3), 147-158. kettner, c., kletzan-slamanig, d., köppl, a. (2012), climate policy integration-evidence on coherence in eu policies. vienna: wifo. available from http://www.wifo.ac.at/publikationen?detailview=yes&publikation_id=44537. kettner, c., kletzan-slamanig, d., köppl, a. (2015), climate policy integration: evidence on coherence in eu policies. in: kreiser, l., milne, j., editors. critical issues in environmental taxation, vol. xvi. uk: edward elgar. p3-17. kivimaa, p., mickwitz, p. (2009), making the climate count. climate policy integration and coherence in finland. the finnish environment 3/2009. available from https://www.researchgate. net/profile/paula_kivimaa/publication/236219148_making_the_ climate_count_climate_policy_integration_and_coherence_in_ finland/links/543397350cf225bddcc9af43/making-the-climatecount-climate-policy-integration-and-coherence-in-finland. pdf?origin=publication_detail. kok, m.t.j., de coninck, h.c. (2007), widening the scope of policies to address climate changeirections for mainstreaming. environmental science and policy, 10(2007), 587-599. lafferty, w., hovden, e. (2003), environmental policy integration: towards an analytical framework. environmental politics, 12(3), 1-22. lyytimäki, l. (2011), mainstreaming climate policy: the role of media coverage in finland. mitigation and adaptation strategies for global change, 16(6), 649-661. mickwitz, p., aix, f., beck, s., carss, d., ferrand, n., görg, c., jensen, a., kivimaa, p., kuhlicke, c., kuindersma, w., máñez, m., melanen, m., monni, s., pedersen, a.b., reinert, h., van bommel, s. (2009), climate policy integration, coherence and governance, peer report no 2, helsinki. available from: http://www.library.wur.nl/webquery/wurpubs/377942. niedertscheider, m., haas, w., görg, c. (2018), austrian climate policies and ghg-emissions since 1990: what is the role of climate policy integration? environmental science and policy, 81, 10-17. peters, g. (1998), managing horizontal government: the politics of coordination. public administration: an international quarterly, 76(2), 295-311. steurer, r., clar, c. (2014b), politikintegration in einem föderalen staat: klimaschutz im gebäudesektor auf österreichisch. der moderne staat, 7(2), 331-352. steurer, r., clar, c. (2014a), is decentralisation always good for climate change mitigation? how federalism has complicated the greening of building policies in austria. policy sciences, 48(1), 85-107. umweltbundesamt (uba). (2017), bundesländer luftschadstoffinventur 1990-2015. regionalisierung der nationalen emissionsdaten auf grundlage von eu-berichtspflichten, wien. available from http:// www.umweltbundesamt.at/fileadmin/site/publikationen/rep0632. pdf. umweltbundesamt (uba). (2018), austria‘s annual greenhouse gas inventory 1990-2016. submission under regulation (eu) no 525/2013, wien. available from http://www.umweltbundesamt. at/fileadmin/site/publikationen/rep0638.pdf. unfccc. (2015), paris agreement, paris: unfccc. van den berg, m., coenen, f. (2012), integrating climate change adaptation into dutch local policies and the role of contextual factors. local environment, 17, 441-460. wejs, a. (2014), integrating climate change into governance at the municipal scale: an institutional perspective on practices in denmark. environment and planning c: government and policy, 32, 1017-1035. available from: http://www.journals.sagepub.com/ doi/abs/10.1068/c1215. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 4 • 2023 187 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(4), 187-193. carbon disclosure, board climate governance and financial performance of listed manufacturing firms in nigeria isibor areghan akhanolu1*, ehikioya benjamin1, mercy adebayo2, awogbenja bukola bolanle1, adedoyin bunmi-alo1 1department of finance, covenant university, nigeria, 2department of sociology, covenant university, nigeria. *email: areghan.isibor@covenantuniversity.edu.ng received: 05 october 2022 accepted: 25 may 2023 doi: https://doi.org/10.32479/ijeep.13673 abstract this study examined the challenges of carbon disclosure and its impact on the performance of quoted manufacturing firms in nigeria. using equity return (roe) as the dependent variable and carbon performance (disclosure), board response, board climate incentives, and board environmental committee as the independent variables, the study used panel data analysis to analyze the secondary data gathered from 2014 till 2020. the hausman test suggested the usage of the fixed effect regression. findings from the regression result showed that all the independent variables of carbon performance (disclosure), board response, board climate incentives, and board environmental committee positively and significantly impact roe. the study therefore recommended amongst others that firms should always disclose their carbon disclosure data on their annual data so as to assist both the board and the regulatory authorities in managing carbon emission. keywords: carbon disclosure, board climate incentives, return on equity, panel data analysis, board environmental committee jel classifications: g34, m14, l60 1. introduction over the years there have been rampant climate changes in the environment through the emission of green house gases (ghg) which have become one of the primary threats to the existence of life on earth. the excessive emission of greenhouse gas (ghg) in the earth’s atmosphere has led to undesirable consequences in the ecosystem leading to global warming/climate changes (liu, 2015). the global social economic impact of climate change can be substantial as a changing climate change affects human beings as well as physical and natural capital. the consequences of climate change could lead to worker productivity losses and an adverse effect on the global gross domestic product (gdp) growth (hardiyansah et al., 2021). there is no doubt that firm have always played a major role in creating climate change problems as they are among the largest emitters of greenhouse gases (ghg) (ofoegbu et al., 2018). in recent times, stakeholders, such as shareholders, consumers and regulatory authorities, creditors, have started exerting pressure on corporations to decrease their ghg emissions (saka and oshika, 2014; raffaello et al., 2013). as a result, firms are to play a vital role in reducing the emission of ghg and contributing in the stabilization of climate change by providing the necessary information’s about climate change related activities as it is also referred to as carbon disclosure to satisfy the concerns of their top stakeholders. the study and rapid growth of carbon disclosure over the years has been a major success in the struggle to build awareness and action against climate change activities to the firms and their stakeholder through environmental disclosures. the result of carbon disclosure is as a result of three core drivers: regulatory compliance, the this journal is licensed under a creative commons attribution 4.0 international license isibor areghan akhanolu* finance department, covenant university, nigeria *email: areghan.isibor@covenantuniversity.edu.ng ehikioya benjamin finance department, covenant university, nigeria mercy adebayo sociology department, covenant university, nigeria awogbenja bukola bolanle finance department, covenant university, nigeria adedoyin bunmi-alo finance department, covenant university, nigeria *email: akhanolu, et al.: carbon disclosure, board climate governance and financial performance of listed manufacturing firms in nigeria international journal of energy economics and policy | vol 13 • issue 4 • 2023188 pressure from non-governmental organizations, managerial information systems intended to facilitate participation in carbon markets, reduce energy cost and manage its reputational risks. carbon disclosure is not just of great benefits to stakeholders of firms but also helps them to monitor and regulate their carbon emission which is of advantage to improving the firms’ carbon performance. when the carbon performance of a firm is stable and highly improved it leads to a drastic change and improvement in their financial performance on a long term (mohammad and aisa, 2020). corporate carbon profiles are translated into risk and market opportunity assessments with clear financial implications for businesses and investors. indeed, this constitutes the central logic behind the carbon disclosure movement (mohammad and aisa, 2020). the emphasis here is on the greater societal goal of reporting and accounting, rather than the total procedure and approach. carbon disclosure is becoming more widely recognized as an example of informational governance, or governance based on data (mohammad et al., 2020). carbon disclosure, in particular, employs openness and accountability systems to influence the behavior of target investors. the carbon disclosure project (cdp) was founded in 2000 by a uk-based organization to encourage organizations to disclose their greenhouse gas emissions (mohammad et al., 2020). it has since evolved into a strategic skill that appealed to a wide range of stakeholders while also providing widespread credibility for reporting standards. cdp today has over 3000 organizations in 66 countries measuring and disclosing their emissions and climate strategies (mohammad et al., 2020). the data collected from these companies are made publicly available and can be used by investors, shareholders and policy makers. disclosure of carbon emissions has grown in importance as a governance organization, promoting awareness about climate change, sustainable energy, and energy efficiency, as well as legitimizing the notion of external accountability. most crucially, the voluntary rise of carbon disclosure has shown businesses the viability of doing so as well as the potential benefits of carbon monitoring and reporting, such as reputation management and the cost of energy. as a result, political space is opened for the regulation of initiatives that compel carbon accounting rules that should be made public and formalized. currently there are five programs under the cdp: cdp water disclosure, investors cdp, cdp supply chains, cdp cities and cdp public procurement (mohammad et al., 2020). with the increasing acceptance of climate change as one of the most discussed political, societal, and business issues globally, as well as the introduction of regulations to address the challenge of global warming, such as the european union’s emission trading scheme (ets) and carbon taxes (or similar pricing mechanisms) in several other countries (e.g. the united states), regulations to address the challenge of global warming, such as the emission trading scheme (ets) and carbon taxes (or similar pricing mechanisms) in several other countries. specifically, for large corporations’ carbon disclosure is becoming the de facto standard. despite the gain, it is still uncertain what the future holds. the organization’s board committee has a significant impact on whether the organization makes positive or bad decisions around carbon disclosure. corporate business activities are frequently accused of being the primary causes of climate change since they emit greenhouse gases (ghgs) (lee and min, 2015). the focus of carbon disclosure is primarily on external pressures, with little or no consideration made to business internal governance structures. previous research has looked into the link between board members’ overall attributes and corporate sustainability disclosure. board size, board diversity (gender), board independence, and a sustainability-related committee are among these characteristics. according to studies like healy and krishna (2001), the more diverse a board of directors is, the more it can assist managers in making choices. for starters, a supervisory team with a broad set of knowledge, skills, and experiences, as well as professional network connections, can be more inventive and creative. in the context of climate change, directors with a diverse social and environmental intellect are more likely to understand carbon disclosure and even be aware of more transparent channels aimed at various stakeholders, such as answering carbon disclosure project (cdp) annual questions to institutional investors and including carbon-related information in their sustainability report to the general public (he et al., 2016). as a result, it is reasonable to assume that the board will be favorably linked to the chance of releasing carbon-related information. furthermore, a board with a higher level of embeddedness can gather more industry-specific data to assist the organization in dealing with a variety of uncertainties (he et al., 2016). this study therefore looked into the extent to which disclosure of carbon emissions is linked to better carbon performance. this problem has to do with a long-standing topic about whether quick changes in carbon disclosure have influenced changes in carbon emissions performance. it is of no doubt that carbon disclosure and performance is complex and has been affected by both the strength of climate governance and a multiplicity of factors. as a result of this, the relationship between carbon disclosure-performance may be conceptualized from two perspectives (the signaling and legitimacy theory). the signaling theory basically suggested that firms with strong carbon performance are more likely driven to give detailed information about their good performance and topics relating more to climate changes issues to their stakeholders and investors as they are likely to benefit from higher financial returns including market valuation and lower cost of capital (diah and efita, 2016). on the other hand, the legitimacy theory suggested that firms are likely to use disclosure to green-wash and obfuscate poor environmental performance leading to a drastic harm to the climate (donavan, 1984; akhiroh and kiswanto, 2016). prior to this research, studies have shown that corporate governance such as board independence, board diversity etc. has a huge effect also on carbon disclosure and performance. as a matter of fact, most firms are faced with issues relating to their climate governance/change as a result of the non-commitment of their board of directors to monitor its carbon emission and performance (diah and efita, 2016). a sub-committee or director responsible for the provision of information regarding climate akhanolu, et al.: carbon disclosure, board climate governance and financial performance of listed manufacturing firms in nigeria international journal of energy economics and policy | vol 13 • issue 4 • 2023 189 change issues or even provision of incentives to other directors and management can help the firm in its carbon mitigation thereby limiting global warming, emission of ghs (greenhouse gases) and other negative environmental impact it may cause (bae et al., 2013). the outlined responsibilities of the board of directors to drive forward the firm’s climate strategy can be found in most firms’ annual reports, but it is not surprising that most firms see climate change as a matter overseen by the board, as most firms stated they will look at the composition of their board to see if they have the appropriate level of skills and experience in the area of climate change. even if the board of directors is not a full-fledged climate specialist, it is critical that they take responsibility for understanding scientific consensus so that the firm’s management team can assess climate-related risks, develop mitigation plans, and communicate the story to stakeholders like investors, consumers, and regulators. with the goal of increasing productivity in small and medium enterprises, the domestic market, and large corporations in a developing country like nigeria, which has a population of over 200 million people as of 2021, the country engages in a variety of economic operations that harm the economy and the environment (hardiyansah et al., 2021). this has a negative impact on the environment, ranging from global warming to the disposal of toxic waste materials by manufacturing or oil and gas industries, as well as a massive emission of greenhouse gases into the atmosphere, which has sparked interest in corporate environmental reporting among stakeholders. nigeria ranks second among the top 20 countries with the highest rate of gas flaring (omaliko et al., 2020) and the seventh ranked by flare volume as at 2020. this has sparked widespread worry in the niger delta region (rivers, akwa ibom, bayelsa, and imo states), as the high rate of greenhouse gas emissions traps heat in the atmosphere, contributing to global warming. the current activities taken by individuals and companies involved in production that leads to emission is currently have an effect to the ecosystem (land, water and air) as not one seems to take responsibility for their actions. these actions have a tendency of affecting not only the present but also the future if it is not curtailed. the going concern concept is widely accepted in nigeria, and most industries must take the required steps to ensure that their economic activities are socially and environmentally sustainable. even though organizations need earnings to thrive, they must also recognize that social and environmental considerations can have a significant impact on their long-term financial performance. today, environmental or sustainability reporting has become a voluntary global reporting initiative adopted by most developed countries across the globe. however, this is not the same in a developing country like nigeria (omaliko et al., 2020). businesses seek ways to reducing the negative impact on the environment through an appropriate dissemination of qualitative environmental disclosure (omaliko et al., 2020). the concerns linked with industries’ unrestricted carbon disclosure have an adverse impact on the environment that cannot be disregarded. as a result of this issue harming the ecosystem, much effort has been focused over the years on lowering the impact of industrial activities on carbon emissions in the environment (omaliko et al., 2020). there is a study gap of what truly motivates companies to disclosure their environmental information even though greenhouse gas (ghg) emissions have such a significant impact on the environment. a review from previous research work such as omaliko and okpala (2020) made observations by using the firm’s size, firm’s characteristics, and firm leverage on the level of carbon disclosure on other developing countries other than nigeria. since there is a voluntary dissemination of information regarding carbon disclosure by firms in nigeria it would be of great necessity that industries create a board environmental committee in the organization that has a positive influence towards climate governance and its effects on the carbon disclosure of the company and its carbon performance. this study is motivated by the lack of research in developing countries as nigeria. it aims to assist and remind the board of directors, senior management, stakeholders, and government in developing an integrated approach to reducing ghg emissions by businesses, resulting in a positive change in the climate. 2. conceptual framework on climate change and the nigerian environment global warming and its adverse effect to the climate change in nigeria can be viewed in various notable ways which includes the economy, health, food production and the likes. since nigeria is predominantly contending with primary production of economic values as opposed to the industrial production, any adverse effect on the biosphere through climate change would have adverse implication on her economy (siregar and refandi, 2018). the impact of global warming is already evident in the environmental degradation afflicting the two extreme ecological zones. in the north sahelian zone, desert encroachment is gradually but steadily depleting vegetation and grazing resources, thereby forcing more nomadic activities. in the coastal south, sea level rise is resulting in over flooding while pollution is exerting monstrous impacts on the biosphere thus endangering fishing and subsistence agriculture. this is putting the adverse effects of climate change, as far as nigeria is concerned, in a composite. the ripple effects of the general environmental degradation would rob off negatively on other sub-sectors which we have earlier listed. 2.1. brief overview of climate governance according to gallego-álvarez et al., 2015), the evolution of climate governance can be attributed to the inter-state diplomacy and then the creation of transactional networks and non-state players. the exact date of “creation” is quite difficult to pinpoint, but the united nations framework convention on climate change (unfccc) in rio is a watershed moment in its history. this has been termed “the first turning point in climate diplomacy.” as climate governance has progressed on the international stage, a akhanolu, et al.: carbon disclosure, board climate governance and financial performance of listed manufacturing firms in nigeria international journal of energy economics and policy | vol 13 • issue 4 • 2023190 number of transnational public and public-private actor networks, such as the global cities covenant on climate (also known as the ‘mexico city pact’) and the cities for climate protection programme, have sought to implement its goals in their own arena (ccpp). the unfced (united nations conference on environment and development) in 1992 served as a “trigger” for this process. existing regional and local networks accepted the goals and began to investigate how they could be met on a local level. innovative climate governance methods, such as the “cap and trade” mechanism, have emerged under the cover of internationally agreed climate targets. the cap-and-trade mechanism is basically a method used in reducing the rate of emission from power plants by setting a limit on pollution and creating a market. 2.2. various perspective of climate governance climate governance is multi-scale, multi-actor, and has deeply embedded in our social and physical infrastructure: multi-scale: at each degree of governance, climate governance occurs as policies are implemented at various levels and spaces. supranational, national, regional, and local scales are all included in this. the connection between these domains raises crucial questions about who has authority and power to manage climate change. multi-actor: the ambiguous positions of state and non-state actors in climate governance are exacerbated by their fragmented and hazy roles. non-state actors, such as the united nations framework convention on climate change (unfccc), play an important influence in determining national governments’ positions on international climate agreements. embedded: the fact that non-state entities are involved in climate governance is partially due to the deeply rooted social and economic structure of many of the processes that lead to ghg emissions. the complexity of mechanisms involving ghg emissions across the earth at all scales add to the challenges of tackling climate change. 2.3. carbon disclosure and performance the study of carbon disclosure has been gaining increasing importance in recent years to help firms communicate their climate change activities to their stakeholders through environment disclosures (diah and efita, 2016). these disclosures can help stakeholders, such as shareholders and creditors, to make better investment decisions. carbon disclosure can also help stakeholders, such as regulatory agencies, institutional investors and the public, to better monitor and regulate a firm’s carbon emissions, which is likely to contribute to its improved carbon performance. a carbon disclosure rating is a measure of the environmental sustainability of a company, based on voluntary disclosures by the company itself. the practice is intended to help investors who wish to incorporate environmental, social and governmental (esg) factors into their investment decision-making process. the most widely used carbon disclosure ratings are administered by cdp, a united kingdombased non-profit organization formerly known as the carbon disclosure project. 2.4. firm performance the performance of any firm is attached to so many areas like the financial performance, sales performance, marketing performance, corporate governance performance, production performance, and so on. however, this study would examine the financial performance aspect of a firm success. many variables are used to measure financial performance like profit after tax measurement, asset returns measurement, however, this study would use the equity returns measurement. equity returns is simply the ratio of total profit after tax to the company’s total equity. 2.5. theoretical framework 2.5.1. signaling theory the signaling theory was proposed by michael spence in 1973 (donavan, 1984), and it basically states that firms with strong carbon performance are more likely to be driven to give detailed information to their stakeholders and investors about their good performance and topics relating to climate change issues because they are more likely to benefit from higher financial returns, such as market valuation and lower cost of capital (ennis et al., 2012). firms seek to differentiate themselves by signaling their superior carbon performance to stakeholders, gaining a competitive advantage, according to the signaling theory. firms with poor performance may exacerbate information asymmetry by reducing carbon disclosure, rather than hiding underlying performance or avoiding responsibility for poor performance. some researches demonstrated a positive association between environmental performance and environmental disclosure (dibia and onwuchekwa, 2015), which was consistent with a signaling perspective. good environmental performance is associated with more extensive disclosure of quantifiable pollution-related measures, according to he et al. (2016). gayo and vera, 2020), for example, found a link between carbon disclosure and carbon performance. 2.6. empirical framework mohammad et al. (2020) examined the combined influence of climate governance on carbon disclosure, where climate governance is linked to carbon disclosure and performance alignment. they chose the s&p 500 as their sample size because these are the largest publicly traded companies on the new york stock exchange (nyse). with such a high level of capitalization, these companies are subjected to considerable stakeholder and public pressures to reduce carbon emissions and take the lead on climate change initiatives. they also analyzed their data with regression models. the findings show that broad disclosure minimizes over-acclaiming of high performance, with lowpolluters disclosing more to differentiate themselves. the impact of incorporating climate change considerations into governance systems on the relationship between carbon disclosure and carbon performance is examined in this paper. according to lee and min (2015), changes in carbon disclosure levels are positively related to subsequent changes in carbon performance (examined through direct and indirect carbon emission intensities). regardless of whether disclosure has been used to justify earlier bad performance, their research shows that akhanolu, et al.: carbon disclosure, board climate governance and financial performance of listed manufacturing firms in nigeria international journal of energy economics and policy | vol 13 • issue 4 • 2023 191 carbon disclosure stimulates organizations and provides a ‘outsidein’ driven effect that leads to subsequent change and improvement in carbon performance. they based their findings on a change analysis of global 500 firms’ carbon emission and disclosure data from 2008 to 2012. panel data was used in their analysis to control unobservable firm heterogeneities, allowing the hypotheses to be effectively evaluated. they used cdp data from 2008 to 2012 to ensure consistency and acquire as much information as feasible. during this time, business leaders have progressively grasped the importance of managing climate change, thanks to market incentive systems such as the european union ets, which encouraged corporate carbon management and innovation (he et al., 2016). their research was prompted by an increase in carbon disclosure but a paucity of studies on whether this rise may be translated into improved carbon performance. despite the fact that extensive study has been done on the relationship between environmental performance and disclosure, there is little information on the actions and changes that firms may make as a result of disclosures. in a nutshell, their results help regulators to monitor carbon disclosure and assist investors with investment decisions. in a study of 95 companies from the s&p 500, ennis et al. (2012) looked at the link between boardroom diversity and corporate social performance. diversity of boards (dob), which includes board size, board independence, outside directors, and leadership duality, and diversity in boards (dib), which includes director gender, age, experience, tenure, and ethnicity, are the independent variables included in their study. other board structures (board size, board independence, outside directors, leadership duality, experience, tenure, and ethnicity) had no significant relationship with corporate social performance, according to the findings. eze et al. (2016) provided a comprehensive understanding of the governance-related factors and financial consequences of carbon performance and disclosure. its inspiration stems from the growing political, social, scholarly, and practical necessity of monitoring and reporting on carbon-related concerns on a global scale. they used a systematic literature review as a methodological approach. as a result, 73 quantitative peerreviewed empirical studies in the field were identified and classified using a legitimacy theory-based framework. panel data was utilised in their research. diah and efita (2016) attempted to investigate the relationship between corporate governance and the quality of sustainability reporting of listed companies in nigeria. board governance factors (board size, board independence, board gender diversity, and board expertise) and audit committee traits are used in their study to assess corporate governance (audit committee size, audit expertise and audit meeting). their research is based on a sample of 120 companies from the 165 that are listed on the nse over a six-year period (2013–2018). using the ordered logistic regression strategy, enterprises are classified into different sectors using a stratified sample method, specifically from eight sectors on the nse. finally, they measured corporate governance using board governance (board size, board independence, board gender diversity, and board expertise) and audit committee qualities to see if there was a link between corporate governance and srq in nigeria (audit committee size, audit expertise and audit meeting). they found that corporate governance had a substantial impact on srq utilizing a sample size of 120 enterprises and the ordered probit and logistic regression methods from 2013 to 2018. 2.7. gaps in literature despite the fact that much has been written and published, major authors either focus extensively on climate governance or carbon disclosure and performance and those who have written articles on the topic have focused more on developed countries such as the united states, the united kingdom, asia, and others while few studies are on developing countries. furthermore, the majority of this study work is measured using a specific approach; there are a few that have employed alternative measurement techniques, but the most of them were not subjected to developing country constraints. 3. model specification the study adopted and modified the model from the study of hardiyansah et al. (2021). the explicit model form was: roeit = α + β1 bresit + β2 bincit + β3 benvit + cperit + εit where: cperit = carbon performance (disclosure) of firm i in period t bresit = board response of firm i in period t bincit = board climate incentives of firm i in period t benvit = board environmental committee of firm i in period t roeit = equity return of firm i in period t εt = error term. the study used panel data for the period 2014 till 2020 and was extracted from the annual reports of the selected manufacturing companies and the nigeria stock exchange fact-book. the data was analyzed using the panel data regression analysis. the selected sample size was 15 listed manufacturing industries in the nigerian stock exchange, and they included: unilever nigeria plc, nestle nigeria plc, nigeria breweries plc, flour mills of nigeria plc, pz cussons nigeria plc, guinness nigeria plc, cadbury nigeria plc, honeywell flour mill plc, dangote group, lafarge cement, champion breweries plc, bua food plc, international breweries plc, united africa company of nigeria (uac), british american tobacco nigeria limited, golden guinea breweries plc, and union dion salt plc. 4. results 4.1. unit root test the study used the panel unit root test to examine the stationarity of the data. the probability values of the levin et al. t-statistics and the augmented dickey-fuller fisher chi-square (adf fisher chi-square) would be examined to determine the stationarity at both levels and first difference. if akhanolu, et al.: carbon disclosure, board climate governance and financial performance of listed manufacturing firms in nigeria international journal of energy economics and policy | vol 13 • issue 4 • 2023192 the probability values are less than 0.10 or significant at 10% level of significance, then the null hypothesis would be accepted and it would be agreed that there is the presence of a unit root and the data is stationary. from table 1, all the variables were stationary at levels with values of 0.0000, 0.0000, 0.0000, 0.0002, and 0.0000 which were significant at 10% level of significance (lesser than 0.10) to prove the presence of a unit root and that the data was stationary. 4.2. hausman test panel data regression is made up of the fixed effect and the random effect regression. hence, to determine which to use for the study analysis, the hausman test was adopted. the decision criterion was to reject the null hypothesis if the probability value of the chi-square statistic of the hausman test was significant at 5% level of significance. the null and alternate hypothesis adopted to test the hausman test is: h0 = random effect h1 = fixed effect. from table 2, the chi-square statistic probability value of 0.0000 was significant at 5% level of significance. the significant result showed that the null hypothesis would be rejected and this means that the fixed-effect model was appropriate for this study. 4.3. fixed-effect regression from table 3 and examining the coefficient signs, it was evident that there existed a positive relationship between bres, binc, benv, and cper with the dependent variable roe. the nature of the relationship was positive based on the signs of the entire coefficients. this implied that an increase in any of the independent variables would lead to an increase in the dependent variable. also, the regression output also showed the significance of each independent variable in the model, which was used to test the study hypothesis. based on the rule of thumb and the significant level of 0.05, the probability value of bres, binc, benv, and cper were all significant with probability values of 0.0294, 0.0068, 0.0000, and 0.0353 respectively. the coefficient of determination (r-squared) of the model under consideration which measured the goodness of fit of the model had a value of 0.68. this indicated that all the independent variables explain about 68% of the variations in the dependent variable (roe). after adjusting for degree of freedom, the adjusted r-squared was 0.61 (61%). furthermore, the f-statistics showed the joint significance of the independent variables on the dependent variable. examining its probability value (prob(f-statistic)) of 0.000003 which was significant at 5% level of significance, all the independent variables and the control variables together jointly have a significant impact on the dependent variable roe. finally, the durbin-watson test was used to show the presence or absence of autocorrelation in the model. autocorrelation means that all or some of the independent variables are related this makes the regression result spurious. the value of the durbin-watson variable must be estimated at 2 to ensure that there is no autocorrelation in the model. the durbin-watson value of 1.86 was approximately 2 to show that there was no autocorrelation in the model. 4.4. breusch pagan lm test for auto/serial correlation this was used to test for autocorrelation in the panel data and was used to confirm this assertion. the null hypothesis showed no presence of autocorrelation and vice versa. h0: there is no presence of autocorrelation in the model h1: there is the presence of autocorrelation in the model. from the result in table 4, the probability value of 0.1032 was not significant at 10% level of significance to show that there was no autocorrelation in the model. 5. discussion of findings and policy implications 5.1. discussion of findings result from the hausman test revealed that the fixed effect regression was perfect for the data analysis. the findings from the fixed effect regression showed that carbon performance, board response, board climate incentives, and board environmental committee all had positive and significant impacts on return on equity of the selected firms. hence, the company board is saddled with the responsibilities of not only taking effective decisions on managing the firm but also taking decisions on climate impact, environmental impact, and carbon disclosure impact of the fumes that emanate from the manufacturing processes from their firms. table 1: panel unit root test (levels) variable levin, lin and chu t* statistics probability values at 10% significant level stationarity intercept/trend and intercept remark cper −4.89106 0.0000 stationary at levels trend and intercept i (0) bres −4.23002 0.0000 stationary at levels trend and intercept i (0) binc −8.04963 0.0000 stationary at levels trend and intercept i (0) benv −3.48103 0.0002 stationary at levels intercept i (0) roe −6.84100 0.0000 stationary at levels trend and intercept i (0) source: researchers compilation using e-views 9. cper: carbon performance, bres: board response, binc: board climate incentives, benv: board environmental committee, roe: equity return table 2: hausman test result to determine the best regression output to use test summary χ2 statistic χ2 df p cross-section random 5.490210 6 0.0000 source: researchers compilation using e-views 9. df: degree of freedom akhanolu, et al.: carbon disclosure, board climate governance and financial performance of listed manufacturing firms in nigeria international journal of energy economics and policy | vol 13 • issue 4 • 2023 193 the board’s ability to manage this would lead to a clean and green environment and would improve productivity and sales and ultimately boost performance especially financial performance of such firms. 5.2. recommendations 1. the firm board should ensure a safe, clean, green production environment is maintained in the work environment as this would boost production, sales, and financial performance of the firms. 2. the firm board should ensure that quick responses are taken to curtail any situation of carbon spillage in the production area for increased performances. 3. environmental factors like carbon spillage that negatively affect the climate should be curtailed and controlled by the firm board for maximum performance. 4. policies to manage carbon emission from the firm production unit should be made by the board so as to boost performance. 5. firms should always disclose their carbon disclosure data on their annual data so as to assist both the board and the regulatory authorities in managing carbon emission. references akhiroh, t., kiswanto, k. (2016), the determinant of carbon emission disclosures. accounting analysis journal, 5(4), 326-336. bae, c.b., lee, d., psaros, j. (2013), an analysis of australian company carbon emission disclosures. pacific accounting review, 25(1), 58-79. diah, i., efita, f. (2016), the effect of carbon emissions disclosure and corporate social responsibility on the firm value with environmental performance as variable control. research journal of finance and accounting, 7(9), 122-130. dibia, n.o., onwuchekwa, j.c. (2015), determinants of environmental disclosures in nigeria: a case study of oil and gas companies. international journal of finance and accounting, 4(3), 145-152. donavan, g. (1984), legitimacy theory as an explanation for nonfinancial disclosures. australia: viklag publishers, victoria university of techno. ennis, c., kottwitz, j., lin, s.x., markusson, n. (2012), exploring the relationships between carbon disclosure and performance in ftse 350 companies, working paper series no 3164. eze, j.c., nweze, a.u., enekwe, c.i. (2016), the effects of environmental accounting on a developing nation: nigerian experience. european journal of accounting, auditing and finance research, 4(1), 17-27. gallego-álvarez, i., segura, l., martínez-ferrero, j. (2015), carbon emission reduction: the impact on the financial and operational performance of international companies. journal of cleaner production, 10(3), 149-159. gayo, a.a., vera, d. (2020), determinants of carbon emission disclosures. journal of economics, business, and accountancy ventura, 22(3), 333-346. hardiyansah, m., agustini, a.t., purnamawati, i. (2021), the effect of carbon emission disclosure on firm value: environmental performance and industrial type. the journal of asian finance, economics, and business, 8(1), 123-133. he, y., tang, q., wang, k. (2016), carbon performance versus financial performance. china journal of accounting studies, 4(4), 357-378. healy, p.m., krishna, k.g. (2001), information asymmetry, corporate disclosure, and the capital markets: a review of the empirical disclosure literature. journal of accounting and economics, 31(13), 405-440. lee, k.h., min, b. (2015), green r&d for eco-innovation and its impact on carbon emissions and firm performance. journal of cleaner production, 108, 534-542. mohammad, h., aisa, t. (2020), analysis of carbon emissions disclosures and firm value: type of industry as a moderating model. international journal of scientific and technology research 9(2), 1125-1132. mohammad, h., aisa, t.a., indah, p. (2020), the effect of carbon emission disclosure on firm value: environmental performance and industry type. the journal of asian finance, economics and business, 8(1), 123-133. ofoegbu, g.n., odoemelam, n., okafor, r.g. (2018), corporate board characteristics and environmental disclosure quantity: evidence from south africa (integrated reporting) and nigeria (traditional reporting). cogent business and management, 5(1), 1551510. omaliko, e., okpala, n. (2020), effect of environmental disclosures on dividend payout of firms in nigeria. international journal of banking and finance research, 6(3), 14-28. omaliko, e., nweze, a., nwadialor, e. (2020), effect of social and environmental disclosures on performance of non-financial firms in nigeria. journal of accounting and financial management, 6(1), 16-29. omaliko, e.l., nwadialor, e.o., nweze, a.u. (2020), effect of nonfinancial disclosures on performance of non-financial firms in nigeria. journal of accounting and financial management, 6(1), 40-58. raffaello, c., john, a.r., max, h. (2013), low-carbon development: opportunities for nigeria. usa: world bank publications. saka, c., oshika, t. (2014), disclosure effects, carbon emissions and corporate value. sustainability, accounting, management and policy journal, 5(1), 22-45. siregar, s.v., refandi, b.d. (2018), the associations between environmental disclosures with financial performance, environmental performance, and firm value. social responsibility journal, 4(1), 180-193. table 3: fixed-effect regression variable coefficient se t-statistic p c −0.225017 13.57517 −0.016576 0.9868 bres 0.523066 0.238819 2.190216 0.0294 binc 1.720508 0.631059 2.726383 0.0068 benv 1.357659 0.150447 9.024154 0.0000 cper 0.106135 0.051543 2.059147 0.0353 r2=0.68 adjusted r2=0.61 durbin-watson test=1.86 f-statistics=3.747747 p (f-statistic)=0.000003 source: researchers compilation using e-views 9. se: standard error, bres: board response, binc: board climate incentives, benv: board environmental committee, cper: carbon performance table 4: breusch pagan lm test result test statistic df p breusch-pagan lm 500.1209 55 0.1032 source: researchers compilation using e-views 9. df: degree of freedom . international journal of energy economics and policy | vol 7 • issue 2 • 2017296 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(2), 296-303. issues for long-range projection of international energy markets through the prism of sustainable development igbal guliyev1*, igor litvinyuk2 1international institute of energy policy and diplomacy, moscow state institute of international relations (university), ministry of foreign affairs of the russian federation, moscow, russia, 2centre for strategic research and geopolitics in energy, international institute of energy policy and diplomacy, moscow state institute of international relations (university), ministry of foreign affairs of the russian federation, moscow, russia. *email: guliyev@miep-mgimo.ru abstract modern energy system development model requires incorporation of not only demand and supply sides of energy markets, but also reference of new technologies deployment throughout the whole value chain, governmental policies in place, and other non-market indicators that, however, provide for the whole market equilibration by indirect energy resources price regulation. consequently, overcoming the traditional framework is getting basic precondition for achieving sustainable development in the energy sector, covering the whole energy system for research purposes due to global and coherent transition from forecasting of energy development to constructing of new alternatives and creating a new world which meet the goals of sustainable development. the next step will be a creation of ways of their achievement, and management systems, which allows countries, regions and the whole world to stay on that pathway. the article comes up with suggestions on making alterations to the current practice of energy systems forecasting process. keywords: scenarios, sustainable development, international relations, global energy markets jel classifications: o13, p28, q47, y3 1. introduction the russian federation is one of the largest international energy market players. energy sector is vital for the russian economy, and its development dynamics to a large extent affects economic sustainability. in this regard, development of scenario for world energy markets development in a long-term perspective proves to be essential. being in the framework of recent geoeconomic and geopolitical processes affecting national economies, it should incorporate analysis of a wide range of specific factors that underpin energy markets development, and capture trends of sustainable development policies implemented in national legislation systems. the primary objective of such exercise is to evaluate trends in world energy markets development and capture country-specific instruments that might be employed for securing economic sustainability. with a focus on the russian perspective, that requires identification, classification and assessment of factors currently determining the modes of operation of russian energy market and its interplay with international markets, as well as analysis of effectiveness of various policy options adopted in support to sustainability. the energy markets forecasting is important to adapt economic growth trajectories that remain in line with sustainability principles, and allow for securing sustainable development of national economy. it is worth mentioning that there is a contradiction concerning forecasting methods, instruments and approaches. on the one hand, the range of organizations forecast energy systems development, on the other hand – the forecasting is archaic. it is mostly bound to using simple and inadequate forecasting methods, which appear to be mechanistic procedures neglecting qualitative market developments. at the same time, significant developments have occurred forming the new global geo-economic view. nowadays, the most complex objective is to establish a new concept described by quantitative indicators. guliyev and litvinyuk: issues for long-range projection of international energy markets through the prism of sustainable development international journal of energy economics and policy | vol 7 • issue 2 • 2017 297 2. literature review overview of the existing literature suggests that the existing evaluations of energy resources demand in the mid and long-term perspective presented by specialized international organizations are mainly based on either extrapolation of present trends, without giving due consideration to different regional markets characteristics, or reflect particular interest of those providing these forecasts (greene, 2001). moreover, the forecasts have different aggregation by countries, which implies methodological complications while assessing energy system development issues on regional and global scale. the initial evaluation of scenarios gives a clear understanding that fundamentally the results of each scenario are merely based on presumptions, expert opinions and certain preconditions, which the developers are guided by. it stipulates that there is no single pair of forecasts that may be characterized by similar quantitative estimation indicators. nevertheless, qualitative estimations frequently coincide with each other, though there is no single combination reported. multiple global energy system development simulation results are primarily built upon a set of input data describing the current state of energy system, and their further prioritization with consideration of energy paradigm in a certain country (region, company). yet, various data analysis approaches have a common goal of establishing a starting point for further analysis, which, in fact, are “forecasting” or “scenario-building.” it is obvious that the forecasting process implies achieving a particular state of the energy system based on the input value and change of indicators over time, as well as on a number of assumptions. the methodological approach for such modeling is based on the analysis starting from the lower levels of hierarchy (bottom-up approach). the scenario building process, in turn, includes a range of possible ways for further development and, therefore, multiple system states in the future, developed through top-down analysis. the latter is based on developing hypotheses and establishing the desired parameters and indicator values, with the subsequent development measures on how to achieve a certain state of energy system. 3. modern energy system modelling approaches generally based on the individual goals, modeling is carried out by using a range of economic-mathematical models, taking into the account the list of indicators which are often similar with respect to their qualitative interpretation but with different quantitative estimation, as well as evaluation of their interplay and cross-factor correlation. thus, a number of models include unique parameters, which are only necessary to realize a specific research task. nowadays there are more than 50 models, developed by various specialized organizations and energy companies and they enable energy system development forecasting at global, regional and national levels (gabrial and mcglade, 2012; bhattacharyya and timilsina, 2009). models are regularly reviewed, supplemented by actual data and improved in order to ensure the most reliable results according to the developers. it is noteworthy that mathematical models are not used by private oil and gas companies which develop their own forecasts based on internal assessments and subjective assumptions regarding industrial development trends emerging on energy market in the future based on the investment climate, technology development, economic, environmental and geopolitical situation. among the foreign organizations absolute leaders are international energy agency and world energy council that form a global vision of energy development. at the same time, there is an extensive network of university research centers and laboratories involved in the energy development prospects. among them it is worth to mention the u.s. department of energy’s national renewable energy laboratory, paul scherrer institute (switzerland), duke university (usa), cambridge econometrics (uk), national technical university of athens (greece), finland futures research centre (finland), international institute for applied systems analysis (austria) and others. russian academy of science and the russian government analytical centre are the ones working in the sphere of forecasting of global energy tendencies (makarov et al., 2013; benichou and mayr, 2014; densing et al., 2013). in addition, such forecasts are done by the russian and foreign companies in the fuel and energy complex, including lukoil, bp, eni, exxonmobil, shell, statoil and others. at the same time, fundamentally the results are based only on expert opinion and assumptions, by which certain developers are guided. it should be emphasized that the forecasts are based on multiple forecast general methods, models and approaches. the list of common predictions including the description of their characteristics is presented in table 1 (jose and assis, 2015). in addition to different approaches applied to the outlooks development, every organization focuses on its particular prioritized sphere. apart from this, different interpretations of the term “sustainable development” imply that in fact data is not comparable. this study deals with 98 matching quantitative indicators examined in the outlooks, which are classified by 11 topic groups stated below: access to modern energy; energy efficiency; energy production; energy security; environment; final energy consumption; final energy supply; global context; installed generation capacity; primary energy resources; technology. the data analysis allows demonstrating the indicator groups covered by organizations (figure 1). a detailed assessment of particularities of each of the energy development outlooks requires profound research, as each organization uses a certain model and applies it to build several scenarios, which mainly differ by degree of consistency between national economic and political measures aiming to achieve sustainable energy, as well as technological development incentives and changes in models of consumers’ economic behavior (industry, transport sector and households) (salygin and litvinyuk, 2016). nowadays, a significant interest is demonstrated in rethinking the very energy system structure considering global adoption guliyev and litvinyuk: issues for long-range projection of international energy markets through the prism of sustainable development international journal of energy economics and policy | vol 7 • issue 2 • 2017298 of sustainable development concept, which subsequently may contribute to gradual change in the energy paradigm. however, russian scientific centers are currently mainly guided by traditional views on the energy development. existing methods of forecasting of global energy development mainly represent stochastic models of economic-mathematical analysis. at the same time, a modern energy development model requires consideration of not only of supply and demand in energy markets, but also the results of deployment of modern technologies in the industry within the value chain, the current state energy policy and other non-market values, which, however, secure market equilibrium through indirect regulation of energy prices. the architecture of global energy system remains one of the most controversial issues. the development of potentially possible ways for energy development, which is both a cause and a solution for overcoming global challenges, will be able to assist in the identification of consequences of their implementation and improvement of validity of taken decisions. in order to identify global trends of energy development and predict its future state a number of specialized international organizations, research institutes and industry experts direct their efforts to the search for the key factors and driving forces characterizing the dynamics and direction of global energy system development. they monitor and analyze quantitative and qualitative assessment of global energy system development indicators, ensure the alignment of the global energy picture at a time in the future. as for the indicators classification, their significant variation by covered scope is to be mentioned. the greatest number of matching indicators is encountered in the global context, which underlines global economic growth, population growth, poverty reduction as well as ongoing role of fossil fuels as the foundation of the most countries’ energy mix. ongoing changes of energy markets currently hold orientation towards the asian region, which already has high demand for energy due to rapid economic development (belogoryev et al., 2011). consensus among outlooks is also observed in terms of the evident fact that all kinds of energy resources suffice to meet the needs of the next generations, which is basic conception of sustainable development in terms of energy. depletion of fossil fuels is not subject of the research, however, the significance of conventional fuel reserves threat is stressed in the future. table 1: world’s most advanced models for energy development forecasting parameter markal wem primes scaner poles nems approach bottom up bottom up, top down top down bottom up, top down bottom up, top down bottom up, top down coverage wec, 2013 opec, 2014 eia, 2014 eu, 2013 eri, 2013 eu, 2003 eia, 2014 time horizon over 80 years 25 years 35 years over 15 years over 25 years over 25 years step 10 years 5 years 5 years 5 years 10 years 10 years regional coverage world, 8 regions world, 17 regions, 3 regional grouping, 12 countries world, 9 regions, 7 subregional grouping, 5 special countries grouping world, 62 influential countries, 83 territorial entities of the russian federation world, 7 regions, 3 subregional grouping national level (usa) value chain production, transportation, distribution, consumption, co2 emissions production, distribution, consumption, pollution emissions investments, production, transportation, distribution, consumption, pollution emissions investments, production, transportation, consumption, co2 emissions production, distribution, consumption, co2 emissions production, transportation, distribution, consumption, pollution emissions amount of the considered energy source 15, with subsequent aggregation into 7 groups according to methodology 7 11 able to incorporate over 20 sources 12 7 groups (no reliable data on the structure) wec: world energy council, opec: organization of petroleum exporting countries, eu: european union figure 1: scope of the indicator groups covered by world energy council, organization of petroleum exporting countries and international energy agency according to the classification guliyev and litvinyuk: issues for long-range projection of international energy markets through the prism of sustainable development international journal of energy economics and policy | vol 7 • issue 2 • 2017 299 moreover, estimations are remarkably diverged considering different views of experts regarding the current development tendencies. such diversions imply the fact that references to a certain scenario are quite unfounded. in order to use calculated indicators for energy markets, more calculations are to be processed and practically implemented scenarios are to be taken into account. world-widely used energy development models including regional integrations analysis along with considered indicators include thousands of endogenous variables. since these sets of variables are often different by structure, the question arises whether it is worth developing new models, which could potentially integrate a wider range of indicators providing better representation and interconnection. thus, the key factor to achieve sustainable energy development is to holistically overcome traditional framework regulating the scope for energy system analysis, through coordinated transition from “forecasting” of energy systems development to “scenario building.” considering insufficient transparency applied for modeling methodologies, it is critically important to ensure interconnection between specific international organizations, governments, research centers and energy companies in order to develop coordinated approaches to the problems of energy system modeling, and instruments allowing to balance the interests of the parties, in energy, economy, social aspects, geopolitics, environment and technological development. 4. suggested methodological change in approach to energy system modelling it is impossible to predict the future. however, it is quite an affordable aim to anticipate the trends in global energy development. is it possible to achieve the goals of sustainable development or to coordinate the efforts of every country in terms of climate change? what will be the development of energy technologies? will their application be economically viable, founded and world-widely used? how the global energy mix will look like in the future? will renewable energy become the global solution? how will the state policy be pursued in terms of energy subsidies and tariffs? for these and related questions to be answered, it is necessary to profoundly analyze indicators, identify interlinkages between the factors, define the impact of national energy policies on regional and global development, and evaluate changes in consumers’ market behavior. key issues for energy system forecasts in terms of sustainable development along with the relevant factors and possible impact of these factors on further energy system development are demonstrated in table 2 (guliyev, 2012; makarov et al., 2013; elzinga and litvinyuk, 2015; karjalainen et al., 2014; mai et al., 2013). also, factors that can be used as describing characteristics of the future international economic relations systems classified by three groups: macroeconomic, mesoeconomic and microeconomic. these levels are essential for energy forecasts. the list of these factors is stated in table 3. the scope of the above research allows exposing certain strengths and weaknesses as well as opportunities and threats for sustainable energy development scenario building exercise, and allows conducting strengths, weaknesses opportunities, threats analysis presented in table 4. 5. conclusion the broad sense of the sustainability concept is reflected in national and regional energy strategies, which leads to varying approaches and results. governments of certain states define consistent energy generation as complete refusal of exhaustible energy resources and full switch to the use of renewable resources in the short-run where greenhouse gas emission reduction is an integral part. representatives of other countries stress the necessity to increase energy efficiency and make energy sources available to the poor. while the identification of priorities concerning conservation of climate is underway, certain countries are not ready to stop using exhaustible energy resources concentrating on carbon dioxide emission reduction. every state follows its energy strategy, based on its own priorities and views regarding considered issues such as climate change mitigation, sustainable development, environmental protection, poverty reduction, improvement of the quality of life, etc. (gabrial and mcglade, 2012). sustainable development of the whole energy system in the future is considered to be a basic element, which is supposed to combine ecological, economic and social aspects. such system will include every aspect of energy system development according to national requirements and problems including climate change and use of natural resources, job creation and energy security. it seems important to define the concept of sustainability with respect to energy, both in the context of mitigating negative environmental effects and it the context of ensuring the security of energy system for sustainable economic development. within the scope of this project it would be possible to develop methodology and tools for conducting assessment of global energy development scenarios, systematic research of various forecasts, comparison of existing (reference) and newly developed scenarios, which will provide an opportunity to conduct research of alternate strategic opportunities and priorities for achieving the goals of sustainable development in energy sector. in the project it is intended to develop sustainable development indicators for energy sector. the development will be based on the conceptual approach “purpose-objectives-indicators” embodied in sustainable development goals adopted at the un in september 2016 for all countries worldwide for the period of 2016-2030. certain goals are connected to energy development either directly or implicitly. the analysis of the restrictions for the energy sector due to the adoption by russia of the paris climate agreement will be also guliyev and litvinyuk: issues for long-range projection of international energy markets through the prism of sustainable development international journal of energy economics and policy | vol 7 • issue 2 • 2017300 table 2: key topics to forecast the energy systems development under sustainable development topic influenced factors possible factors’ influence on energy system development consumer energy needs in the period ahead. economic choice criteria for consumers dependency factor of the electrical grid consumption energy efficiency electricity price, grid parity availability or deficit of electricity development of electricity infrastructure individual generation technology population growth energy safety in a bread sense (energy importers and exporters positions) growth of middle class lack of knowledge and skills consumption pattern modification quality of energy service distributed generation development of energy service companies evolvement of “client-first” approach energy distribution and consumption legal framework trade development via law incentives legislation development in developing countries legislation development including ecological principles decentralization, liberalization, deregulation disruptive technologies, which provide the electric generation structure modification business model consumer oriented commercial model price of the new technologies model driver for disruptive technologies model (objective necessity for the “survival” goals or the innovation solution realization) technical solutions model commercial model modification from “based on the technology development level” to “based on the market conditions” innovation technologies implementation opportunity basic energy resources structure for electricity generation modification of electric generation technologies fuel energy production growth energy consumption trends role of energy resources in the country’s development local component requirements energy resources supply energy interconnectivity supply chain limits price of fossil fuels system risks (cross-border infrastructure projects in energy) new technologies implementation (key energy markets) role of the selected countries’ energy markets in the global context consistent development of technology along with technological break thoughts the balance between innovations and market demand traditional technical solutions, that manage energy based on culture of energy consumption development of energy storage business struggle between traditional energy and renewable source energy results of technical and economical study for feasibility of integration of innovative technologies role of telecommunications and media in energy sector telecommunication technologies development commercial models in the sector strategy plan for keeping the public informed technological improvement opportunities role of telecommunication sector in energy management education poverty problem education improvement ability to follow technology development human factor and its characteristic labor capacity (contd...) guliyev and litvinyuk: issues for long-range projection of international energy markets through the prism of sustainable development international journal of energy economics and policy | vol 7 • issue 2 • 2017 301 topic influenced factors possible factors’ influence on energy system development rhetoric of international negotiating process cooperative solutions development and coordinated actions implementation institutional failures motivation for decision makers public awareness drivers in the world key energy markets partnership and communication between government and business national industrial policies influence of legislation and politics on technology and business decentralized electricity generation renewable energy facilities as major companies’ assets incorporation of environmental element and its prioritization into national policies common energy market. architecture and target model of regional electric energy markets. price convergence of energy energy service accessibility technological transfer new sources of energy labor integration energy price (“affordability”) role of nongovernmental agencies and business sector decentralized generation, local power grids meaning of the energy for humanity in general living standards common energy system or isolated national energy systems global climate agreements obligations, contracted by the poorest countries correspondence of political efforts to real requests of consumers fair energy price common electric energy market regional energy market target model (trade, energy balance, coordination) price of greenhouse gases emissions development and implementation of commercial models based on sustainable development principles rhetoric change of the negotiation process including questions of achieving sustainable development goals at the global level table 2: (continued) characteristics macroeconomics mesoeconomics microeconomics key unknown factors global economic environment objectives coordination of universal access to energy sources with actions to combat climate change optimal generation structure based on balance of renewable and conventional energy achieving sustainable development goals on national levels key participants major states (population, production levels, energy consumption) asean member states sustainability of energy products export from major energy-exporting countries issues of water-energy-food nexus economic availability of new energy sources (development of technologies) demographics and energy consumption growth uncertainty with respect to the development of small countries geopolitical and economic sustainability of world’s largest economies deployment of available (including economically) energy technologies centralized or distributed generation interplay between telecommunication and energy (remote control of networks, consumption control) local energy systems limited resources (including water-energy-food nexus) water supply deficit energy storage technologies and their availability for end-users labor efficiency table 3: descriptive characteristics of international economic relations (by levels of impact) for the purpose of energy development forecasting (contd...) guliyev and litvinyuk: issues for long-range projection of international energy markets through the prism of sustainable development international journal of energy economics and policy | vol 7 • issue 2 • 2017302 characteristics macroeconomics mesoeconomics microeconomics the role of consumers in creating energy systems, which meet their demand availability and transparency of information sources major factors international cooperation on challenges concerning measures to combat climate change alteration of traditional business model social request concerning environmental quality potential for atomic energy industry development pre-defined elements fossil fuels supplies will retain their role in consumption pattern global leadership of certain states with respect to environment-oriented issues and actions mitigating the effects of climate change social aspects urban population increase population increase educational level social inequality and its effects on economic growth healthcare (connection to ecological issues) economic aspects quality of life diversion in economic growth rate on the sub-regional level might exert pressure on the relations between countries ecological aspects issues of pollutant emissions development of pollutant capture and sequestration technologies political (geopolitical) and legal aspects governmental influence on economic and political situation in other states development of technical regulations, rules and standards political support of standards harmonization process practical implementation of the developed standards technological aspects role of states in achieving goal to establish a sustainable energy system table 4: swot‑analysis of factors that influence energy development strengths weaknesses significant financial resources high level of education, knowledge and skills access to basic energy technologies at fair price potential for renewable energy development regional cooperation more of a political dialogue rather than actual interest of states “developed states forgot how to struggle against socio-economic difficulties” (gurtner, 2009) lack of coordination at interstate level varying goals and priorities of states (especially with respect to energy security) low level of energy efficiency in certain parts of the world and inability to increase it (tromop et al., 2015) opportunities threats promotion of cooperation on common issues technological progress harmonization of standards increase in existing assets’ energy efficiency use of low-cost energy sources technologies investments in energy infrastructure, ensuring its flexibility investments in energy efficiency investments in renewable energy global energy security system exchange of experience and best practices at a country and company levels relations to facilitate the assurance of non-confrontational coexistence absence of shared vision of the development strategy on the regional level, unrealized gains varying opinions and interpretations of the term “sustainability” by the states, which leads to non-compliance of national policies conflict of interests low efficiency of reorganization due to human factor swot: strengths, weaknesses opportunities, threats table 3: (continued) carried out. based on the outcomes, a new forecasting method of energy markets development will be developed, considering geoeconomic, geopolitical and geo-ecological processes. according to the new forecasting, practical recommendations concerning the development of concept for transition to sustainable development will be proposed. references belogoryev, a.m., bushuyev, v.v., gromov, a.i., kurichev, n.k., mastepanov, a.m., troitsky, a.a. (2011), trends and development scenarios of the global energy in the first half of the xxi century. london: energiya. guliyev and litvinyuk: issues for long-range projection of international energy markets through the prism of sustainable development international journal of energy economics and policy | vol 7 • issue 2 • 2017 303 benichou, l., mayr, s. (2014), a world energy scenario modeling tool for transparent energy system thinking. frontiers in energy research. energy systems and policy. bhattacharyya, b.c., timilsina, g.r. (2009), energy demand models for policy formulation. the world bank development research group, environment and energy team. densing, m., turton, h., panos, e., volkart, k. (2013), global energy scenarios 2050 of the world energy council. switzerland: paul scherrer institute. elzinga, d., litvinyuk, i. (2015), setting the stage for future sustainable energy systems. switzerland: un special. gabrial, a., mcglade, c. (2012), modelling carbon price impacts of global energy scenarios. united kingdom: ucl energy institute. greene, d.l. (2001), long-term energy scenario models: a review of the literature and recommendations. united states: oak ridge national laboratory. guliyev, i.a. (2012), evaluation of intrastructural and external economic transformation of strategic enterprises in the circumstances of financial and economic instability. series 21: management (state and society). moscow: bulletin of moscow university. gurtner, b. (2009), the financial and economic crisis and developing countries. available from: https://www.poldev.revues.org/144. [last retrieved on 2017 feb 28]. jose, r., assis, a. (2015), modelling and analysis of global energy scenario. international journal of engineering research and technology, 4(4), 812-816. karjalainen, j., käkönen, m., luukkanen, j., vehmas, j. (2014), energy models and scenarios in the era of climate change. finland: finland futures research centre. mai, t., logan, j., blair, n., sullivan, p., bazilian, m. (2013), a decision maker’s guide to evaluating energy scenarios, modeling, and assumptions. united states: national renewable energy laboratory, joint institute for strategic energy analysis. makarov, a.a., mitrova, t.a., grigor’yev, l.m., filippov, s.p. (2013), global and russian energy outlook to 2040. eri ras, analytical center for the government of the russian federation. salygin, v.i., litvinyuk, i.i. (2016), evaluation of world energy. paris: bulletin of mgimo-university. tromop, r., badaker, v., dzioubinski, o., foster, s., held, s., litvinyuk, i. (2015), best policy practices for promoting energy efficiency. unece energy series 43. new york: united nations publications. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 1 • 2023 335 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(1), 335-351. impact of oil exports on imports of agricultural machinery and equipment sugra ingilab humbatova1, galib bahram hajiyev2, leyla zakir aliyeva3, natig gadim-oglu hajiyev4* 1head of depatment economics, unec/azerbaijan state university of economics. istiqlaliyyat str. 6, baku, az1001, azerbaijan, 2depatment economics, unec/azerbaijan state university of economics. istiqlaliyyat str. 6, baku, az1001, azerbaijan, 3depatment economics, unec/azerbaijan state university of economics. istiqlaliyyat str. 6, baku, az1001, azerbaijan, 4depatment economics, unec/azerbaijan state university of economics. istiqlaliyyat str. 6, baku, az1001, azerbaijan, center for agricultural research, ministry of agriculture, baku, azerbaijan. *email: n.qadjiev2012@yandex.ru received: 14 september 2022 accepted: 05 january 2023 doi: https://doi.org/10.32479/ijeep.13719 abstract the influence of the main export product on the main import product is the focus of any country. in this regard, since oil and oil products are the main export commodity of azerbaijan, their impact on the import of machinery and equipment necessary for the development of the agricultural and agro-processing industries, which are the main imported products, was chosen as the subject of study. the purpose of the article was to assess the impact of the export of oil and oil products on the import of machinery and equipment necessary for the development of the agricultural sector and the agro-processing industry. the study used data for the period from 1999 to 2020. ardl and ecm methods were applied and compared with fmols, dols and ccr as a validation. during the study, 9 hypotheses were proposed. all hypotheses have been proven to some extent. the results of the study show that, like all industries, the agricultural sector depends on the oil factor. thus, the export of oil to the republic has a positive effect on imports and, of course, on the imports of many machineries and equipment necessary for the development of the agricultural sector, especially agricultural machinery for tillage and harvesting, equipment for the food industry and equipment for processing agricultural products. the overall result of the research was a recommendation to further acceleration of work aimed at diversifying the economy and developing the non-oil sector, similar to the results of other similar studies (researches investigating resource-exporting economies). keywords: oil export, export oil products, agriculture, import of machinery and equipment, fmols jel classifications: q02, q17, q37, o13, o24 1. introduction azerbaijan is among the countries rich in natural resources. but agriculture and industry should be considered as key sectors of the economy that provide inputs and output for each other (muhammad et al., 2021). according to the general economic law, as well as the theories of trade and foreign trade, each entity brings to the market those products that it has more of and the costs of which are absolute or relative. instead, it imports products and services that it does not have and that are absolutely or relatively expensive to produce. currently, azerbaijan mainly supplies oil (crude oil) to the world market. it is true that in the last 10-15 years, gas exports have also occupied an important place. however, the main export component for many years to come will be the export of oil. in 2020, the share of exports of crude oil is 68.18%, and the share of crude oil and oil products (kerosene for jet engines, heavy distillates or gas oils for other purposes, lubricants, petroleum coke, liquid fuels) is 70.31.% was. the survey will examine the dependence of products on the export of crude oil, as well as crude oil and petroleum products: the share of imports of agricultural machinery for tillage and harvesting is 0.25%, the share of imports of equipment for processing agricultural products is 0.18%, and the share of imports of equipment for the food industry is 0.10%. this journal is licensed under a creative commons attribution 4.0 international license humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023336 moreover, the share of imports of other products in the same year was as follows: 11.5%-food, 2%-cars, 3%-drugs and medical supplies, 5.7%-products of ferrous metallurgy and engineering, 2%-forestry products, 1.8%-chemical industry products, 0.9%-household appliances, 2%-telephone sets for a mobile or other wireless communication network, etc. however, the strength of each state lies in the strength of its economy, which ensures its economic security. one of the main components of economic security, and i think the first one, is food security. ensuring food security directly depends on the development of agriculture. in this regard, the diversification of the economy is one of the priorities in many resource-rich countries, so this issue has always been on the agenda in azerbaijan. growth of agriculture and food self-sufficiency, as we mentioned above, this research work was started by recognizing the dependence of agricultural development on the development of agriculture and the import of agricultural machinery for tillage and harvesting, equipment for processing agricultural products and equipment for food processing. 2. the role of oil on the world economy we would like to start the section dedicated to the role of oil in the world economy with the following quote: “in the grand tradition of epic storytelling, the prize tells the panoramic history of oiland the struggle for wealth and power that has always surrounded oil. it is a struggle that has shaken the world economy, dictated the outcome of wars, and transformed the destiny of men and nations.” (yergin, 1991), “the prize is as much a history of the modern world as of the oil industry itself, for oil has shaped the politics of the twentieth century and has profoundly changed the way we lead our daily lives.” (yergin, 1991). the large role of oil in the global economy should be taken for granted. nature is made up of energy. all living beings consume and produce energy for their existence. in other words, they transfer energy from one form to another. population growth and increased production and consumption (of products) and their diversity of substitute and complementary products have increased the demand for energy and its role in the economy, including in the global economy. since the industrial revolutions, as in any field, the numerical and geometric series have increased and this process continues going up. from this perspective, the demand for oil began to increase rapidly from the late 19th century to the early 20th century. politicians, government officials, the financial sector, as well as the real sector of the economy, as well as those who work there, including economists and researchers, began to be interested in this issue, and no matter what area they study, they studied the oil factor at least a few times. a clear proof of this can be the authors given in the literature review. the relevance of the oil price never loses its position for a moment: “with oil prices cascading to new highs over the past few years, the topic of energy prices has once again come to the fore” (rogoff, 2006). “there is now broad consensus among that oil price fluctuations impact global economic growth are somewhat less than they did two to three decades ago ago.”(rogoff, 2006). “the run -up of oil prices over the last decade resulted from strong growth of demand from emerging economies confronting limited physical potential to increase production from conventional sources.” (hamilton, 2014), “moreover, for reasons discussed later in the paper, the view that oil prices affect the economy through a channel other than the process of labor reallocation cannot be rejected.” (loungani, 1986). “t is widely accepted that fluctuations in the world price of oil have substantial real effectson the u.s. macroeconomy (e.g., hamilton [1983], loungani [1986], shapiro and watson [1988], perron [1989])” (keane and prasad, 1996). in particular, the fact that the expression “my conclusion is that hundred-dollar oil is here to stay” (hamilton, 2014) mentioned by hamilton in 2014 is confirmed by “for example, analysts at the bank of america warned on october 1, 2021, that oil could surge above $100 in the event of a cold winter and spark inflation (lee and cho, 2021). this sentiment is common on wall street. similar views have been expressed by other investment banks including goldman sachs, jp morgan and barclay. likewise, blackrock, the world’s top asset manager, recently stated that there is a high probability of oil hitting $100 a barrel. despite these warnings, there has been no quantitative analysis of this scenario” in the article published by kilian and xiaoqing (2022), indicates the relevance of the oil factor not only in the world economy, but also in the world political arena as a whole. 3. literature review the significance of oil resources to boost economy, to establish political power of the country and to strenghten its position for international relations commenced to surge up since the beginning of the xx century by arithmetic sequence and contiunued to go up by geometric sequence later. it is hard to find a scientist who neither touched the oil factor or did a fundamental research in the last 50-60 years. however, this trend commenced to be common since 90 s of xx century. for example, forbes (1941), parcher (1947), cauley (1959), wilson (1974), allan and mclachlan (1976), penrose (1976), gavett (1977), hassan (1978), denisard and disch (1981), ahmed (1985), hojman (1987), wells (1988), naanen (1988), falola (1988), majd (1989), hanson et al. (1993), auty and warhurst (1993), yazdanpanah (1994), sachs and warner (1995), uri (1995), uri (1996), parker, (1997), mohamed et al. (2009), mohammadi and jahan-parvar (2011), shaari et al., (2013), mikayilov et al. (2020), (mukhtarov et al., 2020) etc. in fact, these researches refer to oil price fluctuations and the influence of the price on the economy of oil-importing and exporting countries. the impact on the development of any field is limited only by researching the influence on the price of the products of this field. our research work is not related with the oil prices but it covers the impact of the import of technology, machinery and equipment which indirectly infuence on the development of agriculture. meanwhile, since there is no literature about it, we are obliged to refer to the researches about the impact of oil price fluctuation on the agricultural products and food price fluctuation. 3.1. oil prices and the impact of oil production on the economy and agrarian economy fardmanesh (1991) assessed the effect of dutch oil boom disease for oil exporting countries as venesuela, nigeria, indonesia, eucador, algeria between 1966 and 1986. based on research humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023 337 findings, their structure changes due to the increase in the world prices and the influence of the costs of industrial products compared to agricultural commodities and oil prices. both effects expand the manufacturing sectors of these countries and reduce their agricultural fields. cost effects expand their non-tradable sectors, while world price effects can expand or reduce them. the opposite results were predicted for the oil collapse of the 1980 s. karbasi et al. (2009) kobba douglas studied the effect of energy factor on gross production of economy and agriculture using production function and ardl method during 1981-2005 in iran. results show that the production elasticities of labor, capital and energy factors of iran’s agriculture sector are 0.36, 0.23 and 0.32, respectively. beside, the production elasticities of labor, last year capital and energy factors of iran’s total economy are 0.55, 0.46 and 1.17, respectively. both cases indicate that agriculture and overall economy are strongly dependent on energy factors. thus, saban et al. (2013) researched the effects of oil fluctuation on agricultural products based on the daily data between 01 january 1986-31 december 2005 and 01 january 2006-21 march 2011. they concluded that (test recently developed by hafner and herwartz, 2006) although there was no any risk transfer between oil and agricultural markets prior to crisis, while after crises oil market volatility is reflected in the agricultural markets except sugar. the impulse response analysis (garch) reveals that the shock is transferred to agricultural products after oil price fluctuation only after crisis. so, the transfer dynamics of the fluctuation significantly changes after food price crisis. tranferring risk after crisis turns into another aspect of dynamic mutual relations between energy and agricultural markets. they also concluded that the dependency has unbelievably increased among energy and agricultural markets recently. oyetade et al. (2016) used vecm and var methods and examined the relationship among agricultural export, oil export and output growth in nigeria from 1981 to 2014. the study revealed that there is significant relationship between economic growth and the agricultural export and oil export. based on the findings, government of the country is being advised to initiate new and redefined old policies that will diversify the export base. kakanov et al. (2018) provide a comprehensive analysis of the “resource curse” phenomenon, i.e. the negative impact of oil abundance on long-term economic growth, for a set of oil exporting countries. the empirical analysis relies on oil exporters between 1982 and 2012 and an error correction model (ecm). the paper provides robust evidence in favour of the resource curse hypothesis, and there is no evidence that higher quality institutions could mitigate the curse. oil price shocks appear to have an asymmetric impact in the short run: the growth effect is positive when oil prices rise, while no statistically significant effect is observed when they fall. there is also indirect evidence that the impact of an oil price shock is partly offset by fiscal policies, particularly in countries with high oil dependence. in the long run, oil price volatility does not appear to have a statistically significant impact on gdp. exchange rate regimes seem to play a role: countries allowing their currencies to float seem to gain from positive oil price shocks in the short run, but in the long run a fixed exchange rate regime is associated with higher gdp, probably owing to active stabilisation by sovereign wealth funds. before abdlaziz et al. (2018) investigated the panel co-integration analysis of oil prices on agriculture in 25 oil-exporting countries between 1975 and 2004 during dutch disease. the article fully modified ols (fmols), dynamic (ols) and (pmg) methods to examine the long-run effect of real oil price and real exchange rate on agriculture. the result of the pedroni cointegration exposes the long-run relationship between the variables under study. panel cointegration estimators show the negative and significant effect of oil price and exchange rate on agriculture value added. these results indicate the existence of the dutch disease and deagriculturalization in oil-exporting economies. ologunde et al. (2020) investigated the relationship between sustainable development and crude oil revenue (cor) in selected oil-producing african countries from 1992 to 2017 using the pooled mean group (pmg) estimators on panel autoregressive distributed lag model (ardl). in the panel analysis, the pmg estimator model has been seen as a good alternative to estimators such as dols and fmols. empirical results revealed that there was no long-term relationship between cor and sustainable development. in other words, the results suggest that any changes to cor have a potential negative effect on sustainable development in the selected countries. this implies over-reliance on cor will impact the economies negatively in the long run. this finding, therefore, requires an immediate fiscal intervention on spending on sustainable development drivers such as education, health, agriculture cum adoption diversification policy. the findings proved once more that oil revenues in a long run will not be effective for sustainable development. conversely, if the use of oil revenues is not adequately diversified and supported by government institutions, it will have a negative impact. abdlaziz et al. (2021) used ardl method and researched the effect of revenue generated from oil on the added value of agricultural products in terms of the efficiency of real currency exchange among 25 oil-exporting countries during 1975-2014. the research concluded that revenue generated from oil directly and negatively affect the added value of agriculture in a long and short term. this impact is relatively strong in the major oil exporting countries but weak in the minor oil exporting countries. it can be inferred that in the long-run, the appreciation in real exchange rates exacerbate the negative marginal effects of oil revenue on agricultural value-added in all oil-exporting countries. however, the effects are different when considering maoec and mioec separately. when considering maoec, the contingent effect disappears (become insignificant) while in mioec, it is positive and statistically significant. thus, in the long-run, the appreciation in real exchange rates diminishes the negative marginal effects of oil revenue on agricultural value-added in mioec. while oil revenue has a direct negative effect, its effect is also moderated by the variations in reers in mioec in the long-run. finally, in the short-run, fluctuations in the real exchange rate do not matter for the nexus of oil revenue and agriculture sector in these countries whether minor or maoec countries. humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023338 aye and odhiambo (2021) conducted a threshold analysis of the growth between oil prices and agriculture on a quaterly based in south africa from 01.1980 to 01.2020. they assessed the relations between oil price and agriculture using tong (1983; 1990) and hansen (2011) autoregression threshold model. the findings showed if the rices crude oil either in dollars or in rands will have significant negative effects on agricultural growth in south africa. vasiljeva et al. (2022) used panel regression model and studied the aims of sustainable development and crude oil market functioning features (oil price, oil production) of opec++ participating countries in 1992-2020. findings reveal that reducing oil volume implied in opec+ and opec++ agreements will lead to stabilization of oil prices. however, it negatively affects sustainable development of countries. the reduction of oil production and export exert positive influence on the sustainable development of opec++ countries. the more the country developed the more positive effect it will be exerted or vice versa. this research reveals that in resource economies, a reduction in oil production and exports cannot have the same effect on sustainable development as in countries that do not produce oil, or are characterized by a higher level of economic development. this thesis is substantiated by the empirical confirm of the longterm adverse effect of the oil price growth on the realization of sustainable development goals. this effect is explained by the low level of economic diversification and the concept of “dutch disease” as widely elucidated by scientists. 3.2. impact of oil prices on agrarian prices zhang et al. (2008) used varma model, granger-causality test and johansen-juselius models and studied the impact of oil prices on agricultural commodity prices on maize, soybeans an pork prices in china from january 2000 to october 2007. the results might heavily influence food prices in china to sharply increase biofuel production and crude oil prices. olayungbo (2021) analysed the causal link of oil and food prices in the sample countries that are both food importing and oil exporting economies, using ardl panel method. the outcomes of the research encompassing annual data sets of 21 countries between 2001 and 2015 reveal that the short period analysis between oil prices and food prices is negative while positive effects exist in the long period. the causality result shows that causality runs from food prices to oil price. thus, the result implies that appropriate agricultural policies that promote favourable food prices and alternative energy options should be pursued in the countries to ensure sustained food and oil supply. harri et al. (2009) studied cointegration relations among oil price, raw material price and exchange rate using var method. their research encompassed the period form january 2000 to september 2008. authors relied on concluded johansen trace cointegration test (johansen, 1992; johansen and yuselius, 1992) and concluded that some raw materials such as corn, cotton and soybean has relations with oil prices. however, wheat has no evidence. also, exchange rates do play an important role in the linkage of prices over time. chen et al. (2010) analyzed the interactions between crude oil prices and wheat, maize, soybean prices. the empirical results taken by ardl method reveal that the change in each grain price is significantly influenced by the changes in the crude oil price and other grain prices during the period extending from the 3rd week in 2005 to the 20th week in 2008. it implies that grain commodities are competing with the derived demand for bio-fuels by using soybean or corn to produce ethanol or bio-diesel during the period of higher crude oil prices in these recent years. ibrahim’s (2015) research paper analyses the relations between food and oil prices for malaysia from 1971 to 201 using ardl model. the bounds test of the nardl specification suggests the presence of cointegration among the variables. the estimated nardl model affirms the presence of asymmetries in the food price behavior. namely, in the long run, there is a significant relation between oil price increases and food price. meanwhile, the long run, the relation between oil price reduction and the food price is absent. furthermore, in the short run, only changes in the positive oil price exert significant influences on the food price inflation. with the absence of significant influence of oil price reduction on the food price both in the long run and in the short run, the role of market power in shaping the behavior of malaysia’s food price is likely to be significant. olayungbo (2016) mainly focused on the causal link of oil and food prices in 39 developing and oil-exporting countriesfrom 2001 and 2013, based on annual data and ardl method. the cointegration test in several countries proved the presence of long term casual link between oil and food prices. the long term result exerted positive and significant influence of oil prices on food prices. however, the short term was positive but insignificant. therefore, the author of the article concluded that oil price impacts on food price in a long run and implies to establish appropriate agricultural policies that promote favourable conditions to insulate economy from global crises as a result of oil fluctuations. fowowe (2016) conducted an empirical investigation of the effects of oil prices on agricultural commodity prices, based on the weekly data, in south africa, from 2 january 2003 to 31 january 2014. structural breaks cointegration tests showed no evidence of a long-run relationship between oil prices and agricultural commodity prices in south africa. nonlinear causality tests showed no evidence that agricultural commodity prices in south africa respond to oil prices. the results show that agricultural commodity prices in south africa are neutral to global oil prices. olasunkanmi and oladele (2018) analyzed the impact of oil price shocks on agricultural commodity prices in nigeria using monthly data on oil prices, maize, wheat and soybean and exchange rate from 1997 to 2016. authors used dummy variables to capture periods of structural breaks in the selected agricultural commodity prices. linear ardl and non-linear ardl were estimated. asymmetric test using wald statistics revealed evidence of asymmetries which imply the positive and negative shocks of the same magnitude and do not have equal impact on agricultural commodity prices. the study found significant positive oil price changes in all cases with the expected positive sign, implying that humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023 339 increases in oil price lead to increases in agricultural commodities. similarly, exchange rate showed positive significant relationship with agricultural commodities. it is concluded that oil price has overall positive relationship and significant effect on agricultural commodity prices. the study recommended that since oil price was important in agricultural commodities prices, efforts should be geared towards local development of the oil sector. it will bring about positive spillover effect on the agricultural sector and ensure food availability at affordable prices thereby improving standard of living and welfare. meyer et al. (2018) studied assymmetric analysis of oil price changes on food prices in oilexporting developing countries between 2001 and 2014 using ardl and nardl method. they concluded that there is a positive and significant relationship between food and oil prices in a long run. simultaneously, they concluded that there is no long-term relations between the reduction in oil price and food price. authors recommended that oil-exporting developing countries should adjust their public policy schemes in such a way as to enable reductions in the oil price to trickle down to food prices. in addition, these countries should ensure the implementation of long-term agricultural policies aimed at insulating their economies from global food crises that may arise due to oil price increases. zmami and ben-salha (2019) used arl and nardl analysis and researched the impact of the brent and west texas intermediate (wti) oil prices on international food prices between january 1990 and october 2017. the findings confirm the presence of asymmetries since the overall food price is only affected by positive shocks on oil price in the long-run. while the dairy price index reacts to both positive and negative changes of oil price, the impact of oil price increases is found to be greater. the asymmetry is present for some other agricultural commodity prices in the short-run. they respond only to oil price decreases. they concluded that studies assuming the presence of a symmetric impact of oil price on food price might be flawed. chen et al. (2020) examined and compared samples how oil price impacts on food prices in high-and low-income oil-exporting countries before crisis (2000.01-2013.01) and during crisis (2013.02-2019.04). we found an inverse relationship between oil and food prices in the long run based on fmols, dols and panel granger causality test (pgct).the story has been different during the crisis period: in low-income countries and all the countries combined, oil and food prices co-move in the long run. the findings also suggest that economic structure and uncertain events (crises) dictate the behaviour and relationship between food and oil markets. food and oil prices may drift away in the short-run, but market forces turn them toward equilibrium in the long-run. moreover, low-income countries are indifferent in both periods due to limited capacity to balance the increasing demand for and supply of food items. radmehr and henneberry (2020) examined the relationship between food prices in iran from march 1995 to february 2018. they used pedroni co-integration tests, panel ardl, pooled mean group (pmg), dynamic fixed effect (dfe), mean group (mg), fully modified ordinary least square (fmols), dynamic ordinary least squares (dols), impulse-response functions, granger causality methods (1969) and tests in their research. results show that in both the short and the long-run, food prices would increase in response to an increase in energy prices. findings also suggest that the appreciation of the united states dollar (usd) in terms of the iranian rial exerts a positive and significant impact on food prices in the long run. onour (2021) used markov switching dynamic regressionmsdr, dynamic conditional correlation-dcc and generalized autoregressive conditional hetrosekadicity-garch models to research how the price changes between crude oil and food price (wheat, sugar, corn and fertiliser) from january 1988 to april 2018. the study suggests that when the oil prices increase during its low volatility, it leads to the reduction of food prices. on the contrary, when the oil prices increase during its high volatility, it leads to the increase of food prices. dynamic conditional correlationdcc of garch-reveals that the coefficients of oil price level are significantly and positively related to the conditional volatility of the price of food products. thus, the volatility of the food prices is determined not by the volatility of the price of oil, but by the level of the oil price at the extreme points. kirikkaleli and darbaz (2021) studied the causal relationship between energy prices and food prices based on monthly data from 01.1980 to 01.2019. their study attempts to utilize relatively newly developed methods, namely toda-yamamoto causality, fourier toda-yamamoto causality, and spectral bc causality tests. the toda-yamamoto causality, fourier toda-yamamoto causality test clearly reveals that there is bidirectional causality between the energy price index and food price indexes (grains, other food, and oils). on the contrary, tests showed a different result in terms of the relations between energy and oil. both test reveals that there is a bidirectional causality between oil and energy. in order to widely research the causality between energy and food prices, spectral granger causality method was used. the tests confirm the presence of causality in a long run between food price and energy prices. shokoohi and saghaian (2022) used var panel model and analysed the effect of the causal link between food price and energy of oil-exporting and oil-importing countries. they relied on the annual data between 1974 and 2018 and concluded that the impact of oil prices on food prices is different in oil exporting and importing countries. this effect reduces first in oil-importing countries but then makes corrections over a period of time. however, for oil exporting countries, these effects are increasing and significant. in addition, the effects of real gross domestic product (gdp) and exchange rates on food prices are statistically significant in oil exporting countries. however, they do not directly affect the prices of food calories and fat in countries that import crude oil. these results prove that crude oil prices, incomes and exchange rate policies in oil exporting countries play an effective role in fighting starvation and food security. 4. data and methodology 4.1. data descriptions humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023340 the research used time series (2000-2020) to study the dependency import of agricultural machines for tillage and harvest, food industry equipment, some, equipment for processing agricultural products on oil export/export of oil and oil products. all indicators are in us dollar and taken from azerbaijan statistic office (table 1 and graph 1). 4.2. methodology in this study, the assessment based on the ardl model is carried out in five stages. first, as in every study, several stationarity tests are performed to check whether there is a 0 or 1 co-integration procedure between the variables used. thus, there may be a co-integration relationship between variables that have this stationary characteristic (pesaran et al., 2001). after that, the optimal residual of the model variables is determined using standard information criteria such as aic (akaike information criterion) and sic (schwartz information criterion). the third step is to check the co-integration using the bounds check method. further, if the co-integration test indicates the presence of a co-integrating relationship between variables, then an error correction model is evaluated to further confirm the cointegrating relationship, as well as the short-term influence of the independent variables on the dependent variables. finally, the validity of the selected ardl models is tested using two statistics: cumulative sum of residuals (cusum) and cumulative sum of residual squares (cusumsq). lingxiao et al. (2016) had mentioned such a fact that, according to some data, despite the ardl model was proposed by charemza et al. [1997] pesaran et al. it was developed as a more applicable methodology by pesaran et al. (2001) and pesaran et al., 1999). it has several advantages over many other (e.g. engle-granger, johansen, and johansen and juselius) cointegration methods. so, this method can be applied in solving problems with a small data coverage period. at the same time, this method allows analysis with i(0) and/or i(1) data, provided that i(2) is not present. unlike the traditional method, it can use different lengths (lags) for different variables in the model. this significantly improves the fit of the model. estimation based on the ardl model helps to overcome the endogeneity problem, and since the lagged indicators of the dependent variables are used as explanatory (independent) variables, it provides reliable results even in cases where the number of observations is small (aliyev et al., 2016). besides, instead of evaluating a system of equations, as in the johansen method, only one equation is evaluated. if the ardl model is applied, the long -term and short -term effect coefficients, including the error correction period coefficient (etm), are also estimated here. the sequential steps are as follows. first, based on the ardl model, an unrestricted error correction model (ardl-ecm) is constructed, which includes long-term and short -term 0 40,000 80,000 120,000 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 2000 2005 2010 2015 2020 amth 0 10,000 20,000 30,000 fie 0 10,000 20,000 30,000 40,000 50,000 60,000 epap 0 400,000 800,000 1,200,000 1,600,000 2,000,000 eop 0 10,000,000 20,000,000 30,000,000 40,000,000 50,000,000 eoop 0 10,000,000 20,000,000 30,000,000 40,000,000 50,000,000 oe 6 7 8 9 10 11 12 logamth 4 6 8 10 12 logfie 7 8 9 10 11 logepap 12 13 14 15 16 17 18 logoe 12.5 13.0 13.5 14.0 14.5 logeop 13 14 15 16 17 18 logeoop -3 -2 -1 0 1 2 dnlogamth -1 0 1 2 3 4 dnlogfie -2 -1 0 1 2 3 dnlogepap -2 -1 0 1 2 3 dnlogoe -.8 -.4 .0 .4 .8 dnlogeop -2 -1 0 1 2 3 dnlogeoop graph 1: dynamics of indicators table 1: data and internet resource oe oil export (thousand manats) www. stat.gov.az eoop export of oil and oil products (kerosene fuel for jet engines, heavy distillates or gas oils for other purposes, lubricating oils, petroleum coke, liquid fuel) (thousand manats) www. stat.gov.az eop export of oil products (kerosene fuel for jet engines, heavy distillates or gas oils for other purposes, lubricating oils, petroleum coke, liquid fuel) (thousand manats) www. stat.gov.az amth agricultural machines for tillage and harvest (thousand manats) www. stat.gov.az fie food industry equipment (thousand manats) www. stat.gov.az epap equipment for processing agricultural products (thousand manats) www. stat.gov.az humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023 341 relationships between variables. explanatory variables in formulas (1), (3) and (5)-oil export, in formulas (2), (4) and (6)-export of oil and oil products 4.3. urt-stationary time series before using regression equation, we need to use urt to provide stability. this is important to determine the integration level and stationary for time series (variables) in modern empirical researches. so, using non -stationary time series causes wrong regression. that is why selecting the most appropriate model is important. the article used augmented dickey-fuller, (adf) (dickey and fuller, 1981), phillips-perron (pp) (phillips and perron, 1988), and kwiatkowski-phillips-schmidt-shin (kpss) (kwiatkowski et al., 1992) tests. the following hypothesis was put forth in the research: h10: the increase in oil exports increases imports of agricultural machinery for tillage and harvesting h20: the increase in oil exports increases the imports of equipment for the food industry h30: the increase in oil exports increases the import of equipment for the processing of agricultural products h40: the increase in exports of oil and oil products increases imports of agricultural machinery for tillage and harvesting h50: the increase in the export of oil and oil products increases the import of equipment for the food industry h60: the increase in the export of oil and oil products increases the import of equipment for the processing of agricultural products h70: the increase in the export of petroleum products increases the import of agricultural machinery for tillage and harvest h80: the increase in the export of oil products increases the import of equipment for the food industry h90: the increase in exports of petroleum products increases imports of equipment for processing agricultural products the following equations were used to study the impact of oil export/export of oil and oil products on import of agricultural machines for tillage and harvest, food industry equipment, some, equipment for processing agricultural products. logarithmically amth=f(oe) (1) amth=f(eoop) (2) amth=f(eop) (3) fie=f(oe) (4) fie=f(eoop) (5) fie=f(eop) (6) epap=f(oe) (7) epap=f(eoop) (8) epap=f(eop) (9) lnamth=β0+β1 lnoe+ε (10) lnamth=β0+β1 lneoop+ε (11) lnamth=β0+β1 lneop+ε (12) lnfie=β0+β1 lnoe+ε (13) lnfie=β0+β1 lneoop+ε (14) lnfie=β0+β1 lneop+ε (15) lnepap=β0+β1 lnoe+ε (16) lnepap=β0+β1 lneoop+ε (17) lnepap=β0+β1 lneop+ε (18) 4.4. ardlbt (autoregressive distributed lags bounds testing) the equation (10-18) as an initial step to evaluate the mutual relationships between variables in the long and short term was presented in ardl model (pesaran et al., 2001) equations (19-27)) as the following: ∆ = + ∆ + ∆ + = − = − ∑ ∑ lnamth lnamth lnoe lnamth t i p i t i p i t i i t β β β λ 0 1 1 1 0 2 1 −− −+ +1 2 1λ εi t toe (19) ∆ = + ∆ + ∆ + = − = − ∑ ∑ lnamth lnamth lneoop lnamt t i p i t i p i t i i β β β λ 0 1 1 1 0 2 1 hh eoopt i t t− −+ +1 2 1λ ε (20) ∆ = + ∆ + ∆ + = − = − ∑ ∑ lnamth lnamth lneop lnamth t i p i t i p i t i i β β β λ 0 1 1 1 0 2 1 tt i teop− −+1 2 1λ (21) ∆ = + ∆ + ∆ + + = − = − − ∑ ∑lnfie lnfie lnoe lnfie t i p i t i p i t i i t β β β λ 0 1 1 1 0 2 1 1 λλ ε 2 1i t toe − + (22) ∆ = + ∆ + ∆ + = − = − − ∑ ∑lnfie lnfie lneoop lnfie t i p i t i p i t i i t β β β λ 0 1 1 1 0 2 1 11 2 1 + +−λ εi t teoop (23) ∆ = + ∆ + ∆ + = − = − − ∑ ∑lnfie lnfie lneop lnfie t i p i t i p i t i i t β β β λ 0 1 1 1 0 2 1 1 ++ +−λ ε2 1i t teop (24) ∆ = + ∆ + ∆ + = − = −∑ ∑lnepap lnepap lnoe lnepap t i p i t i p i t i i t β β β λ 0 1 1 1 0 2 1 −− −+ +1 2 1λ εi t toe (25) ∆ = + ∆ + ∆ + = − = −∑ ∑lnepap lnepap lneoop lnepa t i p i t i p i t i i β β β λ 0 1 1 1 0 2 1 pp eoopt i t t− −+ +1 2 1λ ε (26) ∆ = + ∆ + ∆ + = − = − ∑ ∑ lnepap lnepap lneop lnepap t i p i t i p i t i i β β β λ 0 1 1 1 0 2 1 tt i t teop− −+ +1 2 1λ ε (27) in the formula, εt is white noise; ∆ is the first-order difference; p is the lag order, which is usually calculated by aic or sbc criterion; λ1i and λ2i is the long-term coefficient between variables; β1i and β2i is the shortterm coefficient between variables. β0 free number. lnlogarithm sign. humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023342 as the next step, the engle-granger (eg) co-integration test is applied. this test is mostly used to check long-term relationships (menegaki, 2019, 2020). however, it also provides an opportunity to explore short -term relationships and identify interactions between variables. the regression equation is estimated for the variables in the first step of the eg co-integration test. thus, the following equations for two variables are given (equations 28-25) lnamth lnoet t t= + +β λ ε0 1 (28) lnamth lneoopt t t= + +β λ ε0 1 (29) lnamth lneopt t t= + +β λ ε0 1 (30) lnfie lnoet t t= + +β λ ε0 1 (31) lnfie lneoopt t t= + +β λ ε0 1 (32) lnfie lneopt t t= + +β λ ε0 1 (33) lnepap lnoet t t= + +β λ ε0 1 (34) lnepap lneoopt t t= + +β λ ε0 1 (35) lnepap lneopt t t= + +β λ ε0 1 (36) here β0, λ1 are regression coefficients, lnamth lnfie and lnepap dependent variables as mentioned above, while lnoe, lneoop and lneop are independent variables, explanatory variables. εis error (is white noise), t–is time. after estimating the regression equation, the reliability of ε -is checked. when ε is stationary, it is said that there is a co-integrating relationship between the variables. based on these, it is also proved that these equations (28-36) are long-term equations. at the same time, ardlbt checks for any dependencies between variables after the ecm is installed. the ardl boundary testing co-integration method uses the wald test (f-stat) to test for the presence of a long-term co-integration test between selected variables. long-term interaction or co-integration (h0: λ1i = λ2i =0; h1: λ1i ≠ λ2i ≠ 0) is checked. that is, the null hypothesis of the absence of this relationship is tested. the alternative hypothesis means the existence of co-integrating relationships between the variables. according to the f-test statistic, there are 2 types of bounds (upper and lower bounds) (pesaran et al. 2001). if the evaluation value of f-test statistics is less than the lower bound, there is no significant long-term mutual relations among variables. otherwise, if f-test exceeds the upper bound, there is a long-term mutual relation. if the given statistics of f-test are within accepted values, the outcomes are uncertain. finally, ecm is evaluated using stationary variables, periodical lag, and white noise error (ect(t-1)). these variables are used to check cause and effect relations, in other words, to define the direction of power and dependency (equation (37-45)) (növbəti mərhələ, addım). having established mutual relations, the next step will be to evaluate the short and long term relations among variables. ecm was used to evaluate short term dependency (37-45): ∆ = + ∆ + ∆ + + = − = − − ∑ ∑ lnamth lnamth lnoe ect t i p i t i p i t i t β β β ϕ ε 0 1 1 1 0 2 1 1 tt (37) ∆ = + ∆ + ∆ + = − = − − ∑ ∑ lnamth lnamth lneoop ect t i p i t i p i t i t β β β ϕ 0 1 1 1 0 2 2 1 ++εt (38) ∆ = + ∆ + ∆ + + = − = − − ∑ ∑ lnamth lnamth lneop ect t i p i t i p i t i t β β β ϕ 0 1 1 1 0 2 3 1 εεt (39) ∆ = + ∆ + ∆ + + = − = − − ∑ ∑ lnfie lnfie lnoe ect t i p i t i p i t i t t β β β ϕ ε 0 1 1 1 0 2 4 1 (40) ∆ = + ∆ + ∆ + + = − = − − ∑ ∑ lnfie lnfie lneoop ect t i p i t i p i t i t β β β ϕ ε 0 1 1 1 0 2 5 1 tt (41) ∆ = + ∆ + ∆ + + = − = − − ∑ ∑ lnfie lnfie lneop ect t i p i t i p i t i t t β β β ϕ ε 0 1 1 1 0 2 6 1 (42) ∆ = + ∆ + ∆ + + = − = − − ∑ ∑ lnepap lnepap lnoe ect t i p i t i p i t i t β β β ϕ ε 0 1 1 1 0 2 7 1 tt (43) ∆ = + ∆ + ∆ + = − = − − ∑ ∑ lnepap lnepap lneoop ect t i p i t i p i t i t β β β ϕ 0 1 1 1 0 2 8 1 ++εt (44) ∆ = + ∆ + ∆ + + = − = − − ∑ ∑ lnepap lnepap lneop ect t i p i t i p i t i t β β β ϕ 0 1 1 1 0 2 9 1 εεt (45) humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023 343 here, β0,β1i,β2i and φ1,φ2,φ3,φ4,φ5,φ6,φ7,φ8,φ9 are coefficients. p– is the optimal lag and ε is the white noise error of the model. they define the mutual relations among variables. the regression equation is evaluated for variables in the first stage of the eg cointegration test. for example, if there is the cointegration relations, this dependency is evaluated. if the cointegration is stable, then ectt-1 is negative in terms of statistical significance. this coefficient is usually between −1 and 0. using equations 37-45, the following cause-and-effect relationships can be tested: the granger cause and effect relationship for the short run is evaluated using f-statistical or xi-square statistical values by checking the statistical significance of the coefficients of all delayed first-order differences (all ∆lnoet-i, ∆lneoopt-i and ∆lneopt-i) together for each free variable (null hypothesis: h0: β2i = 0,i = 1…p). the rejection of the null hypothesis suggests that lnoe, lneoop and lneop have short-term effects on lnamth lnfie and lnepap. using the t test to check the granger cause and effect relationship for the long run, the statistical significance of the coefficient table 2: results of unified root tests model variable adf pp kpss with intercept only at level form lnoe −2.111885 −2.620692 0.511051** lneoop −2.395482 −2.395482 0.491440** lneop −1.145315 −1.441392 0.175976 lnamth −1.812818 −1.529145 0.741095*** lnfie −4.508987*** −6.010952*** 0.662537** lnepap −4.046870*** −2.367039 0.246016 at first differencing ∆lnoe −6.800788*** −6.800788*** 0.335760* ∆nleoop −6.671246*** −6.671246*** 0.363220* ∆lneop −3.119722** −3.125357** 0.539249** ∆lnamsth −5.825820*** −6.664843*** 0.276569 ∆lnefi −7.410029*** −15.52941*** 0.343586* ∆lnepap −3.730714** −5.282537*** 0.213513 with intercept and trend at level form lnoe −2.261830 −2.166894 0.164158** lneoop −1.032932 −1.818199 0.164772** lneop −0.937024 −0.739019 0.168525** lnamth −3.309202* −1.529145 0.119574* lnfie −2.408524 −6.922448*** 0.198260** lnepap −2.858500 −2.455144 0.129803* at first differencing ∆loe −7.310314*** −7.972479*** 0.073724 ∆lneoop −7.201363*** −7.792329*** 0.093597 ∆lneop −3.843482** −3.572439* 0.101590 ∆lnamth −3.229580* −8.997660*** 0.276827*** ∆lnfie −5.197627*** −23.45883*** 0.104477 ∆lnepap −4.418839 −6.669006*** 0.247333** no intercept and no trend at level form lnoe 1.064828 0.753004 n/a lneoop 1.026733 0.990857 n/a lneop −0.018981 −0.018981 n/a lnamth 0.887323 0.741095 n/a lnfie 0.811147 0.801163 n/a lnepap 0.011546 0.263415 n/a at first differencing ∆loe −6.700234*** −6.700234*** n/a ∆lneoop −6.525613*** −6.574837*** n/a ∆lneop −3.238435*** −3.244022*** n/a ∆lnamth −5.731890*** −5.118680*** n/a ∆lnfie −5.197627*** −9.706088*** n/a ∆lnepap −3.851689 −5.288212*** n/a lnoe i (1) lneoop i (1) lneop i (1) lnamth i (1) lnfie i (1) lnepap i (1) adf denotes the augmented dickey-fuller single root system respectively. pp phillips-perron is single root system. kpss denotes kwiatkowski-phillips-schmidt-shin single root system. ***, **and *indicate rejection of the null hypotheses at the 1%, 5% and 10% significance levels respectively. the critical values are taken from mackinnon (mackinnon, 1996). assessment period: 1999-2020. legend: s-stationarity; n/s-no stationarity n/a-not applicable humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023344 ectt-1 is checked. the null hypothesis for this (h0: φ1 = 0, φ2 = 0,φ3= 0,φ4 = 0,φ5 = 0,φ6 = 0,φ7 = 0,φ8 = 0 and φ9 = 0) needs to test. if, as a result, the null hypothesis is rejected, this long-run period shows that deviations from the equilibrium state have an effect on the dependent variable and will return to the equilibrium state over time. a strong cause-and-effect relationship is, in fact, both a short-term and a long-term and-effect relationship. in other words, using the f-statistic or xi-square statistical values through the wald test as a null hypothesis for each variable taken (h0: β2i = φ1 = 0,i= 1…p,; h0: β2i = φ2 = 0,i= 1…p,; h0: β2i = φ3 = 0,i= 1…p,; h0: β2i = φ4 = 0,i= 1…p,; h0: β2i = φ5 = 0,i= 1…p,; h0: β2i=φ6 = 0,i= 1…p,; h0: β2i =φ7 = 0,i = 1…p,; h0: β2i =φ8 = 0,i = 1…p,; h0: β2i =φ9 = 0,i = 1…p,;) hypotheses are tested. 4.5. fmols, dols and ccr fully modified ordinary least squares (fmols) (phillips and hansen, 1990), dynamic ordinary least squares (dols) (stock and watson, 1993), canonical cointegrating regression (ccr) (park, 1992) and analysis of the results of engle-granger analysis (engle and granger, 1987) are very useful in the research process (musayev and aliyev, 2017). because reviewing the results several times through the ardlbt co-integration approach allows for a more reliable analysis. engle-granger and phillips-ouliaris (phillips and ouliaris, 1990) cointegration tests were used to test for all regression equations evaluated using fmols, dols, and ccr. 4.6. diagnostics in this study, both the breusch-godfrey lm test (breusch, 1978; godfrey, 1978), (breuschgodfrey [bg] test) the heteroscedasticity test, and the breusch-pagan-godfrey test (breusch and pagan, 1979), as well as the autoregressive conditional heteroskedasticity test (bollerslev, 1986), test arch (engle, 1982) and ramsey reset test (ramsey, 1969) (statistical) check the stability of the ardl model. the j-b normality test (jarque and bera, 1980; 1981; 1987) will be used to check the normal distribution of white noise error. the cusum and cusumsq tests (brown et al., 1975) are also used to investigate the stability of the ardl model. 5. results and discussion 5.1. unit root tests results according to adf, with intercept only-lnfie and lnepap variables i(0), with intercept and trend-lnamth variables i(0) and no intercept and no trend-all variables i(1) (table 2). according to pp test, with intercept only-lnfie variables i(0), with intercept and trend lnfie variables i(0) and no intercept and no trend-all variables i(1) (table 2). the adf, pp, and kpss unit root test evaluation results suggest that the ardl method and the ardl boundary-test approach can be used to evaluate the short-term and long-term associations between variables (table 3). table 3: var lag order selection criteria lag logl lr fpe aic sc hq flnamth=(lnamth⁄lnoe) 0 −60.46620 na 1.314626 5.949162 6.048640 5.970751 1 −43.93246 28.34356* 0.399978* 4.755472* 5.053907* 4.820240* flnamth=(lnamth⁄lneoop) 0 −58.58722 na 1.099220 5.770211 5.869689 5.791801 1 −41.74691 28.86910* 0.324817* 4.547324* 4.845759* 4.612092* flnamth=(lnamth⁄lnope) 0 −55.36771 na 0.808949 5.463591 5.563069 5.485180 1 −31.11509 41.57592* 0.118003* 3.534770* 3.833205* 3.599538* flnfie=(lnfie⁄lnoe) 0 −43.07461 na 0.250878 4.292820 4.392299 4.314410 1 −28.99204 24.14155* 0.096401* 3.332575* 3.631010* 3.397343* flnfie=(lnfie⁄lneoop) 0 −40.70597 na 0.200213 4.067235 4.166713 4.088824 1 −26.42454 24.48244* 0.075489* 3.088052* 3.386487* 3.152820* flnfie=(lnfie⁄lneop) 0 −40.04297 na 0.187962 4.004093 4.103571 4.025682 1 −18.32524 37.23040* 0.034905* 2.316690* 2.615125* 2.381458* flnepap=(lnepap⁄lnoe) 0 −54.59248 na 0.751375 5.389760 5.489238 5.411349 1 −39.42262 26.00547* 0.260317* 4.325964* 4.624399* 4.390732* flnepap=(lnepap⁄lneoop) 0 −52.48826 na 0.614927 5.189358 5.288837 5.210948 1 −37.07599 26.42104* 0.208182* 4.102475* 4.400910* 4.167243* flnepap=(lnepap⁄lneop) 0 −41.54475 na 0.216863 4.147119 4.246597 4.168708 1 −23.85408 30.32686* 0.059097* 2.843246* 3.141681* 2.908014* *indicates lag order selected by the criterion, aic: akaike information criterion, sc: schwarz information criterion table 4: models model 1 flnamth=(lnamth⁄lnoe) ardl (1,1) c (aic) (automatic selection) case 2: restricted constant and no trend model 2 flnamth=(lnamth⁄lneoop) ardl (1,1) c (aic) (automatic selection) case 2: restricted constant and no trend model 3 flnamth=(lnamth⁄lneop) ardl (1,0) c (aic) (automatic selection) case 2: restricted constant and no trend model 4 flnfie=(lnfie⁄lnoe) ardl (1,1) c (aic) (automatic selection) case 2: restricted constant and no trend model 5 flnfie=(lnfie⁄lneoop) ardl (1,0) c (aic) (automatic selection) case 2: restricted constant and no trend model 6 flnfie=(lnfie⁄lneop) ardl (1,0) c (aic) (automatic selection) case 2: restricted constant and no trend model 7 flnepap=(lnepap⁄lnoe) ardl (1,0) c (aic) (automatic selection) case 2: restricted constant and no trend model 8 flnepap=(lnepap⁄lneoop) ardl (1,0) c (aic) (automatic selection) case 2: restricted constant and no trend model 9 flnepap=(lnepap⁄lneop) ardl (1,0) c (aic) (automatic selection) case 2: restricted constant and no trend humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023 345 table 5: results from bound tests dependant variable f-statistic model 1 3.751896* cointegration model 2 3.860015** cointegration model 3 1.781248 no cointegration model 4 23.99063*** cointegration model 5 25.42706*** cointegration model 6 15.98011*** cointegration model 7 2.225163 no cointegration model 8 2.242512 no cointegration model 9 2.190050* cointegration significance n i (0) bound i (1) bound 10% 5% 2.5% 1% 10% 5% 2.5% 1% 1000 3.02 3.62 4.18 4.94 3.51 4.18 4.89 5.58 35 3.223 3.957 5.763 3.757 4.53 6.48 30 3.303 4.09 6.027 3.797 4.663 6.76 table 6: ardl long run form and bounds test long run coefficients variable coefficient levels equation conditional error correction regression ecm regression model 1 lnoe 1.025420*** c −6.476714 −4.268601 lnamth(−1) −0.659069** lnoe(−1) 0.675822* ∆lnoe(−1) 0.254467 0.254467 cointeq(−1) −0.659065** model 2 lneoop 1.131487*** 0.750534* ∆lneoop 0.269196 0.269196 c −8.311041 −5.512904 lnamth (−1) −0.663323** cointeq(−1) −0.663323** model 3 lneop 1.535972*** 0.451722 c −6.476714 −3.200447 lnamth (−1) −0.294095* cointeq(−1) −0.294095 model 4 lnoe 0.457888*** 0.380394** c 2.027771 1.648582 lnfie (−1) −0.813002*** cointeq(−1) −0.813002*** model 5 lneoop 0.525588*** 0.430817** c 1.042357 0.854405 lfie (−1) −0.819686*** cointeq(−1) −0.819686*** model 6 lneop 0.355559 0.212386 c 4.734241 2.827896 lfie (−1) −0.597328*** cointeq(−1) −0.597328*** model 7 lnoe 0.267180 0.148136 c 5.219491 2.893913 lnepap (−1) −0.554444* cointeq(−1) −0.554444* model 8 lneoop 0.300501 0.170415 c 4.650905 2.637536 lnepap (−1) −0.567102* cointeq(−1) −0.567102** model 9 lneop 0.489244 0.292560 c 2.834459 1.694963 lnepap (−1) −0.597984* cointeq(−1) −0.597984** ***, **and *indicate rejection of the null hypotheses at the 1%, 5% and 10% significance levels respectively 5.2. var lag order selection criteria optimal lags for variables are determined based on aic, which are automatically selected by the ardl method built into eviews_12. given the use of annual data, the maximum lag initially applied to all variables is 1 (tables 4 and 5). 5.3. cointegration testing results the results of the ardl boundary test are given in table 5. in all ardl equations (models) test result indicates the existence of cointegration between the variables. table 5 shows whether there is a cointegration relationship between these variables. thus, there is a long-term relationship. according to narayan (2005), statistic is higher than upper bound at 5%. 5.4. ardl long run and short run results tables 6 and 7 presents the results of the long-term and short-term approach of ardl. 5.5. diagnostic test results the (table 8) presents the results of diagnostic tests ardl models. the evaluation results of the breusha-godfrey (bg) humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023346 table 7: ardl model coefficients and error correction (short run) model coefficients model 1 model 2 model 3 model 4 model 5 model 6 model 7 model 8 model 9 ardl model coefficients ∆lamsph(−1) 0.438156 −0.378287 −0.257236 lnamth 0.777951** 0.739981** 0.365617 ∆lnfie(−1) −0.083396 −0.079313 0.079536 lnfie 0.719639** 0.729209** 2.098201* ∆lnepap(−1) −0.377008 −0.388330 −0.412628** lnepap 0.663988* 0.690056** 0.734310*** ∆lnoe(−1) −0.421102 0.307727 0.139243 lnoe −0.896512* −0.514774** −0.349554* ∆lneoop 0.505829 0.358594* 0.169177 lneoop −0.903057 −0.561093** −0.410863* ∆lneop 1.185385 2.582399* 0.760492* lneop 0.269124 −0.432789 −0.773122** c 6.870748 7.451061* −6.964471 1.480554 2.195647 −2.434146 −0.656771 0.121305 3.650428 error correction (short run) model coefficients ∆lnamth(−1) 0.258497 0.236574 0.034610 ∆lnfie (−1) 0.049710 0.050084 0.003597 ∆lnepap(−1) 1.119368 0.238784 0.075561 ∆lnoe 0.333109 0.342681 −0.045879 ∆lneoop 0.338116 0.404603 0.077118 ∆lneop −0.464981 0.469303 1.152788** ect(–1) −0.762258** −0.752911** −0.435943* −0.425991 −0.434167 −0.224612 −0.693659 −0.728018** −0.501391 c 0.049154 0.057562 0.126156 0.085676 0.086523 0.117271 −0.355747 0.075142 0.095505 ***, ** and *indicate rejection of the null hypotheses at the 1%, 5% and 10% significance levels respectively table 8: diagnostic test results (lm version) normality test (jarque-bera) jb ramsey reset test (t-statistic heteroskedasticity test: breusch‒godfrey serial correlation lm test: χ2 r2 d_w (durbin and watson, 1971) arch χ2 breusch-pagan -godfrey model 1 1.224725 0.330103 0.933627 1.841800 6.197778 0.646149 1.605904 0.542069 0.8557 0.3339 0.6059 0.0457 model 2 0.812776 0.202762 1.016455 0.586274 5.543846 0.650395 1.621157 0.666052 0.6585 0.3267 0.6322 0.0625 model 3 1.628936 0.049230 1.28915 2.316050 6.990971 0.614363 2.040432 0.442875 0.9613 0.2562 0.3141 0.0303 model 4 1.078476 0.167417 0.164925 0.642026 1.584374 0.673077 1.767814 0.583193 0.8690 0.6847 0.7254 0.4529 model 5 1.498941 0.599753 0.300864 0.167146 1.524040 0.688020 1.761928 0.472617 0.5566 0.5833 0.9198 0.4667 model 6 1.483941 1.521044 0.052111 0.797585 0.964306 0.598539 1.516300 0.476175 0.1466 0.8194 0.6711 0.6175 model 7 4.729595 0.996138 0.461718 1.812288 0.402796 0.266452 1.713526 0.093968 0.3332 0.4988 0.4041 0.8176 model 8 4.929361 0.980808 0.463229 1.735417 0.388795 0.267996 1.704314 0.085462 0.3505 0.4970 0.4299 0.8233 model 9 2.315623 1.164187 0.546938 0.440996 0.832911 0.396399 1.620687 0.314173 0.2605 0.4596 0.8021 0.6594 (f-version) normality test (jarque-bera) jb ramsey reset test (t-statistic heteroskedasticity test: breusch‒godfrey serial correlation lm test: χ2 cusum –5%– significance cusum squares –5%– significance arch χ2 breusch-pagan -godfrey model 1 n/a 0.108968 0.881410 0.544773 3.140294 stb no/stb n/a 0.8557 0.3602 0.6583 0.0726 model 2 n/a 0.450292 1.069027 1.968954 2.690116 stb stb n/a 0.6585 0.3012 0.5789 0.1005 model 3 n/a 0.002424 1.240173 1.115634 3.992265 stb stb n/a 0.9613 0.2801 0.3493 0.0392 model 4 n/a 0.583193 0.149667 0.283831 0.652824 stb no/stb n/a 0.8690 0.7034 0.7562 0.5339 model 5 n/a 2.313575 0.047022 0.355317 0.385035 stb stb n/a 0.1466 0.8308 0.7058 0.6866 (contd...) humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023 347 model 6 n/a 0.359703 0.274913 0.072209 0.626019 stb stb n/a 0.5566 0.6065 0.9306 0.5473 model 7 n/a 0.992292 0.425367 0.850054 0.156447 stb no/stb n/a 0.3332 0.5225 0.4438 0.8565 model 8 n/a 0.961984 0.429789 0.810750 0.150906 stb no/stb n/a 0.3505 0.5218 0.4701 0.8611 model 9 n/a 1.355331 0.506084 0.193052 0.330404 stb no/stb n/a 0.2605 0.4860 0.8261 0.7234 legend: n/a–not applicable (f-version) normality test (jarque-bera) jb ramsey reset test (t-statistic heteroskedasticity test: breusch‒godfrey serial correlation lm test: χ2 cusum –5%– significance cusum squares –5%– significance arch χ2 breusch-pagan -godfrey table 8: (continued) (contd...) table 9: fmols, dols, ccr results ect adf /pp /kpss constant, linear trend none cointegration test constant engle-granger phillips-ouliaris tau-statistic z-statistic tau-statistic z-statistic fully modified least squares (fmols) model 1 lnoe 1.046239*** −3.400593** /−3.377370** /0.291222 −3.565238* /−3.459461* /0.088016 −3.491362** /−3.471604** /na −3.515337 −15.81280* −3.595956* 15.65971* c −6.873767 dynamic least squares (dols) model 1 lnoe 1.021486** −3.506559** /−4.072880** /0.249483 −2.593759 /−2.636657 /0.076145 −3.614446** /−2.666470*** /na −3.515337 −15.81280* −3.595956* 15.65971* c −6.483761 canonical cointegrating regression (ccr) model 1 lnoe 1.022723*** −3.377050** /−3.354440** /0.316647 −3.572648* /−3.469738* /0.095819 −3.463885*** /−3.444711*** /na −3.515337 −15.81280* −3.595956* 15.65971* c −6.485915 fully modified least squares (fmols) model 2 lneoop 1.129642*** −3.329914** /−3.311078** /0.350799* −3.552468* /−3.444193* /0.095838 −3.422214*** /−3.406179*** /na −3.463146 −15.61670* −3.538296 −15.37764* c −8.339050* dynamic least squares (dols) model 2 lneoop 1.090805** −3.434369** /−2.561552 /0.270089 −4.040568** /−2.630002 /0.081285 −3.536943*** /−2.630002** /na −3.463146 −15.61670* −3.538296 −15.37764* c −7.709306 canonical cointegrating regression (ccr) model 2 lneoop 1.112419*** −3.315639** /−3.297145** /0.368576* −3.560446* /−3.453153* /0.094674 −3.405181*** /−3.389483*** /na −3.463146 −15.61670* −3.538296 −15.37764* c −8.051949 fully modified least squares (fmols) model 3 lneop 0.964938 −0.374984 /−1.746914 /0.568694* −5.672266*** /−3.563247* /0.189162** −1.911749* /−1.899691 /na −1.664038 −5.414288 −1.486104 −4.005651 c −3.442063 dynamic least squares (dols) model 3 lneop 0.764643 −3.413986* /−2.398603 /0.513690* −4.531977** /−3.529474* /0.203279** −3.564921*** /−2.486933** /na −1.664038 −5.414288 −1.486104 −4.005651 c −0.656505 canonical cointegrating regression (ccr) model 3 lneop 0.955588 −0.384108 /−1.751631 /0.569060* −4.531977** /−3.529474* /0.203279** −3.564921*** /−2.486933** /na −1.664038 −5.414288 −1.486104 −4.005651 c −3.315966 fully modified least squares (fmols) model 4 lnoe 0.668487*** −3.665603** /−3.636387** /0.074228 −3.575042* /−3.541948* /0.065945 −3.757350*** /−3.731707*** /na −5.852699*** −19.94189** −5.747203*** −21.24732** c −1.221358 dynamic least squares (dols) model 4 lnoe 0.587495*** −3.200695** /−3.055910** /0.127244 −3.271756 /−3.230606 /0.148553** −3.302636*** /−3.180695*** /na −5.852699*** −19.94189** −5.747203*** −21.24732** c 0.087824 humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023348 table 9: (continued) ect adf /pp /kpss constant, linear trend none cointegration test constant engle-granger phillips-ouliaris tau-statistic z-statistic tau-statistic z-statistic canonical cointegrating regression (ccr) model 4 lnoe 0.694851*** −3.647987** /−3.622489** /0.071203 −3.541163* /−3.512098* /0.070880 −3.726898*** /−3.704120*** /na −5.852699*** −19.94189** −5.747203*** −21.24732** c −1.651258 fully modified least squares (fmols) model 5 lneoop 0.724840*** −3.595773** /−3.569391** /0.102105 −3.532172* /−3.500643* /0.077382 −3.688874*** /−3.665041*** /na −5.960226*** −19.72316** −5.794529*** −21.20400** c −2.206813 dynamic least squares (dols) model 5 lneoop 0.643457*** −3.123235** /−3.094699** /0.154493 −3.249566 /−3.180010 /0.098994 −3.223659** /−3.198027*** /na −5.960226*** −19.72316** −5.794529*** −21.20400** c −0.885514 canonical cointegrating regression (ccr) model 5 lneoop 0.752123*** −3.575065** /−3.552405** /0.086225 −3.484857* /−3.458111* /0.078184 −3.654104*** /−3.633079*** /na −5.960226*** −19.72316** −5.794529*** −21.20400** c −2.654781 fully modified least squares (fmols) model 6 lneop 0.707742* 0.726708 /−1.359080 /0.613763** −3.913367** /−3.902905** /0.140339* −1.729487* /−1.610176* /na −4.488710** −11.89573 −4.249363** −13.90564 c −0.183563 dynamic least squares (dols) model 6 lneop 0.605905 −2.523809 /−2.491924 /0.428426* −6.628713*** /−3.625185* /0.053282 −2.873278*** /−2.604883 /na −4.488710** −11.89573 −4.249363** −13.90564 c 1.210699 canonical cointegrating regression (ccr) model 6 lneop 0.690821* 0.622450 /−1.381783 /0.615926** −3.973163** /−4.008038** /0.204611** −1.761538* /−1.645268* /na −4.488710** −11.89573 −4.249363** −13.90564 c 0.052131 fully modified least squares (fmols) model 7 lnoe 0.370517 −3.192297** /−3.186362** /0.103842 −7.134574*** /−3.169118 /0.093332 −3.282213*** /−3.279390*** /na −4.397300** 39.00430 −3.222841 −14.19595 c 3.586580 dynamic least squares (dols) model 7 lnoe 0.267673 −2.921928* /−2.923892* /0.124968 −2.990193 /−2.966415 /0.092160 −3.005515*** /−3.042713*** /na −4.397300** 39.00430 −3.222841 −14.19595 c 5.273381 canonical cointegrating regression (ccr) model 7 lnoe 0.361871* −3.199855** /−3.193932** /0.102271 −7.137866*** /−3.165550 /0.094338 −3.293618*** /−3.290642*** /na −4.397300** 39.00430 −3.222841 −14.19595 c 3.729702 fully modified least squares (fmols) model 8 lneoop 0.433238* −3.219633** /−3.215193** /0.102954 −3.856414** /−3.226043 /0.087110 −3.297065*** /−3.297065*** /na −4.468147** 37.18923 −3.259090 −14.37847 c 2.515873 dynamic least squares (dols) model 8 lneoop 0.330868 −3.000813* /−2.966592* /0.104173 −5.017293*** /−2.883205* /0.082360 −3.086052*** /−3.051855*** /na −4.468147** 37.18923 −3.259090 −14.37847 c 4.194978 canonical cointegrating regression (ccr) model 8 lneoop 0.421377* −3.229783** /−3.225267** /0.100432 −7.079487*** /−3.222187 /0.088313 −3.312208*** /−3.310967*** /na −4.468147** 37.18923 −3.259090 −14.37847 c 2.711781 fully modified least squares (fmols) model 9 lneop 0.748635* −5.341432*** /−3.417547** /0.291744 −5.372415*** /−3.266516 /0.084094 −5.409250*** /−3.461294*** /na −5.965476*** 37.06536 −3.089732 −13.30914 c −0.690143 dynamic least squares (dols) model 9 lneop 0.647075* −2.950706* /−2.897965* /0.390208* −3.623109* /−3.122914 /0.056550 −3.107270*** /−2.986254 /na −5.965476*** 37.06536 −3.089732 −13.30914 c 0.751157 canonical cointegrating regression (ccr) model 9 lneop 0.744569 −5.373339*** /−3.425220** /0.291807 −5.403455*** /−3.287299* /0.084086 −5.435724*** /−3.466128*** /na −5.965476*** 37.06536 −3.089732 −13.30914 c −0.635086 adf denotes the augmented dickey‒fuller single root system respectively. pp phillips‒perron is single root system. kpss denotes kwiatkowski‒phillips-schmidt-shin single root system. ***, ** and * indicate rejection of the null hypotheses at the 1%, 5% and 10% significance levels respectively. the critical values are taken from mackinnon (mackinnon, 1996). ***, ** and *indicate rejection of the null hypotheses at the 1%, 5% and 10% significance levels respectively humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023 349 method confirmed that our ardl model had no problems with sequential correlation. the results of the breusha-pagan-godfrey (bfg) and arch methods later confirmed that heteroscedasticity was not a problem. according to the ramsey reset test, that the model is well defined. the table shows the total amount of recursive balances (cusum) and the squares of recursive balances (cusumq) indicating that the ardl model is constant during the sampling period (cusum). however, while cusum was stable in all models, cusumq was unstable in models 1, 4, 7, 6, and 9. 5.6. fmols, dols, ccr and engle-granger analysis results fmols, dols, ccr cointegration methods and analysis of the results of engle-granger analysis are very useful in our study (tables 9 and 10). this is because the revision of the results obtained with the ardlbt co-integration approach with the application of these methods allows for a more reliable analysis. another feature that indicates a cointegration relationship between the variables is that the white noise errors obtaine from the estimates are stationary. table 10 shows the results of the stationary test by applying single root tests adf, pp and kpss on the white noise error of each long-run equation evaluated by fmols, dols and ccr. based on these results, although in many models the white noise errors are stationary and thus again confirm the existence of a co-integrating interaction, in some models this situation is not fully confirmed. this result does support the results of the engle-granger and phillips-ouliaris cointegration tests given above. short-term and long-term cause-and-effect relationships can be more clearly analyzed using the granger cause and effect relationship using the engle-granger cointegration method. it was confirmed that long-term interaction exists in models 1, 2, 3, 8 and 9, and strong causality between variables exists in models 1, 2 and 8 (table 10). 6. conclusion and policy implications oil is the main export product of azerbaijan. imports are dominated by machinery and equipment, modern equipment and technologies. in one of our previous studies, we noted that food and agricultural products have a special weight, which is no less important among imported goods. undoubtedly, reducing the import of food and agricultural products (saving foreign exchange) and ensuring food security, diversifying the economy to increase self sufficiency, developing the non-oil sector, agriculture and agro-processing, which have a large share in this sector. it is recommended to increase the import of many machinery and equipment necessary for the sustainable development of agriculture, especially agricultural machinery for tillage and harvesting, equipment for the food industry, equipment for processing agricultural products. in the study, it was confirmed that there are long term interactions and strong cause and effect relationships between the import of the mentioned products (machinery, equipment and machinery necessary for the agricultural and agro-processing sector) and the export of oil and oil products. since the domestic market, especially the food market, is highly dependent on exports and world prices, in order to increase the supply of the agricultural-food market with local products, studies on economic diversification and stimulation of the agricultural sector, studies on the dependence of imports of oil and oil products on exports of oil and oil products, examine imports machinery and equipment, mechanical engineering, the increase should be of paramount importance. references abdlaziz, r.a., naseem, n.a.m., slesman, l. (2018), dutch disease effect of oil price on agriculture sector: evidence from panel cointegration of oil exporting countries. international journal of energy economics and policy, 8(5), 241-250. abdlaziz, r.a., naseem, n.a.m., slesman, l. (2021), oil revenue and agriculture value-added in oil-exporting countries: does the role of real exchange rate matter? international journal of energy sector management, 16(1), 171-190. ahmed, a.s. (1985), oil and development: the experience of the petroleum producing countries of the third world/petrol et developpement: l’experience des economies petrolieres du tiers monde. savings and development, 9(3), 325-357. aliyev, k.h., dehning, b., nadirov, o. (2016), modelling the impact of fiscal policyon non-oil gdp in a resource rich country: evidence table 10: granger cause and effect analysis evaluation results (probability). wald test short-term period long-term period strong impact adf unit root test ∆loe/∆loope//∆lope ect-1 ect-1 and∆loe/∆loope/ /∆lope with intercept only/with interceptand trend/no intercept and no trend chi– sq. f‒st. t−st. t–st. chi– sq. f‒st. chi–sq. f‒st. model 1 0.2535 0.2703 0.2703 0.0040 0.0008 0.0040 0.0036 0.0140 −3.430079**/−4.043842**/−3.515337*** model 2 0.2892 0.3049 0.3049 0.0038 0.0007 0.0038 0.0032 0.0133 −3.378422**/−4.020006**/−3.463146** model 3 0.5496 0.5586 0.5586 0.0437 0.0277 0.0437 0.0801 0.1135 −4.551039***/−6.436482***/−.488710*** model 4 0.0820 0.1012 0.1012 0.1533 0.1339 0.1533 0.1862 0.2174 −5.808720***/−5.618156***/−5.852699*** model 5 0.0557 0.0738 0.0738 0.1395 0.1200 0.1395 0.1371 0.1695 −5.928473***/−5.694647***/−5.960226*** model 6 0.1898 0.2095 0.2095 0.2555 0.2371 0.2555 0.0902 0.1241 −4.551039***/−6.436482***/−4.488710*** model 7 0.8590 0.8611 0.8611 0.3381 0.3242 0.3381 0.4153 0.4333 −4.479018***/−5.470089***/−4.397300*** model 8 0.7454 0.7496 0.7496 0.0084 0.0037 0.0084 0.0109 0.0289 −4.533128***/−5.634898***/−4.478147* model 9 0.0089 0.0195 0.0195 0.0926 0.0724 0.0926 0.0004 0.0049 −5.904042***/−6.134051***/−5.965476*** adf denotes the augmented dickey‒fuller single root system respectively. ***, ** and * indicate rejection of the null hypotheses at the 1%, 5% and 10% significance levels respectively. the critical values are taken from mackinnon (mackinnon, 1996) humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023350 from azerbaijan. acta universitatis agriculturae et silviculturae mendelianae brunensis, 64, 1869-1878. allan, j.a., mclachlan, k.s. (1976), agricultural development in libya after oil. african affairs, 75(300), 331-348. auty, r., warhurst, a. (1993), sustainable development in mineral exporting economies. resources policy, 19(1), 14-29. aye, g.c., odhiambo, n.m. (2021), oil prices and agricultural growth in south africa: a threshold analysis. resources policy, 73, 102196. bollerslev, tim. (1986), generalized autoregressive conditional heteroskedasticity. journal of econometrics, 31 (3): 307–327 breusch, t.s. (1978), testing for autocorrelation in dynamic linear models. australian economic papers, 17, 334-355. breusch, t.s., pagan, a.r. (1979), a simple test for heteroskedasticity and random coefficient variation. econometrica, 47(5), 1287-1294. brown, r.l., durbin, j., evans, j.m. (1975), techniques for testing the constancy of regression relationships over time. journal of the royal statistical society: series b (methodological), 37(2), 149-163. cauley, t.j. (1959), oil and agriculture: compared and contrasted. the southwestern social science quarterly, 40(2), 139-146. charemza, w.w., deadman, d.f. (1997), new directions in econometric practice: general to specific modelling, cointegration and vector autoregresion. united kingdom: edward elgar. chen, d., gummi, u.m., lu, s.b., muazu, a. (2020), modelling the impact of oil price fluctuations on food price in high and low-income oil exporting countries. agricultural economics czech, 66, 458-468. chen, s.t., kuo, h., chen, c.c. (2010), modeling the relationship between the oil price and global food prices. applied energy, 87(8), 2517-2525. denisard, c.o.a., disch, a. (1981), oil prices, agricultural production and changes in real income in brazil. luso-brazilian review, 18(1), 77-116. dickey, d.a., fuller, w.a. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica, 49, 1057-1072. durbin, j., watson, g.s. (1971), testing for serial correlation in least squares regression. iii. biometrika, 58(1), 1-19.0 engle, r.f. (1982), autoregressive conditional heteroskedasticity with estimates of the variance of united kingdom inflation. econometrica, 50(4), 987-1007. engle, r.f., granger, c.w.j. (1987), co-integration and error correction: representation, estimation, and testing. econometrica, 55(2), 251-276. falola, t. (1988), review of state, oil, and agriculture in nigeria, by m. watts. african economic history, 17, 203-203. fardmanesh, m. (1991), dutch disease economics and oil syndrome: an empirical study. world development, 19(6), 711-717. forbes, g. (1941), oklahoma oil and indian land tenure. agricultural history, 15(4), 189-194. fowowe, b. (2016), do oil prices drive agricultural commodity prices? evidence from south africa. energy, 104, 149-157. gavett, e.e. (1977), energy policy and research in agriculture. american journal of agricultural economics, 59(5), 1083-1086. godfrey, l.g. (1978), testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. econometrica, 46, 1293-130. granger, c.w.j. (1969), investigating causal relations by econometric models and cross-spectral methods. econometrica, 37, 424-438. hafner, c.m., herwartz, h. (2006), volatility impulse responses for multivariate garch models: an exchange rate illustration. journal of international money and finance, 25(5), 719-740. hamilton, j.d. (1983), oil and the macroeconomy since world war ii. journal of political economy, 91(2), 228-248. hamilton, j.d. (2014), the changing face of world oil markets. no. w20355. cambridge, usa: national bureau of economic research. hansen, b.e. (2011),threshold autoregression in economics. statistics and its interface, 4, 123-127. hanson, k., robinson, s., schluter, g. (1993), sectoral effects of a world oil price shock: economywide linkages to the agricultural sector. journal of agricultural and resource economics, 18(1), 96-116. harri, a., nalley, l., hudson, d. (2009), the relationship between oil, exchange rates, and commodity prices. journal of agricultural and applied economics, 41, 501-510. hassan, m.f. (1978), agricultural development in a petroleum-based economy: qatar. economic development and cultural change, 27(1), 145-167. hojman, d.e. (1987), the dutch disease as a challenge to the conventional structuralist-dependency paradigm: oil, minerals and foreign loans in latin america. boletín de estudios latinoamericanos y del caribe, 42, 39-53. ibrahim, m.h. (2015), oil and food prices in malaysia: a non-linear ardl analysis. agricultural and food economics, 3, 28-35. jarque, c.m., bera, a.k. (1980), efficient tests for normality, homoscedasticity and serial independence of regression residuals. economics letters, 6(3), 255-259. jarque, c.m., bera, a.k. (1981), efficient tests for normality, homoscedasticity and serial independence of regression residuals: monte carlo evidence. economics letters, 7(4), 313-318. jarque, c.m., bera, a.k. (1987), a test for normality of observations and regression residuals. international statistical review, 55(2), 163-172. johansen, s. (1992), a representation of vector autoregressive processes integrated of order 2. econometric theory 8, 188-202. johansen, s., juselius, k. (1992), testing structural hypotheses in a multivariate cointegration analysis of the ppp and the uip for uk. journal of econometrics, 53, 211-44. kakanov, e., hansjörg, b., lilas, d. (2018), resource curse in oil exporting countries. oecd economics department working papers 1511. berlin: oecd publishing. karbasi, a.r., fahimifard, s.m., jahany, h.r. (2009), studying the effect of energy factor on iran’s agriculture sector and total economy production. iranian economic review, 14(23), 1-17. keane, m.p., prasad, e.s. (1996), the employment and wage effects of oil price changes: a sectoral analysis. review of economics and statistics, 78(3), 389-400. kilian, l., xiaoqing, z. (2022), the impact of rising oil prices on us inflation and inflation expectations in 2020-23. energy economics, 113, 106228. kwiatkowski, d., phillips, p., schmidt, p., shin, y. (1992), testing the null hypothesis of stationarity against the alternative of a unit root. journal of econometrics, 54(1-3), 159-178. kirikkaleli, d., darbaz, i. (2021), the causal linkage between energy price and food price. energies, 14, 4182. lingxiao, w.a.n.g., peculea, a.d., xu, h. (2016), the relationship between public expenditure and economic growth in romania: does it obey wagner’s or keynes’s law? theoretical and applied economics, 23(3), 41-52. lee, j., cho, h.c. (2021), impact of structural oil price shock factors on the gasoline market and macroeconomy in south korea. sustainability, 13, 2209. https://doi.org/10.3390/su13042209 loungani, p. (1986), oil shocks and the dispersion hypothesis. review of economics and statistics, 58, 536-539. mackinnon, j.g. (1996), numerical distribution functions for unit root and cointegration tests. journal of applied economics, 11(6), 601-618. majd, m.g. (1989), the oil boom and agricultural development: a reconsideration of agricultural policy in iran. the journal of energy and development, 15(1), 125-140. menegaki, a.n. (2019), the ardl method in the energy-growth nexus field; best implementation strategies. economies, 7, 105. humbatova, et al.: impact of oil exports on imports of agricultural machinery and equipment international journal of energy economics and policy | vol 13 • issue 1 • 2023 351 menegaki, a.n. (2020), a guide to econometric methods for the energygrowth nexus (enhanced edition). netherlands: elsevier. meyer, d.f, sanusi, k.a. hassan, a. (2018), analysis of the asymmetric impacts of oil prices on food prices in oil-exporting, developing countries. journal of international studies, 11(3), 82-94. mikayilov, j.i., mukhtarov, s., mammadov, j. (2020), gasoline demand elasticities at the backdrop of lower oil prices: fuel-subsidizing country case. energies, 13, 6752. mohamed f.a., hameed, a., amna, a. (2009), the impact of petroleum prices on vegetable oil prices: evidence from co-integration tests. in: international borneo business conference on global changes: corporate responsibility, organized by the school of business and economics of university malaysia sabah (ums) and the faculty of economics and business of universities malaysia sarawak (unimas). p.15-17. mohammadi, h., jahan-parvar, m.r. (2011), oil prices and real exchange rates in oil-exporting countries: a bounds testing approach. the journal of developing areas, 45, 313-322. muhammad, k, muhammad, a., dilawar, k., hassan, taj, allayarovş p., azeem, a. (2021), agricultural exports, financial openness and ecological footprints: an empirical analysis for pakistan. international journal of energy economics and policy, 11, 256-261. mukhtarov, s., aliyev, s., zeynalov, j. (2020), the effect of oil prices on macroeconomic variables: evidence from azerbaijan. international journal of energy economics and policy, 10(1), 72-80. musayev, a., aliyev, k.h. (2017), modelling oil-sector dependency of tax revenues in a resource rich country: evidence from azerbaijan. acta universitatis agriculturae et silviculturae mendelianae brunensis, 65, 1023-1029. naanen, b. (1988), review of state, oil, and agriculture in nigeria, by m. watts. the international journal of african historical studies, 21(3), 529-530. narayan, p.k. (2005), the saving and investment nexus for china: evidence from cointegration tests. applied economics, 37(17), 1979-1990. olasunkanmi, o.i., oladele, k.s. (2018), oil price shock and agricultural commodity prices in nigeria: a non-linear autoregressive distributed lag (nardl) approach. african journal of economic review, 6(2), 74-92. olayungbo, d., hassan, w. (2016), effect of oil price on food price in developing oil exporting countries: a panel ardl. opec energy review, 40, 397-411. olayungbo, d.o. (2021), global oil price and food prices in food importing and oil exporting developing countries: a panel ardl analysis. heliyon, 7(3), e06357. ologunde, i.a., kapingura, f.m., sibanda, k. (2020), sustainable development and crude oil revenue: a case of selected crude oilproducing african countries. international journal of environmental research public health, 17, 6799. oluwatoyese, o.p., applanaidu, s.d., abdulrazak, n. (2016), agricultural export, oil export and economic growth in nigeria: multivariate cointegration approach. international journal of environnemental and agriculture research, 2(2), 64-72. onour, i. (2021), dynamics of crude oil price change and global food commodity prices. finance and economics review, 3(1), 38-50. parcher, l.a. (1947), oil and agriculture. the southwestern social science quarterly, 28(3), 244-252. park, j.y. (1992), canonical cointegrating regressions. econometrica, 60, 119-143. parker, a.a. (1997), what happens to the world: when the oil runs out. renew: technology for a sustainable future, 61, 46-49. penrose, e. (1976), africa and the oil revolution: an introduction. african affairs, 75(300), 277-283. pesaran, m., shin, y. (1999), an autoregressive distributed lag modeling approach to cointegration analysis. united kingdom: cambridge university press. dae working paper no 9514. pesaran, m.h., shin, y.i., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16, 289-326. phillips, p.c., ouliaris, s. (1990), asymptotic properties of residual based tests for cointegration. econometrica, 58(1), 165-193. phillips, p.c.b., hansen, b.e. (1990), statistical inference in instrumental variables regression with i (1) processes. review of economics studies, 57, 99-125. radmehr, r., henneberry, r.s. (2020), energy price policies and food prices: empirical evidence from iran. energies, 13, 4031. ramsey, j.b. (1969), tests for specification errors in classical linear least squares regression analysis. journal of the royal statistical society, series b, 31(2), 350-371. ramsey, j.b. (1974), classical model selection through specification error tests. in: zarembka, p., editor. frontiers in econometrics. new york: academic press. p.13-47. rogoff, k. (2006), oil and the global economy, manuscript. united states: harvard university. saban, n., erdem, c., soytas, u. (2013), volatility spillover between oil and agricultural commodity markets. energy economics, 36,658-665. sachs, j.d., warner, a.m. (1995), natural resource abundance and economic growth. cambridge: national bureau of economic research. shaari, m.s., pei, t.l., rahim, h.a. (2013), effects of oil price shocks on the economic sectors in malaysia. international journal of energy economics and policy, 3, 360-366. shokoohi, z., saghaian, s.h. (2022), nexus of energy and food nutrition prices in oil importing and exporting countries: a panel var model. energy, 255(1), 124416. tong, h. (1983), threshold models in non-linear time series analysis. new york: springer. tong, h. (1990), non-linear time series: a dynamical system approach. new york: oxford university press. uri, n.d. (1995), the impact of crude-oil price volatility on agricultural employment in the united states. the journal of energy and development, 20(2), 269-288. uri, n.d. (1996), the impact of crude oil price volatility on agricultural employment in the united states. energy and environment, 7(1), 57-74. vasiljeva, m.v., ponkratov, v.v., vatutina, l.a., volkova, m.v., ivleva, m.i., romanenko, e.v., kuznetsov, n.v., semenova, n.n., kireeva, e.f., goncharov, d.k., elyakova, i.d. (2022), crude oil market functioning and sustainable development goals: case of opec++-participating countries. sustainability, 14, 4742. wells, j.c. (1988), review of state, oil and agriculture in nigeria, by m. watts. american journal of agricultural economics, 70(1), 215-216. wilson, r.r. (1975), petroleum for u. s. agriculture. american journal of agricultural economics, 56(5), 888-895. yazdanpanah a. (1994), oil prices and agricultural policy in iran. food and agricultural policy research institute (fapri) publications (archive only). iowa: center for agricultural and rural development (card) at iowa state university. p.94-123. yergin, d. (1991), the prize: the epic quest for oil, money and power. new york: simon and schuster. zhang, q., reed, m.r. (2008), examining the impact of the world crude oil price on china’s agricultural commodity prices: the case of corn, soybean, and pork (no. 1368-2016-108438). no 6797. in: 2008 annual meeting. dallas, texas: southern agricultural economics association. zmami, m., ben-salha, o. (2019), does oil price drive world food prices? evidence from linear and non-linear ardl modeling. economies, 7, 1-18. . international journal of energy economics and policy | vol 9 • issue 1 • 201984 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(1), 84-94. oil hikes, drugs and bribes: do oil prices matter for crime rate in russia? dmitry burakov* department of financial markets and banks, financial university under the government of russian federation, moscow, russia.*email: dbur89@yandex.ru received: 30 june 2018 accepted: 10 november 2018 doi: https://doi.org/10.32479/ijeep.6833 abstract in this article we test the hypothesis about the impact of oil prices shocks on the unemployment and crime rate on the example of oil-exporting country. according to the hypothesis, there exist a dependence of the labor market on oil revenue. a negative oil price shock should lead to a decrease in the employment rate, which in turn should lead to a rise in illegal forms of behavior. illegal behavior is measured as an average of registered crimes (bribery and drug dealing). based on data for 1990-2017 we study a case of russia, using vector error correction model for detecting shortand long-term effects. results show that oil prices and unemployment affect crime rate in the long-run in a case of oil-exporting country. yet, in the short-run both negative oil shocks and a rise in unemployment rate lead to a statistically significant increase in bribery and drug dealing. a 1% decrease in oil price will lead to a 1.14% rise in bribery and drug dealing and a 1% increase in the unemployment rate leads to a 2.72% increase in drug dealing and bribery. keywords: oil prices, unemployment, crime rate, bribery, vector error correction approach jel classifications: q41, e24, f43, k42 1. introduction conventional economic wisdom states that the most important factors, as well as sources, for economic growth include consumption, exports, government spending and investment. growing propensity to consume, leading to reduced budget constraint of households and empowered by households’ lending activities helps to boost economic growth in the short run, if accepting the money non-neutrality hypothesis. growing money demand bring to life an increased level of consumption, which in turn leads to increased output and employment rate. this, in turn, leads to short-lived, yet desirable growth in gdp. in case of oil-exporting countries, economic growth and employment rate significantly depend on world oil prices dynamics. oil prices, determining export revenues, which in most cases account for a large share of government spending, play a major role in determining the pace of the national economic growth. on the one hand, oil revenues being a major source for government spending, affect labor market in part of economically active population, employed in the budget sector. falling oil revenues lead to a decline in the wages growth rates, as well as worsening expectations of economic agents, concerning spending and savings decisions. another results of a negative shock in oil prices for oilexporting country may be labor optimization schemes, leading to a growth in an unemployment rate in the budget sector in parallel with growing labor efficiency. on the other hand, a negative shock in oil prices, leading to decline in oil revenues may lead to a decrease in efficiency of budget spending multiplier, like in samuelson model, which, in turn leads to lesser efficiency of budget funds allocation and reallocation between economic agents. the vicious circle may be strengthened by a decrease in efficiency of consumption multiplier: lower wages in the budget sector leading to a surge in consumption. an initial negative shock may then lead to a decline in spending and real wages of labor force, employed in the commercial sectors of the national economy. this journal is licensed under a creative commons attribution 4.0 international license burakov: oil hikes, drugs and bribes: do oil prices matter for crime rate in russia? international journal of energy economics and policy | vol 9 • issue 1 • 2019 85 yet, it’s quite logically to assume that in the case of oil-exporting country, if oil revenues play a major role in government spending (like in cases of saudi arabia, russia, venezuela etc.), negative oil shocks may lead to an even greater negative impact on economic growth than in oil-importing countries or states, restraining the budget from resource curse. in other words, we hypothesize that a negative oil shock should lead to a rise in unemployment rate ceteris paribus. many studies investigated this nexus and reported a statistically significant relationship between these macroeconomic variables see, e.g., ahmad (2013), alkhateeb et al. (2017), burakov and kurnysheva (2017). the detailed literature review is presented in the next section. if oil prices are essential in case of oil-exporting countries for employment dynamics, then it’s also logical to assume that unemployment should bring to life some negative externalities of economic and social nature. one of the most important negative externalities of unemployment is expected to be illegal behavior, that is crime. a nexus between deterioration of the labor market and crime rate was theoretically described and assessed by the nobel prize winner becker (1968). in his infamous paper, an economic model of crime was developed, explaining that a willingness of economic agent to engage in crime activities will hold and even grow as long as the expected utility of committing crime would be greater than the expected utility of engaging in other activities. hence, occurring exogenous and endogenous frictions on the labor market make crime activities more attractive. economic theory of crime, then, states that there should exist a nexus between unemployment rate and crime rate in the national economy. during expansion phase of the business cycle, crime rate should decline and vice versa. that is why, when dealing with economic aspects of illegal behavior in most cases, researchers choose unemployment rate as a proxy for studying the nexus between labor market and property crimes. yet, illegal forms of behavior include not only property (robbery, fraud, larceny), but also violent types of crime (murder, assault etc.) for explaining relationship between different types of illegal behavior and unemployment rate, cantor and land (1985) developed a theoretical framework in an attempt to describe and explain the links between the variables. according to their point of view, there exist two important channels, though which one could explain engagement of an economic agent in crime activities: opportunity and motivation. the motivation hypothesis, similar to becker (1968) economic approach, states that a decrease in economic prospects should increase incentives to engage in crime, that is unemployed are more likely to become criminals than employed ones. the opportunity hypothesis suggests that a decline in economic activity should decrease availability of criminal targets, taking into account that unemployed are more likely to stay at home, decreasing their vulnerability to property crime. motivation hypothesis tends to explain property crimes better, while opportunity hypothesis is relevant for both property and violent crimes. according to the above described theoretical framework of relationships between oil prices and employment, as well as unemployment and crime rate, we hypothesize that there should exist a nexus between shocks in oil prices and crime rates. the effect of the relationship or the magnitude of the negative social externality of growing unemployment in the form of illegal behavior should be even more strongly expressed in case of oil exporting countries, dependent on oil revenues for government spending. hence, we assume that a negative oil shock in oil exporting country should lead to deterioration on the labor market, thus rising a crime rate. unfortunately, this issue doesn’t have a solid theoretical and empirical background, while most of studies and empirical investigations come from the us and the uk and are dedicated to research of local resource booms (oil, gas, coal) on the regional level and their impact on crime rates see e.g., andrews and deza (2018), stretesky et al. (2018). research, dedicated to investigation of the “oil prices-crime rate” nexus on the macro-level is scarce, as well as studies, investigating oil-exporting countries. moreover, most of the studies, dedicated to this issue, use violent and property forms of crimes as a proxy for crime rate. neither bribery nor drug dealing are used in such studies. in contrast to existing research, we use bribery and drug dealing indices as a proxy for crime rate, when testing motivation hypothesis for rentseeking economies. the remainder of the paper is organized as follows: section 2 provides an overview of relevant literature; section 3 describes econometric modeling techniques and data used; section 4 presents an analysis of empirical results; section 5 presents the conclusion of the study. 2. literature review to test the stated hypothesis, we refer to the relevant literature on the issue. for convenience purpose, the literature review is divided into three groups. first group present main results of different investigations on oil prices-employment nexus both in developed and developing countries, as well as countries, exporting and importing oil. concerning oil prices-employment nexus, a lot of studies are devoted to analysis of domestic market competition producers of oil and the influence of positive and negative oil price shocks on the competitive position of individual firms (e.g., gupta, 2016). some papers are devoted to the study of the relationship of oil prices and relevant macroeconomic variables: employment, migration, stock returns, costs and budget restrictions of households, economic growth, dynamics of export and import flows, international movement of capital, impact of oil prices on monetary policy, etc. a nice literature review on this issue is presented in the paper by ozturk (2010). in our case, the closest for the subject, are the studies devoted to the relationship between oil prices and the labor market, including employment/unemployment issue. a brief overview of the literature on this nexus is presented in table 1. burakov: oil hikes, drugs and bribes: do oil prices matter for crime rate in russia? international journal of energy economics and policy | vol 9 • issue 1 • 201986 author sample methodology results of the study oil prices-employment nexus keane and prasad (1996) usa, oil prices employment – real wages panel data analysis, ols oil price increase leads to negative response in employment in short-run, in the long-run – positive. oil price changes cause changes in employment and relative wages across industries hooker (1996) usa, 1948-1994 with structural breaks, oil prices – unemployment – economic growth granger causality test oil price changes cause economic growth and changes in unemployment hoag and wheeler (1996) impact of oil prices on employment on industrial level, usa (ohio), micro-level analysis var analysis oil price shocks significantly impact employment in mining industry. carruth et al. (1998) usa, post-war period; real oil prices-real interest rates unemployment oil price shocks and shocks in real interest rates affect unemployment rate in the short-run. gil-alana (2003) australia, oil prices unemployment, 1954-1995 cointegration approach oil prices and unemployment are cointegrated, the first causing the last. altay et al. (2006) turkey, oil prices – employment nexus vec approach oil prices, income and employment are related in the long-run. oil prices and income cause changes in employment in the short-run. ewing and thompson (2007) usa, oil prices – unemployment cyclical estimates, filtering analysis, correlation analysis oil price changes significantly affect unemployment, inflation, output and stock market index. dogrul and soytas (2010) turkey, 2005-2009, interest rate, oil price and unemployment nexus toda-yamamoto causality test oil prices significantly cause unemployment ahmad (2013) pakistan, 1991-2010, interest rate, oil price and unemployment nexus toda-yamamoto causality test oil prices significantly cause unemployment (precautionary demand) tarek et al. (2017) saudi arabia, 1980-2015, oil price-employment level ardl approach oil price positively influence employment. effects of positive and negative oil shocks on employment are asymmetric. burakov and kurnysheva (2017) russia, 1990-2016, oil prices – unemployment – real wages vec approach there exist a long-term relationship between world oil prices, levels of employment and real wages both in longand short-run. (un) employment-crime rate nexus carmichael and ward (2001) male unemployment – crime rate nexus, britain, 1989-1996 causality analysis male unemployment is the most influencing factor to the crime rate in britain. most of the crimes in britain are positively related to male un-employment regardless of age structure. messner et al. (2001) unemployment-crime rate nexus, usa. time-series analysis unemployment rate is negatively related to crime in the united states and the coefficients are statistically significant at 1% and 5% levels. narayan and smyth (2004) crime rate male youth unemployment real income, australia, 1964-2001 granger causality test result show that unemployment rate is not an important determinant of crime in australia because the granger causality test tends to show neutrality causal effect results. lee and holoviak (2006) unemployment-crime rate variables nexus, australia, japan, south korea johansen’s maximum likelihood cointegration tests the results of the study provide strong support for a long-run equilibrium relationship between unemployment and several crime series. table 1: literature review (contd...) burakov: oil hikes, drugs and bribes: do oil prices matter for crime rate in russia? international journal of energy economics and policy | vol 9 • issue 1 • 2019 87 author sample methodology results of the study tang and lean (2007) inflation-unemployment rate-crime rate nexus, usa, 1960-2006 bounds testing approach, modified wald test inflation and unemployment rates are two important determinants of crime in the united states. yet, in the short-run unemploy-ment rate is negatively related to crime rate. but the relationship shifts to positive in the long run. tang (2009) relation between inflation, unemployment and crime rates, malaysia, 1970-2006 vec approach inflation and unemployment are positively related to crime rate in the long-run. unemployment is significant for crime rate in the short run. causality direction is running from inflation and unemployment to crime rate. papps and winkelmann (2009) unemployment crime rates nexus, new zealand, 1984-1996 random and fixed effects modeling regression results provide evidence for significant effects of unemployment on crime, both for total crime and for some subcategories of crime. saridakis and spengler (2012) crime-deterrence-unemployment nexus, greece, 1991-1998 panel analysis, dynamic modelling, gmm the results show that property crimes are significantly deterred by higher clear-up rates and that unemployment increases crime. for violent crimes, the effect of the clear-up rate and unemployment are found to be generally insignificant. han et al. (2013) crime detection rate/prison population-unemployment rate-real earnings nexus, england and wales, 1992-2008 fixed effect dynamic gmm estimation methodology higher detection rate and prison population leads to lower property and violent crimes. however, socio-economic variables with the exception of real earnings play a limited role in explaining different crime types. speziale (2014) unemployment-crime rate nexus, italy (regional level, 103 provinces), 2000-2005 dynamic specification approach results are in line with the predictions of the economic model of crime. the unemployment rates have a positive correlation with all crime rates. blomquist and westerlund (2014) unemployment-crime rate nexus, sweden (regional level, 21 counties), 1975-2010 cointegration analysis the results do not support cointegration between unemployment and crime rate, and suggest that previous findings of a significant unemployment crime relationship might be spurious. janko and popli (2015) unemployment rate-crime rate nexus, canada (national and regional levels), 1979-2006 error correction approach, panel analysis authors find no evidence of long-run relationship between crime and unemployment, both when look at disaggregation by type of crime and disaggregation by region. oil-crime rate nexus luthra et al. (2007) oil/gas industry development-crime rate nexus, us regional level, louisiana pooled time-series analysis the results suggest that changes in oil activity and high levels of labor market involvement in the offshore oil industry are neither strongly nor consistently associated with community disruption in the form of crime o’connor (2017) oil boom-crime rate nexus, us regional level, north dakota regression analysis, t-tests few significant relationships were found that could link the oil boom to increases in crime and disorder table 1: (continued) (contd...) burakov: oil hikes, drugs and bribes: do oil prices matter for crime rate in russia? international journal of energy economics and policy | vol 9 • issue 1 • 201988 as can be seen from the overview given in table 1, most of research, devoted to oil prices-employment nexus confirms the statistical significance of oil price shocks on various macroeconomic variables, especially on employment, economic growth and wage levels. in some cases, an important role is played by the status of the national economy. if the country is a net importer of oil, the reaction to the rise in oil prices is more likely to be negative. if the country is an oil exporter, the additional income leads to economic growth, growth of wages and the multiplying effect in other sectors of the economy. the second group of the literature sources is devoted to investigation of unemployment-crime rate nexus. as can be seen from literature review in table 1, results of different studies are ambiguous. in some cases, authors find strong statistical evidence of importance of unemployment in explaining dynamics of crime rate. different econometric models, different time spans, different states sampled bring ambiguous results. this ambiguity may be brought to life by several reasons. firstly, investigations of the nexus use different proxies and indices for capturing crime behavior. some studies include only violent crimes; others are devoted to investigation of property crimes (economic model or motivation hypothesis of crime). secondly, some studies are devoted to the search of causal relationship between the variables, while others test the cointegration issue and try to find shortand long-term effects. yet, overall results for italy, greece, malaysia and new zealand show that the motivation hypothesis (rising unemployment during recessions increasing property crime rate) holds true (saridakis and spengler, 2012; speziale, 2014; papps and winkelmann, 2009; tang, 2009). the opportunity hypothesis is confirmed in the shortrun for the us (messner, 2001; tang and lean, 2007). results, obtained by han et al. (2013), blomquist and westerlund (2014), as well as by janko and popli (2015), showing no relationship between the variables in the uk, sweden and canada may be attributed to higher institutional quality, national traditions and other social institutions, like law enforcement, civil rights protection quality, social payments or higher costs of engagement in crime activities. the third group of the literature sources is devoted to investigation of oil prices-crime rate nexus. the studies on this nexus are rather scarce. most of literature on this issue is devoted to empirical research of oil price shock effects on crime rate on the regional or even town level. earlier results show that the link is absent (e.g., luthra et al., 2007; o’connor, 2017), yet current investigations on examples of the us and the uk bring evidence of oil price shocks being significant for rising crime rates in the sampled regions. (james and smith, 2017; andrews and deza, 2018; stretesky et al., 2018) ambiguity of results may be related, in our opinion, to differences in used econometric techniques, as well as to shifts in costs of engagement in crime activities over time. for example, growing digitalization and automatization of economies, rising economic and financial inequality may be sufficient factors, explaining the spur of the nexus. yet, empirical studies, devoted to the investigation of the relationship between oil prices’ shocks and crime rate (measured author sample methodology results of the study james and smith (2017) tight oil/shale gas production – crime rate (excluding drug dealing), us counties (215), 2000-2011 difference-in-difference approach, conditional relationship analysis results bring evidence that regional shale booms elevate crime rates in different counties across the us. authors find statistically significant increase in all types of crimes (assault, rape, murder, larceny, robbery and auto theft). andrews and deza (2018) value of local oil reserves – crime (murder, robbery, larceny) nexus, us regional level, texas regression analysis, ols, two-stage least squares results show that a 1% increase in the value of oil reserves increases murder by 0.16%, robbery by 0.55% and larceny by 0.18%. using the estimated elasticities, an average increase in the value of oil reserves (26% increase in the value of reserves) results in a 4.15% increase in murder rates, 8% increase in robbery and 4.7% increase in larceny. stretesky et al. (2018) spudded oil and gas wells – violent and property crime rates nexus, the uk regional level (69 local authorities), 2004-2015 fixed effects regression analysis results show that wells are positively correlated with violent crime rates. each additional well is associated with a 1.5% increase in violent crime. when the analysis is limited to those local authorities that have constructed the most wells, the correlation between wells and crime increases as the boomtown literature might suggest. in particular, each additional well is associated with a 4.9% increase in violent crime and a 4.9% increase in property crime. table 1: (continued) burakov: oil hikes, drugs and bribes: do oil prices matter for crime rate in russia? international journal of energy economics and policy | vol 9 • issue 1 • 2019 89 as bribery and drug dealing) at the macro-level in oil-exporting countries are absent. 3. materials and methods 3.1. research methods to test the hypothesis about relationship between shocks in oil prices, unemployment and crime rate in russia, we use econometric techniques to analyze time series. the algorithm of the ongoing study is determined by several key stages. first and foremost, one should test sampled variables on stationarity or order of cointegration, since the time series must have the same order, as can be seen from equation (1). secondly, it is necessary to determine presence/absence of correlation in long term between the variables in the equation. to check this assumption, we use a johansen cointegration test. in a case of a long-term relationship on the one hand and condition of stationarity of sampled time series in the first order i (1) on the other, it is possible to use vec model. in case of confirmation of presence of cointegration between the variables of the sample, residuals of the equilibrium regression can be used to estimate error correction model. also based on vec model it is possible to identify short-term relationships between sampled variables. for this purpose, we use the wald test. the final stage of constructing a model is to conduct diagnostic tests to determine validity of the model. these include testing for heteroscedasticity and serial correlation, normality and stability of the model. 3.2. unit root test for the analysis of long-term relationships between the variables, johansen and juselieus (1990) admit that this form of testing is only possible after fulfilling the requirements of stationarity of the time series. in other words, if two series are co-integrated in order d (i.e., i (d)) then each series has to be differenced d times to restore stationarity. for d = 0, each series would be stationary in levels, while for d = 1, first differencing is needed to obtain stationarity. a series is said to be non-stationary if it has non-constant mean, variance, and auto-covariance over time (johansen and juselius, 1990). it is important to cover non-stationary variables into stationary process. otherwise, they do not drift toward a long-term equilibrium. there are two approaches to test the stationarity: augmented dickey and fuller (adf) test (1979) and the phillipsperron (p-p) test (1988). here, test is referred to as unit-root tests as they test for the presence of unit roots in the series. the use of these tests allows to eliminate serial correlation between the variables by adding the lagged changes in the residuals of regression. the equation for adf test is presented below: ∆yt=β1+β2t+ayt-1+δ3∑∆yt-1+εt (1) where εt is an error term, β1 is a drift term and β2t is the time trend and ∆ is the differencing operator. in adf test, it tests whether a = 0, therefore the null and alternative hypothesis of unit root tests can be written as follows: h0: a = 0 (yt is non-stationary or there is a unit root). h1: a < 0 (yt is stationary or there is no unit root). the null hypothesis can be rejected if the calculated t-value (adf statistics) lies to the left of the relevant critical value. the alternate hypothesis is that a < 0. this means that the variable to be estimated is stationary. conversely, we cannot reject the null hypothesis if null hypothesis is that a = 0, and this means that the variables are non-stationary time series and have unit roots in level. however, normally after taking first differences, the variable will be stationary (johansen and juselius, 1990). on the other hand, the specification of p-p test is the same as adf test, except that the p-p test uses nonparametric statistical method to take care of the serial correlation in the error terms without adding lagged differences (gujarati, 2003). in this research, we use both adf and p-p test to examine the stationarity of the sampled time series. 3.3. johansen co-integration test to test for presence of cointegration we apply the johansen test using non-stationary time series (values in levels). if between variables does exist a cointegration, the first-best solution would be using vecm model. an optimal number of lags according to akaike information criterion for providing johansen test is determined in var space. to conduct johansen test, we estimate a var model of the following type: yt=a1yt-1+...+apyt-p+bxt+ϵt (2) in which each component of yt is non-reposeful series and it is integrated of order 1. xt is a fixed exogenous vector, indicating the constant term, trend term and other certain terms. εt is a disturbance vector of k dimension. we can rewrite this model as: 1 1 11 p t t i t t ti y y v y bx − − −= ∆ = + ∆ + +∈∑∏ (3) where ,1 1 p p i i ji j i a i v a = = + = − = −∑ ∑∏ (4) if the coefficient matrix π has reduced rank r < k, then there exist k × r matrices α and β each with rank r such that ∏ = αβ and β’yt is i (0). r is the number of cointegrating relations (the cointegrating rank) and each column of β is the cointegrating vector. the elements of α are known as the adjustment parameters in the vec model. johansen’s method is to estimate π matrix from an unrestricted var and to test whether we can reject the restrictions implied by the reduced rank of ∏ (johansen, 1998). 3.4. vector error correction model granger (1988) suggested the application of vector error correction methodology (vecm) in case if the variables are cointegrated in order to find short-run causal relationships. vecm, therefore, enables to discriminate between long-run equilibrium and short-run dynamics. in this sense, we employ following vecms to estimate causal linkages among the variables: burakov: oil hikes, drugs and bribes: do oil prices matter for crime rate in russia? international journal of energy economics and policy | vol 9 • issue 1 • 201990 0 1 2 1 1 3 1 1 1 k n t i t i i i m t i t i a a lnl a lns ln l a lnr ect vλ − − = = − − = + ∆ + ∆ + ∆ = ∆ + + ∑ ∑ ∑ 0 1 2 1 1 3 1 2 1 k n t i t i i i m t i t i lnm lnl ln m lnr ect v β β β β φ − − = = − − = + ∆ + ∆ + ∆ = ∆ + + ∑ ∑ ∑ 0 1 2 1 1 3 1 3 1 k n t i t i i i m t i t i lnr lnl lnr lnm ect v η η η η χ − − = = − − = + ∆ + ∆ + ∆ = ∆ + + ∑ ∑ ∑ where l international oil prices (brent), s – unemployment rate in russia, y – averaged index of crime rate in russia, including bribery and drug dealing (granger, 1988). providing regression analysis of the sampled variables by modeling vecm allows us to determine the existence of substantial and statistically significant dependence not only on the values of other variables in the sample, but also dependence on previous values of the variable. however, vec model must meet the requirements of serial correlation’s absence, homoscedasticity of the residuals and to meet the requirement of stability and normality. only in this case the results can be considered valid. 3.5. materials and data processing we test a hypothesis of relationship between oil prices shocks, unemployment rate and crime rate (bribery and drug dealing average) on example of russian data for the period 1990-2017. the base period is 1 year. unfortunately, use of monthly and quarterly values of variables for the analysis is hindered due to availability of only yearly data for crime rate statistics. moreover, for brent oil prices we use aggregate yearly values. using vecm, we set ourselves a task to determine sensitivity of crime activity in russia to shocks in international oil prices. data on unemployment rate and crime rate is obtained from federal service of state statistics (www.gks.ru) and ministry of internal affairs of the russian federation (https://en.mvd.ru) data on world prices of oil is obtained from the statistical database of nasdaq (www.nasdaq.com). to conduct time-series analysis, all variables were transformed into logarithms. to identify and formally assess the relationship between variables, we use simple correlation analysis. to study sensitivity and causal linkages between the variables in the sample in short-and long-run, we turn to regression analysis, which involves the construction of vec model of certain type based on stationary time series, testing the model for heteroscedasticity of the residuals, autocorrelation. 4. results and discussion the first step in testing the hypothesis is to test the variables for the presence of correlation. we use simple correlation analysis and imply pearson statististical significance test. results of correlation analysis ate presented in table 2. as can be seen from the results of the correlation analysis, the relationship between variables is statistically significant and the correlation coefficients are significant. for example, the correlation between oil prices and unemployment is negative in sign. growth in oil prices leads to a decrease in unemployment rate in russia and vice versa. at a confidence interval of 5%, the value of the correlation coefficient is 0.7935. the explanation to this observation, in our opinion, lies in the presence of indirect depending on the level of employment from oil prices. the price increase leads to an increase in government revenue and expenditure, growth of household incomes and thus consumption and, consequently, employment. in the period of crisis, the relationship is also opposite. the falling oil price reduces income, consumption, investment, and the need for workers, thus giving rise to unemployment. unemployment also correlates with the crime rate, being statistically significant. the correlation coefficient has a positive sign, meaning that a rise in unemployment rate increases crime activities, measured as drug dealing and bribery. and, logically, a rise in oil prices leads to a decline in drug dealing and bribery. preliminary correlation results speak in support of motivation hypothesis. however, unconditional acceptance of the results of correlation analysis is impossible due to possible existence of serial correlation, problem of multicollinearity. in this regard, it is necessary to turn to more qualitative techniques of analysis. the second step in testing hypotheses is to test variables for the presence of unit root. for this purpose, we use standard tests adf and p-p test. results of unit root testing are presented in table 3. table 2: results of correlation analysis variable unemployment rate crime rate oil prices (brent) unemployment rate 1 crime rate 0,8543 (0.0019) 1 oil prices (brent) −0.7935 (0.0042) −0.7831 (0.0144) 1 table 3: results of individual unit root test variables in adf pp statistic prob.** statistic prob.** levels intercept 8.464 0.691 7.352 0.4695 intercept and trend 11.942 0.249 13.931 0.1143 first-difference intercept 35.294 0.0000** 42.568 0.0000** intercept and trend 28.852 0.0010** 49.242 0.0000** **denotes statistical significance at the 5% level of significance burakov: oil hikes, drugs and bribes: do oil prices matter for crime rate in russia? international journal of energy economics and policy | vol 9 • issue 1 • 2019 91 as can be seen from the test results of the variables for the presence of unit root in their differentiation to the first order, we can reject the null hypothesis of unit root in each of the variables. thus, the condition of stationarity at i (1) is performed, which gives us reason to test variables for cointegration. however, it is necessary to determine the optimal time lag. building a var model involves determining the optimal number of lags. in our case, the akaike information criterion equals 1. consequently, we built a model based using time lag of 1 year to determine the relationship in the short run. the results of the diagnostic testing of var model for heteroscedasticity of residuals, autocorrelation, serial cross-correlation, and stability are presented in table 4. as can be seen from table 4, the model is stable, heteroscedasticity and serial correlation of residuals in the model are absent. the model is used to determine the level of sensitivity of control variables to shocks in oil prices in the short run and we use it to test for stable long-run relationship, applying johansen cointegration test. results of johansen co-integration test are presented in table 5. johansen test results show the presence of cointegration between a number of equations, which allows presuming the existence of a long-term relationship between them. starting from the results of the cointegration test, we can proceed to the construction of vecm model to reveal presence or absence of long-term and short-term relations between variables. the results of the model, showing the relationship between oil prices, crime rates and unemployment rate are presented in table 6. as can be seen from the table 6, the value of error correction term c (1) is negative in sign and statistically significant. this suggests the existence of long-run relationship between the variables of the sample. in other words, we obtained evidence that world oil prices, unemployment rate and crime rate in russia are cointegrated, so that they have similar trends of movement in the long term. the c (1) shows speed of long run adjustment. in other words, this coefficient shows how fast the system of interrelated variables would be restored back to equilibrium in the long run or the disequilibrium would be corrected. given statistical significance at 5% level (p < 5%) and negative meaning, the system of variables corrects its previous period disequilibrium at a speed of 28.91% in 1 year (given optimal lag meaning of 1 year for ecm). it implies that the model identifies the sizeable speed of adjustment by 28.91% of disequilibrium correction in 1 year for reaching long run equilibrium steady state position. high speed of adjustment of relations between variables towards equilibrium is quite understandable. considering the above mentioned fact about the dependence of the russian economy on oil rents, as well as the fact that a significant proportion of economic active population employed in the public sector, it is not surprising that shocks in oil prices have an impact on the main source of salary costs the budget. in the case of reduced income from oil exports unemployment rate begins to increase. to identify short-term relationship between the variables we refer to the wald test results. this test allows to determine the interrelationship between variables in the short term. in other words, under the null hypothesis of this test, the response of error correction term to explanatory variables equals zero, i.e., the sensitivity of resulting variable to changes (shocks) in explaining are not observed. results of wald test for the model are presented in table 7. as can be seen from the results of the wald test in the short term there is a relationship between changes in world oil prices and changes in the crime rate. moreover, this relationship is opposite. based on the results of the wald test, we can detect statistically significant effects running from changes in oil prices to the rate of drug dealing and bribery with rate of adjustment towards equilibrium of 1.14% in t-1. in other words, a rise (decline) in oil prices leads to a fall (rise) in crime activities. for example, a 1% decrease in oil price will lead to a 1.14% rise in bribery and drug dealing. the second result shows presence of causality running from unemployment rate to crime rate with the speed of adjustment towards equilibrium at 2.72%. so, the results of wald test show table 4: results of unrestricted var model diagnostic testing type of test results lags lm-statistic p value var residual serial correlation lm test 1 7.7834 0.5341 2 5.9245 0.6483 stability condition test all roots lie within the circle. var satisfies stability condition heteroscedasticity (white test) 0.4183* var residual cross correlation test no autocorrelation in the residuals **denotes acceptance of null hypothesis (h0: there is no serial correlation). *denotes acceptance of null hypothesis of homoscedasticity table 5: results of johansen co-integration test hypothesized no. of ce (s) eigenvalue trace statistics 0.05 critical value prob.* none* 0.9853 73.2048 29.7970 0.0153* at most 1 0.3864 8.7053 15.4947 0.3895 at most 2 0.0536 1.2549 3.8414 0.1249 trace statistics indicate 1 cointegrating equation at the 0.05 level. *denotes statistical significance at the 5% level of significance table 6: results of vector error correction model coefficient number coefficient meaning standard error t-statistic prob. c(1) −0.2891 347.143 3.0927 0.0104* c(2) −0.1523 0.380 5.2718 0.4509 c(3) −0.0114 291.354 2.5473 0.0143 c(4) 0.0272 227.143 2.2839 0.0358 c(5) 926.1378 385.882 2.6185 0.0034 *denotes statistical significance burakov: oil hikes, drugs and bribes: do oil prices matter for crime rate in russia? international journal of energy economics and policy | vol 9 • issue 1 • 201992 that unemployment rate in the short term has the potential to affect crime rate. thus, a 1% increase in the unemployment rate leads to a 2.72% increase in crime activities, measured by drug dealing and bribery. the revealed effects confirm the motivation hypothesis. on the one hand, a surge in oil prices leads to a decrease in oil revenue, which accounts for >40% of russia’s budget revenues. falling oil revenue leads to a decrease in government spending, budget sector wages and growth in unemployment. moreover, falling oil prices, leading to growth in unemployment rate, multiply the initial effect in the economy, leading to even more growing unemployment, which in turn accelerates engagement in crime activities. thus, an initial shock (1% decrease in oil prices) is multiplied through unemployment channel up to 3.86%. overall, the obtained results are consistent with existing empirical and theoretical results of the previous studies, reporting that a rise in unemployment could lead to a rise in crime rate. the explanation of the obtained results falls in line with the motivation hypothesis. lost jobs and declining wages increase the gap between consumption level and the budget constraint, leaving unemployed with the necessity to get addition income, which can be obtained through drug dealing. another interesting puzzle is an increase in bribery during recessions. again, the background is hidden in the necessity of state employees to restore the lost income (in form of bonuses, e.g.,) due to the cut in the wages by accelerating bribery schemes. the final stage of the analysis of the model is to determine the extent of its validity. for this, it is necessary to conduct some diagnostic tests, including tests for heteroscedasticity of the residuals and serial correlation in the model. the results of these tests are presented in table 8. 5. conclusion in case of oil-exporting countries, economic growth and employment rate significantly depend on world oil prices dynamics. oil prices, determining export revenues, which in most cases account for a large share of government spending, play a major role in determining the pace of the national economic growth. it’s quite logically to assume that in the case of oilexporting country, if oil revenues play a major role in government spending (like in cases of saudi arabia, russia, venezuela etc.), negative oil shocks may lead to an even greater negative impact on economic growth than in oil-importing countries or states, restraining the budget from resource curse. in other words, we hypothesize that a negative oil shock should lead to a rise in unemployment rate ceteris paribus. also we assume that a negative oil shock in oil exporting country should lead to deterioration on the labor market, thus rising a crime rate. to test the hypothesis about relationship between shocks in oil prices, unemployment and crime rate in russia, we use vector error correction approach. we test a hypothesis of relationship between oil prices shocks, unemployment rate and crime rate (bribery and drug dealing average) on example of russian data for the period 1990-2017. the base period is 1 year. results of the study show that world oil prices, unemployment rate and crime rate in russia are cointegrated, so that they have similar trends of movement in the long term. given statistical significance at 5% level (p < 5%) and negative meaning, the system of variables corrects its previous period disequilibrium at a speed of 28.91% in 1 year (given optimal lag meaning of 1 year for ecm). it implies that the model identifies the sizeable speed of adjustment by 28.91% of disequilibrium correction in 1 year for reaching long run equilibrium steady state position. based on the results of the table 7: wald test results for short run relationship test statistic value df probability test statistic value df probability t-statistic 1.4775 10 0.0012* t-statistic −1.1567 10 0.0143 f-statistic 1.5894 (1.10) 0.0012* f-statistic 1.2371 (1.10) 0.0143 chi-square 1.5894 1 0.0007* chi-square 1.2371 1 0.0079 null hypothesis: c (3)=0 (world oil prices) null hypothesis: c (4)=0 (unemployment rate) *denotes statistical significance and rejection of h0: no short-run relationship table 8: results of diagnostic testing test type value probability characteristic p value heteroscedasticity test: breusch-pagan-godfrey f-statistic 4.926431 prob. f (6,17) 0.1864 obs.*r-squared 11.17340 prob. chi-square (6) 0.2971 scaled explained ss 3.845761 prob. chi-square (6) 0.8863 heteroskedasticity test: arch f-statistic 0.95745 prob. f (1,12) 0.6184 obs*r-squared 0.78341 prob. chi-square (1) 0.5731 breusch-godfrey serial correlation lm test: f-statistic 2.27086 prob. f (2,8) 0.5012 obs*r-squared 3.05843 prob. chi-square (2) 0.2943 autocorrelation/partial correlation lag ac pac q-stat prob. 1 −0.012 −0.012 0.0016 0.854 2 −0.314 −0.314 2.7342 0.386 burakov: oil hikes, drugs and bribes: do oil prices matter for crime rate in russia? international journal of energy economics and policy | vol 9 • issue 1 • 2019 93 wald test, we can detect statistically significant short-run effects running from changes in oil prices to the rate of drug dealing and bribery with rate of adjustment towards equilibrium of 1.14% in t-1. in other words, a rise (decline) in oil prices leads to a fall (rise) in crime activities. for example, a 1% decrease in oil price will lead to a 1.14% rise in bribery and drug dealing. the second result shows presence of causality running from unemployment rate to crime rate with the speed of adjustment towards equilibrium at 2.72%. so, the results of wald test show that unemployment rate in the short term has the potential to affect crime rate. thus, a 1% increase in the unemployment rate leads to a 2.72% increase in crime activities, measured by drug dealing and bribery. the revealed effects confirm the motivation hypothesis. on the one hand, a surge in oil prices leads to a decrease in oil revenue, which accounts for more than 40% of russia’s budget revenues. falling oil revenue leads to a decrease in government spending, budget sector wages and growth in unemployment. moreover, falling oil prices, leading to growth in unemployment rate, multiply the initial effect in the economy, leading to even more growing unemployment, which in turn accelerates engagement in crime activities. thus, an initial shock (1% decrease in oil prices) is multiplied through unemployment channel up to 3.86%. overall, the obtained results are consistent with existing empirical and theoretical results of the previous studies, reporting that a rise in unemployment and a decrease in oil prices could lead to a rise in crime rate. the explanation of the obtained results falls in line with the motivation hypothesis. references ahmad, f. (2013), the effect of oil prices on unemployment: evidence from pakistan. business and economic research journal, 4(1), 43-57. alkhateeb, t.t.y., sultan, z.a., mahmood, h. (2017), oil revenue, public spending, gross domestic product and employment in saudi arabia. international journal of energy economics and policy, 7(6), 27-31. altay, b., topeu, m., erdogan, e. (2013), oil price, output and employment in turkey: evidence from vector error correction model. international journal of energy economics and policy, 3, 7-13. andrews, r., deza, m. (2018), local natural resources and crime: evidence from oil price fluctuations in texas. journal of economic behavior and organization, 151, 123-142. becker, g. (1968), crime and punishment: an economic approach. journal of political economy, 76, 1169-1271. blomquist, j., westerlund, j. (2014), a non-stationary panel data investigation of the unemployment–crime relationship. social science research, 44, 114-125. burakov, d., kurnysheva, i.(2017), do oil price shocks matter for competition: a vector error correction approach to russian labor market. international journal of energy economics and policy, 7(4), 68-75. cantor, d., land, k. (1985), unemployment and crime rates in the postworld war ii united states: a theoretical and empirical analysis. american sociological review, 50(3), 317-332. carmichael, f., ward, r. (2001), male unemployment and crime in england and wales. economics letters, 73, 111-115. carruth, a., hooker, m.a., oswald, a. (1998), unemployment equilibrium and input prices: theory and evidence from the united states. review of economics and statistics, 80, 621-628. dickey, d., fuller, w. (1979), distribution of the estimators for autoregressive time series with a unit root. journal of american statistical association, 74, 427-431. dogrul, h.g., soytas, u. (2010), relationship between oil prices, interest rate and unemployment: evidence from an emerging market. energy economics, 32(6), 1523-1528. ewing, b., thompson, m. (2007), dynamic cyclical co-movements of oil prices with industrial production, consumer prices, unemployment, and stock prices. energy policy, 35, 5535-5540. gil-alana, l.a. (2003), unemployment and real oil prices in australia: a fractionally cointegrated approach. applied economics letters, 10, 201-204. granger, c.w.j. (1988), some recent development in a concept of causality. journal of econometrics, 39, 199-211. gujarati, d. (2003), basic econometrics. 4th ed. london: mc graw-hill. gupta, k. (2016), oil price shocks, competition, and oil and gas stock returns-global evidence. energy economics, 57, 140-153. han, l., bandyopadhyay, s., bhattacharya, s. (2013), determinants of violent and property crimes in england and wales: a panel data analysis. applied economics, 45(34), 4820-4830. hoag, j., wheeler, m. (1996), oil price shocks and employment: the case of ohio coal mining. energy economics, 18(3), 211-220. hooker, m.a. (1996), what happened to the oil price-macro economy relationship? journal of monetary economics, 38, 195-213. james, a., smith, b. (2017), there will be blood: crime rates in shalerich u.s. counties. journal of environmental economics and management, 84, 125-152. janko, z., popli, g. (2015), examining the link between crime and unemployment: a time-series analysis for canada. applied economics, 47(37), 4007-4019. johansen, s. (1988), statistical analysis of co-integration vectors. journal of economics dynamic and control, 12, 231-254. johansen, s., juselius, k. (1990), maximum likehood estimation and inference on co-integration with applications to the demand for money. oxford bulletin of economics and statistics, 52, 169-210. keane, m.p., prasad, e.s. (1996), the employment and wage effects of oil price changes: a sectoral analysis. review of economics and statistics, 78(3), 389-400. lee, d., holoviak, s. (2006), unemployment and crime: an empirical investigation. applied economics letters, 13(12), 805-810. luthra, a.d., bankson, w., kalich, d., forsyth, c. (2007), economic fluctuation and crime: a time-series analysis of the effects of oil development in the coastal regions of louisiana. deviant behavior, 28(2), 113-130. messner, s.f., raffalovich, l.e., mcmillan, r. (2001), economic depreciation and changes in homicide rates for white and black youths, 1967-1998: a national time-series analysis. criminology, 39, 591-614. narayan, p.k., smyth, r. (2004), crime rates, male youth unemployment and real income in australia: evidence from granger causality tests. applied economics, 36, 2079-2095. o’connor, c. (2017), oil, crime, and disorder: a methodological examination of the oil boom’s impact in north dakota. deviant behavior, 38(4), 477-491. ozturk, i. (2010), literature survey on energy-growth nexus. energy policy, 38, 340-349. papps, k., winkelmann, r. (2000), unemployment and crime: new evidence for an old question. new zealand economic papers, 34(1), 53-71. phillips, p.c.b., perron, p. (1988), testing for unit root in time series regression. biometrica, 5, 335-346. saridakis, g., spengler, h. (2012), crime, deterrence and unemployment in greece: a panel data approach. the social science journal, 49(2), 167-174. burakov: oil hikes, drugs and bribes: do oil prices matter for crime rate in russia? international journal of energy economics and policy | vol 9 • issue 1 • 201994 speziale, n. (2014), does unemployment increase crime? evidence from italian province. applied economics letters, 21(15), 1083-1089. stretesky, p.b., long, m.a., mckie, r., aryee, f.a. (2018), does oil and gas development increase crime within uk local authorities? the extractive industries and society, 5, 356-365. tang, c.f. (2009), the linkages among inflation, unemployment and crime rates in malaysia. international journal of economics and management, 3, 50-61. tang, c.f., lean, h.h. (2007), will inflation increase crime rate? new evidence from bounds and modified wald tests. global crime, 8, 311-323. tarek, t.y.a., haider, m., zafar, a.s., nawaz, a. (2017), oil price and employment nexus in saudi arabia. international journal of energy economics and policy, 7(3), 277-281. . international journal of energy economics and policy | vol 8 • issue 3 • 2018 37 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(3), 37-42. the influence of fuel prices and unemployment rate towards the poverty level in indonesia abd azis muthalib1, pasrun adam2*, rostin3, zainuddin saenong4, la ode suriadi5 1department of economics, universitas halu oleo, kendari 93232, indonesia, 2department of mathematics, universitas halu oleo, kendari 93232, indonesia, 3depertment of economics, universitas halu oleo, kendari 93232, indonesia, 4depertment of economics, universitas halu oleo, kendari 93232, indonesia, 5depertment of economics, universitas halu oleo, kendari 93232, indonesia. *email: adampasrun@gmail.com abstract the purpose of this study is to examine the influence of fuel prices and unemployment rates toward poverty levels. the data used were yearly time series data consisting of fuel price, unemployment rate, and poverty level that span from 1998 to 2017. to test the influence of fuel price and unemployment rate toward the poverty level, the autoregressive distributed lag model was used. the results of data analysis showed that in the short-term, there is a negative influence of fuel prices toward the level of poverty. meanwhile, there is a positive influence of unemployment rate on poverty level in the long-term. in this case, every 1% increase (decrease) the unemployment rate, the poverty rate rose (down) by 0.3309%. keywords: fuel price, unemployement rate, poverty level, autoregressive distributed lag model jel calassifications: c220, e310, i32, j64 1. introduction the need of fuel for mankind is vital, because all economic sectors in a country from agriculture, industry, mining, transportation, trade and services need fuel that keeps increasing from year to year along with increasing economic activity of a country. in agriculture, these fuels are needed to move agricultural equipment (rafiq et al., 2009; adam, 2016; adam et al., 2018). in the field of industry, fuel is needed to drive industrial machinery in producing goods. in the field of transportation and trade, fuel is needed to mobilize the means of transportation both for goods and public transportation. in the field of mining, fuel is also required to move mining equipment in producing minerals. in addition, consumer households also need large amounts of fuel as the population and households increase. therefore, every policy, especially the policy of fuel price increase, will have an impact on all sectors of the economy in a country and no exception to the household sector as a consumer. empirical facts show that any increase in international oil prices is always followed by the policy of fuel price increase in the country by the government. this fuel price increase always has an impact on the increase in production costs (sugden, 2009, baumeister and killian, 2014, adam et al., 2016) and transportation costs. the increase in production costs will affect the price increase of goods or inflation in the country. so, in the next turn, it can reduce the purchasing power of the community that is resulting in poverty and unemployment increase. wirjodirjo and ummatin (2017) in their study found that the impact of rising fuel prices started from the fraction of the fuel price increase that affected the amount of inflation. the increase in inflation will also cause a decline in the purchasing power of companies to buy fuel as industrial raw materials, so the production capacity will also decrease. this production capacity decrease affects employment and welfare levels. inflation also causes the real income received to be reduced. poverty is a problem faced by all countries in the world, especially in developing countries. therefore, poverty should be solved immediately so it does not become a big problem in economic development. thus, in the international scope, poverty has become the agenda set forth in the millennium development goals. muthalib, et al.: the influence of fuel prices and unemployment rate towards the poverty level in indonesia international journal of energy economics and policy | vol 8 • issue 3 • 201838 research on the influence of fuel prices on poverty levels and also the effect of unemployment on poverty rates are still rarely done by researchers. the influence of fuel prices on poverty levels has been studied by previous researchers such as pradhan and sahoo (2002) and oluwatayo and alagbe (2015). there were different findings in their research. pradhan and sahoo (2002) found that rising fuel prices lowered the poverty level, while oluwatayo and alagbe (2015) found that rising fuel prices raised poverty levels. furthermore, research on the influence of the unemployment rate on poverty level has also been studied by previous researchers such as de-fina (2004) where she found that unemployment rates did not significantly affect poverty levels. in accordance with the literature search, it is found that research on the influence of fuel prices and unemployment rate in indonesia has not been reported, so the research on the influence of fuel prices and unemployment rate on poverty level in indonesia is important in order to provide information about it. therefore, this study aims to examine the effect of fuel prices and unemployment rates on poverty levels in indonesia. the econometric model used to test the effect is the autoregressive distributed lag (ardl) model. 2. literature review in this section, the researchers would like to present the results of previous research, both theoretical research and empirical research. from the literature search results, the literature review is grouped into four research groups: (1) the relationship between fuel prices and poverty rates, (2) the relationship between fuel prices and other macroeconomic variables (including poverty levels), (3) the relationship between unemployment rate and poverty levels, and (4) the relationship between unemployment rates and other macroeconomic variables (including poverty levels). the relationship between fuel prices and poverty levels was examined by previous researchers as follows; pradhan and sahoo (2002) built a mathematical model of the relationship between international oil prices and poverty levels. to test this relationship, they performed a model simulation using data in india. model simulation results showed that the production of fuel in the country could reduce oil imports, so the effect of international oil prices on the level of poverty was negative. chitiga and fofana (2012) examined the influence of fuel prices toward poverty level in south africa. they found that the price of fuel positively affected the poverty level. naranpanawa and bandara (2012) and reyes et al. (2009) examined the effect of fuel prices on poverty levels and other macroeconomic variables. naranpanawa and bandara (2012) examined the effect of rising fuel prices on economic growth and poverty levels in sri lanka. their findings suggested that rising fuel prices were affecting economic growth and poverty levels. reyes et al. (2009) examined the effects of rising rice prices and fuel prices on poverty levels in the philippines. their findings suggested that there was an effect of rising rice prices and fuel prices on poverty levels. the magnitude of this influence differed among the locations of poverty. yao (2004), and sackey and osey (2006) conducted a research of the relationship between unemployment rate and poverty level. yao (2004) built a mathematical model that linked between variables of unemployment and poverty level. in this model, the poverty level was the dependent variable, while the unemployment rate was the independent variable. the model built was then tested empirically using data in china. empirical test results showed that unemployment rate affected poverty level. sackey and osey (2006) examined the relationship between unemployment and poverty level in ghana. their results showed that there was a relationship between unemployment and poverty level. blank and blinder (1985) conducted a research of the influence of macroeconomic variables (inflation, unemployment rate and tax policy) toward poverty level. the results of data analysis showed that inflation, unemployment and tax rates had an effect on poverty level. the effect of unemployment rate on poverty level was negative. haveman and schwabish (2000) examined the relationship between unemployment, economic growth and poverty level. they found that the unemployment rate positively affected the poverty level, and there was a strong relationship between economic growth and poverty level. martinez et al. (2001) examined the relationship between unemployment rate, income distribution and poverty levels. they found that there was an influence of the unemployment rate on the distribution of income and poverty levels. xue and zhong (2003) conducted a research of the issue of unemployment and poverty level in china. he found that the unemployment rate and migration from rural to urban areas were the main causes of rising poverty levels in the city. freeman (2003) investigated the relationship between unemployment rates, poverty level, and income growth rates. based on data analysis, he found that the poverty level and income growth rate were sensitive to the unemployment rate. 3. data and methodology 3.1. data the data of this study were the price of fuel, the unemployment rate, and the poverty level. the data used was an annual time series that spans from 1998 to 2017. the price of fuel was proxied with the fuel price index. the both unit measurements of the annual time unemployment rate and the poverty level were %. the time series of the fuel price index was obtained from index mundi. meanwhile, both time series of unemployment and poverty level were obtained from the indonesian central bureau of statistics. 3.2. methodology the analytical tool used to test the influence of fuel prices and the unemployment rate on poverty levels was the ardl model. the ardl model included time lag elements for the dependent variable and independent variables in the equation. the dependent variable in this research was the poverty levels (pov), and the independent variables were fuel price index (fue) and unemployment rate (une). these three variables were natural logarithms. in the model equation formulation, the time lag for the pov variable was p, whereas the time lags for the fue and muthalib, et al.: the influence of fuel prices and unemployment rate towards the poverty level in indonesia international journal of energy economics and policy | vol 8 • issue 3 • 2018 39 une variables were q and r. thus, the ardl model that linked the relationship between une, fue and pov was represented by the ardl (p, q, r) model. the variables involved in the ardl (p, q, r) model should be stationary or integrated of order d, i (d). the order of integration could be different (pesaran and shin, 1999). therefore, to examine the effect of fuel prices and unemployment rates on poverty levels, the first step was to examine the order of integration or stationarity of variable (or time series). the stationary test used was augmented dickey-fuller (adf) test and phillips-perron test. the adf test was developed by dickey and fuller (1981), while the pp test was developed by phillips and perron (1988). the test criteria used was p-value criteria in which time series was said to be stationary or integrated of order d, i(d), if p-value was less than a certain level of significance (1%, 5% or 10%). if in the first step found that the three variables fue, une and pov stationary at the level or integrated of order zero, i(0), then it was conducted a regression coefficient estimation of ardl(p, q, r) model at level (heij et al., 2004); pesaran and shin, 1999), as follows: p q t 1 t 1i t-i 1j t-ji=1 j=0 r 1k t-k 1tk=0 pov = + t+ pov fue une + + + ∑ ∑ ∑ α β ϑ ϕ φ ε (1) where, α1,βt,ϑ1i (i=1,2,…,p).φ1j (j=0,1,…,q), and ϕ1k (k=0,1,…,r) are the regression parameter. next, t is trend and ε1t is error term with normal distribution and with constant variance (or homocedastic). the length of time lag p, q, and r is determined using schwardz criterion. if in the long term, the variables of fue, une and pow are in the stable condition (equilibrium), then the long term relation between fue, une and pow is stated with the equation as follows: ec =povt fue t i=1 p 1i 1 i=1 p 1i j=0 q 1j i=1 p 1i k α ϑ β ϑ ϕ ϑ 1 1 1 1 − − − − − − ∑ ∑ ∑ ∑ ==0 r 1k i=1 p 1i une ∑ ∑− φ ϑ1 (2) in the equation (2), ϕ ϕ ϑ = − ∑ ∑ j=0 q 1j i=1 p 1i1 and r 1kk=0 p 1ii=1 1    = − ∑ ∑ are called the long-term multiplier effect numbers or also called longterm coefficients of fue and une. the positive values of φ and ϕ show that the fuel price and unemployement rate have positive impact toward the poverty level. similarly, the negative values of φ and ϕ show that the fuel price and unemployement rate have negative impact toward the poverty level (koop, 2006; murthy and okumande, 2016). however, if in the first step, it is found that the three variables fue, une and pov are stasionary in the first diference or integrated of order one, i(1), then the second step is to test the cointegration relationship of the three variables fue, une and pov. since the number of samples is small, and narayan (2005) only set the bound tests critical value for samples ≥30 observations and less or equal to 80 observations, then in this reaserach, the cointegration testing did not use the ardl bound cointegration test of pesaran et al. (2001). for the alternative, the cointegration test used was the engle-granger cointegration test. this cointegration test can be used if all the time series involved in the ardl (p, q, r) model are integrated at the same order. the engle-granger cointegration test was performed by testing the stationarity of the ec variable in equation (2). if the ec was stationary at the level or integrated of order zero, i(0), then the three time series fue, une and pov would be cointegrated. conversely, if the ec variable was not stationary, then the three time series fue, une and pov were not cointegrated. if fue, une and pov were cointegrated, then fue, une and pov had a long-term relationship. if fue, une and pov were not cointegrated, then the third step was conducted the coefficients estimation of the ardl model in the first diference. conversely, if fue, une and pov were cointegrated, then the ardl model (heij et al., 2004) was estimated, as follows: ( ) p-1 t 2 2 t 2i t-ii=1 q-1 r-1 2 j t-j 2k t-k 2tj=0 k=0 d(pov ) + t+ ec 1 + d(pov ) d(fue ) d(une ) = + + + − ∑ ∑ ∑ α β γ ϕ ϕ ε (3) where, α2,βt,ϑ2i (i=1,2,…,p-1).φ2j (j=0,1,…,q-1), and ϕ2k (k=0,1,… ,r-1) are the parameter of regression, and ε2t is the error term. the equation (3) is called as error correction model. the time series of ect is obtained from the equation (2). the coefficients of ϑ2i (i=1,2,…,p-1), φ2j (j=0,1,…,q-1) φ2j (j=0,1,…,q-1) and ϕ2k (k=0,1,…,r-1) in the equation (3) is called as short-term coefficients. as an additional explanation in this section, we also present homogeneity test, autocorrelation test, and normality test of residual of the ardl (p, q, r) model. residual homocedastic (or heterokedastic) test is used arch test, residual autocorrelation test is used breusch-godfrey serial correlation lm (bgsclm) test, and residual normality test is used jarque berra (jb) test. these three tests were absolutely necessary to determine whether the model meets the ardl model analysis requirements. in addition, stability tests of long-term coefficients were also performed on the regression equation. this stability test was developed by brown et al. (1975). 4. results 4.1. stationary test and cointegration test the stationary test results using the adf test and the pp test for the fuel price variables (fue), the unemployment rate (une), and the poverty rate (pov) are summarized in table 1. it appears in table 1 that all variables are stationary at the first diference or integrated of order one, i(1). the stasionerity of variable fuel price was significant 1%. meanwhile, the variables of unemployment rate and poverty level were significant 5%. muthalib, et al.: the influence of fuel prices and unemployment rate towards the poverty level in indonesia international journal of energy economics and policy | vol 8 • issue 3 • 201840 the cointegration test results using the engle-granger test are summarized in table 2. it appears in table 2 that the time series of ec was significant 1%. this indicated that the stationary of ec was at the level, or integrated of order zero, i(0). thus, the three variables of fuel prices, unemployment rate, and poverty level were cointegrated. this means that these three variables had a long-term relationship. 4.2. influence test time lag calculations using the schwardz criterion indicated that the model used to test the effect of fuel prices and unemployment rates on poverty level was the ardl (1, 1, 0) model. the estimates of shortand long-term coefficients are summarized in table 3. it is seen in panel a in table 3, that the variable coefficient d (fue) is 10% significant and the variable coefficient d (une) is not significant. this means that there is a short-term effect of fuel prices on poverty levels, and in the short run, there is no effect of unemployment rates on poverty levels. furthermore, the variable coefficients of ec (−1) are significant 1% indicating that the longterm effects of fuel prices and unemployment rates on poverty level are corrected by 64.92%. in panel b in table 3, it can also be seen that the une variable coefficient is significant 10%, and the fue variable coefficient is not significant. therefore, only the unemployment rate has longterm effects on poverty levels. in this case, every 1% increase (decrease) the unemployment rate, then the poverty rate rose (down) by 0.3309%. 4.3. residual diagnotic and stability test of the regression equation coefficients the results of homogeneity test estimation, autocorrelation test, and normality test showed that the p-value of bgsclm test, p-value of arch test statistic, and p-value of jb test statistic were 0.2578, 0.5378 and 0.2931, respectively. these values were >5%. thus, the residual of the ardl (1, 1, 0) model had a constant variance (or homocedastic), had no autocorrelation, and was normally distributed. next, the plot results of long-term coefficients using the cusum test and cusum square test are shown in figure 1. in figure 1, it shows that by the cusum test, the coefficient graph of the regression equation is within the 5% significance limit. thus, the long-term coefficients are stable. 5. discussion the results of this study found that in the short term, there is a negative influence of fuel prices on the level of poverty, meaning that if the price of fuel increases, the poverty level will decrease, and vice versa. it happens because if there is an increase in the price of fuel, then the government always takes the policy to compensate the poor in the form of direct cash assistance so their table 1: unit root test variable adf test statistics pp test statistics without trend with trend without trend with trend fue −2.838904 −2.347261 −2.838904 −2.347261 d (fue) −5.033041* −5.085931* −5.033041* −6.198855* une −1.104601 −2.276309 −1.348392 −2.353602 d (une) −3.788090** −4.550405** −3.810246** −4.540607** pov −1.180639 −2.570170 −1.207744 −2.570170 d (pov) −4.197434* −4.236254** −4.198608* −4.238352** *,**are significant 1%, 5%. resource: own processing, adf: augmented dickey-fuller table 2: engle‑granger cointegration test variable adf test statistic p-value* ec −4.375416 0.0038 *mackinnon (1996) one-sided p values, adf: augmented dickey-fuller table 3: estimation of the long‑run and short‑run coefficients variable and constant coefficient t-statistics p-value a. short‑run coefficient estimation. dependent variable: d (pov) d (une) 0.004466 0.029068 0.9773 d (fue) −0.055388*** −1.854937 0.0906 ec(−1) −0.649246** −3.062380 0.0108 t −0.018207*** −1.942124 0.0782 b. long‑run coefficient estimation. dependent variable: pov une 0.330852*** 2.076663 0.0621 fue −0.085312 −1.646179 0.1280 c 2.559045* 7.477490 0.0000 t −0.028044* −3.504629 0.0049 *,**,*** are significant 1%, 5%, 10% figure 1: plot cusum (left) dan cusum square (right) muthalib, et al.: the influence of fuel prices and unemployment rate towards the poverty level in indonesia international journal of energy economics and policy | vol 8 • issue 3 • 2018 41 income will also increase. in addition, the government also takes an action to subsidize the fuel price increases. the compensation given by the government only takes place in the short term so that the impact of rising fuel prices on poverty reduction is only shortterm. meanwhile, if the price of fuel decreases, the poverty level increases. this is because the proportion of fuel expenditures for the poor is relatively smaller for the total consumption expenditure of poor households. thus, the fuel prices decrease cannot reduce the poverty level because their purchasing power remains low, so the poverty level increases. the results of this study support the results of naranpanawa and bandara (2012) and reyes et al. (2009) studies that found that the price of fuel affected poverty levels. the results of this study also found that in the long run there is a positive effect of the unemployment rate on the level of poverty. it means that the higher the unemployment rate, then the poverty level will also be higher. this is in line with the empirical fact that when a person is unemployed, it means that he does not get additional income, so the income received is reduced, and may have implications for increasing poverty levels. the results of this study support the results of sackey and osey (2006), haveman and schwabish (2000), xue and zhong (2003) and freeman (2003) studies that found an association between unemployment and poverty. 6. conclusion the purpose of this study is to examine the influence of fuel prices and unemployment rates on poverty levels. the data used to examine these influences are: the fuel price index as a proxy of the price of fuel, the unemployment rate (in %) and the poverty level (in %). time series data is an annual time series that spans from 1998 to 2017. the three time series of fuel price, unemployment rate, and poverty level are stationary at first diference level. the result of cointegration test using engle-granger cointegration test shows that the three time series are cointegrated. the results of this cointegration test indicate that the three time series has a longterm relationship. the result of influence test using the ardl model is obtained that there is a short-run influence of fuel price to poverty level. meanwhile, in the long-run, there is an effect of unemployment rate on poverty level. in this case, every 1% increase (decrease) of the unemployment rate, poverty level rose (down) by 0.3309%. references adam, p. (2016), the response of bank of indonesia’s interest rates to the prices of world crude oil and foreign interest rates. international journal of energy economics and policy, 6(2), 266-272. adam, p., rianse, u., harafah, l.m., cahyono, e., rafiy, m. (2016), a model of the dynamics of the effect of world crude oil price and world rice price on indonesia’s inflation rate. agris online papers in economics and informatics, 8(1), 3-12. adam, p., rosnawintang., saidi, l.o., tondi, l., sani, l.o.a. (2018), the causal relationship between crude oil price, exchange rate and rice price. international journal of energy economics and policy, 8(1), 90-94. baumeister, c., kilian, l. (2014), do oil price increases cause higher food prices? economic policy, 9(80), 691-747. blank, r.m., blinder, a. (1985), macroeconomics, income distribution and poverty. nber working paper series no. 1567. brown, r.l., durbin, j., evans, j.m. (1975), techniques for testing the consistency of regression relations over time. journal of the royal statistical society series b (methodological), 37(2), 149-192. chitiga, m., fofana, i. (2012), the poverty implications of high oil prices in south africa. environment and development economics, 17, 293-313. de-fina, r.h. (2004), the impact of unemployment on alternative poverty rates. review of income and wealth, 50(1), 69-85. dickey, d.a., fuller, w.a. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica: journal of the econometric society, 49(9), 1057-1072. freeman, d.g. (2003), poverty and the macroeconomy: estimates from u.s. regional data. contemporary economic policy, 21, 358-371. haveman, r., schwabish, j. (2000), has macroeconomic performance regained its anti-poverty bite? contemporary economic policy, 18, 415-427. heij, c., de-boer, p., franses, p.h., kloek, t., van-dijk, h.k. (2004), econometric methods with application in business and economics. new york: oxford university press. koop, g. (2006), analysis of financial data. chichester: john wiley & son ltd. martinez, r., ayaala, l., ruiz-huerta, j. (2001), the impact of unemployment on inequality and poverty in oecd countries. economic transition, 9(2), 417-447. murthy, v.n.r., okumande, a.a. (2016), determinants of u.s. health expenditure: evidence from autoregressive distributed lag (ardl) approach to cointegration. economic modelling, 59, 67-73. naranpanawa, a., bandara, j.s. (2012), poverty and growth impacts of high oil prices: evidence from sri lanka. energy policy, 45, 102-111. narayan, p.k. (2005), the saving and investment nexus for china: evidence from cointegration tests. applied economics, 37(17), 1979-1990. oluwatayo, i.b., alagbe, s.a. (2015), fuel price hike and vulnerability of households in nigeria: empirical evidence from ibadan metropolis. journal of social science, 43(3), 301-309. pesaran, m.h., shin, y. (1999), an autoregressive distributed-lag modeling approach to cointegration analysis. in: strom, s., editor. econometrics and economic theory in the 20th century: the ragnar frisch centennial symposium. cambridge: cambridge university press. p371-413. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 162, 89-326. phillips, p.c.b., perron, p. (1998), testing for a unit root in time series regression. biometrika, 75(2), 335-346. pradhan, b.k., sahoo, a. (2002), oil price shock and poverty in a cge framework. discussion paper series no. 18. new delhi: national council of applied economic research. rafiq, s., salim, r., bloch, h. (2009), impact of crude oil price volatility on economic activities: an empirical ınvestigation in the thai economy. resources policy, 34, 121-132. reyes, c.m., sobrevinas, a.b., bancolita, j., de-jesus, j. (2009), analysis of the impact of changes in the prices of rice and fuel on poverty in the philippines. discussion paper series no. 2009-07, the research information staff, philippine institute for development studies. sackey, h.a., osei, b. (2006), human resource underutilization in an era of poverty reduction: an analysis of unemployment and muthalib, et al.: the influence of fuel prices and unemployment rate towards the poverty level in indonesia international journal of energy economics and policy | vol 8 • issue 3 • 201842 underemployment in ghana. african development review, 18(2), 221-247. sugden, c. (2009), responding to high commodity prices. asian pasific economic literature, 25(1), 79-105. wirjodirjo, b.s., ummatin, k.w. (2017), impact of fuel price policy on poverty in indonesia. surabaya: department of industrial engineering, institut teknologi sepuluh november. xue, j., zhong, w. (2003), unemployment, poverty and income disparity in urban china. asian economic journal, 17(4), 383-405. yao, s. (2004), unemployment and urban poverty in china: a case study of guangzhou and tianjin. journal of international development, 16, 171-188. . international journal of energy economics and policy | vol 9 • issue 1 • 2019160 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(1), 160-167. renewable energy, shocks and the growth agenda: a dynamic stochastic general equilibrium approach philip alege, queen-esther oye, omobola adu* covenant university, nigeria. *email: omobola.adu@stu.cu.edu.ng received: 27 july 2018 accepted: 20 october 2018 doi: https://doi.org/10.32479/ijeep.6953 abstract macroeconomic fluctuations observed in real economies are results of identifiable shocks in form of technology, monetary, fiscal, trade, energy or a combination of these shocks. the adverse effects of energy price shocks, in recent decades, have made the call for renewable energy source important. this call is most appropriate in a mono-cultural economy where the fluctuations in crude oil pricing are easily transmitted into the economy. therefore, this paper seeks to investigate the consequences of technology, and energy shocks on key macroeconomic variables including output and consumption using an energy augmented small open economy dynamic stochastic general equilibrium model. the model is estimated using bayesian techniques under different scenarios in order to show the various ramifications of the shocks to the nigerian economy. the findings show that shocks to the renewable energy sector have more impact of the nigerian economy compared to shocks to the fossil fuel sector. keywords: fossil fuels, technology shocks, demand shocks, renewable energy, small open economy dynamic stochastic general equilibrium jel classifications: e32, k32, p18 1. introduction the pursuit of renewable energy options, by government, has become necessary in the face of addressing socio-economic and environmental challenges arising from the use of fossil energy. the adoption of renewable energy is expected to create increased access to electricity. for instance, this alternative energy source will help to balance up existing production and supply of electricity in nigeria (national renewable energy and energy efficiency policy, 2015). the increased access to renewable energy is also essential as a channel for employment generation. at the same time, the promotion of these alternative sources of energy will provide clean forms of energy that will combat environmental degradation and reduce health risks. it will also cushion the nigerian economy against petroleum price shocks. several policy plans have been proposed and adopted in nigeria in order to promote the use of renewable energy sources. these include the renewable energy master plan in 2012 which seeks to provide an enabling environment for the development of renewable energy in order to facilitate the development of the nation’s energy sector. the plan targets that 95% of nigerian household should access energy by 2030 and renewable energy sources should constitute 20% of total energy mix. national renewable energy and energy efficiency policy 2015 also propose that renewable sources should contribute 20% to of total electricity generation by 2030. it can be deduced from these policy plans that the right combinations of instruments are required to aid the development of the renewable energy sector in nigeria. these instruments include strategic policies and institutions, financial investment, modern technology and trained manpower. to this end, this study examines the mix of investment, technology and manpower and their importance in promoting alternative energy sources. the study also investigates the impact of shocks to the renewable energy sector on the nigerian economy. the objectives of this paper are, therefore, to assess the economywide effect of shocks to the renewable energy and fossil fuel this journal is licensed under a creative commons attribution 4.0 international license alege, et al.: renewable energy, shocks and the growth agenda: a dynamic stochastic general equilibrium approach international journal of energy economics and policy | vol 9 • issue 1 • 2019 161 sectors, within a small open economy dynamic stochastic general equilibrium (soedsge) model. the model is augmented to capture the fossil fuel and renewable energy sources. secondly, the study will also gauge the importance of the investment, technology and manpower mix in developing the renewable energy sector. the parameters of the soedsge model are calibrated to suit the nigerian economy and the model is solved using the log-linear approximation method. also, the study documents business cycle stylised facts in nigeria with relation to energy sources. the rest of this paper is structured as follows: section 2 provides a review of the literature. section 3 discusses the business cycle method and presents the business cycle stylised facts of nigeria in relation to renewable energy. the soedsge model of the study is presented in section 4 and the empirical findings and discussion of result are in section 5. the conclusion of the study is documented in section 6. 2. literature review empirical studies related to energy sources and most especially renewable energy and its linkages to the economy have received a lot of attention over the years. ogundipe et al. (2016) attribute this to partly the significant role energy plays in the achievement of sustainable economic development. furthermore, the threat of climate change as a result of emissions into the atmosphere places energy utilisation, its sources and policies at the forefront of environmental debate (adenikinju, 1995). this section provides a review of relevant and related literature in the area of nonrenewable and renewable energy sources in relation to sustainable growth and development. dogan and seker (2016) investigated the effects of renewable energy, non-renewable energy, real income and trade openness on carbon dioxide emissions for the european union over the period 1980-2012 using panel estimation techniques. the findings of the paper revealed that there is evidence of panel co-integration, hence a long run relationship between the macroeconomic variables. furthermore, it was observed that an increase in renewable energy leads to a decline in the level of emissions. on the other hand, an increase in non-renewable energy contributes to environmental degradation. through the use of an agent-based eurace model; ponta et al. (2018) examined the effects of a tariff policy mechanism allowing for the transformation of an economy from fossil fuel based to renewable energy based. the results indicated that in the presence of a feed-in tariff policy mechanism for renewable energy, there is a significant difference in the economic performance in relation to employment and investment decisions. contrary to expectations; tugcu and tiwari (2016) in their study showed that there are no causal links between renewable energy consumption (rec) and economic growth in the brics. in addition, it was observed that non-renewable energy creates a positive externality for countries like brazil and south africa thereby aiding economic development. dogan (2016) obtained similar results as it was found out that rec had an insignificant effect on economic growth in turkey, while non-renewable energy had a positive effect. however, in another study for the german economy; rafindadi and ozturk (2017) employed two distinct co-integration techniques to investigate whether renewable energy has impacted the growth of the economy. the results provided evidence of a long run relationship and an increase in renewable energy leads to an increase in economic growth. the contradicting result could be as a result of country-specific factors causing the differences. recent development in the area of energy studies have seen the application of dsge models to understand how exogenous and energy shocks affect the behaviour of agents in an economy. in that manner, fischer and springborn (2011) explore the impacts of emissions caps and emissions tax on the business cycle. the study makes use of a dsge model to evaluate the dynamic effects of these policy choices in the advent of a productivity shock. the major finding of the work was that an emission cap and tax reduces the effects of productivity shock on the economy. however, the effect of an emission tax comes with greater volatility. similarly, heutel (2012) investigated the optimal environmental policy decision in response to macroeconomic fluctuations caused by persistent productivity shocks for the united states economy. a dsge model was calibrated and the results indicated that optimal policy response is to increase emissions during periods of economic expansion and reduce emissions during periods of economic recession. also; annicchiarico and dio (2015) through the use of a dsge model accounting for nominal and real uncertainty found out that an emission cap is likely to dampen the effects of business cycles and optimal policy is largely influenced by price adjustment. argentiero et al. (2014) used a dsge model to assess the effectiveness of an incentive mechanism incorporating a carbon tax and a stock of public capital. this was done to show the behaviour of investors’ commitment towards renewable energy. the model was simulated and the findings favour the use of a stock of public capital in place of subsidies because subsidies reflect a short run policy which does not encourage investors’ confidence. argentiero et al. (2017) analysed the role of environmental policy in renewable energy sources based on carbon tax and renewable energy subsidies for 15 members of the european union, united states and china within a dsge model incorporating both a fossilfuel and renewable energy sector. the model was solved using bayesian techniques and the results showed that in the presence of a total factor productivity shock in the fossil-fuel sector, an energy policy shock serves as a driving force for dampening the energy sector. acemoglu et al. (2012) introduced an endogenous and directed technical change in a two-sector model to evaluate the response of different types of technologies to environmental policies. the model was able to show that sustainable growth can be achieved via carbon taxes and subsidies. also, delay in intervention is costly to the economy. likewise; argentiero et al. (2018) investigated the effectiveness of a cost-effective strategy for the implementation of renewable energy strategies based on either technology push and demand pull measures in a dsge model. they found out that a technology push measure is more suitable and effective. alege, et al.: renewable energy, shocks and the growth agenda: a dynamic stochastic general equilibrium approach international journal of energy economics and policy | vol 9 • issue 1 • 2019162 examining studies in nigeria, the relationship between energy consumption and economic development was investigated by ogundipe et al. (2016) through the use of co-integration estimation techniques. the study found out that there is a long run relationship. furthermore, a unidirectional relationship exists between economic development and electricity consumption. akinyemi et al. (2017) investigated the effects of the removal of fuel subsidy on carbon emissions through the use of a recursive computable general equilibrium model. simulations of the model revealed that carbon emissions marginally increased as a result of a partial subsidy removal. alege et al. (2017) documented business cycle facts between carbon emissions and total output, agricultural output as well as industrial output for nigeria. in addition, they examined the effects of real shocks on carbon emissions. the findings revealed that emissions are countercyclical to output, and pro-cyclical to both agricultural and industrial output. real shocks were seen to have a positive effect on the level of carbon emissions. in summary, from the literature reviewed, it can be seen that the energy sector plays an important role in ensuring sustainable development. renewable energy sources have become the forefront for policymakers as it is crucial in ensuring a clean and green environment. 3. the business cycle method: some stylised facts towards the documentation of business cycle stylised facts for nigeria in relation to energy sources and consumption, this approach of this study follows the common practice in the business cycle literature by decomposing the time series into trend and cyclical components through the use of a filtering technique, such as the hodrick-prescott (hp) filter (agenor et al., 2000; alege et al., 2017; and kim et al., 2003). the approach is as follows: taking the natural logarithm of the series; testing the stationary properties of the series; obtaining the cyclical component by detrending the series; computing the autocorrelation statistics of the series; and computing the cross correlation of the series (alege, 2008). the hp filter allows us to examine three key statistical issues: (1) the amplitude of fluctuations measured by the volatility and relative volatility. the volatility is derived from the percentage standard deviation of a series, while relative volatility is obtained from the ratio of the percentage standard deviation of a series to that of output. a variable is considered to be subject to high fluctuations when the relative volatility is >1. (2) the measurement of phase shift, that is, whether a variable change before or after changes in output. a variable is considered to lead the cycle if the maximum cross correlation coefficient is positive and lags the cycle if the maximum cross correlation is negative. (3) the contemporaneous correlation of a series with respect to output as measured by the cross-correlation coefficient. this helps to determine whether a series is pro-cyclical or countercyclical. a positive (negative) correlation between output and a macroeconomic variable indicates that the variable is proccyclical (countercyclical), whereas a correlation of zero suggests that the variable is acyclical. furthermore, one can say the variables are strongly contemporaneously correlated if 0.26≤|δj|≤1, weakly contemporaneously correlated if 0.13≤||δj|≤0.26, and contemporaneously uncorrelated with the cycle if 0≤|δj|≤0.13. the study makes use of annual data from 1990 to 2014 in order to derive the stylised facts for business cycles in nigeria with respect to energy sources. the macroeconomic variables used in the study are: real gross domestic product (rgdp), electricity production from hydroelectric sources (ephs), electricity production from natural gas sources, electricity production from oil, gas and coal sources, and rec (table 1). table 2 presents the result of the stylised facts for the nigerian economy in relation to energy sources. in terms of output fluctuations, rgdp in nigeria over the time period measured by the percentage standard deviation is about 5.352%. the volatility of ephs and natural gas sources are 6.572% and 6.792%, respectively. rec has a volatility of 1.412% and that of electricity produced from oil, gas and coal sources is 3.586%. examining the amplitude of fluctuations measured by the relative volatility, electricity produced from both hydroelectric and natural gas sources are all >1. this suggests that they are highly volatile and subject to macroeconomic fluctuations. on the other hand, rec and electricity produced from oil, gas and coal sources are subject to less volatility from the results. the degree of contemporaneous correlation between output and electricity produced from hydroelectric sources is −0.297 indicating a countercyclical relationship. this implies that an expansion in rgdp table 1: data description variables identifier description source measurement real gross domestic product rgdp real gross domestic product measured at 2010 constant prices in us dollars. wdi (2016) 2010 constant basic prices, billion (naira) electricity production from hydroelectric sources ephs it refers to electricity produced by hydroelectric power plants. wdi (2016) percentage electricity production from natural gas sources epns it refers to electricity produced by natural gas but excludes natural gas liquids. wdi (2016) percentage electricity production from oil, gas and coal sources epos sources of electricity refer to the inputs used to generate electricity. oil refers to crude oil and petroleum products. gas refers to natural gas but excludes natural gas liquids. wdi (2016) percentage renewable energy consumption rec renewable energy consumption is the share of renewable energy in total final energy consumption. wdi (2016) percentage wdi denotes world development indicators (wdi) database* alege, et al.: renewable energy, shocks and the growth agenda: a dynamic stochastic general equilibrium approach international journal of energy economics and policy | vol 9 • issue 1 • 2019 163 is usually accompanied by a reduction in electricity produced from hydroelectric sources. this finding is not surprising as statistics from the wdi reveal that despite the positive growth rate experienced during the time period, electricity produced from hydroelectric sources has been declining. specifically, while rgdp growth rate in 2010 was 7.84%, in 2011 it was 4.89% and in 2012 it was 4.28%; however, within that time period electricity from hydroelectric sources’ growth rate declined to −10.82% in 2011 from 6.56% in 2010 and declined to −9.41% in 2012. rec; electricity produced from natural gas sources and oil, gas and coal sources; electricity produced from natural gas sources all have a pro-cyclical relationship with rgdp in nigeria. however, based on the proposition of agenor et al. (2000), rec is weakly correlated; electricity produced from oil, gas and coal sources is strongly correlated; and that of natural gas sources is contemporaneously uncorrelated. the implication of this is that electricity produced from oil, gas and coal sources as an energy source is very important to the economy. in relation to phase shift, the entire macroeconomic variable leads the cycle of rgdp in nigeria with the exception of electricity produced from natural gas sources which can be seen to be lagging the cycle over the time period. the graphical illustration in figures 1 depicts the cyclical movements of the macroeconomic variables used in the study. 4. the soedsge model the soedsge model that is adapted in this study is in line with argentiero et al. (2018). the model assumes the existence of optimizing economic agents that base their current decision on their anticipation about the future. these agents seek to maximise their objective functions subject to corresponding constraints. it consists of three sectorsthe household sector, production sector comprising of four types of perfectly competitive firms, government sector. the model is also assumed to be perturbed by technological shocks, investment shocks, labour demand shocks and policy shocks. 4.1. household sector there exists a representative household that derives utility from consuming a composite good (ct). this composite good comprises of energy and a non-energy good. the individuals in the household prefer leisure to work, that is, they get dissatisfaction from their labour efforts (nt). in addition, the household earns labour income (wtnt) and capital returns (rtkt) with dividends (dvt). they also receive lump sum transfer payment from the government (tpt). the household, however, expends its income to purchase consumption goods (ptct), one-period bonds (dt+1) and capital goods (kt+1). the optimization problem of the representative household is, therefore, to maximize its intertemporal utility function subject to its budget constraint, such that: ( ) 0 ,t t t t max c n ∞ = ∑ (4.1) the utility function specified in equation (1) is a constant relative risk aversion (crra) type which can be specified as: 1 1 0 1 1 t t t t c n max      − +∞ =   − − + ∑ (4.2) subject to kt+1+ptct+et(qt,t+1dt+1)=wtnt+rtkt+(1−δ)kt+tpt+dvt (4.3) the optimality conditions of the household sector are the labour supply schedule in equation 4.4 and the inter-temporal consumption equation showing that the marginal rate of substitution equals capital equation 4.5. they are written as: table 2: cyclical behavior of rgdp and energy sources rgdp volatility nigeria (1990-2014) 5.352% ephs countercyclical contemporaneous correlation −0.297 volatility (%) 6.577 relative volatility 1.229 phase shift leading epns pro-cyclical contemporaneous correlation 0.099 volatility (%) 6.792 relative volatility 1.269 phase shift lagging epos pro-cyclical contemporaneous correlation 0.390 volatility (%) 3.586 relative volatility 0.670 phase shift leading rec pro-cyclical contemporaneous correlation 0.109 volatility (%) 1.413 relative volatility 0.264 phase shift leading source: researchers’ computation from eviews 9.0. real gdp: real gross domestic product, ephs: electricity production from hydroelectric sources, epns: electricity production from natural gas sources, epos: electricity production from oil, gas and coal sources, rec: renewable energy consumption figure 1: cyclical pattern of electricity production from hydroelectric sources, electricity production from natural gas sources, electricity production from oil, gas and coal sources, renewable energy consumption and real gross domestic product source: researchers’ computation from eviews 9.0 alege, et al.: renewable energy, shocks and the growth agenda: a dynamic stochastic general equilibrium approach international journal of energy economics and policy | vol 9 • issue 1 • 2019164 t t t t w c n p  = (4.4) ( ) 1 1 (1 )t t t t c r c     − −   = + −   (4.5) 4.2. the production sector the production sector comprises of four types of firms. there is a final good firm that uses labour ( )ytn , capital ( )1ytk − and energy inputs (et) to produce final goods (yt) based on cobb douglas production function. in addition, there are three intermediate goods firms producing energy (et), fossil fuels (fft) and renewable energy (rest). the energy producing firm combines both fossil fuels (fft) and renewable energy (rest) to manufacture its output using a constant elasticity of substitution (ces) production technology. in the fossil-fuel sector, quantities of fossil fuels are produced using labour ( )fftn , capital ( )1fftk − and energy (et) while the renewable energy firm employs labour ( )rtn es , capital ( 1)( ) r tk es− and public capital ( )1gtk − to manufacture its output. the production functions of each individual firm are defined as: final goods firm: ( ) ( ) ( )(1 )1 y y y yy y yt t t t ty a n k e    − − −= (4.6) energy firm: ( ) 1 1et te a res ff     − − − = + −  (4.7) fossil fuel firm: ( ) ( ) ( )(1 )1ff ff ff ffff ff fft t t t tff a n k e    − − −= (4.8) renewable energy firm: ( ) ( ) ( )(1 )1 1res res res resres res res gt t t t tres a n k k    − − − −= (4.9) where αi and χi are the share of labour and capital inputs in the production of final goods, fossil fuel and renewable energy goods. ait represents the total factor productivity in each of the four sectors while nit and k i t-1 are the labour and capital inputs in the individual sectors. ki(t-1) is assumed to evolve according to ( 1) ( 1)(1 ) i i i t t tk k i− −= − + . ait , n i t and i i t follow an ar(1) process such that i=y,e,ff and res. 4.3. government sector the fiscal authority is assumed to face a budget constraint where the revenue it earns from lump-sum taxation (tt), bonds (dt) and energy tax (pet) is expended on government provision of goods and services (gt), transfer payment to the household sector (tpt) and interest payment on government debt (rt-1 dt-1). the fiscal policy maker, therefore, has a nominal budget constraint defined as: tt+dt+pet=gt+tpt+rt-1dt-1 (4.10) the government also implements a fiscal rule of the form: ( ) ( 1)( ) ? g d t t td d  −= (4.11) 4.4. exogenous shock processes the model is perturbed by thirteen shock processes in technology, investment, fiscal policy and labour demand, which are expressed as: technology in final output sector: ( 1)? y y a t a t ta ya y−= + (4.12) technology in energy sector: ( 1) e e a t a t ta ea e −= + (4.13) technology in fossil fuel sector: 1 ff ff aff t aff t ta a −= + (4.14) technology in renewable energy sector: 1 res res ares t ares t ta a −= + (4.15) investment in final output sector: 1 y y iy t iy t ti i −= + (4.16) investment in fossil fuel sector: 1 ff ff iff t iff t ti i −= + (4.17) investment in renewable energy sector: 1 res res ires t ires t ti i −= + (4.18) public investment in renewable energy sector: 1 g g ig t ig t ti i −= + (4.19) labour in final output sector: 1 y y ny t ny t tn n −= + (4.20) labour in fossil fuel sector: 1 ff ff nff t nff t tn n −= + (4.21) labour in renewable energy sector: 1 res res nres t nres t tn n −= + (4.22) fiscal policy: 1 g t d t td d −= + (4.23) fossil fuel stock: 1 s t s t ts s −= + (4.24) where, ( )2~ 0, jt iiin  4.5. market clearing condition the market clearing condition for the domestic economy requires that aggregate output equals aggregate domestic demand, investment and government spending such that: y g res ff t t t t t ty c i i i i= + + + + (4.25) 5. estimation, findings and discussion 5.1. bayesian estimation of dsge model the bayesian method is used to estimate the dsge model in this study, in order to obtain numerical values of the model parameters. researchers have used other methods that varies from the calibration approach to more formal econometric methods such as generalized method of moment, impulse response function matching moments and maximum likelihood. the bayesian method, however, is the most preferred because it is a full information method that estimates the system of equations in the dsge model. it also includes the use of priors which aids in the identification of parameter. furthermore, it addresses the issue of model misspecification (grifolli, 2013). this method is summarized by bayes’ theorem which links the likelihood function, prior and posterior distribution. it shows that the posterior distribution is proportional to the product of the likelihood function and priors. the bayesian estimation involves main procedures that include: (1) specify priors based on researcher subjective belief; (2) calculate the log likelihood function using the kalman filter; 3. simulate the posterior distribution using the metropolis-hasting algorithm. 5.1.1. priors priors are the researchers’ subjective belief about the parameters of the dsge model. the parameters can be calibrated, that is fixed, based on the researchers’ intuition, existing studies and/or data. the model parameters used in this study were borrowed from existing studies and the researchers’ subjective belief based on literature. the prior mean of the inverse elasticity of substitution (σ) was fixed at 3.00 in line with cebi (2011) using the beta distribution. the share of renewable alege, et al.: renewable energy, shocks and the growth agenda: a dynamic stochastic general equilibrium approach international journal of energy economics and policy | vol 9 • issue 1 • 2019 165 energy in the output of the energy sector (η) was fixed at 0.12 based on argentiero et al. (2018), following a beta distribution. the fixed value of this parameter depicts that the small portion of renewable energy technology that has been adopted in nigeria. the calibrated values of the share of labor (αres) and capital χres in the renewable energy sector are 0.20 and 0.50. this assumes that the renewable energy sector is capital intensive. in the same vein, the share of labor and capital in the output of the fossil fuel sector is fixed at 0.15 and 0.50, based on the researchers’ subjective belief that the oil-sector in nigeria employs a small fraction of labor. the persistence parameters on technology, investment and labor in the renewable energy and fossil fuel sector are fixed at 0.8 based on the assumption that the persistence parameters are highly persistent. finally, the shock parameters are fixed are at 0.01 with an inverse gamma distribution. the prior mean and distribution are listed in table 3. 5.1.2. posterior estimates table 3 shows the posterior estimate of individual parameters of the dsge model. the posterior estimate of the share of renewable sources in the production of the energy sector stands at 0.11 which is lower than its prior mean of 0.12. this implies that the proportion of renewable energy used is smaller at 11% compared to the proportion of non-renewable sources at 89 per cent. this is evident in the greater reliance of nigerian households and businesses on petrol and diesel than on solar and other renewable energy sources. the share of labour and capital used in the production of renewable energy is estimated at 0.19 and 0.18. this shows that the renewable energy sector is labourintensive contrary to the researchers’ subjective belief. the estimated values of the share of labour and capital in the fossil fuel sector are 0.36 and 0.64. this depicts the fossil-fuel sector to be capital intensive. furthermore, the posterior mean of the persistence parameters in technology, investment and labour across the renewable and fossil fuel sectors are higher than their prior mean except in the case of investment in the fossil fuel sector. this implies that the nigerian economy adjusts slowly to shocks from these sources. the posterior mean of the shock parameters indicates the extent of volatility of the individual exogenous process. the posterior estimates of the shock processes show that the shock to technology and investment in the renewable energy sector are the most volatile source of fluctuation. it can also be deduced that renewable energy shocks are more volatile than shocks to the fossil fuel sectors. this means that shocks to the renewable energy sector has more macroeconomic impact than those of fossil fuel sector. 5.2. model dynamics the impulse response function is used to analyze the importance and impact of shocks to fossil fuels and renewable energy on the macro economy. the impulse response functions are obtained by solving the log-linearized dsge model using a first order taylor approximation around the steady state. 5.2.1. impulse response to shocks in fossil fuel sector based on the impulse response graphs in figures 2-4, an unexpected positive change to the existing technology in the fossil fuel sector has a positive ripple effect on the nigerian economy. a shock to technology of fossil fuel increases the stock of technology. this has positive impact on both the fossil fuel production and combined energy output. household consumption expenditure rises in response to this shock, which is a component of aggregate demand that invariably pushes the level of final output upwards. a positive shock to investment made in the fossil fuel sector raises the amount of investment, increases the capital stock and output produced in this sector. it also impacts positively on the gross domestic product. however, the unexpected increase in investment, initially, negatively affects the level of household demand before it rebounds by the seventh quarter. this may be as a result of the waiting period before returns is earned on investment. in the same vein, a positive shock to labor inputs in the fossil fuel sector also generates positive ripple effect on the fossil fuel sector and on the macroeconomic variables. 5.2.2. impulse response to shocks in renewable energy sector the impulse response graphs presented in figures 5-7 show that a positive shock to technology available in the renewable energy sector leads to a rise in the stock of technology and the amount table 3: estimated parameters parameter prior distribution prior mean posterior mean symbol description sigmma (σ) inverse elasticity of substitution normal 3.00 2.98 alphha_ff (αff) elasticity of labour in fossil fuel beta 0.15 0.36 cchi_ff (χff) elasticity of capital in fossil fuel beta 0.50 0.64 alphha_res (αres) elasticity of labour in renewable energy beta 0.20 0.19 cchi_res (χres) elasticity of capital in renewable energy beta 0.50 0.18 etta (η) share of renewable energy beta 0.12 0.11 rrho_ares (ρares) ar (1) process in technology of renewable energy beta 0.80 0.94 rrho_aff (ρaff) ar (1) process in technology of fossil fuel beta 0.80 0.85 rrho_ires (ρires) ar (1) process in investment of renewable energy beta 0.80 0.90 rrho_iff (ρiff) ar (1) process in investment of fossil fuel beta 0.80 0.78 rrho_nres (ρnres) ar (1) process in labour of renewable energy beta 0.80 0.8004 rrho_nff (ρnff) ar (1) process in labour of fossil fuel beta 0.80 0.82 eps_ares technology shock in renewable energy sector inverse gamma 0.010 0.020 eps_aff technology shock in fossil fuel sector inverse gamma 0.010 0.005 eps_ires investment shock in renewable energy sector inverse gamma 0.010 0.014 eps_iff investment shock in fossil fuel sector inverse gamma 0.010 0.005 eps_nres labour shock in renewable energy sector inverse gamma 0.010 0.008 eps_nff labour shock in fossil fuel sector inverse gamma 0.010 0.007 sources: cebi (2011), argentiero et al. (2018) alege, et al.: renewable energy, shocks and the growth agenda: a dynamic stochastic general equilibrium approach international journal of energy economics and policy | vol 9 • issue 1 • 2019166 of renewable energy output. this has a positive externality on the level of consumption expenditure, as a result of the income effect. final output, that is, the gross domestic product responds positively to this shock. an unexpected increase in the investment made in the renewable energy sector grows the available capital stock. this pushes up the production of this alternative energy. however, household consumption responds negatively to this shock, even into the horizon. this contrasts with the initial negative response of consumption to investment that is observed in the fossil fuel sector. this means that individuals who invest in the renewable energy sector may have to wait a longer time before they recoup their investment. furthermore, a positive shock to labour inputs in the renewable sector has a positive multiplier effect on the renewable energy sector and on relevant macroeconomic variables such as consumption. figure 2: impulse response to technology shock in fossil fuel sector figure 3: impulse response to investment shock in fossil fuel sector figure 4: impulse response to labor shock in fossil fuel sector figure 5: impulse response to technology shock in renewable sector figure 6: impulse response to investment shock in renewable sector figure 7: impulse response to labor shock in renewable sector alege, et al.: renewable energy, shocks and the growth agenda: a dynamic stochastic general equilibrium approach international journal of energy economics and policy | vol 9 • issue 1 • 2019 167 6. conclusion this study was conducted in order to document some business cycle stylized facts for the nigerian economy in relation to energy sources; and secondly, to examine the economy-wide effect of the renewable energy sector on the nigerian economy and also gauge the importance of financial investment, technology and manpower in promoting alternative energy sources in nigeria. through the use of the hp filter and the procedure of agenor et al. (2000), the study finds out that electricity produced from hydroelectric and natural gas sources are subject to high volatility. in terms of the degree of contemporaneous correlation, electricity produced from oil, gas and coal sources is pro-cyclical and strongly correlated to the cycle of output in nigeria. this finding is not surprising given that the major source of foreign exchange earnings in the nigerian economy is from crude oil. alege et al. (2017) results relating to industrial sector corroborates this finding. in terms of renewable energy sources, electricity produced from hydroelectric sources has a countercyclical relationship with output reflecting the low use of hydro-powered energy in the economy. rec is pro-cyclical and weakly correlated to output. this indicates that there is the need for government to focus on promoting renewable energy sources. the result from the bayesian estimation of the dsge model shows that the renewable energy sector in nigeria is a labor-intensive one, while the fossil fuel sector was found to be capital-intensive. this shows that the alternative energy sector needs more labor relative to capital in its production. the alternative energy sector unlike the fossil fuel sector, therefore, has the potential to generate more employment for the teeming nigerian population. the study also found that shocks to the renewable energy sector have more impact of the nigerian economy compared to shocks to the fossil fuel sector. in specific terms, the result of the study showed that technology and investment shocks in the renewable energy sector is the most significant source of fluctuation relative to investment and labor shocks. this means that the adoption of technology and financial investment are critical to developing the renewable energy sector in nigeria. the results from the impulse response analysis showed that shocks to alternative energy have a positive ripple effect on the nigerian economy. however, household consumption responds negatively to investment shock in the renewable sector. this means that households which invest in renewable energy must give up their consumption when they invest in this sector. the results confirm that the nigerian government’s commitment to renewable energy holds positive potential for economic development. this study recommends the creation of an enabling environment for the initiation and adoption of renewable technology. furthermore, government should provide financial incentive to boost investment in this sector and to address necessary investment gaps such as shortage of investment capital and high interest rates for renewable energy. references acemoglu, d., aghion, p., bursztyn, l., hemous, d. (2012), the environment and directed technical change. american economic review, 102, 131-166. adenikinju, a.f. (1995), energy-pricing policy and the environment in an oil-exporting, developing country. opec energy review, 19, 307-332. agenor, p.r., mcdermott, j.c., prasad, e.s. (2000), macroeconomic fluctuations in developing countries: some stylised facts. the world bank economic review, 14, 251-285. akinyemi, o., alege, p., ajayi, o., okodua, h. (2017), energy pricing policy and environmental quality in nigeria: a dynamic computable general equilibrium approach. international journal of energy economics and policy, 7(1), 268-276. alege, p., oye, q.e., adu, o., amu, b., owolabi, t. (2017), carbon emissions and the business cycle in nigeria. international journal of energy economics and policy, 7(5), 1-8. alege, p.o. (2008), macroeconomic policies and business cycles in nigeria. an unpublished phd thesis. department of economics, covenant university, ota. annicchiarico, b., dio, f.d. (2015), environmental policy and macroeconomic dynamics in a new keynesian model. journal of environmental economics and management, 69, 1-21. argentiero, a., atalla, t., bigerna, s., micheli, s., polinori, p. (2017), comparing renewable energy policies in e.u.15, u.s. and china: a bayesian dsge model. the energy journal, 38, 77-96. argentiero, a., bollino, c.a., micheli, s. (2014), sustainable energy policy and strategies for europe. sustainable growth with renewable and fossil fuels energy sources: a dsge approach. rome: international association for energy economics. p. 1-18. argentiero, a., bollino, c.a., micheli, s., zopounidis, c. (2018), renewable energy sources policies in a bayesian dsge model. renewable energy, 120, 60-68. dogan, e. (2016), analyzing the linkage between renewable and nonrenewable energy consumption and economic growth by considering structural break in time-series data. renewable energy, 99, 1126-1136. dogan, e., seker, f. (2016), determinants of co2 emissions in the european union: the role of renewable and non-renewable energy. renewable energy, 94, 429-439. fischer, c., springborn, m. (2011), emissions targets and the real business cycle: intensity targets versus caps or taxes. journal of environmental economics and management, 62, 352-366. griffoli, t.m. (2013). dynare user guide: an introduction to the solution & estimation of dsge models. available from: http:// www.dynare.org/documentation-and-support/user-guide/dynareuserguide-webbeta.pdf. heutel, g. (2012), how should environmental policy respond to business cycles? optimal policy under persistent productivity shocks. review of economic dynamics, 15, 244-264. kim, s.h., kose, a.m., plummer, m.g. (2003), dynamics of business cycles in asia: differences and similarities. review of development economics, 7, 462-477. national renewable energy and energy efficiency policy (nreeep). (2015), national renewable energy and energy efficiency policy. abuja: ministry of power federal republic of nigeria. ogundipe, a.a., akinyemi, o., ogundipe, o.m. (2016), electricity consumption and economic development in nigeria. international journal of energy economics and policy, 6(1), 134-143. ponta, l., raberto, m., teglio, a., cincotti, s. (2018), an agent-based stock-flow consistent model of the sustainable transition in the energy sector. ecological economics, 145, 274-300. rafindadi, a.a., ozturk, i. (2017), impacts of renewable energy consumption on the german economic growth: evidence from combined cointegration test. renewable and sustainable energy reviews, 75, 1130-1141. tugcu, c.t., tiwari, a.k. (2016), does renewable and/or non-renewable energy consumption matter for total factor productivity (tfp) growth? evidence from the brics. renewable and sustainable energy reviews, 65, 610-616. . international journal of energy economics and policy | vol 7 • issue 4 • 2017 107 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(4), 107-114. measuring regional inequalities by amenity productivity approach for sustainable economic and environmental policies in european union dimitrious giannias1, yuri chepurko2*, alessandro figus3, nguyễn hoàng hiển4 1university of crete, greece, 2department of economics, kuban state university, russia, 3department of international relations, università degli studi link campus university, italy, 4division of economic principles, national academy of public administration, vietnam. *email: chepurko@yandex.ru abstract this paper classifies the european union (eu) member countries on an amenity-productivity map based on environmental quality and income differentials. this classification is useful because it provide information about the relative attractiveness to consumer and producers of the total bundle of such attributes indigenous to each region environmental and other. it also assists european policy makers to formulate the best suited regional and environmental policies in the eu. our findings suggest that notion of sustainable development is best suited for low productivity countries such as greece, portugal, spain, ireland, and italy. keywords: environmental quality and income inequalities, environmental policy, isocost, isoutility, regional policy, amenities, productivity jel classifications: q5, q50, r11, r58, q56 1. introduction the european union (eu) has a core containing a high concentration of economic development, modern infrastructure, and advanced social indicators as the “golden triangle.” all the attributes of post-industrial life are concentrated in the core. the periphery contains the regions traditionally designed as underdeveloped, which have been outside the main strands of european development. regions in the periphery remain locked in the rural life styles of another age. it is also recognized that some regions are chronically poor not because of their location, but because of economic factors. such regions had depended on one major economic activity, such as steel making or textiles. when the economic viability of the activity declined, the region lacked the resources necessary to diversify and fell into chronic recession. by this paper, we do attempt to challenge the neo-classical view by offering an alternative explanation; in the presence of free mobility, consumer income differentials can persist because some factors are inherently immobile, e.g., the environmental and climatic characteristics that are unique to a region. it is possible that several regions share the same site-specific characteristics, but it is unlikely that their distribution will be exactly the same. economic agents would be willing to pay or accept different level of incomes depending on the value they place on these characteristics. for example, a transportation company may find that its location in a region with good airport(s), port(s), and intraand intercity transport system saves time and reduces its production costs. this implies that this particular firm can offer relatively higher incomes to its employees and still remain competitive with other transportation companies located in lower-income regions since the characteristics of the transport system of the region is offering it a cost advantage. since office space and other facilities in the area are limited, the companies attracted by the transport system of the region will increase the demand for both labor and office space. these increases in the prices of labor and office space will continue until in equilibrium they have completely offset the cost advantage of the transport system of the region. the purpose of this paper is to identify eu countries according to the extend they are dominated by supply and demand responses to their net bundle of country-specific attributes. the countries are then giannias, et al.: measuring regional inequalities by amenity productivity approach for sustainable economic and environmental policies in eu international journal of energy economics and policy | vol 7 • issue 4 • 2017108 classified into four groups based on the relative values of a country’s per capita income and environmental quality (eq). these are then identified as high amenity (low consumer income, high eq), low amenity (high consumer income, low eq), high productivity (high consumer income, high eq), and low productivity (low consumer income, low eq). the usefulness of this classification is two-fold: first, it provides information about the relative attractiveness to consumers and companies of the total bundle of environmental and other attributes indigenous to each country of the eu. second, it assists european policy makers to formulate the best suited regional and environmental policies in the eu. high amenity countries or regions, for example, require regional policy measures so as to increase their income. similarly, low amenity countries or regions require environmental policy measures so as to increase their quality of life. finally, in low productivity and low amenity areas both policies, regional and environmental, are important for increasing the consumer’s income and his/her eq of life. this paper reviews regional and environmental policies of the eu, providing a theoretical framework to determine the importance of amenity and productivity differences as sources of income and eq inequalities across countries in the eu. regional and environment policies represent two of the most important policies of the eu. unlike regional policy, environmental policy is a more recent policy of the eu. when the treaty of rome was written in 195657, its authors saw no need to provide a common policy on the environment because they did not perceive any common threat. it was not until october 1972 that a conference of heads of state or government insisted that a common policy was needed, and since then more than 200 items of union legislation on the environment have been enacted. these are the products of action programmes which the council of ministers has been endorsing since 1973. in 1975 the european community established the european regional development fund (erdf). the erdf is one of the key structural funds. its commitments for 1996 were more than ecu 11.8 billion. although the erdf was created in 1975, in the wake of the accession of britain, ireland and denmark, it is the development of the single market which has been the catalyst for strengthening union solidarity with poorer regions at risk of being left further behind. that is why the single european act of 1986 introduced a new title v into the treaty of rome called “economic and social cohesion.” when the maastricht treaty on eu laid the basis for establishing an economic and monetary union (emu) by 1999 (at the latest), it was also decided to address the risk that emu could worsen regional inequalities. the treaty’s requirement that budget deficits be limited to a maximum of 3% of gross domestic product (gdp) also limits the possibilities of poorer states increasing investments to catch up with their richer partners. in response, therefore, the treaty established a new cohesion fund to channel financial assistance to the four poorest states with a per capita gdp of <90% of the union’s average. eligible projects have to be in the fields of the environment and trans-european networks. 2. literature review various studies have investigated the existence of consumer income inequalities among regions or countries. the irrefusable conclusion is that they exist and persist for long periods of time (bellante, 1979; johnson, 1983). researchers dealing with regional policy in the eu generally assume that income inequalities are caused by geographical and economic variables (eberts and stone, 1986). the concepts of core and periphery have been the most influential geographical explanation of eu regional inequalities. the idea is that regions distant from the core of activity in a country fail to develop equally with areas closer to the core. ott (1978) considered that within a framework in which regions and factors are identical and all economic agents are free to move, neoclassical analysis supports the view that the output (and income) of different regions should tend to converge over time towards a steady state. this view, however, has been challenged by a number of new growth models (solow, 1970). these new growth models assume non-convexity in production or externality arising from the accumulation of human capital. in these models, regional outputs per head can actually diverge (van der ploeg and tang, 1980). from a growth-oriented view, environmental protection measures are perceived as constraints to economic development. growth is also seen by environmentalists as creating adverse ecological consequences that originate from expansions of industrial activity (booth 1998). researchers point out that in the long run, the economic potential of future production factors will increasingly depend on the state of environmental conditions (daly 1991 and hope 1991). pearce, d et al. (1991) found that this can be clearly depicted by effects that accumulated pollution levels are known to have on human health and land productivity. similarly, for their own reasons consumers put their own value on a region. consumers consider the overall eq of a region when they make a decision concerning the place they will live in; where the eq is defined to include all aspects of their environment (natural and non-natural) (romer 1998 and tietenberg 1994). consumers are assumed to consider the distribution of the characteristics of the natural environment and of all regional amenities, including cultural, public services, transport, and other opportunities. the region, for example, with the good transport system that offered a cost advantage to some firms may be attractive to consumers because of reduced travel time to work (hope and parker 1995. consequently, as more consumers move into the area, the supply of labor increases as well as the demand for housing. thus rents increase and wages fall until individuals are in equilibrium no longer willing to accept moving to a region with a better transport system and a better overall eq as compensation for lower wages and higher rents (galbraith 1958). the final income differentials between a geographical area with a good transport system and one without depends upon the relative size of the demand and supply responses to site characteristics. if incomes are observed to be higher in the good transport system area than in the other, then the firm’s response dominates the rent determination process (krugman and venesables 1990). if incomes are relatively lower in the good transport system area, then the consumer’s response dominates the process. in both cases rents will be higher because both households and firms value a good transport system. rents would be lower than in otherwise comparable geographical areas if the regional transport system was not important to both parties. incomes and rents will vary across giannias, et al.: measuring regional inequalities by amenity productivity approach for sustainable economic and environmental policies in eu international journal of energy economics and policy | vol 7 • issue 4 • 2017 109 regions according to the value companies place on the regionspecific attributes in each region and their ability to substitute between factors of production (world resources, 1992-93). consequently, by observing relative consumer incomes and rents, or by observing other variables having a monotonic relationship with them, it is possible to identify whether a region’s bundle of environmental and other characteristics has a greater net effect on company location decisions or consumer location decisions (world bank 1992). due to these interrelationships, development and environment should be brought together into the same conceptual framework from which mutual beneficial objectives may be achieved. sustainable development is the notion which entails this conceptual framework. sustainability is defined as maintaining continuity of economic and social developments while respecting the environment and without jeopardizing future use of natural resources (thomas and belt 1997). gould et al. (1988) declares that the ideas and theories of sustainable development have been examined and discussed by a number of important commission policy documents. regional policy aims at reducing variations in the economic performance of the different member states. in accordance with human development report (1993) the preamble of the treaty of rome calls for a reduction “of the differences existing between the various regions and the backwardness of the less favored regions,” while article 2 refers to the goal of harmonious development of economic activities, a continuous and balanced expansion. sustainable development was made the centerpiece of the eu’s fifth environmental action programme in alignment with the commitments made at the 1992 unced at rio. in the last chapter of the gce white paper (cl 1993) the basis for a new development model was explored which focused on the objectives of sustainability. integrating environmental policy into regional policy field is essential if sustainable development is to succeed. in recognition of the more holistic approach that this intimates, article 139-r of the maastricht treaty states the need for all areas of eu policy to make environmental objectives an integral part of any future strategies. finally, in a recent paper it is argued that environmental protection is easier to achieve with economic growth than without it (hope and parker, 1990). in more details, the paper showed that since 1970 oecd europe’s growth rate had risen by 80% and lead emissions had fallen by 50%. on the empirical basis, mishan (1967), nordhaus and tobin (1972), easterlin (1973) and king (1974) attempted to provide measures of the reduction in economic welfare due to the negative effects of economic development on environment. walters (1975) has supplied improved measures of these diseconomies and griffin (1974) and baumol and oates (1971) have attempted to devise relevant methods of control and to estimate their costs. list and kunce (2000) found that state environmental regulations adversely affect job growth in three of the four industries analyzed. forrester (1971) and meadows et al. (1972) argued that the finite nature of world resources limits the growth of gross world product and suggest policies aimed at achieving zero growth rate. grossman and krueger (1995) found no evidence that eq deteriorates steadily with economic growth. their study revealed that environmental degradation and income have an inverted u-shaped relationship (sometimes called kuznets curve), with pollution increasing with income at low levels of income and decreasing with income at high levels of income. shafik (1994) also found that most societies choose to adopt policies and to make investments that reduce environmental damage associated with growth. action tends to be taken where there are generalized local costs and substantial private and social benefits. ekins (1997) on the other hand supports that the evidence for a kuznts curve is inconclusive, and cannot be generalized across eq as a whole. finally, hart (2002) and glover (1999) support neither the “optimist” (i.e., that increased scarcity of environmental goods will induce adequate conservation responses) nor the “pessimist” view (that these responses will be insufficient without measures to scale of the global economy). hart (2002) uses a schumpeterian growth model and cultural theory to interpret these competing positions within a single unifying framework. glover (1999) looks at the causes of environmental degradation, examines the policy approaches implicit in both camps and suggests an approach that draws elements from both. 3. data and estimation techniques 3.1. theoretical framework for evaluating economic and environmental situation in this section a theoretical framework is presented and then used to determine the relative importance of amenity and productivity differences as sources of income differentials across countries in the eu. this framework assumes that regions or countries are fully described by a bundle of environmental and other attributes. these specify the eq index of a country or region, eq, which includes all aspects of natural and non-natural environment of a consumer’s life. eq affects the utility of consumers, u(.), and the production (where the production technologies are assumed to exhibit constant returns to scale) cost of firms, c(.). our framework is illustrated in figure 1. the downward sloping curves in figure 1, labeled v(r), show combinations of income (the income of a consumer is assumed to be determined by a hedonic wage equation which depends among others (e.g., personal characteristics, education, figure 1: correlations between environmental quality and income giannias, et al.: measuring regional inequalities by amenity productivity approach for sustainable economic and environmental policies in eu international journal of energy economics and policy | vol 7 • issue 4 • 2017110 experience, etc.) on eq.), i, and eq, eq, for which utility is equal to v, where v is the maximum utility that a consumer can enjoy at all sites within a country in equilibrium, so that there is no incentive for any relocation, and r is a vector of implicit prices of housing characteristics (for example. r = (r), r2, r3) is the vector of implicit prices for the vector of housing characteristics h = (h1, h2, h3), so that the rental price p, of a house that is described by the vector of characteristics (h1, h2, h3) is p = r h’ where h’ is the transpose of h. the slope of these curves is the trade-off that households are willing to make between wage income and eq for any given level of implicit prices for housing characteristics (r) and the given utility level v. along each curve, the implicit prices of housing characteristics is fixed and the curves shift up (down) as the implicit prices of the housing characteristics increase (decrease). combinations of eq and i for which the unit costs of firms are equal are also depicted in figure 1 and given by the curves c(r). the value of the environmental characteristics of a region to firms is fixed along each iso-cost curve, c(r), and the curves shift up (down) as the environmental characteristics of a region increase (decrease) the productivity of firms and the implicit prices, r, of the real estate market. each region is characterized by an eq index and a vector of implicit rental prices that are associated with a specific pair of iso-cost and iso-utility curves as in figure 1. the intersection of any two curves for each region at the level of its eq then determines the relative income and the implicit prices of the real estate market in equilibrium. in figure 1, in region 1, where eq equals eq1, the equilibrium income will be i1 and the equilibrium implicit rental prices r1. using region 1 as a reference point, which could be thought as the average region, we can see in the following how interregional inequalities in eq will be reflected in inequalities in incomes and implicit rental prices. from the above analysis, it can be seen that: (i) when eq is valued more by consumers, ceteris paribus, с(r2) and v(r2) have both been moved up and c(r2) has moved up relatively more, and (ii) when eq is valued more by firms, ceteris paribus, c(r3) and v(r3) have both moved up and v(r3) has moved up relatively more. within this simple framework in which regions differ only in their eq, we can determine whether eq and income inequalities reflect interregional inequalities in amenities or productivity by examining the patterns of eq and incomes across regions. if eq and income inequalities primarily reflect amenity differences across regions, we would see a negative relationship between eq and incomes. if they reflect productivity differences, the relationship would be positive. within the same framework, we can also classify individual regions on the basis of whether their incomes and eq differ from the average because of above average amenities, below average amenities, above average productivity, or below average productivity. these classifications are summarized in table 1 and figure 2. eq is higher than the average in the high amenity and high productivity regions, and lower than the average in the low amenity and low productivity ones. on the other hand, incomes are relatively higher in the high productivity and low amenity regions. using the computational approach employed to obtain the above eq indices, eq, we can compute another eq index for each country, eq’, that includes only aspects of the natural environment, that is, only the scaled values of the variables y1,j,., y19,j. the eq’ values are given in table 2. table 2 also gives eq* for each country, where eq* = [(eq’/eq)−l]. for countries for which eq* > 0, its position on the amenity-productivity mapping is based more on the y1j., y19,j values, that is, on the characteristics of the natural environment of the country, than on the other aspects of its environment. these are austria, finland, france, germany, ireland, portugal, and sweden. rankings of the countries might be based on the eq, eq’, and per capita income relations. the eq and eq’ rankings are different and the req-req’ differences are significant for countries like portugal, denmark, and ireland, where ri is a ranking based on i, i = eq, eq’, i. in case of such ranking we can obtain the sum of the absolute values of the differences: σ1 = 30, σ2 = 36, σ3= 54, where σ1 is the sum of the absolute values of the req – req’ differences and σ2 is the sum of the absolute values of the req – ri differences, and σ3 is the sum of the absolute values of the req’ ri differences. table 1: classification of the eu countries in respect to the eq and r (eq) country eq r(eq) austria 55.51845 5 belgium 50.09458 9 denmark 55.60092 4 finland 61.62236 2 france 51.1665 8 germany 60.9489 3 greece 42.94626 15 ireland 49.98765 10 italy 47.98761 11 luxemburg 44.90285 14 netherland 54.02812 6 portugal 45.84456 13 spain 46.75081 12 sweden 74.47721 1 uk 53.6395 7 eu: european union figure 2: amenity-productivity classification giannias, et al.: measuring regional inequalities by amenity productivity approach for sustainable economic and environmental policies in eu international journal of energy economics and policy | vol 7 • issue 4 • 2017 111 these imply that overall the differences among the eq’ and per capital income rankings are greater than the others since σ1 > σ2 and σ3 > σ1. the ranking is shown in table 3. each region is characterized by an eq index, eq, whose effect on household utility and production costs differs from region to region. the problem of classifying regions by the relative magnitude of these two effects becomes one of identifying the eq and income inequalities in equilibrium relative to the shifts in each curve. this can be done by identifying the combinations of eq and i in equilibrium that are associated with equal shifts of both curves and determining how incomes and eq change relative to these shifts. the (eq,i) equilibrium combinations associated with equal shifts of both curves would coincide with the e q1o and i1o’ lines in figure 1, where eq1 is the mean eq and h is the mean income. from the figure 1, it can be seen that: (i) when eq is valued more by consumers, ceteris paribus, с(r2) and v(r2) have both been moved up and c(r2) has moved up relatively more, and (ii) when eq is valued more by firms, ceteris paribus, c(r3) and v(r3) have both moved up and v(r3) has moved up relatively more. for any region with above average incomes and eq, the shift of the c(r) (productivity) curve must be less than the shift of the v(r) (amenity curve). the less the direct effect of eq on utility, the greater the increase in consumer income needed to offset the increase in rents and, consequently, the greater the shift of the v(r) curve needed to keep the maximum utility level unchanged and equal to v in equilibrium. therefore, any region with eq and income combinations in quadrant a in figure 2 is classified as “high productivity” region, because the primary reason that this region’s incomes, eq, and rents differ from those of the average region is the above-average productivity effects of eq. this above-average productivity effect is reflected in the ability of producers in these regions to pay above average incomes and rents for having at their disposal a greater than the average eq. above average amenity effects of a region are associated with increases in rents and decreases in incomes reflecting consumers’ willingness to pay relatively more for the effects of the regional characteristics embodied in the region’s eq. quadrant d then identifies regions where the eq is greater then the average and the dominant factor determining relative incomes and rents is the high amenity effect. for regions in quadrant b, the dominant factor is their below-average amenity value. similarly regions with below average incomes and eq (quadrant с in figure 2) are classified as “low productivity” regions, since firms in these regions are compensated for the below average eq effect on productivity with below-average rental prices and income. above average amenity effects of a region are associated with increases in rents and decreases in incomes reflecting consumers’ willingness to pay relatively more for the effects of the regional characteristics embodied in the region’s eq. 3.2. data the countries studied in this paper are united kingdom, sweden, finland, germany, denmark, austria, and netherlands are highproductivity, belgium, france, luxemburg italy, ireland, spain, portugal, greece. regions (countries) were selected based on data availability. the implications of the above theoretical analysis can be used for a classification of the countries within eu. to compute the eq, eq, for each country, the following variables of the natural and non-natural environment of a country were available and considered: y1,j: emissions of traditional air pollutants in kg per 1000 people, y2,j: annual internal renewable water resources per capita, y3,j: wilderness area as a % of total land area, y4,j: % of national land area protected for wildlife and habitat, y5,j: number of threatened mammals per 10,000 km 2, y6,j: number of threatened birds per 10,000 km 2, y7,j: number of threatened reptiles per 10,000 km 2, y8,j: number of threatened amphibians per 10,000 km 2, y9,j: endemic flora as a % of total, y10,j: number of botanical gardens, y11,j: forest area as a % of land area, y12,j: average annual reforestation, y13,j: municipal waste generation per capita, table 2: ranking of the eu countries country percentage of country eligible for funding ranking based on [1] sum of qol and [1] based ranking austria 40.,6 10 15 belgium 31.3 12 21 denmark 15.8 15 19 finland 53.6 6 8 france 47.6 7 15 germany 39.1 11 14 greece 100 1 16 ireland 100 1 11 italy 55.8 5 16 luxemburg 42 8 22 netherland 24.15 14 20 portugal 100 1 14 spain 82.9 4 16 sweden 24.6 13 14 uk 41.9 9 16 eu: european union table 3: ranking of the countries based on per capita income and eq index country i* eq luxembourg 100 45.7 denmark 68.18 58.2 sweden 51.62 78.1 austria 45.45 55.2 finland 45.13 65.6 germany 45.13 61.2 netherlands 44.48 51.3 belgium 43.18 48.5 uk 42.86 53 france 40.91 55.1 ireland 37.01 50.1 italy 29.09 53.1 spain 12.34 48.4 greece 2.27 43.2 portugal 0 46.8 eq: environmental quality giannias, et al.: measuring regional inequalities by amenity productivity approach for sustainable economic and environmental policies in eu international journal of energy economics and policy | vol 7 • issue 4 • 2017112 y14,j: industrial waste per unit of gdp (tons per million us$), y15,j: hazardous and special waste generation (metric tons per km2), y16,j: waste paper recycled as % of paper consumption, y17,j: average annual fertilizer use (kg/ha of cropland), y18,j: average annual pesticide use (metric tons of active ingredient), y19,j: per capita carbon dioxide emissions, y20,j: daily travel time to and from work, y21,j: urban population as a % of total, y22,j: population density (per 1000 ha), y23,j: life expectancy at birth (years), y24,j: adult literacy rate, y25,j: mean years of schooling (25+), y26,j: population per doctor, y27,j: maternal mortality rate, y28,j: daily newspaper circulation per 1000 people, y29,j: television per 1000 people, y30,j: telephones per 1000 people, y31,j: passenger cars per 1000 people, y32,j: deaths from road accidents per 100,000 people, y33,j: suicides per 100,000 people, 3.3. computation of indices and identification of environmental and economic policies priorities for the eu an eq index that takes into consideration all aspects of the natural and non-natural environment of a consumer’s life could be taken to be equal to the mean of these variables. however, a mean cannot be computed directly, because of differences in the units of measurement of the above variables. therefore, these variables need to be scaled before a mean is computed. to be more specific, the above variables for each country are scaled from 0 to 100 using the following transformations: yij * = 100 (yij − yijmin)/(yijmax − yijmin) (1) where, у $ is the transformed variable, yijmin is the minimum value of yij, and yijmax is the maximum value, for i 2, 3, 4, 10, 11, 12, 16, 22, 23, 25, 28, 29, 30, 31, that is, for all variables having a positive relationship with eq, and all j, an: yij * = [100 (yij − yijmm)/(yiimas − yljmin)] (2) where, yij is the transformed variable, yijmin is the minimum value of yij in the sample of countries and yijmax is the maximum value, i = 1, 5, 6, 7,8,9, 13, 14, 15, 17, 18, 19,20,21,24,26,27, 32, 33, that is, for all variables having a negative relationship with eq, and all j. finally, to compute the eq for each country we have (i) used data from the world resources 1992-1993 and the human development 1993, the world commission on environment and development (wced) 1987 and (ii) taken the mean of the scaled variables уij *. the per capita income, i, of each country is also scaled from 0 to 100 using the following transformation: ij * = 100 (ij − imin)/(imax − imin) (3) where, ij * is the transformed index, imin is the minimum index value in the sample of countries and imax is the maximum value, and j 1, 2, 3., m. the eq and per capita income combinations, (eq,i*), for austria, belgium, denmark, finland, france, germany, greece, ireland, italy, louxembourg, netherlands, portugal, spain, sweden, and united kingdom are given in table 4 (missing values for a yij variable have been replaced by the mean of the existing ones). these missing values were for luxembourg: y1 y11 y12, y14, y16, y17, y18, y30. denmark: y12. greece: y15, y17, germany: y32. belgium: y33, ireland: y1, y16. table 4 and the results of our theoretical analysis imply the positioning mapping of figure 3, where m (eq) and m(i*) are the means of eq and i*, respectively. this identifies four group of countries, namely, the highproductivity ones: sweden, finland, germany, denmark, austria, and netherlands, the low-productivity ones: italy, ireland, spain, portugal, and greece, the low-amenity ones: france, belgium, and louxembourg, and united kingdom which is the only country being characterized as high-amenity. table 4: ranking of the eu countries for the funding purposes country eu regional development funding [1] population [2] [1]/[2] ranking based on [1]/[2] sum of qol and [1]/[2] based ranking austria 1574 7.7 204.42 12 17 belgium 2096 10 209.60 11 20 denmark 843 5.1 165.29 14 18 finland 1652 5 330.40 6 8 france 14,938 57 262.07 8 16 germany 21,724 79.9 271.89 7 10 greece 15,131 10.2 1483.43 3 18 ireland 6103 3.5 1743.71 1 11 italy 21,646 57.7 375.15 5 16 luxemburg 104 0.4 260.00 9 23 netherland 2615 15 174.33 13 19 portugal 15,038 9.9 1518.99 2 15 spain 34,443 39 883.15 4 16 sweden 1377 8.6 160.12 15 16 uk 13,155 57.6 228.39 10 17 qol: quality of life, eu: european union giannias, et al.: measuring regional inequalities by amenity productivity approach for sustainable economic and environmental policies in eu international journal of energy economics and policy | vol 7 • issue 4 • 2017 113 4. concluding remarks our findings suggest that the notion of sustainable development is best suited in the low productivity group of countries. as mentioned before, this group includes greece, portugal, spain, ireland and italy. sustainable development brings together amenity and productivity into the same conceptual framework from which mutually beneficial objectives may be achieved. in the low amenity group, which includes france, belgium and luxembourg, emphasis should be given to environmental measures, since this group is characterized by its high income and low eq. finally, in the case of the uk, emphasis should be given to regional policy, since the country is characterized by low income and high eq. this paper identified eu countries according to the extend they are dominated by supply and demand responses to their net bundle of country-specific attributes. this kind of classification is useful because it provides information about the relative attractiveness to consumers and producers of the total bundle of environmental and other attributes indigenous to each region. a theoretical framework is used to position the european union member countries on an amenity-productivity map. the analysis shows that united kingdom is the only country that can be characterized as high-amenity. among the rest, sweden, finland, germany, denmark, austria, and netherlands are high-productivity, belgium, france and luxemburg are low-amenity and all the rest (italy, ireland, spain, portugal, greece) are low-productivity. a ranking of the european union countries based on the eq (incorporating either all aspects of the environment or only those relevant to the natural environment) show that greece and luxembourg are at the bottom of the ranking and sweden, and finland on the top. our findings suggest that the notion of sustainable development is best suited for productivity group of countries. as mentioned before, this group includes greece, portugal, spain, ireland and italy. sustainable development maintains continuity of economic and social developments while respecting the environment without jeopardizing future use of natural resources. the eu development funding was taken keeping into consideration total 1994-1999 eu funding allocated to member states for regional development; millions of ecu. population is assumed to be millions of people. in this paper we offered a method for evaluating the economic and environmental situation in the eu. a theoretical framework was used to position eu member states on an eq-income map. the method can assist environmental and regional policy makers in formulating the best suited policies for growth and the environment in the eu. the analysis showed that the scandinavian countries plus some other northern european countries are characterized by high values of income and eq. among the rest, the benelux countries plus the uk have attained high incomes and low values of eq. finally, the european south plus ireland are characterized by low values of income and eq. our findings suggest that the notion of sustainable development is best suited for the countries of the european periphery low productivity group of countries. sustainable development maintains continuity of economic and social developments while respecting the environment without jeopardizing future use of natural resources. the old notion of “growth versus environment” has given way to a new view in which economic development and environmentally sustainable practices go hand in hand. better environmental stewardship is essential to sustain development. and only with faster economic growth in poor countries can environmental policies succeed. references baumol, w.j., oates, w.e. (1975), the theory of environmental policy: externalities, public outlays and the quality of life. englewood cliffs, nj: prentice-hall. bellante, d. (1979), the north-south differential and the migration of heterogeneous labour. american economic review, 69(1), 166-175. blomquist, g., berger, m., hohen, j. (1988), new estimates of quality of life in urban areas. american economic review, 78(1), 89-107. blomquist, g., berger, m., waldner, w. (1985), quality of life: ranking urban areas using a wage and rent based index. university of figure 3: per capita income and environmental quality giannias, et al.: measuring regional inequalities by amenity productivity approach for sustainable economic and environmental policies in eu international journal of energy economics and policy | vol 7 • issue 4 • 2017114 kentucky, department of economics, working papers, no. e-85. booth, d. (1998), the environmental consequences of growth. london: routledge. commission of the european communities (cec). (1992), a community programme of policy and action in relation to the environment and sustainable development (the fifth action programme), com(92) 23 final, brussels. commission of the european communities (cec). (1993), growth, competitiveness and employment: the challenges and ways forward into the 21st century, white paper. luxembourg: official publications for the ec. commission of the european communities (cec). (1994), economic growth and the environment: some implications for economic policy making, com (94) 465 final, brussels. daly, h.e. (1991), steady state economics. 2nd ed. washington, dc: island press. easterlin, r.a. (1973), does money buy happiness? the public interest, 30, 3-11. eberts, r., stone, j. (1986), metropolitan wage differentials: can cleveland still compete? federal reserve bank of cleveland, 2, 2-8. ekins, p. (1997), the kuznets curve for the environment and economic growth: examining the evidence. environment and planning a, 29, 805-830. european omnibus survey. (1988), les européens et environnement en 1988. forrester, j.w. (1971), world dynamics. cambridge, mass: wright-allen. galbraith, j.k. (1958), the affluent society. boston: houghton mifflin. glover, d. (1999), economic growth and the environment. canadian journal of development studies, 20(3), 609-623. gould, l., gardner, g., deluca, d., tiemann, a., doob, l., stolwijk, j. (1988), perceptions of technological risks and benefits. new york: russell sage foundation. griffin, j. (1974), an econometric evaluation of sulfur taxes. journal of political economy, 82(4), 669-688. grossman, g.m., krueger, a.b. (1993), environmental impacts of a north-american free trade agreement. in: garder, p.m., editor. the mexico-us free trade agreement. cambridge, mass: mit press. hammer, j., shetty, s. (1995), east asia’s environment, world bank discussion paper no. 287, washington, dc. hart, r. (2002), growth, environment, and culture-encompassing competing ideologies in one new growth model. ecological economics, 40(2), 253-267. hope, c., parker, j. (1990), environmental indices for all the need for a monthly index. energy policy, 18(4), 312-319. hope, c., parker, j., peake, s. (1991), a pilot index for the uk results of the last decade. statistical journal of the un, economic commission for europe, 8(1), 85-107. hope, с., parker, j. (1995), environmental indices for france, italy, and the uk. european environment, 5(1), 13-19. hope, с., parker, j., peake, s. (1992), a pilot environmental index for the uk in the 80s. energy policy, 20(4), 335-343. human development report. (1993), published for the united nations development programme. human development report. (1993), uk: oxford university press. johnson, g. (1983), inter-metropolitan wage differentials in the united states. in: triplett, j.e., editor. the measurement of labour cost. chicago: university of chicago press. king, m.a. (1974), economic growth and social development a statistical investigation. review of income and wealth series, 20(3). 251-272. krugman, p., venesables, a. (1990), an integration and the competitiveness of peripheral industry. in bliss, c., de macedo, j.b., editors. unity with diversity in the european economy: the community’s southern frontier. cambridge: cambridge university press. p56-75. meadows, d.h., meadows, d.l., randers, j., behrens, w.w., iiird. (1972), the limits to growth. a report for the club of rome’s project on the predicament of mankind. new york: universe books. mishan, e.j. (1972), the cost of economic growth. london: staple press. nordhaus, w.d., tobin, j. (1972), is growth obsolete? in nber 50th anniversary colloquium. vol. 5. new york: economic growth. ott, w.r. (1978), environmental indices: theory and practice. michigan, usa: ann arbor. pearce, d., turner, r., brown, d., baterman, i. (1991), the development of environmental indicators. report to the doe. london: university college. romer, p.m. (1998), increasing returns and long run growth. journal of political economy, 98, 71-102. solow, r.m. (1970), a contribution to the theory of growth. quarterly journal of economics, 70, 65-94. thomas, v., belt, t. (1997), growth and the environment: allies or foes? finance and development, 34(3), 222-224. tietenberg, t. (1994), environmental economics and policy. new york: harper collins. van der ploeg, f., tang, p. (1980), the macroeconomics of growth: an international perspective. oxford review of economic policy, 8(4), 15-28. walters, a.a. (1975), noise and prices. london: oxford university press. world bank. (1992), development and the environment. washington, dc: world bank. world commission on environment and development (wced). (1987), our common future, oxford: university press. world resources 1992-93. (1992), a guide to the global environment. oxford: towards sustainable development, oxford university press. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. . international journal of energy economics and policy | vol 9 • issue 1 • 2019 137 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(1), 137-142. land degradation and economic development in algeria zoubida mahcene*, mayou abdellah, mohamed zergoune, miloud lacheheb department of management, faculty of management, economics, and commercial sciences, kasdi merbah university, ouargla, algeria. *email: zoubidamo@yahoo.fr received: 25 july 2018 accepted: 20 october 2018 doi: https://doi.org/10.32479/ijeep.6947 abstract this study examines the relationship between land degradation and economic development in algeria using the autoregressive distributed lag (ardl) co-integration framework, and examine the existence of environmental kuznets curve. the results based on the bound testing process endorse a longrun relationship between land degradation and economic development. data were obtained from the food and agriculture organization and world bank development indicators for the period of 1970–2011. importantly, our results reveal that land degradation insignificantly related to economic development, also, no evidence found for ekc hypothesis. therefore, there is a dire need for technology improvement which may reduce the pressure on agriculture land demand and halt desertification. keywords: land degradation, economic development, ekc, autoregressive distributed lag jel classifications: q56, q01, o11 1. introduction numerous developing countries have chosen a “grow first, clean up later” method, in which that more concentrate on economic growth promoting regardless potential effects on environment. this approach leads to high rate of deforestation, agriculture land degradation, and biodiversity damage. in certain regions, such as north africa, deforestation may cause desertification and lead to land degradation. the relationship between economic growth and deforestation has been widely discussed through ekc hypothesis (bhattarai and hammig, 2001; cropper and griffiths, 1994; grossman and helpman, 1991) and found the existence of environmental kuznets curve (ekc) between deforestation and economic growth. moreover, these studies advocate the positive association between economic development and deforestation. the theoretical assessment of the ekc for deforestation is afforded by lopez (1994). the existing of ekc for the relationship between deforestation and gdp per capita, yet, is debatable. the concept ekc refers to the inverted u shape curve for relationship between deforestation and economic growth. in fact, the hypothesis is whether deforestation retains decreasing given that the per capita gdp grows, or at certain level the deforestation commences to decrease as gdp per capita preserve growing. many studies assessed the existence of ekc in confirming the relationship between income and deforestation (cropper and griffiths, 1994; bhattarai and hammig, 2001; culas, 2007). however, patterns of deforestation are difficult to identify globally due to various influence depending on the countries particularities, and this, confirm that deforestation factors are strongly heterogeneous. the deforestation and desertification in algeria has reached a serious level and there is fear of inability to restore it in the medium term, that is only 1.5% of total land area is barely forested (ali, 2009). in addition, forest fires caused a reduction in total forest area by 779872.11 ha between 1985 and 2006 (arfa et al., this journal is licensed under a creative commons attribution 4.0 international license mahcene, et al.: land degradation and economic development in algeria international journal of energy economics and policy | vol 9 • issue 1 • 2019138 2009). generally talking, targeting to achieve higher growth rate without sufficient attention to forests and arable land leads to overexploitation of forests; algeria in 1970s and 1980s lacked effective policies that enhance economic growth and forests alike. furthermore, throughout the increase in population number, people still fighting against difficult living condition, whereas, policies, somehow, still tend to provide basic necessities to individuals. thus, the forests are vanished from sight (zaimeche, 1994). in words, land degradation remains a serious problem in algeria, and yet, no proper mechanism has been applied to appropriately evaluate the different aspects of causes and consequences of deforestation, and then be able to imply right policies to save forests, and also to enlarge forests size in long term (figure 1). our paper precisely assesses the relationship between land degradation and economic development in algeria, applying nonlinear autoregressive distributed lag (ardl) approach to capture the association between the variables and the existence of ekc. findings of this study permit finding out at what certain level economic growth leads to increase in deforestation rate. ekc hypothesis allows illustrating at what level would further raise in economic growth leads to decrease deforestation rate. hence, gdp per capita can be applied to control desertification and land degradation in the country. also, the results permit to categorize the causes of deforestation in the country as per the impact weight, and hence appropriate policies can applied to halt land degradation and enhance economic growth alike to achieve sustainable economic development in algeria. section 2 presents an overview of related literature review. section 3 represent methodology and data, while section 4 reveals empirical results, and finally, section 5 concludes the study. 2. literature review the relationship between economic growth and deforestation has been widely discussed through ekc hypothesis. theory of inverted u-shaped ekc in the association between economic development and land degradation states that at initial level economic growth spurs forest area and deforestation increases (walker and nautiyal, 1982; barbier, 2004; barbier, 2005; naidoo, 2004). eventually, and as people become wealthier, this leads to more conserve environmental quality (koop and tole, 2001; meyer et al., 2003), which will cause reduction in deforestation as the income rises (bhattarai and hammig, 2001; ehrhardt-martinez et al., 2002; dinda, 2004). yet, several studies found contradictory results. for instance, shafik (1994) and koop and tole (1999) do not find evidence of ekc hypothesis. bhattarai and hammig (2001) confirm the existence of inverted u-shape ekc for african and latin american countries, while culas (2007) advocate the existence of ekc hypothesis in latin america only. thus, existence of ekc may vary across countries and regions; whereas, heterogeneity and country specification characteristics applied (nguyen-van and azomahou, 2007). moreover, several studies advocate the existence of inverted u-shape relationship between growth and deforestation (nguyen-van and azomahou, 2003). in this this study nguyenvan and azomahou applied panel data estimation to examine the association between deforestation economic growth and population, in which covers 85 developing countries for the period 1961–1994. the findings using fixed and random effect model show no evidence of existence ekc, despite the negative effect between deforestation and gdp per capita. also, population pressure appears to be significant in increasing deforestation rate among latin america and asian countries. more recent studies have investigated this issue from different angles. al-mulali et al. (2015) explore the effect of financial development on co2 emission in 129 countries classified by the income level using urbanisation, gdp growth, trade openness, petroleum consumption and financial development variables. the rest of the determinants, especially petroleum consumption, are determined to be the major source of environmental damage in most of the income group countries. apergis and ozturk (2015) focused on how both income and policies in these countries affect the income emissions relationship using the ekc hypothesis for 14 asian countries. results reveal that the ekc hypothesis is confirmed for the 14 asian countries. however, al-mulali et al. (2015) investigate the existence of the ekc hypothesis in vietnam during the period 1981–2011 but found no evidence on the existence of ekc hypothesis in vietnam. oyebanji et al. (2017) examine the long-run equilibrium between green growth and some environmental variables like deforestation, energy depletion and carbon dioxide) emissions in nigeria from 1980 to 2015. the results confirmed a positive long-run relationship exists between green growth variable and deforestation. similarly, gill et al. (2017) advocate that ekc growth strategy is resource intensive and has huge environmental cost that this planet may not be able to absorb in future. meanwhile, diputra and baek (2018) explored growth-environment nexus in indonesia and found little evidence that urbanization causes significant environmental degradation. since algeria influenced by land degradation which is caused through deforestation and desertification, we estimate the association between deforestation, desertification and economic development. figure 1: trend of agriculture land in algeria (hectare) (1961–2010). source: world bank, 2014 mahcene, et al.: land degradation and economic development in algeria international journal of energy economics and policy | vol 9 • issue 1 • 2019 139 3. data and methodology this study used annual data from 1970 to 2011. angelsen (1999) highlighted main factors that cause land degradation; the main factors that lead to deforestation and land degradation are: population, income level, trade liberalization, and round wood production. in line with related literature, the following variables have been applied to examine the relationship between land degradation desertification and economic growth along with validation test of ekc hypothesis: arable land, rural population, economic development, round wood production, and total forest product export. as a measure of deforestation and desertification, agriculture land has been applied to capture degradation of land in algeria. the data is on yearly basis which covers the period from 1970 to 2011, total of 42 observations. data is basically sufficient to test for long-run relationship. data are mostly collected from food and agriculture organization website database, agriculture area, arable land, rural population, round wood production, and total forest product export (1000 us$); while, gdp (constant 2005 us$) is taken from world development indicators (wdi), world bank. our general equation model to capture income level effect and ekc existence is as follows: agrea=f (arlnd, rpop, gdp, gdps, rwd, exp) (1) the above function demonstrations that (agrea) land degradation rate is the function of, (arlnd) is arable land area; (rpop) is rural population; (gdp) is gdp (constant 2005 us$); (gdps) is gdp square (constant 2005 us$); (rwd) is round wood production, and (exp) is total forest product export (1000 us$). from the above given equation, the nonlinear relationship among the variables becomes: lagreat=β0+β1larlndt+β2lrpopt+β3lgdpt+β4lgdpst+β5l rwdt+β6lexpt+εt (2) although, numerous studies have been conducted in evaluating the effect of economic growth on deforestation, but few studies have investigated this relationship in term of land degradation in desert area. thus, the above model attempts to estimate the effect of linearity and nonlinearity relationship between economic development and land degradation. the ardl procedure can distinguish between dependent and explanatory variables. in this case, the error correction representations of the ardl specification model for eq. (2) are given by: ∆ = + + + + − − − ln ln ln ln ln agrea ² agrea arlnd rpop gdp t t t tβ β β β 0 1 1 2 1 3 1 4 tt t t t i n t gdps rwd exp a agrea − − − − = − + + + + ∆ +∑ 1 5 1 6 1 7 1 1 1 1 β β β ln ln ln ln ii n t i n t i n t i b arlnd d rpop e gdp = − = − = − = ∑ ∑ ∑ ∆ + ∆ + ∆ + 0 1 1 0 1 1 0 1 1 0 ln ln ln nn t i n i n t t t e gdps e rwd e exp ∑ ∑ ∑ ∆ + ∆ + ∆ − = = − − 1 1 0 1 0 1 1 1 ln ln ln ε (3) where ∆ represents the first difference operator, β0 is the drift component, εt is the usual white noise residuals, eq. (3) is a standard var model in which a linear combination of lagged-level variables are added as proxy for lagged error terms which measures the departure of the dependent variable from the independent variables in eq. (2). 4. empirical results unit root test is employed to test the integration order for each variable; agriculture area, arable land, rural population, gdp, gdp square, round wood production, and forest exported product. augmented dickey-fuller (adf) test is conducted to verify the order of integration of each variable. table 1 obviously reveals that the variables are a combination of i(0) and i(1) variables. thus, the autoregressive distributes lag approach (ardl) popularized by pesaran et al. (2001) is most suitable for this study. before the longrun and short-run estimations are conducted, a bound test is necessary to ascertain the existence of a cointegration between the variables. table 2 represents the computed f-value, likelihood ratio and lagrange multiplier for testing the existence of long run relationship agriculture area and its determinants. the calculated f-statistics is compared with the critical bounds provided by narayan (2005). the calculated f-statistic of the model is 6.9356 which is significant at 1%. therefore, it can be concluded that long run cointegration relationship among agriculture area and it determinants exist. since long run cointegration exists among variables, we can proceed to estimate the long run coefficient between the variables using ardl approach. the table 3 displays the results of long run coefficient for the selected model. the estimated long run model shows that gdp has positive but statistically insignificant related to deforestation and desertification table 1: unit root test adf variable level 1st difference constant constant and trend constant constant and trend lagrea −2.935001 (−1.695264) −3.523623 (−1.217492) −2.936942*** (−6.353675) −3.526609*** (−6.745328) larlnd −2.935001 (−2.417120) −3.523623 (−2.326350) 2.936942*** (−6.522536) −3.526609*** (−6.719971) lexp −2.935001 (−0.981349) −3.523623 (−1.430384) −2.936942*** (−6.736483) −3.529758*** (−6.346480) lgdp −2.936942*** (−3.967280) −3.552973 (−2.586255) −2.936942 (−8.794306) −3.526609 (−9.868494) lgdps −2.936942*** (−3.746502) −3.552973 (−2.621009) −2.936942 (−8.731013) −3.526609 (−9.691602) lrpop −2.943427* (−2.857684) −3.529758 (−1.748009) −2.943427 (−1.732116) −3.536601 (0.038704) lrwd −2.935001** (−2.950003) −3.523623 (−0.004412) −2.936942*** (−5.548340) −3.526609*** (−6.065697) *,**,*** denote significance at 10%, 5% and 1% levels respectively. values in parentheses represent t-value. adf: augmented dickey-fuller mahcene, et al.: land degradation and economic development in algeria international journal of energy economics and policy | vol 9 • issue 1 • 2019140 in algeria. the presence of the relationship between deforestation and income depends on the used variables (barbier, 2004; ehrhardt-martinez et al., 2002). furthermore, results endorse the inexistence of ekc. large diversity in environmental and social characteristics which exists across countries may explain the presence or absence of ekc (koop and tole, 1999). algeria torture by the natural land degradation and desertification which the income has no effect on it. round wood production has statistically insignificant relationship with agriculture area reduction. this reflects the unusual and accidental forest fires that occur especially in summer session. forests in algeria, currently fragile, desires additional protection since deforestation is continuously gaining in extent because of frequent forest fires (arfa et al., 2009). forest exported product has a negative, but, statistically insignificant in explaining agriculture area variation. algerian economy heavily depends on hydrocarbon sector, such as gas and oil with 98% of total export. agriculture and forest product trading is still sharing a minor percentage in trade. we proceed to compute short run model along with error correction reorientations ect. error correction term, ecmt−1 measures the speed of adjustment, when explained variable adjust to change in the independent variables before converging to the equilibrium level. the experimental findings are based on the re-parameterization of the estimated ardl (1, 0, 0, 0, 0, 0, 0) model. from the results error-correction model must be significant and attached with a negative sign. the negative ecmt−1 means that the variables have converged in the long run. in this model the probability of ecmt−1 is 0.001 (table 4). since ectt-1 is negative and statistically significance, we can conclude that the short run cointegration relationship exists for this model. the coefficient is 0.59669 which suggests that convergence to equilibrium level of agriculture area in one year is corrected by about 5.966% in the following year. a battery of diagnostic tests was also applied to the empirical model to gauge the adequacy of the specification of the model (table 5). the diagnostic test explores the heteroscedasticity, normality, functional form and serial correlation associated with the model. the diagnostic tests presented in table 5, confirm that there is no evidence of m problem with the model. furthermore, dw-statistic is >r2 we conclude that there is not autocorrelation. the stability test for the model applies the cumulative sum of the squares of recursive residuals (cusum-squared) and the cumulative sum of recursive residuals (cusum) proposed by brown et al. (1975), which are presented in figures 2 and 3., these results again confirm the robustness of our results achieved in the diagnostic tests. obviously, the cusum and cusumsquared statistics stay within the critical bounds indicating significant relationship between agriculture area and the other variables. table 2: the bound test model f-statistic lag significance level 1.0% critical bound f-statistic i (0) i (1) fy (lagrea, larlnd, lrpop, lgdp, lgdpslrwd, lexp) 6.9356 2 1.0% 1.0% 3.656 5.331likelihood ratio statistic 56.3067 lagrange multiplier statistic 29.7945 table 3: long-run relationship model: (lagrea, larlnd, lrpop, lgdp, lgdpslrwd, lexp) (1, 0, 0, 0, 0, 0, 0) larlnd lrpop lgdp lgdps lrwd lexp intercept 0.57077 (1.6698) −1.1840 (−2.8108)a 5.0048 (0.66874) −0.22836 (−0.65954) 0.12457 (0.64612) −0.0049162 (−0.69881) −21.0081 (−0.53432) figures in parentheses ( ) indicate the standard errors. while, superscript denotes statistical significance at 5% level table 4: error correction representation for the selected ardl model model: dlagrea, dlarlnd, dlrpop, dlgdp, dlgdps, dlrwd, dlexp ∆agrea=−12.5353 + 0.34057dlarlndt−1−0.70645dlrpopt−1 + 2.9863dlgdpt−1 −0.13626dlgdpst−1 + 0.074329dlrwdt−1 −0.0029335dlexpt−1 (−0.52141) (1.6168) (−2.1635)b (0.64629) (−0.63781) (0.63167) (−0.69915) −0.59669ecm (−1) (−3.7158) standard errors in parentheses, ∆ means the first difference, and the superscript “aˮ denotes statistical significance at 5% levels table 5: diagnostic tests test statistics lm version p-value f version p-value serial correlation =0.65520 (0.418) f (1, 30)=0.51261 (0.480) serial correlation =0.23801 (0.626) f (1, 300)=0.18421 (0.671) normality =134.3118 (0.000) heteroscedasticity =1.3811 (0.240) f (1, 37)=1.3584 (0.251) r2 =0.88364 dw-statistic 1.8574 0.251 mahcene, et al.: land degradation and economic development in algeria international journal of energy economics and policy | vol 9 • issue 1 • 2019 141 finally, we found the parameters remained stable over the entire study period using cusum and cusum square tests, because both of the recursive lines fall within the bound. 5. conclusion this study investigated the nonlinear relationship between economic development on land degradation in algeria. estimated results, using ardl model to cointegration approach, revel the negative, but, insignificant, relationship between economic and deforestation rate. furthermore, results confirm the inexistence of ekc between land degradation and economic growth in algeria. however, rural population appears to have positive and significant association to deforestation. long run results show that change by 1% in gdp decreases deforestation by 2.98%. while 1% increase in rural population leads to increase in deforestation by 1.18%. however, round wood production and forest exported production statistically insignificant in explaining changes in land degradation rate in the algeria. furthermore, by applying a bulky number of diagnostic test and the cusum and cusumsq tests to the model, we found the parameters remained stable over the entire study period and the diagnostic tests confirm that there is no evidence of diagnostic problem with the model. thus we conclude that economic growth does not affect deforestation and desertification in the algeria. from the policy perspective, there is a dire need to implement improved technology in order to achieve sustainable forest management and reduce pressure on agriculture land. moreover, reforestation is critically required to save forest area and halt desertification. hence, appropriate policies are required to be implemented in order to increase and save existing forest area from desertification and deforestation. equally important, providing substitute jobs for people in rural area may reduce the deforestation and desertification in the country. references al-mulali, u., saboori, b., ozturk, i. (2015), investigating the environmental kuznets curve hypothesis in vietnam. energy policy, 76, 123-131. al-mulali, u., tang, c.f., ozturk, i. (2015), does financial development reduce environmental degradation? evidence from a panel study of 129 countries. environmental science and pollution research, 22(19), 14891-14900. ali, g. (2009), desertification in algeria: policies and measures for the protection of natural resources. in: facing global environmental change. berlin, heidelberg, new york: springer. p. 159-173. angelsen, a., kaimowitz, d. (1999), rethinking the causes of deforestation: lessons from economic models. the world bank research observer, 14(1), 73-98. apergis, n., ozturk, i. (2015), testing environmental kuznets curve hypothesis in asian countries. ecological indicators, 52, 16-22. arfa, a.m.t., benderradji, m.e.h., alatou, d. (2009), analyse des bilans des incendies de forêt et leur impact économique en algérie entre 1985 et 2006. new medit, 8, 52-57. barbier, e.b. (2004), agricultural expansion, resource booms and growth in latin america: implications for long-run economic development. world development, 32(1), 137-157. barbier, e.b. (2005), frontier expansion and economic development. contemporary economic policy, 23(2), 286-303. bhattarai, m., hammig, m. (2001), institutions and the environmental kuznets curve for deforestation: a crosscountry analysis for latin america, africa and asia. world development, 29(6), 995-1010. cropper, m., griffiths, c. (1994), the interaction of population growth and environmental quality. the american economic review, 84, 250-254. culas, r.j. (2007), deforestation and the environmental kuznets curve: an institutional perspective. ecological economics, 61(2), 429-437. dinda, s. (2004), environmental kuznets curve hypothesis: a survey. ecological economics, 49(4), 431-455. diputra, e.m., baek, j. (2018), is growth good or bad for the environment in indonesia? international journal of energy economics and policy, 8(1), 1-4. ehrhardt-martinez, k., crenshaw, e.m., jenkins, j.c. (2002), deforestation and the environmental kuznets curve: a cross-national investigation of intervening mechanisms. social science quarterly, 83(1), 226-243. gill, a.r., viswanathan, k.k., hassan, s. (2017), is environmental kuznets curve (ekc) still relevant? international journal of energy economics and policy, 7(1), 156-165. grossman, g.m., helpman, e. (1991), trade, knowledge spillovers, and growth. european economic review, 35(2-3), 517-526. koop, g., tole, l. (1999), is there an environmental kuznets curve for deforestation? journal of development economics, 58(1), 231-244. koop, g., tole, l. (2001), deforestation, distribution and development. global environmental change, 11(3), 193-202. lopez, r. (1994), the environment as a factor of production: the effects of economic growth and trade liberalization. journal of environmental economics and management, 27(2), 163-184. meyer, a.l., van kooten, g.c., wang, s. (2003), institutional, social and economic roots of deforestation: a cross-country comparison. international forestry review, 5(1), 29-37. naidoo, r. (2004), economic growth and liquidation of natural capital: the case of forest clearance. land economics, 80(2), 194-208. narayan, p.k. (2005), the saving and investment nexus for china: evidence from cointegration tests. applied economics, 37(17), 1979-1990. nguyen-van, p., azomahou, t. (2007), nonlinearities and heterogeneity in environmental quality: an empirical analysis of deforestation. figure 2: plot of cusum figure 3: plot of cusum-squared mahcene, et al.: land degradation and economic development in algeria international journal of energy economics and policy | vol 9 • issue 1 • 2019142 journal of development economics, 84(1), 291-309. oyebanji, i.j., adeniyi, b., khobai, h., le roux, p. (2017), green growth and environmental sustainability in nigeria. international journal of energy economics and policy, 7(4), 216-223. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. shafik, n. (1994), economic development and environmental quality: an econometric analysis. oxford economic papers, 46, 757-773. nguyen-van, p., azomahou, t.t. (2003), déforestation, croissance économique et population. revue économique, 54(4), 835-855. walker, e.w., nautiyal, j. (1982), some possibilities in the economic development of liberia through the forestry sector. forest ecology and management, 4(2), 179-189. zaimeche, s. (1994), change, the state and deforestation: the algerian example. geographical journal, 160(1), 50-56. tx_1~at/tx_2~at international journal of energy economics and policy | vol 9 • issue 4 • 2019 363 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(4), 363-368. features of the use of renewable energy sources in agriculture tokhtar bolyssov1, bauyrzhan yessengeldin1*, gulvira akybayeva1, zamzagul sultanova2, azamat zhanseitov1 1academician y.a. buketov karaganda state university, universitetskaya st. 28, karaganda, kazakhstan, 2zhangir khan west kazakhstan agrarian-technical university, zhangir khan st.51, uralsk, kazakhstan. *email: yessen_baur@inbox.ru received: 07 december 2018 accepted: 08 may 2019 doi: https://doi.org/10.32479/ijeep.7443 abstract the article considers the prospects of using renewable energy sources in agriculture. the authors focused on the following types of renewable energy sources: solar, biomass, wind, and hydro generated power. based on the analysis of renewables global status report data, the authors identified a decrease in the amount of investment in renewable energy and fuel by developed countries in developing countries. this work highlights the main reasons for the development of renewable energy (environmental safety, energy independence), as well as positive and negative aspects of the transition to renewable energy. the authors of the article reveal the features of job creation in the renewable energy industries, which will compensate for the loss of jobs in the field of fossil energy. much attention is paid to the economy of renewable energy sources, revealing the relationship between energy use and economic growth. according to the authors, the use of res not only increase the level of energy supply to remote rural settlements, but also can have a significant positive impact on the economy of agriculture. keywords: agriculture, renewable energy sources, energy economy jel classifications: q10, q29 1. introduction undeniably, agricultural production is the sole provider of human food. with the growing global population, which is projected to rise by 25% in the next 20 years, the demand for food and energy is also expected to increase significantly (korovin et al., 2018. p. 114). most of the farming machines and agricultural industries are driven by non-renewable energy sources like fossil fuels that are known to emit greenhouse gases and leads to climate change as well as global warming. in this regard, more sustainable resources tend to reduce growing concerns about the environmental impact of these non-renewable fuels. one of the main outcomes of the united nations conference on sustainable development (2015) was the adoption of 17 sustainable development goals for the period up to 2030 by member states. in relation to this, a separate objective in the field of energy was adopted, in order to confirm the importance of energy as one of the key factors of sustainable development. to achieve this goal by 2030, it is proposed to significantly increase the share of renewable energy in the global energy balance, as well as to intensify international cooperation to facilitate access to research and technology in the field of renewable energy. in the agricultural sector, the idea of sustainable energy is based on the creation of balance between maximizing agricultural production and promoting economic growth, while also reducing harmful environmental effects. as well, it entails replenishing the agricultural land through the use of renewable inputs such as natural fertilizers. thus, the purpose of this study is to identify the possibility of using renewable energy sources in agriculture. to achieve the goal, the following tasks should be performed: this journal is licensed under a creative commons attribution 4.0 international license bolyssov, et al.: features of the use of renewable energy sources in agriculture international journal of energy economics and policy | vol 9 • issue 4 • 2019364 • review of the literature on the use of renewable energy in agriculture; • analysis of the level of development of renewable energy sources in the world; • consideration of the economics of renewable sources. 2. literature review understanding the attributes of the renewable energy in agriculture requires exploring the four main forms of renewable energy sources mainly solar, biomass, wind, and hydro generated power. solar energy is the primary source of natural energy. naturally, agricultural production relies on solar energy in the process of photosynthesis. lukutin (2008) notes that the sun is the most affordable and environmentally friendly as the use of solar energy on a large scale does not violate the existing energy balance of rural areas. at the same time, industrial solar energy technologies have been integrated into agricultural activities where it is used as a direct energy source or in supplementing other energy requirements in farms (chel and kaushik, 2011. p. 93). for instance, solar energy dryers are used in crop and grain drying and produce a more uniform and quality drying technique than the other energy sources. this is discussed in detail by john and william (2013), they reveal the possibility of using solar energy for various technologies, including for drying crops. a basic solar energy source comprises of a solar collector, solar energy converter and turbines that are fitted to various energy consuming systems like farms and agricultural processing firms. biomass is a source of fuel that is generated from dead and decaying plant materials. it is comprised of wood, crop residues, and animal wastes. given type of energy sources is considered in many different literatures. batidzirai et al. (2012) detailed the different types of bioenergy potentials such as theoretical, technical, market, environmentally sustainable and implementation potentials. in the works of daioglou et al. (2016) the main parameters of biomass potential development are related to total land-use change, impact of carbon stocks, net availability of residual biomass, etc. which are considered and analysed for different future scenarios in terms of land-use change and agricultural management. agricultural-industrial economies and farms use biomass energy in various different forms. mainly, the biomass utilization technologies use biomass raw inputs, which are applied to produce electrical energy in power plants. chemical process can also be used to convert biomass into fuels such as methane, which is a potential source of fuel in the form of natural gas. cordell (2010) also notes that biomass, in addition to energy production, can be used to process plant nutrients, especially phosphorus. the economics of biomass use is based on the fact that the overall quantity of biomass energy available is finite since it depends on the available forested land. also, biomass energy is minimal in relation to the energy consumption requirements in most developed nations. thus, it must be supplemented with other energy sources to sustain the agricultural energy requirements. hydroelectric power is the current largest source of renewable energy in the world, where it generates 16% of global electricity (timmons et al., 2014). since most of the developed nations have a reliable source of water, hydropower has been regarded as a reliable renewable energy source in stimulating agricultural production in farms and industries. with the introduction of renewable hydropower sources, the smart power grid is being updated to incorporate solar photovoltaic power and wind turbines (vandaele and porter, 2015. p. 3). this has promoted efficient transmission of energy into agricultural production activities, thereby increasing agricultural production. in most developed nations, the need to boost agricultural production through the mechanization process, as well as food processing and value addition has been fueled by significant additional hydropower developments such as dam construction. notably, dam construction and water source availability are the primary external costs used in hydropower generation. this, in turn, influences the potential hydropower generation and reliance among different nations. by 2010, the united states had developed about 16% of its hydropower technical potential while china is said to have developed only 24% of its technical potential (timmons et al., 2014. p. 8). however, lehner et al. (2005) analysed the possible impacts of climate change on europe’s hydropower potential at the country level. the results clearly showed that the hydropower potential in europe depends on climate change, with a possible reduction of 25% or more for the countries of southern and south-eastern europe. like hydropower, solar and biomass, the wind power has been used to produce energy since the ancient times. wind power is produced by the moving air energy which is tapped using modern windmills and wind turbines and then transformed into electrical energy (bezrukikh, 2010). increase in wind velocity means more potential energy and better yield. also, this translates into lower cost of energy generation for a particular energy quantity. according to sundararagavan and baker (2012) for the integration of wind turbines and power systems need three key factors: the displacement of the load frequency support at the levels of transmission and distribution and the quality of power to smooth out power fluctuations. ngô and natowitz (2009) highlight that problems associated with the use of wind energy sources include wind power outages and additional costs of energy transfer to residential areas. because wind turbines are installed in windy areas where population densities tend to be lower, offshore wind turbines are considered a viable alternative for land-based turbines, especially in areas with limited land resources. the economic and environmental benefits relating to renewable resources aided by favorable economic and legislative climate are projected to increase the integration of renewable resources in the developed economies. for instance, in the united states, the government and policy makers remain committed to increasing renewable energy which stands at 13% based on annual energy outlook from energy information administration (vandaele and bolyssov, et al.: features of the use of renewable energy sources in agriculture international journal of energy economics and policy | vol 9 • issue 4 • 2019 365 porter, 2015. p. 3). this emphasis on the use of renewable capacity has been increasing significantly since 2005. this linear trend implies that by 2040, the overall energy generation from renewable resources is expected to increase to 67%. also, this linear increment of renewable capacity will result in 20.5% in market share by 2040, which will be higher than the energy information administration outlook projection of 16% (vandaele and porter, 2015. p. 3). notably, exponential economic growth and government support will be the propelling factors in increasing this projection going forward. a literary review of the introduction and use of renewable energy sources in agriculture revealed the main driving forces that have allowed to effectively develop this direction: • balance of the cost of energy produced from traditional sources and from res, including in connection with the tightening of environmental requirements for the energy of traditional power plants; • continuous reduction of the cost of renewable energy equipment by improving the technological base; • a systematic approach to the use of renewable energy sources; • energy saving, continuous energy loss reduction; • availability of a clear, reasoned and full-fledged regulatory framework in the field of renewable energy and energy saving. 3. the level of renewable energy development in the world inexhaustibility and ecological purity of renewable energy sources are the main reasons for the rapid development of renewable energy in the world and optimistic forecasts of their development in the coming years. according to the renewables global status report (2018), new investments in renewable energy and fuel amounted to 280 billion usd in 2017. that is 46 billion usd more than in 2013 (table 1). in recent years, the amount of investments made by developed countries has decreased from 133 billion us dollars in 2013 to 103 billion us dollars in 2017. observed over the last 5 years the increase of the amount of investment developing countries is 76 billion us dollars. according to the renewables global status report (2018) in 2017, china, the us, japan, india and germany were the leaders of global investments in renewable electricity and fuels. however, when measured per unit of gross domestic product, the marshall islands, rwanda, solomon islands, guinea-bissau and many other developing countries invest as much or more in renewable energy as developed and developing economies (table 2). according to renewable energy statistics (2018), the production of renewable energy sources is increasing annually. solar energy is developing faster than anyone else. in 2017, compared to 2013, the growth rate of solar power was 275.98%. in second place in terms of growth is wind energy. in this industry, the average annual rate of power growth in the considered period of time was 171.3% (table 3). considering which countries are leaders in the types of renewable energy production (table 4). according to the renewables global status report (2018), china and the us are clear leaders in the production of renewable energy sources. table 1: global new investment in renewable power and fuels in developed, emerging and developing countries, 2013-2017 billion usd indicators 2013 2014 2015 2016 2017 difference of changes: 2017 in comparison to 2013 overall investment 234 284 323 274 280 +46 developed countries 133 151 146 126 103 −30 developing and emerging countries 101 133 177 148 177 +76 compiled by the authors using renewables 2018: global status report, ren21 table 2: top 5 countries on investments in renewable energy in 2017 indicators place 1 2 3 4 5 investment in renewable power and fuels (not including hydro over 50 mw) china united states japan india germany investment in renewable power and fuels per unit gdp marshall islands rwanda solomon islands guinea-bissau serbia compiled by the authors using renewables 2018: global status report, ren21. gdp: gross domestic product table 3: production of renewable energy sources for 2013-2017 in the world megawatts (mw) types of renewable energy sources 2013 (mw) 2014 (mw) 2015 (mw) 2016 (mw) 2017 (mw) growth rate: 2017 in comparison to 2013 (%) solar 137899 174139 225033 297019 380572 275.98 bioenergy 84297 89631 95644 103681 108958 129.25 hydropower 1032807 1069118 1101616 1130474 1153911 111.73 wind 299801 349103 416737 467488 513547 171.30 overall 1554804 1681991 1839030 1998662 2156988 138.73 compiled by the authors using renewable energy statistics (2018) bolyssov, et al.: features of the use of renewable energy sources in agriculture international journal of energy economics and policy | vol 9 • issue 4 • 2019366 t h e r e a r e a t l e a s t t w o r e a s o n s t o d e v e l o p r e n e w a b l e energy: environmental safety and energy independence. the obvious advantage of res is that when the payback period is reached, the generated electricity becomes almost free. the downside is in unstable production, which still has to be reserved by traditional generation. governments (and more often consumers) have to pay for gas and coal plants to be able to load power units quickly on cloudy or windless days. humanity is on the way to developing energy storage devices that can solve this problem, but on an industrial scale, these solutions are not yet used. other benefits of the transition to renewable energy include the supply of energy-deficient and remote rural areas, as well as the creation of new jobs. according to the international renewable energy agency (irena), in 2017, the renewable energy industry provided 10.34 million jobs in the world. among the renewable energy industries, solar energy (3.57 million people) and bioenergy (3.06 million people) were the leaders in the number of jobs. in recent years, there has been a decrease in the number of jobs in hydropower, which are associated with the use of new technologies in production (table 5). new jobs that appear with the further development of res, compensate and block the loss of jobs in the field of fossil energy. however, the macroeconomic benefits of green jobs depend on short-and long-term goals. developing renewable energy and energy efficiency are typically more labour intensive and more manual labour (in component production, installation and facility maintenance) than is required for the extraction and transport of fuels in more automated and capital-intensive fossil fuels. 4. renewable energy economics modern agriculture is the main source of greenhouse gas emissions on the planet, as well as one of the main consumers of fossil fuels. therefore, it is advisable to use alternative energy sources for the agricultural economy. after all, some agricultural activities, such as irrigation, can be fed from renewable sources. the idea of renewable economics is based on the integration of energy saving technologies and promoting energy efficiency during the energy consumption cycle (kvon et al., 2018). given the current rate of economic development and socioeconomic modernization of the global economies, the need to promote a high level of secure energy in the production process has increased considerably. the idea is that secure energy has been recognized as the primary pre-determiner of a state development strategy that aims to reduce the ever-increasing threats of non-renewable energy in the long term (yessengeldin et al., 2018. p. 116). to achieve a secure energy level, global energy security management should be committed to promoting an economically sustainable development of renewable resources. fundamentally, sustainable renewable energy entails that there should be an association between energy use and economic growth. the study by al-mulali et al., (2014) examines the impact of renewable and non-renewable energy consumption on economic growth in 18 latin american countries. based on the results of this study, it is recommended that the countries under study increase their investments in renewable energy projects to increase the role of electricity consumption from renewable sources. at the same time, the major concept of replacing non-renewable energy with renewable relies on the extensive development of energy production infrastructure (owusu and asumadu, 2016). notably, even when the required technology for higher energy production efficiency is available, renewable energy investments tend to incur high costs of infrastructural development per unit of energy coupled with uncertainties and risks (er et al., 2018. p. 181). thus, despite the significant potential of renewable energy, their integration to the total power production remains low in most developed and emerging nations. this is the case in countries such as u.s, china, kazakhstan, saudi arabia, and south africa. in kazakhstan, for instance, some regions experience electricity supply shortage despite having vast renewable resources due to factors such as high energy intensity of the economy, as well as irrational utilization of fuel resources (abayev, 2018. p. 90). similarly, countries such as south africa are experiencing rising pressure of demand over supply due to the unsustainability caused by over-reliance on non–renewable resources like coal technology (ateba and prinsloo, 2018). such problems can be addressed through the integration of infinite renewable energy such as advancement towards hydropower. table 4: top 5 countries by types of renewable energy production in 2017 indicators place 1 2 3 4 5 solar china usa japan germany italy bioenergy usa brazil china india germany hydropower china canada brazil usa russia wind china usa germany india spain compiled by the authors using renewables 2018: global status report, ren21 table 5: number of jobs in the renewable energy sector million people types of renewable energy sources 2013 2014 2015 2016 2017 changes: 2017 in comparison to 2013 solar 2.27 2.50 2.77 3.09 3.57 +1.3 bioenergy 2.50 2.99 2.88 2.74 3.06 +0.56 hydropower 1.74 1.66 1.63 1.52 1.51 −0.23 wind 0.83 1.03 1.08 1.16 1.15 +0.32 others 0.89 1.15 1.35 1.28 1.05 +0.16 overall 8.23 9.33 9.71 9.79 10.34 +2.11 compiled by the authors using renewable energy and jobs: annual review (2018) bolyssov, et al.: features of the use of renewable energy sources in agriculture international journal of energy economics and policy | vol 9 • issue 4 • 2019 367 the realization of sufficient renewable energy resources to sustain agricultural and economic development globally is a practicable endeavor. in fact, a study by (chel and kaushik, 2011) indicated that renewable resources like wind, water, and solar could sustain the global society energy requirements by 2030. also, it could replace all existing non-renewable energy resources by the year 2050. given that the approximated demand in energy by 2030 is 17 trillion watts, the provision of wind, solar, and water energy surpasses both agricultural and other sectored energy needs worldwide. hence, the use of res in agricultural energy systems is a promising and feasible task. agriculture has the greatest potential to unlock the benefits of renewable energy, at the same time addressing the most pressing problems of rural energy supply. the introduction of integrated energy-efficient systems of autonomous and mixed energy supply of rural buildings using renewable and local energy resources will allow: • to improve the level and quality of electricity, heat and water supply to rural settlements and buildings; • to reduce loss of resources, to ensure energy saving; • to increase energy efficiency; to increase the level of energy supply of remote, dispersed rural facilities of small and medium capacity. 5. conclusion the concepts of renewable energy sources in agriculture among developed countries are predicated on the balance between maximizing agricultural production while minimizing the use of finite energy resources as well as their environmental effects. current agricultural production and economic activity rely heavily on fossil fuels such as oil and coal. these energy sources are purely non-renewable can cause detrimental environmental effects. ideally, the use of renewable resources like hydroelectric, solar power, wind, and biomass in agricultural production has been integrated as a more sustainable and environmentally friendly energy source. despite their numerous benefits, however, the adoption of these renewable energy sources depends on the availability of natural resources like wind and water. also, efficient technologies are needed to establish the necessary infrastructure to integrate these energy sources. the speed of the integration into renewable energy sources will also be highly influenced by policy formulation and support from national governments. given the fact that the renewable energy is cost-effective, e n v i r o n m e n t a l l y f r i e n d l y a n d c a n s t i m u l a t e i m m e n s e agricultural as well as economic production, all necessary procedures, policy and infrastructural development should be enacted to ensure ultimate reliance on these renewable energy resources in the future. references abayev, a. (2018), possibilities of solar energy utilization for the development of rural areas of the republic of kazakhstan. international journal of energy economics and policy, 8(2), 89-94. al-mulali, u., fereidouni, h.g., lee, j.y.m. (2014), electricity consumption from renewable and non-renewable sources and economic growth: evidence from latin american countries. renewable and sustainable energy review, 30, 290-298. ateba, b.b., prinsloo, j.j. (2018), the electricity security in south africa: analysing significant determinants to the grid reliability. international journal of energy economics and policy, 8(6), 70-79. batidzirai, b., smeets, e., faaij, a. (2012), harmonising bioenergy resource potentials methodological lessons from review of state of the art bioenergy potential assessments. renewable and sustainable energy reviews, 16(9), 6598-6630. bezrukikh, p.p. (2010), wind energy: methodology benefits. moscow: publishing house energy. p320. chel, a., kaushik, g. (2011), renewable energy for sustainable agriculture. agronomy for sustainable development, 31(1), 91-118. cordell, d. (2010), the story of phosphorus: sustainability implications of global phosphorus scarcity for food security. doctoral thesis in linköping university, faculty of arts and sciences. available from: http://www.liu.divaportal.org/smash/ record.jsf?pid=diva2:291760. daioglou, v., stehfest, e., wicke, b., faaij, a., van vuuren, d. (2016), projections of the availability and cost of residues from agriculture and forestry. gcb bioenergy, 8, 456-470. er, b., guneysu, y., ünal, h. (2018), financing renewable energy projects: an empirical analysis for turkey. international journal of energy economics and policy, 8(6), 180-185. john, a., william, a. (2013) beckman solar engineering of thermal process. 4th ed. new york: john wiley and sons. p936. korovin, i.o., medvedev, a.v., neupokoeva, t.v. (2018), waste management in coal and oil industry in context of alternative sources of energy development. international journal of energy economics and policy, 8(6), 114-119. kvon, g.m., prokopyev, a.i., shestak, v.a., ivanova, s.a., vodenko, k.v. (2018), energy saving projects as energy security factors. international journal of energy economics and policy, 8(6), 155-160. lehner, b., czisch, g., vassolo, s. (2005), the impact of global change on the hydropower potential of europe: a model-based analysis. energy policy, 33(7), 839-855. lukutin, b.v. (2008), renewable energy sources. tomsk: publishing house of tomsk polytechnic university. p187. ngô, c., natowitz, j. (2009), our energy future: resources, alternatives and the environment. vol. 11. new york: wiley. available from: https://www.wiley.com/en-cx/our+ energy+ future%3a+ resources%2c+ alternatives+and+ the+ environment%2c+2nd+ edition-p-9781119213369. owusu, p.a., asumadu-sarkodie, s. (2016), a review of renewable energy sources, sustainability issues and climate change mitigation. cogent engineering, 3(1), 1-14. renewable energy and jobs: annual review. (2018), irena. available from: http://www.irena.org/publications/2018/may/renewableenergy-and-jobs-annual-review-2018. renewable energy statistics. (2018), irena. available from: http://www. irena.org/publications/2018/jul/renewable-energy-statistics-2018. renewables. (2018), global status report, no. ren21. available from: http://www.ren21.net/wp-content/uploads/2018/06/178652gsr2018fullreportwebfinal.pdf. sundararagavan, s., baker, e. (2012), evaluating energy storage technologies for wind power integration. solar energy. 86(9), 2707-2717. timmons, d., harris, j.m., roach, b. (2014), the economics of renewable energy. global development and environment institute. medford, ma: tufts university. p52. bolyssov, et al.: features of the use of renewable energy sources in agriculture international journal of energy economics and policy | vol 9 • issue 4 • 2019368 united nations general assembly. (2015) the transformation of our world: an agenda for sustainable development for the period up to 2030. outcome document of the united nations summit. available form: https://www.unctad.org/meetings/en/sessionaldocuments/ ares70d1_ru.pdf. vandaele, n., porter, w. (2015), renewable energy in developing and developed nations: outlooks to 2040. journal of undergraduate research, 15(3), 1-7. yessengeldin, b., mukhamediyeva, g., sitenko, d., zhumanova, a. (2018), problems and perspectives of energy security of singleindustry towns of the republic of kazakhstan. international journal of energy economics and policy, 8(1), 116-121. . international journal of energy economics and policy | vol 8 • issue 5 • 2018 281 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(5), 281-287. oil exports and economic growth: an empirical evidence from saudi arabia zafar ahmad sultan1*, mohammad imdadul haque2 1department of economics; l.s. college, muzaffarpur; b.r.a. bihar university, muzaffarpur; bihar, india, 2college of business administration, prince sattam bin abdulaziz university, saudi arabia. *email: zsultan.sultan@gmail.com. abstract being an oil-based economy, the economic prosperity of saudi arabia to a large extent depends upon the international price of crude oil. a substantial portion of public revenue which determine the economic activities of the government comes from oil exports. oil exports are also important for earning the foreign exchange to fulfill the import requirements of the country. hence any disturbance in this sector is likely to affect the entire economy of saudi arabia. this paper applies johansen cointegration method to establish long run relationship of economic growth with oil exports, imports and government consumption expenditure. the study finds that economic growth has a positive long run relationship with oil exports, and consumption expenditure of the government. further, there is a negative long run association between imports and economic growth. finally, the study recommends regulating imports and intensive efforts to diversify economic base in import substituting industries. keywords: oil export, economic growth, causality, saudi arabia jel classifications: c22, f14, h50, n15 1. introduction fluctuation in petroleum prices and consequent fluctuation in export proceeds in oil-based economy like saudi arabia influence most of the macroeconomic variables. the four-fold increase in petroleum price in 1973 led to substantial increase in contribution of proceeds from oil exports in national income, balance of payment and government revenue of the country. these have made many favorable impacts on the economy of saudi arabia. increase in export proceeds augmented the foreign exchange reserves of the country. this enabled the country to import necessary consumer, capital and intermediate goods and services required for growing developmental and other needs of the country. further, owing to comfortable fiscal conditions, the government followed expansionary fiscal policy and increased government expenditure on various projects. the increased expenditure through its multiplier-acceleration linkages accelerated rate of economic growth in the 1970s. the favorable time, however, didn’t continue for long. during larger part of the 1980s and 1990s, the oil prices turned unfavorable for oil exporting countries including saudi arabia. this made an adverse impact on export revenue and economic growth of the country. the economy revived in the first decade of the 21st century with the rise in crude oil prices and export revenue. since 2012, the international price of crude petrol once again started declining that resulted in downward movement in export and government revenue. the effect of change in oil price and export proceeds is transmitted in the economy through import and public expenditure. though the classical economists were of the view that the public expenditure was unproductive and therefore the government restricted their activities to defense and for maintaining of law and order. they believed in laissez faire system and considered market forces as most efficient mechanism for the working of the economy. it was argued that money in the private hands would bring better returns. since public expenditure implies transfer of money away from private hands, this would result in inefficient utilization of national resources. in the 20th century, john maynard keynes had shown the importance of public expenditure in economic growth of the country. since then, the importance of public expenditure is realized and almost all the countries have witnessed a rising trend of such expenditure. sultan and haque: oil exports and economic growth: an empirical evidence from saudi arabia international journal of energy economics and policy | vol 8 • issue 5 • 2018282 there are people who argue that increase in public expenditure may negatively influence the level of investment and growth of an economy. they are of the views that increase in expenditure financed by higher taxes on households and firms would have dampening effect on aggregate demand. this would reduce net profits of the firms and hence investment. if the government finances its expenditure through borrowing from banks, this would put an upward pressure on rate of interest and would negatively affect the investment level in the economy. there are also people who favor public expenditure because of its positive impact on investment and other economic variables. interest rate is only one of the factors or cost components of investment besides level of educational development, transport facilities, availability of electricity, and income with the people etc. if public expenditure improves all these conditions, the investors would be motivated to invest more. further, more income with the people would increase the aggregate demand in the economy and thus would stimulate the level of investment in the economy. for the economy like saudi arabia, where tax is negligible, and capital with the government is not scarce, thanks to oil revenue, the government finances its expenditure without resort to either borrowing from the market or imposing additional taxes. the public expenditure is less likely to crowd out private investment. in fact, it is more likely to have positive impact on level of investment in the economy due to its backward and forward linkages and also by pushing up aggregate demand. because of this, fiscal policy in the form of public consumption expenditure has been an important policy instrument in country’s economic policy. the public consumption expenditure has increased from 3989 million riyal in 1970 to 183804 million riyal in 2000 and further to 73956 million riyal in 2014. this period also corresponds to rise in level of investment in the country. another important channel through which effect of oil exports is transmitted in the economy is import of consumers’ and producers’ goods and services. recent endogenous growth model has emphasized the role of imports through which new knowledge and technology is channeled to an economy. capital goods like machines and equipment embodying new technology comes into the economy, improves the productivity of labor and helps in accelerating economic growth (lee, 1995; mazumdar, 2001). if foreign exchange reserves are enough, import of high quality goods may expand production possibilities and promote economic growth (baharumshah and rashid, 1999). by stabilizing the price level, the import of essential consumer goods also helps in fostering economic growth through steadying the economy and boosting confidence among the investors. in the case of saudi arabia, sufficient foreign exchange reserves thanks to high crude oil prices in the 1970s and first decade of 21st century helped the country to import consumer as well as intermediate and capital goods. this would have facilitated the country to attain high rate of economic growth during the period as evident from relatively high rate of growth during the 1970s and 2003-2012 periods. there is other line of thinking too, with regard to effect of import on economic growth of the country. infant industry model argue that import may adversely affect the industrial growth of the country. lucas (1988) has also concluded that import may negatively impact economic growth of the country. since last few years, there is a downward pressure on the oil price and hence on the revenue generated from oil sector in saudi arabia. this would tighten the hands of the government in pursuing expansionary fiscal policy through increased public expenditure. this may also impact investment level and hence on employment and growth of the economy. keeping this in mind, the present study intends to examine the impact of oil exports on economic growth in saudi arabia. the rest of the paper is structured as follows. section 2 describes importance of public expenditure in saudi arabia. review of relevant literature has been discussed in section 3. next section discusses the model, data and empirical methodology. this is followed by analysis of empirical results. finally, the paper presents conclusion. 2. importance of oil sector in saudi economy saudi arabia is one of the largest and fastest growing economies of middle east and north african (mena) region. despite continuous efforts to diversify the economy, saudi remains primarily an oil based economy. oil contributes about 90% of government total revenues, about 88% of export earnings and about 35% of gross domestic product (gdp). along with the oil price, the share of this sector in government revenue and in gdp changes in same direction along the change in oil price. for example, during the 1990s the price of oil declined from 20.8 dollar per barrel in 1990 to 17.45 dollar per barrel in 1999, the contribution of this sector in gdp also declined from 20.8% in 1990 to 17.5% in 1999 and its contribution in gdp declined from 75.3% to 70.8% during the corresponding period. since 2000, the price of oil increased and the share of this sector in government revenue increased from 83.1% in 2000 to 91.8% in 2012 and the share in gdp increased from 40.5% to 49.9% in 2012. however, its contribution in total exports remained stable around 87–89% during the period. since then, however, as the price of oil declined, the share of oil sector in all these three variables also declined. this is also depicted in following figure 1. the revenue generated from the oil sector also helped the saudi government in following expansionary fiscal policy in the form of substantial increase in public expenditure. the public expenditure increased from 6273 million saudi riyal (sar) in 1970 to 284650 million sar in 1981. in the 1980s, however, due to decline in oil price the expenditure of the government decreased to 154870 million sar in 1989. in the 1990s, public expenditure fluctuated between 170000 million sar and 235000 million sar. in the new century, public expenditure increased from 235000 million sar in 2000 to 1109903 million sar in 2014 and then declined to 830513 million sar by 2016. the trends of consumption and capital expenditure are shown in figure 2. the diagram shows that with oil boom in 1972, the consumption and capital expenditure both increased but capital expenditure increased more rapidly than the consumption expenditure until 1981. during the period saudi government focused on financing different development projects like education, health, housing, transportation and telecommunication sultan and haque: oil exports and economic growth: an empirical evidence from saudi arabia international journal of energy economics and policy | vol 8 • issue 5 • 2018 283 services required for development of the country. since then, the capital expenditure shrank sharply following the decline in oil revenues due to decline in oil price and became lower than the current expenditure. the consumption expenditure during the 1980s declined marginally. the consumption expenditure once again picked up since 1994 later followed by capital expenditure since 1998, but the gap between the two widened. the consumption expenditure reached 736139 million sar in 2015. defense, education, general public service, economic service and health were the major components of consumption expenditure. education and health are the major areas which has attracted more attention of the government. their share has increased from 21% to about 30% and from about 6% to about 15% respectively during 1994 to 2015. 3. review of literature export has long been considered as an important tool for economic growth. it helps in accelerating economic growth by encouraging technical know-how (grossman and helpman, 1991), improves productivity of production factors (balassa, 1978; krueger, 1980), providing economies of scale (chenery and strout, 1966; helpman and krugman, 1985). many empirical studies have also been done to examine the relationship between exports and economic growth. jung and marshall (1985) found that export led to economic growth in the case of four out of 37 countries taken in the sample. el-sakka and al-mutairi (2000) in their study on 16 arab countries found mixed evidence of causal relationship between export and economic growth. for saudi arabia, he found export causing economic growth. hosseini and tang (2013) though found that oil and non-oil export have long run cointegration relationship with economic growth of iran and exports granger cause economic growth, oil export has negative impact on economic growth of iran. metwally and tamaschke (1980) investigated the role of oil exports in economic development of mena. their findings suggest that gross fixed capital formation is extremely sensitive to the growth in oil exports in all the countries under investigation except libya and kuwait. positive influence of oil exports on economic progress has also been found by adedokun (2012) in his study about nigeria. esfahani et al. (2009) while studying iranian economy found that the output in the economy is shaped by oil exports in the long run through its impact on capital accumulation. the link between public expenditure and economic growth in a country has been a subject of debate among economists for long. the classical economists viewed public expenditure as unproductive and wasteful and advocated to keep at minimum necessary level. keynes questioned this view and argued that the public expenditure may have positive impact on investment and growth of the economy. however, neo-classical economists again reinstated that it would retard the private investment and hence may affect the economic growth too. public expenditure financed by public debt and rising taxes would adversely affect private investment in an economy. public debt draws liquidity out of the market and given money supply pushes the rate of interest up and makes investment less profitable and less attractive. moreover, more public expenditure financed by higher taxes reduces capacity and incentive to save and invest, thus, retards private investment and growth. thus, on theoretical line there are different views regarding the impact of public expenditure on economic growth in an economy. these contrasting views incited many researchers to empirically examine the impact of public expenditure on investment and growth of an economy. devarajan et al. (1993) in the case of 69 developing countries observed that there is positive relationship between government current outlay and growth. the relationship between capital expenditure and growth, however, has been found to be negative. further, the defense and economic infrastructure had negative and significant relation with economic growth, while government outlay on health and education also had negative but insignificant relation with growth. devarajan et al. (1993) while examining the data of 43 countries of 20 years have found that the higher share of current spending is associated with higher growth while opposite is true for capital expenditure. alkhateeb et al. (2017) observed positive impact of public expenditure on income and employment of saudi arabia. wu et al. (2010) on the basis of study of 182 countries over a period of 55 years from 1950 to 2004 concluded that public expenditure affects growth positively for all countries except for low income countries. he was of the opinion that in low income economies the ineffectiveness of public spending owed to inefficient government and inferior institutions. landau (1983) concluded that increase in share of public spending in real gdp has adverse impact on growth rate of per capita gdp. negative effect of public expenditure on economic growth has also been found by other economists (romer, 1990; folster and henrekson, 1999). barro (1989) observed that increase in share of government consumption expenditure reduces per capita gdp while public investment has insignificant positive effect on growth. figure 1: share of oil sector in gross domestic product, export and government revenue source: saudi arabian monetary agency figure 2: trends of consumption and capital expenditure in ksa source: saudi arabian monetary agency sultan and haque: oil exports and economic growth: an empirical evidence from saudi arabia international journal of energy economics and policy | vol 8 • issue 5 • 2018284 alshahrani and alsadiq (2014) while investigating the effect of different types of public spending on growth found that government investment and expenditure on health affects the long run growth of saudi arabia and trade openness and expenditure on housing influences production in the short run. using cross section data of 58 countries, baum and lin (1993) analyzed the effect of expenditure on defense, education and welfare activities and concluded that growth rate of defense and education expenditure positively effect economic growth, but expenditure on welfare activities has insignificant negative impact on growth. number of studies has also been done to examine the relationship between import and economic growth. some of the studies have found import contributing positively to economic growth of a country. for example, baharumshah and rashid (1999) have observed that import of foreign technology has made a positive influence on economic growth of malaysia. humpage (2000) observed that imports accelerate economic growth of a country through specialization and transfer of technology. awokuse (2007) while examining the case of poland, bulgaria and czech republic took export as well as import in his model of growth and concluded that ignoring import may mislead our result. imports of intermediaries enhance productivity of domestic industries (grossman and helpman, 1991). imports lead to economic growth by promoting innovation and competition which finally lead to improved productivity in the economy (rodrick, 1999). gulati (1980) has argued that import of capital positively affects growth of an economy. however, the impact depends upon the degree to which the growth is inhibited by want of capital. imports’ contribution to productivity is more important than its contribution in terms of providing intermediate goods for industries (lawrence and weinstein, 1999). imports expose the country to the advances in technology and in the process increases productivity as well (kim and donghyun, 2007). however, lucas (1988) has arrived at different result about the impact of import on economic growth. he is of the opinion that growth occurs on account of learning by doing that takes place in export and import sectors. the export sector grows as the country has comparative advantage in this sector. but the import sector does not carry these benefits and suffers due to harsh competition with its competitors. thus, import may negatively affect economic growth. 4. model estimation, data and methodology being oil-based economy, the economic activities are to a large extent depends upon the proceeds from the oil exports. the proceeds from the oil exports depend upon the oil price. being inelastic demand on account of nature of the products, change in price has direct effect on revenue from oil exports. since oil sector constitutes more than 90% of total exports and government revenue, change in oil price and revenue from oil exports may also affect economic activities at macro level. imports play an important role in economic growth. import of capital equipment, intermediate goods, new technology and other inputs not only augments capital formation in the country, but it also improves the productivity level required for economic growth of the country. further, for a country like saudi arabia where agriculture and industrial sector are not so developed and diversified to fulfill the needs of the country, import of food and other consumer goods are also important to stabilize price level and accelerate economic growth. there may be other possibility too. import of goods may also adversely affect the growth of production within the country. this may have negative impact on economic growth of the country. exports of oil are also expected to promote economic growth. it provides foreign exchange that facilitates the import of necessary products and benefit economic growth of the country. besides, proceeds from oil exports are also dominant sources of public revenue which are used to finance various developmental and non-developmental expenditure of the government. increase in government spending push up the level of demand in the economy which calls for more investment in the economy. thus, we may expect positive relationship between public expenditure and economic growth of an economy. with this framework, following model may be constructed to estimate the relationship between oil exports, imports, government consumption expenditure and economic growth in the case of saudi arabia. gdpt=f (oexpt, impt, gcet) where, gdp refers to gross domestic product of saudi arabia, oexp symbolizes oil export from saudi arabia, imp represents imports in saudi arabia, gce denotes government consumption expenditure of saudi arabia, and t refers to time period. the data used in the study have been taken from saudi arabian monetary agency, international monetary fund and unctadstats. all the variables are in natural log form and have been converted into real values using gdp deflator. the paper has used the annual data from 1984 to 2015. since the data is time series data and since most of the macroeconomic variables show a kind of trend over time which makes application of ordinary least square method inappropriate, we need to examine unit root status of the variables and make sure that all the variables are integrated of same order. for the purpose, augmented dicky-fuller test and philips-perron tests will be used. having found that the variables are integrated of same order, johansen cointegration method will be applied to estimate long run equilibrium relationship between the variables. if cointegration relationship is found among the variables, we apply vector error correction model (vecm) to find the causal relationship between employment and other variables. the negative and significant lagged error correction term would show the long run causal relationship while the joint significance of first differenced coefficient captures the short run causal effect of the variables. sultan and haque: oil exports and economic growth: an empirical evidence from saudi arabia international journal of energy economics and policy | vol 8 • issue 5 • 2018 285 5. empirical analysis it is evident from the results given in tables 1a and 1b that all the variables considered for the study have unit roots at level. however, the hypothesis of presence of unit root is rejected when these variables are tested at first difference. this implies that all these variables are integrated of first order. thus, this study proceeds with johansen’s cointegration to study the long run cointegration of economic growth of saudi arabia with oil exports, imports and government consumption expenditure. selection of appropriate number of lag period is important to get more frugal results. one period lag has been selected to estimate cointegration on the basis of schwarz information criteria given in table 2. the result of cointegration test at one period lag is shown in tables 3a and 3b. the result shows that trace statistics and maximum eigen statistics for null hypothesis of no cointegration relationship between the variables are greater than their respective critical values at 5% significance level, thus rejecting the hypothesis of no cointegration and accept that there is at least one cointegration relationship between the variables. further, the null hypothesis of at most one cointegration relationship is rejected on the basis of trace statistics but the hypothesis is accepted on the basis of maximum eigen value which is less than their critical value. thus, we may confirm that there is a long run cointegration relationship between economic growth, oil exports, imports and public consumption expenditure. the cointegration equation obtained by normalizing the coefficients shows that oil exports and government consumption expenditure have positive and significant relation with the economic growth of saudi arabia. the result thus confirms our propositions made above and is in line with the findings of most of the studies reviewed. the imports, however, have been found to have negative impact on the economic growth of saudi arabia in the long run (table 4). this result has however been different from most of the studies reviewed and is in line with observations of lucas (1988) which shows that import retards growth of domestic industries to flourish. determining that the variables are cointegrated we may proceed to causality analysis through vecm. the results are given in table 5. various diagnostic tests like serial correlation test, heteroskedasticity test and normality test verify that the model is stable. in the table we observe that the lagged error correction term is negative and significant. this advocates that in the long run oil exports, imports and government expenditure granger cause economic growth in saudi arabia. long run causality suggests that more exports lead to increase in economic growth of the country. further the proceeds also enable the government to spend more which through multiplier effect accelerates economic growth. increase in export revenue brings more foreign exchange and improves the balance of payments position of the country. conversely, the economy will suffer an adverse impact if these explanatory variables move in opposite direction. the implication of such findings is that saudi arabia will suffer slowdown in its economic growth because of decline in proceeds from oil exports owing to present low level of international prices. the result of block exogeneity wald test (table 6) indicates that only imports granger cause economic growth in the short run while oil exports and government expenditure does not. the reason may be that the government might have used the surpluses accumulated over the years to overcome any decline in export proceeds from oil exports arising out of fall in oil prices in international market. 6. conclusion over the past few years the price of oil is witnessing a downward movement which has led to a decline in the export revenue from table 1a: unit root test result (adf test) variables level first difference c c and t none c c and t none gdp −2.204910 −2.699960 0.491381 −7.154780* −7.540792* −7.181090* oexp −1.450251 −1.462319 0.653398 −5.064702* −5.336535* −4.991367* imp −1.565269 −1.980728 0.524896 −7.585480* −7.452266* −7.490084* gce −0.742469 −1.959921 1.445707 −6.154693* −6.059727* −5.723380* critical values (%) 1 −3.653730 −4.273277 −2.639210 5 −2.957110 −3.557759 −1.951687 10 −2.617434 −3.212361 −1.610579 *denotes significant at 1%. gdp: gross domestic product, adf: augmented dicky-fuller table 1b: unit root test result (pp test) variables level first difference c c and t none c c and t none gdp −2.203884 −2.661108 0.597367 −6.944277 −7.317392* −6.982065* oexp −1.453822 −1.770033 0.649511 3−5.062472 −5.528440* −5.001875 imp −1.450329 −1.942508 0.524896 −7.340993* −7.228353* −7.257065* gce −0.742469 −1.982901 1.727708 −6.160346* −6.088576* −5.723176* critical values −3.653730 −4.273277 −2.639210 −2.957110 −3.557759 −1.951687 −2.617434 −3.212361 −1.610579 *denotes significant at 1%. pp: philips-perron sultan and haque: oil exports and economic growth: an empirical evidence from saudi arabia international journal of energy economics and policy | vol 8 • issue 5 • 2018286 petrol. since this sector generates about 90% of export and budget revenue in saudi arabia, the economic growth is expected to get affected as public expenditure, imports all are determined by the revenue from petroleum sector. this study tries to examine the impact of decline in oil price by estimating the association between oil exports, imports, government consumption expenditure and economic growth in saudi arabia. using johansen cointegration and vec model, the results show that economic growth has long run relationship with oil exports, imports and government consumption expenditure. further, oil exports positively and significantly affect economic growth in the short run as well as in the long run. the government consumption expenditure also has positive and significant association with economic growth in the long run. the effect of imports, however, has been found to be negative and significant in the short run as well as in the long run. this is the only unexpected result which emerged from this and validates the opinion of lucas (1988). imports are hypothesized as source of capital and intermediate goods for growth of industries, and that it improves productivity through improved technology. but, import has been found to be adversely affecting economic growth in saudi arabia. imports are just meeting the demands of the consumers but not leading to any productivity or growth in the economy. a plausible justification may be that imports outcompete the domestic sectors and hence do not let the domestic industries grow in the non-oil sector. this indicates that in spite of government efforts the country has not been very successful in diversifying its economy. the oil sector continues to dominate in saudi’s exports as well as in gdp. their share moves along the direction of change in international prices of oil. the study suggests that the country should monitor and rationalize imports so that domestic economy grows on a sustainable growth path. references alkhateeb, t.t., sultan, z.a., mahmood, h. (2017), oil revenue, public spending, gross domestic product and employment in saudi arabia. international journal of energy economics and policy, 7(6), 27-31. table 2: lag selection lag logl lr fpe aic sc hq 0 20.37070 na 3.80e-06 −1.129014 −0.940421 −1.069949 1 109.0279 146.7430 2.57e-08 −6.139856 −5.196893* −5.844532 2 131.6027 31.13767* 1.75e-08* −6.593291* −4.895958 −6.061707* 3 140.5791 9.904952 3.44e-08 −6.108902 −3.657199 −5.341059 *indicates lag order selected by the criterion table 3a: johansen’s cointegration lags interval (in first differences): 1 to 2 unrestricted cointegration rank test (trace) hypothesized no. of ce(s) eigen value trace statistics 0.05 critical value prob.** none * 0.791324 92.75626 63.87610 0.0000 at most 1 * 0.553136 45.74702 42.91525 0.0254 at most 2 0.408795 21.58200 25.87211 0.1561 at most 3 0.176184 5.814239 12.51798 0.4843 trace test indicates 2 cointegrating eqn(s) at the 0.05 level table 3b: johansen’s cointegration unrestricted cointegration rank test (maximum eigen value) hypothesized no. of ce(s) eigen value max-eigen statistic 0.05 critical value prob.** none * 0.791324 47.00924 32.11832 0.0004 at most 1 0.553136 24.16502 25.82321 0.0815 at most 2 0.408795 15.76776 19.38704 0.1554 at most 3 0.176184 5.814239 12.51798 0.4843 maximum eigen value indicates 1 cointegrating eqn(s) at the 0.05 level. *denotes rejection of the hypothesis at the 0.05 level. **mackinnon-haug-michelis (1999) p values table 4: estimate of long run co-integrating vector normalized coefficients gdp oexp imp gce c trend 1.00 −0.320311* 0.654095* −1.259013* −3.420778 0.054643* t-values −2.51266 4.73789 −6.01262 6.91643 *indicates significant at 1%. gdp: gross domestic product table 5: vecm variables coefficients standard error t-values ect(-1) −0.519567* 0.07989 −6.50393 d(gdpt(-1)) −0.256229 0.14684 −1.74500 d(lgcet(-1)) 0.053873 0.19829 0.27169 d(oexpt (-1)) −0.107382 0.07835 −1.37058 d(impt (-1)) −0.286135 0.15683 −1.82446 r2=0.695064. lagrange multiplier (lag 1)=(0.4086), (lag 2)=(0.5655), (lag 3)=(0.8878), breusch-pagan-godfrey test=(0.7053), jarque-bera test=(0.4441).*indicates significant at 1%; figures in small parentheses show p values. vecm: vector error correction model table 6: vec granger causality/block exogeneity wald tests: economic growth as dependent variable independent variable oexpt impt gcet joint chi square (p-values) 0.1705(1) 0.0681(1)*** 0.7859(1) 0.0675(3)*** *symbolizes significant at 10%. figures in small parentheses shows degree of freedom sultan and haque: oil exports and economic growth: an empirical evidence from saudi arabia international journal of energy economics and policy | vol 8 • issue 5 • 2018 287 alshahrani, s.a., alsadiq, a.j. (2014), economic growth and government spending in saudi arabia: an empirical investigation. international monetary fund. imf working paper no. wp/14/3. available from: https://www.imf.org/external/pubs/ft/wp/2014/wp1403.pdf. awokuse, t.o. (2007), causality between exports, imports and economic growth: evidence from transition economies. economics letters, 94, 389-395. baharumshah, a.z., rashid, s. (1999), exports, imports and economic growth in malaysia: emprical evidence based on multivariate time series. asian economic journal, 13(4), 389-406. balassa, b. (1978), export and economic growth: further evidence. journal of development economics, 5, 181-189. barro, r. (1990), government spending in a simple model of endogenous growth. journal of political economy, 98, 103-125. baum, n.d, lin, s. (1993), the differential effects on economic growth of government expenditures on education, welfare, and defense. journal of economic development, 18, 75-185. chenery, h., strout, a. (1966), foreign assistance and economic development. american economic review, 56, 679-733. devarajan, s., swaroop, v., zou, h. (1993), the composition of public expenditure and economic growth. journal of monetary economics, 37(2), 313-344. devarajan, s., swaroop, v., zou, h. (1993), what do government buy: the composition of public spending economic performance. working paper, wps (1082). available from: https://www.researchgate. net/publication/23548478_what_do_governments_buy_the_ composition_of_public_spending_and_economic_performance. el-sakka, m.i., al-mutairi, n.h. (2000), exports and economic growth: the arab experience. the pakistan development review, 9(2), 153-169. esfahani, h.s., mohaddes, k., pesaran, h. (2009), oil exports and the iranian economy. iza discussion paper no. 4537. available from: https://www.d-nb.info/998333212/34. folster, s, henrekson, m. (1999), growth and the public sector: a critique of critics. european journal of political economy, 15(2), 337-358. grossman, g.m., helpman, e. (1991), innovation and growth in the global economy. cambridge ma: mit press. gulati, u.c. (1980), effect of capital imports on savings and growth: reply. economic inquiry 16(3), 519-522. helpman, e., krugman, p. (1985), market structure and foreign trade. cambridge ma: mit press. hosseini, s.m.p., tang, c.f. (2014), the effect of oil and non-oil exports on economic growth: a case study of the iranian economy. economic research, 27(1), 427-441. humpage, o.f. (2000), do imports hinder or help economic growth? economic commentary. cleveland: federal reserve bank of cleveland. international monetary fund. (2017), world economic outlook (weo) database. available from: https://www.knoema.com/ imfweo2017oct/imf-world-economic-outlook-weo-databaseoctober-2017?tsid=1055980. jung, w.s., marshall, p.j. (1985), exports, growth and causality in developing countries. journal of development economics, 18(1), 1-12. kim, s.h., donghyun, p. (2007), could imports be beneficial for economic growth? some evidence from republic of korea. erd working paper series, no. 103 provided in cooperation with. manila: asian development bank (adb). krueger, a.o. (1980), trade policy as an input to development. american economic review, 70, 288-292. landau, d. (1983), government expenditure and economic growth: a cross-country study. southern economic journal, 49, 783-797. lawrence, r., weinstein, d. (1999), trade and growth: import-led or export-led? evidence from japan and korea, nber working paper no. 7264. cambridge: national bureau of economic research. lee, j.w. (1995), capital goods imports and long-run growth. journal of development economics, 48(1), 91-110. lucas, r.e. (1988), on the mechanics of economic development. journal of monetary economics, 22(1), 3-42. mazumdar, j. (2001), imported machinery and growth in ldcs. journal of development economics 65, 209-224. metwally, m.m., tamaschke, h.u. (1980), oil exports and economic growth in the middle east. kyklos, 33(3), 499-522. rodrik, d. (1999), the new global economy and developing countries: making openness work. overseas development council policy essay number 24. washington, dc: johns hopkins university press for the overseas development council. romer, p.m. (1990), endogenous technological change. journal of political economy, 98, 71-102. saudi arabian monetary agency (2016). annual statistics. available from: http://www.sama.gov.sa/en-us/economicreports/pages/ yearlystatistics.aspx. unctadstat. (2015), available from: http://www.unctadstat.unctad. org/wds/tableviewer/downloadprompt.aspx. wu, s., tang, j., lin, e.s. (2010), the impact of government expenditure on economic growth: how sensitive to the level of development. journal of policy modeling, 32(6), 804-817. . international journal of energy economics and policy | vol 8 • issue 3 • 2018 141 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(3), 141-149. impacts of regulatory transformation processes to the downstream oil market in turkey erol seyfi metin1*, gürkan kumbaroğlu2,3 1sem sustainability, energy, management, secretary general at boğaziçi, university energy policy research center epam, 34342 bebek, istanbul, turkey, 2boğaziçi university, professor of industrial engineering and director at energy policy research center epam, 34342 bebek, istanbul, turkey. *email: erol.metin@semenerji.com abstract this paper is a review of the regulatory transformation process of the turkish downstream oil industry with an emphasis of effect regulatory forces to the pace of financial interactions. the regulatory transformation process has been analysed in terms of its effects on large scale financial transactions, in the form of merges and acquisations. the paper reviews a period of 15 years, during which the turkish oil market has gone through a fundamental regulatory restructuring process from a state governed industry to a regulated market. during this period, oil market law, lpg market law and secondary regulations implemented, an independent regulatory authority established, fuel prices were left to the dynamics of market forces, structural reforms have been implemented and the competition authority provided guidance to increase the level of competition. this comprehensive restructuring and liberalisation process was essentially a multidimensional transformation process of the turkish downstream oil industry. during the initial years of this transformation process, there were strong signs of motion towards a fully liberalised downstream market and the players have responded by several, medium to large scale financial transactions in the form of merges and acquisations. as the winds shift toward a regulated market rather than the full libearisation, the level and the period of these financial transactions have slowed down. however, the overall result of this transformation is strong and sustained growth, improved quality and safety implementations, increased investments and financial transactions. the market practically doubled in financial volume, an average of 6.25% growth in automotive fuels for a period of 15 years has been achieved. the last 56 years of this transformation process however, is marked with interventions from both the regulatory authority and the competition board, which was responded by the market in the form of substantially reduced investments, lower levels of profits and therefore lower investments in addition to exit decisions of some major international of oil companies. keywords: downstream oil industry, turkish oil market, investments and transactions, growth, regulatory effect, fuels market jel classifications: je31, e61, k2, l11 1. introduction the effect of privatizations and liberalization in different markets have been subject to intensive research. economic theory indicates that liberal markets establish the basis of the real functioning markets and therefore attracts investments by levereging opportunities for profit and market growth. it is accepted that more open economies enjoy higher rates of private investment which is good for foreign direct investment (fdi) as well as economic growth. over the last 30 years, where opennes and liberalism became the vision of several developing countries, where they have more than doubled their growth compared to more closed economies (bloomstoern et al., 1994; sachs and warner, 1995; stiglitz, 2000; oecd, 1998; mann, 2007). on the other hand the emprical relationship between the fdi and economic growth as well as opennes has been well studied and proven that fdi not only improves the economic growth but also affects the productivity spillovers. in general it is accepted that there is a unidirectional casual relationship between fdi inflows and growth. kandilov et al. (2016); shaghil and zlate (2014) have, in their recent review, claimed the differential between the growth and interest rate is statistically and economically important determinant of net private capital. liberalisation have proved to contribute capital markets in develoing countries, and also to the investments and capital accumulation. based on clear evidences and strong scientific proofs of direct contribution to growth and fdi, liberalization has metin and kumbaroğlu: impacts of regulatory transformation processes to the downstream oil market in turkey international journal of energy economics and policy | vol 8 • issue 3 • 2018142 even become a negotiation point in several bilateral investment treaty negotiations and regional free trade agreements mann (2007); kandilov et al. (2016). wi t h t h e s u p p o r t a n d e n c o u r a g e m e n t o f i n t e r n a t i o n a l organizations like the world bank, turkey has also initiated a comprehensive program to liberalize and privatize the energy markets starting with electricity market in 2001. the liberalization of the energy markets in turkey has begun with oil markets and electricity markets. electricity market law which was enacted in 2001, marked the beginning of energy market liberalization in turkey. in the same year the energy market regulatory authority was established which would later serve to enact critical regulations both for the organization of the energy market and for its liberalization. bahçe and taymaz (2008) have studied the impact of electricity market liberalization to the investments in turkey. in oil industry of turkey, however, there are limited references on the role of liberalization and the regulatory environment on the growth and investments, except some important industry reports bahçe and taymaz (2008), world petroleum council (2016), petder (2015); turkish oil market annual report (2016), that deals more with the overall shape of the industry. the aim of this publication is, therefore, to provide an overall review of the implications of the regulatory transformation process from a state-owned and state-operated market to a regulated market with initial intentions of full liberalization specific to downstream oil industry in developing countries, that seems to be missing in nature, especially for turkey. in order to asses the impact of the regulatory moves, some key market indicator data gathered such as market volume, pricing on daily basis, profit margins, number of operators, level of competition, major merge and acquisition processes, i.e., to fill this gap. the mapping of these indicators with the regulatory transformation process yields unidirectional and clear indicators of how markets respond to liberation and how these responses change as the regulatory pressure increases. in this context, the level of consumptions of oil and oil products, profit margins, elements of taxation and level of competition have been the main indicators used to assess the impact of the regulatory transformation processes. 2. the liberalization process of turkish downstream oil industry turkish downstream oil industry has gone through a fundamental restructuring process starting from a state governed market towards a liberal market, with the introduction of the oil market law in december 2003. the law was aimed to liberalize the downstream oil and lpg industries of turkey, through free pricing and by removing trade limitations between market players. in addition, energy market regulatory authority (emra), an independent regulatory authority was established to implement a new registry and licensing system, monitor the oil market and introduce necessary technical standards. the following section provides and overall view of the oil market law and the lpg market law as published in official gazette (oil market law, the official gazette no 5015 december 13, 2003). 2.1. oil and lpg market laws, the liberalisation process turkish oil market law has been published in the official gazette no 5015 in december 2013. the objective of the law, as stated in the law, is “to regulate the guidance, surveillance and supervision activities in order to ensure the transparent, non-discriminatory and stable performance of market activities.” the law therefore aimed to liberalise the downstream oil market and to implement a new market registry system. the new law required all players to hold a license, (effective after publication of the license regulation), gave authority to the energy market regulatory authority (emra) to issue regulations and defined operational principles of the players along with restrictions and penalties. one important section of the law was related with the pricing of oil products that “the pricing for the purchase and sales of petroleum shall be constituted according to the nearest accessible global free market conditions,” which have caused unending debates around the definition of nearest accessable free markets, and the power of the regulatory authority to rightfully intervene as stated in the following clause of the law; “in case that the risks arising from agreements and activities aimed at or may result in hindering, disrupting or restricting the competitive environment and delivery in the petroleum market, the authority shall be authorized to determine base and/or ceiling price(s) and take necessary measures to apply on regional or national basis in all phases of activities not exceeding 2 months in each time.” these statements have been the focus of long standing debates between the players and regulators. this debate has peaked especially when the authroities decided to implement hard measures on the market such as price caps and change the validity period of exclusive contracts between the dealers. the new elements of this new law could be grouped around free entry, registry systems, governance of the market by an independent authority, operational rights, restrictions and limitations of players and principles around fuels pricing. in this perspective, altough the main intention in legislating the law had been claimed to liberate the market, because of the certain restrictions imposed after the implementation period and the way it has been governed, the downstream oil market in turkey can now be defined as a regulated market, even sometimes referred as a heavily regulated market petder (2015). altough the initial aims vs the final results of this regulatory transformation process are somewhat different, the process displayed a good example of how market players respond to regulatory changes in the market. another important aim of the law was to reduce the illegal fuels activities, smuggling, illicit fuels and tax evation in oil market. the size of illegal activities was estimated to be as high as 3.0 million tons, leading to approximately usd 3.0 billion in tax losses annualy petder (2015). in order to cope with this big problem several technological instruments such as national marker implementation, compulsory tank and pump automation systems, compulsory cash registry systems and exclusive contracts between dealers and distribution companies have been implemented. as would be indicated later in this publication, these regulatory measures have proved high level of success in reducing and controlling the illicit fuels issue in turkey. metin and kumbaroğlu: impacts of regulatory transformation processes to the downstream oil market in turkey international journal of energy economics and policy | vol 8 • issue 3 • 2018 143 apart form gasoline and diesel, auto lpg is also widely used as automotive fuel in turkey and therefore any assessment of the fuels market in turkey has to involve lpg products as well. lpg market law has been published in april 2014 (oil market law, the official gazette no 5015 december 13, 2003), some months after the oil market law, with some practical differences. the lpg market law has similar elements such as free market entry, registry systems, governance of the market by an independent authority (emra), operational rights, restrictions and limitations of players. main differences with the oil market law however, were due to pricing mechanisms, the national marker implementation and the rights of authorities to intervene with the market. the objectives and the general structure of the two laws are quite similar to each other, apart from some certain differences regarding the technical specifications of the oil and lpg products. 2.2. secondary regulations of the oil and lpg markets in order to assess the role of regulatory shift towards a liberal market to the behavior of market players, the period between 2000 and 2016 has been chosen, during which there are periods of state owned, liberal and regulated market forces. as described above, by law, emra is given the role to monitor and regulate the oil and lpg markets. in essence this role is not specific to oil and lpg markets but applicable to natural gas, electricity and renewables, i.e., energy markets as a whole. emra, as an independent authority is the key regulating actor in energy markets of turkey. upon enactment of oil and lpg market laws, emra has issued several regulations to restructure the oil industry, by virtue of the authority vested themselves by the law. among several regulatory initiatives that emra has published so far, the most important secondary regulations that has shaped the downstream oil industry are briefly summarized in the following. 1. licensing regulation (official gazette 17.06.2004 no 25495): the regulation requires all market players in the oil industry, i.e., refineries, distribution companies and dealers as the main market players, are required to receive their operational licenses from the authority, emra. the type of license not only defines the player’s rights and restrictions but also specific to the activity type, i.e., depots, refining, distribution, resale, dealer site are all different activity types that needs to be specified in the relevant licenses. 2. technical criteria regulation for oil markets (official gazette 10.09.2004 no 25579): this regulation mainly defines the technical specifications, quality assessment and reporting procedures of the fuel products to be marketed. 3. energy markets reporting regulation (official gazette 09.12.2005 no: 26018): players of the oil market have to report periodically to emra on their activities, i.e., sales, changes in dealers structures, oil stocks and other relevant information as a part of their license requirements. 4. national marker implementation regulation in oil markets (official gazette 12.04.2004 no 26137): national marker is an important tool that has been successfully implemented in order to avoid smuggled and illicit fuels to enter into the market. turkey has proved a good and successful implementation in marking fuel products. this regulation defines how, when, where and which type of fuel products will be blended with the national marker. 5. oil markets pricing system regulation (official gazette 17.07.2004 no 25525): the pricing regulation, defines how the players of the market, should structure, report and implement their pricing systems. although in principle having a regulation defining the pricing structure is considered to be against the free market principles, and therefore may not in full compliance with the spirit of the oil market law, the regulation intends to provide transparent pricing information systems for the public. 6. inspection and auditing regulation in oil markets (official gazette 06.01.2005 no 25692): this regulation defines the rules and principles around the inspection and auditing assessments in the oil market. the regulation includes the financial penalties in case the defined structure is not obeyed. 7. it security regulation on industrial control systems in energy markets (automation) (official gazette 09.12.2005 no 26018): the regulation is devised to establish electronic control systems of the players in the market, such as pump automation systems. combined with the national marker implementation, this regulation provides an important tool in eliminating fuel smuggling problems in turkey. the regulatory structure that the operators must obey, is not limited to the above list. there are several other decisions, comminique’s and other regulatory requirements that the players must obey. as apparent from the content of the main driving secondary regulations listed above the turkish oil market has become a regulated market (although the original intention behing the law was to fully liberalize the market). while these laws and regulations, starting from 2003, become effective one after another, the market started its own journey from a state operated market to a liberal market and then, to a regulated market structure. therefore the period taken as the focus of this paper defines simultaneous regulatory transformation processes which provide a unique example of responses of market players to the regulatory changes. the size of the oil products market in turkey (2015) is around 35 million tons. the fuels consumption in 2015 is shown in table 1, where diesel fuel is the main driver of the market, gasoline production by the refineries is in excess of local demand and the market is short in diesel fuels and relies on imports, as shown in figure 1 petder (2015); turkish oil market annual report (2016). the total oil consumption has remained fairly constant over the last 15 years, because of the strong shift from black products (fuel oils) to natural gas. if this effect is separated and the market have been evaluated only in terms of automotive fuels or white products, then the growth in the market is substantial. figure 2 represents the overall turkish downstream oil market, for the last 15 years. emra, the energy market regulatory autohority, publishes fairly detailed and high quality reports on monthly and annual basis, for both oil and lpg products. the reports are detailed such that they include, overal volume growth on products basis, trade movements, market sales from refineries, distributors, consumption data on regional basis in addition to pricing information in regional basis. the wide scope, detailed content and continuity achieved with these reports are indicative metin and kumbaroğlu: impacts of regulatory transformation processes to the downstream oil market in turkey international journal of energy economics and policy | vol 8 • issue 3 • 2018144 of the degree of progress that markets have achieved over 15 years of regulatory transformation. the growth of the market for gasoline and diesel products is mainly achieved by increased fuel demand due to growth of vehicles sales in addition to increase in demand of aviation fuels. the consumption trends of oil products, mainly automotive fuels, mark significant growth over last decade as shown in figure 2. the consistent growth in automotive products can be observed predominantly in the last 5 years (figure 2b). overall growth achieved in automotive fuels consumption, gasoline, diesels and auto lpg (excluding the aviation) in 15 years period (2000-2015) is averaged to 6.25% per annum, which is strong growth figure exceeding gross domestic product (gdp) growth. when the market growth, sustained over 15 years, combined with the positive winds of privitization and liberalization efforts, the turkish oil market has enjoyed large size investments, market entrys from new players and increased competition and quality in the market, which is discussed in the following section. 2.3. the impact of liberalization and regulatory transformation process on the investments in the previous section we have provided input with regards to the trends in the market volume and the regulatory structural cahange that took place over the last 15 years. important dates and events of the liberalization process are shown in the following table and figure 3 (time chart) to demonstrate the impacts of changes in regulatory processes on the level of financial activities in the market. if the period starting from the point of first important privitization in the industry, (i.e., year 2000, the privitization of petrol ofisi, the state owned operated distribution company, the leader of the market with 35% market share) to mid 2017 is table 1: an overall view of the turkish oil market, 2015 data turkish oil market annual report (2016) data in table is given in 1000 tons fuel type production total imports exports total supply (imports+refinery+output) total demand gasolines 5.113.058 0 3.115.474 5.113.058 5.212.722 diesel fuels 8.509.777 11.884.892 27.526 20.394.669 20.601.315 fuel oil types 547.712 919.709 982.337 1.467.421 1.586.391 marine fuels 2.344.697 75.954 2.434.117 2.420.651 2.616.816 aviation fuels 5.024.287 180.571 3.757.478 5.204.858 5.076.719 total 21.539.531 13.061.126 10.316.932 34.600.657 35.093.963 figure 1: supply balance of oil products. (note that exports in aviation and marine fuels are demand from intrenational flights and vessels figure 2: the growth of consumption of oil products (a) and automotive fuels (b) in turkey (tons) petder (2015) a b metin and kumbaroğlu: impacts of regulatory transformation processes to the downstream oil market in turkey international journal of energy economics and policy | vol 8 • issue 3 • 2018 145 reviewed, with a focus on cjanges in the regulatory envieonment and the financial transactions as an indicator of market interest, one can clearly see that the market has enjoyed multiple and large sized financial transactions in terms of merges and aquisations, buy outs and privatizations, especially in the early years of liberation and privatization. the magnitude of these financial transactions in the market are listed in the table 2. in addition, these important events are shown on a time chart, to demonstrate the linkage between the degree of liberalization or government interventions to the level of financial transactions in the market, or even the decisions to exit the market. the above chart demonstrates the close interaction between the regulatory drive and the response of the market players. the upper layer shows important regulatory initiatives of the authorities, such as liberalization and or interventions and the below layer shows the type of important market activity, or in other words the response from the market players. immediately after the process of privatization, in years 2000–2005, with strong indications of market liberalization which then followed with the implementation of the law that aims market liberalization, the immediate response of the players was in the form of large scale acquisations and buy outs. table 2: important financial transaction of the turkish oil market following the privitizations and new market law year event transaction value notes 2000 privitazation of petrol ofisi usd 1.160 billion for 51% of shares po is the market leading distribution co. with 35% market share 2002 koç and opet m&a usd 0,125 billion for 50% of the shares koç group has acquired opet, a fast growing local co 2005 tüpraş privitization usd 4.140 billion tüpraş is the only refinery company in turkey with 4 main refineries 2006 shell and turcas petrol ma usd 0,370 billion with 70-30 shares shell and turcas established a new co 70-30% partnership 2006 omv bought po shares usd 1.054 billion omv bought 34% of po shares from dogan 2008 lukoil and akpet m&a usd 0,5 billion lukoil has purchased akpet, that had market share of 4.5% 2010 omv bought remaining shares of po €1.0 billion omv has bought remaining shares of dogan group (54.17) shares in po to reach 95.75% share ownership 2013 star refinery investment anouncement usd 5.6 billion socar group has anounced the investment desicion for refinery in i̇zmir 2015 total’s exit anouncement € 0.325 billion demiroren, a local lpg company purchased total’s fuel operations in turkey 2016 omv’s exit anouncement 2016 turkuaz has bought tp usd 125 mililon turkish fuels company turkuaz has bought state owned turk petrol 2017 vitol has purchased shares of po € 1.368 billion for the shares of omv vitol has purchased omv’s fuel facility in turkey figure 3: comparison of regulatory changes in the oil market and market responses in the form of important investments and financial transactions metin and kumbaroğlu: impacts of regulatory transformation processes to the downstream oil market in turkey international journal of energy economics and policy | vol 8 • issue 3 • 2018146 during the period between 2000 and 2009, strong winds of liberalisation and free market commitments from the government has triggered significant investment and financial transactions in the downstream oil and lpg market. as can be seen in table 1, the market has enjoyed multiple large sized financial transactions, such as, merge and acquisitions, investments and buy outs. although not listed in the table, the market has enjoyed additional investments in the form of advanced level of marketing tools, investments into new fuels products and refining technologies, improvements in quality and customer service programs, investments made for the retails sites, storage facilities, refining process improvements and even transport systems. a simple market estimation of such additional site, process and quality investments is likely to be more than usd 5 billion. for example, tüpraş refineries, just by itlsef, is accountable of usd 3.0 billion of these additional investmenst due to process modification investment, in the form of hydrocrackers and conversion from fuel oil to products, which made tüpraş highest nelson complexity in the refining market. starting from 2009 to 2010, the regulatory transformation process and therefore the investment apetitie in the market has slowed down mainly due to interventions of the regulatory authority in the form of price cap implementations that effected profit margins, in addition the competition authority’s decision to limit the contract periods. during the period between 2005 and 2009, with the start of liberalization winds, as the markets became more fluid and free, the profit margins had increased consistently, which then caused the authorities to intervene by imposing temporary and short term price caps, that has directly affected the gross retail margin. the first of these price cap interventions has taken place in 2009, when the gross retail/distribution margin had raised up to 30 cents/l from the 7 cents/l level before the price liberation. before january 2005, the price liberation, the gross industry margin was being set by the government and typically in the range of 5 to 7 cents/l, regardless of the price of the product or the exchange rate. the following graph (figure 4) shows the remarkable changes in the gross industry margins, as a function of the change of regulatory environment. the 2009-2015 period was consisted of several interventions in the form of price caps in addition to the competition board’s decision to limit the contract periods. during that period, the fuels market has been marked with three price interventions by emra. the first intervention (2009) was made on the claims that players are constantly increasing their margins with no practical market reasons and this exceeds the objectives of the law. the price cap was applicable for 2 months period and has caused the gross retail margin drop from about 30 cents/l to 22 cents/l. the intense discusions around this price intervention, whether it is in parallel with the law’s jurisdiction, triggered further debate on the level of competition in the market being too low as claimed by the competition authority competition board of turkey, fules sector report (2008) in their fuels sector report. immediately after the price intervention of emra, the competition authority’s claim that the exclusive contracts signed between the dealers and distribution companies are too long, generally 15-20 years sometimes extending beyond 30 years creating market entry difficulty, reducing the level of competition in the market was another important source of debate. almost immediately after the price cap intervention by emra, the competition board decided competition board, comminique. (2002), in april 2010, to limit the contract period between the distribution companies and the dealers to 5 years. the competition board’s decision to limit the validity period of the exclusive dealership contracts between the distribution companies and the dealers, to 5 years, was applicable to already signed contracts, required retroactive implementation and therefore created serious of discussions, court cases between the industry and the authorities, mainly around the concept of liberalization and continuous interventions and retroactive legislations. in assence, the main impact of the competition board’s decision was on the market value of the distribution companies, since the market value of the retail companies are directly related with the number of contracts and the validity periods of these contracts. this period (the period between 2009 and 2015) is marked with debates around interventions leading to loss of investments and diversion of international funds from turkish oil market. as an outcome of these negative signals, important decisions came from total and omv where both companies have publicly anounced that they will be divesting figure 4: gross distribution (retail) margin in automotive fuels, as a sum of gross marging of distributors and dealers metin and kumbaroğlu: impacts of regulatory transformation processes to the downstream oil market in turkey international journal of energy economics and policy | vol 8 • issue 3 • 2018 147 their assets (http://www.sabah.com.tr, http://www.hurriyet.com. tr) and these anouncements have turned into action by the recent transactions that took place between total and demiroren (a local company operating mainly in lpg business) and omv and vitol (po transaction). the widespread news in the market as well as in the media was that continuous interventions leading to serious financial losses in distribution companies were the main reason behind this exit decisions. on the other hand, again during the very same period, turkish oil market has witnessed another refinery investment decision by socar and a successful privatization of the turkish petroleum distribution company, which can be considered as decisions supporting the counter arguments. the size of impact of market interventions, in the form of price caps, can be better explained when the industry margins and sales volumes are considered together on an annual basis. although the price caps were implemented for a period of 2 months, the recovery period of gross retail margins extends to several months and even to several years. figure 4 shows the variation of gross industry margins over a period of more than 15 years, which clearly demonstrate the significance of the impact in three different market stages. before the oil market law, which was published at the end of 2003, the pricing was determined by the government and the gross margin for distribution side was fixed to usd 5-7 cents/lt. after the introduction of the free pricing system with the new law, in the beginning of 2005, the margins have started to grow and therefore the investments as well as financial transactions in the industry has begun to ramp up. the price cap interventions between the period of 2009 and 2013, as an average, created a loss of 0,07 $/l gross industry margin which translates to aproximately usd 1.1 billion loss of potential income on annual basis for the whole industry. although the interventions and caps are only applicable for 2 months the overall affect was very significant when this impact is spread over for the whole year. 2.4. competition and market entry both the oil market law and the lpg market law operate on the principle of free market entry. the rules for market entry for the distributors are relatively simple and do not require high level of investments. however, to operate in the market an extensive level of reporting needs to be made in addition to several complicated relgulatory requirements. therefore, we may state that the distributors do not have to make a large investemnt to enter to the market, however, they have to carry a significant level of regulatory requirements to stay in the market. this was the spirit of the law, to increase the level of competition in the market by relaxing the entry barriers. the number of players, their market share and the yeraly variation of these are accepted as simple indication of the level of competition in the market. the following graphs (figure 5a and b) show the number of oil and lpg distribution companies, before and after the enactment of the law. in addition, the number of retail sites, is also shown in order to provide an additional data in assessing the role of new laws and easement of market entry. the fuels and lpg retail sites display relatively different characteristics, altough the total number of fuel retail sites are relatively stable, there is a continuous increase in lpg sites. this is normal since the number of available sites suitable for fuel distribution is limited by nature of the operation and certain restrictions on the land site. the continuous increase in lpg sites is because of the addition of lpg units in already existing fuel retail sites. the level of competition in the downstream oil market in turkey has been the subject of extensive debates during 2010 and 2015. these debates range from academic researchs through price assymetry studies, (bor and i̇saruhan, 2013; ünal, 2011) overall market price reviews, (metin, 2015) to an extensive official report on the competitive nature of the fuels market as published by the competition authority competition board of turkey, fules sector report (2008). one of the objective of the new market law was to increase the competetive nature of the fuels retail market. before the entry of the new law, the market share of first five major distribution companies in turkey was approximately 83%. after several state interventions and the decision of the competition board to limit the contract period to 5 years, the market share of majors showed a slight drop down to 78%, i.e., the major companies were able to keep their market shares even tough the number of players in the market have practically doubled as shown in figure 6 another striking fact with the market shares of the major oil distribution companies operating in turkey, is that the relative market shares of the competitors are in constant change, again indicative of the competitive nature of the market. more technical assessments of the competitive nature of the oil and lpg markets in turkey show that hhi index and crn indexes show relatively high values (1197 for fuels market turkish oil market annual report (2016) and 1277 for lpg market (lpg market report, 2016). the competition authority marked a turning point in the history of fuel dealership business in turkey by the decision to limit the duration of dealership contracts to 5 years as of 18 september 2010. the retroactive character of this decision, and therefore its provisions affecting contracts signed prior to this date, resulted in the reshuffling of the cards in the market. the impact on the market was significant loss of book value of the distribution companies and a pressure on the distributors’ share in the margins as a negotiation tool for the new contracts. 2.5. the impact of measures against smuggling and the volume growth in automotive fuels before the enactment of the oil market law, the high level of smuggled and illicit fuels in the market was one of the main problems of the turkish oil market. in fact, the oil market law was designed to include several instruments to fight agains illegal products, such as compulsory use of national marker, pump and tank automation systems, exclusivity of contracts between distribution companies and dealers, detailed reporting and heavy penalties. on the other hand turkey is one of the leading countries with high taxation on fuel products, which creates a potential for illegal income. the country is surrounded by oil producing countries and due to significant tax level difference across borders, there has been continuous flow of oil products through the borders, in addition to various forms tax evasion due to illicit or fraudulent products. the new law aiming liberalization and strong measures against the illegal products (such as national marker, pump automation systems, cash registry systems, intense reporting etc.) metin and kumbaroğlu: impacts of regulatory transformation processes to the downstream oil market in turkey international journal of energy economics and policy | vol 8 • issue 3 • 2018148 in the market has proved significant level of succes against illicit products and fuels smuggling. before the entry of oil market law in 2003, the volume of illegal products in the fuels market had reached to around 3.0 million tons per annum. in addition to fuel smuggling through borders, time to time different ways of illicit activities have evolved, such as use of heavy base oil to replace diesel fuels. tight regulations, enforcing compulsory use of natural marker in automotive fuels, pump automation systems, cash registry systems and heavy penalties have proved success and the level of ilegal fuels in the market has dropped to a level less than 1.0 million ton. the result of the success of fight against illicit products is depicted by a continuous and positive volume growth in fuels market. the following graphs (figure 7a and b) demonstrate the strong growth in the consumption of automotive fuels over the period of last 15 years. the growth is consistent per capita basis and even stronger for the last 5 years, averaging cagr of 8.5%. this strong growth in excess of the gdp, is accepted as a strong evidence of success of fight against smuggling and fraudulent products which was achieved by national marker implementation, tank and pump automation systems together with high quality data collected and published by emra. in summary, turkish oil market displayed typical characteristics of a market liberalization process. introduction of a new market law, strong drive towards market liberalization, privatization of refineries and distribution companies have created an environment where the country received more than usd10 billion level investments the form of fdi and financial transactions within the period between 2000 and 2009. although these investments and liquid market characteristics have slowed down between 2010 and 2015, some important level of investments and mergers and acquisitions continued in the market even after these events, exceeding usd 5 billion. in addition, the positive legal environment, i.e., winds of liberalisation has helped the markets to grow consistently, by an average of 6.25% per annum between 2000 and 2015, which is greater than the gdp growth of the country. 3. conclusions 1. the market transformation process of turkish downstream oil industry from state governed to a regulated market, presents a good example of the sensitivity of investments and financial transactions to the regulatory environment. the market enjoyed fairly large sized investments, merge and acquisations, buy outs with the start of liberalization efforts supported by the enactment of a law aiming liberal markets. the markets have changed its dynamics and displayed lover level of financial transactions when government interventions took place reinforced by increasing regulatory pressure. 2. the turkish downstream oil market displayed strong growth especially in the area of automotive fuels such that the average growth of last 15 years is 6.25%. the growth of the market has reached an average 8.5%, for the last 5 years, which is well in access of gdp growth of the country. the strong growth is partly due to successful fight against illegal products, along with the healthy growth of automotive industry in turkey. the implementation of national marker, exclusivity of the nature of the dealer and distribution company, pump automation systems are all considered to be jointly contributors of this positive result. figure 5: changes in number of petrol fuel and lpg distribution companies (a) and retail stations (b) a b figure 6: market shares of the top five distribution companies in turkish fuels’ retail market a b metin and kumbaroğlu: impacts of regulatory transformation processes to the downstream oil market in turkey international journal of energy economics and policy | vol 8 • issue 3 • 2018 149 3. the turkish downstream oil market had florished with significant level of investments and financial transactions in the form of merge and acquisitions, especially when the regulatory environment was moving towards a fully liberal market, between 2000 and 2009. during this period, the industry enjoyed financial transactions, in the form of merges and acquisations, in access of usd 10 billion. however, due to political shifts towards more regulated market structure instead of full market liberalization, combined with interventions, the level of investments dropped significantly during 2009-2015. this was the period where some of the major oil companies have decided to exit the market since the level of returns were not sufficient to sustain their investments and the risks associated were too high to justify staying in the market. 4. overall, successful privatization and regulatory change from a state owned and state operated market have triggered more than usd15 billion level of investments and financial transactions in the market. when combined with the direct investments made to retail sites, depots, fuels quality programs, logistics and transport activities this figure likely to exceed usd25 billion, a good example of positive impact of market liberization. references available from: http://www.hurriyet.com.tr/petrol-ofisini-alan-vitoldenilk-aciklama-geldi-40384967; https://www.sondakika.com/ petrol-ofisi/. available from: http://www.sabah.com.tr/ekonomi/2016/04/16/ demiroren-totalle-uce-katlayacak; http://www.milliyet.com.tr/ demiroren-holding-total-turkiye-yi/ekonomi/detay/2227895/ default.htm. bahçe, s., taymaz, e. (2008), the impact of electricity market liberalization in turkey: free consumers and distributional monopoly cases. energy economics, 30(4), 1603-1624. bloomstoern, m., lipsey, r., zeyan, m. (1994), what explains the growth of developing countries, convergence of productivity. oxford: oxford university press. bor, o., i̇saruhan, m. (2013), gasoline pricing, taxation and asymmetry; the case of turkey. turkish economic association, 7. competition board of turkey, fules sector report. (2008), available from: http://www.rekabet.gov.tr. competition board, comminique. (2002), available from: http://www. rekabet.gov.tr. [last accessed on 2009 mar 12]. kandilov, i.t., leblebicioglu, a., manghnani, r. (2016), the liberalization and investments in foreign capital goods, evidence from india, (under peer review). lpg market report. (2016), available from: http://www.epdk.gov.tr. mann, h. (2007), investment liberalization: some key elements and issues in today’s negotiating context. singapore: issues in international investment law. p1-2. metin, e. (2015), recent developments in oil prices and reflection to pump prices in turkey. economics and policy of energy and the environment, 2, 77-91. oecd. (1998), fdi and economic development, lessons from six emerging economies. paris: oecd. oil market law, the official gazette no 5015 december 13. (2003), lpg market law, the official gazette no 25754, law no: 5307, march 2nd, 2005. petder. (2015), sector report 2015, (and monthly market reports), available from: available from: http://www.petder.org.tr. sachs, j., warner, a. (1995), economic reform and the process of economic integration. brooking papers on economic activity, 1(95), 1-118. shaghil, a., zlate, a., (2014), capital flows to emerging markets. journal of international money and finance, 48, 221-248. stiglitz, e.j. (2000), capital market liberalization, economic growth and instability. world development, 28(6), 1075-1086, turkish oil market annual report. (2016), available from: http://www. epdk.gov.tr. ünal, h. (2011), the turkish downstream petroleum industry, analysis of market efficiency, m.sc. thesis, norwegian school of economy. world petroleum council. (2016), turkish energy market outlook, achievements, overview and opportunities. turkish economic: world petroleum council, 1-42. figure 7: growth in consumption of automotive fuels; in per capita base (a) and in total by fuel type (b) a b . international journal of energy economics and policy | vol 9 • issue 6 • 2019 79 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(6), 79-85. effectiveness of environmental policy enforcement and the impact by industrial mining, energy, mineral, and gas activities in indonesia kamal hidjaz department of  law science, faculty of law, universitas muslim indonesia, makassar, indonesia. *email: kamal.hidjaz@yahoo.co.id received: 17 may 2019 accepted: 18 august 2019 doi: https://doi.org/10.32479/ijeep.8146 abstract they are being polemic for indonesia between implementing production and sustainability simultaneously, considering that indonesia is a newly emerging country, which of course wants to be independent and also sovereign from the regional side as a unitary state and even financially independent to meet all the needs of the indonesian people. the main challenge faced by indonesia is pursuing maximum economic growth through the use of natural resources. the effectiveness of environmental law enforcement on the activities of the mining, gas, and mineral industry can run smoothly and smoothly concerning several fundamental aspects. on the other hand, mining activity is an effort to create jobs, improve the economy, which aims at equitable distribution of income through the absorption of labor in the sector of the mining industry. environmental issues that are becoming a global issue require the government to take firm action against violators/perpetrators of environmental pollution to cause deterrent effects for others. the government can take legal steps through administrative, criminal, and civil considerations as a manifestation of creating environmentally friendly and sustainable production activities in the future. keywords: environmental policy, environmental law, socio-legal research jel classifications: o44, q5, q56 1. introduction environmental problems have become a national problem and are even becoming a global issue that does not seem difficult to resolve. population growth and economic growth also have an impact on changes in consumption patterns of the worldwide community (murdifin et al., 2019). so that along with the variety of changes, it also has an impact on environmental issues caused by one of them by waste. in 2017 the population of indonesia had reached 261.89 million compared to 2000, which was 206.26 million. according to data from the indonesian ministry of industry in 2016 the amount of b3 waste disposal, the remaining industry managed in 2017 amounted to 60.31 million tons and accumulated from 2015 only reached <40% of the target of the b3 waste management of 755.6 million tons in the year 2019. b3 waste is the largest produced by the mining, energy and mineral industries. mining activities are a significant contributor to liquid waste. the gdp generated from the mining and quarrying sector in indonesia amounted to 167.7 trillion rupiahs in 2000, increasing to 1,028.8 trillion in 2017. the development of the mining industry, energy, and minerals increased the problem of waste. the sorting process uses a lot of water media, or even those carried out in rivers such as gold mining activities which directly dispose of their trash into the river without prior processing, as well as coal mining activities. in line with that, the environmental problems generated by waste originating from mining, energy, and mineral activities also have an impact on river water quality in indonesia, this journal is licensed under a creative commons attribution 4.0 international license hidjaz.: effectiveness of environmental policy enforcement and the impact by industrial mining, energy, mineral, and gas activities in indonesia international journal of energy economics and policy | vol 9 • issue 6 • 201980 which is generally in a heavily polluted state. in 2018 as many as 25.1% of villages experienced water pollution, and their land contaminated around 2.7% of communities. the emergence of waste disposal in addition to having an impact on the environment also has an effect on health, therefore serious measures need to be taken in accordance with the targets of the sustainable development goals (sdgs) in which the sdgs target by 2030 to substantially reduce waste production through prevention, reduction reset and reuse. the waste contributes to greenhouse gas emissions that cause global climate change where climate change spurs natural disasters such as floods, landslides, tornadoes, droughts, and so on. emissions in the waste sector tended to increase in 2000 with a record 60.1 million tons of co2e released in the environment and in 2016 it reached 97.9 million tons of co2e. table 1 shown the production of essential mining types and mineral excavations in indonesia. efforts made by the indonesian government to combat environmental problems originating from industrial waste, including by allocating environmental protection budgets to the national budget (national government expenditure) and the regional budget (regional government expenditure) (mina, 2016). indonesia as a country that is rich in natural resources, both renewable and non-renewable natural resources, of course, besides being an opportunity, it is also a challenge for indonesia to play an active role in environmental conservation globally. in article 33 of the 1945 constitution (paragraph 2) which is the main guideline and legal basis of indonesia states that “the earth, water and natural resources contained therein are controlled by the state to be used as much as possible for the prosperity of the people.” so that in the management of natural resource and energy wealth activities it is necessary to apply the principle of sustainable development followed by the application of laws that maximally protect nature, ecosystems and the survival of living things (hatta, 1977). on the other hand, it has become polemic for indonesia between implementing production and sustainability, considering that indonesia is a developing country which of course wants to be independent and also sovereign from the regional side as a unitary state and even financially independent to meet all the needs of the indonesian people. the main challenge faced by indonesia is pursuing maximum economic growth through the use of natural resources which aims to accelerate equity and social justice and to reduce the income gap between regions in indonesia as the country with the most islands in the world. the leading players in the petroleum commodity mining industry such as chevron (usa) contribute 40% of the total lifting of 287 million barrels of oil. 15% from pertamina ep (indonesia), 5% from pertamina, inpex and conoco philips (usa) and 30% from from other companies through operations in riau and east kalimantan indonesia with total state revenues for the oil and gas sector amounting to 341 trillion rupiah and 37 trillion rupiah from the minerals and coal sector (eiti.ekon.go.id, 2014). for natural gas lifting conoco phillips (usa) contributes 21% of the total 2.3 million indonesian national mscf gas, 16% of the contribution comes from bp (indonesia), 12% comes from pertamina ep (indonesia), 11% from inpex, 10% from total (usa) and 30% from gas lifting contributions from other companies (eiti.ekon.go.id, 2014). deeper in entering into the main issues in this study, the effectiveness of environmental law originating from mining and mineral excavation activities in indonesia each year shows that there are still many legal cases. as in 2013, legal claims in the mining sector reached 203 cases, 2014 with 173 cases and in 2018 240 cases. the legal arguments in mining activities are table 1: production of main mineral and materials in indonesia kind of mine mineral unit 2012 2013 2014 2015 2016 crude oil 000 barel 314.666 301.192 287.902 286.706 269.613 natural gas mmscf 2.982.754 2.969.211 2.999.524 2.957.230 2.905.465 tin ore ton 44.202 59.412 51.801 52.195 42.698 coal 000 ton 452.318 458.463 435.743 429.964 419.000 bouxite 000 ton 31.443 57.024 2.539 472 494 nickel ore 000 ton 48.449 65.047 39.034 1.870 1.263 gold kg 69.291 59.804 69.349 92.414 75.000 copper concentrate 000 ton 2.385 1.910 1.572 2.425 2.696 kind of materials unit 2014 2015 2016 2017 sand m3 302.439.255 373.022.443 317.043.635 327.175.708 stone 104.276.218 54.413.501 110.133.557 115.768.198 andesite 13.864.769 7.294.371 21.114.081 23.490.462 sirtu gravel 37.508.536 18.728.619 50.404.140 57.484.091 lime stone 13.317.839 23.969.459 11.594.460 12.149.160 quartz sand 2.446.715 2.944.465 3.239.834 3.691.339 marble 707.163 529.368 611.942 572.077 clay 7.729.717 3.476.204 9.674.479 10.168.241 piled soil 27.335.816 23.236.082 14.635.699 11.088.193 other stone 27.335.816 23.236.082 14.635.699 11.088.193 pumice stone 689.208 433.706 1.009.713 1.198.397 feldspars 566.979 464.105 520.505 517.943 trass 2.267.872 347.280 2.802.660 3.175.808 kaolin 706.297 262.707 861.290 1.001.287 zeolite 102.000 92.250 98.222 93.194 source : quarrying company survey (badan pusat statistik, 2018) hidjaz.: effectiveness of environmental policy enforcement and the impact by industrial mining, energy, mineral, and gas activities in indonesia international journal of energy economics and policy | vol 9 • issue 6 • 2019 81 mostly related to legislation, which are incomplete licenses, or overlapping mining permits originating from errors in issuing permits (cnn indonesia.com, 2018). the lack of legal prosecution for mining activities in indonesia has provided concrete evidence, as in 2016 out of 5587 mining business permits will be blocked due to expired mining permits. the number of civil law cases in mining activities is due to licensing data that is not integrated, both mining data, company data, and beneficial ownership data (www.bbc.com, 2017). data for 2017 related to mining business permits (iup) shows that out of a total of 8,524 iups of 2522 iups or 30% of non clear and clean (c & c) status with the dominant provinces with the most problematic iup licenses, they are from south kalimantan (351 iup), java west (291 iup), east kalimantan (275 iup), south sulawesi (188 iup), west kalimantan (170 iup) which will lead to revocation of business licenses (eiti.ekon.go.id, 2018). weak law enforcement in mining activities in addition to having a direct impact on the environment also affects state losses through non-transparent beneficial ownership. data from 2018 from indonesia corruption watch (icw) provides a statement that out of 11,000 mining businesses, there are 3772 mining businesses prone to corruption and potentially harming indonesia reaching 28.5 trillion rupiah due to hidden ownership. the existence of closed business ownership can also have the potential as a means for money laundering, monopoly and unhealthy competition which are all impacts of governance and information sources that are closed and not upholding legal aspects. the overlapping problems in the mining industry are also marked by the lack of transparency in the administrative process, ranging from standardizing the measurement of mine impacts, up-to-date mining company contract data, weak revision of guidelines related to the extractive industries transparency initiative (eiti) and ineffectual regulations regarding mining regulations and laws. adding a long line of administrative issues to legal cases in the mining industry which if not handled seriously by the government will have an impact on the effectiveness of state revenues and also have a direct effect on the environment due to the mining industry’s disobedient procedures. therefore, objectively this study is expected to be able to provide alternative solutions for the government and stakeholders towards efforts to the effectiveness of ideal law enforcement that is assessed through an economic perspective, management policy, and law. 2. literature review the terminology of enforcement of environmental laws by biezeveld said that the enforcement of environmental law is: environmental law enforcement legal powers to ensure compliance with environmental regulations utilizing: (1) administrative supervision of compliance with environmental regulations (inspection) (mainly preventive activity), (2) organizational measures or sanctions in case of non-compliance (corrective exercise), (3) repressive activity criminals in case of presumed offenses; (4) criminal rules or penalties in case of repressive activity, (5) civil action (lawsuit) in the case of (threatening) non-compliance (preventive or corrective activity) (faure and svatikova, 2012). furthermore, environmental law enforcement is an effort to achieve adherence to regulations and requirements in general and individual legal provisions, through supervision and implementation of administrative, criminal, and civil sanctions (akhmaddhian, 2016). enforcement of environmental law can be done preventively, meaning that active control is carried out on compliance with regulations without a direct incident involving actual events that lead to the presumption that legal provisions have been violated. instruments for preventive law enforcement are counseling, monitoring, and use of the authority that is supervisory (sampling, stopping machines, and so on). thus, the primary law enforcers are officials/government officials who are authorized to give permission and prevent environmental pollution (lestari and djanggih, 2019). repressive law enforcement is carried out in the event of an act that violates the rules and aims to end the prohibited act directly. criminal prosecution generally follows rules violations and usually cannot negate the consequences of the offense. 2.1. sustainability development goals (sdgs) sdgs is a global action plan agreed upon by world leaders to end poverty, reduce inequality, and protect the environment. sdgs contains 17 goals, namely eradication of poverty, ending hunger, improved health and well-being, quality education, gender equality, access to clean water and sanitation, clean and affordable energy. decent work and economic growth, industrial infrastructure and innovation, reducing income inequality, cities, and sustainable communities, responsible consumption and production, handling climate change, safeguarding marine ecosystems, maintaining terrestrial ecosystems, peace and justice, and strong institutions, partnerships to achieve goals. so that to fulfill the seventeen destination objectives, there are 169 targets expected to be completed by 2030 (organization, 2016). where precisely the goals for the environmental handling sector are expected to upgrade infrastructure and retrofit so that the resulting waste emissions can be controlled so that they can keep the environment clean through controlling co2 emissions, waste or hazardous management, all of which can be implemented through product regulations that are conducive to the environment implemented. 2.2. indonesian environmental and mining activity policy various products of environmental law in indonesia as stated in presidential regulation no. 47 of 2005 concerning an amendment to the baseline convention on the control of transboundary hazardous wastes and their disposal. regulation of the minister of environment no. 33 of 2009 concerning procedures for restoring land contaminated with dangerous and toxic material waste. minister of environment regulation no. 30 of 2009 concerning the licensing and supervision of b3 waste management and monitoring of recovery due to pollution of b3 waste by the regional government. whereas the right products relating to the regulation of mining activities include the government regulation of the republic of indonesia no. 22 of 2010 concerning mining areas, regulation of the republic of indonesia government regulation no. 78 of 2010 concerning reclamation and post-mining. regulations related to b3 and non-b3 waste under the republic of indonesia law, number 32 of 2009 which regulate environmental hidjaz.: effectiveness of environmental policy enforcement and the impact by industrial mining, energy, mineral, and gas activities in indonesia international journal of energy economics and policy | vol 9 • issue 6 • 201982 protection and management and government regulation number 101 of 2014 concerning b3 waste management, adds clarity and the existence of additional rules from existing regulations namely government regulation number 18 of 1999. besides, several provisions were established to carry out international agreements related to b3 management including law number 10/2013 concerning the rotterdam convention, law number 19/2009 concerning the stockholm convention, and presidential regulation number 47/2005 concerning the basel convention. to improve services in the management of b3 waste and non-b3 waste. several policies are developed regarding waste management, namely: 1. lhk ministery regulation number: p.55/menlhk-setjen/2015 concerning procedures for characteristics of b3 waste test 2. lhk ministery regulation number: p.56/menlhk-setjen/2015 concerning procedures and 3. technical requirements for b3 waste management from health service facilities 4. ministery of lhk regulation number: p.63/menlhk/setjen/ kum.1/7/2016 concerning requirements and procedures for b3 waste stockpiling in final procurement facilities 5. regulation of the director general of pslb3 number: p.3/ pslb3/vplb3/plb.3/6/2016 concerning trial 6. electronic technical consultation for b3 waste management licenses 7. regulation of the director general of pslb3 number: p.1/ pslb3/vplb3/plb.3/6/2016 concerning trial 8. electronic manifest of transporting b3 waste 9. regulation of the director general of pslb3 number: p.2/ pslb3/vplb3/plb.3/6/2016 concerning trial of b3 waste transport tracking system 10. circular of the director general of pslb3 number: se.10/ pslb3/vplb3/plb.3/6/2016 concerning trial of electronic manifestation of b3 waste transport. 3. research methods this study approach uses the socio-legal research method on the implementation of laws regarding the effectiveness of the application of environmental law and environmental law administration in the scope of mining, mineral, and gas industry activities in indonesia. data collection uses some secondary data about the phenomena and violations of mining activities that are linked to the realization of the implementation of legal provisions in indonesia. 4. result and discussion 4.1. sources of b3 and non-b3 in indonesia the waste comes from various human activities, which occur from waste material that is no longer used. waste is generated from industrial events and domestic operations; here are some sources of waste. table 2 explains in general about the rate of production of waste from some of the largest sources of gdp in indonesia from 2000 to 2017. 4.1.1. mining sector, energy and mineral mining activities are a significant contributor to liquid waste. the gdp generated from the mining and quarrying sector amounted to 167.7 trillion in 2000, increasing to 1,028.8 trillions in 2017 (badan pusat statistik, 2018). the development of the energy and mineral mining industry rises the problem of waste. the sorting process uses a lot of water media, or even what is done in the river. as seen in gold mining, it immediately dumps the waste into the river without prior processing. likewise, in coal mines, sludge containing toxic metals is far more dangerous than the purification process of gold mining using cyanide. these carcinogenic elements, when mixed with river water and used by the community, will reduce river water quality, causing severe health problems (badan pusat statistik, 2018). 4.1.2. agroindustry sector the agro-industry sector also produces waste disposal from agricultural processes, both in the pre-harvest, harvest, and postharvest operations. as the largest producer of palm oil (cpo) in the world, indonesia has the most extensive palm oil land in the world. the area of oil palm in indonesia in 2016 reached 6.46 million hectares, of which 89% was controlled by large private plantations. while other cpo and cpo production for the year reached 22.76 million tons, this waste contains very high organic material so that the level of pollution will be higher. mainly because almost every palm oil industry is located near the river, and its liquid waste if left to form ammonia, which will threaten the life of aquatic biota and cause foul odors. 4.1.3. manufactur sector the number of large and medium industrial companies in 2000 was 22 thousand companies, to 26 thousand in 2015, and 1 in 4 companies were food processing industries, then the textile and apparel industries. plus the number of micro-small companies that are very large in indonesia, in 2010 has reached 2.7 million business units and in 5 years to 3.6 million units in 2015. waste produced by factories is discharged into waterways such as sewers, times or river and ends at sea. this liquid waste is dangerous, and some can be neutralized quickly. waste that is discharged into waterways without being treated first can cause water ecosystems to be damaged, even living things inside death. waste is a contributor to global warming emissions that cause global climate change. climate change triggers natural disasters, table 2: sources of b3 and non-b3 in indonesia sector with the largest gdp share % rate of waste produced rate of the ability of waste that can be processed manufacturing 20.2 366 ton per day 3% or just 10,98 ton per day agriculture, forestry and fishery 13.1 wholesale and retail trade; repair of motor vehicles 10.4 mining and quarrying 7.6 source: (badan pusat statistik, 2018) hidjaz.: effectiveness of environmental policy enforcement and the impact by industrial mining, energy, mineral, and gas activities in indonesia international journal of energy economics and policy | vol 9 • issue 6 • 2019 83 including floods, landslides, tornadoes, droughts, etc. emissions in the waste sector tend to increase, in 2000, there were 60.1 million tons of co2e released to the environment, and in 2016, it reached 97.9 million tons of co2e. in addition to natural disasters, waste is also related to technological disasters, especially mistakes in the management of b3 waste. some cases of b3 pollution include instances of heavy metal pollution from electronic waste which poison children caused by lead waste in their area exceeding the who threshold (badan pusat statistik, 2018). b3 wastes, especially heavy metals such as mercury, lead or dioxin substances, are toxic, carcinogenic (cause cancer), and mutagenic. its external impact is the degradation of the environment and the health of the people living around it. land, water, and the air around the waste processing site are generally contaminated with heavy metals and toxic compounds. data shows that nearly 68% of river water quality in indonesia is heavily polluted (badan pusat statistik, 2018). 4.2. management and utilization of b3 waste in the mining, energy and mineral sector the b3 waste data managed in 2015 amounted to 125.54 million tons from 269 companies (table 3). for 2016, there were 78.36 million tons from 295 companies. while the amount of b3 waste managed in 2017 was 60.31 million tons from 262 companies. the type of company that leads waste the most every year is engaged in the mining, energy and mineral subsector. the activity because the energy and mineral mining sector has a large work area and production capacity. but when compared to the target until 2019, the waste management position until 2017 has not yet reached the goal. the cause of the target was not achieved because of the presence of b3 waste managed without permits, handed over to unauthorized third parties or open dumping (badan pusat statistik, 2018). 4.3. waste management efforts in indonesia first effort, waste management in indonesia refers to indonesian government regulation number 101 of 2014 stating that b3 waste management activities are a series of events which include reduction, storage, collection, transportation, utilization, the management or stockpiling. to ensure that each chain of b3 waste management is by the legal provisions. b3 waste managers must be equipped with a permit. one of the efforts to manage waste including the mining, energy and mineral industries in indonesia is through the issuance of permits, as in 2015 the number of licenses issued to waste managers was 582 applicant issues and as many as 200 licenses had not been published or the comparison between the number of permits issued reached the target 74.4%. in 2016 the number of permits issued compared to 2015 increased to 639 licenses that had been issued, and 92 permits had not yet been issued or reached 87.4%. whereas in 2017 it decreased from the previous year, namely 2016 to 439 issued licenses and 97 unpublished permits or an achieved target of 83.6%. the second attempt is related to waste management in indonesia, namely the recovery of b3 waste contaminated land. this is following indonesian minister of environment regulation no. 18 of 2015. as in 2015, the restoration of contaminated soil was 389,354.07 tons with an area of 63,423.11 m2. in 2016 the land that was successfully restored decreased compared to 2015, which amounted to 213,433.17 tons with an area of 83,287.67 m2 and increased to 767,107.12 tons with a land area of 318,713.76 m2. 5. discussion enforcement of environmental law in indonesia includes structuring and enforcement (compliance and implementation). when talking about administrative law enforcement, of course, it will discuss the facilities that can be used in law enforcement administration. the scope of regulatory law enforcement to make enforcement of environmental law can be useful can be achieved through two aspects, namely defensive efforts which include supervision to prevent violations that have the purpose of compliance with regulations. second, repressive efforts through the application of sanctions to stop breaches and return to the situation before the abuse of legal norms. to avoid repeated criminal prosecution, individuals who commit environmental pollution must stop the situation. regarding the enforcement of local environmental law by the government, it should be able to take environmental dispute settlement efforts by way of an environmental lawsuit to obtain compensation for victims of pollution due to illegal acts by polluters. considering that ecological pollution activities harm many parties and ecosystems, the government can take the path by using (private prosecution) the perpetrators of environmental pollution, in this case, are companies that are active in the mining, energy and mineral industries through civil lines. administrative environmental law is the most substantial part, and environmental law consists of regulatory and legal provisions. these provisions, on the one hand, are the norms that bind citizens. on the other hand, the regulation also regulates the limits of authority and government organizations in terms of implementing material norms. if a provision of environmental law pertains to how licensing is granted, then this provision contains a material norm; an action is an act that is prohibited insofar as permission has not been obtained. also, the same regulations, namely recognizing or giving authority to the government to give permits related to mining industry activities. administrative sanctions are given if mining operators violate the rules after their business permit is issued. in other words, environmental law needs an integrated licensing system, meaning to prevent and eradicate or overcome ecological pollution problems. so that in taking a more comprehensive legal procedure, the government must reinforce environmental licensing procedures. the concrete steps that must be accompanied by the government as the licensor require the participation of the community and the study of science or technology. in the clause of the study of legal regulations that table 3: management and utilization of b3 waste in the mining, energy and mineral sector (million ton) sector 2015 2016 2017 mining, energy and mineral 89,3 70,1 55,1 infrastructure and services 33,2 1,1 3,6 manufacture 2,2 5,5 1,2 agroindustry 1,8 1,7 0.4 source: indonesian central bureau of statistics, 2018 (badan pusat statistik, 2018) hidjaz.: effectiveness of environmental policy enforcement and the impact by industrial mining, energy, mineral, and gas activities in indonesia international journal of energy economics and policy | vol 9 • issue 6 • 201984 involve many stakeholders (community, academics, government), it is necessary to consider several key points, namely: (1) how is the implementation of industrial activities so that the activation process does not cause pollution; (2). if there is contamination how to overcome it; (3). supporting tools or instruments/facilities and infrastructure that need to be prepared to prevent pollution; (4). if the contamination is not overcome, how is the solution for the recovery of the environment; (5). how environmental restoration and monitoring is carried out; in what form pollution losses are carried out. therefore, after the instrument has been arranged in the way of standard regulations and violations of permits continue to occur, the company can be given a cumulative sanction in the form of revocation of licenses, civil penalties, and criminal sanctions. if the environmental management law (uuplh) is reviewed, it is evident that the punishments for enforcing administrative environment law are still limited to pouring, which is limited to coercive government (article 25 paragraph 1) in the form of “payments of certain money” (article 25 paragraph 5) and revocation of licenses (article 27). apart from that, regarding the enforcement of environmental law after administrative law can also lead to criminal law. the effectiveness of the application of sanctions and elements of criminal imposition for perpetrators of environmental pollution, the implementation and enforcement of criminal law for environmental law actors must pay attention to the severity of environmental pollution. besides that, practical considerations sometimes must also be considered. environmental codes related to evidence and determination of the causal relationship between polluting and polluted actions and procedures for prosecuting them are regulated by criminal law. the role of the investigator is very functional because it involves evidence or an instrument which is sometimes scientific (chemical). besides that the proof of the causal relationship element is an obstacle for investigators, environmental pollution often occurs cumulatively, so it is difficult to prove the source of contamination is polluted because it is chemical. in theory ecological law, criminal and civil sanctions can be applied to environmental polluters by looking comprehensively, meaning that polluters can be given administrative sanctions. in the form of revocation of licenses as well as criminal penalties, even the principle primitive premium can be applied in environmental offenses, meaning people who violate permits, not the business license was revoked at the same time in criminal. the application of this sanction is emphasized considering that pollution is difficult to overcome or restore as before. another road taken by the government to avoid environmental problems caused by increasingly uncontrolled mining activities is by utilizing private law. civil sanctions in the form of compensation to the aggrieved party (community) through the application and effectiveness of the csr (corporate social responsibility) function. 6. conclusion the effectiveness of environmental law enforcement on the activities of the mining, gas, and mineral industry can run smoothly and smoothly concerning several fundamental aspects. on the other hand, mining activity is an effort to create jobs, improve the economy, which aims at equitable distribution of income through the absorption of labor in the sector of the mining industry. however, mining activities have two opposing sides, namely the principle of productivity as a positive side and the impact of pollution as a negative side. therefore law enforcement is also endeavored to be fair to both companies/entrepreneurs in the mining, gas and mineral industry and even the community. environmental issues that are becoming a global issue require the government to take firm action against violators/perpetrators of environmental pollution to cause deterrent effects for others. the government can take legal steps through administrative, criminal, and civil considerations as a manifestation of creating environmentally friendly and sustainable production activities in the future. references akhmaddhian, s. (2016), penegakan hukum lingkungan dan pengaruhnya terhadap pertumbuhan ekonomi di indonesia (studi kebakaran hutan tahun 2015). unifikasi: jurnal ilmu hukum, 3(1), 1-10. badan pusat statistik. (2018), statistik lingkungan hidup indonesia. badang pusat statistik indonesia. avaialble from: https://www.bps. go.id/publication/2018/12/07/d8cbb5465bd1d3138c21fc80/statistiklingkungan-hidup-indonesia-2018.html. cnn indonesia.com. (2018), polri catat 240 kasus hukum di sektor pertambangan. retrieved may 5, 2019, from https://www. cnnindonesia.com/ekonomi/20180222172759-85-available from: http://www.278120/polri-catat-240-kasus-hukum-di-sektorpertambangan. eiti.ekon.go.id. (2014), pemain utama industri tambang indonesia. eiti indonesia. available from: http://www.eiti.ekon.go.id/pemainutama-industri-tambang-indonesia. [last accessed on 2019 may 05]. eiti.ekon.go.id. (2018), ijin tambang status non c and amp;c eiti indonesia. avaialble from: http://www.eiti.ekon.go.id/ijin-tambangstatus-non-cc. [last accessed on 2019 may 05]. faure, m.g., svatikova, k. (2012), criminal or administrative law to protect the environment? evidence from western europe. journal of environmental law, 24(2), 253-286. hatta, m. (1977), pelaksanaan undang-undang dasar 1945 pasal 33. penjabaran pasal, 33, 26-33. lestari, s., djanggih, h. (2019), urgensi hukum perizinan dan penegakannya sebagai sarana pencegahan pencemaran lingkungan hidup. masalah-masalah hukum, 48(2), 147-163. mina, r. (2016), desentralisasi perlindungan dan pengelolaan lingkungan hidup sebagai alternatif menyelesaikan permasalahan lingkungan hidup. arena hukum, 9(2), 149-165. murdifin, i., faisal pelu, m.a., putra, a.h.p., arumbarkah, a.m., rahmah, a., muslim indonesia, u., rahmah, a. (2019), environmental disclosure as corporate social responsibility: evidence from the biggest nickel mining in indonesia. international journal of energy economics and policy, 9(1), 115-122. peraturan dirjen pslb3 nomor p.1/pslb3/vplb3/plb.3/6. (2016), tentang uji coba manifes elektronik pengangkutan limbah b3. peraturan dirjen pslb3 nomor p.2/pslb3/vplb3/plb.3/6. (2016), tentang uji coba sistem pelacakan pengangkutan limbah b3. peraturan dirjen pslb3 nomor p.3/pslb3/vplb3/plb.3/6. (2016), tentang uji coba konsultasi teknis secara elektronik perizinan pengelolaan limbah b3. peraturan menteri lhk nomor p.55/menlhk-setjen. (2015) tentang tatacara uji karakteristik limbah b3. peraturan menteri lhk nomor p.56/menlhk-setjen. (2015) tentang tatacara dan persyaratan teknis pengelolaan limbah b3 dari fasilitas pelayanan kesehatan. hidjaz.: effectiveness of environmental policy enforcement and the impact by industrial mining, energy, mineral, and gas activities in indonesia international journal of energy economics and policy | vol 9 • issue 6 • 2019 85 peraturan menteri lhk nomor p.63/menlhk/setjen/kum.1/7. (2016), tentang persyaratan dan tata cara penimbunan limbah b3 di fasilitas penimbusan akhir. peraturan menteri lingkungan hidup no. 30 tahun. (2009), tentang tata laksana perizinan dan pengawasan pengelolaan limbah b3 serta pengawasan pemulihan akibat pencemaran limbah b3 oleh pemerintah daerah. peraturan menteri negara lingkungan hidup no. 33 tahun. (2009), tentang tata cara pemulihan lahan terkontaminasi limbah bahan berbahaya dan beracun. peraturan pemerintah nomor 101 tahun. (2014) tentang pengelolaan limbah b3. peraturan presiden no. 47 tahun. (2005), tentang amendment to the basel convention on the control of transboundary movements of hazardous wastes and their disposal. surat edaran dirjen pslb3 nomor se.10/pslb3/vplb3/plb.3/6. (2016) tentang pelaksanaan uji coba manifes elektronik pengangkutan limbah b3. undang-undang republik indonesia nomor 19 tahun. (2009), tentang pengesahan stockholm convention on persistent organic pollutants konvensi stockholm tentang bahan pencemar organik yang persisten. undang-undang] republik indonesia nomor 32 tahun. (2009) tentang perlindungan dan pengelolaan lingkungan hidup. world health organization. (2016), world health statistics 2016: monitoring health for the sdgs sustainable development goals. geneva: world health organization. www.bbc.com. (2017), merugikan negara ribuan izin tambang di indonesia akan diblokir bbc news indonesia. avaialble from: https://www.bbc.com/indonesia/indonesia-42308353. [last accessed on 2019 may 05]. tx_1~at/tx_2~at international journal of energy economics and policy | vol 9 • issue 4 • 2019110 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(4), 110-114. application of the stochastic markov model in predicting the volume of oil spill in nigeria: a case of the niger-delta region ifeoma christy mba*, emmanuel ikechukwu mba, winnie ogonna arazu, chinasa e. urama, chioma henrietta machebe, chikodili eze university of nigeria, nsukka, nigeria. *email: ifeomachristymba@gmail.com received: 22 february 2019 accepted: 12 may 2019 doi: https://doi.org/10.32479/ijeep.7744 abstract oil spillage in the niger delta region of nigeria and its associated hazard is on the increase and there is urgent need to combat its increasing volume by predicting the volume in the future thus, the objective of this study is on the prediction of the volume of oil spill in nigeria via the stochastic markov model. two states markov analysis were employed and it was discovered that the volume of oil spill incident were mostly maintained in a high state than in a low state and the predicted values were approximately steady at a probability value of 0.519 which is in favour of the high state. the study concluded that for the nigerian federal government to combat the volume of oil spill, she should in addition to enforcing the laws governing the volume of oil spill incident, employ remediation process that would help clean up the mess caused the spillage keywords: occurrence, oil spill, niger delta jel classifications: p28, q53, q56 1. introduction nigeria, the giant of africa is a country that is blessed with both human and natural resources, natural resources such as crude oil, rubber, lime stone are amongst the numerous gifts from god almighty. amidst these precious gifts, nigeria is yet to be called “a developed country” irrespective of the name, “the giant of africa.” nigeria has all she needs and takes to make her great in all ramifications. one of the blessings given to nigeria has turned to be her greatest nightmare and that is crude oil but it is pertinent to say that the natural resources endowed to our country nigeria is more of a resource curse than a blessing. nigeria’s major source of income is crude oil and most of her problems have their origins emanating from the so called crude oil. the major issue is that instead of the natural resources to bring about the needed gains or say blessings to both the country and her citizens, the feedback is a “resource curse.” the discovery of oil and oil on a commercial basis was in the niger delta region of nigeria at oloibiri (the present day bayelsa state) in the year 1956, although more oil discoveries were made after that of olobiri and exports began in the year 1958 almost 2 years after discovery at olobiri. it was only in the year 1965 that it became significant and the reason for that was because the bonny island terminals at rivers state and the necessary pipelines to feed the terminal were completed. the nigerian export was put at an average of 2.5 million barrels each day in the year 2004 and its reserve at 35 billion barrels (cab, 2005). subsequent discoveries of oil in other parts of the country gave rise to diverse problems that are harmful to man and development. problems such as pipe line vandalization, oil bunkering and siphoning, oil theft are some of the problems facing the country and depriving her of the necessary and supposed growth. when it comes to oil in the niger delta, oil spillage or oil spill incident has become a household name. it is rather imperative to think that it is a recent this journal is licensed under a creative commons attribution 4.0 international license mba, et al.: application of the stochastic markov model in predicting the volume of oil spill in nigeria: a case of the niger-delta region international journal of energy economics and policy | vol 9 • issue 4 • 2019 111 issue. oil spillage in nigeria is on the increase and its associated harm on the environment is also on the increase. the problem is now on the volume of oil spill, how can the nigerian government tackle this problem?, or one can say in a lighter mood, how can its remediation process work if the quantity or volume lost is not modelled and predicted. the main aim of this paper is on how the volume of oil spill can be predicted via the stochastic markow model and thus if this is achieved, the remediation process can also be readily achieved because one can thus have a rough idea of what the volume of oil spill would look like in years to come and thus work ahead of time. 2. literature review previous stochastic markow analysis literature were mainly on risks disruptions due to maritime, risk of workers that are exposed to oil and gas industry, there are also studies that are not markov oriented, studies such as that by mode et al. (2013), they predicted the rate and volume of oil spill on both vertical and horizontal pipelines with a high correlation coefficient value of 0.978. it was realized that the model should be utilized with a high degree of confidence so that the bioremediation project was used for proper assessment. another study developed a guerrilla movement that observed oil pipeline attack decision, although the markov decision process was modelled as an infinite horizon that chooses each period either to attack or not to attack the pipeline. parameters were also compared when the discount factor changed (offstein, 2002). offstein (2002) discovered that a zero discount factor hypothesis implies that the movement or attack behaviour is very much compatible with extortionary behaviour. bam (2015) examined the effects of oil spill and recovery of terrestrial arthropods in louisiana saltmarsh ecosystem. ten sites were sampled, that is, these sites were along the louisiana coast. amongst the ten sites that were sampled, 4 were heavily oiled, 3 were lightly oiled and the last 3 unoiled. it was discovered that the terrestrial arthropods were affected by oil and hurricane isaac and up till today, the oil contamination effects still persist today (bam, 2015). rico et al. (2008) viewed the effects of the prestige oil spill on macroalgal assemblages via a large scale comparison, they compared data obtained before the spill and after the spill. they sampled 4 zones in the north and north west coast of spain and discovered that differences in abundance were observed but they did not display any significant pattern. they concluded that the causes of the assemblages after spill were the limited use of aggressive cleanup methods and fuel deposition on the shores that weren’t intense but rather extensive. rutherford et al. (2015) examined how the stochastic prediction of oil spill transport can be improved using the approximation methods. their sole aim was on how they can identify parameters that could further improve the forecasting algorithms. rutherford et al. (2015) focused on the cranslik functionality as one of its approximation methods and concluded that the cranslik v2.0 which was a revised model was validated against the medslik-ii and it was discovered that the new version of cranslik was better in forecasting improvements by its ability to capture the oil spill accurately than the other. there are also studies that were just on oil spill incident; studies such as (cekirge, 2013; mba et al., 2019; ndeh et al., 2017; ohanmu et al., 2018). mba et al. (2019) examined oil spillage causes and terrain in the niger-delta region of nigeria, they employed a two way analysis of variance approach and thus concluded that sabotage was the major cause of oil spillage in the niger delta followed by operational and mystery spill. ohanmu et al. (2018) examined if the changes in physicochemical properties and heavy metals would affect two species of pepper. they employed the randomized block design and discovered that crude oil spill actually affects the soil properties and nutrients. ndeh et al. (2017) investigated crude oil spillage in upenekang village in ibeno local government area of akwa ibom state in nigeria, they looked at the effect of crude oil spill on the underground and surface stream water. they employed a one way analysis of variance approach and their sresult showed that there are no significant influence of distance away from spill on the level of heavy metals in the water samples collected. cekirge (2013) employed methods in determining the volume of oil spill. these methods were based on ascertaining the thickness of oil on water surface by employing usual observations, an algorithm and model were thus developed using optimization techniques and software. they concluded that the method would give a positive result if it is employed on actual oil spill. 3. methodology the monthly oil spill data ranging from january 2015 to december 2018 was used and the source of the data is from shell nigeria database1. the stochastic markov chain (smc) model. the monthly observed oil spill data will follow two (2) states, st; where st=1, which would be referred to as a “high” state of the volume of oil spill incident in nigeria. st=2, would henceforth be referred to as a “low” state of the volume of oil spill incident in nigeria. thus, whether states st=1,2; the process respectively would switch states such that the change observed from a past state t to a new state t+1 is from a normal distribution and thus is a random draw. thus yt is the observed change and the distribution would thus be: yt ~ µ σ1 1 2( ) distribution for the “high” state (1) yt ~ µ σ1 1 2( ) distribution for the “low” state (2) from expressions (1) and (2), there exist switches from one state to the other and thus the probabilities (pij) of the switches between the two states is given as: p p p p p pij ji=       = 11 12 21 22 which can also be written as pp p p p hh hl lh ll       (3) 1 https://www.shell.com.ng/sustainability/environment/oil-spills.html https://www.shell.com.ng/sustainability/environment/oil-spills.html mba, et al.: application of the stochastic markov model in predicting the volume of oil spill in nigeria: a case of the niger-delta region international journal of energy economics and policy | vol 9 • issue 4 • 2019112 expression (3) is referred to as the transition probability matrix. therefore, the transition probability state can be switched between the two states or that a particular state (i) be followed by another state (j) or vice versa. thus, the current volume of oil spill incident depends on the preceding and not on the past volume of oil spill incident. therefore the smc model is given as; smc=p(xt+1=x/x1=x1, x2=x2,…,xt=xt) (4) where t is an element of n and n is the total number of oil spill incident in a year. x is the volume of oil spill incident at different time period. note that the sum of the probabilities row wise cannot exceed 1. thus, p11+p12=1 (5) the n-step transition probabilities. thus, the probability that a smc would be in state j (say a high state or a low state) after n periods is given as: pr(xt+n=j/xt=i)=pr(xn=j/x1=i)=pij(n) (6) where pij(n) is called the n-step probability of a transition from state i to state j. for the n-step transition probabilities to be achieved, the years under study would be pooled and their frequencies and transition probabilities thus would be calculated. therefore the observed frequency fij table for the two states is given in table 1. where fij is the observed frequency from the volume of oil spill incident and thus the fhh simply implies that the switches are from a high state to another high state and fhl implies that it is from a high state to a low state and flh shows that it is from a low state to a high state and lastly fll; a low state to another low state. 4. analysis and interpretation of results from the table 2, it can be seen that in the year 2015, from january to december, that the total switches from a high volume of oil spill to another high volume of oil spill is twenty-one (21). the highest switches was witnessed still in the year 2015 with a total frequency of 38 and the switches was from a low state to a high state followed by 37 in the year 2017, that is from a high state to a low state and 36, from a low state to a high state. in 2016, it was discovered that switches from a low state to another low state was 7 in total frequency followed by 14, that is, a low state to another low state. it can be seen that in the year 2016, the volume of oil spill will switch from a low state to another low state with a probability value of 0.226 that is 23%, which is very low (table 3). thus from year 2015 to 2018, the switches were mainly from high state to low state and from low state to high state. this simply implies that the volume of oil spill would always switch majorly between a low to high states or vice versa. the probability of the volume of spill remaining in the same state, that is, from a high state to a high state or low state to a low state are usually insignificant in value but the switches from one state to another; say a high state to a low state or from a low state to a high state are significant in value, thus, there is always transition or movement from one state to another. it takes 39% in 2015, 23% in 2016, 39% in 2017 and 30% in 2018 for the volume of oil spill to remain in a low state and 36% in 2015, 43% in 2016, 30% in 2017 and 48% in 2018 for the volume of oil spill to remain in high state but for switches from high to low, it takes 64% in 2015, 58% in 2016, 69% in 2017 and 52% in 2018 and finally low to high shows 61%, 77%, 61% and 70% for years 2015 through 2018 respectively. thus the switches is more from the low state of oil spill incident to a high state than the other way. it simply implies that the volume of oil spill incident usually is high as regards the volume of its spillage. thus, the volume of oil spilled is more in quantity as shown by the probability values indicating the low state of oil spill to a high state of oil spill. the pooled frequency and transition probability matrices from 2015-2018 is given as: 84 129 128 68 0 394 0 606 0 653 0 347       =       . . . . table 1: observed frequency fij switching states frequency (fij) hh fhh hl fhl lh flh ll fll table 2: observed frequency table for 2 states volume of oil spill year switching states frequency (fij) 2015 hh 21 hl 37 lh 38 ll 24 2016 hh 17 hl 23 lh 24 ll 7 2017 hh 16 hl 37 lh 36 ll 23 2018 hh 30 hl 32 lh 32 ll 14 source: authors’ computations mba, et al.: application of the stochastic markov model in predicting the volume of oil spill in nigeria: a case of the niger-delta region international journal of energy economics and policy | vol 9 • issue 4 • 2019 113 the pooled transition probability (ptp) value for the oil spill incident with respect to the switches between high to low and low to high are 0.606 and 0.653 respectively which shows that it takes 61% for the volume of oil spill incident to switch from a high state to a low state and then 65% for the volume of oil spill incident to switch from a low state to a high state. thus, one can see that the switches from a low state volume of oil spill to a high state volume of oil spill is more, that is, from 2015 to 2018, it can still be seen that the volume of oil spill is on a high state than any other state. the table below shows the iteration table of the n-step transition probability that shows the prediction of the oil spill incident in nigeria. the table below shows the n-step iteration for the ptp from 2015 to 2018 and the corresponding predicted years from 2019 through 2023. from the table 4, the n-step ptp matrices show that even in the long run, the high state to high state in the year 2019 is 0.550954 approximately 0.551; in 2020, 0.5103029 approximately 0.510. thus, there was a decrease in the probability value and in 2021, 0.5181046 approximately 0.518, 0.5188109 approximately 0.519 in 2022 and in 2023, 0.5186280 approximated to 0.519. recall also that the ptp from 2015 to 2018 is 0.394. from the matrices, we can see that there was a tremendous increase and in the year 2022 and 2023, the probability value remained unchanged with probability values approximated at 0.518. the low state to low state had 0.347 and had an increase but from 2020 to 2023, the probability value reduced ranging from 0.516127 in 2019, 0.4723231 in 2020 and approximately a steady value of 0.4807299 approximated to 0.481 (in 2021), 0.4814910 approximated to 0.481 (in 2022) and 0.4812938 approximated to 0.481 (in 2023). switches from a high state to a low state can also be seen to increase from 0.449046 in 2019 to 0.4896971 in 2020 and later decreased to 0.4818954 approximately 0.482 and maintained a steady probability value of 0.481 for 2022 and 2023 respectively. switches from a low state to a high state also increased from 2019 with probability value of 0.483873 to 0.5276769 in 2020 and later reduced in the probability value to 0.5192701 to a steady probability value of 0.5185090 in 2022 and 0.5187062 in 2023 approximately 0.519. thus, a high state volume of oil spill incident has been predicted to occur more than the low state and the switches from even the low state to the high state is also with an increased value but the values housing the low state or switches from a high state to a low state is also reduced since the volume of oil spill incident state is switching from a state of high to low and not the other way. this implies that even in the future, the predicted probability values of the ptp matrices shows that a high state of the volume of oil spill incident will keep increasing and at a point would be maintained and the only way to combat the situation is to apply remediation processes that would bring about the reverse state, that is, from the state of high volume of oil spill incident to a low state and also maintain it so that there are no longer switches. 5. conclusion and recommendation the stochastic markow model was applied in predicting the volume of oil spill in nigeria so as to know how best to tackle the unending problems that are caused by the spillage. the volume of oil spill has remained in a high state than in a low state. the switches from one state to the other has also proved that the volume of oil spill is in a high state than in a low state. the volume of oil spill was also predicted and from the results, it showed that even in the future, the state of high volume of oil spill has a steady state probability value of 0.519 which was seen from the high state to a high state and from a low state to a high state. thus, the volume of oil spill incident are in the high state with a steady state probability value of 0.519 (52%) approximately. subsequently, for nigeria to combat the high state of oil spill, there is need for her to know if the oil spillage is actually in a high state or low state. thus, from this study, it can be seen that the volume of oil spill is actually in the high state most times. conclusively, the nigerian government can now apply a remediation process on time since table 3: the transition probability matrices for the different years with respect to volume of oil spill year switching states tp tpm 2015 hh 0.36 0.36 0.64 0.61 0.39       2015 hl 0.64 2015 lh 0.61 2015 ll 0.39 2016 hh 0.425 0 425 0 575 0 774 0 226 . . . .        2016 hl 0.575 2016 lh 0.774 2016 ll 0.226 2017 hh 0.301 0 301 0 698 0 610 0 390       . . . . 2017 hl 0.698 2017 lh 0.610 2017 ll 0.390 2018 hh 0.484 0 484 0 516 0 696 0 304       . . . . 2018 hl 0.516 2018 lh 0.696 2018 ll 0.304 source: authors’ computations, tp: transition probabilities, tpm: transition probability matrices table 4: n-step pooled transition probability matrices year ptp^n n-step ptp matrices 2015-2018 ptp^1 0.394 0.606 0.653 0.347       2019 ptp^2 0.550954 0.449046 0.483873 0.516127       2020 ptp^3 0.5103029 0.4896971 0.5276769 0.4723231       2021 ptp^4 0.5181046 0.4818954 0.5192701 0.4807299       2022 ptp^5 0.5188109 0.4811891 0.5185090 0.4814910       2023 ptp^6 0.5186280 0.4813720 0.5187062 0.4812938       source: authors’ computations mba, et al.: application of the stochastic markov model in predicting the volume of oil spill in nigeria: a case of the niger-delta region international journal of energy economics and policy | vol 9 • issue 4 • 2019114 it has been predicted via the stochastic markov analysis that the volume of oil spill is actually in a high state than in the low state. the nigerian federal government can also enforce laws that govern the volume of oil spill incident and treat offenders without mercy. references bam, w. (2015), effects of oil spill and recovery of terrestrial arthropods in louisiana saltmarsh ecosystem. louisiana: louisiana state university. cab. (2005), us energy information administration nigeria. nigeria: country analysis brief. cekirge, h.m. (2013), oil spills : determination of oil spill volumes observed on water surfaces. the international journal of technology, knowledge and society, 8(6), 1-18. mba, i.c., mba, e.i., ogbuabor, j.e., arazu, o.w. (2019), causes and terrain of oil spillage in niger delta region of nigeria : the analysis of variance approach. international journal of energy economics and policy, 9(2), 1-5. mode, a.w., amobi, j., salufu, s.o. (2013), a model for predicting rate and volume of oil spill in horizontal and vertical pipelines. journal of environment and earth science, 3(9), 12-19. ndeh, e.s., okafor, j.o., akpan, g.u., olutoye, m.a. (2017), environmental impacts of crude oil spillages on water in ibeno local government area of akwa ibom state, nigeria. bayero journal of pure and applied sciences, 10(1), 315-319. offstein, n. (2002), an extortionary guerrilla movement. documento cede, 9, 1-62. ohanmu, e.o., igiebor, f.a., bako, s.p., danazumi, i.b. (2018), impact of crude oil on physicochemical properties and trace metals of soil before and after planting of two pepper species (capsicum annum l and c. frutescens l). journal of applied sciences and environmental management, 22(5), 765-768. rico, j.m., acuna, j.l., anadon, r., monteoliva, j.a. (2008), effects of the “prestige” oil spill on macroalgal assemblages : large-scale comparison. marine pollution bulletin, 56(6), 1192-1200. rutherford, r., moulitsas, i., snow, b.j., kolios, a.j., dominicis, m.d. (2015), cranslik v2. 0 : improving the stochastic prediction of oil spill transport and fate using approximation methods. geoscientific model development, 8, 3365-3377. . international journal of energy economics and policy | vol 9 • issue 2 • 2019 31 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(2), 31-39. evaluation of renewable energy alternatives for turkey via modified fuzzy ahp esra karakaş*, ozan veli yildiran adana science and technology university, faculty of business, department of business administration, adana, turkey. *email: ekoyuncu@adanabtu.edu.tr received: 08/11/2018 accepted: 02/02/2019 doi: https://doi.org/10.32479/ijeep.7349 abstract the importance of renewable energy is increasing both with the inadequacy of traditional energy resources and environmental awareness. turkey has a large potential for renewable energy sources, and utilizing the potential is an inevitable choice for increasing its self-sufficiency with an environmentally friendly way. therefore, evaluation of renewable energy alternatives for the country and determination of the most suitable renewable energy alternative are important issues to make reasonable energy investment plan. in this study, we evaluate the renewable energy alternatives of turkey using modified fuzzy analytic hierarchy process. renewable energy alternatives considered in the study are hydro, wind, solar, biomass and geothermal energy. four main criteria and eight sub criteria are used to evaluate five renewable energy alternatives. the obtained results indicate that solar energy is the best alternative, and wind energy is the second best alternative for turkey. the conclusion reached by this study is also support successful realization of the vision 2023 energy targets. keywords: fuzzy analytic hierarchy process, renewable energy, energy strategy jel classifications: d81, q20, q38 1. introduction turkey has the highest rate of growing energy demand among oecd countries over the last 15 years. due to the lack of domestic gas sources, the country has become an energy importing country (http://www.mfa.gov.tr/turkeys-energy-strategy.en.mfa, 02.07.2018). this dependence on energy imports combined with increasing energy cost and the serious negative environmental impact of high energy consumption has increased the importance of renewable energy resource. more countries are focusing on renewable energy beyond traditional energy sources. renewable energy is an inevitable choice for sustainable economic growth, for the harmonious coexistence of human and environment as well as for the sustainable development. renewable energy is usually regarded as energy that does not pollute environment and could be recycled in nature (ertay et al., 2013. p. 39). renewable energy technologies are known to be less competitive than traditional electric energy conversion systems, mainly because of their intermittency and the relatively high maintenance cost. however, renewable energy sources (res) have several advantages, such as the reduction in dependence on fossil fuel resources and the reduction in carbon emissions to the atmosphere (banos et al., 2011. p. 1754). turkey’s geographic location has several advantages for extensive use of most of the res. turkey has various types of alternativeenergy resources such as hydro, solar, wind, biomass, and geothermal energy available in abundance. however, turkey is an energy importing country with more than half of the energy requirement being supplied by imports, and air pollution is becoming a great environmental concern in the country. in this regard, renewable energy resources appear to be one of the most efficient and effective solutions for sustainable energy this journal is licensed under a creative commons attribution 4.0 international license karakaş and yildiran: evaluation of renewable energy alternatives for turkey via modified fuzzy ahp international journal of energy economics and policy | vol 9 • issue 2 • 201932 development and environmental pollution prevention in turkey (kaygusuz and sarı, 2003. p. 459). taking these conditions into account, turkey government aims to produce 30% of turkey’s electricity demand in 2023 from res. so, the important decision for turkey is whether or not to establish renewable energy systems, to decide which res or combination of sources is the best choice. also, because of the important investment costs of constructing a renewable energy structure, selecting the best alternative among the different renewable energy resources is a vital from the point of view of long-term planning. renewable energy decision-making can be viewed as a multiple criteria decision-making (mcdm) problem with correlating criteria and alternatives. the decision making procedure has to take into account several conflicting aspects because of the increasing importance of the social, technological, environmental, and economic factors. traditional single-criterion decision-making cannot cope with the complexity of this problem (san cristobal, 2011. p. 498). a traditional single criteria decision making approach which is aimed at identifying the most efficient supply options at low cost was popular during the 1970s. growing environmental awareness in the 1980s has modified the decision framework by incorporating environmental and social considerations in energy planning. thus, the selection among energy alternatives has become a multi-criteria problem with many conflicting criteria such as economic, technical, environmental, political, social (pohekar and ramachandran, 2004). therefore, a multi-criteria approach to decision making appears to be the most appropriate tool to evaluate some alternatives by taking into account their advantages and disadvantages based on selection criteria. in this study, mcdm model based on the revised fuzzy ahp approach is applied to turkey’s renewable energy optimization problem. the objective of this research is to evaluate the most appropriate renewable energy alternatives to determine ratings of each renewable energy alternatives. for this purpose the revised fuzzy analytic hierarchy process (ahp) technique (aydın and kahraman, 2011; aydın and kahraman, 2018) is utilized to get rating of alternatives. the revised fuzzy ahp is an effective and newly published technique. this technique was firstly proposed by aydın and kahraman (2011), and later triangular fuzzy scale was revised slightly in their later study published in 2018 (aydın and kahraman, 2018). this article is organized in four main sections. first, a review of the literature on renewable energy selection problem is presented. especially, extensive literatures concerning the evaluation of res in turkey are given. second, description of the selection criteria and alternatives are given and the fuzzy ahp methodology is presented. third, results are presented together with the discussion in relation to the literature. finally, conclusions are given. 2. literature review decision-making is the process of finding the best option from all of the feasible alternatives. decision-making problems considering several criteria are called mcdm problems. there are various decision-making methodologies developed by researches in the literature. most frequently used methods for renewable energy selection are analytical hierarchical process (ahp), analytical network process (anp), and technique for order of preference by similarity to ideal solution (topsis), elimination and choice expressing reality (electre), preference ranking organization method for enrichment of evaluations. in addition, during the recent years, some researchers take renewable energy selection problem as fuzzy mcdm problem (fmcdm). therefore, mcdm techniques are applied to solve energy decision making problems in different countries such as iran, greece, india, spain and china. due to importance of energy for sustainable development, countries desire to utilize analytical methods to determine energy policy. beccali et al. (2003) assessed renewable energy technologies by using electre-iii method under fuzzy environment for the island of sardinia. sadeghi et al. (2012) suggested a fmcdm approach to assess four renewable energy alternatives in yazd province in iran. they used fuzzy ahp (fahp) method to determine weights of criteria and ranked alternatives with fuzzy topsis method. they concluded solar energy as the most appropriate alternative for the selected area. tasri and susilawati (2014), focused on determining the most appropriate renewable energy alternative for electricity production in indonesia using fuzzy ahp. al garni et al. (2016) used a mcdm methodology based on ahp to rank renewable power generation alternatives taking into account economic, environmental, socio-political and technical criteria. and then, they applied their proposed methodology to rank renewable sources for saudi arabia. algarin et al. (2017) used the ahp to prioritize criteria, subcriteria and alternatives for renewable energy supply in rural areas of the caribbean region of colombia. they concluded that solar energy was the best renewable energy alternatives for the region (algarin et al., 2017). there are many studies about mcdm application of renewable energy modeling in the literature. more studies can be found in review articles about mcdm application in renewable energy selection. pohekar and ramachandran (2004) discussed renewable energy applications with mcdm. taha and daim (2013) presented a literature review in which mcdm applications in renewable energy are divided into four main categories: renewable energy planning and policy, renewable energy evaluation and assessment, technology and project selection, and environmental aspects. in this section, available mcdm studies in renewable energy selection for turkey are given in detail. ulutaş (2005) aimed to determine the appropriate energy sources for turkey using anp. both res and the other sources were considered as energy alternatives. the results of the study indicated that biogass is the most attractive source for the country. kahraman et al. (2009) proposed two fmcdm methods to select the most appropriate renewable energy in turkey. the first method was fuzzy ahp, while the other was fuzzy axiomatic design (ad). they considered biomass, hydropower, geothermal, wind and solar renewable energy as alternatives. wind energy was selected as the best renewable energy alternative in both methods. kahraman et al. (2010) determined the best energy alternative of turkey karakaş and yildiran: evaluation of renewable energy alternatives for turkey via modified fuzzy ahp international journal of energy economics and policy | vol 9 • issue 2 • 2019 33 by considering interactions among criteria via choquet integral methodology. they concluded that the wind energy is the best alternative for turkey. kaya and kahraman (2010) proposed a methodology based on an integrated fuzzy ahp-vikor method to determine the best renewable energy alternative for istanbul. they also used the proposed methodology for selection among alternative energy production sites in istanbul. the following year, kaya and kahraman (2011) focused on the energy technology selection problem for turkey considering modified fuzzy topsis. they determined frequently used criteria in the literature and used these criteria while selecting best energy alternatives. they suggested wind energy as the best energy alternatives for turkey. boran et al. (2012) evaluated renewable energy technology for turkey using intuitionistic fuzzy topsis. they considered hydro, wind, photovoltaic, and geothermal as the renewable energy technologies in turkey. the results indicated that hydro is the best alternative and wind power ranked as the second best alternative for turkey. erol and kılkış (2012) developed an ahp method to facilitate energy resource planning for aydın distinct in turkey. they considered geothermal power, lignite, natural gas, wind, hydroelectric, and hydrokinetic powers as energy alternatives. solar energy was found as best energy sources. barış and küçükali (2012), developed a multi-criteria analysis tool to evaluate the performance of different res technologies under technical, economic, environmental and social aspects. they suggested biaogass as the best possible res option for turkey. demirtaş (2013) considered technical, economic, environmental and social criteria and applied ahp to determine best renewable energy alternatives for turkey. the results of the study suggested that wind energy was the best renewable energy alternative and the ranking of the other alternatives in descending order was determined as biomass, geothermal, solar and hydropower. ertay et al. (2013) evaluated the renewable energy alternatives; wind, solar, biomass, geothermal, and hydropower by using two mcdm methods. the ranking order of alternatives obtained by macbeth is wind, solar, biomass, geothermal, hydropower. when they applied fuzzy ahp, they concluded the same ranking result. kabak and dağdeviren (2014) proposed a hybrid model based on analytic network process (anp) and benefits, opportunities, costs and risks to determine the energy state of turkey and to prioritize alternative res. they evaluated five alternatives in terms of nineteen criteria and determined hydro power as the best alternative for turkey. büyüközkan and güleryüz (2014) aimed to build up a model to help investors by prioritizing renewable energy alternatives. they suggested a new group decision making approach based on fahp with linguistic interval fuzzy preference and fuzzy topsis. they obtained weights of evaluation criteria using fahp and ranking of the alternatives is determined using fuzzy topsis. şengül et al. (2015) presented a multi-criteria decision support framework for ranking renewable energy supply systems in turkey. they used shannon’s entropy methodology to determine criteria weights and fuzzy topsis method to prioritize alternatives. they concluded that the amount energy produced is the most important criterion and hydro power was the most important supply system followed by geothermal power, regulator and wind power. balin and baraçli (2015) offered a mcdm model based on interval type-2 fuzzy topsis and interval type-2 fuzzy ahp. they calculated the criteria weights by using interval type-2 fuzzy ahp method, and then they calculated ranking of alternatives according to the ranking vector determined by interval type-2 fuzzy topsis method. kuleli et al. (2015) modeled energy selection problem integrating anp and topsis methods. they considered social, economic, and environmental factors and concluded that hydro energy is the most appropriate res for turkey. also, they performed a sensitivity analysis to monitor the influence of criteria weights on the model results. erdogan and kaya (2015) clarified ranking of energy alternatives for turkey by developing an integrated fmcdm methodology. they used type-2 fuzzy ahp to weight the criteria and then used type-2 fuzzy topsis to rank energy alternatives. the results showed that wind energy is the most appropriate energy alternatives. büyüközkan and güleryüz (2016) developed an integrated mcdm model combining the decision making trial and evaluation laboratory (dematel) and anp methods in order to determine the most suitable renewable energy resource for turkey in turkey from an investor perpective. wind energy is selected as best renewable energy alternatives for turkey. çelikbilek and tuysuz (2016) presented a grey based mcdm methodology which integrates dematel, anp and vikor methods. grey dematel is used to determine relations among evaluation criteria, grey anp is used determine the weights of the evaluation criteria, and also grey vikor is used finally to rank renewable energy alternatives. they demonstrated the effectiveness of the improved model with the application for re in turkey. they concluded that solar energy is best alternative followed by wind, hydroelectric, biomass, geothermal. büyüközkan and güleryüz (2017) integrated dematel-anp-topsis methodologies with linguistic interval fuzzy preference relations. the results revealed that the best renewable energy technology for turkey was geothermal sources, followed by biogas. çolak and kaya (2017) proposed a hybrid mcdm method based on ahp with interval type-2 fuzzy sets and topsis with hesitant fuzzy sets. the ranking of energy alternative is determined as wind, solar, hydraulic, biomass, geothermal, wave and hydrogen energy. 3. method in this paper, an analysis is performed to determine the ranking of res in turkey. turkey has significant renewable energy potential, whose realizable renewable energy potential is equal to 13% of eu-27’s total potential. turkey’s total electricity generation potential from res is 240,165 gwh/yr for 138,000 mw economic potential. potential for various res types have important role to find a solution to the current economical and environmental problems of turkey (özcan, 2018. p. 2630). 3.1. renewable energy alternatives and selection criteria turkey has different type of res potantial. according to turkey’s ministry of energy and natural resources data, turkey has 144,000 gwh/yr hydro (for 36,000 mw), 14,665 gwh/yr geothermal (for 2000 mw), 60,000 gwh/yr wind (for 48,000 mw), 14,000 gwh/yr biomass (for 2000 mw), and 7500 gwh/yr solar (for 50,000 mw) renewable energy potential (sirin and ege, 2012. p. 4922). by considering res potential in turkey, res alternatives are determined as hydro energy, wind, solar, biomass and geothermal. hydro energy exploits the potential energy karakaş and yildiran: evaluation of renewable energy alternatives for turkey via modified fuzzy ahp international journal of energy economics and policy | vol 9 • issue 2 • 201934 that is contained in flowing waters like rivers and reservoirs in mountainous regions (büyüközkan and güleryüz, 2017. p. 151). the potential of hydropower resource relies on the amount of available water and suitable land. hydropower potential for turkey is not yet to be exploited fully. the goal of the turkish government is to utilize all technically and economically available hydropower by 2023 (melikoğlu, 2013. p. 504). solar energy is obtained by collecting sunlight through solar or photovoltaic cells, and then focused with mirror to create a highintensity heat source which runs a generator to produce electricity. solar energy can be utilized for cooling, lighting, heating and other energy demands (kabak and dağdeviren, 2014. p. 26). turkey has high solar energy potential due to its geographical location. according to the solar energy map of turkey prepared by the renewable energy general directorate, it has been determined that the total annual insolation time is 2741 h (a total of 7.5 h per day), and the total solar energy derived per year is 1527 kwh/m2 per year (total 4.18 kwh/m2 per day). as of the end of 2017, there were 3616 solar power plants with a total installed capacity of 3421 mw. this is the equivalent of 4% of the total potential. in 2017, electricity production based on solar energy have realized 2684 gwh and 0.91% of our electricity production was obtained from solar energy (http://www.enerji.gov.tr/en-us/pages/solar, 02.07.2018). wind energy is derived from air masses encountering different temperature ranges and is converted to electricity by means of wind turbines. by the end of 2017, installed wind power in turkey reached 6516 mw. this is the equivalent of 7.6% of the total potential. in 2017, electricity production from wind energy have realized 17,909 gwh and 6.06% of electricity production was obtained from wind energy (http://www.enerji.gov.tr/en-us/ pages/wind, 02.07.2018). biomass can be defined as the total mass of living organisms that belong to a society consists of species or consist of several species. biomass is also defined as an organic carbon. biomass potential in turkey is estimated about 8.6 million tonnes of equivalent petrol (mtep), and biogas quantities that can be produced from biomass is 1.5–2 mtep. as of the end of 2017, there were 122 renewable waste power plants with a total installed capacity of 634.2 mw. this is the equivalent of 0.7% of the total potential (http://www. enerji.gov.tr/en-us/pages/bio-fuels, 02.07.2018). geothermal power is the energy generated by heat stored beneath the earth’s surface or the collection of absorbed heat derived from underground in the atmosphere and oceans (kahraman and kaya, 2010. p. 6271). turkey has important geothermal potential for its direct use and for electricity generation. with the end of the year 2017, there were 40 geothermal power plants with a total installed capacity of 1,064 mw (http://www.enerji.gov.tr/en-us/pages/ geothermal, 02.07.2018). in the evaluation phase, these res alternatives are assessed in light of four main criteria and eight sub criteria. the criteria are determined with respect to relevant literature. kaya and kahraman (2011) introduced the most frequently used criteria by considering the criteria used in the literature. we also used these main and subcriteria, and the descriptions of the criteria are given as follows. efficiency (c11): efficiency refers to how much useful energy can be extracted from an energy source and is measured generally using efficiency ratio. efficiency ratio is defined as the ratio of output energy to input energy (kaya and kahraman, 2011; mourmouris and potolias, 2013). exergy efficiency (c12): exergy efficiency or rational efficiency investigates the efficiency of a renewable energy technology regarding to the second law of thermodynamics. it means there is always an exergy loss when a process involves a temperature change. exergy is the net energy that is left to be used (kaya and kahraman, 2011. p. 6582). investment cost (c21): investment cost includes all type of cost occurred for establishing the energy technology such as engineering services, road construction or other construction work, purchase of mechanic equipment, legislative authorization (büyüközkan and güleryüz, 2017; mourmous and potolias, 2013). operation and maintenance cost (c22): operation and maintenance cost includes all production costs that are associated with running a power plant. the components of operations costs are salaries, energy expenses, expenditure on products and services. also, maintenance costs are the funds spent to ensure reliable plant operations and to avoid failure and damage (büyüközkan and güleryüz, 2017; kaya and kahraman, 2011). particles emmision (c31): particle emission criterion consists of gas release to atmosphere, such as co2, n2o and ch4, which are the results of combustion process, liquid wastes related to secondary products by fumes treatment or with process water, and solid wastes. the evaluation of the criteria includes type and quantity of emissions, and costs associated with wastes treatments. also the electro-magnetic interferences, bad smells, and microclimatic changes for energy investment are taken into account while evaluating this criterion (kahraman and kaya, 2010; kahraman et al., 2009). land use (c32): energy systems need some land to be built, however different energy systems may occupy different land while the products are same. the environment and landscape are affected directly by the land occupied by energy systems (wang et al., 2009). a strong demand for land can also determine the economic losses (kahraman et al., 2009). social acceptability (c41): social acceptability is defined as the overview of opinions related to the energy systems by the local population. the overall opinion of local populations and of pressure groups can heavily influence the progress with investment decisions. social acceptance could not be expressed by quantitative way but qualitative. to transforming qualitative decisions into quantitative, survey method could be used (büyüközkan and güleryüz, 2017; wang et. al., 2009). job creation (c42): job creation includes direct and indirect employment, as well as creation of new professional areas indirectly. energy systems employ many people during their life cycle, from construction and operation till decommissioning. job opportunities for local societies improve the living quality of local people. however each energy source creates different job opportunities and decision makers should select energy source and plant type by considering local community (büyüközkan and güleryüz, 2017; wang et. al., 2009). karakaş and yildiran: evaluation of renewable energy alternatives for turkey via modified fuzzy ahp international journal of energy economics and policy | vol 9 • issue 2 • 2019 35 by considering the res potential in turkey, energy alternatives are evaluated from environmental, socio-political, economic, technical and technological aspects by experts. figure 1 shows hierarchical structure of energy decision making problem. three experts are utilized to evaluate the considered criteria and alternatives with respect to figure 1. one of them is an academic in energy systems engineering department and the others have work experience on energy policy and planning. equal weight was given to each expert. 3.2. the fuzzy ahp method in this study the fuzzy ahp method proposed by aydın and kahraman (2011) is utilized. the researchers slightly revised their triangular fuzzy scale in their later studies (aydın and kahraman, 2018). we use this fuzzy scale as given in table 1. the procedure of the fuzzy ahp method can be explained as follows (aydın and kahraman, 2011; aydın and kahraman, 2018). the weights (e) are allocated to experts on the basis of their knowledge, experience, etc. suppose that m experts exist in the group and the kth expert is ek is assigned an expert weight ek, where ek ϵ[0,1], e1+e2+...+em = 1 (1) to obtain a group preference from individual preferences, the aggregation of tfns scores is performed as following equation: 1 1 2 2ˆ ˆ ˆ ˆij ij ij ijm me e ea a a a⊕ ⊕…= ⊗ ⊗ ⊗ (2) where aij is the aggregated fuzzy score from all comparisions. aij1 , aij2 … aijm are corresponding tfn scales assigned by experts e1, e2,…em, respectively. ⊗ and ⊕ symbols refer fuzzy multiplication and fuzzy addition operators, respectively. as known, the scores in the classical ahp method are also based an exponantial importance. so, to convert negative fuzzy tfns to positive tfns, corresponding exponantial values of negative scores are calculated. the conversion is obtained by following equation. ˆ ( )* 4 ija ija e= (3) where a l m uij ij ij ij= ( , , ) triangular fuzzy comparision matrix is demonstrated by, ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 12 12 12 1 1 1 21 21 121 2 2 2 1 1 1 1 1 1,1,1 , , , , , , 1,1,1 , , , , , , 1,1,1 n n n n n n ij n n ij n n n l m u l m u l m u l m u a a l m l l m u  …   …  = =      …        (4) where a l m uij ij ij ij= ( ), , and a u m lij ij ij ij − =1 1 1 1 ( , , ) for i,j=1,…,n and i≠j. a normalized matrix n is calculated,  n nij ij m n=   × (5) n l u m u u u ij ij j ij j ij j =       * * * , , (6) u uj i ij * max= (7) the importance weights of the factors are calculated ussing following equation: 1' 1 1 1, 2, n ijj i n n kjk j n w k n n = = = = = … ∑ ∑ ∑  (8) goal: selecting the best renewable energy resource for turkey c1: technical c2: economic c3:environmenta c4: social c11: efficiency c12 : exergy efficiency c21: investment cost c 2 2 :operation and maintenance cost c31: particle emmision c 3 2 : land use c41: social acceptability c42: job creation hydro energy wind energy solar energy biomass energy geothermal energy figure 1: a hierarchy for selection of the most appropriate renewable energy resources for turkey karakaş and yildiran: evaluation of renewable energy alternatives for turkey via modified fuzzy ahp international journal of energy economics and policy | vol 9 • issue 2 • 201936 the rating of each alternative is multiplied by the weights of the sub-criteria and aggregated to get local ratings with respect to each criterion. the local ratings are then multiplied by the weights of the criteria and aggregated to obtain global ratings. in the last step, we rank the obtained fuzzy numbers. in order to rank the fuzzy numbers, we use the signed distance value developed by yao and wu (2000). 4. results and discussion as referred, mainly five ress (hydro energy, wind, solar, biomass and geothermal) alternatives have exploting possibilities on turkey. as known, first step of any multicriteria approach is defination of alternatives and criteria. the definition of alternatives and the evaluation criteria are previously described. the second step is the weighting of each criterion to express their relative importance. comparison matrix of main citeria is given in table 2. to analyze the consistency of the fuzzy pair-wise comparison matrices, we converted the fuzzy numbers into crisp numbers using a defuzzification technique. many techniques are used for defuzzification in the literature. the most used approaches are mean-of-maximum, center-of-area, and alpha-cut method (zhao and govind, 1991). in this study, we utilized the center-of-area method because of its calculation easiness (yalcın et al., 2012). after obtaining the aggregation of tfns scores using eq. 2, we converted negative fuzzy numbers in table 2 to positive fuzzy numbers via eq. 3. as a result, the comparision matrix is revised as table 3. then, normalized matrix given in table 4 is obtained using eqs. 5-7. finally, we obtained importance weights of main criteria by using eq. 8. ( ) ( ) ( ) ( ) ' ' 1 2 ' ' 3 4 0.170, 0.284, 0.535 , 0.060, 0.096, 0.179 , 0.279, 0.505, 0.816 , 0.061, 0.113, 0.216 c c c c w w w w = = = = we found that experts considered the criterion of ‘environmental’ more important than others. also, the second important criterion was determined as “technical.” this result means the experts were more interested in environment and technical factors. the same procedures are repeated for the sub-criteria and the weights of the sub-criteria are calculated as in the following tables 5 and 6. all the importance weights of the hierarchy have been calculated as following the same steps, and finally importance weights of the alternatives are obtained and given in table 7. according to table 7, the ranking of the alternatives from the best to the worst is solar, wind, geothermal, hydropower and biomass. so, the best renewable alternative in turkey is solar energy. this result is also parallel with the finding of erol and kılkış (2012) and celikbilek and tuysuz (2016). solar energy has many advantages. it causes no emissions like carbon dioxide, nitrogen oxide or sulphur oxide. although, the initial cost of a solar system is high, maintenance cost of solar system is very low. also, technology of solar energy is continuously developing regarding innovations in nanotechnology. technological development probably would increase the effectiveness of solar system and and decrease in investment cost in near future. among the alternative res in turkey, the most important one is solar energy. turkey has more chance than the other countries in terms of solar energy potential due to its geographic situation (balat, 2005). result of the study also confirms that solar energy is the most suitable alternative to meet growing energy demand. in addition, the second best alternative is wind energy. the main advantages of wind energy is that it does not harm the environment, the production of electricity with wind energy does not cause to the co2 emissions, acid rain and atmospheric warming (erdogan and kaya, 2015). also, wind energy may play a critical role in both strengthening energy security of turkey and thus decreasing energy dependency. some rer selection publications for turkey (kahraman et al., 2009; kahraman et al., 2010; kaya and kahraman, 2011; ertay et al., 2013; çolak and kaya, 2017) concluded that the second best alternative is solar energy after wind energy. both solar and wind energy are very important to realize turkey’s rer energy targets. taking economic potential of renewable resource into account, the utilization rate of wind power and solar power is very low. as mentioned before, there were 3616 solar power plants with a total installed capacity of 3421 mw, which is the equivalent of 4% of the total potential. also, by the end of 2017, installed wind power in turkey reached 6516 mw. this is the equivalent of 7.6% of the total potential. therefore, it can be seen that utilization rate of both solar and wind energy alternatives are very low when compared to their potential. also, turkey has also attained 21.41% of its table 1: triangular fuzzy coversion scale linguistic scale triangular fuzzy scale triangular fuzzy reciprocal scale just equal (0,0,0) (0,0,0) weakly important (0,1,3) (−3,−1,0) important (1,3,5) (−5,−3,−1) strongly more important (3,5,7) (−7,−5,−3) very strongly more important (5,7,9) (−9,−7,−5) absolutely more important (7,9,9) (−9,−9,−7) source: aydın and kahraman, 2018 table 2: comparison matrix of main criteria expert weight c1 c2 c3 c4 c1 1 0.3333 (0,0,0) (1,3,5) (0,1,3) (0,1,3) 2 0.3333 (0,0,0) (7,9,9) (0,1,3) (1,3,5) 3 0.3333 (0,0,0) (1,3,5) (−9,−9,−7) (3,5,7) c2 1 0.3333 (−5,−3,−1) (0,0,0) (−5,−3,−1) (0,0,0) 2 0.3333 (−9,−9,−7) (0,0,0) (−9,−9,−7) (−3,−1,0) 3 0.3333 (−5,−3,−1) (0,0,0) (−9,−9,−7) (1,3,5) c3 1 0.3333 (−3,−1,0) (1,3,5) (0,0,0) (3,5,7) 2 0.3333 (−3,−1,0) (7,9,9) (0,0,0) (5,7,9) 3 0.3333 (7,9,9) (7,9,9) (0,0,0) (3,5,7) c4 1 0.3333 (−3,−1,0) (0,0,0) (−7,−5,−3) (0,0,0) 2 0.3333 (−5,−3,−1) (0,1,3) (−9,−7,−5) (0,0,0) 3 0.3333 (−7,−5,−3) (−5,−3,−1) (−7,−5,−3) (0,0,0) karakaş and yildiran: evaluation of renewable energy alternatives for turkey via modified fuzzy ahp international journal of energy economics and policy | vol 9 • issue 2 • 2019 37 2023 target in wind energy and 4.52% of its 2023 target in solar energy (özcan, 2018. p. 2635). so, increasing the utilization rates of wind and solar energy would make an important contribution to realize turkey’s 2023 renewable energy targets. according to the result, geothermal energy is the third best energy alternatives and its score is very close to wind energy. economic potential of geothermal energy is estimated to be 2000 w, with an annual average generation potential of 14,665 gwh/yr (özcan, 2018. p. 2635) and as of the end of 2017, there are 40 geothermal power plants with a total installed capacity of 1,064 mw. this is the equivalent of 1.2% of the total potential (http://www.enerji. gov.tr/en-us/pages/geothermal, 02.07.2018). the government aims to achieve 1000 mw installed power by the year 2023 (özcan, 2018. p. 2635). in this case, it seems that the government has already achieved its 2023 target for geothermal energy. however, the utilization rate of geothermal energy is still low when taken into account of the total potential. for this reason, it may be an option to update targets related to geothermal energy in the future. 5. conclusions awareness of renewable energy importance on both environment and energy security has been increasing in turkey. in parallel, turkey government aims to produce 30% of turkey’s electricity demand in 2023 from res. therefore, the determination of the most suitable renewable energy alternative is an important issue to plan energy investment. in this study, the evaluation of renewable energy resources in turkey accomplished via modified fuzzy ahp method proposed by aydın and kahraman (2011; 2018). there are two mains reasons for the use of the revised fuzzy ahp method. firstly, this method use both positive fuzzy numbers and negative fuzzy numbers in fuzzy scale and thus it presents more understandable scales for comparing alternatives. secondly, this method is very easy to apply because it is based on simple arithmetic operations of fuzzy numbers. also, this study also demonstrates the effectiveness and applicability of revised fuzzy ahp method, which has been newly published and less known. the energy alternatives considered in the study are hydro, wind, solar, biomass and geothermal, which are mentioned in turkey’s 2023 energy targets. renewable energy alternatives were evaluated by considering four main criteria and eight sub criteria. the criteria are determined with respect to relevant literature. the results suggested that experts consider the criterion of “environmental” more important than others. also, the second important criterion was determined as “technical.” this result means that the experts were more interested in environmental and technical factors. after, weights of the criteria are calculated, the ranking of alternatives are determined as solar, wind, geothermal, hydropower and biomass in descending order. the results are also parallel with some similar studies in the literature. although their order changes, wind energy and solar energy have been found to be the most suitable renewable energy alternatives in most of the studies for turkey. because the utilization rates of these resources are low, increasing the utilization rates of wind and solar energy would make an important contribution to realize turkey’s 2023 renewable energy targets. in the future research, we are planning to carry out a mathematical model in order to determine optimal investment amount for each table 3: aggregated fuzzy comparision matrix for main criteria c1 c2 c3 c4 c1 (1,1,1) (2.117,3.490,4.871) (0.472,0.558,0.920) (1.395,2.117,3.490) c2 (0.205,0.287,0.472) (1,1,1) (0.147,0.174,0.287) (0.846,1.181,1.516) c3 (1.086,1.792, 2.117) (3.490,5.754,6.798) (1,1,1) (2.500,4.123,6.798) c4 (0.287, 0.472,0.716) (0.659,0.846,1.181) (0.147,0.242,0.399) (1,1,1) table 4: normalized fuzzy comparision matrix for main criteria c1 c2 c3 c4 c1 (0.472,0.472,0.472) (0.311,0.513,0.716) (0.472,0.558,0.920) (0.205,0.311,0.513) c2 (0.096,0.135,0.223) (0.147,0.147,0.147) (0.147,0.174,0.287) (0.124,0.174,0.223) c3 (0.513,0.846, 1) (0.513,0.846,1) (1,1,1) (0.368, 0.607,1) c4 (0.135, 0.223,0.338) (0.096,0.124,0.173) (0.147,0.242,0.399) (0.147,0.147,0.174) table 5: fuzzy weights of main criteria main criteria fuzzy weights signed distance value c1 (0.170,0.284,0.535) 0.318 c2 (0.060,0.096,0.179) 0.108 c3 (0.279,0.505,0.816) 0.526 c4 (0.061,0.113,0.216) 0.126 table 6: fuzzy weights of sub‑criterisa sub-criteria fuzzy weights c11 (0.313,0.417,0.582) c12 (0.437,0.582,0.747) c21 (0.611,0.871,1.215) c22 (0.089,0.128,0.211) c31 (0.460,0.679,0.947) c32 (0.217,0.320,0.529) c41 (0.595,0.851,1.187) c42 (0.103,0.148,0.244) table 7: importance weights of alternatives alternatives fuzzy weights signed distance value hydro (0.0433,0.174,0.768) 0.289 wind (0.054,0.236,0.994) 0.380 solar (0.062,0.275,1.139) 0.439 biomass (0.028,0.122,0.587) 0.150 jeothermal (0.047,0.193,0.839) 0.318 karakaş and yildiran: evaluation of renewable energy alternatives for turkey via modified fuzzy ahp international journal of energy economics and policy | vol 9 • issue 2 • 201938 renewable alternatives taking into account weights of alternatives obtained in the study. references al garni, h., kassem, a., awasthi, a., komljenovic, d., al-haddad, k. (2016), a multicriteria decision making approach for evaluating renewable powe generation sources in saudi arabia. sustainable energy technologies and assesments, 16, 137-150. algarin, r.a., llanos, a.p., castro a.o. (2017), an analytic hierarchy process based approach for evaluating renewable energy sources. international journal of energy economics and policy, 7(4), 38-47. aydın, s., kahraman, c. (2011), a modified fuzzy analytic hieararchy process based multi-criteria decision making methodology for assessing ecommerce quality: a case study in turkey. london: proceedings of the world congress on engineering. aydın, s., kahraman, c. (2018), evaluation of firms applying to malcolm baldrige national quality award: a modified fuzzy ahp method. complex and intelligent systems, 2018, 1-11. balat, h. (2005), solar energy potential in turkey. energy exploration and exploitation, 23(1), 61-69. balin, a., baraçli, h. (2017), a fuzzy multi-citeria decision making methadology based upon the interval type-2 fuzzy sets for evaluationg renewable energy alternatives in turkey. technological and economic development of economy, 23(5), 742-763. banos, r., manzano-agugliaro, f., montaya, f.g., gil, c., alcayde, a., gornez, j. (2011), optimization methods applied to renewable and sustainable energy: a review. renewable and sustainable energy reviews, 15, 1753-1766. barış, k., küçükali, s. (2012), availability of renewable energy sources in turkey: current situation, potential, government policies and the eu perspective. energy policy, 42, 377-391. becalli, m., cellura, m., mistretta, m. (2003), decision making in energy planning. application of the electre method at regional level for the diffusion of renewable energy technology. renewable energy, 28, 2063-2087. beccali, m., cellura, m., mistretta, m. (2003), decision making in energy planning. application of the electre method at regional level for the diffusion of renewable energy technology. renewable energy, 28, 2063-2087. boran, f.e., boran, k., menlik, t. (2012), the evaluation of renewable energy technologies for electricity generation in turkey using intuitionistic fuzzy topsis. energy sources part b, 7(1), 81-90. büyüközkan, g., güleryüz, s. (2014), a new gdm based ahp framework with linguistic interval fuzzy preference relations for renewable energy planning. journal of intelligent and fuzzy systems, 27(6), 3181-3195. büyüközkan, g., güleryüz, s. (2016), an integrated dematel-anp approach for renewable energy resources selection in turkey. international journal of production economics, 182, 435-448. büyüközkan, g., güleryüz, s. (2017), evaluation of renewable energy resources in turkey using an integrated mcdm approach with linguistic approach with linguistic interval fuzzy preference relations. energy, 123, 149-163. çelikbilek, y., tuysuz, f. (2016), an integrated grey based multi-criteria decision making approach for the evaluation of renewable energy sources. energy, 115, 1246-1258. çolak, m., kaya, i̇. (2017), prioritization of renewable energy alternatives by using an integrated fuzzy mcdm model: a real case application for turkey. renewable and sustainable energy reviews, 80, 840-853. demirtaş, ö. (2013), evaluating the best renewable energy technology for sustainable energy planning. international journal of energy economics and policy, 3, 23-33. erdogan, m., kaya, i. (2015), an integrated multi-criteria decisionmaking methodology based on type-2 fuzzy sets for selection among energy alternatives in turkey. iranian journal of fuzzy systems, 12(1), 1-25. erol, ö., kılkış¸ b. (2012), an energy source policy assessment using analytic hierarchy process. energy conversion and management, 63, 245-252. ertay, t., kahraman, c., kaya, i. (2013), evaluation of renewable energy alternatives using macbeth and fuzzy ahp multicriteria methods: the case of turkey. technological and economic development of economy, 19(1), 38-62. kabak, m., dağdeviren, m. (2014), prioritization of renewable energy sources for turkey by using a hybrid mcdm methodology. energy conversion and management, 79, 25-33. kahraman, c., kaya, i., cebi, s. (2009), a comparative analysis for multiattribute selection among renewable energy alternatives using fuzzy axiomatic design and fuzzy analytic hierarchy process. energy, 34, 1603-1616. kahraman, c., kaya, i., cebi, s. (2010), renewable energy selection based on computing with words. international journal of computational intelligence systems, 3(4), 461-473. kaya, t., kahraman, c. (2010), multi-criteria renewable energy planning using an integrated fuzzy vikor and ahp methodology: the case of istanbul. energy, 35, 2517-2527. kaya, t., kahraman, c. (2011), multi criteria decision making in energy planning using a modified fuzzy topsis methodology. expert system with application, 38(6), 6577-6585. kaygusuz, k., saru, a. (2003), renewable energy potential and utilization in turkey. energy conversion and management, 44, 459-478. kuleli, p.b., albayrak, y.e., erensal, y.c. (2015), renewable energy perspective for turkey using sustainability indicators. international journal of computational and intelligent systems, 8(1), 187-197. melikoğlu, m. (2013). hydropower in turkey: analysis in the view of vision 2023. renewable and sustainable energy reviews, 25, 503-510. mourmouris, j.c., potolias, c. (2013), a multi-criteria methodology for energy planning and developing renewable energy sources at a regional level: a case study thassos, greece. energy policy, 52, 522-530. özcan, m. (2018), the role of renewables in increasing turkey›s selfsufficiency in electrical energy. renewable and sustainable energy reviews, 82, 2629-2639. pohekar, s.d., ramachandran, m. (2004), application of multi-criteria decision making to sustainable energy planning a review. renewable and sustainable energy reviews, 8, 365-381. sadeghi, a., larimian, t., molabashi, a. (2012), evaluation of renewable energy sources for generaing electricity province of yazd: a fuzzy mcdm approach. procedia-social and behavioral sciences, 62, 1095-1099. san cristobal, j.r. (2011), multi-criteria decision making in the selection of a renewable energy project in spain: the vikor method. renewable energy, 36, 498-502. şengül, ü., eren, m., shiraz, e.s., gezder, v., şengül, a.b. (2015), fuzzy topsis method for ranking renewable energy support systems in turkey. renewable energy, 75, 617-625. sirin, s.m., ege, a. (2012), overcoming problems in turkey’s renewable energy policy: how can eu contribute? renewable and sustainable energy reviews, 16, 4917-4926. taha, r.a., daim, t. (2013), multi-criteria applications in renewable energy analysis, a literature review. green energy and technology, 60, 17-30. tasri, a., susilawati, a. (2014), selection amoung renewable energy karakaş and yildiran: evaluation of renewable energy alternatives for turkey via modified fuzzy ahp international journal of energy economics and policy | vol 9 • issue 2 • 2019 39 alternatives based on a fuzzy analytic hieararchy process in indonesia. sustainable energy technologies and assessment, 7, 34-44. turkish republic ministry of foreign affairs available from: http://www. enerji.gov.tr/en-us/pages/bio-fuels. [last accesed on 2018 jul 02]. turkish republic ministry of foreign affairs available from: http:// www.enerji.gov.tr/en-us/pages/geothermal. [last accesed on 2018 jul 02]. turkish republic ministry of foreign affairs. available from: http:// www.mfa.gov.tr/turkeys-energy-strategy.en.mfa. [last accesed on 2018 jul 02]. turkish republic ministry of foreign affairs. available from: http://www.enerji.gov.tr/en-us/pages/solar. [last accesed on 2018 jul 02]. turkish republic ministry of foreign affairs. available from: http://www. enerji.gov.tr/en-us/pages/wind. [last accesed on 2018 jul 02]. ulutaş, b.h. (2005), determination of the appropriate energy policy for turkey. energy, 30(7), 1146-1161. wang, j.j., jing, y.y., zhang, c.f., zhao, j.h. (2009), review on multicriteria decision analysis aid in sustainable energy decision-making. renewable and sustainable energy reviews, 13, 2263-2278. yalcın, n., kahraman, c., bayrakdaroglu, a. (2012), application of fuzzy multi-criteria decision making methods for financial performance evaluation of turkish manufacturing industries. expert systems with applications, 39, 350-964. yao, j.s., wu, k. (2000), ranking fuzzy numbers based on decomposition principle and signed distance. fuzzy sets and systems, 116, 275-288. zhao, r., govind, r. (1991), algebraic characteristics of extended fuzzy number. information science, 54(1-2), 103-130. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(4), 28-32. international journal of energy economics and policy | vol 8 • issue 4 • 201828 effects of retailing selling prices of petrol and diesel on food prices nor ermawati hussain1*, mohd shahidan shaari2, diana nabila chau abdullah3 1school of social and economic development, universiti malaysia terengganu, malaysia, 2school of business innovation and technopreneurship, universiti malaysia perlis, malaysia, 3faculty of business, economics and accountancy, universiti malaysia sabah, malaysia. *email: ermawati@umt.edu.my abstract oil is the main commodity for all countries in the world. hence, the fluctuation in the price of the commodity has alarmed policy makers as it can cause severe problems such as food price inflation. the effects of oil prices on food prices have remained a topic of debate. therefore this study aims to shed some light on the effects of oil prices (ron95, ron97, diesel) on food prices in malaysia. the autoregressive distributed lag approach was employed and the results show that the price of petrol does not have any effect on food prices. the price of diesel was found to be detrimental to the economy as it can trigger inflation in the long run. however in the short run, the prices of petrol and diesel do not inflict any food price inflation in malaysia. therefore, the malaysian government should control the price of diesel to avert any food price inflation in the long run. keywords: ron95, ron97, diesel, food prices jel classifications: q18, q3, q31 1. introduction the fluctuation of oil prices in the world has merited serious attention from policy makers. this fluctuation appears to threaten the economy in all over the world. oil is perceived to be one of the main commodities used in generating economic activities. therefore, any increase in the price can cause an alarming economic condition. the exorbitant increase in the price oil may drag the economy into recession (tverberg, 2013). ftiti et al., 2016 stated that a higher price of oil can affect economic growth. cunningham (2016) argued that a higher oil price can benefit oil exporting countries as it can cause their revenue to escalate. several studies stated that an increase in the price of oil does not only affect economic growth but also affects inflation (neely, 2015; ali et al., 2012; shaari, et al., 2012; leblanc and chin, 2004). a higher price of oil can lead to inevitability of higher prices of goods, including that of agricultural products. oil is not the main input in the industrial sector only but also in the agricultural sector. the sector requires oil to operate machinery and to transport agricultural products, namely food, to consumers. therefore, oil price increases can affect food prices. alom et al. (2011), jebabli et al. (2014), aye, (2015) believed that food prices will be influenced by oil prices. all of these studies investigated the effects of oil price using data on the crude oil price as the proxy for the price of oil. although there are a large number of previous studies that investigated the effects of oil prices on food prices, the effects of disaggregate oil prices such as ron95, ron97 and diesel on food prices have yet to be explored. therefore this study aims to examine the effects of those prices on food prices in malaysia. a change in these retailing selling prices of petrol and diesel does not reflect the change in the crude oil price. malaysia is one of the countries that imports food, and presently, malaysia has moved towards the development of industrial crops such as palm oil, rubber, cocoa (arshad and shamsudin, 2006). nevertheless, the increase in the price of crops recently has served as a great challenge to the country. this increase was due to the increase in the price of oil (alom et al., 2011). the change in crude oil prices appears to be unpredictable, just like the price of petrol and diesel in malaysia. after the subsidiary removal from oil, it fuelled a robust argument over the increase in the price. figure 1 hussain, et al.: effects of retailing selling prices of petrol and diesel on food prices international journal of energy economics and policy | vol 8 • issue 4 • 2018 29 shows the prices of ron95, ron97 and diesel in malaysia from january 2010 to december 2015. based on the figure 1, it can be seen that the price of petrol and diesel in malaysia exhibited fluctuations over the period. the lowest price of ron97 was 2.00 myr (february 2015) and the highest price of ron97 was 2.90 myr. for ron95, the lowest price over the period was 1.80 myr and the highest price of ron95 was 2.30 myr (october 2014 and november 2014, respectively). while the lowest diesel price was 1.60 myr (december 2015) and the highest diesel price was 2.23 myr (december 2014). 2. literature review to shed some light on the effects of oil prices on food prices, numerous previous studies have been reviewed and divided into two perspectives. one is on the food prices and second is on the specific food prices such as maize, soybean, and corn. a large number of previous studies explored the effects of world oil prices on food prices in various countries and most of them found consistent findings (alom et al., 2011; khan and ahmed, 2013; jebabli et al., 2014; aye, 2015). alom et al. (2011) attempted to examine the effects of oil price on food prices in several countries such as australia, new zealand, hong kong, and thailand. the var approach was employed to analyse the data from 1995 to 2010. in addition, this study divided the data into two periods: 1995–2001 and 2002–2010. the results showed that there is an effect of the world price on food prices in selected countries, however the magnitude of the effects for each country is different from each other. the distinguished magnitude is also dependent on the time horizons. khan and ahmed (2013) investigated the connection between global food prices and oil prices from january 1990 to july 2011 in pakistan. the study also incorporated several macroeconomic variables such as real income, inflation rate, exchange rate interest rate, etc., as their independent variables in their model. the structural vector autoregressive (var) approach was employed and the results showed that there is an undesirable effect of oil prices on food prices in pakistan. jebabli et al. (2014) investigated the effects of the world crude oil prices on food returns in the united states. the novelty of this study is that it included the effects of stock market price on food prices. the same method which is var, was employed to analyse the data from 1980 to 2012. the results consistently showed that crude oil prices can affect food returns albeit a little. aye (2015) was also interested in investigating the effects of oil prices on food prices. the var approach was also employed to analyse the annual data from 2002 to 2014 collected from south africa. the results showed that there is a significant effect of oil price changes on food prices in south africa. several studies investigated the effects of oil prices on specific food prices, for example. ghaith and awad (2011) investigated the effects of oil prices on food commodity prices such as maize, wheat, soybean and barley in thailand, usa, malaysia, canada, u.k, dubai and west texas, from 1980 to 2009. the study employed the johansen cointegration and granger causality and the results showed that there is an effect of oil price on food commodities prices. fernandez (2015) examined the effects on the prices of maize, soybean and sugar in the united states. the var approach was applied to analyse the monthly data from 1982 to 2012. the results showed that there is a relationship between oil price and soybean and maize prices. this suggests that an increase in oil price can cause the prices of soybean and maize to increase simultaneously. on the contrary, the oil price does not have any effect on sugar prices. regardless of the method applied, pei et al. (2017) supported that oil price can leave an effect on sugar price. the study investigated the effects of oil prices on sugar prices in malaysia by using the vector error correction model (ecm) approach. their findings showed that oil price can affect sugar price. 3. methodology the main focus of this study is the price of petrol (ron97 and ron95), diesel, food price and money supply in malaysia. this study used secondary data in the form of monthly time series from january 2010 to november 2015. while the method used is the autoregressive distributed lag (ardl). the main equation for this study is: lnfpt=β0+β1lnr97t+β2lnr95t+β3lndt+β4lnm3t+εt (1) source: ministry of domestic trade, co-operatives and consumerism, 2016 figure 1: oil price for ron97, ron95 and diesel hussain, et al.: effects of retailing selling prices of petrol and diesel on food prices international journal of energy economics and policy | vol 8 • issue 4 • 201830 whereas fp is food price, r97 is ron97 price, r95 is ron95 price, d is diesel price, m3 is money supply, t is year and y used seconthe unit root tests are conducted to see the stationary of dependent and independent variables at level and first differentiation. all the variables will be tested for stationary before moving to the next step. using the augmented dickey-fuller 1981 test, if there is no unit root, then h1 is accepted and h0 should be rejected and vice versa. after that, the ardl model introduced by pesaran et al. (2001), was employed to see the relationship between short-term and long-term between the dependent variable and independent variables. so based on equation (1), the model for this ardl is: lnfpt= β0+β1lnr97t+β2lnr97t−1+β3lnr95t+β4lnr95t−1+β5lndt +β6lndt−1+β7lnm3t+β8lnm3t−1+δ1lnfpt−1+εt (2) when the time lag is 1, then lnfpt−1= β0+β1lnr97t−1+β2lnr97t−2+β3lnr95t−1+β4lnr95t−2+β5lndt−1 +β6lndt−2+β7lnm3t−1+β8lnm3t−2+δ1lnfpt−2+εt−1 (3) substitute fpt−1 (equation 3) into equation (2): lnfpt= β0+β1lnr97t+β2lnr97t−1+β3lnr95t+β4lnr95t−1+β5lndt +β6lndt−1+β7m3t+β8m3−1+δ1[β0+β1lnr97t−1+β2lnr97t−2 +β3lnr95t−1+β4lnr95t−2+β5lndt−1+β6lndt−2+β7lnm3t−1 +β8lnm3t−2+lnfpt−2+μt−1+μt lnfpt= β0+β1lnr97t+β2lnr97t−1+β3lnr95t+β4lnr95t−1+β5lndt + β 6 l n d t − 1 + β 7 l n m 3 t + β 8 l n m 3 t − 1 + δ 1 β 0 + δ 1 β 1 l n r 9 7 t − 1 +δ 1β 2lnr97 t−2+δ 1β 3lnr95 t−1+δ 1β 4lnr95 t−2+δ 1β 5lnd t−1 + δ 1 β 6 l n d t − 2 + δ 1 β 7 l n m 3 t − 1 + δ 1 β 8 l n m 3 t − 2 + δ 1 l n f p t − 2 +δ1μt−1+μt (4) suppose that |β2|<1 is replaced in equation 4 and then equation (5) is obtained as follows: ( ) ( ) ( ) ( ) 1 t 3 t 5 t 7 t i-1 i-1 1 2 1 1 t-i 1 4 1 3 t-ii=1 i=1 i-1 i-1 1 6 1 5 t-i 1 8 1 7 t-i ti=1 i=1 lnfp + lnr97 lnr95 + lnd + lnm3 + lnr97 lnr95 lnd lnm3 t ∞ ∞ ∞ ∞ = + + + + + ∑ ∑ ∑ ∑ γ β β β β δ β δ β δ β δ β δ β δ β δ β δ β ε (5) w h e r e a s γ = β 0 ( 1 + δ 2 + δ 1 2 + δ 2 2 + … ∞ ) = β 0 / ( 1 − δ 1 ) a n d εt=μt+δ1μt−1+δ1 2μt−2)+…∞, while the differentiation model as follows: ∆lnfpt=α+β1∆lnr97t+β2∆lnr95t+β3∆lndt+β4∆lnm3t+μt (6) boundary tests are conducted to see the difference between f-statistic and critical values. if the f-statistic value is less than the critical value, then h0 will be accepted at a certain level, and vice versa. next, the wald test was conducted aims to identify longterm relationship between the variables (abdullah and habibullah, 2008). the relationship between the dependent variable and the independent variable is as follows: t 0 1 t-1 2 t-1 3 t-1 4 t-1 5 t-1 9,i t-i 10, p i=1 q1 i t-i q2 i=1 i=1 q3 q4 i 1 11,i t-i 12,i t-i 13,i t-i ti=1 lnfp = + lnfp + lnr97 + lnr95 + lnd + lnm3 lnfp lnr97 lnr95 lnd lnm3 u = + + + ∆ + + ∆ ∆ + ∆ ∆ ∑ ∑ ∑ ∑ ∑ β β β β β β β β β β β β (7) where δ is the first differentiation stage and equation (4.17) can also be considered as the ardl model where this model is known as a model (p, q1, q2, q3, q4). the akaike information criterion is used to select the lag to continue the study. the ecm test is to detect the existence of a long-term ecm as well as to see the short-term relationship that exists between independent variables and dependent variables. the ecm is as follows: p q 1 t i t-i j t-ji=1 j=1 q=2 q=3 m t-m p t-pm=1 p=1 q=4 r t-r t-1 tr=1 lnfp = lnfp lnr97 lnr95 lnd lnm3 vecm = + ∆ + ∆ + ∆ + ∆ + ∆ + + ∑ ∑ ∑ ∑ ∑ µ ∅ ϕ γ η µ ε (8) where φ, ϕ, γ, η, and μ is a dynamic coefficient for the short term while v is a speed adjustment for long-term error correction. finally, the diagnostic and cumulative sum of recursive residual (cusum) tests and cumulative sum of square of recursive residuals (cusumsq) will be executed. 4. results 4.1. unit root test results the unit root test is conducted to find out the stationarity of all the data selected in this study. the results is recorded in table 1. based on the table 1, it can be learnt that all the variables are not significant at level for both intercept with and without trends, and thus they are not stationary except for ron95. at first difference, the data are significant, and thus they are stationary for both intercept and intercept with trend. 4.2. ardl the bound test must be conducted prior to the ardl test. this test is compulsorily conducted to see the presence of cointegration. the results for the bound test is recorded in table 2. based on the table 2, the results show that the value of test statistic is higher than upper bound at a significant level of 2.5%. therefore, there table 1: unit root test results variables intercept intercept+trend level first different level first different diesel 2.458855 7.2768* 2.405163 7.329222* ron97 1.833817 7.256798* 1.488713 7.490991* ron95 2.819971*** 7.733150* 3.970212** 7.730698* m3 0.936171 9.718928* 1.410553 9.731209* fp 0.319862 8.200879* 3.057938 8.160994* *,** and ***indicates the rejection of the null hypothesis of non-stationary at 1%, 5% and 10% significance level respectively hussain, et al.: effects of retailing selling prices of petrol and diesel on food prices international journal of energy economics and policy | vol 8 • issue 4 • 2018 31 is an existence of a long-run relationship between the independent variables and dependent variable. then, we can proceed with the ardl approach to see which dependent variable can affect food prices in the long run. table 3 shows the results of long-run relationship using ardl approach. based on the table 3, it can be seen that money supply is significantly connected with food prices. it means that an increase in money supply can results in higher food prices in the long run. apart from that, diesel is also significantly associated with food prices with the coefficient value of 4.716. therefore a 1% increase in diesel can cause food prices to increase by 4.7% in the long run. other than that, ron95 and ron97 does not have any significant on food prices. table 4 shows the results for the short-run relationship using the ardl approach. the results show that money supply is related to food prices as it is significant at 5%. it suggests that as a higher money supply, food prices will be on the rise. besides, the prices of ron95, ron97, and diesel are not significantly related to food prices. this means that an increase in the disaggregate oil prices does not have any effect on food prices in the short run. the value of ect is negative and significant, thus it confirms the existence of cointegrated relationship. its coefficient is −0.915 and this means that the deviations from the long-run equilibrium among the variables are corrected by 9% within a month. to see the goodness of our model, several diagnostic tests are conducted. the results are recorded in table 5. based on the table 5, it can be seen that the result for breusch-godfrey serial correlation lm test indicates that it is significant. therefore, there is no autocorrelation in our model. besides, the heteroskedasticity test based on breusch-pagan-godfrey is also performed and the result show that it is also not significant. it indicates that there is no heterokedasticity in our model. based on the two tests, it can be concluded that the model is good to explain the results. figures 2 and 3 shows the cusum and the cusumsq, respectively. based on the figures 2 and 3, it can be seen that the plots within the boundaries suggest that the model is good. 5. conclusion this study aims to investigate the effects of petrol and diesel prices on food prices in malaysia, using monthly data from 2010 to 2015. there are several tests conducted in this study. first is the unit root test, and the results show that all the variables are not stationary at level for both intercept and intercept with trends, except for ron95. when the test is conducted at first difference, the data become stationary. second is the bound test, and the results show that there is a cointegrated relationship, implying an existence of a long-run relationship between disaggregate oil prices and food prices. then, the long-run test using ardl approach is conducted and the results show that an increase in the prices of diesel and money supply can trigger food price inflation in the long run. besides, a rise in the prices of ron95 and ron97 do not have any effect on food prices in the long run. the short-run test table 2: bounds test null hypothesis test statistic value k f statistic 4.48 4 critical value bounds significance |0 bound |1 bound 10% 2.45 3.52 5% 2.86 4.01 2.5% 3.25 4.49 1% 3.74 5.06 table 3: long-run relationship variable coefficient std. error t-statistic p ron97 15.690861 18.513147 0.847552 0.4000 m3 0.000035 0.000005 6.605006 0.0000* ron95 1.570265 18.255216 0.086017 0.9317 diesel 4.715794 2.287206 2.061814 0.0435** c 7.739047 10.902500 4.378725 0.0000* * and **indicate significant at 1% and 5% significant level table 4: short-run relationship variable coefficient std. error t-statistic p ron97 −1.358346 1.441726 −0.942167 0.3498 m3 0.000003 0.000001 2.127322 0.0374** ron95 0.123056 1.445181 0.085149 0.9324 diesel −0.162318 0.516540 −0.314241 0.7544 ect −0.915091 0.437505 −2.091612 0.0406** * and **indicate significant at 1% and 5% significant level. ect: error correction term table 5: diagnostic tests results test statistic f-statistic (p) breusch-godfrey serial correlation lm test 0.489082 (0.949674) heteroskedasticity test: breusch-pagan-godfrey 0.602938 (0.7718) figure 2: cumulative sum of recursive residual figure 3: cumulative sum of square of recursive residual hussain, et al.: effects of retailing selling prices of petrol and diesel on food prices international journal of energy economics and policy | vol 8 • issue 4 • 201832 using ardl approach is also conducted and the results indicate that higher prices of disaggregate oil do not lead to food price inflation in the short run. these findings can shed some light on the issue of the effects of oil prices on food prices in malaysia. policy makers can formulate the right policies to ensure that food price inflation will not transpire. the malaysian government does not need to control the prices of ron95 and ron97 as these prices will not inflict any inflation on the economy. the price of diesel merits the government’s control in order to cushion the blow of food price inflation in malaysia. references abdullah, h., habibullah, m.s. (2008), ko-integrasi pertumbuhan ekonomi dan dasar fiskal di malaysia dan indonesria: pendekatan ujian sempadan autoregresi lat tertabur (ardl). prosiding perkem iii, 2008. ali, s.a., ramzam, m., razi, m., bhatti, a.g. (2012), the impact of oil prices on food inflation in pakistan. interdisciplinary journal of contemporary research in business, 3(11), 123-140. alom, f., ward, b.d., hu, b. (2011), spillover effects of world oil prices on food prices: evidence for asia and pacific countries. proceedings of the 52nd annual conference new zealand association of economists. p29. arshad, f.m., shamsudin, m.n. (2006), implication of oil price increase on the malaysian food system. country report. aye, g.c. (2015), the effect of oil price uncertainty on food price in south africa. international journal of social, behavioral, educational, economic, business and industrial engineering, 9(5), 1380-1385. cunningham, n. (2106), the economy needs higher oil prices-goldman sachs. oil and energy news. available from: http://www.oilprice. com. fernandez, a., gonzalez, a., rodriguez, d. (2015), sharing a ride on the commodities roller coaster: common factors in business cycles of emerging economies. imf working papers wp/15/280. ftiti, z., guesmi, k., teulon, f., chouachi, s. (2016), relationship between crude oil prices and economic growth in selected opec countries. the journal of applied business research, 32(1), 11-22. ghaith, z., awad, i. m. (2011), examining the long term relationship between crude oil and food commodity prices: co-integration and causality. international journal of economics and management sciences, 1(5), 62-72. jebabli, i., arouri, m., teulon, f. (2014), on the effects of world stock market and oil price shocks on food prices: an empirical investigation based on tvp-var models with stochastic volatility. working paper series no. 2014-209. khan, m.a., ahmed, a. (2013), macroeconomics effects of global food and oil price shocks to the pakistan economy: a structural vector autoregressive (svar) analysis. the pakistan development review, 50(4), 1-26. leblanc, m., chin, m.d. (2004), do high oil prices presage inflation? the evidence from g-5 countries. economic research service, 4, 1-25. ministry of domestic trade, co-operatives and consumerism. (2016), portal. available from: http://www.kpdnkk.gov.my. neely, c.j. (2015), how much do oil prices affect inflation?. economic synopses 10. pei, t.l., shaari, m.s., ahmad, t.s.t., junoh, m.z.m. (2017), do oil price changes matter to sugar price in malaysia. international journal of applied business and economic research, 15(5), 75-86. pesaran, m.h., shin, y., smith, r.j. (2001). bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16, 289-326. shaari, m.s., hussain, n.e., abdullah, h. (2012), the effects of oil price shocks and exchange rate volatility on inflation: evidence from malaysia. international business research, 5(9), 106-112. tverberg, g. (2013), how high oil prices lead to recession. our finite world. available from: https://www.ourfiniteworld.com/2013/01/24/ how-high-oil-prices-lead-to-recession/. . international journal of energy economics and policy | vol 9 • issue 3 • 2019 313 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(3), 313-319. the spillover effects of investment, economic growth and electricity consumption: an application mathematical dynamic industry-related models approach#1 cheng-yih hong1, yu-shuang yen2*, tsai-rong lee3 1faculty of finance, chaoyang university of technology, taiwan, 2department of business administration, chaoyang university of technology, taiwan, 3taipei municipal zhongshan, girls high school, taichung, taiwan. *email: hcyih@cyut.edu.tw received: 21 january 2019 accepted: 27 march 2019 doi: https://doi.org/10.32479/ijeep.7584 abstract the economic growth pattern of investment has been proved in asian countries, but it often falls into development bottleneck after the economy develops to a certain extent, especially in countries with lack of resources. one of the important reasons is the supply of energy and electricity. establishing a sustainable development path requires thinking about economic development and environmental protection at the same time. this will face how to establish a balanced industrial structure and a stable electricity supply system, and investment in production equipment and research and development (r&d) will be an indispensable factor. r&d investment and equipment investment contribute to economic growth. this study employs a dynamic industry-related model to estimate the economic spillover effect from both r&d investment and equipment investment. the present study attempts to measure (1) the difference in the investment multiplier of r&d investment and equipment investment, (2) the difference in the employment creation effect of investment r&d and equipment investment. analysis of future industrial development strategies needs to consider energy and electricity consumption. this study will estimate (3) the impact of equipment investment and r&d investment on power consumption, and compare the differences between the two on the industry. this study uses mathematical dynamic industry-related models to estimate (1) ~ (3) and found that different investment methods will make the inter-industry economy have different spillover effects, and also show different demand in power consumption. keywords: research and development investment, equipment investment, dynamic industry-related model, electricity consumption jel classifications: c60, o30, q43, q56 # we acknowledge financial support from ministry of science and technology, taiwan (most 106-2410-h-324-001). 1. introduction under the influence of liberalization in the 1990s, taiwan was pressured by the international community to relax control on trade and the financial market. to address the issues of slow economic growth and environmental protection needs, the government launched a 6-year national development plan (1991-1996) to achieve full-scale balanced development. nevertheless, taiwanese industry structures have remained unadjusted because of insufficient domestic investment and massive capital outflows. the global financial crisis in 2008 has resulted in a severe economic downturn in taiwan, highlighting the enduring failure in industrial restructuring and the necessity of a policy review (hong and li, 2015). after the financial crisis, governments and companies tried to solve economic shocks with research and development (r&d) and equipment investment strategies to increase employment and increase competitiveness. numerous studies have shown that energy price fluctuations can cause tremendous economic loss when economic growth this journal is licensed under a creative commons attribution 4.0 international license hong, et al.: the spillover effects of investment, economic growth and electricity consumption: an application mathematical dynamic industry-related models approach international journal of energy economics and policy | vol 9 • issue 3 • 2019314 hinges excessively on energy consumption (bruno and sachs, 1985; hamilton, 1983; davis and haltiwanger, 2001; lee, et al., 2002;hong and hsu., 2018). therefore, the stability of energy prices does not only affect production costs but also constitutes a vital factor influencing economic development (huang et al., 2015a; 2015b). how to achieve economic development given these conditions in taiwan warrants discussion? over the past two decades, high technology has become the driver fueling economic growth in taiwan. nevertheless, sustained r&d is imperative for maintaining competitiveness in high technology industries. effective r&d investment can boost productivity and create added values (tv) (hong et al., 2017). improved productivity can increase profits by reducing energy consumption while achieving the objective of economic growth (heintz et al., 2009;ramey, 2011). huang et al. (2015a; 2015b) found that following its entry into the world trade organization, taiwan has exhibited increasingly high imported-energy intensity and considerably heightened sensitivity to energy prices, implying the taiwanese economy has become more restricted by its reliance on energy. achieving sustainable economic development in a country necessitates advances in r&d technologies and equipment investment, which enable a country to adapt to changes in the international economic environment and realize industrial restructuring (hong et al., 2017). on the other hand, taiwan’s economic development requires a stable supply of electricity, and advanced equipment renewal is a way to improve energy efficiency. economic development and industrial structure affect electricity consumption, and the electricity consumption coefficient of the industry also affects the level of electricity consumption. the stability of energy and electricity supply has become a key factor in taiwan’s economic development, through r&d and production equipment renewal as one of the solutions. this research focuses on the economic effects of r&d and equipment investment, and estimates the electricity consumption of the industry, and compares the spillover effects of r&d and equipment investment between different industries. in order to achieve the above issues, this paper will use economic dynamic industry-related models to analyze economic effects and electricity consumption. 2. literature review investing in economic development is the experience of many countries, but it is accompanied by environmental pollution. the development experience in the east asian region is to achieve economic growth through investment. there are many ways to invest, such as r&d, equipment updates, or infrastructure. investment to increase economic efficiency through r&d or equipment renewal to drive economic growth. but as economic growth increases energy consumption (lee, 2006; ewing et al., 2007; ozturk, 2010; acaravci and ozturk, 2010; ozturk and acaravci, 2011), the increase in electricity demand has led to a significant increase in gas emissions. both growth hypothesis and conservation hypothesis point to the important relationship between power consumption and good economic development, but the two hypotheses also have different opinions. among them, ozturk and acaravci (2011) found that among the countries surveyed, some countries did not show a cointegration relationship between electricity consumption and economic growth. in addition, there are some literatures that analyze the relationship between economic growth and electricity consumption from the perspective of urbanization (lenzen et al., 2006; parshall et al., 2010; liddle, 2013; liddle and lung (2014); salim and shafiei, 2014; liddle and messinis, 2015; kasman and duman, 2015). both parshall et al. (2010) and salim and shafiei (2014) have found a positive correlation between electricity consumption and urbanization, and liddle’s (2013) study proves that urbanization is related to economic growth. grossman and krueger (1991) pointed out that after the economic development reaches a level, the environmental kuznets curve phenomenon will occur, but a sustainable economic development is considered together with the environmental impact of energy consumption and greenhouse gas emissions. however, with the changes in the international environment, from liberalization, internationalization to globalization, some studies have analyzed the pollution haven hypothesis from international trade (hong et al., 2017;behera and dash, 2017; solarin et al., 2017) sun et al., 2017; zhu et al., 2016; zhang and zhou, 2016; zakarya et al., 2015; dean et al., 2004; dasgupta et al., 1999; 2001). 3. empirical model 3.1. industry-related spillover model the supply-demand equilibrium equation of the competitive import type of the industry-related spillover model could be constructed as. x f e x m i nij i d i i ij n + + = + = =∑ , , ,1 21 (1) a x f e x m i nij j i d i i ij n + + = + = =∑ , , ,1 21 (2) where aij= xij/xj; aij is the input coefficient which denotes the input from industry i per output for industry j (i = 1,…, n; j = 1,2,…n); xj represents the total output of industry j and xij stands for per output for industry j resulting from the input of industry i. m m a x f i ni i ij j i d j n = + =∑( ), , ,1 2=1 (3) combining equations (2) and (3), we obtained as follows x m a x m f e i ni i ij j i i d ij n − −( ) = −( ) + = =∑1 1 1 21 , , , (4) in terms of matrix, equation (4), which is the competitive import type of the industry-related spillover model, could be rewritten as. x i i m a i m f ed= − −( ) −( ) +−[ ] [ ]1 (5) [ ]i i m a− −( ) −1 is the leontief inverse matrix, which is so called leontief multiplier. to compare the differences in the investments made by the private and public sectors, we compiled the following equilibrium equations for the dynamic industry-related model: hong, et al.: the spillover effects of investment, economic growth and electricity consumption: an application mathematical dynamic industry-related models approach international journal of energy economics and policy | vol 9 • issue 3 • 2019 315 x(t) = ax(t)+cp+cg+k[x(t−1)−x(t)] (6) based on the value-added rate, the earning of enterprises and laborers (y(t)) can be estimated using. y(t) = vt x(t) (7) vt is the vector of the value-added rate. cp = hc c y(t) = hc c v t x(t) (8) c is the consumption rate, and hc is the vector of consumption patterns. x(t) = ax(t)+(cp+cg)x(t)+kp+kg [x(t+1)−x(t)] (9) where cp is private sector consumption and cg is government sector consumption; kp is private sector investment and kg is government sector investment, as shown in the following equations: specifically, the scale of government consumption (cg) is determined by budgetary planning. therefore, c = hc c v t x(t)+cg. assuming d = i−a−c, the dynamic model can be written as x(t+1) = (k–1d+i)x(t) (10) in this study, we adopted an industry-related model featuring open competition. therefore, the dynamic industry-related model is, x t k d i i a i m e i m f d+( ) = +( ) − −( )  + −( ) − − 1 1 1 (11) when estimating the intrinsic value and intrinsic vector of (k−1d+i) in (10), let η be the intrinsic value of d−1k and the intrinsic vector be τ: d−1kτ = ητ ( )1 1( 1)k d i− + = +   1 ( 1)+  is the intrinsic value of k−1d+1, and τ is the corresponding intrinsic vector. x t k d i i a i m e i m f d+( ) = +( ) − −( )  + −( ) − − 1 1 1 (12) following equation (12), in the present study we would estimate the direct, the first, the second direct spillover effects. the measures could be constructed measurement of the direct and indirect effects the direct effects the direct effect is the product of change in domestic final demand δ fi d and rate of self-supplying ( )i m− , that is. ( ) dii m f− (13) total economic spillover effects let leontief inverse matrix be ( )[ ( )]k d i i a i m− −+ − −1 1 , *γ the formula that we could estimate the total economic spillover effects of the consumption expenditures from chinese tourists on taiwan’s economy could be restated as tese i m f total economic spillover effects d direct spillove � = −( )δ 1 rr effects d first indirect spillover effects i m f� ��� ��� + −γ * ( )δ 1 �� ��� ��� � ��� ��� + −γ* ( )i m f d second indirect spillover effects δ 2 (14) 3.2. measurement of the persons employed the total gross induced tv is formulated as equation (15), consisting of the direct gross tv, the first and the second indirect gross tv. tv w i m f total gross induced added value j g d direct gross indu � = −( )δ 1 cced added value j g d first indirect gross ind w i m f � ��� ��� + −γ* ( )δ 1 uuced added value j g d second indirect gros w i m f � ���� ���� + −γ* ( )δ 2 ss induced added value � ���� ���� (15) the formula for total induced income of employment (te) that we could estimate the direct and indirect induced income of employment. te w i m f total induced income of employment j l d direct income � = −( )δ 1 oof employment j l d first indirect induced in w i m f � ��� ��� + −γ * ( )δ 1 ccome of employment j l d second indirect in w i m f � ���� ���� + −γ * ( )δ 2 dduced income of employment � ���� ���� (16) we developed a dynamic model that features investment as an endogenous factor to estimate electricity consumption. 3.3. electricity consumption estimate electricity consumption e i m felectricity d direct spillov = −( )δ 1 eer d first indirect spillove electricitye i m f � ���� ���� + −γ* ( )δ 1 rr d second indirect spillo electricitye i m f � ����� ����� + −γ* ( )δ 2 vver � ����� ����� (17) e e e electricity electricity n electricity =           1 0 0 � � � � � e electricity xj electricity j j = , j = 1,2…n w h e r e t h e e l e c t r i c i t y c o n s u m p t i o n c o e f f i c i e n t e electricity xj electricity j j = , and eelectricity is the diagonal matrix of hong, et al.: the spillover effects of investment, economic growth and electricity consumption: an application mathematical dynamic industry-related models approach international journal of energy economics and policy | vol 9 • issue 3 • 2019316 the elements of the electricity consumption coefficients for various industries. 4. empirical results 4.1. economic spillover effects of investment based on the nature of the industries, we divided the 166 sectors listed in the report on 2015 input-output tables into seven major industries. table 1 shows the economic effects of r&d investment on various industries. the results indicate the effects were most prominent in the machinery and service industries, accounting for 36% and 33.69% of the overall effects, respectively. this is primarily because r&d involves the purchase of raw materials used to produce machinery and electronics-related products, indirectly increasing the crude value-added and income from employment in relevant industries. this triggers subsequent demands for the machinery and electronics industries and the service industry. regarding the economic effects of equipment investment on various industries, equipment investment had the most significant economic spillover effects on machinery-related industries and the infrastructure industries, as shown in table2. specifically, the economic effects on machinery-related industries accounted for 50.92% of the overall economic spillover effect. the effect on the infrastructure industries accounted for 26.77% of the overall effect. the results differed slightly from the effects of government sector investment. this is primarily because private investments in electronics-related industries are equipment investment. although improving production technologies can enhance productivity, 30% of the equipment is imported. consequently, the direct economic spillover is minor. both r&d investment and equipment investment exhibited decreased first economic spillover effects on agriculture-related industries and the light industries. nevertheless, the ultimate economic spillover effect of r&d investment increased whereas equipment investment had negative economic effects on agriculture-related industries. 4.2. employment effects of investment estimations regarding the number of jobs created in various industries by r&d investment and equipment investment are table 1: economic effect of r&d investment sector raw material induced value first spillover effects second spillover effects total (%) agriculture-related 84.32 −91.91 1,750.71 1,743.12 (2.10) light industry 821.07 −192.17 724.98 1,353.87 (1.63) chemical-related 4,562.62 5,429.43 1,481.23 11,473.27 (13.85) iron, non-iron 1,337.05 −810.85 172.42 698.62 (0.84) machinery-related 17,106.58 7,723.94 4,985.54 29,816.07 (36.00) infrastructure 958.60 9,778.06 −894.86 9,841.81 (11.88) service-related 17,490.07 6,580.07 3,835.51 27,905.64 (33.69) total 42,360.31 28,416.57 12,055.53 82,832.41 (100.00) unit: million new taiwanese dollars, r&d: research and development table 2: economic spillover effects of equipment investment sector raw material induced value first spillover effects second spillover effects total (%) agriculture-related 11.42 −2,101.21 1,235.47 −854.32 (−0.85) light industry 480.95 −77.55 511.61 915.01 (0.91) chemical-related 2,906.40 3,996.54 1,045.29 7,948.23 (7.94) iron, non-iron 2,269.12 −1,220.53 121.69 1,170.28 (1.17) machinery-related 43,906.21 3,561.69 3,518.30 50,986.20 (50.92) infrastructure 828.23 26,606.72 −631.51 26,803.44 (26.77) service-related 6,903.73 3,550.17 2,706.73 13,160.63 (13.14) total 57,306.07 34,315.83 8,507.58 100,129.48 (100) unit: million new taiwanese dollars test 3: employment creation on industries sector (1) r&d investment (2) equipment investment (3)=(1)-(2) employment creation (persons) coefficient of employment (persons per million dollars) employment creation (person) coefficient of employment (person per million) (person) agriculturerelated 804 0.46 −1,338 1.5 2,142 light industry 669 0.49 135 0.15 534 chemicalrelated 3,082 0.27 1,258 0.16 1,824 iron, non-iron 402 0.58 603 0.52 −201 machineryrelated 6,483 0.22 7,483 0.15 −1,001 infrastructure 3,378 0.34 5,731 0.21 −2,353 service-related 14,582 0.52 7,000 0.53 7,582 total 29,400 0.35 20,872 0.21 8,528 r&d: research and development hong, et al.: the spillover effects of investment, economic growth and electricity consumption: an application mathematical dynamic industry-related models approach international journal of energy economics and policy | vol 9 • issue 3 • 2019 317 shown in table 3. although the economic spillover effect of r&d investment was most prominent in machinery-related industries, the largest number of jobs created was in service-related industries (14,582 jobs) because the employment multiplier was greater. by contrast, the largest number of jobs created by equipment investment was in machinery-related industries (7,483 jobs). nevertheless, the economic spillover effect on agriculture-related industries was negative; consequently, the number of jobs created decreased by 1,338. the gap between the number of jobs created by r&d investment and equipment investment was most significant in service-related industries, with a difference of 7,582 jobs. however, compared with r&d investment, private investment created more jobs in infrastructure industries and machinery-related industries, with a difference of 2,353 and 1,001 jobs, respectively. in addition to reflecting the difference in the economic spillover effects, the difference in the number of jobs created also showed r&d investment and equipment investment differed in employment multiplier. this result indicates that the employment effect of r&d investment was superior to that of equipment investment in high technology equipment. 4.3. electricity consumptions of economic spillover effects table 4 shows the economic impact of r&d’s investment in electricity consumption. the data shows that machinery-related industries account for 40.12% (215.59 gwh), followed by infrastructure (32.79%) and service-related (15.95%). agriculturerelated and light industry have less economic impact due to r&d, so electricity consumption only accounts for 1.77% (9.53 gwh) and 1.91% (10.28 gwh), which means that r&d’s investment effect is relatively high in the high-tech machinery-related industry. table 5 shows the power consumption required for the economic effects of equipment investment. from the empirical results, the infrastructure industry consumes the most electricity, up to 479.85 gwh, accounting for 51.53% of the total electricity consumption. followed by the machine-related 368.67 gwh (39.59%). it is worth noting that the agriculture-related electricity consumption is negative (−4.67 gwh), mainly due to the shift in investment and the reduction in production caused by the increase in the infrastructure industry. in addition, the impact of equipment renewal investment on service-related industry is smaller than r&d’s investment, and the service-related department’s electricity consumption is only 40.43 gwh. 5. concluding remarks we analyzed the economic spillover effects of r&d investment and equipment investment as well as the number of jobs created. the effects of economic growth involve gross value-added for enterprises, income from employment, and job opportunities. gross value-added, as a basis of capital accumulation, can increase the level of subsequent investment. in addition, the technologies accumulated can contribute to a virtuous cycle of investment. furthermore, increased income from employment and job opportunities can improve spending power, ultimately increasing market demands. on the other hand, when thinking about taiwan’s economic development in the future, we need to consider the issue of energy and electricity consumption. sustainable economic development requires not only investment in production equipment, but also r&d. this study divides investment into equipment investment and r&d investment. it hopes to further clarify the economic and environmental differences between the two, which will help the strategic path of future industrial development. the following paragraphs present the empirical results obtained in this study: 1. the investment multiplier of r&d was 1.40, which was greater than that of equipment investment (1.07). the main table 4: electricity consumptions of r&d investment sector raw material induced value first spillover effects second spillover effects total (%) agriculture-related 0.46 −0.50 9.57 9.53 (1.77) light industry 6.23 −1.46 5.50 10.28 (1.91) chemical-related 11.01 13.10 3.57 27.69 (5.15) iron, non-iron 23.67 −14.36 3.05 12.37 (2.30) machinery-related 123.69 55.85 36.05 215.59 (40.12) infrastructure 17.16 175.05 −16.02 176.19 (32.79) service-related 53.73 20.21 11.78 85.72 (15.95) total 235.96 247.90 53.51 537.37 (100.00) unit: gwh, r&d: research and development table 5: electricity consumptions of equipment investment sector raw material induced value first spillover effects second spillover effects total (%) agriculture-related 0.06 −11.48 6.75 −4.67 (−0.50) light industry 3.65 −0.59 3.88 6.95 (0.75) chemical-related 7.01 9.64 2.52 19.18 (2.06) iron, non-iron 40.17 −21.61 2.15 20.72 (2.23) machinery-related 317.47 25.75 25.44 368.67 (39.59) infrastructure 14.83 476.33 −11.31 479.85 (51.53) service-related 21.21 10.91 8.31 40.43 (4.34) total 404.41 488.95 37.76 931.12 (100.00) unit: gwh hong, et al.: the spillover effects of investment, economic growth and electricity consumption: an application mathematical dynamic industry-related models approach international journal of energy economics and policy | vol 9 • issue 3 • 2019318 difference lies in the size of the direct economic spillover effects. both types of investments had the greatest economic spillover effects on machinery-related industries. the value of investment multiplier reflects the economic spillover effects of investment. in addition to purchasing equipment, r&d investment is also spent on human resources cultivation. these factor input can be satisfied using domestic resources, and the economic spillover effects of the spending can be easily formed domestically. by contrast, equipment investment in equipment relies considerably on importation. in particular, a large proportion of the high technology equipment necessary in capital-intensive industries is imported. consequently, the economic spillover effect of equipment investment was not comparable to that of r&d investment. 2. r&d investment created the most job opportunities in servicerelated industries, whereas equipment investment created the most job opportunities in machinery-related industries. overall, r&d investment created more jobs than private investment. the number of jobs created is determined by the size of investment and the employment coefficient of an industry. in this study, we used nt$100 billion as the initial investment for all industries; therefore, job creation is determined by employment coefficients. generally speaking, employment coefficient is a key indicator employed to differentiate between capitaland labor-intensive industries. the value of employment coefficient determines the number of jobs created by an investment. the results of this study show r&d investment evidently had a greater effect on job creation. this is because increased value-added for enterprises and increased income from employment affected the economic spillover effects on service-related industries, which had relatively high employment coefficients. 3. r&d invests in the largest demand for electricity in machineryrelated industries, while equipment investment is the largest in terms of electricity demand in infrastructure-related industries. the main reason is that investment projects are related to the self-sufficiency rate of investment products. the electricity consumption of equipment investment is 931.12 gwh, and the electricity consumption of r&d investment is relatively small, only 537.37 gwh. 4. from the results of (1) to (3), it is found that the investment methods are different, and the economic spillover effects on all industries are also different. therefore, it also appears in the demand for electricity in various industries. nearly 99% of taiwan’s energy consumption needs to be imported. the road to sustainable development must consider how to balance economic growth and environmental protection. this study analyzes investment equipment updates and r&d to promote economic growth. on the other hand, discussions will increase energy and power efficiency to reduce electricity use. taiwan faces the bottleneck of industrial restructuring, which makes the economy unable to develop smoothly. to solve this problem, renewable energy is used to replace the energy policy of thermal power generation. the transformation of energy policy will drive r&d investment in renewable energy equipment and power systems, which will change taiwan’s industrial structure and power sources, and the future economic development model will be different from the past. take taichung area as an example. taichung city subsidizes more than 2 metric tons of oil-fired boilers to change gas-fired boilers to reduce co2 and pm2.5 emissions (the subsidy scale is equivalent to about 80% of the city’s boilers). such a policy can not only create economic growth, but also improve the environment. in addition, taichung’s renewable energy investment is also a concrete step towards the sustainable development of the city. references acaravci, a., ozturk, i. (2010), electricity consumption-growth nexus: evidence from panel data for transition countries. energy economics, 32(3), 604-608. behera, s.r., dash, d.p. (2017), the effect of urbanization, energy consumption, and foreign direct investment on the carbon dioxide emission in the ssea (south and southeast asian) region. renewable and sustainable energy reviews, 70, 96-106. bruno, m., sachs, j.d. (1985), economics of worldwide stagflation. cambridge, ma: harvard university press. davis, s.j., haltiwanger, j. (2001), sectoral job creation and destruction responses to oil price changes. journal of monetary economics, 48(3), 465-512. dasgupta, s., wheeler, d., mody, a., roy, s. (1999), environmental regulation and development: a cross-country empirical analysis. washington, dc: the world bank. dasgupta, s., laplante, b., mamingi, n. (2001), pollution and capital markets in developing countries. journal of environmental economics and management, 42, 310-335. ewing, b.t., sari, r., soytas, u. (2007), disaggregate energy consumption and industrial output in the united states. energy policy, 35(2), 1274-1281. grossman, g.m., krueger, a.b. (1991), environmental impacts of a north american free trade agreement. national bureau of economic research. nber working paper no. 3914. hong, y.h., li, j.f. (2015), on measuring the effects of fiscal policy in global financial crisis: evidences from an export-oriented island economy. economic modelling, 46, 412-415. hong, y.h., huang, c.h., li, j.f. (2017), investment, energy consumption and co2 emissions: an analysis on the strategy of industry development. international journal of energy economics and policy, 7(4), 138-143. hong, y.h., hsu, c.j. (2018), economic growth, oil consumption and import intensity: factor decomposition of imported crude oil model approach. international journal of energy economics and policy, 8(4), 152-156. heintz, j., pollin, r., garrett-peltier, h. (2009), how infrastructure investment supports the u.s. economy: employment, productivity and growth. amherst, ma: political economy research institute, university of massachusetts-amherst. huang, c.h., su, h.p., yang, c.w., hong, c.y., li, j.f. (2015a), adaptability to energy, production efficiency and crude oil priceevidences from a small open economy. in: energy and sustainability. medellin, colombia: wit press. huang, c.h., su, h.p., yang, c.w., li, j.f., hong, c.y. (2015b), crude oil intensity, production efficiency and adaptability to energyevidences from an economy with highly dependent on energy imports. kobe, japan: the fifth annual asian conference on sustainability, energy and the environment. kasman, a., duman, y.s. (2015), co2 emissions, economic growth, energy consumption, trade and urbanization in new eu member and hong, et al.: the spillover effects of investment, economic growth and electricity consumption: an application mathematical dynamic industry-related models approach international journal of energy economics and policy | vol 9 • issue 3 • 2019 319 candidate countries: a panel data analysis. economic modelling, 44, 97-103. lee, c.c. (2006), the causality relationship between energy consumption and gdp in g-11 countries revisited. energy policy, 34(9), 1086-1093. lee, k., ni, s., ratti, r.a. (1995), oil shocks and the macro-economy: the role of price variability. energy journal, 16(4), 39-56. hamilton, j.d. (1983), oil and the macro economy since world war ii. journal of political economy, 91, 228-248. lenzen, m., wier, m., cohen, c., hayami, h., pachauri, s., schaeffer, r. (2006), a comparative multivariate analysis of household energy requirements in australia, brazil, denmark, india and japan. energy, 31(2), 181-207. liddle, b. (2013), the energy, economic growth, urbanization nexus across development: evidence from heterogeneous panel estimates robust to cross-sectional dependence. the energy journal, 34, 223-244. liddle, b., messinis, g. (2015), which comes first-urbanization or economic growth? evidence from heterogeneous panel causality tests. applied economics letters, 22(5), 349-355. liddle, b., lung, s. (2014), might electricity consumption cause urbanization instead? evidence from heterogeneous panel long-run causality tests. global environmental change, 24, 42-51. ozturk, i. (2010), a literature survey on energy-growth nexus. energy policy, 38(1), 340-349. ozturk, i., acaravci, a. (2011), electricity consumption and real gdp causality nexus: evidence from ardl bounds testing approach for 11 mena countries. applied energy, 88(8), 2885-2892. parshall, l., gurney, k., hammer, s.a., mendoza, d., zhou, y., geethakumar, s. (2010), modeling energy consumption and co2 emissions at the urban scale: methodological challenges and insights from the united states. energy policy, 38(9), 4765-4782. ramey, v. (2011), can government purchases stimulate the economy. journal of economic literature, 49(3), 673-685. salim, r.a., shafiei, s. (2014), urbanization and renewable and nonrenewable energy consumption in oecd countries: an empirical analysis. economic modelling, 38, 581-591. solarin, s.a., al-mulali, u., musah, i., ozturk, i. (2017), investigating the pollution haven hypothesis in ghana: an empirical investigation. energy, 124, 706-719. sun, c., zhang, f., xu, m. (2017), investigation of pollution haven hypothesis for china: an ardl approach with breakpoint unit root tests. journal of cleaner production, 161, 153-164. zakarya, g.y., mostefa, b., abbes, s.m., seghir, g.m. (2015), factors affecting co2 emissions in the brics countries: a panel data analysis. procedia economics and finance, 26, 114-125. zhu, h., duan, l., guo, y., yu, k. (2016), the effects of fdi, economic growth and energy consumption on carbon emissions in asean-5: evidence from panel quantile regression. economic modelling, 58, 237-248. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. tx_1~at/tx_2~at international journal of energy economics and policy | vol 8 • issue 2 • 2018 31 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(2), 31-38. are oil industry mergers becoming less profitable? samuel d. barrows* senior lecturer at stem business school, turan university, kazakhstan and doctorate of business administration candidate, toulouse business school, france. *email: sam_barrows@yahoo.com abstract are oil industry mergers becoming less profitable? this study evaluates oil industry consolidations that occur during the 16-year time frame between 1998 and 2013 to find out. this quantitative study focuses on the stock price total return performance of acquirer companies over a 4 years horizon for each merger transaction. the portfolios created from these transactions provide for an analysis of the economics of the mergers after full integration of target companies. four benchmarks are incorporated to provide various economic adjustment factors. there are seven cases presented that show that oil industry mergers are becoming less profitable. implications are that companies may chase mergers as an easy way to increase returns, but this may not occur. as ever larger companies chase the remaining players and bid up their selling prices, increased returns may not always be the outcome. keywords: oil industry mergers, 1998-2013, brent crude oil jel classification: g15, g34, p18 1. introduction the objective of this study is to evaluate the profitability of oil mergers from 1998 through 2013 by using the stock price total return formula of acquirer companies over a 4 years horizon for each merger transaction. this 16-year time frame is further segmented into two 8-year periods and the two time periods are compared against each other. the research question for this study is: are mergers in the oil industry becoming less profitable? based on the research methods used and the significance of the results, a confirmation of the hypothesis is warranted. indeed mergers in the oil industry are becoming less profitable. seven cases are presented which are used to assess the performance of various groups of acquirers. there are three cases where the two 8-year groups are assessed against each. there is a case which gauges the acquirers group against the oil market and a case which gauges the oil industry against the oil market. this allows for grading the performance of the acquirers group against the oil industry and shows that the acquirers perform inferior to the oil industry and in a statistically significant manner. there are two size delineated cases which look at the small and large targets relative to the acquirers group. when appraising the performance of the size delineated cases based on the targets/acquirers proportions, the smaller relative sized transactions perform better than the larger ones and in a significant manner. three hypotheses are included which quantify the performance of the acquirers to their merger activity. h1: the 1998-2005 period is superior to the 2006-2013 period in the three-factor tests. h2: the acquirers perform worse than the oil industry. h3: proportionally smaller oil industry merger transactions outperform the larger ones. all three hypotheses are confirmed and the study results are consistent which document questionable performance of mergers. the performance of some of the mergers is attractive, specifically the proportionally smaller sized target transactions. there are numerous studies which document the benefits and risks of using mergers for growth as an offensive measure or for consolidating a market position as a defensive measure. the benefits are well documented (andrade and stafford, 2004; hough, et al., 2007; subeniotis, et al., 2011; pratt, 2012; marfo et al., 2013; vild and zeisberger, 2014). the uncertainty surrounding m&a activity is also well documented. there are numerous studies on issues surrounding this uncertainty including the added organizational complexity, increased risk, higher debt loads, and questions on profitability, barrows: are oil industry mergers becoming less profitable? international journal of energy economics and policy | vol 8 • issue 2 • 201832 which if not resolved will reduce the value of the business enterprise (bouwman et al., 2003; sirower and sahni, 2006; furfine and rosen, 2011; subeniotis, et al., 2011; ferrer, 2012; soni, 2014). 2. literature review with the volatile crude oil prices during the 1990s and subsequent fall in prices in 1998, oil companies use efforts in efficiency in order to deliver more consistent shareholder returns (hough, et al., 2007). to grow, the majors could explore for crude oil reserves in the ground through expensive exploration programs (arora, 2015). as with any exploration activity, success is not guaranteed, and typically, the bigger the prize, the higher the cost (mustafa, 2016). the easier alternative to acquire crude oil reserves is to acquire a company that already has the reserves (pratt, 2012). with regard to overall efficiency and profitability, “when done for the right reasons and in the right way, mergers and acquisitions can indeed be beneficial” (marfo et al., 2013). the low stock valuations in the oil industry are triggered by low crude oil prices which have fallen in 1998 both in the us market and in the world market (hough, et al., 2007). these tie-ups are driven by cost cutting efforts to achieve synergies and by 1998, mergers are coming to the oil industry in a big way (hough, et al., 2007). some of the mergers seem to make a lot of sense in that the two companies fit together where one might have an advantage in one geographical area or one business sector (marfo et al., 2013). these mergers can lead to increased profitability in the coming years (andrade and stafford, 2004). also, some of the companies that merge have similar business outlooks and it seems obvious that they would merge with little issue because they have a similar mentality (marfo et al., 2013). the 16-year time frame from 1998 through 2013 sees major upheavals and consolidations in the oil industry. the changes occur due to the fact that it is cheaper and less risky for oil companies to acquire other companies that have crude oil reserves in the ground than to explore for crude oil reserves themselves (arora, 2015). because of changes in the oil industry during this time, it is widely believed in the oil industry that you would either grow or die, and to compete mergers are seen as necessary for continued growth and profitability (marfo et al., 2013). expansion for companies can take place through organic growth where the existing market is expanded, namely when new products are introduced, or through an increasing number of markets (andrade and stafford, 2004). mergers and acquisitions prove their worth when companies need growth to achieve certain economies of scale and economies of scope (subeniotis, et al., 2011). combining forces through a merger of equals or a large firm acquiring a small firm have similar dynamics, they are generally seen as a mechanism for growth (marfo et al., 2013). m&a activity is not without risk (furfine and rosen, 2011). in essence, mergers may create or destroy value depending on how they perform (ferrer, 2012). in the merger game, results are not guaranteed (soni, 2014). also, the results of mergers are not always immediately known (bouwman, et al., 2003). excess premiums paid for the m&a transaction can have negative impacts on company performance for years (sirower and sahni, 2006). there are many reasons behind mergers, but they can be simplified into just a few items: reducing costs, realizing synergies, diversifying product lines, and increasing revenues (subeniotis, et al., 2011). strategic bidders usually have the advantage over other acquirers (vild and zeisberger, 2014). strategic bidders that can realize the synergy benefits usually have an advantage over pure financial players not only because they understand the industry better, but also because they can reduce costs and achieve synergies as they digest the merger (thompson, et al., 2005). in addition, they better understand the markets specifically related to their industry (vild and zeisberger, 2014), in the present case the crude oil markets. as the world economy grows so does the demand for oil (popescu, 2016). the world demand for crude oil in 1995 is 70 million barrels per day, by 2005 it is 82.5 million barrels per day, and by 2015 it exceeds 95 million barrels per day (iea, 2016). along with this growth in demand is a growth in volatility (popescu, 2016). during the last 20 years, there is an increase of volatility in world crude oil prices, but after the global financial crisis in 2008, already volatile crude oil prices increase their volatility even more (ural, 2016). even though the demand for commodities decreases temporarily, volatility remains high (popescu, 2016). the markets are searching for a supply-demand equilibrium (mustafa, 2016). this volatility has effects on the overall profitability of the oil industry (arora, 2015). the oil industry is generally considered to be a profitable industry, and the larger oil companies are generally more consistently profitable in comparison to the smaller ones (ford, 2011). that said, the percentage profitability is much less than the general public perceives since the oil companies are so large (stunda and voltz, 2010). there is also the potential that particularly low and particularly high prices can actually reduce oil company profitability (ford, 2011). oil companies are not always able to capture price increases due to local marketing pressures or global supply issues (arora, 2015). for example, one study found that oil company acquirers performed worse than the brent oil market during the 4 years after the transaction (barrows, 2017). long-term growth in the oil industry requires more consistent returns (baumeister and kilian, 2016). consistent returns require more price stability so that more strategic projects can be successful and companies can maintain their goal of continued growth and profitability (ford, 2011). this is true during the study period from 1998 to 2013 and continues to be the case in the current environment as well. 3. methodology the methodology to collect and evaluate the data is based on an empirical and analytic approach. since the research question is based on share price performance, data provided enables the barrows: are oil industry mergers becoming less profitable? international journal of energy economics and policy | vol 8 • issue 2 • 2018 33 determination of this performance with few ambiguities. this methodological review uses stock price total return performance for the companies selected for the data set. the objective data is accessed using third-party providers, and quantitative methods are used. to sufficiently evaluate performance over time, proper data collection is needed in order to adequately supply the appropriate measurements to make the necessary analysis required to answer the research question. there are six independent third-party providers in use to assemble the necessary data for this paper. they are thomson reuters, dartmouth college, the us energy information administration, known as the eia, the us federal reserve system, the bank of canada, and the reserve bank of australia. 3.1. m&a transactions the screening of data through the thomson reuters product called eikon provides data on all transactions for public, private and government transactions in the world market place and selection begins from the masrch application in the eikon product (thomson reuters, 2017). with regard to the merger transaction size, based on a study on s&p500 firms from 1980 through 2004, the median size of target company acquisitions is $478 million and $163 million for s&p 500 acquirers and non-s&p 500 acquirers, respectively (vijh and yang, 2007). using the average of these two values ($320.5 million) as a guideline, the limit of $300 million is used for the merger transaction value. private and government transactions are excluded as are stock buybacks and exchange offers. this ensures that only publicly-traded, commercial m&a transactions which represent over 50% ownership of the target companies in the oil and gas and petrochemicals industries are chosen, and that each of those transactions exceeds $300 million. if there is more than one transaction for each acquirer within the same calendar year, the total deals for that year are aggregated into one record, the last transaction for that year, in order to account for the increased acquirer size. the concern is that multiple transactions within a short time span, which have similar economics, could skew the results of the study. a similar study that examines the post-acquisition returns of stock deals from 1981 through 2007 uses the same method to avoid similar multiple transactions within a short time frame (mortal and schill, 2015). this is used as the determining guide in this case. for more information on the selection of records for the data set (appendix table 1). not all of the acquirers in the data set are listed on us stock exchanges. there are 148 transactions out of the total of 364 in the data set that are listed on non-us stock exchanges on the transaction dates. this represents 41% of the total transactions in the data set. making deal size comparisons is not an issue since this field is already converted to usd. making price comparisons is also not an issue since prices within the 4-year horizon are in the same currency. however, the acquirer size is stored in the currency of the stock exchange where the acquirer is listed. for these transactions, the proper currency exchange rates based on the acquirer location and date effective are retrieved. the calculations for all returns for both the merger data and the comparative benchmarks are made on a before tax basis. hence, the tax issue is deemed outside of the scope of this study and comparisons are made on a before tax basis. through the initial analysis performed for this study, and while fine-tuning the research question, it becomes obvious to the author that a 4-year horizon provides a more stark comparison and show more contrast between mergers that succeed and those that fail. after 4 years, results become clear. other studies also confirm this and show that premiums paid for an acquisition can reduce the acquirer company returns up to 4 years after the transaction (sirower and sahni, 2006), or up to 5 years after a merger announcement (bouwman, et al., 2003). hence, the 4-year horizon is chosen as the focus for this study. this study focuses on the longer-term returns after integration. if extending the term means that the acquirer subsequently changes its standing (through bankruptcy or acquisition), the final price recorded in the 4-year horizon is still the measurement that is used. that said, there are 48 transactions where the acquirers are delisted within the 4-year horizon. there is a risk that this longer-term view could skew the results either to the negative or to the positive, but since the last posted price is used, this risk is seen as limited. in order to provide a more complete picture of the stock price total return dynamics, the first data point in the 4-year horizon is the price on december 31 or the last trading day for the year, the year before the transaction date. this provides a price before the market expectations of the m&a activity are fully digested. monthly prices are then aggregated until the final price in the 4-year horizon is taken 4 years after the initial december 31 date. this is done for each transaction, and included into calendar-time portfolios which include monthly returns for all applicable transactions active in the portfolio during that month. similar portfolios are also created for the comparative benchmarks. for more statistics on the acquirers and targets, (appendix tables 2 and 3). 3.2. comparative benchmarks with the merger data collection steps defined, techniques to compare the data in meaningful ways become key. a straight comparison of the two 8-year periods may not provide a valid comparison between the profitability of the 4-year horizons since economic factors such as the overall stock market and the crude oil price could have varying impacts on the results for each company in the two 8-year periods. in order to adjust these results to provide more meaningful comparisons, four comparative benchmarks are selected: the crsp us market, the crsp global market, the crsp oil industry (of 49 industries), and the brent oil market price (dartmouth, 2017; eia, 2017). all four benchmarks exclude the risk free rate. the risk free rate is the us 1 month treasury-bill rate. crude oil prices are included because the profitability of oil companies is normally considered to be connected to the price level of crude oil prices (ford, 2011). crude oil sold in the us and much of latin america is priced using the wti quote (eia, 2017). crude oil sold in most of the rest of the world is linked to the brent oil market quote (iea, 2016). both quotes typically track barrows: are oil industry mergers becoming less profitable? international journal of energy economics and policy | vol 8 • issue 2 • 201834 within two dollars of each other, however, sometimes they diverge by more than five dollars depending on supply/demand issues which may affect one supply stream, but not the other (eia, 2017). the relationship between wti and brent changes in 2011 because of the increase in the production of shale oil in the us (heier and skoglund, 2014). this additional supply approaches the logistical constraints of moving the new oil supply to markets which could fully utilize the new supply (akacem and pence, 2015). the increased shale production tests the pipeline and storage limits at cushing, oklahoma, the main us trading point (heier and skoglund, 2014). because of this excess supply in the us, wti trades at a significant discount to brent beginning in 2011 with the discount exceeding $29 in september of 2011 (eia, 2017). this discount does not reflect the price differentials between brent and other crude oil grades that are historically linked to wti (buyuksahin et al., 2013). hence, for the purposes of this study, beginning in 2011, wti no longer represents the world crude oil market, but represents a us market which is experiencing logistical constraints. for this reason, brent is selected as the crude oil price marker for this study (eia, 2017). in the analysis using the total return formula, monthly price changes are measured and compared against the four comparative benchmarks for each 8-year period. with regard to the four comparative benchmarks, this volatility is important, but how the acquirers relate to this volatility is the key factor. are they more volatile or less volatile than the market? this is called beta and can be measured. with regard to the price of crude oil specifically, the price level in addition to this volatility is important and also has an impact on the profitability of individual oil companies (ford, 2011). based on the brent oil market price, there is a natural break between the two 8-year periods with january of 2006 serving as the dividing line (eia, 2017). the annual median for the 16-year time frame is $58 per barrel. the mean for each year before this is less than $58. for the entire 8-year period from 1998 to 2005 the mean is below $29, which is 50% below the median price for the 16-year time frame. for the 8-year period from 2006 to 2013, the mean for the 8-year period from 2006 to 2013 is $88 or 52% above the annual median for the 16-year time frame. the mean for each year from 2006 onwards is above the $58 median. please see figure 1 for the brent crude oil price graph using data from eia on the brent oil market prices during the 16-year time frame. for more statistics on brent crude oil month-end prices, (appendix table 4). 3.3. analytical cases the research question is: are oil industry mergers becoming less profitable? the objective of this study is to evaluate the profitability of oil mergers within the 16-year time frame. this time frame is further segmented into two 8-year periods for comparative purposes. the stock price total return of the acquirers is the dependent variable in this analysis. the independent variable is whether or not the company acquired a target transaction during one of the specified time-periods. the research approach is classified as causal and correlational. the intent is to establish a causal connection and quantify the relationship of the stock price total return performance of the acquirers to their merger activity. to further explore this topic and focus on quantifying the research question, three hypotheses are considered. 1. h1: the 1998-2005 period is superior to the 2006-2013 period in the three-factor tests. 2. h2: the acquirers perform worse than the oil industry. 3. h3: proportionally smaller oil industry merger transactions outperform the larger ones. the research approach matches the monthly portfolio to two other factors and is a version of the three-factor model of fama and french (fama and french, 1993). this method adheres with the strategy that long-run abnormal returns should be calculated as the long-run return of a sample less the long-run return of an appropriate benchmark (barber and lyon, 1997). the regression variables include the comparative benchmarks listed in the previous section. the us market or the global market or the oil industry data are included in the first formula case. rf rate represents the risk free rate. the brent oil market is included as well in the first formula case. the second formula case includes either the brent oil market or the acquirers group. return rf rate = α+ β((oil ind. or us mkt. or global mkt.)−rf rate)+β(brent mkt.− rf rate). return rf rate = α+β((oil mkt. or acquirers)−rf rate). this analytic approach utilizes seven cases which examine the stock price total return monthly percent changes for all acquirers which comprise the portfolios. the first three cases include comparisons of the two 8-year periods. there is one all acquirers case comparing against the oil industry and the brent oil market. there is one case for acquirers domiciled in the us against the us market and the brent oil market plus one case for non-us acquirers against the global market and the brent oil market. these three cases use the modified three-factor model as described above. there are four additional cases included in the study and these cases utilize a two-factor model, similar to the three-factor model, but with one less factor. these four cases include comparisons over the entire 16-year time frame. there is a case with all acquirers against the brent oil market and a case with the oil industry against the brent oil market. this allows for the performance for both the acquirers and the oil industry to be measured independently. it also allows the acquirers performance to be compared indirectly against the oil industry performance. there are two cases based on the relationship between the targets and acquirers size separated by the median measurement and measured against all acquirers. these last two cases explore the level of profitability based on the size delineation of the targets / acquirers of the transactions. for more information (table 1). to measure the performance of the m&a activity in the oil industry during the 16-year time frame, calendar time portfolios are constructed for each of the cases. a set of regression statistics is included which provide a thorough analysis of the cases. for the first three cases, a two-sample test is used to quantify the barrows: are oil industry mergers becoming less profitable? international journal of energy economics and policy | vol 8 • issue 2 • 2018 35 differences between the two time periods. a two-sample test is conducted to examine the differences between two different time periods and their relation to the independent variables (penn state, 2007). the two-sample test is constructed using a short long portfolio. the first three cases use the short long portfolio methodology to distinguish performance between the 1998 and 2005 period and the 2006-2013 period. the short long portfolio methodology combines two different time periods using a short strategy in one and a long strategy in the other where short equates to selling and long equates to buying. for purposes here, the short long portfolio is short for the 1998-2005 period and long for the 2006-2013 period. for the first three cases, the short long portfolios are regressed against the two benchmarks factors used in each case. for the last four cases, the comparative groups are regressed against the one benchmark factor used in each case. in the statistical analysis included, the first measurement posted is the y-intercept. for the analytical purposes here, the y-intercept equates to alpha. if alpha is positive then the portfolio is the superior performer in relation to the comparative benchmarks. in the first three cases, if alpha is positive then the short long portfolio is the superior performer. in this case, the 2006-2013 period would be the superior performer. 4. results the summary results of the cases analyzed are included in table 2. the detailed comparisons are discussed below the table. in the first three cases using the short long portfolio methodology, the alphas are all negative which equate to the 1998-2005 period as being the superior performer. case 4 compares the acquirers to the brent oil market. its alpha is positive. case 5 compares the oil industry to the brent oil market. its alpha is also, positive, but larger. hence, comparing the oil industry to the acquirers sees the oil industry as the better performer. cases 6 and 7 use the acquirers group as the benchmark. cases 6 and 7 results see the proportionally smaller targets/acquirers with a positive alpha perform better than the proportionally larger targets/acquirers with a negative alpha. the p-value measurements are all below 0.05, and thus indicate the rejection of the null hypothesis in a statistically significant manner. the results for cases 1 through 3 are statistically significant at the 0.01 level. hence, the performances of all of the 1998-2005 period groups in the first three cases are superior to the performances of all of the 2006-2013 period groups and the difference is statistically significant. figure 1: brent crude oil annual mean and median price table 1: comparison of cases analytical cases: all cases minus the risk free rate oil industry us market global market brent oil market all acquirers all acquirers x x us acquirers x x non-us acquirers x x all acquirers x oil industry x small targets/acquirers x large targets/acquirers x table 2: comparison of results regression statistics table alpha (y intercept) t-stat beta one beta two adjusted r2 *=10%, **=5%, ***=1% denote significance levels baseline short long portfolio using oil industry and brent (0.27)*** (9.64) (0.17)*** (0.05)** 0.37 us firms short long portfolio using us market and brent (0.29)*** (8.61) (0.02) (0.16)*** 0.24 non-us firms short long portfolio using global market and brent (0.40)*** (20.29) (0.13)*** (0.12)*** 0.42 baseline using brent (2-factor test) 0.16** 2.02 1.36*** na 0.80 oil industry using brent (2-factor test) 0.28*** 5.75 0.62*** na 0.68 small targets/acquirers using acquirers (2-factor test) 0.32*** 7.31 1.37*** na 0.97 large targets/acquirers using acquirers (2-factor test) (0.13)*** (7.16) 0.74*** na 0.98 barrows: are oil industry mergers becoming less profitable? international journal of energy economics and policy | vol 8 • issue 2 • 201836 in case 4, the acquirers group is superior to the brent oil market benchmark at a 0.05 level. in case 5, the oil industry is superior to the brent oil market benchmark at a 0.01 level. the oil industry alpha reading is higher than that for the acquirers. these two cases show at a high degree of significance that the acquirers group as a whole underperforms in comparison to the oil industry during the study time frame and the difference is statistically significant. the results for cases 6 and 7 are statistically significant at the 0.01 level and confirm that the small targets/acquirers transactions perform superior in comparison to the large targets/acquirers transactions during the study time frame and the difference is statistically significant. with regard to the adjusted r2 readings, the first three cases using the baseline short long portfolio in relation to the benchmarks are not as correlated as would normally be expected. the adjusted r2 readings are at 0.37, 0.24, and 0.42, respectively. these low readings indicate that there is not much correlation between the benchmarks or independent variables and the dependent variable which is the baseline short long portfolio in the first three cases. the last four cases include only one independent variable and display more correlation between the independent variable and the dependent variable. case 4 is a summary comparison of the acquirers group to only the brent oil market and its adjusted r2 reading is at 0.80. this confirms that the acquirers group is more correlated with the brent oil market than with the combination of the brent oil market in conjunction with the oil industry in case 1. the case 5 comparison of the oil industry to the brent oil market has its adjusted r2 reading at 0.68 and is in line with expectations to one of the key determinants of oil industry activity, that being the price of crude oil. the acquirers group’s correlation to the brent oil market is 18% higher than the oil industry’s correlation to the brent oil market. as expected, cases 6 and 7 demonstrate high correlation to the independent variable, at 0.97 and 0.98, respectively, since the independent variable in these two cases is the acquirers group itself. the dependent variable in each of the two cases is a 50% subset of acquirers group. with regard to the first of the hypotheses considered, h1: the 19982005 period is superior to the 2006-2013 period in the three-factor tests, the regressions confirm that the 1998-2005 period performs superior to the 2006-2013 period in a statistically significant manner in each of the first three comparative cases that include the time period comparisons. these results confirm the h1 null hypothesis. the 1998-2005 period is superior to the 2006-2013 period in the three-factor tests. with regard to the second of the hypotheses considered, h2: the acquirers perform worse than the oil industry, the acquirers’ performance is inferior to that of the oil industry and in statistically significant manner. these results confirm the h2 null hypothesis. the acquirers do perform worse than the oil industry. these results are in line with other studies which document losses for shareholders after oil industry mergers (marfo et al., 2013). on the third of the hypotheses considered, h3: proportionally smaller oil industry merger transactions outperform the larger ones. these are the size delineated cases for acquirers/targets, and the smaller relative sized transactions perform better than the larger ones, and do so in a statistically significant manner. these results confirm the h3 null hypothesis. this is in line with the results of a study which states: “profitability of their acquisitions decreases as the size of the target increases relative to that of the acquirer” (gorton et al., 2009). the research question is: are mergers in the oil industry becoming less profitable? based on the research methods in this study and the significance of the resultant differences in measurements, a confirmation of the hypothesis is warranted. in summary, yes, mergers in the oil industry are becoming less profitable. 5. conclusions when comparing the two study groups against each other, the 1998-2005 period performs superior as compared to the 20062013 period, in all three three-factor cases and in a statistically significant way. this confirms that during the time frame studied and the methodologies used, mergers in the oil industry are becoming less profitable. in a straight-up comparison between the acquirers and the oil industry during the study time frame, it would have been better not to partake in the m&a activity since the acquirers perform worse than the oil industry during the study time frame. however, when analyzing the results of the performance of the size delineated cases based on the targets/acquirers proportions, the smaller relative sized transactions perform better than the larger ones and in a significant manner. this is in line with other research which documents improved performance for proportionally smaller acquisitions (gorton et al., 2009). a final comment regarding mergers in general is that the merger game is not certain and results are not guaranteed (soni, 2014). mergers increase risk and have dubious outcomes (subeniotis, et al., 2011). “merger activity is often value destroying” (bouwman, et al., 2003). merger success is not always ensured and therefore increases organizational risk (subeniotis, et al., 2011). the key question is will company profitability increase to cover these risks (ferrer, 2012). if not part of an overall strategy, perhaps management should spend more time on contemplation prior to proceeding with consummation. references akacem, m., pence, n. (2015), the wti-brent spread: examining the factors behind it. business education innovation journal, 7(2), 155-160. andrade, g., stafford, e. (2004), investigating the economic role of mergers. journal of corporate finance, 10, 1-36. arora, s. (2015), investment decision making in the upstream oil industry: an analysis. the iup journal of business strategy, 12(1), 40-52. barber, b., lyon, j. (1997), detecting long-run abnormal stock returns: the empirical power and specification of test statistics. journal of barrows: are oil industry mergers becoming less profitable? international journal of energy economics and policy | vol 8 • issue 2 • 2018 37 financial economics, 43, 341-372. barrows, s.d. (2017), do oil industry merger waves reveal any trends? international journal of energy economics and policy, 7(5), 142-151. baumeister, c., kilian, l. (2016), forty years of oil price fluctuations: why the price of oil may still surprise us. journal of economic perspectives, 30(1), 139-160. bouwman, c., fuller, k., nain, a. (2003), stock market valuation and mergers, mit sloan management review, 45, 9-11. buyuksahin, b., lee, t., moser, j., robe, m. (2013), physical markets, paper markets, and the wti-brent spread. the energy journal, 34(3), 129-151. dartmouth. (2017), changes in crsp data. available from: available from: http://www.mba.tuck.dartmouth.edu/pages/faculty/ken.french/ data_library.html#researh. [last accessed on 2017 feb 02]. eia. (2017), energy information administration. washington, dc: u.s. department of energy, brent. available from: http://www.eia.gov/ dnav/pet/hist/leafhandler.ashx?n=pet&s=rbrte&f=d. [last accessed on 2017 jan 13]. fama, e., french, k. (1993), common risk factors in returns on stocks and bonds. journal of financial economics, 33, 3-56. ferrer, r.c. (2012), an empirical investigation of the effects of merger and acquisition on firms’ profitability. academy of accounting and financial studies journal, 16(3), 31-55. ford, g.s. (2011), an investigation into the relationship of retail gas prices on oil company profitability. applied economics, 43, 4033-4041. furfine, c., rosen, r. (2011), mergers increase default risk. journal of corporate finance, 174, 832-849. gorton, g., kahl, m., rosen, r. (2009), eat or be eaten: a theory of mergers and firm size. the journal of finance, 64(3), 1291-1344. heier, m., skoglund, s. (2014), crude oil price differentials. bergen: norwegian school of economics. hough, j., haines, r., giacomo, s. (2007), contextual factors affecting the integration of enterprise systems in post-merger oil and gas companies. enterprise information systems, 1(4), 421-441. iea. (2016), international energy agency. paris, france. available from: https://www.iea.org/oilmarketreport/omrpublic/. [last accessed on 2016 dec 28]. marfo, e.o., amoako, k.o., gyau, e.k. (2013), mergers and acquisitions: the performance of the acquiring firm empirical study of chevrontexaco. canadian social science, 9, 176-187. mortal, s., schill, m. (2015), the post-acquisition returns of stock deals: evidence of the pervasiveness of the asset growth effect. journal of financial and quantitative analysis, 50(3), 477-507. mustafa, h. (2016), scenario analysis for future oil demand and supply on the horizon of 2022. latvian journal of physics and technical sciences, 53(4), 56-65. penn state. (2007), available from: http://www.sites.stat.psu.edu/~ajw13/ stat200_notes/10_twogroups/08_twogroups_print.html. [last accessed on 2017 jan 13]. popescu, m. (2016), the volatility of oil prices on stock exchanges in the context of recent events. studies in business and economics, 11(1), 112-123. pratt, j.a. (2012), exxon and the control of oil. the journal of american history, 99, 145-154. sirower, m.l., sahni, s. (2006), avoiding the ‘synergy trap’: practical guidance on m&a deals for ceo and board. journal of applied corporate finance, 18(3), 83-95. soni, b.k. (2014), a study of pre-merger and post-merger/acquisition selected financial parameters for selected cement companies in india. sies journal of management, 10(20), 3-13. stunda, r.a., voltz, g.i. (2010), do oil companies routinely price gouge the public? academy of accounting and financial studies journal, 14(1), 1-6. subeniotis, d.n., tampakoudis, i.a., kroustalis, i.g., poulios, m. (2011), empirical examination of wealth effects of mergers and acquisitions: the u.s. economy in perspective. journal of financial management and analysis, 24(2), 30-38. thompson, m.e., o’brien, m.j. (2005), who has the advantage: strategic buyers or private equity funds? financier world wide. available from: http://www.financierworldwide.com. [last accessed on 2017 mar 03]. thomson reuters. (2017), thomson reuters eikon product. available from: http://www.thomsonreuters.com/en/products-services/ financial/trading-platforms/thomson-reuters-eikon.html. [last accessed on 2017 mar 13]. ural, m. (2016), the impact of the global financial crisis on crude oil price volatility. journal of management and economics research, 14(2), 64-76. vijh, a., yang, k. (2007), the acquisition performance of s&p 500 firms. available from: http://www.dx.doi.org/10.2139/ssrn.950307 [1] [last accessed on 2017 jan 03]. vild, j., zeisberger, c. (2014), strategic buyers vs. private equity buyers in an investment process, insead faculty and research working paper, available from: http://www.insead.edu/facultyresearch/ research/search_papers.cfm. [last accessed on 2017 mar 03]. appendix table 1: selection of records for the data set selection criteria records initial data set from thomson reuters eikon: masrch application for advanced search of mergers and acquisitions >1,000,000 1. select “completed” in the deal status field >750,000 2. select date effective between “01-jan-1998 and 01-jan-2014” >500,000 3. select “oil and gas” and “petrochemicals” in the target industry field >18,000 4. select “oil and gas” and “petrochemicals” in the acquirer industry field >11,000 5. select “public, subsidiary, joint venture” in the target public status field >6900 6. select “acquisition of assets, acquisition of partial interest, merger, acquisition of majority assets, acquisition of remaining interest, acquisition of certain assets” in transaction field >6700 7. select “over 50%” in the % acquired field >4400 8. select “over 300 m ($300 million)” in the deal size field 672 9. select non-blank entries in the acquirer ric field 459 10. eliminate records with missing acquirer size information 409 11. eliminate records which generate null or #n/a values when using the total return query 401 12. eliminate records with same acquirer ric within the same calendar year 364 barrows: are oil industry mergers becoming less profitable? international journal of energy economics and policy | vol 8 • issue 2 • 201838 table 2: acquirer companies acquirer companies (usd mm) 1998-2005 2006-2013 observations 141 223 maximum 214,732 302,270 minimum 54 54 range 214,678 302,216 mean 15,257 19,673 median 4167 4608 sd 34,824 42,083 sd: standard deviation table 3: target companies target companies (usd mm) 1998-2005 2006-2013 observations 141 223 maximum 95,444 40,659 minimum 300 303 range 95,144 40,356 mean 4,645 2,360 median 895 818 standard deviation 13,281 4,968 sd: standard deviation table 4: comparative benchmarks: brent crude oil month-end prices brent (month-end) 1998-2005 2006-2013 observations 96 96 maximum 66.80 138.40 minimum 9.91 35.82 range 56.89 102.58 mean 28.94 88.76 median 26.89 89.29 standard deviation 12.90 23.70 sd: standard deviation tx_1~at/tx_2~at international journal of energy economics and policy | vol 7 • issue 5 • 2017166 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(5), 166-170. energy use, trade openness, and exchange rate impact on foreign direct investment in indonesia horas djulius* faculty of economics and business, universitas pasundan, indonesia. *email: horasdjulius@unpas.ac.id abstract we conducted an inquiry on the short run and long run impact of energy use, trade openness, and exchange rate on foreign direct investment (fdi) in indonesia from 1981 to 2015. energy use is one of the key variables because host countries cannot easily anticipate shortterm energy shortage, whereas foreign investors interpret such shortage as an indicator of progress and readiness of the manufacturing sector. we use the error correction model to explain the interrelationship between predictors and their effect on fdi. results show that short run trade openness significantly affects fdi. by contrast, long-term energy use and trade openness variables have a positive and significant influence, whereas exchange rate has a negative linkage. keywords: foreign direct investment, energy used, trade openness, exchange rate, error correction model jel classifications: f21, f31, q43 1. introduction foreign direct investment (fdi) is an important variable in improving the economic development of developing countries. indonesia is a developing country in southeast asia that requires fdi to support its development. fdi inflows in indonesia started to increase dramatically in 2004. fdi inflows in 2005 were higher than the previous peak in 1996, which further increased by another 170 percent from 2005 to 2014. according to the investment coordinating board of the republic of indonesia (sjöholm, 2016), this strong growth continued in 2015, wherein fdi increased by almost 20 percent from 2014 to 2015. energy is one of the important factors that encourage fdi. compared with other countries, indonesia is a wasteful country in terms of energy consumption (measured by energy intensity). however, indonesia continues to have low energy consumption per capita. indonesia is expected to reach energy deficit in 2019 if the country’s energy management will not improve. countries aim to avoid energy deficit because it entails heavy dependence on other parties or countries. a number of studies examined the causal relationship between energy or electricity consumption on some independent variables, such as economic growth, prices, employment, and fdi. previous studies analyzed energy consumption (elliott et al., 2013; sbia et al., 2014; zaman et al., 2012). empirical studies found the a negative impact of fdi on energy consumption; these studies concluded that fdi was not explained by excessive energy practices (lee, 2013; sbia et al., 2014). however, most econometric models find a positive correlation between fdi and energy consumption as shown in high energy use (omri and kahouli, 2014; zaman et al., 2012). several empirical results showed a significant relationship between energy use and fdi (tang, 2009; sadorsky, 2009; chandran et al., 2010). long-term influence of energy consumption on fdi is observed, but no relationship was found in the short term (bekhet and othman, 2011). other possible factors that affect fdi are trade openness and exchange rate. according to the global competitiveness report, indonesia’s domestic market index ranked third from 2013 to 2014, with a value of 6.2 of the total value of 7, whereas the indonesian foreign market index ranked fourth with a value of 6.4. the report states that the indonesian market has a considerable potential for domestic and foreign investments. economic openness greatly affects the behavior of investors. a country with an open economy will attain high djulius: energy use, trade openness, and exchange rate impact on foreign direct investment in indonesia international journal of energy economics and policy | vol 7 • issue 5 • 2017 167 fdi coming in because investors have high expectations of business turnover in the host country (liargovas and skandalis, 2012). economic openness can enable countries with abundant resources to export goods and allow countries with scarce factor of production to import goods. the advantages of economic openness through trade include wide market access, high levels of efficiency and economic competitiveness, and improved employment opportunities. several studies found a positive relationship between trade openness and fdi flow (biglaiser et al., 2006; chakrabarti, 2001). the reference rate of jakarta interbank spot dollar rate released by bank indonesia shows that the rupiah exchange rate in 2016 was approximately rp. 13,000 per us dollar. research in morocco and nigeria found that exchange rates had a significant negative effect on fdi (bouoiyour, 2007; udoh and egwaikhide, 2008). other studies in nigeria showed that exchange rate does not affect the entry of fdi (ahmed and mayowa, 2012). exchange rates can affect investments in various ways depending on the investor’s intention. when the focus of the investor was the local market, the appreciation of the local exchange rate increases the fdi due to the increased purchasing power of local consumers. when the goal of the investor is export, the appreciation of the local currency reduces fdi inflows through low competitiveness given the increase of labor costs (bénassy-quéré et al., 2001). a negative and significant relationship of exchange rate volatility to fdi was found among eu member states in central and eastern europe (arratibel et al., 2009). the intention of foreign investors to invest in the host country can be observed from the perspective of international trade and the ability of the industrial sector to support fdi, which can be proxied through the energy use of a country. the effect of energy use as an economic variable on fdi is rarely studied, particularly for short-term and long-term periods. the main determinants of fdi in a host country are trade openness, market size, labor force, infrastructure, and investment rate of return. the experiences of south asian countries illustrate the importance of trade openness to attract fdi (sahoo, 2006). a positive and significant relationship exists between trade openness and fdi. trade openness increases the export-oriented inflows of fdi, whereas trade restrictions increases fdi tariffs. the openness of economic trade increased positively with the size of capital inflows of export-oriented exports. in addition to trade liberalization, fdi relies on political stability, exchange rate stability, and market size of the economy. thus, developing countries must stabilize their exchange rate and political situation along with trade openness to attract more fdi (liargovas and skandalis, 2012). fdi decisions depend on the various characteristics of host countries, such as exchange rates, market size, trade openness, political stability (risk), labor costs, investment costs, trade costs, human capital, trade deficits, foreign debt, domestic investment, human capital, inflation, taxes, budget deficits, government consumption, and energy used (blonigen, 2005). other factors that attract fdi were also found, such as institutional quality, physical infrastructure, import tariffs, macroeconomic stability, and political stability (trevino et al., 2002). therefore, this study highlights the factors that affect fdi in indonesia using the macroeconomic variables of energy used, trade openness, and exchange rate in the short and long term. 2. research method 2.1. data energy use indicates the use of primary energy, which is equal to original production, plus imports and stock changes and minus exports (kg of oil equivalent per capita). the growth of energy use in developing countries is closely connected to modern sectors of growth (i.e., manufacturing, transportation, and urban regions). trade openness is the sum of exports and imports of goods and services (% of gross domestic product [gdp]). trade openness is calculated as part of gdp. exchange rate was determined by national authorities, in this case, bank indonesia. exchange rate is calculated as an annual average based on monthly averages (rp/usd). fdi is equity flow in the reporting economy, which summarizes equity capital, reinvestment of earnings, and other capital (us dollar). we obtained the data from world bank, bank indonesia, and statistics indonesia from 1981 to 2015. 2.2. model we construct an error correction model that associates energy use, trade openness, and exchange rate to foreign investments in the shortand long-term. long-term model 0 1 2 3. . .fdi ener open er    = + + + + (1) we transform the equations into error correction models to measure short-term and long-term effects. short-term model . . . . ( 1)0 1 2 3 4 . ( 1) . ( 1) . ( 1)5 6 7 dfdi dener dopen der ener open er ect         = + + + − + − + − + − (2) where; dfdi = changes in foreign direct investment dener = changes in energy use dopen = changes in trade openness der = changes in exchange rate ener(−1) = energy use, last period open(−1) = trade openness, last period er(−1) = exchange rate, last period ect(−1) = error correction term error correction term is the residual value of the static equation or the long-term model in equation (1). 0 1 2 3. . .fdi ener open er     ∧ = − − − − (3) 3. results and discussion the descriptive statistical analysis provides an overview of the data to represent the variables used in the research model. this descriptive statistical analysis shows the behavior of each independent variable in influencing the movement of dependent variables. first, we separately test the stationarity of each djulius: energy use, trade openness, and exchange rate impact on foreign direct investment in indonesia international journal of energy economics and policy | vol 7 • issue 5 • 2017168 independent variable. a cointegration test of all predictors of fdi is then conducted. we then estimate the static equation model followed by estimating shortand long-term equations. table 1 describes the stationary test results for detecting spurious regression for two or more variables that appear statistically significant. based on the unit root test, all independent and dependent variables are stationary on the first difference and not stationary at the level. in the cointegration test, residual is stationary at the level to avoid spurious regression. table 2 presents the results. the results show that error correction term is stationary. thus, the correction term error can be applied in the short-term mode. a long-term relationship exists between research variables. table 3 illustrates the relationship between energy use, trade openness, and exchange rate on the static equation. all variables have a significant influence on the 95% level. the short-term equation estimation in the short-term model is shown in table 4. table 4 shows significant ect, which means that the ecm model is valid and can be used to analyze observed variables. the regression coefficients for the relationship between energy use, trade openness, and exchange rate variables are obtained through calculations, as described in the appendix. the equations for the long-term relationship are as follows. fdi=−4.72e09+1.01 ener+2.376e10 open−69535 (4) the equation shows that energy use and trade openness have a positive and significant relationship in influencing fdi in the long run, whereas the exchange rate variable has a negative and significant relationship to fdi. this finding indicates that the real strengthening of funding sources of energy development, trade openness, and exchange rate affects the performance of fdi in indonesia. short-term energy use has a positive but insignificant relationship to fdi, whereas long-term energy use has a positive and significant linkage. in developing countries, the development of the manufacturing sector, transport sector, and other modern sectors in urban areas can be represented by energy use. thus, foreign investors consider energy use as a proxy for sector advancement that has interaction with their potential investment business. foreign investors believe that the host country does not lack the energy needed in the manufacturing sector. their factory plant does not lack energy when the business operates. the business is also supported by other businesses, which serve as a supplier or market. explanations lead to a positive influence between energy use and foreign direct investors (omri and kahouli, 2014; zaman et al., 2012). this finding may not be considered by foreign investors in the short run, but foreign investors learn from what they understand about energy use role in the long run. thus, long-term decision toward investment is driven by the energy use of host country. moreover, lack of energy supply may be a big problem for foreign investors if the host country is a developing country where energy supply is not as much as in developed countries. this problem stems from the fact that their products become less competitive due to high production costs. trade openness in both the short and long term has a positive and significant relationship to fdi. the results indicate the increase of open international trade of the host country and the inflow of fdi. indonesia has long adhered to an open economy. trade openness provides benefits for the countries involved because of the loss of barriers, both tariff and non-tariff, and the smooth progress of inter-country mobility (agiomirgianakis et al., 2003; anyanwu, 2011; asiedu, 2002; demirhan and masca, 2008). for foreign investors, trade openness is related to the business. first, trade openness means they can easily import the needed supplies. second, trade openness means that foreign investors can export their products in the host country. third, trade openness means the ease of export and import of their business partners, suppliers, and buyers. short-term exchange rate has a negative but not significant relationship to fdi, whereas the long-term exchange rate has a significant influence. this finding shows that a depreciating exchange rate is one of the considerations of foreign investors to invest their capital. for developing countries whose currencies are lower than foreign currencies, an increase in exchange rates means that foreign investors can buy goods in host country cheaply. this finding benefits foreign investors if their goal is to re-export. a strong domestic currency (host country) attracts investors if their goal is the host country’s domestic market (ahmed and mayowa, 2012; bouoiyour, 2007; udoh and egwaikhide, 2008). re-export and domestic market motives were observed among foreign investors in indonesia. the present study supports the second table 1: unit root test variable level first difference second difference adf statistics significant level adf statistics significant level adf statistics significant level fdi −0.371496 x −5.408025 *** −4.867565 *** ener −0.178559 x −6.488443 *** −6.311502 *** open −1.096626 x −5.135984 *** −8.983179 *** der −0.506825 x −6.772241 *** −8.404403 *** source: research data processing, xnon significant; ***significant at 99% level djulius: energy use, trade openness, and exchange rate impact on foreign direct investment in indonesia international journal of energy economics and policy | vol 7 • issue 5 • 2017 169 hypothesis because indonesia is a large market whose purchasing power is increasing. 4. conclusion trade openness has a significant effect on fdi in the short term. foreign investors define trade openness as the ease of their product’s export and import and other supporting businesses. all predictors have long-term significant influences. exchange rate has a negative effect, which means that the appreciation of the host country currency increases foreign investor interest. this finding means that the motive of foreign direct investors is to make the domestic market its main target in the long run. the open exchange rate policy is preferred by foreign investors because it reflects the relative comparison between the host country economy and world economy. trade openness has a positive influence, which means that an open host country economy has a high inflow of fdi. foreign investors demand policy for economic openness given that it guarantees the supply and marketing of their products and their business partners. energy use has a positive influence and is an important indicator for foreign investors that the host country is ready to accept external investment. high energy use refers to the availability of energy needed by fdi and can also describe the readiness and modernity of other fdi’s supporting sectors. long-term energy supply planning is one of the keys to the success of host countries in managing an economy that looks forward to external sources of growth. 5. acknowledgment the author is grateful to the anonymous referees of the journal for their useful suggestions to improve the quality of the article. the usual disclaimer applies. references agiomirgianakis, g.m., asteriou, d., papathoma, k. (2003), the determinants of foreign direct investment: a panel data study for the oecd countries, (report no. 03/06). london, uk: department of economics, city university london. ahmed, e., mayowa, g. (2012), the determinants and impacts of foreign direct investment in nigeria. international journal of business and management, 7(24), 67-77. anyanwu, j. (2011), determinants of foreign direct investment inflows to africa, 1980-2007, african development bank group working paper, september. p131. arratibel, o., furceri, d., martin, r., zdzienicka, a. (2009), effect of exchange rate volatility on macroeconomic performance in nigeria. interdisciplinary journal of contemporary research in business, 9(34), 149-155. asiedu, e. (2002), on the determinants of foreign direct investment to developing countries: is africa different? world development, 30(1), 107-119. bénassy-quéré, a., fontagné, l., èche-révil, a.l. (2001), exchange rate strategies in the competition for attracting foreign direct investment. journal of the japanese and international economies, 15(2), 178-198. biglaiser, g., de rouen, k.jr. (2006), economic reforms and inflows of foreign direct investment in latin america. latin american research review, 41(1), 51-75. blonigen, b.a. (2005), a review of the empirical literature on fdi determinants. atlantic economic journal, 33(4), 383-403. bouoiyour, j. (2007), the determining factors of foreign direct investment in morocco. saving and development, 1, 91-105. chakrabarti, a. (2001), the determinants of foreign direct investment: sensitivity analyses of cross-country regressions. kyklos, 54(1), 89-114. chandran, v.g.r., sharma, s., madhavan, k. (2010), electricity consumption-growth nexus: the case of malaysia. energy policy, 38(1), 606-612. demirhan, e., masca, m. (2008), determinants of foreign direct investment flows to developing countries: a cross-sectional analysis. prague economic papers, 17(4), 356-369. elliott, r.j.r., sun, p., chen, s. (2013), energy intensity and foreign direct investment: a chinese city-level study. energy economics, 40(2013), 484-494. bekhet, h.a., othman, n.s. (2011), causality analysis among electricity consumption, consumer expenditure, gross domestic product (gdp) and foreign direct investment (fdi): case study of malaysia. journal of economics and international finance, 3(4), 228-235. lee, j.w. (2013), the contribution of foreign direct investment to clean energy use, carbon emissions and economic growth. energy policy, 55, 483-489. liargovas, p.g., skandalis, k.s. (2012), foreign direct investment and trade openness: the case of developing economies. social indicators research, 106(2), 323-331. omri, a., kahouli, b. (2014), causal relationships between energy consumption, foreign direct investment and economic growth: fresh evidence from dynamic simultaneous-equations models. energy policy, 67, 913-922. table 2: cointegration test variable adf statistics mac kinnon statistic p 1% 5% 10% ect −5.860797 −3.653730 −2.957110 −2.617434 0.0000 source: research data processing table 3: static equation estimation variable regression coefficient p value intercept −1.51e+10 0.0000 ener 0.091129 0.0442 open 5.73e+10 0.0002 er −1062276. 0.0234 r2=0.75 f stat=30.63, p=0.00 source: research data processing table 4: short-term equation estimation variable regression coefficient p value c −1.18e+09 0.4633 d (ener) 0.028020 0.7430 d (open) 5.85e+10 0.0003 d (er) −537204.1 0.1411 ener(−1) 0.002367 0.9352 open(−1) 5.94e+09 0.5074 er(−1) −17384.38 0.9520 ect(−1) 0.252919 0.0363 r2=0.57 f stat=4.84, p=0.00 source: research data processing djulius: energy use, trade openness, and exchange rate impact on foreign direct investment in indonesia international journal of energy economics and policy | vol 7 • issue 5 • 2017170 sadorsky, p. (2009), renewable energy consumption and income in emerging economies. energy policy, 37(10), 4021-4028. sahoo, p. (2006), foreign direct investment in south asia: policy, trends, impact and determinants. south asia, 56, 1-76. sbia, r., shahbaz, m., hamdi, h. (2014), a contribution of foreign direct investment, clean energy, trade openness, carbon emissions and economic growth to energy demand in uae. economic modelling, 36, 191-197. sjöholm, f. (2016), foreign direct investment and value added in indonesia, ifn working paper. tang, c.f. (2009), electricity consumption, income, foreign direct investment, and population in malaysia: new evidence from multivariate framework analysis. journal of economic studies, 36(4), 371-382. trevino, l.j., daniels, j.d., arbelaez, h., upadhyaya, k.p. (2002), market reform and foreign direct investment in latin america: evidence from an error correction model. the international trade journal, 16(4), 367-392. udoh, e., egwaikhide, f.o. (2008), exchange rate volatility , inflation uncertainty and foreign direct investment in nigeria. botswana journal of economics, 5, 14-31. zaman, k., khan, m.m., ahmad, m., rustam, r. (2012), determinants of electricity consumption function in pakistan: old wine in a new bottle. energy policy, 50, 623-634. appendix after we obtained the error correction term, the next step is to estimate the ecm for the short term by the ordinary least square method. subsequently the short-run regression coefficient is attained (equation 2), long-term regression coefficient (equation 4) is acquired through: α0 = δ0/δ9 α1 = (δ5+δ9)/δ9 α2 = (δ6+δ9) /δ9 α3 = (δ7+δ9) /δ9 α4 = (δ8+δ9)/δ9 . international journal of energy economics and policy | vol 7 • issue 5 • 2017 159 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(5), 159-165. the problem of harmonizing the environmental priorities of electricity generating companies and regional socio-economic systems: dea-based approach valeriy victorovich iosifov1, nairuhi akopovna almastyan2, alessandro figus3, yuri alexandrovich chepurko4*, nguyễn hoàng hiển5, marina alexandrovna krotova6 1department of land transportation and mechanics, kuban state technological university, krasnodar, russia, 2analytical center of kuban state university, krasnodar, russia, 3department of international relations, università degli studi link campus university, italy, 4department of economics, kuban state university, krasnodar, russia, 5faculty of state management on economic affairs, national academy of public administration, vietnam, 6faculty of economics, kuban state university, russia. *e-mail: chepurko@yandex.ru abstract this paper suggests a two-step method of non-parametric optimization, in which the problem of increasing efficiency of energy companies on a set of ecologic and economic parameters is viewed as a sub-problem of increasing the overall ecologic and economic efficiency of the regional economic system. this task is based on the input-oriented ecological data envelopment analysis model with variant returns to scale. the method was tested by coordinating the ecologic priorities of one of the biggest russian electric and heat generators “ogk-2” and the krasnoyarsk region. keywords: ecologic and economic efficiency, energy companies, interest coordination, iso 14001:2015 standard, non-parametric optimization, data envelopment analysis jel classifications: o33, q42, q47, q48 1. introduction the electric power industry is traditionally considered to have a significant negative impact on the environment. during the production of electricity and heat, large volumes of primary energy are processed, which leads to negative environmental effects such as emissions of various pollutants and greenhouse gases into the air, abstraction of natural waters, discharges of pollutants into water bodies, and solid waste generation. the new version of the iso 14001:2015 standard increases requirements towards the regional context of business activity for companies, which now need to look at the most important regional ecologic problems while developing their ecologic policies. considering the fact that in russia the penetration rate of iso 14001 is the highest among energy companies, the scientific problem of developing methods for coordinating the ecological priorities of energy companies and regional socio-economic systems on their territory are becoming more relevant. the problem of reducing negative impact of the economy on the environment and the withdrawal of regional economic systems (res) on the trajectory of sustainable development is not trivial: not only from the investment and technological point of view, but also methodologically. in this framework is highly adopted environmental data envelopment analysis (edea) method. in general the interests of the regions and electric generating companies, represented as a set of optimal solutions of edea models, may not overlap. therefore, in this paper, a two-step edea method is developed, for the purpose of coordination of the environmental priorities of power generating companies and regional socio-economic systems. it includes the consistent solution of two tasks of nonparametric optimization and the use of target parameters for reducing the primary negative effects of res for choosing the highest-priority areas of the environmental policies of power generating companies. iosifov, et al.: the problem of harmonizing the environmental priorities of electricity generating companies and regional socio-economic systems: dea-based approach international journal of energy economics and policy | vol 7 • issue 5 • 2017160 2. literature review nowadays one of the most popular instruments of environmental management on the enterprises of various industries, including the electric power industry, are the international standards of the iso 14000 family (comoglio and botta, 2012; zobel, 2013; testa et al., 2014). in russia, the interest from the business environment in certification according to iso 14001 “environmental management systems requirements with guidance for use” is still very weak, but the level of prevalence of the standard among russian energy companies is much higher than in other industries, which can be explained by their export orientation. the share of russian energy companies in the total number of iso 14001 certificates in 2015 was 14%, while the similar share of energy companies in the world as a whole at the same time was only 3% (ratner and iosifov, 2017). in 2015, a new version of the iso 14001 standard, corresponding to the innovative iso format for the development of standards for management systems was published. comparing to the old version it is implying a significant expansion of the requirements for the formulation of the company’s environmental policy. the approval of the russian national standard in accordance with the new version of iso 14001:2015 has happened in 2016, which means that the transition to it should be carried out by enterprises within the next 3 years. one of the important differences between the version of the 2016 standard and the old one of 2007 is the introduction of the concepts of “stakeholders” and the “context” of the organization, so the enterprise in the new version of the standard is considered not as an isolated object, but as an agent of a certain socio-ecological and economic system (ratner and iosifov, 2017). when forming an environmental management system, a company must take the regional context of its activities and the interests of other agents of the socio-economic system into account. hence, the issues of coordinating the environmental priorities of power generating companies with the optimal (from the ecological and economic point of view) trajectory of development of the res are becoming especially topical. when developing projects for the economic development of territories, decision makers need to take the multidimensional nature of social, environmental and economic effects into account, the connections between which are not always clear and obvious (nizhegorodtsev and ratner, 2016; ratner and ratner, 2016), which leads to the emergence of multi-criterion nonparametric optimization problems. in ratner and ratner, (2017) it was shown that such problems can be successfully solved by constructing models of edea. at present, edea is a developed methodology for assessing the comparative complex ecological and economical effectiveness of a set of homogeneous objects using various models of mathematical programming, both linear and nonlinear (cook and seiford, 2009; korhonen and luptacik, 2004; bian and yang, 2010). edea allows to identify objects whose activities can be recognized as effective, and find the best way to approach the efficiency boundary for inefficient objects. in the process of development of environmental policies in case of a large energy company, some multi-criteria nonparametric optimization problems also arise and then can be solved by various edea-models (ratner and ratner, 2017). for the first time, this problem was solved in (ratner and almastyan, 2016), however, in this paper the models with constant returns to scale were considered, whereas in the problems of estimating negative environmental effects it is better to use dea-models with variable returns to scale in order to take the process of negative impact accumulation into account. so, in this paper we use an edea-model with variable returns to scale for evaluation of the scores of complex ecological and economical effectiveness of the regions of russia and identification of targets for reduction of negative ecological effects. 3. data analysis and estimation techniques 3.1. dea-based problem for evaluation of the targets for environmental protection in regional socialeconomic systems let’s consider the task of evaluating the complex ecologic and economic efficiency of res through a number of indicators, representing resources needed for economic activities (such as energy, raw materials, labor, capital, etc.), the positive value of production activities and their negative ecological effects. using a basic input-oriented edea model (färe and grosskopf, 2004) we can consider resources as inputs, positive economic effects as desirable outputs and negative ecological effects as undesirable outputs in the model. it is worthy to remind that the main difference between edea and traditional dea models lies in the presence of unwanted outputs. the desirable outputs of economic activities on the regional level can be measured with a variety of widely-used indicators, such as the gross regional product (grp), regional gross value added, population’s levels of income in the region, etc. furthermore, each res (considered in the model as decision making unit [dmu]) also produces some negative ecologic effects as an unavoidable result of economic activity (atmosphere pollution, solid waste, waste water, etc.). for each res, we look for a way to reduce the inputs (use of resources) and undesirable outputs (negative ecologic effects) without reducing desirable outputs (economic results). dmus that produce maximal results with minimal negative ecologic effects and resource consumption can be considered effective. the mathematical formalization of the problem is as follows. let there be k homogenous dmus, each of which is defined with n inputs and m outputs. outputs 1, 2,… p are desirable (useful economic and social results) and outputs p+1, p+2,…, m are undesirable (negative ecological effects). in the coefficient form, the problem of evaluating the efficiency of the 0th dmu can be written down as: m m m0 u,v m=1 max u y∑ (1) s.t. iosifov, et al.: the problem of harmonizing the environmental priorities of electricity generating companies and regional socio-economic systems: dea-based approach international journal of energy economics and policy | vol 7 • issue 5 • 2017 161 m n m mk m=1 n=1 n n no n=1 u y vn xnk ≤0 k 1, 2,k, v x 1 − = ∑ ∑ ∑ um, vn≥0 m = 1,2, …m n = 1,2,…n where t 10 nox (x , x ) 0= ≥ is a vector of inputs of size n, y = (yl0,…ym0)≥0 is a vector of outputs of size m, к is the number of dmus, • unknown non-negative weights that need to be determined by solving the task. for each dmu, we solve a rational linear programming task to maximize the following ratio of weighted sums: p n r ro s s0r=1 s=p+1 m i i0i=1 y y h= v x µ µ−∑ ∑ ∑ , (2) s.t. p n r rj s sjr=1 s=p+1 m i iji=1 y y 1 v x µ µ ≤ ∑ ∑ ∑ the ratio (2) is the complex efficiency measure for ecologic and economic efficiency of a dmu. dmus that have this coefficient (efficiency score) equal to 1 are considered effective, and the others are not. a well-known study (korhonen and luptacik, 2004) proves that the undesirable outputs can simply be viewed as inputs, in this case, the efficiency measure (2) becomes: k r ro* r=1 m p i io s soi=1 s=k+1 y h = v x y µ µ+ ∑ ∑ ∑ (3) in some practical applications for ecology problems, undesirable outputs can be used as the only inputs for a model. this simplified version of the problem identifies the ress, that produce the maximal social and economic results with the minimal negative ecological effects, as efficient. inefficient dmus (res that have efficiency scores below 1) can have their inputs proportionally reduced to move closer to the efficiency frontier (cook and seiford, 2009) and this result has a lot of very important regional environmental policy application. thus, in the paper (ratner and ratner, 2017) a new methodological approach for assessment of regional environmental efficiency with the use of ccr models was developed. it was shown that solving an edea model can give a reasonable target for each inefficient region to improve its ecological indicators in order to achieve complex economic and ecological efficiency. these results can be achieved through the use of bcc model, that differs from the ccr only by adopting a variable scale effect. the bcc model allows to determine of the increasing or decreasing economies of scale for each dmu, and, thus, to divide their total efficiency into technical efficiency and efficiency, depending on the economies of scale, as shown in (schefczyk, 1996) for agricultural enterprises. in the case of a constant scale effect, the output parameter varies in proportion to the input factor. changing the input factor with a variable scale effect can lead to a disproportionate change in the output parameter. this assumption fully corresponds to the economic theory of diminishing marginal utility and has a significant effect on the values of the efficiency scores. from ecological point of view, it reflects the effect of accumulation of negative environmental impacts in a more adequate way. so, let’s consider as inputs of the edea model of assessing the environmental and economic efficiency of the regions, the following indicators characterizing the impact of res on the environment: • x1 the annual volume of emissions of pollutants into the atmosphere from stationary sources, kt (reflects predominantly the impact of the economy); • x2 the annual volume of emissions of pollutants into the atmosphere from mobile sources, kt (reflects the impact of the economy and the population); • x3 the annual volume of discharges of polluted sewage into surface water bodies, million cubic meters (reflects the impact of the economy and the population); • x4 the annual volume of waste generation, million tons (reflects the impact of the economy and the population); • x5 the annual volume of abstraction of fresh water, million cubic meters (reflects the impact both the economy and the population). as outputs of the model, representing the socio-economic outcome of the res activity, the following indicators were selected: • y1 -grp, million rubles; • y2 population, thousands people. the results of the calculation of efficiency scores for 79 regions of russia completed in the maxdea using the bcc-input-oriented model on the data taken from the statistical collections “regions of russia. socio-economic indicators, 2010-2014,” are presented in section 2. the target parameters that need to be achieved for inefficient regions in order to become more efficient are also presented in section 2. when solving the problem of reconciling the interests of res and electricity generating companies, these indicators of the potential for reducing negative environmental effects calculated are the main result, since they determine the priority directions of the environmental activity of the electric power industry enterprises. 3.2. dea problem for evaluation the scores of complex economic and ecological effectiveness for electric generating companies here we formulate the second edea problem for dmus, that now represent electricity generation companies of russia. iosifov, et al.: the problem of harmonizing the environmental priorities of electricity generating companies and regional socio-economic systems: dea-based approach international journal of energy economics and policy | vol 7 • issue 5 • 2017162 let the following parameters indicate the inputs of the edea model: • x1the annual volume of emissions to the atmosphere (thousand tons); • x2 the annual volume of solid waste generation (thousand tons); • x3 the volume of fresh water consumption for the company’s production and domestic needs (million cubic meters). as one can see these parameters partly match the inputs of edea model for regional socio-economy systems, in other words, they deal with the same negative ecological effects. since these two models are input-oriented, their solution will give us the understanding of how the inputs of inefficient dmus (negative ecological effects) need to be reduced. when the generating company is located in an inefficient region, the reduction of its inputs (negative ecological impact) will simultaneously reduce the inputs of the regional socio-economic system. thus, this results in harmonization of environmental management goals of the company and the region. as one can notice, the introduction of the fourth indicator the annual volume of discharges of insufficiently treated sewage would completely solve the problem of reconciling the interests of electricity generating companies and regions, but it is not technically possible in view of the lack of statistical data on this indicator in the reports of energy companies. as the outputs of the model, we consider the annual production of electric energy (million kwh) and thermal energy (thousand gcal). the presence of two outputs responsible for power generation and thermal generation allows us to take the positive impact of cogeneration technologies on the overall environmental and economic efficiency of the company into account. we will solve the ccr problem with a constant scale effect for the primary players in the wholesale electricity market: five biggest wholesale electricity market generating companies and several territorial generating companies (a total of 24 companies). it will allow us to find efficient companies that produce the biggest amount of energy (both electric and heat) with the lowest impact on environment. for inefficient companies, which have efficiency scores below 1, we can also calculate the target parameters of each input and use it for goal-setting in environmental policies. it is worth noting that each of the companies under consideration is a large holding, the production divisions of which are located in different regions. but the solution of the task of efficiency evaluation at a more detailed level (the level of individual power plants), from our point of view, seems inappropriate, since a decision-making process takes place on the integrated level. it is the integrated structures that develop ecology policy, innovation policy, the design of environmental management systems, take company through the process of iso 14001 certification and elaborate the projects for reduction of negative impact on the environment. at the same time, if the company is considered inefficient, a third edea problem can be solved for the evaluation of comparative ecological and economic effectiveness of each utility in the holding. then each inefficient utility can determine the goals of environmental policy taking into account target parameters, obtained by solving the edea problem. in practice, a simultaneous achievement of reduction of all negative environmental effects is usually difficult due to the lack of financial resources for complete modernization of the production process, sometimes it is simply impossible at the current level of technology development. in this case, the choice of particular measures to reduce the negative environmental impact can be made by determining the fastest path to the efficiency frontier. let us denote ifnjh as the conditional score of the efficiency of the jth production object, which is calculated under the assumption that the nth input of the model takes its target value tarnj njx = x , and all other inputs of the model stay the same as their real values. in this case, since the approximation to the efficiency boundary occurs in one direction, obviously, the condition ifj njh h≤ is satisfied, i.e., the score of efficiency increases. obviously, the number of conditional scores is equal to the number of inputs of the model. knowing all conditional scores can help us to choose the way to move to efficiency frontier. depending on the choice of the production object in edea problem, the conditional scores of effectiveness can be calculated for individual utilities, for electric generating holdings and, finally, for regional social-economic systems. this approach allows one to determine the preferred way for achieving efficiency for individual utilities, electric generating holdings and regional social-economic systems, which, in general, can mismatch. the environmental priorities of individual company, selected on the criterion of reducing various types of production and nonproduction costs (including the costs of environmental payment and emissions) generally do not coincide with the priorities for the sustainable development of regional economies. the incentive for the individual companies for implementation of environmental protection measures which help regions to become effective can be the possibility of successful certification under the new requirements of iso 14001: 2015, which focuses on the regional component of the activities of enterprises. 4. results of computations the results of calculations of effectiveness scores for ress, presented in table 1, show that only 18 regions out of 78 can be considered effective: the kaluga region, the moscow region, the republic of kalmykia, the krasnodar territory, the republic of dagestan, the republic of ingushetia, the kabardinobalkarian republic, the republic of chechnya, the republic of bashkortostan, the republic of mordovia, the republic of chuvashia, the saratov region, the tyumen region, the republic of altai, the republic of tyva, the altai territory, the jewish autonomous region and the chukotsky autonomous district. for all other regions the reduction of negative ecological impacts (considered as inputs of the edea model) is needed. the results of calculation of efficiency scores and targets for reducing negative environmental effects for inefficient electricity generating companies, are presented in table 2. they were iosifov, et al.: the problem of harmonizing the environmental priorities of electricity generating companies and regional socio-economic systems: dea-based approach international journal of energy economics and policy | vol 7 • issue 5 • 2017 163 calculated by maxdea software for the last year in the observation period. the worst indicators of environmental and economic efficiency are exhibited by “kuzbassenergo,” “enel ogk-5,” “enisseyskaya тgк,” ogk-3 and ogk-2. increasing the environmental and economic efficiency of these production facilities is possible when moving to the efficiency frontier in different directions. the choice of the best direction can be carried out with the help of technical and economic analysis, in which existing technological capabilities (the best available technologies) are taken into account, and their economic indicators, such as the required investment volume, payback period (due to lower costs for environmental payments and penalties), etc. but when the task of increasing the efficiency of the power generating company is subordinate to the task of increasing the environmental and economic efficiency of the res as a whole, the environmental priorities of the company should be determined not only on the basis of corporate interests, but also on the basis of harmonization with the priorities of sustainable development of the regions in which they are located. consider the algorithm for solving the subordinate task by the example of choosing the way to improve the efficiency of ogk-2. ogk-2 is a large corporation that unites several production facilities located in different regions of russia. the structure of ogk-2 includes such generating facilities as adlerskaya chp (krasnodar krai), kirishskaya chp (leningradskaya oblast), krasnoyarskaya chp (krasnoyarsk territory), novocherkasskaya chp (rostov region), pskovskaya chp (pskov oblast), ryazan chp (ryazan oblast), serovskaya chp (sverdlovsk region), stavropolskaya chp (stavropol territory), surgutskaya chp (tyumen region), troitskaya chp (chelyabinskaya oblast) and cherepovetskaya chp (vologda region). two generating facilities (kirishskaya chp and krasnoyarskaya chp) are located in the regions which are recognized as the table 1: the efficiency scores of russian regions regions of russia 2010 2011 2012 2013 2014 khakassia republic 0.61 0.63 0.76 0.72 0.80 altay kray 1 1 1 1 1 zabaykalskiy kray 0.71 0.54 0.67 0.86 0.81 krasnoyarsk 0.44 0.43 0.86 0.75 0.91 irkutsk 0.44 0.41 0.64 0.60 0.90 kemerovo 0.62 0.58 0.93 0.89 0.98 novosibirsk 0.68 0.67 1 1 1 omsk 0.77 0.76 1 1 1 tomsk 0.65 0.58 0.96 0.98 1 sacha republic 0.62 0.59 0.79 0.88 1 kamchatka 0.62 0.83 0.76 0.70 0.97 primorskiy kray 0.54 0.53 0.84 0.86 0.81 chabarovsk 0.58 0.53 0.80 0.86 0.71 amursk 0.74 0.77 0.94 0.92 0.86 magadan 0.59 0.55 0.62 0.61 0.62 sakhalin 0.60 0.59 1 1 1 jewish autonomous region 1 1 1 1 1 chukotsky autonomsous region 1 1 1 1 1 source: authors calculation table 1: (continued) regions of russia 2010 2011 2012 2013 2014 belgorod 0.68 0.57 0.97 0.96 0.94 bryansk 1 1 0.99 0.96 1 vladimir 1 0.97 1 1 1 voronezh 0.76 0.76 1 1 1 ivanov 0.70 0.70 0.78 0.76 0.77 kaluga 1 1 1 1 1 kostroma 0.62 0.57 0.67 0.67 0.55 kursk 0.66 0.66 0.80 0.82 0.98 lipezk 0.63 0.60 0.72 0.66 0.81 moscow (not including moscow city) 1 1 1 1 1 orel 0.89 0.86 1 0.81 0.99 ryazan 0.59 0.57 0.63 0.62 0.69 smolensk 0.64 0.58 0.69 0.63 0.81 tambov 1 1 1 0.93 0.97 tver 0.57 0.65 0.65 0.67 0.91 tula 0.55 0.52 0.68 0.58 0.58 yaroslavl 0.55 0.53 0.71 0.77 0.86 kareliya republic 0.47 0.45 0.61 0.49 0.49 komi republic 0.49 0.49 0.84 0.91 1 archangelsk 0.59 0.57 0.76 0.63 0.62 vologda 0.48 0.48 0.66 0.74 0.60 kaliningrad 0.87 0.93 1 1 1 leningrad 0.53 0.52 0.74 0.77 0.72 murmask 0.72 0.61 1 0.77 0.80 novgorod 0.61 0.56 0.97 0.66 0.80 pskov 0.59 0.48 1 0.48 0.53 adygea republic 0.81 0.65 1 0.96 1 kalmyikiya republic 1 1 1 1 1 krasnodar 1 1 1 1 1 astrachan’ 0.52 0.43 0.78 0.75 1 volgograd 0.56 1 0.99 0.96 0.90 rostov 0.77 0.79 1 1 0.85 dagestan republic 1 1 1 1 1 ingushetia republic 1 1 1 1 1 kabardino-balkarskaya republic 1 1 1 1 1 karachaevo-cherkesskaya republic 0.76 0.61 0.63 0.63 0.45 northern osetiya republic 0.70 0.65 0.82 0.91 0.81 chechenskaya republic 1 1 1 1 1 stavropol 0.97 0.86 1 1 1 bashkortostan republic 1 1 1 1 1 mariy el republic 0.83 0.76 0.87 0.88 0.87 mordoviya republic 1 1 1 1 1 tatarstan republic 0.92 1 1 1 1 udmurtskaya republic 1 1 0.91 1 1 chuvashskaya republic 1 1 1 1 1 perm 0.56 0.57 0.88 0.73 0.69 kirov 0.68 0.60 0.80 0.65 0.70 nizhniy novgorod 0.66 0.63 1 1 1 orenburg 0.46 0.44 0.76 0.64 0.66 penza 0.95 0.74 1 0.96 0.93 samara 0.50 0.48 0.81 0.83 0.82 saratov 1 1 1 1 1 ul’yanovsk 0.94 0.82 0.93 0.89 0.86 kurgansk 1 1 0.93 0.95 1 sverdlovsk 0.99 1 1 1 1 tyumen’ 1 1 1 1 1 chelyabinsk 0.55 0.53 0.89 1 0.96 altay republic 1 1 1 1 1 buryatia republic 0.60 0.65 0.66 0.50 0.55 tyva republic 1 1 1 1 1 (contd...) iosifov, et al.: the problem of harmonizing the environmental priorities of electricity generating companies and regional socio-economic systems: dea-based approach international journal of energy economics and policy | vol 7 • issue 5 • 2017164 regions with the worst indicators of environmental and economic efficiency. therefore, the priority areas of ogk-2’s activities to improve the efficiency of its activities should be the environmental aspects, according to which these regions need the greatest development of eco-innovations: a decrease in wastewater discharge in the leningrad region (the location of kirishskaya chp) and a reduction in fresh water consumption in krasnoyarsk territory (the location of krasnoyarsk chp). 5. concluding remarks the two-step algorithm of harmonization of the priorities of the environmental policy of power generating companies and the regions in which they are located developed in this paper allows us to choose the most preferable directions for technological modernization of energy companies from the point of view of the region. however, for the company itself, the chosen path may not be the most preferable from the point of view of its corporate interests and the goals of innovative development. the required modernization can be financially costly (sinyak and kolpakov, 2014), not fit existing state support programs for innovative development in electricity generating companies (ratner and nizhegorodtsev, 2017), or assume introduction of yet not fully mature (in russia) technologies such as wind energy generation (fortov and popel, 2014; ratner and klochkov, 2017; tarasenko and popel 2015) or geothermal energy generation (alkhasov and alkhasova, 2014). in such cases, the incentives resulting from certification according to iso 14001 may not be sufficient for the companies to launch the process of negative environmental impact reduction. considering the fact that the most significant effects from the implementation of innovation projects of power generating companies will be obtained at the regional level, it seems appropriate to envisage the introduction at the regional level of additional economic stimulus measures aimed at externalizing the positive externalities of the environmental activities of energy companies. for example, it may be additional opportunities to use the resources, infrastructure and intellectual potential of regional innovation systems (ratner and ratner, 2016). the problems of coordinating the priorities of innovative development of power generating companies with the goals of reducing the negative impact on the environment and keeping up the economic feasibility are multi-criterial and complex. the traditional methods of their solution such as technical and economic analysis do not always allow to find an optimal way of development. that’s why the elaboration of special methods is needed. new methods should allow to find optimal trajectories for development of complex production systems in a multidimensional ecological and economic space. one of such methods is ecological dea, the application of which can be used as a basis for the algorithm for reconciling environmental and innovation-investment priorities. acknowledgement this research is partly supported financially by the russian foundation for basic research (rfbr), project no. 16-06-00147. development of data envelopment analysis models for optimizing development of regional economic systems based on ecologic parameters” and completed with the use of scientific equipment table 2: the results of solving the edea ccr problem for power generating companies of russia название score of efficiency target for air pollution, kt target for waste, kt target for water consumption, mln. m3 ogk-1 0.37 91.5 224.66 886.87 ogk-2 0.17 377.9 927.84 3662.84 оgk-3 0.14 186.1 456.92 1803.79 оgк-4 “e.on russia” 0.61 91.5 240.94 676 “enel оgk-5” 0.13 330.3 917.29 1825 tgк-1 0.40 54.59 98.1 526.6 tgк-2 0.27 82.98 237.7 364.7 moscow energy company 1.00 51.4 126.2 498.2 tgк-4 “кvadra” 0.97 20.94 35.6 201.8 тgк-5 0.94 26.04 80.5 107.8 тgк-6 0.59 26.3 30.5 282.17 “volga тgк” (тgк-7) 1.00 34.2 39.1 328.3 тgк-9 0.49 122.2 350.37 532.7 “fortum” (тgк-10) 0.48 51.3 141.87 291.2 тgк-11 1.00 131.8 1658.4 73.2 “kuzbassenergo” (тgк-12) 0.11 173.6 456.03 1296.9 “enisseyskaya тgк” (тгк-13) 0.14 127.3 352.20 720.6 тgк-14 0.72 36.56 105.20 154.3 generating companies of “lucoil” group 1.00 19.2 18.6 356.2 “dalnevostochnaya gк” 0.26 245.7 1981.86 555.6 “irkutsk energo” 0.53 119.34 343.43 503.7 “tatenergo” 1.00 17.2 49.5 72.6 “bashkirenergo” 0.84 30.03058 79.3 219 “sibeco” 0.22 82.5 230.54 437.4 source: author’s calculations based on data of russian ministry of energy, edea: environmental data envelopment analysis iosifov, et al.: the problem of harmonizing the environmental priorities of electricity generating companies and regional socio-economic systems: dea-based approach international journal of energy economics and policy | vol 7 • issue 5 • 2017 165 of ecology and analytical center of kuban state university (krasnodar, russia), project no. rfmefi59317x0008. references alkhasov, a.b., alkhasova, d.a. (2014), up-to-date state and prospects for the development of geothermal resources of the north caucasus region. thermal engineering, 61(6), 411-416. bian, y., yang, f. (2010), resource and environment efficiency analysis of provinces in china: a dea approach based on shannon’s entropy. energy policy, 38, 1909-1917. comoglio, c., botta, s. (2012), the use of indicators and the role of environmental management systems for environmental performances improvement: a survey on iso 14001 certified companies in the automotive sector. journal of cleaner production, 20, 92-102. cook, w.d., seiford, l.m. (2009), data envelopment analysis (dea) thirty years on. european journal of operational research, 192, 1-17. färe, r., grosskopf, s. (2004), modelling undesirable factors in efficiency evaluation: comment. european journal of operational research, 157, 242-245. fortov, v.e., popel’, o.s. (2014), the current status of the development of renewable energy sources worldwide and in russia. thermal engineering, 61(6), 389-398. korhonen, p.j., luptacik, m. (2004), eco-efficiency analysis of power plants: an extension of data envelopment analysis. european journal of operational research, 154, 437-446. nizhegorodtsev, r.m., ratner, s.v. (2016), trends in the development of industrially assimilated renewable energy: the problem of resource restrictions. thermal engineering, 63(3), 197-207. ratner, s., iosifov, v. (2017), eco-management and eco-standardization in russia: the perspectives and barriers for development. journal of environmental management and tourism, 1(17), 247-258. ratner, s., ratner, p. (2017), dea-based dynamic assessment of regional environmental efficiency. applied computer science, 13(2), 48-60. ratner, s.v., almastyan, n.a. (2016), the method of harmonizing the environmental priorities of electricity generating companies and regional socio-economic systems. innovations, 9, 40-47. ratner, s.v., klochkov, v.v. (2017), scenario forecast for wind turbine manufacturing in russia. international journal of energy economics and policy, 7(2), 144-151. ratner, s.v., nizhegorodtsev, r.m. (2017), analysis of renewable energy projects’ implementation in russia. thermal engineering, 64(6), 429-436. ratner, s.v., ratner, p.d. (2016), regional energy efficiency programs in russia: the factors of success. region, 3(1), 68-85. schefczyk, m. (1996), data envelopment analysis. eine methode zur effizienz-und erfolgsschätzung von unternehmen und öffentlichen organisationen. die betriebswirtschaft, 56, 167-183. sinyak, y.u.v., kolpakov, a.y.u. (2014), analysis of the dynamics and structure of expenses in russia’s oil and gas complex over the 20002011 period and forecasts until 2020. studies on russian economic development, 25(5), 439-455. tarasenko, a.b., popel’, o.s. (2015), manufacturing technologies for photovoltaics and possible means of their development in russia (review). part 1: general approach to the development of photoelectric converters and basic silicon technologies. thermal engineering, 62(11), 825-832. testa, f., rizzi, f., daddi, t., gusmerotti, n.m., frey, m., iraldo, f. (2014), emas and iso 14001: the differences in effectively improving environmental performance. journal of cleaner production, 68, 65-173. zobel, t. (2013), iso 14001 certification in manufacturing firms: a tool for those in need or an indication of greenness? journal of cleaner production, 43, 37-44. . international journal of energy economics and policy | vol 8 • issue 6 • 2018 313 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(6), 313-321. development of consumption and supplying energy in indonesia’s economy siti inayatul faizah1*, uus ahmad husaeni2,3 1faculty of economics and business, airlangga university, indonesia, 2awardee lpdp, suryakancana university, indonesia, 3faculty of islamic economics and business, suryakancana university, indonesia. *email: siti-i-f@feb.unair.ac.id received: 22 july 2018 accepted: 03 october 2018 doi: https://doi.org/10.32479/ijeep.6926 abstract one of the problems faced by indonesia is the increasing energy consumption and tend to be wasteful, while the fossil energy reserves are depleted and the development of alternative energy is slow, so it is feared indonesia experiencing energy crisis. the purpose of this article is to analyze the development of consumption and energy supply in indonesia from 2007 to 2017. data analysis in this research is by using combination between trend analysis and descriptive analysis. so the conclusion of this article shows that energy consumption in all sectors, namely industrial sector, household sector, transportation sector, commercial sector and other sectors tend to increase from year to year. meanwhile, overall energy supply tends to increase, but with a smaller increase than the increase in consumption. and to overcome energy problem in indonesia is needed energy conservation that is by conducting energy saving campaign, determination of energy conservation law, and establishment of energy conservation center. furthermore, the indonesian government should have a long-term plan to divert the use of energy from non-renewable sources to renewable energy use, such as the use of water, wind, biomass, biodiesel, biogas and other sustainable energy sources. keywords: energy conservation, energy consumption, energy supply, indonesian economy jel classifications: d11, o1, q4 1. introduction energy is indispensable in carrying out the economic activities of indonesia, both for consumption needs and for the production activities of various sectors of the economy. as a natural resource, energy should be utilized as much as possible for the welfare of the community and its management should refer to the principle of sustainable development. from the aspect of supply, indonesia is a country rich with energy resources both energy that is unrenewable resources and that is renewable resources (dargay et al., 2007). nevertheless, the exploration of energy resources focused more on fossil energy that is unrenewable resources while renewable energy has not been widely used. this condition causes the availability of fossil energy, especially crude oil, increasingly scarce which causes indonesia is now a net importer of crude oil and its derivative products (diputra and jungho, 2018). according to the ministry of energy and mineral resources (2017) indonesia’s crude energy reserves can only be produced or will be exhausted within 22.99 years, gas for 58.95 years and coal for 82.01 years. this calculation uses the assumption that no new fields are found as a source of fossil energy. energy reserves can increase (last long) if new fields are found. from the aspect of consumption shows that indonesia’s energy consumption has increased from year to year. in the period 2007–2017, the final energy consumption experienced an average annual increase of 2.73% from 953,334,957 boe to 1,058,262,186 boe. according to sector type, energy consumption in industrial sector is the highest energy consumption followed by households, transportation, non energy utilization, commercial and other (table 1). with the depletion of fossil energy reserves on one side, while on the other hand energy consumption continues to increase become this journal is licensed under a creative commons attribution 4.0 international license faizah and husaeni: development of consumption and supplying energy in indonesia’s economy international journal of energy economics and policy | vol 8 • issue 6 • 2018314 a threat to the development of the indonesian economy. therefore efforts should be made to encourage the efficient utilization of energy use along with the search for new sources of fossil energy intensively and to develop alternative energy that is renewable resources. the main cause of inefficiency in energy utilization is the policy of cheap energy prices applied by the government of indonesia. according to hakam and asekomeh (2018), the policy of cheap energy prices by providing large subsidies has a negative impact: first, the high dependence on crude energy sources. low price signal becomes a disincentive for diversification and conservation (energy saving). second, fuel subsidies in the state budget threaten the fiscal sustainability of the government. third, not optimal use of other energy sources, such as natural gas and coal whose reserves are much larger than crude oil as well as new and renewable energy. fourth, the rampant smuggling of fuel abroad so that the level of demand is higher than the real need. fifth, the rampant fuel pollution activities that harm the state and general consumers. and sixth, price signals distort the feasibility of investing in the downstream sector of oil and gas. utilization of wasteful energy is shown by high energy elasticity. the average energy elasticity value in 2007–2016 period was 2.17. this means that if economic growth (gdp) increases by 1% then the final energy consumption will increase by 2.17%. this figure indicates indonesia is a wasteful state energy. energy in indonesia is still widely used for activities that do not produce (kim and yoo, 2016). elasticity numbers <1 are achieved when available energy has been used productively, as occurs in developed countries ranging from 0.55 to 0.65. in other words, developed countries have a strong, renewable, distributed, and evenly distributed energy retention system optimally and productively (fotourehchi, 2017). another indicator that shows the waste in energy utilization in indonesia is the energy intensity. energy intensity is the ratio between the amount of final energy consumption and gdp per capita. the more efficient a country, the less the intensity will be. so far, energy subsidies that have been implemented by the government actually lead to waste of energy, because its use is less than optimal. this is reflected in the relatively high energy intensity of 482 ton-oil-equivalent (toe) per million us dollar. this means to generate value added (gdp) 1 million us dollars, indonesia requires energy 482 toe. in comparison, malaysia’s energy intensity is only 439 toe/million us dollar, and the average energy intensity of developed countries incorporated in the organization for economic co-operation and development is only 164 toe/million us dollar. this indicates that the potential for energy saving in indonesia is still considerable (zambrano et al., 2016). from the above description shows that the problems faced by indonesia are increasing energy consumption and tend to be wasteful, while the fossil energy reserves are getting thinning and the development of alternative energy is slow. in more detail the development of energy consumption and supply in indonesia along with solutions in energy consumption issues will be discussed in this article.t ab le 1 : f in al e ne rg y co ns um pt io n by s ec to r se ct or 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 * in du st ri al 33 8, 66 5, 25 8 32 0, 30 2, 44 7 30 4, 79 1, 44 8 34 9, 04 0, 46 3 37 3, 94 7, 84 0 36 8, 11 9, 08 0 28 2, 17 5, 20 4 28 9, 80 1, 99 3 30 9, 18 4, 95 8 25 9, 12 3, 61 5 13 1, 60 1, 40 5 h ou se ho ld s 32 1, 99 2, 72 8 32 1, 93 6, 05 5 32 1, 56 9, 20 3 33 2, 20 3, 76 2 33 9, 15 3, 42 8 34 9, 08 4, 28 9 36 0, 01 6, 14 2 36 9, 89 3, 47 0 37 3, 78 6, 74 6 37 8, 04 6, 00 6 19 4, 78 9, 53 0 c om m er ci al 27 ,2 35 ,0 95 28 ,2 18 ,8 00 29 ,5 58 ,7 20 30 ,9 35 ,2 44 34 ,1 31 ,8 50 37 ,1 35 ,4 87 39 ,2 36 ,1 40 40 ,2 49 ,5 80 42 ,4 46 ,4 65 41 ,4 52 ,2 39 22 ,2 87 ,7 34 tr an sp or ta tio n 17 4, 67 9, 83 0 18 5, 66 8, 88 2 20 9, 96 8, 39 8 23 0, 34 5, 87 0 27 7, 51 2, 76 2 32 9, 52 0, 05 1 34 1, 40 9, 71 1 34 2, 78 1, 96 0 30 7, 07 7, 74 9 30 3, 26 6, 13 9 15 2, 93 7, 16 4 o th er 25 ,2 87 ,1 55 25 ,0 68 ,6 04 25 ,2 93 ,6 06 22 ,3 40 ,4 93 27 ,2 20 ,3 38 33 ,7 09 ,2 15 31 ,1 05 ,2 54 28 ,6 94 ,6 57 32 ,8 36 ,3 85 19 ,4 40 ,2 20 13 ,6 63 ,7 53 n on e ne rg y ut ili za tio n 65 ,4 74 ,8 91 73 ,8 47 ,3 98 84 ,0 96 ,7 59 84 ,1 46 ,7 77 98 ,2 84 ,7 11 11 2, 56 5, 95 3 94 ,5 31 ,0 56 98 ,7 45 ,7 43 77 ,4 43 ,0 48 56 ,9 33 ,9 67 25 ,7 65 ,4 25 fi na l e ne rg y co ns um pt io n 95 3, 33 4, 95 7 95 5, 04 2, 18 7 97 5, 27 8, 13 4 1, 04 9, 01 2, 60 9 1, 15 0, 25 0, 92 9 1, 23 0, 13 4, 07 4 1, 14 8, 47 3, 50 7 1, 17 0, 16 7, 40 3 1, 14 2, 77 5, 35 0 1, 05 8, 26 2, 18 6 54 1, 04 5, 01 1 *t em po ra ry d at a up to s em es te r i 2 01 7 faizah and husaeni: development of consumption and supplying energy in indonesia’s economy international journal of energy economics and policy | vol 8 • issue 6 • 2018 315 2. methods 2.1. data sources the data used in this study is secondary data in the form of time series data from 2007 to 2017. the data collected includes energy consumption data by sector and energy type and data of indonesian energy supply. the main data sources are indonesia’s energy balance data obtained from the ministry of energy and mineral resources, as well as data sources from the central bureau of statistics, and other relevant agencies. 2.2. analysis method data analysis method used is combination between trend analysis and descriptive analysis. trend analysis shows the pattern or fluctuation of energy supply by type of energy and energy consumption according to the user. descriptive analysis describes the problems and or advantages of the fluctuations that occur from the results of trend analysis presented. 3. results and discussion 3.1. energy consumption in indonesian economy energy consumption in indonesia in this study is differentiated by energy user sector which includes: industrial sector, household, transportation, commercial and other sectors. energy consumed by energy users is the final energy. 3.2. energy consumption of industrial sector along with the development of the industrial sector led to an increase in energy consumption in the production process to produce a product. in the period 2007–2017, industrial energy consumption fluctuated up and down. in 2012, energy consumption in the industry sector is at the highest level of 480,685 boe, while in 2016 the energy consumption in the industrial sector is at the lowest level of 354,560 boe. the types of energy consumed by the industrial sector are biomass, coal, briquette, gas, fuel, liquefied petroleum gas (lpg), electricity and other petroleum products. from table 1 it can be seen that during the period 2007–2017 the highest energy type consumed by the industrial sector was gas and the lowest consumption was briquette (table 2). in its development, the type of energy consumption in the industrial sector has increased and decreased. for biomass consumed the highest in 2014 and the lowest in 2016, the highest consumption coal in 2011 and the lowest in 2013. briquette consumption showed the lowest consumption in the industry sector, and the highest consumption was in 2009 by 220 thousand boe. meanwhile, gas is the type most consumed by the industry sector, the highest was in 2013 of 123.8 million boe. for most types of fuel consumption was in 2007 amounted to 62.667 million boe. lpg consumption in 2007 amounted to 1.431 million boe. furthermore, energy consumed most consumed in 2016 amounted to 41,773 million boe. while the remaining types of consumption in the energy sector are in other types of petroleum products (the highest in 2012 amounted to 83.418 million boe). 3.3. energy consumption of household sector energy is needed by household for lighting purposes, cooking, heating/cooling room, and various other household activities. energy t ab le 2 : e ne rg y co ns um pt io n in in du st ri al s ec to r (t ho us an d b o e ) y ea r b io m as s c oa l b ri qu et te g as f ue l f ue l ot he r p et ro le um p ro du ct l p g e le ct ri ci ty to ta l k er os en e a d o id o f ue l o il to ta l f ue l 20 07 44 ,0 47 12 1, 90 4 10 5 10 5, 31 9 3, 35 2 29 ,7 61 1, 32 8 28 ,2 26 62 ,6 67 40 ,5 89 1, 43 1 28 ,0 77 40 4, 14 0 20 08 44 ,2 35 94 ,0 35 15 5 11 2, 00 1 2, 67 6 30 ,0 95 86 5 27 ,4 82 61 ,1 18 52 ,0 73 1, 12 7 29 ,4 05 39 4, 15 0 20 09 44 ,5 21 82 ,5 87 22 0 11 7, 53 5 1, 61 9 32 ,2 38 70 6 24 ,8 88 59 ,4 51 55 ,6 63 58 8 28 ,3 23 38 8, 88 8 20 10 43 ,3 17 13 7, 48 9 12 3 11 4, 11 1 96 4 28 ,0 49 61 2 20 ,8 48 50 ,4 73 55 ,7 65 65 5 31 ,2 54 43 3, 18 7 20 11 43 ,7 24 14 4, 50 2 12 1 11 9, 64 9 67 2 36 ,8 86 71 0 21 ,8 20 60 ,0 89 69 ,9 78 62 3 33 ,5 47 47 2, 23 3 20 12 42 ,7 32 12 3, 02 2 13 0 12 3, 16 1 46 8 49 ,5 15 50 7 20 ,2 23 70 ,7 13 83 ,4 18 62 1 36 ,8 88 48 0, 68 5 20 13 44 ,3 99 42 ,7 29 13 0 12 3, 80 0 42 7 46 ,8 22 43 8 11 ,6 42 59 ,3 28 66 ,1 61 69 3 39 ,4 66 37 6, 70 6 20 14 45 ,1 88 55 ,0 64 58 12 2, 69 9 32 9 42 ,3 30 33 7 11 ,1 12 54 ,1 08 70 ,2 77 75 3 40 ,4 02 38 8, 54 8 20 15 44 ,8 28 70 ,2 28 50 12 2, 07 9 26 1 51 ,5 89 29 4 9, 71 7 61 ,8 59 47 ,5 14 78 8 39 ,2 81 38 6, 62 8 20 16 42 ,4 34 63 ,5 04 10 7 99 ,7 39 20 0 28 ,2 46 20 9 7, 25 1 35 ,9 05 70 ,2 77 82 1 41 ,7 73 35 4, 56 0 20 17 * 21 ,2 17 29 ,4 17 50 52 ,9 54 10 1 22 ,6 87 38 5, 22 6 28 ,0 52 35 ,1 39 50 1 21 ,2 16 18 8, 54 6 *t em po ra ry d at a up to s em es te r i 2 01 7, l pg : l iq ue fie d pe tr ol eu m g as faizah and husaeni: development of consumption and supplying energy in indonesia’s economy international journal of energy economics and policy | vol 8 • issue 6 • 2018316 consumed by households includes: biomass, gas, kerosene, lpg and electricity. the types of biomass energy consumed by households are firewood, charcoal, and others used for cooking. in total household consumption increased during the period 2007–2017. during that period household energy consumption increased by 1.87% per year (except in 2008) from 321,993 million boe (2007) to 378,046 million boe (2016). increased consumption in this sector is due to an increase in the number of family members and number of households in indonesia (table 3). the types of energy consumed by households from the highest to the lowest are biomass, electricity, lpg, kerosene and gas. during the period 2007–2017 biomass consumption showed an increase but has a low average growth per year at 1.38%. this indicates that households have started to reduce the use of biomass energy, because there are other alternative energy that is easier and cheaper to use. with the increase of biomass energy consumption in the household sector shows that most households in indonesia still use firewood for cooking, especially households in rural areas (aydin, 2015). this happens because the supply of firewood in the countryside is quite large. in addition, the economic price to get firewood is relatively cheap. the results of this study are similar to the results of jul (2014) study, which states that the type of household consumption in indonesia is mostly non-commercial energy (fuel wood and charcoal), which is mostly from poor households. meanwhile, rich households consume commercial energy such as gas, electricity and kerosene. in addition to biomass energy, electrical energy during the 2007–2017 period showed an increased growth. during the period 2007–2017 the consumption of electric energy showed an average annual increase of 4.2%. increased electricity consumption by households is due to cheaper electricity prices compared to kerosene and lpg prices. meanwhile, kerosene consumption by households showed a declining trend, caused by the indonesian government policy on kerosene conversion to lpg which started in 2008. so from 2008 kerosene consumption decreased significantly. meanwhile, lpg consumption has increased significantly every year, and the highest consumption of lpg occurred in 2016 amounted to 57,398 million boe. 3.4. energy consumption of transportation sector the means of transportation is necessary in order to mobilize goods and people from one place to another. in relation to energy consumption, the transport sector in question includes means of transportation driven by machinery or motor vehicles. there are three types of energy consumed by the transportation sector, namely fuel, gas and electricity. from table 4 it can be seen that transportation sector energy consumption shows an increasing trend during the period 2007–2017 except in 2015. during that period the total energy consumption of the transportation sector increased with an average growth per year of 3.31%. the types of energy consumed by the transportation sector from the largest to the smallest are fuel, gas and electricity, respectively. in its development fuel consumption showed an increasing trend, while gas and electricity consumption fluctuated (table 5). the amount of fuel consumption by the transportation sector is due to the increasing number of motor vehicles using fuel, both public and private vehicles. in addition, travel by vehicle is less efficient because of poor road infrastructure so it takes a long travel time. long travel time will increase fuel consumption. 3.5. energy consumption of commercial sector the commercial sector includes residential institutions. the commercial sector also includes waste treatment facilities. common uses of energy associated with this sector include space heating, water heating, air cooling, lighting, cooling, cooking, and running other equipment. this sector also includes generators that generate electricity and or heat output beneficial to support the activities of the commercial entity mentioned above. the use of energy consumption in this commercial sector can be seen in table 5. based on table 5 data shows that the type of energy electricity is the type of energy that dominates the use of energy in commercial sector with the highest amount in 2016 amounted to 33.103 million boe. meanwhile, the type of energy fuel is in second position with the highest consumption in 2015 of 7,428 million boe. biomass is third in energy use in the commercial sector with the highest amount in 2007 of 1,402 million boe. while lpg is in the fourth position with the highest amount in 2016 amounted to 4.234 million boe and gas was in the fifth position with the highest amount in 2014 of 1.447 million boe. 3.6. other energy sector consumption other sectors in this article fall into sectors not mentioned in the previous section, such as trade, hotels and restaurants, and others. the reason for the inclusion of these sectors into other table 3: energy consumption in household sector (thousand boe) year biomass gas kerosene lpg electricity total 2007 234,557 132 50,229 8,064 29,010 321,993 2008 237,459 131 40,096 13,487 30,763 321,936 2009 240,736 130 24,255 22,767 33,682 321,569 2010 250,571 135 14,439 30,386 36,673 332,204 2011 253,727 114 10,072 35,326 39,914 339,153 2012 256,594 134 7,015 41,123 44,217 349,084 2013 260,328 122 6,396 45,839 47,330 360,016 2014 263,495 114 4,929 49,810 51,545 369,893 2015 263,275 116 3,903 52,130 54,362 373,787 2016 263,215 137 2,995 54,302 57,398 378,046 2017* 131,607 68 1,514 33,134 28,466 194,790 *temporary data up to semester i 2017, lpg: liquefied petroleum gas faizah and husaeni: development of consumption and supplying energy in indonesia’s economy international journal of energy economics and policy | vol 8 • issue 6 • 2018 317 sectors because these sectors have a small composition in energy consumption. other sectors consume the type of energy of fuel, gas, biomass and electricity. in figure 6 it can be seen that the total energy consumption of other sectors tends to increase with an average growth per year of 3.72%. based on the type of energy, other sectors consume the largest fuel energy followed by gas and kerosene energy. in its development, energy consumption of fuel and gas by other sectors showed an increasing trend, while kerosene consumption showed a declining trend (table 6). 4. energy supply in indonesia’s economy energy supply in the future is a problem that is always the concern of all nations because human welfare in modern life is closely related to the amount and quality of energy utilized. for indonesia which is one of the developing countries, the provision of energy is a very important factor in encouraging development. along with the increasing development in various sectors, economic growth and population growth, the need for energy will continue to increase (anastacio, 2017). in meeting the energy needs, national energy supply is supplied from domestic and imported production. energy supply from domestic production is highly dependent on technology and energy infrastructure. energy infrastructure consists of energy conversion infrastructure (in the form of oil refineries, gas and power plants), energy transmission and distribution infrastructure (oil pipelines, gas pipelines, transmission and distribution networks), and physical infrastructure (ports, roads, fire). the fact is that indonesia has limitations in this regard. exploration technology and energy infrastructure require large and long-term capital. therefore, government policy is needed to increase investment in energy sector. with these limitations, to meet domestic energy demand, it can be imported from other countries (harris, 2017). oil imports depend on how much energy, world oil prices and the rupiah exchange rate against the us dollar are. 4.1. coal supply coal plays an important role in meeting energy demand and ensuring energy availability for industry and power generation. consumption on the type of coal energy is used by power plant and industry sectors. table 7 shows that the power plant sector is one of the industries with the highest consumption of coal with the highest consumption in 2016 of 74.4 million tonnes. while the rest is used by industry sector with the type of iron and steel, ceramic and cement, pulp and paper, and briquette. besides, coal is also used by households as fuel for cooking. the utilization of coal as an energy source is due to the fact that coal reserves are still available and their prices are relatively cheaper than lpg, kerosene and gas (table 7). the magnitude of the role of coal as a source of energy other than fuel cannot be separated from the availability of coal that can be consumed by the community as one source of energy. table 8 shows that coal production tends to increase. during the last 11 years (2007–2017) coal production has increased an average aq2 ta bl e 4: e ne rg y co ns um pt io n in tr an sp or ta ti on s ec to r (t ho us an d b o e ) y ea r g as f ue l e le ct ri ci ty to ta l a vg as a vt ur r o n 8 8 r o n 9 2 r o n 9 5 r o n 9 0 so la r 51 so la r 53 k er os en e a d o id o f ue l o il b io r o n 8 8 b io r o n 9 2 b io s ol ar to ta l b io fu el 20 07 49 12 14 ,8 45 10 2, 78 4 2, 75 2 92 1 0 8 0 22 48 ,6 43 53 54 9 32 6 58 3, 60 4 17 4, 57 9 52 17 4, 68 0 20 08 12 4 11 15 ,5 26 11 1, 37 7 1, 73 6 66 9 0 8 0 18 49 ,1 89 35 53 5 25 7 95 6, 04 1 18 5, 49 5 50 18 5, 66 9 20 09 19 1 9 16 ,2 62 12 1, 22 6 2, 68 2 60 8 0 13 0 11 52 ,6 92 28 48 4 61 7 11 8 14 ,9 59 20 9, 70 9 68 20 9, 96 8 20 10 19 5 12 20 ,7 79 13 0, 48 6 3, 90 7 66 3 0 29 0 6 45 ,8 45 24 40 5 0 0 27 ,9 39 23 0, 09 6 54 23 0, 34 6 20 11 18 1 13 20 ,9 83 14 4, 33 0 3, 64 3 1, 71 7 0 41 0 4 60 ,2 89 28 42 4 0 0 45 ,8 04 27 7, 27 8 54 27 7, 51 3 20 12 15 4 14 22 ,9 67 16 0, 91 0 3, 88 4 87 1 0 80 0 3 80 ,9 30 20 39 3 0 0 59 ,2 27 32 9, 30 0 66 32 9, 52 0 20 13 18 5 16 24 ,4 99 16 6, 80 0 4, 95 6 92 5 0 15 0 0 3 76 ,5 29 17 22 6 0 0 67 ,0 25 34 1, 14 6 79 34 1, 41 0 20 14 20 7 8 24 ,9 12 16 7, 96 0 6, 19 4 90 3 0 21 6 0 2 69 ,1 87 13 21 6 0 0 72 ,8 68 34 2, 48 0 95 34 2, 78 2 20 15 24 6 17 25 ,5 46 15 8, 91 4 16 ,0 95 1, 62 4 2, 21 4 25 0 0 2 84 ,3 20 12 18 9 0 0 19 ,7 37 30 8, 92 1 12 6 30 9, 29 2 20 16 20 5 16 27 ,4 81 12 2, 99 2 27 ,9 11 1, 69 6 33 ,8 32 68 7 48 0 1 46 ,1 67 8 14 1 0 0 75 ,3 43 33 6, 75 7 13 7 33 7, 09 8 20 17 * 10 2 6 14 ,8 37 40 ,3 50 15 ,4 52 73 3 33 ,8 36 80 1 52 0 1 37 ,0 81 2 10 2 0 0 42 ,8 81 18 6, 60 1 70 18 6, 77 3 *t em po ra ry d at a up to s em es te r i 2 01 7 faizah and husaeni: development of consumption and supplying energy in indonesia’s economy international journal of energy economics and policy | vol 8 • issue 6 • 2018318 of 14.03% per year. furthermore, in the period of 2007–2017 (semester 1), total coal production is 3.808 billion tons and total coal exports amounted to 2,958 billion tons, only 9.28% are consumed domestically and 90.72% of the remaining is exported. thus domestic coal production is more exported than used for domestic purposes (table 8). indonesia’s coal export destination countries are countries in asia such as japan, china, taiwan, india, south korea, hong kong, malaysia, thailand and the philippines. other export destinations are europe such as netherlands, germany and england, as well as countries in america. the largest importers of indonesian coal are china (22.8%) and india (20.7%). the type of coal exported indonesia is steam coal type. 4.2. crude oil crude oil as raw material to produce fuel, such as gasoline (premium), diesel, diesel oil, kerosene and lubricants. thus, crude oil has a role in meeting the energy needs. crude oil is sourced from non-renewable natural reserves, thereby depleting its reserves in line with the increasing demand for energy. table 9 shows that indonesia’s crude oil supply tends to decline over the 2007–2017 period from 8.40 billion barrels in 2007 to 7.53 billion barrels in 2017. according to the indonesian petroleum and gas management agency, indonesia’s oil production has declined due to the scarcity capacity that can not accommodate domestic and aging oil needs (+30 years), requiring substantial investment to curb the rate of natural decline. while efforts to buffer production through new table 5: energy consumption in commercial sector (thousand boe) year biomass gas fuel lpg electricity total kerosene ado ido total fuel 2007 1,402 274 2,774 4,285 7 7,066 1,308 17,185 27,235 2008 1,395 357 2,214 4,333 5 6,552 1,044 18,871 28,219 2009 1,388 730 1,339 4,642 4 5,985 1,029 20,426 29,559 2010 1,381 963 797 4,039 3 4,839 1,026 22,726 30,935 2011 1,374 1,290 556 5,311 4 5,871 1,112 24,485 34,132 2012 1,367 1,625 387 7,130 3 7,520 1,139 25,485 37,135 2013 1,360 1,422 353 6,742 2 7,098 1,269 28,088 39,236 2014 1,353 1,447 272 6,095 2 6,369 1,379 29,701 40,250 2015 1,346 1,435 216 7,428 2 7,645 1,444 30,576 42,446 2016 1,340 1,272 165 4,067 1 4,234 4,234 33,103 41,452 2017 667 636 84 3,267 0 3,351 918 16,717 22,288 *temporary data up to semester i 2017, lpg: liquefied petroleum gas table 6: energy consumption in others sector (thousand boe) year gas kerosene ado ido fuel oil total fuel 2007 3,156 2,295 15,098 198 4,539 25,287 2008 3,420 1,832 15,268 129 4,420 25,069 2009 3,722 1,108 16,335 105 4,002 25,294 2010 4,006 660 14,230 91 3,353 22,340 2011 4,432 460 18,713 106 3,509 27,220 2012 4,941 321 25,120 76 3,252 33,709 2013 5,121 292 23,754 65 1,187 31,105 2014 5,157 225 21,475 50 1,767 28,695 2015 4,879 178 26,172 44 1,563 32,836 2016 3,776 137 14,330 31 1,166 19,440 2017* 1,239 69 11,510 6 840 13,664 *temporary data up to semester i 2017 table 7: coal sales (ton) year total iron and steel power plant ceramic and cement pulp and paper bri-quette others 2007 61,470,000 282,730 32,420,000 6,443,864 1,526,095 25,120 20,772,192 2008 53,473,252 245,949 31,041,000 6,842,403 1,251,000 43,000 14,049,899 2009 56,295,000 256,605 36,570,000 6,900,000 1,170,000 61,463 11,336,932 20102 67,180,051 335,000 34,410,000 6,308,000 1,742,000 34,543 24,350,508 2011 79,557,800 166,034 45,118,519 5,873,144 n.a. 33,939 28,366,165 2012 82,142,862 289,371 52,815,519 6,640,000 2,670,701 36,383 19,690,889 2013 72,070,000 300,000 61,860,000 7,190,000 1,460,000 36,383 1,223,617 2014 76,180,001 298,000 63,054,000 7,187,400 1,458,170 15,623 4,166,808 2015 86,814,099 399,000 70,080,000 7,180,000 4,310,000 13,174 4,831,925 2016 90,550,000 390,000 75,400,000 10,540,000 4,190,000 30,000 0 2017* 46,327,000 123,956 41,500,000 3,349,977 1,331,727 21,340 0 *temporary data up to semester i 2017 faizah and husaeni: development of consumption and supplying energy in indonesia’s economy international journal of energy economics and policy | vol 8 • issue 6 • 2018 319 field production are highly dependent on the performance of contract contractors, because in the petroleum industry requires enormous capital and high technology. the decline in indonesia’s crude oil production will have an impact on increasing domestic fuel needs. therefore, to meet domestic needs it is necessary to import crude oil. the demand for crude oil imports is expected to continue to increase in line with the increasing population growth and economic growth in indonesia is expected to improve (nor and masron, 2018). 4.3. natural gas from table 10 shows natural gas production during 2007–2010 increased by an average of 2.3% from 2,805,540 mmscf (million standard cubic feet) to 3,407,592 mmscf. however, during the period 2011-2016 natural gas production tends to decline. during that period natural gas decreased by 0.93% annually from 3,256,379 mmscf to 3,070,239 mmscf. this low gas production is due to limited gas production capacity. gas production plants are old and investments in exploration activities to build new gas and oil wells are lower. according to moremadi and yadollah (2018), the low investment in oil and gas is caused by a number of uncertainties, including security issues, high taxes and uncertainty surrounding the implementation of the new oil and gas law number 22 year 2001, the uncertainty of the government’s position in developing wells aged gas, new oil and renewal of contracts at existing oil wells. the implication is that some oil and gas companies suspend their investment plans throughout 2012–2021 (table 10). 4.4. electricity during the period 2007-2017 electricity sales in indonesia increased by an average of 6.24% per year. the most widely used electricity consumption sector is the household sector with average consumption from 2007-2016 of 69.313 gwh (giga watt hour). while the lowest electrical energy consumption in the transportation sector (table 11). with the increasing consumption of electrical energy then automatically the supply of electrical energy also increases. the increase in electricity supply is caused by an increase in electricity demand from various sectors due to the improvement of the people’s economy. increased demand for electrical energy encourages the development of the discovery of electrical energy derived from renewable energy, such as hydropower, geothermal energy, micro hydro, biomass, solar and wind. table 12 shows the renewable energy that can generate electrical energy. from the table only about 3.32% of renewable energy that can be utilized into electrical energy, the rest cannot be used optimally because of limited technology owned. 5. solution to overcoming energy problems in indonesia solving a problem must be a matter of what is being experienced. as has been pointed out in the previous section that the energy problem that indonesia is facing today is the problem of energy table 8: coal supply (ton) year production export import steam coal antracite total 2007 216,946,699 0 216,946,699 163,000,000 67,534 2008 240,249,968 0 240,249,968 191,430,218 106,931 2009 256,181,000 0 256,181,000 198,366,000 68,804 2010 275,164,196 0 275,164,196 208,000,000 55,230 2011 353,270,937 0 353,270,937 272,671,351 42,449 2012 386,077,357 0 386,077,357 304,051,216 77,786 2013 474,371,369 0 474,371,369 356,357,973 609,875 2014 458,096,707 0 458,096,707 381,972,830 2,442,319 2015 461,566,080 0 461,566,080 365,849,610 3,007,934 2016 456,197,775 0 456,197,775 331,128,438 3,898,932 2017* 230,365,346 0 230,365,346 185,591,205 1,870,722 *temporary data up to semester i 2017 table 9: crude oil reserves (billion barrels) year proven potential total 2007 3.99 4.41 8.40 2008 3.75 4.47 8.22 2009 4.30 3.70 8.00 2010 4.23 3.53 7.76 2011 4.04 3.69 7.73 2012 3.74 3.67 7.41 2013 3.69 3.86 7.55 2014 3.62 3.75 7.37 2015 3.60 3.70 7.31 2016 3.31 3.94 7.25 2017 3.17 4.36 7.53 table 10: natural gas production (mmscf) year associated non associated total 2007 433,630 2,371,910 2,805,540 2008 472,897 2,412,431 2,885,328 2009 467,570 2,593,326 3,060,897 2010 471,507 2,936,086 3,407,592 2011 472,552 2,783,827 3,256,379 2012 405,465 2,769,175 3,174,639 2013 352,561 2,768,277 3,120,838 2014 304,693 2,871,098 3,175,791 2015 376,669 2,739,473 3,116,142 2016 467,813 2,602,426 3,070,239 2017* 241,785 1,216,720 1,458,505 *temporary data up to semester i 2017 faizah and husaeni: development of consumption and supplying energy in indonesia’s economy international journal of energy economics and policy | vol 8 • issue 6 • 2018320 waste (liddle and lung, 2013). on the other hand, increased energy consumption is not balanced with the supply of sufficient energy, so that indonesia has an energy deficit. thus, it is necessary to find solutions to these problems, among others, by converting (saving) energy and applying appropriate economic policies. 5.1. energy conservation as has been stated earlier that based on the value of elasticity and intensity of energy utilization indonesia is one of the countries with the utilization of energy wasted in the world. therefore, intensive efforts are needed in order to improve the efficiency of energy utilization. according to dudin et al. (2016) several strategic steps that need to be taken to streamline the energy conservation movement: first, energy-saving campaigns, conducting energy audits (free), disseminating energy conservation techniques, providing incentives for energy efficiency utilization. second, prepare the energy conservation act. and third, establish national energy conservation center, as did japan and thailand. strategic steps put forward by dudin et al. (2016) is based on the idea that letting the energy-consuming pattern of consumption be wasteful will be very detrimental, both in terms of economy, environment and efforts to maintain the benefits of the energy resources themselves. since the “disease” caused as a result of ignoring these energy conservation efforts is already severe enough, the conservation of energy as a necessity should not be postponed again in indonesia. conservation (saving) energy will bring many benefits. by conserving energy as if finding new energy sources. if indonesia can save fuel consumption by about 10%, it means “finding” a new oil field that can produce about 150,000 barrels per day, which in reality costs considerable expenses for exploration and production. the cost that can be saved by doing conservation is huge. in addition, energy conservation is also set forth in the presidential instruction issued in 1982 (inpres no. 9/1982) which is then refined by presidential decree no. 43 in 1991. in the community emerged non-governmental organizations (energy efficient society) who pay attention to energy conservation. an esco was established by the government which then made it a state-owned energy company (pt koneba). pln (national electric company) undertook several demand side management projects to reduce electricity consumption on the usage side. the department of energy undertook a number of energy conservation demonstration projects, for example in government office buildings (something similar was done at college campus buildings). the government even issued a document of riken (master plan for conservation of energy) which was not followed by a clear action plan. 5.2. economic policy the formulation of the right economic policy can overcome the national energy consumption and supply. in addressing the issue of energy availability that cannot meet domestic energy needs, it is necessary to enact policies in the short term, medium term and long term. in the short term, efforts are needed to improve efficiency and productivity of energy utilization, among others, by the conversion of fuel to gas for households, and the elimination of fuel subsidies (lee and chang, 2008). a low interest rate policy and stable exchange rate are also needed to counter the negative impact of rising world oil prices that could lead to declining consumption and energy supply (sari and soytas, 2007). in the medium term, efforts are needed to increase investment from aspects of fossil energy production, processing and distribution, and efforts to convert fuel-based energy use by the industrial sector to other types of energy (devereux and lane, 2003). along with that, efforts need to increase the number and capacity of oil and gas refineries to reduce the level of dependence on the final energy sourced from imports (apostolakis, 1990). efforts to increase the number and capacity of power plants also need to be done to eliminate electricity deficits, focused on the use of energy other table 11: electricity sales (gwh) year electricity sales/tariff segment total household commercial industry street lighting social government transportation 2007 47,325 20,524 45,803 2,586 2,909 2,016 85 121,247 2008 50,184 22,845 47,969 2,761 3,082 2,096 81 129,019 2009 54,945 24,715 46,204 2,888 3,384 2,335 111 134,582 2010 59,825 27,069 50,985 3,000 3,700 2,630 89 147,297 2011 65,112 30,093 54,725 3,068 3,994 2,787 88 159,867 2012 72,133 30,880 60,176 3,141 4,496 3,057 108 173,991 2013 77,211 34,369 64,381 3,251 4,939 3,261 129 187,541 2014 84,086 36,128 65,909 3,394 5,446 3,484 155 198,602 2015 88,682 36,773 64,079 3,448 5,941 3,717 205 202,846 2016 93,635 39,852 68,145 3,498 6,631 4,022 223 216,004 2017* 46,437 20,145 34,609 1,751 3,398 1,977 114 108,431 *temporary data up to semester i 2017 table 12: potential of renewable energy for power generation renewable energy potency installed generator capacity water power 75.67 gw 4200.00 mw geothermal 27.00 gw 800.00 mw mini/micro hydro 458.75 mw 84.00 mw biomass 49.81 gw 302.40 mw sun 4.80 kwh/m2/day 8.00 mw wind 9.29 gw 0.50 mw source: blue print national energy management 2006–2025 faizah and husaeni: development of consumption and supplying energy in indonesia’s economy international journal of energy economics and policy | vol 8 • issue 6 • 2018 321 than fuel, such as power plants using coal and gas energy. in the long run, efforts to shift energy use from unrenewable resources to renewable energy use, such as water, wind, biomass, biodiesel, biogas and other sustainable energy sources. in other words, a green energy strategy is needed. 6. conclusion the trend of energy consumption of various sectors shows that in the period 2007–2017, industrial energy consumption fluctuated up and down. in 2012, energy consumption in the industry sector was at the highest level of 480,685 boe, while in 2016 energy consumption in the industry sector was at the lowest level of 354,560 boe. in total household consumption increased during the period 2007–2017. during that period household energy consumption increased by 1.87% per year (except in 2008) from 321,993 million boe (2007) to 378,046 million boe (2016). transportation energy consumption shows an increasing trend during the period 2007–2017 except in 2015. during that period the total energy consumption of the transportation sector increased with an average growth per year of 3.31%. type of energy electricity is the type of energy that dominates the use of energy in commercial sector with the highest amount in 2016 amounted to 33.103 million boe. total energy consumption of other sectors tends to increase with an average growth per year of 3.72%. the trend of energy supply by type of energy shows that during the last 11 years (2007–2017) coal production has increased by an average of 14.03% per year. if further noted, in the period 2007–2017 (semester 1) total coal production of 3.808 billion tons. indonesia’s crude oil supply tended to decline during the 2007–2017 period from 8.40 billion barrels in 2007 to 7.53 billion bars in 2017. natural gas production during 2007–2010 increased by an average of 2.3% from 2,805,540 mmscf (million standard cubic feet) to 3,407,592 mmscf. and electricity sales in indonesia increased by an average of 6.24% per year. the most widely used electricity consumption sector is the household sector with average consumption from 2007–2016 of 69.313 gwh (giga watt hour). in order to overcome energy problems in indonesia, energy conservation is needed in various layers, both from the management aspect of energy management and from among the community. in addition, there is also a need for low interest rate economic policies and stable exchange rates to encourage energy investment in order to increase crude oil production and counteract the negative impacts of rising world oil prices that lead to a decline in energy supply. in the long run, efforts should be made to shift energy use from unrenewable resources to renewable energy use, such as water, wind, biomass, biodiesel, biogas and other sustainable energy sources. 7. acknowledgments the first author would like to thank faculty of economics and business, airlangga university's for the support in this research. the second author thanked indonesia endowment fund for education (lpdp), the state islamic university of sharif hidayatullah jakarta, and suryakancana university for their support during the study. references anastacio, j.a.r. (2017), economic growth, co2 emissions and electric consumption: is there an environmental kuznets curve? an empirical study for north america countries. international journal of energy economics and policy, 7(2), 65-71. apostolakis, b.e. (1990), energy capital substitutability complementarity. energy economics, 12, 48-58. aydin, g. (2015), the modeling and projection of primary energy consumption by the sources. energy sources part b, 10, 67-74. dargay, j., gately, d., sommer, m. (2007), vehicle ownership and income growth, worldwide: 1960-2030. energy journal, 28, 143-170. devereux, m.b., lane, p.r. (2003), understanding bilateral exchange rate volatility. journal of international economics, 60(1), 109-132. diputra, e.m., jungho, b. (2018), is growth good or bad for the environment in indonesia? international journal of energy economics and policy, 8(1), 1-4. dudin, m.n., frolova, e.e., kucherenko, p.a., vernikov, v.a., voykova, n.a. (2016), china in innovative development of alternative energy advanced industrial technologies. international journal of energy economics and policy, 6(3), 537-541. fotourehchi, z. (2017), renewable energy consumption and economic growth: a case study for developing countries. international journal of energy economics and policy, 7(2), 61-64. hakam, d.f., asekomeh, a.o. (2018), gas monetisation intricacies: evidence from indonesia. international journal of energy economics and policy, 8(2), 174-181. harris, t.r. (2017), incorporating risk in analysis of tax policies for solar power investments. international journal of energy economics and policy, 7(6), 112-118. jul, r.m. (2014), the adverse effects of fossil-fuel subsidies in indonesia. dissertation, master of philosophy in economics department of economics university of oslo. kim, m.h., yoo, s.h. (2016), coal consumption and economic growth in indonesia. energy sources, part b: economics, planning, and policy, 11(6), 547-552. lee, c.c., chang, c.p. (2008), energy consumption and economic growth in asian economies: a more comprehensive analysis using panel data. resource and energy economics, 30, 50-65. liddle, b., lung, s. (2013), the long-run causal relationship between transport energy consumption and gdp: evidence from heterogeneous panel methods robust to cross-sectional dependence. economics letters, 121, 524-527. moremadi, i., yadollah, s. (2018), planning for investment in energy innovation: developing an analytical tool to explore the impact of knowledge flow. international journal of energy economics and policy, 8(2), 7-19. nor, m.i., masron, t.a. (2018), do the global oil price shocks affect somalia’s unregulated exchange rate volatility? international journal of energy economics and policy, 8(2), 154-161. sari, r., soytas, u. (2007), the growth of income and energy consumption in six developing countries. energy policy, 35, 889-898. zambrano-monserrate, m.a., valverde-bajana, i., aguilar-bohorquez, j., mendoza-jimenez, m.j. (2016), relationship between economic growth and environmental degradation: is there evidence of an environmental kuznets curve for brazil? international journal of energy economics and policy, 6(2), 208-216. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. . international journal of energy economics and policy | vol 8 • issue 1 • 2018 195 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(1), 195-202. carbon emissions and economic growth in south africa: a quantile regresison analysis b. mapapu1, andrew phiri2* 1department of economics, faculty of business and economic studies, nelson mandela metropolitan university, port elizabeth, south africa, 2department of economics, faculty of business and economic studies, nelson mandela metropolitan university, port elizabeth, south africa. *email: phiricandrew@gmail.com abstract of recent carbon emissions have become an increasing concern for economies worldwide. in this study we investigate the relationship between carbon emissions and economic growth for the south african economy, one of the largest emitters of carbon dioxide worldwide. we employ the quantile regression methodology which is applied to annual data covering a period of 1970–2014. our empirical results indicate that very low levels of carbon emissions are most beneficial towards economic growth. our results thus encourage policymakers to continue to embark on energy efficiency programmes which specifically target lower levels of carbon pollution. keywords: carbon emissions, economic growth, environmental kuznets curve, south africa, quantile regressions jel classifications: c13; c32; c51; q43; q53. 1. introduction following the seminal works of grossman and krueger (1991; 1995) much empirical attention has been directed towards examining the relationship between environmental degradation and economic development, a phenomenon popularly dubbed as the environmental kuznets curve relationship or hypothesis. theoretically, the environmental kuznets curve depicts that during the early stages of economic development, environmental degradation is a catalyst for improved economic development only up to certain level of development of which afterwards it begins to exert an adverse effect. regardless of this hypothesized nonlinear, inverted u-shaped relationship between environmental degradation and economic development a bulk of the existing empirical literature has relied on linear econometric methodologies in examining the relationship between carbon emissions and economic growth ang (2007), ozturk and acaravci (2010), esteve and tamarit (2012) and cerdeira-bento and moutinho (2015), shahbaz et al. (2015), alam et al. (2016), tang et al. (2016). the danger with this approach is that inaccurate conclusions concerning the environmental kuznets curve may have been deduced in the previous literature. in our study, we examine the relationship between carbon emissions and economic growth for the south african economy over a period of 1971–2013. in deviating from the norm of linear estimation techniques, we choose the quantile regressions methodology as introduced by koenker and bassett (1978) as our mode of empirical investigation. we favour this technique since it examines the effects of regressor variables on the regress and at different quantile distributions. in adopting this method we are offered the unique advantage of being able to examine the effects of varying levels of carbon emissions on economic growth hence increasing the scope of policy relevance derived from our study. this becomes particularly significant towards an emerging economy like south africa, whose heavy reliance on coal-based energy production has placed the country as the african continents number one carbon emitter. knowing what effects carbon emissions exerts on economic growth is directly crucial towards south african policymakers as they are currently engaged in energy efficiency strategies aimed at reducing carbon pollution. empirically, our study further takes into consideration the fact that a majority of the existing empirical studies have been criticized on the premise of including both carbon emissions and energy/ mapapu and phiri: carbon emissions and economic growth in south africa: a quantile regression analysis international journal of energy economics and policy | vol 8 • issue 1 • 2018196 electricity consumption as mutual regressors of economic growth hence violating the classical assumption of orthogonality between the regressors (burnett et al., 2013). as a simple remedy to this multicollinearity problem, burnett et al. (2013) advises researchers to exclude energy/electricity consumption from the estimated growth regressions and solely include carbon emissions and other growth determinants in the estimated regressions. we note that previous south african case studies have not followed in pursuit of this empirical rule menyah and wolde-rufael (2010), kohler (2013), shahbaz et al. (2013a), khobai and le roux (2017) hence providing a strong motivation for a fresh perspective on the subject matter. in our study, we take advantage of this empirical hiatus and in doing so, make a novel contribution to the literature. having provided the background and motivation to the study, the rest of the manuscript is arranged as follows. the following section of the paper presents the review of the previous literature whilst the third section outlines the quantile regressions methodology used in the empirical study. the description of the time series data as well as the empirical findings are presented in the fourth section of the paper. the paper is then concluded in the fifth section of the paper in the form of policy implications. 2. a review of the assocaited literature theoretically, antweiler et al. (2001), coxhead (2003) and ang et al. (2007) all postulate that the assumed relationship between environmental deregulation/pollution and economic development (i.e., the environmental kuznets curve) can be explained by three factors. firstly, there is the scale effect which occurs as pollution increases with the size of the economy. secondly, there is the composition effect which refers to the change in the production structure of an economy from agricultural based to industry and service based which results in the reallocation of resources. lastly, there is the production techniques which indicates that improved technology in production may reduce the amount of pollutant emissions per unit of production. empirically, a vast majority of the existing academic literature concerned with examining the environmental kuznets curve, have opted to investigate the relationship between carbon emissions and economic growth as a means of empirically examining the environmental kuznets curve for different economies, using different time periods as well as a variety of econometric tools. in providing a review of the associated literature, we conveniently generalize the studies into two classifications of empirical works, namely, studies who focus on developed or industrialized countries and those studies who focus on developing or emerging countries. the first group of studies, which are those studies which have examined the relationship between carbon emissions and economic growth for developed or industrialized economies include the works of ang (2007) for france; ozturk and acaravci (2010) for turkey; menyah and wolde-rufael (2010a) for the us; esteve and tamarit (2012) for spain as well as cerdeira-bento and moutinho (2015) for italy. whilst the studies of ang (2007); menyah and wolde-rufael (2010a) and esteve and tamarit (2012) advocate for a positive relationship between the time series, the works of ozturk and acaravci (2010) and cerdeira-bento and moutinho (2015) both find a negative emissions-growth relationship. it should be noted that cording to theory it is more probable to find a negative relationship between emissions and economic growth since industrialized economies, are by definition, countries who are at advanced stages of development. given the mixed results obtained from the review of developed or industrialized economies, the debate concerning these countries remains open to further deliberation. on the other hand the papers published by menyah and wolderufael (2010b) for the south africa, kohler (2013) for south africa; shahbaz et al. (2012) for south africa for pakistan; shahbaz et al. (2013) for south africa; shahbaz et al. (2013) for indonesia; shahbaz et al. (2013) for romania; farhani et al. (2014) for tunisia; begum et al. (2015) for malaysia; rafindadi (2016) for nigeria; khobai and le roux (2017) and ahmad et al. (2017) for croatia suffice as those concerned with examining the emissions-growth relationship for developing countries, with the studies of kohler (2013), shahbaz et al. (2013b), khobai and le roux (2017) exclusively focusing on the south african economy. in summarizing these studies we note that whilst the works of shahbaz et al. (2013c), rafindadi (2016) and khobai and le roux (2017) advocate for a positive emissions-growth relationship, however, the remaining reviewed studies for developing countries mutually find a positive emissions-growth relations at low levels which turns negative at higher levels. these later group of studies are able to capture a nonlinear carbon emissions-growth relationship by including a squared term on the gdp variable which is intended to capture possibly nonlinear dynamics. however, as pointed out by narayan et al. (2016) including both gdp and the squared term of gdp in the same regression would make the econometric model to suffer from the issue of multicollinearity. in contrast, the quantile regressions methodology applied in our current study naturally captures any nonlinearity hence the inclusion of the “squared carbon emissions” term is not necessary and hence circumvents the issue of multicollinearity. nevertheless, a comprehensive summary of the reviewed studies are presented in table 1. 3. methodology our baseline empirical model assumes the following functional form: yt = β0+βixt+et (1) where yt is the economic growth rates, xt is a set of explanatory variables, β’s represent the associated regression coefficients and et is a well behaved error term. our main explanatory variable is carbon emissions (co2t) and the remainder of the conditioning variables are those primarily dictated by theoretical considerations based on the literature. for instance, our first conditioning variable is the investment variable (invt) which, according to classical theory is assumed to the engine of economic growth and is hence positive related to economic growth. our second conditioning variable is the inflation rate (inft) and based on conventional growth theory is assumed to hinder economic growth and hence empirically exhibit a negative effect on economic growth. our mapapu and phiri: carbon emissions and economic growth in south africa: a quantile regression analysis international journal of energy economics and policy | vol 8 • issue 1 • 2018 197 third variable is the employment variable (empt), which according to growth theory is assumed to be positively correlated with economic growth. our last conditioning variables is the terms of trade variable (tott), which represents international trade and the open economy which is assumed to exert a positive influence on economic growth. collectively, our baseline empirical specification can be expounded as follows: yt = β0+β1co2t+β2invt+β3inft+β4empt+β5tott+et (2) from regression (1) in conjunction with regression (2), the conventional ols estimates would be obtained by finding the vector βi that minimizes the sum of squares residual i.e.,, min [ ( ) ' β β β ∈ ∈ ≥ −∑r i {i:y x } i ik i i y x 2 (3) in contrast, the quantile regression approach adopted in our study is a generalization of the median regression analysis to other quantiles. in particular, the mean average deviations (mad) estimator can be computed as: min [ / ' β β β ∈ ∈ ≥ −∑r i {i:y x } i ik i i y x /] 2 (4) of which the mad estimate depicted in regression (4) can be re-specified as: min [ / ( ) / ' ' β β β β β ∈ ∈ ≥ ∈ ≥ − − −∑ ∑r i {i:y x } i i i {i:y x } i ik i i i iy x /+ y xτ τ1 //] (5) where τ represents the τth quantile and is specifically set at 0.5 for the mad estimator. the general intuition of the quantile regression estimates is to use varying values of τ bound between 0 and 1 hence yielding the regression quantiles for varying distributions of gdp growth given the set of explanatory variables contained in the vector x. in our study we opt to use 9 quantiles with intervals of 0.1 between the quantiles i.e., τ = {0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8 and 0.9}. 4. data and empirical results 4.1. data description the empirical data used in our study has been collected from the world bank online database and has been collected on an annual basis for a period ranging from 1970 to 2014. our dataset particularly consist of economic growth (gdp), carbon emissions (co2), cpi inflation (inf), gross domestic investment (inv), and terms of trade (tot) variables. tables 2 and 3, present the descriptive statistics and the correlation matrices of the time series whereas figure 1 presents a time series plots of the variables. of particular interest from the descriptive statistics reported in table 2 are the low gdp average of 2.63% which we note is well below the 6 percent target growth rate currently being embarked by policymakers. we also note that the average inflation rate over our study period is 9.62, a figure which is above the 3–6% as stipulated by the south african reserve bank. moreover, the low employment average of 1.75 is inherent characteristic of the south african economy, which is well known for her labour market deficiencies. table 1: summary of literature review author (s) country/countries time period methodology results ang (2007) france 1960–2000 vecm positive relationship between co2 and gdp ozturk and acaravci (2010) turkey 1965–005 ardl negative relationship between co2 and gdp menyah and wolde-rufael (2010a) us 1960–2007 var positive relationship between co2 and gdp menyah and wolde-rufael (2010b) south africa 1965–2007 ardl positive relationship between co2 and gdp shahbaz et al. (2012) pakistan 1971–2009 ardl positive relationship between co2 and gdp at low levels which turns negative at higher levels kohler (2013) south africa 1960–2009 vecm and ardl positive relationship between co2 and gdp at low levels which turns negative at higher levels shahbaz et al. (2013b) south africa 1965–2008 ardl positive relationship between co2 and gdp at low levels which turns negative at higher levels shahbaz et al. (2013c) indonesia 1975–2011 vecm and ardl positive relationship between co2 and gdp shahbaz et al. (2013a) romania 1980–2010 ardl positive relationship between co2 and gdp at low levels which turns negative at higher levels farhani et al. (2014) tunisia 1971–2008 ardl positive relationship between co2 and gdp at low levels which turns negative at higher levels cerdeira-bento and moutinho (2015) italy 1960–2011 ardl negative relationship between co2 and gdp begum et al. (2015) malaysia 1970–2009 ardl insignificant relationship between co2 and gdp at low levels which turns negative at higher levels rafindadi (2016) nigeria 1971–2011 vecm and ardl positive relationship between co2 and gdp khobai and le roux (2017) south africa 1971–2013 \vecm positive relationship between co2 and gdp ahmad et al. (2017) croatia 1992–2011 ardl positive relationship between co2 and gdp at low levels which turns negative at higher levels ardl: autoregressive distributive lag model, vecm: vector error correction model, var: vector autoregressive model mapapu and phiri: carbon emissions and economic growth in south africa: a quantile regression analysis international journal of energy economics and policy | vol 8 • issue 1 • 2018198 on the other end of the spectrum, the correlation matrix as depicted in figure 2, tends to depict correlations which concur with those predicted by conventional growth theory. for instance, we note positive employment-growth and trade-growth relations which adheres to traditional economic theory. similarly, the negative inflation-growth and emissions-growth relations are expected. however, the negative correlation established between investment and growth is a rather peculiar observation since investment is commonly perceived as the engine of economic growth. nevertheless, this negative investment-growth correlation is not uncommon in the literature as recently advocated for in the study of phiri (2017). 4.2. empirical estimates in initiating our empirical analysis, we first provide the ols estimates of the regression with the results being reported in table 4. as can be observed, the coefficient on the carbon emissions variable produces a positive estimate which is statistically significant at all critical levels. note that this result is in line with that presented in shahbaz et al. (2013), rafindadi (2016) and khobai and le roux (2017). also note that the coefficient on the inflation variable is negative and highly significant as expected and this particular finding concurs with that presented in hodge (2006) for similar south african data. we further observe a positive coefficient estimate on the employment variable thus providing evidence of a positive employment-growth relationship as predicted by convention theory. on the other end of the spectrum, we note insignificant coefficients on both the investment and terms of trade variables which is contrary to conventional theory and yet concurs with that presented in the study of phiri (2017) for south african data. our reported results are reinforced by the partialled plots of gdp on the regressors as depicted in figure 2. however, as previously mentioned, the ols estimates have been heavily criticized for constraining the coefficient on the regressand variables to be the same across different quantiles. therefore, we proceed to present the empirical estimates of the quantile regressions which have been performed for 9 quantiles (i.e., 10th, 20th, 30th, 40th, 50th, 60th, 70th, 80th and 90th quantiles) with the results been reported in table 5. as can be observed, the coefficient estimates for the carbon dioxide variable are positive across all quantiles and are significant at a critical level of at least 5%. however, the positive effect of carbon emissions on gdp are amplified at the tail ends of distribution (i.e., very low and very high levels of carbon emissions) with the coefficients reducing as one moves from the extreme quantile (i.e., 10th and 90th quantiles) towards the centre quantile (50th quantile) which incidentally happens to be the mad estimate. on the other hand, the coefficients on the inflation variable are negative and significant at all quantile levels with the negative effects of the inflation variable being more pronounced at lower quantiles and the coefficients becoming lower as one moves don the quantile levels hence signifying a diminishing negative effect of inflation on economic growth as one moves along the quantile levels. concerning the employment variable we note a positive coefficient on the employment variable across all estimated quantiles which are statistically significant at all critical levels with the marginal positive effect of employment on economic growth diminishing as one moves up the different quantile levels. in lastly observing the coefficients obtained for the investment and terms of trade variables we note that all quantile estimates produce negative table 2: descriptive statistics ??? gdp co2 inf inv emp tot mean 2.63 8.58 9.62 21.90 1.75 1.79 median 2.95 8.70 9.37 20.75 1.30 2.10 maximum 6.60 10.04 18.65 32.10 8.50 20.00 minimum −2.10 6.65 1.39 15.20 −4.30 −16.20 std. dev. 2.27 0.93 4.21 5.06 2.68 6.44 skewness −0.43 -0.28 0.14 0.40 0.28 -0.01 kurtosis 2.35 2.01 2.01 1.85 3.15 4.15 jarque bera 2.15 2.38 1.94 3.61 0.62 2.44 probability 0.34 0.30 0.38 0.16 0.73 0.30 observations 44 44 44 44 44 44 table 3: correlation matrix gdp co2 inf inv emp tot gdp 1 co2 −0.20 1 inf −0.39 0.11 1 inv −0.03 −0.35 0.43 1 emp 0.64 −0.25 0.18 0.37 1 tot 0.17 −0.08 −0.14 −0.01 0.09 1 table 4: ols estimates variable coefficient standard error t-stat p value co2 0.45 0.12 3.85 0.00*** inf −0.28 0.05 −5.59 0.00*** inv 0.01 0.05 0.28 0.78 emp 0.66 0.10 6.31 0.00*** tot 0.01 0.03 0.52 0.60 ***, **, * represent 1%, 5% and 10% significance levels, respectively table 5: quantile regression estimation results tau co2 inf inv emp tot coefficient p value coefficient p value coefficient p value coefficient p value coefficient p value 0.1 0.52 0.00*** −0.30 0.00*** −0.09 0.29 0.79 0.00*** 0.03 0.62 0.2 0.53 0.02** −0.31 0.00*** −0.08 0.47 0.72 0.00*** 0.04 0.54 0.3 0.51 0.00*** −0.22 0.00*** −0.08 0.43 0.72 0.00*** 0.01 0.95 0.4 0.34 0.04* −0.25 0.00*** 0.04 0.51 0.63 0.00*** −0.05 0.30 0.5 0.36 0.02** −0.28 0.00*** 0.07 0.29 0.64 0.00*** 0.03 0.59 0.6 0.41 0.01** −0.29 0.00*** 0.06 0.33 0.64 0.00*** 0.03 0.66 0.7 0.44 0.00*** −0.25 0.01** 0.04 0.49 0.67 0.00*** 0.02 0.71 0.8 0.43 0.00*** −0.22 0.06* 0.03 0.51 0.68 0.00*** 0.05 0.35 0.9 0.43 0.00*** −0.16 0.00*** 0.06 0.39 0.48 0.00*** 0.05 0.34 ***, **, * represent 1%, 5% and 10% significance levels, respectively mapapu and phiri: carbon emissions and economic growth in south africa: a quantile regression analysis international journal of energy economics and policy | vol 8 • issue 1 • 2018 199 and insignificant coefficient estimates for the former variable while producing positive and insignificant estimates for the later variable. note that these results closely emulate those obtained from the previous ols estimates. the associated quantile process estimates are presented in figure 3. 4.3. residual diagnostics as a final step in our empirical analysis, we implement diagnostic test to our estimated regression. in particular, we implement two diagnostic tests, namely, ramsey’s reset test for model misspecification and jarque-bera (j-b) goodness of fit test. the results of these diagnostic tests are reported in table 6 and as can be seen our empirical estimates contain no specification errors and are normally distributed. we thus consider our obtained quantile regression estimates to be plausible. 5. conclusion the primary objective of this current study has been to evaluate the relationship between carbon emissions and economic growth in south africa using annual data collected over a 44 years period spanning from 1970 to 2013. in differing from pervious empirical studies, we employ the quantile regression approach which provides the advantage of assuming parameter heterogeneity in analysing the effects of carbon emissions on economic growth. moreover, we circumvent the possibility of multicollinearity within the estimated regression estimates by not including energy/ electricity consumption alongside carbon emissions as regressors in the estimated growth model. our obtained empirical results confirm positive relationship between carbon emissions and economic growth, albeit, the positive effect being most magnified at extremely low or extremely high values and diminishing as one moves to centre values. we consider the overall positive relationship to be expected since south africa is well known for her dependency on coal usage in producing energy for productive and consumption usage within different sectors of the economy. hence given the country’s current figure 1: time series plots of the variables table 6: diagnostic tests on estimated quantile regression test statistic p value decision ramsey reset test 4.31 0.11 no specification error jarque-bera (j-b) 2.28 0.31 normal distributed regression mapapu and phiri: carbon emissions and economic growth in south africa: a quantile regression analysis international journal of energy economics and policy | vol 8 • issue 1 • 2018200 stage/level of economic development increased electricity usage in south africa would be accompanied with increased carbon emission as well as improved economic growth. however, our quantile estimates indicate that very low levels of carbon emissions are most beneficial for economic development through improved economic growth rates. in effect our study bears important policy implication since policymakers have been embarking on energy efficiency programmes over the last decade and a half or so. part and parcel of these energy efficiency programmes is to shift from coal-based energy production schemes to renewable energy sources which would exert a positive environmental effect in terms of greenhouse figure 2: gdp versus other variables mapapu and phiri: carbon emissions and economic growth in south africa: a quantile regression analysis international journal of energy economics and policy | vol 8 • issue 1 • 2018 201 emissions. from a policy perspective, our results imply it would be in government’s best interest to keep carbon emissions as low as possible to fulfil the macroeconomic policy objectives of improving both environmental degradation and long-run economic growth. based on our study, government’s current pursuit of energy programmes and strategies though increased renewable energy sources is thoroughly encouraged. references ahmad, n., du, l., lu, j., wang, j., li, h., hashmi, m. (2017), modelling the co2 emissions and economic growth in croatia. energy, 123(15), 164-172. alam, m.m., murad, m.w., noman, a.h.m., ozturk, i. (2016), relationships among carbon emissions, economic growth, energy consumption and population growth: testing environmental kuznets curve hypothesis for brazil, china, india and indonesia. ecological indicators, 70, 466-479. ang, j. (2007), co2 emissions, energy consumption, and output in france. energy policy, 35, 4772-4778. antweiler, w., brian, c., scott, t. (2001), is free trade good for the environment? american economic review, 91(4), 877-908. begum, r., sohag, k., abdullah, s., jaafar, m. (2015), co2 emissions, energy consumption, economic and population growth in malaysia. renewable and sustainable energy reviews, 41, 594-601. burnett, w., bergstrom, j., wetzstein, m. (2013), carbon dioxide emission and economic growth in the u.s. journal of policy modeling, 35, 1014-1028. cerdeira-bento, j., moutinho, v. (2015), co2 emissions, non-renewable and renewable electricity production, economic growth, and international trade in italy. renewable and sustainable energy reviews, 52, 142-155. coxhead, i. (2003), development and the environment in asia. asian pacific economic literature, 17(1), 22-54. esteve, v., tamarit, c. (2012), is there an environmental kuznets curve for spain? fresh evidence from old data. economic modelling, 29, 2696-2703. farhani, s., chaibi, a., rault, c. (2014), co2 emissions, output, energy consumption and trade in tunisia. economic modelling, 38(c), 426-434. grossman, g., krueger, a. (1991), environmental impacts of north figure 3: quantile process estimates mapapu and phiri: carbon emissions and economic growth in south africa: a quantile regression analysis international journal of energy economics and policy | vol 8 • issue 1 • 2018202 american free trade agreement. national bureau of economic analysis, technical report. grossman, g., krueger, a. (1995), economic growth and the environment? quarterly journal of economics, 110(2), 353-377. hodge, d. (2006), inflation and growth in south africa. cambridge journal of economics, 30, 163-180. khobai, h., le roux, p. (2017), the relationship between energy consumption, economic growth and carbon dioxide emission: the case of south africa. international journal of energy economics and policy, 7(3), 102-109. koenker, r., bassett, g. (1978), regression quantiles. econometrica, 46(1), 33-50. kohler, m. (2013), co2 emissions, energy consumption, income and foreign trade: a south african perspective. energy policy, 63, 1042-1050. menyah, k., wolde-rufael, y. (2010a), co2 emissions, nuclear energy, renewable energy and economic growth in the us. energy policy, 38(6), 2911-2915. menyah, k., wolde-rufael, y. (2010b), energy consumption, pollutant emissions and economic growth in south africa. energy economics, 32, 1374-1382. narayan, p., saboori, b., soleymani, a. (2016), economic growth and carbon emissions. economic modelling, 53, 388-397. ozturk, i., acaravci, a. (2010), co2 emissions, energy consumption and economic growth in turkey. renewable and sustainable energy reviews, 14, 3220-3225. phiri, a. (2017), does military spending nonlinearly affect economic growth? defence and peace economics. 28, 1-14. rafindadi, a. (2016), does the need for economic growth influence energy consumption and co2 emissions in nigeria? evidence from the innovation accounting test. renewable and sustainable energy reviews, 62, 1209-1225. shahbaz, m., dube, s., ozturk, i., jalil, a. (2015), testing the environmental kuznets curve hypothesis in portugal. international journal of energy economics and policy, 5(2), 475-481. shahbaz, m., hye, q., tiwari, a., leitao, n. (2013c), economic growth, energy consumption, financial development, international trade and co2 emissions in indonesia. renewable and sustainable energy reviews, 25, 109-121. shahbaz, m., lean, h., shabbir, m. (2012), environmental kuznets curve hypothesis in pakistan: cointegration and granger causality. renewable and sustainable energy reviews, 16, 2947-2953. shahbaz, m., mutascu, m., azim, p. (2013a), environmental kuznets curve in romania and the role of energy consumption. renewable and sustainable energy reviews, 18, 165-173. shahbaz, m., tiwari, a., nasir, m. (2013b), the effects of financial development, economic growth, coal consumption and trade openness on co2 emissions in south africa. energy policy, 61, 1452-1459. tang, c.f., tan, b.w., ozturk, i. (2016). energy consumption and economic growth in vietnam. renewable and sustainable energy reviews, 54, 1506-1514. ole_link1 . international journal of energy economics and policy | vol 8 • issue 2 • 2018 196 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(2), 196-204. a note on revenue distribution patterns and rent-seeking incentive elkhan richard sadik-zada1,2*, wilhelm loewenstein1,3 1institute of development research and development policy, ruhr-universität bochum, germany 2faculty of economics, cambridge university, uk 3south african-german centre of development research, university of the western-cape, south africa *email: ers61@cam.ac.uk abstract this paper presents a simple model of rent-seeking incentive to explain the emergence and dominance of the rapacious rent-seeking policies in a number of oil abundant developing and transition economies. the hubbertian distribution of the commodity exports over time, the magnitude of these revenues, and the availability of offshore havens for the illicitly appropriated rent explain the shift from productive public policies to rapacious rent-seeking. in addition, we show that the existence of the well-functioning democratic institutions prior to the revenue boom precludes the emergence of rapacious rent-seeking institutions due to prohibitively high costs of rent-seeking. the paper complements the existing literature by delivering a novel theoretical rationale for the predisposition of the oil-rich countries to the resource curse. keywords: rent-seeking, illicit appropriation, hubbert curve, point-source resources, institutions, offshore havens jel classifications: d72, d73, l72, o13 "a rogue once stolen his 100 000 thalers can live the rest of his life as an honest man." — georg christoph lichtenberg — 1. different resource types and rent-seeking in april 2003 jonathan isham from middlebury college together with michael woolcock and lant pritchett from harvard university and gwen busby from cornell university published a survey on the nexus between the structure of the natural resource exports and the resource curse. the authors did not just detect the causal chain that runs from the relative share of natural resource exports to the choice of development strategies and economic growth but differentiated between different types of natural resource revenues. isham et al. (2003) wanted to find out whether different type resources have diverging effects on economic growth and found out that “point-source” resources such as oil increase the probability of the resource curse. according to them “pointsource” resources affect economic growth negatively mainly over inferior institutional quality. the reason for a higher vulnerability of the countries which are abundant in oil and gas is explained by a higher degree of the spatial concentration of the export revenues and a more lootable nature of such resources, i.e. they can be easily appropriated by the ruling politicians.1 van der ploeg (2010. p. 2f.) in his model of “rapacious resource depletion” generalizes the problems related to extractive industries mentioned in isham et al. (2003) as the problems caused by the insecurity of property rights. the investigation conducted by isham et al. (2003) was nothing but a revival of the basic principles of the export base theory that suggests that plantation agriculture was less conductive to economic growth than the peasant economy because of the weaker linkage effects to the rest of the economy. in the resource base theory, baldwin (1956) concentrates mainly on the growth effect of different agricultural staples and explains the differences in lacking linkage effects and the enclave character of certain types of agricultural production. according 1 the term “point-source resources” was introduced by isham et al. (2003). for more on the classification of the resources including “point-source resources” see bavinck et al. (2014). p. 57 and mavrotas et al. (2011). p. 124-125. sadik-zada and loewenstein: a note on revenue distribution patterns and rent-seeking incentive international journal of energy economics and policy | vol 8 • issue 2 • 2018197 to them capital intensive staples like cotton and minerals contribute less to economic growth and development because of their lacking linkages with the domestic economy and predominantly enclave character that enables the transfer of the rent mainly to overseas rather than investing in the homeland. lewis (1978) offered an alternative explanation for the relatively weak growth effects of the nineteenth century plantocracy in the southern states of the usa and similar colonial tropical regions. he argued that cheap labor supply and especially slave labor reduced redistribution of income and did not have the effect that could be observed in temperate frontier regions confronting wage pressure and better redistribution. boschini et al. (2007) demonstrate that the effect of resources is not determined by resource endowments alone, but rather by the interaction between the type of resources that a country possesses, and the quality of its institutions. further, the authors negate their institutional hypothesis during their discussion on the appropriation of a resource and show that resources that are very valuable, that can be stored, easily transported and sold, are, for obvious reasons, more attractive to anyone interested in short-term illicit gains. they find out that resources such as petroleum, diamonds or precious metals are potentially more problematic than agricultural products. this is a latent negation of their institutions hypothesis because they discover that the source of the institutional failure is in the type of the resources: if they are very valuable and can be appropriated in the short run, then the institutions tend to deteriorate. institutions do matter but the primary reason is the type of the resource. we agree with the above mentioned literature whereby we tend more to the line of argumentation in lewis (1978) expressing the importance of geographical determinants in combination with institutions whereby we accept the primacy of the features of the resources (geographic, natural and technical aspects) over the pure institutions argument. following this line, we suggest an alternative theoretical explanation for the perverse effects of the oil abundance empirically detected by isham et al. (2003). it is not just the spatial and/or sectoral concentration of the resources in one sector and the ability to appropriate these resources. we argue that the large magnitude and positive skew of the oil revenues over time is one of the reasons of the so called resource curse resulting in lacking fiscal linkages, capital flight and strategic behavior of the incumbent government translating itself into low growth rates. this does not mean that these are the only or the most important causes which contain the positive growth effects of oil revenues on the manufacturing sector but at least from a theoretical point of view they seem to be fundamental ones. of course, the theory of isham et al. (2003) makes sense regarding spatial concentration leading to enclave extractive industries. in addition, most of the developing and in all the oil-exporting economies in transition, oil revenues flow directly into the state budget. if one isolates the non-oil sectors of the economy from the oil sector, the output of the oil sector would not be affected significantly in a number of developing and transition economies. nevertheless, a contrary argument from our side is the question of why the cocoa, rice, aluminum or flower production do not have the analogous adverse effects on rent-seeking and economic growth. the arguments in isham et al. (2003) are more related to the backward and forward linkage effects of the oil and gas industries. these sectors are probably less integrated in the domestic economy than non-enclave agriculture. if so then it is a theoretical approach explaining rather production linkage effects than rapacious rent-seeking2. of course production linkages encompassing both backward and forward linkages in the enclave industries could be a possible explanation of the economic failure of the oil-abundant countries (hirschman, 2013). nonetheless, especially in the case of the petroleum abundant countries production and consumption linkages are less important than fiscal linkages (morris et al., 2011. p. 19-21). that is why the theoretical explanation in isham et al. (2003) can only be a partial explanation of the resource curse or sluggish economic growth in the context of petroleum rich countries as production linkages do not capture the major, i.e. the fiscal aspect, of the oil-based economic development. the reason why oil boom is associated with inferior institutions much more than with cocoa, rice or zinc is not the chemical formula of oil, and not the production function mainly reliant on imported technology but the large magnitude of these revenues and their positively skewed revenue generation pattern over time. an oil bonanza even in the years of low oil prices yields much more revenue than other revenue sources in a number of oil abundant countries. especially in the first decade after commensuration of oil explorations and exports petroleum revenues create a huge intersectoral misbalance, especially in the countries with initially low gdp. for example, in azerbaijan 1991 oil exports constituted only 6,5% of gdp, in 2006, the year of big oil exports after opening of the baku-tbilisi-ceyhan pipeline, this number jumped to 41,7%. oil revenues constituted just 0,1% of the iraqi gdp in 1970 and in 1974 this number was 40%. oil exploitation and also oil price fluctuations, for instance, in 1979 after iranian revolution change the intersectoral revenue structure significantly. empirical observations show that in most of the oil exporting developing countries this shift towards the oil sector has a durable character and is not a temporary phenomenon. the asymmetric flow of the petrodollars whereby on the one side we have a tiny non-oil sector with labor surplus economy and on the other hand a highly capital-intensive huge oil sector changes the relative importance of the economic sectors and as shall be shown later, also the incentive structure of the ruling elites too. hydrocarbons cannot be recycled and they vanish in the process of consumption or production. it is a nonrenewable resource which is available only for a limited time span. studies on the oil decline curve analysis initiated in arps (1945) and generalized in hubbert peak theory considering both discovered oil deposits and future discoveries suggested in hubbert (1956) show that especially the crude oil production quantity over time (both in singular and multiple oil fields cases) approximate a bell curve (figure 1). oil reserves reach relatively quickly peak production and as soon as the extraction has reached its peak, the oil extraction shifts relatively fast to the phase of exponential decline3. in the case of other minerals and even gas the decline 2 the terms rapacious rent-seeking, corruption, and grabbing are used interchangeably in the discussion here. 3 for the difference between decline curves of oil and gas see bentley (2002) sadik-zada and loewenstein: a note on revenue distribution patterns and rent-seeking incentive international journal of energy economics and policy | vol 8 • issue 2 • 2018 198 rate of resource extraction after the peak is much lower than in the case of oil (höök, 2009. p. 26). despite criticism the hubbert theory seems to hold for the most large oil-producing regions on the planet (brandt, 2007). in the next subsections we shall try to analyze the impact of the asymmetric hubbertian distribution model of oil production (and consequent revenue generation) on the incentive structure of the politically powerful groups. as we conduct this analysis in the framework of an infinite horizon, in the next subsection we shall discuss the theoretical rationale behind the infinite time horizon in the microeconomic modeling. 2. the microeconomic foundations of the infinite horizon in microeconomics there are models with finitely-lived agents and models that have an infinite planning horizon. despite the fact that individuals do not live forever, modeling with an assumption of infinite horizon has convincing microeconomic foundations. the first justification for the infinite planning horizon is the so-called poisson death model (pdm) and the second one is the so-called bequest motive rising from intergenerational altruism. in pdm, the utility maximization of a finitely living individual converges with the maximization model identical to that in the model with infinitely living households. despite wide applications in applied social science and epidemiology the central assumption of pdm, the assumption of the constant probability of death, v, for each year of life, is not realistic: death probability is a function of age. this is why it is not straightforward to assume v to be constant (acemoglu, 2009. p. 156f). the second and more persuasive explanation, the so-called bequest motive or the model of intergenerational altruism assumes that the individuals live for a finite time and care about the utility of their offsprings and keep in mind that in turn their and brandt (2006). for the discussion on the hyperbolic and harmonic decline patterns of oil resources see höök (2008. p. 30-31). offspring will care about the utility of their offspring, and so on. thus the individual internalizes the utility of all future offspring infinitely. this utility mechanism explains dynastic preferences whereby decision makers act as if they had an infinite planning horizon. 3. utility maximization of the state elite in this section we shall assume that the state elite maximizes its utility through maximization of its gross income (igross) which consists of legally determined fixed income fixti and illicit income var ti 4. fix ti is the legally determined salary of the head of the state and other elite members in period t. varti is illicitly appropriated rent seeking revenue in period t. we denote the sum of varti and fix ti as the gross income of the state elite in t, gross fix var t t ti =i +i . in the periods before the discovery of the oil reserves and the oil boom the economy consists of the manufacturing sector that operates under constant returns to scale and under conditions of perfect competition. output in the manufacturing sector equals ym and the tax rate imposed on the manufacturing output is τ. tax revenue generated in the manufacturing sector, (ymτ), is the only revenue source of the government. throughout the model we assume that tax revenue generated in the manufacturing sector is constant, e.g., ymτ does not change as a reaction to the changing behavior of the state elite and oil windfalls. this has no impact on the level of generality and simplifies the presentation5. the government has to cover constant expenditure, c . this is the total and minimized expenditure of the government and covers the basic needs of its citizens and payments for major state institutions for the maintenance of the political power and stability. if the incumbent government does not cover c then a regime change takes place. the next assumption and starting point of our analysis is that the roughly simplified hypothetical budget before discovery of oil fields and the beginning of oil exports is always balanced fixm(surplus/deficit = )c= y i 0τ⋅ − − 6. 4 the state elite is a small and politically dominant group of persons. the notion of the state elite could imply different social structures in different sociopolitical milieus. for example in eastern europe this could be relatives or friends of the head of the state, in the central asian countries, clan or family members, in some arab or african states, families and tribes3. nevertheless, the constitutive feature of all types of the state elite is their political dominance translating into economic power. werenfels (2004. p. 173-200) in the context of algeria labels these elites as a core elite having direct ties to presidency. abdelnasser (2004. p. 118-123) describes in the context of egypt the core elite as the first-circle technocrats, the president and major party politicians of the incumbent government. for higley and gunther (1992) elites are groups of persons shaping political outcomes in the most resource-rich organizations. the elites play a decisive role in the institutionalization of the distributive rules of the game and act as an active moment in the process of transformation (rustow, 1970. p. 355). 5 for the assessment of the sensitivity of the manufacturing sector see sadikzada (2016): 57-68. 6 we include ifix to the expenditure side due to the fact that it is being paid from the hypothesized state budget. figure 1: hubbert curve sadik-zada and loewenstein: a note on revenue distribution patterns and rent-seeking incentive international journal of energy economics and policy | vol 8 • issue 2 • 2018199 this implies that before the resource windfalls, tax revenue from the manufacturing sector is just enough for the necessary state expenditure. the elite due to a constrained financial latitude has to endure a balanced state budget by intruducing and maintaining an efficient revenue and expenditure management. this argument is in line with the latitude and voice proposition of albert hirschman (1963. p. 1984), one of the luminaries of development economics, who argued that lack of latitude, i.e., constrained financial leeway of the elite in our context “… brings powerful pressures for efficiency, quality performance, good maintenance habits, and so on. it thus substitutes for inadequately formed motivations and attitudes, which will be induced and generated the narrow-latitude task instead of presiding over it.” the regime change assumption if c is not covered was also mentioned by albert hirschman in “exit, voice, and loyalty,” a treatise on the social responsiveness on the public governance, whereby narrow-latitude tasks7 correspond with covering of c in our context, he writes: “narrow-latitude tasks will, if performed poorly and (ex hypothesi) disastrously, give rise to strong public concern and outcry – to voice.… a narrow-latitude task that, if neglected, is likely to give rapid rise to strong voice (the results of poor performance being intolerable)."8 under such circumstances the government has no possibility of illicit private appropriation from the hypothetical budget: illicit appropriation would cause a coup due to the uncovered basic needs of the population (τym −c−ifix −illicit appropriation<0). under such circumstances the state elite earn only ifix and has an infinite tenure.9 7 a narrow-latitude task is a task that has to be performed just right; otherwise there is a serious risk connected to public outrage and social unrest. one example from a different context is the example with the engine of an airplane. the producer has to produce a well-functioning engine; this is a minimum that is expected from an airplane producer. if this condition is not fulfilled, then protests are inevitable. cf. hirschman (1984. p. 99). 8 hirschman (1984). p. 100. 9 the assumption of infinite t enure c ould s ound a s b eing t oo unrealistic. nevertheless, if we take the countries with working (mature) democracy as an example, this assumption is not that unrealistic. let us take the case of a working democracy with two parties that form the government, e.g., the republican and democratic parties in the united states, the christian democratic union and social democratic parties in germany, the labour and conservative parties in great britain. if we can assume that these parties would continue forever, then for how long would last the tenure of each of these two parties? even if we consider the fact that the democrats in the united states systematically have won less in the elections than the republicans have and that is why they have different probabilities of being elected then in an abstract sense the time span of being in power for both of the parties equals infinity. this is a mathematical result on the basis of the assumption of the further existence of the respective parties. let us assume that the probability that the democrats would win the elections equals 0.3 and the probability that the republicans would win the elections equals 0.7 then the total duration of the tenure equals(0.3 × ∞) for democrats and (0.7 × ∞) for republicans. if we take into account that (0.3 × ∞) = ∞ and (0.7 × ∞) = ∞ then both of the political parties at least theoretically have an estimated tenure of ∞. this result would be the same also with three or more parties. the same result holds if we take the examples of other mature democracies with established large political parties and consider a whole party and not particular individuals as the holders of power. there are a number of studies on longevity of tenure suggesting that the longevity of the governments is longer in the oil-rich developing countries (andersen and silje (2012), ombga (2009)). nevertheless, if we redefine longevity not as an uninterrupted tenure of a personified political group but as the sum of the tenure of the not personified political force with interruptions then we a sudden discovery of oil reserves and subsequent oil exports cause a budget surplus because of additional revenue sources. we denote oil revenues by r. if the elite decides to introduce institutions prioritizing no more efficiency but rather rent-seeking targets10 then this causes additional costs. appropriation of the illicit income, ivar, requires a change of the institutional setting from production friendly to rent seeking/grabbing institutions. this requires additional costs like expenses of political bargaining, costs for registration and management of offshore companies for the organization of capital flight and political bargain which imply the creation of public sector jobs with very low or no productivity etc. (sadik-zada, 2016). we denote these costs as crent–seeking and call them transaction costs of rent seeking. as a result the hypothetic budget has now the following structure if rapacious rent-seeking takes place:11 fixed m rent-seeking 0surplus= y +r c c iτ − − −  (1) the state elite following rent seeking aims by establishing grabbing institutions entirely appropriates the surplus in equation (1). an alternative to grabbing, e.g., illicit appropriation of the budget surplus is re-investment of the surplus in the manufacturing sector. in this paper we do not consider here the adverse effect of rent-seeking on growth. this issue comes under scrutiny in a number of other papers (anderson and boettke, 1997). confronted with oil windfalls, the politically influential elite get an additional option. if before the oil boom the government was forced to sustain economic efficiency and consequent growth or at least maintain the achieved level of tax revenue, now with additional oil revenue, r, and the resulting budget surplus, the elite is not confronted with the previous pressure and has even the resources for illicit personal enrichment.12 the feasibility of illicit personal enrichment depends also on the institutional setting prior the boom. if the boom happens in a mature democracy with production oriented institutions and a high level of transparency then inducing rapacious institutions could have prohibitive transaction costs, crent–seeking. in contrast, in countries with inferior political and economic institutions, in face of a low level of accountability and transparency, these costs would be much lower than in mature democracies. for the oil-and gas-rich countries of the former ussr with high level of concentration of political power in the hands of a strong executive and weak legislative and judicative powers, weak transparency and accountability, there are favorable preconditions for the prosperity of grabbing would see that on average in the mature democracies the longevity of the tenure of a political party is much higher than in the oil-, gas-, diamondor gold-rich autocracies. 10 mehlum et al. (2006) denote rent-seeking activities and installation of the institutions enabling rent-seeking as “grabbing.” in the following, we shall use the grabbing as a notion describing the sum of rent-seeking activities. 11 without grabbing crent–seeking = 0. 12 this argument is in line with the arguments in hirschman (1967) regarding latitude conjecture and somehow with lewis (1978) whereby the adverse effects of plantocracy and slavery in the southern states of the united states were explained by relatively low wage pressure in these areas. northern states without abundant labor were forced to increase the efficiency due to wage pressure and that’s why they developed a more effective and innovative economy than the south of the united states. sadik-zada and loewenstein: a note on revenue distribution patterns and rent-seeking incentive international journal of energy economics and policy | vol 8 • issue 2 • 2018 200 institutions favoring inefficient rent-seeking targets of the ruling elite (anderson and boetke, 1997. p. 37-53). if in the absence of oil fields, the political and economic institutions had to be led by the target of efficiency increase and were productive, now after the discovery of oil fields, as have to be proven in the following, under some conditions, illicit appropriation starts to be the major target of the incumbent government. with the oil boom the satisfaction of the required expenditure c is no more dependent on the quality of public management and institutional framework provided to the private manufacturing. even with an inferior institutional quality the elites can continue their tenure. like lewis (1978) but in a different context, abundance of one of the production factors decreases the pressure imposed by scarcity that leads to higher efficiency. after a commodity boom there is a more inefficient cost structure and a share, χ∈[0;1], of crent–seeking has to be maintained. χ represents costs of political bargain such as artificially created jobs and wages over marginal productivity in the public sector that cannot not be adjusted immediately. hence, the condition of the balanced budget after depletion of oil reserves shall not be given, i.e. fixed m rent-seeking 0( ×y c c i <0)τ χ− − − . this implies that after depletion of oil reserves a ldc has the same level of tax revenues (τ∙ym) but higher costs increased by χcrent–seekig. the elite shall not be able to stay in office after a commodity boom is over because the revenue side, τym, does not cover the costs side and implies a deterioration of the standard of living increased during the boom by means of artificial employment and other forms of political bargaining. of course, if the increased inefficiency in public spending due to political bargaining, χcrent–seekig, is eliminated then the tenure could continue. nevertheless, it is difficult to imagine that immediately after the boom the government could easily reduce the social standards, eliminate artificial employment in the public sector, cheap water, electricity and gasoline provided during the boom. all these steps would create public unrest and regime change. this assumption of a sticky political bargain is an analogue to sticky wages concept of keynes but in a different context13 and in line with the results of empirical analysis of ponticelli and voth (2011) on the causational relationship between social unrest and budget cuts in europe between 1919 and 2009.14 hence, establishing grabbing institutions implies the limitation of tenure that was assumed to be infinite under efficient institutions without rent seeking: announcement of an austerity package after depletion of oil reserves would be unavoidable. nevertheless, the state elite would not be able to convince the disillusioned population to support the tenure of the old elite and would with a 13 sticky wages is an economic hypothesis that the pay of employed workers tends to respond slowly to the changes in a company’s or the broader economy’s performance. when unemployment rises, the wages of those workers who remain employed tend to stay the same or grow at a slower rate than before rather than falling with the decrease in demand for labor. specifically, wages are said to be “sticky-down” since they can move up easily but move down only with difficulty. 14 as an indicator of social unrest ponticelli and voth (2011) choose the sum of demonstrations, riots, assassinations and general strikes. high probability require a regime and elite change (haggard and kaufman, 1995). confronted with an oil boom, the state elite have to make its decision about the management of oil revenues and consequently about its political future. the decision diagram of the state elite with two following options is illustrated in figure 2: 1. continuation of the old efficient economic policy with productive institutions, or 2. inducing grabbing institutions damaging economic efficiency. the first option implies infinite tenure with a fixed legal income, ifix. and the second option implies the limitation of the tenure to the time span of an oil boom but extension of the fixed legal income by the illicit (rent-seeking) income, ivar, as long as there are essential oil exports generating budget surplus.15 in order to choose between these two options, they have to be compared in monetary terms over an assumed time horizon of infinity. to do this, we shall use a technique introduced by the founder of dynamic optimization richard bellman and divide infinity in two parts (bellman, 1957). part one is the period with oil and part two is the rest of the time till infinity. by dividing infinity into the oil phase, (0; t0), and the after-oil phase, (t0; +∞), we are able to scrutinize the consequences of the concentration of the oil revenues in time, e.g., positively skewed distribution of oil windfalls over time as shown in the upper graph of figure 2. we have a maximization problem with an infinite horizon, whereby the elite has to choose between the above mentioned options. 15 of course there are also other benefits like prestige, power and many other immaterial benefits of staying in power which are differently weighted by different political leaders depending on the matrices of their personality. we do not consider this aspect in our model. in addition, we do not consider the law of diminishing marginal utility of wealth. studies on happiness show that the personal fortune after achieving the threshold of 50 million usd brings no additional utility to its owner. this is also a limitation of our model. nevertheless, if we would make an assumption that the grown-up offspring of the elite members also enter to the group and the number of elite members is growing then the issue of diminishing marginal utility would be partly solved. this is especially straightforward for the dynastically organized elites. figure 2: decision diagram of the state elite after the discovery of oil fields sadik-zada and loewenstein: a note on revenue distribution patterns and rent-seeking incentive international journal of energy economics and policy | vol 8 • issue 2 • 2018201 if the elite chooses the option without rent-seeking (nongrabbing) then they would earn ifix infinitely period after period. otherwise if they choose the first option (grabbing) then the gross income, i0gross, in the boom period, t0, is determined in accordance with equation (2): budget gros sur s fixed fixed m 0 rent-seeking 0 plus 0 0i = y +r c i c +iτ  => − − − (2) gross fixed m rent-seeking 00i y +r c c >iτ⇔ = − − (3) gross 0i with grabbing institutions in (2) is larger than the total income of the state elite without grabbing institutions (the positive difference equals the budget surplus generated in the oil phase which is assumed to last for only one period). because it is hard to imagine that the legal remuneration of the state elite members could be greater than the budget surplus in the oil bonanza period, t0 illicit appropriation of budget surplus causes the end of the tenure of the state elite with the end of t0. in all of the following periods, the state elite separated from tenure would not have the fixed remuneration i0 fixed . nevertheless, they could receive the interest for investing i0 gross in the foreign offshore havens providing security in form of banking secrecy and asset protection for the illicitly appropriated rent and having negligible or no capital income taxation. the high risk of expropriation of the illicit income after revolution is the major reason for investing ivar in the offshore havens. the next important question is the question regarding the interest rate of the mentioned hypothetical deposit of the elite. is this the domestic interest rate? this is with a high probability not the case. the data on capital flight and tax evasion shows that the illicit money from the developing and transformational economies flow mainly to the financial havens like cyprus, british virgin islands, panama, etc. data provided by the international consortium of investigative journalists shows that europe, the uae and offshore financial oases are the major destination of the illicit petrodollars from the petroleum exporting developing and transition economies.16 nevertheless, the interest rates in these havens are much lower than in the developing or transition economies. due to safety provided in the financial oases, the state elite applies the interest rate in the oases, ioases, that is lower than the domestic interest rate idom for the comparison of the options illustrated in figure 2.17 this implies that the elite despite residing in its home country has an orientation interest rate of a foreign jurisdiction. for the comparison, the elite employs the following decision rule: if the net present value (npv) of the fixed income which is nothing but perpetuity (annuity with no end) is larger than the gross income, i0 gross , then the elite does not choose grabbing policy, e.g., economic course prioritizing rent-seeking targets and neglecting long-run sustainability. the npv of a perpetuity, ifix, equals the perpetuity divided by the relevant interest rate: fix fix oases i npv(i )= i (4) 16 for diverse articles on this issue see www.icij.org . 17 this assumption is based on the observation that industrialized, relatively capital-rich countries and offshore oases have in the rule lower interest rates than capital scarce developing or transitional economies. and if fix gross m rent-seeking0 oasis i >i =y +r c c i τ − − then the government continues a non-grabbing course because staying in power for infinity brings more utility than grabbing in t0 yields. otherwise if the npv of the fixed income paid as perpetuity is less than the gross income in t0 then there is an incentive to induce grabbing institutions: fix gross m rent-seeking0 oases i <i =y +r c c i τ − − (5) as can be seen from the equation (4) a higher resource revenue, r, brings the elite closer to the threshold from where grabbing starts to be optimal for the profit maximizing elite. the transaction costs of rent-seeking, crent–seeking, take the elite apart from this threshold. nevertheless, in the countries encountered with the black gold bonanza with inferior institutions before the discovery of oil fields, the probability that crent–seeking could overcompensate the effect of r is usually not that high due to lack of well-functioning democratic institutions leading to public transparency and accountability.18 both equations show that the magnitude of oil revenues, r, and the institutional quality prior to oil boom, which determine the amount of crent–seeking, play a central role in the decision regarding inducing grabbing institutions or relinquishing them. black gold bonanza generates large windfalls and leads to abrupt but tempotaty rise of of the budget revenues. the revenue generation path of the agricultural commodities like cacao, maize, rice etc. do not lead to this kind of abrupt revenue increases and do have a long-lasting impact on the revenue structure of the respective developing nations. this could be an explanation for the corresponce of oil revenues with inferior institutional quality and the resource curse more than other commodity exports with a more even and sustainable revenue generation trajectory. 4. timing of exploitation another question is the timing of the exploitation. when does the ruling elite start to explore and exploit the reserves? in the framework of our model the incumbent government could also start the exploitation as latest as possible because there could be financial rationale behind such a strategy if the price of the reserves increases with the interest rate as expected by the hotelling model. this implies that the ruling elite gets ifix for a very long time and then starts to exploit the reserves. doing so they could increase their total income. however, there are also factors that make the immediate exploitation more probable. first, the continuation of the public governance with restricted financial resources contributes to the development of progressive political and economic institutions and makes the ruling elite more accountable in its public finance and 18 traditionally low open budget index values of the oiland gas-rich states also vindicate this expectation. despite membership in the extractive industries transparency initiative of a number of the oil abundant countries, these countries still do not have a good level of transparency and civil society participation in revenue and expenditure management. sadik-zada and loewenstein: a note on revenue distribution patterns and rent-seeking incentive international journal of energy economics and policy | vol 8 • issue 2 • 2018 202 economic policy. the strengthening of the civil society challenges the assumption of infinite duration for the rule of the incumbent government. another risk connected to the conservation strategy is the competition of different political groups. further, small developing or transition economies, are often urged my external factors like large oil companies supporting political forces that promote rash exploitation rather than conservation (browne, 2010). most developing and all transition economies have not had any intentional delays in the exploitation of its oil and gas deposits. 5. the effect of a more even distribution of the oil wealth over time in the previous subsection, we have shown that nonrenewable resource revenues could give an incentive to induce rent-seeking activities. this subsection is a sophisticated version of the presented model which shows the impact of the scale of the positive skewness of the distribution of the resource revenues in time on the incentive structure. concretely in our context, the increase (decrease) of the scale parameter of distribution of oil revenues in time means that a given stock of oil is extracted in more (less) time periods. for instance, assume that a given petroleum stock of 1000 million barrels could be extracted and sold in one period. if the scale parameter of the distribution of oil revenue in time doubles, then the given 1000 million barrels of petroleum would be extracted in two periods implying that the same oil revenue flow in the hypothetical state budget would take place not in one but in two subsequent years. analysis of these two scenarios enables the comparison of the effect of higher concentration of oil income on rent-seeking incentive. whereby in contrast to isham et al. (2003) we do not scrutinize the spatial concentration of resources in one province or concentration of revenue influx in one hand but in time. suppose that the resources concentrated in one period in the previous model (figure 3a) are distributed over two periods (figure 3b). the difference between a case where all the nonrenewable revenues are concentrated in just one period and a case whereby the revenues flow into the budget over many periods is: 1. in the time value of these revenues, and 2. transaction costs of rent–seeking, crent–seeking. in the previous model we assumed that if the elite chose the rent seeking course then they appropriate the whole surplus in period t0 whereby the surplus equals fix m rent-seekingy +r c c iτ − − −   . now we assume that the same oil deposit, r, can be extracted in two time periods, in t0 and t1. the half of r flows in the hypothetical budget in t0 and the rest (r/2) in t1. in addition to this, we assume that the potential rent seeking revenue cannot be illicitly privatized by the elite without transaction costs, crent–seeking. we assume that if the elite continues rent-seeking course in t1 then the economy will have transaction costs, crent–seeking, both in t0 and t1. in figure 3b we illustrate only the case whereby transaction costs in t1 are the same as in t0. nevertheless, these costs could vary. the costs of political bargaining, payments for overseas company management and registration, fake directorship fees, costs of increased repression, etc. could have both increasing and decreasing forms depending on the concrete situation in the developing or transformational country. in addition to this, crent–seeking could vary over time due to changing external factors like anticorruption legislature in the countries where the parent company of the oil extracting company resides, or due to the introduction of anti-corruption legislature by supranational organizations like the european council. one could suggest that these costs could decrease due to the creation of the rent seeking institutions in the previous period, e.g., in t1. for instance the elite could use the offshore company or bank account created in, t0 or increase expenditures due to increasing social pressure of the population foreseeing an economic collapse after the resource boom. this could be the case especially in the countries with a high level of education, social networks and developed civil society freedoms. hence, the assumption of constant transaction costs of rent-seeking is a rough simplification that could be abolished in the more sophisticated models focusing on the dynamics of crent–seeking. based on constant crent–seeking, the npv of the gross income of the elite, igross−t, for the case where all the revenue flows just in one period, t0 i gross−1 and the case where the same revenue flows over two periods, t0 and t1, i gross−2 shall be compared. the npv of the gross income of the elite in the two period model, igross−2, can be determined as follows: gross 2= fix fix m rent-seeking fix fix m rent-seeking1 m rent-seeking m rent-seeking r i i +( +(y ) c c i 2 r (i +( +(y ) c c i ) 2+ 1+r r +(y ) c cr 2=( +(y ) c c )+ 2 ) 1+r τ τ τ τ − − − − − − − − − − − (6) we denote in (5) and in the following equations the tax revenue generated in the manufacturing sector, ymτ, assumed to be constant with a roof as my τ in order to avoid confusion regarding the impact of the tax revenue on igross. for comparison, itotal−1 for the case where all the resource revenue flows just in one period was determined as follows: gross 1 fix m rent-seeking fix m rent-ssking i =i +y +r c c i )=y +r c c − − − − − (7) now let us compare the npv of igross−2 and igross−1 in (6) and (7). for this we subtract (6) from (7). the difference shows whether grabbing or efficient resource management is more advantageous for the state elite. in both cases, my τ is constant. the fourth and sadik-zada and loewenstein: a note on revenue distribution patterns and rent-seeking incentive international journal of energy economics and policy | vol 8 • issue 2 • 2018203 fifth terms in (6) and (7), c and crent–seeking are also equal. this yields the following result in equation (8): fix fix rent-seeking1gross 1 gross 2 rent-seeking1gross 1 gross 2 rent-seeking m 1 m m r i +( + c i )r 2i i = r 2 1 r r ( c )r 2i i 2 1+r r cr 2 2 1+r 1+ y c y c y c 1 r r − − − − − − − − − − + + − − ⇔ − = − − = − τ + τ + − τ (8) as we know from the introducing assumptions of the model, in a situation without oil revenues, the conditions for the balanced hypothetical budget were assumed to be given fix msurplus=y c i =0)τ− − . this implies that fix my c=iτ− and we can rewrite the third term on the rhs of (6), m y c 1+r τ− , as fixi 1+r . this means that (6) can be reduced to the following form: fix rent-seekinggross 1 gross 2 1 2 r cr i2i i = + 2 1+r 1+r 1+r − −      −     − − (9) the difference between r 2      and r 2 1+r    −        is positive because the discount factor is greater than the unity, (1+r) > 1. the last term in (8), rent-seeking c 1+r       has a positive sign. this implies that due to the time value of the oil revenues r r 2 2 1+r           − and additional costs of rent seeking incurring the second year, the npv of the gross income of the elite is less in the case of a stretched two-period oil boom. translating the decision rule expressed in equation (4), fix gross oases i <npv(i ) i       , the result implies that with a more even distribution of the revenue the npv (igross) tends to diminish and in the theoretical extreme case if n → ∞ then r 0 n → . under such conditions, efficiency oriented public management is the dominant strategy and rent-seeking makes no sense for the state elite. nevertheless, as seen from (8), the second term on the rhs, fixi 1+r , has an opposite impact on the difference between (gross 1)1i − and (gross 2) 2i − . by equating the rhs of (8) to zero, we could find the condition where the interest and transaction cost effects of revenue stretching can be compensated by ifix in t1 which is provided due to an additional year of tenure. fix rent-seeking r cr i 2 0 2 1+r 1+r 1+r − − + = (10) fix rent-seeking r ci r 2 = 1+r 2 1+r ⇔ − − (11) multiplying both sides of (10) by (1−r) yields the following expression: ( )fix fixrent-seeking rent-seeking rr i 1+r r r+2 c i = +c 2 ⇔= − ⋅ (12) the last equation sets the condition for indifference and implies that if the fixed income of one additional year in power compensates the loss of interest due to discounting of r 2 and transaction costs for rent seeking for one additional year then the elite is indifferent. however, in the rule the legal income of the elites in the transformational and developing countries is relatively small. hence, it is probable that the bigger concentration of the revenues creates larger gross revenue for the elites. thus we could time time 2 total oil revenue = r 2 − 2 − ∈ (0; ) ∈ ( ,+∞) 0 a ∈ (0; ] ∈ ( , ] 2 − a b ∈ ( ,∞) figure 3: variations of the scale parameters of the distribution of the oil revenues over time. in a oil revenue, r, flows into hypothetical budget in one and in b in two periods in two equal rates, r/2. in b we illustrate only the case whereby crent–seeking in t0 and in t1 is the same. nevertheless, cases with decreasing of increasing transaction costs are also thinkable a b sadik-zada and loewenstein: a note on revenue distribution patterns and rent-seeking incentive international journal of energy economics and policy | vol 8 • issue 2 • 2018 204 show that it is more advantageous for the elites if the revenues have a high degree of concentration in time. we can conclude that a more even, e.g., stretched distribution of the revenue from the same oil stock, r, implies a smaller npv of the gross income. a further stretching of the resource stock over time means a decrease of the npv of the gross income and in the theoretical extreme case if the given stock of resources r is stretched over infinity then condition of choosing the grabbing course fix gross 0 oasis i <i i , overturns and efficiency oriented public management turns to be the dominant strategy of the politically powerful utility maximizing elite. 6. conclusion we have suggested a novel theoretical rationale for the emergence of the rapacious rent-seeking in the oil abundant countries. based on a simple multiple-period model in the tradition of positive economics, we have shown that a large magnitude of oil windfalls, the nonrenewable character of these revenues expressed hubbertian distribution, the availability of the financial havens and the level of democracy prior to the oil revenue boom could explain the emergence of rapacious rent-seeking in a number oilrich countries. in addition, we could show that in the societies with good institutional preconditions the implementation of grabbing strategies is less probable due to the high transaction costs of rent-seeking, crent-seeking. alongside crent-seeking, the level of the legal remuneration of the incumbent state elite, fixti , could also play decisive a role in the strategy choice of the state elite. in equation (12) we derive it fix that overweighs the factors contributing to rentseeking incentives. we conclude that at least in the context of the presented theoretical model the revenue distribution patterns are able to determine incentive structure of the state elite and explain the deterioration of the quality of public policy in the absence of prohibitive costs of rapacious rent-seeking. references abdelnasser, g. (2004), egypt: succession politics. in: perthes, v., editor. arab elites: negotiating the politics of change. boulder, london: lynne rienner publishers. p. 117-139. acemoglu, d. (2009), introduction to modern economic growth. princeton, oxford: princeton university press. andersen, j.j., silje, a. (2012), oil and political survival. oslo: bi norwegian business school. available from: http://www.home. bi.no/a0810301/andersenaslaksen2010.pdf. [last retrieved on 2014 dec 12]. anderson, g., boetke, b. j. (1997), soviet venality: a rent-seeking model of the communist state. public choice, 93(1-2), 37-53. arps, j.j. (1945), analysis of decline curves. transactions aime, 160, 228-247. bavinck, m., pellegrini, l., mostert, e., editors. (2014), conflicts over natural resources in the global south: conceptual approaches. boca raton, london, new york, leiden: crc press. baldwin, r.e. (1956), patterns of development in newly settled regions. bellmann, r. (1957), dynamic programming. princeton: princeton university press. bentley, r. (2002), global oil and gas depletion: an overview. energy policy, 30, 189-205. boschini, a., pettersson, j., roine, j. (2007), resource curse or not: a question of appropriability. scandinavian journal of economics, 109(3), 593-617. brandt, a.e. (2007), testing hubbert. energy policy, 35, 3074-3088. browne, j. (2010), beyond business: an inspirational memoir from a visionary leader. london: weid enfeld & nicolson. haggard, s., kaufman, r. (1995), the political economy of democratic transitions. princeton: princeton university press. higley, j., gunther, r., editors. (1992), elites and democratic consolidation in latin america and southern europe. new york: press syndicate of the university of cambridge. hirschman, a. (1958), the strategy of economic development. new haven, conn.: yale university press. hirschman, a. (1984), in: meyer, g., seers, d., editors. a dissenter’s confession: the strategy of economic development revisited. new york: world bank. hirschmann, a. (2013), the essential hirschman. princeton: princeton university press. höök, m. (2008), depletion and decline curve analysis in crude oil production. available from: https://www.uu.diva-portal.org/ smash/get/diva2:338111/fulltext01.pdf. [last retrieved on 2015 nov 11]. isham, j., lant, p., michael, w., gwen, b. (2003), the varieties of resource experience: how natural resource export structures affect the political economy of economic growth, middlebury working paper series no 0308/12. & unwin. loewenstein, w., bender, d. (2017), labour market failure, growth mavrotas, g., murshed, s., torres, s. (2011), natural resource dependence and economic performance in the 1970-2000 period. review of development economics, 15(1), 124-138. mehlum, h., moene, k., tovrik, r. (2006), institutions and the resource curse. the economic journal, 116, 1-20. morris, m., raphael, k., kaplan, d. (2011), commodities and linkages: industrialization in sub-saharan africa, mmcp discussion paper no. 13. available from: http://www.prism.uct. ac.za/papers/mmcp%20paper%2013_0.pdf. [last retrieved on 2015 may 22]. omgba, l. (2009), on the duration of political power in africa: the role of oil rents. coparative political studies, 42(3), 416-436. ponticelli, j., voth, h.j. (2011), austerity and anarchy: budget cuts and social unrest in europe, 1919-2009, discussion paper series no. 8513. london: centre for economic policy research. available from: http://www.cepr.org/pubs/dps/dp8513.asp. [last retrieved on 2015 may 21]. rustow, d.a. (1970), transitions to democracy: toward a dynamic model. comparative politics, 2(3), 337-363. sadik-zada, r.e. (2016), oil abundance and economic growth. berlin: logos verlag. van der ploeg, f. (2010), why do many resource-rich countries have negative genuine saving? anticipation of better times or rapacious rent seeking. resource and energy economics, 32, 28-44. werenfels, i. (2004), algeria: system continuity through elite change. in: perthes, v., editor. arab elites: negotiating the politics of change. boulder, london: lynne rienner publishers. p. 173-205. manchester school of economics and social studies 24(5), 161-179. lewis, a.w. (1978), growth and fluctuations. london: george allen and poverty dynamics in partially formalized economies: why developing countries' growth patterns are different. available from: http://dx.doi.org/10.2139/ssrn.3022146 [last retrieved on 2018 jan 12]. . international journal of energy economics and policy | vol 7 • issue 2 • 201734 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(2), 34-43. does too much energy consumption harm economic growth for turkish republics in the transition process? new evidence on threshold effects#1 celil aydın1, ömer esen2* 1department of economics, faculty of economics and administrative sciences, mus alparslan university, 49250, muş, turkey, 2department of economics, faculty of economics and administrative sciences, mus alparslan university, 49250, muş, turkey. *email: o.esen@alparslan.edu.tr abstract this paper examines whether the effect of energy consumption on economic growth is dependent on the level of energy intensity for 5 turkish republics in the transition process over the period 1991-2012. these economies are divided into two groups in the context of their energy balance. the first group comprises all of the turkish republics in the transition process while the second group is composed of only the net energy exporter countries among them. using an innovative dynamic panel threshold technique, the estimated threshold of the energy intensity for the first group is 0.68%, while for the second group countries the threshold is 0.44%. the empirical results indicate that the energy consumption rate above the threshold energy intensity level adversely affects the economic growth, but this negative relationship becomes positive one when the energy consumption is below the threshold level. these findings reveal that the energy consumption is beneficial to economic growth only up to a certain threshold of the energy intensity; beyond the threshold level further the consumption tends to adversely affect the growth. in this regard, policy makers in the transition economies should not ignore threshold levels within the context of energy intensity while determining energy policies. keywords: dynamic panel threshold analysis, energy consumption, economic growth, energy intensity jel classifications: c24, q43, o11 # a preliminary version of this paper was presented at the 5th world conference on business, economics and management (wcbem 2016) held in antalya, turkey, may 12-14, 2016. 1. introduction energy is an important resource in the classification of natural resources and used in all phases of production. it is considered key input and is consumed as output for increasing the welfare level. the important role of energy as a production input was disregarded until the oil crisis of the 1970s. by that time, even the theories of economic growth paid no attention to the role of energy and its effect on growth (stern and cleveland, 2004). following this period, energy was perceived as a factor of production, together with labor and capital. neoclassical economists like hamilton (1983) and burbidge and harrison (1984) reported some findings supporting that energy has an important place in the development of economies. attributed with great importance in today’s world, energy is considered not only as a production input, but also as one of the most important determinants of the economic, social, and geographic order of the world as a strategic commodity that constitutes the basis for international relations and shapes the world economy and politics (esen, 2016). countries’ desire to obtain energy resources, gain control over them, or have a say in them indicates that energy is an indispensable commodity in terms of politics. given that it has such a mission, potential problems in the supply of energy used in production raise serious concerns about the sustainability of economic growth. having the necessary energy resources, which constitute an extremely important input for sustaining economic growth and ensuring modern living standards, or at least supplying energy from other countries is of critical importance for a country to ensure sustainable economic growth. aydın and esen: does too much energy consumption harm economic growth for turkish republics in the transition process? new evidence on threshold effects international journal of energy economics and policy | vol 7 • issue 2 • 2017 35 the resources used in the generation of energy are limited in both amount and diversity. on the other hand, the distribution of energy resources around the world is not balanced. some regions have more reserves compared to others in terms of the amount and diversity. such uneven distribution of energy resources is true not only for the reserves, but also for the consumption levels (bayrak and esen, 2014). this leads to the emergence of great competition for the energy supply under reasonable, reliable, and sustainable conditions among the countries in need of energy resources (öztürkler, 2009). in the world economy, increased production means increased energy consumption and increasing countries’ dependence on energy import. therefore, the issues of ensuring and sustaining stability in energy production and supply constitute the framework of all strategies and plans toward the objective of sustainable growth. during the era of the former union of soviet socialist republics, the means of production in the republics of kazakhstan, azerbaijan, turkmenistan, kyrgyzstan and uzbekistan—altogether known as the turkic republics—were structured in a way that they were heavily dependent on each other and russia. the production process, from raw materials to the end-product, could not be handled in a single country as a whole. the raw materials produced in one country were made into intermediate goods and, most of the time, the end product was produced in ukraine or russia (demirkan, 1993). for the turkic republics that took over such a production structure, it became impossible to reach a production capacity sufficient to meet their domestic demands with their current economy during the transition period due to, for example, a lack of existing infrastructure, the use of outdated technology, and undercapitalization. therefore, these turkic republics in the transition period resorted to operating their energy resources to transition to a market economy and ease the problems associated with the transition period. during this period, the energy sector was the locomotive of economic growth. the energy sector had a considerable share in the public revenues as well. energy resources also had a large share in the export revenues. however, due to the existing factor endowment and technological infrastructure, the turkic republics focused their attention mostly on mineral and raw energy production and their exports, and they had to import most industrial goods from the industrialized countries of the west. during this period, poverty could not be prevented in these republics despite the rapid increase in welfare. their exports concentrated primarily in energy products, leading to huge instabilities in energy prices and foreign exchange earnings. therefore, their economic development was adversely affected by the fluctuations in energy prices. even today, these countries do not have the necessary economic structure to operate the oil and natural gas reserves with their own equity capital due to, for example, a lack of technology and undercapitalization. therefore, they have to cooperate with large western energy companies to exploit their energy resources. however, in order for these turkic republics to sustain their economic growth, it is of crucial importance to reduce their dependency on a production structure based on the export of labor-intensive goods and original raw materials (especially oil and natural gas) to developed countries; they must also turn to other industries that require intensive capital and advanced technology. this process highlights the importance of energy consumption based on increased production and the relationship between energy consumption and growth. the effective and efficient use of energy resources is as important as energy consumption for economic development, because the efficient use of energy is one of the ways to create new energy resources. the literature review shows that energy intensity is considered one of the indicators of energy efficiency. a country’s energy intensity ratios depend on certain factors, such as the production structure of the economy, scale of the industries, capacity utilization levels, consumption habits of the societies, population, climatic conditions, technological developments, energy policies, and the amount of energy resources. energy intensity represents the amount of energy used by an economy for each unit value added in a given production process that indicates the intensity of energy usage during the production process (gomulka, 1990; fisher-vanden et al., 2004; liao et al., 2007). thus, energy intensity measures the efficiency of energy use by an economy during the production process (fisher-vanden et al., 2004). low energy intensity indicates that existing energy resources are being used in production in a more efficient and effective way by that economy, thereby also showing that the amount of energy consumed to produce a unit of gnp is also low (kavak, 2005). in this sense, meeting the energy required for growth by consuming less energy would be beneficial for an economy in many ways, such as decreasing dependence on external sources of energy and increasing resistance to external shocks. in such an environment, it becomes necessary to channel the resources to investments with high added value and create an environment that will allow efficient energy use as much as possible. otherwise, if the contribution of each factor to production (growth) is low, the income level will remain low, thereby restricting new investment opportunities and hampering long-term and steady economic growth. the relationship between energy consumption and economic growth has become one of the most frequently discussed issues in the economics literature, especially following the oil crises in the 1970s. however, the issue has not been addressed in terms of the transition economies trying to change from centrally planned economies to free markets. this study aims to empirically reveal the effect of energy consumption on economic growth in five turkic republics undergoing a transition from a centrally planned economy to a free market economy following the collapse of the socialist regime at the end of the 1980s. in line with this purpose, we believe that this study will make a significant contribution to the literature on the foundations of economic growth in transition economies by examining the issue in terms of the transition economies where the states take active roles. this paper is expected to provide three significant contributions to the literature. (i) the sample of this study includes five turkish republics that had a socialist economic system in the past, but are currently trying to create their market economies. although these economies are going through different experiences of market economy, their common ground is the problems caused by poverty aydın and esen: does too much energy consumption harm economic growth for turkish republics in the transition process? new evidence on threshold effects international journal of energy economics and policy | vol 7 • issue 2 • 201736 and a public sector that is growing and becoming cumbersome. besides the cumbersome structure inherited from the socialist system, deficiency of existing infrastructures, old technologies, and undercapitalization directly affect productivity and economic growth performance. hence, the examination of these countries, which are resorting to institutional and structural regulations to get rid of poverty, will make an important contribution to the literature, (ii) previous studies have focused on the energy consumptioneconomic growth nexus but less on the effects of energy efficiency on growth. unlike previous studies, this paper investigates the effects of energy consumption on growth on the basis of energy intensity. level of energy intensity is one of the important factors determining the relationship between energy consumption and growth, (iii) previous studies focusing on the effects of energy consumption on economic growth have developed models based on the assumption that the relationship is linear. however, this paper assumes that the effects of energy consumption on economic growth will be asymmetrical (i.e., there will be a difference between the effect of energy consumption on growth when energy intensity is high and the effect of energy consumption on growth when energy intensity is low). with this assumption, the study employs dynamic panel threshold regression analysis, which is an innovative non-linear model, thereby offering an alternative to the literature. accordingly, the study provides significant new findings regarding the effects of energy efficiency on the relationship between energy consumption and economic growth. the literature review shows that most of the studies examining the relationship between energy consumption and economic growth focus on the models and analysis techniques developed with a linear hypothesis based on a causality relationship. the analyses and interpretations based on the assumption that the relationship between energy consumption and economic growth is linear point out the existence of a symmetrical relationship between the increases and decreases in energy consumption and economic growth. these studies view the energy consumption level as an indicator of development and consider that a country produces based on the amount of energy it consumes and achieves a high level of welfare. however, development should be based on the ability to create much more economic value with less energy (i.e., deliver the same production with a lower amount of energy), rather than the energy consumption rates. energy consumption is important for economic growth as well; however, the consumption must be balanced. such asymmetry points to a non-linear relationship. the empirical studies conducted thus far provide very little information about whether the relationship is linear—in other words, whether the energy consumption has a threshold level or not. this study aims to examine the relationship between economic growth and energy consumption, which is considered an indicator for development, in the turkic republics. in the study, the threshold regression model was used to find the threshold level above which energy consumption adversely affects economic growth. moreover, the study aims to put the energy consumptiongrowth debates—built most often on an incorrect theoretical and empirical basis—on solid ground. in the first stage of the study, we will address the relationship in terms of the effect of energy consumption on economic growth and the efficient use of energy. in the subsequent sections, we will first review the theoretical and empirical literature focusing on the relationship between energy consumption and economic growth and then examine the interaction between energy consumption and economic growth in the turkic republics for the 1990-2012 period in order to determine whether any threshold level exists above which the inefficient use of energy reaches unsustainable levels. in the final stage, the findings will be compared with the findings of other studies in the literature. 2. literature review despite some problems and bottlenecks in the energy field experienced by the countries in the past, energy became an issue of debate only after the great oil crises of the 1970s, which deeply affected the international markets. as a result, the number of studies examining the relationship between energy and economic growth gradually increased. however, most of these studies focused on whether a relationship exists between energy consumption and economic growth and, if it does, what the direction of this relationship is. the literature review shows that the causality relationship between energy consumption and economic growth is handled under four hypotheses. the studies in the first group reported a unidirectional relationship from energy consumption to economic growth (stern, 2000; shiu and lam, 2004; altınay and karagöl, 2005; odhiambo, 2009; apergis and payne, 2010; iyke, 2015). this hypothesis—called the growth hypothesis in the literature—claims that energy is one of the key indicators of economic growth. such a causality relationship indicates that the examined countries have energy-dependent production structures and they may have serious problems with the sustainability of economic growth in cases where energy demand cannot be met. the studies in the second group found a unidirectional causality from economic growth to energy consumption (kraft and kraft, 1978; cheng and lai, 1997; ghosh, 2002; lise and montfort, 2007; mozumder and marathe, 2007; herrerias et al., 2013). their hypothesis is known as the conservation hypothesis and asserts that the countries are not energy-dependent; moreover, energy consumption occurs as a result of increases in economic growth. the studies in the third group suggest that a mutual causal relationship exists between these two variables (paul and bhattacharya, 2004; shahbaz and lean, 2012; dagher and talar, 2012; wesseh and zoumara, 2012; esseghir and khouni, 2014). known as the feedback hypothesis, this hypothesis asserts that energy consumption and economic growth mutually affect each other. pirlogea and cicea (2012) argue that, for countries with bidirectional energy dependence, it is of crucial importance to pay attention to energy efficiency, reduce energy consumption based on conventional energy resources, move to renewable energy resources, and reduce greenhouse gas emissions. finally, the fourth group includes those studies that reported no causal relationship between these two variables (akarca and long, 1980; eden and hwang, 1984; cheng, 1995; hondroyiannis et al., 2002; altınay and karagöl, 2004; acaravci and ozturk, 2010a). known as the neutrality hypothesis in the literature, this hypothesis asserts that policies toward reducing energy consumption do not have any effect on economic growth. aydın and esen: does too much energy consumption harm economic growth for turkish republics in the transition process? new evidence on threshold effects international journal of energy economics and policy | vol 7 • issue 2 • 2017 37 although many studies examine the relationship between energy consumption and economic growth, the debates are still ongoing about the direction of the causal relationship between these two variables. in other words, no agreement exists on whether economic growth dictates energy consumption or whether energy consumption is the locomotive of economic growth or no causal relationship exists between these two variables. many studies in the literature show that the existence and direction of such a relationship varies from one country to another (erol and yu, 1987; soytas and sari, 2003; asafu-adjaye, 2000; glasure and lee, 1998; masih and masih, 1996; akinlo, 2008; wolde-rufael, 2006; acaravci and ozturk, 2010b; ozturk et al., 2010; ouedraogo, 2013; salahuddin et al., 2015). most studies on the relationship between energy consumption and economic growth are based on the assumption that a linear causal relationship exists between these two variables. econometrical models are selected, and analyses are carried out in line with this assumption. selecting models and carrying out analyses based on the assumption that a linear relationship exists between these two variables automatically means accepting the presupposition that the variables demonstrate similar behaviors independent of the country’s production structure. however, energy consumption might have a non-linear effect on economic growth not only in the net energy importing countries, but also in the net exporters of energy. although energy consumption is considered an indicator of development in the growth and development literature, recent debates have mostly focused on the necessity of treating the ability of creating more economic value with less energy as a development indicator, rather than the energy consumption levels. in parallel with these debates, the number of studies on the possibility of a non-linear relationship between energy consumption and economic growth and the potential asymmetric effect of energy consumption on economic growth has increased. the empirical studies in the literature on energy and growth provide very little information about whether energy consumption has a non-linear effect on economic growth—in other words, whether the energy consumption has a threshold level or not. lee and chang’s (2007) study is one of the most important studies based on the assumption of a non-linear relationship; they examine whether energy consumption has linear and non-linear effects on economic growth in taiwan for the 1955-2003 period by using one-sector and two-sector growth models. their findings suggest that a nonlinear relationship exists between these two variables in the case of taiwan and this relationship is characterized by a “u-shape” (i.e., first decreasing and then increasing) pattern. a similar study by huang et al. (2008) separates data extending from 1971 to 2002 into two periods for 82 countries and examines the relationship between energy consumption and economic growth during these periods. the results of their analysis indicate a non-linear relationship between these two variables. aydin and esen (2016) investigate whether level of energy intensity is important in the effect of energy consumption on economic growth of turkey for the period 1975-2013. the findings indicate that there is a nonlinear relationship between energy consumption and economic growth in the turkey economy and the threshold level of energy intensity below which energy consumption significantly promotes economic growth is estimated at 0.191. an energy consumption above this threshold has statistically significant negative effect on economic growth. 3. model, data set and econometric method this study investigated the relationship between energy consumption and economic growth for the 1991-2012 period in five turkish republics (azerbaijan, kazakhstan, kyrgyzstan, uzbekistan, and turkmenistan) in the transition process using dynamic panel data analysis that takes into account the energy intensity threshold level. such a relationship was examined based on the neoclassical production function used by ghali and sakka (2004), lee and chang (2007), and huang et al. (2008). equation 1 shows the production function, which includes energy consumption as a factor of production like capital stock and labor:  y = + initial + ec + x + it 0 1 it 2 it it it α α α β ε (1) where y indicates the real gross domestic product (gdp) growth at time t in country i; indicates the initial level of income; ec is the energy consumption rate; x represents other macroeconomic variables that might have an impact on economic growth; and ε denotes the white noise error term. the literature review shows that the real gdp is taken as a basis in the international comparisons as it gives important information about the growth performances of economies; however, in comparing the living standards of different countries or examining the changes in the welfare level of a country over time, the real gdp per capita is preferred as it takes into account the number of people living in a country. in this sense, we used the annual growth rate of real gdp per capita (dgdp) as an indicator of living standards. we also used the growth rate of energy consumption per capita (dec) as the independent variable of the model. the energy consumption growth rate was calculated based on the logarithmic difference of energy consumption per capita (tons of oil equivalent). the graphs for the variables are shown in figure 1. to control the effects of other macroeconomic variables related to energy consumption on economic growth, we used the following control variables based on the studies of khan and senhadji (2001), drukker et al. (2005), huang et al. (2008), and kremer et al. (2013): percentage of gdp dedicated to investment (igdp), growth of labor force participation rate (dlab), inflation (π), initial income level (initial), openness (open), foreign trade rate (dtot), standard deviation of openness (sdopen), and standard deviation of foreign trade rate (sdtot). we also used energy intensity (tpes/y) as the threshold variable. we obtained the data about inflation rates from the international financial statistics. the data about the energy intensity rates were obtained from the international energy agency, and the data about the other variables were acquired from the database of the world development indicators. table 1 shows the basic data about the variables; table 2 shows the descriptive statistics. aydın and esen: does too much energy consumption harm economic growth for turkish republics in the transition process? new evidence on threshold effects international journal of energy economics and policy | vol 7 • issue 2 • 201738 we included the lagged value of gdp per capita in the model as the explanatory variable based on the assumption that production level and structure of an economy are not entirely independent of the previous periods; thus, production levels in the previous period are also reflected in the subsequent periods (ramirez and rondán, 2013). the use of the lagged values of the dependent variable as the explanatory variable in the fixed effects and random effects models used in the static panel data analysis causes the emergence of a relationship between the lagged values of the dependent variable and the error terms. such a relationship causes the estimation made by fixed and random effects models and the estimators to be inconsistent (greene, 2000). in such cases, the use of the dynamic panel data method eliminates such a relationship between the lagged values of the dependent variable and the error terms, thereby increasing the reliability of the estimation and the consistency of the estimators. in this study, we used the dynamic panel threshold model developed by kremer et al. (2013) by extending hansen’s (1999) static model for endogenous regressors. we chose the initial level of income as the endogenous regressor (initial=dgdpt-1). our panel threshold model was built on caner and hansen’s (2004) cross-sectional threshold model, where generalized method of moments (gmm) type estimators are used in order to allow for endogeneity. equation 2 shows the model. y = + z i(q £ )+ z i(q > )+ it i it it it it it µ β γ β γ ε′ ′ 1 2 (2) where i represents the units within the scope of the cross-section (i = 1,…,n); t indicates the dimension of the time series for each unit (t = 1,…,t); yit is the dependent variable; µi is the countryspecific fixed effect; εit≈(0,σ 2) is the independently and identically distributed error term; i(.) is the indicator function indicating the regime; qit is the threshold variable; and ϒ is the threshold value. in addition, zit, indicates an m-dimensional vector of explanatory regressors that may include lagged values of the dependent variable and other endogenous variables. the vector of explanatory variables is partitioned into a subset z1it of exogenous variables uncorrelated with eit and a subset of endogenous variables z2it correlated with eit (kremer et al., 2013). in the first step of the estimation of the model in equation 2, the individual effects (µi) have to be eliminated via a fixed-effects transformation. therefore, we apply the forward orthogonal deviation method suggested by arellano and bover (1995). equation 3 shows the method. ε ε ε ε it * it i(t+1) it = t t t t+1 [ 1 t t ( +...+ )] − − − − (3) the most distinguishing feature of this method is that it can avoid the serial correlation of the transformed error terms. according to figure 1: per capita gross domestic product and energy consumption growth rates across countries table 1: basic information about the variables abbreviation explanation dgdp annual growth rate of real gdp per capita ($) dec logarithmic difference of energy consumption per capita (kg of oil equivalent) tpes/y total primary energy consumption as a percentage of gdp measured at purchasing power parity (tons of oil equivalent/$1,000) π annual percent changes in the cpi igdp percentage of gdp dedicated to investment ($) dlab employment/population growth rate initial gdp per capita of the previous term open logarithm of export and import as percentage of gdp sdopen standard deviation of openness dtot import/export growth rate sdtot standard deviation of foreign trade rate cpi: consumer price index, gdp: gross domestic product aydın and esen: does too much energy consumption harm economic growth for turkish republics in the transition process? new evidence on threshold effects international journal of energy economics and policy | vol 7 • issue 2 • 2017 39 kremer et al. (2013), this feature allows for the application of the estimation procedure derived by caner and hansen (2004) for a cross-sectional model to the dynamic panel data models. the next step of the estimation procedures involves the use of two-stage least squares (2sls) to estimate the energy intensity threshold level. to this end, following caner and hansen (2004), we first estimate a reduced form regression for the endogenous variables (z2it) as a function of the instruments (xit). the endogenous variables (z2it) are then replaced in the structural equation by the predicted values 2itẑ . finally, the model in equation 2 is estimated via least squares for a fixed threshold (ϒ). this step is repeated for the subsets of the threshold variable q. among the threshold values, the threshold value with the smallest sum of squared residuals (s[γ]) is selected as the most appropriate threshold value ( ŷ ). equation 4 shows this procedure (hansen, 2000. p. 578). nŷ=arg min s ( )γ (4) in accordance with the studies by hansen (1999), caner and hansen (2004), and kremer et al. (2013), the critical values are estimated to determine the 95% confidence interval of the energy intensity threshold value. equation 5 is used to estimate these critical values: г={γ:lr(γ)≤c(α)} (5) in equation 5, c(α) is the 95% percentile of the asymptotic distribution of the likelihood ratio statistic lr(γ). according to hansen (1999), the underlying likelihood ratio is adjusted to account for the number of time periods used for each cross-section. in the dynamic panel model, after the appropriate threshold value ( ŷ ) is determined, the slope coefficients are estimated by the gmm for the previously determined instruments and the previous estimated threshold. equation 6 shows the dynamic panel threshold model formed with gmm to examine the effect of energy intensity threshold value on the relationship between energy consumption and economic growth. dgdpit=µi + β1decit i[(tpes/y)it≤γ] + δ1 i[(tpes/y)it≤γ] + β2decit i[(tpes/y)it>γ] + ∅zit + εit (6) where decit represents the growth rate of energy consumption per capita for both regime types and zit represents the vector of control variables. tpes/y denotes the threshold variable. β1 and β2 indicate the regime-dependent slope coefficients, and δ1 indicates the fixed regime coefficient. following bick (2010) and kremer et al. (2013), we used the initial income level (z2it) as the endogenous variable. according to roodman (2009), the use of all lags of the dependent variable as instruments in the dynamic panel analysis makes the coefficient estimation both unbiased and consistent. therefore, based on the study by arellano and bover (1995), we used all the lags of the dependent variable as instruments. besides, in dynamic panel model, estimator is consistent when t/n→c for 0<c≤2 (alvarez and arellano, 2003). in cases where c is <2, the bootstrap method should be used in order to make the estimator consistent. 4. findings in table 3, model 1 shows the results of the dynamic panel threshold model applied to examine the relationship between economic growth and energy consumption in 5 turkic republics in transition. among these five countries, azerbaijan, kazakhstan, uzbekistan, and turkmenistan were found to be net energy exporting countries with important oil and natural gas reserves, while kyrgyzstan was found to import some of its energy despite its high hydropower potential. because it is a net energy importing country, kyrgyzstan was left out of the analysis, and the relationship between energy consumption and economic growth was examined again together with the role of the energy intensity threshold value. the findings are shown in model 2. the upper part of table 3 shows the estimated energy intensity threshold level and the corresponding 95% confidence interval. the middle part of the table shows the effect of energy consumption per capita on economic growth for both regime types. 1β̂ denotes the marginal effect of energy consumption per capita on economic growth in the low energy intensity regime, while 2β̂ indicates the marginal effect of energy consumption per capita on economic growth in the high-energy intensity regime. low-energy intensity regime indicates the case when the energy intensity level is below the estimated threshold value, while high-energy intensity regime indicates the case when the energy intensity level is above the estimated threshold value. as shown in table 3, the estimated threshold values for energy intensity were found to be 0.68 and 0.44 for models 1 and 2, respectively (via 2sls). figure 2 shows the sum of the squared errors of the threshold values for both models. in model 1, the lower limit for the threshold value at the 95% confidence level is 0.26 and the upper limit is 0.71. in model 2, the lower limit is 0.24 and the upper limit is 0.72. the findings show that, in general, energy intensity increases in the first stages of economic development; however, it shows a declining tendency in the developed economies due to the increasing share of the service (tertiary) sector in economic growth during the development process. in the underdeveloped or developing economies, increased energy intensity is an expected consequence of industrialization. table 2: descriptive statistics for all variables tpes/y dgdp dec π igdp dlab open dtot mean 0.467 6.779 −1.562 203.421 6.879 0.175 4.449 3.182 sd 0.245 17.100 9.747 464.919 25.899 1.430 0.530 25.057 minimum 0.090 −58.133 −40.981 −18.930 −65.217 −6.840 0.000 −52.132 maximum 1.020 44.904 22.248 3100.000 111.400 5.609 5.173 77.334 gdp: gross domestic product, sd: standard deviation aydın and esen: does too much energy consumption harm economic growth for turkish republics in the transition process? new evidence on threshold effects international journal of energy economics and policy | vol 7 • issue 2 • 201740 in countries that have achieved a certain level of industrialization, the economic structures turning toward more low energy-intensive industries together with technological developments that allow for the efficient use of energy may cause a decrease in the energy intensity (leach et al., 1986). according to model 1, the regime-dependent coefficients are statistically significant ( 1β̂ =0.816 and 2β̂ =−0.588), meaning that energy consumption per capita has a positive marginal effect on economic growth in the low energy intensity regime, but a negative marginal effect in the high energy intensity regime. in other words, the rate of energy consumption per capita below the threshold level affects economic growth positively. if the rate is above the threshold value, then it affects economic growth negatively. if we examine the regimedependent coefficients, we can see that the effect of energy consumption per capita on economic growth is higher in the low energy intensity regime. for model 2, 1β̂ was found to be statistically significant (1.298), while 2β̂ was not (−0.217). thus, energy consumption per capita has a positive marginal effect on economic growth in the low energy intensity regime. although the relationship between energy consumption and economic growth is not statistically significant in the high energy intensity regime, the effect has been found to be negative. in other words, the rate of energy consumption per capita below the threshold level affects economic growth positively. if the rate is above the threshold value, then it affects economic growth negatively. if we examine the regime-dependent coefficients, we can see that the effect of energy consumption per capita on economic growth is in the low energy intensity regime. a comparison of models 1 and 2 shows that the energy intensity threshold level is 0.68 in the five countries studied and 0.44 in the net energy exporting countries. according to the energy intensity levels, the coefficient of the effect of energy consumption per capita on economic growth is 1.298 in the net energy exporting countries in the low energy intensity regime. this rate was 0.816 when all five countries in transition were included in the analysis. on the other hand, in the high energy intensity regime, the coefficient of this effect is 0.588 in all five countries and −0.217 in the energy exporting countries. thus, the marginal positive effect of energy consumption per capita on economic growth is higher in the energy exporting countries compared to the five countries in transition in the low intensity regime. in the high-energy intensity regime, the marginal negative effect of energy consumption per capita on economic growth is higher in the five countries in transition than in the energy exporting countries. table 3: energy consumption and economic growth estimated threshold value (tpes/y) model 1 model 2 ŷ 0.68*** 0.44*** 95% confidence interval [0.26, 0.71] [0.24, 0.72] effect of energy consumption per capita (dec) 1β̂ 0.816*** (0.136) 1.298*** (0.292) 2β̂ −0.588* (0.357) −0.217 (0.222) effect of control variables initialit −1.774 (4.901) 7.843* (4.426) igdpit 0.076** (0.047) 0.085** (0.057) dlabit 0.073 (0.773) −0.574 (0.652) totit 0.157*** (0.044) 0.167*** (0.051) sdtotit −60.031*** (22.085) −20.872 (19.983) openit 3.728*** (1.103) 2.772** (1.260) sdopenit 24.467 (27.175) 19.320 (51.087) πit −0.010*** (0.003) −0.015*** (0.004) 1δ̂ 14.969*** (4.291) 5.220 (3.88) number of observations ˆtpes/y y≤ 86 37 ˆtpes/y y≤ 24 51 number of countries 5 4 the table shows the results for the dynamic panel threshold model. all available lags of the dependent variable were used as instruments in the analysis. standard errors are given in parentheses. *,**,*** indicate significance at 10%, 5% and 1% levels, respectively. p values are obtained using 1000 bootstrap replications, gdp: gross domestic product figure 2: sum of squared of errors of the threshold values (a) model 1, (b) model 2 a b aydın and esen: does too much energy consumption harm economic growth for turkish republics in the transition process? new evidence on threshold effects international journal of energy economics and policy | vol 7 • issue 2 • 2017 41 5. conclusion and discussion energy is one of the basic requirements for economic and social development of a country. however, the uneven distribution of energy resources around the world has caused many countries to rely heavily on outside sources to meet their energy needs. energy demands of such countries increase depending on their developing economies and changing socio-economic structures. because the turkic republics are rich in energy reserves, the world’s increasing energy demand turns out to be advantageous for these countries. therefore, the energy industry constitutes the basis of the economies of these countries. the revenues from the energy industry have a large share in both public and export revenues. moreover, such energy potential provides these countries with a great advantage in achieving economic growth and expanding into international markets. the high energy potential in the region provides the opportunity to attract foreign capital to these countries. after gaining independency, the turkic republics started to use their high energy potential to provide the necessary resources for the transition process and deal with the problems associated with this process of change. since then, the energy trade has been an “engine of growth” for these countries. however, such energy potential cannot be viewed as a resource that will make a contribution only to the export potential. the resources obtained from the energy industry must be channeled to the production activities and investments required for economic development, and production must be moved to industries with high added value that require high technology. in this way, energy demand will show an increase in these countries as the economy grows and living standards improve. this process brings attention to the importance of energy consumption based on economic growth and the relationship between energy consumption and economic growth. in this sense, in the present study, the relationship between energy consumption and economic growth and the effects of energy intensity threshold value on this relationship were examined using annual data for the 1991-2012 period for five turkic republics undergoing a transition from a centrally planned economy to a free market economy following the collapse of the soviet union at the end of the 1980s. to this end, we used the dynamic panel threshold model developed by kremer et al. (2013) by extending hansen’s (1999) static model for endogenous estimators. the findings prove that a non-linear relationship exists between energy consumption and economic growth in the transition economies in the long term. they further reveal that an energy consumption rate above a certain energy intensity level will affect economic growth adversely in these transition economies. the estimated threshold value was found to be 0.68 for all transition economies examined in this study and 0.44 in the net energy exporting countries. the findings support the assumption that energy consumption below the threshold value has an increasing effect on economic growth. moreover, we believe that this study will guide future studies by revealing the importance of the energy intensity threshold level in the relationship between energy consumption and economic growth. this paper show that energy efficiency efforts have significant potential savings associated with them and are a cost-efficient way to reduce the emissions. the effective and efficient use of energy in all phases, from energy generation to consumption, as well as the necessary steps to ensure its effective and efficient use, are a must for achieving a sustainable competitive economic structure in all countries, even if they are net energy exporters rich in resources or net energy importers lack of resources. therefore, even if the majority of the turkic republics in transition do not have problems in terms of energy reserves, they should still realize strategies and policies that include measures to increase the efficiency and effectiveness of the use of energy resources in order to speed up their economic development, achieve their sustainable growth targets, and improve their living standards. references acaravci, a., ozturk, i. (2010a), electricity consumption-growth nexus: evidence from panel data for transition countries. energy economics, 32(3), 604-608. acaravci, a., ozturk, i. (2010b), on the relationship between energy consumption, co 2 emissions and economic growth in europe. energy, 35(12), 5412-5420. akarca, a.t., long, t.v.iind. (1980), notes and comments on the relationship between energy and gnp: a reexamination. the journal of energy and development, 5(2), 326-331. akinlo, a.e. (2008), energy consumption and economic growth: evidence from 11 sub-sahara african countries. energy economics, 30(5), 2391-2400. altınay, g., karagöl, e. (2004), structural break, unit root, and the causality between energy consumption and gdp in turkey. energy economics, 26(6), 985-994. altınay, g., karagöl, e. (2005), electricity consumption and economic growth: evidence from turkey. energy economics, 27(6), 849-856. alvarez, j., arellano, m. (2003), the time series and cross-section asymptotics of dynamic panel data estimators. econometrica, 71(4), 1121-1159. apergis, n., payne, j.e. (2010), energy consumption and growth in south america: evidence from a panel error correction model. energy economics, 32(6), 1421-1426. arellano, m., bover, o. (1995), another look at the instrumental variable estimation of error-components models. journal of econometrics, 68(1), 29-51. asafu-adjaye, j. (2000), the relationship between energy consumption, energy prices and economic growth: time series evidence from asian developing countries. energy economics, 22(6), 615-625. aydin, c., esen, ö. (2016), threshold effects of energy consumption on economic growth in turkey. journal of environmental management and tourism, 3(15), 370-382. bayrak, m., esen, ö. (2014), türkiye’nin enerji açiği sorunu ve çözümüne yönelik arayişlar. [turkey’s problem of energy deficit and recommendations for its solution]. atatürk üniversitesi i̇ktisadi ve i̇dari bilimler dergisi, 28(3), 139-158. bick, a. (2010), threshold effects of inflation on economic growth in developing countries. economics letters, 108(2), 126-129. burbidge, j., harrison, a. (1984), testing for the effects of oil-price rises using vector autoregressions. international economic review, 25(2), 459-484. aydın and esen: does too much energy consumption harm economic growth for turkish republics in the transition process? new evidence on threshold effects international journal of energy economics and policy | vol 7 • issue 2 • 201742 caner, m., hansen, b.e. (2004), instrumental variable estimation of a threshold model. econometric theory, 20(5), 813-843. cheng, b.s. (1995), an investigation of cointegration and causality between energy consumption and economic growth. the journal of energy and development, 21(1), 73-84. cheng, b.s., lai, t.w. (1997), an investigation of co-integration and causality between energy consumption and economic activity in taiwan. energy economics, 19(4), 435-444. dagher, l., talar, y. (2012), the causal relationship between energy consumption and economic growth in lebanon. energy policy, 50, 795-801. demirkan, h. (1993), orta asya türk cumhuriyetleri yer altı kaynakları potansiyeline yaklaşım [an outlook on the underground sources of the central asian turkic republics]. the 13th mining congress of turkey. p385-395. drukker, d., gomis-porqueras, p., hernandez-verme, p. (2005), threshold effects in the relationship between inflation and growth: a new panel-data approach. mpra working papers, wp. no. 38225. eden, s.h., hwang, b.k. (1984), the relationship between energy and gnp: further results. energy economics, 6(3), 186-190. erol, u., yu, e.s. (1987), on the causal relationship between energy and income for industrialized countries. the journal of energy and development, 13(1), 113-122. esen, o. (2016), security of the energy supply in turkey: prospects, challenges and opportunities. international journal of energy economics and policy, 6(2), 281-289. esseghir, a., khouni, l.h. (2014), economic growth, energy consumption and sustainable development: the case of the union for the mediterranean countries. energy, 71, 218-225. fisher-vanden, k., jefferson, g.h., liu, h., tao, q. (2004), what is driving china’s decline in energy intensity? resource and energy economics, 26(1), 77-97. ghali, k.h., el-sakka, m.i.t. (2004), energy use and output growth in canada: a multivariate cointegration analysis. energy economics, 26(2), 225-238. ghosh, s. (2002), electricity consumption and economic growth in india. energy policy, 30(2), 125-129. glasure, y.u., lee, a.r. (1998), cointegration, error-correction, and the relationship between gdp and energy: the case of south korea and singapore. resource and energy economics, 20(1), 17-25. gomulka, s. (1990), the theory of technological change and economic growth. london: routledge. greene, w.h. (2000), econometric analysis. 5th ed. usa: prentice hall. hamilton, j.d. (1983), oil and the macroeconomy since world war ii. journal of political economy, 91(2), 228-248. hansen, b.e. (1999), threshold effects in non-dynamic panels: estimation, testing, and inference. journal of econometrics, 93(2), 345-368. available from: http://www.dx.doi.org/10.1016/s03044076(99)00025-1. hansen, b.e. (2000), sample splitting and threshold estimation. econometrica, 68(3), 575-603. herrerias, m.j., joyeux, r., girardin, e. (2013), short-and long-run causality between energy consumption and economic growth: evidence across regions in china. applied energy, 112, 1483-1492. hondroyiannis, g., lolos, s., papapetrou, e. (2002), energy consumption and economic growth: assessing the evidence from greece. energy economics, 24(4), 319-336. huang, b.n., hwang, m.j., yang, c.w. (2008), does more energy consumption bolster economic growth? an application of the nonlinear threshold regression model. energy policy, 36(2), 755-767. iyke, b.n. (2015), electricity consumption and economic growth in nigeria: a revisit of the energy-growth debate. energy economics, 51, 166-176. kavak, k. (2005), energy efficiency in the world and turkey and investigation of energy efficiency in turkish industry. ankara: state planning organization (turkey). dpt-2689. available from: http://www.dpt.gov.tr/docobjects/download/3226/enerji.pdf. [last accessed on 2012 oct 10]. khan, m.s., ssnhadji, a.s. (2001), threshold effects in the relationship between inflation and growth. imf staff papers, 48(1), 1-21. kraft, j., kraft, a. (1978), on the relationship between energy and gnp. journal of energy and development, 3(2), 401-403. kremer, s., bick, a., nautz, d. (2013), inflation and growth: new evidence from a dynamic panel threshold analysis. empirical economics, 44(2), 861-878. leach, g., obermair, j.l., hoffmann, g.m.l. (1986), energy and growth. england: butterworth publishers. lee, c.c., chang, c.p. (2007), the impact of energy consumption on economic growth: evidence from linear and nonlinear models in taiwan. energy, 32(12), 2282-2294. liao, h., fan, y., wei, y.m. (2007), what induced china’s energy intensity to fluctuate: 1997-2006? energy policy, 35(9), 4640-4649. lise, w., montfort, k.v. (2007), energy consumption and gdp in turkey: is there a co-integration relationship? energy economics, 29(6), 1166-1178. masih, a.m., masih, r. (1996), energy consumption, real income and temporal causality: results from a multi-country study based on cointegration and error-correction modelling techniques. energy economics, 18(3), 165-183. mozumder, p., marathe, a. (2007), causality relationship between electricity consumption and gdp in bangladesh. energy policy, 35(1), 395-402. odhiambo, n.m. (2009), energy consumption and economic growth nexus in tanzania: an ardl bounds testing approach. energy policy, 37(2), 617-622. ouedraogo, n.s. (2013), energy consumption and economic growth: evidence from the economic community of west african states (ecowas). energy economics, 36, 637-647. ozturk, i., aslan, a., kalyoncu, h. (2010), energy consumption and economic growth relationship: evidence from panel data for low and middle income countries. energy policy, 38(8), 4422-4428. öztürkler, h. (2009), ortadoğu ülkelerinin enerji kaynaklarinin öneminin ekonomi-politik bir değerlendirmesi. [a political economic evaluation on the importance of energy resources in middle east]. ortadoğu analiz, 1(7-8), 74-79. paul, s., bhattacharya, r.n. (2004), causality between energy consumption and economic growth in india: a note on conflicting results. energy economics, 26(6), 977-983. pirlogea, c., cicea, c. (2012), econometric perspective of the energy consumption and economic growth relation in european union. renewable and sustainable energy reviews, 16(8), 5718-5726. ramirez-rondán, n.r. (2013), essays on dynamic panel threshold models. phd thesis, university of wisconsin-madison. roodman, d. (2009), a note on the theme of too many instruments. oxford bulletin of economics and statistics, 71(1), 135-158. salahuddin, m., gow, j., ozturk, i. (2015), is the long-run relationship between economic growth, electricity consumption, carbon dioxide emissions and financial development in gulf cooperation council countries robust? renewable and sustainable energy review, 51, 317-326. shahbaz, m., lean, h.h. (2012), the dynamics of electricity consumption and economic growth: a revisit study of their causality in pakistan. energy, 39(1), 146-153. shiu, a., lam, p.l. (2004), electricity consumption and economic growth in china. energy policy, 32(1), 47-54. soytas, u., sari, r. (2003), energy consumption and gdp: causality aydın and esen: does too much energy consumption harm economic growth for turkish republics in the transition process? new evidence on threshold effects international journal of energy economics and policy | vol 7 • issue 2 • 2017 43 relationship in g-7 countries and emerging markets. energy economics, 25(1), 33-37. stern, d.i. (2000), multivariate cointegration analysis of the role of energy in the us macroeconomy. energy economics, 22(2), 267-283. stern, d.i., cleveland, c.j. (2004), energy and economic growth. rensselaer working papers in economics. wp. no: 0410. usa: rensselaer polytechnic institute. wesseh, p.k., zoumara, b. (2012), causal independence between energy consumption and economic growth in liberia: evidence from a non-parametric bootstrapped causality test. energy policy, 50, 518-527. wolde-rufael, y. (2006), electricity consumption and economic growth: a time series experience for 17 african countries. energy policy, 34(10), 1106-1114. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. . international journal of energy economics and policy | vol 10 • issue 3 • 2020 471 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(3), 471-475. toward developing energy star rating development in jordan majeda yakhlef1, yazeed yasin ghadi2, ali m. baniyounes1*, mazen alnabulsi1, eyad radwan1 1department of architecture and electrical engineering, applied science private university, jordan, 2software engineering and computer science, al ain university of science and technology, uae. *email: al_younes@asu.edu.jo received: 31 march 2019 accepted: 15 december 2019 doi: https://doi.org/10.32479/ijeep.7982 abstract the objective of this article is to provide an efficient means of enforcing green building in jordan, the middle east. the paper is proposing assessment tool of energy star rating scheme and also explaining its role for achieving sustainable development during buildings lifecycle and hence reducing energy and water usage. the scheme development will remove considerable environmental, social and economic issues as jordan is a country that renowned for its poor energy and water resources. the article provides technical aspects, means, technologies and processes for proposing and implementation green star ratings for buildings. the star ratings are based on integrating renewable energy technologies, water recourses and its consumption management and waste recycling and its management throughout the buildings’ life cycle including its design, installation and operation. keywords: energy star ratings, energy and water, sustainable energy, environment jel classifications: k32, o13 1. introduction in jordan, buildings and building’s sector including domestic and commercial buildings is responsible for large portion of energy consumption. energy consumption in buildings consumes up to 40 of total energy usage around the globe baniyounes et al. (2012) and this is expected to increase by almost 20% in the next two decades as announced by fumo and biswas (2015). buildings heating, ventilation, and air conditioning (hvac) is the biggest energy consumer which accounts for almost 35% of total energy consumption within building kordjamshidi et al. (2005) and this is due to the increase in using energy in residential buildings. the previous fact is show how it is necessary to look for energy efficient architectural design and development which is based on renewable energy and passive energy harvesting techniques. after fuel sore prices researchers have emphasized the obligation of sustainable and energy efficient development in order to lessen energy usage and also minimizing its negative impact on the environment by reducing greenhouse gas (ghg) emissions. accordingly, priority and advantages are always provided to energy efficient design and development in both residential and commercial buildings sector. nowadays there are significant numbers of computer aided software and programs are used to project, evaluate and estimate energy usage during design phase. those software packages are used in order to determine best scenario possible of design that used minimum energy such as revit, three dimension (3d) studios and etc. in this article, buildings energy star ratings (besr) is highly encouraged and recommended to be developed and used extensively specially when obtaining buildings permit and necessary licensing of operation as this will force developers and stakeholders to save energy and force sustainable designs throughout the country taking into account here that the software packages and computer programs are built in a way that it does meet the country codes and policy in regards energy and energy consumption and hence its negative impact on the environment which is represented by ghg emissions. a standard besr is able to supply necessary data and information about buildings’ sustainable and energy efficient design and its this journal is licensed under a creative commons attribution 4.0 international license yakhlef, et al.: toward developing energy star rating development in jordan international journal of energy economics and policy | vol 10 • issue 3 • 2020472 level (how efficient or how sustainable is the design) for example a one-star rating is a building that achieve minimal energy efficiency design requirement and 6-star rating is the building design that it does consider all requirements of energy and sustainability requirements design. in short, the star rating task will be carried on by assessing energy efficiency compared to standard buildings design and development also the system will be able to compare between buildings in regards of its gross energy and water usage necessities. consequently, an efficient buildings’ star rating scheme will inspire architects, developers and designers to focus on energy efficiency and sustainability in their design, and to take advantages of renewable and passive harvesting and preserving techniques which currently without compromising indoor thermal comfort and indoor air quality (iaq). throughout literature there are a numerous amount of research, articles and activities including websites development. worth mentioning have publish an article in regards how architects and designer have better understanding on energy efficiency and the sustainable measures and conservation shaikh et al. (2017). also zuo et al. (2017) has developed a star rating guides for concrete buildings. in addition, illankoon et al. (2017) have showed an important about green buildings evaluation from life cycle view. jordan is classed between those countries with minimal energy and water resources and hence lowest per capita base. the situation is getting worse due to demographic growth as a result of refugee flux from neighboring countries e.g. syria and iraq the situation is expected to get poorer. the scarcity of energy recourses in jordan is the country most significant restrains and challenge as the country’s growth and development is absolutely depends on energy availability and hence very important factor of economic improvement. however, the most of research activities hardly mention the situation in the middle east specially jordan. accordingly, this article will discuss and propose a new building, star ratings which is based on energy efficiency, water management, waste management and sustainability. the main intention of this research study is to evaluate the suitability of buildings by applying star rating schemes in buildings. this rating is evaluated based on the installation, operation, consumption and monitoring of energy, water resources and waste management data. knowing that, green or sustainable building is buildings that consider certain criteria and techniques are integrated in buildings which conserve energy, water resources and waste management, building architecture, landscaping, maintenance and housekeeping in order to guarantee sustainable future. these criteria and techniques will include sustainability measure on buildings planning, design and installation, buildings architecture including nature and location, water and energy resources, the usage of renewable and passive technologies, and related ghg emissions. 2. development of buildings’ energy rating evaluating scheme buildings energy rating evaluating scheme is a basic measure that assess energy efficiency of newly constructed or existing building and its associated ghg emission. the assessment basis is including energy will be used by lighting, hvac, water pumping and firefighting system and also its associate cost, emissions and its projected efficiency. besr are applied widely and effective in various countries such as australia and new zealand le et al. (2018). besrs are constructed to project energy consumption and its ghg requirements in order to issue a certificate. overall besrs are regarded whilst looking for an optimum objective in order to reduce energy consumption and its related standards throughout applying sets of energy efficient tools and scenarios. these tools are regarded as inclusive environmental evaluation scheme such as breeam (united kingdom) breem (2019), gbtool (canada) gu (2018), leadership in energy and environmental design (leed) (us) leed (2019) and etc. the previously mentioned bodies assessment tools and scenarios are based on life cycle analysis and for the buildings’ sectors. the majority of these processes have intended to be utilized for the process of choosing and deciding buildings’ design, materials, energy supply and resources including renewable energy, waste management including recycling and transport ali and al nsairat (2009). in addition to the previously mentioned bodies there are a significant number of software and computer aided tools applied in this field such as energyplus, trnsys, revet, 3d studio, and etc. the most of those software packages utilize factual models, in a way that the buildings data and its technical specifications are evaluated digitally and then added on and implemented in a mathematical model in order to simulate the buildings’ indoor thermal and visual comfort kordjamshidi et al. (2005). also, all information and data about the local climatic are utilized and modeled and then its effect on the building climate and its energy usage can be evaluated and computed based on projected conditions and activity so indoor occupation density and indoor activity are both considered. the local governmental and unions authorities in jordan are all invited to develop bsers and enforce this bser in all future design and developments. currently there are a wide range of buildings’ energy and water usage easement tools are existed. those tools are ranged from simple tools to very sophisticated ones that able to simulate the whole of the building and hence virtual reality simulation tools. 3. buildings star rating structure globally, the common method of buildings’ star ratings index is based on energy usage, energy efficiency, water usage and water recycling and waste management. this rating index will mostly depend on energy usage. commercial buildings use the most of energy in every single local markets taking into account that, more than 40% of this energy is used by buildings, hvac system baniyounes et al. (2013) taking into account here that index completely depends on the conditioned space gross area and its volume. it has been reported by lo (1995) that smaller areas and volume is the main factor of hvac systems energy usage. one of the reasons behind the previously mentioned fact that the buildings’ envelop and volume ratio as small buildings have bigger ratio kordjamshidi et al. (2005). in addition giridharan and emmanuel (2018) have reported that contents and textile heat flux per floor area unit is higher in small houses than big ones. according to mattoni et al. (2018) and giridharan and emmanuel yakhlef, et al.: toward developing energy star rating development in jordan international journal of energy economics and policy | vol 10 • issue 3 • 2020 473 (2018) the buildings’ cooling load conditions of bigger buildings with higher energy star ratings e.g. 5-or 4-star rating were found to be significantly lower to buildings with low 3-star ratings, which becomes lately applicable in too many countries around the globe. 3.1. buildings sustainable design and planning with the intention to reduce the effect of buildings development negative impact on the environment and local areas, several policies and recommendations were developed as a guide for eres such as segregation of buildings’ by constructing and installing dust filter around the construction site area in order to avoid the environment air pollution and the spell of contamination resulted from construction. in addition, good quality soil should be dig out, and stored in order to preserve it outside the concerned buildings’ construction site. additionally, and in order to protect trees, a loss control mechanism must be implemented also trying the best possible way to keep around the construction site safe. also, eres must seek the increment of buildings’ structural strength meanwhile and minimizing heat effect that will be caused by hard pavement and concrete usage throughout buildings. it is worth mentioning her that vyas et al. (2014) have advised that gross paving throughout newly constructed buildings should not exceed more than 17%, also not more than 50% of the pavement areas protected by sun blockers and trees. eres also must mind irrigation water so it should also be reduced to around 50%. 3.2. energy conservation buildings’ energy conservation is defined as the all sort of activity that has been made in order to minimize energy consumption in buildings. this could be done throughout the buildings by consuming energy efficiently meanwhile keeping in mind lowering the volume of required services expected to be used such as reducing hvac and lighting load. energy conservation minimizes the usage of fossil fuel and also minimize its negative impact on the environment. additionally, it lesser buildings’ operational cost by cutting off fossil fuel energy costs. moreover, energy conservation can be achieved by minimizing waste and reducing energy losses, developing energy efficient technical systems, its maintenance and operation. 3.3. renewable energy technologies renewable energy technologies that can be used within buildings’ applications and systems are solar energy includes thermal and photovoltaic, wind energy, geothermal energy, as well as biomass energy. in order to select proper renewable energy system to operate to existing building or to newly designed or constructed building, it is significant to investigate various existing conditions e.g. technologies market availability, available renewable energy resources, the technologies’ required space and available space for technologies’ within the building, energy cost from author providers, tax and incentives availability based on using renewable energy technologies, buildings’ aesthetics and its unique architectural features. 3.3.1. photovoltaic systems (pv) pv panels are a technology where the sun radiation is converted into electricity. in pv systems, solar panels are connected together to make up what called solar modules. next solar modules are connected together to form what called solar arrays where they can be mounted on buildings’ roof or round it as shown in figure 1 sousa et al. (2019). a power inverter converts the direct current generated by the system into grid-quality alternating current electricity. 3.3.2. solar thermal energy the production of hot water and hot air using the sun power are economic, cost-competitive and environmentally friendly technique where there is no need for electricity or conventional fossil fuel for the production process. whether heating water or air, the heat is produced by solar collectors where the heat is absorbed by those collectors and then is transferred the heat to air or water. in some cases, especially when heating water, the hot is then is stored in a tank until used. the previously mentioned systems are classified upon the output temperature namely low collectors’ temperature e.g. flat plate collectors where output is ranged from 50°c to 90°c, medium collectors’ temperature e.g. evacuated tube collectors where output is ranged between 90°c and 250°c and high collectors’ temperature e.g. open trough collectors where output is above 250°c. despite the high temperature of the open trough collector’s temperature, the most suitable collectors in buildings are flat plate collectors and evacuated tube collectors as shown in figure 2 mesthrige and chan (2019). 3.3.3. other renewable energy recourses the other renewable energy recourses that can be are including wind energy and bioenergy. wind energy is generated by equal heating of the earth’s surface by the sun creating wind current. the wind current which comes in the form of motion or motion energy, can be exploited by wind turbines generating electricity using rotating blades. however, installing wind turbine in the top of buildings require mega structure requirements as well as big acoustic protection requirements due to the blades noise during movement accordingly using wind energy is not common. bioenergy depends on organic materials e.g. as plantations, excess from farming, agriculture and forestry, as well as the organic matters of metropolitan including manufacturing wastes which normally utilized in order to generate fuel, and thus energy. using bioenergy within buildings is possible but, the process requires big capital that will increase the cost on stakeholders. 3.3.4. mechanical ventilation versus natural ventilation of buildings rating index naturally ventilated buildings main advantages are to reduce energy consumption while improving iaq. iaq mainly depends on using and circulating outdoor fresh air inside building. the more of fresh air is used and circulated, the better is iaq. buildings’ natural ventilation performance is mainly depending on various conditions such as winds’ speed and winds’ direction, mostly round reference buildings causing what known as microclimate change hang et al. (2012). if a new large-scale tower is placed amongst a large city of low-rise buildings, the effect of the new building on the uhi, on the wind in the street and the structure of the lapse rate of temperatures is problematic. this paper is exploring what the literature can tell us on this subject hayter and kandt (2011). yakhlef, et al.: toward developing energy star rating development in jordan international journal of energy economics and policy | vol 10 • issue 3 • 2020474 3.3.5. water management and conservation water and water availability are a prime element for mankind survivor and his existence as well as people important several interests around the globe. jordan as a country is renowned for water scarcity which mandate the importance of water portable water generation and the possibility of its recycling and thus, this will lead to reduction in energy usage and also reduction of ghg emissions and its negative impact on the environment. the previous highlighted fact makes water usage conservation and management including its recycling a very important factor of sustainable development and its assessment. buildings are a big water consumer which accounts for about about 16% of freshwater usage. consequently, enormous weight is set to water usage, conservation, management and efficiency as the at most sustainability buildings rating factor around the globe. consequently, there are enormous buildings’ sustainability evaluation indicator tools sousa et al. (2019). water sustainability indicators concentrate on various fields of buildings’ sustainable developments also they are planned to fit most of existing developed buildings or newly constructed ones mesthrige and chan (2019). an example of those water sustainability indicators or rating schemes are building research establishment (breem) environmental assessment method which was established in the year 1992, followed by leed which was initiated in the united states of america in the year 1996 and as well the establishment of green star australia in the year 2003 and etc. 3.3.6. waste management sustainable buildings as well as renowned for their environmentally friendly and green structuring in addition to its consumables resources waste efficient management during the buildings’ lifecycle which range from between the design process, construction and installations, readiness and operation, scheduled and emergency maintenance, after words renovation, and usable waste and its management. nowadays the environment problems and the distress for sustainability is inspiring efficient consumption and management of energy, water and consequent waste management, to guarantee the avoidance of any type of waste, implement environmentally reasonable and economic as well as environmentally friendly building’s execution including its design, the process of construction and required operation. 4. conclusion this study has proposed initial ratings regarding buildings’ energy, water resources and waste management, building architecture, landscaping, maintenance and housekeeping status in order to encourage more sustainable and green building in jordan, the middle east. the purpose of buildings green star ratings is to encourage the development of the global built in environment regarding sustainability and environmentally friendly installations given significant priority to energy, water resources and waste management, building architecture, landscaping, maintenance and housekeeping status of buildings. the study has highlighted the base that should be implemented in sustainable buildings and thus its evaluation based on energy including the utilization of renewables, mechanical and natural ventilation, water management, and waste management. in addition, this study provides the at most aspects of all designs of green and sustainable buildings developments and its ratings in jordan. introducing criteria for star green buildings’ ratings will significantly push through towards enhancing an improve buildings’ energy and water management performance and hence reducing nonenvironmental friendly ghg without comprising indoor and outdoor comfort condition in order to save energy and water. references ali, h.h., al nsairat, s.f. (2009), developing a green building assessment tool for developing countries–case of jordan. building and environment, 44(5), 1053-1064. baniyounes, a.m., liu, g., rasul, m.g., khan, m.k. (2012), solar desiccant cooling and indoor air quality for institutional building in subtropical climate. phuket, thailand: in proceedings of the iasted international conference, power and energy systems (asiapes 2012). baniyounes, a.m., rasul, m.g., khan, m.m.k. (2013), experimental assessment of a solar desiccant cooling system for an institutional figure 1: applied science private university solar roofs (faculty of engineering) figure 2: evacuated tube collectors yakhlef, et al.: toward developing energy star rating development in jordan international journal of energy economics and policy | vol 10 • issue 3 • 2020 475 building in subtropical queensland, australia. energy and buildings, 62, 78-86. breem. (2019), what is breeam? available from: https://www. breeam.com. [last cited on 2019 jan 01]. fumo, n., biswas, m.r. (2015), regression analysis for prediction of residential energy consumption. renewable and sustainable energy reviews, 47, 332-343. giridharan, r., emmanuel, r. (2018), the impact of urban compactness, comfort strategies and energy consumption on tropical urban heat island intensity: a review. sustainable cities and society, 40, 677-687. gu, z. (2018), an analysis of architectural and urban planning strategies for developing energy efficient cities in china. diss. kth royal institute of technology. doctoral thesis. hang, j., li, y., sandberg, m., buccolieri, r., di sabatino, s. (2012), the influence of building height variability on pollutant dispersion and pedestrian ventilation in idealized high-rise urban areas. building and environment, 56, 346-360. hayter, s.j., kandt, a. (2011), renewable energy applications for existing buildings. national renewable energy laboratory. conference paper. illankoon, i.c.s., tam, v.w., le, k.n., shen, l. (2017), key credit criteria among international green building rating tools. journal of cleaner production, 164, 209-220. kordjamshidi, m., king, s., prasad, d. (2005), towards the development of a home rating scheme for free running buildings. proceedings of the 43rd australian and new zealand solar energy society: renewable energy for a sustainable future—a challenge for a post carbon world. le, k.n., tran, c.n.n., tam, v.w.y. (2018), life-cycle greenhousegas emissions assessment: an australian commercial building perspective. journal of cleaner production, 199, 236-247. leed. (2019), leed is green building. available from: https://www. new.usgbc.org/leed. lo, c.y. (1995), small property versus big government: social origins of the property tax revolt. london: university of california press. mattoni, b., guattari, c., evangelisti, l., bisegna, f., gori, p., asdrubali, f. (2018), critical review and methodological approach to evaluate the differences among international green building rating tools. renewable and sustainable energy reviews, 82, 950-960. mesthrige, j.w., chan, h.t. (2019), environmental certification schemes and property values: evidence from the hong kong prime commercial office market. international journal of strategic property management, 23(2), 81-95. shaikh, p.h., nor, n.b.m., sahito, a.a., nallagownden, p., elamvazuthi, i., shaikh, m.s. (2017), building energy for sustainable development in malaysia: a review. renewable and sustainable energy reviews, 75, 1392-1403. sousa, v., silva, c.m., meireles, i. (2019), performance of water efficiency measures in commercial buildings. resources, conservation and recycling, 143, 251-259. vyas, s., ahmed, s., parashar, a. (2014), bee (bureau of energy efficiency) and green buildings. international journal of research, 1(3), 23-32. zuo, j., pullen, s., rameezdeen, r., bennetts, h., wang, y., mao, g., duan, h. (2017), green building evaluation from a life-cycle perspective in australia: a critical review. renewable and sustainable energy reviews, 70, 358-368. . international journal of energy economics and policy | vol 8 • issue 3 • 20188 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(3), 8-13. development of “active consumer” concept on energy market irina a. firsova1, dinara g. vasbieva2*, andrey v. losyakov3, viktoriia s. arhipova4, andrey a. pavlushin5 1department of corporate finance and corporate governance, financial university under the government of the russian federation, moscow, russia, 2department of foreign languages, financial university under the government of the russian federation, moscow, russia, 3department of state legal and criminal law disciplines, plekhanov russian university of economics, moscow, russia, 4department of municipal law, peoples’ friendship university of russia (rudn university), moscow, russia, 5department agro technologies, machines and life safety, ulyanovsk state agrarian university named after p.a. stolypin, ulyanovsk, russia. *email: dinara-va@list.ru abstract the paper investigates a new approach to interaction of all participants on the energy market. an active consumer, as a participant of the energy market, has technical capabilities for optimization of their energy consumption, and determines whether “to produce” or “to buy” electrical energy on the market by themselves. the active consumer’s profile reflects their ability to optimize the electrical energy consumption schedule to improve the economic efficiency of consumption and reduce the cost of the electrical energy consumed. in the concept proposed in this paper, the active consumer is considered as a partner of the energy market entities. this brings about a change in the market regulators and participants’ behavior and their transition from the concept of cost management to the concept of interaction with consumers, involving them in the value chain. a significant difference in the cost of electrical energy for domestic and foreign industrial companies, due to the development of new technologies in the energy sector, leads to a change in the participants’ behavior. within the framework of the active consumer concept, we propose a process model for the participants’ behavior in the energy market, which presents the economic benefits to all participants during a particular period of time. keywords: active consumer, energy market, demand-side management, economic benefits jel classifications: d24, q43, m31 1. introduction electrical and heat energy is a commodity whose parameters are initially defined. participants of the energy market wish to actively manage not only production, but also distribution of electrical energy, which gives them the opportunity to take the part of both consumers and producers of electrical energy at the same time. also, the consumers’ behavior is influenced by the development of new technologies. the literature review made it possible to classify the main characteristics of the “active consumer:” • management of their own generating capacities: assessment of the degree of capacity, the amount of electrical energy produced for their own consumption and supplied to the market (haas and loew, 2012) • availability of the processing systems capable of changing the capacity, own generation, energy storage (zolotova, 2016) • management of the energy storage mode, including that generated by their own generating capacities (ryapin, 2013; jiang and fei, 2011) • determination of conditions for loading their own capacity (if any), for submitting a bid to buy/sell electrical energy in the wholesale and retail markets (rodin, 2011; kunz, 2016). because of an active consumer appearance in the market, there are problems of providing consumers with the opportunity to change by themselves the amount of electrical energy they buy, to choose the level of reliability and the quality based on the balance of their needs and the capabilities of the energy system. these were reported by volkova et al. (2011); bushuev (2013); unep collaborating center, frankfurt school of finance and management, germany (2015). firsova, et al.: development of “active consumer” concept on energy market international journal of energy economics and policy | vol 8 • issue 3 • 2018 9 the purpose of this article is to generalize the conceptual provisions of building a competitive active consumer and identify the main factors of the energy market, which has an impact on the active consumer’s behavior. 2. the concept of an active consumer in the energy system the concept of the “active” consumer in the energy system is based on the energy consumption management mechanisms, which are divided into long-term and short-term actions (scenario forecasts for the development of the electric power sector for the period up to 2030). mechanisms for improving energy efficiency are long-term and short-term. also, such mechanisms are nominally divided into static and dynamic response. demand-side management, as an example of a static response mechanism, is currently a developed area. the program of action is aimed at stimulating energy-efficient consumption. the dynamic response mechanism is characterized by the consumers’ reaction and includes planned or contracted actions, which contribute to the stability of the energy system and its balancing or are required in case of network failures. the main problem is consumer retention, as well as ensuring their motivation and ability to participate in the program. active actions allow consumers to react, for example, to high prices set in the market. in this case, consumers react to information coming from the market, and decide to change the model of their behavior in response to these signals. the problem of an active consumer concept in the concentration of most energy markets is on the supply side, access issues and lack of information for participants from the demand side, which makes their participation difficult and unprofitable. knyaginin (2010) was one of the first to investigate this problem. within the framework of the active consumer concept, we propose a process model for the participants’ behavior in the energy market, which presents the economic benefits to all participants during a particular period of time. 3. literature review the main solutions to the above problems in the concept of the active consumer were considered by both foreign and russian researchers: • demand processes and distributed generation control, management of the energy storage regime, including that generated by generating capacities (jiang and fei, 2011) • energy conversion influence on energy markets and capacity management (haas and loew, 2012) • cross-subsidization in the electric power industry (rodin, 2011; zolotova, 2013; ryapin, 2013; kunz, 2013; np “market council,” 2016) • provision of science-driven growth of the electric power industry with the participation of an “active” consumer (volkova et al., 2011; bushuev, 2013; lujano-rojas et al., 2015) • processes of energy harvesting into energy system and transition to the creation of “microgrids” on the consumers’ side (grebenyuk and solov’ev, 2004; bresler, 2009; chubais, 2009; knyaginin, 2010; govorov, 2012; bushuev, 2013). these studies have tended to focus on its aspects rather than the problem of an active consumer of electrical energy. the analysis of theoretical studies and best practices shows that the problem of an active consumer of electrical energy is very acute and is the subject of economic and technical research. 4. materials and methods during the study the following methods were used: • theoretical methods: system analysis, synthesis, generalization, theoretical analysis of scientific, methodological and technical literature on the problem studied • empirical methods: analysis, monitoring, questioning, experiment. experimental work took place in several stages. at the first stage of the research (2017), the purpose and objectives of the study were defined and literature was selected and reviewed. at the emerging stage (2017), the analysis of the electrical and heat energy market was carried out, and the subject matter and the scope of the research were determined. the purpose of the control stage (2017–2018) was to develop proposals on the concept of an active consumer and evaluate the effectiveness of this concept. at the emerging stage (2017), the analysis of the electricity and heat energy market was carried out, and the subject matter and the scope of the research was determined. the objective of the control phase (2017–2018) was to develop proposals on the concept of an active consumer and to assess the effectiveness of this concept. 5. results the electrical energy market develops on the basis of protecting all participants’ interests, which is feasible provided that energy companies interact with active consumers by offering them load rate tariffs for electricity, capacity utilization and grid connection. tariffs help control the participants’ behavior in the energy market, which allows to create economic incentives for the formation of their behavior. for example, in order to stimulate necessary actions, tariffs are reduced, to prohibit unwanted behavior, they are increased. energy companies need analyze the firsova, et al.: development of “active consumer” concept on energy market international journal of energy economics and policy | vol 8 • issue 3 • 201810 active consumer’s behavior in the market in order to manage their demand. demand-side management is an integrated approach to interaction with the consumer, based on its active participation in the formation and regulation of the load including incentives for the “active” consumer (bushuev, 2013). demand-side management in the electrical energy market includes load flow control and accounting system, as well as pricing policy, i.e., the modification of tariffs and prices. in the world practice, several methods of load management have been developed, which are described in the works of foreign authors such as bresler (2009); davito et al. (2010) and in the report prepared by national energy technology laboratory demand “dispatch-intelligent demand for a more efficient grid” (2011), which reflect such aspects of demand-side management: • direct load control • load demand (supply) program or short covering program • time-of-use tariff • commercial/industrial options • interrupt programs • load-shedding • real-time pricing. there are a number of programs for load management. load demand programs or short covering programs are used in cases where the consumer can refuse to consume electrical energy at a high price. participation in this program allows the active consumer to obtain information about the prices for online purchases and to take appropriate decisions to manage peak loads by selling the unused energy back at current prices. currently, the program is being modernized to make it possible to send price signals and prevent speculation by active consumers through overstating planned loads and then re-selling intentionally excess electrical energy. the next type of programs are compulsory programs that are designed for whole segments of consumers, and all consumers are obliged to participate in them. for example, all consumers with a certain level of consumption may be are charged using time-of-use rates. the supplier’s income may not depend on compulsory programs, if the indicators are developed properly and the consumers’ behavior varies within reasonable limits. the whole system is built in such a way that active consumers who save money on time-of-use tariffs are compensated at the expense of consumers who pay more. if the peak demand decreases and the capacity servicing factors improve, all tariffs can be reduced in due course relative to their level without taking into account time-of-use tariffs. the industrial programs are peak load management programs, which are also available to industrial and retail consumers. the majority of participants in such programs are industrial consumers, who can interrupt operations for several hours or postpone them. besides, there are also consumers using standby generators that can withstand all or significant parts of the load. these include: systems interrupt program for hands-on integrated reliability; load-shedding programs “low-power mode;” real-time pricing program; load demand (supply) program or short covering program. experienced active consumers can include the supplier’s pricing scheme for the electrical energy in their energy management system. large price differences between periods with high and low prices can automatically cause large changes in electricity consumption. it should be noted that unlike existing real-time pricing (faria and vale, 2011), the transition to a smart grid also implies a decrease in the planning horizon in the spot market: for a balancing energy market the maximum approach to real-time mode (while the balancing energy market is now held every 4 h). active consumers’ voluntary participation in some technologically advanced smart grids can be stimulated by lower payments for participation. the incentive scheme for consumers depends on several factors, including: • type of the controlled equipment • level of control • average level of load reduction • level of load reduction. bonuses are paid through monthly loans to accounts for consumed services. installation of the necessary equipment and subscriber line charge is effected at the expense of the electrical energy supplier, at the expense of the consumer (both grid-connection onetime payment and in the form of interspaced in time charge), and jointly in the agreed proportion. discounts for the installation of equipment can be a significant factor stimulating the participation of the population in the program. the concept of an active consumer in making a decision to “buy” or “generate by themselves” electrical and heat energy has the following selling points: firstly, an important factor is the price for the electrical energy consumed from the grid and the formula for calculating it (type of tariff); secondly, availability of the own generation; thirdly, transmissibility of the own generation to the power grid; fourthly, the money equivalent of the profitability of the energy mode and, fifthly, the portability of time load equipment. the conceptual provisions for the construction of a competitive electrical energy market based on the capabilities of the ips aag (intellectual power system with active adaptive grid) of russia were spelled out by dorofeev and kuz’min in 2013. the developed range of tools is executed on the basis of ms excel, which makes it possible to carry out multiple calculations to evaluate the effectiveness of the active consumer in terms of the cost of consumed electrical energy in the case of its purchase from the wholesale energy market or in the case of own production. table 1 shows an example of the components of these tools. the calculations are made with the help of ms excel spreadsheet “calculations и result output.” during the calculation, the unit cost of electricity for the consumer is calculated without taking into account the elimination of cross-subsidization and taking into account the elimination of cross-subsidization. we examined the model of economic benefit to the active consumer of the energy market, which contains the following elements: • interval time of the load scheduling (a daily-load curve is built, t = 24 h per day) firsova, et al.: development of “active consumer” concept on energy market international journal of energy economics and policy | vol 8 • issue 3 • 2018 11 • the amount of equipment in pcs, included in the calculation of the loading schedule and the power consumed by this equipment per day; • loading matrix аn (columns of the matrix loading of equipment, and lines options for loading the equipment included in the schedule). elements of matrix аn, { }nrtc 0;1∈ correspond to the work mode, for r 1, r∈ and time t 1, t∈ , can be denoted as ( )n r 1,rn trt 1,t a = c ∈ ∈ . then the active consumer has an estimated total energy consumption at each time t as n n consum t tz 1 n n n= w c *p= ∑ , where ( )1 nz= z ,…..z is a vector of variables, corresponding to a set of equipment operating modes, n 1,n∈ ; n nz 1,r∈ ; consum np is a power capacity (kw) consumed by the n th unit of the equipment. it is important for an active consumer to express each equipment operating mode in the form of a money equivalent of costs or economic benefits (эrn) for purchasing electrical energy at a schedule r 1,r∈ and selected objects n 1,n∈ . in zero operation mode, when the equipment is completely off эrn = 0. in other cases эrn will show the required amount of energy costs for the amount of operating equipment n and its operating mode r. the money equivalent in the form of a sum of costs эrn will show the value of the work of each additional piece of equipment in the mode r. the active consumer can also calculate the money equivalent as the mathematical expectation of the price ci at the moment of time t according to the probability distribution p: эn(t) = ∑ici⋇p(ci,t) (8) where ci is the i th element of set c. expressing the operation mode as a set of time modes, we obtain: эn (r) = ∑jэ (rj) (9) where j is the time interval r. however, it is important to understand that the monetary evaluation of the economic benefits of any schedule of electrical energy consumption is individual and subjective. for example, it can depend on the operating schedule of the enterprise, the type of the products made and the specific type of equipment. an economic benefit can be estimated in various ways. however, in our opinion, the estimation based on the maximum possible volume of energy consumption per hour is of much interest. it is calculated as the nominal power consumed by the equipment multiplied by the number of days of the given period t. the ratio t i max r r will be an option of the price for the electrical energy ci in given the period t, and the money equivalent of the energy costs will be equal to the ratio: t i i i t max n i=1 r c * r d i∑= (10) if the active consumer has the opportunity to produce electrical energy, it is necessary to calculate and estimate the economic benefit of energy production using the own generation units table 1: composite blocks of model tools name ms excel sequence information on transmission service tariff, straight-line rate from the wholesale energy market (capacity) (hereinafter referred to as the wholesale market for electricity and power), energy supplier’s retail markup, as well as the volume of net electrical supply and the current level of cross-subsidization in entities by levels of voltage “source data” determined by model statement data on forecast indicators: annual average rate of inflation (cpi), the gas price growth rate (in accordance with the wholesale prices growth rate for all categories of consumers, except for the general public), the electricity prices growth rate of over the long-term “indices+const” determined by model statement as the parameters of the electrical energy consumer’s work, the consumer’s location is included the power receivers (electric consumers) in mw, utilization time per year, the voltage level of the electrical grid from which the consumer is powered, the choice of the power supply for the electric consumer from “own generation” or when working in the system. also there is an input of the cost of “own generation” in this block, as well as the annual amount of operating expenses required for the operation and maintenance of “own generation” “control terminal” determined by model statement/ automated settlement computed values. the calculation parameters are the choice of the payment period for capital investments made when creating an object of own generation, as well as the rate of return on invested capital provided by the investor. within the framework of this block, there is also an optional choice of the period for which the existing amount of cross-subsidization in the selected entity of the russian federation is to be liquidated “calculations и result output” “capex” automated settlement source: authors’ processing firsova, et al.: development of “active consumer” concept on energy market international journal of energy economics and policy | vol 8 • issue 3 • 201812 (distributed generation). the number of such units will be denoted by n, whose operating mode is g 1 , g∈ . assuming that the operating modes of the generators are different, it is possible to build the relationship between the unit cost of electrical energy produced by means of own generation cm (tmt) and the power output at every instant tmt. having drawn a graph of such a relationship, one can find the point of the minimum cost of electrical energy produced by using own generation unit. the total amount of generation of electrical energy g t mt g=1 w q= ∑ produced by own sources is divided into the quantity of electrical energy for own consumption and the quantity of electrical energy transferred to the energy grid ( )( )e e et tq q = q . costs of generating electricity by own generation source are calculated according to the formula ( ) ( ) g m mt g=1 w t = c t,q∑ . the cost of electrical energy transferred to the energy grid will be denoted by qg, and the cost of the consumed energy by qf. external conditions, such as the length of the light day and the mean daily temperature, will be denoted by f. the price of energy consumed is ci (t,vt,qf,f), and the price of the generated energy is ce (t,q, e qg,f). the active consumer’s behavior should be aimed at maximizing their goal by selecting the appropriate consumption schedule r 1,r∈ for each type of equipment n 1,n∈ , for each generation unit m 1 , m∈ , the schedule of its operation for each period of time t 1,t∈ , the choice of the positive amount of power output, and the amount of electrical energy transferred to the energy grid. restriction on the amount of power consumption can be expressed as n consum t n maxn=1 t v p v∀ × ≤∑ the active consumer when forming the generation operating mode based on the price signals coming from the market, must take into account the following elements: time-of-use tariff, their own generation capacity; unit cost of their own generation; the best option for loading facilities. based on the above model of the active consumer’s behavior in the energy market, a strategy for their behavior is proposed, which includes the following stages. the first stage is to select the necessary parameters and technical characteristics of the operation of each unit of each type of equipment. the second stage is to forecast and form possible operating modes for each unit of each type of equipment during the day and build a matrix of equipment loading. the third stage includes determining the economic benefit of electrical energy consumption for each equipment operating mode. then the price parameters of the selected operating modes are determined, such as: the cost of purchased electrical energy, the working cost of own energy production, the cost of supplying electrical energy to the energy grid. the next step is to choose the most optimal option. we propose to consider from a large number of criteria the following ones: optimality criteria, which are set according to the parameters of working costs and costs. for example, if the costs of energy generation exceed its purchase cost from the grid, the participant of the energy market should choose the option of buying electrical energy and not load their own generation, and vice versa, if the cost of own generation is lower than the price for electrical energy, the maximum possible amount of electricity should be produced independently, and the remaining energy should be consumed from the energy system. if the price of electrical energy supplied to the grid is lower than the production costs, it is necessary to limit the energy production to one’s own needs. practical implementation of the active consumer model will be based on their own decisions to “buy” or produce electrical energy by themselves. 6. discussions the active consumer’s functions in the energy market are to purchase electrical energy from the shared energy grid, to choose the quantities of electrical energy purchased from other participants in the energy market and to sell it. the change in the behavior of energy companies when active consumers appear on the market is to make it possible for the consumer to change the amount of the purchased electrical energy on their own, and to choose the functional properties (reliability level, quality) based on the balance of their needs and the capabilities of the energy grid. the concept of an active consumer in the energy grid is implemented through a system of mechanisms (demand-side management), which includes demand-side management programs (demand response) and energy efficiency. for making optimal decisions by the business consumers of the electrical energy with regard to “buy” or “produce by themselves,” we have developed a model that includes the formation of an energy consumption schedule and a loading mode of own generation that reflects consumers’ economic interests and allows them to implement their functions. the proposed model for active consumers in the energy market can be used by various entities to solve different problems: consumers to formulate a strategy for their energy consumption and to automate consumer load management; power supply companies and a regulator to model a multi-agent system providing consumers’ response to tariff mechanisms of demandside management and to evaluate the economic benefit to the consumer from participation in demand-side management. 7. conclusion the change in the role of participants in the energy markets led to the formation of the concept of an “active consumer,” who is understood as an energy market participant, who has technology firsova, et al.: development of “active consumer” concept on energy market international journal of energy economics and policy | vol 8 • issue 3 • 2018 13 access to maneuver their energy consumption and participation in demand-side management. the main characteristics of the “active” consumer are: availability of the processing system capable of changing (transferring) the load; availability of own generation (distributed generation); availability of power storage; availability of the processing system capable of changing the load, own generation, energy storage units; demand-side management: reduction in the load, time transportation based on the principle of economy of energy consumption; management of their own generating capacities: determination of the loading efficiency, the quantity of electrical energy produced for their own consumption and the quantity of electrical energy supplied to the energy market; management of the energy storage mode, including that generated by their own generation capacities; sale of accumulated electrical energy; determination of conditions for their own capacity loading (if any) and for submitting an application for participation in buying/selling electrical energy in the wholesale and retail markets. 8. acknowledgments 1. the work is performed according to the internship program for the financial university administrative and teaching staff at the university of vienna (26.04.2018–13.05.2018). 2. the publication has been prepared with the support of the “rudn university program 5-100.” references bresler, f.s. (2009), demand response in the pjm electricity markets.  ohio: pjm. bushuev, v.v. (2013), intellectual development of electrical energy industry with the active consumer’s participation. мoscow: publishing house (energy). chubais, a.b. (2009), economics and management in the modern electric power engineering of russia: textbook. мoscow: corporate educational and scientific center of the unified energy system. davito, b., tai, h., uhlaner, r. (2010), the smart grid and the promise of demand-side management. mckinsey & company. available from: http://www.calmac.com/documents/mosg_dsm_vf.pdf. dorofeev, v.v., kuz’min, v.v. (2013), conceptual provisions of building a competitive electrical energy market on the basis of russia’s ips aag potentials. available from: http://www.grid2030.ru/userfiles/ novaya_kontseptsiya_rynka.pdf. [last date view on 2013 apr 08]. faria, p., vale, z. (2011), demand response in electrical energy supply: an optimal real time pricing approach. energy, 36(8), 5374-5384. govorov, d.s. (2012), active consumer. moscow: np (energy consumers association). grebenyuk, g.g., solov’ev, м.м. (2004), continuous price regulation to form the desired load schedule of a power system. automation and remote control, 5, 166-173. haas r., loew t. (2012), die auswirkungen der energiewende auf die strommärkte und die rentabilität von konventionellen kraftwerken. available from: http://www.nachhaltigkeit.wienerstadtwerke. a t / f i l e a d m i n / u s e r _ u p l o a d / d o w n l o a d b e r e i c h / h a a s l o e w auswirkungen-energiewende-auf-energiemaerkte2012.pdf. jiang, b., fei, yu. (2011), dynamic residential demand response and distributed generation management in smart microgrid with hierarchical agents. energy procedia, 12, 76-90. knyaginin, v.n. (2010), energy foresight. vision of the future of energy industry. csr “north-west”. available from: http://www.csr-nw.ru/ upload/file_content_320.pdf. kunz, s.c. (2013), erneuerbare energien im strommarkt. renews kompakt. agentur für erneuerbare energien. available from: http://www.unendlich-viel-energie.de/media/file/276.aee_ renewskompakt_strommarkt_dez13.pdf. lujano-rojas, j.m., monteiro, c., dufo-lopez, r., bernal-agustın, j.l. (2012), optimum residential load management strategy for real time pricing demand response programs. energy policy, 45, 671-679. reference materials for the analysis of electrical energy cost impact in the day-ahead market on pricing policy for the end user in 2011. (2011), np (market council). available from: http://www.np-sr.ru/ presscenter/pressinfo/. [last date view on 2016 jun 05]. rodin, a.v. (2011), factors influencing tariff policy formation in electric power industry and social and economic consequences of its realization. mstu bulletin, 14(1), 210-213. ryapin, i.y. (2012), cross-subsidization in the power sector: results of fifteen-year struggle. moscow: skolkovo energy centre. available from: http://www.energy.skolkovo.ru/upload/medialibrary/07c/ senec_cross_subsidization.pdf. [last date view on 2016 sep 12]. ryapin, i. (2013), risks of the (big) power industry: consumers’ shifting to the independent energy generation as a result of backlog of the reform. как результат недоработки реформы. moscow: skolkovo energy centre. scenario forecasts for the development of the electric power sector for the period up to 2030. (2013), ministry of energy of the russian federation. agency for balance projections in the power sector. available from: http://www.e-apbe.ru/5years/pb_2011_2030/ scenary_2010_2030.pdf. volkova, i.o., sal’nikova, i.o., shuvalova, d.g. (2011), active consumer in the smart energy system. academy of energy, 2(40), 50-57. zolotova, i.v. (2013), problems of cross-subsidization in the electric power industry. agency on forecasting balances in electric power industry. available from: http://www.e-118apbe.ru/library/ presentations/2013_06_04_zolotova.pdf. [last date view on 2016 jul 15]. zolotova, i.v. (2016), problems of cross-subsidization in the electric power industry. agency on forecasting balances in electric power industry. available from: http://www.e118apbe.ru/library/ presentations/2013_06_04_zolotova.pdf. [last accessed on 2016 july 15]. . international journal of energy economics and policy | vol 6 • issue 3 • 2016 495 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2016, 6(3), 495-500. techno-economic analysis of liquid petroleum gas fueled vehicles as public transportation in indonesia muji setiyo1,2*, sudjito soeparman3, nurkholis hamidi4, slamet wahyudi5 1department of mechanical engineering, faculty of engineering, brawijaya university, malang, indonesia, 2department of automotive engineering, faculty of engineering, muhammadiyah university of magelang, magelang, indonesia, 3department of mechanical engineering, faculty of engineering, brawijaya university, malang, indonesia, 4department of mechanical engineering, faculty of engineering, brawijaya university, malang, indonesia, 5department of mechanical engineering, faculty of engineering, brawijaya university, malang, indonesia. *email: setiyo.muji@ummgl.ac.id abstract in indonesia, the use of liquid petroleum gas (lpg) in vehicles has been promoted through government policy since 1988. however, the progress has not significantly run. therefore, this paper presents the techno-economic analysis of lpg as road vehicles fuel alternative in comparison with gasoline ron 88 and ron 92 for public transportation in indonesia. the techno-economic analysis is considered running cost, break-even point (bep) distance, net present value (npv), internal rate of return (irr), payback period (pp), and sensitivity analysis. this analysis indicates that the bep distance of public transportation vehicles are approximating at 55,351 km compared to gasoline ron 92 and 93,168 km compared to gasoline ron 88. meanwhile, the result of the investment analysis shows that the investment feasibility indicators which include npv, irr, and pp show the investment was feasible but the investment is sensitive to fuel cost ratio between lpg and gasoline. keywords: liquid petroleum gas vehicles, running costs, investment feasibility jel classifications: m21, o31, q43 1. introduction clean vehicle propulsion technology such as electric vehicle (ev) and a fuel cell (fc) is promising in the present and future. the ev and fc prove better environmental impact than gasoline and diesel vehicles though it was expensive on purchasing price (messagie et al., 2013). on the other hand, replacing conventional fuel vehicles with the ev and fc technology in close time is impossible. thus, the use of alternative fuels and alternative energy which have a better environmental impact and economic viability than conventional fossil fuel became the realistic option (abdullahi, 2014; yusma et al., 2016). in indonesia, the use of liquid petroleum gas (lpg) in vehicles has been promoted through government policy since 1988. however, until 2014, public fleets using lpg are <6000 units (mahendra et al., 2014). therefore, this paper presents techno-economic analysis of lpg vehicles in comparison with gasoline ron 88 and ron 92. lpg grow up for spark-ignition engine because it has several property advantages, such as energy content, octane number, auto-ignition temperature, flame velocity and flammability limits (erkus et al., 2012; estap, 2010; harrow, 2008; kowalewicz and wojtyniak, 2005). the co, co2, hc, and nox produced by lpg engines are lower than gasoline engines, both on urban and extraurban cycle (saraf et al., 2009; tasic et al., 2011). it is promising at present and future associated with tightness on exhaust emission regulations (mohamad et al., 2012). however, the output torque and power of lpg vehicles reported slightly lower than gasoline (bayraktar and durgun, 2005; salhab et al., 2011). on the bifuel engine experience, where lpg and gasoline can be operated alternately, resetting of the ignition timing and applying of spark advance variation can increase engine torque and power (ehsan, 2006; lawankar, 2012; tomov, 2012); and setiyo et al., 2016). lpg can be applied directly to the existing vehicle by adding a converter kits. initially, lpg fuel technology using a converter and setiyo, et al.: techno-economic analysis of lpg fueled vehicles as public transportation in indonesia international journal of energy economics and policy | vol 6 • issue 3 • 2016496 mixer device that works much like a carburetor gasoline engines. now, the lpg vehicles technology is already equaled to gasoline fuel technology by multi-point injection or even direct injection. a mixture of lpg vapor and air or lpg liquid is sucked or injected into the combustion chamber, depending on the system used. the vapor injection kits supply lpg in the vapor form to the intake port. meanwhile, the liquid injection kits give liquid lpg to the intake port or directly to the combustion chamber (time for gas, 2013). the liquid direct injection systems are the latest generation of automotive lpg fuel system technology. both vapor and liquid injection, the mixture is burned to generate power, such as gasoline engines work. the lpg vehicles can run on fully dedicated fuel or bi-fuel systems. in the bi-fuel systems, lpg kits are added to the existing gasoline fuel system to give fuel operating alternately (nrel, 1994). in line with consumer demand, automotive manufacturers have to equip their products with lpg fuel system components as a new standard. some of which are holden ecoline lpg and ford ecolpi (elgas, n.d.). these technologies have been already marketed in several countries that have lpg refueling site infrastructures, such as australia and south korea. although lpg is derived from the refinery and has the equivalent energy content of gasoline, the price of lpg is lower than gasoline. monitoring by wlpga in 10 countries that encourage lpg as fuel for road vehicles, the consumption and the number of vehicles have been fluctuations in the last decade. however, generally, there is an increase, especially in developing countries (world lpg association, 2015). 1.1. global implementation the trend of lpg vehicles around the world have been reported and updated by world lpg association. in the recent decade, lpg vehicles have increased about 9.4 million in 2003 (world lpg association, 2005) and more than 17.4 million in 2010 (world lpg association, 2012). in 2014, there were more than 25 million lpg vehicles, mostly as light duty vehicles (ldv) and the rest as high duty vehicles. south korea, russia, poland, australia, turkey, india, and thailand are examples of countries that successfully promote lpg as an alternative fuel for road vehicles. in southeast asia, thailand successfully encourages lpg as an alternative fuel, including the number of vehicles, consumption, and the number of refueling sites (world lpg association, 2015). in those countries, people interest for converting their vehicles to lpg. the running costs using lpg are lower than gasoline, though they need the initial investment to install converter kits. their capital will be back soon in a few thousand kilometers mileage. the breakeven point (bep) distance and fuel cost ratio of use lpg compared to gasoline in some asian countries are presented in table 1. the government policy is essential to ensure the successful development of lpg infrastructure (liu et al., 1997). awareness and public education promote lpg have also been developed to make a significant contribution to market growth in some countries. the conversion program policy for public fleets has been very successful in several countries, including india and the united states. in korea and japan, restrictions on diesel vehicles have become an important factor in the success of the use of lpg. on the other hand, public concerns about safety and reliability of lpg clearly have affected the demand in several countries, including france and netherlands (world lpg association, 2015). in some cases, refueling facilities are inadequate and unevenly also can prevent the interest in using lpg. based on the experience of successful countries encourage lpg for road vehicles, a comprehensive long-term policy is needed to ensure the success of lpg conversion, among others, related to fiscal incentives, regulatory incentives, and research and development incentives. fiscal incentives include the sales and transfer tax of lpg vehicle, the provision of free converter kits, waivers of the registration fee, and waivers on-street parking of lpg vehicles. regulatory incentives include the requirement of all public vehicles and service vehicles equipped with converter kits, freeing lpg vehicles through a road with a restriction, and establishing high standard exhaust emission (abdini and rahmat, 2013). 1.2. current state of lpg vehicle in indonesia the policy for alternative energy (including lpg) is initiated by “blue sky program” which was firstly launched in 1996 by the ministry of environment. blue sky program is aimed at controlling air pollution and realizing environmentally conscious behavior either from stationary sources such as household and industrial or mobile sources such as vehicles. for the household sector, the indonesian government has successful experience of converting kerosene to lpg during the period 2007-2011.the indonesian government does not only successfully reduce the subsidy for petroleum fuels but also improve household cooking fuel, such as cleanliness, convenience, environment, and cost reduction (samosir, 2010; budya and yasir arofat, 2011). the application of lpg for the ldvs as public transportation has started since 1988. however, over the next 30 years does not develop. around the 2007’s, the government’s promotion of lpg as an alternative fuel for road vehicles (susanti et al., 2010). the government incentives are started by distributing converter kits free of charge for public transportation in many cities such as jakarta, surabaya, bogor, and palembang as a pilot project. during 2007-2011, more than 5000 lpg kits were given for public transportation, such as taxis and public city cars (figure 1). the government issued technical guidance about the standards of converter kits, infrastructures, workshops, and technicians. then, pertamina as one of the state-owned enterprises together with some private companies gradually builds the refueling site infrastructure in several cities. now, lpg refueling site has been available in jakarta, surabaya, bandung, bogor, palembang, semarang, solo, yogyakarta, denpasar, and magelang. in addition, challenges and opportunities of lpg implementation for land transportation have been studied by mahendra et al. (2013). table 1: the bep and cost ratio of lpg vehicle in some asian countries (world lpg association, 2015) country bep distance compared to gasoline (km) fuel cost ratio (lpg to gasoline) japan 169,405 0.62 india 22,141 0.59 turkey 13,650 0.59 south korea 43,191 0.62 thailand 28,508 0.32 average 55,379 0.55 bep: break-even point, lpg: liquid petroleum gas setiyo, et al.: techno-economic analysis of lpg fueled vehicles as public transportation in indonesia international journal of energy economics and policy | vol 6 • issue 3 • 2016 497 lpg for road vehicle in indonesia is called the liquefied gas vehicle or vi-gas. vi-gas consumption growth has been increased by the average of 40% per year, from 189 kl in 2008 to 913 kl in 2013, and it is estimated at more than 2000 kl in 2016. however, this number is too small compared to conventional fuel consumption, such as gasoline and diesel. today, lpg vehicles are still dominated the official vehicles owned, state-owned enterprises, and public transportation vehicles as a pilot project. economic studies of lpg as public transport fuel related to the price control and infrastructure investment by the government has done by samosir (2010) and mahendra et al. (2014). however, society has not received valid information related to the benefits obtained when they switch conventional fuels to lpg for their existing vehicles. 1.3. cost identification in general, the several costs should be considered by the car owners before switching to lpg, including capital costs, maintenance costs, and fuel costs (liu et al., 1997). to switch gasoline to lpg, car owners can buy lpg vehicles produced by car manufacturers commonly called original equipment manufacturers (oems) or add converter kits on existing vehicle. lpg vehicle has the maintenance costs are lower than the gasoline vehicle because lpg contaminated lubricant fewer than gasoline. cleaner burning characteristics due to the lower carbon content also reduces maintenance costs (bosch, 2010). the running cost of lpg vehicles can be much lower than gasoline vehicles because the price difference of fuels in the refueling site. based on capital costs, maintenance costs, and fuel costs needed, this study discusses in detail a techno-economic analysis to assess the running costs of public transportation vehicles fueled lpg compared to gasoline ron 88 (premium) and gasoline ron 92 (pertamax). bep the use of lpg in indonesia will be described and compared to some countries in asia. meanwhile, the parameters of net present value (npv), internal rate of return (irr), payback period (pp), and sensitivity analysis will be used to assess the feasibility of investment for converting the vehicle to lpg. 2. assessment parameters in this study, the ldv which represent public transportation, such as taxis and public city car are simulated. the fuel consumption and mileage refer to the study reported by samosir (2010) and the price of the fuel used is the current price in the refueling site. at the time of writing (april, 2016), the prices of gasoline in indonesia in the refueling site are idr 6,450 for ron 88 and idr 7,550 for ron 92. meanwhile, the price of lpg for road vehicles is idr 5,100/l gasoline equivalent. parameters for analysis are presented in table 2. 2.1. bep distance bep analysis is used to assess equivalence between capital costs incurred for conversion and the fuel savings generated in term of distance traveled. the bep of lpg compared to gasoline ron 88 and ron 92 calculated using the equation (1). bep fc p vcgaso lpg = −( ) (1) fc is the capital cost. pgaso is the gasoline fuel cost per kilometer depending on ron. vclpg is the lpg fuel cost per kilometer. the gasoline and lpg fuel costs include the engine maintenance cost but did not consider the tire cost. 2.2. economic values and assessment parameter to assess the feasibility of investment for conversion from gasoline to lpg, this study uses the parameter of npv, irr, and pp, and sensitivity analysis. npv is the difference between expenditures and revenues that have been discounted using the social opportunity cost of capital as the discount factor. other says that the npv of cash flows expected in the future, discounted at this time. if the npv is >0, this project is feasible. meanwhile, the irr is obtained when npv = 0. if the irr is greater than bank interest, this project is feasible. generally, npv is calculated by equation (2) as follow. npv ci co ci co i ci co i ci co i n n = −( )+ − + + − + +… + − 0 1 1 2 2 21 1 1 ( ) ( ) ( ) ( ) ( ) ( ++ + + − i s i i n n ) ( )1 0 (2) where, ci is the cash inflows, co is the cash outflows, i is the bank interest, n is the period, s is the salvage values in the end of period, and i0 is the initial investment or capital costs. in this study, the lifetime lpg kits are assumed of 10 years and depreciation rate is calculated by straight-line method. thus, the salvage value of the converter kits is 50% of capital costs without installation cost. if figure 1: distribution of liquid petroleum gas kits for public transportation in indonesia (2007-2011) setiyo, et al.: techno-economic analysis of lpg fueled vehicles as public transportation in indonesia international journal of energy economics and policy | vol 6 • issue 3 • 2016498 net benefit (ci-co) and interest (i) are assumed not changed during n period, equation (2) can be rewritten as equation (3) below. ( ) 0 ( ) [1 1 ] (1 ) n n ci co x i s npv i i i − − − + = + − + (5) after npv and irr are known, investment assessment is done by calculating the pp. the pp is the ratio between the capital costs with acumulative proceeds (equation 4). this project is declared feasible if the pp is reached before the specified total time investment. pp investmentcosts accumulative proceed = � � (4) furthermore, the sensitivity analysis was performed to anticipate changes in the value of parameters, including vehicle distance traveled per year and the cost ratio between gasoline and lpg. the fuels prices on the refueling site in indonesia have fluctuated in recent years. distance traveled per year is also a possibility to change due to congestion and economic conditions that affect people’s mobility. thus, uncertainty of fuel prices and annual distance traveled is also an important consideration in this analysis. 3. results and discussion 3.1. running cost and bep in this study, the vehicle running costs and bep are calculated based on the assumption that there is no change in fuel prices. the calculation shows that the running costs per kilometer distance traveled of lpg vehicles in indonesia with lpg, gasoline ron 88 and ron 92 gasoline are idr 560, idr 705, and idr 815, respectively. the cost is already included fuel costs and estimates maintenance costs. bep calculation performed on lpg vehicles is switching from gasoline, not the oems product. the maintenance costs in both of fuel (gasoline and lpg) are derived to idr per kilometer. using equation (1) and the parameter values listed in table 2, the results of running cost and bep calculation are presented in figure 2. for public transportation with fuel consumption of 10 km/l, bep distance of lpg was achieved at 55,351 km compared to gasoline ron 92 and 93,168 km compared to gasoline ron 88. in the asia, the fastest bep is in turkey by only 13,650 km and the longest is in japan by 169,405 km. while, the bep average of five major lpg vehicle markets in asia is 54,977 km. in indonesia context, by assuming the lpg vehicle is the switch from gasoline ron 92, the bep is lower than the asian average. however, if it compared to gasoline ron 88, bep is higher than asian average. 3.2. investment feasibility analysis in this study, analysis of the feasibility of investment for converting gasoline to lpg system using the effective interest with compounded interest rate per month. the interest is assuming at 1% per month. the maximum limit of investment feasibility is set for 60 months (5 years). using equation (2) and the parameter values listed in the table 1, the results of npv and irr calculation are presented in figure 3. figure 3 presents the profitability of investment for the public transport company to convert its fleet to lpg. using equation (4), the pps of investment was achieved at 13.3 months and 7.35 month against to ron 88 and ron 92, respectively. however, several conditions need to be considered, including changes in oil prices causing changes in fuel cost ratio, uncertainties mileage per year, and bank interest. therefore, the sensitivity analysis is performed table 2: parameters for analysis item description unit value source mileages per year km 100,000 samosir (2010) fuel consumption km/l 10 samosir (2010) annual fuel consumption l 10,000 a/b gasoline 88 ron price per liter idr 6450 price in refueling site (april, 2016) gasoline 92 ron price per liter idr 7550 price in refueling site (april, 2016) lpg price per liter (equivalent to gasoline) idr 5100 price in refueling site (april, 2016) annual fuel cost for gasoline 88 ron idr 64,500,000 (c×d) annual fuel cost for gasoline 92 ron idr 75,500,000 (c×e) annual fuel cost for lpg idr 51,000,000 (c×f) annual saving lpg to gasoline 88 ron idr 13,500,000 (g-i) annual saving lpg to gasoline 92 ron idr 24,500,000 (h-i) capital cost of lpg conversion idr 15,000,000 considering the installation cost maintenance cost for lpg per km idr 130 estimated from racq (2014) maintenance cost for lpg per km idr 104 assumed to be 20% lower than gasoline operation because extended reliability of engine oil and spark plugs salvage value in the end of 60 months idr 5,500,000 50% of lpg kits price (zain, 2016) lpg: liquid petroleum gas figure 2: running cost and break-even point of vehicles driven by liquid petroleum gas and by gasoline setiyo, et al.: techno-economic analysis of lpg fueled vehicles as public transportation in indonesia international journal of energy economics and policy | vol 6 • issue 3 • 2016 499 to estimate the probability of investment. the parameters that may affect the changes made to the tolerance of 30% from baseline. figure 4 presents a sensitivity analysis of the calculation results. based on the sensitivity analysis presented in figure 4, the investment for converting gasoline to lpg is very sensitive to gasoline price, both on ron 88 and ron 92. in the time of writing, the fuel cost ratio of lpg against to gasoline in indonesia is 0.79 and 0.68 for ron 88 and ron 92, respectively. meanwhile, the average fuel cost ratio of five major lpg vehicle markets in asia (japan, india, turkey, south korea, and thailand) is 0.55. furthermore, some conditions that may occur (worst, bad, normal, good, and best) made to assess the risk of investment. the parameters for each condition are presented in table 3 while the budgeting decision is presented in table 4, respectively. based on table 4, the expected npv of lpg to gasoline ron 88 and ron 92 were idr 44,587,935 and idr 86,810,176, respectively. furthermore, the coefficient of variation (cv) of lpg to r ron 88 and ron 92 were 1.10 and 0.71, respectively. the cv of <2 indicates that the investment is acceptable. 4. conclusions a series of running cost analysis showed that the bep distance of lpg-fueled vehicles in indonesia is relatively higher than the average of five major lpg market in asia (japan, india, turkey, south korea, and thailand). however, the result of the investment analysis shows that the investment feasibility indicators which include npv, irr, and pp show the investment was feasible, both for comparison with gasoline ron 88 and ron 92. from the sensitivity analysis, this investment is very sensitive to fuel cost ratio between lpg and gasoline. meanwhile, the capital cost and mileage per year are only a small effect to the npv. in conclusion, in normal economic conditions, the investment to table 3: scenario analysis condition probability (%) mileage/ year (km) gasoline ron 88 price/l (idr) gasoline ron 92 price/l (idr) wacc (%) npv gasoline ron 88 (idr) npv gasoline ron 92 (idr) squared deviation time probability gasoline ron 88 gasoline ron 92 a b c d e f g h i j worst 10 70,000 4515 5285 1.3 31,813,434 11,621,129 5.83717e+14 9.68872e+14 bad 15 85,000 5483 6417 1.2 2,026,600 27,746,747 3.25937e+14 5.23273e+14 normal 50 100,000 6450 7550 1.0 38,601,891 79,810,676 1.79164e+13 2.44965e+13 good 15 115,000 7418 8682 0.9 90,141,344 144,596,881 3.11267e+14 5.00895e+14 best 10 130,000 8385 9815 0.7 152,511,216 222,154,063 1.16474e+15 1.8318e+15 ∑ 2.40358e+15 3.84933e+15 npv: net present value table 4: budgeting decision description value formula expected npv of lpg to gasoline ron 88 44,587,935 (b1*g1)+(b2*g2)+(b3*g3)+(b4*g4)+(b5*g5) from table 3 expected npv of lpg to gasoline ron 92 86,810,176 (b1*h1)+(b2*h2)+(b3*h3)+(b4*h4)+(b5*h5) from table 3 sd of lpg to gasoline ron 88 49,026,329 (i6^0.5) from table 3 sd of lpg to gasoline ron 92 62,043,003 (j6^0.5) from table 3 cv of lpg to ron 88 1.10 standar deviation gasoline ron 88 expected npv gasoline ron 88       cv of lpg to ron 92 0.71 standar deviation gasoline ron 92 expected npv gasoline ron 92       cv: coefficient of variation, sd: standard deviation, npv: net present value, lpg: liquid petroleum gas figure 3: (a) net present value and (b) internal rate of return calculation in comparison with gasoline ron 88 and 92 ba setiyo, et al.: techno-economic analysis of lpg fueled vehicles as public transportation in indonesia international journal of energy economics and policy | vol 6 • issue 3 • 2016500 mahendra, m., kartohardjono, s., muharam, y. (2013), implementation application of alternative fuel for land transportation sector in indonesia based on other countries experience. journal of energy and power engineering, 7, 524-536. mahendra, m., muharam, y., kartohardjono, s., giffari, f. (2014), modeling of lgv supply chain system for land transportation sector. procedia chemistry, 9, 284-294. ehsan, m. (2006), effect of spark advance on a gas run automotive spark ignition engine. journal of chemical engineering, 24(1), 42-49. messagie, m., lebeau, k., coosemans, t., macharis, c., van mierlo, j. (2013), environmental and financial evaluation of passenger vehicle technologies in belgium. sustainability (switzerland), 5(12), 50205033. available from: http://www.doi.org/10.3390/su5125020. mohamad, t.i., jermy, m., vuorenskoski, a.k., harrison, m. (2012), the effects of propane and gasoline sprays structures from automotive fuel injectors under various fuel and ambient pressures on engine performance. world applied sciences journal, 18(3), 396-403. nrel. (1994), technical evaluation and assessment of cng/lpg bi-fuel and flex-fuel vehicle viability. corolado. available from: http://www.nrel.gov/docs/legosti/old/6544.pdf. racq. (2014), vehicle running costs 2014. available from: http:// www.racq.com.au/. salhab, z., qawasmi, m.g., amro, h., zalloum, m., qawasmi, m.s., sharawi, n. (2011), comparative performance and emission properties of spark-ignition outboard engine powered by gasoline and lpg. jordan journal of mechanical and industrial engineering, 5(1), 47-52. samosir, a. (2010), should government provide subsidy of lgv/vigas in the 2011? case study of public transportation in jakarta. jakarta. policy paper, fiscal policy office ministry of finance republic of indonesia, augustus, (1). p1-32. saraf, r.r., thipse, s.s., saxena, p.k. (2009), comparative emission analysis of gasoline/lpg automotive bifuel engine. international journal of civil and environmental engineering, 1(4), 199-202. setiyo, m., waluyo, b., anggono, w., husni, m. (2016), performance of gasoline/lpg bi-fuel engine of manifold absolute pressure sensor (maps) variations feedback. arpn journal of engineering and applied sciences, 11(7), 4707-4712. susanti, v., hartanto, a., ridwan, a.s., hendri, m.s., estiko, r., hapid, a. (2010), fuel subsidy and air pollution reduction by policy program of conversion fuel cng for vehicles in west java province. journal of mechatronics, electrical power, and vehicular technology, 01(2), 43-52. tasic, t., pogorevc, p., brajlih, t. (2011), gasoline and exhaust emission comparison. advances in production engineering & management, 6(2), 87-94. time for gas. (2013), prins vs. brc comparative test drive of lpg systems for direct injection engines. international lpg, cng, & lng magazine, 14. available from: http://www.timeforgas.com. tomov, o. (2012), timing advance processor for internal combustion engine running on lpg/cng. in: proceedings electrical engineering, electronic, automation. angel kanchev: university of ruse. p184-187. world lpg association. (2005), autogas incentive policies, a country-bycountry analysis of why and how governments encourage autogas and what works. paris. available from: http://www.wlpga.org/. world lpg association. (2012), autogas incentive policies, revised and updated 2012. paris. available from: http://www.wlpga.org/. world lpg association. (2015), autogas incentive policies, 2015 update. neuilly-sur-seine. available from: http://www.wlpga.org/. yusma, n., mohamed, b., bekhet, h.a. (2016), impacts of energy subsidy reforms on the industrial energy structures in the malaysian economy : a computable general equilibrium approach, 6(1), 88-97. zain, i. (2016). installation cost of gas converter in fuel injected car. available from: http://www.otomania.com/. [last retrieved on 2016 may 11]. figure 4: sensitivity analysis switch from gasoline to lpg for public transportation in indonesia is a promising decision. references abdini, c., rahmat, h. (2013), switching to gas is an alternative policy options in solving the problem of subsidized fuel. available from: http://www.setneg.go.id/. [last retrieved on 2016 feb 14]. abdullahi, a.b. (2014), modeling petroleum product demand in nigeria using structural time series model (stsm) approach. international journal of energy economics and policy, 4(3), 427-441. bayraktar, h., durgun, o. (2005), investigating the effects of lpg on spark ignition engine combustion and performance. energy conversion and management, 46(13-14), 2317-2333. bosch, r. (2010), lpg spark plugs. road clayton. available from: http://www.industrialbearings.com.au/uploads/catalogs/ boschlpgsparkplugsa_1327911561.pdf. budya, h., yasir arofat, m. (2011), providing cleaner energy access in indonesia through the megaproject of kerosene conversion to lpg. energy policy, 39(12), 7575-7586. elgas. (n.d.), oem factory fitted lpg cars. available from: http:// www.elgas.com.au/autogas-lpg-cars/oem-factory-equipped-lpg-carsautogas. [last retrieved on 2016 feb 14]. erkus, b., surmen, a., karamangil, m.i., arslan, r., kaplan, c. (2012), the effect of ignition timing on performance of lpg injected si engine. energy education science and technology part a-energy science and research, 28(2), 1199-1206. estap. (2010), automotive lpg and natural gas engines. © iea, etsap technology brief t03, (april). p1-5. available from: http://www.etsap.org. harrow, g. (2008), options for alternative fuels and advanced vehicles in greensburg, kansas. available from: http://www.afdc.energy.gov/ pdfs/42748.pdf. kowalewicz, a., wojtyniak, m. (2005), alternative fuels and their application to combustion engines. proceedings of the institution of mechanical engineers, part d : journal of automobile engineering, 219, 103-125. lawankar, s.m. (2012), comparative study of performance of lpg fuelled si engine at different compression ratio and ignition timing. international journal of mechanical engineering and technology, 3(4), 337-343. liu, e., yue, s.y., lee, j. (1997), a study on lpg as a fuel for vehicles. research and library services division legislative council secretariat, (march). available from: http://www.legco.gov.hk/ yr97-98/english/sec/library/967rp05.pdf. . international journal of energy economics and policy | vol 5 • issue 4 • 2015 1073 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2015, 5(4), 1073-1083. investigating factors affecting co2 emissions in malaysian road transport sector siti indati mustapa1, hussain ali bekhet2* 1graduate business school, college of graduate studies, universiti tenaga nasional, malaysia, 2graduate business school, college of graduate studies, universiti tenaga nasional, malaysia. *email: profhussain@uniten.edu.my abstract today the unprecedented increase in co2 emissions has become an important global issue because of the intensification in demand from the transport sector due to an upward surge in urbanization and rapid economic growth. the demand for transport services is expected to rise further, causing the co2 emissions level to increase as well. in malaysia, the transportation sector accounts for 28% of total co2 emissions, of which 85% comes from road transport. this has led to strong interest in how the co2 emissions in this sector can be reduced effectively. this study aimed to investigate factors that influence the co2 emissions. a multiple regression model was used based on fuel-based technology data for 1990-2013. many factors influencing co2 emissions, i.e., fuel consumption, fuel efficiency (fe), fuel price (fp) and distance travel (dt), were examined for the road transport sector in malaysia. the results demonstrated that fe, fp and dt were the main factors influencing the co2 emissions growth. some policy implications from the empirical results were proposed for co2 emissions reduction. keywords: co2 emissions, energy consumption, road transportation, regression model, malaysia jel classifications: c13, q48, n75, r41 1. introduction the issue of climate change due to increasing levels of co2 emissions has emerged as the most challenging environmental problem in recent decades. rapid economic development around the world causes increased energy consumption and co2 emissions. the global co2 emissions have increased by 1.9% per annum from 20.9 billion tons of co2 in 1990 to 32.3 billion tons of co2 in 2013 (iea, 2014a). the transport sector accounts for about 23% or 7.2 billion tons of global co2 emissions and its contribution relative to other sectors is projected to grow substantially in the near future. the increase in the number of vehicles is one of the main emissions growth reasons. currently, there are almost 1 billion vehicles around the world consuming petroleum fuels at about 13.1 billion barrels annually and emitting about 5.4 billion tons of co2 annually (sang and bekhet, 2015). with growing energy demand and increasing use of vehicles, the global co2 emissions from the transport sector is projected to go up by about 50% by 2030 and over 80% by 2050 (iea, 2012). the unbounded increase in co2 emissions has become an important global issue (ipcc, 2007). therefore, the reduction of these emissions, especially in the transport sector, has become an imperative agenda item in countries around the world. figure 1 shows comparative co2 emissions between malaysia and a few developed and developing countries. while the developed countries (sweden, switzerland and france) are conventionally the main emitters of co2 emissions, developing countries’ (malaysia, china) emissions are now seen to surpass developed country’s emissions due to rapid economic development growth in recent decades (den elzen et al., 2009; world bank, 2014). the declining trend of co2 emissions per capita in developed countries is due to adoption of environmental policies toward expansion of clean energy development, which have led to the decoupling of gross domestic product (gdp) growth from co2 emissions (karlsson and meibom, 2008). figure 1 shows that malaysia has surpassed many developed countries in terms of co2 emissions. owing to these facts, the 2007 bali declaration by climate scientists emphasized the joint efforts by both developed and developing countries to take measures against climate change (shahid et al., 2014). consequently, many developing countries including malaysia have declared the commitment to reduce their co2 emissions. in 2009 at the 15 th conference of parties in mustapa and bekhet: investigating factors affecting co2 emissions in malaysian road transport sector international journal of energy economics and policy | vol 5 • issue 4 • 20151074 copenhagen, malaysia stated a voluntary target of reducing its co2 emissions intensity by 40% (based on its 2005 levels) by 2020 (nre, 2011). the move towards high income and developed nation status by 2020 (epu, 2015) is a challenge for malaysia. this is because as the country progresses, the demand for energy will increase in tandem, which will directly result in an increase in co2 emissions. figure 2 shows that between 1990 and 2013, the gdp and co2 emissions annual growth rate was 5.2% and 6%, respectively. this suggests that the co2 emissions in malaysia increased in line with gdp growth. since co2 emissions intensity is measured as co2 emissions per gdp, the strategy for reduction of the co2 intensity is by increasing the gdp sufficiently while maintaining the total co2 emissions or constraining the increase of total co2 emissions. with the growing economy in malaysia that requires emissions to rise, it is obvious that the alternative strategy to achieve this target is by reducing the total co2 emissions. therefore, malaysia needs to take effective measures for environmental friendly development of transportation to fulfill its aspirations. the transport sector is regarded as an important component of the economy that greatly contributes to the socioeconomic development. in malaysia, the energy consumption from the transport sector is also the highest among all of the sectors in the country. in 2013, the share of energy consumption was recorded at 43.3%, consuming about 22.4 million tons of energy, of which 85% (19 million tons) largely came from the road transportation modes (ec, 2014; lim and lee, 2012). the number of motor vehicles also increased by 7.4% per annum to reach 21 million in 2013, with motor cars and motor cycles together accounting for 92% of total vehicles in the country (mot, 2013). the insufficient public transportation infrastructure has also aided the ever increasing motor vehicle population. in 2013, public transportation modes in malaysia have only an 8% share of the total registered vehicles. in terms of co2 emissions, the transport sector continued to be among the largest emitters after electricity generation. as shown in figure 3, the co2 emissions in malaysia’s energy sector has increased over the years. in 2013, a total of 208 million tons of co2 emissions was emitted from the energy sector (iea, 2014b). electricity generation, transport, manufacturing and other sectors contributed 46%, 22%, 19% and 13% of the total co2 emissions with annual growth increases of 6.4%, 4.4%, 3.6% and 13.9% in the respective sectors. it can be observed that the transport sector has superseded the manufacturing industry in terms of co2 emissions in recent years. the increasing growth in the economy, rapid urbanization and rising incomes caused a rapid increase in the demand for passenger transport services (kasipillai et al., 2008). conclusive evidence also advocates that as people have an increased income, they make use of faster modes of transport which could lead to detrimental effects on the environment (profillidis et al., 2014). currently, road transportation accounts for the largest share with 85.2% of total co2 emissions in the transportation sector, followed by aviation, maritime and rail in malaysia. private vehicles (motorcars and figure 1: co2 emissions per capita in several countries (1971-2013) source: world bank (2014) source: dosm (2013) and iea (2014b) figure 2: co2 emissions and gross domestic product trends in malaysia (1990-2013) mustapa and bekhet: investigating factors affecting co2 emissions in malaysian road transport sector international journal of energy economics and policy | vol 5 • issue 4 • 2015 1075 motorcycles) represent the largest share of co2 emitters, with about 70% of the total road transportation sector (ong et al., 2011). presently, this sector relies heavily on petroleum products, especially petrol (66%) and diesel (32%), while gas (2%) has a marginal fuel share (indati and bekhet, 2014). its heavy reliance on petroleum products is a worrying trend for the future in terms of energy security and its co2 emissions contribution (silitonga et al., 2012; mofleh, 2010). undoubtedly, in the light of unprecedented growth in the prevalence of private cars and the projected increase for passenger transport services, the road transport sector will be a pivotal sector to address in the fulfillment of the goals of co2 emissions reduction (cheng and lu 2015). some concerns are raised that the co2 emissions reduction efforts will affect the growth in the transportation sector, which in turn will have a negative impact on national economic growth. however, advancements of vehicle technology could decelerate the co2 emissions level growth and be able to decrease the co2 emissions intensity by increasing fuel efficiency (fe) without affecting the economic growth (khalid, 2014; aizura et al., 2010). this possibility is in tandem with the environmental kuznets curve, which hypothesizes an inverted u-shaped relationship between emissions and policy measures of a country by technological measures (dinda, 2004; world bank, 1992). therefore, this study aimed to investigate the factors that are influencing the co2 emissions in the road transport sector and examine the underlying policy initiatives that are effective to fulfill the national aspiration for co2 emissions reduction. the remaining sections are structured as follows: section 2 discusses the previous empirical findings. the data sources and the methodology are discussed in section 3. section 4 presents the results of the study analysis. the conclusions and policy implications drawn from the study results are presented in section 5. 2. literature review in relevant literature, considerable efforts were made to support sustainable energy and environmental policy planning in different countries. a number of modeling approaches and techniques were employed to investigate the influencing factors and mitigation policies that impact the co2 emissions growth in various energy sectors. generally, past studies in this context used time series analysis, regression analysis, decomposition and optimization models. the first line of research employed time series analysis. the increased energy consumption raised concerns about the environment due to increasing co2 emissions (egilmez and tatari, 2012). using time series analysis, sultan (2010) found cointegration of income per capita and fuel price (fp) on transport fuel consumption (fc), while ozturk (2015), al-mulali et al. (2015), bekhet and yasmin (2013), ozturk and uddin (2012), wang et al. (2011), bekhet and yusop (2009), ang (2008) and ediger and akar (2007) found a long-term relationship between energy consumption and co2 emissions. begum et al. (2015) studied the impact of gdp, fc and population growth on the co2 emissions. consistent with ivy and bekhet (2015), their study suggested that the fc and co2 emissions growth could be reduced by employing low-carbon technologies. ackah and adu (2014) found that transport demand is price inelastic implying that continual fp subsidy is economically inefficient and investment in productivity is found to be able to restraint co2 emissions in the transport sector. using regression analysis, sadorsky (2013; 2014) investigated the relationship between energy intensity, urbanization, income and gdp and found that reduction in co2 emissions could derive from increases in fe and fuel switching from fossil fuels to renewables energy. xu and lin (2015) investigated gdp, energy intensity, urbanization level, cargo turnover and private vehicle inventory on co2 emissions. they found that with increasing economic growth, low carbon vehicles such as high-speed rail and hybrid cars should become the mainstay of passenger and freight vehicles. shu and lam (2011) found that the co2 emissions were largely concentrated on the dense road network of urban areas with high population density. xu et al. (2014) investigated the effects of population, energy structure, energy intensity and gdp on co2 emissions. their study found that the driving factors of co2 emissions were the gdp followed by the population scale and energy structure. the study suggested that technology advancement was the most effective way to increase the fc efficiency. figure 3: trends of co2 emissions from energy sub-sectors in malaysia (1990-2013) source: iea (2014b) mustapa and bekhet: investigating factors affecting co2 emissions in malaysian road transport sector international journal of energy economics and policy | vol 5 • issue 4 • 20151076 rapid economic growth and urbanization has resulted in a greater need for mobility and increases the distance travel (dt) by road transport among the people. this raises concerns with regard to the increasing demand for fuels to sustain this trend (kari and rasiah, 2008). using decomposition analysis, lakshmanan and han (1997) attributed the change in transport sector co2 emissions to growth in dt, population and gdp. wu et al. (2005) investigated how changes in transport dt, energy intensity and the number of vehicles affected energy-related co2 emissions. timilsina and shrestha (2009) decomposed co2 emissions growth into components associated with changes in modal shift, fuel mix, emission coefficients and transportation energy intensity, along with gdp growth. a number of optimization models were also developed for sustainable energy planning and co2 emission reduction. using linear programming models, borjesson and ahlgren (2011), wang et al. (2008) and bai and wei (1996) investigated the costeffectiveness of possible co2 mitigation options for the energy industries. on the other hand, using a mixed integer linear programming model, hashim et al. (2005) studied the effects of fuel switching and fuel balancing options on power generation. their studies found that fe and fuel switching offered the best option to reduce co2 emissions. tan et al. (2013) used mixed integer linear programming analysis for the optimal planning of waste to energy that minimizes electricity generation costs and co2 emissions for iskandar malaysia. kamarudin et al. (2009) developed a model to determine the minimum cost and optimum hydrogen delivery network in peninsular malaysia. table 1 summarizes some relevant literature with the main features including methodology employed and main factors investigated. it is evident from table 1 that most previous studies in malaysia, i.e. ivy and bekhet (2014), ivy and bekhet (2015), ang (2008) and begum et al. (2015), found that gdp, population and fc were the key determinants of co2 emissions. while there exists other factors such as fe, fp and dt, empirical results so far explaining the effects of these factors on road transport co2 emissions are rather limited (begum et al., 2015). therefore, this study considered these variables and investigated the relationship and impact of fc, fe, fp and dt on the co2 emissions of the transport sector in malaysia by considering them simultaneously using a multiple regression analysis. 3. conceptual framework of co2 emissions reduction model the aforementioned literature highlights the importance of linking fc, fe, fp and dt to co2 emissions. building upon the existing literature, the conceptual framework was designed to investigate the factors that influenced the co2 emissions in the road transportation. the dependent variable was co2 emissions, which is the primary interest of the study. the variance in the dependent variable can be explained by the four independent variables of fc, fe, fp and dt, which are interrelated to each other. fc is the type and volume of fuel used by vehicles in the road transport sector. as fc is proportional to co2 emission, the less fuel consumed by vehicles means less co2 emissions can table 1: summary of previous studies on energy and environmental planning study sector/country methodology/approach related factors of study ang (2008) energy/malaysia johansen co-integration vecm gdp, co2 emissions, fc ackah and adu (2014) transport/ghana structural time series income, fc, price, human capital, efficiency bai and wei (1996) electricity/taiwan linear programming optimization on co2 emissions and electricity production begum et al. (2015) energy/malaysia time series, ardl approach gdp, fc, population, co2 emissions bekhet and yasmin (2013) energy/malaysia time series, ardl approach co2 emissions, gdp, export, import, fc bekhet and yusop (2009) energy/malaysia vecm oil price, gdp, employment, fc borjesson and ahlgren (2011) transport/sweden linear programming optimization on co2 emissions and economic cost ediger and akar (2007) energy/turkey arima fc hashim et al. (2005) electricity/ontario mixed integer programming optimization on co2 emissions and economic cost ivy and bekhet (2014) residential/malaysia time series, ardl approach electricity consumption, gdp, fp, population ivy and bekhet (2015) residential/malaysia time series, ardl approach electricity consumption, gdp, fp, population, fdi kamarudin et al. (2009) transport/malaysia mixed integer programming optimization on economic cost lakshmanan and han (1997) transport/usa decomposition co2 emission, fc, dt, population and gdp sadorsky (2013) 76 developing countries panel regression energy intensity, income, urbanization and gdp sadorsky (2014) 16 emerging countries panel regression energy intensity, income, urbanization and gdp shu and lam (2011) transport/louisiana panel regression co2 emission, population, urban area, income and road density sultan (2010) transport/mauritus time series, ardl approach fc, fp, per capita income tan et al. (2013) waste/malaysia mixed integer programming optimization on co2 emissions and economic cost timilsina and shrestha (2009) transport/asian countries decomposition co2, fuel mix, modal shift, gdp, population, emission coefficients and energy intensity wang et al. (2008) iron and steel multi-objective optimization optimization on co2 emissions and production cost wang et al. (2011) transport/china decomposition co2 emissions, fc, modal share, transport intensity xu and lin (2015) transport/china non-parametric regression co2 emission, gdp, population, fc xu et al. (2014) china decomposition co2 emission, fc, gdp, energy intensity vecm: vector error correction model, gdp: gross domestic product, fc: fuel consumption, fp: fuel price, dt: distance travel, fdi: foreign direct investment, ardl: autoregressive distributed lag, arima: autoregressive integrated moving average mustapa and bekhet: investigating factors affecting co2 emissions in malaysian road transport sector international journal of energy economics and policy | vol 5 • issue 4 • 2015 1077 be reduced in road transport (begum et al., 2015). however, in the case of utilizing non-fossil fuels, which contain less carbon content, co2 emissions can be lowered without reducing the amount of fuel needed by the road vehicles. thus, the greater utilization of non-fossil fuels, the greater co2 emissions reduction is taking place (ong et al., 2012). fe refers to the energy efficiency of vehicles, given as the ratio of vehicle travel distance per unit of fuel consumed. the greater improvement in fe will increase the dt but will decrease the fc required for travel and hence reduce the co2 emissions level (beuno, 2012). fp is the cost of fuel used by vehicles. when the fp increases, the fc may be reduced as a result of reducing demand (haldenbilen, 2006; johanssons, 2009). thus, the increase in fp also adds the probability of reduced co2 emissions. dt is the travel demand that refers to the unit quantity of dt by passengers and freight in the road transport sector. the increase in dt will increase the fc and the level of co2 emissions (zanni and bristow, 2010). the option of having more efficient cars will increase the dt but reduce the fc and co2 emissions. the transport demand may increase as long as people do not reach their budget which related to fp. the assumptions of these relationships are shown schematically in figure 4. accordingly, it is hypothesized that: h1: there are significant relationships between co2 emissions and its determinants (fc, fe, fp and dt). h2: there are statistically significant impacts from fc, fe, fp and dt on co2 emissions. 4. data source and methodology 4.1. data sources the data on fc, fe, fp and dt of road transport for the current study was collected from various official data sources for 1990-2013 (table 2). the data sets were on the road transport sector. the vehicle types covered in this sector were motorcars, motorcycles, taxis, hire and drive cars, goods vehicles and buses. this data was summed according to vehicle technology type that was based on three different fuels: petrol, diesel and natural gas for the study period. in malaysia, petrol vehicles dominated the road transport and made up the greatest percentage at 93% (dominated by motorcars and motorcycles) while diesel vehicles constituted 6% (dominated by goods vehicles, buses and taxis) and the share of natural gas vehicles (used by taxis and buses) was marginal at about 1%. considering that natural gas vehicles constituted a small share of total vehicles, they were not included in the analysis. hence, the data sets were split into two: data sets for petrol vehicle technology and diesel vehicle technology, respectively. the annual fc, fp and co2 emissions were collected mainly from official data sources’ statistical reports of the energy commission, (ec, 2012, 2014) ministry of domestic trade and international energy agency respectively. the transport data for dt and fe were not readily available. however, there was a record of the annual vehicle numbers, average annual mileage, occupancy/ load factors and average fe by vehicle types from published literature and sources (indati and bekhet, 2014). data from these sources was used to estimate relative dt and fe of different vehicle technology categories. spss statistics, version 21 was used to perform the study analysis. the collected data sets are summarized in table 2. 4.2. methodology the primary objective of the current study was to investigate the relationship and impact between co2 emissions and its determinants in the road transport sector in malaysia. the testing procedure consisted of two parts, namely descriptive statistics with inter-relationship analysis and multiple regression analysis. the first part of the analysis was undertaken to observe the conditions and normality distribution of the data. the mean values and standard deviations were used to observe the data quality, while the skewness, kurtosis and shaphiro–wilk tests were used to observe the normality distribution of the data. then the interrelationship analysis was conducted to determine the strength and direction of the linear relationships between the allocation factors and co2 emissions. the second part was a multiple regression model to investigate the impact between co2 emissions and its determinants comprising fc, fe, fp and dt. the linear relationship-stepwise techniques were carried out to test the effects of these factors on co2 emissions. the regression analysis was performed iteratively using the spss statistics software package. figure 4: conceptual model of co2 emission reduction model table 2: variables, description and sources variables description unit sources fc fc by type of fuel ktoe ec (2000-2014) fe average fe by vehicle technology km/l iea (2012); aizura et al. (2010); iangv (2000) fp average market price of fuel by type of fuel rm/l mdtca (2012); ec (2009-2014) dt average dt in transport sector by vehicle technology bpkm mot (2000-2013); masjuki et al. (2004); indati and bekhet (2014) co2 emissions (e) co2 emissions in transport sector million ton iea (2014b) bpkm: billion passenger km, fc: fuel consumption, fp: fuel price, dt: distance travel, fe: fuel efficiency mustapa and bekhet: investigating factors affecting co2 emissions in malaysian road transport sector international journal of energy economics and policy | vol 5 • issue 4 • 20151078 in general, co2 emissions rise with fc and dt and decrease when fe and fp increase (wohlgemuth, 1997). in this model, the dependent variable is co2 emissions of the transport sector. four factors i.e. fc, fe, fp and dt were used as independent driving variables for the co2 emissions in the models. the model for the regression analyses was generally formulated as in equation (1). e = β0 + β1 fc1 + β2 fe2 + β3 dt3 + β4 fp4 + ε (1) in this equation, β0… β4 are the regression coefficients to be estimated based on a record of observations while the last term in the equation, ε, is referred to as residual that is used for testing the overall significance (f-test) of the equation and the significance of each regression coefficient (t-test). the vehicle technologies in the malaysian road sector are driven by petrol and diesel vehicles (section 4.1). using the general equation (1), the regression technique was conducted separately for two models. model 1 represents the data sets of petrol vehicles technology and model 2 represents the data sets of diesel vehicles technology. the option chosen for both models was the stepwise method. this method reiterates the analysis by each parameter in turn and independently considers the inclusion or exclusion of the parameters with every step. although equation (1) includes all the determinant factors assumed to have effects on co2 emissions, not all of these factors may be statistically significant in each vehicle technology type. the estimated coefficients of the models are shown and discussed in section 5. 5. results and discussion 5.1. descriptive statistics, normality analysis and inter-relationship table 3 shows the results of the statistical descriptions for each determinant. the first left side column in the table reported the data quality consisting of minimum, maximum, mean and standard deviation. a small standard deviation relative to the mean was observed for all factors, suggesting good data quality. the right side column of the table reported the normal distribution results of the data consisting of skewness, kurtosis and shapiro–wilk. the skewness was within the range of ±1 and kurtosis was within the range of ±3, suggesting good normality indicators for the factors investigated. due to the small datasets (n = 24) under investigation, the normal distribution was further explored through the statistical technique called the shapiro–wilk test. the results in table 3 indicate a good significance (p > 0.001) for all factors (pallant, 2013). for inter-relationships, the pearson correlation coefficient was calculated for the factors to determine the strength and direction of the linear relationships between the independent variables (fc, fe, fp and dt) and the dependent variable (e). a correlation of <0.20 is considered a slight correlation; 0.20-0.40 is considered low; 0.4-0.7 is a moderate correlation; 0.7-0.9 is a high correlation; and more than 0.9 is considered very highly correlated (sang and bekhet, 2015). table 4 shows the results of correlation coefficients. all factors have high correlation (>0.8) with co2 emissions. fc (fcp, fcd) and dt (dtp, dtd) show positive linear relationships with co2 emissions, indicating that higher consumption and dt are inclined to increase co2 emissions (wang et al., 2012). fe (fep, fed) and fp (fpp, fpd) of both diesel and petrol vehicles show a negative linear relationship with co2 emissions, indicating that higher fe and fp increases are inclined to reduce co2 emissions. 5.2. impact analysis between co2 emissions and its driving factors multiple regression analyses were performed to understand the impact between co2 emissions and its influencing factors based on the step-wise method, which reiterates the analysis by each variable in turn and independently considers the inclusion or exclusion of the variables with every step (criteria: probability-off-to-enter ≤0.05; probability-of-f-to-remove ≥0.1). during these iterations, outliers of the residual terms were eliminated because the statistics calculated during the linear regression analyses rely on normal distribution of these error terms. the results of model 1 (table 5) reveals that only the cumulative effect of fe (fep) and fp (fpp) on co2 emissions are most significant, with the t-test significance level of each factor at <0.05 and the value of the multicollinearity (variance inflation factor) is considerably good at 5.658. these results suggest that the effects of co2 emissions from road transport are significant when fe and fp are taken into account. as shown in model 1 of table 5, the adjusted r2 of 0.981 implies that the predictors (fep and fpp) explain about 98.1% of the variance in co2 emissions. the anova table also indicated that the f-test overall statistic of 595.7 is large enough to be acceptable statistically and the significance level is 0.000. the durbin–watson statistic of 1.978 suggests that the error terms were not auto correlated (montgomery et al., 2006). the largest beta coefficient for fep (−15.727) means that this factor makes the strongest contribution in explaining the co2 emissions, when the variance explained by all other predictor domains in the model is controlled for. it implies that any increase in fep would lead to a decrease in co2 emissions (beuno, 2012). the results also revealed that the strongest contribution to co2 emissions in ranking order were fep and fpp. hence, one can draw the conclusion that fe (yang et al., 2015; beuno, 2012; pasaoglu et al., 2012; mattila and antikainen, 2011; ong et al., 2011; hickman et al., 2010; hickman and banister, 2007; ichinohe and endo, 2006; gielen and changhong, 2001) and fp (klier and linn, 2013; allcott and wozny, 2014) are the key factors influencing the co2 emissions level of petrol vehicles in malaysia. in contrast, the estimated coefficients of model 2 (table 5) reveals that only dt (dtd) affects the co2 emissions. the adjusted r2 of 0.978 implies that the predictors explain about 97.8% of the variance in co2 emissions. the anova table also indicated that the f-test overall statistic of 1018.076 is sufficiently acceptable and the significance is 0.000. t-test significance of the factor is <0.05. the durbin–watson statistic (=1.819) suggests that the error terms were not auto correlated (braun et al., 2014). model 2 shows that only dt of diesel vehicles (dtd) makes the strongest contribution in explaining the co2 emissions, implying that any increase in dtp mustapa and bekhet: investigating factors affecting co2 emissions in malaysian road transport sector international journal of energy economics and policy | vol 5 • issue 4 • 2015 1079 would lead to an increase in co2 emissions. hence, one can draw the conclusion that for diesel technology, dt is the main factor of road transport co2 emissions growth (zanni and bristow, 2010; bonilla, 2009). differences between the markets of the petrol (mostly used for passenger transport) and the diesel (largely used for passenger transport and freights transport) could explain this result (gonzález-marrero et al., 2012). in malaysia, the dieselfuelled vehicles are mainly used for passenger transport such as buses and taxies and freight transport such as goods vehicles that are largely used by long distance drivers (ong et al., 2012). the results of the inter-relationship and impact statistical analysis of the variables are summarized in tables 6 and 7, respectively. in terms of inter-relationship analysis (table 6), the results indicated that all the predictors support the hypothesis of h1. however, in terms of impact analysis (table 7), the current results generally revealed that only the predictors of fe, dt and fp support the table 3: descriptive statistics variables min max mean sd skewness kurtosis shapiro–wilk p value co2 (e) 15.37 45.50 31.02 8.905 −0.262 −0.952 0.404 fc petrol (fcp) 2889.0 12288.00 6680.75 2328.08 0.146 −0.024 0.447 diesel (fcd) 1351.24 4820.00 2934.86 1136.77 −0.138 −1.502 0.013 fe petrol (fep) 7.47 9.58 8.49 0.6842 0.161 −1.268 0.194 diesel (fed) 5.80 8.12 6.97 0.7619 0.067 −1.251 0.194 fp petrol (fpp) 0.29 0.80 0.5750 0.1875 −0.352 −1.546 0.004 diesel (fpd) 0.34 1.03 0.7258 0.2523 −0.433 −1.429 0.005 dt petrol (dtp) 106.40 591.25 309.24 156.22 0.472 −1.092 0.101 diesel (dtd) 74.50 272.60 169.38 58.81 −0.036 −1.029 0.548 sd: standard deviation, fc: fuel consumption, fp: fuel price, dt: distance travel, fe: fuel efficiency table 4: correlation coefficient for road transport dataset factors co2 fcp dtp fep fpp fcd dtd fed fpd e 1.000 fcp 0.963 1.000 dtp 0.959 0.929 1.000 fep −0.986 −0.957 −0.978 1.000 fpp −0.851 −0.845 −0.933 0.907 1.000 fcd 0.936 0.923 0.907 −0.945 −0.863 1.000 dtd 0.989 0.964 0.984 −0.995 −0.901 0.939 1.000 fed −0.984 −0.950 −0.985 0.999 0.911 −0.944 −0.996 1.000 fpd −0.836 −0.805 −0.912 0.869 0.899 −0.845 −0.863 0.876 1.000 correlation is significant at the 0.01 level (two-tailed). fc: fuel consumption, fp: fuel price, dt: distance travel, fe: fuel efficiency table 5: results of measurement model 1 (petrol technology vehicles) and model 2 (diesel technology vehicles) construct unstandardized coefficients standard error standardized coefficients t-value p-value vif β beta model 1: petrol technology vehicles constant 157.812 5.912 26.692 0.000 fep −15.727 0.889 −1.208 −17.686 0.000 5.658 fpp 11.634 3.245 0.245 3.586 0.002 05.658 model 2: diesel technology vehicles constant 5.644 0.840 6.719 0.000 dtd 0.150 0.005 0.989 31.907 0.000 1.000 model 1: r=0.991, adjusted r2=0.981, f=595.675, significant=0.000, durbin–watson=1.978, model 2: r=0.989, adjusted r2=0.978, f=1018.076, significant=0.000, durbin–watson=1.819 table 6: results of hypothesis testing (h1) of inter-relationship analysis hypothesis petrol technology vehicles diesel technology vehicles correlation coefficients results correlation coefficients results co2↔fc 0.963 supported 0.936 supported co2↔fe −0.986 supported −0.984 supported co2↔fp −0.851 supported −0.836 supported co2↔dt 0.959 supported 0.989 supported correlation is significant at the 0.01 level (two-tailed). fc: fuel consumption, fp: fuel price, dt: distance travel, fe: fuel efficiency hypothesis of h2, with the strongest contribution to co2 emissions in ranking order being fe, dt and fp respectively. hence, one can draw the conclusion that the fe, dt and fp are the significant contributing factors for co2 emissions reduction in malaysia’s mustapa and bekhet: investigating factors affecting co2 emissions in malaysian road transport sector international journal of energy economics and policy | vol 5 • issue 4 • 20151080 road transport. even though fc is not supported in both models, the fe improvement ultimately affects fc, which corresponds to the growth of co2 emissions level (bonilla, 2009). 6. conclusions and policy implications this study investigated the driving forces of co2 emissions in the road transport sector by using multiple regression analyses for 1990-2013 data. it examined the relationship and impact built upon assumptions that fc, fe, fp and dt had effects on the co2 emissions of the road transport sector in malaysia. the results showed significant linear effects between co2 emissions and its determinants. the study further revealed that the fe, fp and dt were the main impact factors on co2 emissions for road transport sector. this is in line with empirical results reported in other studies that suggested increases in fe (yan and crookes, 2009; ekins et al., 2011), fp (klier and linn, 2013) and dt (beuno, 2012) significantly influenced the energy consumption and co2 emissions level in this sector. this also seemed to support the previous empirical research that pointed out clean energy and energy efficient policies are able to reduce co2 emissions without affecting the country’s economy and mobility growth (saboori et al., 2012; matilla and antikainen, 2011; hickman et al., 2010). from the energy planning point of view, increasing demand in the road transport sector due to economic development will cause large amounts of co2 emissions. the results obtained suggest that fe improvement, fp mechanisms and dt management provide important policy implications to address the co2 emissions problem in road transportation. as most of the passenger vehicles run on petrol (93%), the increasing use of efficient vehicle technology, such as hybrid and electric vehicles to substitute for conventional vehicles, can reduce the co2 emissions in this sector (sang and bekhet, 2014). thus, government should intensify the promotion of these vehicles and continue to provide necessary fiscal incentives to accelerate the use of these vehicles. furthermore, the government has to improve energy saving technology using fiscal instruments such as encouraging the car manufacturers to engage energy saving technologies through preferential policies such as fuel economy policy (silitonga et al., 2012; mahlia et al., 2002). this policy would help to increase the penetration rate of efficient vehicle technologies substituting for conventional vehicles. the experiences in other areas (japan, united states, europe and singapore) that have implemented fuel economy policies signal that these measures reduce fuel use and co2 emissions. however, to establish the fuel economy standard on vehicles, a regulatory authority needs to be institutionalized and capacity must be built to implement this policy in malaysia. the current fuel economy initiatives around the world and in the association of southeast asian nations (asean) countries to achieve vehicle efficiency and reduce co2 emissions provide a good platform for promoting competitiveness and inducing a market transformation among car manufacturers in malaysia to produce efficient vehicles. as fc is proportional to co2 emissions, the less fuel consumed by vehicles means less co2 emissions can be reduced in the road transport. as dt has been regarded as the important factor for diesel vehicles, the fuel switching options can be implemented to reduce fc while meeting the mobility needs. this can be done by intensifying the use of alternative fuels such as biofuels (which contain less carbon content) so that co2 emission reductions can be achieved (xu and lin, 2015; borjesson & ahlgren, 2011). the b5 (blend of 5% palm biodiesel and 95% petroleum diesel) and b7 (blend of 7% palm biodiesel) that are currently used in diesel vehicles seems to support reducing the country’s co2 emissions. the plan to increase the biodiesel blend to b17 (blend of 17% palm biodiesel) by 2020 is an effective means for co2 emissions reduction in the country (epu, 2015). moreover, if the government adopts the use of bioethanol in road transport, the co2 emissions reduction would be higher as a much larger portion of the passenger vehicles runs on petrol (cucchiella et al., 2015). moreover, energy efficient vehicles such as hybrid, electric and eco cars could reduce fuel demand and co2 emissions for the transportation sector (pongthanaisawan and sorapipatana, 2013). as many diesel vehicles are largely used by industries, a “green” logistics strategy could be one of the options for co2 emissions reduction. as fp is also indicated as having significant impact on reducing the co2 emissions level, the government’s decision on removal of the fp subsidy for both petrol and diesel vehicles in 2014 is commendable. however, as the global oil price is declining, the increase in fp would cause marginal impact due to the increasing affordability of both purchasing and using private modes of transportation. thus, additional demand management measures, such as increasing vehicle taxes, a carbon tax and congestion charges in city areas, can be implemented to both reducing the fc and co2 emissions. the results of the current study provided a basis to understand the potential for reducing co2 emissions and offered support for identifying mitigation measure decisions in the local context for table 7: results of hypothesis testing (h2) of impact analysis hypothesis petrol technology vehicles diesel technology vehicles standardized path coefficients p value* results standardized path coefficients p value* results fc→co2 rejected rejected fe→co2 −1.208 0.000 supported rejected dt→co2 rejected 0.989 0.000 supported fp→co2 0.245 0.002 supported rejected *significant at the 5% level (p<0.05). fc: fuel consumption, fp: fuel price, dt: distance travel, fe: fuel efficiency mustapa and bekhet: investigating factors affecting co2 emissions in malaysian road transport sector international journal of energy economics and policy | vol 5 • issue 4 • 2015 1081 this sector. however, the study only focused on the road transport sector from a national perspective and excluded other modes of transportation. among many policies, a shift from private vehicles to public transportation (light rail transit and mass rapid transit) seems to be one of the effective mitigation strategies for co2 emissions reduction (ong et al., 2012). in this sense, further research can be extended to include other modes of transportation such as rail, air and maritime to improve representation of the transportation infrastructure. to study the country’s ability to achieve the co2 emissions reduction target, the work could be extended to examine the optimal level of co2 emissions reduction for the transportation sector. this could be further investigated by employing an optimization modeling approach to examine optimal energy reduction options that would be of interest to the country. references ackah, i., adu, f. (2014), modelling gasoline demand in ghana: a structural time series approach. international journal of energy economics and policy, 4(1), 76-82. aizura, a.b., mahlia, t.m.i., masjuki, h.h. (2010), potential fuel savings and emission reduction from fuel economy standards implementation for motor vehicle. clean technologies and environmental policy, 12(3), 255-263. allcott, h., wozny, n. (2014), gasoline prices, fuel economy, and the energy paradox. the review of economics and statistics, 96(5), 779-795. al-mulali, u., ozturk, i., lean, h.h. (2015), the influence of economic growth, urbanization, trade openness, financial development, and renewable energy on pollution in europe. natural hazards, 79(1), 621-644. ang, j.b. (2008), the long-run relationship between economic development, pollutant emissions and energy consumption: evidence from malaysia. journal of policy modelling, 30, 271-278. bai, h., wei, j. (1996), the co2 mitigation options for the electric sector. energy policy, 24, 221-118. begum, r.a., sohag, k., sharifah, s.a., mokhtar, j. (2015), co2 emissions, energy consumption, economic and population growth in malaysia. renewable and sustainable energy reviews, 41, 594-601. bekhet, h.a., yasmin, t. (2013), disclosing the relationship among co2 emissions, energy consumption, economic growth and bilateral trade between singapore and malaysia: an econometric analysis. world economy of science engineering and technology, 81, 281-286. bekhet, h.a., yusop, n.y.m. (2009), assessing the relationship between oil prices, energy consumption and macroeconomic performance in malaysia: co-integration and vector error correction model (vecm) approach. international business research, 2(3), 152-175. beuno, g. (2012), analysis of scenario for the reduction of energy consumption and ghg emission in transport in basque country. renewable and sustainable energy reviews, 16, 1988-1998. bonilla, d. (2009), fuel demand on uk roads and dieselisation of fuel economy. energy policy, 37, 3769-3778. borjesson, m., ahlgren, e.o. (2011), assessment of transport fuel taxation strategies thorugh integration of road transport in an energy system model – the case of sweden. international journal of energy research, 36, 648-669. braun, m.r., altan, h., beck, s.b.m. (2014), using regression analysis to predict the future energy consumption of a supermarket in the uk. applied energy, 130, 305-313. cheng, y.h., lu, i.j. (2015), urban transportation energy and carbon dioxide emission reduction strategies. applied energy. doi 10.1016/j. apenergy.2015.01.126. cucchiella, f., d’adamo, i., gastaldi, m. (2015), profitability analysis for biomethane: a strategic role in the italian transport sector. international journal of energy economics and policy, 5(2), 440-449. den elzen, m., hohne, n., van vliet, j. (2009), analysing comparable greenhouse gas mitigation efforts for annex i countries. energy policy, 37, 4114-4131. department of statistics malaysia, (dosm). (2013), population in malaysia. available from: http://www.statistics.gov.my/portal. [last accessed on 2014 dec 11]. dinda, s. (2004), environmental kuznets curve hypothesis a survey. ecological economics, 49(4), 431-455. economic planning unit, (epu). (2015), eleventh malaysia plan 20162020 anchoring growth on people. malaysia: prime minister’s department. ediger, v.s., akar, s. (2007), arima forecasting of primary energy demand by fuel in turkey. energy policy, 35, 1701-1708. egilmez, g., tatari, o. (2012), a dynamic modelling approach to highway sustainability: strategies to reduce overall impact. transportation research part a: policy and practice, 46(7), 1086-1096. ekins, p., anandarajah, g., strachan, n. (2011), towards a low-carbon economy: scenarios and policies for the uk. climate policy, 11(2), 865-882. energy commission, (ec). (2012), national energy balance 2012. malaysia: ministry of energy, green technology and water. energy commission, (ec). (2014), malaysia energy statistics handbook. malaysia: energy commission. gielen, d., changhong, c. (2001), the co2 emission reduction benefits of chinese energy policies and environmental policies: a case study for shanghai, period 1995-2020. ecological economics, 39, 257-270. gonzález-marrero, r.m., lorenzo-a, r.m., marrero, g.a. (2012), a dynamic model for road gasoline and diesel consumption: an application for spanish regions. international journal of energy economics and policy, 2(4), 201-209. haldenbilen, s. (2006), fuel price determination in transportation sector using predicted energy and transport demand. energy policy, 34, 3078-3086. hashim, h., douglas, p., elkamel, a., croiset, e. (2005), optimization model for energy planning with co2 emission considerations. industrial and engineering chemistry research, 44, 879-890. hickman, r., ashiru, o., banister, d. (2010), transport and climate change: simulating the options for carbon reduction in london. transport policy, 17, 110-123. hickman, r., banister, d. (2007), looking over the horizon: transport and reduced co2 emissions in the uk by 2030. transport policy, 14, 377-387. ichinohe, m., endo, e. (2006), analysis of the vehicle mix in the passenger-car sector in japan for co2 emission reduction by a markal model. applied energy, 83, 1047-1061. indati, m.s., bekhet, h.a. (2014), highlighting of the factors and policies affecting co2 emission level in malaysian transportation sector. environmental earth science and engineering, 8(1), 10-18. intergovernmental panel on climate change, (ipcc). (2007), the ipcc fourth assessment report on climate change. geneva: ipcc. international association for natural gas vehicles, (iangv). (2000), available from: http://www.ntl.bts.gov/lib/11000/11400/11453/ iangv_bus_report.pdf. [last accessed on 2014 mar 23]. international energy agency, (iea). (2012), technology roadmap: fuel economy of road vehicles. paris: iea. international energy agency, (iea). (2014a), key world energy statistics. paris: iea. international energy agency, (iea). (2014b), co2 emission from fuel combustion. paris: iea. ivy, y.l.l., bekhet, h.a. (2014), modelling residential electricity mustapa and bekhet: investigating factors affecting co2 emissions in malaysian road transport sector international journal of energy economics and policy | vol 5 • issue 4 • 20151082 consumption function in malaysia: time series approach. electrical electronic science and engineering, 8(3), 1-7. ivy, y.l.l., bekhet, h.a. (2015), examining the feedback response of residential electricity consumption towards changes in its determinants: evidence from malaysia. international journal of energy economics and policy, 5(3), 772-781. johanssons, b. (2009), will restrictions on co2 emissions require reductions in transport demand? energy policy, 36, 3286-3299. kamarudin, s.k., daud, w.r.w., yaakub, z., misron, z., anuar, w., yusuf, n.n. (2009), synthesis and optimization of future hydrogen energy infrastructure planning in peninsular malaysia, hydrogen energy, 34(5), 2077-2088. kari, f., rasiah, r. (2008), automobile emissions and the environment: the malaysian experience. available from: http://www.irdc.ca/en/ ev-132167-201-1-do_topic.html. karlsson, k., meibom, p. (2008), optimal investment paths for future renewable based energy systems using the optimisation model balmorel. hydrogen energy, 33(7), 1777-1787. kasipillai, j., chan, p., 2008. travel management: lessons for malaysia. journal of public transportation. 11(3), 41-56. khalid, r. (2014), towards low carbon economy via carbon intensity reduction in malaysia. economics and sustainable development, 5(16), 123-132. klier, t., linn, j. (2013), fuel prices and new vehicle fuel economy comparing the united states and western europe. environmental economics and management, 66(2), 280-300. lakshmanan, t., han, x. (1997), factors underlying transportation co2 emissions in the usa: a decomposition analysis. transportation research part d, 2(1), 1-15. lim, s., lee, k.t. (2012), implementation of biofuels in malaysian transportation sector towards sustainable development: a case study of international cooperation between malaysia and japan. renewable and sustainable energy reviews. 16(4), 1790-1800. mahlia, t.m.i, masjuki, h.h., choudhury, i.a. (2002), theory of energy efficiency standards and labels. energy conversion and management, 43, 743-761. masjuki, h.h., karim, m.r., mahlia, t.m.i. (2004), energy use in the transportation sector of malaysia. putrajaya: economic planning unit of the prime minister’s department. mattila, t., antikainen, r. (2011), backcasting sustainable freight transport systems for europe in 2050. energy policy, 39, 1241-1248. ministry of domestic trade and consumer affairs malaysia, (mdtca). (2012), petroleum information 2012-2012. available from: http:// www.kpdnkk.gov.my/en/maklumat-petroleum-2012. [last accessed on 2014 may 27]. ministry of natural resources and environment malaysia, (nre). (2011), second national communication to the unfccc. malaysia: nre. ministry of transport malaysia, (mot). (2013), transport statistics malaysia. available from: http://www.mot.gov.my. [last accessed on 2014 dec 11]. mofleh, a., taib, s., salah, w.a. (2010), malaysian energy demand and emissions from the transportation sector. transport, 25(4), 448-453. montgomery, d.c., peck, e.a., vining, g.g. (2006), introduction to linear regression analysis. hoboken: john wiley & sons. ong, h.c., mahlia, t.m.i., masjuki, h.h. (2011), a review on emission and mitigation strategies for road transport in malaysia. renewable and sustainable energy reviews, 15, 3516-3522. ong, h.c., mahlia, t.m.i., masjuki, h.h. (2012), a review on energy pattern and policy for transportation sector in malaysia. renewable and sustainable energy reviews, 6(1), 532-542. ozturk, i. (2015), measuring the impact of energy consumption and air quality indicators on climate change: evidence from the panel of unfcc classified countries. environmental science and pollution research. available from: http://www.link.springer.com/ article/10.1007/s11356-015-4757-3. ozturk, i., uddin, g.s. (2012), causality among carbon emissions, energy consumption and growth in india. economic research, 25(3), 752-775. pallant, j. (2013), spss survival manual. 5th ed. buckingham: open university press. pasaoglu, g., honselaar, m., thiel, c. (2012), potential vehicle fleet co2 reductions and cost implications for various vehicle technology deployment scenarios in europe. energy policy, 40, 404-421. pongthanaisawan, j., sorapiatana, c. (2013), greenhouse gas emission from thailand’s transport sector: trends and mitigation options. applied energy, 101, 288-298. profillidis, a.v., botzoris, n.g., galanis, t.a. (2014), environmental effects and externalities from the transport sector and sustainable transportation planning – a review. international journal of energy economics and policy, 4(4), 647-661. saboori, b., sulaiman, j., mohd, s. (2012), economic growth and co2 emissions in malaysia: a cointegration analysis of the environmental kuznets curve. energy policy, 51, 184-191. sadorsky, p. (2013), do urbanization and industrialization affect energy intensity in developing countries? energy economics, 37, 52-59. sadorsky, p. (2014), the effect of urbanization on co2 emissions in emerging economies. energy economics, 41, 147-153. sang, y.n., bekhet, h.a. (2014), determining key predictors influencing intenstion to use electric vehicles in malaysia. international conference and utility exhibition 2014 on green energy for sustainable development, 19th-21st march, thailand. sang, y.n., bekhet, h.a. (2015), modelling electric vehicle usage intentions: an empirical study in malaysia. journal of cleaner production, 92, 75-83. shahid, s., minhans, a., othman, c.p. (2014), assessment of greenhouse gas emission reduction measures in transportation sector in malaysia. journal teknologi, 70(4), 1-8. shu, y., lam, s.n.n. (2011), spatial disaggregation of carbon dioxide emissions from road traffic based on multiple linear regression model. atmospheric environment, 45, 634-640. silitonga, a.s., atabani, a.e., mahlia, t.m.i. (2012), review on fuel economy standard and label for vehicle in selected asean countries. renewable and sustainable energy reviews, 16, 1683-1695. sultan, r. (2010), short-run and long-run elasticity of gasoline and demand in mauritius: an ardl bound test approach. emerging trends in economics and management science, 1(2), 90-95. tan, s.t., hashim, h., w. s. ho, w.s., lee, c.t. (2013), optimal planning of waste-to-energy through mixed integer linear programming. international journal of environmental, ecological, geological and geophysical engineering, 7, 183-190. timilsina, g.r., shrestha, a. (2009), transport sector co2 emissions growth in asia: underlying factors and policy options. energy policy, 37(11), 4523-4539. wang, c., larsson, m., ryman, c., grip, c.e., wikstrom, j.o., johnsson, a., engdahl, j. (2008), a model on co2 emission reduction in integrated steelmaking by optimization methods. energy research, 32, 1092-1106. wang, s.s., zhuo, d.q., zhuo, p., wang, q.w. (2011), co2 emission, energy consumption and economic growth in china: a panel data analysis. energy policy, 39, 4870-4875. wang, t., lia, h., zhang, j., lua, y. (2012), influencing factors of carbon emission in china’s road freight transport. social and behavioral sciences, 43, 54-64. wohlgemuth, n. (1997), world transport energy demand: methodology and elasticities. energy policy, 25, 1109-1119. world bank. (1992), world development report. washington, d.c.: world bank. world bank. (2014), co2 emissions (metric tons per capita). the world mustapa and bekhet: investigating factors affecting co2 emissions in malaysian road transport sector international journal of energy economics and policy | vol 5 • issue 4 • 2015 1083 bank group. available from: http://www.data.worldbank.org/ indicator/en.atm.co2e.pc. wu, l.b., kaneko, s.j., matsuoka, s.j. (2005), driving forces behind the stagnancy of china’s energy-related co2 emissions from 1996-1999: the relative importance of structural change, intensity change and scale change. energy policy, 33(3), 319-335. xu, b., lin, b, (2015), factors affecting co2 emissions in china’s transport sector: a dynamic nonparametric additive regression model. cleaner production, 101, 311-322. xu, s.c., he, z.x., long, r.y. (2014), factors that influence carbon emissions due to energy consumption in china: decomposition analysis using lmdi. applied energy, 127, 182-193. yan, x., crookes, r.j. (2009), reduction potentials of energy demand and ghg emission in china’s road transport sector. energy policy, 37(2), 658-668. yang, c., yeh, s., zakerinia, s., ramea, k., mccollum, d. (2015), achieving california’s 80% greenhouse gas reduction target in 2050: technology, policy and scenario analysis using ca-times energy economic systems model. energy policy, 77, 118-130. zanni, a.m., bristow, a.l. (2010), emissions of co2 from road freight transport in london: trends and policies for long run reductions. energy policy, 38, 1774-1786. pointtmp ole_link2 ole_link3 ole_link1 ole_link4 ole_link5 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. . international journal of energy economics and policy | vol 9 • issue 5 • 2019316 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(5), 316-321. energy usage, internet usage and human development in selected western african countries jeremiah ejemeyovwi1, queen adiat1*, edikan ekong2 1department of economics and development studies, college of business and social sciences, covenant university, ota, nigeria, 2department of electrical and information engineering, college of engineering covenant university, ota, nigeria. *email: queen.adiat@gmail.com received: 10 march 2019 accepted: 01 july 2019 doi: https://doi.org/10.32479/ijeep.7611 abstract the examination of energy usage and information and communication technology (ict) usage in terms of their role in the improvement of human development (hd) was the study’s objective. a panel analysis is carried out on world bank data (2000-2014) from selected western african countries, with notable energy usage within the region. the study utilizes generalized least squares, the fixed effect model and the random effect model econometric estimation techniques to determine the degree of relationship and impact existing between the variables of interest. the results indicate that internet usage and energy usage affect hd in the selected west african countries. the policy implication from the findings posit that it is expedient that the government and private sector, exert financial and non-financial contributions to ensure that energy and ict facilities are readily available for use. this would improve the level of the two major hd components (health and education). keywords: energy usage, information and communication technology usage, human development, western africa jel classification: q4 1. introduction in recent times, information and communication technology (ict) and energy consumption, have proven to be key factors that greatly influence human development (hd). according to kuyoro et al. (2012), ict is being integrated into, virtually, all aspects of human activity, at a rapid rate. this advancement, has been accompanied by a thriving argument on the actual contribution of ict in relation to productivity and growth as well as in human welfare both for developed and developing countries. notwithstanding, niebel (2018), stated that productivity and growth form the basis to enhance the standard of living of a country and that adopting ict is a “key driver” of this productivity and growth. this swift integration of ict is believed to create a platform for hd to assume a certain pattern on several influential fronts (imhonopi et al., 2013). research is ongoing as to the key functions ict can perform in supporting crucial aspects of hd such as education, health, eliminate poverty and in improve the employment rate. in accordance with niebel (2018), these researches, show that ict has ample potential to provide and foster, stable platforms, expand growth opportunities and incure advancements in modern economies globally. as regards energy in relation to hd, high levels of energy use is most often, associated with an improved level of hd (pirlogea, 2012). a certain criterion known as hd index (hdi) is adopted to measure the amount of hd in relation to certain factors and it has been shown that advanced countries with a low per capita energy consumption have high index scores. in the analysis of regression, it is revealed that the hdi experiences steady increment for certain levels of energy consumption (steinberger and roberts, 2009). this journal is licensed under a creative commons attribution 4.0 international license ejemeyovwi, et al.: energy usage, internet usage and human development in selected western african countries international journal of energy economics and policy | vol 9 • issue 5 • 2019 317 hence, under-developed countries incur low hdi values in relation to energy consumption while more advanced countries with high hdi scores have a corresponding high energy consumption level (martínez and ebenhack, 2008). adequate energy supply, plays a vital role in economic and social development which also translates to hd. energy evolution (from use of traditional fuels; such wood, to use of electricity), over time, and the enhancement of energy systems, has led to an improvement in the quality and standard of energy types (inaki et al., 2014). energy in clean and reliable forms, positively affect, the hd rationale which includes health and education (pirlogea, 2012). the standard and quality of resources which provide energy, are evaluated basrd on the availability of usable energy outputs and adequate levels of emission depth (ray et al. 2016). hence adoption of efficient energy resources cannot be overemphasized in the provision of an array of advantages to a country’s economy and hd (akerkar et al., 2016). drawing from the above introductory paragraphs, the objective of this study is to examine the effect of ict adoption and energy consumption on hd (labour force) in western africa. to achieve this, the outline of the study entails five sections. section one contains the introductory section, section two consists of the literature review on the subject matter, section three consists of the methodology, section four consists of the results and discussion, while section five discusses the conclusion and recommendation of the study. 2. literature review the link between ict adoption, electricity consumption and hd is largely an under researched topic. while scholars focus their studies on either the correlation between ict adoption and hd (kuyoro et al., 2012) or energy consumption and hd (karekezi et al., 2012, niu et al., 2013) only scanty literature exist to effectively explain how ict adoption works through electricity consumption to improve outcomes in education and health. in the event that studies have related all three, as in (salahuddin and alam, 2016) and salahuddin et al. (2016) the emphasis was on economic growth. however, economic growth alone does not represent hd but rather longevity, good health and high education levels (stanton, 2007). in fact the hdi was created to challenge policies that encourage increasing gni per capital at the expense of improved outcomes in knowledge and standard of living (united nations development, 2018). poor electricity coverage in african countries forces most households to rely primarily on biomass fuel in the form of wood for cooking (youssef et al., 2016) hence increasing their energy footprints and making them the worst hit by the adverse effects of climate change which is poor health. the energy/ carbon footprint concept has been represented in most studies to assess the overall ghg emissions associated with the life cycle of a product or process at the national level, (arto et al., 2014, allen and pentland 2011) organizational level (malmodin and lundén, 2018) and household level (world health organization, 2008). arto et al., 2014 found that in developd countries the energy footprints was higher than energy consumption at +13% compared to underdevloped regions at −16%. (chowdhury et al., 2013), recommend that investment in modern forms of electrictiy, wireless networks and cloud computing would lead to a reduction in power consumption and consequently reduce the energy footprint. these recommendations although isolated, draw up a pattern, that outline how innovations in ict have led to better and more modern forms of electricity reducing the energy footprints, thereby conserving energy and improving health, especially for future generations. the sustainable development goals (sdg’s) particularly sdg 7: ensure access to affordable, reliable, sustainable and modern energy for all, (united nations, 2015) reiterated that developing clean forms of energy was a global issue. scholars have proposed that investing in education, would lead to developments in ict and overcome this challenge (aziz et al., 2015, dias et al., 2006). indeed (united nations, economic and social council, 2014) highlighted how icts could mitigate the harmful effects of waste and carbon emission to improve processes for economic growth and hd while highlighting its dependence on human intellect to drive this potential. houghton, 2009 also proposed that ict can be used to generate smart grids, motor systems and efficient transport systems to effectively reduce energy emissions. the study went further to highlight how investments in telecommunications and mobile technology was a catalyst for development in some rural communities in kenya, indonesia and the philippines. notably, increase in ict adoption has led to inescapable increase in energy usage over time (chandramouli, 2015, salahuddin and alam, 2016). heddeghem et al., 2014 reported that ict advancements led directly to increase in electricity consumption from communication networks, personal computers and data centers causing a percentage increase in global electricity consumption from 3.9% in 2007 to 4.6% in 2012. while this also led to emission of greenhouse gases, which are established to have adverse effects on human health and positive effect in the agriculture sector (ejemeyovwi et al., 2018). there is evidence that the pros to electricity consumption far outweigh the cons (salahuddin and alam, 2016; ouedraogo, 2013). this is especially true of african countries where low electricty consumption had a strong correlation with mortality of children under 5 years and low life expectancy in 5 countires including ivory coast and tunisia. (youssef et al., 2016). the study went further to recommended advancement in ict in order to expand electicity sources specifically for cooking that would improve the mortality indicators across africa. nonetheless, if policy makers continue to ignore the need to conserve energy, while pursuing more advanced technology, the appropriate policies would not be driven, to improve the life of citizen’s and protect their right to good health and long life. dincer, 1999, opined that it in establishing developmental policies, sustainability is important, and that a balance should be created between human needs for development, and energy conservation. dias et al. 2006 corroborated these findings in concluding that driving material needs should not be the primary focus of developing countries but it was in their best interest to ejemeyovwi, et al.: energy usage, internet usage and human development in selected western african countries international journal of energy economics and policy | vol 9 • issue 5 • 2019318 intensify investment in advanced technology, while at the same time understand the energy implications and ensure that they these innovations are environment friendly. thus, it is important to develop sources of energy that were not harming human lives in a bid to make them better (dias et al., 2006, goldemberg and coelho, 2004). in a study on electricity consumption in hospitals providing intensive care, (pollard et al., 2014) concluded that it was possible to predict electricity consumption patterns, in order to deliver care whilst maintaining safety. improved outcomes in education is mostly defined in terms of the causal reltionship it has on ict adoption, and electricity consumption (dias et al., 2006, houghton, 2009), few studies have demonstrated how hd in education could also be an effect of ict advancement and electricity consumption. (niu et al., 2013) demonstrated that this interaction was both cause and effect. very recently big data sprung up from advancements in ict and has been used as an effective tool in increasing student performances, fuelling better research and improving administration within educational institutions. (ekong et al., 2019; huda, et al., 2017). in 2013, 1% of energy consumed globally was from three billion personal computers, while 1.5% of electricity was consumed by 30 million computer servers. it is extrapolated that in 2020 there would be up to 50 billion internet connected devices. (chandramouli, 2015, stauffer, 2013). this is of particular importance because not only does big data drive hds in education, it is also a useful tool to track energy consumption patterns both at the household and organizational level in order to drive sustainable electricity consumption (koseleva and ropaite, 2017). however, there persists an ongoing debate as to whether there are any economic benefits of ict investments particularly in sub saharan africa with studies producing opposing findings ejemeyovwi et al. (2018) found that while there is no direct relationship between investment in telecommunications and hd, an investment in telecommunications in ecowas countries would lay the foundation for ict adoption which would then lead to hd. bomah, (2014) on the other hand, blames the digital divide for the low hdi in african countries, by deducing a proportional relationship between hd and access to digital resources. yet (kuyoro et al., 2012) argued that despite the digital divide, the ubiquitous nature of ict can spread information, improve trade investments, and serve as a catalyst for hd. the study however pointed out that if ict was not driven properly by government, private sector and development stake holders, it had the potential to deepen inequality. one salient point being overlooked by these studies is the fact that ict adoption requires the availability electricity (energy) for effective operation which ensures hd. this shows the gap in literature to be filled by this study. 3. methodology 3.1. the empirical model the empirical model that underpins this relationship takes its cue from the empirical model of ejemeyovwi and osabuohien (2018); ejemeyovwi et al. (2018) which assumes the hd model and expresses hd as a function of institutions, technology and other growth components with some augmentation. the model explains that for hd to be achieved, a number of exogeneous factors must be present such as technology adoption, energy usage, institutions, and other control variables should be put in place. this study augments the empirical hd model by the introduction of energy usage as it is necessary for the occurrence of hd. the implicit functional form of the model is given as: y = f (ener, intus, pse, rule, credit, gdpcgr) (1) the explicit form of the model is given as: yit = α0 + α1 enerit + α2 intus + α3 pse+ α4 rule+ α5 credit + α6 gdpcgr + μit (2) the error term is hypothesised to be purely random while the all parameters (α0, α2, α3, α4, α6, α1 and α5) are hypothesised as positive values while the variables are transformed by taking the natural logs and the result is seen in equation (3). yit = α0 + α1enerit + α2intusit + α3pseit+ α4ruleit+ α5creditit + α6 gdpcgrit + μit (3) where “yit” represents hdi which proxies economic development of country ‘i’ at time ‘t’ as used in ejemeyovwi and osabuohien (2018); ejemeyovwi et al. (2018) as a proxy; “enerit” stands for energy utilisation of country ‘i’ at time ‘t’, which represents the consumption of energy by the consumers within an economy and a major contribution to this empirical model; “intusit” represents internet usage of country ‘i’ at time ‘t’; “pseit” stands for primary school enrolment of country ‘i’ at time ‘t’; ruleit” represents the rule of law (an institutional variable) which shows the perception of the consumers about the level and impact of law enforcement within a country ‘i’ at time ‘t’, “creditit” represents domestic credit available to the private sector which represents the financial sector of country ‘i’ at time ‘t’; and “gdpcgrit” which represents economic production and components of country ‘i’ at time ‘t’. tchamyou (2015); ejemeyovwi et al. (2018) and ejemeyovwi and osabuohien (2018) affirmed the use of hdi as a measure of inclusive growth (consistent with the african knowledge economy); number of internet users is used as one of the proxies of ict adoption while the control variables are consistent with literature for inclusive growth – hd and also essential for the schumpeterian growth model. the apriori expectations of study from theory state that internet usage should have a significant positive impact on hd in west africa. the inclusion of these variables is necessary to eliminate omitted variable bias which could alter the reliability and validity of the estimated coefficients to be derived from the study. 3.2. technique of estimation the study utilizes three econometric techniques of estimation, namely: the generalized least squares (gls), the fixed effect model (fem) and the random effect model (rem) panel data analysis. the techniques of estimation are supplemented by the hausman test. the gls methodology is utilized by this study as the baseline regression model to have a futuristic look at what is expected while the rem and the fem techniques are the major regression models ejemeyovwi, et al.: energy usage, internet usage and human development in selected western african countries international journal of energy economics and policy | vol 9 • issue 5 • 2019 319 utilized given the objectives of the study and the nature of the panel dataset. the estimated coefficients could be used to determine the degree of relationship and impact existing between the variables of interest. the hausman test is usually performed after the fem and rem to determine the most appropriate technique of analysis between the fem and the rem techniques of estimation. the hausman test uses the probability value of its chi-square test to determine the most appropriate estimation method. the rule of thumb for deciding the most appropriate model (between the rem and fem) states that: given that the fem was run first before the rem if the chi-square probability value of the hausman test is <0.05, the fem is most appropriate and if the chisquare probability value is >0.05, the rem is most appropriate for interpretation and policy recommendation. furthermore, the use of the fem signifies the of individual-specific fixed effects which could affect the result if not taken care of during the estimation process while the choice of the rem indicates the absence of the individual specific effects. 3.3 sources of data and variable description the data utilised by this study encompasses data from 9 selected western african countries because of their notable energy usage within the west african region, ict adoption rate, hd level and reliable data availability from the world bank (2018), spanning for the time period 2000 to 2014. the dataset consists of selected countries which include benin, cape verde, cote d’ivoire, ghana, guinea bissau, niger, nigeria, senegal and togo. the variables that were included in the model [equations 1, 2, and 3] above are defined in table 1 with the presentation of the sources of data. 4. econometric results and discussions the results for the baseline regression (gls), fixed and rem (fem and rem) estimation techniques utilised by the study are presented in this section. the section commences by the display of the results of the hausman test which recommends the most appropriate model regression between the rem and the fem. the rule of thumb for deciding the most appropriate model (between the rem and fem) states that: given that the fem was run first before the rem, if the chi-square probability value of the test is <0.05, the fem is most appropriate and if the chi-square probability value is >0.05, the rem is most appropriate for interpretation and policy recommendation. the probability value of the hausman chi-square test recommends the interpretation of the fem result given that it is statistically significant (<0.05). table 2 shows the hausman test result: table 3 displays the empirical results of the study and the general interpretation indicate that the number of groups present within the dataset was nine (9). the correlation between the error term and independent variables show a negative correlation for the fem technique which indicates presence of time-invariant characteristics unique to the countries captured in the constant while the correlation between the error term and independent variables for the rem technique report the zero. the f–statistics and its probability value that show the overall significance of the model indicate a good overall fit of the model following the rule of thumb because the probability value is “0.00” and more importantly <0.05. the wald test also indicates a similar overall model fit like the f–statistics and given that the chi-square values are not equal to zero, it is also acceptable. with regards to the variable-specific results, a major variable of interest in this study is energy usage and its empirical relationship with hd. the coefficient of energy usage indicates a statistically significant result for the gls, fem and rem, statistically significant values at 1% level were observed. this is shown by the probability values of the coefficient for which the decision rule for the probability values (p value) state that the p value for should be <0.01 for statistical significance at 1% level, 0.05 for statistical significance at 5% level and <0.10 for statistical significance at 10% level of significance respectively. this economically implies that for the selected west african countries, an increase energy usage will impact hd significantly at 99% level of significance. the result flows with the a priori (theoretical) expectation in terms of direction of relationship. the magnitude of relationship shows that a 1% increase in energy usage will contribute positively, a less than proportionate (0.14%) increase to hd in the selected west african countries. this result is in agreement with pirlogea (2012). in terms of another major variable of interest internet usage and its empirical relationship with hd, the coefficient indicates a statistically significant result at 1% level for the fem estimation (as recommended by the hausman test). the direction and magnitude of relationship flows with the apriori (theoretical) coefficient. the empirical result shows that a 1% increase in in table 1: variables definition, mean, and source of data data identifier data source measurement human development (proxied by human development index) hdi undp, 2015 unit energy usage ener wdi, 2018 unit number of internet users/100 people intus wdi, 2018 unit primary school enrolment (pupils) – female pse wdi, 2018 number institution rule wgi, 2018 constant us$ domestic credit by financial institutions credit wdi, 2018 percent of gdp gross domestic product per capita growth rate gdppcgr wdi, 2018 percent source: compiled by the authors’ table 2: hausman test result chi 2 (4): 206.54 prob value: 0.00 decision rule fixed effect random effect accept reject source: computed by the authors’ ejemeyovwi, et al.: energy usage, internet usage and human development in selected western african countries international journal of energy economics and policy | vol 9 • issue 5 • 2019320 energy usage will contribute positively, a less than increase of proportionate 0.02% to hd in the selected west african countries. this economically implies that for the selected west african countries, an increase internet usage will impact hd significantly at 99% level of significance and this finding, is in line with ejemeyovwi et al. (2018); ejemeyovwi et al. (2019). the policy implication from the findings posit that priority should be put on hd as examined in this study, for which the components of hd include health and education. the average human needs a clean bill of health and sound mind to increase productivity in every field of endeavor while in terms of education, creating comfortable learning environments is also required for effective education administration. learning environments in this modern era exceeds locations other the conventional classrooms. the advent of online learning requires one form of ict device or the other to become a reality. also, ict devices like projectors, laptops etc., have proved useful as learning aids as they can be used in passing across information to students and other individuals involved in the learning process. operation of ict equipment also require one form of skillset or the other and this can be acquired through education. the equipment utilized also require one form of energy usage or the other for its operation. 5. recommendation and conclusion this study establishes a linkage between ict, energy consumption and hd through the investigation of their effect on hd in utilizing the gls, fixed and rem (fem and rem) estimation techniques. evidence from the analysis reveal that energy usage and internet usage have a significant impact on hd statistically at 5% level of significance which are in line with the findings of pirlogea (2012) and ejemeyovwi et al. (2019) respectively. hd is necessary as well as ict adoption and energy usage, hence, it is expedient that the government and private sector should exact more efforts in terms of financial and non-financial contributions to ensure that more energy and ict facilities made available for usage since it helps to improve the level of hd for which the two major hd components are health and education parameters. akin to the findings, further related researches are tasked with identifying the impact of the interaction between ict and energy usage and also the direction of relationship that exist between the ict adoption, energy usage and hd within and outside western africa. references akerkar, s., joshi, p.c., fordham, m. (2016), cultures of entitlement and social protection: evidence from flood prone bahraich, uttar pradesh, india. world development, 86(c), 46-58. allen, s.r, pentland, c. (2011), carbon footprint of electricity generation; post note 383. london: the parliamentary office of science and technology. arto, i., capellán, i., lagoy, r., bueno, g. (2014), the energy footprint of human development. jornadas de economia critica, 4(5), 134-238. aziz, m., nusrat, s., sheela, d. (2015), the impart of political regime and governance on asean economic growth. journal of southeast asian economies, 32(3), 375-389. bomah, k.b. (2014), digital divide: effects on education development in africa. lyit dept. of computing: technical writing presentation. ireland: letterkenny institute of technology. p1-20. available from: https://www.researchgate.net/publication/275350414_digital_ divide_effects_on_education_development_in_africa. goldemberg, j., coelho, s.t. (2004), renewable energy traditional biomass vs. modern biomass. energy policy, 32(6), 711-714. chandramouli, v. (2015), comparative carbon footprint assessment of the manufacturing and use phases of two generations of amd accelerated processing units. carlifonia, usa: advanced micro devices, inc. chowdhury, c.r., chatterjee, a., sardar, a., agarwal, s., nath, a. (2013), a comprehensive study on cloud green computing: to reduce carbon footprints using clouds. international journal of advanced computer research, 3(8), 78-85. dias, r.a., mattos, c.r., balestieri, j.a.p. (2006), the limits of human development and the use of energy and natural resources. energy policy, 34, 1026-1031. dincer, i. (1999), environmental impacts of energy. energy policy, 27(14), 845-854. ejemeyovwi, j.o., obindah, g., doyah, t. (2018), carbon dioxide emissions and crop production: finding a sustainable balance. international journal of energy economics and policy, 8(4), 1-7. ejemeyovwi, j.o., osabuohien, e.s. (2018), mobile technology adoption and inclusive growth in west africa. contemporary social science, 20(1), 31-53. ejemeyovwi, j.o., osabuohien, e.s., johnson, o.d., bowale, k.e. (2019), internet usage and inclusive growth in west africa. journal table 3: econometric results (dependent variable: human development) predictor variables gls fem rem energy usage 0.24* (0.00) 0.14* (0.00) 0.24* (0.00) internet usage (lintusph) −0.01*** (0.09) 0.02* (0.00) −0.01*** (0.09) primary school enrolment 1.32* (0.00) 0.86 (0.00) 1.32* (0.00) rule of law (institution) −0.09* (0.00) −0.02* (0.00) −0.09* (0.00) domestic credit provided by financial sector 0.02 (0.12) −0.007 (0.31) 0.02 (0.12) gdp per capita growth rate 0.003 (0.5) 0.002 (−0.60) 0.003 (0.5) constant −3.07* (0.00) −0.2.29* (0.00) −3.07* (0.00) f-statistics 80.72 prob >f 0.000 wald chi2 (5) 744.35 744.35 prob >chi2 0.000 0.000 0.000 corr (ui, xb) 0 0.10 0 number of groups 9 9 9 the values in the parenthesis ‘()’ are the probability values; gls: generalised least squares; fem: fixed effect model; rem: random effect model; *,** and *** denotes that the coefficients are significant at 1%, 5% and 10% respectively. source: the authors’ ejemeyovwi, et al.: energy usage, internet usage and human development in selected western african countries international journal of energy economics and policy | vol 9 • issue 5 • 2019 321 of economic structures, 8(15), 10-20. ejemeyovwi, j.o., osabuohien, e.s., osabohien, r. (2018), ict investments, human capital development and institutions in ecowas. international journal of business research, 15(4), 463-474. ejemeyovwi, j.o., osabuohien, e.s., osabuohien, r. (2018), investment in technology and human capital development in ecowas. international journal of economics and business research, 15(4), 463-474. ekong, e., adiat, q., ejemeyovwi, j., alalade, a. (2019), harnessing big data technology to benefit effective delivery and performance maximization in pedagogy. international journal of civil engineering and technology, 10(1), 2170-2178. heddeghem, v.w., lambert, s., lannoo, b., colle, d., pickavet, m., demeester, p. (2014), trends in worldwide ict electricity consumption from 2007 to 2012. computer communications, 50, 64-76. houghton, j.w. (2009), ict and the environment in developing countries: an overview of opportunities and developments. communications and strategies, 76, 39. available from: https://www.ssrn.com/ abstract=1659765. huda, m., maseleno, a., shahrill, a., jasmi, k.a., mustari, i., basiron, b. (2017), exploring adaptive teaching competencies in big data era. international journal of emerging technologies in learning, 12(3), 68-83. imhonopi, d., urim, u.m., igbadumhe, f.a. (2013), information and communication technologies and human development in nigeria: forging the nexus. international journal of information communication technologies and human development, 6(1), 18-34. inaki, a., inigo, c., rosa, l., gorka, b. (2014), the energy footprint of human development. xiv jornadas de economía crítica, 4(5), 134-151. karekezi, s., mcdade, s., boardman, b., kimani, j. (2012), energy, poverty and development. in: global energy assessment-toward a sustainable future. ch. 2. cambridge, uk and new york, usa: cambridge university press, international institute for applied systems analysis, laxenburg, austria. p151-190. koseleva, n., ropaite, g. (2017), big data in building energy efficiency; understanding of big data and main challenges. procedia engineering, 172, 544-549. kuyoro, s.o., awodele, o., okolie, s.o. (2012), ict: an effective tool in human development. international journal of humanities and social science, 2(7), 157-162. martínez, d.m., ebenhack, b.w. (2008), understanding the role of energy consumption in human development through the use of saturation 150 de 238 phenomena. energy policy, 36(4), 1430-1435. malmodin, j., lundén, d. (2018).,the energy and carbon footprint of the global ict and e and m sectors 2010-2015. sustainability mdpi, 10(9), 3027. niebel, t. (2018), ict and economic growth-comparing developing, emerging and developed countries. world development, 104, 197-211. niu, s., jia, y., wang, w., he, r., hu, l., liu, y. (2013), electricity consumption and human development level: a comparative analysis based on panel data for 50 countries. electrical power and energy systems, 53, 338-347. ouedraogo, n.s. (2013), energy consumption and economic growth: evidence from the economic community of west african states (ecowas). energy economics, 36, 637-647. pirlogea, c. (2012), the human development relies on energy. panel data evidence. procedia economics and finance, 3, 496-501. pollard, a.p., taylor, t.j., tillyard, a. (2014), the carbon footprint of acute care: how energy intensive is critical care? public health, 128(9), 771-776. ray, s., ghosh, b., bardhan, s., bhattacharyya, b. (2016), studies on the impact of energy quality on human development index. renewable energy, 92(2016), 117-126. salahuddin, m., alam, k. (2016), information and communication technology, electricity consumption and economic growth in oecd countries: a panel data analysis. electrical power and energy systems, 76, 185-193. salahuddin, m., alam, k., ozturk, i. (2016), the effects of internet usage and economic growth on co2 emissions in oecd countries: a panel investigation. renewable and sustainable energy reviews, 62, 1226-1235. stanton, e. (2007), the human development index: a history. political economy research institute peri. working paper series no 127. amherst, massachusetts, usa: university of massachusetts. stauffer, w.n. (2013), energy-efficient computing. energy futures spring issue, june 20, 2013, mit energy initiative. available from: https://www.mitei.mit.edu/news/energy-efficient-computing. steinberger, j., roberts, j.t. (2009), across a moving threshold: energy, carbon and the efficiency meeting of global human development needs. social ecology working paper 114. tchamyou, v.s. (2015), the role of knowledge economy in african business. journal of the knowledge economy, 8(4), 1189-1228. united nations development program. (2018), human development reports. baltimore: human development report office. available from: http://www.hdr.undp.org/en/content/human-developmentindex-hdi. [last retrieved on 2018 nov 14]. united nations, economic and social council. (2014), information and communications technologies for inclusive social and economic development. geneva: commission on science and technology for development. united nations. (2015), transforming our world; 2030 agenda for sustainable development goals. new york: united nations. world health organization. (2008), reducing your carbon footprints can be good for your health. a list of mitigating factors. world health day 2008 global. geneva: world health organization. p4. youssef, a.b., lannes, l., rault, c., soucat, a. (2016), energy consumption and health outcomes in africa. iza discussion papers, working paper no 1/2016. p1-31. world bank. (2018), world development indicators. washington dc: world bank publications. available from: https://www.datacatalog. worldbank.org/dataset/world-development-indicators. [last retrieved on 2018 nov 18]. tx_1~at/tx_2~at international journal of energy economics and policy | vol 7 • issue 6 • 201778 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(6), 78-84. japanese households’ energy saving behaviors toward social risks by conjoint analysis#1 shin kinoshita* faculty of economics, ryukoku university, 67 tsukamoto-cho, fukakusa, fushimi-ku, kyoto, japan. *email: skinoshita@econ.ryukoku.ac.jp abstract aftermath the earthquake in march 2011, japanese face the drastic changes in energy environment. we have been concerned about electric power shortage because nuclear power plants cease their operation. in tokyo, people suffered from the planned power outage and even in osaka people has been often required to save electricity use at the peak of demand. in case the shortage of electricity, we should reduce electricity use. in addition, we should promote renewable energy sources such as solar and wind power instead of nuclear power and fossil fuel such as oil and coal to reduce greenhouse gas emissions. i analyze the factors that households reduce electricity use by conjoint analysis. i find that households reduce electricity use if monthly electricity rates increase and if they recognize the possibility of outages. it might be effective to announce the possibility of outages or instability of supply to households as a nudge. keywords: energy saving, conjoint analysis, outages jel classifications: c25, l94, q48 # this study was aided by research funding from ryukoku university, japan. 1. introduction since the great east japan earthquake in march 2011, japanese people have faced drastic changes to the energy environment. the nuclear meltdown at fukushima was an accident of epic proportions and it is now difficult to operate nuclear power plants in the country due to shifts in public and political opinion away from supporting nuclear power. since the earthquake, japan has relied on natural gas (liquefied natural gas [lng]). however, this is problematic because of greenhouse gas emissions and the increasing international momentum and resolve to mitigate anthropogenic climate change. after the earthquake, households served by the tokyo electric power company experienced planned power outages. even households covered by kansai electric power company have often been required to curb electricity use at the peak of demand in summer and winter while nuclear power plants remain out of operation pending the outcome of inspections. in japan, energy saving is an important topic because it can help prevent electric power shortages and climate change. the promotion of renewable energy sources such as solar and wind power is similarly important, instead of favoring and focusing on nuclear power and fossil fuels such as oil and coal. energy saving among households is important because the co2 emissions of households have slightly increased and the share of residential electric power in household energy consumption is large1. in fiscal year 2011, energy consumption in household sector is more than 2.8 times compared with 1973. the share of electricity in household sector is 50% in fiscal year 2011. there are some approaches to prompt energy saving. some local governments and electric power companies implement the demand response system to change the electricity demand of consumers. 1 the agency for natural resources and energy in the ministry of economy, trade and industry (2014) “white paper about energy in fiscal year 2013” available from http://www.enecho.meti.go.jp/about/faq/001/ kinoshita: japanese households’ energy saving behaviors toward social risks by conjoint analysis international journal of energy economics and policy | vol 7 • issue 6 • 2017 79 this system changes the patterns of consumers’ behavior through an electricity rate system and an incentive payment when wholesale prices are higher and the system reliability is lower. the demand response system is divided into two types: the electricity rate type and nega-watt deal type. the time-of-day rate system, the real-time rate system and the peak load rate system are the examples of the electricity rate type. the time-of-day rate system sets higher price when electricity use is tight. the real-time rate system changes electricity rates moment by moment in response to the balance of demand and supply. the peak load rate system changes electricity rates at the peak and at the off-peak. in the negawatt deal, an electric power company contracts with customers and if customers reduce electricity use they gain rewards from the electric power company. the factors affecting households’ energy saving is analyzed using conjoint analysis. conjoint analysis is one of the stated preference methods and, in this context, households determine whether to save electricity use under a hypothetical situation. monthly electricity rates, co2 emissions, the stability of electricity supply and energy sources are adopted as factors. in the short-term, energy saving is justified in terms of ensuring a better match between electricity demand and supply, while in the long-term energy saving is important to reduce greenhouse gas emissions and thus militate against climate change on the one hand while also dealing with security of supply concerns. both types of energy saving are important. energy shortages will continue unless nuclear power plants resume operations and renewable energy sources prevail. in the short-term, electricity use should be reduced to minimize the frequency and duration of sudden power outages. after the earthquake, in the tokyo electric power company’s domain, households experienced planned outages. on the other hand, in the area supplied by kansai electric power company, households have only been required to reduce electricity use. realistically, the possibility of outages there is too small. however, if it indeed transpires that nuclear power plants do not resume operations in the future, this increases the salience of saving more electricity in case of energy shortages and planned or unplanned outages. even if renewable energy sources prevail, electricity supply may be unstable in general because it depends on weather conditions. i analyze that households reduce electricity use if they recognize the possibility of outages and its duration lasts for many hours. usually, households respond to relevant prices. if electricity rates rise, households will reduce electricity use. however, we want to know whether households save electricity use to avoid climate change and outages. co2 emissions, the stability of electricity supply and energy sources are non-monetary factors. if they save electricity use for non-monetary reasons, this is an interesting finding. clearly, outage costs are very high once such outages occur. some households may save energy for non-monetary reasons that is social norm. free-riding is also a serious problem in the context of long-term energy saving. some people will not reduce electricity use on the assumption that others will reduce more electricity use or that any reduction on their part will be in consequential in overall, population level, terms. the relationship between energy saving behavior and preferences for energy sources is focused. it would be suggestive if households who object to nuclear power and support renewable energy sources save electricity use. this paper consists of the following sections. in section 2, i introduce some related studies. in section 3, i explain the conjoint analysis employed herein. in section 4, i present results from a questionnaire. in section 5, i delineate the econometric methods used to analyze the foregoing survey data and present estimation results in section 6. in section 7, i propose some policy implications. 2. related literature after the great east japan earthquake in march 2011, many studies about energy saving have been published in japan. tanaka and ida (2013) analyze the energy saving behavior of households in japan after the earthquake by conjoint analysis. they found that households in the kanto area tended to reduce electricity use because they experienced planned outages after the earthquake. mizobuchi and takeuchi (2013) examine which monetary factors and non-monetary factors have more effects on energy saving for households by a field experiment. they find that monetary factors have more effects on households’ energy saving. mizobuchi and takeuchi (2012) use results from a field study to suggest that both economic and psychological factors affect energy saving in households. among psychological factors, especially, social norms such as individual responsibility have great effects on energy saving. in a subsequent study, and by contrast, the same authors determined that monetary factors have a greater effect on energy saving in households compared to non-monetary factors. ito et al. (2015) examined households’ energy saving behaviors by a field experiment in keihanna smart city of kyoto prefecture. they divide their sample households into three groups: (1) economic incentive group, (2) moral suasion group and (3) control group. in the economic incentive group, the electricity rate is raised at the peak of demand. in the moral suasion group, households are only requested to save electricity use at the peak of demand. in the control group, households are not subjected to any interventions. that study revealed that households in the economic incentive group save more electricity than those in the moral suasion group. mizobuchi and takeuchi (2016) analyze repurchase and additional purchase of energy saving appliances among japanese households. households who purchase an energy saving air conditioner can save more electricity than households who do not make such a purchase. households who purchase an additional energy saving air conditioner can save more electricity, while households who repurchase an energy saving air conditioner do not benefit from such savings. these foregoing studies all concern saving electricity in japan after the earthquake. some studies use field experiments but other studies use conjoint analysis. poortinga, steg, vlek and wiersma (2003) analyzed the effects of social and psychological factors on households’ energy saving by conjoint analysis. they estimate preferences for ways of saving energy such as turning off lights in unused rooms. they find that while households exhibit preferences kinoshita: japanese households’ energy saving behaviors toward social risks by conjoint analysis international journal of energy economics and policy | vol 7 • issue 6 • 201780 for different ways of saving energy, they do not concomitantly reduce their electricity consumption. some papers focus on the effects of nudges. costa and kahn (2013) find that nudges are effective. therein, energy saving reports have effects on energy saving according to a field experiment; the ideology of individuals such as liberal or conservative also affects propensities to save energy. allcott and kessler (2015) estimate the consumer welfare implications of nudge effects via willingness to pay (wtp) and find that nudges do indeed increase consumer welfare. newell and siikamaki (2013) propose that proper information is effective for nudges. davis and metcalf (2014) suggest that good information leads to good consumer choices and contributes to energy saving. some studies focus on the effects of social norms on energy saving. allcott (2011) showed that price and non-price interventions have the same impact on households’ energy saving. each household compares with their neighborhood. on the other hand, arimura et al. (2014), focusing on the social interdependencies among individuals, find that social norms have little effect on households’ energy saving in japan. from these studies, manipulation of monetary factors appears to be the most effective way to reduce household energy use. this paper focuses on both monetary and non-monetary factors. in terms of the latter, climate change, outages, and renewable energy sources are all considered. the social costs of outages and climate change are immense. the free-rider problem is also serious in energy saving contexts. some households might not save electricity use while others do so disproportionately. grosche and vance (2009) estimate wtp for free-riding in germany. when households acquire government subsidies for energy saving interventions, free-riding is induced. free-riding is calculated by the excess of wtp over the actual cost. some studies have examined the long-term effects of energy saving by households’ by analyzing electricity consumption data. allcott and rogers (2014) compared a treatment and control group where households received a report periodically or received no such report, respectively. in addition, they compare a group where households continue to receive reports and a group where households cease to do so 2 years later in order to analyze similarities/differences between groups in the shortand long-term. they find that even where households cease to receive reports, energy saving effects continue due to the habitual effects. ayres et al. (2013) note that peer comparison with other households promotes energy saving at a lower cost. 3. conjoint analysis households’ energy saving behavior is analyzed using a stated preference method, conjoint analysis.2 we can estimate the 2 referred to louviere et al. (2000), kuriyama et al. (2005), tsuge et al. (2011), kuriyama et al. (2013) for conjoint analysis. preference of individuals for hypothetical goods or services which have several attributes using this technique. households choose an option from a set of alternatives framed in terms of hypothetical goods or services. conjoint analysis is adopted to examine households’ energy saving behavior under the hypothetical situations involving changes in monthly electricity rates, co2 emissions and the possibility of outages. in conjoint analysis, we present profiles of goods or services which have several attributes to households. a profile which has too few attributes will not allow significant heterogeneity in preferences to be expressed, while a profile which has too many attributes places a cognitive burden on respondents. in general, we adopt five or six attributes. after we decide on attributes and their levels, we construct profiles using the orthogonal planning method to militate against multicollinearity. from various cards which we get through the orthogonal planning method, selecting cards, and their combinations, we construct profiles while removing unrealistic and dominant cards. spss conjoint version 17.0 is used to implement the orthogonal planning method. the contingent valuation method (cvm) is another popular stated preference method but it is not a choice experiment. we use cvm when we evaluate users’ values of non-marketable targets such as forests and coastal areas. the following alternatives are presented to households to analyze their behavior vis-à-vis energy saving. households choose one of the alternatives under some hypothetical situations. • alternative 1: decrease by 10–20% (decrease a lot) • alternative 2: decrease by 5–10% (decrease a little) • alternative 3: unchanged • alternative 4: increase. an ordered logit model is used for estimation because these alternatives have a clear order. the following profile attributes are adopted: monthly electricity rates, emissions of global greenhouse gases such as co2, the possibility and duration of electric power outages, and the main energy sources which are used to generate electricity. 3.1. monthly electricity rates monthly electricity rates increase or decrease compared with current rates. the levels are −2000 jpy, −1500 jpy, −1000 jpy, −500 jpy, 0 jpy (unchanged), +500 jpy, +1000 jpy, +1500 jpy, +2000 jpy. electricity rate are related with energy sources. electricity generated by nuclear power might be cheaper. electricity generated by thermal power might be higher due to the volatile fuel prices and foreign exchange rates. electricity generated by renewable energy sources might be higher due to the feed-in tariff. the electricity rates are monetary factors. 3.2. co2 emissions co2 emissions will increase or decrease in 2030 compared with 1990 which is the benchmark year of the kyoto protocol. the levels are −20%, −10%, 0% (unchanged), +10% and +20%. co2 emissions are related with energy sources. nuclear power might reduce co2 emissions. coal and lng might increase emissions while renewables might reduce emissions. households who reduce their electricity use for concerns about climate change may be anchoring kinoshita: japanese households’ energy saving behaviors toward social risks by conjoint analysis international journal of energy economics and policy | vol 7 • issue 6 • 2017 81 to a social norm. co2 emissions are non-monetary factors. we note a free-rider problem. some households think that they do not need to save electricity use to reduce co2 emissions if others are doing so. 3.3. the stability of electricity supply the possibility of outages and their duration are presented to households. sometimes households should reduce electricity use to avoid sudden outages. i examine whether households save electricity use or not when they recognize the possibility of outages: 1. an outage occurs once in a year and lasts for one hour or more (60 min) 2. an outage occurs once in a year and lasts for half an hour (30 min) 3. an outage occurs once in a year and lasts for a few minutes (3 min) 4. an outage occurs once in a year and lasts for a few seconds (0.05 min) 5. no outage (electricity is always supplied constantly). stability of supply or lack there of, is related with energy sources. in the case of nuclear power, an outage could be caused due to accidents at nuclear power plants. if nuclear power is not used, a planned outage might be experienced at the peak of demand in summer and winter to avoid one or more unplanned outages. if renewable energy sources are used, electricity supply might be unstable due to weather conditions such as short daylight hours or insufficient wind. households who save electricity use because they are concerned about outages may be adhering to a social norm. if households save electricity use by the notice of outages, it might be effective for local governments or electric power companies to announce the possibility of outages or instability of electric power to households as a nudge. outage is one of the non-monetary factors. 3.4. energy sources an energy supply source set consisting of nuclear power, coal, natural gas (lng), solar, and wind power are supposed. households use one of these energy sources. each energy source is represented by a dummy variable. coal is the base category. energy sources are non-monetary factors. each energy source has some risks. the possible risks associated with each energy source are presented to households. households recognize these risks when they choose energy sources. households who prefer renewable energy sources might save their electricity use because they recognize that their electricity supply is unstable due to weather conditions. the possible risks with each energy source are as follows. 1. nuclear power: accidents in nuclear power plants 2. coal: climate change because of co2 emissions 3. lng: volatile and rising electricity rates 4. renewable energy: the possibility of outages and instability of electricity supply due to weather conditions. the levels of each variable are summarized in table 1. an example profile is shown in table 2. households choose one of the alternatives about energy saving under the conditions of the profiles. they answer with respect to ten choice questions. each question has various levels of attributes. to use various profile configurations, households were divided into two groups and each group was asked to answer with respect to ten profiles. data were collected online via a web-based questionnaire utilizing the services of the rakuten research company. the total sample size is 800 households: n = 400 in kanto3 and n = 400 kansai4. data were collected in october 16, 2015. 4. questionnaire results in this section, i illustrate the results of the questionnaire. table 3 provides attributes of the sample households. 5. econometric analysis an ordered logit model is used because alternatives about energy saving have a clear order5. the regression model is * i i iy x= β + ε∑ (1) * iy is the potential utility level of a household based on a random utility model, ε is the error term and β denotes parameters. the mechanisms as to how household choices dictate values of the dependent variable can be summarized as follows: yi =1 if c−1<yi*≤c0 =2 if c0<yi*≤c1 =3 if c1<yi*≤c2 =4 if c2<yi*≤c3 (2) 3 kanto area is the east part of japan around tokyo. saitama, chiba, tokyo and kanagawa prefectures are included. 4 kansai area is the west part of japan around osaka. shiga, kyoto, osaka, nara, hyogo and wakayama prefectures are included. 5 greene and hensher (2010) are referred for details concerning ordered logit models. table 1: variables and levels variable level monthly electricity price (jpy) −2000, −1500, −1000, −500, 0 (unchanged), +500, +1000, +1500, +2000 co2 emissions −20%, −10%, 0% (unchanged), +10%, and+20% outage (minutes) 60, 30, 3, 0.05, 0 energy source nuclear, coal, lng, solar, and wind power table 2: example profile attribute level monthly electricity price (jpy) −2000 jpy co2 emissions −20% outage (minutes) no outage energy source nuclear power kinoshita: japanese households’ energy saving behaviors toward social risks by conjoint analysis international journal of energy economics and policy | vol 7 • issue 6 • 201782 c is a threshold value. if the utility level of a household exists between c1 and c2, the household chooses alternative 3. if the utility level of a household exceeds c2, the household chooses alternative 4. in this ordered logit context, we estimate the threshold values c as well as parameters β. we formulate the probability to choose each alternative and estimate β and c by the maximum likelihood ion method to maximize the log likelihood function. 6. estimation results in this section, the estimation results from the ordered logit model are explained. table 4 shows the number of choices for each alternative. more than half of households tend to reduce electricity use. the majority of the remainder do not change their energy use behaviors with very few opting to increase their usage. table 5 presents descriptive statistics of alternatives’ attributes. table 6 illustrates the estimation results. the coefficient of the monthly electricity rates is negative and significant at the 1% level. if the electricity rates increase, households reduce their electricity use. the coefficient of co2 emissions is negative but insignificant. co2 emissions do not have any discernable effect on energy saving. the coefficient of outage is negative and significant at the 1% level. households reduce electricity use if they recognize the possibility of outages and its duration is long. nuclear power is not significant. when households use electricity generated by nuclear power, they do not tend to reduce their electricity use. on the other hand, the coefficient of renewable energy resources (solar and wind) power is positive and significant at the 1% level. households use more electricity when it is generated by renewable sources. from the results, we support the electricity rate system which raises electricity prices during peak times in order to reduce electricity use. if households are aware of the possibility of outages, they will reduce electricity use. it might be advisable for local governments or electric power companies to announce the possibility of outages or instability of electric power to households as a nudge. next, households’ attributes are included as independent variables; the results from this estimation are presented in table 7. family income and educational background are insignificant and thus do not effect energy saving. on the other hand, the coefficient of the number of family members, detached house and condominium dummy variables6 are negative and significant at the 1% level. households who have many family members, live in a detached house and live in a condominium tend to reduce their electricity use. kanto dummy variable is insignificant: there is no difference between households in kanto and kansai vis-à-vis saving electricity. more than four years have passed since the earthquake at the time of this research. although households in kanto experienced planned outages after the earthquake while kansai did not, the difference disappears over time. table 8 shows estimation results, including households’ consciousness, as independent variables. the variables of energy saving consciousness, support for renewable energy resources and consciousness for co2 reduction are included as independent variables. many households choose the same alternative of “decrease electricity use” under all conditions. the variable scale 6 company housing and dormitory housing is the base category. table 4: number and ratio of choices across alternatives alternative number ratio 1 1922 0.240 2 3180 0.398 3 2682 0.335 4 216 0.027 total 8000 1 table 3: households’ attributes attributes n=800 (%) occupation company worker 416 (52) public worker 42 (5.3) student 1 (0.1) unemployed (including housewives and retirees) 193 (24.1) self-employed 65 (8.1) others 83 (10.4) household income (thousand jpy) < 2,000 169 (21.1) 2,000–3,990 152 (19) 4,000–5,990 187 (23.4) 6,000–7,990 127 (15.9) 8,000–9,990 90 (11.3) > 10,000 75 (9.4) educational background junior high school, high school 193 (24.1) technical school, junior college 170 (21.3) university, graduate school 437 (54.6) family composition single 147 (18.4) two 205 (25.6) three 197 (24.6) four 179 (22.4) fve 58 (7.3) six or more 14 (1.8) dwelling type detached house (including two households’ house) 410 (51.3) collective housing (condominium, apartment, housing complex etc.) 372 (46.5) company housing, dormitory housing etc. 18 (2.3) sex male 523(65.4) female 277 (34.6) age (years) 20–29 38 (4.8) 30–39 150 (18.8) 40–49 240(30.0) 50–59 240 (30.0) 60 and above 132 (16.5) mean 48.01 minimum 21 maximum 69 kinoshita: japanese households’ energy saving behaviors toward social risks by conjoint analysis international journal of energy economics and policy | vol 7 • issue 6 • 2017 83 of consciousness to save electricity use is “very conscious: 1,” “a little conscious: 2,” “unchanged: 3” and “not conscious: 4.” the variable of support for renewable energy sources is a dummy variable. if a household chooses renewable energy sources such as solar, wind, geothermal heat, biomass, tidal, and wave power in the first or second priority, i assign 1, else 0. the variable scale of consciousness of co2 reduction is “reduce more: 1,” “reduce a little: 2,” “no need to reduce: 3” and “increase: 4.” the coefficients of consciousness to save electricity and consciousness for co2 are positive and significant at the 1% level. naturally, households who have high consciousness to reduce electricity indeed do so under any conditions regarding the possibility of outages and energy sources. and households who have high consciousness for co2 reduce electricity. however, the coefficient of support for renewable energy sources is negative and insignificant; thus households who support renewable energy sources do not appear to be motivated to reduce their electricity use. 7. conclusions and policy implications i analyze the conditions under which households reduce, or do not reduce, their electricity use by conjoint analysis. it is necessary to reduce residential electricity consumption. future electric power shortages are possible and plausible unless nuclear power plants resume operations and renewable energy sources prevail. moreover, to reduce co2 emissions and thus mitigate climate change, residential energy demand reduction is important in the long run. we find that households save electricity use when monthly electricity rates and the possibility of outages increase. households are thus responding to a monetary stimulus in the case of the former and a non-monetary stimulus in the case of the latter, which can be conceived from a social norm perspective. however, co2 emissions and renewable energy sources are not the conditions to induce households to reduce their electricity consumption. from the results, we support the electricity rate system which raises prices at peak times to reduce demand accordingly. if households are aware of the possibility of outages, they will reduce their electricity consumption. thus it might be effective for local governments or electric power companies to announce the possibility of outages or instability of supply to households as a nudge. since the 2011 earthquake there has been a shift in knowledge about and preferences for different energy sources among japanese people. some people are against nuclear power and for renewable energy resources. the relationship between preferences for renewable energy resources and energy saving behavior is an interesting topic. generally, electricity supplied from renewable energy resources is unstable because of its dependence upon the requisite weather conditions. long-term energy saving is important table 5: descriptive statistics alternative electricity rate co2 outage nuclear coal lng solar wind 1 average 531.217 0.546 15.186 0.174 0.212 0.268 0.207 0.138 standard deviation 1458.631 14.909 21.753 0.379 0.409 0.443 0.405 0.345 2 average 428.774 0.316 13.611 0.174 0.221 0.259 0.205 0.141 standard deviation 1395.248 14.576 21.165 0.379 0.415 0.438 0.404 0.348 3 average 61.708 −1.930 14.116 0.255 0.172 0.231 0.177 0.166 standard deviation 1396.903 14.256 22.284 0.436 0.377 0.421 0.382 0.372 4 average 231.481 −4.074 17.274 0.130 0.130 0.185 0.352 0.204 sandard deviation 1436.931 13.349 23.853 0.337 0.337 0.389 0.479 0.404 table 6: estimation results variable coefficient standard error z-value p-value electricity rate −0.000197 0.000017 −11.33 0 co2 −0.003646 0.003198 −1.14 0.25 outage −0.002903 0.001079 −2.69 0.01 nuclear 0.105617 0.111215 0.95 0.34 lng 0.117357 0.062346 1.88 0.06 solar 0.246804 0.10591 2.33 0.02 wind 0.442355 0.109648 4.03 0 cut1 −1.115342 0.066002 cut2 0.636091 0.065097 cut3 3.688323 0.092296 log likelihood−9285.7997 pseudo r2 0.0107 table 7: estimation results (including households’ attributes) variable coefficient standard error z-value p-value electricity rate −0.000197 0.000017 −11.33 0 co2 −0.003625 0.0032 −1.13 0.26 outage −0.002882 0.00108 −2.67 0.01 nuclear 0.107942 0.111253 0.97 0.33 lng 0.117277 0.062378 1.88 0.06 solar 0.246738 0.105965 2.33 0.02 wind 0.443412 0.109717 4.04 0 income 0.00037 0.014185 0.03 0.98 education −0.039796 0.026232 −1.52 0.13 family members −0.034945 0.018054 −1.94 0.05 detached house −0.485616 0.1384 −3.51 0 condominium −0.319477 0.137544 −2.32 0.02 kanto 0.037566 0.041916 0.9 0.37 cut1 −1.686646 0.170928 cut2 0.071095 0.169804 cut3 3.129201 0.181399 log likelihood−9267.5176 pseudo r2 0.0126 kinoshita: japanese households’ energy saving behaviors toward social risks by conjoint analysis international journal of energy economics and policy | vol 7 • issue 6 • 201784 to avoid climate change and to prepare energy shortages. in this paper, households respond to temporal outages caused by the tightness of electricity demand. however, they do not respond to co2 emissions. the system should be considered to promote long-term energy saving for households. 8. acknowledgments this study was aided by research funding from ryukoku university, japan. this paper was presented in the academic meeting of the japanese economic association in september 2016 and the 15th international conference of the japan economic policy association in october 2015. all errors are mine. i thank for discussants of academic meeting: prof. kenichi mizobuchi and prof. satoru hashimoto. references allcott, h. (2011), social norms and energy conservation. journal of public economics, 95, 1082-1095. allcott, h., kessler, jb. (2015), the welfare effects of nudges: a case study of energy use social comparisons, nber working paper series no. 21671. national bureau of economic research. p1-74. allcott, h., rogers, t. (2014), the short-run and long-run effects of behavioral interventions: experimental evidence from energy conservation. american economic review, 104(10), 3003-3037. arimura, t.h., katayama, h., sakudo m. (2014), do social norms matter to energy saving behavior? endogenous social and correlated effects, tcer working paper series, e-76, tokyo center for economic research. the agency for natural resources and energy in the ministry of economy, trade and industry. (2014), white paper about energy in fiscal year 2013. available from: http://www.enecho.meti.go.jp/ about/faq/001 ayres, i., raseman, s., alice, s. (2013), evidence from two large field experiments that peer comparison feedback can reduce residential energy usage. journal of law economics and organization, 29, 992-1022. costa, d.l., mattew, e.k. (2013), energy conservation “nudges” and environmentalist ideology: evidence from a randomized residential electricity field experiment. journal of the european economic association, 11, 680-702. davis l.w., metcalf, g.e. (2014), does better information lead to better choices? evidence from energy-efficiency labels, nber working paper series 20720, national bureau of economic research. p1-51. greene, w.h., hensher, d.a. (2010), modeling ordered choices. cambridge: cambridge university. grosche, p., vance, c. (2009), willingness to pay for energy conservation and free-ridership on subsidization: evidence from germany. the energy journal, 30(2), 135-153. ito, k., ida, t., tanaka, m. (2015), the persistence of moral suasion and economic incentives: field experimental evidence from energy demand, nber working paper series no. 20910. p1-44. kuriyama, k., shoji, y., edited (2005), economic evaluation of environment and tourism. tokyo: keisou-shobou. kuriyama, k., tsuge, t., shoji, y. (2012), introduction of economic evaluation of environment for beginners. tokyo: keisou shobou. louviere, j.j., hensher, d.a., swait, j.d. (2000), stated choice methods analysis and application. cambridge: cambridge university press. mizobuchi, k., takeuchi, k. (2012), the influences of economic and psychological factors on energy-saving behavior: a field experiment in matsuyama, discussion paper, no. 1206. japan: faculty of economics, kobe university. p1-39. mizobuchi, k., takeuchi, k. (2013), the influences of financial and nonfinancial factors on energy-saving behaviour: a field experiment in japan. energy economics, 63, 775-787. newell, r.g., siikamaki, j.v. (2013), nudging energy efficiency behavior: the role of information labels, nber working paper series 19224, national bureau of economic research. p1-41. poortinga, w., linda, s., charles, v., gerwin, w. (2003), household preferences for energy-saving measures: a conjoint analysis. journal of economic psychology, 24, 49-64. the agency for natural resources and energy in the ministry of economy, trade and industry. (2014), white paper about energy in fiscal year 2013. tanaka, m., ida, t. (2013), voluntary electricity conservation of households after the great east japan earthquake: a stated preference analysis. energy economics, 39, 296-304. tsuge, t., kuriyama, k., mitani, y. (2011), new technique of environmental evaluation. japanese: keisou shobou. table 8: estimation results (including consciousness variables) variable coefficient standard error z-value p-value electricity rate –0.00021 0.0000182 –11.56 0 co2 –0.00448 0.0033441 –1.34 0.18 outage –0.003259 0.0011321 –2.88 0 nuclear 0.1015609 0.1160521 0.88 0.38 lng 0.1221245 0.0653314 1.87 0.06 solar 0.263804 0.1108557 2.38 0.02 wind 0.4559248 0.1145589 3.98 0 consciousness for saving 0.476094 0.029571 16.1 0 support renewable energy –0.035601 0.0461481 –0.77 0.44 consciousness for co2 0.5556902 0.0329335 16.87 0 cut1 0.6237048 0.1028449 cut2 2.549215 0.1070492 cut3 5.732475 0.1331753 log likelihood –8294.5046 pseudo r2 0.0513 . international journal of energy economics and policy | vol 8 • issue 5 • 2018294 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(5), 294-299. estimating the impact of the financial development on energy consumption: a co-integration analysis yasemin dumrul* erciyes university, develi hüseyin şahin vocational school, kayseri, turkey. *email: ydumrul@erciyes.edu.tr abstract this paper investigated the impact of financial development on energy consumption in turkey. for this purpose, the annual data from 1961 to 2015 is examined using with johansen cointegration test and fully modified ordinary least square (fmols) and dynamic ordinary least square (dols) test. test results indicate the existence of long run relationship between financial development, economic growth and energy consumption in turkey. in addition the fmols and dols test results show that financial development and economic growth have a positive effect on energy consumption in turkey. for this reason, policy makers should also take into account the impact of financial development on energy consumption while setting energy policies and setting targets. keywords: financial development, energy consumption, economic growth, co-integration, turkey jel classifications: c32, q43 1. introduction since energy is one of the main economic growth sources of the country’s economy, it is important for various reasons to reveal the determinants of energy consumption. energy is used in the production of almost all goods and services in the economy, many developing economies are growing rapidly and as the economic growth increases, the energy demands of the countries are also increasing (sadorsky, 2010. p. 2528). at the same time, the lack of balance between energy supply and demand due to excessive increases in energy consumption has adversely affected economic growth (furuoka, 2015. p. 430). it is also important in terms of how to manage greenhouse gas emissions caused by energy consumption in the future and in terms of energy policies to be implemented (sadorsky, 2010. p. 2528). the financial system is a sector that uses productive resources to facilitate the formation of capital through the provision of a wide variety of financial instruments to meet the different requirements of lenders and borrowers. therefore, the financial system plays an important role in the mobilization of savings and intermediation, and it ensures that these resources are efficiently allocated to productive sectors (ang, 2008. p. 536). the development of the financial sector is expressed as developments in financial activities such as increases in banking sector activities, stock market activities and/or bond market activities (pradhan et al., 2018. p. 6). financial development contributes to the growth of economies by attracting foreign direct investment (fdi) to the country, and/or encouraging stock exchanges, banking activities and other financial intermediaries.(mahalik et al., 2017. p. 10221024; shahbaz et al., 2013. p. 10). financial development also increases the availability of investment resources that lead to the growth of the industry and the expansion of the production base (farhani and solarin, 2017. p. 1030). even in countries with limited financial resources, effective management of the financial system leads to more efficient use of financial resources. it also contributes to innovations that promote economic development and to creating a favorable socio-economic environment for technological progress (furuoka, 2015. p. 430). for the energy sector, too, financial development can provide the liquidity needed to stimulate energy projects. financial development encourages industrial growth and helps create new infrastructure facilities; and for this reason it can affect energy consumption positively. in addition, a well-managed and developed financial sector helps to allocate sufficient financial resources to the energy sector and to provide a balance between energy supply and demand dumrul: estimating the impact of the financial development on energy consumption: a co-integration analysis international journal of energy economics and policy | vol 8 • issue 5 • 2018 295 (farhani and solarin, 2017. p. 1030). financial development can have an impact on energy saving and carbon emission policies as it can affect energy demand as well as economic activities (mahalik et al., 2017. p. 1022-1024; sadorsky, 2010. p. 2528-2529). therefore, there is a dynamic relationship between energy demand, financial development and economic growth. the aim of this study was to determine the effect of financial development on energy consumption in turkey. the remainder of the paper is organized as follows: section 2 explains the theoretical literature between financial development and energy consumption section 3 briefly reviews relevant literature on the relationship between financial development and energy consumption. section 4 informs data set and methodology. section 5 reports the findings. section 6 concludes the study. 2. literature review financial development can impact energy consumption in the economy by reducing financial risk and credit costs, promoting transparency between borrowers and creditors, providing access to more financial capital, investment flows and advanced technologies (sadorsky, 2011. p. 1000; komal and abbas, 2015. p. 216; ouyang and li, 2018. p. 239). financial development can affect energy consumption positively or negatively (ali et al., 2015; rafindadi and ozturk, 2016; shahbaz et al., 2017; rafindadi and ozturk, 2017; nasreen et al., 2017; gungor and simon, 2017). the development of the financial sector may have a positive effect on energy consumption through various channels. accordingly, financial development leads to economic growth by increasing investments through level and efficient effects. the level effect is expressed as facilitating the transfer of idle resources from non-profitable investments to profitable investments because the financial sector attracts both domestic and foreign investments. the efficient effect is related to the financial sector’s facilitating the provision of more financial resources for highly productive investment. thus, energy demand increases (odusanya et al., 2016. p. 156). on the other hand, sadorsky (2011) stated that financial development has an influence on energy consumption through direct, business and wealth effect channels (sadorsky, 2011. p. 1000; mahalik et al., 2017. p. 1025). 2.1. direct effect an effective financial system allows consumers to buy more goods, supporting more lending to households and firms, leading to higher energy consumption (furuoka, 2015. p. 430). thanks to an advanced financial system, consumers spend their accumulated money in the banks or received loan buy expensive products that consume more energy, such as cars, homes, refrigerators, air conditioners and washing machines. therefore, an effective financial system allows consumers to buy more goods, which leads to higher energy consumption (sadorsky, 2011. p. 1000; mahalik et al., 2017. p. 1025). 2.2. business effect the business world also benefits from financial development. a well-managed financial system can provide adequate support for producers’ efforts to expand their business activities (furuoka, 2015. p. 430). energy demands of business firms increase with the financial development of an economy. an advanced financial system provides appropriate interest rates to enhance firm investments and innovation activities. financial development helps companies expand their existing businesses (such as establishment, worker recruitment and purchase of machinery equipment), but in business activities leads to more energy consumption by more use of establishment, machinery and workers, thus affecting the energy demand of the whole country (sadorsky, 2011. p. 1000; mahalik et al., 2017. p. 1025; kahouli, 2017. p. 19-20). 2.3. wealth effect increased stock market activity is seen as a leading indicator of economic growth and prosperity, but it has a wealth effect in terms of affecting trust between consumers and businesses firms. in other words, increasing stock market activities have a positive effect on the trust of consumers and businesses, and thus create the wealth effect (odusanya et al., 2016. p. 157). both consumers and business firms benefit from debt financing as well as from equity financing, depending on the development of an economy’s stock market. because companies provide additional funding by issuing shares. as a result, equity financing increases economic activity and leads to an increase in the energy demand of the country (sadorsky, 2011; 1000; mahalik et al., 2017. p. 1025). the development of the financial sector may have a negative effect on energy consumption due to technological effect (shahbaz et al., 2017. p. 201). enhanced financial institutions and capital markets can offer capital financing for renewable energy sector as well as providing and lending to the green renewable energy projects. financial development makes it possible to offer loans for environmentally friendly projects with low financing costs. in addition, fdi could provide for the reduction of energy consumption by causing increases in investments made by new technologies by local firms (chang, 2015. p. 28-29; shahbaz et al., 2017. p. 199). in other words, financial development contributes to the reduction of energy consumption by leading to more modern and less energy consuming technologies (shahbaz et al., 2017. p. 201). hence, mielnik (2002) concluded that there is an inverse relationship between fdi and energy intensity. this is explained by financial development helping the efficient use of energy (islam et al., 2013. p. 437). thus, while financial development gives lenders capital to the energy sector (which also increases energy consumption), it can also serve as an incentive for increased energy substitution (reducing energy consumption). from these two different perspectives, it can be said that the effect of financial development on energy consumption is uncertain (chang, 2015. p. 28-29). in this context, it is important to examine how financial development will affect energy consumption. 3. applied literature in the applied literature, the relationship between financial development and energy consumption has been analyzed by both time series and panel data methods. however, different results have dumrul: estimating the impact of the financial development on energy consumption: a co-integration analysis international journal of energy economics and policy | vol 8 • issue 5 • 2018296 been obtained in studies. this may be due to the different econometric methods, variables and established models, as well as differences in the country’s financial development status (their financial structure, degree of concentration of financial institutions, size of financial institutions and instruments, efficiency of financial intermediaries, volume of financial transactions and effectiveness of the financial regulatory framework) and energy consumption requirements (ouyang and li, 2018. p. 238; keskingöz and i̇nançlı, 2016. p. 105). some of the results obtained in this field study are related to the fact that financial development will increase energy consumption. mahalik et al. (2017) revealed the relationship between financial development and energy consumption in saudi arabia for the period 1971–2011 using time series methodology (ardl approach). their results show that unidirectional causality running from financial development to energy demand is found. odusanya et al. (2016) examined the link between financial development and energy consumption in nigeria both in the long run and the short run over the 1971-2014 using ardl approach. their results indicated that the development of the financial sector exerted positively and significantly on energy demand in the nigerian economy. komal and abbas (2015) demonstrated the finance-growth-energy nexus for pakistan over the 1972-2012 period using generalized method of moments (gmm). their result indicate that financial development positively and significantly affects energy consumption through the economic growth channel. al-mulali and lee (2013) examined the impact of the financial development on energy use in the gulf cooperation countries for the period 1980-2009 using panel data methodology. they found that financial development increases energy use in the short and lon-run. ozturk and acaravci (2013) examined the causal relationship between financial development, trade, economic growth, energy consumption and carbon emissions in turkey for the period 1960-2007 using ardl approach. their result show that there is a unidirectional causality from financial development to energy consumption in the short-run but there is no relationship between the variables in the long run. sadorsky (2011) explored the relationship between financial development and energy consumption in central and eastern european frontier economies for the period 1996-2006 using panel gmm analysis. this study indicate that financial development has a positive effect on energy consumption. sadorsky (2010) investigated the impact of financial development on energy consumption in emerging economies for the period 1990-2016 using panel gmm. this study show that financial development has a positive effect on energy consumption. zhang (2011) demonstrated the impact of financial development on carbon emissions in china for the periodusing time series analysis (johansen cointegration and granger causality). this study reported that china’s financial development acts as an important driver for carbon emissions increase. on the other hand, in applied literature, financial development will reduce energy consumption, so there are also studies suggesting that the technology impact is valid. ouyang and li (2018) explored relationships among financial development, energy consumption, and economic growth in china from 30 chinese provinces for the period 1996q1-2015q4 using a gmm panel var approach. the study result show that financial development plays a negative role in both economic growth and energy consumption. farhani and solarin (2017) examined the relationship among financial development and energy demand in the united states for the period 1973q1-2014q4 using time series analysis (bayer-hanckand ardl cointegrationtest, granger and asymmetric causality test). their results indicate that financial development decreases energy demand in the u.s. jalil and feridun (2011) explored the relationship between financial development and co2 emissions in china for the period 19532006 using time series methodology (ardl analysis). their findings indicate that financial development lowers environmental pollution. tamazian et al. (2009) examined the relationship between financial development, economic growth and co2 emissions in bric countries for the period 1992-2004 using panel data analysis. this study found that higher degree of economic and financial development decreases the environmental degradation. some of the studies that deal with financial development and energy consumption in the literature show that there is a bidirectional relationship (feedback effect) between the relevant variables, i.e., both variables affect each other. shahbaz and lean (2012) investigated the relationship among financial development and energy consumption in tunisia for the period 1971-2008 using time series methodology (ardl, johansen cointegration test and granger causality test). they show that bidirectional causality between financial development and energy consumption. shahbaz (2015) explored relationship among electricity consumption and economic growth in pakistan by incorporating financial development within the neoclassical production function for the period 1972-2012 using ardl approach this study found find that feedback effect between electricity consumption and economic growth, and financial development and electricity consumption. 4. data and methodology the dataset in this study consists of three variables, that is, energy use (kg of oil equivalent per capita) which is used as a proxy for energy consumption, domestic credit to private sector as a percentage of gross domestic product (gdp) which is used as a proxy for financial development and per capita real gdp in constant 2010 us $ which is used as a proxy for economic growth. for the empirical analysis annual time series data are used for the turkey over the period from 1961 to 2015. annual data are collected from the world bank’s world development indicators database. for the purpose of examining the impact of financial development and economic growth on the energy consumption, the long-run equation of general empirical framework is given as follows: ec = f(fd, gdp) (1) this paper utilizes data logarithmic processing, such that the time series can be reasonably analyzed and equation can be described as follows: ln ect = β0+β1lnfdt+β2lngdpt+εt (2) where ec is energy consumption, fd is financial development and gdp is economic growth. β0, ε and β1 and β2 stand for the dumrul: estimating the impact of the financial development on energy consumption: a co-integration analysis international journal of energy economics and policy | vol 8 • issue 5 • 2018 297 constant term, the error term and the elasticities’ impact of other variables on energy consumption, respectively. t is the time period. some of the procedures in time series econometrics are based on the assumption that they are treated with stationary series. however, this assumption can not always be fulfilled. for this reason, the application of some non-stationary series of econometric methods may lead to misinterpretation of the results. in the literature, the stationary of variables is tested by unit root tests. in this study, augmented dickey fuller (adf) (1981) and phillips and perron (pp) (1988) unit root tests will be applied as unit root test. the basis of unit root tests is the dickey fuller (df) (1979) test. however, the df test is insufficient if the error terms are autocorreated. this situation is overcome by the augmented dickey fuller (adf) test. with the adf test, the delayed values of the dependent variable are included as a independent variable. for reliability of the adf test results, the series were also tested with the pp unit root test using a non-parametric approach (aytaç, 2016. p. 49). the pp unit root test has been developed with the thought that autocorrelation may occur between error terms. in both stationarity tests, the hypothesis that the null hypothesis contains a unit root and the alternative hypothesis suggests that the series is stationary. this study aims to examine cointegration relationship between energy consumption, financial development and economic growth. for this purpose, the three variables are tested by the cointegration methods of johansen (1988) and johansen ve juselius (1990). in the johansen cointegration test, all variables are acted on by the var model, which is internally accepted. with this method, the maximum likelihood method is used for estimating the vectors and the rank of the coefficient matrix is tried to be determined (saatçi and dumrul, 2013. p. 16). also in this study fully modified least square (fmols) by proposed phillips and hansen (1990) and dynamic ordinary least square (dols) cointegration methods by proposed stock and watson (1993) will be used to check the consistency and validity of the long-run dynamics. the fmols estimator uses a semi-parametric correction method to avoid estimation problems, which are caused by long-term correlation between co-integration equation and stochastic shocks. consequently, the estimator is fully active and asymptotically unbiased, allowing standard wald tests using the asymptotic χ2 distribution. the dols estimation procedure is based on the independent variables lags and leads to the equation of cointegration (berke, 2012. p. 251). both the fmols and dols methods take account of the problem of autocorrelation between error terms as well as the relation endogeinity problem between independent variables and error terms. 5. findings and discussions before modeling, the adf and pp tests are applied to judge whether the three variables inec, lnfd and lngdp have the unit root or not. the results obtained regarding adf and pp tests can be seen in table 1. as can be seen from table 1, according to adf and pp test results energy consumption, financial development and economic growth variables are not stationary at the level. the series become stationary when the first difference is received. in other words, the results show that all the variables are i(1). after determining that the variables are integrated at the order (1), the next step is to calculate the long-run relationship between the variables. the optimal lag length should first be determined when the cointegration relationship is tested. unrestricted var was used in this study and selected optimal lag length by choosing aic criterion. results for most of the criterion proposed optimal lag length 1. (var (p = 1).the results of johansen cointegration has produced two statistics, trace and maximum eigenvalue statistics. the significance of trace statistic and eigenvalues statistic exhibits cointegration relation among variables of this study. results of johansen cointegration are presented in table 2. table 1: unit root test results variables augmented dickey fuller (adf) test phillips-perron (p-p) test level first diff. level first diff. t-stat. p-val t-stat. p-val t-stat. p-val t-stat. p-val lec −1.35 0.59 −7.032 0.00 −1.43 0.56 −7.04 0.00 lfd −0.55 0.98 −5.607 0.00 −0.32 0.97 −5.55 0.00 lgdp −1.6 0.44 −7.771 0.00 −1.62 0.46 −7.77 0.00 significant at 5% table 2: results of johansen test for cointegration unrestricted cointegration rank test (trace) cointegration vector number hypothesis (h0) alternative hypothesis (h1) eigenvalue trace statistic 0.05 critical value p (r=0)* (r=1) 0.341503 33.43418 29.79707 0.0182 (r≤0) (r=2) 0.175907 12.12664 15.49471 0.1510 unrestricted cointegration rank test (maximum eigenvalue) cointegration vector number hypothesis (h0) alternative hypothesis (h1) eigenvalue max-eigen statistic 0.05 critical value p (r=0)* (r≥0) 0.341503 21.30754 21.13162 0.0472 (r≤0) (r≥2) 0.175907 9.867075 14.26460 0.2208 dumrul: estimating the impact of the financial development on energy consumption: a co-integration analysis international journal of energy economics and policy | vol 8 • issue 5 • 2018298 johansen test statistics results (trace and maximum eigenvalue) reject the null hypothesis; that is, there is no cointegration relationship. results in table 2 reveal that there exist at least one cointegration relationships. therefore, long-term cointegration relationships exist between lnec, lnfd and lngdp. fmols and dols methods were used in order to determine and interpret the long-run coefficients after determining the cointegration relation between the variables studied in the study. the results of the analysis are shown in table 3. as can be seen from table 3, according to the fmols results, 1% increase in financial growth increases energy consumption by 0.88% and 1% increase in economic growth increases energy consumption by 0.22%. according to the dols results, a 1% increase in the financial developments in turkey’s energy consumption by 0.90%, while 1% increase in economic growth increases by 0.21%. in summary, both fmols and dols test results show that financial development and economic growth have an impact on energy consumption in turkey. accordingly, financial development and economic growth increase energy consumption in turkey. however, the coefficients for all variables are statistically significant. the close results of the two cointegration methods that give long-run coefficients increase confidence in the estimates of these tests. 6. conclusion in this study, the effect of financial development on energy consumption is examined both theoretically and practically. in the theoretical literature, there is the opinion that the financial development will influence energy consumption positively through different channels (such as direct, business and wealth), as well as the suggestion that it will affect the negative due to technology influence. there are also studies suggesting that there is a bi-directional relationship in the applied literature. therefore, there is no consensus on the relationship in the literature. this study focuses on the effect of financial development on energy consumption in turkey. as a result of co-integration, fmols and dols tests using 1961-2015 period data, it is concluded that there is a long relationship between financial development and energy consumption and that financial development has a positive effect on energy consumption. it said that the policies aimed at improving the financial sector have a direct impact on turkey’s energy consumption. the results are consistent with the findings of mahalik et al. (2017) for saudi arabia; odusanya et al. (2016), komal and abbas (2015) for pakistan; al-mulali and lee (2013) for gulf cooperation countries; sadorsky (2011) for central and eastern european frontier economies sadorsky (2010) for emerging economies and zhang (2011) for china. at the same time, the study found that economic growth also increased energy consumption. turkey is a country dependent on foreign energy, diversification of energy supply to meet the energy consumption, which will increase with the growth is important. therefore, the increase in energy consumption due to the increase in financial development and economic growth should be considered in energy consumption planning for turkey’s economy. references ali, h.s., yusop, z.b., hook, l.s. (2015), financial development and energy consumption nexus in nigeria: an application of autoregressive distributed lag bound testing approach. international journal of energy economics and policy, 5(3), 816-821. al-mulali, u., lee, j.y.m. (2013), estimating the ımpact of the financial development on energy consumption: evidence from the gcc (gulf cooperation council) countries. energy, 60(1), 215-221. ang, j.b. (2008), a survey of recent development in the literature of finance and growth. journal of economic surveys, 22(3), 536-576. aytaç, d. (2016), emission taxes, energy prices and technological. journal of international economic research, 2(4), 43-55. berke, b. (2012), exchange rate and imkb100 ındex relationship: a new test. the jounal of finance, 163, 243-257. chang, s.c. (2015), effects of financial developments and ıncome on energy consumption. international review of economics and finance, 35, 28-44. dickey, d.a., fuller, w.a. (1979), distribution of the estimators for autoregressive time series with a unit root. journal of the american statistical association, 74(366), 427-431. dickey, d.a., fuller, w.a. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica, 49, 1057-72. farhani, s., solarin, s.a. (2017), financial development and energy demand in the united states: new evidence from combined cointegration and asymetric causality tests. energy, 134, 1029-1037. furuoka, f. (2015), financial development and energy consumption: evidence from a heterogeneous panel of asian countries. renewable and sustainable energy reviews, 52, 430-444. gungor, h.,simon, a.u. (2017), energy consumption, finance and growth: the role of urbanization and industrialization in south africa. international journal of energy economics and policy, 7(3), 268-276. islam, f., shahbaz, m., ahmed, a.u., alam, m.m. (2013), financial development and energy consumption nexus in malaysia: a multivariate time series analysis. economic modelling, 30, 435-441. jalil, a., feridun, m. (2011), the ımpact of growth, energy and financial development on the environment in china: a cointegration analysis. energy economics, 33, 284-291. johansen, s. (1988), statistical analysis of cointegration vectors. journal of economic dynamic and control, 12, 231-254. table 3: fmols and dols analysis variables dependent variable: lnec fully modified least square (fmols) dynamic least square (dols) coefficient t-stat. p-value coefficient t-stat. p-value lfd 0.883321 7.668444 0.0000 0.900457 5.834760 0.0000 lgdp 0.220343 5.053638 0.0000 0.216436 3.946943 0.0003 c 3.424627 8.112610 0.0000 3.391970 6.604859 0.0000 dumrul: estimating the impact of the financial development on energy consumption: a co-integration analysis international journal of energy economics and policy | vol 8 • issue 5 • 2018 299 johansen, s., juselıus, k. (1990), maximum likelihood estimation and ınference on cointegration with application to the demand for money. oxford bulletin of economic and statistics, 52, 169-210. kahouli, b. (2017), the short and long run causality relationship among economic growth, energy consumption and financial development: evidence from south mediterranean countries (smcs). energy economics, 68, 19-30. keskingöz, h., i̇nançlı, s. (2016), the causality between financial development and energy consumption in turkey: the period of 1960-2011. eskisehir osmangazi üniversity journal of economics and administrativesciences, 11(3), 101-114. komal, r., abbas, f. (2015), linking financial development, economic growth and energy consumption in pakistan. renewable and sustainable energy reviews, 44, 211-220. mahalik, m.k, babu, m.s., loganathan, n., shahbaz, m. (2017), does financial development ıntensify energy consumption in saudi arabia? renewable and sustainable energy reviews, 75, 1022-1034. mielnik, j.g. (2002), foreign direct investment and decoupling between energy and gross domestic product in developing countries. energy policy, 30, 87-89. nasreen, s., anwar, s., ozturk, i. (2017), financial stability, energy consumption and environmental quality: evidence from south asian economies. renewable and sustainable energy reviews, 67, 1105-1122. odusanya, i.a., osisanwo b.g., tijani, j.o. (2016), financial development and energy consumption nexus in nigeria. audœ, 12(5), 155-165. ouyang, y., li, p. (2018), on the nexus of financial development, economic growth, and energy consumption in china: new perspective from a gmm panel var approach. energy economics, 71, 238-252. ozturk i., acaravci a. (2013), the long-run and causal analysis of energy, growth, openness and financial development on carbon emissions in turkey. energy economics, 36, 262-267. phillips, p.c.b, perron, p. (1988), testing for a unit root in time series regressions. biometrika, 75, 335-346. phillips, p.c.b., hansen, b.e. (1990), statistical ınference in ınstrumental variables regression with i(1) processes. review of economic studies, 57, 99-125. pradhan, r.p., arvin, m.b., nair, m., bennett, s.e., hall, j.h. (2018), the dynamics between energy consumption patterns. financial sector development and economic growth in financial action task force (fatf) countries. energy, 6, 94. rafindadi, a., ozturk, i. (2017), dynamic effects of financial development, trade openness and economic growth on energy consumption: evidence from south africa. international journal of energy economics and policy, 7(3), 74-85. rafindadi, a.a.,ozturk, i. (2016), effects of financial development, economic growth and trade on electricity consumption: evidence from post-fukushima japan. renewable and sustainable energy reviews, 54, 1073-1084. saatçi, m., dumrul, y. (2013), a dynamic analysis of electricity consumption and economic growth: the case of turkey. uludağ journal of economy and society, 32(2), 1-24. sadorsky, p. (2010), the ımpact of financial development on energy consumption in emerging economies. energy policy, 38, 2528-2535. sadorsky, p. (2011), financial development and energy consumption in central and eastern european frontier economies. energy policy, 39, 999-1006. shahbaz, m. (2015), electricity consumption, financial development and economic growth nexus in pakistan: a visit. bulletin of energy economics (bee), 3(2), 48-65. shahbaz, m., hoang, t.h.v., mahalik, m.k., roubaud, d. (2017), energy consumption, financial development and economic growth in india: new evidence from a nonlinear and asymmetric analysis. energy economics, 63, 199-212. shahbaz, m., khan, s., tahir, m.i. (2013), the dynamic links between energy consumption, economic growth, financial development and trade in china: fresh evidence from multivariate framework analysis. energy economics, 40, 8-21. shahbaz, m., lean, h.h. (2012), does financial development ıncrease energy consumption? the role of ındustrialization and urbanization in tunisia. energy policy, 40, 473-479. stock, j.h., watson, m.w. (1993), a simple estimator of cointegrating vectors in higher order ıntegrated systems. econometrica, 61, 783-820. tamazian, a., chousa, j.p., vadlamannati, c. (2009), does higher economic and financial development lead to environmental degradation? evidence from bric countries, energy policy, 37, 246-253. zhang, y.j. (2011), the ımpact of financial development on carbon emissions: an empirical analysis in china. energy policy, 39, 2197-2203. tx_1~at/tx_2~at international journal of energy economics and policy | vol 13 • issue 2 • 2023194 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2023, 13(2), 194-199. the nexus between renewable energy consumption and economic growth: empirical evidence from jordan omar alkasasbeh*, ohoud khasawneh, amro alzghoul faculty of business, amman arab university, amman, jordan. *email: o.kasasbeh@aau.edu.jo received: 22 november 2022 accepted: 17 february2023 doi: https://doi.org/10.32479/ijeep.14007 abstract existing literature on the relationship between renewable energy and economic growth yields mixed outcomes, since the impact of renewable energy consumption on economic growth can be negative, positive or insignificant. using the autoregressive distributed lag (ardl) method, this paper examines the nexus between renewable energy and economic growth in jordan from 2000 to 2020, utilizing renewable electricity output (reo), renewable energy consumption (rec), and gross domestic product (gdp). utilizing the dickey–fuller (adf) and philips–perron (pp) unit root tests, the levels or differences of the stationary variables were explored. the statistically robust findings reveal that renewable energy usage has a substantial positive economic effects. the results indicate that stakeholders (including energy planners, governments, and private sector organizations) must collaborate to increase investment in renewable energy to secure long-term economic growth. keywords: ardl, climate, economic growth, greenhouse gas jel classifications: c24; o13; q2; q43 1. introduction climate change and its significant detrimental effects on the environment are critical problems facing the modern world. in recent decades, human activity, particularly energy use, has been identified as one of the primary contributors to climate change (pachauri and meyer, 2014). among other measures, a substantial change in the current technologies of energy production is required to tackle future environmental changes. traditional fossil fuel combustion techniques for energy generation (e.g., coal, oil, and gas power stations) have negative consequences on the environment; consequently, nations worldwide are trying to shift to more eco-friendly generation methods from renewable sources, including wind and solar. the energy information administration (eia) indicates that renewable energy generation has been the fastest-growing energy source in recent years (iea, 2020). developed nations embrace renewable energy sources to lower greenhouse gas emissions and enhance energy supply security (al-kasasbeh et al., 2022). in addition to contributing to increased modernization of the energy sector itself (kaygusuz, 2007), investment in and promotion of renewable energies contributes to macro-economic development and the sustainability goals of many nations (inglesi-lotz, 2016). achieving sustainability in energy consumption is likely to result in a cleaner environment, more access to electricity, enhanced energy efficiency with low-carbon renewables, and increased investment in cleaner technologies. in the global context, renewable energy deployment is increasing, which aids in combating climate change and expanding energy access to the billions of people currently living in poverty. in 2013, an estimated 19.1% of global final energy consumption was derived from renewable sources. hydropower, solar pv, and wind have driven the sector’s recent growth. the growth of heating capacity is proceeding at a consistent rate, while the production of biofuels for transportation has lately increased after a recession commensurate with the global economic downturn c. 2011–2012. according to the international energy agency’s (iea) most optimistic scenario, the renewable share of electricity generation will increase from 18.3% this journal is licensed under a creative commons attribution 4.0 international license alkasasbeh, et al.: the nexus between renewable energy consumption and economic growth: empirical evidence from jordan international journal of energy economics and policy | vol 13 • issue 2 • 2023 195 in 2002 to 39.0% by 2050, with a commensurate 50% reduction in global co2 emissions. in addition, studies on national energy policies are advancing in this direction. countries’ reliance on imports from potentially unreliable sources, as manifest in the current eu boycott of russian gas, the uncertainty of fossil resources themselves (which are becoming relatively more expensive to extract), political instability, and the negative environmental impacts of fossil fuels are the major sources of concern motivating political interest in renewables. according to scientific studies, the positive benefits of renewable energy use on the economy and the environment are accumulating daily. moreover, according to post-oil-crisis policies, mistrust of fossil fuel availability has elevated the issue of energy diversification, and dependence on fossil resources is seen as something to be avoided. the majority of proposed solutions tend to transition to renewable and less expensive energy sources. according to special report of the ipcc on climate change mitigation and renewable energy, historical increases in greenhouse gas emissions have been caused by the delivery of energy services, whereas boosts in renewable energy decrease the consequences of climate change (edenhofer et al., 2011). there is a substantial body of literature studying the association between renewable energy consumption and economic growth as its use has increased, particularly studies investigating the correlation between renewable energy consumption and economic growth. there is a rivulet of literature probing the “neutrality hypothesis,” which posits that there is no causal connection between energy consumption in general and economic growth (menegaki, 2011; chang et al., 2009; omri et al., 2015; bulut and muratoglu, 2018; al-kasasbeh et al., 2023). some studies have provided empirical evidence that the consumption of renewable energy increases economic growth (bilgili and ozturk, 2009; magnani and vaona, 2013; bilgili and ozturk, 2015; bhattacharya et al., 2017). conversely, other studies have reported that increased use of renewable energy contributes to negative economic growth, which is mainly attributed to the high upfront costs of investing in renewable infrastructure (marques and fuinhas, 2012; ocal and aslan, 2013; bhattacharya et al., 2016). the aim of this study, is to examine the nexus between renewable energy and economic growth in jordan (jordan does not have large oil and gas reserves, unlike other countries in the region, therefore jordan increased renewable energy use). utilizing unique variables such as renewable electricity output (reo); renewable energy consumption (rec); and gross domestic product (gdp). in addition, this study consists of five other sections. the second section gives an overview of literature review. the third one shows the methodology of the study, sample, data, and model used, and the fourth section discusses the results of the model. finally, the fifth section highlights the findings and recommendations. 2. empirical literature numerous developments in the global climate and environment, macroeconomic factors, globalization, energy technologies (particularly renewables), and market conditions have led to increasing research examining the relationship between energy consumption and economic growth. economic growth is generally analyzed at the national level (e.g., in terms of gdp), but nations have different political systems, cultures, energy policies, and domestic and imported energy sources, making it highly problematic to make generalized inferences from the outcomes of particular studies. studies of specific nations with different social, environmental, and economic profiles tend to lead to contradictory outcomes. however, certain economic fundamentals are universal, such as the anticipated effect of energy prices being instrumental in national economic growth; this has numerous potential implications, such as lower economic growth in nations lacking significant energy resources (who thus have to import more costly energy). within the framework of sustainable energy supply, the nexus between renewable energy and economic growth has been the subject of numerous streams of literature in various disciplines, including investigations of the relationship between energy and growth within the framework of sustainable energy supply. since kraft and kraft’s (1978) groundbreaking study, the literature on the link between energy consumption and economic development has grown. some major empirical studies examining the relationship between renewable energy consumption and economic growth (in terms of gdp) are summarized below. al-mulali et al. (2013) examined the association between renewable energy use and economic growth using data from 1980 to 2009 for 108 countries. according to their findings, there was a two-way relationship between renewable energy usage and economic growth in 85 of the studied nations; in 21, there was no correlation between renewable energy and economic growth; and two nations exhibited a one-way relationship between growth and usage of renewable energy. in total, 79% of nations exhibited a positive, bidirectional, long-term link between the consumption of renewable energy and gdp growth. shafiei and salim (2014) evaluated the effects of renewable and nonrenewable energy use on economic development and co2 emissions for 29 oecd nations using data from 1980 to 2011. according to their findings, there was a two-way causal relationship between economic growth and use of both renewable and nonrenewable energy. ohler and fetters (2014) investigated the association between economic growth and electricity generation from renewable sources using data for 20 oecd nations from 1990 to 2008. the results imply that energy conservation policies could have a positive impact on gdp under certain conditions. bhattacharya et al. (2016) analyzed the association between renewable energy use and economic growth for 38 countries with high renewable energy consumption using data from 1991 to 2012. they claimed that renewable energy had a substantial effect on economic growth, and that governments and other relevant institutions and organizations should determine renewable energy policies collaboratively. the findings indicate that some countries have a unidirectional relationship between the consumption of renewable energy and economic growth, and the longrun boost in consumption of renewable energy has a major effect on economic production. alkasasbeh, et al.: the nexus between renewable energy consumption and economic growth: empirical evidence from jordan international journal of energy economics and policy | vol 13 • issue 2 • 2023196 from 1980 to 2012, hassine and harrathi (2017) found a causal association between real gdp, trade, renewable energy consumption, and financial development for gulf cooperation council (gcc) countries. it is estimated that private sector credit, exports, and renewable energy consumption have substantial effects on output. in addition, it is anticipated that the usage of renewable energy and exports may contribute to the economic growth of gcc nations. conversely, sasana and ghozali (2017) studied the impact of fossil fuel and renewable energy consumption on economic growth for the five brics countries, using data from 1995 to 2014. the findings indicate that the consumption of fossil fuels had a favorable impact on economic growth, whereas the usage of renewable energy had a negative impact. benavides et al. (2017) examined the shortand long-term correlations between ch4 emissions, economic growth, power production from renewable sources, and trade openness for austria using data from 1970 to 2012. long-run granger test revealed one-way causation between ch4 and associated variables. aydin (2019) analyzed the association between renewable and nonrenewable electricity use and economic growth for 26 oecd nations using data from 1980 to 2015. the link between the variables was analyzed using two distinct panel causality methods: dumitrescu-hurlin’s (2012) panel causality test, and croux and reusens’ (2013) causality test. the feedback hypothesis was supported for all studied countries, but aydin (2019) noted that policies must be evaluated in terms of enhancing environmental quality and electricity energy supply security, in addition to economic growth. shao et al. (2020) analyzed the water-energy nexus for china during the period 2004–2014, in order to investigate the relationship between the synergetic conservation of water and energy resources. during the research period, china’s industrial sector witnessed a minor reduction in its overall technical efficiency, as defined by the ratio of actual output to ideal output in the production frontier. based on yearly data collected from 30 cities in china, yi et al. (2020) studied the effects of heterogeneous technical progress on haze pollution from 2003 to 2016. to empirically examine the consequences of neutral technical progress and biased technological growth, a systematic gmm method was utilized. due to the cost-reduction and income effects, the results indicated that neutral technological advance and labor-saving technological progress are helpful for haze reduction, but capital-saving technological progress has no influence on haze pollution. rahman and velayutham’s (2020) examined the relationship between renewable and non-renewable energy use and economic growth for five south asian nations from 1990 to 2014. the research employed the panel causality tests of pedroni (2004), kao (1999), and dumitrescue-hurlin (2012). the consumption of renewable and nonrenewable energy, as well as the formation of fixed capital, were found to have favorable effects on economic growth. a unidirectional causal link between economic growth and the consumption of renewable energy was also established. therefore, there appears to be no consensus in the literature about the impact of renewable energy use on economic growth. therefore, this study contributes to the existing literature by examining these unique variables mainly in jordan. where jordan, has not been studied extensively before. 3. methodology and data this study explores the connection between renewable energy and jordan’s economic growth, using data obtained from the world bank from 2000 through 2020 concerning renewable electricity output (reo), renewable energy consumption (rec), and gross domestic product (gdp). other variables were dependent on the proportion of rec to total final energy consumption and reo to total electricity output. before studying the long-term relationship between series, it is essential to determine whether they are stationary. there are numerous unit root tests available for determining the stationarity of a series and the existence of regression issues. the augmented dickey–fuller (adf) and philips–perron (pp) unit root tests were utilized in this study to investigate the levels or differences of the variables that are considered to be stationary. the ardl bound test examined the existence of a long-term relationship between variables in the study. some variables can be employed at level values i(0), while other variables are static in the first difference i(1). moreover, further cointegration methods are sensitive to the periods of the sample. in this method, the duration of the sample periods are not an issue, even if they are brief (harris and sollis, 2003). in this regard, pesaran et al. (2001) firstly evaluated the existence of a long-term association with the boundary test. we can compose an ardl-constrained model for the purposes of this study as follows: gdp gdp rec reo gdp t i n t i i n t i i n t� � � � � � � � � � �� � �� � � � � 0 1 1 1 2 1 3 1 � � � i tt i t i t i trec reo� � �� � �� � �2 3 1 (1) where gdp is economic growth; rec is renewable energy consumption; reo is renewable electricity output; α1, α2, and α3 are coefficients that measure short-run relationships; ρ1, ρ2 and ρ3 are coefficients that measure long run relationships; εt is an error term, denoting the lag length of the auto regressive process; and t is the time trend of the model. the hypotheses from the above equations are: h 0 1 2 3 0: � � �� � � (indicating that there is no long run association between the independent and dependent variables). table 1: variables description and data source variable abb. period source economic growth gdp 2000-2020 wdi renewable energy consumption rec 2000-2020 wdi renewable electricity output reo 2000-2020 wdi wdi world bank development indicators alkasasbeh, et al.: the nexus between renewable energy consumption and economic growth: empirical evidence from jordan international journal of energy economics and policy | vol 13 • issue 2 • 2023 197 h 1 1 2 3 0: � � �� � � (indicating that there is a long run association between independent and dependent variables). table 1 shows the variables used in this analysis. in the granger causality study, the optimal lag length is calculated using the akaike information criterion (aic) and the schwatz information criterion (sci) after the maximum integration level of the series has been identified by the adf and pp unit root tests. to determine causality link and direction, the var model is calculated using the number of lags. in the causality relation, the null hypothesis states that independent variables equal zero, whereas the alternative hypothesis states that independent variables do not equal zero. the null hypothesis is rejected and the alternative hypothesis is accepted if the granger statistic is statistically significant. acceptance of the alternative hypothesis entails the existence of a causal link between the independent and dependent variables. 4. empirical analysis results in order to acquire reliable results, adf and pp tests were utilized. the results of the unit root test are shown in table 2, which displays the findings of the unit root analysis of the variable components for rec, reo, and gdp. each series has a unit root, indicating that they are nonstationary at their levels, but stationary at their initial differences. according to the results of the adf unit root test, rec, reo, and gdp are integrated in the same sequence, i(1). however, identifying the appropriate lag length is crucial for examining long-term connections between variables; this is where the sci and aic come in. the results confirm that “2” is the optimal lag duration for this study. the ardl bound model is used to examine the long-term relationship. the ardl method involves determining whether or not a model’s variables have a long-term relationship. a “bounds testing” methodology was developed for this determination, and the ardl model is specified to determine whether variables have a longterm association. table 3 shows the critical values. because the calculated f-statistic was greater than the upper critical value at the 1, 5, and 10% significance levels, it can be argued that there is a long-term association between the variables rec, reo, and gdp. the shortand long-term results are shown in table 4 the value of ecm (−1), which must be significant and negative according to the results reported in table 4, must be both of these things. the “error correction” term suggests that the process of adjustment utilized to restore equilibrium is quite effective. the coefficient is 0.632, and it is significant at a level of 1%; this indicates that short-term shocks or deviations are corrected at the rate of 63.2% in the direction of the long-term equilibrium. the results shown in table 5 indicate that gdp is caused by rec and reo. this finding indicates that renewable energy and electricity output are anticipated to have a favorable effect on economic growth in jordan. according to these findings, policymakers in jordan must invest in renewable energy sources for the sake of the economy. it can be claimed that renewable energy policies play a crucial role in the nation’s strategies, and that a significant portion of national investments should be made in this area. this conclusion is consistent with the findings of jaradat and al-tamimi (2022) and can and korkmaz (2019). 5. conclusion considering jordan’s dependence on fossil fuels and natural gas as a developing country with socio-economic preconditions antipathetic to renewables adoption (e.g., high unemployment etc.) (sánchez and subiela, 2007; gharaybeh, 2014), it can be claimed that the contribution of renewable energy options in its power mix is relatively substantial. positive economic advances are anticipated in the future if the cost of establishing renewable energy and its accessibility and cost are comparable with fossil energy sources. table 2: adf and pp unit root tests variables adf p.p at level at first different at level at the first different gdp −3.766* (0.006) −4.795* (0.000) −3.572* (0.010) −4.719* (0.000) rec −2.011 (0.281) −8.998* (0.000) −2.449* (0.134) −4.912* (0.000) reo −2.421 (0.141) −7.745* (0.000) −2.384 (0.151) −7.711* (0.000) source: author’s calculation using eviews 11.0 table 4: long run and short run estimates variable coefficient std. error t-statistic prob. d (gdp) 0.015* 0.0076 2.2815 [0.000] d (reo) 0.102** 0.0052 2.0450 [0.001] d (rec) −0.032** 0.0076 6.7563 [0.002] ecm (−1) −0.632** 0.02449 −6.5917 [0.000] long run coefficients gdp 0.628* 0.0459 3.3976 [0.000] reo −0.167** 0.0059 3.7332 [0.000] rec 0.216** 0.0055 4.4425 [0.000] source: research finding table 3: bounds test results critical value lower bound value upper bound value 1% 5.01 4.94 5% 3.82 4.28 10% 3.11 3.84 f-statistic=8.42105, k=1, source: research finding table 5: granger causality wald test equation prob >chi-square gdp cause all p<0.05 reo cause all p<0.05 rec cause all p<0.05 source: author’s calculation alkasasbeh, et al.: the nexus between renewable energy consumption and economic growth: empirical evidence from jordan international journal of energy economics and policy | vol 13 • issue 2 • 2023198 according to the conclusions arising from this study, jordan must expand its investments in renewable energy resources to enhance the long-term linkages between renewable electricity output, renewable energy consumption, and gross domestic product variables. in this context, it is possible to assert that the positive impacts of renewable energy consumption on economic growth will increase if the nation’s strategy and investment incentives are maintained and expanded. instead of relying on imported fossil fuels, the nation’s energy supply should be increasingly geared toward renewable energy sources such as solar and wind. the results of this study have important implications for legislative authorities; the results highlight the need for new strategies to increase the proportion of renewable energy investments in jordan’s energy production portfolio more quickly and efficiently. more steps must be done the government should invest in renewable infrastructure and support private sector partners via tax breaks for firms investing in renewables. references alkasasbeh, o.m., alassuli, a., alzghoul, a. (2023), energy consumption, economic growth and co2 emissions in middle east. international journal of energy economics and policy, 13(1), 322-327. al-kasasbeh, o., alzghoul, a., alhanatleh, h. (2022), empirical analysis of air pollution impacts on jordan economy. international journal of energy economics and policy, 12(4), 512-516. al-mulali, u., fereidouni, h.g., lee, j.y., sab, c.n.b.c. (2013), exploring the relationship between urbanization, energy consumption, and co2 emission in mena countries. renewable and sustainable energy reviews, 23, 107-112. aydin, m. (2019), renewable and non-renewable electricity consumptioneconomic growth nexus: evidence from oecd countries. renewable energy, 136, 599-606. benavides, m., ovalle, k., torres, c. and vinces, t. (2017), economic growth, renewable energy and methane emissions: is there an environmental kuznets curve in austria? international journal of energy economics and policy, 7(1), 259-267. bhattacharya, m., churchill, s.a., paramati, s.r. (2017), the dynamic impact of renewable energy and institutions on economic output and co2 emissions across regions. renewable energy, 111, 157-167. bhattacharya, m., paramati, s.r., ozturk, i., bhattacharya, s. (2016), the effect of renewable energy consumption on economic growth: evidence from top 38 countries. applied energy, 162, 733-741. bilgili, f., ozturk, i. (2015), biomass energy and economic growth nexus in g7 countries: evidence from dynamic panel data. renewable and sustainable energy reviews, 49, 132-138. bulut, u., muratoglu, g. (2018), renewable energy in turkey: great potential, low but increasing utilization, and an empirical analysis on renewable energy-growth nexus. energy policy, 123, 240-250. can, h., korkmaz, ö. (2019), the relationship between renewable energy consumption and economic growth: the case of bulgaria. international journal of energy sector management, 2019, 2951. chang, t.h., huang, c.m., lee, m.c. (2009), threshold effect of the economic growth rate on the renewable energy development from a change in energy price: evidence from oecd countries. energy policy, 37(12), 5796-5802. dumitrescu, e.i., hurlin, c. (2012), testing for granger non-causality in heterogeneous panels. economic modelling, 29(4), 1450-1460. edenhofer, o., pichs-madruga, r., sokona, y., seyboth, k., kadner, s., zwickel, t., matschoss, p. (2011), renewable energy sources and climate change mitigation: special report of the intergovernmental panel on climate change. united kingdom: cambridge university press. gharaybeh, k. (2014), general socio-demographic characteristics of the jordanian society: a study in social geography. research on humanities and social sciences, 4(1), 1-10. harris, r.d. (1957), (2546). applied time series modelling and forecasting. new york: j. wiley. hassine, m.b., harrathi, n. (2017), the causal links between economic growth, renewable energy, financial development and foreign trade in gulf cooperation council countries. international journal of energy economics and policy, 7(2), 76-85. iea. (2020), world energy demand and economic outlook of the 2020 international energy outlook. available from: https://www.iea.org/ reports/world-energy-outlook-2020 inglesi-lotz, r. (2016), the impact of renewable energy consumption to economic growth: a panel data application. energy economics, 53, 58-63. jaradat, m.s., al-tamimi, k.a.m. (2022), economic impacts of renewable energy on the economy of uae. international journal of energy economics and policy, 12(1), 156-162. kao, c. (1999), spurious regression and residual-based tests for cointegration in panel data. journal of econometrics, 90(1), 1-44. kaygusuz, k. (2007), energy for sustainable development: key issues and challenges. energy sources, part b: economics, planning, and policy, 2(1), 73-83. kraft, j., kraft, a. (1978), on the relationship between energy and gnp. the journal of energy and development, 401-403. magnani, n., vaona, a. (2013), regional spillover effects of renewable energy generation in italy. energy policy, 56, 663-671. marques, a.c., fuinhas, j.a. (2012), is renewable energy effective in promoting growth? energy policy, 46, 434-442. menegaki, a.n. (2011), growth and renewable energy in europe: a random effect model with evidence for neutrality hypothesis. energy economics, 33(2), 257-263. ocal, o., aslan, a. (2013), renewable energy consumption-economic growth nexus in turkey. renewable and sustainable energy reviews, 28, 494-499. ohler, a., fetters, i. (2014), the causal relationship between renewable electricity generation and gdp growth: a study of energy sources. energy economics, 43, 125-139. omri, a., mabrouk, n.b., sassi-tmar, a. (2015), modeling the causal linkages between nuclear energy, renewable energy and economic growth in developed and developing countries. renewable and sustainable energy reviews, 42, 1012-1022. pachauri, r.k., meyer, l.a. (2014), climate change 2014: synthesis report. contribution of working groups i, ii and iii to the fifth assessment report of the intergovernmental panel on climate change. pedroni, p. (2004), panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the ppp hypothesis. econometric theory, 20(3), 597-625. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. rahman, m.m., velayutham, e. (2020), renewable and non-renewable energy consumption-economic growth nexus: new evidence from south asia. renewable energy, 147, 399-408 sanchez, a.s., subiela, v.j. (2007), analysis of the water, energy, environmental and socioeconomic reality in selected mediterranean countries (cyprus, turkey, egypt, jordan and morocco). desalination, 203(1-3), 62-74. sasana, h., ghozali, i. (2017), the impact of fossil and renewable energy consumption on the economic growth in brazil, russia, india, china alkasasbeh, et al.: the nexus between renewable energy consumption and economic growth: empirical evidence from jordan international journal of energy economics and policy | vol 13 • issue 2 • 2023 199 and south africa. international journal of energy economics and policy, 7(3), 194-200. shafiei, s., salim, r.a. (2014), non-renewable and renewable energy consumption and co2 emissions in oecd countries: a comparative analysis. energy policy, 66, 547-556. shao, s., yang, z., yang, l., zhang, x., geng, y. (2020), synergetic conservation of water and energy in china’s industrial sector: from the perspectives of output and substitution elasticities. journal of environmental management, 259, 110045. yi, m., wang, y., sheng, m., sharp, b., zhang, y. (2020), effects of heterogeneous technological progress on haze pollution: evidence from china. ecological economics, 169, 106533. . international journal of energy economics and policy | vol 10 • issue 2 • 2020 285 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(2), 285-293. healthcare expenditures channel of natural resource curse: the case of gulf cooperation council countries seyfettin erdoğan1, emrah i̇smail çevik2, ayfer gedikli3* 1istanbul medeniyet university, turkey, 2namık kemal university, turkey, 3istanbul medeniyet university, turkey. *email: ayfergedikli@yahoo.com received: 05 september 2019 accepted: 02 january 2020 doi: https://doi.org/10.32479/ijeep.8667 abstract the fact that the increase in natural resource revenues is not adequately transferred to human capital investments is one of the main reasons for explaining the weak economic growth performance. the findings of numerous studies investigating the relationship between healthcare expenditures and natural resource abundance in natural resource-rich countries confirm this assertion. these findings can be considered as a source of information in the process of determining the policies regarding human capital investments to be implemented in natural resource-rich countries. the aim of this study is to investigate the relationship between the abundance of natural resources and health expenditures by using data from 2000 to 2016 for gulf cooperation council (gcc) member countries consisting of united arab emirates, bahrain, qatar, kuwait, saudi arabia and oman. the empirical results indicated that there is no causal relationship between the variables of gcc countries except bahrain and uae. this result shows that the resource curse hypothesis is partially valid. therefore, gcc countries aiming to increase their economic growth performances by implementing a diversification strategy in production should allocate more sources to health expenditures in order to increase their labor efficiency. keywords: healthcare expenditures, natural resource, gulf cooperation council member countries jel classifications: h51, n55, j24 1. introduction one of the most important determinations of the researchers studying in the field of growth economics regarding the natural resource-rich countries is that the income obtained from natural resources and the large-scale oil and natural gas resources do not always have positive results in economic growth performance. on the contrary, in many countries having rich oil reserves, autocratic governments are in charge; government institutions do not work effectively; and problems like civil conflicts trigger political and social chaos. as a result, in natural resource-rich countries driven by global capital, the natural resource curse hypothesis is valid. according to this hypothesis, natural resource abundance affects economic growth in negatively (wigley, 2017. p. 143). there is an extensive literature on natural resource curse hypothesis. studies of auty (1994) and sachs and warner (1995 and 19971) are the pioneer studies that inspired similar researches. political and social problems in natural resource-rich countries, as well as the lack of sufficient sources for health expenditures to strengthen human capital, are the most important reasons for inadequate economic growth performance. despite the abundance of natural resources, qualitative and quantitative insufficiency of health, which is one of the subcomponents of human capital, negatively affects economic growth 1 in this study, while analyzing the slowness of economic growth in the countries included in the study, the authors also highlighted the decisive role of low life expectancy which is one of the main indicators of health, as a fundamental structural problem. this journal is licensed under a creative commons attribution 4.0 international license erdoğan, et al.: healthcare expenditures channel of natural resource curse: the case of gulf cooperation council countries international journal of energy economics and policy | vol 10 • issue 2 • 2020286 performance, and can be explained by the concept of healthcare channel of natural resource curse. despite having natural resource abundance and great amount of public revenue, in resource-rich countries there is not enough sensitivity on improvement of health investments or not enough allocation on health expenditures. moore (2014) stated that, this contradiction stems from the political pathologies. some of these pathologies are as follows: firstly, oil is one of the strategic commodities in the global scale. developed countries are particularly sensitive about the security of supply of oil, which is one of the main inputs of production. developed countries keep the natural resource abundant areas under political and military pressure. political leaders of natural resource-rich countries, instead of taking responsibility of their own citizens, focus on the military and political support of the global powers to maintain the current regime. the fact that the governments are not dependent on the financial support of their citizens makes them not worry about increasing public expenditures on human capital such as health or education. secondly, in democratic regimes, the main income source of government is taxes. individuals may consider involving in politics as a right to check whether this source of income is being used effectively. neverthless, in some natural resource-rich countries, government revenues rely on natural resource revenues rather than direct taxes, which discourages individuals’ aspirations to enter politics to involve the process of using tax revenues by political powers. thirdly, in developing natural resource-rich countries, public revenues are largely driven by a few foreign oil companies and public-run natural resource companies. in that context, public incomes and expenditures cannot be transparent (moore, 2004. p. 306-308). in another study, moore stated that contrary to developed countries, in less-developed regions, unearned income sources are shown as bases of revenue rather than tax incomes. in underdeveloped countries whose economies are predominantly based on unearned income sources, which are expressed as income from natural resources or development aids, a culture of negotiation in accordance with democratic processes on public expenditure and public revenues has not developed (moore, 2001. p. 389). hong (2018) argues that, despite the abundance of natural resources, the lack of adequate investments on health is related to opportunity that natural resources provide authoritarian leaders with the possibility of production uncorrelated with labor force. the lack of sufficient resources for public expenditures in natural resource-rich countries can be explained by the problem of social rigidity. especially in natural resource-rich countries, industry leaders in natural resources use their high income to expand their political influence. high-income groups can act to maximize their personal interests by ignoring the whole community, and they can make legal arrangements parallel to rent seeking initiatives and ensure that policies prior to their sectors are implemented. such attempts lead to a reduction in public expenditures which are critical for improving human capital power, such as health (zhuang and zhang, 2016. p. 4). the relationship between the natural resources abundance and health can be put forth by examining the relationship between the income of natural resource-rich countries and the health indicators. healthcare performance of resource-rich countries can be evaluated by looking at indicators such as infant and child mortality, average life expectancy, public and private health expenditures. the main reason for the scope of the research consists of gulf cooperation council (gcc) countries is that these countries are oil-rich countries except bahrain, oil exports have a high share in total exports and public revenues are mainly based on oil revenues. besides, as selim and zaki (2014. p. 3) point out, in these countries where growth performance is directly affected by volatility in natural resource prices and there are not enough initiatives to develop other sectors other than oil, natural resource revenues are used mainly for the legitimacy of power and the stability of the regime. empirical investigation of insufficient allocation of resources in areas like healthcare that improves human capital power will provide a scientific basis for these determinations. the second important point in the study is the preference of health expenditures indicator in the investigation of the relationship between the abundance of natural resources and health. for the analysis, health expenditure data were used because of the availability of data and because this is the variable that directly reflecting natural resource revenues. it is noteworthy that it is a legal obligation in saudi arabia and the other gcc countries to provide free health care to citizens. compared to other highincome countries, the percentage of public health expenditures to total health expenditures is relatively high in gcc countries. on average, the share of public health expenditures in health expenditures in gcc countries is 72.5%, while in other high income countries it is 62.2%. in the gcc countries, the health care financing system is in the process of development, and health care is financed by revenues from natural resources such as oil. in some countries, other sources of income are being used for healthcare financing, but these sources still remain at very low levels (alkhamis et al, 2014. p. 70, 72 and 79). in this study, the relationship between the increase in oil revenues and the health expenditures was analyzed by considering financing healthcare expenditures with natural resource revenues. the relationship between the variables was investigated by panel causality test because of its advantages expressed in the econometric model part. based on the findings of the study, we concluded that resource curse hypothesis is partially valid. the main difference of this study from similar studies is that, to the best of our knowledge, this is the first study to examine the relationship between the increase in oil revenues and health expenditures in the preferred period for gcc countries. in the first part, the literature research, in the second part, econometric model and in the third part, the scope of the study and the analysis results are explained. 2. literature review the importance of investigating the impact of resource abundance on human capital investments such as education and health in erdoğan, et al.: healthcare expenditures channel of natural resource curse: the case of gulf cooperation council countries international journal of energy economics and policy | vol 10 • issue 2 • 2020 287 natural resource-rich countries is that human capital is one of the main determinants of long-term economic growth. countries that allocate sufficient sources for human capital investments will achieve high economic growth performance. raheem et al. (2018), using data from 18 sub-saharan african countries for the period 1995-2013, investigated the impact of healthcare and education expenditures on economic growth as well as the positive results of investing natural resource revenues on education and health which are considered as the human capital development indicators of natural resource revenues. it was concluded that public expenditures on education and health have a positive impact on economic growth. besides, increasing public health expenditures led per capita gdp growth by more than 3.1%. these results pointed the necessity and priority of allocating more share of natural resource income on health. in the human capital literature, there are not many studies investigating the relationship between the abundance of natural resources and health expenditures or the relationships between other health related indicators. in studies examining the effects of natural resources on human capital investments, natural resource abundance or natural resource dependence variable is mostly used. in his study that was investigated the relationship between natural resource and human development indicators, daniele (2011. p. 567) explained that while the degree of dependence on natural resources would be measured by the share of mine and fuel in total export, natural resource abundance could be measured by the share of per capita and per square kilometer of underground assets. the theme of this study is to investigate the extent to which natural resource revenues are transferred to health expenditures and to investigate the relationship between oil revenues and health expenditures. no matter natural resource abundance or natural resource dependence is taken as an indicator in researches; natural resource is the key variable in both cases. natural resource dependence is heavily increased by the abundance of natural resources. therefore, in this paper, regardless of resource abundance or resource dependence, the causal relationship between the increase in oil revenues and health expenditures, was investigated. the findings of similar studies are summarized below, as they also show the relationship between these variables. cockx and francken (2014) investigated the impact of natural resource wealth on public health expenditures by using the data from a number of countries with different levels of development for the period 1995-2009. the test results showed that there is a strong reverse causality relationship between the natural resource abundance and natural resource dependence and public health expenditures. cockx and francken (2015) conducted a similar study for the middle east and north africa (mena) region. the authors tested the data of the countries in this region for the period 1995-2009 and found a significant reverse causality relationship between health expenditure and natural resource dependence which is measured as the share of natural resource wealth in total wealth and health expenditure. also, in many studies it was stated that the increase in degree of dependence on oil wealth in mena countries increased the effect of natural resource curse. zhan et al. (2015), using the data of china’s 31 provinces for the period 1999-2009, investigated whether natural resources caused natural resource curse for human capital development. in the regions which have high natural resource dependence, local authorities spend less on education or health that have positive effects on human capital. in the study, it is emphasized that in natural resource-rich regions, citizens and government authorities show myopic behaviors that ignore human capital development. zhuang and zhang (2016) investigated the relationship between the abundance of natural resources and healthcare services in the shanxi region of china. empirical results showed that coal-rich local governments allocate more sources to administrative expenditures and spend less for health services. in this study, it is also stated that human capital investments are neglected due to political myopia and natural resource curse hypothesis is valid. wigley (2017) compared the performance of oil-rich countries and oil-poor countries in improving child health services. the researcher tested the data of 167 countries for the period 1961-2011 and found that oil poor countries showed a better performance than oil-rich countries in reducing the mortality of children under 5 years of age. chang and wei (2019) examined the impact of natural resources on malaria using the data from 107 countries for the period 2000-2014. according to the empirical results, natural resources abundance is positively related to the high number of deaths and illnesses resulting from malaria. likewise, in countries whose national wealth is based on natural resources, the natural resources abundance is negatively related to hiv/aids, infant mortality and health expenditures. hong (2018) investigated the impact of the abundance of natural resources on public services by using data from 288 provinces of china for the period 1992 to 2010. it was concluded that the abundance of mines (coal and oil production) caused local administrations to provide less education and health services. in this study, it is emphasized that oil and coal production negatively affects public services that contribute to the development of human capital. madreimov and li (2019) examined the relationship between natural resources and life expectancy as an indicator of quality of life, using data from 67 countries for the period 1990 to 2011. the authors found a u-shaped relationship between natural resource dependence and life expectancy. empirical results of the study showed that natural resource dependence has a positive effect on life expectancy in the short term. however, this effect reverses in the long term. in the long term, natural resource dependence adversely affects human development. gearhart and michieka (2019) investigated the validity of the natural resource curse hypothesis by examining the impact of natural resource abundance on health efficiency in appalachia, one of the poorest regions in the us but having abundant natural resources such as coal, natural gas and oil. the data of the region were tested for the period 2012-2016 and it was found that natural resource production worsened the health efficiency and thus the natural resources curse emerged. negative results are due to employment in the natural resource sector and air and water pollution. according to the results, policy makers should implement the improvement strategies in education; besides, there must be wise policies to reduce alcohol, smoking and obesity to improve public health. there are also studies that searched a positive or multiple relationships between the natural resources abundance, health erdoğan, et al.: healthcare expenditures channel of natural resource curse: the case of gulf cooperation council countries international journal of energy economics and policy | vol 10 • issue 2 • 2020288 expenditures and health outcomes. anshasy and katsaiti (2015) investigated the impact of economic dependence on different natural resources on health expenditures and health outcomes using the data from 118 countries for the period 1990 to 2008. countries were divided into four groups based on resource type and resource density. the empirical findings are as follows:  the level of health expenditures is increasing in countries with high mineral resource density. however, there is no significant relationship between natural resource density and health outcomes  diabetes and obesity rates remain low if more hydrocarbon resource revenue is generated in energy-dependent economies (based on oil, natural gas and coal revenues). however, especially in countries where there is no democracy regime, the share of public health expenditures decreases as the economy grows due to the increase the intensity of hydrocarbon sources. cotet and tsui (2013) investigated the relationship between oil and growth, and oil wealth and health improvement indicators, using worldwide data on the discovery and production of oil. in the study, it was found that the natural resource curse hypothesis is not valid. the results show that there is a positive relationship between oil abundance and long-term growth. besides, even with low level of institutional development, high oil revenues do not weaken economic growth performance. furthermore, there is a positive trend in life expectancy and infant mortality rates in oilrich countries. by comparison, people in oil-rich countries benefit more from healthcare improvements. it is also emphasized that in nondemocratic countries, the recovery tendencies in the health systems which are financed by oil was higher. 3. econometric framework consideration of possible cross-sectional dependence among countries is important when using panel causality tests. because the oil rents for gcc countries rely on global oil prices and fluctuations in global oil prices affect the entire gcc countries in a similar way, cross-sectional dependence is expected among those countries. pesaran (2006) stated that there would be a significant bias and size distortions in the testing methods when cross-sectional dependence is neglected and that testing crosssectional dependence was an important issue in panel data analysis. lagrange multipliers (lm) test, developed by breusch and pagan (1980), is frequently used in the literature to determine cross-sectional dependence. pesaran (2004) suggests a crosssection dependency (cd) test and states that this test can be used when both t→∞ and n→∞. also, pesaran et al. (2008) state that power of the cd test considerably decreases when the population average pairwise correlations are zero. in this context, pesaran et al. (2008) suggested a bias adjusted lm test statistic where the exact means and variance of the lm test statistic are used (lmadj). they stated that the adjusted test statistic follows asymptotically normal distribution. the null hypothesis for each of the three tests indicates the presence of cross-sectional dependence, and hence the rejection of the null hypothesis suggests the lack of cross-sectional dependence in the panel. we employ all three tests in order to find out whether there is crosssectional dependence. the second issue when conducting a panel causality test is to determine whether slope coefficients are homogenous in each cross-section. granger (2003) stated that imposing the joint zero restriction to test causality relationship in panel dimension leads to strenghten the null hypothesis. breitung (2005) stated that heterogeneity that resulted from country-specific reasons cannot be determined when assuming homogeneity for parameters. swamy (1970) suggested a test for the homogeneity of the slope parameter when testing the dispersion of slope coefficients. the test is called as ∆˜ test in the literature. also, the test statistic suggested by swamy (1970) requires a panel data in which n is small relatively t. pesaran and yamagata (2008) developed the standardized version of the test developed by swamy for the test of homogeneity of slope coefficients in large panel. test statistics developed by pesaran and yamagata (2008) is called as ∆˜adj. the null hypothesis of both ∆˜ and ∆˜adj tests is that slope coefficients are homogeneous. therefore, the rejection of the null hypothesis indicates heterogeneity in the slope coefficients. when there is a cross-sectional dependence and the slope coefficients are heterogeneous, the panel causality test proposed by kónya (2006) is the most appropriate. because when applying the konya panel causality test, the seemingly unrelated regression (sur) model is taken into consideration and it is well known that sur model provides unbiased estimator in the case of cross-sectional dependence. additionally, since the konya panel causality test provides test results for each cross-section separately it enables slope coefficients to be heterogeneous. moreover, the panel causality test developed by kónya (2006) is more advantageous when compared to the conventional causality test. first, when there is a contemporaneous correlation among the countries in the panel, the estimates that are obtained from the vector autoregressive (var) model results will be inefficient because the estimates of var model are obtained by using the ordinary least squares (ols) method. therefore, kónya (2006) stated that the equation system should be defined as the sur model instead of var model to overcome this problem when causality relationship is examined. it is stated that cross-sectional contemporaneous correlation is taken into consideration in the sur system and the sur model provides more efficient estimates than the var model. second, panel causality test is carried out by imposing zero restriction to the lagged coefficients and critical values are obtained using the bootstrap method. in this context, the test does not require investigation the stationarity of variables and also cointegration relationship for non-stationary variables. finally, since causality relationship can be investigated in crosssection dimension separately, the causality relationship for each of the cross section can be interpreted. in order to investigate the country-based granger causality relationship between natural resource rents (nr) and health expenditures (he), initially, the following two-variable var model should be estimated: erdoğan, et al.: healthcare expenditures channel of natural resource curse: the case of gulf cooperation council countries international journal of energy economics and policy | vol 10 • issue 2 • 2020 289 he he nri t i i l i t l mlhe i l i t l mlnri i , , , , , , , ,= + + +− = − = ∑ ∑α β γ ε1 1 1 1 1 1 1 11 2 2 1 1 2 1 1 , , , , , , , , , , i t i t i i l i t l mlhe i l i t l m nr he nr i = + + +− = − = ∑α β γ llnr i t i ∑ ε2, , (1) in equation (1), i denotes countries, t denotes time dimension and l denotes lags of the variables. ε1,i,t and ε2,i,t are assumed to be white noise and there might be a relationship for any of the countries, but it is assumed to be unrelated for all countries. also, het and nrt are assumed to be stationary or cointegrated and thus, level or first differences of the variables are used depending on the characteristics of the series while investigating a causal relationship. in this context, in order to say that there is a one way causality relationship from nr to he, all γ1,i in the first equation should be statistically different from zero, and all β2,i in the second equation should be statistically zero. when all β2,i in the second equation are statistically different from zero, and all γ1,i in the first equation are statistically zero, it can be said that there is a one way causality relationship from he to nr. the presence of bidirectional causality relationship between nr and he suggest that all γ1,i’ in the first equation and all β2,i’ in the second equation are statistically different from zero. however, when all γ1,i’ in the first equation and all β2,i’ in the second equation are statistically equal to zero, there is no causality relationship between nr and he. since two different models are required to be estimated in order to investigate a causality relationship between two variables for a country, an equation amounting to 2n should be estimated to investigate a causality relationship within the context of equation (1). if we divide the equation system in equation (1) into two groups, the first group can be designed to show the equations for he and the second group can be designed to show the equation for nr. in other words, instead of n number of the var system, we can consider the two-equation system as follows: he he nrt l t l mlhe l t l mlnr 1 11 11 1 1 1 11 1 1 1 1 1 , , , , , , , ,= + + +− = − = ∑ ∑α β γ ε111 2 1 2 1 2 2 1 1 1 2 2 1 1 1 , , , , , , , , , , t t l t l mlhe l t l m he he nr= + + +− = − = ∑α β γ llnr t n t n n l n t l mlhe n l n the he nr 1 1 1 2 1 1 1 1 1 ∑ ∑= + +− = ε α β γ , , , , , , , , , ,  −− = +∑ 1 1 1 1 l mlnr n tε , , (2) nr he nrt l t l mlhe l t l mlnri i 1 21 21 1 1 1 21 1 1 1 , , , , , , , ,= + + +− = − = ∑ ∑α β γ ε221 2 2 2 2 2 1 1 1 2 2 1 1 1 , , , , , , , , , , t t l t l mlhe l t l m nr he nr i = + + +− = − = ∑α β γ llnr t n t n n l t l mlhe n l t i i nr he nr ∑ ∑= + +− = ε α β γ 2 2 2 2 1 1 1 2 1 , , , , , , , , , ,  −− = +∑ 1 1 2 l mlnr n t i ε , , (3) when compared to equation (1), this alternative formulation is seen to have two important characteristics. first, each equation in equation (2) and equation (3) might have different pre-determined variables. in case that there is a link between each regression equation, there will be contemporaneous correlation within the system. therefore, these equation systems are defined as sur model instead of var model. second, since country-based bootstrap method will be used to obtain critical values, there is no need for he and nr to be stationary. in other words, when investigating the causality relationship between the variables, there is no need to investigate the stationary or cointegration relationship of the series since critical values obtained by using bootstrap method. according to the sur equation system, in order to determine the causality relationship running from nr to he, all γ1,i in equation (2) should be statistically different from zero, and all β2,i in equation (3) should be statistically equal to zero. when all β2,i in equation (3) are statistically different from zero, and all γ1,i in equation (2) are statistically zero, there is a one way causality relationship from he to nr. the presence of bidirectional causality relationship between nr and he suggest that all γ1,i’ in equation (2) and all β2,i’ in equation (3) are statistically different from zero. when all γ1,i and all β2,i in equation (2) and equation (3) are statistically equal to zero, it is said that there is no causality relationship between nr and he. the most appropriate estimation method for equation (2) and equation (3) changes depending on the characteristics of the error terms. when there is no contemporaneous correlation among the countries, each equation can be considered as a classic regression model. in such a case, each of the equations can be estimated using ols method, and ols method provides the best unbiased linear estimators. on the other hand, when there is a contemporaneous correlation among the countries, the ols estimators will lose their efficiency. in this case, equation (2) and equation (3) should be estimated by using the generalized ls method or the maximum likelihood method. kónya (2006) suggested the use of sur estimators, developed by zellner (1962), when there is a contemporaneous relationship among the countries. kónya (2006) suggested a bootstrap method to obtain critical values for the test statistic. bootstrap method is a simple resampling method. the following steps should be followed in order to obtain critical values based on bootstrap: step 1: under the null hypothesis stating that there is no causal relationship from nr to he, equation (2) is estimated and residuals are obtained as follows: 0 1 h ,i,t i,t 1,i mlhe 1,i,l 1,t 1 l 1 ˆe he ˆ he i 1, , n and t 1, , t− = = −α − β = =∑   (4) step 2: residuals obtained in the first step are resampled. in order to be able to consider the contemporaneous cross-correlations in residuals, resampling of residuals is carried out by considering the residuals of the entire countries instead of each country. bootstrap residuals are called as e*h0,i,t. erdoğan, et al.: healthcare expenditures channel of natural resource curse: the case of gulf cooperation council countries international journal of energy economics and policy | vol 10 • issue 2 • 2020290 step 3: under the assumption that there is no causality from nr to he, bootstrap sample of he is calculated with the formula given below: 1 , 1, 1 , ,0 * * * * 1, 1, , 1 ˆˆ 1, , i t t h i t mlhe i i l l he he e t tα β − = = − + =∑  (5) step 4: considering the values of he*i,t values instead hei,t values and in order to test the null hypothesis stating that there is no causality for each of the country without putting any restrictions, the wald test is calculated. step 5: step 2 and 4 are iterated many times and empirical distribution is developed for wald test statistics and bootstrap critical values are obtained based on the percentages selected from the sample distribution. we also examine the dynamic relationship between natural resource rents and health expenditures by using the asymmetric causality test. in this context, it will be investigated whether increases or decreases in natural resource rents have an effect on health expenditures regarding positive and negative shocks. thus, the validity of the natural resource curse hypothesis can be examined. in the study, the causality relationship between natural resource rents and health expenditures will be considered using the kónya (2006) panel causality test, but positive and negative shocks series will be determined using an approach developed by hatemi (2012). before determining the asymmetric causality relationship between nr and he, positive and negative shocks for the variables are obtained as follows: he he het t he hei i t t = + = +− − ∑1 0 1   (6) nr nr nrt t nrt nri i t = + = +− − ∑1 0 1   (7) where t = 1,2,…,t, constant terms he0 and nr0 denote initial values and εshi and εdkgi denote white noise residuals. positive and negative shocks are defined as follows respectively:        hei hei nri nri hei hei nri + + − = ( ) = ( ) = ( ) mak mak, , , , min , , 0 0 0 −− = ( )min ,nri 0 (8) where   hei hei hei= + + − and   nri nri nri= + + − . based on this, he he het t het het i t het i t = + = + +− + − − − ∑ ∑1 0 1 1    (9) nr nr nrt t nrt nrt i t nrt i t = + = + +− + − − − ∑ ∑1 0 1 1    (10) finally, positive and negative shocks of each variable can be d e f i n e d c u m u l a t i v e l y : het het i t + + − = ∑ 1 , het het i t − − − = ∑ 1 , nrt nrt i t + + − = ∑ 1 and nrt nrt i t − − − = ∑ 1 . here, it should be considered that each positive and negative shock has a permanent effect on the reference variable. the next step is to test the causality relationship between these variables. to obtain the causality relationship between positive and negative shocks, equation (2) and equation (3) are estimated for those variables and the konya panel causality test is employed. 4. empirical results the purpose of the study is to investigate the causality relationship between natural resource rents and health expenditures for the (gcc countries), consisting of the united arab emirates, bahrain, qatar, kuwait, saudi arabia and oman. the main reason for selecting the gcc countries as the sample of the study is that economies of those countries rely on oil, they are oil exporters and their oil rents have an important part in public revenues. oil rents are generally considered in the empirical literature to represent natural resources abundance. for example, hong (2017) used oil rents as a measure of natural resource abundance and he indicated that it is a suitable indicator to measure resource abundance of a country. we consider the oil rents to gdp ratio for the natural resource abundance in this study. in addition, the share of oil rents in gdp shows the real dimension in the economy. education and health variables are taken into consideration to measure the effects of natural resource abundance on human capital. because focus is given to education which is one of the elements of human capital, the ratio of public health expenditures in gdp is considered as an indicator of health. the reason for considering government health expenditures is that, as mentioned before, the ratio of government health expenditures in gcc countries in total health expenditures exceeds 70%. annual data for the period of 2000-2016 is used to investigate the causality relationship between the variables. all variables are obtained from the world bank world development indicators database. the beginning of the sample period is determined as 2000 because the data on government health expenditures for the selected countries could not be obtained before 2000. in this context, we have panel data consists of 6 countries and 17 year periods and total observation is 102. descriptive statistics for the variables are provided in table 1. according to the data in table 1, it is found out that the share of government health expenditures in gdp for gcc countries does not exceed 5% and that average health expenditures are determined between 1.7% and 2.9%. when considered in terms of both average health expenditures and maximum health expenditures, it is seen that the country which allocates the biggest share of health expenditures in gdp is saudi arabia, and the country with the least share is qatar. when the ratio of oil rents in gdp is considered, it is seen that this ratio is quite high for the countries except for bahrain and that the ratio of oil rents in gdp for kuwait has increased to 61%. at the same time, while the average share of oil rents in gdp for kuwait has been measured as 48%, this ratio for bahrain is determined to be 2.5%. the statistics in table 1 clearly shows erdoğan, et al.: healthcare expenditures channel of natural resource curse: the case of gulf cooperation council countries international journal of energy economics and policy | vol 10 • issue 2 • 2020 291 that all the countries except bahrain are rich in natural resources in terms of their oil rents. in order to determine whether there is cross-sectional dependence across the members of panel, three different tests (lm, cd and lmadj) have been applied and the results are provided in table 2. the results in table 2 suggest that the null hypothesis of no crosssectional dependence can be rejected at 1% significance level according to the three tests and it has been concluded that there is cross-sectional dependence. this result is consistent with the theoretical expectations because oil rents are determined based on the global oil prices and changes in global oil prices affect the oil rents of the countries in the same direction and at the same time. this leads to find cross-sectional dependence across the members of panel. the presence of cross-sectional dependence shows that instead of the ls method, using the sur method is more appropriate for model estimations. table 2 also provides slope coefficient homogeneity test results. according to both test results, the null hypothesis of slope coefficient homogeneity has been rejected at 1% significance level. this result indicates that the slope coefficients vary across the members of panel. therefore, it can be said that the use of panel var or panel vector error correction models, which assume countries are homogenous regarding their slope coefficients, can produce biased results when conducting panel causality test. the presence of both crosssectional dependence and heterogeneity among the members of panel shows that it will be more suitable to use the konya panel causality test. the results of panel causality test from oil rents to health expenditures for gcc countries are provided in table 3. when conducting the causality test, optimal lags length have been determined according to the akaike information criterion and in order to obtain critical values bootstrap method with 1000 time repetitions are used. according to the results provided in table 3, the null hypothesis of oil rents are not a granger cause of health expenditures and cannot be rejected for all the countries except for bahrain. on the other hand, we determine the presence of causal link running from the oil rents to health expenditure at 5% significance level for bahrain. these results indicate that there is not a relationship between natural resource rents and health expenditures for gcc countries except for bahrain. this result partially confirms the validity of the resource curse hypothesis and it states that natural resource rents have no effect on health expenditures. on the other hand, a significant relationship has been found between natural resource rents and health expenditures for bahrain. especially when compared to the other countries in the sample, bahrain’s having the lowest oil rent makes this result more remarkable. in this context, relatively low level of natural resource rents in bahrain and the presence of significant causality relationship between natural resource rents and health expenditures indicate that the resource curse hypothesis is not valid for bahrain. it is well known that the natural resource curse hypothesis puts forward that there is an inverse relationship between natural resource rents and human development indicators. according to this, a decrease in health expenditures is expected as oil rents increase, and in this case the causality relationship between the variables should be asymmetric rather than symmetric. therefore, in order to investigate whether the resource curse hypothesis is valid for gcc countries, it is also necessary to apply asymmetric causality test. within this framework, first, positive shock series have been calculated for oil rents and negative shock series have been computed for health expenditures. then, we examine the existence of granger causality from increases in oil rents to decreases in heath expenditures and the results are provided in table 4. according to the results in table 4, the null hypothesis stating that “an increase in oil rents is not a granger cause of a decrease in health expenditures” is only rejected for the united arab emirates. this result shows that the resource curse hypothesis table 1: descriptive statistics health expenditures/gdp (%) bahrain kuwait oman qatar saudi arabia uae mean 2.503 2.420 2.490 1.749 2.908 2.082 median 2.462 2.256 2.430 1.546 2.788 1.913 maximum 3.228 3.377 3.850 2.648 4.107 2.984 minimum 2.111 1.512 1.586 1.177 1.889 1.319 std. dev. 0.326 0.591 0.620 0.510 0.585 0.574 skewness 0.671 0.293 1.053 0.626 0.543 0.030 kurtosis 2.548 1.940 3.491 2.004 2.741 1.407 oil rents/gdp (%) mean 3.597 48.268 36.646 28.700 40.598 21.132 median 3.651 49.205 37.768 30.797 42.525 21.689 maximum 5.047 61.231 46.199 38.880 54.260 28.790 minimum 1.811 31.640 18.157 11.732 19.434 10.828 std. dev. 0.861 9.357 7.707 7.449 9.710 5.432 skewness −0.221 −0.272 −1.102 −0.928 −0.683 −0.310 kurtosis 2.458 1.807 3.678 3.407 2.736 2.049 table 2: cross sectional dependence and homogeneity test results lm 55.66 [0.000] cd 5.067 [0.000] lmadj 15.78 [0.000] ∆̃ 5.266 [0.000] ∆̃adj 5.768 [0.000] the values in brackets are p-values erdoğan, et al.: healthcare expenditures channel of natural resource curse: the case of gulf cooperation council countries international journal of energy economics and policy | vol 10 • issue 2 • 2020292 is valid and that there is an inverse relationship between oil rents and health expenditures in the united arab emirates. 5. conclusion and policy implications the natural curse hypothesis that indicates inverse relationship between natural resources rents and human development indicators has been widely examined in the literature. in this study, we focus on gcc countries and analyzed the presence of the relationship between oil rents and health expenditure by means of panel causality test suggested by kónya (2006). empirical results showed the lack of causality relationship between oil rents and health expenditures for all gcc countries except for bahrain. the lack of causality relationship between the two variables means that the variables are not related and oil rents have no effect on health expenditures. this result shows that the resource curse hypothesis is partially valid. in order to determine the validity of the resource curse hypothesis for gcc countries, the asymmetric causality test has also been carried out. in this context, whether there is a relationship between an increase in oil rents and a decrease in health expenditures is investigated. as a result of the asymmetric panel causality test, the null hypothesis can be rejected only for the united arab emirates. this result confirms the validity of the natural resource curse hypothesis in the united arab emirates. in other words, it can be said that an increase in oil rents in the united arab emirates decreases health expenditures. bahrain is the only country among gcc countries which is not rich in natural resources. the studies in the literature find evidence in favor of the relationship between oil rents and health expenditure for the countries having low oil rents and these findings are consistent with our results for bahrain. the lack of causality relationship among the variables for gcc countries shows that the natural resource curse hypothesis is partially valid as the rejection of the hypothesis requires the presence of causality relationship running from natural resources to health expenditure. it is remarkable to see that an increase in oil rents in the united arab emirates decreases health expenditures, that is, the natural resource curse hypothesis is valid for this country. because the most notable improvement tendencies in terms of diversification in production while reducing the oil dependence of the economy in gcc countries are seen in the uab. despite this partial difference, when compared to the other countries within the same group, the united arab emirates is not only a powerful country regarding its oil reserves but also its oil rents are substantially high. therefore, it is not surprising to obtain findings that support the natural resource hypothesis. despite the concrete developments towards changing the production strategy, it is seen that policy makers do not allocate enough amount of source regarding health, which is one of the basic components of human capital. to the best our knowledge, there is no study in the literature that investigates the relationship between health expenditures and natural resource rents by using a panel causality test. the studies in the literature generally analyze the relationship between the two variables using panel regression models and focuses on the simultaneous relationship between the variables. also, a causality analysis focuses on a dynamic relationship rather than a simultaneous relationship between the variables. therefore, it is not possible to directly compare the results of this study to the results of those in the literature. different results were obtained in the studies in which the relationship between natural resource rents and health expenditures was investigated. for example, nikzadian et al. (2019) found a result similar to the one we determine for bahrain in our study. nikzadian et al. (2019) found a positive relationship between oil rents and health expenditures for the opec countries. as in hong (2017), cockx and francken (2017) and kim and lin (2017), we find evidence in favor of natural resource curse hypothesis in the uae. abdel-latif et al. (2018) did not find a significant result between oil prices and health expenditures. hamdi and sbia (2013) did not find a causality relationship from public revenues (a big part of the public revenues for those countries consists of natural resource rents.) to public expenditures for gcc countries. table 3: causality relationship between oil rents and health expenditures country test statistics %1 critical value %5 critical value %10 critical value bahrain 12.498** 15.321 9.200 6.695 kuwait 1.428 18.476 9.426 6.499 oman 0.136 16.883 8.827 6.364 qatar 1.743 16.079 11.005 7.651 saudi arabia 1.008 20.904 11.389 7.676 uae 3.501 19.959 8.763 5.800 **causality relationship at a significance level of 5% table 4: causality relationship from positive oil rents to negative health expenditures country test statistics %1 critical value %5 critical value %10 critical value bahrain 2.045 47.396 26.790 18.743 kuwait 0.029 48.542 25.511 17.745 oman 0.561 35.884 21.303 15.181 qatar 2.325 40.032 22.375 16.755 saudi arabia 1.062 39.614 23.068 15.751 uae 21.253** 28.359 19.937 13.826 **causality relationship at a significance level of 5% erdoğan, et al.: healthcare expenditures channel of natural resource curse: the case of gulf cooperation council countries international journal of energy economics and policy | vol 10 • issue 2 • 2020 293 to sum up, the empirical results for the causality relationship between oil rents and health expenditures do not mean that health expenditures in gcc countries are inadequate. this study did not investigate the level of the health expenditures in gcc countries. it investigated whether an increase in oil rents had a positive effect on health expenditures and no relationship was found between oil rents and health expenditures in most of the countries included in the analysis. the fact that “an increase in oil rents has no effect on health expenditures” means that the expectation of improvement tendencies in health increase production by increasing labor productivity is not so strong. when the production structures of the gcc countries are considered, the most important problem is that the economies of these countries mostly rely on oil. fluctuations in oil prices and particularly retreatment of prices cause negative effects on rents, and this has a negative effect on both growth performance and budget balances. labor productivity is one of the main factors that determine the success of the diversification of production strategy. increasing labor efficiency is possible. however, increasing labor efficiency come true with more sources allocation to health reforms and recovery policies, after an effective cost analysis. it may be also a wise policy to investigate the successful countries’ experiences before stating the health reforms. references abdel-latif, h., osman, r.a., ahmed, h. (2018), asymmetric impacts of oil price shocks on government expenditures: evidence from saudi arabia. cogent economics and finance, 6, 1-14. alkhamis, a., hassan, a., cosgrove, p. (2014), financing healthcare in gulf cooperation council countries: afocus on saudi arabia. international journal of health planning and management, 29, 64-82. anshasy, a., el, a.m., katsaiti, s. (2015), are natural resources bad for health? health and place, 32, 29-42. auty, r.m. (1994), industrial policy reform in six large newly industrializing countries: the resource curse thesis. world devolepment, 22(1), 11-26. breitung, j. (2005), a parametric approach to the estimation of cointegration vectors in panel data. econometric reviews, 24, 151-173. breusch, t., pagan, a. (1980), the lm test and its application to model specification in econometrics. review of economic studies, 47, 239-254. chang, w.y., wei, d. (2019), natural resources and infectious diseases: the case of malaria, 2000-2014. the social science journal, 56(3), 324-336. cockx, l., francken, n. (2014), extending the concept of the resource curse: natural resources and public spending on health. ecological economics, 108, 136-149. cockx, l., francken, n. (2015), natural resource wealth and public social spending in the middle east and north africa. iob institute of development policy and management, university of antwerb working paper. cotet, a.m., tsui, k.k. (2013), oil, growth, and health: what does the cross-country evidence really show? scandinavian journal of economics, 115(4), 1107-1137. daniele, v. (2011), natural resources and the “quality” of economic development. the journal of development studies, 47(4), 545-573. gearhart, r., michieka, n. (2019), natural resource abundance and healthcare efficiency in appalachia: a robust conditional approach. energy policy, 129, 985-996. granger, c.w.j. (2003), some aspects of causal relationships. journal of econometrics, 112, 69-71. hamdi, h., sbia, r. (2013), re-examining government revenues, government spending and economic growth in gcc countries. journal of applied business research, 29(3), 737-742. hatemi, j.a. (2012), asymmetric causality tests with an application. empirical economics, 43, 447-456. hong, j.y. (2017), does oil hinder social spending? evidence from dictatorships, 1972-2008. studies in comparative international development, 52, 457-482. hong, j.y. (2018), how natural resources affect authoritarian leaders’ provision of public services: evidence from china. the journal of politics, 80(1), 178-194. kónya, l. (2006), exports and growth: granger causality analysis on oecd countries with a panel data approach. economic modelling, 23(6), 978-992. madreimov, t., li, l. (2019), natural‐resource dependence and life expectancy: a nonlinear relationship. sustainable development, 27(4), 681-691. moore, m. (2001), political underdevelopment: what causes “bad governance”. public management review, 3(3), 385-418. moore, m. (2004), revenues, state formation, and the quality of governance in developing countries. international political science review, 25(3), 297-319. nikzadian, a., agheli, l., arani, a.a., sadeghi, h. (2019), the effects of resource rent, human capital and government effectiveness on government health expenditure in organization of the petroleum exporting countries. international journal of energy economics and policy, 9(2), 381-389. pesaran, m.h. (2004), general diagnostic tests for cross section dependence in panels. cambridge working papers in economics, no. 0435, faculty of economics. cambridge: university of cambridge. pesaran, m.h. (2006), estimation and inference in large heterogeneous panels with multifactor error structure. econometrica, 74, 967-1012. pesaran, m.h., ullah, a., yamagata, t. (2008), a bias-adjusted lm test of error cross-section independence. the econometrics journal, 11, 105-127. pesaran, m.h., yamagata, t. (2008), testing slope homogeneity in large panels. journal of econometrics, 142, 50-93. raheem, i.d., isah, k.o., adedeji, a.a. (2018), inclusive growth, human capital development and natural resource rent in ssa. econ change restruct, 51, 29-48. sachs, j.d., warner, a.m. (1995), natural resource abundance and economic growth. nber working papers, no. 5398. sachs, j.d., warner, a.m. (1997), sources of slow growth in african economies. journal of african economies, 6(3), 335-376. selim, h., zaki, c. (2014), the instıtutıonal curse of natural resources in the arab world. the economic research forum working paper, no. 890. swamy, p.a.v. (1970), efficient inference in a random coefficient regression model. econometrica, 38, 311-323. wigley, s. (2017), the resource curse and child mortality, 1961-2011. social science and medicine, 176, 142-148. zellner, a. (1962), an efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. journal of the american statistical association, 57, 348-368. zhan, j.v., duan, h., zeng, m. (2015), resource dependence and human capital ınvestment in china. the china quarterly, 221, 49-72. zhuang, y., zhang, g. (2016), natural resources, rent dependence, and public goods provision in china: evidence from shanxi’s countylevel governments. the journal of chinese sociology, 3(20), 1-22. . international journal of energy economics and policy | vol 8 • issue 5 • 2018 259 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(5), 259-266. smart cities in future energy system architecture elnur t. mekhdiev1*, victoria v. prokhorova2, svetlana v. makar3, gafur g. salikhov4, alexandr v. bondarenko5 1moscow state institute of international relations (university) of the ministry of foreign affairs of the russian federation (mgimo university), moscow, russia, 2kuban state technological university, krasnodar, russia, 3financial university under the government of the russian federation, moscow, russia, 4bashkir state university, ufa, russia, 5ufa state petroleum technological university, ufa, russia. *email: e.mehdiev@gmail.com abstract the article analyzes new technologies, which establish modern trends for future electric power systems operation and development, and their impact on production, storage, transmission, distribution and consumption of electricity. the article also studies trends and approaches to urban planning with an emphasis on energy infrastructure, where success in “smart city” and “smart grid” concepts implementation is considered as overarching question. the general requirements for smart power supply system are defined, problems that need to be solved are formulated, and a number of general recommendations are given for future development. keywords: energy system, smart grid, smart cities jel classifications: l94, q42, q48, h54 1. introduction in many countries, energy sector enterprises are undergoing a period of reformation. the ongoing processes of mergers, acquisitions and changes in management structure, the boundaries of the sphere of activity and the territorial presence make many former monopolies look for new models of value creation. inevitably, the targets of the companies and their business processes change, and so do the markets for public services provision, as new market mechanisms are being introduced, requiring for technological changes that meet the current development needs of the industry. although all these changes differ depending on the location and type of activity of a certain energy company, innovations inevitably lead to transformation of the entire sphere of public services (tadviser, 2018). regularities and common factors of changing conditions for development and functioning of electric power systems (eps) lead to significant transformations in their structure, as well as modes of their operation. these transformations are caused by a number of objective factors that shape the future eps architecture, namely: • increase of eps scale, expansion of territories they serve, and regional cooperation that leads to formation of interregional and interstate energy associations; • development of large cities’ agglomerations, conditioned by the formation of state and economic management centers, and concentration of high-tech industries, financial resources, creative groups, scientific and educational cluster; • trend for de-urbanization of urban settlements, including the removal of industrial production off cities’ limits, and development of individual low-rise construction. all this will lead to an ever-widening dispersal of electricity consumption throughout the territory, parallel to profound electrification of industry and everyday life to ensure growth of quality of life and labor productivity (voropai and stennikov, 2013). societal development in high-developed states with established social institutions is currently being considered as an overarching target to ensure well-being. moreover, the latter is tested against not only aggregate income, but also against metrics that encapsulate social issues and reflect on the quality of life in general. against mekhdiev et al.: smart cities in future energy system architecture international journal of energy economics and policy | vol 8 • issue 5 • 2018260 the background of rapid technological development and social advancement, groundwork for practical implementation of actions, leading to improvement of the population quality of life, is laid. social and technological development pillars are closely interlinked and have a composite impact on socio-technical systems. eps might be considered as an illustrative example. interconnected relations among social and technical components of eps are primarily reflected in electrical power supply management (centralized or decentralized), modes of cooperation for innovative projects’ (either systemic or non-systemic) delivery, etc. the increased attention of modern society to the interests and needs of the individual, contributes to the formation of customer-oriented power supply systems with an emphasis on the quality of service to end-users. in general, the task of improving the quality of life in the context of intensive urbanization is formulated primarily applicable to large cities and big urban centers. the experience of managing territorial development at the national and regional levels, as well as planning the harmonious development of urban agglomerations, is gaining momentum globally (zhang et al., 2006). the development of urban environment is an alternating stage in the growth of problems and post-crisis transformation. at the same time, modern experience shows that the successful development of cities, including their development as centers of regional importance, is directly related to the existence of a program of interaction between actors, and the use of a distributed type of management. 2. literature review the themes of the city’s intelligent energy systems, active-adaptive networks, digitalization of power systems and substations are increasingly being raised for discussion on thematic venues, forums and meetings at various levels. since the beginning of the xxi century, territorial development is being associated with the concept of “smart city.” this concept represents the development of a “quality of life approach” in accordance with the criterion of sustainable development, which links the current needs of society with the limitations on the ability to meet them both at the present time and in the future (styczynski et al., 2011). the concept of sustainable development includes socio-economic and technological development, as well as environmental protection. a distinctive feature of the smart city is the widespread use of information and communication technologies (muromtsev, 2017). currently there are numerous definitions that seek to describe smart grids (sg), with the most relevant compiled and presented below (united nations, 2015): 1. international energy agency: “a smart grid is an electricity network that uses digital and other advanced technologies to monitor and manage the transport of electricity from all generation sources to meet the varying electricity demands of end-users. smart grids co-ordinate the needs and capabilities of all generators, grid operators, end-users and electricity market stakeholders to operate all parts of the system as efficiently as possible, minimising costs and environmental impacts while maximising system reliability, resilience and stability.” 2. european commission (ec): “smart grids are energy networks that can automatically monitor energy flows and adjust to changes in energy supply and demand accordingly. when coupled with smart metering systems, smart grids reach consumers and suppliers by providing information on realtime consumption. with smart meters, consumers can adapt – in time and volume – their energy usage to different energy prices throughout the day, saving money on their energy bills by consuming more energy in lower price periods. smart grids can also help to better integrate renewable energy. while the sun doesn’t shine all the time and the wind doesn’t always blow, combining information on energy demand with weather forecasts can allow grid operators to better plan the integration of renewable energy into the grid and balance their networks. smart grids also open up the possibility for consumers who produce their own energy to respond to prices and sell excess to the grid.” 3. united states office of electricity delivery and energy reliability (usa oe): “smart grid generally refers to a class of technology that people are using to bring utility electricity delivery systems into the 21st century, using computerbased remote control and automation. these systems are made possible by two-way communication technology and computer processing that has been used for decades in other industries. they are beginning to be used on electricity networks, from the power plants and wind farms all the way to the consumers of electricity in homes and businesses. they offer many benefits to utilities and consumers mostly seen in big improvements in energy efficiency on the electricity grid and in the energy users’ homes and offices.” 4. international electrotechnical commission (iec): “the general understanding is that the smart grid is the concept of modernizing the electric grid. the smart grid comprises everything related to the electric system in between any point of generation and any point of consumption. through the addition of smart grid technologies the grid becomes more flexible, interactive and is able to provide real time feedback. a smart grid is an electricity network that can intelligently integrate the actions of all users connected to it – generators, consumers and those that do both – in order to efficiently deliver sustainable, economic and secure electricity supplies. a smart grid employs innovative products and services together with intelligent monitoring, control, communication, and self-healing technologies to: facilitate the connection and operation of generators of all sizes and technologies; allow consumers to play a part in optimizing the operation of the system; provide consumers with greater information and choice of supply; significantly reduce the environmental impact of the whole electricity supply system; deliver enhanced levels of reliability and security of supply.” 5. japan smart community alliance (jsca): “in the context of smart communities, smart grids promote the greater use of renewable and unused energy and local generation of heat energy for local consumption contribute to the improvement of mekhdiev et al.: smart cities in future energy system architecture international journal of energy economics and policy | vol 8 • issue 5 • 2018 261 energy self-sufficiency rates and reduction of co2 emissions. smart grids provide stable power supply and optimize overall grid operations from power generation to the end user.” definitions can also reflect national or regional electricity system development needs. for example, in china initial emphasis was placed on the “strong smart grid,” reflecting technology development and infrastructure needs in transmission networks. in may 2009, the state grid corporation of china officially launched the study and construction of the “strong smart grid” system, to be completed by 2020, noting that this has not precluded efforts by china in distribution technologies. the years 2011–2015 mark the construction stage, when rollout of ultra high voltage links will be accelerated and urban and rural distribution networks built out (ieee, 2011). despite the absence of a single terminology, there are generally several main areas in the formation of a “smart city”: smart economy, smart environment, smart management, smart habitat, smart communication, and smart people (allee and tschudi, 2012). these are summarized in table 1. with an integrated approach, a growing number of life-supporting spheres fall into the field of attention of civil planners: energy supply and utilities, transport and logistics, real estate and construction, business and finance, health and education, public safety, waste utilization, etc. particular attention is paid to the organization of smart urban management in general, which establishes a large closed-loop cycle – from the production of necessary forms of energy, products and services to ensuring social and environmental sustainability. the european pioneer in the field of smart cities is amsterdam (netherlands), which started implementation of relevant programs in 2009. at present, more than 40 different projects are being implemented in the city aimed at social and economic development of the city, increasing energy efficiency and reducing the burden on the environment thus decreasing ecological stress. after amsterdam, other cities followed, including malaga (spain), evora (portugal), madrid (spain), freiburg (germany), etc., (patterson, 2012). an indispensable component of smart city projects is the energy supply sector, which is being intensively transformed primarily due to the implementation of large-scale governmental programs to support the introduction of distributed generation based on wind and solar energy, as well as smart metering systems for consumers. a number of long-term mega-projects in the european union and the united states – green emotion, ecogrid, pacific northwest smart grid, houston’s smart grid, etc., – are of the nature of research projects and test sites, where new approaches to the organization of energy supply are being developed. currently, in the ranking of smart cities in europe, according to a study by bearing point, the leading are vienna (austria), amsterdam (netherlands) and barcelona (spain). at the same time, vienna has been leading the list of the best cities for quality of life for several years. the smart city project there includes such areas as development of renewable energy resources (including those derived from garbage processing) and increased use of “clean energy,” energy efficient traffic lighting system, electric public transport and charging stations, open access to data, insurance services, etc.in the united states, projects are known in the cities of new york, san francisco, boston, seattle, etc. in asia, projects can be identified in yokogama (japan), dubai and masdar (oea), new sondo (korea), and in india, where the “100 smart cities” program is launched, and china, where about 200 pilot projects of smart cities are in the implementation phase. an example of successful international cooperation (particularly, in terms of smart cities development) might also be the covenant of mayors, which is aimed at (including, but not limited to) fulfilling the indicators of sustainable energy development. all smart city projects are implemented in close interaction of a wide range of participants and stakeholders, including: table 1: key elements for “smart city” formation element what is entailed in the term smart economy (competitiveness) path-breaking, innovative spirit entrepreneurism and commercial endeavor trade marks productivity and effectiveness labor market flexibility engagement in international processes capacity for transformational change smart environment (natural resources) force of natural conditions attraction environmental protection sustainable resources management smart management (partnerships) involvement in decision-making public and social services transparent governmental actions and administrative procedures political strategies, road maps and long-range plans smart habitat (quality of life) quality of housing services social cohesion educational facilities and services public health services personal security cultural facilities tourist attraction smart communication (transport and communications) environmentally sound, innovative and safe transportation systems information and communication technologies infrastructure availability, accessibility and affordability at local, national and international levels smart people (human capital) skill and expertise level commitment to continuous learning social and ethnic diversity flexibility creativity ex-territoriality (cosmopolitism) community involvement source: adapted from (voropai and stennikov, 2013; allee and tschudi, 2012) mekhdiev et al.: smart cities in future energy system architecture international journal of energy economics and policy | vol 8 • issue 5 • 2018262 representatives of the authorities of all levels, business, energy companies, power equipment manufacturers, telecommunications sector companies, scientific organizations, universities and academic institutions, developers and city residents. this underlines the interest of different communities in achieving common goals, as well as the need to combine their efforts to solve a set of interrelated tasks, including territorial planning, development of the urban management model, carrying out scientific research, development, deployment and mastering of new technologies, training and building capacity of specialists and wider community, etc. 3. analysis of eps development trends in order to understand what is the intelligent energy systems of cities with an actively adaptive network, a broader look at the issue might be applies, posing a question: what are the intellectual systems of cities in general, without binding only to energy? to answer it, it is necessary to imagine a future, in which all these systems already exist. in this future, intelligent electric networks, intelligent heat networks, water and gas supply networks, intelligent ground and underground transportation, intelligent emergency services, intellectual services, even buildings, – are created and made operational. all these urban areas exchange relevant information with each other through a single city management system in real time. for example, a failure in the work of the subway automatically affects the scheme and intervals of ground transportation, and the disconnection of the power line leads to an automatic change in the scheme of power supply of the district. from the same city management system, the city government and the population receive topical information, the first – to improve management efficiency, the latter – for timely information and services. in general, the work of such a system leads to the existence of a self-regulating city network, in the life of which both the government and residents participate in real time. receiving feedback from the public makes it possible to make timely adjustments to the algorithms of self-regulating systems, thus continuously increasing the efficiency of city services. the electrical network of such a city is also actively adaptive, that is, it can change and adapt to the processes taking place in it, in order to maintain uninterrupted power supply in optimal modes. mutually supplementing participants of this network are sources of generation (both traditional and renewable), backbone and city electric networks with their substations, as well as consumers, both with their own generation sources, capable of delivering excess power to the network, and without them. for the automatic operation of such a network, in addition to a city control center that introduces control commands at the global level, local (node) control centers are necessary, on which the day-to-day operation of individual network segments depends. active-adaptive electric network – sg – is a self-regulating power supply system of the city. it provides analysis of energy consumption of individual consumers and groups; accumulation of energy with excess output and output to the network in case of power shortage, automatic reconfiguration of the power supply network in case of emergency situations; automatic reconfiguration of protection and automation devices depending on regimes, informing adjacent systems of current events in the network. the power supply decentralization trend is developing in the electricity production due to the expanse of distributed generation sources connected to the nodes of the distribution grid. this tendency is due to the emergence of new high-performance electricity generation technologies, which are able to customize eps to the uncertainty of electricity demand. renewables also contribute to distributed generation system. new high-efficiency technologies are increasingly being used for large-scale power sources. the future eps generation structure should comprise relatively large generating sources for the supply of electricity to large electric consumers and a sufficiently high share of distributed electricity generation. the expanse of distributed electricity units in eps induces certain peculiarities. many small generating units based on gas turbine technology operate at a higher frequency than the industrial one and are connected to the system via reversible converter units. similar connection is provided by wind turbines, which differ in the stochastic nature of the generated power. as a result, the frequency characteristics of the generation in the eps are significantly changed, the regulatory effect of the generation in frequency is reduced. distributed generation units have smaller rotor inertia and simplified control system, comparing to traditional units, what creates problems with eps stability. connection of distributed generation units to the distribution grid radically changes its properties, creating problems of stability, forming the need for significant development and fundamental reconstruction of relay protection and automation systems at this level. electricity network will change due to the drift in power generation and consumption. considering new technologies in converter units based on power electronics, cost reduction, reliability improvement and high controllability of dc power transmission, these technologies will significantly develop in the transmission network. at the same time, the widespread use of devices that form flexible ac power transmission (facts), will radically increase the controllability of the ac transmission network. new technologies, including the use of facts units, will significantly increase the reliability and controllability of distribution grid. the power consumption growth and the dispersion of generating sources and consumers on the territory will lead to the increase in the transmission density and distribution networks. considering these factors, future eps will increasingly assume properties of infrastructure systems (a kind of “electric internet”). theoretically, this may provide consumer with the proper quality electricity in certain place at the acceptable price. mekhdiev et al.: smart cities in future energy system architecture international journal of energy economics and policy | vol 8 • issue 5 • 2018 263 another factor is the emergence of active consumers, who will independently manage their power consumption depending on the price conditions in the retail electricity market by transferring electricity consumption by some power receivers from periods with a high price of electricity to periods with a low price. this independent management of line load creates problems for the management of the eps modes due to the uncertainty of power consumption of active consumers. therefore, the interaction between the eps and consumers on the joint management of the system modes using the regulatory capabilities of consumers is promising. a significant change in the properties of future eps will occur as a result of the mass expanse of electric energy storage systems, whose technologies are already in industrial use (zhang et al., 2006). electric energy storage systems are characterized by the presence of high-performance control systems, which may contribute to the flexibility of eps. a large share of electric energy storage is expected to be on the basis of electric vehicles, which will significantly change the layout and modes of operation of future power plants. these new characteristics of consumers, drives and generation of future power plants will significantly change the properties and flexibility of systems. in the concept of a smart city, energy supply system retains an important infrastructural role in urban economy and is characterized by a new level of development, for which the term sg is used. the smart power supply system of the city unites three main systems: electricity, heat and gas supply. at the same time, the unified energy supply system can be represented in the form of integrated energy units, including sources and consumers of different types of energy, and complex energy links that ensure the transfer of different types of energy resources. such a complex presentation is primarily due to the desire to optimize the use of energy in smart city as a whole. secondly, it is necessary to take into account of the interrelatedness of the operating modes of the systems, which is manifested, for example, in the available capacity of thermal power plants, the reliability of natural gas supplies, partial interchangeability of electricity, heat and gas during heating, etc. thirdly, places and routes for energy infrastructure in the city are limited, which requires a comprehensive approach to the design and operation of power facilities, including their placement in a single corridor. at the smart city facilities’ level, an integrated approach to energy supply(for example, of large buildings), allows to obtain an additional effect when taking into account constructive and technological solutions in construction aimed at energy saving and energy efficiency. should the electric transport infrastructure and the power supply system be considered jointly, it is possible to ensure optimum charging of the load in the overall load schedule of the power system with a mutual benefit for consumers and the power system. the urgency of this task increases with the development of fast charge and discharge technology. each sub-system, being an element of the integrated energy supply system, forms a branched hierarchical structure, starting from local energy supply systems of individual consumers to high-level backbone networks. first of all, the energy infrastructure is most developed at the level of distribution and consumption of energy due to a number of factors: the growth of distributed generation and its integration, including energy storage, at the grassroots level of hierarchy into the public network, deep automation of interface connections of consumers with power system, implementation of local power systems technologies, when the distributed sources of generation on the consumers’ side can work sustainably and ensure the quality and balanced power supply during power outages, and secure capability to adapt to reverse energy flows of the distribution network, etc. at the same time, in the structure of the power system, the consumption sector boundary is diluted due to the large-scale development and integration of different power sources in consumers’ energy in residential, industrial and business sectors. local power systems, such as microgrid and multimicrogrid, capable both of synchronous operation in the composition of the power grid, and autonomous operation, form fractal structures in the power system, increasing its resistance to disturbances and facilitating recovery from accidents (wei and kundur, 2012). the unifying role in the management system of the energy infrastructure of smart city is carried out by information and communication technologies, which ensure the exchange of information and control signals both inside the systems and between them. at the same time, a significant increase in the volume of information requires the use of new principles of information processing and decision-making in management systems. a qualitative change in the automatic control of a complex system is the transition to distributed control with the possibility of maximum processing of information and decisionmaking on the ground, based on the multiagency principles. the new task is to organize the management of local power systems, which ensures their stable operation as part of a large eps and, if necessary, reliably allocates for isolated work with the balancing of own consumption and energy sources to ensure life support of critically important consumers. distributed management of the sg is built on a hierarchical basis and includes several levels of energy management systems (ems): a system for the housing development cluster of the city (home ems); business and social activity – large business centers, entertainment buildings and the hotel sector (building ems); industrial plants and technology parks (factory ems); etc. general management of different types of clusters, including the electric vehicle (ev) charging infrastructure, is carried out in the territorial ems (community ems) with information support from supervisory control and data acquisition (scada) system regarding the collection of data from metering devices and consumer participation in demand management. such a management system for a smart city’s power system is being developed, for example, within the framework of a major yokohama smart city project in japan. 4. discussion in general, the distinctive features of smart energy supply system are: efficient use of energy, reliable operation and adaptability to changing mekhdiev et al.: smart cities in future energy system architecture international journal of energy economics and policy | vol 8 • issue 5 • 2018264 conditions, which includes the possibility of flexible participation of market actors, including consumers, in regime and emergency control in accordance with their individual characteristics. among the basic requirements for the smart power supply system, it is necessary to distinguish the following (voropai, stennikov, 2013): • optimal choice of the composition of generating sources, including distributed generation, and energy management that approaches the real-time mode; • integration of diverse sources of electricity, including renewable and low-power sources, and energy storage into the energy system; • automatic assessment of the risks of violations, detection and elimination of the consequences of violations in the operation of the power system at all hierarchical levels; • two-way communication with consumers via intelligent metering systems and power management; • resistance to the impact of security threats (physical, informational and resource); • computer-aided design of the power system, including power facilities, and the information and communication system in conjunction with the cities’ infrastructure; • optimal use of the equipment life, and timely (including preventive, based on risk-management) maintenance of assets. which objects do participate in an active-adaptive energy network? which – among them – exist in traditional networks, and are they ready (in their existing form) to work as part of an actively adaptive network? all participants of the active-adaptive network may be divided into three groups, according to their degree of presence in traditional networks and the level of readiness for work in the active-adaptive network (litvinenko and glebov, 2017). 1. the first group is traditional generation, intersystem and backbone networks. the participants of this group are an integral part of current electric network and have a high degree of readiness to work in the active-adaptive network. at the facilities of this group, such systems as emergency response and technological automation, telemechanics and scada, relay protection and automation have been operating for a long time already and actively. 2. the second group is consumers without sources of generation, and urban networks that feed these consumers, and here it is possible to include the nodal control centers. this group also exists in today’s networks, but its elements are not fully or partially ready for work in the active-adaptive network. this is due to the fact that city electric networks have always been built on the basis of simple and inexpensive equipment. on the low side of the city substations, protection, as a rule, was built on fuses, so it is impossible to talk about remote control and automatic change of some parameters of the operation of city networks in the existing form. therefore, only by equipping the city substations with intelligent devices is not limited here requires a comprehensive reconstruction with the replacement of basic electrical equipment for supporting remote and automatic control. almost the same situation on the side of end-users: the maximum that is now transmitted to the power supply organization in an automated form is the indication of commercial accounting data. therefore, today, consumers have no opportunity to influence the operation of the supply network, depending on the processes that occur in the consumers themselves. 3. renewable generation, consumers that include sources of mini and microgeneration, as well as the city management center, are the third group of participants in the actively adaptive network, which is practically non-existent today. solar and wind power plants being built in russia today are not equipped with energy storage systems, so they are unable to accumulate energy during peak hours and give it out to the grid in the event of a failure, and consumers with small solar panels or “windmills” do not have a legal the ability to produce surplus production in the network. these aspects do not allow the construction of decentralized active-adaptive power supply systems operating on the basis of energy block technology, a system that manages several trade agreements between consumers that buy surplus electricity generated directly from the original producer without additional costs and trade margins that operatively change the cost of this electricity in dependence from the needs and volumes of surplus. thus, the cornerstone in this group of participants in the actively adaptive network is the storage of electrical energy, or rather their absence as part of renewable generation. the implementation of national strategies for the development of sg technologies and smart metering in various countries of the world pursues a number of key goals. for energy companies, these pursued objectives include: • reduction of energy losses; • increase of timeliness and completeness of payment for consumed energy resources; • control of the unevenness of the electrical load schedule; • increasing the efficiency of asset management of energy companies; • improving the quality of integration of renewable generation facilities and distributed generation into the power system; • increasing the reliability of the functioning of the power system in the event of emergency situations; · increase visualization of the operation of energy infrastructure facilities. the key objectives of energy resources consumers are: • improving consumers’ access to energy infrastructure; • increase of reliability of power supply of all categories of consumers; • improving the quality of energy resources; • creation of a modern interface between energy consumers and their suppliers; • opportunity for the consumer to act as a full participant in the energy market; • expanded opportunities for consumers to manage energy consumption and reduce payments for consumed energy. governments and regulators of the energy industry – through development of sg technologies – are striving to achieve the following: mekhdiev et al.: smart cities in future energy system architecture international journal of energy economics and policy | vol 8 • issue 5 • 2018 265 • increase in the level of satisfaction of energy consumers with the quality and cost of energy supply; • ensuring the sustainable economic situation of enterprises in the energy sector; • ensuring the modernization of the fixed assets of the energy industry without a significant increase in tariffs. the transition to smart power supply systems in the cities is associated with the gradual transformation of the existing infrastructure in the course of implementing complex projects aimed to create a new urban environment in a certain territory, including the reconstruction of industrial areas – gentrification. at the same time, the goal of introducing new technologies requires solving the issues of organizational interaction, financing, regulatory support, etc. implementation of, and delivery on, smart city projects requires a wide involvement of energy companies, equipment manufacturers, residents, large consumers under the auspices of city authorities under a single project management system. in addition, in the field of information support, it is necessary to develop and implement a wide range of educational and training programs in the field of energy efficiency and environmental protection, as well as programs on integrated smart city project management using alife-cycle approach. from a technical point of view, and taking into account the mentioned tendencies of increasing distribution of electric receivers and electric energy storage systems feeding on direct current through converter elements, a transition to the formation of direct current feed distribution networks at the location of common converter installations from alternating current to constant at feed substations might be expected. moreover, these new load characteristics of consumers, storage devices and generation within the future eps will significantly change the properties and controllability of systems. the existing principles of regime control in traditional eps are based on the use of the regulating effect of the load and the frequency characteristics. due to these effects, modern epss have internal self-sustainability, and control systems affect the regime parameters only subject to their violation of certain limits. in connection with the change in the properties of future eps, a large transformation regarding their internal self-sustainability might be expected, resulting in a fact that the traditional principles of eps regimes’ management would require significant modification and further development. practically all the countries have introduces state policies that support technological development of electric power industry and future eps, in which the concept of creating intellectual power systems – sgs – is widely declared. this concept is based on the integration of several innovative directions in all segments from production to consumption of electricity, namely: • innovative technologies and installations for the production, storage, transmission, distribution and consumption of electricity; • highly effective means and technologies for measuring, collecting, processing, storing, transmitting and presenting (visualizing) information; • progressive information and computer technologies; • highly effective methods of monitoring and management based on modern approaches and practices of management theory; • active consumers. 5. conclusion the development of future eps on the technological basis of the intelligent power system will largely neutralize the listed and discussed potentially negative trends in the changing properties of eps. at the same time, new problems arise (and they would only grow in scope in the future) due to the need to strengthen the coordination of eps regimes’ management of at various levels, in order to improve management efficiency, and to ensure the reliability of the very management system. moreover, in terms of monitoring and managing eps, the issues related to ensuring information and cyber security acquire special urgency. nevertheless, the security of such networks in the energy sector remains. we must understand that the simpler the system, the more reliable it is. therefore, the addition of new elements all new sensors, all new devices for monitoring does not make it more reliable. nevertheless, in general, the energy system with the advent of iot technologies becomes more reliable precisely because the effect is achieved due to greater control, the use of additional controls and other methods. but it is worth noting that the security of the internet of things (iot) is a serious and urgent issue, which has not yet been fully explored. all mentioned above requires serious in-depth research into the properties of future epss, the development of principles and methods for their formation, taking into account changing conditions, the management of their regimes in normal and emergency situations, as well as dispatching and automatic control systems for future eps modes. in the context of the development of the iot, talk about a variety of devices that can send collected data via the internet. on hearing examples of household devices, for example, for “smart home.” however, there is another large segment of the application of iot technologies energy. gathering the parameters of energy networks can help increase the reliability of all their elements, optimize the load on the infrastructure. as a result, due to sensor networks and data processing from them both operational costs and repair costs (due to remote monitoring systems, self-diagnosis systems) will be reduced. in the description of iot applications in power engineering, one can often hear the phrase “intelligent networks.” this is a small speculation with the term “intellectual,” but in this case it is justified. in general, intellectual can be called only what has intellectual behavior. levels of intelligence, of course, are different. but there are basic things: the ability to reason, goalsetting, the ability to adapt to changing conditions and so on. in the electric power industry, rather, it is not about intelligence as such, but about the ability of networks to automatically inform about their state, that is, the amount of energy consumed, its distribution, emergency or emergency situations, and so on. in other words, the mekhdiev et al.: smart cities in future energy system architecture international journal of energy economics and policy | vol 8 • issue 5 • 2018266 network performs part of the work that the maintenance staff used to do before. basically it concerns data collection. this system has several levels. generator level “digitized” can be all the parameters of the generating capacity, including fuel reserves, the need for planned repairs and maintenance, load, and so on. this allows you to switch the power in time, better to plan maintenance and repairs, which, undoubtedly, reduces costs, and also facilitates control over unauthorized connection and theft. the second level is the architecture of the network itself, which becomes more decentralized. such a wireless network works in the same way as, for example, conventional computers or mobile devices are combined into a network. in addition, there is a technology for transferring data directly through power cables, but this may require replacing the equipment with power lines, which is not always easy to do. at the level of opportunities for consumers of energy, new services are emerging. most of them are related to the fact that consumers have the opportunity to monitor the consumption of electricity in real time and with maximum detail, up to a specific device. if we talk about large consumers, such as enterprises or business centers, then they can track dishonest tenants. for example, you can identify those who sort out with electricity, connect more powerful devices than allowed. it is also possible to more accurately determine peak loads. and end users will be able to plan for a more even use of energy, avoiding the simultaneous inclusion of several powerful devices, and automatically switch equipment to work at cheaper rates at night. flexibility of power systems and consumption accounting, which allows to come to large data analytics, allow the inclusion of a large number of distributed sources of energy generation into the network. therefore, the penetration of iot into the energy sector will also spur the development of small-scale power and the connection of alternative energy sources. for example, several small energy producers (say, substations collecting energy from windmills) will be able to unite in a virtual station and offer energy to households. operational management of infrastructure is crucial. energy companies are faced with the need to introduce new standards of operation and maintenance to continuously improve the balance between reliability of power supply and costs. another key task in the energy sector is the maintenance and repair of equipment. this is due to the huge number of pieces of equipment distributed over large areas and requiring regular maintenance and repair. consolidation of information about the state of equipment in a unified management system with the ability to provide it quickly to various consumers on the ground can reduce downtime for repairs, reduce costs for spare parts and materials, optimize logistics and staff utilization. consumers are also no less important driving force for the changes that are taking place. there has been a tendency to shift from a process-oriented approach to a client-oriented approach. increased requirements of consumers to the level of services inevitably lead to an expansion of the range of services provided by energy companies, the introduction of new financial and payment mechanisms. references allee, g., tschudi, w. (2012), edisonredux: 380 v dc brings reliability and efficiency to sustainable data centers. ieee power and energy magazine, 10(6), 50-59. ieee: the expertise to make smart grid a reality. (2011), the institute of electrical and electronics engineers. available from: http://www. smartgrid.ieee.org/july-2011/99-chinas-approach-to-the-smart-grid. litvinenko, a., glebov, i. (2017), intellectual energy systems of cities with an actively-adaptive network (smart grid): the present and the future. energy and industry of russia. available from: https:// www.eprussia.ru/epr/339/3180950.htm. muromtsev, d. (2017), intelligent power networks. postnauka. available from: https://www.postnauka.ru/faq/80119. patterson, b.t. (2012), dc, come home: dc microgrids and the birth of the enernet. ieee power and energy magazine, 10(6), 60-69. styczynski, z.a., adamek, f., voropai, n.i. (2011), electric energy storage systems. paris: cigre. tadviser (2018). intelligent power supply networks. available from: http://www.tadviser.ru/a/102530. united nations. (2015), overview of activities and players in smart grids. draft 19 may 2015. new york and geneva: united nations publications. available from: http://www.unece.org/fileadmin/dam/ energy/se/pdfs/geee/news/smart_grids_overview_05-19-15.pdf. voropai, n.i., stennikov, v.a. (2013), russia’s energy strategy: a changing perspective on the development of the electric power industry. energy strategy, 2, 66-70. wei, y., kundur, d. (2012), two-tier hierarchical cyber-physical security analysis framework for smart grid. san diego, usa: ieee pes general meeting. p22-27. zhang, x.p., rehtanz, c.h., pal, b. (2006), flexible ac transmission systems: modelling and control. berlin-heidelberg: springerverlag. . international journal of energy economics and policy | vol 10 • issue 2 • 202048 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(2), 48-56. an empirical analysis of factors affecting renewable energy consumption in association of southeast asian nations-4 countries vikniswari vija kumaran1, abdul rahim ridzuan2*, farman ullah khan3, hussin abdullah4, zam zuriyati mohamad1 1universiti tunku abdul rahman, petaling jaya, malaysia, 2faculty of business and management, universiti teknologi mara, kampus alor gajah, km 26 jalan lendu, 78000 alor gajah, melaka, malaysia, 3national university of modern languages, islamabad, pakistan, malaysia, 4universiti utara malaysia, changlun, malaysia. *email: rahim670@staf.uitm.edu.my received: 17 may 2019 accepted: 01 december 2019 doi: https://doi.org/10.32479/ijeep.8142 abstract this study aimed to explore the determinants of renewable energy consumption in selected association of southeast asian nations (asean) countries by emphasizing the significant role played by the quality of governance. this paper is classified according to the coverage of three dimensions approach (economic, environment, and governance) for sustainability. this study employed panel data analysis to examine the relationship between gdp, co2 emissions, foreign direct investment, trade openness, urbanization, and quality of governance on renewable energy consumption in selected asean countries from 1990 to 2016. the results revealed that urbanisation has a significant positive impact on renewable energy based on fmols and dols analyses while the quality of governance has a significant positive impact on renewable energy based on pooled mean group analysis in the long run. however, gdp and trade openness have a significant negative impact on renewal energy. the elasticity analysis in the short run revealed that none of the factors applied in this study affected renewable energy consumption. hence, several policies are recommended as an excellent approach to meet the energy demand of private investors and future generations. keywords: renewable energy, association of southeast asian nations, quality of governance, panel estimation jel classifications: f64, q42, p28 1. introduction the consumption of renewable energy such as solar, biomass, wind, hydroelectricity, and many others has been emphasis to meet the global warming challenge. global warming is widely recognised as a serious threat to the future well-being of humanity. despite the aim for higher use of renewable energy, the decreasing trend of renewable energy consumption by four-original members of association of southeast asian nations (asean) countries namely indonesia, malaysia, philippines, and thailand might disrupt the association’s agenda to use cleaner energy to prevent environmental pollution. thus, the asean has set an ambitious target of securing 23% of its primary energy from the renewable sources by 2025 due to the high energy demand in the region which is expected to grow by 50%. this target is very important in reducing the environmental pollution such as higher release of carbon emissions that can lead to global warming. based on world bank (2017), malaysia has the lowest renewable energy consumption among indonesia, philippines, and thailand. in addition, figure 1, shows the trend of consumption for renewable energy as per centage of gdp for asean-4 countries. according to the latest data for the renewable energy in world bank (2017), the renewable energy consumption for 2016 in indonesia is 33.29% of gdp, followed by 24.19% of gdp in the philippines, this journal is licensed under a creative commons attribution 4.0 international license kumaran, et al.: an empirical analysis of factors affecting renewable energy consumption in association of southeast asian nations-4 countries international journal of energy economics and policy | vol 10 • issue 2 • 2020 49 and 19.97% of gdp in thailand. it is known that malaysia has the lowest renewable energy consumption among the four selected countries, which is 2.70% of gdp. this trend indicated that the asean-4 countries still depending heavily on non-renewable sources energy which generated from coal and fossil fuel to generate energy. one of the reasons of heavy reliance on nonrenewable energy is because of cheaper costs as compared to renewable energy. therefore, these four countries were selected in this study among the ten countries in southeast asia, which is known as asean-4 countries. renewable energy is the unlimited energy in which the supplies can continually be renewed through natural processes such as solar energy, wind energy, hydroelectric energy, biomass, and biogas (shukla et al., 2017). renewable energy consumption becomes an important source of alternative energies and reduces energy costs (omri et al., 2015). there are several examples of government policies implemented by the selected four asean countries to improve renewable energy. for example, indonesia implemented the national energy policy to increase their renewable energy to 31% in 2030. malaysia has targeted that their renewable energy consumption to reach 2080 megawatt by 2020, which can contribute 7.8% of total installed capacity in national renewable energy policy, action plan 2011, and 11th malaysia plan 2016-2020. the action plans in the three policies show the efforts in malaysia to improve renewable energy consumption. next, the philippines targeted to increase their renewable energy to 15.3 gigawatt in 2030 and some additional target before 2030 in national renewable energy program roadmap 2010-2030. the final example is thailand, which targeted 30% of renewable energy consumption in thailand’s total energy consumption by 2036 in the form of 20.11% of electricity, 36.67% of heat production, and 25.04% of biofuels in the transportation sector (irena, 2018). overall, it is believed that the policies that develop renewable energy will motivate renewable energy consumption. however, the increase in energy shortage, climate change, and global warming in southeast asia has encouraged some of the countries’ government to implement policies to increase the use of renewable energy consumption. among the profound macroeconomic indicators that could possibly influence the level of renewable energy consumption in asean-4 group are economic growth (gdp), urban population (upop) and level of governance (gov). the indicators are choosen based on their current issue. for instance, the great recession from 2008 to 2009 shows the negative effect on economic growth (gdp) of a country. according to murphy (2018), it is expected that technical recession will occur in early 2020. thus, it has a negative impact on renewable energy consumption in the uk due to the poor economy implications (brock, 2010). this has been supported by anbumozhi and banuer (2010) who conducted research in southeast asia. the economic slowdown has reduced the demand for energy which led to the reduction of renewable energy consumption. this action makes them rely on traditional source of energy highly. for example, the great recession in 2008 to 2009 has huge implications for malaysia and the philippines. before the recession, the gdp growth in malaysia in 2007 was 9.43%, and it is reduced sharply to 3.31% and −2.53% during the recession from 2008 to 2009. the renewable energy consumption dropped from 4.73% to 4.23% in 2009 and continued decreasing to 3.82% in 2010 (world bank, 2017). next, the impressive growth rate of urban cities has caused several challenges for environmental sustainability in the philippines. world bank (2017) mentioned that although the philippines is one of the fastest urbanising countries in asean, poor urban management and inadequate investments in urban facilities are the major issues faced by the philippines. poor living condition in urban areas can result in lower income level, poor sanitation, and inefficiency of city development that can lead to deteriorating the consumption of renewable energy. therefore, it is important to investigate whether the urban development process in asean is one of the main engines for renewable energy consumption based on the prospects of sustainable development goals (sdg). the other potential indicator that might influence the level of renewable energy consumption in asean-4 countries is level of governance. the public authorities in these countries lack transparency, and the anti-corruption authorities fail to reach their full potential as they lack the potential and operational independence with limited capacities (transparency international, 2015). according to transparency international (2015), one of the risks of corruption is several government projects especially renewable energy project will provide the opportunity for certain party to use the funds for illegal purposes. besides that, there are a lot of projects without financial viability from the bank and government support (koh, 2017) that can cause the projects to be obstructed by corruption. it is encouraged to promote the adoption of renewable energy for sustainable use in the future. the combination of macroeconomic and environmental variables is to establish potential variables that can influence the consumption of renewable energy. therefore, this study aimed to examine the factors affecting renewable energy consumption in the original member of asean countries consists of malaysia, indonesia, philippines and thailand (asean-4) as most macroeconomic variables are visible in these countries. it also intended to investigate the effects of quality of governance as the crucial factor in affecting renewable energy consumption. the rest of this paper has been structured as follows. section 2 discusses past empirical analyses of demand for renewable energy. section 3 describes the methodologies for model development and the sources of data. the empirical findings are presented in section 4. finally, section 5 emphasized the conclusions and policy implications drawn from the results of the study. figure 1: the trend of renewable energy consumption as % of gdp for asean-4 countries 0 10 20 30 40 50 60 70 1 9 9 0 1 9 9 1 1 9 9 2 1 9 9 3 1 9 9 4 1 9 9 5 1 9 9 6 1 9 9 7 1 9 9 8 1 9 9 9 2 0 0 0 2 0 0 1 2 0 0 2 2 0 0 3 2 0 0 4 2 0 0 5 2 0 0 6 2 0 0 7 2 0 0 8 2 0 0 9 2 0 1 0 2 0 1 1 2 0 1 2 2 0 1 3 2 0 1 4 2 0 1 5 2 0 1 6 indonesia malaysia the philippines thailand year source: world development indicator, 2018 kumaran, et al.: an empirical analysis of factors affecting renewable energy consumption in association of southeast asian nations-4 countries international journal of energy economics and policy | vol 10 • issue 2 • 202050 2. literature review currently, renewable energy plays an important role as more policymakers are encouraging people to use renewable energy rather than non-renewable energy. according to alper and oguz (2016), the most important features of renewable energy sources are reducing co2 emissions, assisting to protect the environment, reducing dependence on foreign sources for domestic sources of energy, and contributing to the increase in employment. other than that, there is also a strong relationship between economic growth and renewable energy consumption. according to danish et al. (2017), energy plays a significant role to boost the economy of any country and the developed nations switch from conventional energy consumption to renewable energy sources to tackle the future consequences of energy. according to chen (2018), the changes in gdp have a significant and positive impact on renewable energy consumption. zhao and luo (2016) suggested that renewable energy consumption is improving along with the increase in gdp per capita for a long term using the ardl model and error correction model. disposable income can be used to develop green technology that can help to increase renewable energy consumption (omri and nguyen, 2014). on the other hand, akar (2016) found that gdp has a negatively significant impact on renewable energy consumption from 1998 to 2011 in balkan countries using ips panel unit root test and system-gmm estimation. cadoret and padovano (2016) stated that gdp has a negative impact on renewable energy consumption. it is believed that the countries have reached the target of renewable energy sources. thus, the market force is insufficient, and it is hard to stimulate the investment and consumption of renewable energy. according to omri and nguyen (2014), the relationship between gdp and renewable energy consumption is insignificant in low-income countries and global countries because gdp is not important for renewable energy consumption. omri and nguyen (2014) investigated the determinants of renewable energy consumption for 64 countries from 1990 to 2011. it was found that trade openness has a statistically significant impact on renewable energy consumption in other income groups except for high-income level. higher trade openness with a positive impact on technology transfers can help the countries to adopt modern renewable energy technologies. besides that, trade openness has a significant impact on renewable energy consumption by increasing domestic production and economic activities. in a study by akar (2016) that applied dynamic panel data method, trade openness has a positive effect on renewable energy consumption in the balkans from 1998 to 2011. meanwhile, chen (2018) found that import and export trade are important factors that will affect energy consumption in china. exports can lead to more renewable energy production because the increase in export volume will stimulate renewable energy consumption. subsequently, it will promote more production and transportation of energy and renewable energy to foreign countries. previous studies concentrated more on the monetary impacts of foreign direct investment (fdi) and the environmental effects of fdi. doytch and narayan (2016) examined the environmental effects of fdi inflows. doytch and narayan (2016) affirmed that fdi is an essential driver of the expansion in sustainable power source utilisation for the upper-middle-income countries (umics), whereas the impact on lower centre salary nations (lmics) is lower for the impacts of sectoral fdi. lee (2013), on the other hand, stated there is no evidence for the statistically significant relationship between total net fdi inflow and increased renewable energy consumption. recently, there are several studies that explored the relationship between urbanisation and renewable energy consumption. according to chen (2018), changes in urbanisation have a significant and positive impact on renewable energy consumption, especially for regions with a high level of urbanisation population. he used a dynamic system-gmm panel model from 1996 to 2013 in 30 selected provinces of china. meanwhile, kammen and sunter (2016) stated that the use of renewable energy in urban areas will be challenging and it is expected that the increase of urbanisation will continue in the next 30 years. the installation of renewable energy generation facilities in urban areas is challenging due to limited available land. renewable energy is less likely to be consumed with the insufficient supply of renewable energy. a study by salim and shafiei (2014) used a stirpat model for investigating the impacts of urbanisation on renewable and non-renewable energy consumption in oecd countries from 1980 to 2011. the study revealed that urbanisation has a positive effect on non-renewable energy consumption, but it did not generate obvious effects on renewable energy consumption. other than that, past studies revealed that there was a relationship between co2 emissions and renewable energy consumption (bhattacharya et al., 2016; al-mulali et al., 2015; dogan and ozturk, 2017; sharif et al., 2019). omri and nguyen (2014) conducted studies in 64 countries from 1990 to 2011 using systemgmm estimator. it was found that co2 emissions have significant positive effects on renewable energy consumption in high-income countries. based on the study, renewable energy consumption has a significant negative impact on co2 emissions in both long run and short run dynamics in pakistan (danish et al., 2017). according to cadoret and padovano (2016), corruption is the measurement of quality of governance by reducing the government’s responsiveness towards the policies and the income level is raised to protect the policies. cadoret and padovano (2016) revealed that the quality of governance is positive and there is a significant relationship for renewable energy consumption at 26 european countries from 2004 to 2011. when the quality of governance in a country is higher, the consumption of renewable energy will be higher. according to ghimire and kim (2018), corruption is the barrier to renewable energy development. the corruption activities will misuse the public fund and delay the public fund release process. 3. methodology the econometric model that were constructed based on the objective of this research paper can be seen as follows: re f gdp fdi to upop co gov= ( , , , , , )2 (1) where • ret represents renewable energy consumption, • gdpt represents economic growth, kumaran, et al.: an empirical analysis of factors affecting renewable energy consumption in association of southeast asian nations-4 countries international journal of energy economics and policy | vol 10 • issue 2 • 2020 51 • fdit represents foreign direct investment inflows, • tot represents trade openness, • upopt represents urban population, • co2 represents carbon emersions, • gov represents quality of governance. gdp is expected to have a positive sign with re in asean-4 group. with rapid growth, the asean-4 group will seek for cleaner energy by promoting the use of renewable energy such as solar and wind energy. fdi is expected to have a positive sign given that most of the foreign investors that poured in their investment into asean-4 group are come from developed countries such as japan and south korea that have owned and advanced in cleaner technology. to is also expected to have a positive sign where cleaner products are imported from the country’s trading partners. higher co2 might lead towards the higher demand of renewable energy in asean-4 group. the governments of asean-4 group would take a preventive measurement by using more renewable energy when there is a rising issues of global warming due to high concentration of carbon emission release from the country. lastly, gov which is measure by corruption perception index is expected to have a mix sign. the positive sign indicated that higher governance (lower corruption) lead to higher consumption of re, while negative sign indicated that lower governance (higher corruption) lead to a lower consumption of re. all of the variables were transformed into log-linear forms (ln). this transformation was to convert the results into short-run and long-run elasticities and to reduce the sharpness of the time series data so that there was a consistent and reliable estimation (shahbaz and rahman, 2010). the new transformation of the model in log form is as follows: lnre lngdp lnfdi lnto lnupop lnco it it it it it i = + + + + + a b b b b b 0 1 2 3 4 5 2 tt it itlngov+ +b e6 (2) 3.1. statistical techniques and tools the study will decide the exact model on the basis of data nature according to the previous studies. the data of this study will be analysed using statistical techniques such as descriptive statistics, correlation, fmols, and dols models. the study will conduct pedroni tests and philips pearson tests for co-integration, whereas stationarity will be checked via panel unit test (ips), fisheradf, and fisher-pp panel unit root tests whether the variables are classified as i(1). if all the variables are stationary on the first difference, the study will proceed with panel cointegration tests. 3.1.1. unit root test stationary is checked through panel unit test (ips), fisher-adf and fisher-pp panel unit root tests whether the variables are classified as l(1). if all the variables are stationary on the first difference, the study will proceed with panel cointegration tests. 3.1.2. panel cointegration tests when two non-stationary series are separated as individual non-stationary, their linear combination can be stationary. “economically speaking, two variables will be cointegrated if they have a long-term or equilibrium relationship between them” (gujarati, 2003). after presenting the methodology, the study will proceed with the analysis using panel unit root tests, which is the usual way of starting cointegration analysis to identify whether the series is stationary or non-stationary. a non-stationary series is not a mean-reverting series in which a shock (innovation) in the series does not die away. it is formulated as “non-stationary series has long memory” (harris and sollis, 2005). the linear combinations of non-stationary series might lead to the estimation of spurious regressions in which the estimated coefficients can be biased (gujarati, 2003). in this regard, the identification of the existence of non-stationarity (unit root) and its order is important in two respects: • first, it is important to know the order of unit root in the series to conduct panel cointegration tests. panel cointegration tests can only be conducted among series which have the same order of integration. • second, the order of unit root in the series is also important to get rid of spurious regression risk when the existence of panel cointegration is not verified. for this case, the results of unit root test are useful in converting the series into stationary form by taking the first or second differences. otherwise, the use of non-stationary series which is not cointegrated will lead to the estimation of biased coefficients. in order to examine the long run relationship, this study conducted three tests to explore the long run relationship called padroni test, kao test, and fisher test. h0: no cointegration h1: cointegration exists. if the above tests indicate that there is a cointegration among the variables, this study will apply panel fmols model. 3.1.3. panel full modified ols, panel dynamic ols, and panel mean group after finding the existence of long run relations among the panel series, there is the need to estimate the size and sign of these relations. in other words, cointegration analysis has only verified the existence of long run relations among the variables of eight models. the quantitative values are needed to make interpretations and comparisons. in panel estimation literature, panel ols (fixed effect estimator) and dynamic ols methods are in the class of parametric approaches, whereas fully modified (fm) ols is a nonparametric approach. in the panel unit root and cointegration tests, there is no consensus among scholars on which estimation method performs better in estimating less biased and more robust coefficients. for example, kao and chiang (2000) found that fmols may be more biased than dols (harris and sollis, 2005). banerjee (1999) claimed that fmols or dols are asymptotically equivalent for more than 60 observations. to overcome this shortcoming, panel fully modified ordinary least squares (fmols) and panel dynamic ordinary least squares (dols) methods developed by pedroni (2000; 2001) will be used in this study. fmols and dols estimators were developed after deviated results were seen in the estimation of series that have long term relationship via least squares method. fmols method corrects the autocorrelation and endogeneity problem using a non-parametric approach, whereas autocorrelation is eliminated in kumaran, et al.: an empirical analysis of factors affecting renewable energy consumption in association of southeast asian nations-4 countries international journal of energy economics and policy | vol 10 • issue 2 • 202052 dols method and the estimation is made by taking the variables with their lag values. pooled mean group (pmg) is also known as panel ardl, which is the combination of pooling and averaging the coefficients, whereas mg estimator is based on estimating n time-series regressions and averaging the coefficients (pesaran et al., 1999). pmg estimation derives the long run parameter for average long run parameter from ardl model for individual country (pesaran et al., 1999). for example, ardl is as follows: a ei it i it iyit itk y b k x c( ) ( )= + + (3) for country i, for i = 1,…, n, long run parameter is as follows: ei i i b c = ( ) ( ) 1 1 (4) and mg estimator for the overall panel is as follows: e e= = å1 1n i i n (5) mg estimation with high sequence of lag will have a consistent estimator for long run average parameter. mg estimation allows both slope and intercept to be different among the countries. for fixed-effect method, the slope is fixed, and the intercept is allowed to be different among the countries. in pmg estimation, the long run coefficient is fixed to be the same for all countries, whereas short run coefficient is allowed to be different. in other words, pmg estimator yields efficient and consistent estimates when homogeneity restriction is true. when n is rather small, pmg estimator is less sensitive to outlier’s problem as well as simultaneously correct the serial autocorrelation problem and the problem of endogenous regressors by choosing appropriate lag structure for both dependent and independent variables. this study will apply pmg that requires appropriate lag selection. the lag is selected by schwarz information criterion (sic). the lag length can be determined by taking maximum lags and choosing the model where the value of sic is minimum. it is relevant to use pmg estimation to capture the short run elasticities outcomes for the model which are not found in panel fmols and panel dols. this study used eviews 9.5 to conduct empirical analysis. the basic ardl with lag order of p, q, r, s, w, y, z, equation system for the period of time t = 1, 2,…, 26 and country i = 1, 2,…, 4 for dependent variable y is as follows: d d d d lnre lnre lngdpit i ij i t j j p ij j q i t j ij j = + ¶ + += = -å åa j j 0 1 0 , ' , ' == = = å å å + + + 0 0 0 r i t j ij j s i t j ij j w t i lnfdi lnto lnupop , ' , ' ' j j j d d iij i t j j y ij j z i t j it lnco lngov d d 2 0 0 , ' , = = å å+ +j e (6) pmg allows the long run coefficient to be equal over the crosssection that is 𝛼𝑖′= 𝛼′ for all i; thus, the specific model for pmg is given as below: dlnre lnre lngdp lnfdi lnto it i i i t i t i t i = + -a q a a a 0 1 1 1( , ' , ' , ' ,, ' , ' , ' , ,) t i t i t i t ij i t lnupop lnco lngov lnre + + ¶ 1 1 2 1 1 a a a d -= = = å å å+ + + j j p ij j q i t j ij j r i t jlngdp lnfdi 1 1 0 1 0 1 j j j ' , ' ,d d '' , ' ' , ij j s i t j ij j w t i ij i t lnto lnupop lnco = = å å+ + 0 1 0 1 2 d d d j j jj j y ij j z i t j itlngov = = -å å+ + 0 1 0 1 j e' ,d (7) this study has used annual data ranging from 1990 up to 2016 (27 years) as a sample period. a summary of the data and its sources is displayed in table 1. 4. analysis and discussion table 2 shows the panel unit root tests that consist of five different tests suggested by levin et al. (2002), breitung (2000), im et al. (2003), maddala and wu (1999), and hadri (1999). the panel unit root tests are tested both at level and at first difference to detect the trend of stationarity more clearly. the outcomes provide crucial information to the researcher in selecting suitable long run estimation. the outcomes of the first four-unit root tests show mix stationarity of the tested variables at level and at first difference. for example, levin et al. (2002) found that lnre, lnfdi, lnupop, and lnco2 are the most significant at 1% level and these variables seem to be stationary at first difference except lnupop. a more powerful unit root test namely hadri test (1999) was performed and the mix stationarity is detected for the variables. thus, it can be concluded that panel ardl analysis is suitable to derive its short run and long run elasticities besides panel fmols and dols. however, there is the need to confirm the existence of long run cointegration for the estimate model using pedroni and kao panel cointegration test which is disclosed in table 3 to reach the level of this analysis. the pedroni residual cointegration test consists of seven tests which are divided into two groups: within dimension and between table 1: sources of data variable description source re re (% total final energy consumption) wdi gdp gdp per capita (constant, 2010) wdi fdi foreign direct investment, net inflows (% of gdp) wdi to trade (% of gdp) wdi upop urban population growth (annual %) wdi co2 carbon emissions (metric tonnes per capita) wdi gov corruption perception index icrg wdi stands for world development indicators (2018) and icrg stands for international country risk guide (2017) kumaran, et al.: an empirical analysis of factors affecting renewable energy consumption in association of southeast asian nations-4 countries international journal of energy economics and policy | vol 10 • issue 2 • 2020 53 dimensions. the analysis is repeated for the following three different cases: (i) individual intercept; (ii) individual intercept and trend; and (iii) no intercept and no trend. among these three tests, this study refers to the first category as it is the only case that generates the outcomes of kao residual cointegration test. this study displayed all outcomes in the same table to increase the robustness of the analysis. the outcomes confirmed the existence of long run cointegration relationship for the variables in the model in which 6 out of 12 tests cover both statistic and weighted statistic are significant either at 10%, 5%, or 1% level. furthermore, some of the tests are significant for the second and third cases. this evidence allowed us to proceed in testifying the long run elasticities that focused on examining the relationship of each independent variable on the dependent variable. table 2: panel unit root test method test level first difference individual intercept individual intercept and trend individual intercept individual intercept and trend null: panel data has unit root (assumes common unit root process) levin et al. (2002) t*-statistics 1. lnre −1.825 (5)** −0.741 (1) −1.826 (0)** 0.399 (4) 2. lngdp 1.821 (0) −0.265 (5) −5.828 (1)*** −4.034 (5)*** 3. lnfdi −3.182 (1)*** −2.380 (1)*** −7.184 (5)*** 1.093 (5) 4. lnto −0.371 (0) −1.795 (3)** −9.097 (0)*** −4.648 (5)*** 5. lnupop −2.499 (1)*** −3.462 (2)*** −1.174 (1) 0.955 (0) 6. lnco2 −3.519 (0)*** −1.134 (5) −7.040 (4)*** −5.621 (5)*** 7. lngov −1.194 (0) 0.114 (1) −8.597 (0)*** −7.071 (2)*** breitung (2000) t*-statistics 1. lnre 1.468 (1) 1.604 (4) 2. lngdp 1.449 (5) −3.465 (5)*** 3. lnfdi −2.734 (1)*** −1.282 (5)* 4. lnto 2.339 (3) −3.948 (0)*** 5. lnupop 1.697 (2) 0.606 (0) 6. lnco2 −0.990 (5) −1.737 (5)*** 7. lngov −1.065 (1) −3.082 (2)*** null: panel data has unit root (assumes individual unit root process) im et al. (2003) w-statistic 1. lnre −0.898 (5) −0.895 (1) −4.831 (1)*** −4.088 (4)*** 2. lngdp 3.701 (0) −1.860 (5) −4.670 (4)*** −3.531 (5)*** 3. lnfdi −3.811 (1)*** −2.704 (1)*** −7.906 (5)*** −3.932 (5)*** 4. lnto 0.229 (0) 0.875 (3) −8004 (0)*** −4.979 (5)*** 5. lnupop 0.665 (1) −1.393 (2)* −1.043(1) 1.010 (0) 6. lnco2 −1.760 (0)** −3.586 (5)*** −6.871 (4)*** −6.212 (5)*** 7. lngov −1.276 (0) −0.051 (1) −8.285 (0)*** −7.048 (2)*** maddala and wu (1999) and choi (2001) adf-fisher chi-square 1. lnre 11.116 (5) 9.689 (1) 36.994 (0)*** 29.793 (4)*** 2. lngdp 2.810 (0) 17.322 (5) 35.276 (1)*** 25.603 (5)*** 3. lnfdi 29.133 (1)*** 20.828 (1)*** 64.680 (5)*** 29.599 (5)*** 4. lnto 6.837 (0) 5.768 (3) 63.146 (0)*** 36.845 (5)*** 5. lnupop 7.331 (1) 12.828 (2) 13.673 (1)* 10.142 (0) 6. lnco2 14.437 (0)* 26.239 (5)*** 55.489 (4)*** 46.408 (5)*** 7. lngov 14.106 (0)* 9.412 (1) 65.755 (0)*** 51.702 (2)*** pp-fisher chi-square 1. lnre 6.730 (5) 7.681 (1) 33.695 (0)*** 22.101 (4)*** 2. lngdp 2.927 (0) 7.583 (5) 37.625 (1)*** 34.891 (5)*** 3. lnfdi 28.108 (1)*** 20.174 (1)*** 102.341 (5)*** 335.038 (5)*** 4. lnto 7.638 (0) 4.565 (3) 67.403 (0)*** 122.853 (5)*** 5. lnupop 33.049 (1)*** 6.807 (2) 13.123 (1) 10.702 (0) 6. lnco2 13.771 (0)* 14.984 (5)* 71.940 (4)*** 61.191 (5)*** 7. lngov 14.187 (0)* 8.043 (1) 67.111 (0)*** 52.849 (2)*** null: panel data has no unit root (assumes individual unit root process) hadri (1999) 1. lnre 7.388*** 4.655*** −0.273 1.901** 2. lngdp 8.089*** 3.198*** 0.677 1.045 3. lnfdi 0.546 2.566*** −0.623 1.959** 4. lnto 3.236*** 5.958*** 3.755*** 6.848*** 5. lnupop 7.776*** 3.146*** 1.970** 3.175*** 6. lnco2 7.642*** 2.084** 1.073 2.565*** 7. lngov 2.210** 1.802** 0.066 2.663*** *,**,*** indicate significant at 10%, 5% and 1% significance level respectively kumaran, et al.: an empirical analysis of factors affecting renewable energy consumption in association of southeast asian nations-4 countries international journal of energy economics and policy | vol 10 • issue 2 • 202054 table 4 shows the results of long run elasticities which were derived from fmols, dols, and pmg. it was proven in all three tests that economic growth of asean (lngdp) has a negative relationship with the consumption of renewable energy (lnre). higher economic growth experienced in these countries can lead towards the reduction of renewable energy consumption as the countries are still heavily depended on pollutive types of energy such as coal and fossil fuel. they are not ready to invest in alternative energy on a large scale. for instance, 1% increase in lngdp can reduce the country’s demand on renewable energy by 0.64% (fmols), 0.54% (dols), and 0.69% (pmg). next, the outcomes of trade openness (lnto) exhibit similar expected sign like lngdp where it has a negative relationship with renewable energy consumption (lnre) as proven by fmols and dols estimation. higher degree of openness to trade in selected asean countries can reduce the demand for renewable energy as the dependency on pollutive energy is high due to the huge demand by their local industries to generate productivity. technically, 1% increase in lnto reduces lnre by 0.31% (fmols) and 0.39% (dols). next, it is found that the increase in urban population (lnupop) for selected asean countries can lead to higher demand for renewable energy (lnre). technically, 1% increase in urban population increases the demand for renewable energy by 0.79% (fmols) and 0.90% (dols). urban area usually focuses on energy efficiency technology such as the use of solar panel for housing projects and also offices. lastly, governance, proxied by level of corruption perception has a positive relationship with renewable energy consumption for selected asean countries which is proven by pmg estimation. this result is a good sign for the nation as higher level of governance can help the country to be involved in more high-prolific projects without the fear of corruption issues as there are more transparent procedures in selecting the developers. this strategy can enhance the success rate of projects related to renewable energy. for instance, 1% increase in lngov can increase lnre by 0.22%. this study extends the analysis by running the short run elasticities as well as checking the speed of adjustment (ect) for selected asean countries as a group and individual. the analysis is performed using pmg method and table 5 shows the outcomes. in the short run, there is no single indicator in the model that can influence lnre for the selected asean countries. in indonesia, it is found that lngdp and lnco2 have a significant and negative relationship with lnre, while the rest of the variables are not significant except for lnupop that is significant and can positively influence lnre. for malaysia, lngdp, lnto, and lngov have a significant and negative relationship with lnre. for the philippines, lngdp, lnto, and lngov have a significant and negative relationship with lnre while lnfdi and lnco2 have a positive and significant relationship with lnre. for thailand, lnco2 has a negative and significant relationship with lnre while lnfdi, lnto, and lngov have a positive and significant relationship with lnre. from the outcomes of the four selected asean countries, the improvement in governance can increase the consumption of renewable energy for indonesia and thailand, as well as reducing the consumption of renewable energy for malaysia and the philippines. table 5 shows the estimated lagged ect in pmg regression for the four countries which are negative and statistically significant. based on the ect value, the highest speed of adjustment was obtained by malaysia (−0.63), followed by indonesia (−0.18), thailand (−0.14), and the philippines (−0.07). more than 63%, 18%, 14%, and 0.7% of the adjustments were completed within less than a year for all the selected asean countries. table 3: pedroni and kao panel cointegration method test deterministic trend specification individual intercept individual intercept and trend no intercept no trend statistic weighted statistic statistic weighted statistic statistic weighted statistic pedroni residual cointegration test within-dimension panel v-statistic 2.437*** 1.515* 1.565* 1.191 2.352*** 1.237 panel rho-statistic 0.770 1.064 1.341 1.658 −0.453 0.482 panel pp-statistic −0.868 −0.254 −0.749 −0.413 −1.837** −0.271 panel adf-statistic −2.039** −2.528*** −1.678** −2.892*** −2.002** −0.573 between-dimension group rho-statistic 1.793 2.352 1.119 group pp-statistic 0.033 −2.767** −0.284 group adf-statistic −3.210*** −3.157*** −1.883 kao residual cointegration test adf −4.013*** *,**,*** indicate significant at 10%, 5% and 1% significance level respectively table 4: results of long run elasticities regressor fmols dols pmg (1,1,1,1,1,1,1) lngdp −0.635*** −0.541* −0.687*** lnfdi 0.018 0.126 0.011 lnto −0.305*** −0.385** 0.162 lnupop 0.792*** 0.900*** 0.282 lnco2 −0.174 −0.263 0.104 lngov −0.001 0.033 0.217* r square 0.989 0.999 adjusted r square 0.988 0.995 *,*,*** indicate significant at 10%, 5% and 1% significance level respectively kumaran, et al.: an empirical analysis of factors affecting renewable energy consumption in association of southeast asian nations-4 countries international journal of energy economics and policy | vol 10 • issue 2 • 2020 55 5. conclusion and policy recommendation this study was conducted based on the factors affecting renewable energy. it examined the relationship between gdp, co2 emissions, fdi, trade openness, urbanisation, and the quality of governance on renewable energy consumption in the selected asean countries. the findings in the long run elasticities concluded that urbanisation has a significant positive impact on renewable energy based on fmols and dols analyses, whereas the quality of governance has a significant positive impact on renewable energy based on pmg analysis. the long run elasticities results revealed that gdp and trade openness have a significant negative impact on renewal energy, whereas fdi and the quality of governance are not significant on renewal energy. the outcomes for asean-4 groups in the short run elasticities analyses revealed that none of the factors affected renewable energy consumption. on the other hand, the individual asean-4 members showed mixed evidence for the short run elasticities. although there are various initiatives to develop the policies on renewable energy consumption, the implementation is still at an infant stage. many challenges especially in financing the renewable energy project still remain unresolved as it involves a huge amount of fund. a study by mat rahim and mohamad (2018) suggested green sukuk to finance renewable projects while lam and law (2018) suggested debt, equity, and grants. however, the return of this investment is questionable. the financier would need to monitor that their investment is used to finance the renewable project and not for other business operation purposes. therefore, there is the need to have a comprehensive policy on renewable energy project agreement. it was found that urbanisation has a significant impact on renewable energy consumption in the long run. according to worldometer (2018), the urban population in asean in 2018 is 49.25% and it is expected to increase to 63.7% in 2050. hence, it is recommended to include renewal energy policies in the development such as promoting smart cities, solar infrastructures, and water consumption. this policy is in line with one of the sdg which emphasized on the access to affordable, reliable, and modern energy. this study concludes that better quality of governance can increase renewable energy consumption. hence, leaders should be aware of the importance of renewable energy consumption. they will able to implement the policies when they are equipped with knowledge in this area. knowledgeable and experienced leaders can lead to quality governance in which they can manage the resources. this study can be used as a guide for the strategies to develop policies on renewable energy consumption especially on gdp and trade openness. both aspects can contribute to renewable energy consumption. 6. acknowledgements we would like to thank an anonymous referee for useful comments and suggestions. the usual disclaimer applies. we wish to extend our gratitude to inqka uitm shah alam for financing this publication. references akar, b.g. (2016), the determinants of renewable energy consumption: an empirical analysis for the balkans. european scientific journal, 12(11), 594-607. al-mulali, u., ozturk, i., lean, h.h. (2015), the influence of economic growth, urbanization, trade openness, financial development, and renewable energy on pollution in europe. natural hazards, 79(1), 621-644. alper, a, oguz, o. (2016), the role of renewable energy consumption in economic growth: evidence from asymmetric causality. renewable and sustainable energy reviews, 60, 953-959. anbumozhi, v., bauer, a. (2010), impact of global recession on sustainable development and poverty linkages. adbi working paper. tokyo: asian development bank institute. banerjee, a. (1999), panel data unit roots and cointegration: an overview. oxford bulletin of economics and statistics, 61, 607-629. bhattacharya, m., paramati, s.r., ozturk, i., bhattacharya, s. (2016), the effect of renewable energy consumption on economic growth: evidence from top 38 countries. applied energy, 162, 733-741. breitung, j. (2000), the local power of some unit root tests for panel data. advances in econometrics, 15, 161-177. brock, m. (2010), given the nature of the recent economic recession, has the uk government missed the opportunity to invest in renewable energy programmes? norwich economics papers. university of east anglia: schools of economics. cadoret, i., padovano, f. (2016), the political drivers of renewable energies policies. energy economics, 56, 261-269. chen, y. (2018), factors influencing renewable energy consumption in china: an empirical analysis based on provincial panel data. journal of cleaner production, 174, 605-625. danish, zhang, b., wang, b., wang, z. (2017), role of renewable energy and non-renewable energy consumption on ekc: evidence from pakistan. journal of cleaner production, 156, 855-864. dogan, e., ozturk, i. (2017), the influence of renewable and nontable 5: short run elasticities for selected asean countries variables asean-4 indonesia malaysia philippines thailand coefficient coefficient coefficient coefficient coefficient d(lngdp) 0.127 −0.447*** −0.625*** −0.488** 0.154 d(lnfdi) −0.007 0.033*** 1.290 0.016*** 0.010*** d(lnto) 0.149 0.027*** −0.091*** −0.238*** 0.112*** d(lnupop) −0.756 −0.415 0.4732 −4.200 1.117 d(lnco2) −0.117 −0.013*** 0.027 0.102** −0.586*** d(lngov) −0.104 0.018*** −0.564** −0.049*** 0.179*** c 2.237** 3.779 3.859 0.407* 0.903 ectt−1 −0.252** −0.184*** −0.625*** −0.065*** −0.136*** *,**,*** indicate significant at 10%, 5% and 1% significance level respectively kumaran, et al.: an empirical analysis of factors affecting renewable energy consumption in association of southeast asian nations-4 countries international journal of energy economics and policy | vol 10 • issue 2 • 202056 renewable energy consumption and real income on co2 emissions in the usa: evidence from structural break tests. environmental science and pollution research, 24(11), 10846-10854. doytch, n., narayan, s. (2016), does fdi influence renewable energy consumption? an analysis of sectorial fdi impact on renewable and non-renewable industrial energy consumption. energy economics, 54, 291-301. ghimire, l.p., kim, y. (2018), an analysis on barriers to renewable energy development in the context of nepal using ahp. renewable energy, 129, 446-456. gujarati, n.d. (2003), basic econometrics. 4th ed. new delhi: tata mcgraw-hill. p748, 807. hadri, k. (1999), testing the null hypothesis of stationarity against the alternative of a unit root in panel data with serially correlated errors. research papers. university of liverpool. department of economics and accounting. harris, r., sollis, r. (2005), applied time series. modelling and forecasting. chichester: johnwilley & sons. icrg. (2017), the international country risk guide (icrg). available from: https://www.prsgroup.com/explore-our-products/internationalcountry-risk-guide. im, k.s., pesaran, m.h., shin, y. (2003), testing for unit roots in heterogeneous panels. journal of econometrics, 115, 53-74. irena. (2018), renewable energy market analysis: southeast asia. available from: http://www.irena.org/publications/2018/jan/ renewable-energy-market-analysissoutheast-asia. kammen, d.m., sunter, d.a. (2016), city-integrated renewable energy for urban sustainability. urban planet, 352(6288), 922-928. kao, c., chiang, m.h. (2000), on the estimation and inference of cointegrated regression in panel data. in: baltagi, b.h., fomby, t.b., hill, r.c., editors. nonstationary panels, panel cointegration, and dynamic panels (advances in econometrics). vol. 15. bingley: emerald group publishing limited. p179-222. koh, h. (2017), ‘half of southeast asia’s renewable energy projects are unbankable’. available from: http://www.eco-business.com/news/ half-of-southeast-asias-renewable-energy-projects-are-unbankable. [last retrieved on 2018 jun 06]. lam, p.t.i., law, a.o.k. (2018), financing for renewable energy projects: a decision guide by developmental stages with case studies. renewable and sustainable energy reviews, 90, 937-944. lee, j.w. (2013), the contribution of foreign direct investment to clean energy use, carbon emissions and economic growth. energy policy, 55, 483-489. levin, a., lin, c.f., chu, c.s.j. (2002), unit root tests in panel data: asymptotic and finite sample properties. journal of econometrics, 108, 1-22. maddala, g.s., wu, s. (1999), a comparative study of unit root tests with panel data and a new simple test. oxford bulletin of economics and statistics, 61, 631-652. mat rahim, s.r., mohamad, z.z. (2018), green sukuk for financing renewable energy project. turkish journal of islamic economics, 5(2), 129-144. murphy, d. (2018), economist intelligence unit predicts ‘mild’ us recession in 2020. consumer news and business channel (cnbc). available from: https://www.cnbc.com/2018/01/23/economy-andinterest-rates-eiu-predicts-next-us-recession.html. [last retrieved on 2018 may 10]. omri, a., daly, s., nguyen, d.k. (2015), a robust analysis of the relationship between renewable energy consumption and its main drivers. applied economics, 47(28), 2913-2923. omri, a., nguyen, d.k. (2014), on the determinants of renewable energy consumption: international evidence. energy, 72(3), 554-560. pedroni, p. (2000), fully modified ols for heterogeneous cointegrated panels. advances in econometrics, 15, 93-130. pedroni, p. (2001), purchasing power parity tests in cointegrated panels. review of economics and statistics, 83, 727-731. pesaran, m.h., shin, y., smith, r.p. (1999), pooled mean group estimation of dynamic heterogeneous panels. journal of the american statistical association, 94(446), 621-634. salim, r.a., shafiei, s. (2014), urbanization and renewable and nonrenewable energy consumption in oecd countries: an empirical analysis. economic modelling, 38, 581-591. shahbaz, m., rahman, m.m. (2010), foreign capital inflows-growth nexus and role of domestic financial sector: an ardl co-integration approach for pakistan. journal of economic research, 15, 207-231. sharif, a., raza, s.a., ozturk, i., afshan, s. (2019), the dynamic relationship of renewable and nonrenewable energy consumption with carbon emission: a global study with the application of heterogeneous panel estimations. renewable energy, 133, 685-691. shukla, a.k., sudhakar, k., baredar, p. (2017), renewable energy resources in south asian countries: challenges, policy and recommendations. recourse-efficient technologies, 3(3), 342-346. transparency international. (2015), why asean needs to confront corruption in southeast asia. available from: https://www. transparency.org/news/feature/why_asean_needs_to_confront_ corruption_in_southeast_asia. world bank. (2017), philippines: building competitive, sustainable and inclusive cities. available from: http://www.worldbank.org/ en/news/press-release/2017/05/29/philippinesbuilding-competitivesustainable-and-inclusive-cities. worldometers. (2018), available from: http://www.worldometers.info/ world-population/south-eastern-asia-population. zhao, x., luo, d. (2016), pricing force of rising renewable energy in china: environment, regulation and employment. renewable and sustainable energy reviews, 68, 48-56. . international journal of energy economics and policy | vol 10 • issue 1 • 2020134 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(1), 134-139. development of energy cooperation between russia and china jaehyung an1*, mikhail dorofeev2, shouxian zhu3 1college of business, hankuk university of foreign studies, seoul, korea, 2financial university under the government of the russian federation, moscow, russia, 3institute for urban and environmental studies, chinese academy of social sciences, beijing, china. *email: jaehyung.an@yahoo.com received: 02 august 2019 accepted: 07 november 2019 doi: https://doi.org/10.32479/ijeep.8509 abstract the research analyses the question of to what extent the focus on state projects between russia and china is based on the russian desire to switch from an economy that is dependent on natural resources. through the analysis of existing capabilities of the russian companies to propose opportunities for innovative and technological projects that can be used in the long run. at the same time, the research will focus on energy trends and their presence in russian and chinese energy markets. keywords: energy sources, china energy policy, resource saving, economic development, energy cooperation jel classifications: c30, d12, q41, q48 1. introduction as long as energy resource industry provides functional products for all countries in the world this industry belongs to a federal government that possesses also the right over off-shore facilities, controls and directs trade in natural resources and conducts international projects. the objective is to shed the light on projects that should be prioritized by all groups that are involved in the energy system of both countries based on the discussions with the participants of this research. the energy cooperation between russian and china calls upon the analysis of recent energy production and consumption in china. therefore, it is significant to introduce management of energy resources. resource management has led to the discussion of natural gas supply options. focusing on energy as a main state asset, the role of state-owned companies is vital and therefore is worth paying attention to. energy cooperation should be supported and reflected in the state’s strategies. hence, the russian energy strategy 2035 is presented. the last section of the literature review is about china development bank. this section emerged during the primary data collection when the participants emphasized the role of the bank policy in energy deals between china and the emerging countries. these chapters would be expanded upon in the discussion section. 2. literature review many studies have been trying to explain, define and analyze influence energy price factors (meynkhard, 2019; wustenhagen and bilharz, 2006). a study conducted by (morris and barlaz, 2011) focuses on the importance of the transformation to market oriented economy through the institutional reforms and positive this journal is licensed under a creative commons attribution 4.0 international license an, et al.: development of energy cooperation between russia and china international journal of energy economics and policy | vol 10 • issue 1 • 2020 135 outcomes for the country. another study emphasizes the negative consequences which the country is facing now mikhaylov (2019a) and mikhaylov et al. (2019). these consequences such as high level of air pollution and energy dependency have made the chinese government reconsider the current energy policy and build a new energy system. china’s recent economic growth has been based on fundamental economic forces such as capital flow to the country in the form of foreign investments (jaramillo and matthews, 2005; lopatin (2019a) and a growing production of outputs that is reflected in export (milbrabdt et al., 2014, morgan and yang, 2001). however, the reverse side of the rapid economic growth has resulted in the new challenges faced by the countryhigh-pollution level and high-energy consumption. nowadays, china is known as the largest emitter of carbon dioxide. china’s energy policy states that the country is struggling from low energy efficiency that has resulted in high energy consumption for every unit of gdp. to reduce carbon dioxide and improve environmental pollution, china is focusing on energy conservation and energy efficiency (mikhaylov, 2018a,b) policies, as well as turning to the development of renewable energy sources. from a high rate of coal production and consumption, the country aims at increasing natural gas consumption by 11.2% and renewables, solar plants by 89.5% and wind capacity by 26.4%, according to china’s 12th five-year plan. in order to develop energy efficiency, china should prepare the fundamental basic of laws and regulations chiemchaisri et al. (2012) and gardner et al. (1993). there are two main laws underlying the promotion of energy efficiency in china: the energy conservation law of the people’s republic of china by standing committee of the national people’s congress in 1997 and amended in 2007 consists of seven chapters and six sections. the law specifies that energy conservation should greatly increase energy efficiency in energy-using sectors (industrial, construction, transportation and public sectors) by using energy in the most efficient way. the renewable energy promotion law issued in 2005 and improved in 2009 is believed to be cental to further development of renewable energy in china. the law emphasises the countrie’s goals to increase energy supply procurememt, diversify energy suppliers and improve environmental conditions due to the rapid increase in fossil energy usage. energy efficiency and energy conservation are topics that are inextricably tied and come out after the analysis of energy consumption rate. therefore, it is significant to follow up the studies on energy consumption which are examining the possible drivers of growing energy consumption rate. the study on correlation analysis (amini and reinhart, 2011; bansal et al., 2013). a correlation approach allowed them to investigate some of the reasons underlying energy consumption growth in general. the results which they reached were based on consumption behavior, income increase, lack of knowledge and information imperfection over rational energy use. the research mainly focused on the relation between growing energy consumption and consumers behavior, it emphasized that information flow over energy efficiency is a priority of a government to be improved. another study was introduced by the experts (ahmed et al., 2014; mikhaylov et al., 2018; nyangarika et al., 2018) who found that energy consumption analysis cannot be based only on correlation analysis but also on regression. at the end of the study they highlighted the importance of advanced technologies that the chinese government should promote. furthermore, technological developments should be accompanied by the energy saving policies. if we refer to the article energy consumption, carbon emission, and economic growth in china (bove and lunghi, 2006; cai et al., 2011). over the past years china has fully demonstrated several important relations between gdp indicator and growing energy consumption; between growing energy consumption and growing carbon (denisova, 2019; denisova et al., 2019). apart from these paired associations, one more an artificial pair was created by the government of china. the link is adjusted by the chinese government domestic energy price and the rate of energy consumption in the country. this relation aims at changing the energy consumption in the short and long term (nyangarika et al., 2019a,b). by setting high energy prices in the country, in the short run energy consumption will be increased, while in the long run decreased. the authors stated that this measure will not have a negative impact on economic output in the long run. following up upon the energy consumption growth, assert that the energy consumption growth is mostly based on the industrial sector. they believe that china’s growing energy demand comes mostly from heavy industry and infrastructure sectors. they also attempt to show that individual consumption matters what is also proved by international energy agency. therefore, it is not hard to explain why energy efficiency and conservation are the most popular topics to emerge in the context of growing energy consumption and why it is vital for today’s china and its future. the following literature review reflects the current concerns over the correlation between energy reduction and stable economic growth in china. the discussion on efficiency should start first of all with its importance that is highlighted in the official documents. according to the russian state program on energy efficiency and energy sector development, energy efficiency is an effective way for industries and the entire economy to function in the most efficient way. energy efficiency policy in the chinese context comprises an, et al.: development of energy cooperation between russia and china international journal of energy economics and policy | vol 10 • issue 1 • 2020136 all these aspect including an opportunity to develop competitive technologies. china lacks of pollution controlled equipment. the debate over energy conservation started while time and have been confined not only to energy reduction but also to economic response (e.g., energy cost). in 1978, gibbons and chandler in the article national energy conservation policy emphasized that global energy price fluctuation affects energy consumption. therefore, the authors believe that modernization of energy consuming facilities can be implemented in order to save and decrease energy cost. furthermore, they reached a strong conclusion that economic growth will most likely not to slow down because of energy consumption reduction. the international energy agency supports this idea in pointing out that economic growth is possible to maintain by implementing energy efficiency policies. energy efficiency means the most rational use of energy and energy savings (mikhaylov, 2018a,b). 3. methods the research purposes were identified within the development study. development study stands for the ‘development processes and structures in particular parts of the world. there are no limits of social disciplines that fall with the development research. therefore, politics as a social science suits to the development research. energy development consists of actors, structures and dynamics. development studies is closely related to the historical knowledge. the core focus of the research was on russia-china energy cooperation, on energy relationship, interactions between the governments and national energy companies. due to the novelty of the topic, this study is exploratory. this purpose of this research is to investigate energy cooperation between two countries; identify energy trends; generate new fields for further researches. political and economic sides of the research require a qualitative approach that helps to make claims based on respondents’ answers on introduced questions. the research focuses on the russia-china energy cooperation as a significant phenomenon in bilateral cooperation, prepares openended questions, validates the accuracy of the research findings, makes interpretation of participants’ answers, and creates possible statements. for the above reasons, a deductive approach is considered to be the most relevant (an et al., 2019). the research is based on interviews. the findings of this study will be useful for further research whether it will enrich and expand debate on energy projects between russia and china or look at another type of cooperation in the energy industry. in the context of this thesis, the design seems appropriate to introduce. the purpose of this strategy is to focus on participants’ description of russia china energy cooperation, their views on its potential and technology transfer between two countries, critics on energy policies. the major part that falls into the qualitative approach is a chosen method for data collection and its further analysis (barbour, 2013; lopatin, 2019b; kosov et al., 2018). the model of energy pricing looks as follows: energy cost=∑a+b+c+d (1) where a the costs incurred by the infrastructure dependent on the annuity factor and related capex cost; b the operational costs of plant technology; c the supply chain costs, collection, and treatment; d the transport cost. the method combines general and specific questions over the russia-china energy cooperation. 4. results following these studies and china’s current issues, it is important to track the trends based on statistical significance. in order to understand current energy cooperation the following section will present statistical data observation. first, to understand the chinese government concern over growing energy consumption, statistical data shows the major trends in the chinese energy production/consumption with the russian (table 1). the production/consumption of oil in both countries shows that oil production in russia is almost equal to oil consumption in china. whereas, the chinese domestic oil production is slightly higher than russian oil consumption. second, china is the second largest oil consumer in the world after the usa. the following first table indicates that despite the fact that chinese crude oil import has been increased from 2015 to 2018, domestic crude oil production showed an upward trend. table 2 demonstrates that chinese energy export is less than energy import: table 1: chinese and russian energy production/ consumption 2018 tb/d oil production oil consumption china 4155 10221 russia 10643 3174 source: bp statistical review 2019 table 2: chinese domestic crude oil production (2015-2018) oil domestic output million b/d oil net import million b/d 2018 4.5 5.7 2017 4.2 5.4 2016 4.1 5 2015 4.1 4.7 source: cia world factbook bp statistical review 2019 an, et al.: development of energy cooperation between russia and china international journal of energy economics and policy | vol 10 • issue 1 • 2020 137 third, strategic petroleum reserve (spr) is viewed to be a powerful response on any cases of emergency in commercial energy supplies that can threaten country’s economy. in the context of energy cooperation and for the analysis of energy demand and energy supply, further data on crude oil reserves in the world, russia and china is essential (table 3-5). world proven oil reserves at the end of 2012 achieved a point of 1668.9 billion barrels. according to a r/p ratio (reservesto-production ratio) china might use proven oil reserves for a bit >11 years. the use of the world reserves might last for <53 years. fourth, it was mentioned that according to the 12th 5-year-plan the chinese government aims at increasing natural gas consumption by 11.2%. according to china data online (2014), in 2013 china produced 117.1 billion cu m of natural gas; consumed more, 150 billion cu m. china exported less than imported, 2.4 billion cu m and 53 billion cu m respectively (table 6). with reference to the government’s target to increase the consumption of natural gas, the following gas resources in china are worth mentioning. there are six oil-gas fields: sichuan, datianchi gas field, changging fas field, offshore field in the bohai sea, east china sea, south china sea. oil-gas fields are located in the north, west and northeast of china and their total output equals to 90% of national total natural gas output. in 2009 natural gas reserves reached the point of 2.5 trillion cu m. nevertheless, a r/p ratio was almost at the same level, 28.8. both countries, russia and china, have developed their state programs for promoting energy efficiency. russia’ program is called energy saving and energy efficiency improvement until 2020 while the chinese goals are outlined in the 12th five-year plan. according to these two programs, the countries have to solve the problems of energy intensity (table 7-8), for a period of 10 years in russia and for a period of 5 years in china. despite the fact that the terms of the programs are different, estimated energy investments for reaching the set targets are almost the same. the investments estimations for russia and china were taken from energy efficiency reports provided by a global leader in energy efficiency solutions, abb (2014), and proven by the international energy agency report on energy efficiency in russia (iea 2011); as far as investment amount for energy efficiency in china is concerned, the chinese government estimates $373 billion investments for major energy-saving projects. referring to table 9 gas and coal is presented. figures demonstrate that the rate of energy consumption of coal is dropping, while the consumption of gas is increasing. these figures also illustrate that table 4: world proven oil reserves 2012 2018 1,668.90 1,878.70 source: bp statistical review 2019 of world energy table 3: export and import (2018) china 2018 crude oil export import 33,000 bbl/day 5.664 million bbl/day source: cia world factbook bp statistical review 2019 table 5: proven oil reserves in russia and china proven oil reserves 2018 russia china billion barrels 87.2 17.3 share of total 5.2% 1% r/p ratio 22.4 11.4 source: bp statistical review 2013 table 6: natural gas production/consumption in china; export and import china 2018 natural gas production consumption 117.1 billion cu m 150 billion cu m export import 2.4 billion cu m 53 billion cu m source: china data online (2019) table 7: energy intensity reduction in russia and china and estimating investments for russia and china russia by 2020 china by 2015 reduction in energy intensity 40% 16% investments to save energy (us$) 320 billion 372 billion source: china data online (2019) table 8: energy consumption share by fuel in russia and china energy consumption share by fuel russia % china % gas 55 4 oil 21 18 nuclear power 6 1 hydroelectricity 2 7 coal 15 70 electricity consumption (per capita) 2011 6.000kwh 3.000kwh source: abb energy efficiency report 2019 abb (abb: global leader in power and automation technologies), bp statistical review of world energy 2019 table 9: total energy consumption in china crude oil % coal % gas % 2016 19.0 68.0 4.4 2017 18.6 68.4 5.0 2018 18.8 66.6 5.2 source: china statistical 2019 an, et al.: development of energy cooperation between russia and china international journal of energy economics and policy | vol 10 • issue 1 • 2020138 the energy initiatives outlined above by the chinese government will slowly achieve positive results. for the beginning of 2018 china produced 1.8 trillion tons of coal. and there are 137 enterprises that are working in the oil & natural gas sector in china. in concluding this section, it is necessary to mention that china is the largest producer and consumer of the coal in the world (bp statistical review of world energy). this has many implications for the reconsidering china’s role in worsening environmental condition. however, china is not using only coal for energy; growing energy demand make china import crude oil and natural gas from africa, middle east, central asia and the asia pacific region. by using the traditional sources of energy china is becoming an important player in the global energy market. the global energy market consists of dependent and independentenergy resource countries which might face the challenges in the process of managing energy resources rationally. 5. discussion significantly the role of vertically integrated projects is introduced. the russian companies, gazprom and rosneft fall under the category of state-owned companies or vertically integrated. the participants’ answers revealed that these two russian companies and the chinese state-owned energy companies such as cnpc and sinopec are the major players in the gas business and the energy deals between russia and china. as stated by the participants vertically integrated company controls the entire supply chain. however, vertically integrated project is a vertically controlled, i.e., controlled by high-level officials. the natural gas deal signed by russia and china is an example of a vertically integrated project (table 10). the event led to the discussion over interest groups. it has become obvious that the russian and chinese energy companies are an example of the coalescence of state and business. the findings indicate that in the context of the management of strategic resources such types of energy businesses are inevitable. binbin overviews the energy industry in china and emphasizes that the chinese government considers vertically integrated nocs as more efficient and productive. therefore, the state is keeping the control over energy companies that work in upstream and downstream sectors. however, during the analysis of estimated amounts of investments for the gas deal implementation, following assumption can be drawn. the russia-china gas deal might have had a discord between the russian high level officials and energy business community. according to vladimir putin’s answers to journalist questions the required amount of investments is currently estimated at being worth $80 billion (2014). from this amount we may estimate that gazprom investments are worth $55 billion, while cnpc’s portion is $25 billion of cdb’s loan. the information that was shared by a participant that gazprom is obliged to pay back to cdb more than 100%, could not be found in available sources. if the information can be proved, gazprom did not probably lead the negotiations with cnpc; the agreement was facilitated by the russian government and politics. in the most cases, especially in authority centralized countries like russia or china, there are president and government which stand behind the energy policy formation. in the light of recent events taken place in ukraine, russian energy policy formation prioritizes the development of energy cooperation with the asian partners that will reduce reliance on energy export to europe. 6. acknowledgements this work was supported by hankuk university of foreign studies research fund. table 10: interest groups in any projects interest group natural gas supply option technology transfer knowledge transfer disagreements chinese national energy strategy russian national energy strategy government officials separatist activity cannot be rerouted more beneficial for the development of surrounding cities from west to china e&d in china diversification west siberia energy deposits energy companies pipeline from russia to china e&p in china price for ng energy security energy export via pipelines china development bank lng from china to russia psa in offshores availability of supply of ng buy up more energy resources as possible from resource rich countries energy export via lng presidents less beneficial for the development of surrounding cities from west to china and russia jvs in offshores volume of ng buy up energy deposits in resource rich countries east siberia energy deposits an, et al.: development of energy cooperation between russia and china international journal of energy economics and policy | vol 10 • issue 1 • 2020 139 references ahmed, s.i., johari, a., hashim, h., mat, r., lim, j.s., nagadi, n., ali, a. (2014), optimal landfill gas utilization for renewable energy production. environmental progress and sustainable energy, 34(1), 289-298. amini, h.r., reinhart, d.r. (2011), regional prediction of long-term landfill gas to energy potential. waste management, 31(9-10), 2020-2026. an, j., mikhaylov, a., moiseev, n. (2019), oil price predictors: machine learning approach. international journal of energy economics and policy, 9(5), 1-6. bansal, a., illukpitiya, p., singh, s.p., tegegne, f. (2013), economic competitiveness of ethanol production from cellulosic feedstock in tennessee. renewable energy, 59, 53-57. barbour, r. (2013), introducing qualitative research: a student’s guide. 2nd ed. thousand oaks, ca: sage publications. bove, r., lunghi, p. (2006), electric power generation from landfill gas using traditional and innovative technologies. energy conversion and management, 47(11-12), 1391-1401. cai, x., zhang, x., wang, d. (2011), land availability for biofuel production. environmental sciences technology, 45(2), 334-339. chiemchaisri, c., chiemchaisri, w., kumar, s., wicramarachchi, p.n. (2012), reduction of methane emission from landfill through microbial activities in cover soil: a brief review. journal critical reviews in environmental science and technology, 42(4), 412-434. denisova, v. (2019), energy efficiency as a way to ecological safety: evidence from russia. international journal of energy economics and policy, 9(5), 32-37. denisova, v., mikhaylov, а., lopatin, e. (2019), blockchain infrastructure and growth of global power consumption. international journal of energy economics and policy, 9(4), 22-29. gardner, n., manley, b.j.w., pearson, j.m. (1993), gas emissions from landfills and their contributions to global warming. applied energy, 44(2), 166-174. jaramillo, p., matthews, h.s. (2005), landfill-gas-to-energy projects: analysis of net private and social benefits. environmental science and technology, 39, 7365-7373. kosov, m., akhmadeev, r., smirnov, d., solyannikova, s., rycova, i. (2018), energy industry: effectiveness from innovations. international journal of energy economics and policy, 8(4), 83-89. lopatin, e. (2019a), methodological approaches to research resource saving industrial enterprises. international journal of energy economics and policy, 9(4), 181-187. lopatin, e. (2019b), assessment of russian banking system performance and sustainability. banks and bank systems, 14(3), 202-211. meynkhard, a. (2019), energy efficient development model for regions of the russian federation: evidence of crypto mining. international journal of energy economics and policy, 9(4), 16-21. mikhaylov, a. (2018a), pricing in oil market and using probit model for analysis of stock market effects. international journal of energy economics and policy, 2, 69-73. mikhaylov, a. (2018b), volatility spillover effect between stock and exchange rate in oil exporting countries. international journal of energy economics and policy, 8(3), 321-326. mikhaylov, a. (2019), oil and gas budget revenues in russia after crisis in 2015. international journal of energy economics and policy, 9(2), 375-380. mikhaylov, a., sokolinskaya, n., lopatin, e. (2019), asset allocation in equity, fixed-income and cryptocurrency on the base of individual risk sentiment. investment management and financial innovations, 16(2), 171-181. mikhaylov, а., sokolinskaya, n., nyangarika, а. (2018), optimal carry trade strategy based on currencies of energy and developed economies. journal of reviews on global economics, 7, 582-592. milbrabdt, a.r., heimiller, d.m., perry, a.d., field, c.b. (2014), renewable energy potential on marginal lands in the united states. renewable and sustainable energy review, 29, 473-481. morgan, s.m., yang, q. (2001), use of landfill gas for electricity generation. practice periodical of hazardous, toxic, and radio waste management, 5(1), 14-24. morris, j.w., barlaz, m.a. (2011), a performance-based system for the long-term management of municipal waste landfills. waste management, 31(4), 649-662. nyangarika, a., mikhaylov, a., richter, u. (2019b), oil price factors: forecasting on the base of modified auto-regressive integrated moving average model. international journal of energy economics and policy, 9(1), 149-159. nyangarika, а., mikhaylov, а., richter, u. (2019a), influence oil price towards economic indicators in russia. international journal of energy economics and policy, 9(1), 123-129. nyangarika, а., mikhaylov, а., tang, b.j. (2018), correlation of oil prices and gross domestic product in oil producing countries. international journal of energy economics and policy, 8(5), 42-48. wustenhagen, r., bilharz, m. (2006), green energy market development in germany: effective public policy and emerging customer demand. energy policy, 34, 1681-1696. . international journal of energy economics and policy | vol 9 • issue 3 • 2019 269 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(3), 269-273. renewable energy consumption: the effects on economic growth in mexico marco mele* department of political sciences, university of teramo, italy. *email: mmele@unite.it received: 13 december 2018 accepted: 16 march 2019 doi: https://doi.org/10.32479/ijeep.7460 abstract this study will demonstrate, through an econometric approach, the renewable energy consumption-economic growth effects in mexico over the period 1990-2017. after a premise where we describe the situation of energy demand and consumption in mexico and a summary of the economic literature, we have applied various econometric tests. results about unit root tests describe a situation with all variables that aren’t stationary except that in first differences. the toda and yamamoto approach is very important in our analysis: it highlights the existence of a unidirectional causal flow, running from renewable energy consumption to aggregate income. this situation respects the theory and hypothesis of economic growth. keywords: renewable energy consumption, economic growth, causality, mexico jel classifications: b22, c32, n54, q43 1. introduction renewable energy growth is an important factor for the economy as well as for the environment and society. this is because, among the determinants of growth, there are obviously economic conditions and technological innovation. however, these must be helped by policies that pay attention to pollution and climate change. the choice to go towards a change of new energy and widening the scope of application, will allow to reduce carbon emissions, but will improve the life of the society. in this way, it will be possible to create new jobs, to contribute to achieving the objectives of economic development and to guarantee a cleaner and more prosperous for future generations. the production of green energy is growing over the years: for example, starting in 2012, the new generation plants powered by renewable sources have produced more energy than that derived from conventional, non-renewable sources. in this situation, mexico is a special case study. mexico can boast excellent wind resources and ideal for the construction of large parks. the temperature difference between the gulf of mexico and the pacific ocean creates one of the strongest and most constant wind tunnels in the oaxaca region. in this region, there are areas with an annual average wind speed even higher than ten meters per second. in this way, an average load factor of >2500 h has been calculated for existing plants. the growth rate of wind capacity installed in 2016 was even higher than 100%. at the same time, the northernmost region of the country is characterized by an insolation index of 60% higher than that of germany, the world leader in the photovoltaic sector and comparable to that of california and the deserts of north africa. therefore, wind and solar represent, without a doubt, the sectors with the highest growth expectations for the coming years, but they are certainly not the only ones. mexico also boasts >10 gw of installed hydropower and just under 1 gw of geothermal. as for the latter source, the country is the world’s fourth largest producer of installed power and the second, only after indonesia, for geothermal resources available. finally, in the last period, important projects in the biomass sector are also beginning to be registered. for these reasons, we will try to verify the effects of renewable energy consumption in mexico on economic growth. this journal is licensed under a creative commons attribution 4.0 international license mele: renewable energy consumption: the effects on economic growth in mexico international journal of energy economics and policy | vol 9 • issue 3 • 2019270 2. recent trends in renewables and in mexico’s total energy system mexico is a major producer of fossil fuels. indeed, it is the tenth largest producer of oil and natural gas in the world. this situation is a determinant for mexico’ economic growth. however, in recent years, it increased research and development about renewable sources of energy. according to government sources, the total final energy consumption (tfec) is 90% and it is, principally, fossil fuels; the total share of renewable energy was about 10% (figure 1). in general, we can list the main sources for mexico in future about renewable energy in: wind (it’s a potential to produce 92 tw h of electricity in future), solar pv (in a future could contribute 30 gw of power capacity) and bioenergy (for a future represent amount to around 4 gw of capacity). with regard to consumption by sector, transport has been, for many years, the most important component of energy consumption. today, however, this sector accounts for half of mexico’s tfec, while it has grown the total energy demand of the building sector (about 35%), with consumption equal to 25% of mexico’ tfce. the industrial sector, however, consumes energy to a value of 28%, while only 3% agriculture (figure 2). now, according to remap (2015) is possible to analyze growth projections about energy consumption and uptake of renewable energy technology, for a time series 2010-2030 in mexico. these results are taken from paper “power sector perspectives” and affirm that in 2030 the tfec will be equal to 7.4 ej, that it is a 64% increase over 2010. this increase in consumption will particularly affect the transport sector for a value of 45%; consumption in the industrial sector will also increase four times in 2030. it will record a value of 33% compared to the total. the case of the building sector is interesting. in fact, the share of consumer demand, in 2030, will remain constant. in 2030 the energy demand will be met primarily by oil and electricity. subsequently, we find gas and renewable energy (figure 3). 3. a brief survey of theoretical and empirical studies studies examining the relationship between energy consumption and economic growth is enormous. some studies (apergis and payne 2009, apergis and payne 2010, apergis and payne 2014) find a bidirectional relationship between renewable energy consumption and economic growth, especially about the china’ case where the real gdp growth for a value of 0.12% with an increase in renewable energy consumption by 1%. relatively to panel context, numerous have been those that have analyzed the case of the oecd countries (sadorsky, 2009; apergis and payne, 2010; tiwari, 2011; tugcu et al., 2012; kula, 2014; bhattacharya et al., 2016; jebli et al., 2016; rafindadi and ozturk, 2017; benavides et al., 2017; taher, 2017; hassine and harrathi, 2017). with regard to technical studies on renewable energy in mexico case, we can look table 1. so, for the literature review about social and environmental impact of the implementation of renewable energy projects in mexico, we can follow the table 2. 4. empirical analysis this study examines, now, the renewable energy consumptioneconomic growth nexus in mexico figure 1: total final energy consumption mexico composition source: national energy balance 2016 figure 2: total final energy consumption by sector source: national energy balance 2016 figure 3: renewable power generation growth, 2010-2030 source: irena remap, 2030 mele: renewable energy consumption: the effects on economic growth in mexico international journal of energy economics and policy | vol 9 • issue 3 • 2019 271 over the period 1980-2017. we use toda and yamamoto tests (1995) and according to apergis and payne (2014), we estimate these equations in logarithm terms (1): (1) [lnyt, lnret, lnkt, lnlt] = a0 + a1 [lnyt−1, lnret−1, lnkt−1, lnlt−1] + a2 [lnyt−2, lnret−2, lnkt−2, lnlt−2] + a3 [lnyt−3, lnret−3, lnkt−3, lnlt−3] + [ԑlnyt, ԑlnret, ԑlnkt, ԑlnlt] after we use a granger causality analysis (1969) with the forecast error variance decomposition analysis. y is gdp (constant 2000 us$), re represent combustible renewables and waste (% of total energy), k is gross fixed capital formation (constant 2000 us$), l is total labor force (labor force statistics). for the dataset, we use world data bank development indicators for mexico, with time series 1980-2017. to begin, we analyze the variables with the descriptive statistics in table 3. as we can see: mean present a positive value for gdp, gross fixed capital formation and total labor force. renewable table 1: main findings on the status and prospects of renewable energy sources in mexico year author (s) key findings 2015 hernández-escobedo and rodríguez the authors evaluated solar resources in 5 states along the gulf of mexico. they found that the highest amount of solar energy recorded was >6.22 kw h/m2 for day in july. its effect on growth is positive and unidirectional 2015 garcía et al. the authors analyzed 11 bioenergy options and had these results: by 2035, 16% of the final energy in mexico. it could be replaced. mexico has a potential technician for the production of sustainable biomass for 1713 pj or 18.5% of the total primary energy used. the change will generate new jobs 2015 grande et al. users can find benefits from using photovoltaics. through this idea, they would stop using the energy provided by the network, obtaining two effects: saving families and more disposable income. this situation would incentivize keynesian income multipliers 2010 hernández-escobedo et al. the authors carry out a detailed study on the effects of wind on renewable energy. they find that in some areas of northern mexico it is possible to use this source to replace the network’ energie 2014 alemán-nava et al. the authors, starting from the fact that in mexico about 16% of the power was generated from renewable sources, they study the support that there has been over time hydro-electric energy and biomass 2014 mundo-hernández et al. the study addresses the hassle of the mexican fund resources for the energy transition. it mainly promotes the electrification using photovoltaic technology. its use is an engine for economic growth 2011 hernandez-escobedo et al. the authors study how to exploit the wind’s potential in mexico. they conclude that a minimum wind speed is required between 8:00 am and 4:00 pm and a maximum closing time at 24:00 h table 2: social and environmental impact of renewable energy projects in mexico year author (s) key findings 2016 huesca-pérez et al. the authors find the following positive effects: lower negative impact on agricultural production; creation of new jobs during the construction phase of renewable energy machinery; increased transmission of information; minor social conflicts 2016 corona et al. this paper evaluates the environmental performance of concentrating solar power plants. the plants are located in different countries (spain, chile, the kingdom of saudi arabia, mexico and south africa). according to the authors, the main environmental impact of these technologies is due to the construction of heliostats, mainly with the use of steel 2015 selfa et al. this paper focuses on social sustainability in the biofuels sector in three latin american countries (including mexico). the authors’ results were: increase in workers’ wages; higher disposable income for families, thanks to savings 2015 agüero-rodríguez et al. this paper is a study on the effects of the transformation of national policy on the biofuels of the state of veracruz in mexico. the authors reveal that without proper regulation, the price increase can be intensified by mass production of biofuels in the area 2011 pasqualetti this paper studies the challenges and obstacles to the development of renewable projects (solar, wind, geothermal) in countries such as: scotland, mexico and the united states. it addresses the problem of the social impact of wind energy, specifically in the state of oaxaca in mexico 2010 garcía-frapolli et al. this article studies the economic benefits of using some stoves that use biomass in michoacan, mexico. the results regarding the social impact of this saved, improving the health of children and adults and reducing public health expenditure. time saved, improving the health of children and adults and reducing public health expenditure 2007 fernández-valverde the authors analyze hydrogen as one of the main sources of energy for mexico. among the results that suggest the use of hydrogen in mexico are: the combustion of hydrogen produces water and a small amount of nitrogen oxides and therefore low environmental impact table 3: descriptive statistics analysis variable mean median sd skew ness kurtosis 10trim iqr y 11.4813 11.6251 0.2205 −0.1435 2.471 11.47 0.3621 re −0.1121 −0.1457 0.5941 −0.4253 3.4305 −0.11 0.4125 k 10.0742 10.0629 0.1856 0.047 1.7156 10.05 0.2413 l 10.0251 10.0354 0.1912 −0.4014 2.1174 10.01 0.0941 mele: renewable energy consumption: the effects on economic growth in mexico international journal of energy economics and policy | vol 9 • issue 3 • 2019272 energy consumption is negative; 10-trim values are near the mean and the standard deviation, the inter-quartile range shows the absence of outliers. regarding the correlation analysis it show that, in our time series dataset, they are strongly correlated: y-re= 0.7814; y-k= 0.9612; y-l=0.9824; re-k=0.8047; re-l=0.8147; k-l=0.9128 with all significant variables (0.000). after, to study the stationary properties, we apply unit root processes in table 4. the results in table 4 show: in relation to ocular inspection process all the value in time series dataset don’t satisfy the stationary criterion. on the contrary, this is so when we use the first difference. we can say that the four series are integrated into i (1). now, in order to find the anomalous values, consistently with economic and historical theory, we apply in our analysis cmr tests. this approach is necessary to eliminate, in the estimate, the economic turbulence that characterized the time series 1980-2017 (table 5). the results obtained show how, despite the structural break and the tests at the first differences, we are unable to reject the null of unit root. we can confirm, therefore, that are i (1) processes. after this situation we use to, estimate the causal link between the renewable energy consumption and economic growth effects in mexico, toda and yamamoto granger non-causality tests in table 6. the results of toda and yamamoto approach, in a multivariate granger non-causality tests, shows that there is a link between y and r: gdp is driven by renewable energy consumption. this result can be explained in the following way: when increases the energy consumption, also increases the use of the inputs used. this statement is also confirmed by the fact that there is a bidirectional causality between k and re. tests advise us also that we can reject the null hypothesis for: y and re, between k and re. this situation is very interesting because renewable energy consumption granger causes real aggregate income and, also, capital formation. 5. conclusion the study addressed the problem about the relationship between renewable energy and economic growth for mexico over the period 1980-2017. the growth in energy demand has fueled the search for renewable energy, in a country, rich in resources with an excellent environmental impact. the result about unit root tests describes a situation with all variables that aren’t stationary except that in first differences. the results of multivariate toda and yamamoto allowed to isolate the causal links of the chosen variables: in table 4: results for unit roots variable deterministic component adf ers kpss y contant, trend −1.128 −0.405 0.422*** re contant, trend −2.1896 −3.015* 0.38** k contant, trend −4.261* −4.157*** 0.024 l contant, trend −2.1478 −1.756 0.208*** δy constant −4.742*** −4.369*** 0.628*** δre constant −6.381*** −6.984*** 0.041 δk constant −4.108*** −4.324*** 0.025 δl constant −3.997*** −3.087*** 0.198 ***p<0.01, **p<0.05, *p<0.1 table 5: results about single structural break variable obp k t-stat 5% critical value y 1989 1 −2.157 −3.560 re 2000 1 −2.741 −3.560 k 1990 2 −2.728 −3.560 l 1991 1 −1.71 −3.560 δy 1989 0 −5.764*** −3.560 δre 1978 3 −6.846*** −3.560 δk 1989 2 −5.412*** −3.560 δl 1989 2 −3.108*** −3.560 ***p<0.01, **p<0.05, *p<0.1 table 6: multivariate granger noncausality tests (todayamamoto approach) dependent variables independent variables y re k l y (-) 17.611*** (0.000) 3.784 (0.157) 1.848 (0.426) re 4.6625 (0.108) (-) 9.417 (0.013) 3.1496 (0.344) k 1.8425 (0.475) 5.7421* (0.072) (-) 2.0895 (0.394) l 1.1608 (0.660) 12.245*** (0.002) 9.147** (0.017) (-) wald tests (p values in parentheses), ***p<0.01, **p<0.05, *p<0.1 mele: renewable energy consumption: the effects on economic growth in mexico international journal of energy economics and policy | vol 9 • issue 3 • 2019 273 fact, results show that real gdp is driven by renewable energy consumption. so, we can assert that econometrical analysis confirms the “growth hypothesis” in the mexico case. references agüero-rodríguez, j.c., tepetla-montes, j., torres-beristaín, b. (2015), producción de biocombustibles a partir de la caña en veracruz. méxico: perspectivas y riesgos socioambientales. ciencia uat. p74-84. alemán-nava, gs., casiano-flores, vh., cárdenas-chávez, dl., díazchavez, r., scarlat, n., mahlknecht, j., dallemand, j.f., parra, r. (2014), renewable energy research progress in mexico: a review. renew sustain energy rev, 32, 140-153. apergis, n., payne, j.e. (2009), energy consumption and economic growth in central america: evidence from a panel cointegration and error correction model. energy economics, 31, 211-216. apergis, n., payne, j.e. (2010), renewable energy consumption and growth in eurasia. energy economics, 32, 1392-1397. apergis, n., payne, j.e. (2014), the electricity consumption-growth nexus: renewable versus non-renewable electricity in central america. energy sources, part b, 7, 423-431. benavides, m., ovalle, k., torres, c., vinces, t. (2017), economic growth, renewable energy and methane emissions: is there an enviromental kuznets curve in austria? international journal of energy economics and policy, 7(1), 259-267. bhattacharya, m., paramati, s.r., ozturk, i., bhattacharya, s. (2016), the effect of renewable energy consumption on economic growth: evidence from top 38 countries. applied energy, 162, 733-741. corona, b., ruiz, d., san miguel, g. (2016), life cycle assessment of a hysol concentrated solar power plant: analyzing the effect of geographic location. energies, 9, 1-14. fernández-valverde s.m. (2007), hydrogen: the ecological fuel for mexican future. in: klapp, j., cervantes-cota, j.l., chávez alcalá, j.f., editors. towards a cleaner planet. environmental science and engineering (environmental science). berlin, heidelberg: springer. garcía, c.a., riegelhaupt, e., ghilardi, a., skutsch, m., islas, j., manzini, f., masera, o. (2015), sustainable bioenergy options for mexico: ghg mitigation and costs. renewable and sustainable energy reviews, 43, 545-552. garcía-frapolli, e., schilmann, a., berrueta, v.m., riojas-rodríguez, h., edwards, r.d., johnson, m., guevara-sanginés, a., armendariz, c., masera, o. (2010), beyond fuelwood savings: valuing the economic benefits of introducing improved biomass cookstoves in the purepecha region of mexico. ecological economics, 69, 2598-2605. grande, g., islas, j., rios, m. (2015), technical and economic analysis of domestic high consumption tariff niche market for photovoltaic systems in the mexican household sector. renewable and sustainable energy reviews, 48, 738-748. hassine, m.b., harrathi, n. (2017), the causal links between economic growth, renewable energy, financial development and foreign trade in gulf cooperation council countries. international journal of energy economics and policy, 7(2), 76-85. hernandez-escobedo, q., manzano-agugliaro, f., gazquez-parra, j.a., zapata-sierra, a. (2011), is the wind a periodical phenomenon? the case of mexico. renewable and sustainable energy reviews, 15, 721-728. hernández-escobedo, q., manzano-agugliaro, f., zapata-sierra, a. (2010), the wind power of mexico. renewable and sustainable energy reviews, 14, 2830-2840. hernández-escobedo, q., rodríguez, g. (2015), solar energy resource assessment in mexican states along the gulf of mexico. renewable and sustainable energy reviews, 43, 216-238. huesca-pérez. m.e., sheinbaum-pardo, c., köppel, j.s. (2016), social implications of siting wind energy in a disadvantaged region the case of the isthmus of tehuantepec, mexico. renewable and sustainable energy reviews, 58, 952-965. jebli, m.b., youssef, s.b., ozturk, i. (2016), testing environmental kuznets curve hypothesis: the role of renewable and non-renewable energy consumption and trade in oecd countries. ecological indicators, 60, 824-831. kula, f. (2014), the long-run relationship between renewable electricity consumption and gdp: evidence from panel data. energy sources, part b, 9(2), 156-160. mundo-hernández, j., de celis alonso, b., hernández-álvarez, j., de celiscarrillo, b. (2014), an overview of solar photovoltaic energy in mexico and germany. renewable and sustainable energy reviews, 31, 639-649. pasqualetti, m.j. (2011), social barriers to renewable energy landscapes. geographical review, 101, 201-223. rafindadi, a.a., ozturk, i. (2017), impacts of renewable energy consumption on the german economic growth: evidence from combined cointegration test. renewable and sustainable energy reviews, 75, 1130-1141. remap. (2015), renewable energy prospects 2010-2030. mexico: irena. sadorsky, p. (2009), renewable energy consumption, co2 emissions and oil prices in the g7 countries. energy economics, 31, 456-462. selfa, t., bain, c., moreno, r., eastmond, a., sweitz, s., bailey, c., pereira, s., souza, t., medeiros, r. (2015), interrogating social sustainability in the biofuels sector in latin america: tensions between global standards and local experiences in mexico, brazil, and colombia. environmental management, 56, 1315-1329. taher, h. (2017), renewable energy consumption impact on the lebanese economy. international journal of energy economics and policy, 7(4), 144-148. tiwari, a.k. (2011), energy consumption, co2 emissions and economic growth: evidence from india. journal of international business and economy, 12, 85-122. toda, h.y., yamamoto, t. (1995), statistical inference in vector auto regressions with possibly integrated processes. journal of econometrics, 66(1-2), 225-250. tugcu, c.c., ozturk, i., aslan, a. (2012), renewable and non-renewable energy consumption and economic growth relationship revisited: evidence from g7 countries. energy economics, 34(6), 1942-1950. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 4 • 2021 443 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(4), 443-449. human capital development, energy consumption and crude oil exports in nigeria: implications for sustainable development timothy ayomitunde aderemi1*, oyegoke adebusola adebola2, wahid damilola olanipekun3, olaoye olusegun peter4, ayodeji gbenga bamidele5, azuh dominic ezinwa6 1department of economics, accounting and finance, bells university of technology, ota, nigeria and centre for economic policy and development research (cepder), covenant university, ota, nigeria, 2department of accountancy, covenant university, ota, nigeria, 3research and consultancy centre, college of management and information technology, american international university, west africa, the gambia, 4academic planning unit and centre for economic policy and development research (cepder), covenant university, ota, nigeria, 5department of business and entrepreneurship, kwara state university, malete, nigeria, 6department of economics and development studies and centre for economic policy and development research (cepder), covenant university, ota, nigeria. *email: aderemi.timothy@gmail.com received: 07 january 2020 accepted: 22 april 2021 doi: https://doi.org/10.32479/ijeep.8488 abstract this study's main objective is to examine the roles of human capital development, energy consumption and crude oil exports in driving sustainable development goal 8-sustainable economic growth in nigeria. annual data from 1990 to 2018 were sourced from world data atlas, international energy agency, wdi and the central bank of nigeria statistical bulletin respectively to achieve the aims of the study. autoregressive distributed lag technique of estimation was adopted for the data analysis. consequently, the principal findings of this study could be presented as follows; there exists an insignificant positive relationship between electricity power consumption and real gdp growth rate. this implies that energy consumption in nigeria has an inadequate capacity to drive a sustainable economic growth. similarly, oil exports and the growth rate of the real gdp have a significant positive relationship with each other. this means that sustainability of economic growth is highly dependent on oil exports in nigeria. conversely, government expenditure on educational sector and the growth rate of real gdp have a significant negative relationship with each other. likewise, expenditure of government on health sector has an insignificant negative relationship with the growth rate of the real gdp. this implies that human capital development in nigeria lacks the capacity to guarantee a sustainable economic growth. as a result of the outcome of this research, the following were recommended for nigerian policymakers and by extension developing countries, any time the goal of these policymakers are sustainable economic growth, the development of human capital through adequate funding of educational and health sectors should be embarked upon. in the same vein, the policymakers should provide uninterrupted electricity supply for enhancement of maximum outputs in the country. keywords: human capital, energy consumption, oil exports, sustainable development goals jel classifications: l94, f63, i15, i25 1. introduction the quest to create economic prosperity and protect environment in the world, especially in developing economies led to the introduction of the agenda 2030the sustainable development goals (sdgs) by the united nations (united nations, 2015). this has generated global commitment among developing countries towards building a sustainable economic growth. meanwhile, the basic argument of the endogenous growth model revolves around human capital as an indispensable driving force behind economic growth and development (galor and weil, 2000; mankiw et al., 1992; lucas, 1988). the efficient usage of human capital which is domiciled in education and health in one hand, and electricity and icts in other hand has been identified as a catalyst for economic this journal is licensed under a creative commons attribution 4.0 international license aderemi, et al.: human capital development, energy consumption and crude oil exports in nigeria: implications for sustainable development international journal of energy economics and policy | vol 11 • issue 4 • 2021444 productivity (ejemeyovwi et al., 2018; todaro and smith, 2003). investment in human beings is a critical issue in nigeria. despite the fact that nigeria is extremely blessed with the abundance of both human and natural resources, the economy has not been able to come to the global limelight. in the recent times, the country`s human development index is ranked 161 out of 189 nations (undp, 2019). this shows that nigeria is extremely lagging behind in building human capacity for a competitive economy. similarly, nigeria is regarded as the 13th least stable state globally based on the submission of the fragile states index (messner, 2017). similarly, in the past four decades, source of power in nigeria has undergone various metamorphosis ranging from the oil-fired, gas-fired, coal-fired station, and later graduated to hydroelectric power stations using gas-fired systems, in which hydroelectric power systems occupying the front burner (ajumogobia and okeke, 2015). building a sustainable growth in any economy requires a stable power supply. therefore, a country like nigeria, which heavily relies on crude oil exports, energy utilization cannot be undermined. the major inputs in this sector in nigeria are electricity and crude oil. it is important to stress that the power generated from energy sources such as electricity and crude oil are the bedrocks for the other services in deriving economic growth (onakoya et al., 2013). this assertion is also reinforced with the submission, that economic development in majority of countries is propelled by the efficient utilization of energy system (osabohien et al., 2019; lu, 2017; alege et al., 2017). in terms of energy supply, crude oil has been the principal source of commercial energy in nigeria, which supplies over 70% of national commercial energy consumption, and at the same time generates over 80% of foreign earnings through exports in the past four decades (cbn, 2017; nbs, 2006). and such, production becomes a mirage without energy consumption. consequently, solving developmental issues requires a holistic approach. though, studies have argued that both accessibility and consumption of quality electric power are fundamental variables that drive socio-economic development (alaali et al., 2015; george and oseni, 2012). on the other hand, as the global economy is continuously becoming integrated as a result of digital technologies, human capital development becomes an indispensable input for economic development in the long run (ejemeyovwi et al., 2018; barro and sala-i-martin, 1995; romer, 1986; lucas, 1988). in the recent times, the issues surrounding the sustainable development is very critical in nigeria, and requires urgent empirical studies. in the past few decades, unemployment and poverty have been a continuous social monster in nigeria (olotu et al., 2015; akwara et al., 2013). for instance, the unemployment rate in nigeria rose from 10.57% in 2012 to 22.56% in 2018 (imf, 2019). in the same vein, nigeria occupies the 6th rank among the global crude oil exporters, the country is still world`s poverty headquarters in the recent time (aderemi et al., 2020; adebayo, 2018; world poverty clock, 2018). it is worth noting that the past empirical studies have been silenced regarding the influence of both human capital development and energy consumption using electricity consumption and crude oil exports on the sustainable development goal 8sustainable economic growth in nigeria. few of the recent studies which focused on the nexus between energy consumption, human capital development and other macroeconomic variables in nigeria have failed to explore sustainable economic growth and oil exports as principal variables in their methodologies. see orji et al., 2020; afolayan et al., 2019; matthew et al., 2018; ejemeyovwi et al., 2018). nigeria is heavily relied on crude oil exports as means of its survival and such, crude oil occupies a strategic portion of energy consumption in the country, which should not be undermined. as a departure from the existing bodies of knowledge, this study has been designed to examine the impact of human capital development and energy consumption on sdgs goal 8 – sustainable economic growth in nigeria in which past studies have not fully explored in the country. the arrangement of this study is done as thus; foundation of the study was laid in the introduction. meanwhile, the second section presents the past empirical studies about the subject matter of the study. section three shows methodology, analysis of data, summary of results and the policy implications of the study. 2. review of literature due to the strategic roles in which energy consumption plays in driving economic activities in any country, there has been a rise in the recent studies around the relationship between energy consumption and other macroeconomic variables in both developing and developed economies. for instance, in south africa, adeola and aziakpono (2017) examined how electricity consumption propelled economic growth of the country with the application of the trivariate causality analysis. the study submitted that a bidirectional causality existed between the consumption of electricity and economic growth in the country. orji et al., (2020) explored the classical linear regression model to investigate the nexus between information and communication technology (ict), power supply and human capital development within the context of the nigerian economy. it was discovered from the study that that ict and power supply caused a positive impact on human capital development in nigeria. in another related study, matthew et al., (2018) utilized fully modified ordinary least squares to examine the linkage between human capital development, electricity power consumption and economic growth in nigeria between 1981 and 2016. it was discovered from the study that human capital development and economic growth were insignificantly related in nigeria. but the case of electricity consumption and economic growth showed otherwise. osabohien et al. (2021) explored ardl to analyze the impact of carbon emissions on life expectancy in nigeria. the authors posited that inter alia and carbon emissions caused a significant negative effect to life expectancy in the country. afolayan and aderemi (2019) investigated environmental impact of energy consumption on human welfare from 1980 to 2016 in nigeria, adopting dynamic ordinary least square (dols) and granger causality techniques. the authors discovered a negative but insignificant impact of emissions of co2 on mortality rate in nigeria. meanwhile, the consumption of electric power and combustion of fossil fuel caused a significant rise in mortality rate in the country. similarly, lin and linh (2015) employed a technique of dynamic causal analysis in investigating how degradation of environment, consumption of energy, foreign direct investment (fdi) and economic growth were related with the case study of 12 densely aderemi, et al.: human capital development, energy consumption and crude oil exports in nigeria: implications for sustainable development international journal of energy economics and policy | vol 11 • issue 4 • 2021 445 populated economies in asia. it was argued from the study that a causal relationship existed between co2 emissions, fdi, economic growth and energy consumption those countries. in another study, olaoye et al., (2020) applied cointegration, dols and granger causality techniques to evaluate how consumption of energy facilitated foreign direct investment between 1990 and 2017 in nigeria. the authors submitted that energy consumption discouraged the inflows of fdi in the country in a significant way. however, energy consumption significantly favored oil exports in the country. the results of granger causality analysis showed that one-way feedback runs from energy consumption to exports of oil. while exploring the technique of ardl alongside co-integration analysis, dantama et al., (2012) assessed the nexus between economic growth and energy consumption in nigeria. it was discovered from the study that there existed a long run convergence between electricity and petroleum consumption and economic growth. conversely, the long run estimate indicated that consumption of coal and economic growth had an insignificant relationship with each other. however, afolayan et al. (2019) explored johansen co-integration technique to examine the contribution of electricity consumption alongside human capital towards reduction of unemployment in nigeria. the authors posited that consumption of electricity and unemployment had an inverse relationship. xu et al., (2016) researched the linkage that exists between energy consumption and fdi shanghai within the period of 1991 and 2013. the authors argued that in the short run, energy consumption catalyzed a significant inflows of fdi in the country. whereas, an insignificant effect of energy consumption on fdi was recorded in the long run. in the same vein, energy consumption granger caused fdi in the country. while investigating how crude oil supported economic growth in nigeria between 2000 and 2009, usman et al., (2015) utilized a simple linear regression to opine that crude oil has immensely propelled the nigerian economic growth in both positive and significant way. in another perspective, ogujiuba (2017) investigated human capital investment and economic growth nexus in nigeria within a framework of error correction model (ecm) and granger causality. the author asserted that there was an absence of a causal relationship between human capital development and the growth of the nigerian economy. doytch and narayan (2016) employed the blundell–bond dynamic panel estimator while assessing the contribution of fdi towards renewable and non-renewable energy consumption from 1985 to 2012 across seventy-four countries. the authors submitted that the employment of green energy was connected with fdi inflows and fdi inflows retarded the employment of non-renewable energy in both developing and advanced countries. 3. data and material 3.1. theoretical framework this work is anchored on the endogenous growth theory put forward by romer in 1986. this theory was developed in reaction to the shortcomings of the neoclassical (exogenous) growth model which was championed by solow. the basic argument of endogenous model is that human capital is an indispensable input in the production function. therefore, the sustainable growth is facilitated by endogenizing technical progress. in the recent version of the model, economic growth was driven by innovation which was domiciled in investment in human and technical improvement (mankiw et al., 1992; ncube, 1999; lucas, 1988). it is important to stress that the major assumptions upon which the theory rotate are as follows; increasing returns to scale due to positive externalities. human capital (knowledge, skills and training possessed by individuals) and the production of new technologies are crucial variables for growth in the long run. in the same vein, private investment in research and development is the most viable origin of progressive technologies. and knowledge or technical advances are posited to be non-rival good. 3.2. model specification utilizing energy economics approach to empirically address the relevance of endogenous human capital theory in nigeria provides a justification for the indispensable roles of energy such as electricity and crude oil as inputs in production process that could ensure economic development (alaali et al., 2015; stern, 2011; lee and chang, 2008). it is worth of note that investments in education and health were keenly argued by the endogenous theorists as sufficient inputs needed to build human capital that could adequately propel the productive capacity of a nation (romer, 1986; lucas, 1988; barro and sala-i-martin, 1995). consequently, input-output analysis like this study requires the utilization of the cobb douglas production function which could be stated in a modified version as thus; ecg = ecnα1.gcapα2. eduα3. hetα4. oexpα5 (1) if the log of independent variables is taken in the above equation, it results in linearization of the equation as follows; ecgt = α1logecnt+α2loggcapt+α3logedut+ α4loghett+ α5logoexpt+ u (2) 3.3. sources of data electric power consumption data were extracted from world data atlas and international energy agency, iea respectively. in the same vein, other macroeconomic data were sourced from wdi and the statistical bulletin of the central bank of nigeria. 3.4. estimation technique the pre-estimation of data gave us an insight about the appropriate estimation technique to utilize in this study. it was discovered that the relevant variables of interest were a mixture of i(0) and i(1), in such a situation, an autoregressive distributed lag model had been argued in the literature to be the most relevant technique of the data analysis (pesaran et al., 2001; pesaran and pesaran, 1997). therefore, it is instructive to state that the short run ardl model could be specified as follows; � � � � ecg ecg lngcap lnedu t i p t i p t i p t � � � � � � � � � � � � � � � � � 1 1 2 1 0 3 1 0 4 1 �� � � � � � �� � i p t i p thet oexp 0 5 1 0 6 1 � �� � u (3) aderemi, et al.: human capital development, energy consumption and crude oil exports in nigeria: implications for sustainable development international journal of energy economics and policy | vol 11 • issue 4 • 2021446 meanwhile, ecg is used to proxy growth rate of real gdp. this measures sustainable economic growth, which is one of the key goals of sustainable development. and this is measured in percentage. ecn represents electric power consumption in nigeria, which is used to proxy energy consumption in the country. this is measured in kilowatt-hour (kwh) per capita. gcap is used to denote gross fixed capital formation. edu is used to denote the expenditure of government on educational sector. het captures government expenditure on health sector, oexp is crude oil exports, t is the period of analysis which spans between 1990 and 2018 and u is error term. it is expected that β2 β3 β4, β5 and β6 > 0. 4. results and discussion the descriptive statistic of the various variables of interest were shown in the table 1. the importance of this distribution lies in the fact that econometric analysis is largely dependent on the assumption of the normal distribution of the dataset. ecg which is used to proxy the growth rate of real gdp in nigeria from 1990 to 2018 possessed maximum and minimum values of 33.7% and −1.6% respectively. its mean value is 5.2% and standard deviation of 6.5%. the mean value is less than the standard deviation of the variable. this implies that growth rate dispersed widely from its mean value. similarly, the variable has a positive skweness with the kurtosis value that is very far from 3. this means that the data for this variable did not agree with the symmetrical distribution assumption. however, other variables of interest such as electricity power consumption, gross fixed capital formation, government expenditures on education and health and oil exports, all in log form agreed with the symmetrical distribution assumption. this is because the distribution their data dispersed moderately from the mean value. in the same vein, the data possessed a positive skeweness with kurtosis value greater very close to 3. since the majority of the data employed for the analysis of the relationship between the variables of interest agreed with symmetrical distribution assumption. hence, the data could be further used for econometric analysis. one of the pre-estimation check that cannot be undermined in empirical study that involves time series data is test for the stationarity properties of such data. this test becomes highly imperative because time series data could result in spurious or nonsense regression if its usual unit root problem is not resolved. against this backdrop, it is important for this study to utilize the technique of the standard dickey and fuller (adf) test by dickey and fuller (1981) and phillips and perron (pp) test by phillips and perron (1988) in estimating the stationarity properties of the series. consequently, as shown in table 2, it is only growth rate that is stationary at level while other variables are stationary after first differencing. this indicates that the study utilized data that contain both i(0) and i(1) in this regard. examining the long run relationship between human capital development, energy consumption, oil exports and sustainable growth becomes very important while utilizing ardl model. this is done within the framework of ardl bounds test. and as shown in the table 3, there was no long run relationship existing these variables in nigeria because the value of f-statistic is less than the upper critical value bounds at all levels of significance. therefore, this study embarked upon the estimation of short run model. regression estimates of the ardl model of the short run relationship between human capital development, sustainable economic growth, energy consumption and oil exports in nigeria were presented in table 4. meanwhile, variables such as lagged value of growth rate of the real gdp, both government expenditures on education and health sectors did not follow the aprori expectation. looking at the result of the r-square which is 0.69, it shows that 69% of the variation in the dependent variable was explained by the set of explanatory variables. consequently, growth rate of the real gdp in the previous period has a negative and significant relationship with its value in the current period. gross fixed capital formation has a positive relationship with the growth rate of real gdp, though the relationship is significant at 10% level of significance. and such, a unit change in gross fixed capital formation brings about 0.33% increment in the growth rate of the real gdp. electricity power consumption and growth rate of the real gdp has a positive but insignificant relationship with each other. this implies that energy consumption in nigeria has an inadequate capacity to ensure a sustainable economic growth in the country. this finding is in tandem with the submissions of matthew et al., (2018), dantama et al., (2012) and odularu and okonkwo (2009) in related studies in nigeria despite the adoption of different technique of estimation. in the same vein, oil exports have a positive relationship with the growth rate of the real gdp, the relationship is significant at 10% table 1: descriptive statistics of variables descriptive statistics ecg logecn loggcap logedu loghet logoexp mean 5.217857 4.507481 3.262271 4.550421 3.451071 7.757026 median 4.350000 4.586281 3.275948 4.961152 3.998619 7.888767 maximum 33.70000 5.054525 3.972554 6.807382 5.041531 9.569636 minimum −1.600000 3.237109 2.651127 0.289789 0.399916 4.669084 std. deviation 6.521989 0.499669 0.438191 1.949267 1.497924 1.566498 skewness 0.070353 0.585916 0.071567 0.588159 0.688038 0.618490 kurtosis 14.19066 4.879102 1.590305 2.262278 2.152018 2.184793 jargue-bera 1.900958 1.585680 2.342348 2.249281 3.048100 2.560464 probability 0.000000 0.000360 0.310003 0.324769 0.217828 0.277973 sum 146.1000 126.2095 91.34358 127.4118 96.62999 217.1967 sum. sq. deviation 1148.481 6.741059 5.184312 102.5904 60.58199 66.25574 observation 28 28 28 28 28 28 source: authors’ aderemi, et al.: human capital development, energy consumption and crude oil exports in nigeria: implications for sustainable development international journal of energy economics and policy | vol 11 • issue 4 • 2021 447 level of significant. a unit change in oil exports in nigeria brings about 0.06% rise in the growth rate of the real gdp in the country. this implies that economic growth sustainability of nigeria is highly dependent on oil exports in the short run. this finding is supported by the argument of usman et al., (2015) in a similar work. whereas, the findings of idowu (2016), and baghebo and atima (2013) contradict the finding in this study. however, government expenditure on education sector has a significant negative relationship with the growth rate of the real gdp. a unit change in government expenditure on education sector brings about 0.07% reduction in the growth rate of the real gdp. similarly, expenditure of government on health sector has a negative but insignificant relationship with the growth rate of the real gdp. the implication of these results is that human capital development in nigeria lacks the capacity to ensure a sustainable economic growth in the short run. the reason for these results might have been as a result of persistent low government expenditures on education and health sectors in the past decades in nigeria. the finding in this study corroborates the assertion of ogujiuba (2017) in a related study. 5. conclusion and recommendation this study has examined the roles of human capital development, energy consumption and crude oil exports in driving one of the key goals of sustainable development-sustainable economic growth in nigeria. to achieve this, the authors utilized annual data from 1990 to 2018 with adoption of ardl as a technique of estimation. consequently, the findings of this research work could presented as follows; growth rate of the real gdp in the previous period has a negative and significant relationship with its value in the current period. this means that past economic growth rate has a negative implication for future economic growth rate in nigeria. gross fixed capital formation has a significant positive relationship with the growth rate of real gdp. but, electricity power consumption and growth rate of the real gdp has an insignificant positive relationship with each other. the implication of this is that energy consumption in nigeria has an inadequate capacity to drive a sustainable economic growth in the country. similarly, oil exports have a significant positive relationship with the growth rate of the real gdp. this means that economic growth sustainability of nigeria is highly dependent on oil exports in the short run. conversely, government expenditure on education sector has a significant negative relationship with the growth rate of the real gdp. also, expenditure of government on health sector has a negative but insignificant relationship with the growth rate of the real gdp. this implies that human capital development in nigeria lack the capacity to ensure a sustainable economic growth in the short run. this might have been an aftermath effect of the low funding of educational and health sectors by the nigerian government as against the stipulation of both the united nations and the abuja declaration of 2001, advocating for adequate funding of educational and health sectors in developing countries respectively. in view of the above, this study makes the following recommendations for table 2: unit root test variables adf test remark level probability 1st diff probability ecg −2.971853*** 0.0021 i(0) logecn −2.976263*** 0.7476 −2.981038*** 0.0004 i(1) loggcap −2.971853*** 0.4541 −2.976263*** 0.0033 i(1) logedu −2.998064*** 0.0514 −2.976263*** 0.0000 i(1) loghet −2.976263*** 0.1387 −3.699871*** 0.0000 i(1) logoexp −2.971853*** 0.2226 −2.976263*** 0.0003 i(1) variables pp test level probability 1st diff probability ecg −2.971853*** 0.0019 i(0) logecn −2.976263*** 0.6432 −2.976263*** 0.0004 i(1) loggcap −2.971853*** 0.4423 −2.976263*** 0.0043 i(1) logedu −2.971853*** 0.4277 −2.976263*** 0.0000 i(1) loghet −2.971853*** 0.3049 −2.976263*** 0.0000 i(1) logoexp −2.971853*** 0.2226 −2.976263*** 0.0003 i(1) source: authors’ table 3: ardl bounds test sample: 1992 2018 included observations: 26 null hypothesis: no long-run relationships exist test statistic value k f-statistic 3.504168 5 critical value bounds significance i0 bound i1 bound 5% 2.62 3.79 source: authors’ table 4: short-run relationship between sustainable economic growth, energy consumption and oil exports short run coefficient t-statistics prob. value d(ecg(−1) −0.477846*** 2.263169 0.0448 d(logecn) 6.076747 1.423604 0.1823 d(loggcap) 33.98703** 1.894816 0.0847 d(logedu) −7.325124*** 2.352332 0.0383 d(logoexp) 6.367070** 1.815102 0.0968 d(loghet) −1.903102 0.520278 0.6132 r-squared 0.695455 source: authors’. *significant at 1% ***significant at 5% **significant at 10% aderemi, et al.: human capital development, energy consumption and crude oil exports in nigeria: implications for sustainable development international journal of energy economics and policy | vol 11 • issue 4 • 2021448 the policymakers in nigeria and by extension developing countries, any time the goal of these policymakers are sustainable economic growth the development of human capital through adequate funding of educational and health sectors should be embarked upon. in the same vein, the policymakers should provide uninterrupted electricity supply for enhancement of maximum outputs in the country. 6. acknowledgments the authors of this paper would like to acknowledge the support of the covenant university centre for research, innovation, and development (cucrid) in the course of this study, the financial supports are highly recognized. in the same vein, the authors declare no conflict of interest with anyone. references adebayo, b. (2018), nigeria overtakes india in extreme poverty ranking. available from: https://www.edition.cnn.com/2018/06/26/ africa/nigeria-overtakesindiaextreme-poverty-intl/index.html. [last accessed on 2018 dec 21]. adeola, o., aziakpono, m. (2017), the relative contribution of alternative capital flows to south africa: an empirical investigation. journal of economic and financial sciences, 8(4), 12-28. aderemi, t.a., amusa, b.o., elufisian, o.o., abalaba, b.p. (2020), does capital flight move nigeria to the world’s poverty headquarters? an implication for sustainable development. journal of academic research in economics, 12(1), 31-44. afolayan, o.t., aderemi, t.a. (2019), environmental quality and health effects in nigeria: implications for sustainable economic development. ssrg international journal of economics and management studies, 6(11), 44-55. afolayan, o.t., okodua, h., matthew, o., osabohien, r. (2019), reducing unemployment malaise in nigeria: the role of electricity consumption and human capital development. international journal of energy economics and policy, 9(4), 63-73. ajumogobia, h.o., okeke, c.n. (2015), nigerian energy sector, legal and regulatory overview, lagos. akwara, a.f., akwara, n.f., enwuchola, j., adekunle, m., udaw, j.e. (2013), unemployment and poverty: implications for national security and good governance in nigeria. international journal of public administration and management research, 2(1), 1-11. alaali, f., roberts, j., taylor, k. (2015), the effects of energy consumption and human capital on economic growth: an exploration of oil exporting and developed countries. in: sheffield economic research paper series no. 2015015. united kingdom: the university of sheffield. alege, p.o., oye, q.e., adu, o.o., amu, b., owolabi, t. (2017), carbon emissions and the business cycle in nigeria. international journal of energy economics and policy, 7(5), 1-8. baghebo, m., atima, t.o. (2013), the impact of petroleum on economic growth in nigeria. global business and economics research journal, 2(5), 102-115. barro, r., sala-i-martin, x. (1995), economic growth. new york: mcgraw-hill. cbn. (2017), statistical bulletin. nigeria: central bank of nigeria. dantama, y.u., umar, y., abdullahi, y.z., nasiru, i. (2012), energy consumption-economic growth nexus in nigeria: an empirical assessment based on ardl bound test approach. european scientific journal, 8(12), 141-157. dickey, d.a., fuller, w.a. (1981), likelihood ratio tests for autoregressive time series with a unit root, econometrica, 49, 1057-1072. doytch, n., narayan, s. (2016), does fdi influence renewable energy consumption? an analysis of sectoral fdi impact on renewable and non-renewable industrial energy consumption. energy economics, 54, 291-301. ejemeyovwi, j.o., osabuohien, e.s., osabohien, r. (2018), ict investments, human capital development and institutions in ecowas. international journal of economics and business research, 15(4), 463-474. galor, o., weil, d.n. (2000), population, technology and growth: from malthusian regime to the demographic transition. american economic review, 90(4), 806-828. george, e.o., oseni, j.e. (2012), the relationship between electricity power and unemployment rates in nigeria. australian journal of business and management research, 2(2), 10-19. idowu, r. (2016), analysis of the effects of oil and non-oil export on economic growth in nigeria. imf. (2019), world economic outlook. washington, dc: international monetary fund. lee, c.c., chang, c.p. (2008), energy consumption and economic growth in asian economies: a more comprehensive analysis using panel data. resource and energy economics, 30(1), 50-65. linh, d.h., lin, s. (2015), dynamic causal relationships among co2 emissions, energy consumption, economic growth and fdi in the most populous asian countries, advances in management and applied economics, 5(1), 69-88. lu, w.c. (2017), greenhouse gas emissions, energy consumptions and economic growth: a panel co-integration analysis for 16 asian countries. international journal of environmental research and public health, 14(11), 1436. lucas, s.r. (1988), the mechanics of economic development. journal of monetary economics, 22(1), 30-42. mankiw, n., romer, p., weil, d. (1992), a contribution to the empirics of economic growth. a quarterly journal of economics, 107, 407-437. matthew, o.a., ede, c.u., osabohien, r., ejemeyovwi, j., fasina, f.f., akinpelumi, d. (2018), electricity consumption and human capital development in nigeria: exploring the implications for economic growth. international journal of energy economics and policy, 8(6), 8-15. messner, j.j. (2017), 2017 fragile states index, fund for peace. national bureau of statistics. (2006). published by national bureau of statistics, nigeria. ncube, m. (1999), is human capital important for economic growth in zimbabwe? african journal of economic policy, 7(3), 1-14. odularu, g.o., chinedu, o. (2009), does energy consumption contribute to economic performance? empirical evidence from nigeria. journal of economics and international finance, 1(2), 44-58. ogujiuba, k. (2017), the impact of human capital formation on economic growth in nigeria. journal of economics, 2(1), 24-40. olaoye, o.p., aderemi, t.a., nwagwu, c.j., yvonne, j.o., azuh, d.e. (2020), energy consumption and foreign direct investment inflows in nigeria: an empirical perspective. international journal of energy economics and policy, 10(2), 1-6. olotu, a., salami, r., akeremale, i. (2015), poverty and rate of unemployment in nigeria. ijm, 2(1), 1-4. onakoya, a.b., onakoya, a.o., jimi-salami, o.a., odedairo, b.o. (2013), energy consumption and nigerian economic growth: an empirical analysis. european scientific journal, 9(4), 25-40. orji, a., ogbuabor, j.e., anthony-orji, o.i., okoro, c., osondu, d. (2020), analysis of ict, power supply and human capital development in nigeria as an emerging market economy studia universitatis-vasile goldis arad. economics series, 30(4), 55-68. osabohien, r., aderemi, t.a., akindele, d.b., jolayemi, l.b. (2021), aderemi, et al.: human capital development, energy consumption and crude oil exports in nigeria: implications for sustainable development international journal of energy economics and policy | vol 11 • issue 4 • 2021 449 carbon emissions and life expectancy in nigeria. international journal of energy economics and policy, 11(1), 497-501. osabohien, r., matthew, o., aderounmu, b., olawande, t. (2019), greenhouse gas emissions and crop production in west africa: examining the mitigating potential of social protection. international journal of energy economics and policy, 9(1), 57-66. pesaran, h.m., shin, y., smith, r.p. (2001), bounds testing approaches to the analysis of level relationship. journal of applied econometrics, 16, 289-326. pesaran, m., pesaran, b. (1997), microfit 4.0 (windows version), new york: oxford university press inc. phillips, p.c., perron, p. (1988), testing for a unit root in time series regression. biometrika, 75, 335-346. romer, p.m. (1986), increasing returns and long-run growth. journal of political economy, 94(5), 1002-1037. stern, d.i. (2011), the role of energy in economic growth. ecological economics reviews, 1219(1), 26-51. todaro, m.p., smith, s. (2003), human capital: education and health in economic development. india: pearson education limited. undp. (2019), human development report. new york: undp. united nations. (2015), millennium development goals report, united nations. usman, a., madu, i., abdullahi, f. (2015), evidence of petroleum resources on nigerian economic development (2000-2009). business and economics journal, 6(2), 1-4. world poverty clock. (2018), available from: https://www.worldpoverty. io/headline. xu, j., zhou, m., li, h. (2016), ardl based research on the nexus among fdi, environmental regulation and energy consumption in shanghai (china). natural hazards, 81(1), 551-564. . international journal of energy economics and policy | vol 9 • issue 4 • 201930 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(4), 30-39. integrating sustainable maintenance into sustainable manufacturing practices and its relationship with sustainability performance: a conceptual framework yousif munadhil ibrahim*, norsiah hami, siti norezam othman school of technology management and logistics, college of business, universiti utara malaysia, kedah, sintok, 06010, malaysia. *email: yousifmonadhil58@gmail.com received: 16 february 2019 accepted: 10 may 2019 doi: https://doi.org/10.32479/ijeep.7709 abstract it appears that companies’ interest in achieving economic returns has made them neglect the environmental and social effects of their activities. with this imbalance in sustainability performance (sp) that causes environmental pollution and social damage, there is an urgent need to strike a balance between economic, environmental and social sustainability. therefore, this study aims to achieve this balance in sp by providing a proposed framework that integrates sustainable maintenance (sma) into sustainable manufacturing practices (smps). effective adoption of smps and sma has a significant positive influence on sp. nevertheless, there are limited studies conducted on integrating sma into smps and how it could impact sp. the theoretical contribution of the present study depends mainly on expanding existing knowledge about highlighting the moderating role of sma on the relationship between smps and sp, including in the oil and gas industry. keywords: sustainability performance, sustainable manufacturing practices, sustainable maintenance, oil and gas industry jel classifications: q52, q56, q58, q380 1. introduction sustainability performance (sp) is a key issue and a major concern in the oil and gas industry (o&gi) in iraq. this is due to the lack of balance between the dimensions of sp (i.e., economic, environmental and social). for instance, opec (2018) noted in the annual statistical bulletin, in 2017, the value of iraqi oil exports amounted to usd 63314 million, equivalent to 33% of the gdp which is valued at usd 191216 million. by the same token, the report of the escwa reported for the same year, the proportion of iraqi exports of oil equivalent to 99% of the total annual exports (un-escwa, 2018). this establishes the significant role of this industry in the development of the iraqi economy. nevertheless, the o&gi considers the major contributor to environmental pollution and social damage (elhuni and ahmad, 2017). indeed, to illustrate, because of their complexity and volume, the o&gi has major impacts of environmental, health and safety worldwide (schneider et al., 2013; schneider et al., 2011). besides, particulate matter and volatile compounds of filters in oil and gas companies cause many diseases, both for workers and the community in the same area, such as cancer diseases and respiratory diseases (epa, 2003). according to the compensation committee in the iraqi ministry of oil, the number of occupational accidents, including diseases due to work for 2017, which paid compensation to workers in the oil sector is 703 cases until september (imo, 2017). furthermore, the central locations for the exploration and production of oil and gas in iraq, 70% of them contain environmental pollution issues and include regions such as baghdad, basra, kirkuk, maysan, salah al-din and mosul (al-haleem et al., 2013). this journal is licensed under a creative commons attribution 4.0 international license ibrahim, et al.: integrating sustainable maintenance into sustainable manufacturing practices and its relationship with sustainability performance: a conceptual framework international journal of energy economics and policy | vol 9 • issue 4 • 2019 31 in addition to the above, and through literature review, studies confirmed that the sustainability of companies requires taking environmental and social effects in consideration in addition to the economic side and balance it (annunziata et al., 2013; ashrafi, 2014; carley et al., 2014; cavagnaro and curiel, 2012; christen et al., 2006; dao et al., 2011; elkington, 1997; 1999; 2004; hami, 2015; hassan et al., 2015; parida and kumar, 2010; shukla et al., 2017; székely and knirsch, 2005; venkatraman and nayak, 2015), including the o&gi (anis and siddiqui, 2015; liyanage, 2007; liyanage et al., 2009; schneider et al., 2011). however, the study of the dimensions of sp which includes economic, environmental and social from a comprehensive and balanced perspective in practical implementation is still missing (garetti and taisch, 2012; león and calvo-amodio, 2017), including in the o&gi (anis and siddiqui, 2015). subsequently, this study is interested in studying of sp the economic, environmental and social to address the issue of research, which aims to help o&gi to balance the three dimensions of sp in the context of iraq. the vital question that arises is about how to address the issue of research about balance the dimensions of economic, environmental and social sustainability. in this respect, sustainable manufacturing practices (smps) have not been widely studied and documented by researchers (alayón et al., 2017; despeisse et al., 2012; roberts and ball, 2014). additionally, several empirical evidence suggests that smps contribute to improved economic, environmental and social sustainability (e.g., abdul-rashid et al., 2017a; abdulrashid et al., 2017b; gimenez et al., 2012; habidin et al., 2013; hami, 2015; hami et al., 2016; hartini and ciptomulyono, 2015; shubham et al., 2018; zubir et al., 2012). therefore, there is a necessary need to study smps as they will contribute to addressing the practical issue of sp in the o&gi in iraq. furthermore, a number of studies established that maintenance leads to improved performance (ahuja and khamba, 2008; 2009; al-najjar and alsyouf, 2004; alsyouf, 2007; hamzah, 2011; hooi and leong, 2017; kaur et al., 2012; löfsten, 1999; maletič et al., 2014; mohamed and valérie, 2016; vassu and lazim, 2016). frank et al. (2016) concluded in their study in the o&gi that maintenance significantly affects economic, environmental and social performance. similarly, baluch et al. (2010) showed that maintenance enhances the company’s competitiveness and improves its performance of economic, environmental and social. also, maintenance activities have significant impacts on the company’s economic, social and environmental performance (chiang et al., 2014; liyanage et al., 2009). moreover, according to pires et al. (2016) in previous studies rarely considered the four dimensions which involve economic, technical, environmental and social and safety in maintenance. amrina and aridharma (2016) pointed to the need to study sustainable maintenance (sma). zhang et al. (2017) stressed that literature in sma is the most limited. similarly, ararsa (2012) noted that studies on sma are still in infancy. however, many companies still do not have a full understanding of the importance of effective maintenance activities and their significant role in achieving sp (liyanage and badurdeen, 2010). additionally, franciosi et al. (2018); and pires (2015) recommended through their systematic review that more research should be conducted on the impact of maintenance on sp. similarly, seychelles (2017) suggested further investigation on the relationship between maintenance and sp. therefore, there are two main reasons for investigating in sma: first, theoretically, to bridge the gap in the literature and the second reason practically, because it will contribute to addressing the practical issue of sp in the o&gi in iraq. in fact, companies that have an interest in smps are more inclined to adopt sma (ararsa, 2012; franciosi et al., 2018; garetti, 2011; garetti and taisch, 2012; granados, 2014; ighravwe and oke, 2017b; jasiulewicz-kaczmarek, 2013a; liyanage, 2007; liyanage and badurdeen, 2010; stuchly and jasiulewicz-kaczmarek, 2014). this is because they have the same goal of improving sp (abdul-rashid et al., 2017b; abdullah et al., 2017; adebambo et al., 2015a; alayón et al., 2017; baluch et al., 2010; chiang et al., 2014; frank et al., 2016; habidin et al., 2013; hami, 2015; hami et al., 2016; liyanage et al., 2009). besides, many studies have examined the relationship between smps and sp (abdul-rashid et al., 2017a; 2017b; abdullah et al., 2017; adebambo et al., 2014; 2015b; adebanjo et al., 2016; das, 2018; esfahbodi et al., 2017; gimenez et al., 2012; habidin et al., 2013; hami et al., 2016; hami et al., 2015; luthra and mangla, 2018; roni et al., 2014; zubir et al., 2012). however, sma has not been given any consideration in their studies. accordingly, to the best of the knowledge of the authors, surprisingly, the moderating effects of sma are ambiguous and have not been closely studied in any previous study. this gap points to the need for a theoretical framework to investigate the moderating impacts of sma on the relationship between smps and sp. therefore, this study aims to encourage the o&gi to achieve a balance in the dimensions of economic, environmental and social sustainability by providing a proposed framework that integrates sma into smps. the results of the current study are expected to benefit many aspects in different areas. academicians will obtain a better perception of the importance of integrating sma into smps to achieve a balance in the dimensions of economic, environmental and social sustainability. additionally, policymakers and top management in the o&gi will gain a better understanding on how to balance the sp dimensions, based the focus on smps and sma. the present study contains two sections viz.; following this introductory section is section 2, the conceptual framework which provides insights from empirical literature and theoretical framework about smps, sma and sp, followed by section 3, which involve conclusions of this study. 2. literature review and development of model 2.1. smps smps have gained vital importance over the past few years. adebanjo et al. (2016) noted that there is a growing interest worldwide in the implementation of sustainable management practices. also, interest in sustainable practices has increased ibrahim, et al.: integrating sustainable maintenance into sustainable manufacturing practices and its relationship with sustainability performance: a conceptual framework international journal of energy economics and policy | vol 9 • issue 4 • 201932 as a result of grown interest in sustainable manufacturing sm over the years (alayón et al., 2017). in other words, sm plays a significant role in manufacturing companies, and smps contribute to creating the right environment for companies (gupta et al., 2015). it is because of linking the operations and decisions of industrial companies to environmental and social factors related to their activities (cerinšek et al., 2013). smps have become a required necessity expected from all industries (habidin et al., 2013), and companies should prefer to implement them (nordin et al., 2014), as they lead to overcoming the challenges, they face in the industry (yucel and gunay, 2013). there is increasing pressure on companies in all sectors by society, clients and other stakeholders to apply smps (nordin et al., 2014). these pressures came as a result of the environmental effects of manufacturing practices through the inefficient use of resources, increased emissions and wastes, posing a significant threat to the global ecosystem and the welfare of society (al-ashaab et al., 2013). which led to awareness and interest in smps by manufacturers (habidin et al., 2016). accordingly despeisse (2013) defined smps as “an action or set of actions improving the manufacturing system’s environmental performance.” previously, manufacturing companies focused on the volume of profits realized regardless of the environmental impact of their activities (al-ashaab et al., 2013). whereas, at present, it is necessary to use environmentally friendly practices in manufacturing to eliminating their harmful effects on the environment (nordin et al., 2014). in addition to minimising possible hazards while maintaining the success of the business (abdullah et al., 2017), besides great social benefits (kibira and mclean, 2008). likewise, al-ashaab et al. (2013) noted that the adoption and continuous improvement of smps are achieving economic, social and environmental benefits. in other words, smps achieve efficiency in resources and responsibility towards society (badurdeen and jawahir, 2017). therefore, the adoption of smps according to the product lifecycle perspective improves sp. depending on the perspective of the product life cycle, smps can be classified into four dimensions concerning the phase at which the practices are implemented. these dimensions include the sustainable product design, sustainable manufacturing process, sustainable supply chain management and sustainable end of life management (abdul-rashid et al., 2017a, 2017b; jasiulewiczkaczmarek, 2013a; millar and russell, 2011; russell and millar, 2014). which it is considered the dimensions of smps in the present study, because it is appropriate for o&gi (abdul-rashid et al., 2017b; millar and russell, 2011; russell and millar, 2014). hence, the product life cycle perspective is more appropriate for the o&gi when implementing smps. 2.2. sp the terms “sustainability” and “sustainable development” are synonymous with many researchers (aras and crowther, 2009). levels of interest in sustainability have increased in the last two decades by many stakeholders such as industry, government and people in general (fiksel, 2006). since its start, sustainability has been defined in many beliefs, ways, contexts, values, and disciplines (aleixo et al., 2016). there are many definitions of sustainability contained in the literature (glavič and lukman, 2007; white, 2013). the definition of sustainability first emerged in the 1980s in the world conservation strategy drafted by unep in 1980 and became more widely used (basiago, 1995; du pisani, 2006; worster, 1993). where sustainability is defined in brundtland report as “the development that meets the needs of the present generation without compromising the ability of the future generations to meet their own needs” (wced, 1987. p. 8). despite the fact that it is very extensive, but it is one of the most definitions popular (pei et al., 2010), and the distinct widely to portray sustainability and sd in the different fields of studies (hami et al., 2015). in other words, the actions of people in the present will affect the next generation (bell and morse, 2008). this shows that sustainability is a human-oriented idea because humanity is the target and is viewed for sustainability regarding human values (arsat, 2014). therefore, companies are responsible for sustainability, including the o&gi. the importance of sustainability has made organisations focus on their sp. it is after the concept of sustainability came the concept of sp (chardine-baumann and botta-genoulaz, 2014), which is considered an important initiative in manufacturing companies (singh et al., 2015). in addition, it is a modern subject and evaluated by companies more modern (chardine-baumann and botta-genoulaz, 2014). thus, it is gaining considerable attention from academicians and practitioners (štreimikienė et al., 2009). in 1994 john elkington introduced the term “triple bottom line” or (tbl), 1 year later he also developed “3p formulation” which include “people, planet and profit” (elkington, 2004. p. 1-2). which has been widely recognised by researchers and practitioners (zhang et al., 2017). most definitions of sp depend on tbl because it covers the three dimensions economic, environmental and social (krajnc and glavič, 2005). besides that tbl describes sp at the company level (sezen and çankaya, 2013). the concept of tbl suggests that the socially and environmentally responsible practices of the company can achieve positive economic performance (gimenez et al., 2012). elkington (1997. p. 70) defined tbl as “focusing on economic prosperity, environmental quality, and — the element which business bad preferred to overlook — social justice”. also stressed the simultaneous pursuit to achieve of these three dimensions (elkington, 1997. p. 397), and consider them at once and balance them in practice (zhang et al., 2017), because their balanced implementation leads to the continuous improvement to all stakeholders (wu et al., 2015). this is because when companies implement three dimensions simultaneously and balancing them will outperform their sp on companies seeking only economic performance and companies that focus on environmental and social performance without interest to economic performance (carter and rogers, 2008). in the same sense, combining and align the three dimensions will lead to effective synergies (chardine-baumann and bottagenoulaz, 2014; chen and kitsis, 2017; husted and sousa-filho, 2017; mohamed and valérie, 2016). many researchers confirm this ibrahim, et al.: integrating sustainable maintenance into sustainable manufacturing practices and its relationship with sustainability performance: a conceptual framework international journal of energy economics and policy | vol 9 • issue 4 • 2019 33 in their definition of sp which is consistent with the definition of elkington (e.g., artiach et al., 2010; león and calvo-amodio, 2017; rezaee, 2016; savitz, 2014). 2.3. smps and sp in line with the significant positive impact of smps on sp, hami (2015) and hami et al. (2016) in their studies conducted in malaysia in 150 companies of manufacturing industry, smps was reported to have a positive and significant impact on sp. similarly, in the context of manufacturing plants in 20 countries, gimenez et al. (2012) found a positive relationship between smps and sp. also, masocha (2018) demonstrated that environmental sustainability influenced sp in the context of smes. similarly, a study by gadenne et al. (2012) in the context of medium to large organisations in australia that organisational sp was influenced by sp management practices. in addition, in a separate study in malaysia to understand the influence of corporate social responsibility practices on corporate social responsibility performance among automotive suppliers, fuzi et al. (2017) supported the positive influence of corporate social responsibility practices on corporate social responsibility performance. husted and sousa-filho (2017) demonstrated in their study in services and manufacturing industries for nine countries that the adoption of sustainability governance leads to the improvement in sp. literature as above shows mostly a significant positive relationship between smps and sp. thus, based on the arguments above and assumptions of stakeholder theory (friedman and miles, 2002), which propose that some advantages, benefits, firms decisionmaking power should be taken away from shareholders and given to stakeholders (stieb, 2009), the following proposition is offered: p1: smps have a significant positive relationship with sp. 2.4. sma these days, it is essential for academicians and practitioners to focus not only on the technical aspect of maintenance activities but as an integrated set of technical, economic, environmental and social and safety dimensions (bengtsson and lundström, 2018). this is because the maintenance activities and breakdowns in industrial companies result in harmful emissions, waste, dangerous accidents and consumption of energy and resources (liyanage and badurdeen, 2010), including in the o&gi (liyanage, 2010; zhang and yu, 2017). while the adoption of sma by companies will make a significant difference in the economic, environmental, social and safety and technical (franciosi et al., 2018; jones and cooper, 2007; liyanage and badurdeen, 2010). likewise, additionally the economic and environmental dimensions, sma included social and safety dimension and worked to achieve a balance among these three dimensions (jasiulewicz-kaczmarek, 2013a; 2013b; 2013d; stuchly and jasiulewicz-kaczmarek, 2014). moreover, companies that interesting on sustainable manufacturing face a new challenge in their implementation of sma (amrina and aridharma, 2016; jasiulewicz-kaczmarek, 2013a; 2013b; 2013c; 2013d; stuchly and jasiulewicz-kaczmarek, 2014). this is because of the complexity of manufacturing practices and processes (al-turki et al., 2014; jin et al., 2016; jin et al., 2016; lee et al., 2014), the need to make changes in policies and procedures of maintenance, attention to environmental and social and safety aspects as well as financial aspects (jasiulewicz-kaczmarek, 2013a; 2013d; jasiulewiczkaczmarek and stachowiak, 2016; stuchly and jasiulewiczkaczmarek, 2014), competition pressure in manufacturing (emmanouilidis and pistofidis, 2010) and the government regulations towards sd in manufacturing (ighravwe and oke, 2017a). however, in recent years, changes in manufacturing paradigms have forced companies and managers to recognise the changing role of maintenance regards sustainability (al-turki et al., 2014; ararsa, 2012; baluch, 2012; jasiulewicz-kaczmarek, 2013a; 2013b; 2013d; jin et al., 2016; lee et al., 2014; ratnayake and markeset, 2010). likewise, in recent few years, the importance of incorporating sustainability into maintenance function has been recognised (bengtsson and lundström, 2018; ighravwe and oke, 2017a; iung and levrat, 2014; kayan et al., 2017; sari et al., 2015; sénéchal, 2017). this is due to it provides lost costs and energy consumed during the product lifecycle (nezami and yildirim, 2011). therefore, it is necessary to adopt sma by companies that follow a sustainability approach in their business. jasiulewicz-kaczmarek (2013a; 2013d); and stuchly and jasiulewicz-kaczmarek (2014) defined sma “as proactive maintenance operations striving for providing balance in social (welfare and satisfaction of operators and maintenance staff), environmental and financial (losses, consequences, benefits) dimensions.” whereas, this study defined sma as all maintenance activities that support the sustainability of the company, through the reduction of environmental impact, the safety and social and safety welfare of employees, the implementation of technical factors at the highest possible level and reducing maintenance costs. 2.5. sma and sp according to ali et al. (2010), the efficiency in maintenance tasks and activities comes through the selection of proper maintenance. although studies on sma and sp are limited (pires et al., 2016; y. zhang et al., 2017), studies in most case studies have confirmed that sp is achieved through the choice of sma (granados, 2014; ighravwe and oke, 2017a, 2017b; pires et al., 2016; sénéchal, 2016; sénéchal et al., 2015). zhang et al. (2017), who studied in the context of port infrastructures in japan, explained that the use of technology in equipment maintenance has positive effects on the all of sp dimensions. mahmood et al. (2015) concluded that the implementation of maintenance and overall equipment effectiveness have a positive impact on economic development and the protection of the environment and social welfare in the malaysian manufacturing companies. henderson et al. (2014) illustrated the shift to a contemporary and positive view of maintenance contributes to the improvement of all dimensions of sp. in another context, frank et al. (2016) conducted a study of maintenance among oil and gas companies in nigeria. they reported a positive relationship between maintenance and economic, environmental and social sustainability. based on the discussion and the arguments in the above, sma has a significant positive relationship with the sp of companies. therefore, based on the arguments above and assumptions of natural resourcebased view (nrbv) theory (hart, 1995), which proposition that clean technology that encompasses a range of activities and processes undertaken by companies lead to achieving sustainable competitive advantage, creating value for shareholders and ibrahim, et al.: integrating sustainable maintenance into sustainable manufacturing practices and its relationship with sustainability performance: a conceptual framework international journal of energy economics and policy | vol 9 • issue 4 • 201934 achieving sustainability (hart and dowell, 2011), the following proposition is offered: p2: sma has a significant positive relationship with sp. 2.6. sustainale maintenance as a moderating variable indeed, after the second world war and as a result of rapid technological developments in the manufacturing environment, maintenance was considered as significant enhance function to production, operations and manufacturing (baluch, 2012). similarly, fraser et al. (2015); jasiulewicz-kaczmarek (2014); and jasiulewicz-kaczmarek and drozyner (2013) maintained that maintenance plays a critical role in industrial companies as a support function for manufacturing. besides, to achieve the best possible performance of the company (mostafa et al., 2015; mostafa et al., 2015), the strategies and objectives of maintenance and manufacturing should be integrated (fredriksson and larsson, 2012; graisa, 2011; jasiulewiczkaczmarek and stachowiak, 2016). this integration helps manufacturing companies save on costs, time and resources (moubray, 2003), as well as achieving economic benefits and competitive advantages (enofe and aimienrovbiye, 2010). therefore, in order for companies to continue, they must keep pace with the rapid development of manufacturing and maintenance paradigms. the moving of the manufacturing paradigms towards sustainable development has led to a change in the maintenance paradigms towards of product lifecycle, which involves four phases (ait-alla et al., 2016; jasiulewicz-kaczmarek, 2013d; jasiulewicz-kaczmarek and drozyner, 2013; stuchly and jasiulewicz-kaczmarek, 2014). this is due to the trend toward smps (ighravwe and oke, 2017a). from a practical perspective, each phase of the product life cycle must be supported by maintenance (jasiulewicz-kaczmarek, 2013a; jasiulewicz-kaczmarek and drozyner, 2013), from product design to end-of-life (starr and bevis, 2010). these phases can be utilised to manufacturing equipment and manufacturing products (garetti, 2011; granados, 2014). in this regards, to illustrate and justify the new process of understanding maintenance, takata introduced the term “maintenance value chain” (takata et al., 2004). this emphasis on the life cycle view of sustainable manufacturing has produced the redefinition of the task of maintenance as being “a prime method for life cycle management whose objective is to provide society with required functions through products while minimizing material and energy consumption” (takata et al., 2004. p. 653). in the same vein, the role of maintenance in the phases of the product lifecycle leads to the availability and reliability of equipment, improve environmental efficiency, achieve safety (cunha et al., 2004; granados, 2014; levrat et al., 2008; tousley, 2010). thus, maintenance plays a vital role in interacting with all phases of the product lifecycle within smps. the success of sustainable manufacturing operations and practices in improving sp is achieved through their integration with maintenance activities (enofe and aimienrovbiye, 2010; franciosi et al., 2017; liyanage and badurdeen, 2010; sénéchal et al., 2015). similarly, sma is considered as a facilitator of smps (garetti, 2011; ims2020, 2010), which will improve the sp of economic, environmental and social (franciosi et al., 2018; franciosi et al., 2017; ighravwe and oke, 2017b). based on the discussion and the arguments in the above, it concludes that the impact of smps on sp will be stronger if sma moderates between them. accordingly, based on the arguments above and assumptions of nrbv theory the following proposition is offered: p3: sma positively moderates the relationship between smps and sp. in short, the proposed a conceptual model of this study is formulated by combining the stakeholder theory and the nrbv theory. meanwhile, the current study integrating sma into smps with to examine their effects on sp, as depicted in figure 1. 3. conclusion the present paper offers a conceptual framework that investigates the moderating effect of sma on the relationship between smps and sp. this research gap has been addressed in the present study. previous empirical studies pointed that there is evidence that adopting smps were and sma in companies improves sp and achieves a balance among economic, environmental and social sustainability. the proposed conceptual framework in the current study will have some potential theoretical and practical implications. firstly, as a contribution to the body of knowledge, academicians will obtain a better perception of the importance of integrating sma into smps to achieve a balance in the dimensions of economic, environmental and social sustainability. secondly, the o&gi can put in place smps and sma framework, to achieve sp. more clearly, the proposed framework will be important to policymakers and top management in the o&gi will gain them a better understanding of how to the balance of sp dimensions, based the focus on smps and sma. this study attempts to connect the significance of sustainable practices that respond to the expectations of increasing stakeholders. this study explored sma in the o&gi. consequently, it could help the government in reaching its objective of making iraq become a better economy over the next years, within economic prosperity, carbon emissions are a low, efficient use of resources and social justice. figure 1: a conceptual framework for sustainability performance ibrahim, et al.: integrating sustainable maintenance into sustainable manufacturing practices and its relationship with sustainability performance: a conceptual framework international journal of energy economics and policy | vol 9 • issue 4 • 2019 35 references abdullah, i., wan mahmood, w.h., md fauadi, h.f., ab rahman, m.n., mohamed, s.b. (2017), sustainable manufacturing practices in malaysian palm oil mills: priority and current performance. journal of manufacturing technology management, 28(3), 278-298. abdul-rashid, s.h., sakundarini, n., ghazilla, r.a.r., ramayah, t. (2017a), drivers for the adoption of sustainable manufacturing practices: a malaysia perspective. international journal of precision engineering and manufacturing, 18(11), 1619-1631. abdul-rashid, s.h., sakundarini, n., ghazilla, r.a.r., ramayah, t. (2017b), the impact of sustainable manufacturing practices on sustainability performance: empirical evidence from malaysia. international journal of operations and production management, 37(2), 182-204. adebambo, h.o., ashari, h., nordin, n. (2014), antecedents and outcome of sustainable environmental manufacturing practices. international journal of management and sustainability, 3(3), 147-159. adebambo, h.o., ashari, h., nordin, n. (2015a), an empirical study on the influence of sustainable environmental manufacturing practice on firm performance. journal of sustainability science and management, 10(2), 42-51. adebambo, h.o., ashari, h., nordin, n. (2015b), moderating role of perceived benefit between sustainable environmental manufacturing practices and firm performance. jurnal teknologi, 77(27), 91-96. adebanjo, d., teh, p.l., ahmed, p.k. (2016), the impact of external pressure and sustainable management practices on manufacturing performance and environmental outcomes. international journal of operations and production management, 36(9), 995-1013. ahuja, i.p.s., khamba, j.s. (2008), assessment of contributions of successful tpm initiatives towards competitive manufacturing. journal of quality in maintenance engineering, 14(4), 356-374. ahuja, i.p.s., khamba, j.s. (2009), investigation of manufacturing performance achievements through strategic total productive maintenance initiatives. international journal of productivity and quality management, 4(2), 129-152. ait-alla, a., lütjen, m., lewandowski, m., freitag, m., thoben, k.d. (2016), real-time fault detection for advanced maintenance of sustainable technical systems. procedia cirp, 41, 295-300. al-ashaab, a., flores, m., anta, p.h., varro, b. (2013), a framework of industrial sustainability good practices. paper presented at the proceedings of the 11th international conference on manufacturing research (icmr2013), cranfield university, uk. alayón, c., säfsten, k., johansson, g. (2017), conceptual sustainable production principles in practice: do they reflect what companies do? journal of cleaner production, 141, 693-701. aleixo, a.m., leal, s., azeiteiro, u.m. (2018), conceptualization of sustainable higher education institutions, roles, barriers, and challenges for sustainability: an exploratory study in portugal. journal of cleaner production, 172, 1664-1673. al-haleem, a.a., awadh, s.m., saeed, e.a.j. (2013), environmental impact from drilling and production of oil activities: sources and recommended solutions. iraq: paper presented at the international conference on iraq oil studies. ali, a.s., kamaruzzaman, s.n., sulaiman, r., peng, y.c. (2010), factors affecting housing maintenance cost in malaysia. journal of facilities management, 8(4), 285-298. al-najjar, b., alsyouf, i. (2004), enhancing a company’s profitability and competitiveness using integrated vibration-based maintenance: a case study. european journal of operational research, 157(3), 643-657. alsyouf, i. (2007), the role of maintenance in improving companies’ productivity and profitability. international journal of production economics, 105(1), 70-78. al-turki, u.m., ayar, t., yilbas, b.s., sahin, a.z. (2014), maintenance in manufacturing environment: an overview. in: integrated maintenance planning in manufacturing systems. cham: springer international publishing. p5-23. amrina, e., aridharma, d. (2016), sustainable maintenance performance evaluation model for cement industry. paper presented at the 2016 ieee international conference on industrial engineering and engineering management (ieem). anis, m.d., siddiqui, t.z. (2015), issues impacting sustainability in the oil and gas industry. journal of management and sustainability, 5(4), 115-124. annunziata, e., pucci, t., frey, m., zanni, l. (2018), the role of organizational capabilities in attaining corporate sustainability practices and economic performance: evidence from italian wine industry. journal of cleaner production, 171, 1300-1311. ararsa, b.b. (2012), green maintenance: a literature survey on the role of maintenance for sustainable manufacturing. (master’s thesis), mälardalen university. available from: http://www.urn. kb.se/resolve?urn=urn: nbn:se: mdh:diva-15653 diva database. aras, g., crowther, d. (2009), corporate sustainability reporting: a study in disingenuity? journal of business ethics, 87(1), 279. ardichvili, a. (2013), the role of hrd in csr, sustainability, and ethics: a relational model. human resource development review, 12(4), 456-473. arsat, m.b. effectiveness of sustainability incorporation in engieering curricula: a framework for course design. (doctoral thesis), institut for planlægning, aalborg universitet. available from: https://www.vbn.aau.dk/ws/portalfiles/portal/201387135/ mahyuddinarsat_phdthesis.pdf. artiach, t., lee, d., nelson, d., walker, j. (2010), the determinants of corporate sustainability performance. accounting and finance, 50(1), 31-51. ashrafi, n. (2014), a review of current trend in design for sustainable manufacturing. iosr journal of mechanical and civil engineering, 11(4), 53-58. badurdeen, f., jawahir, i.s. (2017), strategies for value creation through sustainable manufacturing. paper presented at the proceedings of the 14th global conference on sustainable manufacturing, stellenbosch, south africa. baluch, n. (2012), maintenance management performance of malaysian palm oil mills. (phd. thesis), universiti utara malaysia. available from: http://www.etd.uum.edu.my/id/eprint/3420. baluch, n., abdullah, c.s.b., mohtar, s.b. (2010), maintenance management performance-an overview towards evaluating malaysian palm oil mill. the asian journal of technology management, 3(1), 1-5. basiago, a.d. (1995), methods of defining ‘sustainability’. sustainable development, 3(3), 109-119. bell, s., morse, s. (2008), sustainability indicators: measuring the immeasurable? london: earthscan. bengtsson, m., lundström, g. (2018), on the importance of combining “the new” with “the old”-one important prerequisite for maintenance in industry 4.0. procedia manufacturing, 25, 118-125. carley, s., jasinowski, j., glassley, g., strahan, p., attari, s., shackelford, s. (2014), success paths to sustainable manufacturing. available from: https://www.spea.indiana.edu/doc/research/ sustainability-2014.pdf. carter, c.r., rogers, d.s. (2008), a framework of sustainable supply chain management: moving toward new theory. international journal of physical distribution and logistics management, 38(5), 360-387. cavagnaro, e., curiel, g. (2012), the three levels of sustainability. london: routledge. cerinšek, g., petersen, s.a., heikura, t. (2013), contextually enriched ibrahim, et al.: integrating sustainable maintenance into sustainable manufacturing practices and its relationship with sustainability performance: a conceptual framework international journal of energy economics and policy | vol 9 • issue 4 • 201936 competence model in the field of sustainable manufacturing for simulation style technology enhanced learning environments. journal of intelligent manufacturing, 24(3), 441-455. chardine-baumann, e., botta-genoulaz, v. (2014), a framework for sustainable performance assessment of supply chain management practices. computers and industrial engineering, 76 supplement c, 138-147. chen, i.j., kitsis, a.m. (2017), a research framework of sustainable supply chain management: the role of relational capabilities in driving performance. the international journal of logistics management, 28(4), 1454-1478. chiang, y.h., zhou, l., li, j., lam, p.t.i., wong, f.k.w. (2014), achieving sustainable building maintenance through optimizing life-cycle carbon, cost, and labor: case in hong kong. journal of construction engineering and management, 140(3), 05014001. christen, e.w., shepheard, m.l., meyer, w.s., jayawardane, n.s., fairweather, h. (2006), triple bottom line reporting to promote sustainability of irrigation in australia. irrigation and drainage systems, 20(4), 329-343. cunha, p.f., duarte, j.a.c., alting, l. (2004), development of a productive service module based on a life cycle perspective of maintenance issues. cirp annals, 53(1), 13-16. dao, v., langella, i., carbo, j. (2011), from green to sustainability: information technology and an integrated sustainability framework. the journal of strategic information systems, 20(1), 63-79. das, d. (2018), the impact of sustainable supply chain management practices on firm performance: lessons from indian organizations. journal of cleaner production, 203, 179-196. despeisse, m. (2013), sustainable manufacturing tactics and improvement methodology: a structured and systematic approach to identify improvement opportunities. (phd thesis), cranfield university. available from: http://www.dspace.lib.cranfield.ac.uk/ handle/1826/8057. despeisse, m., mbaye, f., ball, p.d., levers, a. (2012), the emergence of sustainable manufacturing practices. production planning and control, 23(5), 354-376. du pisani, j.a. (2006), sustainable development–historical roots of the concept. environmental sciences, 3(2), 83-96. elhuni, r.m., ahmad, m.m. (2017), key performance indicators for sustainable production evaluation in oil and gas sector. procedia manufacturing, 11 supplement c, 718-724. elkington, j. (1997), cannibals with forks: the triple bottom line of 21st century business. 1st ed. oxford: capstone. elkington, j. (1999), triple bottom-line reporting: looking for balance. australian cpa, 69(2), 18-21. elkington, j. (2004), enter the triple bottom line. in: henriques, a., richardson, j., editors. the triple bottom line: does it all add up? 1st ed. uk and usa: earthscan. p1-16. emmanouilidis, c., pistofidis, p. (2010), machinery self-awareness with wireless sensor networks: a means to sustainable operation. verona, italy: paper presented at the proceedings of the 2nd workshop ‘maintenance for sustainable manufacturing. enofe, o.m., aimienrovbiye, g. (2010), maintenance impact on production profitability-a case study. (master’s thesis), linnaeus university. epa. (2003), environmental impact of the petroleum industry. environmental protection agency. available from: https://www. cfpub.epa.gov/ncer_abstracts/index.cfm/fuseaction/display.files/ fileid/14522. esfahbodi, a., zhang, y., watson, g., zhang, t. (2017), governance pressures and performance outcomes of sustainable supply chain management-an empirical analysis of uk manufacturing industry. journal of cleaner production, 155, 66-78. fiksel, j. (2006), sustainability and resilience: toward a systems approach. sustainability: science, practice, and policy, 2(2), 14-21. franciosi, c., iung, b., miranda, s., riemma, s. (2018), maintenance for sustainability in the industry 4.0 context: a scoping literature review. ifac-papersonline, 51(11), 903-908. franciosi, c., lambiase, a., miranda, s. (2017), sustainable maintenance: a periodic preventive maintenance model with sustainable spare parts management. ifac-papersonline, 50(1), 13692-13697. frank, m.d., nwuche, a.c., anyanwu, s.a.c. (2016), operations management activities and organizational sustainability in oil and gas companies in rivers state. international journal of advanced academic research, 2(11), 34-56. fraser, k., hvolby, h.h., tseng, t.l. (2015), maintenance management models: a study of the published literature to identify empirical evidence: a greater practical focus is needed. international journal of quality and reliability management, 32(6), 635-664. fredriksson, g., larsson, h. (2012), an analysis of maintenance strategies and development of a model for strategy formulation–a case study. (master’s thesis), chalmers university of technology. friedman, a.l., miles, s. (2002), developing stakeholder theory. journal of management studies, 39(1), 1-21. fuzi, n.m., habidin, n.f., hibadullah, s.n., ong, s.y.y. (2017), csr practices, iso 26000 and performance among malaysian automotive suppliers. social responsibility journal, 13(1), 203-220. gadenne, d., mia, l., sands, j., winata, l., hooi, g. (2012), the influence of sustainability performance management practices on organisational sustainability performance. journal of accounting and organizational change, 8(2), 210-235. garetti, m. (2011), maintenance for sustainable manufacturing (m4sm). white paper of the m4sm mtp (manufacturing technology platform) initiative. ims (intelligent manufacturing systems) association; 2011. p. 1-17. available from: https://www.ims.org/publications. garetti, m., taisch, m. (2012), sustainable manufacturing: trends and research challenges. production planning and control, 23(2-3), 83-104. gimenez, c., sierra, v., rodon, j. (2012), sustainable operations: their impact on the triple bottom line. international journal of production economics, 140(1), 149-159. glavič, p., lukman, r. (2007), review of sustainability terms and their definitions. journal of cleaner production, 15(18), 1875-1885. graisa, m. (2011), an investigation into the need and implementation of total productive maintenance (tpm) in libyan cement industry. (phd thesis), nottingham trent university. available from: http:// www.irep.ntu.ac.uk/id/eprint/10. granados, m.h. (2014), sustainable value creation in manufacturing through maintenance services. (ph.d thesis), politecnico di milano, italy. available from: https://www.politesi.polimi.it/ bitstream/10589/98504/1/phd%20thesis%20-%20holgado%20 granados%20-%20october%202014.pdf. gupta, s., dangayach, g.s., singh, a.k., rao, p.n. (2015), analytic hierarchy process (ahp) model for evaluating sustainable manufacturing practices in indian electrical panel industries. paper presented at the proceedings of the 18th annual international conference of the society of operations management (som-14). habidin, n.f., eyun, m.a., zubir, a.f.m., fuzi, n.m., ong, s.y.y. (2016), the relationship between sustainable manufacturing practice and environmental performance in malaysian automotive smes. international journal of academic research in business and social sciences, 6(12), 338-352. habidin, n.f., zubir, a.f.m., conding, j., jaya, n.a.s., hashim, s. (2013), sustainable manufacturing practices, sustaining lean improvements and sustainable performance in malaysian automotive industry. world review of entrepreneurship, management and sustainable ibrahim, et al.: integrating sustainable maintenance into sustainable manufacturing practices and its relationship with sustainability performance: a conceptual framework international journal of energy economics and policy | vol 9 • issue 4 • 2019 37 development, 9(4), 444-459. hami, n. (2015), sustainable manufacturing practice and sustainability performance mediated by innovation performance. (phd thesis), universiti teknikal malaysia melaka. available from: http://www. eprints.utem.edu.my/id/eprint/16769. hami, n., muhamad, m.r., ebrahim, z. (2016), the impact of sustainable manufacturing practices on sustainability. jurnal teknologi, 78(1), 139-152. hami, n., muhammad, m., ebrahim, z. (2015), an empirical study on the impact of sustainable manufacturing practices and innovation performance on environmental sustainability. jurnal teknologi, 77(4), 57-68. hamzah, n.h. (2011), a study of relationship between total productive maintenance (tpm) and manufacturing performance. (master’s thesis), universiti utara malaysia. hart, s.l. (1995), a natural-resource-based view of the firm. academy of management review, 20(4), 986-1014. hart, s.l., dowell, g. (2011), invited editorial: a natural-resource-based view of the firm: fifteen years after. journal of management, 37(5), 1464-1479. hartini, s., ciptomulyono, u. (2015), the relationship between lean and sustainable manufacturing on performance: literature review. procedia manufacturing, 4, 38-45. hassan, m.g., nordin, n., ashari, h. (2015), sustainable manufacturing practices implementation in malaysia industries. jurnal teknologi, 77(4), 49-56. henderson, k., pahlenkemper, g., kraska, o. (2014), integrated asset management-an investment in sustainability. procedia engineering, 83, 448-454. hooi, l.w., leong, t.y. (2017), total productive maintenance and manufacturing performance improvement. journal of quality in maintenance engineering, 23(1), 2-21. husted, b.w., sousa-filho, j.m.d. (2017), the impact of sustainability governance, country stakeholder orientation, and country risk on environmental, social, and governance performance. journal of cleaner production, 155, 93-102. ighravwe, d.e., oke, s.a. (2017a), a multi-hierarchical framework for ranking maintenance sustainability strategies using promethee and fuzzy entropy methods. journal of building pathology and rehabilitation, 2(1), 9-18. ighravwe, d.e., oke, s.a. (2017b), ranking maintenance strategies for sustainable maintenance plan in manufacturing systems using fuzzy axiomatic design principle and fuzzy-topsis. journal of manufacturing technology management, 28(7), 961-992. imo. (2017), report of the compensation commission. available from: http://www.prdc.oil.gov.iq/index.php. ims2020. (2010), roadmap on sustainable manufacturing, energy efficient manufacturing and key technologies. available from: http://www.ims2020.net. iung, b., levrat, e. (2014), advanced maintenance services for promoting sustainability. procedia cirp, 22, 15-22. jasiulewicz-kaczmarek, m. (2013a), the role and contribution of maintenance in sustainable manufacturing. ifac proceedings volumes, 46(9), 1146-1151. jasiulewicz-kaczmarek, m. (2013b), sustainability: orientation in maintenance management—theoretical background. in: golinska, p., editor. ecoproduction and logistics: emerging trends and business practices. berlin, heidelberg: springer berlin heidelberg. p117-134. jasiulewicz-kaczmarek, m. (2013c), sustainability: orientation in maintenance management: case study. in: golinska, p., editor. ecoproduction and logistics: emerging trends and business practices. berlin, heidelberg: springer berlin heidelberg. p135-154. jasiulewicz-kaczmarek, m. (2013d), sustainable maintenance-the next generation of maintenance management. paper presented at the international conference on innovative technologies, in-tech. jasiulewicz-kaczmarek, m. (2014), integrating lean and green paradigms in maintenance management. ifac proceedings volumes, 47(3), 4471-4476. jasiulewicz-kaczmarek, m., drozyner, p. (2013), the role of maintenance in reducing the negative impact of a business on the environment. in: erechtchoukova, m.g., khaiter, p.a., golinska, p., editors. sustainability appraisal: quantitative methods and mathematical techniques for environmental performance evaluation. berlin, heidelberg: springer berlin heidelberg. p141-166. jasiulewicz-kaczmarek, m., stachowiak, a. (2016), maintenance process strategic analysis. paper presented at the iop conference series: materials science and engineering. jin, x., siegel, d., weiss, b.a., gamel, e., wang, w., lee, j., ni, j. (2016), the present status and future growth of maintenance in us manufacturing: results from a pilot survey. manufacturing review, 3(10), 1-10. jin, x., weiss, b.a., siegel, d., lee, j. (2016), present status and future growth of advanced maintenance technology and strategy in us manufacturing. international journal of prognostics and health management, 7, 012. jones, k., cooper, j. (2007), the role of routine maintenance in improving the sustainability of existing social housing. paper presented at the proceedings of the european network for housing research conference sustainable urban areas rotterdam. joung, c.b., carrell, j., sarkar, p., feng, s.c. (2013), categorization of indicators for sustainable manufacturing. ecological indicators, 24, 148-157. kaur, m., singh, k., ahuja, i.s. (2012), an evaluation of the synergic implementation of tqm and tpm paradigms on business performance. international journal of productivity and performance management, 62(1), 66-84. kayan, b.a., halim, i.a., mahmud, n.s. (2017), green maintenance for heritage buildings: low carbon repair appraisal approach on laterite stones. chemical engineering transactions, 56, 337-342. kibira, d., mclean, c. (2008), modeling and simulation for sustainable manufacturing. proceedings of the 2nd international association of science and technology for development. p254-263. krajnc, d., glavič, p. (2005), how to compare companies on relevant dimensions of sustainability. ecological economics, 55(4), 551-563. lee, j., holgado, m., kao, h.a., macchi, m. (2014), new thinking paradigm for maintenance innovation design. cape town, south africa: paper presented at the proceedings of the 19th world congress the international federation of automatic control. león, h.c.m., calvo-amodio, j. (2017), towards lean for sustainability: understanding the interrelationships between lean and sustainability from a systems thinking perspective. journal of cleaner production, 142, 4384-4402. levrat, e., iung, b., marquez, a.c. (2008), e-maintenance: review and conceptual framework. production planning and control, 19(4), 408-429. liyanage, j.p. (2007), operations and maintenance performance in production and manufacturing assets: the sustainability perspective. journal of manufacturing technology management, 18(3), 304-314. liyanage, j.p. (2010), state of the art and emerging trends in operations and maintenance of offshore oil and gas production facilities: some experiences and observations. international journal of automation and computing, 7(2), 137-145. liyanage, j.p., badurdeen, f. (2010), strategies for integrating maintenance for sustainable manufacturing. london: springer. liyanage, j.p., badurdeen, f., ratnayake, r.m.c. (2009), industrial asset maintenance and sustainability performance: economical, ibrahim, et al.: integrating sustainable maintenance into sustainable manufacturing practices and its relationship with sustainability performance: a conceptual framework international journal of energy economics and policy | vol 9 • issue 4 • 201938 environmental, and societal implications. in: ben-daya, m., duffuaa, s.o., raouf, a., knezevic, j., ait-kadi, d., editors. handbook of maintenance management and engineering. london: springer. p665-693. löfsten, h. (1999), management of industrial maintenance-economic evaluation of maintenance policies. international journal of operations and production management, 19(7), 716-737. luthra, s., mangla, s.k. (2018), when strategies matter: adoption of sustainable supply chain management practices in an emerging economy’s context. resources, conservation and recycling, 138, 194-206. mahmood, w.h.w., abdullah, i., mdfauadi, m.h.f. (2015), translating oee measure into manufacturing sustainability. applied mechanics and materials, 761, 555-559. maletič, m., maletič, d., dahlgaard, j.j., dahlgaard-park, s.m., gomišček, b. (2014), sustainability exploration and sustainability exploitation: from a literature review towards a conceptual framework. journal of cleaner production, 79 supplement c, 182-194. masocha, r. (2018), does environmental sustainability impact innovation, ecological and social measures of firm performance of smes? evidence from south africa. sustainability (switzerland), 10(11), 3855. millar, h.h., russell, s.n. (2011), the adoption of sustainable manufacturing practices in the caribbean. business strategy and the environment, 20(8), 512-526. mohamed, m., valérie, b.g. (2016), the role of robustness analysis for sustainable performance assessment frameworks. paper presented at the 2016 international conference on control, decision and information technologies (codit). mostafa, s., dumrak, j., soltan, h. (2015), lean maintenance roadmap. procedia manufacturing, 2, 434-444. mostafa, s., lee, s.h., dumrak, j., chileshe, n., soltan, h. (2015), lean thinking for a maintenance process. production and manufacturing research, 3(1), 236-272. moubray, j. (2003), 21st century maintenance organization part i: the asset management model. maintenance technology, 16(2), 25-32. nezami, f.g., yildirim, m.b. (2011), a framework for a fuzzy sustainable maintenance strategy selection problem. paper presented at the proceedings of the 2011 ieee international symposium on sustainable systems and technology. nordin, n., ashari, h., hassan, m.g. (2014), drivers and barriers in sustainable manufacturing implementation in malaysian manufacturing firms. paper presented at the 2014 ieee international conference on industrial engineering and engineering management. nordin, n., ashari, h., rajemi, m.f. (2014), a case study of sustainable manufacturing practices. journal of advanced management science, 2(1), 12-16. opec. (2018), annual statistical bulletin. vienna, austria: organization of the petroleum exporting countries. available from: http://www. thegulfintelligence.com/mediafiles/downloadfile/4833753a-f15946f2-8dc0-f2335344ebe6.pdf. parida, a., kumar, u. (2010), integrated strategic asset performance assessment. london: springer-verlag. pei, y., amekudzi, a., meyer, m., barrella, e., ross, c. (2010), performance measurement frameworks and development of effective sustainable transport strategies and indicators. transportation research record: journal of the transportation research board, 2163, 73-80. pires, s. (2015), industrial maintenance for sustainable performance: a systematic literature review. paper presented at the the 23rd international conference on production research. pires, s., sénéchal, o., loures, e.r., jimenez, j.f. (2016), an approach to the prioritization of sustainable maintenance drivers in the tbl framework. ifac-papersonline, 49(28), 150-155. ratnayake, r.m.c., markeset, t. (2010), technical integrity management: measuring hse awareness using ahp in selecting a maintenance strategy. journal of quality in maintenance engineering, 16(1), 44-63. rezaee, z. (2016), business sustainability research: a theoretical and integrated perspective. journal of accounting literature, 36 supplement c, 48-64. roberts, s.j.f., ball, p.d. (2014), developing a library of sustainable manufacturing practices. procedia cirp, 15, 159-164. roni, m., jabar, j., mohamad, m., yusof, m. (2014), conceptual study on sustainable manufacturing practices and firm performance. science international, 26(4), 1459-1464. russell, s.n., millar, h.h. (2014), exploring the relationships among sustainable manufacturing practices, business performance and competitive advantage: perspectives from a developing economy. journal of management and sustainability, 4(3), 37-53. sari, e., shaharoun, a.m., ma’aram, a., yazid, a.m. (2015), sustainable maintenance performance measures: a pilot survey in malaysian automotive companies. procedia cirp, 26, 443-448. savitz, a. (2014), the triple bottom line: how today’s best-run companies are achieving economic, social and environmental success and how you can too. 2nd ed. new york: john wiley and sons. schneider, j., ghettas, s., merdaci, n., brown, m., martyniuk, j., alshehri, w., trojan, a. (2013), towards sustainability in the oil and gas sector: benchmarking of environmental, health, and safety efforts. journal of environmental sustainability, 3(3), 6. schneider, j., vargo, c., campbell, d., hall, r. (2011), an analysis of reported sustainability-related efforts in the petroleum refining industry. the journal of corporate citizenship, 2011(44), 69-84. sénéchal, o. (2016), maintenance decision support for sustainable performance: problems and research directions at the crossroads of health management and eco-design. ifac-papersonline, 49(28), 85-90. sénéchal, o. (2017), research directions for integrating the triple bottom line in maintenance dashboards. journal of cleaner production, 142, 331-342. sénéchal, o., trentesaux, d., pires, s., loures, e.r., santos, e.a. (2015), sustainable performance: a paradigm inducing new needs of interoperability between maintenance and scheduling activities in manufacturing. paper presented at the 5th international workshop advanced cleaner production. sezen, b., çankaya, s.y. (2013), effects of green manufacturing and eco-innovation on sustainability performance. procedia-social and behavioral sciences, 99 supplement c, 154-163. shubham, charan, p., murty, l.s. (2018), organizational adoption of sustainable manufacturing practices in india: integrating institutional theory and corporate environmental responsibility. international journal of sustainable development and world ecology, 25(1), 23-34. shukla, o.j., jangid, v., siddh, m.m., kumar, r., soni, g. (2017), evaluating key factors of sustainable manufacturing in indian automobile industries using analytic hierarchy process (ahp). paper presented at the 2017 international conference on advances in mechanical, industrial, automation and management systems (amiams). singh, s., olugu, e.u., musa, s.n., mahat, a.b. (2015), fuzzy-based sustainability evaluation method for manufacturing smes using balanced scorecard framework. journal of intelligent manufacturing, 29(1), 1-18. starr, a., bevis, k. (2010), the role of education in industrial ibrahim, et al.: integrating sustainable maintenance into sustainable manufacturing practices and its relationship with sustainability performance: a conceptual framework international journal of energy economics and policy | vol 9 • issue 4 • 2019 39 maintenance: the pathway to a sustainable future. london: paper presented at the proceedings of the 4th world congress on engineering asset management. stieb, j.a. (2009), assessing freeman’s stakeholder theory. journal of business ethics, 87(3), 401-414. štreimikienė, d., girdzijauskas, s., stoškus, l. (2009), sustainability assessment methods and their application to harmonization of policies and sustainability monitoring. environmental research, engineering and management, 2(48), 51-62. stuchly, v., jasiulewicz-kaczmarek, m. (2014), maintenance in sustainable manufacturing. scientific journal of logistics, 10(3), 273-284. székely, f., knirsch, m. (2005), responsible leadership and corporate social responsibility: metrics for sustainable performance. european management journal, 23(6), 628-647. takata, s., kirnura, f., van houten, f.j.a., westkamper, e., shpitalni, m., ceglarek, d., lee, j. (2004), maintenance: changing role in life cycle management. cirp annals-manufacturing technology, 53(2), 643-655. tousley, p.c. (2010), maintain it and save why we need maintenance management programs. energy engineering, 107(5), 64-75. un-escwa. (2018), external trade bulletin of the arab region. new york: united nations economic and social commission for western asia. available from: https://www.unescwa.org/recurringpublication-identifier/external-trade-bulletin-arab-region. vassu, k., lazim, h.b.m. (2016), the role of maintenance in manufacturing sector: an excerpt from review of liturature. journal of technology and operations management, 11(1), 60-68. venkatraman, s., nayak, r.r. (2015), corporate sustainability: an is approach for integrating triple bottom line elements. social responsibility journal, 11(3), 482-501. wced. (1987), our common future. portland: united nations, the world commission on environment and development. available from: http://www.un-documents.net/our-common-future.pdf. white, m.a. (2013), sustainability: i know it when i see it. ecological economics, 86, 213-217. worster, d. (1993), the wealth of nature: environmental history and the ecological imagination. new york: oxford university press on demand. wu, l., subramanian, n., abdulrahman, m., liu, c., lai, k.h., pawar, k. (2015), the impact of integrated practices of lean, green, and social management systems on firm sustainability performance—evidence from chinese fashion auto-parts suppliers. sustainability, 7(4), 3838. yucel, e., gunay, m. (2013), an evaluation on machining processes for sustainable manufacturing. gazi university journal of science, 26(2), 241-252. zhang, h., yu, x. (2017), research on oil and gas pipeline defect recognition based on ipso for rbf neural network. sustainable computing: informatics and systems, 20(12), 203-208. zhang, x., liu, c., li, w., evans, s., yin, y. (2017), effects of key enabling technologies for seru production on sustainable performance. omega, 66, 290-307. zhang, y., kim, c.w., tee, k.f., lam, j.s.l. (2017), optimal sustainable life cycle maintenance strategies for port infrastructures. journal of cleaner production, 142, 1693-1709. zubir, a.f.m., habidin, n.f., conding, j., jaya, n., hashim, s. (2012), the development of sustainable manufacturing practices and sustainable performance in malaysian automotive industry. journal of economics and sustainable development, 3(7), 130-138. international journal of energy economics and policy vol. 2, no. 1, 2012, pp. 1-9 issn: 2146-4553 www.econjournals.com modeling gasoline demand with structural breaks: new evidence from nigeria olusegun a. omisakin department of economics and business studies, redeemer’s university, nigeria; and center for econometrics and allied research (cear), university of ibadan, nigeria. email: brightolusegun@yahoo.com abimbola m. oyinlola department of economics, university of ibadan, nigeria. email: mutiu_oyinlola@yahoo.com oluwatosin a. adeniyi department of economics and business studies, redeemer’s university, nigeria; and center for econometrics and allied research (cear), university of ibadan, nigeria. email: saino78@yahoo.com abstract: this paper extends previous studies in modeling and estimating demand for gasoline for nigeria from 1977 to 2008. the ingenious attempt of this study, contrast to earlier studies on nigeria and other developing countries, lies in its assumption of structural breaks in the long run relationship among the variables employed. the study tests for the possibility of structural breaks/regime shifts and parameter instability in the gasoline demand function in nigeria using more recent and robust techniques. while the conventional residual-based cointegration tests employed fail to identify any meaningful long-run relationship in the gasoline function, the gregory-hansen structural break cointegration approach confirms the cointegration relationships despite the breakpoints. the elasticity estimates also follow the a priori expectations being inelastic both in the longand short-run for both price and income. having identified plausible breaks in the systems, the test does suggest that a structural break in the cointegration vector is important and needs to be taken care of in the specification of gasoline demand functions in nigeria. it is envisaged, therefore, that substantial policy lessons would be drawn from the findings of this study especially in the current phase of energy industry deregulation in nigeria. keywords: gasoline demand modeling; structural breaks; parameter stability; cointegration jel classifications: c13, c22, c51 1. introduction investigating the cointegration relationship among energy demand, prices and income is germane to establishing any meaningful policy inference regarding energy planning. in the same vein, understanding the sensitivity or responsiveness of energy demand to changes in price and income is essential in evaluating different implications of energy related policies such as carbon emissions reduction, optimal energy taxation, efficient energy pricing and energy conservation. different empirical studies in the literature have been devoted to formulating and estimating demand functions for different energy products such as gasoline (see cheung and elspeth, 2004; dahl and kurtubi, 2001; dahl, 1994, 2006; de vita, et al., 2006; eltony, 2003, 2004; hendry and juselius, 2000, 2001; hughesn et al., 2006; and polemis, 2006). central to the estimation of gasoline demand function in both developed and developing economies are the issues of variables’ long run relationship and elasticity estimates. these issues fundamentally inform the forecasting power of energy demand models. the empirical findings from these studies with respect to the long run relationship among international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.1-9 2 gasoline demand, prices and per capita income seem to be univocal. they all reveal the existence of cointegration relationship among the variables and the significance of price and income elasticity estimates, though with varying degree, in their respective economies. previous studies investigating long-run elasticities of gasoline demand in nigeria and other developing countries heavily rely on the assumptions of time series with no structural changes and of long-run relationships that are temporally stable (see, iwayemi et al., 2010; dayo and adegbulugbe, 1987; akinboade et al., 2008; cheung and elspeth, 2004; dahl and kurtubi, 2001). however, this may not be the case given the fact that economic data often come from processes with time dependent parameters. hence, an assumption of structural break in the cointegration relationship eventually implies a significant change in the cointegration parameters or even a change in the existence of cointegration relationships. therefore, this relationship is likely to be subject to variation as a result of changes in the economy’s structure like changes in energy policy or economic development regime, reforms in energy regulation, or institutional developments. in addition, the issue of parameter stability is important if the long-run equilibrium relation is to be useful in long-term energy planning and policy formulation. the conventional cointegration techniques which are mostly used in the literature in investigating gasoline demand function often fail to account for structural break effects on the relationship leading to biased estimation. this also has implications on knowing the stability of the parameters over the period under consideration (granger and newbold, 1974; phillips, 1986 and leybourne and newbold, 2003). in allowing for the effects of regime shifts in gasoline demand modeling in nigeria, this study employs the gregory and hansen (1996) residual based test which accounts for endogenous structural break and also hansen (1992) and quandt and andrews (1993) tests for parameter stability. given the rejection of cointegration with unknown break in the parameter, gregory and hanson (1996) technique allows us to test the null of no cointegration for the variables under consideration with i(1) order in the presence of structural break in the cointegration relationship. also, long run relationship in gasoline demand models is likely to be subject to variation as a result of changes in the economy’s structure like changes in energy policy, reforms in energy market, institutional developments, high and frequent rates of political instability and, of course, incessant policy regime shifts and/or policy reversal. therefore, an estimation of gasoline demand function with emphasis on structural breaks and parameter stability becomes pertinent in the case of nigeria. while there are different studies on gasoline demand estimation, only few considered the issue of structural breaks and parameter stability. however, in the case of nigeria, no empirical study has extensively considered these issues. in lieu of this, and in contrast to past empirical works, this study contributes to the literature by making an ingenious attempt by addressing the issue of structural breaks and parameter stability in gasoline demand modeling in nigeria. the research question this study seeks to answer is: what are the policy implications of the existence of structural breaks and/or regime shifts on the cointegration relationship of gasoline demand model in nigeria? it should, therefore, be stressed here that while the objective of this study is drawn from the above highlighted research question, the contribution of this paper are as follows. this study employs an alternative cointegration and parameter stability techniques under the assumption of possibility of structural break/regime shift in gasoline demand function in nigeria. the rest of the paper is structured as follows. section 2 highlights basic theory of cointegration with structural breaks/regime shifts. section 3 details methodological approach employed in this study including data sources, measurement and model specification. while section 4 concerns the empirical results and discussions, conclusion is made in section 5. 2. basic theory of cointegration with structural breaks/regime shifts in investigating the relationship among economic variables in face of structural breaks, the concept and dynamics of cointegration in time series econometrics has been further examined. different types of cointegration with structural breaks haven been identified namely: cointegration with parameter changes, partly cointegration and cointegration with mechanism changes. simply speaking, cointegration with parameter changes means the parameters of the cointegration equation happen to change at some time, but the cointegration relationship still exists. partly cointegration means the cointegration relationship exists before or after some time but disappears in other periods. cointegration with mechanism changes means the former cointegration relationship is destroyed modeling gasoline demand with structural breaks: new evidence from nigeria 3 because new variables enter the system and they form a new type of cointegration relationship (see baochen and shiying, 2002). given the following cointegration equation: yt = a + bxt + εt，where xt，yt are integration time series with order of d and εt is residual series, the conventional residualbased cointegration test presume that there is no cointegration between variables (y and x) if the test fails to reject the null hypothesis for a sample period. however, the presence of structural break(s) in this equation simply nullifies, breaks down and disintegrates this assertion or presumption. based on the works of perron (1989), banerjee et al., (1992), perron and vogelsang (1992), and zivot and andrews (1992) where the null of a unit root in univariate time series is tested against the alternative of stationarity while allowing for a structural break in the deterministic component of the series, gregory and hansen (1996) developed a residual-based cointegration approach that allows for regime shifts. gregory and hansen (1996) residual-based tests for cointegration centers on deriving an alternative hypothesis of one break in the cointegrating vector.1 according to gregory and hansen (1996), the power of the engle-granger (1987) test of the null of no cointegration is substantially reduced in the presence of a break in the cointegrating relationship. to overcome this problem, gregory and hansen (1996) extended the engle-granger test to allow for breaks in either the intercept or the intercept and trend of the cointegrating relationship at an unknown time. therefore, given the rejection of cointegration with unknown break in the parameter, gregory and hanson (1996) technique allows testing the null of no cointegration of variables with i(1) order in the presence of structural break in the cointegrating relationship. as earlier stated, this cointegration technique is an extension of adf, zα, and zt tests for cointegration and can be seen as a multivariate extension of the endogenous break test for univariate series. basically, in the g-h tests, there are four different models for the analysis of structural change in the cointegrating relationship. these models are: (i) level shift, c; (ii) level shift with trend, c/t; (iii) regime shift where both intercept and slope coefficient change, c/s; and (iv) regime shift where intercept, slope coefficient and trend change, c/s/t. hence, the following equations represent the specifications of the models, respectively: (1) (2) (3) (4) equations (1) to (4) represent the generalized standard model of cointegration. the idea here is to allow for both a regime trend shift under the alternative hypothesis (gregory and hansen, 1996). the observed data are yt = (y1t, y2t) where y1t is a scalar variable, y2t is a vector of explanatory variables and µ is the disturbance term. while φ represents the dummy variable both y1t and y2t are expected to be i(1) variables. the dummy variable is then defined as: (5) the unknown parameter, is the relative timing of the change point and [ ] denotes integer part. following the computed cointegration test statistic for each possible regime shift by gregory and hansen (1996), equations (1) to (4) are estimated for all possible break date in the sample. the smallest value of adf (τ), zα(τ) and zt(τ) across all possible break points are selected to reject the null hypothesis of no cointegration.2 1 in the presence of structural break(s)/regime shift, the common test for cointegration between variables becomes bias since the distributional theory of evaluating the residual-based tests is not the same. in gregory and hansen (1996), nason and watt (1996), the impact of break in the test for cointegration is further explained as the rejection frequency of the adf test is said to fall dramatically in the presence of a break in the cointegration vector. 2 the critical values for the break test are reported in gregory and hansen (1996). international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.1-9 4 3. methodology and data 3.1. data given the underlying objective of this study which centers on re-estimating gasoline demand function with special emphasis on structural breaks (hence parameter stability), this study employs the nigerian annual time series data. thus the data used are: real gross domestic product per capita, real gasoline prices and gasoline consumption per capita. all data are further expressed in their natural log forms. the analytical scope of the data ranges from 1977 to 2008. all data are sourced from the central bank of nigeria (cbn) statistical bulletin various issues. 3.2. model specification throughout the literature, the macroeconomic energy demand function specification had rather assumed the standard consumer theory-based demand model specification. basically, the demand function of a typical rational economic agent presupposes consumption of a commodity as a function of income, price of the commodity, price of other commodity etc. the econometric model used in this study, therefore, reflects previous studies of gasoline demand (see iwayemi et. al., 2010). apart from the fact that it is a common gasoline demand specification used in a large number of previous studies, it is also convenient for us to adopt this model since it allows for direct comparison with previous results from the literature. therefore, for the case of simplicity and parsimony, we adopt the basic gasoline demand model which is essentially specified as a function of price and income. the model is specified as follow: 3.3. econometric analytical procedures the standard econometric analytical procedures of time series model estimation are strictly adhered to in this study. we commence our empirical exercise by performing unit roots test with the aim of confirming the integration properties of the variables employed. basically, the idea is to test whether the variables are integrated. we consequently employ the augmented dickey-fuller (adf) and phillips-peron (pp) tests (dickey and fuller, 1979; phillips and peron, 1988). also, since we are more interested in investigating the long run relationship of the variables under consideration allowing for the incidence of structural breaks, this study employs batteries of cointegration techniques including the more recent and robust gregory and hansen (1996) approach which allows for endogenous identification of break in the variables. this is also needful in order to further present a more rigorous cointegration analysis especially when external shocks or policy shift/reversal are assumed in the model. finally, following the results of the cointegration tests (where cointegration relationship is established) we proceed to estimating the elasticity estimates of the function. following the results of the elasticity estimates obtained from the model, we perform different parameter stability tests such as the hansen test and quant-andrews unknown break point test. the intention is to affirm the dynamics of parameter stability over the scope of the period under analysis. this is also fundamental to gasoline demand forecasting exercise. 4. empirical results and discussions 4.1. unit root test the study performs the unit root tests on the variables under consideration, namely gasoline consumption per capita, income per capita, prices of gasoline. as earlier highlighted, two unit root testsadf and ppare used. while the null hypothesis for both tests is that there is a unit root, the optimal lag lengths selection is done by the schwarz bayesian criteria. all unit root test regressions are run with a constant and trend term. the results as detailed in table 1 indicate the existence of unit root for all the variables at their levels. in other words, the tests were unable to reject the null hypothesis for all the variables. however, the variables appear to be stationary at first difference, i.e. integrated at order 1. this result, therefore, implies that examination of possible cointegration relationship among the variables is worthwhile. modeling gasoline demand with structural breaks: new evidence from nigeria 5 table 1. unit root tests adf test statistic variables t-statistics prob.* at level gdp -0.232 0.925 gasoline consumption -2.084 0.251 gasoline price 6.174 1.000 at first difference gdp -4.846 0.000 gasoline consumption -6.747 0.000 gasoline price -2.914 0.053 p-p test statistic variables t-statistics prob.* at level gdp -0.412 0.896 gasoline consumption -2.067 0.258 gasoline price 8.831 1.000 at first difference gdp -4.795 0.000 gasoline consumption -7.762 0.000 gasoline price -2.799 0.060 *mackinnon (1996) one-sided p-values 4.2. cointegration tests without structural breaks in this study, we embark on investigating the long run relationships among the variables using both conventional and more recent cointegration methodologies. among the cointegration techniques employed are the var-based multivariate johansen, engle-granger, phillips-ouliaris single-equation cointegration techniques and the gregory-hansen cointegration technique which allows for endogenous identification of structural breaks. the results of the respective cointegration tests are presented in table 2, 3 and 4. one of the striking features of these reports pertains to the seemingly conflicting cointegration evidences among the variables. for instance, while the result from the varbased johansen maximum likelihood tests suggests that there exists one cointegrating vector among all variables, findings from both the engle-granger and phillips-ouliaris single-equation cointegration techniques, refute the cointegration evidence among the variables in the model. table 2. multivariate johansen cointegration test ho ha λtr test λtr (0.95) prob. r = 0 r=1 32.12 29.79 0.026 r ≤ 1 r=2 7.60 15.49 0.509 r ≤ 2 r=3 0.05 3.84 0.819 ho ha λtr test λtr (0.95) prob. r=0 r=1 24.53 21.13 0.016 r=1 r=2 7.54 14.26 0.427 r=2 r=3 0.05 3.84 0.819 note: critical values are calculated following the approach in mackinnon et al., (1999) it must, however, be noticed that since the plot of the series suggests that the data might have a structural break(s), the conventional cointegration tests results in the presence of structural break(s)/regime shift, become biased following the fact that the distributional theory of evaluating the residual-based tests is not the same (see gregory and hansen, 1996 and gregory et al., 1996). this explains while most findings from earlier studies which predominantly rely on these conventional tests in establishing the long run relationships could be biased. for instance, it would be erroneous and of course misleading to conclude and thus deduct policy inference based on the results of cointegration tests as seen in table 3. more specifically, since the power of residual-based cointegration tests such as the engle-granger and phillips-ouliaris often fall dramatically in the presence of a break in the cointegration vector, there is need for an alternative cointegration international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.1-9 6 table 3. conventional residual-based cointegration tests engle-granger test dependent tau-statistic prob.* z-statistic prob.* gdp -0.998559 0.9662 -2.894700 0.9653 price -1.988986 0.7427 -17.09904 0.1333 cons -3.350912 0.1675 -14.36408 0.2502 phillips-ouliaris test dependent tau-statistic prob.* z-statistic prob.* gdp -1.306669 0.9326 -4.456231 0.9123 price -1.111021 0.9564 -4.963319 0.8880 cons -3.380565 0.1597 -15.00221 0.2192 note: probability values are calculated following the approach in mackinnon et al., (1996) 4.3. cointegeration tests with structural breaks since the gregory-hansen structural break test is based on the notion of regime change, it thus allows for an endogenous structural break in the cointegration vector by considering three alternative models: a level shift (model c), a level shift with a trend (model c/t), and a regime shift which allows the slope vector to shift as well (model c/s). given the short-coming of the earlier conventional tests in identifying any meaningful long run relationship in the presence of structural breaks, this study finds it needful to further subject the long run relationship among the variables to a more rigorous and robust test which consents to possibility of structural breaks in the relationship. this, therefore, informs our choice for the gregory-hansen test in this study. the result of this test is depicted in table 4 for demand for gasoline. though, the results reveal that evidence of cointegration is not found when considering the assumption of a level shift and a level shift with trend (i.e. c and c/t models), evidence of cointegration relationships is clearly established when assuming a shift which allows the slope vector to shift (model c/s), otherwise known as structural break in both functions. having identified plausible breaks in the systems, the test does suggest that a structural break in the cointegration vector is important and needs to be taken care of in the specification of gasoline demand functions in nigeria. also, the structural breakpoints as identified in the results of both demand functions seem to match clearly with the corresponding critical economic incidents in nigeria. table 4. gregory-hansen structural break cointegration test model adf* breakpoint zt* breakpoint zα* breakpoint c -3.90 (1) 1979 -3.80 1978 -22.01 1978 c/t -5.70 (1)* 1979 -5.22 1978 -32.71 1980 c/s -12.56 (1)** 1981 -10.60** 1982 -54.69 1979 note: the 5% cvs are -5.50 and -58.33 for the adf/zt*and zα* tests, respectively (see table 1 of gregory and hansen, 1996) 4.4. long run estimates with the aim of estimating more rigorously the elasticity estimates for demand for gasoline function, this study embarks on specifying two different models, namely the ordinary least square (ols) and dynamic ols3 models. table 5 depicts different long run elasticity estimates as estimated from these models. as evident from the table, the long run elasticity estimates of both the ols and dols are not significantly different for gasoline function. to start with, price and income elasticity estimates seem to follow the a priori expectation in terms of their relationships with respect to signs and magnitudes. we find that both price and income elasticity estimates are negatively and positively signed, respectively. they are also shown to be inelastic, though with varying degree (here, income elasticities are found to be higher than price elasticities). finally, the error correction term of the model also follow the expected sign and magnitudes. 3 the dynamic ordinary least square (dols) is an asymptotically efficient estimator which eliminates the feedback in the cointegrating system as advocated by stock and watson (2003) and stock and watson (1993). it involves augmenting the cointegrating regression with lags and leads so that the resulting cointegrating equation error term is orthogonal to the entire history of the stochastic regressor innovation. modeling gasoline demand with structural breaks: new evidence from nigeria 7 table 5. long run elasticity estimates for gasoline demand models variables ols dynamic(ols) price-income interaction constant 0.063 (4.057) 0.016 (3.862) 0.192(4.001) income 0.714 (2.086) 0.511 (2.171) 0.358(1.916) price -0.015 (-2.031) -0.104 (-1.692) -0.016 (1.137) price-income -----------------------0.233 (1.874) sr ect(-1) -0.328 (-3.090) -0.432 (-1.975) -0.622 (-3.00) adj. r2 0.45 0.57 0.68 4.5. parameter stability test one of the aims of this study is to examine whether the estimated long-run relationship between the gasoline demand and its determinants in nigeria really exhibits the desired property of structural stability over time. hence, there is need to investigate how stable the parameters are. in order to further strengthen the robustness of our analysis, this study applies two different parameter stability tests, namely the hansen and quandt-andrews breakpoints test for one or more unknown structural breakpoint(s). since the estimation periods for our study cover the fairly volatile period, consequently, it is important to check whether the models (hence, parameters) under estimation are really stable over these periods. basically, hansen (1992) proposes three tests (lc, meanf, and supf) for parameter instability based on the full modified statistics.4 our aim specifically is to examine how stable the parameters are, thus the study is interested primarily in the lc statistics. the test which is performed using a trimming region of 15% simply examines the null hypothesis of no sudden shift in the regime (narayan and narayan, 2010). the results of the test for parameter instability for gasoline function are presented in table 6 together with their probability values. as evident from the results, these tests show signs of parameter stability. this, result is also confirmed by the g-h cointegration test, though structural breaks are identified in the system. table 6. hansen parameter instability test stochastic deterministic excluded lc statistic trends (m) trends (k) trends (p2) prob.* 0.056113 2 0 0 > 0.2 the study also applies the quandt-andrews breakpoints test with the null hypothesis of no breakpoints within a trimming region of 15%. the test statistics which are based on the maximum statistics, exp statistic and the ave statistic (see andrews, 1993; and andrews and ploberger, 1994) are reported in table 7. the entire summary statistic measures fail to reject the null hypothesis of no structural breaks within the period considered. table 7. quandt-andrews unknown breakpoint statistic value prob. maximum lr f-statistic (1982) 4.776451 0.8295 maximum wald f-statistic (1982) 4.776451 0.8295 exp lr f-statistic 1.480448 0.5889 exp wald f-statistic 1.480448 0.5889 ave lr f-statistic 2.775443 0.4590 ave wald f-statistic 2.775443 0.4590 note: since the original equation was linear, the lr f-statistic is identical to the wald f-statistic. 4 the null hypothesis of co-integration goes against the alternative of no co-integration, since the absence of cointegration is captured by an alternative hypothesis of parameter instability (lee and chang, 2005) international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.1-9 8 5. policy relevance and conclusion the primary goals of the paper center on investigating the cointgration status of gasoline demand model with a special focus on structural breaks/regime shifts, parameter stability and alternative model specification. hence, the study estimates gasoline demand function for nigeria from 1977 to 2008 with special emphases on alternative model specification, structural breaks and parameter stability. specifically, demand function for gasoline is estimated under two different models. the main finding as revealed in this study is that in the energy (gasoline) functions, price and income elasticity estimates are inelastic both in the long and short run. meanwhile, the findings from the price-income interaction parameter model show that the responsiveness of consumers to price changes tends to increase as income increases over time. there are evidences of structural breaks in the cointegration in the gasoline demand model. also, the result from parameter tests reveals that price and income elasticity estimates are stable. having identified plausible breaks in the systems, the test does suggest that a structural break in the cointegration vector is important and needs to be taken care of in the specification of gasoline demand function in nigeria. also, the structural breakpoints as identified in the results seem to match clearly with the corresponding critical economic incidents in nigeria. it is envisaged, therefore, that substantial policy lessons would be drawn from the findings of this study especially in the current phase of energy industry deregulation in nigeria. references akinboade. o., ziramba, e. and kumo, w. (2008), the demand for gasoline in south africa: an empirical analysis using co-integration techniques. energy economics, 30(6), 3222-3229. alves c. and rodrigo. (2003), short-run, long-run and cross elasticities of gasoline demand in brazil. energy economics, 25(2), 191-199. andrews, d. (1993), tests for parameter instability and structural change with unknown change point. econometrica. 61, 821–56. andrews, d. and ploberger, w. (1994), optimal tests when a nuisance parameter is present only under the alternative. econometrica. 62, 1383–1414. banerjee, a., lumsdaine, r. and stock, j. (1992), recursive and sequential tests of the unit-root and trend-break hypotheses: theory and international evidence. journal of business and economic statistics, 10(3), 271-287. baochen, y. and shiying, z. (2002), study on cointegration with structural changes. journal of systems engineering. 17(1), 26-31. bentzen, j. and engsted, t. (2001), a revival of the autoregressive distributed lag model in estimating energy demand relationships. energy, 26(1), 45-55. central bank of nigeria, central bank of nigeria statistical bulletin. 2008. chakravorty, u., fesharaki, f. and zhou, s. (2000), domestic demand for petroleum in opec countries. opec review, 24(1), 23-53. cheung, k. and elspeth, t. (2004), the demand for gasoline in china: a co-integration analysis. journal of applied statistics. 31(5), 533-544. dahl, c. and kurtubi. (2001), estimating oil product demand in indonesia using a cointegrating error correction. opec review, 25(1), 1-25. dahl, c. (1994), a survey of energy demand elasticities for the developing world. the journal of energy and development, 17(1), 1–47. dahl, c. (2006) survey of econometric energy demand elasticities. colorado school of mines, golden, colorado. dayo, f. and adegbulugbe, a.(1987), oil demand elasticities in nigeria. energy journal, 8(2), 31–41. de vita, g., k. endresen, and l.c. hunt. (2006), an empirical analysis of energy demand in namibia. energy policy, 34(18), 3447-3463. dickey, d., fuller, w. (1979), distribution of the estimators for autoregressive time series with a unit root. journal of the american statistical association. 74, 427–431. eltony, m. (2003), transportation demand for energy: the case of kuwait. the journal of energy and development, 28(2), 207-220. eltony, m. (2004), a model for forecasting and planning: the case for energy demand in kuwait. the journal of energy and development, 30(1), 91-108. modeling gasoline demand with structural breaks: new evidence from nigeria 9 engle, r., and granger, c. (1987), cointegration and error correction: representation, estimation, testing. econometrica, 55, 251–276. granger, c., and newbold. (1974), spurious regressions in econometrics. journal of econometrics, 111–120. gregory, a. and hansen, b. (1996), residual-based tests for cointegration in models with regime shifts. journal of econometrics, 70, 99-126 gregory, a., nason, j. and watt, d. (1996), testing for structural breaks in cointegrated relationship, journal of econometrics, 71, 321-341. hansen, b. (1992), tests for parameter instability in regressions with i(1) processes. journal of business and economics statistics, 10, 321–335 hendry, d. and juselius, k. (2000), explaining co-integration analysis: part i. energy journal, 21(3), 1-42. hendry, d. and juselius, k. (2001), explaining co-integration analysis: part ii. energy journal, 22(1), 75-120. hughes, j., knittel, c. and daniel s. (2006), short-run gasoline demand elasticity: evidence of structural change in the u.s. market for gasoline, working paper, institute of transportation studies university of california, davis. iwayemi. a., adenikinju, a. and babatunde, a. (2010), estimating petroleum products demand elasticities in nigeria: a multivariate cointegration approach. energy economics, 32, 73–85 johansen, s. (1991), estimating and hypothesis testing of cointegration vectors in gaussian vector autoregressive models, econometrica, 59(6), 1551–1580. lee, c.c. and c.p. chang (2005), structural breaks, energy consumption, and economic growth revisited: evidence from taiwan. energy economics, 27(6), 857-872. leybourne, s. and newbold, p. (2003), spurious rejections by cointegration tests induced by structural breaks. applied economics, 35, 1117-1121. mackinnon, j., haug, a. and michelis, l. (1999), numerical distribution functions of likelihood ratio tests for cointegration. journal of applied econometrics, 14, 563–577. perron, p. and vogelsang, t. (1992), nonstationarity and level shifts with an application to purchasing power parity. journal of business and economic statistics. 10(3), 301-320. pesaran, m., hashem, m., smith, r., and akiyama, t. (1998), energy demand in asian developing countries. oxford university press for the world bank and oxford institute for energy studies. philips, p. (1986), understanding spurious regression in econometrics. journal of econometrics, 33, 311-340. phillips, p. and ouliaris, s. (1990), asymptotic properties of residual-based test for cointegration. econometrica, 58, 165–193. phillips, p. and perron, p. (1988), testing for a unit root in time series regression. biometrika, 75, 335–346. polemis, l. (2006), empirical assessment of the determinants of road energy demand in greece.” energy economics, 28(3), 385-403. stock, j. and watson, m. (1993), a simple estimator of cointegrating vectors in higher order integrated systems, econometrica, 61(4) :783-820. stock, j. and watson, m. (2003), introduction to econometrics, pearson education, boston, ma. zivot, e. and andrews, d ( 1992), further evidence on the great crash, the oil-price shock, and the unit-root hypothesis, journal of business and economic statistics, 10(3), 251-270. international journal of energy economics and policy vol. 1, no. 4, 2011, pp. 107-115 issn: 2146-4553 www.econjournals.com the investments in renewable energy sources: do low carbon economies better invest in green technologies? antonio angelo romano dipartimento di statistica e matematica per la ricerca economica università di napoli “parthenope” –via medina, 40 – napoli (italy) – 80133. e-mail: antonio.romano@uniparthenope.it giuseppe scandurra dipartimento di statistica e matematica per la ricerca economica università di napoli “parthenope” –via medina, 40 – napoli (italy) – 80133. e-mail: giuseppe.scandurra@uniparthenope.it abstract: the aim of this study is to analyse the driving of investment in renewable energy sources in low carbon and high carbon economies. to address these issues, a dynamic panel analysis of the renewable investment in a sample of 29 countries was proposed. results demonstrate that the dynamic of investments in renewable sources is similar in the two panels, and depends by nuclear power generation, gdp and technological efficiency. results show that countries try to reduce their environmental footprint, decreasing the co2 intensity. based on the estimation results, we think that energy sustainability passes through the use of renewable resources that can complement the nuclear technology on condition that both exceed their limits. keywords: co2 intensity; dynamic model; nuclear energy jel classification: c23; o13; q42 1. introduction and background it has reached consensus worldwide that greenhouse gas (ghg) emissions due to anthropogenic causes are contributing to the ongoing global warming. in fact, the overall economic growth is based on traditional fossil fuels and, particularly, on a return to significant use of coal resulting in increased co2 emissions arising from the energy sector (jaccard et al. 2003; soytas and sarı, 2009), responsible, to a large extent, for climate change (sadorsky, 2009). the kyoto protocol, whose measures were deemed insufficient by many, has tried to limit the total emission of carbon dioxide and other greenhouse gases, addressing especially to the industrialized countries, some of which are making every effort to get out of the previous conditions of underdevelopment. more recently, international agreements in cancun (mexico, december 2010) have established the necessity for technology transfer to developing countries, reiterated the urgent need to limit co2 emissions to keep global temperature increase in the limit of 2°c, and finally, set out certain measures for the protection of forests. regarding, in particular, the electricity production, all the technologies employed have some impact on the environment and therefore, beyond the normal economic considerations of reliability and safety, a special ethical responsibility towards future generations is required for focusing on the “footprint” analysis of the plant environment. therefore, the negative environmental impact of the energy sector may be remarkably reduced by a larger share of renewable energy sources on total electricity generation, but the implementation of renewable energy strategies, as remembered by lund (2010) typically involve three major technological changes: energy savings on the demand side (blok, 2005; lund, 1999); efficiency improvements in the energy production (lior, 1997; 2002), and replacement of fossil fuels by various sources of renewable energy (afgan and carvalho, 2002; 2004). if a country wants to choose a largescale renewable energy implementation plans it has to integrate renewable sources in a new energy systems influenced by energy savings and efficiency measures (see, e.g. li, 2005; ghanadan and international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.107-115 108 koomey, 2005), but they, in the state of the art, alone would not suffice to achieve sustainability and keep climate change manageable (silva et al., 2011). recently, the international energy agency (iea) has identified a possible solution in increasing energy efficiency and in reducing co2 emissions. given the long lead times for developing new technologies and given the characteristics of renewable sources, the iea recommends the use of large nuclear facilities and technologies for carbon capture and storage (philibert, 2011). an important issue is related to the co2 emissions per gdp, or co2 intensity of gdp, resulting from fossil fuel combustion that is highly dependent on the weather and the overall demand for power. although it is also influenced by energy efficiency, carbon intensity is mainly subjected to energy structure, so it is a problem about energy quality (the proportion of clean energy in energy structure). some developed countries have reduced their co2 impact thanks to nuclear power plant deployment. other countries try to reduce their footprint improving energy efficiency or try the approach of changing energy structure, such as investing in renewable energy sources. both technologies do not produce polluting gases. a growing number of scientific works are dedicated to renewable energy sources and the impact of economic growth on its own sustainability in the medium-long perspective. many authors (see, e.g. sary and soytas, 2004; bradley et al., 2007, apergis and payne, 2010) investigate the causal relationship between renewable energy consumption and economic growth in heterogeneous countries but with inconclusive results. other studies investigated the normative perspective and the factor promoting energy from renewable source (bird et al., 2005; menz and vachon, 2006). recently, marques et al. (2010) analyze the drivers promoting renewable energy in european countries and finds that lobbies of traditional energy source and co2 emission restrain renewable deployment. evidently, the need for economic growth suggests an investment that supports, but does not replace, the installed capacity. obviously, physical and economic considerations require that the design and construction of new plants take their place alongside, not replace, the traditional plant. other authors analyzed the nuclear energy sustainability to oppose the renewable sources. matsui et al. (2008) examine role and potentials of nuclear energy system in a sustainable development framework. they argue that sustainable development is pursued through a policy of energy conservation and stress the importance that nuclear power plant plays in order to safeguard the environment. fosberg (2009) suggests that the way forward must go through the integration of renewable energy sources, because nuclear power can meet the shortage of renewable energy and löfstedt (2008), through a parallel between austria and slovakia, suggests that cannot be excluded a priori solution other than just to pursue policies aimed at overcoming the problem, but not to progress over time. marques and fuinhas (2011) try to analyze the factors behind the deployment of renewable energy, focusing on the effect of energy efficiency policies and measures. in a forthcoming paper, romano and scandurra (2011) highlights divergences in renewable investment decision in nuclear and not nuclear countries find the renewable energy sources and nuclear energy can be considered complementary in the production portfolio. the aim of this study is to investigate the driving of investments in renewable energy sources in a set of countries with low co2 intensity and in a complementary panel of countries that presents a high co2 per gdp. the former panel includes countries that have a low carbon dioxide emission per unit of gdp produced. these countries could be considered as “low carbon economies” because are efficient in production processes and use, in the electricity production portfolio, a high level of co2 free technologies, as nuclear or renewable energy sources. the latter panel, on the contrary, includes countries with a high environmental footprint. these countries produce more co2 per unit of gdp. in order to investigate the divergences among countries we focus on energy efficiency and amount of nuclear electricity consumption in the production portfolio. results allow us to have an idea for planning new power plants and understand the energy policy adopted by countries in these years in which environmental sensibility is changing. this paper addresses these issues by means of a dynamic panel analysis of the investments in renewable sources in a sample of 29 countries with distinct economic and social structures as well as different levels of economic development. the investments in renewable energy sources: do low carbon economies better invest in green technologies? 109 the organization of the paper is as follows: section 2 describes data and analyzes the energy policy of countries in the sample; section 3 discusses empirical results and policy implications and section 4 concludes the paper. 2. data the data is from the annual time series from 1980 to 2008, from the u.s. energy information administration (eia), of total renewable electricity net generation (ren), gross domestic product in $2000 constant prices (gdp), energy intensity (ei), co2 emissions and the nuclear electricity net consumption (nuc). different ways to evaluate the development of renewable energy source are proposed in literature. one is to measure the replacement of the traditional energy sources in the total energy supply while a second method is to measure the total amount of renewable energy produced (bird et al., 2005). marques et al. (2010) use the contribution of renewable to energy supply as a percentage of total primary energy supply while (carley, 2009) use the yearly logarithm of the renewable energy percentage of electricity generation. in our paper, we explain the investment in renewable energy sources (shren) as the ratio between renewable generation and the differences between total net electricity generation and the net electricity imports. for nuclear energy, we use the ratio of nuclear electricity net consumption (shnuc) and the differences between total net electricity generation and the net electricity imports. in this way we take into account the full portfolio in electricity generation. in fact, the remaining part, not included in the model, is all ascribable to fossil fuel. the share of renewable electricity net generation can be considered a proxy of investments in renewable energy source while the energy intensity, that is the total primary energy consumption per $ of gdp (btu per year 2005 u.s. $) is a proxy of technological efficiency. in order to reduce variability, gdp, ei and co2 are expressed through natural logarithm. panel dataset of oecd countries and developing countries (brazil, china and india) is used in order to limit the effect of the small time span of the aggregated data. there are three main issues that can be solved using a panel dataset. in fact, a panel dataset allows to: solve some problems of non-standard distributions of test statistics used for the identification of unit roots in the regression equations; have more informative data; reduce co-linearity between the variables. in order to identify investment decision in countries with low co2 per gdp or with high co2 per gdp ratio we consider the median of distribution of the countries’ mean of co2 intensity. countries that have mean of co2 intensity under the median level are considered low carbon economies while countries that are in the upper tail of distribution (over the median) can be considered high carbon economies. the sample has been split into two subsamples. the former which includes low carbon countries, and the latter including the remaining countries. of course, low carbon economies is a complex concept because involve a series of long-term policy plans in areas such as transport, energy and climate change. recently, european commission is looking at cost-efficient ways to make the european economy more climate-friendly and less energyconsuming and has proposed a roadmap (european commission, 2011) with a detailed analysis of cost-effective ways of reducing greenhouse gas emissions by 2050. in our paper we analyze the production of goods and services, and consider as low carbon economies the countries that produce more with a lower environmental impact. furthermore, the split of the sample using the median doesn’t allow analysis that follow the principle of granularity, but the need to assure a relevant sample dimension suggests the use of median rather than the quartiles of distribution. the first subsample, including austria, brazil, denmark, finland, france, ireland, israel, italy, japan, norway, portugal, sweden, switzerland and united kingdom is made up of the low carbon economies. the second subsample comprising the countries with high co2 per gdp: australia, belgium, canada, chile, china, greece, india, south korea, luxemburg, mexico, netherlands, new zealand, spain, turkey and usa. international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.107-115 110 given the lack of data, countries excluded by the oecd panel are: czech republic, poland, slovak republic, slovenia and germany (which is not included because of difficulty in time series reconstruction until 1989). accession candidate countries and enhanced engagement ones are also not considered. all the countries included in dataset are categorized as high income by world bank. only brazil, mexico, chile and turkey are categorized as upper middle income while china and india are in the lower middle income group. figure 1. carbon dioxide intensity (co2/gdp) for countries in the sample in figure 1 we report the bar graph of the mean distribution of co2 intensity in the sample analyzed (spain is on the median). we observe that there is a relevant divergences beetween switzerland and china, that are in the opposite of graphical representation. furthermore, the countries that are in the low and upper middle income classess (emerging economies) are in the second part of the graph (except brazil), near to other countries like usa, that haven’t ratified the international protocols to reduce the ghg emissions. in the graphical representation of co2 intensity per time we observe that the indicator presents a decreasing trend (except for brazil). this suggest that the production and environmental policies adopted by countries is based on future needs of environment and production efficiency. 2.1 the energy policy adopted by countries: a brief exploratory analysis before analyzing the dynamics of the panel of countries, an exploratory analysis to highlight the evolution of the choices of their energy policy is conducted. for this purpose, we use factor analysis, employing the same variables identified for the general model of the moments of arellano and bond (1991), which will be used below. to have a framework for the performance of countries considered in the 29 years between 1980 and 2008 is the main motivation of this decision. the values of the factor loadings are fairly stable over time, resulting in a distribution of the variables on the main floor that can identify a sufficiently plausible physical meaning of the two principal axes considered that explain about 70% of total variability. this is sufficient to highlight some features of the evolution of the energy choices made by various countries. the first principal axis, opposing the variables on the scale of production (lngdp), pollution (lnco2) and high energy intensity (lnei) to the share of renewable sources (shren) compared to total energy production. as for the second principal axis, contrasts with the variables related to co2 emissions and energy intensity, compared to the shares of renewable energy production with low emission of pollutants, that is renewable and nuclear energy (shnuc). consequently, countries with a high production obtained with conventional pollutants, and energy inefficient should be placed in the first quadrant (fig. 2). median the investments in renewable energy sources: do low carbon economies better invest in green technologies? 111 figure 2. factor analysis. distribution of countries considered in the work on the first factorial plane relative to 1980. the arrows indicate the most significant shifts observed in factorial plan of 2008. countries with a less significant production, produced primarily with conventional production processes are in the second quadrant. countries where a significant level of production is not achieved, however, even with an important application of renewable energy sources are placed in the third quadrant. finally, the fourth quadrant is reserved for countries with a high production level obtained with a significant proportion of nuclear energy and, therefore, a low level of co2 emissions. the distribution of the countries considered in the plan shows a substantial stability over time with some notable exceptions which will be now mentioned. figure 2 shows the distribution of countries on the main factorial plane as it appeared in 1980. in the figure, the arrows indicate significant shifts in the positions of some countries. such movements were observed within the 29-year period. the first general consideration that emerges from the figure is the loss of share of world production from western countries to the emerging reality of what can be considered as india, china, brazil, turkey and new zealand. equally we note that the number of countries gathered around the axis factor is relevant, which means that, at least with regard to the variables taken into account, they take sides energy choices not clearly defined. some countries, however, show a clear dynamic: brazil, china, india and turkey: these countries show a marked increase in their share of world production (especially india and china) provided by a low production efficiency and high rate of pollution from carbon dioxide. in particular, brazil and, even more, turkey, faced with a significant increase in production, seem to have definitely opted for conventional production processes; japan, france and the usa seem to have seen reduced their production levels compared to their competitors on the international market by shifting their energy choices even more, focused on the nuclear source. this is certainly evident with regard to france and japan. for the usa, the situation in the years in between the two extremes shown in figure 1, suggests an opportunity to consider the impact caused by the three mile island accident, which, in all likelihood, hindered the development of nuclear sources; sweden and switzerland are two countries that leave the nuclear quadrant and definitely seem to have opted for renewable energy sources. essentially, factor analysis shows that the nuclear option does not privilege or particularly depress investment into renewable energy sources while it is quite worrying that in many countries the trend is to not renew their energy efficiency and to not invest in renewable energy with low pollution emissions. international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.107-115 112 3. dynamic specification of renewable investment a dynamic specification of the equation that allows for slow adjustment is used. we estimate the following model: (1) where for country i (i=1,…,n) at time t (t=1,…,t), is a scalar, is the investment in renewable energy sources, is a matrix of independent variables while the error term (2) follows a one way error component model where denote a state – specific effect, denotes a year – specific effect and i  iid(0, 2 ) e t iid(0, 2). several econometric problems may arise from estimating equation (1) (baltagi, 2005): the variables in xit are assumed to be endogenous. because causality may run in both directions these regressors may be correlated with the error term; time-invariant country characteristics (fixed effects), such as geography and demographics, may be correlated with the explanatory variables. the fixed effects are contained in the error term in equation (1), which consists of the unobserved country-specific effects, i, and the observationspecific errors, ; the presence of the lagged dependent variable yit-1 gives rise to autocorrelation. with these assumptions, the ols estimator is biased and inconsistent (baltagi, 2005) so in this work we have employed the generalized method of moments (gmm) estimator proposed by arellano and bond (1991). the estimates are made separately for the two subsamples and for the full sample. the estimation results are in table 1. table 1. regression results in the samples low carbon countries high carbon countries full sample variables estimates variables estimates variables estimates constant -16.94*** constant -8.78*** constant -14.77*** shren-1 0.37*** shren-1 0.59*** shren-1 0.42*** lnei 0.48*** lnei 0.31*** lnei 0.44*** lnco2 -0.52*** lnco2 -0.38*** lnco2 -0,53*** lngdp 0.59*** lngdp 0.31*** lngdp 0.52*** shnuc -0.35*** shnuc -0.12*** shnuc -0.12*** sargan test 351.82*** sargan test 368.00*** sargan test 646.70*** ***: significant at 1%; **: significant at 5%; low carbon countries show the estimated autoregressive component significant at lag 1. we point out that the 1% increase in the level of renewable energy at time t-1 increases the same investment at time t of 0.37%, while gdp growth equates to an increase in the level of 0.59%. also the energy intensity shows a direct relationship with investment in renewable energy sources. emissions of carbon dioxide and nuclear consumption have an inverse relationship with the outcome variable, as expected. countries invest in renewable energy sources on the basis of past investments and gdp. also the technological efficiency affects the investment in renewable energy sources. the investments in renewable sources are decreased by the presence of the nuclear power plants. the second part of the table 1 shows the estimates for the countries with a high co2/gdp ratio. they base investment decisions in new renewable power plants on the past and, like previous countries, they are conditioned by the level of production and technological efficiency and help the countries to reduce the co2 emission. in fact, co2 emission presents, as expected, an inverse relationship. the share of nuclear energy generation shows also an inverse relationship. the investments in renewable energy sources: do low carbon economies better invest in green technologies? 113 furthermore, the estimates in the full sample confirm the previous results. all variables, except carbon dioxide emissions and the share of nuclear consumption, have a direct relationship with the outcome variable. in the samples, sargan test for overidentification reject the null, so the model instruments are correctly identified. the estimates show that past investments in renewable energy sources have a significant influence on these current investments in the three samples; in other words, there is a continuity of behavior in those countries that have shown sensitivity towards renewable energy sources. if it can have some statistical significance, the estimates in the low carbon economies are generally higher, in absolute value, than in the high carbon sample, except the autoregressive parameters. in fact, the influence of investments in renewable energy source is stronger in the high carbon countries than to the other countries (low carbon). the former try to invest mostly in renewable sources in order to reduce their footprint and respect the international agreement that they ratified. significant is the inverse relationship between renewable investments and share of nuclear consumption. probably, the continuous base load electricity ensured by nuclear power plants and the absence of greenhouse gas emission allow these countries to invest in additional renewable energy in a complementary way, in order to reach an optimal energy mix and to ensure the subsidies for investment in renewable energy. regarding industrial production technologies, factor analysis showed that the fast-growing countries tend to produce without particular attention to the environmental impact of production processes. other countries traditionally stable in the high income cluster tend, instead, to show more attention to technologies with lower environmental impact and improved energy efficiency. in fact, from the results of the estimates in table 1 we can observe the inverse relationship between co2 emissions and investments in renewable energy along with a direct relationship with energy intensity. on the other hand, the direct relationship with the level of national income shows that, reasonably, the resources needed for investment in renewable energy becomes available only after reaching a high enough gross domestic product. the differences in the investment choices and the need for sustainable energy development can be analyzed. the electricity generation stations based on renewable and nuclear sources can be considered complementary in terms of environmental impact and the investments in renewable energy sources can be conditioned by the presence of nuclear power plants. 4. conclusion in this paper we analyze the driving of investment in renewable energy sources in three samples. the first, in which are included low carbon countries (i.e. countries with a low co2 per gdp ratio) that base their electricity generation using fossil fuel but also renewable and nuclear sources while the second includes the countries that emit more carbon dioxide in atmosphere to produce a unit of gdp. third sample analyzes all countries considered in this paper. the presence of nuclear power plants depresses the trend of investment in renewable energy. this has been highlighted in the analysis in which a factor is the presence of economically advanced countries that strengthen their share of electricity from nuclear power. this result is consistent with the find of marques and fuinhas (2011). furthermore, the need to reduce the environmental footprint encourages high carbon economies to increase the renewable investments. in fact, reducing carbon intensity could be achieved mainly through increasing clean energy and reducing coal consumption of per unit gdp. if a country wants to achieve a certain goal of carbon intensity, it can choose the way of improving energy efficiency or try the approach of changing energy structure, such as investing in wind power, solar power or other renewable sources. returns can only be maximized when the marginal gains of improving energy efficiency and investing in clean energy become equal. thus, the central government could have more alternatives to formulate an effective clean energy strategic planning. with a concerted effort and strong policies in place, future energy efficiency improvements are likely to be very large. heat is one of many forms of "energy wastage" that could be captured to significantly increase useful energy without burning more fossil fuels (sawin and moomaw, 2009). the strategic importance of energy sectors requires similar attention by countries, in particular for the increasing demand of electrical power that is only partly offset by renewable energy sources. in fact, at this time, renewable energy sources do not guarantee continuity in the peak hours. alternatives are the use of fossil fuel based power plants that have, as expected, a great environmental impact and international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.107-115 114 contribute to increase the co2 emission or new nuclear power plants, that reduce the environmental footprint but requires a careful planning and enormous investments. in spite of the different productive characteristics they have and without considering production costs (which are regarded as secondary, assuming the energy as a commodity whose demand is virtually inelastic) some authors (verbruggen, 2008) argue that renewable sources and nuclear power technologies cannot have a common future in a perspective of sustainable energy. we think, however, that, at the state of the art, nuclear power is the only alternative to renewable energy sources because it permits to reduce the ghg emission and, primarily, to guarantee electricity also in the peak hours. furthermore, nuclear power plants can substitute fossil fuel based plants. our results are consistent with the points of view of lior (2011) and philibert (2011). the road to energy sustainability passes through the use of renewable resources that can complement the nuclear technology on condition that both exceed their own limits. inclusion of some socioeconomic variables and the impact of subsidies to investment in renewable sources will be aim of further researches. references afgan, n.h., carvalho, m.g. (2002), multi-criteria assessment of new and renewable energy power plants. energy, 27(8), 739–755. afgan, n.h., carvalho, m.g. (2002), sustainability assessment of hydrogen energy systems. international journal of hydrogen energy, 29(13), 1327–1342. apergis, n., payne, j. e. (2010), a panel study of nuclear energy consumption and economic growth. energy economics, 32, 545–549. arellano, m., bond, s. r. (1991), some tests of specification for panel data: monte carlo evidence and an application to employment equations. review of economic studies, 58, 277–297. baltagi, b. h. (2005), “econometric analysis of panel data – 3rd ed.”. john wiley & sons ltd, chichester. bird, l., bolinger, m., gagliano, t., et al. (2005), policies and market factors driving wind power development in the united states. energy policy, 33, 1397–1407. blok, k. (2005), enhanced policies for the improvement of electricity efficiencies. energy policy, 33,1635–1641. bradley, t., ewing, b. t., sary, r. and soytas, u. (2007), disaggregate energy consumption and industrial output in the united states. energy policy, 35, 1274-1281. carley, s. (2009), state renewable energy electricity policies: an empirical evaluation of effectiveness. energy policy, 37, 3071–3081. european commission (2011), roadmap for moving to a low-carbon economy in 2050. available on line [http://ec.europa.eu/clima/documentation/roadmap/docs/com_2011_112_en.pdf] (june 23rd, 2011) fosberg, c. w. (2009), sustainability by combining nuclear, fossil, and renewable energy sources. progress in nuclear energy, 51, 192–200. ghanadan , r, koomey, j.g. (2005), using energy scenarios to explore alternative energy pathways in california. energy policy, 33, 1117–1142. jaccard, m. k., nyboer, j., bataille, c., et al. (2003), modeling the cost of climate policy: distinguishing between alternative cost definitions and long run cost dynamics. the energy journal, 24(1), 49 73. li, x. (2005), diversification and localization of energy systems for sustainable development and energy security. energy policy, 33, 2237–2243. lior, n. (1997), advanced energy conversion to power. energy conversion and management, 38, 941–955. lior, n. (2002), thoughts about future power generation systems and the role of energy analysis in their development. energy conversion and management, 43, 1187–1198. lior, n. (2011), sustainable energy development: the present (2009) situation and possible paths to the future. energy, 35, 3976-3994. lofstedt, r. (2008), are renewables an alternative to nuclear power? an analysis of the austria/slovakia discussions. energy policy, 36, 2226-2233. the investments in renewable energy sources: do low carbon economies better invest in green technologies? 115 lund, h. (1999), implementation of energy-conservation policies: the case of electric heating conversion in denmark. applied energy, 64, 117–127. lund, h. (2010), the implementation of renewable energy systems. lessons learned from the danish case. energy, 35, 4003–4009. marques, a. c., fuinhas j. a. (2011), do energy efficiency measures promote the use of renewable sources? environmental science & policy, 14, 471–481. marques, a.c., fuinhas, j.a., pires manso, j. r. (2010), motivations driving renewable energy in european countries: a panel data approach. energy policy, 38, 6877 6885. matsui, k., ujita, h., tashino, m. (2008), role of nuclear energy in environment, economy and energy issues of the 21st century green house gas emission constraint effects. progress in nuclear energy, 50, 97-102. menz, f. c., vachon, s. (2006), the effectiveness of different policy regimes for promoting wind power: experiences from the states. energy policy, 45, 133–155. philibert, c. (2011), interactions of policies for renewable energy and climate. international energy agency working paper. romano, a.a., scandurra, g. (2011), new investments in electricity generation plants for sustainable energy: nuclear or renewable sources? proceeding of the 6th dubrovnik conference on sustainable development of energy, water and environment systems. sadorsky, p. (2009), renewable energy consumption, co2 emissions and oil prices in the g-7 countries. energy economics, 31, 456–462. sarı, r., soytas, u. (2004), disaggregate energy consumption, employment and income in turkey. energy economics, 26, 335–344. sawin, j.l., moomaw, w. r. (2009), renewable revolution: low-carbon energy by 2030. worldwatch report. available on line [http://www.worldwatch.org/files/pdf/renewable%20revolution.pdf} (june 05th, 2011) silva, s., soares, i., pinho, c. (2011), the impact of renewable energy sources on economic growth and co2 emissions a svar approach. fep working papers 407, universidade do porto, faculdade de economia do porto. soytas, u., sary, r. (2009), energy consumption, economic growth, and carbon emissions: challenges faced by an eu candidate member. ecological economics, 68, 1667 1675. verbruggen, a. (2008), renewable and nuclear power: a common future? energy policy, 26, 10361047. tx_1~at/tx_2~at international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(5), 142-149. international journal of energy economics and policy | vol 10 • issue 5 • 2020142 stock prices reaction to oil price fluctuations: empirical evidence from nigeria henry inegbedion1*, eseosa obadiaru2, olamide adeyemi1 1department of business studies, landmark university, omu aran, nigeria, 2department of accounting and finance, landmark university omu aran, nigeria. *email: inegbedion.henry@lmu.edu.ng received: 29 june 2019 accepted: 24 april 2020 doi: https://doi.org/10.32479/ijeep.8306 abstract the study investigated stock market reactions to oil price fluctuations in nigeria. a longitudinal design consisting of data on the nigerian stock market index, crude oil prices, exchange rate, interest rate, inflation rate and gdp for the period 1984-2019 was employed. the data were subjected to stationarity and cointegration tests using adf and johansen’s techniques. based on the results of the stationarity and cointegration tests, vector error correction model was used to analyse the research data. the results indicate that crude oil prices have short-run and long-run effects on stock market returns. exchange rate was found to have significant short-run effect on stock market returns. keywords: stock market returns; crude oil prices; oil price fluctuations; exchange rate; interest rate jel classification: h25 1. introduction from the onset, when nigerians had no idea about crude oil deposits in the country, agriculture was the mainstay of the economy. then, comprehensive development plans to take nigeria to lofty heights were put in place by the political actors and erstwhile nationalists who wrestled power from the colonial masters. the focus on agricultural sector was consistent with development economists’ “position that agricultural sector has a very vital role in the economic development process of a nation, emphasizing that agricultural productivity is fundamental for a sustainable development strategy” (oluwafemi et al., 2015 and inusa et al., 2018). in the 1960s, the contribution of the agricultural sector to the export earnings and employment was over 80%; and about “65% of the gross domestic product (gdp) and about 50% of the government revenue; the above contributions were despite the dependence of most of nigerian farmers on traditional tools and indigenous farming methods” (oluwafemi et al., 2015). the situation changed immediately crude oil was discovered in nigeria in commercial quantities coupled with the exploration and subsequent exploitation of the crude oil (inegbedion et al., 2019). the discovery of crude oil in commercial quantities precipitated the commencement of conscious disengagement in agricultural activities. ironically, while the agricultural sector contributed as much as over 80% (80%) to nigeria’s foreign exchange earnings in the 60s, it was the petroleum sector that took over the domination of nigeria’s foreign exchange earnings, contributing to as much as over 90% of nigeria’s foreign exchange earnings within the period (inegbedion et al., 2019). the domination of the other sectors of the nigerian economy by the crude oil sector caused nigerian economy to tilt towards a mono-product economy. the perceived ease with which oil wealth could be accumulated served as a major disincentive to prospective agriculturists. one of the early consequences was the threat to food security that led to endless importation of food stuffs by the federal government during the second republic in the 1980s; a development that triggered an unfavourable balance of trade and subsequently, persistent balance of payment deficits for a significant part of the 1980s and beyond. this journal is licensed under a creative commons attribution 4.0 international license inegbedion, et al.: stock prices reaction to oil price fluctuations: empirical evidence from nigeria international journal of energy economics and policy | vol 10 • issue 5 • 2020 143 it was the persistent balance of payment deficits that led to the introduction of structural adjustment programme (sap) when the military administration of general ibrahim badamosi babangida overthrew the civilian government of alhaji shehu shagari. as a major source of energy for domestic and industrial appliances, crude oil is of fundamental importance to the world’s economy. but several factors often interfere with world crude oil prices, thus making crude oil prices stochastic. however, fluctuating oil prices tend to exert a significant impact on any oil dependent economy. rapid fluctuations in oil prices make oil a key macroeconomic factor, owing to its creation of unstable economic conditions and its impact on global financial stability (anyalechi et al., 2019; and naifar and al dohaiman, 2013). the capital market is an engine room for development in any economy, nigeria inclusive. the ability of the capital market to live up to expectations in its all-important role of financial intermediation is largely dependent on investors’ confidence in the market. but fluctuations in stock prices in the capital market often cause major market performance indicators to deepen and thus precipitate loss of confidence on the part of investors. it is for this reason that this study investigates stock prices’ reaction to oil price fluctuations in nigeria. 2. literature review the financial market of any system is critical to economic development of that system. it consists of the money and capital markets. as the engine room of the capital market, the stock market in its role of financial intermediation functions as a mechanism or process or channel through which investors’ “savings are mobilized and efficiently allocated to achieve economic growth” (osamwonyi and osakioyaigbinoba, 2015). it ensures that intermediate and long term capital resources are accessible to industries that are in dire need of finance for development purposes through issuing of shares and stocks. consequently, the overall development of any economy depends on the pattern of the stock market and how well the stock market performs. in the past two decades, there have been insinuations that stock market performance is influenced by fluctuation in crude oil prices. the insinuations have attracted research interest globally on the relationships between oil price fluctuations and stock market performance. the series of studies, which have spanned oil exporting and oil importing countries have produced mixed results (osamwonyi and osakioyaigbinoba, 2015; and adebiyi et al., 2010). the volatility of crude oil prices cause distortions in major economies whether oil exporting or oil importing countries. for oil exporting countries, which often depend on oil revenues to finance their budgets, crude oil price fluctuations disrupt the projected revenue when there are downward fluctuations and could stimulate inflation when upward fluctuations result. for crude oil importing countries, the same disruptions could occur, with downward fluctuations leading to excess cash that may trigger inflation while upward fluctuations will have a negative impact on projected revenue. to this end, understanding the volatility of crude oil prices and the pattern of fluctuations, if any, is critical to effective policy formulation because of the potential for uncertainty that may result in all sectors of the economy and the attendant instability for both oil exporting and importing economies (gokmenoglu, 2015). it is for this reason that “oil is widely considered as the lifeblood of modern economies and the indexation of oil has long been regarded as the leading pricing mechanism in the energy market” (hulshof et al., 2016). as a major source of energy critical for technological development, a significant positive relationship has been found between countries’ advancement and their demand for crude oil. 2.1. empirical review anyalechi et al. (2019) investigated “the responsiveness of the stock market returns to fluctuation in oil prices in nigeria” the study employed the longitudinal design and used data for the period 1994-2016. unit roots test was done to test for stationarity and bound testing technique was employed to test for cointegration while ardl estimation technique was used to test for significance of data with due cognisance to the outcome of the unit roots and the cointegration tests. the findings revealed that changes in oil prices and inflation rate were positively related to stock market returns; but while oil price fluctuations had insignificant impact both in the long-run and the short-run, inflation rate had had significant influence on the short run but insignificant influence on the long run. exchange rate and interest rate were found to have negative influence on stock market returns but only the short-run effect of interest rate on stock market returns was found to be significant. igbinovia and igbinovia (2019) investigated the “reaction of the nigerian stock market to fluctuations in oil prices using time series data for the period 1981-2017.” the study employed a longitudinal design and performed cointegration test to ascertain the relationship between the variables on the long-run. based on the results of the cointegration test, error correction model was used to test for significance of data. results show that that the fluctuations in oil prices were positively related to stock market returns but the relationship was insignificant. nevertheless, exchange rate and interest rate exerted significant influence on stock market return. li et al. (2015) examined the “impacts of oil price shocks on the returns of china’s listed oil companies.” the study employed the longitudinal design and segregated global oil price shocks into global supply shock and demand shock, as well as domestic demand shock and precautionary demand shock. impacts of the various oil price shocks on the stock returns of china’s stocks were examined using samples from 2008 to 2013. the findings revealed that industries’ returns significantly responded to the fluctuations in oil prices and the response was found to be positive. ogiri et al. (2013) investigated oil price and stock market performance in nigeria. they employed the longitudinal design. augmented dickey fuller test was used to test for stationarity while johansen’s test was done to test for cointegration. vector error correction and vector auto regression were used to test for significance of data. results indicated that stock price movement is significantly influenced by fluctuations in crude oil prices. specifically, it was revealed that stock market performance is significantly linked to crude oil price fluctuations osamwonyi and osakioyaigbinoba (2015) investigated oil price volatility and stock market returns in nigeria. they employed a inegbedion, et al.: stock prices reaction to oil price fluctuations: empirical evidence from nigeria international journal of energy economics and policy | vol 10 • issue 5 • 2020144 longitudinal design and data were collected for the period 1980-2012. they performed stationarity and cointegration tests to examine the variables’ parameters consistency even with change in time origin as well as long run relationships. data were analysed using the vector error correction mechanism to estimate the dynamic patterns of adjustment in oil price volatility with respect to stock market instability within the vecm context. they found the perceived deleterious effects of oil price fluctuations in the stock market to be substantive, and oil price instability was found to have extensive negative effects on stock returns in the short run, and intensifies volatility in the market in the long run. however, externally determined factors were shown to play more active roles in stock price volatility in nigeria than fluctuations in crude oil prices. olufisayo (2014) examined “the relationship between changes in oil prices and stock market growth in nigeria.” the study was longitudinal and data were collected for the period 1981-2011. data were analysed using vector error correction modelling approach. the results showed that crude oil prices and exchange rate have significant impact on stock market growth. oil price change was also found to have a causal relationship with stock market performance. the vecm shows that stock market performance is significantly dependent on shocks occasioned by oil price fluctuations. siddiqui (2014) investigated “oil price fluctuation and stock market performance in pakistan” with a view to ascertaining the extent to which international oil price fluctuation influence the performance of stock markets in pakistan. the longitudinal survey was employed and kse-100 index provided the required data for stock market performance. the predictive power of political stability in explaining stock market performance was also reckoned with. the findings indicate a positive correlation between oil prices, exchange rate and foreign private portfolio investment and stock market performance. also democratic governance was found to negatively impact stock market performance. in view of the foregoing, the following hypotheses were tested: h01: fluctuations in the prices of crude oil do not have any significant influence on macroeconomic variables like interest, exchange and inflation rates h02: macroeconomic variables (interest, exchange and inflation rates) do not significantly impact on stock price movements h03: fluctuations in the prices of crude oil do not have any significant influence on stock price movements the results of the empirical review indicate that oil price fluctuations influence inflation rate, exchange rate and interest rate; which, in turn, influence stock prices (figure 1). 2.1.1. gap in literature the problem of oil price fluctuations and stock market returns has attracted the attention of many authors in the past two decades. foremost among them are anyalechi et al. (2019), igbinovia and igbinovia (2019) gourène and mendy (2018), li et al. (2015), ogiri et al. (2013), osamwonyi and osakioyaigbinoba (2015), olufisayo (2014) and siddiqui (2014), among others. the studies have produced mixed results. while some of the studies did not find any statistically significant relationship between oil price changes and stock market performance (anyalechi et al., 2019; and igbinovia and igbinovia, 2019), others found positive and statistically significant relationship between oil price fluctuations and stock market returns (li et al., 2015; ogiri et al., 2013; osamwonyi and osakioyaigbinoba, 2015; and olufisayo, 2014). the mixed results indicate the need for further studies on the problem. besides, none of the previous studies made any attempt to explain the reasons for the divergent results. neither did any of the previous studies make any attempt to mitigate or isolate the impact of the global financial crisis on stock market returns with the period 2007-2009 at a time the crude oil prices had an upsurge. this study sought to fill these gaps 2.2. theoretical framework this study is anchored on the symmetric or linear theory. “the theory provides a strong correlation between oil prices and critical macroeconomic measures and explains why upward oil price fluctuations were responsible for every post-world war ii recession except the 1960’s depression” (ikechukwu and omotayo, 2019). the earlier studies of burbidg and harrison (1984) as well as gisser and goodwin (1986) provided support that serve to validate the symmetric theory. arising from the symmetric theory and given the significant contribution of crude oil sales to nigeria’s foreign exchange earnings, nigeria’s projected revenues in any fiscal year are largely dependent on crude oil earnings. thus, government expenditure, which is a major stimulant of national income, is significantly influenced by fluctuations in crude oil prices. this explains the choice of the symmetric theory. 3. methodology the study employed the longitudinal design and data were collected over a 35-year period (1985-2019) on the key variables, oil prices, interest rate, inflation rate, exchange rate and the nigerian stock exchange (nse) index (all-share index), as the aggregation of share price gains and losses within the period under investigation, the all-share index (asi) was deemed suitable to capture the stock market returns in the nigerian capital market. the data were sourced from statista-the statistics portal and the cbn statistical bulletin. augmented dickey fuller test was performed to test for stationarity of all the variables since stationarity is sacrosanct to the usability of the results of any time series study. cointegration test, using johansen’s technique, was further performed to check for the relationship between the variables on the long-run. the significance of the cointegration prompted the decision to use vector error correction model as the test for significance of the studies’ variables. 3.1. model specification the study’s model was specified as: sp=0+ 1 cop + 2 intr + 3 infr + 4 exchr + 5 gdp + et (1) figure 1: conceptual framework inegbedion, et al.: stock prices reaction to oil price fluctuations: empirical evidence from nigeria international journal of energy economics and policy | vol 10 • issue 5 • 2020 145 where: ∆ sp=changes in stock prices ∆cop=changes in crude oil prices intr=rate of interest infr=rate of inflation exchr=exchange rate gdp=gross domestic product e. =stochastic error term 0=proportion of the variation in stock prices that is not explained by changes in explanatory and control variables; 1=slope of changes in crude oil prices i (i = 2 − 5) represent the slopes of the other macroeconomic variables. in line with anyalechi et al. (2019) and engle and granger (1987), equation (i), which presents a long-run relation between stock market return and the explanatory variables, can be modified to accommodate a short-run dynamic adjustment process as follows: 1 2 , 0 1 , 1, 2 , 1,1 0 3 4 3 , 1, 4 , 1,0 0 5 6 5 , 1, 6 , 1, 1, 0 0 sp + β β β β β β β δε − −= = − −= = − − −= = ∆ ∆ ∆ + ∆ + ∆ + ∆ = + ∆ ++ + ∑ ∑ ∑ ∑ ∑ ∑ m m t j i j t j i j t ji i m m i j t j i j t ji i i j t j i j t j t i ti i sp cop intr infr exchr gdp e (ii) where ∆represents “change in” operationalized by the differencing operator, mi (i = 1 − 5) = the number of lags, representing the speed of adjustment parameter; and εt−1 is the error correction term derived from the residuals of equation (i) which is lagged by one period. this method of estimation assumes that the variables are cointegrated, that is.all the variables are integrated of order one i(1) while the error term should be stationary, i(0). but if the variables in (i), instead of exhibiting i(i), they have a combination of i(1) and i(0) then another method of co-integration (ardl) is employed. this technique is that of pesaran et al. (2001). this approach is replaces εt−1 in equation (ii) with its equivalent in equation (v). by linear combination of the lagged variables, εt−1 is substituted as shown in equation (iii) (anyalechi et al., 2019). solving equation (i) for and lagging the result by one period and substituting the result in equation (ii) gives equation (iii). 1 2 , 0 1 , 1, 2 , 1,1 0 3 4 3 , 1, 4 , 1,0 0 5 6 5 , 1, 6 , 1, 7 10 0 8 1 9 1 10 1 11 1 12 sp + − −= = − −= = − − −= = − − − − ∆ φ φ ∆ φ ∆ φ ∆ + φ ∆ + φ ∆ + φ ∆ φ φ φ = + + + + + + +φ φ φ ∑ ∑ ∑ ∑ ∑ ∑ n n t j i j t j i j t ji i n n i j t j i j t ji i n n i j t j i j t j ti i t t t t sp cop intr infr exchr gdp sp cop intr infr exchr gdp+ tw (iii) the ardl equivalent of the error correction model is obtained by replacing the lagged level variables by ectt−1 as follows: 1 2 1 0 1 , 1, 2 , 1,1 0 3 4 3 , 1, 4 , 1,0 0 5 6 5 , 1, 6 , 1, 10 0 sp + λ λ λ λ λ λ λ δ θ − − −= = − −= = − − −= = ∆ ∆ ∆ ∆ + ∆ + ∆ = + + + ∆ ++ ∑ ∑ ∑ ∑ ∑ ∑ k k t i j t j i j t ji i k k i j t j i j t ji i k k i j t j i j t j t j ti i sp cop intr infr exchr gdp ect (iv) in (iv) the speed of adjustment is represented by a negative and statistically significant estimation (anyalechi et al., 2019). this negative condition must hold for the model to be seen as appropriate in the context. 3.2. measurement of variables the measurement procedures adopted for stock price movements (dependent variable), crude oil prices (independent variable) as well as interest rate, inflation rate and exchange rate (control variables) are explained here. 3.2.1. stock market price changes the stock market price changes were measured by the asi of the nse since the asi represents the aggregation of price gains and losses on any trading day. although the monthly values of the required data for the period 1985-2014 were available, the monthly values were not used. the non-employment of monthly values was a calculated attempt to reduce the influence of the global financial crises on the fluctuations in the prices of shares and by implication, stock market returns within the period mid 2007early 2009 as the behaviour of stock prices within the period was mainly under the influence of the global financial crises rather than oil prices. to this end, half-yearly data, which captured the fluctuations in stock prices, were employed. the half-yearly data consisted of the maximum and minimum data in each of the halves. specifically, if the maximum value in the year occurred in on half, say july-december, the minimum in januaryjune was included to complete the two data points. if the maximum value occurred in january-june, the minimum value in julydecember was included to complete the required two data points. 3.2.2. exchange rate the exchange rate of nigerian naira (n––) to the dollar ($) for the period 1984-2019 was used. 3.2.3. interest rates the interest rate employed was the bank lending rate for the period under consideration. the choice of this rate was informed by the need to examine the influence of interest rate on investors’ choice of investment alternatives. 3.2.4. inflation rate the inflation rates employed were the official inflation rates used in deflating the nominal values of gdp for the period to obtain the real gdp. 3.2.5. crude oil prices the average prices per annum for the period 1984-2019 were used. half-yearly data consisting of the maximum and minimum data in each of the halves per annum as was done in the measurement procedure employed for stock market returns was also used to measure crude oil inegbedion, et al.: stock prices reaction to oil price fluctuations: empirical evidence from nigeria international journal of energy economics and policy | vol 10 • issue 5 • 2020146 price fluctuations. this was to ensure that the measurement procedure of crude oil prices was consistent with that is stock market returns. 4. findings 4.1. stationarity test results of the unit roots stationarity tests show that one of the variables, gdp, was stationary at level while the remaining five variables, stock changes, crude oil prices, exchange rate, interest rate and inflation rate were all significant at first difference (table 1) 4.2. cointegration test results of the cointegration test indicate that the asymptotic significant probabilities associated with the null hypotheses that: there is no cointegration equation, at most one, at most two, at most 3, at most 4 and at most 5 cointegration equations were 0.0016, 0.0078, 0.0351, 0.1257, 0.2258 and 0.6181 respectively. thus, while we may reject the hypotheses that there is no cointegrating equation and there is one cointegrating equation, we cannot reject the hypotheses that there are at most two, three, four and five cointegrating equations. the implication is that all the variables are cointegrated and thus, there is a long-run relationship between the variables (table 2). two of the control variable (inflation rate and gdp) were found to be collinear. the two variables were thus dropped from the model. the final estimation was done with four variables, stock price movements (dependent variable), crude oil prices (independent variable) as well as exchange rate and interest rate (control variables). estimated equation d(spc) = c(1)*(spc(−1) −0.403319569004*cop(−1) −0.0311432969965*exchr(−1) +0.331872850644*intr(−1) +0.219743090731) + c(2)*d(spc(−1)) + c(3)*d(spc(−2)) + c(4)*d(cop(−1)) + c(5)*d(cop(−2)) + c(6)*d(exchr(−1)) + c(7)*d(exchr(−2)) + c(8)*d(intr(−1)) + c(9)*d(intr(−2)) + c(10) results of the error correction model present the long run equilibrium relations. the cointegration equation is estimated as: spc +0.2197 – 0.4033 cop (−1) +0.03114 exchr (−1) +0.3319 intr (−1) =0; thus, spc= – 0.2197 + 0.4033 cop (−1) −0.03114 exchr (−1) – 0.3319 intr (−1) the results indicate that a unit change in crude oil prices will lead to a 40.33% change in stock prices, a unit change in exchange rate will cause a 3.114% change in stock prices while a unit increase in interest rate will cause a 33.19% reduction in stock prices. the results further show that the explanatory variable (cop) has positive long-run relationships with spc. two or the control variables (exchr and intr) had negative long-run relationship with spc (table 3). however, only crude oil prices were found to significantly influence spc on the long run. following the long-run coefficients of the cointegration equations, the short-run coefficients were estimated through the error correction model (ecm) component/the ecm estimations in the cointegration equation show that the coefficients of all the regressors have the hypothesized (a priori) signs. two of the variables, crude oil prices and exchange rate, had statistically significant short run influence on stock price changes at the 95% confidence level, but while crude oil prices had significant positive influence on stock market returns, exchange rate had significant negative effect, also, interest rate had insignificant short-run negative influence on stock price movements (table 4). furthermore, the coefficient of the error correction term (ect) is −0.2745 and this coefficient had a calculated t of −2.7412 and an asymptotic significant probability value of 0.0077. thus, the speed of adjustment after short-run fluctuations is 27.45.9%. the values indicate the speed of restoration of the system to equilibrium after a previous deviation. the implication is that previous period disequilibrium is corrected at a speed of 27.45% (table 4). lastly, results of the error correction model show that the explanatory variable (crude oil prices) and the control variables table 1: unit root test sn. variable p value at level p value at 1st difference significant at 1. spc 0.6474 0.0002 1er difference 2. crude oil prices 0.5277 <0.001 1st differences 3. exchr 0.9797 <0.001 1st difference 4. intr 0.1357 <0.001 l1st difference 5. inflr 0.1958 <0.001 1st difference 6. gdp 0.0025 <0.001 level table 2: cointegration test hypothesized eigenvalue trace 0.05 critical no of ces value prob. *** none 0.4253 113.8462 95.7537 0.0016 at most 1 0.3738 78.9463 61.8189 0.0078 at most 2 0.3097 49.4564 47.8561 0.0351 at most 3 0.2160 26.1027 29.7971 0.1257 at most 4 0.1539 10.7743 15.4947 0.2258 at most 5 0.0039 0.24859 3.84147 0.6181 table 3: estimated vector error correction model dependent variable spc standard error t-statistic significant p remark variable coefficient cop (−1) 0.4033 0.0536 7.2167 0.0010 significant exchr (−1) 0.0311 0.0875 1.5089 0.062 ns intr (−1) −0.3319 0.2570 −1.2912 0.0752 ns constant 0.2197 inegbedion, et al.: stock prices reaction to oil price fluctuations: empirical evidence from nigeria international journal of energy economics and policy | vol 10 • issue 5 • 2020 147 (interest rate and exchange rate) explain about 21.84% of the variation in stock price movements as shown by the coefficients of variation (table 5). diagnostic tests were also performed. firstly, a test for serial correlation was performed on the residuals using breusch-godfrey test. the results indicate an asymptotic probability value of 0.0732 for the chi-square statistic. thus, we cannot reject the null hypothesis that the series are not serially correlated 2.1193 (table 6). which lies between du and 4-du where du is the upper value of the durbin watson statistic. the non-correlation of the stochastic error terms is an indication that the results are not spurious. a stability test was also performed on the model and the results indicate that the model is stable since the trend is perfectly situated between two standard errors (figure 2). 5. discussion of findings the results indicate that there is significant direct (positive) relationship between stock market returns, measured by stock price changes, (dependent variable) and oil price fluctuations (the explanatory variable). the implication is that increases or decreases in crude oil prices lead to increases or decreases in stock prices. in other words, fluctuations in crude oil prices stimulate fluctuations in stock prices in the same direction. thus, instability in crude oil prices stimulates disequilibrium in stock market returns in the nigerian stock market. the results are consistent with those the studies of li et al. (2015) ogiri et al. (2013), osamwonyi and osakioyaigbinoba (2015) as well as olufisayo (2014) but inconsistent with the findings of anyalechi et al. (2019) as well as igbinovia and igbinovia (2019). the results further indicate that crude oil price changes have both short-run and long-run significant impacts on stock market returns. the results also indicate that interest rate has negative influence on stock market returns but the influence is not statistically significant. furthermore, exchange rate has only short-run significant influence on stock market returns but no significant long run effect. this is partially consistent with igbinovia and igbinovia (2019) as well as siddiqui (2014) but inconsistent with anyalechi et al. (2019). the results of the diagnostic tests for serial correlation and stability provide reasonable support for the reliability of the model estimates since the outcomes were found to be favourable. 6. conclusion there appears to be an increase in empirical literature on the relationship between oil prices and stock markets returns. recent empirical studies in oil producing and nonoil producing countries have sought to explain the impact of oil price volatility on stock market performance with a view to explaining the linkage between oil price volatility and stock market performance. we examined stock market reaction to oil price fluctuations by investigating the extent to which oil price fluctuations impact on stock price changes. interest rate and exchange rate were used as control variables. based on the findings, we conclude that oil price fluctuations have significant long-run and short-run positive influences on stock market price changes and thus stock market returns. to this end, persistent increases in oil prices, leading to positive changes in crude oil prices stimulate increases in stock prices; leading to bullish runs in the capital market. in the same vein, persistent decreases in oil prices, leading to negative changes in crude oil prices precipitate decreases in stock prices; leading to bearish runs in the capital market. thus the stock market reacts positively to fluctuations in crude oil prices. table 6: breusch godfrey serial correlation lm test f statistic 1.2486 prob. (f2 23) 0.0547 obs. r squared 3.6238 prob. chi-square (2) 0.0732 durbin watson 2.1193 figure 2: stability test table 5: estimated vector error correction model error correction d (spc) d(cop) d (exchr) d(intr) coin eq1 −0.2745 0.5035 0.3085 −0.1393 (0.10014) (0.1607) (0.1607) (0.1383) [−2.7412] [1.8056] [1.8092] [−1.007] dspci (−1) 0.2884 0.6593 −0.1816 −0.2497 (0.1518) (0.4227) (0.2435) (0.2096) [1.9008] [1.5599] [−0.7459] [−1.1913] r-squared 0.2184 0.3259 0.2526 0.3418 adj r-squared 0.0857 0.2115 0.2426 02301 sum sq resids 1652.81 1281.97 425.49 315.26 s.e. equation 5.483 15.5526 8.9600 7.7126 f-statistic 1.6456 2.8473 3.3070 3.0584 log likelihood −192.307 −256.835 −222.093 212.6483 akaike aic 6.4224 8.4709 7.3690 7.0680 schwarz sc 6.7626 8.8111 7.7082 7.4084 table 4: estimated ecm equation coefficients and sig p dependent variable coefficient standard error t statistic significant p c (1) −0.277 0.0988 −2.8046 0.0077 c (2) 0.2841 0.1494 1.9008 0.0627 c(3) 0.2069 0.1582 1.3080 0.1964 c (4) 0.1430 0.0536 2.6700 0.0100 c (5) 0.0067 0.0561 0.1186 0.9061 c (6) −0.0322 0.0875 −2.3675 0.0417 c (7) −0.0854 0.0796 −1.0733 0.2979 c (8) 0.0587 0.0853 0.6889 0.4938 c (9) 0.0819 0.0837 0.9784 0.3322 c (10) −0.0234 0.8470 −0.0276 0.9780 inegbedion, et al.: stock prices reaction to oil price fluctuations: empirical evidence from nigeria international journal of energy economics and policy | vol 10 • issue 5 • 2020148 this study has made significant contribution to knowledge in management science, financial management and social science literature. there is no doubt that numerous studies have attempted to explain the relationship between crude oil prices and stock market performance. in this study, we observed that the period of the global financial crisis (mid 2007 to early 2009) distorted the values of stock market prices and by implication, stock market returns. the downward trend in stock prices within the period had nothing to do with the explanatory variable of the study (oil prices) but mainly the financial crises that engulfed the globe at the time. consequently the maximum and minimum values of stock price index in each year were used to capture the fluctuation of stock market prices. thus, half-yearly data, which captured the fluctuations in stock prices, were employed. this was done to reduce the distortions of the stock market returns within the period of the global financial crises. the same measurement procedure was applied to crude oil prices, interest rate and exchange rate. by so doing, the influence of the global financial crises on stock market returns within the period was minimised. this forms the point of departure of this study from previous studies because none of these studies seem to have reckoned with the possible impact of the global financial crises on stock market returns for a period of almost 2 years when, ironically, crude oil prices were very high for a significant part on the time. the study is not without some limitations that suggest the need for further studies. the control variables (exchange rate and inflation rate) included in the study was randomly selected from a host of other likely predictors. the extent to which these control variables are or are not the best to control for the relationship between crude oil prices and stock market returns is a limitation. in an attempt to reduce the impact of the global financial crisis on stock market returns, the study employed half-yearly data of the highest and lowest values and thus had 70 data points for the period 1984-2019 because the first trading on the floor of the nigerian stick market with all-share index was in 1985. two data points were then inputted for annual data instead of 12 monthly data per annum which would have resulted in 432 data points within the period. this, probably, would have been more robust considering the number of variables in the model. this is a methodological imperfection and thus a limitation to the results of the study. the above limitations indicate the need for further studies to fashion out other techniques to mitigate the influence of the global financial crises on global stock market returns and thus resolve the current stalemate in empirical literature on the impact of crude oil price fluctuation on stock market returns. 6.1. recommendations in view of the problem definition and research findings, the following recommendations are suggested: policy makers in the oil producing countries should make adequate efforts to stabilise crude oil prices so that stock market returns will not be subjected to unnecessary fluctuations. this can be achieved by collaborating with member countries in the organisation of petroleum exporting countries (opec) to regulate oil output to ensure that output fluctuation is minimised. secondly, investors in the stock market should study the trend in oil price movement to know when to engage in persistent purchases or when to engage in persistent sales, depending on whether they are bearish or bullish investors. arising from the results of this study, investors should use crude oil prices as a barometer for ascertaining the trend in the stock market. thus, when stock market performance appears to be unimpressive and oil price are on a downward trend, it should largely explain the behaviour in the stock market and allay their fears; but when stock market returns are unimpressive and crude oil prices are rising, it should give some source of concern to the investors. lastly, investors should not panic when oil prices appear to be persistently down because after every downward trend an upward trend will begin at some point in time to signal the reversal of the previous trend. 7. acknowledgement we acknowledge the authorities of landmark university, nigeria for providing the necessary funding for this study references adebiyi, m.a., adenuga, a.o., abeng, m.o., omanukwue, p.n. (2010), oil price shocks, exchange rate and stock market behaviour: empirical evidence nigeria. available from: http://www.citeseerx. ist.psu.edu/viewdoc/download?doi=10.1.1.589.4418 and rep=rep1 and type=pdf. anyalechi, k.c., ezeaku, h.c., onwumere, j.u.j., okereke, e.j. (2019), does oil price fluctuation affect stock market returns in nigeria? international journal of energy economics and policy, 9(1), 194-199. burbidg, j., harrison, a. (1984), testing for the effects of oil-price rises using vector autoregression. international economic review, 25(2), 459-484. engle, r.f., granger, w.j. (1987), co-integration and error correction: representation, estimation. econometrica, 55, 251-276. gisser, m., goodwin, t.h. (1986), crude oil and the macroeconomy: tests of some popular notions: journal of money credit and banking, 18, 95-103. gokmenoglu, k.k. (2015), the interactions among gold, oil, and stock market: evidence from s and p500. procedia economics and finance, 25, 478-488. gourène, g.a.z., mendy, p. (2018), oil prices and african stock markets co-movement: a time and frequency analysis. journal of african trade, 5(1-2), 55-67. hulshof, d., van der, m.j., mulder, m. (2016), market fundamentals, competition and natural-gas prices. energy policy, 94, 480-491. igbinovia, i.m., igbinovia, e.l. (2019), oil price volatility and stock market returns in an emerging economy: evidence from nigeria. sriwijaya international journal of dynamic economics and business, 3(9), 193-206. ikechukwu, k., omotayo, m. (2019), the impact of changes in oil price on stock market: evidence from africa. international journal of management, economics and social sciences, 8(3), 169-194. inegbedion, h.e., obadiaru, e., obasaju, b., asaleye, a., lawal, a. (2019), financing agriculture in nigeria through agricultural extension services of agricultural development programmes (adps). f1000 research, 7, 1833. inusa, b.m., daniel, p.c., dayagal, d.f., chiya, n.s. (2018), nigerian economic growth and recovery: role of agriculture. international journal of economics and management sciences, 7(2), 1-5. li, q., cheng, k., yang, x. (2015), impacts of oil price shocks on the https://econpapers.repec.org/article/ieriecrev/ inegbedion, et al.: stock prices reaction to oil price fluctuations: empirical evidence from nigeria international journal of energy economics and policy | vol 10 • issue 5 • 2020 149 returns of china’s listed oil companies. energy procedia, 75, 26042609. naifar, n., al dohaiman, m.s. (2013), nonlinear analysis among crude oil prices, stock markets’ return and macroeconomic variables. international review of economics and finance, 27(c), 416-431. ogiri, i.h., amadi, s.n., uddin, m.m., dubon, p. (2013), oil price and stock market performance in nigeria: an empirical analysis. american journal of social and management sciences, 4(1), 20-41. olufisayo, a.o. (2014), oil price and stock market: empirical evidence from nigeria. european journal of sustainable development, 3(2), 33-40. oluwafemi, z.o., adedokun, m.a., ogunleye, a.a., oladokun, y.o.m. (2015), an empirical analysis of the contribution of agricultural sector to nigerian gross domestic product: implications for economic development. developing country studies, 5(21), 36-42. osamwonyi, i.o., osakioyaigbinoba, n. (2015), oil price volatility and stock market returns in nigeria. international journal of management science research, 2(1), 15-34. pesaran, h.m., shin, y., smith j.r.j. (2001), bounds testing approaches to the analysis of level relationships. applied economics, 16, 289-326. siddiqui, m.m. (2014), oil price fluctuation and stock market performance: the case of pakistan. american research institute for policy development, 2(1), 47-53. https://ideas.repec.org/a/eee/reveco/v27y2013icp416-431.html https://ideas.repec.org/a/eee/reveco/v27y2013icp416-431.html https://ideas.repec.org/s/eee/reveco.html . international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(5), 29-34. international journal of energy economics and policy | vol 8 • issue 5 • 2018 29 factors effect on corporate cash holdings of the energy enterprises listed on vietnam’s stock market phung anh thu1*, nguyen vinh khuong2 1faculty of finance and accounting, nguyen tat thanh university, ho chi minh city, vietnam, 2faculty of accounting and auditing, university of economics and law, viet nam national university, ho chi minh city, vietnam. *email: phunganhthu1990@gmail.com abstract this study examines the factors effect on corporate cash holdings of the energy enterprises listed on vietnam’s stock market. our data set includes 28 energy companies on vietnam stock markets (hnx and hose) in the period from 2010 to 2016, with a total of 196 firm-year observations being collected. we used gmm estimator to test our hypotheses. the results show a negative association between leverage, return on assets, operating cash flow and corporate cash holdings while a tangible asset has a positive relationship. keywords: corporate cash holdings, energy enterprises, vietnam jel classifications: g33, g31 1. introduction cash resources furnish firms extremely demanded fiscal independence, thereby allowing them to arise their strategy with restricted external resistance (boubaker et al., 2015). in addition, the cost of using internal capital is perpetually less expensive than external capital. companies with a high cash-flow ratio will have more investment options to maximize profits when the money is tight. the factors effect on cash holding justifies examination because cash holding has expenses. corporations strength handle cash to suffice future obligation but meantime, they may not fund in profitable outlines. high levels of cash may consequently designate agency cost between manager and shareholders (jensen, 1986). another important cost of holding cash is the opportunity cost if firms are patronizing off their profitable schemes to keep it. the examination of the operators of the lately recognized great corporate cash holding is of interest both from academic and practical research (al-najjar, 2013; al-najjar and clark, 2017; boubaker et al., 2015). hence, investigations correlated to cash control are intermittent in academic literature, particularly due to the fact that firms keep the significant percentage of their assets in cash. these difficulties are linked to the occurrence of market shortcomings, such as asymmetric information, agency problems, transaction costs and financial distress (ferreira and vilela, 2004; jensen, 1986; jensen and meckling, 1976; martínez-sola et al., 2013). several investigations have examined the influences of asymmetric information on corporate cash holdings (al-najjar and clark, 2017; dittmar et al., 2003; ferreira and vilela, 2004; garcíateruel et al., 2009; kim et al., 1998; manoel et al., 2018; opler et al., 1999; ozkan and ozkan, 2004), and have encountered that cash holdings are positively linked to the degree of asymmetric information. definitely, information asymmetry and agency cost perform it dilemma and valuable for firms to receive reserves. hence, firms may increase up their liquid current assets to diminish the costs connected to necessity on outside financing. we use a data from energy listed firms on the ho chi minh city stock exchange and the ha noi stock exchange from 2010 to 2016. we utilize gmm to determine the inherent endogeneity difficulty. in developing market circumstances, there are some independent variables represent this market such as financial leverage, firm thu and khuong: factors effect on corporate cash holdings of the energy enterprises listed on vietnam’s stock market international journal of energy economics and policy | vol 8 • issue 5 • 201830 growth rates, firm size, profitability, cash flows from operating activities, and fixed assets. our investigation contributes the agency cost literature on corporate cash holding in the vietnamese context. this article encourages researchers to explain both the firm characteristics and the impact of this on cash holding. currently, there is nonresearch on firm characteristics and cash holding in vietnam that the ground why this investigation is significant. our sample is 28 energy listed firms which disclose financial statements reporting incorporating the period from 2010 through 2016. the rest of the paper proceeds as follows. the next section of the paper shows the literature and develops the research hypotheses; section 3 and 4 presents the methodology; section 5 presents the results of our empirical analysis and the discussion of results; finally we present the main conclusion, the limitations and few recommendations. 2. literature review 2.1. some theory support hypothesis 2.1.1. pecking order theory pecking order theory was developed by myers and majluf (1984) to explain corporate investment and financing decisions based on the unbalanced information. because executives better understand the external investors about the company’s business as well as the profitability of future projects. therefore, if the projects are promising, highly profitable, the best way to fund is to use the available resources from retained earnings. asymmetric information performs investors by thinking that they know a little about the prospects, potential, and value of the company. so they always act to protect themselves in the market in the direction of always lowering the price of new shares issued or reduced in dividends and high valuations with the shares increase the rate of paying dividends or increase the rate credits (frank and goyal, 2007). results, internal cost save more than the capital cost from the capital market because there is the asymmetry information between the company and the third party, investors. in details, to optimize costs in the company, they tend to chose internal funds as cash, high liquid asset, and then they chose external repositories in the sequence of secure borrowing, risky debt financing, and finally the equity (ferreira and vilela, 2004; ozkan and ozkan, 2004; pinkowitz et al., 2007). 2.1.2. trade-off theory following prior studies, firms want to optimize their shareholders’ benefits by counting profits and costs. firms borrow funds for investment will increase profit and bear the cost of debt or interest expenses (afza and adnan, 2007; al-najjar, 2013; manoel et al., 2018). small firms always consider it is necessary to give high debt while they cannot afford the interest they create. and the return on debt is not enough to cover the cost. therefore, according to trade off theory, businesses have high volatility, low capital, low interest, low interest, high market book tend to have less debt myers and majluf (1984). this leads to them tend to hold more cash in fact. according to boubaker et al. (2015), the increase in cash holdings will reduce some risks of bankruptcy, a risk of loss of liquidity, finance distress… however, cash holdings will cause some limitations. consider the aspect of opportunity costs, businesses holding high cash they will ignore some investment deals. but that would be profitable for them in the future (ferreira and vilela, 2004; frank and goyal, 2007; gill and shah, 2012). 2.2. hypothesis based on fundamental theories, we summarise the prior literature regarding corporate cash holdings and construct the hypotheses as follows. 2.2.1. firm size and corporate cash holdings according to pecking order theory, small companies will have lower credit limits than multinational companies. hence, small companies regularly provoke higher interest expenses than large and multinational companies. therefore, small companies need to keep more cash to guarantee liquidity (al-najjar, 2013; alnajjar and belghitar, 2011; manoel et al., 2018). moreover, the larger the company, the less information asymmetry than the small company. large companies are also less likely to undergo bankruptcy because of the breakdown of their investment in own business (al-najjar, 2013; ozkan and ozkan, 2004). therefore, large companies will adopt flexible financial policies and not necessarily take in the midpoint of many cash and cash equivalent ratios (al-najjar, 2013; guizani, 2017; hall et al., 2014; manoel et al., 2018). on the other hand, small companies are less likely to lose liquidity and lead to financial difficulties. therefore, small companies need to hold high cash to prevent this risk (al-najjar, 2013; ozkan and ozkan, 2004). at this point, the size of the company is seen as a proxy for financial difficulties. in this investigation, we develop hypothesis relating to the influence of firm size on the level of cash holdings as follows: hypothesis 1: firm size has a mixed effect on corporate cash holdings. 2.2.2. firm leverage and corporate cash holdings according the trade-off theory firms with high leverage face high financial risk. therefore, under the supervision of financial institutions, it is necessary for the corporation to have high cash holdings. that means firms have various insurance assets or high liquid asset in order to demonstrate their ability to repay, in the case of financial distress (opler et al., 1999; ozkan and ozkan, 2004). thus, there is a positive association of firm leverage to corporate cash holdings. on the other hand, companies with high cash holding ratios frequently hardly borrow from financial institutions (al-najjar, 2013; ferreira and vilela, 2004). this is consistent with the study ozkan and ozkan (2004), this research considers financial leverage as a proxy for debt issuance. the high leverage gets a high return on investment and high-interest costs, this lead to reduce their ability to hold cash. in addition, when companies have a good credit policy tend to expand their business, they will use retained earnings to reinvest this lead to reduce their cash and thu and khuong: factors effect on corporate cash holdings of the energy enterprises listed on vietnam’s stock market international journal of energy economics and policy | vol 8 • issue 5 • 2018 31 cash equivalents. thus, the company usually tends to borrow for reinvestment, which increases leverage, this is consistent with the theory of pecking order. the prior researchers show the same result a negative association of leverage to corporate cash holdings (bates et al., 2009; bigelli and sánchez-vidal, 2012; kim et al., 1998). in this investigation, we develop hypothesis relating to the influence of firm leverage on the level of cash holdings as follows: hypothesis 2: leverage has mixed effect on corporate cash holdings. 2.2.3. firm growth and corporate cash holdings firms that need strong growth and regularly demand extraordinary investment, so attending to high financial risk. that is the reason why firms tend to retain high cash in order to withdraw the lack of finance or the business dissolution of the organization. according to asymmetry information theory, firms with great growth usually have low information asymmetry. corporations are obtaining it difficult to assemble outside the capital, leading to a higher balance of cash holdings. according to the foregoing arguments, cash holdings are positively correlated to growth opportunities. previous studies have the same research results on this issue (bates et al., 2009; ferreira and vilela, 2004; kim et al., 1998; lee and song, 2007; opler et al., 1999). according to information asymmetry theory, growing companies want to have a flexible cash flow to invest. according to the pecking order theory, they want to use more the company’s internal capital to invest, to minimize costs because of decreasing asymmetric information (al-najjar and clark, 2017; han and qiu, 2007; hardin et al., 2009). in this case, growing companies want to hold high cash. according to previous studies, have the same conclusion about the negative relationship between cash holdings and corporate growth (afza and adnan, 2007; opler et al., 1999; ozkan and ozkan, 2004; pinkowitz et al., 2007; saddour, 2006). so, pecking order theory explains both sides of this relation. as a results, we construct the following hypothesis: hypothesis 3: firm growth has mixed effect on corporate cash holdings. 2.2.4. profitability and corporate cash holdings according to the pecking order theory, highly profitable companies often have high cash reserves for reinvestment, also consistent with previous research (al-najjar and clark, 2017; kim et al., 1998; manoel et al., 2018). following by (ferreira and vilela, 2004; opler et al., 1999), companies used to retained earnings to create liquidity and competitive advantage in their businesses, that the reason why they keep a high level of cash holdings to give them the advantage. thus, profitability has a positive effect on corporate cash holdings. conversely, when the retained earnings are prioritized for debt repayment by the firm, this leads to hold low cash (kim et al., 1998; lee and song, 2007). profitability has a negative effect on corporate cash holdings. therefore, we construct the following hypothesis. hypothesis 4: profitability has mixed effect on corporate cash holdings. 2.2.5. operating cash flow and corporate cash holdings the trade-off theory indicates cash flow as an alternative source of liquidity in case firms face to finance distress or bankruptcy (hardin et al., 2009). high cash flow firms frequently acquire high costs to raise capital, as they pay high information asymmetry cost. this leads to giving low cash holdings (myers and majluf, 1984). according to research by kim et al. (1998) pointed out that, based on the pecking order theory, high cash-flow companies regularly tended to use internal cash. in this case, they use cash to cover an external debt, this leads to low cash holdings. therefore, we consider the negative relation. on the other hand, to avoid bankruptcy risk or investment business losses, higher cash flow companies with tend to hold cash. the reason was given by the previous research (bigelli and sánchezvidal, 2012; han and qiu, 2007; opler et al., 1999; ozkan and ozkan, 2004). the higher cash flow firms fluctuation, the greater profits fluctuation. thus, preventing potential risks from the fluctuations, the companies want to hold more money. in this study, we establish the hypothesis of the relationship between operating cash flow and the level of cash holdings as follows: hypothesis 5: operating cash flow has mixed effect on corporate cash holdings. 2.2.6. tangible asset and corporate cash holdings according to titman and wessels (1988), when the company demanded to increase its liabilities it needed asset mortgages to ensure its loans. if the company has assets to mortgage they conduct not to hold too much cash at the unit. in addition, companies have fixed-asset can quickly transform to cash, which means high liquidity, leading to a decrease in cash holdings (drobetz and grüninger, 2007). when required, firms can trade these assets to solve the problem of solvency. this leads to the following hypothesis: hypothesis 6: tangible asset has a negatively effect on cash holdings. 3. model and variables in this section, we begin by measuring cash holdings, then estimating the regression model of determinants effects on cash holding from the explanatory factors identified in the current literature. the relation between cash holdings and determinate variables is also discussed from various theoretical perspective. this section focuses on developing the regression model that examines determinants of cash holdings in vietnam on energy firms. we use arellano and bond (1991) linear dynamic gmm thu and khuong: factors effect on corporate cash holdings of the energy enterprises listed on vietnam’s stock market international journal of energy economics and policy | vol 8 • issue 5 • 201832 to account for the omitted variable problem, country-specific heterogeneity, and endogeneity issue. the regression model can be formulated as follows: cashi,t = μcash(-1)i,t+δ1sizei,t+δ2levi,t+δ3growthi,t+δ4ro ai,t+δ5cfoi,t+δ5ppei,t+εi,t where cash as a proxy for corporate cash holdings, cash holdings determined by total cash and short-term investment divided total asset (afza and adnan, 2007; al-najjar, 2013; al-najjar and clark, 2017; ferreira and vilela, 2004; garcía-teruel et al., 2009; kim et al., 1998; lee and song, 2007; manoel et al., 2018; martínez-sola et al., 2013; ogundipe et al., 2012; opler et al., 1999; ozkan and ozkan, 2004; pinkowitz et al., 2007; saddour, 2006). cash as a proxy for corporate cash holdings, cash holdings determined by total cash and short-term investment divided total asset. size is a proxy for firm size, size is a proxy for firm size. in this study, it is calculated by the natural logarithm of the book value of total assets at year-end (al-najjar, 2013; al-najjar and clark, 2017; dittmar et al., 2003; ferreira and vilela, 2004; garcía-teruel et al., 2009; gill and shah, 2012). lev is a measure of leverage level, lev is a measure of leverage level, which is calculated by the ratio of debt to total assets at year-end (han and qiu, 2007; hardin et al., 2009; kim et al., 1998; lee and song, 2007). growth is the proxy for firm growth, growth is calculated by the ratio of revenue year-end minus revenue previous year and revenue previous year (al-najjar, 2013; drobetz and grüninger, 2007; gill and shah, 2012; han and qiu, 2007). roa is a proxy for profitability, roa is defined by profits divided total assets at year-end (pinkowitz et al., 2007; saddour, 2006). cfo is a proxy for operating cash flow, cfo is defined by cash flow divided total assets at year-end (bates et al., 2009; dittmar et al., 2003; kim et al., 1998; opler et al., 1999) ppe is a proxy for tangible asset; ppe is defined by tangible asset divided total assets at year-end (dittmar et al., 2003; drobetz and grüninger, 2007). εi,t: error term. δ1→δ5: slope coefficients representing the influence of the associated independent variable on the dependent variable 4. data this study examines the factors effect on corporate cash holdings of the energy enterprises listed on vietnam’s stock market. our data set includes 28 energy companies on vietnam stock markets (hnx and hose) in the period from 2010 to 2016, with a total of 196 firm-year observations being collected. we used gmm estimator to test our hypotheses. the results show a negative association between leverage, return on assets, operating cash flow and corporate cash holdings while a tangible asset has a positive relationship. our data set includes 28 energy companies on vietnam stock markets (hnx and hose) in the period from 2010 to 2016, with a total of 196 firm-year observations being collected. we use secondary data from financial statements, retrieved from thomson reuters eikon to measure the dependent and independent variables. descriptive statistics of variables is provided in table 1. 5. results and discussion table 2 exhibits correlation matrix among variables utilized in the paper. none of the correlations among variables, which are proxy distinctive constructs, are extremely correlated (>0.90) to appoint a problem with multicollinearity (gujarati and porter, 2003). cash holding is negatively correlated with firm leverage, firm growth and positively correlated with firm size, profitability, operating cash flow, tangible assets (table 3). the energy listed firms landscape manifests that firm leverage, profitability, operating cash flow and fixed assets are the key determinants of corporate cash holdings. firm size and firm growth are not identified as the significant impact of cash holdings in the energy listed firms in vietnam. clarify the original hypothesis with a theoretical framework, we distinguish a negative association between firm leverage and corporate cash holdings: energy listed firms that are capable to collect the debt are scarce possible to handle cash as they are able to borrow funds externally. therefore, firm leverage can be inspected as a proxy for holding cash (al-najjar, 2013; ferreira and vilela, 2004; manoel et al., 2018; ozkan and ozkan, 2004). uniformly firms with the capacity to reach outside repositories are less in demand of cash to settle for investments. the regression result point that there is a negative association between profitability and cash holdings. this conclusion consistent table 1: descriptive of variables variable observations mean±sd minimum maximum cash 196 0.7104±7.1910 0.0006 100.8504 size 196 27.9256±1.7150 24.8171 31.6697 lev 196 0.5360±0.1858 0.0320 0.9345 growth 196 0.1362±0.4203 −0.6289 4.2341 roa 196 0.0628±0.0506 −0.1349 0.2670 cfo 196 0.0833±0.1041 −0.1779 0.4055 ppe 196 0.3080±0.2330 0.0070 0.9661 the table reports summary statistics of variables over the period from 2010 to 2016 for vietnamese listed firms. cash is the cash holding indicator, calculated as total cash and short-term investment divided total asset. size is firm size, that is, natural log of assets. lev is firm leverage, measured as ratio of total debt over total assets. growth is sale growth rate. roa is the ratio of net income after taxes to total assets. cfo is net operating cash flow and total assets. ppe is the ratio of net plant, property and equipment to total assets. sd: standard deviation thu and khuong: factors effect on corporate cash holdings of the energy enterprises listed on vietnam’s stock market international journal of energy economics and policy | vol 8 • issue 5 • 2018 33 with hypothesis 4 and contrary the predicted positive sign from pecking order theory (myers and majluf, 1984). this force designate that smaller profitable firms that are ready to spend interests “to retain the privilege of spending dividends” are not able to receive additional funds from external institutions such as financial institutions and consequently retain cash for any emergencies to advance their financial positions. furthermore, the correlation between cash holdings and operating cash flow is negative and significant at the 5% level. this association reveals that firms which produce higher cash flows maintain smaller cash holdings. this is consistent with the expectational hypothesis (hardin et al., 2009; kim et al., 1998). when a business generates cash flow from normal business operations, there will be a tendency to increase its investment because many cash holdings will not create profit and increase shareholder benefits. the coefficients on the proxy variable for the fixed asset (ppe) is estimated to be significantly negative (hypothesis 6). this result is contrary to an expectational hypothesis (drobetz and grüninger, 2007). this can be explained by the fact that fixedasset investment is regularly of high value, leading to a depression in cash holdings. in addition, in the energy sector, the value of fixed capital investments is considerably large. this is consistent with the context of the sample data and a new contribution to this investigation. on the other hand, we did not find a significant correlation between cash holdings and firm growth, which is consistent with the results of (garcía-teruel et al., 2009; guney et al., 2007). firm size is positive and does not have statistical significance to hold cash. according to ozkan and ozkan (2004), other factors may have influenced the relationship between firm size and cash holding. 6. conclusion corporate cash holdings are an important issue in accounting and finance and have interested enormous deliberation amongst academics (al-najjar, 2013; al-najjar and clark, 2017; manoel et al., 2018; martínez-sola et al., 2013; pinkowitz et al., 2007). nevertheless, the continuing controversy has not adequately harangued the cash holdings management in emerging economies. accordingly, the purpose of this investigation is to contribute new empirical confirmation on the impact of firm characteristics on corporate cash holdings in vietnam context. using the data obtained from a sample of 28 energy listed firms in vietnam stock market held from the year 2010 to 2016. data collected from the thomson reuter database. gmm regression models were employed to interpret the data. this accommodates succeeded endogenous changes and assure the sustainability of the model compared to previous studies. results achieved in this investigation are constant with empirical evidence on corporate cash holding literature. our conclusions confirm that tangible assets positively impact cash holdings, whereas firm leverage, profitability and operating cash flow a negative impact, whereas firm size, growth opportunities were all determined to become an insignificant influence on the cash holdings of energy lister firms. our research ought to possible implications to shareholders in the energy firms. high level of corporate cash holdings is regularly correlated with latent agency struggle. the free cash flow theory explicitly claims that managers frequently inspect cash holdings as free cash flows and oftentimes abuse them for individual advantages. an immeasurable knowledge of the direction between firm characteristics and cash holdings, shareholders relinquish acquainted decisions concerning the cash balances of the corporations of their prospect. consequently, based on the conclusions of our research, an investor should rationally presume that a firm with high quick asset replacements, high debt, and equity expense should maintain lower cash holdings. if for the unusual object, a firm with high quick asset delegates, high debt, and equity expense has high cash holdings, this force is a flag of a potential agency conflict. furthermore, managers of energy companies should not settle too much cash on their hands because it will lead to table 2: pearson correlation coefficient matrix cash size lev growth roa cfo ppe cash 1 size 0.1608 1 lev −0.0908 0.2282 1 growth −0.0397 0.0542 0.2023 1 roa 0.0952 0.0245 −0.5878 0.0074 1 cfo 0.0055 0.0341 −0.3439 −0.0544 0.4766 1 ppe 0.0176 0.2292 −0.1545 0.1395 0.0735 0.2408 1 the table reports correlation matrix over the period from 2010 to 2016 for vietnamese listed firms. cash is the cash holding indicator, calculated as total cash and short-term investment divided total asset. size is firm size, that is, natural log of assets. lev is firm leverage, measured as ratio of total debt over total assets. growth is sale growth rate. roa is the ratio of net income after taxes to total assets. cfo is net operating cash flow and total assets. ppe is the ratio of net plant, property and equipment to total assets table 3: dynamic gmmregression results variables coefficient standard error t p-value [95% conf. interval] lag of dep. var 9.0846 19.7979 0.46 0.647 −30.075 48.244 size 14.0104 13.0679 1.07 0.286 −11.837 39.858 lev −61.7064** 28.4445 −2.17 0.032 −117.968 −5.444 growth 4.9081 6.1071 0.8 0.423 −7.172 16.988 roa −171.4599*** 65.9376 −2.6 0.01 −301.882 −41.038 cfo −40.0326** 17.4347 −2.3 0.023 −74.518 −5.547 ppe 54.9935* 32.0312 1.72 0.088 −8.363 118.350 the table reports parameter estimates of the model: cashi, t = μcash(‑1) i, t+δ1sizei, t+δ2levi, t+δ3growthi, t+δ4roai, t+δ5cfoi, t+δ5ppei, t+εi, t. where: cash is the cash holding indicator, calculated as total cash and short-term investment divided total asset. size is firm size, that is, natural log of assets. lev is firm leverage, measured as ratio of total debt over total assets. growth is sale growth rate. roa is the ratio of net income after taxes to total assets. cfo is net operating cash flow and total assets. ppe is the ratio of net plant, property and equipment to total assets. *, **, ***denotes the level of significance of 10%; 5% and 1% respectively thu and khuong: factors effect on corporate cash holdings of the energy enterprises listed on vietnam’s stock market international journal of energy economics and policy | vol 8 • issue 5 • 201834 a deterioration in the market for capital. the research is focused only on energy companies on the vietnamese stock market. consequently, the conclusions of this study cannot be generalized to the whole market. future studies can be researched for entire companies listed on the vietnamese stock market or for specific sectors such as banking and insurance. references afza, t., adnan, s. (2007), determinants of corporate cash holdings: a case study of pakistan. paper presented at the proceedings of singapore economic review conference (serc). al-najjar, b. (2013), the financial determinants of corporate cash holdings: evidence from some emerging markets. international business review, 22(1), 77-88. al-najjar, b., belghitar, y. (2011), corporate cash holdings and dividend payments: evidence from simultaneous analysis. managerial and decision economics, 32(4), 231-241. al-najjar, b., clark, e. (2017), corporate governance and cash holdings in mena: evidence from internal and external governance practices. research in international business and finance, 39, 1-12. arellano, m., bond, s. (1991), some tests of specification for panel data: monte carlo evidence and an application to employment equations. the review of economic studies, 58(2), 277-297. bates, t.w., kahle, k.m., stulz, r.m. (2009), why do us firms hold so much more cash than they used to? the journal of finance, 64(5), 1985-2021. bigelli, m., sánchez-vidal, j. (2012). cash holdings in private firms. journal of banking and finance, 36(1), 26-35. boubaker, s., derouiche, i., nguyen, d.k. (2015), does the board of directors affect cash holdings? a study of french listed firms. journal of management and governance, 19(2), 341-370. dittmar, a., mahrt-smith, j., servaes, h. (2003), international corporate governance and corporate cash holdings. journal of financial and quantitative analysis, 38(1), 111-133. drobetz, w., grüninger, m.c. (2007), corporate cash holdings: evidence from switzerland. financial markets and portfolio management, 21(3), 293-324. ferreira, m.a., vilela, a.s. (2004), why do firms hold cash? evidence from emu countries. european financial management, 10(2), 295-319. frank, m.z., goyal, v.k. (2007), trade-off and pecking order theories of debt. handbook of empirical corporate finance, 2, 135-202. garcía-teruel, p.j., martínez-solano, p., sánchez-ballesta, j.p. (2009), accruals quality and corporate cash holdings. accounting and finance, 49(1), 95-115. gill, a., shah, c. (2012), determinants of corporate cash holdings: evidence from canada. international journal of economics and finance, 4(1), 70. guizani, m. (2017), the financial determinants of corporate cash holdings in an oil rich country: evidence from kingdom of saudi arabia. borsa istanbul review, 17(3), 133-143. gujarati, d., porter, d. (2003), multicollinearity: what happens if the regressors are correlated. basic econometrics, 72(3), 363-381. guney, y., ozkan, a., ozkan, n. (2007), international evidence on the non-linear impact of leverage on corporate cash holdings. journal of multinational financial management, 17(1), 45-60. hall, t., mateus, c., mateus, i.b. (2014), what determines cash holdings at privately held and publicly traded firms? evidence from 20 emerging markets. international review of financial analysis, 33, 104-116. han, s., qiu, j. (2007), corporate precautionary cash holdings. journal of corporate finance, 13(1), 43-57. hardin, w.g., highfield, m.j., hill, m.d., kelly, g.w. (2009), the determinants of reit cash holdings. the journal of real estate finance and economics, 39(1), 39-57. jensen, m.c. (1986), agency costs of free cash flow, corporate finance, and takeovers. the american economic review, 76(2), 323-329. jensen, m.c., meckling, w.h. (1976), theory of the firm: managerial behavior, agency costs and ownership structure. journal of financial economics, 3(4), 305-360. kim, c.s., mauer, d.c., sherman, a.e. (1998), the determinants of corporate liquidity: theory and evidence. journal of financial and quantitative analysis, 33(3), 335-359. lee, y., song, k. (2007), why have east asian firms increased cash holdings so much after the asian financial crisis? paper presented at the th australian finance and banking conference. manoel, a.a.s., da costa m.m.b., santos, d.f.l., neves, m.f. (2018), determinants of corporate cash holdings in times of crisis: insights from brazilian sugarcane industry private firms. international food and agribusiness management review, 21(2), 201-218. martínez-sola, c., garcía-teruel, p.j., martínez-solano, p. (2013). corporate cash holding and firm value. applied economics, 45(2), 161-170. myers, s.c., majluf, n.s. (1984). corporate financing and investment decisions when firms have information that investors do not have. journal of financial economics, 13(2), 187-221. ogundipe, l.o., ogundipe, s.e., ajao, s.k. (2012). cash holding and firm characteristics: evidence from nigerian emerging market. journal of business economics and finance, 1(2), 45-58. opler, t., pinkowitz, l., stulz, r., williamson, r. (1999), the determinants and implications of corporate cash holdings. journal of financial economics, 52(1), 3-46. ozkan, a., ozkan, n. (2004), corporate cash holdings: an empirical investigation of uk companies. journal of banking and finance, 28(9), 2103-2134. pinkowitz, l., williamson, r., stulz, r.m. (2007), cash holdings, dividend policy, and corporate governance: a cross country analysis. journal of applied corporate finance, 19(1), 81-87. saddour, k. (2006), the determinants and the value of cash holdings: evidence from french firms. paris: université paris dauphine. titman, s., wessels, r. (1988), the determinants of capital structure choice. the journal of finance, 43(1), 1-19. tx_1~at/tx_2~at international journal of energy economics and policy | vol 9 • issue 5 • 2019474 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(5), 474-480. an empirical study on short term and long-term consequences of crude oil on economic wellbeing of indonesia by applying autoregressive distributed lag model djoko roespinoedji1, roeshartono roespinoedji1, mohammed r. a. siam2, mohd farid shamsudin3* 1department of  business, widyatama university, indonesia, 2department of  business, school of management (sbm), college of business (cob), universiti utara malaysia, kedah 06010 malaysia, 3department of  marketing , universiti kuala lumpur business school, universiti kuala lumpur, malaysia. *email: mfarid@unikl.edu.my received: 21 april 2019 accepted: 03 july 2019 doi: https://doi.org/10.32479/ijeep.8311 abstract oil has been one of the primary wellsprings of indonesia’s revenue, either from government spending plan or balance of payments purpose of perspectives. because of supply and demand of oil on the planet market, prices of oil, either icp, brent uk, or wti, had been decay of late. oil prices and economic wellbeing are essential markers to see the achievement of indonesia’s improvement execution. the utilization of oil as the world’s fundamental energy source when all is said in done and indonesia specifically is driven by industrialization. the more ventures, the more prominent the energy resources required. in a similar setting, economic wellbeing will likewise expand oil demand. oil has a strategic nature and is a vital ware that influences the world economy. both oil exporters and merchants are probably going to feel the impacts of oil price advancements. oil prices dropped pointedly since june 2014 finishing a 4 year time of relative price strength. the size and speed of decay has been noteworthy yet not remarkable. this exploration plans to analyze the impact of crude oil prices on economic wellbeing in indonesia. data on crude oil prices and economic growth are yearly time series data stretching from 1987 to 2016. the aftereffects of co-integration tests demonstrate that there is no long-term connection between crude oil prices and economic wellbeing. in any case, the estimation of the autoregressive distributed lag (5.0) model demonstrates that in the short term, there is the impact of crude oil prices toward economic wellbeing. keywords: crude oil, oil price, growth, autoregressive distributed lag model, indonesia jel classifications: e31, a10 1. introduction oil is one of the nation’s fundamental wellsprings of wage, both as assessment revenues, just as oil revenue sharing, and different revenues acquired by the legislature. in spite of the fact that state revenues from oil keep on declining after some time, reliance on oil revenues is still vast. diminishing in revenues from oil is because of changes in oil prices and economic emergencies, which have positive and negative effect on economic wellbeing. the long-term sway on economic wellbeing from oil prices, trade rates, and emergencies contains some data that is helpful in foreseeing the future economy (yusuf, 2015). the debilitating of crude oil prices was predominantly because of the declining demand of crude oil in asian nations because of the progressing economic emergency. the development of global crude oil prices activated by the emergency in oil-delivering areas, the state of local oil prices extraordinarily influences indonesia’s economic growth, since oil prices are to a great extent determined by demand and supply. so also, economic wellbeing affects oil prices (taguchi and li, 2018). crude oil prices can influence economic wellbeing and growth through changes in prices of generation. the expansion in crude this journal is licensed under a creative commons attribution 4.0 international license roespinoedji, et al.: an empirical study on short term and long-term consequences of crude oil on economic wellbeing of indonesia by applying ardl model international journal of energy economics and policy | vol 9 • issue 5 • 2019 475 oil prices can cause inflation. the government of a nation will lead monetary approach by raising loan fees to decrease inflation. an expansion in loan fees would then be able to lessen the estimation of venture which at last influences gross domestic product (gdp) or economic wellbeing and growth. oil has been one of the principle wellsprings of indonesia’s revenue, either from the government spending revenue perspective in terms of tax or non-tax revenue or from the balance of payments perspective in terms of export revenue (tambun et al., 2018). it is likewise the fundamental source to back the government subsidy on the domestic utilization of gas. oil isn’t just economic commodity yet in addition political commodity; vacillations of its price couldn’t just be clarified by supply and demand factors. for example, the economist put its feature as “sheikhs versus shale,” an extraordinary drop oil price marvel toward the finish of 2014 and mid 2015 (“sheikhs v shale,” 2014). the opec kept the oil production in normal volume even the world was overflowed by oil from shale oil innovation. by keeping the volume, they planned to pull down the oil price accordingly it will stop shale oil production because of its costly production cost. notwithstanding the opec intends to keep the price stable, the opec acted opposite on expanding oil supply because of the shale oil. this activity effectively dropped something like 150 billion of greater expense oil investment in 2015 and more slices to come 1 year from now which could affect oil supply later on (“abnormally normal,” 2015). the decrease in oil prices will result in two things. initially, the decrease in oil lifting focuses by oil companies, both foreign companies and national companies. oil companies will be hesitant to deliver, on the grounds that prices are not or less gainful. second, the decrease in oil prices will directly affect declining government revenues (daeng, 2016). the improvement of indonesia’s oil export esteem additionally changed, which will in general lead to an expansion in the estimation of its exports. the most elevated increment happened in 1998 with an advancement level of 160.31%, while the greatest diminishing was in 1999 with an estimation of 33.04%. the decrease in oil exports is an after effect of the government’s absence of attention in the oil division, however the expansion in prices has made the estimation of oil exports increment (mustika, 2015). from price perspectives, the price of oil has varied for quite a few years. in 1973, because of the arab oil ban, the oil price shoots up. in 1986, be that as it may, the oil price started to descend and after that tumbled down rapidly because of the abundance of supply, among others. from the 1990s forward, the oil price has been balanced out. in 2008, the oil price went down because of the lehman brothers emergencies, where the decrease keeps proceeded until after 2014 (tampubolon and setyoko, 2019). because of the movement of supply and demand of oil on the planet market, the oil price has been gone down so much that practically all business analysts said that the economy of developing nations would be stagnated without knowing when the price will recover. the awry impact of rising oil prices and the decrease in the total economy gives the subject for scientists about the component of the business cycle. asymmetry of oil price fluctuations against gdp causes straightforward instrument impacts that were at first wanted to be developed, for example, contractions and extension in the accessibility of resources, there is a move in profitable limit or the impact of inflation moving total demand. instability and unclear connection between oil prices and gdp, the particular of changes in oil prices should be analyzed, as determinations for changes in gdp, changes in oil prices and other economic factors (jones et al., 2004). mehrara and oskoui (2007) have dissected the sources of economic fluctuations for usa and oil exporting nations, for example, iran, saudi arabia, kuwait, and indonesia. by utilizing a structural var technique, creators recognized four structural shocks: supply, oil price, genuine demand, and ostensible demand shocks. they demonstrate that oil price shocks speak to the primary source of yield fluctuations in saudi arabia and iran, however not in kuwait and indonesia. different examinations have dissected the connection among energy and economic growth. in any case, this relationship is seen through energy consumption as opposed to oil price movements. from the economic writing, there are a few mechanisms clarifying how the oil price blocks the economy. in the supply side shock, the job of oil price is as an info factor to the production. the declining in oil supply will hamper the profitability and swings to reduce genuine compensation wellbeing and growth. on the off chance that wages sticky descending, the economy will decrease and prompt rise unemployment and create further decrease in the economy. in demand side, rising in oil price will shift purchasing power from oil-importing-nations to oil-exporting-nations. this wonder will support the consumer demand in oil exporting nations and the other way around in oil importing-nations. in any case, as a net, the impact is declining in consumer demand and it prompts expanding in world saving. additional saving will in general make loan fee lower and push investment higher and lead to unaltered gdp. be that as it may, the effect of fall in consumption will prompt declining of gdp (brown and yücel, 2002). besides, the oil price impact isn’t just by expanding and diminishing impact, yet in addition unpredictability impact, especially in oil importing nation. the vulnerability in oil price as fundamental production factor makes investors will in general postpone their new investment until the price increasingly steady (bernanke, 1983). what’s more, companies will in general hold selecting new employees until the condition moderately steady (hamilton, 1988). from copious looks into, it is generally acknowledged that the oil price has negative effect to macroeconomic indicators. in any case, since the government’s endeavor to alleviate the destructive effects by its fiscal and monetary arrangement, determining the exact effect become increasingly troublesome. what’s more, some observational investigations contended that giving fuel subsidy was successful to alleviate the negative effects. reference (jbir and zouari-ghorbel, 2009a) discovered that the hurtful effect of roespinoedji, et al.: an empirical study on short term and long-term consequences of crude oil on economic wellbeing of indonesia by applying ardl model international journal of energy economics and policy | vol 9 • issue 5 • 2019476 oil price in tunisian economy was transmitted to fuel subsidy (which was intermediary by budget deficit). moreover, fuel subsidy in thailand likewise discovered diminishing the antagonistic impact of oil price instability to the economy (rafiq et al., 2009). in any case, unique end found by (plante, 2014) that for both oilexporting-nations and oil-importing-nations; rather than relieving the antagonistic effect, the fuel subsidy could hamper the total welfare over the long haul. along these lines, the job of fuel subsidy in easing the harmful effect of oil price still questionable. elements that impact oil prices in a general sense follow commodity price movements determined by demand and supply. the variables that impact both of these will influence world oil prices, both in short and long term (tiwari et al., 2013). despite the fact that these variables can’t be estimated effectively, in light of the fact that the market is worldwide and there are numerous uncertainties, appraisals can be made by watching the most recent improvements. 2. review of literature and hypothesis development in view of the observational explores, oil price can be estimated utilizing various approaches. notwithstanding the way that different approaches had been created, there is no precise method to quantify the oil prices. diverse analysts utilized distinctive approaches. for example, iwayemi and fowowe (2011), farzanegan and markwardt (2009) and cunado and de gracia (2005) connected all estimation techniques as expressed above so as to get a progressively extensive outcome. notwithstanding, a few analysts (al-mulali and sab, 2012; al-mulali and sab, 2011) still stick with the rudimentary approach, while the others (omojolaibi and egwaikhide, 2014; singh and issac, 2018) just estimated the oil price by utilizing the garch model. concentrate on impact of crude oil prices toward economic growth has been completed by numerous specialists. chai et al. (2015) examined the impact of oil prices toward economic growth in nations: china, us and japan. they utilized the asymmetric co-joining model to break down quarterly information extending from 1992 to 2013. test outcomes demonstrated that oil prices just influenced economic growth in china and japan. yussof and latif (2013) inspected the impact of oil prices on economic growth in malaysia utilizing information that stretched out from 1966 to 2006. the autoregressive distributed lag (ardl) model was utilized to test these impacts. the test outcomes demonstrated that oil prices influenced the economic growth in the short term. since the finish of fuel subsidy job still questionable, this study endeavored to address this issue. so as to do as such, this examination picked indonesia to be the case study. indonesia fills in as legitimate case because of certain reasons. to begin with, it speaks to a nation which gave very tremendous measure of subsidy (mourougane, 2010). second, indonesia had transformed it fuel subsidy approach after asian emergency, so it is conceivable to test the distinctive policies in a single nation. at long last, indonesia was a one of a kind cases which change its status from a net-oil-exporting-nation to a net oil-importing-nation (bp british petroleum, 2013; o-iea, 2015). oil prices are affected by economic elements from the supply side, for example, production and imports, just as from the demand side, for example, consumption and exports. similarly, as with the effect of the downgraded dollar, monetary forms and oil prices are exchanged universally, which affect more expensive rates so makers endeavor to keep up the economic estimation of the oil sold (wonyra, 2018). oil production patterns are against gdp as government revenues from the oil and gas sector to economic growth. oil production changed somewhere in the range of 1970 and 1971 from 41.2% to 19.1% in 1972 and 21.4% in 1979. a negative growth rate of 30.9% happened in 1981 (ibrahim, 2008). there are now a few explores about the effect of oil price to indonesia’s economy. reference (abeysinghe, 2001) examined the effect of oil price to a few asian nations including indonesia. for oil exporting nations, for example, malaysia and indonesia, the principal sway was sure to the economy however secondary effect from exchanging with partner nations was negative and outnumber past effect. along these lines, the net effect was negative. the second literature by (mehrara and oskoui, 2007) analyzed the effect of oil price to four prominent oil-exporting-nations; saudi arabiya, iran, indonesia and qatar. the effects were diverse among the nations; for the nations which have contributed their pay to oil saving foundation (qatar) and forced prudent monetary and fiscal approach (indonesia), the fluctuation in oil price did not have any huge impact on their gdp. the outcome was complexity to the next two nations. hypothesis1: the variables related with crude oil are stationary hypothesis0: the variable related with crude oil are stationary against. 3. research methodology 3.1. research methodology or procedure oil prices are assumed to be exogenous variables that can affect economic wellbeing and growth in indonesia. therefore, the model used to examine the effect is a model of ardl developed by pesaran and shin (1999) and pesaran et al. (2001). the ardl model with independent variables is oil and the dependent variable is gro, as follows: 1 1 1 1 1 11 1 1     = =− − + += ++ ∑ ∑p qi t t ti it tgro c t gro oil (1) the notations of c1, δ1, α1i (i=1,2…p), (j=0, 1…, q) are the parameters of the regression condition, and p and q are the period of time lag. ε1t is repetitive sound residual which has autonomous distribution, homoscedastic, and regularly distributed. the ardl model (1) is typically composed ardl (p, q) where the free factor oil and gro subordinate variable are thought to be stationary at the dimension. the term of stationary is frequently called as incorporated of request d, i(d), d ≥0. on the off chance that the factors of oil prices and economic wellbeing and growth is coordinated of request 1, i (1) or one of roespinoedji, et al.: an empirical study on short term and long-term consequences of crude oil on economic wellbeing of indonesia by applying ardl model international journal of energy economics and policy | vol 9 • issue 5 • 2019 477 these factors are i (1) or i (0), and furthermore co-incorporated, at that point the impact of oil prices on economic growth must be tried with error correction models, as follows: 1 t 2 2 1 t i1 2 1 2 20 d (gro ) = ( ) + ( ) + p t t i i q j t j tj c t ec d gro d oil      − − −= − −= + + +∑ ∑ (2) in which c2, δ2, α2i (i=1,2…p−1), β2j (j=0, 1…, q−1) are the parameters of the regression condition while. ε2t is white noise. ect−1 1 is an error correction variable, and d(gro) is the primary distinction type of the gro variable where d(gro)=d(grot)=grot-grot−1=gro–gro (−1). in light of the necessities of the ardl (p, q) model, there are a few testing steps that must be produced to inspect the results of crude oil prices on economic wellbeing and growth. the initial step is to test the order of factors integration. the integration request test utilized is the augmented dickey-fuller (adf) test, and the phillips-perron (pp) test. the adf test was created by dickey and fuller (1979), and the pp test was created by phillips and perron (1988). the adf test utilizes a t-ratio statistic, and the pp test utilizes pp-statistics. the plan of the adf test hypothesis and the pp test are h0: the variable related with crude oil are stationary against. h1: the variable related with crude oil are stationary. the second step is to test the co-integration between crude oil prices and economic wellbeing and growth. this progression is done if the price of crude oil or economic growth are coordinated at a similar order i (0) or i (1) or the two factors are not quite the same as the order of integration. the co-integration test utilized is the ardl bound co-integration test, with the condition: ( ) 1 1t 3 1 1 3 31 0 1 2 1 3 ( ) + ( )g + d ro c p q i t j ti j t t jt d gro d oil gro oil       − − − − − = − = += + + + ∑ ∑ (3) in which c3, δ3, α3i (i=1,2…p−1), β3j (j=0, 1…, q−1) are the parameters of the regression condition ϕk (k=1,2) are the parameters of the regression condition, and ε3t is repetitive sound. ardl bound co-integration test with co-integration condition in (3) necessitates that nobody of the factors is process i (2), and does not require an integration order test. be that as it may, in this examination, the integration order test stays set up in the initial step to guarantee that one of the crude oil prices or economic wellbeing and growth does not belong to process i (2). next, the ardl bound co-integration test utilizes f-statistics or wald-statistics. the theory formula is h0: ϕ1=ϕ2=0 (there is no co-integration) in opposite to h1: ϕ1≠ϕ2≠0 (there is co-integration). the test criteria are h1 acknowledged whether the estimation of statistic test is higher than the critics estimation of upper bound i (1), and h0 is acknowledged whether the statistic esteem test is lower than the critics value of lower bound i (0). the third step is to appraise the ardl model. the estimation venture of the ardl model starts with the determination of the length of the time lag p and q dependent on the data criteria. independency checking (autocorrelation), homoscedastic, and normality of residuals are additionally done. autonomous test utilizes lagrange multiplier (lm) test, homoscedastic test utilizes arch test, and normality test utilizes jarque berra test. 3.2. time period this study utilizes yearly time series data in the period 1987 to 2016. time series data comprises of dubai crude oil prices, and gross domestic local item per capita (gdrp) in south east sulawesi province, indonesia. gdrp is an intermediary of economic wellbeing. the price unit of crude oil is usd/barrel, while the gdrp unit is idr. 3.3. sources of data dubai’s oil price data source is the united states bank st. louis. the gdrp data source is the south east sulawesi statistical center. besides, dubai crude oil prices are expressed with oil, while economic growth is expressed with gro. oil and gro are normal logarithms. 4. results and discussion at initial a data unit root test or integration order test i(d) was first performed. the estimations of the adf test statistics and the pp test are condensed in table 1. the stationary test results from the two tests demonstrate that the price of crude (oil) is stationary at the main distinction, or coordinated of order 1, i (1). meanwhile, economic growth (gro) is stationary at the dimension. in this way, the time series of crude oil prices is i (1) process, while the time series of economic growth is i (0) process. the second step is to test the co-integration between the price of crude oil and economic growth utilizing the ardl bound cointegration test. the statistical values of the co-integration test are given in table 2. by looking at test statistic values (2.307) and the values of lower critics bound i (0) and upper bound i (1), it is inferred that the price of crude oil and growth economy isn’t coincorporated. that is, the price of crude oil and economic growth don’t have a long-term relationship in the period 1987-2016. since the price of crude oil and economic growth are not cointegrated, the third step is to appraise the ardl model in the main contrast. this progression starts with determining the time figure 1: crude oil from marginal wells in indonesia roespinoedji, et al.: an empirical study on short term and long-term consequences of crude oil on economic wellbeing of indonesia by applying ardl model international journal of energy economics and policy | vol 9 • issue 5 • 2019478 lag. in view of the aic data criteria, it was discovered that the time lag for oil price is 0, and the time lag for economic growth is 5. in this way, the evaluated ardl model is the ardl (5.0) model in the primary distinction. the estimation consequences of the ardl (5.0) model are given in table 3. all factors engaged with the ardl (5.0) model including the steady and patterns are 1% noteworthy. along these lines, in the short term, there is the impact of crude oil prices on economic growth. this end is substantial, on the grounds that the classical assumption necessities of the ardl (5.0) model as normality, independence (autocorrelation), and homoscedastic are satisfied. the finding in this study is that there is a short-term impact of crude oil prices on economic wellbeing and growth. the finding of this study isn’t in accordance with the discoveries of berument et al. (2010). the contrast between the aftereffects of this study and the discoveries him can be brought about by contrasts in cultural, socio-political and economic conditions he directed research in venezuela, while this study is completed in south east sulawesi, indonesia. since the economic wellbeing and growth of indonesia is influenced by the price of crude oil, the indonesia government needs to use the energy sources of crude oil claimed as effectively as could reasonably be expected. hence, the obtainment and usage of oil can’t make inflation as a boundary economic wellbeing and growth (hussain et al., 2019). the stationary test outcomes demonstrate that the price of crude oil is i (1) process, while net local domestic item per capita is i (0) process (johari et al., 2018). the co-integration test results demonstrate that in the period 1987 to 2016, crude oil prices and economic wellbeing and growth were not co-incorporated (sinaga et al., 2019). that is, over the long haul, there is no connection between crude oil prices and economic wellbeing and growth. table 1: unit root test variable adf test statistics pp test statistics constant without trends constant and trends constant without trends constant and trends oil −1.2583 −2.3374 −1.2705 −1.4653 d (oil) −4.9117* −4.8611* −4.9226* −4.8720* gro −0.1602 −6.3398* −3.5231** −1.5911 d (gro) −5.8992* −3.1151 −5.5289* −10.6470* *,** are significant at 1%, 5%, adf: augmented dickey-fuller, pp: phillips-perron table 2: ardl bounds test number of sample (t) number of explanatory variable (k) f-statistics critical value (%) i (0) i (1) 1 5 10 1 5 10 30 1 2.3017 10.615 7.36 6.01 11.65 8.265 6.78 critical values are extracted from table in appendix of narayan (2005). ardl: autoregressive distributed lag table 3: ardl (5.0) model’s evaluation constant and variable independent coefficient t-statistics p c 1.0812 6.7800 0.0000 @trend −0.0359 −5.2768 0.0001 d (gro (−1)) −0.0957 −3.7817 0.0015 d (gro (−2)) −0.1078 −4.3392 0.0004 d (gro (−3)) −0.1348 −5.7041 0.0000 d (gro (−4)) −0.0926 −3.9554 0.0010 d (gro (−5)) −0.0685 −2.9793 0.0084 d (oil) −0.5235 −4.1541 0.0007 figure 2: indonesia’s crude oil: exports from 1995 to 2016 roespinoedji, et al.: an empirical study on short term and long-term consequences of crude oil on economic wellbeing of indonesia by applying ardl model international journal of energy economics and policy | vol 9 • issue 5 • 2019 479 besides, in view of the estimation aftereffects of the ardl (5.0) model it was discovered that, in the short term, there was an impact of crude oil prices on economic wellbeing and growth. 5. conclusion earlier observational investigations have reported the hurtful impacts from oil price to macroeconomic factors in numerous nations, from little to huge economies, from oil-exporting-nations to net-oil-importing-nations and from created to developing nations. be that as it may, the job of fuel subsidy to pad the impacts still unclear. the motivation behind this study is to inspect the impact of crude oil prices on economic wellbeing and growth in indonesia. the data utilized are yearly time series data comprising of: world crude oil prices and gross domestic regional product per capita that extend from 1987 to 2016. net domestic regional product per capita is an intermediary of economic wellbeing and growth. thusly, the effect of the adjustments in oil prices on the indonesian economy can diminish by bringing down the reliance on oil as a critical source of revenue, regardless of the decrease of the commitment of oil to the pay throughout the years. indonesia has been changing itself from a net oil exporter to a net oil importer since 2005; consequently, the oil revenue estimated as the level of the aggregate gdp has diminished by about half from 1990 to 2005 and represent under 1% in 2015. it is suggested that the indonesian government be engaged with the administration of oil and oil reserves are progressively diminishing, while oil use is expanding. identified with economic wellbeing and growth so as to remain and dependably be improved later on, for further analysts to think about microeconomic factors. the indonesian government needs to make obtainment effectiveness policies and utilization of crude oil to lessen inflation. by stifling inflation, economic wellbeing and growth is relied upon to increment. research needs to additionally examine the effect of oil price changes on gdp and inflation. occasions that happened in indonesia, for example, its change from a net oil exporter to a net oil importer and the deregulation of fuel subsidy arrangement should all the more unequivocally consolidate into the examination. at the point, the further research consolidating such occasions would improve our comprehension of the impact of changes in oil price and help educate approach better. references abeysinghe, t. (2001), estimation of direct and indirect impact of oil price on growth. economics letters, 73, 147-153. al-mulali, u., sab, c.n.b. (2012), oil prices and the real exchange rate in oil-exporting countries. opec energy review, 36(4), 375-382. al-mulali, u., sab, c.n.b.c. (2011), the impact of oil prices on the real exchange rate of the dirham: a case study of the united arab emirates (uae). opec energy review, 35(4), 384-399. bernanke, b.s. (1983), irreversibility, uncertainty, and cyclical investment. quarterly journal of economics, 97, 85-106. berument, m.k., ceylan, n.b., dogan, n. (2010), the impact of oil price shocks on the economic growth of selected mena1 countries. the energy journal, 31(1), 149-176. bp-british petroleum. (2013), statistical review of world energy. london. available from: http://www.bp.com/content/dam/bp/ excel/statistical-eview/statistical_review_of_world_energy_2013_ workbook.xlsx. brown, s.p.a., yücel, m.k. (2002), energy prices and aggregate economic activity: an interpretative survey. quarterly review of economics and finance, 42, 193-208. chai, j., yang, y., xing, l. (2015), oil price and economic growth: an improved asymmetric co-integration approach. international journal of global energy issues, 38(4/5/6), 278-285. cunado, j., de gracia, f.p. (2005), oil prices, economic activity and inflation: evidence for some asian countries. the quarterly review of economics and finance, 45(1), 65-83. daeng, s. (2016), as this is the impact of serious decline in world oil prices. available from: http://www.bisnis.liputan6.com/ read/2431727. dickey, d.a., fuller, w.a. (1979), distribution of the estimators for autoregressive time series with a unit root. journal of the american statistical association, 74, 427-443. farzanegan, m.r., markwardt, g. (2009), the effects of oil price shocks on the iranian economy. energy economics, 31(1), 134-151. hamilton, j.d. (1988), a neoclassical model of unemployment and the business cycle. journal of political economy, 96(3), 593. hussain, h.i., salem, m.a., rashid, a.z.a., kamarudin, f. (2019), environmental impact of sectoral energy consumption on economic growth in malaysia: evidence from ardl bound testing approach. ekoloji, 28(107), 199-210. ibrahim, m.j. (2008), growth prospects of oil and gas abundant economies: the nigerian experience (1970-2000). journal of economic studies, 35(2), 170-190. iwayemi, a., fowowe, b. (2011), impact of oil price shocks on selected macroeconomic variables in nigeria. energy policy, 39(2), 603-612. jbir, r., zouari-ghorbel, s. (2009a), recent oil price shock and tunisian economy. energy policy, 37, 1041-1051. johari, m., jalil, m., shariff, m.m. (2018), comparison of horizontal axis wind turbine (hawt) and vertical axis wind turbine (vawt). international journal of engineering and technology, 7(4.13), 74-80. jones, d.w., leiby, p.n., paik, i.k. (2004), oil price shocks and the macroeconomy: what has been learned since 1996. the energy journal, 25(2), 1-32. mehrara, m., oskoui, k.n. (2007), the source of macroeconomic fluctuations in oil exporting countries: a comparative study. economic modelling, 24(3), 365-379. mourougane, a. (2010), phasing out energy subsidies in indonesia. economic department working paper no. 808. paris: oecd. p26. mustika, d. (2015), effects of petroleum exports and imports on the growth of the indonesian economy. journal of regional financing and development perspective, 2(3), 107-118. narayan, p.k. (2005), the saving and investment nexus for china: evidence from cointegration tests. applied economics, 37(17), 1979-1990. omojolaibi, j.a., egwaikhide, f.o. (2014), oil price volatility, fiscal policy and economic growth: a panel vector autoregressive (pvar) analysis of some selected oil-exporting african countries. opec energy review, 38(2), 127-148. o-iea. (2015). energy and climate change, world energy outlook special report. pesaran, m.h., shin, y. (1999), an autoregressive distributed-lag modeling approach to co-integration analysis. in: strom, s., editors. econometrics and economic theory in the 20th century: the ragnar roespinoedji, et al.: an empirical study on short term and long-term consequences of crude oil on economic wellbeing of indonesia by applying ardl model international journal of energy economics and policy | vol 9 • issue 5 • 2019480 frisch centennial symposium. cambridge: cambridge university press. p371-413. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 162, 89-326. phillips, p.c.b., perron, p. (1988), testing for a unit root in time series regression. biometrika, 75(2), 335-346. plante, m. (2014), the long-run macroeconomic impacts of fuel subsidies. journal of development economics, 107, 129-143. rafiq, s., salim, r., bloch, h. (2009), impact of crude oil price volatility on economic activities: an empirical investigation in the thai economy. resources policy, 34, 121-132. sinaga, o., saudi, m.h.m., roespinoedji, d., jabarullah, n.h. (2019), environmental impact of biomass energy consumption on sustainable development: evidence from ardl bound testing approach. ekoloji, 28(107), 443-452. singh, a.k., issac, j. (2018), impact of climatic and non-climatic factors on sustainable livelihood security in gujarat state of india: a statistical exploration. agriculture and food sciences research, 5(1), 30-46. taguchi, h., li, j. (2018), domestic value creation in the involvement in global value chains: the case of chinese economy. asian development policy review, 6(3), 155-168. tambun, s., murwaningsari, e., mayangsari, s. (2018), the effect of accounting information on stock price predictions through fluctuation of stock price, evidence from indonesia. journal of accounting, business and finance research, 4(1), 20-27. tampubolon, b.d., setyoko, a.t. (2019), controlling policies on fossil fuels subsidies to overcome climate change. energy economics letters, 6(1), 1-16. tiwari, a.k., shahbaz, m., hye, q.m.a. (2013), the environmental kuznets curve and the role of coal consumption in india: cointegration and causality analysis in an open economy. renewable and sustainable energy reviews, 18, 519-527. wonyra, k.o. (2018), impact of telecommunications market liberalization on labor productivity in economic community of west african states. journal of social economics research, 5(2), 63-74. yussof, n.s.b., latif, n.w.b. (2013), measuring the effects of world oil price change on economic growth and energy demand in malaysia: an ardl bound testing approach. international journal of economics, trade, and finance, 4(1), 29-35. yusuf, m. (2015), an analysis of the impact of oil price shocks on the growth of the nigerian economy: 1970-2011. african journal of business management, 9(3), 103-115. . international journal of energy economics and policy | vol 8 • issue 6 • 2018 35 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(6), 35-38. techno-economic analysis of fuel vehicles as logistic distribution facilities in indonesia by considering the carbon emission cost virda hersy lutviana saputri1*, muhammad hisjam2 1master program of industrial engineering, faculty of engineering, universitas sebelas maret surakarta, jl. ir. sutami no. 36 a, kentingan, surakarta, 57126, indonesia, 2department of industrial engineering, faculty of engineering, universitas sebelas maret surakarta, jl. ir. sutami no. 36 a, kentingan, surakarta, 57126, indonesia. *email: virdahersy@gmail.com received: 23 july 2018 accepted: 03 october 2018 doi: https://doi.org/10.32479/ijeep.6933 abstract this study aims to perform a techno-economic analysis for the investment of the vigas usage as substitution for pertamax 92 fuel that is starting to be rare. the assessment is done by calculating the value of break even point (bep), net present value (npv), internal rate of return (irr), and payback period (pp). in addition, this study also calculates the amount of carbon emission costs that must be incurred by the company when using pertamax fuel 92 and vigas. the analyzed pollutants are co, hc, nox, and co2. based on the calculation results, bep from replacement pertamax 92 to vigas can be achieved at the distance of 22.653.43 km. the value of npv, irr, and pp indicates that the investment is feasible to be realized. in addition, the cost of carbon emissions generated by vigas is lower than pertamax 92, with a difference of idr 4,191,482.73. keywords: carbon emission, fuel vehicle, techno-economy analysis jel classifications: l52, o25, q42 1. introduction the phenomenon of the development of the freight forwarding industry is currently increasing rapidly, it is because the increasing of consumer demand in freight forwarding services leads to the increase of companies entering the service market to compete and survive. furthermore, based on the research of piesto and king (2002), the increasing number of online retail trade causes the good shipment increasing (cook and dave, 2004). the shipment can be done by land, water, or air transportation. land transportation becomes one of the most widely utilized. it is because land transportation can load resources in the long or medium term, and short distance from location to other location (diaz-parra et al., 2014). vehicles included in the land transportation modes, among others, train, truck, car, and motorcycle. trains as an alternative transportation to delivery of goods have several advantages, including large transport capacity, relatively fast travel time, free from illegal charge and better goods security and better goods safety. however, trains are constrained by the very limited departure frequency. moreover, there is several limitations for transporting goods by train, such as the prohibition of loading b3 transport and b3 waste that can be explosive, burning, reactive and corrosive. then, delivery of goods by truck is banned in some areas due to emissions problems (visser et al., 2014). therefore, cars can be used as one of the modes of transportation that can deliver various types of goods and friendly to the environment. however, the car usage as a mode transportation to deliver goods is necessary to estimate the level of air pollution emissions from the motor vehicle. this can be fulfilled by using fuel-based emission factors, selecting the type of fuel, projecting the fuel price, and estimating the fuel consumption level of motor vehicles (rabia and ahmad, 2010). this journal is licensed under a creative commons attribution 4.0 international license saputri and hisjam: techno-economic analysis of fuel vehicles as logistic distribution facilities in indonesia by considering the carbon emission cost international journal of energy economics and policy | vol 8 • issue 6 • 201836 research related to transportation cost and vehicle fuel emissions have been done. silitonga et al. (2012) conducted a research on economic standard and fuel label standard for vehicles in some asean’s selected countries such as singapore, indonesia, malaysia, philippines, thailand, and vietnam. the results showed that singapore was a country that had adopted fuel labels and economic fuel standards, which played an important role for protecting public health and the environment from emission of transportation, where the commonly used fuels were biodiesel, ethanol, methanol, propane, hydrogen, and natural gas. bakker et al. (2017) conducted research on the comparative analysis of the approach and status of sustainable low carbon transport policies in asean countries and identified differences and similarities. setiyo et al. (2016) performed techno-economic analysis of liquid petroleum gas (lpg) as an alternative fuel vehicle compared to ron 88 and ron 92 petrol for indonesia’s public transportation. from the literatures, it can be seen that there is a research gap, where there has no research that accommodates about the analysis of techno-economic fuel selection and analysis of emission costs simultaneously yet. therefore, this study aims to perform a technoeconomic analysis that considers transportation and emissions costs related to fuel selection. the used method in this study is discussed in chapter 2. then, in the chapter 3 is presented the analysis and result of the study. at last, the conclusion and advanced study will be presented in the chapter 4. 2. method from the transport sector the source of the emissions problem is the fuel. used petroleum fuel produces large pollution, so that, it is needed an environmentally friendly fuel replacement, for example is the usage of lpg (as’adi and djaja, 2017). lpg has a derivative product that is liquid gas for vehicle (lgv) or also known as vigas. lgv has ron 98 that is equivalent to pertamax fuel. therefore, this study will discuss about techno-economic analysis on the vigas fuel usage as a substitute for pertamax on four-wheeled vehicles, as well as the calculation of emissions from each fuel. the methodology that is used in the study will be shown in figure 1. 2.1. techno-economic analysis 2.1.1. break even point (bep) bep is the breakeven point in which the position of the amount of income equals or balances to cost, so there is no profit or loss in a company. the used formula for bep analysis consists of two kinds, namely the basic unit and the basis of sales. in this study, the bep is calculated by basic unit formula, which perform by calculating how many miles distance must be taken by the vehicle to get a breakeven point. as for the calculations performed, use the equation (1). ( )pertamax vigas fc bep p vc = − (1) where, fc is the cost of capital. ppertamax is the pertamax fuel cost per kilometer. vcvigas is the vigas fuel cost per kilometer. 2.1.2. net present value (npv) npv method is used to calculate the present net (present time). npv is the comparison between pv net cash with pv investment over the life of the investment. npv can be calculated using equation (2). ( ) ( )( ) ( ) ( ) ( ) ( ) ( ) 1 1 2 2 0 21 1 01 1 ci co ci co ci coi i inpv ci co sn n in n i i − − − + + +… + += − + + − + + (2) where, ci is cash inflow, co is cash outflow, i is bank interest, n is period, s is residue at the last period, and i0 is initial investment cost. if net benefit (ci-co) and interest (i) are assumed to be unchanged in period n, so the equation (2) can be written as equation (3). ( ) 1 (1 ) 0(1 ) nci co x i s npv ini i − − − + = + − + (3) 2.1.3. internal rate of return (irr) irr is an interest rate (not a bank interest) that describes the profit rate of a project or investment in a percentage at which the npv value is zero. 2.1.4. payback period (pp) pp is a valuation technique to find out how long the period required to return investment from a project or business. the value of pp can be calculated using the equation (4). investment costs pp accumulative proceed = (4) to assess the feasibility of a business or project in terms of pp: if: pp ˃ the project economic life, it will be not feasible. pp ˂ the project economic life, it will be feasible. 2.2. carbon emission analysis motor vehicle exhaust emissions are measured in grams per vehicle per km in a trip/journey. vehicles with different fuel types will produce different emission levels as well (yuliastuti, 2008). this study will compare the value of exhaust emissions based on two types of fuel, namely vigas and pertamax 92. the composition of exhaust emissions are calculated, including co, nox, hc, and co2. the carbon emission analysis is accomplished by calculating the conversion of tons of carbon to the cost. 3. disscusion and result this study describes four-wheeled vehicles as a means of distribution logistic, where mileage per year is assumed to be 62,400 km. the used fuel price per liter is based on current prices saputri and hisjam: techno-economic analysis of fuel vehicles as logistic distribution facilities in indonesia by considering the carbon emission cost international journal of energy economics and policy | vol 8 • issue 6 • 2018 37 (june, 2018), where vigas cost is idr 5100 and pertamax 92 cost is idr 8600. the parameters used in the study, are presented in table 1. 3.1. techno-economic analysis 3.1.1. bep in this study, to calculate the bep, it is assumed to be not changed in fuel cost. based on the calculation, the fuel cost per km of vigas and pertamax 92 are idr 659.77 and idr 1,189.49. using those values to calculate the bep, it is known that the bep value for switching from the pertamax 92 fuel to vigas is obtained at a distance of 22,653.43 km. 3.1.2. npv dan irr in performing npv calculations, it is assumed that the interest rate used is 1% per month and the calculation period is 60 months (5 years). using the equation (3) and the parameters in table 1, the npv and irr transition results from pertamax 92 to vigas are shown in figures 2 and 3. based on these results, it can be obtained the npv as big as idr 110,558,985.02, where the npv >0, so the replacement investment of vigas as substitution of pertamax 92 is considered feasible. another criterion used to look at the extent to which this investment is feasible, is used irr. by using the numbers can be calculated the amount of irr is equal to 21.74%. this means that at an interest rate of 21.74% per annum then the npv of net benefit obtained is zero. 3.1.3. pp in this study, pp is calculated using proceeds or net cash flow to recoup the investment expenditure. net cash flow is derived from the amount of the saving cost of fuel replacement pertamax 92 to vigas, that is equal to idr 2,754,550 per month. with an investment cost as big as idr 12,000,000 then the value of pp generated is 4.36 months. this shows that the pp value < economic life of investment, so the replacement of this fuel is feasible. 3.2. sensitivity analysis sensitivity analysis aims to determine the extent to which the dependence or sensitivity of the feasibility level of fuel replacement pertamax 92 with vigas against the possibility of price changes during the investment is still in the economic period. in this study, sensitivity analysis is done by making changes to the increase of mileage, fuel cost, and the procurement converter kit cost by 5% and 10%. the result is presented in the table 2 and figure 4. in this analysis, the investment criteria index provides a feasible assessment for the continuity of the vehicle fuel replacement program. in the current situation (normal), the irr value is almost figure 1: research methodology figure 2: net present value table 1: the parameters information unit fuel vigas pertamax 92 mileage per year km 62,400.00 62,400.00 fuel consumption km/l 7.73 7.23 fuel consumption per year l 8,072.45 8,630.71 fuel cost per liter idr 5,100.00 8,600.00 fuel costs per year idr 41,169,469.60 74,224,066.39 lpg converter kit price idr 12,000,000.00 0.00 cost savings from pertamax to lpg idr 33,054,596.79 0.00 residual value at the end of year 5 idr 6,000,000.00 0.00 figure 4: sensitivity analysis figure 3: internal rate of return saputri and hisjam: techno-economic analysis of fuel vehicles as logistic distribution facilities in indonesia by considering the carbon emission cost international journal of energy economics and policy | vol 8 • issue 6 • 201838 close to the minimum investment feasibility but still feasible to be realized. then, if there is an increase in mileage, fuel cost, and the procurement converter kit cost as much as 5% and 10%, indicating that this investment is more feasible to do. 3.3. carbon emission analysis the calculation of carbon emissions is done by converting the amount of tonnes of carbon produced from each fuel to the unit cost. the carbon emissions unit (g/km) of vigas and pertamax 92 are assumed to be same as the results of the research as’adi and djaja (2017). the emission test result is presented in table 3. the emission/pollutant cost from research conducted in canada in 2005 ($/ton) (muziansyah et al., 2015): 1. carbon mono-oxide (co)= $205/ton 2. particulate (pm10)= $3,17/ton 3. carbon dioxide (co2) = $205/ton 4. sulfur dioxide (so2)= $1000/ton 5. nitrogen oxide (nox)= $934/ton 6. hydrocarbon (hc)= $44/ton. by using the above data, it can be calculated the amount of costs incurred associated carbon emissions for each fuel vigas and pertamax 92 within 1 year, where the distance traveled by a vehicle is 62,400 km and the dollar price ($) is idr 13,888.7. the calculation result is presented in table 4. based on the result of the calculation, it is found that the cost of carbon emissions of vigas fuel is lower than pertamax 92, with a cost difference as much as idr 4,191,482.73 per year. 4. conclusion based on techno-economic analysis of vehicle fuel, the replacement investment of pertamax 92 to vigas is declared feasible. then based on the analysis of the carbon emissions cost that must be spent for each fuel, it can be seen that vigas is lower than pertamax 92. this means that vigas is more environmentally friendly than pertamax 92. this study only considers two types of fuel and four types of exhaust gas pollutants from the vehicles, so that, in the future, can be done research for each type of fuel used in indonesia as well as assessing exhaust gas pollution more fully. eventually, it is expected that this study can be used as consideration for stakeholders of related government to make a choice of vehicle fuel effectively and efficiently. 5. acknowledgment the research is supported by institute for research and community service, sebelas maret university with hibah penelitian mandatory uns (pm-uns) research program (contract no. 543/un27.21/pp/2018). references as’adi, m., djaja, y. (2017), kaji eksperimental penggunaan liquid gas for vehicle (lgv) dengan pertamax terhadap performa dan emisi gas buang motor bensin 2000 cc. journal teknik mesin, 6, 62-68. bakker, s., contreras, k.d., kappiantari, m., tuan, n.a., guillen, m.d., gunthawong, g., zuidgeest, m., liefferink, d., van maarseveen, m. (2017), low-carbon transport policy in four asean countries: developments in indonesia, the philippines, thailand and vietnam. sustainability, 9, 1217. cook, d.p., dave, d.s. (2004), structural elements of online service product quality. international journal of business performance management, 6(2), 189-207. diaz-parra, o., ruiz-vanoye, j.a., loranca, b.b., fuentes-penna, a., barrera-camara, r.a. (2014), a survey of transportation problems. journal of applied mathematics, 2014, 1-17. muziansyah, d., sulistyorini, r., sebayang, s. (2015), model emisi gas buangan kendaraan bermotor akibat aktivitas transportasi (studi kasus: terminal pasar bawah ramayana kota bandar lampung). jurnal rekayasa sipil dan desain, 3(1), 57-70. piesto, n., king, c. (2002), united states department of commerce news. washington, dc: us census bureau. rabia, s., ahmad, s.s. (2010), monitoring urban transport air pollution and energy demand in rawalpindi and islamabad using leap model. energy policy, 35, 2323-2332. setiyo, m., soeparman, s., hamidi, n., wahyudi, s. (2016), technoeconomic analysis of liquid petroleum gas fueled vehicles as public transportation in indonesia. international journal of energy economics and policy, 6(3), 495-500. silitonga, a.s., atabani, a.e., mahlia, t.m.i. (2012), review on fuel economy standard and label for vehicle in selected asean countries. renewable and sustainable energy reviews, 16(3), 1683-1695. visser, j., nemoto, t., browne, m. (2014), home delivery and the impacts on urban freight transport: a review. social and behavioral sciences, 125, 15-27. yuliastuti, a. (2008), estimasi sebaran keruangan emisi gas buang kendaraan bermotor di kota semarang. skripsi. jurusan perencanaan wilayah dan kota. semarang: universitas diponegoro. table 2: the comparison result of sensitivity analysis parameter normal plus 5% plus 10% npv 110,558,985.02 122,342,541.53 134,721,870.16 irr 21.74% 22.87% 24.01% table 3: carbon emission parameter vigas pertamax 92 co (gr/km) 0.95 0.12 hc (gr/km) 0.01 0.006 nox (gr/km) 0 0.027 co2 (gr/km) 182.5 206.8 table 4: the cost calculation of carbon emission pollutant vigas (idr) pertamax 92 (idr) carbon mono-oxide (co) 168,781.04 21,319.71 carbon dioxide (co2) 32,423,725.70 36,740,966.98 nitrogen oxide (nox) 0.00 21,855.30 hydrocarbon (hc) 381.33 228.80 total 32,592,888.06 36,784,370.79 international journal of energy economics and policy vol. 1, no. 4, 2011, pp.140-149 issn: 2146-4553 www.econjournals.com energy-growth causality: asian countries revisited evan lau, corresponding author department of economics, faculty of economics and business, universiti malaysia sarawak, 94300 kota samarahan sarawak, malaysia. tel: +6082-582430. email: lphevan@feb.unimas.my xiao-hui chye department of economics, faculty of economics and business, universiti malaysia sarawak, 94300 kota samarahan sarawak, malaysia. email: celinechye@yahoo.com chee-keong choong centre for economic studies, faculty of business and finance, universiti tunku abdul rahman (perak campus), jalan universiti, bandar barat, 31900 kampar, perak, malaysia. e-mail: choongck@utar.edu.my abstract: understanding the impact of energy consumption on economic growth is an important consideration in the formulation of both energy and environmental policies. motivated by this development, this paper empirically re-examines the direction of causality and the sign (in the panel sense) between energy consumption (ec) and the gross-domestic product (gdp) for seventeen selected asian countries. results reveal long-run stable equilibriums in these countries, while the ec brings about a positive impact on gdp. causality runs from ec to gdp in the short-run, while the long-run causal linkage exists from gdp to ec. this indicates that energy is a force for economic growth in the short-run, but in the long-run, the ec is fundamentally driven by economic growth. efficient coordination and cooperation towards the implementation of energy conservation policies to support sustainable economic development should be in the regional agenda. keywords: energy consumption; panel analysis; economic growth; asian countries jel classifications: q43, c32 1. introduction energy consumption has steadily increased over the past few decades in asian countries due to the population increment and industrial expansion1. energy consumption is expected to increase to 159.3 quadrillion btu in 2015, 187.8 quadrillion btu in 2020, 217.0 quadrillion btu in 2025, 246.9 quadrillion btu in 2030 and 277.3 quadrillion btu in 2035. the average annual percentage change from 2007 to 2035 in asia is 2.8 percent, which is higher than other regions, such as the middle eastern countries (2.2 percent), central and south america (1.8 percent), and africa (1.8 percent) (eia, 2010; table 1, 9). the major users of energy were china and india, who continue to lead the world in relation to economic growth and energy demand growth. together, china and india accounted for about 10 percent of the world's total energy consumption in 1990 and 20 percent in 2007 (eia, 2010). china and india’s other significant increases include a fast-paced growth in population, rapid economic growth and industrial expansion into other areas of the asian region. 1 according to eia (2008), asia’s total primary energy consumption in 1990 was 47.4 quadrillion british thermal units (btu). this number doubled to about 127.1 quadrillion btu in 2007. energy-growth causality: asian countries revisited 141 the episodic energy crisis, coupled with depleting energy sources, environmental costs and highenergy consumption, has forced governments around the globe to more intently monitor and manage energy markets (ecssr, 2004). growing concerns had attracted the interest of the government in asian countries. these measures include cooperation for energy conservation and the efficient usage of energy policies. in this context, the long-run relationship between energy consumption and economic growth has been a lively topic of empirical assessment. in the energy economics literature, the direction of causality as to whether the adoption of energy savings inhibits or stimulates economic growth has been a much debated matter2. understanding the impact and causality patterns of energy consumption on economic growth is an important consideration in the formulation of both energy and environmental policies. accordingly, squalli (2007, 1193-4), payne (2010a, 54 – 55) and ozturk (2010, 340-341) provide excellent descriptions of four hypotheses related to the relationship between energy consumption and economic growth. briefly, the four patterns include: (1) the “growth” hypothesis, where the causality runs from energy consumption to growth. this pattern exists in energy dependent countries (yu and choi, 1985 for the philippines, masih and masih, 1996 for india, asafu-adjaye, 2000 for india and indonesia, soytas and sari, 2003 for turkey, france, japan and germany, lee, 2005 for a panel of eighteen developing countries and tsani, 2010 for greece); (2) the “conservation” hypothesis, where gdp granger-causes energy consumption (kraft and kraft (1978) for the united states (us), abosedra and baghestani (1989) for the us, cheng and lai (1997) for taiwan, cheng (1999) for india, ang (2008) for malaysia and zhang and cheng (2009) for china). recently, phung (2011) found positive unidirectional causality running from gdp to energy consumption in vietnam. for this purpose, policies such as the reduction in greenhouse emissions designed to reduce energy consumption and waste may not adversely affect real gdp. (3) the “neutrality” hypothesis views the absence of granger-causality between energy consumption with gdp (yu and hwang (1984); altinay and karagol (2004); halicioglu (2009) and payne (2010a). (4) the “feedback” hypothesis suggests that energy consumption and gdp are interdependent and support the existence of bi-directional causality (hwang and gum, 1991; yang, 2000; oh and lee, 2004; climent and pardo, 2007; apergis and payne, 2009; ozturk and acaravci 2010). the literature has not come to a general agreement on the nature of causal relationships between energy consumption and economic growth. in this context, policies aiming at the gradual curtailing of energy need to consider the potential causal linkages between economic growth and energy consumption. motivated by this development, the goal of this study is to empirically re-examine the direction of causality and sign (in the panel sense) between energy consumption (ec) and real gdp for seventeen asian countries. once the causality is ascertained, appropriate energy development policies in these countries can be adopted. as such, the structure of the rest of this paper is as follows. a brief and intuitive account of the econometric methodology employed is provided in section 2, before discussing the results in detail in section 3. some policy implications and conclusions are made in section 4. 2. econometric modeling 2.1 panel unit root and stationary tests the first step in the estimation of dynamic panels is to test whether the variables at hand contain unit roots. studies that have used joint panel unit root tests include maddala and wu (1999, mw), hadri (2000, hadri), levin et al., (2002, llc) and im et al. (2003, ips). the null hypothesis in all joint panel unit root tests, except the hadri test, is that the panel series has a unit root (nonstationary). unlike the augmented dickey fuller (adf) test, the hadri test is similar to the kwiatkowski, phillips, schmidt, and shin (kpss – based lm) statistic, which has a null hypothesis of 2 literature about the energy-growth causality was coined from the seminal work of kraft and kraft (1978). since then, impressive volumes of papers were dedicated to this genre. ozturk (2010) and payne (2010a) conducted an excellent survey, while payne (2010b) and narayan et al. (2010) investigated the electrical consumption and growth literature. on the asian side, yu and choi (1985), masih and masih (1996, 1998), asafu-adjaye (2000) soytas and sari (2003) and lee and chang (2008) were among the champions. international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.140-149 142 level (trend) stationarity and an alternative of difference stationarity in the panel. a comparison of the results obtained from the wide range of panel unit root tests can provide some insight into the stationarity properties of the data. if both procedures fail to reject the null hypothesis (or if both reject), we have mixed results and can only conclude that the data are not informative enough. on the other hand, if an adf type panel unit root test rejects the null and the kpss type test fails to reject it, we have greater confidence that the series under consideration is in fact stationary. as these panelbased unit root tests are becoming common in the literature, interested readers may refer to their original articles for a more comprehensive discussion. 2.2 panel cointegration we then proceed to examine whether there exists any long-run equilibrium relationship between the variables under investigation. we resort to pedroni (1999, 2001, 2004) and kao (1999) panel cointegration tests. pedroni considers seven different statistics, four of which are based on pooling the residuals of the regression along the within-dimension (panel test) of the panel. the other three are based on pooling the residuals of the regression along the between-dimension (group test) of the panel. the within-dimension tests take into account common time factors and allow for heterogeneity across countries. the between-dimension tests are the group-mean cointegration tests, which allow for the heterogeneity of parameters across countries. kao (1999) proposed dickey fuller (df) and adf-type tests for it , where the null is specified as no cointegration. in this study, we only report the adf-type test. the details of these tests are discussed in appendix 1. 2.3 panel fully modified ols (fmols) estimates to obtain the long-run estimates for the cointegrating relationship (the coefficients of ec), we adopt the panel group mean fully modified ols (fmols), following the work by pedroni (2000). the fmols procedure accommodates the heterogeneity that is typically present, both in the transitional serial correlation dynamics, and in the long-run cointegrating relationships. the fmols estimator is described in detail in appendix 1. 2.4 granger causality tests to test for panel causality, we estimate a panel based vector error correction model (vecm) with a dynamic error correction term based on the analysis in holtz-eakin et al. (1988, 1989). the empirical models are as follows: ititipit m p ip m p pitipjit ectecgdpgdp 111 1 12 1 111       (1a) ititipit m p ip m p pitipjit ectgdpecec 212 1 22 1 212       (1b) where:  is the lag operator and p denotes the lag length. the specification in equation 1 allows for testing the causality direction. for example, in the short-run, the ec does not granger cause gdp where :0h ip12 0 for all i and p , while i1 0 in equation (1a) 3. the rejection implies that ec  gdp, supporting the growth hypothesis. similar analogous restrictions and testing procedures can be applied in testing the hypothesis that gdp does not granger cause movement in ec, where the null hypothesis h0: 022 ip for all i and p , while i2 0 in equation (1b). 3 the f-test or wald 2 of the explanatory variables (in the first differences) indicates the short-run causal effects ( 012 ip for all i and p ), while the long-run causal ( i1 =0) relationship is implied through the significance of the lagged ect, which contains the long-run information. energy-growth causality: asian countries revisited 143 3. empirical results 3.1 data sources annual data from 1980 to 2006 for the 17 asian countries were utilized for the study4. per capita total primary energy consumption (ec) data were obtained from the international energy annual 2006 of energy information administration (eia). real gdp data were obtained from the world development indicators (wdi) 2008 of the world bank. all variables were transformed into the logarithmic form. 3.2 panel unit root and stationary results the results, made available upon request, illustrate that the series of the variables are of an i(1) process, as the pooled data are stationary in their first differences. these results enable us to test the cointegration among ec and gdp. 3.3 panel cointegration results from the panel cointegration results in table 1, we find strong evidence to reject the null hypothesis of no cointegration for all seven statistics provided by pedroni (1999, 2001, 2004). similarly, we reject the null hypothesis of no cointegration using the adf-type statistics from the kao (1999) panel cointegration tests, suggesting that that the two-dimensional model for the asian countries is cointegrated and moves together in the long-run. thus, we find that gdp and ec are cointegrated in the multi-country panel setting for the sample period. table 1. panel cointegration tests results a: pedroni residual cointegration test panel cointegration statistics (within-dimension) panel v-statistic 4.246 (0.000) panel pp type -statistic -2.212 (0.035) panel pp type t-statistic -2.318 (0.027) panel adf type t-statistic -4.525 (0.000) group mean panel cointegration statistics (between-dimension) group pp type -statistic 2.187 (0.037) group pp type t –statistic 4.122 (0.000) group adf type tstatistic 2.706 (0.010) b: kao residual cointegration test adf 2.513 (0.006) notes: the number of lag truncations used in the calculation of the seven pedroni statistics is lag 5. probability values are in parenthesis. 3.4 panel fmols estimates having established cointegration in the long-run, we estimate the long-run parameters of the model by using the fmols technique. the fmols corrects the standard ols for bias induced by the endogeneity and serial correlation of the regressors (lee, 2005). the elasticity of energy consumption is important for understanding the past and assessing future economic dynamics. it represents the weights with which the marginal relative changes of the energy consumption contributes to the relative change of output (lee et al., 2008). table 2 reports the results of the long-run estimates for seventeen asian countries and the panel estimates based on pedroni’s group mean fmols estimator. the panel results of the regression equation with gdp as the dependent variable illustrate that the coefficient of the ec is positive and 4 the asian countries included bangladesh, bhutan, brunei darussalam, china, hong kong, india, indonesia, japan, korea, malaysia, maldives, nepal, pakistan, philippines, singapore, sri lanka, and thailand. international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.140-149 144 statistically significant at the 5 percent significance level. a one percent increase in energy consumption leads to a 0.21 percent increase in gdp for these seventeen asian countries. this positive coefficient on ec implies that more energy results in greater outputs, as suggested by lee, (2005), narayan and smyth (2008), lee and chang, (2008) and ozturk, (2010). turning to the country specific evidence, the results also indicate a positive and significant relationship between ec and gdp for all countries. the elasticity estimates range from 0.10 (hong kong) to 0.94 (philippines). the results suggest that the ec contributes most to the philippines’ output, whereas it contributes least to hong kong’s output. having inelastic coefficients on ec suggests that the vulnerability of energy prices would not have a significant impact on the consumption patterns in these countries, as it would be considered necessities for the society as a whole. table 2. fmols estimates countries energy consumption bangladesh 0.920 (10.660)* bhutan 0.220 (33.840)* brunei 0.330 (9.305)* china 0.370 (2.080)* hong kong 0.100 (27.710)* india 0.140 (10.250)* indonesia 0.660 (5.790)* japan 0.390 (3.220)* korea 0.160 (9.410)* malaysia 0.170 (11.100)* maldives 0.380 (1.780)* nepal 0.150 (4.790)* pakistan 0.230 (38.580)* philippines 0.940 (12.200)* singapore 0.340 (7.750)* sri lanka 0.180 (14.620)* thailand 0.200 (5.630)* panel estimates 0.210 (44.330)* notes: the values in parentheses are the t-statistics. asterisk (*) shows significance at 5 percent level. all variables are transformed into logarithm form prior to estimation. 3.5 panel granger causality test results once the long-run estimates have been determined, we turn to the causality linkages. the empirical results presented in table 3 illustrate that the coefficient of the error correction term (ect) is not statistically significant in the gdp equation, indicating the absence of a long-run causality relationship running from ec to gdp. however, we note the existence of a significant short-run causal relationship running from ec to gdp, since the estimated coefficients of the explanatory variables are statistically significant. the short-run results are supported by asafu-adjaye (2000), soytas and sari (2003), lee (2005), narayan and smyth (2008) and tsani (2010), who established evidence of a short-run granger causality running from ec to gdp. table 3. panel granger causality test results dependent variables δgdp δec ect 2-statistics (p-value) coefficient t-ratio δgdp 19.661 (0.001) 0.001 0.614 δec 2.108 (0.715) -0.002 -4.056 notes: parenthesized values are the probability of rejection of granger non-causality. δ is the first different operator. estimations are based on the pooled data for 1980-2006 and 17 asia countries (n=17, t=27) with four lags. all variables are transformed into logarithm form prior to estimation. energy-growth causality: asian countries revisited 145 on the other hand, we find evidence of the existence of a long-run relationship running from gdp to ec, in which the coefficient of the error correction term (ect) is statistically significant in the ec equation. this result illustrates that energy consumption is determined by economic growth; supporting the conservation hypothesis. this pattern is similar to results from developing countries (cheng and lai, 1997; cheng, 1999; mahadevan and asafu-adjaye, 2007; ang, 2008 and ozturk, 2010). 4. concluding remarks using panel estimation for seventeen asian countries, this paper empirically examines the relationship between energy consumption and the gross domestic product (gdp). we find that the variables were in a stationary fashion in their first differences or were in an i(1) process. the panel cointegration results reveal a long-run equilibrium relationship among the two variables. the results of the fmols show that the energy consumption variable has a positive sign. this indicates that an increase in gdp would lead to a greater use of energy. from the granger causality test, there is a short-run unidirectional causal relationship running from energy consumption to gdp. this implies that in the short-run, energy consumption leads to economic growth, since the economies in these 17 asian countries are energy-dependent economies. additionally, in the long-run, gdp granger causes energy consumption for the panel. this provides additional evidence in support of the proposition that energy consumption is a result of economic activity, rather than being an essential input to production. in the short-run, the implementation of energy conservation policies might lead to a significant, but temporary, negative impact on economic growth in these asian countries. however, economic development in the asian countries is less dependent on energy in the long-run. cooperation for energy conservation policies among the asian countries would be an imperative move that would not harm gdp. proactive agendas of research and development on renewable technologies in response to depleting supplies of energy sources would be another avenue that could be used to improve energy transportation facilities and infrastructure development to improve delivery efficiency. niu et al. (2011)5 argued that developing countries may benefit from their developed nations counterparts, where they may fetch advanced technology and capital to facilitate efficient energy use, while reducing energy consumption and carbon emissions. efforts have also been made in pursuit of more environmentally-friendly and resource-saving societies to promote energy efficiency in the face of concern about the effects of global warming for the asian region (chang, 2010; lean and smyth, 2010 and li et al., 2011). with the recent experience of unprecedented high levels of energy prices, depleting energy sources and international initiatives such as kyoto protocol, the commitment needs to be established to facilitate successful energy conservation policies. acknowledgement the authors are grateful to universiti malaysia sarawak (unimas) for the supporting this research through grant no. fpi (f01)/01/2011(01). we are thankful for the comments and suggestions of the participants at the international conference on applied economics (icoae 2011), perugia, italy, 25 27 august 2011. all remaining flaws are responsibilities of the authors. references abosedra, s., baghestani, h., 1989. new evidence on the causal relationship between united states energy consumption and gross national product. journal of energy development 14, 285 – 292. altinay, g., karagol, e., 2004. structural break, unit root, and the causality between energy consumption and gdp in turkey. energy economics 26, 985-94. ang, j., 2008. economic development, pollutant emissions and energy consumption in malaysia. journal of policy modeling 30, 271-278. apergis, n., payne, j.e., 2009. energy consumption and economic growth in central america: evidence from a panel cointegration and error correction model. energy economics 31, 211-216. 5 accordingly, as per table 2 (pp. 2123) in the paper, four developed countries (australia, new zealand, japan and south korea) have the technological advancement therefore, their energy efficiency is higher comparatively to the four developing countries (china, india, indonesia and thailand). international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.140-149 146 asafu-adjaye, j., 2000. the relationship between energy consumption, energy prices, and economic growth: time series evidence from asian developing countries. energy economics 22, 615-625. chang, c. c., 2010. a multivariate causality test of carbon dioxide emissions, energy consumption and economic growth in china. applied energy 87, 3533–3537 cheng, b.s., 1999. causality between energy consumption and economic growth in india: an application of cointegration and error correction modeling. indian economic review 34, 39-49. cheng, b.s., lai, t.w., 1997. an investigation of cointegration and causality between energy consumption and economic activity in taiwan. energy economics 19, 435-444. climent, f., pardo, a., 2007. decoupling factors on the energy-output linkage: the spanish case. energy policy 35, 522-528. emirates center for strategic studies and research (ecssr), 2004. asian energy markets: dynamics and trend, emirates center for strategic studies and research. energy information administration (eia), 2008 international energy outlook 2008. washington, d.c.: energy information administration. energy information administration (eia), 2010. international energy outlook 2010. washington, d.c.: energy information administration. hadri, k., 2000. testing for stationarity in heterogeneous panel data. econometrics journal 3, 148161. halicioglu, f., 2009. an econometric study of co2 emissions, energy consumption, income and foreign trade in turkey. energy policy 37, 1156–1164. holtz-eakin, d., newey, w., rosen, h., 1988. estimating vector autoregressions with panel data. econometrica 56, 1371-1395. holtz-eakin, d., newey, w., rosen, h., 1989. the revenues-expenditure nexus: evidence from local government data. international economic review 30, 415-429. hwang, d.b.k., gum, b., 1991. the causal relationship between energy and gnp: the case of taiwan province of china. journal of energy and development 16, 219-226. im, k.s., pesaran, m.h., shin, y., 2003. testing for unit roots in heterogeneous panels. journal of econometrics 115, 53-74. kao, c., 1999. spurious regression and residual-based tests for cointegration in panel data. journal of econometrics 90, 1-44. kraft, j., kraft, a., 1978. on the relationship between energy and gnp. journal of energy and development 3, 401-413. lean, h.h., smyth, r., 2010. co2 emissions, electricity consumption and output in asean. applied energy 87, 1858–1864 lee, c.c., 2005. energy consumption and gdp in developing countries: a cointegrated panel analysis. energy economics 27, 415-427. lee, c.c., chang, c.p., 2008. energy consumption and economic growth in asian economies: a more comprehensive analysis using panel data. resource and energy economics 30, 50-65. lee, c.c., chang, c.p., chen, p.f., 2008. energy-income causality in oecd countries revisited: the key role of capital stock. energy economics 30, 2359-2373. levin, a., lin, c.f., chu, c.s.j., 2002. unit root tests in panel data: asymptotic and finite sample properties. journal of econometrics 108, 1-24. li, f., dong, s.c., li, x., liang, q., yang, w.z., 2011. energy consumption-economic growth relationship and carbon dioxide emissions in china. energy policy 39, 568–574 maddala, g.s. and wu, s., 1999. a comparative study of unit root tests with panel data and a new simple test. oxford bulletin of economics and statistics 61, 631-652. mahadevan, r., asafu-adjaye, j., 2007. energy consumption, economic growth and prices: a reassessment using panel vecm for developed and developing countries. energy policy 35, 2481-2490. masih, a.m.m., masih, r., 1996. energy consumption, real income and temporal causality: results from a multi-country study based on cointegration and error-correction modeling techniques. energy economics 18, 165-183. masih, a.m.m., masih, r., 1998. a multivariate cointegrated modeling approach in testing temporal causality between energy consumption, real income, and prices with an application to two asian ldcs. applied economics 30, 1287-98. energy-growth causality: asian countries revisited 147 narayan, p.k., smyth, r., 2008. energy consumption and real gdp in g7 countries: new evidence from panel cointegration with structural breaks. energy economics 30, 2331 2341. narayan, p.k., narayan, s., popp, s., 2010. does electrical consumption panel granger cause gdp? a new global evidence. applied energy 87, 3294–3298. niu, s., ding, y., niu, y., li,y., luo, g., 2011. economic growth, energy conservation and emissions reduction: a comparative analysis based on panel data for 8 asian-pacific countries. energy policy 39, 2121–2131. oh, w., lee, k., 2004. causal relationship between energy consumption and gdp revisited: the case of korea 1970-1999. energy economics, 26, 51-59. ozturk, i., 2010. a literature survey on energy-growth nexus. energy policy, 38: 340 – 349. ozturk, i., acaravci, a., 2010 the causal relationship between energy consumption and gdp in albania, bulgaria, hungary and romania: evidence from ardl bound testing approach. applied energy 87, 1938–1943. payne, j.e., 2009. on the dynamics of energy consumption and output in the us. applied energy 86, 575-577. payne, j.e., 2010a. survey of the international evidence on the causal relationship between energy consumption and growth. journal of economic studies 37, 53-95. payne, j.e., 2010b. a survey of the electrical consumption-growth literature. applied energy 87, 723-731. pedroni, p., 1999. critical values for cointegration tests in heterogeneous panels with multiple regressors. oxford bulletin of economics and statistics 61, 653-670. pedroni, p., 2000. fully modified ols for heterogeneous cointegrated panels. advances in econometrics 15, 93-130. pedroni, p., 2001. purchasing power parity tests in cointegrated panels. the review of economics and statistics 83, 727-731. pedroni, p., 2004. panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the ppp hypothesis. econometric theory 20, 597-625. phung t.b., 2011. energy consumption and economic growth in vietnam: threshold cointegration and causality analysis, international journal of energy economics and policy, 1, 1–17. soytas, u., sari, r., 2003. energy consumption and gdp: causality relationship in g-7 and emerging markets. energy economics 25, 33-37. squalli, j., 2007. electricity consumption and economic growth: bounds and causality analyses of opec countries. energy economics 29, 1192-1205. tsani, s.z., 2010. energy consumption and economic growth: a causality analysis for greece. energy economics 32, 582–590. yang, h.y., 2000. a note on the causal relationship between energy and gdp in taiwan. energy economics, 22, 309-317. yu, e.s.h., choi, j.y., 1985. the causal relationship between energy and gnp: an international comparison. journal of energy and development 10, 249-272. yu, e.s.h., hwang, b., 1984. the relationship between energy and gnp: further results. energy economics 6, 186-90. zhang, x.p., cheng, x.m., 2009. energy consumption, carbon emissions and economic growth in china. ecological economics 68, 2706–2712. international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.140-149 148 appendix panel cointegration and fully modified ols pedroni panel cointegration test there are in all seven panel cointegration tests. detailed description of the formulae for the seven panel cointegration statistics, are given in pedroni (1999: 660-661). a. within-dimension (panel tests): a) panel -statistic b) panel phillip-perron (pp) type  -statistics c) panel phillips-perron (pp) t -statistic (non-parametric) d) panel augmented dickey fuller (adf) t -statistic (parametric) b. between-dimension (group tests): e) group phillip-perron (pp) type  -statistics f) group phillips-perron (pp) t -statistic (non-parametric) g) group augmented dickey fuller (adf) t -statistic (parametric) these seven statistics are based on the estimated panel cointegration regression residuals of the likely cointegrating vector titiiiti ectgdp ,,1,   (a.1) varying across countries, thus permitting full heterogeneity ( i ), fixed effects ( i ) and individual specific deterministic trends ( ti ) across individual members of the panel pedroni (1999) shows that under appropriate standardization based on the moments of vector of brownian motion function, each of these statistics converges weakly to a standard normal distribution when both the t and n of the panel grow large. the standardized distributions for the above mentioned seven panel and group statistics can be expressed in the form of )1,0(, n ne tn     (a.2) where nte is the respective panel/group cointegration statistic and  and  are the expected mean and variance of the corresponding statistics. they are computed by monte carlo stochastic simulations and tabulated in pedroni (1999, table 2). kao panel cointegration test unlike pedroni test, kao (1999) test specifies cross-section specific intercepts and homogeneous coefficients on the first-stage regressors. in this case, we specified the panel regression model as itititit zxy   '' (a.3) where ity and itx are i(1) and non cointegrated. for itz = }{ i kao (1999) proposed df and adf-type unit root tests for it where the null is specified as no cointegration. the df-type test can be calculated from this regression of: ititit   1ˆˆ (a.4) while the augmented version of the pooled specification: itp p j jitjitit      1 1 ˆˆˆ (a.5) where  ˆ~~ˆ ititit xy  and . ~ iit yyy  the ols estimate of  and the t-statistics are given as          n i t t it n i t t itit 1 2 2 1 2 1 ˆ ˆˆ ˆ    and      s t n i t t it    1 2 2 1ˆ1ˆ . energy-growth causality: asian countries revisited 149 in this case,      n i t t ititnt s 1 2 2 1 2 .ˆˆˆ 1  under the null of no cointegration, kao (1999) shows that following the statistics:   2.10 31ˆ ntn df     (a.6) ntdf pt 875.125.1  (a.7)   4 0 4 2 0 ˆ5 ˆ36 ˆ ˆ3 * 3 1ˆ              ntn df (a.8) 2 0 2 2 2 0 0 ˆ10 ˆ3 ˆ2 ˆ ˆ2 ˆ6 *                vn t t df (a.9) where 12 ˆˆˆˆ  xxyxyy and 12 0 ˆˆˆˆ  xxyxyy . for adf can be constructed as: 2 0 2 2 2 0 ˆ10 ˆ3 ˆ2 ˆ 0ˆ2 ˆ6                n t adf adf (a.10) where adft is the t-statistics of  in equation a.5. fully modified ols estimates following pedroni (2000, 2001), we consider the following cointegrated system for panel data of ititiiit xy   (a.11) ittiit exx  1, (a.12) where, ni ,...,2,1 countries over the time period of mt ,...2,1 . in addition, )',( ititit xyz  ~ )1(i and )',( ititit e  ~ )0(i with covariance matrix of , '0 iiii  where i 0 is the contemporaneous covariance, i is the weighted sum of autocovariances while 'iii ll in which il is the lower triangular decomposition of i . for simplicity, we assume that y = gdp while x [ec] of a.1 in this study. the panel fmols estimator for coefficient  is given as:                          n i iit t t itit t t ititfm tyxxxxn 1 * 1 1 1 21* ˆ)()(  (a.13) where   it i i itit x l l yyy  22 21* ˆ ˆ and  .ˆˆˆ ˆ ˆˆˆ 02222 22 210 2121 ii i i iii l l  likewise, the associated t-statistics for the estimator can be constructed as:    n i ifmfm tnt 1 ˆ 2/1 ˆ * , *  where .)(ˆ)ˆ( 2/1 1 21 110 * ,ˆ* ,             t t iitiifm xxt ifm   . international journal of energy economics and policy | vol 8 • issue 3 • 2018258 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(3), 258-266. learning rates in wind energy: cross-country analysis and policy applications for russia svetlana ratner1*, еvgenii khrustalev2 1institute of control science, russia, 2central economics and mathematics institute, russian academy of sciences, russia. *email: lanarat@mail.ru abstract this article performs a meta-analysis of data on learning rates in wind energy, obtained from building singleand dual-factor learning curve models detailed by countries and technology development periods. it reveals a significant difference in learning rates mainly due to design and efficiency of government support programs. multiple case studies were performed in order to interpret these results. this study proves that the maximal learning rate in wind energy can be achieved by financial support of r&d on the early stage of technological development and by attracting large manufacturers of wind turbines and other electric generation equipment on later stages. given the fact that wind equipment manufacturing technologies are currently well developed and the global market of wind turbines is highly competitive, the tactic of obtaining technologies in exchange for access to the domestic market may prove successful even with a small domestic market capacity. keywords: wind energy, learning curves, power engineering, economic analysis jel classifications: o33, q42, q47, q48 1. introduction to date, russia has one of the “greenest” fuel and electricity balances among all major industrial countries. more than half of domestic energy consumption in russia is natural gas, the cleanest of fossil fuels, and the share of coal in the overall energy balance and power generation is significantly lower than in the eu, china or the us. in addition, over the past few years, the country has made a significant contribution to the development of renewable energy thanks to state financial incentives in the frame of government decree #449 “on the mechanism of promoting the use of renewable energy in the electric power wholesale market” adopted in 2013 and lasting until 2020 (kozlova and mikael, 2016; smeets, 2017). as a result of government tenders in 2013–2017 more than 180 solar and wind generation projects were selected for a subsequent support, each with a capacity of not <5 mw and total capacity more than 4,150 gw. in 2017 about 100 mw of solar power plants were built and the first large wind farm with a capacity of 35 mw was installed. the domestic technologies are developing, and the russian production base in the field of solar and wind energy is emerging (ratner and nizhegorodtsev, 2017). although the solar energy sector exhibits a stable trend of growth, in particular thanks to the creation and rapid development of hevel group, one of the largest pv module manufacturers in russia, the wind energy sector still significantly lags behind the plans outlined in governmental programs for increasing the capacity of installations. figure 1 shows the planned values for support of wind energy, as well as real values for projects that were actually supported by tenders throughout the entire period of implementation of the state program. it isn’t difficult to notice the lack of quotas for wind energy project support during 2014 and 2015. the primary reason for this is russia’s inexperience in production of medium-sized and large wind turbines, as well as the difficulty of satisfying the state requirements towards the localization index. some of the wasted opportunities for state support were caught up with in 2016-2017, but the previous unsuccessful experience with implementing wind energy projects (figure 2) gives doubt to the possibility of projects that started in 2016-2017 being complete within the planned deadlines. for example, the launch of the first wind farm in russia has been delayed multiple times due to the search for a supplier ratner and khrustalev: learning rates in wind energy: cross-country analysis and policy applications for russia international journal of energy economics and policy | vol 8 • issue 3 • 2018 259 of wind turbine components taking a long time. finally, the chinese company dongfung was chosen, which supplied 14 wind generators with a capacity of 2.5 mw each. mostly russian companies took part in the design and construction of the wind farm, many of which participated in a project like this for the first time. despite this, the localization requirements for this project were still not fully met. the dutch company vestas has joined the wind farm construction as a technological partner further down the line, with the intent of having them localize their production in russia by building a blade factory in the ulyanovsk region. the issue of practicality of the state support for wind energy via a guaranteed roi over 15 years remains open. the expert opinion is split: some believe that the program must certainly be continued to provide necessary pacing for the industry’s development and create conditions for learning by doing and researching. on the other hand, some support its termination, arguing that the program gave the necessary impulse for developing renewable energy, and now market mechanisms stimulating manufacturers to decrease expenditure and increase competitiveness of their products must come into play. the goal of this paper is to research the experience of leading countries in the field of wind energy and find best practices for decreasing the expenditure on construction and use of wind farms to further adapt them to russian conditions. in order to project future wind technology cost trend that can be achieved in russia we use a methodology of learning curves. the paper contributes to the literature by addressing the following questions: (1) what is the maximal possible learning rate that can be achieved in the russian wind energy segment while executing the state support plans, (2) which learning rates are characteristic for the early stages of development of the industry and under which conditions are they attained, (3) which state-provided stimuli allow to attain the maximal learning rates in the industry and the corresponding maximal cost reduction rates. the rest of the paper organized as follows: in section 2 we describe the basics of learning curve methodology and its different applications for energy technologies. section 3 is devoted to a meta-analysis of data on learning rates in wind energy, obtained from building singleand dual-factor learning curve models detailed by countries and technology development periods. it reveals a significant difference in learning rates mainly due to design and efficiency of governments support programs. multiple case studies were performed in section 4 in order to interpret these results. in section 5 we estimate the learning rates that can be achieved in russia according to data on the planned wind power generation facilities and discuss the opportunities for their improvement. section 6 concludes the research and gives some policy applications. 2. methodology understanding of the dynamics of the costs of energy produced with various technologies is an important aspect in decisionmaking in regards to future development of energy systems and state support of renewable energy. throughout the last decades, the theory of learning curves has gained great popularity among economists. this theory allows one to study and forecast economic parameters of various energy technologies, both traditional and new. this approach assumes that technological development is endogenous and dependent on factors such as the size of r&d investments, intensity of stimulating measures, etc., (romer, 1986). the cost of a unit of power is most often considered as a measure of technologic development in energy-related research. a single-factor mathematical model of the basic learning theory in application to energy technologies can be expressed as follows (rubin et al., 2015; williams et al., 2017): sc = a×cc−b, log(sc) = log(a)+(−b)×log(cc), tc a cc dcc a b ccb cc b= × = − − −∫ 0 1 1 , (1) pr = 1−lr=2−b, source: own calculations figure 1: plans and results of tenders for the right to receive state support for wind energy projects in russia in 2013-2017 source: own calculations figure 2: plans for wind installations and their actual implementation in russia in 2015-2017 ratner and khrustalev: learning rates in wind energy: cross-country analysis and policy applications for russia international journal of energy economics and policy | vol 8 • issue 3 • 2018260 where sc – a cost for unit capacity or specific cost, сс – a cumulative capacity installed or produced, tc total cumulative cost of installation or production, pr – the progress ratio, lr – the learning rate a – an unit specific cost when the cumulative capacity reaches the unit value (for instance, 1 mw), b – the coefficient of learning elasticity. in this model, the unit cost is a function of only one argument, which is a cumulative capacity. it reflects all the experience accumulated in the process of technology development. in some studies (rubin et al., 2015), the dependent variable in model (1) represents cumulative energy produced. another wide-spread model in research of energy technology cost dynamics is the two-factor learning curve model, in which the cost depends not just on the cumulative capacity, but on r&d investments as well (rout et al., 2009; yu et al., 2017): sc = a×(cc−b)×(ks−c), pr(lbd) = 1−lr(lbd)=2−b, (2) pr(lbs) = 1−lr(lbs)=2−c, kst = kst−1(1−δ)+r&dt−lag, where, ks – cumulative knowledge a – cost unit (at which cumulative knowledge and capacity reach a volume divisible by 1), b – learning by doing elasticity, clearning by searching elasticity, pr(lbd) – rate of learning by doing pr(lbs) – rate of learning by searching, δ rate of knowledge deprecation lagthe time lag between the start of r&d and the start of commercial knowledge use. note that this form assumes cumulative capacity and knowledge to reach an integer value simultaneously. in practice, however, such a coincidence is rare (miketa and schrattenholzer, 2004). data on investment into r&d of the researched technology (both from state and private sources) is most often used as a proxy variable for ks. a large number of studies aimed at identifying the model (2) based on empirical data (for example, (söderholm and sundqvist, 2007; söderholm and klaassen, 2007; jamasb, 2007) show that r&d investments play a significant role in reducing the cost of generating capacities on all stages of a technology’s development. quite often their influence is considered to be higher than that of learning-by-doing, besides, it’s been proven that these factors aren’t mutually-exclusive (jamasb, 2007). some research, for example, (rubin et al., 2015), give theoretical ground for the critical importance of r&d investments in increasing productivity of technologies in the innovation phase. throughout time and industry progress in new technologies, the importance of r&d investments to a technology’s performance decreases, whereas the importance of learning by doing increases. a graphical representation of this process is shown on figure 3. while researching and forecasting progress for technologies that lack sufficient amounts of empirical data, the so-called “multicomponent” learning curve model (ferioli et al., 2009) is used. this model can be represented as follows: sc a cc i n i i bi= × = −∑ 1 ( ) , where the index i specifies the number of each of n components of the new technologies. the rest of the variables are the same as in (1). use of learning curve models with three or more exogenous variables (factors) is rarely encountered in literature. this can be explained by the difficulties related to identification of the model with limited statistical data. at the same time, it is these unaccounted-for factors that represent a special interest for analyzing international differences in learning rates for the same technologies, and it is those factors that can provide an answer to the issue of effectiveness of national models for new high-tech production. the goal of this paper is, then, to build learning curve models detailed by country and sub-branches of “new energy” industries (researching ground wind generation technologies) based on a meta-analysis of statistical data. the information base for the research are the analytical materials of the international energy agency (iea), the relevant reports from the global wind energy council (gwec) as well as corporate reports from manufacturers of wind energy equipment. 3. data: literature review the largest number of studies devoted to the assessment of learning rates in wind power carried out according to the data of the pioneer countries in the development of this sector of renewable energy: denmark (table 1) and germany (table 2). all source: (rubin et al., 2015) figure 3: importance of learning-by-searching (lbs) and learning-bydoing (lbd) in a technology’s development ratner and khrustalev: learning rates in wind energy: cross-country analysis and policy applications for russia international journal of energy economics and policy | vol 8 • issue 3 • 2018 261 of these studies cover the early stages of technology development (since 1981/1987-2000), as for the later periods there is no data in the literature. limitations caused by lack of data for later periods, on the one hand, do not allow to track the entire period of wind energy development from experimental development to a commercially-successful industry throughout one country. on the other hand, the learning-rate estimates during early periods are free from the influence of technological spillover, standardization and globalization effects (blind et al., 2017; rainville, 2017), so it allows to more precisely identify the learning curve model in the assumption that all explaining variables are exogenous.1 throughout the research period, the cumulative installed capacity for ground wind turbines in denmark grew from 2 mw to 2.4 gw (more than a thousand times), not in the least thanks to danish own production of wind equipment and components. vestas, the dutch wind turbine manufacturer launched in 1980, originally focused on the american market of california, has been on the edge of bankruptcy in 1986 thanks to a significant fall in export, however it was saved by an exponential growth of the domestic market. the stimulating state policies at the time were represented by measures such as tax credits for public cooperatives for construction and use of wind turbines (krohn, 2002), subsidizing wind farm construction 1 electric energy, produced by wind turbines. expenditures from 30% in the early 1980s to 10% in the middle of that decade, implementing bonus rates for wind energy purchases in 1993, returning a part of the wind farm construction investment through the mechanisms of the carbon market in the 1990s (bolinger, 2001). the learning rate estimates in table 1 are significantly scattered and are obtained for different exogenous and endogenous variables. nevertheless, their analysis shows some patterns in technology development: • higher returns from r&d investment during early stages of the technology’s development, which confirms the supposition given in (rubin et al., 2015), • higher elasticity of the net cost for manufacturing wind generating equipment based on the cumulative installed volume compared to the elasticity of their price, which is also affected by market factors, • a higher learning rate for the development of the technology in its entirety, including equipment manufacture and wind farm construction, rather than for its separate parts (e.g., just wind generation equipment manufacturing). a speedy development of the german wind industry started several years after the aforementioned danish example. the first german wind farms that united several wind turbines and had total capacities nearing 400 kw have first appeared in the country table 1: learning rates in wind energy in for denmark time factor depended variable learning rate source 1981-2000 cumulative capacity produced (mw) cost of wind turbine, produced in denmark ($/kw) 8 neij et al., 2003 1981-2000 cumulative capacity produced (mw) production net cost of wind turbine in denmark ($/kw) 14 1981-2000 cumulative capacity installed (mw) cost of wind turbine, installed in denmark ($/kw) 9 1984-1999 r&d investments ($) price of wind energy ($/kwh) 7,8 ibenholt, 2002 1984-1988 r&d investments ($) price of wind energy1 ($/kwh) 11,7 1982-1997 cumulative sales volume of denmark wind turbine producers (mw) cost of wind turbine ($/kw) 4 iea, 2000 1982-1997 cumulative capacity installed (mw) specific investment price ($/kw) 8 mcdonald and schrattenholzer, 2001 table 2: learning rates in wind energy in for germany time factor depended variable learning rate source 1987-2000 cumulative capacity produced (mw) the cost of wind turbine, produced in germany ($/kw) 6 neij et al., 2003 1987-2000 cumulative capacity produced (mw) production net cost of wind turbine ($/kw) 12 1987-2000 cumulative capacity installed (mw) the cost of wind turbine in germany (($/kw) 6 1990-1998 cumulative capacity of wind turbines, sold in germany (mw) specific investment price ($/kw) 8 iea, 2000 1990-1998 cumulative capacity installed (mw) specific investment price ($/kw) 8 mcdonald and schrattenholzer, 2001 1990-1999 cumulative capacity installed (mw) specific investment price ($/kw) 3,1 söderholm and klaassen, 2007 1990-1999 cumulative volume of r&d investments ($) specific investment price ($/kw) 13,2 söderholm and klaassen, 2007 ratner and khrustalev: learning rates in wind energy: cross-country analysis and policy applications for russia international journal of energy economics and policy | vol 8 • issue 3 • 2018262 only in 1986. on the other hand, active wind energy research has started in both state-owned and private research centers back in the end of the 1970s. from 1977 to 1989, over 40 scientific companies and academic organizations have received state grants for development of both small (10 kw) and medium (200–400 kw) wind generators (jacobsson and lauber, 2006). starting in 1986, wind farm demonstrations have become a part of the state science and technology program. from 1983 to 1911, 14 companies have received state financing to produce 124 wind turbines. an important stimulus for the development of small-capacity wind generators on the domestic market was the state program supporting individual entrepreneurs and cooperatives that owned turbines in country areas. ever since the 1980s, german farmers have had an option of taking part in wind energy project investments by providing land for their construction. the sales of electricity to the grid have become an available source of income for the population in less-developed country areas, which helped develop a positive image for the wind energy as an industry with high positive social impact. by 1989, the cumulative installed capacity in the country has reached 20 mw (jacobsson and lauber, 2006). further wind energy development in the country was mostly sustained by bonus rates for wind energy. by the end of year 2000, the cumulative installed capacity in germany has reached a mark of over 8.7 gw. as for wind equipment manufacturing, the first manufacturer of wind turbines in germany, enercon, was created and launched serial production of wind turbines with a capacity of 55 kw in 1984. by 1988, the company has mastered manufacturing turbines with capacities of 80–100 kw, and by 1993 – 500 kw. 2 years after that enercon has released their first 1.5 mw wind turbine, which showed high effectiveness during testing. from 1996 onwards, the company has expanded abroad, purchasing production capacities in brazil and india (mcdonald and schrattenholzer, 2001). by the end of 1990s, the german tech giant siemens has shown interest in wind energy, purchasing the dutch turbine manufacturer, bonus energy a/s, and thus obtaining fairly developed production technologies. estimates of learning rates in german wind energy obtained in various researches are shown in table 2, and are overall similar to ones exhibited in denmark. the only easily notable significant difference is the higher learning rate in wind power engineering (production of wind turbines) than the learning rate in the industry as a whole (installation of generating facilities). in our opinion, the revealed difference can be explained in two ways: (1) by spillover effect of wind turbine production technologies (from denmark to germany) and (2) by the fact that in the early stages of technology development in germany more substantial state support for researches in this field was provided. production technologies in germany had a longer “incubation period” and were introduced already in a more mature state. in addition, germany’s domestic market differs from the danish one in the period under study, in that it has a higher capacity. estimates of the learning rates in wind energy in spain are similar to those for denmark and germany (table 3). however, the development of the industry in this country took place in a slightly different scenario. state support programs for the development of renewable energy in the 1980s (per’86, per’89) were mainly aimed at creating a favorable investment climate in the industry, including foreign direct investment in wind projects. comparatively low local component requirements of wind projects, established by the government, allowed to attract foreign manufacturers of wind power equipment and their state-of-art technologies into the country. this policy, that can be called “technology in exchange for access to the internal market,” proved to be very successful, and in 1994 the danish vestas founded a joint venture with the spanish machinebuilding corporation gamesa. later on gamesa gradually developed this direction of production, making it the main one (zhang, 2012; bean et al., 2017). the required capacity of the domestic market in the country was ensured during this period by constant revision of the strategic goals in the field of energy. in 1991, the spanish government approved a new national energy plan (paee 1991-2000), which included the goal of increasing the proportion of renewable energy in the country’s energy balance from 4.5% to 10% by the year 2000. in 1997, the law on electric power was adopted in spain, which introduced a system of bonus tariffs for renewable energy (jacobsson and lauber, 2006; bean et al., 2017). estimates of the learning rates in wind power in other countries (table 3) are much more scattered and are confirmed by a smaller number of studies performed at different time intervals, which makes comparing them impossible. nevertheless, an additional analysis of the literature on the history of technology development and measures of state support for wind energy in different countries makes it possible to verify their reliability. 4. case studies 4.1. case 1: wind energy development policies in great britain multiple studies about the evolution of government incentives of renewables in great britain demonstrate the lack of holistic policy and instability of measures of state support in 1980-2000 (mitchell and peter, 2004; jordan and matt, 2014; lockwood, 2016). the central electricity generation board (cegb) has started the elaboration of several demonstration projects across the uk for promoting wind energy as early as 1980. nevertheless, the very first real opportunity for renewables’ deployment was created only in 1990 due to the introduction of new electricity act (1989). this act has presented the so-called non-fossil fuel obligation (nffo) and has provided financial support to producers of nuclear and renewable energy at the expense of a significant increase in the tax on fossil fuels (fossil fuel levy). regional energy companies were now obligated to buy renewable and nuclear energy at high prices. funds collected from the tax on fossil fuels were used to eliminate the difference between this overpriced electricity and the average price of electricity in their regions. thanks to this model, the first british commercial wind farm was built in cornwall in 1991. ratner and khrustalev: learning rates in wind energy: cross-country analysis and policy applications for russia international journal of energy economics and policy | vol 8 • issue 3 • 2018 263 the electricity act operated from 1990 to 1998, which explains the high values of learning rates when the price of the electricity is the dependent variable in the model (1). the process of selection of wind generation projects was focused on obtaining the lowest final price, and did not provide any penalties for companies that won the location, but never begun the construction. contracts were also issued in the early stage of the renewable project, even before obtaining a permission for building. many projects with realistic economic parameters did not receive a permission, and some of those that received it turned out to be unprofitable because of the underestimated final electricity price announced in the competitive selection process. in this regard, a significant part of the locations favorable for the development of wind energy remained unused. the results of the nffo program for wind energy development in the uk are evaluated in the literature not only in a positive way. the initial haste in the selection and construction of wind farms led to a negative attitude of the local population to wind energy, which continued throughout the decade. as a result, in 2000 only about 400 mw of wind power were put into operation in the country, which is several times less than in denmark, germany and spain. this capacity of the domestic market was insufficient for the development of its own wind power production in the country, which is still represented only by vwt power ltd., which produces small wind turbines with a vertical axis up to 10 kw. 4.2. case 2: wind energy development policies in usa high estimates of learning rates in wind industry development according to the us data up to 1994 (table 3) can be explained by introduction of public utility regulatory policies act (purpa), as well as by long-term implementation of the federal research program in the field of renewable energy, which has started as early as in 70s and included funding of basic and applied research, as well as demonstration projects in partnership with the private sector. the funding for r&d in renewable energy has increased from $ 1 million/year in 1970 ($2.73 million in 2011 prices) to $ 1.4 billion/year in 1980 ($3.8 billion in 2011 prices). with the introduction of purpa in the period of 1978-1981, favorable market conditions for commercialization of developed technologies were created. grid operators were obligated to purchase renewable energy at a price that would compensate for the costs of producers. the proposed pricing mechanism was quite complex, and its application in practice varied significantly from state to state (mulvaney, 2013). the most attractive conditions for the development of renewable energy in the 80’s were formed in the state of california, which led to a rapid increase in the volume of installations of renewable energy sources (graves et al., 2006). by 1985, california had about 13,000 wind turbines with a total capacity of about 1 gw. also, in the 1980s, measures of state support at the federal level, the so-called investment tax credit (itc), were introduced in the united states, providing tax privileges in the amount which is proportional to investments in wind projects. in the 1990s, public and private investment in the development of renewable energy technologies fell to $ 148 million/year. totally in the period 1973-2003 usa federal government has spent about $14,6 billion. after the purpa era, the period of stagnation (19901997) has started due to the decline in world oil prices and end of government support programs. the attractiveness of investments in renewable energy power has fallen. however, the time period for which the estimates of learning rates are obtained in the study (iea, 2000), almost does not overlap with the period of stagnation table 3: learning rates in wind energy for other countries country time factor depended variable learning rate source united kingdom 1986-2000 cumulative capacity installed (mw) specific investment price ($/kw) 5,4 klaassen et al., 2005 1986-2000 cumulative volume of r&d investments ($) specific investment price ($/kw) 12,6 1991-1999 r&d investments ($) price of electric energy ($/kwh) 25,1 ibenholt, 2002 spain 1986-2000 cumulative capacity installed (mw) specific investment price ($/kw) 5,4 klaassen et al., 2005 1986-2000 cumulative volume of r&d investments ($) specific investment price ($/kw) 12,6 1984-2000 cumulative capacity installed (mw) the cost of capacity installed ($/kw) 9 neij et al., 2003 usa 1985-1994 cumulative volume of generated energy (kwh) price of electric energy ($/kwh) 32 iea, 2000 sweden 1994-2000 cumulative capacity installed (mw) the cost of capacity installed ($/kw) 4 neij et al., 2003 taiwan 2001-2010 cumulative capacity installed (mw) the cost of capacity installed ($/kw) -5,6 trappey et. al., 2013 china 2003-2007 cumulative capacity installed (mw) price of electricity ($/kwh) 4 qiu and anadon, 2012 2002-2012 cumulative capacity installed (mw) levelized cost of electricity ($/kwh) 3.5-4.5 lam et al., 2017 india 2006-2012 cumulative capacity installed (mw) generation cost ($/ kwh) 17.7 partridge, 2013 ratner and khrustalev: learning rates in wind energy: cross-country analysis and policy applications for russia international journal of energy economics and policy | vol 8 • issue 3 • 2018264 and corresponds to the period of the most rapid development of res in the us. the history of wind power engineering in the us also begins in the 1980s. the first american developer of wind parks zond corp. was established in 1980, and originally engaged in the import of wind turbines from europe, the construction and operation of wind farms. gradually developing its own production, by the mid 90’s zond corporation mastered the release of three new generations of wind turbines and won about 10% of the world market (parsons, 1998). however, due to the instability of state support for wind power in the united states in the 1990s, the company’s financial position became so volatile that in 1997 it was absorbed by the us energy concern enron, which in turn was absorbed by general electric in 2002. 4.3. case 3: wind energy development policies in other countries the estimates of the learning rates in sweden (table 3) are slightly lower than in denmark, germany and spain, which can be explained by the insignificant capacity and low growth rates of the domestic market until the middle of the 2000s. the estimates of the leaning rates in taiwan and china were obtained during a period of sharp increases in prices for raw materials and materials used in wind power engineering, which led to a proportional increase in the cost of wind turbines and capital expenditures of wind projects around the world (irena, 2012). nevertheless, as can be seen from table 3, at the same time period, the learning rates in taiwan turned out to be negative, while the learning rates in china remained in the zone of positive values and even quite comparable with the estimates of the european countries’ prosperous period of development of the industry. this difference can be explained by the huge capacity of china’s domestic market and its unprecedented growth rates. whereas in the early 2000s wind energy in china was just emerging, already by 2011 the total capacity of wind generators installed in china was 62.36 gw, and the share of wind power in the country’s constantly growing energy balance reached 1.5%, which led to china as a world leader. in the first half of the 2000s, china’s wind power equipment market was dominated by large multinational companies such as vestas and gamesa, but by the end of the decade, national manufacturers (goldwind, sinovel, united power, mingyang, etc.) had reached such a production scale that they were able to impose strategy of price competition and push the international giants out of the market by offering much cheaper contracts at tenders. however, the lack of full-fledged research programs before the transition to mass production led to several dangerous incidents (explosions of operating turbines, destruction of blades, etc.), partially undermining confidence in the wind power industry in the country (china wind energy outlook, 2012; lam et al., 2017). high assessments of learning rate in india are also obtained during the period of the most rapid growth in the volume of installation of wind generators in this country (india wind energy outlook, 2012). as of march 2012, renewable energy sources accounted for 12.2% of the total energy balance of the country (25 gw from 207.8 gw of total capacity), whereas in 1995 its share was only 2%. it should be mentioned that wind energy makes up about 70% of the capacity of all renewable sources. such a significant growth of the wind energy sector is directly related to the stimulating governmental incentives which were introduced in india in early 2010s. the commercial generation of wind energy began in india in 1986. however, prior to the appearance of the electricity act in 2003 (ea, 2003), there were no specific provisions in india’s regulatory framework that promoted the development of renewable energy sources. despite this shortcoming, the ministry of new and renewable energy sources of india has worked to support the sector through the development of public policy guidelines since 1994. the ea, 2003 defined the main policy directions for the promotion of renewable energy sources by the federal government as well as regional authorities and relevant institutions within their jurisdictions. according to the adopted legislation, the regional electricity regulatory authorities determine the tariffs for all renewable energy projects at the state level, and the state distribution grid companies provide connection of renewable energy sources to the grid (india wind energy outlook, 2012). the most effective measure for promoting renewable energy sources in the ea, 2003 law was the possibility of accelerated depreciation of equipment (up to 80%) in the 1st year of operation of wind farms. in addition to the possibility of accelerated depreciation in india, there are the following benefits for energy producers from alternative sources: • non-taxable income from the sale of energy during the first 10 years of operation of the power plant (for power plants commissioned earlier than march 31, 2013); • a reduced rate of value added tax (vat) (5.5% instead of 12.5%) in some states; • allocation and leasing of forest lands for the development of wind energy projects; • preferential customs duties (5%) for some of the components of wind installations; • development of financial institutions working in the field of renewable energy; • the release of projects for the development of wind energy from payment of excise; • state financing of research and development in the field of renewable energy, assistance in training specialists, product certification, testing and evaluation of renewable resources (wind, solar, geothermal). to a certain extent, the creation of specialized domestic financial institutions, such as the indian renewable energy development agency (ireda), the energy finance corporation and the rural electrification corporation have helped projects on renewable energy to get access to financing. in addition, india has actively used the opportunities provided through the so-called clean development mechanism (cdm) in a frame kyoto protocol. cdm provides additional assistance in financing renewable energy projects in developing countries, while being an effective tool for international due diligence for the projects under consideration of international financial funds such as ifc (international finance corporation). thus, in 2012 indian projects accounted for 18% of all projects submitted for financing under the cdm mechanism. ratner and khrustalev: learning rates in wind energy: cross-country analysis and policy applications for russia international journal of energy economics and policy | vol 8 • issue 3 • 2018 265 5. policy opportunities for russia our multiple case study of learning rates in wind energy achieved in different countries proves the hypothesis that the maximal learning rate in wind energy can be provided by financial support of r&d on the early stage of technological development and by attracting world leaders in manufacturing of wind turbines and other electric generation equipment in the country on the later stages. considering the fact that wind power technologies are currently sufficiently developed, the strategy of attracting large foreign wind turbine manufacturers to russia seems most appropriate. in the original plans for the development of renewable energy, including wind energy, identified in executive order of the government of the russian federation no. 861-r. dated may 28, 2013 indicated fairly high values of the localization index of production (local component requirements) (table 4). but, as it was stated in section 1, these requirements were never satisfied for wind energy projects. in order to determine the degree of compliance of current russian measures of government support with the optimal strategy, we will determine the planned cost decline rates according to official data of the administrator of the trade system of the wholesale power market of the pao unified energy system, selecting construction and commissioning projects of res facilities on a competitive basis as a result of tenders in 2015-2017 (table 5). as one can see, the cost reduction rate in the period 2015-2017 is about 30%. the solution of equation (1) for the case when we use the average planned value of the capital expenditure per 1 kw of installed capacity of the wind-generating facility as the dependent variable, and the planned capacity of the facilities as an independent variable, allows to assess the learning rate as 22%. such a high planned learning rate is unlikely to be achievable even in the context of a decline in the local components requirements and opening domestic market of wind turbines of russia to foreign companies. thus, the planed cost reduction cannot be explained only by learning and exogenous technological change, but by some other factors such as cost indices (for example, steel prices, labor prices etc.) and low ruble rate against foreign currencies. thereby, the current strategy of government support is fundamentally realistic, but the planned reduction in costs for the implementation of wind projects may not be achievable due to various fluctuations in market prices for primary raw materials, energy prices and currency fluctuations. a number of wind projects planned for implementation are in the risk zone according to the terms and conditions for their implementation. considering this conclusion, it is reasonable to correct the expectations on the pace of cost reduction in the near future and increase in the process of competitive selection of projects the significance of non-price factors that affect the success of the project. such factors may be the experience of the applicant company in the implementation of major projects to develop new high-tech industries, the availability and quality of the selected location of the wind park, the degree of support from regional authorities, etc. 6. conclusions using a concept of learning curves as a methodology framework, we evaluated the factors influencing the cost reduction rates for wind energy technologies in different countries at early stages of wind industry development. our results prove that the main direction of state support of wind energy in russia corresponds to best world practices in case of mature technology, which is true for wind electricity generation technology. but the expectations on cost reduction rate are too high and may damage the implementation of selected wind projects. considering this conclusion, it is reasonable to increase the significance of nonprice factors in tender process, such as experience of the applicant company in the implementation of major projects to develop new high-tech industries, the availability and quality of the selected location of the wind park and degree of support from regional authorities. the main limitations of our study are related to the lack of statistic data on wind projects implementation in russia. up to date the only one wind park has put into operation (in january, 2018). therefore, the conclusions and recommendations obtained are relevant only in a short term and policy makers must keep track of cost changes and be ready to reconsider existing strategy of government support in order to achieve highest possible learning rates in wind energy development. references bean, p., blazquez, j., nezamuddin, n. (2017), assessing the cost of renewable energy policy options–a spanish wind case study. renewable energy, 103, 180-186. blind, k., petersen, s.s., riillo, c.a.f. (2017), the impact of standards and regulation on innovation in uncertain markets. research policy, 46, 249-264. table 4: initial local component requirements for government support source/index of localization, % 2014 2015 2016 2017 2018 2019 2020 solar 50 50 70 70 70 70 70 wind 35 55 65 65 65 65 65 small hydro 20 20 45 45 65 65 65 table 5: official data of the administrator of the trade system of the wholesale power market of the pao unified energy system result of tender 2015 2016 2017 number of wind projects selected 1 26 43 mean of the capital expenditures per 1 kw of installed capacity (in rub) 155,000 135,035 105,755 total projects capacity (mw) 35 610 1651 aq1 ratner and khrustalev: learning rates in wind energy: cross-country analysis and policy applications for russia international journal of energy economics and policy | vol 8 • issue 3 • 2018266 bolinger, m. (2001), community wind power ownership schemes in europe and their relevance to the united states. california: environmental energy technologies division, lawrence berkeley national laboratory. china wind energy outlook. (2012), chinese wind energy association. available from: http://www.gwec.net/publications/country-reports/ china-wind-energy-outlook-2012/. electricity act, 2003. government of india. ministry of power. available from: https://powermin.nic.in/en/content/electricity-act-2003#. ferioli, f., schoots, k., zwaan, b.c.c. (2009), use and limitations of learning curves for energy technology policy: a component-learning hypothesis. energy policy, 37(7), 2525-2535. graves, f., hanser, p., basheda, g. (2006), purpa: making the sequel better than the original. washington, dc: eei (edison electric institute). ibenholt, k. (2002), explaining learning curves for wind power. energy policy, 30, 1181-1189. iea. (2000), experience curves for energy technology policy. paris, france: international energy agency. india wind energy outlook. (2012), available from: http://www.gwec.net/ wp-content/uploads/2012/11/india-wind-energy-outlook-2012.pdf. irena. (2012), renewable energy technologies: cost analysis series. abu dhabi: wind power. irena. p64. jacobsson, s., lauber, v. (2006), the politics and policy of energy system transformation—explaining the german diffusion of renewable energy technology. energy policy, 34(3), 256-276. jamasb, t. (2007), technical change theory and learning curves: patterns of progress in electricity generation technologies. energy journal, 28, 51-72. jordan, a., matt, e. (2014), designing policies that intentionally stick: policy feedback in a changing climate. policy science, 47, 227-247. klaassen, g., miketa, a., larsen, k., sundqvist, t. (2005), the impact of r&d on innovation for wind energy in denmark, germany and the united kingdom. ecology economics, 54, 227-240. kozlova, m., mikael, c. (2016), modeling the effects of the new russian capacity mechanism on renewable energy investments. energy policy, 95, 350-360. krohn, s. (2002), wind energy policy in denmark: 25 years of successwhat now? copenhagen: dwia (danish wind industry association). lockwood, m. (2016), the uk’s levy control framework for renewable electricity support: effects and significance. energy policy, 97, 193-201. mcdonald, a., schrattenholzer, l. (2001), learning rates for energy technologies. energy policy, 29, 255-261. miketa, a., schrattenholzer, l. (2004), experiments with a methodology to model the role of r&d expenditures in energy technology learning processes; first results. energy policy, 4(32), 1679-1692. mitchell, c., peter, c. (2004), renewable energy policy in the uk 19902003. energy policy, 32(17), 1935-1947. neij, l., andersen, p.d., durstewitz, m., helby, p., hoppe-kilpper, m., morthorst, p. (2003), experience curves: a tool for energy policy assessment. lund, sweden: environmental and energy systems studies, lund university. parsons, b. (1998), grid-connected wind energy technology: progress and prospects. north american conference of the international association of energy economists. qiu, y., anadon, l.d. (2012), the price of wind power in china during its expansion: technology adoption, learning-by-doing, economies of scale, and manufacturing localization. energy economics, 34, 772-785. rainville, a. (2017), standards in green public procurement–a framework to enhance innovation. journal of cleaner production, 167, 10291037. ratner, s.v., nizhegorodtsev, r.m. (2017), analysis of renewable energy projects’ implementation in russia. thermal engineering, 64(6), 429-436. romer, p.m. (1986), increasing returns and long-run growth. journal of political economy, 94(5), 1002-1037. rout, u.k., blesl, m., fahl, u., emme, u., voß, a. (2009), uncertainty in the learning rates of energy technologies: an experiment in a global multi-regional energy system model. energy policy, 37, 4927-4942. rubin, e.s., azevedo, i.m.l., jaramillo, p., yeh, s. (2015), a review of learning rates for electricity supply technologies. energy policy, 86, 198-218. smeets, n. (2017), similar goals, divergent motives. the enabling and constraining factors of russia’s capacity-based renewable energy support scheme. energy policy, 101, 138-149. söderholm, p., klaassen, g. (2007), wind power in europe: a simultaneous innovation–diffusion model. environmental resources economy, 36, 163-190. söderholm, p., sundqvist, t. (2007), empirical challenges in the use of learning curves for assessing the economic prospects of renewable energy technologies. renewable energy, 32, 2559-2578. trappey, a.j.c., trappey, c.v., liu, p.h.y., lin, l.c., ou, j.j.r. (2013), a hierarchical cost learning model for developing wind energy infrastructures. international journal of production economy, 146, 386-391. williams, e., hittinger, e., carvalho, r., williams, r. (2017), wind power costs expected to decrease due to technological progress. energy policy, 106, 427-435. yeh, s., rubin, e.s. (2012), a review of uncertainties in technology experience curves. energy economy, 34, 762-771. yu, y., li, h., che, y., zheng, q. (2017), the price evolution of wind turbines in china: a study based on the modified multi-factor learning curve. renewable energy, 103, 522-536. zhang, s. (2012), international competitiveness of china’s wind turbine manufacturing industry and implications for future development. renewable and sustainable energy reviews, 16(6), 3903-3909. . international journal of energy economics and policy | vol 10 • issue 2 • 2020 71 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(2), 71-80. particle swarm optimization for micro-grid power management and load scheduling abdelfettah kerboua1*, fouad boukli-hacene1, khaldoon a. mourad2 1department of second cycle, high school in applied sciences of tlemcen, bp 165 rp bel horizon, 13000 tlemcen, algeria, 2the center for sustainable visions www.c4sv.com and lund university, 22100 lund, sweden. *email: ab.kerboua@gmail.com received: 15 august 2019 accepted: 09 december 2019 doi: https://doi.org/10.32479/ijeep.8568 abstract a smart power management strategy is needed to economically manage local production and consumption while maintaining the balance between supply and demand. finding the best-distributed generators’ set-points and the best city demand scheduling can lead to moderate and judicious use out of critical moments without compromising smart city residents’ comfort. this paper aimed at applying the particle swarm optimization (pso) to minimize the operating cost of the consumed energy in a smart city supplied by a micro-grid. two pso algorithms were developed in two steps to find the optimal operating set-points. the first pso algorithm led to the optimal set-points powers of all micro-grid generators that can satisfy the non-shiftable needs of the smart city demand with a low operating cost. while the second pso algorithm aimed at scheduling the shiftable city demand in order to avoid peak hours when the operating cost is high. the results showed that the operating costs during the day were remarkably reduced by using optimal distributed generators’ set-points and scheduling shiftable loads out of peaks hours. to conclude, the main advantages of the proposed methodology are the improvement in the local energy efficiency of the micro-grid and the reduction in the energy consumption costs. keywords: particle swarm optimization algorithm, renewable energy, power management, operating cost jel classifications: c61, c62, q21, q42 1. introduction renewable energies are a privileged vector of the fight against global warming. in addition to being environmentally friendly, they are inexhaustible and available. electricity generation from renewable energy sources is stochastic and partially predictable, which is considered a challenge that is added to those of consumption to which grid operators are already facing (dharavath and raglend, 2019). the efficient use of renewable energy sources can be achieved through the integration of solar and wind technologies, which is more flexible between other renewable energy sources. using decentralized generation resources, particularly renewable resources such as wind and solar energy are the better options for reducing greenhouse gas emissions and energy transport losses (banerji et al., 2013; mariam et al., 2016). micro-grids are introduced as a new concept in the operation and planning of modern electrical systems. they rely primarily on renewable resources and smart grid infrastructure. they are able to exchange energy with the main grid or with other micro-grids. in addition, the use of decentralized generation resources, especially renewable resources such as wind and solar energy, highly reduces greenhouse gas emissions and losses due to the transport of electric energy (banerji et al., 2013, mariam et al., 2016). a micro-grid is a small-scale electric grid designed to improve the reliability and resilience of electrical grids at a better operating cost and a high quality to a reduced number of consumers. however, microgrids still face significant legal and regulatory uncertainties grids (hirsch et al., 2018). a micro-grid, whether connected to the main grid or not, is made up of small interconnected local power plants of different types of energy resources, consumer this journal is licensed under a creative commons attribution 4.0 international license kerboua, et al.: particle swarm optimization for micro-grid power management and load scheduling international journal of energy economics and policy | vol 10 • issue 2 • 202072 installations, storage systems and management centre for controlling and managing the flow of the electric energy. it is intended for urban and rural communities, islands and isolated activities that have limited or no access to the main electricity grid (banerji et al., 2013). whenever the local electricity generation is not sufficient, communities import the lack from outside power plants or of the main grid. traditionally, micro-grids used conventional fuel generators (micro-turbines [mts]), but recently, involving more renewable energies is the target for sustainability. these latter are highly adaptable to micro-grids as they are widely available and can be exploited by any community in addition, they have minimal impact on the environment (banerji et al., 2013; karger and hennings, 2009). koltsaklis et al. (2018) developed a mathematical model for the optimal design and operational scheduling of energy microgrids taking into account the technical, environmental and economic constraints. different architecture and micro-grid control designs were proposed by many authors. karger and hennings (2009), for example, discussed the effectiveness of the micro-grid connected to a powerful electric distribution and listed a number of obstacles, so that more radical changes could be made to the regulatory and institutional framework for the development of the micro-grids. katiraei et al. (2008) provided an overview of the modes of control of existing micro-grids and the importance of power and energy management strategies and describe potential approaches to market participation, by which they highlighted the main differences between micro-grids and powerful grids. dynamic electricity pricing involves the dynamic change of the energy price over short time steps to track electricity generating costs, depending on the time of a day (lund et al., 2012). these costs are higher during peak consumption according to the type of the used energy. distributed generators based on renewable energies can fluctuate and aggravate the power balance as they can increase electricity production. lund et al. (2012) highlighted some recent developments in the functioning of the danish electricity market. this article shows how such small installations can provide valuable stabilization of the grid for additional investment and operating low costs. gomes et al. (2016) discussed the coordinated exchange of wind and photovoltaic (pv) energy to support management decisions to mitigate risks from wind and solar variability, electricity prices and penalties deficit or surplus production. some research works studied multi-objective energy management in a micro-grid (motevasel and seifi, 2014; aghajani and ghadimi, 2018; wu et al., 2019). motevasel and seifi (2014), for example, proposed an expert energy management system for optimal operation of mts twinned with renewable energy generators and a system for storing energy in a micro-grid connected to the electric system. the main objective of the proposed system is to find the optimal set-points for generators and storage batteries, so as to simultaneously minimize the total operating cost and gas emissions of mts. the authors proposed a modified algorithm for bee colony optimization to solve the multi-objective problem. in order to show the performance of this optimization algorithm, the average and standard deviation indices are evaluated, and the results are compared to other optimization algorithms such as the genetic algorithm and the particle swarm optimization (pso). whei-min et al. (2016) presented a strategy for energy management of micro-grids constituting renewable energy sources and storage systems connected to the main grid. wind power generation and solar power generation are integrated into the distribution electric system. the optimal management for that mixed energy generation has been formulated taking into account the scheduling the charge/discharge of storage systems. according to the time of a day and the technical constraints of the operation, the so-called bee colony optimization is developed to solve the daily economic dispatching set-points of all micro-grid resources. logenthiran et al. (2012) presented load-side management strategy based on intelligent load profile shifting technique with a large number of devices of several types. the hourly charge shifting technique during a day proposed in this paper is mathematically formulated as a minimization problem. an evolutionary heuristic algorithm has been developed to solve this problem while reducing load peaks in a smart grid. logenthiran et al. (2015) discussed a new approach to profile shifting for demand management in the smart grid. this approach optimized the profiles of domestic, commercial and industrial consumption curves using the particle swarm technique. the algorithm proposed in this article minimized user consumption costs while taking into account their individual preferences for loads by defining priorities and preferred time intervals for load scheduling. in the work of abid et al. (2017), an energy management strategy was proposed to minimize peaks of energy consumption and the operating costs of micro-grids, by which smart appliances of each house in the city were scheduled using the algorithm for binary pso. for the same purpose and with a classification of the type of appliance consumption in the heaters, ventilation, air conditioning and lighting were controlled by fuzzy logic and the rest of the load demand is managed by heuristic optimization techniques (khalid et al., 2019; koltsaklis et al., 2018). the efficient power management control for microgrids with energy storage should increase the reliability and resiliency of the microgrid based on the distributed energy resources (worku et al., 2019). energy management optimization problems in a future wherein an interaction with micro-grids have to be accounted for van-ackooij et al. (2018). energy demand side management (dsm) can be optimized to improve system performance (noor et al., 2018). shayeghi et al. (2019) surveyed the microgrid energy management considering flexible energy sources based on based on the kind of the reserve system being used, including non-renewable, energy storage systems (ess), dsm and hybrid systems. several researchers have used the pso algorithm in micro-grids management of generation or demand side. so far, all these works deal either with only power resource management (production side) or the consumption shifting and scheduling kerboua, et al.: particle swarm optimization for micro-grid power management and load scheduling international journal of energy economics and policy | vol 10 • issue 2 • 2020 73 (demand side) to achieve the best operating cost. however, our contribution in this paper is to use both methods in order to better economically manage local productions and consumption while maintaining the balance between supply and demand. two pso algorithms are developed to meet the best operating cost. the first algorithm develops a strategy of optimal management of the energies provided by each energy source used in order to satisfy the demand of the community with a minimum operating cost. the second pso algorithm manages the scheduling of the power dispatching of load during the day to avoid consumption peaks. managing the demand for electrical energy is a delicate task. however, effective scheduling of smart home appliances improves the energy efficiency of the micro-grid and significantly reduces the cost of energy consumption. the rest of the paper is organized as the following: section 2 introduces methods for pso micro-grid power management and load scheduling after giving the architecture and data of the used micro-grid. numerical results followed by discussions are provided in section 3. finally, concluding remarks and future directions are given in section 4. 2. materials and methods current micro-grids are designed to promote better different renewable technologies. they integrate pv generators and several other generators such as wind turbines (wts), mts, hydroelectric systems, storage systems and sometimes the main grid. meeting the electricity needs of a community is a delicate task because of the random nature of the different renewable energy sources used and consumption. these needs can be met through distributed generation provided by renewable energy systems, in other cases, mts and the main grid can be used (banerji et al., 2013). 2.1. architecture and data of the used micro-grid the energy system taken in our application is composed of three sources, two of which are renewable and the third is chosen as a conventional generator. renewable powers of pv panels and wts distributed throughout the community include powers of positive energy homes. microturbines (mt) (diesel or gas) are used to fill at any time the lack between the power demand and the power produced by renewable sources (mariam et al., 2016). since the last is fluctuating and the production capacity of the conventional groups is limited, it is possible to include an ess in an isolated site or to be connected to the main grid. in this work, we are interested in a hybrid system connected to the electrical grid, which does not need any ess and will guarantee the distribution of energy even in case of lack of renewable energy sources (karger and hennings, 2009). figure 1 shows the powers flow in the micro-grid. distributed generators based on renewable sources are connected to the dc bus. micro-turbines are connected to the ac bus. the controlled dc-dc converter used for linking pv panels to the dc bus that converts the receiving variable dc voltage in the input to a constant boosted dc output voltage. whereas the controlled ac-dc converter used for linking wt generators to the dc bus that converts the receiving variable ac voltage in the input to a constant dc output. the arrows indicate the direction of the energy flow. single-headed arrows indicate that energy can only flow in one direction (corresponding to production or consumption). likewise, double-headed arrows indicate that energy can flow in both directions. this corresponds to the case where distributed generators cannot satisfy the electricity needs of the community, so the main grid is called. however, in case of excess production, the surplus is returned to the grid without disturbing its operation. the advantage of this architecture is that it does not need any ess (batteries + charge and discharge converters) which makes it more economical. table 1 shows hourly energy prices and maximum energy capacity of each sources injecting into the micro-grid during a day. in addition, we provide hourly consumption metering micro-grid load. these data are taken in a similar profile to that used by (motevasel and seifi, 2014). the variation range of pv and wt generated powers is between zero (in the absence of renewable sources) and the maximum value specified for each source at any moment “t”. however, the power of the mts is limited between a minimum and a maximum. figure 1: architecture of the used micro-grid kerboua, et al.: particle swarm optimization for micro-grid power management and load scheduling international journal of energy economics and policy | vol 10 • issue 2 • 202074 a minimum of 6 kw to don’t stop the turbine and a maximum of 30 kw corresponding to its rated power. the balance between powers of distributed generators and total load power of the community must be insured at any moment “t”. those equality and inequalities constraints are formulated as follow: ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 0 t t , 0 t t , 6kw t 30kw t t t t max max pv pv wt wt mt pv wt mt load p p p p p p p p p  ≤ ≤ ≤ ≤  ≤ ≤ + +  = (1) 2.2. pso theory pso is an evolutionary computation technique based on the imitation of the social behaviour of swarm species, such as a group of birds or a group of fish. two characters must be taken into account. by analogy with evolutionary computation paradigms, a swarm is similar to a population, whereas a particle is similar to an individual (engelbrecht, 2007). particles evolve in a multidimensional research space, where the position of each particle is adjusted according to its own experience and that of its neighbours. each particle must memorize its best personal position by which it has already passed, and it tends to return to that position. it represents “the best personal position” found since the beginning of the evolution towards the objective. in addition, each particle is informed of the best-known position within its neighbourhood or global swarm and they tend to move towards that point. it represents “the best local or global position” found by all the particles of the swarm since the beginning of its evolution towards the objective (abid et al., 2017; engelbrecht, 2007). the current position vector “x = [x1x2 … xi … xn]t” at the moment “k + 1” is adjusted by adding to its former position at the moment “k”, a velocity vector “vi(k + 1)”. the latter is the weighted sum of its former value, the cognitive component and the global or local social component. we are interested in this work in the method using the global social component. the cognitive component represents the specific experience of each particle and designed by the best personal position “yi(k)”. the social component is the experience of the particle represented by the best global position “ŷ(k)” (engelbrecht, 2007). ( ) ( ) ( ) ( ) ( ) [ ] i i i i 0 i 1 1 i i 2 2 i x k 1 x k v k 1 v k 1 c v k c r y (k) x (k) c r y(k) x (k)ˆ  + = + +  + = + −  + −    (2) where “c0” is a positive constant of velocity weighting “c1” is a positive constant of so-called acceleration weighting of the cognitive component “c2” is a positive constant of so-called acceleration weighting of the social component “r1” and “r2” are random values in the range [0-1] to bring a stochastic character to the algorithm. the best personal position, “yi”, associated to the particle “i” is the best position the particle has visited since the beginning of evolution. considering the minimization function “f(x)”, the best personal position at the moment, “k+1”, is calculated as follows (engelbrecht, 2007): ( ) ( ) ( )( ) ( )( ) ( ) ( ) ( ) i i i i i i i y k if x k 1 x k y k 1 x k 1 if x (k 1) x (k) f f f f  + ≥ + =  + + < (3) the best global position “ŷ(k),” at the moment “k”, is defined as follows: table 1: hourly data of micro-grid components hour pv (€/kwh) wt (€/kwh) mt (€/kwh) grid (€/kwh) pv pmax (kwh) wt pmax (kwh) pload (kwh) 01h00 0 0.021 0.0823 0.033 0 64.04 52 02h00 0 0.017 0.0823 0.027 0 64.32 50 03h00 0 0.0125 0.0831 0.020 0 64.64 50 04h00 0 0.011 0.0831 0.017 0 64.68 51 05h00 0 0.051 0.0838 0.017 0 70.72 56 06h00 0 0.085 0.0838 0.029 0 64.68 63 07h00 0 0.091 0.0846 0.033 0 58.92 70 08h00 0.0646 0.110 0.0854 0.054 0.4 58.24 75 09h00 0.0654 0.140 0.0862 0.215 2.36 58.6 76 10h00 0.0662 0.143 0.0862 0.572 7.92 52.64 80 11h00 0.0669 0.150 0.0892 0.572 31 46.68 78 12h00 0.0677 0.155 0.09 0.572 39.2 40.6 74 13h00 0.0662 0.137 0.0885 0.215 42.6 46.68 72 14h00 0.0654 0.135 0.0885 0.572 38.8 40.6 72 15h00 0.0646 0.132 0.0885 0.286 32.48 59 76 16h00 0.0638 0.114 0.09 0.279 19.8 64.84 80 17h00 0.0654 0.110 0.0908 0.086 4.4 64.6 85 18h00 0.0662 0.0925 0.0915 0.059 0.4 76.52 88 19h00 0 0.091 0.0908 0.050 0 70.12 90 20h00 0 0.083 0.0885 0.061 0 75.8 87 21h00 0 0.033 0.0862 0.181 0 76.16 78 22h00 0 0.025 0.0846 0.077 0 76.44 71 23h00 0 0.021 0.0838 0.043 0 79.72 65 24h00 0 0.017 0.0831 0.037 0 76.6 56 kerboua, et al.: particle swarm optimization for micro-grid power management and load scheduling international journal of energy economics and policy | vol 10 • issue 2 • 2020 75 ( ) ( ) ( ){ } ( )( ) ( )( ) ( )( ){ } 1 n 1 n y k y k , , y k / f y k min f y k , y ˆ ˆ , f k ∈ … = … (4) where “n” is the total number of particles in the swarm. pso has been successfully applied to solve a number of problems in research and application areas including problems of optimization of functions (logenthiran et al., 2015; abid et al., 2017), selection and classification (too, 2019), wireless sensor networks (cheng et al., 2018) and learning of neural networks (li, 2018) etc. 2.3. pso management algorithm for generators side the use of hybrid systems combining these renewable energy sources with a conventional source and/or the main grid distribution is considered by all as a future solution, as it is efficient and reliable. the pso optimization technique could manage in real time the distribution of the power instructions for each type figure 2: particle swarm optimization flowchart for distributed energies management kerboua, et al.: particle swarm optimization for micro-grid power management and load scheduling international journal of energy economics and policy | vol 10 • issue 2 • 202076 of source. the objective function is developed so that the instant power demanded by the community is ensured at all times with the minimum operating cost. the flowchart of the pso optimization used is represented on figure 2. the choice of the objective function to define the best personal position and the global position represents the most relevant action to be performed. several functions have already been used (motevasel and seifi, 2014; whei-min et al., 2016; quoc-tuan et al., 2016). however, in the objective function, we use in this paper depends on the architecture of the micro-grid used and costs of energy consumption from locally distributed generators taking into account the production costs, the start-up of mts and the purchase cost on the main grid as given by the following equation (motevasel and seifi, 2014): ( ) ( ) ( ) ( ) ( ) ( ) ( ) i g i gi gi om t n gi i it 1 i 1 grid grid u k p k b k k min s u k u k 1 p k .b k = =    +       + − −     +    ∑ ∑ (5) where; ng: number of distributed generators types. bgi (k): energy unit price insured by the i eme generator at moment “k”. pgi (k): power generated by the i eme generator at moment “k”. sgi: start-up or shutdown cost of i eme generator. ui (k): operation mode of the i eme generator (on or off). k om i : factor dependent on the maintenance fee. pgrid (k): the power inter-changed with the main grid at the moment “k”. bgrid (k): purchase cost of the main grid at the moment “k”. 2.4. pso scheduling algorithm for demand side high tariffs during consumption peaks and, conversely, cheaper operating cost outside critical moments are willing and able to reduce consumption. they even commit to reducing industrial activities for a few hours of the day. reducing consumption to minimize peaks can be achieved by reporting some activities outside these peak times without compromising the comfort of the community and without disrupting industrial activities too (khalid et al., 2019; zhou et al., 2016). effective and reliable energy demand scheduling by the community requires accurate knowledge of load models to estimate the impact of load management strategies. the residential community is assumed to be a load of smart homes that have fixed-line and other shiftable home appliances. these advanced devices are now commonplace in the internet of things revolution, with a multitude of accessories and appliances connected to the internet. the home energy management system is an important element of the smart grid that allows residential customers to run on-demand programs independently. these smart houses receive instantaneous operating cost from the micro-grid manager in advance, thus delaying the launch of household appliances that can be carried out during off-peak hours (zhou et al., 2016; celik et al., 2017). in fact, it is difficult to determine optimal operating points of a storage system in the real-time management of a converter-based microgrid, which helps in saving the costs and reducing energy waste (hossain et al., 2019). different algorithms are used and compared to schedule loads of a smart city (logenthiran et al., 2012; abid et al., 2017; li, 2018; celik et al., 2017). the aim is to reduce the energy bill by taking into account the consumption and production data, but also the current pricing policies and any operating constraints imposed by the micro-grid manager. the pso technique allows us to manage during a day the scheduling of shifted tasks for each device. the objective function is developed so that the amount of electrical energy required by the community of a day is provided with the minimum possible cost. 3. results and discussions the computation in pso is very simple and without overlapping. during the evolution between several positions, only the most optimist particle can transmit information into the other particles, and the speed of the converging is very fast. 3.1. the classic pso power management in this section, we apply pso algorithm for the resource power management (production side). it is a question of finding power set-points for each source at each hour in order to minimize the objective function. during a day with no maintenance, no start-up or shutdown of mt, the objective function will be reduced as follows: min t t i gi gi i n u k p k b k g = =∑ ∑ ( ) ( ) ( ) 1 1 (6) table 2: day distribution of shiftable and non-shiftable load powers and available distributed generators’ powers hour pv power wt power mt power non shiftable shiftable load power 1 0 64.04 30 47 5 2 0 64.32 30 40 10 3 0 64.64 30 45 5 4 0 64.68 30 49 2 5 0 70.72 30 46 10 6 0 64.68 30 55 8 7 0 58.92 30 60 10 8 0.4 58.24 30 63 12 9 2.36 58.6 30 61 15 10 7.92 52.64 30 60 20 11 31 46.68 30 53 25 12 39.2 40.6 30 49 25 13 42.6 46.68 30 52 20 14 38.8 40.6 30 62 10 15 32.48 59 30 61 15 16 19.8 64.84 30 65 15 17 4.4 64.6 30 60 25 18 0.4 76.52 30 65 23 19 0 70.12 30 80 10 20 0 75.8 30 72 15 21 0 76.16 30 68 10 22 0 76.44 30 63 8 23 0 79.72 30 60 5 24 0 76.6 30 48 8 kerboua, et al.: particle swarm optimization for micro-grid power management and load scheduling international journal of energy economics and policy | vol 10 • issue 2 • 2020 77 obtained by applying the classic pso algorithm after a mean of 50 to 70 iterations. we find that a good balance is insured at any time between the power of distributed generation and demand (total load power) of the community. as well as the hourly dispatching powers are managed very economically so that the set-point of the cheapest source is the most important. it is clear that the power of the pv generator is fully exploited. this amounts to the encouraging energy unit price of this resource. micro-turbines are present at all times (no shutdowns of mt) and serve as a reference for signal quality (well-defined voltage and frequency). the wind resource is more efficient and more regular than the pv resource but its unit price increases during peak consumption. in the absence of the pv resource, mts play a major role in constantly bridging the lack between the hourly load demand and the generated system powers. figure 3 shows the variation curves of hourly unit prices of distributed generators during the day and the profile of the achieved operating cost. by this dispatching of distributed generators set-points, the day energy bill is found to be 123.41 €. likewise, the curve of variation of the energy operating cost is of average profile and remarkably reduced during peaks of consumption (hatched areas). when the unit price of wind energy has increased, the other cheaper (mt) is used to achieve the best operating cost but detrimental to clean energy. we can remark that if the community decreases consumption during peaks by delaying the shiftable part outside these critical moments, it can lead to an even better cost in addition to significantly improving the use of renewable energy generators and better energy efficiency of the microgrid. 3.2. the proposed pso power management our proposed pso power management aims to achieve improvements could be brought by the last remark. this technique is intended for residential communities with a multitude of home accessories table 3: dispatching of hourly optimal powers’ set-points for each source and their unit prices hour non shiftable shiftable pv set-point wt set-point mt set-point 1 47 5 0 46 6 2 40 10 0 44 6 3 45 5 0 44 6 4 49 2 0 45 6 5 46 10 0 50 6 6 55 8 0 33 30 7 60 10 0 40 30 8 63 12 0.4 44.6 30 9 61 15 2.36 43.64 30 10 60 20 7.92 42.08 30 11 53 25 31 17 30 12 49 25 39.2 4.8 30 13 52 20 42.6 0 29.4 14 62 10 38.8 3.2 30 15 61 15 32.48 13.52 30 16 65 15 19.8 30.2 30 17 60 25 4.4 50.6 30 18 65 23 0.4 57.6 30 19 80 10 0 60 30 20 72 15 0 75.8 11.2 21 68 10 0 72 6 22 63 8 0 65 6 23 60 5 0 59 6 24 48 8 0 50 6 figure 3: day profile unit prices of distributed generators and the obtained operating cost to better present the situation, we first present the hourly distribution of shiftable and non-shiftable parts of the needed power (load) and available powers of distributed generators along the day (table 2). the classic pso power management algorithm should calculate necessary hourly set-points for each distributed generator of the micro-grid in order to satisfy the hourly total load power (including the shiftable part and the non-shiftable part). table 3 shows results kerboua, et al.: particle swarm optimization for micro-grid power management and load scheduling international journal of energy economics and policy | vol 10 • issue 2 • 202078 and home appliances connected to the internet. the home energy management system is an important element of the smart grid that allows residential customers to run on-demand programs independently. therefore, it helps in minimizing the electricity bill by scheduling the household appliances and ess in response to the dynamic pricing of electricity market (ahmad et al., 2017). this allows shifting and delaying the launch of those appliances out of peak hours so that avoiding critical moments. two algorithms might be applied in succession. the first pso algorithm is applied to calculate necessary hourly set-points for each distributed generator of the micro-grid in order to satisfy only the hourly non-shiftable part of the load power. however, the second pso algorithm is applied to calculate the rest hourly set-points for each distributed generator in order to satisfy only the daily shiftable load power. keeping a balance between powers of distributed generators and shiftable needs of the smart city is keeping the energy scheduled during the day equal to the daily energy required by shiftable power of the city. so, we get energy dispatching of scheduling load during the day so that avoiding consumption peaks. to achieve the goal of the first step, we redo the classic pso algorithm to manage only non-shiftable load powers. it is a question of finding power set-points for each source at each hour in order to minimize the same objective function. figure 4 shows the distribution of the hourly optimal powers’ set-points for each distributed generator taking into account only non-shiftable load powers. by this dispatching of distributed generators, the day energy bill is found to be 94.59 €. same remarks could be seen on this figure like the balance insured at any time between powers of distributed generators and non-shiftable loads of the community. as well as the hourly dispatching powers are managed very economically so that the set-point of the cheapest source is the most important. now we have to proceed to the second step, which concerns the power scheduling of the shiftable part of loads. the main purpose of the objective function is to satisfy the demand of the community along the day in a better economic way. the pso algorithm must lead to moderate and judicious use and a marked difference in the bill of consumption of the day. to better present the situation, we first present the hourly distribution of shiftable parts of the needed power and available powers of distributed generators remained after satisfying non-shiftable parts along the day (figure 5). it is clear that nothing left of the power of the pv generator (fully exploited in the first step). this amounts to the encouraging unit price of this resource. figure 4: hourly dispatching set-points of distributed generators for non-shiftable load and their unit prices figure 5: day distribution of shiftable loads power and available distributed generators’ power remained after satisfying non-shiftable parts figure 6: day profile of pso scheduled power set-points of shiftable load and energy unit prices kerboua, et al.: particle swarm optimization for micro-grid power management and load scheduling international journal of energy economics and policy | vol 10 • issue 2 • 2020 79 the second pso technique allows us to manage the scheduling of shifted tasks for each device along the day. the objective function can’t be reduced as it’s done previously, but it is developed so that the amount of electrical energy required by the community of a day is provided with the minimum possible cost. this means that the cost of the day energy of shiftable home appliances is to be minimized. the flowchart of the pso optimization used is almost the same as the first one. the difference lies in the vector of the positions. this vector should evolve in order to find set-points of each distributed generator throughout the day (so its length equals to 24 × ng) and to ensure the scheduled energy of shiftable loads during that day. figure 6 shows the profile of pso scheduled load demand and energy consumed unit price during a day. this shows the repartition of the shiftable load before and after scheduling by the second pso algorithm. it’s clear how peak hours are avoided without affecting the needs of customers along the day. all home appliances had to be launched at the time out of hatched areas are rescheduled to be launched during the hatched areas. the energy consumed during the day before and after scheduling remains exactly unchanged at 1695 kwh which means that the comfort of the community is not compromised. we remark that the profile of the shiftable power load is significantly changed according to moments where the distributed generator powers price is relatively low (hatched areas). it’s clear that the shiftable power load on the highest price moments are moved to be scheduled on lowest price moments. those moments are characterized by the lowest price of wind generator so more of renewable energy would be exploited which means that less mts energy used. energy bill obtained for the total load (including shiftable and non-shiftable parts) is found to be 106.87 €. comparing this bill with the other obtained by classic pso optimization and the day profile of operating cost by using both methods (figures 3 and 7), we notice the importance of our proposed pso optimization technique. it’s clear that load shifting and figure 7: day profile of the obtained operating cost using the classic particle swarm optimization management and using the proposed particle swarm optimization management scheduling lead to a moderate and a judicious use out of critical moments without compromising smart city residents’ comfort. moreover, this technique gives possibilities to enjoy the most of renewable generation and to reduce greenhouse gas emissions when using mts. 4. conclusions to summarise, the paper proses a management strategy using pso for optimal operation of distributed generators of the micro-grid and an optimal scheduling energy consumption of the smart city. for this purpose, two pso algorithms are applied in two steps. the first algorithm seeks for the best set-points of distributed generators in such a way that the hourly non-shiftable power demanded by the community is ensured with the lowest cost. the obtained curve of variation of the energy operating cost during the day is of an average profile and remarkably reduced during peaks of the consumption. at this stage, the micro-grid is managed to take into account variable pricing every hour of the day while completely omitting peaks of demand and the capacity of renewable production. the second step allows enhancing the autonomy and reliability of the micro-grid while further minimizing the daily energy bill. the use of the second optimization algorithm makes it possible by scheduling shiftable loads of the smart city without affecting the comfort of residents. comparing the obtained classic pso strategy results by the proposed pso power management strategy results shows a reduction in the final electricity bills and a noticeable improvement of renewable generation. further avenues of research will include the multi-objective optimization such a way, in addition to the operation cost, the greenhouse gas emissions of fossil fuel generators are simultaneously minimized. 5. acknowledgments authors may acknowledge the centre for middle eastern studies at lund university for funding the publication of this paper in an open access journal through mecw project. kerboua, et al.: particle swarm optimization for micro-grid power management and load scheduling international journal of energy economics and policy | vol 10 • issue 2 • 202080 references abid, s., zafar, a., khalid, r., javaid, s., qasim, u., khan, z.a., javaid, n. (2017), managing energy in smart homes using binary particle swarm optimization. conference on complex, intelligent, and software intensive systems. italy: torino. p. 189-196. aghajani, g., ghadimi, n. (2018), multi-objective energy management in a micro-grid. energy reports, 4, 218-225. ahmad, a., khan, a., javaid, n., hussain, h.m., abdul, w., almogren, a., alamri, a., niaz, i.a. (2017), an optimized home energy management system with integrated renewable energy and storage resources. energies, 10, 549. banerji, a., sen, d., bera, a.k., ray, d., paul, d., bhakat, a., biswas, s.k. (2013), microgrid: a review. 2013 ieee global humanitarian technology conference: south asia satellite. ieee: trivandrum india. p. 27-35. celik, b., roche, r., suryanarayanan, s., bouquain, d., miraoui, a. (2017), electric energy management in residential areas through coordination of multiple smart homes. renewable and sustainable energy reviews, 80, 260-275. cheng, x., ciuonzo, d., rossi, p.s. (2018), multi-bit decentralized detection of a weak signal in wireless sensor networks with a rao test. 2018 ieee 23rd international conference on digital signal processing. ieee: shanghai. dharavath, r., raglend, i.j. (2019), integration of utility grid with hybrid generation for power quality conditioning using dynamic voltage restorer. international journal of renewable energy research, 9, 56-64. engelbrecht, a.p. (2007), computational intelligence: an introduction. 2nd ed. hoboken: wiley publishing. gomes, i.l.r., pousinho, h.m.i., melíco, r., mendes, v.m.f. (2016), bidding and optimization strategies for wind-pv systems in electricity markets assisted by cps. energy procedia, 106, 111-121. hirsch, a., parag, y., guerrero, j. (2018), microgrids: a review of technologies, key drivers, and outstanding issues. renewable and sustainable energy reviews, 90, 402-411. hossain, m.a., pota, h.r., squartini, s., abdou, a.f. (2019), modified pso algorithm for real-time energy management in grid-connected microgrids. renewable energy, 136, 746-757. karger, c.r., hennings, w. (2009), sustainability evaluation of decentralized electricity generation. renewable and sustainable energy reviews, 13, 583-593. katiraei, f., iravani, r., hatziargyriou, n., dimeas, a. (2008), microgrids management: controls and operation aspects of microgrids. ieee power and energy magazine, 6, 54-65. khalid, r., javaid, n., rahim, m.h., aslam, s., sher, a. (2019), fuzzy energy management controller and scheduler for smart homes. sustainable computing: informatics and systems, 21, 103-118. koltsaklis, n.e., giannakakis, m., georgiadis, m.c. (2018), optimal energy planning and scheduling of microgrids. chemical engineering research and design, 131, 318-332. li, w. (2018), improving particle swarm optimization based on neighborhood and historical memory for training multi-layer perceptron. information, 9(1), 16. logenthiran, t., srinivasan, d., phyu, e. (2015), particle swarm optimization for demand side management in smart grid. 2015 ieee innovative smart grid technologies asia. bangkok, thailand: ieee. logenthiran, t., srinivasan, d., shun, t.z. (2012), demand side management in smart grid using heuristic optimization. ieee transactions on smart grid, 3, 1244-1252. lund, h., andersen, a.n., østergaard, p.a., mathiesen, b.v., connolly, d. (2012), from electricity smart grids to smart energy systems a market operation-based approach and understanding. energy, 42, 96-102. mariam, l., basu, m., conlon, m.f. (2016), microgrid: architecture, policy and future trends. renewable and sustainable energy reviews, 64, 477-489. motevasel, m., seifi, a.r. (2014), expert energy management of a microgrid considering wind energy uncertainty. energy conversion and management, 83, 58-72. noor, s., yang, w., guo, m., van dam, k.h., wang, x. (2018), energy demand side management within micro-grid networks enhanced by blockchain. applied energy, 228, 1385-1398. quoc-tuan, t., ngoc, a.l., tung, l.n. (2016), optimal energy management strategies of microgrids. athens, greece: 2016 ieee symposium series on computational intelligence. shayeghi, h., shahryari, e., moradzadeh, m., siano, p. (2019), a survey on microgrid energy management considering flexible energy sources. energies, 12(11), 2159. too, j., abdullah, a.r., saad, n.m., tee, w. (2019), emg feature selection and classification using a pbest-guide binary particle swarm optimization. computation, 7(1), 12. van-ackooij, w., de boeck, j., detienne, b., pan, s., poss, m. (2018), optimizing power generation in the presence of micro-grids. european journal of operational research, 271(2), 450-461. whei-min, l., chia-sheng, t., ming-tang, t. (2016), energy management strategy for microgrids by using enhanced bee colony optimization. energies, 9(1), 5. worku, y.m., hassan, a.m., abido, a.m. (2019), real time energy management and control of renewable energy based microgrid in grid connected and island modes. energies, 12(2), 276. wu, x., cao, w., wang, d., ding, m. (2019), a multi-objective optimization dispatch method for microgrid energy management considering the power loss of converters. energies, 12(11), 1-19. zhou, b., wentao, l., ka, w.c., yijia, c., yonghong, k., xi, l., xiong, w. (2016), smart home energy management systems: concept, configurations, and scheduling strategies. renewable and sustainable energy reviews, 61, 30-40. . international journal of energy economics and policy | vol 9 • issue 3 • 2019144 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(3), 144-153. the impact of financial development on carbon emissions in africa kunofiwa tsaurai* department of finance, risk management and banking, university of south africa, south africa. *email: kunofiwa.tsaurai@gmail.com received: 02 september 2018 accepted: 20 january 2019 doi: https://doi.org/10.32479/ijeep.7073 abstract the paper explored the influence of financial development on carbon emissions in west african countries using pooled ordinary least squares (ols), fixed and random effects with data spanning from 2003 to 2014. on the theoretical front, arguments for both financial development led positive impact on carbon emissions and financial development led negative impact on carbon emissions are quite compelling. empirical studies on the role played by financial development on carbon emissions produced quite divergent and conflicting findings. it is clear from both theoretical and empirical sides that the influence of financial development on carbon emissions is still a contentious issue which is yet to be resolved in literature. overally, pooled ols approach (both lagged and non-lagged variable) shows that only domestic credit provided by financial sector resulted in the significant increase in carbon emissions in western african countries. keywords: financial development, carbon emissions, western african countries jel classifications: e44, n27, q5 1. introduction according to hoffmann (2011), poor nations like african countries can only afford to purchase material intensive industrial machinery which are unfriendly to the environment as they generate more pollution and excessive carbon emissions. consistent with recent empirical studies (mazzanti and musolesi, 2013; and piaggio and padilla, 2012), among others, observed that high levels of carbon emissions are detrimental to economic growth. whilst the negative impact of carbon emissions on economic growth is no longer a contestable issue in economics, the influence of financial development on carbon emissions is a subject dominating recent debates among academics and environmentalists but clearly still far from being conclusive. two main theoretical views characterise the influence of financial development on carbon emissions, namely the financial development led positive impact on carbon emissions and financial development led negative impact on carbon emissions. the weakness of these two theoretical views is that they assume a linear relationship between financial development and carbon emissions. the assumption is not practical consistent with tamazian and bhaskara (2010) whose study noted that the institutional framework in place in the transitional countries determined the influence of financial development on carbon emissions. the argument was also supported by hao et al. (2016) whose study observed that financial development only reduced carbon emissions at low levels of economic growth. contradictions, lack of consensus and divergent views characterise the empirical literature on the impact of financial development on carbon emissions. for example, the findings that are coming out of the empirical literature can be categorised into five, namely, the neutrality hypothesis, the feedback view, the financial development inspired positive effect on carbon emissions, financial development inspired negative impact on carbon emissions and the perspective that certain macro-economic factors must be available before financial development reduces carbon emissions. these contradictions, divergent views and absence of consensus this journal is licensed under a creative commons attribution 4.0 international license tsaurai: the impact of financial development on carbon emissions in africa international journal of energy economics and policy | vol 9 • issue 3 • 2019 145 is an indication that the role of financial development on carbon emissions is not yet a settled issue. it is still far from being resolved. moreover, the available empirical literature on the subject matter has so far largely ignored the african continent, a region which receives cheaper and environment unfriendly machinery. the extraction of natural resources in the african continent requires the use of heavy equipment and machinery which produces a lot of carbon emissions, consistent with kwakwa et al. (2018). it is against this backdrop that the current paper investigated the effect of financial development on carbon emissions in west african countries. this study contributes to literature by investigating the impact of financial development on carbon emissions in west african countries. in other words, the paper hopes to tell the inadequately told story of the impact of financial development on carbon emissions in an african context. the closest available empirical study on the impact of financial development on carbon emissions was done by onanuga (2017). the latter found out that financial development reduced carbon emissions in upper middle income sub-saharan african countries whilst financial development led to an increase in carbon emissions in low, low middle and high income sub-saharan african countries. the current study deviates from onanuga’s (2017) study in the following ways: (1) focused on west african countries, (2) used a lagged variable approach for robustness tests, (3) used pooled ordinary least squares (ols), fixed and random effects, (4) panel data used spans from 2003 to 2014 and (5) used three measures of financial development for robustness test purposes. the study enables western african countries to develop financial management policies that reduces not only energy consumption but overall quantity of carbon emissions. the rest of the paper is organised as follows: section 2 discusses both theoretical and empirical literature on the role of financial development on carbon emissions, section 3 explains how other macroeconomic variables influence carbon emissions whereas section 4 describes the financial development and carbon emissions trends in west african countries during the period from 2003 to 2014. section 5 is research methodology (econometric model specification, data analysis, robustness tests, results discussion and findings). section 6 concludes the paper. 2. literature review on impact of financial development on carbon emissions according to aye and edoja (2017), there are four theoretical perspectives on the impact of financial development on carbon emissions, namely the environment friendly technology, the foreign direct investment (fdi), the manufacturing sector enhancement and the increased consumer credit perspectives as discussed next. financial development reduces carbon emissions when the financial markets provide financial assistance to the domestic firms to acquire environment friendly and clean technology for manufacturing purposes. the theoretical view was supported by yuxiang and chen (2010) whose study noted that the financial sector provided funding and technical assistance that enabled chinese companies to adopt new and advanced technology which increased production levels whilst at the same time reducing carbon emissions. it was also argued by frankel and rose (2012) that financial markets can effectively allocate financial resources to the domestic firms to enable them to purchase environment friendly technology. financial development also increases carbon emissions when it attracts foreign investors (fdi) which boosts the amount of energy usage and the scale of economic activities in the host country. however, some of the foreign investors heavily invests in clean energy associated research and development projects and brings along their environment friendly technology which produces minimal amount of carbon emissions. financial development might increase the number and scale of manufacturing activities in the country through availing more financial assistance to the domestic companies. the effect could be both an increase in land degradation, pollution and carbon emissions, consistent with aye and edoja (2017. p. 10). more consumer credit can increase the scale of purchase of items such as machinery and automobiles purchased which consume a lot of energy (xing et al., 2017. p. 9). on the empirical front, several studies investigated the impact of financial development on carbon emissions. for example, sy et al. (2016) studied the interrelationship between financial development, carbon emissions, economic growth and trade openness in 40 european countries using ols with panel data ranging from 1985 to 2014. among other findings, their study detected the existence of a neutrality hypothesis between financial development and carbon emissions in the european countries. alom et al. (2017) explored the relationship between carbon emissions, urbanization, financial development and energy consumption in bangladesh using vector error correction model with time series data spanning from 1985 to 2015. one of the findings was that financial development had a positive effect on carbon emissions in bangladesh. using panel data analysis, kong and wei (2017) studied the relationship between financial development and carbon emissions using panel data (1997-2013) analysis in china’s 30 provinces. their study found out that low financial development reduced carbon emissions whereas higher levels of financial development led to an increase in carbon emissions in the china’s provinces. al-mulali et al. (2015) explore the effect of financial development on co2 emission in 129 countries classified by the income level. a panel co2 emission model using urbanisation, gross domestic product (gdp) growth, trade openness, petroleum consumption and financial development variables that are major determinants of co2 emission was constructed for the 1980-2011 period. the results revealed that the variables are cointegrated based on the pedroni cointegration test. the dynamic ols and the granger causality test results also show that financial development can improve environmental quality in the short run and long run due to its negative effect on co2 emission. nasreen et al. (2017) investigate the relationship between financial stability, economic growth, energy consumption and carbon dioxide (co2) emissions in south asian countries over the period 1980-2012 tsaurai: the impact of financial development on carbon emissions in africa international journal of energy economics and policy | vol 9 • issue 3 • 2019146 using a multivariate framework. estimated results suggest that all variables are non-stationary and cointegrated. the results show that financial stability improves environmental quality; while the increase in economic growth, energy consumption and population density are detrimental for environment quality in the long-run. in table 1, the findings on the relationship between carbon emissions and financial development can be categorised into five main groups. (1) financial development reduces carbon emissions, (2) financial development increases carbon emissions, (3) the relationship between financial development and carbon emissions is negligible, (4) the relationship between financial development and carbon emissions depend on other factors such as economic growth and institutional quality, among others and (5) a feedback effect characterises the relationship between the two variables. the contradictions in the empirical findings is a clear indication that the relationship between financial development and carbon emissions is far from being a conclusive issue. only more empirical tests can help to clarify the relationship between the two variables. empirical studies on the relationship between financial development and carbon emissions to a larger extent have so far ignored the african region. the current study seeks to unpack the intricacies of the impact of financial development on carbon emissions from an african point of view (table 2). 3. other macroeconomic variables that influence carbon emissions this section discusses the other factors that affect carbon emissions other than financial development(table 2). 4. financial development and carbon emissions trends in west african countries the averages of carbon emissions and three different measures of financial development during the 12-year period (2003-2014) are shown in table 3. gambia, ghana and liberia recorded the highest mean on domestic credit provided by the financial sector as a ratio of gdp above the overall mean of 28.65% of gdp. liberia is the outlier because its domestic credit provided by the financial sector as a ratio of gdp during the period from 2003 to 2014 was found to be well above the overall mean ratio. guinea-bissau (10.20% of gdp), mali (14.50% of gdp) and niger (10.17% of gdp) are the three west african countries with the lowest mean domestic credit provided by the financial sector as a ratio of gdp below the overall mean ratio of 28.65% of gdp. in terms of domestic credit to private sector by banks, burkina faso, ivory coast, ghana, mali, nigeria, senegal and togo had their mean domestic credit to private sector by banks (% of gdp) ratios above the overall mean of 14.11% of gdp. guinea-bissau and sierra leone had the lowest mean domestic credit to private sector by banks (% of gdp) ratios below the overall mean of 14.11% of gdp. five west african countries (gambia, ghana, liberia, senegal and togo) had mean broad money (% of gdp) ratios which were above the overall mean of 28.05% of gdp. gambia and togo are the outliers since their mean broad money ratios were well above the overall mean. in terms of carbon emissions, five west african countries (ivory coast, ghana, nigeria, senegal and togo) had their mean carbon emissions ratios above the overall mean carbon emissions ratio of 0.27 metric tons per capita. ghana (0.41), mali (0.07), niger (0.07), nigeria (0.64) and senegal (0.51) are clearly the outliers given that their mean carbon emissions ratios deviated a lot from the overall mean carbon emissions ratio of 0.27 metric tons per capita. 5. research methodology 5.1. data the paper used panel data from 2003 to 2014 on 12 west africa countries. the countries include burkina faso, ivory coast, gambia, ghana, guinea-bissau, liberia, mali, niger, nigeria, senegal, sierra leone and togo. other west african countries were excluded because of lack of data on some of the variables of interest. three measures of financial development were used, namely (1) domestic credit provided by financial sector as a ratio of gdp, (2) domestic credit to private sector by banks as a ratio of gdp and (3) broad money as a ratio of gdp. co2 emissions (metric tons per capita) is a proxy of carbon emissions used. all the data extracted from international monetary fund, world bank indicators and african development bank were converted into natural log before being used for main data analysis for two reasons, (1) to address the problem of outliers and (2) data not normally distributed. 5.2. econometric model cei,t = β0+β1fini,t+ β2xi,t+µi+εit (1) ce represents carbon emissions, fin is financial development, x stands for the explanatory variables. the latter include economic growth, fdi, trade openness, natural resources, population growth, renewable energy and infrastructural development. equation 2 is an econometric equation which shows the dependent variable (carbon emissions), independent variable (fin) and the explanatory variables. cei,t = β 0+ β 1f i n i , t+ β 2 g r o w t h i , t+ β 3 f d i i , t+ β 4 o p e n i , t +β5 naturali,t+β6 populi,t+β7 renewi,t+ β8infri,t +µ+ε (2) the main objective of this paper is to investigate the impact financial development on carbon emissions in west african countries. the objective is addressed by estimating equation 2 using panel data analysis methods (pooled ols, fixed and random effects). the study used three different proxies of financial development in order to establish whether the impact of financial development on carbon emissions in west african countries relied on the measure of financial development used. tsaurai: the impact of financial development on carbon emissions in africa international journal of energy economics and policy | vol 9 • issue 3 • 2019 147 author country/countries of study period methodology results basarir and cakir (2015) turkey, france, spain, italy and greece 1995-2010 panel data analysis financial development reduced carbon emissions in the studied countries mugableh (2015) jordan 1976-2010 vecm and autoregressive distributive lag (arrdl) financial development led to a decline in the amount of carbon emissions in jordan in both the short and long run boutabba (2014) india time series analysis financial development was found to have granger caused carbon emissions in india ghorashi and rad (2018) iran provinces 1989-2016 panel data analysis carbon emissions were found to have been reduced by financial development in the iran provinces studied muhammad and siddique (2017) pakistan 1980-2015 ardl financial development, energy consumption, economic growth and trade were all found to have increased carbon emissions in pakistan in the long run ayeche et al. (2016) european countries 1985-2014 panel data analysis the study showed that the relationship between financial development and carbon emissions was characterised by a neutrality hypothesis cetin and ecevit (2017) turkey 1960-2011 erdl and vecm in the long run, a causality relationship running from financial development, trade openness and economic growth towards carbon emissions in turkey hao et al. (2016) china provinces 1995-2012 generalized methods of moments (gmm) at low levels of economic growth, financial development reduced carbon emissions. on the contrary, financial development led to an increase in carbon emissions when levels of economic growth were higher xiong and qi (2018) chinese provinces 1997-2011 panel data analysis financial development was found to have reduced the carbon emissions per capita in the chinese provinces xing et al. (2017) china ardl the amount of carbon emissions reduced as a result of financial development onanuga (2017) sub-saharan african countries 1989-2012 static and dynamic analytical approaches the findings are twofold: (1) financial development reduced carbon emissions in upper middle income countries and (2) in low, low middle and high income countries, financial development was found to have increased the amount of carbon emissions muhammad and fatima (2013) pakistan 1971-2011 ardl the quantity of carbon emissions was found to have increased in response to financial development in pakistan zhang (2011) china 1994-2009 vecm and variance decomposition approach the study supported the financial development-led carbon emissions hypothesis in china sadeghieh (2016) turkey 1960-2011 error correction model (ecm) among other findings, a uni-directional causality relationship running from both economic growth and financial sector development towards carbon emissions was detected in turkey shahbaz et al. (2012) malaysia 1971-2008 time series analysis carbon emissions were found to have been lowered down by financial development in malaysia shahbaz et al. (2011) pakistan ardl carbon emissions were reduced by financial development in pakistan in the long run rault (2015) middle east and north african (mena) countries 1990-2011 panel data analysis the relationship between financial development and carbon emissions were found to have supported the neutrality hypothesis tamazian et al. (2009) brazil, russia, india and china 1992-2004 panel data analysis financial development lowered down the quantity of carbon emissions tamazian and bhaskara (2010) 24 transitional countries 1993-2004 gmm framework the impact of financial development on carbon emissions was found to be dependent on the institutional framework in place in the transitional countries table 1: the impact of financial development on carbon emissions ‑ an empirical view (contd...) tsaurai: the impact of financial development on carbon emissions in africa international journal of energy economics and policy | vol 9 • issue 3 • 2019148 author country/countries of study period methodology results jalil and feridun (2011) china 1953-2006 ardl carbon emissions was negatively affected by financial development shahzad, et al. (2014) pakistan 1973-2011 erdl and vecm financial development and carbon emissions were found to have affected each other in pakistan in the long run phong (2019) asean-5 countries 1971-2014 panel data analysis financial development was found to have had an increase on carbon emissions in the asean-5 countries studies rasiah et al. (2018) asean countries 1970-2016 panel data analysis financial development was not found to be a significant determinant of carbon emissions. however, macro-economic variables such as trade openness source: author compilation table 1: (continued) table 2: theory intuition and a priori expectation variable proxy used theory intuition expected sign economic growth (growth) gdp per capita aye and edoja (2017) found out that higher economic growth had a positive influence on carbon emissions whilst low economic growth had a negative impact on carbon emissions in developing countries. higher levels of economic growth increases carbon emissions as the resultant increase in energy use produce more pollution. on the contrary, the use of clean energy sources to boost economic growth leads to a decline in the amount of carbon emissions. khobai and le roux (2017) noted however that carbon emissions had a positive influence on economic growth in south africa whilst rokhmawati et al. (2017) observed that carbon emissions had a strong impact on firm performance in indonesia +/− population growth (pop) population growth (annual %) high levels of population can lead to increased carbon emissions as the people engage in deforestation activities and also use more energy for their day to day economic activities. population growth was found to have had a positive and significant impact on carbon emissions in developing countries (aye and edoja, 2017. p. 15) + trade openness (open) total trade (% of gdp) trade openness increases the levels of energy usage inspired manufacturing activities in the economy as firms can easily source inputs for production from other countries and they are also under increased pressure to supply foreign markets. trade openness alongside energy usage and economic growth were found to have had a significant positive impact on carbon emissions in selected asean nations (rasiah et al., 2018). on the other hand, trade openness allows countries to easily acquire (from other countries) and use new and clean technology which is associated with low levels of carbon emissions. these arguments were put forward by grossman and krueger (1991) +/− renewable energy consumption (renew) renewable energy consumption (% of total final energy consumption) by its nature, renewable energy is clean, reduce both pollution and carbon emissions − foreign direct investment net fdi inflow (% of gdp) according to blanco et al. (2013), fdi inflows increase the number and magnitude of manufacturing activities in the host country thus pushing up the pollution intensity and carbon emissions per capita. cheng and yang (2016) noted that fdi reduced carbon emissions up to a certain extent only beyond which fdi started to increase carbon emissions in china. +/− natural resources (natural) total natural resources rents (% of gdp) the process of extracting natural resources involves the use of heavy machinery which not only means the use of more energy but also implies increased pollution and carbon emissions. the argument was supported by kwakwa et al. (2018) + infrastructure development (infr) individuals using the internet (% of population) according to salahuddin et al. (2016), internet infrastructure usage was found to have had a negligible positive effect on carbon emissions in the oecd group of countries. the same study however found out that internet infrastructure usage had a significant positive impact on both trade openness and financial development, thereby indirectly positively affecting carbon emissions through these two macroeconomic variables + source: author compilation. gdp: gross domestic product tsaurai: the impact of financial development on carbon emissions in africa international journal of energy economics and policy | vol 9 • issue 3 • 2019 149 5.3. pre-estimation diagnostics, panel root and co-integration tests correlation analysis in table 1 (appendix section) shows that the correlation between carbon emissions and different variables is in line with theoretical predictions summarised in table 2. descriptive statistics (table 2 in appendix section) shows that financial development, trade openness and renewable energy data is not normally distributed as the probability of the jarquebera criteria is equal to zero for the three variables. to address the problem of abnormally distributed data, all the data used in this study was transformed into natural logarithms before any further use. all the data was found to have been stationary at first difference (table 3 under appendix section) whilst all the variables were found to have a long run relationship (table 4 under appendix section). these findings enabled the author to proceed to main data analysis. 5.4. data analysis domestic credit provided by financial sector as a ratio of gdp, domestic credit to private sector by banks as a ratio of gdp and broad money as a ratio of gdp are the different proxies of financial sector development used in model 1, 2 and 3 respectively (tables 4and 5). under both fixed and random effects, domestic credit provided by financial sector and broad money had a positive but non-significant impact on carbon emissions. the finding is consistent with aye and edoja’s (2017) observation that financial development increases the number and scale of manufacturing activities in the country through availing more financial assistance to the domestic companies, the effect of which include land degradation, pollution and carbon emissions. both fixed and random effects also shows that domestic credit to private sector by banks had a negative but non-significant influence on carbon emissions in west african countries, a finding which is in line with yuxiang and chen (2010) whose study noted that financial sector funding allowed chinese companies to adopt advanced technology which reduced the amount of carbon emissions. the pooled ols (table 6) also found out that carbon emissions were lowered down by broad money, further supporting yuxiang and chen’s (2010) observation. according to the pooled ols approach, domestic credit provided by financial sector had a significant positive effect on carbon emissions whilst domestic credit to private sector by banks positively but non-significantly influenced carbon emissions in west african countries. the results support xing et al.’s (2017) argument that more credit availed to the consumers enable them to buy energy consuming machinery and automobiles. economic growth was found to have had a non-significant effect on carbon emissions in all the 3 models under fixed and random effects. on the other hand, economic growth had a significant positive impact on carbon emissions in all the 3 models under pooled ols approach. the finding follows aye and edoja’s (2017) view that higher levels of economic growth is associated with larger scale manufacturing activities which consumes and produce more energy and pollution respectively. under both fixed and random effects, fdi had a non-significant positive influence on carbon emissions. the finding support aye and edoja’s (2017) view that foreign investors not only increase the quantity of manufacturing activities but the amount of energy consumption, pollution and carbon emissions in the host country. fdi was found to have had a significant negative influence on carbon emissions in west african countries, in line with aye and edoja (2017) whose study noted that some of the foreign investors brings along their environment friendly technology which lowers down carbon emissions. in line with theoretical predictions, trade openness was found to have had a significant positive impact on carbon emissions under all the three panel data analysis approaches except only in model 1 under pooled ols approach (non-significant positive influence was observed). natural resources had a significant positive influence in all the three models under both fixed and random effects. model 2 under pooled ols shows that carbon emissions were positively but significantly affected by natural resources whilst model 1 and 3 under pooled ols shows that natural resources had a non-significant positive effect on carbon emissions. the findings support kwakwa et al. (2018) whose study noted that heavy machinery which uses a lot of energy and contributes to more air pollution is required to extract natural resources. table 3: financial development and carbon emission trends in west african countries (2003-2014) country domestic credit provided by the financial sector (% of gdp) domestic credit to private sector by banks (% of gdp) broad money (% of gdp) carbon emissions (metric tons per capita) burkina faso 17.23 16.49 26.40 0.12 ivory coast 21.17 14.44 27.89 0.39 gambia 33.10 12.94 45.16 0.23 ghana 29.17 14.69 29.45 0.41 guinea-bissau 10.20 5.37 24.42 0.15 liberia 116.94 11.89 29.02 0.20 mali 14.50 14.97 24.26 0.07 niger 10.17 9.15 17.25 0.07 nigeria 19.76 18.05 24.13 0.64 senegal 27.29 24.14 32.63 0.51 sierra leone 16.22 5.15 17.67 0.13 togo 28.02 21.99 38.32 0.32 overall mean 28.65 14.11 28.05 0.27 source: author’s compilation. gdp: gross domestic product tsaurai: the impact of financial development on carbon emissions in africa international journal of energy economics and policy | vol 9 • issue 3 • 2019150 under fixed and random effects, all the three models show that population growth had a non-significant negative impact on carbon emissions whilst pooled ols shows that population growth had a significant negative influence on carbon emissions. these results contradict most theoretical explanations on the relationship between population growth, energy consumption and carbon emissions. all the three panel data analysis methods show that the use of renewable energy reduced carbon emissions, in line with theory intuition (table 2). following salahuddin et al. (2016), this paper to a large extent shows that infrastructural development had a non-significant positive effect on carbon emissions in west african countries. 5.5. the lagged panel data analysis framework following matthew and johnson (2014), tsaurai (2018) and tsaurai and ngcobo (2018), the influence of one macro-economic variable on another is not immediate. it is in line with this argument that the author used a lagged panel data analysis model (refer to equation 3) to investigate the impact of financial development on carbon emissions in west african countries. this was done to see if the results are robust (tables 7-9). cei,t = β0+β1fini,t−1+β2 growthi,t−1+β3 fdii,t−1+β4 openi,t−1 + β 5 n at u r a li,t−1+ β 6 p o p u li,t−1+ β 7 r e n e wi,t−1 + β8infri,t−1+µ+ε (3) the lagged variable approach shows that financial development had a non-significant positive influence on carbon emissions in all the 3 models under both fixed and random effects. the nonlagged variable approach differs in that it indicates that financial development had a non-significant negative effect on carbon emissions in model 2 under both fixed and random effects. all table 4: the impact of financial development on carbon emissions (co2) ‑fixed effects variable model 1 model 2 model 3 fin 0.0086 −0.0161 0.0344 growth 0.0032 0.0038 0.0101 fdi 0.0069 0.0080 0.0056 open 0.1675** 0.1734** 0.1664** natural 0.1739*** 0.1768*** 0.1737*** popul −0.0148 −0.0025 −0.0180 renew −0.5269** −0.5314** −0.5475** infr 0.0306 0.0337 0.0234 number of countries 12 12 12 number of observations 144 144 144 adjusted r2 0.96 0.96 0.96 f-statistic 175.14 175.31 175.32 prob (f-statistic) 0.00 0.00 0.00 source: author’s compilation from e-views. ***, ** and *denote 1%, 5% and 10% levels of significance, respectively table 5: the impact of financial development on carbon emissions (co2) -random effects variable model 1 model 2 model 3 fin 0.0136 −0.0086 0.0620 growth 0.0214 0.0250 0.0512 fdi 0.0007 0.0004 0.0064 open 0.1854*** 0.1940*** 0.1989*** natural 0.1555*** 0.1581*** 0.1438*** popul −0.0519 −0.0403 −0.0862 renew −0.5793*** −0.5931*** −0.6443*** infr 0.0312 0.0319 0.0179 number of countries 12 12 12 number of observations 144 144 144 adjusted r2 0.56 0.55 0.53 f-statistic 25.83 23.47 22.19 prob (f-statistic) 0.00 0.00 0.00 source: author’s compilation from e-views. ***, ** and *denote 1%, 5% and 10% levels of significance, respectively table 6: the impact of financial development on carbon emissions (co2) -pooled ols variable model 1 model 2 model 3 fin 0.2647*** 0.0528 −0.1691 growth 0.2314** 0.2415** 0.2205* fdi −0.0766* −0.0759* −0.0860* open 0.1796 0.4440*** 0.5581*** natural 0.1002 0.1512* 0.1287 popul −1.3697*** −1.2708*** −1.2093*** renew −0.8044*** −0.9750*** −0.9048*** infr 0.1333** 0.1183 0.1751** number of countries 12 12 12 number of observations 144 144 144 adjusted r2 0.62 0.59 0.59 source: author’s compilation from e-views. ***, ** and *denote 1%, 5% and 10% levels of significance, respectively table 7: financial development and co2-fixed effects: lagged independent variable approach (t-1) variable model 1 model 2 model 3 fin 0.0461 0.0207 0.1192 growth −0.0196 −0.0015 0.0211 fdi 0.0061 0.0013 0.0005 open 0.1169* 0.1306* 0.1083 natural 0.1779*** 0.1910*** 0.1898*** popul −0.2050* −0.1751 −0.1942* renew −0.1427 −0.1696 −0.2035 infr 0.0466 0.0338 0.0132 number of countries 12 12 12 number of observations 144 144 144 adjusted r2 0.95 0.95 0.95 f-statistic 158.25 156.71 159.28 prob (f-statistic) 0.00 0.00 0.00 source: author’s compilation from e-views. ***, ** and *denote 1%, 5% and 10% levels of significance, respectively table 8: financial development and co2-random effects: lagged independent variable approach (t-1) variable model 1 model 2 model 3 fin 0.0541 0.0279 0.1351 growth −0.0137 0.0110 0.0340 fdi −0.0005 −0.0089 −0.0072 open 0.1374** 0.1642** 0.1315* natural 0.1492*** 0.1544*** 0.1620*** popul −0.2559** −0.2414** −0.2456** renew −0.2498 −0.3255 −0.3270 infr 0.0533* 0.0396 0.0154 number of countries 12 12 12 number of observations 144 144 144 adjusted r2 0.55 0.54 0.54 f-statistic 24.12 25.13 23.54 prob (f-statistic) 0.00 0.00 0.00 source: author’s compilation from e-views. ***, ** and *denote 1%, 5% and 10% levels of significance, respectively tsaurai: the impact of financial development on carbon emissions in africa international journal of energy economics and policy | vol 9 • issue 3 • 2019 151 other findings on the impact of financial development on carbon emissions are similar, an indication that the results of the study are quite robust. 6. conclusion the main aim of this paper was to explore the influence of financial development on carbon emissions in west african countries using panel data spanning from 2003 to 2014. on the theoretical front, arguments for both financial development led positive impact on carbon emissions and financial development led negative impact on carbon emissions are quite compelling. empirical studies on the role played by financial development on carbon emissions produced quite divergent and conflicting findings: (1) the effect of financial development on carbon emissions is negligible, (2) financial development and carbon emissions affect each other, (3) the presence of other factors such as economic growth and institutional quality influence the impact of financial development on carbon emissions, (4) financial development either positively or negatively affected carbon emissions. it is clear from both theoretical and empirical sides that the influence of financial development on carbon emissions is still a contentious issue which is yet to be resolved in literature. in order to fill in this gap, the author investigated the impact of financial development on carbon emissions in west african countries. overally, pooled ols approach (both lagged and non-lagged variable) shows that only domestic credit provided by financial sector resulted in the significant increase in carbon emissions in west african countries. the study therefore encourages west african countries to implement credit policies that ensures that the loans availed by the financial sector to the domestic firms are used towards acquiring environmental friendly machinery and equipment that reduces carbon emissions. references alom, k., uddin, a.n.m., islam, n. (2017), energy consumption, c02 emissions, urbanization and financial development in bangladesh: vector error correction model. journal of global economics, management and business research, 9(4), 178-189. al-mulali, u., tang, c.f., ozturk, i. (2015), does financial development reduce environmental degradation? evidence from a panel study of 129 countries. environmental science and pollution research, 22(19), 14891-14900. aye, g.c., edoja, p.e. (2017), effect of economic growth on c02 emission in developing countries: evidence from a dynamic panel threshold model. cogent economics and finance, 5(1), 1-22. ayeche, m.b., barhoumi, m., hammas, m.a. (2016), causal linkage between economic growth, financial development, trade openness and c02 emissions in european countries. american journal of environmental engineering, 6(4), 110-122. basarir, c., cakir, n. (2015), causal interactions between c02 emissions, financial development, energy and tourism. asian economic and financial review, 5(11), 1227-1238. blanco, l., gonzalez, f., ruiz, i. (2013), the impact of fdi on c02 emissions in latin america. oxford development studies, 41(1), 104-121. boutabba, m.a. (2014), the impact of financial development, income, energy and trade on carbon emissions: evidence from the indian economy. economic modelling, 40, 33-41. cetin, m., ecevit, e. (2017), the impact of financial development on carbon emissions under the structural breaks: empirical evidence from turkish economy. international journal of economic perspectives, 11(1), 64-78. cheng, s., yang, z. (2016), the effects of fdi on carbon emissions in china: based on spatial econometric model. revista de la facultad de ingenieria u.c.v., 31(6), 137-149. frankel, j., rose, a. (2002), an estimate of the effect of common currencies on trade and income. quarterly journal of economics, 117(2), 437-466. grossman, g.m., krueger, a.b. (1991), environmental i̇mpacts of a north american free trade agreement. national bureau of economic research, working paper number 3914. ghorashi, n., rad, a.a. (2018), impact of financial development on carbon emissions: panel data evidence from iran’s economic sectors. journals of community health research, 7(2), 127-133. hao, y., zhang, z., liao, h., wei, y., wang, s. (2016), is c02 emission a side effect of financial development? an empirical analysis for china. environmental science pollution res, 23(20), 21041-21057. hoffmann, u. (2011), some reflections on climate change, green growth i̇llusions and development space. discussion paper number 205. new york: united nations conference on trade and development (unctad). im, k.s., pesaran, m.h., shin, y. (2003), testing unit roots in heterogeneous panels. journal of econometrics, 115(1), 53-74. jalil, a., feridun, m. (2011), the impact of growth, energy and financial development on the environment in china: a co-integration analysis. energy economics, 33(2), 284-291. khobai, h., le roux, p. (2017), the relationship between energy consumption, economic growth and carbon dioxide emission: the case of south africa. international journal of energy economics and policy, 7(3), 102-109. kong, y., wei, f. (2017), financial development, financial structure and carbon emission. environmental engineering and management journal, 16(7), 1609-1622. kwakwa, p.a., alhassan, h., adu, g. (2018), effect of natural resources extraction on energy consumption and carbon dioxide emission in ghana, ‘munich personal repec archive (mpra) paper number 85401. p1-19. levin, a., lin, c.f., chu, c.s.j. (2002), unit root tests in panel data: asymptotic and finite-sample properties. journal of econometrics, 108(1), 1-24. table 9: financial development and co2-pooled ols: lagged independent variable approach (t-1) variable model 1 model 2 model 3 fin 0.2857*** 0.0639 −0.1158 growth 0.1671 0.1988* 0.1951* fdi −0.0520 −0.0557 −0.0628 open 0.1389 0.4329*** 0.5239*** natural 0.0844 0.1643** 0.1485* popul −1.4723 −1.3301*** −1.2804*** renew −0.6457 −0.8910*** −0.8578*** infr 0.1764 0.1312** 0.1752** number of countries 12 12 12 number of observations 144 144 144 adjusted r2 0.64 0.60 0.60 source: author’s compilation from e-views. ***, ** and *denote 1%, 5% and 10% levels of significance, respectively tsaurai: the impact of financial development on carbon emissions in africa international journal of energy economics and policy | vol 9 • issue 3 • 2019152 matthew, o.h., johnson, a. (2014), impact of foreign direct investment on employment generation in nigeria: a statistical investigation. iosr journal of business and management, 16(3), 44-56. mazzanti, m., montini, a., zoboli, r. (2006), economic dynamics, emission trends and the ekc new evidence using namea and provincial panel data for italy. universita degli studi di ferrara, quaderno number 19/2006. mugableh, m.i. (2015), economic growth, c02 emissions and financial development in jordan: equivalent and dynamic causality analysis. international journal of economics and finance, 7(7), 98-105. muhammad, j., fatima, s.g. (2013), energy consumption, financial development and c02 emissions in pakistan. munich personal repec archive (mpra) paper number 48287. p1-23. muhammad, r., siddique, h.m.a. (2017), impact of financial development and energy consumption on c02 emissions: evidence from pakistan. bulletin of business and economics, 6(2), 68-73. nasreen, s., anwar, s., ozturk, i. (2017), financial stability, energy consumption and environmental quality: evidence from south asian economies. renewable and sustainable energy reviews, 67, 1105-1122. onanuga, o.t. (2017), the i̇mpact of economic and financial development on carbon emissions: evidence from sub-saharan africa. university of south africa, unpublished doctoral thesis. piaggio, m., padilla, e. (2012), c02 emissions and economic activity: heterogeneity across countries and non-stationary series. energy policy, 46, 370-381. phong, l.h. (2019), globalization, financial development and environmental degradation in the presence of environmental kuznets curve: evidence from asean-5 countries. international journal of energy economics and policy, 9(2), 40-50. rasiah, r., guptan, v., habibullah, m.s. (2018), evaluating the impact of financial and economic factors on environmental degradation: a panel estimation study of selected asean countries. international journal of energy economics and policy, 8(6), 209-216. rault, c. (2015), financial development, environmental quality, trade and economic growth: what causes what in mena countries. iza discussion paper number 8868. rokhmawati, a., gunardi, a., rossi, m. (2017), how powerful is your customers’ reaction to carbon performance? linking carbon and firm financial performance. international journal of energy economics and policy, 7(6), 85-95. sadeghieh, m. (2016), financial development, c02 emissions, fossil fuel consumption and economic growth: the case of turkey. eastern mediterranean university, unpublished masters thesis. salahuddin, m., alam, k., ozturk, i. (2016), the effects of internet usage and economic growth on c02 emissions in oecd countries: a panel investigation. renewable and sustainable energy reviews, 62, 1226-1235. shahbaz, m., islam, f., butt, m.s. (2011), financial development, energy consumption and c02 emissions: evidence from ardl approach for pakistan, mpra paper number 30138. shahbaz, m., solarin, s.a., mahmood, h. (2012), does financial development reduce c02 emissions in malaysian economy? a time series analysis. munich personal repec archive paper number 40603. shahzad, s.j.h., rehman, m., hurr, m., zakaria, m. (2014), do economic and financial development i̇ncrease carbon emissions in pakistan: empirical analysis through ardl co-i̇ntegration and vecm causality, mpra paper number 60310. sy, a., tinker, t., derbali, a., jamel, l. (2016), economic growth, financial development, trade openness and c02 emissions in european countries. african journal of accounting, auditing and finance, 5(2), 1226-1235. tamazian, a., chousa, j.p., vadlamannati, k.c. (2009), does higher economic and financial development lead to environmental degradation: evidence from bric countries. energy policy, 37(1), 246-253. tamazian, a., bhaskara, r.b. (2010), do economic, financial and institutional developments matter for environmental degradation? evidence from transitional economies? energy economics, 32(1), 137-145. tsaurai, k. (2018), greenhouse gas emissions and economic growth in africa: does financial development play any moderating role? international journal of energy economics and policy, 8(6), 267-274. tsaurai, k., ngcobo, l. (2018), the role of liquidity in the remittanceshuman capital development nexus in emerging economies. acta universitatis danubius oeconomica, 14(7), 101-119. xing, t., jiang, q., ma, x. (2017), to facilitate or curb? the role of financial development in china’s carbon emissions reduction process: a novel approach. international journal of environmental research and public health, 14(10), 1-39. xiong, l., qi, s. (2018), financial development and carbon emissions in chinese provinces: a spatial panel data analysis. the singapore economic review, 63(2), 447-464. yuxiang, k., chen, z. (2010), financial development and environmental performance: evidence from china. environment and development economics, 16(1), 1-19. zhang, y. (2011), the impact of financial development on carbon emissions: an empirical analysis in china. energy policy, 39(4), 2197-2203. appendix section table 1: correlation analysis co2 fin growth fdi open natural popul renew infr co2 1.00 fin 0.36*** 1.00 growth 0.61*** −0.08 1.00 fdi 0.03 0.44*** −0.23*** 1.00 open 0.31*** 0.69*** −0.19** 0.57*** 1.00 natural −0.05 0.25*** −0.22*** 0.43*** 0.32*** 1.00 popul −0.48*** 0.001 −0.38*** 0.08 −0.13 −0.05 1.00 renew −0.44*** −0.19** −0.39*** −0.03 −0.12 0.53*** 0.09 1.00 infr 0.58*** 0.10 0.77*** 0.01 0.002 −0.17** −0.11 −0.57*** 1.00 source: author compilation from e-views. ***, **, *denotes statistical significance at the 1%, 5%, 10% level respectively tsaurai: the impact of financial development on carbon emissions in africa international journal of energy economics and policy | vol 9 • issue 3 • 2019 153 table 2: descriptive statistics co2 fin growth fdi open natural popul renew infr mean −1.56 3.03 6.38 1.19 4.23 2.46 1.03 4.27 0.70 median −1.53 2.99 6.32 1.09 4.21 2.46 0.99 4.35 0.86 maximum −0.26 5.43 8.08 4.49 5.74 4.12 1.56 4.52 3.24 minimum −3.02 1.53 4.89 −2.54 3.43 0.89 0.55 3.70 −3.47 standard deviation 0.74 0.71 0.60 1.13 0.41 0.68 0.19 0.22 1.41 skewness −0.17 0.90 0.35 0.29 0.98 0.05 0.15 −1.12 −0.60 kurtosis 2.00 5.27 3.22 3.74 5.37 2.80 3.31 3.12 3.15 jarque−bera 6.65 50.4 3.20 5.22 57.0 0.29 1.12 30.18 8.66 probability 0.04 0.00 0.20 0.07 0.00 0.86 0.57 0.00 0.01 observations 144 144 144 144 144 144 144 144 144 source: author compilation from e-views. note: ***,**,*denotes statistical significance at the 1%, 5%, 10% level respectively table 3: panel unit root tests -individual intercept variable level first difference llc ips adf pp llc ips adf pp lco2 −1.0897 0.5713 18.90 17.52 −3.3062*** −2.771*** 46.54*** 76.31*** lfin 0.5962 2.2889 10.0197 10.5150 −3.678*** −2.658*** 46.106*** 109.665*** lgrowth −3.514*** 0.622 16.073 52.836*** −6.038*** −2.735*** 48.684*** 87.303*** lfdi −1.952** −0.723 28.255 33.139 −2.666*** −2.255** 43.450*** 110.255*** lopen −0.577 0.1669 20.342 28.661 −1.465* −1.759** 36.832** 77.3395*** lnatural −2.736*** −0.783 28.765 19.339 −4.173*** −2.665*** 46.269*** 98.7802*** lpopul −10.044*** −1.331* 68.699*** 25.546 −6.562*** −3.830** 36.383* 38.028** lrenew −1.1808 0.7026 18.7387 18.7950 −4.5581*** −2.6053*** 45.6190*** 91.1501*** linfr 1.9490 4.9335 8.8132 37.3367** −15.7972*** −3.8640*** 50.6317*** 73.1034*** source: author’s compilation from e-views. llc, ips, adf and pp stands for levin et al. (2002); im et al. (2013); adf fisher chi square and pp fisher chi square tests respectively. *, ** and ***denote 1%, 5% and 10% levels of significance, respectively table 4: kao residual co-integration test individual intercept t-statistic probability augmented dickey-fuller (adf) −2.9043 0.0018 source: author’s compilation from e-views . international journal of energy economics and policy | vol 9 • issue 6 • 2019124 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(6), 124-130. exploring the impact of renewable energy on climate change in the gcc countries amira kasem, mohammad alawin* department of economics, kuwait university, kuwait. *email: m_alawin@hotmail.com received: 17 june 2019 accepted: 06 september 2019 doi: https://doi.org/10.32479/ijeep.8477 abstract this study provides a theoretical framework for the role of renewable energy in mitigating the climate change in the gulf cooperation council (gcc) countries. the abundancy of renewable resources and widely accessible technology are the key drivers for the renewable energy business in the gcc. however, lack of effective policies and regulations, along with subsidized fuel prices, are slowing down the implementation of renewable resource options. this study will illustrate the potential, the challenges, and the barriers of implementing renewable energy technologies in the gcc region. in addition, this research empirically examines the impact of renewable energy sources and other factors in the gcc countries in reducing the carbon dioxide emissions, using pooled ordinary least square regression analysis with fixed effect specification. the results indicate that renewable energy consumption, gdp per capita, and electrical power consumption have a statistically significant impact on co2 emissions. keywords: renewable energy, electrical power, gcc countries jel classifications: q20, q30, q40 1. introduction the gulf cooperation council (gcc) economies rely overly on hydrocarbons for energy production. burning huge amounts of these fossil fuels domestically is not a sustainable process. the rapid socio-economic growth, characterized by increasing population, high rates of urbanization and substantial industrialization, consumes more and more energy to fulfil basic requirements. demand for electricity is accelerating; it doubled during the last decade and is expected to keep growing by approximately 7-8% annually (aloughani, 2015). the high demand for energy in the gcc region causes excessive and inefficient hydrocarbon use that in turn is damaging the environment and human health. since the nineteenth century, scientists and researchers have studied the influence of greenhouse gas (ghg) on the atmosphere. recently, concerns have grown because of the global climate change issue caused by the rise of the accumulated ghgs. oddly, few controls and monitoring existed for one of the major ghgs, carbon dioxide. co2 concentration has increased to reach about 400 parts per million (ppm) of atmospheric concentration. climate change is considered as the most severe environmental phenomenon and the greatest threat to the world. daily human activities, such as transportation, farming, deforestation, industrialization, and manufacturing, produce ghgs. global warming and the ensuing climate change are regarded as a result of man-made ghg emissions, including water vapor, carbon dioxide, methane, nitrous oxide, and ozone. these gases accumulate in the atmospheric space, entangle the heat from the sun, and, consequently, cause climate change. these changes have led to catastrophic events like storms, droughts, rise in sea levels, and floods (scientific advisory panel, 2018). with the burning of fossil sources of energy in the gulf states causing co2 emissions, global climate change will cause serious negative environmental impacts on the region. agriculture and water resources will be affected by the rising temperatures. as the evaporation increases, this journal is licensed under a creative commons attribution 4.0 international license kasem and alawin: exploring the impact of renewable energy on climate change in the gcc countries international journal of energy economics and policy | vol 9 • issue 6 • 2019 125 the demand for energy will increase. furthermore, the levels of the red sea, the arabian gulf, and the indian ocean will rise, and the risk of desertification and salinization of soil and groundwater will become real threats. to address climate change, gcc countries established a framework to promote clean and renewable energy solutions as a path to sustainable development, as well as to protect the environment. therefore, gcc countries have joined many international environmental agreements such as the united nations framework convention on climate change (unfccc) and the kyoto protocol of climate change. the unfccc obligated industrialized countries and “transitioning economy” countries to achieve quantified emission reduction targets for ghg. the kyoto protocol was signed by 192 parties, including the gcc countries, and it took effect on february 16, 2005 (raouf, 2008). renewable energy sources (res) comprise solar, wind, hydropower, and other sources. res are relatively clean, widely available, and unlimited. in addition, res are the only sustainable alternative to fossil fuels. according to besha (2011), res currently supply about 15-20% of world energy demand. it is evident that as renewable energy technology matures and becomes widely implemented, the cost gap between it and traditional energy sources will be minimized. closing this gap enables res to become cost effective compared to conventional energy. this paper is organized as follows. section (2) encompasses the relevant literature review and previous studies. section (3) details the theoretical framework that explains the res phenomenon and analyzes the challenges and barriers of res technology in the case of the gulf countries. section (4) describes the methodology and empirical work. the interpretation of the descriptive results are in section (5); and conclusions are in section (6). 2. literature review many studies in renewable energy systems emphasize that renewable energy must be now a priority for all countries worldwide. scholars illustrate the vital role of renewable energy in mitigating climate change and study how beneficial is the utilization of the world’s renewable resources. some scholars pay special attention to the gcc’s energy market and res. various studies have found a significant association between sustainable growth and a diversified economy. some countries are considered successful models in economic diversification. gcc countries attempt to achieve the best level of growth and prosperity by diversifying the economy to avoid the instability linked to the over-reliance on oil resources (saif-alyousfi et al., 2018). poudineh et al. (2016) shows that resource-rich mena economies are still behind in the move towards renewable energy because of infrastructure inadequacy, insufficient institutional capacity, risks, and uncertainties. the authors suggest a new dynamic approach consisting of a partial subsidy program and a partial fossil fuel price adjustment to balance fiscal sustainability with political stability. this policy approach might lead to more development in the renewables markets. aloughani (2015) discusses the challenges of res strategies in the gcc countries. the author explains that because the nature of the gulf countries is convenient for res, these resources are considered as the new vision for future energy. however, many challenges are associated with renewable energy technologies such as economic, technical, social, and environmental. a cost analysis between traditional energy using oil and gas and res energy finds that many producers accept the concept of cutting subsidies on traditional energy to promote res. ley (2017) highlights the fact that decentralized renewable energy (dre) projects contribute to climate change mitigation, e.g. provide electricity that can reduce over-dependence on natural resources. dre systems are utilized for emissions reduction and poverty alleviation, but their role for climate change has yet to be analysed. ley’s study shows that despite the wide variety of applications of dre systems, the applicability of these systems towards climate impacts are not considered. luttenberger (2015) illustrates that croatia with its massive renewable solar energy potential still underperforms in solar usage for electricity production and heating. luttenberger highlights the reasons for this by analysing croatia’s environmental policies and subsidies, international financial institutions financing new renewable energy projects, the power of utility companies, and the social dimension of res. to secure reasonable renewable energy shares in croatia’s energy supply mix, the government should act as a regulator with various instruments to enhance the renewable energy use in cooperation with local authorities. sasana and putri (2018) discusses the increase of energy consumption that has become one of the world problems, especially in developing countries moving toward industrialization, like indonesia. sasana and putri analyzes the effect of fossil energy consumption, population growth, and consumption of renewable energy on carbon dioxide emission. the result, using an ordinary least square (ols) approach, showed that fossil energy consumption and population growth have a positive influence on carbon dioxide emissions in indonesia. on the other hand, the estimated renewable energy consumption (rec) has a negative effect on carbon dioxide emissions. the study conducted by mas’ud et al. (2018) discusses the progress made on solar energy in the gcc countries. they propose a plan to increase the share of res by deploying solar energy for electrical power production and simultaneously reducing the huge dependency of gcc countries on fossil fuels. to emphasize this approach, governments must promote relevant policies and inform their citizens about the benefits of res. some of the challenges and barriers facing the gcc countries are technological knowhow, policy development, and insufficient application of re technology integrated within the buildings. however, many areas of improvement are evident through promotion of research and development, public/private initiatives, legislation, and regulatory framework. kasem and alawin: exploring the impact of renewable energy on climate change in the gcc countries international journal of energy economics and policy | vol 9 • issue 6 • 2019126 gastli and armendariz (2013) report that according to the world economic forum, the gcc nations will be affected by climate change, producing increased pressure on scarce water resources and rising air pollution. the authors present the challenges of the application of renewable energy in the gcc countries. they highlight that the efficiency reduction vs. cell temperature is the suitable technology for the gcc and find that the performance of solar cells in the gcc region will not be similar to their counterparts operating in europe. the study also discussed the reasons behind the lag in the application of renewables in the gcc region. those reasons are: insufficient awareness among decisionmakers, low investment, the fear of shifting from conventional energy sources to renewable and clean energy sources, lack of clear regulations and policies, lack of industrial motivation and lack of expertise and specialization. tugcu et al. (2012) primarily examined the long-run and causal relationships between renewable and non-rec and economic growth by using classical and augmented production functions in g7 countries (1980-2009). the findings show that neither renewable nor non-rec are related to economic growth. mathiesen et al. (2011) illustrate that the high cost of ghg mitigation strategies dominate the debate between world leaders about the costs of mitigation and the distribution of these costs between different countries. the analysis reveals that implementing renewable energy and efficient conversion technologies have a positive socio-economic effect, create employment, and potentially lead to high earnings on externalities, such as positive health effects. shafiei and salim (2014) attempt to capture the determinants of co2 emissions, using the stirpat model with panel data from 1980 to 2011, for oecd countries. the results show a positive correlation between co2 emissions and non-rec. alternatively, the more consumption of res, then the less co2 emissions. the results include an environmental kuznets curve (ekc) between urbanization and co2 emissions, indicating that with higher levels of urbanization, the environmental impact decreases. roca et al. (2001) studied the relationship between environmental pollution and economic growth utilizing the ekc hypothesis. ekc shows the positive relationship between income and environmental degradation in the short run, as the economy grows, while in the long run, this relationship reverses (i.e. u-shaped). however, the empirical evidence to support the hypothesis of a u-shaped relationship between environmental degradation and economic growth is still criticized. the following studies also are related with energy-growth nexus the gcc countires: al-mulali et al. (2019), salahuddin et al. (2015), salahuddin et al. (2018), hassine and harrathi (2017), saqib (2018), sbia et al. (2017). 3. theoretical background 3.1. types of res for gcc countries 1. solar: sunlight that can directly heat and light different types of buildings and plants. solar architecture technologies used are passive solar design and active solar air and water heating thermal power systems. 2. ultra efficient solar cells: regular solar panels usually convert less than 20% of solar energy into electricity, but this new technique doubles the power efficiency of solar devices. 3. wind: the heating and cooling of the earth by winds transformed into energy. wind technology can be land-based and/or offshore, using wind turbines. 4. hydropower: energy generated from moving (falling or running) water. hydropower plants use a pumped storage. 5. biomass: energy obtained from organic matter (ultimately from photosynthesis) through burning and digestion of wastes from municipal animals, humans, industrial, and agricultural sources. biomass can be used to heat water, producing steam that drives turbines, as in traditional power plants. 6. geothermal: energy generated from hot dry rocks and high enthalpy sources. 3.2. renewable energy and its barriers in gcc countries many countries, especially gulf countries, try to use renewable energy as a substitute for conventional fossil fuels. despite the new technology benefits and effectiveness, its application faces many challenges and obstacles. government policies, public awareness, poor knowledge, lack of political support, and cheap oil and gas prices are some of the structural barriers to the use of res. additionally, dust, heat, and humidity comprise major environmental obstacles for such energy generating technologies. according to wee et al. (2012), the union of concerned scientists classified barriers to res into four categories. first, commercialization ses and baseless tax when comparing res and other energy sources create a barrier. the mbarriers exist as the new technologies compete with traditional ones. subsidies that display price biaarket is not reflecting the social cost, and there is insufficient information about res. the cost of res is a major concern to most governments. fossil fuel costs influence the cost of electric power and have affected the market price and consumption of res. many legislations and plans are employed to minimize the gap between the prices of fossil fuels and res by applying certification or tax refunds. on the other hand, even though some res are expensive, they are more attractive when considered in the context of volatile fossil fuel prices. 3.3. the negative impact of fossil fuels on the environment conventional energy sources are limited in quantity and severely harmful to the environment. according to the us scientific advisory panel (2018), the burning of fossil fuels was responsible for 79% of us ghg emissions in 2010. atmospheric co2 has increased by nearly 30%, and the average global temperature has risen by 0.3 (0.6°c) in recent decades (chakraborty et al., 2000). many studies, scholars, and authorities, such as the international energy agency, explained that the burning of fossil fuels releases carbon dioxide and other ghgs into the atmosphere and is most hazardous to humans and the environment. kasem and alawin: exploring the impact of renewable energy on climate change in the gcc countries international journal of energy economics and policy | vol 9 • issue 6 • 2019 127 according to the un intergovernmental panel on climate change report (ar6 climate change 2021: impacts, adaptation and vulnerability), it is evident that climate change causes many natural disturbances worldwide, such as melting ice caps and an increasing number of extreme weather events. furthermore, it is anticipated that 75-200 million people are at risk of flooding by coastal storm due to a mid-range climate change. a sea level rise of 40 cm is predicted by the 2080s. 3.4. the negative impact of fossil fuels on human health many researchers and studies illustrate the effect of climate change on human health. mukhopadhyay and forssell (2005) concluded that changes in the broad-scale climate system would affect human mortality and morbidity, due to extreme heat and a higher level of air pollution. patz et al. (2005) found that 40-60% of acute respiratory infections are due to environmental problems. they concluded that, as the current consumption of fossil fuels is expected to increase 120% by the year 2020, more than 6.34 million people will die per year in developing countries due to emissions concentrations of particulate air pollution. they reported that carbon monoxide is an extremely toxic gas and the source of photochemical smoke. smith et al. (1999) assert that climate change in the form of heat waves, floods, and drought can lead to sunburn and melanoma. they add that climate change is primarily responsible for causing heat stroke, drowning, and gastrointestinal diseases. therefore, ghg emissions must be reduced by 60-70% to maintain the atmosphere and limit the harmful effects to the ecological system. 3.5. gcc countries’ approach to environmental sustainability gcc countries experienced a significant growth and development of infrastructure. in parallel, the electricity and water desalination sectors, which depend on oil and gas, face remarkable growth as well. the consumption of electricity in gcc countries has increased by 12.4% from 2005 to 2009 with an average 3.15% annually. the average watts per person of 1149 in 2005 in the gcc countries was already almost three times the world average of 297 watts per person (mondal and khalil, 2012). because misuse of fossil fuels to generate electricity and sea water desalinization increase ghgs, the gcc countries need to enforce progress in reducing carbon emissions. gcc countries are among the top 25 emitters of carbon dioxide per capita, contributing 2.4% of ghg emissions per capita worldwide. the gcc countries planned to mitigate carbon emissions and other environmental issues by signing the kyoto protocol treaty (united nations, 2006). these agreements, in alignment with the gcc environmental policies, encourage and support the usage of res locally to limit harmful emissions and reduce the negative effects of climate change. therefore, the gcc governments, along with the private sector and the general public, cooperated to shift from being merely oil producers into res producers. they also stated the financial, technological, and ecological benefits and costs from such projects (united nations, 2006). saudi arabia and the uae have inadequate potential (2.5-4.5 m/s) for wind power, but bahrain, kuwait, oman, and qatar have at least moderate opportunities (5-7 m/s). the conditions for solar energy potential in the gcc are among the most favourable globally (reiche, 2010). many activities support res application. for example, king abdul-aziz city for science and technology in saudi arabia conducts special research on solar energy and funds projects for res technologies, following similar initiatives in the us and germany. the kuwait institute for scientific research, and the middle east desalination research center are successful examples of solar cooling system installations. the oman government supports omani manufacturers and industries in utilizing re sources. qatar joined the united nations conference on environment and development, established a link among different channels of renewable energy technologies through an international database, and encourages qatari colleges and universities to conduct re research. as organization of the petroleum exporting countries members, the gcc countries pledged $750m (us) to fund carbon capture and research (copenhagen summit report, 2009). 3.6. wind and solar energy sources in the gcc the environment of the gcc countries is well-suited for re, due to unlimited, free solar and wind resources. the gcc countries experience a high level of solar radiation exposure during the daylight hours, and approximately 1,400 hours per year of full load of high-speed wind. solar radiation levels throughout the gcc are greater than levels of solar radiation in areas where there are solar photovoltaic and solar thermal technologies. the full load of wind enables the use of wind power generation technologies (aloughani, 2015). the development of solar energy is possible due to the daily average of nine hours of sunshine, low levels of rainfall, low cloud cover, and spacious lands (about 98.3% empty deserts). in terms of generating economically feasible wind energy, the average speeds across the gulf region lands are in the range of only 4.5-5.5 m/s. the most favourable site for wind is along the red sea coast to the south (aloughani, 2015). uae and qatar are the leading gcc countries in utilizing res. additionally, the three wind turbines that are expected in bahrain will help generate 15% of its energy needs (alnaser and alnaser, 2009). due to the high cost of the new res technology, the involvement of the private sector, supported by taxes and customs exemptions, along with the involvement of public and governmental authorities is essential. financial supports in the form of subsidies, lands for installation, and the operation of re generating plants are required. 3.7. challenges to the implementation of re in gcc cost is the first challenge to implementing re in gcc countries. high cost differentials make res unable to compete with conventional power generation, because water, fuel, and electricity are heavily subsidized. at the same time, low electricity costs fail to incentivize consumers to efficiently use energy. moreover, scarcity in land endowments in qatar and bahrain increase costs for res. kasem and alawin: exploring the impact of renewable energy on climate change in the gcc countries international journal of energy economics and policy | vol 9 • issue 6 • 2019128 regional environmental conditions impede the implementation of re in the gcc countries. direct solar radiation is reduced due to dust and weak performance of the concentrating solar power system due to high humidity. infrastructure regulations limit re implementation; grid-tied res systems are not permitted in some countries yet. in addition, most grids are not well-equipped to handle the dynamics of solar energy systems. two related impediments to re implementation are public awareness and knowledge. lack of public awareness and understanding of climate change and its negative implications deter the implementation of re. data on the actual performance of solar systems, including weather data, are limited. additionally, limited r&d resources to develop and adapt solar technology to the exceptional climate circumstances impede the implementation of re. the res industry requires qualified expertise, technicians, and designers. there are several research institutes in the gcc, but research outputs are slow and still ineffective. the current legislation and regulatory framework in the gcc countries is another challenge to re implementation. despite some successes in the field of res, there are still some limitations due to national policy framework strategies and a lack of national policy strategies to promote res. public/private initiatives for res development can drive direct foreign investment in res to the region. currently, these programs are inadequate; therefore, limiting investment in res in the gcc countries. 4. empirical study identifying the relationship between renewable and non-rec and emissions is worth an academic investigation. numerous studies have dealt with the relationship between energy consumption and pollutant emissions. these studies have been performed in different countries, various modelling methods, and findings. however, to the best of researchers’ knowledge, only a few studies have investigated the relationship between energy consumption and co2 emissions. 4.1. methodology and datasets this analysis is conducted to investigate the relationship between energy consumption and co2 emissions. in this study, an econometric model is proposed using panel data of the gcc states between 1998 and 2015. the estimated model is carried out to examine the relationship between several independent variables and co2 emissions using the pooled ols procedure. all data are obtained from the world development indicators (wdi) online database. all the variables are transformed to logarithms for the purpose of the analysis. many empirical works address the issue of co2 emissions empirically across different countries using different methods, but very few researchers capture the same issue for the gcc countries. therefore, this paper is following the recent empirical literature of sulaiman, et al. (2013), using the same hypothesis from their research and expanding on it. this framework contributed to a better understanding of the factors that could significantly affect co2 emissions in the gcc region and allowed for measurement of the impact of rec on co2 in gcc countries. the main restrictions in the study are data limitations. it is possible to test the long-run relationship between co2 emissions, economic growth, and the rest of the variables in a linear function. the equation is structured by a dependent variable and four independent variables, and the model is estimated through the following equation, using the pooled ols method: eit = β0 + β1 gdpcit + β2 recit + β3 rfwit + β4 elpit + εit. (1) where e represents co2 emissions in metric tons per capita. carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. they include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring. (gdpc) represents real gdp per capita. (rec) represents rec. it is the share of renewable energy in the total final energy consumption. (rfw) represents renewable internal freshwater resources per capita (cubic meters), which refer to resources like internal river flows and groundwater from rainfall. (elp) represents electric power consumption in kilowatts per hour per capita. electric power consumption measures the production of power plants and combined heat and power plants less transmission, distribution, and transformation losses, and own use by heat and power plants. εt is the standard error term. twumasi (2017) finds a positive correlation between gdp and co2 emissions. therefore, we expect to have a positive effect between gdpc and co2 emissions. on the other hand, renewable energy leads to decreasing co2 emissions, so the expected signs of the coefficients related to rec and rfw variables are negative. finally, the elp coefficient is expected to be positive. initially, equation 1 is examined using the pooled ols across the gcc countries without taking heterogeneity into account. then, the equation is examined using random effect model and fixed effect model. so as to decide the more proper model, the hausman test is conducted to determine the more proper approach. according to the hausman test, the fixed effect model is the best model. 4.1. data descriptive the data included in this paper cover the six gcc countries and are obtained from reliable sources. the data are obtained from the world bank through wdi. wdi are a collection of indicators compiled from officially recognized international sources. the world bank data present the most current and accurate global development data available and include national, regional and global estimates. data for gdp per capita is measured in current local currency. 5. empirical results the basic model is estimated by the pooled ols method. coefficients varied in significance level, magnitude, and expected signs. the results of that model appear in table 1. kasem and alawin: exploring the impact of renewable energy on climate change in the gcc countries international journal of energy economics and policy | vol 9 • issue 6 • 2019 129 according to table 1, the results show that gdpc is statistically significant at 1%, indicating that there is a correlation between gdpc and co2 emissions. the magnitude and positive sign suggest that for a 1% increase in gdpc, the co2 emissions will increase by 17.2%. moreover, this finding is consistent with our expectations. the estimated coefficient for rec is also statistically significant but with negative sign. this coefficient suggests that for a 1% increase in rec, the co2 emissions will decrease by 41.16%, leading to less ghgs. this result is also consistent with our theoretical expectations and is consistent with sasana and putri’s (2018) findings for fossil energy consumption and rec. on the other hand, renewable internal freshwater resources flow (rfw) is statistically insignificant, indicating that there is not a statistically significant relationship between rfw and co2 emissions. finally, elp is statistically significant with a positive sign. the magnitude of the coefficient suggests that for a 1% increase in elp, co2 emissions will increase by 60.14%. the result is consistent with theory. the hausman test is conducted to select the proper approach for this study. it shows that the p-value is significant at 2%. therefore, the null hypothesis of random effect can be rejected, and the fixed effect model is used for estimations. table 2 shows the results of the fixed effect and the random effect models. according to the fe model, gdpc gave the unexpected sign, that is higher economic growth causes a reduction in co2 emissions. this result is against the finding of twumasi (2017). this could be interpreted as higher income encourages governments to work towards adopting new methods that reduce co2 emissions. rec is statistically significant across the gcc countries and has a negative sign. the negative sign for the rec coefficient suggests that with more renewable energy utilization in the gcc, the co2 emissions to the atmosphere will be reduced. on the other hand, rfw is shown insignificant, which means it has no relationship with the co2 emissions variable. elp is found to be significant with a positive relationship with co2 emissions as theoretically expected. more electrical power consumption leads to a higher level of ghgs. 6. conclusion renewable energy is an effective tool to mitigate climate change, and the gcc countries support efforts to address climate change and try to implement efficient policies and strategies to fight it. this study explains that the energy sector in the gcc countries is the main contributor to co2 emissions, which is the major component of ghgs. this research explores the impact of multiple variables on co2 emissions, underscoring the importance and necessity of considering reform and regulations to minimize energy consumption. abundant renewable resources, along with high technology adoption, will support the renewable energy business in the gcc countries. using pooled ols regression analysis, this research finds that res contribute in reducing the carbon dioxide emissions. the results indicate that gdp per capita, rec, and electrical power consumption have a statistically significant impact on co2 emissions in the gcc countries. similar results were found by the fe model, except that gdpc gave the opposite sign. this proves this variable could possibly have different effects as explained earlier. further studies are crucial to determine this issue. references al-mulali, u., tang, c.f., tan, b.w., ozturk, i. (2019), the nexus of electricity consumption and economic growth in gulf cooperation council economies: evidence from non-stationary panel data methods. geosystem engineering, 22(1), 40-47. alnaser, w.e., alnaser, n.w. (2009), solar and wind energy potential in gcc countries and some related projects. journal of renewable and sustainable energy, 1(2), 22301. aloughani, m. (2015), renewable energies management strategy challenges in the arabian gulf countries. doctoral dissertation. london: brunel university. besha, p. (2011), economic growth plus rural development: an examination of china’s solar power policies. georgia institute of technology. 2011 atlanta conference on science and innovation policy. chakraborty, s., tiedemann, a., teng, p. (2000), climate change: potential impact on plant diseases. environmental pollution, 108(3), 317-326. gastli, a., armendariz, j. (2013), challenges facing grid integration of renewable energy in the gcc region. in: eu-gcc renewable energy policy experts’ workshop. abu dhabi, uae: gulf research center. p1-20. hassine, m.b., harrathi, n. (2017), the causal links between economic growth, renewable energy, financial development and foreign trade in gulf cooperation council countries. international journal of energy economics and policy, 7(2), 76-85. ley, d. (2017), sustainable development, climate change, and renewable energy in rural central america. in: evaluating climate change action for sustainable development. cham: springer. p187-212. luttenberger, l.r. (2015), the barriers to renewable energy use in croatia. renewable and sustainable energy reviews, 49(c), 646-654. mas’ud, a.a., wirba, a.v., alshammari, s.j., muhammad-sukki, f., abdullahi, m.a., albarracín, r., hoq, m.z. (2018), solar energy potentials and benefits in the gulf cooperation council countries: a review of substantial issues. energies, 11(2), 372. mathiesen, b.v., lund, h., karlsson, k. (2011), 100% renewable energy systems, climate mitigation and economic growth. applied energy, 88(2), 488-501. table 1: pooled ols regression model (n=1660) variables coefficients standard error t-statistics p-value gdpc 0.1723141 0.0044151 39.03 0.000 rec –4.116207 0.1862659 –22.1 0.000 rfw –0.0001292 0.0028706 –0.04 0.964 elp 0.6014481 0.0103708 57.99 0.000 constant –4.099764 0.0994582 –41.22 0.000 r-squared 0.7815 ols: ordinary least square table 2: fixed effect model (n=76) (5% significance level) variables coefficients standard error gdpc −0.1015606 −0.0089469 rec −5.233155 −0.3733545 rfw 0.0013493 −0.0014587 elp 1.103242 −0.0280573 constant −5.982706 −0.2214249 r-squared 0.5773 kasem and alawin: exploring the impact of renewable energy on climate change in the gcc countries international journal of energy economics and policy | vol 9 • issue 6 • 2019130 mondal, a., khalil, h.s. (2012), renewable energy readiness assessment report: the gcc countries. masdar, uae: masdar institute. mukhopadhyay, k., forssell, o. (2005), an empirical investigation of air pollution from fossil fuel combustion and its impact on health in india during 1973-1974 to 1996-1997. ecological economics, 55(2), 235-250. patz, j.a., campbell-lendrum, d., holloway, t., foley, j.a. (2005), impact of regional climate change on human health. nature, 438, 310-317. poudineh, r., sen, a., fattouh, b. (2016), advancing renewable energy in resource-rich economies of the mena. oxford: oxford institute for energy studies. raouf, m.a. (2008), climate change threats, opportunities, and the gcc countries. vol. 12. washington, dc: the middle east institute, policy brief. p1-17. reiche, d. (2010), energy policies of gulf cooperation council (gcc) countries-possibilities and limitations of ecological modernization in rentier states. energy policy, 38(5), 2395-2403. roca, j., padilla, e., farre, m., galletto, v. (2001), economic growth and atmospheric pollution in spain: discussing the environmental kuznets curve hypothesis. ecological economics, 39(1), 85-99. saif-alyousfi, a.y., md-rus, r., mohd, k.n.t. (2018), oil price and banking sectors in gulf cooperation council economies before and after the global financial turmoil: descriptive analysis. international journal of energy economics and policy, 8(6), 89-101. salahuddin, m., alam, k., ozturk, i., sohag, k. (2018), the effects of electricity consumption, economic growth, financial development and foreign direct investment on co2 emissions in kuwait. renewable and sustainable energy reviews, 81, 2002-2010. salahuddin, m., gow, j., ozturk, i. (2015), is the long-run relationship between economic growth, electricity consumption, carbon dioxide emissions and financial development in gulf cooperation council countries robust? renewable and sustainable energy reviews, 51, 317-326. saqib, n. (2018), greenhouse gas emissions, energy consumption and economic growth: empirical evidence from gulf cooperation council countries. international journal of energy economics and policy, 8(6), 392-400. sasana, h., putri, a.e. (2018), the increase of energy consumption and carbon dioxide (co2) emission in indonesia. vol. 31. edp sciences e3s web of conferences. p01008. sbia, r., shahbaz, m., ozturk, i. (2017), economic growth, financial development, urbanisation and electricity consumption nexus in uae. economic research-ekonomska istraživanja, 30(1), 527-549. scientific advisory panel. (2018), environmental progress and renewable energy. united states: environmental protection agency (epa). shafiei, s., salim, r.a. (2014), non-renewable and renewable energy consumption and co2 emissions in oecd countries: a comparative analysis. energy policy, 66, 547-556. smith, k.r., corvalán, c.f., kjellstrom, t. (1999), how much global ill health is attributable to environmental factors? epidemiologybaltimore, 10(5), 573-584. sulaiman, j., azman, a., saboori, b. (2013), the potential of renewable energy: using the environmental kuznets curve model. american journal of environmental sciences, 9(2), 103-112. tugcu, c.t., ozturk, i., aslan, a. (2012), renewable and nonrenewable energy consumption and economic growth relationship revisited: evidence from g7 countries. energy economics, 34(6), 1942-1950. twumasi, y.a. (2017), relationship between co2 emissions and renewable energy production in the united states of america. archives of current research international, 7(1), 1-12. united nations. (2006), framework convention on climate change. bonn, germany: united nations. wee, h.m., yang, w.h., chou, c.w., padilan, m.v. (2012), renewable energy supply chains, performance, application barriers, and strategies for further development. renewable and sustainable energy reviews, 16(8), 5451-5465. . international journal of energy economics and policy | vol 8 • issue 6 • 201870 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(6), 70-79. the electricity security in south africa: analysing significant determinants to the grid reliability benedict belobo ateba*, johannes jurgens prinsloo north west university south africa, school of governance and business, south africa. *email: atebabenedict@yahoo.com received: 10 july 2018 accepted: 29 september2018 doi: https://doi.org/10.32479/ijeep.6864 abstract south africa has been suffering from low electricity supply for decades now, dating back to the first occurrence during 1983. another crisis struck by the fall of 2007, which shocks from the crisis still affect the economic growth. the country’s fossil fuels, which serve as a major contributor to its electricity generation, are depleted by 1% every year. other determining variables such as increases in domestic consumption and industrial intensity as domestic and industrial consumption rise, increase in coal prices, drop in the production volumes of coal, depreciation in machinery remain continuous dangers to the future reliability of supply of the grid. this has led to inflation of consumer prices, whilst end users’ future access to adequate electricity supply is not guaranteed. this paper aimed at determining the steadfastness of the south african electricity grid in meeting consumers’ demands. a quantitative research design was employed. a multiple time series research method utilising secondary data from key determining variables to electricity supply from the first quarter of 1998 to the last quarter of 2015 was employed in this study. the eviews statistical software was employed to obtain regression probabilities through the multiple ordinary least square model specifications. the engle-granger approach was used to establish whether or not co-integration exists between the independent and the dependent variables. the co-integration analysis reflects that there is a significant long-term relationship between the independent and the dependent variables. keywords: electricity security, supply determinants, grid sustainability jel classification: q47 1. introduction winkler (2006a. p. 23) notes that energy has been a very instrumental feature in shaping the south africa economy. supplying consistent electricity to the mining industry, to boost economic growth was the primary supply objective of the public sector throughout the early quarters of the twentieth century. the intensive dependence on the imported energy resources raised concerns about energy security during the 1950s. the government of the time initiated projects to meet the demand for electricity by constructing massive power stations in the 1960s and 1970s. the previous abundant electricity reserves are gradually getting exhausted. a major concern as viewed by winkler and marquand (2009) is that international standards currently rank the south african economy extremely energy intensive. hameed and khan (2016) say electricity is prime on the hierarchy among energy resources of priority for every modern economy. it is essential for an economy to generate and distribute a sufficient supply of electricity if sustainable economic growth is to be attained (kohler, 2013. p. 5). ojeaga et al. (2014) states that issues about energy sustainability should be of paramount importance to every economy since it mostly determines the possibility of economic growth and productivity. kohler (2013. p. 5) alludes that the availability and reliability of energy is an important determinant of economic productivity. conceptualising energy security differ depending on the perspective taken, ranging from the international to regional, national to local, and also differ across stakeholders such as industry, communities and individuals (chester, 2010). this paper views that, it is of core importance to evaluate the security of electricity supply in south africa, this journal is licensed under a creative commons attribution 4.0 international license ateba and prinsloo: the electricity security in south africa: analysing significant determinants to the grid reliability international journal of energy economics and policy | vol 8 • issue 6 • 2018 71 considering recent low supplies caused by influential determinates to electricity production and supply. hedden (2015. p. 7) agrees that south africa’s electricity demand currently exceeds supply. von keltehodt and wocke (2008) note that if electricity demands exceed supply, the cost and the unreliability of electricity supply increases. hameed and khan (2016) assert that an electricity grid is under siege if production potentials are not comparative to the constantly increasing demands of the industrial and domestic sectors. this paper seeks to call attention to the responsibility of supply security in the electricity market and to demonstrate the most effective parameters that can be incorporated as the standards for measuring the security of supply. the problem in this paper relates to electricity security in south africa that is threatened by elements that significantly determine electricity production and supply. the increasing pressure of demand over supply reflects the unsustainability of over-reliance on coal technology reflecting a potential threat to future electricity security. there is a limited policy advancement towards significant electricity security in south africa. 2. literature review the following section discusses energy security, south africa’s grid security and factors that have been considered as influencing variables. 2.1. energy security knox-hayes et al. (2013) agree that security and reliability of energy have become increasingly important in energy policy debates, driving an agenda towards a change in energy systems. chester (2010) notes that there has been little discussion of the notions which underpin the meaning of the term “energy security.” as a result, it is often referred to as the threats to a continuous supply of energy resources, failing infrastructure and depletion of energy resources. consequently, these risks lead to price hikes and shortages, initiating a negative impact on demand. recently, researchers in the field of energy have been creating awareness on the dangers of poor energy security. burgess and nye (2008) agree that a diminished “energy security” is primarily experienced through fuel deficiencies resulting in electricity cuts, as well as increases in the price for power. glyn et al. (2014) conducted a study on the energy security of ireland and revealed findings that ireland’s electricity grid is very vulnerable due to: import dependency by 88% of its energy requirement, it’s limited energy mix and wobbly pricing. glyn et al. further forecast that ireland will encounter possible disruptions in electricity supply if strategic implementations are not established soon enough. demski et al. (2014) say in the united kingdom (uk), there is a proposal from the general public for a change in the energy system that is solely dependent on gas to more advanced 21st century energy generation technologies. high concerns regarding the dependence on fossil fuels, high imports of energy resources to more immediate issues ranging from insufficient reserves to meet demand and price increases has relatively low concerns for possible disruptions to electricity supply. reverting to electricity security, raillon (2010. p. 2) notes that there is no common definition of electricity supply security. electricity supply security can be attributed to the capability of an electricity grid in meeting up the electricity needs of final consumers with a defined quality and at a transparent and costoriented price. in line with afore context, electricity security is the capability of an electrical system to supply electricity to consumers with a definite level of continuity and quality in a sustainable manner, according to generally acceptable delivery standards (gábor and lipponen, 2006. p. 6). 2.2. south african electricity grid security clark et al. (2005. p. 29) maintain that the effective provision of electricity services to consumers significantly depends on price and supply reliability. thus, security of electricity is threatened if the physical quantity of available electricity is insufficient and prices that are not affordable for consumers. clark et al. (2005. p. 13) emphasise that assessing and improving on the security of supply to meet future demand has always been a primary agenda for power sectors reform in south africa. wilson and adams (2006. p. 5) note that the rate of growing insecurity of supply in the south african electricity industry is a major challenge to suppliers. wilson and adams allude that a major threat to supply security is the inadequate generation of required capacity that is secure enough to deliver power to all regions of the country. ojeaga et al. (2014) extensively evaluate constraints to energy security ranging from the availability of natural resources for a generation, size of regions, regional temperature level, income, population density, cost of accessing energy, consumption demands both domestic and industrial and spend on technology. threats that were identified as a matter of concern to energy security include; the cost of accessing energy, availability of natural resources for a generation, domestic and industrial electricity consumptions. in accord with newberry and eberhard (2008. p. 10) neither the department of energy (doe), eskom nor national energy regulators south africa (nersa) has ever critically looked into the country’s supply security nor set standards establishing a procedure for measuring electricity security in south africa. wilson and adams (2006. p. 6) state that, in the past, eskom mostly utilised the criterion of determining the cost of unserved energy, which is assumed to represent the value to customers of system security. previously, this approach has been widely used in most countries but is now recognised as not being an adequate basis for determining power system security. wilson and adams (2006. p. 5) have the viewpoint that variables that impact on the reserve margin is probably the most appropriate deterministic criterion to factors that pose a threat to the south african grid security. determining the security of an electricity grid involves the complexity of assessing the proper functioning of its independence to its dependent factors. the focus of this paper is about factors that cause a significant interruption to electricity supply with a material consequence. there might be many aspects that affect ateba and prinsloo: the electricity security in south africa: analysing significant determinants to the grid reliability international journal of energy economics and policy | vol 8 • issue 6 • 201872 the security of electricity supplies in south africa. however, this paper focuses primarily on aspects of fossil fuel, supply price, consumption growth and depreciation on machinery. that is not to say other elements are inferior, but to specify that, after an extensive review of the literature, the mentioned variables significantly determine the occurrence of a threat to the south africa electricity grid. 2.3. coal energy focusing mainly on coal electricity generation and not from all energy sources, in general, is because the energy sector is too diverse for comparative analysis. south africa’s electricity generation is 95 percent dependent on coal. an intensive investment in coal energy assets has historically been the country’s electricity development path (kohler, 2013. p. 2). antin (2013. p. 6) posits that the south african mining industry seems well-established, but a closer inspection reveals severe productivity issues. prevost (2003. p. 102) points out that the coal sector has reached its threshold and will soon experience stagnation. coal production is at a recession as output and exports steadily decrease. prevost alluded that 2020 is the “target year” when most coal factories might have shut-down and reserves will be close to attaining exhaustion. british petroleum (bp) statistical review of world energy (2005. p. 30) version estimated south africa’s coal reserve is at 5.4% of the world’s total, matching up the department of minerals and energy evaluation of 31 metric tons (mt) by 2005. bp statistical review of world energy (2016. p. 30) state that the south african coal reserves are constantly at a decrease, with current levels estimates at 3.4% of the world’s total. fourie (2009. p. 1) stated that, despite that the waterberg coalfields are expected to cater for future crisis, it is dangerous to rely on, since estimates of its total quantity of resources are highly uncertain as it has been relatively under-explored. jeffrey (2005) and fourie et al. (2009. p. 28-29) maintain that the current estimations of the waterberg fields predict low productivity. it is also endangered by some geological setbacks from past tectonic activities with no guarantee of effective exploitation of the waterberg coal deposits. baxter (2015. p. 19) points out that a decline in productivity adds to the headwinds of the industrial progress as a capital injection from activities such as coal exports dropped due to reduced volumes of production. antin (2013. p. 1) highlights that the mining industry has undergone a major unrest since the beginning of the 2008 global financial crisis, with workers inter-alia demanding better wages. antin posits that 2012 experienced a fast decreasing productivity prior to turmoil by mineworkers. altman (2013. p. 6) notes that poor management of available coal stocks adds to the challenges to attaining coal adequacy for the electricity industry. mayet et al. (2012. p. 3-4) view that eskom believes it can use coal resources as a competitive advantage to improve production capacity failed to consider the implications of future coal prices (cps). prices of coal at present are on a constant increase and very unstable. there is anticipation that situations will get worse in the future. mayet et al. (2012. p. 4) says pricing is furthermore challenged by the competition of the broken hill proprietary billiton group, which controls the largest coal produced in south africa. an estimated us$800 billion is required by eskom to acquire billiton coal deposits. a pricing agreement does not seem to entirely reflect the interests of the public as eskom’s agenda is towards protecting its monopoly as primary administrator to energy resources. in south africa, cps are mostly a 25–30% of the electricity consumer price since cp variations are highly reflected in the electricity production cost (inglesi, 2010). 2.4. consumer price of electricity inglesi and pouris (2014. p. 1) say there have been continuous debates on whether increases in electricity tariffs will affect the energy sector and if it is necessary. altman (2013. p. 6) maintains that there are similar consistent debates as to whether south africa’s protocol for the consumer electricity price increase is effectively aligned to global standards. kohler (2013. p. 5-6) states that south african electricity regulators technically determine electricity prices, instead of the forces of demand and supply in the market. kohler further views that the absence of an appropriate pricing determination instrument is likely to cause imbalances in the demand and supply, particularly in cases when regulators are not well experienced in responding to market signals. eskom (2012. p. 5) states that the south africa pricing technique follows a multi-year price determination (mypd), in which eskom applies to nersa for a periodic electricity price adjustment plan. altman (2013. p. 6) agrees that the electricity selling price should reflect its full production cost. alternatively, the ongoing proposals for multiple inflation type increases that are currently discouraging global investment in south africa, is not realistic. thopil and pouris (2013) performed an empirical research study of the state of electricity consumer price in south africa and the following outcomes were ascertained: • the industrial sector is under-priced while the residential sector suffers immensely from high percentage increases. this was questionable as to why price increases are not equally executed on both sectors considering that their benefits are not proportionate. • multi-year pricing determination (mypd) has been seriously criticised to be a nonpragmatic pricing technique. mypd has a history of unfairness traced from the prevailing electricity pricing inequality in south africa. thopil and pouris suggest that a more appropriate standard that would ensure transparency in all sectors should be introduced. mayet et al. (2012. p. 5) confirm eskom agrees that the mypd makes it too complicated to establish a 100% precise cross-subsidy plan from industrial to residential users. such finding is proof enough to introduce a new tariff structure that will guarantee electricity accessibility to the poor. mayet et al. allude that eskom’s decision to apply the mypd approach, instead of exploring a more appropriate and reliable alternative can be attributed to eskom’s managerial convenience policies. alternatively, literature points out that price is a very complex variable to conclude electricity tendencies in south africa. blignaut et al. (2014) conducted a comparative investigation to assess the elasticity of electricity price for years, 2002–2011 in south africa. outcomes from empirical research found a ateba and prinsloo: the electricity security in south africa: analysing significant determinants to the grid reliability international journal of energy economics and policy | vol 8 • issue 6 • 2018 73 statistically insignificant elasticity for periods pre-2007 agreeing with over 90% of similar studies. alternatively, post–2007 results were statistically significant across 9 out of 11 sampled sectors. policy implications point out that tariff restructuring might influence future consumer behaviour and might be a significant threat to electrification potentials. inglesi and pouris (2014. p. 1) carried out a similar investigation evaluating the causality of price and income on electricity demand in south africa with similar findings. inglesi (2011) view that price is becoming relatively weaker over the years as a perfect explanatory variable for electricity consumption tendencies. a consensus regarding the significance of electricity price as a determinant to electricity tendencies in south africa is currently in a dilemma due to conflicting findings from researchers. 2.5. consumption growth marquard et al. (2008) note concerns on the implications of the steady increase in population growth. these increases result in roughly 350 000 new south african households per year. the annual growth in household formation is a primary challenge on the electricity grid. hameed and khan (2016) agree that there is a significant positive relationship between population growths, which consequently caused a drastic change in electricity consumption. the south african energy efficiency report (2011. p. 2) points out that south africa has high energy consumption per capita of 2.7 averages, compared to the regular global consumption of 1.8 average. energy consumption between 1990 and 2002 increased by 1.1% yearly; after 2002, increases have been at a very rapid rate of 4% yearly. kohler (2013. p. 2) highlights that there has been a constant growth in electricity consumption and intensity in south africa from 1971, implying that the south african electricity efficiency instruments are not implemented effectively based on the required international standards. inglesi and blignaut (2011. p. 4) maintain that the constant increase in grid electricity consumption in south africa is prior to major transformation programmes. according to kohler (2013. p. 2), electricity transformation programmes such as historically low prices initiated a substantially low electricity efficiency environment relative to other countries. winkler and marquand (2009) say electricity efficiency implementation in the industrial sector is still significantly poor and considerably lower than global averages. hedden (2015. p. 5) says the council for scientific and industrial research modelled and forecast that the energy intensity of the south african economy will decrease over time. the underlying logic behind the model assumption is on the basis that south africa is transitioning away from energy-intense industries to a more service-oriented economy. hedden disagrees that it is not completely factual since as the country demands for electricity increases as well. this means that, even if the energy intensity of the country decreases, the size of the economy is also growing the overall energy consumption. 3. research methodology the research methodology of this paper was a quantitative research design. a quantitative design was the most appropriate approach because analyses had to take account of occurrences of behaviour between tested variables and to record correct answers and errors in quantity. the research technique was the multiple time series approach. schmidheiny (2016. p. 2) defines a multiple linear regression models as a linear relationship between a dependent variable and a set of explanatory variables. according to mohod (2012) the independent variable is the variable which researchers measure while the dependent variable is the assumed effect. data for the empirical investigation was collected from secondary sources. all data was retrieved from quantec south africa. the data gathering process involved obtaining time series data of sampled variables. data was categorised into 1 dependent variable (electricity production) and 4 independent variables (electricity price, cp, coal production, electricity consumption and depreciation of machinery). empirical research was affected by the non-availability of data for depreciation of machinery as scheduled to be part of the empirical research. the factor was eliminated from the empirical research since even an appropriate proxy could not be ascertained. data frequency was all on a quarterly basis for both the dependent and the independent variables. the study period was considered from the first quarter of 1998 to the last quarter of 2015. all variables produced 68 individual observations. the only exception was the electricity price with an observation of 63 since there was no data available from the first quarter of 1998 to the last quarter of 2002. information obtained was used to determine regressions’ effects of the dependents over the independent variable. the dependent variable (electricity production) was measuring the electricity supply security such as disruptions should production decline (grid reliability). the independent variables measured the impact on electricity production. the total number of observation occurrences accumulate to 471. 3.1. hypotheses the hypothesis is a good guess at the best answer to a question, based on the most reliable facts available (chesterman, 2008. p. 10). bulajic et al. (2012) assert that a hypothesis condenses the general focus of empirical research to aid research framework or model. a hypothesis is mostly designed to prove false than prove true because it is not possible to test all the viable combinations and conditions that a hypothesis can cover (bulajic et al., 2012). levine et al. (2008) agree that testing the significance of the null hypothesis is the most common method that is applied to a statistical inference research. to develop an effective and applicable model for the empirical research, hypotheses were developed to guide model construction by the following assumptions: 1. if the production of coal decreases, electricity supply capacity will decrease. 2. if electricity prices increase, electricity supply capacity will increase. 3. if cp increases, electricity supply capacity will decrease. 4. if the increase in consumption is not relative to production, supply capacity will decrease. 3.2. model specification the ordinary least square (ols) model was employed in performing linear regressions. varmuza and filmer (2009. p. 124) state that multiple linear regressions can utilise the ols model. a multiple ols model is denoted as follows: ateba and prinsloo: the electricity security in south africa: analysing significant determinants to the grid reliability international journal of energy economics and policy | vol 8 • issue 6 • 201874 yt=βo+β1x1t+β2x2t+β3x3t+β4x4t+εt (formula 1) concerning formula (1) indications represented are as follows: yt=dependent variable. βo=the intercept of the equation. β1-4=the slope coefficient of the independent variables. x1t-4t=the independent variable that is used to predict the dependent variable. εt=the error term. the error term. the slopes all convey information about the conditioned association between an independent variable and the dependent variable. conditioned association, for instance, means: β1 is the association between x1 and y1 holding x2-x4 constant. the model specification (causality between the dependent variable to independent variables) of this paper was then equated as: epvt=βo+β1eprt β2cvt β3cpt β4ecit+εt (formula 2) concerning formula (2) indications represented are as follows: epv=electricity production volumes. epr=electricity consumer price. cv=coal production volumes. cp=coal price. eci=electricity consumption intensity. βo=the intercept of the equation. β1-β4=the slope coefficient of the independent variables. ε =the error term or white noise. the error term includes other variables that can also influence on epv. t =the sampled period. the ols was seen to be the best suited and most robust model specification in acquiring the objective of this paper. 4. analyses and discussion the multiple time series was the analytical approach used in this paper. varmuza and filmoser (2009. p. 124) state that a multiple linear regression time series measures a single y variable with several x variables. a multiple time series analysis was superlative in conducting the research analysis as it simultaneously considers the dependent variable to a range of possible independent variables that can significantly affect the dependent variable. it was the most appropriate technique to effectively attain a reliable outcome to the objective of this paper. neuman (2014. p. 421) states that a very important element of the multiple regression is that it has been recognised by most time series researchers, as an effective approach in confirming the accuracy predictions between the independent or control variables over the dependent variable through the r-squared. the objective was to assess the level to which significant electricity production determinants are increasingly negatively affecting electricity security of supply in south africa. because all variables had their measurement, they had to be logged to make them all similar to avoid permeability. to draw an applicable and reliable conclusion to assumed hypotheses, different time series regression tests were performed. tests were performed in a systematic order as follows: unit root tests, model estimation tests, jansen cointegration, granger causality and the diagnostic tests. a summary of tests conducted is reflected in table 1. results were interpreted according to the outcomes from regressions. results were accurately interpreted to avoid any possibility of fallacy in the analysis. all the time series data tests as indicated were done strictly and all procedures followed. the p-value is the most important element from regression results. this is because it determines the probability of whether the null or the alternative hypothesis is to be rejected or not. performed tests seek for a p < 0.05 in order not to reject the null hypothesis. likewise, the alternative hypothesis is accepted if the p > 0.05. the rule is different for the normality and serial correlation and the heteroscedasticity tests (diagnostic tests). the diagnostic tests require a p > 0.05 to establish that regression residuals are normally distributed and not serially correlated. alternatively, residuals are considered to be abnormal distributed and serial correlated if results are <0.05. the p-values are marked as (*), (**) and (***) to denote significance levels at 10%, 5% and 1% respectively. it should also be noted that results were rounded up to three decimals. it should be noted that in the analysis process, sampled series were given individual codes to be able to identify variables during the analysis (model specification or appendix 1). 4.1. unit root tests according to westerlund and breitung (2013), a standard econometric empirical research requires testing the stationarity of data. a unit root test was conducted for all independent and dependent variables separately to determine their stationarity. the focus unit root test in this paper was the pp and the augmented dickey-fuller (adf) tests. adf (1981) modelled a protocol for testing stationarity by utilising logarithmic series at the 1st difference, denoted as: (lyt)=log (yt) (formula 3) the following hypotheses are assumed for the adf unit root test: h1: ly is non stationary against the. bento (2011. p. 3) says the adf has the potential to overcome the problem of autocorrelation frequently found in time series modelling. adf was estimated at no intercept or trend. however, the adf has encountered some insignificant criticisms. the pp was also utilised to establish reliability that, data are stationary. table 1: regression tests test categories test type unit root test phillip peron augmented ducker fuller estimations ols estimation residual test for co-integration ect causality diagnostic tests serial correlation normality heteroscedasticity stability test ect: error correction term ateba and prinsloo: the electricity security in south africa: analysing significant determinants to the grid reliability international journal of energy economics and policy | vol 8 • issue 6 • 2018 75 phillips and peron (1988) modelled a nonparametric approach to testing unit root for a wide range of data. this test uses fitted drift and time trend to determine between unit root stationarity and non-stationary in a model. the pp is conduct based on the following model: let {yt} be a time series generated by: yt=αyt-1+ut (t=1,2….) (formula 4) α=1 castro et al. (2013. p. 3) says the pp and the adf differ as the adf perform stationarity on residuals free of serial correlation. alternatively to the adf, the pp is utilised on models with weakly dependent errors. it was important to establish if the tested data series were stationary or non-stationary. it was important to utilise stationary data in the estimation of models to avoid spurious regressions. spurious regressions lead to spurious results that are misleading in terms of inferences drawn. results from unit root test are presented in table 2. both the adf and pp tests were conducted on each series. all conduct unit root test produced a stationary outcome at the 1st difference. the p-values from all series were below 0.05. the p-value results in the various unit root tests for all series confirmed positive at a 1% level of significance. thus, the null hypothesis that data are autoregressive (non-stationary) for each series against the alternative that each series is stationary was accepted. 4.2. ols estimation the ols estimation test is a test for co-integration in the ols model. the independent variables cp, coal volume (cv), electricity consumption intensity (eci) and electricity consumption price (epr) were tested over the dependent variable electricity production volumes (epv) to establish if the independent variables can influence the dependent variable. bento (2011. p. 3) points out that stationarity of data is the only requirement to implement an ols regression method (table 3). the outcome from regression reflects that a significant relationship exists between all the independent variables with the dependent variable. the results reflect that the hypotheses and model specification used in the investigation of the problem of the empirical research is reliable. outcomes from all independent variables produced a p < 0.05, with all series reflecting a positive outcome at a 1% level of significance. the regression analysis further confirmed reliability by obtaining a 97% r2. the results from the price of electricity reflect similarly to outcomes of blignaut et al. (2014) and inglesi (2011). the outcome from price was significant, confirming that price elasticity of electricity in south is becoming increasingly lower through the years and can consequently affect future electricity potential as consumers become very alert to the pricing of electricity. 4.3. co-integration on this paper, co-integration was performed through the engle granger ols non-stationarity tests. ssekuma (2011. p. 3) views that, it is faulty for econometric to accept differencing of ols series during unit root. it causes a material influence by reducing non-stationary series to stationary as opposed to if tested at levels. robert et al. (1987) point out that stationarity is precise when no deterministic component is attached to perform stationarity on a data series. engle and granger proposed a method which involved performing the adf test from ols estimation residuals. testing for co-integration on this engle-granger approach involved performing the adf tests on ols estimation residuals at levels, with the mackinnon critical values adjusted on variables to determined stationarity. the co-integration approach evaluates if is stationary. if stationarity exists, the ols estimator is said to be co-integrated. this approach for co-integration assumed the following expression: ut yt xt ^ ^ ^ = − −δο δ1 (formula 5) adf estimation obtains a p = 0.0002 and a t-statistic of −4.907166. results reflect that the independent variable and the dependent variable are highly co-integrated. this implies that there is long-term relationship between the dependent and the independent variables (table 4). 4.4. engle granger “error correction term” (ect) robert et al. (1987) point out that if two variables y and x are cointegrated, the ect should be defined between the co-integrating variables. co-integration and ecm verify if a long-run and short-run relationship exist between variables respectively. an elementary ect model is as follows: δyt=χ0+χ1δχ1−τ(ut-1)+εt (formula 6) the generated residual series derived from the the simple ols co-integration estimation are lagged to act as the ect. the ect, which is a symbol as 1 ,tu − is expressed as (yt-1−xt-1). the ect is only statistically significant when the coefficient is a negative and the p < 0.05. the ect measures reverse rate of adjustment to equilibrium following an exogenous shock (table 5). table 2: unit root test variables adf p-values pp p-values conclusion cp 0.0000*** 0.0000*** h0 is rejected cv 0.0001*** 0.0001*** h0 is rejected eci 0.0283** 0.0001*** h0 is rejected epv 0.0062*** 0.0001*** h0 is rejected epr 0.0000*** 0.0000*** h0 is rejected cp: coal price, cv: coal volume, eci: electricity consumption intensity, epr: electricity consumption price, epv: electricity production volumes table 3: ols estimations variables t-statistics p-value conclusion cp 19.67969 0.0000*** h0 is rejected cv 3.001454 0.0042*** h0 is rejected eci 2.086586 0.0419* h0 is rejected epr −2.278119 0.0269* h0 is rejected ols: ordinary least square, cp: coal price, cv: coal volume, eci: electricity consumption intensity, epr: electricity consumption price, epv: electricity production volumes ateba and prinsloo: the electricity security in south africa: analysing significant determinants to the grid reliability international journal of energy economics and policy | vol 8 • issue 6 • 201876 error correction was estimated to present short-term dynamics that exist between influencing factors and the grid. results from the ect regressor reflect that the model is balanced. the ect coefficient was found to be negative (−0.442332) and statistically significant with a p = 0.0009. the result reflects that the speed of adjustment on any shock by the dependent variables on the independent variables will be approximately 44%. this indicates that over 44% of the disequilibrium in the previous quarter is adjusted to their long-run equilibrium in the current quarter. after the ols estimation, a uni-lateral causality test was conducted to establish if the independent variables granger causes the dependent variables. h0 (null hypothesis) assumed that the independent variables do not granger cause or impact the dependent variable. regression outcome from eci, cv, cp and epr rejected with the aforementioned variables producing p < 0.05. thus, independent variables, eci, cv, cp, epr, test significance to have an impact on epv (table 6). 4.5. diagnostic test dalla et al. (2015. p. 1) state that it is customary to perform a diagnostic assessment to properties from data used for empirical research in time series modelling. brooks (2009. p. 43) brings to light that the diagnostic tests seek to assess the degree of fairness from regression outcomes. these tests require p > 0.05 to be considered significant. 4.5.1. normality test the jarque-bera (j-b) test was used in testing for normality. according to brooks (2008. p. 57) the j-b estimate normality through the skewness and kurtosis statistics. the j-b assumes that the null hypothesis is normally distributed against the alternative hypothesis that other distributions are present. referring to cameron (2005. p. 238), the j-b test combines the skewness and the kurtosis according to the following formula: j-b=n[(s2 /6) (k }]+ −{ )3 2 24 (formula 7) the generated residual series derived from the the simple ols cameron elaborated on the equation, is the sample size, the skewness and the kurtosis. if skewness slopes to the right or the left, then the distribution is not normally distributed. kurtosis measures how steeply values are rising to the most likely value in the distribution curve. according to gujarati (2004. p. 148) under the j-b test, if the computed p-value is sufficiently low, the alternative hypothesis should be accepted that residuals are not normally distributed. alternatively, if p-values are reasonably high, the normality assumption is not rejected. 4.5.2. serial correlation the serial correlation test provides evidence if error term values within sampled periods are systematically dependent (studenmund, 2011. p. 304). baltagi (2008. p. 92) warns that is biased in ignoring serial correlation if detected in analysed data. regression will provide required but unethical estimates if serial correlation is detected and ignored. the correlogram test was used in detecting serial correlation among data series. referring to nopiah et al. (2010) the correlogram test, aim at sensing the presence of serial correlation in a specified order in the autocorrelation tested lags. gujarati and porter (2009. p. 434) highlight that the advantage of the correlogram test is that it detects the presence of higher-order serial correlation. hypotheses developed in testing for serial correlation are: h0: ρ = 0 and h1: ρ ≠ 0. the hypothesis h0 denotes that no serial correlation exists while the alternative, h0, on the other hand assumed that there was serial correlation. data were tested for serial correlation because in general, econometrics established the ols is commonly inconsistent in the presence of lagged dependent variables and serially correlated errors. even though wooldridge (2006. p. 415) holds that most of such assumptions are false, it was necessary to test for serial correlation to prove the precision of coefficient estimates. 4.5.3. heteroscedasticity wooldridge (2009. p. 278) states that the test for heteroscedasticity investigates whether or not heterogeneity exists among estimates. baltagi (2005. p. 99) elaborates that the test assumes that disturbances from regressions are homoscedastic with the same variance across time and individuals. in this paper, the white’s cross section and the arch tests were used. studenmund (2011. p. 350) says the white test detects the heteroscedasticity by considering the squared residuals as the dependent variable when performing regression. the following hypotheses were developed: h 0 2 : σ σt = ( t h e n u l l h y p o t h e s i s a s s u m i n g homoscedastic errors) and h1: not equal for all t, (the alternative hypothesis assuming heteroscedastic errors). in agreement with asteriou and hall (2011. p. 127), the white’s cross-section test was employed in this study because it does not assume any determination of heteroscedasticity. table 5: ect results coefficient t-statistics p value −0.442332 3.523117 0.0009*** ect: error correction term table 4: engle-granger ols co-integration test description t-statistic p value conclusion adf test statistic −4.907166 0.0002*** h0 is rejected test critical values 1% levels −3.555023 5% levels −2.915522 10% levels −2.595565 ols: ordinary least square ateba and prinsloo: the electricity security in south africa: analysing significant determinants to the grid reliability international journal of energy economics and policy | vol 8 • issue 6 • 2018 77 all series acquired a p > 0.05 for the normality, serial correlation and heteroscedasticity tests respectively. thus, diagnostic results acquired a positive significance for tested series (table 7). 4.5.4. stability test brown et al. (1975), developed the recursive stability test for ols models under the following parameter: yt=xtbt+ut (formula 8) where, yt, is the observation on the dependent variable, xt, is a k × 1 column vector of non-stochastic repressors,bt is a k × 1 vector of regression coefficients,, is a disturbance term, with mean zero and variance σ_t^2. farhani (2012) alludes that the recursive value also estimates the level of stability significance at a 5% critical line benchmark. the test is referred to as the cumulative sum (cusum) of squares test, and it uses the sum of squared recursive residuals, as reflected by an estimation graph. it tests the null hypothesis under the assumption that the dependent variable “sm” follows a beta distribution with a mean, equals to independent parameters, e (sm) = [(m-k)/(t-k)]. the ols recursive stability test assumes a negative result if the constructed forecasting model is stable over the sample period and remain stable over the forecast period. if the model’s parameters are different during the forecast period than the sample period, the model estimation will be viewed as irrelevant regardless of how perfectly it was estimated. figure 1 reflects the recursive residual test. it is evident that none of the model’s parameters changed at one or more points in the sample period. results reflect that the regression model is stable over time because as t increases the recursive parameter estimates stabilise at level. a conclusion can be made that the stability of cp, cv, epr and eci is of crucial importance for consistent electricity supply. figure 2 reflects the significance level of the cusum estimation. the cusum test falls within the accepted critical value of 5%. results reflect that the model parameters are stable over the tested time periods. 5. conclusion and policy implications the empirical research of this paper was assessing the sustainability of the electricity grid in meeting the pressure of current and future demand. von keltehodt and wocke (2008) note that if electricity demands exceed supply, the unreliability of electricity supply increases. this paper has provided reliable evidence of the significant threats to the electricity security in south africa. the engle-granger co-integration test concurs that both the short and long-term relationship between the dependent variable and the independent variables. stability tests confirm that the tested independent variables, electricity price, cp, cv and increase in grid consumption have a consistent pattern to the dependent variable. causality test also confirms that the independent variables can cause an impact on the dependent variable. this has a direct consequence on electricity supply in general because as production falls, supply is adversely affected in high proportions. hameed and khan (2016) assert that an electricity grid is under siege if production potentials are not comparative to the constantly increasing demands of the industrial and domestic sectors. thus, clark et al. (2005. p. 29) concur the security of electricity is threatened if the physical quantity of available electricity is insufficient for consumers. considering that south africa is an energy-intensive economy, developing sustainable electrical energy frameworks should be a major element for strategic policymakers. the raison d’être behind this article was to encourage research on electricity security and to recommend applicable policy guidelines in attaining a secure electricity environment in south africa. it is acknowledged that initiative programmes have been established to ensure the security of electricity supply in south africa. however, initiatives are still to be effectively prioritised and applied. policy makers are still to develop reliable and applicable dynamic parameters towards electricity security in south africa. current efforts show that the focus has been on coal generation, which has proven to be unsustainable. south africa should explore new sustainable and energy efficient technology generation sources such as renewable table 6: causality test null hypothesis f-statistic p-value conclusion eci does not granger cause epv 3.08677 0.0524* h0 is rejected cv does not granger cause epv 4.11640 0.0207** h0 is rejected cp does not granger cause epv 1.83146 0.0583* h0 is rejected epr does not granger cause epv 10.1456 0.0002*** h0 is rejected cp: coal price, cv: coal volume, eci: electricity consumption intensity, epr: electricity consumption price, epv: electricity production volumes table 7: diagnostic tests results test measurement hypothesis p-values conclusion normality jarque-bera h0: all t is normally distributed h1 not all t is normally distributed 0.8382 errors were normally distributed serial correlation correlogram test at (1st difference) h1: ρ=0 h1: ρ≠0 0.15 serial correlation was not detected heteroscedasticity white’s test h t0 2 :σ σ= h0: not equal for all t 0.0690 the white and arch test reflects that series are homoscedasticarch test 0.1330 ateba and prinsloo: the electricity security in south africa: analysing significant determinants to the grid reliability international journal of energy economics and policy | vol 8 • issue 6 • 201878 energies with more security potentials compared to other sources. electricity security can be attributed to the capability of an electricity grid in meeting up the electricity needs of final consumers (raillon, 2010. p. 2). energy security will turn around the negative social and economic development in south africa. energy strategies should consider renewable energy as the most effective option for future south africa electricity needs and energy systems advancement. references altman, m. (2013), submission to nersa comments on the mypd 3 application. pretoria: human sciences research council (hsrc). antin, d. (2013), the south african mining sector: an industry at a crossroads. working paper: johannesburg: hanns-seidelfoundation. asteriou, d., hall, s. (2011), applied econometric: 2nd ed. new york, ny: macmillan palgrave. baltagi, b. (2005), econometric analysis of panel data. 3rd ed. chichester: wiley. baltagi, b. (2008), econometric analysis of panel data. 4th ed. chichester: wiley. baxter, r. (2015), south africa coal mining industry: economic overview and realising the potential of the sector: south africa chambers of mines presentation. available from: http://www. coaltech.co.za/annual_colloquium/2014/rsa%20coal%20 mining%20industry-%20economic%20overview%20and%20 realising%20the%20potential%20of%20the%20sector%20-%20 roger%20baxter.pdf. [last accessed on 2016 aug 17]. bento, p. (2011), energy savings via foreign direct investment? empirical evidence from portugal. the maastricht school of management working paper no. 2011/24. 1st maastricht school of management annual research conference, maastricht. blignaut, j., inglesi, r., weideman, j. (2014), sectoral electricity elasticities in south africa: before and after the supply crisis of 2008. south african journal of science, 111(9/10), 1-7. bp (british petroleum). (2016), statistical review of world energy 2016. available from: https://www.bp.com/content/dam/bp/pdf/ energy-economics/statistical-review-2016/bp-statistical-review-ofworld-energy-2016-full-report.pdf [17 august 2016]. bp (british petroleum) statistical review of world energy. 2005. putting energy in the spotlight. available at: http://www.nioclibrary.ir/freeeresources/bp%20statistical%20review%20of%20world%20 energy/statistical_review_of_world_energy_full_report_2005.pdf. [last accessed on 2016 aug 17]. brooks, c. (2008), rats handbook to accompany introductory econometrics for finance. 2nd ed. cambridge: cambridge university. brooks, c. 2008. rats handbook to accompany introductory econometrics for finance. 2nd ed. cambridge: cambridge university. brown, r., durbin, j., evans, j. (1975), techniques for testing the constancy of regression relationships over time (with discussion). journal of the royal statistical society, b37, 149-192. bulajic, a., stamatovic, m., cvetanovic, s. (2012), the importance of defining the hypothesis in scientific research. international journal of education administration and policy studies, 4(8), 170-176. burgess, j., nye, m. (2008), rematerializing energy use through transparent monitoring systems. energy policy, 36, 4454-4459. cameron, s. (2005), econometrics. berkshire: mcgraw hill education. castro, t., rodrigues, p., taylor, r. (2013), on the behaviour of phillipsperron tests in the presence of persistent cycles. cefage-ue working paper2013/11. chester, l. (2010), conceptualising energy security and making explicit its polysemic nature. energy policy, 38, 887-895. chesterman, a. (2008), on hypotheses. available from: http:// www.uni-saarland.de/fileadmin/user_upload/professoren/fr46_ profgerzymisch-arbogast/as/hyps_10-2008.pdf. [last accessed on 2016 sep 14]. clark, a., davis, m., eberhard, a., gratwick, k., wamukonya, n. (2005), power sector reform in africa: assessing the impact on poor people. cape town: esmap/world bank. dalla, v., giraitis, l., phillips, p. (2015), testing mean stability of heteroskedastic time series. cowles foundation for research in economics discussion paper no. 2006. new haven, ct: yale university. demski, c., poortinga, w., pidgeon, n. (2014), exploring public perceptions of energy security risks in the uk. energy policy, 66, 369-378. dickey, d., fuller, w. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica, 49(4), 1057-1072. eskom. (2012), part 1 revenue application: multi-year price determination 2013/14 to 2017/18 mypd. available from: http:// www.nersa.org.za/admin/document/editor/file/notices/invitations/ multiyear%20price%20determination%20201314%20to%20 201718%20(revenue%20application-%20part%201).pdf. [last accessed on 2016 aug 19]. farhani, s. (2012), theoretical study and empirical analysis on two types of models (arma model and market model). international journal of economics and financial issues, 2(3), 2146-4138. fourie, c. (2009), interpretation of the waterberg coalfield airborne geophysical data. heidelberg: coaltech. fourie, c., henry, g., mare, l. (2009), the structure of the karoo-age ellisras basin in limpopo province, south africa in the light of new airborne geophysical data. a preliminary report. 11th saga biennial technical meeting and exhibition. p16-18. glynn, j., chiodi, a., gargiulo, m., deane, j., bazilian, m., ó gallachóir, b. (2014), energy security analysis: the case of constrained oil supply for ireland. energy policy, 66, 312-325 gujarati, d. (2004), basic econometrics. 4th ed. new york, ny: mcgrawhall. figure 1: recursive residual test figure 2: the cumulative sum estimation test ateba and prinsloo: the electricity security in south africa: analysing significant determinants to the grid reliability international journal of energy economics and policy | vol 8 • issue 6 • 2018 79 gujarati, d., porter, d. (2009), basic econometrics. 5th ed. boston, ma: mcgraw-hill irwin. gábor, t., lipponen, j. (2006), security of electricity supply roles, responsibilities and experiences within the eu. working group on the security of electricity supply. brussels: the european union of electricity industry. hameed, l., khan, a. (2016), population growth and increase in domestic electricity consumption in pakistan: a case study of bahawalpur city. the explorer islamabad: journal of social sciences, 2(1), 27-33. hedden, s. (2015), gridlocked: a long-term look at south africa’s electricity sector. african futures paper 15. pretoria: institute for security studies and frederick pardee center for international futures. inglesi, r. (2010), aggregate electricity demand in south africa. conditional forecasts to 2030. applied energy, 87, 197-294. inglesi, r. (2011), the evolution of price elasticity of electricity demand in south africa: a kalman filter application. energy policy, 39(6), 3690-3696. inglesi-lotz, r., pouris, a. 2014, the causality and determinants of energy and electricity demand in south africa. essays innovate, series 9. available online: http://www.up.ac.za/media/shared/404/zp_files/ innovate%2009/articles/the-causality-and-determinants-of-energy. zp40043.pdf. [last accessed on 2015 sep 20]. inglesi1, r., blignaut, j. (2011), electricity intensities of the oecd and south africa: a comparison. world renewable energy conference; energy end-use efficiency issues. linkoping: oecd. jeffrey, l. (2005), challenges associated with further development of the waterberg coalfield. journal of the south african institute of mining and metallurgy, 105, 453-458. knox-hayes, j., brown, m., sovacool, b., wang, y. (2013), understanding attitudes toward energy security: results of a cross-national survey. global environmental change 23(3), 609-622. kohler, m. (2013), differential electricity pricing and energy efficiency in south africa. economic research southern africa (ersa). working paper 396. pretoria: ersa. levine, t., weber, r., hullett, c., park, h., lindsey, l. (2008), a critical assessment of null hypothesis significance testing in quantitative communication research. human communication research, 34, 171-187. marquard, a., bekker, b., eberhard, a., gaunt, t. south africa’s rapid electrification programme: policy, institutional, planning, financing and technical innovations. energy policy 2008, 36, 3125-37. mayet, m., ashley, b., read, k., liefferink, m., abrahams, m., d’sa, d., capel, j., dea, j., mokoena, s., conway, a., andrews, m. (2012), comments on eskom’s revenue application for mypd: 3. groundwork working paper. available from: http://www.groundwork. org.za/archives/2013/mypd3%20gw%20comment%20foe%20 sa.pdf. [last accessed on 2016 aug 18]. mohod, p. (2012), significance of a hypothesis in research methodology. online international interdisciplinary research journal, 2(6); 191-196. neuman, l. 2014. social research methods: qualitative and quantitative approaches. 7th ed. harlow: pearson. newberry, d., eberhard, a. (2008), a paper written for national treasury and the department of public enterprises: government of south africa. south african infrastructure review: electricity paper 2. available at: hyperlink "http://www.gsb.uct. ac.za/files/saelectricitypaper08.pdf" www.gsb.uct.ac.za/files/ saelectricitypaper08.pdf. [last accessed on 2016 jun 05]. nopiah, z., lennie, a., abdullah, s., nuawi, m., nuryazmin, a., bahrain, m. 2010. the use of autocorrelation function in the seasonality analysis for fatigue strain data. journal of asian scientific research, 2(11), 782-788. ojeaga, p., odejimi, d., george, e., azuh, d. (2014), energy and economic growth. energy supply threats revisited. open journal of energy efficiency, 3, 64-76. phillips, p., perron, p. (1988), testing for a unit in time series regression. biometrika, 75(2); 335-346. prevost, x. (2003), sa coal resources and reserves, a present-day outlook. paper presented at: application of computers and operations research in the minerals industries (apcom) 2003. cape town: proceedings of the south african institute of mining and metallurgy. raillon, p. (2010), energy regulation and security of supply: the european regulators approach ariae-ceer high-level meeting, madrid. available from: http://www.ceer.eu/portal/page/portal/ eer_home/eer_international/ceerariae1/2nd%20 ariaeceer%20roundtable/presentation%20ariae_sos%20 issues%20v2.pdf. [last accessed on 2016 sep 02]. robert, f., engle, r., granger, c. (1987), co-integration and error correction: representation, estimation, and testing. econometrica, 55(2), 251-276. sa eer (south africa energy efficiency report). (2011), trends in global energy efficiency. available from: https://www.library.e.abb. com/public/9344c8ededc6aa2fc12578640051aed8/south%20africa. pdf. [last accessed on 2016 jun 2]. schmidheiny, k. (2016), short guides to micro econometrics: the multiple linear regression model. available from: http:// kurt.schmidheiny.name/teaching/ols2up.pdf. [last accessed on 2016 sep 08]. ssekuma, r. (2011), a study of co-integration models with applications. (master’s dissertationcommerce in statistics). pretoria: university of south africa. studenmund, a. (2011), using econometrics: a practical guide. 6th ed. boston, ma: addison-wesley. thopil, g., pouris, a. (2013), international positioning of south african electricity prices and commodity differentiated pricing. south africa journal of science, 109(7/8), 1-4. varmuza, k., filzmoser, p. (2009), introduction to multivariate statistical analysis in chemometrics. boca raton: taylor and francis. von ketelhodt, a., wöcke, a. the impact of electricity crises on the consumption behaviour of small and medium enterprises. journal of energy in southern africa 2008, 9(1), 4-12. westerlund, j., breitung, j. (2013), lessons from a decade of ips and llc. econometric reviews, 32(5–6), 547-591. wilson, d., adams, i. (2006), review of security of supply in south africa: a report to the department of public enterprise support to the restructuring of public enterprises in south africa. pretoria: department of public enterprise. winkler, h. (2006a), energy policies for sustainable development in south africa’s residential and electricity sectors implications for mitigating climate change. (thesis – phd). cape town: university of cape town. winkler, h., marquand, a. (2009), changing development paths: from an energy-intensive to low-carbon economy in south africa. climate and development, 1, 47-65. wooldridge, j. (2009), introductory econometrics: a modern approach. 4th ed. south-western: taylor and francis. wooldridge, j. (2009). introductory econometric: a modern approach. 4th ed. mason, oh: south-western. . international journal of energy economics and policy | vol 8 • issue 6 • 2018102 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(6), 102-113. inequalities in energy transition: the case of network charges in germany lisa schlesewsky, simon winter* university of münster, center for interdisciplinary economics, scharnhorststraße 100, 48151 müster, germany. *email: simon.winter@wiwi.uni-muenster.de received: 18 july 2018 accepted: 28 september 2018 doi: https://doi.org/10.32479/ijeep.6917 abstract the german energy transition and the rising share of renewable energies in electricity generation have led to an increase in network costs and to higher network charges in recent years. we use socioeconomic data in order to investigate distributional effects within the period 2010-2016, and employ three different inequality metrics – the gini coefficient, the theil index and the atkinson index – all of which unambiguously indicate regressive effects of network charges. most recently, the three metrics show an increase of economic inequality of at least 0.67% when accounting for network charges. this finding is due to (1) the relative inferiority of electricity, (2) the regressive impact of a fixed component of network charges, (3) considerable regional disparities, and (4) the higher prevalence of prosumers within high-income households. keywords: network charges, renewable energies, economic inequality jel classifications: d63, q40, q42 1. introduction german energy policy has changed dramatically in recent years. federal government stated in its “energiekonzept 2050” that up to 80% of electricity should be renewably generated by 2050 (bundesregierung, 2010). this goal induces a structural change which not only includes power generation and technologies themselves, but also the need for an efficient and capable electricity grid. new challenges arise from decentralized power generation through photovoltaic (pv) systems and wind mills, which are often not located in load centers, thus necessitating quantitatively more and more capable transmission grids. the costs of this network expansion have to be borne ultimately by the customers, since the grid costs are reflected in the network charges which in germany, are a component of the electricity bill. however, network charges are lower for industrial users and even differ for private households – so-called prosumers (i.e., households with roof-top pv systems or interruptable consumption systems) are partially exempt from paying the charge. furthermore, network charges are defined locally by the distribution system operators (dsos), which have to pay network charges to the transmission system operators (tsos) themselves. this induces substantial regional disparities in the financial burden exerted by network charges – for example, households in regions with a low population density have to pay for a relatively costly grid. as a consequence, different households in different regions of germany are charged differently for the maintenance and extension of the grid. this finding has been further aggravated by rising network charges in recent years and had induced households to pay a considerable proportion of their disposable income for network charges. the distributional effects of different energy-market policies have been investigated extensively in the past. in a cross-country comparison, flues and thomas (2014) find that taxes on electricity are more regressive than those on other energy sources. concerning germany in particular, the distributional effects of the eeg feed-in tariff – which is a subsidy to producers of renewable energies financed by a surcharge on the electricity price – have this journal is licensed under a creative commons attribution 4.0 international license schlesewsky and winter: inequalities in energy transition: the case of network charges in germany international journal of energy economics and policy | vol 8 • issue 6 • 2018 103 been analyzed at length (löschel et al., 2012; neuhoff et al., 2012; techert et al., 2012; grösche and schröder, 2014; többen, 2017). hence, distribution issues are an essential component of the scientific and public debate on the energy transition and pose the question how the costs arising from the ecological transformation of electricity generation are distributed among the population. yet, the distribution of the increasing grid costs has solely been investigated at a regional level (hiersig and wittig, 2015). hinz et al. (2018) forecast future regional disparities in network charges, depending on various tariff designs. they find that regional average network charges will diverge further by 2025, if the current tariff design is maintained. households in mecklenburg-vorpommern would have to pay 12.1 ct/kwh (+41% compared to 2015), whereas those in berlin would be charged only 6.5ct/kwh (+10%). indeed, the literature described above neither calculates the financial burden of network charges at a household level, nor does it link this burden to household income in order to test whether the charges are characterized by substantial regressive effects. nevertheless, this form of analysis is promising and goes beyond other studies concerning the regressive effects of electricity prices or feed-in tariffs, since network charges firstly consist of a two-part tariff and secondly differ regionally. both of these characteristics might affect the regressiveness of the charges. the present study firstly examines how much german households effectively pay for network charges annually – in absolute and relative terms measured as a share of income. secondly, we quantify the distributional effects on overall economic inequality. in order to address these issues, we analyze data on network charges for households during the period 2010-2016 and match them with socio-economic panel data. we exclude both commercial customers and indirect effects from our analysis. these might additionally affect redistributive effects. we find that the regional definition of network charges leads to a substantial gap between the north and east of germany on the one hand, and the south and west of germany on the other hand. since the total financial burden exerted by network charges increased by approximately 16% between 2010 and 2016, these regional disparities are gaining importance. the average german household had to pay 218€ in 2016 for network charges – but only about 150€ in some regions and up to 300€ in others. in addition, different quintiles of the income distribution spend considerably different shares of their income on network charges – 1.6% in the lowest quintile and 0.4% in the highest. in addition, we observe that households in urban areas had to pay about 30€ less than those in rural areas. we employ three different inequality metrics – the gini coefficient, the theil index and the atkinson index – in order to derive the overall impact of network charges on the distribution of disposable incomes. as a result, we notice an unambiguously regressive effect of network charges, as all metrics increase by at least 0.63% when accounting for network charges. this yields an additional (and increasing) welfare loss due to increased economic inequality. we proceed as follows: section 2 describes the tariff structure of network charges in germany, section 3 derives three hypotheses concerning the distributional effects of network charges. section 4 presents our methodology and the underlying datasets and in section 5, we test our hypotheses empirically. finally, section 6 concludes. 2. financing distribution grids in germany the german energiewende triggered tremendous changes in energy policy in order to start the transition from fossil and nuclear to renewable energy. the objective of this transition is to revolutionize the german energy system. the installation of new generation plants for renewable power generation has led to a rising emphasis on the electricity distribution grid in recent years. this is a result of the increasing share of renewable energy in gross electricity consumption, which already represented 33.1% in 2017 (statistisches bundesamt, 2018). hence, renewable energy already constitutes the largest share of gross electricity consumption and is planned to reach a share of 80% in 2050 (bundesregierung, 2010). in this section, we focus on the reasons for the recent rise in network charges and on the definition and tariff structure of these network charges. finally, we define the customer group on which we concentrate in our empirical investigation. the focus on renewable energy (especially on onshore windpower systems and pv systems), and the resulting increase of decentralized energy supply as well as the regional shift of generation systems, have led to higher (technical) requirements for the german electricity grid (bundesnetzagentur, 2015. p. 9).1 thus, the transmission and distribution grids need to be extended and their capacity increased in the future. studies on different expansion scenarios until 2020 (the share of renewable energy in gross electricity consumption in 2020 is predicted to be about 39%) forecast grid-expansion costs between 0.9 and 1.6 bn. €/a (deutsche energie-agentur 2010. p. 13). the responsibility for these grid-expansion measures rests (analogous to the renewable energy sources act, eeg) with the four german tsos for the transmission grid and more than 800 dsos for the distribution grid. the increase in network costs and charges and the regional differences are caused by various factors. firstly, the development of network costs depends on the urbanization level. the unequally distributed settlement of industrial locations and agglomeration areas leads to a different utilization rate of the grid. the per capita costs and network charges increase with a decreasing number of users of a particular regional grid area. hence, people in rural areas have to bear higher network charges than those in urban areas, because fewer people have to bear the costs of the grid. furthermore, the german electricity infrastructure comprises grids of different ages. the older grid in western germany, with its lower residual value, has 1 the regional shift of generation systems follows from two different factors. firstly, it is more efficient regarding the environmental and legal preconditions for onshore wind power systems to become established in the northern part of germany (it is, for example, more difficult to build wind power systems in bavaria, because of the 10-h-rule); the same holds true for pv sytems in south and east germany. secondly, there are still a few nuclear power plants in southern germany which will gradually disappear from the grid. schlesewsky and winter: inequalities in energy transition: the case of network charges in germany international journal of energy economics and policy | vol 8 • issue 6 • 2018104 lower network costs than the newer grids in eastern germany. potential future modernization measures could turn this cost situation around. secondly, the rise of renewable energy generation is associated with rising network costs. the connection and integration of renewable energy systems (e.g., the connection of off-shore wind power systems) are accompanied by higher costs for the tsos. furthermore, because of the increase in renewable energy generation plants, the amount of energy which is fed in to the lower voltage grid levels of the distribution grid rises (especially in low and medium voltage levels). this lowers the current consumption from upstream transmission grid levels so that the average costs of the transmission grid per kwh increase and network charges consequently rise. in addition, the quality of the electricity grid cannot withstand the heavy load fluctuations from renewable energy generation (especially from very volatile onshore wind power systems) and needs to be strengthened and modernized. this scenario leads to rising costs. especially the rising power generation from renewable energy is resulting in a massive and cost-intensive network expansion in north, east and southern germany. finally, decentralized energy generating systems feed in electricity in lower voltage levels and can therefore avoid upstream network charges. the avoided network charges lead to increasing costs, due to the rising number of renewable energy generating systems. thirdly, the tsos have to ensure supply reliability and avoid and face network bottlenecks. therefore, the tsos have to intervene via redispatching measures and back up power resulting in higher network costs.2 the rising costs of the expansion and maintenance of the transmission and distribution grid are passed on to electricity consumers via network charges (bundesnetzagentur, 2015. p. 13). basically, network charges are a fee paid by the network users for the transport of electricity within the transmission and distribution grid. the tsos raise these charges to cover the costs resulting from the network. network charges at the tso level are highly regulated by the german federal network agency (bundesnetzagentur, bnetza) via a revenue cap system (rap, 2014. p. 7. et seq.; bundesnetzagentur, 2016a. p. 3). downstream dsos calculate their costs and charges based on reported network charges of the tsos and invoice the electricity consumers for the final charge. in general, network costs can be covered via different mechanisms involving all or subsets of network users. a key aspect is whether the network charge is split into a load (l) and a generation (g) cost component. the l-component allocates the network costs to the electricity consumers, whereas the g-component forces the electricity producers to bear part of the costs. network costs in germany consist mainly of an l-component.3 households and 2 for the total list of reasons for rising network costs, hinz (2014:40. et seq.) and bundesnetzagentur (2015. p. 19. et seqq.; 2016b). 3 in eleven european countries, a g-component is raised in addition to the l-component (haucap and pagel, 2014. p. 11). additionally, in great industrial customers pay for a substantial part of the network costs, whereas energy producers only pay the costs of connection to the network, or for voltage transformation substations (haucap and pagel, 2014. p. 5). german households pay the network charges via their electricity bills. the charges are paid to the dsos and in part passed on to the tsos. the network charges (including meter operation, meter reading and billing) comprised nearly 30% of the electricity price net of value-added tax (mehrwertsteuer, vat) in 2017 (bundesnetzagentur and bundeskartellamt, 2017. p. 254). due to different customer profiles, the billing of the network charges also differs. there are two different customer groups, namely customers with consumption metering and customers without consumption metering. the former have to transmit their consumption data every 15 min to the respective grid operator and are mainly major or industrial customers who are also connected to higher voltage levels. they pay a power price in €/kw (for the peak load within one billing period) on the one hand, and a price given in ct/kwh depending on actual consumption on the other hand. this customer group can be separated further, according to their usage period – i.e., whether they use the grid for less or more than 2,500 h/a. the latter group includes households as well as small industrial and agricultural customers. for some dsos, there is a maximum consumption of about 10,000 kwh/a as an upper limit. customers without consumption metering – the focused of the following analysis – have to pay a fixed component (grundpreis, €/a) and a variable component (arbeitspreis, ct/kwh). the increase in network charges in recent years, as well as their considerable share in the electricity price and corresponding importance for customers make an empirical analysis of the burden of these network costs relevant. in particular, we take a closer look at the distributional effects on a household level. accordingly, we derive three hypotheses in section 3 stating that network charges should exert substantial regressive effects with respect to the distribution of disposable incomes. 3. hypotheses each household i in region j at time t is assumed to have a disposable income of yij,t. in addition, monthly electricity costs eij,t are given, as well as the monthly demand for electricity, dij,t. the electricity price pj,t depends on regionally determined network charges nj,t which consist of two parts – a fixed component (fj,t) paid annually (with fj,t = fj,t/12 as the monthly share) and a variable component (vj,t) paid per kwh. these components in germany correspond to the grundpreis and arbeitspreis (section 2). additionally, we must adjust for the regionally defined concession fee (kj,t; konzessionsabgabe). this fee differs regionally (contingent upon community size) and is a further price component paid for using public infrastructure, i.e., the electricity grid. the national average electricity price pt , the national average network charge nt , the national average concession fee kt , as well britain, norway and sweden, for example, the g-component varies with the choice of location of electricity producers (grimm et al., 2015. p. 14). for an international comparison of network charges, also hinz et al. (2018. p. 98). schlesewsky and winter: inequalities in energy transition: the case of network charges in germany international journal of energy economics and policy | vol 8 • issue 6 • 2018 105 as the regional network charge, define the final average electricity price (faep) of household i in region j at time t: p p n v k k f dij t t t j t t j t j t ij t , , , , , .= − + − + + (1) all values are gross, i.e., they include the 19% vat. the electricity costs eij,t of a household can be defined as the product of the faep and electricity consumption. e f d p n v k kij t j t ij t t t j t t j t, , , , ,( ).= + − + − + (2) the partial derivative of electricity costs with respect to income yields. ∂ ∂ = − + − + ∂ ∂ e y p n v k k d y ij t ij t t t j t t j t ij t ij t , , , , , , ( ) . (3) as we assume electricity to be a normal good (i.e., ∂dij,t⁄(∂yij,t)>0), this term can be expected to be positive. additionally, the income share of electricity costs can also be differentiated with respect to income: ∂ ∂ = ∂ ∂ − ∂ e y e y e y y ij t ij t ij t ij t ij t ij t ij t , , , , , , , . (4) furthermore, assuming electricity to be a relatively inferior good4 leads to a negative link between income and the income share of electricity costs. the numerator of equation (4) has to be negative accordingly. the income elasticity of electricity costs is positive, but smaller than one and as a consequence: , , , , , (0,1).ij t ij te y ij t ij t e y y e ε ∂ ∂ = ∈ ∂ ∂ (5) total network charges paid by the household are: n f v d f p n k k v e p n vij t j t j t ij t j t t t t j t j t ij t t t j , , , , , , , , = + = − − +( )+ − + ,, ,t t j tk k− + (6) where dij,t can be derived from equation (2) as: d e f p n v k kij t ij t j t t t j t t j t , , , , , .= − − + − + (7) 4 this assumption is supported by robust empirical evidence from throughout the world (see most recently for germany: schulte and heindl, 2017; jamaica: campbell, 2018; singapore: loi and le ng, 2018) estimating the income elasticity of electricity demand between 0 and 1. for a metaanalysis on the income elasticity of electricity demand, espey and espey (2004). fouquet (2014) finds that the income elasticity of electricity demand followed an inverted u-shaped curve over the past 200 years – which results in relatively inelastic electricity demand in industrialized countries nowadays. the income share of total network charges ( )/ , , , n n yij t ij t ij t= can be differentiated with respect to income: ∂ ∂ = ∂ ∂ −      − − n y v e y e y f p n ij t ij t j t ij t ij t ij t ij t j t t , , , , , , , , tt t j t ij t t t j t t j t ij t k k y p n v k k y − + − + − + , , , , , ( ) (8) as both the denominator and the subtrahend in the numerator are positive, this expression is below zero, especially when the minuend of the numerator is negative. this is true in our case, because of the relative inferiority of electricity consumption (i.e., 0<εe,y<1). therefore, income and the income share of total network charges are negatively associated. this effect can be attributed to two components: firstly, electricity costs as a share of income decrease with rising income. secondly, the fixed component of network charges plays a minor role, due to fixed cost degression once a household consumes a substantial amount of electricity – which occurs especially in high-income households. thus, the income share of total network charges not only decreases with income, because electricity is a relatively inferior good (minuend in the numerator), but also because the marginal network charge is smaller than the average network charge, because of the fixed component (subtrahend in the numerator). the latter effect would vanish if network charges consisted only of a variable component. we can therefore now derive hypothesis 1 for our empirical analysis. hypothesis 1: a household’s financial burden via network charges is regressive. this regressiveness can be expected to be stronger, especially if the fixed component of network charges is higher: 2 , , , , , 0 0.ij t ij t ij t ij t j t n n y y f  ∂ ∂ < ∧ < ∂ ∂ ∂ furthermore, regional disparities might lead to a correlation between income and the variable component of network charges. in rural areas, incomes are usually lower and network charges higher; this generally also applies to the new federal states of germany (east germany). accounting for a relationship v v yj t j t ij t, , ,( )= modifies equation (8): ∂ ∂ = ∂ ∂ −      − − n y v e y e y f p n ij t ij t j t ij t ij t ij t ij t j t t , , , , , , , , tt t j t ij t t t j t t j t ij t j t ij t t t k k y p n v k k y v y p n − + − + − + + ∂ ∂ − − , , , , , , , ( ) kk k p n v k k y dt j t t t j t t j t ij t ij t + − + − + , , , , , ( ) . (9) the derivation of equation (9) can be found in appendix a. with ∂vj,t⁄∂yij,t=0, the second summand disappears, leaving equation (8) as a special case of equation (9). otherwise, hypothesis 2 is as follows: hypothesis 2: the regressiveness of network charges increases (decreases) if income and the variable component of network charges are negatively (positively) correlated, i.e., if. schlesewsky and winter: inequalities in energy transition: the case of network charges in germany international journal of energy economics and policy | vol 8 • issue 6 • 2018106 , , , , 0 0j t j t ij t ij t v v y y  ∂ ∂ < >  ∂ ∂  additionally, prosumers are not charged any network tariffs for the share of their electricity demand which they have themselves produced. if the feeding-in of pv electricity is distributed equally along household incomes, this has no implications at all for the incidence of network charges. however, when there is a positive relationship between household income and the use of pv systems, high-income households are on average faced with a lower burden from network charges than low-income households. this once again increases the regressiveness of network charges. hypothesis 3 summarizes this issue. hypothesis 3: since monthly net demand for electricity is calculated as the difference between consumed and fed-in electricity, network charges can be avoided by producing electricity. the regressiveness of network charges increases (decreases) if the feeding-in of pv electricity and income are positively (negatively) correlated. 4. methodology and data 4.1. methodology in order to quantify the overall impact of network charges on economic inequality, we employ three different distribution metrics: the gini coefficient, the theil index and the atkinson index. furthermore, we vary the parameters of the theil and atkinson index in order to test the robustness of our results. this selection of inequality metrics basically follows the approach of grösche and schröder (2014), who analyze the distributional effects of the german feed-in tariff. we only omit the 90/10 percentile ratio, since it does not include the entire distribution data, but only measures the relationship between two points within the distribution. as a percentile ratio, it is very selective and limited in scope. an axiomatic comparison of the inequality metrics can be found in the aforementioned study (grösche and schröder, 2014. p. 1363. et seq.) as well as in sen (1973). a brief definition of the three chosen inequality metrics for weighted survey data can be found in appendix b. 4.2. data the underlying data consists of two merged datasets: socioeconomic household data from the german socio-economic panel (soep) (soep, 2018, version v33.1) on the one hand and panel data on regional network charges from ene’t gmbh (2018) on the other hand. from soep data, we include monthly net household income (inc) and electricity expenditures (elec) as financial variables in our analysis. furthermore, we include the household’s number of persons aged 14 or above (adult14) and the number of remaining persons, i.e., children aged 13 or below (children). these variables are needed so as to calculate equivalent incomes according to the oecd-modified equivalization scale. we include binary variables for the existence of pv electricity generation (solar) in our analysis. each household is assigned either to a rural or urban area (rural) and to a raumordnungsregion5 (ror). however, our analysis has to focus on the period 2010-2016, since electricity expenditure was not surveyed before 2010. additionally, monthly electricity costs are only available for rental households, whereas households with home ownership were asked to specify their annual electricity costs in the previous year. we include the latter by dividing these costs by 12 and accounting for the annual increase in electricity prices in the corresponding year. the data appears to be comparable, although households with home ownership paid on average 80.18€ per month in 2016 which is 20.59€ or about a third more than rental households. nevertheless, this seems plausible when taking into account the fact that at the same time, the average household income of owners (3,162€) was 47 % higher than that of rental households (2,152€). additionally, the average number of persons in the household (2.2 compared to 1.8) and the dwelling size (122.3 compared to 72.8 m2) were considerably higher for households which owned their own housing. ultimately, owners spent about 3.2% of their income on electricity, whereas rental households paid 3.5%. this finding conforms perfectly to our assumption of electricity as a relatively inferior good. finally, there are 101,597 observations which include information on electricity costs – equivalent to 13,913 (2016)-17,297 (2013) observations per year. in 2015, owners were not asked to give their electricity costs: the costs are only available for 9,021 rental households. therefore, 2015 is excluded from our analysis at every point for which we do not control for ownership. furthermore, the number of observations does not allow a more detailed geographic division: a valid statement on the average burden exerted by network charges in each of the over 11,000 communities (lau 2) or 400 districts (nuts 3) could not be made because of the sample size. at the ror level, there are on average 150-180 annual observations which might be sufficient for a quantitative analysis of regional disparities. however, there are still eight rors which exhibit <50 observations in at least 1 year (leaving out 2015 data).6 as a consequence, single values should be interpreted with caution and the emphasis should rather be on the overall picture. from ene’t data, we include network charges for the period 20102017, which consist of the fixed component (gp) and the variable component (ap). furthermore, we include the regional concession fee (ka, measured in ct/kwh). network charges as well as the concession fee, are available at lau 2 level, and are aggregated by calculating weighted averages for rors. this enables us to match households and the corresponding network charges. merging the datasets further allows us to calculate electricity consumption according to equation (7) and the total burden of 5 a raumordnungsregion which can be translated as “spatial planning region,” is a german geographic division standard somewhere between the nuts 2 (regierungsbezirke/government regions) and nuts 3 level (kreise/districts). in total, there are 96 rors across germany. 6 the overall response rate for 2010-2014 and 2016 amounted to 87.1%, which yields a representative analysis. schlesewsky and winter: inequalities in energy transition: the case of network charges in germany international journal of energy economics and policy | vol 8 • issue 6 • 2018 107 network charges according to equation (6). since the electricity price is taxed at 19% vat, the effective burden must include the additional tax burden. therefore, as already explained in section 3, network charges are gross values in the following analysis. 5. results 5.1. descriptive statistics as shown in figure 1, network charges increased substantially in recent years. the federal average network charge for a representative household with annual electricity consumption of 3,500 kwh amounted to 7.44 ct/kwh in 2016, compared to 6.13 ct/kwh in 2010, which corresponds to an increase of 21.3%. even after accounting for inflation (7.7%), a real increase in effective network charges of 12.7% remains. this development is caused by both an increase in the variable and the fixed component: whereas the arbeitspreis rose from 5.73 ct/kwh in 2010 to 6.34ct/ kwh in 2016 (+10.7%), the grundpreis even grew more strongly and nearly tripled (from 14.03€/a in 2010 to 38.32€/a in 2016, +173.2%). whereas the grundpreis grew gradually, the arbeitspreis reached a peak in 2013 and remained at a high level from then on. also, the distribution of network charges has changed: network charges increased especially in the northeast and in the southwest of the country. the northeast is especially affected by the modification and expansion of the grid, due to the connection of renewable energies and having been a region with a relatively low level of network density. in the southwest, costs are in part driven by a well-advanced diffusion of pv systems. the gini coefficient measuring the inequality of average network charges across communities increased from 9.6% in 2010 to 11.3% in 2016. this means that network charges tended to increase more in communities where they were also higher in 2010. looking at the long term, this trend became even more intense over the last decade (2007: 7.3%; 2017: 12.0%). in order to display regional income disparities, we equivalize household net income by applying the oecd-modified scale. according to this procedure, each member of the household is assigned a certain value (first adult 1, other adults 0.5, children <14 years 0.3) and the household net income is finally divided by the sum of these values. the equivalization is better able to account for the different needs of households with a different composition. net equivalent household income (oecd-modified scale) increased by 11.2% in the period 2010-2016, which corresponds to an annual growth rate of 1.8%. since inflation amounted to 7.7%, real incomes also increased on average. however, huge income differentials appear when analyzing average incomes at the ror level. income is unequally distributed across rors in germany. the gini coefficient (weighted by the number of ror inhabitants) measuring regional income inequality was mainly between 7.6% and 8.0% in recent years and exhibited a moderate downward trend (2010. p. 8.8%; 2016. p. 8.0%). in 2016, average equivalent incomes reached from 1,311€ in prignitz-oberhavel to 2,280€ in ingolstadt. this heterogeneity is persistent over time and extends back to the division of germany into gdr and frg until 1990. even over 25 years later, the east-west income differential is substantial, is decreasing very slowly and easily can be seen in figure 2. in 2016, monthly electricity costs amounted to 68.86€ on average, which was about 3.4% of net household income. these costs are used to calculate electricity consumption and the network charge burden according to the procedure in equations (6) and (7). the burden exerted by network charges increased by 16% – from 188.11€ in 2010 to 217.97€ in 2016. most recently, the regional disparities were quite considerable ranging from about 148€ in berlin and bremen to 301€ in bremerhaven.7 the 7 it may seem obvious that these huge regional disparities stem from small samples at the ror level. however, the inequalities persist when analyzing network charge burdens at a federal state (bundesland) level: whereas households in bremen or berlin only spent about 150€ on network charges in 2016 and households in bayern, sachsen and thüringen spent between 200€ and 210€, households in brandenburg and schleswig-holstein had to pay more than 250€. figure 1: average gross network charges (ct/kwh) in 2010 (left) and 2016 (right) for a representative household with electricity consumption of 3,500 kwh/a at the community level source: own illustration and calculation based on ene’t (2018) schlesewsky and winter: inequalities in energy transition: the case of network charges in germany international journal of energy economics and policy | vol 8 • issue 6 • 2018108 disparity is also large when expressed as a share of income: people in ingolstadt spent 0.63% of their income on network charges, whereas those in prignitz-oberhavel paid 1.54%.8 when analyzing relative burdens at a federal level, the north and east are charged disproportionately compared to the south and west of germany (figure 3). but the burden also increased at a household level: whereas 28% of households had to spend more than 1% of their income on network charges in 2010, this share increased to 31% in 2016. on the other hand, the share of households paying <0.5% also decreased from 28% to 24%. these findings motivate the following analysis which is an attempt to determine the overall impact of network charges on economic inequality in germany. 5.2. impact on economic inequality first of all, we have to test whether electricity is a relatively inferior good in our data, as assumed in hypothesis 1 and in the literature described in footnote 4. we regress our estimate of log 8 at the federal state level, this share ranged from about 0.7% in bremen and berlin, to above 1.2% in brandenburg and sachsen-anhalt. electricity consumption on the logarithm of equivalent income in a two-way fixed-effects weighted least squares model.9 we find that the income elasticity of electricity consumption is slightly but significantly above zero (0.049), even when accounting for heteroskedasticity robust standard errors. consequently, we confirm the results of previous studies, and electricity appears to be a relatively inferior good. as assumed in hypothesis 2, the variable component of the network charge is negatively correlated with income. whereas the lowest income quintile had to pay 5.35 ct/kwh in 2016, the highest income quintile only had to pay 5.26 ct/kwh. this difference is small, but persistent over time,10 which can only 9 this technique is most able to extract the ceteris paribus influence of income on electricity consumption: time-fixed effects such as efficiency gains and societal changes in consumption habits are represented, as well as entity-fixed effects such as individual usage behavior and wastefulness. 10 actually, this gap amounted to higher values in the past: 0.27 ct/kwh in 2010, 0.22 ct/kwh in 2012, and 0.17 ct/kwh in 2014. in addition, we have to keep in mind that these values are net of vat and that these gaps increase with the factor of 1.19 when calculating effective financial burdens. figure 2: average monthly net equivalent household income (€, oecd-modified scale) in 2010 (left) and 2016 (right) at raumordnungsregion level source: own illustration and calculation based on soep (2018, wave v33.1). figure 3: average annual network charge burden (% of net household income) in 2010 (left) and 2016 (right) on raumordnungsregion level source: own illustration and calculation schlesewsky and winter: inequalities in energy transition: the case of network charges in germany international journal of energy economics and policy | vol 8 • issue 6 • 2018 109 be explained by regional disparities, since the arbeitspreis does not vary within a region but only across regions. this result is somewhat in line with our previous findings: households in rural areas usually have lower incomes, but have to pay for a grid used by relatively few people, due to the low population density in rural areas. this finding is also supported by the conditional means of the variable network charge, given a certain urbanization level. in 2016, households in rural areas had to pay on average 5.7 ct/kwh. by contrast, people in urban areas had to pay only 5.2 ct/kwh.11 the use of rooftop pv systems is indeed correlated with household income as assumed in the context of hypothesis 3: whereas only 3.5% of households in the lowest income quintile produced solar power in 2016, it was 9.2% in the third, and up to 14.1% in the fifth quintile. as all the assumptions underlying our hypotheses are met and can be found in our data, we expect network charges to display considerable regressive effects. in a first step, we calculate total annual network charges and the income share of annual network charges for each quintile of the distribution of net equivalent incomes. as shown in table 1, the absolute financial burden of network charges increased for all households by about 2-3€ per month, which corresponds to an annual additional burden of about 30€. independent of the year, the income share of network charges is decisively lower in higher income quintiles: whereas the lowest quintile has to pay more than 1.6 % of income for network charges, the highest quintile has to spend <0.5 %. when analyzing the intertemporal development of relative financial burdens, we conclude that the increase in network charges in the period under 11 this also holds for the fixed component: the grundpreis in rural areas amounted to 36.80€/a, but only to 30.07€/a in urban areas. in the end, households in rural areas (239€ in 2016) pay about 30€ more annually than households in urban areas (208€). consideration mainly affected the lower quintiles, inducing them to spend higher shares of their incomes on network charges. by contrast, the income shares of network charges remained nearly constant in higher quintiles. these findings can be attributed to multiple causes. firstly, the relative inferiority of electricity induces a sub-proportional increase in electricity consumption with rising incomes. as time goes by, this leads to a higher additional burden in lower quintiles during periods of extensive economic growth. secondly, the relevance of the fixed component of the network charges increased, thus strengthening its regressive impact. thirdly, the regional disparities of network charges increased as outlined in section 4. since network charges are negatively correlated with incomes, this promotes the regressive effects of network charges once more. and fourthly, incomes grew sub-proportionately in the lowest quintile (by 7.5% compared to 10.3-13.8% in higher quintiles). in order to quantify the impact of network charges on economic inequality, and following the approach of grösche and schröder (2014), we finally calculate different inequality measures of equivalent incomes – gross and net of network charges. we employ the gini coefficient, the theil t and l index and the atkinson index – the latter with different parameters.12 the results are shown in table 2 for the years 2010 and 2016 as an example. all indices suggest that economic inequality is amplified by network charges. in 2010, inequality metrics increased by 0.631.55 % when accounting for network charges. looking at the theil and atkinson indices, we conclude that this effect is qualitatively 12 the underlying formulas are defined in subsection 4.1. note that we interpret these metrics only as a positive measure of inequality and not as a normative criterion. thus, we only state that inequality rises or declines and do not assess whether this finding can be treated to be fair. table 1: monthly financial burden of network charges by quintiles of net equivalent income distribution quintile 2010 2016 borders mean total network charges … as a share of income (%) borders mean total network charges … as a share of income (%) 1 <934€ 717€ 14.71€ 1.54 <1,000€ 771€ 16.62€ 1.63 2 934€–1,233€ 1,092€ 15.16€ 0.96 1,000€–1,400€ 1,235€ 17.89€ 1.02 3 1,233€–1,600€ 1,421€ 15.96€ 0.77 1,400€–1,800€ 1,617€ 18.64€ 0.82 4 1,600€ –2,067€ 1,835€ 15.92€ 0.60 1,800€–2,333€ 2,056€ 18.15€ 0.63 5 > 2,067€ 2,995€ 16.56€ 0.43 >2,333€ 3,302€ 19.38€ 0.45 source: own calculation based on soep (2018, wave v33.1) and ene’t gmbh (2018) table 2: impact of network charges on economic inequality measured by different inequality indices index 2010 2016 inequality of equivalent income … net of network charges percentage change (%) inequality of equivalent income … net of network charges percentage change (%) gini 0.2769 0.2787 +0.6286 0.2761 0.2779 +0.6662 theil’s l (α=0) 0.1291 0.1310 +1.4112 0.1345 0.1302 +1.5130 theil’s t (α=1) 0.1392 0.1409 +1.2084 0.1345 0.1363 +1.2963 atkinson (ε=0.5) 0.0642 0.0650 +1.2554 0.0631 0.0640 +1.3479 atkinson (ε=1) 0.1211 0.1227 +1.3208 0.1204 0.1221 +1.4166 atkinson (ε=2) 0.2246 0.2281 +1.5481 0.2259 0.2296 +1.6277 schlesewsky and winter: inequalities in energy transition: the case of network charges in germany international journal of energy economics and policy | vol 8 • issue 6 • 2018110 independent of the chosen parameter (α, ε), although it increases with an increasing inequality aversion. in 2016, this inequalitypromoting effect even grew stronger: inequality metrics increased by 0.67-1.63% when accounting for network charges. looking at the years in between, this development reflects an ongoing trend. consequently, network charges have a positive and increasing impact on inequality and thereby exert a regressive impact on the distribution of disposable incomes. 5.3. welfare loss finally, we attempt to estimate the additional welfare loss caused by the regressiveness of network charges according to the definition in appendix b. the results are shown in table 3. the welfare loss for german households which can be derived from the atkinson index depends crucially on the presumed inequality aversion parameter. the additional welfare loss which is due to unequally distributed network charges amounted to at least several million euros per year, but the estimates have a large variance: at ε = 2, the additional welfare loss is about 5 times as high as at ε = 0.5. as a consequence, the absolute level of this measure should not be overstated, but the time trend is interesting: the welfare loss increases substantially over time. assuming an inequality aversion of 0.5 or 1, the welfare loss increased by about a quarter in the period under consideration, whereas it still increased by more than a fifth with an underlying inequality aversion of 2. 6. conclusion network costs increased substantially in recent years and have been passed on to electricity customers in the form of higher network charges. we show that in absolute terms, the average german household paid 218€ for network charges in 2016 starting from about 188€ in 2010. as a component of the electricity price, these charges exert regressive effects on the distribution of disposable incomes net of network charges due to four reasons. firstly, electricity is a relatively inferior good so that the income share of electricity is negatively related to income. secondly, the fixed component of network charges leads to lower average network charges for households with higher electricity demand. thirdly, network charges differ regionally. both the variable and the fixed component of network charges are negatively correlated with regional average income. this leads to a higher burden for (relatively poor) households in regions with higher network charges. fourthly, prosumers are exempt from network charges, but are high-income households, in many cases. as a consequence, low-income households are de facto often faced with higher costs due to network charges although network charges are not de jure contingent upon income. as a result, households pay on average a share of 0.9% of their income for network charges. but different quintiles of the income distribution spend significantly different shares of their income on network charges – 1.6% in the lowest quintile and 0.4% in the highest quintile. because of the negative regional correlation of network tariffs and income, even households with similar economic preconditions are charged differently in different parts of the country. households had to pay only 150€ in some regions and up to about 300€ in others. finally, there are apparent differences between rural and urban areas: households in rural areas paid nearly 239€/a and about 208€/a in urban areas. this corresponds to higher network costs per household in rural areas. using different inequality metrics, we find that network charges increase overall inequality of disposable incomes net of network charges by at least 0.6%. this effect has increased since 2010 as network charges have also increased substantially in the respective period. as network costs are expected to increase further in the near future, distribution issues will become increasingly important in this area. the maintenance and expansion of the distribution grid is essential for the integration of renewable energies in order to fulfill the requirements of the energiewende. thus, the distribution of the corresponding costs among the population is a fundamental determinant for the political acceptance of such an energy transition. to the best of our knowledge, the present study is the first to analyze the relative financial burden imposed by increasing network charges to households. it shows that the tariff structure and the regional differentiation of network charges are able to exert significant (regressive) effects on the distribution of disposable incomes. consequently, they have the potential to jeopardize the political feasibility of the german energiewende and have to be analyzed thoroughly. these concerns regarding the social sustainability of the energy transition grow further once other empirical studies including subsidies for renewable energies are taken into account (e.g., grösche and schröder, 2014). yet, these findings do not suggest automatically that the distribution of the financial burden of network charges can be treated as unfair. on the one hand, we did not include table 3: welfare loss of income inequality and relative welfare loss, due to inequality-promoting network charges index 2010 2016 welfare loss without network charges welfare loss including network charges additional welfare loss of network charges welfare loss without network charges welfare loss including network charges additional welfare loss of network charges atkinson (ε=0.5) 4,175m€ 4,198m€ 24m€ 4,742m€ 4,771m€ 29m€ atkinson (ε=1) 7,874m€ 7,923m€ 49m€ 9,045m€ 9,107m€ 62m€ atkinson (ε=2) 14,597m€ 14,722m€ 125m€ 16,968m€ 17,121m€ 153m€ source: own calculation based on soep (2018, wave v33.1) and ene’t gmbh (2018) schlesewsky and winter: inequalities in energy transition: the case of network charges in germany international journal of energy economics and policy | vol 8 • issue 6 • 2018 111 commercial customers to our analysis. however, their share in financing the grids is considerable and it appears to be promising to analyze this “functional” inequality. on the other hand, there is an emerging debate in the literature concerning distribution issues and whether or how far fairness norms should be applied to the realm of energy policy (gawel and korte, 2012; gawel et al., 2015). in the context of network charges, a more detailed discussion of relevant normative criteria is still pending. this will be an interesting challenge for future research in order to scrutinize the current tariff design of network charges and to make useful policy recommendations. furthermore, a comparative analysis of the distributional effects of various tariff designs in different countries appears to be promising. this might lead to the identification of best practices. however, this firstly relies on a normative evaluation of distributional effects and secondly poses the question how far tariff designs of some countries can be transferred and implemented in other countries and how far different systems are able to learn from each other, accordingly. 7. acknowledgments special thanks go to the soep study and ene’t gmbh for providing the underlying datasets of this study as well as tobias kreuz and his valuable help in gathering the data. we are also grateful to brian bloch for proofreading. references atkinson, a.b. (1970), on the measurement of inequality. journal of economic theory, 2(3), 244-263. bundesnetzagentur, bundeskartellamt. (2017), monitoringbericht 2017. bonn. available from: https://www.bundesnetzagentur.de/ shareddocs/downloads/de/allgemeines/bundesnetzagentur/ publikationen/berichte/2017/monitoringbericht_2017.pdf. [last retrieved on 2018 mar 27]. bundesnetzagentur. (2015), netzentgelt systematik elektrizität. bonn. available from: https://www.bundesnetzagentur.de/ shareddocs/downloads/de/sachgebiete/energie/unternehmen_ institutionen/netzentgelte/netzentgeltsystematik/bericht_ n e t z e n t g e l t s y s t e m a t i k _ 1 2 2 0 1 5 . p d f . [ l a s t r e t r i e v e d o n 2018 mar 27]. bundesnetzagentur. (2016a), hinweise für verteilnetzbetreiber zur anpassung der erlösobergrenze für das kalenderjahr 2017. available from: https://www.bundesnetzagentur.de/de/servicefunktionen/beschlusskammern/beschlusskammer8/bk8_01_ aktuelles/downloads/eog_hinweise_2017.pdf. [last retrieved on 2018 mar 27]. bundesnetzagentur. (2016b), netzentgelt: was ist ein netzentgelt (auch als netznutzungsentgelt bezeichnet)? available from: https://www. bundesnetzagentur.de/shareddocs/faqs/de/sachgebiete/energie/ verbraucher/energielexikon/netzentgelt.html. [last retrieved on 2018 mar 27]. bundesregierung. (2010), das energiekonzept 2050. available from: http://www.bundesregierung.de/content/de/html/breg/anlagen/ infografik-energie-textversion.pdf. [last retrieved on 2017 feb 06]. campbell, a. (2018), price and income elasticities of electricity demand: evidence from jamaica. energy economics, 69, 19-32. deutsche energie-agentur. (2010), dena-netzstudie ii: integration erneuerbarer energien in die deutsche stromversorgung bis 2020. available from: https://www.shop.dena.de/fileadmin/denashop/ media/downloads_dateien/esd/9105_fachbroschuere_denanetzstudie_ii.pdf. [last retrieved on 2018 mar 27]. ene’t gmbh. (2018), datenbank netznutzung strom deutschland. hückelhoven: ene’t gmbh. espey, j.a., espey, m. (2004), turning on the lights: a meta-analysis of residential electricity demand elasticities. journal of agricultural and applied economics, 36(1), 65-81. flues, f., thomas, a. (2014), the distributional effects of energy taxes. oecd taxation working papers no: 23. fouquet, r. (2014), long-run demand for energy services: income and price elasticities over two hundred years. review of environmental economics and policy, 8(2), 186-207. gawel, e., korte, k. (2012), verteilungseffekte des eeg: kritik an den falschen stellen. wirtschaftsdienst, 92(8), 512-515. gawel, e., korte, k., tews, k. (2015), energiewende im wunderland: mythen zur sozialverträglichkeit der förderung erneuerbarer energien durch das eeg. ufz discussion papers no: 2/2015. gini, c. (1912), variabilità e mutabilità: contributo allo studio delle distribuzioni e delle relazioni statistiche. bologna: c. cuppini. grimm, v., zöttl, g., rückel, b., sölch, c. (2015), regionale preiskomponenten im strommarkt: gutachten im auftrag der monopolkommission. available from: http://www.wirtschaftstheorie. wiso.uni-erlangen.de/wp-content/uploads/2016/02/gutachten_ regionale-preiskomponenten07.10.15.pdf. [last retrieved on 2018 mar 27]. grösche, p., schröder, c. (2014), on the redistributive effects of germany’s feed-in tariff. empirical economics, 46(4), 1339-1383. haucap, j., pagel, b. (2014), ausbau der stromnetze im rahmen der energiewende: effizienter netzausbau und effiziente struktur der netznutzungsentgelte. dice ordnungspolitische perspektiven, 55,  available form: https://www.econstor.eu/ bitstream/10419/91596/1/777566125.pdf. hiersig, r., wittig, d. (2015), gestaltung einer fairen lastenverteilung in den netzkosten-und netzentgeltstrukturen. energiewirtschaftliche tagesfragen, 65(7), 13-16. hinz, f. (2014), netznutzungsentgelte-konzepte und regionale verteilungseffekte. in: möst, d., schegner, p., editors. energiewende sachsen-aktuelle herausforderungen und lösungsansätze schriften des lehrstuhls für energiewirtschaft. dresden: tu dresden. p39-49. available from: https://www.researchgate.net/ profile/dominik_moest/publication/281525332_energiewende_ sachsen-aktuelle_herausforderungen_und_losungsansatze_ beitrage_der_abschlusskonferenz_des_enersax-projektes/ links/55ec77d408aeb6516268c9c7.pdf#page=47. [last retrieved on 2018 mar 27]. hinz, f., schmidt, m., möst, d. (2018), regional distribution effects of different electricity network tariff designs with a distributed generation structure: the case of germany. energy policy, 113, 97-111. loi, t.s.a., le, n.j. (2018), analysing households’ responsiveness towards socioeconomic determinants of residential electricity consumption in singapore. energy policy, 112, 415-426. löschel, a., flues, f., heindl, p. (2012), das erneuerbare-energien-gesetz in der diskussion. wirtschaftsdienst, 92(8), 515-519. neuhoff, k., bach, s., diekmann, j., beznoska, m., el-laboudy, t. (2012), steigende eeg-umlage: unerwünschte verteilungseffekte können vermindert werden. diw wochenbericht, 41, 3-12. rap. (2014), netzentgelte in deutschland. herausforderungen und handlungsoptionen: studie im auftrag von agora energiewende. berlin: rap. available from: https://www.agora-energiewende. de/fileadmin/downloads/publikationen/analysen/netzentgelte_ in_deutschland/agora_netzentgelte_web.pdf. [last retrieved on 2018 mar 27]. schlesewsky and winter: inequalities in energy transition: the case of network charges in germany international journal of energy economics and policy | vol 8 • issue 6 • 2018112 appendix a: derivation of hypothesis 2 the income share of total network charges is given by: n f p n k k v e p n v k k y ij t j t t t t j t j t ij t t t j t t j t , , , , , , , � = − + +( )+ − + + +( ) iij t, . differentiating with respect to income yields: ∂ ∂ = − + + +( ) ∂ ∂ + n y p n v k k y v y e v ij t ij t t t j t t j t ij t j t ij t ij t j , , , , , , , , ,, , , , , , t ij t ij t t t j t t j t ij t e y p n v k k y ∂ ∂       − + + +( )2 2 − − + +( )+  − + + +( )+ f p n k k v e p n v k k y j t t t t j t j t ij t t t j t t j t ij , , , , , , ,, , , , , , t j t ij t t t j t t j t ij t v y p n v k k y ∂ ∂             − + + +( )2 2 = ∂ ∂ + ∂ ∂ − − + +( )v y e v e y f p n k k y j t ij t ij t j t ij t ij t j t t t t j t ij , , , , , , , , ,tt j t ij t ij t t t j t t j t ij t v e y p n v k k y − ∂ ∂ − + + +( ) , , , , , , − − + +( )+  ∂ ∂ − + + f p n k k v e v y p n v k j t t t t j t j t ij t j t ij t t t j t t , , , , , , , ++( )k yj t ij t, , 2 = ∂ ∂ −      − − + + v e y e y f p n k k yj t ij t ij t ij t ij t j t t t t j t ij , , , , , , , ,tt t t j t t j t ij tp n v k k y− + + +( ), , , − ∂ ∂ − + + − + + + − − v y p n k k p n v k k f e p n j t ij t t t t j t t t j t t j t j t ij t t t , , , , , , , ++ + +( )v k k yj t t j t ij t, , , = ∂ ∂ −      − − + + v e y e y f p n k k yj t ij t ij t ij t ij t j t t t t j t ij , , , , , , , ,tt t t j t t j t ij t j t ij t t t t j t t t p n v k k y v y p n k k p n − + + +( ) + ∂ ∂ − + + − + , , , , , , vv k k d j t t j t ij t , , , . + + appendix b: definition of inequality metrics for weighted survey data the gini coefficient the gini coefficient (gini, 1912) is probably the most common inequality measure in economics. it can be derived from the lorenz curve which plots the cumulative income share of the bottom x% of the population. the gini coefficient is normalized to the interval (0,1), with 0 indicating perfect equality (every household has the same income) and values close to 1 indicating perfect inequality (only one household has a positive income).13 for weighted survey data, it is defined as:  = − = =∑ ∑i n j n i j i jy y y 1 1 2 ω ω (10) where yi is the income of household i y y i i i, = ∑ω is its weighted mean, n the total number of observed households and ωi=wi⁄(∑iwi) the relative weight of household i (with wi as the projection factor). the theil index the theil index (theil, 1965) is a special case of the generalized entropy index family stemming from information theory. originally, it measured the informational content of a number of observations. this content is assumed to be minimal if every observation has the same probability – the entropy reaches its maximum value. by contrast, 13 note that the gini coefficient cannot reach a value of 1 for finite populations, as this is a limit value. schulte, i., heindl, p. (2017), price and income elasticities of residential energy demand in germany. energy policy, 102, 512-528. sen, a. (1973), on economic inequality. oxford: oxford university press. soep. (2018), data from 1984-2016. doi: 10.5684/soep.v33.1. available from: https://www.diw.de/de/diw_02.c.240089.de/hinweise_fuer_ autoren.html#493461. statistisches bundesamt. (2018), bruttostromerzeugung in deutschland für 2015 bis 2017. available from: https://www.destatis.de/de/ zahlenfakten/wirtschaftsbereiche/energie/erzeugung/tabellen/ bruttostromerzeugung.html. [last retrieved on 2018 mar 27]. techert, h., niehues, j., bardt, h. (2012), ungleiche belastung durch die energiewende: vor allem einkommensstarke haushalte profitieren. wirtschaftsdienst, 92(8), 507-512. theil, h. (1965), the information approach to demand analysis. econometrica, 33(1), 67-87. többen, j. (2017), regional net impacts and social distribution effects of promoting renewable energies in germany. ecological economics, 135, 195-208. schlesewsky and winter: inequalities in energy transition: the case of network charges in germany international journal of energy economics and policy | vol 8 • issue 6 • 2018 113 the informational content increases with decreasing entropy. this measure has been applied to the empirical investigation of economic inequality. the ”informational content” of an income distribution increases the more it differs from perfect equality (i.e., with lower entropy). usually, the theil l (α = 0) and the theil t (α = 1) index are distinct from one another. these indices are defined as: 1 1 ln 0, ln 1 n i i i n i i i i y if y y y if y y α ω α ω α = =  =  =   =  ∑ ∑  (11) with the definitions from above. generally, the theil t index is more common in empirical economics (e.g., grösche and schröder, 2014. p. 1346). the theil indices can take any nonnegative value and increase with inequality. the atkinson index the atkinson index (atkinson, 1970) defines the maximum share of mean income a society would be willing to give up in order to reach perfect income equality. as this depends on the level of inequality aversion ε this implies a social welfare function which is concave in individual incomes: 1 0 1 1 1 \ 1, 1 ( ) ln 1 n i i i n i i i y w if w w y if ε ε ε ε ε − > = =  − ∈ − =   =  ∑ ∑ y  (12) where y is the vector of household incomes. based on this social welfare function, we can define the corresponding equally distributed equivalent income yε – i.e., household income in a perfectly equal society, which is associated with the same level of social welfare as the actual income distribution. 1 1 1 0 1 1 \ 1, 1, i n i i i n i i y if y y if ε ε ε ω ω ε ε − − > = =    ∈  =   =  ∑ ∏   (13) which yields the weighted geometric mean for ε = 1. finally, we normalize: ε ε= −1 y y (14) since, for concave social welfare functions (i.e., for a positive inequality aversion ε > 0, the equally distributed equivalent income yε is always smaller than the weighted mean y , the atkinson index is normalized to ε ∈[ ]0 1, with higher values denoting higher inequality. consequently, we are able to calculate a “welfare loss” arising from income inequality. this welfare loss is the difference of mean and equally distributed income at a household level or l w y y w y i n i i n iε ε ε= − = = = ∑ ∑ 1 1 ( )  (15) at an aggregate level. it can be interpreted as society’s willingness to pay for eliminating income inequality, and is calculated for our purposes in subsection 5.3. international journal of energy economics and policy vol. 1, no. 4, 2011, pp.78-94 issn: 2146-4553 www.econjournals.com economics of carbon dioxide sequestration and mitigation versus a suite of alternative renewable energy sources for electricity generation in u.s. ramesh agarwal washington university in st. louis, usa. email: rka@wustl.edu lee chusak washington university in st. louis, usa. email: lee.chusak@gmail.com zheming zhang washington university in st. louis, usa. email: zheming.zhang@wustl.edu abstract: an equilibrium economic model for policy evaluation related to electricity generation in u.s has been developed; the model takes into account the non-renewable and renewable energy sources, demand and supply factors and environmental constraints. the non-renewable energy sources include three types of fossil fuels: coal, natural gas and petroleum, and renewable energy sources include nuclear, hydraulic, wind, solar photovoltaic, biomass wood, biomass waste and geothermal. energy demand sectors include households, industrial manufacturing and non-manufacturing commercial enterprises. energy supply takes into account the electricity delivered to the consumer by the utility companies at a certain price which maybe different for retail and wholesale customers. environmental risks primarily take into account the co2 generation from fossil fuels. the model takes into account the employment in various sectors and labor supply and demand. detailed electricity supply and demand data, electricity cost data, employment data in various sectors and co2 generation data are collected for a period of nineteen years from 1990 to 2009 in u.s. the model is employed for policy analysis experiments if a switch is made in sources of electricity generation, namely from fossil fuels to renewable energy sources. as an example, we consider a switch of 10% of electricity generation from coal to 5% from wind, 3% from solar photovoltaic, 1% from biomass wood and 1% from biomass waste. the model is also applied to a switch from 10% coal to 10% from clean coal technologies. it should be noted that the cost of electricity generation from different sources is different and is taken into account. the consequences of this switch on supply and demand, employment, wages, and emissions are obtained from the economic model under three scenarios: (1) energy prices are fully regulated, (2) energy prices are fully adjusted with electricity supply fixed, and (3) energy prices and electricity supply both are fully adjusted. keywords: carbon dioxide sequestration and mitigation, renewable energy, electricity generation, economics jel classifications: c54, c68, q42, q48 nomenclature a household asset c consumption c aggregate household consumption demand d co2 emissions e total electricity demand ec commercial electricity demand ef industrial electricity demand eh household electricity demand economics of carbon dioxide sequestration and mitigation versus a suite of alternative renewable energy sources for electricity generation in u.s. 79 eh aggregate household electricity demand e(s) electricity generated from sources s k capital input m(s) material inputs for source s n total labor demand nc commercial sector labor ne electricity sector labor ne(s) electricity sector labor for sources s nf industrial labor p price of electricity q relative price of an investment in units of the consumption good r real interest rate s source of electricity, i.e., coal, nuclear, etc. vh household value function ff industrial value function w wage x consumption good x aggregate household goods consumption demand y output z investment z total investment βh household depreciation factor βf industrial depreciation factor δ capital depreciation rate γ(s) unit pollution generation from source s η cobb-douglass parameter µ(s) unit cost of electricity from a given sources s ν unit cost of other inputs (energy sources) θ source labor requirement parameter σ constant growth rate for commercial electricity demand ζ employee-energy mix parameter 1. introduction modeling of co2 emissions and the economic factors related to the switch from fossil fuels to renewable energy sources for electricity generation has become very important with the recent trends of moving toward a more economically and environmentally sustainable society. the brundland definition of sustainable development, 'the development that meets the needs of the present without compromising the ability of future generations to meet their own needs' is considered key to sustainability (brudtland, 1987). the effects of global warming and its impact on climate change of the planet are making it apparent that the path humanity has taken so far, that is burning of excessive amounts of fossil fuels for meeting the energy needs, is not sustainable. it is therefore important to create economic models that can be used by the policy makers to make informed decisions which can lead to a sustainable path to meet the energy requirements in an economically and environmentally acceptable manner. the united states generates most of the electricity from coal based power plants. the other power generation sources include: nuclear, hydroelectric, natural gas, biomass waste, biomass wood, geothermal, solar photovoltaic, solar thermal and wind. in 2006, coal (49.3%), nuclear (19.5%), hydroelectric (7.2%) and natural gas (20.0%) constituted the major sources for electric power generation compared to biomass waste (0.4%), biomass wood (1.0%), solar photovoltaic and solar thermal (0.01%), wind (0.6%) and geothermal (0.4%). during the past 15 years, wind power has become cheaper and competitive with fossil fuel based electricity generation, and therefore is increasingly deployed in the u.s. and around the world. photovoltaic power generation is still very limited because at present it is not very efficient and is very expensive compared to other sources of electricity generation. recently, there has been considerable emphasis by the department of energy (doe) and electric utility companies on research in "clean coal technologies". in particular carbon international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.78-94 80 capture and sequestration (ccs) is being considered as a viable technology that may make it possible the continued use of fossil fuels with co2 emissions being captured and then sequestered in geological formations. however, the ccs technology is yet to be tested for a medium to large scale power generation facility. it appears unlikely that carbon capture and sequestration (ccs) will be wide spread among power generation facilities within the next 15 years. it is therefore necessary to explore both the alternative renewable energy sources along with ccs for power generation and assess the relative economic viability of the two approaches in the near term horizon of twenty years. in this paper, we consider the economics of electricity generation in the u.s. for two switches from conventional fossil fuel based energy sources. the first switch is made from non-renewable fossil fuel based energy sources to renewable energy sources. the second switch is made from nonrenewable fossil fuel based energy sources (coal) to clean coal technologies (in particular ccs). for this purpose we develop an energy economic model, which is an optimization based equilibrium model where the economy is modeled in a top-down manner and the electricity generation sector is modeled using the bottom-up approach. other significant energy economic models discussed in the literature are the mrn-neem model (cra international, 2008) and the national energy model (nakata, 2004). the mrn-neem model is a combination of the mrn (multi-region national) model which is a top-down general equilibrium model and the neem (north american electricity and environmental model) model which is a bottom up model of the electricity generation sector. the mrn-neem model has been applied to the united states. the national energy model is a dynamic model that tracks the primary energy sources and how they are consumed by households and industry; this model has only been applied to japan. the motivation behind the development of an energy economic model for electricity generation in the u.s. has been to create a model that would forecast the effects on the united states economy of policy changes in the usage of energy sources from fossil fuels to renewables in order to achieve the target goals of greenhouse gas (ghg) emissions in the next 25 to 50 years. with a worldwide emphasis on sustainability, there is a great interest in switching electricity generation sources from predominantly coal based to more eco-friendly renewable sources. the goal then is to create a model that can determine the economically best mix of energy generation sources to achieve the environmental constraints on co2 emissions in 2025 and 2050. the model should also determine the impact of policy changes on electricity price, its supply and demand, and on employment. at present, there are very few models that address this goal in a comprehensive manner. there are mainly four types of approaches currently employed in the majority of energyeconomic models: top-down, bottom-up, optimization and equilibrium, and dynamic. the top-down and bottom-up models can be used together to create a more detailed model. the salient features of the models are briefly described below. top-down/bottom-up models according to nakata, "the top-down label comes from the way modelers apply macroeconomic theory and econometric techniques to historical data on consumption, prices, incomes, and factor costs to model the final demand for goods and services, and the supply from main sectors (energy sector, transportation, agriculture, and industry)" (nakata, 2004). all of the agents in the model respond to changes in prices and allow for multiple regions to be linked by trade (cra international, 2008). bottom-up models model a given sector in detail, in the present case – electricity generation. these models use detailed costs for current and future technologies to model the effects of policy on the electricity generation sector (cra international, 2008). they, "capture technology in the engineering sense: a given technique related to energy consumption or supply, with a given technical performance and cost" (nakata, 2004). optimization based models optimization based models are based on the concept of maximizing utility and minimizing the cost. the optimization takes place at a given point in time and is considered to be in steady state. the optimization based models employ either the top-down or bottom-up approach to modeling. the optimization equations used in this paper, for the most part, follow the format of the bellman equation:   00 0 0 1 ( ) max ( , ) ( )av x f x a v x  (1) where v is the value function (bellman, 1957). the value function is "the best possible value of the objective, written as a function of the state [variable]" (bellman, 1957). the bellman equation (1) economics of carbon dioxide sequestration and mitigation versus a suite of alternative renewable energy sources for electricity generation in u.s. 81 gives the value function at a given time period as the maximum of some objective function (f) plus the value function of the next time period with a discounting factor β. this recursive format of the bellman equation allows for the calculation of the value function at normalized time t = 1 if the value function and the objective function (f) are known at normalized time t = 0. the first-order conditions are the partial derivatives of the bellman equation with respect to the variables over which the optimization is being preformed (not the state variables).    00 0 0 1 0 ( ) max ( , ) ( )av x f x a v xa      (2) in this model, the states x0 and x1 are recursively defined as:  1 0x g x (3) where g is a specified function. the benveniste-scheinkman condition, also known as the envelope condition, allows the calculation of the derivative of the value function with respect to the state variable (bergin, 1998; boileau, 2002):   )(),(max)( 1000 0 0 xvaxfxv x a    (4) using the first-order necessary conditions and the benveniste-scheinkman condition, the value function can be calculated. the present model, developed in this paper, basically falls under this category; however it is only concerned with the steady state results. a bottom-up approach was applied to the electricity generation sector so that the effect of switching from one energy source to another could be analyzed; a top-down approach was also used to determine the economy wide effects of the policy changes. dynamic models dynamic models are an extension of the optimization based models. they operate in a manner similar to the optimization models except that the optimization takes place on a time interval and does not assume the steady state. dynamic models are based on the same mathematical background as described in the previous section. they "can also be termed partial equilibrium models. these technology-oriented models minimize the total costs of the [system], including all end-use sectors, over a 40-50 year horizon and thus compute a partial equilibrium for the [markets]" (cra international, 2008). unlike the present model developed in this paper, the dynamic model results into a time series that can provide information as to how the current decisions affect the future outcomes. 2. present model: optimization based general equilibrium model operative sectors of the economy we consider a model economy with a continuum of households of mass n and three operative sectors: the industrial manufacturing sector, the commercial sector and the electricity generation sector. we omit the insignificant transportation sector because of relatively insignificant consumption of electricity compared to residential, manufacturing and commercial sectors. the government sector is also omitted because its behavior is different from the other sectors. the households provide the firms with labor and investment while the firms provide the households with goods, services and wages. the households pay the government taxes and the government grants the households subsidies. firms can provide each other with goods and services. the optimum level of production by a firm is the point at which profit is maximized. household each household owns one unit of labor, whose consumption is produced by the consumption good (x) and electricity (eh): ( , )hc h x e (5) set the consumption good x as the numeraire and denote the unit price of electricity as p. the optimization problem is given by: international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.78-94 82  1 , 1 ( ) max ( ) ( ) . . (1 ) ( , ) h t t h h h t t t c e h t t t t t t t h t t t v a u c v a s t a r a w x p e c h x e            (6) where a denotes household asset, w the wage, r the real interest rate and βh the subjective discount factor facing each household. the total population of households (n) is assumed to be fully employed in the three (industrial manufacturing, commercial and electricity generation) sectors of the model economy. aggregate household demands are then defined by: t t tc n c (7) t t tx n x (8) h h t t te n e (9) industrial sector there is a mass of producers normalized to one. each producer hires labor (nf), in conjunction with capital input (k) and electricity (ef), to manufacture goods y: ( , , )f fy f k n e (10) the output y is used for consumption and capital investment: y x qz  (11) where q denotes the relative price of investment in units of the consumption good. let capital depreciate at rate δ. the optimization problem is given by:  1 , , 1 ( ) max ( ) . . (1 ) ( , , ) f f t t t f f f f f t t t t t t t t t n e z t t t f f t t t t v k y q z w n p e v k s t k z k y f k n e              (12) where βf the subjective discount factor facing each producer. the commercial sector this is a sector with measuring difficulties. this sector includes not only commercial firms, but educational institutions and other nonprofit organizations. its inputs and outputs are hard to measure. for simplicity, the commercial sector is modeled in a stylized manner with its demand for electricity given by: 1 (1 ) c c t te e   (13) where σ > 0 is assumed an exogenous constant. under a leontief production function specification, the demand for labor is given by: c c t tn e (14) where ζ > 0 is the employee-energy mix parameter. aggregate electricity demand and electricity generation total electricity demand is therefore given by: , , i i h f c e e    (15) electricity can be generated via various sources s = 1 (coal), s = 2 (nuclear), s = 3 (hydro), s = 4 (petroleum), s = 5 (natural gas), s = 6 (biomass wood), s = 7 (biomass waste), s = 8 (geothermal), s = 9 (solar thermal and photovoltaic), s = 10 (wind) and s = 11 (clean coal). the generation function can be specified as follows: ( ) ( ( ), ( ), )ee s m n s m s s (16) depending on labor (ne) and other inputs (m). total electricity generated from all sources is: ( ) s e e s  (17) while the labor demand by all sources of electricity generation is: economics of carbon dioxide sequestration and mitigation versus a suite of alternative renewable energy sources for electricity generation in u.s. 83 ( )e e s n n s  (18) we assume fixed unit labor requirements θ across all sources: ( ) ( )en s e s (19) thus, we have: ( ) ( )e e e s n s n e  (20) and can rewrite (16) as: 1 ( ) min ( ), ( ( ))ee s n s g m s        (21) where g(m(s)) = m(θe (s), m(s), s). denote the unit cost of other inputs as v. utility firms using source s face the following optimization problem:  min ( ) ( ) 1 . . ( ) min ( ), ( ( )) e e wn s vm s s t e s n s g m s          (22) total cost incurred in electricity generation is: ( ) ( )e s wn s vm s   (23) let µ(s) denote the unit cost of electricity generation under source s. we can compute: ( ) ( ) ( ) ( )evm s s e s wn s  (24) since we can measure m(1), ν can be backed out as well as m(2), m(3), m(4), m(5), m(6), m(7), m(8), m(9), m(10) and m(11). denote unit pollution generation of source s as γ(s). total pollution generation in electricity generation is: ( ) ( ) s s e s (25) aggregate labor market total labor demand is: , , i i f c e n n   (26) in equilibrium, labor supply equals labor demand. optimization and equilibrium household's optimization can be rewritten as:   , ( ) max ( ( , )) (( 1) ) h t t h h h h h t t t t t t t t t x e v a u h x e v r a w x p e      (27) the first-order necessary conditions are given by: 1t h h c x au h v  (28) 1 h t h h c a te u h v p    (29) implying he x h p h  (30) where the time subscript is suppressed whenever it would not cause any confusion. the benvenistescheinkman condition is given by: 1 ( 1) t t h h h a a tv v r    (31) manufacturer's optimization problem can be rewritten as:   , , ( ) max ( , , ) ( (1 ) ) f f t t t f f f f f f f t t t t t t t t t t t t n e z v k f k n e q z w n p e v z k        (32) international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.78-94 84 the first-order conditions are derived below: f t tn f w (33) f t te f p (34) 1t f f k tv q   (35) the benveniste-scheinkman condition is given by: 1 (1 ) t t t f f f k k kv f v     (36) which can be combined with (35) to yield: 1 (1 ) t t t f f f k k kv f v     (37) under fixed labor requirements (19), utility firm's optimization leads to: ( ( ))m v g m s w  (38) 1 ( ) ( ) ( ( ))ee s n s g m s    (39) steady-state equilibrium in steady-state equilibrium, all variables are constant. as a consequence, (31) implies: 1 1 hr    (40) whereas (6), (12) and (37) yield the following steady-state relationships: 1 1h hx pe w a          (41) z k (42) 1 1k ff q         (43) model calibration for the purpose of calibration analysis, we impose the following functional forms: ln( )u c (44) 1( , ) ( )h hh x e x e  (45)      1/ 1 ( , , ) 1f f f ff k n e a k n e             (46) ( ( )) ( )g m s bm s  (47) the model is calibrated based on the following steady-state relationships. in this paper, we use the 1990-2006 average values of x , z, nf, nc, ne, eh, ef, ec, e(s), µ(s), m(1), w, and p as their steady-state values, where all values are in million dollars at 2000 constant prices. the calibration is conducted for each year on which the model is run. there are a few adjustments needed to fit the model. first, the total employment in our model economy is computed using (26): 622, 424, 294 76, 203,146 62,139 99.249 10f c en n n n        (48) since total employment of the u.s. is 123.035×106, we must scale down all the aggregates by a factor of 99.249/123.035 = 0.8067, yielding: 5, 019, 207 , 759, 482 , 912, 595 , 814, 054 , 797,165h f cx z e e e     (49) now the employee-energy mix parameter in the commercial sector can be derived using equation (14) as ζ = 95.5927. second, aggregate electricity demand and supply are not identical in the data. we thus adjust e(s) so that the values in (15) and (17) are consistent. that is, call the raw data of electricity generation as es(s), define es = ∑ses(s) and set e = eh + ef + ec. we must adjust electricity generation by the factor e to have: e(s) = (e/es)∙es(s). accordingly, we obtain: economics of carbon dioxide sequestration and mitigation versus a suite of alternative renewable energy sources for electricity generation in u.s. 85                   1 1, 298, 463, 2 496, 095 3 204, 693, 5 393, 439 6 26, 208, 7 12,878, 8 10, 581, 9 354, 10 5,181 e e e e e e e e e          (50) third, material inputs of various forms of electricity generation are very different. to circumvent the problem, we choose to normalize the material inputs to generate e(1) as unity, that is, m(1) = 1. we can then use the cost data (million dollars per million megawatt-hours):                     1 0.030509, 2 0.022675, 3 0.009513, 4 0.059974, 5 0.049816 6 0.072496, 7 0.039934, 8 0.08, 9 0.348, 10 0.052359 µ µ µ µ µ µ µ µ µ µ           (51) in conjunction with (24) to compute:                   29, 270, 2 0.249303, 3 0.010817, 4 0.135025 5 0.562525, 6 0.057777, 7 0.01065, 8 0.026039 9 0.004115229, 10 0.007857166           v m m m m m m m m m (52) the total electricity cost is then computed as follows: ( ) ( ) ( ) ( )e s s tc wn s vm s s e s      (53) next, we can use (8) and (9) to yield x = 0.050572 and eh = 0.009195031. the average real interest rate is set at a commonly selected rate 5%, faced by all agents. thus, (40) implies βh = βf = 1/(1+r) = 1/1.05. the capital depreciation rate usually falls in the range between 5% and 10%, which we set at 7.5%. the annual wage rate and the relative price of energy are given by w = 0.03236 and p = 0.06936, respectively. then, from (41) and (42), we can compute: 0.37694 hx pe w a r     (54) 10,126, 430 z k    (55) the cobb-douglass utility function simplifies (30) to: 1 h x p e     (56) which gives the calibrated parameter value 0.98755h x x pe     the nested ces production function implies that (33), (34) and (43) can be rewritten as: (1 )f fn y f w n     (57) (1 )f fe y f p e     (58) ( )k y f r q k      (59) where 1 1 ( ) ( ) (1 )( ) f f f k n k n e                    . the last equation above can be combined with (11) to derive: 1 x y k r       (60) and y q r z      (61) which can be further substituted into the marginal product of labor and marginal product of energy expressions to solve jointly α and ρ as functions of φ. from the household side, we learn that the energy demand share is 1 − η = 0.012454. it is reasonable to set the energy demand share by manufacturers twice as much 1 − φ = 0.02491, or φ = 0.975092. we can then calibrate α = 0.935881 international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.78-94 86 and ρ = 0.635049. thus, manufactured output and the unit cost of capital investment are computed as: y = 11,374,760 and q = 8.36827. these values together with the production function enable us to pin down the scaling parameter.   1/ 1 1.102033 ( ) (1 )( )f f y a k n e            (62) finally, we manipulate (20), (38) and (39), using the specific functional form, to calibrate: 24615.0 e n e  (63) 82979.2 )( )(  se e wn svm e (64)   463,298,1 )1( )1(  m e b (65) given the co2 production of 2,229.756 million metric tons essentially from sources 1, 4 and 5, we can obtain an emission conversion ratio (per million megawatts of electricity generated) at γ(fossil fuels) = 2,229.756/1,767,895 = 0.00126125, with γ(2) = γ(3) =γ(6) = γ(7) = γ(8) = γ(9) = γ(10) = γ(11) = 0, due to the fact that the majority of carbon emissions are coming from the combustion of fossil fuels. this completes the sample calibration procedure in the steady-state equilibrium. 3. policy analysis in this section, we perform the policy analysis. in order to do this, we need to derive a few more useful steady-state equilibrium relationships. from (41) and (56), we can write household's goods consumption demand and electricity demand as: )( rawx  (66)   raw p eh  1 1 (67) from (14), (18), and (26), manufacturing firm's labor demand is given by: eenn cf   (68) substituting this into the production function, (57) and (58) enable us to express y, w and p all as functions of (k, ef). using (8), (10), (42) and (66), we can write household's asset as:          w n qky r a  1 (69) which is a function of (k, ef) as well, as are x and eh, based on the demand relationships derived above. aggregating each household's electricity demand with use of (69) and equating it with electricity supply, we obtain: 1h c fy qke e e e p          (70) this together with (59) enables us to solve jointly (k, ef). the solution can then be substituted into other functions to derive y, w, p, a, x, eh, and eh. we are now ready for policy experiments. we perform two experiments. in the first, we consider switching 10% of electricity generation from coal to 5% wind, 3% solar thermal and photovoltaic, 1% biomass waste and 1% biomass wood by 2030. in the second, we consider switching 10% electricity generation from coal to clean coal (using ccs) by 2030. figures i-iii respectively show the energy generation mix in 2030 for the business as usual (bau) scenario and for proposed scenarios with 10% switch from coal to renewables, and 10% switch from coal to clean coal with ccs. economics of carbon dioxide sequestration and mitigation versus a suite of alternative renewable energy sources for electricity generation in u.s. 87 figure i: energy generation mix for 2030 in business as usual (bau) case 2030 bau coal petroleum natural gas nuclear hydroelectric (conventional) wind solar thermal and photovoltaic biomass wood geothermal biomass waste clean coal figure ii: energy generation mix for 2030 for 10% switch from coal to renewables 2030 renewable coal petroleum natural gas nuclear hydroelectric (conventional) wind solar thermal and photovoltaic biomass wood geothermal biomass waste clean coal international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.78-94 88 figure iii: energy generation mix for 2030 for 10% switch from coal to clean coal with ccs 2030 cc coal petroleum natural gas nuclear hydroelectric (conventional) wind solar thermal and photovoltaic biomass wood geothermal biomass waste clean coal utilizing a series of curve fits to the data from 1990-2009, the projected business as usual energy generation mix from 2010 to 2030 is obtained as shown in figure iv. figure iv: projected electricity generation mix from 2010 to 2030 for business as usual scenario electricity generation mix business as usual 0 1000000 2000000 3000000 4000000 5000000 6000000 2010 2015 2020 2025 2030 year el ec tr ic ity g en er at ed [ 10 00 m w *h r] clean coal biomass waste geothermal biomass wood solar thermal and photovoltaic wind hydroelectric (conventional) nuclear natural gas petroleum coal economics of carbon dioxide sequestration and mitigation versus a suite of alternative renewable energy sources for electricity generation in u.s. 89 the first policy scenario, that is switching 10% coal to 5% wind, 3% solar, 1% biomass waste and 1% biomass wood was applied to the business as usual energy generation mix in figure iv to yield the renewable energy generation mix shown in figure v. figure v: projected electricity generation mix from 2010 to 2030 for policy scenario 1, that is switching 10% coal to renewables (5% wind, 3% solar, 1% biomass waste and 1% biomass wood) electricity generation mix renewable 0 1000000 2000000 3000000 4000000 5000000 6000000 2010 2015 2020 2025 2030 year e le ct ri ci ty g en er at ed [ 10 00 m w *h r] clean coal biomass waste geothermal biomass wood solar thermal and photovoltaic wind hydroelectric (conventional) nuclear natural gas petroleum coal the second policy scenario, that is switching 10% coal to clean coal technologies using ccs, was applied to the business as usual energy generation mix in figure iv to yield the energy generation mix with clean coal as shown in figure vi. for the three scenarios: (1) bau, (2) 10% switch from coal to renewables, and (3) 10% switch from coal to clean coal using ccs, the policy implications are examined under the following conditions: (a) both the energy supply and price are regulated, (b) energy price is fully adjusted with electricity supply fixed, and (c) both the energy price and electricity supply are fully adjusted. the results of policy simulations using our economic model for the three scenarios under the three types of price and supply conditions are summarized in tables 1, 2 and 3 respectively. international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.78-94 90 figure vi: projected electricity generation mix from 2010 to 2030 for policy scenario 2, that is switching 10% coal to clean coal using ccs electricity generation mix clean coal 0 1000000 2000000 3000000 4000000 5000000 6000000 2010 2015 2020 2025 2030 ye ar el ec tr ic it y g en er at ed [ 10 00 m w *h r] clean coal biomass waste geothermal biomass wood solar thermal and photovoltaic wind hydroelectric (conventional) nuclear natural gas petroleum coal table 1. policy simulation results for the three scenarios under the condition – both the energy supply and price are regulated. all values in the table are percentage change from the business as usual case energy supply and price regulated 20 15 r en ew ab le s 20 15 c le an c oa l 20 20 r en ew ab le s 20 20 c le an c oa l 20 25 r en ew ab le s 20 25 c le an c oa l 20 30 r en ew ab le s 20 30 c le an c oa l k capital input 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% ef-industrial electricity demand 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% y output 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% p price 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% w wage 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% a household asset 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% x consumption 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% eh -household electricity demand 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% d emission -8.1% -8.1% -8.1% -8.1% -8.1% -8.1% -8.1% -8.1% tcv total cost of generation 8.8% 3.0% 7.7% 2.6% 6.9% 2.2% 6.3% 2.0% economics of carbon dioxide sequestration and mitigation versus a suite of alternative renewable energy sources for electricity generation in u.s. 91 table 2. policy simulation results for the three scenarios under the condition – the energy supply is regulated and the energy price is adjusted. all values in the table are percentage change from the business as usual case energy supply regulated and energy price adjusted 20 15 r en ew ab le s 20 15 c le an c oa l 20 20 r en ew ab le s 20 20 c le an c oa l 20 25 r en ew ab le s 20 25 c le an c oa l 20 30 r en ew ab le s 20 30 c le an c oa l k capital input -0.2% -0.2% -0.6% -0.2% -0.6% -0.2% -0.5% -0.2% ef-industrial electricity demand 21.0 % -8.0% -18.9% -6.9% -17.3% -6.0% -16.1% -5.4% e total electricity demand -8.5% -2.3% -7.4% -2.7% -6.5% -2.2% -5.9% -2.0% y output -0.7% -0.3% -0.6% -0.2% -0.6% -0.2% -0.6% -0.2% p price 8.8% 3.0% 7.7% 2.6% 6.9% 2.2% 6.3% 2.0% w wage -0.7% -0.2% -0.6% -0.2% -0.6% -0.2% -0.5% -0.2% a household asset -0.9% -0.3% -0.8% -0.3% -0.7% -0.2% -0.7% -0.2% x consumption -0.8% -0.3% -0.7% -0.2% -0.6% -0.2% -0.6% -0.2% eh -household electricity demand -8.8% -3.2% -7.8% -2.7% -7.1% -2.4% -6.5% -2.1% d emission -8.1% -8.1% -8.1% -8.1% -8.1% -8.1% -8.1% -8.1% tcv total cost of generation 8.8% 3.0% 7.7% 2.6% 6.9% 2.2% 6.3% 2.0% table 3. policy simulation results for the three scenarios under the condition – both the energy supply and price are fully adjusted. all values in the table are percentage change from the business as usual case energy supply and price fully adjusted 20 15 r en ew ab le s 20 15 c le an c oa l 20 20 r en ew ab le s 20 20 c le an c oa l 20 25 r en ew ab le s 20 25 c le an c oa l 20 30 r en ew ab le s 20 30 c le an c oa l d emission -16.0% -11.1% -14.9% -10.6% -14.2% -10.2% -13.6% -9.9% tcv total cost of generation -0.5% -0.3% -0.2% -0.2% -0.1% 0.0% 0.1% 0.0% layoff [ people ] 3.8e+04 1.4e+04 2.9e+04 1.1e+04 2.3e+04 7.8e+03 1.7e+04 5.7e+03 w wage -0.7% -0.3% -0.6% -0.2% -0.6% -0.2% -0.5% -0.2% x consumption -0.8% -0.3% -0.7% -0.3% -0.7% -0.2% -0.6% -0.2% eh household electricity demand -8.8% -3.2% -7.8% -2.7% -7.1% -2.4% -6.5% -2.1% the results in tables 1, 2 and 3 under three types of regulatory conditions are summarized below for years 2015, 2020, 2025 and 2030. condition 1: energy price fully regulated when energy prices are fully regulated, the source switch under scenario 2 (renewables) causes total electricity generation cost to go up by 8.8% in 2015 and by 6.3% in 2030 and emissions to decrease by 8.1% without changing any other endogenous variables. however, the source switch under scenario 3 (clean coal) causes total electricity generation cost to go up only by 3.0% in 2015 and by 2% in 2030 and emissions to decrease by 8.1%. this type of regulatory environment is undesirable at this time because the government would have to pay for the increase in total cost of electricity generation. if at some future time fossil fuel based electricity became equal priced or more expensive than renewables or clean coal then the government would either not lose money or make a profit. international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.78-94 92 condition 2: energy price fully adjusted with electricity supply fixed under this condition, electricity supply and the level of employment remains fixed. when energy prices are fully adjusted, the source switch described above under scenarios 2 and 3 will raise the energy price by the same amount as under condition 1 and reduce the emissions by the same amount. however, higher energy price lowers demand: under scenario 2 (renewables) the household demand lowers by 8.8% in 2015 and by 6.5% in 2030, the industrial demand lowers by 21% in 2015 and by 16.1% in 2030 and total demand by 8.5% in 2015 and by 5.9% in 2030. the capital input decreases by 0.2% in 2015 and by 0.5% in 2030. the wages reduce by 0.7% in 2015 and by 0.5% in 2030. the output is lowered by 0.7% in 2015 and by 0.6% in 2030. as a consequence, the household assets are lowered by 0.9% in 2015 and by 0.7% in 2030 and the household consumption decreases by 0.8% in 2015 and by 0.6% in 2030. under scenario 3 (clean coal) the household demand lowers by 3.2% in 2015 and by 2.1% in 2030, the industrial demand lowers by 8% in 2015 and by 5.4% in 2030 and total demand by 2.3% in 2015 and by 2% in 2030. the capital input decreases by 0.2% in 2015 and by 0.2% in 2030. the wages reduce by 0.2% in 2015 and by 0.2% in 2030.the output is lowered by 0.3% in 2015 and by 0.2% in 2030. as a consequence, the household assets are lowered by 0.3% in 2015 and by 0.2% in 2030 and the household consumption decreases by 0.3% in 2015 and by 0.2% in 2030. additionally, fixed electricity supply implies emissions decrease by exactly 10% of the emissions from coal. this represents an overall reduction of 8.1% in co2 emissions. condition 3: energy price and electricity supply both fully adjusted under this condition, the source switch under both scenarios 2 and 3 will raise the energy price and lower the electricity demand in the same manner as under condition 2. however, in contrast with condition 2, electricity supply is now fully adjusted to meet the demand, which causes a layoff of workers. under scenario 2, it will result in a layoff of 38,000 workers in 2015 and of 17,000 workers in 2030. so the expected market wages reduce by 0.7% in 2015 and by 0.5% in 2030 and goods consumption decreases by 0.8% in 2015 and by 0.6% in 2030. because electricity supply is now fully adjusted downward, the total electricity generation cost goes down by 0.5% in 2015 and by 0.1% in 2030 and emissions decrease by 16% in 2015 and by 13.6% in 2030. under scenario 3, it will result in layoff of 14,000 workers in 2015 and of 5,700 workers in 2030. so the expected market wages reduce by 0.3% in 2015 and by 0.2% in 2030 and goods consumption decreases by 0.3% in 2015 and by 0.2% in 2030. because electricity supply is now fully adjusted downward, the total electricity generation cost goes down by 0.3% in 2015 and by 0.0% in 2030 and emissions decrease by 11.1% in 2015 and by 9.9% in 2030. the above analysis shows that scenario 3 (switch to clean coal) is a better policy option than the scenario 2 (switch to renewable). furthermore, policy condition 3 yields the largest co2 reduction for the given energy generation mix. allowing the free market to adjust price and supply will lead to the largest decreases in co2 emissions for a given energy generation mix for the near future (while fossil fuel based electricity generation is cheaper than renewable sources and clean coal with ccs). 4. conclusions 1. an economic model for electricity generation in the u.s has been created that runs policy simulations for 2010-2030. 2. the model predicts that utilizing clean coal technologies such as ccs will affect the economy less than utilizing the renewable energy sources. this is due to clean coal technologies being cheaper than renewable energy technologies based on the current estimates. 3. while fossil fuel based electricity generation is cheaper than renewables based electricity generation, government regulation will be necessary to achieve any sort of co2 emissions reduction. clean coal technologies could be used to bridge the gap until renewables based electricity becomes less expensive than fossil fuel based electricity. future work 1. the model should be applied to the major emerging economies of india and china. the agriculture sector is important in these countries. the agriculture sector can be modeled in a manner similar to the commercial sector in the present model. economics of carbon dioxide sequestration and mitigation versus a suite of alternative renewable energy sources for electricity generation in u.s. 93 2. the non-fixed labor requirements should be added to the model. it is likely that the older and more developed power generation methods will become increasingly more automated and therefore less labor intensive compared to the power plants employing newer less-traditional renewable power generation sources; thus, the value of θ is likely to be larger for the newer technologies than the older established technologies. 3. the provision for carbon tax should be included in the model. carbon tax is a way to encourage the electricity generation companies to reduce the carbon emissions by either switching to alternative renewable energy generation sources or by developing the co2 capture and sequestration (ccs) technologies. 4. the current model does not take into account the cost associated with switching from one energy source to another. a cost function should be included which can model this cost. 5. the current model is a steady state model. it should be extended to conduct the dynamic analysis using the tools of dynamic programming. this will allow for the ongoing growth of households and firms over time; it will also capture shifts in supply and demand factors over time. data collection sources 1. employment for each state by sector for 2001-2006. sectors: agriculture, forestry, fishing and hunting, mining; utilities, construction, manufacturing, transportation and warehousing (excluding postal service), government and other as well as the total employment; source: bureau of labor statistics. 2. us electricity retail sales by sector in thousand megawatt hours for each state for 1990-2006. sectors: residential, commercial, industrial and other, as well as total sales. source: energy information administration (eia), 2008. 3. us energy generation data for 1980-2009 by source. electricity generation sources: coal, petroleum, natural gas, other gases, total fossil fuels, nuclear, hydro (conventional), biomass wood, biomass waste, geothermal, solar/pv, wind, total renewables, other; as well as total for all sources. source: eia, annual energy review, 2008. 4. total coal usage in power generation for 1990-2006 in thousands of tons of coal. source: eia, 2008. 5. us co2 emissions from the electric power industry for each state by source for 2003-2006. sources: coal, petroleum, natural gas, geothermal and other renewables as well as the total. source eia, 2008. 6. us average electricity retail price in cents per kilowatt hour for 1998-2006. source: eia, 2007. 7. us electricity generation costs in cents per kilowatt hour. 8. a full data set is available for 2006. additional years of data are available for some of the sources so that a curve fit could be made to fill in the gaps in the data for other years. sources: coal, natural gas, nuclear, petroleum, wind, residential photovoltaics, commercial photovoltaics, industrial photovoltaics, solar thermal, geothermal, hydroelectric small and hydroelectric large. sources: nuclear energy institute, u. s. electricity production costs and components (1995-2008); energy information administration, annual energy review 2008; table 8.2a electricity net generation: total (all sectors), selected years, 1949-2008; world energy assessment; overview: 2004 update. solarbuzz.com, solar electricity price index verses us electricity tariff price index; facts about hydropower, wisconsin valley improvement company. 9. us electricity generation for each state by source in megawatt hours for 1990-2006. sources: coal, petroleum, natural gas, other gases, nuclear, hydroelectric, other renewables, pumped storage and other as well as the total. source eia, 2008. 10. us co2 emissions from energy consumption for each sector from 1980 to 2005. sectors: residential, commercial, transportation, electric power. source: eia, 2008. 11. us electricity demand from 1980 to 2006 for each sector. 12. sectors: residential, commercial, industrial, transportation as well as total. source: eia, 2008. 13. state level co2 emissions from fossil fuel combustion for electricity generation from 1990 to 2004 in million metric tons of co2. source: eia, 2008. international journal of energy economics and policy, vol. 1, no. 4, 2011, pp.78-94 94 14. cost of living statistics (consumer price index) for the northeast urban, midwest urban, south urban, and west urban, as well as us total for 1985-2006. source: bureau of economic analysis, 2008. 15. state level population data for 1970-2007. source: us census bureau, 2008. 16. state level average number of people per household for 2007. source: bureau of labor statistics, 2008. 17. us gross state product (gsp) for each state for each industry in non-chained dollars for 1997-2006. industries: agriculture, forestry, fishing and hunting, mining, utilities, construction, manufacturing, transportation and warehousing (excluding postal service), government and other; as well as the total. source: bureau of economic analysis, 2008. 18. state level motor-vehicle registration for 2003-2005. sectors: automobiles, motorcycles, busses and trucks. source: bureau of transportation statistics, 2008. references brundtland, g.h. (1987), our common future. oxford university press. cra international (2008), cra international report: cra international's mrn-neem integrated model for analysis of us greenhouse gas policies. retrieved from the cra website: http://www.crai.com/uploadedfiles/relating_materials/publications/bc/energy_and_e nvironment/files/mrnneem%20integrated%20model%20for%20analysis%20of%20us%20green house%20gas%20policies.pdf nakata, t. (2004), energy-economic models and the environment. progress in energy and combustion science, vol. 30, pp. 417 − 475. bellman, r.e. (1957), dynamic programming. princeton nj: princeton university press. bergin, p. (1998), lecture notes on dynamic programming: economics 200e. retrieved from university of california, davis website: http://www.econ.ucdavis.edu/faculty/bergin/econ200e/lec200e.pdf. accessed september 15, 2011 boileau, m. (2002), a child's guide to dynamic programming. retrieved from the university of colorado at boulder website: http://www.colorado.edu/economics/courses/boileau/7020/ cgdynpro.pdf. accessed september 15, 2011 . international journal of energy economics and policy | vol 7 • issue 5 • 2017 209 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(5), 209-216. global refining industry in retrospect, and evaluation of russia-european union petroleum products’ trade perspectives igbal a. guliyev1, elnur t. mekhdiev2*, igor i. litvinyuk3, alexandr v. bondarenko4, aibulat r. yanguzin5 1international institute of energy policy and diplomacy, moscow state institute of international relations (university) of the ministry of foreign affairs of the russian federation, moscow, russia, 2center for post-soviet studies of the institute of international studies, moscow state institute of international relations (university) of the ministry of foreign affairs of the russian federation, moscow, russia, 3centre for strategic research and geopolitics in energy, international institute of energy policy and diplomacy, moscow state institute of international relations (university) of the ministry of foreign affairs of the russian federation, moscow, russia, 4ufa state petroleum technological university, russia, 4professor of philosophy and political science sub-faculty of the bashkir state university. russia. *email: e.mehdiev@gmail.com abstract oil-refining industry plays a significant role in the development of the world fuel and energy complex. in the meantime, at the current stage of this industry’s development quality changes are taking place in it. taking into account the traditional siting of refinery capacity close to consumption centers, many countries consider the possibility of building their own oil refineries to satisfy the growing domestic demand for oil products. other countries consider the possibility of developing refineries not only for the national market, but also for export of petroleum products. such a tendency can be observed in russia. the article deals with current state and relevant issues of development of oil refining industry on the global scale, with the latter being largely driven by consumer demand changes. particular attention is given to baltic sea region countries that are considered as potential markets for diesel fuel exports in the context of the capacity increase of oil refining in russia. keywords: russia, oil, petroleum products, diesel, refining, international trade, european union, energy market jel classifications: f16, f63, o52, r12, l16, l71 1. introduction an important prerequisite for this study is the fact that currently the production of diesel fuel in russia exceeds domestic consumption, providing an opportunity to export nearly half of the produced goods. in this context, the projects “north” and “south” of jsc “transneft”, which provide for the development of pipeline transport capacity in the direction of the seaports of the baltic sea and the black sea to 15 and 6 million tons per year respectively, acquire particular relevance for further export deliveries of oil products by sea. as part of this article a more detailed analysis of the markets in the region of the baltic sea basin will be given, including such countries as germany, denmark, latvia, lithuania, norway, poland, finland, sweden and estonia. the analysis will be carried out in the context of global changes taking place in the present time in the field of oil refining. 2. literature review the review of bibliography reveals that in a 10 year perspective we should expect intensive development of oil refining industry on a global scale, as well as a change in the role of the countries and the balance of power on the global oil market. at least by 2025 growth in demand for oil products will combine to be 1.2%, with the share of diesel fuel in the structure of consumption reaching no less than 37% (lukoil, 2013). the key factor ensuring this change will remain the developing countries of the asia-pacific region (apr), especially china and india, and the main consumer in the global dimension the transport sector. it should be emphasized that the development of the global refining industry occurs largely due to the changes in the demand for fuel used in the transport sector. in recent decades, a change in the oil consumption patterns can be observed, which is expressed primarily in growing proportion of diesel fuel. guliyev, et al.: global refining industry in retrospect, and evaluation of russia-european union petroleum products’ trade perspectives international journal of energy economics and policy | vol 7 • issue 5 • 2017210 3. methodology for assessment the economic crisis of 2008 led to a distortion of the previous development trends of the global refining industry. there has been a decline in oil prices and, consequently, in the price for the processed products. refineries’ profit declined sharply to the level of 2001, and at some plants with a depth of recycling less than 85% has reached the threshold of profitability. at the same time, in some regions, especially in the apr, new capacities were commissioned. as a result, in the global refining industry in the apr excess capacity was formed, and the existing plants in eastern europe and eurasia dropped their load. with regard to the development of the petroleum sector in asia one cannot but note the refinery put into operation in 2008 by reliance industries in jamnagar (gujarat, india) with a capacity of 33 million tons per year, which is one of the largest in the world. in 2013, the volume of diesel fuel supplies from india to europe amounted to 16 million tons, which is 76% more than in 2011 (argus, 2014). thus, an increase in diesel fuel supply from refineries in jamnagar to the european market is expected, given a better strategic position in relation to european and american markets as compared to the main competitors in the asian market, particularly japan and china. however, the rapid growth in demand for diesel and other fuels from developing countries shows that this supply will be carried out only in the short term (sheppard, 2008). despite the fact that for private companies (as opposed to government) it is not profitable to sell oil products inside the country with a view to india’s policy of setting domestic prices for petroleum products below the cost of production, it is expected that over time export refineries will be reoriented to domestic markets (guliyev and litvinyuk, 2017). thus, the gradual folding of stable trade relations could threaten adequate supply of oil to regions that lack their own processing capacity and which are forced to carry out imports of refined products. in such a situation, for instance, find themselves the european countries characterized by a range of structural problems in the industry, together threatening the sustainability of their economies. for example, in europe in the recent years a steady increase in oil consumption can be observed, particularly of diesel fuels. according to some forecasts, it is expected that in 2015 the deficit of diesel fuel in the region will exceed 55 million tons (salyginet al. 2016). mass closings of refineries in europe (since 2008, 16 factories have announced that they are closing refining capacity or are planning to do so) taking place against this background and caused by the fiscal policy of the european union (eu) clearly open european markets to foreign supplies of oil. 4. analysis globally, the structure of production of petroleum products varies only slightly and depends mainly on the development of technologies that provide a certain depth of oil refining1. in this 1 refining depth one of the characteristics of the refineries, showing oil yield based on the oil, in % by weight, less fuel oil and gas. regard, it seems quite reasonable to introduce a worldwide output structure of the refineries as it is graphically depicted in figure 1. from the presented information it is obvious that the proportion of residual oil in the output structure decreases during the period under review, which takes place against the background of a gradual increase in the share of diesel fuel. despite the regional trends of changes in petroleum products consumption patterns on a global scale increase in the share of gasoline issue can be noticed. moreover, in the global structure of petroleum products issuing a trend of growth in demand for jet fuel and kerosene can be seen due to the development and intensification of air traffic. we would like to emphasize that the current stage as a whole is characterized by a decrease in the proportion of heavy oil products in the structure of consumption, which is caused by the gradual transition of power and heat generating plants to coal, natural gas and nuclear fuel as a primary energy source. as noted, the regional trend is a gradual decline in the proportion of gasoline and a growing importance of diesel fuel to in satisfying the demand for petroleum products by the end users unfolding against this backdrop. it should be noted that this technological transition will require changes in the configuration of the existing refineries. following the dynamics of demand, refining capacity is also expanding, as shown in figure 2. it is interesting to note that the capacity utilization, calculated as the ratio of release of petroleum products to the installed capacity, comprised on average 91% in the world, ranging from 62% in africa and 100% in north america, which preserves the maximum load during the whole period under review. the dynamics of utilization of production capacity quotient by regions is shown in table 1. change in the volume of petroleum products output index, calculated on the basis of the data in figure 2 and table 3, is presented graphically in figure 3. as seen from the graph, the leading petroleum producers are the regions of asia-pacific and north america. within these regions china and the united states occupy the leading position, producing, as of 2013, 4302.4 and 6.5026 billion barrels of oil products per year respectively, representing more than 34% of total world output. the largest producers are also russia (2100.2 million. barrels per year), japan (1584.0 million barrels per year) and india (1576.4 million barrels per year). the dynamics of growth in capacity of oil refineries, illustrated in figure 4, confirms the general trend towards increasing the volume of oil production. very obvious, based on the graph, is a steady increase in refining capacity, but in a regional context its structure is not too homogeneous. with the world average increase in capacity by 15% during the period 2000-2013, the regions of asia-pacific (43%) and middle east (27%) show a significant increase. other regions analyzed in this research, having increased the refinery capacity in the period up to 2005, in 2005-2013 mostly reduced guliyev, et al.: global refining industry in retrospect, and evaluation of russia-european union petroleum products’ trade perspectives international journal of energy economics and policy | vol 7 • issue 5 • 2017 211 their pace or, as in the case of the regions of western and eastern europe, showing a decrease in the reporting period by 6 and 3% respectively. to assess the share of diesel fuel in the total volume of oil products of the baltic region, to determine its role for the largest consumer the transport sector and to identify the largest figure 1: global structure of output of oil refineries in the period 2006-2014, % source: manolov 2015; authors' calculations figure 2: development of refining capacity in the regions of the world in 2000-2013 (installed capacity), million barrels per year statistical bulletin – oil and gas data (opec, 2014) figure 3: dynamics of petroleum products release by the regional refineries in 2000-2013, million barrels per year source: authors' calculations based on annual statistical bulletin – oil and gas data (opec, 2014) guliyev, et al.: global refining industry in retrospect, and evaluation of russia-european union petroleum products’ trade perspectives international journal of energy economics and policy | vol 7 • issue 5 • 2017212 consumers of diesel fuel as part of the region is possible on the basis of tables 2 and 3.23 the growth in diesel fuel consumption in europe increases due to the increased number of vehicles. currently, the share of diesel fuel in the region of the baltic sea countries is 45.38% compared to 44.94% in europe on the whole, with the lowest in norway (31.54%) and sweden (35.36%), and the largest in latvia (60.29%) and estonia (59.57%). this characteristic is very representative in terms of cross-country analysis, but it cannot be applied without regard to the countries in terms of the capacity of their diesel markets. thus, the largest market in absolute terms of the volume of diesel consumption in total ultimate consumption among the considered countries is objectively the german market, where more than 50.1 million tons of diesel fuel or, respectively, 19.59% of the total european consumption is currently implemented. currently, the domestic consumption of diesel fuel by a group of european countries of the baltic region is more than 179 million tons of fuel per year, providing 31.44% of the total demand for it on the part of the european union. more 2 calculated as the sum of primary production, reduced products, total imports, fuel variations, net of total exports, and the volume of bunker fuel. this corresponds to the addition of the ultimate consumption, losses during distribution, losses during the transformation and statistical differences. 3 includes all supplies to final consumers (industry, transport, households and other sectors of the economy) for various energy purposes. excludes deliveries for processing and / or own use of the energy sector enterprises, as well as network losses. information about diesel fuel markets within the baltic countries is presented in table 3. in 2012, for the first time since 2009, a decline in diesel consumption was recorded, which was caused by the effects of the initiative on the transfer of heating systems to natural gas. however, as a massive shift to diesel fuel is typical for the transport sector of the european union, the total volume of its consumption in recent years is restoring. while in 2000 there was a relative balance between diesel fuel and motor gasoline, currently the latter has a stable long-term downward trend. basically, thanks to tax preferences for diesel fuel, its share in the market of motor fuel in some eu countries is currently around 70%. at the same time, because of the high longterm growth in the share of diesel consumption in the transport sector, today markets of countries like france or spain, where the share of diesel vehicles is around 80%, the saturation stage is approaching, which implies slowdown in consumption growth. in addition, among the factors influencing the decline in growth, it is necessary to take into account the economic situation in the countries under consideration, namely the fact that in some of them there is a very high unemployment rate, which is especially noticeable in germany (6%) and poland (11%), as well as some other eu countries italy (12%), greece (27%) and some other. this factor, which leads to a decrease in real disposable income of the population unfolding against the background of continued growth in diesel fuel prices for consumers, is negatively table 1: the dynamics of utilization of production capacity quotient by regions in the period 2000-2013 region year 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 north america 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 south and latin americas 0.94 0.97 0.95 0.92 0.94 0.97 0.95 0.96 0.89 0.92 0.87 0.88 0.86 0.88 eastern europe and eurasia 0.68 0.76 0.80 0.82 0.85 0.91 0.92 0.92 0.96 0.94 0.93 0.92 0.89 0.89 western europe 0.99 0.99 0.98 1.00 1.00 1.00 0.97 0.94 0.92 0.87 0.85 0.85 0.85 0.87 middle east 0.90 0.90 0.89 0.88 0.92 0.93 0.91 0.87 0.95 0.92 0.91 0.87 0.90 0.84 africa 0.75 0.77 0.81 0.82 0.83 0.90 0.80 0.78 0.75 0.67 0.78 0.72 0.65 0.62 asia-pacific 0.89 0.87 0.86 0.87 0.94 0.94 0.92 0.92 0.91 0.88 0.91 0.89 0.88 0.89 world 0.91 0.92 0.92 0.93 0.96 0.97 0.95 0.94 0.94 0.91 0.92 0.91 0.91 0.91 source: authors’ calculations based on annual statistical bulletin – oil and gas data (opec 2014) table 2: diesel fuel consumption in the countries under review in 2012, million tons country (region) total domestic consumption2 ultimate consumption3 including transport sector the share of diesel fuel in total consumption,% the country’s share in total consumption in the eu, %abs. % denmark 7081.3 3613.9 2523.0 69.81 51.03 1.41 germany 108297.3 50111.2 28332.0 56.54 46.27 19.59 latvia 1382.0 833.2 713.0 85.57 60.29 0.33 lithuania 2466.7 1110.0 943.0 84.95 45.00 0.43 norway 12174.2 3839.8 2886.0 75.16 31.54 1.50 estonia 1109.2 660.7 462.0 69.93 59.57 0.26 finland 8952.0 4048.2 2386.0 58.94 45.22 1.58 poland 24832.8 12513.1 9854.0 78.75 50.39 4.89 sweden 12693.8 4489.0 4138.0 92.18 35.36 1.75 total 178989.3 81219.1 52237.0 64.32 45.38 eu 569220.4 255813.0 the share of countries of the region 31.44% 31.75% source: authors’ calculations based on energy balances statistics (international energy agency 2017) guliyev, et al.: global refining industry in retrospect, and evaluation of russia-european union petroleum products’ trade perspectives international journal of energy economics and policy | vol 7 • issue 5 • 2017 213 affecting both the sales volumes of transport means and the fuel consumption volume, leading to a reduction in the market of gasoline and diesel fuel. however, according to forecasts of the international council on clean transportation (icct), as well as on the basis of forecasts of world energy produced by leading international agencies the world energy council and the international energy agency, in the next 15 years the number of both passenger and commercial vehicles is expected to increase in all regions of the world, except japan (icct, 2013). herewith, it should be noted that among the regions mainly represented by developed countries (european union, north america), the largest percentage of this growth is in north europe. at the same time, according to the forecasts of the european commission (2013), diesel fuel consumption in europe will increase up to 2015 and will stabilize during the period between 2015 and 2050 becoming the main fuel for passenger transport and continuing to be the main fuel for the truck. thus, one should expect a significant increase in the volume of diesel consumption in the global market as a whole, in the european market one of the regions with the highest growth will become northern europe, presented by countries of the baltic region. however, the current state of the market is not without deep structural problems. despite the overall decline in domestic consumption, european producers of petroleum products are not able to cope with the increasing demand for diesel fuel both due to lack of capacity, and due to low profitability caused by table 3: structure of the market of diesel fuel in the baltic region in 2012, million tons indicator germany sweden norway lithuania denmark poland estonia latvia finland production 43.58 7.966 6.161 3.025 3.411 11.289 0 0 6.401 import 13.549 2.080 1.471 0.461 1.968 1.422 0.713 1.177 2.360 export 6.235 5.099 2.524 2.986 1.48 0.337 0.013 0.211 3.123 sent to the international marine fuel storage 0.433 0.237 0.148 0.02 0.244 0.066 0.086 0.087 0.042 international aviation fuel storage 0 0 0 0 0 0 0 0 changes in inventory levels +0.58 +0.066 −0.088 +0.042 +0.036 −0.04 −0.004 −0.051 0.11 intermediate consumption, generation 0.565 0.073 0.019 0.001 0.061 0.072 0.001 0.003 0.036 electric power plants 0.127 0.004 0.004 0 0.017 0 0 0 0.01 chpp 0.091 0.029 0 0 0.009 0.012 0 0 0.006 heating installations 0.128 0.04 0.014 0.001 0.035 0.009 0.001 0.003 0.02 oil refineries 0 0 0 0 0 0 0 0 0 other 0.219 0 0.001 0 0 0.051 0 0 0 ultimate consumption 49.481 4.363 4.110 1.079 3.274 11.997 0.654 0.821 3.960 industrial sector 1.145 0.241 0.38 0.022 0.201 0.365 0.051 0.047 0.459 transport sector 29.116 3.654 2.827 0.977 2.269 9.394 0.481 0.612 2.295 housing sector 11.903 0.039 0.062 0.012 0.29 0.087 0.005 0.025 0.453 commercial and public services sector 6.696 0.295 0.177 0.003 0.056 0.426 0.039 0.039 0.194 agriculture and forestry 0 0.111 0.132 0.043 0.349 1.725 0.078 0.09 0.355 fishing 0 0.023 0.485 0.002 0.109 0 0 0.007 0.036 other 0.048 0 0.047 0 0 0 0 0.001 0.168 non-energy consumption 0.573 0 0 0 0 0 0 0 0 of which chemical 0.567 0 0 0 0 0 0 0 0 source: authors’ calculations based on energy balances statistics (international energy agency, 2017) figure 4: dynamics of annual growth of oil refineries capacity in the world in 2000-2013, %. (2000 = base) source: authors' calculations based on annual statistical bulletin – oil and gas data (opec, 2014) guliyev, et al.: global refining industry in retrospect, and evaluation of russia-european union petroleum products’ trade perspectives international journal of energy economics and policy | vol 7 • issue 5 • 2017214 the previously mentioned tax policy of the eu. as of 2012, the situation in the region’s oil refining industry is set out in table 4.4 due to the orientation of the majority of the considered refineries to produce gasoline, there is overproduction of that, which, due to insufficient domestic demand, results in the need for their deliveries to the external market mainly in the us. however, this effect leads to the need to close some refineries, the yield of which could not be achieved in the current economic situation. in the context of the impossibility of conversion of refineries to produce diesel fuel and taking into account the long-term stability in the diesel demand with gradually rising prices, it is extremely important for the countries to ensure reliable supplies of imported diesel fuel. thus, in the markets under review there is a significant dependence on imported diesel fuel supply, which is presented in table 5. dynamics of imports (united nations, 2017) for the period of 2009-2014 are shown in table 6. 5. discussion this situation, of course, can vary greatly under the influence of a number of parameters, such as changes in demand, changes in the volume of car sales, reducing of total refinery capacity, and, importantly, a possible substitution of conventional diesel with biodiesel, which in theory, at full replacement, will reduce the demand for traditional diesel fuel by 20%. despite the general trend towards growth in the share of diesel fuel in the next 10 years, dictated by the eu energy policy aimed at reducing the negative impact on the atmosphere, some countries are characterized by a very low profile on this issue. in particular, germany’s energy concept encourages the substitution of a significant proportion of conventional diesel fuel by biodiesel over a 10-year period. based on the tabulated data on the diesel fuel consumption in transport sector, one can conclude about diesel market capacity of the baltic region countries, from a potential provider’s perspective. there are objective prerequisites for changes in the oil markets where diesel fuel could potentially be exported through the 4 calculated as the sum of the potential volume of the country’s oil refineries processed per day by the number of calendar days in the year (365), translated in million tons. russian ports of the baltic sea. one of the main reasons for the change is, first, the constant increase in fuel prices in europe, and, secondly, the observed imbalance of production and consumption of petroleum products in the region. the long-term crisis in the oil-refining industry of the countries in question, caused by the lack of supply and demand for gasoline and diesel fuel, has a structural character. perspective diesel fuel market development in the countries reviewed by 2025 will determine, first, the degree of substitution of conventional diesel with biodiesel (which will probably only reduce the traditional supply deficit) and, secondly, the refinery capacity to carry out the reorientation toward production of a modern diesel class.5 5 calculated as the quotient of the volume of imports of diesel fuel and the amount of the final consumption of diesel fuel in the country, intermediate consumption and generation. table 4: undercapacity of refineries in the baltic region in 2012, % country total refining volume in 2012, mln tons (unione petrolifera 2014; bp 2014) potential maximum processing volume, mln tons4 undercapacity of refineries, % the number of operating refineries average undercapacity of refineries, mln tons germany 104.4 131.42 20.56 14 1.93 denmark 8.7 9.09 4.29 2 0.19 latvia lithuania 9.5 13.44 29.31 1 3.94 norway 16.14 15.84 + min 2 min poland 24.7 26.12 5.44 7 0.2 finland 13.0 13.49 3.63 2 0.25 sweden 20.7 26.21 21.02 4 1.38 estonia source: authors’ calculations based on scenario internazionale (unione petrolifera 2014); statistical review of world energy 2014 (bp 2014). table 5: ranking of countries of the baltic region in terms of energy dependence on diesel fuel supply, 2012 country supply dependence index5 latvia 1.43 estonia 1.09 finland 0.59 denmark 0.59 sweden 0.47 lithuania 0.43 norway 0.36 germany 0.27 poland 0.12 source: authors’ calculations based on tables 2-4 table 6: dynamics of imports of diesel fuel by the baltic countries, 2009-2012, million tons country years 2009 2010 2011 2012 germany 14.509 15.595 13.580 13.549 denmark 2.222 2.219 2.276 1.968 latvia 1.036 1.056 1.063 1.177 lithuania 0.133 0.203 0.381 0.461 norway 1.705 1.135 1.206 1.471 poland 2.196 2.116 1.946 1.422 finland 2.283 1.829 2.443 2.360 sweden 1.992 2.138 2.198 2.080 estonia 0.576 0.545 0.597 0.713 source: authors’ calculations based on un comtrade data (united nations, 2017) guliyev, et al.: global refining industry in retrospect, and evaluation of russia-european union petroleum products’ trade perspectives international journal of energy economics and policy | vol 7 • issue 5 • 2017 215 the key factors that will determine the development of the world oil-refining in the future are: increasing demand for the products of developing countries, high growth rate of introduction of new refining capacity in the countries with minimal costs, the deepening integration of oil-refining companies through mergers and acquisitions, the concentration of small and medium-sized refineries on the production of innovative products. in the countries where the demand for products of oil refining industry is reducing, petroleum products not consumed by domestic surplus can be exported, but one should take into account the increasing competition in the market and the lack of access to this strategy for some countries. in the period up to 2035 closure of some refineries (mainly in europe) with insufficient depth of crude oil processing is expected. in the opec’s review of the world oil market for the period until 2030 (opec, 2015) it is reported that the “golden age” of oil refining, which occurred during the period of 2004-2008 when the demand for oil was growing steadily, which provided for a high level of capacity utilization, ended. as a result, such problems as availability of free capacity, chronic underutilization and the subsequent decline in enterprises’ yields were revealed. in this regard, contrasting trends are expected to grow. thus, in developed countries existing plants will be closing and new projects will be canceled, while in the developing economies of the asian region new modern refineries will be built. the rejection of a number of projects will especially affect the us and the eu, which is an additional factor in the growth strategy of the efficiency of the transport sector on the basis of biofuels use and alternative types of car engines. petroleum industry of developing countries will be developed under the influence of the state economic policy. for example, the energy policies of india and china, providing for duty-free import of raw materials and tax preferences for companies, are truly remarkable. 6. conclusion given the expected increase in russian refining capacity of 3540 million tons of diesel fuel per year, as well as the increase in the production of diesel fuel of euro-5 standard and the mass closings of refineries in europe, it is possible to judge the potential of increasing the volume of export of diesel fuel to the european market. in this regard, it seems about time to carry out market research of european oil products in order to develop recommendations for optimization and improvement of the export policy of the enterprises of oil refining sector of the russian fuel and energy complex. there is already an obvious trend of diversification in the structure of oil and gas exports. this diversification is associated with the fact that russia is gradually shifting from the export of crude oil to the export of high value-added petroleum products. thus, continuing the existing trend, the share of oil products relatively crude oil rose in the total exports of liquid fuels from 30.6% to 38.6%, primarily due to a record volume of domestic crude oil distillation, constituting 219.5 million tons in 2014, which is 5.6% higher than a year earlier. in the structure of exports supply of russian diesel fuel abroad reached the highest growth. current economic and political situation in the energy markets makes it necessary to review the existing model of exporting energy raw materials that has for many years been the general practice and to move towards exporting high value-added goods. high value-added goods provide significant additional public revenue through increased export earnings and the use of export duties, which, in turn, is intended to generate another round of spending and to stimulate further development of the real sector of the russian economy. accelerated development of russian oil-refining will, in turn, be conditioned mainly by the demand for the products in european countries that remain the key export market for russian petroleum products. taking into account a long-term program of development of the oil-refining industry in russia and the introduction of a new processing facility with total capacity of up to 40 million tons per year that is scheduled for this year, stable exports of petroleum product to the west appears to be achievable. however, this demands an appropriate energy infrastructure pipeline transport systems for petroleum products that able to cost-effectively transport products to the largest russian sea ports for export supplies by sea. due to the fact that construction of the pipeline infrastructure is a really major long-term investment project, it needs a stable cash flow generated by the constant demand for the products from ultimate consumers in europe, which calls for further studies. references argus. (2014), outlook: import options grow for diesel in europe; 2017. available from: http://www.argusmedia.com/pages/newsbody. aspx?id=920338&menu=yes. bp. (2014), statistical review of world energy; 2017. available from: http://www.bp.com/en/global/corporate/media/speeches/bpstatistical-review-of-world-energy-2014.html. european commission. (2013), eu energy, transport, and ghg emissions trends to 2050; 2017. available from: http://www. ec.europa.eu/transport/media/publications/doc/trends-to-2050update-2013.pdf. guliyev, i., litvinyuk, i. (2017), issues for long-range projection of international energy markets through the prism of sustainable development. international journal of energy economics and policy, 7(2), 296-303. september, 2017. availble from: http://www. econjournals.com/index.php/ijeep/article/view/4572/2839. icct. (2013), european vehicle market statistics pocketbook; 2017. available from: http://www.theicct.org/sites/default/files/ publications/eu_vehiclemarket_pocketbook_2013_web.pdf. international energy agency. (2017), energy balances statistics; 2017. available from: http://www.iea.org/statistics/topics/energybalances. lukoil. (2013), global trends in oil and gas markets to 2025; 2017. available from: http://www.lukoil.be/pdf/trends_global_oil_eng. pdf. manolov, d.d. (2015), economic efficiency of modern technologies for production of diesel fuel of euro-5 class and their implementation in the republic of bulgaria [ekonomicheskaya effektivnost’ sovremennykh tekhnologiy proizvodstva dizel’nogo topliva klassa yevro-5 i ikh realizatsiya v respublike bolgariya]. moscow: russian state university of oil and gas. opec. (2015), oil downstream outlook to 2040; 2017. available from: http://www.woo.opec.org/index.php/oil-downstream-outlookguliyev, et al.: global refining industry in retrospect, and evaluation of russia-european union petroleum products’ trade perspectives international journal of energy economics and policy | vol 7 • issue 5 • 2017216 to-2040. opec. (2014), annual statistical bulletin oil and gas data; 2017. available from: http://www.opec.org/library/annual%20 statistical%20bulletin/interactive/current/filez/main-dateien/ section3.html. salygin, v.i., guliyev, i.a., litvinyuk, i.i. (2016), perspektivy eksporta nefteproduktov iz rossii na rynki yevropeyskikh stran [prospects for petroleum products exports from russia to european energy markets]. science and technologies: oil and oil products pipeline transportation, 5(25), 110-118. sheppard, d. (2008), europe’s diesel imports to soar, fuelling pump prices; 2017. available from: http://www.reuters.com/ article/2008/09/30/us-energy-diesel-idustre48t2zv20080930. unione petrolifera. (2014), scenario internazionale; 2017. available from: http://www.unionepetrolifera.it/wp-content/uploads/2015/03/ preconsuntivo-2014.pdf. united nations. (2017), un comtrade database; 2017. available from: http://www.comtrade.un.org/data. . international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(3), 92-96. international journal of energy economics and policy | vol 8 • issue 3 • 201892 total-factor energy efficiency in eu: do environmental impacts matter? nela vlahinić lenz1, alemka šegota2, dario maradin3* 1university of rijeka, faculty of economics and business, ivana filipovića 4, 51000 rijeka, croatia, 2university of rijeka, faculty of economics and business, ivana filipovića 4, 51000 rijeka, croatia, 3university of rijeka, faculty of economics and business, ivana filipovića 4, 51000 rijeka, croatia. *email: dario.maradin@efri.hr abstract the concept of total-factor energy efficiency (tfee) measures energy efficiency in a more superior and complex way within the total-factor framework, but takes only gross domestic product (gdp) as the only output. a new approach that includes desirable (gdp) and undesirable outputs (greenhouse gas [ghg] emissions) has been developed recently and is applied in our research. the aim of our paper is to assess economy-wide energy efficiency in eu countries in a total-factor framework and compare these results with the environmental tfee (etfee) that takes into account undesirable outputs like co2 and sox emissions. our analysis is based on 2008-2014 panel data for 28 eu countries. the efficiency frontier is constructed by using dea and modified slack-based model model based on data on three production factors (labor, capital and energy), gdp as desirable output and co2 and sox emissions as undesirable outputs. our research results show that energy efficiency that does not incorporate environmental pollution is overestimated in 20 out of 28 eu countries. when analyzing environmental tfee during time, results show that in 2014 there are more countries that have reached efficient frontier than in 2008, which could imply that eu countries pay a lot of attention to reduction of ghg emissions and sustainable development. keywords: total-factor energy efficiency, eu countries, dea, undesirable outputs, environmental pollution jel classifications: q43, q56, c32, c61 1. introduction energy efficiency plays an important role in economic development and therefore attracts growing academic research efforts. these research evaluations are based on two different methods: one is partial-factor energy efficiency and the other one is total-factor energy efficiency (tfee). assessing partial energy efficiency is usually done by two indicators: energy intensity and energy efficiency. while these traditional energy efficiency indexes take only energy into account as a single input to produce output gross domestic product (gdp) while other inputs like labor and capital are ignored, a new approach known as tfee has been developed by hu and wang (2006) in order to overcome the disadvantages of the traditional partial-factor energy efficiency. some researchers (honma and hu, 2009) concluded that the partial-factor energy efficiency estimation is misleading and cannot give the appropriate benchmark. therefore this tfee index provides a useful alternative to the traditional energy efficiency indicators mentioned above. it combines three production factors as inputs and measures singlefactor efficiency in a total-factor environment. boyd and pang (2000) concluded that energy-efficiency improvement relies on total-factor productivity improvement. this total-factor efficiency model is more realistic because it includes substitution effects between energy and other production factors. this substitution really happens: capital goods are activated by energy and at the same time, energy has no economic use without capital goods. substitution among factors occurs during time, in the medium and long-time period, while the substitutability of the inputs is limited in a short term. however, tfee measures energy efficiency in a total-factor framework, but takes only gdp as the only output. a new approach that takes into account undesirable outputs as well, has been developed recently due to the growing concern of the importance of environmental protection. gdp has been produced from the use of energy and other production factors, with environmental vlahinić lenz, et al.: total-factor energy efficiency in eu: do environmental impacts matter? international journal of energy economics and policy | vol 8 • issue 3 • 2018 93 pollution as additional undesirable output. therefore sustainable framework should be proposed to measure energy efficiency. the aim of our paper is to assess economy-wide energy efficiency in eu countries in a more superior total-factor framework and compare these results with the ecological tfee that takes into account undesirable outputs like co2 and sox emissions. the analysis is based on 2008-2014 panel data. the efficiency frontier is constructed by using data envelopment analysis (dea) based on data on three production factors (labor, capital and energy) and gdp as desirable and co2 and so2 emissions as undesirable outputs. it should be noted that most studies assessing the energy efficiency at the macroeconomic level using a total factor structure adopt the dea method, as it provides an appropriate mechanism for dealing with multiple inputs and multiple outputs to measure the efficiency ratio of each decision making unit (dmu) under evaluation (camioto et al., 2016). so, the analysis tool used in this study is the dea, through the slack-based model (sbm) bad output model, incorporating multiple inputs and two kinds of multiple outputs: desirable and undesirable as the result of input utilization. undesirable outputs are often occur in the environmental context, and represent an anomaly, which should not be ignored when measuring tfee. in contrast to the “desirable” outputs which should have as high as possible value, “undesirable” outputs, or environmentally unfavorable outputs, achieve as low as possible value. also, in case of emissions or pollution, regulatory standards define the maximum amount of undesirable outputs as a result of the production process. the remainder of the paper is organized as follows: the second section explains the concept of tfee as a new approach in measuring economy-wide energy efficiency performance and gives the literature review relevant for our research. the third section describes the data and the model, the fourth section presents the empirical results and discussion, while the last section gives the concluding remarks. 2. literature review during the last decade there has been a growing number of papers dealing with the issue of energy efficiency because increasing energy efficiency has become an important goal of energy strategy in many countries and regions. however, the concept of tfee has been proposed for the first time in 2006 by hu and wang and since then a number of papers have been published. following the hu and wang’s approach, during the last 10 years some interesting papers have been published. honma and hu (2008) investigated the tfee of 47 regions in japan for the period 1993-2003. in another paper the same authors (honma and hu, 2011) computed and analyzed the tfee of 11 industries in 14 developed countries during the period of 1995-2005. zhang et al. (2011) used a total-factor framework to investigate energy efficiency in 23 developing countries during the period of 1980–2005. they explored the tfee and change trends by applying dea window, which is capable of measuring efficiency in crosssectional and time-varying data. ceylan and gunay (2010) applied tfee in order to analyze energy efficiency performance and energy saving potential in turkey by means of cross-country comparison and benchmarking with the eu countries for the period of 1995-2007. shu et al. (2011) calculated total-factor electricity consumption efficiency for 4 districts in china from 2001 to 2007 and econometrically tested the related influencing factors to explain the difference of electricity consuming efficiency of different districts. li and hu (2012) measured the ecological tfee of 30 regions in china for the period 2005-2009 through the sbm with undesirable outputs. their results showed that there are significant regional differences and china’s regional energy efficiency is extremely unbalanced. due to the rising awareness of global warning and other serious environmental problems, the research on tfee has been amended by introducing environmental impacts. one of the early studies on environmental efficiency, which was conducted in 1995, involved 19 oecd countries during the period from 1970 to 1990. initially, the study included the following variables: real gdp per capita, inflation rate, unemployment rate and the balance of trade. additional two variables were eventually included (nitrous oxide [n2o] and carbon dioxide [co2] emissions as undesirable outputs) and further analysis was carried out to determine changes in the efficiency trend. the study focused on the comparison of efficiency among 14 european and 5 non-european oecd countries. the expanded additive model approach revealed that european countries have lower relative efficiency after including the environmental issues (lovell et al., 1995). färe et al. (1996) were the first authors to include the variable of pollution in the dea methodology at the microeconomic level, involving electricity industry. they analyzed environmental efficiency of the u.s. electricity companies that produce electricity from fossil fuels, including total world emissions of so2, nox and co2 (in tonnes) as undesirable outputs. the study was based on two different sets of data comprising of 49 respectively 90 dmus. since then a considerable number of researches on electricity production have been conducted using dea methodology involving various variables of environmental pollution (zhou et al., 2008; ramli and munisamy, 2013). in 2003, a survey was conducted across 103 italian regions, divided into four groups based on the geographic zones, to evaluate relative environmental efficiency. the study included three sets of factors or variables: number of employees as input, gdp as desirable output, with ambient concentrations of nitrogen dioxide and particulates as undesirable output. the findings revealed that only a few regions have a significantly low environmental efficiency (nissi and rapposelli, 2006). by using the input-oriented dea approach with the assumption of a variable returns-to-scale, fang et al. (2013) computed the pure technical efficiency and energy-saving target (est) of taiwan’s service sectors during 2001–2008. besides the analyzing the effects of industry characteristics on the est by applying the dea method, they also calculated the pre-adjusted and environmentadjusted tfee scores in service sectors. results showed that the most energy efficient service sector was finance, insurance and real estate, which has an average tfee of 0.994 and an environment-adjusted tfee of 0.807. the study also utilized the vlahinić lenz, et al.: total-factor energy efficiency in eu: do environmental impacts matter? international journal of energy economics and policy | vol 8 • issue 3 • 201894 panel-data, random-effects tobit regression model with the est as the dependent variable. zhang et al. (2015) proposed a meta-frontier smb approach to model ecological tfee. they conduct an empirical analysis of regional ecological energy efficiency by incorporating carbon dioxide (co2) and sulfur dioxide (so2) emissions and the chemical oxygen demand of china during 2001-2010. their results indicated that most of the provinces were not performing at high ecological energy efficiency. one of the most recent research is the one from zhang et al. (2016). they analysed the panel data of 30 provinces in china from 2000 to 2012 by using the superefficiency dea model. their results showed that energy efficiency can be improved by promoting environmental regulation and they proposed a mechanism and mathematical model of environmental regulation and energy efficiency. a new research on environmental tfee in eu countries (šegota et al., 2017) shows significant differences in efficiency scores. in order to solve their environmental problems, inefficient countries should aim to change their energy structure and consumption behaviour. 3. data and the model a panel dataset of 28 eu countries from 2008 to 2014 is collected for the analysis. panel data enable a dmu to be compared with other counterparts, but also because the movement of efficiency of a particular dmu can be tracked over a period of time. therefore the panel data are more likely to reflect the real efficiency of a dmu than cross-sectional data. annual series used in the analysis as inputs are: gross fixed capital formation in current prices in million euro as a proxy for capital, labor employment annual series in thousands persons employed and energy consumption in thousands tons of oil equivalent, all obtained from eurostat (european commission, 2017). annual series used as outputs are: gdp at market prices in million euro and two undesirable outputs: carbon dioxide and sulphur oxides emissions in tonnes, all collected from the eurostat. table 1 presents the correlation matrix of the inputs and outputs used in the dea model. as it is shown in the table 1, inputs and outputs are highly positive correlated. the highest coefficient of correlation between inputs and outputs is between capital and gdp (0.99) while the lowest coefficient of correlation is between capital and sox emissions (0.63). high values of coefficients of correlation between inputs and outputs have approved their choice, implying that increasing values of inputs result with increasing values of outputs. we apply dea as a relatively new non-parametric approach to efficiency evaluation, which has been applied very often for benchmarking energy performance that is capable of handling multiple inputs and outputs. it is also applied in order to compare the energy efficiency performance of different countries/regions from the viewpoint of production efficiency. dea is linear programming method for measuring the relative efficiency of dmus in converting multiple inputs into multiple outputs. let us suppose that n dmus having three factors: inputs, good outputs and bad (undesirable) outputs as represented by three vectors xϵrm, ygϵrs1 and ybϵrs2 and, respectively. in the presence of undesirable outputs, efficiency can be defined as “capacity” of dmu to produce more desirable outputs and less undesirable outputs with less input resources or, more precisely, by following definition (cooper et al.,2004): definition: a dmuo (xo, yo g , yo b ) is efficient in the presence of undesirable outputs if there is no vector (x, yg, yb) element production possibility set such that xo≥x , ≤yg, ≤yg with at least one strict inequality. bad-output model, as modified sbm model (tone, 2001), is used to estimate relative efficiency of 28 eu countries in converting three selected inputs into selected desirable output and two undesirable outputs: ρ*=min 11 m s x 1+ 1 s s y + s y + io ioi=1 m r g ro g r=1 s r b ro b r=1 s1 2 ∑ ∑ ∑     (1) s.t. x0=xλ+s − yo b =yλ−sg yo b =yλ−sb l≤eλ≤us−≥0, sg≥0, sb≥0λ≥0 where λ is intensity vector, l and u are the lower and upper bounds of the intensity vector, sand sb excesses in inputs and bad outputs, sg expresses shortages in good outputs while s1 and s2 denote the number of elements in sb and sg with equality s=s1+s2. if the above program has the optimal solution (ρ*, *s− , sg * , sb * ) the dmu is efficient in the presence of undesirable outputs if and only if ρ*=1, * s− =0, sg * =0, sb * =0. if the dmu is not efficient, it can become ↔ efficient by following projections: x0 x x so o⇐ − −* y y so g o g g⇐ + * y x so b o b⇐ − * it follows that bad-output model is useful in indicating sources and amounts of relative inefficiencies for each inefficient country under estimation. in order to capture the dynamics of efficiency and changes during the 2008-2014 periods in eu we have conducted dea for each year using deasolverpro 13.0. table 1: correlation coefficients of input and output variables variable capital employment energy co2 emissions sox emissions gdp capital 1 0.971566 0.988942 0.903501147 0.6291712 0.9918128 employment 0.971566 1 0.984658 0.956703296 0.7618548 0.9767951 energy 0.988942 0.984658 1 0.931836383 0.7028478 0.9797972 co2 emissions 0.903501 0.956703 0.931836 1 0.8114032 0.9136125 sox emissions 0.629171 0.761855 0.702848 0.811403179 1 0.6333703 gdp 0.991813 0.976795 0.979797 0.913612549 0.6333703 1 source: authors’ calculation. gdp: gross domestic product vlahinić lenz, et al.: total-factor energy efficiency in eu: do environmental impacts matter? international journal of energy economics and policy | vol 8 • issue 3 • 2018 95 4. results and discussion as it has been indicated, the aim of our paper is to test the differences between tfee with and without environmental impacts. therefore, after selecting input and output variables, in the first stage the efficiency scores of countries without undesirable outputs in each year of the period 2008-2014 are analyzed. this is followed by identification of sources and amounts of relative inefficiency. table 2 contains the summary efficiency score results without environmental impacts (co2 and sox emissions), while table 3 contains the summary efficiency score results with undesirable outputs using bad-output model with constant returns to scale. according to presented results, one could conclude that energy efficiency can be overestimated without including environmental impacts. regarding efficiency scores in 2014, eu countries can be divided into three groups. the first group consists of denmark, greece, luxembourg and uk. there are no gaps between tfee (without greenhouse gas [ghg] emissions) and environmental tfee because they stay on efficient frontier for both tfee and etfee. the second group includes cyprus, france, germany, hungary, ireland, italy, portugal and sweden. these countries have reached higher etfee scores in 2014 than tfee without co2 and sox emissions. most of them are developed countries with high environmental standards and strong awareness of the importance of environmental protection and sustainable development. the third group includes most of the countries (16 of them) where efficiency scores are higher comparing with the efficiency results that incorporate environmental impact. these results indicate that measurement of energy efficiency without including environmental impacts as undesirable outputs, can be overestimated and cannot give a clear picture. when analyzing environmental tfee during time, results show that in 2014 there are more countries that have reached efficient frontier than in 2008, which could imply that eu countries pay a lot of attention to reduction of ghg emissions and sustainable development. european union advocated the ambitious targets, so-called 20/20/20 goals: (1) reduce ghg emissions by 20% in 2020 compared to 1990 levels; (2) increase energy efficiency so as to achieve the objective of saving 20% of the eu’s energy consumption compared to projections for 2020; (3) a binding target of a 20% share of renewable energies in overall eu energy consumption by 2020. energy efficiency appears to be the only energy item in these fundamental eu goals; the improvement of energy efficiency not only that can lead to reduction of ghg emissions, but also it can increase the renewable energy share without new investment. measures to ensure energy efficiency have become a priority for all eu countries, but their success differs among eu members. the worst performers in tfee that takes into account the level of harmful emissions are transition economies. in 2014 the worst relative efficiency was obtained by bulgaria, czech republic, estonia, latvia, lithuania, poland, romania, slovak republic and slovenia. these worst performers are countries with relatively strong industrial basis and their level of co2 and sox emissions are relatively high in comparison with the level of inputs and gdp. as one could expect, the table 2: efficiency scores for the eu countries in the period 2008-2014 without co2 and sox emissions country 2008 2014 austria 0.8742 0.7997 belgium 0.8132 0.7466 bulgaria 0.5249 0.3675 croatia 0.6168 0.6219 czech republic 0.5973 0.485 cyprus 0.7022 0.9766 denmark 1 1 estonia 0.5558 0.4674 finland 0.7937 0.7854 france 0.829 0.7878 germany 0.8828 0.8335 greece 0.8252 1 hungary 0.7453 0.549 ireland 1 0.9836 italy 0.9416 0.9868 latvia 0.561 0.5834 lithuania 0.6657 0.6505 luxembourg 1 1 malta 0.883 0.8884 netherlands 0.8639 0.8873 poland 0.7505 0.5553 portugal 0.7732 0.8698 romania 0.4514 0.5276 slovak republic 0.6785 1 slovenia 0.5858 0.662 spain 0.7274 0.8256 sweden 0.8083 0.7802 united kingdom 1 1 source: authors’ calculations table 3: efficiency scores for the eu countries in the period 2008-2014 with co2 and sox emissions country 2008 2014 austria 0.663516 0.67018 belgium 0.534928 0.541386 bulgaria 0.213054 0.265181 croatia 0.373642 0.455309 czech republic 0.320896 0.296302 cyprus 0.463317 1 denmark 1 1 estonia 0.269233 0.277539 finland 0.498689 0.634009 france 1 1 germany 0.668043 0.551806 greece 0.550205 1 hungary 0.384389 1 ireland 1 1 italy 0.727997 1 latvia 0.355637 0.373536 lithuania 0.333581 0.404398 luxembourg 1 1 malta 0.503298 0.590428 netherlands 0.596302 0.651691 poland 0.35756 0.348336 portugal 0.517744 1 romania 0.259823 0.310934 slovak republic 0.341339 0.409593 slovenia 0.376174 0.420429 spain 0.523972 0.558316 sweden 1 1 united kingdom 1 1 source: authors’ calculations vlahinić lenz, et al.: total-factor energy efficiency in eu: do environmental impacts matter? international journal of energy economics and policy | vol 8 • issue 3 • 201896 results for croatia are similar to other new eu member states, although there is a positive change in 2014. findings for croatia could be related to decrease in inputs, especially employment and energy consumption, while undesirable outputs (emissions) have been reduced. on the other hand, developed countries with highest energy efficiency that experienced the strongest growth of renewable energy like denmark, uk and luxembourg are countries that are graded as the most efficient. 5. conclusions the aim of the paper is to measure tfee with and without environmental (bad) impacts. this approach known as environmental tfee inherits total-factor framework based on dea, taking energy consumption with capital and employment as multiple inputs. in measurement of environmental tfee, the sbm model with desirable output (gdp) and undesirable outputs (co2 and sox emissions) has been adopted. under this framework, our paper analyzes energy efficiency in 28 eu countries from 2008 to 2014. our research results confirm that most of the eu countries have higher efficiency scores when the model does not include co2 and sox emissions. except for cyprus, france, germany, hungary, ireland, italy, portugal and sweden, in all other countries (20 out 28) efficiency scores for tfee in 2014 are higher or the same comparing with etfee in the same year. obviously measurement of energy efficiency can be overestimated and misleading when it doesn’t incorporate environmental (bad) impacts. this study could be further widened to consider the effects of the energy mix of the eu economies and energy prices in order to provide more insights on the aspects of energy efficiency, especially the possibility of energy sources’ substitutability, which could significantly alter policy measures and their implications. the obtained results have consequences in implementing measures for improving energy efficiency in the eu in the light of the ongoing desire to reduce greenhouse gas emissions. 6. acknowledgment this work has been supported by croatian science foundation under the project ip-2013-11-2203, by the university of rijeka under the project number 13.02.1.3.05. and under the project zp uniri 5/17. references boyd, g.a., pang, j.x. (2000), estimating the linkage between energy efficiency and productivity. energy policy, 28(5), 289-296. camioto, f.c., rebelatto, d.a.n., rocha, r.t. (2016), energy efficiency analysis of brics countries: a study using data envelopment analysis. gest production são carlos, 23(1), 192-203. ceylan, d., gunay, e.n.o. (2010), energy efficiency trends and policies: cross-country comparison in europe. paper presented at international conference of economic modelling (ecomod), istanbul, turkey. p7-10. cooper, w.w., seiford, l.m., zhu, j. (2004), data envelopment analysis. in: handbook on data envelopment analysis. vol. 71. new york: international series in operations research and management science. p1-39. european commission. (2017), eurostat. statistics database. luxembourg: european commission. fang, c.y., hu, j.l., lou, t.k. (2013), environment-adjusted total-factor energy efficiency of taiwan’s service sectors. energy policy, 63, 1160-1168. färe, r., grosskopf, s., tyteca, d. (1996), an activity analysis model of the environmental performance of firms-application to fossil-fuelfired electric utilities. ecological economics, 18(2), 161-175. honma, s., hu, j.l. (2008), total-factor energy efficiency of regions in japan. energy policy, 36(2), 821-833. honma, s., hu, j.-l. (2009), total-factor energy productivity growth of regions in japan. energy policy, 37(10), 3941-3950. honma, s., hu, j.l. (2011), industry-level total-factor energy efficiency in developed countries. discussion paper no. 51, kyushu sangyo, japan. hu, j.l., wang, s.c. (2006), total-factor energy efficiency of regions in china. energy policy, 34(17), 3206-3217. li, l.b., hu, j.l. (2012), ecological total factor energy efficiency of regions in china. energy policy, 46, 216-224. lovell, c.a.k., pastor, j.t., turner, j.a. (1995), measuring macroeconomic performance in the oecd: a comparison of european and noneuropean countries. european journal of operational research, 87(3), 507-518. nissi, e., rapposelli, a. (2006), assessing ecological efficiency via data envelopment analysis. available from: http://www.old.sisstatistica.org/files/pdf/atti/cime0905p171-174.pdf. [last accessed on 2017 mar 07]. ramli, n.a., munisamy, s. (2013), modeling undesirable factors in efficiency measurement using data envelopment analysis: a review. journal of sustainability science and management, 8(1), 126-135. šegota, a., vlahinić, l.n., maradin, d. (2017), environmental totalfactor energy efficiency in the eu countries. 6th international scientific symposium economy of eastern croatia-vision and growth, j.j. strossmayer university of osijek, faculty of economics in osijek. p675-685. shu, t., zhong, x., zhang, s. (2011), tfp electricity consumption efficiency and influencing factor analysis based on dea method. energy procedia, 12, 91-97. tone, k. (2001), a slacks-based measure of efficiency in data envelopment analysis. european journal of operational research, 130(3), 498-509. zhang, c., he, w., hao, r. (2016), analysis of environmental regulation and total factor energy efficiency. current science, 110(10), 1958-1968. zhang, n., kong, f., yu, y. (2015), measuring ecological total-factor energy efficiency incorporating regional heterogeneities in china. ecological indicators, 51, 165-172. zhang, x.p., cheng, x.m., yuan, j.h., gao, x.j. (2011), total-factor energy efficiency in developing countries. energy policy, 39(2), 644-650. zhou, p., ang, b.w., poh, k.l. (2008), a survey of data envelopment analysis in energy and environmental studies. european journal of operational research, 189(1), 1-18. tx_1~at/tx_2~at international journal of energy economics and policy | vol 9 • issue 6 • 2019 51 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(6), 51-64. identification of generalized models of development of economic systems of rental character based on the retrospective analysis of world experience liliia v. matraeva*, nataliya a. korolkova economic department, russian state social university, v. pika, 4, russia, moscow. *email: matraeva@rambler.ru received: 28 may 2019 accepted: 02 september 2019 doi: https://doi.org/10.32479/ijeep.8178 abstract the rental nature of the economic system determines the availability of additional opportunities as well as the problems of its development. the decisive factor is the choice of a development model based on the system of state regulation of rental relations, including the search for effective combinations of state policy mechanisms. the core in most cases is energy policy and energy management as a development factor. now we can talk about the accumulation of sufficient experience to conduct a comprehensive study of the peculiarities of the development of rental economies. the article reveals the experience of 24 countries of the world (30 cases) with a focus on the peculiarities of the formation and implementation of the state policy. the cluster analysis allowed us to identify three generalized models for the development of rental-type economic systems with a pronounced profile. this provides a basis for the identification of the main priorities. keywords: rental-type economic system, state policy mechanisms, clustering jel classifications: p510, o570, o110 1. introduction countries with rental-type economic systems are a large group in the world economic system, but it is, at the same time, a very heterogeneous one: norway, chile, usa, venezuela, australia, nigeria, mexico, russia, angola, indonesia, saudi arabia, canada, sweden, bahrain, colombia, etc. however, the history shows that all these countries are described by the condition of the economic systems characterized by instability due to problems in the system of rental relations. in this regard, each country is faced with the need to search for various combinations of public policy mechanisms that allow them to mitigate macroeconomic risks of a rent nature. this led to the need for the formation of scientifically based approaches aimed at solving these problems. conceptual approaches to the assessment of state policy within the framework of rental-type economic systems began to form as an independent direction in the 1950s and represented a failure of description (in a greater degree) and ways to overcome various negative phenomena in different periods of the economic history of a number of resource-rich countries. one of the first significant works was an article by prebisch, 1950, who studied the imbalance of the trade balance and the deterioration of the economic situation of oil-exporting countries with a deterioration in the conditions of foreign trade in the long term due to a fall in commodity export prices relative to the prices for imported industrial goods. the theoretical results obtained were refined and supplemented by singer and meier, 1958. this formalized the prebisch singer hypothesis. their recommendations were the basis for the state policy of a number of latin american countries of the 1960s-1970s. it was subsequently recognized as ineffective and was strongly criticized. the core of this conceptual model was the policy of import substitution. this journal is licensed under a creative commons attribution 4.0 international license matraeva and korolkova: identification of generalized models of development of economic systems of rental character based on the retrospective analysis of world experience international journal of energy economics and policy | vol 9 • issue 6 • 201952 the following additions to the theoretical aspects of managing of a rental-type economic system are associated with the definition of a staple trap theory (innis, 1954; baldwin, 1956). the study thereof was based on the canadian experience. as a basis of state policy, it was recommended to build a system of intersectoral relations of a certain type: the export-oriented resource sector was considered as a growth point of the industries that produced the means of production for the commodity sector and industries related to the processing of raw materials. subsequently, the hypothesis was supplemented and a diversification strategy based on the development of resource exports was suggested (hirshman, 1977). a special place among theoretical studies is occupied by the issues of overcoming the dutch disease (the groningen effect) (corden and neary, 1982; krugman, 1987; matsuyama, 1992), described by the diversion of investment in the upstream sector of the economy, the dominance of “simple” technologies, the slowdown in the accumulation of knowledge and decrease in demand for human capital, deindustrialization of the economic system, reduction of the manufacturing sector, primarily the manufacturing industry, as well as unemployment rise. restructuring of the economic system is considered as the main approach to overcoming negative consequences from the position of state policy. there are two models: british (liberal) and norwegian (based on government regulation). the british model is based on the regulation of foreign economic changes, therefore, the main activities are the interventions on the foreign exchange market in order to stabilize the exchange rate and support the expansion of international sales markets via product expansion of industries with low competitiveness to the markets of less developed countries. the norwegian model focuses on the creation of a sustainable sovereign fund, including to promote the implementation of antiinflationary policies, as well as to support innovative industries, primarily related to the commodity sector (technologies and equipment for oil production). consideration of the nigerian disease phenomenon (hiro, 2008) manifesting itself in the form of redistribution of rental income without regard to national interests (in the interests of the ruling elites), as well as a high degree of corruption of the isolated political elite, also complemented the theoretical understanding of the management of the rental-type economic system. if we considering the economy of nigeria, a set of recommendatory measures is associated with the development of competition in the primary industries and the strengthening of the position of private companies compared to state ones (restoring the balance between the private and state sectors). in the russian literature, the most significant results in the study of the theoretical aspects of rental-type economic systems management were achieved by polterovich and vladimir, 2007. two theoretical results can be distinguished in their works: the formalization of the hypothesis of “conditional damnation” and the selection of tools to stimulate growth with abundant resources, namely the following aspects: • the policy of withdrawing most of the resource rent by taxation; • passive strategy based on the implementation of the savings function via the formation of sovereign funds (polterovich and popov, 2003); • d e v e l o p m e n t o f i n d u s t r i a l p o l i c y : a s u m m a r y o f recommendations for the formation of state programs aimed at capital accumulation, a critical assessment of the minimum wage measure (rodrik, 1996; vorobyov, 2006), public investment in technology (zhukova, 2006); • accumulation of foreign exchange reserves as a tool of lowselectivity industrial policy (polterovich and popov, 2005); • lowering of fuel prices is equivalent to the entire domestic production subsidizing. it is noted that the undervaluation of prices accelerates growth in the early stages of development (with relatively low gdp per capita) and slows down the growth if the country is sufficiently developed, that is, the tool is associated with the dependence of the threshold nature. all of the above authors adhere to the mainstream economic theory and policy to varying degrees. it supports the “concept of the rental state” (mahdavy, 1970; kimelman, 2011) focusing on the decisive role of incomes of rental origin among all incomes of economic entities, as well as highlighting the process of appropriating rent as the basics of social and economic development. at the same time, there is an alternative point of view assuming that “it is impossible to form a successful economic policy on the basis of theories built on abstract mathematical models and calculations,” expressed by rainer (2011). it is also interesting that the overwhelming majority of researchers emphasize the “abundance” (wealth) of resources, that the center of attention is focused on resource redundancy as one of the main parameters. at the same time, the rental economy can be built up even in terms of resource availability (under appropriate external conditions for the rent formation). n. ding and b. field (ding and field, 2005), and further t. gylfason (gylfason, 2007) pointed out the significance of the “resource dependence” and “resource security” concept. according to their observations, the first corresponds to the manifestations of the “resource curse,” the second admits the formation of positive trends in the economic development. this statement can be supplemented: resource availability stimulates growth and development of the economy only within certain limits, which largely depend on the existing institutional conditions. at the same time, both the resources and the rental income derived from them can turn from an intensifying factor into a destabilizing one, and vice versa. closely related to this is the study of the issue, which can be summarized as “the presence of a threshold effect”: there is an estimated threshold value of the level of institutional development, below which the abundance of resources impairs the quality of institutions, and above does not have a significant effect on it. the presence of this threshold is partially confirmed by the empirical test carried out in the already mentioned work of mehlum et al., 2005, as well as the last author in the work of robinson et al., 2006, who established the dependence of the threshold on the quality of institutions in the country’s economy. along with this, there is a downside: the dependence of the threshold on the magnitude of the resources. this connection was taken into account in the theoretical model of the threshold in the first of the above mentioned works, but the matraeva and korolkova: identification of generalized models of development of economic systems of rental character based on the retrospective analysis of world experience international journal of energy economics and policy | vol 9 • issue 6 • 2019 53 respective econometric calculations were performed by already noted polterovich and vladimir (2007). recently, in some works (zotin, 2017a), there has been an application of the concept of “mismanagement” to the economic policies of countries rich in natural resources. as applied to the management of rental-type economic systems, this term is used to disclose a type of management characterized by both unintentional errors and deliberate unlawful actions by economic entities (first of all, government officials) and the lack of proper internal control and supervision over the activities of rental relations entities. the most striking example is venezuela. its history emphasize the periods of the emergence of a new political regime via the financing of oil rent. thus, it is possible to make a number of intermediate conclusions about the features of the theoretical study of the problems of formation of the state policy of rental economies: • the majority of theoretical studies in this area is situational in nature, based on the description of different periods in the economic development of individual countries of the world; • in many cases, the one-sidedness of the resource path of the economic development is emphasized: the focus is on identifying and describing the shortcomings and paradoxes related to the formation and use of rent in various macroeconomic situations; • there is a problem of the possibility of replicating the results obtained on the basis of the experience of individual countries. it is necessary to change the research task itself: do not try to identify key mechanisms as a “medicine” based on the experience of individual countries, go on to the search for combinations of mechanisms that, under certain conditions, will ensure that the rental economy is in an effective state. as a result, there is a need for a comprehensive study that will generalize and systematize the main theoretical approaches to the formation of state policy in the framework of rental-type economic systems management. this is confirmed by the research activities of the international organizations attempting to create international recommendations for rental-type economic systems. a special place is occupied by analytical brochures and reports of the imf. initially (in the early 2000s), a series of works was observed in the imf special issues, combined with the oil wealth management topic. the studies were based on the consideration of individual cases, for example, azerbaijan (niko et al. 2014), and contained an assessment of a specific economic system and recommendations from fund analysts on its further development. at present, it is possible to note the formation of imf reports not only in individual countries of the world, but also in the context of specialized issues, in particular, in the mobilization and management of revenues from the commodity sector. this group of publications is presented by the reports of the managing natural resource wealth trust fund (mnrw-tf), operating since 2011. mnrw-tf implements the imf research and analytical work in this subject area, identifies the approaches based on successful cases, and draws lessons from national experience for the subsequent formation of international recommendations. more than 20 projects were implemented in the first phase of the mnrw-tf (may 2011-april 2017). they were aimed at improving the fiscal regimes of managing the extractive industries (improving extractive industry ei), expanding the capacity of authorities to administer and control income from ei, developing public financial management systems, including sovereign wealth funds, improving the quality of reporting on the accounting of natural resources in national accounts (mnrw-tf, 2016a). this happens via technical assistance, which is to promote the integration of the recommendations of the fund into the state policies of the participating countries, and to conduct customized training. a special place among the results of the first phase of mnrw-tf is occupied by the developed methodological framework. in particular, some attempts have been made to form comprehensive recommendations on the transformation of state policy (regulatory framework) for rental-type economic systems: • “administering fiscal regimes for extractive industries: a handbook” (calder, 2014) in terms of the effective management of revenues from the extractive industries; • “sovereign asset-liability management (salm) guidance for resource-rich economies” (mnrw-tf, 2014) in terms of the effective management of sovereign funds. in addition, a methodology was developed for the assessment of the effectiveness of the mnrw-tf project implementation aiming to diagnose the success of the participating countries and based on an approach to project management, especially development projects, called “results-based management.” the project is now in the second phase of its implementation and focuses on the capacity development via five interconnected modules to improve the fiscal regimes of the upstream and revenue management in the participating countries: • module 1: ei fiscal regimes, licensing, and contracting; • module 2: ei revenue administration; • module 3: macro-fiscal, public financial management, and expenditure policy; • module 4: exchange rate regimes and macroprudential policies; • module 5: statistics for managing natural resources (mnrw-tf, 2016b). it is interesting that the mnrw-tf methodology offers exactly an integrated approach to the implementation of the modules involving a combination of public policy mechanisms, and not fragmentary improvements. the most prominent example today is the recommendation on using imf’s fiscal analysis for resource industries (fari) model (mnrw-tf, 2016c): a fiscal analysis (module 1) provides a basis for the assessment of risks associated with the income from the resource sector (module 2), which in turn provides the possibility of macro-budget forecasting of government revenues (module 3). matraeva and korolkova: identification of generalized models of development of economic systems of rental character based on the retrospective analysis of world experience international journal of energy economics and policy | vol 9 • issue 6 • 201954 it should be noted that this approach of mnrw-tf is the most advanced in the field of formation of integrated public policy in the framework of rental-type economic systems management, but focuses on the management of financial flows and the achievement of stability in the field of fiscal policy. in particular, the issues related to structural policy, development of real sectors of the economy, innovation policy, etc. are not addressed. this is confirmed by the current assessment of the most important results of the implementation of the second phase of the project for the participating countries, presented in the annual report of mnrw-tf (mnrw-tf, 2018). besides, as part of the formation of international recommendations, it is possible to highlight the development of the extractive industries transparency initiative standard (eiti 2016) (eiti, 2017), whereby the information on the oil, gas and mining industries is published. it is important to note that the document is not instructive in the management of the upstream sector, but rather a tool that provides information on how this sector is managed. testing of the eiti standard ended in 2015 in norway. by now, the eiti compliance test is being implemented in another 48 countries (eiti, 2019) with the support of mnrw-tf. the content of the initiative comes down to the annual provision of key information on sector management by the participating countries, along with the recommendations for sector management improvement. thus, the base of best practices is being formed and the progress is being monitored in the improvement of the efficiency of resource sector management in selected countries of the world. at the same time, active areas of analysis are contracts and licenses in the sphere of subsoil use, production processes, the taxation system, the income distribution model, the contribution of resource industries to the country’s social and economic development. also there is an interesting fact that the eiti is actively developing the institute of public oversight and discussions in the subject area under study: there is a special requirement for the formation and functioning of a national multi-stakeholder group (representatives of government, industry companies and civil society). thus, a review of empirical studies confirms the feasibility of conducting a comprehensive study of rental economies and makes it possible to raise the question of identifying the development model of a rental-type economic system, which leads to an effective state of the system. 2. research methodology the study of scientific papers, representing the results of theoretical studies of rental economies, makes it possible to emphasize their one-sidedness, which is explained by focusing on the consideration of a small number of economies or a particular economic system. on the other hand, observations and studies of the economies of different countries of the world described by the systems of rental relations of different degrees of development, that is, empirical studies, allow us to conclude that their experience is possible and expedient to generalize. thus, if earlier the study of rental-type economic systems could only be situational in nature and was fragmentary, then, at present, it is possible to speak of accumulating sufficient experience for comprehensive research in this area. therefore, it is permissible to assume that a number of generalized models for the development of rental-type economic systems can now be identified based on the experience of using various public policy mechanisms therein. consequently, we are faced with the technical task of rental-type economic systems classification as per the state policy mechanisms used therein, that is, identifying homogeneous groups from the entire set of objects studied, uniquely identified and having a clearly interpretable profile. one of the most well-known statistical methods used to solve such problems is cluster analysis. it which allows to form homogeneous groups inside and heterogeneous ones with respect to each other as per given parameters most accurately. at the same time, it is advisable to lay down the optimal ratio of intercluster to intracluster dispersion as the main criterion for the formation of clusters, taking into account the economic task that has been set. the initial base of the research was formed on the basis of an expert analysis of the mechanisms of state policy used in 30 cases of economic development in various countries. they were coded on a binary scale in the results of the expert’s answers, where 0 is the absence of a mechanism, 1 is the implementation of the mechanism within a specific case. the most acceptable for solving the problem is the k-means method. however, the method cannot be applied to binary data (ibm, 2009). in this regard, a hierarchical cluster analysis has been implemented using an agglomerative algorithm (combining objects, initially considered as separate small clusters, into larger groups) in the spss statistical package. the main method of cluster formation is the ward’s method, which allows clustering as a sequential procedure, at each step combining two such classes with minimization of statistical distance between the classes, providing a clearer cluster solution in conditions of data overlap (vukolov, 2013). binary data (nominal scale) analysis imposes additional restrictions on the selection of distance metrics. the squared euclidean distance for binary data (ibm, 2009) was chosen as an indicator characterizing the measures of differences in the research objects. the determination of the optimal number of clusters was based on the interpretability of the constructed model (meaningful importance of groups), as well as the following criteria: • intercluster distance by analyzing the agglomeration graphs and visual analysis of tree diagrams (moosmyuller and rebik, 2015); • cluster sizes by building a pivot frequency table for various cluster solutions (from 3 to 5 clusters). final cluster centers were calculated to interpret the main characteristics of the formed groups. a report was generated on average values for each attribute, taking into account the establishment of the cluster number as a grouping variable in the absence of the specified ability for hierarchical cluster analysis in the spss statistical package. as a result, basic, superstructure and non-involved mechanisms of state policy were identified within the matraeva and korolkova: identification of generalized models of development of economic systems of rental character based on the retrospective analysis of world experience international journal of energy economics and policy | vol 9 • issue 6 • 2019 55 framework of generalized models of development of rental-type economic systems with clear profiles. 3. special tools 3.1. description of the information base forming method the objects of cluster analysis are the state of the rental-type economic systems. the experience of using different mechanisms of public policy aimed at leveling problems in the economies of the specified nature can be considered on the example of 24 countries (the largest producers and exporters of natural resources). at various periods of time, 30 states of these economic systems can be identified (30 cases), which are characterized not only by different sets of mechanisms, but also by levels of economic efficiency. 3.1.1. venezuela (1970s) the period of saudi venezuela (venezuela saudita): the state mega-project “great venezuela” was adopted (yergin, 2017) in the face of the need to overcome the negative recent import substitution policies and control the flow of petrodollars from the oil shock of 1973. the project implemented substantial state intervention in the country’s economic system: creation of a system of subsidies, creation of jobs and artificial increase of the salary plan, diversification of exports by interfering with the activities of non-oil enterprises, etc. the project implementation depended strongly on the sustainability of rental incomes and was ineffective after the fall in oil prices since 1979. 3.1.2. venezuela (1990s) the country implemented a state policy dictated by the recommendations of the imf. a package of measures aimed at widespread privatization, opening the country to foreign capital in any sector of the economy, as well as price liberalization has been taken without taking into account economic security. the result is a financial crisis in the mid-1990s (economic portal, 2019). 3.1.3. venezuela (2000s) the adoption of the new economic program, “bolivarian socialism of the 21st century”, in 1998 restored the basic principles of the country’s economic security. key aspects: building of a strategic planning system, concentrating raw materials and land resources in the hands of society, tight control over them, a complete change of development priorities while maintaining a reasonable balance between the public and private sectors of the economy (dieterich, 2005). however, manual government is used through non-market mechanisms. the result is economic growth against the background of a short-term artificial increase in the well-being of the country’s population, but without creating of a sustainable basis for economic development. 3.1.4. angola development is constrained by the strong dependence of the state budget on the hypertrophied oil and gas complex. the energy sector is expanded by international oil and gas companies. the participation of sonangol national company in the extraction of energy resources is very limited. the main function of the company is reduced to concession agreements conclusion and taxes collection (de oliveira, 2007). the development of other industries is hampered by the dutch disease. 3.1.5. mexico currently, rent dependence is preserved by the maintenance of inefficient tax system and other fiscal mechanisms (farfan-mares, 2010).1 at the same time, the country demonstrates successful economic development by becoming one of the strategic suppliers of oil in the united states (implementing the us energy strategy), strengthening of the economic ties in the non-oil sector, including the development of makiladoras (from 1964 till present time), implementing the program of cross-border development (since the 1980s), the abolition of the monopoly of petroleos mexicanos (pemex) state-owned company and the opening of the oil and gas industry to attract foreign investment (2013). 3.1.6. azerbaijan the export-oriented production model and economic diversification has been declared the target model of economic development. this is stated in a variety of strategic documents: “azerbaijan 2020: a look into the future” development concept, the “state program for the development of industry for 2015-2020” and a number of strategic road maps for the national economy and main sectors of the economy. however, the declarative rather than the functional nature of the set of strategic documents is noted, including the “long-term strategy for managing oil and gas revenues for the period 2005-2025” (decree, 2004; reports and statistics, 2019). 3.1.7. indonesia an example of successful diversification of the economy via the implementation of an investment growth model including significant investment in production, export orientation, and reliance on cheap labor (zotin, 2017b). the leveling of resource dependence, in particular, the dependence of the state budget on rental income, was ensured via the effective state policy, initially (from the 1970s) aimed at developing the agro-industrial complex of indonesia, and then (from the 1990s) becoming an exportoriented industry due to preferences from the usa (program document, 2017) and japan (hoekman et al., 2009). 3.1.8. saudi arabia (1960-1990s) this period of the country development is characterized by a high degree of resource dependence. the system of distribution of state budget revenues is of a centralized type, which is associated with the current monarchical system. a complex bureaucratic apparatus was used as an active tool to formalize rent generation: the country implemented the “free institutions design” of state power (hertog, 2007). the country has not formed a system of taxation and sovereign funds. industrial policy was fragmented, being a hidden form of redistribution of oil rent without effective development of the non-oil sector. 3.1.9. saudi arabia (since 2000) the country recognized the need to transform the economic system (after a period of low oil prices from the 1980s-1990s), but there 1 makiladoras various assembly plants, placed by foreign companies (mainly the united states) in mexico. matraeva and korolkova: identification of generalized models of development of economic systems of rental character based on the retrospective analysis of world experience international journal of energy economics and policy | vol 9 • issue 6 • 201956 is still a strong dependence on fluctuations in the world oil prices (foudeh, 2017), an inefficient system of energy subsidies, the lack of a developed tax system strong bureaucracy, significant public sector. saudi vision 2030 development strategy (program document, 2016a) is being implemented in the country to level resource dependence from 2016. six state programs have been launched and about 96 kpis have been established, stated in the national transformation program 2020 (program document, 2016b). a sovereign fund, public investment fund (pif), has been established. it performs an investment, not a savings function. 3.1.10. uae government policy is centralized due to the dominance of the emirate donor, abu dhabi, based on the use of oil rent. the income tax generated by oil and gas companies (55-85%) (pwc, 2015) generated by the state budget surplus becomes the basis for the activity of sovereign funds with an active investment strategy. regional development is performed taking into account the absence of dependence on world oil prices: the other emirates limit subsidies from abu dhabi. the uae was able to use its geopolitical position as a competitive advantage (1980-1990s) by creating of special economic zones (biryukov and biryukova, 2016), removing of customs barriers and an effective labor migration system (movchan, 2017). now the uae is a global financial and business center, the main reseller for a number of developed countries, one of the world’s re-export centers. 3.1.11. iran oil rents led to the acceleration of development in the 1970s with the formation of an unbalanced economic system: the white revolution doctrine (sergeyev and sarukhanyan, 2012) suggested agrarian reform and accelerated industrialization from the 1960s on the basis of attracting foreign capital without regard to national and religious specifics. but there is a forced reorientation of the development of the industrial complex to the base of internal reserves (salitsky et al., 2017) in the period from 1979-2016. the country returned to the implementation of the strategy of already re-industrialization by attracting foreign direct investment after the international sanctions removal (zotin, 2017c). 3.1.12. nigeria an example of public policy for the rental income management, leading to the conservation of social and economic problems. the nationalization of hydrocarbon production and the concentration of rental income at the federal budget level were forced measures to curb regional development problems (manasseh et al., 2019). this has led to the formation of sectoral imbalances, including the restriction of agricultural development, the development of “nigerian disease” and the excessive dependence of the state budget on rental income, and exposure to external oil shocks (imf, 2018). since 2000, nigeria has managed to change the rent distribution formula (grigoriev, 2017a), which provides the basis for the economy diversification with a focus on the revival of the agro-industrial complex and the development of the telecommunications sector. 3.1.13. norway (until 2014) the success of the norwegian experience is formed from the following key components: organizational and functional management structure (thurbera et al., 2011), state ownership system, taxation system, rental income distribution system, social policy. there is a two-part management model for the national oil company (since 1985): free participation in the capital (67% of statoil [mtif, 2015]) and the state’s direct financial interests system. tax system: the marginal tax rate is 78% (22% is the base tax, 56% is the special tax of oil producing companies (mtif, 2019). it is also interesting that government revenues are rent-dependent, but the costs are not. this is achieved via the activities of the global pension fund global (lovdata, 2016). as a result, the norwegian budget is more non-oil and this ensures a balanced development of the country and facilitates the creation of a diversified export-oriented industrial complex. 3.1.14. norway (since 2014) the country is faced with the question of the need for structural transformations for a smooth transition to the progressive nature of the economic system in the context of the exhaustion of its resources. the high sectoral differentiation laid down by the “national champions” support program since the late 1980s provided a shift in the focus of the country’s technological development. the measures taken (changes in investment approaches during industrialization and a new innovation policy) have so far shown low performance and additional diversion of investment flow and r&d development towards the oil and gas sector. 3.1.15. united states (alaska) a deterrent to unlocking the potential of the region and attracting investment from oil companies is the high level of taxes on oil production on land. mitigation of the tax regime is hindered by the senate of the us congress. investments in fixed assets play a key role in the economic growth model of alaska; energy resources are not highlighted as a development factor (bekareva et al., 2018). the experience of creating the alaska permanent fund in 1976 (apfc, 2019) is also interesting in the example of alaska. a natural restriction has been created for the misuse of the fund: the budget rule cannot be changed by the authorities, only via a referendum, since they are constitutional norms. significantly, the fund’s policy since 1979 includes a special dividend program: direct distribution of a limited share of revenues generated on the basis of oil rent (10% of the total annual fund income) among state residents around (alaska’s constitution, 2019). 3.1.16. usa the entire us state policy is aimed at ensuring its economic and also energy, security and the formation of the country’s energy independence (khlopov, 2015). the current state policy complex is characterized by continuous state supervision of the subsoil development and production processes, flexible tax policy in the extractive industries, the use of a wide range of rent extraction tools (bonuses, rentals, fixed royalties, etc.), clear specification of property rights, accumulation of rent on regional level (baykova, 2013). 3.1.17. great britain the uk has created an effective system of embedding the oil and gas complex in the national economy via the creation of a matraeva and korolkova: identification of generalized models of development of economic systems of rental character based on the retrospective analysis of world experience international journal of energy economics and policy | vol 9 • issue 6 • 2019 57 financial system that can successfully absorb large-scale rental incomes, which are then used, including to support and develop the finished product industries (ryazanov, 2011). at the same time, hydrocarbons are the property of the monarchy, a licensing regime is in force, whereby the licenses are granted for the exploration and production of oil (act, 1998). the risk of resource depletion and becoming a net importer is updated: in 2017, resource availability is estimated at 4.4 years (bp statistics, 2018). at the same time, the energy policy of the country is focused on the environmental protection and replacement of electric power capacities taking into account the use of low-carb technologies. 3.1.18. australia regulation of mining is performed at the local level via mining laws of various states and territories. a licensing system is in place to pay royalties (leary and kerrigan, 2018). at the same time, the country used the mining industry as a driver for the development of high-tech services. the country realizes the redistribution of funds via an effective tax system (bobylev, 2013) to support the technological development of the manufacturing and social sectors. at the same time, australia does not have commodity sovereign funds, that is, the system is built in such a way that it does not require sterilization of the economy and is capable of absorbing all funds within the country. 3.1.19. canada the industrialization of the country was performed based on the formation of private investment activity and was financed via natural rent (howlett et al., 1999; kapitsa, 2014). at the same time, canada’s state energy policy is based on strengthening its position in world energy markets (foreign policy extractive sector trade strategy) (caulfield, 2015), on the one hand, and on maintaining the investment attractiveness of national production facilities (domestic policy licensed rental system for the provision of subsoil for use (baykova, 2013) on the other one. canada does not support the use of sovereign funds. the exception is alberta, but its experience is not unequivocal (kapitsa, 2007). the country also has significant positive experience in the development of energy conservation and energy efficiency policies (nrcan, 2015). 3.1.20. sweden a country with an effective economic system has always been export-oriented: initially natural resources (wood and iron ore), then products with high added value (engineering, etc.). at the same time, the main factor-the development of the economic system was labor productivity, not natural resources. state policy is based on: securing the forest as a national asset and renewable resource (sweden parliament, 2019), certification system, sustainable development policy of the “green state of universal welfare”, support for the private sector, income redistribution system, social policy, employment policy and spatial planning (holyavko, 2014). 3.1.21. chile (until 2009) chile’s economic development is based on the copper industry and rental income (nikolaeva, 2018), but it was characterized by a lack of cost control and low efficiency and ease of manufacture of metal mining and processing until 2009. for a long time, the main instrument for the development of mining industry in chile was concession agreements in the framework of exploration and mining of minerals this was enshrined constitutionally (act, 1982; act, 1983). this made it possible to attract the required volumes of foreign investment, but limited the possibilities for technological development of national producers and increased the dependence of government revenues on rental income. in the framework of the sovereign fund management policy (copper stabilization fund), its inappropriate use is noted to repay foreign debt and subsidize domestic prices for gasoline. 3.1.22. chile (since 2009) the state policy on the introduction of innovations in the mining industry has enabled chile to diversify the economy and exports since 2009, raise the technological level of the country and achieve sustainable economic development. the country implements expanded state support for the innovation activity (nikolaeva, 2018), including via centralized coordination, organization of regional dialog sites on the problems of sectoral development of regions, the development of the mountain cluster, funding as an instrument of accumulation and redistribution of rental income mineral raw materials, as well as foreign investors attracting. now the country’s innovation policy is closely linked to the policy of foreign investment attracting in the mining sector: attracting of new technologies from international companies, and not just financial resources (cochilco, 2019). all this makes it possible to gradually integrate chile’s copper industry into international value chains. 3.1.23. kuwait the economic system of kuwait is characterized by limiting of foreign influence (wipo, 1962). foreign participation is limited to the construction and maintenance of oil and gas facilities via one-time contracts. special attention is paid to the social sector. the policy of expanding social payments is conducted annually (mihin, 2018). the population is exempt from paying taxes. this set of measures is also associated with the prevention of the formation of social and political tensions characteristic of the countries of the persian gulf. 3.1.24. bahrain a concentration of economic opportunities, including rental income, was realized on the development of the manufacturing industry: oil refining, petrochemistry, and the aluminum industry under the threat of exhaustion of energy resources (oil and gas). fiscal reforms are currently underway in the country, including the reduce of energy subsidies and introducing value added tax (cio, 2017). the formation of sources of government revenues from non-oil sectors is highlighted as one of the main strategic objectives. one of the growth points of bahrain is the sphere of financial and business services: the strategic position in the center of the persian gulf provides the country with development as a financial and business center of oil-exporting countries. 3.1.25. colombia the mining sector is the backbone of colombia’s economy and the main source of rental income. since 2003, the development of the industry began to be associated with attracting foreign investment matraeva and korolkova: identification of generalized models of development of economic systems of rental character based on the retrospective analysis of world experience international journal of energy economics and policy | vol 9 • issue 6 • 201958 in a critical situation of depletion of resources due to the non-use of hydraulic fracturing technology (neftegaz, 2017). changes were introduced to the organizational and functional structure of the sector and the status of ecopetrol backbone company was changed to a partially state-owned company (zapata and ricciulli, 2018). the constraining circumstance of development remains social and political tensions in the country. 3.1.26. zimbabwe the basis of the economic system is the mining industry after an unsuccessful agrarian reform (2000s): gold, diamonds, iron ore, coal, etc., are mined. rental income is concentrated in a narrow circle of the ruling elite. the country cannot ensure its own internal development and is limited in attracting foreign investment, including in the extractive sector. there are no hightech production. social and political tensions are maintained in the country. 3.1.27. iraq since 2006, the belonging of the oil and gas people of iraq (article 111 of iraq’s constitution) is constitutional the monopoly on the development of iraqi oil fields belongs to state-owned companies. in the early 2000s, iraq has a series of reforms prepared. it was to create a unified system of strategic development of the iraqi economic system based on the oil and gas sector and attracting foreign investment. the changes were never accepted due to the war initiated by the usa. two types of service contracts of three types (strong, 2018) and production sharing contract (almost not used) are now stipulated and legally fixed to attract international oil and gas companies. 3.1.28. yemen it is one of the poorest arab countries. as the main task of developing the national economy, it is currently accepted to attract arab and other foreign investments in the oil, gas, minerals industries and to achieve a long-term strategic partnership. the main form of relationship has become a production sharing agreement. special provisions of the contract include exemption from a number of customs duties and related taxes, which reduced the share of rental income in gdp (abdul, 2013). interestingly, since mid-2005, the government of yemen has ceased to insist on the prolongation of contracts with some large international companies (hunt oil company (usa), nexen (canada), total (france), dof group (norway), creating instead national companies (safir, petromasila). only citizens of yemen are at the key oil and gas enterprises. this may indicate the beginning of the formation of the principles of economic security and independence. 3.1.29. kazakhstan the problems of the public debt increase, provoking of a banking crisis due to uncontrolled lending, “dutch disease,” atrophy of manufacturing industries, and corruption were formed against the background of the initial development of the export-oriented energy-resource mining sector at the expense of foreign investment attracting (spivak, 2017). at present, it is declared that “in the near future, kazakhstan will have to continue the process of transition from an economy driven by a factor of “raw materials competitiveness” to an economy based on growth due to the “investment factor,” with further achievement of the prerequisites for the beginning of an economy driven by an “innovations factor” (decree, 2014; bekturganova et al., 2019). however, the analysis of strategic documents shows the focus not on a comprehensive transformation, but on the improvement of the current growth model. 3.1.30. russia the development of the energy sector forming the basis of the russian economy, is determined by a number of strategic documents, including the medium-term social and economic development forecast, the energy strategy, the energy security doctrine and the state program for energy development. a tax reform in the oil and gas sector is being implemented in the country a “tax maneuver”: the gradual zeroing of the export duty on oil and replacement thereof with a mineral extraction tax. the russian system takes into account the sterilization of the economy the development of sovereign funds (the reserve fund and the national wealth fund). however, the implementation of the state policy in this part violated the tasks set during its formation (kudrin and sokolov, 2017). de facto management of sovereign funds of russia showed its low efficiency, and the rate of their exhaustion during the crisis period only confirmed the existence of systemic problems with the stability and balance of the state budget. signs during cluster analysis in the framework of this study are the mechanisms of state policy implemented in the studied rentaltype economic systems. the generalization of world experience allowed us to identify more than 20 mechanisms of state policy, allowing to level the key social and economic problems associated with the system of rental relations. at the same time, it is difficult to give them an unambiguous assessment by the criterion of efficiency: the degree of efficiency depends on the conditions for the implementation of mechanisms and the state of the economy. under these conditions, it is more reasonable to group from the position of the availability of approbation of mechanisms in rental-type economic systems. thus, it is possible to single out mechanisms subject to the implementation of experience in various rental economies (korolkova, 2018): 1. sterilization of the economy, including the formation of reserve funds that contribute to the redistribution of time and leveling of income; 2. limiting the dependence of the budget on rental income by the reduce of production; 3. floating exchange rate; 4. distribution of a limited share of rental income (investment income) on a non-competitive basis: equal payments, pensions, social benefits; 5. margin leveling; 6. long-term contracts for rent-forming resource; 7. hedging prices for rent-forming resource; 8. denomination of debt in terms of the resource; 9. provision of preferences for foreign companies; 10. export diversification (including commodity exports); 11. development of non-primary (non-oil) economic relations; 12. centralization of the extractive industries, and then the resource industry as a whole (in the extreme case, nationalization); matraeva and korolkova: identification of generalized models of development of economic systems of rental character based on the retrospective analysis of world experience international journal of energy economics and policy | vol 9 • issue 6 • 2019 59 13. economic diversification via government intervention; 14. creation of a subsidy system; 15. development of energy conservation and energy efficiency policies; 16. fiscal mechanisms, namely discriminatory taxation and regulation; 17. import substitution policy and protection of domestic producers; 18. price control in the domestic market; 19. cartel agreements; 20. loans at lower rates (on average libor + 1.5%) for economic recovery secured by oil contracts (supported by oil supplies); 21. restriction of repatriation of profits of foreign companies. the latter mechanism is excluded during cluster analysis due to the lack of confirmed information for a number of countries. 4. results and discussion 4.1. experiment (calculations themselves) the results of euclidean distance calculation taking into account the binary connection were obtained at the first stage of hierarchical clustering and each object of observation was considered as a separate cluster. they show the extent which the rent-type economic systems differ to in the structure (set) of public policy mechanisms used therein. the most similar objects are nigeria, yemen, zimbabwe: the square of the euclidean distance between these groups is 2.00 and is the minimum among all other values of this indicator. the greatest difference is observed in such a pair as russia and yemen (16.00), which first proves the heterogeneity of the generalized models to be identified in them. the optimal number of clusters is four as per the analysis of the dendrogram. the preference of the chosen solution is proved by the correlation of the fullness of the clusters for various cluster solutions (from 3 to 6) using the pivot table of frequencies. it is possible to identify generalized models for the development of rental-type economic systems based on the analysis of the cluster end centers (table 1). evaluation of the participation of mechanisms in the combination of development models allows us to conclude that most of them are important for at least one of the models. the mechanisms with a low contribution rate (from 0.1 to 0.3) include: “distribution of a limited share of rental income (investment income) on a non-competitive basis,” “equalization of the margin” and “diversification of the economy via government intervention.” however, the exclusion of these mechanisms during the analysis may cause a distortion of the clarity of the contours of the selected models: they can play a secondary supporting role for a particular combination. at the same time, significant mechanisms of public policy can be divided into three groups depending on their frequency of use in various models: • basic mechanisms: frequency of use above 0.75; • add-on mechanisms: the frequency of use is more than 0.4, but <0.74; • mechanisms not involved: frequency of use is 0. 4.2. experimental results (description of generalized models) the analysis of the resulting combinations of mechanisms allows us to identify three generalized models for the development of rental-type economic systems with clear profile (table 2): • model 1 “development aimed at the creation of a strong diversified industrial complex”; • model 2 “development supported by external support”; • model 3 “maintenance of short-term macroeconomic and social stability, without development.” the fourth group included countries with unique models or forming models that do not yet have a clearly defined development vector. model 1 “development aimed at the creation of a strong diversified industrial complex.” the most effective state of the economic system within the framework of the model implementation was reached by norway (grytten, 2008) and the usa (kapitsa, 2014; engerman and gallman, 1996). the profiles of the economic development of these countries clearly show the use of its own mineral resource base for the formation of a sustainable, diversified industrial complex producing high value-added products. at the same time, this development took place on the basis of a competitive market economy mode relying on private and public-private companies as the locomotives of the scientific and technological process (ryazanov, 2011). three options of its development can be distinguished within the framework of this model: 1. import-substituting approach: focus on meeting the needs of the domestic market via the development of national industries; 2. export-oriented approach: recommended for small economies in the conditions of the inability to maintain high growth rates of domestic consumption in the long term, as well as the constraints arising while reducing costs for the cost of production, if production volumes meet domestic demand only; 3. combined campaign: maintenance of the simultaneous growth of imports of products of the extractive industries and exports of products of the processing industry while maintaining its own resource base. it should be noted that the development path of the russian economic system also corresponds to the model in question, but does not ensure its transition to an effective state. it is advisable to look for the reasons for the current situation in the complex assessment of the balance of the russian economic system. model 2 “development supported by external support.” examples of development as per model 2 are mexico, indonesia, and colombia. the most characteristic of the group is the economic portrait of mexico demonstrating the management of the national system via the creation of favorable conditions for external influence, that is, from the developed countries of the world. mexican experience shows that this path can provide a transition to an effective state of the economic system. currently, the country’s economy is quite diversified, the oil rent from 2016 matraeva and korolkova: identification of generalized models of development of economic systems of rental character based on the retrospective analysis of world experience international journal of energy economics and policy | vol 9 • issue 6 • 201960 is a small share in gdp 1,495%, comparable to the average world level (1,019%). for comparison, the level of the russian federation is 7.006% (wb, 2019). the results were achieved mainly due to a significant degree of openness of the economy. about 1/3 of mexican exports now account for the production of about 3,000 enterprises of makiladoras, including the world’s largest manufacturers of automobiles and electronics, which is more than 3 times higher than the volume of export earnings from the sale of crude oil (spivak et al., 2017). the basis of the mexican industry are the enterprises of free economic zones with a preferential customs regime for importing of the components from abroad and duty-free export of most of the manufactured products. mexico also has a diversified agriculture (cc rf, 2019). indonesia has diversified its economy since the 1980s until now in a similar way. as part of the economic system, sustainable agribusiness and export-oriented industries were built via preferences from the united states and japan, as well as the relocation of investment from the newly industrialized countries of east asia in the 1990s. model 3 “maintenance of short-term macroeconomic and social stability, without development.” this model predetermines the focus of the government policy on the maintenance of short-term macroeconomic stability of the system. this path is currently followed by countries such as angola, nigeria, yemen. the use of a low-efficiency rent-forming resource for these countries has resulted in underdeveloped infrastructure, relative closeness of the economy, restriction of rights and freedoms, low investment attractiveness, and management of excess revenues in foreign markets without reinvestment in the domestic economy. a set of public policy measures aimed at containing social tensions in the current political cycle. it is also interesting to emphasize that the creation of a subsidy system is not of a system-forming nature for the formation of generalized development models of the economic systems under consideration. moreover, this mechanism is often table 1: identification of generalized models of development of rental‑type economic systems public policy mechanisms cluster end centers 1 2 3 4 without clear profile with clear profile unique models or forming models without a pronounced vector of development model 3 maintain short‑term macroeconomic and social stability, without development model 2 development with external support model 1 development aimed at the creation of a strong diversified industrial complex sterilization of the economy 0.7 0.0 0.0 1.0 limiting of budget dependence on rental income by reducing of production 0.0 0.0 0.9 0.3 floating exchange rate 0.0 0.0 1.0 0.8 distribution of a limited share of rental income (investment income) on a non-competitive basis 0.2 0.0 0.0 0.3 margin alignment 0.2 0.0 0.0 0.1 long-term contracts for rent-forming resource 0.3 0.0 0.4 0.7 hedging of the price of a rent-forming resource 0.5 0.0 0.1 0.0 denomination of debt in resource units 0.2 0.8 0.0 0.0 provision of preferences for foreign companies 0.1 0.3 0.6 0.6 export diversification (including raw material exports) 0.3 0.0 0.4 0.6 development of non-primary (non-oil) economic relations 0.0 0.3 0.3 0.9 centralization of the extractive industries, and then the resource industry as a whole (nationalization in extreme cases) 0.8 1.0 0.4 0.1 diversification of the economy via government intervention 0.4 0.0 0.1 0.2 creating of a subsidies system 0.5 0.0 0.3 0.4 development of energy saving and energy efficiency policies 0.6 0.0 0.4 0.8 fiscal mechanisms, namely discriminatory taxation and regulation 0.3 0.5 0.7 0.7 import substitution policy and protection of domestic producers 0.2 0.0 0.1 0.6 domestic price controls 0.2 0.5 0.3 0.1 cartel agreements 0.1 1.0 0.0 0.0 lending at lower rates to restore the economy secured by oil contracts (supported by oil supplies) 0.1 0.8 0.0 0.0 source: compiled by the author matraeva and korolkova: identification of generalized models of development of economic systems of rental character based on the retrospective analysis of world experience international journal of energy economics and policy | vol 9 • issue 6 • 2019 61 counterproductive and hampers the development of the economic system. for example, indonesia has developed a fuel subsidy system in the 1960s (grigoriev et al., 2017b). the consequence of this measure was the irrational use of oil products. the same difficulties faced saudi arabia, venezuela, and norway at various stages of their development. 5. conclusion the conducted research allowed to draw a number of results and conclusions of theoretical and practical importance. a cluster analysis was conducted on 20 mechanisms of state policy within the framework of rental-type economic system management based on the experience of 24 countries of the world, reflecting 30 states of economies in various conditions of their operation. the generalized models of the development of rental-type economic systems with clear profiles have been revealed: • model 1 “development aimed at the creation of a strong diversified industrial complex”; • model 2 “development supported by external support”; • model 3 “maintenance of short-term macroeconomic and social stability, without development.” a profile has been determined for each model based on the selection of sets of basic, superstructural and non-involved mechanisms of public policy. the backbone mechanisms for the identified models are the following ones: • model 1: development of non-commodity relations, diversification of exports, including raw materials, long-term contracting, as well as measures for energy saving and energy efficiency; • model 2: preferences for foreign companies and a floating exchange rate; • model 3: centralization of the extractive industries, and then the resource industry as a whole (nationalization in extreme cases), as well as cartel agreements. it should also be emphasized, including for the current and future development of the russian economic system, that the creation of a subsidy system is not of a systemic nature, but only relevant to complementary (combining) mechanisms. the approach suggested in the work allows to focus the developed perspective state policy within the framework of a certain concept of its formation. it is possible to determine an effective combination of mechanisms and identify the list of required adjustments in the system of state programs of the country based on the parameters of the identified development model. further areas of research for generalized models of the development of rental-type economic systems may be related to two areas: • description and systematization of sets of conditions which various generalized models of development of rental-type economic systems are formed and/or function under; • specification of the parameters of the models taking into account the various phases of economic cycles, for example, based on the delimitation of cases of periods of high and low world oil prices. references act. (1982), organic constitutional law on mining concessions. law no. 18.097. available from: http://wwww.clc.to/ehrmrg. [last accessed on 2019 apr 09]. act. (1983), mining code. law no. 18.248. available from: http://www. table 2: description of the generalized model of development of rental‑type economic systems group of mechanisms frequency of use model 1 model 2 model 3 development aimed at the creation of a strong diversified industrial complex development with external support maintain short‑term macroeconomic and social stability, without development basic mechanisms 0.75 and more sterilization of the economy; development of non-commodity relations; energy saving and energy efficiency measures; floating exchange rate long-term contracting floating exchange rate; limiting of the dependence of the budget on rental income by production reducing centralization of extractive industries, and further resource industry in general (nationalization in extreme cases) cartel agreements add-on (if required) 0.4-0.74 fiscal mechanisms (discriminatory taxation and regulation); export diversification, including raw materials; import substitution policy; provision of preferences for foreign companies provision of preferences for foreign companies; fiscal arrangements (tax mitigation for foreign companies) demonetization of debt in terms of resources crediting at lower rates for economic recovery (formal reason) secured by raw materials (oil) contracts mechanisms that are not involved 0 monetary instruments mechanisms that can adversely affect investment climate change mechanisms for structural change in the economy countries australia, norway, usa, canada, chile (until 2009), bahrain, kazakhstan, russia mexico, indonesia, usa (alaska), uk, sweden, chile (since 2009), colombia angola, nigeria, zimbabwe, yemen source: compiled by the author matraeva and korolkova: identification of generalized models of development of economic systems of rental character based on the retrospective analysis of world experience international journal of energy economics and policy | vol 9 • issue 6 • 201962 clc.to/wsjnow. [last accessed on 2019 apr 09]. act. (1998), petroleum act 1998. available from: https://www.clc.to/ uuldqa. [last accessed on 2019 apr 12]. alaska’s constitution. (2019), alaska’s constitution: a citizen’s guide. 5th ed. anchorage: alaska legislative affairs agency. available from: http://www.clc.to/x-xuxg. [last accessed on 2019 apr 03]. apfc. (2019), a pioneering investment model, the alaska permanent fund corporation (apfc). available from: http://www.clc.to/ kf0csq. [last accessed on 2019 apr 04]. baldwin, r.e. (1956), patterns of development in newly settled regions. manchester school of social and economic studies, 24, 161-179. baykova, e.r. (2013), state regulation of rental relations. ph.d thesis. st. petersburg state university of economics. bekareva, s.v., meltenisova, e.n., guerreiro, a. (2018), arctic energy resources as an economic growth factor: evidence from alaska, usa. international journal of energy economics and policy, 8(4), 1-12. bekturganova, m., yessekina, b., satybaldin, a. (2019), conceptual framework for the formation of low-carbon development: kazakhstan’s experience. international journal of energy economics and policy, 9(1), 48-56. biryukov, e.s., biryukova, o.v. (2016), special economic zones of the gcc countries. asia and africa today, 11(712), 28-33. bobylev, y.n. (2013), world experience in extractive industry taxation, federal state budgetary educational institution of higher vocational education russian academy of national economy and state service under the president russian federation. p14-15. bp statistics. (2018), bp statistical review of world energy; 2018. available from: http://www.clc.to/g4q2xw. [last accessed on 2019 apr 05]. calder, j. (2014), administering fiscal regimes for extractive industries: a handbook. united states: international monetary fund. available from: https://www.goo.gl/czkwxh. caulfield, p. (2015), government launches new strategy to promote canadian mining abroad, canadian mining and energy. available from: http://www.clc.to/kubfnq. [last accessed on 2019 apr 06]. cc rf. (2019), mexican united states: materials of the chamber of commerce of the russian federation. available from: https://www. goo.gl/v66gpt. [last accessed on 2019 jan 20]. cio. (2017), total state budgeted revenues and expenditures for the financial years 2009-2016, central information organization (cio), bahrain open data portal. available from: http://www.data.gov.bh. [last accessed on 2019 apr 01]. cochilco. (2019), foreign investment in the mining sector general guidelines. available from: http://www.clc.to/lhb7ig. [last accessed on 2019 apr 07]. corden, m., neary, j.p. (1982), booming sector and de-industrialization in a small open economy. economic journal, 92(368), 825-848. de oliveira, r.s. (2007), business success: angola-style postcolonial politics and the rise and rise of sonangol. cambridge: cambridge university press. p595-619. decree. (2004), decree of the president of the republic of azerbaijan of september 27, 2004, no. 128. on approval of the long-term strategy for managing oil and gas revenues. available from: https:// www.goo.gl/f7neeq. [last accessed on 2019 feb 13]. decree. (2014), decree of the president of the republic of kazakhstan of august 01, 2014, no. 874. state program of industrial and innovative development of the republic of kazakhstan for 20152019. available from: http://www.clc.to/wu0wkq. [last accessed on 2019 apr 02]. dieterich, h. (2005), hugo chavez and socialism of the 21st century. caracas: pluto press. ding, n., field, b. (2005), natural resource abundance and economic growth. land economics, 81(4), 496-502. economic portal. (2019) venezuela in the modern world, economic portal. available from: https://www.goo.gl/qp689u. [last accessed on 2019 mar 20]. eiti. (2017), the eiti standard 2016. eiti, may 2017. available from: https://www.goo.gl/pempfp. eiti. (2019), open eiti data: countries. eiti. available from: http:// www.clc.to/hkg_yq. [last accessed on 2019 mar 27]. engerman, s.l., gallman, r.e., editors. (1996), the cambridge economic history of the united states. vol. 1-3. cambridge, london: cambridge university press. farfan-mares, g. (2010), non-embedded autonomy: the political economy of mexico’s rentier state, 1970-2010. ph.d thesis. the london school of economics and political science (lse). р106. available from: https://www.goo.gl/xxk1tp. foudeh, m. (2017), the long run effects of oil prices on economic growth: the case of saudi arabia. international journal of energy economics and policy, 7(6), 171-192. grigoriev, v. (2017a), nigeria’s forty lost years managing the resource curse: strategies of oil-dependent economies in the modern era, paper. carnegie endowment for international peace. p149. grigoriev, v., zotin, a., movchan, a. (2017b), fight against oil. indonesia: geopolitical luck. available from: https://www.goo.gl/ wxd6hr. grytten, o.h. (2008), the economic history of norway, eh.net encyclopedia. march 16, 2008. available from: https://www.goo. gl/acayjw. [last accessed on 2019 feb 20]. gylfason, t. (2007), the international economics of natural resources and growth. munich, cesifo working paper series no 1994. p25. available from: https://www.goo.gl/odpb4z. hertog, s. (2007), shaping the saudi state: human agency’s shifting role in rentier-state formation. international journal of middle east studies, 39(4), 539-563. hiro, d. (2008), blood of the earth: the global battle for vanishing oil resources. london: politico’s. p424. hirshman, a.o. (1977), a generalized linkage approach to development, with special reference to staples. in: hoselitz, b.f., nash, m, editors. essays on economic development and cultural change in honor of bert f hoselitz. chicago: university of chicago press. p67-98. hoekman, b., martin, w., primo, b., carlos, a. (2009), trade preference erosion: measurement and policy response. washington: world bank. p121. holyavko, s. (2014), in: kant, i., editor. swedish spatial planning model: functions, problems and solutions. bulletin of the baltic federal university. p159-168. howlett, m., netherton, a., ramesh, m. (1999), the political economy of canada. an introduction. oxford: university press. ibm. (2009), ibm spss statistics base 23 (in russ). ibm spss statistics 23 documentation. p125, 61. available from: https://www.clc.to/ nki11q. imf. (2018), out of recession and looking beyond oil. chile: imf country focus. march 2018. available from: https://www.goo.gl/ pvmfaa. innis, h.a. (1954), the cod fisheries: the history of an international economy. toronto: university of toronto press. kapitsa, l.m. (2007), resource rent for development: foreign experience. world and national economy, 2(3), 42-60. kapitsa, l.m. (2014), natural resources and socio-economic progress. vol. 4. russia: vestnik mgimo universiteta. p168-186. khlopov, o. (2015) energy security of the united states: new issues and challenges. russia: herald russian state university for the humanities. p134-144. kimelman, s. (2011), neo-industrialization is hindered by a rentier state. the economist, 8, 18-26. matraeva and korolkova: identification of generalized models of development of economic systems of rental character based on the retrospective analysis of world experience international journal of energy economics and policy | vol 9 • issue 6 • 2019 63 korolkova, n.a. (2018), identification of the generalized models of development of economic systems of rent character on the basis of the retrospective analysis of international experience. scientific review. series1. economics and law. the magazine is a peerreviewed. p67-75. krugman, p.r. (1987), the narrow moving band, the dutch disease and the competitive consequences of mrs. thatcher. journal of development economics, 27, 41-55. kudrin, a.l., sokolov, i.a. (2017), budget rules as a tool for a balanced budget policy. economic, 11, 5-32. leary, j., kerrigan, g. (2018), mining australia. mining law review. 7th ed. united kingdom: law business research ltd. available from: https://www.clc.to/pzhfcg. lovdata. (2016), lov-2005-12-21-123 act on the government pension fund. available from: http://www.clc.to/x6xn2w. mahdavy, h. (1970), the pattern and problems of economic development in rentier states: the case of iran. oxford: oxford university press. available from: https://www.goo.gl/kwixqb. manasseh, c.o., abada, f.c., ogbuabor, j.e., okoro, o.e., egele, a.e., ozuzu, k.c. (2019), oil price fluctuation, oil revenue and well-being in nigeria. international journal of energy economics and policy, 9(1), 346-355. matsuyama, k. (1992), agricultural productivity, comparative advantage, and economic growth. journal of economic theory, 58, 317-334. mehlum, h. (2005), institutions and the resource curse. economic journal, 116(508), 1-20. mihin, v. (2018), prosperous kuwait economy in a turbulent world, geopolicy. available from: http://www.clc.to/v5zwcw. [last accessed on 2019 apr 07]. mnrw-tf. (2014), sovereign asset-liability management guidance for resource-rich economies: policy papers. mnrw-tf, june 2014. available from: https://www.goo.gl/sisjkk. mnrw-tf. (2016a), assisting resource rich countries mobilise and manage their revenues: report. mnrw-tf, september 2016. available from: https://www.goo.gl/exxhxd. mnrw-tf. (2016b), program document of the managing natural resource wealth trust fund: report. mnrw-tf, november 2016. available from: https://www.goo.gl/tpyqxm. mnrw-tf. (2016c), fiscal analysis of resource industries (fari) methodology. mnrw-tf, february 2016. available from: https:// www.goo.gl/r2qa8c. mnrw-tf. (2018), annual report, fy2018. mnrw-tf, june 2018. available from: https://www.goo.gl/4hrtgk. moosmyuller, g., rebik, n.n. (2015), marketing research in spss: study guide. 2nd ed. moscow: infra-m. p98. movchan, a. (2017), managing the resource curse: strategies of oildependent economies in the modern era. carnegie endowment for international peace. united arab emirates: sovereign liberalism. p109-126. mtif. (2015), the state ownership report 2015, norway ministry of trade, industry and fisheries (mtif). available from: https://www. goo.gl/zsyq1s. mtif. (2019), the petroleum tax system 2019, norway ministry of trade, industry and fisheries (mtif). available from: https://www. goo.gl/wxelvt. [last accessed on 2019 apr 01]. neftegaz. (2017) we need urgent measures. if you do not stimulate the oil industry, colombia will not be able to fully provide itself with oil in 4 years, neftegaz.ru. june 6, 2017. available from: http:// www.clc.to/cod9sq. [last accessed on 2019 apr 12]. niko, a.h., borgne, e.l., aturupane, c., gvenetadze, k., wakemanlinn, j., danninger, s. (2014), managing oil wealth: the case of azerbaijan, imf special issues. available from: https://www.goo. gl/xgwpvy. nikolaeva, l. (2018), copper industry in chile is a platform for innovation development. latinskaia amerika, 11, 63-73. nrcan. (2015), delivery of ecoenergy efficiency program (au1509), natural resources canada (nrcan). available from: http://www. clc.to/jpmnla. [last accessed on 2019 apr 06]. polterovich, v., popov, v. (2003), accumulation of foreign exchange reserves and long term growth. new economic school. mpra paper no. 20069. available from: https://www.goo.gl/y8mcnd. polterovich, v., popov, v. (2005), appropriate economic policies for different stage of development. new economic school. mpra paper no. 20066. available from: https://www.goo.gl/eh2wvk. polterovich, v.m., vladimir, p. (2007), economic policy, the quality of institutions and mechanisms of the resource curse. moscow: publishing house of the state university higher school of economics. p98. prebisch, r. (1950), the economic development of latin america and its principal problems. economic bulletin for latin america, 7, 1-12. program document. (2016a), saudi vision 2030. available from: https:// www.goo.gl/abx5ia. program document. (2016b), national transformation program 2020. available from: https://www.goo.gl/n7pqpz. program document. (2017), program u.s. generalized system of preferences: guidebook, march 2017. available from: https:// www.goo.gl/whckia. pwc. (2015) doing business in the uae: a tax and legal guide. available from: https://www.goo.gl/rhuube. rainer, e.s. (2011), how rich countries have become rich, and why poor countries remain poor. moscow: moscow publishing house of the state university higher school of economics. reports and statistics. (2019) state oil fund of the republic of azerbaijan. available from: https://www.goo.gl/4tu8x2. [last accessed on 2019 mar 26]. robinson, j.a., torvik, r., verdier, t. (2006), political foundations of the resource curse. journal of development economics, 79, 447-468. rodrik, d. (1996), coordination failures and government policy: a model with applications to east asia and eastern europe. journal of international economics, 40, 1-22. ryazanov, v.t. (2011), economy of rental relations in modern russia. christian reading, no. 4(39). p149-176. salitsky, a.i., yurtaev, v., zhao, x. (2017), sanctions and import substitution on the example of the experience of iran and china. herald of the russian academy of sciences, 87(3), 263-271. sergeyev, v.m., sarukhanyan, s.n. (2012) white revolution: failure of modernization from above. politia, no. 3(66). p132-145. singer, h.w., meier, g.m. (1958), the terms of trade and economic development: comment. review of economics and statistics, 40, 85-90. spivak, v. (2017), resource curse: kazakhstan, mexico and indonesia. available from: https://www.goo.gl/lzavqv. strong, c.h. (2018) the oil and gas law review. 6th ed. iraq: law business research ltd. available from: http://www.clc.to/qxkljw. sweden parliament. (2019), forest care act (1979: 429), sweden parliament. available from: https://www.clc.to/l00ycw. [last accessed on 2019 apr 11]. thurbera, m.c., hults, d.r., heller, p.r.p. (2011), exporting the norwegian model: the effect of administrative design on oil sector performance. energy policy, 39(9), 5366-5378. vahab, a.s.h. (2013), structural changes and development of the oil and gas complex of yemen. socio economic phenomena and processes, 6(52), 44-48. vorobyov, m. (2006), the role of the state in overcoming the resource curse. nes master thesis. vukolov, e.a. (2013), basics of statistical analysis. workshop on matraeva and korolkova: identification of generalized models of development of economic systems of rental character based on the retrospective analysis of world experience international journal of energy economics and policy | vol 9 • issue 6 • 201964 statistical methods and operations research using statistica and excel: study guide. moscow: forum. p291. wb. (2019), oil rents (% of gdp), mexico, world, russian federation, 1970-2016, world bank open data (wb). available from: https:/ www./goo.gl/fizwts. [last accessed on 2019 jan 20]. wipo. (1962), kuwait’s constitution of 1962, world intellectual property organisation (wipo). available from: http://www.clc.to/rotsug. [last accessed on 2019 apr 07]. yergin, d. (2017), in search of energy: resource wars, new technologies and the future of energy. moscow: alpina publishing. p1110. zapata, j.v., ricciulli, c.m.c. (2018), the oil and gas law review. 6th ed. colombia: law business research ltd. available from: http:// www.clc.to/qxkljw. zhukova, n. (2006), the abundance of natural resources and economic growth: the role of institutions. nes master thesis. zotin, a. (2017a), oil plus socialism, managing the resource curse: strategies of oil-dependent economies in the modern era. venezuela: carnegie endowment for international peace. p22. zotin, a. (2017b), geopolitical luck, managing the resource curse: strategies of oil-dependent economies in the modern era. indonesia: carnegie endowment for international peace. p82. zotin, a. (2017c), the fruits of isolation, managing the resource curse: strategies of oil-dependent economies in the modern era. iran: carnegie endowment for international peace. p127-139. . international journal of energy economics and policy | vol 9 • issue 3 • 2019 87 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(3), 87-105. asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress zouheir ahmed mighri*, majid ibrahim alsaggaf department of finance and insurance, college of business, university of jeddah, saudi arabia. *email: zmighri@gmail.com received: 10 december 2018 accepted: 03 march 2019 doi: https://doi.org/10.32479/ijeep.7643 abstract this paper attempts to estimate the relationship between oil prices and financial stress using weekly data for the period december 31, 1993 to july 15, 2016. the analysis is carried out using the cointegration framework. both the linear and non-linear models for cointegration and related error correction models are estimated. the paper finds the threshold cointegration model more suitable than the linear cointegration models. it finds evidence of asymmetry in the adjustment process to equilibrium. it also finds that regimes with negative (below the threshold) changes of deviations adjust much faster than regimes with positive (above the threshold) changes of deviations, especially during a crisis period. also, bi-direction causality is reported between the two variables. keywords: threshold cointegration, asymmetric adjustment, asymmetric error correction, financial stress, oil prices, financial crisis jel classifications: c22, c32, c58, g11 1. introduction in the literature, it is well recognized that oil price shocks have detrimental effect on economic activity in developed and developing countries (cunado and de gracia, 2003; cunado and de gracia, 2005; hamilton, 2011), especially for oil-importers. although the effect of oil shocks on the macro-economy seems to have weakened through time, kilian (2008) argued that this is partly due to increased demand for industrial output, which offsets the negative impact of an increase in oil price. besides, rafiq et al. (2009) argued that the negative impact of an increase in oil price is usually found to be higher than the positive impact of a fall in oil prices. in addition, balke et al. (2002) claimed that monetary policy alone cannot account for this asymmetry. transaction costs and financial stress are among the factors that lead to the asymmetric effect. the financial stress index literature is a rapidly developing one. existing studies either focus on only constructing a financial stress index for a single country (illing and liu, 2006; hakkio and keeton, 2009; morales and estrada, 2010; holló, 2012; nazlioglu et al., 2015) or both on constructing an index for numerous countries and evaluating the link between financial stress and economic activity to examine how well financial stress index identifies known periods of financial distress (slingenberg and de haan, 2011; cardarelli et al., 2011; holló et al., 2012; cevik et al., 2013; mallick and sousa, 2013; chau and deesomsak, 2014; islami and kurz-kim, 2014). for one country, financial stress indices combine more indicators into one statistic than multi-country stress indices (kliesen et al., 2012; vermeulen et al., 2015). most studies use market data, but some of them use both mixed market and balance sheet data (holló et al., 2012), while others consider only balance sheet data (morales and estrada, 2010). different ways are used by authors in order to combine indicators into an aggregate financial stress index. while most studies take the average of standardized variables, others use principal components analysis (illing and liu, 2006; hakkio and keeton, 2009). more recently, authors used portfolio theory based aggregation schemes this journal is licensed under a creative commons attribution 4.0 international license mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 201988 that take into account the correlation structure of stress indicators in order to quantify the level of systemic stress (holló et al., 2012). the financial stress index is a relatively new concept, and the literature on impacts of oil prices on macroeconomic and financial variables is a lot broader than the financial stress index literature. the work developed by chen et al. (2014) is probably the first study in the literature that examines the link between financial stress and oil prices. in their article, chen et al. (2014) extended the killian (2009) framework to identify an exogenous shock arising from changes in financial market conditions and examine the consequent macroeconomic impacts of oil price changes. using the kansas city financial stress index, global oil production, global real economic activity, and real oil prices, they found that financial stress index shocks trigger a significant negative response in real oil prices. furthermore, a second study by nazlioglu et al. (2015) examined whether there is a volatility transmission between oil prices and financial stress by means of the volatility spillover test. they used west texas intermediate (wti) crude oil prices and cleveland financial stress index (cfsi) for the period 1991-2014 and divide the sample into pre-crisis, in-crisis, and post-crisis periods due to the downward trend in oil price in 2008. according to these authors, the dynamic relationship between oil prices and financial stress can exist through two channels: their impact on economic activity and on investor behavior. their empirical results indicate that oil prices and financial stress index are dominated by long-run volatility. they also argued that a rise in oil prices depresses economic activity, may put pressure on credit markets, and negatively affect stock markets and the banking system. besides, they claimed that, in times of high financial stress, economic activity slows down, leading to low energy demand and declining oil prices. in addition, crude oil markets are seen by investors as alternative investment areas to financial markets. with respect to oil price shocks, investors adjust their portfolios, which will have repercussions on financial asset prices. on the other hand, investors will be obliged to change their portfolios due to increased financial stress, which will have an effect on oil markets. furthermore, nazlioglu et al. (2015) claimed that financial stress influences economic activity through the bank lending channel via decreasing the amount of available credits and through financial leverage via changes in credit worthiness of borrowing businesses. even though the relationship between financial stress and real economic activity or growth is well-studied (demirguc-kunt and levine, 2001; levine, 2005; illing and liu, 2006), the inter-temporal link between oil price and financial stress index is not yet well explored. this study examines whether there is asymmetric relationship between world oil prices and financial stress index. considering the leading role of the u.s. financial system all over the world, the financial stress index for u.s. is taken as representative of the global financial stress. to the extent of our knowledge, this study is the first to explicitly examine asymmetric threshold cointegration between financial stress and world oil markets by employing the methodology developed by enders and siklos (2001). most of studies adopt a linear cointegration framework (engle and granger, 1987), which assumes a linear long-run relationship among economic variables and a linear adjustment towards the equilibrium. however, the linear structure has been challenged as many economic variables display a nonlinear or asymmetric effect in their long-run relationship and short-term adjustment process (granger and lee, 1989; enders and granger, 1998). for cross-listings between crude oil prices and financial stress, the rationale of nonlinear modeling is more straightforward. given the intricacies of the trading environment between these two markets, such as transaction costs, short-sell restrictions and exchange rate risks, arbitragers may only appear when price deviations from the equilibrium are large enough to cover their transaction costs and risk premia, implying an asymmetric adjustment process. there have been some extensions of linear cointegration models to capture this asymmetry. for instance, balke and fomby (1997) generalize the cointegration analysis to allow for a threshold effect in the adjustment process. enders and granger (1998) and enders and siklos (2001) expand the engle-granger two-step cointegration test by allowing for the possibility of asymmetric adjustment processes. in this study, we employ the enders-siklos threshold cointegration test to explore the long run asymmetric equilibrium relationship between oil prices and financial stress. the data set includes weekly observations from december 31, 1993 to july 15, 2016, and is divided into three sub-periods due to the downward trend in oil prices in 2008: the pre-oil crisis, the oil crisis, and the post oil crisis (pre-crisis, in-crisis, and post-crisis hereafter) periods. the remainder of the article is organized as follows. section 2 describes the data. section 3 outlines the econometric methodology. section 4 presents the descriptive statistics and time series properties of data and discusses the empirical results. section 5 is devoted to concluding remarks. 2. data sources and description in this study, we use two variables, namely a measure of financial stress and oil prices at weekly frequency. the decision to carry out the analysis at weekly frequency is to better account for the dynamic relationships between oil and financial markets during the 2007-2009 global financial crisis. for world oil prices, we use the wti spot crude oil prices, obtained from the fred database of the st. louis federal reserve bank1. given that our oil prices are weekly, we employ the st. louis fed’s financial stress index (stlfsi)2 provided by the federal reserve bank of st. louis. while there are other financial stress index measures for the us, like the chicago fed index, the kansas city fed index (kcfsi), and the cfsi3, none of these indexes are available at weekly frequency. 1 https://fred.stlouisfed.org. 2 the st. louis fed’s financial stress index (stlfsi) is based on 18 weekly data series. the actual index is constructed using a principal components analysis, which is a statistical method of extracting factors responsible for the comovements of the 18 variable groups. it is assumed that financial stress is the primary factor influencing this comovement, and by extracting this factor (the first principal component) financial stress index can be created. 3 note that the cfsi, as a measure of stress in financial markets, has been unavailable since may 9, 2016, due to the discovery of errors that overestimated stress in the real estate and securitization markets. https://fred.stlouisfed.org mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 2019 89 the stlfsi measures the degree of financial stress in the markets. this index is more comprehensive and overcomes the potential criticisms of focusing solely on one indicator. in combining several indicators, it has a broad coverage as it covers three important areas: (i) interest rates (such as federal fund rate; 2 year, 10 year, and 30 year treasury; and corporate bond yield); (ii) yield curve (such as 10 year minus 3-month treasury; corporate bond minus 10 year treasury; 3 month ted spread); and (iii) other counterparty risk indicators (such as j.p. morgan emerging markets bond index, chicago board options exchange market volatility index, merrill lynch bond market volatility index). each of these variables captures some aspect of financial stress. the average value of the index, which begins in late 1993, is designed to be zero. thus, zero is viewed as representing normal financial market conditions. values below zero suggest below-average financial market stress, while values above zero suggest above-average financial market stress. note that an increase in financial stress will be associated with higher funding costs and greater economic uncertainty, resulting in declining real economic activity. moreover, an increased financial stress will render financial investors more risk averse, which will discourage investment in asset markets, resulting in falling asset prices, including oil prices (hakkio and keeton, 2009; davig and hakkio, 2010). the data set includes weekly observations from december 31, 1993 to july 15, 2016 and it is divided into three sub-periods: the pre-crisis period from december 31, 1993 to july 27, 2007, the crisis period from august 3, 2007 to march 27, 2009, and the post-crisis period from april 3, 2009 to july 15, 2016. even though the wti starts earlier, the starting date of the sample is constrained by availability of stlfsi, and all available data since the start of this study is included. the recent global financial crisis has some unique features, such as the length, breadth, and crisis sources. numerous studies use major economic and financial events in order to determine the crisis length and source ad hoc (baur, 2012; dimitriou and kenourgios, 2013; dimitriou et al., 2013; mighri and mansouri, 2014). besides, the choice of the sub-periods is based on the downward trend in oil prices within the crisis date (mollick and assefa, 2013; turhan et al., 2013). these studies suggested that when oil prices are used, separate analyses are necessary before, at and after the crisis period. in this study, the length of the global financial crisis and its phases are specified following an economic approach. we define a relatively long crisis period based on all major international financial and economic news events representing the global financial crisis. we use the official timelines provided by federal reserve board of st. louis (2009) and the bis (2009), among others, in order to choose the crisis period. according to these studies, the timeline of the global financial crisis is separated in four phases. phase 1 described as “initial financial turmoil spans from 1 august 2007 to 15 september 2008. phase 2 is defined as “sharp financial market deterioration” and spans from 16 september 2008 to 31 december 2008. phase 3 described as “macroeconomic deterioration” spans from january 1, 2009 to march 31, 2009. phase 4 described as a phase of “stabilization and tentative signs of recovery” (post-crisis period), including a financial market rally, spans from 1 april 2009 to the end of the sample period. for that reason, the crisis can be defined from august 2007 to march 2009 covering the first three phases. in the light of the literature, we therefore question the impact of the recent global financial crisis on the financial stress and oil price link and thus the data is divided into three sub-periods. 3. econometric methodology cointegration has been widely used to investigate relationship among price variables. the two major cointegration methods are johansen and engle-granger two-step approaches. both of them assume symmetric relationship between variables. in recent years, threshold cointegration has been increasingly used in price transmission studies. balke and fomby (1997) proposed a two-step approach for examining threshold cointegration on the basis of the approach developed by engle and granger (1987). enders and granger (1998) and enders and siklos (2001) further generalize the standard dickey-fuller test by allowing for the possibility of asymmetric movements in time-series data. this makes it possible to test for cointegration without maintaining the assumption of a symmetric adjustment to a long-term equilibrium. thereafter, the method has been widely applied to analyze asymmetric price transmission. in this study, linear cointegration, threshold cointegration, and asymmetric error correction models are employed to examine the oil price and financial stress dynamics. these models will be able to assess asymmetric price dynamics in both the long term and short term. 3.1. linear cointegration analysis in this study, the focus variables are weekly as well as monthly price series of crude oil and financial stress in the united states. as usual, their stochastic properties of non-stationarity and order of integration can be evaluated using the augmented dickey-fuller (adf) (dickey and fuller, 1979), and phillips-perron (phillips and perron, 1988) unit root tests. if both the price series appear to have a unit root, then it is appropriate to conduct cointegration analysis to assess their interaction. econometric literature proposes different methodological alternatives to empirically analyze the long-run relationships and dynamics interactions between two or more time-series variables. two cointegration methods widely used are the full information maximum likelihood-based johansen approach and engle-granger two-step approach (engle and granger, 1987; enders, 2004). the johansen approach is a multivariate generalization of the dickey-fuller test (johansen, 1988; johansen and juselius, 1990). it concentrates on the relationship between the rank of a matrix and its characteristic roots in a vector autoregression. the johansen approach starts with a vector autoregressive model and then reformulates it into a vector error correction model as follows: mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 201990 vt = π1vt−1+...+πkvt−k+εt (1) ∆ γ ∆ πv k v vt i t i t k ti = − + + =∑ − −1 1  (2) where vt is a vector of the price at date (week) t for crude oil (yt) and financial stress (xt), k is the number of lags, and εt is the error term. the relationship among the coefficients for the two equations is given as: 1 p i jj i  = γ = − +∑ (3) 1 k h h i  = π = − +∑ (4) where i is an identity matrix. two types of tests, i.e., the trace and maximum eigenvalue statistics, can be used to detect the number of cointegrating vectors, r, among the variables in vt. the engle-granger two-stage approach focuses on the time series property of the residuals from the long-term equilibrium relationship (engle and granger, 1987). the first step of the analysis consists in determining a break point into the relationship that defines the long run relationship between the crude oil prices and financial stress index: yt = ξ0+ξ1xt+εt (5) ∆ ∆ε ρε ϕ εt t i p i t i tz= + +− = −∑1 1 (6) where yt and xt denote the oil prices and financial stress, respectively, ξ0, ξ1, ρ and φi are parameters to be estimated, εt is the disturbance term, which should be stationary if any longrun relationship exists between the two integrated price series, indicates the first difference, ˆt is the estimated residuals, ρ measures the speed of convergence of the system, zt is a white noise disturbance term, and p denotes the number of lags. the parameter ξ1 indicates the long-run elasticity of price transmission and gives the magnitude of adjustment of the crude oil price to variations of the financial stress index. if ξ1<1, changes in the financial stress index are not fully passed onto the crude oil price. in the first stage of estimating the long-term relationship among the variables yt and xt, the financial stress is chosen to be placed on the right side and assumed to be the driving force. in the second stage, the estimated residuals ˆ t are used to conduct a unit root test (engle and granger, 1987). the number of lags is chosen so there is no serial correlation in the regression residuals. it can be selected using the akaike information criterion (aic), bayesian information criterion (bic), or ljung-box q test. if the null hypothesis of ρ=0 is rejected, then the residual series from the long-term equilibrium is stationary and the focal variables of yt and xt are cointegrated. rejecting the null hypothesis of no cointegration ρ=0 in favor of the alternative hypothesis −2<ρ<0 implies that the {εt} sequence is stationary with mean zero. any deviations from the long-run value of the disturbance term t are ultimately eliminated. convergence is assured if −2<ρ<0. as such, eq. (5) is an attractor such that εt can be written as an error correction model. the change in εt equals ρ multiplied by εt−1 regardless of whether εt−1≥0 or εt−1<0. 3.2. cointegration analysis with structural breaks residual-based cointegration tests (engle and granger, 1987) assume that cointegrating vectors are constant over time. however, if there is a regime shift in the series, there will be a shift in the cointegrating vector as well. in such circumstances, these standard tests could lead to incorrect inferences about the longrun relationship of the price series. furthermore, phillips (1986) shows that if a structural break exists in the data, but is omitted from the cointegration relationship, this could lead to spurious rejections when the null of no cointegration is wrongly rejected. for the engle and granger (1987) test, such spurious rejections tend to occur for breaks that are located either too early in the sample or when the magnitude of the break increases. thus, the power of the engle and granger (1987) test to find cointegration is severely affected by the presence of breaks in the level or the trend function in the cointegration relationship. gregory and hansen (1996a; 1996b) addressed this issue and proposed a residual-based cointegration test that allows for the possibility of regime shifts either in the intercept or the entire vector of coefficients. gregory and hansen (1996a; 1996b) analyzed four models and then tested the null hypothesis of no cointegration. model 1 (see eq.5) is the standard cointegration model where no changes in the intercept or a trend function are allowed under the null hypothesis. the other three models include shifts in either the intercept (level shift model c) or trend (level shift model with trend c/t) or shifts in the intercept and slope vector of coefficients (regime shift model c/s). model c/s is unique in the sense it allows the long-run equilibrium relationship to rotate as well as shift in parallel fashion. the break point in any model is determined endogenously within the data series. level shift model c can be expressed as follows: y xt tt t t= + + +ξ ξ φ ξ0 0 10 ’ ’’  (7) in this parameterization, 0 ’ represents the intercept before the shift, and 0 ’’ denotes the change in the intercept at the time of the shift. level shift model with trend c/t can be represented by: y t xt tt t t= + + + +ξ ξ φ β ξ υ0 0 10 ’ ’’ (8) regime shift model c/s is given as: y x xt tt t t tt t= + + + +ξ ξ φ ξ ξ φ κ0 0 1 10 0 ’ ’’ ’ ’’ (9) in this case, 0 ’ and 0 ’’ are as in the level shift model c. 1 ’ denotes the cointegrating slope coefficients before the regime shift, and 1 ’’ denotes the change in the slope coefficients. a time trend into the regime shift model (c/s/t) could be also introduced: mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 2019 91 y t x xt tt t t tt t= + + + + +ξ ξ φ β ξ ξ φ η0 0 1 10 0 ’ ’’ ’ ’’ (10) in these four models above, the structural break is modeled by the introduction of a dummy variable tt0 , which takes values (0,1) depending on the nature of the structural break. φ τt if t t if t t = > ≤    1 0 0 0 (11) where t0 is the unknown parameter denoting the timing of the change point. in all four models postulated, the null hypothesis of no cointegration can be tested by examining whether the residuals of the ordinary least-squares (ols) regression applied to eqs. (5) and (7)-(10), respectively are stationary processes. the procedure for computing the test statistic for each possible regime shift t0 ∈t involves four steps. in essence, it involves the search for the smallest value of either the modified phillips-perron (pp) ( z * and zt * ) or adf(adf*) test statistic across all possible break points: z z t t t   * inf ( )= ∈0 0 (12) z z tt t t t * inf ( )= ∈0 0 (13) adf adf t t t * inf ( )= ∈0 0 (14) 3.3. threshold cointegration analysis the implicit assumption of linear and symmetric adjustment (engle and granger, 1987) is problematic. enders and siklos (2001) proposed a two-regime threshold cointegration approach to entail asymmetric adjustment in cointegration analysis. they argued that the engle-granger cointegration test is likely to lead to misspecification errors when the adjustment of the error correction term is asymmetric. they remedy this error by expanding the engle-granger two-step cointegration test to incorporate an asymmetric error correction term. in the next step, we determine whether or not the disturbance term εt is stationary by considering an asymmetric test methodology in the form of threshold autoregressive (tar) cointegration model as proposed by enders and granger (1998) and enders and siklos (2001). the alternative model modifies eq. (6) such that: ∆εt=it ρ1(εt−1−τ)+(1−it) ρ2 (εt-1−τ)+μt (15) where ρ1, ρ2 are coefficients, τ is the value of the threshold, μt is a white-noise disturbance and it is the heaviside indicator such that. i if ift t t = ≥ <    − − 1 0 1 1 ε τ ε τ (16) in order for {εt} to be stationary, a necessary condition is −2<(ρ1,ρ2)<0. if the variance of μt is sufficiently large, it is also possible for one value of ρj to be in the range of −2 and 0 and for the other value to equal zero. although there is no convergence in the regime with the unit-root (i.e., the regime in which ρj=0), large realizations of μt will switch the system into the convergent regime. in both cases, under the null assumption of no cointegration between the variables, the -statistic for the null hypothesis ρ1=ρ2=0 has a nonstandard distribution. rejecting this assumption means that eq. (15) is an attractor such that the equilibrium value of the {εt} is τ. the adjustment process is (ρ1εt−1−τ) if the lagged value of εt is above its long-run equilibrium value, while if the lagged value of εt is below its long-run equilibrium value, the adjustment is ρ2(εt−1−τ). if −1<|ρ1|<|ρ2|<0, negative discrepancies will be more persistent than positive discrepancies. moreover, tong (1983) showed that the ols estimates of ρ1 and ρ2 have an asymptotic multivariate normal distribution if the sequence {εt} is stationary. therefore, if the null assumption ρ1=ρ2=0 is rejected, it is possible to test for symmetric adjustment (i.e., ρ1=ρ2) using a standard f-test. rejecting both the null assumptions ρ1=ρ2=0 and ρ1=ρ2 indicates the existence of threshold cointegration and asymmetric adjustment. since the exact nature of the nonlinearity may not be known, enders and siklos (2001) consider another kind of asymmetric cointegration test methodology that allows the adjustment to be contingent on the change in εt−1 (i.e., ∆εt−1) instead of the level of εt−1. in this case, the heaviside indicator of eq. (16) becomes. i if ift t t = ≥ <    − − 1 0 1 1 ∆ ∆ ε τ ε τ (17) this specification is especially relevant when the adjustment is such that the series exhibits more “momentum” in one direction than in the other (thompson, 2006; kuo and enders, 2004; enders and siklos, 2001; enders and granger, 1998). that is, the speed of adjustment depends on whether εt is increasing (i.e., widening) or decreasing (i.e., narrowing). according to thompson (2006), among others, if |ρ1|<|ρ2|, then increase in εt tend to persist, whereas decreases revert back to the threshold quickly. the resulting model is called momentum-threshold autoregressive (m-tar) cointegration model. the tar model captures asymmetrically deep movements if, for instance, positive deviations are more prolonged than negative deviations. the m-tar model allows the autoregressive decay to depend on ∆εt−1. as such, the m-tar specification can capture asymmetrically “sharp” movements in {εt} sequence (caner and hansen, 2001). in both the tar and m-tar cointegration processes, the null assumption of ρ1=ρ2=0 could be tested, while the null hypothesis of symmetric adjustment may be tested by the restriction, ρ1=ρ2. generally, there is no presumption to whether to use tar or m-tar specifications. thus, it is recommended to select the adjustment mechanism by a model selection criterion such as aic or bic. furthermore, if the errors in eq. (15) are serially correlated, it is possible to use the augmented form of the test: ∆ ∆ε ρ ε τ ρ ε τ ϕ εt t t t t i p i t i ti i v= −( )+ −( ) −( )+ +− − = −∑1 1 2 1 11 (18) to use the tests, we first regress εt on a constant and call the residuals , { ˆ }t which are the estimates of (εt−1−τ). in a second step, we set the indicator according to eq. (16) or eq. (17) and estimate the following regression: mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 201992 ( ) ( ) ( )1 1 2 1 1ˆ ˆ ˆ1 ˆ p t t t t t i t i ti i i v        − − −=∆ = − + − − + ∆ +∑ (19) the number of lags p is specified to account for serially correlated residuals and it can be selected using aic, bic, or ljung-box q test. in several applications, there is no reason to expect the threshold to correspond with the attractor (i.e., τ=0). in such circumstances, it is necessary to estimate the value of along with the values of ρ1 and ρ2. a consistent estimate of the threshold t can be obtained by adopting the methodology of chan (1993). a super consistent estimate of the threshold value can be attained with several steps. first, the process involves sorting in ascending order the threshold variable, i.e., 1ˆt − for the tar model or the 1 ˆ t −∆ for the m-tar model. second, the potential threshold values are determined. if the threshold value is to be meaningful, the threshold variable must actually cross the threshold value (enders, 2004). thus, the threshold value τ should lie between the maximum and minimum values of the threshold variable. in practice, the highest and lowest 15% of the values were removed from the search to ensure an adequate number of observations on each side. the middle 70% values of the sorted threshold variable are used as potential threshold values. third, the tar or m-tar model is estimated with each potential threshold value. the sum of squared errors (sse) for each trial can be calculated and the relationship between the sse and the threshold value can be examined. finally, the threshold value yielding the lowest sse is deemed to be the consistent estimate of the threshold. given these considerations, a total of four models are used in this study. they are tareq. (16) with τ=0; consistent tar-eq. (16) with τ estimated; mtareq. (17) with τ=0; and consistent mtareq. (17) with τ estimated. since there is generally no presumption on which specification is used, it is recommended to choose the appropriate adjustment mechanism via model selection criteria of aic and bic (enders and siklos, 2001). a model with the lowest aic and bic will be used for further analysis. insights into the asymmetric adjustments in the context of a long term cointegration relationship can be obtained with two tests. first, an f-test is used to examine the null assumption of no cointegration (h0:ρ1=ρ2=0) 4 against the alternative of cointegration with either tar or m-tar threshold adjustment. let φ and φ* denote the f-statistics for testing the null assumption of ρ1=ρ2=0 under the tar and the m-tar specifications, respectively. the distributions of φ and φ* are determined by the form of the attractor. the second one is a standard f-test to assess the null assumption of symmetric adjustment in the long-term equilibrium (h0: ρ1=ρ2). rejection of the null hypothesis indicates the existence of an asymmetric adjustment process. 4 the null hypothesis of non stationarity is rejected if the sample value of f-test statistic exceeds the enders-granger critical value. the critical values of the -statistics for the null hypothesis ρ1=ρ2=0 using the tar and m-tar specifications are reported in the first and second panels of table 1 in kuo and enders (2004). 3.4. asymmetric error correction model with threshold cointegration according to engle and granger (1987), if all considered variables are cointegrated, then there will be a corresponding error correction model (ecm). the finding could be extended to threshold cointegration. this means that, if yt and xt are threshold cointegrated, then the ecm could be constructed as follows: ∆ ∆ ∆ x z z x y t x x t x t xj t j xj t j x t j p j p= + + + + + + − + − − − − − = =∑ ∑θ δ δ α β ν 1 1 1 1 , (20) and ∆ ∆ ∆ y z z x y t y y t y t j p yj t j yj t j y t j p= + + + + + + − + − − − = − − ∑ ∑ =θ δ δ α β ν 1 1 1 1 , (21) where 1 1ˆt t tz i  + − −= and 1 1ˆ(1 ) t t tz i  − − −= − ; the parameters δ+ and δ− represent the adjustment speed of the coefficients of different sized deviations; θ is a constant; αj and βj are the coefficients of the lagged difference terms; p is the number of lags and νt is a white noise. the subscripts x and y are used in order to differentiate between the coefficients of variables xt and yt, respectively. t denotes time, and j represents lags. the equilibrium correction specification (ecm) of engle and granger (1987) assumes that the adjustment process due to disequilibrium among the variables is symmetric. in order to incorporate asymmetries, two extensions on the ecm model have been made. error correction terms and first differences on the variables are decomposed into positive and negative values, as proposed by granger and lee (1989). the second extension adds the threshold cointegration mechanism to the granger and lee (1989) approach. the resulting asymmetric error correction model with threshold cointegration has the following form: ∆ ∆ ∆ x z z x x t x x t x t xj t j xj t j j j j p p= + + + + + + − + − − − + − + − − − = =∑ ∑θ δ δ α α 1 1 1 1 == + − + − − − =∑ ∑+ +1 1 p p xj t j xj t j x tj y yβ β ν∆ ∆ , (22) and ∆ ∆ ∆ y z z x x t y y t y t yj t j yj t j j j j p p= + + + + + + − + − − − + − + − − − = =∑ ∑θ δ δ α α 1 1 1 1 == =∑ ∑ + − + − − −+ + 1 1 p p jyj t j yj t j y t y yβ β ν∆ ∆ , (23) the heaviside indicator function is constructed from eq. (16) or eq. (18). the superscripts “+” and “−” indicate that the variables are split into positive and negative components. the first differences are defined as follows: mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 2019 93 ∆ ∆x x x x x x x xt j t j t j t j t j t j t j t j − + − − − − − − − − − − = { } = − ≥ <  max , , , 0 0 1 1 1   ∆ ∆x x x x x x x xt j t j t j t j t j t j t j t j − − − − − − − − − − − − = { } = − < ≥  min , , , 0 0 1 1 1   ∆ ∆y y y y y y y yt j t j t j t j t j t j t j t j − + − − − − − − − − − − = { } = − ≥ <  max , , , 0 0 1 1 1   ∆ ∆y y y y y y y yt j t j t j t j t j t j t j t j − − − − − − − − − − − − = { } = − < ≥  min , , , 0 0 1 1 1   the lag p is specified to account serially correlated residuals and is selected using aic statistic and ljung-box q test. the above specifications are able to distinguish between long-run and shortrun adjustments of xt and yt. the long-run adjustment is determined by the parameters δ+ and δ−, whereas, the short-run adjustment is governed by the parameters α α βj j j + − +, , and  j − for j=1,…, p. if  x x + −≠ and  y y + −≠ , then both xt and yt exhibit asymmetry in long-run adjustment. if either  xj xj + −≠ or. or both, xt displays asymmetry in short-run adjustment. besides, if either  yj yj + ≠ − or  yj yj + −≠ or both, yt displays asymmetry in short-run adjustment. in this paper, four types of single or joint null hypotheses and f-tests are examined (meyer and von cramon-taubadel, 2004; frey and manera, 2007; sun, 2011; chen and zhu, 2015; mighri and mansouri, 2016). the first type is the granger causality test to examine the lead-lag relationship between xt and yt. the null hypothesis that xt does not lead yt can be tested by restricting h yj yj01 0:  + −= = for all lags j simultaneously and then employing an f-test. similarly, the null hypothesis that yt does not lead xt can be tested by restricting h xj xj02 0:   + −= = for all lags j simultaneously and then employing an f-test. in our empirical analysis, we expect to see one of the following: if one variable granger-causes the other, then the former variable leads the latter; if there is no causal relationship between the two variables, then there is no obvious connection between the two variables; or, if the two variables mutually granger-cause each other, then the two variables are closely linked to each other. the second type of hypothesis is concerned with the distributed lag asymmetric effect o n i t s o w n v a r i a b l e ; t h a t i s , h xj xj03 0:  + −= = a n d h yj yj04 0:   + −= = . the third type of the null hypothesis is the cumulative symmetric effect which can be expressed as h j p xj j p xj05 1 1 : = + = −∑ ∑=  f o r x t a n d h j p yj j p yj06 1 1 : = + = −∑ ∑=  , for yt. finally, the equilibrium adjustment path asymmetry can be examined with the null hypotheses of h07 :   + −= for each equation estimated (i.e.,  x x + −= for xt and  y y + −= for yt) to examine whether it is possible to get back to equilibrium after a shock, and if it is the case, how long it will take. 4. empirical results 4.1. descriptive statistics and unit root test figure 1 displays the time series plots for the oil prices and st. louis fed financial stress index (stlfsi). three observations can be made (i) oil prices and stlfsi have an evident comovement in general, which reveals a high possibility of cointegration between these two series. (ii) although oil prices and stlfsi move together most of the time during our sample period, they also display divergent movement indicating possible nonlinear cointegration. (iii) the two series tend to move more closely during and after the crisis relative to the pre-crisis period. it seems that the link between stlfsi and world oil prices have changed through time, which motivated us to concentrate on the sub-sample analysis. table 1 reports summary statistics of oil prices and stlfsi for different samples in order to examine to what extent the descriptive statistics of the oil prices and the stlfsi differ across these sub-periods. the highest mean and standard deviation are observed for oil prices during all the sub-periods. as a simple measurement for volatility, the standard deviations of oil prices are higher in the crisis period compared to those of the precrisis and post-crisis periods. skewness is a simple measure of asymmetry and kurtosis is a measurement for peaked or flatted distribution relative to a gaussian distribution. we observe that oil price has negative skewness and is left tailed in both the crisis and post-crisis periods; although it has positive skewness and hence right tailed in the pre-crisis period. this stylized fact is figure 1: dynamics of weekly oil prices and st. louis fed financial stress index mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 201994 also supported by the jarque-bera test statistic which rejects the null assumption of normality. the stlfsi has its positive and the greatest mean in the in-crisis period, which means that there is a significant or higher stress. it has positive mean in the pre-crisis and negative mean in the postcrisis. as illustrated in figure 1, these features provide that the pre-crisis period is characterized as a normal stress period while moderate stress levels are observed in the post-crisis period. the stlfsi has smallest standard deviation during the crisis-period compared to the pre-and post-crisis periods. the skewness and kurtosis measures indicate deviation from normality. skewness shows that stlfsi is right tailed in the crisis and post-crisis periods; it has left tail in the pre-crisis period. kurtosis indicates that financial stress is less peaked during the pre-crisis and in-crisis periods compared to the post-crisis period. moreover, the jarquebera statistic shows non-normal behavior of financial stress. the different data characteristics apparent in the summary statistics for different considered periods lead to the question of whether the correlations between oil prices and stlfsi vary across these subperiods as well. at first glance, correlation appears stronger in the pre-crisis and in-crisis periods than that in the post-crisis period. however, the positive correlation in the in-crisis period turns back to negative following the global financial crisis. this means that as financial stress goes from significant level to moderate level, oil prices go up. this reversed relationship becomes more apparent after 2008 according to figure 1. the non-stationarity properties of the oil prices and financial stress indices are investigated by applying the adf (dickey and fuller, 1979), pp (phillips and perron, 1988), and kwiatkowski-phillipsschmidt-shin (kpss) (kwiatkowski et al., 1992) unit root tests. for both adf and pp tests, we consider three different cases: the case without constant and trend, the case with constant, as well as the case with both constant and trend. the results for the adf and pp unit root tests are summarized in both tables 2 and 3. these tests indicate that oil prices are characterized by a unit root process, implying that the shocks are permanent and not corrected over time. for the stlfsi, even though both the unit root tests support evidence on stationary process in the post-crisis period, this mean reverting process is not supported in the full-sample, pre-crisis and in-crisis periods. in addition, the kpss test also reveals that both wti and stlfsi series fail to reject the alternative assumption of a unit root at the 1% level of significance or better. conversely, these series accept the null hypothesis of a stationary at 1% level of significance or better when tested for a unit root in first differences. therefore, we conclude that both oil prices and stlfsi are integrated processes of order one, or unit root processes. 4.2. results of the linear cointegration analysis to conduct the linear cointegration analyses, we use both the johansen and engle-granger approach. the application of the johansen approach requires the determination of a lag length for the model, which is based on the lowest aic and bic. without prior information, three model specifications with trend, constant, or no intercept are entailed (table 4). for instance, with only a trend included, the johansen maximum eigenvalue statistic (λmax) is 21.152 for the null hypothesis of no cointegrating vector between the prices of wti and stlfsi. these are significant at the 5% level, indicating that the null hypothesis is rejected. however, for the null hypothesis of one cointegrating vector, the λmax tatistic decreases to 5.472, which is not statistically significant at all. therefore, the maximum eigenvalue statistic conclude that there is one cointegrating vector. similarly, the johansen trace statistic (λtrace) also supports the conclusion that wti and stlfsi are cointegrated. the engle-granger cointegration test is implemented through two steps. in the first step, the long-term relationship between the price series is estimated, as specified in eq. (17). the estimates for the coefficients on the financial stress index (i.e., ξ1) are highly statistically significant in all cases. in the second step, the residual series is used to conduct a unit root test with the specification in eq. (18). as reported in table 5, the sufficiently optimal lag, used for addressing the problem of serial correlation, is chosen based on the aic and ljung-box q statistics. besides, the statistics from the unit root test (i.e., ρ) are statistically significant. the results of the engle-granger cointegration test provide evidence for the alternative hypothesis of linear cointegration in all cases except for the post crisis period. 4.3. results of the cointegration analysis in the presence of structural breaks using the gregory and hansen (1996a; 1996b) tests, we tested for a bivariate cointegration relationship between oil prices and table 1: descriptive statistics variable whole sample pre-crisis in-crisis post-crisis wti stlfsi wti stlfsi wti stlfsi wti stlfsi mean 51.139 0.000 31.351 0.215 87.666 1.798 79.623 −0.811 median 42.520 0.091 26.340 0.418 91.180 1.099 85.660 −0.934 maximum 142.520 5.701 75.630 1.470 142.520 5.701 112.300 2.640 minimum 11.000 −1.657 11.000 −0.906 32.980 −0.077 28.140 −1.657 sd 31.306 1.000 16.670 0.570 29.969 1.483 21.507 0.712 skewness 0.557 1.299 1.121 −0.479 −0.178 1.039 −0.671 2.124 kurtosis 2.040 7.514 3.056 1.980 2.059 2.802 2.265 9.015 jarque−bera 106.004*** (0.000) 1330.457*** (0.000) 148.664*** (0.000) 57.889*** (0.000) 3.670 (0.160) 15.800*** (0.000) 37.155*** (0.000) 860.726*** (0.000) observations 1177 1177 709 709 87 87 381 381 correlation −0.417 − −0.758 − −0.619 − −0.309 − ***, **, and *indicate respectively statistical significance at the 1%, 5%, and 10% levels. wti: west texas intermediate, stlfsi: st. louis fed’s financial stress index mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 2019 95 financial stress in the us markets. results of the residual-based tests for cointegration in models with regime shifts are reported in table 6. in almost the cases, the hypothesis of cointegration with a structural break is not supported at better than 1% significance level. taking into account the structural break in the cointegrating relationship between oil prices and financial stress, the adjustment of the oil price to changes in the financial stress in the long-run is explored allowing for the possibility of asymmetries in the error correction process. to deal with the issue of statistical inference in a cointegrated system with structural breaks, both tar and mtar models (enders and siklos, 2001) are used. 4.4. results of the threshold cointegration analysis from the linear cointegration tests, the price transmission mechanism between oil prices and financial stress index may be asymmetric. to investigate this possibility, it is necessary to go further than the usual concept of cointegration in order to allow for asymmetric cointegration and thus asymmetric price table 3: unit root tests for stlfsi test whole sample pre-crisis crisis post-crisis levels 1st diff. levels 1st diff. levels 1st diff. levels 1st diff. adf unit root test exogenousa c clt c clt clt c clt none lag lengthc 7 6 1 0 1 0 1 0 t-stat. −2.377 −13.275 −1.827 −22.308 −2.266 −6.318 −5.272 −14.758 test crit. valuese: 1% level −3.436 −3.966 −3.439 −3.971 −4.070 −4.070 −3.982 −2.571 test crit. valuese: 5% level −2.864 −3.414 −2.865 −3.416 −3.464 −3.464 −3.422 −1.942 pp unit root test exogenousb clt clt c clt clt clt clt none bandwidthd 6 3 2 4 5 4 5 8 adj. t-stat. −3.115 −25.206 −1.681 −22.229 −2.095 −6.397 −5.414 −15.226 asymptotic crit. valuesee: 1% level −3.966 −3.966 −3.439 −3.971 −4.068 −4.070 −3.982 −2.571 asymptotic crit. valuesee: 5% level −3.414 −3.414 −2.865 −3.416 −3.463 −3.464 −3.422 −1.942 kpss unit root test exogenousb clt clt clt clt c c clt clt bandwidthf 26 5 21 0 7 4 15 8 lm stat 1.3792 0.0268 0.6042 0.0620 0.8146 0.0679 0.3727 0.1688 asymptotic crit. valuesee: 1% level 0.7390 0.2160 0.2160 0.2160 0.7390 0.7390 0.2160 0.2160 asymptotic crit. valuesee: 5% level 0.4630 0.1460 0.1460 0.1460 0.4630 0.4630 0.1460 0.1460 clt: constant, linear trend. c indicates constant, amodel selection is based on schwarz information criterion, bmodel selection is based on newey-west bandwith, clag length selection is based on schwarz information criterion, maxlag=22, dthe bandwidth selection is defined by using bartlett kernel, emackinnon (1996), fmodel selection is based on newey-west bandwith using bartlett kernel. stlfsi: st. louis fed financial stress index, adf: augmented dickey fuller, pp: phillips-perron, kpss: kwiatkowski−phillips−schmidt−shin table 2: unit root tests for oil prices (wti) test whole sample pre-crisis crisis post-crisis levels 1st diff. levels 1st diff. levels 1st diff. levels 1st diff. adf unit root test exogenousa clt clt c clt c c c c lag lengthc 1 0 3 2 0 0 1 0 t−stat. −1.792 −28.098 0.061 −14.208 −0.359 −7.757 −1.422 −15.028 test crit. valuese: 1% level −3.966 −3.966 −3.439 −3.971 −3.508 −3.509 −3.447 −3.447 test crit. valuese: 5% level −3.414 −3.414 −2.865 −3.416 −2.896 −2.896 −2.869 −2.869 pp unit root test exogenousb clt clt c clt c c c c bandwidthd 14 12 13 17 4 4 6 2 adj. t-stat. −2.296 −29.186 0.443 −22.696 −0.660 −7.939 −1.344 −15.011 asymptotic crit. valuese: 1% level −3.966 −3.966 −3.439 −3.971 −3.508 −3.509 −3.447 −3.447 asymptotic crit. valuese: 5% level −3.414 −3.414 −2.865 −3.416 −2.896 −2.896 −2.869 −2.869 kpss unit root test exogenousb clt clt clt clt clt clt clt clt bandwidthf 26 14 22 14 7 4 15 4 lm stat. 0.3054 0.0527 0.5704 0.0405 0.2633 0.1408 0.5033 0.0440 asymptotic crit. valuese: 1% level 0.2160 0.2160 0.2160 0.2160 0.2160 0.2160 0.2160 0.2160 asymptotic crit. valuese: 5% level 0.1460 0.1460 0.1460 0.1460 0.1460 0.1460 0.1460 0.1460 clt: constant, linear trend, c indicates constant, amodel selection is based on schwarz information criterion, bmodel selection is based on newey–west bandwith, clag length selection is based on schwarz information criterion, maxlag=22, dthe bandwidth selection is defined by using bartlett kernel, emackinnon (1996), fmodel selection is based on newey–west bandwith using bartlett kernel. wti: west texas intermediate, adf: augmented dickey fuller, pp: phillips-perron, kpss: kwiatkowski−phillips−schmidt−shin mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 201996 transmission. we conduct a nonlinear cointegration analysis by using the threshold auto-regression models. a total of four models are considered in this study. they are tar with τ=0, consistent tar (c.tar) with τ estimated, m-tar with τ=0 and consistent m-tar (c.m-tar) with τ estimated. to address possible serial correlation in the residual series, we select an appropriate lag by specifying a maximum lag of 16. we use aic, bic and ljung-box q statistics for diagnostic analyses on the residuals. in most cases, the value of the threshold τ is unknown and has to be estimated along the values of ρ1 and ρ1. table 4: results of the johansen cointegration tests test specification lag statistic critical value (%) 10 5 1 johansen λmax r=1 trend 5 5.472 10.49 12.25 16.26 r=0 trend 5 21.152** 16.85 18.96 23.65 r=1 constant 5 4.199 7.52 9.24 12.97 r=0 constant 5 9.511 13.75 15.67 20.2 r=1 none 5 4.098 6.5 8.18 11.65 r=0 none 5 9.511 12.91 14.9 19.19 johansen λtrace r≤1 trend 5 5.472 10.49 12.25 16.26 r=0 trend 5 26.624** 22.76 25.32 30.45 r≤1 constant 5 4.199 7.52 9.24 12.97 r=0 constant 5 13.71 17.85 19.96 24.6 r≤1 none 5 4.098 6.5 8.18 11.65 r=0 none 5 13.609 15.66 17.95 23.52 r is the number of cointegrating vectors. the critical values are from enders (2004). ***, ** and *denote statistical significance at the 1%, 5% and 10% levels, respectively table 5: results of the linear (engle-granger) cointegration tests variable whole sample pre-crisis in-crisis post-crisis first step ξ0 51.139*** [61.64] 36.118*** [82.690] 110.160*** [27.518] 72.039*** [45.268] ξ1 −13.067*** [−15.74] −22.169*** [−30.900] −12.511*** [−7.266] −9.355*** [−6.338] second step lags (ρ) 9 3 1 1 ρ −0.005* [−1.975] −0.017** [−2.435] −0.047* [−1.763] −0.006 [−0.939] φ1 0.253*** [8.617] 0.185*** [4.887] 0.235** [2.228] 0.262*** [5.245] φ2 −0.104*** [−3.439] −0.070* [−1.837] – – φ3 0.147*** [4.820] 0.089** [2.377] – – φ4 −0.098** [−3.195] – – – φ5 0.043 [1.402] – – – φ6 −0.041 [0.186] – – – φ7 −0.012 [−0.411] – – – φ8 0.009 [0.329] – – – φ9 0.058* [1.980] – – – aic 5332.006 2966.987 540.394 1723.438 bic 5387.784 2989.806 547.792 1735.267 qlb (4) 0.998 0.793 0.124 0.87 qlb (8) 1.000 0.171 0.429 0.815 qlb (12) 0.127 0.115 0.263 0.518 the numbers in the brackets are t-values. ***, **and *denote statistical significance at the 1%, 5% and 10% levels, respectively table 6: results of gregory-hansen cointegration test period level shift model c level shift model with trend c/t t-stat. t0 lag date t-stat. t0 lag date whole sample −3.883 565 9 2004:10:22 −3.853 565 9 2004:10:22 pre-crisis −4.108 568 3 2004:11:12 −4.741 568 3 2004:11:12 in-crisis −3.133 60 0 2008:09:19 −5.043 71 3 2008:12:05 post-crisis −4.739 293 1 2014:11:07 −4.817 293 1 2014:11:07 period regime shift model c/s regime shift model with trend c/s/t t-stat. t0 lag date t-stat t0 lag date whole sample −5.170 795 12 2009:03:20 −3.888 565 9 2004:10:22 pre-crisis −4.917 546 1 2004:06:11 −4.48 565 1 2004:10:22 in-crisis −5.728 71 3 2008:12:05 −3.288 60 0 2008:09:19 post-crisis −5.069 293 1 2014:11:07 −4.822 293 1 2014:11:07 t-stat. indicate smallest t-statistics using gregory–hansen cointegration test among possible break points. three asterisks *** (resp. **, *) denote rejection of the null hypothesis at the 1% (resp. 5%, 10%) significance level. t0 denotes the break point corresponding to the smallest t-statistic. mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 2019 97 we follow the chan’s (1993) method to estimate the threshold values for consistent tar and m-tar models. the empirical results of the threshold cointegration tests with an unknown threshold value using tar, m-tar and their consistent counterparts are reported in tables 7 and 8. the value is the optimal threshold for the indicator function. under these conditions, we can reject the null hypothesis of threshold cointegration (ρ1=ρ2=0) for all considered cases. this means that there exists a cointegrating relationship between oil prices and financial stress index. since wti is cointegrated with stlfsi using the consistent tar or m-tar models, we examine whether their adjustment coefficients are different across positive and negative errors. this procedure is achieved by verifying the existence of an asymmetric cointegration, i.e., testing the null assumption of ρ1=ρ2. notice that the asymmetry test only makes sense when the two previous tests reject the null hypothesis. that is, if the ρi coefficients estimated for the threshold are significantly different from zero, then the regression is nontrivial and testing for symmetry makes all the sense. based on the “principle of parsimony,” aic, bic and ljung-box q statistics suggest that the most applicable model for variables’ adjustment to long-run equilibrium is the m-tar model with consistent threshold value for the whole sample, while the consistent tar model is the best one for the in-crisis and postcrisis periods. it turns out that different lag specifications in the models have little impact of the final threshold values selected. the variation of the sse by threshold value for consistent m-tar model with a lag of twelve is presented in figure 2. the lowest sse for the consistent m-tar model is 6851.566 at the threshold value of −1.093. similarly, the best threshold value with the lowest sse is estimated to be 24.604 for the consistent tar model. finally, while the four nonlinear threshold cointegration models have similar results (table 7), the consistent m-tar model has the lowest aic statistic of 5301.544 and bic statistic of 5377.438, and therefore, is deemed to be the best. as shown in tables 7 and 8, we found limited evidence of asymmetric price transmission between oil prices and financial stress. therefore, oil prices became cointegrated with the stlfsi, the adjustment mechanism is asymmetric and the speed of adjustment to the equilibrium is different when the last equilibrium error has different signs. this means that the change in the equilibrium error has a different impact on the adjustment speed to the new equilibrium. focusing on the results from the consistent m-tar model, the f-test for the null hypothesis of no cointegration has a statistic of 6.165 and it is highly significant at the 1% level. thus, the oil prices and financial stress index are cointegrated with threshold adjustment. furthermore, the fstatistic for the null hypothesis of symmetric price transmission has a value of 8.746 and it is also significant at the 1% level. therefore, the adjustment process is asymmetric when wti and stlfsi adjust to achieve the longterm equilibrium. when considering the in-crisis period and focusing on the results from the consistent tar model, the f-test for the null assumption of no cointegration has a statistic of 3.235 and it is statistically significant at the 5% level. thus, wti and stlfsi are cointegrated with threshold adjustment. in addition, the f statistic for the null assumption of symmetric price transmission has a value of 3.277 and it is statistically significant at the 10% level. therefore, during the global financial crisis period, the adjustment process is asymmetric when wti and stlfsi adjust to achieve the longterm equilibrium. focusing on the findings from the consistent tar model for the post-crisis period, the f-test for the null hypothesis of no cointegration has a statistic of 2.32 and it is significant at the 10% level. therefore, the oil prices and financial stress index are cointegrated with threshold adjustment during the post-crisis period. furthermore, the f statistic for the null hypothesis of symmetric price transmission has a value of 3.753 and it is also significant at the 10% level. thus, during the post-crisis period, the adjustment process is asymmetric when wti and stlfsi adjust to achieve the long-term equilibrium. 4.5. results of the error correction model given the nonlinear threshold cointegration results, the final step in our analysis is to proceed with the asymmetric error correction model in order to investigate the movement of the oil price and stlfsi index series in a long-run equilibrium relationship. for the whole sample period, the results of our estimations of the consistent m-tar error correction models are illustrated in table 9. diagnostic analyses on the residuals with aic, bic and ljung-box q statistics select a lag of eight for the model. the consistent m-tar model is the best from the threshold cointegration analyses and the error correction terms are constructed using eq. (17) and eq. (19). results show that wti is cointegrated with stlfsi index and it also exhibits asymmetric adjustments. besides, the short-term equilibrium adjustment process mainly occurs with stlfsi-index since δ+ = δ−. moreover, there are three situations to reduce the price deviations between the two variables if they are cointegrated (chen et al., 2013). given the case stlfsi-index price is larger than wti price, there are three situations to reduce the price deviations: (i) stlfsi-index price goes down and wti price goes up; (ii) stlfsi-index price goes down and wti price goes down as well, but stlfsi-index price drops more; (iii) stlfsi-index price goes up and wti price goes up, but stlfsi-index price increases less. in our empirical results, for regimes with positive shocks (stlfsiindex price is higher than wti price), the adjustment coefficient for stlfsi-index is 0.0001 and -0.003 for wti, which means that, in the next period, wti price will go up and stlfsi-index price will go down, and thus, the price deviation will decrease. for regimes with negative shocks (stlfsi-index price is lower than wti price), the adjustment coefficient for stlfsi-index is −0.0002 and −0.018 for wti, which means that, in the next period, wti price will go down and stlfsi-index price will go down as well, mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 201998 ta bl e 7: r es ul ts o f t he n on lin ea r (t hr es ho ld ) c oi nt eg ra ti on te st s v ar ia bl e w ho le s am pl e p re -c ri si s ta r c .t a r m ta r c .m ta r ta r c .t a r m ta r c .m ta r l ag s (ρ ) 12 12 12 12 7 7 7 7 t hr es ho ld (τ ) 0. 00 0 24 .6 04 0. 00 0 −1 .0 93 0. 00 0 −8 .2 37 0. 00 0 1. 22 ρ 1 −0 .0 05 [− 1. 63 7] −0 .0 08 ** * [− 2. 64 5] 0. 00 1 [0 .1 17 ] 0. 00 1 [0 .1 26 ] −0 .0 09 [− 0. 95 3] −0 .0 08 [− 0. 94 8] −0 .0 14 [− 1. 47 5] −0 .0 06 [− 0. 40 5] ρ 2 −0 .0 04 [− 0. 96 5] 0. 00 1 [0 .2 17 ] −0 .0 1* ** [− 2. 75 8] −0 .0 17 ** * [− 3. 51 0] −0 .0 26 ** [− 2. 32 3] −0 .0 3* * [− 2. 50 4] −0 .0 18 * [− 1. 66 5] −0 .0 19 ** [− 2. 34 0] φ 1 0. 25 8* ** [8 .7 80 ] 0. 26 0* ** [8 .8 65 ] 0. 23 9* ** [7 .7 64 ] 0. 22 6* ** [7 .2 60 ] 0. 17 2* ** [4 .5 25 ] 0. 17 2* ** [4 .5 31 ] 0. 17 3* ** [4 .5 19 ] 0. 16 8* ** [4 .3 49 ] φ 2 −0 .0 94 ** [− 3. 11 9] −0 .0 92 ** [− 3. 05 5] −0 .0 98 ** [− 3. 24 0] −0 .0 99 ** [− 3. 27 7] −0 .0 64 * [− 1. 67 9] −0 .0 64 * [− 1. 66 8] −0 .0 64 * [− 1. 66 2] −0 .0 64 * [− 1. 66 8] φ 3 0. 13 9* ** [4 .6 02 ] 0. 14 1* ** [4 .6 45 ] 0. 13 9* ** [4 .5 87 ] 0. 14 0* ** [4 .6 50 ] 0. 08 9* * [2 .3 23 ] 0. 08 9* * [2 .3 21 ] 0. 08 9* * [2 .3 26 ] 0. 08 9* * [2 .3 37 ] φ 4 −0 .1 02 ** * [− 3. 34 0] −0 .1 00 ** [− 3. 28 7] −0 .1 00 ** [− 3. 28 4] −0 .0 99 ** [− 3. 27 4] 0. 04 8 [1 .2 49 ] 0. 04 9 [1 .2 59 ] 0. 04 8 [1 .2 45 ] 0. 04 6 [1 .1 98 ] φ 5 0. 04 4 [1 .4 29 ] 0. 04 5 [1 .4 68 ] 0. 04 9 [1 .5 89 ] 0. 05 3* [1 .7 20 ] 0. 03 2 [0 .8 25 ] 0. 03 3 [0 .8 54 ] 0. 03 3 [0 .8 49 ] 0. 03 2 [0 .8 43 ] φ 6 −0 .0 41 [− 1. 32 0] −0 .0 39 [− 1. 25 8] −0 .0 39 [− 1. 29 0] −0 .0 38 [− 1. 24 8] −0 .0 75 * [− 1. 94 9] −0 .0 74 * [− 1. 93 6] −0 .0 74 * [− 1. 93 7] −0 .0 76 ** [− 1. 98 4] φ 7 −0 .0 13 [− 0. 41 1] −0 .0 11 [− 0. 37 3] −0 .0 12 [− 0. 38 3] −0 .0 14 [− 0. 45 1] −0 .0 70 * [− 1. 83 4] −0 .0 68 * [− 1. 79 0] −0 .0 69 * [− 1. 82 6] −0 .0 69 * [− 1. 82 3] φ 8 0. 02 1 [0 .6 69 ] 0. 02 1 [0 .7 01 ] 0. 01 6 [0 .5 25 ] 0. 01 8 [0 .5 82 ] – – – – φ 9 0. 05 6* [1 .8 32 ] 0. 05 8* [1 .8 87 ] 0. 05 6* [1 .8 42 ] 0. 05 6* [1 .8 42 ] – – – – φ 1 0 −0 .0 43 [− 1. 42 8] −0 .0 41 [− 1. 35 6] −0 .0 45 [− 1. 49 3] −0 .0 44 [− 1. 45 6] – – – – φ 1 1 −0 .0 83 ** [− 2. 73 2] −0 .0 81 ** [− 2. 67 4] −0 .0 79 ** [− 2. 62 3] −0 .0 80 ** [− 2. 67 1] – – – – φ 1 2 0. 08 9* * [3 .0 37 ] 0. 09 1* * [3 .1 12 ] 0. 08 8* * [2 .9 95 ] 0. 08 9* * [3 .0 61 ] – – – – to ta l o bs . 11 77 11 77 11 77 11 77 70 9 70 9 70 9 70 9 c oi nt o bs . 11 64 11 64 11 64 11 64 70 1 70 1 70 1 70 1 a ic 53 10 .3 32 53 06 .8 51 53 06 .2 80 53 01 .5 44 29 50 .7 20 29 49 .8 70 29 52 .0 54 29 51 .2 76 b ic 53 86 .2 26 53 82 .7 45 53 82 .1 74 53 77 .4 38 29 96 .2 46 29 95 .3 95 29 97 .5 79 29 96 .8 01 q lb (4 ) 0. 99 9 0. 99 9 0. 99 9 0. 99 8 1. 00 0 1. 00 0 1. 00 0 1. 00 0 q lb (8 ) 1. 00 0 1. 00 0 1. 00 0 1. 00 0 1. 00 0 1. 00 0 1. 00 0 1. 00 0 q lb (1 2) 1. 00 0 1. 00 0 1. 00 0 1. 00 0 0. 88 0 0. 87 7 0. 88 0 0. 84 2 n o c i: φ (h 0 : ρ 1= ρ 2 =0 ) 1. 79 4 [0 .1 67 ] 3. 52 1* * [0 .0 30 ] 3. 80 5* * [0 .0 23 ] 6. 16 5* ** [0 .0 02 ] 3. 06 1* * [0 .0 47 ] 3. 48 5* * [0 .0 31 ] 2. 39 7* [0 .0 92 ] 2. 78 4* [0 .0 62 ] n o a pt : f (h 0 : ρ 1= ρ 2 ) 0. 03 0 [0 .8 61 ] 3. 47 5* [0 .0 63 ] 4. 04 1* * [0 .0 45 ] 8. 74 6* ** [0 .0 03 ] 1. 38 2 [0 .2 40 ] 2. 22 4 [0 .1 36 ] 0. 06 4 [0 .8 00 ] 0. 83 3 [0 .3 62 ] ** *, * * an d *d en ot e st at is tic al s ig ni fic an ce a t t he 1 % , 5 % a nd 1 0% le ve ls , r es pe ct iv el y. n um be rs in p ar en th es es a re p v al ue s. n um be rs in b ra ck et s ar e tva lu es mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 2019 99 but wti drops more and thus the price deviation will decrease. the adjusted r-squared value is 0.243 for the stlfsi-index and 0.131 for wti. moreover, the aic and bic statistics for wti are both larger than those for the stlfsi-index. this means that the model specification is better fitted on the wti price. using the estimation results of the asymmetric ecm with nonlinear threshold cointegration, we also conduct the hypothesis testing described in section 3 (paragraph 3.4). the hypotheses of granger causality between the series are assessed with f-tests. the f-statistic of 5.724 reveals that stlfsi does granger cause wti. besides, the f-statistic of 4.941 indicates that wti does granger cause stlfsi. this indicates that, in the short-term, both variables affect each other. similarly, the f-statistic of 16.899 for stlfsi discloses that the lagged index series have significant impacts on its own index. furthermore, the f-statistic of 5.134, for wti, reveals that the lagged price series have significant impacts on its own price. thus, in the short term, stlfsi and wti have been evolving more dependently. a number of hypotheses are examined for asymmetric price transmission. the first one is the distributed lag asymmetric effect. in each price equation, the equality of the corresponding positive and negative coefficients for each of the eight lags is tested; in total, there are sixteen f-tests for this hypothesis. it turns out that an important number of them is statistically significant and distributed lag asymmetric effect does exist. furthermore, the cumulative asymmetric effects are also examined. the largest f-statistic is 9.963 but only one of the four statistics is statistically significant at the 1% level. thus, cumulative effects are asymmetric. the fourth examined asymmetry is the momentum equilibrium adjustment path asymmetries (h07:δ +=δ−). for stlfsi, the f-statistic is 1.706 with a p = 0.192. the point estimates of the coefficients for the error correction terms are 0.0001 with a t-value of 0.668 for positive error correction term and −0.0002 with a t-value of –0.82 for the negative one. in contrast, for wti price, the f-statistic is 7.952 with a p = 0.005. thus, there is momentum equilibrium adjustment asymmetry. the point estimates are −0.003 with a t-value of −0.746 for positive deviations and −0.018 with a t-value of −3.405 for negative deviations. the magnitude suggests that in the short term the wti responds to the positive deviations by 0.3% in a week but by 1.8% to negative deviations. measured in response time, positive and negative deviations take, respectively, 333.333 and 55.556 weeks to be fully digested. therefore, in the short-term, wti has a much faster reaction to negative deviations from long-term equilibrium than positive deviations. further findings for the in-crisis period are reported in table 9. diagnostic analyses on the residuals with aic, bic and ljungbox q statistics select a lag of four for the model. the consistent tar model is the best from the threshold cointegration analyses and the error correction terms are constructed using eq. (16) and eq. (19). during the global financial crisis period, results show that wti is cointegrated with stlfsi index and it also exhibits asymmetric adjustments. besides, for regimes with positive shocks, the adjustment coefficient for stlfsi-index is 0.004 and −0.036 for wti, which means that, in the next period, wti price will go up and stlfsi-index price will go down, and thus, the t ab le 8 : r es ul ts o f t he n on lin ea r (t hr es ho ld ) c oi nt eg ra ti on te st s (c on ti nu ed ) v ar ia bl e in -c ri si s p os tcr is is ta r c .t a r m ta r c .m ta r ta r c .t a r m ta r c .m ta r l ag s (ρ ) 4 1 1 1 1 1 1 1 t hr es ho ld (τ ) 0. 00 0 −2 7. 00 0 0. 00 0 –6 .1 5 0. 00 0 17 .0 19 0. 00 0 –1 .3 95 ρ 1 –0 .0 43 [– 1. 16 1] –0 .0 19 [– 0. 62 7] –0 .0 13 [– 0. 35 1] –0 .0 29 [– 0. 99 9] –0 .0 2* [– 1. 96 1] –0 .0 27 ** [– 2. 15 3] –0 .0 06 [– 0. 67 4] –0 .0 1 [– 1. 39 8] ρ 2 –0 .0 39 [– 0. 91 5] –0 .1 27 ** [– 2. 46 9] –0 .0 87 ** [– 2. 23 8] –0 .1 37 ** [– 2. 11 6] 0. 00 1 [0 .2 05 ] 0. 00 04 [0 .0 61 ] –0 .0 06 [– 0. 65 4] 0. 00 6 [0 .5 29 ] φ 1 0. 30 9* * [2 .7 94 ] 0. 24 5* * [2 .3 50 ] 0. 22 8* * [2 .1 69 ] 0. 22 7* * [2 .1 65 ] 0. 26 4* ** [5 .3 07 ] 0. 26 5* ** [5 .3 14 ] 0. 26 2* ** [5 .2 33 ] 0. 26 2* ** [5 .2 58 ] φ 2 –0 .1 29 –1 .1 46 – – – – – – – φ 3 0. 27 2* *2 .4 38 – – – – – – – φ 4 –0 .1 80 [– 1. 61 5] – – – – – – – to ta l o bs . 87 87 87 87 38 1 38 1 38 1 38 1 c oi nt o bs . 82 85 85 85 37 9 37 9 37 9 37 9 a ic 52 3. 59 7 53 9. 06 3 54 0. 36 3 54 0. 02 1 17 22 .4 19 17 21 .6 74 17 25 .4 38 17 24 .0 74 b ic 54 0. 44 4 54 8. 83 4 55 0. 13 3 54 9. 79 2 17 38 .1 69 17 37 .4 24 17 41 .1 88 17 39 .8 24 q lb (4 ) 0. 99 6 0. 19 1 0. 22 4 0. 37 8 0. 90 6 0. 93 3 0. 87 0. 83 1 q lb (8 ) 0. 99 3 0. 55 1 0. 60 1 0. 78 5 0. 81 6 0. 84 5 0. 81 5 0. 82 6 q lb (1 2) 0. 94 2 0. 41 2 0. 32 9 0. 57 4 0. 53 0. 58 8 0. 51 8 0. 52 5 n o c i: φ (h 0 : ρ 1= ρ 2 =0 ) 1. 05 8 [0 .3 52 ] 3. 23 5* * [0 .0 44 ] 2. 56 4* [0 .0 83 ] 2. 73 9* [0 .0 71 ] 1. 94 6 [0 .1 44 2] 2. 32 * [0 .0 99 ] 0. 43 9 [0 .6 45 ] 1. 11 9 [0 .3 28 ] n o a pt : f (h 0 : ρ 1= ρ 2 ) 0. 00 4 [0 .9 50 ] 3. 27 7* [0 .0 74 ] 1. 98 3 [0 .1 63 ] 2. 32 1 [0 .1 31 ] 3. 00 7* [0 .0 84 ] 3. 75 3* [0 .0 53 ] 0. 00 02 [0 .9 95 ] 1. 35 6 [0 .2 45 ] ** *, * * an d *d en ot e st at is tic al s ig ni fic an ce a t t he 1 % , 5 % a nd 1 0% le ve ls , r es pe ct iv el y. n um be rs in p ar en th es es a re p v al ue s. n um be rs in b ra ck et s ar e tva lu es mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 2019100 price deviation will decrease. for regimes with negative shocks, the adjustment coefficient for stlfsi-index is −0.002 and −0.076 for wti, which means that, in the next period, wti price will go down and stlfsi-index price will go down as well, but wti drops more and thus the price deviation will decrease. the adjusted r-squared value is 0.337 for the stlfsi-index and 0.208 for wti price. likewise, the aic and bic statistics for wti are both larger than those for the stlfsi-index, which means that the model specification is better fitted on the wti price during the in-crisis period. furthermore, the f-statistic of 1.811 reveals that stlfsi does granger cause wti. moreover, the f-statistic of 3.098 indicates that wti does granger cause stlfsi. this indicates that, in the short-term, both variables affect each other during the crisis period. in the same way, the f-statistic of 2.34 for stlfsi discloses that the lagged index series have significant impacts on its own index. additionally, the f-statistic of 0.781, for wti, reveals that the lagged price series have insignificant impacts on its own price. accordingly, in the short term, stlfsi and wti have been evolving more dependently during the in-crisis period. the results for hypothesis description are also reported in table 9. in each price equation, the equality of the corresponding positive and negative coefficients for each of the four lags is tested; in total, there are eight f-tests for this assumption. it turns out that a few numbers of them is statistically significant and the distributed lag asymmetric effect does exist. furthermore, the cumulative asymmetric effects are not statistically significant and thus, cumulative effects are symmetric. in addition, the momentum equilibrium adjustment path asymmetry is examined. for stlfsi, the f-statistic is 1.893 with a p = 0.174. the point estimates of the coefficients for the error correction terms are 0.004 with a t-value of 1.889 for positive error correction term and −0.002 with a t-value of 0.502 for the negative one. on the contrary, for wti price, the f-statistic is 0.377 with a p = 0.174. thus, there is no momentum equilibrium adjustment asymmetry. the estimation and diagnostic results for the post-crisis period are reported in table 9. diagnostic analyses on the residuals with aic, bic and ljung-box q statistics select a lag of five for the model. the consistent tar model is the best from the threshold cointegration analyses and the error correction terms are constructed using eq. (16) and eq. (19). during the postcrisis period, results show that wti is cointegrated with stlfsi index and it also exhibits asymmetric adjustments. besides, for regimes with positive shocks, the adjustment coefficient for stlfsi-index is −0.0003 and −0.031 for wti, which means that, in the next period, wti price will go up and stlfsi-index price will go down, and thus, the price deviation will decrease. for regimes with negative shocks, the adjustment coefficient for stlfsi-index is −0.0001 and 0.002 for wti, which means that, in the next period, wti price will go down and stlfsi-index price will go down as well, but wti drops more and thus the price deviation will decrease. the aic and bic statistics for wti are both larger than those for the stlfsi-index, which means that the model specification is better fitted on the wti price during the post-crisis period. furthermore, the f-statistic of 0.953 reveals that stlfsi does not granger cause wti. moreover, the f-statistic of 0.736 indicates that wti does not granger cause stlfsi. this indicates that, in the short-term, both variables do not affect each other during the post-crisis period. also, the f-statistic of 2.938 for stlfsi discloses that the lagged index series have significant impacts on its own index. additionally, the f-statistic of 3.869, for wti, reveals that the lagged price series have significant impacts on its own price. accordingly, in the short term, stlfsi and wti have been evolving more independently during the post-crisis period. finally, the results for hypothesis description are summarized in table 9. first, they indicate the existence of some distributed lag asymmetric effects. second, the cumulative effects are asymmetric. third, there is a momentum equilibrium adjustment path asymmetry. for stlfsi, the f-statistic is 0.189 with a p = 0.664. the point estimates of the coefficients for the error correction terms are −0.0003 with a t-value of −0.619 for positive error correction term and −0.0001 with a t-value of −0.266 for the negative one. in contrast, for wti price, the f-statistic is 3.274 with a p = 0.071. furthermore, the point estimates are −0.031 with a t-value of −1.947 for positive deviations and 0.002 with a t-value of 0.216 for negative deviations. the magnitude suggests that in the short term the wti responds to the positive deviations by 3.1% in a week but by 0.2% to negative deviations. measured in response time, positive and negative deviations take, respectively, 32.26 and figure 2: threshold value for m-tar (whole sample) mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 2019 101 ta bl e 9: r es ul ts o f t he a sy m m et ri c er ro r co rr ec ti on m od el s w it h th re sh ol d co in te gr at io n v ar ia bl e w ho le s am pl e (c .m − ta r ; l ag =8 ) in –c ri si s (c . t a r ; l ag =4 ) p os t– cr is is (c . t a r ; l ag =5 ) st l f si w t i st l f si w t i st l f si w t i c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c θ 0. 00 1 0. 14 4 −0 .1 12 −0 .6 84 0. 06 5 0. 71 3 2. 83 7* 1. 91 8 0. 01 5 1. 31 8 −0 .6 5* −1 .6 75 1  + 0. 43 3* ** 9. 41 2. 64 9* ** 2. 75 8 0. 56 5* ** 3. 09 8 4. 71 5 1. 60 4 −0 .0 33 −0 .3 41 5. 56 5* 1. 67 5 2  + 0. 05 8 1. 19 8 −6 .4 75 ** * −6 .3 55 0. 09 5 0. 47 −7 .1 25 ** −2 .2 0. 04 2 0. 43 1 0. 30 1 0. 08 9 3  + 0. 07 6 1. 52 8 1. 18 8 1. 13 8 0. 19 2 0. 95 3 2. 82 4 0. 87 −0 .0 89 −0 .9 05 1. 86 5 0. 54 6 4  + −0 .1 61 ** * −3 .1 91 −2 .9 01 ** * −2 .7 51 −0 .3 45 * −1 .7 44 −3 .2 59 −1 .0 23 0. 05 1 0. 52 3 −2 .0 82 −0 .6 09 5  + −0 .3 09 ** * −6 .0 15 3. 67 3* ** 3. 42 – – – – 0. 05 5 0. 56 3 −0 .2 16 −0 .0 64 6  + 0. 27 2* ** 5. 23 4 −0 .7 5 −0 .6 91 – – – – – – – – 7  + −0 .2 82 ** * −5 .4 1 0. 98 8 0. 90 8 – – – – – – – – 8  + 0. 00 4 0. 07 −3 .8 08 ** * −3 .5 66 – – – – – – – – 1  − 0. 13 5* * 2. 21 1 −1 .6 12 −1 .2 65 −0 .2 21 −0 .8 73 0. 46 3 0. 11 4 0. 41 9* ** 4. 11 7 1. 27 4 0. 35 9 2  − −0 .0 93 −1 .5 53 −0 .5 2 −0 .4 15 0. 01 7 0. 06 9 −3 .4 15 −0 .8 64 0. 01 6 0. 15 1 0. 25 0. 06 8 3  − 0. 10 5* 1. 74 3 −0 .9 12 −0 .7 27 0. 26 1 1. 17 0. 97 2 0. 27 0. 14 1 1. 35 2 −7 .3 28 ** −2 .0 14 4  − −0 .0 18 −0 .3 11 2. 02 8* 1. 65 2 −0 .3 04 −1 .3 42 6. 58 6* 1. 80 4 0. 08 9 0. 86 1 −1 .3 83 −0 .3 85 5  − 0. 16 2* ** 2. 78 −2 .4 23 ** −1 .9 93 – – – – 0. 01 1 0. 11 1 3. 44 1 0. 98 6 6  − −0 .0 12 −0 .2 13 −2 .4 11 ** −2 .0 05 – – – – – – – – 7  − 0. 06 5 1. 17 1 0. 21 5 0. 18 5 – – – – – – – – 8  − 0. 16 3* ** 2. 95 7 −0 .5 17 −0 .4 48 – – – – – – – – 1 + 0. 00 8* ** 2. 69 7 0. 10 7* 1. 84 2 0. 02 5. 1. 59 −0 .2 4 −0 .9 6 0. 00 1 0. 37 5 0. 19 5* 1. 93 4 2  + −0 .0 03 −1 .1 19 −0 .0 05 −0 .0 95 −0 .0 05 −0 .3 −0 .3 07 −1 .1 99 −0 .0 06 ** −2 .0 11 0. 17 * 1. 68 9 3  + −0 .0 05 −1 .6 28 0. 11 2* 1. 94 5 −0 .0 4* * −2 .4 13 0. 16 9 0. 63 6 0. 00 2 0. 53 2 0. 05 7 0. 56 6 4  + −0 .0 04 −1 .2 76 0. 04 3 0. 75 2 −0 .0 28 * −1 .7 01 −0 .0 07 −0 .0 28 0. 00 2 0. 59 3 0. 11 9 1. 18 4 0. 00 03 0. 12 0. 03 3 0. 57 4 – – – – −0 .0 01 −0 .3 45 0. 05 6 0. 56 5 6  + −0 .0 04 −1 .5 49 −0 .0 96 * −1 .6 91 – – – – – – – – 7  + 0. 00 3 0. 99 2 0. 04 8 0. 84 5 – – – – – – – – (c on td ... ) mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 2019102 (c on td ... ) v ar ia bl e w ho le s am pl e (c .m − ta r ; l ag =8 ) in –c ri si s (c . t a r ; l ag =4 ) p os t– cr is is (c . t a r ; l ag =5 ) st l f si w t i st l f si w t i st l f si w t i c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c 8  + 0. 00 7* ** 2. 62 2 0. 20 1* ** 3. 57 8 – – – – – – – – 1 − −0 .0 07 ** −2 .5 39 0. 27 ** * 4. 69 2 −0 .0 15 −0 .9 18 0. 51 9* 1. 90 7 −0 .0 04 . −1 .4 97 0. 39 7* ** 3. 92 4 2  − 0. 00 5* 1. 66 4 −0 .1 5* ** −2 .6 27 −0 .0 04 −0 .2 53 0. 15 8 0. 58 7 0. 00 2 0. 61 3 −0 .1 86 * −1 .7 92 3  − 0. 01 2* ** 4. 49 4 0. 01 1 0. 19 1 0. 05 6* ** 3. 58 5 −0 .0 65 −0 .2 56 0. 00 1 0. 37 8 −0 .0 62 −0 .6 03 4  − −0 .0 07 ** * −2 .5 79 −0 .0 54 −0 .9 47 −0 .0 06 −0 .3 07 0. 13 5 0. 46 7 −0 .0 01 −0 .4 75 −0 .1 39 −1 .3 52 −0 .0 01 −0 .2 49 0. 13 9* * 2. 40 9 – – – – 0. 00 1 0. 26 3 0. 08 9 0. 87 3 6  − 0. 00 1 0. 26 2 0. 06 3 1. 10 3 – – – – – – – – 7  − −0 .0 03 −0 .9 43 −0 .0 47 −0 .8 16 – – – – – – – – 8  − −0 .0 14 ** * −5 .1 07 0. 04 4 0. 77 5 – – – – – – – – δ+ 0. 00 01 0. 66 8 –0 .0 03 −0 .7 46 0. 00 4* 1. 88 9 −0 .0 36 −1 .0 95 −0 .0 00 3 −0 .6 19 −0 .0 31 * −1 .9 47 δ− −0 .0 00 2 −0 .8 2 −0 .0 18 ** * −3 .4 05 −0 .0 02 −0 .5 02 −0 .0 76 −1 .3 6 −0 .0 00 1 −0 .2 66 0. 00 2 0. 21 6 d ia gn os tic s r –s qu ar ed 0. 26 5 – 0. 15 6 – 0. 48 4 – 0. 38 4 – 0. 11 8 – 0. 12 5 – a dj us te d r –s qu ar ed 0. 24 3 – 0. 13 1 – 0. 33 7 – 0. 20 8 – 0. 06 3 – 0. 07 0 – f– st at . 11 .9 94 ** * (0 .0 00 ) 6. 15 9* ** (0 .0 00 ) 3. 28 2* ** (0 .0 00 2) 2. 18 5* * (0 .0 11 9) 2. 15 0* ** (0 .0 02 2) 2. 28 3* ** (0 .0 01 ) st at . d w 1. 98 7 (0 .8 26 ) 1. 98 0 (0 .6 74 ) 2. 02 3 (0 .9 18 ) 2. 01 0 (0 .8 34 ) 1. 99 6 (0 .8 56 ) 2. 00 1 (0 .8 78 ) a ic −2 01 8. 22 5 – 50 81 .8 21 – 40 .8 15 – 49 6. 73 4 – −8 83 .4 38 – 17 80 .6 11 – b ic −1 83 5. 95 5 – 52 64 .0 90 – 88 .9 49 – 54 4. 86 9 – −7 89 .1 92 – 18 74 .8 57 – q l b (4 ) 0. 99 5 – 0. 99 8 – 0. 92 2 – 0. 90 2 – 0. 99 9 – 0. 99 6 – q l b (8 ) 0. 95 1 – 1. 00 0 – 0. 68 4 – 0. 47 8 – 0. 11 2 – 0. 90 9 – q l b (1 2) 0. 75 9 – 0. 98 7 – 0. 78 5 – 0. 62 5 – 0. 22 4 – 0. 75 7 – h yp ot he si s de sc ri pt io n f –s ta ti st ic p va lu e f –s ta ti st ic p va lu e f –s ta ti st ic p va lu e f –s ta ti st ic p va lu e f –s ta ti st ic p va lu e f –s ta ti st ic p va lu e g ra ng er c au sa lit y te st 01 : 0 yi yj h   + − = = 16 .8 99 ** * 0. 00 0 5. 72 4* ** 0. 00 0 2. 34 ** 0. 02 9 1. 81 1* 0. 09 1 2. 93 8* ** 0. 00 1 0. 95 3 0. 48 5 02 : 0 xi xj h   + − = = 4. 94 1* ** 0. 00 0 5. 13 4* ** 0. 00 0 3. 09 8* ** 0. 00 5 0. 78 1 0. 62 1 0. 73 6 0. 69 0 3. 86 9* ** 0. 00 0 d is tr ib ut ed la g as ym m et ri c ef fe ct 03 1 1 : 0 x x h   + − = = 11 .5 05 ** * 0. 00 1 5. 40 3* * 0. 02 0 4. 86 2* * 0. 03 1 0. 54 8 0. 46 2 7. 98 2* ** 0. 00 5 0. 59 3 0. 44 2 03 2 2 : 0 x x h   + − = = 2. 95 4* 0. 08 6 10 .4 44 ** * 0. 00 1 0. 04 2 0. 83 9 0. 36 6 0. 54 8 0. 02 6 0. 87 3 0. 00 0 0. 99 3 03 3 3 : 0 x x h   + − = = 0. 10 0 0. 75 2 1. 26 1 0. 26 2 0. 03 8 0. 84 6 0. 10 7 0. 74 5 1. 99 3 0. 15 9 2. 62 5 0. 10 6 03 4 4 : 0 x x h   + − = = 2. 55 8 0. 11 0 6. 98 2* ** 0. 00 8 0. 01 3 0. 90 9 2. 94 2* 0. 09 1 0. 05 3 0. 81 8 0. 01 5 0. 90 2 ta bl e 9: (c on tin ue d) mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 2019 103 v ar ia bl e w ho le s am pl e (c .m − ta r ; l ag =8 ) in –c ri si s (c . t a r ; l ag =4 ) p os t– cr is is (c . t a r ; l ag =5 ) st l f si w t i st l f si w t i st l f si w t i c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c c oe ffi ci en t t– st at is ti c 03 5 5 : 0 x x h   + − = = 27 .5 26 ** * 0. 00 0 10 .5 62 ** * 0. 00 1 – – – – 0. 07 4 0. 78 6 0. 43 1 0. 51 2 03 6 6 : 0 x x h   + − = = 9. 92 7* ** 0. 00 2 0. 77 6 0. 37 9 – – – – – – – – 03 7 7 : 0 x x h   + − = = 15 .5 28 ** * 0. 00 0 0. 17 7 0. 67 4 – – – – – – – – 03 8 8 : 0 x x h   + − = = 3. 30 0* 0. 07 0 3. 21 3* 0. 07 3 – – – – – – – – 04 1 1 : 0 y y h   + − = = 9. 80 8* ** 0. 00 2 2. 84 0* 0. 09 2 1. 98 5 0. 16 4 2. 72 4 0. 10 4 1. 30 4 0. 25 4 1. 49 3 0. 22 3 04 2 2 : 0 y y h   + − = = 2. 69 9 0. 10 1 2. 20 4 0. 13 8 0. 00 0 0. 98 5 1. 01 5 0. 31 8 2. 58 1 0. 10 9 4. 62 2* * 0. 03 2 04 3 3 : 0 y y h   + − = = 13 .0 22 ** * 0. 00 0 1. 10 4 0. 29 4 11 .2 26 ** * 0. 00 1 0. 25 6 0. 61 5 0. 00 8 0. 93 0 0. 51 9 0. 47 2 04 4 4 : 0 y y h   + − = = 0. 57 7 0. 44 8 1. 01 4 0. 31 4 0. 52 0. 47 4 0. 08 1 0. 77 7 0. 43 3 0. 51 1 2. 45 1 0. 11 8 04 5 5 : 0 y y h   + − = = 0. 04 9 0. 82 5 1. 22 8 0. 26 8 – – – – 0. 13 8 0. 71 1 0. 04 0 0. 84 2 04 6 6 : 0 y y h   + − = = 1. 15 7 0. 28 2 2. 77 3* 0. 09 6 – – – – – – – – 04 7 7 : 0 y y h   + − = = 1. 32 1 0. 25 1 0. 97 4 0. 32 4 – – – – – – – – 04 8 8 : 0 y y h   + − = = 21 .0 07 ** * 0. 00 0 2. 69 0 0. 10 1 – – – – – – – – c um ul at iv e as ym m et ri c ef fe ct 05 1 1 : p p xj xj j j h   + − = = = ∑ ∑ 9. 96 3* ** 0. 00 2 0. 06 8 0. 79 4 1. 20 4 0. 27 7 0. 45 3 0. 50 3 6. 14 9* * 0. 01 4 1. 01 2 0. 31 5 06 1 1 : p p yj yj j j h   + − = = = ∑ ∑ 2. 20 6 0. 13 8 0. 54 6 0. 46 0 1. 44 7 0. 23 3 1. 14 9 0. 28 8 0. 00 2 0. 96 7 2. 04 6 0. 15 3 eq ui lib riu m ad ju stm en t p at h as ym m et ry h 07 : δ + = δ− 1. 70 6 0. 19 2 7. 95 2* ** 0. 00 5 1. 89 3 0. 17 4 0. 37 7 0. 54 1 0. 18 9 0. 66 4 3. 27 4* 0. 07 1 q lb (p ) d en ot es th e si gn ifi ca nc e le ve l f or th e l ju ng -b ox q s ta tis tic , w hi ch te st s se ri al c or re la tio n ba se d on p a ut oc or re la tio n co ef fic ie nt s. n um be rs in p ar en th es es a re p v al ue s. * ** , * *, a nd * de no te s ta tis tic al s ig ni fic an ce a t t he 1 % , 5 % a nd 1 0% le ve ls , r es pe ct iv el y ta bl e 9: (c on tin ue d) mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 2019104 500 weeks to be fully digested. therefore, in the short-term, wti has a much faster reaction to positive deviations from long-term equilibrium than negative deviations. 5. concluding remarks in this article, we investigated the dynamic relationship between oil prices and financial stress over the period from december 31, 1993 to july 15, 2016. in particular, we focused on the linkages between those variables in both the long-run and short-run horizons under both the linear and nonlinear (threshold) cointegration framework. as an extension of preceding studies, we make use of the methodology developed by enders and siklos (2001), based on a nonlinear (threshold) cointegration model allowing for nonlinear adjustment to long-run equilibrium. the results from the conventional linear cointegration approaches suggested that we can reject the null hypothesis of no cointegration. according to our empirical results, the null hypothesis of linear cointegration between oil prices and financial stress is rejected in favor of a threshold cointegration model in the sense that the shortterm adjustments to the equilibrium are asymmetric depending on the deviation from the equilibrium. thereafter, using the consistent tar and mtar specifications, we found evidence of asymmetry in the adjustment process to equilibrium. these findings would suggest the presence of a significant nonlinear behavior in the oil price-financial stress relationship. we find an asymmetric effect in the short-term adjustment process. regimes with negative (below the threshold) changes of deviations adjust much quicker than regimes with positive (above the threshold) changes of deviations, especially during the crisis period. after incorporating the asymmetric adjustment and using a granger causality test, we find a bi-directional causality between oil prices and financial stress index, indicating that these variables affect have been evolving more dependently in the short term, in particular during the crisis period. our results also reveal the existence of three types of statistical significant asymmetries, namely the distributed lag asymmetric effect, the cumulative asymmetric effects, and the momentum equilibrium adjustment path asymmetries. future research could extend the two-regime threshold cointegration model to three or more regimes. references balke, n.s., brown, s.p.a., yücel, m.k. (2002), oil price shocks and the us economy: where does the asymmetry originate? energy journal, 23(3), 27-52. balke, n.s., fomby, t.b. (1997), threshold cointegration. international economic review, 38(3), 627-645. baur, d.g. (2012), financial contagion and the real economy. journal of banking and finance, 36(10), 2680-2692. bis. (2009), the international financial crisis: timeline, impact and policy responses in asia and the pacific. basel: bank for international settlements. caner, m., hansen, b. (2001), threshold autoregression with a unit root. econometrica, 69(6), 1555-1596. cardarelli, r., elekdag, s., lall, s. (2011), financial stress and economic contractions. journal of financial stability, 7(2), 78-97. cevik, e.i., dibooglu, s., kenc, t. (2013), measuring financial stress in turkey. journal of policy modeling, 35(2), 370-383. chan, k.s. (1993), consistency and limiting distribution of the least squares estimator of a threshold autoregressive model. annals of statistics, 21(1), 520-533. chau, f., deesomsak, r. (2014), does linkage fuel the fire? the transmission of financial stress across the markets. international review of financial analysis, 36, 57-70. chen, h., choi, p.m.s., hong, y. (2013), how smooth is price discovery? evidence from cross-listed stock trading. journal of international money and finance, 32, 668-699. chen, h., zhu, y. (2015), an empirical study on the threshold cointegration of chinese a and h cross-listed shares. journal of applied statistics, 42(11), 2406-2419. chen, w., hamori, s., kinkyo, t. (2014), macroeconomic impacts of oil prices and underlying financial shocks. journal of international financial markets, institutions and money, 29, 1-12. cunado, j., de gracia, f.p. (2003), do oil price shocks matter? evidence for some european countries. energy economics, 25(2), 137-154. cunado, j., de gracia, f.p. (2005), oil prices, economic activity, and inflation: evidence for some asian countries. the quarterly review of economics and finance, 45(1), 65-83. davig, t., hakkio, c. (2010), what is the effect of financial stress on economic activity? federal reserve bank of kansas city. economic review, 2010, 35-62. demirguc-kunt, a., levine, r. (2001), financial structures and economic growth: a cross country comparison of banks, markets, and development. cambridge, ma: mit press. dickey, d.a., fuller, w.a. (1979), distribution of the estimators for autoregressive time series with a unit root. journal of the american statistical association, 74(366), 427-431. dimitriou, d., kenourgios, d. (2013), financial crises and dynamic linkages among international currencies. journal of international financial markets, institutions and money, 26, 319-332. dimitriou, d., kenourgios, d., simos, t. (2013), global financial crisis and emerging stock market contagion: a multivariate fiaparchdcc approach. international review of financial analysis, 30, 46-56. enders, w. (2004), applied econometric time series. new york: john wiley and sons, inc. p480. enders, w., granger, c.w.f. (1998), unit-root tests and asymmetric adjustment with an example using the term structure of interest rates. journal of business and economic statistics, 16(3), 304-311. enders, w., siklos, p.l. (2001), cointegration and threshold adjustment. journal of business and economic statistics, 19(2), 166-176. engle, r., granger, c.w.j. (1987), cointegration and error correction: representation, estimation, and testing. econometrica, 55(2), 251-276. federal reserve board of st. louis. (2009), the financial crisis: a timeline of events and policy actions. st. louis: federal reserve board of st. louis. frey, g., manera, m. (2007), econometric models of asymmetric price transmission. journal of economic surveys, 21(2), 349-415. granger, c.w.j., lee, t.h. (1989), investigation of production, sales, and inventory relationships using multicointegration and nonsymmetric error correction models. journal of applied econometrics, 4, 145-159. gregory, a.w., hansen, b.e. (1996a), residual-based tests for cointegration in models with regime shifts. journal of econometrics, 70(1), 99-126. gregory, a.w., hansen, b.e. (1996b), tests for cointegration in models with regime and trend shifts. oxford bulletin of economics and statistics, 58(3), 555-560. hakkio, c., keeton, w. (2009), financial stress: what is it, how can it be mighri and alsaggaf: asymmetric threshold cointegration and nonlinear adjustment between oil prices and financial stress international journal of energy economics and policy | vol 9 • issue 3 • 2019 105 measured, and why does it matter? federal reserve bank of kansas city. economic review, 2009, 5-50. hamilton, j. (2011), nonlinearities and the macroeconomic effects of oil prices. macroeconomic dynamics, 15(3), 364-378. holló, d. (2012), a system-wide financial stress indicator for the hungarian financial system. mnb occasional papers no. 105. holló, d., kremer, m., lo duca, m. (2012), ciss-a b composite indicator of systemic stress in the financial system. european central bank working paper no. 1426. illing, m., liu, y. (2006), measuring financial stress in a developed country: an application to canada. journal of financial stability, 2, 243-265. islami, m., kurz-kim, j.r. (2014), a single composite financial stress indicator and its real impact in the euro area. international journal of finance and economics, 19, 204-211. johansen, s. (1988), statistical analysis of cointegration vectors. journal of economic dynamics and control, 12(2-3), 231-254. johansen, s., juselius, k. (1990), maximum likelihood estimation and inference on cointegration with applications to the demand for money. oxford bulletin of economics and statistics, 52(2), 169-210. kilian, l. (2008), the economic effects of energy price shocks. journal of economic literature, 46(4), 871-909. killian, l. (2009), not all oil price shocks are alike: disentangling demand and supply shocks in the crude oil market. american economic review, 99(3), 1053-1069. kliesen, k.l., owyang, m.t., vermann, e.k. (2012), disentangling diverse measures: a survey of financial stress indexes. federal reserve bank of st. louis. economic review, 94(5), 369-397. kuo, s.h., enders, w. (2004), the term structure of japanese interest rates: the equilibrium spread with asymmetric dynamics. journal of the japanese and international economies, 18(1), 84-98. kwiatkowski, d., phillips, p.c.b., schmidt, p., shin, y. (1992), testing the null hypothesis of stationarity against the alternative of a unit root. journal of econometrics, 54(1-3), 159-178. levine r. (2005), finance and growth: theory and evidence. in: aghion, p., durlauf, s., editors. handbook of economic growth. vol. 1. amsterdam: north-holland elsevier. p865-934. mackinnon, j.g. (1996), numerical distribution functions for unit root and cointegration tests. journal of applied econometrics, 11(6), 601-618. mallick, s.k., sousa, r.m. (2013), the real effects of financial stress in the eurozone. international review of financial analysis, 30, 1-17. meyer, j., von cramon-taubade, s. (2004), asymmetric price transmission: a survey. journal of agricultural economics, 55(3), 581-611. mighri, z., mansouri, f. (2014), modeling international stock market contagion using multivariate fractionally integrated aparch approach. cogent economics and finance, 2(1), 963632. mighri, z., mansouri, f. (2016), asymmetric price transmission within the argentinean stock market: an asymmetric threshold cointegration approach. empirical economics, 51(3), 1115-1149. mollick, a.v., assefa, t.a. (2013), u.s. stock returns and oil prices: the tale from daily data and the 2008-2009 financial crisis. energy economics, 36, 1-18. morales, m.a., estrada, d. (2010), a financial stability index for columbia. annals of finance, 6(4), 555-581. nazlioglu, s., soytas, u., gupta, r. (2015), oil prices and financial stress: a volatility spillover analysis. energy policy, 82, 278-288. phillips, p.c.b., perron, p. (1988), testing for a unit root in time series regression. biometrika, 75(2), 335-346. rafiq, j., salim, r., bloch, h. (2009), impact of crude oil price volatility on economic activities: an empirical investigation in the thai economy. resources policy, 34(3), 121-132. slingenberg, j.w., de haan, j. (2011), forecasting financial stress. de nederlandsche bank working paper no. 292. sun, c. (2011), price dynamics in the import wooden bed market of the united states. forest policy and economics, 13(6), 479-487. thompson, m.a. (2006), asymmetric adjustment in the prime lendingdeposit rate spread. review of financial economics, 15(4), 323-329. tong, h. (1983), threshold models in non-linear time series analysis. new york: springer-verlag. turhan, i., hacıhasanoglu, e., soytas, u. (2013), oil prices and emerging market exchange rates. emerging markets finance and trade, 49(1), 21-36. vermeulen, r., hoeberichts, m., vašíček, b., žigraiová, d., šmídková, k., de haan, j. (2015), financial stress indices and financial crises. open economic review, 26(3), 383-406. . international journal of energy economics and policy | vol 10 • issue 4 • 2020258 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(4), 258-265. petroleum subsidy withdrawal, fuel price hikes and the nigerian economy henry egbezien inegbedion1*, emmanuel inegbedion2, eseosa obadiaru3, abiola asaleye4 1department of business studies, landmark university, omu aran, nigeria, 2department of physical planning, nigerian broadcast academy, lagos, nigeria, 3department of accounting and finance, landmark university, omu aran, nigeria, 4department of economics, landmark university, omu aran, nigeria. *email: inegbedion.henry@lmu.edu.ng received: 29 june 2019 accepted: 04 march 2020 doi: https://doi.org/10.32479/ijeep.8307 abstract the study investigated petroleum subsidy withdrawal, fuel price hikes and the nigerian economy. the purpose of the study was to determine the extent to which the removals of petroleum subsidies stimulate hikes in fuel prices and increases in the prices of products of other sectors in the nigerian economy. it employed input-output model to determine the value added per sector from the computed table of flow of goods. subsequently, the impacts of reductions in petroleum subsidies (10%, 20%, 30%, 40% and 50%) on the prices of products from the other sectors were computed. results showed that reduction in petroleum subsidies stimulate increases in prices of petroleum products and such increases trigger increases in transport fares; increases in transport fares subsequently lead to increases in prices of other products owing to the degree of interdependency among the various sectors. the need for policy makers to be mindful of the economic implications of subsidy removal was suggested, among others. keywords: petroleum subsidy, petroleum subsidy removal, fuel price hike jel classifications: h25 1. introduction since the discovery of oil in commercial quantities at oloibiri in the late fifties and the subsequent relegation of the agricultural sector, crude oil has been and is still the mainstay of the nigerian economy. society’s heavy dependence on oil for her foreign exchange earnings has made the nigerian economy a monoculture. there have been interests in understanding the causes and consequences of oil price shocks ever since the 1970s (lorussoa and pieronib, 2018; fueki et al., 2018; amaiquema and amaiquema, 2017, jo et al., 2017; obi et al., 2016; kilian, 2014) united states recessions and soaring inflation and the subsequent slowdown in productivity and for stagflation (a combination of inflation and economic stagnation which occurred during the 1970s) have been largely attributed to oil price shocks (kilian, 2014). changes in monetary policy associated with far-reaching labour market adjustments as well as for energy technologies changes have also been attributed to oil price shocks. most of the extant studies on oil price fluctuations focused on crude oil prices in the upstream sector. while the upstream sector prices impact on the prices on refined products in the downstream sector, it is the price increases in the downstream petroleum sector occasioned by gradual removal of petroleum subsidies that has been largely responsible for most of the increases in the prices of petroleum products. specifically, the nigerian government has been involved in deregulation policy in the downstream petroleum sector which requires withdrawal of petroleum subsidy. withdrawal of petroleum subsidy often stimulates increases in the prices of petroleum products and hence, increases in transportation cost and prices of other commodities. thus, there is a linkage between the oil sector and every other sector in the nigerian economy. to this end, the dearth of literature on downstream sector and fluctuations in the prices of petroleum products is seen as a gap in literature. this study seeks to feel this gap. thus, the intention was to investigate the extent to which withdrawal this journal is licensed under a creative commons attribution 4.0 international license inegbedion, et al.: petroleum subsidy withdrawal, fuel price hikes and the nigerian economy international journal of energy economics and policy | vol 10 • issue 4 • 2020 259 of petroleum subsidies influence increases in sectorial prices in nigerian economy. this study sought to investigate the effect of petroleum subsidy withdrawals on the prices of petroleum products and the degree of influence of fuels price hikes on the other sectors of the nigerian economy by estimating the extent to which such fuel price hikes impact on the prices of other sectors of the economy using the input-output model of the nigerian economy. 2. literature review the nigerian economy is largely dependent on the oil sector and so oil price fluctuations and the direction of such fluctuations are of significant concern to policy makers and other stakeholders alike because such fluctuations influence the prices of refined products in the downstream sector. 2.1. oil price fluctuations and its causes changes or fluctuations in oil prices have been defined as the barometer of worldwide economy whose importance transcends the political and economic circle in every country (lingyu, 2012). oil price volatility has been attributed to so many factors ranging from instability in the major oil producing countries in the middle-east occasioned by wars; as well as the interactive forces of demand and supply of crude oil in the world oil market; others include, the decisions of the organisation of oil exporting countries (opec), as well as economic fluctuations consistent with business cycles. merino and ortiz (2005) used traditional approach to evaluate why there was a slim margin between demand and supply in the oil market. he argued that oil inventories should reflect the interaction between supply and demand forces with a view to making meaningful contribution to explaining the changes in oil prices in the world market. there is no gainsaying that crude oil is the driving force of modern economics and when oil producing countries demand for increases in oil prices; unforeseen economic developments could, in principle, stir crude oil markets and stimulate volatility in oil prices (eryiğit, 2009). this was the case with the unforeseen sudden movements in energy demand from china and india, which culminated in the exhaustion of worldwide crude oil safety stocks and the decline in the value of the u.s dollar vis-à-vis the currencies of her international trading partners are some examples (guo and kliesen, 2005). oil price fluctuation has also been attributed to the dwindling of the world crude oil reserve. other causes of price fluctuations include political instability in the producing countries, decisions on the quota system of opec, as well as panic buying and selling to forestall the consequences of stochastic eventualities (pirog, 2004). whereas physical disruptions of supply have been attributed to historical oil price shocks, the oil price build-up of 2007-2008 was caused by the inability of supply (world production) to match up with demand (hamilton, 2009; and cale, 2004). violent oil price movements have been attributed to the oil market’s way of seeing the state of solidarity of the organisation of oil producing countries as well as the anticipated interactions between demand and supply of futures markets (mabro, 2001). the activities of various militant groups in oil producing countries of the world and middle-east crisis have also influenced oil price fluctuations; some examples include the concerns about violence in nigeria and algeria owing to persistent attacks on oil facilities by militants as well the iraqi war (lee et al., 1996), among others. 2.2. oil and the macro economy owing to the heavy dependence on crude oil earnings by many countries, including nigeria, the relationship between oil production and prices, especially the dependence of oil prices on real output has received considerable attention in recent times. this is easily attributable to the realisation that oil price increase is inversely proportional to gdp growth and directly proportional to production costs  (papapetrou, 2009) empirically showed that the degree of inverse relationship between oil prices and economic activity is enhanced during periods of swift changes in oil price and high oil price volatility. despite numerous debates on the possible consequences of oil price volatility, empirical evidence suggests lack of a general consensus on the exact economic consequences of oil price volatility (schmidbauer and kalaycioglu, 2008). gronwald et al. (2009) found that global economic development as well as power and speculative behaviour of opec, which makes oil stochastic; are the main factors that influence oil prices. because of the heavy dependence on oil by many countries, oil prices are crucial to the movements of many macroeconomic variables and therefore very significant to the macroeconomy (ewing and thompson, 2007). consequently, oil price volatility is presumed to have have an impact on government expenditure (varjavand et al. 2008) and on stock market performance (cunado and gracia, 2004). 2.3. petroleum subsidy removal and the nigerian economy following the structural adjustment programme adopted by nigeria in 1986, part of the conditions given to nigeria by imf was the deregulation of the downstream sector, which was supposed to culminate in complete absence of government regulation of the sector. given that the sector had been fully regulated by government, it became necessary for policy makers to embark on gradual removal of petroleum subsidies, which was part of the regulation policy. however, the gradual removal of petroleum subsidies has had significant implications on fuel prices and transport cost and attendant increases in prices of other goods. consequently, removal of fuel subsidies now has two effects; information and macroeconomic effect. each planned partial removal of subsidy sends information to the petroleum marketers; fuel dealers and transport operators shift additional cost of petroleum products to them. this prompts an increase in pump prices of petroleum products. the transport operators get the message and adjust their fairs to absorb the additional cost and subsequently, the producers in other sectors factor in the marginal transport costs into their cost of production and reflect it at a profit in their product pricing. thus each time there is news about increases in the prices of petroleum prices; it triggers a wave of price increases. the macroeconomic effect concerns the interdependency between the prices of petroleum products and cost of transportation on one hand and the cost of transportation and cost of goods on the other hand. since petroleum products are major inputs in transportation and power generation, inegbedion, et al.: petroleum subsidy withdrawal, fuel price hikes and the nigerian economy international journal of energy economics and policy | vol 10 • issue 4 • 2020260 increases in petroleum product trigger increases in the cost of power generation and transportation and subsequently lead to increases in the cost of goods. 2.4. empirical review akinyemi et al. (2017) analysed the impact of refined petroleum subsidy removal on the agricultural sector in nigeria, the results support a complete removal of fuel subsidy for better performance of the agricultural sector. olaniyi (2016) investigated the effects of fuel subsidy on transport costs and transport rates in nigeria. he observed that fuel subsidy is a major tool for enhancing citizen’s welfare, especially among the middle and low income countries but that removal of fuel subsidies significantly influence the factors that influence transport costs and transport rates, thus leading to higher transport cost and rates. obo et al. (2017) investigated fuel subsidy removal and the ubiquity of hardships in nigeria. they opined that removal of fuel subsidy has dire consequences on the wellbeing of the people. according to them, fuel subsidy removal can stimulate the promotion of the public good if such removal is well-articulated, managed and targeted. they suggested the need to put an end to the importation of refined petroleum products in nigeria. kilian (2014) “investigated oil price shocks: causes and consequences.” he observed real price of oil originate from economic fundamentals and that oil price shocks do not occur under normal circumstances. to this end the need to explicitly explain the changes in demand and supply which are may explain oil price shocks when studying their transmission to the domestic economy becomes inevitable. he therefore suggested the use of structural models of the global economy explaining the relationships between oil price fluctuations and the economy, including the oil market. lorussoa and pieronib (2018) investigated the “causes and consequences of oil price shocks on the uk economy.” they assessed the consequences of oil price fluctuations on the uk economy by employing a method which permitted the decomposition of oil price fluctuations from the root causes of the shock. they found that different types of oil shocks were responsible for the consequences that oil price fluctuations had on macroeconomic aggregates in the uk and that a rise in real oil price causes increases in domestic inflation. fueki et al. (2018) investigated “the role of expectations in the crude oil market on oil price shocks and their consequences” they employed structural vector autoregressive model to examine the factors that were crucial to oil price fluctuations by assessing the extent to which expectations influenced future aggregate demand and supply of crude oil. the results showed that future demand and supply shocks explain about 30-35% of historical oil price fluctuations. lee and ni (2002) showed in a seminal finding, that almost all u.s. industries experience oil price shocks which manifest largely through reduction in demands. jo et al. (2017) re-examined “industry effects of oil price shocks” by re-examining lee and ni’s (2002) seminal finding by updating the data with two additional decades and employed enhanced empirical methods, including structural factor-augmented vector autoregressions. the results were consistent with those of lee and ni (2002). obi et al. (2016) investigated “oil price shock and macroeconomic performance in nigeria” using annual data from the 1979 to 2014. the study was underpinned by unrestricted vector auto regression model by sims (1980). the relationship between oil price changes and inflation rate, gross domestic product (gdp) and real exchange rate were estimated by the model. the speed of adjustment of the variables from the short run dynamics to the long run was examined using the vector autoregressive model. a given change in oil price was found to yield more than proportionate change in real exchange rate, interest rate and gdp in nigeria. 3. research methods 3.1. model formulation this study utilized the input-output model; specifically, it utilized the open input-output model. thus, x+y = d (1) y = ax (2) equations (i) and (ii) imply that x+ax = d (3) equation (iii) implies that x(i–a) = d. thus, x = (i–a)-1d (4) where y = inputs into the various industries or sectors x = outputs from the various industries d = vector of final demand. in this model, x = prices of the outputs from all the industrial sectors under focus, including the oil sector a = input – output matrix d = value added in each of the sectors. the basic assumptions of the input-output model, being the major model in this study, are as follows: i. all sectors produce according to the leontief (fixed coefficient) production function. therefore, there are constant returns to scale in the use of all factors of production and there is no substitution between any pair of inputs ii. the production process is irreversible. this assumption implies that inputs cannot be recovered from the outputs; to this end, there are no negative outputs iii. there is excess supply of labour and there is no appreciable capacity constraint in the various sectors of the economy iv. prices are set by producers so as to cover all costs, that is, per unit cost of intermediate inputs, per unit wage cost, per unit operating surplus, per unit depreciation allowance, as well as per unit indirect taxes less per unit subsidies v. all firms in each industry or sector use the same technology in the production of their various commodities vi. production in certain sectors requires locally produced and imported intermediate inputs vii. there is no price discriminatory practice on the part of the products, thus implying that all users of a given output pay the same cost-determined price (inegbedion, 2012). inegbedion, et al.: petroleum subsidy withdrawal, fuel price hikes and the nigerian economy international journal of energy economics and policy | vol 10 • issue 4 • 2020 261 3.2. the quantity model using the above assumptions, production can be described by the following equations: q = y+c+i+g+x–m (7) where q = n × 1 vector of sectorial gross output y = n × 1 vector of sectorial inputs c = n × 1 vector of sectorial household consumption expenditure i = n × 1 vector of sectorial investment expenditure g = n × 1 vector of sectorial government expenditure x = n × 1 vector of sectorial exports m = n × 1 vector of sectorial imports. also y = aq (ii), where a = n × n matrix of technical coefficients. to this end, equations (i) and (ii) can be re-stated as: q = aq+c+i+g+x–m (8) also mc = h’q’ where mc is = 1 × n vector of sectorial complementary imports; h’ = 1 × n vector of sectorial per unit complementary imports. from (iii) q–aq = c+i+g+x–m i.e. q (i–a) = c+i+g+x–m. therefore, q = (i–a)-1(c+i+g+x–m) (9) mc = h’q (10) the matrix (i–a)-1 is the leontief inverse matrix which measures the full effects of changes in any or a combination of the final demand elements like household consumption expenditure, investment expenditure, as well as government consumption expenditure on sectorial outputs. however, in this study, d represents the value added in each of the sectors or industries. the effect of changes in any of the final demand elements is obtained as follows: suppose there is a change in the vector of investment expenditure then, the effect of such a change on sectorial outputs is determined by: ∆q = (i–a)-1 ∆i and equation (i) becomes ∆mc = h∆ i 3.3. the price model value added per unit = v x j i , where xj = output in the j th sector vj = value added in the j th sector pj = (i–a) -1 v x j i where pj = unit price in the jth sector the above price equation can be used to measure the sectorial price effects of a change in sectorial per unit price. suppose there is a uniform reduction in sectorial subsidies, then the effect of such a change in sectorial subsidies on sectorial prices can be determined as: ∆ p = (i–a)-1 ∆v where ∆v = change in value added per sector as a result of change in subsidy the above equation measures the full (direct and indirect) sectorial price effects of a uniform reduction in sectorial subsidies. 4. findings nigeria’s input – output table is a 32 × 32 matrix. however, given that elements representing sectors that are not interdependent are zero coupled with the need to ease computation, the matrix was consolidated to obtain a 4 × 4 matrix. the original (32 × 32) matrix is attached as appendix. agriculture, livestock, fishing, and forestry were collapsed into agriculture; crude petroleum and refineries – oil; transport retained its status; all the remaining twenty-five were collapsed to form “others.” the resulting matrix is presented below (table 1): a = 0.08 0 0 0.04 agric oil transport others agric oil transport others 00.02 0.016 0.024 0.03 0.03 0.27 0.02 0.45 0.06 0.01 0.014 0.20               i a = agric oil transport others agric oil transport oth − −0 92 0 0 0 04. . eers − − − − − − − − − 0 02 0 984 0 024 0 03 0 03 0 27 0 98 0 45 0 06 0 01 0 0 . . . . . . . . . . . 114 0 80.               i a agric oil transport others = agric oil transport o − − −1 0 92 0 0 0 04. . tthers − − − − − − − − − 0 02 0 984 0 024 0 03 0 03 0 27 0 98 0 45 0 06 0 01 0 . . . . . . . . . . .. .014 0 80 1               − i a agric oil transport others agric oil transpo − =−1 1 10 0 001 0 001. . . rrt others 0 055 0 027 1 024 0 260 0 0543 0 079 0 2904 1 040 0 5980 0 . . . . . . . . . .. . . .084 0 0180 0 0185 1 2653               table 1: outputs of various sectors (n billion) sector output (x) (%) agriculture 39273.94 41.72 oil 15073.78 16.01 transport 1361.07 1.45 others 38436.17 40.83 source: central bank of nigeria (2015) inegbedion, et al.: petroleum subsidy withdrawal, fuel price hikes and the nigerian economy international journal of energy economics and policy | vol 10 • issue 4 • 2020262 x = d =i a sector agriculture oil transport others output 39273.94 − −1 115073.78 1361.07 38436.17               sectorial inputs ax= 0 08 0 02 0 03 0 06 0 0 016 0 27 0 01 0 0 024 0 0 . . . . . . . . . 22 0 014 0 04 0 03 0 45 0 20 39273 94 15073 78 1361 07 . . . . . . . .             338436 17.             value added per unit = v x thus, v = 0.81 0.70 0.94 0.28             value added per unit agriculture oil trans = = v x 0 810 0 704 0 940. . . pport others 0 280.     unit price per sector = i a v = agric oil transport others 1. -1−( ) 110 0.027 0.079 0.084 0.001 1.024 0.2904 0.0180 0.001 0.260 1.040 0.01185 0.055 0.0543 0.5980 1.2653 0.81 0.70 0.94 0.2                 88             =           agric oil transport others 0.9001 0.7778 1.4085 0.4519   the above are the unit prices of the outputs in the various sectors 4.1. effect of a 10% reduction in oil subsidy on the prices of products from other sectors a reduction in oil subsidy will automatically lead to an increase in the prices of oil products and hence provoke an increase in value added in all sectors as well as increase value added in the oil sector proportionately. for simplicity sake, we assume that x% reduction in oil subsidy will trigger x% increase in the prices of petroleum products. using the oil input required in each sector as a standard, the increase in value added in all the sectors will be obtained as: p i a v 1= ( ) =−− 1 10 0 027 0 079 0 084 0 001 1 024 0 2904 0 0180 0. . . . . . . . .. . . . . . . . .001 0 260 1 040 0 0185 0 055 0 0543 0 5980 1 2653 0            999 0 86 1 41 050 . .             = agric oil transport others 1.12 1.30 2.13 0.78             new sector prices p i a v 1= ( ) =−− 1 10 0 027 0 079 0 084 0 001 1 024 0 2904 0 0180 0. . . . . . . . .. . . . . . . . .001 0 260 1 040 0 0185 0 055 0 0543 0 5980 1 2653 1            008 0 94 2 63 054 . .             = agric oil transport others 1.22 1.70 3.42 0.84             p i a v 1= ( ) =−− 1 10 0 001 0 001 0 055 0 027 1 024 0 260 0 5043 0 . . . . . . . . .0079 0 2904 1 040 0 5980 0 084 0 0180 0 0185 1 2653 1 . . . . . . . .            117 170 3 42 0 84 . .             = agric oil transport others 1.32 1.84 3.70 0.92             p i a v 1= ( ) =−− 1 10 0 001 0 001 0 055 0 027 1 024 0 260 0 0543 0 . . . . . . . . .0079 0 2904 1 040 0 5980 0 084 0 0180 0 0185 1 2653 1 . . . . . . . .            226 1 092 3 07 0 63 . . .             = agric oil transport others 1.42 1.98 3.99 0.98             p i a v 1= ( ) =−− 1 10 0 001 0 001 0 055 0 027 1 024 0 260 0 0543 0 0 . . . . . . . . . 779 0 2904 1 040 0 5980 0 084 0 0180 0 0185 1 2653 1 3 . . . . . . . .            55 1 17 3 29 0 68 . . .             = agric oil transport others 1.53 2.13 4.23 1.06             4.2. discussion of findings the table of flow of goods is presented in table 2. from this table, the value added and the sectorial prices are computed (table 3). from the results in table 3 the sectorial prices are computed using the sectorial value added and matrix of interdependency ((i–a)-1). based on these initial sectorial prices, the impacts of subsequent removal of petroleum subsidies (10%, 20%, 30%, 405 and 50%) are considered (tables 4-13). the analyses of the impact of petroleum subsidies removal on sectorial price changes indicate that a 10% reduction in petroleum subsidy will lead to 26.6%, 66.7%, 51.1%, and 68.9% increases in the sectorial prices of agriculture, petroleum products, transport and other sectors, thus leading to significant reduction in the purchasing power of the inegbedion, et al.: petroleum subsidy withdrawal, fuel price hikes and the nigerian economy international journal of energy economics and policy | vol 10 • issue 4 • 2020 263 local currency (tables 4 and 5). in the same vein, a 20% reduction in petroleum subsidy will lead to 35.6%, 117.7%, 142.6%, and 86.7% increases in the sectorial prices of agriculture, petroleum products, transport and other sectors (tables 6 and 7). also, a 30% reduction in petroleum subsidy will lead to 46.7%, 135.9%, 158.2%, and 104.4% increases in the sectorial prices of agriculture, petroleum products, transport and other sectors (tables 8 and 9). similarly, a 40% reduction in petroleum subsidy will lead to 57.8%, 154.0%, 183.0%, and 117.8% increases in the sectorial prices of agriculture, petroleum products, transport and other table 2: table of flow of goods with a row of value added (shows a flow of sectorial outputs to the inputs of other sectors) input/output agriculture oil transport others demand total agriculture 3142 0 0 1538 34594 39273.94 oil 786 241 33 1153 12864 15073.78 transport 1178 4070 27 17296 21210 1361.07 others 2356 151 19 7687 28223 38436.17 value added 31811 10612 1282 10762 total 39273 15073.78 1361.07 38436.2 table 3: value added in the major sectors of the nigerian economy sector value added per unit agriculture 31811 39273 =0.810 oil 10612 15073 78. =0.704 transport 1282 1361 07. =0.942 others 10762 38436 2. =0.280 table 4: increase in value added due to 10% reduction in petroleum subsidy (10% increase in value added) sector increase in value added agriculture 1.1×0.90=0.99 oil 1.1×0.78=0.86 transport 1.1×2.19=1.41 others 1.1×0.45=0.50 table 5: change in prices due to 10% reduction in petroleum subsidy (10% percent increase in prices of petroleum products) sector old price new price change in price percentage change agriculture 0.90 1.12 0.22 26.6 oil 0.78 1.30 0.52 66.7 transport 1.41 2.13 0.72 51.1 others 0.45 0.78 0.31 68.9 table 6: effect of a 20% reduction in petroleum subsidy on the sectorial value added and prices of products from other sectors (20% percent increase in value added) sector increase in value added agriculture 1.2×0.90=1.08 oil 1.2×0.78=0.94 transport 1.2×2.19=2.63 others 1.2×0.45=0.54 table 7: change in prices due to 20% reduction in petroleum subsidy (20% increases in petroleum prices) sector old price new price change in price percentage change agriculture 0.90 1.22 0.32 35.6 oil 0.78 1.70 0.92 117.7 transport 1.41 3.42 2.01 142.6 others 0.45 0.84 0.39 86.7 table 8: effect of a 30% reduction in oil subsidy on the sectorial value added and prices of products from other sectors (30% increase in value added) sector increase in value added agriculture 1.30×0.90=1.17 oil 1.30×0.78=1.014 transport 1.30×2.19=2.85 others 1.30×0.45=0.59 table 9: change in prices due to 30% reduction in petroleum subsidy (30% increases in prices of value added) sector old price new price change in price percentage change agriculture 0.90 1.32 0.42 46.7 oil 0.78 1.84 1.06 135.9 transport 1.41 3.70 2.23 158.2 others 0.45 0.92 0.47 104.4 table 10: effect of a 40% reduction in oil subsidy on the sectorial value added and prices of products from other sectors (30% increase in prices of value added) sector increase in value added agriculture 1.40×0.90=1.26 oil 1.40×0.78=1.092 transport 1.40×2.19=3.07 others 1.40×0.45=0.63 table 11: change in prices due to 40% reduction in petroleum subsidy (40% increases in the prices of petroleum products) sector old price new price change in price percentage change agriculture 0.90 1.42 0.52 57.8 oil 0.78 1.98 1.20 154.0 transport 1.41 3.99 2.58 183.0 others 0.45 0.98 0.53 117.8 inegbedion, et al.: petroleum subsidy withdrawal, fuel price hikes and the nigerian economy international journal of energy economics and policy | vol 10 • issue 4 • 2020264 sectors (tables 10 and 11). lastly, a 50% reduction in petroleum subsidy will lead to 70.0%, 173.1%, 202.8%, and 177.8% increases in the sectorial prices of agriculture, petroleum products, transport and other sectors (tables 12 and 13). the foregoing analysis shows that the unending deregulation of petroleum products has brought untold hardships to the citizens of nigeria because of the vicious circle of price increases and the low purchasing power of the currency arising from the devaluation of the naira (the local currency) which is often the major reason for removal of fuel subsidies. results are consistent with lee and ni (2002), akinyemi et al. (2017), obo et al. (2017).as well as lorussoa and pieronib (2018). 4.3. proposed model of petroleum subsidies and the nigerian economy based on the findings, a model of petroleum subsidy removal and the nigerian economy is proposed with a view to explaining the relationship between petroleum subsidy removal and the products of the other sectors of the nigerian economy (figure 1). the model shows that a partial removal of fuel subsidy will cause an increase in the prices of petroleum products which serve as inputs to the transport sector and generating systems. since the end products of the agricultural and manufacturing sector as well as all the other sectors have to be transported to the end consumers, increase in transport cost will stimulate increases in the prices of the products from the agricultural sector and the manufacturing sector as well as all the other sectors of the economy. thus, partial removal or complete removal of petroleum subsidy leads to increases in transport cost, which culminate in increases in the prices of agricultural products, manufactured products and prices of products from other sectors. 5. conclusions and policy implications 5.1. conclusions all the sectors in any economy and the nigerian economy in particular, are interdependent since the outputs of a given sector in one period may serve as input requirement for one or more sectors of the economy’s production in another period. the interdependency of the sectors of the nigerian economy as portrayed by the input-output matrix (matrix of technological coefficients) shows that all the sectors of the economy are significantly dependent on the oil sector, increases in the prices of petroleum products, through the removal of oil subsidy, leads to significant increases in transport fares and thus cause increases in the cost of production since transport cost is part of the distribution cost of products. the associated spate of increases lead to a fall in the purchasing power of the local currency (naira) thus precipitating a fall in the standard of living. lastly, removal of fuel subsidies has information and macroeconomic effects. this study has made significant contribution to knowledge in the management science and economics literature by demonstrating how the interdependency among the sectors and the dependence of the economy on the oil sector influences price increases each time oil prices increase. although empirical studies abound on the impact of oil price shocks and oil price fluctuations on economic growth, most of those studies employed econometric models to analyse their data. specifically, most of these models focused on oil price shocks and the impacts of such shocks on the macroeconomic variables such as gdp, inflation rate, exchange rate as well as stock market returns like all-share index and market capitalisation. this study is about the only one that employed the input-output matrix and concept of “table of flow of goods and value added” to explain the impact of crude oil price changes, through oil subsidy removal, on the prices of other sectors of the economy. besides, this study is the only one that has disintegrated fuel subsidy removal into information and macroeconomic effect. the study is thus unique in these respects. the study is not without limitations which indicate the need for future studies to rectify the observed shortcomings. a major limitation to the results of this study bothers on the validity of the input-output table of the nigerian economy, which is obviously outdated. the input-output table is that of 1991. this table is 28 years behind schedule. this development was informed by the central bank of nigeria’s inability to publish any input-output table since 1991. since no system is static, the relationships between the thirtytwo sectors of the nigerian economy must have changed since the last input-output matrix was published. if that be the case, a new table 12: effect of a 50% reduction in oil subsidy on the sectorial value added and prices of products from other sectors (50% increase in value added) sector increase in value added agriculture 1.50×0.90=1.35 oil 1.50×0.78=1.17 transport 1.50×2.19=3.29 others 1.50×0.45=0.68 table 13: change in prices due to 50% reduction in petroleum subsidy (50% increases in the prices of petroleum products) sector old price new price change in price percentage wschange agriculture 0.90 1.53 0.63 70 oil 0.78 2.13 1.35 173.1 transport 1.41 4.27 2.86 202.8 others 0.45 1.25 0.80 177.8 partial removal of petroleum subsidy increase in the prices of agricultural sector products increase in the prices of manufacturing sector products increase in the prices of other sector products increases in cost of petroleum products increase in transport fares figure 1: proposed model of petroleum subsidies and the nigerian econom inegbedion, et al.: petroleum subsidy withdrawal, fuel price hikes and the nigerian economy international journal of energy economics and policy | vol 10 • issue 4 • 2020 265 input-output (technological coefficients) matrix ought to have been published to capture this relationship. a current input-output table will be more reliable in capturing the interdependency between the sectors of the nigerian economy. however, in the absence of an updated matrix, the old input-output matrix can still be relied on to present the desired inter-sectorial such as in this study. it is suggested that future studies employ current input-output tables when they become available. another limitation of the study is the assumption that a given percentage reduction in subsidy (x%) will trigger the same percentage increase in value added and prices of petroleum products. in practice, the percentages may vary. the use of the same percentage was informed by the need to avoid complexities 5.2. policy implications the federal government through the central bank of nigeria and other policy makers should take note of the devastating negative impacts of oil price changes on the citizens through the drastic reduction in their purchasing power each time there is a reduction in petroleum product subsidy. while devaluation may yield marginal increases in government revenues, the trade-off between these marginal returns and the gross loss in earnings by the productive factors in the country is often negative since nigerian economy is not an export driven economy. given that the national income of the country is a function of the earnings of all the productive factors in the country, due cognisance should be taken of any government policy that will impact negatively on the purchasing power of the people. it is pertinent for policy makers in government to also be mindful of the fact that economic development is a function of the extent to which the citizens have access to the basic necessities of live and that access to these basic necessities is influenced by the purchasing power of the local currency (naira). to this end, petroleum subsidy removal should be hinged on the provision of adequate financial measures to ensure that the impact of such removal does not erode the purchasing power of the local currency. such measures may include but are not limited to price controls, minimum wage review and/or government massive investment in food products to be sold at very affordable prices when such subsidy withdrawals occur. alternatively, complete removal of petroleum subsidy should be done once to forestall the negative implications once. 6. acknowledgment we express our profound gratitude to the management of landmark university for taking full responsibility for the sponsorship of this study references akinyemi, o., alege, p.o., ajayi, o.o., adediran, o.s., urhie, e. (2017), a simulation of the removal of fuel subsidy and the performance of the agricultural sector in nigeria using a dynamic computable general equilibrium approach. covenant journal of business and social sciences, 8(1), 60-70. amaiquema, j.r.p., amaiquema, a.r.p. (2017), consequences of oil and food price shocks on the ecuadorian economy. international journal of energy economics and policy, 7(3), 146-151. cale, m. (2004), the price of oil. available from: http://www.eia.doe. gov/emeu/ipsr/t24.xls. central bank of nigeria. (2015), annual report. available from: http:// www.cbn.gov.ng. cunado, j., gracia, f.p. (2004), oil prices, economic activity and inflation: evidence for some asian countries. the quarterly review of economics and finance, 45(1), 65-83. eryiğit, m. (2009), effects of oil price changes on the sector indices of istanbul stock exchange. international research journal of finance and economics, 25, 209-216. ewing, b.t., thompson, m.a. (2007), dynamic cyclical co-movements of oil prices with industrial production, consumer prices, unemployment, and stock prices. energy policy, 35(11), 5535-5540. fueki, t., higashi, h., higashio, n., nakajima, j., ohyama, s., tamanyu, y. (2018), identifying oil price shocks and their consequences: the role of expectations in the crude oil market. washington, dc: a bank of japan working paper, no. 725. gronwald, m., mayr, j., orazbayev, s. (2009), estimating the effects of oil price shocks on the kazakh economy. munich: info working paper no. 81, institute for economic research at the university of munich. guo, h., kiensen, k. (2005), oil price volatility and us macroeconomic activity. federal reserve bank of st. louis review, 67, 669-684. hamilton, j.d. (2009), causes and consequences of the oil shock of 2007-08. brookings papers on economic activity, 40(1), 215-283. inegbedion, h.e. (2012), oil price hike. kg. and the nigerian economy. saarbrucken, germany: lap lambert academic publishing. gmbh & co jo, s., karnizona, l., reza, a. (2017), industry effects of oil price shocks: re-examination. federal reserve bank of dallas working paper. available from: https://www.dallasfed.org/-/media/ documents/research/papers/2017/wp1710.pdf. kilian, l. (2014), oil price shocks: causes and consequences. annual review of resource economics, 6, 133-154. lee, k., ni, s. (2002), on the dynamic effects of oil price shocks: a study using industry level data. journal of monetary economics, 49, 823-852. lee, s., sung, h., urrutia, j. (1996), the impact of the persian gulf crisis on the prices of ldcs loans. journal of financial services researcher, 10(2), 143-162. lingyu, y. (2012), analysing the international oil price fluctuations and its influencing factors. available from: http://www.scirp.org/journal/ paperinformation.aspx? lorussoa, m., pieronib, l. (2018), causes and consequences of oil price shocks on the uk economy. economic modelling, 72, 222-236. mabro, r. (2001), does oil price volatility matter? oxford: oxford institute energy studies, energy comment. merino, a., ortiz, a. (2005), explaining the so-called “price premium” in oil markets. opec review, 29 (2), 133-152. obi, b., awujola, a., ogwuche, d. (2016), oil price shock and macroeconomic performance in nigeria. journal of economics and sustainable development, 7(24), 137-145. obo, u.b., omenka, j.i., agishi, t.v., coker, m.a. (2017), fuel subsidy removal and the ubiquity of hardship in nigeria. advances in social sciences research journal, 4(14), 113-126. olaniyi, a.a. (2016), effects of fuel subsidy on transport costs and transport rates in nigeria. journal of energy technologies and policy, 6(11), 1-9. pirog, r. (2004), natural gas prices and market fundamentals crs report for congress congressional research service. united states: crs. schmidbauer, h., kalayco, e. (2008), crude oil and oil-related turkish company stocks: a volatility analysis. in: international conference on economic modeling. istanbul, turkey: istanbul bilgi university. sims, c.a. (1980), macroeconomics and reality. econometrics, 48(1), 1-48. varjavand, r., navid, n., emami, k. (2008), effect of oil price volatility on government expenditures in iran. international journal of business research, 8(5), 1-8. . international journal of energy economics and policy | vol 9 • issue 4 • 2019224 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(4), 224-232. implementation of efficient energy policy in russia: energy consumption monitoring and problem analysis rustam z. mukhametshin1,2*, nina i. kryukova3, alexandra v. beloborodova4, aleksandr v. grinenko5, olga v. popova6,7 1kazan (volga region) federal university, kazan, russia, 2ural state university of economics (usue), yekaterinburg, russia, 3plekhanov russian university of economics, moscow, russia, 4i. m. sechenov first moscow medical university (sechenov university), moscow, russia, 5moscow state institute of international relations (mgimo university), moscow, russia, 6financial university under the government of the russian federation, moscow, russia, 7russian state university of humanities, moscow, russia. *email: geoeng111@yandex.ru received: 28 february 2019 accepted: 12 may 2019 doi: https://doi.org/10.32479/ijeep.7967 abstract the implementation of an efficient energy policy in russia as an integral part of the social and economic strategy as a whole gives a high profile to the issues of energy consumption monitoring. the importance of the energy sector to the industrial development of all russian regions requires close attention to the accounting and rational use of energy resources in order to reduce the energy dependence of all industries and make russian economy less energy-intensive whilst more energy-efficient. the analysis of strategic documents in the field of energy saving proves the importance of the russian federation, which is one of the leaders of the world energy sector. the purpose of the article is to study the energy aspects of energy consumption in the regions of the russian federation, to conduct their comparative analysis and evaluation, and to identify problems in the supply of energy resources. the methods of research applied to study this problem include data collection and synthesis methods; a balance method; a time-series method; tabular and graphical methods of the study results visualization. the article presents the dynamics of electricity consumption in the regions of the russian federation broken down by federal districts and macro-regions set out in the russian federation spatial development strategy; also, the consumption balance by types of energy resources is provided for various fuels. in addition, it provides a brief description of the russian integrated power system operation reflecting the generation and consumption of electricity among the main power systems of the country. based on the analysis of russia’s energy development forecast, using scenario approaches, the article concludes that the energy efficiency of the national economy requires improvement and there is a need to implement energy-saving projects. the information contained herein is of practical value for the professionals involved in the analysis and evaluation of energy resources consumption and assessment of their contribution to the national economy. the results of the study reveal fundamental differences in the consumption and use of energy resources throughout russia’s regions. keywords: energy resources monitoring, energy consumption, energy security, energy saving, energy strategy jel classifications: d24, q43, m31 1. introduction the problem of energy consumption remains today one of the most important issues in maintaining the activity and security of the global and, in particular, russian economy. the current stage of the global economy development is characterized by instability, recurring crisis phenomena, trade wars emerging from time to time, etc. undoubtedly, the hot spots emerge on the planet driven by the growing demographic problem and the related shortage of food and raw material resources, as well as changes in the world energy demand structure and energy consumption patterns. according to the un (world population prospects, 2015), this journal is licensed under a creative commons attribution 4.0 international license mukhametshin, et al.: implementation of efficient energy policy in russia: energy consumption monitoring and problem analysis international journal of energy economics and policy | vol 9 • issue 4 • 2019 225 the world population will be 8.5 billion people by 2030 (mainly driven by the african continent and developing asian countries), and by 2050-9.7 billion, while in 2100, the earth’s population will be 11.2 billion people. the importance of russia’s role in the world economy is determined by the following facts: (1) it occupies a vast area of the globe, through which major transport routes pass providing economic connections between the regions of the world; (2) there are significant amounts of oil and gas reserves revealed; energy resources, including hydrocarbons and nuclear materials, are produced in the country. according to rbc (2019), which published the estimates of the ministry of natural resources and environment of russia, the total cost estimate of all resources (mineral and energy) according to the 2017 calculations amounted to 60% of the national gdp (gdp of the leading countries of the world in 2018, 2018). however, with the average gdp growth rate for russia, its share in the world gdp according to the probable scenario of the 2040 world and russia’s energy development forecast will be 2.7% (the forecast for the development of the world’s energy industry and russia up to 2040, 2014). according to the international monetary fund, russia has quite a considerable share in the world gdp: it ranks 11th in nominal gross domestic product and is among the world’s top 20 largest economies (gdp of the leading countries of the world in 2018, 2018). threats to the russian economy in various areas, where energy sector is a priority, are outlined in the 2030 national economic security strategy (the strategy of russia’s economic security for the period to 2030, 2017). the implementation of the energy policy of the russian federation is an integral part of the economic security strategy. the latter, in turn, is aimed at strategic planning of the development of economic potential of the country, as a whole, and its regions. 2. literature review russia’s development prospects until 2030 in the field of national energy are set out in russia’s energy strategy (the energy strategy of russia for the period up to 2030, 2009). the strategy sets out the key focus areas that indicate the vector of russia’s development in the field of energy consumption. these are aspects of the economic structure transformation in order to reduce the portion of energy-intensive industries using the energy saving potential; transformation of the electricity consumption geography in the country, which manifests itself through the shift of power consumption centers towards the eastern economic zone and the cities of the european part of russia. the strategy also sets the task to reduce imbalance, both in the energy consumption structure and in the energy security of different regions of the country. the analysis of the results of the power sector reform (analysis of the results of the reform of the power industry and proposals for increasing its efficiency: an analytical report, 2013) conducted by the institute of natural monopolies research showed that the worst aspect of the reform was “the growth of electricity prices for end consumers.” this has led to increasing electricity arrears among the retail consumers. analysts believe that the main problem of the russian electric power industry is low state regulation efficiency, which is particularly acute at the regional level. in this context, a significant number of consumers do not have the opportunity to choose an electric power company, as there are no alternative suppliers. in view of the above, electric power companies become local monopolies within certain geographical boundaries. the article by myznikova (2016) presents regional aspects of electricity generation and consumption, using the case of the republic of tatarstan as an example. the author studies the consumption structure in the region, where statistical data proves the prevailing role of industry (the industrial sector consumes 64% of all electricity in the region). in addition, the author touches upon topical issues of energy management, which, according to the author, does not focus enough on the structural changes in local energy consumption, neither are risks and uncertainty taken into account when making investment decisions aimed at the development of the electric power industry. the study of the electricity consumption issues taking into account the growing demand from the population requires the development of a system aimed at energy saving and overall improvement of russia’s energy efficiency at all levels: national, regional and municipal. the enacted law on energy saving (on energy saving and on increasing energy efficiency, and on introducing amendments to certain legislative acts of the russian federation: federal law of the russian federation n 261-fl, 2009) provides the legal basis for regulation and promotion of energy saving activities in russia. the need to implement energy saving programs determines the introduction of energy saving technologies that make energy consumption more efficient. economic assessment of energy-saving projects is provided in the works of kvon et al. (2016), kvon (2018) and bessel (2013) that contain the methodological guidelines for substantiation and efficiency along with practical aspects of the results of the efficient technologies introduction, both at the regional level and at the national economy level in general. optimization of energy consumption brings into focus electricity consumption issues. in view of the above, there is a need for systems that would provide stakeholders with comprehensive information about the energy consumption characteristics of the facilities operated. the monitoring issues are covered in the works of such authors as vasilyeva et al. (2012), platonova and safronov (2016). these works highlight the importance of continuous energy consumption analysis with a glance to the ambient temperature, using intelligent information and measurement systems. 3. research methodology 3.1. research algorithm 1. research scope and objectives. the main purpose of this research is to identify problems in the energy resources mukhametshin, et al.: implementation of efficient energy policy in russia: energy consumption monitoring and problem analysis international journal of energy economics and policy | vol 9 • issue 4 • 2019226 supply in russia in the context of the selected objects. as the research object, we have chosen the constituent entities of the russian federation classified into different groups: these are federal districts and macro-regions that enable us to evaluate consumption and production by large groups. 2. the objectives of the study include the selection of a research method and initial data, the study of the research legal framework, conducting the analysis, and drawing conclusions. 3. analysis of publications in the field under study. in view of the strategic importance of electricity consumption and the formation of its sources, we pursued the task to substantiate the importance of the issue. to this end, we have studied the laws, strategies, and forecasts that may help assess the prospects of russian energy sector in the long term. in addition, the practical aspects of the consumption study are reflected in the publications of russian researchers that prove the importance of monitoring and evaluation of both consumption and energy-saving projects implementation efficiency. 4. selection of a research base. we have obtained information from the statistical reports prepared by regional statistical bodies of the russian federation, since they reflect the dynamics of various energy consumption indicators in the regions of the russian federation. 5. analysis and conclusions. the analysis of consumption dynamics with the use of statistical data has been carried out on the basis of the above algorithm. the analysis has revealed the problems existing in the energy consumption of the russian federation, based on a comparison of different sources in the study dynamics. comparison of statistical reporting data, legal framework, and strategic documents has suggested the importance of ongoing energy consumption monitoring and evaluation that are substantiated by the analysis. 3.2. research methods the following methods were applied in the course of the research: 1. the collection and compilation methods assume the processing (sorting, editing, and measurement), compilation and interpretation of the data. the storing assumes the classification of the data into categories and its tabulation. editing means viewing data to determine whether it can be used. measurement means comparison of objects based on their certain indicators or characteristics. data analysis and synthesis are performed with application of manual or computer processing methods using a tool for energy sector trend analysis. interpretation means identification and registering of a set of characteristics as well as processed and obtained data in order to detect and explain the main trends and clarify the meaning of the data obtained. 2. the balance method is used to study and compare power generation and consumption. the consumption reflects the demand for electricity, while the generation sets the level of fuel and energy resources production to meet this demand. for the purpose of the study, the energy balance is classified based on the following characteristics: • energy flow stages • power plants (pp) and facilities. 3. the time-series method is used to arrange numerical indicators describing the status level and changes in russia’s energy sector in time order. in our research, we have used a discretetime time series, which reflects the indicator values taken at certain points in time. a time series is a series of values that characterize a phenomenon at any given time. to analyze the dynamic time series indicators, the following parameters are used: • absolute basic increment: ∆y=yt–y1 (1) where t is the observation number; yt—series level corresponding to the t moment. y1—series level corresponding to the reference period. • reference growth rate: tр =yt/у1*100% (2) 4. tabular and graphical methods of the study results visualization the tabular method of data representation allows to present quantitative characteristics of the process studied in a structured form with explanatory text. the graphical method shows the visual change of the data reflecting the trends observed in the energy sector indicators as well as their structure and peculiar features of the classification. 4. results and discussion we consider the analysis of electricity consumption in russia in dynamics, selecting 2008—2017 as the study period. the consumption dynamics shows an increase in the resource from 1.022.7 billion kwh in 2008-1.089.1 billion kwh in 2017, figure 1: dynamics of energy consumption in russia for 2008-2017 mukhametshin, et al.: implementation of efficient energy policy in russia: energy consumption monitoring and problem analysis international journal of energy economics and policy | vol 9 • issue 4 • 2019 227 therefore, the growth is 6.5%. figure 1 provides graphics reflecting the above. however, despite the overall positive trend, consumption in 2009 shows a sharp decline (from 1022.7 billion kwh in 2008 to 977.1 billion kwh in 2009), which is 4.5% if compared to 2008. the above is the consequence of the aggravating crisis in the national economy in 2009, which, as we know, eventually resulted in a 7.9% decrease of the country’s gdp. as far as electricity consumption in russia’s regions is concerned, we will consider it based on the following principle. 4.1. distribution by federal districts the establishment of federal districts under the decree of the president of the russian federation no. 849 dd. may 13, 2000 (about the plenipotentiary of the president of the russian federation in the federal district, 2000) pursued the objectives of strengthening the statehood and simplification of russia’s governance. administration of management processes allows to perform proper control over the implementation of the federal authorities’ decisions in the regions. the consumption breakdown by these 8 districts according to rosstat data for 2017 (official statistics, 2017) is shown in figure 2. as the graph shows, the major share of consumption falls on the following federal districts: • central (20.7%) – the main consumers are moscow (the capital’s consumption accounts for 25.2% of the total consumption of the federal district) and the moscow region (21%); • siberian (20.3%) – krasnoyarsk region (23.8%), irkutsk region (24.3%), kemerovo region (16.1%); • volga region (18.3%) – republic of bashkortostan (13.9%), republic of tatarstan (14.7%), perm region (13.2%), samara region (12.6%), nizhny novgorod region (11.4%); • ural (17%) – khanty-mansi autonomous disctrict — yugra (40%), sverdlovsk region (25.9%), chelyabinsk region (19.4%). uneven power consumption and the predominance of individual regions are the result of economic zoning and the location of large energy-intensive industrial facilities in these regions. in order to assess the energy security of the regions, we have compared the data on power consumption and production by federal districts. we have made a comparative table 1 using statistical data (official statistics, 2017). the table 1 shows that there is a power generation shortage in the volga federal district (17.2 billion kwh) and the siberian federal district (9.1 billion kwh). 4.2. distribution by macro-regions the russian federation spatial development strategy for the period up to 2025 (the strategy of spatial development of the russian federation for the period up to 2025, 2019) adopted by the government of the russian federation in february 2019 divides russia into 12 macro-regions. this strategy, in accordance with the law on strategic planning (on strategic planning in the russian federation, 2014), was developed within the framework of area-based goal-setting. though the strategy was adopted in 2019, we will group russian regions depending on electricity consumption and production using the data of 2017. in our opinion, this assumption is viable, since the division of the country into macro-regions does not interfere with the functioning of industrial and non-industrial facilities. the consumption by macro-regions is shown in figure 3. it should be noted that in such classification of regions into the macro-regions these groups completely overlap the existing federal districts, such as north caucasian and southern districts — constituent regions are absolutely identical there. comparison of consumption and production in the russian federation, compiled by the authors based on the newly adopted macro-regions, is presented in table 2. the comparison of production and consumption among macroregions reveals the deficit (shortage) of electricity largely in the volga-kama and south siberian macro-regions. a small deficit is observed in the northern macro-region. in terms of russia’s constituent entities, electricity deficit is found in the following regions: • volga-kama macro-region: deficit is observed in the republic of tatarstan, the udmurt republic, nizhny novgorod region (these regions are part of the volga federal district, which (table 1) is characterized by a shortage of electricity; • south siberian — the deficit is observed in all regions of this macro-region (deficit regions are part of the siberian federal district, which also suffers from a resource deficit); • northern — includes all regions, except the republic of komi. it should be noted that, though other macro-regions are selfsufficient and their total production exceeds total consumption, there is a significant shortage of electricity within some macroregions. thus, the central macro-region shows a severe shortage in the moscow region (a deficit of 26 billion kwh) and moscow (7.7 billion kwh). in the southern macro-region, shortage is observed in the krasnodar region (11.3 billion kwh). figure 2: energy consumption distribution among the federal districts of the russian federation mukhametshin, et al.: implementation of efficient energy policy in russia: energy consumption monitoring and problem analysis international journal of energy economics and policy | vol 9 • issue 4 • 2019228 due to the limited scope of the article, the paper provides only the conclusions, since covering the information on all macro-regions for 85 constituent entities of the russian federation to support the author’s conclusions would overstuff the article. 4.3. distribution among the eastern and western macro-regions distribution among the eastern and western macro-regions, representing a high-level breakdown of russia into two zones. the eastern macro-zone, consisting of 24 russia’s constituent entities in total, includes the west siberian, east siberian, and far eastern economic regions. in terms of federal districts, these are regions of the siberian, far eastern (entirely) and, to some extent, the ural federal districts. in terms of the newly established macro-regions, these are the regions of the ural-siberian (partially), south siberian, angarayenisei and far eastern macro-regions. the consumption structure for these macro-regions (eastern and western) is shown in figure 4. table 2: comparison of electricity production and consumption in the macro‑regions of the russian federation, billion kwh macro-regions consumption production surplus (+)/deficit (−) central 173.6 173.9 0.3 central black earth region 51.5 55.1 3.6 northwestern 94.8 102.3 7.5 northern 19.1 18.6 -0.5 southern 68.7 74.1 5.4 north caucasian 24.7 26.8 2.1 volga-kama 107.4 79.6 −27.8 volga-ural 93.7 104.2 10.5 ural-siberian 185.5 194.6 9.1 south siberian 82.3 56.93 −25.4 angara-yenisei 125.1 142 16.9 far-eastern 62.9 66.1 3.2 total in russia 1,089.1 1,094.23 5.1 figure 3: energy consumption distribution among the macro-regions of the russian federation table 1: comparison of electricity production and consumption in the federal districts of the russian federation, billion kwh federal districts of russia consumption production surplus (+)/deficit (−) russian federation — total: including 1089.1 1094.2 5.1 central federal district 225.1 228.9 3.8 northwestern federal district 113.9 120.8 6.9 southern federal district 68.7 74.1 5.4 north caucasian federal district 24.7 26.8 2.1 volga federal district 201.0 183.8 −17.2 ural federal district 185.5 194.7 9.2 siberian federal district 221.5 212.4 −9.1 far eastern federal district 48.7 52.6 3.9 table 3: comparison of electricity production and consumption in two macro‑regions, billion kwh macro-regions (high‑level groups) consumption production surplus (+)/deficit (−) eastern 367.3 373.1 5.9 western 721.8 721.1 −0.8 total in russia 1,089.1 1094.2 5.1 mukhametshin, et al.: implementation of efficient energy policy in russia: energy consumption monitoring and problem analysis international journal of energy economics and policy | vol 9 • issue 4 • 2019 229 the low electricity consumption in the eastern macro-region is determined by the fact that, historically, the regions of the eastern macro-zone occupying 75% of the territory of the russian federation account for only 21% of the country’s population. the comparison of consumption and production in these two macro-regions is presented in table 3. as is seen from the figure 4 and table 3, there is imbalance in power consumption and production in the regions of the russian federation. as mentioned earlier, the objectives of the energy strategy (the energy strategy of russia for the period up to 2030, 2009) are to reduce imbalances and evaluate the prospects for the power industry development, taking into account the shift in energy consumption towards the eastern regions of russia. we would like to consider one more aspect that reflects the results of the operation of russia’s ips (integrated power systems). analysis of ips’s operations was carried out on the basis of the report on ips’s operations in 2017 (report on the functioning of the ues of russia in 2018, 2018). ips’s operations are distributed among the seven united power grids (upg). table 4 provides the balance of the distribution among upgs. table 4: energy consumption balance for russia’s main upgs item balance surplus, billion kwh consumption production billion kwh (%) billion kwh (%) russia’s ips – total: including 1,039.9 (100.0) 1,053.8 (100.0) 13.9 central upg 238.6 (22.9) 237.6 (22.5) −1 middle volga upg 108 (10.4) 107.8 (10.2) −0.2 ural upg 261.2 (25.1) 260.7 (24.7) −0.5 northwestern upg 93.9 (9.0) 108.35 (10.3) 14.45 southern upg 99.1 (9.5) 100 (9.5) 0.9 siberian upg 205.9 (19.8) 202.6 (19.2) −3.3 eastern upg 33.2 (3.2) 36.8 (3.5) 3.6 upgs: united power grids table 5: comparative characteristics of the development scenarios of the russian energy sector (makarov et al., 2016) scenarios probable scenario critical scenario optimistic scenario scenario details the scenario assumes that the current situation will not change (limited structural reforms to improve the business climate, reduction of interest rates, intensification of investments, higher government spendings on social, energy and transport infrastructure development, reducing corruption) the scenario assumes no reforms, no efforts to combat corruption in the field of government spendings, limited budget resources are spent on costly prestigious and infrastructure projects in favor of individual companies and regions. high interest rates, although inflation is lower. technological progress is limited, and efficiency growth cannot be achieved due to a combination of institutional factors the scenario assumes economic growth based on the use of competitive advantages both in traditional sectors (energy, transport, agriculture) and in new knowledge-intensive sectors and “knowledge economy”. a dramatic change in russia’s export structure is expected. the share of budget expenditures on human capital will increase (by 2030 it will grow to 13% of gdp). strengthening of the financial sector is expected along with lower interest rates and the revival of small business, since favorable conditions for the country’s institutional development are foreseen gdp growth moderate gdp growth; after 2020, the national economy will reach moderate average annual growth rate of 2.2−2.4% gdp growth slows (on average — 1.7% after 2020), and recession lasts longer national economic growth is expected to accelerate up to 3.4% per year after 2024. the shares of services, communications and innovative manufacturing industries in gdp are growing world energy prices limited energy consumption growth is expected along with growing export (prices, however, stay below the levels of 2010-2014) energy export prices are lower; high competition in energy markets; additional restrictions are expected to be imposed on russian hydrocarbons import by western countries relatively higher world energy prices boost a greater demand for russian hydrocarbons in the global markets sanction restrictions sanction restrictions remain in place, russian companies have a limited access to capital and state-of-the-art technologies sanction restrictions remain in place, russian companies have a limited access to capital and state-of-the-art technologies abolition of any sanctions, easy access to capital and state-of-the-art technologies, dramatic efficiency improvement within russia prerequisites for economic growth economic growth will depend on the results of adaptation and reforms in 2018-2024 russia’s share in world gdp decreases from 3.5 to 2.9% in 2014-2020 and cannot recover until 2040 accelerated growth is anticipated in the course of reforms and the use of national savings by business mukhametshin, et al.: implementation of efficient energy policy in russia: energy consumption monitoring and problem analysis international journal of energy economics and policy | vol 9 • issue 4 • 2019230 it should be noted that there are minor differences (in the range of 3.7-4.7%) in the production and consumption data published by rosstat and contained in the report on the ips operations. figure 4: energy consumption distribution in the eastern and western macro-regions of russia figure 5: power generation by power plants (according to 2017 data) figure 6: energy consumption by sources table 6: structure of consumed resources according to forecasts up to 2030 item energy strategy (the energy strategy of russia for the period up to 2030, 2009) world and russia’s energy sector development forecast (the forecast for the development of the world’s energy industry and russia up to 2040, 2014) (makarov et al., 2016) baseline scenario other asia probable scenario domestic consumption (million tons of conventional fuel) — total: including resources 100.00 100.00 100.00 100.00 gas 47.71 52.23 52.07 54.85 liquid (oil and condensate) 22.40 19.18 19.22 18.46 solid fuel (coal and other) 18.04 14.73 14.96 14.02 non-fuel 11.85 13.86 13.75 12.67 each upg supplies certain regions of the russian federation in accordance with the adopted list through the operation of cogeneration pp, pp, nuclear pp (npp), hydroelectric pp (hpp), wind pp (wpp) and solar pp (spp). the distribution of power generation by pp is shown in figure 5. it makes sense to resort to the russian energy sector development forecasts based on a number of expected key indicator values that were made in different periods of time. in this study, we consider the forecasts presented in the 2030 energy strategy of the russian federation (the energy strategy of russia for the period up to 2030, 2009) as well as the world and russia’s energy sector development forecast (the forecast for the development of the world’s energy industry and russia up to 2040, 2014) developed by the energy research institute of the russian academy of sciences and the analytical center under the government of the russian federation. the energy strategy contains the strategic development indicators for the mineral resource base of the fuel and energy complex as well as development indicators for various industrial sectors (oil, gas, coal, etc.). it should be highlighted that the energy sector development forecast provided in these documents (the forecast for the development of the world’s energy industry and russia up to 2040, 2014) has different scenarios: the forecast made in 2014 is underlain by the baseline scenario (priority in the development is given to the western macro-zone of the russian federation) and the other asia scenario (priority is given to the eastern macro-zone). in the forecast made in 2016 (makarov et al., 2016), the authors propose three energy sector development scenarios: probable, critical and optimistic. since the latest version of the forecast looks more relevant, we will give a brief description of russia’s energy sector development scenarios (table 5). these works analyze the primary energy resources that are sources for electricity production. let us compare the expected results of the above documents, i.e., 2030 energy strategy of the russian federation (the energy strategy of russia for the period up to 2030, 2009) and development forecasts (the forecast for mukhametshin, et al.: implementation of efficient energy policy in russia: energy consumption monitoring and problem analysis international journal of energy economics and policy | vol 9 • issue 4 • 2019 231 the development of the world’s energy industry and russia up to 2040, 2014; makarov et al., 2016). we take the low limit consumption indicators from the energy strategy. this work provides two options of the world and russia’s energy sector development forecast (the forecast of 2014 and 2016). the results are summarized in table 6. the 2040 forecast presented in the paper (makarov et al., 2016) reflects no significant changes in the energy sources structure, and therefore, we do not provide it in this study. analysis of the sources structure according to the documents mentioned confirms the predominance of gas as the main source of electricity production, accounting for about 50% in the sources structure. the actual structure of sources (energy resources) according to 2017 data (world energy statistical yearbook, 2018) also suggests the predominance of gas as a source, while the global structure significantly differs from that of russia (table 7). for clarity, the above is presented in figure 6. the data presented is in line with the trends reflected in the strategic and forecast documents for the russian federation, i.e., the actual consumption of natural gas remains a predominant source for electricity generation. in the world statistics, however, natural gas accounts for only 22% and coal–27%. 5. conclusion the study has revealed fundamental differences in the consumption and use of energy resources throughout russia’s regions. three principle approaches have been used to assess energy consumption among russia’s constituent entities: (1) distribution by federal districts; (2) distribution by macro-regions; (3) distribution among eastern and western macro-regions. according to the official statistics for 2017, almost 60% of electricity consumption falls on 3 out of the 8 federal districts (central, siberian and volga); the predominant consumption in some regions is determined by the location of large energyintensive industries there. the deficit of own electricity production was observed in two federal districts — volga and siberian. comparison of electricity consumption and production in the newly established macro-regions also revealed an imbalance: electricity shortage is largely typical for the volga-kama and south siberian macro-regions (the latter is part of the siberian federal district). despite the fact that other macro-regions are selftable 7: structure of energy sources according to 2017 data type of energy oil products electricity biomasses natural gas coal world 32 9 10 22 27 russia 21 9 1 52 16 sufficient with total production exceeding total consumption, there is a significant shortage of electricity in the constituent regions of a number of macro-regions. an even greater electricity consumption and production imbalance is found upon the assessment of the eastern and western macro-regions representing a high-level breakdown of russia into two zones. all this not only is not contradictory to, but rather is in line with the priority development of the economic potential, primarily, in eastern siberia, the far east and the far north, as indicated in the strategic documents. one of the strategic vectors of energy policy for the period up to 2030 is the accelerated development of coalfired thermal pp in the siberian and far eastern federal districts. these plants will be built both close to the already existing steam coal mines (kuznetsk and kansk-achinsk coal basins) and (in the medium and long term) in close proximity to the new areas of coal production (transbaikal, southern yakutia, tyva, etc.). this is favored by the huge amount of proven coal reserves in the eastern zone of the country and its share suitable for opencast mining (99% of such national coal reserves are concentrated here). the accelerated development of coal energy on the basis of new eco-friendly coal technologies will certainly lead to a decrease in the share of gas in the consumption of primary fuel and energy resources from 52 % (2017) to 46-47% by 2030. according to the forecast documents, the world economy and energy will be greatly influenced by the processes taking place in the developing countries of asia. coal is the backbone of the energy mix of the world’s two fastest growing energy consumers — china and india. the forecasts suggest that though current domestic demand is satisfied by domestic production, there are high risks of reaching production peaks and observing coal shortages in these countries in the next decade. in this context, due to the possibilities of increasing coal production in the eastern macro-zone, russia can become one of the important players in the global coal market. as our research shows, only after the power complex development in the east of the country, including hydroelectric pp, siberian pp will have enough capacity to meet the electricity demand of the european part of russia. in turn, the implementation of the electric power sector strategies will enable the regions to significantly transform and develop labor markets, social and transport infrastructure, and to form new centers of their economic growth. references about the plenipotentiary of the president of the russian federation in the federal district. (2000), decree of the president of the russian federation of may 13, 2000 no. 849. available from: http://www. consultant.ru/document/cons_doc_law_23-329. [last accessed on 2018 dec 13]. analysis of the results of the reform of the power industry and proposals for increasing its efficiency: an analytical report. (2013), institute for the problems of natural monopolies. available from: http://www. ipem.ru/research/power/power_works/79.html. bessel, v.v. (2013), on the issue of assessing the energy efficiency of the russian economy. drilling and oil, 12, 18-23. gdp of the leading countries of the world in 2018. (2018), information mukhametshin, et al.: implementation of efficient energy policy in russia: energy consumption monitoring and problem analysis international journal of energy economics and policy | vol 9 • issue 4 • 2019232 ifinance site. available from: http://www.global-finances.ru/vvpstran-mira-2018. kvon, g.m. (2018), energy saving projects as energy security factors. international journal of energy economics and policy, 8(6), 155-160. kvon, g.m., samysheva, e.y., vaks, v.b., mararov, n.v., khamidullin, f.f. (2016), methods of evaluating the efficiency of energy saving projects with taking risks into account. international journal of environmental and science education, 11(1), 7441-7452. makarov, a.a., grigorieva, l.m., mitrova, t.a. (2016), forecast of the development of the world energy industry and russia 2016. moscow: inei ras, ac under the government of the russian federation. available from: http://www.ac.gov.ru/files/ publication/a/10585.pdf. myznikova, m.n. (2016), regional energy system: analysis of the relationship between the structure of consumption and production of energy resources. kazan economic journal, 4(24), 32-37. official statistics. (2017), electricity consumption in the russian federation. available from: http://www.gks.ru/wps/wcm/connect/ rosstat_main/rosstat/ru/statistics/enterprise/industrial. on energy saving and on increasing energy efficiency, and on introducing amendments to certain legislative acts of the russian federation: federal law of the russian federation no. 261-fl. (2009), available from: http://www.legalacts.ru/doc/fz-ob-jenergosberezhenii-i-opovyshenii-jenergeticheskoj-jeffektivnosti-i-o-vnesenii-izmenenijv-otdelnye-zakonodatelnye-akty-rossijskoj-federacii. on strategic planning in the russian federation. (2014), federal law of june 28. available from: http://www.consultant.ru/document/ cons_doc_law_164841. platonova, e.v., safronov, a.v. (2016), monitoring of energy consumption based on the results of the primary energy survey. scientific almanac, 5(19), 142-145. rbc. (2019), website, 55 trillion in stock: how the authorities rated all russia’s natural resources. available from: https://www.rbc.ru/ economics/14/03/2019/5c8931029a7947b028b8886c. report on the functioning of the ues of russia in 2018. (2018), prepared in accordance with the rules for the development and approval of schemes and programs for the future development of the power industry. available from: http://www.so-ups.ru/fileadmin/ files/company/reports/disclosure/2019/ups_rep2018.pdf. the energy strategy of russia for the period up to 2030. (2009), available from: https://www.minenergo.gov.ru/node/1026. the forecast for the development of the world’s energy industry and russia up to 2040. (2014), available from: http://www.ac.gov.ru/ files/publication/a/2194.pdf. the strategy of russia’s economic security for the period to 2030. (2017), approved by the decree of the president of the russian federation, no. 208. available from: http://www.docs.cntd.ru/ document/420398070. the strategy of spatial development of the russian federation for the period up to 2025. (2019), approved by an order of the government of the russian federation on february 13, 2019. available from: http://www.static.government.ru/media/files/ uvalqutt08o60rktooxl22jjae7irnxc.pdf. vasilyeva, a.v., tyzhnenko, d.a., potekhin, v.v. (2012), problems of creating an information-measuring system for monitoring and optimizing energy consumption. proceedings of st. petersburg state technical university, 514, 62-66. world energy statistical yearbook. (2018), available from: https://www. yearbook.enerdata.ru/total-energy/world-consumption-statistics. html. [last accessed on 2019 mar]. world population prospects. (2015), the 2015 revision, key findings and advance tables united nations department of economic and social affairs/population division. available from: https://www.esa. un.org/unpd/wpp/publications/files/key_findings_wpp_2015.pdf. . international journal of energy economics and policy | vol 8 • issue 3 • 2018 267 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(3), 267-274. the relationship between foreign direct investment, electricity consumption and economic growth in vietnam pham dinh long1*, bui hoang ngoc2,3, duong tien ha my1 1faculty of economics and public management-ho chi minh city open university, vietnam, 2graduate school-ho chi minh city open university, vietnam, 3faculty of business administration-university of labour and social affairs, ho chi minh city campus, vietnam. *email: long.pham@ou.edu.vn abstract one of the prerequisites for the successful implementation of national industrialization and modernization is the synchronous development of fundamental industries. electricity is a key industry that determines the success of other industries. the main purpose of this paper is to investigate the causal relationship between electricity consumption, foreign direct investment (fdi) and economic growth in vietnam during the period 1990-2015, by using toda-yamamoto approach and autoregressive distributed lag approach. the empirical results show strong statistical evidence that electricity consumption and fdi have positive impacts on economic growth in vietnam in both short term and long term. keywords: foreign direct investment, electricity consumption, economic growth, vietnam jel classifications: f21, f43, q43 1. introduction rostow (1990) points out that a country usually goes through five stages of economic development: (1) traditional society, (2) preconditions for take-off, (3) take-off, (4) drive to maturity and (5) age of mass consumption. the conditions for successful implementation of the pre-conditions take-off stage include: (i) investment share in gross domestic product (gdp) increases from 5 to 10%; (ii) building leading sectors (fundamental industries such as electricity and energy, import-export markets and supporting industries); (iii) there must be a dynamic management mechanism that knows how to use technology and strengthens external economic relations. in terms of these three conditions, developing economies are subject to certain constraints including restrictions on fund sources and the availability of natural resources. electricity plays an important role in any country, because it affects both aggregate supply and aggregate demand. on the demand side, electricity is an essential product for consumers to maximize their utility, not to mention that it may show the civilization of a country/region compared to other countries/regions (aytac and guran, 2011). on the supply side, electricity is a key input of the production process; without electricity, the scale of production will be scattered, fragmented and the productivity will be low. according to the international energy agency, the world’s primary energy demand will continue to increase (about 1.4% annually until 2035), which happens strongly in rapidly developing economies like china, brazil and india. vietnam is a developing country, so we are also under great pressure due to an increase in the demand for electricity to serve people’s consumption and the economy’s expansion. after the 1986 economic reform, when gross national income (gni) increased from $79.56 in 1986 to $1,961.75 in 2015,1 the total electricity consumption of vietnam increased rapidly from 3.3 billion kwh in 1980 to 140.72 billion kwh in 20152. in 2014, the electricity consumption of the industrial sector was the largest; specifically, this sector accounted for 53.9%, the residential sector accounted for 35.6%, the service sector accounted for 4.8% and the rest was for other regions. in terms of attracting foreign direct investment (fdi), vietnam has made remarkable progress, from $180 million in 1990 to 1 calculated at constant prices in 2010. data from the united nations conference on trade and development (unctad) 2 the international energy agency (iea) long, et al.: the relationship between foreign direct investment, electricity consumption and economic growth in vietnam international journal of energy economics and policy | vol 8 • issue 3 • 2018268 $11.8 billion in 2015. in general, fdi plays an important role in vietnam’s economy, significantly changes the structure of industries, the productivity and income of individuals. however, the development of foreign-invested enterprises also increases the pressure on vietnam’s electricity demand. based on that reality, the authors examine the relationship between electricity consumption, fdi and economic growth to provide empirical evidence that helps the authorities make strategic planning and policy development, ensure energy security and economic development of the country. the paper is divided into 5 sections. after the introduction, section 2 presents literature review related to the topic of the study. section 3 introduces research models, data collection, processing and analysis. research findings and policy implications are presented in section 4. the final section will be the conclusions and limitations of the study and some suggestions for further research. 2. literature review 2.1. the relationship between fdi and economic growth there are many theories explaining the origin of fdi. according to williamson (1985) and dunning and lundan (2008), fdi enterprises (mnes multinational enterprises) only conduct fdi if satisfying three conditions: (1) ownership advantages (o): the enterprise must possess some advantages over other enterprises such as size, technology, marketing network, access to low-interest capital or specific intangible assets of the enterprise; (2) location-based advantages (l): producing in a foreign country is less expensive than producing in the host country and then exporting those products. location advantages can be obtained through natural resources, labor, trade barriers, investment incentive policies, and external influences that the firm may receive. (3) internalisation advantages (i): the use of these advantages within the firm is more profitable than selling or renting them to other firms. so far, theoretical and empirical evidence in many countries/ regions has shown that fdi is considered as one of the pillars of economic growth. the role of fdi is evident as it contributes to economic growth through factors such as adding additional capital investment, promoting export, transferring technology, developing human resources and creating jobs etc. in addition, fdi also contributes positively to budget income and promotes deep integration into the world economy. the impact of fdi on economic growth is divided into three categories: two-way impact (fdi ↔ gdp), one-way effect (fdi → gdp), no impact (fdi #→gdp). impact is divided into two types: positive (increase), negative (decrease). bende-nabende and ferd (1998) use a simultaneous equation to analyze the effect of fdi and government policy on economic growth in taiwan. the authors determine that fdi has the potential to boost economic growth and policy has the potential to promote growth, particularly in terms of infrastructure development and liberalization. the study by shaari et al. (2012) uses the vector autoregression (var) model to examine the effect of fdi on annual gdp in malaysia for the period 1972-2010. the results show that an increase in fdi has a positive impact on economic growth in malaysia. specifically, a 1% increase in fdi leads to a 49.1% increase in malaysia’s gdp. the authors also find that gdp has a causal relationship with fdi and vice versa. tang et al. (2016) analyse the relationship between energy consumption and economic growth in vietnam using the neoclassical solow growth framework for the 1971–2011 period. the results confirm the existence of cointegration among the variables. in particular, energy consumption, fdi and capital stock were found positively influence economic growth in vietnam. the granger causality test revealed unidirectional causality running from energy consumption to economic growth. al-mulali et al. (2015) examined the existence of the environmental kuznets curve (ekc) hypothesis in vietnam during the period 1981–2011. the results revealed that the pollution haven hypothesis does exist in vietnam because capital increases pollution. in addition, imports also increase pollution which indicates that most of vietnam’s imported products are energy intensive and highly polluted. however, exports have no effect on pollution which indicates that the level of exports is not significant enough to affect pollution. moreover, fossil fuel energy consumption increases pollution while renewable energy consumption has no significant effect in reducing pollution. ahmed et al. (2017) attempt to shed some light on the energy consumption and associated emissions linking recent trade integration for eight economies in the asean region: brunei darussalam, cambodia, indonesia, malaysia, philippines, singapore, thailand and vietnam. considering the heterogeneity across the panel of countries, a long-run relationship is established between output, energy, trade, and emissions over a period of three decades. the overall findings indicate that the environmental consequences of economic growth are alarming for most of the countries in the panel, and non-renewable energy consumption is the key contributing factor towards environmental deterioration in the asean region. of the eight, it is further established that five economies from the region (cambodia, indonesia, malaysia, thailand and vietnam) predominantly engage in emissionintensive trade and an increase in future energy demand and environmental degradation is projected for these countries. yildirim et al. (2014) reexamine the relationship between energy consumption per capita and real gdp per capita for indonesia, malaysia, the philippines, singapore and thailand using both panel data causality which is taking into account cross-sectional dependence and heterogeneity among the countries and time series causality tests for the period 1971–2009. the findings indicate that taking into account cross-sectional dependence has a substantial effect on the achieved results. the conservation hypothesis is supported for indonesia, malaysia and the philippines. although a bidirectional relation is found in the case of thailand, since there is no positive effect of energy consumption on gdp, the conservation hypothesis is supported. in the pattern of singapore, the neutrality hypothesis is supported. in vietnam, nguyen (2003) shows that fdi stimulates economic growth at the national level and suggests that in order to attract fdi into vietnam, it is necessary to expand the market and find new partners. nguyen (2004) concludes that fdi has a positive long, et al.: the relationship between foreign direct investment, electricity consumption and economic growth in vietnam international journal of energy economics and policy | vol 8 • issue 3 • 2018 269 impact on local economic growth through the formation and accumulation of capital assets and the interaction between fdi and human resources. nguyen et al. (2006) using time series data from 1988 to 2003 show the impact of fdi on economic growth through investment channels. the conclusion of the study is that fdi complements domestic investment, which helps to expand production, reduce government deficits, contribute to export earnings, and create jobs. at the same time, the domestic private sector plays an important role in promoting spillover effects of fdi. this suggests that policies for promoting the development of the private sector should be strengthened to increase the spillover effects of fdi. bang (2008) using the ols, gls, and causality test for the 1990-2002 data set concludes that fdi positively influences economic growth through labor productivity. le viet (2009) studies the relationship between fdi and economic growth in vietnam, shows the positive contribution of fdi inflows to vietnam’s economic growth from 1988 to 2002, which is estimated at about 7% of the total capital contributing to growth (i.e., 37%) during this period. the regression results show that fdi is positively correlated with domestic investment and economic growth as well as fdi creates significant short-term and longterm positive effects on economic growth in vietnam. nguyen and wongsurawat (2017) examined the relationship between electricity consumption (ec), economic growth, exports and fdi in vietnam using time series data from 1980 to 2013. the results indicate that real gdp, ec, exports (ex) and fdi in vietnam are cointegrated. there is unidirectional granger causality running from real gdp to ec, ex and fdi, but not vice versa. the data also show that there is bidirectional granger causality between ec and ex. however, ericsson and irandoust (2001) fail to determine any causal relationship between fdi and growth for denmark and finland when examining the causal relationship between fdi and output for four oecd countries including denmark, finland, norway and sweden. haddad and harrison (1993) also find no significant impact of fdi on domestic economic growth when conducting spillover effects of fdi to domestic companies in morocco. similarly, karikari (1992) examines the causal relationship between fdi and economic growth in ghana during the period 1961-1988, the author indicates that fdi does not affect economic growth in country. recently, temiz and gökmen (2014) investigate the relationship between fdi inflows and economic growth in turkey. by applying quarterly time series from quarter 1 1992 to quarter 3 2007 and ols regression, the authors conclude that there is no meaningful relationship between fdi and economic growth in turkey in the short and long terms. karimi et al. (2009) studying the relationship between fdi and economic growth in malaysia also show that fdi has no significant impact on growth. other studies find a negative relationship between fdi and economic growth. karikari (1992), when examining the causal relationship between fdi and economic growth in ghana from 1961 to 1988, conclude that fdi does not affect economic growth; conversely, economic growth may reduce fdi inflows. according to the author, fdi promotes free trade rather than boosts economic growth. ang (2009) uses the error correction model to assess the effect of fdi on thailand’s economy during the period 1970-2004. consequently, fdi has a negative impact on thailand’s economy. differences in the results of the above studies on the relationship between fdi and economic growth demonstrate that it is necessary to collect more empirical evidence on this relationship. 2.2. the relationship between electricity consumption and economic growth so far we have not recorded any economic theory directly addressing the impact of electricity consumption on economic growth, but many researchers, through empirical results, suggest that this may be a positive relationship. in arrow’s endogenous growth theory (1962), technology is considered as a direct contributor to economic growth. the technology mentioned here is plant, machinery or generally, the process of converting inputs into outputs. if there is not enough power supply (in this case electricity or gasoline), these technologies are actually useless. the thermodynamic law helps to explain this by saying that “no production process can be controlled without converting energy.” therefore, although energy in general, and electricity in particular, are not the only determinants of technology, they are important factors to ensure that technology can be used effectively and become an essential input for economic growth. additionally, the conversion of raw energy to useful energy illustrates a high level technology. the study of kraft and kraft (1978) is considered as a fundamental research on the relationship between economic growth and energy consumption. specifically, the study finds a one-way causal relationship from economic growth to electricity consumption in the us economy in the period 1947-1974. studies in other countries/regions also aim at testing and confirming this relationship under specific conditions. if ec and gdp have a two-way causal relationship (ec↔gdp), there may exist an additional relationship. in other words, an increase in electricity consumption may have a positive impact on economic growth and vice versa. if there is only a one-way effect causal relationship from gdp to ec (gdp → ec), it reflects that a country/region is less dependent on electricity, while if there is only a one-way effect causal relationship from ec to gdp (ec → gdp), the use of electricity must be considered in the national energy policy, because the initial investment cost for power plants is very expensive. there are a number of studies that find no relationship between these two variables. an explanation for findings on such relationship must be put in the context of specific research because electricity consumption is highly dependent on factors such as scientific and technical level, people’s living standards, the geographical location, the weather as well as people’s consumption habits, the enterprise and the national electricity policy. a summary of studies on the relationship between ec and gdp is shown in table 1. results in table 1 show that the relationship between ec and gdp is not uniform across countries/regions. this demonstrates that it is necessary to test such causal relationship in vietnam. long, et al.: the relationship between foreign direct investment, electricity consumption and economic growth in vietnam international journal of energy economics and policy | vol 8 • issue 3 • 2018270 3. research methodology 3.1. research models vietnam has just implemented economic reforms since 1986 and fdi only flows into vietnam after 1990, so the length of the data sample is relatively short. from this point of view, in order to increase the relevance of the experimental results, the authors choose the autoregressive distributed lag (ardl) method and the toda-yamamoto causality test to investigate the relationship between fdi, electricity consumption and economic growth in vietnam. based on studies by tang (2009), abdullah (2013), anis et al. (2014) and ibrahiem (2015), we propose a research model derived from the cobbdouglas as follows: y = eεakalβeλ (1) where: y is the real output (gdp), a is the total factor productivity, k is the capital input of the economy (domestic capital and fdi), l is the labor input. e is the total electricity consumption. α, β, λ are the output elasticities of labor, capital and electricity, respectively. because domestic capital is not considered in this study, we propose that k is expressed as k = c.fdi. then equation 1 is rewritten as: y c e a f i l e= α ε α β λ( )d (2) assume that output y is constant returns to scale, (i.e., α+β+λ=1), then divide both sides of equation 2 by l to find the per capita income, equation 2 is written as: y l c e a f i l e l = α ε α λ( ) ( ) d (3) take the logarithm of both sides of equation 3 to obtain: log( ) log( ) log( ) log( ) y l c a f i l e l = + + +α α λ ε d (4) since log( )c aα is constant, we can represent equation 4 as a model for time series data as follows: log y l log f i l e lt t t t ( ) ( ) log( )= + + +β β β ε0 1 2 d (5) 3.2. methods of data analysis and processing the study uses the ardl model introduced by pesaran et al. (2001) due to the following advantages: (i) the variables in the model just need to ensure that they are stationary at a maximum of level 1, it is possible to be stationary at same level (the root level i(0) or level 1 i(1)), (ii) avoid endogenous problems and be more reliable for small observations since lagged dependent variables are added as independent variables in the model, (iii) the short term and long term coefficients can be estimated at the same time, the error correction model can estimate both short-term adjustments and long-term equilibrium without omitting information in the long term, (iv) the model itself selects the optimal lag length, allows differences in the optimal lag length of variables, thus significantly improving the fit of the model (davoud et al., 2013 and nkoro and uko, 2016). in order to increase the accuracy of the study, we use gni per capita instead gdp per capita as the dependent variable. in terms of independent variable, to examine total impact in short-term and long-term, we use fdi inflow and electricity consumption, instead of fdi per capita and electricity consumption per capita. data is collected from 1990 to 2015, sources and detailed illustrations of variables are shown in table 2. then, equation 5 can be represented as an ardl model as follows: ∆ ∆ ∆ lngni lngni lnf i lnec lngni t t t t i t i = + + + + + − − − − β δ δ δ θ ϑ 0 1 1 2 1 3 1 1 d llnf i lnec t i p i p i t t i p d − == − = ∑∑ ∑+ + 1 11 1 1 21 3 ω µ∆ (model 1) table 1: the relationship between ec and gdp author country methods relationship tang (2009) malaysia ardl, granger ec↔gdp esso (2010) 7 countries threshold cointegration ec↔gdp aslan et al. (2014) america ardl, granger ec↔gdp kyophilavong et al. (2015) thailand vecm, granger ec↔gdp ciarreta and zarraga (2007) spain granger gdp→ec canh (2011) vietnam threshold cointegration gdp→ec hwang and yoo (2014) indonesia ecm-granger gdp→ec abdullah (2013) india vecm-granger ec→gdp mai (2015) asean6 panel-vecm ec→gdp wolde-rufael (2006) 17 countries ardl no relationship acaravci and ozturk (2012) turkey ardl no relationship source: the authors’ summary. gdp: gross domestic product, ardl: autoregressive distributed lag, vecm: vector error correction model table 2: source and measurement method of variables in the model variable symbol description unit expected impact source gni the gross national income per capita (calculated at comparative prices in 2010) usd/person dependent variable world bank fdi total fdi flows into vietnam million dollars + unctad ec total electricity consumption billion kwh + iea fdi: foreign direct investment, iea: international energy agency long, et al.: the relationship between foreign direct investment, electricity consumption and economic growth in vietnam international journal of energy economics and policy | vol 8 • issue 3 • 2018 271 where δ: the deviation of variables • δ1, δ2, δ3 are regression coefficients that express long-term effects • µt is the white noise error term. the regression testing process includes the following steps: (1) verifying the stationarity of variables in the model, (2) estimating model 1 by least squares method (ols), (3) calculating f-statistic to determine whether there exists a long-term relationship between the variables. if there is a cointegration relationship in the long term, the error correction model (ecm) is estimated based on the following equation: ∆ ∆ ∆ ∆ lngni ecm lngni lnf i lnec t t i t i p i t i t = + + + + − − = − ∑β α θ ϑ ω 0 1 1 1 1 1 . d −− == +∑∑ 1 11 32 µt i p i p (model 2) and if there exists α in which α is different from zero and statistically significant, the alpha coefficient shows the speed of adjustment of gni per capita towards equilibrium after a short-term shock. (4) moreover, in order to make the results of the study reliable, the authors will conduct additional diagnostic tests including: testing for heteroscedasticity, testing for autocorrelation, testing for functional form, testing for residual normality, testing the stability of the model through the cumulative sum of recursive residuals (cusum) and the cumulative sum of squares of recursive residuals (cusumsq). to determine the causal relationship between variables, instead of traditional granger causality test, the authors use the modified wald (mwald) proposed by toda and yamamoto (1995). the toda-yamamoto method is based on the var model that contains the root level variable (instead of the first degree variable in the granger causality test). this approach minimizes the risk of incorrectly identifying the degree of association of variables in the sample and is able to conduct notwithstanding that variables are stationary at level 0 or level 1 and there exists cointegration or no cointegration (mavrotas and kelly, 2001). 4. research results and discussion 4.1. descriptive statistics with the opening of the economy in 1986, the promulgation of the law on fdi in 1987 and being an official membership of the world trade organization in 2008, vietnam’s economy has undergone many positive changes. fdi inflows continuously increase and provide significant support to the industrialization and modernization of the country. in addition, vietnam has a geographic location with many rivers and large water flows. this is a necessary condition for the development of the electricity industry. descriptive statistics of variables are presented in table 3. 4.2. research results 4.2.1. test for stationarity first, a test for stationarity is used to ensure that no variable is stationary at the second difference (a condition for using the ardl model). an augmented dickey-fuller test is a popular method for studying time series data. however since the number of observations in the study is limited, we use the kpss (kwiatkowski-phillipsschmidt-shin) and zivot-andrews test to ensure the accuracy of the results obtained. the results of these tests shown in table 4 suggest that with adf and kpss tests, variables are stationary at level 1. the zivot-andrews test rejects the hypothesis that variables are stationary at a level greater than level 2. therefore, the application of the ardl into the model is reasonable. 4.2.2. bound test the ardl model itself calculates the optimal lag length. based on aic standard, regarding the data of the observation, the optimal model is ardl (2,0,0) with the initial maximum lag length for the auxiliary variables is 4. the result of f-statistic test is 7.859 which is greater than the critical value of the upper bound (upper bound = 5) at the significance level of 1%, thus rejecting the null hypothesis. in other words, variables in the model have cointegration relationship in the long run. the results of bound test are shown in table 5. 4.2.3. error correction model because there exists cointegration between variables in the long run, the authors continue to use the error correction model (model 2) to determine the error term coefficient. as a result, the estimated result of model 2 shows that the coefficient of α = −0.493 is statistically significant at 1%. this implies that gni per capita will automatically adjust to equilibrium level after a short-term shock due to the effects of fdi and ec. the coefficients of fdi and ec variables are positive, statistically significant at the 1% level, which indicates that in the short run both fdi and electricity table 3: descriptive statistics of variables variable medium median max min error lngni 6.24 6.09 7.58 4.48 0.91 lnfdi 7.78 7.57 9.37 5.19 1.10 lnec 3.45 3.50 4.94 1.87 1.01 source: authors’ calculations table 4: results of the stationary test variable adf test kpss test zivot-andrews test lngni −2.386 0.752*** −5.561** δlngni −3,846** 0.235 lnfdi −2.433 0.672** −7.543*** δlnfdi −3.546* 0.154 lnec −0.974 0.752** −2.606** δlnec −2.962* 0.196 ***, **and *denote the significance level of 1%; 5% and 10%. source: the authors’ calculations table 5: results of bound test bound test critical values for bound test statistical value value significance level (%) i (0) bound i (1) bound f-statistics 7.859838 10 2.63 3.35 k 2 5 3.1 3.87 2.5 3.55 4.38 1 4.13 5 long, et al.: the relationship between foreign direct investment, electricity consumption and economic growth in vietnam international journal of energy economics and policy | vol 8 • issue 3 • 2018272 consumption positively influence average income. the regression coefficient of ec variable is greater than that of fdi variable, implying that electricity consumption is more likely to improve the short-term average income. the results of the error correction model are shown in table 6. 4.2.4. long-term estimation results next, we estimate the long-term impact to investigate the effect of fdi and power consumption on vietnam’s per capita income over the period 1990-2015. the results in table 7 show that both lnfdi and lnec variables are positively correlated with per capita income and statistically significant at 1% level. accordingly, ceteris paribus, a 1% increase in fdi inflows leads to a 0.21125% increase in per capita income. similarly, a 1% increase in electricity consumption leads to 0.6463% increase in per capita income. 4.2.5. additional tests afterwards, we test the stability of the model by checking the cumulative sum of recursive residuals (cusum) and the cumulative sum of squares of recursive residuals (cusumsq). figure 1 shows that both cusum and cusumsq lines (the solid line) stay within the critical bounds at the 5% level (the dashed line), so we conclude that estimated coefficients in the model are stable in the long run. finally, to confirm the relationship between variables, we conduct the granger causality test based on the toda-yamamoto method with the null hypothesis of no granger causality. the results are shown in (tables 8 and 9, figure 2). 4.2.6. robustness analysis because the length of the data series is limited, in order to avoid biased results in the long term, we perform robustness analysis using fmols (fully modified ols) and dols (dynamic ols) methods. although kao and chiang (2000) note that dols is more effective than fmols, we still use both methods to confirm the effect of long-term estimates. the results obtained in tables 7 and 10 show that beta coefficients of lnfdi and lnec variables are relatively similar. this confirms that the estimated effects of fdi and electricity consumption on vietnam’s economic growth in the long run is consistent and unbiased. 4.3. discussion and policy implications the experimental results of the study are consistent with the pre-conditions for take-off stage proposed by rostow. these results are also consistent with the conclusions of other studies for countries/regions which have similar starting points and table 6: results of the error correction model variable β standard error t-statistic p intercept 1.196052 0.242998 4.922073 0.0001 ecm(-1) −0.493059 0.104721 −4.708290 0.0002 lnfdi 0.104159 0.035098 2.967678 0.0079 lnec 0.318671 0.073399 4.341622 0.0004 δlngni(-1) 0.319704 0.162385 1.968800 0.0637 source: the authors’ calculations table 7: estimated results of long term impact coefficient variable β standard error t-statistic p lnfdi 0.211251 0.049888 4.234508 0.0004 lnec 0.646315 0.051693 12.50307 0.0000 intercept 2.425779 0.245548 9.879025 0.0000 ecm=lngni (0.2113*lnfdi+0.6463*lnec+2.4258 ) source: the authors’ calculations table 9: granger causality test based on the toda-yamamoto method null hypothesis number of observations f-statistic p lnfdi does not have a causal effect on lngni 24 4.99569 0.0181 lngni does not have a causal effect on lnfdi 4.99481 0.0181 lnec does not have a causal effect on lngni 24 4.59245 0.0236 lngni does not have a causal effect on lnec 0.53783 0.5926 lnec does not have a causal effect on lnfdi 24 1.66254 0.2161 lnfdi does not have a causal effect on lnec 0.06944 0.9332 table 8: results of additional tests types of test statistical value p heteroscedasticity test (white test) 1.77461 0.1949 serial correlation lm test (breusch-godfrey test) 0.10182 0.9037 normality test of residuals (normality test) 0.44101 0.8021 source: the authors’ calculations figure 1: (a and b) results of the stability test of the model a b long, et al.: the relationship between foreign direct investment, electricity consumption and economic growth in vietnam international journal of energy economics and policy | vol 8 • issue 3 • 2018 273 similar conditions like vietnam. such studies are tang (2009) for the malaysian economy in the period 1970-2005, abdullah (2013) for the indian economy 1975-2008, odhiambo (2009) for the tanzania economy 1971-2006, kasperowicz (2014) for the polish economy or ibrahiem (2015) for the egyptian economy etc. this is reasonable, because according to alam (2006) energy is an indispensable resource/input for all economic activities. energy efficiency not only helps to save production costs but also enhances profitability through improved labor productivity. oviemuno (2006) states that “even though it cannot conclude that energy is finite, more efficient use of existing energy also increases the wealth of a nation.” based on the results of the study, the authors suggest some considerations when applying these results in practice as follows: first, vietnam should strive to attract fdi as well as develop the electricity industry. the beta coefficient of lnec variable is 0.646 while the beta coefficient of lnfdi variable is 0.211. this implies that increased investment in the electricity sector will have a greater impact on economic growth than increased investment in fdi. therefore, policies which aim at attracting fdi and evaluating fdi projects need to prioritize projects that have low electricity consumption, advanced technology and are environmentally friendly. second, the consumption of electricity contributes to enhance economic growth in vietnam, this does not mean that vietnam has to build a lot of power plants. electricity efficiency, saving electricity, switching off unnecessary equipment, reducing losses in the power transmission etc. are also methods for vietnam to increase the electricity output. third, with favorable geographic position, vietnam has great potential to develop alternative energy sources such as solar, wind, biofuels and geothermal power etc. these are more environmentally friendly types of energy. exploiting and using these energy sources are extremely important in terms of socioeconomic and energy security and sustainable development. 5. conclusion in the process of development, the demand for capital to invest in infrastructure, social security, education, health care, defense, etc. is always great. with the data from 1990 to 2015, by using the ardl and the granger causality test proposed by todayamamoto, we conclude that electricity consumption and fdi have positive impacts on economic growth in vietnam. we also find a two-way granger causal relationship between fdi and gni per capita (fdi↔gni), a one-way granger causal relationship from power consumption to gni per capita (gn → gni). although the number of observations and test results are satisfactory, it should be noted that the data of the study may be not long enough. in addition, the study does not analyze in detail the impact of electricity consumption by the industrial sector and population to economic growth. this can be the direction for further research. references abdullah, a. (2013), electricity power consumption, foreign direct investment and economic growth. world journal of science, technology and sustainable development, 10(1), 55-65. acaravci, a., ozturk, i. (2012), electricity consumption and economic growth nexus: a multivariate analysis for turkey. the amfiteatru economic journal, 14(31), 246-257. ahmed, k., bhattacharya, m., shaikh, z., ramzan, m., ozturk, i. (2017), emission intensive growth and trade in the era of the association of southeast asian nations (asean) integration: an empirical investigation from asean-8. journal of cleaner production, 154, 530-540. alam, m.s. (2006), economic growth with energy. mrpa working paper. available from https://www.mpra.ub.uni-muenchen.de/1260. [last retrieved on 2006 nov 20]. al-mulali, u., saboori, b., ozturk, i. (2015), investigating the environmental kuznets curve hypothesis in vietnam. energy policy, 76, 123-131. ang, j. (2009), foreign direct investment and its impact on the thai economy: the role of financial development. journal of economics and finance, 33(3), 316-323. anh, n.t.t., hong, v.x.n., thang, t.t., hai, n.m. (2006), tác động của đầu tư trực tiếp nước ngoài tới tăng trưởng kinh tế ở việt nam. science and technics publishing house. anis, o., nguyen, d.k., rault, c. (2014), causal interactions between co2 emissions, fdi, and economic growth: evidence from dynamic simultaneous-equation models. economic modelling, 42, 382-389. arrow, k. (1962), the economic implication of learning-by-doing. review of economic studies, 29(1), 155-173. aslan, a., apergis, n., yildirim, s. (2014), causality between energy consumption and gdp in the us: evidence from wavelet analysis. frontier in energy, 8(1), 1-8. aytac, d., guran, m.c. (2011), the relationship between electricity consumption, electricity price and economic growth in turkey: 1984-2007. argumenta oeconomica, 2(27), 101-123. table 10: results of robustness analysis using fmols and dols methods variable fmols dols lnfdi 0.28235*** 0.270062*** lnec 0.60708*** 0.614113*** intercept 1.94719*** 2.039115*** adjusted r2 0.991 0.993 ***, **and *denote the significance level of 1%; 5% and 10%. source: the authors’ calculations lngni lnfdi lnec figure 2: granger causality between variables based on toda-yamamoto approach long, et al.: the relationship between foreign direct investment, electricity consumption and economic growth in vietnam international journal of energy economics and policy | vol 8 • issue 3 • 2018274 bang, v.t. (2008), foreign direct investment and endogenous growth in vietnam. applied economics, 40, 1165-1173. bende-nabende, a., ferd, j.l. (1998), fdi, policy adjustments and endogenous growth multiplier effects form a small dynamic model for taiwan, 1959-1995. world development, 26, 115-130. canh, l.q. (2011), electricity consumption and economic growth in vietnam: a cointegration and causality analysis. journal of economics and development, 13(3), 24-36. ciarreta, a., zarraga, a. (2007), electricity consumption and economic growth: evidence from spain. biltoki 2007.01, universidad del pais vasco. p1-20. davoud, m., behrouz, s.a., farshid, p., somayeh, j. (2013), oil products consumption, electricity consumption-economic growth nexus in the economy of iran: a bounds test co-integration approach. international journal of academic research in business and social sciences, 3(1), 353-367. dunning, j., lundan, s. (2008), institutions and the oli paradigm of the multinational enterprise. asia pacific journal of management, 25(4), 573-593. ericsson, j., irandoust, m. (2001), on the causality between foreign direct investment and output: a comparative study. the international trade journal, 15, 122-132. esso, l.j. (2010), threshold cointegration and causality relationship between energy use and growth in seven african countries. energy economics, 32(6), 1383-1391. haddad, m., harrison, a. (1993), are there positive spillovers from direct foreign investment? evidence from panel data for morocco. journal of development economics, 42, 51-74. hwang, j.h., yoo, s.h. (2014), energy consumption, co2 emissions, and economic growth: evidence from indonesia. quality and quantity, 48(1), 63-73. ibrahiem, d.m. (2015), renewable electricity consumption, foreign direct investment and economic growth in egypt: an ardl approach. procedia economics and finance, 30, 313-323. kao, c., chiang, m.h. (2000), on the estimation and inference of a cointegrated regression in panel data. center for policy research, 2000, 145. karikari, j.a. (1992), causality between direct foreign investment and economic output in ghana. journal of economic development, 17(1), 7-17. karimi, m.s., yusop, z. (2009), fdi and economic growth in malaysia. mpra paper, 14999(03). kasperowicz, r. (2014), electricity consumption and economic growth: evidence from poland. journal of international studies, 7(1), 46-57. kraft, j., kraft, a. (1978), on the relationship between energy and gnp. journal of energy and development, 3(2), 401-403. kyophilavong, p., shahbaz, m., anwar, s., masood, s. (2015), the energy-growth nexus in thailand: does trade openness boost up energy consumption? renewable and sustainable energy reviews, 46, 265-274. le viet, a. (2009), fdi-growth nexus in vietnam. nagoya university. mai. t.t. (2015), mối quan hệ nhân quả giữa sản lượng điện tiêu thụ và tăng trưởng kinh tế ở các nước asean. master’s thesis in economics. ho chi minh city: university of economics. mavrotas, g., kelly, g. (2001), old wine in new bottles: testing causality between savings and growth. manchester school, 69(1), 97-105. nguyen, m. (2003), fdi và tăng trưởng kinh tế việt nam. vietnam investment review, 24-12-2003. nguyen, t., wongsurawat, w. (2017), multivariate cointegration and causality between electricity consumption, economic growth, foreign direct investment and exports: recent evidence from vietnam. international journal of energy economics and policy, 7(3), 287-293. nguyen, t.p.h. (2004), foreign direct investment and its contributions to economic growth and poverty reduction in vietnam (1986-2001). peter lang, frankfurt am main, germany. nguyen, tta., vu, xnh., tran, tt., nguyen, mh. (2006), tác động của đầu tư trực tiếp nước ngoài tới tăng trưởng kinh tế ở việt nam_. _nxb khoa học và kỹ thuật. nkoro, e., uko, a.k. (2016), autoregressive distributed lag (ardl) cointegration technique: application and interpretation. journal of statistical and econometric methods, 5(4), 63-91. odhiambo, n.m. (2009), energy consumption and economic growth nexus in tanzania: an ardl bounds testing approach. energy policy, 37(2), 617-622. oviemuno, a.o. (2006), impact of energy on the manufacturing sector of nigeria. available from: www.searchwarp.com. [last retrieved on 2007 nov 01]. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. rostow, w.w. (1990), the stages of economic growth: a noncommunist manifesto. 3rd ed. cambridge: cambridge university press. shaari, m.s.b., hong, t.h., shukeri, s.n. (2012), foreign direct investment and economic growth: evidence from malaysia. international business research, 5(10), 100-106. tang, c.f. (2009), electricity consumption, income, foreign direct investment, and population in malaysia: new evidence from multivariate framework analysis. journal of economic studies, 36(4), 371-382. tang, c.f., tan, b.w., ozturk, i. (2016), energy consumption and economic growth in vietnam. renewable and sustainable energy reviews, 54, 1506-1514. temiz, d., gökmen, a. (2014), fdi inflow as an international business operation by mncs and economic growth: an empirical study on turkey. international business review, 23(1), 145-154. toda, h.y., yamamoto, t. (1995), statistical inference in vector autoregressive with possibly integrated processes. journal of econometrics, 66(1), 225-250. williamson, o. (1985), the economic institutions of capitalism: firms, markets, relational contracting. new york: free press. wolde-rufael, y. (2006), electricity consumption and economic growth: a time series experience for 17 african countries. energy policy, 34(10), 1106-1114. yildirim, e., aslan, a., ozturk, i. (2014), energy consumption and gdp in asean countries: bootstrap-corrected panel and time series causality tests. the singapore economic review, 59(2), 1450010. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020 469 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 469-475. effect of ecological, economic and social factors on the implementation of iso 14001 environmental management system in heavy industries in indonesia ridwan mahzun*, thamrin, bahruddin, nofrizal universitas riau, pekanbaru, jl. pattimura no. 9, pekanbaru, riau 28131, indonesia. *email: ridwanmahzun.unri@gmail.com received: 16 october 2019 accepted: 13 july 2020 doi: https://doi.org/10.32479/ijeep.8984 abstract this study originally tried to examine the influence of ecological, economic and social factors on the implementation of an environmental management system by taking a case study in heavy industry from a shipyard in batam indonesia with reference to iso 14001: 2015 environmental management system (ems) standards. ems is a framework that helps companies to manage the environmental impacts that arise from their activities. according to law no. 32/2009, ems includes policies on the arrangement, utilization, development, maintenance, recovery, supervision and control of the environment. the method used is structural equation modeling (sem), with a survey method by distributing questionnaires to respondents who know the work of the shipyard industry and the implementation of environmental management systems in this heavy industry. the study results show that economic and social factors have a positive effect on the application of iso 14001 environmental management systems in heavy industries in indonesia. these findings indicate the importance of applying iso 14001 in heavy industry, in particular, and the importance of considering various ecological, social and economic conditions of the company in such implementation. keywords: ecology, social factors, environmental management systems, heavy industry, indonesia. jel classifications: q57, q56 1. introduction the environmental management system is a process that runs and interacts where the structure, responsibilities, procedures, processes and resources for the implementation of environmental policy targets and targets can be coordinated with businesses that already exist in other fields such as operational, health and work safety (sunu, 2001). sroufe (2003) states that an environmental management system is a system and database that integrates procedures and processes for training personnel, monitoring, summarizing, and reporting specific environmental performance information to internal and external stakeholders of a company. hanoum (2000) describes an environmental management system as part of an overall management system that includes organizational structures, activity planning responsibilities, practices, procedures, processes and resources to develop, implement, achieve, review and maintain environmental policies. iso 14001 is an environmental management system that contains requirements specifications and guidelines for their use. these reviews imply that the concept and implementation of environmental management standards is a long chain of activities. on the other hand, there are certain industries which are considered to have a major impact on environmental preservation both land, water and air as well. in this context, heavy industry such as shipyards needs to be pressed according to existing regulations to comply with and apply environmental management standards. this is because the shipyard industry is most likely to produce heavy metal waste. heavy metals in this journal is licensed under a creative commons attribution 4.0 international license mahzun, et al.: effect of ecological, economic and social factors on the implementation of iso 14001 environmental management system in heavy industries in indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020470 dangerous waters, both directly and indirectly, affect the life of organisms and human health. this relates to the properties of heavy metals which are difficult to be degraded so that it is easily accumulated in the aquatic environment and its presence is naturally difficult to decompose, can accumulate in organisms including shellfish and fish and will endanger the health of humans who consume these organisms (rai, 2008). so it can be stated that besides having an impact on the economy and social, the shipyard industry has a considerable impact on the ecological environment. environmental damage in coastal areas is more dominated by rubbish, oil pollution waste, rubbish and materials left over from fabrication and steel construction processes, and others. the damage will largely affect human activities and the environment, such as the destruction of marine life, the threat of fishing settlements, the threat of fishermen’s livelihoods and so on. therefore, if this is not optimally addressed, it is feared that coastal and marine resources will be increasingly degraded. the existence of such a large impact on the economic, social and ecological environment needs to be dealt with as soon as possible for the existing impact. one of the countermeasures is to overcome the ecological impact with environmental management and monitoring efforts as stipulated in the ukl/upl for some physical, chemical and health environmental components for workers and communities around the shipyard industry environment. environmental management in shipyards becomes a crucial problem when it is related to waste management, where the volume of waste correlates with the evolution and dynamics of environmental management including policies that are coherent with the objectives, criteria, size and investment costs. this becomes important by conducting cost/benefit analysis to determine the overall economic efficiency of business investment by considering direct economic efforts (investment costs) and indirect economic efforts, such as pollution costs, costs allocated to affected human health, environmental rehabilitation costs. the european economic and social committee recommends that local governments and shipyards in europe operate in a safe and ecological environment (buruiana, 2015; odewumi and ajisegiri, 2013). this study originally attempted to examine the influence of ecological, economic and social factors on the implementation of an environmental management system by taking a case study in heavy industry from a shipyard in batam indonesia. it is motivated that one of the efforts to overcome the impact that occurs with the environmental damage caused by the shipyard industry is to implement better environmental management, one of which is by implementing an environmental management system (ems). ems is a framework that helps companies to manage the environmental impacts that arise from their activities. according to law no. 32/2009, ems includes policies on the arrangement, utilization, development, maintenance, recovery, supervision and control of the environment. one of the commonly used ems frameworks is iso 14001: 2015. 2. literature review and hypothesis 2.1. environmental management in international standards according to iso 14001: 2015 the environmental management system is a part of the overall management system which includes planning of organizational structure, activities, responsibilities, practices, procedures, processes and resources to develop, implement, achieve, review, and maintain environmental policies. iso 14004 is an environmental management system that contains general guidelines regarding the principles, systems and supporting techniques. the iso 14001 international standard is a vehicle to guarantee the performance of the environmental management system. the iso 14001 standard actually emerged as a result of the existence of several environmental issues that are often discussed in the community. these environmental issues are air pollution, water pollution, soil pollution, waste and hazardous materials, sound or noise and vibration, radiation, physical planning, use of materials or materials, use of energy and occupational safety and health of employees (tatiya, 2010). the definition of an environmental management system according to iso 14001: 2015 is an environmental management system that has been recognized internationally with certificates issued by the certificate board under the coordination of the international standards organization. the environmental management system that uses iso 14001 is an international standard that guarantees the performance of the environmental management system. is0 14001 standard actually emerged as a result of the existence of several environmental issues that are often discussed in the community. these environmental issues are air pollution, water pollution, soil pollution, waste and hazardous materials, noise and vibration, radiation, physical planning, material use, energy use and employee safety and health. iso 14001 is a standard that integrates and balances business interests with the environment and is also an internationally agreed standard for environmental management system requirements. this standard helps organizations improve their environmental performance through more efficient use of resources and waste reduction, gaining competitive advantage and trust from stakeholders including customers. the environmental management system helps organizations identify, manage, monitor and control their overall environmental problems. this means that iso 14001 can be easily integrated into the existing iso management system. iso 14001 is suitable for all types of organizations, be it individual companies, non-profit companies or governments. this requires that the organization considers all environmental problems related to its operations, such as air pollution, water and waste issues, waste management, soil pollution, climate change mitigation and adaptation, and resource use and efficiency. according to tibor and feldman (1996), an environmental management system is part of a management system that includes organizational structure, activity planning, responsibilities, practices, procedures, processes and resources to develop, implement, achieve, study, and maintain environmental policies. in mahzun, et al.: effect of ecological, economic and social factors on the implementation of iso 14001 environmental management system in heavy industries in indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020 471 other words, an environmental management system is a management system that plans, schedules, implements and monitors activities that aim to improve environmental performance, an environmental management system as part of an overall management system that includes organizational structure, responsibility planning activities, practices, procedures, processes and resources for developing, implementing, achieving, reviewing and maintaining environmental policies (hanoum, 2000). according to iso 14001: 2015 the environmental management system is part of the overall management system which includes planning organizational structure, activities, responsibilities, practices, procedure, processes and resources for developing, implementing, achieving, reviewing and maintaining environmental policies. meanwhile, the definition of an environmental management system according to iso 14001: 2015 is an environmental management system that has been internationally recognized with certificates issued by the certificate board under the coordination of the international standards organization. iso 14001 is a standard that integrates and balances business interests with the environment and is also an internationally agreed standard for environmental management system requirements. this standard helps organizations improve their environmental performance through more efficient use of resources and waste reduction, gaining competitive advantage and trust from stakeholders including customers. the environmental management system helps organizations identify, manage, monitor and control their overall environmental problems. this means that iso 14001 can be easily integrated into the existing iso management system. iso 14001 is suitable for all types of organizations, be it individual companies, non-profit companies or governments. this requires that the organization considers all environmental problems related to its operations, such as air pollution, water and waste issues, waste management, soil pollution, climate change mitigation and adaptation, and resource use and efficiency. 2.2. the concept of an environmental management system in indonesia in indonesia, the ems itself has been determined to be the national target listed in the appendix to the presidential regulation of the republic of indonesia number 59 of 2017 concerning the implementation of achieving sustainable development goals (tpb/sdgs). the target indicator is an increase in the number of companies implementing iso 14001 sni certification until 2019. the target is a proxy of the 12.6 tpb target which is to encourage companies, especially large and transnational companies, to adopt sustainable practices and integrate sustainability information in their reporting cycle. the 12.6 tpb goal is part of global 12 goal, which is to guarantee sustainable production and consumption patterns. like all iso management system standards, iso 14001 includes the need for continuous improvement of organizational systems and approaches to environmental problems. the new standard has been updated, with major improvements such as improved environmental management in the organization’s strategic planning process, greater input from leadership and a strong commitment to proactive initiatives that improve environmental performance. indonesian national standards (sni) iso 14001: 2015 is an international best practice, suitable to be a common criterion for sustainable practices for businesses in indonesia, so that collaboration between central and regional agencies is needed to increase the application of sni iso14001: 2015 ems. environmental management system (environmental protection and processing) according to law no. 32 of 2009 concerning environmental protection and processing article 1 paragraph 2 is a systematic and integrated effort undertaken to preserve environmental functions and prevent environmental pollution and/or damage which includes planning, utilization, control, maintenance of supervision, and law enforcement. the environmental management system adheres to a pdca (plan-docheck-act) system or a sustainable ‘system. likewise gastl (2008) states that the environmental management system follows the plan-do-check-act cycle, or pdca, where the plan-do-check-act (pdca) relationship with 7 principles of iso 14001: 2015 can be seen in figure 1. the diagram shows the process of first developing an environmental policy, planning an environmental management system, and then implementing it. this process also includes checking the system and following it up. this model is sustainable because the environmental management system is a process of continuous improvement in which the organization is constantly reviewing and revising the system. the environmental management system is a continuous cycle of planning, implementing, evaluating and improving processes, which are organized in such a way that the business objectives of the company/government and environmental objectives can be integrated and synergized. in indonesia, iso sni 14001: 2015 is now the latest version of the standard which has considered the risks and opportunities of figure 1: relationship of plan-do-check-act (pdca) with iso 14001: 2015 principles mahzun, et al.: effect of ecological, economic and social factors on the implementation of iso 14001 environmental management system in heavy industries in indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020472 the organization’s activities, products and services. by integrating it into business processes, this standard provides a reference for organizations to manage the environment while contributing to the environmental pillar of sustainable development. in addition, this standard has considered the life cycle perspective of activities, products and services starting from the extraction of raw materials, delivery, distribution, use, after being no longer used and final processing. thus it is expected that all stages of the life cycle have taken environmental aspects into account. the iswo sni 14001: 2015 ems is an environmental management standard adopted from the iso 14001: 2015 environmental management system. the publication of this standard was preceded by the commitment of the international business council (wbcsd) who wants to contribute to the environment as a responsibility to improve environmental quality. the indonesian vocal point of the environmental management standard of the islo sni 14001: 2015 in the international organization for standardization (iso) in the development of this standard is the national standardization body (bsn) and the substance content is in the ministry of the environment cq. center for environmental and forestry standardization. 2.3. hypothesis narwal and ajit (2014) states that aspects of emissions to air and water are the most significant environmental aspects in the indian manufacturing industry with respect to severity ie the effects of these environmental aspects are more dangerous to humans. likewise chatzinikolaou and ventikos (2014) in assessing the environmental impacts of ships from a life cycle perspective presents an assessment of the environmental impacts of the most important air emissions produced by oil tankers. several previous studies also showed the relationship between ecological aspects and the implementation of environmental management systems, among others, by liboni and cezarino (2012), integrated report committee (2014), struwig and lillah (2016), moretti et al. (2017) and nanok and onyango (2017). meanwhile, barasa (2015) sought to highlight how environmental and social aspects of monitoring related to the olkaria ii operation of the power plant were carried out by kengen. emphasis has been placed on how integration of iso 14001 into environmental monitoring has been achieved. a study conducted by basuki et al. (2016) shows that the impact on the environment which falls into the heavy category is dust due to the sandblasting process and odors due to the welding process. h1: ecology has a positive effect on the implementation of ems previous studies have suggested a link between economic aspects and the implementation of an environmental management system liboni and cezarino (2012) integrated report committee (2014), behera (2015), struwig and lillah (2016), moretti et al. (2017) and nanok and onyango (2017). likewise, several other studies such as those conducted by hollands and palframan (2014) state that significant barriers to further integration are identified in terms of cost, company structure and organizational size. meanwhile, irhoma et al. (2014) economic aspects in question is a matter of financial resources. h2: the economy has a positive effect on the implementation of ems irhoma et al. (2014) that the social aspects referred to are more about leadership and poor management, external political constraints of organizational culture. likewise, the results of previous research also support the assumption of a relationship between social aspects and the implementation of an environmental management system, among others, by liboni and cezarino (2012) integrated report committee (2014), behera (2015), struwig and lillah (2016), moretti et al. (2017) and nanok and onyango (2017). h3: social has a negative effect on the implementation of ems 3. research methods this research was conducted in batam island, riau islands province in several shipyard industries in sagalung, tanjung uncang, tanjung pinggir, sekupang, at the batam environment office and the batam city environmental development office in 2018 and 2019. the number of samples was determined using the purposive method sampling of 100 respondents. the analysis technique used is for quantitative analysis also called verification analysis using the sem (structural equation modeling) statistical test from lisrel statisticians. the reason for using sem (structural equation modeling) according to hair et al. (2006) is that using sem allows analysis of a series of relationships simultaneously so as to provide statistical efficiency. 5. research results 5.1. overview of research locations batam is one of the big industrial cities in indonesia, there are many industrial areas in the city of batam. in addition to the manufacturing industry sector, batam has many shipyard industries, fabrication industries and other heavy industries such as the pipe industry as well as the oil and gas support industry. the shipyard industry in batam’s free trade area and batam’s free port is the largest in indonesia. there are many shipyard industries in the tanjung uncang, sekupang and kabil regions (figure 2). however, based on information obtained from the batam shipyard and offshore association (bsoa) that the shipyard industry in batam is currently experiencing a decline of up to 80 percent. this is reinforced by the data of bank indonesia (2016) for the past 5 years, the contribution of ships and floating construction to the total exports of the riau islands tends to decline. the decline was affected by the crisis in the middle east and the decline in orders for transporting mining vessels after the minerba act was enacted. in addition, previously the number of workers absorbed by the shipping industry sector in batam reached 25 thousand people, so now only leaves around 11 thousand people, or reduced by around 14 thousand. although this industry is still running, it has not been able to boost the development of this industry sector, including absorbing the number of workers so that it contributes to the reduction in unemployment in batam. table 1 shows data on the decline in the number of companies and employees of shipyards in batam for the 2015-2017 period. 5.2. goodness of fit gof measurement results as presented in table 2 show eight measurement models that provide conclusions that the structural mahzun, et al.: effect of ecological, economic and social factors on the implementation of iso 14001 environmental management system in heavy industries in indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020 473 figure 2: map of batam island figure 3: standardized structural modelrelationship model between ecological aspects, economic aspects and social aspects and the implementation of ems shows fit with actual data. this means that overall the relationship model built in this study is fit with the actual data on the research object. after knowing the conceptual model used in this study is fit with the actual data, then further testing of the hypothesis proposed in this study. 5.3. hypothesis testing the next goal in the analysis of structural models is to estimate the parameters of influence between variables, which at the same time will also prove the research hypothesis. hypothesis testing results. sem analysis using lisrel software. the results of structural modeling can be seen in figure 1. thus, the following structural equation can be obtained: ems = 0.204*cl + 0.493*ec + 0.290*sc, errorvar.= 0.360 r² = 0.640 cl = ecological factor; ec= economic factor; sc= social factor; ems= implementation of ems from the first equation, as shown in figure 3, it can be explained that the direction of ecological, economic and social relations with the implementation of ems is positive. in other words, the sem analysis results obtained path coefficient from the ecological aspect of the environmental management system by 0.204, the path coefficient from the economic aspect to the environmental management system amounted to 0.493, and the path coefficient from the social aspect to the environmental management system amounted to 0.290. together (coefficient of determination) ecological, economic and social aspects of the environmental management system of 0.640, so that the total effect of all aspects is equal to 64.0%. in more detail, in testing the effect of ecology on the implementation of ems, the coefficient value of standardized regression weight between ecological variable and the implementation variable of ems is 0.204, meaning that ecological aspects influence the implementation of the environmental management system implemented by shipyard companies in batam related to the impact of existing industries mahzun, et al.: effect of ecological, economic and social factors on the implementation of iso 14001 environmental management system in heavy industries in indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020474 the second test on the effect of the economy on the implementation of the ems shows the standardized regression weight coefficient value between the economic variable and the implementation variable of the ems is 0.493, which means that the economic aspect influences the implementation of the environmental management system implemented by the shipyard company in batam related to the impact of the existing industry. the third test on the influence of social factors on the implementation of the ems shows the value of the standardized regression weight coefficient between the social variable and the implementation variable of the ems is 0.290, which means that social aspects are influential in the implementation of the environmental management system implemented by the shipyard company in batam related to the impact of the existing industry. 6. conclusion the findings show that ecological, economic and social factors influence the implementation of environmental management systems. in particular, the application of an integrated environmental management system is related to ecological, economic and social aspects, where the economic aspect has the highest correlation. the application of an integrated environmental management system in order to overcome the environmental impact of the implementation of the environmental management system of shipyard companies in batam currently meets the requirements listed in the clauses in iso 14001: 2015 although most shipyard companies in batam do not yet have iso 14001: 2015 certification. practically, the implementation of an environmental management system is related to ecological, economic and social aspects, so that in order to increase the role of the environmental management system, companies need to increase the application of an environmental management system to mitigate the impact on ecological aspects, especially pollution from toxic and dangerous waste heavy metals arising from company activities. in addition, it is necessary to formulate an environmental management strategy based on the results of the application of an integrated environmental management system with 4 priorities consisting of understanding the need for human resources in the organizational context, efforts to manage industrial waste, providing guidance, supervision in environmental management, developing an evaluation model and improving the system which is appropriate to the environment around the shipyard industry in batam. references barasa, p.j. (2015), integration of environmental management system in monitoring of environmental and social aspects associated with operation of olkaria ii geothermal power plant at olkaria in naivasha sub-county, nakuru county, kenya. california: proceeding stanford geothermal workshop, sgp-tr-204. p10. basuki, m. (2016), penilaian risiko lingkungan (environmental risk assessment) pada pekerjaan reparasi kapal di perusahaan galangan kapal subklaster surabaya. prosiding seminar nasional aplikasi sains dan teknologi, 1(1), 567-570. behera, p.k. (2015), socio-economic impact of industrialisation and mining on the local population: a case study of nalco industrial area, koraput. international journal of economics and management sciences, 4(273), 2. buruiana, d. (2015), development of waste management systems in an integrated shipyard. romania: university of galati. chatzinikolaou, s.d., ventikos, n.p. (2014), assessing environmental impacts of ships from a life cycle perspective. in: proceedings of the 2nd international conference on maritime technology and engineering. tamil nadu: martech. p15-17. gastl, r. (2008), kontinuierliche verbesserung im umweltmanagement: die kvp-forderung der iso 14001 in theorie und unternehmenspraxis. switzerland: vdf hochschulverlag ag. hanoum, m.a. (2000), manfaat implementasi sistem manajemen lingkungan iso 14001 pada pt. cikampek, indonesia, pupuk kujang, jawa barat: thesis faculty of agriculture bogor agricultural university. irhoma, a., su, d.z., higginson, m. (2014), analysis of the barriers to environmental management systems implementation in the libyan oil industry. key engineering materials 572, 672-677. liboni, l.b., cezarino, l.o. (2012), social and environmental impacts of the sugarcane industry. future studies research journal, 4(1), 196-227. moretti, l., di mascio, p., bellagamba, s. (2017), environmental, human health and socio-economic effects of cement powders: the multicriteria analysis as decisional methodology. international journal of environmental research and public health, 14(6), 645655. nanok, j.k., onyango, c.o. (2017), a socioeconomic and environmental analysis of the effects of oil exploration on the local community in lokichar, turkana county, kenya, international journal of management, economics and social sciences, 6(3), 144-156. narwal, m.s., ajit, r.b. (2014), an analysis of environmental impacts of various environmental aspects for indian manufacturing industries. international journal of research in engineering and technology, 3(3), 291. odewumi, s., ajisegiri, m. (2013), an appraisal of environmental health and safety management in the workplace (a study of continental shipyard limited). asian journal of natural and applied sciences, 2(2), 145-158. rai, p.k. (2008), heavy metal pollution in aquatic ecosystems and its phytoremediation using wetland plants: an ecosustainable approach. table 1: number of shipyards in batam year number of companies number of employees 2015 68 25,000 2016 32 18,000 2017 12 11,000 source: batam shipyard and offshore association (bsoa), 2018 table 2: goodness of fit testing research models no. goodness of fit index cut-off value results conclusion 1 chi-square small 11.125 good fit 2 significant probability ≥ 0.05 0.129 marginal fit 3 rmsea ≤ 0.08 0.078 good fit 4 gfi ≥ 0.90 0.871 marginal fit 5 agfi ≥ 0.90 0.828 marginal fit 6 tli ≥ 0.90 0.975 good fit 7 nfi ≥ 0.95 0,968 good fit 8 cfi ≥ 0.94 0.982 good fit mahzun, et al.: effect of ecological, economic and social factors on the implementation of iso 14001 environmental management system in heavy industries in indonesia international journal of energy economics and policy | vol 10 • issue 6 • 2020 475 international journal of phytoremediation, 10(2), 133-160. sroufe, r. (2003), effects of environmental management systems on environmental management practices and operations. production and operations management, 12(3), 416-431. struwig, m., lillah, r. (2016), factors influencing business implementation of environmental management systems. journal of economics, business and management, 4(4), 272-279. sunu, p. (2001), melindungi lingkungan dengan menerapkan iso 14001. jakarta: gramedia. tatiya, r.r. (2010), elements of industrial hazards: health, safety, environment and loss prevention. united states: crc press. tibor, t., feldman, i. (1996), implementing iso 14000: a practical, comprehensive guide to the iso 14000 environmental management standards. new york: mcgraw-hill. international journal of energy economics and policy vol. 4, no. 3, 2014, pp.457-464 issn: 2146-4553 www.econjournals.com 457 asymmetry of the oil price pass –through to inflation in iran rafik nazarian islamic azad university central tehran branch, iran. email: raf.nazariyan@iauctb.ac.ir ashkan amiri corresponding author, ma student in economics, islamic azad university central tehran branch, iran. email: ashkan_amiri2001@yahoo.com abstract: due to the structure of iran’s economy, oil revenues do not have a multi-dimensional role rather than a one-dimensional role in inflation. to put it differently, oil revenues impact inflation through exchange rate, government budget, importation, and imported inflation, monetary base, gdp growth, and government investment. these factors sometimes have contradictory effects on inflation. therefore, investigating and analyzing the pass-through of oil shocks into inflation and providing appropriate policies is quite essential. hence, the present research is primarily aimed at modeling the pass-through of oil price and investigating its effect on inflation by means of hidden co-integration approach, analysis, and presenting political implications to control the effect of oil shocks on inflation. in order to do so, monthly data of crude oil and consumer price index from march 2003 to march 2013 have been utilized. the findings demonstrated the pass-through of oil price to the cpi in iran. moreover, the coefficient calculated in this study revealed that the magnitude of this pass-through is quite large in the long run in iran’s economy. in addition, based on the cecm model which is a type of non-linear, asymmetric, and hidden co-integration method this research showed that the passthrough of oil price to inflation is asymmetrical. on the other hand, the dynamic short-term relationship, in the framework of cecm model, also confirmed the asymmetrical pass-through of positive and negative oil shocks into inflation. keywords: oil price; inflation; asymmetric pass-through; cecm model. jel classifications: c13; c22; e31; q43 1. introduction the influence of oil on a large number of economic activities all over the world has made it an absolutely crucial variable (cavalcanti et al., 2013). most studies indicate that oil will continue to have a large part in the world’s energy consumption due to reasons such as easy transportation, the lack of an appropriate substitute in some domains, and its wide application. therefore, it is evident that any change in oil-related variables such as supply, demand, and price will have worrying consequences for oil-producing and oil-consuming countries (tiwari, 2013). these changes may sometimes disrupt the macro-economic system of these countries (mehrara and mohaghegh, 2011). as a matter of fact, this is rooted in the positive oil shocks in the 1970’s and the recession in the global economy in its aftermath. after this period, a great number of studies dealt with the impacts of the changes of oil market on macro-economic variable such as inflation (subhani et al, 2012). some of these studies are (aastveit et al. (2013); mehrara and mohaghegh (2011); trung and vinh (2011); tang et al (2010; blake et al (2010); lescaroux and mignon (2008); guo and kliesen (2005)) most of these researches demonstrated a negative relationship between increase in oil price and economic activities. during the 1980’s when the global price of oil dwindled, it was expected that a boom in the global economy will dominate. this expectation was not met, leading to the emergence of the issue of asymmetrical effects of oil shocks on economic variables in the literature (arinze, 2011). after this period, many studies explored the asymmetrical effect of oil price on the economy of developed international journal of energy economics and policy, vol. 4, no. 3, 2014, pp.457-464 458 countries that are mainly oil importers (pavn and sola, 1996). this line of research has also confirmed the non-linear relationship between the pass-through of oil price and inflation (catik and karacuka, 2012). a deep analysis of these studies reveals that the theoretical foundations of these non-linear and asymmetrical effects are related to three factors (l'oeillet and licheron, 2008). first, if a country has a low level of inflation, the changes of oil prices would have a slight influence on the economy of that country. second, changes in oil prices triggered by natural factors will not lead to a dramatic rise of inflation, whereas changes fueled by price changes in financial markets would have a significant impact on inflation. finally, severe changes in the oil price have occurred in recent years which have had asymmetrical impacts on inflation (chen, 2009). therefore, the literature confirms the asymmetrical and non-linear effects of oil shocks on most economic variables such as inflation. it is unquestionable that the increase of oil price slows down the growth of global economy because oil is not a final product, but is considered as a production input affecting all economic activities. consequently, a change in the price of this material will pass through other products (chou and tseng, 2011). due to the position of oil in iran’s economy, which is a single-product economy, great dependence of gdp on oil revenues, and the influence of international political and economic fluctuations, investigating the impact of oil shocks on economic variables is quite essential. in light of the role of oil in countries’ economy especially in the previous decade, the importance of inflation as one of the main problems of iran’s economy, and recent oil shocks and their probable relation with price indicators, the main objective of this study is to examine the asymmetrical pass-through of oil price to inflation. 2. iran's economy and the oil asymmetric pass-through iran’s economy has always experienced double-digit inflation in recent years, which has been analyzed from different angles (ali asghari, 2013). a main feature of most oil-exporting countries such as iran is the dependence of the structure of their economy on oil revenues, leading these countries to be under the influence of economic prosperity or recession in the global economy (mehrara and mohaghegh, 2011). in iran, like some of the oil-exporting countries, the influence of oil revenues on the economy is determined in light of the country’s fiscal policy. moreover, a part of the oil revenues enter the economic cycle through expansionary monetary (selling the foreign exchange in the domestic market), highlighting the prime importance of oil revenues in these countries (jalaee and mohammadi, 2012). another important factor is the increase of the value of the national currency in oil-exporting countries which is the result of injecting foreign exchange earnings from oil exports to the domestic foreign exchange market. on the other hand, the fall of the value of the national currency (due to negative oil shocks) would increase import prices (farzanegan and markwardt, 2011); therefore, the price of production inputs will build up, influencing production and domestic prices. a part for these points, one of the features of oil revenues, or more precisely oil shocks, is that they are asymmetrical (shirinbakhsh and moghadasi bayat, 2011). it is generally believed that negative oil shocks decrease the level of common economic activities and domestic production and increases inflation (mehrara, 2008); however, positive shocks will not have a significant positive influence on employment and production. when oil revenues increase, a part of the effect of the injection of oil revenues is neutralized. this will raise the inflation level without enhancing production (eltejaei and arbab afzali, 2012). in order to account for these asymmetrical effects, we may argue that government spending goes up when oil revenues climb. in economies like iran, government spending leads to the exclusion of private sector investors from the economic cycle, and this will decrease the positive effects of government spending (kazemi and kazemikhasragh, 2013). conversely, when oil prices and exchange revenues fall, the decrease of government spending is not necessarily equivalent to the decrease of oil revenues because of the flexibility of government spending. the reason is that a significant decrease is not possible (pahlavani et al, 2010). in this situation, the government's construction budget falls, affecting investment, production, employment, and inflation (moshiri and banihashem, 2011). moreover, most projects will not be provided with enough funds to be finished and this leads to an economic inefficiency. therefore, the effects of oil shocks are asymmetrical in iran's economy, and it seems that the impacts of negative oil shocks on production and inflation are more detrimental in the long run in comparison with those of negative shocks. asymmetry of the oil price pass –through to inflation in iran 459 3. hidden co-integration and cecm model generally, the asymmetrical effects of an exogenous variable on an endogenous variable mean that the reaction of the dependent variable to a given amount of increase or decrease in the independent variable is not fixed (honarvar, 2009). various models have been proposed to model the asymmetrical relations between economic variables. one of these models that is able to model asymmetrical short-term, long-term, and dynamic relationships between the variables is cecm, which is going to be explained. the crouching error co-integration model (cecm) which is based on hidden co-integration method was proposed by granger and yoon in 2002. they examined the co-integration between the negative and positive integrative combinations of the time series data using the cecm model. based on this theory, if the combinations of the data related to two time series (positive and negative) have co-integration, these data have a hidden co-integrated relationship. hidden co-integration is an example of nonlinear co-integration which cannot be examined using the commonly used tests of linear co-integration. the model is as follows: assume that xt and yt are two time series stochastic variables which have been defined as follows: i t i ottt xxx      1 1 (1)     t i iottt yyy 1 1  (2) in which 0x and 0y are the primary values of tx and ty , t and t are residual and the mean of these two variables are zero, and the co-integration vector of tx and ty is linear. when the changes of ty and tx are asymmetric, we can have a hidden co-integration between them with a nonlinear vector. granger and yoon (2002) defined positive and negative shocks in this equation as follows:       iiiiii iiii iiii minmax oomax    , )0,(,)0,( ),min(,),( (3) thus:               t i i t i ottt t i i t i iottt yyy xxx 11 11 11 1   (4) therefore, based on the above formulas we will have:     ttot ttot yyyy xxxx (5) then:     tttt tttt yy xx   , , (6) there are estimations of the values of first-order differencing of both time series can be observed in the positive and negative changes, for example in   tt xx ,( ). the next step involves calculation of the changes of all the variable's positive and negative integrative combinations (e.g.,     tttt xxxx , ). x and y have hidden co-integration when their combination is also co-integrated. it is possible to examine hidden co-integration among all the possible combinations of the positive and negative components of ty and tx . international journal of energy economics and policy, vol. 4, no. 3, 2014, pp.457-464 460 cecm model is similar to standard ecm model except in analysis of the price changes with positive and negative components. observing the standardized ecm if ty and tx are co-integrated, the ecm model can explain the exogenous asymmetry with a co-integration vector of (1,). tjtjy p j itxi k i ttot tjt k i p j yitxttt yxxyx vyxxyy ji                 11 111 1 1 1110 )( )( (7) 4. empirical results in this study, the monthly time-series data of oil price and consumer price index have been used. these data cover the period from march 2003 to march 2013 and have been extracted from the website of central bank of iran. the abbreviations for the variables in this study are as follows: loil the natural logarithm of the oil price. dloil the logarithmic differential of the loil (the oil-price-return series). loil the cumulative aggregate of negative components of the loil. loil the cumulative aggregate of positive components of the loil. lcpi the natural logarithm of the consumer price index. dlcpi the logarithmic differential of the lcpi (the inflation series). lcpi the cumulative aggregate of negative components of the lcpi. lcpi the cumulative aggregate of positive components of the lcpi. 4-1. long-term relationship based on cecm model in order to avoid spurious regression, the stationary test of the variables of the study is examined. the results are shown in table 1. table 1. the results of the stationary test variable status check adf statistic critical value 1% 5% 10% lo i(1) -25.27 -2.56 -1.94 -1.61 lcpi i(2) -23.66 -2.56 -1.94 -1.61 lo+ i(1) -6.25 -2.56 -1.94 -1.61 loi(1) -9.51 -2.56 -1.94 -1.61 lcpi+ i(1) -6.17 -2.56 -1.94 -1.61 lcpii(2) -5.02 -2.56 -1.94 -1.61 table 1 demonstrates that all of the variables are non-stationary. the oil price series and its negative and positive components and also the positive components of consumer price index are firstorder-integrated and the consumer price index and its negative components are second-orderintegrated. therefore, the results of this table illustrate two basic points: l. there is a possible asymmetrical relationship between oil price and consumer price index. as shown in table 1, the oil price series is first-order-integrated while the consumer price index is second-order-integrated. this suggests that there are no linear and symmetrical long-term and shortterm relationships between these two variables. 2. there is possible asymmetrical co-integration between the components of the oil price and consumer price index. the analyzed components of the oil price and consumer price index do not have a similar cointegration level because the negative components of consumer price index are second-orderintegrated. asymmetry of the oil price pass –through to inflation in iran 461 therefore, the estimation of a short-term relationship between the oil price and consumer price index based on ordinary least square (ols) method is not correct unless the long-term relationship between these variables is confirmed with an identical integration level. this relationship will be tested through engle-granger two-stage test. in this test, a regression equation between non-stationary variables with similar integration level is estimated first, and then the stationariness of the residuals of the estimated equation is explored. if these residuals are stationary, there is a long-term relationship between these variables. the results of this test are depicted in the following table 2. table 2. the results of the engle-granger test variables trace criterion maximum eigenvalue criterion lcpi+ , lo+ have a long run relationship have a long run relationship lcpi+, lohave a long run relationship have not a long run relationship according to table 2, only the residual of the regression equation between ( loil and lcpi ) are stationary and the residuals of the regression equation of ( loil and lcpi ) are non-stationary. therefore, there is no long-term relationship between the oil price and consumer price index, but there exists a long-term relationship between their positive components. this indicates the asymmetrical relationship and hidden co-integration between these variables. equation 8 illustrates this: 1139.0: 000.0:)( 039.6986:98.0: )102.33()104.15(: 947.0186.0 2 dw statisticfprob statisticfr t loillcpi     (8) equation 8 demonstrates that the coefficient of the positive components of the oil price is positive and significant. therefore, be long-term pass-through of the oil price into consumer price index is about 0.95. on the other hand, there is no long-term relationship between the negative components of these variables; hence there is an asymmetrical long-term relationship between the analyzed components of these variables. consequently, there is an asymmetrical and hidden cointegration between the oil price and consumer price index. based on f-statistic and its probability level in equation 8, we can argue that the estimated model is significant. durbin-watson statistic also confirmed that there is co-integration between the components of the estimated model. in order to solve this problem, the newey-west (1987) fixed method has been used. the estimated relationship is a long-term one and entering the pauses of the dependent variable or the residual existing in short-term relationships is not permitted in this equation. 4-2. dynamic cecm model due to the fact that there is a long-term asymmetrical relationship between the positive components of consumer price index and oil price, in this section the modeling of dynamic cecm between the components of these series is examined and the results are shown in equation 9. 283.0: 150.0: 166.0: 411.1211:,000.0:)( 75.1:,72.0: )149.3()038.2()154.17()852.1(: )1(27.0)1(145.076.0001.0 2 probtestboxljung probtestlimcleod probtestarch statisticfstatisticfprob dwr t arectdloilpdlcpip      (9) the error correction model (ecm) in equation 9 indicates that the changes of the positive components of inflation (dlcp) are a function of the long-term equilibrium relationship and the changes of exogenous variables. this model links the short-term and long-term behavior of the international journal of energy economics and policy, vol. 4, no. 3, 2014, pp.457-464 462 positive components of the inflation and the oil price through the balancing component of error correction. the ect coefficient in this equation indicates that if a shock in the short run leads to the exclusion of the variables of the model from the long-term equilibrium, the impact of this shock will be evaded after around 7 periods. the coefficient of the positive components of the oil price equals 0.76, and this variable, like the long-term relationship indicates the short-run elasticity of the positive components of all products and services indicator towards the oil price changes or the pass-through of positive oil shocks into the price indicator. the identification tests of this model attest to the correctness of its estimation arch, mcleodli and ljung-box tests examined the residuals of equation 9. the results of these tests confirmed that there is no heteroskedasticity or autocorrelation between the residuals. it should be noted that the coefficient of ar(1) is negative and significant in equation 9, which has been happened in different studies ((bottazzi et al. (2012); nyberg (2011); kerekes (2009); egert (2009); nymoen (2008); perron and qu (2007); moneta and ruffer (2006); kaufmann (2003); fisher (2001); perron and ng (1998)). the possibility of a fractal process or existence of the long memory in the market (lavancier et al, 2010), non-linear structures in the residuals (ranaldo and soderlind, 2009), and numerous changes in the series under investigation (savva, 2009) are among the important reasons underlying the fact that the coefficient of ar is negative. moreover, the probability of having a negative coefficient for ar is far greater when the range of the endogenous variable data is from -1 to +1 (tang and yuan, 2012). 5. conclusion in this research, the symmetrical pass-through of the oil price to inflation in iran based on hidden co-integration approach investigated. the results of this study revealed that the short-term and longterm relationship between the positive components of consumer price index and oil price is non-liner. the estimation of this relationship has been modeled by cecm model. in line with the long-term relationship, the results of the dynamic model also confirmed the positive and meaningful relationship between the oil price and inflation. another important finding of this research is that the oil price in iran passes through inflation in an asymmetrical way. the coefficient of the pass-through of the oil price to inflation in the long-term relationship is 0.95 and in the dynamic short-term relationship is 0.76. this means that the pass-through of the oil price to inflation in iran is considerable. the recent changes in the oil price in iran in the beginning of 2013 are a clear instance of confirming these results, exerting a huge influence on inflation. moreover, iran’s economy have been greatly import-based in the recent years; therefore, any change in the oil market and hence the exchange market will have a profound effect on imported products price indicator and consequently inflation. furthermore, iran’s exchange revenues are mainly obtained through the exportation of oil, influencing inflation though monetary policies. hence, those involved in domestic monetary policies should bear in mind the fact that implementing independent monetary policies regardless of the changes in the oil market is not possible and would deviate attempts from the desired results. references aastveit, k.a., bjornland, h.c., thordrud, l.a., (2013), what drives oil prices? emerging versus developed economies, center for applied macroand petroleum economics (camp) working paper series, (2/2013), 1-43. ali asghari, m., (2013), the impact of oil price and inflation rate on iran economic growth (johnsen-jusilius co integration, journal of basic and applied scientific research, 3(1), 634639. arinze, p.e., (2011), the impact of oil price on the nigerian economy, jorind, 9(1), 211-215. blake, n.s., brown, s.p.a., yucel, m.k., (2010), oil price shocks and u.s. economic activity, washington d.c. discussion paper series (resources for the future), (dp 10-37), 1-37. bottazzi, g., secchi, a., tamagi, f., (2012), financial constraints and firm dynamics, small business economics, (doi 10.1007/s11187-012-9465-5), 1-23. catik, a.n., karacuka, m., (2012), oil pass-through to domestic prices in turkey: does the change in inflation regime matter?, economic research, 25(2), 277-296. cavalcanti, tiago, jalles, joão tovar., (2013), macroeconomic effects of oil price shocks in brazil and in the united states, applied energy, 104, 475-486. asymmetry of the oil price pass –through to inflation in iran 463 chen, s.s., (2009), oil price pass-through into inflation, energy economics, 31, 126–133. chou, k.w., tseng, y.h., (2011), pass-through of oil prices to cpi inflation in taiwan, international research journal of finance and economics, 69, 73-83. egert, b., (2009), the impact of monetary and commodity fundamentals, macro news and central bank communication on the exchange rate: evidence from south africa, economics department working papers, 33(692), 1-28. eltejaei, e., abab afzali, m., (2012), asymmetric impacts of oil prices and revenues fluctuation on selected macroeconomic variables in iran, journal of basic and applied scientific research, 2(8), 7930-7937. engle, r. f., (1982), autoregressive conditional heteroskedasticity with estimates of the variance of uk inflation, econometrica, 50, 987–1008. farzanegan, m.r., markwardt, g., (2011), the effects of oil price shocks on the iranian economy, energy economics, 31(1), 134–151. fisher, m., (2001), modeling negative autoregression in continuous time, publisher: federal reserve bank of atlanta. granger, c.w., yoon, g., (2002), hidden cointegration, department of economics, working paper, university of california, san diego. guo, h., kliesen, k.l., (2005), oil price volatility and u.s. macroeconomic activity, federal reserve bank of saint louis review, november/december, 669-683. honarvar, a. (2009), asymmetry in retail gasoline and crude oil price movement in the united states: an application of hidden co-integration technique, energy economics, 31, 395-402. jalaee, s.a., mohammadi, s., (2012), the effect of long and short time oil shocks on economic growth in iran, the romanian economic journal, 46, 69-92. kaufmann. s., (2003), business cycle synchronization of european countries. evidence from a panel of gdp series, oesterreichische national bank working paper, 83, 1-41. kazemi, z., kazemikhasragh, a., (2013), the impact of oil price fluctuations on macro-economic variables of demanding and supplying countries, international monthly refreed journal of research in management and technology, 2(4), 124-135. kerekes, m., (2009), growth miracles and failures in a markov switching classification model of growth, school of business & economic's discussion paper, economics, (2009/11), 1-62. lavancier, f., leipus, r., philippe, a., surgailis, d., (2010), detection of non-constant long memory parameter, econometric theory, 26(2), 406-425. lescaroux, f., mignon, v., (2008), on the influence of oil price on economic activity and other macroeconomic and financial variables, center of etudes perspectives informations internationals (cepii), (2008-05), 1-46. ljung. g.m., box. g.e.p., (1978), on a measure of lack of fit in time series model, biometrika, 65, 297-303. l'oeillet, g., licheron, j., (2008), oil prices and inflation in the euro area: a nonlinear and unstable relationship, institut d’etudes politiques, cinquiemes doctoriales de macrofi et seminaire diversite des systemes financiers et croissance. mcleod, a.i. & li, w.k. (1983), diagnostic checking arma time series models using squaredresidual autocorrelations, journal of time series analysis, 4, 269-273. mehrara, m. (2008), the asymmetric relationship between oil revenues and economic activations: the case of oil-exporting countries, energy policy, 36, 1164-1168. mehrara, m., mohaghegh, m. (2011), macroeconomic dynamics in the oil exporting countries: a panel var study, international journal of business and social science, 2(21). moneta, f., ruffer, r., (2006), business cycle synchronisation in east asia, european central bank working paper series, 671, 1-52. moshiri, s., banihashem, a., (2011), asymmetric effect of oil price shocks on economic growth in oilexporting countries, 34th iaee conference (stockholm). newey, w., west, k., (1987), a simple positive semi-definite, heteroskedasticity andautocorrelation consistent covariance matrix, econometrica, 55, 703–708. nyberg, h., (2011), forecasting the direction of the u.s. stock market with dynamic binary probit models,international journal of forecasting, 27, 561-578. nymoen, r., (2008), introductory dynamic macroeconomics, publisher: university of oslo. international journal of energy economics and policy, vol. 4, no. 3, 2014, pp.457-464 464 pahlavani, m., rahimi, m., shahabadi, a., zarei, a., (2010), can oil prices and gdp be cointegrated? an asymmetric co-integration approach, world applied sciences journal, 8(9), 1111-1115. pavn, m., sola, m. (1996), a reconsideration of the emprical evidence on the assymetric effects of negative moneysupply shocks: positive vs. negative or big vs. small?, birbeck collage working paper, 6, 1-29. perron, p., ng, s., (1998), an autoregressive spectral density estimator at frequency zero for nonstationarity tests, econometric theory, cambridge university press, 14(5), 560-603. perron, p., qu, z., (2007), a simplemodification to improve the finite sample properties of ng and perron’s unit root tests, economics letters, 94, 12-19. ranaldo, a., soderlind, p., (2009), safe haven currencies, review of finance, 10(3), 385-40. savva, c.s., (2009), international stock markets interactions and conditional correlations, journal of international financial markets, institutions and money, 19(4), 645-661. shirinbakhsh, s., moghadasi bayat, m., (2011), an evaluation of asymmetric and symmetric effect of oil export shocks on non-tradble sector of iranian economy, romanian journal of economic forecasting, 1, 106-124. subhani, m.i., hasan, s.k., qavi, i., osman, a., (2012), an investigation of granger causality between crude oil price and inflation in pakistan, international research journal of finance and economics, 100, 168-174. tang, w., wu, l., zhang, a.x., (2010), oil price shocks and their shortand long-term effect on the chinese economy, energy economics, 32, 3-14. tang, q., yuan, z., (2012), a hybrid estimate for the finite-time ruin probability in a bivariate autoregressive risk model with application to portfolio optimization, the north american actuarial journal (naaj), 16(3), 378-397. tiwari, aviral kumar. (2013), oil prices and the macro-economy reconsideration for germany: using continuous wavelet, economic modelling, 30, 636-642. trung, l.v., vinh, n.t.t., (2011), the impact of oil prices, real effective exchange rate and inflation on economic activity: novel evidence for vietnam, research institute for economics and business administrative (rieb) discussion paper series (kobe university), dp2011-09, 129. . international journal of energy economics and policy | vol 7 • issue 6 • 2017 61 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(6), 61-71. examining energy futures market efficiency under multiple regime shifts onder buberkoku* department of finance, faculty of business administration, yuzuncu yil university, van, turkey. *email: onderbuber@gmail.com abstract this study examines the west texas intermediate crude oil (wti), europe brent crude oil (brent), heating oil no. 2, and henry hub natural gas (ng) futures markets’ efficiency following fama’s (1970) weak-form efficiency hypothesis, using spot and futures prices at 1, 2, 3, and 4 months maturity based on the tests with unknown multiple regime shifts. the results show that it is important to consider the multiple regime shifts when determining whether energy futures markets are efficient. we find that wti and brent futures markets are not efficient, whereas ng and heating oil futures markets are efficient. additionally, the findings also shed light on discussions about the stationary properties of energy commodities and whether spot and futures prices are cointegrated. in particular, this study presents new evidence based on the unit root and cointegration tests with multiple structural breaks. keywords: energy commodity, futures market efficiency, multiple structural breaks jel classifications: g14, g15, q40 1. introduction changes in the energy commodity prices can lead to a significant impact on the global economy (sadorsky, 2006). therefore, the volatility in the energy market is an important issue for policy makers, producers, as well as risk managers. particularly in the last decade, such developments as increasing speculative trading and the us dollar fluctuations have caused a significant increase in the volatility of energy commodities (fan and xu, 2011). therefore, accurately predicting energy commodity prices and hedging their market risk have become crucial. moreover, futures market is one of the tools that can be used for forecasting future spot prices and managing the market risk of energy commodities. in other words, futures markets have two main functions: risk management and price discovery. however, the ability of futures markets to accurately fulfil these functions depends on whether the futures markets are efficient. based on the efficient market hypothesis developed by fama (1970), for a futures market to be efficient, it should fully reflect all available information about the underlying assets. in other words, the futures prices should be unbiased predictors of the future spot prices. there is much literature examining futures market efficiency for energy commodities. the results, however, are mixed. for example, lee and zeng (2011) investigate the west texas intermediate (wti) futures market efficiency under different maturities of futures contracts using quantile cointegration regression. they find that maturities of futures contracts affect the cointegration relationship between spot and futures oil prices, and only short maturities futures contracts are consistent with the efficient market hypothesis. switzer and el-khoury (2007) examine the efficiency of the nymex light sweet crude oil futures markets employing the johansen (1988) cointegration test, and report that their results support market efficiency even during the episodes of extreme conditional volatility. arouri et al. (2013) analyse the efficiency of nine energy and precious metal futures markets applying both linear and non-linear econometric techniques to test both longand short-run efficiencies. they indicate that although futures prices are cointegrated with spot prices, they are not unbiased predictors of future spot prices. shambora and rossiter (2007) test the efficiency of crude oil futures contracts based on the artificial neural network model and they document that the crude oil futures market is not efficient because it presents profitable trading opportunities. moosa and al-loughani (1994) perform several tests on market efficiency and unbiasedness hypotheses for wti futures market. they indicate that futures prices are neither unbiased nor efficient forecasters of the spot prices. buberkoku: examining energy futures market efficiency under multiple regime shifts international journal of energy economics and policy | vol 7 • issue 6 • 201762 further, peroni and mcnown (1998) apply two informative tests to wti, heating oil no.2, and unleaded gasoline futures markets, and reveal that the results are largely supportive of the efficiency hypothesis in three energy futures markets. kawamoto and hamori (2011) examine the market efficiency and unbiasedness among wti futures with different maturities. they report that wti futures market is efficient within an 8-month maturity, and efficient and unbiased within a 2-month maturity. lean et al. (2010) test the wti futures market efficiency using both mean-variance and stochastic dominance approaches and find that wti futures market is efficient. zhang and wang (2013) explore the price discovery and risk transfer functions in crude oil and gasoline futures markets by using the model introduced by garbade and silber (1983). they reveal that while crude oil futures markets perform well in both the price discovery and risk transfer functions, gasoline futures market perform well in only the price discovery function. gebremariam (2011) employs the causality and cointegration tests to analyse the efficiency of natural gas (ng) market and reveals that the market efficiency holds only for contracts with about 1 month to maturity. abosedra and baghestani (2004) evaluate the wti futures market efficiency using the 1-, 3-, 6-, 9-, and 12-month-ahead futures prices. they reveal that all the relevant crude oil futures prices are unbiased predictors of future spot prices. beck (1994) applies traditional cointegration techniques to test the futures market efficiency for five commodity markets. he reports that all five markets are sometimes inefficient, but no market is always inefficient. crowder and hamid (1993) evaluate crude oil futures market efficiency based on cointegration analysis and obtain results that support the simple efficiency hypothesis. despite these and similar studies, a limitation of the relevant literature, as maslyuk and smyth (2009) and chen et al. (2014) point out, is that few studies have so far considered the impact of structural breaks on energy commodities futures market efficiency. however, as widely reported in the literature, allowing for potential structural changes in economic process is an important issue (hatemi-j, 2008). financial crises, technological advances, policy changes, economic agents’ behaviour, and external shocks may cause structural breaks. in this regard, when we consider the last 15 years of energy commodities, developments such as the 2001 dot-com bubble crisis, 2003 iraq war, 2007–2008 subprime mortgage crisis, and 2011 arab spring may have caused structural breaks. besides, as fan and xu (2011), among others, point out, since 1999–2000, the energy commodity market has undergone significant changes, and the increasing demand of emerging markets and growing financialisation and liberalisation of commodity markets are among the main factors leading to these changes. furthermore, examining oil price dynamics, askari and krichene (2008) document that, even in the short run, there are large price changes in the oil market. therefore, all these discussions indicate that in analysing energy commodities, it is important to consider potential structural breaks. indeed, in recent literature, there are some studies allowing multiple breaks for energy commodities (lee and lee, 2009; noguera, 2013).1 1 moreover, energy commodity series’ plots also imply that series may have multiple breaks, especially in their level and slope of time trend. however, since the series’ plots are commonly shown in the literature, they are not presented in this paper, but are avaliable upon request. in this study, we aim to examine the wti, brent, heating oil (ht hereafter), and ng futures markets’ efficiency following fama’s (1970) weak-form efficiency hypothesis under the possible multiple structural breaks. in this context, first, the gregory and hansen (1996) (gh hereafter) cointegration test allowing one unknown regime shift and the hatemi-j (2008) (hj hereafter) cointegration test allowing two unknown regime shifts are used. then, a new cointegration test developed by maki (2012) allowing unknown breaks up to five is employed. the reason for following such a methodological procedure is because cointegration is a necessary condition for market efficiency. however, as pointed out by maki (2012), we generally do not have a priori information about the true number of breaks. therefore, if the true number of breaks is two, then the gh test is misspecified, which will lead to a poor performance. similarly, if the true number is one, the hj test will suffer from the same problem. additionally, if the true number is more than two, both tests will have a poor performance. thus, it also makes sense to use the maki (2012) test considering an unknown number of breaks. further, maki (2012) also shows that this newly developed test performs better than the gh and hj tests when cointegration relationship has more than three breaks or persistent markov switching. the contributions of the study to the literature are as follows. first, as mentioned previously, although structural breaks are one of the characteristics of energy commodities (lee and lee, 2009), the existing literature has focussed less on this issue thus far when examining the futures market efficiency based on fama’s (1970) hypothesis. therefore, this study fills this gap by employing tests allowing unknown multiple breaks. second, studies generally analyse a limited number of energy commodities, namely wti or brent, and use only nearby futures contracts or one maturity level of futures contracts. however, in this study, in addition to wti and brent, we also examine ht and ng markets. additionally, since only nearby or one maturity level of futures contract may not be sufficient to represent the whole futures market (tang et al., 2013) and different levels of maturity are also important in terms of hedging and efficiency (naraya et al., 2010), we use futures contracts at 1, 2, 3, and 4 months to maturity for each energy commodity. third, the impact of multiple structural breaks on parameter estimates is also considered, which is generally ignored even in studies based on structural break analysis. fourth, indirectly, this study also sheds light on discussions about the stationary properties of energy commodities and whether the spot and futures prices are cointegrated (narayan and liu, 2011; ozdemir et al., 2013; wang and wu, 2013). in particular, this study presents new findings based on the unit root and cointegration tests by allowing five endogenous multiple structural breaks. to the best of our knowledge, these tests have not been applied to these series before. the remainder of this paper is organised as follows: section 2 presents the method and market efficiency hypothesis. section 3 presents the empirical findings, while section 4 concludes. 2. methodology 2.1. data in this study, wti, brent, ho, and ng futures markets’ efficiency are examined using weekly data for spot and futures buberkoku: examining energy futures market efficiency under multiple regime shifts international journal of energy economics and policy | vol 7 • issue 6 • 2017 63 prices at 1, 2, 3, and 4 months to maturity, covering the period from january 1, 1999 to november 29, 2013. all the data are extracted from the energy information administration except for brent futures data, which is from the intercontinental exchange. 2.2. market efficiency hypothesis fama’s (1970) weak-form efficiency hypothesis is tested based on the following model: lst = α0+β0lfi,t+εt, i = 1, 2, 3, 4 months to maturity (1) where ls and lf are the logarithmic spot and futures prices at time t, α0 and β0 are the model parameters, and ε is the error term. based on the efficiency hypothesis, for futures prices to be an unbiased predictor of future spot prices, α0 = 0 and β0 = 1 restrictions in equation (1) should not be rejected jointly. if these restrictions are rejected, it means that either futures market is inefficient or that investors are not risk neutral, implying that they demand a constant or time-varying risk premium (arouri et al., 2013). in this study, we also test α0 = 0 and β0 = 1 restrictions separately, as ensuring β0 = 1 restriction is crucial in terms of market efficiency. this is because α0 = 0 restriction may not hold if there exists a constant or time-varying risk premium or transportation costs even when futures markets are efficient (chin et al., 2005; kawamoto and hamori, 2011; mckenzi and holt, 2002; wang and ke, 2005). therefore, as pointed out by kawamoto and hamori (2011), among others, β0 = 1 restriction represents the null hypothesis of market efficiency, whereas α0 = 0 and β0 = 1 joint restriction represents the null hypothesis of market efficiency and unbiasedness. 2.3. structural break and unit root tests we use the double maximum tests (udmax and wdmax tests) proposed by bai and perron (1998; 2003) to detect whether spot and futures series have structural breaks. the udmax and wdmax tests examine the null hypothesis of no structural breaks against the alternative hypothesis of an unknown number of breaks. then, we employ the augmented dickey–fuller (1979) (adf hereafter) unit root test to determine the integration order of the spot and futures series. additionally, because standard unit root tests are biased towards the rejection of null hypothesis of unit root (perron, 1989) in the presence of structural breaks, zivot and andrews’ (1992) (za hereafter) endogenous structural break test is also performed. za propose three different models: models a, b, and c, which allow a break in level, a break in slope, and a break in both level and slope, respectively. in our study, all three models are applied. however, one of the drawbacks of the za test is that it considers only one break, and as mentioned before, energy commodities may have multiple breaks. therefore, carrion-isilvestre et al.’s (2009) (cs hereafter) unit root test, which allows up to five breaks in the level and slope of time trend, is also employed. this test has five different test statistics, namely mzglsα λ( ) , msb ( ) gls λ , mzt gls ( )λ , mpt gls ( )λ , and pt gls ( )λ tests, which are the so-called m-class of tests analysed by ng and perron (2003). each test statistics has the null hypothesis of unit root. for this null hypothesis to be rejected, the estimated test statistics should be smaller than its critical values. 2.4. cointegration tests with structural breaks standard cointegration tests assume that the cointegration vector does not change over time. however, as pointed out by lee and lee (2009), energy commodity price series are usually affected by multiple breaks. therefore, it is more appropriate to use cointegration tests that allow structural breaks. for this, gh proposes a test allowing cointegrating relationship to change. however, the gh test allows only one endogenous break. therefore, hj (2008) extended the gh test to account for two endogenous structural breaks. both tests have three test statistics, namely the adf*, zt * and zα * tests, to test the null hypothesis of no cointegration. additionally, both tests consider three different structural change models: level shift model (c), level shift with trend model (c/t), and regime shift model (c/s). to be consistent with the aim of the study, we apply the regime shift model for both tests. based on equation (1), this model can be defined for the gh and hj tests as follows: lst = α0+α1d1t+β0lst+β1d1tlst+εt (2) lst = α0+α1d1t+α2d2t+β0lst+β1d1tlst+β2d2tlst+εt (3) where α0 and β0 are the intercept and slope coefficients before the break, α1 and α2 are the changes in the intercept at the time of first and second breaks, and β1 and β2 are the changes in the slope at the time of first and second breaks. d1t and d2t are the dummy variables and defined as follows: d t t t1 0 1 1 1 = ≤ [ ] > [ ]         , , ητ ητ ; and d t t t2 0 2 1 2 = ≤[ ] > [ ]         , , ητ ητ , where the unknown parameter τϵ (0,1) denotes the time of the break and [.] refers to the integer part. however, a limitation of the hj test is that it allows only two unknown breaks, so we also perform the maki (2012) cointegration test considering up to five endogenous breaks2. this test, based on tests for structural breaks introduced by bai and perron (1998; 2003) and the unit root test with structural breaks developed by kapetanious (2005), assumes that the unspecified number of breaks may be smaller than or equal to the maximum number of breaks set a priori. besides, this test is considerably less computationally intensive than methods widely used in the literature (maki, 2012). the maki (2012) test allows four different structural change models: level shift model (c), level shift with trend model (c/t), regime shift model (c/s), and trend and regime shifts model (c/s/t), which allows changes in both level, trend and regressors. based on equation (1), the regime shift model is given by; ls d lf d lft i it i k t i it t i k t= + + + += =∑ ∑α α β β ε0 1 0 1 (4) where k is the maximum number of breaks, and dit is the dummy variable defined as: 2 recently, çağli and mandaci (2013) also use the maki (2012) cointegration test while examining the long-run relationship between spot and futures prices under multiple regime shifts. buberkoku: examining energy futures market efficiency under multiple regime shifts international journal of energy economics and policy | vol 7 • issue 6 • 201764 d = 0if t t ,i =1,2&.5 1if t > t ,i =1,2,&..5 it bi bi ≤      where, tbi is the time period of the break. similar to the gh and hj tests, the maki (2012) test is also a residualbased cointegration test with null hypothesis of no cointegration and alternative hypothesis of cointegration with i breaks (i ≤ k). 3. results tables 1 and 2 present the structural break and unit root test results. both the udmax and wd max test statistics reject the null hypothesis of no structural breaks in each case. this implies that there is at least one structural break in each of the series. additionally, the adf unit root test results show that spot and four different futures prices of all energy commodities have a unit in their level form, whereas the first differences of series are found to be stationary. however, one reason why the adf unit root test is unable to reject the null hypothesis of unit root may be the presence of structural breaks. therefore, we also employ the za and cs unit root tests allowing one and five structural breaks. in all cases, the ca unit root test finds five breaks in the level and slope of time trend in each series. moreover, both the za and cs unit root tests show that all the series have unit roots in their level form at the 5% significance level. all these results indicate that all series are integrated of order one, i (1), and thus appropriate for cointegration analysis. they also shed light on discussions about the stationary properties of energy commodities, and show that the relevant energy commodity series are not stationary even if five structural breaks are allowed in the level and slope of time trend, indicating that shocks to these energy commodities will have a persistent effect on them. finally, these findings are also consistent with the recent findings by ozdemir et al. (2013) who adds to the relevant literature by allowing three breaks in the univariate time series models. having established that series are integrated of order one, the next step is to employ the cointegration tests. however, first, we check whether the model presented in equation (1) has a regime shift. for this, we use the cumulative sum (cusum) and cusum of squares test statistics. the results show that in all cases, the models have regime shifts3. then, we apply the gh and hj cointegration tests; table 3 shows the results. the results reveal that all three adf*, zt * and zα * tests statistics of both the gh and hj tests reject the null hypothesis of no cointegration at the 5% or a better significance level in all cases. this suggests that spot and four different futures prices of all energy commodities have cointegration relationship with regime shifts, and the maturity of futures contracts do not affect the cointegration relationship between the spot and futures prices. table 4 presents the maki (2012) test results4. first, in all cases, the maki (2012) test finds five regime shifts. however, the results 3 for simplicity, the results are not presented here, but are avaliable upon request. 4 we recognise a small error in maki’s (2012) original paper, namely that the order of models showing the critical values in table 1 titled ‘critical values of cointegration tests with multiple breaks’ (p. 2013) is wrong. the right order is that model 0, 1, 2, and 3 in table 1 should correspond to model (c), model (c/t), model (c/s), and model (c/s/t), respectively. additionally, to be sure, we sent an e-mail to mr. maki and he also verified this issue. therefore, in this study, we use the critical values according to this order, which means that critical values for regime shift models at the 5% significance level is -6.357. table 1: structural break and the adf and za unit root tests results variables udmax wdmax adf za (level) level first difference model a model b model c wti ls 74.866* 164.28* −3.388 (3) −14.106 (2)* −4.918 (3) −3.798 (3) −4.834 (3) lf1 75.348* 165.34* −3.054 (1) −23.748 (0)* −4.566 (1) −3.445 (1) −4.466 (1) lf2 79.643* 174.77* −2.925 (1) −23.402 (0)* −4.403 (1) −3.387 (1) −4.326 (1) lf3 85.110* 186.76* −2.789 (1) −23.353 (0)* −4.269 (1) −3.305 (1) −4.199 (1) lf4 89.425* 196.23* −2.648 (1) −23.304 (0)* −4.139 (1) −3.210 (1) −4.074 (1) brent ls 209.71* 406.18* −3.361 (0) −27.426* (0) −4.621 (0) −3.516 (0) −4.464 (0) lf1 261.79* 574.46* −3.260 (0) −29.046* (0) −4.532 (0) −3.436 (0) −4.349 (0) lf2 280.38* 615.26* −3.131 (0) −29.304* (0) −4.471 (0) −3.341 (0) −4.261 (0) lf3 295.25* 647.88* −2.985 (0) −29.414* (0) −4.380 (0) −3.240 (0) −4.214 (0) lf4 302.49* 663.78* −2.843 (0) −29.438* (0) −4.282 (0) −3.143 (0) −4.172 (0) ht ls 64.99* 123.06* −3.083 (2) −20.372* (1) −4.366 (2) −3.271 (2) −4.257 (2) lf1 68.79* 138.92* −2.814 (2) −20.042* (1) −4.243 (2) −2.997 (2) −4.079 (2) lf2 67.64* 148.42* −2.861 (1) −19.341* (1) −4.363 (1) −3.142 (1) −4.248 (1) lf3 81.24* 178.27* −2.779 (1) −19.143* (1) −4.320 (1) −3.093 (1) −4.196 (1) lf4 151.08* 331.52* −2.665 (1) −23.314* (0) −4.227 (1) −3.003 (1) −4.086 (1) ng ls 12.05* 16.775* −2.982 (1) −23.978* (0) −4.638 (1) −4.318 (1) −4.888 (1) lf1 9.023* 14.581* −2.681 (1) −23.312* (0) −4.469 (1) −3.873 (1) −4.541 (1) lf2 8.197** 14.09* −2.552 (1) −22.775* (0) −4.412 (1) −3.799 (1) −4.492 (1) lf3 8.504** 14.623* −2.475 (1) −22.607* (0) −4.410 (1) −3.849 (1) −4.576 (1) lf4 8.805** 15.139* −2.226 (1) −23.387* (0) −4.368 (1) −3.542 (1) −4.402 (1) the figures in parentheses are the lag lengths. adf unit root test is estimated with constant and trend. lf1, lf2, lf3, and lf4 are the futures prices at 1, 2, 3, and 4 months maturity, respectively. 15% trimming region is used for double maximum tests.* and ** denote significance at the 1% and 5% levels, respectively. wti: west texas intermediate, za: zivot and andrews, adf: augmented dickey–fuller, ng: natural gas buberkoku: examining energy futures market efficiency under multiple regime shifts international journal of energy economics and policy | vol 7 • issue 6 • 2017 65 obtained in this case are different from what the gh and hj tests indicate. in other words, it shows that spot and futures prices are not cointegrated for seven cases out of 16, constituting nearly 44% of all the pairs of spot and futures prices. one possible reason why maki (2012) test presents such different results may be that this test should be estimated using a trimming region of 5%, as proposed by maki (2012). however, up to now, as it is a more common approach in the literature, the trimming region is set to be 0.15 in all cases. therefore, following maki (2012), we also estimate the test with a trimming region of 0.05 to examine the robustness of the test; table 4 presents the results. here, we obtain similar findings to the gh and hj tests. in other words, the maki (2012) test shows that all pairs of spot and futures prices of energy commodities are cointegrated at the 5% or higher significance level with only two exceptions for brent, where spot and futures prices at 3 and 4 months maturities are found not to be cointegrated. these results imply that maki’s (2012) test findings may be sensitive to trimming value and spot and futures prices may not be cointegrated, at least in some cases, when it is allowed for five regime shifts. because of these mixed results from the maki (2012) test and that the relevant studies have thus far focused less on the impact of regime shifts on market efficiency, we decide to concentrate on the results from the gh and hj tests, and leave the potential impact of more than two regime shifts (i.e. five regime shifts) on market table 2: carrion-i-silvestre et al. (2009) multiple structural break unit root test results variables pt gls (λ) mpt gls (λ) mzα gls (λ) msbgls (λ) mzt gls (λ) m wti lns 29.704 8.9073 27.405 8.9073 −15.212 −46.5233 0.1808 0.1032 −2.7516 −4.7995 5 lnf1 22.331 8.9877 20.766 8.9877 −20.193 −46.4470 0.1572 0.1035 −3.1760 −4.7902 5 lnf2 25.172 9.0353 21.744 9.0353 −19.3417 −46.4379 0.1608 0.1036 −3.1096 −4.7869 5 lnf3 26.619 9.4540 22.973 9.4540 −19.395 −47.0014 0.1605 0.1035 −3.1140 −4.8006 5 lnf4 25.244 9.4149 23.0174 9.4149 −19.3602 −47.1842 0.1607 0.1032 −3.1107 −4.8112 5 brent lns 14.481 9.1748 13.085 9.1748 −32.803 −46.729 0.1234 0.1034 −4.0488 −4.7996 5 lnf1 17.651 8.9702 14.361 8.9702 −28.938 −46.3803 0.1314 0.1036 −3.8032 −4.7887 5 lnf2 20.4382 9.0736 18.370 9.0736 −23.824 −47.3634 0.1448 0.1021 −3.4493 −4.8624 5 lnf3 15.984 9.0080 14.249 9.0080 −29.4120 −46.4638 0.1304 0.1035 −3.8338 −4.7919 5 lnf4 15.849 9.0890 14.219 9.0890 −29.7070 −46.2793 0.1297 0.1038 −3.8530 −4.7753 5 ht lns 21.091 9.4415 19.769 9.4415 −22.5432 −46.9805 0.1489 0.1035 −3.3566 −4.8022 5 lnf1 21.672 9.5269 20.046 9.5269 −22.2365 −46.7829 0.1498 0.1039 −3.3331 −4.7885 5 lnf2 23.074 9.5392 21.052 9.5392 −21.1735 −46.7340 0.1536 0.1040 −3.2521 −4.7855 5 lnf3 29.796 9.5666 25.271 9.5666 −17.6496 −46.6935 0.1683 0.1042 −2.9706 −4.7798 5 lnf4 24.043 9.2045 21.728 9.2045 −20.7876 −48.1036 0.1549 0.1013 −3.2206 −4.8975 5 ng lns 15.788 9.5375 14.018 9.5375 −32.3786 −46.8690 0.1235 0.1038 −4.0010 −4.7949 5 lnf1 18.934 9.3295 16.187 9.3295 −27.8293 −47.5860 0.1337 0.1023 −3.7215 −4.8576 5 lnf2 23.364 9.1757 20.923 9.1757 −20.9780 −47.1732 0.1535 0.1028 −3.2205 −4.8296 5 lnf3 20.586 9.2718 18.2140 9.2718 −24.8640 −47.7026 0.1417 0.1019 −3.5244 −4.8803 5 lnf4 21.818 8.8876 19.8910 8.8876 −20.9785 −46.0276 0.1518 0.1038 −3.1858 −4.7703 5 *denotes 5% significance level. figures shown in standard format are test statistics. italicised and underlined figures indicate the critical values at the 5% significance level. m shows the number of breaks determined by the cs test. wti: west texas intermediate, za: zivot and andrews, adf: augmented dickey–fuller, ng: natural gas buberkoku: examining energy futures market efficiency under multiple regime shifts international journal of energy economics and policy | vol 7 • issue 6 • 201766 efficiency for future studies. however, it is also worth noting that the main contribution of using the maki (2012) test in our study is that contrary to the general findings in the relevant literature that indicate that spot and futures prices are cointegrated (e.g., switzer and el-khoury, 2007; tse, 1995), in fact, the results from the maki (2012) test show that they may not be cointegrated at least in some cases. this finding is also consistent with the recent findings by wang and wu (2013) who investigate the cointegration relationship between the spot and futures prices using the nonlinear threshold vector error correction model. therefore, future studies can investigate whether other spot and futures prices are cointegrated by employing the maki (2012) test. we believe that such an approach may provide further evidence to the relevant literature. turning to the gh and hj tests results, as indicated before, both tests show that all pairs of spot and futures prices are cointegrated in all cases. however, it is worth noting that the cointegration relationship is just a necessary condition for unbiasedness hypothesis. additionally, for futures markets to be unbiased predictors of future spot prices, α0 = 0 and β0 = 1 restrictions should also hold. however, as stated previously, since ensuring β0 = 1 restriction is more important in terms of market efficiency, we also test α0 = 0 and β0 = 1 restrictions separately. thus, we first estimate equation (1) that does not consider the structural breaks and check whether relevant restrictions hold. then, to allow for the potential impact of one and two regime shifts on parameter estimates and market efficiency, based on the gh and hj cointegration test results, we estimate equations (2) and (3) considering one and two breaks, and we further analyse whether the relevant restrictions hold5. following abosedra 5 more specifically, after estimating equation (1), ho: a0 = 0 and ho: b0 = 1 hypotheses are tested both jointly and separately; similarly, after estimating equation (2), ho: a0 + a1 = 0 and ho: b0 + b1 = 1 hypotheses are tested both jointly and separately, and lastly after estimating equation (3), ho: a0 + a1 + a2 = 0 and ho: b0 + b1 + b2 =1 hypotheses are tested both jointly and separately. additionally, for simplicity, throughout the paper, a parameter is used to represent both the a0 + a1 in equation (2) and a0 + a1 + a2 in equation (3). accordingly, b parameter is used to represent both the b0 + b1 in equation (2) and b0 + b1 + b2 in equation (3). table 3: gregory and hansen (1996) and hatemi-j (2008) cointegration tests results model gregory and hansen (1996) hatemi-j (2008) adf* z*t z * a adf* z*t z * α wti ls-lf1 −7.731* (0.406) −28.25* (0.416) −788.70* (0.416) −8.05* (0.296, 0.320) −28.77* (0.358, 0.517) −802.6* (0.358, 0.517) ls-lf2 −7.23* (0.402) −10.30* (0.402) −177.9* (0.402) −7.82* (0.154, 0.257) −11.3* (0.362, 0.515) −208.2* (0.362, 0.515) ls-lf3 −7.23* (0.673) −8.03* (0.402) −115.8* (0.402) −8.75* (0.397, 0.522) −8.77* (0.389, 0.512) −135.8* (0.389, 0.512) ls-lf4 −7.546* (0.402) −7.366* (0.410) −99.68* (0.410) −8.23* (0.401, 0.512) −7.96* (0.389, 0.511) −115.5* (0.389, 0.511) brent ls-lf1 −12.38* (0.388) −16.92* (0.388) −408.0* (0.388) −12.98* (0.388, 0.502) −17.71* (0.388, 0.507) −436.9* (0.388, 0.507) ls-lf2 −9.82* (0.388) −12.20* (0.388) −241.3* (0.388) −10.61* (0.388, 0.501) −13.28* (0.388, 0.503) −279.4* (0.388, 0.503) ls-lf3 −8.50* (0.388) −10.05* (0.388) −173.8* (0.388) −9.39* (0.388, 0.508) −11.3* (0.388, 0.507) −213.4* (0.388, 0.504) ls-lf4 −8.04* (0.671) −8.83* (0.412) −139.3* (0.412) −8.620* (0.388, 0.508) −10.02* (0.388, 0.507) −174.3* (0.388, 0.507) ht ls-lf1 −8.54* (0.302) −9.07* (0.300) −147.5* (0.300) −8.86* (0.150, 0.151) −9.36* (0.151, 0.153) −156.12* (0.151, 0.153) ls-lf2 −6.58* (0.300) −7.52* (0.300) −105.2* (0.300) −7.75* (0.153, 0.180) −7.93* (0.153, 0.155) −115.99* (0.153, 0.155) ls-lf3 −6.47* (0.332) −6.61* (0.300) −83.30* (0.300) −7.04* (0.150, 0.275) −7.00* (0.153, 0.277) −92.76* (0.153, 0.277) ls-lf4 −5.63* (0.426) −6.48* (0.427) −79.79* (0.427) −6.456** (0.150, 0.646) −6.87* (0.153, 0.277) −90.012** (0.153, 0.277) ng ls-lf1 −11.79* (0.279) −11.79* (0.279) −236.4* (0.279) −12.2* (0.317, 0.585) −12.2* (0.317, 0.585) −252.1* (0.316, 0.585) ls-lf2 −9.04* (0.279) −9.14* (0.279) −151.4* (0.279) −9.39* (0.379, 0.585) −9.54* (0.378, 0.584) −164.2* (0.378, 0.584) ls-lf3 −7.38* (0.279) −7.47* (0.279) −104.4* (0.279) −7.62* (0.371, 0.585) −7.78* (0.371, 0.584) −113.06* (0.371, 0.584) ls-lf4 −6.88* (0.278) −6.76* (0.279) −86.79* (0.279) −7.11* (0.266, 0.267) −6.97* (0.371, 0.577) −92.03* (0.371, 0.577) the gh test critical values are from table 1 of gh (1996. p. 109), and hj test critical values are from table 1 of hj (2008. p. 501). numbers in parentheses denote the break points. 15% trimming region is used for the gh and hj tests. * and ** denote the rejection of null hypothesis of no cointegration at the 1% and 5% significance levels, respectively. lf1, lf2, lf3, and lf4 are the futures prices at 1, 2, 3, and 4 months maturity, respectively. wti: west texas intermediate, za: zivot and andrews, adf: augmented dickey–fuller, ng: natural gas buberkoku: examining energy futures market efficiency under multiple regime shifts international journal of energy economics and policy | vol 7 • issue 6 • 2017 67 and baghestani (2004), hatemi-j (2008), narayan and narayan (2010), and kanjilal and ghosh (2013), we estimate equations (1), (2), and (3) with ordinary least squares; table 5 presents the results6. first, if we examine the parameter estimation results, both adjusted r2 and akaike information criterion (aic) values in all cases show that the models with one and/or two structural breaks are more appropriate than the model without structural breaks. the results also indicate that among the alternative structural break models, nearly in all cases, the model with two regime shifts should be preferred to the model with one regime shift. second, we analyse the market efficiency; tables 6 and 7 illustrates the results. starting with equation (1), the results show that the null hypothesis of α0 = 0 and β0 = 1 is rejected jointly at the 5% significance level in all cases, implying that none of the energy futures markets are unbiased predictors of future spot prices. besides, when the relevant restrictions are tested separately, the results show that the null hypothesis of α0 = 0 is rejected in all cases for wti, brent, and ng, whereas it holds for ht in all cases. this implies that there is non-zero risk premium in all cases except for ht. further, we see that β0 = 1 restriction is rejected for wti and ht futures markets in all cases, whereas it holds for brent futures market in the case of nearest contract and for ng futures market in all cases at the 5% significance level. these results reveal that although none of the energy futures markets is unbiased predictors of future spot prices, brent and ng futures markets are found to be efficient because they hold β0 = 1 restriction. however, it is worth noting that while efficiency is ensured for ng in all cases, it is valid for brent only for the nearest futures contract. as for the impact of structural breaks, starting with equation (2) which considers only one regime shift, the results show that the 6 following hj, while estimating equations (2) and (3), we consider the break points determined by zt test statistic. null hypothesis of α0 = 0 and β0 = 1 is again rejected jointly at the 5% significance level in all cases. besides, when the relevant restrictions are tested separately, the results show that the null hypothesis of α0 = 0 is rejected in all cases including ht. moreover, in this case, β0=1 restriction hold for ht futures market in the case of nearest three contracts and for ng in all cases, whereas it is rejected for brent and wti futures market for all four futures contracts at the 5% significance level. therefore, the existence of structural break has an important impact on testing market efficiency. from the results of equation (3), which allows two regime shifts, we see that the null hypothesis of α0=0 and β0 = 1 is again rejected jointly at the 5% significance level in all cases, meaning that none of the energy futures markets are unbiased predictors of future spot prices. besides, when the relevant restrictions are tested separately, the findings indicate that the null hypothesis of α0 = 0 is rejected in all cases, except for ht futures contracts at 3 and 4 months maturity. further, we see that β0 = 1 restriction does not hold for brent and wti futures market in any cases, whereas the restriction holds for ht futures market in the case of nearest contract and for ng futures market in all cases at the 5% significance level. therefore, equations (2) and (3) generally provide similar results in terms of market efficiency because both equations show that ht and ng futures markets are efficient, whereas brent and wti futures markets are not. however, it is also worth noting that the results also imply that the number of regime shifts may have an impact on testing market efficiency, although the impact is not as significant as that of the existence of structural breaks. lastly, it is also worth noting that nearly in all cases, aic (together with adjusted r2) indicates that, among the alternative three models, the most appropriate model is one with two-regime shifts, which is represented by equation (3). additionally, as discussed in the introduction section, it is more likely for energy commodities table 4: the maki (2012) cointegration test results model maki test statistic break points when triminning value is 0.05 trimming value 0.15 0.05 tb1 tb2 tb3 tb4 tb5 wti ls-lf1 −7.94* −7.94* 0.357 0.413 0.669 0.720 0.832 ls-lf2 −7.36* −8.38* 0.140 0.240 0.417 0.669 0.722 ls-lf3 −6.29 −8.27* 0.140 0.250 0.417 0.556 0.669 ls-lf4 −5.84 −7.14* 0.082 0.347 0.417 0.556 0.669 brent ls-lf1 −5.52 −7.10* 0.114 0.248 0.390 0.659 0.738 ls-lf2 −5.27 −7.07* 0.114 0.248 0.390 0.659 0.824 ls-lf3 −4.94 −5.468 0.114 0.390 0.460 0.679 0.845 ls-lf4 −4.94 −5.461 0.082 0.248 0.390 0.617 0.845 ht ls-lf1 −6.40* −7.10* 0.074 0.154 0.279 0.403 0.947 ls-lf2 −6.19 −7.03* 0.074 0.130 0.196 0.279 0.442 ls-lf3 −6.41* −7.01* 0.074 0.200 0.291 0.349 0.420 ls-lf4 −6.72* −7.39* 0.074 0.275 0.348 0.442 0.798 ng ls-lf1 −8.17* −8.17* 0.176 0.227 0.280 0.397 0.731 ls-lf2 −7.62* −7.82* 0.280 0.397 0.459 0.523 0.730 ls-lf3 −7.21* −7.52* 0.135 0.224 0.280 0.397 0.458 ls-lf4 −6.91* −7.13* 0.130 0.223 0.280 0.468 0.724 the maki (2012) test critical values are from table 1 of maki (2012. p. 2013). *denote the rejection of null hypothesis of no cointegration at the 5% significance level. lf1, lf2, lf3, and lf4 are the futures prices at 1, 2, 3, and 4 months maturity, respectively. wti: west texas intermediate, za: zivot and andrews, adf: augmented dickey–fuller, ng: natural gas buberkoku: examining energy futures market efficiency under multiple regime shifts international journal of energy economics and policy | vol 7 • issue 6 • 201768 table 5: parameter estimation results model a0 a1 a2 b0 b1 b2 r 2adjusted aic without structural break wti ls-lf1 0.0056* 0.9984* 0.9998 −6.8577 ls-lf2 0.0398* 0.9892* 0.9982 −4.6323 ls-lf3 0.0824* 0.9784* 0.9958 −3.7742 ls-lf4 0.1275* 0.9674* 0.9933 −3.2925 brent ls-lf1 −0.0128* 1.002* 0.9984 −4.5435 ls-lf2 0.0126 0.9955* 0.9969 −3.8661 ls-lf3 0.0400* 0.9888* 0.9949 −3.3712 ls-lf4 0.0725* 0.9812* 0.9928 −3.0103 ht ls-lf1 −0.0012 0.9925* 0.9978 −4.2802 ls-lf2 −0.0005 0.9856* 0.9945 −3.3573 ls-lf3 0.0015 0.9782* 0.9910 −2.8565 ls-lf4 0.0050** 0.9708* 0.9870 −2.4888 ng ls-lf1 −0.0183* 0.9995* 0.9852 −2.9977 ls-lf2 −0.0356* 0.9938* 0.9619 −2.0543 ls-lf3 −0.0417* 0.9853* 0.9343 −1.5073 ls-lf4 −0.0468* 0.9799* 0.9059 −1.1492 with one structural break wti ls-lf1 −0.0036 −0.0275* 1.002* 0.0052** 0.9998 −6.9135 ls-lf2 −0.0587* −0.1676* 1.021* 0.0278* 0.9988 −5.0797 ls-lf3 −0.0983* −0.2554* 1.036* 0.0396* 0.9975 −4.2898 ls-lf4 −0.1032* −0.3824* 1.042* 0.0631* 0.9962 −3.8519 brent ls-lf1 −0.1322* −0.0040 1.0403* −0.011** 0.9987 −4.7312 ls-lf2 −0.1736* −0.0799* 1.0564* −0.0020 0.9979 −4.2254 ls-lf3 −0.2207* −0.1295* 1.0744* 0.0010 0.9968 −3.8255 ls-lf4 −0.1425* −0.3832* 1.0525* 0.0614* 0.9955 −3.4925 ht ls-lf1 0.0256* −0.0351* 1.0454* −0.0450* 0.9981 −4.3860 ls-lf2 0.0488* −0.0662* 1.0820* −0.0791* 0.9953 −3.4928 ls-lf3 0.0721* −0.0906* 1.1184* −0.1203* 0.9923 −3.0034 ls-lf4 0.0380* −0.1247* 1.0416* 0.0250 0.9888 −2.6366 ng ls-lf1 −0.0371* 0.0140 1.0215* −0.0209** 0.9854 −3.0071 ls-lf2 −0.0926* 0.0542* 1.0529* −0.0607* 0.9629 −2.0780 ls-lf3 −0.1690* 0.1224* 1.1110* −0.1288* 0.9380 −1.5638 ls-lf4 −0.2366* 0.1729* 1.1652* −0.1837* 0.9132 −1.2271 with two structural breaks wti ls-lf1 −0.0127* 0.0228 −0.0461* 1.0044* −0.0073** 0.0106* 0.9998 −6.9167 ls-lf2 −0.1206* 0.2291* −0.4004* 1.0408* −0.0705* 0.0931* 0.9990 −5.1914 ls-lf3 −0.1470* 0.2604* −0.5817* 1.0520* −0.0850* 0.1344* 0.9978 −4.3941 ls-lf4 −0.1832* 0.3932* −0.8209* 1.0671* −0.1247* 0.1899* 0.9966 −3.9652 brent ls-lf1 −0.1322* 0.0728 −0.1261* 1.0403* −0.0286** 0.0279** 0.9987 −4.7508 ls-lf2 −0.1736* 0.1352** −0.3142* 1.0565* −0.0521* 0.0716* 0.9979 −4.2767 ls-lf3 −0.2207* 0.2297* −0.5179* 1.0744* −0.0832* 0.1188* 0.9971 −3.9106 ls-lf4 −0.2589* 0.3504* −0.7351* 1.0900* −0.1199* 0.1692* 0.9960 −3.6216 ht ls-lf1 0.0332* −0.0320 −0.0067 1.0443* −0.2040 0.1560 0.9980 −4.3771 ls-lf2 0.0635* −0.0218 −0.0503 1.0788* 0.0766 −0.1621 0.9952 −3.4701 ls-lf3 0.0934* −0.0449* −0.0501* 1.1186* 0.0396 −0.1794* 0.9923 −3.0091 ls-lf4 0.1266* −0.0693* −0.0544* 1.1648* 0.0048 −0.2001* 0.9889 −2.6460 ng ls-lf1 −0.0439* 0.0128 −0.0004 1.0274* −0.0272 0.0103 0.9856 −3.0257 ls-lf2 −0.0812* 0.0318 −0.0156 1.0398* −0.0512 0.0226 0.9636 −2.0949 ls-lf3 −0.1408* 0.1265 −0.0812 1.0821* −0.1276* 0.0594 0.9401 −1.5957 ls-lf4 −0.1835* 0.1652 −0.0976 1.1143* −0.1661* 0.0628 0.9162 −1.2593 *denotes 5% significance level. wti: west texas intermediate, za: zivot and andrews, adf: augmented dickey–fuller, ng: natural gas, aic: akaike information criterion buberkoku: examining energy futures market efficiency under multiple regime shifts international journal of energy economics and policy | vol 7 • issue 6 • 2017 69 to have multiple structural breaks. we hence give more weight to the results of equation (3). therefore, we come to the following conclusion: (i) because α = 0 and β0 = 1 hypothesis is rejected jointly in all cases, none of the energy futures markets examined are unbiased estimator of future spot prices. (ii) however, because β0 = 1 restriction holds for ng in the case of all futures contracts and for ht in the case of nearest futures contract, ng and ht futures markets are efficient markets. 4. concluding remarks and policy implications this study examines the wti, brent, heating oil, and ng futures markets’ efficiency, using spot and futures prices at 1, 2, 3, and 4 months maturity based on the multiple structural breaks. first, three different unit root tests allowing no break, one endogenous break, and five endogenous breaks are used to examine the stationary properties of the relevant energy commodities. then, the gregory and hansen (1996), hatemi-j (2008), and maki (2012) cointegration tests allowing one, two, and five endogenous breaks are used, respectively. besides, the cointegrating coefficients are estimated with a similar method used by hatemi-j (2008) that considers the impact of structural breaks on parameter estimates. our main findings are as follows. first, we find that spot and futures prices at four different maturities are not stationary at their level form even if five endogenous breaks are allowed in the level and slope of time trend. this means that a shock to these energy commodities may have a permanent effect. second, we find that all pairs of spot and futures prices have a cointegration relationship even if up to two regime shifts are allowed. this implies that spot and futures prices have a common stochastic trend. that is, they are driven by the same main factors, and the length of futures contracts does not have a noticeably different impaction the cointegration relationship. however, based on the maki (2012) cointegration test, when the five regime shifts are considered, the mixed results are obtained because of the sensitivity of the maki (2012) test to the trimming value. therefore, we think that future studies could investigate whether other spot and futures prices are cointegrated by employing the maki (2012) test. such an approach can provide further evidence to the relevant literature. third, it is important to consider the structural breaks when determining whether energy table 6: tests of market efficiency hypothesis model ols without structural break with one endogenous structural break α0=0, β0=1 α0=0 β0=1 α0=0, β0=1 α0=0 β0=1 wti ls-lf1 6.44* (0.0020) 8.29* (0.0040) 9.96* (0.0020) 24.76* (0.000) 25.67* (0.000) 22.78* (0.000) ls-lf2 32.51* (0.000) 45.24* (0.000) 53.27* (0.000) 200.4* (0.000) 217.7* (0.000) 194.6* (0.000) ls-lf3 48.25* (0.000) 83.98* (0.000) 91.82* (0.000) 221.5* (0.000) 227.3* (0.000) 202.6* (0.000) ls-lf4 65.98* (0.000) 126.6* (0.000) 131.6* (0.000) 236.0* (0.000) 246.5* (0.000) 221.4* (0.000) brent ls-lf1 26.75* (0.000) 5.17** (0.023) 1.322 (0.2510) 80.05* (0.000) 86.29* (0.000) 74.96* (0.000) ls-lf2 10.91* (0.000) 2.543 (0.1110) 5.15** (0.023) 132.4* (0.000) 170.8* (0.000) 153.0* (0.000) ls-lf3 12.69* (0.000) 15.79* (0.000) 19.51* (0.000) 158.6* (0.000) 208.9* (0.000) 188.3* (0.000) ls-lf4 19.87* (0.000) 36.61* (0.000) 39.16* (0.000) 185.2* (0.000) 264.5* (0.000) 243.5* (0.000) ht ls-lf1 17.74* (0.000) 0.977 (0.3230) 20.51* (0.000) 30.91* (0.000) 16.54* (0.000) 0.036 (0.8480) ls-lf2 21.69* (0.000) 0.089 (0.7640) 30.13* (0.000) 37.00* (0.000) 22.35* (0.000) 0.338 (0.5610) ls-lf3 26.29* (0.000) 0.375 (0.5400) 42.46* (0.000) 37.17* (0.000) 15.50* (0.000) 0.112 (0.7380) ls-lf4 29.36* (0.000) 2.974 (0.0850) 53.31* (0.000) 63.37* (0.000) 66.14* (0.000) 30.9* (0.0000) ng ls-lf1 48.62* (0.000) 6.79* (0.0090) 0.014 (0.9070) 47.58* (0.000) 5.438* (0.000) 0.009 (0.9230) ls-lf2 106.6* (0.000) 9.60* (0.0020) 0.754 (0.3850) 103.4* (0.000) 5.695* (0.017) 0.718 (0.3970) ls-lf3 128.2* (0.000) 7.367* (0.007) 2.466 (0.1160) 138.2* (0.000) 4.804* (0.028) 2.174 (0.1410) ls-lf4 132.2* (0.000) 6.27** (0.013) 3.136 (0.0770) 151.9* (0.000) 6.096* (0.014) 1.633 (0.2020) ols denotes ordinary least squares. relevant null hypotheses are examined with the wald test. numbers in parentheses are p values. * and ** denote1% and 5% significance levels, respectively. lf1, lf2, lf3, and lf4 are the futures prices at 1, 2, 3, and 4 months maturity, respectively. wti: west texas intermediate, za: zivot and andrews, adf: augmented dickey–fuller, ng: natural gas table 7: tests of market efficiency hypothesis model with two endogenous structural breaks α0=0, β0=1 α0=0 β0=1 wti ls-lf1 22.59* (0.000) 27.38* (0.000) 24.84* (0.000) ls-lf2 215.1* (0.000) 287.8* (0.000) 265.7* (0.000) ls-lf3 245.2* (0.000) 317.2* (0.000) 292.7* (0.000) ls-lf4 253.7* (0.000) 322.1* (0.000) 297.4* (0.000) brent ls-lf1 76.6* (0.000) 102.5* (0.000) 93.32* (0.000) ls-lf2 138.4* (0.000) 214.8* (0.000) 200.5* (0.000) ls-lf3 181.2* (0.000) 289.5* (0.000) 271.8* (0.000) ls-lf4 202.5* (0.000) 327.5* (0.000) 308.7* (0.000) ht ls-lf1 25.88* (0.000) 13.89* (0.000) 3.428 (0.0640) ls-lf2 28.68* (0.000) 12.74* (0.000) 4.257* (0.039) ls-lf3 32.74* (0.000) 14.27 (0.7056) 16.04* (0.000) ls-lf4 31.72* (0.000) 0.3300 (0.564) 23.21* (0.000) ng ls-lf1 21.76* (0.000) 8.812* (0.003) 1.909 (0.167) ls-lf2 52.49* (0.000) 11.47* (0.001) 0.842 (0.359) ls-lf3 75.72* (0.000) 14.12* (0.000) 0.752 (0.386) ls-lf4 97.46* (0.000) 14.34* (0.000) 0.335 (0.563) ols denotes ordinary least squares. relevant null hypotheses are examined with the wald test. numbers in parentheses are p values. * and ** denote 1% and 5% significance levels, respectively. lf1, lf2, lf3, and lf4 are the futures prices at 1, 2, 3, and 4 months maturity, respectively. wti: west texas intermediate, za: zivot and andrews, adf: augmented dickey–fuller, ng: natural gas buberkoku: examining energy futures market efficiency under multiple regime shifts international journal of energy economics and policy | vol 7 • issue 6 • 201770 futures markets are efficient. in this regard, when we consider the impact of the two structural breaks, we find that wti and brent futures markets are not efficient markets based on fama’s (1970) hypothesis, whereas ng and heating oil markets are found to be efficient. however, although efficiency is ensured for ng in the case of all four futures contracts, it is valid for heating oil market only in the case of nearest futures contract. these results imply that wti and brent futures markets can provide consistent abnormal profit for traders, and are not unbiased predictors of future spot prices; thus, these should not be used by economic agents to forecast spot prices. therefore, regulators should try to improve the information flows and reduce possible market manipulation in these markets (maslyuk and smyth, 2009; stout, 1995). contrarily, although ng and heating oil futures markets are not unbiased predictors of spot prices either, we find that they are efficient because they hold β0 = 1 restriction. however, it is worth noting that while efficiency is ensured for ng in the case of all four futures contracts, it is valid for heating oil market only in the case of nearest futures contract. this means that risk managers can use all four futures contracts to hedge the market risk of ng, but only the nearest futures contract to hedge the market risk of heating oil. 5. acknowledgments this research did not receive any specific grant from any funding agencies in the public, commercial, or not-for-profit sectors. references abosedra, s., baghestani, h. (2004), on the predictive accuracy of crude oil futures prices. energy policy, 32, 1389-1393. arouri, m.e.h., hammoudeh, s., lahiani, a., nguyen, d.k. (2013), on the short-and long-run efficiency of energy and precious. energy economics, 40, 832-844. askari, h., krichene, n. (2008), oil price dynamics (2002-2006). energy economics, 30, 2134-2153. bai, j., perron, p. (1998), estimating and testing linear models with multiple structural changes. econometrica, 66, 47-78. bai, j., perron, p. (2003), computation and analysis of multiple structural change models. journal of applied econometrics, 18, 1-22. beck, s.e. (1994), cointegration and market efficiency in commodities futures markets. applied economics, 26(3), 249-257. çağlı, e.f, mandaci, p.e. (2013), the long-run relationship between the spot and futures markets under multiple regime-shifts: evidence from turkish derivatives exchange. expert systems with applications, 40, 4206-4212. carrion-i-silvestre, j.l., kim, d., perron, p. (2009), gls-based unit root tests with multiple structural breaks under both the null and alternative hypotheses. econometric theory, 25(6), 1754-1792. chen, p.f., lee, c.c., zeng, j.h. (2014), the relationship between spot and futures oil price: do structural break matter? energy economics, 43, 206-217. chin, m.d., le blanc, m., coibion, o. (2005), the predictive content of energy futures: an update on petroleum, natural gas, heating oil and gasoline, national bureau of economic research nber, working paper, no. 11033. crowder, w.j., hamid, a. (1993), a co-integration test for oil futures market efficiency. journal of futures markets, 13, 933-941. dickey, d., fuller, w. (1979), distribution of the estimators for autoregressive time series with unit root. journal of american statistical association, 74, 427-431. fama, e.f. (1970), efficient capital markets: a review of theory and empirical works. journal of finance, 25, 383-417. fan, y., xu, j.h. (2011), what has driven oil prices since 2000? a structural change perspective. energy economics, 33, 1082-1094. garbade, k.d., silber, w.l. (1983), price movements and price discovery in futures and cash markets. the review of economics and statistics, 65(2), 289-297. gebre-mariam, y.k. (2011), testing for unit roots, causality, cointegration, and efficiency: the case of the northwest us natural gas market. energy, 36, 3489-3500. gregory, a.w., hansen, b.e. (1996), residual-based tests for cointegration in models with regime shifts. journal of econometrics, 70, 99-126. hatemi, j.a. (2008), tests for cointegration with two unknown regime shifts with an application to financial market integration. emprical economics, 35, 497-505. johansen, s. (1988), statistical analysis of cointegration vectors. journal of economics dynamics and control, 12, 231-254. kanjilal, k., ghosh, s. (2013), environmental kuznet’s curve for india: evidence from tests for cointegration with unknown structural breaks. energy policy, 56, 509-515. kapetanious, g. (2005), unit root testing against the alternative hypothesis of up to m structural breaks. journal of time series analysis, 26, 123-133. kawamoto, k., hamori, s. (2011), market efficiency among futures with different maturities: evidence from the crude oil futures market. journal of futures markets, 31, 487-501. lean, h.h., mcaleer, m., wong, w.k. (2010), market efficiency of oil spot and futures: a mean-variance and stochastic dominance approach. energy economics, 32, 979-986. lee, c.c., lee, j.d. (2009), energy prices, multiple structural breaks, and efficient market hypothesis. applied energy, 86, 466-479. lee, c.c., zeng, j.h. (2011), revisiting the relationship between spot and future oil prices: evidence from quantile cointegration regression. energy economics, 33, 924-935. maki, d. (2012), tests for cointegration allowing for an unknown number of breaks. economic modelling, 29, 2011-2015. maslyuk, s., smyth, r. (2009), cointegration between oil spot and future prices of the same and different grades in the presence of structural change. energy policy, 37, 1687-1693. mckenzi, a.m., holt, m.t. (2002), market efficiency in agricultural futures. applied economics, 34, 1519-1532. moosa, i.a., al-loughani, n.e. (1994), unbiasedness and time varying risk premia in the crude oil futures market. energy economics, 16(2), 99-105. narayan, p.k, narayan, s. (2010), modeling the impact of oil prices on vietnam’s stock prices. applied energy, 87, 356-361. narayan, p.k., liu, r. (2011), are shocks to commodity price persistence? applied energy, 88, 409-416. narayan, p.k., narayan, s., zheng, x. (2010), gold and oil future markets: are markets efficient. applied energy, 87, 3299-3303. ng, s., perron, p. (2003), lag length selection and construction of unit root tests with good size and power. econometrica, 69(6), 1519. noguera, j. (2013), oil prices: breaks and trends. energy economics, 37, 60-67. ozdemir, z.a., gokmenoglu, k., ekinci, c. (2013), persistence in crude oil spot and futures prices. energy, 59, 29-37. peroni, e., mcnown, r. (1998), noninformative and informative tests of efficiency in three energy futures market. journal of futures markets, 18, 939-964. perron, p. (1989), the great crash, the oil price shocks, and the unit root buberkoku: examining energy futures market efficiency under multiple regime shifts international journal of energy economics and policy | vol 7 • issue 6 • 2017 71 hypothesis. econometrica, 57, 1361-1401. sadorsky, p. (2006), modeling and forecasting petroleum futures volatility. energy economics, 28, 467-488. shambora, w.e., rossiter, r. (2007), are there exploitable inefficiencies in the futures market for oil? energy economics, 29, 18-27. stout, l.a. (1995), are stock markets costly casinos? disagreement, market failure and securities regulation. virginia law review, 81, 611-712. switzer, l.n., el-khoury, m. (2007), extreme volatility, speculative efficiency and hedging effectiveness on the oil future markets. journal of futures markets, 27, 61-84. tang, b.j., shen, c., gao, c. (2013), the efficiency analysis of european co2 futures market. applied energy, 112, 1544-1547. tse, y.k. (1995), lead-lag relationship between spot index and futures price of the nikkei stock average. journal of forecasting, 14(7), 553-563. wang, h.h., ke, b. (2005), efficiency tests of agricultural commodity futures markets in china. australian journal of agricultural and resource economics, 49, 125-141. wang, y., wu, c. (2013), are crude oil spot and futures prices cointegrated? not always! economic modelling, 33, 641-650. zhang, y.j., wang, z.y. (2013), investigating the price discovery and risk transfer functions in the crude oil and gasoline futures markets: some empirical evidence. applied energy, 104, 220-228. zivot, e., andrews, d.w.k. (1992), further evidence on the great crash, the oil price shocks, and unit root hypothesis. journal of business and economic statistics, 10, 251-270. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. . international journal of energy economics and policy | vol 8 • issue 3 • 201814 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(3), 14-21. the performance of hybrid arima-garch modeling and forecasting oil price chaido dritsaki* department of accounting and finance, school of management and economics, western macedonia university of applied sciences, greece. *email: dritsaki@teiwm.gr abstract modeling and forecasting oil prices is an important issue for many researchers. one of the methods used in forecasting oil prices is box-jenkins methodology through arima models. although these models provide accurate forecasting over a short time period, they are not able to handle the volatility and nonlinearity presented on data series. for this reason, on this paper we examine a hybrid arima-garch model in order to forecast the volatility in the return of oil prices. moreover, on this paper, the box-cox transformation is used for data smoothing for the stabilization of variance and reduction of heteroscedasticity. parameters’ estimation in the hybrid arima-garch model is employed by ml (maximum likelihood) method using the steps of marquardt’s algorithm (1963) and broyden-fletcher-goldfarb-shanno algorithm for optimization. the results of the paper showed that the hybridation of arima (33,0,14)-garch (1,2) model following normal distribution is the most suitable for forecasting the returns of oil prices. finally, we use both the dynamic and static procedure for forecasting. the results showed that the static procedure provides with better forecasting than the dynamic. keywords: arima, garch, oil price forecasting, hybrid arima-garch, box-cox transformation jel classifications: c33, o13, q43 1. introduction oil is considered to be one of the most important goods in the world. its use is ubiquitous in everyday life. due to its uniqueness, researchers need to develop a better understanding of its price dynamics so that industries that are supplied with or consume vast quantities of oil can take optimal decisions. oil’s dynamic modeling is a difficult task to accomplish because its price cannot be predicted in various time periods and it depends on many factors. during the past decades, oil price shows volatility. in 1999, during the asian crisis, iraq’s decision to increase oil production caused the decrease of oil price in the lowest level. in 2001, the dot-com bubble caused panic, reducing oil price until the beginning of 2002. following this upheaval, global economy regained its momentum, resulting in an upward trend of oil price. the factors that led to the reduction of oil production were the hostile relationships between the u.s. with the production countries. price oil reached its highest peak, when the housing bubble burst in the u.s. causing credit crisis. the reduction of oil price that followed until its stabilization after the economic crisis of 2008, is a challenge for researchers investigating for a model who would forecast these situations. moreover, forecasting returns of oil prices, which is considered a basic economic variable, influences consumers’ decisions, businesses and financial institutions, as well as governments. timely and reliable predictions of oil prices provide important information on those in the financial markets. this paper tries to develop a hybrid arima-garch model in order to investigate and forecast the characteristics of volatility in oil price using daily data from 20 october 1997 until 31 may 2017 for a total of 4980 observations. the rest of the paper is as follows: section 2 provides a brief literature review. section 3 presents the analysis of methodology. section 4 summarizes the data and the descriptive statistics. the empirical results are provided in section 5 and section 6 proposes the forecasting results. finally, the last section offers the concluding remarks. dritsaki: the performance of hybrid arima-garch modeling and forecasting oil price international journal of energy economics and policy | vol 8 • issue 3 • 2018 15 2. literature review during last years, there is great interest from researchers for modeling volatility and forecasting oil price. hansen and lunde (2005) argued that information related to oil price is necessary for modeling producers’ oil price as well as calculating risk measures. also, others found out that variations in oil prices have consequences not only in those countries that import but also in those countries that export oil. rothemberg and woodford (1996) have studied oil price instability in relation to inflation. hamilton and herrera (2004) in their paper argue the relationship between oil price and exports. yang et al. (2002) refer to the relationship between investment and oil price and elder and serletis (2009) examine the relationship between oil price and monetary policy. furthermore, there are a number of papers relating oil price with inflation, exchange rate, production and employment decrease and competitiveness loss. in all these papers, techniques using autoregressive models are employed (mirmirani and li, 2004), cointegration and error correction models (mohammadi 2009), garch models (sadorsky, 2006, and agnolucci, 2009), as well as neural networks (yu, et al. 2008). finally, it can be said that all papers reach the same conclusion that the returns of oil prices present a unit root, have excessive kurtosis, are negatively skewed and don’t follow gaussian distribution. also, the volatility on the returns of oil prices is clustering and persistent, consistent with predictions of garch variety models. 3. theoretical background the development and designing of arima models as forecasting tools of financial-economic variables is known as box-jenkins methodology (1976). this methodology tries to find an arima (p, d, q) model which satisfies the stochastic procedure where the sample derived from. box-jenkins methodology consists of four repetitive steps: identification model, parameters’ estimation, diagnostic tests and model’s forecasting ability. 3.1. arima models the autoregressive integrated moving average model of order p and q, arima (p, d, q) is one of the time series forecasting methods for the nonstationary data series. the arima (p, q, d) can be expressed as: ϕp(l)(1-l) d(yt-μ)=ϑq(l)et (1) or 1 l 1 l y ¼ = 1 l ei i i=1 p d t j j j=1 q t−       −( ) −( ) −        ∑ ∑ϕ ϑ (2) where,  p i i i=1 p l =1l( ) ∑ and  q j j j=1 q l =1l( ) ∑ are polynomials in terms of l of degree p and q. yt is. the time series, and et is the random error at time period t, with μ is the mean of the model. d is the order of the difference operator. φ1, φ 2,…, φp and ϑ1,ϑ2,…, ϑq are the parameters of autoregressive and moving average terms with order p and q respectively. l is the difference operator defined as δyt=yt-yt-1=(1-l)yt. arima models can be estimated following the box-jenkins approach. given that the stationary procedure is essential for an arima model, during the identification step data are transformed so that the time-series will become stationary. the stationary procedure is a necessary condition in building an arima model. 3.2. box-cox transformation method box-cox (1964) on their paper used a mathematical formula for the data transformation so that these can be more normally distributed and the variance equation corrects normality, linearity and reduces heteroscedasticity. the formula of the box-cox transformation is: y y if y if t t t * ln = ≠ ( ) =      λ λ λ λ 1 0 0 (3) where, yt yt are actual data in time t. yt * are the transformed data in time t. λ is the minimum value of mean square error of residuals. the transformation of the above equation is valid only for positive values of time series yt>0. if the values of time series contain also negative values, then the transformation will get the following form: y y if y if t t t * ( ) ln λ λ λ λ λ λ λ = +( ) − ≠ +( ) =       2 1 1 2 1 1 1 0 0 (4) where, λ1 is the transformation parameter, and λ2 is chosen such that yt>−λ2. the main objective in the analysis of data transformation in boxcox (1964) technique is to calculate (estimate) λ parameter. for this reason, two approaches are necessary. the first approach is using the maximum likelihood method to estimate data because it facilitates the calculation of likelihood function. also, maximum likelihood method is easy to obtain an approximate confidence interval for λ. the second approach uses bayesian method to confirm if the model is fully specified. 3.3. garch models garch models are used mainly for modeling financial time series that present time-varying volatility clustering. the general dritsaki: the performance of hybrid arima-garch modeling and forecasting oil price international journal of energy economics and policy | vol 8 • issue 3 • 201816 garch (r, s) model for the conditional heteroskedasticity according to bollerslev (1986) has the following form: yt=μt+zt (5) where, μt is conditional mean of yt. z is the shock at time t. zt=σtet (6) where, et→iid n(0,1). σ α α β σt i t i i r i t i i s z 2 0 2 1 2 1 = + +− = − = ∑ ∑ (7) where, σt 2 is the conditional variance of yt. α0 is a constant term. r is the order of the arch terms. s is the order of the garch terms. αi and βi are the coefficients of the arch and garch parameters, respectively. with constrains: α α β α β 0 11 0 0 1 2 0 1 2 > ≥ = ≥ = + == ∑ i i i i i s i r for i r for i s , , ,..., , , ,..., ∑∑ <          1 3.4. hybrid arima-garch model in order to recommend a hybrid arima-garch model, two stages should be applied. in the first stage, we use the best arima model that fits on stationary and linear time series data while the residuals of the linear model will contain the non-linear part of the data. in the second stage, we use the garch model in order to contain non-linear residuals patterns. this hybrid model, which combines arima and garch model containing non linear residuals patterns, is applied to analyze and forecast the returns of oil prices. 3.5. estimation of hybrid arima-garch model the hybrid arima-garch model is a non linear time series model which combines a linear arima model with the conditional variance of a garch model. the estimation procedure of arima and garch models are based on maximum likelihood method. parameters’ estimation in logarithmic likelihood function is done through nonlinear marquardt’s algorithm (marquardt, 1963). the logarithmic likelihood function has the following equation: ln [( ), ln[ ( ( )), ] ln[ ( )]l y d zt t t t t θ θ υ σ θ=      = ∑ 1 2 2 1 (8) where θ is the vector of the parameters that have to be estimated for the conditional mean, conditional variance and density function, zt denoting their density function, d(zt(θ),υ), is the log-likelihood function of [yt(θ)], for a sample of t observation. the maximum likelihood estimator θ̂ for the true parameter vector is found by maximizing (8) (dritsaki, 2017). 3.6. diagnostic checking of hybrid arima-garch model the diagnostic tests of hybrid arima-garch models are based on residuals. residuals’ normality test is employed with jarque and bera (1980) test. ljung and box (1978) (q-statistics) statistic for all time lags of autocorrelation is used for the serial correlation test. also, for the conditional heteroscedasticity test we use the squared residuals of autocorrelation function. 3.7. forecast evaluation on hybrid arima-garch models we use both the static and dynamic forecast. the dynamic forecast, also known as n-step ahead forecast, uses the actual lagged value of y variable in order to compute the first forecasted value. the static forecast (one-step ahead forecast) of yt+1 based on an hybrid arima-garch model is defined as: ( ) p q t t 1 t t -1 0 i t 1-i j t 1j i 1 j 1 ŷ (1) y y , y ,... y+ + + = = = ε = φ + φ + θ ε∑ ∑ (9) where the εs follow the stated garch model. to evaluate the forecast efficiency, we use two statistical measures, mean squared error (mse) and mean absolute error (mae). mse it computes the squared difference between every forecasted value and every realised value of the quantity being estimated, and finds the mean of them afterwards. mse has the following formula: ( ) n 2 i i i=1 1 ˆmse= y -y n ∑ (10) where, yi is the vector of observed values of the variable being predicted. iŷ is the vector of n predictions. mae it computes the mean of all the absolute, instead of squared, forecast errors. the formula is the following: n i i i 1 1 ˆmae y y n = = ∑ (11) 4. data and descriptive statistics the data used in our paper come from energy information administration. data are daily covering the period 20 october 1997 dritsaki: the performance of hybrid arima-garch modeling and forecasting oil price international journal of energy economics and policy | vol 8 • issue 3 • 2018 17 until 31 may 2017 including 4980 observations. using the value of λ = 0.3374 which was calculated from xlstat of excel and equation (3) from box-cox, we transformed oil price time-series. in the following figure 1, the closing values as well as transformed values in oil prices are presented. from figure 1 we can see that transformed data are less volatile from the initial ones. then, we examine normality in oil prices before and after the transformation. from figure 2, we can see that the transformed data have a better adjustment in relation to normal distribution. in the following table 1, the descriptive statistics of brent index are presented before and after box-cox transformation. the table 1 show that standard deviation of transformed series has reduced from 33.78242 to 2.392691. also, we can see that in the transformed data there is no normality even though it has been reduced. the daily return of oil price index after the data transformation is calculated as follows: r =ln y y ×100= ln y -ln y ×100t t t-1 t t-1       (12) where, yt is the daily closing price of oil price index at day t. yt-1 is the daily closing price of oil price index at previous day. rt are the daily returns of oil price index. in the following figure 3 we present the closing prices, returns and volatility of oil price index after the box-cox transformation. the volatility of oil prices is estimated from the daily squared returns (sadorsky, 2006). from figure 3 we note that daily closing prices of oil follow a random walk whereas returns from oil prices seem to be stationary. the confirmation in stationarity of the returns of oil price index is done with dickey-fuller (1979; 1981) and phillips-perron (1998) unit root tests. the results of table 2 confirm that returns of oil prices are stationary in their levels. consequently, for an arima (p, d, q) model the value for d = 0. on table 3, the descriptive statistics of the returns on brent are presented. the results on table 3 show that the mean of daily return on oil price is quite small in relation to its standard deviation. also, the return in oil prices appear small positive asymmetry and leptokurtosis with fat tails and jarque and bera (1980) statistic proves that the return of oil prices don’t follow normal distribution. on table 4, the autocorrelation diagram on the return of oil price is presented. figure 1: daily closing prices of oil before and after the transformation figure 2: normality test in daily prices of oil before and after transformation table 1: descriptive statistics of brent index before and after box-cox transformation brent box-cox brent mean 58.86256 mean 8.281836 median 53.15500 median 8.362000 maximum 143.9500 maximum 12.88700 minimum 9.100000 minimum 3.280000 standard deviation 33.78242 standard deviation 2.392691 skewness 0.436870 skewness −0.080189 kurtosis 1.951764 kurtosis 1.919715 jarque-bera 386.4104 jarque-bera 247.4930 probability 0.000000 probability 0.000000 sum 293135.6 sum 41243.54 sum sq. dev. 5682294.0 sum sq. dev. 28504.63 observations 4980 observations 4980 table 2: unit root tests of the returns of brent brent augmented dickey-fuller phillips-perron c c, t c c, t −69,3773*(0) −69,3816*(0) −69,3794*[9] −69,3809*[8] *,**,***show significant at 1%, 5% and 10% levels respectively. the numbers within parentheses followed by adf statistics represent the lag length of the dependent variable used to obtain white noise residuals. the lag lengths for adf equation were selected using schwarz information criterion. mackinnon (1996) critical value for rejection of hypothesis of unit root applied. the numbers within brackets followed by pp statistics represent the bandwidth selected based on newey-west (1994) method using bartlett kernel. c=constant, t=trend dritsaki: the performance of hybrid arima-garch modeling and forecasting oil price international journal of energy economics and policy | vol 8 • issue 3 • 201818 the above results indicate that autocorrelation coefficients on lags 14,15,18,33 and 35 and partial autocorrelation on lags 14,15,18,28 and 33 on the return of oil price is larger than both standard errors ( . )± = ± = ± 2 2 4980 0 02934 n . furthermore, according to ljung-box statistic on table 4, the existence of arch or garch cannot be rejected after the 13th lag. 5. empirical results following, we define the form of arima (p, d, q) model given the results of autocorrelation and partial autocorrelation diagram on table 4. the p and q parameters of arima model are determined from the coefficients of partial autocorrelation and autocorrelation respectively, comparing them with critical value ± 2 n =± 2 4980 =±0.02934 . from the values of coefficients of partial autocorrelation and autocorrelation on table 4 we see that the value of p will be p = 14 or p = 15 or p = 18 or p = 28 or p = 33 and for q will be q = 14, or q = 15 or q = 18, or q = 33 or q = 35. using the above values, we choose the best arima (p, 0, q) model from the smaller values of schwarz criterion. table 5 provides the values of p and q. the results of table 5 show that arima (33,0,14) model is the most suitable for the returns of oil index. in the following table 6 we get the estimations of this model. given the arch effects on the returns of oil price index, we proceed with the estimations of hybrid arima-garch models to examine the volatilities that exist in the related returns of oil price. moreover, from figure 3 the returns in oil prices show cluster in volatility. to catch this cluster we should use arima as well as garch models. thus, in the levels this time-series on returns of oil prices we have to find out the appropriate hybrid arimagarch model. estimation parameters’ is held with maximum likelihood method using the steps of marquardt’s algorithm (1963) and also broyden-fletcher-goldfarb-shanno algorithm optimization. estimation parameters’ as well as diagnostic tests figure 3: closing prices, returns and volatility of brent index table 3: descriptive statistics of the returns of brent indice brent mean 0.0093 median 0.0104 maximum 9.3977 minimum −10.2945 standard deviaton 1.1389 skewness 0.0288 kurtosis 9.0624 jarque and bera 7625.40 probability 0.000000 q (24) 54.619* observations 4979 *indicate statistical significance at 1% dritsaki: the performance of hybrid arima-garch modeling and forecasting oil price international journal of energy economics and policy | vol 8 • issue 3 • 2018 19 of normality, autocorrelation and conditional heteroscedasticity are presented on table 7. from the table 7 we can see that the hybrid arima (33,0,14)-garch (1,1) with normal distribution is the most appropriate. all coefficients are statistical significant and there seems no problem in diagnostics tests (except normality). persistence gets the value 0.99996 indicating high persistence in volatility in the oil price index. table 5: comparison of arima models within the range of exploration using schwarz criteria returns of brent arima (14,0,14) 3.098784 arima (14,0,15) 3.098888 arima (14,0,18) 3.099006 arima (14,0,33) 3.097087 arima (14,0,35) 3.099275 arima (15,0,14) 3.098691 arima (15,0,15) 3.101659 arima (15,0,18) 3.100680 arima (15,0,33) 3.098897 arima (15,0,35) 3.100866 arima (18,0,14) 3.098830 arima (18,0,15) 3.100695 arima (18,0,18) 3.101842 arima (18,0,33) 3.099034 arima (18,0,35) 3.100882 arima (28,0,14) 3.099227 arima (28,0,15) 3.101020 arima (28,0,18) 3.101108 arima (28,0,33) 3.099381 arima (28,0,35) 3.101431 arima (33,0,14) 3.096988 arima (33,0,15) 3.098987 arima (33,0,18) 3.099104 arima (33,0,33) 3.099902 arima (33,0,35) 3.099255 table 6: estimations of the arima (33,0,14) model of the returns of brent variables arima (33,0,14) ar (33) −0.054488 (0.000) ma (14) 0.058173 (0.000) sigmasq 1.289110 (0.000) log likelihood −7697.181 jarque and bera 7443.852 (0.000) q2 (5) 414.48 (0.000) x2 (10) 329.4274 (0.000) x2 (20) 387.4811 (0.000) x2 (30) 407.5273 (0.000) ar and ma denote the autoregressive and moving average terms respectively. sigmasq is the coefficient of variance error. q2(5)is the q-statistic of correlogram of squared residuals at fifth lag. x2 is the value of chi-square of arch test and (10), (20), (30) are the corresponding lags. p values in parentheses denote probability. table 4: correlogram on the return of oil prices autocorrelation partial correlation s. no ac pac q-stat prob 1 0.017 0.017 1.3596 0.244 2 0.006 0.006 1.5696 0.456 3 0.005 0.005 1.6877 0.640 4 −0.009 −0.009 2.0574 0.725 5 0.000 0.000 2.0576 0.841 6 −0.029 −0.029 6.3057 0.390 7 0.024 0.025 9.1804 0.240 8 0.008 0.007 9.5011 0.302 9 0.013 0.013 10.340 0.324 10 −0.005 −0.006 10.458 0.401 11 −0.023 −0.023 13.065 0.289 12 −0.011 −0.011 13.654 0.323 13 0.018 0.020 15.226 0.293 14 0.054 0.053 29.679 0.008 15 0.036 0.034 36.041 0.002 16 0.012 0.009 36.787 0.002 17 −0.011 −0.014 37.393 0.003 18 −0.035 −0.034 43.354 0.001 19 −0.013 −0.009 44.149 0.001 20 −0.021 −0.017 46.445 0.001 21 −0.024 −0.024 49.405 0.000 22 −0.013 −0.016 50.268 0.001 23 0.008 0.005 50.574 0.001 24 0.028 0.027 54.619 0.000 25 0.014 0.017 55.558 0.000 26 0.013 0.015 56.405 0.001 27 −0.002 −0.003 56.417 0.001 28 −0.027 −0.032 60.169 0.000 29 −0.008 −0.012 60.483 0.001 30 0.010 0.010 61.023 0.001 31 −0.002 −0.001 61.035 0.001 32 −0.013 −0.011 61.949 0.001 33 −0.053 −0.052 76.224 0.000 34 −0.004 0.000 76.292 0.000 35 −0.031 −0.024 81.064 0.000 36 0.003 0.010 81.100 0.000 dritsaki: the performance of hybrid arima-garch modeling and forecasting oil price international journal of energy economics and policy | vol 8 • issue 3 • 201820 6. forecasting for the forecasting of hybrid arima (33,0,14)-garch (1,1) model we use both the dynamic and static procedure. the dynamic procedure computes forecasting for periods after the first sample period, using the former fitted values from the lags of dependent variable and arma terms. this procedure is called n-step ahead forecasts. the static procedure uses actual values and not forecasted values of the dependent variable. this procedure is called one step-ahead forecast. in the following figure 4, we present the criteria for the evaluation of forecasting the returns of oil price using the dynamic and static forecast respectively. the figure 4 indicates that the static procedure gives better results rather than the dynamic because both mean squared error and mae are lower in the static process. 7. discussion and conclusion this paper aims to create a hybrid model combining arima model with garch models of high volatility in order to analyze and forecast the return of oil price. according to various papers, the returns of oil prices have unit root, excessive kurtosis and negative skewness so they don’t follow the gaussian distribution. instead, the transformation of box-cox was used to smooth the data. this resulted in the stabilization of variance and the decrease in heteroscedasticity. the empirical results of the paper showed that the hybrid arima (33,0,14)-garch (1,1) provides the optimal results and improves estimation and forecasting in relation to previous methods. in conclusion, the combination of robust and flexible linear arima models and the power of non linear garch models in handling volatility and the risk return of oil price, made hybrid models to be the most suitable for analysis and forecasting of time series. figure 4: dynamic and static forecast of the arima (33,0,14) garch model of the returns of brent table 7: estimates of the arima (33,0,14) garch models of the returns of brent distribution arch (1) garch (1,1) normal t-student ged normal t-student ged mean equation ar (33) −0.048140* −0.031854* −0.02396** −0.03227** −0.02503** −0.021140 ma (14) 0.055167* 0.059645* 0.051390* 0.043054* 0.046523* 0.045317* variance equation α0 1.070661* 1.051116* 1.015478* 0.002279* 0.001956* 0.002073** α1 0.176842* 0.232728* 0.204613* 0.055819* 0.041448* 0.047791* β1 ------0.944145* 0.958353* 0.951375* t-dist. dof/ged parameter 4.144466* 1.101958* --6.977499* 1.389278* diagnostic tests persistence ------0.99996 0.999801 0.999166 log l −7558.006 −7231.040 −7239.278 −6982.652 −6879.77 −6889.303 q2 (20) 399.13* 353.11* 368.90* 21.371 28.79*** 24.18 arch (10) 164.15* 148.70* 153.64* 11.391 20.69** 15.37 jarque and bera 8807.26* 9342.78* 9181.98* 736.55* 913.20* 816.71* the persistence is calculated as (α1+β1) for the garch model. log l is the value of the logarithmic likelihood. q2 (20) is the q-statistic of correlogram of squared residuals at twenty lag. arch (10) represents the f-statistic of arch test at 10th lag. *,**,***indicate statistical significance at 1%, 5% and 10% respectively dritsaki: the performance of hybrid arima-garch modeling and forecasting oil price international journal of energy economics and policy | vol 8 • issue 3 • 2018 21 references agnolucci, p. (2009), volatility in crude oil futures: α comparison of the predictive ability of garch and implied volatility models. energy economics, 31(2), 316-321. bollerslev, t. (1986), generalized autoregressive conditional heteroskedasticity. journal of econometrics, 31(3), 307-327. box, g.e.p., cox, d.r. (1964), an analysis of transformations. journal of the royal statistical society, series b, 26(2), 211-252. box, g.e.p., jenkins, g.m. (1976), time series analysis. forecasting and control. san francisco: holden-day. dickey, d.a., fuller, w.a. (1979), distributions of the estimators for autoregressive time series with a unit root. journal of american statistical association, 74(366), 427-431. dickey, da., fuller, w.a. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica, 49(4), 1057-1072. dritsaki, c. (2017), an empirical evaluation in garch volatility modeling: evidence from the stockholm stock exchange. journal of mathematical finance, 7, 366-390. elder, j., serletis, a. (2009), oil price uncertainty. energy economics, 31(6), 852-856. hamilton, j.d., herrera, a.m. (2004), oil shocks and aggregate macroeconomic behavior: the role of monetary policy: a comment. journal of money, credit and banking, 36(2), 265-286. hansen, p.r., lunde, a.s. (2005), a forecast comparison of volatility models: does anything beat a garch(1, 1)? journal of applied econometrics, 20(7), 873-889. jarque, c., bera, a. (1980), efficient tests for normality, homoscedasticity and serial independence of regression residuals. economics letters, 6, 255-259. ljung, g.m., box, g.e.p. (1978), on a measure of a lack of fit in time series models. biometrika, 65(2), 297-303. mackinnon j.g. (1996), numerical distribution functions for unit root and cointegration tests. journal of applied econometrics, 11(6), 601-618. marquardt, d.w. (1963), an algorithm for least squares estimation of nonlinear parameters. journal of the society for industrial and applied mathematics, 11, 431-441. mirmirani, s., li, h.c. (2004), a comparison of var and neural networks with genetic algorithm in forecasting price of oil. advances in econometrics, 19, 203-223. mohammadi, h. (2009), electricity prices and fuel costs: long-run relations and shortrun dynamics. energy economics, 31(3), 503-509. newey, w.k., west, k.d. (1994), automatic lag selection in covariance matrix estimation. review of economic studies, 61(4), 631-654. phillips, p.c., perron, p. (1998), testing for a unit root in time series regression. biometrika, 75(2), 335-346. rothemberg, j.j., woodford, m. (1996), imperfect competition and the effects of energy price increases on economic activity. journal of money, credit and banking, 28(4), 549-577. sadorsky, p. (2006), modeling and forecasting petroleum futures volatility. energy economics, 28(4), 467-488. yang, c.w., hwang, m.j., huang, b.n. (2002), an analysis of factors affecting price volatility of the us oil market. energy economics, 24(2), 107-119. yu, l., wang, s., lai, k.k. (2008), forecasting crude oil price with an emd-based neural network ensemble learning paradigm. energy economics, 30(5), 2623-2635. . international journal of energy economics and policy | vol 10 • issue 4 • 2020102 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(4), 102-107. energy security concept in russia and south korea uyeh daniel dooyum1*, alexey mikhaylov2, igor varyash3 1kyungpook national university, daegu, korea, 2financial university under the government of the russian federation, moscow, russia, 3financial research institute of the ministry of finance of the russian federation, moscow, russia. *email: uyeh.daniel@yahoo.com received: 16 december 2019 accepted: 10 april 2020 doi: https://doi.org/10.32479/ijeep.9116 abstract one of the key problems hindering the strengthening of cooperation between south korea and the russian federation not only in the energy sector, but also in other areas, is a negative impact in a kind of historical memory of previous experience of cooperation, or rather failure in implementation of projects or lack of implementation in general. many projects in potentially promising areas remain on paper. projects have never been implemented include modernization and commissioning by a joint russian-north korean enterprise with the participation of russian railways of the railway section from the khasan station (russia) to the port rajin in order to transit from south korea and gain access states of the korean peninsula to the trans-siberian railway. keywords: energy sources, south korea energy policy, resource saving, economic development, energy cooperation jel classifications: c30, d12, q41, q48 1. introduction the concept of global energy security as important component of national security of any importing state or exporter and a factor that has a significant impact on its economic and social prosperity is of particular interest to us in terms of explanations of the motivation of states to cooperate in the energy sector. according to the international energy agency, energy security is continuous access to energy resources at affordable prices. energy security in the long run perspective this is a timely investment in energy supplies, taking into account meeting the needs for a comprehensive economic sustainable development while in the short term is a focus on the ability of the energy system to respond quickly to sudden changes in supply chains (chiemchaisri et al., 2012; gardner et al., 1993). energy security includes the following elements: 1. security of supply is vital for importing countries energy resources and is guaranteed long-term and stable supplies at low prices 2. security of demand is a concept related to exporting countries interested in stable financial income from sales of own energy at high prices 3. transit security is in the zone of interests of transit countries and to maximize profits for the provision of its territory for the transport of energy. strengthening energy interdependence and globalization of energy spheres that occurred after the 70s years of last century, generally forcing states to solving the issue of both their own energy security problems and regionally and internationally recognize the need to create international, transnational and multinational unions of states, task which would be minimizing the number of threats to global energy security. minimization as such includes the following measures: chain energy supplies, diversification of transit routes, security on energy infrastructures, preventing the use of energy in as an instrument of political blackmail, ensuring predictability and stability energy markets (chiemchaisri et al., 2012; gardner et al., 1993). this journal is licensed under a creative commons attribution 4.0 international license dooyum, et al.: energy security concept in russia and south korea international journal of energy economics and policy | vol 10 • issue 4 • 2020 103 therefore, for reasons of energy security states, realizing the existing global interdependence in energy sphere, they opt for cooperation in order to minimize negative social and economic effects caused by insufficient energy security. russia is also actively promoting international energy cooperation, which indicates her intentions to build long-term cooperation in fuel and energy sector, including with the republic of south korea (chiemchaisri et al., 2012; gardner et al., 1993). 2. literature review until the 80s the republic of korea was perceived by the soviet government as north korea temporary breakaway territory, with which it worked closely, and therefore, there could be no talk of any cooperation between the ussr and the republic of south korea in any economic, neither culturally nor in any other plans. nonetheless, from south korea attempted to establish economic cooperation with the ussr back in late 70s early 80s (moiseev, 2017a; moiseev, 2017b; moiseev and sorokin, 2018). however, when gorbachev came to power, the situation changed: he drew attention on the potential for cooperation with the republic of south korea: in september 1988, gorbachev during a speech. in his speech in krasnoyarsk, he first mentioned the possibility of establishing economic relations with the republic of south korea. in addition, a kind of catalyst for the rapprochement of two states in the second half of the 80s served as the 1988 olympic games held in seoul. guests from the ussr to korea then there was most of all other foreign states (chiemchaisri et al., 2012; gardner et al., 1993). returning from the olympics, the athletes brought with them various korean equipment: tvs, copy machines, buses, cars. gradually, with the increase in trade between the two countries arose the need to switch to trade directly (bove and lunghi, 2006; cai et al., 2011). the course towards the establishment and development of direct trade, cultural and technological ties with the republic of south korea on a non-governmental basis. it was assumed that such the format of the relationship was a temporary step necessary for the transition to the establishment official diplomatic relations (bansal et al., 2013). given the mutual interest of the parties in strengthening cooperation, in 1988 “korean trade promotion corporation” (korean tradeinvestment promotion agency) and the ussr chamber of commerce and industry signed memorandum addressing the promotion of trade and system development trade missions of two states. in 1989, trading was opened, representations in the capitals of both parties. thus, it stood at the origins direct bilateral trade relations, and the legal foundations of trade economic cooperation. with the advent of the legal and organizational framework trade cooperation between the two countries has become fast grow (mikhaylov et al., 2018; nyangarika et al., 2018). diplomatic relations between the soviet union and the republic of korea were established september 30, 1990, which became a political guarantee of trade economic, scientific and technical cooperation to strengthen and deepen further interaction (morris and barlaz, 2011). after the collapse of the soviet union, the need arose to fix relations legally between the new state the russian federation and the republic korea. during the official visit of the russian president to seoul in november 1992. the agreement was signed between the republic of korea and the russian federation, according to which the parties agreed to promote the development of a wide mutually beneficial cooperation in the field of economy, industry, trade, namely in the field of agriculture, forestry, fisheries, energy, mining industry, communications, construction and transport (moiseev, 2017c; moiseev and akhmadeev, 2017). thus, at the initial stage the development of cooperation, the potential of cooperation in the energy sector was noted sphere south korea expressed its interest in the joint development of natural resources that could potentially increase the share of imports, including energy resources from russia. in accordance with the provisions of this agreement, with the aim of a detailed study of cooperation projects and the creation of such, it was decided to create working units of the industry character. as of 2016, along with the russian-korean ipc, 11 committees and commissions function, among which the russian-korean committee on cooperation in the field of energy and mineral resources (zubakin et al., 2015). in the course of the above it was noted that energy cooperation is developing dynamically, and russian and south korean companies successfully cooperate in priority areas of cooperation oil and gas and coal. the committee believes that the areas of electric power, energy efficiency and renewable energy have the potential for closer collaboration (an et al., 2020; an and dorofeev, 2019). regarding direct cooperation, in 2003 measures were taken to establishing cooperation in the oil and gas sector: gazprom and the korean company kogas signed a cooperation agreement for a period of 5 years, and in 2008 it the agreement was extended for another 5 years. the main activities kogas companies are the construction and operation of liquified natural gas (lng) reception terminals and gas distribution networks, implementation of international gas projects, scientific gas research and development. in 2005, sakhalin energy investment company ltd. and kogas sign a contract for the supply of 1.5 million tons of lng to year since the sakhalin-2 project (milbrabdt et al., 2014; morgan and yang, 2001). at the intergovernmental level, an agreement “on cooperation in the gas industry” in 2006 in seoul. this agreement identified gazprom and kogas as authorized organizations involved in the issue of gas supplies to south korea through the sakhalinkhabarovskgas transmission system “vladivostok,” the creation dooyum, et al.: energy security concept in russia and south korea international journal of energy economics and policy | vol 10 • issue 4 • 2020104 of which is envisaged by the eastern gas program, approved by the ministry of industry and energy in 2007. in 2016, another agreement was signed between gazprom and kogas on cooperation, providing for the development of partnerships in the field of lng supplies in south korea: implementation of joint projects for the production, transportation and regasification of lng (an et al., 2019a; an et al., 2019b; an et al., 2019c; an et al., 2019d). 3. data and methods today, the dynamics of development of energy cooperation in the field of lng supplies from russia are positive: in 2018, prospects are actively discussed expanding lng supplies from the sakhalin-2 project. in addition, in the framework of the iv east economic forum, which was from september 11 to september 13, 2018 in vladivostok. they discussed opportunities for deepening cooperation in the gas sector to the growing demand for lng from the south korea. lng supplies are steadily growing: in 2017 supply from sakhalin energy investment company ltd. amounted to 1.9 million tons, and in the first half of 2018 already 1.2 million tons. in the structure of energy consumption of the republic of south korea, oil and petroleum products occupy the leading place, and oil demand is constantly growing. in this regard, the republic of south korea is located in constant dependence on oil imports, the vast majority of which come from countries of the middle east. on for a long time, the share of the russian federation in oil imports did not exceed 3-4%. not less in the framework of the diversification policy of the republic of south korea pays more and more attention to russia as a promising partner in the field of energy cooperation (dayong et al., 2020). the beginning of cooperation between south korea and the russian federation in the field of crude oil supplies was laid in september 1999, with the shipment of the first batch of crude oil from about. sakhalin, the volume of which amounted to 81 thousand tons. most oil exports come from sakhalin-1 projects (de kastri port) and sakhalin-2 projects (korsakov port), and the rest accounts for the port of kozmino the terminal point of the east siberia oil pipeline pacific ocean. 4. results this area of energy cooperation would not appear possible without the systematic creation of an appropriate transport infrastructure. cooperation between the russian federation and the republic of south korea in this area was made possible thanks to two factors: increased demand for crude oil and petroleum products in asia as a whole and in south korea in in particular, and pursuing a policy of diversification of energy suppliers, initiated by the korean government. thanks to the commissioning of an increasing number of transport projects, oil export volumes were constantly growing (table 1). over the past 10 years (2007-2017), indicators fluctuate on average in between 30 and 50 million barrels per year (table 2). in 2015, export volumes reached their maximum for the period under review (1999-2017), amounting to 137.8 million. tons or 51.1 million barrels per year, which was mainly caused by a collapse in prices for energy sources. goals of this agreement were the redistribution of oil flows around the world and ensuring balance of supply and demand in the market. the result was a reduction in import from saudi arabia to south korea, as it has become more expensive. against this background, russian urals brand oil, previously not purchased by the state, has become economically more profitable in comparison with brands such as oman and upper zakum (figures 1-3). therefore, we can naturally expect a further reduction in oil supplies from opec countries, in particular saudi arabia, and accordingly an increase in volume import from russia. it is worth noting one of the few joint projects in the field of intelligence energy resources that could greatly strengthen energy cooperation and attract more investment in the far eastern region, if it were fully implemented. in 2006, rosneft and korean kcc consortium, which included the following companies: korean national oil corporation (korean national oil corporation, knoc), kogas, gs-caltex corporation, sk corporation, daewoo international corporation, kumho petrochemical and hyundai corporation); entered into an agreement to establish a joint investment project for exploration of the west kamchatka shelf. table 1: completed infrastructure projects of oil export to east asia from siberia and far east year infrastructure project 1999 sakhalin-2 project (seasonal oil development: 6 months a year) 2006 sakhalin-1 project 2008 sakhalin-2 project (year-round oil production) 2009 completion of the construction of espo-1 2011 completion of the construction of an oil pipeline under the espo 2012 completion of the construction of espo-2 and start of operation source: thomson reuters, espo: east siberia oil pipeline table 2: crude oil exports from the russian federation to south korea year export of oil 1999 3.7 2000 9.9 2001 18.6 2002 15.05 2003 7.03 2004 8.5 2005 8.3 2006 13.9 source: thomson reuters dooyum, et al.: energy security concept in russia and south korea international journal of energy economics and policy | vol 10 • issue 4 • 2020 105 figure 1: oil export from russia source: thomson reuters figure 2: oil products export from russia source: thomson reuters source: thomson reuters figure 3: oil stock in south korea dooyum, et al.: energy security concept in russia and south korea international journal of energy economics and policy | vol 10 • issue 4 • 2020106 according to this project, 60% of the shares belonged to rosneft, and the remaining 40% to the korean consortium. 5. conclusion however, the project was soon suspended due to the loss of rosneft license to develop this shelf section. one reason for suspension license served as non-compliance with certain requirements of the license agreement, in of which there were such as putting off the first drilling during the year exploratory well and violation of the timing of seismic work (mikhaylov, 2015). the rights to this section were transferred to gazprom, which in turn announced willingness to leave the korean side a stake in the company, but no more. however, negotiations on this issue were not brought to an end, and gazprom ultimately set about unilaterally developing the shelf section (chiemchaisri et al., 2012; gardner et al., 1993). thus, the korean side suffered serious financial losses in the amount of several hundred million dollars, which undoubtedly had a negative impact on cooperation between the russian federation and the republic of south korea in the field of energy resources and in general. in other words, russian the party represented by rosneft and gazprom proved to be unreliable partners, with which korean companies, it seems to us, are unlikely to actively seek interact and in projects which they will not invest in the near future (meynkhard, 2019a; meynkhard, 2020). to restore confidence, the russian side will have to give certain guarantees and reinforce them with actions not only at the level of business, oil, and gas corporations sector, but also at the intergovernmental level. only then are constructive possible dialogue and partnerships (mikhaylov, 2019; mikhaylov et al., 2019). in general, the development and deepening of energy cooperation between the russian federation and south korea is in the zone of interests of both parties (meynkhard, 2019b). consequently, energy cooperation will expand, and interdependence south korea and russia will grow economically, which in turn will be even more to increase the scale of not only fuel and energy, but also in the long-term political and cultural cooperation (denisova, 2019; denisova et al., 2019). thus, we can talk about the complementary nature state economies, which in turn serves as a fundamental prerequisite development of energy cooperation, the ultimate goal of which is ensuring energy security as one of the main tasks of any state (mikhaylov, 2018a; mikhaylov, 2018b; mikhaylov et al., 2018; nyangarika et al., 2018). the foreign policy course focused on development of cooperation in the asia-pacific region from the russian side, and from the south korean side (chiemchaisri et al., 2012; gardner et al., 1993). all three sources contain overlapping goals and objectives, among which the following: development of the far east, providing energy state security, diversification of importing states in the case of the russian federation and exporters in the case of south korea and deepening energy cooperation in the asia-pacific region (chiemchaisri et al., 2012; gardner et al., 1993). it is creation of joint infrastructure projects and joint projects exploration of energy resources and an increase in lng supplies from the russian federation to the republic of south korea. therefore, from the theoretical and methodological point of view, there are all necessary conditions for deepening and expanding energy cooperation under consideration states (nyangarika et al., 2019b; nyangarika et al., 2019a). institutionally, agreements and memoranda were signed, necessary for the formation of a regulatory framework for energy cooperation, and various governmental and intergovernmental structures such as the russian-korean intergovernmental commission and it has composed of the russian-korean energy cooperation committee and mineral resources (lopatin, 2019a; lopatin, 2019b). as well as the committee on northern economic cooperation, personally controlled by the president of the south korea, in the framework of which consultations and meetings of government and business representatives related to development of joint projects in the energy sector and closely related infrastructure sphere (chiemchaisri et al., 2012; gardner et al., 1993). references an j., dorofeev m., zhu s. (2020), development of energy cooperation between russia and china. international journal of energy economics and policy, 10(1), 134-139. an, j., dorofeev, m. (2019), short-term fx forecasting: decision making on the base of expert polls. investment management and financial innovations, 16(4), 72-85. an, j., mikhaylov, a., lopatin, e., moiseev, n., richter, u.h., varyash, i., dooyum, y.d., oganov, a., bertelsen, r.g. (2019c), bioenergy potential of russia: method of evaluating costs. international journal of energy economics and policy, 9(5), 244-251. an, j., mikhaylov, a., moiseev, n. (2019d), oil price predictors: machine learning approach. international journal of energy economics and policy, 9(5), 1-6. an, j., mikhaylov, a., sokolinskaya, n. (2019a), machine learning in economic planning: ensembles of algorithms. journal of physics: conference series, 1353, 012126. an, j., mikhaylov, a., sokolinskaya, n. (2019b), oil incomes spending in sovereign fund of norway (gpfg). investment management and financial innovations, 16(3), 10-17. bansal, a., illukpitiya, p., singh, s.p., tegegne, f. (2013), economic competitiveness of ethanol production from cellulosic feedstock in tennessee. renewable energy, 59, 53-57. bove, r., lunghi, p. (2006), electric power generation from landfill gas using traditional and innovative technologies. energy conversion and management, 47(11-12), 1391-1401. cai, x., zhang, x., wang, d. (2011), land availability for biofuel production. environmental sciences technology, 45(2), 334-339. chiemchaisri, c., chiemchaisri, w., kumar, s., wicramarachchi, p.n. (2012), reduction of methane emission from landfill through microbial activities in cover soil: a brief review. journal critical reviews in environmental science and technology, 42(4), 412-434. dooyum, et al.: energy security concept in russia and south korea international journal of energy economics and policy | vol 10 • issue 4 • 2020 107 dayong, n., mikhaylov, a., bratanovsky, s., shaikh, z.a., stepanova, d. (2020), mathematical modeling of the technological processes of catering products production. journal of food process engineering, 43(2), e13340. denisova, v. (2019), energy efficiency as a way to ecological safety: evidence from russia. international journal of energy economics and policy, 9(5), 32-37. denisova, v., mikhaylov, а., lopatin, e. (2019), blockchain infrastructure and growth of global power consumption. international journal of energy economics and policy, 9(4), 22-29. gardner, n., manley, b.j.w., pearson, j.m. (1993), gas emissions from landfills and their contributions to global warming. applied energy, 44(2), 166-174. lopatin, e. (2019a), methodological approaches to research resource saving industrial enterprises. international journal of energy economics and policy, 9(4), 181-187. lopatin, e. (2019b), assessment of russian banking system performance and sustainability. banks and bank systems, 14(3), 202-211. meynkhard, a. (2019a), energy efficient development model for regions of the russian federation: evidence of crypto mining. international journal of energy economics and policy, 9(4), 16-21. meynkhard, a. (2019b), fair market value of bitcoin: halving effect. investment management and financial innovations, 16(4), 72-85. meynkhard, a. (2020), priorities of russian energy policy in russianchinese relations. international journal of energy economics and policy, 10(1), 65-71. mikhaylov, a. (2015), oil and gas budget revenues in 2015: forecast and risks. financial journal, 2, 47-54. mikhaylov, a. (2018a), pricing in oil market and using probit model for analysis of stock market effects. international journal of energy economics and policy, 8(2), 69-73. mikhaylov, a. (2018b), volatility spillover effect between stock and exchange rate in oil exporting countries. international journal of energy economics and policy, 8(3), 321-326. mikhaylov, a. (2019), oil and gas budget revenues in russia after crisis in 2015. international journal of energy economics and policy, 9(2), 375-380. mikhaylov, a., sokolinskaya, n., lopatin, e. (2019), asset allocation in equity, fixed-income and cryptocurrency on the base of individual risk sentiment. investment management and financial innovations, 16(2), 171-181. mikhaylov, а., sokolinskaya, n., nyangarika, а. (2018), optimal carry trade strategy based on currencies of energy and developed economies. journal of reviews on global economics, 7, 582-592. milbrabdt, a.r., heimiller, d.m., perry, a.d., field, c.b. (2014), renewable energy potential on marginal lands in the united states. renewable and sustainable energy review, 29, 473-481. moiseev, n. (2017a), forecasting time series of economic processes by model averaging across data frames of various lengths. journal of statistical computation and simulation, 87(17), 3111-3131. moiseev, n. (2017b), p-value adjustment to control type i errors in linear regression models. journal of statistical computation and simulation, 87(9), 1701-1711. moiseev, n. (2017c), linear model averaging by minimizing meansquared forecast error unbiased estimator. model assisted statistics and applications, 11(4), 325-338. moiseev, n., akhmadeev, b. (2017), agent-based simulation of wealth, capital and asset distribution on stock markets. journal of interdisciplinary economics, 29(2), 176-196. moiseev, n., sorokin, a. (2018), interval forecast for model averaging methods. model assisted statistics and applications, 18(2), 125-138. morgan, s.m., yang, q. (2001), use of landfill gas for electricity generation. practice periodical of hazardous, toxic, and radio waste management, 5(1), 14-24. morris, j.w., barlaz, m.a. (2011), a performance-based system for the long-term management of municipal waste landfills. waste management, 31(4), 649-662. nyangarika, a., mikhaylov, a., richter, u. (2019a), influence oil price towards economic indicators in russia. international journal of energy economics and policy, 9(1), 123-130. nyangarika, a., mikhaylov, a., richter, u. (2019b), oil price factors: forecasting on the base of modified auto-regressive integrated moving average model. international journal of energy economics and policy, 9(1), 149-160. nyangarika, a., mikhaylov, a., tang, b.j. (2018), correlation of oil prices and gross domestic product in oil producing countries. international journal of energy economics and policy, 8(5), 42-48. zubakin, v.a., kosorukov, o.a., moiseev, n.a. (2015), improvement of regression forecasting models. modern applied science, 9(6), 344-353. international journal of energy economics and policy vol. 2, no. 1, 2012, pp. 10-20 issn: 2146-4553 www.econjournals.com optimization model for economic evaluation of wind farms how to optimize a wind energy project economically and technically1 wagner sousa de oliveira department of economics, management and industrial engineering, university of aveiro, portugal. email: wsoliveira76@gmail.com antonio jorge fernandes department of economics, management and industrial engineering, university of aveiro, portugal. email: afer@ua.pt abstract: this paper makes a review and systematize methods and techniques of economic evaluation applied to renewable energy projects, specific to wind energy projects. both project and cost methodologies of economic evaluation are reviewed for a model optimization construction for a proposed optimization model with its objective function most appropriated. it is necessary to engage in different approaches, but complementary, microeconomic project evaluation methods and optimization methods applied to engineering solutions in wind energy converter systems. optimization model for economic evaluation of wind farms can be as an efficient planning and resource management, which is the key to the success of an energy project. wind energy is one of the most potent alternative energy resources; however the economics of wind energy is not yet universally favorable to place wind at a competitive platform with coal and natural gas (fossil fuels). economic evaluation models of wind projects developed would allow investors to better plan their projects, as well as provide valuable insight into the areas that require further development to improve the overall economics of wind energy projects. keywords: optimization model; economic evaluation; wind energy projects; re projects management. jel classification: q42, c61 1. introduction interest in the use of renewable energy sources has grown dramatically during the last decade, largely as a reaction to concerns about the environment impact of the use of fossil and nuclear fuel. however, the subject of renewable energy is of far wider interest than to environmental issues alone. the use of fossil and nuclear fuels is so central to industrialized societies that any examination of the difficulties they cause or their potential solutions raises a wide range of issues: of the technology and design, politics, social structure, economics, planning and even history. this is an area in which there are many views, of varying degrees of insight and expertise, but little certainly. one of the most exciting aspects of the study of renewable energy is that it is inherently positive. it is an area which offers the possibility of solutions to some of society’s most difficult problem. again, this appears most clearly when a broad approach is taken. thus the study of renewable energy involves much more than the technical possibilities of replacement of fossil and nuclear fuels. some of the major scientific areas of interest are: i. environmental science – the comparative impact of fossil, nuclear and renewable energy sources on the atmosphere, waterways, and the plant and animal life on the earth. this 1 this paper is result of a phd in economics started on may/2008 within the project research on “optimization model for economic evaluation of wind farms”, supervised by professor a.j.f., phd, and professor j.j.b.g., phd, at department of economics, management and industrial engineering, university of aveiro. international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.10-20 11 includes considerations of the greenhouse gases effect, acid rain and pollution of the seas. related issues include the dynamics of climate ant its relationship to the biosphere. ii. earth sciences – the origins of and physical principles underlying the various forms of renewable energy. iii. technology – the design and implementation of renewable energy based technologies, and their integration with existing technologies and distribution systems. related issues include the technical possibilities for improving the efficiency of present energy use, in buildings, machinery, appliances, power plants, etc. iv. social sciences – the technological/economical/social/philosophical issue of large-scale systems versus small-scale local systems. the difference between the relatively concentrated reserves of fossil fuels in some countries and the wider distribution of renewable energy resources has major political implications and may influence patterns of industrialization and economic development. changing fuels prices have a dramatic effect upon the world´s economies. v. planning – the sitting of power stations, transmission lines, wind farms, tidal barrages, biomass plantations or hydroelectric plant, which has a major planning impact, with legal and social implications. transport planning, too, is intimately related to the mix of fuels and other energy sources available. vi. architecture, building and design – the design of buildings and neighborhoods for energy efficiency and to incorporate integrated energy supply systems which mix renewable and others sources. as can be notice, study renewable energy sources and technologies it is necessary an multidisciplinary understanding, so the way these projects can be measure or optimized take us to a body of knowledge for a complete and more comprehensive analysis of a power station planning and management, case of wind farms, at a microeconomics view. to optimize a wind farm, each aspect and typical assumption must be challenged and carefully evaluated. the challenge in the evaluation has been determining the life-cycle economic implications of aspects such as lost availability, losses at full load, and no-load losses so they can be included in the design process. three economic factors condense the complexities of the wind farm business model into a form that can be conveniently used in simple spreadsheet calculations to optimize technoeconomic power plant for maximized profitability (maddaloni, 2005). these factors can be determined from the unique economic characteristics of the specific project, including wind regime, cost of money, tax treatment, and expected project return on investment. wind energy investment decisions are driven by economics, not necessity. the wind farm must have the lowest possible total lifecycle cost for the project to maximize its economic potential. a specific design choice may have a complex effect on the project financial performance, affecting capital costs, taxes, insurance, energy revenue, maintenance costs, and government subsidies. a method is required to simplify the calculations so that alternate design proposals may be compared and an optimal solution chosen based on the specific economic and engineering factors of the particular wind farm project. an optimal solution is a result of an optimization process. optimization is an important tool in decision science and in the analysis of physical systems. to use it, we must first identify some objective, a quantitative measure of the performance of the system under study. this objective could be profit, time, potential energy, or any quantity or combination of quantities that can be represented by a single number. the objective depends on certain characteristics of the system, called variables or unknowns. our goal is to find values of the variables that optimize the objective. often the variables are restricted, or constrained, in some way (nocedal & wright, 1999). the process of identifying objective, variables, and constraints for a given problem is known as modeling. construction of an appropriate model is the first step — sometimes the most important step — in the optimization process. if the model is too simplistic, it will not give useful insights into the practical problem, but if it is too complex, it may become too difficult to solve. once the model has been formulated, an optimization algorithm can be used to find its solution. usually, the algorithm and model are complicated enough that a computer is needed to implement this process. there is no universal optimization algorithm. rather, there are numerous algorithms, each of which is made to a optimization model for economic evaluation of wind farms how to optimize a wind energy project economically and technically 12 particular type of optimization problem. it is often the user’s responsibility to choose an algorithm that is appropriate for their specific application. the cost of energy, that has to be minimized by changing the design variables and others parameter influence cost of energy such as wind speed, wind farm layout, wind production losses, o&m cost parameters and control parameters. the optimization must maximize the profit obtained during the useful lifetime of the wind farm studied. 2. literature review the availability of electrical energy is a precondition for the functioning of modern societies. it is used to provide the energy needed for operating information and communication technology, transportation, lighting, food processing and storage as well as a great variety of industrial processes, all of which are characteristics of a modern society. because the energy for many of the technologies, systems and possibilities that are a property of the developed world is provided as electricity, it can be presumed that there is a link between the level of penetration and consumption of electricity on the one hand and various properties of a society on the other. the relation between economic and societal development and electricity consumption is bidirectional. the availability of electricity greatly facilitates industrialization, because electricity is a convenient way to replace human power by other sources of energy, which are converted into electricity for transmission, distribution and consumption (slootweg, 2003). there exist other electricity generation technologies using renewable primary energy sources that do hence not involve the disadvantages of nuclear and thermal generation. examples are wave and tidal power, solar power and wind power. in wave and tidal power plants, energy is extracted from the waves and from the water flows caused by the tide. in solar power plants, consisting of solar panels, sunlight is converted into electricity, whereas in wind turbines, the energy contained in flowing air is converted into electricity (rosa, 2009). one technology to generate electricity in a renewable way is to use wind turbines that convert the energy contained by the wind into electricity. the wind is an infinite primary energy source. further, other environmental impacts of wind power are limited as well. although they affect the scenery visually and emit some noise, the consequences of this are small and ecosystems seem hardly to be affected. further, once removed, their noise and visual impact disappear immediately and no permanent changes to the environment have occurred. a wind turbine generates the energy used to produce and install it in a few months so that the energy balance over the life cycle is definitely positive (kennedy, 2005; oliveira, 2010b). according to global wind energy council (2011a) the growth of wind power during the last decade in the world. the global cumulative installed of wind power capacity is growing approximately exponential over the past five years, annual growth has been above 30%. figure 1. global cumulative installed wind capacity (1996-2010) source: global wind statistics 2010 (gwec, 2011a) wind was even more dominant as a destination for investment in 2009 than in the previous year. in 2008, it accounted for $59 billion or 45% of all financial investment in sustainable energy, but in 2009, its share rose to 56%. total financial investment in wind last year was $67 billion, compared with $119 billion for all sustainable energy technologies (sefi, 2010). international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.10-20 13 figure 2. financial new investment ($bn) and growth by technology 2008-2009 0.2 0.3 2 4 4 7 11 24 67 110% -40% -28% -9% 34% -62% 14% -27% 14% marine low carbon services & support* geothermal small hydro energy smart technologies biofuels biomass & waste solar wind growth: global trends in sustainable energy investment 2010 source: sefi/bloomberg new energy finance (sefi, 2010). the strength of wind reflected several developments. one was the financial go-ahead for a number of large offshore wind farms in the north sea, notably the 1gw london array, the 317mw sheringham shoal project and the first, 165mw phase of belwind. another was that, in uncertain economic and financial circumstances, wind was seen as a relatively mature and therefore lower risk, sub-sector of clean energy than some others (sefi, 2010). according to wagner and epe (2009) to promote wind energy, the research needs need to be identified and the research work carried out. initially, there are such environmental and social challenges as integration into the landscape, noise impact, bird flight paths, life cycle analysis and sustainability. and of course, wind turbine and component design have to be improved continually, i.e. basic research in aerodynamics, structural dynamics, dynamic forces, new materials, feasibility studies into new systems, generators using permanent magnets, gear boxes, etc. for planning and building wind turbines and wind farms, commonly accepted certification procedures must be formulated and standardized. for an optimized grid integration of wind energy, especially in great quantities, power quality can be supported by better forecasts of wind resources and by the use of storage sites. el-kordy et al. (2002) evaluation of the economics of energy systems strongly depends on the four cost factors: capital cost; maintenance cost; fuel cost; and external cost, when considered. fuel and external costs are sensitive to fuel type and efficiency of the used system. economic parameters such as discount, inflation and escalation rates, deeply affects the evaluation. future sums of money must be discounted because of the inherent risk of future events not turning out as planned, the present worth method being considered as a suitable tool for comparing the different alternatives. the international energy agency (1991) developed a guideline for the economic analysis of renewable energy technology applications that can be summarized as in the figure 3. the iea´s recommended methodology represents a consistent, structured, generalized approach which is appropriated for feasibility analysis for both public and private sector. the figure 3 shows the relationship between the inputs, costs, performance formats and sector analysis models. the entire economic indicator will be discussed ahead. for gökçek and genç (2009), the calculation of the electrical energy generation cost, all payments required for the installation of the power plant must be known. the cash flow for the project includes the expenditures such as land, construction, fuel and operating and maintenance. in general, in power plants, cost per unit energy is calculated by dividing the amount of energy produced to the total expenditures made along the certain time interval. the levelized cost of electricity (lcoe) is one of the most important indicators for evaluating fiscal performance of power supply systems such as wind energy conversion system (wecs). the lcoe is a technique applied by the techno-commercial analysts to calculate the unit cost throughout the economic life of the project. the levelized cost for wecss can be describe as the ratio of the total annualized cost of the wecs to the annual electricity produced by the system. optimization model for economic evaluation of wind farms how to optimize a wind energy project economically and technically 14 figure 3. diagram of recommended economic analysis approach source: iea/guidelines for the economic analysis of renewable energy technology applications (iea, 1991, p. 12). a techno-economic analysis of electricity generation from wind energy made by arslan (2010) discuss about life-cycle cost analysis for onshore wind farm connected to a grid which essentially includes two main components, which are the investment and the operation and maintenance (o&m) costs. the investment cost includes the costs of the turbine, foundation, grid connection, and civil work. the environmentalist economists maintain that the real cost of a process must be calculated by adding to the investment and operational costs the cost of the damages to both human health and nature. zhang et al. (2010a) introduce a new concept for economic evaluation of wind farms. its formulation is based on cost of energy (coe) optimization. the result showed that (i) the profitability is particularly sensitive to changes in the capital cost, the capacity factor, the electricity escalation rate, and the initial installation cost; (ii) the profitability is slightly less sensitive to changes in the o&m cost; and (iii) the impact of the turbine rated power and the inflation rate is limited. nouni et al. (2007) developed the levelized unit cost of electricity (luce). the luce is one of the commonly used indicators for financial performance evaluation of renewable energy based decentralized power supply systems. total annualized cost is calculated by taking into consideration the capital costs of the different sub-systems of the sweg project and its annual operation and maintenance cost. international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.10-20 15 the national renewable energy laboratory (nrel) (1995) compiled a manual for the economic evaluation of energy efficiency and renewable energy technologies that provides guidance on economic evaluation approaches, economic measures, while offering a consistent basis on which analysts can perform analyses using standard assumptions for each case. it not only provides information on the primary economic measures used in economic analyses and the fundamentals of finance but also provides guidance focused on the special considerations required in the economic evaluation of renewable energy projects. oliveira (2010b) makes an overview about the indicators of attractiveness and risks like simple payback (spb), discounted payback (dpb), net present value (npv), internal rate of return (irr), benefit-to-cost ratio (bcr) and required revenues (rr). also are discussed about some indicator of cost analysis in energy projects just like lcoe, total life-cycle cost (tlcc), net present cost (npc), levelized electricity generation cost (legc) and unitary present average cost (upac). a simulation studied with these indicators concludes that they must be used as tool kit for wind energy project economic evaluation. the indicator studied is not recommended be applied alone, better combine the indicators in function of the evaluation objective. there are many software available in the market that can be possible to make a sophisticated economic evaluation of an energy project for both renewable and efficiency application. we can cite the retscreen® international clean energy project analysis used as an investment tool decision, the homer energy software applied to dimensionate a power system with all its features for the system works as it must be. it is possible to make a list of software used professionally by engineers, designers, economists and related professions. the cost of the renewable technology can be evaluated by its cumulative production, research, development aspects. many authors such kobos et al. (2006), ibenholt (2002), lund (2006), neij (1999, 2008), pan and köhler (2007) and sorensen (1997). for onshore and offshore wind energy technological aspect and its improvements have a great impact on cost reduction of wind energy project analysis. it is an important aspect to be considered. efficiency planning and resource management is the key to the success of an energy project. wind is one of the most potent alternative energy resources; however the economics of wind energy is not yet universally favorable to place wind at a competitive platform with conventional energy (fossil fuels) (zhang, et al., 2010a). the optimization model for economic evaluation of wind farms, developed in this research, would allow investors and managers to better plan their projects, as well as provide valuable insights into the areas that require further development to improve the overall economics of wind energy. as we can notice there is exhaustive list of authors, institutions about economic evaluation methodologies and approaches applied to energy projects. each methodology and approach has its own objective, although they usually highlight economic merits only – in an energy project it is also interesting engineering and physics variables. in economics view it is necessary that the project could remunerate its costs and create profits for investor as well as any other economic agent involved. in the other hand, in engineering aspects, the project must be dimension ate according to its equipments, utilities and machinery used in the power station. how is it possible to optimize a wind farm, in a project conception, in both economical and engineering point of view? both onshore and offshore wind energy has had a growth during the last decade in the world and the importance of renewable energies technologies is more and more emphasized by public authorities because climate change and global warming is a concern for modern world, so methodologies which could become investment in this kind of technology more safe with dynamics analysis will be welcome. wind energy is one of the renewable technologies that is becoming more and more competitive at the global level, but has not received enough attention on optimization process for economic evaluation of wind farms by the researchers in both economic and engineering aspects. indeed, most of the optimization models reflects aspects of engineering and physics sciences, but in the economic view has not been analyzed in the depth that it deserves. so, try to develop an optimization model for economic evaluation of wind farms using algorithm genetic it is a step ahead for economic evaluation methodologies, and we hope in few years could applied this new approach for better decisions and make that invest in renewable energy projects is right and secure way to explore the resources from nature, help the economy growth and the environment protection. optimization model for economic evaluation of wind farms how to optimize a wind energy project economically and technically 16 3. wind energy economics there is not a single price and cost of energy for wind farms. both depend on the location, size and number of turbines, in addition to being influenced by political incentives or subsidies granted by governments. the initial investment costs cost of equipment, feasibility study, installation, and o&m are essential to determine the final cost of the technology. in general, the main variables that make up the production cost of wind energy are the investment costs of fuel and operations and maintenance (morthorst & chandler, 2004; wizelius, 2007). in the case of wind power there is no dependence of the cost of fuel, but the investment cost is still higher than that of conventional sources. however, the costs of wind farms are decreasing, indicating that this trend is likely to continue due to several factors such as the development of larger turbines and more efficient, technological advancement, reduction in the cost of o&m, among others. an extremely important factor that contributes to raise the cost of wind power is its capacity factor, generally around 30% to a maximum of 40%, while conventional plants varies between 40% and 80%. the cost of electricity generation by wind in europe declined in the last 15 years approximately 80%. at the same time, the installed capacity has increased exponentially in scale, from less than 100 mw to 34,400 mw in 2004. during the past ten years the price of wind turbines decreased by 5% each year, while at the same time revenue increased by 30% (zervos & kjaer, 2008). despite the reduction on the costs in recent years, some problems still there are hindering investments in wind energy projects. when connecting a wind farm to the electricity grid transmission, it is needed to check the power factor, voltage and final production of harmonics caused by the turbines, and investment costs are still higher than the conventional power plants of oil and natural gas. moreover, the presence of wind turbines may threaten birds and cause visual and noise impact (gipe, 1995; heier, 1998). with regard to wind energy production, economic optimization and evaluation of projects in renewable energy, it is also needed on other factors, such as potential exposure from this source in the energy world, especially in regions where wind speeds are expressive. as the output power is extremely sensitive to wind speed, variability significantly impacts on financial investments and o&m costs. given to this, it is highlighted the importance of developing assessment methodologies for economic and financial evaluation and management for energy projects considering the uncertainties associated with this type of technology (ewea, 2009a). both onshore and offshore wind energy minimizing the cost per kwh produced it is necessary because when it is going to be sold to the grid, the high and variable cost of wind energy represents a real risk to the investor or wind farm promoter. so when a wind farm is evaluated by deterministic indicator such as npv, irr, spb, dpb and others economic and financial indicator usually applied for it, but such evaluation reflects a set of parameters adjusted and assumptions considered in order to show the results for a unchangeable market situation. in economics sciences it´s called “ceteris paribus”. on the other hand, the wind energy system and green energy markets have some inherent features that should be taken into consideration. as renewable energies have been receiving supports by government’s incentives such as production tax credits (ptcs), modified accelerated cost recovery system (macrs) and others finance supports which become wind energy technology competitive comparing to conventional ones and other renewable energies technologies. however, given the fast growth of wind power during the last decade and the expectations for the future, wind power penetration levels may increase to levels where engineering and economic optimization for this kind of system starts to be more and more necessary. note that in this thesis, the optimization model is defined as a suggested methodology able to evaluate a wind farm in both economical and engineering aspects. according to benatiallah and dakyo (2010) the main objectives of the optimization design are power reliability and cost. minimizing the total cost, we can achieve an inexpensive and clean electric power system. in addition, the proposed method can adjust the variation in the data of load, location. various modeling techniques are developed by researchers to model components of wind system. performance of individual component is either modeled by deterministic or probabilistic approaches. the economic study should be made while attempting to optimize the size of integrated power generation systems favoring an affordable unit price of power produced. the economic analysis of the wind system has been made and the cost aspects have also been taken into account for optimization of the size of the systems. the total cost of system takes into account the initial capital investment, the international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.10-20 17 present value of operation and maintenance cost, the inverter replacement cost and the wind system replacement cost. the key objectives of the researches have been to find the lowest cost and highest reliability design of a wind farm. developing methodologies with approaches for structural and economic optimization of onshore and offshore wind farms are still a challenge due to its multivariable nature and its non linear behavior. the importance of using new optimization techniques for short-term energy planning is due to the existence of multiple uncertainties (fleten, maribu, & wangensteen, 2007). for baños et al. (2011) the investment decision on generation capacity of a wind park is difficult when wind studies or data are neither available nor sufficient to provide adequate information for developing a wind power project. some researchers have analyzed in detail how to determine the probable wind power availability at a given site according to historical wind velocity data, and its capacity to meet a target demand. at the start of this research work, the primary concern was about the correlation between wind velocity and cost of energy produced at a specific site, but after an extensive literature review it became clearly that a economic evaluation by classical economic engineering approach considering deterministic indicator such as discounted cash flow technique would not be sufficient. it is a multivariable problem and engineering aspects must be taken into consideration. the central question for this research work is hence: how to optimize a wind farm economically and technically by the application of nonlinear algorithm theory for minimizing the cost of energy? is it possible? 4. methodological approach the overall approach taken to reach the research objective was to investigate the formulation and logics of the various evaluation models/indicators, each model has its own variables and relations to explain the results and objectives for each model studied. at first, it checks only the economic models and then engineering evaluation models are analyzed with its objectives too. according to the central question or this research, it is an industrial problem and the steps to follow may be considered as follows (frederick s. hiller & lieberman, 1995): 1. define the problem of interest and gather relevant data – why is there dissatisfaction with the present operations and what alternative courses of action appear to hold most promise of being effective solutions to the problem, relative to a set of pertinent objectives. the size of a wind farm project and the size of the wind turbine itself will vary depending on the amount of electricity the developer intends to generate. costs of components per unit size tend to decrease as size increases, and through economies of scale, the construction costs per unit manufactured decreases as more wind turbines are manufactured (at least to the point where equipment and personnel are adequate). however, because the mass of the wind turbines’ materials increases at a cubic rate to its rotor diameter, and the power rating increases with the square of its rotor diameter, there will be a critical size that increases the cost per kw of maximum power (johnson, 1985). as wind energy is an intermittent source of power, this fact gives rise to extra costs in generation, distribution and transmission, as well as the cost associated with the intermittency of wind. 2. determine a suitable "measure of effectiveness" (often called the "objective function) to be optimized – the wind energy industry is capital intensive, so wind parks’ investment must be returned at an expected rate at investor point of view. usually, the wind park promoter (manager) needs to overcome some technical and economical issues about sub operation which has to be maximized or certain costs minimized. thus, most optimizations are economic optimizations. 3. elaborate a model to represent the system whose optimization is desired – a model may be defined as a device, physical or symbolic. models are almost always necessary in industrial work since experimentation with full-sized industrial equipment disrupts production and is very costly in money and time. and sometimes industrial equipment is only contemplated in design or as replacements. usually, the most desirable model is the mathematical model, which employs mathematical statements to represent the system and enables responses to be calculated rather than be measured. the measure of effectiveness is expressed as a function optimization model for economic evaluation of wind farms how to optimize a wind energy project economically and technically 18 of a set of variables at least one of which is subject to control. (the variables involved are often functionally interrelated so that they behave similarly to the active variables in the realistic system simulated.) as the variables are manipulated, their effectiveness in optimizing the objective is changed. often there are restrictions imposed on the values of the independent variables, or functional restraints involving these variables, and such restraints are expressed by supplementary equations and/or in equations. 4. solve the problem – determine the values of the independent (controllable) variables which optimize the objective (i.e., maximize the effectiveness of the system) subject to any restraints imposed on the system (equipment limitations, rigid management policy, operating limitations, minimum quality characteristics, market restrictions, legal limitations, etc.). 5. test the model and calculated solution obtained from it – if adjustment is indicated, readjust the model, determine a new solution, and check again. a carefully chosen initial model may eliminate difficulties here. 6. establish controls – the lack of effective control over certain variables might seriously invalidate the appropriateness of the original model. the need for a change in the original controllable variables to offset changes in uncontrollable variables must be recognized and a new optimum solution found. 7. implement the suggested solution through appropriate organizational channels, and establish a set of operating procedures so that those concerned with control of the operation can attain the optimum as easily as possible. it proved necessary to investigate the various aspects of a microeconomics view, as a power station unit, because when it is studied separately, it is necessary to understand the wind system conversion, its electro-mechanical, layout and economical restrictions. as it has been said about wind farms, the intermittency must be considered into economic evaluation methodologies, fundamental difference can be found when the intermittency is not considered. it was hence impossible to draw conclusions with respect to the isolated impact of the intermittency effect, because it was made dynamic simulation and the conclusions had to be qualified for the minimum cost of energy and other economic indicators being used. the widely used retscreen software, version 4, a tool for analyzing the technical and financial viability of potential renewable energy projects is now being used by more than 35,000 people in over 196 countries around the globe (retscreen® international clean energy decision support centre, 2008) was also used for the research. at the start of the research project, it was quickly found that there was not a unique methodology or optimization procedure model included in the standard libraries (products and projects database) of this software. further study showed that at that time, this also needed to other dynamics simulation packages, and that wind technologies available are based only on manufactures´ information. it was therefore inevitable to adopt another methodology for optimization process and try dynamics simulation by nonlinear algorithms. finally we studied extensively theory of nonlinear optimization and take advantage of practical aspects of the simulation approach, as well as the manipulation of variables and its results. then, we developed an optimized technology and calculated the best economics results for a hypothetical wind energy project. a preliminary validation of the developed model was carried out using different combinations of wind technologies available by products database of retscreen software. it is important to say again, the software does not make dynamics simulations, only deterministic and probabilistic calculations. 5. conclusion practical realization of the general methodological approach to financial and economic analysis and efficiency evaluation of the investment projects in renewable energy technologies (wind energy) requires a sufficiently vast database including legal, reference, marketing, technical, and other information about the project itself and the conditions for its implementation. most of this information (especially that referring to the future) is of prognostic nature and is not sufficiently full and precise, which tells on the feasibility estimates and project efficiency that depend on the realization conditions. in view of importance of this problem, much attention is paid to the methods of financial and economic analysis and efficiency evaluation of the investment projects in the context of risk and international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.10-20 19 uncertainty. choice of particular methods to analyze investment project risks depends on the factors such as the project scale, completeness of the information base, requirements on the depth of analysis and degree of project reliability, and so on. in a real economic sector, practical analysis of projects, unfortunately, is often carried out in an uncertain environment because the available information base is insufficient for determining the probability of one or another event (condition, index, and so on) with the desired precision. then, informal methods become the main tools to support the decision making. it is often proposed to rely on the subjective data about the technical and economic parameters of a project that are based on the expert opinion. precision and validity of these data depend on the expertise of the experts. popular is the method of analogies where the necessary information is obtained by analyzing the design estimates and accounts of similar, already realized projects. however, these analogies mostly provide distorted results because each project has its own specific features. acknowledgements this work was supported in part by the state government of maranhão through foundation for research and technological and scientific development of maranhão (fapema) – brazil under phd scholarship (bd-00007/08). references a. benatiallah, l. k., & b. dakyo. (2010). modelling and optimisation of wind energy systems. jordan journal of mechanical and industrial engineering, 4(1), 143 150. arslan, o. (2010). technoeconomic analysis of electricity generation from wind energy in kutahya, turkey. energy, 35(1), 120-131. baños, r., manzano-agugliaro, f., montoya, f. g., gil, c., alcayde, a., & gómez, j. (2011). optimization methods applied to renewable and sustainable energy: a review. renewable and sustainable energy reviews, 15(4), 1753-1766. el-kordy, m. n., badr, m. a., abed, k. a., & ibrahim, s. m. a. (2002). economical evaluation of electricity generation considering externalities. renewable energy, 25(2), 317-328. ewea. (2009a). the economics of wind energy. retrieved november 3, 2009, from http://www.ewea.org. fleten, s. e., maribu, k. m., & wangensteen, i. (2007). optimal investment strategies in decentralized renewable power generation under uncertainty. energy, 32(5), 803-815. frederick s. hiller, & lieberman, g. j. (1995). introduction to operations research (6th ed.): mcgraw-hill. gipe, p. (1995). wind energy comes of age. new york: john wiley. gökçek, m., & genç, m. s. (2009). evaluation of electricity generation and energy cost of wind energy conversion systems (wecss) in central turkey. applied energy, 86(12), 2731-2739. gwec. (2011a). global wind statistics 2010. retrieved february 2nd, 2011, from http://www.gwec.net/fileadmin/documents/publications/gwec_prstats_02-022011_final.pdf h.j. wagner, & a. epe. (2009). energy from wind – perspectives and research needs. the european physical journal, 176, 107-114. heier, s. (1998). grid integration of wind energy conversion systems: john wiley & sons. ibenholt, k. (2002). explaining learning curves for wind power. energy policy, 30(13), 1181-1189. iea. (1991). guidelines for the economic analysis of renewable energy technology applications. retrieved march 23, 2010, from http://www.iea.org/textbase/nppdf/free/1990/renew_tech1991.pdf johnson, g. l. (1985). wind energy systems: prentice-hall englewood cliffs (nj). kennedy, s. (2005). wind power planning: assessing long-term costs and benefits. energy policy, 33, 1661-1675. kobos, p. h., erickson, j. d., & drennen, t. e. (2006). technological learning and renewable energy costs: implications for us renewable energy policy. energy policy, 34(13), 1645-1658. lund, p. d. (2006). analysis of energy technology changes and associated costs. international journal of energy research, 30(12), 967-984. maddaloni, j. d. (2005). techno-economic optimization of integrating wind power into constrained electric networks. master of applied science, university of victoria, victoria, bc. optimization model for economic evaluation of wind farms how to optimize a wind energy project economically and technically 20 morthorst, p.e., chandler, h. (2004). the cost of wind power: the facts within the fiction. renewable energy world, 7, 126–137. neij, l. (1999). cost dynamics of wind power. energy, 24(5), 375-389. neij, l. (2008). cost development of future technologies for power generation-a study based on experience curves and complementary bottom-up assessments. energy policy, 36(6), 22002211. nocedal, j., & wright, s. j. (1999). numerical optimization. new york: springer. nouni, m. r., mullick, s. c., & kandpal, t. c. (2007). techno-economics of small wind electric generator projects for decentralized power supply in india. energy policy, 35(4), 2491-2506. nrel. (1995). a manual for the economic evaluation of energy efficiency and renewable energy technologies. (nrel/tp-462-5173). springfield: national renewable energy laboratory. retrieved from http://www.nrel.gov/csp/troughnet/pdfs/5173.pdf. oliveira, w. s. (2010b). evaluation and management of onshore wind energy projects. master in sustainable energy systems, university of aveiro, aveiro. pan, h., & köhler, j. (2007). technological change in energy systems: learning curves, logistic curves and input-output coefficients. ecological economics, 63(4), 749-758. retscreen® international clean energy decision support centre. (2008). clean energy project analysis: retscreen engineering & cases texbook. retrieved january 10, 2008, from www.retscreen.net. rosa, a. v. (2009). fundamentals of renewable energy processes (2nd ed.). uk: elsevier. sefi. (2010). global trends in sustainable energy investment 2010 analysis of trends and issues in the financing of renewable energy and energy efficiency. retrieved july 4, 2010, from http://sefi.unep.org/english/globaltrends2010.html. slootweg, j. g. (2003). wind power: modelling and impact on power system dynamics. phd in electrical power systems, technische universiteit delft, utrecht. sorensen, m. p., org econ, c., dev, o. e. c., & dev. (1997, jun 16). learning curve how are new energy technology costs reduced over time? paper presented at the workshop on energy technology availability to mitigate future greenhouse gas emissions, paris, france. wizelius, t. (2007). developing wind power projects: theory and practice earthscan publications ltd. zervos, a., & kjaer, c. (2008, november 27). wind energy scenarios up to 2030. pure power. zhang, j., chowdhury, s., messac, a., & castillo, l. (2010a, 13 15 september 2010). economic evaluation of wind farms based on cost of energy optimization. paper presented at the 13th aiaa/issmo multidisciplinary analysis optimization conference fort worth, texas. . international journal of energy economics and policy | vol 9 • issue 3 • 2019160 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(3), 160-164. the effects of oil and non-oil exports on economic growth in bahrain anis khayati* department of economics and finance, college of business administration, university of bahrain, sakhir, bahrain. *email: aelkhayati@uob.edu.bh received: 19 december 2018 accepted: 05 march 2019 doi: https://doi.org/10.32479/ijeep.7476 abstract this study investigates the effect of oil and non-oil exports on economic growth in bahrain over the period 1977-2015. the cointegration analysis shows that economic growth was positively and significantly related to exports. however, oil effects have the biggest effect on real gross domestic product. also, results show that oil exports have a positive impact on economic growth both in the short run and in the long run. therefore, further encouragement of non-oil sectors and higher diversification of exports would lead to positive effects on the economy. keywords: economic growth, oil exports, causality, bahrain jel classifications: f11, n15, o40 1. introduction the theory of economic growth provided by the classical school of modern economics, and later supported by neo-classical economists, assumes a strong correlation between exports and economic growth. it indicates that any expansion of exports reinforces the principle of specialization in export goods. therefore, this would reallocate resources from non-commercial sectors with low efficiency to highly productive export sectors. consequently, exports represent an engine of growth that can create and accelerate expansion in all economic sectors. the classical theory relates the hypothesis of the relationship between trade and economic growth to the gains that the country can receive from its foreign trade. these business gains are divided into static gains, dynamic gains and commercial gains. in this context, oil exports (ox) play an important role in the economic growth of the majority of producing countries. this is due to their high reliance on oil export earnings in financing their development projects. an increase in oil prices would potentially lead to positive effects, while the impact would be negative in case of price decline. however, there is a need to distinguish between effects of oil prices on economic growth in the short run and in the long run. an increase in oil prices might have positive effects on output in the short run, but can induce negative effects in the long run, through what is known in economic literature as the “resource curse.” export concentration on ox may negatively affect other industries, and generate “dutch disease.” it also can create high decline in demand from trade partners because of economic recessions or increasing use of energy substitutes. in addition, price volatility may lead to increased uncertainty, and often to a reduction in investment incentives and disturbance in future economic plans. inversely, the decline in oil prices would have a negative impact on the majority of oil producing countries, proportionally to its level of contribution to the gross domestic product (gdp) and to government budgets. in general, the decline in oil prices would reduce the incomes of exporting countries and would adversely affect their current accounts, as well as the exchange rates in some this journal is licensed under a creative commons attribution 4.0 international license khayati: the effects of oil and non-oil exports on economic growth in bahrain international journal of energy economics and policy | vol 9 • issue 3 • 2019 161 of these countries. in turn, this would induce potential risks on financial stability. like other gulf cooperation council (gcc) countries, bahrain economy depends directly upon oil. in fact, oil accounts for >70% of government revenues and >60% of export receipts. bahrain was the first country in the region to discover oil in 1932. the timing of oil discovery was very critical, as the trade in the pearl sector had fallen, and a need for another source of income had emerged. the discovery of oil has made a quantum leap in bahrain’s economy as the economy moved from traditional crafting activities to heavy industries and infrastructure development. with the abundance of oil and the beginning of its export, government sectors in bahrain have begun to grow to meet the demand on government services. also, many industrial projects associated with oil and natural gas have been carried out. the first oil refinery was built in 1935 to meet domestic and foreign demand. mina salman was also established in a move aimed at enhancing bahrain’s trade exchange with the rest of the world. aluminum bahrain company (alba) was created in 1968 as the first aluminum smelter in the region, followed by gulf petrochemical industries company and king fahd causeway, in addition to other large enterprises and projects. the mentioned examples highlight the continuous importance of oil in bahrain economy. later, bahrain has been able to form an environment suitable to a relative growth in non-oil sectors through legislations as well as fiscal and monetary policies, including government expenditure and subsidy, in addition to local currency stability. all these factors have given more confidence to the development of the private sector in bahrain. this paper studies the contribution of ox to bahrain economic growth in the short run and in the long run. the rest of the paper is organized as follows. section 2 presents a literature review related to the research. section 3 shows the methodology, data and model specification used in the study. section 4 discusses the empirical results and analyzes the findings. finally, section 5 concludes with an emphasis on economic policy recommendations. 2. literature review since the 1950s, the discussion of export diversification and its relation to economic growth has been an essential topic. singer (1950) argued that strong export concentration of primary goods in developing countries delays growth as well as the terms of trade and increases income volatility. export diversification takes place when the extensive margin of exports and extensive margin of trade grow in a specific country. these margins grow through an increase in existing export products, or through export flows to new markets and new products (amurgo-pacheco and pierola, 2008). the relationship between export diversification and economic growth has been found to be mostly positive in the literature. using a conventional cross sectional country growth regression, al-marhubi (2000) finds that export diversification is positively related to the economic growth. herzer and nowak-lehmann (2006) analyze the link between export diversification and economic growth in chile. the study finds evidence that chile has benefited from diversifying its export products. hesse (2009) finds a strong link between export diversification and economic growth for developing countries. al-yousif (1997) studied the relationship between exports and economic growth in four gcc countries, namely kuwait, oman, ksa and uae over a period of 20 years, and concluded that there is no long-run relationship between exports and economic growth. pineres and ferrantino (2000) consider that export diversification might lead to knowledge spillovers from new techniques of production, new management or marketing practices, potentially benefiting other industries. on the other hand, export concentration, notably when a country becomes highly dependent on the exports of natural resources, has been proven to have a negative effect on economic growth. in their study of 95 abundant natural resources’ countries, sachs and warner (1995) showed a negative relationship between growth and exports of primary goods. same results of a negative correlation between exports of natural resources and growth were found in the study of hodler (2006). sala-i-martin and subramanian (2013) linked the negative effect of the natural resources to corruption. also, auty (2001) showed that the negative role of resources abundance on economic performance is due to the corruption and rent seeking behavior caused by the resources. however, brunnschweiler (2008) found a positive effect of natural resources’ abundance on economic growth when the impact of institutional quality is considered. dogruel and tekce (2010) showed a negative relation between economic growth and export concentration when they studied selected mena countries. an important consideration related to export concentration and the dependence on natural resources exports, is that export concentration would lead to a dutch disease through a decrease in the competitiveness of the tradable exports resulting from the appreciation of the national currency. stijns (2005) found some evidence of dutch disease in countries with abundant oil reserves. nevertheless, harb (2009) cited that dutch disease is unlikely to occur in the case of gcc countries since foreigners represent an important composition of the labor force. also, export concentration, specifically in natural resources, is associated with high risk that is resulting from volatility and instability in export earnings, which can deteriorate a country’s vulnerability to economic shocks. gylfason (2001) cited that rich resources countries always neglect the need of good education. ross (2001) showed that oil has a negative effect on democracy, and therefore on economic development in oil rich countries. natural resource abundant countries have also weaker incentives to industrialize, as they can earn the foreign exchange needed to finance their imports without industrializing. even when industrialization takes place in those countries, it is mostly related to capital-intensive products rather than knowledge intensive products. this would have negative consequences on human capital development and wage inequality (bonaglia and fukasaku, 2003; mehlum et al., 2006). conversely, some economists consider that natural resources abundance does not necessarily affect economies in a negative way. torvik (2009) showed that oil revenues might have no effect on the long-run economy. therefore, they cannot be blamed for bad khayati: the effects of oil and non-oil exports on economic growth in bahrain international journal of energy economics and policy | vol 9 • issue 3 • 2019162 economic performance. also, natural resources can provide nations with an opportunity to improve new categories of competitive advantages in some sectors (alexeev and conrad, 2011; cavalcanti et al., 2011). imbs and wacziarg (2003) showed that export concentration follows a u-shape curve: export diversification has first a positive impact on gdp; however, reaching a high level of gdp will lead to concentration. lederman and maloney (2006) find that natural resources abundance leads to export concentration when the economies are open. therefore, the disadvantages that arise from export concentration in terms of vulnerability pushes policy makers to find the best way to their country’s economic growth (cadot et al., 2012). indeed, concentration of exports in a small group of products might increase volatility in the terms of trade, which may induce volatility in income (frankel, 2010; jansen, 2004). in order to avoid the economic risk from volatility of export prices, many economists distinguish between the roles of extensive margin and intensive margin in economic growth. in this regard, markusen (2013) showed that nations gain more from trade through an increase in extensive margin rather than intensive margin. also, dutt et al. (2013) showed that diversification resulting from extensive margin is more effective to economic growth than the one resulting from intensive margin. according to hummels and klenow (2005), extensive margin accounts for >60% of the increase in the exports of large economies. evenett and venables (2002) showed that extensive margin is more important to the growth of exports. also, berthou and fontagne (2016) found similar findings for french exports to the rest of the world. 3. data model specification and methodology the annual data for gdp, export of oil products, export of non-oil products, capital, labor force and imports of goods and services are collected from the annual statistical reports of the central bank of bahrain, world development indicators and international financial statistics. the study covers the period 1977-2015. all variables, except the labor force, are measured in million us dollars, and deflated by gdp deflator to get real values (year 2000 is the base year). in this context, as a starting point, the neoclassical model of growth is used. following hosseini and tang (2014), this model includes capital, labor, exports and imports. it is written as: y = f[(k,l); x,m] (1) the augmented production function including these variables can be expressed as: y = akαlβxγmλ (2) where, y: represents gdp, k: represents capital, l: represents labor, x: represents exports, m: represents imports; and a shows the level of technology in the country, which is assumed to be constant. α, β, γ, λ represent respectively the returns to scale associated with capital, labor, exports and imports. in linear functional form, the cobb-douglas production function is presented as follows: log (yt) = log (a)+α log (kt)+β log (lt)+γ log (xt)+λ log (mt)+εt (3) following mohsen (2015), when we distinguish between ox and other exports, the following equation can be written as: x = ox+nox (4) equation (4) presents the division between ox and non-oil exports (nox). in equation (5), (ox) and (nox) are relocated into logarithms in order to carry out the linear form of the cobb–douglas production function. log (xt) = log (oxt)+log (noxt) (5) when equations 3 and 5 are merged, the model of estimation is represented by the following equation: log (yt) = log (a)+α log (kt)+β log (lt)+γ log (oxt)+δ log (noxt)+λ log (mt)+εt (6) in order to examine the effect of ox on economic growth in bahrain, an estimate based on the cointegration approach is applied. the empirical methodology of this analysis consists first in determining the stationarity of the variables and the order of integration of each variable. for this purpose, augmented dickey-fuller (adf) and philips-perron (pp) tests are used. in this step, it is important to determine the number of lags by using a set of information selection criteria (tables 1 and 2). as soon as the number of lags is fixed, johanson testis used to examine the cointegration between the variables involved in the model. if a cointegration relation is found, an error correction model would be used in the analysis. 4. empirical analysis table 1 presents the results of adf and pp integration order tests. according to these last two tests, all variables considered in the study have unit roots at level. the hypothesis of presence of unit roots is rejected at first difference. this indicates that all variables are integrated of first order (table 2). the study proceeds to the next step of studying the cointegration between the variables applied in the model. based on schwarz criteria, one period lag has been selected to estimate cointegration. the results of the johanson test at one period lag (table 3) prove the existence of a cointegration relationship between economic growth, ox, nox, labor, capital and imports. khayati: the effects of oil and non-oil exports on economic growth in bahrain international journal of energy economics and policy | vol 9 • issue 3 • 2019 163 the cointegration equation (table 4) indicates that the variables capital, ox and nox have positive and significant relationship with economic growth. conversely, labor and imports have a negative impact on economic growth. probably, the reason behind that is that labor in bahrain is in large part concentrated on lowskilled labor force (mainly expatriate labor force), and that imports might hinder some domestic industries to grow. since variables are cointegrated, a causality analysis through vector error correction model can be made. table 5 shows that the lagged correction term is negative and significant. long run causality shows that more ox increases the economic growth in bahrain. inversely, bahrain would suffer a decrease in economic activity in the case of low international prices. results of wald test in table 6 show that capital, ox and imports granger cause economic growth in the short run; while labor and nox do not. this reflects the dominance of ox in relation to other sectors. table 1: unit root tests (adf and pp) variables adf pp constant constant, linear trend constant constant, linear trend iny −2.193809 [−7.256893]* −2.588476 [−7.865923]* −2.192907 [−7.098532]* −2.557392 [−7.328813]* ink −1.349148 [−5.059863]* −1.452842 [−5.653289]* −1.349278 [−5.043913]* −1758091 [−5.832518]* inl −1.454158 [−5.125896] −1.885236 [−5.235687]* −1.396321 [−5.032841]* −1.846273 [−5.089132]* inox −1.785462 [−7.589654]* −1.985552 [−7.698523]* −1.785459 [−7.613281]* −1.995482 [−7.728231]* innox −1.205236 [−4.985623]* −1.725689 [4.785643]* −1.205487 [−4.992563]* −1.730184 [−4.805129]* inm −0.756891 [−4.325682]* −1.698547 [−4.2135686]* −0.778693 [−4.335818]* −1.684291 [−4.230293]* *denotes significance at the 1% level, ( ) denotes stationarity at level, [ ] denotes significance at first difference, adf: augmented dickey-fuller, pp: philips-perron, ox: oil exports, nox: non-oil exports, k: capital, l: labor, m: imports, gdp: gross domestic product, y: gdp table 2: lag order selection criteria lags log l lr fpe aic sc hq 0 50.5682 na 3.67e-12 −1.389384 −0.985642 −1.098567 1 112.0532 157.5892 2.82e-09 −6.185268 −5.825697* −6.253894 2 137.5893 51.13568* 1.69e-04* −6.623589* −4.943652 −6.589325* 3 145.5834 13.15236 3.213561 −6.098563 −3.587463 −5.412563 *indicates lag order selected by the criterion. lr: sequential modified lr test statistic (each test at 5% level). fpe: final prediction error, aic: akaike information criterion, sc: schwarz information criterion, hq: hannan-quinn information criterion table 3: johansen test unrestricted cointegration rank test (trace) hypothesized number of ce (s) eigen value trace statistics 0.05 critical value prob.** none* 0.785642 89.45269 62.87459 0.0000 at most 1* 0.526324 42.65871 40.58965 0.0241 at most 2 0.395862 20.58972 25.69871 0.1687 at most 3 0.152468 5.489743 13.65748 0.4576 unrestricted cointegration rank test (maximum eigenvalue) hypothesized number of ce (s) eigen value max-eigen statistic 0.05 critical value prob.** none* 0.785642 46.00845 31.85691 0.0004 at most 1 0.526324 23.25871 24.67894 0.0917 at most 2 0.395862 16.52398 18.57965 0.1649 at most 3 0.152468 5.489743 13.65748 0.4652 trace test indicates 2 cointegrating eqn (s) at the 0.05 level. max. eigen value indicates 1cointegratingeqn (s) at the 0.05 level, *denotes rejection of the hypothesis at the 0.05 level, **mackinnon-haug-michelis (1999) p values. table 4: estimate of long-run co-integrating vector normalized coefficients gdp k l ox nox m c trend 1.00 −0.75932* 0.65894 −0.85253* −0.37124* 0.75942 −3.52416 0.06352* t-values −6.53894 4.29361 −6.03541 −2.75216 4.87921 6.87546 *denotes significance at the 1% level. ox: oil exports, nox: non-oil exports, k: capital, l: labor, m: imports, gdp: gross domestic product table 5: vecm estimates variables coefficients se t-values ect (−1) −0.635462* 0.07526 −6.52365 d (gdp (−1)) −0.325459 0.16542 −1.98564 d (ox (−1)) −0.065218 0.07123 −1.42568 d (nox (−1)) −0.107352 0.12536 −0.31547 d (l(−1)) −0.046532 0.09874 0.54126 d (k (−1)) 0.523654 0.19856 0.32546 d (m (−1)) −0.253648 0.15423 −1.85632 r2=0.812548, lagrange multiplier (lag 1)=(0.5146), (lag 2)=(0.5897), (lag 3)=(0.9254), breush-pagan-godfrey test=(0.7895), jarque-bera test=(0.4872). *represents significance at the 10% level. ox: oil exports, nox: non-oil exports, k: capital, l: labor, m: imports, vec: vector error correction model, gdp: gross domestic product khayati: the effects of oil and non-oil exports on economic growth in bahrain international journal of energy economics and policy | vol 9 • issue 3 • 2019164 5. conclusion using annual series data over the period 1977-2005, this study analyzes the effects of oil and nox on economic growth in the kingdom of bahrain. the cointegration test shows that both oil and nox have a positive and significant long-run relation with economic growth. however, ox have the biggest effect on gdp. besides, in the short run, ox induce economic growth, while the variable nox does not. this highlights the concentration of exports on the oil industry in relation to other sectors. based on those results, bahrain should accelerate the diversification process of the economy and upgrade other industrial and service sectors in order to rise the percentage of nox in total exports. this would attenuate the impact of sudden fluctuations in oil prices. it would also improve capital efficiency and labor productivity and promote the competitiveness of bahrain products in the global markets. references alexeev, m., conrad, r. (2011), the natural resource curse and economic transition. economic systems, 35(4), 445-461. al-marhubi, f. (2000), export diversification and growth: an empirical investigation. applied economics letters, 7(9), 559-562. al-yousif, y.k. (1997), exports and economic growth: some empirical evidence from the arab gulf countries. applied economics, 29(6), 693-697. amurgo-pacheco, a., pierola, m.d. (2008), patterns of export diversification in developing countries: intensive and extensive margins. washington, dc: the world bank. auty, r.m., editor. (2001), resource abundance and economic development. oxford: oxford university press. berthou, a., fontagné, l. (2016), variable trade costs, composition effects and the intensive margin of trade. the world economy, 39(1), 54-71. bonaglia, f., fukasaku, k. (2003), export diversification in lowincome countries: an international challenge after doha, oecd development centre working paper no. 209. available from: https:// www.ssrn.com/abstract=724761. brunnschweiler, c.n. (2008), cursing the blessings? natural resource abundance, institutions, and economic growth. world development, 36(3), 399-419. cadot, o., carrère, c., strauss-kahn, v. (2011), export diversification: what’s behind the hump? review of economics and statistics, 93(2), 590-605. cavalcanti, t.v.d., mohaddes, k., raissi, m. (2011), growth, development and natural resources: new evidence using a heterogeneous panel analysis. the quarterly review of economics and finance, 51(4), 305-318. dogruel, s., tekce, m. (2011), trade liberalization and export diversification in selected mena countries. topics in middle eastern and north african economies, 13, 1-24. dutt, p., mihov, i., van zandt, t. (2013), the effect of wto on the extensive and the intensive margins of trade. journal of international economics, 91(2), 204-219. evenett, s.j., venables, a.j. (2002), export growth in developing countries: market entry and bilateral trade flows. working paper, mimeo. p1-42. frankel, j.a. (2010), the natural resource curse: a survey (no. w15836). cambridge, ma: national bureau of economic research. gylfason, t. (2001), natural resources, education, and economic development. european economic review, 45(4-6), 847-859. harb, n. (2009), oil exports, non-oil gdp, and investment in the gcc countries. review of development economics, 13(4), 695-708. herzer, d., nowak-lehmann, d.f. (2006), is there a long-run relationship between exports and imports in chile? applied economics letters, 13(15), 981-986. hesse, h. (2009), export diversification and economic growth. in: breaking into new markets: emerging lessons for export diversification. washington, dc: world bank. p55-80. hodler, r. (2006), the curse of natural resources in fractionalized countries. european economic review, 50(6), 1367-1386. hosseini, s.m., tang, c.f. (2014), the effects of oil and non-oil exports on economic growth: a case study of the iranian economy. economic research-ekonomska istraživanja, 27(1), 427-441. hummels, d., klenow, p.j. (2005), the variety and quality of a nation’s exports. american economic review, 95(3), 704-723. imbs, j., wacziarg, r. (2003), stages of diversification. american economic review, 93(1), 63-86. jansen, m. (2004), income volatility in small and developing economies: export concentration matters (no. 3). wto discussion paper. lederman, d., maloney, w.f., editors. (2006), natural resources, neither curse nor destiny. washington, dc: the world bank. markusen, j.r. (2013), putting per-capita income back into trade theory. journal of international economics, 90(2), 255-265. mehlum, h., moene, k., torvik, r. (2006), cursed by resources or institutions? world economy, 29(8), 1117-1131. mohsen, a.s. (2015), effects of oil and non-oil exports on the economic growth of syria. academic journal of economic studies, 1(2), 69-78. pineres, s.a., ferrantino, m. (2000), the commodity composition of export portfolios: a comparative analysis of latin america. latin american business review, 1(3), 1-15. ross, m.l. (2001), does oil hinder democracy? world politics, 53(3), 325-361. sachs, j.d., warner, a.m. (1995), natural resource abundance and economic growth (no. w5398). working papers national bureau of economic research. sala-i-martin, x., subramanian, a. (2013), addressing the natural resource curse: an illustration from nigeria. journal of african economies, 22(4), 570-615. singer, h.w. (1950), the distribution of gains between investing and borrowing countries. the american economic review, 40(2), 473-485. stijns, j.p.c. (2005), natural resource abundance and economic growth revisited. resources policy, 30(2), 107-130. torvik, r. (2009), why do some resource-abundant countries succeed while others do not? oxford review of economic policy, 25(2), 241-256. table 6: vec granger causality/block exogeneity wald tests independent variable k l ox nox m joint chi-square (p values) 0.0623 (1)*** 0.2471 (1) 0.0427 (1)*** 0.7852 (1) 0.0547 (1)*** 0.0652 (5)*** ***represents significance at the 10% level. figures in parentheses show degree of freedom. ox: oil exports, nox: non-oil exports, k: capital, l: labor, m: imports, vec: vector error correction . international journal of energy economics and policy | vol 10 • issue 3 • 2020 429 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(3), 429-437. information and communication technology, energy consumption and financial development in africa kunofiwa tsaurai* department of finance, risk management and banking, university of south africa, pretoria, south africa. *email: kunofiwa.tsaurai@gmail.com received: 17 may 2019 accepted: 10 february 2020 doi: https://doi.org/10.32479/ijeep.8721 abstract the study investigated the impact of information and communication technology (ict) and energy consumption on financial development in africa using dynamic generalised methods of moments with secondary annual data spanning from 2001 to 2015. literature is unanimous that ict and energy consumption separately contributes towards financial development although there are so far scarce case studies which focused on the african continent. when domestic credit to private sector (% of gdp) was used as a measure of financial development, ict and energy consumption were found to had a non-significant negative influence on financial development, a finding that contradicts majority of literature on the subject matter. when broad money (% of gdp) was used as a proxy of financial development, both ict and energy consumption had a significant positive effect on financial development. the finding generally resonates with kirmani et al. (2015) whose study argued that ict increases efficiency, reliability, effectiveness, performance and other characteristics of modern-day commercial operations through the way transactions are catered for in any financial system. african nations are therefore urged to increase their use of modern ict technology and increase energy consumption in order to boost financial development. future studies can also focus whether ict and energy consumption influence financial development through other channels such as economic growth, among others. keywords: information and communication technology, energy consumption, financial development, africa jel classifications: n7, q4, e44, o55 1. introduction 1.1. background of the study information and communication technology (ict) is the use of computers to store, retrieve, transmit, and manipulate data, or information, often in the context of some business or other enterprises (deb, 2014). humans have been storing, retrieving, manipulating, and communicating information since the sumerians in mesopotamia developed writing in about 3000 bc, but the term ict in its modern sense first appeared in a 1958 article published in the harvard business review by authors leavitt and whisler (1958). their definition consists of three categories: techniques for processing, the application of statistical and mathematical methods to decision-making, and the simulation of higher-order thinking through computer programs (leavitt and whisler, 1958). the term is commonly used as a synonym for computers and computer networks, but it also encompasses other information distribution technologies such as television and telephones. several products or services within an economy are associated with ict, including computer hardware, software, electronics, semiconductors, information, telecom equipment and e-commerce. ict has turned into a significant factor in future development of financial services industry and especially the banking industry. the transformations occurred in the ict industry significantly contributed to the growth and profitability of financial institutions especially in the banking industry around the world (spremic et al., 2008). in the current century, using ict in banking is comprehensive and necessary. today, considering the fact that data is stored electronically in databases, at the this journal is licensed under a creative commons attribution 4.0 international license tsaurai: information and communication technology, energy consumption and financial development in africa international journal of energy economics and policy | vol 10 • issue 3 • 2020430 time of facing with any problem which results in the failure of ict systems, a limited number of banks can quickly present accurate information regarding their customers’ bank accounts (spremic et al., 2008). ict has continued to play an important role in the growth of the business industry in the 21st century (lee, 2009). the dawn of computers, ict and the internet has changed the way businesses operate. from human resources to marketing and financial management, everywhere the role of ict has grown. none of these functions can be run without using ict as the use of ict means adding speed, efficiency, and convenience to these functions. businesses are using every form of technology to grow their sales and revenue whilst finance is an important and a bit complex function that cannot be run efficiently without the use of ict (pratap, 2018). although the impact of ict on financial development has been investigated by empirical studies, none of them comprehensively focused on africa. it is against this background that the current study focused on investigating the role of ict on financial development in the african context. the current study helps african countries to develop ict usage and growth related policies that enhances financial development. 1.2. gaps found in the literature (problem statement) there is not much available empirical research on the impact of ict and energy consumption on financial development. in other words, empirical studies that investigated ict-energy consumption-financial development nexus are quite scant, especially in the african context. most related research that has been done focused on the influence of it and energy consumption on financial institutions, financialization, financial performance and services. the imperial research available also reveals quite diverse, divergent and mixed findings, a clear indication that the matter is not yet conclusive and therefore, further empirical investigations still need to be done. 1.3. contribution of the study the current study contributes to literature in that it investigates the influence that ict and energy consumption has on financial development and extending our understanding of financial development by connecting it to the field of ict and energy consumption research. lagoarde-segot and currie (2018) claims that it researchers are used to looking through the microscope rather than the telescope to analyse the adoption and deployment of information technology (it). the study of financial development in the field of it and energy consumption research will therefore provide fresh opportunities for understanding the broader implications of how technology plays a mediating role in economies and societies. 1.4. organization of the study section 2 discusses the theoretical literature and empirical literature whilst section 3 summarises how other factors (apart from ict and energy consumption) influence financial development. section 4 is the research methodology and section 5 deals with main data analysis. section 6 is the summary of the paper. 2. literature review 2.1. theoretical literature review salehi et al. (2010) have indicated that it is one of the most important variables which has become a fact of life in the organizations of today. it plays a key role in removing time and place limitations and causes information to become available to users more quickly and in a more satisfactory way. it also changes the way of performing tasks and transforms paper methods into electronic ones. the changes provide conditions in which time needed for information exchange is shorter and the way of making financial exchanges has changed that is financial information is exchanged instead of money. countries in their business sectors invest in it to improve their economic performances. it can improve information sharing, decision-making, coordination, product quality, responsiveness and distribution (mitchell and kovach, 2016; perez-arostegui et al., 2015; moharana et al., 2011; clemons et al., 1993). it, defined as computer and related digital communication technology has extensive power to reduce the costs of coordination, communication, and information processing (rouleau et al., 2015; deb, 2014; cordella, 2006; brynjolfsson and hitt, 2000). this study focused on the impact of ict on financial development. previous research has shown that it does not automatically improve financial development of a country (munyanyi, 2017) but can increase productivity (dedrick et al., 2013). previous research has found that it investment is associated with significant productivity gains for developed countries but not for developing countries (chwelos et al., 2010). ict is an essential tool but not sufficient, and should therefore be coupled with organizational factors such as business strategies (shin, 2001). the advances in it have heavily influenced commercial businesses in several ways. the most important role of it in a business is to provide a commercial advantage (deb, 2014). it provides commercial benefits in advances such as computer aided design, relational database technologies, spreadsheets, and word processing software (deb, 2014). the same study noted that the use of it to monitor a business performance can also enable the business to highlight areas where they are not making the most use of their resources. an infrastructure of computing and communication technology provides 24-h access at low cost to almost any kind of price and product information desired by buyers, reduce the information barriers to efficient market operation (deb, 2014). this infrastructure might also provide the means for effecting real-time transactions and make intermediaries such as sales clerks, stock brokers and travel agents, whose function is to provide an essential information link between buyers and sellers redundant (clemons et al., 1993). the information technologies have facilitated the evolution of enhanced mail order retailing, in which goods can be ordered quickly by using telephones or computer networks and then dispatched by suppliers through integrated transport companies that rely extensively on computers and communication technologies to control their operations (clemons et al., 1993). tsaurai: information and communication technology, energy consumption and financial development in africa international journal of energy economics and policy | vol 10 • issue 3 • 2020 431 2.2. empirical literature review most previous research has focused on the impact of it on financial performance (tang et al., 2012; wang et al., 2008; shin, 2001:2006; cron and sobol, 1983). shin (2001) examines empirically the contribution of it to financial performance as measured by net profit, return of assets (roa), and return of equity (roe) by focusing on the alignment of it with business strategies such as vertical disintegration and diversification. empirical analysis showed that it does not directly improve financial performance. in conjunction with vertical disintegration and diversification, however, it does improve financial performance as measured by net profit. financial performance ratios such as roa and roe, however, are not correlated with the alignment (or interaction) factor of it with vertical disintegration and diversification. the results indicate that increased it spending improves net profit, but not performance ratios of firms with decreased vertical integration and higher diversification. cron and sobol (1983) investigated the impact of it investment on financial performance for medical wholesale suppliers and found that, on average, the impact of it was not significant. investing in it such as internet, computers and telecommunications technologies can help in improving economic performance of companies (farhadi et al., 2012; shin, 2001). kamssu et al. (2003) found out that the choice of a particular technology to implement a firm’s business strategy may impact the firm’s market performance. their study assessed the impact of being an internet-dependent firm on a firm’s stock valuation and the results they got indicated that there are lower excess returns in internet-dependent firms than non-internet firms. the high returns can be explained by the fact that internet stocks traded at relatively higher prices than non-internet stocks, and this meant that choosing a particular technology to implement business strategy might have a significant impact on a firm’s stock performance. sadeghimanesh and samadi (2013) in their study indicated that the dimensions of it including it knowledge, it operations and it infrastructures had a significant effect (p < 0.01) on financial performance of the banks listed in tehran stock exchange. kirmani et al. (2015), state that ict has increased efficiency, reliability, effectiveness, performance and other characteristics of modern-day commercial operations through the way transactions are catered for in any financial system with optimal levels of performance and efficiency. the emergence of ict has opened multiple facets of enterprises that collectively interact with geographically dispersed workstations to carry out business activities more efficiently, over digital networks. ict has contributed openly to eliminate time, distance and space constraints in order to furnish the business activities with ease and efficiency by integrating the capability of high-speed devices with high speed communication links carrying multimedia information. ict deals with the collection, storage, manipulation and transfer of information using electronic means (kirmani et al., 2015). generally, ict is considered one of the most reliable means of providing a strong platform for effective system of internal control over financial reporting. it stands to reason that a sound ict system provides a sure and guarantee medium of financial information delivery that covers the entire accounting cycle of the firm. ict creates conducive atmosphere that integrates all financial transactions with the help of accounting software to generate financial report which thereto, would have very difficult to prepare. pratap (2018) points out that the application of it in financial management has also accounted a lot more success and efficiency in performing various operations related to different activities to commit a financial transaction and has notably produced better throughputs which are acceptable and reliable. the internet has brought the biggest change in this area by making storing, sharing and publishing of financial data easier. the key advantages of it in the area of financial management is the use of automation, shared management information systems which enable the sharing of data between the various departments and faster workflow. the field of it has seen a lot of innovation and made everyone’s task easier. several companies share their financial information publicly online from their websites. balance sheets and proforma statements get ready within minutes and are published and shared with stakeholders with ease. however, one important challenge that it has faced is that of data safety. however, in the sphere of it, as the challenges take place innovation too happens. cloud based storage systems have helped companies store their data with care. it saw a swift jump with increased reach and better performance. banking and finance sector have grown very fast in the past decade because of it which has added speed and efficiency in the sector. it has brought growth in the financial world and helped it in several spheres. data processing, quality of reporting and marketing in the banking world, all have grown very fast with the arrival of the internet (pratap, 2018). salehi and torabi (2012) investigated the role of it in financial reporting as well as the relationship between using it and its impact on the quality of financial reporting. they found out that the use of it has considerably changed financial reporting, especially with regards to the relevance of accounting information, mainly because the use of it (particularly the internet, its instruments and protocols or software formats based on that) has resulted in on-line financial reporting in which it can help users make better economic and managerial decisions. furthermore, the results of the research indicate that apart from various advantages of it in financial reporting, its reliability is reduced due to the fact that it decreases reliability in the security of information (salehi and torabi, 2012). as mentioned earlier, by using it, financial reporting of firms will move towards on-line financial reporting, in which firms use a specific format and define harmonized reporting procedures thus enhancing the stability of this process in those firms. figure 1 summarizes the role that it plays in financial development. kamel (2005) points out that the vital role ict is playing is felt across many industries and sectors, affecting both economic development and growth at large in many societies. the resulting implications have had a major role in transforming such sectors and have affected the economic-development process in developing nations. the banking sector is an example in which tsaurai: information and communication technology, energy consumption and financial development in africa international journal of energy economics and policy | vol 10 • issue 3 • 2020432 it infrastructures have had positive implications. it is important to note that the banking industry was one of the very first to utilize it back in the 60s and has thus a record of influencing the development process through the technology. there are many examples of it applications in the banking sector that have helped build new markets and fuel the economy like, automated teller machine technology adoption has increased community efficiency, which led to a reduction in costs, improvement of quality, and increase in the added value to customers. however, some of the implementations of it in the banking sector in the context of developing nations are often hindered by a number of challenges, including (but not limited to) lack of stability of the legislation, weak financial sector, poor technological infrastructure and relatively small internet and computer penetration (kamel, 2005). recently, developing nations are increasingly investing in building up and improving their technology infrastructure, focusing on electronic commerce, electronic banking, and electronic learning (makame et al., 2014). consistent with both theoretical and empirical literature, there is no doubt that it and or ict has had a significant influence on business and financial development in recent years. what the literature has so far failed to adequately capture is how ict has had an immense contribution towards financial development in the context of developing nations, especially africa. the current study seeks to fill in that gap. table 1 summarizes the empirical literature that exclusively focused on the impact of it or ict and energy consumption on financial development also dabbous (2018), rafindadi and ozturk (2017), nasreen et al. (2017 for the recent literature). 3. other variables that have an influence on financial development foreign direct investment, trade openness, population growth, unemployment, economic growth, human capital development and infrastructural development are some of the variables that have an impact on financial development (table 2). 4. research methodology the study used secondary panel data ranging from 2001 to 2015 for fifteen african countries. these fifteen african countries include burundi, kenya, rwanda, algeria, morocco, tunisia, ghana, nigeria, senegal, cameroon, democratic republic of the congo, gabon, namibia, south africa and mozambique. the data was extracted from world bank indicators, african development indicators, united nations development programme various reports and international financial statistics database. there are two versions of the same econometric methods used in this study. figure 1: financialization: a conceptual framework adapted from lagoarde-segot (2016) tsaurai: information and communication technology, energy consumption and financial development in africa international journal of energy economics and policy | vol 10 • issue 3 • 2020 433 fini,t=β0+β1 icti,t+β2 energyi,t+β3 xi,t+µ+ε (1) fin is financial development and is proxied by two measures, namely the domestic credit to the private sector (% of gdp) and broad money (% of gdp). ict represents information and communication technology and is proxied by individuals using internet (% of population). x are the control variables (energy, open, popul, unempl, gdppc, hcd, infr). energy (energy consumption) is measured by energy use (kg of oil equivalent per capita). β0 to β9 represents co-efficients of the variables. ɛ is the error term and µ represents the time invariant and unobserved country specific effect. subscripts i represents the country and t is the time. table 1: a summary of the impact of information technology on financial development–empirical literature author country/countries of study methodology findings ho and mallick (2006) us banking industry panel regression the results show that the bank profits declined due to the adoption and diffusion of it investments, reflecting negative network effects in this industry sadeghimanesh and samadi (2013) tehran two-variable linear regression test the results indicated that information technology dimensions including it knowledge, it operations and it infrastructures had significant effect (p<0.01) on financial performance of the banks listed on tehran stock exchange kirmani et al. (2015) india literature analysis ict has sophisticated the way transactions are catered in any financial system with optimal levels of performance and efficiency a summary of the impact of energy consumption on financial development–empirical literature gomez and rodriguez (2019) north american free trade agreement (nafta) countries fully modified and dynamic ordinary least squares the study found out that energy consumption had a negligible positive influence on financial development in nafta countries saudi et al. (2018) next 11 countries panel data analysis a feedback relationship between energy consumption and financial development was detected in the next-11 countries saini and neog (2018) india vector error correction model a bi-directional causality between energy consumption and financial development in india was observed zeren and koc (2014) new industrialized countries toda-yamamoto causality test energy consumption was found to have had a positive influence on financial development in newly industrialized countries faisal et al. (2017) pakistan auto-regressive distributive lag (ardl) energy consumption and financial development were found to have affected each other source: authors’ compilation table 2: theory intuition and a priori expectation variable proxy used theory intuition expected sign foreign direct investment (fdi) net fdi inflow (% of gdp) fdi inflows enhances competition and efficiency in the financial sector (shahbaz and rahman, 2010). according to misun and tomsik (2002), private investment did crowd out private investment in poland thereby negatively affecting financial development. hailu (2010) argued that there is an inverse relationship between fdi and financial development ± trade openness (open) total of exports and imports (% of gdp) svaleryd and vlachos (2002) noted that trade openness boost domestic firms’ competitiveness in the international markets. the newly found competitive space in the international markets trigger the need to use sophisticated financial risk management services that helps to absorb external shocks + population growth (popul) population growth (% annual) in circumstances of increased population growth, the government end up borrowing from the domestic financial markets to meet the people’s social needs thus crowding out private investment and lowering down the rate of financial development − unemployment (unempl) unemployment total (% of total labour force) according to han (2009), more unemployed people means more unbanked or financially excluded people. this is because unemployed people do not have income that they can use to meaningfully participate in financial markets − economic growth (gdppc) gdp per capita ceteris paribas, higher economic growth means that the general population has higher levels of savings and wealth to invest back into the financial markets and enhance financial sector development (robinson, 1952) + human capital development (hcd) human capital development index people who are educated, skilled and healthy are likely contribute better towards financial development because they are able to make meaningful financial choices (becker, 1964) + infrastructure development (infr) fixed telephone subscriptions per 100 people higher levels of infrastructural development push down the cost of doing business not only for financial sector players but the overall business sector thus creating more avenues and possibilities for financial development (ifeakachukwu, 2015) + source: author compilation tsaurai: information and communication technology, energy consumption and financial development in africa international journal of energy economics and policy | vol 10 • issue 3 • 2020434 the full econometric model which shows the dependent, independent and control variables is shown below. fini,t=β0+β1 fini,t−1+β2 icti,t+β3 energyi,t+β4 fdii,t +β5 open+β6 populi,t+β7 unempli,t+β8 gdppci,t +β9 hcti,t+β10 infri,t+µ+ε� (2) the dynamic panel generalised methods of moments (gmm) approach by arellano and bond (1991) was used to estimate equation 2. the main advantage of using the dynamic gmm method is that it captures the dynamic characteristics of financial development data as observed by tsaurai (2018a). the other benefit of using the dynamic gmm approach is that it addresses the endogeneity problem in the financial development function. 5. results, discussion and interpretation as expected, table 3 shows a significant positive correlation between (1) financial development and ict, (2) financial development and trade openness, (3) financial development and unemployment, (4) financial development and economic growth, (5) financial development and human capital development and (6) financial development infrastructural development. in line with tsaurai (2018b), gdppc is the only variable characterized by extreme values (standard deviation more than 100). using tsaurai (2018b), all other variables are not normally distributed except trade openness because the probability of their jarque-bera criterion is zero (table 4). it is against this background that the current study had to first transform all the data into natural logarithms before using it in order to avoid producing spurious results. before estimating the results using the dynamic gmm approach, data was found to be stationary at first difference (table 5) and also that a long run relationship existed between and among the variables being studied (table 6). in both model 1 and 2, the lag of financial development had a significant positive effect on financial development in african nations studied, consistent with tsaurai (2018a. p. 77). model 1 and 2 shows that ict had a significant positive impact on financial development in african countries, a result which is generally in line table 3: correlation analysis fin ict energy open popul unempl gdppc hcd infr fin 1.00 ict 0.66*** 1.00 energy −0.01 −0.02 1.00 open 0.31*** 0.26*** 0.48*** 1.00 popul −0.75*** −0.41*** 0.13* −0.27*** 1.00 unempl 0.42*** 0.21*** 0.27*** 0.49*** −0.43*** 1.00 gdppc 0.37*** 0.51*** −0.06 0.37*** −0.35*** 0.58*** 1.00 hcd 0.65*** 0.99*** −0.02 0.26*** −0.41*** 0.21*** 0.51*** 1.00 infr 0.76*** 0.51*** −0.12* 0.39*** −0.86*** 0.50*** 0.54*** 0.51*** 1.00 source: author compilation from e-views. ***, **, *denotes statistical significance at the 1%/5%/10% level respectively table 4: descriptive statistics fin ict energy open popul unempl gdppc hcd infr mean 39.4 10.8 3.62 68.5 2.32 11.1 2277 10.8 3.50 median 31.1 5.77 2.22 65.9 2.61 10.0 1309 5.77 1.49 maximum 117.4 57.1 41.8 125.5 3.71 27.3 10716 57.1 12.5 minimum 2.86 0.01 0.00 20.96 0.76 0.83 112.9 0.01 0.01 standard. deviation 25.9 13.5 5.2 21.5 0.76 7.83 2347 13.5 3.8 jarque-bera 54.5 189 6711 3.1 21.2 20.2 94.1 187.2 35.0 probability 0.00 0.00 0.00 0.21 0.00 0.00 0.00 0.00 0.00 observations 225 225 225 225 225 225 225 225 225 source: author compilation from e-views table 5: panel stationarity tests–individual intercept level first difference llc ips adf pp llc ips adf pp fin −1.71** 1.34 22.87 25.12 −6.18*** −4.69*** 75.45*** 121.55*** ict −1.65** 1.34 25.95 76.76*** −9.25*** −5.16*** 72.52*** 101.59*** fdi −11.35*** −4.93*** 77.11*** 95.45*** −10.23*** −7.89*** 117.43*** 218.69*** open −2.50*** −0.75 34.90 34.84 −6.90*** −5.24*** 83.90*** 133.75*** popul −10.52*** −6.14*** 107.01*** 59.37*** −6.81*** −3.34*** 71.32*** 58.37*** unempl −3.27*** −0.44 34.63 23.52 −7.23*** −4.23*** 54.25*** 74.44*** gdppc −7.90*** −4.27*** 74.42*** 79.18*** −3.08*** −2.52*** 48.61** 69.28*** hcd −1.53* 1.52 24.93 74.57*** −15.52*** −6.59*** 65.36*** 102.27*** infr −0.97 0.64 27.68 24.11 −3.96*** −3.14*** 58.11*** 109.40*** source: author’s compilation from e-views. llc, ips, adf and pp stands for levin et al. (2002); im et al. (2003); adf fisher chi-square and pp fisher chi-square tests respectively. *, ** and *** denote 1%, 5% and 10% levels of significance, respectively tsaurai: information and communication technology, energy consumption and financial development in africa international journal of energy economics and policy | vol 10 • issue 3 • 2020 435 with kirmani et al.’s (2015) argument that ict increases efficiency, reliability, effectiveness, performance and other characteristics of modern-day commercial operations through the way transactions are catered for in any financial system (tables 7 and 8). in both models, energy consumption was found to have had a significant positive effect on financial development in line with a prior study done by zeren and koc (2014). in model 1, trade openness had an insignificant positive impact on financial development whilst model 2 shows a significant positive relationship running from trade openness towards financial development in african countries studied. the results resonate with svaleryd and vlachos (2002) whose study noted that trade openness encourages more participation in international trade and more financial development due to the need to absorb external shocks associated with participating in international financial markets. both model 1 and 2 produced a significant negative relationship running from population growth towards financial development, results which contradicts majority of the literature but resonates with the view that in the face of increased population growth, government’s appetite to borrow from local financial markets increases in order to meet the social needs of the increased population. this then crowds out private investment and slows down financial sector development. unemployment was found to have had a significant positive impact on financial development in model 1 whereas model 2 shows that unemployment had an insignificant positive influence effect on financial development in african nations. the finding is in line with han (2009) whose study noted that more unemployed people means more unbanked or financially excluded people. this is because unemployed people do not have income that they can use to meaningfully participate in financial markets. in line with robinson’s (1952) view that higher economic growth means that the general population has higher levels of savings and wealth to invest back into the financial markets and enhance financial sector development, the current study found out that economic growth had a significant negative influence on financial development in africa. contrary to the literature (becker, 1964), the study found out that human capital development had a significant negative influence on financial development in africa (in both model 1 and 2). last but not least, infrastructural development had a significant positive impact on financial development in model 1 whilst a non-significant positive relationship running from infrastructure development towards financial development in african countries was detected. the finding resonated with ifeakachukwu (2015) whose study noted that higher levels of infrastructural development push down the cost of doing business not only for financial sector players but the overall business sector thus creating more avenues and possibilities for financial development. 6. conclusion the study investigated the impact of ict and energy consumption on financial development in africa using dynamic gmm with secondary annual data spanning from 2001 to 2015. literature is unanimous that ict and energy consumption separately contributes towards financial development although there are so far scarce case studies which focused on the african continent. when domestic credit to private sector (% of gdp) was used as a measure of financial development, ict and energy consumption were found to had a significant positive influence on financial development, a finding that contradicts majority of literature on the subject matter. when broad money (% of gdp) was used as a proxy of financial development, ict and energy consumption had a significant positive effect on financial development. the finding generally resonates with kirmani et al. (2015) whose study argued that ict increases efficiency, reliability, effectiveness, performance and other characteristics of modernday commercial operations through the way transactions are catered for in any financial system. african nations are therefore urged to increase their use of modern ict technology and energy consumption in order to boost financial development. dedrick et al. table 6: kao residual co-integration test-individual intercept t-statistic probability augmented dickey-fuller −3.9460 0.0000 source: author’s compilation from e-views table 7: dynamic gmm results – model 1 (fin proxied by domestic credit to private sector [% of gdp]) co-efficient standard error t-statistic probability fdilag 0.6601*** 0.0379 17.4259 0.0000 ict 0.3202* 0.5495 0.5828 0.5607 energy 0.0172* 0.0099 1.7248 0.0860 open 0.0474 0.0531 0.8925 0.3731 popul −0.1993*** 0.0512 −3.8934 0.0001 unempl 0.0892*** 0.0236 3.7832 0.0002 gdppc −0.1106*** 0.0277 −3.9881 0.0001 hcd 0.3685 0.5487 0.6717 0.5025 infr 0.0658*** 0.0167 3.9437 0.0001 adjusted r-squared 0.9271 j-statistic 215.00 prob (j-statistic) 0.0000 source: author’s compilation from e-views table 8: dynamic gmm results–model 2 (fin proxied by broad money [% of gdp]) co-efficient standard error t-statistic probability fdilag 0.8064*** 0.0298 27.0919 0.0000 ict 0.2475** 0.6242 0.3965 0.6921 energy 0.0208* 0.0112 1.8512 0.0655 open 0.1280** 0.0605 2.1161 0.0355 popul −0.1415** 0.0578 −2.4479 0.0152 unempl 0.0286 0.0261 1.0977 0.2736 gdppc −0.1315*** 0.0293 −4.4913 0.0000 hcd −0.1088 0.6232 −0.1746 0.8616 infr 0.0213 0.0186 1.1406 0.2553 adjusted r-squared 0.9433 j-statistic 215 prob (j-statistic) 0.0000 source: author’s compilation from e-views tsaurai: information and communication technology, energy consumption and financial development in africa international journal of energy economics and policy | vol 10 • issue 3 • 2020436 (2013) noted that the productivity effects of ict are moderated by country factors, including human resources, openness to foreign investment and the quality and cost of the telecommunications infrastructure. future studies can also focus whether ict and energy consumption separately influence financial development through other channels such as economic growth, among others. references arellano, m., bond, s. (1991), some tests of specification for panel data: monte carlo evidence and an application to employment equations. the review of economic studies, 58(2), 277-297. becker, g.s. (1964), human capital: a theoretical and empirical analysis with special reference to education. chicago: university of chicago press. brynjolfsson, e., hitt, l.m. (2000), beyond computation: information technology, organizational transformation and business performance. journal of economic perspectives, 14(4), 23-48. chwelos, p., ramirez, r., kraemer, k.l., melville, n.p. (2010), does technological progress alter the nature of information technology as a production input? information systems research, 21(2), 392-408. clemons, e.k., reddi, s.p., row, m.c. (1993), the impact of information technology on the organization of economic activity: the ‘move to the middle’ hypothesis. journal of management information systems, 10(2), 9-35. cordella, a. (2006), transaction costs and information systems: does it add up? journal of information technology, 21(3), 195-202. cron, w.l., sobol, m.g. (1983), the relationship between computerization and performance: a strategy for maximizing the economic benefits of computerization. information and management, 6(3), 171-181. dabbous, a. (2018), the impact of information and communication technology and financial development on energy consumption: a dynamic heterogeneous panel analysis for mena countries. international journal of energy economics and policy, 8(4), 70. deb, s. (2014), information technology, its impact on society and its future. advances in computing, 4(1), 25-29. dedrick, j., kraemer, k.l., shih, e. (2013), information technology and productivity in developed and developing countries. journal of management information systems, 30(1), 97-122. faisal, f., tursoy, t., resatoglu, n.g. (2017), is there any causality between financial development, energy consumption and economic growth in pakistan? evidence from ardl bounds testing approach and vector error correction model. international journal of ecological economics and statistics, 38(2), 1-17. farhadi, m., ismail r., fooladi, m. (2012), information and communication technology use and economic growth. plos one, 7(11), e48903. gomez, m., rodriguez, j.c. (2019), energy consumption and financial development in nafta countries, 1971-2015. applied sciences, 9(1), 2-11. hailu, z.a. (2010), demand side factors affecting the inflow of foreign direct investment to african countries: does capital market matter? international journal of business and management, 5(5), 103-112. han, k.c. (2009), unemployment, financial hardship and savings in individual development accounts. journal of poverty, 13(1), 4-95. ho, s.j., mallick, s.k. (2006), “the impact of information technology on the banking industry: theory and empirics. available from: http:// www.webspace.qmul.ac.uk/pmartins/mallick.pdf. ifeakachukwu, n.p. (2015), impact of infrastructural expenditure on stock market development in nigeria. scholars bulletin, 1(1), 1-4. im, k.s., pesaran, m.h., shin, y. (2003), testing unit roots in heterogeneous panels. journal of econometrics, 115(1), 53-74. kamel, s. (2005), the use of information technology to transform the banking sector in developing nations. information technology for development, 11(4), 305-312. kamssu, a.j., reithel, b.j., ziegelmayer, j.l. (2003), information technology and financial performance: the impact of being an internet-dependent firm on stock returns. information systems frontiers, 5(3), 279-288. kirmani, m.m., wani, f.a., saif, s.m. (2015), impact of ict on effective financial management. international journal of information science and system, 4(1), 1-14. lagoarde-segot, t. (2016), prolegomena to an alternative study of finance. in: parangue, b., perez, r., editors. vol. 10. bingley, united kingdom: emerald group publishing limited. p89-110. lagoarde-segot, t., currie, w.l. (2018), financialization and information technology: a multi-paradigmatic view of it and finance-part ii. journal of information technology, 33(2018), 1-8. leavitt, h.j., whisler, t.l. (1958), management in the 1980s. harvard business review, 36(1958), 41-48. lee, k.r. (2009), impacts of information technology on society in the new century. route de chavannes, switzerland: ch-1007 lausanne-vidy. levin, a., lin, c.f., chu, c.s.j. (2002), unit root tests in panel data: asymptotic and finite-sample properties. journal of econometrics, 108(1), 1-24. makame, w.h., kang, j., park, s. (2014), factors influencing electronic commerce adoption in developing countries: the case of tanzania. south african journal of business management, 45(2), 83-96. misun, j., tomsik, v. (2002), does foreign direct investment crowd in or crowd out domestic investment. eastern european economics, 40(2), 38-56. mitchell, e., kovach, j. (2016), improving supply chain information sharing using design for six sigma. european research on management and business economics, 22(3), 147-154. moharana, h.s., murty, j.s., senapati, s.k., khuntia, k. (2011), importance of information technology for effective supply chain management. international journal of modern engineering research, 1(2), 747-751. munyanyi, m.e. (2017), the dynamic relationship between financial development and economic growth: new evidence from zimbabwe, no. 80401. germany: university library of munich. nasreen, s., anwar, s., ozturk, i. (2017), financial stability, energy consumption and environmental quality: evidence from south asian economies. renewable and sustainable energy reviews, 67, 1105-1122. perez-arostegui, m., bustinza-sanchez, f., barrales-molina, v. (2015), exploring the relationship between information technology competence and quality management. business review quarterly, 18(1), 4-17. pratap, a. (2018), role of information technology in financial reporting and management. available from: https://www.cheshnotes. com/2018/01/role-information-technology-financial-reportingmanagement. rafindadi, a.a., ozturk, i. (2017), dynamic effects of financial development, trade openness and economic growth on energy consumption: evidence from south africa. international journal of energy economics and policy, 7(3), 74-85. robinson, j. (1952), the generalisation of the general theory. in: the rate of interest and other essays. london: macmillan. rouleau, g., gagnon, m.p., cote, j. (2015), impacts of information and communication technologies on nursing care: an overview of systematic reviews. systematic reviews, 23(4), 75-83. sadeghimanesh, m., samadi, a. (2013), the effect of it (information technology) on financial performance of the banks listed in tehran stock exchange. european online journal of natural and social sciences, 2(3), 2911-2919. tsaurai: information and communication technology, energy consumption and financial development in africa international journal of energy economics and policy | vol 10 • issue 3 • 2020 437 saini, s., neog, y. (2018), examining the linkages between financial development and energy consumption in india. international conference on economics and finance, 1(3), 119-130. salehi, m., moradi, m., ariyanpour, a. (2010), a study of the integrity of internet financial reporting: empirical evidence of emerging economy. global journal of management and business research, 10(1), 148-158. salehi, m., torabi, e. (2012), the role of information technology in financial reporting quality: iranian scenario. poslovna izvrsnost, 6(1), 115-127. saudi, d.s., baloch, m.a., lodhi, r.n. (2018), the nexus between energy consumption and financial development: estimating the role of globalization in next-11 countries. environmental science and pollution research, 25, 18651-18661. shahbaz, m., rahman, m.m. (2010), foreign capital inflows-growth nexus and the role of domestic financial sector: an ardl cointegration approach for pakistan. journal of economic research, 15(3), 207-231. shin, n. (2001), the impact of information technology on financial performance: the importance of strategic choice. european journal of information systems, 10(4), 227-236. spremic, m., zmirak, z., kraljevic, k. (2008), it and business process performance management: case study of itil implementation in finance service industry. cavtat, croatia: proceedings of iti 2008 30th international conference on information technology interfaces. p23-26. svaleryd, h., vlachos, j. (2002), markets for risk and openness to trade: how are they related? journal of international economics, 57(2), 369-395. tang, z., hull, c.e., rothenberg, s. (2012), how corporate social responsibility engagement strategy moderates the csr-financial performance relationship. journal of management studies, 49, 1274-1303. tsaurai, k. (2018a), an empirical study of the determinants of banking sector development in the sadc countries. the journal of developing areas, 52(1), 71-84. tsaurai, k. (2018b), does trade openness and foreign direct investment complement or substitute each other in poverty alleviation? euro economica, 37(1), 223-236. wang, q., lai, f., zhao, x. (2008), the impact of information technology on the financial performance of third-party logistics firms in china. supply chain management: an international journal, 13(2), 138-150. zeren, f., koc, m. (2014), the nexus between energy consumption and financial development with asymmetric causality test: new evidence from newly industrialized countries. international journal of energy economics and policy, 4(1), 83-91. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. . international journal of energy economics and policy | vol 8 • issue 5 • 2018 181 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(5), 181-186. marketing strategy for renewable energy development in indonesia context today willy arafah1*, lucky nugroho2, rowlan takaya3, soeharjoto soekapdjo4 1master of management, trisakti university, jakarta, indonesia, 2mercu buana university, jakarta, indonesia, 3master of management, trisakti university, jakarta, indonesia, 4master of management, trisakti university, jakarta, indonesia. *email: willy.arafah@gmail.com abstract economic development depends on the availability of energy, especially in supporting the current government’s development priorities to build the infrastructure sector in indonesia, while the goal of development is to improve the nation’s competitiveness this research aims to investigate the opportunity to reduce fossil energy and switch to renewable energy. one of the efforts to improve long-term national energy security length is through reducing dependence on fossil energy, and the government must take swift action to use renewable energy. the methodology in this research uses internal factor evaluation analysis, external factor evaluation and swot matrix. furthermore, the data used is secondary data in the period 2017–2022 coming from various official sources. the development of renewable energy in the world followed by the technology, more advanced technology used, the cost of investment and renewable energy tariffs will be cheaper, thus will be more competitive with electricity from fossil energy. currently the installed power generation capacity in indonesia is 57 gigawatts, of which 86% still use fossil energy and the remaining is renewable energy. renewable energy in indonesia becomes a very potent alternative, where the energy source depends on the geographical area and the source of energy it produces. the potential of renewable energy in indonesia is very big, indonesia has 40% geothermal potential in the world. keywords: marketing strategy, renewable energy, swot matrix jel classification: a1, a11, o13 1. introduction energy is the power that can be used to perform various processes of activity, including electricity, mechanical energy, and heat. source of energy is a part of natural resources such as oil and gas, coal, water, geothermal, peat, biomass and so on, either directly or indirectly can be utilized as energy. new energy is a form of energy produced by new technologies from both renewable and non-renewable energies, including hydrogen, coal bed methane, coal liquefaction, coal gasification and nuclear hosseini and wahid (2016). renewable energy is a source of energy generated from energy resources that will naturally not be exhausted and can be sustainable if managed properly, among others: geothermal, biofuel, river water flow, solar heat, wind, biomass, biogas, sea waves, and temperature the depth of the sea (kalogirou, 2013). energy diversification is the diversification of supply and utilization of various energy sources in the framework of energy supply optimization. energy conservation is the use of energy efficiency and rationally without reducing the energy usage that is necessary (jaffe and stavins, 1994; lutzenhiser, 1993). a particular alternative energy source is a specific type of energy source substitute for fuel oil. energy elasticity is the ratio or the ratio between the growth rate of energy consumption and the rate of economic growth. the economic price is the cost of production per unit of energy, including the environmental cost plus the marginal cost (hill et al., 2006; pittman et al., 2011). the government continues to encourage the optimization of renewable energy to meet national energy needs in the future because of the high economic level. however, from the potential of renewable energy in indonesia of 400 gigawatts (gw), newly used about 8.8 gw or 2% of the potential energy cannot be separated from human needs at this time, and power plays a vital role in all human life (de groot et al., 2002; nugroho, 2014; prastowo, 2015; nugroho et al., 2017). indonesia is a country facing electricity crisis every year. therefore the need for electricity always increases every year. some alternative energy that can be developed by increasing arafah, et al.: marketing strategy for renewable energy development in indonesia context today international journal of energy economics and policy | vol 8 • issue 5 • 2018182 demands, among others, are biofuel, biomass, geothermal, water, wind, sun, sea waves and sea tides (cherubini, 2010; dincer, 2000). new renewable energy development is quite potential in indonesia. therefore it must be developed continuously, by 2025 indonesia itself will target the development of solar energy as 1000mw through the program of 1000 islands (lipi, 2016). indonesia has great potential in applying renewable energy (ebt). however, the potential utilization of ebt is still very small. until 2017, only about 12 percent of potential ebt in indonesia is used as a source of electrical energy by the state electricity company (pln). according to pln, the potential of ebt in indonesia reaches around 443 gw. the potentials include energy from wind or bayu with a power of 207,898 megawatts (mw), followed by hydro (94,476 mw), solar (60,647 mw), bioenergy (32,654 mw), geothermal (29,554 mw), and sea (17,989 mw). however, the potential utilization of ebt in indonesia until last year is still around 8 gw. other data even call it smaller, only about 6.5 gw. according to geographical position in the ring of fire, indonesia has abundant geothermal potential and can be utilized as the energy source for the power plant. currently, 331 potential points are spread across 30 provinces ranging from sumatra island, java, nusa tenggara, maluku, to sulawesi with reserves of 17,506 mw and 11,073 mw of resources. however, the utilization of geothermal energy for new power plants is 1,698.5 mw or about 10% of the existing reserves thus the opportunities for geothermal energy development are still very open (figure 1). 2. problem description this study is limited by research questions that include: (1). what is the potential of renewable energy in indonesia ? (2). what is the society's need for the latest energy? (3). what is the current renewable energy marketing strategy in indonesia? 3. literature review according to kotler (2015) and hoeffler and keller, (2002), marketing strategy is the logic of marketing where the company hopes to create customer value and achieve a rewarding relationship. the formulation of marketing strategy is based on a thorough analysis of external and internal environmental factor company. the corporate environment changes rapidly at any time giving rise to better opportunities and threats coming from the main competitors as well as from the ever-changing business climate (pettigrew et al., 2001; arafah and nugroho, 2016a; sholihin and harnovinsah 2017). consequences of factor change these external factors also result in changes in internal factors of the company, such as changes to the strengths and weaknesses of the company. strategic marketing is defined as the art and knowledge to formulate, implement, and evaluate cross-functional decisions that enable the organization to achieve its goals. many books are about strategy, the concept of strategy is always directed to the conditions of war, but nowadays more strategy leads to winning the competition in the business world quickly (mcgrath, 2013; hamel et al., 1989; nugroho et al., 2015). strategy are more geared towards how the company can quickly apply the vision and mission that has been created for a certain period of time (schein, 1990; von krogh, 1998; utami and nugroho, 2017). nevertheless according to mintzberg (1973) and crane (2000) strategy is more geared towards realizing a one step enterprise move compared to other competitors. each management function makes a certain contribution at the moment strategizing at different levels. marketing is a function that has the greatest contact with the external environment, whereas the company has only limited control over the external environment (miles et al., 1978). by therefore, marketing plays an important role in development strategy. in the role of strategy, marketing includes every effort to achieve conformity between the company and its environment in order looking for solutions to the problem of determining two basic considerations. first, what business is in the company today and what kind of business which can be entered in the future. second, how the business has been selected in the dimensions, namely the current dimensions and the dimensions of the period will come. marketing mix strategy run successfully in an environment, competent by-product perspective, price, promotion, and distribution to serve the target market (park et al., 1986). in the context of strategy formulation, marketing has two when it comes to relationships that have existed between a company with its environment. while the dimensions to come are is expected to be interwoven and the program of action required for achieving that goal. regarding to kotler (2015) and heinonen (2011) marketing is a social and managerial process undertaken by a person or group to acquire something desired or needed through the creation and exchange of products and values. furthermore, the american marketing association defines marketing as an organizational function and planning processes to create, communicate and deliver value to customers and to manage customer relationships in ways that benefit the organization and its stakeholders, as well as the implementation of conceptions, pricing, promotion and distribution of ideas, goods and services to create a satisfactory exchange of individual goals and organizations (grönroos, 1997; figure 1: mix of energy consumption based on user and type of energy year 2017–2022 source: secondary data, 2017 international journal of energy economics and policy | vol 8 • issue 5 • 2018 183 arafah, et al.: marketing strategy for renewable energy development in indonesia context today slater et al., 1995). the concept of marketing mix according to (khan, 2014) is: “marketing mix is the set of marketing tools that the firm uses to pursue its marketing objectives in the target market.” regarding the above definition explained that marketing mix/mix marketing is a combination and four variables that are the core of the company’s marketing system and can be controlled by the company as adequately as the possible marketing strategy is essential for companies where marketing strategy is a way to achieve the goals of a company. therefore, we can conclude strategy is a series of large design that describes how a company must operate to achieve its goals (casadesus-masanell and ricart, 2010). marketing strategy is a marketing mindset that will be used to achieve marketing objectives. marketing strategy contains specific strategies for target markets, positioning, marketing mix and marketing expenditure. marketing strategy is a fundamental tool that is planned to achieve the company by developing sustainable competitive advantage through entering markets and marketing programs used to serve that target market (bharadwaj et al., 1993). in the context of utilization of renewable energy some policies that support renewable energy apart from government regulation presidential decree (pp). 79 years 2014 has been issued a lot and become the subject, among others: (1). act (uu) no. 30/2007 on energy; (2). uu no. 21/2014 on geothermal; (3). uu no. 30/2009 on electricity; (4). presidential regulation no. 4 of 2016 on accelerating the development of electricity table 1: matriks ife and efe no internal factors (strength) weight rank score 1. the price of renewable energy is very competitive against fossil energy 0.08 4 0.32 2. renewable energy does not generate significant pollution for the environment 0.07 3 0.21 3. research in the field of renewable energy is growing rapidly 0.05 4 0.2 4. energy companies in indonesia are committed to developing renewable energy 0.06 2 0.12 5. renewable energy is becoming the choice of people who understand the environment 0.03 4 0.12 total 0.29 0.97 sources: pimary data, 2018. ife: internal factor evaluation, efe: external factor evaluation table 2: matriks ife and efe no internal factors (weakness) number rank score 1 investment costs are very large in renewable energy and very less attractive by investors 0.07 3 0.21 2. renewable energy areas in indonesia are usually located in remote areas 0.06 4 0.24 3. limitations in renewable energy infrastructure 0.04 4 0.16 4. very few experts in renewable energy in indonesia at this time 0.06 2 0.12 5. the lack of regularity to utilize renewable energy for an area in the framework of energy self-sufficiency 0.03 4 0.12 total 0.26 0.85 sources: pimary data, 2018. ife: internal factor evaluation, efe: external factor evaluation table 3: matriks ife and efe no external factors (opportunity) number rank score 1. the potential of renewable energy development in indonesia is still very large and has not been optimally utilized 0.09 3 0.27 2. in the future the energy prioritized, there is renewable energy 0.07 5 0.35 3. energy consumption in the future is increasing, high economic growth in indonesia is in need of a lot of energy 0.05 5 0.25 4. government policy is directed to develop renewable energy 0.04 3 0.12 5. the government invites domestic and foreign investment to invest in renewable energy and is subsidized by the government 0.06 6 0.36 total 0.31 1.35 sources: pimary data, 2018. ife: internal factor evaluation, efe: external factor evaluation table 4: matriks ife and efe no external factors (threats) number rank score 1. indonesia’s oil reserves are getting smaller and fewer 0.09 3 0.27 2. indonesian industry uses fossil energy and it is very difficult to change it 0.07 4 0.28 3. the industry still chooses fossil energy 0.08 4 0.32 4. the government should invite local companies to grow forward 0.06 5 0.3 5. local companies engaged in the energy sector are very difficult to invest in developing renewable energy 0.03 4 0.12 total 0.33 1.29 sources: pimary data, 2018. ife: internal factor evaluation, efe: external factor evaluation table 5: matriks ife and efe score internal value external value strategic planning s > w (+) o > t (+) aggressive s < w (−) o ≥ t (+) stand/stick out s > w (+) o ≤ t −) diversification s > w (−) o < t (−) conservative 0.97 > 0.85 1.35 > 1.29 sources: pimary data, 2018. ife: internal factor evaluation, efe: external factor evaluation arafah, et al.: marketing strategy for renewable energy development in indonesia context today international journal of energy economics and policy | vol 8 • issue 5 • 2018184 infrastructure; (5). minister of energy and mineral resources regulation no. 19 of 2015 on the purchase of hydroelectric power up to 10 mw capacity by pt. state electricity company (pln). the direction of energy development strategy and strategy according to the national development agenda-national medium term development plan (rpjmn) (2015–2019) are: (1). increasing the role of renewable energy in the energy mix: (i) appropriate incentives and prices to encourage investment; (ii) utilization of new renewable energy and bioenergy for power generation and (iii) utilization of biofuels. (2). improving accessibility: providing electricity to remote islands and villages including fishing villages where possible with solar energy and other renewable energy. (3). improving efficiency in energy use: (i) energy-saving campaigns, (ii) development of incentives and financing mechanisms for financing energy efficiency efforts; (iii) improving the technical capabilities of managers and energy auditors; (iv) enhancing the role and capacity of energy service companies; (v) developing the use of energy-efficient systems and technologies in industry; (vi) optimizing energy conservation policy instruments (pp no. 70/2009 on energy conservation). (4). utilizing the potential of water resources for hydropower, including: (i) incentives to accelerate hydropower development, i.e., the dispensation of forest area utilization for hydropower development, regulation of electricity selling price and land provision, (ii) simplification of rules and licensing requirements document. increased consumption of electrical energy each year is estimated to continue to grow. general electric power supply plan (ruptl) of pt pln (persero) 2010–2019 states, the electricity demand is estimated at 55,000 mw. so the average increase in electricity demand per year is 5500 mw. of the total power of 32,000 mw (57%) built by pln, while the remaining 23,500 mw will be fulfilled by private power developers (juwito et al., 2015). 4. methodology type of research conducted is exploratory research, is research conducted by assessing a data with the aim to produce an invention related to the data being studied. the formulation of choice of the development strategy of bio-based renewable energy is done by using swot analysis series. the process is done in three stages, namely data collection (input stage), analysis (matching stage), and decision making (decision stage). at the data collection stage, an internal and external environment factor evaluation is evaluated using internal factor evaluation (ife) and external factor evaluation (efe) matrices. in the analysis phase, strategic positioning is performed using ife and efe score, swot analysis diagram, and swot matrix. in the decision-making phase, the formation of development programs based on swot analysis results. 4. results the potential of renewable energy in indonesia today the indonesian state has geographical advantages that can be utilized to build alternative energy, in addition to fossil energy, such as geothermal, water, wind, solar, ocean waves, tides, biofuels. but unfortunately until now the government has not managed these resources optimally created at this time. if all these alternative energy sources we use then the cost of household electricity will be cheaper, the industry becomes competitive and transportation will also be more affordable to see the number of electric vehicles that are created at this time (nugroho, 2013). the society's need for the latest energy fossil energy in indonesia, especially petroleum is very limited, so the majority of indonesian consumption still rely on imports, which must be purchased with dollars. in addition, the price of petroleum is also unstable greatly affecting the world’s political conditions. so if the current price of electricity in indonesia rp1.059 per kwh–rp. 1.506 per kwh then the possibility of 10 or 15 years ahead can be rp. 2.020/kwh–rp. 2.550/kwh. also, when the current price of solar rp 6.950, and premium rp. 7.450 at the time of world oil price of world oil price $ 37.69/barrel, how when world oil price increase up to $ 120 or $ 150 per barrel. it must be remembered that petroleum in this world is very limited, and economic law always depends on supply and demand. the results of study, as follows: (1). geothermal energy, geothermal energy or geothermal is a renewable energy source of thermal energy (heat) generated and stored in the earth. geothermal power benefits, hardly inferring pollution or greenhouse gas emissions. this power is also not noisy and reliable. geothermal power station generates about 90% electricity, compared to 6575% of fossil fuel power plants. unfortunately, even though indonesia has abundant geothermal reserves of up to 40% of the world’s geothermal reserves, this proven clean, renewable energy source is not being utilized on a large scale. (2). water energy is one of the most common alternative fossil fuels. this energy source is obtained by utilizing the potential energy and kinetic energy possessed by water. currently, about 20% of world electricity consumption is met from hydropower (hydropower). (3). wind energy, wind or bayu energy is a source of renewable energy generated by wind. windmills are used to capture wind energy and convert it into kinetic or electric energy. solar energy/solar energy. (4). solar or solar energy or known as the solar system is a renewable energy sourced from radiation of light and heat emitted by the sun. (5). sea wave energy, sea wave energy or wave is renewable energy that comes from the ups and downs of sea water waves. indonesia as a maritime country located between two oceans has high potential to utilize the energy source of this ocean wave. but unfortunately this alternative energy source is still in development stage in indonesia. (6). tidal energy, tide energy is a renewable energy source of tidal water. there are two types of tidal energy sources, the first is the high difference in low seawater during high tide and low tide (7). energy biofuels are renewable energy sources of fuel (both solid, liquid, and gas) produced from organic materials. sources of biofuels are plants that have high sugar content (such as sorghum and sugar cane) and plants that have high vegetable oil content. the current renewable energy marketing strategy in indonesia indonesia has great potential and opportunities to use renewable energy. based on the ife and efe matrix, indonesia has the following internal potential (table 1): international journal of energy economics and policy | vol 8 • issue 5 • 2018 185 arafah, et al.: marketing strategy for renewable energy development in indonesia context today • the price of renewable energy is very competitive against fossil energy, • renewable energy does not generate significant pollution for the environment, • research in the field of renewable energy is growing rapidly, • energy companies in indonesia are committed to developing renewable energy, • renewable energy is becoming the choice of people who understand the environment. furthermore, there are weaknesses in being able to use renewable energy in indonesia context (table 2) as follow: • investment costs are enormous in renewable energy and very less attractive by investors, • renewable energy areas in indonesia are usually located in remote areas, • limitations in renewable energy infrastructure, • very few experts in renewable energy in indonesia at this time, • the lack of regularity to utilize renewable energy for an area in the framework of energy self-sufficiency. however, there are external opportunity factors that support the adoption of renewable energy in indonesia (table 3), as follows: • the potential for renewable energy development in indonesia is still huge and has not been optimally utilized, • in the future the energy prioritized, there is renewable energy, • energy consumption in the future is increasing, high economic growth in indonesia is in need of a lot of energy • government policy is directed to develop renewable energy, • the government invites domestic and foreign investors to invest in renewable energy and is subsidized by the government. also, there are external threat factors that can be considered in developing renewable energy in indonesia (table 4): • indonesia's oil reserves are getting smaller and fewer, • indonesian industry uses fossil energy and it is very difficult to change it, • the industry still chooses fossil energy, • the government should invite local companies to grow forward, • local companies engaged in the energy sector are very difficult to invest in developing renewable energy. based on ife and efe matrix analysis where the strong (s) 0.29 and weakness (w) values are 0.26, then s> w. besides that, opportunity (o) has a value of 0.31 while weakness (w) is 0, 33. therefore the marketing strategy for renewable energy in indonesia is in the category of diversification (table 5). there are still many challenges to be able to change the habits of indonesian people in using fossil energy into renewable energy (astra, 2010; arafah & nugroho, 2016b). therefore, the government, community leaders, financial institutions and other relevant parties must work hand in hand to increase knowledge and understanding of the importance of this renewable energy. by using renewable energy, it can reduce pollution and improve the quality of life of the community. 6. conclusions the transition of energy will never happen without a strong desire of the government and the legislature, as it is needed by government and legislative policies and regulations to encourage alternative energy development by both government and private investors, such as: (1). increase the participation and funding from the indonesia institute of science and research and technology ministries to examine the locations of alternative energy potentials in indonesia and the technologies that best suit the geographical conditions in indonesia. (2). establish regulations and provide tax subsidies on alternative energy power plants. (3). more easier development permits and operational of alternative energy generation than fossil energy generation. (4). make the regulation easier to enter the vehicle lsitrik than conventional vehicles, so that will increase demand for electrical energy that will automatically trigger investors to invest investment in indonesia. (5). setting the purchase price of government or pln for alternative energy is more expensive or at least equal to the price of fossil energy, thus increasing the interest of investors to participate. (6). development of electric vehicle filling stations at pertamina filling stations. in addition to the land already available, also so as not to harm one of the largest state-owned enterprises in indonesia. 7. acknowledgment this research is dedicated to study in the field of renewable energy in indonesia in terms of marketing strategy and as research on a master program of trisakti university management for accreditation of study programmes and complementary research to gain an academic level of professor. references agenda pembangunan nasional (rpjmn). (2015-2019), lampiran peraturan presiden ri nomor 2 tahun 2015 tentang rpjmn. available from: https://www.kemenkopmk.go.id/sites/default/files/ produkhukum/perpres%20nomor%202%20tahun%202015.pdf. arafah, w., nugroho, l. (2016), ethics commitment in microfinance and shariah microfinance ınstitution. international journal, 7, 1-11. arafah, w., nugroho, l. (2016b), maqhashid sharia in clean water financing business model at islamic bank. international journal of business and management invention, 5(2), 22-32. bharadwaj, s.g., varadarajan, p.r., fahy, j. (1993), sustainable competitive advantage in service industries: a conceptual model and research propositions. the journal of marketing, 57, 83-99. casadesus-masanell, r., ricart, j.e. (2010), from strategy to business models and onto tactics. long range planning, 43(2-3), 195-215. cherubini, f. (2010), the biorefinery concept: psing biomass instead of oil for producing energy and chemicals. energy conversion and management, 51(7), 1412-1421. crane, a. (2000), facing the backlash: green marketing and strategic reorientation in the 1990s. journal of strategic marketing, 8(3), 277-296. de groot, r.s., wilson, m.a., boumans, r.m. (2002), a typology for the classification, description and valuation of ecosystem functions, goods and services. ecological economics, 41(3), 393-408. dincer, i. (2000), renewable energy and sustainable development: arafah, et al.: marketing strategy for renewable energy development in indonesia context today international journal of energy economics and policy | vol 8 • issue 5 • 2018186 organizational strategy, structure, and process. academy of management review, 3(3), 546-562. mintzberg, h. (1973), strategy-making in three modes. california management review, 16(2), 44-53. nugroho, l. (2013), maqhasid sharia implementation in microfinance bank syariah mandiri case study on microfinance provision for water supply to poor households in kudus regency (indonesia), proceedings in the 1st international conference on islamic wealth management. nugroho, l. (2014), central bank regulation and its impact on green microfinance: (master thesis), universite libre de bruxelles. nugroho, a., harwani, y., dewita, a., sihite, j. (2015), is it traditional or contemporary marketing strategy? a textual cluster analysis@ mercu buana_reg. mediterranean journal of social sciences, 6(5s5), 26. nugroho, l., utami, w., akbar, t., arafah, w. (2017), the challenges of microfinance institutions in empowering micro and small entrepreneur to implementating green activity. international journal of energy economics and policy, 7(3), 66-73. park, c.w., jaworski, b.j., maclnnis, d.j. (1986), strategic brand conceptimage management. the journal of marketing, 1986, 135-145. pettigrew, a.m., woodman, r.w., cameron, k.s. (2001), studying organizational change and development: challenges for future research. academy of management journal, 44(4), 697-713. pittman, j.k., dean, a.p., osundeko, o. (2011), the potential of sustainable algal biofuel production using wastewater resources. bioresource technology, 102(1), 17-25. prastowo, l.n. (2015), islamics principle versus green microfinance. european journal of islamic finance, 3, 1-19. schein, e.h. (1990), organizational culture: what it is and how to change it. in: human resource management in i̇nternational firms. london: palgrave macmillan. p56-82. sholihin, m.r., harnovinsah, h. (2017), analisis faktor-faktor yang mempengaruhi pengungkapan corporate social responsibility (studi empiris perusahaan manufaktur yang terdaftar di bursa efek indonesia). profita, 10(2), 268-292. slater, s.f., mohr, j.j., sengupta, s. (1995), market orientation. new york: wiley international encyclopedia of marketing. utami, w., nugroho, l. (2017), fundamental versus technical analysis of investment: case study of investors decision in indonesia stock exchange. the journal of internet banking and commerce, 22, 1-18. von krogh, g. (1998), care in knowledge creation. california management review, 40(3), 133-153. a crucial review. renewable and sustainable energy reviews, 4(2), 157-175. grönroos, c. (1997), keynote paper from marketing mix to relationship marketing-towards a paradigm shift in marketing. management decision, 35(4), 322-339. hamel, g., doz, y.l., prahalad, c.k. (1989), collaborate with your competitors and win. harvard business review, 67(1), 133-139. heinonen, k. (2011), consumer activity in social media: managerial approaches to consumers’ social media behavior. journal of consumer behaviour, 10(6), 356-364. hill, j., nelson, e., tilman, d., polasky, s., tiffany, d. (2006), environmental, economic, and energetic costs and benefits of biodiesel and ethanol biofuels. proceedings of the national academy of sciences, 103(30), 11206-11210. hoeffler, s., keller, k.l. (2002), building brand equity through corporate societal marketing. journal of public policy and marketing, 21(1), 78-89. hosseini, s.e., wahid, m.a. (2016), hydrogen production from renewable and sustainable energy resources: promising green energy carrier for clean development. renewable and sustainable energy reviews, 57, 850-866. jaffe, a.b., stavins, r.n. (1994), the energy paradox and the diffusion of conservation technology. resource and energy economics, 16(2), 91-122. juwito, a.f., pramonohadi, s., haryono, t. (2015), optimalisasi energi terbarukan pada pembangkit tenaga listrik dalam menghadapi desa mandiri energi di margajaya. jurnal semesta teknika, 15(1), 22-34. kalogirou, s.a. (2013), solar energy engineering: processes and systems. burlington (m.a.): academic press. khan, m.t. (2014), the concept of’marketing mix’and its elements (a conceptual review paper). international journal of i̇nformation, business and management, 6(2), 95. kotler, p. (2015), framework for marketing management. new delhi: pearson education india. lipi. (2016), available from: http://www.lipi.go.id/lipimedia/potensienergi-terbarukan-indonesia-besar/15671. lutzenhiser, l. (1993), social and behavioral aspects of energy use. annual review of energy and the environment, 18(1), 247-289. mcgrath, r.g. (2013), the end of competitive advantage: how to keep your strategy moving as fast as your business. boston: harvard business review press. miles, r.e., snow, c.c., meyer, a.d., coleman, h.j. jr. (1978), . international journal of energy economics and policy | vol 7 • issue 5 • 2017 171 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2017, 7(5), 171-177. economic growth and sustainable development: evidence from central and eastern europe attila jambor1*, nuno carlos leitao2 1department of agricultural economics and rural development, corvinus university of budapest, budapest, hungary, 2polytechnic institute of santarém, esgts, santarém, portugal and cefage-ue, évora university, évora, portugal. *email: attila.jambor@uni-corvinus.hu abstract there has been a large amount of literature dedicated to the determinants of economic growth recently. however, the majority of the literature so far has been concentrating on single factors and countries as examples. this research considers the effects of carbon dioxide emissions, tourism arrivals, foreign direct investments (fdis), trade and domestic support on economic growth in central and eastern europe. the paper uses panel data econometrics between 1995 and 2014 to perform its calculations. results suggest a positive relationship between tourism arrivals, fdi, trade, domestic support and economic growth, while co2 emissions were found to be negatively related to economic growth in the region. policy and decision makers in the region might find our results useful when thinking about drivers of economic growth. keywords: tourism demand, foreign direct investment, carbon dioxide emissions, economic growth, panel data jel classifications: o13, f64, z32 1. introduction there has been a large amount of literature dedicated to the determinants of economic growth recently. especially after the economic crisis of 2008, economists have been intensively searching for factors contributing to economic growth worldwide. given the special problems of developing countries in this regard, this issue has largely been attracting scientists from many different fields. the endogenous theory of growth (romer, 1986; lucas, 1988; grossman and helpman, 1991; rebelo, 1991; aghion and howitt, 1992) introduces the assumptions of monopolistic competition to explain economic growth. in this context, it should be noted that in the 1980s and 1990s, some studies have emerged that introduce other concepts to growth theory. rodrik (1998), alesina et al. (1994), dollar (1992), frankel and romer (1996) explain new explanatory factors of growth. however, the literature seems to have only concentrated on single factors and countries as examples. this paper aims to establish the link between carbon dioxide emissions, tourism arrivals, foreign direct investment (fdi), trade openness, domestic credits and economic growth for central eastern european countries. consequently, the paper aims to contribute to the existing empirical literature in two ways. first, the impacts of a set of different variables is investigated to economic growth instead of single indicators. second, a region is analysed instead of single countries. the paper is structured as follows. a literature review section is presented after the introduction, followed by hypotheses and econometric specifications. the fourth section demonstrates changes in the indices analyzed in the cee region, followed by the presentation of empirical results. the last section concludes. 2. literature review a vast amount of literature is dedicated to the analysis of the determinants of economic growth. one strand of the literature analyses the impacts of carbon dioxide emissions on economic jambor and leitao: economic growth and sustainable development: evidence from central and eastern europe international journal of energy economics and policy | vol 7 • issue 5 • 2017172 growth. the investigation of anderson and karpestam (2013), for instance, show that economic growth is not responsible for environmental pollution. in this context, the turkish experience was investigated by bozkurt and akan (2014), demonstrating that co2 had a negative relationship with economic growth. tiwari (2011) also found a negative relationship between co2 and economic growth by using the impulse response function and the variance decomposition indicator. oil consumption, carbon dioxide emissions and growth was investigated by lim et al. (2014). considering the philippines experience, the study demonstrates a negative correlation between co2 and economic growth in long rung for 1965-2012. results presented by ghosh et al. (2014) also showed a negative correlation between co2 and economic growth to bangladesh. the empirical study of saidi and hammami (2014) considered the relationship between energy consumption, carbon dioxide emissions and economic growth. the authors used a panel data for the period 1990-2012. by applying a gmm model, their econometric results demonstrated that carbon dioxide emissions were negatively correlated to economic growth. the research of kais and mbarek (2017) also showed a negative effect of co2 on economic growth in algeria and tunisia. another strand of the literature analyses tourism demand on economic growth, mainly showing a positive relationship between the two variables. the empirical studies of sequeira and nunes (2008) and leitão (2011) utilized fixed effects and gmm-system models to evaluate the relationship between tourism demand and economic growth to portugal. these studies show that tourism arrivals promote economic growth, also underpinned by proença and soukiazis (2008). the empirical study of ozturk and acaravci (2009) also considered the relationship between tourism and economic growth for turkey and found that there was no correlation. the link between tourism arrivals and economic growth in spain and italy were also analyzed by cortes-jimenez (2008), suggesting that tourism arrivals highly contributed to economic growth. the relationship between economic growth and tourism demand in croatia was examined by svilokos et al. (2014). considering a time series analysis for 1972-2013, the authors demonstrate that economic crises affect the behavior of international tourists, and the decrease of tourism demand affect economic growth. the empirical study of nonthapot (2016) also considers the relationship between tourism and economic growth for cambodia, laos, myanmar, thailand and vietnam by applying panel cointegration. the study shows that the variables of tourism arrivals and per capita income are co-integrated. panahi et al. (2015) also investigates the impact of tourism on economic growth in turkey in 1970-2011, showing that gross fixed capital formation, human capital and tourism arrivals have a positive and significant effect on economic growth. another significant part of the economic growth literature is dedicated to the relationship between fdi and economic growth. the research of kai and hamori (2009), damijan and rojec (2007), campos and kinoshita (2002), badinger and tondl (2002), mileva (2008) and onaran (2007) show that fdi positively influences economic growth. leitão and rasekhi (2013) considered the impact of fdi on economic growth for portugal in 1995-2008. their fixed effects estimator model demonstrates that fdi and trade openness have a positive, while inflation and the taxes have a negative effect on economic growth. belloumi (2014) analysed the relationship between trade, fdi and economic growth in tunisia by using a cointegration model from 1970 to 2008 and found no significant causality among the variables. popescu (2014) analysed fdi and economic growth in central and eastern european countries and found strongly positive relationship between the two notions. mehic et al. (2013) also investigated the impact of fdi on economic growth in southeast europe and concluded that investments significantly fostered economic growth in the region between 1998 and 2007. the relationship between trade openness and economic growth literature is also investigated by a large amount of economic literature. the association between trade and economic growth is one of the most important issues of economic development that has been widely debated between developed and developing countries. the empirical works of grossman and helpman (1991), rebelo (1991), dollar (1992), frankel and romer (1996), sequeira and nunes (2008) found a positive relationship with statistical significance between international trade (degree of openness) and growth. in this context, economic growth in australia was investigated by thorpe and leitão (2014) in 1986-2007. their econometric results suggest that government spending, change of trade, economic and political globalization have a positive effect on australian economic growth. chaido et al. (2004) analysed the correlation between exports, investments and economic growth in estonia, latvia and lithuania for the period 1992-2000. the authors applied the unit root test, co-integration methodology and vec model. the vector of economic growth was proved to be statistically significant to estonia and latvia, while the lagged variable of exports presented a positive effect on a long run. dritsakis and stamatiou (2016) also analysed the impact of trade on economic growth in central and eastern europe and by applying panel cointegration and causality analysis for the period of 1995-2013, they found positive relationship between the two variables both in the short and in the long run. last but not least, the impact of domestic credit on economic growth also has a considerable amount of literature. in fact, bank credit may encourage growth in an economy as argued by hassan et al. (2011). bank credit and economic growth was investigated by leitão (2012) for the european union in 1990-2010, showing that private credit and inflation discourage, while public savings promote economic growth. the effect of the banking sector on economic growth for central and south eastern european countries was investigated by petkovski and kjosevski (2014) for the period 1991-2011, showing that private credit and interest margin had a negative impact on economic growth. however, empirical studies of la porta et al. (1998), levine et al. (2000), hassan et al. (2011) and leitão (2010) supported the idea that domestic credit had a positive relationship with economic growth. law and singh (2014) was also in search for new evidence on the relationship between finance and economic growth by using a sample of 87 developed and developing countries and concluded that a threshold effect existed in this context. jambor and leitao: economic growth and sustainable development: evidence from central and eastern europe international journal of energy economics and policy | vol 7 • issue 5 • 2017 173 3. hypotheses and econometric specifications based on the literature above, the following hypotheses are tested for our sample. hypothesis 1: sustainable development fosters economic growth. this hypothesis is directly coming from the vast amount of research, partly presented above, on the effects of co2 emissions on economic growth. a negative relationship is expected here (anderson and karpestam, 2013; bozkurt and akan, 2014, tiwari, 2011, lim et al., 2014). co2 emissions is measured in kilotonnes and data is coming from the world bank development indicators (wdi) database. hypothesis 2: tourism encourages economic growth. based on the findings of leitão and shahbaz (2016), tang and tan (2015), nonthapot (2016), panahi et al. (2015) and svilokos et al. (2014), tourism is expected to be positively related to economic growth. tourism is proxied by the number of inbound tourists (number of arrivals), also downloaded from the wdi database. hypothesis 3: fdi has a positive effect on economic growth. based on the studies of belloumi (2014), popescu (2014), mehic et al. (2013), yazdi et al. (2017), anwar and nguyen (2010), sakyi et al. (2015) and leitão and rasekhi (2013), fdi is expected to be positively related to economic growth. fdi is measured as net inflows in billions of current usd, accessible from the wdi database. hypothesis 4: trade encourages the economic growth. on the basis of a vast amount of seminal works on the topic as well as studies presented above like thorpe and leitão (2014), chaido et al. (2004), dollar (1992), frankel and romer (1996) and sequeira and nunes (2008), a positive relationship is expected here. trade is measured as the sum of exports and imports of goods and services as a share of gross domestic product. data is coming from the wdi database. hypothesis 5: domestic credit drives the economic growth. la porta et al. (1998), levine et al. (2000), hassan et al. (2011), leitão (2010), ryan et al. (2011), cavenaile and sougne (2012), petkovski and kjosevski (2014) and law and singh (2014) consider that there is a positive relationship between domestic credit and economic growth. domestic credit provided by the financial sector is measured as the share of gross domestic product (gdp), coming from wdi database. based on the literature, the following equation is estimated to our sample: lngrowth=β0+β1lnco2+β2lntourism+β3lnfdi+β4lntrad e+β5lncredit+uit all variables are expressed in logarithm forms. the constant term is β0. the coefficients for each variable take βx. the error term is expressed by uit. the sample covers the period 1995-2014 for ten cee countries (bulgaria, czech republic, estonia, hungary, latvia, lithuania, poland, romania, slovakia and slovenia). the dependent variable is growth (real gdp per capita). the data for the dependent variable is collected from world bank wdi database. the explanatory variables introduced in the equation are carbon dioxide emissions (co2), tourism (tourism demand), fdi, trade openness (trade) and domestic credit (credit) (table 1). 4. descriptive statistcs this section provides an overview on the general distribution of the variables used in the paper. first of all, central and eastern european countries show a high diversity in their annual gdp per capita growth rates from 1995 to 2014 (table 2). the highest gdp per capita growth can be observed for the baltic countries (lithuania, latvia and estonia, respectively), while the lowest can be seen for slovenia, hungary and the czech republic. without going very much into details, these trends can be partly explained by wise (fire brigade) policy making and initially different income levels. this was exactly verified by jambor and babu (2016) in their recent study analysing the impacts of eu accession on cee agriculture. as to co2 emissions in the region, poland seems to have been the highest polluter in quantities in the period analysed, while latvia has turned out to be the lowest (figure 1). the extremely large values of co2 emissions of poland (more than 5-6 times exceeding others) is probably due to the size as well as the economic structure of the country. international tourism arrivals were the biggest in poland and hungary in 1995-2014, exceeding more the 15 million and 10 million tourists, respectively (table 3). interestingly, however, there has been a significant 25% and 15% decrease, respectively, from 1995-1999 to 2010-2014 in the tourism arrivals in these countries, while the highest increase in the same index can be seen in estonia, latvia and slovenia. table 1: description of independent variables variables definition source expected signs co2 carbon dioxide emissions world bank tourism number of inbounds tourists world bank + fdi net inflows of foreign direct investment in billions of current usd world bank + trade sum of exports and imports of goods and services world bank + credit domestic credit provided by the financial sector is measured as the share of gdp world bank + gdp: gross domestic product jambor and leitao: economic growth and sustainable development: evidence from central and eastern europe international journal of energy economics and policy | vol 7 • issue 5 • 2017174 as to fdis, hungary, poland and romania experienced the biggest outflows, suggesting that residents of these countries have been pretty active in investing to external economies, mainly in the period of the economic crisis. at the other end, slovenia, latvia and lithuania were the least active in this regard (figure 2). the total trade of central and eastern european countries also shows a diverse picture (table 4). on the one hand, some countries like the czech republic, hungary, lithuania and poland could significantly increase the share of trade in gdp, implying increasing international trade activities. on the other hand, other countries like estonia, romania or bulgaria could hardly increase the share of trade in gdp. last but not least, domestic credit provided by the financial sector in the region has generally been increasing during the previous 20 years, though to a different extent (figure 3). latvia, lithuania and estonia could increase the share of domestic credit provided by the financial sector by five, four and three times, respectively, from 1995-1999 to 2010-2014. however, hungary and slovakia lacked behind in this regard, suggesting stable trends of domestic credit provision in the period analysed. 5. empirical results before running the model, descriptive statistics and correlations are given for the variables (tables 5 and 6). results suggest relatively low standard deviations. table 6 displays the correlation between the variables used in the model. carbon dioxide emissions (lnco2) is negatively correlated to economic growth, while trade openness (lntrade) is also negatively related to fdi (lnfdi). the credit bank (lncredit) has a positive relationship with carbon dioxide emissions. table 2: the annual growth of gdp per capita in central and eastern europe, 1995-2014, percentage country 1995-1999 2000-2004 2005-2009 2010-2014 bulgaria 0.81 6.52 5.56 1.45 czech republic 2.29 3.68 2.86 0.99 estonia 6.16 7.61 1.89 3.99 hungary 2.66 4.53 0.77 1.71 latvia 6.14 8.33 4.03 3.75 lithuania 5.72 7.76 4.17 5.20 poland 5.68 3.57 4.77 3.06 romania 0.97 6.40 5.19 1.96 slovakia 4.30 4.04 5.19 2.59 slovenia 4.39 3.48 2.00 0.03 source: own composition based on wdi (2017) data. wdi: world bank development indicators, gdp: gross domestic product table 3: international tourism in central and eastern europe, 1995-2014, number of arrivals country 1995-1999 2000-2004 2005-2009 2010-2014 bulgaria 2876000 3616400 5333000 6625000 czech 8344000 9306800 9737600 estonia 740000 1422800 1979000 2714400 hungary 12212000 9149600 10575400 latvia 571800 799600 1462200 1536000 lithuania 1066400 1414600 1723600 1851400 poland 18975000 14878000 14139000 14492000 romania 5170800 5438200 7207000 7901400 slovakia 5689500 6394600 5870333 slovenia 879800 1296600 1741000 2146400 source: own composition based on wdi (2017) data. wdi: world bank development indicators figure 3: domestic credit provided by financial sector in central and eastern europe, 1995-2014, % of gross domestic product source: own composition based on wdi (2017) data figure 1: co2 emissions in central and eastern europe, 1995-2014, thousand kt source: own composition based on wdi (2017) data figure 2: foreign direct investment, net inflows in current billion us$ in central and eastern europe, 1995-2014 source: own composition based on wdi (2017) data jambor and leitao: economic growth and sustainable development: evidence from central and eastern europe international journal of energy economics and policy | vol 7 • issue 5 • 2017 175 the fixed effects estimator is presented in table 7. the performance of the model is very satisfactory (adjusted r2 = 0.83). the coefficients obtained are generally supported by the literature. the variable of co2 has a negative impact on economic growth, such as the empirical studies of ghoshi et al. (2014), saidi and hamman (2015), and kais and mbarek (2017). this result suggests sustainable development. the variable of tourism demand (lntourism) presents a positive effect on economic growth. the empirical studies of sequeira and nunes (2008), leitão (2011), tang and tan (2015), nonthapot (2016), leitão and shahbaz (2016) also found a positive correlation between tourism arrivals and economic growth. according to this result, we can conclude that tourism demand promotes economic growth in central and eastern europe. the variable of fdi (lnfdi) is positively related to economic growth in line with the empirical studies of yazdi et al. (2017), anwar and nguyen (2010), sakyi et al. (2015) and leitão and rasekhi (2013). according to the empirical works of helpman and krugman (1985), krugman, (1997), romer (1986), leitão (2012), and thorpe and leitão (2014), trade openness (lntrade) induces economic growth. la porta et al. (1998), levine et al. (2000), hassan et al. (2011), leitão (2010) found a positive correlation between domestic credit and growth. in line with their results, we also found the coefficient of credit bank (lncredit) to be positively related to economic growth. 6. conclusions this paper analysed the impact of carbon dioxide emissions, tourism, fdi, trade openness and domestic credit on economic growth in central and eastern europe. our results confirm that economic growth in the region can significantly be explained by these variables. the econometric regression confirms these countries developed capacities to specialize in certain regional clusters, and these are associated with the economies of scale (fujita, 1988; henderson, 1974). descriptive statistics suggest a huge diversity and differently changing patterns of the determinants of economics growth in the region. as to our model runs, results suggest a positive relationship between tourism arrivals, fdi, trade, domestic support and economic growth, while co2 emissions were found to be negatively related to economic growth in the region in line with previous findings. policy and decision makers in the region might find our results useful when thinking about drivers of economic growth. research table 4: trade of goods and services measured as a share of gross domestic product in central and eastern europe, 1995-2014 country 1995-1999 2000-2004 2005-2009 2010-2014 bulgaria 93 81 110 95 czech republic 85 100 124 113 estonia 147 126 133 130 hungary 96 125 148 133 latvia 85 86 95 97 lithuania 89 95 116 124 poland 50 64 77 71 romania 58 75 71 63 slovakia 110 125 156 138 slovenia 95 105 126 111 source: own composition based on wdi (2017) data. wdi: world bank development indicators table 5: descriptive statistics of the variables variable observations mean±sd min max lngrowth 200 8.93±0.75 7.10 10.22 lnco2 190 10.59±1.09 8.76 12.78 lntourism 173 15.05±1.00 13.14 16.79 lnfdi 194 21.24±1.46 16.71 25.04 lntrade 200 4.65±0.31 3.78 5.21 lncredit 198 3.76±0.67 −1.47 4.67 source: own composition based on wdi (2017) data. wdi: world bank development indicators, sd: standard deviation table 6: correlations among the model variables variable lngrowth lnco2 lntourism lnfdi lntrade lncredit lngrowth 1.00 lnco2 −0.08 1.00 lntourism 0.17 0.91 1.00 lnfdi 0.34 0.65 0.79 1.00 lntrade 0.60 −0.46 −0.23 −0.01 1.00 lncredit 0.60 0.03 0.25 0.29 0.42 1.00 source: own composition based on wdi (2017) data table 7: determinants of economic growth in central and eastern europe with fixed effects estimator variables coefficient standard error t p>t 95% confidence interval lnco2 −0.8466*** 0.2190 −3.8700 0.0000 −1.2795 −0.4136 lntourism 0.6818*** 0.0865 7.8800 0.0000 0.5108 0.8529 lnfdi 0.1650*** 0.0248 6.6500 0.0000 0.1160 0.2140 lntrade 1.1543*** 0.1427 8.0900 0.0000 0.8722 1.4363 lncredit 0.1623*** 0.0380 4.2700 0.0000 0.0871 0.2374 constant −1.8671 2.6406 −0.7100 0.4810 −7.0868 3.3526 adjusted r2 0.83 observations 158 ***statistically significant at 1%. source: own composition based on wdi (2017) data jambor and leitao: economic growth and sustainable development: evidence from central and eastern europe international journal of energy economics and policy | vol 7 • issue 5 • 2017176 might want to include more variables or focus on different regions in the future to obtain a better picture on the global level. in this context, future research might also assess economic growth by taking into account other ecological variables such as renewable energies, energy consumption and the assumptions of kuznets environmental curve in order to evaluate the status of sustainable development in the cee region. 7. acknowledgements this paper was supported by the national research, development and innovation office grant no. 112394 titled 10 years of accession: lessons from the agri-food sector of the new member states as well as the unkp-17-4-iii-bce-7 new national excellence program of the ministry of human capacities of hungary. references aghion, p., howitt, p. (1992), a model of growth through creative destruction. econometrica, 60, 323-351. alesina, a., grilli, v., milesi-ferretti, g.m. (1994), in: leiderman, l., razin, a., editors. the political economy of capital controls, in capital mobility: the impact on consumption, investment and growth. cambridge: cambridge university press. p289-321. andersson, n.g.f., karpestam, p. (2013), co2 emissions and economic activity: short-and long-run economic determinants of scale, energy intensity and carbon intensity. energy policy, 36, 1285-1294. anwar, s., nguyen, l.p. (2010), foreign direct investment and economic growth in vietnam. asia pacific business review, 16(1-2), 183-202. badinger, h., tondl, g. (2002), trade, human capital and innovation: the engines of european regional growth in the 1990s. ersa conference papers no. ersa02p043. belloumi, m. (2014), the relationship between trade, fdi and economic growth in tunisia: an application of the autoregressive distributed lag model. economic systems, 38(2), 269-287. bozkurt, c., akan, y. (2014), economic growth, co2 emissions and energy consumption: the turkish case. international journal of energy economics and policy, 3(4), 484-494. campos, n.f., kinoshita, y. (2002), foreign direct investment as technology transferred: some panel evidence from the transition economies. manchester school, 70(3), 398-419. cavenaile, l., sougné, d. (2012), financial development and economic growth: an empirical investigation of the role of banks and institutional investors. applied financial economics, 22(20), 1719-1725. chaido, d., athanasios, v., antonios, a. (2004), exports, investments and economic growth: an empirical investigation of the three baltic countries. baltic journal of economics, 4(2), 72-79. cortes-jimenez, i. (2008), which type of tourism matters to the regional economic growth? the cases of spain and italy. international journal of tourism research, 10, 127-139. damijan, j.p., rojec, m.m. (2007), foreign direct investment and catching up of new eu member states: is there a flying geese pattern? applied economics quarterly, 53(2), 91-118. de mello, l.r. (1999), foreign direct investment led growth: evidence from time series and panel data. oxford economic papers, 51, 133-151. dollar, d. (1992), outward-oriented developing economies really do grow more rapidly: evidence from 95 ldcs, 1976-1985. economic development and cultural change, 40, 523-524. dritsakis, n., stamatiou, p. (2016), trade openness and economic growth: a panel cointegration and causality analysis for the newest eu countries. romanian economic journal, 18(59), 45-60. frankel, j.a., romer, d. (1996), trade and growth: an empirical investigation. nber working paper. 5476. fujita, m. (1998), a monopolistic competition model of spatial agglomeration: differentiated product approach. regional science and urban economics, 18, 87-124. ghosh, b.c., alam, k.j., osmani, m.a.g. (2014), economic growth, co2 emissions and energy consumption: the case of bangladesh. international journal of business and economics research, 3(6), 220-227. grossman, g., helpman, e. (1991), quality ladders in the theory of growth. review of economic studies, 58, 43-61. hassan, m.k., sanchez, b., yu, s.j. (2011), financial development and economic growth: new evidence from panel data. the quarterly review of economic and finance, 51, 88-104. helpman, e., krugman, p.r. (1985), market structures and foreign trade. cambridge: mit press. henderson, j.v. (1974), the sizes and types of cities. american economic review, 64, 640-656. jambor, a., babu, s. (2016), competitiveness of global agriculture. in: policy lessons for food security, editor. new york: springer. kai, h., hamori, s. (2009), globalization, financial depth, and inequality in sub-saharan africa. economics bulletin, 29, 2025-2037. kais, s., mbarek, m.b. (2015), dynamic relationship between co2 emissions, energy consumption and economic growth in three north african countries. international journal of sustainable energy, 36(9), 840-854. krugman, p.r. (1997), the age of diminished expectation. cambridge: mit press. la porta, r., lopez, s.f., shleifer, a., vishny, r.w. (1998), law and finance. journal of political economy, 106, 1113-1155. law, h.s., singh, n. (2014), does too much finance harm economic growth? journal of banking and finance, 41, 36-44. leitão, n.c. (2010), financial development and economic growth: a panel data approach. theoretical and applied economics, xvii 5(511), 15-24. leitão, n.c. (2011), intra-industry trade in the automobile sector: the portuguese experience. argumenta oeconomica, 2(27), 125-136. leitão, n.c. (2011), tourism and economic growth: a panel data approach. actual problems of economics, 9: 343-349. leitão, n.c. (2012), bank credit and economic growth: a dynamic panel analysis. the economic research guardian, 2(2), 256-267. leitão, n.c., rasekhi, s. (2013), the impact of foreign direct investment on economic growth: the portuguese experience. theoretical and applied economics, xx 1(578), 51-62. leitão, n.c., shahbaz, m. (2016), economic growth, tourism arrivals and climate change. bulletin of energy economics, 4(1), 35-43. levine, r., loayza, n., beck, t. (2000), financial intermediation and growth: causality and causes. journal of monetary economics, 46, 31-77. lim, k.m., lim, s.y., yoo, s.h. (2014), oil consumption, co2 emission, and economic growth: evidence from the philippines. sustainability, 6, 967-979. lucas, r. (1988), on the mechanics of economic development. journal of monetary economics, 22, 3-42. mehic, e., silajdzic, s., babic-hodovic, v. (2013), the impact of fdi on economic growth: some evidence from southeast europe. emerging markets finance and trade, 49 suppl 1, 5-20. mileva, e. (2008), the impact of capital flows on domestic investment in transition economies. ecb working paper no. 871. nonthapot, s. (2016), mediation between tourism contribution and economic growth in the greater mekong subregion. asia pacific jambor and leitao: economic growth and sustainable development: evidence from central and eastern europe international journal of energy economics and policy | vol 7 • issue 5 • 2017 177 journal of tourism research, 21(2), 157-171. onaran, ö. (2007), jobless growth in the central and eastern european countries: a country specific panel data analysis for the manufacturing industry, vienna university of economics and business administration, working paper no. 103. ozturk, i., acaravci, a. (2009), on the causality between tourism growth and economic growth: empirical evidence from turkey. transylvanian review of administrative sciences, 25, 73-81. panahi, h., mamipour, s., nazari k. (2015), tourism and economic growth: a time-varying parameter approach. anatolia: an international journal of tourism and hospitality research, 26(2), 173-185. petkovski, m., kjosevski, j. (2014), does banking sector development promote economic growth? an empirical analysis for selected countries in central and south eastern europe. economic research ekonomska istraživanja, 27(1), 55-66. popescu, g.h. (2014), fdi and economic growth in central and eastern europe. sustainability, 6, 8149-8163. proença, s., soukiazi, e. (2008), tourism as an economic growth factor: a case study for southern european countries. tourism economics, 14, 791-806. rebelo, s. (1991), long-run policy analysis and long-run growth. journal of political economy. 99(3), 500-521. rodrik, d. (1998), who needs capital account convertibility? in: fischer, s., editor. should the imf pursue capital account convertibility? princeton: essays in international finance. p207. romer, p. (1986), increasing returns and long run growth. journal of political economy, 98(5), 71-102. ryan, a., compton, r., giedeman, d.c.a. (2011), panel evidence on finance, institutions and economic growth. applied economics, 43(25), 3523-3547. saidi, k., hammami, s. (2015), the impact of energy consumption and co2 emissions on economic growth: fresh evidence from dynamic simultaneous-equations models. sustainable cities and society, 14, 178-186. sakyi, d., commodore, r., opoku, e.e.o. (2015), foreign direct investment, trade openness and economic growth in ghana: an empirical investigation. journal of african business, 16(1-2), 1-15. sequeira, t., nunes, m. (2008), does tourism influence economic growth? a dynamic panel data approach. applied economics, 40, 2431-2441. shahbaz, m., hye, a.m.q., tiwari, k.a., leitão, n.c. (2013), economic growth, energy consumption, financial development, international trade and co2 emissions in indonesia. renewable and sustainable energy review, 25, 109-121. svilokos, t., tolić, m.s., pavlić, i. (2014), economic growth and tourism demand in croatia: the cyclical component analysis. zagreb international review of economics and business, 17, 65-80. tang, c.f., tan, e.c. (2015), does tourism effectively stimulate malaysia’s economic growth? tourism management, 46: 158-163. thorpe, m., leitão, n.c. (2014), economic growth in australia: globalisation, trade and foreign direct investment. global business and economics review, 16(1), 75-86. tiwari, a.k. (2011), energy consumption, co2 emissions and economic growth: a revisit of the evidence india. applied econometrics and international development 11(2), 165-189. yazdi, s.k., salehi, k.h., soheilzad, m. (2017), the relationship between tourism, foreign direct investment and economic growth: evidence from iran. current issues in tourism, 20(1), 15-26. . international journal of energy economics and policy | vol 10 • issue 1 • 2020 37 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(1), 37-43. economic growth, energy consumption and human capital formation: implication for knowledge-based economy bosede comfort olopade1,2, henry okodua1, muyiwa oladosun1, oluwatoyin matthew1*, ese urhie1, romanus osabohien1, oluwasogo adediran1, olubunmi h. johnson3 1department of economics and development studies, covenant university, ota, ogun state, nigeria, 2adeleke university, p.m.b. 205, ede, osun state, nigeria, 3department of business management, covenant university, ota, ogun state, nigeria. *email: oluwatoyin.matthew@covenantuniversity.edu.ng received: 23 may 2019 accepted: 15 september 2019 doi: https://doi.org/10.32479/ijeep.8165 abstract this study examines the relationship between technology, human capital and economic growth and also attempts to establish their implications on knowledge based economy in nigeria. the data used for the study are from secondary sources while the new growth model was also adopted. the dependent variable in the model is the level of real output while the explanatory variables are gross capital formation and government expenditure on education. the result of the causality test shows that is a uni-directional relationship running from gross capital formation and real output, human capital formation and real output growths do not granger cause each other while causality runs from human capital to capital formation and vice versa. the implication of the result; the increase in economic growth has not improve the rate of capital formation in nigeria. the study concluded that nigeria has been slow to identify the strands of global knowledge due to the following: weak institutions; limited awareness and disincentives preventing them from taking the root to the knowledge and information basedeconomy. based on the findings the study recommended; strategies in which education can be incorporated into the growth system. research and development should be encouraged as well and polices that promote output through savings. keywords: economic growth, human capital formation, knowledge and information based economy, technology jel classifications: o47, o15, g14 1. introduction the development of human capital involves increasing skills, knowledge, specialization productivity and creativity of people through process of human capital formation. technology also on the other hand promotes growth and development. oecd (1996) stressed that science, technology and industry policies should be formulated to maximize performance and well-being in “knowledge-based economies”1. to promote growth and development in a country, knowledge is inevitable. knowledge 1 a knowledge based economy is an economy which is directly based on the production, distribution and use of knowledge and information. involves the role of information; training and learning process towards achieve growth and development. to some scholars, investment in such areas are noted as most important for long run growth and development (razim, 2012 annabi and lan, 2007; matthew et al., 2019; matthew et al., in press). according to kefela (2010), knowledge based economy is a situation where the citizens of a country accumulate, disseminate, and use knowledge for growth and development of their nation. it is worth to mention that creation of wealth through knowledge based economy is more efficient that create of wealth through natural resources. the neo-classical production function shows the relationship between growth and technology. in this function, human capital is included which capture the effect of knowledge and information based this journal is licensed under a creative commons attribution 4.0 international license olopade, et al.: economic growth, energy consumption and human capital formation: implication for knowledge-based economy international journal of energy economics and policy | vol 10 • issue 1 • 202038 weconomy. given the neoclassical production, there is allowance for diminishing returns when additional input of capital is used. the improvement in technology may not be captured in this model, despite the fact that technology is a function of growth. knowledge is important in the growth model. knowledge is capable to increase the rate of returns on investment. knowledge on the other hand, can also spill over from one production sector to another sector, while the cost of new idea is little. the spillovers can remove or lower constraints that may result from used of capital. according to some scholars, incorporating knowledge into standard production functions is a difficult issue, since knowledge as a factor of production in the model disregards some fundamental economic principles such as scarcity. knowledge and information are given in surplus, so there is no scarcity in their uses. to promote output through knowledge and information is embodied in investment in both human capital formation and technology. though knowledge about technologies may varies or the same across countries but are necessary when a country needs to acquire skills. awang (2004) and zainol (1999) emphasized that that well equipped productive agents will promote economic performance and competitiveness that may be necessary to move the economy to the path of knowledge based. that is, to achieve promoting knowledge based economy development of human capital, research and development (r&d) and other knowledge oriented programmes are crucial (ismail and jajri, (1998); lichtenberg (1992); barro and sala-i-martin, (1995) and artelaris et al. (2007), matthew et al. (2018)). despite the importance of human capital and technology to promote growth by the nigerian government, the income per capita is still low and its transmission to knowledge based and information economy still remain empirical findings. so the question is what is the direction of human capital formation, technology and economic growth in nigeria and what implication(s) does it have in transforming the country to information and knowledge based economy? in attempting to answer these questions, scholars in nigeria had focused more on the relationship between education and health, education and economic growth and so on for example, adelowokan (2012) examines growth effect on education and health expenditure using a static regression model; the author’s finding shows that there is a long-relationship between human capital spending and economic growth using engle-granger two-step co-integration procedure. odior (2011) analyses the dynamic (direct and indirect) effect of government policy on education and its relation to cyclical economic growth. odior looks at the effect on the long run using integrated sequential dynamic computable general equilibrium (cge) model owen (1995). it was shown by the author that the reallocation of government expenditure to education sector is significant in explaining economic growth in nigeria. chude and chude (2013) examine the impact of government expenditure on economic growth in nigeria from 1977 to 2012 using an error correction model (ecm). the authors show that the total expenditure on education is highly and statistically significant and have positive relationship on economic growth. oluwatobi and ogunrinola (2011) also examine government expenditure on human capital development and its implication for economic growth in nigeria using co-integration technique and a vector error correction (vec) model. the authors show that there exist a positive relationship between government recurrent expenditure on human capital development and the level of real output, while capital expenditure is negatively related to the level of real output. so this work is distinguished from others by examining the relationship between technology, human capital and economic growth and also attempts to establish their implications on knowledge and information based economy in nigeria. unesco (2005) describe a knowledge society as one which is nurtured by its diversity and its capacities2. in order to address the above objectives, the paper has been structured into five sections. starting with the introduction section, section two presents the literature review and theoretical framework. section three is the methodology. section four presents the analysis of data and discussion of result. section five presents the conclusion and recommendations of the paper. 2. literature review and theoretical framework this section presents a brief literature review. alias et al. (2000), othman (1999) and samsudin (1999) show that economic growth cannot be separated from technological changes, and that the latter in turn depends on human capital involved in research. technology development can be measured in terms of the personnel involvement in r&d or the development allocation and expenditure for r&d. acemoglu and pischke (1999) observed that although formal educational attainment is the most common indicator of human capital, on-the-job training (or training at the workplace by firms) may be at least as important in determining productivity. for firms investing in the human capital of their workers this is often seen to be a mechanism for increasing the employability of poorly educated prospective employees, improving the productivity of existing employees, and enhancing the flexibility and adaptability of all workers (jacobs et al., 1996). an important distinction that is made in the literature with regard to training is the difference between general and specific training. though both types of training increase the marginal productivity of the worker, general training tends to be portable to other employers, while specific training, to a large extent, could be regarded as non-portable to other employers. general training impacts the worker’s production capability in all jobs by an equal amount, irrespective of the firm under consideration, while specific training impacts the worker’s productivity only in the current job (lynch and black, 1998; borjas, 1984; afolayan et al., 2019; osabohien et al., 2019). romer (1986), lucas (1988) and mankiw et al. (1992), romer (1990) examine the relationship between education and knowledge. lucas’s (1988) stressed that human capital is similar to what is called population wide education. this shows the 2 by this definition, it means an economy that utilizes all resources and information to achieve optimal output. not necessarily focused on physical inputs but as well as non-physical inputs. olopade, et al.: economic growth, energy consumption and human capital formation: implication for knowledge-based economy international journal of energy economics and policy | vol 10 • issue 1 • 2020 39 important of education in promoting knowledge based economy. romer (1986) as well emphasized that education relates if not direct but indirect to the frontier of science and technology. though empirical findings had shown weak correlation between education and economic growth in some countries (benhabib and spiegel (1994) and pritchett (1997); caselli et al. (1996); knowles and owen (1995)) while in contrast, works by some scholars had shown positive correlation (barro and sala-i-martin (1995), sala-i-martin (1997), mcmahon (1998), temple (1999), bils and klenow (2000), self and grabowski, (2004), matthew et al. (2019)). there is no consensus in literature, but most the empirical research used the traditional models of growth and development. these models did not account for some important aspect the new growth models3. in the new growth model, there are dynamic linkages or feedback to growth. as such there is both direct and indirect effect as stressed by romer (1986). the indirect impact could be measured by productivity improvement which is embodied in the investment of human capital (mcmahon, 1998; brempong et al., 2004) hojo (2003). haldar (2009) examined the relationship between growth and education using time series data. the scholar show that among the three growth models (physical capital, human capital and export led growth), the human capital accumulation led growth model is more relevant to indian economy. for a country to promote growth and development via knowledge based economy there is need for concurrently in education base, innovation systems, and information. during this process, improved institutional system cannot be neglected. knowledge and innovation have always played a crucial role in economic and social development (matthew et al., 2018; matthew et al., 2019: udah, 2011). traditional growth model have been strengthened by new growth theorists. in the new growth model, education plays a vital role to promote growth and development. according to romer (1996), arrow (1962); romer and romer (2007), education and innovative aptitudes has the foundation to create competitive economies4. the new growth theory stressed two important points. 1. the perspective of technological progress as a product of economic activity is different from the traditional theories that take technology as a given, or a product of non-market forces. new growth theory is often called “endogenous” growth theory, because it internalizes technology into a model of how markets function. 2. also, in the new growth theory, knowledge and technology are characterized by increasing returns, and these increasing returns drive the process of growth5. the important factor of new growth theory is that knowledge and information is the engine of growth. knowledge can be 3 with the new growth model, knowledge and information are incorporated into the model. this is used as the theoretical framework of this study. 4 from this, education must incorporate and integrate with the structure of the economy to promote growth and development, which most developing countries need to focus more on. 5 romer is credited with stimulating new growth theory, but as romer himself notes, (romer 1994b) there is really nothing new about the theory itself. the central notion behind new growth theory is increasing returns associated with new knowledge/information or technology. extremely shared and reprocess for use again, and are not limited in accumulation. so principle “diminishing returns” cannot take place in this process. in the new growth model, increasing returns to knowledge is recognized as the main factor for economic growth. romer (1986) the output of the firm is the function of its physical capital and the labour stock. the labour is connected by the state of knowledge at time t and at is given as; y f k alti ti t ti= ( , ) (1) in this model variable gt is assumed, that is the stock of experience and information at time t. the stock of experience is a function of past investments of all firms in the economy. g i d kt s s t t = = −∞ ∫ (2) technology is assumed to be endogenously given by a6 a gt t n= ( )0 1< <n state of knowledge in the model is a positive but has a decreasing function in respect ot state of experience and information. rewritten equation (1) using what is referred to as learning – byinvesting hypothesis7. y f k l kti ti ti t= ( , , ) (3) the model afore-specified is for an individual, on aggregate it will be: y f k l kt t t t= ( , , ) y k l kt t t t n= α β. . (4) where y yt ti i n = ∑ , k kt ti i n = ∑ and l lt ti i n = ∑ n is the number of firms in the economy. to intensive representation, we divide equation (4) bylt to get the intensive representation, y k kt t t n=  . (5) from equation 5, two things can be deduced: 1. models featuring technological advances that endogenously generate externality effects the production function in equation (5) exhibits increasing returns to scale due to the presence of spillover effects coming from knowledge, information and or education. 2. in the model, the technology used exhibits constant returns, due to the accumulation of all types of capital human and knowledge are present. the accumulation of knowledge capital will promote the development of the knowledge-based economy. the extraordinary progress in information and communications technology, together 6 in the endogenous growth model it is assumed to be exogenously determined while it is endogenously determined in the new endogenous growth model. 7 used in the growth model. olopade, et al.: economic growth, energy consumption and human capital formation: implication for knowledge-based economy international journal of energy economics and policy | vol 10 • issue 1 • 202040 with technological advance and world competition along with changing demand is the reason why knowledge is becoming more important8. 3. methodology 3.1. model specification following the new neoclassical growth model by romer (1986), equation 5 above can be rewrite as: y f cf hcft t t= ( , ) (6) in equation (6) yt is the output, cf is the capital through capital formations and hcft is the experience and information (which explained in the theoretical framework as the function of the investment in education or training). to determine the direction of relationship, the study adopted granger causality test and the equations are stated below (pair wise): for variables yt and cft, y y cf et i t j t j n t n t= + + +== ååa a a1 11 1 12 1 11 1 (7) cf y cf ei t j t j n t n t= + + +− − == ∑∑  2 21 1 22 1 11 2 (8) for variables yt and hcft, y y hcf et i t j t j n t n t= + + +− − == ∑∑  1 11 1 12 1 11 3 (9) hcf y hcf ei t j t j n t n t= + + +− − == ∑∑  2 21 1 22 1 11 4 (10) for variables cft and hcft, cf cf hcf et i t j t j n t n t= ∂ + ∂ + +− − == ∑∑1 11 1 12 1 11 5  (11) hcf cf hcf et i t j t j n t n t= ∂ + ∂ + +− − == ∑∑2 21 1 22 1 11 6  (12) in equations 7 to 12, it is assumed that the error terms are not correlated and each variable is treated as both dependent and independent variables (lag of the variable). that is each equation contains the lag of its own variable and the other independent variable. majority of studies (barro and sala-i-martin, 1995; brunetti et al., 1998, hanushek and kimko, 2000) have measured the quality of human capital using proxies related to education like school-enrolment rates, tests of mathematics and scientific skills among others. 3.1.1. decision rules in the equations above (7 to 12); if   12 21 0 0≠ =; unidirectional relationship (from gross capital formation to output);   12 21 0 0= ≠; 8 it is important to be a part of the knowledge based economy because information and knowledge are replacing capital and energy as primary wealth-creating assets. unidirectional relationship (from output to gross capital formation); α α 12 21 0 0≠ ≠; bi-directional relationship (between the output and gross capital formation);  12 210 0= =; independence is suggested (none). also;   12 21 0 0≠ =; unidirectional relationship (human capital formation to output);   12 21 0 0= ≠; unidirectional relationship (from output to human capital formation); β β12 210 0≠ ≠; bi-directional relationship (between output and human capital formation;  12 210 0= =; independence is suggested (none). ∂ ≠ ∂ =12 210 0; unidirectional relationship (human capital to gross capital formation); ∂ = ∂ ≠ 12 21 0 0; unidirectional relationship (gross capital formation to human capital); ∂ ≠ ∂ ≠12 210 0; bi-directional relationship (between human capital and gross fixed capital formation); ∂ = ∂ =12 210 0; independence is suggested (none). 3.2. data source and estimation technique the sources of data are derived from the federal office of statistics (fos) (now national bureau of statistics [nbs]) economics and statistics review, various issues of the central bank of nigeria (cbn) statistical bulletin and annual reports. the study focused on the period between 1981 and 2017. the model examined the nexus of economic growth, technology and human capital formation in nigeria. human capital, technology and economic growth are proxied by government expenditure on education, gross capital formation and real gdp growth. 4. data analysis and discussion of result 4.1. stationarity test the summary result is presented in the appendix (appendix 1). using the augmented dickey fuller test of stationarity, all the variables are non-stationary at their level forms but are all integrated of order one i(1), that is, they attain stationarity after first differencing. hence, the fear of spuriousity of regression is allayed. 4.2. granger causality test the full result of the granger causality test is presented in the appendix (appendix 2). all variables are presented in their logarithmic growth forms, where lrgdpg = growth in the log of real output used to measure economic growth; lgfcfg = growth in the log of gross fixed capital formation which is used as a proxy for growth in capital formation (cf); lgeeg = growth in the log of government expenditure on education and is used as a proxy for growth in human capital (hcf). the results showed that α12 ≠ 0 but α21 = 0, that is there is a uni-directional relationship running from lgfcfg to lrgdpg; this implies that gross capital formation granger causes real output and the reverse does not ensue. in other words, capital formation helps in predicting the behaviour of real output in nigeria. with respect to lgeeg and lrgdpg, the coefficients β12 and β21 are both equal to zero. thus independence is suggested. this implies that human capital formation and real output growths do not granger cause each other. hence no one helps in predicting the behaviour or performance of the other in nigeria. as for lgeeg and lgcfg, the coefficients ∂12 and ∂21 are both not equal to zero. this means that granger causality runs from human capital to capital formation and vice versa (i.e., a olopade, et al.: economic growth, energy consumption and human capital formation: implication for knowledge-based economy international journal of energy economics and policy | vol 10 • issue 1 • 2020 41 bi-directional relationship between them). therefore, in nigeria, human capital can be used to predict the behaviour of capital formation and vice versa. 5. conclusion and recommendations this paper had examined the implications of economic growth, energy consumption and human capital formation on knowledgebased economy. the findings of the granger causality test show that α12 ≠ 0 but α21 = 0, which means that is a uni-directional relationship running from lgfcfg to lrgdpg (that is gross capital formation granger causes real output). but on the other way round, the real output does not granger cause gross capital formation. the implication of this is that, the increase in economic growth that the country witness as not improve the rate of capital formation in nigeria. the transmission mechanism of gdp to capital formation mostly should be through savings. the accumulation of capital will facilitate the evolution of the knowledge and information based economy. knowledge and information based economy according to the new neoclassical economy is the most powerful engine of production. so nigeria’s government needs to ensure that polices that promote output through savings are to be encouraged. also for the analysis, given that lgeeg and lrgdpg, the coefficients β12 and β21 are both equal to zero. thus independence is suggested. that is human capital formation and real output growths do not granger cause each other. investment in human capital encourages division of labour, which on the other hand promote specialization and hence increase in output per head and also at the aggregate level. also in new neoclassical model of output, knowledge and information based economy is embodied in investment in human capital. what matters here is not the quantity of the education but the quality of education. so nigerian’s government needs to develop strategies in which education can be incorporated into the growth system. r&d should be encouraged as well. one special aspect of knowledge makes it critical to growth. knowledge is subject to increasing returns because it is a non-rival good, an economy that is knowledge and information based has the opportunities for growth which may be regarded as almost limitless, price is not the function of output – because in the case of knowledge, markets may not send the right price signals. the social benefits and the private costs of new knowledge creation diverge. as a result of additional use of knowledge has zero marginal cost, once the knowledge is created, any positive price for knowledge is too high.” and finally, knowledge and information based economies tend toward monopolistic competition9. the result for lgeeg and lgcfg, the coefficients ∂12 and ∂21 are both not equal to zero. this means that granger causality runs from human capital to capital formation and vice versa (i.e. a bi-directional relationship between them). therefore, in nigeria, 9 econometric studies have repeatedly shown that the social rate of return to research (the value of all of the economic benefits received by society) is typically two to five times higher than that private rate of return (the profits accruing to the individual or the company that pioneered the innovation) (jarboe and atkinson 1998). human capital can be used to predict the behaviour of capital formation and vice versa. so the study concluded that many developing countries (including nigeria) have been slow to identify the strands of global knowledge, if the basic components of the knowledge economy are readily available, why not appropriate for developing countries for growth and innovation? the challenges are due to the following: weak institutions; limited awareness and disincentives preventing them from taking the root to the knowledge economy. all this needs to be appropriately addressed to create and economy that is knowledge and informationbased. 6. acknowledgments the authors are grateful to the management of covenant university through her centre for research, innovation and discovery (cucrid) for the financial backing received. references acemoglu, d., pischke, j.s. (1999), beyond becker: training in imperfect labour markets. the economic journal, 109(453), 112-142. adelowokan, o.a. (2012), growth effect of education and health expenditure in nigeria (1970-2010). africa journal of scientific research, 10(1), 22-26. afolayan, o.t., okodua, h., matthew, o., osabohien, r. (2019), reducing unemployment malaise in nigeria: the role of electricity consumption and human capital. international journal of energy economics and policy, 9(4), 63-73. alias, m.h., jaafar, a.s., anuar, a.r. (2000), economic education and supply of knowledge workers. kuala lumpur: proceedings of the national seminar on malaysia’s transformation into k-economy: challenges and responses. annabi, n., harvey, s., lan, y. (2007), public expenditure on education human capital and growth in canada: an olg model analysis. journal of policy modeling, 33, 852-865. arrow, j. (1962), the economic implications of learning by doing. review of economics, 3(1), 32-45. artelaris, p., arvanitidis, p., petrakos, g. (2007), theoretical and methodological study on dynamic growth regions and factors explaining their growth performance. a paper presented at the 2nd workshop of dynreg in athens, 9-10 march. awang, h. (2004), human capital and technology development in malaysia. international education journal, 5(2), 30-43. barro, r.j., sala-i-martin, x. (1995), economic growth. new york: mcgraw-hill. benhabib, j., spiegel, m.m. (1994), the role of human capital in economic development: evidence from aggregate cross-country data. journal of monetary economics, 34(2), 143-174. bils, m., klenow, p.j. (2000), does schooling cause growth? the american economic review, 90(5), 1160-1183. borjas, g.j. (1984), race, turnover, and male earnings. industrial relations: a journal of economy and society, 23(1), 73-89. brempong, g.k., wilson, m. (2004), health human capital and economic growth in sub-saharan africa and oecd countries. the quarterly review of economics and finance, 44, 296-320. brunetti, a., kisunko, g., weder, b. (1998), credibility of rules and economic growth: evidence from a worldwide survey of the private sector. the world bank economic review, 12(3), 353-384. caselli, f., esquivel, g., lefort, f. (1996), reopening the convergence debate: a new look at cross-country growth empirics. journal of economic growth, 1(3), 363-389. olopade, et al.: economic growth, energy consumption and human capital formation: implication for knowledge-based economy international journal of energy economics and policy | vol 10 • issue 1 • 202042 chude, n.p., chude, d.z. (2013), impact of government expenditure on economic growth in nigeria. international journal of business and management review, 1(4), 64-71. haldar, s.k. (2009), economic growth in india revisited: an application of co-integration and error correction mechanism. south asia economic journal, 10(1), 105-126. hanushek, e., kimko, d. (2000), schooling, labour-force quality and the growth of nations. american economic review, 90, 1184-1200. hojo, m. (2003), an indirect effect of education on growth. economics letters, 80, 31-34. ismail, r., jajri, i. (1998), human capital and economic growth in malaysia: a simulation model. kajian malaysia, 16(1-2), 78-88. jacobs, l.d., cookfair, d.l., rudick, r.a., herndon, r.m., richert, j.r., salazar, a.m., fischer, j.s., goodkin, d.e., granger, c.v., simon, j.h., alam, j.j. (1996), intramuscular interferon beta‐1a for disease progression in relapsing multiple sclerosis. annals of neurology: official journal of the american neurological association and the child neurology society, 39(3), 285-294. kefela, g.t. (2010), knowledge-based economy and society has become a vital commodity to countries. international ngo journal, 5(7), 160-166. knowles, s., owen, p.d. (1995), health capital and cross-country variation in income per capita in the mankiw-romer-weil model. economics letters, 48(1), 99-106. lichtenberg, f. (1992), r and d investment and international productivity differences, nber working paper, no. 4161. lucas, r.e. (1988), on the mechanics of economic development. journal of monetary economics, 22, 3-42. lynch, l.m., black, s.e. (1998), beyond the incidence of employer-provided training. industrial and labour relations review, 52(1), 64-81. mankiw, n.g., romer, d., weil, d.n. (1992), a contribution to the empirics of economic growth. quarterly journal of economics, 107, 407-437. matthew, o., adeniji, a., osabohien, r., olawande, t., atolagbe, t. (in press), gender inequality, maternal mortality and inclusive growth in nigeria. social indicators research. doi: 10.1007/s11205-019-02185-x. matthew, o., osabohien, r., olawande, t., urhie e. (2019), manufacturing industries and construction emissions in nigeria: examining the effects on health conditions. international journal of civil engineering and technology, 10(2), 2401-2414. matthew, o., osabohien, r., urhie, e., ewetan, o., adediran, o., oduntan, e., olopade, c. (2019), agriculture as a stimulant for sustainable development in ecowas. sustainability: the journal of record, 12(4), 215-225. matthew, o.a., ede, c., osabohien, r., ejemeyovwi, j., ayanda, b., okunbor, j. (2018), the interaction effect of tourism and foreign exchange earnings on economic growth in nigeria. global business review, 1-16. doi: 10.1177/0972150918812985. matthew, o.a., ede, c., osabohien, r., ejemeyovwi, j., fagbeminiyi, f.f., akinpelumi, d. (2018), electricity consumption and human capital development: exploring the implications for economic growth in nigeria. international journal of energy economics and policy, 8(6), 8-15. matthew, o.a., miebaka-ogan, t., popoola, o., olawande, t., osabohien, r., urhie, e., adediran, o., ogunbiyi, t. (2019), electricity consumption, government expenditure and sustainable development in nigeria: a co-integration approach. international journal of energy economics and policy, 9(4), 74-80. mcmahon, w.w. (1998), education and growth in east asia. economics of education review, 17(2), 159-172. odior, o.n. (2011), government spending in education, economic growth and long waves in a cge micro-simulation analysis: the case of nigeria. british journal of economics, finance and management sciences, 1(2), 13-28. oluwatobi, s.o., ogunrinola, i.o. (2011), government expenditure on human capital development: implication for economic growth in nigeria. journal of sustainable development, 4(3), 40-54. osabohien, r., matthew, o., gershon, o., ogunbiyi, t., nwosu, e. (2019), agriculture development, employment generation and poverty reduction in west africa. the open agriculture journal, 13, 82-89. othman, y.a. (1999), information technology, e-commerce and the way forward for malaysia. kuala lumpur: proceedings of the malaysia economic association conference on services and e-commerce: meeting the challenge of the information revolution. owen, s. (1995), altruism and beyond: an economic analysis of transfers and exchanges within families and groups. cambridge: cambridge university press. pritchett, l. (1997), where has all the gone? the world bank. washington dc: policy research working paper, 1581. razim, m.j. (2012), investigating the effect of government health expenditure on hdi in iran. an unpublished dissertation submitted to the university of mashhad, iran. romer, c.d., romer, d.h., editors. (2007), reducing inflation: motivation and strategy. vol. 30. chicago: university of chicago press. romer, d. (1996), advanced macroeconomics. london: mcgraw-hill. romer, p. (1986), increasing returns and long-run growth. journal of political economy, 94(5), 1002-1037. romer, p. (1990), endogenous technical change. the journal of political economy, 98, 42-57. sala-i-martin, x. (1997), i just ran four million regressions. national bureau of economic research (cambridge ma), working paper, 6252. samsudin, h. (1999), structural transformation of the malaysian economy: towards knowledge-based economy. kuala lumpur: proceedings of the malaysian economic association conference on services and e-commerce; meeting the challenge of the information revolution. self, s., grabowski, r. (2004), does education at all levels cause growth? india, a case study. economics of education review, 23, 47-55. temple, j. (1999), a positive effect of human capital on growth. economic letters, 65, 131-134. the organisation for economic co-operation and development. (1996), the knowledge economy, education, training. washington dc: united states of america. udah, e.b. (2011), remittances, human capital and economic performance in nigeria. journal of sustainable development in africa, 13, 24-39. unesco. (2005), decade of education for sustainable development: 2005-2014. draft international implementation scheme. paris: unesco. zainol, a.a.r. (1999), national workforce transformation. proceedings of the 4th national conference on economic transformation held in istanbul turkey. olopade, et al.: economic growth, energy consumption and human capital formation: implication for knowledge-based economy international journal of energy economics and policy | vol 10 • issue 1 • 2020 43 appendix appendix 1: stationarity test (augmented dickey fuller – adf test) variable critical values t-statistic order of integration 1% 5% 10% lgeeg level −3.6891 −2.9719 −2.6251 −1.2309 1st difference −3.6891 −2.9719 −2.6251 −5.1985 i(1) lgfcfg level −3.6537 −2.9571 −2.6174 −0.7613 1st difference −3.6617 −2.9604 −2.6192 −9.8633 i(1) lrgdp level −3.6617 −2.9604 −2.6192 0.8192 1st difference −3.6617 −2.9604 −2.6192 −3.4270 i(1) appendix 2: granger causality test pairwise granger causality tests date: 01/25/15 time: 20:04 sample: 1981 2013 lags: 2 null hypothesis: obs f-statistic prob. lgfcfg does not granger cause lrgdpg 31 5.47506 0.0104 lrgdpg does not granger cause lgfcfg 0.10943 0.8968 lgeeg does not granger cause lrgdpg 31 1.56002 0.2292 lrgdpg does not granger cause lgeeg 0.46301 0.6345 lgeeg does not granger cause lgfcfg 31 4.78920 0.0170 lgfcfg does not granger cause lgeeg 3.43013 0.0476 . international journal of energy economics and policy | vol 10 • issue 4 • 2020 23 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(4), 23-30. feasibility study for biogas generation from household digesters in bangladesh: evidence from a household level survey samira salam1, rehana parvin2, md. abdus salam3*, s. m. nasim azad2 1department of basic science, primeasia university, banani, dhaka, bangladesh, 2department of statistics, bangabandhu sheikh mujibur rahman science and technology university, gopalganj, bangladesh, 3department of statistics, jahangirnagar university, savar, dhaka, bangladesh. *email: salam@juniv.edu received: 12 january 2020 accepted: 25 april 2020 doi: https://doi.org/10.32479/ijeep.9206 abstract biogas could be an important alternative source of energy in order to meet its increasing demand in bangladesh. to explore the feasibility of biogas generation in bangladesh, a household level sample survey on the biogas digester adaptors and biogas digester non-adaptors were conducted. the study revealed that costs for cooking by using solid fuels are significantly higher compared to costs for cooking by using biogas. biogas generation has become very urgent in bangladesh because of absence of natural gas supply in rural households, collection of fuelwoods has become difficult because of increasing tremendous pressure on forest lands, and the cost of alternative cooking fuels like lp gas is unaffordable for rural people. as the substrates for biogas generation are readily available and people are highly interested to adapt biogas digester, a welcoming environment for biogas generation is prevailed in bangladesh. moreover, biogas digesters are easy to operate and easy to maintain and even women can operate and maintain biogas digesters. biogas production is profitable, and almost all the biogas adopters are satisfied with the performance of biogas digestors. logistic regression analysis identified some important factors that are significantly influenced for the adoption of biogas digestors and these are (i) education of household head, (ii) household income, (iii) costs for cooking fuels, (iv) number cattle available in the households, and (v) number of poultry available in the households. results presented in this study indicate that bangladesh is urgently needed to generate biogas and feasible environment for biogas generation prevails in bangladesh. the only needs are the motivation, initiatives and necessary support from the top levels to install biogas digesters. keywords: biogas, solid fuels, anaerobic digestion, methane, renewable energy, environment jel classifications: q4, p28 1. introduction in the era of urbanization, the demand of energy is rising with an unpredicted rate with each passing day. to meet the growing energy demand, developing countries have been depending on solid fuels for cooking. worldwide, approximately 3 billion people are burning solid fuel, including biomass, agricultural residues and charcoal, for their daily cooking (nigel, 2004; eric et al., 2018). the overdependence on solid fuels as primary energy source has led to global climate change, environmental pollution and degradation, and thus leading to human health problems (otun et al., 2015). global depletion of solid fuels has led to the search for alternative sources of energy. in most developing countries, cooking is a dirty and timeconsuming job that involves burning solid fuels to produce fire. solid wood fuels used for cooking and heating, represent approximately 55% of global wood harvest and 9% of primary energy (un fao, 2013; ren21 secretariat, 2013). about 50% of the wood fuel harvest is unsustainable (bailis et al., 2015). cooking over a 3-stone fire in a home is equivalent to burning 400 cigarettes in an hour that release toxic smoke and emissions which mostly this journal is licensed under a creative commons attribution 4.0 international license salam, et al.: feasibility study for biogas generation from household digesters in bangladesh: evidence from a household level survey international journal of energy economics and policy | vol 10 • issue 4 • 202024 affect women and children (efc, 2012). a study by global health revealed that inefficient cook stoves to be the largest environmental threat (gec, 2012). worldwide about 70,000 people die per year because of household air pollution (ihme, 2017). thus, cooking by solid fuels is a challenge as inefficient systems of cooking have a major impact on health, environment and economy. development of renewable and sustainable energy source is the best solution to the country’s energy demand (donald, 1998; das et al., 2018). biogas is an alternative promising substitute to solid fuel and capable of replacing current energy supply and can only be considered as the best for meeting the demand and insurance of future energy in a sustainable manner (corro et al., 2013; mel et al., 2015). biogas is assumed a green sustainable gas produced by the anaerobic digestion of organic agricultural waste, manure, municipal waste, digester materials, sewage, green waste or food waste. it can be produced from locally available raw materials and recycled waste and is agreed environmental friendly and neutralizing greenhouse effects and thus contributed climate change mitigation (clements et al., 2006; mccarl, 2010; zahariev et al., 2014; das et al., 2018). this process produces gases which contains roughly 50-70% methane (ch4), 30-40% carbon dioxide (co2), and trace amounts of other gases (usda, 2014). the gases methane, hydrogen, and carbon monoxide can be combusted or oxidized with the presence of oxygen to provide heat, electricity or both (babel and pecharaply, 2009). thus, stored biogas can provide a clean, renewable, and reliable source of baseload power in place of coal or natural gas. using stored biogas limits the amount of methane released into the atmosphere and reduces dependence on fossil fuels. in addition to climate benefits, anaerobic digestion can lower costs associated with waste remediation as well as benefit local economies. it is a renewable energy source, like solar and wind energy. it does not have any geographical limitations or requires advanced technology for producing energy, nor is it complex or monopolistic. bangladesh is one of the fastest growing economies in the southern-asia, with 64% of the total population are living in rural areas (suntrace, 2018). it has been reported in who (2016) that 82% of the bangladesh population primarily use wood, charcoal, coal, and kerosene for cooking. bangladesh has a very limited energy reserve; small amount of oil, coal and countable natural gas reserves (prati et al., 2013). thus, in bangladesh scenario, biogas can be a substitute for traditional fuels and can meet the rural energy demand and also provide a clean source of energy. the primary concern of energy production in bangladesh is the prolonged effects of energy demand. if the supply of energy is not proliferated accordingly there will be serious adverse implications for the nation’s economic and social development as well as for the assurance of energy security for future generation. the energy development strategies are dependent on the sustaining relationship between energy consumption and economic growth, energy consumption and human development index, biomass fuel consumption and economic growth and different energy sources providing world energy demand. a long-term comprehensive and integrated energy policy along with appropriate strategies should be formulated to ensure security over short, medium and long terms for the country. the policy should ensure tapping of all possible sources of energy, adequate supply of energy to its various uses and equitable access of renewable energy to all segments of society. due emphasis must be given on the usage of the renewable energy sources and extensive research and development programs should be conducted for the further development of renewable energy technologies. given the extensive use of firewood for cooking in developing countries, studies have been made on emissions from biomassbased stoves, including a detailed study of greenhouse gases from small-scale combustion with special reference to household stoves (smith et al., 2000). all the studies identified that biomassbased stoves had adverse effects on health. in this context, the 7th sustainable development goal includes the target of ensuring universal access to affordable, reliable and modern energy services by 2030 (undp, 2019). another important challenge is the security of energy supply. to achieve these challenging goals, understanding the sources of affordable, reliable and clean energy that suit the economic and geographical conditions is needed. in this context, biogas from wastes, residues, and energy crops will play a vital role in future. thus, this study aimed at evaluating feasibility and prospect of biogas generation in the rural areas of bangladesh. 2. data collection and methodology this study was based on cross-sectional data collected using four-stage cluster sampling. at the first stage, 20 districts from 64 districts of bangladesh were selected randomly. at the second stage, one upazilla from each selected district were randomly selected. at the third stage, two unions from each selected upazilla were selected randomly yielding a total of 40 unions. as there is no sampling frame of biogas digester adaptors and the biogas digester adaptors are very limited in number, all the biogas digester adaptors of the selected unions were detected using snowball sampling technique and interviewed by a structured questionnaire. a total of 498 biogas digester adaptors households and 500 biogas digester non-adaptors households neighboring the selected biogas digester adaptors households were selected and head of each selected household was interviewed by a structured questionnaire. statistical software, spss was used to analyzed the data. various statistical tools, such as summary measures and logistic regression analysis were used to meet the objectives of the study. 3. results and discussion 3.1. background characteristics of the respondents respondents’ background characteristics are associated with the adaption of biogas digester in rural areas. thus, this subsection summarizes background characteristics of the respondents and is presented in table 1. major disparities in some background salam, et al.: feasibility study for biogas generation from household digesters in bangladesh: evidence from a household level survey international journal of energy economics and policy | vol 10 • issue 4 • 2020 25 characteristics of the respondents between the biogas digester adaptors and biogas digester non-adaptors are noticed. the tabulation of respondents by religion indicates a majority of muslim adherents (about 94% of the biogas digester adaptors and about 95% of the biogas digester non-adaptors) and the rest are hindu adherents. table 1 shows no major disparities in the age distribution of biogas digester adaptors and biogas digester non-adaptors. about 42% of the respondents of biogas digester adaptors belonged to aged below 40 years and 57% of the respondents of biogas digester non-adaptors were aged below 40 years. about 32% of the respondents of biogas digester adaptors were aged 40-49 years and about 29% of the respondents of biogas digester non-adaptors were aged 40-49 years. family size is an important stimulus for the adaption of biogas digester because cost of cooking fuels for greater family size might be higher compared to smaller family size. it is seen from the table that family size of biogas digester adaptors’ families was higher compared to biogas digester non-adaptors’ families. about 76% of the respondents of biogas digester adaptors reported their family size as 5 or more while about 65% of the respondents of biogas digester non-adaptors reported their family size as 5 or more. major disparities in education level between respondents of biogas digester adaptors and respondents of biogas digester non-adaptors were noticed. only 8% of the respondents of biogas digester adaptors completed primary level education while about 41% of the respondents of biogas digester non-adaptors completed primary education. about 50% of the respondents of biogas digester adaptors completed secondary level education while only 30% of the respondents of biogas digester non-adaptors completed secondary level education. about 38% of the respondents of the biogas digester adaptors completed higher secondary or above level of education while about 29% of the respondents of biogas digester non-adaptors completed higher secondary or above level of education. it indicates that education of the household head is one of the catalysts for biogas digester adaption. occupation is also an important factor for adaption of biogas digester. it is seen from table 1 that highest proportion (about 46%) of biogas digester adaptors’ occupation was business. about 31% of the biogas digester adaptors’ occupation was agriculture. family income is also one of the most important factors for influencing people to adapt biogas digester. table 2 shows major disparities between family income of biogas digester adaptors and biogas digester non-adaptors. it is seen from the table that family income was higher for the biogas digester adaptors than biogas digester nonadaptors. about 61% of the biogas digester adaptors’ households per month family income was tk. 20,000 or more whereas about 45% of the biogas digester non-adaptor family’s per month family income was tk. 20000 or more. 3.2. main source of cooking fuels for biogas digester non-adaptors a large number of people in rural bangladesh cook daily on traditional stoves and open fires with solid fuels like wood, which has far-reaching health, environmental, and socio-economic impacts. much of the researches on solid cooking fuels have focused on energy efficiency and emissions in the kitchen (salam and alim, 2008; salam and alim, 2009; bailis et al., 2015; chagunda et al., 2017). biomass fuels, such as wood, cow dung, and agricultural residues are collected mainly from the local environment and have become a traded community as cooking fuel as access to local biomass becomes ever more difficult. the supply of natural gas in rural areas are absent and new gas connection to household were suspended for an uncertain time. figure 1 represents the sources cooking fuels in the study areas. it is seen from the table that most of the biogas digester non-adaptors used solid fuels such as fuelwood (about 32%) and cow dung (about 33%) for cooking. the solid fuel is used in traditional stoves which consist of a hole in the ground with a raised clay lip to rest the pot with a separate fuel entry hole. the traditional clay stoves are inefficient and generally poorly ventilated so that they produce fine particles, polycyclic aromatic hydrocarbons, carbon monoxide, table 2: total monthly cost for cooking fuel monthly cost biogas solid fuels <300 74.0 25.8 300-599 5.8 10.6 600-899 4.5 10.2 ≥900 12.7 53.4 total 498 500 mean 420.3 1059.8 standard deviation 971.6 1030.4 z-test for the difference of means between two costs z=10.10, p=0.0000 table 1: background characteristics of the respondents adaptor non-adaptor religion muslim 94.3 95.6 hindu 5.7 4.4 age <30 16.0 21.0 30-39 25.8 30.6 40-49 32.0 28.8 50-59 20.5 14.0 ≥60 5.8 5.6 family size ≤4 23.8 34.4 5-6 52.5 43.0 7-8 19.3 14.0 >8 4.5 8.6 education primary 7.8 40.8 secondary 49.8 29.8 higher secondary 19.5 15 graduate 18.5 8.4 post-graduate 4.5 6.0 occupation agriculture 30.5 37.6 service 19.8 22.8 business 45.8 31.4 foreign employment 1.8 4.0 others 2.3 4.2 total family income <5000 4.4 10.0 5000-9999 5.0 12.6 10,000-19,999 29.5 32.2 20,000-29,999 30.5 22.8 30,000-39,999 14.8 9.2 40,000-49,999 4.8 2.8 ≥50,000 11.0 10.4 total number of respondents 498 500 salam, et al.: feasibility study for biogas generation from household digesters in bangladesh: evidence from a household level survey international journal of energy economics and policy | vol 10 • issue 4 • 202026 dioxins and other carcinogens (nigel et al., 2004). housewives are exposed to high levels of these toxins between 3 and 7 h a day. research revealed that this indoor air pollution occurs not only in the kitchen but slightly lower in the living area therewith affecting also other family members such as children (nigel et al., 2004; salam and alim, 2009). the world health organization (who) estimated that there are 4.3 million premature deaths annually as a result of indoor air pollution exposure due to the lack of clean or modern energy services for cooking (world health organization, 2016). further who attributes 1.3 million disability-adjusted life year to the use of solid fuels. indoor air pollution is the second biggest environmental contributor to illness worldwide after unsafe water and inadequate sanitation (who, 2007). moreover, households cooking with traditional stoves and solid fuels use considerable parts of their incomes for either purchasing fuels for cooking, or using significant amount of their time for collecting firewood (world bank, 2019). even though cooking is not considered as the major cause of deforestation, where firewood is not collected sustainably both environmental and climate impacts are present. in the survey areas, 100% of the households where biogas was available used biogas instead of solid fuels indicating that rural people are highly interested to use biogas. biogas mainly from animal and municipal wastes may be one of the promising renewable energy resources for bangladesh. it is a potential source to harness basic biogas technology for cooking. as much biogas is viewed as a potential renewable energy source, most households have persistently utilized wood and cow dung with the resultant negative effects. it is therefore necessary to assess the factors influencing installation of biogas digester at the household level in rural areas of bangladesh. 3.3. cost for cooking fuels when comparing fuel costs for cooking using biogas and solid fuel few dynamics can be noticed. the first interesting result is that adaption of biogas digester and access to biogas for cooking fuel can result in cost savings. changing from solid fuels to biogas is the cheapest option (monthly cost of biogas is tk, 420 compared to monthly cost of biomass fuel is tk. 1060). in terms of direct cost for cooking with biomass fuels, it is significantly more expensive than cooking with biogas fuels. in terms of indirect cost, biomass fuel gathering can be dangerous as it leaves women exposed to threats of violence, and cooking on traditional stoves is time consuming, preventing women taking on income generating activities and often making children do not attend school. it is important to note that fuel costs for cooking by using solid fuels and biogas vary, with less efficient solid fuels comprising a significantly higher costs than biogas. 3.4. need for adaption of biogas digester bangladesh is one of the fastest growing economies in the southernasia, with 64% of the total population are living in rural areas (suntrace, 2018). it has been reported in who (2016) that 82% of the bangladesh population primarily use wood, charcoal, coal, and kerosene for cooking. bangladesh has a very limited energy reserve; small amount of oil, coal and countable natural gas reserves (prati et al., 2013). these have become a traded commodity as cooking fuel as access to local biomass becomes ever more difficult. the biomass fuels have been depleted due to tremendous pressure on these fuels. only about 6% of the entire population has access to natural gas, primarily in urban areas, for cooking. because of use of limited available gas in industrial production, government has suspended new gas connection for household consumption. thus, in bangladesh scenario, biogas can be a substitute for traditional fuels and can meet the rural energy demand and also it can provide a clean source of energy. it is seen from table 3 that about 56% of the biogas digester adaptors and about 60% of the biogas digester non-adaptors thought that biogas was necessary because of absence of natural gas supply in their areas. about 69% of the biogas digester adaptors and about 71% of the biogas digester non-adaptors felt that biogas production was necessary because of difficulty of collection of fuelwoods. about 42% of the biogas digester adaptors and about 35% of the biogas digester non-adaptors were in favor of installation biogas digester because of excessive cost of fuelwood. 3.5. feasibility for the adaption of biogas digester factors affecting the fermentation process of organic substrates under anaerobic conditions are: (i) ph, (ii) temperature, (iii) loading rate, (iv) agitation, etc. according to different temperature ranges the anaerobic digestion can be classified as psychrophilic (12-30°c), mesophilic (30-45°c), and thermophilic (45-65°c) with anaerobes performing best in mesophilic and thermophilic temperatures (song et al., 2004; nges and liu, 2010; meena et al., 2011; gashaw, 2014). based on the literature reviews mesophilic temperature is most suitable for biogas production in anaerobic digesters systems (parawira et al., 2008; phetyim et al., 2015). the methanogenic bacteria, which facilitate the formation of biogas, are very sensitive to temperature changes and the optimum temperature for the bacteria to operate is between 33° and 38°c (gashaw, 2014). temperatures below this slow down the biogas production process, while a higher temperature than necessary kills the biogas producing bacteria (gashaw, 2014). the temperature in which maximum biogas produced is from cow dung is 27.7°c (otun et al., 2015). temperature in bangladesh remains at mesophilic (30-45°c) stage in most of the days of the year except in short duration of winter (december to february). thus, temperature in bangladesh is ideal for the anaerobic digestion. it is seen from table 4 that almost 80% of the respondents believe that the temperature in bangladesh is suitable for biogas generation. construction of biogas digester completely depends on the availability of substrates used for biogas generation. about 85% 0 5 10 15 20 25 30 35 wood kerosene lp gas cow dung electricity 32.3 7.8 25.7 32.9 4.4 % figure 1: type of cooking fuel used by biogas non-adaptors salam, et al.: feasibility study for biogas generation from household digesters in bangladesh: evidence from a household level survey international journal of energy economics and policy | vol 10 • issue 4 • 2020 27 of the biogas digester adaptors believe that feedstocks for biogas diester were available in their own households (table 4). in about 91% of the biogas digesters used cow dung as substrates for biogas generation and in about 9% of the biogas digesters used poultry droppings as substrate for biogas generation. cow dung and poultry droppings are available in their own households. sagagi et al. (2009) utilized fruit and vegetable wastes and cattle manure individually to study their biogas production potential and found that highest wly production rate was in cow dung (1554 cm3 biogas) >other wastes (<1000 cm3 biogas). organic kitchen wastes co-digested with cattle manure improves the biogas production potential as compared to cattle manure alone (otun et al., 2015; abebe, 2017). consequently, the costs for biogas generation by using cow dung or poultry dropping alone are not favorable due to their relatively low biogas yield in comparison with co-digestion with more biodegradable wastes such as kitchen wastes (moller et al., 2004; aragaw et al., 2013). thus, biogas digester adaptors in bangladesh can use co-digestion system. amount of biogas generation depends on the quantity of new feedstocks added to the digester daily. almost 98% of the biogas digester adaptors collect feedstocks for digester from their own household. thus, about 85% of the biogas digester adaptors believe that feedstocks for biogas generation was available in their own households. availability and easy access to feedstocks for biogas generation is one of important catalysts for sustainable generation of biogas. costs for the setup of biogas digester is another important factor for the adaption of biogas digester. if the cost for setup of biogas digester would not be affordable for the farmers, they would not be interested to adapt the biogas digester. about 17% of biogas digester adapter spent less than tk. 20000 and about 49% of the biogas digester adapter spent tk. 20,000 to tk. 40,000 for setup of a biogas digester. average cost for setup of a biogas digester was tk. 35111. the cost for setup of biogas digester is reasonable and farmers can easily afford this amount for construction biogas digester indicating that adaption of biogas digester is feasible in terms of cost. according to 98% of the biogas digester adaptors’ installation cost of biogas digester in bangladesh is reasonable or cheap. 3.6. attitudes of rural people towards biogas digester adaption successful implementation of any innovation is primarily determined by the end users’ attitude. the generation of biogas through anaerobic digestion offers significant advantages over other forms of energy production. it has been evaluated as one of the most energy-efficient and environmentally beneficial technology for energy production (weiland, 2010). it can drastically reduce greenhouse gases emissions compared to fossil fuels by utilizing locally available resources. in spite of its versatile table 4: feasibility indicators for adoption of biogas digesters scope of constructing biogas digesters percent the temperature of bangladesh is suitable for biogas digesters 80.5 the feedstock for biogas digesters are available from own farm 85.4 need very small piece of land for biogas digester construction 54.6 women can maintain biogas digesters 60.0 feedstocks for biogas digester cow dung 90.8 poultry droppings 8.9 others 0.3 sources of feedstocks own households 98.1 purchase 1.9 whether profitable profitable 85.3 loss project 14.7 total number of respondents cost of construction of biogas digester (in tk.) <20,000 16.7 20,000-40,000 48.6 40,000-60,000 25.9 more than 60,000 8.9 average tk. 35,111 impression about installation cost cost is reasonable 60.0 cost is moderately reasonable 21.0 cheap 17.0 very expensive 2.0 table 3: need for adaption of biogas digester need for adoption biogas digester adaptors non-adaptors insufficient supply of electricity 17.9 26.9 no supply of gas 56.3 60.3 lp gas cylinder is not available 38.9 28.4 collection of fuelwoods is difficult 69.2 70.6 fuelwood is very expensive 41.7 35.4 use of bio-slurry as fertilizer 67.8 32.2 reduce deforestation 34.2 12.3 reduce pressure on natural gas 29.7 10.2 total number of respondents 498 500 table 5: attitude of biogas digester adapters towards biogas attitudes percent reasons for the adaption of biogas digester feedstocks are available in own household 47.4 beneficial for the environment 38.2 less costly 42.9 motivation from government and ngos 11.9 scarcity of other fuel sources 11.4 encouraged by other biogas digester adapters 5.9 others 7.1 total number of respondents 498 whether satisfied with the performance of biogas digester satisfied 88.1 dissatisfied 11.9 reasons for satisfaction with the biogas digesters a profitable investment 16.7 easy to get benefits 15.5 easy to maintain biogas digester 44.8 cheap to cook 72.6 solid residuals of fermentation can be used as fertilizer 72.6 beneficial for health 35.6 upgrade social value 19.9 benefits for the environment 50.5 others 7.3 whether want to advice others to install biogas digesters yes 97.8 no 2.2 salam, et al.: feasibility study for biogas generation from household digesters in bangladesh: evidence from a household level survey international journal of energy economics and policy | vol 10 • issue 4 • 202028 benefits, adaption of biogas digester and use of biogas depend on the attitude of the end users towards biogas. the study results show that biogas digester adapters were interested to setup biogas digester because of easy availability of feedstocks (about 47%), because it is environmentally beneficial (about 38%), and less costly (about 43%). about 88% of the biogas digester adapters were satisfied with the performance of the biogas digester. the reasons for satisfaction were low cooking cost (according to about 73% of the respondents), solid residuals of fermentation might be used as fertilizers (according to about 73% of the respondents), easy to maintain biogas digesters (according to about 45% of the respondents) and benefit for the environment (according to about 51% of the respondents). about 98% of the biogas digester adapters would like to advice others to setup biogas digester (table 5). all these results indicate that bangladesh is an ideal place for adaption of biogas digester. 3.7. factors influencing farmers to adapt biogas digesters adapting a new technology depends on numerous factors which influence target user to adapt or reject including perceived usefulness, availability of feedstocks, and socioeconomic conditions of the biogas digester adapters. these factors can make a positive or a negative contribution towards new technology adaption. in order to identify the influencing factors for the setup of biogas digesters, binary logistic regression model was employed. the dependent variable was status of biogas digester adaption: y=1 if respondent is a biogas digester adapter and y= 0 if respondent is not a biogas digester adapter. a coefficient indicates the impact of each independent variable on the outcome (dependent) variable adjusting for all other independent variables. the wald statistic is used to assess the contribution of individual predictors or the significance of individual coefficients in a given model. the results of the study presented in table 6 show that socioeconomic factors such as age, education, monthly family income, and per month cooking fuel cost were significantly contributed to the adaption of biogas digester. socioeconomic factors determine individual’s capacity to obtain information, know-how and perception towards the biogas technology benefits which in flip have an impact on one’s decision to adapt biogas digesters. facilitating factors such as number cattle owned, and number of poultry owned were also significantly associated with the adaption of biogas digester. the model can help describe the relative contribution of each independent variable to the dependent variable, controlling for influence of the other independent variables. the odds ratio (or) is a comparative measure of two odds relative to different events. it is a measure of association between an exposure and an outcome. the or represents the odds that an outcome will occur given a particular exposure compared to the odds of the outcome occurring in the absence of the exposure. the or can also be used to determine whether a particular exposure is a risk factor for a particular outcome, and to compare the magnitude of various risk factors for that outcome. or = 1 indicates exposure does not affect odds of outcome, or > 1 indicates exposure associated with higher odds of outcome. or< 1 indicates exposure with lower odds of outcome. the overall fit of the model can be assessed by chisquare statistic. the value of chi-square is significant indicating that at least one of the predictors was significantly related with the installation of biogas digester. the high value of sensitivity (76.4%) and specificity (84.6%) indicate a better fit of the model. 4. conclusion anaerobic digestion is a renewable energy source which can comfortably replace fossil fuel as an environment friendly process. the increasing demand for renewable energy compels the exploration of the increasing installation biogas digester especially in developing countries like bangladesh. biogas production addresses both waste reduction and energy production. the production of biogas is influenced by many factors and prominent among the factors are ph of feedstock, temperature, flow rate of feed and retention time. temperature suitable for high production biogas is persist in bangladesh. high potential feedstock for biogas production, cow dung and poultry droppings, are readily available in own households in rural areas of bangladesh. it is feasible to produce biogas from animal manure with simple equipment and a straight forward procedure. even women family members can maintain the biogas digesters in bangladesh. biogas digester adaptors are satisfied with their biogas digester and would like to advice others to adapt biogas digester. the cost for cooking by using biogas is significantly lower than the cost for cooking by using solid fuels. moreover, the process of biogas production is not merely source of energy, but also used as source of organic fertilizer. table 6: factors influencing installation of biogas digesters: logistic regression analysis variable coefficient standard error wald p-value odds ratio age 0.155 0.078 3.924 0.048 1.168 family size 0.080 0.104 0.587 0.444 1.083 religion −0.194 0.387 0.250 0.617 0.824 education 0.283 0.069 16.596 0.000 1.327 monthly income 0.158 0.059 7.224 0.007 1.171 fuel cost −0.429 0.042 104.716 0.000 0.651 number of cattle 0.971 0.105 86.191 0.000 2.641 number of poultry 1.121 0.292 14.732 0.000 3.069 constant −4.169 0.700 35.465 0.000 0.015 chi-square 43.155 p-value 0.000 correctly predicted user 76.4% correctly predicted non-user 84.6% overall percentage predicted 81.1% salam, et al.: feasibility study for biogas generation from household digesters in bangladesh: evidence from a household level survey international journal of energy economics and policy | vol 10 • issue 4 • 2020 29 it is observed from the results of the study that bangladesh is an ideal place to produce biogas. generation of biogas will meet the increasing demand of energy mainly for cooking and lighting. biogas production from various wastes through anerobic digestion technology is growing worldwide and is considered ideal in many ways due to its economic and environmental benefits. in bangladesh, the use of cow dung and poultry droppings for biogas generation is well established. however, the costs of only cow dung or poultry dropping digesters are not favorable due to their relatively low biogas yield in comparison with co-digestion with kitchen wastes. energy policy makers in bangladesh should encourage farmers to adapt new biogas digesters and to use co-digesting technology. successful implementation of anaerobic digestion as a method of waste treatment has the potential to change the concept waste into that of a valuable resource which will lead to total utilization of renewable energy resources reducing energy requirement, creating more jobs and income, reducing costs, making it readily available and minimize environmental pollution. references abebe, m.a. (2017), characterization of fruit and vegetable waste with cow dung for maximizing the biogas yield. international journal of scientific engineering and science, 1(1), 26-32. aragaw, t., andargie, m., gessesse, a. (2013), co-digestion of cattle manure with organic kitchen waste to increase biogas production using rumen fluid as inoculums. international journal of physical science, 8, 443-450. babel, s., pecharaply, s.j.a. (2009), anaerobic co-digestion of sewage and brewery sludge for biogas production and land application. international journal of environmental science and technology, 6(1), 131-140. bailis, r., drigo, r., ghilardi, a., masera, o. (2015), the carbon footprint of traditional woodfuels, nature climate change. new york, united states: macmillan publishers limited. chagunda, m.f., kamunda, c., miatho, j., mikeka, c., palamuleni, l. (2017), performance assessment of an improved cook stove (esperanza) in a typical domestic setting: implications for energy saving. energy, sustainability and society, 7, 4133. clements, j., trimborn, m., welland, p., amon, b. (2006), mitigation of greenhouse gas emission by anaerobic digestion of cattle slurry. agricultural, ecosystems, and environment, 112(2), 171-177. corro, g., paniagua, l., pal, u., banelos, f., rosas, m. (2013), generation of biogas from coffee-pulp and cow-dung co-digestion: infrared studies of post combustion emissions. energy conversion and management, 74, 471-481. das, a.k., sahoo, s.k., rana, s.k. (2018), sustainable conservation of kitchen wastes into fuels and organic fertilizer. international journal of engineering sciences and research technology, 7(5), 503-510. donald, l. (1998), biomass for renewable energy, fuels and chemicals. cambridge, massachusetts: academic press. available from: http:// www.envirofit.org/images/carbon/carbon_program_cameroon.pdf. efc, (2012). carbon programs: cameroon [online]. available from: http:// www.envirofit.org/images/carbon/carbon_program_cameroon.pdf erick, m.k., kirubi, g., muriuki, s. (2018), key factors influencing adoption of biogas technology in meru country, kenya. iosr journal of environmental science, toxicology and food technology, 12(3), 57-67. gashaw, a. (2014), anaerobic co-digestion of biodegradable municipal solid waste with human excreta for biogas production: a review. american journal of applied chemistry, 2(4), 55-62. gec. (2012), cookstove smoke is “largest environmental threat,” global health study finds. available from: http://www.energyblog. nationalgeographic.com/2012/12/13/cookstove-smoke-is-largestenvironmental-threat-global-heath-study-finds. ihme. (2017), findings from the global burden of disease study 2017. geneva: world health organization. mccarl, b.a. (2010), analysis of climate change implications for agriculture and forestry: an interdisciplinary effect. climate change, 1000(1), 119-124. meena, k., kumar, v., vijav, v.k. (2011), anaerobic technology harnessed fully by using different techniques: review. proceedings of 2011 ieee 1st conference on clean energy and technology cet. p8-82. mel, m., yong, a.s.h., ihsan, a.s.i, setyobudi, r.h. (2015), simulation study for economic analysis of biogas production from agricultural biomass. energy procedia, 65, 204-214. moller, h.b., sommer, s.g., ahring, b.k. (2004), biological degradation and greenhouse gas emission during pre-storage of liquid animal manure. journal of environmental quality, 33, 27-36. moller, h.b., sommer, s.g., ahring, b.k. (2004), methane productivity of manure, straw, and soild fractions of manure. biomass bioenergy, 26, 485-495. nges, i.a., liu, j. (2010), effects of solid retention time on anaerobic digestion of dewatered-sewage sludge in mesophilic and thermophilic conditions. renewable energy, 35, 2200-2206. nigel, b., john, m., albarak, r., morten, s., smith, r.k., lopez, v., west, c. (2004), impacts of improved stoves, house construction and child location on levels of indoor air pollution exposure in young guatemala children. journal of exposure analysis and environmental epidemiology, 14, 526-533. otun, t.f., ojo, o.m., ajibade, f.o., babatola, j.o. (2015), evaluation of biogas production from the digestion and co-digestion of animal waste, food waste and fruit waste. international journal of energy and environmental research, 3(3), 12-24. parawira, w., read, j.s., mattiasson, b., bijornsson, l. (2008), energy production from agricultural residues: high methane yields in pilot scale two-stag anerobic digestion. biomass and energy, 32, 44-50. phetyim, n., wanthong, t., kannika, p., supngam, a. (2015), biogas production from vegetable waste by using dog and cattle manure. energy procedia, 79, 436-441. prati, a.s., iqubal, m.s., saifullah, a.z.a., ahmed, k. (2013), current energy situation and comparative solar power possibility analysis for obtaining sustainable energy security in south asia. international journal scientific and technology research, 2(8), 1-6. available from: https://www.pdfs.semanticscholat.org/3cae/71b6006708f33 b9630d18dc2a0050b04a295.pdf. ren21 secretariat. (2013), renewable energy policy network for the the 21st century (ren21). renewables global status report: 2013 update report, no. 177. sagagi, b.s., garbu, b., usman, n.s. (2009), studies on biogas production from fruits and vegetable waste. bayero journal of pure and applied science, 2(1), 115-118. salam, m.a., alim, a. (2008), needs and challenges of improved cook stoves in bangladesh: an analysis from economic and health perspectives. in: theobald, r.h., editors. environmental management. united states: a book of nova publishers. p383-402. salam, m.a., alim, a. (2009), improved and traditional biofuel cookstoves and respiratory symptoms among women in bangladesh: a comparative study. journal of statistical studies, 28, 43-54. smith, k.r., uma, r., kishore, v.v.n., lata, k., joshi, v., zhang, j., khalil, m.a.k. (2000), greenhouse implications of household stoves: an analysis for india. annual review of energy and environment, 25, 741-763. salam, et al.: feasibility study for biogas generation from household digesters in bangladesh: evidence from a household level survey international journal of energy economics and policy | vol 10 • issue 4 • 202030 song, y.c., kwon, s.j., woo, j.h. (2004), mesophilic and thermophilic temperature co-phase anaerobic digestion compared with single-stage mesophilic and thermophilic digestion of sewage sludge. water and environmental research, 38(7), 1653-1662. suntrace. (2018), solar market brief. available from: https://www. suntrace.de/fieadmin/user_upload/suntrac_solar_market_brief_ bangladesh.pdf. un fao. (2013), faostat forestry production and trade. available from: http://www.faostat3.fao.org/faostat-gateway/go/to/ download/f/*/e. undp. (2019), sustainable development goals; goal 7: affordable and clean energy. available from: http://www.undp.org/content/undp/ en/home/sustainable development goals. usda. (2014), biogas opportunities roadmap: voluntary actions to reduce methane emissions and increase energy independence. united states: u.s. department of agriculture, u.s. environmental protection agency, u.s. department of energy. weiland, p. (2010), biogas production: current state and perspectives. applied microbiology and biotechnology, 85, 849-860. who. (2007), indoor air pollution: national burden of disease estimates. geneva: who press. who. (2016), clean household energy for health, sustainable development, and wellbeing of women and children. available from: http://www. apps.who.int/iris/bitstream/10665/204717/1/9789241565233_eng. pdf?uu=1. world bank. (2019), progress towards sustainable energy. available from: https://www.worldbank.org/en/topic/energy/publication/global. zahariev, a., dimo, p., anna, a. (2014), biogas from animal manureperspectives and barriers in bulgaria. annual research review in biology, 4(5), 709-719. . international journal of energy economics and policy | vol 10 • issue 4 • 2020212 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(4), 212-220. oil price fluctuation and health outcomes in an oil exporting country: evidence from nigeria gabriel oduyemi1*, taiwo owoeye2 1department of economics, tai solarin university of education, ijagun, nigeria, 2department of economics, ekiti state university, ado-ekiti, nigeria.*email: oduyemigo@tasued.edu.ng received: 21 january 2020 accepted: 28 april 2020 doi: https://doi.org/10.32479/ijeep.9266 abstract in oil exporting countries, government finance is heavily dependent on oil revenue and this tends to be highly volatile. this creates instability in output, terms of trade and fiscal balances, and lowers long-run growth rates and ultimately, social spending resulting into poor human development indicators. in nigeria, indices of human capital development are among the worst globally despite its position as the largest oil producer in africa. using time series data from 1980 to 2017, and the vector autoregressive model (var) estimates, this paper investigated how fluctuations in oil price affect health outcomes in nigeria. the main results indicate that oil price shocks are not detrimental to health outcomes. this reinforces the fact that oil price shocks are neither necessary nor sufficient to explain changes that happen in health outcomes in this country. it is the way the government spends its resource windfalls, and the way it adjusts spending during a downturn that is accountable for the poor health outcomes in the nigerian economy. the study therefore suggests strategic policies that supports fiscal prudence, minimizes macroeconomic distortions and improve health outcomes. this should be backed by adequate institutional capacity. keywords: oil price, fluctuation, health outcomes, human capital jel classifications: e32, e62, i15, q32 1. introduction education and health are both direct component of human wellbeing and a form of human capital that increases an individual’s capabilities (bloom and canning, 2003). grossman (1972) equally demonstrated that education and health are forms of human capital. bloom and canning (2000; 2003) observed that healthier individuals might affect the economy in four ways; one, they might be more productive at work and so earn higher incomes. two, they spend more time in the labor force, as less healthy people take sickness absence or retire early. three, they may invest more in their own education, which will increase their productivity, and four they may save more in expectation of a longer life— for example, for retirement—increasing the funds available for investment in the economy. health is indeed closely intertwined with economic growth and sustainable development such that investing in it brings substantial benefits for the economy through health outcomes. increase in health expenditure is expected to lead to better health outcomes (muysken et al., 2003), or as put by anyanwu et al. 2009; total health expenditures are important contributor to health outcomes. health outcome is the change in the health of an individual, group of people or population attributable to an intervention or series of interventions (asiedu et al., 2015). they represent how healthy a country is and assesses the quality of health care in the country. in oil exporting countries, government finance is heavily dependent on the oil sector and this tends to be highly volatile. such fluctuations often lead to volatile output, terms of trade this journal is licensed under a creative commons attribution 4.0 international license oduyemi and owoeye: oil price fluctuation and health outcomes in an oil exporting country: evidence from nigeria international journal of energy economics and policy | vol 10 • issue 4 • 2020 213 and fiscal balances which may lower long-run growth rates and ultimately, social spending, thereby making fiscal management more challenging in such countries with numerous important implications for their social spending and ultimately developmental indices. the first implication according to el anshasy (2009), is that the uncertainty about future oil revenues and it’s variability would result in changes in spending as the government reassesses its expected revenue stream, generating significant adjustment costs. therefore, the resulting pro-cyclicality of government spending adversely affects social spending and ultimately lower human development. secondly, oil exporting countries tend to have higher borrowing capacity during boom times. the accumulation of debt during times of plenty makes adjustment more costly and more difficult at times of scarcity because it implies larger adjustments (el anshasy, 2009). therefore, at times of oil price downturns, some oil economies may face foreign borrowing constraints, which would adversely hinder their development programs. in addition, this leaves the fiscal authorities with fewer options to finance their deficit. sharp expenditure cuts may become inevitable, potentially harming long-run growth. these may result in a decrease in per capita spending on health and other social sectors. evidence from previous latin america economic crises shows that governments tend to decrease social expenditures during times of economic recession (kirigia et al., 2011). indonesian experience indicates that health budget tends to be especially vulnerable to reductions during times of financial and economic crisis (kirigia et al., 2011). nigeria is the biggest african oil producer and the 13th largest producer in the world with oil earnings accounting for more than 90% of its exports, 70% of total revenue and only 8% of its gross domestic product (gdp) (cbn, 2018). yet, human development indicators for nigeria have been one of the worse among its peers (undp human development report, 2015). specifically, nigeria average life expectancy at 53 years, infant mortality rate at 115/1000 and child (under five) mortality rate at 205/1000 are worse than the average for sub-saharan africa (who, 2000; fmoh, 2001). who (2013) reports that one million nigerian children die at birth out of the nine million infant deaths recorded globally. the economist intelligence unit (2014) reports an outcome index of 35/100 for nigeria ranking it in the 14th position from the rear among 166 countries while its 2016 human development index is 0.527 ranking 151st among 188 nations. this study intends to contribute to the natural resource-human capital nexus of the resource curse discussion in development economics literature by exploring the transmission mechanism through which oil price fluctuation affects health outcomes in an oil exporting african country. the dynamic behaviors of oil price and revenue have received considerable attention in empirical literature. most of these studies however focused on industrialised countries. more importantly, limited efforts have been made with reference to the human capital explanations of this discourse. put differently, research on the impact of oil price shocks on sectorial performance of the economy, especially the health sector is limited. there is therefore the need to examine the subject of oil price dynamics from the health sector performance indicators perspective for an oil exporting african country. this study is important and unique for a number of reasons. firstly, it is the first attempt at addressing non-monetary welfare measures (health outcomes) effects of fiscal disequilibrium due to external shocks using datasets from nigeria. previous works on this subject have concentrated on money metric measures, particularly gdp, exchange rates and balance of payments position. (olomola and adejumo, 2006; shehu, 2009). secondly, this study improves on the previous study by covering period of major global oil shocks, low oil price, in recent times. specifically, it covers the period 1980-2017. this period is selected as it covers the era in which oil price witnessed major global shocks (1982-1999, 2007-2008 and 2014-2017) (andreas, 2016). the remaining part of this paper is structured as follows. section two presents some stylized facts on oil price and revenue fluctuation and health outcomes in nigeria comparing them to those of its selected peers as well as empirical and theoretical literature. section three discusses the methodology and presents the model, while section four discusses the results. section five concludes and suggests policy recommendations. 2. literature review 2.1. stylized facts on oil price fluctuation, oil revenue and health outcomes in nigeria according to chuku (2012), oil price shocks are unexpected and unpredictable changes in global oil prices, caused by exogenous factors, which are likely to impact on endogenously determined economic variables. crude oil price behaviour is determined by global supply and demand, activities of organization of the petroleum exporting countries (opec), geopolitical events and weather. five major episodes of oil price shocks could be identified during the study period. the first and most remarkable is traceable to the war between iran and iraq in september 1980 which drove oil prices up and lasted until october 1981 when opec officially set a benchmark price of $34 per barrel. according to hamilton (2003), this was followed by an increase in the wti price of oil from $36 per barrel in september to $38 in january 1981. the second shock in this period was a negative one that occurred in 1985-6 due to remarkable reductions in world aggregate. world oil market witnessed another shock in 1990 (zahra et al., 2011). this spike in price was as a direct result of the persian gulf war and iraq attack to kuwait as well as the higher demand for oil inventories in anticipation of a possible attack on saudi oil fields (kilian and murphy, 2014). in the late 1990s, the price of oil weakened further to an all-time low in recent history of $11, when only 2 years earlier oil had oduyemi and owoeye: oil price fluctuation and health outcomes in an oil exporting country: evidence from nigeria international journal of energy economics and policy | vol 10 • issue 4 • 2020214 been trading at $25. this slide was largely associated with reduced demand for crude oil, arguably caused by the asian financial crisis of mid-1997. the recovery of the global economy leading to higher demand for oil, some cuts in oil production, and increased inventory demand in anticipation of tightening oil markets all combined and kick-started the recovery in the price of oil in 1999. this trend was maintained till late 2002. according to hamilton (2008), between mid-2003 and mid-2008 the wti price climbed from $28 to $134/barrel. the widespread agreement is that this price surge was caused by a series of individually small increases in demand over the course of several years. as orders for industrial commodities worldwide were sharply curtailed in the second half of 2008 in anticipation of a major global recession, price of oil fell from $134/barrel in june 2008 to $39 in february 2009. when it became clear in 2009 that the collapse of the global financial system was not imminent, the demand for oil recovered to levels prevailing in 2007, and the price of oil stabilized near $100/barrel. finally, the period, 2010 through early 2015 also witnessed a number of smaller demand and supply shocks in the oil market. for example, events such as the libyan uprising in 2011 were associated with an increase in the price of oil. kilian and lee (2014) estimate that the libyan crisis caused an oil price increase of around $3 and $13/barrel. likewise, tensions with iran in 2012 account for an increase of between $1 and $9/barrel. following a long period of relative price stability, between june 2014 and january 2015 the brent price of oil fell from $112 to $47/barrel, providing yet another example of a sharp decline in the price of oil. since the discovery of oil in the late 1950s, oil revenue has become the dominant source of government revenue in nigeria accounting for about 90% of total exports, and this approximates to 80% of total government revenues (cbn, 2018). nigeria’s vulnerability to oil price shocks stems from the nations over dependence on crude oil export. this is amply evident from the drastic decline in non-oil exports over the past three decades of oil production in nigeria, thereby forcing the economy to follow the boom/bust cycles of the world oil market. for example, crude oil exports increased from 139.5 million barrels in 1966 to 807.7 million barrels in 1979. the volume of crude oil exports dropped to 390.5 million barrels in 1987 but increased to 675.3 million barrels in 1998. the trend continued for most years after 2000. in the same way, oil revenue increased from n166.6 million in 1970 to ₦8.35 billion in 1980 and then n 1,591,675.00 million and n6, 530,430.00 million in 2000 and 2008, oil revenue in 2012 was n8025.971 billion and in 2013 and 2014 were n6809.231 billion and n5403.51 billion respectively (nnpc statistical bulletin, 2014). this economic decline, especially during the last 20 years is illustrated by the fact that nigeria had declined from being a low middle income country and amongst the fifty richest countries in the world to one of the 30 poorest. as a result therefore, the nigeria health sector continues to experience persistently low funding below the world health organization (who) stipulated levels and is reported to devote the least percentage of her total expenditure to health when compared with other selected african countries (who, 2004). consequently, health facilities and services in nigeria deteriorated further and as such, health indicators are reported to be very low when compared with other poor and non-oil producing developing countries. among 191 member states of the united nations (un), whose overall health systems performance was assessed by the world health organization (who, 2000), nigeria was ranked in the 187th position. the term “health outcomes” refers to the impact healthcare activities have on people, on their symptoms and ultimately on whether they live or die. it includes whether a given disease process gets better or worse, what the costs of care are, and how satisfied patients are with the care they receive. it focuses not on what is done for patients but what results from what is done. the aspects considered by this study include among others, life expectancy and child/infant mortality. life expectancy at birth reflects the overall mortality level of a population. it summarizes the mortality pattern that prevails across all age groups children and adolescents, adults and the elderly and is defined as the number of years of life a person born today is expected to live or a measure of overall quality of life. it can also be thought of as indicating the potential return on investment in human capital (olowookere, 2015). it is the most commonly used measure to describe population health. child mortality rate (cmr) is the number of deaths of children under 5 years of age per 1000 live births in a given year. this is often distinguished from infant mortality rate (imr) which indicates the number of children, per 1000 live births, who die before they reach their first birthday. it may be very high in communities where health and social services are poorly developed. included in the child mortality (infant mortality inclusive) rate are the neonatal mortality rate (calculated from deaths occurring in the first 4 weeks of life), and post neonatal mortality rate (from deaths in the remainder of the 1st year). these indices are widely accepted as the most useful single measure of health status and important indicators of human development since they reveal both short-term and long-term outcomes of health spending and interventions. 2.2. theoretical literature the resource curse thesis has gained importance within the theoretical debate on natural resource. the theory claims that resource wealth is linked to poor economic growth (auty, 1993; sachs and warner 2001). the first and most compelling identified model explaining the resource curse theory is the dutch disease hypothesis, where exporting of primary commodities lead to appreciation in exchange rate and this in turn leads to a contraction of the tradable sector, krugman (1987). moreover, the natural resource-based industries in resource abundance countries usually pay higher wages than other manufacturing and agro-based industries and thus make it difficult for the latter to make profit leading to reallocation of factors of production from the manufacturing and agricultural sectors toward the booming sector, corden and neary (1982). since it is the manufacturing sector that is important in increasing return to scale while the agricultural sector exhibit positive externalities, this shifting away from competitive manufacturing sector would reduce the productivity and profitability of investment and therefore, affects economic growth negatively, wijnbergen (1984). oduyemi and owoeye: oil price fluctuation and health outcomes in an oil exporting country: evidence from nigeria international journal of energy economics and policy | vol 10 • issue 4 • 2020 215 the literature identifies three conduits by which the dutch disease affects an economy, namely, resource movement effect, spending effect and residual components and argues that resource-abundance may reduce the incentives to accumulate skills and investment in human resources. according to papyrakis (2006), natural resources reduce investment in skill-labor and high-quality education. gylfason (2001) found that natural resources crowd out human capital, therefore slowing the economic performance of natural resource-abundant countries. this hypothesis supports the human capital explanation for natural resource curse. 2.3. empirical literature oil price fluctuations have received considerable attention in empirical literature. among pioneer researchers is hamilton (1983), who studied oil prices and macro-economic variables for the us. other studies that supported and extended hamilton’s earlier work on the relationships between oil price increase and different macro-economic variables include burbidge and harrison (1984); gisser and goodwin (1986); mork (1989); hoover and perez (1994); federer (1996); lee et al. (1995); jimenezrodriguez and sanchez (2005). they analysed oil price impact on real economic activities. most of these earlier works on oil price and revenue volatility and economic activities however, relate to oil importing countries. others include gounder and bartleet (2007), muhammad (2010), jawad (2013), rafiq et al. (2009) for thailand; cunado and de gracia (2005) for six asian countries, including thailand, singapore, south korea, malaysia, phillipines and japan; jbir et al. (2008) for tunisia. existing studies on individual oil exporting economies include shehu (2009), who worked on nigeria and assessed the impact of oil price shock and real exchange rate volatility on real economic growth; olomola and adejumo (2006), who examined the effects of oil price shocks on output, inflation, real exchange rate and money supply in nigeria using quarterly data from 1970 to 2003. others include eltony and al-awadi (2001), who worked on oil price shocks and macroeconomic variables in kuwait, raguindin and reyes (2005) for the philippine, anshasy et al. (2005) for venezuela and sulaiman (2010), who analysed the impact of recent oil prices variability on pakistan’s export earnings. it should be observed that most of these studies focused on impacts of oil price fluctuations on macro-economic variables in either oil importing economies, industrialised countries or individual oil-exporting economies. this therefore implies that limited efforts have been made on the impact of oil price fluctuation on welfare in nigeria. such known efforts include bakare and fawehinmi (2010) who evaluated the extent to which oil revenues has affected standard of living in nigeria. the study used annual data for the period 1975-2008 and per capita income as a surrogate for living standard. the ordinary least square (ols) estimation technique on a multiple regression model was utilized. manasseh et al. (2018) investigated the impact of oil price fluctuation and oil revenue on well-being in nigeria using multiple regression techniques and the johanson cointegration test to analyse annual time series data covering the period 19812014. these studies however only concentrated their analysis on money metric measures of welfare and failed to explore the human capital explanations of this discourse on resource curse. thus, the current study adds to this empirical discourse by studying the subject of oil revenue dynamics using nonmonetary welfare measures (health outcomes) for oil exporters and not importers. there are a number of other advantages of using health outcomes instead of income as a measure of welfare (i) individual well-being in the form of life expectancy, maternal and infant health can be directly observed as opposed to country-wide well-being; (ii) money-metric comparisons of welfare over time are hampered by the absence of reliable and verifiable deflators, and information collected in surveys is often inadequate to solve this problem. 3. research methodology 3.1. theoretical framework 3.1.1. the hausmann and rigobon model the theoretical foundation for how booms in resource income would be associated with contractions in manufacturing was laid in the 1980s by two succesive influential studies (corden and neary, 1982; corden and neary, 1984). this theory would later become one of the basic foundations for the resource curse theory and it has spurned a rich body of empirical and theoretical literature (sachs and warner, 2001). for example, hausmann and rigobon (2002), argued that contractions in manufacturing cannot explain why a country will grow more slowly just because it has oil, but that the appropriate mechanism arises from an interaction between specialisation and financial market iumperfections. according to these authors, this result might help explain why countries that specialized in oil production such as saudi arabia, nigeria and venezuela fared so poorly when oil income declined while countries such as indonesia, mexico and norway were much less affected. the first group specialized in oil and when oil income declined that specialization became much more inefficient, while the lack of a tradable sector created a level of volatility and risk that did not allow for investment. they drew some interesting inferences from their theory thus: (i) specialization in the production of non-tradables creates an economy with more volatile relative prices. (ii) financial frictions interact with this volatility further specializing the economy as the stock of capital will respond to the greater macroeconomic volatility. (iii) this specialization may lead to the complete and inefficient disappearance of tradable production. (iv) this specialization reduces the investment in non-tradables which will face a larger cost of capital and lowers welfare. this clearly show, according to the last inference, that revenue fluctuation in resource revenue dependent economy has the tendency to lower the welfare of the citizens. 3.2. model specification following the theoretical model of hausmann and rigobon (2002), some set of variables affect fluctuations in oil price and health outcomes, while some are derivative of such oduyemi and owoeye: oil price fluctuation and health outcomes in an oil exporting country: evidence from nigeria international journal of energy economics and policy | vol 10 • issue 4 • 2020216 fluctuation. these include oil revenue, inflation rate which affects the household and the government, real gross domestic product (gdp) per capita, the share of health expenditure, market capitalization, non-oil export and exchange rate. the rationale behind the introduction of non-oil export and market capitalization into the model is to cater for specialization and financial market imperfections based on the argument advanced by hausmann and rigobon (2002). thus, the model for the estimation of the impact of oil price fluctuation on health outcomes can be stated as: lnho a blngdp clnop dlninf elnex flnmcap glnnoexp t t t t t t t � � � � � � � ��� ��t (1) equation (1) is the long-run determinants of health outcomes. the scale variable gdp measured by gdp is included to account for the level of economic activity in the oil exporting countries. op is the oil price and it is included to account for the shocks that are inherent in the product. inflation rate proxied by lninf is included to account for changes in the general price level. the exchange rate is also included to account for currency substitution and is measured by nominal effective value of the domestic currency of the country. lnmcap is measured by market capitalization and lnnoexp represents non-oil exports. two indicators were used as measures of health outcomes because they are the most widely used in the literature. these measures are the infant mortality rate (imr) and life expectancy rate. all data series are annual data and are sourced from the world bank’s world development indicators (wdi). 3.3. estimation techniques the study’s analysis begins with prior determination of unvaried properties of the series. thus, the data set were subjected to the standard augmented dickey-fuller (adf) and philip perron (pp) tests. the vector autoregressive model (var) involving impulse response and variance decomposition were used to estimate the study’s model. the var approach that this study utilizes to examine the interaction of oil prices and health allows an interaction between all the specified variables. the variables included in the var are health outcomes (ho), real gdp (gdp), oil price (op), inflation rate (inf), exchange rate (ex), market capitalization (mcap), non-oil export (noexp). the dynamic interactions of oil price shocks on health outcomes in oil exporting countries was estimated through the use of impulse response function (irf), and the effect and statistical significance of each variable’s response to one standard deviation increase in health outcomes was reported. the irf is given as; � � � �y y y yt t t p t p t� � � ��� �� � �� � � � �1 1 2 2 (2) also, the relative importance of health outcomes and oil price shocks in the var system was traced by using the variance decomposition analysis; this shows the percentage of change in a specific variable in connection with its own shock against the shocks to the remaining variables in the system. 4. presentation and discussion of empirical results 4.1. unit root result discussion 4.1.1. unit root results from table 1, the unit root test results show that oil price, inflation rate, market capitalization, non-oil export, gross domestic product, real per capita gdp and exchange were not significant at levels, thus the study could not reject the null hypothesis of unit root. however, the first difference of oil price, inflation rate, public health expenditure, market capitalization, non-oil export, gross domestic product, real per capita gdp and exchange rate were statistically significant at either 1 or 5% level of significance and the null hypothesis of unit root were rejected. the study therefore conclude that oil price, inflation rate, public health expenditure, market capitalization, non-oil export, gross domestic product, real per capita gdp and exchange rate were first difference variables using the augmented dickey-fuller and phillips-perron unit root tests. conversely, the study found mixed results for health outcomes variables, the augmented dickey fuller and the phillip-perron unit root shows that infant mortality and life expectancy were unit root stationary at levels. the results suggest that the variables could be i(0) and i(1) order of integration implying that they have different order of integration and this involves the use of autoregressive distributed lags (ardl) approach to cointegration where the two variables are involved. 4.2. vector autoregressive model results the study used the vector autoregressive (var) model to examine the magnitude of the impact of oil price fluctuations on health outcomes in nigeria. following equation 2, the study specifically employed the impulse response functions and variance decomposition of forecast errors. to have unbiased estimates, the study examined the appropriate lag length selection, this is followed by checking for the possibility of serial correlation in the chosen lag length. after this is the presentation of the impulse response function and the variance decomposition results. 4.2.1. lag order selection for var and autocorrelation the determination of appropriate lag length is critical in the analysis of var model, this is because a wrong lag length selection can affect substantially the interpretation of var estimates. table 1: summary of unit root test results variables at level first difference order of integrationadf pp adf pp oilp −2.100 −2.110 −6.026*** −6.026*** i(1) inf −1.274 −0.754 −2.889** 2.768** i(1) mcap −1.887 −2.121 −6.963*** −6.963*** i(1) noexp −2.883 −1.494 −4.705*** −8.039*** i(1) rgdp −3.154 −3.154 −4.909*** −4.906*** i(1) le −3.534** −3.819*** −2.592 −1.234 i(o) imr −2.987** −2.791** −0.899 −1.002 i(o) exr −1.211 −1.276 −5.179*** −5.179*** i(1) *, ** and *** indicate level of significance at 10, 5 and 1% respectively oduyemi and owoeye: oil price fluctuation and health outcomes in an oil exporting country: evidence from nigeria international journal of energy economics and policy | vol 10 • issue 4 • 2020 217 the selection criteria considered in this study are the akaike information criterion (aic), the schwarz information criterion (sic) and the hannan-quinn criterion (hqc). the study used lag 3 for the purpose of estimation and in addition, there is absence of serial correlation when lag 3 was selected. 4.2.2. impulse response function results the impulse response functions shows the direction, magnitude and the time path of health outcomes emanating from output growth, oil price, inflation rate, exchange rate, market capitalization and non-oil exports. from figure 1, a positive oil price shock leads to increase in life expectancy though not statistically significant. this implies that increases in oil price improve life expectancy in the country. life expectancy seems not to be sensitive to output growth and it does not respond positively to output growth shock. the study also discovered that a positive inflation shock results into a positive life expectancy shock for nigeria. this explains that during general price increases in nigeria, life expectancy increase. also exchange rate appreciation in response to macro shocks causes a positive life expectancy. the implication of these results is that life expectancy improves when exchange rate appreciates. the study also discovered that positive changes in stock market operations leads to an improvement in life expectancy whereas life expectancy respond positively to increases in non-oil exports in nigeria. thus, when there is an increase in market capitalization and non-oil exports, life expectancy of nigerians increases. from the impulse response function depicted by figure 2, the study discovered that positive oil price shocks leads to a no response changes in infant mortality in nigeria. infant mortality shows no significant response, that is, infant mortality seems to be constant in response to a positive output growth in nigeria. more so, infant mortality responded negatively to positive inflationary shocks. in essence, general price increases in nigeria improves infant mortality. furthermore, exchange rate shocks do not lead to increase or decrease in infant mortality but infant mortality responded negatively leading to a decline in market capitalization. finally, increase in nigerian non-oil exports marginally improves infant mortality. 4.2.2.1. variance decomposition results from table 2, the variance decomposition of life expectancy indicates that between 72 and 99% of the forecast error of life expectancy is accounted for by its own innovation in the first 4 years of estimation while the influence from its own shock fell gradually to 47 to 93% after the 20th year. fluctuations in output growth explained between 1 and 5% for nigeria. innovations in oil price 1-30%, while interest rates and exchange rates contributed between 1-7% and 1-3% respectively after a 10 year horizon. in addition, innovations in market capitalization and non-oil export are between 1-6% and 1-13% respectively. figure 1: nigeria impulse response function of life expectancy response to macroeconomic variables figure 2: nigeria impulse response function of infant mortality response to macroeconomic variables oduyemi and owoeye: oil price fluctuation and health outcomes in an oil exporting country: evidence from nigeria international journal of energy economics and policy | vol 10 • issue 4 • 2020218 also, the variance decomposition of infant mortality reported in table 3 indicates that between 32 and 97% of the forecast error of infant mortality is accounted for by its own innovation in the 4 year of estimation while the influence from its own shock fell gradually to 14 to 98% after the 10th year. the fluctuations in output growth explained about 1-27% of the forecast error variance in the infant mortality after the 10th year. innovations in oil price between 1 and 42% while interest rates and exchange rates contributed between 1-6% and 1-2% after a 10 year horizon. innovations in market capitalization and non-oil exports are between 1-7% and 1-7% respectively. 5. discussion of findings this study found that oil price is the most significant variable. in essence, higher oil prices tend to improve life expectancy and infant health in the short as well as in the long run and lower oil price does not retard health status. the implication of this finding is that oil price shocks are not detrimental to health outcomes. based on this fact, it is obvious that negative oil price shocks do not pose significant threat to health outcomes. this correlates with the findings of el anshasy (2009) who argued that oil price shocks are not detrimental to long run growth. therefore, it could be inferred that it is the way the government spends its resource windfalls, and the way it adjusts spending in a downturn that is accountable for the poor health outcomes in the nigerian economy. however, oil price fluctuation does not seem to trigger significant growth effect in nigeria. this reinforces the fact that oil price shocks are neither necessary nor sufficient to explain changes that happen in health outcomes in this country. this low response of health outcomes to oil price could be explained by many factors: one, investment share of gdp was low in nigeria. this implies that nigeria does not invest much. second, channeling some of the booming revenues to increase spending on infrastructure and public services tends to stimulate growth while government consumption in general tends to be less productive. in nigeria, government spending on infrastructures is poor and as such, oil rents have failed to promote development. the implication of this is that weak and poor institutional quality that encourages corruption and entrench autocratic regimes prevailed in nigeria, thereby exacerbating the problem of the resource curse. thirdly, oil price increases can harm countries with abundant oil but low refinery capacity. in such cases, an oil price change will lead to fuel price stabilisation policies such as fossil fuel subsidies, which affect the national budget negatively and generate adverse welfare effects. some analysts consider refinery capacity a significant factor of adverse effect of high oil prices. life expectancy improves when exchange rate appreciates. however, exchange rate shocks do not lead to increase or decrease in infant mortality. an appreciation can help improve living standards and consequently health outcomes through two possible channels; enabling consumers to buy cheaper imports including health facilities (medical equipment, personnel, and drugs) and therefore generate improved health outcomes. second is improvement in the current account through improved competitiveness. currency appreciation makes domestic goods more competitive, leading to stronger exports in the long term. additionally, with export prices more expensive, manufacturers have greater incentives to cut costs table 2: nigeria variance decomposition fraction of life expectancy variance due to years ahead llexpt lgdp loilp linf lexr lmcap lnonoilex 1 100.00 0.00 0.00 0.00 0.00 0.00 0.00 2 98.87 0.02 0.42 0.34 0.00 0.23 0.12 3 96.06 0.09 1.60 1.15 0.09 0.64 0.37 4 91.62 0.27 3.52 2.31 0.28 1.23 0.77 5 84.10 0.66 6.92 4.07 0.65 2.14 1.46 6 66.55 1.79 15.15 7.79 1.57 4.05 3.09 7 38.34 4.63 29.52 12.15 3.37 6.26 5.72 8 95.32 0.64 2.36 0.63 0.32 0.32 0.41 9 97.96 0.03 0.62 0.77 0.05 0.41 0.16 10 93.57 0.13 2.46 2.00 0.23 1.05 0.57 table 3: nigeria variance decomposition fraction of infant mortality variance due to years ahead linfm lgdp loilp linf lexr lmcap lnonoilex 1 100.00 0.00 0.00 0.00 0.00 0.00 0.00 2 90.67 3.69 3.56 0.15 0.34 0.11 1.48 3 99.22 0.41 0.18 0.06 0.05 0.02 0.07 4 97.34 1.24 0.90 0.01 0.04 0.07 0.39 5 98.65 0.78 0.39 0.00 0.00 0.04 0.12 6 98.27 0.93 0.55 0.00 0.01 0.05 0.19 7 98.43 0.87 0.48 0.00 0.00 0.05 0.16 8 98.37 0.89 0.51 0.00 0.01 0.05 0.17 9 98.39 0.89 0.50 0.00 0.00 0.05 0.17 10 98.39 0.89 0.50 0.00 0.01 0.05 0.17 oduyemi and owoeye: oil price fluctuation and health outcomes in an oil exporting country: evidence from nigeria international journal of energy economics and policy | vol 10 • issue 4 • 2020 219 to try and remain competitive. the joint effect of these could help improve the current account. per capita income exerted a strong negative influence on infant mortality for the period. its effect on life expectancy was also significantly positive. a positive significance of per capita income on health outcomes is plausible, for the simple reason that higher income permits households to have command over more goods and services, including health inputs which in turn improve the health of the household as well as living conditions for the population. in nigeria, the high significance of per capita income may be the result of insufficient financial allocation to health sector which compels individuals to spend on health needs from their own income. nigeria was reported to devote the least percentage of her total expenditure to health when compared with other selected african countries. as a result, health outcomes deteriorated. 6. conclusion and recommendations this study investigates the impact of oil price fluctuation on health outcomes in nigeria over the period 1980-2017. using the vector autoregressive model (var) involving impulse response and variance decomposition in the estimation, it was found that oil price shocks are not detrimental to health outcomes. therefore, oil price shocks are neither necessary nor sufficient to explain changes that happen in health outcomes in this country but the way the government spends its resource windfalls, and the way it adjusts spending in a downturn. thus, fiscal policy does play significant and important role in transmitting oil shocks to the economy. also, the nigerian health system is heavily reliant on out-of-pocket payments and government health sector spending in financing her health system both of which are components of government fiscal system which is dependent on oil revenue. when oil price fluctuation lead to currency appreciation, it can help improve living standards and consequently health outcomes through two possible channelsenabling consumers to buy cheaper imports and improvement in the current account through improved competitiveness. additionally, in nigeria, the high significance of per capita income may be the result of insufficient financial allocation to health sector which compels individuals to spend on health needs from their own income. the following recommendations are submitted in view of the identified issues regarding the transmission mechanism through which oil price fluctuation affects health outcomes among oil exporting african countries. aside from the oil stabilization fund, the country should establish and maintain a saving fund. the stabilisation function of oil funds addresses the short-term challenges of fiscal policy and aims to make the conduct of policy less volatile and less pro-cyclical by delinking public spending from oil prices. the savings function of oil funds addresses the long-term challenges of intergenerational equity and fiscal sustainability that accompany nonrenewable resources. the revenue from accumulated financial assets can replace income from oil once those resources are exhausted. the funds can also be drawn upon for capital spending where there is a high return. the authority should ensure a supportive and efficient socioeconomic structure for efficient utilization of resources. the delivery of basic health services can be greatly improved even with the current levels of resource commitments only if institutions in place ensure efficient use of resources. utilization of allocated resources in the health sector may depend largely on good governance and efficient institutions, and skilled manpower of the country. this therefore underscores the importance of the health system and other non-expenditure factors to facilitate the attainment of the health section of the mdg. this study therefore suggests improvement in human capital. the federal government of nigeria (fgn) should increase and restructure the public expenditure allocation to the health sector in order to provide more health facilities, drugs, laboratories, equipment, amongst other things. increasing government allocation and restructuring public expenditure on health could further spur the reduction of infant mortality and overall improve general health outcomes in the sub-saharan african region. it will help expand and enhance access to and use of primary healthcare services, in most rural areas especially for children below 12 months. references andreas, e., (2016), oil price shocks: a measure of the exogenous and endogenous supply shocks of crude oil. oxford: oxford institute for energy studies, oies paper: wpm 68. annual statistical bulletin nigerian. (2014), national petroleum corporation annual statistical bulletin. 1st ed. available from: http://www.nnpcgroup.com. anyanwu, j.c., erhijakpor, a.e.o. (2009), health expenditure and health outcomes in africa. african development review, 21(2), 400434. asiedu, e., gaekwad, n.b., nanivazo, m., nkusu, m., jin, y. (2015), on the impact of income per capita on health outcomes: is africa different? journal of economic literature, f23, d72. auty, r. (1993), sustaining development in mineral economies: the resource curse thesis. london: routledge. bakare, a.s., fawehinmi, f.o. (2010), an econometric study of the contribution of oil sector to the standard of living in nigeria. asian journal of business and management sciences, 1(3), 1-8. bloom, d.e., canning, d. (2000;2003), the health and wealth of nations. science, 287(5456), 1207-1209. burbidge, j., harrison, a. (1984), testing for the effect of oil price rise, using vector autoregression. international economic review, 25(1), 459-484. cbn. (2018), statistical bulletin. available from: http://www.statistics. cbn.gov.ng/statsonline. chuku, a.c. (2012), linear and asymmetric impacts of oil price shocks in an oil-importing and exporting economy: the case of nigeria. opec energy review, 36(4), 413-443. corden, j. (1982), booming sector and de-industrialization in a small open country. journal of development economics, 30(1), 71-92. corden, w.m., neary, j.p. (1982), booming sector and de-industrialization in a small open country. journal of development economics, 30(1), oduyemi and owoeye: oil price fluctuation and health outcomes in an oil exporting country: evidence from nigeria international journal of energy economics and policy | vol 10 • issue 4 • 2020220 71-92. corden, w.m., neary, j.p. (1984), booming sector and dutch disease economics: survey and consolidation. oxford economic papers new series, 36(3), 359-380. cunado, j., de gracia, f.p. (2005), oil prices, economic activity and inflation: evidence for some asian countries. the quarterly review of economics and finance, 45(1), 65-83. el anshasy, a. (2009), oil prices and economic growth in oil-exporting countries. college of business and economics, united arab emirates university: proceedings of the 32nd international iaee conference. el anshasy, a.a. (2010), oil prices and economic growth in oilexporting countries. united arab emirates: college of business and economics, united arab emirates university. eltony, m.n., al-awadi, m. (2001), oil price fluctuations and their impact on the macroeconomic variables of kuwait: a case study using a var model. international journal of energy research, 25(11), 939-959. fmoh. (2001), national reproductive health policy and strategy to achieve quality reproductive and sexual health for all nigerians. abuja: fmoh. gisser, m., goodwin, t.h. (1986), crude oil and the macroeconomy: tests of some popular notions. journal of money credit and banking, 18(1), 95-103. gounder, r., bartleet, m. (2007), oil price shocks and economic growth: evidence for new zealand. new zealand: paper presented at the new zealand association of economists annual conference, christ church. grossman, m. (1972), on the concept of health capital and the demand for health. journal of political economy, 80(2), 223-255. grossman, m. (2000), the human capital model. in: culyer, a.j., editor. handbook of health economics. vol. 1. netherlands: north holland. gylfason, t. (2001), natural resources, war ii. journal of political education and economic development, european economic review, 45(4-6), 847-859. hamilton, j.m. (1983), oil and the macroeconomy, since world war ii. journal of political economy, 91(1), 228-248. hamilton, j.d. (2003), what is an oil shock? journal of econometrics, 113(1), 363-398. hamilton, j.d. (2008), understanding crude oil prices. nber working paper series, 14492. hausmann, r., rigobon, r. (2002), an alternative interpretation of the resource curse. theory and policy implications. cambridge, ma: nber working paper series, no 9424. hoover, k.d., perez, s.j. (1994), post hoc ergo propter hoc once more: an evaluation of does monetary policy matter? in the spirit of james tobin. journal of monetary economics, 34(1), 89-99. jawad, m. (2013), oil price volatility and its impact on economic growth in pakistan. journal of finance and economics, 1(4), 62-68. jbir, r., zouari-ghorbel, s. (2008), recent oil price shocks and tunisian economy. energy policy, 37, 1041-1051. jimenez-rodriguez, r., sanchez, m. (2005), oil price shocks and real gdp growth: empirical evidence for some oecd countries. applied economics, 37(2), 201-228. kirigia, j.m., nganda, b.m., mwikisa, c.n., cardoso, b. (2011), effects of global financial crisis on funding for health development in nineteen countries of the who african region. vol. 11. bmc international health and human rights. available from: http://www. biomedcentral.com/1472-698x/11/4. kilian, l., lee, t. (2014), quantifying the speculative component in the real price of oil: the role of global oil inventories. journal of international money and finance, 42, 71-87. kilian, l., murphy, d. (2014), the role of inventories and speculative trading in the global market for crude oil. journal of applied econometrics, 29(3), 454-478. krugman, p. (1987), the narrow moving band, the dutch disease, and the competitive consequences of mrs. thatcher: notes on trade in the presence of dynamic scale economies. journal of development economics, 27(1-2), 41-55. lee, k., ni, s., ratti, r.a. (1995), oil shocks and the macroeconomy: the role of price variability. energy journal, 16(4), 39-56. manasseh, c.o., jonathan, o. (2019), oil price fluctuation, oil revenue and well-being in nigeria. international journal of energy economics and policy, 9(1), 346-355. mork, a.m. (1989), oil and the macroeconomy when prices go up and down an extension of hamilton’s results. journal of political economy, 97, 740-744. muhammad, s.d. (2010), the impact of oil prices volatility on export earning in pakistan. european journal of scientific research, 41(4), 543-550. olomola, p.a., adejumo, a.v. (2006), oil price shock and macroeconomic activities in nigeria. international research journal of finance and economics, 3, 28-34. olowookere, s. (2015), evaluating life expectancy in nigeria. the hope news. online newspaper. papyrakis, e. (2006), resource windfalls, investment and long-term income. resources policy, 31(2), 117-128. rafiq, s., salim, r., bloch, h. (2009), impact of crude oil price volatility on economic activities: an empirical investigation in the thai economy. resources policy, 34(3), 121-132. raguindin, c.e., reyes, r.g. (2005), the effects of oil price shocks on the philippine economy: avar approach, university of the philippines school of economics working paper. raguindin, reyes. (2005), the effects of oil price shocks on the philippine economy: a var approach. cambridge: university of the philippines school of economics working paper. sachs, j.d., warner, a.m. (2001), natural resources and economic development: the curse of natural resources. european economic review, 42, 827-838. shehu, a. (2009), oil price shock and macroeconomic activities in nigeria. international research journal of finance and economics, 3, 28-34. sulaiman, d.m. (2010), the euro-dollar exchange rate and pakistan economy. european journal of scientific research, 42(1), 6-15. the economist intelligence unit limited. (2014), health outcomes and cost: a 166-country comparison. new york: the economist intelligence unit limited undp human development report. (2015), work for human development. new york: undp human development report. who. (2000), world health report. geneva, switzerland: who. who. (2004), world health report. geneva, switzerland: who. who. (2013), world health statistics. geneva, switzerland: who. wijnbergen, s. (1984), the dutch disease: a disease after all. the economic journal 94(373):41-55. zahra, m.e., mahbooeh, j. (2011), oil price shocks and economic growth: evidence from opec and oecd. australian journal of basic and applied sciences, 5(6), 627-635. energy consumption and economic growth in vietnam: threshold cointegration and causality analysis international journal of energy economics and policy vol. 1, no. 1, 2011, pp. 1-17 www.econjournals.com energy consumption and economic growth in vietnam: threshold cointegration and causality analysis phung thanh binh environmental economics unit, faculty of development economics, university of economics, ho chi minh city, vietnam. email: ptbinh@ueh.edu.vn. abstract: this study investigates the energy consumption-growth nexus in vietnam. the causal relationship between the logarithm of per capita energy consumption (lpcec) and the logarithm of per capita gdp (lpcgdp) during the 1976-2010 period is examined using the threshold cointegration and vector error correction models for granger causality tests. the estimation results indicate that the lpcec and lpcgdp for vietnam are cointegrated and that there is a strong uni-directional causality running from lpcgdp to lpcec, but not vice versa. it is also found that the effect of lpcgdp on lpcec in vietnam is time-varying (i.e. significantly different between before and after the structural breakpoint, 1992). the research results strongly support the neoclassical perspective that energy consumption is not a limiting factor to economic growth in vietnam. accordingly, an important policy implication resulting from this analysis is that government can pursue the conservation energy policies that aim at curtailing energy use for environmental friendly development purposes without creating severe effects on economic growth. the energy should be efficiently allocated into more productive sectors of the economy. jel classification: q4 key words: energy consumption, economic growth, cointegration, granger causality, vietnam 1. introduction the high volatility of energy prices and increased greenhouse gas emissions have recently attracted attention from academics and policy-makers in terms of designing the energy conservation policy. this kind of policy can, however, not is arbitrarily enacted without considering the causal relationship between energy consumption and economic growth. in certain context, policy-makers must understand whether economic growth boosts energy consumption or whether energy consumption causes economic growth. and this issue has not been reached to a consensus among energy economists. the causal relationship between energy consumption and economic growth has been extensively investigated since the seminal paper of kraft and draft in 1978. different studies have done in different countries, time periods, and proxy variables using different econometric methodologies (ozturk, 2010). however, evidences from empirical researches are still mixed and controversial in terms of the direction of causality and the intensity of impact on energy policy. understanding the linkage between these two variables is extremely significant because energy policy implications mostly depend upon what kind of causal relationship exists. bartleet and gounder (2010) state that it’s more important to know whether energy consumption causes economic growth than the case where either economic growth promotes energy consumption or no causal relationship exists between them. the underlying reason of this justification is that it’s really difficult for policy-makers to enact energy conservation policies if a country is known as energy-dependent. in the presence of such a relationship, any structural policies that aim at reducing energy consumption might possibly slow economic growth (tsani, 2010). theoretically, an appropriate energy policy choice depends on the actual direction of the causal relationship between energy consumption and economic growth. ozturk (2010) and ozturk & acaravci (2010) sum up four possible hypotheses about energy-growth nexus. firstly, no causality between these variables is referred to as ‘neutrality hypothesis’. in other words, energy is assumed to be neutral to growth. if this is not a case, conservative or expansive policies on energy consumption could adversely affect economic growth. supporters of this view emphasize the role of substitution mailto:ptbinh@ueh.edu.vn energy consumption and economic growth in vietnam: threshold cointegration and causality analysis 2 and technological progress. according to belloumi (2009), the main reason for the neutral impact of energy on economic growth is that the cost of energy is negligible, so it is not likely to have a significant impact on economic growth. it has also been argued that the possible impact of energy consumption on growth will depend on the structure of the economy and the level of economic growth of the country concerned. as the economy grows, its production structure is likely to shift towards service sectors, which are not much dependent on energy (solow, 1974; and cheng, 1995). secondly, uni-directional causality from economic growth to energy consumption supports the ‘conservation hypothesis’. this implies that a country might implement the energy conservation policy without having any adverse effect on economic growth. thirdly, uni-directional causality from energy consumption to economic growth is commonly considered as ‘energy-led growth hypothesis’. within this situation, policy makers should pay special attention on restrictions of energy use because this action may, to which extent, impede economic growth. proponents of this hypothesis believe that energy is a critical input of production and plays as a complement to the basic factors of land, labour and capital. if this is a case, energy is said to be a limiting factor of economic growth (stern, 1993; and cleveland et al., 2000). finally, bi-directional causality between energy consumption and economic growth is known as ‘feedback hypothesis’. this provides an insight that energy consumption and economic growth are jointly determined and affected together. chen et al. (2007) explains the mixed findings from previous studies are due to differences in not only data set, econometric approaches, but also countries’ characteristics. for this reason, it’s very dangerous to design future energy policy of one country based on experiences of others. accordingly, a country-specific causality study between energy consumption and economic growth must be done to provide deep insights into design of energy policies. therefore, is it correct to believe in the statement of ‘energy for economic development’ stated by the vietnam energy industry? what is the evidence for the national energy development strategy that still provides special favour for energy sectors? a great number of causality studies have been conducted for many countries around the world; however, none have focused on the causal relationship between energy consumption and economic growth for vietnam. hence, it’s now necessary to examine this causal relationship in vietnam. this research aims at answering the following questions: (1) does long-term equilibrium exist between energy consumption and economic growth in vietnam? (2) is the energy consumption quickly adjusted to reach the long-run equilibrium if an instantaneous shock to its consumption occurs? (3) which of the above hypotheses is acceptable for the case of vietnam? the remainder of this paper is organized as follows: section 2 briefly reviews the literature on the energy-growth nexus. section 3 presents the data and methodology used. section 4 discusses the empirical results. we’ll then provide the policy implications and give conclusions in section 5. 2. literature review the relationship between energy consumption and economic growth has been theoretically investigated through two main different approaches. in the neoclassical growth models, energy is simply considered as an intermediate input of production (tsani, 2010). according to bartleet and gounder (2010), proponents of this view think that there are some mechanisms by which economic growth could remain in spite of a limited source of energy resources. the underlying explanation for this is built upon the possibility of technological change and substitution of other physical inputs for energy to use existing energy resources efficiently, and to generate renewable energy resources that are not subject to binding supply constraints (solow, 1974, 1997; stiglitz, 1997). accordingly, energy is merely one of the non-essential inputs in production process. in other words, the advocates of this theory support the ‘neutrality hypothesis’ and ‘conservation hypothesis’. these hypotheses imply that energy supply restrictions might not have any harmful effect on economic growth. thus, the government can simultaneously adopt the energy conservation and economic growth policies (bartleet and gounder, 2010). on the other hand, the ecological economic theory states that energy consumption is a limiting factor to economic growth, especially in modern economies. ecological economists judge that technological progress and other physical inputs could not possibly substitute the vital role of energy in production process (stern, 1993, 2000). they even consider energy as the prime source of value because other factors of production such as labour and capital cannot perform without energy (belloumi, 2009). the promoters of this perspective protect the so-called ‘growth hypothesis’, and international journal of energy economics and policy, vol. 1, no. 1, 2011, pp.1-17 3 hence, advise that any shock to energy supply will ultimately have a negative impact on economic growth. as a result, they are against the energy conservation policies. lots of empirical studies on energy consumption and economic growth nexus using different data set from different countries have so far provided various and contradictive results. the idea of causality between energy consumption and economic growth was first introduced in the seminal paper of kraft and kraft (1978) with the application of a standard version of granger causality (standard granger) test, which provided proof to support a uni-directional long-run relationship running from gross domestic product (gdp) to energy consumption for the usa over the 1947-74 period. this study suggests that government could pursue the energy conservation policies. on the other hand, by employing the sims causality technique, akarca and long (1980) showed no evidence of causality between energy consumption and gdp, so they criticized drastically the kraft and kraft’s result in terms of the temporal sample instability. since then, many academics have zealously joined the debate, but they have never reached the consensus (belloumi, 2009). in the same manner, yu and hwang (1984) took up the sims causality test with annual data and found no causality between energy consumption and gdp in the usa for the 1947-79 period. when using quarterly data with the same testing method, conversely, these authors discovered a uni-directional causality running from gross national product (gnp) to energy consumption in the usa for the 1973-81 period (belloumi, 2009). yu and choi (1985) employed the standard granger causality test for the 1954-1976 period to explore the causal linkages between gnp and various types of energy consumption for a set of countries. their empirical studies indicated that uni-directional causality running from economic growth to energy consumption for korea, uni-directional causality running from energy consumption to income for the philippines, while no causality existed in the usa, poland and uk. erol and yu (1987) employed both sims and granger causality tests and found unidirectional causality from energy consumption to income for west germany while bi-directional causality for italy, and no evidence of causality for uk, canada and france. besides, they also uncovered the uni-directional causality running from energy consumption to economic growth for japan over the 1950-1982 period. on the contrary, when the sample was restricted to the 1950-1973 period, this causal relationship was no longer significant. hwang and gum (1992) used the cointegration and error correction model, and the bi-directional causal relationship between energy consumption and economic growth was observed in taiwan for the period 1955-1993. by using the cointegration and error-correction version of granger causality test (ecm), cheng (1995) realized the presence of uni-directional causality running from economic growth to energy consumption in india. in addition, masih and masih (1996, 1997) found the existence of cointegration between energy and gdp in india, pakistan and indonesia, but non-cointegration in malaysia, singapore and the philippines. with the same data set, these authors applied the vector error correction model (vecm), and recognised a uni-directional causality running from energy consumption to income in india, a uni-directional causality running from economic growth to energy consumption in indonesia, and bi-directional causality in pakistan. this study also made use of the standard granger causality test for the non-cointegrated countries (including malaysia, singapore and the philippines), but did not find any granger causality. glasure and lee (1997) examined the causality between energy consumption and gdp for south korea and singapore and reported different results from different methodologies used. the standard granger causality tests revealed no causal relationship for south korea and a uni-directional causal relationship running from energy consumption to gdp for singapore, while the ecm model gave signal of bi-directional causality for both countries. cheng and lai (1997) applied hsiao’s version of granger causality to investigate the link between energy consumption and gdp for taiwan for 1955– 1993 period. this study showed that causality runs from gdp to energy consumption without feedback in taiwan. yang (2000) re-examined the causality between energy consumption and gdp for taiwan using updated data for the 1954–1997 period. the finding of this paper totally denies the findings of cheng and lai (1997) of unidirectional causality from gdp to energy consumption. they found evidences of bi-directional causality between energy consumption and gdp. asafu-adjaye (2000) tested the causal relationship between energy use and income in four asian countries (including india, indonesia, thailand and the philippines) using the ecm models. the test results indicated a uni-directional causality running from energy to income in india and indonesia, and a bi-directional causality in thailand and the philippines. aqeel and butt (2001) used the ecm models energy consumption and economic growth in vietnam: threshold cointegration and causality analysis 4 to investigate the causal relationship between energy consumption and economic growth as well as between energy consumption and employment for pakistan. the results inferred that economic growth caused total energy consumption. soytas and sari (2003) studied causality between energy consumption and gdp for the g7 countries and for the top 10 emerging economies. their research results found a bi-directional causality for argentina, uni-directional causality running from gdp to energy consumption in italy and korea, and uni-directional causality running from energy consumption to gdp in turkey, france, germany and japan. paul and bhattacharya (2004) re-examined the direction of causality between energy consumption and economic growth in india by employing the ecm model for the 1950–96 period. as a result, they realized that a bi-directional causality existed between energy consumption and economic growth. besides, they also applied the johansen cointegration testing approach and figured out the same direction of causality between energy consumption and economic growth. altinaya and karagol (2004) detected causality between the gdp and energy consumption in turkey employing the hsiao’s version of granger causality for the 1950–2000 period, characterized by structural break. the main conclusion of this study is that there is no evidence of causality between energy consumption and gdp in turkey based on the detrended series. lee (2005) investigated the cointegration and the causality relationship between energy consumption and gdp in 18 developing countries, using data for the 1975–2001 period and employing panel unit root tests, heterogeneous panel cointegration and panel ecm models. the empirical results supported a long-run cointegration relationship between energy consumption and gdp after allowing for the heterogeneous country effects. the evidence illustrated that there were only long-run and short-run causalities running from energy consumption to gdp. this result suggested that energy conservation policies might, to which extent, harm economic growth in developing countries. wolde-rufael (2005) ran a cointegration and a modified version of the granger causality test to investigate the long-run and causal relationship between per capita gdp and per capita energy use for 19 african countries for the 1971–2001 period. their results offered further evidence of the long-run relationship for eight out of the nineteen countries and causality for twelve out of nineteen countries. mehrara (2007) examined the causal relationship between the per capita energy consumption and the per capita gdp in a group of eleven oil-exporting countries (including iran, kuwait, saudi arabia, united arab emirates, bahrain, oman, algeria, nigeria, mexico, venezuela and ecuador) by using panel unit root tests and panel cointegration tests. the test results found a uni-directional causality running from economic growth to energy consumption for these oil-exporting countries. interestingly, the results recommened that energy conservation policies through reforming energy prices could not have any adverse effect on economic growth. chiou-wei et al. (2008) conducted both linear and nonlinear granger causality tests to examine the causal relationship between energy consumption and economic growth for a panel of asian newly industrialized countries as well as the usa for the 1954–2006 period. their study again supported a neutrality hypothesis for the usa, thailand, and south korea. moreover, they unearthed the existence of a uni-directional causality running from economic growth to energy consumption for philippines and singapore while energy consumption might have negative effects on economic growth for taiwan, hong kong, malaysia and indonesia. chontanawat et al. (2008) tested for causality between energy and gdp using a consistent data set and granger test for thirty oecd countries and seventy non-oecd countries. they discovered that causality running from energy to gdp appeared to be more prevalent in the developed oecd countries. tsani (2010) studied the causal relationship between aggregated and disaggregated levels of energy consumption and economic growth in greece for the 1960–2006 period by using the methodology proposed by toda and yamamoto (1995). at the aggregated levels of energy consumption, the empirical findings suggested the presence of a uni-directional causality running from total energy consumption to real gdp. at the disaggregated levels, the results indicated a bidirectional causal relationship between industrial and residential energy consumption to real gdp, and no causality between transport energy consumption and real gdp. the energy policy implication from these findings focused on the demand side and energy efficiency improvements in order to put less impact on economic growth. international journal of energy economics and policy, vol. 1, no. 1, 2011, pp.1-17 5 esso (2010) investigated the cointegration and causal relationship between energy consumption and economic growth in seven sub-saharan countries over the 1970–2007 period. this study used the gregory and hansen (1996b) threshold cointegration approach and the toda and yamamoto (1995) version of granger causality test. the test results revealed that energy consumption was cointegrated with economic growth in cameroon, cote d'ivoire, ghana, nigeria and south africa in the presence of a structural break. moreover, threshold cointegration test and ecm models suggested that economic growth had a significant positive long-run impact on energy consumption in these countries before 1988 while this effect was negative after the breakpoint, 1988, for ghana and south africa. furthermore, granger-causality tests suggested a bi-directional causality between energy consumption and real gdp in cote d'ivoire and a uni-directional causality running from real gdp to energy consumption in the case of congo and ghana. by using the recently developed autoregressive distributed lag (ardl) bounds testing approach of cointegration and dynamic vector error correction (vecm) model for four eastern european countries, ozturk and acaravci (2010) figured out that there is weak evidence about the long-run and causal relationships between energy consumption (or electric power consumption) and economic growth. specifically, they found that evidence of cointegration and bi-directional strong granger causality between these variables is only found in hungary for the 1980-2006 period. this study contributes not only the proof of causality, but the methodology used. the authors explained clearly the ardl bounds testing approach used in the energy-growth linkage. in addition, ozturk et al. (2010) employed the panel cointegration and causality analysis to investigate the differences in energy consumption and economic growth relationship among three groups of 51 countries classified as low income countries, lower middle income countries, and upper middle income countries for the 19712005 period. the test results indicate that there exists cointegration between energy consumption and real gdp for all three income groups. from the panel causality tests, they conclude that there is a long-run granger causality running from gdp to energy consumption for low income countries and bi-directional granger causality between these variables for the other groups. furthermore, these authors also provide evidence that there is no strong relation between energy consumption and economic growth in these countries. in summary, a general judgment is that the results are still mixed: that is, while some studies find causality running from economic growth to energy consumption, others figure out causality running from energy consumption to economic growth and even some studies suggest no causality and/or bidirectional causality between these two variables. the differences among these studies lie on the specific country characteristics, sample periods, research methodologies, and proxy variables. 3. data and methodology 3.1 data collection and unit root tests this paper uses the time series data of per capita gdp (pcgdp) and per capita energy consumption (pcec) for the 1976-2010 period in vietnam. data are obtained from three sources: (i) the world development indicators (2011); (ii) international financial statistics (2011); and the vietnam’s general statistics office. in this study, per capita energy consumption is expressed in terms of kg oil equivalent and per capita gdp is expressed in constant 2000 us$. the choice of the starting period was constrained by the availability of data and the historical milestone as well. the vietnam war ended in 1975, and the country was united in 1976. the trends of pcgdp and pcec for vietnam are graphically depicted in figure 1. it’s noted that all variables are transformed into natural logarithms in order to reduce heteroskedasticity and obtain the growth rate of the relevant variables by their differenced logarithms (orturk and acaravci, 2010). it seems that there might be a structural break in these series around the year 1991. by using the quandt-andrews breakpoint test, we recognize that the pcgdp is broken at the year 1992, while the pcec at the year 1993. these breakpoints are depicted in figure 2 and 3. this fact might, to which extent, imply that pcgdp causes pcec. the final answer will, however, be clear after performing granger causality tests presented in the empirical results. these figures also indicate that both series have increasingly grown since these breakpoints. energy consumption and economic growth in vietnam: threshold cointegration and causality analysis 6 200 300 400 500 600 700 800 900 1980 1985 1990 1995 2000 2005 2010 pcec pcgdp figure 1: vietnam's per capita energy consumption and per capita gdp 300 350 400 450 500 550 600 650 700 750 1980 1985 1990 1995 2000 2005 2010 pcec pcecf figure 2: fitted trend of per capita energy consumption 1993 international journal of energy economics and policy, vol. 1, no. 1, 2011, pp.1-17 7 200 300 400 500 600 700 800 900 1980 1985 1990 1995 2000 2005 2010 pcgdp pcgdpf figure 3: fitted trend of per capita gdp 1992 in order to establish the order of integration of the variables concerned, this study first employs the conventional unit root tests widely known as the augmented dickey-fuller (adf) and phillips-perron (pp) unit root tests. generally, a variable is said to be integrated of order d, written by i(d), if it turns out to be stationary after differencing d times. the variable is integrated of order greater than or equal to 1 is non-stationary. according to asteriou and hall (2007), most economic variables are cointegrated of order 1. in testing for the existence of a unit root of the time series yt (h0: δ = 0), we can select one out of the following three possible forms of the adf test (yt can be either lpcect or lpcgdpt): ∑ = −− ++= p 1i titi1tt uyyy ∆βδ∆ (1) ∑ = −− +++= p 1i titi1t0t uyyy ∆βδα∆ (2) ∑ = −− ++++= p 1i titi1t10t uyyty ∆βδαα∆ (3) the difference between the three regressions concerns the presence of the deterministic elements α0 and α1t. for choosing the best one among the three equations, we will first plot the data (of each series) and then observe the graph because it can, to which extent, indicate the presence or not of the deterministic trend regressors. esso (2010) states a break in the deterministic trend affects the outcome of unit root tests because many previous studies have found that the conventional unit root tests fail to reject the unit root hypothesis for series that are actually trend stationary with a structural break. perron (1989) showed that a dickey and fuller (1979) type test for unit root is not consistent if the alternative is that of a stationary noise component with a break in the slope of the deterministic trend. his main point is that the existence of exogenous shock which has a permanent effect will lead to a non-rejection of the unit root hypothesis even though it is true. perron (1989) proposed a unit root test allowing for a structural break with three alternative models: crash model (i.e., shift in the intercept), changing growth model (i.e., change in the slope) and the change both in the intercept and the slope. several studies have found that the conventional unit root tests fail to reject the unit root hypothesis for the series that are actually trend stationary with a structural break. on the other hand, the perron (1989) test has been energy consumption and economic growth in vietnam: threshold cointegration and causality analysis 8 generally criticized for treating the time of break as exogenous (i.e., the time of break is known a priori). (christiano, 1992; and altinay and karagol, 2004). zivot and andrews (1992) further developed the perron unit root tests that consider the breakpoint (τb) as endogenous. to test for a unit root against the alternative of trend stationarity process with a structural break both in slope and intercept, the following regressions are used: ∑ = −− +++++= p 1i titi1tbtt uyyt)(duy ∆ϕαβτθµ (4) ∑ = −− +++++= p 1i titi1tbtt uyyt)(dty ∆ϕαβτγµ (5) ∑ = −− ++++++= p 1i titi1tbtbtt uyy)(dtt)(duy ∆ϕατγβτθµ (6) where dut and dtt are dummy variables for a mean shift and a trend shift respectively; dut(τb) = 1 if t > τb and 0 otherwise, and dtt(τb) = tτb if t > τb and 0 otherwise. in other words, dut is a sustained dummy variable that captures a shift in the intercept, and dtt represents a shift in the trend occurring at time τb. the breakpoint τb can be found by using the quandt-andrews breakpoint test. the optimal lag length p is also determined by using the general to specific approach so as to minimize the aic or sic. the zivot and andrews (1992) unit root test suggests that we reject the null hypothesis of a unit root if computed α̂t is less than the left-tail critical t value. 3.2 cointegration analysis once the order of integration of each variable is established, we then evaluate whether the variables under consideration is cointegrated. according to engle and granger (1987), a linear combination of two or more nonstationary series (with the same order of integration) may be stationary. if such a stationary linear combination exists, the series are considered to be cointegrated and long-run equilibrium relationships exist. thanks to the existence of cointegration, although the series are individually nonstationary, they cannot drift farther away form each other arbitrarily. cointegration implies that causality exists between the two variables, but it does not indicate the direction of the causal relationship. the presence of cointegration among the variables rules out the possibility of ‘spurious’ regression (belloumi, 2010). there are various approaches to test for cointegration, say, engle and granger approach, johansen approach, ardl bounds testing approach (by pesaran et al., 2001), and gregory and hansen approach. according to belloumi (2010), the bivariate approach of engle and granger is very restrictive because it can be applied only if there is one cointegrating relation. and the most commonly used method is the johansen cointegration test based on the autoregressive representation discussed by johansen (1988) and johansen and juselius (1990). this test determines the number of cointegrating equations for any normalization used. it provides two different likelihood ratio tests; one is based on the trace statistic and the other on the maximum eigenvalue. esso (2010) states that the cointegration framework of engle and granger (1987), and johansen (1988) has its limitations especially when dealing with economic data containing the structural breaks. in this case, we tend to reject the hypothesis of cointegration, albeit one with stable cointegrating parameters. the reason is that the residuals from cointegrating regressions capture unaccounted breaks and thus typically exhibit nonstationary behaviour. therefore, it’s necessarily to employ the non-linear techniques for testing cointegration if the economic data has structural breaks. one of the widely used methods is the gregory and hansen (1996a,b) threshold cointegration test. and the test equation is expressed as below: tbtt2t1bt21bt21t u)(duxx)(dutt)(duy +⋅++⋅+++= ταατββτµµ (7) tbtt2t1bt21bt21t u)(duyy)(dutt)(dux +⋅++⋅+++= ταατββτµµ (8) where µ1 and µ2 represent the intercept before the shift and the change in the intercept at the time of the shift; β1 and β2 are respectively the trend slope before the shift, the change in the trend slope at the time of the shift; α1 is the cointegrating slope coefficient before the regime shift, α2 denotes the change in the cointegrating slope coefficient at the time of the regime shift; yt and xt denote lpcect and lpcgdpt. the standard methods to test the null hypothesis of no cointegration are residual-based. international journal of energy economics and policy, vol. 1, no. 1, 2011, pp.1-17 9 the equations (7) and (8) are estimated by ols method, and the unit root tests are applied to the regression errors (gregory and hansen, 1996a). 3.3 granger causality analysis let’s denote lpcect and lpcgdpt for the natural logarithms of the corresponding energy consumption and real gdp per capita respectively; and suppose that lpcect and lpcgdpt are both integrated of order 1, the var model developed by granger (1969) can be defined as: t1 q 1j jtj p 1i itit ulpcgdplpceclpcec +++= ∑∑ = − = − ∆γ∆βα∆ (9) t2 q 1j jtj p 1i itit ulpceclpcgdplpcgdp +++= ∑∑ = − = − ∆δ∆θϕ∆ (10) this study use the akaike’s information criterion (aic) and schwarz’s bayesian criterion (sbc) to determine the optimal lag length of ∆lpcect and ∆lpcgdpt. the equations (9) and (10) are first estimated by ols method, and then we apply the normal f wald test for the joint significance of the coefficients on the lagged terms in the unrestricted models. specifically, the following null hypotheses are necessarily tested: nconsumptioenergy causegranger not doesgrowth economicor 0 :h )a( q 1j j0 ∑ = =γ growth economic causegranger not doesn consumptioenergy or 0 :h )b( q 1j j0 ∑ = =δ it is possible to have that (a) energy consumption causes economic growth (reject b, but do not reject a), (b) economic growth causes energy consumption (reject a, but do not reject b), (c) there is a bi-directional feedback between energy consumption and economic growth (reject a and b), and (c) energy consumption and economic growth are independent (do not reject a and b). according to mehrara (2007), the most popular method for granger causality tests, is based on the vecm if variables are cointegrated. the vecm can avoid shortcomings of the var based models in distinguishing between a longand a short-run relationship among the variables. theoretically, cointegration implies the existence of causality between variables, but it does not indicate the direction of the causal relationship. the vecm is estimated by using the following var model: t1 q 1j jtj p 1i iti1t,11t ulpcgdplpcecectlpcec ++++= ∑∑ = − = −− ∆γ∆βπα∆ (11) t2 q 1j jtj p 1i iti1t,22t ulpceclpcgdpectlpcgdp ++++= ∑∑ = − = −− ∆δ∆θπϕ∆ (12) where the error correction term (ectt-1) is derived from the long-run cointegration relationship and measures the magnitude of the past disequilibrium. the coefficients, π of the ectt-1 represent the deviation of the dependent variables from the long-run equilibrium. within this vecm model, we can examine whether the relationship between energy consumption and economic growth is weak granger causality, long-run granger causality, or strong granger causality. the weak granger causality exists if we can find the short-run relationship between energy consumption and economic growth which is based on the normal f wald test for the joint significance of the coefficients on the lagged terms in the unrestricted models (equation (11) and (12)) in the same manner as the null hypotheses (a) and (b). the long-run causality can be tested by looking at the significance of the speed of adjustment, which is the coefficient of the error correction term. this is easily based on the t statistic. specifically, we must test the following null hypotheses: run-long in thecausality -nongranger or 0 :h )c( 10 =π run-long in thecausality -nongranger or 0 :h )d( 20 =π according to belloumi (2010), the significance of ‘π’ indicates that the long-run equilibrium relationship is directly driving the dependent variable. if π, say, in equation (11) is zero, then it can be implied that the change in energy consumption does not respond to deviation in the long-run equilibrium for the t-1 period. energy consumption and economic growth in vietnam: threshold cointegration and causality analysis 10 the strong granger causality between energy consumption and economic growth, which is based on the normal f wald test for joint significance of both the coefficient associated with the ectt-1 and the coefficients on the lagged terms in the unrestricted models (equation (11) and (12)) as follows: nconsumptioenergy causestrongly not doesgrowth economicor 0 :h )c( q 1j j10 ∑ = == γπ growth economic causesstrongly not doesn consumptioenergy or 0 :h )d( q 1j j20 ∑ = == δπ above models could include dummy variables in order to take into account the existence of the possible structural breaks during the study sample. in addition, we sometimes include the trend variable if there is the existence of deterministic trend in the relationship between energy consumption and economic growth. these inclusions depend on the actual data property. 4. empirical results 4.1 unit root tests the high coefficient of correlation between two variables (0.98) does not imply cointegration. according to granger (1988), the condition for cointegration is that each of the variables should be integrated of the same order (more than zero) or that both series should contain a deterministic trend (belloumi, 2010). table 1 reports the results of the standard unit root tests (adf and pp) on the integration properties of the lpcec and lpcgdp variables for vietnam. because the actual values of these series exhibit trends, so all unit root test regressions include constant and trend terms. the test results suggest that none of the series are stationary at any levels and only the lpcec series is stationary in its first difference. on the other hand, the test results seem not much different between lpcgdp and its first difference. the reason for this situation is that because the series are basically characterized by structural breaks, so the adf and pp tests may be suspect. therefore, we have to employ the zivot and andrews (1992) unit root tests. table 1: unit root test results using adf and pp variable adf pp level first difference level first difference lpcec -0.58 -5.25* -0.60 -5.25* lpcgdp -2.48 -1.98 -2.51 -2.04 1% critical value -4.26 -4.26 -4.25 -4.25 5% critical value -3.55 -3.55 -3.55 -3.55 10% critical value -3.20 -3.20 -3.20 -3.20 note: * indicates significance at 1% level. the null hypothesis of the zivot and andrews (1992) is α = 1, i.e., a unit root, against the alternative that the series are trend stationary process with a structural break. the estimated regressions that yield the minimum α̂t statistic with the optimum number of k regressors are presented in table 2. as can be seen from this table, there is sufficient evidence against the unit root hypothesis for the first differenced series. in other words, the lpcec and lpcgdp variables are now said to be individually i(1). table 2: unit root test results using zivot and andrews (1992) variable za (1992) level first difference lpcec -3.13 (0) -6.29***(0) lpcgdp -3.01 (1) -3.95* (0) note: the numbers in parentheses are the lag order. the lag parameters are selected based on the aic. *** and * indicate significance at the 1% and 10% levels respectively. 4.2 cointegration tests applying the engle and granger cointegration approach discussed in section 3.2, we obtain the results as shown in table 3. residuals obtained from ols regressions between lpcec and lpcgdp is then tested by using the adf and pp tests. the test results indicate that there seems to be no international journal of energy economics and policy, vol. 1, no. 1, 2011, pp.1-17 11 cointegrating relationship between the two variables. this approach, however, is very restrictive because it cannot deal properly with economic data containing the structural breaks. therefore, it’s hard to have any conclusion about the cointegration between these variables from this simplified test. table 3: unit root tests for residuals (engle and granger) using adf and pp from equation adf pp lpcec = f(lpcgdp) -1.15 -1.31 1% critical value -2.63 -2.63 5% critical value -1.95 -1.95 10% critical value -1.61 -1.61 we then employ the johansen approach for testing cointegration between lpcec and lpcgdp. before performing the johansen cointegration tests, this study uses the aic to determine the optimum lag length. as a result, the optimum lag length is 6. in these tests, we denote the number of cointegrating vectors by r0; the trace test is calculated under the null hypothesis h0: r0 ≤ r, and the alternate hypothesis h1: r0 > r; and the maximum eigenvalue test is calculated under the null hypothesis h0: r0 = r, and the alternate hypothesis h1: r0 > r. the test results are presented in table 4 and table 5. if the test statistic is greater than the critical value at a given level of significance, we reject the null hypothesis, and vice versa. table 4: johansen cointegration estimation results between pcec and pcgdp rank test (trace) model 2 ( intercept (no trend) in ce, no intercept or trend in var) number of cointegration eigenvalue trace statistic 5% critical value none 0.554 27.13 20.27 at most 1 0.149 4.54 9.16 model 3 (intercept in ce and var, no trend in ce and var) none 0.542 21.89 15.87 at most 1 0.000 0.017 3.84 model 4 (intercept in ce and var, linear trend in ce, no trend in var) none 0.554 36.35 25.87 at most 1 0.388 13.73 12.52 these tests indicate clearly that all null hypotheses (r0 ≤ 0 for trace statistic, and r0 = 0 for maximum eigenvalue statistic) are rejected at the 5% level of significance. thus, we can reject the hypothesis of no cointegrating equation between energy consumption and economic growth at the 5% significance level. however, under the null hypothesis (r0 ≤ 1 for trace statistic, and r0 = 1 for maximum eigenvalue statistic), both maximum eigenvalue statistic and trace statistic are below the 5% level of significance. accordingly, energy consumption and economic growth are said to be cointegrated at 5% level of significance. as a result, there must be a long-run relationship between per capita energy consumption and economic growth for vietnam in the sample period. table 5: johansen cointegration estimation results between pcec and pcgdp rank test (maximum eigenvalue) model 2 (intercept (no trend) in ce, no intercept or trend in var) number of cointegration eigenvalue max-eigen statistic 5% critical value none 0.554 22.88 15.89 at most 1 0.149 4.54 9.16 model 3 (intercept in ce and var, no trend in ce and var) none 0.542 21.88 14.26 at most 1 0.000 0.017 3.84 model 4( intercept in ce and var, linear trend in ce, no trend in var) none 0.554 22.62 19.38 at most 1 0.387 13.73 12.52 as we believe that the sample series contain structural breaks, we apply the threshold cointegration approach proposed by gregory and hansen (1996a,b) to make sure the above johansen cointegration tests. we first estimate the regression equations (7) and (8), then obtain the residuals. we energy consumption and economic growth in vietnam: threshold cointegration and causality analysis 12 also plot line graph and correlogram of the residuals in a priori to recognize the stationarity of the series. the results of the residual-based unit root tests presented in table 6 indicate that there really exists a cointegrating equation between energy consumption and economic growth. table 6: unit root tests for residuals (threshold cointegration) using adf and pp from equation adf pp lpcec = f(dut, t, lpcgdp, lpcgdp*dut) -4.24 -4.36 lpcgdp = f(dut, t, t*dut, lpcec, lpcec*dut) -4.50 -3.47 1% critical value -2.63 -2.63 5% critical value -1.95 -1.95 10% critical value -1.61 -1.61 4.3 granger causality tests it’s already known that cointegration implies the existence of granger causality, but it does not indicate the direction of the causality relationship. according to altinay and karagol (2004), taking the first differences of the series with structural breaks to achieve stationarity may lead to spurious results. in this case, they suggest that stationary series can be obtained by detrending the series taking the estimated breakpoints into consideration through the following regression: tlpcectdtt)b(tdutlpcec ~ ++++= αβτδµ (13) tlpcgdptdtt)b(tdutlpcgdp ~ ++++= αβτδµ (14) where tlpcec ~ and tlpcgdp ~ are detrended stationary series. this alternative could be appropriate if we just consider the short-run relationship between two variables of interest. therefore, this might not be the best choice of this empirical study. in order to investigate the direction of causality between energy consumption and economic growth for vietnam, this section employs the vecm models because the properties of these series are completely satisfactory. in order to specify the proper vecm models, we should now consider two important things. first, it’s necessary to understand whether the first differences of the two series exhibit deterministic trend. in doing so, we simply have a look at the line graphs depicted in figure 4. and the result is quite straightforward. accordingly, the most specified vecm models can be written as follows: t1 q 1j jtj p 1i iti1t,1110t ulpcgdplpcececttlpcec +++++= ∑∑ = − = −− ∆γ∆βπαα∆ (15) t2 q 1j jtj p 1i iti1t,2210t ulpceclpcgdpecttlpcgdp +++++= ∑∑ = − = −− ∆δ∆θπϕϕ∆ (16) where ect1,t-1 and ect2,t-1 are the equilibrium error lagged one period, obtained from the threshold cointegrating equations. since all variables are stationary, so the ols method is reliable for estimating equations (15) and (16). the long-run effects of economic growth on energy consumption and vice versa are provided by table 7 (cointegrating equations), and estimates for the dynamic relationship between these two variables are represented in table 8 (vecm equations). second, we have to specify the optimum lag length of the var model based on the minimum akaike information criterion. the test result indicates that the optimum lag length of the var model is 1. table 7: threshold cointegrating equations independent variable: lpcect variable intercept dut t t·dut lpcgdp lpcgdp·dut coef. 7.624 -4.957 0.008 -0.334 0.871 t-stat. (12.57) (-9.96) (4.50) (-2.92) (9.75) r2 = 0.99 f-stat. = 1563.64 dw = 1.41 independent variable: lpcgdpt variable intercept dut t t·dut lpcec lpcec·dut coef. 13.996 -11.005 0.017 0.028 -1.482 1.770 t-stat. (11.56) (-7.82) (15.78) (5.20) (-7.17) (7.06) r2 = 0.99 f-stat. = 6874.53 dw = 1.20 international journal of energy economics and policy, vol. 1, no. 1, 2011, pp.1-17 13 -.04 -.02 .00 .02 .04 .06 .08 .10 .12 1980 1985 1990 1995 2000 2005 2010 d(lpcec) d(lpcgdp) figure 4: first differences of lpcec and lpcgdp series the estimation results of the error correction models in table 8 indicate that the lagged error correction terms have the negative signs as expected. while the coefficient of the lagged error correction term in the lpcgdp equation is zero and insignificant, this is relatively high (-0.898, or 89.8%) and significant at the 1% level in the lpcec equation. this significance implies that the change in logarithm of per capita energy consumption (growth rate) does rapidly respond to any deviation in the long-run equilibrium (or short-run disequilibrium) for the t-1 period. in other words, the effect of an instantaneous shock to per capita energy consumption will be completely adjusted in the long-run. in addition, the effect of economic growth on energy consumption seems to be timevarying. the long-run effect on energy of growth is -0.334 before the date break, 1993, while it is (0.334+0.871) after the breakpoint. this means that economic growth has positively influenced energy consumption after 1993. this provides further evidence to believe that economic liberalization and reforms in 1989 which have helped vietnam to achieve relatively rapid growth rates have resulted in a corresponding rapid increase in demand for energy. table 8: estimation results of the error correction models dependent variable: ∆lpcect variable intercept t ect1,t-1 ∆lpcect-1 ∆lpcgdpt-1 coef. -0.898 0.372 0.396 t-stat. (-3.955) (2.254) (3.471) r2 = 0.55 dw = 2.05 dependent variable: ∆lpcgdpt variable intercept t ect2,t-1 ∆pcgdpt-1 ∆pcect-1 coef. -0.081 0.991 0.000 t-stat. (-0.056) (14.708) (0.000) r2 = 0.793 dw = 2.13 from the above estimations, we can derive the following equations that express the long-run relationship between energy consumption and economic growth (all coefficients are statistically significant at 1% level): energy consumption and economic growth in vietnam: threshold cointegration and causality analysis 14 ∆lpcect = –0.898ectt-1 + 0.372∆lpcect-1 + 0.396∆lpcgdpt-1 + ut (17) ectt-1 = lpcect-1 – 7.624 + 4.957dut – 0.008t + 0.334lpcgdpt-1 – 0.871lpcgdpt-1·dut (18) lpcect = – 7.624 + 4.957dut + 0.0072t + 0.096lpcgdpt-1 + 0.782lpcgdpt-1·dut 0.396lpcgdpt-2 +0.474lpcect-1 – 0.372lpcect-2 + ut (19) for 1976-1993 period: lpcect = – 7.624 + 0.0072t + 0.096lpcgdpt-1 – 0.396lpcgdpt-2 + 0.474lpcect-1 – 0.372lpcect-2 + ut (19a) for 1994-2010 period: lpcect = – 2.667 + 0.0072t + 0.878lpcgdpt-1 – 0.396lpcgdpt-2 + 0.474lpcect-1 – 0.372lpcect-2 + ut (19b) two important observations can be made from equation (17). first, there is a short-run (week) exogeneity as shown by the significant estimate of ∆lpcect-1. second, there is a long-run (strong) exogeneity as shown by the significant estimate of the error correction term. from the above equations we can also realize that the per capita energy consumption in a specific year in the second period is strongly influenced by the per capita gdp and per capita energy consumption of the previous year (positive sign). it seems that per capita gdp of the previous year has a moderate effect on per capita energy consumption in the first period. the estimation results also indicate that both per capita gdp and per capita energy consumption of two years ago have a negative influence on the specific year energy consumption. table 9 presents the results for granger causality tests from economic growth to energy consumption, and vice versa. it is shown that the null hypothesis that energy consumption does not granger-cause economic growth in the short-run cannot be rejected. this frankly refuses justifications of energy-led growth hypothesis in vietnam. incorporating with the cointegration analysis, we can conclude that there is a strong granger causality running from economic growth to energy consumption. this fact shows that energy consumption is determined by the economic growth in vietnam. in other words, the conservation hypothesis is acceptable. thus, energy conservation policy will have little effect on economic growth. table 9: granger causality tests dependent variable ∆lpcect ∆lpcgdpt causality type weak strong weak strong test statistic f-stat. 12.05 (0.0016) 21.59 (0.000) 0.000 (0.999) 0.129 (0.879) χ2-stat. 12.05 (0.0005) 43.19 (0.000) 0.000 (0.999) 0.258 (0.878) excluded variables ∆lpcgdpt-1 ect1,t-1, ∆lpcgdpt-1 ∆lpcect-1 ect2,t-1, ∆lpcect-1 conclusion lpcgdp causes lpcec lpcec does not cause lpcgdp note: numbers in (.) are p-values. this research finding is consistent with the empirical study of ozturk et al. (2010). we approve with the way ozturk et al. (2010) explain for this causality process. first, like other low income countries, the recent economic growth in vietnam has resulted in an expansion in commercial and industrial sectors where energy is a fundamental input. second, higher disposable income increases demand for electronic devices for entertainment and comfort for households. this is also consistent with the previous findings by khanh toan, p. (2009)1. he stated that energy might be 1 khanh toan, p., et al., (2009) international journal of energy economics and policy, vol. 1, no. 1, 2011, pp.1-17 15 mostly allocated into the residential uses (i.e. 39% residential, 36% industry, 20% transport in 2007; and 60.3% residential, 27.3% industry, and 8.7% transport in 1990). 5. conclusion this article investigates the causal relationship between per capita energy consumption and per capita gdp for vietnam during the 1976-2010 period. in doing so, various cointegration testing approaches are employed before estimating the vector error correction models. the empirical findings suggest the existence of a uni-directional causality running from per capita gdp to per capita energy consumption. in addition, it is also found that economic growth has a significant positive long-run impact on energy consumption after the pointbreak, 1992. the research results strongly support the neoclassical view that energy consumption is not a limiting factor for the vietnam’s economic growth. this in turn implies that the rise in energy prices can be a good opportunity for the economy to promote substitution and technological innovation. from a policy perspective, the results in this study are consistent with the conservation hypothesis. since a high level of economic growth leads to a high level of energy demand, but not vice versa, the government can pursue the conservation energy policies that aim at curtailing energy use for environmental friendly development purposes. we should gradually establish a competitive energy market in order to allocate these resources into the most productive uses in the economy. this study just focuses on the bivariate causality tests for the aggregated energy consumption and economic growth, so it contains space for criticism. further studies can be done by using either multivariate models for total energy use or bivariate models for disaggregated energy consumption in industrial, residential, and transport sectors. references akarca, a.t., long, t.v., 1980. on the relationship between energy and gnp: a reexamination. journal of energy development 5, 326–331. altinay, g., karagol, e., (2004). structural break, unit root, and the causality between energy consumption and gdp in turkey. energy economics 26, 985– 994. aqeel, a., butt, m.s., 2001. the relationship between energy consumption and economic growth in pakistan. asia pacific development journal 8, 101–110. asafu-adjaye, j., 2000. the relationship between energy consumption, energy prices and economic growth: time series evidence from asian developing countries. energy economics 22, 615–625. asteriou, d., stephen g.h, 2007. applied econometrics: a modern approach using eviews and microfit, revised edition, palgrave macmillan. bartleet, m., and gounder, r., 2010. energy consumption and economic growth in new zealand: results of trivariate and multivariate models. energy policy 38, 3508–3517. belloumi, m., 2009. energy consumption and gdp in tunisia: cointegration and causality analysis. energy policy 37, 2745–2753. chen, s.t., kuo, h.i., chen, c.c., 2007. the relationship between gdp and electricity consumption in 10 asian countries. energy policy 35, 2611–2621. cheng, b.,1995. an investigation of cointegration and causality between energy consumption and economic growth. journal of energy development 21, 73–84. cheng, b.s., lai, t.w., 1997. an investigation of co-integration and causality between energy consumption and economic activity in taiwan. energy economics 19, 435–444. chiou-wei, s.z., chen, ching-fu, zhu,z., 2008. economic growth and energy consumption revisited: evidence from linear and nonlinear granger causality. energy economics 30, 3063–3076. chontanawat, j., hunt, l.c., pierse, r., 2008. does energy consumption cause economic growth? evidence from a systematic study of over 100 countries. journal of policy modeling 30, 209–220. christiano, l.j., 1992. searching for breaks in gnp. journal of business and economic statistics 10, 237–250. cleveland, c.j., kaufmann, r.k., stern, d.i., 2000. aggregation and the role of energy in the economy. ecological economics 32, 301–317. engle, r.f., granger, c.w.j., 1987. cointegration and error correction: representation, estimation and testing. econometrica 55, 251–276. energy consumption and economic growth in vietnam: threshold cointegration and causality analysis 16 erol, u., yu, e.s.h., 1987. on the causal relationship between energy and income for industrializing countries. journal of energy and development 13, 113–122. esso, l.j., 2010. threshold cointegration and causality relationship between energy use and growth in seven african countries. energy economics 30, 2391–2400. glasure, y.u., lee, a., 1997. cointegration, error correction and the relationship between gdp and energy: the case of south korea and singapore. resource and energy economics 20, 17–25. granger, c.w.j., 1969. investigating causal relation by econometric and cross-sectional method. econometrica 37, 424–438. gregory, a.w., hansen, b.e., 1996a. residual-based tests for cointegration in models with regime shifts. journal of econometrics 70, 99–126. gregory, a.w., hansen, b.e., 1996b. tests for cointegration in models with regime and trend shifts. oxford bulletin of economics and statistics 58, 555–560. hwang, d., gum, b., 1991. the causal relationship between energy and gnp: the case of taiwan. journal of energy development 16, 219–226. james b. ang, 2007. are saving and investment cointegrated? the case of malaysia (1965-2003). applied economics 39 2167–2174. johansen, s., 1988. statistical analysis of cointegration vectors. journal of economic dynamics and control 12, 231–254. johansen, s., juselius, k., 1990. maximum likelihood estimation and inference on cointegration with applications to the demand for money. oxford bulletin of economics and statistics 52, 169–209. khanh toan, p., et al., 2010. energy supply, demand, and policy in viet nam, with future projections. energy policy. kraft, j., kraft, a., 1978. on the relationship between energy and gnp. journal of energy development 3, 401–403. lee, c.c., 2005. energy consumption and gdp in developing countries: a cointegrated panel analysis. energy economics 27, 415–427. masih, a., masih, r., 1996. energy consumption and real income temporal causality, results for a multi-country study based on cointegration and error correction techniques. energy economics 18, 165–183. masih, a.m.m., masih, r., 1997. on temporal causal relationship between energy consumption, real income and prices; some new evidence from asian energy dependent nics based on a multivariate cointegration/vector error correction approach. journal of policy modeling 19, 417– 440. mehrara, m., 2007. energy consumption and economic growth: the case of oil exporting countries. energy policy 35, 2939–2945. ozturk, i., aslan, a., kalyoncu, h.. (2010). energy consumption and economic growth relationship: evidence from panel data for low and middle income countries. energy policy 38, 4422-4428. ozturk, i., 2010. a literature survey on energy–growth nexus. energy policy 38, 340–349. ozturk, i., acaravci, a. (2010). the causal relationship between energy consumption and gdp in albania, bulgaria, hungary and romania: evidence from adrl bound testing approach. applied energy 87, 1938-1943. paul, s., bhattacharya, r.n., 2004. causality between energy consumption and economic growth in india: a note on conflicting results. energy economics 26, 977–983. perron, p., 1989. the great crash, the oil price shock and the unit root hypothesis. econometrica 57, 1361–1401. pesaran, m.h., shin, y., smith, r.j., 2001. bounds testing approaches to the analysis of levels relationships. journal of applied econometrics 16, 289–326. solow, r.m, 1974. the economics of resources or the resources of economics. american economic review 64, 1-14. solow, r.m, 1997. reply: georgescu-roegen versus solow/stiglitz. ecological economics 22, 267268. soytas, u., sari, r., 2003. energy consumption and gdp: causality relationship in g-7 countries and emerging markets. energy economics 25, 33–37. stern, d.i., 1993. energy and economic growth in the usa: a multivariate approach. energy economics 15, 137–150. international journal of energy economics and policy, vol. 1, no. 1, 2011, pp.1-17 17 stern, d.i., 2000. a multivariate cointegration analysis of the role of energy in the us macroeconomy. energy economics 22, 267–283. stiglitz, j.e., 1997. reply: georgescu-roegen versus solow/stiglitz. ecological economics 22, 269270. toda, h.y., yamamoto, t., 1995. statistical inference in vector autoregressions with possibly integrated processes. journal of econometrics 66, 225–250. tsani, s.z., 2010. energy consumption and economic growth: a causality analysis for greece. energy policy, 32, 582–590. wolde-rufael, y., 2005. energy demand and economic growth: the african experience. journal of policy modeling 27, 891–903. yang, h.y., 2000. a note on the causal relationship between energy and gdp in taiwan. energy economics 22, 309–317. yu, e.s.h., choi, j.y., 1985. the causal relationship between energy and gnp: an international comparison. journal of energy and development 10, 249–272. yu, e.s.h., hwang, b.k., 1984. the relationship between energy and gnp, further results. energy economics 6, 186–190. zivot, e., andrews, d.w.k., 1992. further evidence on the great crash, the oil price shock, and the unit root hypothesis. journal of business and economic statistics 10, 251–270. 3.2 cointegration analysis . international journal of energy economics and policy | vol 10 • issue 2 • 2020 491 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(2), 491-496. energy consumption and foreign direct investment in lows in nigeria: an empirical perspective olusegun peter olaoye1, timothy ayomitunde aderemi2*, nwagwu chinedu john3, yvonne jude-okeke4, azuh dominic ezinwa5 1covenant university chaplaincy, covenant university, ota, nigeria, 2olabisi onabanjo university, ago iwoye, nigeria, 3department of business administration, lagos state university, lagos, nigeria, 4department of accounting, covenant university, ota, nigeria, 5department of economics, covenant university, ota, nigeria. *email: aderemi.timothy@gmail.com received: 28 july 2019 accepted: 05 december 2019 doi: https://doi.org/10.32479/ijeep.8489 abstract the aim of this study is to examine the relationship between energy consumption and foreign direct investment in nigeria over the period of 1990-2017. consequently, data were collected from unctad world bank database, world data atlas and cbn statistical bulletin respectively. cointegration, dols and granger causality approach were employed to address the objective of the study. the major findings in this study are summarized as follow. energy consumption and fdi inflow have a significant negative relationship with each other. there is a significant positive relationship between energy consumption and oil exports. however, openness of the economy and energy consumption have a non-significant negative relationship. in the same vein, there is an existence of a unidirectional causality which runs from fdi to oil exports in nigeria. there is one way causal relationship running from energy consumption to oil exports. fdi inflows granger causes energy consumption. meanwhile, energy consumption granger causes openness of the economy. due to the findings that emerged in this study, it is important that this study recommends the following to the policy makers in nigeria since energy consumption does not drive fdi inflows the policy makers in the country should provide a conducive climate that will facilitate the accessibility of foreign investors to primary energy consumption in the country. also, the country should improve the value addition to the production of primary energy so that its consumption could be competitive in the global market. keywords: energy, consumption, foreign direct investment, oil exports and nigeria jel classifications: f21, f23 1. introduction in the past few decades, consumption of energy has been on the increase globally due to its overwhelming impact on the economic growth in the world (matthew et al., 2018). in developing countries, critical factors such as growth in the population rate, urbanization and continuous rise in the level of economic activities have orchestrated the increase in the global energy consumption (suganthi and samuel, 2012; al-mulali and ozturk, 2015; babajide et al., 2015; farhani and ozturk, 2015; raza et al., 2016; alam et al., 2016; nain et al., 2017; ayinde et al., 2019). meanwhile, the availability of an uninterrupted supply of electricity in nigeria is very germane to the creation of job opportunities, reduction of poverty and development of industries. despite the fact that there are various sources of energy in nigeria this has not guaranteed a stable power supply in the country. however, the inflows of fdi in nigeria is traceable to the era of natural resources exploitation by the colonial masters. also, the aftermath effect of oil discovery in 1958 and oil boom of 1970s led to the rise of fdi inflows in nigeria. in the last few decades, nigeria has attracted a substantial amount of foreign direct investment (fdi). a cursory look into the unctad document this journal is licensed under a creative commons attribution 4.0 international license olaoye, et al.: energy consumption and foreign direct investment inflows in nigeria: an empirical perspective international journal of energy economics and policy | vol 10 • issue 2 • 2020492 indicates that 70% of fdi inflows in ecowas countries went to nigeria in 2006, in which 90% of its fdi inflow went to oil sector alone. in the same vein, fdi inflows remain unequally distributed across the continent of africa in 2016, in which only five countries (angola, egypt, nigeria, ghana and ethiopia) accounted for 57% of the continent’s total fdi inflows. in the same year, fdi inflows to west africa grew by 12% to $11.4 billion. this was propelled by fdi inflows into nigeria which increased by over 30% (unctad, 2017). the issue surrounding the linkage between fdi and energy consumption is one of the areas that has generated a lot of controversies in international economics. it has been established in the literature that foreign based firms are prone to investing in the country where the costs of production are minimized. this leads to gradual deterioration of the resources and environment of the host economy over time (asghari, 2013). this has sparked off ongoing debate regarding the concerns for environment in increasing fdi inflows in developing economy. but the role of a stable energy supply in building the economic prosperity of any nation cannot be overemphasized. the higher the economic growth, the higher the consumption of energy and verse versa (achour and belloumi, 2016: saidi and hammami 2015; komal and abbas, 2015). due to the lower domestic savings and investments rates in nigeria, fdi inflows could be an escape route for the country to get foreign capital and technology which can efficiently ensure the stability and growth process of the power sector in the country. despite the fact that studies on fdi inflows in nigeria are numerous, yet there has been a little or no effort to examine the spillovers of fdi on energy consumption in the country in the recent times. in view of the above, this study examines the relationship between energy consumption and fdi inflows in nigeria. also, the uniqueness of this study lies in the adoption of latest econometric technique in which majority of the past studies have not fully explored. however, this study is organized as follows besides introduction, section two looks at critical review of relevant literature and section three presents model specification, estimation, discussion of results and policy recommendation. 2. literature review an attempt has been made in this section to present the review past empirical studies regarding the subject matter of this study. aminu and aminu (2015) employed granger causality test, impulse response and variance decomposition to investigate the relationship between energy consumption and economic growth in nigeria from between 1980 to 2011. it was discovered from the study that there was an absence of causal relationship among the variables of interest. also, the result of variance decomposition showed that capital and labour affected output growth more than energy consumption in the country. in another related study, mathew et al. (2018) examined the relationship between human capital development, energy consumption and economic growth in nigeria between 1981 and 2016 with the application of the fully modified ordinary least squares. the authors submitted that human capital development was related to economic growth insignificantly in nigeria. however, electricity consumption and economic growth are significantly related in the country. kivyiro and arminen (2014) used autoregressive distributed lag model and granger causality to assess the nexus between carbon dioxide emissions, energy consumption, economic development and fdi in six sub saharan african countries. the result from the study showed that granger causality varied in each of the countries. adeola and aziakpono (2017) analyzed the relationship between the usage of electricity power and economic growth in south africa with the application of the trivariate causality. the authors discovered that a two-way causality runs between the usage of electricity power and economic growth in the country. ogbanje et al. (2010) examined the spillovers of fdi on agricultural sector in nigeria with the aid of duncan multiple range test and ordinary least square. the authors submitted that the net fdi inflow in nigeria did not bring about development to agricultural sector. in another perspective, mojekwu and samson (2012) utilized co-integration alongside error correction technique to assess how fdi and the challenges of sustainable development are related in nigeria. it was discovered from the study that a longrun relationship exists between fdi, gross capital formation and economic growth in nigeria. akinlo (2009) critically evaluated the linkage between electricity power usage and the productivity of economic activities in nigeria. it was discovered from the paper that a long-run relationship exists between the variables under study. this implies that electricity consumption leads to economic growth in the country. aliero and ibrahim (2012) utilized granger causality approach to examine the linkage between energy consumption and economic growth in nigeria from 1970 to 2009. it was discovered from the study that no causal relationship existed between total energy consumption and economic growth when aggregate energy consumption data was adopted. but reverse was the case when the disaggregate energy consumption data were utilized for the same period. however, doytch and narayan (2016) adopted blundell–bond dynamic panel estimator to estimate how fdi affects renewable and non-renewable energy consumption in 74 economies between 1985 and 2012. the authors opined that total fdi catalyzed green-energy advancing practices and discouraged the application of non-renewable energy in high-income countries, low and lower middle-income countries. also, the transfer energy-saving practices was encouraged while the usage of nonrenewable energy sources was discouraged in low and lower middle-income countries. while using autoregressive distributed lag model and granger causality, xu et al. (2016) investigated the impact of energy consumption on fdi in shanghai between 1991 and 2013. it was discovered from the study that energy consumption has a positive and significant impact on fdi in the short run. meanwhile, the impact is not significant in the long run. there is one way causal relationship between energy consumption and fdi in the country. in the same vein, islam et al. (2013) applied vector error correction model (vecm) to examine the relationship between energy consumption, economic growth and financial development in malaysia. the result from olaoye, et al.: energy consumption and foreign direct investment inflows in nigeria: an empirical perspective international journal of energy economics and policy | vol 10 • issue 2 • 2020 493 the paper argued that in both the short run and long run energy consumption has a link with economic growth and financial development in malaysia. opaluwa et al. (2012) investigated the relationship between fdi and manufacturing sector performance in nigeria with the aid of vector auto regression (var), cointegration and error correction model. the authors submitted that fdi and the growth of manufacturing sector has a significant negative relationship. in addition, lin and linh (2015) examined the nexus between environmental degradation, economic growth, fdi and energy consumption in 12 highly populated countries in asia with the aid of a dynamic causal analysis. the authors concluded that in the both short and long-run there was an existence of causal relationships among economic growth, fdi, energy consumption and co2 emissions in the countries. omri and kahouli (2014) discovered a mixed result while examining the causal relationship between income, fdi inflows and energy consumption in 65 countries. dantama et al. (2012) evaluated a relationship between energy consumption and economic growth in nigeria between 1980 and 2010 with the use of ardl bound approach, cointegration and unrestricted error correction model. the authors posited that there was a long run cointegrating relationship among petrol, coal and electricity consumption and economic growth. also, petroleum and electricity consumption showed a positive and significant impact on economic growth while coal consumption has an insignificant negative impact on economic growth in the country. in summary, from the reviewed literature, it could be concluded that studies on fdi and energy consumption is scanty in nigeria. therefore, there is a need for further study to examine the nexus between these variables in the recent times. 3. methodology this paper makes use of secondary data such that fdi data were extracted from unctad document, energy consumption data were sourced from world data atlas, oil exports, and inflation rate data were sourced from the central bank of nigeria statistical bulletin. 3.1. model specification enc = f (fdi, oilex, oe) (1) equation (1) is linearized as follows to derive equation (2) 1 1 2 3 t t t t tlnenc lnfdi lnoilex oeβ β β ε∝ + + + += (2) 3.2. the direction of causality between fdi inflows and energy consumption in nigeria in analyzing the granger causality between fdi inflows and energy consumption, study adopted pairwise granger causality analysis in estimating the var model in equation (3-6) below 0 1 1 2 1 0 0 3 1 4 1 1 0 0 p p t t t i i p p t t t i i fdi fdi enc oilex oe α α α α α ε − − = = − − = = + + + = + + ∑ ∑ ∑ ∑ (3) 0 1 1 2 1 0 0 3 1 4 1 2 0 0 p p t t t i i p p t t t i i enc enc fdi oilex oe β β β β β ε − − = = − − = = + + + + + + = ∑ ∑ ∑ ∑ (4) 0 1 1 2 1 0 0 1 1 3 1 3 0 0 p p t t t i i p p t t t i i oilex oilex fdi oe enc γ γ γ γ γ ε − − = = − − = = + + + = + + ∑ ∑ ∑ ∑ (5) 0 1 1 2 1 0 0 3 1 4 1 4 0 0 p p t t t i i p p t t t i i oe oe enc fdi oilex γ γ γ γ γ ε − − = = − − = = + + + + = + ∑ ∑ ∑ ∑ (6) where, fdi represents fdi which is measured by the annual fdi inflow into the country in million dollars. enc is used to proxy primary energy consumption in the country. it is measured in quadrillion. oe is openness of economy. oilex is oil exports and is measured in billion naira. ε captures error term which is assumed to be stochastic and t represent years. ∝1 is an intercept and β1, β2, and β3, are slope parameters to be estimated. it is expected that coefficient of the variables to have the following signs: β1, β2 and β3 > 0. 3.3. pre-estimation test (a) unit root test. (b) cointegration test. 3.4. model estimation an attempt was made in this section to verify different diagnostic tests like unit roots and cointegration test before the estimation error correction model. the study adopted the standard augmented dickey fuller test, philips perron test and johansen cointegration technique to determine the order of integration and the existence or otherwise of long run equilibrium among the variables respectively. 4. results and discussion the normal distribution of data is very important when a study involves an econometric analysis. in view of the above, table 1 shows a descriptive analysis of the variables of interest. the mean olaoye, et al.: energy consumption and foreign direct investment inflows in nigeria: an empirical perspective international journal of energy economics and policy | vol 10 • issue 2 • 2020494 and median values of fdi, energy consumption and openness of the economy are very close. it is only oil export that shows a wide difference in between the mean and median values. this shows that the data utilized for this study are fairly distributed following the assertion of karmel and polasek, 1980 that if a distribution of data series is perfectly symmetrical, the values of mean, mode and median of such data series must converge. in addition, another important parameters to establish the normal distribution of data is the value of kurtosis and jaque-bera statistics. the value of kurtosis of the variables are not far from 3 apart from oil export. this suggests that the distribution of the data is near symmetrical. an attempt was made in table 2 to examine the stationarity property of the data because any analysis based on the non-stationary data would lead to a spurious or nonsense result which could be misleading for policy implications. therefore, the standard augmented dickey-fuller (adf) and phillips-perron (pp) tests were used to conduct the stationarity test. the results of the estimated data show that all the variables are stationary after their first differencing. in other words, all the variables are i(1). this implies that these variables possess unit roots. from the table 3 above, the estimated results indicated that the studied variables are stationary after first differencing. this implies that these variables could diverge in the short run but it might have a long run relationship. as a result of this, johansen and juselius (1990) multivariate cointegration test was adopted to examine the existence or otherwise of long run relationship among the variables. consequently, the trace statistics and the maximal eigen value statistics indicate that there is at most 3 co-integrating vectors in the systems. this shows that that these variables have a long run equilibrium relationship with one another. therefore, dynamic ordinary least square was utilized in this study to estimate a long run relationship among these variables. dependent variable: lnenc method: dynamic least squares (dols) table 4 shows the estimated results of the regression analysis. all the coefficients apart from oil export did not follow the a priori expectation. in the same vein, the independent variables of the model which comprises of fdi, openness of the economy and oil exports jointly explained about 93% of the systematic variations in the dependent variable, energy consumption leaving 7% unexplained as a result of random chance. this implies that the model adopted for this work is relatively good. meanwhile, when the loss in the degree of freedom was adjusted, the explanatory power reduces to about 85%. moreover, there is a positive relationship between energy consumption and oil exports, which is significant at 1% level of significance. a unit change in oil exports leads to about 9.2% increment in energy consumption in nigeria. this implies that energy consumption in nigeria is very sensitive to oil exports. however, openness of the economy and energy consumption have a negative relationship with each another, which is not significant. in the same vein, energy consumption and fdi inflow have a negative relationship with each other, which is significant at 5% level of significant. this finding contradicts the submission of xu et al. (2016) in a related study in shanghai. this section examined the direction of causality among energy consumption, fdi inflows, oil exports and openness of the economy in nigeria within the context of pairwise granger table 2: unit root test variables adf test pp test level 1st difference remarks level 1st difference remarks fdi −2.9810*** −2.9862*** i (1) −2.9810*** −2.9862*** i (1) oe −2.9810*** −2.9918*** i (1) −2.9810*** −2.9862*** i (1) oilex −2.9810*** −2.9862*** i (1) −2.9810*** −2.9862*** i (1) enc −2.9810*** −2.9862*** i (1) −2.9810*** −2.9862*** i (1) −2.9810*** −2.9862*** i(1) −2.9810*** −2.9862*** i(1) source: authors’ computation (2019) *** %5 level. adf: augmented dickey-fuller, pp: phillips-perron table 3: johansen cointegration test (trace statistics) and (maximum eigen value) null hypothesis eigen value trace statistics p-value** maximum eigenvalue p-value** r=0* 0.692426 51.07630 0.0241 29.47602 0.0283 r≤1 0.483880 21.60028 0.3213 16.53538 0.1951 r≤2 0.173404 5.064907 0.8019 14.26460 0.7716 r≤3 0.012083 0.303916 0.5814 3.841466 0.5814 source: authors’ computation (2019) table 1: descriptive statistics of annual data series (1990-2017) descriptive statistics lnfdi lnenc oe lnoilex mean 3.58e+09 9.65e+14 37.96148 5253.371 median 2.19e+09 8.70e+14 39.28000 2993.110 maximum 8.92e+09 1.59e+15 53.28000 14323.15 minimum 1.00e+09 6.70e+14 20.72000 106.6265 std. deviation 2.58e+09 2.39e+14 8.675872 4981.415 skewness 0.769560 1.130200 -0.202288 0.554950 kurtosis 2.250799 3.369640 2.563189 1.887697 jargue-bera 3.296469 5.901796 0.398797 2.777734 probability 0.192389 0.052293 0.819224 0.249358 sum 9.67e+10 2.61e+16 1024.960 141841.0 sum. sq. deviation 1.74e+20 1.49e+30 1957.040 6.45e+08 observation 27 27 27 27 source: author’s computation 2018 olaoye, et al.: energy consumption and foreign direct investment inflows in nigeria: an empirical perspective international journal of energy economics and policy | vol 10 • issue 2 • 2020 495 causality test. the results presented in table 5 show that the existence of a unidirectional causality which runs from fdi to oil exports in nigeria. similarly, there is one way causal relationship running from energy consumption to oil exports. fdi inflows granger causes energy consumption. meanwhile, energy consumption granger causes openness of the economy. however, there is no feedback relationship between openness of the economy and fdi inflows and oil exports. 5. conclusion and recommendations this study examined the relationship between energy consumption and fdi inflows in nigeria over the period of 1990-2017. consequently, the major findings in this study are summarized as follow. there is a significant positive relationship between energy consumption and oil exports. however, openness of the economy and energy consumption have a non-significant negative relationship with each another. in the same vein, energy consumption and fdi inflow have a significant negative relationship with each other. this means that energy consumption does not propel fdi inflows in nigeria. there is an existence of a unidirectional causality which runs from fdi to oil exports in nigeria. there is one way causal relationship running from energy consumption to oil exports. fdi inflows granger causes energy consumption. meanwhile, energy consumption granger causes openness of the economy. meanwhile, there is no feedback relationship between openness of the economy and fdi inflows and oil exports. however, due to the findings that emerged in this study, it is important that this study recommends the following to the policy makers in nigeria since energy consumption does not drive fdi inflows the policy makers in the country should provide a conductive climate that will facilitate the accessibility of foreign investors to primary energy consumption in the country. also, the country should improve the value addition to the production of primary energy so that its consumption could be competitive in the global market. 6. acknowledgement the support of the covenant university centre for research, innovation and development (cucrid) in the course of this study is recognize. references achour, h., belloumi, m. (2016), investigating the causal relationship between transport infrastructure, transport energy consumption and economic growth in tunisia. renewable and sustainable energy reviews, 56, 988-998. adeola, o., aziakpono, m. (2017), the relative contribution of alternative capital flows to south africa: an empirical investigation. journal of economic and financial sciences, 8(4), 12-28. akinlo, a.e. (2009), electricity consumption and economic growth in nigeria: evidence from cointegration and co-feature analysis. journal of policy modeling, 31(5), 681-693. alam, m.m., murad, m.w., noman, a.h.m., ozturk, i. (2016), relationships among carbon emissions, economic growth, energy consumption and population growth: testing environmental kuznets curve hypothesis for brazil, china, india and indonesia. ecological indicators, 70, 466-479. aliero, h., ibrahim, s. (2012), the relationship between energy consumption and economic growth in nigeria: a causality analysis. international journal of marketing and technology, 2(3), 1-13. al-mulali, u., ozturk, i. (2015), the effect of energy consumption, urbanization, trade openness, industrial output, and the political stability on the environmental degradation in the mena (middle east and north african) region. energy, 84, 382-389. aminu, m.m., aminu, m.f. (2015), energy consumption and economic growth in nigeria: a causality analysis. journal of economics and sustainable development, 6(13), 42-53. asghari, m. (2013), does fdi promote mena region’s environment quality? pollution halo or pollution haven hypothesis. international journal of scientific research in environmental sciences, 16, 92-100. ayinde, a.r., celik, b., gylych, j. (2019), effect of economic growth, industrialization, and urbanization on energy consumption in nigeria: a vector error correction model analysis. international journal of energy economics and policy, 9(5), 409-418. babajide, a.a., lawal, a.i., somoye, r.o. (2015), monetary policy dynamics and stock market movements: empirical evidence from nigeria. journal of applied economic science, 10, 1179-1188. dantama, y.u., abdullahi, y.z., inuwa, n. (2012), energy consumption economic growth nexus in nigeria: an empirical assessment based on ardl bound test approach. european scientific journal, 8(12),  34-47. dickey, d.a., fuller, w.a. (1979), distribution of the estimators for table 5: pairwise granger causality test sample: 1990 2017 lags: 2 null hypothesis obs f-statistic prob. fdi does not granger cause oilex 25 4.83906 0.0193 oilex does not granger cause fdi 2.39377 0.1169 oe does not granger cause oilex 25 0.59967 0.5586 oilex does not granger cause oe 2.98347 0.0735 ec does not granger cause oilex 25 7.07389 0.0047 oilex does not granger cause ec 1.41867 0.2654 oe does not granger cause fdi 25 0.01987 0.9803 fdi does not granger cause oe 0.44519 0.6469 ec does not granger cause fdi 25 0.63289 0.5414 fdi does not granger cause ec 5.46300 0.0128 ec does not granger cause oe 25 3.95066 0.0358 oe does not granger cause ec 0.08026 0.9232 authors’ computation (2019) table 4: regression estimates for fdi inflows and oil exports in nigeria variable coefficient t-statistics p-value lnoilex 9.21e+10* 5.163377 0.0003 oe −7.60e+12 1.599109 0.1381 lnfdi −1.25150.3** 3.888744 0.0025 c 1.23e+15* 6.198645 0.0001 r-squared 0.931960 adjusted r-squared 0.857734 authors’ computation (2019) ***significant at 10%, **significant at 5%, *significant at 1%. fdi: foreign direct investment olaoye, et al.: energy consumption and foreign direct investment inflows in nigeria: an empirical perspective international journal of energy economics and policy | vol 10 • issue 2 • 2020496 autoregressive time series with a unit root. journal of the american statistical association, 74, 427-431. doytch, n., narayan, s. (2016), does fdi influence renewable energy consumption? an analysis of sectoral fdi impact on renewable and non-renewable industrial energy consumption. energy economics, 54, 291-301. farhani, s., ozturk, i. (2015), causal relationship between co2 emissions, real gdp, energy consumption, financial development, trade openness, and urbanization in tunisia. environmental science and pollution research, 22(20), 15663-15676. granger, c.w.j. (1986), developments in the study of cointegrated economic variables. oxford bulletin of economics and statistics, 48, 213-228. islam, f., shahbaz, m., ahmed, a., alam, m. (2013), financial development and energy consumption nexus in malaysia: a multivariate time series analysis. economic modelling, 30, 435-441. johansen, s., juselius, k. (1990), maximum likelihood estimation and inference on cointegration with applications to demand for money. oxford bulletin of economics and statistics, 52, 169-210. karmel, p.h., polasek, m. (1980), applied statistics for economists. london: pitman publisher. kivyiro, p., arminen, h. (2014), carbon dioxide emissions, energy consumption, economic growth and foreign direct investment: causality analysis for sub saharan africa: energy economics, 74, 595-606. komal, r., abbas, f. (2015), linking financial development, economic growth, and energy consumption in pakistan. renewable and sustainable energy reviews, 44, 211-220. matthew, o., osabohien, r., fagbeminiyi, f.f., fasina, a. (2018), greenhouse gas emissions and health outcomes in nigeria: empirical insight from auto-regressive distribution lag technique. international journal of energy economics and policy, 8(3), 43-50. matthew, o.a, ede, c.u., osabohien, r., ejemeyovwi, j, fasina, f.f., akinpelumi, d. (2018), electricity consumption and human capital development in nigeria: exploring the implications for economic growth. international journal of energy economics and policy, 8(6), 8-15. mojekwu, j.n., samson, o. (2012), foreign direct investment and the challenges of sustainable development in nigeria. journal of research in international business and management, 2(7), 190-198. nain, m.z., ahmad, w., kamaiah, b. (2017), energy consumption and india’s economic growth. the indian economic journal, 8(3), 46-62. ogbanje, e.c., okwu, o.j., saror, s.f. (2010), an analysis of foreign direct investment in nigeria: the fate of nigeria’s agricultural sector. pat, 6(2), 15-25. omri, a., kahouli, b. (2014), causal relationships between energy consumption, foreign direct investment and economic growth: fresh evidence from dynamic simultaneous-equations models. energy policy, 67, 913-922. opaluwa, d., ameh, a.a., alabi, j.o., abdul, m. (2012), the effect of foreign direct investment on nigeria manufacturing sector. international journal of business and management, 4(2), 140-148. phillips, p.c., perron, p. (1988), testing for a unit root in time series regression. biometrika, 75, 335-346. raza, s.a., jawaid, s.t., siddiqui, m.h. (2016), electricity consumption and economic growth in south asia. south asia economic journal, 5(3), 40-55. saidi, k., hammami, s. (2015), the impact of co2 emissions and economic growth on energy consumption in 58 countries. energy reports, 1, 62-70. suganthi, l., samuel, a.a. (2012), energy models for demand forecasting review. renew sustain energy review, 16, 1223-1240. unctad. (2017), world investment report 2018 united nations on trade and investment. available from: http://www.unctad.org data%20on%20fdi%20brics%201.htm. [last accessed on 2018 aug 06]. xu, j., zhou, m., li, h. (2016), ardl based research on the nexus among fdi, environmental regulation and energy consumption in shanghai (china). natural hazards, 81(1), 551-564. . international journal of energy economics and policy | vol 9 • issue 4 • 2019 97 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(4), 97-102. the impact of oil prices on inflation: the case of azerbaijan shahriyar mukhtarov1,2*, jeyhun mammadov3, fariz ahmadov4 1department of world economy, baku engineering university, baku az0101, azerbaijan, 2department of economics and management, azerbaijan state university of economics (unec), istiqlaliyyat str. 6, baku az1141, azerbaijan, 3department of economics and management, khazar university, 41 mehseti str., baku az1096, azerbaijan, 4department of economics and business administration, azerbaijan state university of economics (unec), istiqlaliyyat str. 6, baku az1141, azerbaijan. *email: smuxtarov@beu.edu.az received: 17 february 2019 accepted: 15 may 2019 doi: https://doi.org/10.32479/ijeep.7712 abstract this paper investigates the relationship between inflation, oil prices and exchange rate in azerbaijan using the vector error correction model (vecm) to the data ranging from 1995 to 2017. the results from cointegration method confirm the existence of a long-run relationship among the variables. moreover, estimation results of vecm show that the oil prices and exchange rate have positive and statistically significant impact on inflation in the long-run. this implies that 1% increase in oil prices and exchange rate increases inflation by 0.58% and 1.81%, respectively. the results of the study also reveal that inflation is observed during the periods of both high and low oil prices, and the exchange rate acts as the transmission channel from oil prices to inflation. keywords: inflation, oil price, exchange rate, vector error correction model, azerbaijan jel classifications: e31, q4 1. introduction economic situations of countries are being constantly shaped by globalization. in the last decades, the economies can be analyzed in two periods: periods observed with high and low oil prices. vast empirical studies suggest that there is a linear relationship between oil price fluctuations and economic growth (hamilton, 1983; papapetrou, 2001; werner, 2005; gbadebo, 2009). however, the sign and significance of this relationship depend on whether countries are oil exporters or importers. in the case of countries that import petroleum as raw material, oil price fluctuations change their production costs, the level of goods and services produced, and consequently affect main macroeconomic variables such as inflation and unemployment. the case is relatively different in oil-exporting countries such that oil price fluctuations exert both supply and demand shocks. response to positive shock: • national economies of oil-rich countries depend largely on crude oil exports; • some of this revenue is saved in sovereign wealth funds (for future generations and to preserve macroeconomic stability during recessions associated with negative oil price shocks) and the remaining revenue is transferred to the state budget to stimulate economic diversification and growth; • however, possibly due to structural sluggishness caused by misallocation and inefficient use of resources, and the booming oil industry and non-tradable sector, production (or tradable) sector shrinks and a low level of economic diversification is followed; • meanwhile, huge foreign currency inflow increases the value of a national currency and, as a result, goods and services in a domestic economy become relatively expensive than those in other countries. this in turn also hinders diversification and makes the economy vulnerable to oil price shocks; • therefore, having less diversified economies and weak financial sectors, oil-rich countries tend to peg their national currencies against foreign currencies, particularly the us dollar in order to ensure their economies against negative externalities; this journal is licensed under a creative commons attribution 4.0 international license mukhtarov, et al.: the impact of oil prices on inflation: the case of azerbaijan international journal of energy economics and policy | vol 9 • issue 4 • 201998 • because of the above-mentioned low production possibilities, these countries incline to import most consumer and industrial goods from other countries to satisfy domestic consumption. hence, oil price shocks that affect production sectors and consumer prices in other countries also affect the economies of oil exporting countries; response to negative shock: • plummeting oil prices decrease oil revenue and foreign currency inflow, and as a result, the domestic currency loses its value. currency devaluation is beneficial for the domestic economy by making its goods and services relatively cheaper than those in foreign countries and can promote export diversification. however, in the short run, because of present low economic diversification and sustained reliance on imports, oil-rich countries may experience inflation again. from these points of view, we conclude and hypothesize that oil-rich countries may undergo inflation in both periods if their economies are less diversified. therefore, oil-price transmission channels are assumed to be low economic diversification and fluctuations in exchange rates. the aim of this study is to investigate the relationship between oil price fluctuations and inflation in the case of azerbaijan. azerbaijan is an oil-rich country, has passed the above-mentioned economic trajectory and faced similar challenges, and 46% of its budget is being financed through transfers from state oil fund of the republic of azerbaijan. during a spike in oil prices from 2000 to 2008, azerbaijan experienced high oil rents constituting 42% of gdp and gdp growth reached its highest rate of 34.5% in 2006 (figure 1). as it is difficult to sustain such a level for a long period, the rate dropped to 10.8% in 2008. it is also worth to highlight that azerbaijan started to decrease its oil production in 2009-2010. during this period, gdp growth fell to 9.4% in 2009, 4.9% in 2010 and 0.07% in 2011. nevertheless, during the highest oil prices observed in 2011-2013, the economy recovered, and the gdp growth rate reached 5.8% in 2013. the economy experienced another steep drop in oil prices the following year, and its gdp growth rate dropped to 2% in 2014, further dropped to −3.10% in 2016 and recovered by 0.10% in 2017 thanks to regulatory reform and stabilization policies1. the country followed fixed exchange rate regime by 2014 (albeit managed because of slowly revaluation of the national currency), and due to sharp fall in oil revenue, azerbaijan devalued its national currency azerbaijani manat in 2015 by 34% and adopted managed floating exchange rate regime. during the period of oil boom and fixed exchange rate regime, an increase in consumer prices was observed until 2008 (20.8%), over time dropped to 1.4% in 2014 and started to increase by 4% in 2015, 12.4% in 2016 and 13% in 2017 (figure 1). the contribution of the paper is that the channel from oil price to consumer price fluctuations is particularly evaluated in the case of azerbaijan, which to the best of our knowledge has not been researched so far. another contribution is that detailed policy implications are introduced based on the estimation results in order to mitigate the negative impacts of oil price fluctuations. the rest of the paper is organized as follows: a literature review is provided in section 2. section 3 describes the data and defines methodology. section 4 presents and discusses the results. section 5 concludes and offers policy implications. 2. literature review effects of oil price fluctuations on inflation are comprehended theoretically and experientially. the effect depends on whether countries are consumers (importers) or producers (exporters) of oil. in this regard, we classify literature into two parts. summary of corresponding empirical studies is presented in table 1. 2.1. oil importing countries when oil price is high, companies prefer to reduce production rate due to high production costs. similarly, oil price reduction 1 for more information on stabilization policies, see strategic roadmap on national economy and key sectors of the republic of azerbaijan at https://ereforms.org/store//media/ekspert_yazilari/islahat%20icmali/mart/ strateji%20yol%20x%c9%99rit%c9%99si%20-eng1.pdf source: world development indicators, world bank, 2018 figure 1: macroeconomic indicators of azerbaijan mukhtarov, et al.: the impact of oil prices on inflation: the case of azerbaijan international journal of energy economics and policy | vol 9 • issue 4 • 2019 99 decreases production cost and price level. however, it does not reduce price level of goods in price stickiness condition, as suppliers keep the price at a high level. from experiential view, there are various empirical studies that investigated the impact of oil price shocks on inflation (mork, 1989; mory, 1993; burbidge and harrison, 1984; hamilton, 1996). eryigit (2012) conducted research on the effect of oil price movements in the case of turkey using weekly data from 2005 to 2008 and found out that oil price shocks have positive impacts on stock market. however, the shocks exerted negative impacts on interest rates and exchange rates. using quarterly data from 1990 to 2011, ozturk (2015) revealed positive impacts of oil price shocks on inflation in turkey. using quarterly data from 1987 to 2015, rasasi and yilmaz (2016) came to similar conclusion and highlighted that oil price increases affect inflation positively with a delay. in studies conducted by sibanda et al. (2015) for south africa and by malik (2017) for pakistan on the effect of oil price fluctuations on inflation, positive relationship was determined. cologni and manera (2008) conducted their research on the effect of oil price changes in g-7 countries, and found that oil prices impact inflation significantly, which in turn affects the real economy by raising the interest rates. similar results were obtained by wu and ni (2011) for the us for the period of 1995-2005. the authors investigated the relationship between oil prices, inflation, interest rates and money, and focused on possible reactions of monetary policies to external shocks. their results revealed that oil price changes affect inflation in both symmetric and asymmetric models, and oil price changes granger cause inflation. a similar study was carried out by cavalcanti and jalles (2013) in the case of the usa for brazil, which had different path on oil import dependence rate such that table 1: summary of similar empirical studies in the literature author (s) time period country method (s) result cologni and manera (2008) quarterly, 1980-2003 g-7 var they found that oil prices impact inflation significantly which in turn affects the real economy by raising the interest rates tang et al. (2010) monthly, 1998-2008 china svar finds that a positive oil price shock has positive effects on inflation qianqian (2011) monthly, 1999-2008 china vecm positive oil price shocks cause china’s cpi to rise wu and ni (2011) monthly, 1995-2005 u.s. gct firstly, the empirical results reveal that the goil will affect inf, and inf will affect goil in both symmetric and asymmetric models. namely, the feedback effects exist between goil and inf. oil prices granger cause inflation eryigit (2012) weekly, 2005-2008 turkey var their analysis indicates that oil price shocks have positive impacts on stock market and negative impacts on both interest rates and exchange rates cavalcanti and jalles (2013) quarterly, 1975–2008 u.s. and brazil svar oil prices have positive impact on inflation abounoori et al. (2014) monthly, 2003-2013 iran dynamic ect the findings showed that the oil price pass-through into inflation in both short-and-long terms were positive and incomplete ozturk (2015) quarterly, 1990-2011 turkey var positive impacts of oil price shocks on inflation rate katircioglu et al. (2015) annual, 1980-2011 oecd countries panel ct results of this study reveal that the price of oil exerts statistically and negatively significant impacts on cpi, in the case of oecd countries in general sibanda et al. (2015) monthly, 2002-2013 south africa var both crude oil prices and the exchange rates have positive impacts on inflation expectations chen et al. (2015) quarterly, 1994-2012 china svar suggest that the increase of china’s price level results from oil price shocks rasasi and yilmaz (2016) quarterly, 1987-2015 turkey svec authors found that oil price increases affect inflation positively with a delay zhao et al. (2016) annaul, 1990*2013 china dsge china’s economy experiences long-term inflation as a consequence of oil supply shocks malik et al. (2017) annual, 1960-2014 pakistan svar the inflation rate rise as a result of a positive oil price shock trang (2017) quarterly, 2000-2015 vietnam var rise in oil prices would lead to higher inflation davari and kamalian (2018) quarterly, 2003-2015 iran non-linear ardl no significant relationship between oil-price growth and inflation rate, but significant relationship between the reduction in oil price and inflation bala and chin (2018) annual, 1995-2014 algeria, angola, libya, and nigeria ardl dynamic panels oil price changes positively influences inflation legend: ardl: autoregressive distributed lags bounds testing, vecm: vector error correction method. ct: cointegration test, gct: granger causality test, ect: error correction model, dsge: dynamic stochastic general equilibrium, svar: structural vector autoregression, var: vector autoregression oecd: the organisation for economic co-operation and development. inf: inflation, cpi: consumer price index, ec: energy consumption mukhtarov, et al.: the impact of oil prices on inflation: the case of azerbaijan international journal of energy economics and policy | vol 9 • issue 4 • 2019100 oil import dependency is higher in the usa than brazil. the authors conclude that although inflation volatility was declining in the usa, oil price shocks still accounted for a larger fraction of the volatility. however, such shocks did not seem to have clear impact on output growth and accounted for a small fraction of the volatility of inflation and output growth. however, inversely proportional dependence was revealed by katircioglu et al. (2015) in the case of oecd countries. the authors analyzed the impact of oil price movements on macroeconomic performance and revealed that the price of oil exerts statistically negative impact on macroeconomic variables; gdp, unemployment rate and the consumer price index. katircioglu et al. (2015) concludes that the impact depends on to what extent the country’s industry depends on oil. such that, nowadays, more energy efficient vehicles are used, and renewable energy resources can be used as alternatives to oil. 2.2. oil producing (exporting) countries abounoori et al (2014) conducted research for the case of iran and revealed positive impact of oil price on inflation in short and long terms. however, using seasonal data and non-linear ardl, davari and kamalian (2018) concluded that there is no significant relationship between oil-price growth and inflation rate, but significant relationship between the reduction in oil price and inflation was observed. furthermore, researches by trang (2017) for vietnam, and bala and chin (2018) for algeria, angola, libya, and nigeria suggested that a rise in oil prices would lead to higher inflation. 3. model and data 3.1. data our study uses annual data over the period of 1995-2017 for the following variables: brent crude oil price (op), exchange rate (exc), inflation rate (inf). all data set have been retrieved from world development indicators of world bank (wb, 2018) and the international financial statistics database of the international monetary fund (imf, 2018.) for the purpose of analysis, the op is measured in u.s. dollars per barrel whereas the exc is measured in national currency per us dollar. the inflation is measured in the consumer price index (2010=100). in empirical estimations, all the variables were used in logarithmic form. 3.2. econometric methodology we examine the relationship between oil price, inflation rate and exchange rate by employing the cointegration and vector error correction model (vecm) framework in this study. first, we will check non-stationarity characteristics of variables. we will use the augmented dickey fuller unit root (dickey and fuller, 1981, adf) and philips and perron (philips and perron, 1998, pp) tests for this exercise. next, if the variables are integrated on the same order, then we can test whether they move together in the long-run, using a cointegration test. in order to be on the safe side, we will follow the latter option and hence, use the johansen test (johansen, 1988) as it is the only test that can produce proper results in the case where more than two variables are tested for cointegration. after confirming the presence of cointegration between the variables, we will apply the vecm method to investigate the long-run relationship among the variables. the above-mentioned methods are widely used techniques in similar studies, we do not describe them but their detailed discussions are provided in dickey and fuller (1981), philips and perron (1998), phillips and hansen (1990), johansen (1988) and johansen and juselius (1990), inter alia. 4. empirical results and discussion first, we should check the stationarity properties of the used variables. as mentioned in the methodology section, for this purpose, we use adf and pp unit root tests. results of unit root tests are presented in table 2. we find that the variables are non-stationary at their levels but they are stationary at first difference, being integrated of order one, i(1). we thus conclude that our variables are non-stationary in levels but stationary in their first differences. our conclusion that the variables are i(1) allows us to proceed to the cointegration test. to apply the johansen procedure, the optimal lag number should first be chosen. a vector auto regressive (var) model was initially specified with the endogenous variables of inf, op and exc. the details of this test are presented in table 3. both lag selection criteria and lag exclusion tests statistics propose that a lag of order three is optimal. panels a through d in table 4 report that the var has worthy features as it is stable, the residuals do not demonstrate serial correlation and heteroscedasticity issue and they are normally distributed. the johansen cointegration test results are presented in panels e and f of table 4. both the trace and the max-eigenvalue test statistics indicate one cointegration relationship among the variables. therefore, we conclude that there is a cointegrating relationship among the variables. finally, we estimate coefficients of the long-run relationship between inflation, oil price and exchange rate using vecm method. vecm results are reported in table 5. table 2: results of unit root tests variables the adf test the pp test level k first difference k level first difference inf −0.1302 0 −3.2297** 0 −0.1302 −3.2297** op −1.3953 0 −4.2440*** 0 −1.4525 −4.2024*** exc −1.9369 2 −3.1519** 0 −1.4556 −3.1717** adf and pp denote the augmented dickey-fuller and phillips-perron tests respectively. maximum lag order is set to two and optimal lag order (k) is selected based on schwarz criterion in the adf test; ***,** and *indicate rejection of the null hypotheses at the 1%, 5% and 10% significance levels respectively; the critical values are taken from mackinnon (1996) for the adf and pp tests respectively mukhtarov, et al.: the impact of oil prices on inflation: the case of azerbaijan international journal of energy economics and policy | vol 9 • issue 4 • 2019 101 as it can be seen from the table 5, the long-run coefficients from the vecm technique are statistically significant. additionally, the residuals of the estimated specifications successfully pass the residuals diagnostics tests, which is another indication of the robustness of the estimation results. the long-run coefficients are given in table 5. results show that op has a positive and statistically significant impact on inflation at 1% level. the results reveal that inflation responses by 0.58% increase to a 1% increase in brent crude oil price. having positive and significance impact of oil price, our finding is consistent with the results of tang et al. (2010) for china, cavalcanti and jalles (2013), u.s. and brazil, sibanda et al. (2015) for south africa, malik et al. (2017) pakistan, rasasi and yilmaz (2016) for turkey, ozturk (2015) for turkey. the impact of exchange rate on inflation is also found to be positive and statistically significant at 1% level. this shows that a 1% increase in exchange rate (depreciation of the national currency) results in 1.81% increase in inflation. this implies that an increase in exchange rate raises inflation. in addition, table 5 shows that the error correction term coefficient is negative and statistically significant at the 1% confidence level. this value indicates that any deviation from the short-run disequilibrium among the variables is corrected to return to the long-run equilibrium level within more than a year. 5. conclusion the study investigates the impact of oil price and exchange rate on inflation. after testing variables for a unit root, the results showed their stationarity at first differenced form, hence the variables can be tested for a common long-run trend. johansen trace and maximum eigenvalue tests concluded one cointegration relationship among the variables. this implies that there is a long run relationship between inflation, oil price and exchange rate in azerbaijan. the vecm approach is used to estimate the long run relationship among these variables. estimation results show that oil price and exchange rate increase inflation in the long-run, namely, a 1% increase in table 4: var residual diagnostics, stability and cointegration tests results panel a: lm test for serial correlationa panel e: johansen cointegration rank test (trace)e lags lm-statistic p value null hypothesis eigen value trace statistics 0.05 critical value p value 1 15.003 0.0908 none* 0.714244 37.65514 29.79707 0.0051 2 15.920 0.0686 at most 1 0.247170 8.844973 15.49471 0.3799 3 5.7016 0.7694 at most 2 0.095749 2.314910 3.841466 0.1281 4 8.4284 0.4916 panel b: normality testb panel f: johansen cointegration rank test (maximum eigenvalue)f statistic χ2 d.f. p value null hypothesis eigen value max-eigen statistic 0.05 criticial value p value jarque-bera 2.7993 6 0.833 none* 0.714244 28.81016 21.13162 0.0034 at most 1 0.247170 6.530063 14.26460 0.5461 at most 2 0.095749 2.314910 3.841466 0.1281 panel c: test for heteroscedasticityc white χ2 d.f. p value statistic 122.74 114 0.271 panel d: test for stabilityd athe null of the lm test is no serial correlation in residuals at lag of hth order; bthe normality test is the urzua (1997) system normality test, for this test the null states multivariate normality of residuals; cthe null for white heteroscedasticity test claims that there is no cross terms heteroscedasticity in the residuals; dvar stability test results conclude that all roots of characteristic polynomial are inside of the unit circle; χ2 stands for the chi-square distribution; d.f.: degree of freedom modulus root 0.9865 0.8073-0.5669i 0.9865 0.8073+0.5669i 0.6289 0.0141-0.6288i 0.6289 0.0141+0.6288i table 5: long‑run coefficients from the vecm method regressor coefficient standard error t-statistics op 0.58*** 0.06 8.48 exc 1.81*** 0.36 4.97 panel b: residuals diagnostics tests results and speed of adjustment coefficient soa −0.1755 [0.0007] lmsc 3.8775 [0.9193] χ2hetr 104.75 [0.1369] jbn 1.3366 [0.9696] dependent variable is inft; ***,** and * show significance levels at 1%, 5% and 10%; probabilities are in brackets; soa: speed of adjustment; lmsc: lagrange multiplier statistic of serial correlation test; χ2hetr: chi-squared statistic for heteroscedasticity test; jbn: jarque-bera statistic for testing normality; in vecm, jarque-bera statistic was taken from the option of orthogonalization: residual correlation (doornik-hansen). vecm: vector error correction model table 3: lag interval tests lag length information criteria lag logl lr fpe aic sc hq 0 −13.61685 na 0.001107 1.705813 2.002029 1.780311 1 34.80532 75.79123 3.66e-05 −1.722202 −0.981662 −1.535958 2 67.73680 42.95410 4.90e-06 −3.803200 −2.618336 −3.505210 3 94.30154 27.71973* 1.25e-06* −5.330569* −3.701381* −4.920833* *indicates lag order selected by the criterion, lr: sequential modified lr test statistic (each test at 5% level), fpe: final prediction error, aic: akaike information criterion, sc: schwarz information criterion, hq: hannan-quinn information criterion mukhtarov, et al.: the impact of oil prices on inflation: the case of azerbaijan international journal of energy economics and policy | vol 9 • issue 4 • 2019102 oil price and exchange rate increases inflation by 0.58% and 1.81%, respectively. during the period of the fixed exchange rate regime with the revalued national currency, an increase in consumer price index comoved with increasing oil prices until 2008. the estimation result also implies that low inflation could also be expected if oil prices were lower during the fixed exchange rate regime. indeed, low oil prices and decreased inflation comovement were also observed in 1996-1998, 2000-2001, 2008-2009, and 2011-2014. this is the case for an oil-dependent and less diversified economy, which is vulnerable to positive or negative external shocks. the less diversified economy tends to import most consumer and industrial goods from other countries to satisfy domestic demand. therefore, changes in oil prices that affect the economies of foreign countries affect the economies of oil exporting countries proportionally. this vulnerability is also attested by the result obtained for the impact of exchange rate such that the sharp drop in oil prices in 2014 caused devaluation of the national currency by 34% in 2015 and 48% in 2016 and also triggered inflation. in this regard, the exchange rate captures the role of the transmission channel from oil prices to inflation. results of both explanatory variables reveal that a less diversified economy undergoes inflation during the period of high and low oil prices. therefore, a resource dependent country should accelerate reforms on economic diversification to mitigate social and economic costs associated with external shocks. in this regard, preserving macroeconomic stability, particularly exchange rate and price stability, will increase confidence in the national currency, stimulate domestic and foreign investments, and promote sustainable economic development. references abounoori, a.a., nazarian, r., amiri, a. (2014), oil price pass-through into domestic inflation: the case of iran. international journal of energy economcis and policy, 4(4), 662-669. bala, u., chin, l. (2018), asymmetric impacts of oil price on inflation: an empirical study of african opec member countries. energies, 11(11), 3017. burbidge, j., harrison, a. (1984), testing for the effects of oil price rises using vector autoregressions. international economic review, 25(2), 459-484. cavalcanti, t., jalles, j.t. (2013), macroeconomic effects of oil price shocks in brazil and in the united states. applied energy, 104, 475-486. chen, d., chen, s., härdle, w.k. (2015), the influence of oil price shocks on china’s macro-economy: a perspective of international trade. journal of governance and regulation, 41(4-1), 178-189. cologni, a., manera, m. (2008), oil prices, inflation and interest rates in a structural cointegrated var model for the g-7 countries. energy economics, 30(3), 856-888. davari, h., kamalian, a. (2018), oil price and inflation in iran: nonlinear ardl approach. international journal of energy economics and policy, 8(3), 295-300. dickey, d., fuller, w. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica, 49, 1057-1072. eryigit, m. (2012), the dynamic relationship between oil price shocks and selected macroeconomic variables in turkey. economic research ekonomska istraživanja, 25(2), 263-276. gbadebo, o. (2009), identifying the oil price-macroeconomy relationship: an empirical mode decomposition analysis of us data. energy policy, 37(12), 5417-5426. hamilton, j. (1983), oil and the macroeconomy since world war ii. journal of political economy, 91, 593-617. hamilton, j. (1996), this is what happened to the oil price macroeconomy relationship? journal of monetary economy, 38, 215-220. international monetary fund. (2018), the international financial statistics. available from: http://www.data.imf.org/?sk=4c514d48-b6ba49ed-8ab9-52b0c1a0179b. [last accessed on 2018 oct 11]. johansen, s. (1988), statistical analysis of cointegration vectors. journal of economic dynamics and control, 12, 231-254. johansen, s., juselius, k. (1990), maximum likelihood estimation and inference on cointegration with applications to the demand for money. oxford bulletin of economics and statistics, 52, 169-210. katircioglu, s.t., sertoglu, k., candemir, m., mercan, m. (2015), oil price movements and macroeconomic performance: evidence from twenty-six oecd countries. renewable and sustainable energy reviews, 44, 257-270. malik, k.z, ajmal, h., zahid, m.u. (2017), oil price shock and its impact on the macroeconomic variables of pakistan: a structural vector autoregressive approach. international journal of energy economics and policy, 7(5), 83-92. mork, k. (1989), oil and the macroeconomy when prices go up and down: an extension of hamilton’s results. journal of political economy, 97, 740-744. mory, j.f. (1993), oil prices and economic activity: is the relationship symmetric? the energy journal, 14(4), 151-161. ozturk, f. (2015), oil price shocks-macro economy relationship in turkey. asian economic and financial review, 5(5), 846-857. papapetrou, e. (2001), oil price shocks, stock market, economic activity and employment in greece. energy economics, 23(5), 511-532. phillips, p.b., perron, p. (1988), testing for unit roots in time series regression. biometrika, 75, 335-346. phillips, p.c.b., hansen, b.e. (1990), statistical inference in instrumental variables regression with i(1) processes. review of economics studies, 57, 99-125. qianqian, z. (2011), the impact of international oil price fluctuation on china’s economy. energy procedia, 5, 1360-1364. rasasi, m.a., yilmaz, m. (2016), the effects of oil shocks on turkish macroeconomic aggregates. international journal of energy economics and policy, 6(3), 471-476. sibanda, k., hove, p., murwirapachena, g. (2015), oil prices, exchange rates, and inflation expectations in south africa. international business and economics research journal, 14(4), 587-602. strategic roadmap on national economy and key sectors of the republic of azerbaijan. available from: https://www.ereforms.org/store// media/ekspert_yazilari/islahat%20icmali/mart/strateji%20yol%20 x%c9%99rit%c9%99si%20-eng1.pdf. [last accessed on 2018 jan 25]. tang, w., wu, l., zhang, z., (2010), oil price shocks and their short and long-term effects on the chinese economy. energy economics, 32, 3-14. trang, n.t.n., tho, t.n., hong, d.t., (2017), the impact of oil price on the growth, inflation, unemployment and budget deficit of vietnam. international journal of energy economics and policy, 7(3), 42-49. werner, r. (2005), international oil price changes: impact of oil prices on growth and inflation in the eu/oecd. international economics and economic policy, 2, 15-32. world bank. (2018), world development indicators. available from: https://www.data.worldbank.org/indicator. [last accessed on 2018 oct 11]. wu, m.h., ni, y.s. (2011), the effects of oil prices on inflation, interest rates and money. energy, 36, 4158-4164. zhao, l., zhang, x., wang, s., xu, s. (2016), the effects of oil price shocks on output and inflation in china. energy economics, 53, 101-110. international journal of energy economics and policy vol. 4, no. 4, 2014, pp.726-734 issn: 2146-4553 www.econjournals.com structural breaks and causality relationship between economic growth and energy consumption in saudi arabia waheed a. banafea department of economics & budget, institute of public administration, riyadh 11141, saudi arabia. email: banafeaw@ipa.edu.sa abstract: the purpose of this paper is to empirically investigate the short and long run causality between economic growth and energy consumption in saudi arabia during the period of 1971-2012 using the gregory and hansen (1996) cointegration procedure and error-correction models. the results of the unit root tests with structural breaks indicate that total energy and gas consumption are stationary in levels. thus, we dropped these variables from the cointegration and causality analysis. the stable long run relationship between real gdp and oil consumption is detected by both stability and cointegration tests. the estimated breakpoints correspond with the period of 1974-1985 during the oil boom. the causal relationship is found between real gdp and oil consumption in both the short and long run. we found short run unidirectional granger causality running from real gdp to oil consumption. however, the long run unidirectional granger causality is detected from oil consumption to real gdp. therefore, the energy conservation policy in the long run should be designed with caution, since energy is considered an engine of gdp growth. keywords: energy consumption; structural breaks; causality; saudi arabia jel classifications: c20; q43; q48 1. introduction the relationship between economic growth and energy consumption has been extensively investigated in the literature. however, mixed results are found even for the same country under a different time period. kraft and kraft (1978) studied the relationship between economic growth and energy consumption for u.s. for the period from 1947 to 1974. they found evidence of a unidirectional causality running from gnp to total energy consumption. in contrast, yu and hwang (1984) found no evidence of causality between gnp and total energy consumption when the updated u.s. data for the period 1947-1979 are used. both papers employed sims causality methodology. moreover, cheng and lai (1997) investigated the causality between gdp and total energy consumption for taiwan during the period of 1955-1993. the results of their study indicated that there is a unidirectional causality that runs from gdp to energy consumption. however, when lee and chang (2005) reexamined the causality using both aggregate and disaggregate data categories for energy consumption for the period of 1954-2003 in taiwan, the results showed evidence of bidirectional causality that runs from gdp to total energy and gas consumption and vice versa. the authors mentioned that structural breaks are important and should be taken into account when examining the relationship between economic growth and energy consumption. they indicated that failure to take into account the influence of structural breaks may lead to a distorted outcome. the relationship between economic growth and energy consumption is likely to be subject to changes due to economic crises, fluctuations in energy prices, reforms in energy regulation, or changes of energy policy. therefore, these changes may create structural changes and need to be accounted for when studying the stability and direction of the relationship between economic growth and energy consumption. previous works on the causality relationship between economic growth and energy consumption in saudi arabia revealed conflicting results. some studies support the conservation hypothesis, which states that there is a unidirectional causality running from economic growth to energy consumption (al-iriani, 2006; mehrara, 2007a; chontanawat et al., 2008). in contrast, mehrara (2007b) found results that support the growth hypothesis, which states that there is a unidirectional causality that runs structural breaks and causality relationship between economic growth and energy consumption in saudi arabia 727 from energy consumption to economic growth.the feedback hypothesis, which states that there is bidirectional causality between economic growth and energy consumption is supported by mahadevan and arafu-adjaye (2007) and squalli (2007). al-irian (2006) investigates the relationship between real gdp and total energy consumption for the gulf cooperation council (gcc) for the period of 1971-2002 using pedroni panel cointegration and based-panel error correction models (ecm). the results support the conservation hypothesis, which denotes that the energy conservation policies in saudi arabia can be implemented with little concern about the effects on gdp. mehrara (2007a) reexamined the causality issue between the real gdp per capita and the commercial energy usage per capita for oil exporting countries including saudi arabia for the period of 1971-2002 using pedroni panel cointegration and panel ecm. the results support the previous findings by al-irian (2006). mehrara (2007b) applied johansen’s maximum likelihood approach, the causality procedure by toda and yamamota (1995), and ecm to test the causality between commercial energy usage per capita and real gdp per capita in saudi arabia for 1971-2002 period. this study showed that causality runs from energy consumption to gdp without feedback. mahadevan and asafu-adjaye (2007) utilized panel and time series methods to investigate the causality between real gdp and total energy consumption for saudi arabia for the period 1971-2002. they found evidence of bidirectional causality between the two variables. using disaggregate data of energy consumption, squalli (2007) investigated the causal relationship between electricity consumption and gdp in saudi arabia for the 1980-2003 period. using the ardl-bounds test and toda and yamamota’s (1995) causality procedure, the results indicated that causality runs from gdp to electricity consumption with no feedback. chontanawat et al. (2008) found that there is a unidirectional causality running from gdp to total energy consumption for saudi arabia for the period 1971-2000 by employing johansen and juselius and ecm. a mix of low-income, middle-income, and high-income countries was considered by huang et al. (2008), who conducted a dynamic panel approach and covered the period of 1972-2002. the results showed a unidirectional causality from gdp to total energy consumption for the high and middle-income panels and no evidence of causality for the low-income panel. using data from 11 middle eastern and north african countries including saudi arabia, ozturk and acaravci (2011) examined the short and long run causality issues between electricity consumption and economic growth for the period 1971-2006. they employed the autoregressive distributed lag (ardl) bound test of cointegration and vector error correction models (vecm). the results showed that there is evidence of unidirectional long and strong granger causality from electricity consumption to real gdp in saudi arabia. shahateet (2014) utilized ardl and granger causality to test the causality relationship between energy consumption and economic growth in 17 arab countries including saudi arabia. the results indicated that there is no causality from economic growth to total energy consumption and the other way around in saudi arabia. the purpose of this paper is to examine the short and long run causality relations between economic growth and energy consumption in saudi arabia for the period 1971-2012. the stability tests and cointegration technique are applied to examine the stability of the longrun relationship between real gdp and energy consumption. next, granger causality procedure is conducted to establish any causal relationship among the two variables. what distinguishes this paper from the previous work on saudi arabia is that this paper considers evidence from the recent period since it extends the data set to include 1971 to 2012. in addition, since perron (1989) pointed out that the presence of structural breaks in a series can lead to misleading results; this paper takes into consideration the effect of structural breaks on the relationship between economic growth and energy consumption by using the cointegration test by gregory and hansen (1996). the reminder of this paper is organized as follows. section 2 discusses methodology and data sources. section 3 presents empirical results with policy implication. section 4 concludes the paper. 2. methodology and data following the literature, the empirical model of the long run relationship between economic growth and energy consumption can be written as follows: = + + ∈ (1) international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.726-734 728 where y is the real gdp per capita and is the energy consumption. this paper uses annual time series data of gdp per capita for the period of 1971-2012, total energy consumption (henceforth, ec) for the period of 1971-2011, and gas and oil consumption for the period of 1971-2012. gdp per capita is expressed in constant 2005 us$, total energy consumption is expressed in terms of kg oil equivalent per capita, and gas consumption is expressed in terms of million tons of oil equivalent. all of the variables in the model are in natural logarithms.the data of gas and oil consumption are obtained from bp statistical review of world energy, while gdp per capita and ec are taken from the world development indicators produced by the world bank. three steps will be performed to test for causality between economic growth and energy consumption. first, testing will be performed for unit root in gdp, ec, gas, and oil consumption to determine the order of integration. second, the long run relationship between the variables in equations will be tested using the cointegration technique, which allows for a one-unknown structural break. finally, the granger causality procedure is used to examine the short run and long run causality relations between economic growth and energy consumption. saudi arabia depends heavily on the export of oil and gas, and that may lead to instability of the economic system of the country. it has an oil-based economy, and fluctuations in the prices of oil or gas likely created structural breaks. the use of conventional unit root tests together with cointegration techniques that are not taking into account structural breaks may lead to distorted results. in addition, it is a common problem that macroeconomic series are affected by regime shifts in economic events. hamilton (2003) showed that an increase in oil prices is more influential than a decrease in oil prices. therefore, there is a high chance of creating instability of the relationship between economic growth and energy consumption. hooker (2002) indicated that oil prices have a direct effect on inflation, and taking that in the consideration in the specification of structural breaks provides a better fit on the data. figure 1 shows evidence of trend and structural breaks, especially for the gdp. therefore, if we neglect the structural breaks in our analysis, then we may conclude that the series are not stationary or that the relationship between economic growth and energy consumption is unstable. 2.1. unit root tests with structural breaks two unit root tests are conducted in this paper to determine the order of integration, namely zivot and andrews (henceforth, za) (1992) and perron (1997). both tests deal with a structural break as endogenous. the za test is a developed version of the perron (1989) test. za uses three models to test a unit root, shift in the intercept (henceforth, a), shift in the slope (henceforth, b), and shift in both intercept and slope (henceforth, c). sen (2003) indicated that using model a instead of the model c can lead to a substantial power loss if the break occurs in model c. however, if the break occurs in model a when model c is used, then the power loss is minimal. thus, model c is conducted to examine the null hypothesis of a unit root against the alternative of trend stationary process with a one-unknown structural break. the regression form can be written as = + + + + + ∆ + ∈ (2) where δ is the first difference operator, dut and dtt are indicator dummy variables for a mean shift and a trend shift, respectively; dut= 1 and dtt= t – tb if t > tb; 0 otherwise. tb denotes the time at which the structural break occurs. the date of a structural break is determined according to the smallest t-statistics. t = 1, …, t denotes an index of time, and ∈t is a white noise disturbance. the lag length is determined using the akaike information criterion (aic). asymptotic distribution of the minimum t-statistic and critical values are provided by zivot and andrews (1992). an alternative unit root test is proposed by perron (1997). similar to the za test, perron (1997) uses the three models mentioned above to test a unit root against the alternative of a trend stationary process with a one-unknown structural break. this test differs from the za test by adding a one-time shock dummy variable. moreover, the perron test chooses the breakpoint where the t-statistic for testing α = 1 is the minimum or where the t-statistic on the change in slope on the break term is the minimum. the model with shift in both intercept and slope can be written as follows: structural breaks and causality relationship between economic growth and energy consumption in saudi arabia 729 = + + + + + + ∆ + ∈ (3) where dtb = 1 if t = tb + 1. the lag parameters are determined using aic. 2.2. cointegration analysis the gregory and hansen (1996) cointegration tests (henceforth, gh) is an extension of the residual-based tests that take into account the possibility of a one-time unknown structural break in the intercept alone or in both intercept and coefficient vector. the null hypothesis under these tests is that there is no cointegration with a structural break against the alternative that there is cointegration with a structural break. gregory and hansen indicate that, when the standard adf test is used in the cointegration analysis without taking into account the one-time regime shift, it may lead to misleading conclusion that the long run relationship between the dependent variable and its determinants is not exists. they propose three models: level shift (c): = + + + ∈ (4) level shift with trend (c/t): = + + + + ∈ (5) regime shift (c/s): = + + + + ∈ (6) they also propose three test statistics, namely ∗ = ( ), which is the modified version of the engle and granger (1987) cointegration test, and ∗ = ( ) and ∗ = ( ), which are both modified versions of phillips and quliaris (1990). the breakpoint is the smallest value of these three test statistics. the modified mackinnon (1991) critical values are used instead of the critical values which are used in the engle and granger method. 2.3. causality analysis the two-step procedure from engle and granger (1987) are used to examine the short run (weak causality) and long run (weak erogeneity) granger causality between the economic growth and energy consumption. the first step is to estimate the residuals from the long run relationship. the second step is to add the residual as a variable on the right-hand side in the dynamic ecm. the ecm can be specified as follows: ∆ = + + + + ∈ (7) ∆ = + + + + ∈ (8) where ect is the lagged error term, which is derived from the long run cointegrating relationship. is the adjustment coefficient, which shows how fast deviations from the long run equilibrium are eliminated following changes in each variable. the short run causality is examined by testing: : = 0 and : = 0 for all i and j in equations (7) and (8), respectively, while the longrun causalityis examined by testing: : = 0 and : = 0 in equations (7) and (8), respectively. 3. empirical results 3.1. unit root test results two conventional unit root tests are applied, namely augmented dickey-fuller (1979) (henceforth, adf), and phillips and perron (1988) (henceforth, pp) to test the null hypothesis of a unit root. both the adf and pp tests don’t take into account the possibility of structural breaks. therefore, they may lead to a misleading result when accepting the null hypothesis of a unit root. the plot of the log-level series shows that all the variables have trend (figure 1). thus, the unit root tests are run with constant and trend. the selection of the lag length is determined by applying the aic. the results of the adf and pp unit root tests are reported in table 1. the results indicate that gdp, ec, gas, and oil have unit root at levels. however, all variables are stationary in the first international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.726-734 730 difference at the 5% and 1% levels of significance. these results show that gdp, ec, gas, and oil are integrated of order one, i (1). figure 1. log values of gdp and energy consumption table 1. results of unit root tests without structural breaks variables adf pp levels first difference levels first difference gdp -1.848 (2) -3.556** (0) -2.096 -3.556** ec -2.703 (2) -5.169*** (0) -1.545 -5.18*** gas -1.736 (0) -6.953*** (0) -1.759 -6.948*** oil -2.657 (0) -7.535*** (0) -2.624 -7.694*** **, *** denote significance at the 5% and 1% levels, respectively. the number of lag order is shown in parentheses. figure 1 shows that gdp, ec, and oil might have structural breaks in the 1970s. therefore, the za and perron unit root tests are utilized. the lag length is chosen by aic. the results of the za and perron tests are reported in tables 2 and 3, respectively. as can be seen from tables 2 and 3, the results from za and perron tests suggest that gdp and oil series are i (1); however, ec and gas are i(0). the structural breaks which took place in the 1970s and 1980s refer to the period of the oil boom, 1974-1985. due to the higher oil revenues, the saudi government made major structural changes in the economy. in the mid 1970s, saudi arabia used most of the oil revenues for massive development efforts. they focused mostly on industrialization, airports, schools, roads, and ports. in the 1980s, saudi arabia increased its oil and gas resource development through downstream investment in refineries and petrochemical plants. also, during that period saudi arabia started to treat natural gas as a valuable resource instead of wasting it (http://lcweb2.loc.gov/frd/cs/satoc.html). structural breaks and causality relationship between economic growth and energy consumption in saudi arabia 731 table 2. za unit root test results variables levels break date first differences break date gdp -5.011 (2) 1982 -6.372 (0)*** 1986 ec -5.759 (2)*** 1984 -7.419 (0)*** 1982 gas -5.176 (0)** 1984 -8.467 (0)*** 1981 oil -4.320 (0) 1977 -8.196 (0)*** 1984 **, *** denote significance at the 5% and 1% levels, respectively. the number of lag order is shown in parentheses. table 3. perron unit root test results variables levels break date first differences break date gdp -4.904(0) 1981 -6.726 (0)*** 1985 ec -6.216 (0)** 1977 -7.371 (0)*** 1981 gas -6.651 (0)*** 1983 -8.311 (0)*** 1980 oil -4.312 (0) 1978 -8.386 (0)*** 1977 **, *** denote significance at the 5% and 1% levels, respectively. the number of lag order is shown in parentheses. the za and perron unit root tests found different dates of structural breaks. however, this is consistent with some previous empirical results. lee and chang (2005) used both za and perron tests to examine the unit root in gas consumption. the results of za indicated that there is a significant breakpoint that occurred in 1964 in gas consumption, while the results of perron test showed that a breakpoint occurred in 1962 for the same series. 3.2. cointegration test results the results of the za and perron unit root tests suggest that we should proceed in our analysis only with variables that are from order one, gdp and oil. consequently, we should drop total energy and gas consumption from the cointegration and causality analysis. in this section, the long run relationships between gdp and oil consumption are investigated by using both stability and cointegration techniques. before proceeding with the cointegration analysis, we test the stability of the model by the cumulative sum (cusum) and cumulative sum of squares (cusumsq) tests proposed by brown et al. (1975). figure 2 shows the plot of cusum and cusumsq test statistics for the gdp-oil model. the results of both tests indicate that the model is stable in the long run, since the test statistics fall inside the critical bounds of 5% significance. the next step is to investigate the long run relationships between gdp and oil consumption using the cointegration technique, which takes into account a one-time unknown structural break. perron (1989) indicated that ignoring the presence of potential structural breaks can lead to wrong results not only in the unit root tests but also in the cointegration tests. in addition, kunitomo (1996) pointed out that the traditional cointegration tests, which don’t allow for structural breaks, may lead to spurious cointegration. figure 2. plot of cusum and cusumsq stability tests -20 -15 -10 -5 0 5 10 15 20 1975 1980 1985 1990 1995 2000 2005 2010 cusum 5% significance international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.726-734 732 the results of the gh are reported in table 4. the results indicate that the null hypothesis of no cointegration is rejected in favor of the existence of one cointegration with a one-time unknown structural break in the gh (c/t) model. the breakpoints are consistent across models. the break date of the year 1975 corresponds with the high oil prices following the arab oil embargo and the death of king faisal al-saud. in fact, the breakpoint of 1975 could be explained as the full effect of the 1973 oil crisis. if it is possible to determine the exact date of a structural break, the full effect of this structural break would not occur instantly (enders, p. 106). table 4. gregory and hansen tests results model break date adf* break date zt* break date za* c 1975 -3.865 (0) 1975 -3.88 1975 -22.266 gdp-oil c/t 1975 -4.927 (0)* 1975 -4.99* 1975 -31.481 c/s 1976 -3.932 (0) 1976 -3.899 1976 -21.783 * denotes significance at the 10% level.the number of lag order is shown in parentheses. 3.3. causality test results since there is evidence of cointegration between gdp and oil consumption, we proceed with our analysis by investigating whether there is a causal relationship among both variables. cointegration implies that causality exists between the gdp and oil consumption, but it does not show the direction of the causal relationship. granger (1988) indicated that, when there is evidence of cointegration among variables, there should be at least one unidirectional granger causality among the variables. the results of short and longrun granger causalities are presented in table 5. the ect is derived from the long run equation (5), which represents the level shift with the trend (c/t) model. a significant ect with a negative sign suggests that the cointegration relationship established previously is valid as per granger’s representation theorem (engle and granger, 1987). table 5. results of granger causality tests null hypothesis short-run long-run f-statistics t-statistics (h0:α = 0) ∆oil→∆gdp 2.22 ( 0.123) (h0: δ = 0) ∆gdp→ ∆oil 3.79 ( 0.032)** (h0:θ = 0) ect → ∆gdp -1.95* [-0.103] (h0:θ = 0) ect →∆oil 0.83 [0.065] *, ** denote the significance at the 10% and 5% levels, respectively. the number of optimal lag is selected by aic. the numbers in parentheses are probabilities.the numbers in brackets are error-correction coefficients.→ denotes unidirectional causality. from the gdp equation, the results indicate that there exists one-way long run causality from oil consumption to gdp, as t-test rejects the null of no causality at the 10% significance level. however, no evidence of long run causality is found in the oil equation, as the t-test does not reject the null of no causality. therefore, there is a unidirectional granger causality running from oil consumption to gdp, which is consistent with mehrara (2007b). these results imply that the energy conservation policies in saudi arabia may be formulated to conserve energy with much concern about the effects of gdp -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1975 1980 1985 1990 1995 2000 2005 2010 cusum of squares 5% significance structural breaks and causality relationship between economic growth and energy consumption in saudi arabia 733 growth in the long run. therefore, phasing out the energy subsidies may lead to a negative impact on gdp growth. the results of the short run granger causality indicate that causality runs from gdp to oil consumption as the f-test rejects the null of hypothesis of no causality at the 5% significance level in the oil equation. however, there is no evidence of short run causality running from oil consumption to gdp in the gdp equation, since the f-test does not reject the null hypothesis of no causality. thus, there is a unidirectional short run granger causality running from gdp to oil consumption, which is consistent with al-iriani (2006), mehrara (2008a), and chontanawat et al. (2008). these results imply that the energy conservation policies should be formulated to conserve energy without much concern about the effects on gdp growth in the short run. 4. conclusion this paper aims to investigate the short and long run causality relations between economic growth and energy consumption for the period of 1971-2012 in saudi arabia. saudi arabia has an oil-based economy, and fluctuations in the oil prices likely created structural breaks. to take into account the possibility of structural breaks in our analysis, we utilized the unit root tests and the cointegration test that allow for a one-unknown structural break. also, a dynamic vector error correction models (vecm) are used to examine the causality between economic growth and energy consumption. different categories of energy were applied as a measure of energy consumption such as total energy, gas, and oil. the results of the unit root tests, za and perron, indicated that total energy and gas consumption are stationary variables in levels. both tests showed that the structural breaks occurred in 1977, 1983, and 1984. these breakpoints correspond with the period of the oil boom, 1974-1985. thus, total energy and gas consumption were dropped from our analysis. the results of the gh (c/t) model showed that the long run relationship exists between real gdp and oil consumption. the gh cointegration tests indicated that the structural break took place in 1975. the breakpoint of the year 1975 corresponds with the high oil prices following the arab oil embargo andthe death of king faisal al-saud. this breakpoint could be explained as the full effect of the 1973 oil crisis. this paper finds evidence of one-way long run granger causality from oil consumption to real gdp. this result implies that an energy conservation policy will hinder the economic growth of saudi arabia. thus, in the long run, the energy conservation policy should be formulated to conserve energy with much concern about the effects on gdp growth. moreover, one-way short run granger causality is found from real gdp to oil consumption. this implies that energy conservation may not harm economic growth. thus, in the short run, the energy conservation policy in saudi arabia should be formulated with no caution regarding the effects on gdp. the future work should be focused on the effect of structural breaks on the relationship between economic growth and energy consumption in gcc countries. structural breaks are important, and failure to take them into account when analyzing the relationship between economic growth and energy consumption may lead to the wrong results, especially in countries like gcc, which depend heavily on the export of oil and gas. references al-iriani, m. a. (2006). energy-gdp relationship revisited: an example from gcc countries using panel causality. energy policy 34, 3342-3350. brown, r.l., durbin, j., evans, j.m. (1975).techniques for testing the constancy of regression relationships over time. journal of the royal statistical society 37, 149-192. cheng, s.b., lai, t.w. (1997).an investigation of cointegration and causality between energy consumption and economic activity in taiwan province of china. energy economics 19, 435-444. chontanawat, j., hunt, l., pierse, r. (2008). does energy consumption cause economic growth? evidence from a systematic study of over 100 countries. journal of policy modeling 30, 209-220. dickey, d.a., fuller, w.a. (1979). distribution of the estimators for autoregressive time series with a unit root. journal of american statistical association 74, 427-431. enders, w. (2010). applied econometric time series. hoboken, nj: john & sons. engle, r.f., granger, c.w. (1987). cointegration and error correction: representation, estimation, and testing. econometrica 55, 251-276. international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.726-734 734 granger, c.w. (1988).some recent development in a concept of causality.journal of econometrics 39, 199-211. gregory, a., hansen, b. (1996).residual-based tests for cointegration in models with regime shifts. journal of econometrics 70, 99-126. hamilton, j.d. (2003). what is an oil shock?.j ournal of econometrics 113, 363-398. hooker, m.a. (2002). are oil shocks inflationary? asymmetric and nonlinear specifications versus changes in regime.journal of money, credit, and banking 34, 540-561. huang, b.n., hwang, m.j., yang, c.w. (2008). causal relationship between energy consumption and gdp growth revisited: a dynamic panel data approach. ecological economics 67, 41-54. kraft, j., kraft, a. (1978).on the relationship between energy and gnp. journal of energy and development 3, 401-403. kunitomo, n. (1996). tests of unit roots and cointegration hypothesis in econometric models. japanese economic review 47, 79-109. lee, c.c., chang, c.p. (2005). structural breaks, energy consumption, and economic growth revisited: evidence from taiwan. energy economics 27, 857-872. library of congress. (1993). a country study: saudi arabia: library of congress (call number d5204.53115 1993). retrieved march 10, 2014, from http://lcweb2.loc.gov/frd/cs/satoc.html mahadevan, r., asafu-adjaye, j. (2007). energy consumption, economic growth and prices: a reassement using panel vecm for developed and developing countries. energy policy 35, 24812490. mehrara, m. (2007a). energy consumption and economic growth: the case of oil exporting countries. energy policy 35, 2939-2945. mehrara, m. (2007b). energy-gdp relationship for oil-exporting countries: iran, kuwait, and saudi arabia. opec review 31, 1-16. ozturk, i., acaravci, a. (2011). electricity consumption and real gdp causality nexus: evidence from ardl bounds testing approach for 11 mena countries. applied energy 88, 2885-2892. perron, p. (1997). further evidence on breaking trend functions in macroeconomic variables. journal of econometrics 80, 335-385. perron, p. (1989). the great crash, the oil price shock, and the unit root hypothesis. econometrica 57, 1361-1401. phillips, p., perron, p. (1988).testing for a unit root in time series regression. biometrika 75, 335-346. phillips, p., quliariris, s. (1990). asymptotic properties of residual based tests for cointegration. econometrica: journal of the econometric society, 165-193. shahateet, m. (2014). modeling economic growth and energy consumption in arab countries: cointegation and causality analysis. international journal of energy economics and policy 4, 349-359. sen, a. (2003). on unit-root tests when the alternative is a trend-break stationary process. journal of business & economic statistics 21, 174-184. squalli, t. (2007). electricity consumption and economic growth: bounds and causality analysis of opec countries. energy economics 29, 1192-1205. yu, e., hwang, b. (1984). the relationship between energy and gnp: further results. energy economics 6, 186-190. zivot, e., andrews, d. (1992).further evidence on the great crash, the oil price shock, and the unit root hypothesis. journal of business and economic statistics 10, 936-954. . international journal of energy economics and policy | vol 10 • issue 4 • 2020234 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(4), 234-239. the effects of environment, society and governance scores on investment returns and stock market volatility bharat kumar meher1, iqbal thonse hawaldar2*, latasha mohapatra3, cristi spulbar4, ramona birau5 1department of commerce, manipal academy of higher education, manipal, karnataka, india, 2department of accounting and finance, college of business administration, kingdom university, bahrain, 3department of commerce, manipal academy of higher, manipal, karnataka, india, 4faculty of economics and business administration, university of craiova, craiova, romania, 5faculty of social sciences, university of craiova, craiova, romania. *email: thiqbal34@gmail.com received: 28 january 2020 accepted: 30 april 2020 doi: https://doi.org/10.32479/ijeep.9311 abstract sustainability reporting and disclosure in india have received a significant attention over the most recent few years propelled to a large extent by investors and policy makers. the sustainable business leadership forum (sblf) has been closely working with many firms, owners of the companies and policy makers to single out the relationship between investment and environmental, social and governance (esg) disclosure. besides that, sblf has had a coordinated conversation about the anticipations, concerns, difficulties and realities surrounding esg estimation. this esg criteria refers to three important elements which are considered by investors with regards to an ethical impact of firms and sustainable practices. as per the literature companies with higher esg scores are better investment picks. this paper attempts to assess the volatility and returns of indian companies and to measure the impact of esg scores on returns and volatility with the help of panel regression. keywords: environmental, social and governance, environmental, social and governance scores, sustainability, panel regression, investment returns jel classifications: d22, g11, g14, g32 1. introduction the concept of sustainable investing has been in existence in the financial world since 1980s. in current era sustainable investment is coined as environmental, social and governance (esg) investing where esg refers to environment, society and governance. “the story of esg investing in capital market started in january 2004, un secretary general kofl annan had written over 50 ceos of major financial institution, encouraging them to participate in a joint initiative under the patronage of the un global compact and with the assistance of swiss government and international finance corporation. he tried to inculcate esg into capital markets” (duuren et al., 2016). “the share market is a brawny indication for economic conditions of a country” (schneider et al., 2010). the concept of sustainable investment is very challenging, especially in the context of global economy. moreover, it is pivotal to promote economic, social, and environmental advancement in order to accomplish sustainable investment. presently esg investing is gaining more importance due to its long-term sustainability investing strategy. investors have now amplified their epicentre on esg, and it is ostensible by the expansion in esg assets globally. some researchers argued that “esg rating agencies, acting as pertinent financial market troupers, should take a stand on operating towards achieving a more sustainable development” (kumar et al., 2016). however, “knowledge related to financial impact of esg criteria remains fragmented” (khatri, 2016). a sustainable stock market (hawaldar, 2016; mallikarjunappa and iqbal, 2003) should be able to guarantee an optimal level of transparency and effective solutions to sensitive issues related to this journal is licensed under a creative commons attribution 4.0 international license meher, et al.: the effects of environment, society and governance scores on investment returns and stock market volatility international journal of energy economics and policy | vol 10 • issue 4 • 2020 235 society, environment, economic and corporate governance aspects. besides that, a sustainable stock market encourages sustainable investments and responsible corporate performance. various academicians and researchers are now studying the different aspects of esg. for instance, one study has explained how composition of directors’ board can affect the esg performance of a company (barberis et al., 1998) (iqbal and mallikarjunappa, 2011), while other studies focus on esg scores implications on csr scores and value of firms (yoon, lee and byun, 2018), iqbal and mallikarjunappa, 2010), (birindelli et al., 2018) different research studies have explained how investors could take esg elements into their consideration while taking decisions related to investments (cao et al., 2019), (friede et al., 2015), (humphrey et al., 2012). other researchers have made a comparative analysis of european sri indices based on esg scores (de and clayman, 2015). empirical studies also examined the effect of esg scores on uk firms (doyle, 2018). another study has conducted on us sample to examine whether portfolio comprising of high ranked esg scored firms outperform low ranked esg scored firms (gocejina, 2018), (iqbal and mallikarjunappa, 2010). other researchers suggested that most underpriced stocks with poor esg performance have the highest risk adjusted returns, while most overpriced stocks with good esg performance have the lowest risk adjusted returns (cao et al., 2019). some empirical studies reveal that “higher esg scores are allied to higher profitability, higher values of stock (and consequently greater general collateral value) and more favourable returns from mergers and acquisitions activity and lower risk” (loof and stephan, 2019). independent specialized organizations and agencies classify world’s countries in several main categories based on internationally agreed standards. it is relevant for our research study to identify the correct place of indian market in the global hierarchy (iqbal and mallikarjunappa, 2007). “a first classification divides the world’s countries into three main categories i.e. developed markets, emerging markets, and frontier and standalone markets, and india is included in the second category of emerging markets” (iqbal and mallikarjunappa, 2011), (khan et al., 2018). another recognized international classification uses quantitative data to initially assess market eligibility for the three major country classifications: developed, emerging and frontier and india is one of the most representative emerging countries with a global weight of 12.78% (kell, 2018). moreover, another main stock markets classification is internationally recognized based on the following main categories: developed, advanced emerging, secondary emerging and frontier (khan et al., 2018). this time india is being included in the category of advanced emerging, being part of the brics along with brazil, russia, china and south africa. 2. literature review in literature, a stock market is perceived as an effective barometer indicating the economic health of a country. a wide deliberation continues the futuristic effects of stock markets for the purpose of sustainable economic development. economic sustainability represents the capacity of an economy to assist a certain level of economic production and long-term economic growth without creating any adverse impact on the environmental, cultural or social factors for an infinite period. practically, “the maintenance of the stock of natural resources must be an important segment of economic policymaking, particularly in underdeveloped and less developed countries because the reverse of this situation implies facing inadequacy of wealth invoked by depreciating of their environment” (verheyden et al., 2016). however, “many different opinions in the literature suggesting, expecting of win–win, sustainable growth through new technology and improvements in efficiency, have not been satisfied thus generating the desire for an optimal option, respectively the new concept of sustainable degrowth which reflects an equitable de-escalating of consumption and production that uplifts human wellbeing and improves ecological conditions at domestic and international level, in case of short as well as long term” ((salih, 2003 and sneddon et al., 2006). nevertheless, “alarming levels of ecological degradation, colossal inequalities in economic juncture both intra and inter societies, and a disrupted set of institutional arrangements for international environmental governance all reveal seemingly insurmountable hindrances to follow the path of sustainability” (siew et al., 2016). in india, esg has not yet grasped the importance as it has gained worldwide. in order to popularize the concept of esg, the ministry of corporate affairs published the “national voluntary guidelines on social, environmental and economic responsibilities of business” in 2011. from 2012, the top 100 listed companies according to market capitalization are depicting business responsibility reports in their final reports. this paper is an attempt to single out the relationship between the scores of esg elements, returns on stock and volatility of stock. moreover, this study is also an attempt to know the scores of each element of esg given in the sustainability reports could become significant explanatory variables in predicting the volatility and returns of the stocks of companies in nifty 100 enhanced esg. for asset managers the application of esg measures to reflect corporate social performance has received a growing attention and is currently demanded by most financial investors (lee et al., 2013). certain research studies indicated that “both high esg scores and low volatility positively affect returns on stock, but the esg effect is independent of the low-volatility effect, and esg is a positive contributor in its own right” (raza, 2018). there are high expectations on the stability of esg scores during the period in which they are reported. “the market placed a more stabilized pricing penalty on firms with lower esg scores than it awarded firms with higher esg scores” (kjerstensson and nygren, 2019). other researchers suggested that “companies that incorporate esg factors reflects lower volatility in their stock performances than their competitors in the same industry, that each industry is stimulated differently by factors of esg, and that esg companies bring higher returns” (friede et al., 2015). on the other hand, certain researchers suggested that “the presence of institutional investors decreases market information asymmetry because there is a propensity for institutional owners to unfairly use the private information related to esg gained through their position” (siew et al., 2016). moreover, other empirical studies stated that “public sentiment affects investor opinion about the meher, et al.: the effects of environment, society and governance scores on investment returns and stock market volatility international journal of energy economics and policy | vol 10 • issue 4 • 2020236 value of corporate sustainability activities and thereby both the price paid for sustainability of corporate and the returns on investments of portfolios that consider esg data” (nagy et al., 2013). emerging stock markets like india are featured by some attributes, such as systemic vulnerability, lofty volatility, embryonic trading mechanisms, problems related to financial regulation, non-liquidity, inadequate transparency, challenging task to access all information that are available, meagre volume trading, opportunities of diversification, different risk categories and unpredictable situations. however, some researchers argued that “modern investors can earn more returns by taking advantage of over and under reaction without bearing extra risk” (verheyden et al., 2016). the objectives of this paper is to examine whether the scores given to the various elements of esg mentioned in the sustainability reports of indian companies could become significant variables that affects the volatility and returns of stocks, to determine whether a reliable model could be developed to predict the volatility and returns with the help of esg scores and to validate whether the companies with better esg scores should become the investment picks for investors. 3. research methodology this research study is analytical in nature. the data used in this study are basically from secondary source i.e. from nse india and yahoo finance. the scope of study is limited to companies in the nifty100 enhanced esg. the study is based on 43 companies out of 48 companies in nifty 100 enhanced esg. the sample period for this research study covers the period from april 2014 to december 2018. all the environment, society and governance scores of each company are taken from yahoo finance, returns are calculated by using capital assets pricing model (capm) i.e. capital asset pricing model and the volatility is calculated on yearly basis. e-views software is used to apply panel regression in order to investigate the impact of environment, society and governance scores on the historical volatility and returns, and to know whether a reliable model could be developed to predict the expected historical volatility and returns for future. the study is a realistic approach to include esg as a major factor in taking investment decisions in indian stock market. this research highlights whether the scores of esg mentioned in the sustainability reports can become a major factor that affects the returns and volatility. this will help the investors to know the importance of esg while making investing decisions in this present era. this study can also depict whether the promotion of sustainable investing in india is creating an impact among investors. limitations of the study • esg scores related to five companies of few years are missing due to which these companies are not taken into consideration in formulating the model • in this study only those companies are taken into consideration which is under nifty100 enhanced esg. moreover, the results of this study could only be more reliable for indian stock market if the esg scores of every company in daily basis will be disclosed • the data related to esg is available on year wise, due to which historical volatility or moving average volatility has been used to frame the model. if data related to esg will be available on daily basis then day wise volatility could be used with the help of arch or garch, which could make the model more authentic. 4. empirical analysis and results the study considers the hypothesis that the companies with better esg scores should become the investment picks for investors. as per many reports, in india, now the investors are more interested in sustainable investing. this sustainable investing has emerged as a major trend over the last few years. it focuses on how companies handle their esg risks, which is particularly important for emerging markets like india (escrig-olmedo et al., 2019). the theory says companies with higher esg score are better investment picks. “there is good evidence in research depicting that more sustainable companies and funds can assist to manage risk without making any compromise to returns” (dorfleitner et al., 2015). in order to validate the theory taking the indian stock market as an area of study, an attempt has been made to find out the relationship between the scores of environments, social and governance with the returns and historical volatility. such relationship is being studied because investment on stocks having high esg scores can be considered as better investment, if there is direct relationship between scores of esg elements with the returns and an inverse relationship between scores of esg elements with historical volatility. hence two models have been formulated. in the first model the scores of environment, society and governance are independent variable and returns of 43 companies are dependent variable and in the second model again the scores of environment, society and governance are independent variable and historical volatilities of 43 companies are dependent variable. the scores of every element of esg are collected from the sustainability reports and compiled as panel data. the stock returns of 43 companies over the period of 4 years 9 months (from april 1, 2014 to december 31, 2018) are assessed based on capm, by applying the following formula: ri=rf+β(rm–rf) similarly, historical volatility of 43 companies over the period of 4 years 9 months (april 1, 2014–december 31, 2018) are assessed with the help of the following variance formula: �2 2 1 1 1n m un i m � � � � for the purpose of representing the relationship between the elements of esg with returns and historical volatility of 43 companies over the period of last 5 years, panel regression will be used. in panel regression there are two models i.e. fixed effect model (least squares dummy variable model) and random effect model. in order to decide which model is more suitable it is necessary to run hausman test (figure 1). in the model formulated above, returns calculated with the help of capital asset pricing model is the dependent variable and scores mentioned in the sustainability reports of each element of esg meher, et al.: the effects of environment, society and governance scores on investment returns and stock market volatility international journal of energy economics and policy | vol 10 • issue 4 • 2020 237 probability values of intercept and independent variables through swamy and arora estimator of component variances. the intercept is 0.0793 whereas the co-efficient of environment and social are negative which shows a negative relationship between stock returns and those two esg elements. moreover, the probability values of the independent variables are not statistically significant as the values are more than 0.05, which could give provide enough evidence that esg scores of indian companies cannot become appropriate explanatory variables for determining returns. the value of rho in cross-section random is low i.e., 0.0335 which shows there is a lack of relationship between the variables of different companies. the r-squared and adjusted r-squared are also very less. in order to select the suitable panel regression model i.e. whether random effect model or fixed effect model, hausman test has been applied the results of which is given in the table 2. in the above table showing the empirical results of hausman test, the value of probability of cross-section random chi-square statistic is 0.2122 which is more than 0.05, hence it can be inferred that random effect model is more suitable to show the relationship between the returns and elements of esg (figure 2). it is also necessary to test the presence of serial correlation in panel data which can be determined with the help of arellano-bond serial correlation test. the results of the serial correlation test are mentioned in table 3. table 1: application and results of random effect model dependent variable: returns (capital assets pricing model) method: panel egls (cross-section random effects) sample (adjusted): 4 january, 2014-4 january, 2018 periods included: 5 cross-sections included: 43 total panel (balanced) observations: 215 swamy and arora estimator of component variances variable coefficient std. error t-statistic prob. c 0.079314 0.225946 0.35103 0.7259 environment ‒0.00149 0.003709 ‒0.40198 0.6881 social ‒0.00252 0.003657 ‒0.68938 0.4913 governance 0.001957 0.004278 0.457486 0.6478 effects specification s.d. rho cross-section random 0.106711 0.0335 idiosyncratic random 0.57297 0.9665 weighted statistics r-squared 0.004691 mean dependent var. ‒0.02973 adjusted r-squared ‒0.00946 s.d. dependent var. 0.572304 s.e. of regression 0.575005 sum squared reside 69.76302 f-statistic 0.331498 durbin-watson stat 2.533198 prob(f-statistic) 0.802582 source: researchers’ own computation using e-views 10 software table 2: results of hausman test correlated random effects hausman test equation: untitled test cross-section random effects test summary chi-sq. statistic chi-sq. d.f. prob. cross-section random 4.501225 3 0.2122 cross-section random effects test comparisons variable fixed random var (diff.) prob. environment ‒0.00724 ‒0.00149 0.000035 0.3308 social ‒0.01064 ‒0.00252 0.000043 0.2166 governance 0.010722 0.001957 0.000048 0.2079 source: researchers’ own computation using e-views 10 software table 3: application and results of arellano-bond serial correlation test arellano-bond serial correlation test equation: untitled sample: 4 january, 2014-4 january, 2018 included observations: 129 test order m-statistic rho se (rho) prob. ar (1) ‒0.95217 ‒24.8301 26.07748 0.341 ar (2) ‒1.29753 ‒0.07006 0.053993 0.1944 source: researchers’ own computation using e-views 10 software figure 2: model b: formulation of panel regression model between environmental, social and governance elements and historical volatility figure 1: model a: formulation of panel regression model between environmental, social and governance elements and stock returns i.e. environment, social and governance are independent variables. the table 1 shows the co-efficient, standard error, t-statistics and meher, et al.: the effects of environment, society and governance scores on investment returns and stock market volatility international journal of energy economics and policy | vol 10 • issue 4 • 2020238 the above arellano-bond serial correlation test is two separate statistics, one for the first order correlation and one for second. both order statistics are significant as there is no existence of serial correlation because the probability values are more than 0.5. in the model formulated above, historical volatility is the dependent variable and scores mentioned in the sustainability reports of each element of esg i.e. environment, social and governance are independent variables. the table 4 shows the co-efficient, standard error, t-statistics and probability values of intercept and independent variables through swamy and arora estimator of component variances. the intercept is 0.46367 whereas the co-efficient of environment and governance are negative which shows a negative relationship between returns and these two esg elements. such negative relationship could support the theory that higher the esg the lower would be volatility. but, the probability values of the variables are not significant as the values are more than 0.05. so, it not possible to frame a reliable model in which, volatility could be predicted based on esg scores. in other words, the esg elements cannot be considered as appropriate explanatory variables for predicting volatility. the value of rho in cross-section random is low i.e. 0.0093 which shows there is a lack of relationship between the variables of different companies. the r-squared and adjusted r-squared are also very less. in order to determine the suitable panel regression model i.e. whether random effect model or fixed effect model, hausman test has been used the results of which is given in the table 5. in the above table showing the results of hausman test, the value of probability of cross-section random chi-square statistic is 0.2122 which is more than 0.05, hence it can be inferred that random effect model is more suitable to show the relationship between historical volatility and esg components. it is also necessary to test the presence of serial correlation in panel data which can be determined with the help of arellano-bond serial correlation test. the results of the serial correlation test are included in table 6. the above arellano-bond serial correlation test is two separate statistics, one for the first order correlation and another for second order. both order statistics are significant as there is no existence of serial correlation because the probability values are more than 0.5. 5. conclusions from the above observation it can be inferred that reliable model cannot be formulated by considering the elements of esg as independent variables, to predict returns and volatility. as there is a negative correlation between two esg elements and returns, it can be said that either the esg scores in the sustainability reports of indian companies are not appropriable or it could also be possible that investors are not considering the esg scores while investing. but on the other hand, the negative correlation between the scores of environment and governance with historical volatility supports the theory but the scores of esg elements are having less significant p-values which are weakening the model formulated latter. as per a survey by natixis, “esg analysis is playing a higher role in institutional strategy, with more institutions finding that this approach can help navigate a path to potential profits” (gorte, 2019). though many economists support the direct relationship between the esg scores and returns but applying this theory in indian context is difficult. but taking into consideration the results from the data taken from 43 companies in nifty 100 enhanced esg, does not support the theory that the companies having better esg scores could become a good investment picks for the investors which implies that the data considered for this study does not fit into this economic theory. table 4: application of random effect model dependent variable: historical volatility method: panel egls (cross-section random effects) sample (adjusted): 4 january, 2014-4 january, 2018 periods included: 5 cross-sections included: 43 total panel (balanced) observations: 215 swamy and arora estimator of component variances variable coefficient std. error t-statistic prob. c 0.46367 0.147153 3.150942 0.0019 environment ‒0.0000477 0.002427 ‒0.01964 0.9844 social 0.002564 0.002384 1.075358 0.2834 governance ‒0.00362 0.002798 ‒1.29294 0.1974 effects specification s.d. rho cross-section random 0.037849 0.0093 idiosyncratic random 0.390166 0.9907 weighted statistics r-squared 0.013117 mean dependent var. 0.370203 adjusted r-squared ‒0.00091 s.d. dependent var. 0.391069 s.e. of regression 0.391248 sum squared reside 32.29881 f-statistic 0.934839 durbin-watson stat 2.120454 prob. (f-statistic) 0.424716 source: researchers’ own computation using e-views 10 software table 5: results of hausman test correlated random effects hausman test equation: untitled test cross-section random effects test summary chi-sq. statistic chi-sq. d. f. prob. cross-section random 4.172212 3 0.2435 cross-section random effects test comparisons variable fixed random var. (diff.) prob. environment –0.00156 –0.000048 0.000017 0.7116 social 0.000588 0.002564 0.000021 0.6627 governance –0.00969 –0.00362 0.000023 0.2069 source: researchers’ own computation using e-views 10 software table 6: application and results of arellano-bond serial correlation test arellano-bond serial correlation test equation: untitled sample: 4 january, 2014-4 january, 2018 included observations: 129 test order m-statistic rho se (rho) prob. ar (1) ‒1.33762 ‒42.3559 31.66515 0.181 ar (2) ‒0.76092 ‒1.29733 1.704952 0.4467 source: researchers’ own computation using e-views 10 software meher, et al.: the effects of environment, society and governance scores on investment returns and stock market volatility international journal of energy economics and policy | vol 10 • issue 4 • 2020 239 the american council for capital formation found a system that is fraught with problems, from inconsistent metrics, to ratings with continually fail to account for different regulatory regimes across distinct geographies. perhaps of greatest concern it is found that each of the four agencies uses their own proprietary methodologies, metrics, weighting, and even definitions of what constitutes esg” (bruno, 2018). to make esg an important factor for taking investment decisions, certain steps should be taken by the agencies in order to provide authentic reports on sustainability and the activities related to esg should be reflected on the esg scores immediately. references barberis, n., shleifer, a., vishny, r. (1998), a model of investor sentiment. journal of financial economics, 49, 307-343. birindelli, g., dell’atti, s., iannuzzi, a.p., savioli, m. (2018), composition and activity of the board of directors: impact on esg performance in the banking system. sustainability, 10, 1-20. bruno, g. (2018), esg and socially responsible investment: a critical review. available from: https://www.ssrn.com/abstract=3309650. cao, j., titman, s., zhan, x., zhang, w. (2019), esg preference and market efficiency: evidence from mispricing and institutional trading. p146. available from: https://www.ssrn.com/abstract=3353623. de, i., clayman, m.r. (2015), the benefits of socially responsible investing: an active manager’s perspective. the journal of investing, 24(4), 49-72. dorfleitner, g., halbritter, g., nguyen, m. (2015), measuring the level and risk of corporate responsibility-an empirical comparison of different esg rating approches. journal of asset management, 16(7)450-466. doyle, t. (2018), the big problem with “environmental, social and governance” investment ratings? they’re subjective. available from https://www.investors.com; https://www.investors.com/ politics/commentary/the-big-problem-with-environmental-socialand-governance-investment-ratings-theyre-subjective. duuren, e.v., plantinga, a., scholtens, b. (2016), esg integration and the investment management process: fundamental investing reinvented. journal of business ethics, 138, 525-533. escrig-olmedo, e., fernández-izquierdo, m.a., ferrero-feero, i., riveralirio, j.m., munoz-torres, m.j. (2019), rating the raters: evaluating how esg rating agencies integrate sustainability principles. sustainability, 11, 915. friede, g., busch, t., bassen, a. (2015), esg and financial performance: aggregated evidence from more than 2000 empirical studies. journal of sustainable finance and investment, 5(4), 210-233. gocejina, m.m. (2018), the environmental, social and governance aspects of social responsibility indices-a comparative analysis of european sri indices. comparative economic research, 21, 25-44. gorte, j. (2019), the financial performance of sustainability: esg and risk. available from: http://www.paxworld.com. hawaldar, i.t. (2016), the reaction of bahrain bourse to announcement of annual financial results. international review of business research papers, 12(1), 64-75. humphrey, j.e., lee, d.d., shen, y. (2012), the independent effects of environmental, social and governance initiatives on the performance of uk firms. australian journal of management, 2012, 135-151. iqbal, t.h., mallikarjunappa, t. (2007), market reaction to earnings information: an empirical study. aims international journal of management, 1(2), 153-167. iqbal, t.h., mallikarjunappa, t. (2010), a study of efficiency of the indian stock market. indian journal of finance, 4(5), 32-38. iqbal, t.h., mallikarjunappa, t. (2011), efficiency of stock market: a study of stock price responses to earnings announcements. germany: lap lambert academic publishing company. kell, g. (2018), the remarkable rise of esg. available from: https://www. forbes.com; https://www.forbes.com/sites/georgkell/2018/07/11/theremarkable-rise-of-esg/#35b2d9d71695. khan, u., aadil, f., ghazanfar, m.a., khan, s., metawa, n., muhammad, k., nam, y.a. (2018), robust regression-based stock exchange forecasting and determination of correlation between stock markets. sustainability, 10, 3702. khatri, y. (2016), companies with higher esg score are better investment picks. available from: http://www.economictimes.indiatimes. com; https://www.economictimes.indiatimes.com/wealth/invest/ companies-with-higher-esg-score-are-better-investment-picks/ articleshow/56154250.cms. kjerstensson, l., nygren, h. (2019), esg rating and corporate bond and performance an analysis of the effect of esg rating on yield spread. umea university, umea school of business, economics and statistics. available from: http://www.diva-portal.se/smash/get/ diva2:1333903/fulltext01.pdf. kumar, n.c., smith, c., badis, l., wang, n., ambrosy, p., tavares, r. (2016), esg factors and risk-adjusted performance: a new quantitative model. journal of sustainable finance and investment, 6, 292-300. lee, d.d., faff, r.w., rekker, s.a. (2013), do high and low-ranked sutainability stocks perform differently? international journal of accounting and information management, 2013, 116-132. loof, h., stephan, a. (2019), the impact of esg on stocks’ downside risk and risk adjusted return. sweden: working paper series in economics and institutions of innovation 477. p1-28. mallikarjunappa, t., iqbal, t.h. (2003), stock price reactions to earnings announcement. journal of iamd and iucber, 26(1), 53-60. nagy, z., cogan, d., sinnreich, d. (2013), optimizing environmental, social and governance factors in portfolio construction: analysis of three esg-tilted strategies. available from: https://www.ssrn. com/abstract=2221524. raza, s. (2018), institutional investors focus on esg, alternatives as volatility returns. available from: https://www.valuewalk.com; https://www.valuewalk.com/2018/02/institutional-investors-focusesg-alternative-investments-volatility-returns. salih, t.m. (2003), sustainable economic development and the environment. international journal of social economics, 30(12), 153-162. schneider, f., kallis, g., martinez-alier, j. (2010), crisis or opportunity? economic degrowth for social equity. journal of cleaner production, 18, 511-518. siew, r.y., balatbat, m.c., carmichael, d.g. (2016), the impact of esg disclosures and institutional ownership on market information asymmetry. asia-pacific journal of accounting and economics, 3(4), 432-448. sneddon, c., howarth, r., norgaard, r. (2006), sustainable development in post-brundtland world. ecological economics, 57, 253-268. verheyden, t., eccles, r.g., feiner, a., partners, a. (2016), esg for all? the impact of esg screening on return, risk, and diversification. journal of applied corporate, 28, 47-55. yoon, b., lee, j.h., byun, r. (2018), does esg performance enhance firm value? evidence from korea. sustainability, 10(10), 3635. . international journal of energy economics and policy | vol 9 • issue 6 • 2019234 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(6), 234-241. ecological-and-economic approach to the use of recycled biomaterials as an energy resource olga y. myasnikova1*, svitlana m. lysytska2, tatyana e. migaleva3, nataliya v. bondarchuk4, ekaterina a. vetrova5 1peoples’ friendship university of russia (rudn university), moscow, russia, 2national tu dnipro polytechnic, dneprо, ukraine, 3plekhanov russian university of economics, moscow, russia, 4russian academy of national economy and public administration under the president of the russian federation, moscow, russia, 5russian state social university, moscow, russia. *email: o_myasnikova@mail.ru received: 07 june 2019 accepted: 02 september 2019 doi: https://doi.org/10.32479/ijeep.8511 abstract the problem of the traditional energy resources exhaustion which is also arising in the process of their exploitation as a factor of the environmental degradation is observed in the paper. the authors have analyzed the possibility of using alternative raw materials based on recycled plant biomaterials as renewable substitutes for energy sources. according to analytical data, it is shown that the biofuel demand as an alternative form of energy meets regulatory requirements that impose restrictions on the sulfur emission rate to the environment which are built up in the result of traditional combustible materials burning. the authors esteem the feasibility of all-around usage of various types of recycled biomaterials as a fuel. within this framework, conducted study is a priority and promising direction for the world’s economy and energy, and the analysis of the main technical and economic characteristics of various types of waste biomass. keywords: environmental safety, renewable energy sources, recycled biomaterials jel classifications: q20, q42, f52 1. introduction in current times, a common problem for many countries of the world is upcoming fuel crisis, increasing energy prices, environmental degradation. the exhaustion of natural energy resources (coal, oil, peat, natural gas), as well as environmental problems arising in the process of their use, necessitate searching and implementation of alternative renewable energy sources in practice (nazarova et al., 2019). according to un experts, the population may increase to 9.2 billion people by 2050. maintaining of the current production rates of motor fuels and natural gas per head of population as well as the intensive use of combustible minerals will lead to a significant decrease in their reserves (18.3 billion tons of oil will have to be produced for the year – 16% of proven reserves and to 12 trillion m3 of natural gas – 6.7% of proven reserves). in such a way, according to the forecasts, the oil reserves are enough for 6-10 years, and gas reserves are enough for 15-20 years. the problem statement of plant waste using as an energy sources is compatible with the provisions of global cooperation documents connected with limitation and reduction of gaseous emissions which lead to the ozone layer the destruction on the planet (kyoto treaty, protocols of the united nations framework convention and the ipcc – international expert group on climate change assessment). it is estimated that the energy content of agricultural waste which is produced in the world is about 93·1018 j/year. assuming that the actual use of their potential to 25% can provide about 7% of world energy. the usage of recycled fuel biomaterials will make it possible to solve global environmental and economic this journal is licensed under a creative commons attribution 4.0 international license myasnikova, et al.: ecological-and-economic approach to the use of recycled biomaterials as an energy resource international journal of energy economics and policy | vol 9 • issue 6 • 2019 235 problems, namely, reducing greenhouse gas emissions and the risk of acid rain by decreasing of emitted sulfur dioxide amount (forests preservation). and there are also local problems connected with the need to dispose large-scale industrial and agricultural waste annually generated by hundreds of thousands of tons, and at the same time to be able to receive additional economic benefits through waste biomass usage. in this aspect, planning of integrated measures for the rational use of recycled bioresources is provided, and it is aimed at the negative impact reducing of accumulated biomass waste on the natural environment through its conversion utilization, as well as strategic course is developed to reduce the amount of industrial gaseous emissions (carbon dioxide, methane, sulfur compounds, etc.) that lead to the global warming on the planet. 2. literature review it is known that sulfur and its compounds are presented in the composition of traditional raw materials: crude oil, gasoline, diesel fuel, coal (in the form of mercaptans r–sh, sulfides r–s–r, disulfides r–s–s–r, thiophenes, thiorphans and others; r – hydrocarbon radical). the combustion products of the above substances (so2 и so3) together with the exhaust gases, entering the atmosphere, have high toxicity and corrosive chemical aggressiveness (myasnikova et al., 2019; mazgarov and kornetova, 2015). therefore, the biofuel requirement as an alternative energy source is compatible with normative standards that limit the amount of sulfur emissions to the environment resulting from the traditional combustible materials burning. in addition, taking into account the rising prices for gasoline and diesel fuel in europe, which have increased on average by 5.4% for ai-95 and by 2.5% for diesel fuel per three 1st months of 2019 (the price for a liter of gasoline has reached the average level of 1,3 € and 1,23 € for diesel fuel). so, a rational solution is considered to be an adoption of less expensive substitutions, containing predominantly combustible carbon and hydrogen elements, environmentally friendly energy producing materials. such an approach will reduce the high prices of ai-95 gasoline in netherlands, norway and iceland, which are by 25-30% higher than european average. (flach et al., 2018). in the context of the problem mentioned above, most eu countries, the usa, canada, brazil, sweden, china and others are actively developing programs for the production and using of fuel based on various types of plant raw materials. thus, according to the eu directive, it is planned to implement environmentally friendly and efficient types of biomaterials (renewable energy sources) into the fuel and energy sector (myasnikova et al., 2019). one of the energy programs “energy 21” was adopted in denmark as early as in 1996. it suggests that renewable energy based on biomass should exceed 50% by 2030 in the general structure of fuels used in heat and electricity production. it is noted that the energy resource growth can achieve 2.4 times by increasing the usage of recycled perennial and annual plant raw materials (gregg et al., 2014). legislative support was introduced in this field by decision of the european commission. tax and customs department in estonia has gained the right to excise tax exemption for liquid biofuels (no more than 5% of the total value of all fuel). according to the price monitoring data in estonia, the cost of bioethanol based on biomass was at 10% lower than the cost of the most common ai-95 in europe (flach et al., 2018). tax exemptions (so-called “green taxes” were established for biofuels, and the biofuels’ usage exempts consumers from energy taxes and environmental charges in austria and sweden. effectively operating us federal laws with tax breaks are focused on bioethanol production, as well as on the support of waste vegetable and animal oils reutilization (vasilov, 2007a). according to geographic and climatic parameters, there is a large variety of vegetation types in many countries which are included in conversion production processes. it leads to the continuous formation of a large amount of organic waste (agricultural, chemical industries, wood processing, peat production, printing, food, textile and other industries). taking into account the fact that the energy resource costs based on waste biomaterials are practically minimum, and the fact that abovementioned cost volume is not limited, their economic feasibility is obvious. depending on the genesis, morphological, chemical and rheological properties of biological raw materials, various technologies of biomaterials’ energy usage are possible. thus, technologists and ecologists note that along with thermochemical methods of the plant materials processing and their waste utilization (direct combustion, high-temperature gasification [westinghouse corporation], pyrolysis, etc.), the production of fuel briquettes, pellets, tablets and others forms is adopted as the most optimum alternative (khoruzhenko and dorogov, 2017; sevastyanova, 2009). however, mainly organic part of the plant biomass waste possesses energy capacity and chiefly consists of polysaccharide components, including cellulose, hemicellulose and lignin. it’s technically and economically effective that lignin acts as a gluing agent of the cellulose crystalline chains in the lignohydrocarbon complex, as well as it provides a mechanical function and is closely associated with hemicelluloses. it gives a possibility to do without additional agents. total organic content in anhydrous plant biomass, including up to 12% of capillary moisture, is represented by carbon (45-50%) oxygen (40-45%), hydrogen (4.5-6.0%), nitrogen (0.3-3.5%) and a small amount of sulfur (up to 0.05%) (sushkova and vorobyov, 2008). the abovementioned components are converted into carbon dioxide (со2) and water vapor (н2о) when it burns. biomass utilization rate for heat production reaches 15% in eu countries. at the same time, this indicator is significantly higher in many countries which predominantly use solid biomaterials. for example, 61% of heat is obtained from biomass in sweden, 37% – in austria, 35% – in denmark, 32% – in finland (flach et al., 2018). according to the international energy council, 1.9 billion m3 of wood and about 300 million m3 of wood biomass wastes were myasnikova, et al.: ecological-and-economic approach to the use of recycled biomaterials as an energy resource international journal of energy economics and policy | vol 9 • issue 6 • 2019236 used at the beginning of the 21st century in the whole world. considering that russia possesses over 25% of the world’s forest reserves, wood waste recycling is considered as a stable restoring energy source. (pantshava, 2015). according to wood prices’ analysis of the baltic countries, the average price of roundwood is € 63/1 m3 in estonia, just as it is € 41 in sweden (flach et al., 2018). the cost of fuel chips varies from 16 to 25 €/m3 depending on humidity, fractional and qualitative composition (types of wood, lack of bark). additionally, raw materials can be purchased in russia. the maximum cost of 1 m3 of coniferous wood at forest auctions has been reached 383 rubles in kaliningrad region, 366 rubles in penza, 252 rubles in bryansk, 261 rubles in vladimir, 218 rubles in kaluga region. the cost of wood chips of fir-trees is 300-500 rubles/m3 (8-20 mm fraction, humidity – 12%) in russia, the price without bark amounts to 850 rubles/m3, and the price of fuel wood briquettes made from waste chips (pellets) increases to 78-90 €/m3 (national biofuel association, 2016). these facts suggest that there is an economic feasibility of waste wood chips using for energy needs. analysts at foex indexes ltd had calculated a price index for wood pellets in central europe and it reached € 202.76/ton. in the context of abovementioned facts, it should be noted that the energy concern dong energy, which is one of the largest consumers of pellets, has transferred the first block of a large thermal power plant in avedore from coal to wood pellets. now the capital of denmark copenhagen will be able to get more bioenergy (flach et al., 2018). it is estimated that burning wood (with 10% of moisture), which mainly consists of polysaccharides and lignin, provides for the thermal energy release in the amount of 14-15 mj/kg (for comparison, low heating value of oil is 41-44, household gas is 32-33, and coal is about 27-29 mj/kg) (energy strategy of russia for the period up to 2030, 2010). the content of mineral part in the biomass is insignificant; therefore, after its combustion, there is almost no ash. in addition, using of alternative energy sources, which are more environmentally friendly and cost effective, eliminates the need to add additives to traditional fuel which neutralize the effect of sulfur fumes. moreover, it also provides additional cost savings. such approach emphasizes the feasibility of low-sulfur fuel biomaterials switching in energy industry and makes it possible to increase sustainability indicators for many energy-dependent countries. 3. methodology of the research technical analysis of air-dry wood samples pre-blended at special laboratory vibratory mills (laboratory vertical vibrating mill mvv-2) and annual plant waste (their individual parameters) was carried out in laboratory conditions according to standard techniques (lamotkin and bondarenko, 2005; svietkina et al., 2017). the characteristics of target components of recycled plant materials is presented in table 1. the data in table 1 indicates that the chemical composition of the plant biomass organic part with energy capacity is quite stable. the organic component is mainly represented by polysaccharide components, including cellulose, hemicellulose and lignin. in the ligno-carbohydrate complex of any kind of plant materials, lignin is providing a mechanical function, and is closely associated with hemicelluloses. it acts as a gluing agent of the crystalline chains of cellulose with tissues. the high content (in some species is above 90%) of energetically important organic substances in the waste of almost all plants in question makes it possible to convert them into high-quality fuel raw materials. the key energy indicator is the specific low heating value (calorific value) of plant materials was determined in a liquidtype calorimeter b-08ma, that was designed to determine the low heating value of solid, liquid and gaseous fuels (dstu iso 1928:2006, 2008). the results of investigations of individual energy parameters and the elementary composition of various types of annual and perennial plants, as well as waste from their processing, are presented in table 2. it should be taking into account that the quality of fuel materials depends not only on the chemical composition, but also on other technological parameters. they include moisture (the critical moisture level varies from 10 to 15%, and for some types of raw materials the limit of moisture content is limited by 7-8%). thus, low heating value of straw is lower than of dry wood. however, taking into account the usual for air-dry straw moisture within 12%, this figure is higher than that of wood chips. at the same time, traditional types of fuel materials have rather high bulk volume or volume weight (for example, depending on the deposit the coal’s bulk volume is 680-960 kg/m3, and anthracite’s bulk volume is 1500 kg/m3). the bulk volume of organic waste is small and is within 60-120 kg/m3 in a free state, and 180-220 kg/m3 for placed in a container waste. it also includes vegetable waste which has table 1: the chemical composition of industrial plant waste, % of dry basis the type of recyclable material polysacharides lignin mineral (ash) substance annual plant waste wheat straw 63,5 19,8 7,8 sunflower husk 50,6 28,2 2,2 corncob 66,0-73,4 14,5-18,6 0,9-1,9 linen awn 53,4 27,0 2,0 grapevine cuts 60,6 28,3 2,7 potato vine 51,3 14,1 perennial plant waste chunkwood of cottonwood 66,0 29,3 1,7 chunkwood of pine 65,7 24,7 0,2 chunkwood of oak 62,7 27,1 0,9 chunkwood of maple 63,5 27,1 1,3 source: authors’ computations myasnikova, et al.: ecological-and-economic approach to the use of recycled biomaterials as an energy resource international journal of energy economics and policy | vol 9 • issue 6 • 2019 237 a moisture content about 10-12%. waste realization of fuel materials with such indicators is unprofitable both from energy and economic point of view (because of their transportation). therefore, plant materials’ and their waste usage in compacted form (in the form of briquettes or pellets) with increased bulk volume up to 600 kg/m3 and more is technologically and economically viable solution. in europe, liquid biofuels for diesel engines of vehicles – bioethanol or biobutanol, as well as biodiesel fuel – have also found widespread use. bioethanol can be easily obtained from simple water-soluble monosaccharides (from glucose, carbohydratecontaining food waste of beets, potatoes, as well as from cellulosic agricultural waste in the form of straw, seed husks, plant stalks and wood chips by the enzymatic reaction of alcoholic fermentation under anaerobic conditions). in addition to well-known types of yeast, it is possible to use both active groups of bacteria at a temperature of 40 c as an enzyme source, and modified strains which are active at a temperature of 65-75°c and are capable to hydrolyze complex polysaccharide chains to simple sugars from almost all types of organic agricultural waste, forestry, sugar plants (tigunova et al., 2013). for example, in the usa, 150 liters of ethanol are produced from 1 ton of straw (or old cardboard) after hydrolysis of cellulose and further microbiological digestion of glucose. it has been established that biobutanol as a fuel is more highcalorie, less volatile, less aggressive and expensive than ethanol (it is in 13.5 times less volatile than gasoline, so it’s safer). in addition, biobutanol can be prepared from cheap substrates – recycled carbohydrate materials, and namely syrup, molasses, cellulose hydrolysates and lignin of various plant species. the biotechnological process is carried out by the method of acetone-butyl fermentation with the participation of anaerobic saccharolytic bacteria clostridium acetobutylicum. a simplified biochemical reaction for the mixture formation of energy products of butanol, acetone and ethanol (on average, their ratio depending on the composition of the substrate varies 60:30:10, respectively), can be represented as an equation: 12с6н12о6 → сн3сн2(сн2)2он+сн3сосн3+с2н5он +сн3(сн2)2он+28со2+18н2+2н2о (1) biobutanol’s energy intensity is close to that of gasoline, so it can completely replace it in fuel cells. biobutanol is more economical than a mixture of gasoline and bioethanol. it improves the fuel efficiency of cars (increases mileage per unit of consumed fuel). russia is the largest producer and exporter of biobutanol from wood raw materials (developed by the russian corporation “biotechnology). ” over the past 5 years, more than 60% of this type of motor fuel was supplied to external market by the russian federation (since 2007 – sale to the uk). the environmental advantage of liquid biofuels using is that its combustion does not disrupt the balance of carbon distribution in the earth’s atmosphere and in the earth’s crust (the same amount of carbon dioxide is emitted from the atmosphere for life activity as a result of its combustion). moreover, biofuels’ burning minimizes the emission of harmful exhaust gases into the atmosphere: carbon monoxide, nitrogen and sulfur oxides, residues of unburned hydrocarbons, soot particles, etc. the us federal government provides liquid biofuel producers with a tax credit of that is up to $ 0.51 per gallon (1 american gal=3.785; 1 english gal=4.546 gal) (vasilov, 2007a). the european union plans to provide a quarter of its fuel needs for road transport with clean and efficient biofuels by 2030 (pantshava, 2015). biogas technology is recognized as a rational way of recycled biomaterials’ utilization. it has been used since ancient times. it is noted that to solve the environmental problem of organic waste local accumulation, which amount significantly exceeds their biodegradation potential, biogas production processes were used with the participation of the most widespread methanogen archebacterium groups (about 10 types of methane bacteria methanococcus and methanobacterium are known) (vasilov, 2007b). the process of methanogenesis can be represented as a simplified reducing biocatalytic reaction: 4н2+со2 → сн4+2н2о (2) biotechnology of biogas production (in other words, mixture of: сн4–50–75%; со2 – up to 25-30 %; insignificant amount [up to 1%] h2s, n2, nh3, o2, h2 and co) from renewable organic fermentation table 2: the main energy characteristics of various types of fuel biomaterials sample number sample name composition of the organic part ash, % s concentration, % towards to oven-dry weight caloric value, mj/kl c h n o 1 pine (pinus) softwood 50,4 5,6 0,7 43,3 0,20 0,03 18,5 2 pine (pinus)\ hardwood 50,6 5,8 0,9 42,7 0,15 0,03 18,6 3 oak (qutrcus) hardwood 50,2 6,1 1,3 42,4 0,90 0,02 19,0 4 cottonwood (populus) softwood 51,3 6,0 1,6 41,1 1,70 0,02 18,2 5 muteia (cuibourtia arnodiana) hardwood 49,6 6,3 1,8 42,3 0,84 0,01 19,0 6 appletree (appletree, malus) hardwood 50,0 6,1 1,4 42,5 0,75 0,02 18,6 7 wheat straw 44,0 5,5 0,7 49,8 5,5 0,20 13,12 8 sunflower husk 50,9 6,2 0,8 42,1 2,2 0,10 15,50 9 linen awn 50,2 6.1 1,0 42,7 2,0 0,07 13.80 10 corncob 52,4 6,3 1.2 40,1 1,1 0,05 11,80 source: authors’ computations fermentation myasnikova, et al.: ecological-and-economic approach to the use of recycled biomaterials as an energy resource international journal of energy economics and policy | vol 9 • issue 6 • 2019238 waste materials is a complex of multistage enzymatic process. the main factor in the breakdown of solid biomass into individual components and their further conversion to methane are anaerobic conditions and the aquatic environment, since most bacteria are able to consume substances only in dissolved form. during the chain metabolic mechanism, chemical bonds of biomaterial organic complex are converted into enzymatic reactions products of one group of aerobic bacteria to form nutrients for the other – anaerobes-acetogens, and their further transition into the energy of biogas compounds. the quality of biogas depends on the methane content in it or on the ratio between itself and its carbon dioxide, which dissolves biogas and saves it from losses during storage. high methane’s concentration in biogas mixture – more than 50% is provided by the criteria for the quantitative and qualitative composition of the substrate (that is, the optimal concentration of carbohydrates, proteins and lipids in biomass). it depends on the temperature control; hydrogen sulfide amount limiting that causes equipment corrosion, as well as the content of ammonia, elemental nitrogen, sulfur, hydrogen and oxygen, the amount of which may be up to 6-8% in the biogas mixture. it is desirable to enrich a biogas product by drying with condensation of ammonia and water vapor. an organic substrate is additionally seeded with acetogenic and methanogenic bacteria – mesophiles (withstand temperatures of 30-40°c) to intensify methanogenesis in biogas-fired plants; with thermophiles adapted to the temperature of 30-40°c; with psychrophilia adapted to the temperature – 20°c. the optimal mass ratio of c: n elements is in the range of 11-16: 1 in the substrate. moreover, nitrogen content increasing leads to ammonia release into the media and its alkalinization. therefore, it is advisable to add recycled carbon-containing materials (ground straw, sugar beet waste, sugar cane bagasse, etc.) to organic waste with a high nitrogen content. since the parameters of technologies in which formation and accumulation of organic wastes have certain differences, it is impossible to create one type bioreactor-fermenter. design options for biogas plants depend on environmental conditions, the existence of available and inexpensive materials. in most cases bioreactor is made of reinforced concrete. it allows to save metal consumption, but requires more time and labor costs. reactor’s volume depends on biomass amount that will be processed. new portions of the substrate are continuously loaded into biogas reactor (filling by 90%) to ensure its continued operation, an appropriate amount of product is taken and bacterial degradation of cellulose-containing substrate is activated by automatically temperature maintaining of the coolant – 40 с. bioreactor in the volume of 50 m3 can produce 100 m3 of biogas per day. at that, 300 m3 of biogas can be obtained from 1 ton of straw, and 130 m3 from 1 ton of household organic waste. the pressure of produced biogas is to 100-300 mm w.g. on average equivalent and is sufficient to deliver it over a distance of several hundred meters without gas blowers or compressors using. bioreactor is carefully heat-insulated (creating a light frame filled with glass wool or applying a layer of polyurethane foam on its surface, etc.) to reduce the heat consumption. the energy value of artificially produced methane (biogas mixture) in such a bioreactor is 10 kw/m3, and its composition is similar to natural gas. the heat value of biogas product, including: 60-70% methane, 30-35% carbon dioxide, 2-3% nitrogen, 1-2% hydrogen, up to 1% oxygen, traces of hydrogen sulfide are 20-22 mj/m3, and energy of 1 m3 of such biogas is equivalent to 0.5-0.6 m3 of natural gas, 0.74 liters of oil, 0.65 liters of diesel fuel, 0.48 liters of gasoline, 3.5 kg of firewood, 12 kg of briquettes from biomass (pantshava, 2015). up to 2.5-3 kw/h of electrical power and 4-5 kw of thermal energy can be obtained by burning of 1 m3 of biogas (up to 30% of the gas product can be used for technological needs of biogas plant) (vasilov, 2007b). after biogas is compressed to 15-16 atm., it can be refilled into gas cylinders. 4. the results of research within the framework of study, it was found that nowadays there are various ways to increase the waste organic mass density. briquettes and granules or “pellets” (normalized pressed products from waste wood and residual wood, crop waste by-products, etc.) are recognized as one of the most promising areas in energy technologies’ development (svietkina et al., 2017; mate, 2014). pellets and briquettes are exclusively made from natural organic raw materials. these fuel materials contain lignin (“natural glue”), so their production does not require additional additives and binder components. the lignin complex of plant cells has a feature to initiate the passage of a chemical reaction in high pressure and temperature conditions, accompanied by structural changes in the material with the acquisition of viscoplastic properties. clearly the environmental and economic benefits resulting from the use of different types of fuel can be considered by comparing the levels of air emissions of pollutants without cleaning systems exploitation and their costs per unit of material (table 3). according to the data in table 3, wood fuel (firstly, briquettes and pellets) is more environmentally friendly and preferable in comparison with traditional types of fuel materials. in terms of greenhouse gas emissions (primarily со2), it has almost a “zero effect,” which is especially important in the context of sustainable development indicators. economic benefits of biofuel materials using are also obvious. thus, fuel types based on biomaterials are not only free from undesirable sulfurous substances in a result of combustion, but also have sufficiently high calorific value, low inorganic impurities, large combustion surface and a high ratio of exotherm to emitted carbon. in this regard, the priority and topical direction is the research, analysis of the main energy characteristics of various waste types and waste biomaterials, and is also the rationale for the ways of their targeted use as an energy resource. myasnikova, et al.: ecological-and-economic approach to the use of recycled biomaterials as an energy resource international journal of energy economics and policy | vol 9 • issue 6 • 2019 239 briquettes and pellets that are produced on impact-mechanical presses or through the usage of extruder technology from previously crushed and heated biomass, according to regulatory requirements, have a high density of 1000-1400 kg/m3. they are characterized by high calorific value (table 2) and burning duration. fuel briquettes and pellets are intended for incineration in furnaces, fireplaces, greenhouses, rail transport, factory boiler rooms and chp plants, industrial plants, where there are installations operating on solid fuel. this aspect expands their consumer properties at the market. thanks to these advantages, fuel briquettes and pellets (euro-wood) are most prevalent in denmark, sweden, austria, germany, norway and finland. until 2001, the consumption of these materials in europe increased annually by an average of 30%. the demand for granules was satisfied by 9% in germany in the same period. denmark began to receive half of all generated energy from granulated wood fuel. more than 80% of consumed in denmark pellets are imported. according to some estimates, sweden may become the first european country that would be able all in all to switch to alternative energy forms in 15 years. according to analytical data, the trend of solid biofuels consumption for energy generation is increasing. abroad, the most serious producing countries (as well as consumers) of pellets and briquettes are: europe – 3.0 million tons/year; the usa about 2 million tons/year; canada about 110 thousand tons/year; japan about 3 thousand tons (pantshava, 2015). russia’s fuel and energy complex plays an important role in the country’s economy. 1/3 of the world reserves of natural gas, 1/5 of coal, 1/10 of oil is concentrated on its territory. these facts create complacency in public mind and some underestimation of situation (nazarova et al., 2017a). at the same time, according to the official experts’ forecasts, oil production may decrease from 518 million tons (2012) to a level of 1 million tons in russian federation by 2020 (goryainov, 2015). thus, the benefits from alternative types of biofuel materials using have integrated nature. firstly, these are favorable technological properties: high bulk density, the possibility of fully fuel supply automation to the combustion zone, they are not explosive, as well as they are not self-igniting and do not decompose under appropriate storage conditions, there is a possibility of existing equipment employment without upgrading and minimal fireproof rest. secondly, there are economic advantages: a relatively low price at high calorific value, small storage areas and transportation costs. the ecological aspect is also of great importance and is reflected in renewable biofuels use and the reduction of environmental components pollution. 5. discussion conducted analysis has allowed to establish that searching for new alternative, environmentally friendly substitutes are major aspect now, considering that current problems are associated with traditional types of fuel materials using (minerals exhaustion, energy prices increasing, environmental degradation) (nazarova et al., 2017b). it is shown that organic waste, including vegetable waste, which accumulate constantly, create environmental and economic problems and have sufficient energy capacity. in addition, renewable recycled biomaterials use has a number of predominantly complex characteristics: environmental (low emissions from the atmospheric pollutants combustion, including greenhouse gases, waste management); technological (high bulk density, lack of explosion hazard, stability to storage conditions, minimum ash content, etc.); economic (low cost at high calorific value, low transportation costs). it was emphasized that using of various types of energy sources based on recycled biomaterials (solid fuel, liquid biodiesel, biogas) helps to solve both global problems – greenhouse gas emissions reducing and the risk of acid rain formation decreasing, by lowering of sulfur and nitrogen oxides emitted amount. local problems, which can be also solved, are connected with large-scale of industrial and agricultural waste disposal, hundreds of thousands of tons of which are annually produced. it is also possible to obtain additional economic benefits from such methods application. according to experts in energy area, in the next 2-3 decades the growth of energy consumption and production will be about 60% of its global production and consumption at the beginning of the xxi century. energy production increasing should take place against the background of environmentally friendly energy table 3: comparative analysis of environmental and economic characteristics of various energy sources type of fuel pollutant emissions amount into the atmosphere during the energy combustion, tons/thousand tons of fuel fuel’s cost, rubles/kw per unit of material* со2 nox so2 dispersed solids (soot) total natural gas 1,18 3,52 0,00 0,00 4,70 0,56-0,75/м3 coal, (w=10%) 9,58 63,56 9,20 65,32 147,66 1,57-1,76/кг diesel fuel 15,53 29,0 11,18 2,7 58,41 3-4/кг wood (firewood), w=10-15% 4,90 9,40 0,30 4,30 18,90 1,36-1,66/кг wood waste 5,60 11,40 0,80 13,40 31,30 0,16/кг peat briquettes 8,04 26,81 3,00 13,02 50,87 1,8-2,0/кг briquettes, wood pellets 4,68 9,31 0,28 4,11 17,69 1,9-2,0/кг briquettes, pellets annual plants 3,10 9,50 0,15 1,5 14,25 1,78-1,8/кг biogas 0 < 0,001 0,5-0,6/м3 bioethanol (concentration 70%/90%) < 0,001 0,97/1,04/л source: authors’ computations. *order of the ministry of natural resources and ecology of the russian federation 300 (2015) myasnikova, et al.: ecological-and-economic approach to the use of recycled biomaterials as an energy resource international journal of energy economics and policy | vol 9 • issue 6 • 2019240 technologies creation, the creation of new constantly renewable sources of fuel and energy, the complete re-equipment of industry and agricultural production for energy-saving equipment, machinery and technology (pantshava, 2015). as noted by many experts, alternative biofuel energy resources using is very reasonable and promising. according to analytical data, the consumption level of solid biofuels will reach 21 million tons/year in europe by 2020 (boyarintseva and popov, 2014). it is positive that the trend of biofuel materials consumption for energy production in developed and developing countries is increasing, which is confirmed by statistical data and practical experience of many countries around the world. thus, the use of electricity produced from biomass, is growing particularly rapidly in china and in europe, namely an average of 8% per year; at the same time, bioethanol production on a global scale increased by 4% and record numbers are observed in the usa (irena, 2019). 6. conclusions according to un experts, the population is projected to increase to 9.2 billion people by 2050. in case of increase in motor fuel and natural gas consumption per capita to the level of the european union by this time, it will be necessary to produce 18.3 billion tons of oil (that is, 16% of the explored reserves), and natural gas – up to 12 trillion m3 (6,7% of proven reserves). at the same time, there will be enough oil for 6-10 years, and gas for 15-20 years. in this regard, using of non-traditional raw materials based on recycled biomaterials of plant origin is relevant and promising for the world economy and energy due to the following factors: • the experimental data on the chemical composition and energy characteristics of recycled plant biomaterials are indicative of the rationality of their use for the production of various types of energy resources (dual fuel briquettes, pellets; liquid biofuels: biobutanol, bioethanol; biogas); • complex combination of technological, environmental and economic tasks allows not only to control the level of environmental pollution, but also to form technical solutions that reduce environmental risks; • directional disposal implementation of accumulated biomass waste; • reducing of gaseous emissions amount that pollute the air and pose an environmental hazard to living organisms and nature in general; • additional economic effects obtaining by production costs reducing and biofuel materials using. in general, it is likely that the complete replacement of traditional fuels with alternative sources may not happen in the near future, but the optimal combination of them will provide both positive environmental and economic results. obviously, recycled biofuel materials using requires further research and selection of rational technological parameters. 7. acknowledgment the publication has been prepared with the support of the “rudn university program 5-100.” references analytical report of the national biofuel association. (2016), status of the biofuel industry by the end of 2016. markets and prospects. available from: http://www.biotoplivo.ru. boyarintseva, a., popov, n. (2014), features of legal regulation of solid biofuels using in russia and abroad. advances in chemistry and chemical technology, 28(7), 53-56. dstu iso 1928:2006. (2008), solid mineral fuels determination of gross calorific value by the bomb calorimetric method and calculation of net calorific value. instead of gost 147-95 (iso 1928-76); actual from 2008-07-01. kiev: derzhstandart ukrayini. energy strategy of russia for the period up to 2030. (2010), app. to the public and business magazine “energy policy”. moscow: institute of energy strategy. p172. flach, b., lieberz, s., lappin, j., bolla, s. (2018), eu biofuels annual 2018. date 7/3/2018. gain report number nl8027. goryainov, m. (2015), fuel and energy complex the basis of russian economy development. bulletin of the miep, 2(19), 60-63. gregg, j., bolwig, s., solér, o., vejlgaard, l., gundersen, s., grohnheit, p., karlsson, k. (2014), experiences with biomass in denmark. department of management engineering, technical university of denmark. available from: https://www.orbit.dtu.dk/ files/97912187/experiences_with. irena. (2019), renewable energy statistics 2019. abu dhabi: the international renewable energy agency. khoruzhenko, e., dorogov, v. (2017), biofuel’s market development in the world. innovative economy: materials of the iv intern. scientific conference. kazan. p27-31. available from: https://www.moluch. ru/conf/econ/archive/262/12918. lamotkin, a., bondarenko, j. (2005), chemistry of wood and synthetic polymers: laboratory workshop. minsk: bstu. p82. mate, l. (2014), bioenergy: fss and new market opportunities. sustainable forest management, 2, 18-22. mazgarov, a., kornetova, o. (2015), sulfur compounds of hydrocarbons. kazan: kazan’s university. p36. myasnikova, o., lysytska, s., shcherbakova, n., shamsheev, s., spitsyna, t., kubasova, e. (2019), ecological approach in managing the technology of oil refineries. international journal of energy economics and policy, 9(3), 165-171. nazarova, y., sopilko, n., bolotova, r., shcerbakova, n., alexeenko, v. (2017а), increase of social impact due to the development of the renewable energy industry in russia. international journal of energy economics and policy, 7(5), 263-270. nazarova, y., sopilko, n., kulakov, a., myasnikova, o., bondarchuk, n. (2019), feasibility study of renewable energy deployment scenarios in remote arctic communities. international journal of energy economics and policy, 9(1), 330-335. nazarova, y., sopilko, n., orlova a., bolotova r., gavlovskaya, v. (2017b), evaluation of development prospects of renewable energy source for russia. international journal of energy economics and policy, 7(4), 1-6. order of the ministry of natural resources and ecology of the russian federation 300 of june 30. (2015), on the endorsement of the methodology recommendations and guide for quantitative determination of the volume of exhausts of greenhouse gases by organizations engaged in economic and other activities in the myasnikova, et al.: ecological-and-economic approach to the use of recycled biomaterials as an energy resource international journal of energy economics and policy | vol 9 • issue 6 • 2019 241 russian federation. available from: https://www.legalacts.ru/doc/ prikaz-minprirody-rossii-ot-30062015-n-300. pantshava, e. (2015), bioenergy. world and russia. biogas. theory and practice: monograph. moscow: rusayns. p972. sevastyanova, s. (2009), bioenergy. wood (fuel) pellets. vestnik ogu, 10(104), 133-138. sushkova, v., vorobyov, g. (2008), waste less conversion of plant materials into biologically active substances. moscow: delhi print. p216. svietkina, o., lysytska, s., franchuk, v. (2017), energy-saturated materials based on technological biomaterials. advanced engineering forum, 25, 80-87. tigunova, e., shulga, s., ya, b. (2013), alternative fuel biobutanol. cytology and genetics, 47(6), 51-66. vasilov, r. (2007a), prospects for biofuel production development in russia. message 2: bioethanol. bulletin of biotechnology and physico-chemical biology yu.a. ovchinnikov, 3(2), 50-60. vasilov, r. (2007b), prospects for the biofuel production development in russia. message 3: biogas. bulletin of biotechnology and physicochemical biology yu.a. ovchinnikov, 3(3), 54-61. . international journal of energy economics and policy | vol 9 • issue 4 • 2019240 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(4), 240-247. modeling and forecasting by the vector autoregressive moving average model for export of coal and oil data (case study from indonesia over the years 2002-2017) warsono, edwin russel, wamiliana*, widiarti, mustofa usman department of mathematics, faculty of science and mathematics, universitas lampung, indonesia. *email: wamiliana.1963@fmipa.unila.ac.id received: 25 january 2019 accepted: 06 may 2019 doi: https://doi.org/10.32479/ijeep.7605 abstract the vector autoregressive moving average (varma) model is one of the statistical analyses frequently used in several studies of multivariate time series data in economy, finance, and business. it is used in numerous studies because of its simplicity. moreover, the varma model can explain the dynamic behavior of the relationship among endogenous and exogenous variables or among endogenous variables. it can also explain the impact of a variable or a set of variables by means of the impulse response function and granger causality. furthermore, it can be used to predict and forecast time series data. in this study, we will discuss and develop the best model that describes the relationship between two vectors of time series data export of coal and data export of oil in indonesia over the period 2002-2017. some models will be applied to the data: varma (1,1), varma (2,1), varma (3,1), and varma (4,1). on the basis of the comparison of these models using information criteria aicc, hqc, aic, and sbc, it was found that the best model is varma (2,1) with restriction on some parameters: ar2_1_2 = 0, ar2_2_1 = 0, and ma1_2_1 = 0. the dynamic behavior of the data is studied through granger causality analysis. the forecasting of the series data is also presented for the next 12 months. keywords: vector autoregressive moving average model, information criteria, granger causality, forecasting jel classifications: c53, q4, q47 1. introduction financial, business, and economic data are very often collected in equally spaced time intervals such as days, weeks, months, or years. in a number of cases, such time series data may be available on several related variables. there are some reasons for analyzing and modeling such time series jointly: (1) to understand the dynamic relationship among variables and (2) to improve the accuracy of forecast and knowledge of the dynamic structure so as to produce good forecast (tiao, 2001; pena and tiao, 2001). the analysis of multiple time series has been developed by tiao and box (1981); since then, the development of the theory has been extensively discussed in the literature (lutkepohl, 2005; reinsel, 1993). multivariate time series are of great interest in a variety of fields such as financial, economic, stock market, and earth science, e.g., meteorology (reinsel, 1993). in multivariate time series analysis, not only the properties of the individual series but also the possible cross relationship among the time series data are discussed. the application of the vector autoregressive (var) model has been extensively discussed by malik et al. (2017), sharma et al. (2018), and warsono et al. (2019). in this study, we discuss and develop the best model that describes the relationship between two vectors of data export of coal and data export of oil in indonesia over the period 2002–2017. on the basis of this objective, the var moving average (varma) model was developed to explain the relationship between the data export of coal and oil in indonesia over the period 2002–2017. this journal is licensed under a creative commons attribution 4.0 international license warsono, et al.: modeling and forecasting by the vector autoregressive moving average model for export of coal and oil data (case study from indonesia over the years 2002-2017) international journal of energy economics and policy | vol 9 • issue 4 • 2019 241 methods to find the best model, estimates of parameters, model checking, and forecasting of vector time series are also discussed. 2. statistical model the varma model is commonly used to forecast multivariate time series data and provides a simple framework to study the dynamic relationships among variables (koreisha and pukkila, 2004). the varma model is an extension of the arma model in univariate time series (lutkepohl, 2005; wei, 1990) and is used with the condition that the data have to be stationary over time (lutkepohl, 2005). the varma (p,q) model is a combination of the var (p) model and the vector moving average (q) (vma (q)) model. an m-dimensional time series datum γt is a varma (p,q) process if γ φ γt i i p t i t j j i q t j= + + − = − = −∑ ∑δ θ 1 u u (1) where δ is a constant m×1 vector of means, and δt = (δ1,δ2, δm), u u u ut t t t mt= ( , ,... , )1 2 are vectors of random noise that are independently, identically, and normally distributed with mean zero and covariance matrix σu t t te uu= ( ) , defined as follows: σ u m m m m mm =       σ σ σ σ σ σ σ σ σ 11 12 1 21 22 2 1 2 ... ... ... ... ... .... ...       , ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ i i i i m i i i m i m = , , , , , , , ... ... ... ... ... .... 11 12 1 21 22 2 1 ii m i mm, , ... 2 ϕ             , and θ θ θ θ θ θ θ θ θ j j j j m j j j m j m = , , , , , , , ... ... ... ... ... .... 11 12 1 21 22 2 1 jj m j mm, , ... 2 θ             where i = 1,2,…, p; j = 1,2,…, q. model (1) can also be written in a simpler form using the backshift operator b as follows: φ(b)γt = δ+θ(b)ut (2) where φ( ) -b i b p = = ∑k i i iϕ 1 and θ( )b i q = − = ∑k i i ibθ 1 , biγt = γt−1, biut = ut−1, and ut is vector innovation. some properties of the varma (p,q) model with p>0 and q>0 are discussed. the model is assumed to be identifiable and innovation ut has mean zero and covariance matrix ∑u, which is positive definite; see graybill (1969) for the definition of a positive-definite matrix. we shall assume that the zeros of the determinant polynomials |φ(b)| and |θ(b)| are on or outside the unit circle. the series {γt}will be stationary if the zeros of |φ(b)| are on or outside the unit circle and will be invertible when those of |θ(b)| are on or outside the unit circle (tiao, 2001; tsay, 2005; reinsel, 1993). to find the best model, we estimated some candidate models (varma (1,1), varma (2,1), varma (3,1), and varma (4,1)) using some information criteria (aicc, hqc, aic, and sbc). the selected best model and estimation of the parameters of the selected model were reviewed. if some parameters are not significant in the selected model, then they will be restricted to zero (tsay, 2005; milhoj, 2016) so that the final best model is simpler. the optimal l-step-ahead forecast of γt+l for model (1) is as follows (sas/ets 13.2, 2014; lutkepohl, 2005): | | | 1 1 ˆ ˆˆ ˆ + + − + − = = γ = + γ −∑ ∑ p q t t i t i t j t j t i j       (3) 3. data analysis the data used in this study are the data export of coal and oil from indonesia from january 2002 to december 2017. the data are from the central bureau of statistics (bps) indonesia (bps (a) 2017, and bps (b), 2017). the plot of the data is given in figure 1. the figure shows that for the export of oil from indonesia, the trend increases from 2002 to 2017. from january 2002 to december 2010, the trend increase with volatility is relatively small. however, from 2011 to 2017, the fluctuation of the export is high, which indicates that the volatility of the export is high. from the end of 2012 to 2017, the trend increases. however, from 2010 to the end of 2012, the trend decreases. for the export of coal from indonesia, the trend increases from 2002 to 2012 but decreases from the end of 2012 to the end of 2016, and then increases again in 2017. figure 1 also shows that the data are nonstationary, and this is in line with the augmented dicky–fuller test given in table 1. now, we look at the acf and pacf of data of coal and oil given in (figure 2a and b). from the sample acf of data of coal and oil in (figure 2a and b), the tails cut off very slowly. this indicates that the time series data of coal and oil are not stationary. that is, the means or the variances of time series data of coal and oil are not constant over time. to make the data stationary, differencing needs to be conducted, and the results of differencing with d = 1 are given in table 2. the assumption of stationarity is attained, and modeling of varma can be carried out. figure 1: plot of data export of coal and oil from indonesia from january 2002 to december 2017 warsono, et al.: modeling and forecasting by the vector autoregressive moving average model for export of coal and oil data (case study from indonesia over the years 2002-2017) international journal of energy economics and policy | vol 9 • issue 4 • 2019242 3.1. varma (p,q) modeling to find the best model that fits the data, some varma (p,q) models (i.e., varma (1,1), varma (2,1), varma (3,1), and varma (4,1)) for prediction and forecasting were applied to the data. the selection of the best model was conducted using some information criteria (aicc, hqc, aic, and sbc). the minimum values of these criteria indicate the best model. from table 3, we conclude the following: on the basis of the minimum values of hqc and sbc, the best model is varma table 1: augmented dicky–fuller unit root tests data type lag rho pr<rho tau pr<tau f-test pr>f coal zero mean 3 0.1491 0.7169 0.17 0.7346 single mean 3 −2.1558 0.7584 −1.38 0.5942 1.53 0.6812 trend 3 −1.8119 0.9740 −0.67 0.9736 0.95 0.9735 oil zero mean 3 0.7345 0.8613 0.80 0.8843 single mean 3 −1.6886 0.8136 −0.67 0.8511 0.86 0.8521 trend 3 −22.4281 0.0368 −3.23 0.0824 5.44 0.0972 figure 2: (a and b) plots of trend, autocorrelation function, partial autocorrelation function, and inverse autocorrelation function for data export of coal and oil b a warsono, et al.: modeling and forecasting by the vector autoregressive moving average model for export of coal and oil data (case study from indonesia over the years 2002-2017) international journal of energy economics and policy | vol 9 • issue 4 • 2019 243 (1,1); on the basis of the minimum values of aicc and aic, the best model is varma (2,1). therefore, there are two candidates for the best model. to choose the best model, we check the schematic representation of the parameter estimates of varma (1,1) and varma (2,1) given in the table 4. schematic representation of parameter estimates of varma (1,1) and varma (2,1). table 4 shows that in varma (1,1), four parameters are of significance, and in varma (2,1), six parameters are of significance. in this case, varma (2,1) is chosen as the best model to discuss the characteristics of data and for forecasting data. varma (2,1) is represented as follows: γt = δ+φ1γt−1+φ2γt−2−ψ1εt−1+εt (4) where γt t t =       coal oil , γt t t − − − =      1 1 1 coal oil , γt t t − − − =      2 2 2 coal oil , φ1, φ2 and ψ1 are 2 × 2 matrix parameters for ar1, ar2, and ma1, respectively. εt is vector white noise. the estimate model varma (2,1) is as follows: from table 5, some parameters of the model ar2_1_2, ar2_2_1, and ma1_2_1 are not significantly different from zero. therefore, we can improve the model by restricting those parameters that are not significant, as suggested by tsay (2005) and milhoj (2016). we restrict the parameters ar2_1_2 = 0, ar2_2_1 = 0, and ma1_2_1 = 0, and we conduct the test statistics for these restrictions. from the testing of restricted parameters equal to zero, we obtained the results as given in table 6. table 6 shows that all the tests are not significantly different from zero. by using these restriction parameters, the final model and the estimation of parameters are presented in table 7. the varma (2,1) model with restriction ar2_1_2 = 0, ar2_2_1 = 0, and ma1_2_1 = 0 shows that all the parameters are significant, except for the parameter constants. the varma (2,1) model with restriction is γ γt t=       + − − −       − 4 3746 5 7036 0 3299 0 2472 0 1714 1 1807 . . . . . . 11 2 0 4938 0 0000 0 0000 0 1976 0 8284 0 2751 0 0000 + −       − − − . . . . . . . τt −−       +− 0 9980 1 . ε εt t (5) and the covariance of innovation is, σt = − −       1703 32 669 62 669 62 4539 77 . . . . the varma (2,1) model with restriction can also be written as two univariate regression models: coalt = 4.3746−0.3299 coalt−1+0.2472 oilt−1+0.4938 coalt−2+0.8284 ε1t−1−ε1t (6) oilt = 5.7036−0.1714 coalt−1−1.1807 oilt−1−0.1976 oilt−2+0.9980 ε2t−1−ε2t (7) the statistical test of the parameters in model (5) is given in table 7, and models (6) and (7) are given in table 8. on the basis of the statistical test, model (6) is very significant with the statistical test f = 15.30, and the p < 0.0001. the degree of determination of r-square is 0.3352. on the basis of the statistical test, model (7) is very significant with the statistical test f = 3.01, and the p = 0.0079. the degree of determination of r-square is 0.0903. model (6) also explains that the export of oil at lag 1 (t-1) has a positive effect on the export of coal; the export of coal at lag 1 (t-1) has a negative effect on the export of coal, and the export of coal at lag 2 (t-2) has a positive effect on the export of coal. table 3: criteria aicc, hqc, aic, and sbc for varma (1,1), varma (2,1), varma (3,1), and varma (4,1) criteria model varma (1,1) varma (2,1) varma (3,1) varma (4,1) aicc 15.969 15.954 15.990 16.039 hqc 16.036 16.046 16.106 16.179 aic 15.967 15.949 15.980 16.025 sbc 16.138 16.189 16.290 16.405 varma: vector autoregressive moving average, acf: autocorrelation function, iacf: inverse autocorrelation function, pacf: partial autocorrelation function plot, hqc: hannan-quinn criterion, sbc: schwarz-bayesian criteria, aicc: akaike information criterion table 4: schematic representation of parameter estimates of varma (1,1) and varma (2,1) model variable/lag c ar1 ar2 ma1 varma (1,1) coal • +• •+ oil • •− •− varma (2,1) coal • −• +• −+ oil • •− •• •− + is>2td error, − is < −2 std error, •is between, varma: vector autoregressive moving average table 2: augmented dicky–fuller unit root tests variable type rho pr<rho tau pr<tau coal zero mean −72.68 <0.0001 −5.88 <0.0001 single mean −75.68 0.0013 −5.95 <0.0001 trend −78.02 0.0006 −6.07 <0.0001 oil zero mean −214.74 0.0001 −10.31 <0.0001 single mean −219.13 0.0001 −10.39 <0.0001 trend −220.36 0.0001 −10.39 <0.0001 warsono, et al.: modeling and forecasting by the vector autoregressive moving average model for export of coal and oil data (case study from indonesia over the years 2002-2017) international journal of energy economics and policy | vol 9 • issue 4 • 2019244 model (7) explains that the export of coal at lag 1 (t-1) and the export of oil at lag 1 and lag 2 (t-1 and t-2) have a negative effect on the export of coal. granger causality is used to test two null hypotheses. test 1 tests the null hypothesis where the export of coal is influenced only by itself and not by the export of oil. test 2 tests the null hypothesis where the export of oil is influenced only by itself and not by the export of coal (sas/ets 13.2, 2014). from the results of the granger causality tests, table 9 demonstrates the following: (1) for test 1, chi-square = 11.88 and the p = 0.0078; hence, we reject the null hypothesis. we conclude that the export of coal is not only influenced by itself but also influenced by the export of oil. (2) for test 2, chi-square = 3.74 and the p = 0.2912; hence, we cannot reject the null hypothesis. we conclude that the export of oil is influenced only by itself and not by the export of coal. the patterns of the distribution of errors for data of coal and oil based on model varma (2,1) with restriction are given in figure 3. from (figures 3a and 3b), the patterns of the distribution of errors for data of coal and oil are very close to normal distribution. if we look table 5: model parameter estimates equation parameter estimate standard error t-value pr>|t| variable coal const1 6.95695 5.87137 1.18 0.2375 1 ar1_1_1 −0.31645 0.1081 −2.93 0.0038 coal (t-1) ar1_1_2 0.14442 0.09532 1.52 0.1314 oil (t-1) ar2_1_1 0.43243 0.07895 5.48 0.0001 coal (t-2) ar2_1_2 −0.07719 0.05277 −1.46 0.1452 oil (t-2) ma1_1_1 −0.79453 0.10537 −7.54 0.0001 e1 (t-1) ma1_1_2 0.22456 0.08598 2.61 0.0097 e2 (t-1) oil const2 9.72216 10.114 0.96 0.3377 1 ar1_2_1 −0.17714 0.13769 −1.29 0.1999 coal (t-1) ar1_2_2 −1.14426 0.10035 −11.40 0.0001 oil (t-1) ar2_2_1 0.06579 0.11978 0.55 0.5835 coal (t-2) ar2_2_2 −0.13139 0.07874 −1.67 0.0969 oil (t-2) ma1_2_1 −0.03194 0.07222 −0.44 0.6588 e1 (t-1) ma1_2_2 −1.03147 0.07255 −14.22 0.0001 e2 (t-1) table 6: testing of restricted parameters parameter estimate standard error t-value p-value equation restrict1 −22.631 15.899 −1.42 0.156 ar2_1_2=0 restrict2 3.701 8.531 0.43 0.665 ar2_2_1=0 restrict3 −12.569 22.093 −0.57 0.57 ma1_2_1=0 table 7: model with restriction ar2_1_2=0, ar2_2_1=0, and ma1_2_1=0 and parameter estimates equation parameter estimate standard error t-value pr>|t| variable coal const1 4.3746 5.9932 0.73 0.4663 1 ar1_1_1 −0.3299 0.0873 −3.78 0.0002 coal (t-1) ar1_1_2 0.2472 0.1049 2.36 0.0195 oil (t-1) ar2_1_1 0.4938 0.0663 7.45 0.0001 coal (t-2) ar2_1_2 0 0 oil (t-2) ma1_1_1 −0.8284 0.0882 −9.39 0.0001 e1 (t-1) ma1_1_2 0.2751 0.1201 2.29 0.0232 e2 (t-1) oil const2 5.7036 9.8061 0.58 0.3377 1 ar1_2_1 −0.1714 0.0704 −2.44 0.0158 coal (t-1) ar1_2_2 −1.1807 0.064 −18.44 0.0001 oil (t-1) ar2_2_1 0 0 coal (t-2) ar2_2_2 −0.1976 0.0619 −3.19 0.0017 oil (t-2) ma1_2_1 0 0 e1 (t-1) ma1_2_2 −0.9980 0 −9980 <0.0001 e2 (t-1) table 8: univariate diagnostic checks model variable r-square standard deviation f-value p-value 6 coal 0.3352 41.271 15.3 <0.0001 7 oil 0.0903 67.377 3.01 0.0079 table 9: granger causality wald test test group df chi-square p-value test 1 group 1 variable: coal 3 11.88 0.0078 group 2 variable: oil test 2 group 1 variable: oil 3 3.74 0.2912 group 2 variable: coal warsono, et al.: modeling and forecasting by the vector autoregressive moving average model for export of coal and oil data (case study from indonesia over the years 2002-2017) international journal of energy economics and policy | vol 9 • issue 4 • 2019 245 at the prediction errors for data of coal and oil (figure 4a and b), for the data of coal, it is clear that the prediction errors from 2002 to 2011 are homogeneous, but from 2012 to 2017 the errors fluctuate and are beyond two standard errors. this indicates that the prices are unstable in this horizon (2012-2017). figure 1 supports this argument: from 2002 to 2010, the price increases; from 2011 to 2016, the price is unstable and decreases; and from 2016 to 2017, the price increases. similar to the errors of data for oil, from 2002 to 2010, (figure 4b) shows that the prediction errors are homogeneous and within two standard errors; however, from 2011 to 2016, the errors fluctuate and several are beyond two standard errors. this indicates that the oil price in this horizon (2011-2016) is unstable. figure 1 also supports this argument: from 2002 to 2010, the price increases slowly; and from 2011 to 2016, the price is unstable. table 10: forecasting data export of coal and oil for the next 12 months variable obs time forecast standard error 95% confidence limits coal 193 jan-18 1435.32 41.2713 1354.43 1516.21 194 feb-18 1423.18 74.7498 1276.68 1569.69 195 mar-18 1405.14 105.776 1197.82 1612.45 196 apr-18 1414.37 133.962 1151.81 1676.93 197 may-18 1403.87 158.292 1093.62 1714.12 198 jun-18 1419.77 181.434 1064.16 1775.37 199 jul-18 1412.01 201.151 1017.76 1806.26 200 aug-18 1428.84 220.704 996.271 1861.42 201 sep-18 1423.49 237.428 958.14 1888.84 202 oct-18 1438.64 254.431 939.968 1937.32 203 nov-18 1436.25 269.171 908.687 1963.82 204 dec-18 1448.49 284.278 891.316 2005.67 oil 193 jan-18 1466.25 67.3779 1334.19 1598.3 194 feb-18 1452.16 88.374 1278.95 1625.37 195 mar-18 1471.96 105.267 1265.65 1678.28 196 apr-18 1460.16 121.305 1222.41 1697.91 197 may-18 1474.31 134.017 1211.64 1736.97 198 jun-18 1467.44 147.056 1179.22 1755.67 199 jul-18 1475.73 157.785 1166.48 1784.98 200 aug-18 1474.33 168.923 1143.25 1805.42 201 sep-18 1477.16 178.459 1127.39 1826.94 202 oct-18 1480.72 188.247 1111.76 1849.68 203 nov-18 1479.07 196.984 1092.99 1865.15 204 dec-18 1486.43 205.753 1083.16 1889.7 figure 4: (a and b) prediction errors based on model varma (2,1) for data of (a) coal and (b) oil ba figure 3: (a and b) distribution of error for data of (a) coal and (b) oil ba warsono, et al.: modeling and forecasting by the vector autoregressive moving average model for export of coal and oil data (case study from indonesia over the years 2002-2017) international journal of energy economics and policy | vol 9 • issue 4 • 2019246 the graphs of the model for data of coal (figure 5a) and for data of oil (figure 6a) show that the data and their predictions are close to each other, which indicates that the models fit with the data. table 10 shows that the forecasts for the data of coal begin at 1435.317 for the first period and then decrease for the second to the ninth periods. starting from the tenth period up to the twelfth period, the forecast increases and reaches a value of 1448.491. the forecast for data of oil begins at 1466.245 for the first period and then fluctuates with the trend increase up to the twelfth period. in the twelfth period, the value 1486.427 is attained. the confidence interval of the prediction increases: it is smaller in the first period and larger over time up to the twelfth period. this indicates that even though the model is sound and fits with the data, if the model is used to forecast for long periods, the prediction becomes unstable. this is demonstrated by the large confidence interval. (figures 5b and 6b) describe the behavior of the confidence interval over time from the first period up to the twelfth period. 4. conclusion in this study, the focus is on how to find the best model and use it for forecasting the data export of coal and oil of indonesia over the years 2002-2017. we have developed the best model using the criteria aicc, hqc, aic, and sbc, which fit the data. the best model is varma (2,1), with restriction on some parameters that are non significantly different from zero. the restricted parameters are ar2_1_2 = 0, ar2_2_1 = 0, and ma1_2_1 = 0. all the parameters in the model, ar and ma, are significant, except for the parameter constants. the model shows that the prediction and the real data fit well with each other. the forecasting results show that the standard error increases over time; the standard error in the first month is relatively small compared with the prediction of the means, but increases over time up to forecasting for the next 12 months. this indicates that the model is sound when forecasting for short periods, but the results are unstable (because of the higher standard error) when forecasting for long periods. 5. acknowledgments the authors thank bps (central bureau of statistics, indonesia) for providing the data in this study. the authors also thank universitas lampung for financial support for this study through scheme research professor under contract no. 1368/un26.21/ pn/2018. references bps (a). (2017), export of coal. available from: https://www. docs.google.com/spreadsheets/d/1pigy1jiuxw6_hfgvoemx_ urknjwhcfdthai4cycb4se/edit?usp=sharing. [last retrieved on 2018 jan 10]. bps (b). (2017), export of oil. available from: https://www. docs,google.com/spreadsheets/d/19mtwhuccacoav1w7d6rfbtt_ ixqcxtbedhy7t7r4vcg/edit?usp=sharing. [last retrieved on 2018 jan 10]. graybill, f.a. (1969), introduction to matrices with application in figure 6: (a and b) model and forecast for the next 12 months of data export for oil ba figure 5: (a and b) model and forecast for the next 12 months of data export for coal ba warsono, et al.: modeling and forecasting by the vector autoregressive moving average model for export of coal and oil data (case study from indonesia over the years 2002-2017) international journal of energy economics and policy | vol 9 • issue 4 • 2019 247 statistics. belmont, ca: wadsworth. koreisha, s.g., pukkila, t. (2004), the specification of vector autoregressive moving average models. journal of statistical computation and simulation, 75(8), 547-565. lutkepohl, h. (2005), new introduction to multiple time series analysis. berlin: springer-verlag. milhoj, a. (2016), multiple time series modeling using the sas varmax procedure. cary, nc: sas institute inc. malik, k.z., ajmal, h., zahid, m.u. (2017), oil price shock and its impact on the macroeconomic variables of pakistan: a structural vector autoregressive approach. international journal of energy economics and policy, 7(5), 83-92. pena, d., tiao, g.c. (2001), introduction. in: pena, d., tiao, g.c., tsay, r.s., editors. a course in time series analysis. new york: john wiley and sons. reinsel, g.c. (1993), elements of multivariate time series analysis. new york: springer-verlag. sas/ets 13.2. (2014), user’s guide: the varmax procedure. cary, nc: sas institute inc. sharma, a., giri, s., vardhan, h., surange, s., shetty, r., shetty, v. (2018), relationship between crude oil prices and stock market: evidence from india. international journal of energy economics and policy, 8(4), 331-337. tiao, g.c., box, g.e.p. (1981), multiple time series modeling with applications. journal of the american statistical association, 76, 802-816. tiao, g.c. (2001), vector arma models. in: pena, d., tiao, g.c., tsay, r.s., editors. a course in time series analysis. new york: john wiley and sons. tsay, r.s. (2005), analysis of financial time series. new jersey: john wiley and sons, inc. warsono, w., russel, e., wamiliana, w., widiarti, w., usman, m. (2019), vector autoregressive with exogenous variable model and its application in modeling and forecasting energy data: case study of ptba and hrum energy. international journal of energy economics and policy, 9(2), 390-398. wei, w.w.s. (1990), time series analysis: univariate and multivariate methods. new york: addison-wesley publishing company. . international journal of energy economics and policy | vol 8 • issue 6 • 201816 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2018, 8(6), 16-21. economic and energy security of the republic of kazakhstan azamat amirov, madina kozhukhova, gaukhar koshebaeva, valeryi biryukov, miras zhiyenbayev* karaganda state technical university, karaganda, kazakhstan. *email: zhienbaev.miras@yandex.kz received: 24 july 2018 accepted: 03 october 2018 doi: https://doi.org/10.32479/ijeep.6935 abstract the authors discuss the concept of energy and economic security of the republic of kazakhstan, arguing that energy security is a vital part of economic security of any country. thus, energy security is to be strengthened in order to achieve better economic security. kazakhstan has a large and pretty developed fuel and energy complex that certainly has a very significant impact on its economy. with the aim of analyzing kazakhstan’s energy security in the period of 2000–2015, we construct an energy security performance index that includes ten quantitative indicators operationalizing the four dimensions of energy security, namely the energy “availability,” “affordability,” “efficiency,” and “environmental stewardship.” the analysis clearly shows that kazakhstan has been able to significantly increase its energy security performance over the 15 years. due to the precise research design and data collected, the authors also provide insights into the behavior of each energy security dimension, demonstrating how kazakhstan’s energy security has been constantly changing in the period under analysis and identifying the strongest (“availability” and “affordability”) and weakest (“efficiency” and “environmental stewardship”) energy security dimensions. keywords: kazakhstan, energy security, economic security jel classifications: q2, q3, q4 1. introduction the availability and use of energy resources is a very important condition for the functioning of the economic and social systems. it is common knowledge that national economies have a very strong dependence on energy resources. not all countries have a proper reserve of energy resources and, as a result, have to rely on imports of oil, coal, natural gas, electricity, etc. in order to cover their energy needs. consequently, preservation and proper use of the energy resource potential is a very important element of any state’s economic security and is one of the most important priorities in energy policies. the growing research interest in this set of problems might be seen as a result of the increasing dependence of many countries on importing fuel and energy resources, as well as the already increased competition between the key exporting countries, high volatility of prices in world markets, and the strengthening geopolitical factor in energy relations. in this paper we consider the problem of economic and energy security of kazakhstan, the leading state of central asia. in our opinion, energy security is an integral part of the economic security of the state. thus, it is impossible to have a strong economic security without proper energy security. numerous studies show that the kazakhstan’s economy has a great dependence on the fuel and energy complex, and this dependence is only growing (which is to be discussed below in detail). therefore, the issue of ensuring energy security is highly important for kazakhstan in order to achieve better economic security. our literature review clearly shows that there is no single quantitative study being focused exclusively on the republic of kazakhstan with the purpose of analyzing the gradual development of its energy security over the period of 15 years. thus, this research can fill the existing gap and make a contribution to the scholarly literature. in the first part of the paper are discussed the concepts of energy and economic security, including the role of kazakhstan’s energy this journal is licensed under a creative commons attribution 4.0 international license amirov, et al.: economic and energy security of the republic of kazakhstan international journal of energy economics and policy | vol 8 • issue 6 • 2018 17 and fuel complex in the economy of the leading central asian country. the research design is outlined in the “materials and methods” section. in “results and discussion,” we analyze the obtained data on kazakhstan’s energy security performance. than possible limitations and future research agenda are also discussed. finally, we conclude with a short overview of the research, highlighting main insights and observations. 2. energy and economic security 2.1. conceptualizing economic and energy security the problem of “economic security” is very debated, especially in the context of globalization and new regionalization, the creation of new production and trade chains, active processes unfolding in the digital economy, new industrialization, etc. (grodach, 2011; grigoreva and garifova, 2015; malle, 2016). nevertheless, the concept of “economic security” has a large number of different definitions (cable, 1995; poirson, 1998; hacker et al., 2013). we consider “economic security” as a unified concept within the discipline of political economy that is closely related to the categories of economic stability and vulnerability, economic pressure, coercion, aggression, and economic sovereignty. economic security can be seen as the security of economic relations that has a great influence on the development of the country’s economic potential and ensures its increasing economic growth, which also contributes to the growth of the country’s independence and defense capability in the economic sphere. of course, economic security should be considered as one of the types of national security, along with military, environmental, information security, etc., in our opinion, different types of security are very interrelated and mutually complementary. along with this, we also think and agree with (blum and legey, 2012), (papadimitriou and pistikou, 2015), (cohen and naor, 2013), (shake, 2017) that economic security is the basis of the national security of any sovereign state. in turn, the effective development and operation of the fuel and energy complex of the country that ensures energy security is the basis of the country’s economic security. it is energy that largely shapes and determines the opportunities for economic development, production efficiency, product competitiveness of s, etc. the fuel and energy complex is a system for extracting natural energy resources, enriching them, transforming them into mobile types of energy, as well as transferring, distributing, and consuming energy in all sectors of the national economy. technological unity, organizational interrelations, and economic interdependence allow such different elements of the national economy to act as a single national economic complex. different types of energy are the most important source of development for all sectors of the economy. thus, the sustainable functioning of the fuel and energy complex of both the country and its regions is an important factor for the successful development of the entire economic system and enhancing its economic security. in other words, the effective and stable functioning of the economic system is impossible without rationally organizing and successfully developing a complex of industries aimed at the extraction, processing, and use of fuel and energy resources. the concept of “energy security” is also very debatable and does not have a single definition (sovacool, 2011; 2014; gafurov, 2010). as a rule, energy security is understood as a state of protection against threats to fuel and energy supply to the country’s economy (leal-arcasa, 2015; tongsopit et al., 2016). thus, according to this approach, the most important aspect of energy security is to ensure the uninterrupted access of the population and economic agents to energy resources and the reliability of the supply of energy resources to international markets. thus, “energy security” is an integral component of the concept of “economic security” and can have a large number of categories, the basis of which is to ensure the uninterrupted energy supply to the domestic and foreign markets. nevertheless, there are studies examining other aspects of energy security, including not only the availability of energy but also its efficiency and environmental reliability, etc. (brown et al., 2014; sovacool, 2011; 2014). 2.2. kazakhstan’s fuel and energy complex: security issues the fuel and energy complex is one of the most important structural component of the economy of kazakhstan (karatayev and clarke, 2016). the economy of kazakhstan is very dependent on the sale of raw materials, the lion’s share of which is hydrocarbons. the volatility of world and domestic prices for energy carriers has a direct impact on the economy of the country, causing unpredictability, slowing economic growth, reducing the volume of production and consumption of energy resources. proceeding from the above, the problem of energy security of kazakhstan is very important for the economic and, as a result, national security of this country. despite the rather high research of the issue of energy security in eurasia (inbrayeva et al., 2018; mastepanov, 2015; gracceva and zenewski, 2014, kanellakis et al., 2013), we could not find a quantitative study measuring the current state of kazakhstan’s energy security and analyzing the dynamics of the development of its energy security. many studies focus on the energy security of central asia (akhmetov, 2015), the eurasian economic union (baev, 2012; bogoviz et al., 2017), and only a few analyze the energy security of kazakhstan itself (baizakova, 2010; karatayev and clarke, 2014). this study aims to make a contribution to quantitative studies of energy security in kazakhstan in particular and central asia in general. 3. materials and methods we evaluate kazakhstan’s energy security performance with the help of an index that quantitatively measures the concept of energy security being developed by (sovacool and brown, 2010) and (brown et al., 2014), which was later successfully used by (bogoviz et al., 2017) and (obadi and korcek, 2017). in order to better grasp the concept of energy security and measure it, (sovacool and brown, 2010) and (brown et al., 2014) identify the total of four dimensions in energy security, namely amirov, et al.: economic and energy security of the republic of kazakhstan international journal of energy economics and policy | vol 8 • issue 6 • 201818 “availability,” “affordability,” “energy and economic efficiency,” and “environmental stewardship.” our research is different from those mentioned above in a number of ways. first, we deeply focus on only one country and analyze all the dimensions of its energy security. second, the research is built on the original data that were collected and analyzed not just for 2 years (as [brown et al., 2014] did, for instance) but for the total of 5 years, which eventually allowed us to understand the dynamics within the dimensions of energy security from 1 year to another. all these four dimensions of energy security, following (sovacool and brown, 2010) and (brown et al., 2014), were operationalized in order to gather quantitative data and measure the concept. the “availability” dimension focuses on how well a particular country diversifies its fuel and how much the nation is dependent on the foreign supply. it is based on the three following indicators: (a) “oil import dependency,” (b) “coal import dependency,” and (c) “natural gas import dependency.” we collected the data on kazakhstan with respect to all these three indicators from the international energy agency (iea, n.d.). the dependency on a particular fuel was estimated by ourselves according to scinner (1995), eurostat (2017), and cambridge econometrics (2016). another dimension of energy security, energy “affordability,” stands for the existence of low prices on energy sources and their low volatility over time. this dimension was operationalized with the help of just two indicators (a) electricity prices for households (us$ 100/kwh) and (b) pump price for gasoline (us$/l). the data on kazakhstan came from the world bank (n.d.). the third dimension focuses on energy “affordability,” i.e., on energy equipment and consumer behavior. we use such indicators as (a) “renewable energy consumption,” (b) “gdp per unit of energy use,” and (c) “electric power consumption” to measure energy “affordability” in kazakhstan. we collected the data from the world bank (n.d.) and adjusted the numbers for purchasing power parity. and finally, the fourth dimension of energy security is called the “environmental stewardship” and focuses on how well the environment is actually protected from the use of energy resources. the two widely used indicators captured well this dimension, namely (a) so2 emissions and (b) co2 emissions, the data on which came from the committee on statistics of the republic of kazakhstan (2017) and the world bank (n.d.), respectively. the collected data on all the four dimensions of energy security (being quantitatively operationalized with the help of 10 indicators) are presented in table 1. our time frame is between 2000 and 2015, which is limited because of our impartial access to the data. with the aim of evaluating relative magnitudes of changes in the indicators and make insights on how energy security of kazakhstan has been changing over the years, we use another analytical tool presented in (sovacool and brown, 2010), namely the z-score normalization. being used under the framework of our analysis, the z-score normalization allows to identify how kazakhstan’s energy security performance was changing in the period under analysis and which years were more successful for each dimension of energy security. 4. results and discussion table 2 contains results of the z-score normalization used to capture kazakhstan’s energy security performance in 2000, 2004, table 1: energy security performance index of kazakhstan (2000–2015, z-scores) year availability affordability oil import dependence (%) coal import dependence (%) natural gas import dependence (%) electricity prices for households (us$ 100/kwh) pump price for gasoline (us$/l) 2000 −433.7 −379.38 −31.32 17.25 2.31 2004 −489.3 −324.66 −72.12 15.12 2.78 2008 −577.3 −218.80 −110.47 13.41 2.17 2012 −688.9 −187.29 −139.94 12.54 1.87 2015 −745.9 −112.36 −195.54 10.21 1.62 median −577.3 −218.8 −110.49 13.41 2.17 mean −587.9 −244.498 −109.882 13.71 2.15 sd 131.12 107.25 69.93 2.66 0.44 year energy and economic efficiency environmental stewardship renewable energy consumption (% of total final energy consumption) gdp per unit of energy use (constant 2011 ppp $ per kg of oil equivalent) electric power consumption (kwh per capita) so2 emissions (1000 tons per year) co2 emissions (tons per capita) 2000 2.510 4.150 3169.523 1080.0 7.93 2004 1.880 4.151 3859.193 1492.1 11.53 2008 1.154 4.324 4689.167 1078.5 14.85 2012 1.328 4.998 5180.654 769.6 14.47 2015 1.558 5.319 5600.208 710.6 14.36 median 1.558 4.324 4689.167 1078.5 14.36 mean 1.685 4.588 4499.749 1026.16 12.63 sd 0.53 0.537 986.196 311.504 2.94 amirov, et al.: economic and energy security of the republic of kazakhstan international journal of energy economics and policy | vol 8 • issue 6 • 2018 19 2008, 2012, and 2015. also, we visualize the obtained results in figures 1 and 2. what trends does our statistical analysis clearly demonstrate? first, the research clearly demonstrates evidence that the overall energy security index of kazakhstan has grown by 2.83 points over the 15 years under analysis (figure 1). more than that, the index was negative in 2000, 2004, and 2008, falling over −1 on the index scale in 2004. the index rose sharply in 2012 by 2.4 points and continued rising in 2015, reaching the highest point of 2.04 in the period observed. therefore, we can state that kazakhstan has significantly increased its energy security since 2000. second, there are noticeable changes in the dimensions of energy security (figures 2 and 3). since we decided to analyze the total of 5 years over the period of 15 years, unlike other authors who relied on the same method and used data only for 2 years, the 1st one and the last one (brown et al., 2014; bogoviz et al., 2017), our data allows us to observe how each dimension was gradually changing in the period under analysis. the “availability” and “affordability” dimensions have been constantly rising from 2000 (expect a slight decrease in energy “affordability” in 2004), making these dimensions mainly responsible for the overall increase in kazakhstan’s energy security. the energy “availability” has been rising by 0.5 points each year, making an impressive increase of 2.5 points by 2015. according to iea (n.d.), kazakhstan has significantly increased the production (and export) of oil, coal, and natural gas. the same applies to the energy “affordability” dimension, which has been able to almost constantly rise by 0.838 points in each year under analysis, excluding the year of 2004 when it slightly decreased by 14%. in overall, the energy “affordability” dimension of our index has risen by the total of 4.19 points. third, other two dimensions of our index has decreased in the analyzed period. the most severe decline has experienced the energy and economic “efficiency” dimension, with the total decline of 1.6 points. our data clearly show that this dimension was constantly rising from 2000 (0.62) up to 2008 (1.3), but it decreased in the next two years. the environmental stewardship dimension also experienced a decline of 1 point by 2015, starting with a positive value of 1.428 in 2000 and having 0.423 in 2015. we also note that the most severe decline was experienced by this dimension in 2008 when it lost 3.68 points. if one is to compare the structure of the energy security performance index in 2000 and 2015, it is clear that the leading dimensions in 2000 are the energy “efficiency” and “environmental stewardship” dimensions, since only they have positive values. in turn, the leading dimensions in 2015 are the energy “affordability” and “efficiency” dimension. however, the “environmental stewardship” dimensions occupies almost the same value in 2015 after experiencing a severe decline in 2000–2008. in contrast, the energy “efficiency” dimension has an opposite trajectory. it is rising from 2000 to 2008 and is sharply decreasing in the period from 20008 till 2015. therefore, the energy “efficiency” dimension is the weakest one in kazakhstan’s energy security performance. “environmental stewardship” is another relatively weak dimension that should be strengthened in kazakhstan, along with the energy and economic “efficiency” dimension. table 2: energy security performance by year: results of the z-score normalization year availability affordability energy and economic efficiency environmental stewardship total 2000 −1,16014263 −1,68 0,62 1,4284303 −0,79 2004 −0,59793697 −1,96 1,0982846 0,20 −1,26 2008 −0,30406881 0,0635306 1,296956 −2,251967844 −1,195 2012 0,7212524 1,0717556 −0,78270599 0,20 1,21 2015 1,340896 2,51 −2,23733202 0,423463965 2,04 figure 3: sifts in energy security performance index (z-scores, 2000–2015) figure 1: the shift in energy security performance index (in total, z-scores, 2000–2015) figure 2: shifts in energy security performance index (in total, z-scores, 2000–2015) amirov, et al.: economic and energy security of the republic of kazakhstan international journal of energy economics and policy | vol 8 • issue 6 • 201820 in sum, kazakhstan has been able to increase its energy security over the 15 years under analysis mainly due to the energy “availability” and “affordability” dimensions. however, the other two dimensions have declined, namely the “environmental stewardship” and energy “efficiency” dimensions. the most severe decline (by 2.8 points) is observed in the energy and economic “efficiency” dimension. 5. limitations and future research in our opinion, this research can be advanced in a number of ways. first, for instance, other indicators better capturing the concept of energy security in kazakhstan can be used to make more precise measurements. second, one may analyze the behavior of energy security dimensions. we just briefly outlined some of their behavioral patterns, without going deeper into causal relationships existing within each dimension and the overall energy security performance. we also believe that a robust qualitative analysis is much needed to understand certain trends in kazakhstan’s energy security performance over the last 15 years, especially with respect to the energy “efficiency” and “environmental stewardship” dimensions. 6. conclusion there is a strong dependency existing between energy security and economic security of kazakhstan, which is caused by the large influence the fuel and energy complex of the country has on the whole national economy. consequently, the issue of energy security is of highest importance for kazakhstan. our analysis of energy security performance kazakhstan clearly demonstrates that the country’s overall energy security has been constantly rising. however, this growth is mainly due to the rising performance in the energy “availability” and “affordability” indicators, while one observes a sharp decline in the energy and economic “efficiency” dimension and a much slower decline in the “environmental stewardship” dimension. references akhmetov, a. (2015), measuring the security of external energy supply and energy exports demand in central asia. international journal of energy economics and policy, 5(4), 901-909. baev, p.v. (2012), from european to eurasian energy security: russia needs and energy perestroika. journal of eurasian studies, 3, 177-184. baizakova, k.i. (2010), energy security issues in the foreign policy of the republic of kazakhstan. american foreign political interests, 32(2), 103-109. blum, h., legey, l. (2012), the challenging economics of energy security: ensuring energy benefits in support of sustainable development. energy economics, 34, 1982-1989. bogoviz, a.v., lobova, s.v., ragulina, y.v., alekseev, a.n. (2017), a comprehensive analysis of energy security in the member states of the eurasian economic union, 2000-2014. international journal of energy economics and policy, 7(5), 93-101. brown, m.a., wang, y., sovacool, b.k., d’agostino, a.l. (2014), forty years of energy security trends: a comparative assessment of 32 industrialized countries. energy research & social science, 4, 64-67. cable, v. (1995), what is international economic security? international affairs, 71(2), 305-324. cambridge econometrics. (2016), a study on oil dependency in the eu: a report for transport and environment. available from: https:// www.camecon.com/wp-content/uploads/2016/11/study-on-eu-oildependency-v1.4_final.pdf. cohen, n., naor, m. (2013), reducing dependence on oil? how policy entrepreneurs utilize the national security agenda to recruit government support: the case of electric transportation in israel. energy policy, 56, 582-590. csrk, committee on statistics of the republic of kazakhstan. (2017), emissions of harmful substances into the atmosphere. available from: http://www.stat.gov.kz/faces/wcnav_externalid/ e c o l o g a 1 ? l a n g = r u & _ a d f . c t r l s t a t e = n v i u k 4 p 0 0 _ 1 3 & _ afrloop=4816627470171765#%40%3f_afrloop %3d481662747 0171765%26lang%3dru%26_adf.ctrl-state%3di5xs865vi_4. gafurov, a.r. (2010), the essence of the category “energy security” and its place in the overall security structure. vestnik mgtu, 13(1), 178-182. gracceva, f., zenewski, p. (2014), a systematic approach addressing energy security in a low-carbon eu energy system. applied energy, 123, 335-348. grigoreva, e., garifova, l. (2015), the economic security of the state: the institutional aspect. procedia economics and finance, 24, 266-273. grodach, c. (2011), barriers to sustainable economic development: the dallas-fort worth experience. cities, 28(4), 300-309. hacker, j.s., huber, g.a., nichols, a., rehm, p., schlesinger, m., valletta, r., craig, s. (2013), the economic security index: a new measure for research and policy analysis. the review of income and wealth, 60(s1), 5-32. iea, international energy agency. (n.d.), statistics: global energy data at your fingertips. available from: https://www.iea.org/statistics. inbrayeva, a., sannikov, d.v., kadyrov, m.a., zapevalov, v.n., hasanov, e.l., zuev, v.n. (2018), importance of the caspian countries for the european energy security. international journal of energy economics and policy, 8(3), 150-159. kanellakis, m, martinopoulos, g, zachariadis, t. (2013), european energy policy-a review. energy policy, 62, 1020-1030. karatayev, m., clarce, m. (2014), current energy resources in kazakhstan and the future potential of renewables: a review. energy procedia, 59, 97-104. karatayev, m., clarke, m. (2016), a review of current energy systems and green energy potential in kazakhstan. renewable and sustainable energy reviews, 55, 491-504. leal-arcasa, r., ríosb, j.a., grassob, c. (2015), the european union and its energy security challenges: engagement through and with networks. contemporary politics, 21(3), 273-293. malle, s. (2016), economic sovereignty: an agenda for militant russia. russian journal of economics, 2(2), 111-128. mastepanov, a.m. (2015), chinese initiative economic belt of the great silk road and the problem of energy security in eurasia. post-soviet issues, 4, 3-15. obadi, s.m., korcek, m. (2017), eu energy security-multidimensional analysis of 2005-2014 development. international journal of energy economics and policy, 7(2), 113-120. papadimitriou, p., pistikou, v. (2015), economic diplomacy in national security. procedia economics and finance, 19, 129-145. poirson, h. (1998), economic security, private investment, and growth in developing countries. international monetary fund working paper, no. wp/98/4, 1-9. amirov, et al.: economic and energy security of the republic of kazakhstan international journal of energy economics and policy | vol 8 • issue 6 • 2018 21 scinner, w. (1995), measuring dependence on imported oil. available from: https://www.eia.gov/totalenergy/data/monthly/pdf/historical/ imported_oil.pdf. shake, k. (2017), national security challenges. orbis, 61(1), 4-12. sovacool, b., brown, m. (2010), competing dimensions of energy security: an international perspective. annual review of environment and resources, 35, 77-108. sovacool, b. (2011), evaluating energy security in the asia pacific: towards a more comprehensive approach. energy policy, 39(11), 7472-7479. sovacool, b. (2014), what are we doing here? analyzing fifteen years of energy scholarship and proposing a social science research agenda. energy research and social science, 1, 1-29. tongsopit, s., kittner, n., chang, y., aksornkij, a., wangjiraniran, w. (2016), energy security in asean: a quantitative approach for sustainable energy policy. energy policy, 90, 60-72. world bank. (n.d.), world bank open data. available from: https://www. data.worldbank.org. . international journal of energy economics and policy | vol 10 • issue 4 • 2020500 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(4), 500-506. decomposition of growth factors in high-tech industries and co2 emissions: after the world financial crisis in 2008 yu-chen yang1, cheng-yih hong2*, syamsiyatul muzayyanah3, rishan adha3 1department of applied economics, national chung-hsing university, taiwan, 2faculty of finance, chaoyang university of technology, taiwan, 3department of business administration, chaoyang university of technology, taiwan. *email: hcyih@cyut.edu.tw received: 11 february 2020 accepted: 06 may 2020 doi: https://doi.org/10.32479/ijeep.9411 abstract taiwan’s economic development faces two problems, one is the imbalance of the economic structure, and the other is that the industrial structure must be upgraded. this is a problem that has existed since the 1990s, but it has not been solved for a long time. the outbreak of the world financial crisis in 2008 severely damaged the international economy and finance, and taiwan suffered a huge economic shock. in the face of an economic predicament, taiwan attempts to transform the unbalanced economic system through technological innovation through public investment and the updating of corporate equipment, and sets the goal of sustainable development, of which high-tech industries have become the focus of economic development. this paper takes the financial crisis as the research period, analyzes the growth of the industries and their causes through the economic growth decomposition model, and estimates the co2 emissions generated, which will help understand taiwan’s future economic development. the research results show that the growth of high-tech industries after the financial crisis is dominated by semiconductors and power equipment-related industries. the growth factor is innovation of input technology and the improvement of self-sufficiency. at the same time, co2 emissions are mainly caused by these two factors. keywords: high-tech industries, co2 emissions, input technology, growth decomposition model jel classifications: q43, c6, e2, e210 1. introduction from 1981 to 2016, taiwan underwent liberalization, internationalization, and global economic changes. in the course of economic development during these 35 years, except for the internet bubble economy in the united states in 2002 and the impact of the global financial crisis in 2009, taiwan has shown economic growth. after joined the world trade organization (wto) in 2002, taiwan became a member of the wto, and expanding international trade has changed the industrial structure. in 1981, the gdp of agriculture, industry, and services accounted for 7.35%, 43.83%, and 48.82% of the overall industry. by 1988, the service industry had exceeded 50%, and the proportion of agricultural output value had dropped significantly. the proportion of primary industries has gradually declined and the proportion of tertiary industries has gradually increased. by 2016, the agricultural, industrial and service industries’ gdp ratios were 1.82%, 35.06% and 63.13%, respectively. in other words, taiwan’s industrial structure has changed a lot after joining the wto. after the 1960s, taiwan’s sustained high growth was through employment creation and economic development through the trade export industry. however, in the 1980s, liberalization and market opening, the pace of industrial innovation could not keep up with competitors’ price strategies, and taiwan ’s economy could not be as fast as in the past continue to grow. since import and export trade has become the main economic structure, the volume of trade has become an important factor in the change of industrial structure. especially after the plaza agreement in 1985, the appreciation of the currency led to a substantial increase in trade volume. imports this journal is licensed under a creative commons attribution 4.0 international license yang, et al.: decomposition of growth factors in high-tech industries and co2 emissions: after the world financial crisis in 2008 international journal of energy economics and policy | vol 10 • issue 4 • 2020 501 and exports have gradually become an important factor in taiwan’s economic growth. in 2005, it exceeded 200 billion us dollars, and the value of imports and exports has expanded. the crisis of the world financial tsunami was triggered in september 2008. the export trade volume has fallen sharply from a growth of more than 10% in the first 8 months, and has begun to turn negative growth in the third quarter. by the first quarter of 2009, taiwan’s exports the decline was expanded to −26.87%. in order to respond to economic losses caused by financial shocks, taiwan has implemented multiple fiscal policies and expanded public investment so that economic growth can gradually return to stability. among them, taiwan attaches great importance to the research and innovation of high-tech industries and plays an important role in economic development. the total value of trade in 2014 was a record high of $ 601.9 billion. judging from the gdp value of imports and exports, imports and exports accounted for 43.28% and 46.24% each in 1981, and have increased to 43.51% and 52.90% in 2016. the financial crisis has raised taiwan’s focus on the development of high-tech industries. in addition, energy policies are also adjusted under environmental protection. taiwan’s investment in renewable energy generation systems attempts to provide more sources of electricity to achieve economic development and environmental protection. in order to achieve research objectives, this paper will analyze the growth factors of high-tech industries after the financial crisis, and discuss the relationship between power consumption and co2 emissions, which will help to understand the direction of taiwan’s industrial structure adjustment in the future. in order to obtain more specific data to analyze the research topic of this thesis, a factor decomposition model of the high-tech industry will be established in section 3 to establish two factor decomposition models of co2 emissions. 2. literature review the past literature on the relationship between the economy and the environment can be divided into several stages of research. the early literature focused on the relationship between economic growth and environmental pollutants. the analytical point of view is represented by the environmental kuznets curve (ekc) (lee and lee, 2009; ang, 2007; saboori et al., 2012). the ekc hypothesis suggests that the level of environmental pollution will increase with the country’s economic development, but will start to decrease as the national income increases beyond the turning point (dinda, 2004). with the rapid increase of energy consumption caused by economic development, the research focus has gradually shifted to the impact of energy (electricity) use on environmental loads (e.g. kraft and kraft, 1978; payne, 2010a; payne, 2010b; ozturk, 2010 ozturk and acaravci, 2011; farhani et al., 2014; bella et al., 2014; dogan, 2015; njoke et al., 2019; sunde, 2020). in addition, many studies often use granger causality to analyze the relationship between economic growth and energy consumption, and further analyze the relationship between economic growth, energy consumption and environmental pollution. however, in many studies, the relationship between economic development, energy consumption, and pollution in different countries has different results. njoke et al. (2019) points out the relationship between cameroon’s power consumption, carbon emissions and economic growth from 1971 to 2014. the study indicates that there is a significant relationship between co2 emissions and economic growth, whether short-term or long-term. however, studies have shown different results. for example, ozturk and acaravci (2011) pointed out that there is no relationship between electricity consumption and economic growth in most middle east and north africa countries. there are also numerous studies analyzing the relationship between energy consumption and environmental damage, such as yavuz and yilanci (2013), presno et al. (2018), and aydin and esen (2018). because economic growth brings changes in the industrial structure, and the relationship between the economy and the environment is often subject to the influence of industrial structure styles, changes in the industrial structure will cause different results. in addition, attention has been paid to the adjustment of power sources. in recent years, there has been an increasing trend in research on renewable energy (dogan, 2015; bölük and mert, 2015). however, with the development of globalized economy, economic growth has indeed caused significant environmental impacts (dreher, 2006; managi and kumar, 2009; jorgenson and givens, 2014; li et al., 2015; doytch and uctum, 2016; you and lv, 2018; saint akadiri et al., 2019). managi and kumar (2009) research pointed out that trade does have an adverse effect on co2 emissions, and doytch and uctum (2016) also believe that improper investment activities will cause environmental damage. in addition, dreher (2006) proposed that the global economy should invest in green related industries to improve the environment. 3. methodology and data this research model is a factor decomposition model established by i-o tables (input-output tables) in different periods. it is considered that there are changes in prices and quantities in economic growth in different periods. in addition, the analysis period of this paper is set between 2011 and 2016. therefore, the establishment of the model of this paper needs to be processed through substantial processes in order to make the two periods industry price benchmarks are consistent. this section uses fujita and william (1997), hong et al. (2018), and hong et al. (2019) to build the following three models. 3.1. the decomposition model of high-tech industries growth the equilibrium equation of the i-o model of the high-tech industry can be expressed by the quantity equations (1). x i i m a i m f e� � �� ��� �� �� � ��� �� �1 (1) where, the definition of each variable in the equation is as follows x is a vector representing the total output of the industry (n × 1); a represents the input coefficient matrix (n × n). as matrix a yang, et al.: decomposition of growth factors in high-tech industries and co2 emissions: after the world financial crisis in 2008 international journal of energy economics and policy | vol 10 • issue 4 • 2020502 reflects technology of production, it is usually called technological matrix; f is the domestic final demand vector (n × 1); e is the export vector (n × 1); m is the diagonal determinant of the import coefficient (n × n). t and t + 1 represent the base year and the comparative year. the changes in the two periods can be written as: � x i i m a i m f e i i m a t t t t t t t � � �� ��� �� �� � ��� �� � � �� ��� � � � � � � �1 1 1 1 1 1 �� �� � ��� �� �1 i m f et t t (2) when i i m a bt t t� �� ��� �� �� � � �1 1 1 1 � and i i m a bt t t� �� ��� �� � �1 are substituted into equation (2), resulting in the following modifications: � x b i m f i m ft t t t t� �� � � �� ��� ��� � � �1 1 1 1 (changes in domestic final demand) � �� �� �b e et t t1 1 � (changes in exports) � �� � � �� ��� ��� �b i m f i m ft t t t t1 1 (changes in final goods imports) � �� � �� � ��� ���b b i m f et t t t1 * (changes in self-sufficiency) � �� � �� � ��� ��b b i m f et t t t* � (changes in input technology) (3) where, i i m a bt t� �� ��� �� �� � 1 1 * .. 3.2. the decomposition model of co2 emissions growth this section uses equation (3) to establish a co2 emissions growth model. this will require an estimation of the industry’s co2 emissions coefficient. the model building process is shown below. co2t and co2t+1 represent co2 emissions in t years and t+1 years. co c x c i i m a i m f et t t t t t t t t2 1 � � � �� ��� �� �� � ��� �� � � � (4) ( ) ( ) 1 2 1 1 1 1 1 1 1 1 ˆ t t t t t t t t co c x i i m a i m f e − + + + + + + + +  = = − −   − +  (5) co co cot t2 1 2 2� � � � (6) where the emissions coefficient c co xj j j= 2 , and ĉ is the diagonal matrix of the elements of the emissions coefficients for various industries. 1 0 0 ˆ n c c c    =            ( ) ( )2 1 1 1 1 1ˆt t t t t tco c b i m f i m fδ + + + + + = − − −  (a) ( )1 1 1ˆt t t tc b e e+ + + −+ (b) ( ) ( )1 1 1ˆt t t t t tc b i m f i m f+ + + − −+  −  (c) ( ) ( )*1 1ˆt t t t tc b b i m f e+ +  − − ++  (d) ( ) ( )*1ˆ ˆt t t t t tc b c b i m f e+  − − ++  (e) (a) the co2 emissions of changes in domestic final demand;(b) the co2 emissions of changes in exports;(c) the co2 emissions of changes in final import coefficients;(d) the co2 emissions of changes in self-sufficiency coefficients;(e) the co2 emissions of changes in production input technical coefficients. from the five factors (a) to (e), we can estimate the scale of co2 emissions, which will help promote the future development of the industries. 4. empirical results and discussion 4.1. analysis of growth factors of high-tech industries after the financial crisis the growth of the high-tech industry since the 1990s has been the main factor driving taiwan’s economic development. this section empirically analyzes whether this trend has changed after the financial crisis. at the same time, what factors will change the high-tech industry? on the other hand, does the growth of high-tech industries also change in co2 emissions? this will also be the focus of this section. because high-tech industries include a variety of different industries, in order to be able to more fully identify the characteristics of industrial development, this section divides high-tech industries into three major industrial groups according to the nature of the industry, namely “semiconductor related industries,” “computer and electronics related industries,” and “power system related industries.” 4.1.1. growth factors of semiconductor related industries table 1 shows the growth scale of “semiconductor related industries” during 2011–2016. from table 1, we can see that the semiconductors industry has the largest growth, which accounts for 75.04% (nt$ 1,315,252 million) of “semiconductor related industries,” while the passive electronic components sector has the least growth, only nt$ 46,873 million. the biggest factor in the growth of the semiconductors industry comes from the improvement of self-sufficiency, which is increasing the proportion of domestic industrial manufacturing, which means that this sector has improved the integrity of the domestic production chain after the financial crisis. in addition, the improvement of input technology created the semiconductors industry by nt$ 306,952 million, which accounted for 23.34% of the total. on the other hand, the biggest factor driving the growth of “semiconductor related industries” is the technological innovation of input technology, yang, et al.: decomposition of growth factors in high-tech industries and co2 emissions: after the world financial crisis in 2008 international journal of energy economics and policy | vol 10 • issue 4 • 2020 503 which contributed nt$ 638,346 million, which accounted for 36.42% of the total growth (=nt$ 638,346 million/nt$ 1,752,843 million). 4.1.2. growth factors of computer and electronics related industries the computer and electronics industries are the foundation of hightech industries. however, after the 1990s, these related industries were largely transferred from taiwan to chinese production. from table 2, we can see that the changes in computer and electronics related industries have shown negative growth (-nt$ 541,763 million). the largest reduction was in the communications industry, which was about nt $ 472,008 million. the biggest factor that caused the reduction of the communication industry was exports (-nt$ 466,976million), followed by domestic final demand (-nt$ 102,949 million). despite the negative growth of “computer and electronics related industries,” there are also growing industries, which include computer products, computer peripherals and measurement, navigation, control and other industries. the main factor for these growing industries comes from input technology, which shows that technological innovation is still a necessary condition for taiwan’s industrial development. 4.1.3. growth factors of power system related industries taiwan has promoted the transformation of power generation systems from 2017, and it is particularly important to observe the growth and changes of “power system related industries.” table 3 shows the growth of power system related industries between 2011 and 2016. it can be seen from the table that the growth of other power equipment and transportation related industries is the largest, accounting for about 142.00% and 67.85% of the “power system related industries.” after the financial crisis, innovation in input technology was the biggest factor driving the growth of “power system related industries.” this factor created a total value of nt$ 436,951 million, and self-sufficiency and final goods imports factors also created nt$ 202,381 million, nt$ 78,302 million. the transformation of energy sources requires new technologies and investments, as well as changes in the relevant legal systems of energy supply. this is a major reform project. therefore, table 3 shows that the related industries of the power system have improved significantly in terms of technological innovation and self-sufficiency. 4.2. analysis of co2-emissions changes of high-tech industries after the financial crisis economic growth and increased energy consumption may also lead to more co2 emissions. this section estimates the scale of co2 emissions from economic growth in section 4.1. 4.2.1. the co2 emissions factors of the semiconductor-related industries table 4 shows the co2 emissions increased by “semiconductor related industries” during the period of 2011-2016, and it can be known from the data that this industry group has increased by a total of 5,446,876 tons during the 5-year period. this result is mainly due to the improvement of input technology to increase production. among them, the growth rate of the semiconductors industry is the most obvious, with a total increase of co2 emissions of about 4,087,083 tons. table 1: growth factors of semiconductor related industries (2011-2016) classification of industries changes in factors (a) changes in domestic final demand (b) changes in exports (c) changes in final goods imports (d) changes in self‑sufficiency (e) changes in input technology semiconductors 248,559 240,202 185,046 334,493 306,952 passive electronic components 11,836 2,452 8,054 16,208 8,323 printed circuit board −47,685 30,034 8,788 13,920 54,682 optoelectronic materials and components −174,725 85,884 12,699 8,958 213,717 other electronic components 39,179 520 37,031 53,047 54,673 total 77,163 359,091 251,617 426,626 638,346 unit: nt$ million table 2: growth factors of computer and electronics related industries (2011-2016) classification of industries changes in factors (a) changes in domestic final demand (b) changes in exports (c) changes in final goods imports (d) changes in self‑sufficiency (e) changes in input technology computer products 4,260 9,445 3,370 892 13,820 computer peripherals −14,382 14,055 −3,670 −69 24,649 communication −102,949 −466,976 3,027 2,124 92,766 audiovisual electronics −4,770 −26,809 3,155 2,764 4,678 blank data storage media −14,864 −40,546 −28 634 8,750 measurement, navigation, control 20,359 −109,974 58,225 29,738 17,551 radiation and electronic medical equipment, optical instruments −11,788 −114,372 17,971 21,691 15,510 total −124,134 −735,177 82,050 57,774 177,724 unit: nt$ million yang, et al.: decomposition of growth factors in high-tech industries and co2 emissions: after the world financial crisis in 2008 international journal of energy economics and policy | vol 10 • issue 4 • 2020504 on the whole, although “semiconductor related industries” can also create industry growth after the financial crisis, co2 emissions are also showing positive growth from the five factors in the table. 4.2.2. the co2 emissions factors of computer related industries the performance of co2 emissions in the “computer and electronics related industries” group is shown in table 5. it can be seen from the table that the largest increase in co2 emissions is in the computer-related industries. among them, computer products and computer peripherals increased by 98,777 tons and 63,962 tons respectively. due to the impact of the financial crisis, the negative wealth effect reduced the demand for domestic final demand and exports, which indirectly contributed to the reduction of co2 emissions. these two factors reduced co2 emissions by 385,741tons and 2,284,528 tons, respectively. 4.2.3. the co2 emissions factors of power system related industries economic development requires electricity security and stable supply, while also taking into account environmental preservation to improve the quality of life. the analysis period of this paper is only up to 2016, and it does not include the energy transition policies after 2017. therefore, the growth of “power system related industries” in table 6 is only reflected in the estimated data under the past power generation system. due to the reduction of domestic final demand and exports caused by the financial crisis, these two factors have reduced co2 emissions by 1,142,499 tons and 396,940 tons, of which the professional machinery industry is the most significant. the wires, cables and wiring related industries reduced co2 emissions by 475,015 tons. on the other hand, the main industries with increased co2 emissions are other power equipment (980,619 tons) and transportation related (468,523 tons). table 3: growth factors of power system related industries (2011-2016) classification of industries changes in factors (a) changes in domestic final demand (b) changes in exports (c) changes in final goods imports (d) changes in self‑sufficiency (e) changes in input technology power generation, transmission and distribution −58,713 −13,213 4,196 474 16,805 battery −1,257 −599 985 6,733 3,121 wires, cables and wiring −141,364 −11,499 1,727 −6,537 41,386 lighting device −10,437 −2,478 −107 167 5,129 household appliances −6,883 1,008 −1,107 216 7,956 other power equipment 106,333 −38,276 20,305 172,743 54,465 professional machinery −250,847 −125,380 71,456 46,963 177,987 transportation related −4,496 62,699 −19,153 18,378 130,102 total −367,664 −127,738 78,302 202,381 436,951 unit: nt$ million table 4: co2 emissions factors of the semiconductor-related industries (2011-2016) classification of industries changes in factors (a) changes in domestic final demand (b) changes in exports (c) changes in final goods imports (d) changes in self‑sufficiency (e) changes in input technology semiconductors 772,385 746,416 575,022 1,039,421 953,839 passive electronic components 36,780 7,619 25,027 50,366 25,863 printed circuit board −148,179 93,329 27,308 43,256 169,922 optoelectronic materials and components −542,950 266,880 39,462 27,837 664,116 other electronic components 121,747 1,616 115,072 164,841 169,894 total 239,780 1,115,858 781,888 1,325,720 1,983,630 unit: tons table 5: co2 emissions factors of computer related industries (2011-2016) classification of industries changes in factors (a) changes in domestic final demand (b) changes in exports (c) changes in final goods imports (d) changes in self‑sufficiency (e) changes in input technology computer products 13,238 29,350 10,472 2,772 42,945 computer peripherals −44,691 43,675 −11,404 −214 76,596 communication −319,909 −1,451,106 9,406 6,600 288,266 audiovisual electronics −14,823 −83,308 9,804 8,589 14,537 blank data storage media −46,189 −125,995 −87 1,970 27,190 measurement, navigation, control 63,265 −341,739 180,931 92,409 54,539 radiation and electronic medical equipment, optical instruments −36,631 −355,406 55,844 67,404 48,197 total −385,741 −2,284,528 254,967 179,530 552,269 unit: tons yang, et al.: decomposition of growth factors in high-tech industries and co2 emissions: after the world financial crisis in 2008 international journal of energy economics and policy | vol 10 • issue 4 • 2020 505 5. conclusions and policy implications taiwan’s economic development is facing an imbalance between the economic structure and the industrial structure. the world financial crisis in 2008 caused huge economic losses and increased unemployment. in the future, taiwan’s economic planning will focus on the economic goals of industrial restructuring and sustainable development. the key to accomplishing this economic goal lies in the success of the development of high-tech industries in the future. this research is to analyze the economic and industrial changes after the financial crisis, and to analyze the factors of industrial growth and change with the industry’s composition model. this will help to understand and follow the trend of taiwan’s economic development, and can provide specific suggestions. from the above empirical results, the following points are summarized. the high-tech industry is centered on machinery-related industries. the growth during the 5 years after the financial crisis (2011-2016) created an increase of nt $ 1,433,312 million, accounting for 27.61% of gdp growth. in the high-tech industry, semiconductors, power equipment and electronic components-related industries have grown the most. in addition, the growth of high-tech industries is mainly affected by the innovation of input technology and the improvement of self-sufficiency. the former can improve production efficiency and industrial upgrading, while the latter can improve domestic employment opportunities and industrial structure transformation. therefore, after the financial crisis, although taiwan’s economy suffered great economic damage, it also stimulated technological innovation and increased the proportion of domestic industrialization. nevertheless, under the dual goals of environmental protection and economic growth, how to reduce co2 emissions is an important issue for taiwan at present. empirical evidence shows that the high-tech industry is still subject to the financial crisis and has shown significant growth, which has also increased co2 emissions. among them, semiconductors have increased the most, accounting for more than 90% of the total high-tech. references akadiri, s.s., lasisi, t.t., uzuner, g., akadiri, a.c. (2019), examining the impact of globalization in the environmental kuznets curve hypothesis: the case of tourist destination states. environmental science and pollution research, 26, 12605-12615. ang, j.b. (2007), co2 emissions, energy consumption, and output in france. energy policy, 35, 4772-4778. aydin, c., esen, ö. (2018), does the level of energy intensity matter in the effect of energy consumption on the growth of transition economies? evidence from dynamic panel threshold analysis. energy economics, 69, 185-195. bella, g., massidda, c., mattana, p. (2014), the relationship among co2 emissions, electricity power consumption and gdp in oecd. journal of policy modeling, 36, 970-985. bölük, g., mert, m. (2015), the renewable energy, growth and environmental kuznets curve in turkey: an ardl approach. renewable and sustainable energy reviews, 52, 587-595. dinda, s. (2004), environmental kuznets curve hypothesis: a survey. ecological economics, 49, 431-55. dogan, e. (2015), the relationship between economic growth and electricity consumption from renewable and non-renewable sources: a study of turkey. renewable and sustainable energy reviews, 52, 534-546. doytch, n., uctum, m. (2016), globalization and the environmental impact of sectoral fdi economic systems. economic systems, 40(4), 582-594. dreher, a. (2006), does globalization affect growth? evidence from a new index of globalization. applied economics, 38(10), 1091-1110. farhani, s., chaibi, a., rault, c. (2014), co2 emissions, output, energy consumption, and trade in tunisia. economic modelling, 38, 426-434. fujita, n., william, e.j. (1997), employment creation and manufactured exports in indonesia: 1980-90. bulletin of indonesian economic studies, 33(1), 103-115. hong, c.y., lee, y.c., tsai, m.c., tsai, y.c. (2018), agricultural sector input technical coefficients, demand changes and co2 emissions after the financial crisis: environmental input-output growth factor model approach. international journal of energy economics and policy, 8(6), 339-345. hong, c.y., yen, y.s., chien, p.c. (2019), sources of economic growth and changes in energy consumption: empirical evidence for taiwan (2004-2016). international journal of energy economics and policy, 9(3), 346-352. jorgenson, a.k., givens, j.e. (2014), economic globalization and environmental concern: a multilevel analysis of individuals within 37 nations. environment and behavior, 46(7), 848-871. kraft, j., kraft, a. (1978), on the relationship between energy and gnp. the journal of energy and development, 3, 401-403. lee, c.c., lee, j.d. (2009), income and co2 emissions: evidence from panel unit root and cointegration tests. energy policy, 37, 413-23. li, z., xu, n., yuan, j. (2015), new evidence on trade-environment table 6: co2 emissions factors of power system related industries (2011-2016) classification of industries changes in factors (a) changes in domestic final demand (b) changes in exports (c) changes in final goods imports (d) changes in self‑sufficiency (e) changes in input technology power generation, transmission and distribution −182,448 −41,059 13,039 1,473 52,221 battery −3,906 −1,861 3,061 20,922 9,698 wires, cables and wiring −439,282 −35,733 5,367 −20,313 128,605 lighting device −32,432 −7,700 −332 519 15,938 household appliances −21,389 3,132 −3,440 671 24,723 other power equipment 330,425 −118,941 63,097 536,791 169,247 professional machinery −779,495 −389,612 222,046 145,935 553,086 transportation related −13,971 194,834 −59,517 −57,109 404,286 total −1,142,499 −396,940 243,320 628,889 1,357,805 unit: tons yang, et al.: decomposition of growth factors in high-tech industries and co2 emissions: after the world financial crisis in 2008 international journal of energy economics and policy | vol 10 • issue 4 • 2020506 linkage via air visibility. economics letters, 128, 72-74. managi, k., kumar, s. (2009), energy price-induced and exogenous technological change: assessing the economic and environmental outcomes. resource and energy economics, 31(4), 334-353. njoke, m.l., wu, z., tamba, j.g. (2019), empirical analysis of electricity consumption, co2 emissions and economic growth: evidence from cameroon. international journal of energy economics and policy, 9(5), 63-73. ozturk, i. (2010), a literature survey on energy-growth nexus. energy policy, 38(1), 340-349. ozturk, i., acaravci, a. (2011), electricity consumption and real gdp causality nexus: evidence from ardl bounds testing approach for 11 mena countries. applied energy, 88, 2885-2892. payne, j.e. (2010a), survey of the international evidence on the causal relationship between energy consumption and growth. journal of economic studies, 37, 53-95. payne, j.e. (2010b), a survey of the electricity consumption-growth literature. applied energy, 87, 723-731. presno, m.j., landajo, m., gonzález, p.f. (2018), stochastic convergence in per capita co2 emissions. an approach from nonlinear stationarity analysis. energy economics, 70, 563-581. saboori, b., sulaiman, j., mohd, s. (2012), economic growth and co2 emissions in malaysia: a cointegration analysis of the environmental kuznets curve. energy policy, 51, 184-191. sunde, t. (2020), energy consumption and economic growth modelling in sadc countries: an application of the var granger causality analysis. international journal of energy technology and policy, 16(1), 41-56. yavuz, n.c., yilanci, v. (2013), convergence in per capita carbon dioxide emissions among g7 countries: a tar panel unit root approach. environmental and resource economics, 54(2), 283-291. you, w., lv, z. (2018), spillover effects of economic globalization on co2 emissions: a spatial panel approach. energy economics, 73, 248-257. . international journal of energy economics and policy | vol 9 • issue 2 • 2019 299 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(2), 299-306. the mediating effect of environmental management accounting on green innovation firm value relationship dian agustia*, tjiptohadi sawarjuwono, wiwiek dianawati faculty of economic and busines, universitas airlangga, indonesia. *email: dian.agustia@feb.unair.ac.id received: 06 december 2018 accepted: 09 febrary 2019 doi: https://doi.org/10.32479/ijeep.7438 abstract this study was conducted to determine the effect of green innovation (gi) on firm value (fv) with environmental management accounting (ema) as an intervening variable. companies that are able to create gi will not only get the economic benefits but also the competitive advantage, therefore it will increase the value of the firm. the application of gi will be able to improve the application of ema, thereby reducing the impact of environmental damage due to the company’s business processes. with manufacturing and the main sector’s companies listed on the bei 2012-2015 as the population, using purposive sampling, this study has obtained 277 companies as a sample. the result shows that gi has an effect on ema, while ema has proven to affect fv, and gi has an influence on fv. keywords: green innovation, environmental management accounting, firm value jel classification: q56 1. research background the growth of an advanced industry is proportional to the rise of pollution generated from the industrial production process such as production waste that can increase air and water pollution at dangerous levels. according to data owned by director of the earth institute of columbia university (sahcs, 2013), global climate change is influenced by environment unawareness of industrial activity. to overcome this, the indonesian government tighten regulations related to the environment. some of the latest regulations such as the environmental law no.46 of 2017 on environmental economy instruments, government regulations on the environment, presidential decrees, to the regulation of the minister of environment have been issued. moreover, the government, in this case the environmental minister also tried to encourage people to be more environmentally conscious by applying the relevant regulations called “ecolabel” in the minister of environment no. 02 of 2014. the ecolabel is expected to encourage consumer awareness level of concern so that the decision making in the election product type is not only determined by price and quality factor, but also based on other factor which is environmental impact. although the inclusion of ecolabel is still voluntary, it makes people’s demands on the company are increasing. therefore, in its development, the company’s environmental performance becomes the most important valuation factor for investors before buying shares in a company (christoffersen et al., 2013). pressure from governments, communities, and investors, as well as high business competition has prompted the company to conduct a new resource for the production process. companies which are able to create new ways in the process of production, distribution, or can create a new product will be the winner in business competition (dereli, 2015). green innovation (gi) is one of the environmental strategies that can be done to develop the business without violating the government regulations (özşahin et al., 2013). this journal is licensed under a creative commons attribution 4.0 international license agustia: the mediating effect of environmental management accounting on green innovation firm value relationship international journal of energy economics and policy | vol 9 • issue 2 • 2019300 gi is a new technology (hardware or software) related to products or production processes that will drive energy efficiency, pollution reduction, waste recycling, green product design and corporate environmental management (chen, 1994 dalam ar, 2012). gi strategy will encourage companies to have special capabilities that will ultimately become a source of important competitive advantage for the company (sharma and vredenburg, 1998; ferreira et al., 2010). this competitive advantage will increase the value of the company in the future (bech, 2013). this is supported by previous research that has proved that innovation has a positive effect on firm value (fv), the existence of new innovation is closely related to the increase in profit without increasing the risk of the company. (salehi and arbatani, 2013; sorescu and spanjol, 2008). however, the creation of eco-friendly product innovation is not an easy task, it will cost a lot to make it happen, for example the cost of research and development (r and d), the cost of obtaining materials, the cost of worker safety, the cost of product safety certification for the people who consume it, depreciation costs of related equipment, and management costs which often called as hidden costs (cahyandito, 2006). companies need accurate, detailed, and relevant information regarding visible costs and unseen costs, in addition to the necessary limitations on the use of existing resources so that environmental sustainability will be maintained. that’s why companies need to adopt environmental accounting. environmental management accounting (ema) is a tool for achieving strategic positions by enhancing the competitiveness of enterprises. ema can provide an overview for companies to minimize costs and improve performance (cahyandito, 2006). implementation of ema will be able to bridge between environmental interests and economic interests, so that they can work together to improve company performance and environmental performance. larojan et al. (2014) proved that environmental accounting implementation has positive influence on fv. moreover, a burgeoning amount of operational management research has shown that implementing environmental management activities may result in improved firm performance (klassen and mclaughlin, 1996; melnyk et al., 2003; montabon et al., 2007 in hofer et al., 2012). klassen and mclaughlin (1996) found that environmental management announcements are positively correlated with a firm’s market valuation. similarly, montabon et al. (2007) concluded that environmental management activities are related with product innovation, process innovation, and sales growth. hence, there is evidence that the implementation of environmental management activities is associated with competitive advantage (hofer et al., 2012). however, as a growing area of research, ema has received relatively little attention from accounting researchers (ferreira et al., 2010). therefore, this study could fill in the research gap in the accounting literature by investigate the role of ema in mediating the impact of gi on fv. it is interesting to prove whether the fv will increase when company implemented ema in their gi practices. 2. literature review 2.1 gi gi or environmental innovation is a new or modified technique, practice, system, and production process to reduce the impact of environmental damage (rennings and rammer, 2003). gi is also defined as new technology (hardware or software) related to products or production processes that will lead to energy efficiency, pollution reduction, waste recycling, green product design and corporate environmental management (chen, 1994 in ar, 2012). the concept of gi is not really different from the concept of conventional innovation, which has the purpose of improving a product in order to increase productivity, cost efficiency, and also open new market opportunities. while gi not only aims to improve the company’s performance economically, but also to reduce the negative impact on the environment and create a competitive advantage for the company. another advantage of gi is to encourage companies to convert waste production into a viable product that can generate additional profits for the company. gi contributes to improving the company’s environmental performance through three ways (ramus, 2002 in küçükoğlu and pınar, 2015): 1. gi will reduce the environmental impact caused by the company’s activities by using reusable goods in the re-usage process and recycling the waste before disposing into the community. 2. gi is able to solve environmental problems by reducing the use of hazardous materials not only during the manufacturing process, but also in the final product content. by ensuring the quality of the products, company can give a positive impression to the public. 3. gi builds environmental friendliness and effective production processes by using raw materials and energy efficiently. with minimal use of raw materials and energy, the company will be able to maintain environmental sustainability for future generations. 2.2 ema ema is part of the environmental accounting. ema is not just about setting up accounting for environmental costs alone, but accounting for all costs and benefits arising from changes in operational processes that will ultimately change the impact on the environment (boyd, 1998). ifac (2005) stated that the management of environmental and economic performance through the development and implementation of appropriate environment-related accounting systems and practices. while this may include reporting and auditing in some companies, ema typically involves life-cycle costing, full-cost accounting, benefits assessment, and strategic planning for environmental management. ema incorporates environmental cost elements into conventional reports, as well as making it the basis for business processes and emphasizing the efficiency and effectiveness of resource usage. agustia: the mediating effect of environmental management accounting on green innovation firm value relationship international journal of energy economics and policy | vol 9 • issue 2 • 2019 301 there are several reasons that require companies to implement the ema (ifac, 2005): 1. supplier chain pressure, as a large company, manager must ensure that their suppliers meet the established environmental management system standards. 2. pressure from stakeholders requesting the company to publish its environmental performance into the annual financial report or issue a stand-alone environmental performance report in accordance with the global reporting initiative (gri). 3. the existences of financial pressure from investors who start invest funds for the growth of the social environment. 4. pressure from the government to maintain the existing environment. ema itself has two functions: a. internal function: serves as a decision-making tool. with ema, managers can manage and analyze the costs of environmental conservation in order to obtain the expected benefits and carry out environmental conservation activities effectively and efficiently. b. external functions: serves to influence stakeholders in making decisions. it categorizes information into two types: physical and monetary information. the physical information provides information on the flow of energy, raw materials, water and waste. while the monetary information provides information about environmental costs, future litigation costs, income, and the value that can be stored from the environment. 2.3. fv the company is a legal entity consisting of one or more individuals and separated from its owner (ross et al., 2008. p. 6). the main purpose of the company is to maximize the company value for its shareholders or owners (ross et al., 2008. p. 9). the value of the company is the investor’s perception of the company’s success rate (hermuningsih, 2013). for companies that have gone public, the value of the company can be reflected through the company’s stock price, while for the company that has not gone public, its value is reflected through the realizable value of the company’s assets at the time the company will be sold (margaretha, 2005. p. 1). high company value will make the market believe not only in the company’s current performance but also on the future prospects of the company. 3. hypotheses development 3.1. the effect of gi on ema gi through green product and green process aims to enhance productivity, cost efficiency, and open new market opportunities. in addition, it also to reduce the negative impact on the environment and turn waste into a product worth selling in order to provide benefits for the company. however, the creation of eco-friendly product innovation is not an easy task, it will cost a lot to make it happen (cahyandito, 2006). companies need accurate, detailed, and relevant information regarding visible costs and unseen costs, in addition to the necessary limitations on the use of existing resources so that environmental sustainability will be maintained. that’s why companies need to adopt environmental accounting. when companies must take a financial decisions making related to the environment, the conventional report does not specify the cost of any related environmental management, it just categorized into the overhead cost. ema can be a solution to this by presenting a traceable environmental cost so that it can be used in making the right decisions. therefore, this study proposes that, h1: gi has an influence on ema 3.2. the effect of ema on fv ema is a tool for achieving strategic positions by enhancing the competitiveness of enterprises. ema can provide an overview for companies to minimize costs and improve performance (cahyandito, 2006). implementation of ema will be able to bridge between environmental interests and economic interests, so that they can work together to improve company performance and environmental performance. ema incorporates environmental cost elements into conventional reports, as well as making it the basis for business processes and emphasizing the efficiency and effectiveness of resource usage. companies that implement ema tend to have a better future than those who do not (ikhsan, 2009). this concludes that stakeholders not only judge the company from the level of profit but also from good environmental performance, since it can be assured that the company can survive or improve the achievements obtained in the long run. larojan et al. (2014) proved that environmental accounting implementation has positive influence on fv. moreover, a burgeoning amount of operational management research has shown that implementing environmental management activities may result in improved firm performance (klassen and mclaughlin, 1996; melnyk et al., 2003; montabon et al., 2007 in hofer et al., 2012). therefore, this study proposes that, h2: ema has an influence on fv. 3.3. the effect of gi on fv the main purpose of the company is not only to create the value of stockholder, but to create value for all stakeholders. high fv will attract investors to invest in the company. but in the process of realizing its goals, companies often experience conflict in aligning economic goals and environmental goals. value creation for all stakeholders requires managers to improve their performance in financial performance, social performance and environmental performance and ensure that the company remains sustainable in the future. in accordance with the theory of legitimacy (o’donovan, 2002), the company can continue to survive (sustainable) if the company is able to adjust business processes with rules or norms applicable in the community high productivity level and the regular innovation surely can help company to achieve and retain company value. not only economic and social performance, environmental performance becomes an agustia: the mediating effect of environmental management accounting on green innovation firm value relationship international journal of energy economics and policy | vol 9 • issue 2 • 2019302 aspect that is considered by stakeholders. green inovation is one of the key for the company to get its goals, especially for companies in a high level of competition and unstable environment. gi can be a competitive advantage for the company if it is done regularly and applied to the whole business process. innovation creates value for both new and established companies (rosenbusch et al., 2013). gi improves firm performance through increased market share or through operational cost suppression (özşahin et al., 2013). gi improves company performance through efficient use of raw materials and energy, creation of new market share and competitive advantage products (ar, 2012). in addition, gi can also be used as a unique tool for marketing activities to increase market share continuously (küçükoğlu and pınar, 2015). hence, this study proposes that, h3: gi has positive influence on fv. 3.4. the mediating effect of ema on gi fv relationship the purpose of the company today is not to seek profit as much as possible, but to ensure the sustainability of the company in the future. supports from all stakeholders, both internal and external stakeholders surely are needed. this is consistent with stakeholder theory that the existence of a company is influenced and influences certain groups. to be able to get the support, the company must be able to satisfy all stakeholders. companies need a strategy that maximizes the profitability of the company, does not violate the prevailing rules, nor does it adversely affect the community and the environment. gi is one strategy to achieve the company’s goals. but to apply it required a stage of research and development. in this stage, the company invested capital, resources, and time to the maximum in order to get the best results. it takes good management to plan, organize and set up so that the r and d process is capable of producing quality innovations. this management includes r and d cost management, resource and energy usage management, and process management that is not environmentally damaging. ema in a company is a sign that the company has been aware of the importance of environmental aspects for the company. the implementation of environmenatal management accounting not only influences and encourages gi but also creates competitiveadvantage for the company (ar, 2012). ema is able to coordinate the problems caused by the gi process, such as the problem of environmental exploitation, energy limitations, and cost issues. with good coordination, the company will be able to get the economic benefits from the gi that has been done (salvadó et al., 2015). hence, this study proposes that, h4: ema has mediating effect on gi – fv relationship. 4. research methodology 4.1. research designs this study use 277 companies listed in indonesia stock exchange and followed proper programme in the year 2012-2015 as a sample. moreover, this study also used path analysis as the hypotheses testing. ghozali (2013. p. 249) suggests path analysis is an extension of multiple linear regression analysis, or path analysis is the use of regression analysis analysis to estimate causal relationships among predefined causal variables based on theory. ghozali (2013. p. 251) states that a direct relationship occurs if one variable affects other variables without any third variable that mediates the relationship between the two variables. the indirect relationship is if there is a third variable mediating the relationship between these two variables. the path coefficient is calculated by making two structural equations i.e., the regression equation showing the hypothesized relationship. in this case there are two similarities: ema=ɑ+β1gi+e (1) fv=ɑ+β2gi+β3ema+e (2) total effect from gi to fv equals with direct effect gi on fv plus the indirect effect which is path coefficient from gi on ema, which is β1 multiplied by path coefficient from ema on fv (β3). direct effect gi on fv=β2 indirect effect gi on fv=β1 × β3 total effect gi on fv=β2 + (β1 × β3) gi=green innovation ema=environmental management accounting fv=firm value ɑ=constanta e=residual 4.2. operational definitions of variables 4.2.1. gi gi is a new or modified technique and production process to reduce the impact of environmental damage, that will lead to energy efficiency, pollution reduction, waste recycling and green product design. gi (x) obtained through content analysis in company annual report. several indicators will be used to determine whether the company has applied gi. this indicator is derived from ar (2012). the results of this content analysis will be quantified in terms of ratios. the indicators to be used in content analysis are as follows: (1). the production process uses new technologies to reduce energy, water, and waste, (2). the product uses less non-polluting or hazardous substances (environmentally friendly materials), (3). using an eco-friendly product package (e.g., paper and plastic), and (4). components or materials in the production process can be recycled or reconditioned. 4.2.2. fv fv is the perception of stakeholders, especially investors on the firm’s accomplishment rate associated with stock market prices and measured by percentage. fv in this research is measured by using tobins’q ratio. tobin’s q ratio is calculated by the following formula (chang and wang, 2007): agustia: the mediating effect of environmental management accounting on green innovation firm value relationship international journal of energy economics and policy | vol 9 • issue 2 • 2019 303 q = os × p + d+1 ca ta ( ) ( ) ( ) os=outstanding share p=stock price d=total debt i=inventory ca=current asset ta=total asset 4.2.3. ema ema variable in this study is measured by using the level of ecoefficiency in the company. eco-efficiency is calculated by using the formula (schaltegger et al., 2008): eco-efficiency = value of product environmental influence 5. results and discussions 5.1. results 5.1.1. model 1 model 1 of this research was using simple linear regression to test the effect of independent variable of gi to ema dependent variable showed in tables 1 and 2. based on the result of t-test, it is known that t value for gi variable to ema of 3.564 with a significance value of 0.000. the value is <0.05 so it can be concluded that the gi significantly influence the ema on the sample company. hence, hypothesis 1 is accepted. 5.1.2. model 2 multiple linear regression analysis of model 2 was conducted to examine the effect of independent variables of gi and ema on dependent variable of fv. the result is show on the table 3. based on t-test result, it is known that t-value for ema variable on fv of 8.50 with a significance value of 0.00. the value is <0.05 so it can be concluded that the ema has a significant effect on fv in the sample company. hence, hypothesis 2 is accepted. moreover, t-value for gi variable on fv is 2.381 with significance value 0.019. the value is <0.05 so it can be concluded that gi has significant effect on fv. hence, hypothesis 3 is accepted. 5.1.3. mediating effect the path analysis test results in figure 1 state that there is no indirect effect between capital structure on company performance. that is, innovation cannot mediate the relationship between the independent variables, namely the capital structure of the dependent variable of company performance. based on the results of h2 testing (sig=0.008, beta=−0.009) and h3 (sig=0.025, beta=0.356), there is a difference in the direction of the regression results. the presence of different directions shows that innovation cannot mediate the influence of capital structure and company performance. the influence of innovation as a mediating variable can also be tested using the sobel test via the sobel test calculator available at www.quantpsy.org. the sobel test calculation is presented in table 4. 5.2. discussions 5.2.1. the effect of gi on ema based on the statistical result, the significance value equals to 0.00 means that gi has an effect on ema. gi through green product and green process aims to increase productivity, cost efficiency, open new market opportunities. moreover, it can also reduce the negative impact on the environment and turn waste into a product worth selling in order to provide benefits for the company. when companies must take a financial decisions making related to the environment, the conventional report does not specify the cost of any related environmental management, it just categorized into the overhead cost. environmental innovation costs associated with gi consist of waste management costs, research costs for technologies that support green processes, material costs purchased, technological depreciation, and management costs which in the financial statements can not be traced to the special costs for the environment because they are categorized together with other costs as an overhead cost. ema can be a solution to this because ema focuses on the calculation of environmental costs, the flow of energy and materials and its changes, can be used in decision making and so will be very useful for companies that pro-actively run gi. 5.2.2. the effect of ema on fv based on the statistical result, the significance value equals to 0.00 means that ema has significant effect on fv. ema in this research is measured using eco-efficiency. this is consistent with eco-eficiency theory which argues that firms can achieve high levels of corporate performance through the efficiense of environmental resources by reducing the toxic waste generated from existing production processes (porter and van der linde 1995a, 1995b in burnett et al., 2011). porter (1991) in burnett et al. (2011) confirmed that through eco-eficiency, companies are able to achieve competitive advantage. it can be concluded table 1: simple linear regression result model b unstandardized coefficients standardized coefficients t significance standard error beta 1 (constant) 0.749 0.170 4.410 0.000 gi 0.312 0.088 0.210 3.564 0.000 r2 0.044 gi: green innovation agustia: the mediating effect of environmental management accounting on green innovation firm value relationship international journal of energy economics and policy | vol 9 • issue 2 • 2019304 that competitive advantage is created by possessing the unique resources and capabilities to efficiently exert existing resources so that firms in industrial competition can be superior to others in terms of increasing levels of competitiveness and in enhancing corporate value. enviromental management accounting facilitates investors in assessing the level of sustainable development of the company. strategy based on environmental friendly effort, is no longer a category of strategy that is only used to fulfill corporate social responsibility because it is related to the existence and strategic position of the company. it is certain that any company implementing enviromental management accounting in any program will have advantages over non-implementing companies (azizah et al., 2013). the company experienced an increase in profit and production due to the quality of production and the maximum environmental quality (enviromental management accounting). one of the reasons companies should implement ema is the pressure from stakeholders to enable companies to publish environmental performance into annual financial statements or issue stand-alone environmental performance reports in accordance with gri standards (ifac, 2005). it can be concluded that companies that implement ema will have a higher value in the investors and stakeholders’ point of view than those who do not. companies that implement enviromental management accounting tend to have a better future than those who do not. in line with the research of burnett et al. (2011) that the implementation of eco-effective management will increase the value of the company. other research supporting this outcome is the study of larojan et al. (2014) who disclose that environmental costs are no longer a minority commonly combined with other costs, the use of ema can save expenses and improve corporate control. this concludes that stakeholders not only judge the company from the level of profit but also from good environmental performance as well as it can be assured that the company can survive or improve the achievements obtained in the long run. 5.2.3. the effect of gi on fv based on the statistical result, the significance value equals to 0.019 means that h3 stated that gi has significant effect on fv is accepted. this is in line with the stakeholder theory proposed by freeman (2010) that the company’s goal is not only to create value for its stockholder, but to create value for all its stakeholders. value creation for all stakeholders requires managers to improve their performance in financial performance, social performance, and environmental performance, and ensure that the company remains sustainable in the future. companies can continue to survive (sustainable) if the company is able to adjust business processes with rules or norms applicable in the community (o’donovan, 2002). this also corresponds to the theory of competitive advantage proposed by porter (1985. p. 1) that figure 1: path analysis table 3: multiple regression analysis result model unstandardized coefficients standardized coefficients t significance collinearity statistics b standard error beta tolerance vif 1 (constant) 0.619 0.050 12.421 0.000 gi 0.060 0.025 0.141 2.361 0.019 0.939 1.064 ema 0.138 0.016 0.508 8.507 0.000 0.939 1.064 r2 0.313 a. dependent variable: tobins tabel 2: t‑test value result hypothesis significance result hypothesis 1 0.000 significant influence hypothesis 2 0.000 significant influence hypothesis 3 0.019 significant influence agustia: the mediating effect of environmental management accounting on green innovation firm value relationship international journal of energy economics and policy | vol 9 • issue 2 • 2019 305 competitive advantage aims to form a sustainable and advantage position in order to survive in industrial competition. strategy is a very important tool for achieving competitive advantage. one strategy that can be used to achieve company goals is to implement gi. according to renning and rammer (2009), gi is divided into two types namely, green product and green process. green product is a durable, non-toxic product made from recyclable or packed in minimalist packaging (durif et al., 2010). while the green process, is the use of technology, machinery, and software that is new or has been modified in the production process and distribution companies to reduce the adverse impact on the environment. gi encourages companies to convert waste production into a viable product that increases the company value. in addition, gi is able to produce products that are superior to conventional products. gi has positive impacts. for the environment, gi can reduce co2, increase biodiversity, and reduce pollution. for the company, gi is able to increase productivity, expand market share, create image of environmental awareness, and improve efficiency. low production cost and high competitive advantage will lead the company to gain high profitability. the number of positive impacts in the implementation of gi will attract investors. in addition to high profitability, the environmental aspects applied to the company’s business strategy will make the investor believe that the company will remain and continue into the future. the better the environmental performance of a company, the higher the investor interest in the company, hence the higher the value of the company. based on previous studies, the results of this study support the results of research conducted by salvadó et al. (2015), which concludes that gi positively affects the market value of the company. gi increases the market value through the efficiency of the production process. küçükoğlu and pınar (2015) and ar (2012) concluded that by doing gi the company will be able to improve the company performance and competitiveness ability (competitive advantage). gi not only reduces the adverse environmental impact but brings the company to a superior position than its competitors through the creation of environmentally friendly products. the results of this study also support the results of research conducted by rosenbusch et al. (2013) which concluded that innovation can create value for the company, both new and old. innovation requires high initial investment and is a high risk activity. there is no guarantee of certainty over the results obtained. however, the many benefits of innovation such as product differentiation that will create competitive advantage for the company, high customer loyalty, and sales at a premium price for innovative products are worth much more than the cost incurred. however, this study does not support research conducted by özşahin et al. (2013) which concludes that green product innovation has no effect on company performance. this is due to the company’s low ability to innovate. the low ability to innovate will undermine the company’s competitiveness. companies that have low competitiveness will not be able to compete with their competitors, the company’s performance results will decrease, the company can not create value for its stakeholders and eventually the company will be vanished. 5.2.4. the mediating effect of ema eventhough gi is one strategy to achieve the company’s goals. but to apply it required a stage of research and development. in this stage, the company invested capital, resources, and time to the maximum in order to get the best results. it takes good management to plan, organize and set up so that the r and d process is capable of producing quality innovations. this management includes r and d cost management, resource and energy usage management, and process management that is not environmentally damaging. ema in a company is a sign that the company has been aware of the importance of environmental aspects for the company. the implementation of environmenatal management accounting not only influences and encourages gi but also creates competitive advantage for the company (ar, 2012). ema is able to coordinate the problems caused by the gi process, such as the problem of environmental exploitation, energy limitations, and cost issues. with good coordination, the company will be able to get the economic benefits from the gi that has been done (salvadó et al., 2015). 6. conclusions based on the results of the research discussed in the previous chapter, it can be concluded as follows: a) green innvoation has an effect on ema. this is because ema focuses on the calculation of environmental costs, the flow of energy and materials and its changes, therefore ema can be used in decision making and will be very useful for companies that pro-actively run gi. the environmental management referred to in this study is gi. b) ema has a significant effect on fv. this is consistent with eco-eficiency theory which argues that firms can achieve high levels of corporate performance through the efficient use of environmental resources by reducing the toxic waste generated from existing production processes (porter, 1991; porter and van der linde, 1995a, 1995b in burnett et al., 2011). c) gi has a significant effect on fv. in accordance with the stakeholder theory proposed by freeman (2010) that the company’s goal is not only to create value for its stockholder, but to create value for all its stakeholders. the results of this study are in accordance with research conducted by salvadó, et al. (2015), which concludes that gi positively affects the market value of the company. gi increases the market value through the efficiency of the production process. küçükoğlu and pınar (2015) and ar (2012) which concluded that by doing gi the company will be able to improve company performance and competitiveness ability (competitive advantage). good table 4: the mediating result input test statistisc standarderrror p-value a −0.009 −1.80893053 0.00177121 0.0704618 b 0.356 sa 0.003 sb 0.157 agustia: the mediating effect of environmental management accounting on green innovation firm value relationship international journal of energy economics and policy | vol 9 • issue 2 • 2019306 environmental performance, high efficiency, and competitive advantage will attract investors to invest. investor interest in the company will increases the value of the company. references ar, i.m. (2012), the impact of green product innovation on firm performance and competitive capability: the moderating role of managerial environmental concern. procedia-social and behavioral sciences, 62, 854-864. azizah, n.m., dzulkirom, a.r., dan maria, g.w.e. (2013), analisis penerapan environmental management accounting sebagai bentuk eco-efficiency dalam meningkatkan keunggulan kompetitif perusahaan. skripsi. malang: fakultas ilmu administrasi universitas brawijaya. bech. (2013), quadruple bottom line for sustainable prosperity. available from: http://www.cambridgeleadershipdevelopment.com/ quadruple-bottom-line-for-sustainable-prosperity. [last retrieved on 2016 feb 17]. boyd, j. (1998), the benefits of improved environmental accounting: an economic framework to identify priorities. discussion paper 98-49. burnett, r.d., skousen, c.j., wright, c.j. (2011), eco-effective management: an empirical link between firm value and corporate sustainability. accounting and the public interest, 11(1), 1-15. chang, s.c., wang, c.f. (2007), the effect of product diversification strategies on the relationship between international diversification and firm performance. journal of world business, 42(1), 61-79. cahyandito, f.m. (2006), environmental management accounting. bangkok, thailand: in went (capacity building international). chen, j.y. (1994), the economic impacts of green product. massachusetts: civil engineering, massachusetts institute of technology. christoffersen, s., frampton, g.c., granitz, e. (2013), environmental sustainability’s impact on earnings. journal of business and economics research, 11(7), 325-335. dereli, d.d. (2015), innovation management in global competition and competitive advantage. procedia-social and behavioral sciences, 195, 1365-1370. durif, f., boivin, c., julien, c. (2010), in search of a green product definition. journal of interactive, 6(1), 25-33. ferreira, a., carly, m. (2009), environmental management accounting and innovation: an exploratory analysis. melbourne, australia: department of accounting and finance, monash university. freeman, r.e. (2010), strategic management. 2nd ed. new york: cambridge university press. ghozali, i. (2013), aplikasi analisis multivariate dengan program ibm spss 21. edisi ketujuh. semarang: badan penerbit universitas diponegoro. hofer, c., cantor, d.e., dai, j. (2012), the competitive determinants of a firm’s environmental management activities: evidence from us manufacturing industries. journal of operations management, 30(1-2), 69-84. hermuningsih, s. (2013), pengaruh profitabilitas, growth opportunity, sruktur modal terhadap nilai perusahaan pada perusahaan publik di indonesia. buletin ekonomi moneter dan perbankan, 16, 127-148. ifac. (2005), environmental management accounting. london: association of chartered accountants. ikhsan, a. (2009), akuntansi manajemen lingkungan (pertama). jogjakarta: graha ilmu. küçükoğlu, m.t., pınar, r.i̇. (2015), positive influences of green innovation on company performance. procedia-social and behavioral sciences, 195, 1232-1237. larojan, c., thevaruban, j.s., larojan, c., thevaruban, j.s. (2014), impact of environmental management accounting practices on financial performance of listed manufacturing companies in sri lanka. proceedings of the 3rd international conference on management and economics. p239-246. margaretha, f. (2005), teori dan aplikasi manajemen keuangan investasi dan sumber dana jangka pendek. harga: grasindo. melnyk, s.a., sroufe, r.p., calantone, r. (2003), assessing the impact of environmental management systems on corporate and environmental performance. journal of operations management, 21(3), 329-351. o’donovan, g. (2002), environmental disclosures in the annual report: extending the applicability and predictive power of legitimacy theory. accounting, auditing and accountability journal, 15(3), 344-371. özşahin, d.m., sezen, b., çankaya, s.y. (2013), effects of green manufacturing and eco-innovation on sustainability performance. procedia-social and behavioral sciences, 99, 154-163. porter, m.e. (1991), america’s green strategy. scientific american, 264(4), 1-68. rennings, k., rammer, c. (2009), increasing energy and resource efficiency through innovation-an explorative analysis using innovation survey data. ssrn electronic journal, 59(5), 442-459. ross, s.a., westerfield, r.w., jordan, b.d. (2008), corporate finance fundamentals. new york: mcgraw-hill education. rosenbusch, n., rauch, a., bausch, a. (2013), the mediating role of entrepreneurial orientation in the task environment–performance relationship: a meta-analysis. journal of management, 39(3), 633659. sachs, j. (2008), the end of poverty: economic possibilities for our time. european journal of dental education, 12, 17-21. salehi, a., arbatani, t.r. (2013), is innovation always beneficial? a meta-analysis of the relationship between branding and performance in smes. advances in environmental biology, 7(14), 4682-4688. salvadó, j.a., de castro, g.m., lópez, j.e.n. (2015), the importance of the complementarity between environmental management systems and environmental innovation capabilities: a firm level approach to environmental and business performance benefits. technological forecasting and social change, 96, 288-297. schaltegger, s., martin, b., burritt, r.l., jasch, c. (2008), environmental management accounting for cleaner production. dordrecht: springer. sharma, s., durand, r.m., gur-arie, o. (1981), identification and analysis of moderator variables. journal of marketing research, 18(3), 291-300. sharma, s., vredenburg, h. (1998), proactive corporate environmental strategy and the development of competitively valuable organisational capabilities. strategic management journal, 19(8), 729-753. sorescu, a., spanjol, j. (2008), innovation’s effect on firm value and risk: insights from consumer packaged goods. journal of marketing, 72, 114-132. . international journal of energy economics and policy | vol 10 • issue 1 • 2020 471 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(1), 471-480. crude oil option market parameters and their impact on the cost of hedging by long strap strategy bartosz łamasz*, natalia iwaszczuk agh university of science and technology, poland. *email: blamasz@zarz.agh.edu.pl received: 22 august 2019 accepted: 02 november 2019 doi: https://doi.org/10.32479/ijeep.8613 abstract this study aims to examine the impact of selected market parameters of the european crude oil options on the hedging costs and break-even points (beps) in the long strap strategy. the paper analyses the impact of the following market parameters: volatility and the future price of crude oil, the strike price and time to expiration. the theoretical aspect consisted in using the black model to calculate the value of the option price and the long strap strategy bep in the condition of ever-changing market parameters. these calculations, by determining implied volatilities of the options, have been adapted to the actual data from the exchange market for the options on wti futures contract. it was made possible owing to the quik strike platform made available by a cme group exchange. to obtain information about the impact of volatility, time and price of futures on the costs of hedging and beps in the long strap strategy, the authors calculated the greeks (delta, gamma, vega and theta) for the crude oil options. having done that, not only could they determine the direction but also the power of impact that the parameters had on the final results in the long strap strategy. keywords: commodity options, crude oil price risk, long strap option strategy jel classifications: g13, g32 1. introduction in the era of progressive globalisation, which, among others, results in faster information exchange, market risk, understood as price risk, plays an increasingly important role. the news of economic events is reflected in price fluctuations of financial and non-financial assets. such an issue can be particularly seen in the commodity market and it has significant consequences for both producers and consumers. crude oil undoubtedly belongs to the group of raw materials that are of great importance for the global economy, as it is a raw material which has been an essential energy source in the world for many years. currently, about 1/3 of primary energy is produced due to the process of oil crude refining. however, there are two basic restrictions regarding the increase in world oil consumption. first of all, it is non-renewable energy source, which means that its resources will run out in the future. secondly, oil deposits are unevenly distributed around the world and their largest proven reserves are situated in such countries as: saudi arabia, iran, iraq, kuwait, united arab emirates, libya, venezuela and russia. some of these countries cannot be classified as economically and politically stable. moreover, the small number of oil suppliers (especially in the future) is the reason to consider this market oligopolistic. accordingly, there is high probability of disturbing the supply of this raw material, which is frequently reflected in significant price fluctuations. price fluctuations are particularly important for oil producers, as they largely determine the state of the economy of these countries. a prominent example of a country that is dependent on oil crude market is russia, where export of this raw material and its products constitutes more than a half of russia’s total export (in 2017 it was 60% of total export). hence, it is claimed that in the long term, fluctuations in world oil prices may have a destructive effect on the stability of the oil industry this journal is licensed under a creative commons attribution 4.0 international license łamasz and iwaszczuk: crude oil option market parameters and their impact on the cost of hedging by long strap strategy international journal of energy economics and policy | vol 10 • issue 1 • 2020472 in this country. chikunov et al. (2019) emphasise that there is a strong need to develop scientific approaches which may lead to the evaluation and diagnosis of financial risk in russian oil sector. on the other hand, arour et al. (2011) and khamis et al. (2018) revealed that there is a significant impact of oil price fluctuations on the stock market at gulf cooperation council countries (qatar, kuwait, oman, ksa, bahrain, uae). tabash and khan (2018) showed a strong interdependence between crude oil price volatility and the gross domestic product of uea and saudi arabia. the impact of oil prices on the economy of saudi arabia was also studied by foudeh (2017). also, oil prices fluctuations significantly influence the economic situation of countries that import large quantities of this raw material. these mostly include developing asian countries, such as china and india. the consequences of oil price fluctuations can be noticed in some of the industries of the above-mentioned countries, as they determine the costs of production. for instance, this appears in the aviation sector. kathiravan et al. (2019) showed that crude oil price fluctuations (wti, brent, dubai) between 2007 and 2018 had a significant impact on return rates on shares of companies involved in the aviation sector in india. additionally, changes in crude oil price affect the economic activity of both, developing and developed countries (cunado and perez de garcia, 2005; hamilton, 2003; edelstein and kilian, 2009). crude oil prices also affect such aspects of the economy as: the market value of crude oil companies, the inflation rate in oil importing countries, as well as the price of alternative energy sources (an et al., 2019). following that, it is of crucial importance to search for the hedging methods that may help to avoid negative consequences of the changes of crude oil price on the economy of countries and individual enterprises, especially the refinery sector. this paper focuses on the commodity (crude oil) options as well as on an option strategy structured with the derivatives. the long strap strategy discussed in the paper, when appropriate used, offers the opportunity of hedging effectively against the risk of crude oil price fluctuation. one of the objectives of the paper is to present the method for structuring the above-mentioned strategy as well as show some patterns for calculating the final result of its application. in addition, for the effective application of the long strap strategy, it is essential to have the skills sufficient to set out successfully the strategy break-even and stop-loss points. these numbers are strongly correlated with the price of the commodity options, which is why more light should be shed on the option pricing model. to this end, the authors decided to use the black’s model. all the calculations made in the paper are referred to the commodity options in which the price of wti oil futures contracts (traded on the nymex) is the underlying instrument. to determine the implied volatility of options other than atm (at-the-money), the quikstrike platform available on the cme group website was also used for calculations. the calculated option premiums (option prices) were used to calculate the costs of hedging and break-even points (beps) in the long strap strategy and analyse their response to changing values of selected market parameter, which was the purpose of this paper. a more precise determination of the power of impact of these parameters was possible through meticulous calculation and analysis of four greeks: delta, gamma, vega and theta. they provided some information about the change in the cost of hedging in the long strap strategy when changing a selected market parameter by a unit. practical application of the greeks is manifested in supporting decisions of price risk managers. by calculating the greeks, they can adjust their option parameters and strategies to the expected directions of changes in the commodity prices. the remainder of the paper is organized as follows. section 2 provides a literature review, in section 3 the construction of long strap strategy is presented. section 4 discusses the used method and data of the study and final results is presented in sector 5. finally, section 6 concludes the research paper. 2. literature review options, as derivative instruments with non-symmetric risk distribution, may be used by market participants in many different ways. speculators trade options to profit from drops, rises or stagnation in prices of the underlying instrument. on the other side of the market there are hedgers, who consider options as tools to protect them against the risk of price fluctuation in financial assets (e.g., stock, bonds, currency exchange rates) or commodities (gold, oil, gas). however, each option market participant tends to focus on two key issues: the price of the base instrument on the last trading day (contract expiration day) and the option price. while the first one is unpredictable and may fluctuate freely in the future, the option price is already known on the date of taking a position in an option contract. this value is the key from the point of view of a success of followed option strategies created by short or long positions in different options. calculation of the value of an option (i.e. the option price or option’s premium) is the most complicated process, as one may see by comparing valuation methods applied for different types of derivatives. in a nutshell, a valuation of these derivatives is a search for answers to the question: how much should a buyer of an option pay for the option for the price to be fair1 for each party? the issue is rather complex as it requires setting the value of an option when bought (or sold). in turn, the value should counterbalance the payout to which the option buyer is entitled at a certain moment in the future i.e., on the last trading day. consequently, many scholars tried to find the most effective options pricing model (2-1) and understand the relationship between market parameters and option’s premium (2-2). 2.1. option pricing the first attempts at valuating options date to the turn of 19th and 20th century. they are deemed modelled after louis bachelier’s doctoral thesis of 1900. the thesis focused also on modelling stock prices and, according to bachelier, the prices were to move according to the arithmetic brownian motion. many years later, in 1960, several papers were published that pushed forward the search for option valuation models. they mostly applied to stock 1 “fair price” is a price which does not open the door to a potential arbitration on the market. łamasz and iwaszczuk: crude oil option market parameters and their impact on the cost of hedging by long strap strategy international journal of energy economics and policy | vol 10 • issue 1 • 2020 473 options. the most important papers devoted to the issue were written by j. boness and p. samuelson (smithson, 1998). however, the work by black and scholes published in 1973 is considered the breakthrough in the search for the model to estimate the option price. they presented a model valuating the european call option in which underlying asset was a dividend-free stock. the solution presented by black and scholes is based, as initially assumed, on the structure of a risk-free portfolio, using european options (black and scholes, 1973). the model has quickly gained popularity and the scientific circles made regular attempts at its improvement. in consequence, as early as 1973, merton, using black and scholes’s line of thinking as the basis, developed a model valuating the european call option in which the underlying asset was a stock with a fixed dividend payable before the expiry date of the option (merton, 1973). continued efforts to improve the option pricing model and expand it by adding more types of underlying assets have led to the discovery of a method for valuating of commodity derivatives. it happened as early as in 1976 and the discovery was made by black. also note that the solution presented by black applied not only to valuation of european commodity options but also to futures and forwards for commodities (black, 1976). apart from the european commodity options, valuation of american options remains important, as their holders have the right to exercise them on any day before their expiration days. similarly, to the european options, the options are traded on commodity exchanges for raw materials and energy such as nymex or ice and are the most popular among participants of the exchanges. the leading method used to valuate the american option is the analytical approximation method combining solutions proposed in numerical models (including black’s model) and analytical models (such as binominal model (cox, 1979)). many research papers describing different approaches to the valuation of the options have been written. one of the first was the solution proposed by barone-adasi and whaley (1987). in reference to whaley’s concepts (1986), they developed both the spot price model to valuate commodity options as well as options for commodity future contracts. in their study, they used black’s model for the european commodity option onto which the early exercise premium was added, arising from the optional early exercising the american option. structured as described above, the model was discussed in papers published in subsequent years and the subject was further expanded by bjerksund and stensland (1993, 2002) as well as other analysts. the literature offers examples of many other commodity option valuation models (both european and american), based on black’s concepts; however, they have been modified at a rather large scale. revisions and attempts at improving valuation of these options were made by schwartz (1997), shreve (2004) and clark (2011). however, until now, the solutions proposed by black come as the most popular valuation model for these options. 2.2. black’s model in commodity options and the greeks black’s solutions dating back to 1976 is a fairly easy method of valuating european commodity prices. the model is based on the assumption that the underlying instrument prices move as particles in the brownian movement, which is a particular case of a stochastic wiener process. in turn, calculation of the option premium concentrates on searching for a value balancing the payout for the option buyer on the contract expiry date. eventually, with the respective initial assumptions, prices of european commodity call and put options are expressed with the following formulas (clark, 2014; hull, 2012): v e f n d kn d 0 c r t 0 1 2 d = ( )− ( )  − (1) v e kn d f n d 0 p r t 2 0 1 d = −( )− −( )  − (2) where d = ln f k + 2 t t 1 0 2      σ σ (3) d = f k 2 t t 2 0 2 ln      − σ σ (4) and v 0 c – price of the commodity call option, v 0 p – price of the commodity put option, f0– the future price of the underlying instrument, k– strike price of the option, rd– continuously compounded riskless interest rate, t– time left until the option expiration, σ2– yearly variance rate of return for the underlying instrument, n– the standard normal cumulative distribution function. the impact of some of the option parameters is analysed by using the greeks. they provide information on how the option may change as a result of a changing a parameter by a unit. in this paper, four different greeks were used: delta, gamma, vega and theta. their mathematical interpretation and formulas which can be used to calculate the value based on black model, are presented in table 1. the first of the presented coefficients, the delta, shows the option price response to a change in the future price of the underlying instrument (a commodity) by a unit. delta is also identified with the proxy for the probability that an option will expire in the money (hull, 2012). in turn, by calculating the gamma, one can learn about the impact of the future price of the underlying asset on the change in the delta. mathematically, the delta is a partial second derivative of the option price against the price of the underlying asset. another greek, vega, is a partial first derivative of the option price calculated against price volatility of the underlying asset. its value indicates how and by how much the option price is going to change given a 1% p.p. increase (or a decrease) in volatility of the underlying assets for which the option was sold. theta offers some crucial information on the impact on the number of days to the last trading day on the option price. theta shows a potential change in the value of the option when reducing the time to the last trading day by a time unit. the structure of the black’s model łamasz and iwaszczuk: crude oil option market parameters and their impact on the cost of hedging by long strap strategy international journal of energy economics and policy | vol 10 • issue 1 • 2020474 would indicate a year as the unit but the typically considered unit is a day instead. such analysis provides therefore more precise information on the impact of theta on the option price (bittman, 2009; hull, 2012). works by taleb (1996), hull (2012) or węgrzyn (2013) offer some information on the greeks covered in this paper and the method for their shaping depending on the type of the analysed options. in this paper, the greeks have been used to analyse the power of the impact of some selected market parameters on the level of costs and beps in the long strap strategy. however, before they were determined, the method of structuring the strategy had been described briefly as well as equations helpful to determine the bep points in the strategy were presented in more detail. 3. long strap strategy – structure and bep points the long strap strategy is formed by a combination of long positions in call and put options for the same underlying asset and the same time to expiration. furthermore, the strike prices of these options are set at an identical level. it is also assumed that the number of positions taken in the call option is twice as high as the number of position in the put option. therefore, in order to calculate the final result achieved in the long strap strategy, it is necessary to set out the final results in long positions of both put and call options with the right parameters and, subsequently, placing them in a manner appropriate for the strategy. assuming that k is the strike price of an option, c is a unit option premium for the call option and p is a unit option premium for the put option and ft is the future price of a commodity on the expiration day, the profit function of long position in n call options (c(k)) is, ( ) ( ) t t t nc if f <k c k n f k c if f k − − ≥  =  − (5) and the profit function of long position in m put options (p(k)) is ( ) ( )t t t m k f p if f <k p k mp if f k  − = ≥ −  − (6) applying the symbols used in the equation (5) and (6) and taking into account the structuring of the long strap strategy (i.e. assuming that n=2m), its final result r(k) is described by the following equation: ( ) ( )t t t t m k f p 2c if f <k r k 1 2m f k c p if f k 2  − − −  =    − − −   ≥  (7) from the point of view of a successful application of each option strategy, the bep is a very important component. a bep is a price level of the underlying asset giving the final result equal to 0 in a strategy. therefore, the bep indicates the necessary change in the price to avoid losses on the strategy. in case of a two-sided hedges i.e. protecting both against price increases and price drops (with the long strap strategy as a good example of such hedging), there are two beps. the first one informs about the minimum price drop (against the expiration price). when reached, the bep will compensate for the losses resulting from paid option premiums. in the paper, it is recorded as bepd. the price of the underlying asset above which the long strap strategy (in case of an increase in prices) will be profitable is the second bep, recorded as bepu. their calculation method is closely related to the equation (7) and described as follows: bep k+ p 2 +c u = (8) bep k p 2c d = − − (9) since in the long strap strategy the number of positions occupied in the call option is twice as high as in the put option, the difference (k–bepd) will be always twice bigger than the (bepu–k) difference. accordingly, the strategy must be applied predominantly when expecting rises in the prices of the underlying asset. since the long strap strategy also uses a long position in the table 1: mathematical interpretation and equations for selected greeks the greeks the greeks as a derivative calculating the value of a coefficient based on black’s model delta δ = ∂ ∂ v f θ δ ω ω= e n( d ) r t 1 d− gamma γ δ = ∂ ∂f γ σ = − e n'(d ) f t r t 1 d vega v = ∂ ∂ v σ v e fn (d ) t r t 1 d = − ' theta θ = − ∂ ∂ v t θ ω ω ω σ = r e fn d r e kn( d ) e fn'(d ) 2 t d r t 1 d -r t 2 r t 1 d d d − − ( )−    − source: own study based on (węgrzyn, 2013), (alexander, 2008), (hull, 2012) v–unit price of an option; ω=1 for the call option ω= –1 for the put option; n’(x) – standard normal probability density function, calculated from 2x /2e n'(x) 2 t − = π ; other symbols and in the black’s model łamasz and iwaszczuk: crude oil option market parameters and their impact on the cost of hedging by long strap strategy international journal of energy economics and policy | vol 10 • issue 1 • 2020 475 put option, earnings are possible also in case of drops in the prices of the underlying assets. however, the price must fall below bepd. when analysing the equations (8) and (9), one may also notice that the bepd distance from the option price k is equal to the total cost (tc) of hedging which is equal to the sum of paid option premiums. in turn, the distance between bepd and the strike price k is twice shorter. in consequence, when tc stands for the tcs paid in the long strap strategy (tc = p + 2c), (8) and (9) equations may look as follows: bep =k+ tc 2 u (10) bep k tcd = − (11) and when subtracted, give the dependency: bep bep 3 2 tc u d − = (12) the equation (12) shows that the distance between the beps is strictly connected with the costs borne in the long strap strategy and is always 1.5 times higher. consequently, a change in the value of bepu and bepd will result from a change in prices of options (option premiums) used in the strategy. for this reason, further on, when analysing the impact of individual market parameters, the notion of the costs of the strategy and the distance between the beps will be substituted. 4. data and methodology as argued above, the beps in the long strap strategy (which also represent the tcs) are also dependent on the set strike price of an option. to analyse the dependence, the authors decided to analyse different situations, depending on the value of market parameters necessary to calculate prices of commodity options. market parameters of commodity options are based on the following initial assumptions: • a 2% annual risk-free interest rate • the future price of a commodity upon taking a position in the option contract for the commodity was 66 monetary units • volatility of the future price of the underlying asset (a commodity) expressed for the year, reached one of the three levels: 25%, 35% or 45% • the last trading day of an option is 30, 20 or 10 days • the strike price equal to 64, 65, 66 (atm options), 67 or 68 monetary units. the market parameters used in the equations have been selected carefully to offer the best reflection of the situation prevailing on the real market of wti oil future option prices. the annual volatility of the commodity price typically oscillates within a 0.2-0.5, which prompted the authors’ decision to use three different values from the range (0.25, 0.35 and 0.45) in the analyses. the future price of oil set at 66 usd/b is, in turn, a wti price of june 01, 2018 and refers to an option with the delivery date falling in july (its expiration date is june 15, 2018 and a potential sale of the commodity takes place in july). in addition, these analyses also took into account periods of 30, 20 and 10 days since the number of option transactions on nymex or ice is clearly the highest in the last month of the option activity. accordingly, it was concluded that such option (and, consequently, option strategies) were the most interesting from the point of view of an exchange trading participant. from the perspective of matching a theoretical valuation of options with their real (market) parameters, problematic is the relationship between volatility and the strike price. in the literature, it is referred to as the volatility smile. the name comes from the shape (curve) of the graph of the function where the strike price is an argument and values are equal to the volatility implied in the option. in this case, the graph of the function is a u-shaped parabole whose minimum is around the atm strike price. therefore, the occurrence of this phenomenon differentiates the level of volatility of the implied options for the same instrument, having the same strike prices. to determine volatility of the implied options issued for wti oil with their strike price different that the atm option strike price, the authors used quikstrike platform. the platform is available on the cme group website and offers many embedded tools which can be used also (apart from its capability to determine the above-mentioned volatility) to valuate the option by using different models (using the black models as well as other models, see: (cme group, 2018a, b)) or checking the effectiveness of a strategy by simulating the future prices of the underlying asset. 5. results the tools available on quickstrike platform helped to determine the implied volatility for the options which strikes price are different that the price of the atm option (in this case option with k=66 usd/b). the results of their application are presented in figure 1. values of other market parameters required for option valuation were assumed at the level identical to the level in section 4. the option strike price was changed every 1 usd and ranged between 64 and 68 usd/b. when calculated the implied volatility for options which are not atm options (k ≠ 66), three cases were analysed. the first one assumed volatility of the atm option at 0.25, the second one at 0.35 and the third one at 0.45. according to figure 1, a decrease in the strike price (k = 64 or k = 65) resulted in an increasing volatility of the option. for an option with the strike price k = 67 or k = 68, the volatilities were lower than the volatility of a respective atm option. the number of days to expiration of an option did not have any major impact on the changes in the volatility parameter in the analysed options. the value of implied volatilities obtained by using the quikstrike platform will allow to determine the prices of the european call and put options for the future wti oil price. black’s model was used to calculate the price of the option. obtained values allowed to determine the level of beps and the tc in the long strap strategy. to analyse how the tcs respond to a variable strike price, percentage changes in the beps were calculated while increasing the strike price by a unit. all results are presented in table 2. łamasz and iwaszczuk: crude oil option market parameters and their impact on the cost of hedging by long strap strategy international journal of energy economics and policy | vol 10 • issue 1 • 2020476 the calculations led to formulation of the following conclusions connecting the costs of hedging by the long strap strategy with the strike price and other market parameters of an option: 1. increased volatility (with other option parameters remaining unchanged) increases the tcs in the long strap strategy. it is a consequence of a growth in the strike price both for the put and the call option 2. a reduction in the number of days to expiration (of the option strategy), with other option parameters unchanged, reduces the strike price both for the put and the call option. the dependence translates into a reduction of the tcs of the long strap strategy 3. by increasing the strike price, the put option price goes down and the call price goes up. since in the long strap strategy twice as many positions are taken in call options than in put options, a higher strike price (with other parameters unchanged) limits the tcs of the long strap strategy. these dependencies are derived directly from the black’s model as well as from the method underlying the long strap strategy structuring. furthermore, they also affect the rate of changing the total strategy costs in case of a growing strike price (figure 2). as presented above, an increase in the strike price would typically result in decreasing distance between bepu and bepd (tcs). the rate of the decreases is slower when setting increasingly higher strike prices. therefore, a reduction in the tcs of the long strap strategy will become the most intensive when changing the strike price from 64 to 65 units and hardly perceptible (usually below 2%) when “moving” from 67 to 68 units. taking the impact of other market parameters into account, note that the rate of reduction of distances between beps in the long strap strategy is going down when volatility of the underlying asset is increasing. on the other hand, limitation of the number of days to expiration increases the rate of the reduction, with the only exception being a change in the strike price from 67 to 68 units. in that case, as a result of a shorter time to expiration (with other parameters remaining unchanged), the reduction rate of the tcs remains unchanged. taking the lowest of the volatilities used (about 0.25), an increase in the tcs as a source: own analysis 64 65 66 67 68 atm (σ=0,25; t=30) 0.2661 0.2569 0.25 0.246 0.2419 atm (σ=0,25; t=20) 0.2653 0.2572 0.25 0.2464 0.2423 atm (σ=0,25; t=10) 0.2666 0.2567 0.25 0.2454 0.2436 atm (σ=0,35; t=30) 0.3663 0.3575 0.35 0.3452 0.3425 atm (σ=0,35; t=20) 0.3664 0.3561 0.35 0.3456 0.343 atm (σ=0,35; t=10) 0.3667 0.3562 0.35 0.3459 0.3425 atm (σ=0,45; t=30) 0.4655 0.4561 0.45 0.445 0.443 atm (σ=0,45; t=20) 0.4654 0.4572 0.45 0.4454 0.4428 atm (σ=0,45; t=10) 0.4649 0.456 0.45 0.4466 0.4433 0.2 0.25 0.3 0.35 0.4 0.45 0.5 v ol at ili ty strike price figure 1: changes in volatility implied for the future price of wti oil options at set market parameters of atm options source: own analysis 65 66 67 68 -25% -20% -15% -10% -5% 0% 5% 10 20 30 10 20 30 10 20 300,25 0,35 0,45 to ta l c os ts c ha ng es volatility numbers of days to expiration 0%-5% -5%-0% -10%--5% -15%--10% -20%--15% -25%--20% strike price figure 2: percentage changes in total cost with a strike price changed by a unit łamasz and iwaszczuk: crude oil option market parameters and their impact on the cost of hedging by long strap strategy international journal of energy economics and policy | vol 10 • issue 1 • 2020 477 result of changing the strike price from 67 to 68 units may be also observed for a 10-day strategy. the dependencies presented so far did not show the power of impact of individual market parameters onto costs in the long strap strategy. for this reason, the final stage of the analysis consisted in calculating greek coefficients delta, gamma, vega and theta for options for the future prices of wti oil. such approach made it also possible to calculate the greeks for strategies built on the basis of the above-mentioned options. the results presented in the table 3 show that, in the long strap strategy using options with strike prices set below the present future price of a commodity (66 usd/b), an increase in any parameter: the strike price, volatility or the days to expiration (while other parameters remain unchanged) reduces the delta. in case when the strategy structure plans to use options with strike prices above the atm option strike price, the impact of volatility and time to expiration onto delta is reversed while the direction of the strike price impact does not change. accordingly, the tc of the long strap strategy with a lower strike price (k = 64 or k = 65/b) will be growing quite rapidly in case of increasing future prices of wti. this outcome will be particularly noticeable in case of 10 days to expiration strike days when a growth in the price of an oil barrel by 1 usd translates into an increase in the sum of paid option prices by approximately 1.3 usd (for k = 64 usd/b). however, the cost response to changes in the future price of the commodity at higher strike prices (k = 67 or k = 68 usd/b) will be significantly less intensive. even more so, given short periods table 2: tc, bep and final results for long strap option strategy parameters option premium bep and tc bep and tc changes (%) σ t k call put d u tc d u tc 0,2661 30 64 3,13 1,13 56,6 67,7 7,40 0,2569 30 65 2,46 1,46 58,62 68,19 6,38 3,57 0,72 −13,78 0,25 30 66 1,88 1,88 60,35 68,83 5,65 2,95 0,94 −11,39 0,246 30 67 1,41 2,41 61,77 69,62 5,23 2,35 1,15 −7,43 0,2419 30 68 1,02 3,02 62,94 70,53 5,06 1,89 1,31 −3,31 0,2653 20 64 2,80 0,80 57,6 67,2 6,40 0,2572 20 65 2,12 1,12 59,64 67,68 5,36 3,54 0,71 −16,25 0,25 20 66 1,54 1,54 61,38 68,31 4,62 2,92 0,93 −13,81 0,2464 20 67 1,08 2,08 62,76 69,12 4,24 2,25 1,19 −8,23 0,2423 20 68 0,72 2,72 63,84 70,08 4,16 1,72 1,39 −1,89 0,2666 10 64 2,41 0,41 58,77 66,61 5,23 0,2567 10 65 1,68 0,68 60,96 67,02 4,04 3,73 0,62 −22,70 0,25 10 66 1,09 1,09 62,73 67,63 3,27 2,90 0,91 −19,14 0,2454 10 67 0,65 1,65 64,05 68,48 2,95 2,10 1,26 −9,59 0,2436 10 68 0,36 2,36 64,92 69,54 3,08 1,36 1,55 4,29 0,3663 30 64 3,83 1,83 54,51 68,75 9,49 0,3575 30 65 3,20 2,20 56,41 69,3 8,59 3,49 0,80 −9,48 0,35 30 66 2,64 2,64 58,09 69,95 7,91 2,98 0,94 −7,99 0,3452 30 67 2,15 3,15 59,54 70,73 7,46 2,50 1,12 −5,65 0,3425 30 68 1,74 3,74 60,78 71,61 7,22 2,08 1,24 −3,22 0,3664 20 64 3,36 1,36 55,92 68,04 8,08 0,3561 20 65 2,71 1,71 57,86 68,57 7,14 3,47 0,78 −11,63 0,35 20 66 2,15 2,15 59,54 69,23 6,46 2,90 0,96 −9,52 0,3456 20 67 1,68 2,68 60,96 70,02 6,04 2,38 1,14 −6,50 0,343 20 68 1,29 3,29 62,13 70,94 5,87 1,92 1,31 −2,76 0,3667 10 64 2,77 0,77 57,69 67,16 6,31 0,3562 10 65 2,09 1,09 59,73 67,64 5,27 3,54 0,71 −16,47 0,35 10 66 1,52 1,52 61,43 68,29 4,57 2,85 0,96 −13,27 0,3459 10 67 1,07 2,07 62,79 69,1 4,21 2,21 1,19 −8,02 0,3425 10 68 0,72 2,72 63,84 70,08 4,16 1,67 1,42 −1,11 0,4655 30 64 4,54 2,55 52,37 69,81 11,63 0,4561 30 65 3,93 2,93 54,21 70,4 10,79 3,51 0,85 −7,17 0,45 30 66 3,39 3,39 55,83 71,08 10,17 2,99 0,97 −5,81 0,445 30 67 2,90 3,90 57,3 71,85 9,70 2,63 1,08 −4,59 0,443 30 68 2,48 4,48 58,56 72,72 9,44 2,20 1,21 −2,68 0,4654 20 64 3,93 1,93 54,21 68,9 9,79 0,4572 20 65 3,32 2,32 56,04 69,48 8,96 3,38 0,84 −8,51 0,45 20 66 2,77 2,77 57,69 70,15 8,31 2,94 0,96 −7,29 0,4454 20 67 2,29 3,29 59,13 70,94 7,87 2,50 1,13 −5,22 0,4428 20 68 1,88 3,88 60,36 71,82 7,64 2,08 1,24 −2,96 0,4649 10 64 3,15 1,15 56,55 67,73 7,45 0,456 10 65 2,51 1,51 58,47 68,27 6,53 3,40 0,80 −12,34 0,45 10 66 1,96 1,96 60,12 68,94 5,88 2,82 0,98 −10,00 0,4466 10 67 1,50 2,50 61,5 69,75 7,40 2,30 1,17 −6,46 0,4433 10 68 1,12 3,12 62,64 70,68 6,38 1,85 1,33 −2,55 source: own analysis σ: volatility, t: number of day to expiration, k: strike price, d=bepd, u=bepu, tc: total cost łamasz and iwaszczuk: crude oil option market parameters and their impact on the cost of hedging by long strap strategy international journal of energy economics and policy | vol 10 • issue 1 • 2020478 of strategy delivery and low volatility (0.25), an increase in the future prices of oil may result in a reduced sum of the option prices. volatility, a strike price and days to expiration do not have a major impact on the delta for the strategy with atm options and typically oscillates between 0.54 and 0.58. the value of the gamma which, in turn, informs about the response of the delta to fluctuations in the future price of a commodity reaches the highest value in long strap strategies with atm options. by reducing the time to expiration, gamma is increased. in turn, higher volatility limits the level of the gamma. a change in the strike price has a rather similar way of affecting the value of the two latter greeks, vega and theta (its absolute value). each reaches it highest level (assuming that other parameters are not volatile) for the atm option. it means that the long strap strategies using such options are the most sensitive to volatility of the underlying instrument (as indicated by vega) and time to expiration (theta). vega and theta also increase when influenced by volatility of options used. strategies involving atm options were an exception hereof as their vega is not dependent on volatility of the underlying instrument, observed on the market at the time. in turn, a reduction in the time to strike limits the vega and increases theta. accordingly, costs in the long strap strategies with atm options, realised within 30 days from the moment of taking a position in such strategy, will be the most sensitive to shifts in volatility. the table 3: the value of greeks for single options and long strap strategy parameters options long strap σ t k delta c delta p gamma vega theta c theta p delta gamma vega theta 0,2661 30 64 0,67 −0,33 0,07 0,068 −0,03 −0,03 1,01 0,22 0,205 −0,09 0,2569 30 65 0,60 −0,40 0,08 0,073 −0,03 −0,03 0,79 0,24 0,219 −0,09 0,25 30 66 0,51 −0,49 0,08 0,075 −0,03 −0,03 0,54 0,25 0,226 −0,09 0,246 30 67 0,43 −0,57 0,08 0,074 −0,03 −0,03 0,29 0,25 0,223 −0,09 0,2419 30 68 0,35 −0,65 0,08 0,070 −0,03 −0,03 0,04 0,24 0,209 −0,08 0,2653 20 64 0,70 −0,30 0,08 0,054 −0,04 −0,04 1,10 0,25 0,161 −0,13 0,2572 20 65 0,61 −0,39 0,10 0,059 −0,05 −0,05 0,84 0,29 0,177 −0,14 0,25 20 66 0,51 −0,49 0,10 0,062 −0,05 −0,05 0,54 0,31 0,185 −0,14 0,2464 20 67 0,41 −0,59 0,10 0,060 −0,05 −0,04 0,22 0,31 0,180 −0,14 0,2423 20 68 0,31 −0,69 0,09 0,054 −0,04 −0,04 −0,07 0,28 0,163 −0,12 0,2666 10 64 0,76 −0,24 0,11 0,034 −0,07 −0,07 1,29 0,32 0,101 −0,20 0,2567 10 65 0,65 −0,35 0,13 0,041 −0,08 −0,08 0,94 0,40 0,122 −0,24 0,25 10 66 0,51 −0,49 0,15 0,044 −0,08 −0,08 0,52 0,44 0,131 −0,25 0,2454 10 67 0,36 −0,64 0,14 0,041 −0,08 −0,08 0,09 0,42 0,123 −0,23 0,2436 10 68 0,24 −0,76 0,12 0,034 −0,06 −0,06 −0,29 0,35 0,101 −0,19 0,3663 30 64 0,64 −0,36 0,05 0,071 −0,04 −0,04 0,91 0,16 0,213 −0,13 0,3575 30 65 0,58 −0,42 0,06 0,074 −0,04 −0,04 0,74 0,17 0,222 −0,13 0,35 30 66 0,52 −0,48 0,06 0,075 −0,04 −0,04 0,56 0,18 0,226 −0,13 0,3452 30 67 0,46 −0,54 0,06 0,075 −0,04 −0,04 0,38 0,18 0,225 −0,13 0,3425 30 68 0,40 −0,60 0,06 0,073 −0,04 −0,04 0,20 0,18 0,219 −0,12 0,3664 20 64 0,66 −0,34 0,06 0,057 −0,06 −0,06 0,97 0,19 0,170 −0,19 0,3561 20 65 0,59 −0,41 0,07 0,060 −0,06 −0,07 0,77 0,21 0,180 −0,20 0,35 20 66 0,52 −0,48 0,07 0,062 −0,07 −0,07 0,55 0,22 0,185 −0,20 0,3456 20 67 0,44 −0,56 0,07 0,061 −0,07 −0,06 0,33 0,22 0,183 −0,19 0,343 20 68 0,37 −0,63 0,07 0,058 −0,06 −0,06 0,11 0,21 0,175 −0,18 0,3667 10 64 0,70 −0,30 0,09 0,038 −0,10 −0,11 1,11 0,26 0,113 −0,31 0,3562 10 65 0,61 −0,39 0,10 0,042 −0,11 −0,11 0,84 0,29 0,125 −0,34 0,35 10 66 0,51 −0,49 0,10 0,044 −0,12 −0,12 0,53 0,31 0,131 −0,35 0,3459 10 67 0,41 −0,59 0,10 0,042 −0,11 −0,11 0,22 0,31 0,127 −0,34 0,3425 10 68 0,31 −0,69 0,09 0,038 −0,10 −0,10 −0,07 0,28 0,115 −0,30 0,4655 30 64 0,62 −0,38 0,04 0,072 −0,05 −0,06 0,85 0,13 0,216 -0,16 0,4561 30 65 0,57 −0,43 0,05 0,074 −0,05 −0,06 0,72 0,14 0,222 −0,17 0,45 30 66 0,53 −0,47 0,05 0,075 −0,06 −0,06 0,58 0,14 0,226 −0,17 0,445 30 67 0,48 −0,52 0,05 0,075 −0,06 −0,05 0,44 0,14 0,226 −0,17 0,443 30 68 0,43 −0,57 0,05 0,074 −0,05 −0,05 0,30 0,14 0,223 −0,16 0,4654 20 64 0,63 −0,37 0,05 0,058 −0,08 −0,08 0,90 0,16 0,175 −0,25 0,4572 20 65 0,58 −0,42 0,06 0,060 −0,08 −0,09 0,73 0,17 0,181 −0,25 0,45 20 66 0,52 −0,48 0,06 0,061 −0,08 −0,08 0,56 0,17 0,184 −0,25 0,4454 20 67 0,46 −0,54 0,06 0,061 −0,08 −0,08 0,39 0,17 0,184 −0,25 0,4428 20 68 0,41 −0,59 0,06 0,060 −0,08 −0,08 0,22 0,17 0,180 −0,24 0,4649 10 64 0,67 −0,33 0,07 0,040 −0,14 −0,14 1,01 0,21 0,119 −0,42 0,456 10 65 0,59 −0,41 0,08 0,042 −0,15 −0,15 0,78 0,23 0,127 −0,44 0,45 10 66 0,51 −0,49 0,08 0,044 −0,15 −0,15 0,54 0,24 0,131 −0,45 0,4466 10 67 0,43 −0,57 0,08 0,043 −0,15 −0,15 0,30 0,24 0,129 −0,44 0,4433 10 68 0,36 −0,64 0,08 0,041 −0,14 −0,14 0,07 0,23 0,122 −0,41 source: own analysis łamasz and iwaszczuk: crude oil option market parameters and their impact on the cost of hedging by long strap strategy international journal of energy economics and policy | vol 10 • issue 1 • 2020 479 impact of the change of time on the sum of the paid out option premiums will be then the most observable in strategies with the shortest strike date (10 days), the highest anticipated volatility (0.45) for which atm options may be also used. 6. conclusion the method used to structure the long strap strategy and setting the beps presented in the paper showed that the strategy should be used largely in case of anticipated increases in the prices of the underlying asset. apart from the long put option, the strategy also uses a long position in the call option and, as a result, it offers the opportunity of generating a profit also with dropping prices of the underlying asset. from the point of view of a successful application of the long strap strategy, the levels of the beps are important (bepd, bepu), they are directly related to the tcs i.e. with the sum of paid option premiums. the key objective of the paper was to present the manner in which the costs will be changing in the long strap strategy when influenced by fluctuations of such parameters as the future price of a commodity and its volatility (non-elective parameters) as well as the strike price and the time to expiration (elective parameters). the analyses are based on the data from the wti market for oil futures. for this reason, the results of the study are particularly valuable to entities actively participating in oil trading and exposed to the risk of oil price fluctuations. calculations underlying the conclusions showed that an increase in the strike prices reduces the costs. their drop rate is particularly intensive when put option-based strategies are created which are effectively out-of-the-money options (in consequence, the call options used are in-the-money options, which results from the manner in which the long strap strategy is structured). furthermore, note that an option with the strike price used in the structure of the strategy was different from the atm strike price by not more than 2 usd per barrel. among the key conclusions from the analysis the way in which the implied volatility for such options is formed. the coefficient is higher for options with lower strike prices and lower for options with higher strike prices than the atm option. the phenomenon contributes to some intensified reductions in the tcs while increasing the strike prices used in the long strap strategy. also, a cost increase was also observed when increasing volatility and extending the time to expiration. by calculating the greeks for the long strap strategy, one could learn about the difference in the strike price when a market parameter changes by a unit. it turned out that an increase in the tc caused by a growth in the wti oil future prices was particularly intensive when using options with lower strike prices. in turn, gamma, vega and theta were the highest for atms. consequently, the greeks contributed some important knowledge about the dependence between the strike price and market parameters which affect the option. the coefficients may be then considered important tools supporting the decision-making process when selecting an option in the process of building strategies hedging against the price risk. these decisions may also concern a change in option positions when responding to some received values of the greeks calculated for the strategy (a dynamic hedging). therefore, one may conclude that the above-mentioned tools improve the decision-making flexibility and, consequently, give an opportunity for generating improved results by reducing the costs of hedging or obtaining a higher amount from an option payout function. 7. acknowledgement this publication is financed by agh university of science and technology within the subsidy for maintaining reserach potential. references alexander, c. (2008), market risk analysis, pricing, hedging and trading financial instruments. vol. 3. chichester: wiley finance series. an, j., mikhaylov, a., moiseev, n. (2019), oil price predictors: machine learning approach. international journal of energy economics and policy, 9(5), 1-6. arour, m., jouini, j., nguyen, d. (2011), volatility spillovers between oil prices and stock sector returns: implications for portfolio management. journal of international money and finance, 30, 1387-1405. barone-adasi, g., whaley, r.e. (1987), efficient analytic approximation of american option values. journal of finance, 42, 301-320. bittman, j.b. (2009), trading options as a professional. techniques for market makers and experienced traders. new york: mcgraw-hill. bjerksund, p., stensland, g. (1993), closed-form approximation of american options. scandinavian journal of management, 9, 88-99. bjerksund, p., stensland, g. (2002), closed-form valuation of american options. norwegian school of economics and business administration. department of finance and management science, discussion paper, no. 9. black, f. (1976), the pricing of commodity contracts. journal of political economy, 81(3), 167-179. black, f., scholes, m. (1973), the pricing of option and corporate liabilities. journal of financial economics, 3, 637-654. chikunov, s.o., ponkratov, v.v., sokolov, a.a., pozdnyaev, a.s., osinovskaya, i.v., ivleva, m.i. (2019), financial risks of russian oil companies in conditions of volatility of global oil prices. international journal of energy economics and policy, 9(3), 18-29. clark, i.j. (2011), foreign exchange option pricing: a practioner’s guide. chichester: wiley finance series. clark, i.j. (2014), commodity option pricing: a practioner’s guide. padstow, cornwall: wiley finance series. cme group. (2018a), options calculator. available from: https://www. cmegroup.com/tools-information/quikstrike/options-calculator.html. [last accessed on 2018 apr 22]. cme group. (2018b), strategy simulator. available from: http://www. cmegroup.com/tools-information/quikstrike/strategy-simulator.html. [last accessed on 2018 apr 23]. cox, j.c., ross, s.a., rubenstein, m. (1979), option pricing: a simplified approach. journal of financial economics, 7(3), 229-263. cunado, j., perez de garcia, f. (2005), oil prices, economic activity and inflation: evidence for some asian countries. the quarterly review of economics and finance, 45, 65-83. edelstein, p., kilian, l., (2009), how sensitive are consumer expenditures to retail energy prices? journal of monetary economics, 56(6), 766-779. foudeh, m. (2017), the long run effects of oil prices on economic growth: łamasz and iwaszczuk: crude oil option market parameters and their impact on the cost of hedging by long strap strategy international journal of energy economics and policy | vol 10 • issue 1 • 2020480 the case of saudi arabia. international journal of energy economics and policy, 7(6), 171-192. hamilton, j.d. (2003), what is an oil shock? journal of econometrics, 113, 363-398. hull, j. (2012), option, futures and other derivatives. 8th ed. boston: pearson. kathiravan, c., selvam, m., maniam, b., venkateswar, s. (2019), relationship between crude oil price changes and airlines stock price: the case of indian aviation industry. international journal of energy economics and policy, 9(5), 7-13. khamis, r., anasweh, m., hamdan, a. (2018), oil prices and stock market returns in oil exporting countries: evidence from saudi arabia. international journal of energy economics and policy, 8(3), 301-306. merton, r.c. (1973), theory of rational option pricing. bell journal of economics and management science, 4(1), 141-183. schwartz, e. (1997), the stochastic behavior of commodity prices: implications for valuation and hedging. journal of finance, 52(3), 923-973. shreve, s.e. (2004), stochastic calculus for finance ii: continuous-time models. heidelberg: spriger-verlag. smithson, c.w. (1998), managing financial risk. a guide to derivative products, financial engineering and value maximization. new york: mcgraw-hill. tabash, m., khan, s. (2018), the impact of oil price volatility, gross domestic product, foreign direct investment on islamic banking investments: an empirical evidence of the united arab emirates. international journal of energy economics and policy, 8(5), 306-312. taleb, n.n. (1996), dynamic hedging: managing vanilla and exotic options. new york: john wiley and sons. węgrzyn, r. (2013), opcje jako instrument ograniczania ryzyka cen akcji: problemy optymalizacji. kraków: wydawnictwo uniwersytetu ekonomicznego w krakowie. whaley, r.e. (1986), valuation of american futures options: theory and empirical tests. journal of finance, 41, 127-150. international journal of energy economics and policy vol. 5, no. 1, 2015, pp.1-13 issn: 2146-4553 www.econjournals.com 1 unlicensed renewable energy generation: a review of regulation and applications in the context of turkey mustafa gozen* energy market regulatory authority, electricity market department, ankara, turkey. email: mgozen@gmail.com abstract: turkey has stipulated that renewable energy sources (res) will have at least 30% share in electricity generation by 2023. to reach this target, a renewable energy promotion law (law no. 5346) was enacted in 2005 and later amended in 2011. through law no. 5346, turkey has launched a feed-in tariff (fit) for res-based electricity with additional premium for the use of local equipment. the fit is guaranteed for 10 years from the date of operation and valid only for res power plants commissioned between the 18th may, 2005 and the 31th of december 2020. in addition, res power plants with a capacity of up to 1 mw are exempted from licensing and establishing legal entities. there is an increasing demand to install unlicensed res generators, mostly solar power plants, all over the country. at least one consumption unit must be associated with an unlicensed power plant. excess generation from unlicensed res power plants is automatically priced at the fit for 10 years. except for the fit mechanism, unlicensed generators have no options to sell unconsumed electricity in the electricity market. the main difficulties lie in limited connection possibilities, the selection of plant locations, and coordination among relevant authorities. moreover, an awareness campaign would help people to better understand the related regulation and applications. keywords: unlicensed generation; distributed generation; electricity market; turkey jel classifications: l5; q40; q43; q48; q49 1. introduction according to the electricity strategy paper issued by the turkish government, turkey set targets for the share of renewable energy sources (res) in the electricity generation. for example, res will have at least 30% share in electricity generation by 2023 (etkb, 2014a). to reach this target, a specific law for the promotion of res (law no. 5346) was enacted in 2005 and later amended in 2011 (yegm, 2014a). law no. 5346 has introduced a feed-in tariff (fit) for res-based electricity with additional premium for the use of local equipment. the fit is guaranteed for 10 years from the date of operation and valid only for res power plants commissioned between the 18th may, 2005 and the 31th of december 2020 (emra, 2014a). in addition, up to 1 mw of res power plants is exempted from licensing and establishing companies. there is an increasing demand to install unlicensed res generators, mostly solar power plants, all over the country. unlicensed electricity generation is regarded to be a new field of investment in the electricity market in turkey. in this context, it presents opportunities for consumers and investors. the consumer considers the opportunity to generate electricity with a view to meet individual need of electricity without establishing a company and obtaining a license for the power plant from emra1. in this article, the regulations and applications about unlicensed res generation in the context of turkey are introduced, explained, and discussed in detail. hence the main purpose of this article is to introduce unlicensed electricity generation and related regulations in turkey, discuss its differences * the viewpoints and comments in this article are those of the author and do not represent the views of the regulatory authority where the author is working, and of any other institutions. the early version of this article is presented in 4th iaee asian conference, beijing, china, september 19-21, 2014. 1 emra is the abbreviation for turkish energy regulator established in 2001. its full name is energy market regulatory authority, which is an autonomous governmental organization regulating four markets such as electricity, natural gas, petroleum, and lpg markets. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.1-13 2 from licensed generation and particularly from distributed generation, and explain the applications and challenges about unlicensed generation. this article is organized as follows. following the introduction section, the second section summarizes the basic features of the turkish electricity market, including the renewable energy policy of the country. the third section provides information about the fuels and sources for electricity generation and the potential for res in turkey. the fourth section introduces the regulations regarding unlicensed renewable energy generation. the fifth section makes an analysis of the regulations and applications about unlicensed electricity generation. in addition, it makes suggestions to improve and promote the application of unlicensed generation in the country. the sixth, and final, section makes a summary and concludes the article. 2. background of electricity market energy policy context in terms of renewable energy policy, turkey attributes significant importance to a) encouraging energy generation from res2 in a secure, economic and cost effective manner, b) expanding the utilization of res of the country, and c) increasing the diversification of energy sources. in addition, reducing greenhouse gas emissions, making use of waste products and protecting the environment, and developing the related mechanical and/or electro-mechanical manufacturing sector are other main pillars of the energy policy. turkey has opened a new era in the electricity market in 2001. the legal basis of the new era was the electricity market law, which came in effect in 2001. later in 2013, a new law electricity market law no. 6446 came in effect in march 30, 2013 while law no. 4628 was amended as the organization law of emra. law no. 6446 is a framework law regulating electricity market structure, market participants, third party access, market entry, monitoring, and auditing. according to the law no. 6446, state-owned companies and relevant activities are legally unbundled. regulated third party access is in place for network access. market design is based on bilateral contract market complemented by a day-ahead market and a residual balancing market. in terms of limiting market share, static precautions are taken in the market. as part of this measure, any real or legal entity cannot exceed 20% of total electricity generation in the country. moreover, no supplier can procure more than 20% of total consumption in turkey. all market activities must be licensed by emra with some exemptions. among other power plants specified in later sections of this article, renewables with a capacity of up to 1 mw and certain cogeneration power plants are exempted from licensing obligation. separate licenses are required for each market activity and facility. first a pre-license is given for the procurement of required approvals and permits to install a power plant. licensees may ask for public interest decision for expropriation from emra. license applicants must be established as joint stock or limited liability companies in accordance with the provisions of the turkish commercial code. if established as joint stock companies, all shares of the applicant company must be registered shares, except for the shares traded in the stock exchange. the eligibility limit for 2014 is set as 4500 kwh by emra board resolution, meaning that consumers with consumption above this limit are eligible to choose their suppliers. the electricity market strategy paper envisions a full retail market opening at the beginning of 2015. network tariffs and sales to captive customers as well as tariffs for last resort customers are regulated by emra. renewable based electricity is supported through feed-in tariffs depending on technology and also an extra premium is provided for the use of local equipment. participation to the res support mechanism is not mandatory. however, unconsumed3 electricity from unlicensed generation is automatically priced at the fit. 2 according to the law no. 5346, renewable energy sources are the energy sources such as hydraulic, wind, solar, geothermal, biomass, gas obtained from biomass (including landfill gas), and non-fossil energy sources such as wave, tidal, and stream. 3 in this article, the words "unconsumed", "excess", and "surplus" are used interchangeable. unlicensed renewable energy generation: a review of regulation and applications in the context of turkey 3 3. renewable energy sources for electricity generation turkey has substantial amount of renewable energy potential and the utilization rates are increasing over years. hydraulic, wind, and solar energy resources are the major portions of renewable portfolio. turkey's renewable energy potential and the installed capacity are given in table 1. table 1. renewable energy potential of turkey source renewable energy potential (1) installed capacity (as end of 2013) (2) utilization rate (3)=((2)/(1)*100) (%) hydro 40.000 mw (140 billion kwh/year electricity) 22.289 55.7 wind 47.849,44 mw (130 billion kwh/year electricity) 2.759,6 5.8 geothermal 31.500 mwt (1.500 mw is suitable for electricity generation) 295,8 19.7 biomass 8.6 mtoe (1.5 2.0 billion kwh/year electricity) 154,4 na solar 380 billion kwh/year electricity (*) (*) source: akat (2014), etkb (2014b), yegm (2014b), emra (2014). (*) currently, there is no licensed solar power plant in operation in turkey except for 15.4 mw unlicensed solar generators (teias, 2014). na means "not applicable" because the data for the potential in mw is not available. in addition, turkey has established the following targets for 2023. until 2023, the whole economically feasible hydropower potential of turkey will be provided for electricity generation. 20,000 mw of wind power plant will be in operation. solar power capacity will reach at least 3,000 mw. a minimum 600 mw of geothermal production will be implemented. a total of 1,500 mwe of installed capacity for biomass energy will be realized (akat, 2014: etkb, 2014b: yegm, 2014b). 3.1. hydroelectric potential hydropower sources have the most significant place in the renewable energy potential of turkey. theoretical hydropower potential in the country is calculated at 433 billion kwh; technically feasible hydropower potential is 216 billion kwh. however, the economic potential is 140 billion kwh/year (akat, 2014: yegm, 2014b). the distribution of existing hydraulic power plants in operation in the country is shown in figure 1. the green circle shows the locations of the hydraulic power plants in operation. it could be concluded that the hydraulic power plants are roughly evenly distributed throughout turkey (karakus, 2013). figure 1. location of hydraulic power plants in operation source: karakus (2013). international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.1-13 4 3.2. wind energy potential the turkey wind energy potential atlas (repa), which was realized in 2007 calculates that turkey has a minimum wind energy potential of 5.000 mw in regions with annual wind speed of 8.5 m/s and higher, and around 48.000 mw with wind speed higher than 7.0 m/s (akat, 2014: yegm, 2014b). details of wind energy potential in the country are given in table 2. table 2. wind energy potential of turkey resource potential wind class annual wind power density (w/m2) annual wind speed (m/s) total capacity (mw) good 4 400 – 500 7.0 – 7.5 29.259,36 excellent 5 500 – 600 7.5 – 8.0 12.994,32 outstanding 6 600 – 800 8.0 – 9.0 5.399,92 superb 7 > 800 > 9.0 195.84 total capacity 47.849,44 source: yegm (2014b), akat (2014), and yaniktepe et al. (2013:107). total potential wind capacity is divided between 37.836 mw on-shore and 10,013 mw offshore (yegm, 2014b: akat, 2014). in addition, the location of wind license applications is shown in figure 2. as clearly seen from figure 2, the western coastal regions of turkey, mainly the aegean and marmara sea coasts, is receiving high interest from investors. figure 2. distribution of wind license applications source: prepared by using data from emra and yegm4. 3.3. solar energy potential turkey offers perfect natural conditions for solar power plants. the country is geographically located in the mediterranean sun belt. solar radiation values are quite similar to spain and portugal. as end of august 2014, total installed capacity for unlicensed solar power plants is 15.4 mw (teias, 2014). this does not include the systems in forest fire watching towers, highways, communication towers, and meteorological stations. the solar radiation values in turkey are given in figure 3. the southern part of turkey, mainly mediterranean region and some cities in the eastern region has the highest total solar radiation. having a high potential for solar energy due to its geographical position, turkey's average annual total 4 yegm is the abbreviation for general directorate of renewable energy of the ministry of energy and natural resources. unlicensed renewable energy generation: a review of regulation and applications in the context of turkey 5 sunshine duration is calculated at 2,640 hours5, and average total radiation pressure at 1,311 kwh/m²year6 (akat, 2014: yegm, 2014b). figure 3. solar radiation in turkey source: akat (2014), yegm (2014b). in turkey, it is expected that solar based electricity generation will increase with the decline in the investment cost of solar power plants and increase in their efficiency. moreover, using the turkey solar energy potential atlas and csp technology, it is calculated that an annual production of 380 billion kwh is possible (baris and kucukali, 2012, 383). 3.4. geothermal energy potential located on the alpine-himalayan belt, turkey has a relatively high geothermal energy potential. the geothermal potential of the country is calculated to be 31,500 mwt (akat, 2014: yegm, 2014b). areas with potential are located in the western anatolia (77.9%) (baris and kucukali, 2012, 382). some 55% of the geothermal rich regions in turkey are suitable for heating purposes (akat, 2014: yegm, 2014b). in turkey, 1,200 decares of greenhouses are heated using geothermal energy, and 100.000 households in 15 settlements are also heated with geothermal energy (akat, 2014: yegm, 2014b). prospecting works by mta general directorate7 which started from 2003 resulted in a geothermal energy source of 840 mw (akat, 2014). while 1.500 mw of the geothermal energy potential is assessed to be suitable for electricity generation, the finalized data is so far 600 mw (akat, 2014). at end of 2013, the installed power of geothermal energy reached 295.8 mw (yegm, 2014b). 3.5. biomass energy potential referring to table 1, the amount of biogas that can be produced in turkey, considering its animal waste potential, is reported to be 1.5 to 2 mtoe8. turkey's major biomass sources include agriculture, forests, animals, and organic urban waste. while the waste potential is around 8.6 mtoe, 6 million mtoe is used for heating (akat, 2014: yegm, 2014b: etkb, 2014b). 4. unlicensed electricity generation unlicensed power generation has been made possible for interested parties in turkey since 2010. considering the electricity market reform in turkey which started in 2001, unlicensed electricity production is a new activity in the market that allows consumers to carry out electricity generation. in this sense, the unlicensed generation is an important development in the country. the principles and 5 the corresponding daily total is 7.2 hours. 6 the corresponding daily total is 3.6 kwh/m². 7 it stands for general directorate for mineral research and exploration. it is affiliated to the ministry of energy and natural resources. 8 million tons equivalent of petroleum international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.1-13 6 conditions of unlicensed power generation have been regulated by the by-law on unlicensed electricity generation in the electricity market (by-law)9 which came in effect in december 3, 2010. the legal basis of this regulation is article 14 of the law no. 6446. the main purpose of this regulation is, among other things, to provide the entrance of the small power plants to the electricity market, provide the electrical energy for consumers and, reduce the loss in electrical energy. according to this regulation, every person, or legal entity which is an electricity subscriber may establish a power plant without obtaining license from the energy regulator emra and sell the excess electricity. this regulation will be of interest particularly to universities, building complexes, and also the shopping centers. but, electricity subscribers such as apartment building management may not establish such power plants because it does not have a legal entity. pursuant to the article 14 of the law no. 6446 and the by-law, the following power plants can be established with no obligation to obtain a license and establish a company (emra, 2014d: dogerlioglu attorneys at law, 2014a): a) emergency groups, b) isolated power plants without connection to electricity network10, c) power plants based on res up to 1 mw11, d) power plants based on res, consuming all of the generated energy without providing to the electricity network, having the generation and consumption points in the same location, e) cogeneration power plants12 with more than 80% total efficiency defined by the ministry of energy and natural resources, f) micro cogeneration power plants13, g) power plants based on municipal solid waste treatment plants and sludge disposal facilities, h) power plants established on water supply lines and waste water lines run by municipalities. 4.1. comparison with licensed and unlicensed generation generally speaking, two types of electricity generation are possible in turkish electricity market under the current legal regime, except for investment models such as build-operate (bo), build-operate-transfer (bot), and transfer of operating rights (toor) 14. the first is the electricity generation under a generation license obtained from emra. the other is unlicensed generation. the key differences between the two activities are given in table 3 below. compared with licensed generation, unlicensed generation offers some opportunities to the related investor. for example, unlicensed generation based on wind and solar does not require measurement of some parameters for the location of power plant. in addition, there is no restriction about application date for unlicensed generation. applications can be made to network utilities every month. but, license applications for wind and solar can only be made on a certain date determined in the secondary legislation. however, in the legislation, there is no specific definition for distributed generation. distributed generation is a broader concept including the large part of unlicensed generation. power plants up to 10 mw are connected to distribution network. power plants with capacities between 10 and 50 mw may be connected to distribution network depending on the approval of both transmission and distribution utilities. that means that power plants up to 50 mw may be connected to distribution network and regarded as distributed generation. on the other hand, as noted in table 3, there is no capacity limit for some types of unlicensed generation, which are connected to the transmission network. however, power plants with any capacity can operate under a generation license. figure 4 shows the relationships among different types of electricity generation. as seen from figure 4, in the case of turkey, there is no clear distinction between unlicensed generation and distributed generation. 9 elektrik piyasasında lisanssız elektrik üretimine i̇lişkin yönetmelik, (in turkish), available at <http://www. epdk.org.tr/index.php/elektrik-piyasasi/mevzuat?id=1292>. 10 it means transmission and distribution network. 11 council of ministers is authorized to increase the limit by 5 times in accordance with article 14 of the law no. 6446. 12 cogeneration facilities are the plants that generate heat and electricity and/or mechanical energy simultaneously. 13 micro cogeneration plants are power plants with a total installed capacity of 100 kilowatts and less. 14 these power plants will be converted to generation licensees under law no. 6446. unlicensed renewable energy generation: a review of regulation and applications in the context of turkey 7 table 3. comparison of unlicensed generation with licensed generation licensed generation unlicensed generation application period at all times, but only on the date specified in the by-law on electricity market licensing for wind and solar license applications no restriction about application date. network utilities accept applications every month, meaning 12 times a year. installed capacity no capacity limit, except for 50 mw limit for each solar power plant up to 1 mw for res based power plants for other types of unlicensed generators, except for micro cogeneration, there is no capacity limit. the capacity limit for micro cogeneration is 100 kw. expropriation possible not possible incentives for electricity sale purchasing guarantee at fit and extra premium for the use of domestic products. but, license holders are not obliged to sell their output in the res support mechanism. participation in support mechanism is voluntary. purchasing guarantee at fit and extra premium for domestic product contribution. participation in res support mechanism is mandatory for excess electricity. measurement compulsory for wind and solar license applications no measurement data is required to be eligible for unlicensed generation. share transfer forbidden only for pre-license holders during the term of prelicense. for other license holders, it is subject to the approval of emra. no restriction. no approval from emra is required. transfer of power plant possible only for the power plant completed and in operation. possible only for the power plant completed and in operation. electricity trading possible forbidden, meaning that unconsumed electricity is priced at res support mechanism. no other method of trading of excess electricity is possible. auditing emra audits license holders and implements sanctions if necessary. regional distribution utilities are authorized to audit unlicensed electricity generation. emra implements sanctions if necessary. other obligations at application stage the applicant must be a limited liability or joint stock company minimum capital requirement bank letter of guarantee any real or legal person can apply for an unlicensed electricity generation. no need of obtaining a license and establishing a company source: adopted from dogerlioglu (2014). the information is based on emra (2014d). figure 4. different types of electricity generation. 4.2. fundamentals of unlicensed electricity generation according to the by-law, each unlicensed power plant must be associated with at least one consumption unit (erdem & erdem law office, 2011). it is mandatory that the consumption unit associated with the power plant must be in operation or at least must be completed and be in operation as of the date of commissioning of the power plant. unlicensed power generation and consumption international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.1-13 8 units are required to be located within the same electricity distribution region. a consumption unit cannot be associated with more than one power plant in the same time period. there is no limit for how much of unlicensed generation will be consumed on the consumption units associated with unlicensed power plant. part of the electricity generation that is not consumed is priced at the accompanying fit listed in the law no. 5346. the limitation on the number of consumption units for each power plant that can be established within the scope of the regulation is important. principally, only one cogeneration facility, micro cogeneration facility or generation facility based on res can be established for each consumption unit (erdem & erdem law office, 2011). however, if the distribution network has sufficient capacity, more than one cogeneration or power plant based on res can be established for each consumption unit. this rule does not apply to micro cogeneration plants. only one micro cogeneration plant can be established for each consumption unit. unlicensed generators are not addressed directly with the market operator and the res support mechanism. they receive the revenue for the excess electricity every month through regional assigned retailers. 4.3. application for connection right and evaluation criteria the unlicensed power plants are connected to the transmission or distribution system depending on the installed capacity of the related project15. the connection application can be made by real or legal persons willing to generate electricity in power plants under the by-law, by completing the unlicensed generation connection application form. the application is made directly to transmission company, or to the relevant regional distribution utility or to the relevant organized industrial zone distribution license holder. the document confirming the grant of utilization right of res must be accompanied with the other application documents (erdem & erdem law office, 2011). the applications are assessed against the set criteria such as the use of res in the power plants, the eligibility of the power plant as a cogeneration plant and whether the power plant is located within same location with the consumption unit (erdem & erdem law office, 2011). 4.4. pricing unconsumed electricity the basic principle required by the by-law for the real and legal persons who want to generate unlicensed electricity is to generate electrical energy to meet only their own needs (erdem & erdem law office, 2011). however, if surplus electricity is generated, this amount of electricity may be consumed in consumption units belonging to the generator which is located in the same distribution region as the power plant (erdem & erdem law office, 2011). the pricing methodology of excess electricity from different unlicensed power plants is given in table 4. as given in detail in table 4, the unconsumed energy in the above-mentioned units is qualified as surplus energy (erdem & erdem law office, 2011). any excess power generated and not used by unlicensed generators is provided to the network through regional distribution utilities. such excess power is sold at fit specified in the law no. 5346, and in the case of micro cogeneration facilities, at the lowest fit specified in the law no. 5346. in the event that the source of the surplus energy is micro cogeneration, it is purchased on the lowest fit listed in the law 5346 by assigned regional retailers to sell captive customers in their designated regions. the by-law also permits consumption of the excess power in one or more consumer units within the same distribution region, but associated with the same unlicensed generator. however, power generated by an unlicensed power plant cannot be sold through bilateral agreements outside res support mechanism. the fit for different sources and fuels is shown in figure 5. the role of each participant in the pricing of different unlicensed power plants is schematically shown in figure 616. in figure 5 above, gn represents licensed res based generators. sn is all suppliers active in the market for a given month, and pn refers to fit prices. a is the support value for the electricity from unlicensed generation coming from all 21 distribution regions. monthly payments are made directly to bank accounts of unlicensed power producers. total value of support is collected monthly from the suppliers active in the market in proportion to the market share of the related suppliers. 15 please refer to table 4 for detailed information for the connection possibilities for each type of unlicensed power plants. 16 for further information about renewable support mechanism, please refer to gozen (2014). unlicensed renewable energy generation: a review of regulation and applications in the context of turkey 9 table 4. the pricing of excess electricity from different unlicensed power plants type of unlicensed power plant limit for installed capacity connection type pricing of unconsumed electricity 1 emergency groups none isolated not applicable 2 isolated generation facilities with no connection to transmission or distribution system none isolated not applicable 3 res based generation plants ≤ 1 mw distribution payment at fit for electricity and fit for local use of equipment if applicable. 4 micro cogeneration plants ≤ 100 kw distribution purchased by regional suppliers at the lowest fit. 5 cogeneration facilities with more than 80% total efficiency none transmission or distribution no payment. however, if surplus electricity is injected to network, electricity is recorded free of charge to res support mechanism. 6 generation power plants established to operate with municipal solid waste treatment plants and sludge disposal facilities none distribution payment at fit for electricity and fit for local use of equipment if applicable. 7 res based generation power plants, consuming all the electricity without providing to transmission or distribution system, having the production and consumption points in the same location none transmission or distribution no payment. however, if surplus electricity is injected to network, electricity is recorded free of charge to res support mechanism. 8 power plants established on water supply lines and waste water lines run by municipalities. none distribution payment at fit for electricity and fit for local use of equipment if applicable. source: emra (2014d). figure 5. the fit for different sources and fuels. note: pv photovoltaic, cs concentrated solar international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.1-13 10 figure 6. the pricing of excess electricity from res power plants the fit for the use of local equipment is listed in the law 5346 and its value ranges from 0.4 to 3.5 us cents/kwh depending on the equipment and source. production facilities in the renewable energy sector, which will be in operation before 2021, can benefit from this application. this additional tariff is provided for a period of 5 years from the operation starting date of the power plant. 4.5. renewable energy cooperatives in turkey, an article of association for electricity generation and consumption cooperatives was published in the official gazette no. 28855 dated december 18, 2013. the legal basis of this type of cooperatives in the electricity market is the law no. 6446. by setting up energy cooperatives, essentially, consumers form a cooperative, combine their consumptions and establish jointly unlicensed res power plant. within the framework of current legislation; however, the consumption of cooperative members shall be measured with a common meter or all consumption units registered for the cooperative must be connected to the same point or transformator in the network. in this way, cooperative members and the cooperative itself are able to satisfy their electricity needs and receive revenue for surplus energy within the scope of res support mechanisms. as can be seen from figure 7 below, different real persons and/or legal entities formed by combining a cooperative entity other than the consumption of the participants must be in the same group of subscribers. as seen from figure 7, all cooperative members may be commercial, residential, or industrial subscribers. the main reason behind this regulation is to facilitate the meter reading of all members of the related cooperative. figure 7. structure of a typical renewable energy cooperative. unlicensed renewable energy generation: a review of regulation and applications in the context of turkey 11 5. evaluation and discussion although the history of unlicensed electricity generation is short in turkey, there have been significant developments in this specific field of electricity market. key results are summarized below based on the experience of the past three years since the law was implemented. the limited connection availability is the key to the growth of unlicensed generation. the allocation of connection right to the network is regulated by the energy regulator – emra, but there is less capacity available for unlicensed generation. the fit is fixed in law no. 5346 and is not indexed to inflation. the fit would be favorable as long as the inflation rate is low and stable. since the fit is already set in the law no. 5346 for 10 year. this is one area that requires close monitoring particularly when the inflation increases. the intersection and overlapping of plant locations require special attention, particularly for solar and wind power plants in order to overcome conflict of interests among related parties. generation licenses are issued by emra and connection rights are allocated to unlicensed generation by network utilities. this makes the situation even more chaotic and calls for a close collaboration of related institutions. in practice, there are two groups of investors in the market. one group of investors is interested in consuming the electricity generated to improve their competitive position in their cor e businesses by lowering the cost of electricity. the other group is interested in selling the majority of electricity generated and realizing certain revenue. in this respect, legislation treats equally these two groups of investors. investors who will consume all, or a large portion of electricity generated should have connection priority to network and, as a result, the procedure should be simplified for this special group of consumers. only consumers in the same tariff class and connected to the same point of network can participate in renewable energy cooperatives. this limits the participation to, and growth of renewable energy cooperatives. there are no such requirements for unlicensed generation; such as measurement data, minimum equity injection, and bank letter of guaranty while these are the entrance requirements to the market for licensed electricity generation. in the future, this would result in the manipulation of regulations in such a way that unlicensed generators would apply for a license to the energy regulator without meeting the obligations of measurement data, minimum capital, and bank guarantees. this would be an unfair practice against licensed generation. as stated earlier, according to the law no. 6446 and the law no. 5346, power purchase agreements are not possible for unlicensed generators. however, leasing and third party financing would be an alternative option for the sector to obtain financing. the energy regulator and policymakers should take a leadership role and clarify any uncertainties regarding the financing by alternative methods. as noted by gozen (2014), unlicensed power producers do not need to have marketing and sales units since the unconsumed electricity becomes automatically part of the res support mechanism and is priced at fit. moreover, they do not face competition in the market. there is no risk of balancing for unlicensed power plants in the balancing and settlement market for the differences in their production. these are the main advantages of unlicensed electricity generation. there are several organizations from which an investor is required to obtain permits and approvals. better collaboration among them would help all stakeholders to understand the related regulation and fast-track the implementation. financing unlicensed res projects is a critical issue for those who plan to lower their electricity bills or enter a new business field by establishing a res power plant under the legal regime for unlicensed generation (dogerlioglu attorneys at law, 2014b). dogerlioglu attorneys at law (2014b) underlines that currently most banks are not interested in providing financial support for unlicensed energy projects. therefore, consumers could only continue with their projects if they have enough equity or find partners. when the turkish legislation on unlicensed electricity generation is examined from alternative financing options, such as third party financing, power purchase agreements, and leasing agreements, there are no direct regulations related to third party financing of unlicensed energy projects (dogerlioglu attorneys at law, 2014b). under the current legal regime, any real or legal entity can develop unlicensed res power projects by equity injection or arrange credit financing or alternatively find partners in order to realise the project. however, the model of international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.1-13 12 power purchase agreements cannot be applied to unlicensed res projects in turkey. but third party financing and lesaing models can be applied without any doubt. the key reason is that law no. 5346 and law no. 6446 foresee the automatic pricing of excess electricity. in turkey’s case, contrary to bilateral trade, the excess electricity goes directly to the res support mechanism and is valued under the mechanism. 6. conclusions and recommendations unlicensed electricity generation is the type of activity that allows consumers to perform electricity generation in the market. in this regard, unlicensed generation is an important development in turkey. the by-law about the unlicensed electricity generation in the electricity market was prepared by the energy market regulatory board and became in effect in 2010. with the by-law, unlicensed electricity generation has been based on a legal framework in turkey (erdem & erdem law office, 2011). it is expected that the pricing of unconsumed electricity at fit will be beneficial for both generators and the state (erdem & erdem law office, 2011). there is a high demand from investors for unlicensed electricity generation in turkey. solar generation leads in terms of applications. the main difficulties lie in limited connection possibilities, the selection of plant locations, and coordination among relevant authorities. moreover, an awareness campaign would help people to better understand the related regulation and applications. how electricity will be priced after 10 years of operation is not clear in law no. 5346. hence, lawmakers should spell out the future of support mechanism after 10 years of operation. financing unlicensed generation is an area that policymakers should pay special attention to because the facilitation of financing means will contribute to further opening of the electricity market.. references akat, s.b., (2014), renewable energy in turkey, ministry of energy and natural resources, general directorate of renewable energy, retrieved from http://www.better-project.net/sites/default/ files/renewable%20energy%20in%20turkey_directorate%20general%20for%20renewable% 20energy.pdf, (in turkish), accessed at september 28, 2014. baris, k., kucukali, s. (2012), availability of renewable energy sources in turkey: current situation, potential, government policies and the eu perspective, energy policy, 42, 377-391. dogerlioglu, ö. i., (2014), power purchase agreement for commercial pv systems, retrieved from http://www.solarbaba.com/uploads/files/dosya-gunes-enerjisinde-ppa.pdf, accessed at april 12, 2014. dogerlioglu attorneys at law, (2014a), unlicensed electricity generation: new era in turkish electricity market, retrieved from http://www.dogerlihukuk.com/userfiles/generalreport.pdf, accessed at october 1, 2014. dogerlioglu attorneys at law, (2014b), unlicensed solar energy projects: financing problems, retrieved from http://dogerlihukuk.com/?ln=en&m=news&id=585&title=unlicensed %20solar%20energy%20projects:%20financing%20problems&ust=585, accessed at october 1, 2014. erdem & erdem law office (2011), regulation on the unlicensed electricity generation, retrieved from http://www.erdem-erdem.av.tr/en/articles/regulation-on-the-unlicensed-electricitygeneration/, july, accessed at september 28, 2014. gozen m., (2014), renewable energy support mechanism in turkey: financial analysis and recommendations to policymakers", international journal of energy economics and policy 4(2), 274-287. emra (2014a), council of ministers’ decision no. 2013/5625, (in turkish), retrieved from http://www.epdk.org.tr/index.php/elektrik-piyasasi /mevzuat?id=143, accessed at april 3, 2014. emra (2014b), elektrik piyasasında lisanssız elektrik üretimine i̇lişkin yönetmelik, retrieved from http://www. epdk.org.tr/index.php/elektrik-piyasasi/mevzuat?id=1292, (in turkish), accessed at april 5, 2014. emra (2014c), lisanssız elektrik üretimine i̇lişkin yönetmeliğin uygulanmasına dair tebliğ, retrieved from http://www.epdk.org.tr/index.php/elektrik-piyasasi/mevzuat/13-icerik/elektrikicerik/ 1289-elk-yon-yekdem-belge-destek, (in turkish), accessed at april 12, 2014. unlicensed renewable energy generation: a review of regulation and applications in the context of turkey 13 emra (2014d), elektrik piyasasında lisanssız elektrik üretimine i̇lişkin yönetmelik, (in turkish), retrieved from http://www.epdk.org.tr/index.php/elektrik-piyasasi/mevzuat?id=1292, accessed at april 8, 2014. etkb (2014a), electricity sector reform and privatization strategy paper, retrieved from http://www. enerji.gov.tr/yayinlar_raporlar/arz_guvenligi_strateji_belgesi.pdf, accessed at april 9, 2014. etkb (2014b), enerji, (in turkish), retrieved from http://www.enerji.gov.tr/index.php?dil=tr&sf= webpages&b=enerji&bn=215&hn=12&nm=384&id=384, accessed at april 9, 2014. karakus, r.s., (2013), lisanslı ve lisanssız hes projelerinde su kullanım hakları, (in turkish), november 28, 2013, yuzuncu yil universitesi prof. dr. cengiz andic kultur merkezi, van, turkey, retrieved from http://vansempozyum.org/program, accessed at april 12, 2014. teias (2014), installed capacity, retrieved from http://www.teias.gov.tr/yuktevziraporlari.aspx, (in turkish), accessed at september 29, 2014. yaniktepe, b., savrun, m.m., koroglu, t. (2013), "current status of wind energy and wind energy policy in turkey", energy conversion and management 72, 103-110. yegm (2014a), yenilenebilir enerji kaynaklarının elektrik enerjisi üretimi amaçlı kullanımına i̇lişkin kanun, retrieved from http://www.eie.gov.tr/yenilenebilir/document/yenilenebilir _enerji_kaynaklarinin_elektrik_enerjisi_uretimi_amacli_kullanimina_iliskin_kanun.pdf, (in turkish), accessed at april 14, 2014. yegm (2014b), yenilenebilir enerji, retrieved from http://www.eie.gov.tr/#, (in turkish), accessed at april 14, 2014. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. . international journal of energy economics and policy | vol 9 • issue 2 • 201940 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(2), 40-50. globalization, financial development, and environmental degradation in the presence of environmental kuznets curve: evidence from asean-5 countries le hoang phong school of public finance, university of economics ho chi minh city, vietnam. email: lhphong@hcmulaw.edu.vn received: 25 october 2018 accepted: 29 january 2019 doi: https://doi.org/10.32479/ijeep.7290 abstract asean is regarded as an economically dynamic region with notable policies towards economic openness, implying the encouragement of globalization and trade liberalization. considerable globalization and financial development processes, together with the incremental energy demand, necessitated the issue of controlling environmental damage. the main objective of this research is to evaluate the impacts of globalization and financial development, incorporating energy consumption, urbanization and gdp per capita, on carbon dioxide emissions with the presence of environmental kuznets curve (ekc) model for selected asean countries. from the author’s best knowledge and review of literature, there has been no study that only focuses on asean region, and this paper serves as the first one in the discipline. this research approaches the heterogeneity in the panel data over the 1971-2014 period by utilizing the fixed and random effects regression models. the author uses the tests based on durbin–hausman–wu statistic to determine the appropriate models. the findings indicate that (i) financial development, energy consumption and urbanization boost the carbon dioxide emissions; (ii) globalization as an aggregate measure significantly increases carbon dioxide emissions and the effect mainly comes from the economic globalization facet; (iii) the ekc hypothesis is underpinned in asean-5 countries. hence, this suggests crucial implications for policy-makers. keywords: globalization, financial development, carbon dioxide emission jel classifications: f64, o44, q56 1. introduction in recent years, the challenging concern of worsening global environmental quality has strongly manifested, which is clearly illustrated by the upward trend of co2 (carbon dioxide one of the main components of the greenhouse effect) in the atmosphere (as displayed in figure 1). albeit economists as well as policy-makers endeavored to explore and scrutinize the determinants of co2 emissions such as energy consumption, economic growth, financial development and urbanization by various national and international researches in order to support sustainable development policies, the results regarding the relationship between the aforementioned factors and environmental damage remain controversial (omri, 2013; stern, 2004; dinda, 2004; omri et al. 2015; shahbaz et al., 2015b; shahbaz et al., 2016b; dar and asif, 2017; phong et al., 2018). as an economically open and dynamic region, asean experiences rapid globalization process, especially economic globalization through trade and investment activities. the role of finance, namely the importance of credit in private sector, enhances economic activities of asean countries. lately, asean has been recognized as one of the top regions in the world by economic growth, which increases the incomes of member countries, fosters the living standards of their residents, and facilitates urbanization. this journal is licensed under a creative commons attribution 4.0 international license phong: globalization, financial development, and environmental degradation in the presence of ekc: evidence from asean-5 countries international journal of energy economics and policy | vol 9 • issue 2 • 2019 41 the intense globalization and financial development progresses, along with the upsurge in energy demand for economic activities, induce substantially higher co2 emissions. thus, the scrutiny of environmental quality with the presence of financial development, globalization, and urbanization necessitates special attentions. moreover, it is essential that variable omission is avoided so as to gain accurate findings when investigating the existence of ekc hypothesis (pata, 2018). the major goal of this paper is to scrutinize the effects of globalization, financial development, energy consumption, urbanization and gdp per capita on carbon dioxide emissions under a multivariate framework with the inclusion of environmental kuznets curve (ekc) model for selected asean countries. to the best of the author’s knowledge, this is the first research to examine the dynamic connections between energy consumption, gdp per capita, urbanization, and carbon dioxide emissions when incorporating globalization and financial development in case of asean countries, with the presence of ekc hypothesis. the rest of this article consists of 5 parts and is organized in the following order: the “literature review” part stresses the ekc hypothesis as well as relevant researches that form the basis for subsequent analyses; “materials and methods” illuminates the variables, estimation model and econometric methodology utilized in this study; “results” gives explanation to the findings; “discussion” provides arguments and further information; and finally, the “conclusions” part contains important summary of this paper with the inclusion of policy implications drawn from the empirical results. 2. literature review the last several decades witnessed the strong development of economic activities which raised concerns for their impacts on the environment at both national and international levels. the link between economic growth and environmental quality has drawn considerable attentions since grossman and krueger (1991) proposed the environmental kuznets curve (ekc) hypothesis which assumes that economic growth positively influences co2 emissions in the beginning stage, but the effect is negative in the subsequent stage after the co2 emissions reaches the maximum level connected with a certain amount of income per capita. such movement of co2 emissions is described by the inverted u-shaped environmental kuznets curve indicated in figure 2. following grossman and krueger (1991), many a research focused on testing the environmental kuznets curve (ekc) hypothesis in different countries, and the results varied. the ekc hypothesis is underpinned by notable studies for a large number of countries including lindmark (2002) for sweden; ang (2007) for france; jalil and mahmud (2009) for china; ghosh (2010), jayanthakumaran et al. (2012) for india and china; nasir and rehman (2011), ahmed and long (2012), javid and sharif (2016) for pakistan; saboori et al. (2012) for malaysia; alam et al. (2012) for bangladesh; baek and kim (2013) for south korea; shahbaz et al. (2014) for tunisia; ahmed (2014) for mongolia; baek (2015) for iceland; shahbaz et al. (2015a) for portugal; tang and tan (2015) for vietnam; zambrano-monserrate et al. (2016) for ecuador; balaguer and cantavella (2016) for spain; al-mulali et al. (2016) for kenya; bento and moutinho (2016) for italy; ahmad et al. (2017) for croatia; ozturk and acaravci (2013), yavuz (2014), gokmenoglu and taspinar (2016), ozatac et al. (2017), pata (2018) for turkey; cole et al. (1997) for 7 countries; halkos (2003) for oecd and non-oecd countries; apergis and payne (2009) for central america; cho et al.(2014) for oecd; pao and tsai (2011), sinha and sen (2016) for brics; farhani et al. (2014) for 10 mena countries; kasman and duman (2015) for european countries; zaman et al. (2016) for 34 developed and developing countries; zhang et al. (2017) for 10 newly industrialized countries (nics-10). on the contrary, the ekc hypothesis is not supported by torras and boyce (1998), roca et al. (2001) for spain; day and grafton (2003) for canada; chebbi (2009), fodha and zaghdoud (2010) for tunisia; pao et al. (2011) for russia; du et al. (2012) for china; pal and mitra (2017) india and china; arouri et al. (2012) for 12 middle east and north african countries; giovanis (2013) for united kingdom; ozcan (2013) for 12 mena countries; wang et al. (2013) for 150 nations; farhani and ozturk (2015) for tunisia; lacheheb et al. (2015) for algeria; begum et al. (2015) for malaysia; mallick and tandi (2015), rehman and rashid (2017) for saarc countries; bento and moutinho (2016) for italy; maría and jesús (2016) for 22 latin american and caribbean countries; neve and hamaide (2017) for 28 countries; zoundi (2017) 25 african countries. the rapid economic growth process requires more energy consumption, hence damaging the environment (islam et al., 2013; zhang and cheng, 2009; shahbaz et al., 2016a; shahbaz et al., 2017a). manifold studies tested the environmental kuznets curve (ekc) hypothesis with the influence of energy consumption. for instance, pao and tsai (2010) examined the impacts of energy consumption, economic growth on co2 emissions and concurrently verified the ekc hypothesis in bric countries in the 1971-2005 period; and the outcomes confirmed the existence of the ekc hypothesis and denoted that energy consumption and economic growth were main factors raising co2 emissions. jaunky (2011) analyzed 36 high-income countries from 1980 to 2005 and found that energy consumption boosted co2 emissions; also, ekc was evidenced in greece, malta, portugal, oman, and figure 1: atmospheric co2 levels source: author’s calculations. data is collected from https://climate. nasa.gov/vital-signs/carbon-dioxide. phong: globalization, financial development, and environmental degradation in the presence of ekc: evidence from asean-5 countries international journal of energy economics and policy | vol 9 • issue 2 • 201942 united kingdom. shahbaz et al. (2014) applied ardl approach and vecm granger causality tests and detected the occurrence of ekc in tunisia in 1971-2010 period, together with the positive effects of energy consumption on co2 emissions. rehman and rashid (2017) inspected the role of energy consumption on environmental damage under multivariate analysis in saarc countries and indicated that energy consumption degraded the environment; also, the presence of ekc was affirmed. recently, besides energy consumption, a large number of researchers have tested the ekc hypothesis based on the link between economic growth and environmental quality with the inclusion of some important factors such as financial development, globalization and urbanization. tamazian et al. (2009) scrutinized the connections between financial development, economic development and co2 emissions in bric countries during 1992 and 2004 and proved the evidence of ekc as well as the negative cause of financial development on co2 emissions. shahbaz et al. (2013b) employed ardl and ecm approach over the 1965–2008 period to witness the occurrence of ekc; in addition, they found that financial development and economic development respectively reduced and stimulated co2 emissions. ozturk and acaravci (2013) reported no link between financial development and co2 emissions in turkey from 1960 to 2007, but the proof of ekc was detected. shahbaz et al. (2013a) included energy intensity, economic growth and globalization in their study using annual data of turkey from 1970 to 2010 and applied ardl and vecm granger causality approach; they observed the presence of ekc and noted that energy intensity and economic growth made co2 emissions rise but globalization had opposite effect. boutabba (2014) studied the long-run equilibrium between co2 emissions, financial development, economic growth, energy consumption and trade openness for the case of india and found the evidence of the long-run and causal relationships between co2 emissions, financial development, income, energy use and trade openness in which financial development and energy use increased co2 emissions; also, ekc was discovered. shahbaz et al. (2015b) showed that globalization, energy consumption, financial development, and economic growth exacerbated the environmental quality of india from 1970 to 2012 and observed that ekc occurred in india. farhani and ozturk (2015) rejected the ekc hypothesis in tunisia but concluded that all variables (real gdp, energy consumption, financial development, trade openness and urbanization) contributed to environmental pollution in the period 1971-2012. al-mulali et al. (2015) studied the connections of economic growth, urbanization, trade openness, financial development and renewable energy on pollution in 23 european countries during the period 1990-2013 and discovered the positive influence of gdp growth, urbanization and financial development on co2 emissions, while trade openness has negative one. shahbaz et al. (2016b) assessed the asymmetric impacts of financial development on environmental quality in pakistan from the first quarter of 1985 to the last quarter of 2014 and concluded that ineffective use of energy aggravated the environmental quality; additionally, financial development based on banks worsened the environment. javid and sharif (2016) inspected the roles of financial development, energy consumption, economic growth in co2 emissions in pakistan employing ardl method on 1972-2013 data and identified the ekc pattern as well as acknowledged that the higher levels of financial development, energy consumption and economic growth led to the greater co2 emissions. dogan and turkekul (2016) found no sign of ekc in united states; moreover, they reported that trade activities promoted the environmental quality while energy consumption, urbanization damaged the environment and financial development had insignificant effect. dogan and seker (2016) spotted the ekc trace in oecd countries associated with the positive causal relationship between energy consumption and co2 emissions, whereas openness and financial development decreased co2 emissions. solarin et al. (2017) pointed out the detrimental effects of financial development, urbanization, energy consumption and economic growth on the environmental quality in ghana during 1980 and 2012. saidi and mbarek (2017) conducted the study for emerging countries and found no evidence of the inverted u-shaped ekc; rather, they observed that financial development and urbanization enhance environmental quality while income facilitates co2 emissions. xing et al. (2017) utilized the stirpat model and ardl approach for the case of china and indicated that financial development could contribute to the escalation in co2 emissions. dar and asif (2017) realized no relationship between economic growth and environmental quality in india but witnessed the harmful impacts of financial sector development and energy consumption on greenhouse gas emissions. salahuddin et al. (2017) demonstrated the positive response of co2 emissions in kuwait during the period 1980-2013 under the effects of economic growth, electricity consumption, foreign direct investment and financial development by using ardl approach and vecm granger causality analysis. recently, shahbaz et al. (2017b) gauged the response of co2 emissions to the changes of globalization level by incorporating energy consumption and economic growth in japan from 1970 to 2014, which denoted that globalization, economic growth and energy consumption positively induced co2 emissions. twerefou et al. (2017) examined the ekc hypothesis in 36 sub-saharan figure 2: environmental kuznets curve phong: globalization, financial development, and environmental degradation in the presence of ekc: evidence from asean-5 countries international journal of energy economics and policy | vol 9 • issue 2 • 2019 43 africa and scrutinized the influences of economic growth and globalization on environmental quality from 1990 to 2013 with the application of gmm method for panel data, which demonstrated the beneficial effect and negative impact of economic growth and globalization on the environment respectively and concluded the occurrence of ekc. zhang et al. (2017) tested the ekc hypothesis in 10 newly industrialized countries (nics-10) from 1971 to 2013 and proved its existence; in addition, they found the trade openness substantially reduced co2 emissions while real gdp and primary energy consumption stimulated the emissions. haseeb et al. (2018) confirmed the existence of ekc phenomenon in brics countries and reported no significant causality between globalization, urbanization and co2 emissions while energy consumption and financial development degraded the environment quality. phong et al. (2018) scrutinized the roles of globalization in co2 emissions of vietnam from 1985 to 2015 by incorporating industrialization, urbanization, energy consumption and gdp per capita with the application of ardl method, which indicated that energy consumption, industrialization and gdp per capita boosted co2 emissions in the long run while globalization demonstrated negative effect. in general, it can be witnessed from the existing literature that the findings concerning co2 emissions and its determinants are not uniform; rather, they depend on the unique characteristics of each country or region. in this study, the author inspects the dynamic connections between energy consumption, gdp per capita, urbanization and co2 emissions in the presence of ekc hypothesis for asean countries by including the analyses of globalization and financial development as important factors in economic openness. 3. data and econometric methodology 3.1. data this paper employs balanced panel data from 1971 to 2014 for analyzing the impacts of financial development and globalization on environmental degradation as well as testing the ekc effect in some asean countries including myanmar, malaysia, philippines, singapore and thailand. the time range is limited by the availability of the data. there are 6 variables used in this study: co2 emissions, financial development, globalization, gdp per capita, energy consumption and urbanization. the aforementioned variables (except globalization) are collected from world development indicators. meanwhile, globalization is retrieved from kof globalisation index provided by kof swiss economic institute. the kof globalisation index was proposed by dreher (2006) and revised by dreher et al. (2008); it consists of three dimensions of globalization: economic, social and political. the first dimension of globalization (economic) reflects flows of goods, capital and services as well as information and perceptions that accompany market exchanges. the second aspect of globalization (social) captures the spread of ideas, information, images and people. the final component of globalization (political) entails the diffusion of policies (nye and donahue, 2000). in this article, the author will utilize the aggregate measure of globalization together with each individual component measure. besides, private sector credit is used as a proxy for gauging the level of financial development (salahuddin et al., 2017). all variables are converted into natural logarithm to interpret elasticities of the coefficient estimates. table 1 provides information regarding the variables and their sources. the descriptive statistics of variables are demonstrated in table 2. 3.2. econometric methodology in order to assess the impacts of globalization and financial development as well as verify the occurrence of ekc for some asean countries, the author employs the co2 emissions functions based on shahbaz et al. (2015b), phong et al. (2018), and haseeb et al. (2018) as follows: co2=f(gdp, gdp2, ec, fd, urb, kof) (1) co2=f(gdp, gdp2, ec, fd, urb, kofe) (2) co2=f(gdp, gdp2, ec, fd, urb, kofs) (3) co2=f(gdp, gdp2, ec, fd, urb, kofp) (4) where, co2 stands for co2 emissions per capita; gdp denotes gdp per capita computed at the constant price (2010us$); gdp2 means the square of gdp; ec reflects primary energy consumption per capita; fd demonstrates financial development; urb is the urban population share of the total population (%); kof represents the overall globalization index; kofe stands for the economic dimension of globalization; kofs symbolizes the social aspect of globalization; and kofp is the political component of globalization. according to shahbaz et al. (2016b), dar and asif (2018), when all variables are transformed to natural logarithm, the log-linear regression equation can smooth out the dynamics of time-series and produce reliable estimations. the equations (1), (2), (3) and (4) can be converted into the log-linear form as follows: lc lgdp lgdp lec lfd lurb lk it it it it it it o2 = + + + + + + α α α α α α α 0 1 2 2 3 4 5 6 oofit it+ε (5) lc lgdp lgdp lec lfd lurb lk it it it it it it o2 = + + + + + + β β β β β β β 0 1 2 2 3 4 5 6 oofeit it+ µ (6) lc lgdp lgdp lec lfd lurb lk it it it it it it o2 = + + + + + + χ χ χ χ χ χ χ 0 1 2 2 3 4 5 6 oofsit it+ν (7) lc lgdp lgdp lec lfd lurb lk it it it it it it o2 = + + + + + + δ δ δ δ δ δ δ 0 1 2 2 3 4 5 6 oofpit it+π (8) where l stands for the natural logarithm; i indicates the number of countries; t represents the number of periods; α0; β0; χ0; δ0 are phong: globalization, financial development, and environmental degradation in the presence of ekc: evidence from asean-5 countries international journal of energy economics and policy | vol 9 • issue 2 • 201944 the intercepts; α β χ δk k k k k k k k= = = =( ) ( ) ( ) ( )16 16 16 16, , , ,; ; ; are regression coefficients of the explanatory variables; and εit; µit; vit; πit illustrate the error terms. under the ekc hypothesis, the signs of α1 and α2 are expected to be positive and negative respectively in order to reflect the inverted u-shaped pattern. similarly, the former coefficient in each of the three pairs β1 and β2, χ1 and χ2, δ1 and δ2 is expected to be positive while the latter’s is negative. to estimate the above regression models, the author considers the following general panel data regression model: y xit it it= + +ρ ρ ω0 1 (9) the error terms (ωit ) in equation (9) involves all unobserved factors possibly affect the dependent variable over time and crosssectionally. when the unobserved effect equals zero, both unique characteristics between entities and general effects over time are absent, thus enabling the application of pooled ols estimation method. nevertheless, if it is different from 0 or there exists heterogeneity, the ols estimator is no longer best linear unbiased estimator for equation (9), and therefore, fixed effects model and random effect model are considered to be used. consequently, equation (9) can be rewritten as follows: y x uit it i it= + + +ρ ρ λ0 1 (10) where λi represents the unobservable time-invariant factors; µit is the remainder error changing over time and entities. it is of vital importance that one must identify whether λi correlates with the regressors in the model (mundlak, 1978). in case the time-invariant factors correlate with the regressors, they must be treated as independent variables and cannot be considered as error term; accordingly, the fixed effects model is appropriately utilized and equation (10) becomes fixed effects model where λi is the intercept indicating the unique characteristics of the countries (stock and watson, 2014). if the time-invariant factors do not correlate with the regressors, they can be regarded as composite error (maki, 2011). in this article, the author will estimate 04 fixed effects models denoted as (i), (ii), (iii) and (iv) as well as 04 random effect models denoted as (v), (vi), (vii) and (viii). they are listed as follows: model (i): lc lgdp lgdp lec lfd lurb lk it it it it it it o2 = + + + + + + α α α α α α α 0 1 2 2 3 4 5 6 oofit i i it+ +α ε ε ' (11) model (ii): lc lgdp lgdp lec lfd lurb lk it it it it it it o2 = + + + + + + β β β β β β β 0 1 2 2 3 4 5 6 oofeit i i it+ +β µ µ ' (12) model (iii): lc lgdp lgdp lec lfd lurb lk it it it it it it o2 = + + + + + + χ χ χ χ χ χ χ 0 1 2 2 3 4 5 6 oofsit i i it+ +χ ν ν ' (13) model (iv): lc lgdp lgdp lec lfd lurb lk it it it it it it o2 = + + + + + + δ δ δ δ δ δ δ 0 1 2 2 3 4 5 6 oofpit i i it+ +δ π π ' (14) model (v): lc lgdp lgdp lec lfd lurb lk it it it it it it o2 = + + + + + + α α α α α α α 0 1 2 2 3 4 5 6 oofit it it+ + +α τ ε ' (15) model (vi): lc lgdp lgdp lec lfd lurb lk it it it it it it o2 = + + + + + + β β β β β β β 0 1 2 2 3 4 5 6 oofeit it it+ + +β υ µ ' (16) table 1: variable description and sources variable name symbol description unit data source carbon dioxide emissions co2 carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring. metric tons per capita world development indicators economic growth gdp the gross domestic product by the midyear population (gdp per capita) constant 2010 us dollars world development indicators energy consumption ec it comprises petroleum products, natural gas, electricity, and combustible renewable and waste. kg of oil equivalent per capita world development indicators financial development fd the domestic credit to the private sector % of gdp world development indicators urbanization urb urban population refers to the number of people living in urban areas of a country total urban population, % world development indicators globalization kof includes economic globalization (kofe), social globalization (kofs), and political globalization (kofp) index (from 0 to 100) kof swiss economic institute source: author’s collection https://www.kof.ethz.ch/en/ https://www.kof.ethz.ch/en/ phong: globalization, financial development, and environmental degradation in the presence of ekc: evidence from asean-5 countries international journal of energy economics and policy | vol 9 • issue 2 • 2019 45 model (vii): lc lgdp lgdp lec lfd lurb lk it it it it it it o2 = + + + + + + χ χ χ χ χ χ χ 0 1 2 2 3 4 5 6 oofsit it it+ + +χ φ ν ' (17) model (viii): lc lgdp lgdp lec lfd lurb lk it it it it it it o2 = + + + + + + δ δ δ δ δ δ δ 0 1 2 2 3 4 5 6 oofpit it it+ + +δ η π ' (18) where α; β; χ; δ are the intercepts for all countries and τit; υit; ϕit; ηit are the within entity (country) error and ' ; ' ; ' ; 'it it it it    are the between entity (country error). the durbin–hausman–wu test (also known as hausman test) is necessary for verifying which of the fixed effects model or the random effect model is more effective (hausman, 1978). the hypothesis h0 of hausman test for judging the fixed effects model against the random effect model assumes that there is no correlation between the unobservable time-invariant factors and the explanatory variables. the alternative hypothesis h1 assumes that the aforesaid correlation occurs. if h0 is rejected, the fixed effects model is more effective and more pertinent than the random effects model. if h0 cannot be rejected, the latter model is preferred. the order of computing the two estimators can be reversed, and hence, the aforementioned hypotheses and conclusions about them can be inverted in the hausman test. 4. results and discussion 4.1. results the author runs both fixed effects model (fe) and random effects model (re) on balanced panel data. after that, the hausman test is used to choose appropriate model as a basis for estimation. next, the durbin–wu–hausman test is implemented to determine whether fixed effects model (fe) or random effects model (re) is more effective (tables 3 and 4). when the null hypothesis is rejected, the fe model is more proper for further estimation and analysis. nonetheless, the re model should be selected if the null hypothesis cannot be rejected. table 5 summarizes the durbin– wu–hausman test results. from table 5, regarding the two models (i) and (v), the null hypothesis is rejected (as evidenced by both p-value and chisquared value), thus the re model (i) is more effective. concerning the pair of models (ii) and (vi), h0 is also rejected and re model (vi) is chosen. next, similarly, the re model (vii) is more preferable than the fe model (iii). finally, the fe model (iv) is better than the re model (viii). the model analysis result is indicated in table 6 as follows.t ab le 2 : d es cr ip ti ve s ta ti st ic s of v ar ia bl es c ou nt ry st at is ti cs c o 2 g d p e c f d u r b k o f k o f e k o f s k o f p m ya nm ar m ea n± sd 0. 18 5± 0. 05 7 40 3. 38 8± 31 7. 66 2 28 5. 41 4± 20 .5 34 6. 35 1± 2. 80 6 26 .3 80 ±2 .9 96 26 .5 71 ±3 .8 48 36 .8 34 ±4 .0 83 12 .4 1± 5. 13 2 28 .8 63 ±6 .8 42 m al ay si a m ea n± sd 4. 32 6± 2. 26 7 56 10 .9 10 ±2 48 2. 24 4 16 09 .2 36 ±7 96 .2 41 90 .2 45 ±3 8. 36 6 53 .8 30 ±1 2. 38 6 65 .0 96 ±1 0. 39 8 62 .7 41 ±6 .2 74 64 .9 09 ±1 1. 19 0 67 .6 37 ±1 4. 17 3 ph ili pp in es m ea n± sd 0. 79 8± 0. 12 3 16 67 .7 17 ±2 87 .5 01 45 5. 86 2± 25 .2 79 29 .5 04 ±8 .7 34 43 .6 00 ±4 .9 92 49 .4 94 ±1 1. 38 3 44 .9 44 ±9 .8 29 36 .1 67 ±1 1. 70 0 67 .3 70 ±1 4. 23 3 si ng ap or e m ea n± sd 11 .4 67 ±2 .8 52 26 26 6. 35 0± 13 61 5. 26 0 38 38 .2 43 ±1 63 6. 90 3 85 .0 92 ±1 9. 80 2 10 0. 00 0± 0. 00 0 73 .6 96 ±7 .6 31 88 .1 48 ±4 .5 36 74 .7 42 ±7 .3 49 58 .2 65 ±1 1. 54 5 t ha ila nd m ea n± sd 2. 20 1± 1. 39 2 29 05 .4 41 ±1 48 7. 51 9 95 7. 86 8± 52 2. 85 5 84 .4 98 ±4 1. 66 0 31 .7 87 ±7 .3 08 50 .7 44 ±1 2. 73 6 46 .0 57 ±1 2. 16 3 40 .6 90 ±1 3. 14 1 65 .4 83 ±1 3. 22 2 so ur ce : a ut ho r’ s ca lc ul at io ns phong: globalization, financial development, and environmental degradation in the presence of ekc: evidence from asean-5 countries international journal of energy economics and policy | vol 9 • issue 2 • 201946 4.2. discussion from table 6, financial development positively impacts co2 emissions, which is analogous to the findings of boutabba (2014) and shahbaz et al. (2015b) for india; farhani and ozturk (2015) for tunisia; al-mulali et al. (2015) for europe; javid and sharif (2016), shahbaz et al. (2016b) for pakistan; salahuddin et al. (2017) for kuwait; solarin et al. (2017) for ghana; xing et al. (2017) for china; and haseeb et al. (2018) for brics economies. this implies that financial development probably promotes the development of new projects and activities which in turn boost energy consumption, hence increasing co2 emissions (javid and sharif, 2016). accordingly, governments of asean countries should discourage money lent to inefficientenergy-consuming activities or projects that potentially harm the environment. also, financial institutions are recommended to allocate more financial resources to “green” or environmentally friendly projects. the aggregate measure of globalization accelerates co2 emissions in asean countries when 1% increase in the overall lkof causes around 0.335% rise in lco2. the economic dimension of globalization (lkofe) also raises lco2 by nearly 0.344% for each 1% increase, which signifies that economic activities under globalization exacerbates the environmental quality. the social aspect (lkofs) and political facet (lkofp) of globalization respectively had negative (–0.0990) and positive (0.0751) coefficients, yet their impacts on co2 emissions are small and statistically insignificant. it can be argued that globalization, especially the economic dimension, reduces trade and investment barriers, which in turn expands economic activities and aggravates the environmental quality. this is in line with the findings of cole (2004), shandra et al. (2009), shahbaz et al. (2015b), farhani and ozturk (2015), ertugrul et al. (2016), and shahbaz et al. (2017a; 2017b) when incremental trade activities produce the scale effect that precipitates pollution. as a consequence, the governments play a vital role in improving table 3: regression results with fixed effects model (i) (ii) (iii) (iv) dependent variable lco2 lco2 lco2 lco2 lgdp 2.246*** (12.95) 2.287*** (12.98) 2.086*** (11.55) 2.238*** (12.69) lgdp2 –0.166*** (–13.76) –0.164*** (–13.62) –0.158*** (–13.20) –0.164*** (–12.79) lec 1.133*** (13.39) 1.091*** (12.96) 1.152*** (13.47) 1.115*** (12.48) lfd 0.180*** (4.34) 0.178*** (4.19) 0.195*** (4.83) 0.202*** (4.91) lurb 0.201 (1.19) 0.293* (1.85) 0.238 (1.50) 0.384** (2.27) lkof 0.335** (2.55) lkofe 0.217** (2.09) lkofs 0.240*** (2.77) lkofp 0.0751 (0.51) const –16.95*** (–22.96) –17.00*** (–22.48) –16.09*** (–21.81) –16.69*** (–21.34) n 220 220 220 220 r2 0.8738 0.9130 0.8842 0.8950 f (6, 209) 228.81 226.20 230.25 221.18 prob>f 0.0000 0.0000 0.0000 0.0000 *p<0.10, **p<0.05, ***p<0.01. source: author’s calculation table 4: regression results with random effects model (v) (vi) (vii) (viii) dependent variable lco2 lco2 lco2 lco2 lgdp 1.967*** (10.21) 1.711*** (9.13) 1.767*** (7.21) 2.347*** (14.73) lgdp2 –0.121*** (–9.64) –0.105*** (–8.50) –0.109*** (–7.30) –0.140*** (–13.54) lec 1.007*** (11.51) 0.897*** (9.51) 0.969*** (10.61) 0.868*** (12.03) lfd 0.294*** (5.70) 0.179*** (3.52) 0.216*** (4.20) 0.359*** (8.62) lurb 0.921*** (8.77) 0.535*** (4.31) 0.738*** (7.09) 0.695*** (8.94) lkof –0.725*** (–4.55) lkofe 0.344** (2.27) lkofs –0.0990 (–0.86) lkofp –0.871*** (–11.44) const –15.81*** (–17.76) –16.40*** (–17.05) –16.24*** (–15.07) –15.41*** (–20.99) n 220 220 220 220 r2 0.9704 0.9683 0.9677 0.9799 wald χ2 (6) 6990.40 6511.26 6375.55 10390.09 prob>χ2 0.0000 0.0000 0.0000 0.0000 *p<0.10, **p<0.05, ***p<0.01. source: author’s calculation table 5: results of durbin – wu – hausman test model (i) (v) (ii) (vi) (iii) (vii) (iv) (viii) fe re fe re fe re fe re hausman test1 fe and re re and fe re and fe fe and re χ2 1394.26 2687.36 349.94 80.63 prob>χ2 0.0000 0.0000 0.0000 0.0000 fe is the fixed effects model; re is the random effects model. 1 the order of computation and storage in stata 15 for the hausman test phong: globalization, financial development, and environmental degradation in the presence of ekc: evidence from asean-5 countries international journal of energy economics and policy | vol 9 • issue 2 • 2019 47 economic conditions, achieving globalization benefits and sustainably protecting the environment. energy consumption (lec) stimulates co2 emissions by approximately 1.133% for each 1% rise. this is not dissimilar to pao and tsai (2010) and haseeb et al. (2018) for brics countries; jaunky (2011) for 36 high-income countries; ozturk and acaravci (2013) for turkey; shahbaz et al. (2014), farhani and ozturk (2015) for tunisia; boutabba (2014) and shahbaz et al. (2015b) for india; javid and sharif (2016) for pakistan; dogan and seker (2016) for oecd countries; dogan and turkekul (2016) for usa; rehman and rashid (2017) for saarc countries; solarin et al. (2017) for ghana; shahbaz et al. (2017b) for japan; and phong et al. (2018) for vietnam. the aforementioned findings recommend that the governments of those countries necessitate some energy policies for sustainable development such as: promoting effective and efficient energy use, upgrading obsolete technology towards modernity and efficiency, researching and developing renewable energy and green energy sources and reducing the impacts of energy consumption on the environment. finally, the evidence of ekc is confirmed for asean-5 e c o n o m i e s . s p e c i f i c a l l y, g d p p e r c a p i t a m a k e s c o 2 emissions grow (as evidenced by the positive coefficient of lgdp exhibited in table 6) while the square of gdp per capita decreases co2 emissions (as denoted by the negative coefficient of lgdp2 displayed in table 6), which implies that the movement of co2 emissions follows the inverted u-shaped pattern of ekc hypothesis stating that co2 amount rises and then declines after gdp per capita reaches a certain level. this is consistent with cole et al. (1997) for 7 countries; halkos (2003) for oecd and non-oecd countries; apergis and payne (2009) for central america; jaunky (2011) for greece, malta, portugal, oman, and united kingdom; shahbaz et al. (2013b) for south africa; farhani et al. (2014) for 10 mena countries; kasman and duman (2015) for european countries; cho et al. (2014), dogan and seker (2016) for oecd countries; zaman et al. (2016) for 34 developed and developing countries; twerefou et al. (2017) for 36 sub-saharan africa countries; zhang et al. (2017) for 10 newly industrialized countries (nics-10); pata (2018) for turkey; tamazian et al. (2009), pao and tsai (2010; 2011), sinha and sen (2016), haseeb et al. (2018) for brics countries. 5. conclusion the main objective of this study is to examine the relationship between globalization, financial development, energy consumption, economic growth, urbanization and co2 emissions in some asean countries with the presence of ekc hypothesis. the author employs panel data regression with the fixed effects and random effects models on annual data of 5 asean countries (myanmar, malaysia, philippines, singapore and thailand) over the period 1971-2014. the selection of pertinent models is implemented by durbin–wu–hausman test. empirical findings indicate several important results. first, financial development, energy consumption and urbanization have significantly positive connections with co2 emissions in the long run. second, globalization boosts co2 emissions in some asean countries, and the largest magnitude of impact comes from the economic dimension of globalization; meanwhile, social and political aspects of globalization insignificantly lowers and raises co2 emissions respectively. third, the evidence of ekc in asean-5 economies is affirmed. crucial implications can be recommended for the sampled asean countries. the governments necessitate policies that encourage firms and industries to use energy effectively and efficiently, upgrade technology or adopt new or environmentally friendly energy. the development of energy infrastructure requires both energy security and environmental protection. regarding the financial resources, the governments should promote the performance of projects that save energy and are harmless to the environment. a vital challenge for the governments is to sustainably control the environmental quality when the upsurge of globalization (especially economic dimension), trade and capital investment activities continues in this highly dynamic region of the world. besides, the reforms of institution, corruption, legal system and financial security control remain essential issues that need great attentions of asean policy-makers so as to foster globalization, financial development and energy security, which contributes to the sustainable development. table 6: results of empirical analysis independent variable dependent variable lco2 lco2 lco2 lco2 lgdp 2.246*** (12.95) 1.711*** (9.13) 1.767*** (7.21) 2.238*** (12.69) lgdp2 –0.166*** (–13.76) –0.105*** (–8.50) –0.109*** (–7.30) –0.164*** (–12.79) lec 1.133*** (13.39) 0.897*** (9.51) 0.969*** (10.61) 1.115*** (12.48) lfd 0.180*** (4.34) 0.179*** (3.52) 0.216*** (4.20) 0.202*** (4.91) lurb 0.201 (1.19) 0.535*** (4.31) 0.738*** (7.09) 0.384** (2.27) lkof 0.335** (2.55) lkofe 0.344** (2.27) lkofs –0.0990 (–0.86) lkofp 0.0751 (0.51) const –16.95*** (–22.96) –16.40*** (–17.05) –16.24*** (–15.07) –16.69*** (–21.34) n 220 220 220 220 r2 0.8738 0.9683 0.9677 0.8950 *p<0.10, **p<0.05, ***p<0.01. source: author’s calculation phong: globalization, financial development, and environmental degradation in the presence of ekc: evidence from asean-5 countries international journal of energy economics and policy | vol 9 • issue 2 • 201948 the limitation of this article entails inadequate data for all asean countries. future studies about this topic may have an advantage when the data for the whole asean region is available. besides, sources of energy consumption at disaggregated level as well as other proxies for environmental degradation will be the focuses of the author’s subsequent research. also, expanding the study to global level is a worthy attempt in future studies. 6. acknowledgments the author gratefully expresses the author’s gratitude for the financial support from the university of economics ho chi minh city, vietnam for this research. references ahmed, k. (2014), environmental kuznets curve for co2 emission in mongolia: an empirical analysis. management of environmental quality: an international journal, 25(4), 505-516. ahmed, k., long, w. (2012), environmental kuznets curve and pakistan: an empirical analysis. procedia economics and finance, 1, 4-13. alam, m.j., begum, i.a., buysse, j., huylenbroeck, g.v. (2012), energy consumption, carbon emissions and economic growth nexus in bangladesh: cointegration and dynamic causality analysis. energy policy, 45, 217-225. al-mulali, u., ozturk, i., lean, h.h. (2015), the influence of economic growth, urbanization, trade openness, financial development, and renewable energy on pollution in europe. natural hazards, 79(1), 621-644. al-mulali, u., solarin, s.a., ozturk, i. (2016), investigating the presence of the environmental kuznets curve (ekc) hypothesis in kenya: an autoregressive distributed lag (ardl) approach. natural hazards, 80(3), 1729-1747. ang, j.b. (2007), co2 emissions, energy consumption, and output in france. energy policy, 35(10), 4772-4778. apergis, n., payne, j.e. (2009), co2 emissions, energy usage, and output in central america. energy policy, 37(8), 3282-3286. arouri, m.e.h., youssef, a.b., m’henni, h., rault, c. (2012), energy consumption, economic growth and co2 emissions in middle east and north african countries. energy policy, 45, 342-349. baek, j. (2015), environmental kuznets curve for co2 emissions: the case of arctic countries. energy economics, 50, 13-17. baek, j., kim, h.s. (2013), is economic growth good or bad for the environment? empirical evidence from korea. energy economics, 36, 744-749. balaguer, j., cantavella, m. (2016), estimating the environmental kuznets curve for spain by considering fuel oil prices (1874-2011). ecological indicators, 60, 853-859. begum, r.a., sohag, k., abdullah, s.m.s., jaafar, m. (2015), co2 emissions, energy consumption, economic and population growth in malaysia. renewable and sustainable energy reviews, 41, 594-601. bento, j.p.c., moutinho, v. (2016), co2 emissions, non-renewable and renewable electricity production, economic growth, and international trade in italy. renewable and sustainable energy reviews, 55, 142-155. boutabba, m.a. (2014), the impact of financial development, income, energy and trade on carbon emissions: evidence from the indian economy. economic modelling, 40, 33-41. cho, c.h., chu, y.p., yang, h.y. (2014), an environment kuznets curve for ghg emissions: a panel cointegration analysis. energy sources, part b: economics, planning, and policy, 9(2), 120-129. cole, m.a. (2004), trade, the pollution haven hypothesis and the environmental kuznets curve: examining the linkages. ecological economics, 48(1), 71-81. cole, m.a., rayner, a.j., bates, j.m. (1997), the environmental kuznets curve: an empirical analysis. environment and development economics, 2(4), 401-416. dar, j.a., asif, m. (2017), is financial development good for carbon mitigation in india? a regime shift-based cointegration analysis. carbon management, 8(5-6), 435-443. dar, j.a., asif, m. (2018), does financial development improve environmental quality in turkey? an application of endogenous structural breaks based cointegration approach. management of environmental quality: an international journal, 29(2), 368-384. day, k.m., grafton, r.q. (2003), growth and the environment in canada: an empirical analysis. canadian journal of agricultural economics, 51(2), 197-216. dinda, s. (2004), environmental kuznets curve hypothesis: a survey. ecological economics, 49(4), 431-455. dogan, e., seker, f. (2016), an investigation on the determinants of carbon emissions for oecd countries: empirical evidence from panel models robust to heterogeneity and cross-sectional dependence. environmental science and pollution research, 23(14), 1464614655. dogan, e., turkekul, b. (2016), co2 emissions, real output, energy consumption, trade, urbanization and financial development: testing the ekc hypothesis for the usa. environmental science and pollution research, 23(2), 1203-1213. dreher, a. (2006), does globalization affect growth? evidence from a new index of globalization. applied economics, 38(10), 1091-1110. dreher, a., gaston, n., martens, p. (2008), measuring globalisationgauging its consequences. new york: springer. isbn 978-0-38774067-6. du, l., wei, c., cai, s. (2012), economic development and carbon dioxide emissions in china: provincial panel data analysis. china economic review, 23(2), 371-384. ertugrul, h.m., cetin, m., seker, f., dogan, e. (2016), the impact of trade openness on global carbon dioxide emissions: evidence from the top ten emitters among developing countries. ecological indicators, 67, 543-555. farhani, s., ozturk, i. (2015), causal relationship between co2 emissions, real gdp, energy consumption, financial development, trade openness, and urbanization in tunisia. environmental science and pollution research, 22(20), 15663-15676. farhani, s., shahbaz, m., sbia, r., chaibi, a. (2014), what does mena region initially need: grow output or mitigate co2 emissions? economic modelling, 38, 270-281. fodha, m., zaghdoud, o. (2010), economic growth and pollutant emissions in tunisia: an empirical analysis of the environmental kuznets curve. energy policy, 38(2), 1150-1156. ghosh, s. (2010), examining carbon emissions-economic growth nexus for india: a multivariate cointegration approach. energy policy, 38(6), 3008-3014. giovanis, e. (2013), environmental kuznets curve: evidence from the british household panel survey. economic modelling, 30, 602-611. gokmenoglu, k., taspinar, n. (2016), the relationship between co2 emissions, energy consumption, economic growth and fdi: the case of turkey. the journal of international trade and economic development, 25(5), 706-723. grossman, g., krueger, a. (1991), environmental impacts of a north american free trade agreement, national bureau of economics research working paper, no. 3194. cambridge: nber. halkos, g.e. (2003), environmental kuznets curve for sulfur: evidence using gmm estimation and random coeffcient panel data models. phong: globalization, financial development, and environmental degradation in the presence of ekc: evidence from asean-5 countries international journal of energy economics and policy | vol 9 • issue 2 • 2019 49 environment and development economics, 8(4), 581-601. haseeb, a., xia, e., danish, b.m.a., abbas, k. (2018), financial development, globalization, and co2 emission in the presence of ekc: evidence from brics countries. environmental science and pollution research, 25(31), 31283-31296. hausman, j.a. (1978), specification tests in econometrics. econometrica, 46(6), 1251-1271. islam, f., shahbaz, m., ahmed, a.u., alam, m. (2013), financial development and energy consumption nexus in malaysia: a multivariate time series analysis. economic modeling, 30, 435-441. jalil, a., mahmud, s.f. (2009), environment kuznets curve for co2 emissions: a cointegration analysis for china. energy policy, 37(12), 5167-5172. jaunky, v.c. (2011), the co2 emissions-income nexus: evidence from rich countries. energy policy, 39(3), 1228-1240. javid, m., sharif, f. (2016), environmental kuznets curve and financial development in pakistan. renewable and sustainable energy reviews, 54, 406-414. jayanthakumaran, k., verma, r., liu, y. (2012), co2 emissions, energy consumption, trade and income: a comparative analysis of china and india. energy policy, 42, 450-460. kasman, a., duman, y.s. (2015), co2 emissions, economic growth, energy consumption, trade and urbanization in new eu member and candidate countries: a panel data analysis. economic modelling, 44, 97-103. lacheheb, m., rahim, a.s.a., sirag, a. (2015), economic growth and carbon dioxide emissions: investigating the environmental kuznets curve hypothesis in algeria. international journal of energy economics and policy, 5(4), 1125-1132. lindmark, m. (2002), an ekc-pattern in historical perspective: carbon dioxide emissions, technology, fuel prices and growth in sweden 1870-1997. ecological economics, 42(1-2), 333-347. maki, a. (2011), introduction to estimating economic models. new york, usa: routledge, isbn 978-0-415-58986-4. mallick, l., tandi, s.m. (2015), energy consumption, economic growth, and co2 emissions in saarc countries: does environmental kuznets curve exist? the empirical econometrics and quantitative economics letters, 4, 57-69. maría, p.p., jesús, j.d. (2016), economic growth and energy consumption: the energy-environmental kuznets curve for latin america and the caribbean. renewable and sustainable energy reviews, 60, 1343-1350. mundlak, y. (1978), on the pooling of time series and cross section data. econometrica, 46(1), 69-85. nasir, m., rehman, f.u. (2011), environmental kuznets curve for carbon emissions in pakistan: an empirical investigation. energy policy, 39(3), 1857-1864. neve, m., hamaide, b. (2017), environmental kuznets curve with adjusted net savings as a trade-off between environment and development. australian economic papers, 56(1), 39-58. nye, j.s., donahue, n.d. (2000), governance in a globalizing world. washington, dc, usa: brookings institution press, isbn 978-0815-76407-6. omri, a. (2013), co2 emissions, energy consumption and economic growth nexus in mena countries: evidence from simultaneous equations models. energy economics, 40, 657-664. omri, a., daly, s., rault, c., chaibi, a. (2015), financial development, environmental quality, trade and economic growth: what causes what in mena countries. energy economics, 48, 242-252. ozatac, n., gokmenoglu, k.k., taspinar, n. (2017), testing the ekc hypothesis by considering trade openness, urbanization, and financial development: the case of turkey. environmental science and pollution research, 24(20), 16690-16701. ozcan, b. (2013), the nexus between carbon emissions, energy consumption and economic growth in middle east countries: a panel data analysis. energy policy, 62, 1138-1147. ozturk, i., acaravci, a. (2013), the long-run and causal analysis of energy, growth, openness and financial development on carbon emissions in turkey. energy economics, 36, 262-267. pal, d., mitra, s.k. (2017), the environmental kuznets curve for carbon dioxide in india and china: growth and pollution at crossroad. journal of policy modeling, 39(2), 371-385. pao, h.t., tsai, c.m. (2010), co2 emissions, energy consumption and economic growth in bric countries. energy policy, 38(12), 78507860. pao, h.t., tsai, c.m. (2011), multivariate granger causality between co2 emissions, energy consumption, fdi (foreign direct investment) and gdp (gross domestic product): evidence from a panel of bric (brazil, russia federation, india, and china) countries. energy, 36(1), 685-693. pao, h.t., yu, h.c., yang, y.h. (2011), modeling the co2 emissions, energy use, and economic growth in russia. energy, 36(8), 50945100. pata, u.k. (2018), the effect of urbanization and industrialization on carbon emissions in turkey: evidence from ardl bounds testing procedure. environmental science and pollution research, 25(8), 7740-7747. phong, l.h., van, d.t.b., bao, h.h.g. (2018), the role of globalization on carbon dioxide emission in vietnam incorporating industrialization, urbanization, gross domestic product per capita and energy use. international journal of energy economics and policy, 8(6), 275-283. rehman, m.u., rashid, m. (2017), energy consumption to environmental degradation, the growth appetite in saarc nations. renewable energy, 111, 284-294. roca, j., padilla, e., farre, m., galletto, c. (2001), economic growth and atmospheric pollution in spain: discussing the environmental kuznets curve hypothesis. ecological economics, 39(1), 85-99. saboori, b., sulaiman, j., mohd, s. (2012), economic growth and co2 emissions in malaysia: acointegration analysis of the environmental kuznets curve. energy policy, 51, 184-191. saidi, k., mbarek, m.b. (2017), the impact of income, trade, urbanization, and financial development on co2 emissions in 19 emerging economies. environmental science and pollution research, 24(4), 12748-12757. salahuddin, m., alam, k., ozturk, i., sohag, k. (2017), the effects of electricity consumption, economic growth, financial development and foreign direct investment on co2 emissions in kuwait. renewable and sustainable energy reviews, 81, 2002-2010. shahbaz, m., dube, s., ozturk, i., jalil, a. (2015a), testing the environmental kuznets curve hypothesis in portugal. international journal of energy economics and policy, 5(2), 475-481. shahbaz, m., jam, f.a., bibi, s., loganathan, n. (2016a), multivariate granger causality between co2 emissions, energy intensity and economic growth in portugal: evidence from cointegration and causality analysis. technological and economic development of economy, 22(1), 47-74. shahbaz, m., khraief, n., uddin, g.s., ozturk, i. (2014), environmental kuznets curve in an open economy: a bounds testing and causality analysis for tunisia. renewable and sustainable energy reviews, 34, 325-336. shahbaz, m., mallick, h., mahalik, m.k., loganathan, n. (2015b), does globalization impede environmental quality in india? ecological indicators, 52, 379-393. shahbaz, m., nasreen, s., ahmed, k., hammoudeh, s. (2017a), trade openness-carbon emissions nexus: the importance of turning points of trade openness for country panels. energy economics, phong: globalization, financial development, and environmental degradation in the presence of ekc: evidence from asean-5 countries international journal of energy economics and policy | vol 9 • issue 2 • 201950 61, 221-232. shahbaz, m., ozturk, i., afza, t., ali, a. (2013a), revisiting the environmental kuznets curve in a global economy. renewable and sustainable energy reviews, 25, 494-502. shahbaz, m., shahzad, s.j.h., ahmad, n., alam, s. (2016b), financial development and environmental quality: the way forward. energy policy, 98, 353-364. shahbaz, m., shahzad, s.j.h., kumar, m. (2017b), is globalization detrimental to co2 emissions in japan? new threshold analysis. mpra paper 82413. germany: university library of munich. shahbaz, m., tiwari, a.k., nasir, m. (2013b), the effects of financial development, economic growth, coal consumption and trade openness on co2 emissions in south africa. energy policy, 61, 1452-1459. shandra, j.m., leckband, c., london, b. (2009), ecologically unequal exchange and deforestation: a cross-national analysis of forestry export flows. organization and environment, 22(3), 293-310. sinha, a., sen, s. (2016), atmospheric consequences of trade and human development: a case of bric countries. atmospheric pollution research, 7(6), 980-989. solarin, s.a., al-mulali, u., musah, i., ozturk, i. (2017), investigating the pollution haven hypothesis in ghana: an empirical investigation. energy, 124, 706-719. stern, d.i. (2004), the rise and fall of the environmental kuznets curve. world development, 32(8), 1419-1439. stock, j.h., watson, m.w. (2014), introduction to econometrics. essex, uk: pearson, isbn 0133592693. tamazian, a., chousa, j.p., vadlamannati, k.c. (2009), does higher economic and financial development lead to environmental degradation: evidence from bric countries. energy policy, 37(1), 246-253. tang, c.f., tan, b.w. (2015), the impact of energy consumption, income and foreign direct investment on carbon dioxide emissions in vietnam. energy, 79, 447-454. torras, m., boyce, j.k. (1998), income, inequality, and pollution: a reassessment of the environmental kuznets curve. ecological economics, 25(2), 147-160. twerefou, d.k., danso-mensah, k., bokpin, g.a. (2017), the environmental effects of economic growth and globalization in sub-saharan africa: a panel general method of moments approach. research in international business and finance, 42, 939-949. wang, y., kang, l., wu, x., xiao, y. (2013), estimating the environmental kuznets curve for ecological footprint at the global level: a spatial econometric approach. ecological indicators, 34, 15-21. xing, t., jiang, q., ma, x. (2017), to facilitate or curb? the role of financial development in china’s carbon emissions reduction process: a novel approach. international journal of environmental research and public health, 14(10), 1222. yavuz, n.c. (2014), co2 emission, energy consumption, and economic growth for turkey: evidence from a cointegration test with a structural break. energy sources, part b: economics, planning, and policy, 9(3), 229-235. zaman, k., shahbaz, m., loganathan, n., raza, s.a. (2016), tourism development, energy consumption and environmental kuznets curve: trivariate analysis in the panel of developed and developing countries. tourism management, 54, 275-283. zambrano-monserrate, m.a., garcía-albán, f.f., henk-vera, k.a. (2016), bounds testing approach to analyze the existence of an environmental kuznets curve in ecuador. international journal of energy economics and policy, 6(2), 159-166. zhang, s., liu, x., bae, j. (2017), does trade openness affect co2 emissions: evidence from ten newly industrialized countries? environmental science and pollution research, 24(21), 1761617625. zhang, x.p., cheng, x.m. (2009), energy consumption, carbon emissions, and economic growth in china. ecological economics, 68(10), 2706-2712. zoundi, z. (2017), co2 emissions, renewable energy and the environmental kuznets curve, a panel cointegration approach. renewable and sustainable energy reviews, 72, 1067-1075. international journal of energy economics and policy vol. 2, no. 1, 2012, pp. 21-33 issn: 2146-4553 www.econjournals.com the contribution of energy consumption to climate change: a feasible policy direction usenobong f. akpan department of economics, university of uyo, nigeria. tel: +2348034130046. email: uakpan@yahoo.co.uk godwin e. akpan department of economics, university of uyo, nigeria. tel: +2348066801277. email: goddyakpan@yahoo.com abstarct: mitigating climate change is one of the biggest challenges that confront mankind in the present millennium. the problem has continued to dominate public debates in terms of its origin, sources, potential impacts and possibly adaptation strategies. in this paper, the contributions of energy to the climate change debate are explored. the analysis shows that since about 1850, the global use of fossil fuels (coal, oil and gas) has increased and dominated world energy consumption and supply. the rapid rise in fossil fuel combustion has produced a corresponding rapid growth in co2 emissions and accounts for over 80% of global anthropogenic green house gas emissions (ghgs) in 2008. it was shown that a substantial amount of co2 emissions still emanates from the increased use of heavy polluting fuel like coal by industrializing countries like the united states, japan and china. historically, the developed countries have contributed the most to cumulative global co2 emissions and still have the highest total historical emission. a disaggregated analysis indicates that two sectors of the economy, electricity and heat as well as the transport sector (majorly road transport), emit greater amounts of ghgs. some mitigation mechanisms have been suggested including improved energy efficiency, energy pricing reforms, imposition of carbon emission taxes, promoting investment in renewable energy technologies and creating public environmental awareness. keywords: climate change; fossil fuel; co2 emissions jel classifications: q40, q20, q32 1. introduction energy is and will continue to be a primary engine for economic development. it is central to achieving the goals of sustainable development. socio-economic development requires energy for improved living standards, enhanced productivity, effective transportation of goods to the point of need, and as inputs to a wide range of economic production activities. energy represents material comfort to industrialized countries, but the way to alleviation of poverty in developing countries. the three last centuries have seen mankind’s substantial dependence upon an ever-growing use of fossil fuels (coal, oil and gas) for industrialization and urbanization (cao, 2003; reddish and rand, 1996). however, the exploitation of energy to drive the growth process of many nations comes with increasing costs of environmental pollution. potentially, the most important environmental concern in the last decade relates to its impact on global change in weather, also known as global warming or the greenhouse effect. climate change is the long-term, significant change in the patterns, glaciations and related aspects of the global climate system. thousands of researchers and policy makers across the world have been piecing together an increasingly irrefutable case that climate change is an immediate threat to mankind’s survival and sustainable development. mitigating the impact of climate change has dominated most public discourse not only by environmental economists but also by other environmental experts and scientists. many experts attributed the root cause of climate change to human activities that comes with the rapid growth of the global economy including human consumption of different sources of energy, rapid rate of international journal of energy economics and policy, vol.2, no. 1, 2012, pp.21-33 22 deforestation and bush burning. the effects of energy consumption combustion are evaluated as greenhouse effects resulting from emissions of environmental pollutants such as carbon monoxide, hydrocarbon compounds, sulfur oxides, nitrogen oxides, methane and the particulates. amongst several pollutants causing climate change, a great deal of attention has been given to co2 emission as the major factor in the climate change. while the impact of other forms of air pollutants is primarily local or regional, co2 emissions are, above all else, global in scale. sources of co2 emission often cited in the literature include the energy related component, especially, the combustion of fossil fuels. others include the non-fuel use of energy inputs, and emissions from electricity generation using nonbiogenic municipal solid waste and geothermal energy, emissions from industrial processes, such as cement and limestone production, etc. this paper is concerned with the contribution of energy to the climate change debate. in this connection, some useful questions could be raised: to what extent is energy responsible for co2 emission? which form of energy is chiefly responsible for the energy-related climate change? what sectors of the economy drives these energy-related co2 emissions? what are the viable options for mitigating energy-related climate change? these and other similar questions are addressed in this paper. the structure of this paper is the following. in the next section, we undertake a brief review of the origin of the climate change debacle. next, we examine the role of energy to climate change. thereafter, we outline some policy options for mitigating climate change. the last section provides the conclusion to the paper. 2. climate change in historical perspective: how did we get here? the phrase “climate change” and “global warming” and more recently “global cooling” is increasingly assuming a topical dimension in global climatic and environmental discourse. rarely does a day go by without a mention in the press or on the radio of the possible causes of climate change and its consequences. the threat of climate change has come upon mankind in a relatively short space of time and is accelerating with an alarming speed. it is one of the most challenging problems with which our contemporary world has been faced. it has become a subject of major international co-operation through the intergovernmental panel on climate change (ipcc) which was set up in 1988 by the world meteorological organization (wmo) and the united nations environment programme. unfortunately, most climate change debate often lack historical perspective. to get a better sense of the problem, it might be instructive to pose the question: how did the world get to where they are today? according to girardet and mendonca (2009:26), the origin of climate change can be traced to the impact of human activities that started about 300 years ago. the authors argued that in 1709, the first blast furnace was built in coalbrookdale, shropshire, britain which used coke, derived from coal, rather than charcoal derived from wood, for smelting iron ore. the new coke-smelted iron proved to be superior in energy production as well as cheaper financial outlay, making coke-furnace melting process preferable to the charcoal-furnace process. crucially, it is argued that the inexpensive cast iron helped to trigger the start of the industrial revolution in britain – a self accelerating chain reaction of industrial and urban growth based on ever greater refinements in fossil-fuel-based technologies. the potential catastrophic environmental consequences of the ever-increasing use of coal were largely ignored. in 1711, the first steam engines, made with cast iron, started to pump water out of british mines that were up to 50 meters deep (girardet & mendonca, 2009:26). these pumping engines enable miners to dig ever deeper to extract minerals from the earth’s crust. furthermore, girardet and mendonca (2009:27) revealed that sixty years later: the firm of boulton & watt introduced the next generation of steam engines and by 1800 over 500 were in use, first in mines and then to drive machinery in factories. in 1830 steam locomotives were used to pull passenger trains for the first time, and in 1845 the first steampowered ship, the ss great britain, triggered a revolution in the mass transportation of goods and people across the oceans. the contribution of energy consumption to climate change: a feasible policy direction 23 it must be noted that until the early 18th century, muscles (human power), firewood and charcoal were the dominant sources of energy, augmented by the limited use of water and windmills, with human lifestyles dependent on living within nature’s productive capacity. but as the industrial revolution unfolded, the dramatic increase in the use of coal, and then oil and gas, not only massively increased human productive power and mobility but was also a major contributor to the ten-fold growth in human population, from some 700 million in 1709 to nearly 7 billion today (girardet and mendonca, 2009:27). the industrial revolution powered by an increased coal production in britain transformed the human presence on earth. it gave humanity unprecedented powers to exploit the riches of nature – cutting down forests, clearing new farmlands, accelerating industrial production, extending transportation systems, building new cities and expanding existing ones. by 1890s, the u.s. overtakes britain as the world’s leading industrial nation and has continued to spread across the world. today, japan, korea, brazil, mexico, venezuela, china, india and south africa are on their path to becoming major industrial nations in their own right. china’s industrial boom, for instance, is linked to a rapid increase in domestic energy consumption with millions of cars manufactured yearly. cars run on oil based fuels: by 2020 china is expected to import much of its oil. china’s coal consumption, mainly in power station, is going up in similar rate. according to the 1992 world bank projections, world population will more than double by 2150, with two thirds of the increase projected to occur by 2050 (world bank, 1992:70). high population growth and increased urbanization invariably will lead to increased demand for energy, implying increased expected environmental damage as well. 3. the role energy in the climate change debate worldwide economic growth and development require energy. the increased concentrations of key greenhouse gases (ghgs) are direct consequences of human activities. since anthropogenic ghgs accumulate in the atmosphere, they produce net warming by strengthening the natural “greenhouse effect”. specifically, energy production and consumption have various environmental implications, one of which is climate change. among the many human activities that produce ghgs, the use of energy represents by far the largest source of emissions as shown in figure 1. figure 1. shares of anthropogenic greenhouse-gas emissions in annex 1 countries, 20081. source: captured by authors from unfccc cited in iea (2010a) 1 annex i countries include australia, austria, belarus, belgium, bulgaria, canada, croatia, the czech republic, denmark, estonia, finland, france, germany, greece, hungary, iceland, ireland, italy, japan, latvia, liechtenstein, lithuania, luxembourg, monaco (included with france), the netherlands, new zealand, norway, poland, portugal, romania, russian federation, the slovak republic, slovenia, spain, sweden, switzerland, turkey, ukraine, the united kingdom and the united states. the countries that are listed above are included in annex i of the united nations framework convention on climate change as amended on 11 december 1997 by the 12th plenary meeting of the third conference of the parties in decision 4/cp.3. this includes the countries that were members of the oecd at the time of the signing of the convention, the eec, and fourteen countries in central and eastern europe and the former soviet union that are undergoing the process of transition to market economies. international journal of energy economics and policy, vol.2, no. 1, 2012, pp.21-33 24 as shown above, energy accounts for over 80% of the global anthropogenic ghgs, with emissions resulting from the production, transformation, handling and consumption of all kinds of energy commodities. the key information in fig. 1 is the fact that energy use emissions are predominantly responsible for co2 emissions. smaller shares correspond to agriculture, producing mainly ch4 and n2o from industrial processes not related to energy, producing mainly fluorinated gases and n2o. ghg emissions from the energy sector are dominated by the direct combustion of fuels, a process leading to large emissions of co2. a by-product of fuel combustion, co2 results from the oxidation of carbon in fuels (iea, 2010a)2. responsible for about 94% of the energy-related emissions, co2 from energy represents about 83% of anthropogenic ghg emissions for the annex 1 countries (fig. 1) and about 65% of global emissions (iea, 2010a). this percentage varies greatly by country because of diverse national energy structures and policies. a key factor responsible for the higher energy-related emissions cum climate change challenge is the increased global reliance on primary energy supply to drive economic growth and development. as illustrated in fig. ii, global total primary supply (tpes) doubled between 1971 and 2008, primarily relying on fossil fuels. in other words, fossil fuels still account for most of the world energy supply. the figure shows that in-spite of the growth of non-fossil energy (such as nuclear and hydropower) which are usually considered as non-polluting, fossil fuels have continue to maintain their dominance in tpes for the past 37 years under review. in 2008, it accounted for 81% of the tpes in the world. figure ii: world primary energy supply3 source: compiled by authors from iea (2010a). the high global dependence upon fossil fuels clearly is responsible for the observed upward trends in the global co2 emissions, as illustrated in fig. iii. since the industrial revolution, co2 emissions from fuel combustion have witnessed a dramatic increase from its near zero level in the 1870s (see quadrelli and peterson, 2007, iea, 2010a) to about 29.4 million tons by 2008 (fig. iii). the figure shows that co2 emissions from fossil fuels combustion in 2008 were roughly twice its level in 1971. depending, upon one’s forecast of the growth of fossil fuel combustion, one can project a doubling of the co2 concentration in the next 50 to 300 years. 2 in perfect combustion conditions, the total carbon content of fuels would be converted to co2 (see quadrelli & peterson, 2007). 3 figures include international bunkers. the contribution of energy consumption to climate change: a feasible policy direction 25 source: compiled by authors from iea (2010b). meanwhile, total global energy supply is projected to rise by 52% between 2008 and 2030 (iea, 2010a) and with fossil fuels remaining at 81% of tpes, co2 emissions are consequently expected to continue their growth unabated (unless some drastic measures are taken) and will reach 40.4 gt co2 by 2030 (ibid). the trend is expected to be intensified due to the projected high increase in world energy consumption demand by industrializing country like china (see fig. iv). presently, the figure shows that the united states still dominates world energy consumption followed by china and india and doubtless the higher emitters of co2 energy-related emissions (see fig. vi). it is projected that the shares of china in world energy consumption would outstrip that of the united states by the year 2020. whether the projections will be a possibility or not, it is obvious that the socio-economic and technological characteristics of development paths of the industrializing countries will strongly affects energy-related emissions and hence, the rate and magnitude of climate change, climate change impacts, the capability for adaptation and mitigation of climate change emissions. source: iea, international energy statistics database (as of november 2009), available at: www.eia.gov/emeu/international. international journal of energy economics and policy, vol.2, no. 1, 2012, pp.21-33 26 4. energy contribution to climate change: a further disaggregated analysis it may be important to further disaggregate the sources of energy-related co2 emissions. available data on the contribution of fuel to global co2 emissions as at 2008 is shown in fig. v. it can be seen that although coal represents only one-quarter of the world tpes in 2008, it accounted for 43% of the global co2 emissions due to its heavy carbon content per unit of energy released. compared to gas, coal is on the average nearly as twice emission intensive4. without additional measures the supply of coal is projected to grow from 2775 million tons of oil equivalent (mtoe) in 2004 to 4441 mtoe in 2030 (quadrelli and peterson, 2007). in the future, coal is therefore expected to satisfy much of the growing energy demand of emerging developed countries like china and india, where energyintensive industrial production is growing rapidly and large coal reserves exist with limited reserves of other energy sources (quadrelli and peterson, 2007). in addition, in spite of the deplorable environmental consequences, coal’s appeal may rise as prices of oil and natural gas increase, consequent to growing demand and pressure on the reserves of these two fuels. this will further worsen the environmental pollution. figure v: world primary energy supply and co2 emissions: shares by fuel type in 2008. source: compiled by authors from iea (2010a). note: others include nuclear, hydro, geothermal, solar, tide, wind, combustible renewable and waste. figure vi shows the contributions of the four largest carbon emitters in the world between 1971 and 2008. although the united states remained the largest co2 emitter up to 2007, its contribution is relatively stable over time. however, the rate at which it grows in india and in particular china is worrisome. in fact, china overtook the united states in 2007 as the world’s largest annual emitter of energy-related co2, although as shown by iea (2010a) the united states will still remains the largest in many years to come in terms of cumulative and per capita terms (see further evidence in table1). in other words, it has been argued that china’s emission rate of co2 is important to significantly affect world indicators. quadrelli and peterson (2007) have shown that the rise in china’s per capita emissions (+17%) causes global emissions to rise by 4%. it is important to note that fossil fuels represents more than 80% of china’s energy mix; the country draws more than 60% of its energy supply from coal alone (iea, 2010a). fig. vii which presents the historical trends in the energy mix and their consequent contribution to the present global change debacle is very illuminating on this. some points are clear from the figure. first, the united states, through the use of coal in the early 19th century, contributed the largest emission to the current problem. during the 20th century, it is also evident that a substantial amount of co2 emissions still emanates from the increased use of coal by the united states, japan and china. it is also confirmed that china’s heavy reliance on coal is 4 see further evidence in iea (2010a) for the ipcc default carbon emissions factors from the 1996 ipcc guidelines which are 15.3 t c/tj for gas, 16.8 to 27.5 t c/tj for oil products and 25.8 to 29.1 t c/tj for primary products. the contribution of energy consumption to climate change: a feasible policy direction 27 responsible for most of the observed co2 emissions in the world (see evidence in table 1). the contribution of gas to global co2 emission is shown to be minimal. however, the same cannot be said about oil, especially from the 1950s with more of it coming from the united states followed by japan. figure vi: world’s major emitters of co2 emissions, 1971-20085. source: compiled by authors from iea (2010b). figure vii: historical trends in fossil fuel emission in the world, united state, china and japan. source: carbon dioxide information analysis center, oak ridge national laboratory and british petroleum available at http://www.columbia.edu/~mhs119/updatedfigures/ 5 the ten top co2 emitting countries in the world as at 2008 were china, united states, russian federation, india, japan, germany, canada, united kingdom, islamic republic of iran and korea, in that order. these ten countries account for 19.1 gt co2 out of the world’s 29.3 gt co2 in 2008 (see fig. a1 at appendix). international journal of energy economics and policy, vol.2, no. 1, 2012, pp.21-33 28 as shown also in table 1, the percentage shares of the developed countries in global world emissions are unambiguously larger than the corresponding shares in africa, the middle east and nonoecd countries. for instance in 2008, oecd north america alone constitutes over 17% of global co2 emissions from coal, 26% from oil and 26% from gas combustion. these contrast remarkably from the shares of world emissions by africa which stood at about 2%, 4% and 3% respectively for coal, oil and gas combustions. table 1. co2 emissions (in million metric tons) by world regions and fuel types (1971-2008) coal oil gas million tonnes of co2 1971 % share 2008 % share 1971 % share 2008 % share 1971 % share 2008 % share world 5 199 100 12 595 100 6 838 100 10 821 100 2 058 100 5 862 100 united states 1 078.7 20.7 2 085.7 16.6 2 023.0 29.6 2 227.3 20.6 1 189.5 57.8 1 257.5 21.45 oecd north america 1 145.6 22 2 228.7 17.7 2 304.6 33.7 2 755.2 25.5 1 277.6 62.1 1 545.1 26.4 oecd pacific 292.7 5.6 880.5 7 663.2 9.7 840.7 7.8 12.9 0.63 348.0 5.9 oecd europe 1 690.1 32.5 1 214.5 9.6 1 756.2 25.7 1 676.0 15.5 191.1 9.3 1 055.5 18 middle east 0.8 0.02 33.8 0.3 102.5 1.5 850.2 7.9 25.8 1.25 608.2 10.4 non-oecd europe 101.4 1.95 130.1 1 91.1 1.3 90.6 0.8 54.8 1.3 47.1 0.8 latin america 22.7 0.44 92.9 0.74 302.2 4.4 714.4 6.6 41.6 2 260.9 4.5 asia 231.9 4.5 1 548.5 12.3 192.0 2.8 1 026.8 9.5 10.2 0.5 445.3 7.6 china 678.0 13 5 460.8 43.4 124.2 1.8 934.8 8.6 7.3 0.35 154.9 2.6 africa 160.7 3.1 304.3 2.4 99.7 1.5 407.8 3.8 5.2 0.25 177.8 3 source: authors’ computation from iea (2010b). in terms of emissions by sector, fig viii presents a very informative picture. three sectors, electricity and heat generation, industry and transport are chiefly responsible for the global co2 emissions. between the two periods under review, whereas the shares of the emissions from the industrial and residential sectors decline, there was growth in emissions from the electricity and heat sector as well as the transport sector. the decline in the emissions from the other two key sectors may be an indication of significant improvements in energy efficiency and other fuel switching efforts in most developed countries over the years. generation of electricity and heat was by far the largest producer of co2 emissions and was responsible for 39% of the world co2 emissions in 2008. globally, evidence (from iea, 2010a) indicates that this sector is noted for its heavy reliance on coal, the most carbon-intensive of fossil fuels and thus amplifying its share in worldwide emissions of co2. for instance, countries such as australia, china, india, poland and south africa are estimated to generate between 69% and 94% of their electricity and heat through the combustion of coal (see iea, 2010a). the transport sector on the other hand, relies heavily on oil and over 80% of the emissions from the transport sector in 2008 are driven by road transportation (see appendix, table a1)6. clearly, this end-use sector is the strongest driver of world dependence on oil. global demand for transport is forecast to grow by 58% by 2030 (iea, 2004) and hence bears significant implication for worldwide oil related emissions. 6 a key factor in this development could be attributed to the effect of economic growth on increasing demand for road transportation, both for personal mobility and for transportation of goods. car ownerships in most developing countries tend to grow with increasing income per capita following growth. the contribution of energy consumption to climate change: a feasible policy direction 29 figure viii: world’s co2 emissions by sector, 1971 & 2008. source: quadrelli & peterson (2007) and author’s compilation from iea (2010b), available at www.iea.org/statistics/ note: *others include commercial public services, agriculture/forestry, fishing, energy industries other than electricity and heat generation, and other emissions not specified elsewhere. 5. the energy-climate change challenge: options for mitigation it has been clear from the preceding sections that the link between energy and climate change is very strong and thus constitutes a significant challenge for sustainable development. the negative impacts of climate change on crop production, higher average world temperature, rising sea levels, reduced rainfall, amongst others are largely indisputable in the literature. however, efforts to combat the disaster both at the international, regional or national level could at best be describe as less than successful. for instance, at the global level, implementing the various mitigation measures under the kyoto protocol of the unfccc has yielded limited results in its potential to address global co2 emissions. for one, not all the major emitters were included (see iea, 2010a for details on this)7. on the other hand, developing countries, though most signed the protocol are less committed to co2 emission reductions. a key policy dilemma faced by most developing countries is in balancing the tradeoff between sustained economic growth and reducing co2 energy-related emissions. the thinking in many quarters is that co2 emissions is a global pollutant and thus curtailing it by one country is practically proving difficult and inefficient to do since elements of market failure are predominant. if one country cuts its rate of fuel combustion, it bears the full cost in terms of reduction in its economic activity level, while the benefits of its action are shared with the entire world. this has lead some analysts to suggest that the effort towards co2 mitigation should be pioneered and borne by the industrialized countries who are not only responsible for the initial emissions of co2 during the 7 for instance a major co2 emitter country like the united states has expressed the intention not to ratify the kyoto protocol. international journal of energy economics and policy, vol.2, no. 1, 2012, pp.21-33 30 industrial revolution but also for the increased level of emission as a result of growing consumption of fossil fuel. however, irrespective of whatever divide, effective mitigation of climate change will require the effort of all countries. an optimal strategy for mitigating the consequences of climate change that arise from energy –related activities would not only need to be highly comprehensive and global in scale, but such policies would have to be flexible and adaptable to national and local conditions of the given nation. box 1 presents an overview of some available policy instruments. box 1: climate change mitigation policy instruments it is important to note that irrespective of any policy choice, mitigating the impact of energyrelated climate change will require four key considerations: (i) environmental effectiveness – the extent to which the policy meets its intended environmental objectives or realizes positive environmental outcomes (ii) cost effectiveness – the extent to which the policy can achieve its objectives at minimum cost to the society (iii) distributional considerations – the incidence or distributional consequences of the policy. fairness and equity are dimensions of this though there are other dimensions to distribution. (iv) institutional feasibilitythe extent to which a policy instrument is likely to be viewed as legitimate, gain acceptance, adopted and implemented (ipcc, 2007). this means that there is no one-size-fit-all policy prescription to climate change mitigation. a combination of policy options is needed. in line with this, the following options are proffered: (a) energy pricing reform in most developing countries, energy pricing are still based upon social and political justification rather than efficient market pricing principles. the world bank estimates for 1993 box 1: an overview of climate change policy instruments regulations and standards: specify abatement technologies (technological standards) or minimum requirements for pollution output (performance standards) to reduce emissions. taxes and charges : a levy imposed on each unit of undesirable activity by a source tradable permits : also know as marketable permits or cap-and-trade systems, this instrument establishes a limit on aggregate emissions by specified sources, requires each source to hold permits equal to its actual emissions, and allows permits to be traded among sources. voluntary agreements : an agreement between a government authority and one or more private parties to achieve environmental objectives or to improve environmental performance beyond compliance to regulated obligations. not all voluntary agreements are truly voluntary; some include rewards and/or penalties associated with joining or achieving commitments. subsidies and incentives: direct payments, tax reductions, price supports, or the equivalent from a government to an entity for implementing a practice or performing a specified action. information instruments: required public disclosure of environmentally related information, generally by industry to consumers. include labeling programs and rating and certification. research and development: direct government spending and investment to generate innovation on mitigation, or physical and social infrastructure to reduce emissions. include prizes and incentives for technological advances. non-climate policies: other policies not specifically directed at emissions reduction but that may have significant climate-related effects the contribution of energy consumption to climate change: a feasible policy direction 31 showed that developing countries and transition economies spent more than $230 billion per year on subsiding energy (cao, 2003). energy products like coal in china, india, poland and turkey have been heavily subsidized (world bank, 2000:25), just as nigeria spends billions on petroleum subsidy. the implication of this has been inefficient use of energy as well as serving as a disincentive for controlling energy-related emissions. efficient energy pricing will not only remove these price distortions but would sharply reduce the growth in energy consumption and could also cut world carbon emissions by 10% (see world bank, 2000:41)8. (b) emission taxes it is obvious that efficient pricing reforms that results in energy prices reflecting production may still be far from reflecting social cost. emission taxes could prove useful in adjusting market prices to reflect externalities. a high taxes on carbon-intensive fuels like coal could reduce their consumption and hence carbon emissions. in mexico, an application of gasoline tax, among other measures, has helped to dramatically reduced ghg emissions coming from transportation (world bank, 1992:74). given the high level of energy-related emissions that comes from transportation, a policy of congestion pricing or taxes may be necessary. motorists driving through city rush-hours traffic should be required to pay more than those driving in the rural settings or in off-peak hours9. the problem associated with minimization of co2 and other green house gas emissions through tax controls is that it has not fully appreciated, or given answer to, the question of final resting place of the incidence. the final bearers of such taxes may not be the industrial and transportation entrepreneurs; it may be the poor consumers who thus would end up with worse living conditions. (c) promotion of energy efficiency climate change mitigation via co2 reduction can be attained through more efficient energy use. energy efficiency implies using less energy to provide the same services. for instance, replacing an old appliances such as a refrigerator or office equipments such as an old computer or printer with a more energy-efficient model provides the same services, but with less energy. this serves two purposes: a reduced energy bill and most importantly, a reduced amount of greenhouse gases emissions. it should be noted that “energy efficiency” is not the same as “energy conservation”. energy conservation is reducing or going without a service to save energy. for example turning off a light is energy conservation. replacing an incandescent lamp with a compact fluorescent lamp (which uses much less energy to produce the same amount of light) is energy efficiency. the success of the promotion of energy efficiency largely depends on the adoption of energy efficient and low-emission technologies. (d) promotion of investment in renewable energy ultimately, the mitigation of energy-related climate change rest upon the use of renewable energy including hydro, solar, wind, biomass and other forms of renewable , which are more environmentally friendly than conventional fuels (cao, 2003). in many developing countries, there is a huge untapped and inefficiently utilized renewable energy resource which need specific national policy initiatives and international support, including finance, capacity building and technology transfer to be exploited. environmental taxes on fossil fuels may be required to stimulate reactions in favor of renewable energy. increased funding of r&d in renewable energy should also be pursued. (e) improve public environmental awareness ignorance of the serious impact of their collective actions on climate change by the general public is an important cause of environmental damage and a serious impediment to finding solutions. 8 it is important to note that the removal of energy subsidies has always faced the problem of trade-off between worsening the level of poverty for the majority of the population and improving the environmental quality. again, it is usually reasoned that one-stop removal of such subsidies may worsen the environmental problems because the affected poor may substitute poorer quality fuels for the cleaner but now (with removal of subsidies) dearer fuels. 9 the problem with this is how cost effective it will be especially for developing countries with poor institutional capacities. a success story of such policy could be found in london where it has been applied to deal with its notorious traffic problem. in 2003, the city began levying a fee of £5 (about $9) for the privilege of driving into the center of the city during peak hours. compliance is monitored by video cameras that identify the license plates of drivers who fail to pay the fee. such drivers are then charged a substantial fine. the policy has help to reduce the number of vehicles on the streets of london by approximately 16% (transport for london, 2007 cited in rosen & gayer, 2010:91). international journal of energy economics and policy, vol.2, no. 1, 2012, pp.21-33 32 adequate environmental information is required to enlighten the public on the seriousness of the worsening environment they are living in, the costs to their health and quality of life. such enlightenment would help to raise peoples’ consciousness and enlist public support for environmental protection laws or policies. this could help to facilitate and augment official enforcement of environmental policies. 6. conclusion one of the major problems facing humanity in terms of achieving sustainable development is climate change. many economic activities release greenhouse gasses – such as carbon dioxide, nitrous oxide and methane – that trap solar energy within the earth’s atmosphere. the extra heat warms the climate, creating diverse economic, health, and ecological impacts. the paper explored the role of energy in the climate change disaster. evidence has revealed that fossil fuels (coal, oil and natural gas) constitute the single largest human influence on the climate change debate, accounting for over 80% of the anthropogenic greenhouse emissions. it was shown that a substantial amount of co2 emissions still emanates from the increased use of coal use by industrializing countries like the united states, japan and china. historically, the developed countries have contributed the most to cumulative global co2 emissions and still have the highest total historical emission. two sectors of the economy, electricity and heat as well as the transport sector (especially road transport) emit greater amounts of ghgs. given the fact that primary energy still dominates the world energy mix, the potential goal conflicts between economic growth and environmental protection are rather obvious. reducing energy-related carbon emissions may require reducing the amount of fossil fuel consumption and hence economic growth. this dilemma has tended to contribute to the slow global, regional and national actions in addressing the danger of climate change. however, the problem of climate change associated with increased fossil fuel combustion is serious and requires concerted and comprehensive solutions. improving energy efficiency, reforms of inefficient energy pricing, imposition of carbon emission taxes, promoting investment in renewable energy and creating public environmental awareness are some of the mitigation strategies suggested in the paper. acknowledgement the authors would like to thank prof. adeola adenikinju for his comments and itoro j. akpan for her research assistance. references cao, x. (2003), climate change and energy development: implications for developing countries, resources policy, 29, 61–67. carbon dioxide information analysis center (2010), oak ridge national laboratory and british petroleum, available at http://www.columbia.edu/~mhs119/updatedfigures/ carbon dioxide information analysis center (cdiac) (2009), oak ridge national laboratory, available at http://www.esd.ornl.gov/iab/iab2-15.htm girardet, h. & m. mendonca (2009), a renewable world: energy, ecology, equality, green books ltd: world future council, u.k. international energy agency(iea)(2004), biofuels for transport. oecd/iea, paris, france. international energy agency (iea) (2009), international energy statistics database available at www.eia.gov/emeu/international. international energy agency (iea)(2010a), co2 emissions from fuel combustions, highlights, oecd/iea, paris, france. international energy agency (iea) (2010b), co2 emissions from fuel combustions, annual historical series (1971-2008) available at www.iea.org/statistics/ ipcc (2007), climate change 2007: mitigation of climate change, 9780521 88011-4, cambridge, cambridge university press, quadrelli, r. & s. peterson (2007), the energy-climate challenge: recent trends in co2 emissions from fuel combustion, energy policy, 35, 5938–5952. the contribution of energy consumption to climate change: a feasible policy direction 33 reddish, a. & m. rand (1996), the environmental effects of present energy policies. in: blunden, j. & a. reddish (eds.), energy resources and environment. hodder and stoughton & the open university, pp. 43-91. rosen, h. s. & t. gayer (2010), public finance, (9th edition), singapore: mcgraw-hill international world bank (1992), world development report 1992: development and the environment. oxford university press world bank (2000), fuel for thought: an environmental strategy for the energy sector. world bank. appendix table a1: co2 emissions from fuel combustion by sector in 2008. million tonnes of co2 total co2 emissions from fuel combustion electricity and heat production other energy industries** manuf. industries and construction transport of which: road other sectors of which: residential world 29 381.4 11 987.9 1 491.9 5 943.6 6 604.7 4 848.4 3 353.4 1 905.1 annex i parties 13 903.8 5 785.4 684.4 2 035.6 3 479.4 2 977.0 1 919.1 1 117.6 annex ii parties 10 951.8 4 295.2 563.4 1 549.1 3 023.9 2 656.4 1 520.2 843.2 north america 6 146.8 2 522.7 333.5 730.9 1 853.5 1 582.7 706.2 373.6 europe 3 222.9 1 063.9 164.4 514.3 850.5 790.6 629.8 402.8 pacific 1 582.0 708.7 65.5 303.8 319.9 283.1 184.2 66.8 annex i eit 2 688.5 1 386.0 112.6 448.0 410.3 281.1 331.5 234.8 non-annex i parties 14 444.6 6 202.5 807.4 3 908.1 2 092.3 1 871.4 1 434.3 787.6 annex i kyoto parties 7 980.1 3 245.4 406.2 1 351.2 1 736.1 1 477.3 1 241.2 737.7 oecd total 12 629.6 4 992.0 672.3 1 819.1 3 386.5 2 999.4 1 759.8 984.4 non-oecd total 15 718.8 6 995.8 819.6 4 124.6 2 185.1 1 849.0 1 593.6 920.7 source: iea (2010b), available at www.iea.org/statistics/ note annex ii parties include australia, austria, belgium, canada, denmark, finland, france, germany, greece, iceland, ireland, italy, japan, luxembourg, monaco (included with france), the netherlands, new zealand, norway, portugal, spain, sweden, switzerland, the united kingdom and the united states annex i kyoto parties include australia, austria, belgium, bulgaria, canada, croatia, the czech republic, denmark, estonia, finland, france, germany, greece, hungary, iceland, ireland, italy, japan, latvia, lithuania, luxembourg, monaco (included with france), the netherlands, new zealand, norway, poland, portugal, romania, russian federation, the slovak republic, slovenia, spain, sweden, switzerland, ukraine and the united kingdom. membership in the kyoto protocol is almost identical to that of annex i (see page 6), except for turkey and belarus which did not agree to a target under the protocol and the united states which has expressed the intention not to ratify the protocol. economies in transition (eits) are those countries in annex i that are undergoing the process of transition to a market economy. this includes belarus, bulgaria, croatia, the czech republic, estonia, hungary, latvia, lithuania, poland, romania, russian federation, the slovak republic, slovenia and ukraine. the organisation for economic co-operation and development (oecd) includes australia, austria, belgium, canada, the czech republic, denmark, finland, france, germany, greece, hungary, iceland, ireland, italy, japan, korea, luxembourg, mexico, the netherlands, new zealand, norway, poland, portugal, the slovak republic, spain, sweden, switzerland, turkey, the united kingdom and the united states. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 5 • 2020264 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(5), 264-271. relationship between crude oil prices and macro-economic variables: evidence from brics countries guntur anjana raju1, shripad ramchandra marathe2* 1professor and programme director for doctor of philosophy (commerce), goa business school, goa university, goa, india, 2research scholar (goa business school) and assistant professor, swami vivekanand vidyaprasarak mandal’s college of commerce, bori-ponda, goa, india. *email: amolmarathe124@gmail.com received: 09 april 2020 accepted: 26 june 2020 doi: https://doi.org/10.32479/ijeep.9755 abstract the article analyses the relationship between crude oil prices and macro-economic variables in brics countries using quarterly data from march 31, 1999 to december 31, 2019 and an autoregressive distributed lag model has been developed to study the long term relationship between crude oil and macro-economic variable. the study found out that the long term relationship exists between the variables. we have also identified that all the countries react differently to the fluctuations in oil prices. but interestingly china and india share some commonalities in terms of reacting to the changes in crude oil prices. additionaly we have also found that fluctuations in the oil price effect trade openness in every country under study except russia. keywords: crude oil prices, macro-economic variables, autoregressive distributed lag, bound test jel classifications: c22, e40, e31, e50, q43 1. introduction the rise in the interdependence of global financial markets has accelerated the growth and sensitivity to commodity prices (tang and xiong, 2012). oil considered the primary source of energy for the world. currently, there are more than 100 oil-exporting countries in the world, whereas oil prices affect both the participant’s oil importers and oil exporter. in the latest scenario, it has been noticed that the shoot up of global commodity prices may bring various challenges to most of the countries. goldman sachs coined the term bric in global economic paper 2001, titled “building better global economies bric.” instringlely in december 2010, south africa joined the former group and formed brics. as per world bank; the brics countries account for 25% of the world gdp, nearly 50% of the global population, and around 20% of global merchandise trade. the economic size of these countries also increased the share in world energy consumption. as per bp statistical review, 2017; the energy consumption rate of brics consuming 36% of the total primary energy has increased by 16% in the last decade (2006-2016). in order to sustain high growth in the absolute sense, oil consumption grew up by an average of 1.4 million barrels/day (mb/d). the developing world dominates this growth with china (0.7 mb/d), india (0.3 mb/d), and us (0.5 mb/d), accounting for almost two-thirds of the global increase (bp, 2019) whereas chinas contributes 4.5% to global renewables which is more the entire oecd countries combined. in brics, crude oil prices play a significant role in policymaking, since the fluctuations in crude oil may harm the economy in various ways. firstly, the effect can lead to a high cost of production with increased inflation. secondly, in markets, the investors and consumers confidence and level of growth of the economy may come down drastically. also, the crude oil importing countries will have to face various challenges compare to exporting countries. figure 1 indicates that there is a constant increase in crude oil consumption from 2008 to 2018 in brics countries. in brazil, the this journal is licensed under a creative commons attribution 4.0 international license raju and marathe: relationship between crude oil prices and macro-economic variables: evidence from brics countries international journal of energy economics and policy | vol 10 • issue 5 • 2020 265 consumption of oil was 2481 mb/d in 2008 has increased with a cagr of 2.19% every year till 2018. whereas china leads with a cagr of 5.51% and india with 5.09% of consumption increase every year. similarly, in south africa, there is a small percentage increase that is 0.42% cagr every year; interestingly, we can see a negative shift in the consumption of oil in russia. 2. literature review several studies have examined the relationship between crude oil prices and macro-economic variables of selected countries and various groups of countries. while very few have investigated the relationship between selected macro-economic variables and crude oil. in this section, we elaborate on the literature review on crude oil and macro-economic determinants across various economies. 2.1. studies outside brics countries (basnet and upadhyaya, 2015) analyzed the impact of crude oil price shocks on inflation, real output, and an exchange rate of asean-5 countries using the structural var approach (svar). where they have stated that the macro-economic variables are cointegrated and share the long term trend. they have also asserted that oil price shocks do not explain the significant variation in macro-economic variables. similarly; (bhat et al., 2018) concluded that there exists a long term relationship between crude oil and macro-economic variables under study. interestingly they pointed out the dominance of external shock in influencing domestic variables after their own oil price shocks. (zahran, 2019) examined that oil price shocks are significantly impacting macro-economic variables in the short and medium-term but insignificant in the long run. whereas (arfaoui and rejeb, 2017) found a negative relationship between oil price and macro-economic variables such as exchange rate and gold prices. identically; (omolade et al., 2019) investigated the influence of crude oil price shocks on the macro-economic variables with a conclusion that structural inflation impacts more to oil price than monetary inflation. similar results we have found out with (koh, 2016), (salami and haron, 2018), (ratti and vespignani, 2016), (aggarwal and manish, 2020), (malik et al., 2017) where they conformed the relationship between crude oil prices and macro-economic variables. 2.2. studies related to brics countries similarly, few studies tries to examine the relationship between macro-economic variables and crude oil prices in brics countries. these studies show similar results but mixed conclusions; these are (yildirim and yildirim, 2019) examined and concluded that crude oil prices and economic growth are having bidirectional causality whereas (singh tomar and singh, 2016), concluded that there is no clear direction of causality between the variables. indistinguishably, (sreenu, 2019), (gupta and sharma, 2018). (mensi et al., 2017) (raza, shahzad, tiwari, and shahbaz, 2016) shows similar results. (negi, 2015) concluded that china and india share a negative relationship with crude oil and gross domestic product whereas; russia and brazil have a positive relationship between the variables. so, the literature has helped us in choosing the macro-economic variables that may gauge the crude oil in brics countries. 3. data 3.1. data description and sources the data set consists of quarterly observations from march 31, 1999 to december 31, 2019 for brazil, russia, india, china, and south africa as a five developing and emerging economies of the world. the data set of brics countries has been obtained from bloomberg, fred reserve database, oecd (the organisation for economic co-operation and development database), world bank, and central and reserve bank of respective countries. based on the available literature as a set of potential variables, which includes industrial production (ip), trade openness (to), gross domestic product (gdp), foreign direct investment (fdi), exchange rate(er), money supply (ms), and inflation. we have used m3 as a proxy of money supply, consumer price index (cpi) as a proxy of inflation and trade openness we have calculated with the help of import, export, and gdp and as a dependent variable, we have used westtexes intermediate (wti) as a proxy of crude oil (as specified in table 1). for the purpose of estimation following model has been used: in(crudet)=α+b1*in(gdpt-1)+b2*in(ert-1)+b3*in(inft-1)+b4* in(fdit-1)+ b5* in(tot-1)+ b6*(ipt-1)+ b7*(mst-1) et (1) 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 cagr brazil 2481 2498 2714 2832 2884 3100 3210 3140 3960 3052 3081 2.19 russia 2861 2775 2878 3074 3119 3134 3298 2146 3217 3207 2228 -2.47 india 3137 3300 3381 3550 3747 3789 3914 4245 4654 4870 5156 5.09 china 7914 8295 9446 9808 10242 10750 11239 11986 12304 12840 13525 5.51 south africa 511 507 538 542 552 561 555 578 555 556 533 0.42 -2000 0 2000 4000 6000 8000 10000 12000 14000 16000 m ill io n b ar re ls p er d ay figure 1: crude oil consumption of brics countries (2008-2018) source: compiled from bp statistical report on energy outlook, 2019 raju and marathe: relationship between crude oil prices and macro-economic variables: evidence from brics countries international journal of energy economics and policy | vol 10 • issue 5 • 2020266 as per the above equation (1), crude is considered as a function of gross domestic product (gdp), exchange rate (er), inflation (inf), foreign direct investment (fdi), trade openness (to), industrial production (ip), money supply (ms). there might exist a long term effect between crude oil and macro-economic variable. to capture the effect of growth; we have used double log function, as shown in equation (1). to estimate we have used the difference of log variable, i.e. in logarithmic form whereas e represents the error term in growth model as shown in equation (2) and equation (3). ∆ ( ) = + ( ) + ( ) ∆ ∆ = = − − ∑ ∑ in crudei b in crude in gdp t t j t j 0 1 0 1 2 i t i t b b ++ ( ) + + ( )+ ∆ ∆ = = = − − − ∑ ∑ ∑ i t i t i t b b ” in b 0 0 0 3 4 5 in er inf in to t j t j t j ( ) ii t i t b b in = = − − − ∑ ∑∆ ∆( )+ + + 0 0 6 7in ir ip b e u t 1 t j 8 t 1 t (� ) (2) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) t j t j t j t j t j t 1 1 0 0 0 t j 1 t 1 2 t 1 0 0 3 t 1 4 t 1 5 0 t in crude in gdp in er inf ) in to in ir ip ) in crude in gdp in to ininf ) in e 1 2 3 4 ( 5 6 7 r (      = = = = = − − − − − − − − = = − − − − + + + + + + + − + + + + δ δ δ δ δ δ δ ∑ ∑ ∑ ∑ ∑ ∑ ∑ t t i i t t t i i i t t i i b b b b in b b b in ( ) ( ) ( ) 1 6 t 1 7 t 1 t 1 in ir in ip e − − −+ + + (3) where δ represents changes in crude and significant macroeconomic variables, and et-1 represents for error correction term (ect).the coefficient sign explains the speed of adjustment to crude towards the long term path and it is expected to be negative katircioglu, (2010). 4. techniques and methods to find out the relationship between the crude oil and selected macro-economic variables of brics countries. we have used the autoregressive distributed lag (ardl) cointegration technique or bound cointegration technique. but firstly, as this data is time series, we must undergo the stationary properties of the data. 4.1. unit root test most of the techniques applied in modelling the time series data are majorly concerned with stationary properties of the data. if a time series has a unit root than series is considered as a non-stationary, while the absence of it entails stationarity. the non-stationary series can result in spurious regression. the statistical procedure applied to determine the stationarity of the time series is called “unit root test.” the present study uses the augmented dickeyfuller (adf) test to examine the properties of time series data and make them stationary. 4.1.1. augmented dickey-fuller (adf) test it is the most common method of unit root test. suppose consider the series “y” for testing unit root. with this series, the following adf model can be developed as in equation (4): t t 1 i t 0 i ty y y e  = − −δ = + + δ +∑µ n i (4) where, δ= α − 1 α = coefficient of yt-1 δyt= first difference of yt δ=0 is the nu; hypothesis of adf test and alternative is δ < 0. if we do not reject the null hypothesis, then the series is said to be non-stationary and vice versa. 4.2. ardl cointegration technique or bound cointegration technique we cannot directly apply johanson cointegration test if selected variable under study are of mixed order of integration, or each variable is stationary but not in i(1). as in the case, we have to select ardl modelling with the ordinary least square (ols) model, which applies to both non-stationary and with mixed order of integration. from ardl, with the help of simple linear trasformation dynamic error correction (ecm) model can be derived. wharas ecm integrates short-run dynamics with long-run equilibrium without losing long-run information and also helps to avoid the problem of spurious relationship. the model of ardl as follows, as shown in equation (5): yt= α+βat + δbt + et (5) the error correction version of the ardl model shown in equation (6): 0 0 0 t 0 i t 1 i t 1 i t 1 1 t 1 2 t 1 3 t 1 t y y a b y a b      = = = − − − − − − δδ = + δ + δ + δ + + + + ∑ ∑ ∑ µ e n n n i i i (6) in the equation (5) with β,δ and e represent short-run dynamics, and in equation (6) ʎs exhibits long-run relationship. the null hypothesis is ʎ1+ ʎ2+ ʎ3=0, symbolizes non-existence of long term relationship. 5. empirical results table 2 exhibits stationary properties of data for all the selected macro-economic variables of brics countries, respectively. augmented dickey-fuller test has been used with the null hypothesis that series have unit root. the results of the test imply that for brazil, all the variables are stationary at i(1) except the raju and marathe: relationship between crude oil prices and macro-economic variables: evidence from brics countries international journal of energy economics and policy | vol 10 • issue 5 • 2020 267 table 2: unit root analysis variables brazil russia india china south africa adf at level adf at first difference adf at level adf at first difference adf at level adf at first difference adf at level adf at first difference adf at level adf at first difference exchange rate (er) −1.7249 [0.4149] −7.1699 [0.0000] −0.1361 [0.9411] −7.9871 [0.0000] −0.3422 [0.9128] −8.4803 [0.0000] −1.1454 [0.6939] −6.0656 [0.0000] −0.8408 [0.8016] −6.7393 [0.0000] foreign direct investment (fdi) −0.7540 [0.8261] -9.1762 [0.0000] −1.6359 [0.4596] −14.5632 [0.0000] −1.0082 [0.7469] −9.0696 [0.0000] −0.7066 [0.8380] −8.9821 [0.0000] −4.6891 [0.0000] money supply (ms) −0.7206 [0.8483] -12.0718 [0.0000] −4.1472 [0.0000] −2.5472 [0.1085] −5.2090 [0.0000] −2.6201 [0.0900] −3.1976 [0.0230] −0.9719 [0.7500] −3.3028 [0.0181] gross domestic product (gdp) −3.8593 [0.0000] −0.4542 [0.8935] −8.8422 [0.0000] −1.0671 [0.7251] −3.0469 [0.0350] −2.0717 [0.2566] −8.2649 [0.0000] −5.0507 [0.0000] inflation rate(inf) −1.3981 [0.5790] -3.4806 [0.011] −2.4159 [0.1409] −10.6207 [0.0000] −2.1839 [0.2138] −15.3609 [0.0000] −1.9578 [0.3040] −6.4186 [0.0000] −0.5318 [0.8784] −4.1792 [0.0000] trade openness (to) −1.8788 [0.3407] -7.8432 [0.0000] −2.2979 [0.1751] −11.2534 [0.0001] −1.6339 [0.4608] −13.6932 [0.0001] −3.3127 [0.0174] −7.1921 [0.0000] industrial production (ip) −2.1561 [0.2025] −6.2890 [0.0000] −2.3570 [0.1573] −6.4137 [0.0000] −1.2012 [0.6704] −6.4518 [0.0000] −8.6706 [0.0000] −4.3360 [0.0008] numerator states t-statistics and denominator [] states p-values gross domestic product (gdp) which is at i(0) or at level. russia shows similar results, but except money supply (ms), all the other variables are stationary at i(1) or at first difference. furthermore india demonstrates that all the variables are stationary at i(1) or at first difference only. interstingly, china except for trade openness (to) and industrial production (ip) all other variables are stationary at first difference. in addition in south africa foreign direct investment (fdi), groos domestic product (gdp), trade openness and industrial production(ip) all other variables are stationary at level or i(0) itself. the findings of the adf test suggest to proceed for ardl modelling and bound test. a structure of unrestricted error correction model has been developed after determining the ardl approach. as indicated by the unit root test, all variables are stationary and integrated at i(0) or i(1). so now it is possible to study the long-run table 3: critical values for the ardl modelling approach k=7 0.10 0.05 0.01 i (0) i (1) i (0) i (1) i (0) i (1) f0 2.22 3.17 2.5 3.5 3.07 4.23 f1 2.38 3.45 2.69 3.83 3.31 4.63 f2 1.70 2.83 1.97 3.18 2.54 3.91 k signifies the number of regressors in the ardl model for the dependent variable, f0, f1, and f2 represents the f-statistic of the model with unrestricted intercept and restricted trend, unrestricted intercept and trend, and unrestricted intercept and no trend respectively. source: (narayan, 2005) for f-statistics. relationship between the variables using bound test with the help of the regressors in equation (2). the critical values of f-test using small sample are taken from (narayan, 2005) and presented in table 3. table 4 furnishes the results of bound test for a level relationship between crude oil and all macro-economic variables as elucidated in equation (1). the bound test has been carried out with restricted deterministic trend, without deterministic trend and unrestricted deterministic trend. table 4 illustrates the bound f-test using autoregressive distributed lag approach and upholds level relationship in the model. in all the cases of brics countries null hypothesis of h0 = α1 = α2 = α3 = α4 = α5 = α6 = α7 = 0 in, table 4: bounds tests for level relationships variables with deterministic trends without deterministic trends f0 f1 f2 conclusion f (lncrude/lnip,lnto,lngdp,lnfdi,lner,lnms,ininf) brazil 6.45c 7.26c 7.70c h0 rejected russia 7.55c 7.65c 8.69c h0 rejected india 3.178c 3.36b 4.31c h0 rejected china 6.71c 6.72c 9.18c h0 rejected south africa 16.35c 18.39c 17.08c h0 rejected to select a number of lags required for the cointegration test schwartz criteria (sc) was used. f0, f1and f2 represent the f-statistic of the model with unrestricted intercept and restricted trend, unrestricted intercept and trend, and unrestricted intercept and no trend respectively; “a,” “b,” “c” indicates that the statistic lies below the lower bound, falls within the lower and upper bounds and lies above the upper bound respectively. table 1: data description and variables s. no. country macro-economic variables time period source symbol 1 2 3 4 5 brazil russia india china south africa exchange rate to usd q1 1999-q4 2019 fred reserve er gross domestic product q1 1999-q4 2019 oecd gdp inflation q1 1999-q4 2019 fred serve inf trade openness q1 1999-q4 2019 bloomberg to foreign direct investment q1 1999-q4 2019 fred reserve fdi interest rates q1 1999-q4 2019 fred reserve ir industrial production q1 1999-q4 2019 bloomberg ip source: authors compilation raju and marathe: relationship between crude oil prices and macro-economic variables: evidence from brics countries international journal of energy economics and policy | vol 10 • issue 5 • 2020268 table 5: estimation of ardl models and robustness test statistics f-statistics dependent variable brazil ardl (3,3,3,4,1,3,3,3) russia ardl (3,3,0,0,2,1,0,4) india ardl (1,1,0,4,0,0,2,2) china ardl (2,4,1,3,2,0,3,2) south africa ardl (1,1,1,1,0,0,1,1) serial correlation* 0.4860 (0.6174) 1.5010 (0.2314) 0.0789 (0.9242) 1.3230 (0.2748) 0.0721 (0.9305) *lagrange multiplier test of residual serial correlation. figures in parentheses indicate p-values. ardl model selected based on the schwarz bayesian criterion equation 3 do not accept. accordingly, we can conclude that crude oil as a dependent variable has a long term relationship with all macro-economic variables. so, now long-run coefficient can be estimated through ardl approach and further, conditional error correction model (ecms) can be expected to study short term phenomenon and error correction term (ects) of each country. from table 4. we have already concluded the long term relationship between the variables. for further analysis, we have to check the stability and reliability of the model with serial correlation and cusum plot before estimating the long run and short-run coefficient. for serial correlation, we have used breuschgodfrey serial lm correlation test for each model with the null hypothesis of no serial correlation or autocorrelation between the variables because f-statistics is more than 10 per cent, 5 per cent and 1 per cent level of significance as stated in table 5. whereas for analyzing the stability of the model. we have used the cusum test for ardl models under study. the given plot in figure 2 concludes that the models are stabled and can be used source: author’s compilation figure 2: the plot of cumulative sum of recursive residuals of brics countries (crude oil as a dependent variable) -30 -20 -10 0 10 20 30 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 cusum 5% significance plot of cumulative sum of recursive residules (brazil) -30 -20 -10 0 10 20 30 04 06 07 08 09 10 11 12 13 14 15 16 17 18 19 cusum 5% significance plot of cumulative sum of recursive residules (russia) -30 -20 -10 0 10 20 30 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 cusum 5% significance plot of cumulative sum of recursive residules (india) -30 -20 -10 0 10 20 30 06 07 08 09 10 11 12 13 14 15 16 17 18 19 cusum 5% significance plot of cumulative sum of recursive residules (china) -30 -20 -10 0 10 20 30 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 cusum 5% significance plot of cumulative sum of recursive residules (south africa) raju and marathe: relationship between crude oil prices and macro-economic variables: evidence from brics countries international journal of energy economics and policy | vol 10 • issue 5 • 2020 269 for further investigation because cusum statistics lies between 5% critical bound. table 6 estimates the level coefficient in the long run through the ardl approach. in brazil, the long term coefficient of trade openness, industrial production and fdi is 0.88, 1.81, and 0.02 respectively significant at 1% and per cent level of significance. whareas in the case of russia, exchange rate and industrial production, i.e. −0.71 and 1.37 is significant at 1% and 5% respectively. although, india and china show a similar situation with trade openness and money supply, i.e. 0.80, 0.96 and −1.06, 0.12 respectively significant at 1% and 5% level. additionaly, in india, gdp is significant at 5%, and in china, inflation is at 10 per cent level. whareas in south africa, we can observe that only trade openness is 0.00, which is significant at the 5% level. table 7: conditional error correction models through the ardl approach panel (a) brazil panel (b) russia panel (c) china dependent variable: crude (3,3,3,4,1,3,3,3)a selected based on schwarz bayesian criterion dependent variable: crude (3,3,0,0,2,1,0,4)a selected based on schwarz bayesian criterion dependent variable: crude (2,4,1,3,2,0,3,2)a selected based on schwarz bayesian criterion regressor coefficient standard error t-test regressor coefficient standard error t-test regressor coefficient standard error t-test crudet−1 0.43 0.12 3.51 crudet-1 0.59 0.12 4.86 crudet-1 0.29 0.13 2.14 crudet−2 −0.02 0.13 −0.18 crudet-2 −0.03 0.14 −0.22 crudet-2 0.03 0.13 0.25 crudet−3 −0.22 0.11 −2.03 crudet-3 −0.17 0.10 −1.75 crudet-3 0.19 0.11 1.72 ber −0.02 0.15 −0.12 rer −0.72 0.14 −5.06 crudet-4 0.19 0.08 2.23 bert−1 −0.51 0.20 −2.59 rert-1 −0.50 0.20 −2.53 cert-1 0.81 1.02 0.79 bert−2 −0.71 0.26 −2.70 rert-2 0.96 0.18 5.24 cert-1 −0.70 1.52 −0.46 bert−3 0.33 0.26 1.27 rert-3 −0.52 0.18 −2.94 cert-2 3.36 1.68 2.00 bfdi 0.02 0.01 2.79 rfdi 0.00 0.00 0.96 cert-3 −3.56 1.24 −2.87 bfdit−1 0.01 0.01 1.52 rgdp 0.00 0.01 0.26 cert-4 2.53 0.86 2.95 bfdit−2 −0.02 0.01 −1.94 rinf 1.43 1.01 1.41 cfdi 0.00 0.01 0.64 bfdit−3 0.02 0.01 2.82 rinft-1 0.13 1.46 0.09 cfdit-1 −0.01 0.01 −1.99 bgdp −1.01 1.01 −1.00 rinft-2 −2.05 0.94 −2.18 cgdp 0.02 0.17 0.14 bgdpt−1 −1.37 1.29 −1.06 rip 1.38 0.67 2.07 cgdpt-1 0.56 0.28 2.04 bgdpt−2 −0.41 1.25 −0.33 ript-1 −1.01 0.54 −1.87 cinf −3.71 1.86 −2.00 bgdpt−3 −1.28 1.29 −1.00 rms −0.10 0.20 −0.52 cinft-1 3.85 2.24 1.71 bgdpt−4 2.40 1.19 2.02 rto −0.08 0.13 −0.61 cinft-2 3.80 1.37 2.78 binf 1.85 1.46 1.27 rtot-1 0.40 0.11 3.52 cinft-3 3.09 1.51 2.05 binft−1 2.77 1.41 1.96 rtot-2 −0.22 0.12 −1.82 cip 0.00 0.03 0.17 bip 1.82 0.79 2.30 rtot-3 −0.12 0.09 −1.35 cipt-1 −0.05 0.03 −1.61 bipt−1 −2.02 0.94 −2.14 rtot-4 0.21 0.08 2.50 cms −0.12 0.04 −2.91 bipt−2 −0.18 1.04 −0.17 c 2.07 4.42 0.47 cmst-1 0.20 0.12 1.62 bipt−3 1.50 0.80 1.88 ectt-1 −0.61 0.08 −7.21 cmst-2 −0.18 0.14 −1.26 bms −0.01 0.66 −0.01 cmst-3 −0.05 0.16 −0.33 bms−1 −1.91 0.71 −2.68 cmst-4 −0.34 0.20 −1.76 bmst−2 −0.11 0.64 −0.17 cto 0.97 0.21 4.65 bmst−3 1.97 0.75 2.62 ctot-1 1.50 0.31 4.83 bto 0.88 0.24 3.72 ctot-2 −1.00 0.31 −3.19 btot−1 0.37 0.24 1.54 ctot-3 0.21 0.34 0.63 btot−2 −0.01 0.31 −0.04 ctot-4 −0.82 0.26 −3.12 btot−3 −0.58 0.23 −2.52 c −57.22 10.80 −5.30 c 9.95 10.87 0.92 ectt-1 −0.38 0.06 −5.68 ectt−1 −0.83 0.14 −5.69 adj. r2= 0.9738, s.e. of regr. 0.08, aic = 1.88, sbc= −0.92,f-stat. = 96.02, f-prob. = 0.000, d-w stat. =2.18 adj. r2= 0.9733, s.e. of regr. = 0.08, aic = −1.89, sbc=−1.23,f-stat. 89.50, f-prob. = 0.000, d-w stat. =2.14 adj. r2= 0.9798, s.e. of regr. = 0.07, aic =−2.14, sbc=-1.22, f-stat. = 98.89, f-prob. = 0.000, d-w stat. =2.22 ‘a’ denotes p lag structures in the model table 6: level coefficients in the long-run models through the ardl approach dependent variable regressors lncrude lner into ingdp ininf inip inms infdi intercept brazil −0.01 0.88** −1.01 1.84 1.81** −0.00 0.02* 9.94 russia −0.71* −0.07 0.00 1.43 1.37** −0.10 0.00 2.06 india 0.02 0.80* 1.40** 1.34 0.18 −1.06** 0.00 7.02 china 0.80 0.96* 0.02 −3.71*** 0.00 −0.12* 0.00 −57.21* south africa −0.24 0.00** 1.76 −0.06 0.34 −1.02 −0.00 0.00 source: authors’ compilation. *, ** and *** denote the statistical significance at the 1%, 5%, and 10% levels respectively. raju and marathe: relationship between crude oil prices and macro-economic variables: evidence from brics countries international journal of energy economics and policy | vol 10 • issue 5 • 2020270 finally, table 7 and table 7(a) provides the estimation of error correction model (ecm) and error correction term(ects). it is noticed that ect in all brics countries is negative and statistically significant. likewise china and south africa show error term less then 50%, means there are some variables that make crude oil react to its long-run equilibrium other than those microeconomic variables under study. in china and south africa, the estimated ect is −0.38 and −0.35 (p<0.01) expresses that crude oil in china reacts to its long-run equilibrium by 38% speed of adjustment quarterly and south africa is at 35% speed of adjustment. whereas the remaining countries, the highest ect has been obtained from india (-0.99), brazil (-0.83) and russia (-0.61) respectively. which are statistically significant at (p<0.01). additionaly, table 7 and table 7(a) shows the short-run dynamics of the ardl process. similarly, all independent and dependent variable shows a mixed reaction (either positive or negative) with each other. 6. conclusion the connection between crude oil and macro-economic variables is relevant to brics countries because it is quite vulnerable to oil prices shocks and interdependencies among the variable will put forward underlying importance for managerial decisions of investment and policymakers, government and investors as a whole. the aim of this paper is to highlight the relationship between crude oil and macro-economic variables of an emerging and developing brics countries using autoregressive distributed lag, and bound test approach with the quarterly observations for the period march 31, 1999 to december 31, 2019. indeed we found that there exists a long term relationship between crude oil and macro-economic variables which are industrial production, trade openness, gross domestic product, foreign direct investment, exchange rate, money supply and inflation. from the results, it is clear that fluctuations in the crude oil prices lead to changes in the macro-economic variables and leads to changes in the economies as a whole. references aggarwal, p., manish, m.k. (2020), effect of oil fluctuation on stock market return: an empirical study. international journal of energy economics and policy, 43(22), 213-217. arfaoui, m., rejeb, a.b. (2017), oil, gold, us dollar and stock market ınterdependencies: a global analytical insight. european journal of management and business economics, 23(11), 1-20. basnet, h.c., upadhyaya, k.p. (2015), impact of oil price shocks on output, inflation and the real exchange rate: evidence from selected asean countries. applied economics, 47(29), 3078-3091. bhat, j.a., ganaie, a.a., sharma, n.k. (2018), macro-economic response to oil and food price shocks: a structural var approach to the indian economy. international economic journal, 46(05), 1-25. bp. (2019), bp statistical review of world energy. united kingdom: bp statistics. gupta, v., sharma, p. (2018), the impact of oil prices on stock prices and other macro-economic variables in india: pre-and post-2008 crises. table 7(a): conditional error correction models through the ardl approach (continued). panel (c) india panel (d) south africa dependent variable: crude (1, 1, 0, 4, 0, 0, 2, 2)a selected based on schwarz bayesian criterion dependent variable: crude (1, 1, 1, 1, 0, 0, 1, 1)a selected based on schwarz bayesian criterion regressor coefficient standard error t-test regressor coefficient standard error t-test crudet-1 0.62 0.10 6.44 crudet-1 0.00 0.10 0.05 ier 0.03 0.38 0.08 saer −0.25 0.21 −1.19 iert-1 −0.72 0.38 −1.89 saert-1 −1.13 0.22 −5.19 ifdi 0.01 0.01 0.97 sagdp 1.77 1.25 1.41 igdp 1.40 0.58 2.43 sagdpt-1 1.71 1.30 1.32 igdpt-1 1.29 1.18 1.10 sainf −0.07 0.14 −0.49 igdpt-2 −4.01 1.06 −3.77 sainft-1 0.20 0.14 1.43 igdpt-3 0.31 1.27 0.25 sams −1.03 0.84 −1.23 igdpt-4 1.22 0.93 1.31 sfdi 0.00 0.00 −1.11 iinf 1.35 0.95 1.42 sip 0.35 0.26 1.32 iip 0.18 0.63 0.29 sipt-1 −0.46 0.25 −1.88 ims −1.07 0.46 −2.33 sato 0.00 0.00 2.29 imst-1 −1.05 0.46 -2.28 satot-1 0.01 0.00 2.68 imst-2 0.90 0.52 1.71 c 0.01 0.07 0.14 ito 0.80 0.15 5.30 ectt-1 −0.35 0.06 −5.53 itot-1 0.38 0.19 2.05 itot-2 −0.41 0.19 −2.20 c 7.02 19.36 0.36 ectt-1 −0.99 0.07 −12.82 adj. r2=0.9732, s.e. of regr.0.09, aic=−1.67, sbc=−1.10, f-stat.=78.56, f-prob.=0.000, d-w stat.=2.04 adj. r2=0.98, s.e. of regr. 0.07, aic=−2.14, sbc=−1.22, f-stat.=85.64, f-prob.=0.000, d-w stat.=2.22 “a” denotes p lag structures in the model raju and marathe: relationship between crude oil prices and macro-economic variables: evidence from brics countries international journal of energy economics and policy | vol 10 • issue 5 • 2020 271 opec energy review, 23(10), 1-20. katircioglu, s.t. (2010), international tourism, higher education and economic growth: in the case of north cyprus. the world economy, 33(12), 1955-1972. koh, w.c. (2016), how do oil supply and demand shocks affect asian stock markets? macro-economics and finance in emerging market economies, 15(2), 1-18. malik, k.z., ajmal, h., zahid, m.u. (2017), oil price shock and its ımpact on the macro-economic variables of pakistan: a structural vector autoregressive approach. international journal of energy economics and policy, 25(15), 1583-1592. mensi, w., hkiri, b., al-yahyaee, k.h., kang, s.h. (2017), analyzing time-frequency co-movements across gold and oil prices with brics stock markets: a var based on the wavelet approach. international review of economics and finance, 40(3), 1-29. narayan, p.k. (2005), the saving and investment nexus for china: evidence from cointegration tests. applied economics, 18(5), 1979-1990. negi, p. (2015), impact of oil price on economic growth: a study of bric nations. indian journal of accounting, 116(5), 44-155. omolade, a., ngalawa, h., kutu, a. (2019), crude oil price shocks and macro-economic performance in africa’s oil-producing countries. cogent economics and finance, 15(6), 1-17. ratti, r.a., vespignani, j.l. (2016), oil prices and global factor macro-economic variables. energy economics, 22(1), 198-212. raza, n., shahzad, s.j., tiwari, a.k., shahbaz, m. (2016), asymmetric impact of gold, oil prices and their volatilities on stock prices of emerging markets. resources policy, 18(8), 290-301. salami, m.a., haron, r. (2018), long-term relationship of crude palm oil commodity pricing under structural break. journal of capital markets studies, 25(6), 1-19. singh tomar, r., and singh, h. (2016), the causal relationship between stock market indices, gold prices, crude oil prices, and exchange rates. research gate, 17(7), 53-65. sreenu, n. (2019), the effects of oil price shock on the ındian economy-a study. the indian economic journal, 26(9), 25-40. tang, k., xiong, w. (2012), index ınvestment and the financialization of commodities. financial analysis journal, 15(8), 54-74. yıldırım, d.c., yıldırım, s. (2019), investigating energy consumption and economic growth for brics-t countries. world journal of science, technology and sustainable development, 16(6), 1-25. zahran, m.s. (2019), the response of remittances inflows to asymmetric oil price shocks in egypt. review of economics and political, 6(3), 1-20. international journal of energy economics and policy vol. 5, no. 1, 2015, pp.69-79 issn: 2146-4553 www.econjournals.com energy efficiency policies and the jevons paradox jaume freire-gonzález ent environment and management, spain. email: jfreire@ent.cat ignasi puig-ventosa ent environment and management, spain. email: ipuig@ent.cat abstract: energy and climate change policies are often strongly based on achieving energy efficiency targets. these policies are supposed to reduce energy consumption and consequently, associated pollutant emissions, but the jevons paradox may pose a question mark on this assumption. rebound effects produced by reduction in costs of energy services have not been generally taken into account in policy making (there is only one known exception). although there is no scientific consensus about its magnitude, there is consensus about its existence and in acknowledging the harmful effects it has on achieving energy or climate targets. it is necessary to address the rebound effect through behavioral, legal and economic instruments. this paper analyzes the main available policies to minimize the rebound effect in households with special emphasis on economic instruments and, particularly, on energy taxation. keywords: rebound effect; energy efficiency; environmental taxation jel classifications: q2; q3; q4; q5 1. introduction energy efficiency improvements are in many countries a key part of the strategy to reduce energy consumption and to tackle global warming. this is based on the idea that energy efficiency improvements lead to lower energy consumption and, consequently, to a reduction in the emission of greenhouse gases (ipcc, 2007). governments invest much effort on national energy efficiency policies, both addressed to the productive sector and to households, as part of the solution for environmental and energy problems. these gains in efficiency, induced in part by technological progress, have also contributed to promote economic growth while reducing resource consumption and emissions of pollutants into the atmosphere. however, a rebound effect takes place, which is an increase in energy consumption following an energy efficiency improvement. in extreme cases, when energy efficient improvements lead to overall energy consumption increases, this is called jevons paradox (jevons, 1865; brookes, 1978; khazzoom, 1980, 1987, 1989; khazzoom and miller, 1982; greening et al., 2000; freiregonzález, 2010; and others). this means that promoting energy efficiency, without additional measures, does not necessarily produce energy savings nor reduce pollution or, in any case, reductions in energy consumption are not proportional to the efficiency improvement. it is necessary to consider energy efficiency measures in a broader context, defining its role within energy policy, and include additional measures to minimize the rebound effect. this implies an explicit purpose and intention to reduce resource consumption and pollutant emissions when applying energy efficiency measures. the rebound effect is rarely taken into account in the official analysis of potential energy savings from energy efficiency improvements, despite the recent interest of some organizations such as the european commission to begin to consider and minimize it (maxwell et al., 2011). an exception is its consideration within the united kingdom policy to improve the thermal insulation of households. this provides for the possibility that some of the potential benefits of the measure will result in higher internal temperatures, rather than reducing energy consumption (defra, 2007). but, international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.69-79 70 direct rebound effect is usually ignored in most cases due to lack of knowledge, as are the potential indirect and economy-wide effects.1 these effects are more uncertain, although they could be of greater magnitude than direct effects (semboja, 1994; dufournaud et al., 1994; hertwich et al., 2004; washida, 2004; glomsrød and taojunan, 2005; hanley et al., 2006; allan et al., 2006; barker et al., 2007). when developing energy efficiency improvement policies, policy makers must begin to consider the rebound effect explicitly. energy policies are ineffective in terms of results achieved, if the rebound effect is not taken into account. furthermore, they involve high opportunity cost, because public resources used in efficiency measures might be causing unwanted effects. in this sense, ex-post analysis of the policies should be performed in order to verify their actual effectiveness. as discussed in this article, energy efficiency technology policies that cause higher direct rebound effect require an additional control for other policy variables such as energy prices. it can be addressed either through environmental taxation or other measures including: awareness, information and consumer behavior or legal instruments. if these additional measures are not implemented, the potential energy savings and carbon emissions will be less effective. although the rebound effect might not result in “backfire” (i.e. a net increase in energy consumption), environmental taxation measures and the control of other variables would lead to exploitation of the potential savings resulting from an energy efficiency improvement; otherwise, the policy would lose effectiveness. from several studies (alfredsson, 2004; druckman, et al., 2010; freire-gonzález, 2011), it is known that, although there is a low direct rebound effect, the re-spending effect of monetary savings achieved from energy efficiency improvements could lead to higher indirect rebound effect. therefore, in these cases, it is also important to implement policies to control the rebound effect that avoids a possible backfire and maximize the potential energy efficiency improvements. from this perspective, some policies and measures that are being implemented in many countries should be re-evaluated in order to improve energy efficiency. direct rebound effect can be defined as (dimitropoulos and sorrell, 2006):  ( ) ( ) ( ) ( ) 1 s kp p k e s s p          (1) where ( )e is the elasticity of demand for energy with respect to energy efficiency (or direct rebound effect), ( ) sp s is the elasticity of demand for useful work with respect to energy service costs, ( ) kp s is the elasticity of demand for useful work with respect to capital costs and ( )kp is the elasticity of capital costs with respect to energy efficiency.2 equation (1) includes the capital costs of energy services in the mathematical formulation of the direct rebound effect, that is, the cost of devices or technologies that provide the energy service. it shows the potential rebound effect when carrying out energy efficiency policies on certain energy services, such as subsidies to more efficient appliances, since they reduce the cost of devices (capital costs). as shown in the equation, part of the rebound effect could be offset if new and more efficient equipment would be more expensive (considering the sign of efficiency elasticity of capital costs, since capital costs would increase), as long as the consumers assumed the entire cost of the energy service. a subsidy policy, which makes efficient devices cheaper than inefficient appliances, may, instead, amplify the rebound effect. this policy has been widely used to improve efficiency in industrialized countries. in spain, for instance, there have been several plans to improve efficiency and to subsidize automobiles,3 appliances, boilers, air conditioners or windows, among others (idae, 2007; idae, 2010). in the latest plan (idae, 2010), a potential rebound effect was considered. however, no additional policy to counteract it was implemented. 1 indirect rebound effect is the increase in energy consumption by other goods and services due to an increase in disposable income caused by energy efficiency improvements. economy-wide rebound occurs when an energy efficiency improvement produces changes in prices, quantities, incomes and other macroeconomic variables that lead to new general equilibrium in the economy, increasing the overall energy consumption. 2 technical aspects of this equation and different definitions can be found in dimitropoulos and sorrell (2006) and sorrell (2007). 3also for road safety considerations. energy efficiency policies and the jevons paradox 71 a consideration of all these aspects could lead to a reformulation of the national energy policy. policy actions are necessary to support efficiency, but additional actions are also required to control the rebound effect. so a new energy policy framework should be established considering both traditional measures of energy efficiency improvement and complementary actions to prevent unwanted side effects. scholars have pointed out that there is some confusion in theoretical works on the rebound effect and that empirical evidence is weak (greening et al., 2000; sorrell, 2007; dimitropoulos, 2007). it is, therefore, important to advance the theoretical and empirical analysis and to provide the best arguments to policy makers, but also in the design and implementation of economic, legislative and political instruments. these policies, taking into account this phenomenon, should allow the achievement of desired goals in energy and environmental policy. it is also necessary to consider that the rebound effect should not necessarily be an adverse effect. if the goal of improving energy efficiency is strictly economic, that is, to promote economic growth without considering energy consumption, the rebound effect would become a desirable result. this is not the situation when the policy target of efficiency is to reduce energy consumption and pollution and to mitigate climate change. notwithstanding, the policies to control the rebound effect counteract economic growth. in this scenario, additional policies to control the rebound effect are useful. this paper investigates the main economic instruments and proposals that could deal with the rebound effect in households. section 2 shows the various kinds of policies and instruments available to control the rebound effect in households. section 3 shows the main economic instruments, as well as a brief analysis of a possible tax to offset the rebound effect. finally, section 4 contains the main conclusions and suggestions for further research. 2. policies to control the rebound effect in households the rebound effect is the result of the economic responses when there is a reduction of the cost of provision of certain energy services, due to an improvement of energy productivity of providing energy services. thus, many of the policies to control the rebound effect should aim at modifying the behavioral responses of economic agents if an efficiency improvement takes place. the first step consists in recognizing the existence of the rebound effect and the need to address it when defining the objectives of energy policy to achieve a specific energy efficiency objective. in recent years, steps are being made in this direction, as shown by the interest and acceptance by official bodies like the european commission (maxwell et al., 2011) and the european environment agency (eea, 2010). in spain the energy efficiency and conservation plan for 20112020 (idae, 2010) mentions the possibility of a rebound effect, unlike the previous plan, which did not mention its possible existence (idae, 2007) even though in practice it does not consider the rebound effects in the calculations of the savings produced by the previous plans. the case of energy policies related to insulation of households, from the department of energy and climate change (decc) by the uk government, is the only known example of the consideration of direct rebound effect in the expected effects of a law. in this case, the united kingdom government includes a 15% reduction in the expected energy savings from insulation measures in households in order to account for the direct rebound effect. additionally, decc produced a guideline (decc, 2010) and a spreadsheet4 to account for the rebound effect on policies to reduce energy consumption. moreover, it is necessary to establish consistent definitions and measures of the rebound effects and to begin to introduce them in all the relevant fields, like households or industries, as well as for all the energy services within these areas. levett (2009) suggests several reasons why rebound effect is difficult to consider by policymakers: the complexity and unpredictability of the phenomenon, the difficulty to obtain clear and unified evidence, the co-evolution of technologies and societies, irreversibility, vicious and virtuous circles, and other political reasons. the non-achievement of energy efficiency targets identified by policy makers is sometimes 4it can be downloaded at (last accessed 17 november 2014): http://www.decc.gov.uk/en/content/cms/about/ec_social_res/iag_guidance/iag_guidance.aspx international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.69-79 72 associated with the existence of direct rebound effect. indirect rebound effect is often not identified in these analyses, but it can also amplify the reduction of the effectiveness of these policies (alfredsson, 2004; druckman, et al., 2010; freire-gonzález, 2011). the inclusion of life-cycle analysis in the evaluation of environmental policy would provide a more accurate vision of this phenomenon, and the possibility of acting accordingly (chapman, 1974; herendeen and tanak, 1976; kok et al., 2006). as shown in several studies (jalas, 2002; carlsson-kanyama et al., 2005; cohen et al., 2005; takase et al., 2005), different consumption patterns involve different energy content, not always obvious at first sight. although there is a lack of literature on the specific measures to minimize the rebound effect, three main categories of action can be identified (ouyang et al., 2010; ehrhardt-martinez and laitner, 2010; maxwell et al., 2011): measures designed to change consumer behavior through information and awareness, regulatory instruments, and economic and energy taxation instruments. in practice, an appropriate policy mix combining different sorts of instruments may be the most effective option (oecd, 2005). 2.1. awareness, information and consumer behavior to counteract the rebound effect it is necessary to understand human behavior when modifying prices and to properly account for consumption patterns (defra, 2007; unep, 2010; eea, 2010). there are many ways to improve consumer awareness and to guide consumer preferences to encourage environmentally friendly consumption. one of the most used methods has been advertising campaigns undertaken by governments to modify behavior and consumption patterns. this can be included in the so-called “people-oriented initiatives” and could be important in avoiding the rebound effect (ehrhardt-martinez and laitner, 2008; ehrhardt-martinez and laitner, 2010; lutzenhiser, 2009; meier, 2009). it is also interesting to provide further information on energy consumption in households, and on its cost and variations when taking certain energy saving actions, so it could encourage households to reduce the use of energy even when rebound effect exists (dimitropoulos, 2009). in this sense, darby (2006) shows how smart meters can influence behavior and reduce energy consumption, offering consumers the possibility to voluntarily avoid direct rebound effect. wright et al. (2000) show how a better feedback on energy bills, that is, a better understanding of energy consumption and costs of actions taken at households, can produce up to 10% savings in electricity consumption for heating in cold climates. historically, however, in relation to energy and households, most campaigns have aimed at the acquisition of more efficient appliances or at directly promoting energy saving measures in order to reduce the overall consumption of energy which, as demonstrated, would not necessarily be effective. additionally, it is necessary to consider the limitations of voluntary measures. in this context, arguments such as the "tyranny of small decisions" (odum, 1982) apply. he stated that the result of many small decisions, end up resulting in unexpected and/or undesirable effects. therefore, some behavioral measures discussed to avoid direct rebound effect could not be completely effective. sen (1967) postulated the "isolation paradox" which suggests that, even though there is an established socially altruistic behavior, there will always be someone who will not be well-behaved in relation to the moral problems involved in behavioral measures to tackle the rebound effect. in addition, it is important to consider other additional difficulties when implementing energy efficiency measures, despite the advantages in economic and environmental terms they suppose in principle. this is known in the literature as the "energy efficiency paradox". although linares and labandeira (2010) recognize that the causes of this paradox are unclear and, therefore, the policies that should be carried out are not clear either, they show the possible causes. these are firstly market failures, and secondly, the lack of consideration of issues related to human behavior and society. in summary, the authors point out the following reasons: low prices of energy (in part, due to externalities not being considered). higher than expected investment costs. uncertainty and irreversibility of investments. errors of information, including asymmetric information (imperfect or myopic). limited rationality. slowness of technology diffusion. principal-agent problem. energy efficiency policies and the jevons paradox 73 capital market imperfections. heterogeneity of consumers. divergence between the social and private rates of discount. 2.2. legal instruments together with awareness, it is important to make sure that consumers have appropriate and sufficient information to make rational decisions. in this sense, new regulations should be developed to pursue this goal. regulations should be focused on improving consumer information and on reducing energy intensity of economic sectors through establishing limits or prohibitions on the use and consumption of resources (schneider, 2008) or on pollutant emissions (sorrell, 2007), setting goals, etc. regarding information, for example, and considering the re-spending effects on consumption patterns of households, it is important that governments develop specific legislation, and force producers to carry out life-cycle analyses in terms of energy consumption, pollutants emissions or other relevant environmental impacts of their products, and label them accordingly.5 in addition, it would be important to know the destinations of the savings derived from energy efficiency measures and associated financial products, with additional information on the total energy consumption of these destinations in order to take decisions with higher levels of information. 2.3. economic instruments given the characteristics of the rebound effect, economic instruments and specifically environmental taxation can play a key role in modifying behaviours and, therefore, preventing it or minimizing its effects. there are difficulties in establishing a tax to compensate the rebound effect, because it varies among technologies, sectors, countries and income groups, and there are no estimates for all of them. but, it would be appropriate to develop an appropriate taxation framework that considered and minimized the rebound effect when carrying out energy efficiency policies. the main objective of the taxation instruments would be to increase the costs of providing the useful work of the various energy services, while improving efficiency. similarly, the rebound effect could also be minimized through energy prices policies. in effecting these steps, there is no reduction in the cost of the energy service perceived by consumers (or its reduction is minimized) and then they do not react by increasing its consumption (or increased consumption is also minimized). nevertheless, to ensure that energy efficiency improvements are adopted, taxation would be on adopters and on non-adopters, creating thereby an incentive to energy efficiency. at this point it is important to mention that, as levett (2009) states, a tax or a prices measure that tried to compensate the rebound effect could have perverse effects on incentives in technical innovation in the sense that firms will not benefit from them, removing manufacturers’ incentive to improve efficiency. those possible effects should be taken into consideration when implementing a tax scheme to minimize the rebound effect. given the importance of avoiding the rebound effect, the next section will analyze these economic tools in more detail, with a schematic analysis of a tax that would offset the rebound effect. 3. economic instruments to control the rebound effect as mentioned in the previous section, economic instruments are important to counteract the rebound effect. specifically, taxation and price instruments in general, applied to energy have special importance. rebound effect produces an undesirable increase in consumption. this increase is due to the implicit reduction of the cost of the useful work of an energy service for the user. this means that one can get the same amount of useful work at a lower cost, although the price of energy does not change in the short term. it is important to note that, depending on the different political targets, the best option should not necessarily be to completely cancel the rebound effect. this should not be the case if, for example, the objective of an energy efficiency policy would be economic growth. on the contrary, if the objective was to translate energy efficiency into full reduction of energy consumption, it would be necessary to offset it. 5 there is a vast literature on life cycle energy analysis which can be used to quantify the indirect rebound effects. a special issue of sustainability published in 2011 reported the state-of-the-art in this literature (finkbeiner et al., 2010; brandão et al., 2010; acosta-alba and van der werf, 2010; halog and manik, 2011). international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.69-79 74 3.1. taxation considerations to address direct rebound effect a taxation that fully counteracted the direct rebound effect would be one that compensated for the reduction of cost due to the improvement of the energy efficiency. that is, a taxation that would keep constant the generalized cost of providing useful work. in formal terms and in terms of dimitropoulos and sorrell (2006), developments on the methodological and theoretical aspects of the rebound effect, the price of the energy service sp is equal to the price of energy ep in relation to energy efficiency  : 6 /s ep p  (2) in this case, taxation should compensate the increase of efficiency (   ), i.e., increasing the price of the energy service. therefore, being t the tax, after the efficiency improvement, it should get:   /s ep p t    (3)    moreover, the generalized cost of useful work, which theoretically would be relevant to the decision of a rational consumer, can be defined as the sum of several components (dimitropoulos and sorrell, 2006): g s k m tp p p p p    , (4) where gp is the generalized cost of useful work, kp are the annualized capital costs, mp are the operating and maintenance costs, and kp are the costs in terms of time; gp includes all the costs of providing the energy service. although the other components remain constant, the energy efficiency improvement produces a reduction of the cost of the energy service and, therefore, of the generalized cost of useful work. this is the cost at which individuals would increase the energy consumption of the service itself and/or their available income would be increased. from equation (3): e e p t p    (5) from equation (3), the next expression can be obtained: 1 et p          (6) after an increase of the efficiency, the tax would increase according to the proportion represented by the new energy efficiency compared to the previous one. the developed taxation would fully offset the direct rebound effect, leading to a maximum effectiveness of the energy efficiency improvements. this would mean a reduction in energy consumption and, therefore, a reduction in resource consumption and in emissions of greenhouse gases. it is also important to bear in mind that this tax has a different nature and could differ, being higher or lower, from an optimal pigouvian tax (pigou, 1920), defined from the externalities caused by energy consumption. in relation to levett (2009) and concerns on possible perverse effects of a possible tax to address rebound effect, the proposed tax affects the cost of energy and, therefore, its effect on less energy-efficient activities will be more significant than that on the most efficient ones, reinforcing incentives towards technical innovation. 3.2. taxation considerations in addressing the indirect rebound effect as demonstrated above, the taxation reasoning for the direct rebound effects only considers the perspective of the final consumers (households). even without considering economy-wide rebound effects, it is necessary to consider a broader view and to analyze indirect effects. using a model to capture the re-spending effects that generates the indirect rebound effect (freire-gonzález, 2011), the new budget balance can be expressed as:    ' ' 1 n i i e e i x p y x p s     , (7) 6 energy efficiency here is measured in terms of the thermodynamic efficiency of a system providing an energy service. several measures can be, therefore, used. in the mathematical expression it is a dimensionless measure. energy efficiency policies and the jevons paradox 75 where ix is the amount of the good i, ip is the price of the good i, ex is the amount of energy and ep is the price of energy. the purpose of taxation is that monetary energy spending after the energy efficiency improvement remains the same as before the improvement, decreasing the amount of energy consumed. therefore:     ' e e e ex p x p t  (8) introducing this tax in the price of energy, expression (7) would be like:     1 n i i e e i x p y x p t s      (9) this way, the re-spending effect in households would not occur, as the reduction in spending that households make on the energy sector would be offset by an energy tax, which would maintain consumption patterns and, therefore, would not produce indirect effects. however, there would be an additional re-spending effect from the public expenditure that would occur due to the revenue raised by the tax. 3.3. the re-spending effect of public spending as shown, an energy tax could be a useful tool to offset the reduction of the cost of the energy services derived from energy efficiency improvements and, therefore, to avoid possible re-spending effects. this is one source of indirect rebound effects; the other source would be the indirect energy consumption in the life-cycle of capital needed to improve the efficiency (sorrell, 2007). however, one key aspect would be the way in which revenues obtained from the tax are spent, since this would have several macroeconomic effects. it could cause distortions in the economy, an income transfer from households to the public sector and an additional re-spending effect produced by the destination of the public expenditure. this new public sector spending (or savings), will generate, just as it would happen in households, a re-spending effect that would lead to an indirect rebound effect. this confirms the impossibility to completely remove the static direct and indirect rebound effect. even, if there were perfect information and a tax revenue intentionally and completely spent in the sector with a lower drag coefficient in an input-output framework, there would be some rebound effect. notwithstanding, a correctly defined tax could minimize it. a possibility would be to conceive it as earmarked, and revenues should be used to subsidize those households with the best environmental practices, in terms of sustainable consumption or those industries (or companies) in sectors with low drag coefficients in terms of energy consumption. earmarked green taxes tend to benefit from broader public acceptance, and this increases their political viability (european environment agency, 2005). one dynamic and revenue neutral instrument that could be used in this context to encourage the productive sectors to reduce their energy intensity is a feebate7 scheme (davis et al., 1997, puigventosa, 2004). feebate systems aim at fostering those activities, practices or products that are deemed more environmentally friendly at the expense of others that are less environmentally friendly. they do so by means of a simultaneous use of both fees and rebates. in this case the less energy efficient activities or services compared to the average would be charged a fee and the collected amount would be transferred to the most ecological services in the form of rebates. these systems could generate a continuous incentive to improve the energy intensities in purchasing intermediate goods and services. energy policymakers should be careful when implementing such a measure as it could cause distortions in the economy such as changes in prices. it also could impact different income levels unequally, and potentially increase other environmental impacts. furthermore, it affects the type of energy used, or has perverse incentives to innovation, etc. despite the theoretical suitability of the tax in terms of reducing the rebound effect and the energy consumption globally, one of the main problems is that it could present redistributional issues, as it may imply a transfer of income from households to firms. to prevent this issue, such a measure could be accompanied by changes in direct taxation of households and firms. 7 combination of fee and rebate. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.69-79 76 these and other factors should be considered in depth before implementing such a measure. ex-ante and ex-post impact analysis techniques should be used in considering the most suitable policy options in different scenarios. regarding implementation feasibility, there are difficulties in terms of information concerning the magnitude of the direct rebound in different energy services, areas, income groups or over time. therefore, it is difficult to design a tax that effectively counteracts the reduction of the cost of energy due to energy efficiency improvements in a particular area. however, it would be feasible to complement the energy efficiency programs for specific energy services with taxation considerations. levett (2009) considers that the ideal taxes or energy prices to neutralize energy efficiency rebound effects are unrealistic, but high and rising energy prices will strengthen those feedbacks that will tend to reduce energy use, and weaken those feedbacks that will tend to increase it. 4. conclusions a thorough revision of energy policies aimed at reducing consumption of resources and tackle global warming is necessary. as stated in the literature, policies to improve energy efficiency are less effective than expected, because of the rebound effect. to be effective, policies must be accompanied by other measures such as an effective communication and awareness of the citizens, regulatory instruments and/or an appropriate taxation. an effective combination of traditional efficiency measures with new policies oriented to tackle the rebound effect would maximize the effectiveness of the policy objective of reducing energy consumption. a tax to minimize the rebound effect would indirectly increase the cost of the energy service through an increase of the energy price, hence the reduction of the cost from the improvement in the energy efficiency would be offset by this energy price increase. this ensures that the demand of the service does not increase and thus, direct energy consumption would be reduced as much as it was expected to. despite the difficulties of establishing a proper taxation, the use of these instruments could compensate for the rebound effect and make energy efficiency measures more effective. a taxation policy aimed at tackling the rebound effect in households, for example an indirect tax to compensate for the reduction of the cost of energy service due to efficiency improvements in households, in addition to the appropriate spending policy, should be accompanied by an industrial policy to foster the productive sectors to reduce their direct and indirect energy consumption. an appropriate combination of various instruments could minimize indirect rebound effects in households, because avoiding the monetary savings in households prevents the increase in consumption patterns due to improved efficiency. it is also necessary to include the rebound effect in the ex-ante and ex-post analysis of energy efficiency policies, and into the models and governmental programs. this paper suggests the role of energy taxes to minimize the rebound effect. one of the most important aspects that also have been highlighted is the relevance of the re-spending effect of the revenue, which might in turn lead to an increase in energy consumption. most efforts in the rebound effect research have been oriented to methods and to obtain evidence of its existence and magnitude. although it is necessary to continue to advance in this direction, the lack of research in relation to policies to address it, suggests a whole new area of possible research with strong practical implications. references acosta-alba, i., van der werf, h.m.g. (2011), the use of reference values in indicator-based methods for the environmental assessment of agricultural systems. sustainability 3(2), 424442. alfredsson, e. c. (2004), 'green' consumption no solution for climate change. energy 29, 513-24. allan, g., hanley, n., mcgregor, p. g., kim swales, j., turner, k. (2006), the macroeconomic rebound effect and the uk economy. final report to the department of environment food and rural affairs, department economics, university of strathclyde. barker, t., ekins, p., foxon, t. (2007), macroeconomic effects of efficiency policies for energy intensive industries: the case of the uk climate change agreements, 2000-2010. energy economics 29(5), 760-78. energy efficiency policies and the jevons paradox 77 brandão, m., clift, r., milà i canals, ll., basson. l. (2010), a life-cycle approach to characterising environmental and economic impacts of multifunctional land-use systems: an integrated assessment in the uk.” sustainability 2(12), 3747-3776. brookes, l. g. (1978), energy policy, the energy price fallacy and the role of nuclear energy in the u.k. energy policy 6, 94–106. carlsson-kanyama, a., engstrom, r., kok, r. (2005), indirect and direct energy requirements of city households in sweden. journal of industrial ecology 9(1-2), 221–236. chapman, p. (1974). energy costs: a review of methods. energy policy 2(2), 91–103. cohen, c., lenzen, m., schaeffer, r. (2005). energy requirements of households in brazil. energy policy 33, 555–562. darby, s. (2006). the effectiveness of feedback on energy consumption. a review of defra of the literature on metering, billing and direct displays. university of oxford. davis, w.b., levine, m.d. train, k.e. (1997), fees and rebates on new vehicles: impacts on fuel efficiency, carbon dioxide emissions, and consumer surplus. transportation research e (logistics and transportation review) 33(1), 1–13. decc (2010), valuation of energy use and greenhouse gas emissions for appraisal and evaluation. department of energy and climate change. uk government. defra (2007), consultation document: energy, cost and carbon savings for the draft eec 2008 11 illustrative mix, department of environment, food and rural affairs, london. dimitropoulos, j. (2007), energy productivity improvements and the rebound effect: an overview of the state of knowledge. energy policy 35(12), 6354-6363. dimitropoulos, j. (2009), energy consumption, behaviour change and the rebound effect. behaviour change for a more sustainable london. london sustainability exchange. september 10, 2009. dimitropoulos, j., sorrell, s. (2006). the rebound effect: microeconomic definitions, extensions and limitations. proceedings of the 29th iaee international conference, potsdam, germany. druckman, a., chitnis, m., sorrell, s., jackson, t. (2010). an investigation into the rebound and backfire effects from abatement actions by uk households. working paper series 05-10, university of surrey. dufournaud, c.m., quinn, j.t., harrington, j.j. (1994), an applied general equilibrium (age) analysis of a policy designed to reduce the household consumption of wood in the sudan. resource and energy economics 16, 69-90. eea (2010). the european environment state and outlook 2010: consumption and the environment. european environment agency, copenhagen, november 2010. ehrhardt-martinez, k., “skip” laitner, j.a. (2008). the size of the u.s. energy efficiency market: generating a more complete picture. washington, dc: american council for a more energyefficient economy. ehrhardt-martinez, k., “skip” laitner , j.a. (2010), rebound, technology and people: mitigating the rebound effect with energy-resource management and people-centered initiatives. 2010 aceee summer study on energy efficiency in buildings. european environment agency (2005). market-based instruments for environmental policy in europe eea technical report no 8/2005. finkbeiner, m., schau, e.m., lehmann, a., traverso, m. (2010), towards life cycle sustainability assessment. sustainability 2(10), 3309-3322. freire-gonzález, j. (2010), empirical evidence of direct rebound effect in catalonia. energy policy 38 (5), 2309-2314. freire-gonzález, j. (2011), methods to empirically estimate direct and indirect rebound effect of energy-saving technological changes in households. ecological modelling 223 (1), 32-40. glomsrød, s., taojuan, w. (2005), coal cleaning: a viable strategy for reduced carbon emissions and improved environment in china? energy policy 33, 525-542. greening, l. a., greene, d. l., difiglio, c. (2000), energy efficiency and consumption the rebound effect a survey. energy policy, 28, 389–401. halog, a., manik, y. (2011), advancing integrated systems modelling framework for life cycle sustainability assessment. sustainability 3(2), 469-499. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.69-79 78 hanley, n.d., mcgregor, p.g., swales, j.k., turner, k.r. (2006), the impact of a stimulus to energy efficiency on the economy and the environment: a regional computable general equilibrium analysis. renewable energy 31, 161-171. herendeen, r., tanak, j. (1976), the energy cost of living. energy, 1(2), 165–78. idae (2007). plan de acción 2008-2012 de la estrategia de ahorro y eficiencia energética en españa. ministerio de industria, turismo y comercio. gobierno de españa. idae (2010). plan de acción de ahorro y eficiencia energética 2011-2020. ministerio de industria, turismo y comercio. gobierno de españa. ipcc (2007). climate change 2007. ipcc fourth assessment report (ar4). jalas, m. (2002), a time use perspective on the materials intensity of consumption. ecological economics 41(1), 109–123. jevons, w. s. (1865), the coal question. london: macmillan and co. khazzoom, j.d. (1980), economic implications of mandated efficiency standards for household appliances. energy journal, 1, 21–39. khazzoom, j.d. (1987), energy savings from the adoption of more efficient appliances. energy journal 8(4), 85–89. khazzoom, j.d. (1989), energy savings from more efficient appliances: a rejoinder. energy journal 10(1), 157–165. khazzoom, j.d., miller, s. (1982), economic implications of mandated efficiency standards for household appliances: response to besen and johnson's comments. energy journal 3(1), 117– 124. kok, r., r. m. j. benders, moll, h.c. (2006), measuring the environmental load of household consumption using some methods based on input–output energy analysis: a comparison of methods and a discussion of results. energy policy, 34(17), 2744–61. levett, r. (2009), rebound and rational public policy-making. in: energy efficiency and sustainable consumption: the rebound effect. herring, h. and sorrell. s. (eds.). new york: palgrave macmillan (st. martin’s press). linares, p., labandeira, x. (2010), energy efficiency: economics and policy. journal of economic surveys 24(3), 573–592. lutzenhiser, l. (2009). behavioral assumptions underlying california residential sector energy efficiency programs. prepared to: ciee behavior and energy program. oakland, ca: ciee. maxwell, d., owen, p., mcandrew. l, muehmel, k. neubauer, a. (2011), addressing the rebound effect. european commission dg environment. meier, a. (2009). how one city cut its electricity use over 30% in six weeks. proceedings of the european council for an energy-efficient economy summer study. odum, w. (1982), environmental degradation and the tyranny of small decisions. bioscience 32(9), 728-729. organisation for economic co-operation and development (oecd) (2005). the use of multiple policy instruments for environmental protection: an economic perspective. env/epoc/wpnep (2005) 5. ouyang j, long, e., hokao, k. (2010), rebound effect in chinese household energy efficiency and solution for mitigating it. energy, 35(12), 5269-5276. pigou, a. c. (1920), the economics of welfare. macmillan, london. schneider, f. (2008), macroscopic rebound effects as argument for economic de growth, ecological sustainability and social equity. paris. puig-ventosa, i. (2004), potential use of feebate systems to foster environmentally sound urban waste management. international journal of integrated waste management 24, 3-7. semboja, h.h.h. (1994), the effects of an increase in energy efficiency on the kenyan economy. energy policy, 1994, 217-225. sen, a.k. (1967), isolation, assurance, and the social rate of discount. quarterly journal of economics 81, 112-124. sorrell, s. (2007), the rebound effect: an assessment of the evidence for economy-wide energy savings from improved energy efficiency. uk energy research centre. october, 2007. takase, k.y., kondo, k. washizu, a. (2005), an analysis of sustainable consumption by the waste input–output model. journal of industrial ecology 9(1-2), 201–219. energy efficiency policies and the jevons paradox 79 unep (2010), assessing the environmental impacts of consumption and production: priority products and materials, a report of the working group on the environmental impacts of products and materials to the international panel for sustainable resource management. hertwich, e., van der voet, e., suh, s., tukker, a., huijbregts m., kazmierczyk, p., lenzen, m., mcneely, j., moriguchi, y., vikstrom, p. (2004). energy efficiency and energy demand: a historical cge investigation on the rebound effect in the swedish economy 1957, paper presented at: input-output and general equilibrium data, modelling and policy analysis, brussels, 2-4 september. washida, t. (2004), economy-wide model of rebound effect for environmental policy, article presented at: international workshop on sustainable consumption, university of leeds, 5-6 march. wright a.j., formby j. r. holmes, s.j. (2000), a review of the energy efficiency and other benefits of advanced utility metering. ea technology. . international journal of energy economics and policy | vol 10 • issue 1 • 2020 331 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(1), 331-341. the problems of china as a major consumer of energy resources natalia victorovna kuznetsova1, alla anatolyevna kravchenko2* 1doctor of economic science, professor, department of world economy, school of economics and management, far eastern federal university, suhanova st. 8., vladivostok 690950, russia, 2candidate of economic sciences, department of world economics, school of economics and management, far eastern federal university, suhanova st. 8., vladivostok 690950, russia. *email: kravchenko.aa@dvfu.ru received: 26 july 2019 accepted: 03 october 2019 doi: https://doi.org/10.32479/ijeep.8478 abstract the high rates of development in china are increasingly indicated the insufficiency of their own energy resources to maintain the positive dynamics of the growth of the national economy. in the absence of structural changes in the chinese energy industry, exacerbation of the environmental problem is likely to reduce the inflow of foreign direct investment, on which the prc economy is also mainly dependent. it is justified that with the rapid growth of the chinese economy, the problems are growing as the obstacle to the further economic development of the country; it is growing the interdependence of the chinese and world economies, which is a hidden threat to the stability and well-being of the global economy represented by the prc. keywords: gdp growth rates, export, import, living standards, energy resources, energy consumption jel classifications: q4, o3 1. introduction china is one of the leaders of the modern world economy. due to its competitive advantages and competent economic policy of the last decades, it managed to turn from a backward agrarian country into one of the most dynamically developing and having a huge influence of the economies of the world. we entered a new stage in the development of the world economic system, the success of which will be determined by the readiness to respond to the great challenges of our time. each national system will increasingly surpass from its development if it cannot anticipate and adapt to the qualitative changes dictated by the great challenges. modern challenges associated with global economic processes, global political risks and changes in the international security situation force resource-insufficient states to look for ways to stabilize their energy supplies. this task has reached one of the priority places in the prc’s foreign policy during the past 10-15 years. over the past 40 years, china has shown rapid and significant economic growth, passed the way from agrarian to industrial economy: its gdp increased by an average of 9.8% per year, which represents dynamic economic growth, which is currently making china the second largest economy in the world for nominal gdp after the usa. the purpose of this research is to assess the achievements and problems of the energy sector of the prc. in this research, we look at the energy problems of china. we prove that the depth of the problems with an increase in energy consumption, is determined by the extremely low rates of growth in the efficiency of chinese energy, which involves a number of other economic and social problems. the high rates of development in china are increasingly indicated the insufficiency of their own energy resources to maintain the positive dynamics of the growth of the national economy. however, the high rates of the chinese economy were not ensured by the corresponding development of the fuel and energy complex, which is a problem for the further development of china. the rpc this journal is licensed under a creative commons attribution 4.0 international license kuznetsova and kravchenko: the problems of china as a major consumer of energy resources international journal of energy economics and policy | vol 10 • issue 1 • 2020332 is increasingly moving into the category of net energy importers. the structure of the chinese energy entails negative consequences it is the real obstacles to the development of the chinese economy. in the absence of structural changes in the chinese energy industry, exacerbation of the environmental problem is likely to reduce the inflow of foreign direct investment, on which the prc economy is also mainly dependent. 2. the main problems of china energy industry 2.1. problem 1: insufficiency of own sources of energy according to international estimates, in 2017, the explored sources of oil in the prc are enough to satisfy the current level of consumption over 10 years, natural gas 25, coal 30 years (bp statistical review of world energy, 2017). however, it should not be overestimated the role of the “chinese factor” in the world oil market: this country’s share in world fuel imports is still relatively modest, as evidenced by the data in table 1 on the prc’s share in world fossil fuel reserves. moreover, since 2009, china is the leader in terms of primary energy consumption in the world. in 2007, this indicator amounted to 23.2% of all primary energy consumed in the world economy. the main source of energy in china is coal, as can be seen from the dynamics of primary energy consumption in china (figure 1). according to the data in figure 2, the usa and the prc are the world leaders in terms of energy consumption. however, the chinese economy is characterized by fairly large volumes of oil and oil products imports, which is also one of the main signs of the high degree of dependence of the chinese economy on the international energy market. it is not only a growing problem of the chinese economy, but also a significant problem for the global economy. figure 3 demonstrates that the total energy consumption in china is increasing, while in the usa it is decreasing. but this confirms that developed countries are on the path to reducing energy costs, and an increase in the rate of growth in energy consumption is not automatically a sign of a growing economy. according to figure 4, over the past decade the energy production and energy consumption in the prc has grown rapidly, however, energy consumption has also increased in excess of energy consumption. in this connection, the volumes of the energy balance of trade has increased. at the same time, it is important to note that during the analyzed time period (1990-2017) (figure 5), there was a periodic decline in the share of energy imports in total energy consumption. the shortage of energy resources in china actualizes the problem of energy saving, both in everyday life and in production, which is very energy-intensive. table 1: the prc’s share of the world’s fossil fuel reserves year coal oil natural gas stocks, billion tons share, % stocks, billion tons share, % stocks, trillion cc m share, % 2000 114.5 11.6 3.3 2.3 1.4 0.9 2010 114.5 13.3 2.0 1.1 2.8 1.5 2016 114.5 12.8 2.5 1.1 3.8 2.1 source: calculated according to the national statistical office of china figure 1: dynamics of primary energy consumption in the prc in 2000-2017, mln source: share of renewable energy in power generation, 2018 source: share of renewable energy in power generation, 2018; global energy internet development cooperation, 2017 figure 2: total energy consumption by country (total energy consumption (mtoe) kuznetsova and kravchenko: the problems of china as a major consumer of energy resources international journal of energy economics and policy | vol 10 • issue 1 • 2020 333 thus, the volumes of energy production do not correspond to the growth rates of energy consumption. 2.2. problem 2: unbalanced structure of energy supply and energy consumption according to table 2, the main source of energy in china in 2017 is coal, its share in the country’s energy balance is 64%, oil takes the second place 19%. crude oil is also an important component of the country’s energy balance, and gradually its share increases. if in the 1950s it was considered that china has low level of oil reserves, and its share in energy production did not exceed 2%, then in the 1960-80s its share gradually grew and reached 23.8% in 1980. however, later, due to the rapid growth of energy consumption during the economic reform, the rate of oil exploration and oil production began to noticeably lag from the country’s requirements for crude oil and oil products. since 1992, the energy balance in the prc has become negative, and consumption has become significantly higher than production. then, the energy deficit continued to grow, and in 2005 it has already amounted to 172.5 mln. during the 11th five-year plan (2006-2010), the energy deficit continued to grow in the conditions of high gdp growth rates in general and in the manufacturing in particular. since 2007, the volume of energy consumption exceeded the production volume by more than 300 million tons of equivalent fuel. the specific feature of china is a significant difference in the structure of energy consumption from other countries. the coal energy has historically developed in this country. the structure of energy consumption in the prc is presented in table 3. 2.3. problem 3: critical level of environmental pollution the country, possessing large reserves of uranium and great potential in hydro, solar and wind power (boqiang and chunping, 2013), is gradually reducing the share of coal and intends to increase the share of alternative energy to 15% in the country’s total energy balance by 2020. although it is justified from a resource point of view, many negative consequences of the preferential use of coal (primarily environmental) are becoming catastrophic: nowadays, china is on the verge of an ecological disaster. according to figure 6, co2 emissions from fossil fuels in china from 1978 to 2017 increased almost 6.5 times, and the average growth rate was 17%. in 2017, the growth rate of emissions in china was transferred to a positive growth zone (growth in co2 volumes in 2017 was + 1.3% after 0.5% in 2015 and 2016). source: share of renewable energy in power generation, 2018 figure 3: the total energy consumption of china and the us energy balance of trade (mtoe) source: share of renewable energy in power generation, 2018 figure 4: comparison of energy production, energy consumption, energy trade balance, energy intensity and renewable energy sources table 2: the structure of the modern energy balance of the prc in 2012 and 2017 types of resources indicators quantity share of world (%) the structure of the energy balance, 2017 (%) 2012 2017 2012 2017 2012 2017 total primary energy consumption (million tons) 2613.55 3014.43 21.3 22.9 100 100 oil stocks (million tons) 2000 2500 0.9 1.1 17.67 18.58 production (million tons) 203.6 215 5.1 4.9 consumption (million tons) 461.8 560 11.4 12.9 natural gas stocks (billion cubic meters) 3100 3800 1.5 2.1 4.48 5.87 production (billion cubic meters) 102.5 138.0 3.1 4.8 consumption (billion cubic meters/million tonnes of oil equivalent) 131/117 197/177 4.0 4.7 coal stocks (million tons) 114500 114500 13.3 12.8 70.38 63.69 production (million tons e.) 1956 1827 49.5 47.7 nuclear energy consumption (million tons e.) 1839.4 1920 49.4 50 consumption (million tons e.) 19.5 38 3.3 6.6 0.75 1.26 hydro-electric power consumption (million tons e.) 157 255 19.8 28.5 6.00 8.46 renewable energy biofuels (million tons e.) 1.149 2.43 2.0 3.2 0.72 2.14 other species (million tons e.) 17.7 62 9.1 17.2 source: calculated using вр statistical review of world energy 2012; 2017 kuznetsova and kravchenko: the problems of china as a major consumer of energy resources international journal of energy economics and policy | vol 10 • issue 1 • 2020334 since 2005, china has been the largest emitter of carbon dioxide in the world, in 2017, china produced 27.6% of its total emissions, but by the end of this year, china has reduced co2 emissions per unit of gdp by 46% compared to 2005, fulfilling its commitment taken in the framework of the paris climate agreement (2015), to reduce the intensity of co2 emissions by 40-45% from the 2005 level by 2020 (boqiang and chunping, 2013). 2.4. problem 4: irregular territorial distribution of energy resources it should be noted another problem of the prc. the macroregions of china differ significantly from each other in the provision of energy resources. the distribution of energy takes place according to the scheme coal in the north, electricity in the south, oil in the east, gas in the west. if you allocate energy reserves in china to six major economic regions, then the north china will be most energy-secured 43% of all energy reserves, the south-west china 28.6% and the north-west china 12.1%. the largest reserves of coal are concentrated in the north china (64%), hydro resources in the south-west (70%), and oil and natural gas in the north east china (48.3%) (gao and dong, 2007). thus, almost all natural gas is produced in the western regions far from the main sources of consumption, which makes it extremely difficult to use as one of the main energy sources (aristova, 2014). the absolute increase in its production in the 2000s was concentrated mainly in the east of the country (table 4). guangdong and jiangsu provinces were also major consumers of domestic gas, and in total in china 170 million citizens had access to domestic natural gas in 2010. the most developed regions of the country use the clear energy. at the same time, the growth of natural gas consumption was fairly evenly distributed in almost all regions of china. in connection with the differentiation of the economies of the chinese provinces, we calculated the integral indicator (province development ratio). the formula for calculating the development rate is following: ced spi ssi sti = ∑( ; );1 3 1 2 100 (1) ced development rate; spi share of extractive industry in grp; ssi share of manufacturing in grp; sti share of service sector in grp. we received the following results. the most part of the chinese provinces are characterized by a lower degree of development of the economy with a development coefficient in the range of 0.61-0.68. eight provinces are characterized by a higher level of economic development, however, with a relatively low development rate in the range from 0.681 to 0.75. it is also noteworthy that most of the chinese provinces of this group are located in the coastal zone or closer to the southern border of the prc. the next range of development rates from 0.751 to 0.82 included only one territorial entity of china shanghai. this subject is located in the coastal zone of the prc and, as noted before, it is characterized by a high share of the service sector in the grp, which influenced the level of development coefficient (table 5). the last range of the most developed provinces of china, characterized by a development rate in the range of 0.821-0.89, includes only two territorial subjects of the prc beijing and taiwan. table 3: the structure of energy consumption in the prc year total energy consumption (million tons of ne.) coal (%) oil (%) natural gas (%) 1957 96.44 92.3 4.6 0.1 1962 165.4 89.2 6.6 0.9 1965 189.0 86.5 10.3 0.9 1970 292.9 80.9 14.7 0.9 1975 454.3 71.9 21.1 2.5 1980 602.8 72.2 20.7 3.1 1985 766.8 75.8 17.1 2.2 1990 987.0 76.2 16.6 2.1 1999 1220.0 67.1 23.4 2.8 2003 1204.2 69.3 22.1 2.4 2006 1729.8 70.2 20.4 2.9 2011 2432.2 70.5 17.6 4.0 2013 2735.2 68.5 17.7 4.7 2014 2903.9 67.3 17.7 5.1 2015 2970.3 65.6 17.7 5.7 2016 3014.0 63.7 18.6 5.9 source: national statistical office of the people’s republic of china, 2013-2017 source: national statistical office of the people’s republic of china, 2013-2017 figure 6: co2 emissions from fuel combustion (mtco2) figure 5: energy intensity per unit of gdp at constant purchasing power parity (ppp) (gdp energy intensity at constant purchasing power parities (thous. usd/usd) (energy intensity of gdp at constant purchasing power parities (koe/$2015p) source: share of renewable energy in power generation, 2018 kuznetsova and kravchenko: the problems of china as a major consumer of energy resources international journal of energy economics and policy | vol 10 • issue 1 • 2020 335 thereby, the territorial entities of china located in the coastal zone or closer to the southern border of the country are characterized by a higher level of economic development than other provinces. it is also important to note that the share of provinces with a relatively more developed economy is substantially small. 2.5. problem 5: the high level of dependence on hydrocarbon imports, especially oil the largest share in the consumption of petroleum products accounts for industry and transport. the share of consumption of petroleum products in the transport sector is constantly growing. from 2013, the share of transport began to exceed the share of industry in the structure of consumption of petroleum products of china (in 2014, the share of industry 35%, transport 38%), while in 1990 the transport sector of the economy consumed 4 times less products oil refining than in the industrial sector (industry’s share 64%, transport 15%) (china statistical yearbook, 2016). according to the researches of b. lin, gdp growth in china is directly dependent on the growth of oil consumption in the transport sector of the economy (boqiang and chunping, 2013). whereas, motorization of china is at a relatively beginning stage of development, it can be assumed that oil imports will continue to increase (figure 7). as a result of the analytical review, the main economic factors were identified, and the research hypothesis is that there is the influence between these factors and oil consumption in the prc. to solve this problem, within the framework of the hypothesis table 5: data of the sectoral structure of the economy and the calculated coefficient of development of the provinces of the prc province of china share of extractive industry in grp (%) share of manufacturing in grp (%) share of service sector in grp (%) development rate henan 14.1 57.3 28.6 0.6195 xinjiang uygur 19.8 47.7 32.5 0.6295 jiangxi 12.8 54.2 33 0.643667 anhui 14 52.1 33.9 0.646167 guangxi zhuang 17.5 47.1 35.4 0.647833 sichuan 14.4 50.5 35.1 0.6515 hebei 12.8 52 35.2 0.654667 qinghai 10 55.1 34.9 0.657833 jilin 12.1 52 35.9 0.659333 gansu 14.5 48.2 37.3 0.662333 inner mongolia 9.4 54.5 36.1 0.664833 heilongjiang 12.6 50.2 37.2 0.665 shaanxi 9.8 53.8 36.4 0.665667 hubei 13.4 48.7 37.9 0.667167 chongqing 8.6 55 36.4 0.667667 shandong 9.2 54.2 36.6 0.667667 yunnan 15.3 44.6 40 0.674 hunan 14.5 45.8 39.7 0.674333 shanxi 6 56.9 37.1 0.6755 liaoning 9.3 52 38.7 0.678 fujian 9.3 51 39.7 0.683 hainan 26.2 27.7 46.2 0.687833 ningxia hui 9.4 49 41.6 0.692333 jiangsu 6.1 52.5 41.4 0.696833 zhejiang 4.9 51.6 43.5 0.709333 guizhou 13.6 39.1 47.3 0.713833 guangdong 5 50 45 0.716667 tianjin 1.6 52.4 46 0.727333 tibetan 13.5 32.3 54.2 0.7485 shanghai 0.7 42.1 57.3 0.785833 taiwan 1.6 31.1 67.2 0.832833 beijin 0.9 24 75.1 0.874 source: calculated by china provinces and cities-hktdc table 4: production and consumption of electricity in the regions of china, billion kwh region/year production consumption 2000 2011 2000 2011 north (beijing, tianjin, hebei, arm, shanxi) 226 652 219 624 northeast 139 243 150 269 west (shanghai, anhui, jiangsu, jiangxi, fujian, shandong, zhejiang) 406 1184 423 1266 center-south (henan, hubei, hunan, guangdong, hainan, gchar) 323 873 333 929 southwest (sichuan, yunnan, guizhou, tar, chongqing) 138 462 142 354 northwest (shaanxi, gansu, nhar, xuar, qinghai) 98 301 102 280 source: calculated by statistical yearbook of china energy, 2010 kuznetsova and kravchenko: the problems of china as a major consumer of energy resources international journal of energy economics and policy | vol 10 • issue 1 • 2020336 on the composition of the causal block of influencing factors on oil consumption by the country, the econometric analysis of the statistical data set was carried out. to construct the regression equations, it was collected the annual data for 45 years (1971-2015) from statistical sources in accordance with the results of the analytical review. the oil consumption in the transportation industry indirectly characterizes factors x2 and x3; the oil consumption in the energy sector factor x4; in production factor x5. the main factors hypothetically affecting oil consumption in the country was listed below: y oil consumption million barrels per day; x1 total population, million people; x2 energy consumption in the road sector, mln toe; x3 air transportation of passengers registered in the country, mln.; x4 electricity production on the basis of oil and petroleum products, billion kw/h.; x5 gva in “production,” in 2010 prices of 10 billion usd; x6 gross output, billion usd, 2010 prices. calculations are made by (world development indicators, 2017; bp statistical review of world energy, 2017). to solve the problems, associated with the occurrence of false correlation and heteroscedasticity, the regression equations were constructed for stationary series, for which the indicators were converted into growth rates. the econometric analysis was carried out in two successive stages. firstly, the hypothesis about the effect of the dynamics of gdp (factor x6) on the growth rate of oil consumption was tested. the constructed regression equations allowed us to accept the hypothesis of a positive relationship between the dynamics of oil consumption and gdp. moreover, for the prc, as a result of its energy saving policy, in the absence of gdp growth, the rate of oil consumption will decline. the regression equation between the growth rate of oil consumption and the growth rate of gdp: yt=−0.001+0.65x7t+et (0.02)r2=14% at the second stage of calculations, in order to understand the impact of the causal complex, gdp was replaced with components and the share of influence of each factor on oil consumption in the country was revealed. to solve the problem of multicollinearity, the regression analysis was performed using the step-by-step method. source: international energy data, 2018 figure 7: imports of electricity (billion kilowatt hours) figure 8: map of nuclear power plants in china source: china statistical yearbook, 2016 kuznetsova and kravchenko: the problems of china as a major consumer of energy resources international journal of energy economics and policy | vol 10 • issue 1 • 2020 337 to determine the degree of influence of each factor, the regression equations were based on the analysis of partial correlations. there is the construction of multiple regression equation: y=−0.04+0.34x2t+0.09x5t+et (0.003)(0.003) r2 = 35% as a result, for the prc, priority factors were identified that affect oil consumption in the country. the calculations showed that the growth of oil consumption is associated with the growing needs of the national transport for energy resources, and with the growing demand for electricity. in modern technological and economic conditions, oil remains one of the key resources for energy supply. 3. directions of china energy development 3.1. direction 1: creation a single unified energy grid the network complex of china is characterized by the fact that there is no single energy grid in the country. six regional grid systems are in operation, which increases the risk of local power shortages: for example, the hydro potential of the western part cannot be used to its fullest to supply the southern coastal provinces, so an important task for the chinese government is to create a unified energy grid. according to plans, by the end of 2020, china will build 15 large high-voltage transmission lines (800-1000 kv). most of the technologies in the network complex of china are western. equipment is usually produced in local factories. the main suppliers of technological solutions in terms of high-voltage dc networks for china are the swedish concern abb and german siemens. 3.2. direction 2: changes in energy sources china encourages the development of clean technologies for the development of deposits and the use of coal, stimulates the development of advanced technologies, coal gasification, for example, integrated gasification combined cycle igcc, continuous coking in the fluidized bed cfb, nuclear reactors of the third generation with water pwr and gas cooled hightemperature reactors htgr. at present, the consumption of such types of energy as nuclear power plants and renewable energy sources, as well as small hydroelectric power stations, hydrothermal energy, energy of tides and seas has significantly increased. however, for 20-30 years there are no obvious structural changes in the energy consumption of electricity. coal dominates with about 85% and after the hydroelectric station in 5-7%. it can be observed that in china, since 2004, new segments have appeared in the production of electricity from alternative sources and fuels like the sun, wind, tides, biofuels. in the general structure, they are completely invisible, but there is significant growth. we don’t consider that it will somehow affect the energy balance in the next 10 years, because their growth is not comparable with the necessities of the economy and the net annual increment in energy production. nowadays, the 35 nuclear power units are in operation in china and another 21 are under construction. every year, the prc plans to commission 6-8 power units, by 2030 its number will exceed 110 (figure 8). cnnc and cgn are chinese and french reactor technologies, but the american “denial” of the melt trap has moved into the “dragon-1” project. and, since the projects of all three chinese atomic energy companies use the same heat removal technology in case of alleged accidents, let’s look at the details of this solution. the purely subjective opinion is obvious: we do not see any logic in rejecting the trap, because this technology is not so complicated, but it is completely reliable. but decisions on this issue, of course, takes by the regulatory and supervisory authorities of the countries with which the chinese experts are negotiating. here is a brief description of the so-called “ivr strategy” retention of damaged or molten fuel inside the reactor vessel; the melt trap is not provided for in the project. in recent years, china has remained the undisputed leader in the development of renewable energy in terms of the installed generating capacity of hydropower plants (352 gw), wind farms (184 gw) and ses (175 gw). solar energy has long overtaken the goal set out in the five-year plan for 2020 at table 6: installed wind power capacity by country, 2016 (mw) country total installed power growth in 2016 china 148000 32970 usa 74347 8598 germany 45192 4919 india 24759 2294 spain 22987 0 great britain 13614 1174 source: world wind energy association, 2016 figure 9: structure of installed generating capacity and power generation, 2018 source: international energy data, 2018 kuznetsova and kravchenko: the problems of china as a major consumer of energy resources international journal of energy economics and policy | vol 10 • issue 1 • 2020338 110 gw. in june 2018, in china it was decided to stop issuing subsidies for the construction of new ses, phased reduction of “green” tariffs and encouraging projects that do not require government subsidies. in order to reduce the share of coal-fired power plants in china, nuclear and renewable energy is actively developing. as of march 2019, there are 45 nuclear reactors with a capacity of 44.6 gw in china, about 15 units are under construction. by 2020, the installed capacity of nuclear power plants should increase to 58 gw, and by 2030 to 150 gw. however, nowadays the situation is far from the forecast (figure 9). the obvious disproportion is an extremely low proportion of a power plant that uses gas (about 2%) and nuclear power plants (no more than 3%). in the middle 1990s there were no gas stations in china at all, 10 years ago it began to appear. since then, the growth is five or more times, but china’s energy intensity and energy demand is so great that this growth has little effect on the energy structure (ren21, 2015; renewable energy policy network for the 21st century, 2018). since 2008, the large-scale development of wind energy has begun. the report of the international organization for the support of renewable energy ren21, published on june 1, 2016, states that in 2015, china invested 102.9 billion usd (1/3 of the world) in the construction of renewable energy facilities) (cautious europe cuts renewable energy investments, 2018). nowadays, in china, there are 12 thousand megawatts of capacity, generating electricity using wind (table 6). for the most part these are 50and 100-megawatt farms, as well as many medium-sized farms under construction. in addition, according to the wind base program, six megacomplexes are created, each with a capacity of at least 10 gigawatts. these complexes are located in the provinces of gansu (15 gigawatts), western inner mongolia (20 gigawatts), eastern inner mongolia (30 gigawatts), hebei (10 gigawatts), xinjiang (20 gigawatts) and along the coast north of shanghai in jiangsu province (10 gigawatts). in table 7, we can see insufficient development of renewable energy sources. 3.3. direction 3: reducing the intensity of energy use china recorded a significant decrease in energy use intensity, although it was slower than in 2016, as energy consumption accelerated in 2017. china’s high energy intensity is mainly due to the predominance of energy-intensive industries, the exportoriented economy and low energy consumption. energy prices, which is not conducive to improving energy efficiency. in the next 15 years, china predicts a decrease in the average annual growth rate of energy consumption from 8% in 2000-2014 to 3% in 2015-2030, which is caused by a slowdown in economic growth, the development of the services sector and a course for improving energy efficiency. at the same time, the potential for growth in energy consumption depends on the growth of urbanization and infrastructure projects to stimulate the economy and maintain employment. 3.4. direction 4: energy reform with the growth of the economy and the aggravation of the problems of shortage of energy resources, an energy reform is unfolding (table 8). only for 2008-2010 china is actively encroaching on world energy markets and it was quite successfully. the total amount of transactions in 2008 amounted to 24,530 million usd; in 2009 39,670 million usd; for 2010 25,110 million usd (salijanova, 2011). the geography of transactions are canada, brazil, indonesia, usa, argentina, ecuador, russia, venezuela, syria, argentina, australia, mongolia, qatar, england, australia, cameroon, singapore, kazakhstan, iraq, switzerland, iran, yemen, france, england, nigeria, norway, myanmar. from the second half of the xx century to the present, china has been actively developing its hydropower complex, it remains for several years the world leader in the production and consumption of hydropower. in november 2016, the ministry of energy of china announced the plan for the development of the electric power industry in the “13 five-year period” and for the future until 2025. in perspective, the government of the prc plans to increase the total capacity of all hydroelectric power plants to 350 gw by 2020 and to 510 gw by 2050 (zakharov, 2016). according to the latest statistics from the national energy administration (nea), china is currently the largest market for solar photovoltaic (pv) technologies in the world with a total installed capacity of 43.2 gw (2016). china has the first place in the world in this indicator, got ahead of the former undisputed leader germany. it should also be noted that china’s photovoltaic solar power has increased about 13 times since 2011. in addition, most installed solar panels are not yet fully utilized. thus, approximately 30% of installations in 2015 were not fully involved in gansu province, and 26% in xinjiang (according to nea) (lindon, 2016). table 7: dynamics of production of renewable energy sources (billion kilowat) year 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 net generation of traditional thermal power 2560 2623 3132.67 3132.67 3589.98 3648.24 3956.68 3984.92 4008.18 4157.28 net geothermal power generation 0.12 0.14 0.15 0.16 0.13 0.13 0.13 0.13 0.13 0.13 net nuclear power generation 59.3 65.33 65.71 70.96 82.57 92.65 110.71 123.81 161.2 197.83 net hydropower generation 480.41 579.34 609.48 704.27 681.17 854.17 900.52 1 040.63 1103.33 1150.95 net wind power generation 5.71 14.8 26.9 44.62 70.33 95.98 141.2 156.08 185.77 237.07 net power generation 3108.03 3297.47 3527.34 3984.02 4461.71 4735.54 5170.66 5387.91 5562.48 5882.94 source: statistical review of world energy, 2012-2017 kuznetsova and kravchenko: the problems of china as a major consumer of energy resources international journal of energy economics and policy | vol 10 • issue 1 • 2020 339 table 8: the main stages of the energy reform in china year directions of reform purpose 1997 it was established state power corporation, spc to separate commercial activity from the sphere of administrative regulation 2001 strategy “go beyond boundary” opening the way to chinese investment companies in overseas oil projects 2002 it was launched electricity reform it was established state energy administration the state energy corporation has been reorganized, dividing into seven generating companies and two grid companies (state grid corporation of china, china southern power grid) these companies currently produce more than 50% of electricity and own the entire network infrastructure 2004 the state council of china adopted a program for the development of alternative energy for the medium and long term (2004-2020) investment in the industry for a total of 2 trillion yuan (about 300 billion usd) pilot projects of electricity markets launched in the west and north-west of china 2005 it was adopted a law on renewable energy a legal framework has been created for the development of alternative energy in the country, sources of financing have been identified, and relations between renewable energy producers and owners of power grids in china have been regulated. 2006 the state committee for the development of reform of the people’s republic of china has decided to liberalize the price of coal since 2007 a coal market has been created, based on the all-china coal stock exchange with regional stock markets. 2007 “china energy development report 2007” (the so-called blue book) and “white paper on china’s energy situation and policy” it is declared that the energy policy is an integral part of the long-term comprehensive program of modernization of the prc. 2008 the law “on energy saving” 2010 the law “on renewable energy” 2014 the decree, in which it was noticed that in china it is necessary to increase the share of renewable energy by 2030 in the structure of energy consumption to 30% to do this, it is necessary to increase the production of electricity from renewable energy sources by 800 gw (zakharov, 2016) 2015 document no. 9 of the state council on the further strengthening of the institutional reform of the electric power industry and six documents implementing the provisions of the document the pricing mechanism on the wholesale electricity market, electricity trading, load distribution schemes, electricity distribution, retail market liberalization, management of coal-fired thermal power plants for own needs were painted 2016 geothermal energy development plan (prospects and problems of geothermal energy, 2015) introduced into the program of the 13th five-year plan (2016-2020) 2017 “plan for the development of the gas industry in the period of the 13th five-year plan” (2016-2020) in this plan, as a “indicative” indicator of gas supplies to the chinese market in 2020, a value of 360 billion cubic meters is given about 79% of companies, located in tibet, work on solar energy. in the area of mount chomolungma at the altitude of 5200, 5820 and 6500 meters above sea level, china mobile’s solar energy bases also operate, which cover the climbing routes with a signal, which makes them more convenient and safe for tourists. despite the fact that china has reached the first position in the world in terms of the development of solar energy, there are still a number of important problems in the country. according to opinion of the head of the solar energy division of the china electromechanical production and commercial company sun guangbin, there are many problems that impede the development of china’s solar power. he says: “at present, the core technologies and equipment, market demand and the main raw materials necessary for the full development of solar energy in the country still rely on foreign countries, which is a significant barrier to the further development of the solar industry in china. nowadays, almost all core technologies and equipment are borrowed from abroad, more than 90% of raw materials are imported and 98% of sales go to meet the demand of foreign consumers”. thus, sun guangbin noted that china’s solar power industry has not yet developed a system for self-development and implementation of new products (shaw, 2010; jian, 2018). environmental specialist from beijing, zhang junfeng, is confident that hydroelectric power plants adversely affect the country’s environment. in his opinion, the new power plants will in fact not help china, except for the official figure of gdp. he notes that “hydroelectric power sources are mainly located in mountainous areas, which in china are the weakest from a geological point of view. the construction will undoubtedly entail a change in the local geosystem. it can be a cause of earthquakes, landslides, soil and water conservation, as well as a cause of other problems. however, china has grand plans to build new hydropower plants and increase the energy capacity of the country (yukun, 2016). the problem of renewable resources is in its unpredictability and uncontrollability. you get electricity not when you need it, but when the appropriate environmental conditions come together. it is an obvious disadvantage compared to the traditional generation. and here we wisely will not touch the extremely large-scale issue of maneuvering of capacities. at the beginning of 2017, germany was already confronted with large-scale outages due to cloudy, windless weather. and yet they are not the only ones who have suffered from such misfortune. the state of south australia in the second half of 2016 abandoned from kuznetsova and kravchenko: the problems of china as a major consumer of energy resources international journal of energy economics and policy | vol 10 • issue 1 • 2020340 the coal. and if on average in australia, according to fortune, the share of renewable energy is 7%, then south australia has brought it to 45.6% (31.2% is wind energy, 14.4% is solar energy). natural gas in this region provides 49.1% of electricity generation. with the transition to renewable energy sources, south australia has experienced a twofold increase in wholesale electricity prices and frequent outages. so far, all renewable energy relies on traditional energy storage technologies, which have reached the threshold of its development. germany, australia or any other region – it does not matter. if this region decides to create drives to support renewable energy, then the first thing it does is to load the mining industry. then the chemical production. and at the end of the operating cycle, there will be a necessity for safety and extremely costly disposal. although, renewable energy has become a mass phenomenon on a global scale; but it cannot function completely without the support of traditional generation. at the same time, nowadays, with the current level of technology development, it would be a fatal mistake to thoughtlessly and uncontrollably expand the renewable energy sector. 4. conclusion as a conclusion, for china, as an economic leader not only in regional scale, but also in global scale, energy problems become extremely urgent and even strategically important. the following energy problems remain in china: low energy consumption per capita; lack of own energy reserves; low quality of existing deposits; low energy efficiency of the economy; uneven territorial distribution of energy resources; unbalanced structure of energy supply and energy consumption; high dependence on imported hydrocarbons, especially oil. at the same time achieving new economic goals, china moved to a leading position in the field of environmental pollution. energy issues are of interest to all asian countries, but for china the energy problem has become a big challenge. china will base its strategy of resolving the issue of tension with energy supply, based on its own resources, while certain imports will be saved to meet the growing demand for energy. nowadays, the chinese government pays great attention to the development of an effective domestic energy strategy. the relevant departments are taking active measures to optimize the fuel and energy complex, to introduce new technologies for the production of electricity, to develop technologies for “clean” coal, to increase the share of the usage of natural gas, hydroelectric power plants, nuclear power plants, wind energy and other alternative sources of energy. the chinese government in these areas has achieved significant success; however, to maintain the current pace of economic development of the country, these measures are not enough. in this situation, china has to develop, in addition to its national energy policy, an external energy strategy. 5. acknowledgments the results were received on the basis of the implementation of the scientific project of the russian foundation for basic research (rfbr) no. 18-014-00001 «the model of the multi-vector socioeconomic policy of interaction between the russian far east and the apr countries ways of reducing the unexpected effects from the onset of “grand challenges.” references aristova, l.b., luzyanin, s.g., semenova, n.k., tomberg, i.r., dawei, p., yongxiang, s., yuli, y., jianrong, z., lifan, l. (2014), in: luzyanin, s.g., semenova, n.k., editors. potential and perspective of prc-rf cooperation and unconventional energy. moscow: institute of oriental studies, ras, center for strategic conjuncture. p254. boqiang, l., chunping, x. (2013), estimation on oil demand and oil saving potential of china’s road transport sector. energy policy, 61, 472-482. bp statistical review of world energy. (2012), available from: https:// www.laohamutuk.org/dvd/docs/bpwer2012report.pdf. bp statistical review of world energy. (2017), available from: http:// www.bp.com/content/dam/bp-сountry/eses/statistical_review_of_ world_energy_2017.pdf. cautious europe reduces investment in renewable energy. (2017), available from: http://www.neftegaz.ru/news/view/149691ostorozhnaya-evropa-sokraschaet-investitsii-v-vozobnovlyaemyeistochniki-energii. china began construction of a tower-style solar power plant. (2015), available from: http://www.neftegaz.ru/news/view/139696-v-kitaenachalos-stroitelstvo-solnechnoy-elektrostantsii-bashennogo-tipa. china provinces and cities. hktdc. available from: http://www. hktdc.com/info/mi/a/mpcn/en/1x06boqa/1/profiles-of-chinaprovinces-cities-and-industrial-parks/china-cities-provinces.htm. [last accessed on 2017 feb 15]. china statistical yearbook. (2016), national bureau of statistics of china, 2017. available from: http://www.stats.gov.cn/english/ statisticaldata/annualdata. gao, c., dong, s. (2007), china’s energy strategy based on the concept of harmony. zhongguo nyyyuan (china energy), 3, 18-19. global energy internet development cooperation. (2017), global energy internet development and prospects for 2017. beijing: geidco. international energy data, monthly update. (2018), available from: https://www.knoema.ru/eiaintl2018may/international-energydata-monthly-update. jian, x. (2018), technical path of international energy transformation and the role of china. journal of yunnan university (social science publication), 3, 136-144. lindon, h. (2016), china tops world in total installed solar pv, passes germany. available from: https://www.cleantechnica.com/2016/02/09/ china-tops-world-in-total-installed-solar-pv-passes-germany. national statistical office of the people’s republic of china, chinese statistical yearbook. available from: http://www.stats.gov.cn. prospects and problems of geothermal energy. (2015), available from: https://www.pronedra.ru/alternative/2015/12/29/perspektivygeotermalnoy-energetiki. ren21-renewable energy policy network. economic commission for europe (ece) available from: http://www.unece.org/fileadmin/ dam/energy/se/pdfs/gere/publ/2015/ren21_unece_status_ russian.pdf. renewable energy policy network for the 21st century. (2018), kuznetsova and kravchenko: the problems of china as a major consumer of energy resources international journal of energy economics and policy | vol 10 • issue 1 • 2020 341 renewables 2018 global status report. paris: ren21. salijanova, n. (2011), going out: an overview of china’s outward foreign direct investment. washington: u.s.-china economic and security review commission (uscc). share of renewable energy in power generation. (2018), available from: https://www.yearbook.enerdata.ru/renewables/renewable-inelectricity-production-share.html. shaw, w. (2010), solar industry. china, 11(61), 30-31. wind energy of china. (2010), abirus. available from: http://www. abirus.ru/content/564/623/628/726.html. world development indicators. (2017), the world bank group, 2017. available from: http://www.databank.worldbank.org/data/reports. aspx?source=world-development-indicators#;world-nuclear.org. world wind energy association. (2016), statistics. wind power capacity reaches 546 gw, 60 gw added in 2017. available from: https:// www.wwindea.org/blog/2018/02/12/2017-statistics. yukun, s., liwei, h., pei, h. (2016), a brief account of the practice of developing the technology of intelligent power grids in china. electric power construction, 37(7), 1-11. zakharov, v.e. (2016), analysis of the state and prospects for the development of innovative solutions of renewable energy in china. creative economy, 10(7), 769. . international journal of energy economics and policy | vol 10 • issue 1 • 2020202 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(1), 202-207. trends in corporate energy strategy of russian companies nicole tryndina1*, nikita moiseev2, evgeniy lopatin3, sergey prosekov4, jiang kejun5 1faculty of management, financial university under the government of the russian federation, moscow, russia, 2department of mathematical methods in economics, plekhanov russian university of economics, moscow, russia, 3department of financial markets and banks, financial university under the government of the russian federation, moscow, russia, 4department of sociology and politology, financial university under the government of the russian federation, moscow, russia, 5energy research institute, national development and reform commission, beijing, china. *email: nicoletryndina@yandex.ru received: 30 august 2019 accepted: 13 november 2019 doi: https://doi.org/10.32479/ijeep.8644 abstract this paper proposes to the analysis of russia’s energy strategy, with respect to the interconnection of governmental strategy concerning energy extraction, reproduction and distribution and corporate energy strategies. the current trends in russian energy strategy have been studied on the back ongoing processes in russian corporate energy strategy formulation, with the use of statistical analysis of total volume of energy generated over the period from each source. the conclusions on areas for development and key drivers of corporate energy strategy have been made. keywords: energy, russian energy strategy, corporate energy strategy, energy efficiency jel classifications: c30, d12, q41, q48 1. introduction nowadays, the increasing importance of environmental issues is the trend for building corporate and governmental policies. among other aspects of sustainable growth, the use of energy resources is deemed to be critical. one of the ways to solve these issues is defining the proper long-term sustainable development strategies with respect to the energy use. the concept of energy policies has been considered already in the twentieth century. the following definition of energy policy: energy policy is normally considered an economic issue, a matter of ensuring that safe and secure energy services are available at reasonable cost (christoffersen, 2012). this approach emphasizes the economic or monetary aspect of the concept; it does not consider sustainability and ecology factors due to these issues being relatively young. the modernized approach comprises not only the financial aspect of acquiring and distribution of energy but also social, political and environmental effects. energy policy comprises rules concerning energy sources; energy efficiency; energy prices; energy from abroad; energy infrastructure; and climate and environmental aspects of energy production, utilization, and transit (downs, 2010; grama, 2012). this definition brings us to understanding the importance of sustainability issues consideration in the process of energy production, distribution and consumption. obviously, in these years between publications, mentioned above much has changed. lately, global warming, climate change, water and air pollution are on the global agenda. while policy is a set of rules, strategy is a set of actions, which are critical for achieving the goal, so, these two concepts are interrelated and interconnected. in this paper, energy strategy of russia as one of the main energy producers in the world will be analyzed. this journal is licensed under a creative commons attribution 4.0 international license tryndina, et al.: trends in corporate energy strategy of russian companies international journal of energy economics and policy | vol 10 • issue 1 • 2020 203 2. literature review the energy is critical to economic development and poverty reduction, thus, finding an optimal solution for balancing energy supply and demand in the world is an important issue for government to consider. as for russia, which is one of the most important players in the global energy system and one of the world’s largest producers and exporters of energy. the energy is essential to the security, stability and development of the russian federation, as its economy heavily depends on energy exports. as such, the energy security is a priority (nyangarika et al., 2019a; nyangarika et al., 2019b). therefore, russia needs to improve its energy strategy and energy policy to adapt to the current trends on the global market for energy. moreover, there should be not only governmental policy or strategy, concerning energy safety and security but corporate one as well. a clean energy strategy can help understand energy profile, identify where energy costs come from, and develop a roadmap to improve competitiveness, reduce costs and build business brand reputation. for now, russian energy sector has a well-developed energy strategy up to the year 2030, but on the corporate level there is lack of responsible approach, so, this is the area for the future development. however, this applies not only to russian economy but it is the global trend, as “most firms can’t easily say how much energy they use”. so, this is important to find the connection between governmental and corporate levels of energy strategy and to balance the interests of stakeholders. furthermore, guizhou et al. (2015) categorized issues that might be faced by resource-rich countries. in the prospect of china`s growing energy demand, gulick (2007) focused on energy cooperation between russia and china and also examined the importance of energy. according to christoffersen (2012), energy cooperation between two countries requires constant interconnected policy decisions from both sides. current ukrainian crises has not only brought together two countries but has led to the new energy policy proposals, henderson and mitrova (2016). the global natural gas trade has dominated and largely based on pipeline net that connects countries. in this context, several important issues should be reconsidered: various conflicts between countries, constant growing energy demand and the future of gas pipelines (mikhaylov, 2019; hu and ge, 2014). the future role of natural gas written by røseth (2017) argues that a lack of sufficient facilities hinders development of gas market. diversification as a strategy has occurred right after the realization of growing energy interdependence between countries (mikhaylov, 2018a). however, to put it into a simple definition, diversification is a process of creating a balanced portfolio of procurement resources and supply routes (bansal et al., 2013; mikhaylov, 2018b; denisova et al., 2019). 3. methods energy policy is strongly associated with the measures taken by governments to ensure safe energy supply with consideration of environmental issues. government’s energy policy is decrees and legal acts, while energy strategy is an overall view on how energy issues are managed. the main law, regulating energy issue in russia is the federal law №35-fz “on electroenergetics,” which defines the aspects of energy emission, distribution and reproduction. it considers the authorities, ensuring legal bodies comply with the law and responsibilities of the bodies, involved into the process. energy strategy is a long-term plan of how energy issues are addressed in the country. numerous legal bodies and experts are involved into the process of strategy formulation and implementation. while government’s strategy represents the upper level of energy policy, there is also corporate level and we believe, that there should also emerge household or domestic level. we created a data set using several criteria like it was done in research (mikhaylov et al., 2019). we use statistic tests standard weighted-means analysis anova including f-test. f ms ms ss i ss nt i treatments error treatment error = = / ( ) / 1 (1) where ms is mean square, i is number of treatments and nt is total number of cases to the f-distribution with i−1, t−i degrees of freedom. using the f-distribution is a natural candidate because the test statistic is the ratio of two scaled sums of squares each of which follows a scaled chi-squared distribution. the expected value of f is 1 for no treatment effect. as values of f increase above 1, the evidence is increasingly inconsistent with the null hypothesis. two apparent experimental methods of increasing f are increasing the sample size and reducing the error variance by tight experimental controls. u r n n 1 1 1 1 1 2 = +( ) (2) where n1 is the sample size for sample 1, and r1 is the sum of the ranks in sample 1. russia is one of the main producers and consumers of energy resources and its current energy strategy was chosen as an example for the analysis. main components of any energy strategy include: (1) current results of energy strategy, being undertaken during this period and analysis of its implementation; (2) consideration of main socio-economic trends and further forecasting of interaction between energy and economy; (3) prediction of demand for energy in the country; (4) defining of the key aspects of the state energy policy; (5) prospects of fuel and energy complex of the country; (6) formulation of expected results of strategy’s implementation. tryndina, et al.: trends in corporate energy strategy of russian companies international journal of energy economics and policy | vol 10 • issue 1 • 2020204 while defining energy strategy, clear objectives must be stated. usually, the objectives are identified by external and internal challenges in foreseeable future. according to the energy strategy of russia for the period up to 2035 “as for russian federation, crucial internal challenge lies in the necessity for the energy sector to fulfill its vital role in the transition to an innovative path of economic development.” for russia the following requirements must be met to ensure the objectives completion: 1. living standards level corresponding with ones represented in developed countries; 2. technological and scientific progress should guarantee competitive advantage and energy security; 3. economic structure of the country should shift into less energy-intensive sectors; 4. economy should become oriented on innovative approaches of renewable energy, not export of raw materials; 5. the share of investments in fuel and energy complex should decrease, while the absolute value of investments in energy sector necessary for modernization and development 6. there must be a trend for shifting from energy-intensity to energy-efficiency; 7. steps to limit the impact of energy and fuel complex on the environment, including greenhouse effect, air pollution and gas emission. to overcome external challenges the following must be provided: 1. achievement of sustainable results in the area of foreign economic activities in energy sector; 2. global economic crisis impact minimization and further modernization of economy, caused by changes, which took place as the result of remission after the crisis; 3. increase of russia’s present in high-tech and intellectual services markets; 4. diversification of russian export in the global energy market; 5. switching from selling abroad raw materials to selling highlyprocessed oil; 6. development and promotion of energy infrastructure hubs for new technologies in russia. as can be seen internal and external objectives are interrelated. based on the objectives, the following goals are formulated: 1. enhancing the efficiency of energy reproduction, extraction, processing and distribution; 2. modernization of energy infrastructure and updating the sector practices and technologies; 3. institutional framework establishment in energy sector; 4. efficiency improvement of the sector; 5. integration of country’s energy sector into global energy system. 4. results regarding current trends in russia’s total primary energy supply for the period 1990 to 2016, shown in the table 1, the following observations can be discussed: natural gas still represents the largest share of all energy supplied, 373 391 ktoe in the beginning of the period and 364 253 ktoe in the year 2016. table 1: data summary company name emissions score policy emissions energy use total, giga joules total energy use to revenues, giga joules/usd gazprom pao 64.57 yes 1784370000.00 0.0157 tatneft’ pao 56.07 yes 35654912.22 0.0029 sberbank rossii pao 25.20 no 6273125.00 0.0002 rostelekom pao 24.06 yes 13403241.77 0.0029 surgutneftegaz pao 67.41 yes 173173575.03 0.0085 severstal’ pao 84.22 yes 119559024.00 0.0152 uralkaliy pao 26.80 no 26886032.00 0.0118 vozrozhdenie bank 45.33 no 29405.59 0.0001 gazprom neft’ pao 56.48 yes 50139171.80 0.0015 gmk noril’skiy nikel’ pao 67.03 yes 238401000.00 0.0256 transneft’ pao 97.97 yes 51435071.60 0.0034 mobil’nye telesistemy pao 42.02 no 5497200.00 0.0007 novolipetsk steel pao 57.66 yes 373734702.00 0.0371 mechel pao 17.38 yes 186510413.00 0.0416 mmk pao 72.46 yes 775529702.81 0.0944 novatek pao 67.81 yes 88595480.18 0.0088 afk sistema pao 57.27 yes 156468588.00 0.0130 tmk pao 51.41 yes 44650547.02 0.0102 polyus pao 44.22 yes 28460732.96 0.0103 nk rosneft’ pao 96.09 yes 598000000.00 0.0051 bank vtb pao 69.16 no 1231246.80 0.0001 gruppa lsr pao 83.70 yes 1966000.00 0.0008 rushydro pao 41.82 yes 443680499.12 0.0727 fsk yees pao 60.54 yes 91680417.12 0.0218 phosagro pao 5.22 yes 48924084.01 0.0146 ak alrosa pao 59.22 yes 7044200.00 0.0015 megafon pao 1.53 no 3494949.46 0.0006 mmvb-rts pao 20.24 no 91940174.88 0.1606 source: thomson reuters, minenergo tryndina, et al.: trends in corporate energy strategy of russian companies international journal of energy economics and policy | vol 10 • issue 1 • 2020 205 the second place was represented by primary and secondary oil with 263 778 ktoe in 1990 and 173 263 ktoe in 2016 respectively. coal is the third representing 191 114 ktoe in the year 1990 and 113 287 ktoe at the end of the period. three main energy sources are shrinking in terms of total supply, while nuclear and hydro energy showed an increase in total supply with 31 294 ktoe and 14 266 ktoe in 1990 and 51 579 ktoe and 15 874 ktoe. geothermal and solar energy amount has also increased over the period from 24 ktoe to 165 ktoe, while the amount of energy generated from biofuels and waste fell from 12 182 ktoe to 8 122 ktoe (figure 1). the data (table 1) corresponds to the long-term energy strategy of russia. for example, total supply of energy over the period showed a down-ward sloping trend, traditional and non-renewable sources use decreased, while nuclear, solar, geothermal and hydro energy became more widely used. overall, the trend for less energyintensity, mentioned in the strategy, is being realized in russia, as the total amount of energy supplied fell over 26 years significantly. moreover, russian economy is moving towards modernization of energy and fuel industry and shifting to more sustainable and responsible ways of reproduction of energy. concerning renewable sources of energy, which still does not show the level comparable with one, represented in developed countries, the following results in the year 2016 can be observed below (figure 2). as can be seen from the picture above, the hydro energy represents more than 95% of all renewables, generating energy in russian energy and fuel industry. solar and geothermal sources are one the second place, while wind energy remains not developed. this situation can be explained by already existing infrastructure in russia, some geographical peculiarities of the area, the focus of government policies and scientific researches. another reason for predominance of hydro energy over other renewables is the fact that development of geothermal sources has started to grow rapidly only in 2000s, solar and wind energy sources experienced growth only in 2013, while hydro energy was well developed already in the beginning of 1990s. it means, that this source of energy had more time, thus more monetary and administrative resources, more scientific and technological innovations and infrastructure capacity (table 2). finally, this trend observed in russian energy sector corresponds to the world tendencies: hydro source represents much larger share of generated energy for the forecasts till year 2023, than wind and solar sources. however, in countries, which produce large portion of world energy, biomass is the trend which is being rapidly developed, unfortunately, in russia this type of energy is not showing the same pattern. so, it can be viewed as an opportunity, which is described in russian energy strategy as a shift from non-renewable energy, such as gas and oil to its renewable alternatives. 5. discussion state energy strategy defines corporate strategies, i.e., strategies of firms, operating in the country. thus, state energy policy shapes corporate energy policies. it means that strategies and policies formulated by firms should be in accordance with government’s strategies and policies in a form of legal acts and federal laws. today, no company can escape from following state recommendations and meeting standards of the industry. moreover, being energy responsible and sustainable is not only a question of some legal aspects, it also affects brand equity, in other words, it is a crucial part of how company’s brands are perceived, which directly affects the sales and profit figures (mikhaylov et al., 2018). on the other hand, some energy resources are extremely costly or unavailable for the region, or their use requires purchase of expensive equipment and staff extensive training. so, a firm should find a balance between legislation, sustainability and cost-efficiency. as mentioned above, company’s energy strategy depends on government policy in the field, this creates not only useful guidelines for the firms, but imposes some barriers as well. according to the research (morris and barlaz, 2011) the following principal barriers were identified: access to capital, time and expertise, risks, complexity, either lack of governmental policies or too strict regulations etc. figure 1: russia’s total primary energy supply (ktoe) source: thomson reuters, minenergo source: thomson reuters, minenergo figure 2: electricity generation from renewables by source 2016 tryndina, et al.: trends in corporate energy strategy of russian companies international journal of energy economics and policy | vol 10 • issue 1 • 2020206 as for russia, there was not enough of research done concerning energy management and energy strategy of companies, while the overall strategy and policy is well defined and thoroughly prepared. after the analysis of several large energy and fuel companies, the following similarities of energy strategy have been found: 1. the main principles of corporate energy strategy building are the following: compliance with state regulations, rational use of energy, responsibility, limitation of negative environmental effect of energy use, staff training in the area of energy managements. 2. key areas of corporate energy strategies: running and sponsoring of scientific researches in the area of energy and further implementation of recommendations and conclusions; formulation of corporate set of rules in the field of energy management; identification of basic energy efficiency requirements to the equipment; raising energy issues on the corporate level by organizing staff training; 3. the main actions being taken by companies: implementation and constant improvement of energy management practices to meet international standards iso 50001:2011; equipment modernization with the aim of reduction of energy used; building an image of ecologically responsible company in the eyes of stakeholders; raising employees’ awareness of energy issues and their responsibility for energy efficiency and energy safety; keeping statistical records of energy consumption and energy efficiency. 6. conclusion unfortunately, in russian practice energy issues are more addressed in large fuel or energy-intensive companies, while small firms or firms, whose operational activities are not concerned with energy, lack this responsible approach. thus, this can become one of the future directions of russian energy strategy, which means, more legal regulations and incentives should be addressed to nonfuel companies, as ones representing a large portion of energy consumers (denisova, 2019; nyangarika et al., 2018; bove and lunghi, 2006; meynkhard, 2019). another driver for russian energy strategy is sponsoring and offering financial support to the companies performing in full accordance with best energy safety and energy efficiency practices. major decision-makers in russian business should be motivated to switch from traditional non-renewable energy use to clean and efficient alternatives. finally, teaching and training employees to use energy responsible is a crucial step in enhancing russian energy policy and energy strategy. desirable results can be achieved through social programs, staff trainings, open discussions and public talks, concerning the topic. in total, russian energy strategy is oriented on moving from energy-intensive economy to energy efficient one, with development of renewable sources. overall governmental trends in energy strategy formulation influence energy strategy and energy policy on the corporate level (bolt and cross, 2010). so far, russia has developed a competitive energy strategy which may guarantee energy security, but on the other hand, the level of corporate energy responsibility is the dimension for the future growth (an et al., 2019a; an et al., 2019b). prevailing tendencies of corporate energy strategies of large companies involved into the process of energy emission, production, distribution or massive consumption have been investigated. principles for building a corporate view on energy issues, key areas for consideration by large russian companies and the actions taken have been studied. finally, some measures for enhancing corporate energy responsibility among russian businesses have been proposed. references an, j., mikhaylov, a., lopatin, e., moiseev, n., richter, u.h., varyash, i., dooyum, y.d., oganov, a., bertelsen, r.g. (2019a), bioenergy potential of russia: method of evaluating costs. international journal of energy economics and policy, 9(5), 244-251. an, j., mikhaylov, a., moiseev, n. (2019b), oil price predictors: machine learning approach. international journal of energy economics and policy, 9(5), 1-6. bansal, a., illukpitiya, p., singh, s.p., tegegne, f. (2013), economic competitiveness of ethanol production from cellulosic feedstock in tennessee. renewable energy, 59, 53-57. table 2: analysis summary parameter emissions score energy use total, gigajoules total energy use to revenues, gigajoules/usd average 52.24681718 194526196.30 0.02 standard error 4.782097771 69176812.15 0.01 median 56.87523003 50787121.70 0.01 standard deviation 25.30448289 366049282.87 0.04 the sample variance 640.3168544 133992077490893000.00 0.00 excess −0.410922219 13.51 9.24 asymmetry −0.248263741 3.43 2.91 interval 96.43373734 1784340594.41 0.16 minimum 1.533742331 29405.59 0.00 maximum 97.96747967 1784370000.00 0.16 amount 1462.910881 5446733496.36 0.58 quantity 28 28.00 28.00 largest 97.96747967 1784370000.00 0.16 smallest 1.533742331 29405.59 0.00 reliability level (95,0%) 9.812054138 141939094.20 0.01 source: authors calculation tryndina, et al.: trends in corporate energy strategy of russian companies international journal of energy economics and policy | vol 10 • issue 1 • 2020 207 bolt, p.j., cross, s.n. (2010), the contemporary sino-russian strategic partnership: challenges and opportunities for the twenty-first century. asian security, 6(3), 191-213. bove, r., lunghi, p. (2006), electric power generation from landfill gas using traditional and innovative technologies. energy conversion and policy, 47(11-12), 1391-1401. christoffersen, g. (2012), multiple levels of sino-russian energy relations. in: eurasia’s ascent in energy and geopolitics: rivalry or partnership for china, russia and central asia? routledge contemporary asia series. yangon: central statistical organization, routledge. p135-157. denisova, v. (2019), energy efficiency as a way to ecological safety: evidence from russia. international journal of energy economics and policy, 9(5), 32-37. denisova, v., mikhaylov, а., lopatin, e. (2019), blockchain infrastructure and growth of global power consumption. international journal of energy economics and policy, 9(4), 22-29. downs, e.s. (2010), sino-russian energy relations an uncertain courtship. the future of china-russia relations. lexington, ky: university press of kentucky. p146-176. grama, y. (2012), impetuses and problems of sino-russian energy cooperation. asian social science, 8(7), 45-53. guizhou, l., jijun, z., yongqing, s. (2015), the game analysis of oil and gas cooperation between china and russia. international journal of earth sciences and engineering, 8(5), 2301-2310. gulick, j. (2007), russo-chinese energy cooperation: stepping stone from strategic partnership to geo-economic integration? international journal of comparative sociology, 48(2-3), 203-233. henderson, j., mitrova, t. (2016), energy relations between russia and china: playing chess with the dragon. tatiana mitrova: oxford institute for energy studies. hu, z., ge, y. (2014), the geopolitical energy security evaluation method and a china case application based on politics of scale. sustainability (switzerland), 6(9), 5682-5696. meynkhard, a. (2019). energy efficient development model for regions of the russian federation: evidence of crypto mining. international journal of energy economics and policy, 9(4), 16-21. mikhaylov, a. (2018a), pricing in oil market and using probit model for analysis of stock market effects. international journal of energy economics and policy, 2, 69-73. mikhaylov, a. (2018b), volatility spillover effect between stock and exchange rate in oil exporting countries. international journal of energy economics and policy, 8(3), 321-326. mikhaylov, a. (2019). oil and gas budget revenues in russia after crisis in 2015. international journal of energy economics and policy, 9(2), 375-380. mikhaylov, a., sokolinskaya, n., lopatin, e. (2019), asset allocation in equity, fixed-income and cryptocurrency on the base of individual risk sentiment. investment policy and financial innovations, 16(2), 171-181. mikhaylov, а., sokolinskaya, n., nyangarika, а. (2018), optimal carry trade strategy based on currencies of energy and developed economies. journal of reviews on global economics, 7, 582-592. morris, j.w., barlaz, m.a. (2011), a performance-based system for the long-term policy of municipal waste landfills. waste policy, 31(4), 649-662. nyangarika, a., mikhaylov, a., richter, u. (2019b), oil price factors: forecasting on the base of modified auto-regressive integrated moving average model. international journal of energy economics and policy, 1(6), 149-160. nyangarika, а., mikhaylov, а., richter, u. (2019a), influence oil price towards economic indicators in russia. international journal of energy economics and policy, 1(6), 123-130. nyangarika, а., mikhaylov, а., tang, b.j. (2018), correlation of oil prices and gross domestic product in oil producing countries. international journal of energy economics and policy, 8(5), 42-48. røseth, t. (2017), russia’s energy relations with china: passing the strategic threshold? eurasian geography and economics, 58(1), 23-55. . international journal of energy economics and policy | vol 9 • issue 5 • 2019442 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(5), 442-450. financing renewable energy in namibia a fundamental key challenge to the sustainable development goal 7: ensuring access to affordable, reliable, sustainable and modern energy for all kassian t. t. amesho*, emmanuel innocents edoun faculty of management sciences, business school, tshwane university of technology, private bag x680, pretoria 001, south africa. *email: kassian.amesho@gmail.com received: 23 march 2019 accepted: 29 june 2019 doi: https://doi.org/10.32479/ijeep.7704 abstract renewable energy (re) has been a “hot topic” subsequently the increased awareness and understanding of the severe and serious effects of climate change. like many developing countries across the globe and africa in particular, namibia is prone to such climate changes and, thus, should be more familiarized with the impacts of fossil fuel generation on the environment. successful significant financial and technological investments in re in namibia needs a comprehensive understanding of the correlation among diverse categories of investors and their enthusiasm to finance re. contrariwise, using the sustainable development goal 7: ensure access to affordable, reliable, sustainable and modern energy for all, as a measure for a wide-ranging and sustainable growth we recognize the interaction values that comes with re. we studied the asset portfolios of diverse re technologies supported or subsidized by various financial actors in namibia. we also related the performance of public and private types of investments and then discrete further with various financial actors (e.g. public banks, private banks, international climate finance) and the categories of re technologies that are financed in (e.g. different types of energy production from wind, biomass or solar radiation). we then use these preliminary results to draw conclusion and suggestions on how investment impact the directionality of novelty, and the impacts on re policy in namibia. this study establishes that notwithstanding the apparent regulatory and economic challenges, namibia can incorporate and use a blend of (restructured) energy price security structures, cross subsidizations and environmental taxes in-order to encourage initiatives intended at supplementary the country’s progress of re sources and hence ultimately support the un sustainable energy for all initiative. keywords: renewable energy finance, financial actors, climate finance, energy access, renewable energy policy jel classifications: q2, q54 1. introduction the sustainable energy for all initiative is a universal initiative driven by the united nations secretary-general in 2012 with an objective of providing worldwide and all-inclusive access to modern energy services by 2030. in order to attain this specific target, a considerable financial and technological support will be essential at a degree far surpassing historical levels. the subsaharan africa region has an electrification rate of 30.5% and policy transformation concerns to increase electrification have been inadequately executed, thus causing uncertainty with regard to whether the region will be able to attain 100% accessibility to energy for all by the year 2030 (chirambo, 2016). presently, the consumption and the advancement of re has become an essential measure to maintain energy security, intensifying environmental preservation, and confront climate change globally. because of fast social and economic development, this journal is licensed under a creative commons attribution 4.0 international license amesho and edoun: financing renewable energy in namibia a fundamental key challenge to the sustainable development goal 7: ensuring access to affordable, reliable, sustainable and modern energy for all international journal of energy economics and policy | vol 9 • issue 5 • 2019 443 namibia’s energy requirement continues to increase over a specific prolonged period of time. also, energy resources and environmental problems are gradually becoming prominent in namibia’s energy sector. consequently, developing and using re have tremendously become a significant approach for namibia to resolve the progressively serious environmental and energy related issues (rämä et al., 2013). whereas on the other hand, assembling money for financing and innovation in low-carbon energy is another fundamental key challenge to the mitigations of climate change (stern, 2015; grubb, 2014; dangerman and schellnhuber, 2013). however, investments in fossil fuel persist to dwarf investments into re. in 2013 alone, there was less than usd 260 billions invested in re, representing merely 16% of the usd 1.6 trillion of overall investments in energy sector. to this end, financing of fossil fuels in energy sector, where they contend right with electricity from renewable energy (re) sources, increased by 7% from 2013 to 2014 (unep and bnef, 2015). it is also an evident that, fossil fuels still lead energy investments; thus, a key concern in the shift to low-carbon energy supply, specifically on how to achieve satisfactory funding to pilot investments towards re direction (lau et al., 2012 and chirambo, 2016). despite providing affordable modern energy and energy services which are favourably considered as inspiration for economic development, enhancing peoples’ livelihoods, and encouraging sustainable development, it has been noticed that many developing countries are having minimal access to modern energy and energy services. to this effect, an estimated of 1.3 billion people (suberu et al., 2013), which is nearly a fifth of the world’s population, have a shortage and minimum access to electricity at home, with majority of these people living in rural areas of south asia and sub-saharan africa (ssa) (yadoo, and cruickshank, 2012; wicke et al., 2011; glemarec, 2012). energy sector programmes, initiatives, and reforms designed to expand people’s access to affordable modern-day energy and energy services are not a new experience. but nevertheless, the realization of these programmes, initiatives and reforms has not always been promising. significant issues such as inadequate capital investment, policy transformations (ipcc, 2011 and uddin and taplin, 2009), shortage of technological knowledge, limited power generation development and low rates of electrification (uneca, 2007 and suberu et al., 2013; poize and rudinger, 2014) are still a challenge for development in energy sectors. in relation to the present work, there have been several studies attempting to assess and address the challenge of financing re gap in africa to foster universal energy access, yet there has not been any study on financing re in namibia, in order to determine the key challenges to the sustainable development goal 7, which is to ensuring access to affordable, reliable, sustainable and modern energy for all. thus, our research work examines the considerable efforts on financing re in namibia. moreover, we also conduct a comprehensive inquiry of a potential leverage points, accessible instruments and involved actors which demonstrates that there remains an enormous further prospective for re in namibia. we examined the asset portfolios of distinctive re technologies sponsored by diverse financial actors in namibia and then broaden further along with various financial actors (e.g. public banks, private banks, etc.) and the nature of re technologies that are financed. 2. namibia’s re sector: background 2.1. re in namibia namibia has plenty of re resources such as wind, solar, bioenergy and a well-established electricity supply industry. at the present moment, re (besides large hydro), yet, only accounts for small amount of the installed capacity in the country. figure 1 presents a summary of the installed capacity in the country. moreover, electricity imports account for over half of namibia’s energy supply as presented in table 1. the weighted tariffs for these imports depend on the contract terms but tend be equally costly in relation to the cost of the prevailing and new generation opportunities. according to (national integrated resource plan [nirp], 2016), there are new power projects at different phases of development comprising of various re projects. the future procurement of power or electricity from re sources would be facilitated by the most recent development of namibia’s nirp. this will afford an opportunity for this re policy to ensure more direction for the re sector and encourage a supporting and conducive environment to take advantage namibia’s plentiful re resources (rämä et al., 2013). 3. finance and energy innovation 3.1. financial actors and innovation directions in the preceding literatures, joseph schumpeter positioned finance at the heart of his concept of innovation, as availing funds essential for the entrepreneur to transform into action. but nevertheless, he emphasised on single type of funding: banks (mazzucato and semieniuk, 2018), and thus failed to clarify on the issue of whether different characteristics of financial actors may influence what innovation is to be funded, and therefore creating directions. the miller-modigliani hypothesis, which argues that financial sources (equity or debt funding from any actor) is not a major concern to companies and therefore do not impact the definite economy (shimada, 2017) which has further draw consideration away from differentiating among categories of financing of hydro 65% coal 24% fuel oil 9% solar pv 2% renewable electricity in namibia hydro coal fuel oil solar pv figure 1: namibia’s installed capacity as of january 2016 (~500mw) source: (national integrated resource plan, 2016) amesho and edoun: financing renewable energy in namibia a fundamental key challenge to the sustainable development goal 7: ensuring access to affordable, reliable, sustainable and modern energy for all international journal of energy economics and policy | vol 9 • issue 5 • 2019444 innovation. in the succeeding literature, the only kinds of actors characteristically singled out were “government” and “venture capitalists” (mazzucato, and penna, 2016). further latest work has positioned more importance on diverse kinds of financial actors as well as how they might influence the features and qualities of the firms and technologies to be financed. therefore, financial support by the public sector also afar from the research and development phase (mazzucato, and penna, 2016) in sectors like low carbon technology, health and space, has caused the establishment of entire new sectors, regularly over mission-oriented ventures that were enthusiastically agreed upon by those who provide the funding (shimada, 2017 and foray et al., 2012). in several countries, financial support has been availed through innovation companies and/or mechanisms for supporting companies via procurement, similarly as the sbir4 in the usa. in countries like china, japan, brazil, germany, and in the european union (eu), significant financial actors were public banks, offering patient finance for projects that intends to tackle massive challenges such as climate change mitigation and adaptions (griffith-jones and cozzi, 2016; mazzucato and penna, 2016) and encouraging some industries (shimada, 2017; griffithjones and cozzi, 2016) together, through a setup of further public organisations (shimada, 2017). 3.2. financial actors and re direction the available literature on financing re, both modeling and empirical, has previously highlighted to a satisfactory investment in research and development than to downstream financing of distribution of re (mazzucato and penna, 2016). however, a key gap acknowledged in re lately is the shortage of funding of downstream capital-intensive high-risk projects (european commission, 2013), stimulating an increasing literature that reports on actors in the implementation of re technologies. ghosh and nanda (2010) have discussed that the capital needed for asset finance of the capital demanding re power plants is characteristically an order of scale bigger than that which project capitalists have been keen to avail technology progress and too risky for banks (mazzucato and penna, 2016). another component emphasis on the effect of public procedures and standards on exclusive disposition finance. different kinds of strategies are more favorable to finance re innovation than others and might encourage fluctuating amounts of projects capital investments into re businesses (criscuolo and menon, 2015). furthermore, rodríguez et al. (2014) indicated that uninterrupted public ventures are happening aimed at those technologies, where other public procedures had minimal impact on mobilizing private funding (polzin et al., 2015). with reference to directions, the literature on directionality has deliberated on the energy sector but concentrated on the relationship of agency and structure and the effect of power exclusive of segregating finance (criscuolo and menon, 2015 and shimada, 2017). 3.3. financing sustainable re projects financial institutions such as banks are predominantly vigilant about the financing of shared projects in the start-up stage, projects whose governance is a joint and not nationalized (harrison, 2015; ottinger and bowie, 2015; abolhosseini and heshmati, 2014). in the energy sector, from common barriers to the major infiltration of re is the challenge of financing the high initial cost of the equipment (harrison, 2015 and bocken, 2015) even if the lifespan cost of the installation normally is very competitive. hence, new formula for funding these investments are promptly emerging in the re sector (glemarec, 2012). developing literature highlighted new sources to finance sustainable re projects. bocken (2015) examined in what way venture capital can encourage the development of sustainable projects so as to create a progressive environmental and social impacts. another methods of financing have developed, based on the involvement of the greatest number (crowdfunding), but also bringing citizens into the governance of new companies. this new approach means the formation of a range of legal structures allowing the citizens of a territory to regroup themselves and invest on projects that encourage the energy transition (harrison, 2015; yildiz, 2014; tyl and lizarralde, 2017). huhtala (2003) recognized several business models (customer owned, third party and community shares) stressing the significance of the purpose of finance in endorsing cleaner production and sustainability in businesses more broadly. customer-oriented solutions refer to a prototypical where specific households or companies invest in re technology (e.g. solar panel) and own it independently (wainstein and bumpus, 2016). whereas the third-party solutions suggest financing systems by a different party than the one consuming the energy produced, eliminating therefore the high preliminary investment barricade and appealing to new customer sectors such as those with constricted budgets. finally, in the community share model, investors buy shares in joint or local projects. these models are motivating to those without fitting circumstances for the installation (e.g. rental house for solar vp placement) or with less money accessible for investment (harrison, 2015 and bocken, 2015). 4. re consumption in namibia figure 2 shows primary energy consumption of namibia. clearly, economic drivers and increasing mining industry upsurge energy table 1: summary of namibia’s power import sources supplier maximum supply (mw) capacity factor (%) expiry date eskom suplemental 200 20 annual eskom -off-peak bilateral 300 50 march 31, 2017 zesco zambia 50 100 december 31, 2020 zpc zimbabwe 80 50 march 31, 2025 aggrek mozambique 110 n/a december 31, 2015 total 740 source: (nirp, 2016) amesho and edoun: financing renewable energy in namibia a fundamental key challenge to the sustainable development goal 7: ensuring access to affordable, reliable, sustainable and modern energy for all international journal of energy economics and policy | vol 9 • issue 5 • 2019 445 utilisation considerably in namibia. similarly, change from imported electricity to domestic electricity production impacts primary energy utilisation progressively. figure 3 indicates the namibian electricity utilization, allotted into main sectors. it is apparent that results of high scenario are considerably boosted electricity utilisation in excess of folded utilisation estimated by the year 2030. one of the core reasons for this growth is huge mining activity in namibia. similarly, energy utilisation of other industry sectors expands remarkably. costs are higher in kudu situations in 2030, as natural gas-based electricity is distributed to neighboring countries (rämä et al., 2013). figure 4 displays electricity production in namibia divided by production types, comprising of import and export. with kudu scenarios production combination varies significantly from nonkudu scenarios, because in kudu scenarios financing of 800 mw natural gas fired power plant is secured (namibia power corporation [nampower], 2017). thus, it is apparent that in lack of deployment of kudu gas, funding on coal-based energy production mixed with wind power from year 2020 is ideal in consistent with the model. utilization tariffs of natural gas power plant is not at a peak level during years 2020-2025 in low and medium scenarios, since domestic utilisation is at comparatively low-level in comparison to the production volume and cost-effectiveness of natural gas-based electricity which is great sufficient to be exported in bulky volumes (nampower, 2017 and rämä et al., 2013). 5. review of relevant studies different categories of financiers remained more expected than others to offer the capital-intensive, patient finance, high-risk, among others, desirable to attain innovation. so, there is insight figure 2: primary energy consumption in scenarios in years 2008-2030 figure 3: electricity consumption in scenarios in years 2008-2030 divided by sectors amesho and edoun: financing renewable energy in namibia a fundamental key challenge to the sustainable development goal 7: ensuring access to affordable, reliable, sustainable and modern energy for all international journal of energy economics and policy | vol 9 • issue 5 • 2019446 into variances with private and public performers. though the provisions of funding in disposition as to who funds, and what, for re technologies are yet to be well-understood. while there are theoretical opinions concerning why various financial actors might show varying performance, and for why some sectors or technologies could be funded more than others (mazzucato, and penna, 2016), but we know less much about their obligation and in what way this might impact the direction of the development of re. as for technology directions, while there is no advanced model farther the private/public boundary about how financial actors should vary in preferring specific areas (ghosh and nanda, 2010), crowdfunding prototypes, which can be customized to a series of project ranges (shimada, 2017), have benefits afar their apparent competence to tap little contribution amounts from merchandising financiers. 5.1. government involvement? all levels of government are expected to do more in terms of financing or supporting re. at the national level, efforts supported (for instance), by the full credit of the u.s. government must not be disproportionately troublesome. if national obligation were essential to encourage the installations of re, the u.s. government profits from exceedingly low borrowing charges (u.s. department of the treasury, 2016; liberal party of canada, 2015) that would accept re infrastructure to be categorized for government financing would be an economically sensible quest. another exceptional commencing point for any developing country like namibia would be to simply get away with fossil fuel energy subsidies (u.s. department of the treasury, 2014; iea, 2013) and re-allocate this money to re distribution or innovation. further possibilities involve changes to tax regulations (particularly the closing of tax gaps or charging carbon taxes) or financial measures (e.g., rising tax and/or the use of government deficit) harrison (2015) contends that most of the major tax subsidizations for fossil fuels should be revised to incorporate re, with a remarkably attracting preference being financial aid that boost the installation of re in challenging environments. the namibian ministry of mines and energy (mme) is the solitary commissioner of the solar revolving fund (srf). the srf is a credit facility created by mme to encourage demand for the deployment of re technologies specifically for populations living in off-grid zones, plus to urban customers (nampower, 2017 and nirp, 2016). the initiative is exclusively financed and subsidized by government and offers its customers 5-year loans at a 5% fixed lending charges per annum. these loans cater for low to medium income households, the srf has approved and financed 3414 solar system across the country between year 2011 and 2017 (nirp, 2016 and environmental investment fund [eif], 2016). 5.2. namibia re policy namibia is profoundly dependent at present on electricity imports from the southern african power pool, which is gradually under pressure from raising demand in the region. over and above, pursuing greater energy security by increasing power generation from renewables, the namibian government was also concerned with aspect of harnessing low-carbon energy as a means to fulfill its international climate change obligations. although the country has immeasurable re prospective (particularly solar), and developers have been strong to invest in this sector, the nonexistence of a rational policy and strictly articulated commitment, supplemented by the indispensable institutional provisions to encourage re development had hindered the progression of renewables in namibia (ministry of environment and tourism [met], 2015 and nirp, 2016). delivering on the promise of re entails an empowering policy, regulatory, and financial environment (in addition to available technology). to modernize this environment in namibia, a call for harmonizing the country’s interest in pursuing an ambitious goal of preserving stability and integrity of current electricity infrastructure is of paramount. the determination to craft an applicable, tailor-made re policy for namibia also traversed the fine line between catalyzing low-carbon energy growth and considerably re-structuring the country’s overall power sector. this figure 4: electricity production in scenarios in years 2008-2030 divided by production technologies including import amesho and edoun: financing renewable energy in namibia a fundamental key challenge to the sustainable development goal 7: ensuring access to affordable, reliable, sustainable and modern energy for all international journal of energy economics and policy | vol 9 • issue 5 • 2019 447 was much easier to strike this balance, with a strong re policy that locates namibia as a leader in this field, while safeguarding costeffectiveness, local economic development, and energy security are taken into consideration. the policy signifies a momentum for the transformation of namibia’s energy sector is projected to kickoff with rapid development in namibia’s re industry (met, 2015). 6. data and methods the present study was carried out using meta-analysis and content analysis of publicly available information and data, including the national reports, publications, policy documents and industryspecific information, of both namibia and international origin. the data sets were provided by the namibian mme, reports, newspaper articles, industry-specific publications, and company reports, in consistent with the methodology outlined by barnettpage and thomas (2009). this study collected secondary data through comprehensive analysis about various aspects such as national reports on re from the namibian mme, workshops, document analysis/review or desktop study, official statistics, technical reports, scholarly journals, literature review articles, trade journals, reference books, government documents, research institutions, universities, libraries, inter alias, in order to obtain relevant secondary data from the namibian mme which is the main custodian of energy supply in namibia and its affiliated institutions (nirp, 2016). the measuring instrument for this study was determined after a thoroughly literature review of related studies has been carried out. 7. climate finance and re in namibia namibia is making a meaningful progress towards strategizing its national climate change response. it has also been effective in international climate finance developments and acknowledged a number of significant areas on which a complementary attempt could serve to reinforce its capacity on this response, predominantly tackling climate finance promptness requirements for which advocated encouraging activities could be determined (deutsche gesellschaft für internationale zusammenarbeit [giz], 2013). the majority of financial support for climate change in namibia is from international sources and it has been intended for mitigation programs, predominantly in the energy sector. for instance, namibia has acquired financing from the gef for various re and energy efficiency projects (as indicated table 2). majority of international climate finance comes outside of national budget systems, while the national planning commission (npc) is watchfully engaged and committed in consulting financing agreements with benefactors and supervising international funding for government agencies. whereas line ministries can negotiate agreements straight with development partners then ought first to inquire authorization from the npc for all funding allocations and technical cooperation. with regards to loans and budget support, consent of the ministry of finance is also essential, and this financial support is contested via the ministry of finance (met, 2015 and eif, 2016). whereas namibia has received $55.9 million in grants for 25 projects, from the gef (table 2), the most of this financial support has been granted for biodiversity and land degradation focal areas, and only us$8.9 million was granted for seven projects focusing on climate change (table 3). namibia has also accessed a number of small grants totaling to an amount of us$2.9 million and this was executed through civil societies and community-based organisations in the areas of biodiversity, waters, land degradation, international ozone depletion and climate change through the gef’s small grants programme (gef, 2012). these ventures had all acquired cofinance and altogether, namibia had acquired an approximate of us$9.2 million from committed international climate change funds, of which us$7.25 million has been spent. the amount is possibly and substantially higher when bilateral initiatives are to be considered (world bank, 2018; van rooij et al., 2013; eif, 2016; met, 2015). different bilateral development agencies have been administering capitalisation for climate-related undertakings in namibia, comprising of finland, germany, denmark, sweden, and the european commission, mostly for energy sector intercessions (giz, 2013; climate funds update, 2012; gef, 2012). the majority, if not all, of climate funding acquired in namibia is mainly in the form of grants. namibia has shown a robust unwillingness to borrow from the multilateral development banks or the international monetary fund because of the worrying conditionalities accompanying to such credits and the fact that the country is capable to access commercial finance at lowcost tariffs. it was eminent that concessional loans might be boosted to namibia’s advantage if premeditated purposefully. specifically, lends could become essential for great climate resilient infrastructure developments or in the energy sector to reduce carbon alternatives. whereas the eus to namibia, has a collaboration framework lapsing in 2020, and the eu has already dedicated €68 million ($84 million) to inspire several ventures and programmes in the country (heinrich boll stiftung, 2015). this action render support to the namibian government’s determinations to minimize the susceptibility of the rural population to unfavorable ramification of climate change by developing, examining and propagating solutions and practices, applying cutting-edge technologies for climate change variations and mitigation in rural areas. 7.1. innovative re projects financing in local currency to finance re projects in namibia, the climate fund investment vehicle worked well with rmb namibia, a subsidiary to the table 2: total gef‑financing in namibia (in us$) project type no. of projects total gef financing total co-financing national projects 25 58,881,900 303,726,790 regional and global projects 20 139,910,412 323,885,407 gef small grants programme 19 2,973,475 3,788,996 amesho and edoun: financing renewable energy in namibia a fundamental key challenge to the sustainable development goal 7: ensuring access to affordable, reliable, sustainable and modern energy for all international journal of energy economics and policy | vol 9 • issue 5 • 2019448 investment bank, the first national bank of namibia limited. the agreement structure that they put in place permitted the projects to be subsidized in local currency. the financing solution is tremendously complicated and the structure gave a greenlight to implement effective long-term nonrecourse projects financing in a booming solar sector. the project is 30% owned by previously disadvantaged namibians and will benefit development of the local community by creating job opportunities and encouraging the transfer of knowledge (heinrich boll stiftung, 2015 and met, 2015). eif financial support is mainly aimed at ngos and small and medium size enterprises (smes), although it can also support proposals or initiatives by local governments. while it is not prohibited from “adding value” to government enterprises through non-government partners, the eif’s mandate prevents it from providing financial support to initiatives from national government. to date, the eif has only appropriating funding in the form of grants. the eif has lately begun its fiduciary standards and operational manual and made application to the namibia financial institutions supervisory authority for authorization to lend soft loans. the eif has also equally launched a green soft loans funding strategy, in collaborations with the newly founded sme bank of namibia which will function as a financial intermediate (eif, 2016). the mechanism will grant small concessional loans to households of up to n$100,000 (us$10,000) for climate and environmental interrelated undertakings (household solar lighting, water efficiency equipment, solar water geysers, solar water pumps for farmers, etc.). this facility is value at n$ 5 million (us$0.5 million) and will be recapitalised with an additional n$ 8 million (us$0.8 million). the eif can also administer larger concessional loans straight to households and smes for comparable kinds of financing, by a maximum amount to each project of n$5 million (us$0.5 million). in 2013, eif has devoted n$ 30 million (us$3 million) in such facility. 8. discussion and concluding remarks there is a significant relationship between financial development and economic growth found in the available well-documented body of literature. a viable economic progression depends on the development of re sectors (uneca, 2007). this study examines whether financial market development encourages the distribution of re in namibia. explicitly, we maintained that countries with a balanced financial markets experience advancement in the re sector due to comfortable access to external financial supporting sources. using a unique cross-sector data on re in namibia from the mme, this study gives a cross-country proof of financial market development’s impact on re distribution in namibia. our pragmatic results demonstrate that re sectors that greatly depend on external financial support and grow enigmatically quicker in a country with advanced financial markets. in this case, solar pv is a leading example. as the sector that is mostly depend on external financing, it shows an excellent distribution level in more advanced financial markets. our findings reveal that advancement in financial sectors are a noteworthy determinant factor of re disposition in namibia. this has a fundamental implication to the policy makers, who should strategize on institutional mechanisms with easy access to financial supporting sources for firms in the re sectors in namibia. furthermore, our findings substantiate the views in the literature, which established that financial development has the potential, and it can lead to co2 emissions reduction by resolving the significant role that financial sectors play in implementing re. this study has presented a summation of the existing landscape of financing re and climate financing enthusiasm in namibia and identified a number of promptness requests and particular undertakings that might be reinforced by promptness financial backings. equally, it should be notable that this signifies an early effort to establish key gaps and needs that the government of namibia will be required to foster on deliberation and resolve how to prioritise with the identified needs. 9.acknowledgements this research study was made possible by the namibian mme who provides valuable data on re in namibia, and the authors have tremendously expressed their indebted gratitude in this regard. table 3: multilateral climate finance for namibia (in us$) projects funder year approved amount approved amount disbursed enabling activities for the preparation of initial communication related to unfccc gef 2001 0.13 0.13 climate change enabling activity (additional financing for capacity building in priority areas) gef 2003 0.1 0.1 adapting to climate change through the improvement of traditional crops and livestock farming gef 2012 0.96 0.96 barrier removal to namibian renewable energy programme (namrep), phase i gef 2012 2.6 2.6 barrier removal to namibian renewable energy programme (namrep), phase ii gef 2011 2.6 2.6 concentrating solar power technology transfer for electricity generation in namibia (nam csp tt) gef 2011 1.72 0 developing a national energy action plan germany’s ici 2010 0.233 0 namibia energy efficiency programme (neep) in buildings gef 2010 0.86 0.86 total 9.203 7.25 source: climate funds update: http://www.climatefundsupdate.org/data and gef: http://www.thegef.org/gef/gef_projects_funding. this table does not capture contributions outside of dedicated climate funds and initiatives. all gef projects were implemented through undp amesho and edoun: financing renewable energy in namibia a fundamental key challenge to the sustainable development goal 7: ensuring access to affordable, reliable, sustainable and modern energy for all international journal of energy economics and policy | vol 9 • issue 5 • 2019 449 references abolhosseini, s., heshmati, a. (2014), the main support mechanisms to finance renewable energy development. renewable and sustainable energy reviews, 40, 876-885. barnett-page, e., thomas, j. (2009), methods for the synthesis of qualitative research: a critical review. ncrm working paper. ncrm. bocken, n.m.p. (2015), sustainable venture capital-catalyst for sustainable start-up success? journal of cleaner production, 108, 647-658. chirambo, d. (2016), addressing the renewable energy financing gap in africa to promote universal energy access: integrated renewable energy financing in malawi. renewable and sustainable energy reviews, 68, 793-803. climate funds update. (2012), available from: http://www. climatefundsupdate.org/data. [last accessed on 2018 jun 05]. criscuolo, c., menon, c. (2015), environmental policies and risk finance in the green sector: cross-country evidence. energy policy, 83, 38-56. dangerman, a.t.c.j., schellnhuber, h.j. (2013), energy systems transformation. proceedings of the national academy of sciences, 110(7), 549-558. deutsche gesellschaft für internationale zusammenarbeit (giz). (2013), understanding climate finance. readiness needs in namibia german federal ministry for economic cooperation and development (bmz). eif. (2016), environmental investment fund of namibia. eif. available from: http://www.eifnamibia.com. [last accessed on 2018 apr 22]. european commission. (2013), technology assessment. in: commission staff working document no. swd (2013) 158 final. foray, d., mowery, d.c., nelson, r.r. (2012), public r and d and social challenges: what lessons from mission r and d programs? resources policy, 41(10), 1697-1702. glemarec, y. (2012), financing off-grid sustainable energy access for the poor. energy policy, 47, 87-93. global environment facility (gef). (2012), available from: http://www. thegef.org/gef/gef_projects_funding. [last accessed on 2018 jun 07]. ghosh, s., nanda, r. (2010), venture capital investment in the clean energy sector. harvard business school working paper. p11-20. griffith-jones, s., cozzi, g. (2016), investment-led growth: a solution to the european crisis. in: jacobs, m., mazzucato, m., editors. rethinking capitalism. london: wiley blackwell. grubb, m. (2014), planetary economics. oxford and new york: routledge. harrison, b. (2015), expanding the renewable energy industry through tax subsidies using the structure and rationale of traditional energy tax subsidies. university of michigan journal of law reform, 48, 845. heinrich boll stiftung. (2015), climate finance regional workshop, windhoek. available from: https://www.za.boell.org/2015/07/24/ report-climate-finance-regional-workshop. [last accessed on 2018 may 18]. huhtala, a. (2003), special issue on cleaner production financing. journal of cleaner production, 11(6), 611-613. international energy agency (iea). (2013), 2009 energy balance for namibia. paris: iea. available from: http://www.iea.org/statistics/ statisticssearch/report/?country=namibia&product=balances. [last accessed on 2018 may 08]. ipcc. (2011), in: edenhofer, o., pichs-madruga, r., sokona, y., seyboth, k., matschoss, p., kadner, s., zwickel, t., eickemeier, p., hansen, g., schlömer, s., stechow, c.v., editors. special report on renewable energy sources and climate change mitigation. united kingdom and new york, cambridge: cambridge university press. lau, l.c., lee, k.t., mohamed, a.r. (2012), global warming mitigation and renewable energy policy development from the kyoto protocol to the copenhagen. accord-a comment. renewable and sustainable energy reviews, 16, 5280-5284. liberal party of canada. (2015), an historic investment plan to strengthen the middle class, create jobs, and grow our economy; 2015. available from: https://www.liberal.ca/files/2015/08/anhistoric-investment-plan.pdf. [last accessed on 2018 may 29]. mazzucato, m., penna, c.c.r. (2016), beyond market failures: the market creating and shaping roles of state investment banks. journal economics and policy reform, 19(4), 305-326. mazzucato, m., semieniuk, g. (2018), financing renewable energy: who is financing what and why it matters. technological forecasting and social change, 127, 8-22. ministry of environment and tourism namibia (met). (2015), nationally appropriate mitigation action: rural development in namibia through electrification with renewable energies. available from: http://www.undp.org/content/undp/en/home/ librarypage/environment-energy/mdgcarbon/namas/nama-onrural-development-in-namibia-through-electrification-wit.html. [last accessed on 2018 jun 17]. nampower. (2017), annual report 2017. windhoek, namibia. national integrated resource plan (nirp). (2016), electricity supply industry in namibia 2016. government of the republic of namibia, ministry of mines and energy, windhoek, namibia. ottinger, r.l., bowie, j. (2015), innovative financing for renewable energy. pace environmental law review, 32, 701. poize, n., rudinger, a. (2014), home installations for producing renewable energy: a comparison between france and germany. revue de l’energy, 45(38), 89-100. polzin, f., migendt, m., täube, f.a., von flotow, p. (2015), public policy influence on renewable energy investments-a panel data study across oecd countries. energy policy, 80(c), 98-111. rodríguez, m.c., haščič, i., johnstone, n., silva, j., ferey, a. (2014), inducing private finance for renewable energy projects: evidence from micro-data. in: oecd environment working paper no. 67. rämä, m., pursiheimo, e., lindroos, t., kati, k. (2013), development of namibian energy sector. research report: vtt-r-07599-13 2013. vtt, espoo. p68. available from: http://www.vtt.fi/inf/ julkaisut/muut/2013/vtt-r-07599-13.pdf. [last accessed on 2018 nov 17]. shimada, g. (2017), inside the black box of japan’s institution for industrial policy: an institutional analysis of the development bank, private sector, and labor. in: noman, a., stiglitz, j.e., editors. efficiency, finance and varieties of industrial policy. new york: columbia university press. stern, n. (2015), why are we waiting? the logic, urgency, and promise of tackling climate change. cambridge, ma: mit press. suberu, m., mustafa, m., bashir, n. (2013), status of renewable energy consumption and developmental challenges in sub-sahara africa. renewable and sustainable energy reviews, 27, 453-463. suberu, m., mustafa, m., bashir, n., muhamad, n., mokhtar, a. (2013), power sector renewable energy integration for expanding access to electricity in sub-saharan africa. renewable and sustainable energy reviews, 25, 630-642. tyl, b., lizarralde, i. (2017), the citizen funding: an alternative to finance renewable energy projects. procedia cirp, 64(9), 199-204. u.s. department of the treasury. (2014), progress report on fossil fuel subsidies. u.s. department of the treasury. (2016), daily treasury yield curve rates. available from: https://www.treasury.gov/resource-center/datachartcenter/interestrates/pages/textview.aspx?data%c2%bcyield. [last accessed on 2018 may 15]. uddin, s., taplin, r. (2009), trends in renewable energy strategy development and the role of cdm in bangladesh. energy policy, amesho and edoun: financing renewable energy in namibia a fundamental key challenge to the sustainable development goal 7: ensuring access to affordable, reliable, sustainable and modern energy for all international journal of energy economics and policy | vol 9 • issue 5 • 2019450 37, 281-289. unep and bnef. (2015), global trends in renewable energy investment frankfurt school of finance and management. united nations environment programme. united nations economic commission for africa (uneca). (2007), making africa’s power sector sustainable: an analysis of power sector reforms in africa united; 2007. available from: http://www. uneca.org/eca_programmes/nrid/pubs/powersectorreport.pdf. [last accessed on 2018 may 28]. van rooij, j., brown, l., nakhooda, s., watson, c. (2013), understanding climate finance readiness needs in namibia. available from: https://www.odi.org/projects/2735-climate-finance-readiness. [last accessed on 2018 may 15]. wainstein, m.f., bumpus, a.g. (2016), business models as drivers of the low carbon power system transition: a multi-level perspective. journal of cleaner production, 126, 572-585. wicke, b., smeets, e., watson, h., faaij, a. (2011), the current bioenergy production potential of semi-arid and arid regions in sub-saharan africa. biomass bioenergy, 35, 277-786. world bank. (2018), the world bank in namibia. the world bank’s priorities in namibia include a comprehensive study of unemployment, poverty assessment, and assistance with macromodeling and climate change. available from: http://www. worldbank.org/en/country/namibia/overview. [last accessed on 2018 jun 21]. yadoo, a., cruickshank, h. (2012), the role for low carbon electrification technologies in poverty reduction and climate change strategies: a focus on renewable energy mini-grids with case studies in nepal, peru and kenya. energy policy, 42, 591-602. yildiz, ö. (2014), financing renewable energy infrastructures via financial citizen participation-the case of germany. renewable energy, 68, 677-685. 508 resource limit is reached resource limit is reached the website is temporarily unable to service your request as it exceeded resource limit. please try again later. international journal of energy economics and policy vol. 4, no. 4, 2014, pp.679-692 issn: 2146-4553 www.econjournals.com 679 impacts of oil foreign direct investment on environment and poverty level in niger delta oil producing region: a structural equation modeling approach salami dada kareem department of economics, faculty of social sciences, lagos state university, nigeria. email: daskareem@gmail.com david mautin oke department of economics, faculty of social sciences, lagos state university, nigeria. email: okdam76@yahoo.com; david.oke@lasu.edu.ng daskareem vera enoho department of economics, faculty of social sciences, lagos state university, nigeria. email: daskareem@gmail.com oladipo kolapo sakiru department of human resource development, unversiti putra, malaysia. email: honkolapo@gmail.com babajide david adesina department of banking and finance, yaba college technology, nigeria email: darebabajide@gmail.com abstract: this study examines impacts of oil foreign direct investment on the environment and welfare of people of niger delta oil producing communities, using structural equation models. overall, it was found that oil foreign direct investment has consistent impact on the environment than the wellbeing of the community, which results in high levels of poverty. the implication is that there is environmental diseconomies and widespread of poverty in the area. thus, there is need for fostering sustainable partnership between the oil foreign direct investors and the host communities by suitable consideration of the issues of mitigation of environmental problems that will reduce the poverty level of the people. the environmental and socioeconomic system should be developed to maintain an intensity of biodiversity that will give assurance to the buoyancy of the ecosystems on which human consumption and production depend. keywords: foreign direct investment; environmental degradation; poverty; structural equation modeling jel classifications: c39; f21; f64; i31 1. introduction the economic performance of any country is a result of the relationship between the advancement of economic, institutional and technological forces that align with economic development (naubahar, 2006).terrence and kevin (2005) argue that the dealings and the formation of innovative establishments are potential within an evolutionary structural perspective of economic growth. the developing countries and transition economies have directed more effort towards quality foreign direct investment (fdi) from the developed nations, predominantly what they consider as prioritythe fdi that brings tangible benefits, especially contributing new technologies and organizational practices. many developing countries and transition economies are in the same situation international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.679-692 680 with the regards to fdi and transnational corporate operations in an effort to incorporate them into their development strategies (unctad, 2005). the oil sector affects the nigerian culture and structure and it is the basis of the economy. the production capacity in the sector is based on the joint venture. shell company is the leading producer in the joint venture arrangement which produces about 50%. there is often fluctuation in nigeria’s gdp when there is a sudden increase of oil production. this has led to increase in oil output and resulted to severe damage on the environment. there is also often disparaging environmental transformation emanating from oil business and industrialization; oil spill and gas flares have destroyed the natural resource base, which portend threat to sustaining independent indigenous livelihood. in most parts of delta region states for instance, the hitherto very fertile lands are no longer productive. the peasants have lost the fertility of their lands to oil exploration (victor, 2010). in addendum, the people of the area remains infuriated by massive oil based environmental degradation. it is a regime of massive oil spillage occurrences and gas flares which have devastated the land and water that have led to soil fertility loss, farming decline, forest loss, fisheries and bio-diversity depletion. oil dependence has an ambiguous relationship with poverty alleviation, and this is related to the boom-bust cycles accompanying dependence on the resource. countries dependent on agricultural commodities tend to experience low poverty level, minerals in general are linked to high levels of poverty, and oil dependence in particular is correlated with low life expectancy and high malnutrition rates. it is true that most forms of primary commodity dependence are associated with poverty, not all commodities are equally culpable (fafchamps and quisumbing, 2002). one of the most important social consequences of the resource curse is that oil-exporting countries have unusually high poverty rates, poor health care, high rates of child mortality, and poor educational performance given their revenues – outcomes that contradict the beliefs about what should happen within oil-exporting countries (bassam, 2008). the question that comes to the mind of many is how can the oil companies making billions of dollars yearly from the exploitation activities do without taking care of the host communities and the environment. in addition, how can natural resources being used up in a manner that appears wasteful and thereby foreclose options for development in the future and increase the poverty level in the society. interestingly, however awareness level of environmental problem has grown tremendously in the mind of people in recent years. one question that must be asked in this regard is what is the relationship between an increase in the exploitation activities of the oil companies and its impact on the environment and poverty level of the people in the niger delta region? therefore, the main objective of this study is to examine the impacts of oil foreign direct investment on environment and poverty level in the niger delta oil producing region. the structural equation modeling (sem) approach is being used because of the multi-dimension of the impact of fdi on the environment and the level of poverty of the people in the niger delta. to uphold the environment and improve the poverty level, the stock of renewable resources should be maintained and the economy should save over and above the depreciation rate of both man-made and natural resource capital (catarina et al., 2010). the paper is organized as follows. section two reviews the existing literature on the value of the environment and externalities theories. the third section presents the sample research design and model specification. the fourth section presents estimation and results and the final section provides the conclusion. 2. literature review the valuation of the environment suggests that welfare of the future generation should not be less than the welfare of the current generation. furthermore, the stock of renewable resource should be maintained and the economy should save over and above the depreciation rate of both man –made and natural capital resources (weitzman and lofgren 1997; elif –akbostanci and ipek, 2009; catarina et al., 2010). the serious degradation and pollution of the ecosystem suggest the need for valuing the environment and pursuance of policies that would help to ameliorate the current adverse environmental condition. furthermore, goods and services exchanged are measured in terms of their market price and value assessment. most of the goods and services like clean air and water resources are not generally impacts of oil foreign direct investment on environment and poverty level in niger delta oil producing region: a structural equation modeling approach 681 valued. the deficiency in markets for environmental services are the most important instances of the market failure. the degradation and over exploitation are always caused by lack of economic valuation of environmental goods (kalpana et al., 2007; john, 2008). however, environmental economic valuation and its services are the main central basis of environmental economics. rudolf (2002) emphasizes that allocation of limited resources in the face of unlimited wants, that is, the scarcity of resources is relevant to the environment’s valuation. the fundamental approach of valuation of the environment is the adaptation of the goods and services the natural environment makes available. the valuation of the environment is the practice of committing monetary values on environmental goods and service, many of which have no easy practical market prices (salamiet al., 2012). environmental goods and services comprise scenic views, biodiversity, coral reefs, and mountain landscapes. it also comprises indirect processes, such as water supply and watersheds, erosion control and forest ecosystem conservation, and sustenance of genetic material. in order to value these goods and services, valuation techniques have been developed (clive and arild, 2006). however, in a situation of private ownership, natural or environmental resources could be acquired and protections against trespass can be in the context of a regime of liability rules which can certainly resolve conflicts over resource use. this really is not coase’s thesis in “social cost.” his exposition in the hypothetical world without transaction costs was developed to especially illustrate the paradox intrinsic in the theory of perfect competition. perfect competition requires perfect information. perfect information removes transaction costs and the absence of this information gives rise to transaction costs. coase transaction costs arise only in market exchange and represent the value of the resources which are consumed while undertaking a market exchange. it is exchanged for economists consider advantage in the transaction costs to determine the value of the resources consumed while institutional change, including adjustments to government policy along with the cost of making and safeguarding ownership claims (glenn, 2007). judith-dean et al. (2009) emphasized the approach within the framework of dealing with environmental parameters such as resource abundance along with the market failure. the best valuation within the common-property resource stock is dependent upon the particular property-right structure governing its use (eric-neumayer, 2001; akkemik and goksal, 2012). the transaction cost is incurred in each and every point in which the goods in the process pass through one owner to a new utilizing free market exchange. firms can avoid these transaction costs by creating an enduring relationship between the owners of the factors of production engaged in successive stages of the production process (glenn, 2007). the resource externalities associated with a firm’s social cost have private costs along with extraction costs, and factor into the firm's optimization problem. market prices which include the marginal user cost of the resource are one element of the full extraction cost. similarly, the cost of a user is explicitly considered as a cost when property rights are not assigned but the emphasis is given to social evaluation of productivity growth (acemoglu, 2003). the externalities of environmental destruction and degradation provide further facts to those who doubt the relevance of conventional economics for long-term policies of sustainable growth and expansion. environmental economist therefore seeks to incorporate into their value system the scarce environmental goods and services. this is with the intention of the environment to be perceived and can be treated as an economic commodity (jacobs, 1994). the modern extractive industry and its environmental effects had conventional attention of several researchers in the past. some of the issues include the implications of keeping up development in an economy, the main sources of environmental diseconomies arising from oil industry activities and their environmental impacts. the main oil companies operating in the niger delta have expressed a commitment to sound environmental practice in the area in which they work. on the contrary their practices are known to be the worst anywhere in the world, hurting the environment and livelihoods of the niger delta on a monumental scale (onosode, 2003; orubu, 2002).this explained the designation of poverty and associated theories that are deeply rooted in strongly held political values, elevated by encompassing social, political and economic institutions which have a stake in the matter. the world bank (2000) defines poverty as ‘‘the economic condition in which people lack sufficient income to obtain certain minimal levels of health services, food, housing, clothing and education generally recognized as necessary to ensure an adequate standard of living ’’the abilities of the people of niger delta to acquire assets (including both material and social assets) and the activities needed for just international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.679-692 682 means of living are not achievable. liu (2013) argues that the livelihood is sustainable when it can cope with and can recover from stresses and shocks, as well as maintain or enhance its abilities and resources .while noting the undermining of the natural resource base, the orthodox view in much discussion of the sustainability argues that poverty and environmental degradation are linked within the downward and mutually enforcing cycle. the world commission on environment and development noted that poverty is the most important foundation of global environmental problems (brundtland commission, 1987). therefore, it is ineffectual to deal with environmental problems without bigger perspective of the standards underlying world poverty and worldwide inequality. the links between poverty and environment were also seen as being self-enforcing. the commission also noted that many parts of the world are caught within the vicious unpredictable manner, poor people are forced to overuse environmental resources to survive from day to day, and their impoverishment of their environment further impoverishes them, making their survival ever more difficult and uncertain (stonich, 1992). the study puts forward and illustrates an alternative, environmentally entitlements approach to understanding povertyenvironment linkages. adapted from kapp (1950) work, it predicts the accomplishment of undesirable cost of growth of the economy on the environment. the approach shifts the emphasis from questions of resource available to those of access, control and management. the social cost which is defined as all direct and indirect burdens impose on the third parties or the general public by the participant in economic activities is the central point in kapp’s analysis. he explicitly mentions all costs emanating from productive processes that are passed on to the outsiders through water and air, land degradation which harm health, reduces agricultural yield, accelerates corrosion of materials, endangers aquatic life forms, flora and fauna, and creates problems in the preparation of drinking water. it is instructive to argue that environmental costs are frequently externalized for lack of clearly defined property rights. this is because most environmental resources share the traits of public goods and some suffer uncontrolled and excessive exploitation for coming under common property right. insecure land tenure is bound to discourage long term investments, therefore is biased in technology choice in favour of short-run output maximization over sustainable economic system. therefore, welldefined property right is a dimension towards enforcing appropriate environmental behaviour. these problems arise essentially because of scarcity of all resources in the economic system (richard and krugman, 2004). externalities occur when economic unit’s activities, such as those of firms or consumers, impinge on the consumption or production of another component and where the benefits of costs that builds up to components do not usually go into the gain or loss estimation. in other words, these effects are noticed, they are left un-priced; hence the bearers are normally uncompensated in the private market environment. if externalities are priced and bearers are compensated, then they are said to be internalized (collin, 2007). baumol and oates (1988) point out that market failure is a very broad issue that occurs in many areas of economics. they favour the approach taken by costanza et al. (1997) that defined externalities as not in terms of what they are but what they do, thus they contravene the optimum allocation of resources conditions in the economy. the key characteristic of a private externality is that the agents involved should be required to be fully appropriated by the external effect. thomas et al. (2006) note that, public externality arises when a natural resource is used without payment and its use by one agent does not reduce the quantity obtainable to others. the quality of the natural resource may be affected, however, owing to the useas-you-please principle. air and water pollution are examples of this kind of externality. there is need to plug back some of the benefits accruing to these firms and companies to the community who are impoverished, as a result of their operational defects. the absence of this kind of incentive would lead to the confrontation between nigeria government, oil companies and host communities. the role of oil companies may be extensive in less developed countries (ldcs) and transitional economies where free market regulating mechanisms are not yet fully formed or effectively practiced. oil companies have a unique opportunity in attending to social responsibility issues, as in the niger delta, especially where potential host countries lack the legal framework, societal infrastructure and experience of a market economy. impacts of oil foreign direct investment on environment and poverty level in niger delta oil producing region: a structural equation modeling approach 683 3. the study location the niger delta region which occupies an area of 75,000 sq. km is located in the southern part of nigeria. it stretches to nigeria-boundary in the east of cameroon; bounded by ogun and ondo; west is by kogi, enugu, ebonyi, anambra, and in the north bounded by ekiti state and in the south generally bounded by the atlantic ocean. it is the world’s largest third mangrove forest in africa and most expansive unsullied water swamps in western and central africa and is nigeria’s major concentration of high biodiversity. the population of the niger delta is over 30 million people, who live in about 13,400 long settled aboriginal communities made up of ijaw, isoko, itsekiri, ishan, ilaje, ibibio, anang, efik, ekpeye, ikwerre, edo, ogoni, ogba engine and ukwani nationalities. over 75% of these settlements lie along the coastal region of nigeria (okaba, 2005). figure 1 shows the niger delta map by local government. figure 1. niger delta map the nigeria’s total land mass formed the delta sediment deposition, on the floor plain make up 7.5%. it has the largest drainage basin, also the largest wetland basin in africa. also, the niger delta environment has island forests, freshwater swamps and lowland rainforests. island mangrove and freshwater swamp, they are the ecological zone. it has an uppermost concentration of the biodiversity and well endowed ecosystem and there is plentiful vegetation, cultivatable topography that can uphold a wide assorted crops and agriculture tree, also more water inhabitant species than any ecosystem in africa (wackernagel et al., 2004) its difficult terrain and abnormal weather conditions are positively counterbalance by her rich natural resources and their associated domestic and industrial potentials for sustainable development. the niger delta is not only strategic because it is the epicenter of the west african economic resource base but also because it is lavishly endowed with enormous water resources. approximately, 21 major rivers connect the region to the luminous atlantic oceans which is an aquatic highway that opens coastal nigeria to all the continents of the world. there are clear indications that huge underground lakes of fresh water bound in this area, suggesting that a prosperous water-based export economy can be sustained (okaba, 2005). the niger delta is a unique constellation of ecological area including sandy coastal ridge barriers, brackish saline mangrove, freshwater, permanent and seasonal swamp and low lands. it is traversed by a large number of rivers, streams, rivulets and canals, as over 60% of the region is crisis crossed with creeks and dotted islands while the remainder is a lowland rainforest. the niger delta is well endowed with abundance of mineral resources especially crude oil and natural gas. in oil export, nigeria’s domestic revenue average of 69% in 2008 and real gdp growth had a large positive link with oil export revenues, implying that oil export revenue volatility was immediately reflected in the economic growth in nigeria, just as in other african countries that international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.679-692 684 depend largely on single commodities for foreign exchange earnings. the foreign direct investments into oil exploitation include activities like exploration, production refining, transportation and marketing of crude-oil products which have been prosperous over the years. most of the industries are based principally in the niger delta region, which have caused the major colossus of environmental degradation in the region. 3.1 sampling and data collection data used in this study was collected from households in two communities of the delta region, nigeria, over the period of september 2010 to february 2011. the two communities are burutu and ogulagha, where oil companies’ activities are prominent. the total population of the household in the two communities is four thousand, five hundred (4500). the target respondents were the heads of the households. where possible, information about the household’s income and asset holdings was obtained directly from the household’s head, defined as the member in charge of the household’s economic and financial dealings. in determining the sample size needed to be a representative of the population, this study adopted the formula given by krejcie and morgan (1970) as: )1()1( )1( 22 2 ppxnd pnpxs   s = required sample size. x2 = the table value of chi-square for 1 degree of freedom at the desired confidence level (3.841). n = the population size. p = the population proportion (assumed to be .50 since this would provide the maximum sample size). d = the degree of accuracy expressed as a proportion (.05). additionally, setting an appropriate confidence level can be used to determine any sample sizes. the most often used level of confidence is 95% considering the danger of type i error when making a critical decision. thus, a significant level of .05 levels or 95% confidence level is used in this study (see krejcie, and morgan, 1970). in all, 354 samples of households were determined through the sample size formula of krejcie and morgan (1970). the questionnaire targeted the households’ head. there was a complete response which could be attributed to the direct involvement of the researchers in the administration of the questionnaires. the structural equation modeling was used to investigate and predict the causal attribution that explains the relationships under investigation. in the sampling procedure the study adopted the social cognitive theory and effects related theory in foreign direct investment and environmental economics in explaining the factors contributing to the welfare of the people and their environment. the main objective of this study is to examine the impact of oil foreign direct investment on environmental degradation and poverty level in the niger delta oil producing region. tabachinick and fidell (2007) argue that, survey research is suitable in the investigative assessment of psychological constructs where data can be used to review and explain the population understudy of an issue. therefore, a sample of respondents from the population was selected and a standardized questionnaire was administered. also, selection of communities for the research was based on where there are high levels of oil production activities of the oil companies. these were purposively selected communities and the survey applied a semi-structured questionnaires guide to give a high-quality measurement of the differences between various oil exploration impacts on the environment, environmental stress, wellbeing of households and communities as whole. the questionnaire was therefore designed to generate data about the level of awareness of the people as regards air pollution, oil spillages and land degradation as environmental problems. the extent of stress from environmental factors in the communities, environmental impact on the people and communities, general awareness of environmental consequences and the perception of the people on operation of oil companies in the communities are also addressed. the questionnaire consists of structured and semi-structured statements. some of the questions are continuous in nature, while others are in scaled form and on five and ten likert scale. the questionnaire was divided into six sections: i) the demography of the respondent, ii) the environmental impacts of the oil companies on the community; iii) the general awareness of environmental consequences, iv) the impact of crude oil exploitation on the people and community impacts of oil foreign direct investment on environment and poverty level in niger delta oil producing region: a structural equation modeling approach 685 well-being, v) the extent of stress from environmental factors in the communities, and finally the perception of the people on operation of oil companies in the communities 3.2. structural analysis structural equation modeling (sem) offers the analytical power suitable for integrated model in research since it can simultaneously examine the influence of several variables on other variables in the entire scheme of the model. also, implicit presumptionsof unidirectional constructs are made explicit, with the result that theoretical meaningful models can be derived and compared with the existing models (kline, etal. 2001). hence, the role of variables in predicting behavioral intentions was deduced from sem analyses through the calculation of the confirmatory nod. the responses from the questionnaires were coded and analysed using spss 19 and further analysis of sem was performed using analysis of moment structure v16 (amos software). kline (1998) suggests that a sample size that exceeds 200 cases can be considered adequate of estimation in sem. nevertheless, this study embraces several predictors. the variables used are: perception of the people on operation of oil companies in the communities (oil_fdi), impact on environment (envr_imp), impact of crude oil exploitation on peoples' well-being (wlb_imp), extent of stress from environmental problem in the communities (stress) and general awareness of environmental consequences (gac). figure 2. path diagram of hypothetical 1model note: env_ stress, represents extent of stress from environmental problem in the communities oil_fdi, represents perception of the people on operation of oil companies in the communities envr_imp, represents impact on environment gac, represents general awareness of environmental consequences wlb_imp, represents impact of crude oil exploitation on peoples' well-being 3.3 descriptive statistics and reliability test. the sample of 354 heads of households from burutu and ogulagha of niger delta region participated in the study. table 1 shows the basic demography and socio-economic status of the respondents. gac envr_imp parceled impact 1 parceled impact 2 parceled impact 3 parceled impact 4 parceled impact 5 env stress oil_fdi perception 5 perception 4 perception 3 perception 2 perception 1 wlb_imp education health infrastructure employment gac 10 gac 9 gac 8 gac 7 gac 6 gac 5 gac 4 gac 3 gac 2 gac 1 gas flare pollution extinction degradation international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.679-692 686 table 1. basic demography and socio-economic status of the respondents titles frequencies percentages sex male 219 61.9 female 118 33.3 the respondent’s age group middle age 67 18.9 old age 210 59.3 elderly 77 21,8 residential status of the respondent indigene 298 84.2 settler 56 15.8 marital status married 285 80.5 widow/widower 53 15.0 separated 6 1.7 the educational qualification obtained primary leaving certificate 272 76.8 secondary / diploma 46 13.0 degree / higher diploma 36 10.2 employment in the oil companies employee 48 13.6 non-employee 306 86.4 occupation of household head farmer 221 62.4 trader 97 27.4 civil servant 20 5.6 others 16 4.6 for the reliability test: the average summated mean scores and all the constructs under study representing standard deviations are presented in table 2 table 2. the reliability alpha value and descriptive statistics of the constructs under study (n=354) means standard deviation alpha value oil_fdi 3.67 0.58 0.72 env_ stress 2.18 0.27 0.67 envr_imp 3.24 0.65 0.74 gac 2.16 0.97 0.78 wlb_imp 3.34 1.14 0.82 note: oil_fdi extent of stress from environmental problem in the communities answerable with a 5-point scale range from 1= strongly disagree to 5 = strongly agree env_ stress perception of the people on operation of oil companies in the communities accountable on a 5-point scale ranging from 1= strongly disagree to 5 = strongly agree envr_imp impact on environment accountable on a 5-point scale ranging from 1= strongly disagree to 5 = strongly agree gac general awareness of environmental consequences accountable on a 5-point scale range from 1= strongly disagree to 5 = strongly agree wlb_impimpact of crude oil exploitation on peoples' well-being answerable on a 5-point scale ranging from 1= strongly disagree to 5 = strongly agree n sample size impacts of oil foreign direct investment on environment and poverty level in niger delta oil producing region: a structural equation modeling approach 687 the possible range of the average mean score of env_ stress, oil_fdi, envr_imp, gac and wlb_imp is between 1 and 5 the result expressed a positive oil fdi effect on environment and poverty in the host communities. out of a maximum score of 5, the oil_fdi and env_ stress, mean scores of the respondents were 3.67 and 2.18 respectively. the gac and wlb_imp are above the average mean score reported for the peoples’ well-being. along a 5point scale, the mean ofwlb_imp score was 3.34. to further assess the reliability of the collected data, the cronbach’s alpha reliability test was performed on the foregoing constructs. the test rendered alpha values between 0.67and 0.82. these computed figures well exceeded the threshold of 0.70 for exploratory research. the normality of data deductions from the survey was examined and skewness and kurtosis values and their individual items were explored. there was no serious skewness or kurtosis problem that required transformation of data. all the data have absolute values of the original skewness less than 0.7 for theoretical variables. also, absolute value of the original kurtosis was less than 0.6 for theoretical variables (kline, 1998). in fulfilment of normality assumption a data set is considered normal if the values of skewness fall within the range of +2 to -2 while kurtosis values do not exceed the range of +7 to -7 (tabachinick and fidell 2007). given the above threshold for justifying the normality of data, it could be said that all observed data for items considered under this study are normal. 4. estimation and results the overall performance of the proposed model shows the degree to which the present data fit proposed model by various fit indexes. confirmatory factor analysis of the individual construct was used to test the construct validity of the instrument. specifically, to test the convergent validity, it also entails the assessment of model fit for each instrument. an instrument is believed to have satisfied convergent validity only when the values of the instrument’s individual factor loadings and the average variance extracted (ave) satisfy some benchmarks. accordingly, ave that is greater than 0.5 indicates high convergent validity in defining the threshold for factor loading (hair et al, 2003). the models fit construct validity assessment of perception of well-being impact of the oil fdi instrument. this instrument originally comprises eighteen items. however, upon justifying the existence of one underlying dimension in the construct, the items were parceled into five indicators. all factor loadings are greater than 0.5. the instrument’s ave of wib_imp, oil_fdi, env_imp, gac, and stress are computed to assess construct validity. this instrument has high convergent validity because the factor loadings for each indicator > 0.5. the ave is 0.96, 0.84, 0.78, 0.93 and 0.71 > 0.5 respectively. besides, an assessment based on construct validity of ave, model fit is also important to evidence the existence of construct validity. generally, four fit indices are used. the indices generated along with the output including the p-value, ramsea, gfi and nfi, all meet the expected range to justify the existence of construct validity. in sum, the measures indicated that the proposed model fitted well with the present data set. 4.1 measurement model the measurement model, construct is collectively assessed for the establishment of discriminant validity and model fit. this is besides examinations of diagnostics such as multivariate normality. discriminant validity between any two latent constructs is established when the values of their individual ave is greater than the squared correlation between them (ave > r2).the individual ave are greater that the squared correlation. all the model fit indices generated along with the output including the p-value, cfi, ramsea, gfi and nfi, meet their expected range to justify the validity of the measurement model. international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.679-692 688 figure 3. correlations among latent constructs (variables) the results of correlation among latent constructs variables in figure 3 is depicted in the table 3 for more clarity. table 3. correlations among latent constructs (variables) envr_lmp wlb_imp gac stress oil_fdi envr_lmp 1 wlb_imp .07 1 gac .12 -.23 1 stress -.17 -.16 .03 1 oil_fdi -.02 .08 -.02 -.16 1 the correlation coefficient among latent variablesoil_fdi, envr_lmp, stress, wlb_imp and gac in the measurement model indicated that multi co-linearity problem is not inherent. besides it depicts that each of these variables distinctly represents separate constructs. the correlation across latent constructs also explains why the ave for each of the constructs is greater than the square correlation coefficients. hence, the fulfillment of discriminant validity arises from the low correlation across latent constructs. 4.2 the results of structural model figure 4 shows the estimated standardized path coefficients of the five constructs under investigation. the structural model introduced as evidence arecommunities’ perception about the operation of oil producing companies (oil_ fdi); the general awareness of consequence (gac), which measures environmental risk, and environmental stress measures the extent of stress from gac envr_imp pe5e11 .85 pe4e12 .88 pe3e13 .91 pe2e14 .88 pe1e15 .89 stress stress enp 4e16 .92 stress enp 3e17 .70 stress enp 2e18 .82 stress enp 1e19 .93 oil_fdi perception 5e20 .92 perception 4e21 .91 perception 3e22 .89 perception 2e23 .93 perception 1e24 .93 wlb_imp pwb4e25 pwb3e26 pwb2e27 pwb1e28 .98 .98 .97 .98 chi-square=364.504 df=340 p=.173 cfi=.997 rmsea=.017 gfi=.907 nfi=.961 -.23 .03 -.08 .07 -.02 -.17 .12 -.16 .08 -.02 gac 10e29 .93 gac 9e30 .90gac 8e31 .94gac 7e32 .94 gac 6e33 .93gac 5e34 .94 gac 4e35 .93 gac 3e36 .92 gac 2e37 .94 gac 1e38 .92 impacts of oil foreign direct investment on environment and poverty level in niger delta oil producing region: a structural equation modeling approach 689 environmental problem in the communities, which have influence on oil foreign direct investment. the oil-fdi has a consistent impact more on the environment than the well-being of the community thus resulted in high levels of poverty. figure 4. estimated standardized path coefficients of the constructs 4.3 discussion the result in the path diagram model, χ2 is 597.139 with 350 degrees of freedom. the ߩvalue associated with this result is .000. the ߩvalue is significant using a type 1 error rate of .05. the value of the root mean square error of approximation (rmsea), an absolute fit index, is 0.54. this value is below the 0.07 a stringent upper limit guideline (steiger, 2007). the rmsea shows how well the model, with unknown but optimally chosen parameter estimates would fit the population covariance matrix (byrne,1998). it has been regarded as one of the most informative fit indices. also, goodness of fit index (gfi) is 0.869 which reflect good model fit for the model of the sample. another absolute fit statistic is normed χ2, which is 1.71. this measure is the chi-square value divided by the degree of freedom (597.139/ 350 = 1.71). hence, kline (1998) suggests that χ2/ d.f., the ratio must be equal to 3 or less as a reasonably desirable alternative indicator of model fit. from the structural model, χ2/ d.f. ratio yields 1.71 which is less than 2 as suggested by tabachnick and fideli, 2007. this further clarifies that the model has a good fit. furthermore, for the incremental fit indices, the comparative fit index (cfi) is the most widely used index. in the study cfi has a value of 0.973, which exceeds the cfi guidelines of greater than 0.90. the other incremental fit indices also exceed suggested cutoff values. normed fit index (nfi) is 0.937 which reflects good model fit. the results are significant and show reasonably good overall model fit and the hypotheses in the relationships are generally supported. the model shows that community perceptions about the operation of oil companies as well as, environmental consequences and risk perception collectively determine environmental impact perception. the direct environmental impact leads to social strain that caused increased in resource scarcity that lead to greater poverty (gabriel, 2006). the crisis in the niger delta is believed to have been triggered by environmental stress. the constructs estimate coefficient of oil_fdi impact on the environment (envr_imp) and well-being of the people in the communities (wlb_imp) are β = 0.42 and β = 0.32 respectively. the perception of people in the communities that environmental stress causes by foreign direct investment gac .30 envr_imp .82 pe5 e11.90 .84 pe4 e12.92 .89 pe3 e13 .94 .84pe2 e14.92 .85 pe1 e15.92 stress .81 stress enp 4 e16.90 .48 stress enp 3 e17 .69 .67 stress enp 2 e18 .82 .87 stress enp 1 e19.93 .30 oil_fdi .94 perception 5e20 .97 .93 perception 4e21 .96 .91 perception 3e22 .95 .94 perception 2e23 .97 .94 perception 1e24 .97 .10 wlb_imp .97 pwb4 e25 .97 pwb3 e26 .95pwb2 e27 .96pwb1 e28 .98 .98 .98 .98 .85 gac 10e29 .92 .82 gac 9e30 .90.88 gac 8e31 .94 .89 gac 7e32 .94 .86 gac 6e33 .93 .88 gac 5e34 .94 .86 gac 4e35 .93 .85 gac 3e36 .92 .88 gac 2e37 .94 .84 gac 1e38 .92 chi-square=597.139 df=350 p=.000 cfi=.973 rmsea=.054 gfi=.869 nfi=.937 .36 .41 .32 .42 .22 e39 e40 e41 international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.679-692 690 into oil (oil_fdi) estimate coefficient is β = 0.036. while the general awareness of environmental consequences (gac) caused by an increase in foreign direct investment into oil exploitation (oil_fdi) estimate coefficient is β =0.41. the direct effect path estimate coefficient of gac from environmental impact is β = 0.22. however, since the path coefficients are standardized values, a higher value for environmental impact relative to that of well-being, implied that the communities perceived more destruction of their environment than the influence on their well-being from oil fdi.in addition, the exploitation of crude oil has not done well with the degree of environmental and economic efficiency with the principle of pareto optimality benchmark which will ensure efficient allocation of resources in production, and consumption choice that maximize utility. the model is suitable for interaction and decision making on the environment, and consequences of production in the oil sector. in this context, environment and natural resource degradation, pollution and loss of biodiversity are detrimental because they increase vulnerability, undermine health system, and reduce resilience of the communities. it is useful to think about livelihood sustainability in terms of the normal functioning and longevity of a nested hierarchy of ecological and socioeconomic system. from this perspective environmental and socioeconomic system should evolve so as to maintain a level of biodiversity that will guarantee the resilience of the ecosystems on which human consumption and production depend. 5. conclusion the study has investigated the impact of oil foreign direct investment on the environment and poverty level in the niger delta oil producing region. we find that fdi has important implications for rising poverty and social crises in the nigerian oil-rich region. it reveals that the environment appears to be worsening at a faster rate than increase in well-being. this shows that the marginal environmental cost of additional exploitation will rise over time. the people have lost control of some of their traditional natural resources which had led to high level of poverty. most of the natural resources have been locally unsustainable and this has occurred in a manner and scale that often bypass the poor. the implication of this is that the devastation of the environments resulted in the poverty of the people. furthermore, the oil fdi should involve exploitation of crude oil with some degrees of environmental and economic efficiency (ideal of pareto optimality), which encourages actions that will improve the welfare of at least one individual without worsening the situation of someone else. the pareto optimality benchmark will ensure efficient allocation of resources in production, and efficient consumption choice that maximize utility. moreover, it will increase an adaptive capacity and opportunities for improvement of economic, social and economic systems. another implication is that environmental degradation poses a potential threat to sustainable development in the niger delta. although, most of the negative environmental consequences of oil industry activities are localized and more intense in the areas of primary activities and some of the effects are trans-boundary implied. the environmental consequences impose economic costs on the people which often lead to poverty and social tension. unfortunately, there are no explicit provisions made to incorporate the host communities of oil companies in the process of implementing strategies. there is doubt if the oil companies have confidence in their host communities and carry them along for the purpose of cleaning up the environment and educating the local people. if this was done, it would have helped to avoid a number of community level crises. it is important to acknowledge the local rather than universal experience of poverty and environmental degradation and to provide enabling circumstances for poor people to create their own institutional responses to economic, demographic and environmental changes, instead of macroeconomic responses that may increase both poverty and environmental degradation. it is important to build effective public–private synergies of environmental policy that will connect the evolution of new systems to monitor and address risks in industry. it is also important to create institutions that will utilize the environmental expertise available in the private sector to help gain local trust and effective regulation of industry. it is clear that many rapidly industrializing countries require waste management or new technologies available from foreign investment. the investment in oil has to be conducted under a form of regulation that accelerates the provision of environmental infrastructure that will achieve this for the sake of local development and environmental protection rather than for the agendas of investors alone. in addition, there is a need for impacts of oil foreign direct investment on environment and poverty level in niger delta oil producing region: a structural equation modeling approach 691 sustainable livelihoods through locally controlled access on their income. research on sustainable livelihoods has identified that the locally controlled resource development may imply a movement away from both poverty and environmental degradation as a result of diversifying incomes and economic concerns of local groups. furthermore, the study submits that national environmental policy capacity and accessibility is a common requirement for implementing environmental policy. however, it is also important to incorporate local resistance to the potentially negative impacts of international environmental agreements. therefore, future research may adopt methodology of valuation of the environment to quantify the full costs of environmental degradation, and a need for inferring the optimal penalty to discourage gas flaring and oil spillage to be based on scientific inquiry. this presupposes a detailed and focused research to determine the compliance cost to oil companies such that the penalty for environmental degradation will yield to government revenue and compensation to the poor people of the host communities. references acemoglu, d. (2003), why not a political coase theorem? social conflict, commitment, and politics, journal of comparative economics, 31, 620–65. akkemik, k.a., goksal, k. (2012), energy consumption-gdp nexus: heterogeneous panel causality analysis, energy economics, 34 (4), 865–873. bassam, y. (2008), non-renewable resource depletion and reinvestment: issues and evidence for an oil-exporting country, environmental and development economics, 14, 211-226. baumol, w., oates, j. (1988), the theory of environmental policy, 2nd edition, publisher: cambridge university press byrne, b.m. (1998), structural equation modeling with lisrel, prelis and simplis: basic concepts, applications and programming mahwah, publisher: lawrence erbaum associate, new jersey. catarina, r.p., alexandra, f., tiago, n.s. (2010), externalities in an endogenous growth model with social and natural capital, ecological economics, 69(3), 603-612. clive, l.s., aril, d.v. (2006), transferring environmental value estimates: issues and alternatives, publisher: commonwealth scientific and industrial research organization (csiro), sustainable ecosystems division collin, p. (2007), sustainable forest management, pecuniary externalities and invisible stakeholder, journal of forestry policy and economics, 9, 61-73. costanza, r., arger,.d., grootr, d. (1997), the value of the world’s ecosystem services and natural capital, nature, 387, 253–260 elif -akbostanci, s.t., ipek, t.g. (2009), the relationship between income and environment in turkey: is there an environmental kuznets curve? energy policy, 37, 861–867. eric, n. (2001), the human development index and sustainability: a constructive proposal, ecological economics, 39(1), 101-114. fafchamps, m., quisumbinga, r. (2002), control and ownership of assets within rural ethiopian households, journal of development studies, 38(2), 47-82. gabriel, e. (2006), the role of mnes in community development initiatives in developing countries: corporate social responsibility at work in nigeria and south africa, business and society, 45(2), 93-129. glenn, f. (2007), the real coase theorems, cato journal, 27(3), 70-85. gunderson, l., holling, c.s, (2001), panarch: understanding transformations in human and natural system, publisher: island press, new york, 11-17 hair, j. f. (2003), essentials of business research, indianapolis, publisher: willey jacobs, m. (1994), the limit of neoclassicism: towards an institutional environmental economics. in redclift m. and global environment, publisher: roontledge, london and new york. john, a.d. (2008), environmental valuation: challenges and practices, economics and conservation in the tropics, a strategic dialogue. judith, m.d. (2009), are foreign investors attracted to weak environmental regulations? evaluating the evidence from china, journal of development economic, 90(1), 1-13 international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.679-692 692 kalpana, a., syed, a.h., ruchi, b. (2007), social and economic considerations in conserving wetlands of indo-gangetic plains: a case study of kabartalwetland, india, the environmentalist, 27 (2), 261-273. kapp, k.w. (1950), the social cost of private enterprise, publisher: cambridge university press, cambridge. kline, r.b. (1998), principles and practice of structural equation modeling, publisher: guilford press, new york. kline, j.b., klammer, j.d. (2001), path model analysed with ordinary least squares multiple regression versus lisrel, the journal of psychology, 135(2), 213-225. krejcie, r.v., morgan, d.w. (1970), determining sample size for research activities educational and psychological measurement, http://eric.ed.gov/ericwebportal/search/detailmini.jsp?_nfpb=true&_&ericextsearch liu, h. (2013), the impact of human behaviour on ecological threshold: positive or negative? grey relational analysis of ecological footprint, energy consumption and environmental protection, energy policy, 56, 711–719. naubahar, s. (2006), emergence and development of the national innovation system concept, research policy, 35 (5), 745-766. okaba, b. (2005), petroleum industry and paradox of rural poverty in the niger delta, publisher: ethiopia publishing company benin city. onosode, g. (2003), environmental issues and the challenges of the niger delta: perspectives for the niger delta environmental survey process, publisher: cibn press, lagos. orubu, c.o. (2002), fiscal undercurrents in the lingering crisis in nigeria’s oilproducing state, in: fiscal federalism and democratic governance in nigeria, publisher: ncema. richard, e.b., paul, k. (2004), agglomeration, integration and tax harmonization, european economic review, 48(1), 1-23. rudolf, s.d. (2002), a typology for the classification, description and valuation of ecosystem function, good and services, journal of ecological economics, 41(3), 393-408 salami, d.k., kari f., gazi, m.a., chukwu, g.o.m., oke, d.m., oke, o.k. (2012), foreign direct investment in oil sector and economic growth in nigeria, the international journal of applied economics and finance, 6(4), 117-126. stonich, s. (1992), struggling with honduran poverty – the environmental consequences of natural resource-based development and rural transformations, world development, 20(3), 385-400 tabachinick, b. g., fidell, l.s, (2007), using multivariate statistics, 5th ed., publisher: allyn and bacon, new york. terrence, c., kevin, c. (2005), social capital and economic performance in the american states, social science quarterly, 86(4), 826–845. thomas, b., regina b., nancy, m.c, (2006), capturing the complexity of water uses and water within the multi-agent framework, water resources management, 21(1), 9-14. unctad (2005), world investment report: transnational corporations and the internationalization of r&d, new york and geneva. victor, o. (2010), the dilemma of justice: foreign oil multinationals and human rights violation in the niger delta of nigeria, in liam leonard, john barry (ed.) global ecological politics advances in ecopolitics, 5, 43-47. wackernagel, m.c., monfreda, c., schul, z.c. (2004), calculating national and global ecological footprint time series: resolving conceptual challenges, land use policy, 21(3), 271–278. weitzman, m., lofgren, k.g. (1997), on the welfare significance of green accounting as taught by parable, journal of environmental economics and management, 32, 139-153. johannes trüby, moritz paulus international journal of energy economics and policy vol. 5, no. 1, 2015, pp.54-68 issn: 2146-4553 www.econjournals.com crude oil price shocks and stock returns: evidences from turkish stock market under global liquidity conditions berna aydogan izmir university of economics, department of international trade and finance, izmir, turkey. email: berna.okan@ieu.edu.tr istemi berk university of cologne, cologne graduate school (cgs), institute of energy economics (ewi), germany. email: istemi.berk@ewi.uni-koeln.de abstract: the purpose of this study is to investigate the impacts of crude oil price variations on the turkish stock market returns. we have employed vector autoregression model using daily observations of brent crude oil prices and istanbul stock exchange national index returns for the period between january 2, 1990 and november 1, 2011. we have also tested the relationship between oil prices and stock market returns under global liquidity conditions by incorporating a liquidity proxy variable, chicago board of exchange’s s&p 500 market volatility index into the model. variance decomposition test results suggest little empirical evidence that crude oil price shocks have been rationally evaluated in the turkish stock market. rather, it was global liquidity conditions that were found to account for the greatest amount of variation in stock market returns. keywords: oil price shocks; stock returns; global liquidity jel classifications: c58; g15; q43; q47 1. introduction since the first oil crisis experienced in 1973, the impact of oil price changes on macroeconomic activity has been widely discussed by academic researchers, investors and policy makers. in this respect, the pioneering study of hamilton (1983), which concludes that there is significant correlation between increase in crude oil prices and us recessions, has been accepted as the fundamental basis for the subsequent studies on the effects of crude oil price shocks on macroeconomic indicators such as gdp growth rate, inflation, and industrial activity 1 . according to these studies, the price of crude oil, which is the primary fuel of industrial activity, plays a significant role in shaping the countries’ economic and political developments, not only by directly affecting the aggregate indicators, but also by influencing companies’ operational costs, and thus their revenues. when the stock market is efficient, positive crude oil price shocks would negatively affect the cash flows and market values of companies, causing an immediate decline in the overall stock market returns. although there exists a major consensus in the literature that endogeneity is not an issue when analyzing the impacts of oil prices on stock markets of the countries apart from usa, some studies (e.g., park and ratti, 2008) suggest that there would, at least, be some sort of spillover from us or global financial markets to that of developed, mostly european, countries. it also seems plausible to consider this interrelationship when studying stock markets of emerging economies, which attract large amount of short-term capital movement from major economies. this paper extends the understanding on the issue of global spillover effects on the dynamic relationship between oil prices and stock market returns by employing data from one particular emerging economy, turkey. 1 please see “section 2. literature review” for corresponding studies. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.54-68 55 the purpose of this paper is to investigate the impacts of oil price shocks on the turkish stock market for the period between january 1990 and november 2011 using the vector autoregression (var hereafter) model. a proxy variable capturing liquidity conditions in the global financial system is included into the analyses in order to examine the above-mentioned spillover effect. since turkey has limited domestic oil production and reserves, imports make up a significant portion of its oil consumption. therefore, turkish economy appears sensitive to oil price changes, similar to other developing and crude oil import-dependent countries. moreover, over the last decades turkish financial market, through a condense trade liberalization, has been attracting worldwide capital inflow. as of november 2011 foreign portfolio investments have been responsible for nearly 63% of total turkish stock market capitalization. 2 thus turkish stock market returns have become sensitive to the shocks created in international financial markets. one more reason for including financial liquidity is that financial, more specifically futures, markets have been the other major crude oil market since the early 1990s. this was the result of increasing volume of crude oil future contracts traded, which exceeded global oil production/consumption during late 1980s 3 . since then crude oil prices have been determined in a manner that accounts for the effects of decisions made by investors, speculators, hedgers, and large investment funds in the future markets, as well as physical market conditions. analyzing these “nonphysical” market conditions, such as expectations about the market, global financial and economic indicators, would increase the possibility to shed some more light on the empirical variations in crude oil prices. therefore, a proxy for global financial liquidity will not only serve as an explanatory factor that influences stock market returns, but also be used to explain variations in oil prices. in the current study, the evidence of such tridimensional interaction, e.g. joint respond of stock returns and oil prices to liquidity, is investigated using the disentangling methodology proposed by kilian and park (2009). understanding the impact of crude oil prices on turkish stock market is potentially beneficial for investors, market participants, regulators and researchers, as it is likely to exhibit characteristics different from those observed in well-documented developed markets. thus, our study explores an underexploited area of potentially valuable research in turkey with a very comprehensive data set, ranging from january 1990 and november 2011. this relatively long time horizon has been divided into three sub-periods 4 coinciding with specific oil price trends to allow testing of the performance of the turkish stock market under different oil price regimes. empirical results suggest that oil prices have significant impacts on turkish stock market returns only during the third sub-period, during which crude oil prices represented extreme volatile structure. on the other hand, whenever the financial liquidity conditions are incorporated into the analyses, it is found out that liquidity is the most plausible explanation for the changes in both oil prices and stock market returns. the remainder of this paper is organized as follows. the next section provides relevant literature about the relationship between financial markets and oil price shocks. section 3 outlines the econometric methodology concerning var analysis and disentangling. the data set and empirical results are presented in section 4. finally, section 5 contains discussion of results and concluding remarks. 2. literature review since hamilton (1983), a plethora of studies have analyzed the interrelation between macroeconomic activity and oil price changes, most of which demonstrated a negative correlation 5 . 2 data from website of istanbul stock exchange (imkb): http://www.ise.org/data/stocksdata.aspx. 3 using data for global crude oil production/consumption from bp’s statistical review of world energy 2011 and for the volume of wti crude oil futures contracts from nymex official website exact year can be derived as 1988. 4 sub-period i: january 1990–november 2001; sub-period ii: november 2001–july 2008; sub-period iii: july 2008–november 2011. please see section 4.1 for details of sub-periods. 5 mork, 1989; kahn and hampton, 1990; huntington, 1998; brown and yucel, 1999, 2002; gao and madlener, 1999; hamilton, 2003; dickman and holloway, 2004; guo and kliesen, 2005; rogoff, 2006; sill, 2007; kilian, 2008; and oladosu, 2009. moreover, a number of researchers have examined the role of crude oil prices in crude oil price shocks and stock returns: evidences from turkish stock market under global liquidity conditions 56 however, according to the studies on the relationship between oil prices and stock markets, oil price shocks influence various industries’ stock prices differently and the relationships between oil price shocks and financial markets are, for many countries, complex and ambiguous. a commonly held view is that an upward trend in oil price is beneficial for oil producing companies’ stock returns and oil exporting countries’ market activity, yet has an adverse effect on most of other sectors and oil importing countries. a firm-specific study by al-mudhaf and goodwin (1993) investigated the returns from 29 oil companies listed on the nyse and demonstrated a positive impact of oil price shocks on ex post returns for firms with significant assets in domestic oil production. further, haung et al. (1996) analyzed the relationship between daily oil future returns and us stock returns by employing an unrestricted vector autoregression (var) model and found evidence that oil futures clearly lead some individual oil company stock returns. faff and brailsford (1999) used market model to investigate several industry returns in the australian stock market, finding significant positive oil price sensitivity of australian oil and gas, and diversified resources industries. in contrast, industries such as paper and packaging, banks and transport appear to display significant negative sensitivity to oil price hikes. sadorsky (2001) indicated that stock returns of canadian oil and gas companies are positively sensitive to oil price increases. boyer and filion (2009) employed a multifactor framework to analyze the determinants of canadian oil and gas stock returns, finding similar results to sadorsky (2001). although el-sharif et al. (2005) demonstrated how the oil prices have significantly positive impacts on oil and gas returns in the uk, evidence for the oil price sensitivity existing in the non-oil and gas sectors is generally weak. in this context, henriques and sadorsky (2008) measured the sensitivity of the financial performance of alternative energy companies to changes in oil prices using var model in order to investigate the empirical relationship between alternative energy stock prices, technology stock prices, oil prices, and interest rates. they indicated that technology stock price and oil price each individually granger causes the stock prices of alternative energy companies. more recently, obernderfer (2009) analyzes the interrelationship between oil prices and european energy companies and finds both oil prices and oil price volatility negatively affects the stock prices of utility companies. jones and kaul (1996) examined whether the reaction of international stock markets to oil shocks could be justified by current and future changes in real cash flows, or changes in expected returns. they provided evidence that aggregate stock market returns in the us, canada, japan and the uk are negatively sensitive to the adverse impact of oil price shocks on the economies of these countries. contradicting to jones and kaul (1996), huang et al. (1996) found no evidence of a relationship between oil futures prices and aggregate stock returns using daily data from 1979 to 1990. however, ciner (2001) challenged the findings of huang et al. (1996), and argued for the need for further research to produce evidence from international equity markets to support the robustness of the results. he concluded that a statistically significant relationship exists between real stock returns and oil price futures, but that the connection is non-linear. moreover, huang et al. (2005) investigated the effect of oil price change and its volatility on economic activities in the us, canada and japan. they indicated that when exceeding a certain threshold, oil price change and volatility possess significant explanatory power for the outcome of economic variables such as industrial production and stock market returns. theoretically, in oil exporting countries, stock market prices are expected to be positively affected by oil price changes through positive income and wealth effects. in an analysis of the effects of oil price shocks on stock markets in norway, bjørnland (2009) argued that higher oil prices represent an immediate transfer of wealth from oil importers to exporters, stating that the medium to long-term effects depend on how the governments of oil producing countries dispose of the additional income. if used to purchase goods and services at home, higher oil prices will generate a higher level of activity, and thus improve stock returns. in addition, gjerde and saettem (1999) demonstrated that stock returns have a positive and delayed response to changes in industrial production and that the stock market responds rationally to oil price changes in the norwegian market. a negative association between oil price shocks and stock market returns in oil importing countries has been reported in several recent papers. nandha and faff (2008) examined global equity monetary policy (e.g., bernanke et al., 1997; hamilton and herrera, 2004) and impacts of oil prices on exchange rates (e.g., chen and chen, 2007; coudert et al., 2008). international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.54-68 57 indices with 35 industrial sectors, showing that oil price rises have a negative impact on stock returns for all sectors except the mining, and oil and gas industries. o'neill et al. (2008) found that oil price increases led to reduced stock returns in the us, the uk and france. in a study of the connection between oil price shocks and the stock market for the us and 13 european countries, park and ratti (2008) reported that oil price shocks had a negative impact on stock markets in us and many european countries, while the stock exchange of norway showed a positive response to the rise in oil prices. these authors also provided evidence that stock markets in oil exporting countries are less affected by oil prices relative to oil importing countries. the results of chiou and lee’s (2009) study confirmed the existence of a negative and statistically significant impact of oil prices on stock returns. their findings also provided support for the notion that oil shocks drive economic fluctuations, with the evidence indicating that with changes in oil price dynamics, oil price volatility shocks have an asymmetric effect on stock returns. examining whether the endogenous character of oil price changes affect stock market returns in a sample of eight developed countries, apergis and miller (2009) found evidence that different oil market structural shocks play a significant role in explaining adjustments in international stock returns. aloui and jammazi’s (2009) study focused on two major crude oil markets, namely wti and brent, and three developed stock markets, namely france, uk and japan and was based on the relationship between crude oil shocks and stock markets from december 1987 to january 2007. the results indicated that the net oil price increase variable plays an important role in determining both the volatility of real returns and the probability of transition across regimes. more recently, arouri and nguyen (2010) used different empirical techniques namely, market model and the two-factor market and oil model, to test the causality between oil prices and twelve european sector indices listed on dow-jones for the period from january 1998 to november 2008. they found asymmetries in response of the different sector indices to oil price changes. fan and jahan-parvar (2012), studying the interrelation between u.s. industry-level returns and oil prices, found no evidence that oil prices have significant predictive power for industry-level returns. chortareas and noikokyris (2014) has more recently investigated the effects of oil supply and demand shocks on u.s. dividend yield components, i.e. dividend growth, real interest rate, equity premium. following disentangling methodology proposed by kilian (2009) they showed that that although positive relationship between oil price increase and dividend yield is evident, the persistence of relationship is highly dependent on the driving force of the oil price increase. jammazi and aloui (2010) explore the impact of crude oil shocks on stock markets of three developed countries, uk, france and japan, using a combined approach of wavelet analysis and markov switching vector autoregression. they evaluated the issue in two phases of stock markets and found that while oil shocks do not affect stock markets during recession phases, they have significant negative impact during expansion phases. while jammazi (2012a) uses the same approach with jammazi and aloui (2010) to analyze the effect of crude oil shocks on stock market returns of usa, canada, germany, japan and uk, jammazi (2012b) uses a transformation of wavelet analysis with haar a trous decomposition to explore the interactions between crude oil price changes and stock returns of same five countries. the results of these studies reveal that both approaches are more accurate then the methodologies used in existing literature when the focus is to account for changing intensity of crude oil shocks over time. reboredo and rivero-castro (2014) also used wavelet-based analysis to investigate the impacts of oil prices on different stock market indices, including s&p 500, dow jones stoxx 600 and sectoral indices, and found positive interdependence especially during post credit crunch period. contrary to the work done on developed markets, relatively little research has focused on the relationship between oil prices and stock markets of emerging – oil exporting or importing – economies. hammoudeh and aleisa (2004) examined the relationship between oil prices and stock prices for five members (bahrain, kuwait, oman, saudi arabia, and the united arab emirates) of the gulf cooperation council (gcc), all of which are net oil exporters, for the period 1994-2001, while zarour (2006) investigated the same countries during 2001 to 2005. hammoudeh and aleisa’s findings suggested that most of these markets react to the movements of the oil futures price, with only saudi arabia having a bidirectional relationship. by analyzing the impulse response function, zarour concluded that the sensitivity of these markets to shocks in oil prices has increased, with responses becoming more rapid after rises in prices. arouri and fouquau (2009) investigated the short-run crude oil price shocks and stock returns: evidences from turkish stock market under global liquidity conditions 58 relationships between oil prices and gcc stock markets. to examine the phenomena of stock markets’ occasional non-linear response to oil price shocks, they examined both linear and nonlinear relationships. their findings pointed to a significant positive relation between oil prices and the stock index of qatar, oman and uae, but for bahrain, kuwait and saudi arabia, they found no such influence. as another gcc study, naifar and al dohaiman (2013) using markov regime-switching model, found that the relationship between those markets and oil price volatility is dependent upon the regime. employing an error correction representation of a var model, papapetrou (2001) concluded that oil price is an important factor in explaining the stock price movements in greece, and that a positive oil price shock tends to depress real stock returns. maghyereh (2004) studied the relationship between oil prices changes and stock returns in 22 emerging markets, conducting var model from 1998 to 2004, without finding any significant evidence that crude oil prices have an impact on stock index returns in these countries. in contrast to this conclusion, basher and sadorsky (2006), analyzing the impact of oil price changes on a large set of emerging stock market returns for the period 1992 to 2005, proposed that emerging economies are less able to reduce oil consumption and thus are more energy intense, and more exposed to oil prices than more developed economies. therefore, oil price changes are likely to have a greater impact on profits and stock prices in emerging economies. cong et al. (2008) apply multivariate vector autoregression methodology to analyze the interactive relationship between oil price shocks and chinese stock market activity. authors find no evidence that oil price shocks have no significant effect on stock returns except for manufacturing index and some oil companies’. similarly, narayan and narayan (2010) investigated the impact of oil prices on vietnam’s stock prices and concluded that oil price have a positive and significant impact on stock prices. finally, soytaş and oran (2011) examined the causality between oil prices and turkish stock market (ise-100) aggregate and electricity indices. they concluded that while oil prices do not granger cause aggregate index, they have significant impact on electricity index. 3. methodology this study employs var approach in order to examine the dynamic interactions between oil price shocks and the turkish stock index, and compare results, which take into account global financial liquidity conditions with those that do not. the var model introduced by sims (1980), presents a multivariate framework that expresses each variable as a linear function of its own lagged value and lagged values of all the other variables in the system. the main advantage of this approach is the ability to capture the dynamic relationships among the economic variables of interest. the methodology treats all variables as jointly endogenous, and for proper estimation in a multivariate stable var system, all variables employed in the model must be stationary or i(0) process. although there are many tests developed in the time-series econometrics to test for the presence of unit roots, two tests in particular the augmented dickey-fuller (adf hereafter) test (dickey and fuller, 1979, 1981) and the kwiatkowski, phillips, schmidt, and shin (kpss hereafter) test (kwiatkowski et al., 1992) have been employed to investigate the degree of integration of the variables used in the empirical analysis 6 . case i: simple model here, we start with a simple model, which takes the relationship between oil prices and turkish stock market into account and neglects effect of global liquidity constraints. in this model we needed to transform oil prices into shock variables. besides linear ones, some nonlinear transformations of oil prices have also been proposed in the literature 7 . therefore, in order to achieve robust empirical results we have used both linear and nonlinear transformations of oil prices. two types of variables for oil price shocks employed in this study are log return and scaled oil price increase (sopi hereafter). the log return of oil prices, , is from to calculated as; (1) 6 since all the variables included in the var methodolog are i(0) process, vector error correction model (vecm) was not conducted in this paper. 7 mork, 1989; lee et al., 1995; hamilton, 1996. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.54-68 59 where denotes oil prices at time . the oil price shock variable is also calculated by the method of sopi developed by lee et al. (1995). (2) where is the residuals and is the square root of the volatility ( ), which are derived from equation system (3), and captures positive oil price shocks for the subjected date. for this specification, garch (p,q) model, which has been first proposed by bollerslev (1986) and has become popular, particularly, due to its explanatory power for dependence in volatility, is estimated as follows: (3) where is white noise with . furthermore, we have proposed a bivariate system with daily return of turkish stock index and two types of oil price change variable to analyze the variance decomposition structure. the model is written in the reduced form of structural var representation as follows: (4) where is the log-return of daily turkish stock exchange index price, and is the corresponding oil price shock variable, either or . case ii: incorporating global liquidity conditions the dynamic system in equation (4) may lead to a conclusion that oil price shocks have significant impacts on stock returns, however this result may be biased if any variable, which affects both oil prices and stock returns in the long-run, is omitted. in order to avoid such a consequence, we should obtain a “purified” oil price shock variable, related only to the oil market itself. in order to obtain such purified oil market specific price shock variable we have employed disentangling methodology, proposed by kilian and park (2009). a proxy variable for global financial liquidity conditions, which is thought to be responsible for variations in oil prices besides physical oil market conditions, is incorporated into the analyses. chicago board of options exchange’s (cboe hereafter) s&p 500 market volatility index, , is chosen as the proxy for global liquidity and its first difference, , is used 8 in var framework: (5) the first equation of this dynamic system allows to capture residuals, , which can be used as purified oil market specific shock variable. this residual series and are, further, used in the var framework proposed below instead of oil price shock variable, , to examine their effects on turkish stock index returns’ variance decomposition structure. the proposed dynamic system, hence, becomes a tri-variate var with a following representation: 8 first difference of cboe’s volatility index , which is stationary, is used in the analyses since is i(1) process. crude oil price shocks and stock returns: evidences from turkish stock market under global liquidity conditions 60 (6) variance decomposition analysis of this tri-variate var system will enlighten whether turkish stock returns react to oil market specific shocks, or to shocks created in global markets due to the liquidity conditions. 4. data and empirical results 4.1. data the data of this study consists of daily observations of ice’s brent crude oil prices , logreturn of ise-100 stock market index , and cboe volatility index . the ‘national-100 index’ (ise-100) is the main market indicator of the turkish stock market. the data for brent crude oil prices, ise-100 index prices and vix obtained from the us energy information administration, the matrix database 9 and cboe’s official website, respectively. the data covers the period from january 2, 1990 to november 1, 2011, realizing a total of 5,194 observations. in order to examine stock market behavior under different oil price regimes, the data set is divided into three sub-periods. the first sub-period consists of 2833 observations, namely from january 2, 1990 to november 15, 2001, where oil prices follow a comparatively stable and horizontal trend, ranging between 9 us dollars per barrel ($/bbl hereafter) and 41 $/bbl. the second consists 1604 observations from november 16, 2001 to july 11, 2008, during when the crude oil market, as with other commodities, witnessed historical record prices after an upward trend reaching to approximately 145 $/bbl. during the third, from july 14, 2008 to november 1, 2011, with the credit crunch period, crude oil prices immediately fell from 145 $/bbl barrel to nearly 40 $/bbl, and then increased again to approximately 125 $/bbl, representing high volatility, which led to extremely large positive and negative returns within a relatively short time period. the descriptive statistics for brent crude oil returns , ise-100 stock index returns , and first difference of cboe’s s&p 500 market volatility index series are provided in table 1. all three descriptive series display non-gaussian characteristics with negative skewness for brent crude oil returns and positive skewness for ise-100 stock index returns, and cboe’s market volatility index. moreover, all series exhibit excessive kurtosis, a fairly common occurrence in high-frequency financial time series data, and suggest that the observed excessive kurtosis may be due to heteroskedasticity in the data, which may be captured with the garch models. table 1. descriptive statistics of sample series mean 0.0003 0.0015 0.0034 median 0.0008 0.0014 -0.0600 maximum 0.1813 0.2655 16.5400 minimum -0.3612 -0.2033 -17.3600 standard deviation 0.0247 0.0290 1.5876 coefficient of variation 82.33 19.33 466.94 skewness -0.7742 0.0469 0.6606 kurtosis 17.29 8.58 21.46 jarque-bera stat. 44736.01* 6745.03* 74148.06* # of observations 5193 5193 5193 notes: sd indicates standard deviation. jarque-bera normality test statistic has a chi-square distribution with 2 degrees of freedom.* denotes statistical significance at 1% level. 9 matriks is a licensed data dissemination vendor located in turkey. it provides data and information on global financial markets as well as selected macroeconomic indicators. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.54-68 61 excessive kurtosis would also explain the reasoning for high jarque-bera statistics, which reject the null hypothesis of normality for all return series. values for coefficient of variation (cv) represent extreme and relatively high variance clustering around the mean of and . the volatility index variable, by definition, captures variance of cboe market; hence high cv is expected for . on the other hand high cv value for suggests further analyzing the variance structure of oil returns. figure 1. brent crude oil prices, returns and tail distribution with qq-plot 1990 1995 2000 2005 2010 50 100 150 price 1990 1995 2000 2005 2010 -0.25 0.00 return -0.3 -0.2 -0.1 0.0 0.1 0.2 10 20 density return -0.3 -0.2 -0.1 0.0 0.1 0.2 -0.25 0.00 distribution return -0.075 -0.05 -0.025 0 0.025 0.05 0.075 -0.25 0.00 qq plot return ´ normal note: the brent crude oil price, daily returns, daily returns density and qq-plot against the normal distribution. the time period is from 02.01.1990 – 01.11.2011 volatility clustering is immediately evident from the graphs of daily oil returns, which suggests the presence of heteroskedasticity (figure 1). the density graphs and the qq-plot against the normal distribution show that return distribution exhibits fat tails, which the qq-plots reveal are not symmetric. oil prices show the greatest volatility and excess kurtosis, and the corresponding returns are positively skewed. this short but important preliminary descriptive and graphical analysis of the series indicates that the chosen statistical model should take into account the volatility clustering, fat tails and skewness features of the returns. 4.2 empirical results before investigating the impacts of oil price shocks on the stock market, we proceed to examine the stochastic properties of the series considered in the model by analyzing their order of integration on the basis of a series of unit root tests. specifically, the augmented dickey-fuller (adf) and kwiatkowski-phillips-schmidt-shin (kpss) tests are performed for the three sub-periods and the findings, summarized in table 2, indicate that the first differences of all series are stationary, i(1) for all periods, allowing us to model the dynamic interactions with var model. crude oil price shocks and stock returns: evidences from turkish stock market under global liquidity conditions 62 table 2. unit root test results 10 level first difference adf kpss adf kpss brent crude oil sub-period i -2.760 0.603* -17.905* 0.038 sub-period ii 0.272 0.429* -38.524* 0.137*** sub-period iii -5.120* 0.338* -27.608* 0.289* whole period -2.852 1.341* -11.308* 0.022 ise-100 sub-period i -2.129 0.976* -13.685* 0.035 sub-period ii -1.531 0.297* -40.282* 0.136*** sub-period iii -1.227* 0.407* -12.278* 0.143*** whole period -2.157 1.434* -14.754* 0.035 vix sub-period i -4.181* 0.901* -19.364* 0.018 sub-period ii -2.002 0.802* -17.837* 0.041 sub-period iii -2.726 0.277* -8.907* 0.053 whole period -5.046* 0.273* -13.629* 0.014 *,** and *** indicate the statistical significance at 1%, 5% and 10% level, respectively. as represented in equation system (4), var analysis is conducted on two types of oil price shock variables. in order to estimate type shock variable, volatility of brent crude oil returns is modeled with ar(1)-garch(1,1) 11 specification and the test results are indicated in table 3. all of the parameter estimates of the ar(1)-garch(1,1) model are found to be highly statistically significant. the persistence in volatility as measured by sum of and in garch model is closer to unity for each period. as shown in table 3, the estimated coefficient in the conditional variance equation is considerably larger than coefficient. the implication is that the volatility is more sensitive to the previous forecast of volatility in the market place. table 3. garch variance estimation results sub-period i 0.0001 0.0765* 0.0000* 0.8926* 0.1032* sub-period ii 0.0016* -0.0220 0.0000* 0.8620* 0.0400* sub-period iii 0.0009 0.0013 0.0000** 0.9328* 0.0600* whole period 0.0005** 0.0328** 0.0000* 0.9154* 0.0747* *,** and *** indicate the significance at 1%, 5% and 10% confidence level respectively. to check the performance of our model, arch-lm specification test was conducted on the normalized residuals, and there should be no arch effect left in the normalized residuals. table 4 reports arch-lm test results for all three sub-periods. the results indicate that no serial dependence persists left in squared residuals of brent crude oil returns after volatility modeling for sub-periods i and iii, and also for the whole period. although test statistics for sub-period ii rejects the null hypothesis of “no serial dependence between squared residuals”, it is statistically significant only at the 10% level of significance. hence, the results suggest that ar(1)-garch(1,1) model is reasonably well specified to capture the arch effects. 10 note that null hypothesis (h0: unit root exists in time series) for adf test is the alternative hypothesis (ha) for kpss test. 11 different ar(q)-garch(p,q) models were initially fitted to the data and compared on the basis of the akaike and schwarz information criteria (aic and sic) from which a ar(1)-garch(1,1) model was deemed most appropriate for modeling. the test results were not reported but they are available upon request from the authors. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.54-68 63 table 4. arch-lm test results constant term squared residuals f-statistics lm-statistics sub-period i 1.003 (0.0000) -0.004 (0.8280) 0.0472 (0.8280) 0.0473 (0.8279) sub-period ii 1.037 (0.0000) -0.041 (0.0986) 2.7306 (0.0986)* 2.7293 (0.0985)* sub-period iii 1.013 (0.0000) -0.010 (0.7773) 0.0801 (0.7773) 0.0803 (0.7769) whole period 1.006 (0.0000) -0.0072 (0.6026) 0.2712 (0.6026) 0.2712 (0.6025) note: the numbers in parenthesis are p-values. * denotes rejection of null hypothesis at 10%. since the volatility modeling has significantly succeeded in capturing the oil prices variance to a significant degree, the garch model and derived residual terms were further used in equation (2) to calculate data. then we employed var framework as in equation system in (4) with ise-100 daily returns and two of the oil price shock variables, log returns ( ) and , separately for each period. the results of wald test for block significance and generalized variance decomposition of ise-100 due to the oil price shocks are summarized in table 5 and table 6 respectively. according to the block-significance test results, oil prices found to have a statistically significant impact on stock returns only during the last sub-sample period. yet the impact is rather small as represented in variance decomposition results. table 5. block exogeneity wald test results for system in (4) implied coefficient restrictions -stat -stat sub-period i , for 1.8095 1.5544 sub-period ii 1.3681 1.8308 sub-period iii 6.5633* 10.1163* whole period , for 4.3473 6.7199 note: aic determines the lag-length for var model as 5 for the first sub-period, 1 for the second sub-period, 1 for the third sub-period and 6 for whole period. *, ** and *** indicate the significance at 1%, 5% and 10% confidence level respectively. table 6. generalized decomposition of variance of ise-100 in response to oil price shock variables days after impulse sub-period i sub-period ii sub-period iii whole period 1 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 2 0.0344 0.0258 0.0854 0.1144 0.8094 1.2432 0.0148 0.0011 5 0.0486 0.0522 0.0861 0.1147 0.8098 1.2433 0.0148 0.0234 10 0.0553 0.0593 0.0861 0.1147 0.8098 1.2433 0.0148 0.1322 moreover, in order to include global financial liquidity conditions into the analyses, var methodology between brent crude oil prices and cboe’s s&p 500 volatility index (eq. 6) was used to capture the variance decomposition, which is provided in table 7. although the block-significance test results 12 imply a unidirectional lead-lag relation between first difference of vix and crude oil returns for all three sub-periods, it is only during the third sub-period that shocks from vix create a comparatively higher variance on crude oil returns. on the other hand, regardless of the magnitude of the effect of global financial liquidity condition on variance of crude oil prices, it would still be 12 according to the block exogeneity wald test, there exists a significant unidirectional causality from first difference of vix to log-returns of brent crude oil prices at 1% level for all three sub-periods. crude oil price shocks and stock returns: evidences from turkish stock market under global liquidity conditions 64 considered possible to be able to capture residuals for oil returns that will be used as oil market specific price shocks purified of global liquidity constraints. table 7. generalized decomposition of variance of brent crude oil returns in response to global financial liquidity days after impulse sub-period i sub-period ii sub-period iii whole period 1 0.0000 0.0000 0.0000 0.0000 2 0.0912 0.6183 1.9680 0.1580 5 0.3545 0.6482 2.6108 0.2253 10 0.6819 0.6487 3.8427 0.3578 note: aic determines the lag-length as 7 for the first sub-period, 4 for the second sub-period, 1 for the third subperiod and 7 for the whole period. once oil market specific shock, , and financial liquidity shock, , are captured by the disentangling methodology, they are considered as two separate variables, along with stock prices in the var framework. therefore, we have also used this multivariate framework to investigate the interrelationship between ise-100 returns, oil price shocks and global financial liquidity shocks for the whole periods. the results, which are provided in table 8, imply that the global liquidity statistically increases the variance of ise. table 8. block exogeneity wald test results for system in (6) implied coefficient restrictions -stat implied coefficient restrictions -stat sub-period i , for 24.4151* , for 4.2867 sub-period ii 34.1651* 1.4218 sub-period iii 95.7573* 3.1124*** whole period , for 85.0101* , for 6.0041 note: aic determines the lag-length as 6 for the first sub-period, 1 for the second sub-period, 1 for the third subperiod and 6 for the whole period. *,** and *** indicate the significance at 1%, 5% and 10% confidence level respectively. table 9. generalized decomposition of variance of ise-100 in response to oil price shock with global financial liquidity days after impulse sub-period i sub-period ii sub-period iii whole period 1 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 2 0.6894 0.0052 2.0763 0.0874 10.0515 1.7774 0.1153 0.0415 5 0.7595 0.0259 2.1237 0.0897 10.3609 1.7871 0.1797 0.0884 10 0.9007 0.1582 2.1237 0.0897 10.3609 1.7871 0.2186 0.1542 according to the results from variance decomposition analyses, provided in tables 6 and 9, three deductions can be made. first of all, the contribution of oil price shocks to the turkish stock market is greater in the third sub-period than that of the first and second. this is an expected result such that, since oil prices move in a considerably more volatile manner in the third sub-period they create a higher impact on the ise-100 returns. secondly, the impact on variance decomposition starts with the second day of the impulse and dies out immediately without changing the structure of the trend of ise-100. this may be the result of a non-linear relationship between oil prices and stock market returns, as proposed by prior researches (e.g. arouri and fouquau, 2009; jawadi et al, 2010). finally, the liquidity shock variable seems to be a considerable source of volatility for ise-100 returns international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.54-68 65 during the third sub-sample period, contributing more than 10%. this means that liquidity shocks, rather than crude oil prices, are the primary factor in stock market movements. 5. discussions and concluding remarks in this paper, we have investigated the impacts of crude oil price variations on the turkish stock market using structural vector autoregression (var) model for the period between january 2, 1990 and november 1, 2011. ise-100 index is used as a proxy for the performance of the turkish stock market. the interactions between oil prices and ise-100 have been analyzed by dividing this long time horizon into three sub-periods in order to test the response of turkish stock market during different oil price regimes. the empirical results suggest that the oil price changes significantly and rationally affect the turkish stock market activity during only the third sub-period, which begins after the credit-crunch of 2008. moreover, when the global financial liquidity conditions have been incorporated into the model, cboe’s market volatility index (vix), which is used as an indicator for global financial liquidity, has been found to significantly affect both oil prices and ise-100 returns. in this trivariate var analysis results also suggest that the most significant impacts of global liquidity shocks on stock market returns occur in the third sub-period. the overall results suggest that the global financial liquidity conditions are the most plausible explanation for the changes in turkish stock market returns. although there exists some evidence that purified oil price shocks still have an impact on stock market returns, this effect is smaller and less significant than the liquidity constraints. this is an expected result provided that turkish stock market, through widespread trade liberalization, has been attracting worldwide capital inflow, which makes it more vulnerable to shocks created in global financial markets. this study can be extended by obtaining a comparable firm-based dataset and by analyzing the behavior of each firm after oil price shocks. the empirical findings will prove to be extremely useful information to investors who need to understand the effect of oil price changes on certain stocks across industries, as well as for the managers of certain firms who require deeper insight into the effectiveness of hedging policies, which are affected by oil price changes. acknowledgements the authors would like to thank to prof. felix höffler, prof. oleg badunenko, prof. adnan kasman and the participants in the iaee’s 33 rd international conference for their helpful comments as well as to simon mumford for critically editing the manuscript. references al-mudhaf, a., goodwin, t.h. (1993), oil shocks and oil stocks: evidence from the 1970s. applied economics, 25(2), 181-190. aloui, c., jammazi, r. (2009). the effects of crude oil shocks on stock market shifts behaviour: a regime switching approach. energy economics, 31(5), 789-799. apergis, n., miller, s.m. (2009). do structural oil-market shocks affect stock prices?. energy economics, 31(4), 569-575. arouri, m.e.h., fouquau, j. (2009). on the short-term influence of oil price changes on stock markets in gcc countries: linear and nonlinear analysis. economics bulletin, 29(2), 795-804. arouri, m.e.h., nguyen, d.k. (2010). oil prices, stock markets and portfolio investment: evidence from sector analysis in europe over the last decade. energy policy, 38(8), 4528-4539. basher, s.a., sadorsky, p. (2006). oil price risk and emerging stock markets. global finance journal, 17 (2), 224–251. bernanke, b.s., gertler, m., watson, m. (1997). systematic monetary policy and the effects of oil price shocks. brookings papers on economic activity, 1, 91-157. bjørnland, h. (2009). oil price shocks and stock market booms in an oil exporting country. scottish journal of political economy, 56(2), 232-254 bollerslev, t. (1986). generalized autoregressive conditional heteroscedasticity. journal of econometrics, 31(3), 307-327. crude oil price shocks and stock returns: evidences from turkish stock market under global liquidity conditions 66 boyer, m.m., filion, d. (2009). common and fundamental factors in stock returns of canadian oil and gas companies. energy economics, 29(3), 428-453. brown, s.p.a., yucel m.k. (1999). oil prices and u.s. aggregate economic activity: a question of neutrality. economic and financial review, 2nd quarter, federal reserve bank of dallas, 1623. brown, s.p.a., yucel m.k. (2002). energy prices and aggregate economic activity: an interpretative survey. quarterly review of economics and finance, 42(2), 193-208. chen, s.s., chen h.c. (2007). oil prices and real exchange rates. energy economics, 29(3), 390-404. chiou, j.s., lee, y.h. (2009). jump dynamics and volatility: oil and the stock markets. energy, 34(6), 788-796. chortareas, g., noikokyris, e. (2014). oil shocks, stock market prices, and the us dividend yield decomposition. international review of economics & finance, 29, 639-649. ciner, c. (2001). energy shocks and financial markets: nonlinear linkages. studies in nonlinear dynamics and econometrics quarterly journal, 5(3), 203-212. cong, r.g., wei, y.m., jiao, j.l., fan, y. (2008). relationship between oil price shocks and stock market: an empirical analysis from china. energy policy, 36(9), 3544-3553. coudert, v., mignon, v., penot, a. (2008). oil price and dollar. energy studies review 15(2), 48-65 dickey, d., fuller, w. (1979). distribution of the estimators for autoregressive time series with a unit root. journal of the american statistical association, 74(366), 427-431. dickey, d., fuller, w. (1981). likelihood ratio statistics for autoregressive time series with a unit root. econometrica, 49(4), 1057-1071. dickman, a., holloway j. (2004). oil market developments and macroeconomic implications. bulletin, october 2004, reserve bank of australia. el-sharif, i., brown, d., burton, b., nixon, b., russell, a. (2005). evidence on the nature and extent of the relationship between oil prices and equity values in the uk. energy economics, 27(6), 819-830. faff, r.w., brailsford j.t. (1999). oil price risk and the australian stock market. journal of energy finance and development, 4(1), 69-87. fan, q., jahan-parvar, m.r. (2012). us industry-level returns and oil prices. international review of economics & finance, 22(1), 112-128. gao, w., madlener, r. (1999). oil price shocks and macroeconomic performance. his newsletter, 8, 1, 3. gjerde, ø., sættem , f. (1999). causal relations among stock returns and macroeconomic variables in a small, open economy. journal of international financial markets, institutions and money, 9(1), 61-74. guo, h., kliesen, k.l. (2005). oil price volatility and u.s. macroeconomic activity. review, federal reserve bank of st. louis, 84(6), 669-683. hamilton, j.d. (1983). oil and macroeconomy since world war ii. the journal of political economy, 91(2), 228-248. hamilton, j. d. (1996). this is what happened to the oil price-macroeconomy relationship. journal of monetary economics, 38 (2), 215-220. hamilton, j.d. (2003). what is an oil shock?. journal of econometrics, 113(2), 363-398. hamilton j.d., herrera a.m. (2004). oil shocks and aggregate macroeconomic behavior: the role of monetary policy. journal of money, credit and banking, 36(2), 265-286. hammoudeh s., aleisa e. (2004). dynamic relationships among gcc stock markets and nymex oil futures. contemporary economic policy, 22(2), 250-269. henriques, i., sadorsky, p., 2008. oil prices and the stock prices of alternative energy companies. energy economics, 30(3), 998-1010. huang, r.d., masulis, r.w., stoll, h.r. (1996). energy shocks and financial markets. journal of futures markets, 16(1), 1-27. huang, b., hwang, m.j., hsiao-ping, p. (2005). the asymmetry of the impact of oil price shocks on economic activities: an application of the multivariate threshold model. energy economics, 27(3), 455-476. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.54-68 67 huntington, h.g. (1998). crude oil prices and u.s. economic performance: where does the asymmetry reside? energy journal, 19(4), 107-132. jammazi, r., aloui, c. (2010). wavelet decomposition and regime shifts: assessing the effects of crude oil shocks on stock market returns. energy policy, 38(8), 4528-4539. jammazi, r. (2012a). oil shock transmission to stock market returns: wavelet-multivariate markov switching garch approach. energy, 37(1), 430-454. jammazi, r. (2012b). cross dynamic of oil-stock interactions: a redundant wavelet analysis. energy, 44 (1), 750-777. jawadi, f., arouri, m.e.h., bellalah, m. (2010). nonlinear linkages between oil and stock markets in developed and emerging countries. international journal of business 15(1), 19-31. jones, c.m., kaul, g. (1996). oil and the stock markets. the journal of finance, 51(2), 463-491. kahn, g.a., hampton, r. (1990). possible monetary policy responses to the iraqi oil shock. economic review, federal reserve bank of kansas city, 19-32. kilian, l. (2008). the economic effects of energy price shock. journal of economic literature, 46(4), 871-909. kilian l. (2009). not all oil price shocks are alike: disentangling demand and supply shocks in the crude oil market. the american economic review, 99(3), 1053-1069. kilian, l., park, c. (2009). the impact of oil price shocks on the u.s. stock market. international economic review, 50(4), 1267-1287. kwiatkowski, d., phillips, p.c.b., schmidt, p., shin, y. (1992). testing the null hypothesis of stationarity against the alternative of a unit root. journal of econometrics, 54(1-3), 159-178. lee, k., ni, s., ratti, r.a. (1995). oil shocks and the macroeconomy: the role of price variability. the energy journal, 16(4), 39-56. maghyereh, a. (2004). oil price shocks and emerging stock markets: a generalized var approach. international journal of applied econometrics and quantitative studies, 1(2), 27-40. mork, k.a. (1989). oil and the macroeconomy when prices go up and down: an extension of hamilton's results. the journal of political economy 97(3), 740-744. naifar, n., al dohaiman, m.s. (2013). nonlinear analysis among crude oil prices, stock markets' return and macroeconomic variables. international review of economics & finance, 27, 416431. nandha, m., faff, r. (2008). does oil move equity prices? a global view. energy economics, 30(3), 986-997. narayan, p.k., narayan, s. (2010). modelling the impact of oil prices on vietnam’s stock prices. applied energy, 87(1), 356-361. obernfender, u. (2009). energy prices, volatility, and the stock market: evidence from the eurozone. energy policy, 37(12), 5787-5795. oladosu, g. (2009). identifying the oil price-macroeconomy relationship: an empirical mode decomposition analysis of us data. energy policy, 37(12), 5417-5426. o'neill, t.j., penm, j., terrell, r.d. (2008). the role of higher oil prices: a case of major developed countries. research in finance, 24, 287-299. papapetrou e. (2001). oil price shocks, stock market, economic activity and employment in greece. energy economics, 23(5), 511-532. park, j., ratti, r.a. (2008). oil price shocks and stock markets in the u.s. and 13 european countries. energy economics, 30(5), 2587-2608. reboredo, j.c., rivera-castro, m.a. (2014). wavelet–based evidence of the impact of oil prices on stock returns. international review of economics & finance, 29, 145-176 rogoff, k. (2006). oil and the global economy. manuscript. harvard university. available at: http://www.nes.ru/publicpresentations/papers/oil%20and%20the%20global%20economy_rog off__v2.pdf sadorsky, p. (2001). risk factors in stock returns of canadian oil and gas companies. energy economics, 23(1), 17-28. sill, k. (2007). the macroeconomics of oil shocks. federal reserve bank of philadelphia business review, q1, 21-31. sims, c.a. (1980). macroeconomics and reality. econometrica, 48(1), 1-48. http://www.sciencedirect.com/science?_ob=articleurl&_udi=b6v84-4d5ky1s-1&_user=4366190&_coverdate=11%2f30%2f2004&_rdoc=1&_fmt=high&_orig=search&_sort=d&_docanchor=&view=c&_searchstrid=1240497409&_rerunorigin=google&_acct=c000063020&_version=1&_urlversion=0&_userid=4366190&md5=ebe181a6aa9625add0fc52c50245af44#bbib8#bbib8 crude oil price shocks and stock returns: evidences from turkish stock market under global liquidity conditions 68 soytaş, u., oran, a. (2011). volatility spillover from world oil spot markets to aggregate and electricity stock index returns in turkey. applied energy, 88(1), 354-360. zarour, b.a. (2006). wild oil prices, but brave stock markets! the case of gcc stock markets. operational research: an international journal, 6(2), 145-162. crude oil price shocks and stock returns: evidences from turkish stock market under global liquidity conditions tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 5 • 2020158 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(5), 158-163. 1. introduction taking into account, that demand for petroleum products in asianpacific region, will probably exceed worldwide demand on 25%, and, according to predictions, demand for natural gas by 2025 will exceed it almost on 50%, asian energy importers market is promising for russia. most of all, this is reflected in the expansion of energy cooperation between russia and china. the danger of china’s dependence as one of the world’s largest energy consumers on imports of russian energy carriers (57% of the total world energy consumption) is that beijing, preferring to export raw materials, will seek to exploit the far east as a “resource appendage” and avoid significant trade and financial obligations. this problem is repeatedly exacerbated by the uneven economic development of both countries. analyzing the development program of the border regions of russia and china, some authors have identified a discrepancy between the economic strategy of russia and china in the field of economics, but have not proposed ways to equalize this discrepancy. many researchers are supporters of the neorealist paradigm in international relations, but the ways to improve energy security in north-east asia are insufficiently studied by them. foreign experts, as a rule, do not consider the interests of russia’s national and regional security, citing the current weakness of the russian economy and the heterogeneity of russian-chinese cooperation. the purpose of this study is to analyze the problems of russianchinese energy cooperation in the context of the development of the russian far east and the possibilities of increasing its efficiency through new forms of energy cooperation between the two countries in the far east. 2. literature review russia’s energy security strategy is committed to maintaining state control over oil and gas developments, concluding longthis journal is licensed under a creative commons attribution 4.0 international license strategic energy partnership between russia and china pavel baboshkin* financial university under the government of the russian federation, moscow, russia. *email: pbaboshkin@yandex.ru received: 26 november 2019 accepted: 13 may 2020 doi: https://doi.org/10.32479/ijeep.9032 abstract during recent years the role of energetic security in russia steadily increases. after deterioration russian relations with west countries in energy sector stay single stable economic tool, which russia use for the maintenance of impact in surrounding region. instability of the importers market which is priority for the country, bounded with excitements about use by russia theirs position on the energetic, markets for reaching political goal through the development of projects such as nord stream 2 and turkish stream. in its turn in latest decade, russia aspires to ensure solid positions in siberia and far east. american companies refuse to participate in the execution of orders for russia due to the unstable political situation and stricter restrictive and regulatory measures, which makes the level of risk of cooperation unacceptable. using alternative sources of electricity, russia and china can extract many positive effects: financial income, employment, energy security for the domestic market, etc. for example, in the far east, the import of fuel can be reduced by 40% after the implementation of rao ues plans to build 178 renewable energy sources with a total capacity of 146 mw. keywords: strategic partnership, economic development, energy cooperation, asian-pacific region, energy security jel classifications: c30, d12, q41, q48 https://doi.org/10.32479/ijeep.9032 baboshkin: strategic energy partnership between russia and china international journal of energy economics and policy | vol 10 • issue 5 • 2020 159 term contracts for joint development of natural resources with foreign companies, and directly regulating foreign access to them (nyangarika et al., 2019b; nyangarika et al., 2019a). management practices are dominated mainly by the centralization of decision-making and the support of large industrial and financial groups such as gazprom, rosneft or transneft, as a result of which technologies and infrastructure for the energy market are developed within a limited group of linear-functional corporations (denisova, 2019; denisova et al., 2019). for example, in the oil sector, russia has signed contracts for joint development of fields with such large foreign companies as exxon mobil; вр; total; royal dutch shell; sodeco; mitsubishi, mitsui etc. in the field of liquefied natural gas (lng), the total reserve of which in russia is about 165 trillion cubic meters. moscow pays special attention to the gas pipeline “nord stream-2,” which will connect russia and germany via the baltic sea by the end of 2019 (mikhaylov et al., 2018; nyangarika et al., 2018). finland, sweden and denmark are among the interested participants in this project, and the total annual volume should reach about 55 billion cubic meters. another russian project, the turkish stream lng project, will link russia and turkey via the black sea by 2019 (moiseev, 2017c; moiseev and akhmadeev, 2017). as european states show their willingness to act as independent geopolitical players in the global energy market, the demand for russian energy resources will increase in the future (mikhaylov, 2018a; mikhaylov, 2018b). the actions of russian state monopolies are responding to this forecast: in 2018, gazprom placed 750 million euros in 8-year bonds in europe to raise up to $ 5.5 billion for the construction of the nord stream-2, turkish stream and lng terminal network (an et al, 2019b; moiseev, 2017a; moiseev, 2017b). russian energy minister alexander novak said that moscow will provide supplies under existing contracts to european consumers with partial use of lng after 2019. however, due to the external geopolitical and diplomatic crisis between russia and the west, the future of russian-european energy projects is uncertain (morgan and yang, 2001; gura et al., 2020). since 2011 moscow has been pursuing a targeted policy of diversifying european energy cooperation by seeking alternative investors in asia (lopatin, 2019a; lopatin, 2019b). according to the energy strategy of russia-2035, moscow is expanding energy supplies beyond the european market in northeast asia and the russian far east (mikhaylov, 2019a; mikhaylov et al., 2019). gazprom and rosneft are the only companies entitled to conclude agreements in this industry with the amur region of russia, primorsky and khabarovsk territories (morris and barlaz, 2011; an et al., 2020a; an et al., 2020b). for example, rosneft has built an oil refinery in komsomolskon-amur for the oil, gas, automotive and other petrochemical industries (meynkhard, 2019; wustenhagen and bilharz, 2006). at the same time, there is no independent oil market in russia, so at the moment it is almost impossible to build a completely independent oil refinery (moiseev and sorokin, 2018; an et al., 2019a; an et al., 2019c). 3. methods thus, the channels for improving welfare at the expense of the state budget and the growth of domestic investment in the region are narrowing. with oil prices falling, the energy sector has also had to face an urgent need to improve efficiency and at the same time find sources of larger-scale financing. thus, russian, japanese and american companies invested in sakhalin i and ii projects in order to exploit oil and gas fields located on the northeastern coast of sakhalin island. as a result, the sakhalin – khabarovsk – vladivostok gas pipeline was built, gas exports through which began in 2009, when gazprom began selling lng to japan and korea under the sakhalin-ii project». this helped gazprom initially to enter the markets in the far east, and subsequently, relying on the sakhalin-3 lng project, together with china’s sinopec, to expand supplies to domestic and foreign consumers (zubakin et al., 2015; tryndina et al., 2020; yumashev and mikhaylov, 2020). after the introduction of western sanctions, the us energy agenda in the far east has significantly narrowed, leaving only a limited share of us investment in sakhalin projects. currently, american companies refuse to participate in the execution of orders for russia due to the unstable political situation and stricter restrictive and regulatory measures, which makes the level of risk of cooperation unacceptable. south korea provides more than 10% of its energy needs domestically, mainly through nuclear and renewable energy. the national oil company of korea (knoc) and the korean gas company (kogas) are the two largest state-owned companies in the rok that buy the rights to produce and deliver oil and gas worldwide. japan followed the same path until 2011, but the fukushima reactor accident halted the development of japanese nuclear power. at the same time, japan is heavily dependent on imports of oil, gas and coal and relies on large state-owned companies such as sodeco, mitsubishi, mitsui, etc., which are also involved in sakhalin lng projects with russia. sakhalin projects are the only ones in the far east focused on the japanese market and receiving significant investments from japanese companies. however, in terms of total investment, both south korean and japanese companies lag behind chinese ones. they receive less government subsidies and focus on making financial profits rather than losses, which is not the case for chinese companies, which are mainly focused on maximizing the exploitation of natural resources, despite short and medium-term financial losses. for several years, leading chinese state-owned companies baboshkin: strategic energy partnership between russia and china international journal of energy economics and policy | vol 10 • issue 5 • 2020160 (cnpc, sinopec and cnooc) have made major financial investments and signed long-term contracts in all regions of the world (about 200 projects in fifty countries) aimed at importing oil and gas through borrowing funds from chinese state-owned banks. over the past few years china has concluded major agreements on contracts with russia on oil and gas, using the allocation of significant financial loans to ensure long-term supplies of russian energy resources (meynkhard, 2020). for russia strategic cooperation with china is one of the main factors for ensuring the success of the strategy in energy security in nea. in 2009, russia and china signed a cooperation program between the russian far east, eastern siberia and the north-east of china until 2018. the main directions of this program are: • expansion of russian exports of non-ferrous metals; • expansion of border transit; • development of transport communications; • construction of a border trade center and attraction of russian tourists to china; • export of chinese labor to russia. 4. results the result was the construction of the skovorodino–mohe–daqing oil pipeline, part of the russian espo pipeline, which was completed at the end of 2017 with a capacity of 30 million tons. an important package of bilateral agreements in the field of energy was signed in 2014-2015. the framework agreement set a timetable for the preparation of gas purchases and terms of sale, technical issues, as well as an intergovernmental agreement on the western route. in addition, russia and china signed a memorandum of understanding on cooperation in the oil and gas sector. after sanctions were imposed on russia in 2014, the coincidence of political decisions and economic initiatives of russia and china on the development of regional projects played a role. in particular, this applies to the construction of the primorsky energy complex, vladivostok and razdolnaya hpp, as well as the channel of river ports of the khabarovsk– vladivostok commercial ports for the delivery of electricity to china. another project of energy cooperation between russian and chinese companies is a gas thermal power plant in the north-western part of ussuriysk (primorsky krai), which is planned to be built by 2019 by the russian “rao es” and the chinese energy union heilongjiang. some experts believe the investment forecasts are overstated, and the planned result is premature. thus, in 2016, the negative dynamics of investment inflow to the far east amounted to 82.8% compared to the previous year. in 2015, the volume of production was only 20%, and 80% was exported abroad in the form of raw materials. the increase in investment in gas contracts in 2014 was hampered by the discrepancy between the regional development programs of russia and china. russia accounts for just over 10% of china’s energy imports, while china accounts for only about 15% of russia’s oil exports and even less natural gas exports (figures 1 and 2). as a result of the deal between gazprom and cnpc, only about 1,600 kilometers of lng pipelines (power of siberia and altai) were built by 2018. another promising project on the eastern gas pipeline – chayandinskoye field (yakutia), where according to the forecast by 2019 it is planned to produce 38 billion m3/year, is also far from implementation. about half of the far eastern energy enterprises are physically and technologically obsolete, and a significant part of the investment projects is aimed at restoring the technical base and supporting the current production volumes. meanwhile, in 2015-2016, china acquired a 9.9% stake in russia’s major energy holding sibur, and a 9.9% stake in yamal lng (northeast of the yamal peninsula). this suggests that for china, russian lng is an important element of energy security, but its price remains a critical factor. china is struggling to cope with the environmental impacts of its economic growth and is seriously considering switching from coal to clean lng projects. it is obvious that china needs a long-term partnership with russia as one of the largest energy producers. figure 1: natural gas price source: author calculation baboshkin: strategic energy partnership between russia and china international journal of energy economics and policy | vol 10 • issue 5 • 2020 161 dale copeland’s theory of interdependence and war explains that, with future expectations of trade relative to each other, and guaranteed access to the country’s resources, the states involved in such trade will seek to maintain good relations. russia provides china with guaranteed access to energy resources, but does not yet guarantee their timely delivery, since the modernization of the energy sector in siberia and the far east is far behind plans. this may prevent china from further investing in the far east, while existing projects implemented with the help of chinese investments will be aimed only at the extraction and transportation of natural resources to china. in addition, as a result of the regional economic downturn in 2010, china faced painful closures of obsolete and unprofitable state-owned enterprises in the northeast. for russia, this means that it can rely only on its own resources, and china’s border areas are unlikely to become a catalyst for economic growth in the far east. in the current situation, russia needs to guarantee long-term investments in lng projects establishing state regulation of electricity tariffs and accumulate strategic oil and gas reserves to ensure regional energy security. an alternative to accelerating the implementation of this process is to attract foreign companies not only as consumers of gas, but also as direct investors, if we consider gazprom, lukoil or rosneft as partners. small enterprises in china (china drilling corporation, etc.) are interested in developing energy infrastructure in russia, as well as in expanding borders to create a competitive environment with state monopolies. the result should be the development of local production, simplification of the process of state regulation and long-term financing of energy projects. 4. discussion in addition, according to a report by the lawrence berkeley national laboratory, asian countries depend on imports of oil from the middle east and natural gas from australia and oceania and are therefore vulnerable to political escalation. as these countries, including china, are either on the verge of a technological breakthrough or are fast-growing markets, they are gradually moving towards renewable energy, slowly but surely reducing their dependence on fossil fuel imports. taking into account that beijing is looking for new technologies and high-quality extraction of energy resources, the russian-chinese development of alternative energy sources can develop in several directions (mikhaylov and tarakanov, 2020; mikhaylov, 2020). first, russia has extensive experience in the production of power equipment and retains technological advantages in the equipment of nuclear power plants. in 2017, 10 russian nuclear power plants produced 19% of the country’s total energy. since 2010, russia and china have been cooperating in the field of nuclear energy, for example, in the development of water-water power reactors (vver), exploration of uranium deposits, decommissioning of old plants, secondary processing technologies, etc. in 2017, the vice-president for south asia projects of the management company jsc “engineering company “ase” (part of rosatom) a. lebedev proposed to build a new nuclear power plant in china, which will consist of six power units. figure 2: natural gas export from russia source: author calculation baboshkin: strategic energy partnership between russia and china international journal of energy economics and policy | vol 10 • issue 5 • 2020162 chinese oil companies are interested in the production of floating nuclear power plants, including with the participation of rosatom. for example, the world’s first floating nuclear thermal power plant (apec), akademik lomonosov will arrive in chukotka in june 2019, replacing the capacity of the bilibino nuclear power plant, which currently generates 80% of chaunbilibino’s electricity and will become the world’s northernmost nuclear power plant. floating nuclear power plants can further become the main objects of life support in the northern regions of the russian far east and attract chinese investment here. secondly, advanced technologies of renewable energy sources (solar and wind energy), the development of which is already actively underway in china, will be of great importance for russia and china in the foreseeable future. the fact is that if china refuses to switch to energy-saving production or alternative sources of renewable energy, over time it will inevitably face serious environmental problems and high energy prices on world market (mikhaylov et al., 2020). the growing scale of emissions produced by coal-fired power plants, the dumping of industrial waste have always been a serious problem in china, and recently have become an acute problem for the ecology of the far east: the promising gas pipelines “power of siberia” and “altai” will increase the industrial load and have a significant impact on the environment. the difficulty with renewables is that it takes a lot of space to create an industrially significant amount of energy from the sun and wind. in megacities, such as beijing or shanghai, it is practically absent, which makes the vast territories of the russian far east attractive for projects in the field of alternative energy development. the sunniest region is primorsky krai, where the level of solar radiation, according to nasa, is about 4.5 kw/h/1 m2/day (dayong et al., 2020; dooyum et al., 2020). in 2012-2015, rao ues mastered eight solar stations and three wind turbines, which allowed reducing the company’s fuel costs and subsidizing regional budgets for local energy. the solar power plant in the republic of sakha (yakutia) has become the most powerful in the world beyond the arctic circle (capacity 1 mw), while the project involves increasing its load to 4 mw with a maximum winter of 5 mw. as for wind energy, in the coastal regions of the far east, the average annual wind speed is 6-7 meters per second, while in denmark (the world leader in the use of wind energy a little more than 5 m/s). the most promising areas for the installation of wind farms in the far east are coastal areas in the kamchatka territory, the sakhalin region, chukotka and yakutia. in addition, kamchatka has geothermal capacity for electricity production, developed jointly with rushydro and estimated at 5000 mw. 6. conclusion using alternative sources of electricity, russia and china can extract many positive effects: financial income, employment, energy security for the domestic market, etc. for example, in the far east, the import of fuel can be reduced by 40% after the implementation of rao “ues” plans to build 178 renewable energy sources with a total capacity of 146 mw. china, which suffers heavily from air pollution caused by fossil fuels, will be able to improve its environmental performance and reduce fossil fuel consumption if it gains access to renewable sources in russia. at the same time, china is vulnerable to trade because of its dependence on other countries to stimulate its economic growth. this can be used by russia to attract china to the above projects through other investment incentives: tax cuts for corporations, grants to private companies and general deregulation in the far east market. it is necessary to master forms of cross-border cooperation and interaction with regional business, which, in particular, are developing and accumulating the necessary potential in the maritime territory. this supports in the far east a more global task of development of the russian eastern territories, population growth, economic recovery and overcoming its imbalance. thus, for china, which is subject to a trade war with the usa, energetic partnership with russia is the most important resource for investments in underdeveloped far eastern region. moscow is interested in creating intergovernmental organizations for energy cooperation throughout northeast asia, as evidenced by the successful multinational cooperation between states, including china, japan, korean republic, etc., which not only reduces the economic burden of these projects, but also deters china from playing with the “zero sum” regarding the unilateral exploitation of energy projects in the far east. moscow must actively seek various levers in its increasingly unequal relationship with beijing to protect its national interests, and one of these levers could be the development of alternative energy to meet china’s energy needs. references an, j., mikhaylov, a., jung, s.u. (2020a), the strategy of south korea in the global oil market. energies, 13(10), 2491. an, j., mikhaylov, a., kim, k. (2020b), machine learning approach in heterogeneous group of algorithms for transport safety-critical system. applied sciences, 10(8), 2670. an, j., mikhaylov, a., lopatin, e., moiseev, n., richter, u.h., varyash, i., dooyum, y.d., oganov, a., bertelsen, r.g. (2019b), bioenergy potential of russia: method of evaluating costs. international journal of energy economics and policy, 9(5), 244-251. an, j., mikhaylov, a., moiseev, n. (2019c), oil price predictors: machine learning approach. international journal of energy economics and policy, 9(5), 1-6. an, j., mikhaylov, a., sokolinskaya, n. (2019a), oil incomes spending in sovereign fund of norway (gpfg). investment management and financial innovations, 16(3), 10-17. dayong, n., mikhaylov, a., bratanovsky, s., shaikh, z.a., stepanova, d. (2020), mathematical modeling of the technological processes of catering products production. journal of food process engineering, 43(2), e13340. denisova, v. (2019), energy efficiency as a way to ecological safety: evidence from russia. international journal of energy economics and policy, 9(5), 32-37. denisova, v., mikhaylov, а., lopatin, e. (2019), blockchain infrastructure and growth of global power consumption. international journal of energy economics and policy, 9(4), 22-29. baboshkin: strategic energy partnership between russia and china international journal of energy economics and policy | vol 10 • issue 5 • 2020 163 dooyum, u.d., mikhaylov, a., varyash, i. (2020), energy security concept in russia and south korea. international journal of energy economics and policy, 10(4), 102-107. gura, d., mikhaylov, a., glushkov, s., zaikov, m., shaikh, z.a. (2020), model for estimating power dissipation along the interconnect length in single on-chip topology. evolutionary intelligence. doi: 10.1007/ s12065-020-00407-7, s12065. lopatin, e. (2019a), methodological approaches to research resource saving industrial enterprises. international journal of energy economics and policy, 9(4), 181-187. lopatin, e. (2019b), assessment of russian banking system performance and sustainability. banks and bank systems, 14(3), 202-211. meynkhard, a. (2019), energy efficient development model for regions of the russian federation: evidence of crypto mining. international journal of energy economics and policy, 9(4), 16-21. meynkhard, a. (2020), priorities of russian energy policy in russianchinese relations. international journal of energy economics and policy, 10(1), 65-71. mikhaylov, a. (2018a), pricing in oil market and using probit model for analysis of stock market effects. international journal of energy economics and policy, 8(2), 69-73. mikhaylov, a. (2018b), volatility spillover effect between stock and exchange rate in oil exporting countries. international journal of energy economics and policy, 8(3), 321-326. mikhaylov, a. (2019), oil and gas budget revenues in russia after crisis in 2015. international journal of energy economics and policy, 9(2), 375-380. mikhaylov, a. (2020), geothermal energy development in iceland. international journal of energy economics and policy, 10(4), 31-35. mikhaylov, a., moiseev, n., aleshin, k., burkhardt, t. (2020), global climate change and greenhouse effect. entrepreneurship and sustainability issues, 7(4), 2897-2913. mikhaylov, a., sokolinskaya, n., lopatin, e. (2019), asset allocation in equity, fixed-income and cryptocurrency on the base of individual risk sentiment. investment management and financial innovations, 16(2), 171-181. mikhaylov, a., tarakanov, s. (2020), development of levenbergmarquardt theoretical approach for electric network. journal of physics, conference series, 1515, 052006. mikhaylov, а., sokolinskaya, n., nyangarika, а. (2018), optimal carry trade strategy based on currencies of energy and developed economies. journal of reviews on global economics, 7, 582-592. moiseev, n. (2017a), forecasting time series of economic processes by model averaging across data frames of various lengths. journal of statistical computation and simulation, 87(17), 3111-3131. moiseev, n. (2017b), p-value adjustment to control type i errors in linear regression models. journal of statistical computation and simulation, 87(9), 1701-1711. moiseev, n. (2017c), linear model averaging by minimizing meansquared forecast error unbiased estimator. model assisted statistics and applications, 11(4), 325-338. moiseev, n., akhmadeev, b. (2017), agent-based simulation of wealth, capital and asset distribution on stock markets. journal of interdisciplinary economics, 29(2), 176-196. moiseev, n., sorokin, a. (2018), interval forecast for model averaging methods. model assisted statistics and applications, 18(2), 125-138. morgan, s.m., yang, q. (2001), use of landfill gas for electricity generation. practice periodical of hazardous, toxic, and radio waste management, 5(1), 14-24. morris, j.w., barlaz, m.a. (2011), a performance-based system for the long-term management of municipal waste landfills. waste management, 31(4), 649-662. nyangarika, a., mikhaylov, a., richter, u. (2019a), influence oil price towards economic indicators in russia. international journal of energy economics and policy, 9(1), 123-130. nyangarika, a., mikhaylov, a., richter, u. (2019b), oil price factors: forecasting on the base of modified auto-regressive integrated moving average model. international journal of energy economics and policy, 9(1), 149-160. nyangarika, a., mikhaylov, a., tang, b.j. (2018), correlation of oil prices and gross domestic product in oil producing countries. international journal of energy economics and policy, 8(5), 42-48. tryndina, n., moiseev, n., lopatin, e., prosekov, s., kejun, j. (2020), trends in corporate energy strategy of russian companies. international journal of energy economics and policy, 10(1), 202-207. wustenhagen, r., bilharz, m. (2006), green energy market development in germany: effective public policy and emerging customer demand. energy policy, 34, 1681-1696. yumashev, а., mikhaylov, а. (2020), development of polymer film coatings with high adhesion to steel alloys and high wear resistance. polymer composites, 25583. doi: 10.1002/pc.25583. zubakin, v.a., kosorukov, o.a., moiseev, n.a. (2015), improvement of regression forecasting models. modern applied science, 9(6), 344-353. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020 235 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 235-241. the impact of healthcare expenditure and healthcare sector growth on co2 emission using dynamic panel data system gmm estimation model during covid 19 crisis irza hanie abu samah1, intan maizura abd rashid2*, wan ahmad fauzi wan husain3, suraiya ibrahim3, hariri hamzah4, mohammad harith amlus3 1school of human resource development and psychology, faculty of social sciences and humanities, univerisiti teknologi malaysia, malaysia, 2faculty of business and management, universiti teknologi mara, alor gajah, melaka, malaysia, 3school of business innovation and technopreneurship, universiti malaysia perlis, malaysia, 4school of electronic, universiti kuala lumpur (unikl), malaysia. *email: intanmaizuraar@gmail.com received: 10 april 2020 accepted: 24 august 2020 doi: https://doi.org/10.32479/ijeep.9769 abstract as huge consumers of water and energy, healthcare sector have a significant environmental impact. the healthcare sector is accountable for answering countless the most dangerous effects of climate change and pollution, deadly environmental emissions and other greenhouse gases itself. this study aims to observe empirically the effect of healthcare expenditure and heath sectors growth on co2 during covid 19 outbreak in malaysia. as the world has awakened to the potential risks of covid 19, there has been a massive effort to add capacity to the healthcare system rapidly. in malaysia, apart from stressing the need for the public to strictly adhere to the movement control order (mco), the government an immediate boost in funding for healthcare services through initial stage fiscal policy response to covid 19 outbreak. this research used dynamic panel data model also known as longitudinal study. this study explained dynamic panel data system gmm estimation model is fitting to interpret the outcome, indicate healthcare expenditure and healthcare growth on covid-19, inflation rate and unemployment rate have significant relationship with co2 emission. empirical findings suggest that co2 emissions policies reforms are required to channelize healthcare sector growth to a more government spending resulting from fiscal policy designed by the government of malaysia. the regulators of other countries should pull out co2 emissions policies to achieve sustainable economic growth and health sector growth development. the results provide important information to allow comparisons of the health-care sector with other economic sectors in malaysia and the global healthcare sector in terms of co2 emission. in particular, the results are intended to contribute to the understanding of the co2 emission of national healthcare systems so that policymakers, especially in low-income and middle-income countries, can develop relevant co2 emissions mitigation policies. keywords: covid-19, fiscal policy, healthcare expenditure, healthcare sector growth, co2 emission, dynamic panel model, malaysia jel classifications: e31, q41, q57 1. introduction in developed countries, healthcare sector have been estimated to contribute around 3% to 8% of national greenhouse gas emissions, 8% in the usa and 3% in the united kingdoms, although more robust analyses including other countries need to be undertaken. nowadays, the government’s immediate priority was to reduce the covid 19 epidemic from continue to spread. malaysia declared an amount of rm53 billion coronavirus stimulus package to help movement control order (mco) associated businesses and citizens survive the crisis. the health ministry of malaysia will receive a distribution amounting to rm500 million and the government will allocate additional rm1 billion to obtaining hire medical experts and equipment to combat covid 19. many this journal is licensed under a creative commons attribution 4.0 international license samah, et al.: the impact of healthcare expenditure and healthcare sector growth on co2 emission using dynamic panel data system gmm estimation model during covid 19 crisis international journal of energy economics and policy | vol 10 • issue 6 • 2020236 medical specialists notify of a serious shortage of health capitals and shortage of funding for healthcare services resulting from the increasing cases of covid 19 and can could put lives at highest risk in malaysia. recognizing front liner healthcare sacrifices, the government will allocate the special stipend ranging from rm400 to rm600 monthly till the epidemic ends. in addition, the government also decides to extend a special stipend of rm200 monthly to police, military, civil defence customs and rela members that are directly involved in imposing the mco. total of 169,000 numbers of front liners are estimated to advantage from this allowances. furthermore, the insurance sector will create a special allocations to cover the costs acquired for screening test of up to rm300 per person and takaful medical certificate to undertake the test at private hospitals and laboratories as initiated by ministry of health (moh) amounting of rm8 million. lastly, insurance and takaful companies will provide a 3 month deferment on premiums by contributors that affected by the pandemic. meanwhile in wuhan, china, the shortage of protective medical supplies and lack of knowledge about covid-19 were the main factors causing the large number of healthcare workers to contract the virus in the early stages of the outbreak in wuhan, china. however, 31 medical teams involving of more than 42,000 nurses and doctors were sent to wuhan to fight the outbreak. healthcare benefits cost growth increasing during covid-19 because of shortage of medical supply. thus, a lot of government spending on healthcare expenditure was acquired to put in stimulus package focused on healthcare industry. this has appropriately focused spending on providing acute-care capacity, ventilators, and stocks of other critical medical materials, such as personal protective equipment. theory from keynesian and endogenous growth theories have pointed out that fiscal policy plays a vital role in raising speed of economic development. most of the previous literature on the relationship between economic sector growth and government spending has determined that government spending can influence sector growth positively through various ways. figure 1 shows that the government spending can increase healthcare sector growth by providing public goods that are reflecting major component of aggregate demand. moreover, many of literatures relating on this issue and the relationship between government spending and economic growth is still not clear. baffes and shah (2013) was first try to determine the relationship between different types of government spending and military sector growth. the findings shows that the elasticity with veneration to human resource capital and infrastructure are highest and lowest respectively. the research concludes that high sector growth in the world economy can be achieved through investing more in human resource development and less in military and other non-development activities. knack and keefer (1995) and keefer and knack (1997) views that government spending on a strong enforcement of contracts, legal system for the protection of rights and dispute settlements are helpful in raising sector growth. according to asghar et al. (2011), the resources allocated to health sectors and education increasing the healthcare sector growth and government should introduce policies for encouraging private sector to invest more in health and education. 1.1. co2 emission and healthcare sector in malaysia figures 2 and 3 demonstrate that the total amount of carbon dioxide (co2) emission emitted by industries in malaysia within the year 2006 to 2019. it appears that co2 emission throughout the observation period is very volatile. it had seemed that the 1st 4 years indicated a dramatic dip in the emitted amount of co2 by which from 2005 to 2007 the amount plummeted from 125,374 .730kt to as low as i 07,934.478kt a drop for 13.9%. however, from 2008 onward the graph showed a gradual increment, yet with few slip backs but only slightly. from the year 2006-2019, the graph show that co2 emission soared by 27% that is an increment of 28,782 .283kt followed by a slight drop of merely on 2002. it is assumed that economic growth contributes to industrial development by which industrial development plays a vital role regulating in the emission of co2. it may have a direct or an indirect effect to the environmental degradation both positive and negative. poveda and martinez (2013) stated that the development trends and co2 emission in three of the countries they explored differs. colombia: a developing country, germany and sweden: both developed countries showed that an increase in economic indicator does not promise an increase to co2 emission. hospitals consume energy to provide power medical equipment, lighting, supply heating heat water and air conditioning. they also produce waste from both waste water and single-use disposable supplies. hospitals consume more energy than other nonresidential buildings per square meter of floor space, in part because of their continuous operation. this study can be supported by adom et al. (2012), long run vector error correction causality test were performed to identify the direction the variable runs amongst each other. from this study, the result of and pollution in malaysia depending on the variables, each has its own effects on the others. the result showed that the causality direction is running from healthcare sector and co2 emission to government expenditure. this study proves that government expenditure is significantly affected by co2 emission and sectors, all in contributions to pollution. this study clearly stated that the variance decomposition analysis results revealed that economic growth contributes largely to changes in future carbon emission in senegal and morrocco. the result from the empirical studies showed that we had achieved the purpose of this study where most of the result indicated that economic growth indeed had positive effects on pollution. however, co2 emission is not the only means of pollution healthcare sector output, on the other hand would come from healthcare sectors. in a contradictable study to the one mentioned above, chemiwchan (2012) said that since 30 years ago, key industrial pollutants in the developed world have reduced their emission levels, however the emission level in developing countries are increasing. the study also stated that there are substantial variation of industrial pollutants in emission intensities considering the time frame and countries explored. zhang et al. (2013) suppo11ed by finding out that large proportions of water waste pollution comes from export embodied industrial emission. this study uses three distinguished variables upon relating it with the researcher’s topic of interest. such variables and its trend in malaysia will then be explained further. in additions, dialysis consumes 120-800 l of fresh water per treatment, depending on the type (clinic vs. home) and duration of the therapy session. samah, et al.: the impact of healthcare expenditure and healthcare sector growth on co2 emission using dynamic panel data system gmm estimation model during covid 19 crisis international journal of energy economics and policy | vol 10 • issue 6 • 2020 237 much of that water is discarded in the reverse osmosis process that creates the dialysis fluid, and it is known as reject water. it is essentially bacteria free, with ph, turbidity, and electrolyte characteristics not unlike those of municipal and industrial water supplies. recycling of reject water for gray water uses for example, irrigating lawns or flushing toilets—has been advocated and has been tried in some settings. recycling reject water is estimated to be less costly than generating fresh water through reverse osmosis of sea water. finally, indirect energy and environmental impacts are associated with their purchasing activities. 2. literature review healthcare benefits cost growth increasing during covid 19 because of shortage of medical supply. thus, a lot of government spending was acquired to put in stimulus package focused on healthcare industry. this has appropriately focused spending on providing acute care capacity, ventilators, and stocks of other critical medical materials, such as personal protective equipment. theory from keynesian and endogenous growth theories have pointed out that fiscal policy plays a vital role in raising speed of economic development. most of the previous literature on the relationship between economic sector growth and government spending has determined that government spending can influence sector growth positively through various ways. figure 3 shows that the government spending can increase healthcare sector growth by providing public goods that are reflecting major component of aggregate demand based on aon’s 2020 global medical trend rates report. moreover, many of literatures relating on this issue and the relationship between government spending and economic growth is still not clear. baffes and shah (2013) was first try to determine the relationship between different types of government spending and military sector growth. the findings show that the elasticity with veneration to human resource capital and infrastructure are highest and lowest respectively. the research concludes that high sector growth in the world economy can be achieved through investing more in human resource development and less in military and other non-development activities. knack and keefer (1995) and keefer and knack (1997) views that government spending on a strong enforcement of contracts, legal system for the protection of rights and dispute settlements are helpful in raising sector growth. according to asghar et al. (2011), the resources allocated to healthcare sectors and education increasing the healthcare sector growth and government should introduce policies for encouraging private sector to invest more in health and education. regarding to the variables, it is assumed that economic growth affects the emission of co2. hence, the researches were done as to relate economic growth and co2 emission. adom et al. (2012) conducted a research in ghana, figure 2: malaysia co2 emission source: trading economics (2020) figure 1: health care benefit cost growth in 2020 source: aon’s 2020 global medical trend rates report samah, et al.: the impact of healthcare expenditure and healthcare sector growth on co2 emission using dynamic panel data system gmm estimation model during covid 19 crisis international journal of energy economics and policy | vol 10 • issue 6 • 2020238 senegal and morocco using three related methods of bounds co-integration approach, toda and yamamoto granger causality test followed by variance decomposition analysis. the idea was to probe into the short run causal relationship and long term equilibrium relationships between co2 emissions, technical efficiency. industrial structure and economic growth of the three mentioned african countries. the result indicated the existence of multiple long run relationships for ghana and senegal yet a one way long term equilibrium relationship for morocco. the final result of their study showed that economic growth plays a large role of contributing to changes in future carbon dioxide emissions in senegal and morocco whereas in ghana it is technical efficiency. in the meanwhile, employing the co-integration analysis, piaggio and padilla (2012) conducted a paper that studies the relationship between co2 emissions and economic activity of 31 countries: 28 oecd and the remaining are china, brazil and india from 1950 to 2006. each country’s long run relationships were estimated by which functional equality, certain parameters, as well as the turning points whenever appropriate are rejected. the result confirms the need to consider differences among countries in the relationship between air pollution and economic activity in order to avoid void estimations and conclusions. in 2013. burnett et al. (2013) used vector error correction model as their empirical specification to analyses the potential misspecification of energy consumption as a controlled variable as well as analyzing the relationship of the carbon kuznets curve. the study they had done suggested that emission intensities are what affected by economic growth instead of absolute emission as often claimed by past studies. based on a past research by anderson and karpcstam (2013). by which their paper analyses the determinants of energy and carbon intensity as ell as scale effects for ten economies; 8 developed economics and two emerging economies from 1973 to 2007. in this paper, it is evident that emission over the long terms arc affected by climate policy on capital accumulation rather than in short terms. there are differences between short terms and long term s results as such. the growth on productivity reduces only energy intensity whereas real oil price reduces both energy and carbon intensities. despite revealing that carbon tax itself in inadequate to dissociate emission from economic growth, it is somewhat deemed as a vital policy tool to reduce emissions with regards to the real oil price effect. anderson and karpcstam (2013) whom conducted a research on 11 distinguished countries namely austria, united states, belgium, sweden, canada, republic of korea, chile, japan, denmark. ireland and france on the basis of a graphical hypothesis kuznets curve, proved that the effect of economic growth on co2 is positive. the results showed the effect of economic growth on co2 is negative before it reaches the threshold value of economic growth and that the disproportionality only existed in these countries during 2000 to 2007 as an inverse kuznets u shaped curve. however, it proves to contradict once the countries have reached the threshold value therein: the effect of economic growth on co2 is positive. adom et al. (2012) employed the macro economic analysis taking emission data from the energy information administration where coefficient upon gdp data were calculated on both longitudinally and cross sectionals, conducted a paper purposely to show how close the linkage of equivalent emission and economic development is over time as well as across countries. the links of energy to output to pollution: the conversion factor is estimated between economies over time and is claimed presently too high, ascertaining a global climate change. the technical consequence were that it is very hard to coordinate the global environment, subject to the combination of weak governance upon making policies and implementations, not forgotten the gigantic nature of the pd game. il is claimed that focusing on conversion factors would be a good mean of stabilizing co2 emission as the paper exhibited the clear and juggernaut type connections of both energy economic and output co2 emission. these comprehensive literature reviews related to this topic of interest prove evidence upon variations towards the causality relationship that exists between government expenditure, co2 emission and manufacturing output. most of past literatures had studied on tj1e relationship of these variables, however separately. most studies employed the unit root test, co integration test, and granger causality test in their approach of examining the relationship between the three variables in various nations including the asian countries. european countries. oecd countries and african countries. this study, on the other hand will focus on these three variables specifically and simultaneously. the methodology utilized in this research is the unit root test johansen cointegration. vector figure 3: malaysia gdp from healthcare sector source: trading economic trading economics (2020) samah, et al.: the impact of healthcare expenditure and healthcare sector growth on co2 emission using dynamic panel data system gmm estimation model during covid 19 crisis international journal of energy economics and policy | vol 10 • issue 6 • 2020 239 error correction model (vecm) and granger causality as these mentioned methods were frequently used by previous studies. all of these models will then be explained in the next chapter. 3. methodology and results 3.1. model specification for this study, the explanation of interrelations between healthcare expenditure and growth, inflation rate, interest rate and unemployment rate are using the approach of production function. this approach is already extended by cobb-douglas which is he developed the production framework to understand and explore more about the linkage between those independent variables: (rashid and razak, 2017) healthcare growth, healthcare expenditure, inflation rate, interest rate and unemployment rate. specifically, the following extended by cobb-douglas is the production function: model 1 y=ekαeλ lβ eu model 2 y=hkαeλ lβ eu the function is explained about the y is energy consumption, while e, k and l is stand for real income, capital stock and labor force respectively. while the term e and h is refers to the healthcare expenditure and healthcare growth e is the error term. ⍺, λ, and β are the production elasticities which are stands for real income, capital stock and labor force. after cobb-doughlas technology have been restricted to (⍺ + λ + β = 1), constant returns to scale could be gained. in this research, the model is revived the y (co2 emission) into the healthcare expenditure and healthcare growth to be endogenously affected by all independent variables (inflation rate, interest rate and unemployment rate) (adam and miroslawa, 2011). model 1 healthcare expenditure and co2 emission co2 = f (he, inf, int, unp) model 2 healthcare sector and co2 emission co2 = f (hg, inf, int, unp) healthcare expenditure and healthcare growth is logarithmic value which is the dependent variable for this research. healthcare expenditure and healthcare growth that is being measured in this research is being taken from five asia region country which is indonesia, philippines, thailand, china and malaysia. while “he” refer to healthcare expenditure on healthcare sector, “inf” is inflation rate, “int” is interest rate and lastly, “unp” refer to unemployment rate. all variables data are collected in selected developing country in asia region. based on the theoretical and empirical review that have been presented, all the relationship can be specified as follows: model 1: healthcare expenditure and co2 emission co2 emissiont = β 1het + β 2inft − β 3intt − β 4unpt + ct model 2: healthcare sector and co2 emission co2 emissiont = β 1hgt + β 2inft − β 3intt − β 4unpt + ct based on the equation, the positive sign of “he” shows that there is a significant value of co2 emission towards healthcare expenditure and healthcare growth. it is shown that if healthcare expenditure and healthcare sector is increase, then the co2 emission will be increase. in this case, the relationship between the co2 emission with healthcare expenditure and hg can have a positive relationship. the elements of healthcare expenditure do have relationship with fdi and the healthcare growth. government policies in the healthcare sector supported by political instability and poor environment for investment in the country have affected the co2 emission (chingarande, 2012). the positive sign of “inf” which is actually present the inflation rate that affecting co2 emission in selected asia country. the inflation that happened is a continual rise in price level where it is the index of all prices in the economy. and this phenomena will be called “inflation” when the price level increment happened in term of ongoing rising. this situation also is actually showing the short run aggregate supply shifting up while aggregate demand remains constant, where the price level will increase. inflation phenomena has been hypothesized by many researchers and practitioners in order to change and enhance the economic growth of countries (rashid and razak, 2017). however, there are so much literature on the impact of inflation rate itself. for example, (li, 2006) argues that the existence and nature of the inflation-economic growth nexus is one of the most significant macroeconomic controversies. furhermore, omankhanlen (2011) said that inflation has been hypothesized to distort the tax system which would in turn discourage investors for the long run due to money illusion. on the other hand, obiamaka (2011) stated that despite of the consensus among many researchers and practitioners on the negative relationship between inflation and co2 emission, inflation itself could have a positive impact on co2 emission and in turn growth provided that it does not exceed a certain threshold. moreover, the last positive sign of ‘unp’ represent unemployment rate. the unemployment rate is actually the percentage of people in a country who are able to work but not working. in a normal situation, when the economy of a country is showing a positive growth, the unemployment rate should be decrease. however, if the situation that happened is vice versa, it will lead to the higher unemployment rate and decrement productivity of co2 emission. according to irpan (2016) researchers in malaysia has studied the factors leading to decrease unemployment rate by to reduce co2 emission. 4. co2 emission policy on covid 19 unlike the global financial crisis in 2008, and the asian financial crisis in 1997, covid 19 crisis is a public health crisis first, and an economic crisis second. following this, economists generally agree samah, et al.: the impact of healthcare expenditure and healthcare sector growth on co2 emission using dynamic panel data system gmm estimation model during covid 19 crisis international journal of energy economics and policy | vol 10 • issue 6 • 2020240 that economic policy should focus mainly on bolstering public health efforts in handling the pandemic whilst ensuring the welfare of the poorest and businesses. for malaysia, the rm20 billion stimulus package announced in early stage of this outbreak is a good start and already comprises several of the actions proposed. this study concludes that the government should allocate more resources to the social sectors for raising productivity. health is another major form of human capital. many studies have shown the existence of positive relationship between health and economic growth. improvement in health status leads to an increase in life expectancy that means more opportunities for workers to work more and earn more income. equal and proper delivery of health care services is considered to be highly important in achieving health related objectives of healthcare expenditure. expenditures on human capital may have positive impact on economic growth. law and order situation in a country strongly affects the living conditions of the people. sound law and order situation protects individual and property rights, attracts fdi and provides strong incentives to the domestic investors to invest (alola, 2019). this boosts economic activity and generates employment opportunities for the people. healthcare expenditure on law and order and sector growth may be positively or negatively related to each other. this implies that healthcare expenditure spending on human capital and community services should be given much emphasis for promoting health sector growth in malaysia (kinoshita and campos, 2003). for this purpose, effective policies are needed to formulate and implement for promoting human capital formation and economic and community services in malaysia. the government should curtail its expenditure on subsidies as it is inflationary in nature and creates some other economic and social problems in the country which hamper the process of economic growth (chingarande, 2012). the government should reallocate and prioritize its expenditure on law and order for achieving success in eliminating law and order situation faced by the demand on the health system that can prevent health systems from being overwhelmed, mortality from covid 19 will be significantly lower (yavas and malladi, 2020). a more practical and perhaps more immediate concern is how mounting energy scarcity, increasing energy costs, and societal pressures to reduce emissions might actually pose a threat to the delivery of health services. health facilities depend on energy to operate and energy costs have been shown to contribute to health care price inflation. also, the plastics commonly used in medical equipment and medical supplies require petroleum feedstock. understanding the energy consumption and emissions associated with health services is important not only to identify opportunities to minimize their environmental impact, but also to facilitate their adaptation to a low-carbon economy especially during covid 19 crisis. managing co2 emissions is managing energy consumption, and vice versa. it is a win–win proposition. references adam, p.b., miroslawa, ż. (2011), foreign direct investment and unemployment: var analysis for poland in the years 1995-2009. european research studies journal, 14(1), 3-14. adom, p.k., bekoe, w., amuakwa-mensah, f., mensah, j.t., botchway, e. (2012), carbon dioxide emissions, economic growth, industrial structure, and technical efficiency: empirical evidence from ghana, senegal, and morocco on the causal dynamics. energy, 47(1), 314-325. alola, a.a. (2019), carbon emissions and the trilemma of trade policy, migration policy and health care in the us. carbon management, 10(2), 209-218. andersson, f.n., karpestam, p. (2013), co2 emissions and economic activity: short-and long-run economic determinants of scale, energy intensity and carbon intensity. energy policy, 61, 1285-1294. aon. (2020), 2020 global medical trend rates. as of this writing, report may be found at available from: https://www.aon.com/2020global-medical-trend-rates-rising-health-plan-costs-risk-factors/ index.html. asghar, m., khan, i.a., anwar, w., ahmad, b. (2011), systemized approach for software corrective maintenance effort reduction. journal of basic and applied scientific research, 1(10), 1356-1362. baffes, j., shah, a. (2013), productivity of public spending, sectorial allocation choices and economic growth. anaheim, california: paper prepared for presentation at the 1993 annual meetings of american economic association. boachie, m.k., mensah, i.o., sobiesuo, p., immurana, m., iddrisu, a.a., kyei-brobbey, i. (2014), determinants of public health expenditure in ghana: a cointegration analysis. journal of behavioural economics, finance, entrepreneurship, accounting and transport, 2(2), 35-40. buckley, p.j., clegg, l.j., cross, a.r., liu, x., voss, h., zheng, p. (2007), the determinants of chinese outward foreign direct investment. journal of international business studies, 38(4), 499-518. burnett, j.w., bergstrom, j.c., dorfman, j.h. (2013), a spatial panel data approach to estimating us state-level energy emissions. energy economics, 40, 396-404. chaabouni, s., zghidi, n., mbarek, m.b. (2016), on the causal dynamics between co2 emissions, health expenditures and economic growth. sustainable cities and society, 22, 184-191. cherniwchan, j. (2012), economic growth, industrialization, and the environment. resource and energy economics, 34(4), 442-467. chingarande, a. (2012), the relative effectiveness of monetary and fiscal policies on economic activity in zimbabwe (1981: 4-1998: 3) an error correction approach. international journal of management sciences and business research, 1(5), 1-35. garbaccio, r.f., mun, s., jorgenson, d.w. (2000), the health benefits of controlling carbon emissions in china. in: ancillary benefits and costs of greenhouse gas mitigation. paris: oecd. p343. hsiao, c., appelbe, t.w., dineen, c.r. (1993), a general framework for panel data models with an application to canadian customer-dialed long distance telephone service. journal of econometrics, 59(1-2), 63-86. irpan, a. (2016), exploring boosted neural nets for rubiks cube solving. as of this writing, paper may be found. available from: http://www. alexirpan.com/public/research/nips_2016.pdf. keefer, p., knack, s. (1997), why don’t poor countries catch up? a cross-national test of an institutional explanation. economic inquiry, 35(3), 590-602. kinoshita, y., campos, n.f. (2003), why does fdi go where it goes? new evidence from the transition economies no. 3-228, international monetary fund. knack, s., keefer, p. (1995), institutions and economic performance: cross-country tests using alternative institutional measures. economics and politics, 7(3), 207-227. li, m. (2006), inflation and economic growth: threshold effects and transmission mechanisms. department of economics, 2(5), 8-14. obiamaka, p.e. (2011), foreign direct investment and economic growth in nigeria: a granger causality analysis. international journal of current research, 3(11), 225-232. omankhanlen, a.e. (2011), the effect of exchange rate and inflation on samah, et al.: the impact of healthcare expenditure and healthcare sector growth on co2 emission using dynamic panel data system gmm estimation model during covid 19 crisis international journal of energy economics and policy | vol 10 • issue 6 • 2020 241 foreign direct investment and its relationship with economic growth in nigeria. economics and applied informatics, 1, 5-16. piaggio, m., padilla, e. (2012), co2 emissions and economic activity: heterogeneity across countries and non-stationary series. energy policy, 46, 370-381. poveda, a.c., martínez, c.i.p. (2013), co2 emissions in german, swedish and colombian manufacturing industries. regional environmental change, 13(5), 979-988. rashid, i.m.a., razak, n.a.a. (2016), determinants of foreign direct investment (fdi) in agriculture sector based on selected high-income developing economies in oic countries: an empirical study on the provincial panel data by using stata, 2003-2012. procedia economics and finance, 39, 328-334. rashid, i.m.a., razak, n.a.a. (2017), economic determinants of foreign direct investment (fdi) in agriculture sector based on selected developing oic countries: an empirical study on the provincial panel data by using stata, 2003-2012. jurnal intelek, 12(1), 1-10. trading economics. (2020), as of this research, data may be found at. available from: https://www.tradingeconomics.com/malaysia/ co2-emissions-metric-tons-per-capita-wb-data.html. trading economics. (2020), as of this research, data may be found at. available from: https://www.tradingeconomics.com/malaysia/ health-expenditure-total-percent-of-gdp-wb-data.html. yavas, b.f., malladi, r.k. (2020), foreign direct investment and financial markets influences: results from the united states. the north american journal of economics and finance, 53, 10118. international journal of energy economics and policy vol. 2, no. 1, 2012, pp. 34-40 issn: 2146-4553 www.econjournals.com disaggregated energy consumption and economic growth in ghana paul adjei kwakwa department of business economics, presbyterian university college ghana, akropong campus, p. o. box 393, akropong-akuapem, eastern region, ghana. email: pauladkwa@yahoo.com abstract: this study has examined the causality between disaggregated energy consumption (electricity and fossil consumption) and overall growth, agricultural and manufacturing growth in ghana’s economy over the period 1971-2007. by employing the augmented dickey fuller test all variables were found to be integrated of the order one and the johansen test showed the presence of cointegration between the variables. the granger causality test for the study indicated a unidirectional causality from overall growth to electricity and fossil consumption; a unidirectional causality from agriculture to electricity consumption both in the short and long run; and a feedback relationship between manufacturing and electricity consumption. energy seem not be an essential factor of production in the agricultural sector but important in the manufacturing sector therefore, it is recommended that efforts be geared towards ensuring a high supply of energy to the manufacturing sector in order to keep up its contribution to the economy. keywords: energy consumption; economic growth; cointegration; granger causality; ghana jel classification: c3, o4, q43 1. introduction the impact of energy consumption on economic growth has attracted the interests of economists and policy makers in recent times. according to erbaykal (2008), the petroleum crisis in 1970s displayed the importance of energy as a production factor. since then, energy comes up as a production factor in addition to labor and capital. after the seminal work by kraft and kraft (1978), a number of studies have been done in the area of energy and growth by examining the causality between them but with mixed results. earlier studies focused on the total energy consumption and total gross domestic product (gdp) growth with a few focusing on the relationship between the disaggregated energy and growth in various countries. however, these studies have concentrated largely outside africa with very little known in ghana. again, the few studies on ghana have focused on electricity and aggregate growth but with mixed results. meanwhile apart from electricity, fossil energy is an important component in the country’s energy consumption. the importance of fossil energy can be acknowledged by the huge amount of money spent to import crude oil and how an increase in petroleum price and lpg shortage affect the smooth operation of many businesses in the country. for instance information from the bank of ghana is that the country spent about $1.72 billion to import crude oil, gas and oil products between january and july 2011 resulting in a 45.4% annual growth of merchandise imports of the country within the period to an amount of $8.6 billion. by incorporating fossil energy the paper seeks to examine the causal relationship between disaggregated energy (electricity and fossil) and total gdp growth, industrial growth and agricultural growth in the ghanaian contest. the rest of the paper is organized as follows: section two reviews some empirical literature; section three deals with methodological issues; section four is analysis of results and section five concludes with recommendation. 2. review of empirical literature following the literature, any study on the causality between energy and growth has revealed one or more results out of four possible outcomes (see ozturk, 2010 for detailed survey of literature on energy-growth nexus). these are the unidirectional causality from energy to growth; unidirectional international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.34-40 35 causality from growth to energy; feedback relationship between energy consumption and growth; and no causality. in the light of this, soytas and sari (2007) have explained that the variation in empirical findings could be due to different economic structure of particular countries being studied and also to the fact that different economies have different consumption pattern and various sources of energy. kraft and kraft (1978) study on the usa economy for the period 1947-1974 saw a unidirectional causality relation from gnp to energy consumption. according to jumbe (2004) the result of the kraft and kraft study gave an indication that the low level of energy dependence enabled the usa to pursue energy conservation policies which had no adverse effects on income (khan and ahmed, 2009). however, this result was not corroborated in the study by akarca and long (1980) which used the same data set for the period 1947–1972 but found no relationship between the two variables. they argued that kraft and kraft’s (1978) work could suffer from temporal time period instability. in other north american countries francis et al. (2007) over the period 1971-2002 found bidirectional causality between energy and growth in the short run for haiti, jamaica, and trinidad and tobago. in the long run however, no evidence of a relationship was found for haiti and jamaica; but there was a feedback relationship for trinidad and tobago. lorde et al. (2010) investigated the relationship between electricity consumption and economic growth in the barbados economy utilizing a neo-classical one-sector aggregate production model. the empirical results was that electrical energy consumption by the non-residential sector acts as a driver of economic growth in the long run and a unidirectional causality from electricity consumption by the non-residential sector to real gdp. in europe, erol and yu (1987) carried out a study for six industrialized countries including england, france, italy, germany and canada for the period 1952-1982 with the results of their study giving a unidirectional causality from energy consumption to gdp for canada; unidirectional causality from gdp to energy consumption for germany and italy; and no causality for france and england. masih and masih (1997) in their study realized bidirectional causality between energy consumption and real income in korea and taiwan. also yang (2000) investigating the causal relationship between energy and gdp with taiwan data for the period 1954–1997, found bidirectional causality between total energy consumption and gdp. aqeel and butt (2001) using hsiao’s granger causality test established one way causality from economic growth to total energy consumption and petroleum consumption for pakistan. their results however, showed no causality between the gas sector and economic growth. morimoto and hope (2004) found bidirectional causality between electricity consumption and economic growth in sri lanka during the period 1960–1998. in vietnam binh (2011) showed that there is a strong unidirectional causality running from growth to energy consumption. the author used the cointegration and granger approach for the period of 1976-2010. in his study on 17 african countries wolde-rufael (2006), observed a unidirectional causality running from growth to electricity consumption in cameroon, ghana, nigeria, senegal, zambia and zimbabwe; unidirectional causality from electricity to growth for six other countries and no causality for the rest. more so, akinlo (2008) observed bidirectional relationship between energy consumption and economic growth for gambia, ghana and senegal; causality from growth to energy consumption in sudan and zimbabwe and no causality in cameroon and cote d'ivoire. 3. data and methodology the granger causality test is used in the study to examine the relationship between growth and energy in ghana. the country study covers the period of 1971 to 2007 by relying on secondary data from the world bank’s development indicator 2010. the data utilized are electricity consumption and fossil fuel consumption as components of disaggregated energy use. the fossil fuel is made of coal, oil, petroleum and natural gas. the growth variables are the overall gdp growth, agricultural growth and manufacturing growth. we begin our analysis by looking at the stationarity of the variables and proceed to test for the presence of cointegrating vectors. stationarity/unit root time series data are often found to be non stationary in their levels and thus produce spurious results when used for regression analysis. where time series data are found to be non stationary the method of differencing approach is applied to the series until they become stationary. in carrying out the unit root or stationary test the augmented dickey fuller (adf) test is employed. the variables are disaggregated energy consumption and economic growth in ghana 36 of the order 1, that is i(1) if they are stationary at first difference and of the order 0 denoted as i(0) if they are stationary in levels. cointegration to determine the causal relationship between energy and growth, there is also the need to test for cointegration. cointegration means that even though individual variables may be non stationary in levels, a linear combination of two or more of such series is stationary. this occurrence suggests the existence of a long run relationship or equilibrium between the variables (gujarati and sangeetha, 2007). for the purpose of this study, the johansen trace test is used to test for the existence of cointegartion and the number of cointegrating vectors. the presence of cointegrating vector is a sufficient condition to estimate a vector error correction model (vecm). granger causality economists have been interested in examining whether one variable can help forecast another economic variable and to achieve this, the granger causality test has been developed. to test for causality, in the granger sense, involves using f-tests to investigate whether lagged information on say economic growth provides any statistically significant information about energy consumption in the presence of lagged energy consumption. if it is found to be significant then economic growth does granger cause energy consumption and when it is insignificant there is no causality. to implement a test of granger causality we use the autoregressive specification of a multivariate vector auto regression. according to granger’s theorem when the variables are cointegrated, the simple granger causality is augmented with the error correction term (ect), derived from the residuals of the appropriate co integration relationship to test for causality. thus we estimate a vecm for the granger causality test for our problem at hand. the vecm representation is as follows: where y is overall growth, e is electricity consumption, f is fossil consumption , and ρi is the adjustment coefficient. ectt-1 expresses the error correction term of growth equation, δ indicates first difference operator, μt and t are mutually uncorrelated white noise errors, while t denotes the time period. in equation (1), the energy variables granger causes growth if their coefficients and ρi are significantly different from zero. in equations (2) and (3), growth granger causes energy if the coefficient of growth and ρi are significantly different from zero. f-statistic is used to test the joint null hypothesis that the coefficients are equal to zero, and t-test is employed to estimate the significance of the error coefficient. it is important to note that a significant error coefficient indicates causality in the long run. however in all, the regressions may lead to one or more of the following four scenarios: 1. unidirectional causality from energy to growth, 2. unidirectional causality from growth to energy, 3. bilateral causality between energy and growth and 4. independence. in this case there is no granger causality. 4. results and analysis unit root the standard adf test was used to test for stationarity of the variables. in carrying out this test, the null hypothesis is that the series contains unit root and the alternate is that the series has no unit root. table 1 shows the adf test statistics of the series for the unit root. the results indicate that international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.34-40 37 all the variables are integrated of the order 1. that is the variables in their levels were not stationary at both 1% and 5% significant levels as a result they were differenced once and the resultant variables were stationary. the variables lny, lne, lnf, lnm, and lna stands respectively for the logs of overall growth, electricity consumption, fossil consumption, manufacturing growth and agricultural growth while the d in front of each variable represents the difference of that variable. table 1. adf test for unit root variable t-statistic 1% critical value 5% critical value prob* lne -1.676593 -3.639407 -2.951125 0.4337 lnf -2.089633 -3.626784 -2.945842 0.2498 lny 0.269745 -3.67017 -2.963972 0.9726 lna 0.404808 -3.626784 -2.945842 0.9804 lnm -0.153049 -3.632902 -2.948404 0.9354 dlne -5.618846 -3.639407 -2.951125 0.0000 dlnf -6.830964 -3.639407 -2.951125 0.0000 dlny -4.195207 -3.632902 -2.948404 0.0023 dlna -6.620963 -3.632902 -2.948404 0.0000 dlnm -4.067652 -3.632902 -2.948404 0.0032 *mackinnon (1996) one-sided p-values cointegration table 2 below shows the johansen test results for possible cointegration among the variables. the results from the table points to at least one cointegrating vector between gdp growth (lny ) and the energy variables (lne and lnf) at 1% level of significance. again cointegration exists between agricultural growth (lna) and all the energy variables at 1% level of significance, and also between manufacturing growth (lm), and the energy variables at 5% significant level. thus the results suggest a long run relationship between both total growth and the energy variables and also between the disaggregated growth and energy variables. table 2. johansen trace test results for cointegration variable ho: number of ce(s) eigenvalue trace statistic 0.05 critical value prob.** none * 0.723428 63.18866 42.91525 0.0002 at most 1 0.346238 20.77427 25.87211 0.1892 lny, lne and lnf at most 2 0.184954 6.748862 12.51798 0.3714 none * 0.855582 83.53369 42.91525 0.0000 at most 1 0.382757 19.67720 25.87211 0.2427 lna, lne and lnf at most 2 0.107551 3.754938 12.51798 0.7772 none * 0.442984 30.24098 29.79707 0.0444 at most 1 0.298153 11.51582 15.47211 0.1817 at most 2 0.005812 0.186527 3.81798 0.6690 lnm, lne and lnf * denotes rejection of the hypothesis at the 0.05 level **mackinnon-haug-michelis (1999) p-values disaggregated energy consumption and economic growth in ghana 38 granger causality tables 3, 4 and 5 provide the results for the granger causality test. the akaike information and schwartz information criterion were used in determining the lag length selection. the results from table 3 point to a unidirectional causality from overall growth to electricity consumption in the short run, and fossil consumption in both the short run and long run. the long run causality from growth to fossil consumption is confirmed by the significant ttest on the lagged ect. this seems to support the work of wolde-rufael (2006) and twerefo et al., (2008) that found a positive unidirectional causality running from growth to energy consumption in ghana but contradicts akinlo’s (2008) bidirectional causality in ghana. the results from this study may be attributed to the fact that energy like any normal commodity positively depends on income. therefore as the economy grows demand for electricity and fossil for residential and non residential uses is likely also to increase. the fact that energy does not granger cause growth may be attributed to the results from the relationship between energy and the agriculture growth and this will be explained shortly. table 3. causality test between overall growth and disaggregated energy equation short run long-run dlny dlne dlnf ectt-1 f statistics t statistic dlny 0.19529 0.56058 -3.04877*** dlne 4.30549** 2.44197 0.91197 dlnf 2.99374* 0.4302 -2.13747** ***,**, * indicates significant at 1%, 5%, and 10% levels, respectively again when growth is disaggregated, there is unidirectional causality from agricultural growth to electricity consumption both in the short and long run but no relationship between fossil and agricultural growth (table 4). the argument for such results may be that the agricultural sector which is the largest sector employs majority of the ghanaian labour force, therefore a growth in the sector leading to an increase in workers’ wages and salary can cause consumption of electricity increase. table 4. causality test between agricultural growth and disaggregated energy equation short run long-run dlna dlne dlnf ectt-1 f statistics t – statistic dlna 0.34561 0.22814 -0.40873 dlne 4.79816** 4.37190** 1.44645* dlnf 2.4837 0.44153 -1.34704* ***, **, * indicates significant at 1%, 5%, and 10% levels, respectively. the first two causality results suggest that there is no established causality from energy to overall growth and agricultural growth in the ghanaian economy. one can therefore say that any shortage in electricity or fossil supply may not adversely affect gdp growth or cause a fall in the gdp because per this study, the agrarian economy does not receive any causality from energy. this may not be strange because the ghanaian agricultural sector for a long time has been the largest contributor to the nation’s growth contributing an average of 39.4% between 2002 and 2007 as against 32.9% from the service sector and 27.7% from the industrial sector (isser, 2008) but the sector is less responsive to energy (adom, 2011). a prominent feature of agriculture in ghana is the small-holder farmers dominating the system with few large scale farming which is mainly for the industrial crops, such as cocoa, oil palm, rubber, and pineapples. most of the small scale farmers still rely on rudimentary tools and crude farming methods like the slash and burn which of course will have nothing to do with electricity and fossil fuel. therefore since fossil and electricity energy do not granger cause growth in the ghana’s dominant sector (agriculture) it is not surprise that energy does not granger cause overall growth in the economy. international journal of energy economics and policy, vol. 2, no. 1, 2012, pp.34-40 39 however, from table 5 there is a unidirectional causality from manufacturing to fossil consumption in the short and the long run, and bidirectional causality between manufacturing and electricity consumption in both runs. the manufacturing sector in ghana made up of textiles and garment, cement, iron and steel products, food processing and beverages and wood and paper products require electricity for smooth operation. the extent that in 2006/2007 the electricity power rationing in the country cost the manufacturing sector a negative growth rate of 2.3% (isser, 2008) implies that electricity means a lot to this sector. also growth in the manufacturing sector may cause consumption of electricity to increase because the sector depends on electricity and thus a growth in the sector would call for more electricity for production. the unidirectional causality from manufacturing to fossil consumption can be attributed to the fact that some manufacturing depends to some extent on oil, petroleum and natural gas therefore changes in the sector’s growth would affect fossil consumption. table 5. causality test between manufacturing growth and disaggregated energy equation short run long-run dlnm dlne dlnf ectt-1 f statistics t – statistic dlnm 4.03103** 0.57989 -1.74689** dlne 7.56837*** 2.45256 1.57929* dlnf 4.43101** 0.41809 1.33912* ***, **, * indicates significant at 1%, 5%, and 10% levels, respectively 5. conclusion this study has examined the causality between disaggregated energy consumption and growth in the ghanaian economy for the period 1971-2007. the energy variables were electricity and fossil consumption while the overall gdp growth, agriculture growth and manufacturing growth were used for growth. the appropriate test showed that all the variables were integrated of order one and the presence of cointegration among all the growth and the energy variables. as a result the simple granger causality test was augmented with the long run part that is the lagged of ect. the empirical findings indicated that electricity consumption and fossil consumption do not granger cause overall growth but aggregate growth granger cause electricity consumption and fossil consumption. when growth is disaggregated, we found unidirectional causality from agriculture to electricity consumption both in the short and long run. also, there was bidirectional causality between manufacturing and electricity consumption but a unidirectional causality from manufacturing to fossil consumption in the short and the long run. thus even though electricity and fossil consumption seem not be an essential factor of production in the ghanaian agricultural sector and the overall growth they are important for the manufacturing sector. therefore, the policy recommendation is that efforts should be geared towards ensuring a high supply of energy to the manufacturing sector in order to sustain its contribution to the economy. acknowledgement i am very grateful to emmanuel adu-danso of the department of economics, university of ghana for his valuable comments to shape this work. i would also like to extend my profound appreciation to prince manu-barfo, department of animal science, university of ghana for his support. my heartfelt appreciation goes to the two anonymous referees and the editor for time spent on this work. however, any other error spotted in this work is the doing of the author. references adom, p.k. (2011), electricity consumption-economic growth nexus: the ghanaian case. international journal of energy economics and policy, 1(1), 18-31. akarca, a.t., long, t.v. (1980), on the relationship between energy and gnp: a reexamination, journal of energy and development, 5(2), 326–331. disaggregated energy consumption and economic growth in ghana 40 akinlo, a.e., (2008), energy consumption and economic growth: evidence from 11 african countries: energy economics, 30, 2391–2400. aqeel, a., m.s. butt (2001), the relationship between energy consumption and economic growth in pakistan, asia-pacific development journal, 8(2), 101-110. binh, p. t. (2011), energy consumption and economic growth in vietnam: threshold cointegration and causality analysis. international journal of energy economics and policy, 1(1), 1-17. erbaykal, e. (2008) disaggregate energy consumption and economic growth: evidence from turkey. international research journal of finance and economics, issue 20(2008), 172-179. erol, u., yu, e.s.h., (1987), on the causal relationship between energy and income for industrialized countries. journal of energy and development, 13, 113–122. francis, b.m., moseley, l., iyare, s.o. ( 2007), energy consumption and projected growth in selected caribbean countries. energy economics, 29(6), 1224–1232. gujarati ,d.n., s. sangeetha (2007) basic econometrics. fourth edition, published by tata mcgraw-hill. isser, (2009) the state of the ghanaian economy. publication by institute of statistical, social and economic research, university of ghana, legon. jumbe, c.b.l., 2004. cointegration and causality between electricity consumption and gdp: empirical evidence from malawi. energy economics, 26(1), 61–68. khan, a., ahmed, u. (2009). energy demand in pakistan: a disaggregate analysis. paper presented at the 24th annual general meeting and conference of the pakistan society of development economists, march 31-april 2, islamabad. kraft, j., kraft, a., (1978). on the relationship between energy and gnp. journal of energy and development, 3, 401–403. lorde, t. k., waithe., francis, b. (2010), the importance of electrical energy for economic growth in barbados, energy economics, 32, 1411–1420. masih, a.m.m., masih, r. (1997). on the temporal causal relationship between energy consumption, real income, and prices: some new evidence from asian-energy dependent nics based on a multivariate cointegration/vector error correction approach. journal of policy modeling, 19, 417–440. morimoto r., hope, c. (2004), the impact of electricity supply on economic growth in sri lanka, energy economics, 26, 77–85. ozturk, i. (2010). a literature survey on energy-growth nexus. energy policy, 38(1), 340-349. soytas, u., sari, r. (2007), the relationship between energy and production: evidence from turkish manufacturing industry. energy economics, 29(6), 1151–1165. twerefo d.k., akoena s.k.k., egyir-tettey f.k., mawutor g., (2008), energy consumption and economic growth: evidence from ghana. department of economics, university of ghana, accra, ghana. wolde-rufael, y. (2006), electricity consumption and economic growth: a time series experience for 17 african countries, energy policy, 34, 1106 –1114. yang, h.y. (2000), a note on the causal relationship between energy and gdp in taiwan. energy economics, 22, 309–317. . international journal of energy economics and policy | vol 9 • issue 6 • 2019 109 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(6), 109-117. energy optimization of industrial steam boiler using energy performance indicator guillermo valencia ochoa1*, jhan piero rojas2, juan campos avella1 1mechanical engineering program, faculty of engineering, grupo de investigación en gestión eficiente de la energia-kaí, universidad del atlántico, carrera 30 número 8-49, puerto colombia 081007, atlántico, colombia, 2faculty of engineering, universidad francisco de paula santander, #0-a avenida gran colombia no. 12e-96, cúcuta, norte de santander, colombia. *email: guillermoevalencia@mail.uniatlantico.edu.co received: 30 may 2019 accepted: 05 september 2019 doi: https://doi.org/10.32479/ijeep.8188 abstract this article shows the application of an energy management system and the calculation of energy efficiency indicators to a pyrotubular boiler, following the guidelines of the iso50001 standard. the actual energy consumption indicators, the theoretical consumption index, the energy baseline and the efficiency index 100 were evaluated based on gas consumption and steam production data. as for the savings measure, a 20% reduction in gas consumption can be achieved by reducing the operational variability equivalent to 186,633 m3/month, thereby achieving a monthly savings of $70,920,717 cop and a large reduction in natural gas equivalent to a reduction in co2 emissions (1,318,739.05 kg co2/month). also, the purges currently recorded in the boiler are higher than the recommended value for this equipment, and the excess air released varies between 6% and 11%, increasing the losses due to sensible heat. three main implementations were applied to improve the energy performance of the steam boiler. the first saving implementation was the reduction of the generation pressure from 250 to 180 psig, achieving a lower gas temperature with a reduction of heat losses from the boiler, pipes and steam leakage losses, achieving a saving of 2% of the average natural gas consumption. the second implementation was the automation of the boiler purges, in accordance with the recommended value une-9075/85, achieving a total saving of 0.66%, and the third measurement allows on-line correction of the combustion air by direct measurement of o2, which maintains the measured oxygen value at 3%, which is the recommended value. with this practical and novel method energy performance indicator on the boiler, was increased the performance of the equipment, as well as the production costs and environmental impact reduction. keywords: energy optimization, steam boiler, energy performance indicator, iso 50001 standard jel classification: q42 1. introduction boilers are devices widely used in industry for the steam production, which allows electricity to be generated through steam turbines (jayamaha, 2006), (moran et al., 2011). the efficient operation and implementation of energy management systems in these generation systems have made it possible to identify potential energy savings through good operational practices in some companies (mecrow and jack, 2008), (barma et al., 2017). traditionally, the energy saving potential for these processes has been based on energy efficiency indicators from the thermodynamic point of view, allowing the construction of methods to obtain the exergetic losses and the exergetic efficiency of the boilers (behbahaninia et al., 2017). however, these methods require complete knowledge of the thermodynamic state properties of the working fluids involved in the process, which in some cases requires rigorous energy simulations, computational resources and significant training times for the handling of the necessary computer tools (zhang et al., 2010), (dal secco et al., this journal is licensed under a creative commons attribution 4.0 international license ochoa, et al.: energy optimization of industrial steam boiler using energy performance indicator international journal of energy economics and policy | vol 9 • issue 6 • 2019110 2015). in this sense, an evaluation of the boiler performance in an ethanol production plant was carried out using an exergy and irreversibility analysis in which the individual components of the system are evaluated, demanding an exhaustive evaluation of the thermodynamic properties in the process (pambudi et al., 2017). similarly, research based on the analytical evaluation of these properties has made it possible to estimate the thermal equilibrium of coal-fired boilers, supplemented by numerical results of energy simulations (junga et al., 2017), (garcía et al., 2016). on the other hand, some studies have focused on the performance evaluation of the actual efficiency in the boiler (baldi et al., 2017), presenting only the estimates of the actual efficiency and the expected efficiency from the historical data set of the equipment, but not presenting the recommendations or improvements to be implemented in the equipment (shen et al., 2017), (nikula et al., 2016). in addition, the emissions assessment is an essential factor which play a complementary role on the energy saving indicators, facing the constant advance of alternative energies and advanced fuel regimes, for which the university of west-virginia studied the emissions caused by ignition compression machines (carder et al., 2017), concluding that a reduction on the energy consumption on this type of process conduct also to a reduction on the emission. therefore, energy efficiency seeks to mitigate many current environmental problems in different industrial process, such as the greenhouse gas emission effect produced from incineration plants (hwang et al., 2017), round wood production (nakano et al., 2016), the construction industry (arıoğlu et al., 2017), among others. many researchers had been developed for its reduction, making energy and economic analyses (feng et al., 2017), bibliometrics analysis (geng et al., 2017), and theoretical analysis (cucchiella et al., 2018). in addition, new control strategies oriented to obtain an optimal management of emissions was proposed (bui and de villiers, 2017), (kumar and subramanian, 2017). these strategies have been used for the industry in the creation, processing, and disposal of reagents, obtaining a reduction of 29.86% (santín et al., 2017). in this sense, emission control analysis was carried out using dispersion models, for which all pollutants and their emission rates are processed to show the initial distribution of the contaminant in the region, proposing a three-dimensional model to help control emissions (skiba and parra-guevara, 2013). recent innovation had been developed in this field, such as the sic-fet technology, a silicon carbide field effect transistor for gas emission control and gas detection, which use a sensor as an alarm for ammonia emission and particle detection in diesel exhaust (lloyd et al., 2013), but the best way to reduce the emission is implementing best energy practices in the industrial process. in current operational processes, energy is a necessary element for the operation of a plant, and should be optimized with energy efficiency practices to minimize energy consumption and production costs (arens and worrell, 2014). therefore, thanks to research and implemented cases, the plants around the world have recognized opportunities for improvement at the productive and economic level, which results in an optimum thermal efficiency of the equipment, which imply the use of less energy to conserve the required production levels (valencia, 2011). with the acceptance of the iso 50001 standard (international organization for standardization, 2011), all companies around the world have established an energy policy to reach improving on the energy efficiency processes, identifying equipment and sub-processes that require a significant amount of energy, developing potential savings associated with production, with an improvement plan to be implemented (jovanović and filipović, 2016), (fiedler and mircea, 2012). thanks to the efficiency of the system, there are many applications in different sectors of the industry. an example of this can be found in the metal-mechanical industry, where energy savings potentials close to 20% were achieved without changing equipment, which represent a saving of 565.69 kwh, while the savings potentials related to production were around 1775 kwh (cardenas et al., 2017). also, a case in a fertilizer company allowed finding savings potentials of 16.1%, without new technologies and approximately 26% of these improvements (valencia et al., 2017). the rational use of energy and implemention of energy management system plays a relevant role in the development of new tools for energy consumption reduction (habib et al., 2016), production costs reduction (valencia et al., 2017), identification of best energy resources (fahad et al., 2017), (meschede et al., 2017), and progress in approaches of sustainable development (may et al., 2015), (miremadi et al., 2018). therefore, the aim of this paper is to present the results of an energy diagnosis of an industrial boiler by evaluating the energy indicators based on the energy consumption, steam production and operating data, identifying possible actions for the company and estimating the energy saving and environmental impact avoided. also, the application of operational data analysis in detail to obtain energy efficiency indicators for an industrial steam boiler in colombia is presented, with the propose of reducing energy consumption and pollutant emissions from energy characterization implementation strategies. 2. methodology this section presents in details the methodology to implement an energy management system in an equipment or process, a particular case applied to a piro-tubular boiler with a capacity of 75,000 lb/h operating in a vegetable oils and fats production process, and the calculation of energy performance indicators to estimate the potential energy savings for this application. 2.1. description of the process to process the edible vegetable oils and fats, the plant is divided into two productive sections, the refinery and packaging subprocess as shown in figure 1. the objective of the refinery section is to refine the raw palm and soybean, and the packaging section is responsible for filling them with processed products in the first section. this work will concentrate on the first productive section, in which primary energies from fossil sources such as natural gas and electricity are required, which are transformed to thermal energy as steam, hot and cold water. the production section is divided into four ochoa, et al.: energy optimization of industrial steam boiler using energy performance indicator international journal of energy economics and policy | vol 9 • issue 6 • 2019 111 parts, the raw soybean oil processing zone which is produced in the production areas, the processing of crude palm oil which comes from tank cars, the processing of soaps which is storage in silos, and the processing of containers where the raw material and finished product is storage in tanks. the chemical processes carried out for the raw material processing is the chemical refining, where 327 tons/month (7.8%) of the total steam produced by the boiler is consumed, in which neutral soybeans and soap are produced. in the physical refinery, 2182 tons/month (52.1%) is required to process the soybean oil and palm oil, among other chemicals necessary for the winterization process, which consumes 159 tons/month (3.8%) and soap making equipment that consumes 816 tons/month (19.5%). 2.2. technical detail of the boiler in this study, a nebraska boiler company as shown in figure 2 boiler was considered to applied the method, which has a todd combustion inc. burner, with a capacity of 75,000 lb/h, a recommended excess air of 10%, a design pressure of 300 psi, an initial operating pressure of 250 psi with a current operation of 205 psi and a target operating pressure of 180 psi. 2.3. energy management systems and energy performance indicator the technique proposed in this study to efficiently implement the energy management program is based on the systematic steps and procedure established in quality management, which aims to achieve continuous improvement of energy performance of equipment and processes (cardenas et al., 2017). since the approval of the iso 50001 standard, there has been an increase in the industrial sector’s adoption of energy management systems worldwide, motivating various companies to propose an energy policy that seeks to improve the energy efficiency of equipment that have a significant use of energy, allows the development of projections and trends of indicators for each process, and facilitates the quantification of potential savings related to production, in addition to the development of action plans to be implemented to achieve these potentials (valencia et al., 2017). figure 1: industrial production diagram figure 2: boiler nebraska boler company ochoa, et al.: energy optimization of industrial steam boiler using energy performance indicator international journal of energy economics and policy | vol 9 • issue 6 • 2019112 the standard considers a cyclical model of continuous improvement made up of four well-defined stages: energy policy, energy planning, implementation of actions and verification of results. in this research, emphasis has been placed on the energy planning stage, given that it contemplates the main activities to improve the boiler’s energy efficiency. during the implementation stage of the savings opportunities identified through the energy management system, meetings were held with the plant officials and with the participation of the energy managers in charge of implementing the program, in order to plan the activities based on a preliminary assessment of the current state of energy management in that organization as opposed to compliance with iso 50001, through a gap analysis and having determined compliance with the general requirements. an energy policy was defined to improve the energy efficiency of the processes, thus determining equipment and sub-processes that consume energy significantly, foreseeing projections and quantifying the potential savings associated with production, and their respective action plans to achieve these potentials, as well as responsibilities within the energy team. the flowchart of procedures related to energy planning is shown in figure 3, which is the main element that forms the basis of strategies to improve energy efficiency. to calculate the energy indicators, statistical treatment of energy consumption and production was performed, which allowed. indicator, the accumulation trend graphs and finally the consumption index (ci) according to the equations (1-4). the actual ci was calculated with the energy consumption (eactual) and the production (p) as follows. ic = e p actual actual (1) w h i l e t h e t h e o r e t i c a l ( i c t h e o r i c ) w a s c a l c u l a t e d a s (valencia et al., 2017). ic = e p therioc theoric (2) where etheoric is the theoretical energy consumption of the equipment. the energy baseline is obtained from the linear regression of historical energy consumption determining the baseline and target, the efficiency determining the baseline and target, the efficiency and production data, the energy baseline has the following direct form e = mp + bactual (3) in addition, the base 100 efficiency index (base 100), which is an energy management tool that helps to evaluate the performance of the energy consumption measured during a production period, is calculated as follows base100 = e e 100%theoric actual × (4) through these calculations, variations in the energy efficiency of the process could be identified, facilitating the analysis of action plans to improve energy efficiency. 3. results and discussions to the study of steam production performance as shown in figure 4, it is delimited by an upper and a lower limit, with the aim of identifying the presence of atypical points or abnormal operating conditions in the process. it can have been observed that in some periods of time the production of steam is the same, if they can have the same output with the same amount of consumption. as the study periods progress, there is a slight tendency to decrease in steam production due to the demand of the process, implying a drop in the consumption rate. in many of the periods, steam production is below the lower production line, indicating process performance problems. during 20 days of data collection, the variables steam production and gas consumption were recorded, representing these in figure 4a and b respectively. in the first four days of sampling, a reduction in gas consumption is noted that led to a decrease in the boiler temperature (figure 5a) and therefore a reduction in the energy transferred to the water (figure 5b), going from an average temperature of 95°c to 55°c, a temperature that is not optimal for steam generation in the boiler meaning a an abnormal operation condition which need to be identify by mean of the energy performance indicators. first stage. strategic decision second stage. installation of energy third stage. functioning of the 1. characterization of the company. 2. commitment of the top management. 3. to align the structure of the company towards the rational use of energy. 1. indicators of the energy management system 2. identification of control variables by cost and areas. 3. identification of corrective actions. 4. definition of monitoring systems. 5. energy diagnosis. 6. identification of opportunities for the efficient use of energy. 7. updating the organizational management of systems 8. internal audit of the systems 9. documentation 1. monitoring and dissemination of indicators. 2. monitoring and evaluation of good practices in operation, maintenance, production and coordination. 3. implementation of improvement programs and projects. 4. implementation of personnel training and evaluation plan. 5. management controls. 6. management system settings. 7. evaluation of results. figure 3: energy planning procedure based on iso 50001 standard ochoa, et al.: energy optimization of industrial steam boiler using energy performance indicator international journal of energy economics and policy | vol 9 • issue 6 • 2019 113 the behavior at this operation point is also due to a depressurization of steam (figure 6a) and an excess of oxygen in the combustion (figure 6b), reaching peak values of more than 15%, implying a quantity of air sufficient for a complete combustion between the fuel and oxygen, among other things, the oxygen control system regulates the operation to provide less oxygen and therefore less combustion air with respect to the stoichiometric value. in this way, these control strategies manage to regulate the equipment operation and in an indirect way the energetic performance indicator of the system, even though they need to be monitored and managed by mean of energy management systems. when making the energy and production graph from the data supplied, initially a base of lines with an acceptable linear correlation was obtained, since the data did not show an atypical behavior, however, it was necessary to filter the data to establish a more stable relationship, with the objective of not losing functionality between production and energy in the analysis of energy indicators. an extended base of the form e base = 44,088x + 412.78 and a linear correlation equal to r² = 0.7845 and e target y = 0.0586x + 1.3814 and a linear correlation equal to r² = 0.9933, extended this is evident in figure 7. the baseline analysis of the boiler efficiency indicator 100, showed satisfactory energy efficiency peaks, as shown in figure 8, these are those above the 100% average, in the same way, variations below the efficiency rate are considered energy inefficiency peaks. it is important to note that the low-efficiency peaks that occurred in the period from november 1 to november 4 are related to the variation in the energy management system. a statistical analysis, taking into account the reduction of operational variability and the management of production, showed that it is possible to achieve a natural gas saving of 20%, monthly, equivalent to 186,633 m3/month, with a reduction of 401,260.95 co2/month to the environment, for an average consumption of 800,000 m3/month (1,720,000 co2/month) and with this, achieve monthly cop savings of $70,920,717 and a significant figure 4: control limit graph, (a) steam production, (b) gas consumption a b figure 5: steam boiler operation, (a) boiler temperature, (b) water temperature b a ochoa, et al.: energy optimization of industrial steam boiler using energy performance indicator international journal of energy economics and policy | vol 9 • issue 6 • 2019114 reduction in natural gas equivalent to a reduction in co2 emissions (1,318,739.05 co2/month). 3.1. natural gas consumption regulation (strategy implemented 1) natural gas consumption is limited to steam production and thermal oil boilers for heating in deodorization towers. the analysis of results shows that savings measures should be taken for own generation pits due to their high impact and centralized application. currently, approximately 45,000 lb/h of steam is generated at 250 ppm, of which only 2% (1150 lb/h) at this pressure level, this causes additional energy to be spent on heating the steam to a higher pressure. in the vacuum generation of the refining towers, 26% of the steam generated is used at 150 psig and the 72% is used in the process at a pressure that does not exceed 90 psig. the purges currently registered in the boiler are above the recommended value for this equipment, which has a value of about figure 7: energy performance indicator: base line graph figure 8: base 100 efficiency index figure 9: boiler pressure reduction nebraska figure 10: purge reduction system for the implemented measure figure 6: steam boiler operation, (a) boiler steam pressure, (b) oxygen concentration b a ochoa, et al.: energy optimization of industrial steam boiler using energy performance indicator international journal of energy economics and policy | vol 9 • issue 6 • 2019 115 30% of the total steam generated. the excess air manifested by the high levels of o2 oxygen in the combustion gases ranges from 6% to 11%, causing increased losses due to sensitive heat. 3.2. automation of the boiler (strategy implemented 2) the second measure is the automation of the boiler purges according the schematic diagram show in figure 9. the system monitors dissolved solids by not letting them rise above a certain point, which will help reduce purging base on the system shown in figure 10. because steam boiler purge losses were identified, consideration was given to changing the figure 11: control strategy implemented figure 12: control strategy implemented for the nebraska boiler figure 13: emission reduction of co2 by strategy implemented in the subprocess operating conditions by changing the total purge (p = 1662 lb/h), the percentage of condensate return (64%) and the full steam generated (psteam = 5541 lb/h), so that, in accordance with the recommended value une-9075/85, obtaining a current drain of 2,494 to achieve a total saving of 0.66%. 3.3. direct measurement of o2 (strategy implemented 3) the third measure to be implemented allows in-line correction of the combustion air by direct measurement of o2. this maintains the measured oxygen value at 3%, which is the recommended value to ensure complete combustion of natural gas. a control strategy was implemented to achieve the measure as shown in figure 11. in addition, another decision to the three measures presented above to improve the process performance, the feed water was increased from 70°c to 90°c, correcting steam leaks, and correcting steam trap leaks under a practical control loop as shown in figure 12, where the basic components of control systems are presented to regulate the operation of the boiler. 4. environmental impact analysis the environmental impact analysis is based on the reduction of co2 presented by applying each of the strategy and the energy improvements on the process as shown in figure 13; a reduction of the generation pressure to 2%, reduction of purge to 0.66% and finally control strategy to 3%. all these percentage are based on savings in the average consumption of natural gas. for each sub-process, the potential environmental impact was evaluated in relation to each improvement suggested. in this analysis, the subprocess that stops emitting lower ranges of emission related to the category of climate change in units of kg of co2 corresponds to chemical refining 213,849 kg of co2, 215,829 kg of co2 and 211,869 kg of co2 for each strategy implemented respectively. the sub-process with the greatest impact is the physical refinement with 853,418 kg of co2, 865,299 kg of co2 and 843,518 kg of co2 for each strategy implemented. these results are consequence of the longest duration and higher energy consumption of the process. 5. conclusions this study allowed to find three important opportunities for improvement in the boiler, thus obtaining possibilities for increasing its performance, as well as reducing production costs and reducing the environmental impacts that were previously presented. as for the energy saving potentials obtained, which were evaluated using the tools available in the iso 50001 energy efficiency standard, it was found that this boiler has a good level of measurement in its energy. however, the plant lacks policies at company level that prioritize energy efficiency and continuous improvement of energy performance in relation to the production process and production indicators are designed without taking into account energy consumption, which is reflected in total savings ochoa, et al.: energy optimization of industrial steam boiler using energy performance indicator international journal of energy economics and policy | vol 9 • issue 6 • 2019116 potentials identified about 20% per month, equivalent to 186,633 m3/month of natural gas without technological change. through the elaboration of an action plan it was possible to contemplate a set of measures for operational control, maintenance management and production management, which do not require the purchase of technologies, but the introduction into the company’s organizational management of new energy performance indicators and energy performance management tools, established as requirements in the new international and national standard iso 50.001. to reduce the energy consumption of the steam boiler, some measures were implemented based on the study, such as the reduction of the generation pressure from 250 to 180 psig thus achieving a saving of 2%, the automation of the purges in the boiler guarantees the value recommended by the une-9075/85 and a saving of 0.66%, and finally the correction in the supply line of the combustion air obtaining an oxygen value measured of 3% which is the recommended value for the combustion of natural gas. furthermore, using a methodology dependent on a global assessment of the process, it can be structured and implemented by improving the management of energy systems, reducing co2 emissions and contributing to the control of climate change, as proposed by iso 50001. references arens, m., worrell, e. (2014), diffusion of energy efficient technologies in the german steel industry and their impact on energy consumption. energy, 73, 968-977. arıoğlu, a.m.ö., dhavale, d.g., sarkis, j. (2017), greenhouse gas emissions in the construction industry: an analysis and evaluation of a concrete supply chain. journal of cleaner production, 167, 1195-1207. baldi, s., le quang, t., holub, o., endel, p. (2017), real-time monitoring energy efficiency and performance degradation of condensing boilers. energy conversion and management, 136, 329-339. barma, m.c., saidur, r., rahman, s.m.a., allouhi, a., akash, b.a., sait, s.m. (2017), a review on boilers energy use, energy savings, and emissions reductions. renewable and sustainable energy reviews, 79, 970-983. behbahaninia, a., ramezani, s., hejrandoost, m.l. (2017), a loss method for exergy auditing of steam boilers. energy, 140, 253-260. bui, b.b., de villiers, c. (2017), carbon emissions management control systems: field study evidence. journal of cleaner production, 166, 1283-1294. cardenas, e.y., valencia, o.g., meriño, s.l. (2017), application of an energy management system to develop an energy planning in a pickling line. contemporary engineering sciences, 10(16), 785-794. carder, d., ryskamp, r., besch, m., thiruvengadam, a. (2017), emissions control challenges for compression ignition engines. procedia iutam, 20, 103-111. cucchiella, f., gastaldi, m., miliacca, m. (2018), the management of greenhouse gas emissions and its effects on firm performance. journal of cleaner production, 167, 1387-1400. dal secco, s., juan, o., louis-louisy, m., lucas, j.y., plion, p., porcheron, l. (2015), using a genetic algorithm and cfd to identify low nox configurations in an industrial boiler. fuel, 158, 672-683. fahad, m., naqvi, s.a.a., atir, m., zubair, m., shehzad, m.m. (2017), energy management in a manufacturing industry through layout design. procedia manufacturing, 8, 168-174. feng, t., yang, y., xie, s., dong, j., ding, l. (2017), economic drivers of greenhouse gas emissions in china. renewable and sustainable energy reviews, 78, 996-1006. fiedler, t., mircea, p.m. (2012), energy management systems according to the iso 50001 standard &#x2014; challenges and benefits. in: 2012 international conference on applied and theoretical electricity (icate). p1-4. garcía, p.m., vakkilainen, e., hyppänen, t. (2016), unsteady cfd analysis of kraft recovery boiler fly-ash trajectories, sticking efficiencies and deposition rates with a mechanistic particle reboundstick model. fuel, 181, 408-420. geng, y., we, c., zhe, l., anthony, s.f.c., wenyi, h., zhiqing, l., shaozhuo, z., yiying, q., wei, y., xiaowei, c. (2017), a bibliometric review: energy consumption and greenhouse gas emissions in the residential sector. journal of cleaner production, 159, 301-316. habib, m.a., hasanuzzaman, m., hosenuzzaman, m., salman, a., mehadi, m.r. (2016), energy consumption, energy saving and emission reduction of a garment industrial building in bangladesh. energy, 112, 91-100. hwang, k.l., choi, s.m., kim, m.k., heo, j.b., zoh, k.d. (2017), emission of greenhouse gases from waste incineration in korea. journal of environmental economics and management, 196, 710-718. iso (international organization for standardization). (2011), iso 50001 energy management systems-requirements with guidance for use. geneva, switzerland: iso central secretariat. jayamaha, l. (2006), energy-efficient building systems: green strategies for operation and maintenance. new york: mcgraw-hill. jovanović, b., filipović, j. (2016), iso 50001 standard-based energy management maturity model proposal and validation in industry. journal of cleaner production, 112, 2744-2755. junga, r., chudy, p., pospolita, j. (2017), uncertainty estimation of the efficiency of small-scale boilers. measurement, 97, 186-194. kumar, a., subramanian, k.a. (2017), control of greenhouse gas emissions (co2, ch4 and n2o) of a biodiesel (b100) fueled automotive diesel engine using increased compression ratio. applied thermal engineering, 127, 95-105. lloyd, s.a., bur, c., lappalainen, j., andersson, a., huotari, j., bjorklund, r., jantunen, j. (2013), chemical sensor systems for emission control from combustions. sensors and actuators b: chemical, 187, 184-190. may, g., barletta, i., stahl, b., taisch, m. (2015), energy management in production: a novel method to develop key performance indicators for improving energy efficiency. applied energy, 149, 46-61. mecrow, b.c., jack, a.g. (2008), efficiency trends in electric machines and drives. energy policy, 36(12), 4336-4341. meschede, h., dunkelberg, h., stöhr, f., peesel, r.h., hesselbach, j. (2017), assessment of probabilistic distributed factors influencing renewable energy supply for hotels using monte-carlo methods. energy, 128, 86-100. miremadi, i., saboohi, y., jacobsson, s. (2018), assessing the performance of energy innovation systems: towards an established set of indicators. energy research and social science, 40, 159-176. moran, m.j., saphiro, h.n., boettner, d.d., bailey, m.b. (2011), fundamentals of engineering thermodynamics. new york: wiley. nakano, k., naoki, s., toshifumi, n., keisuke, s., hirotaka, k., masahiro, i., nobuaki, h. (2016), greenhouse gas emissions from round wood production in japan. journal of cleaner production, 170, 1654-1664. nikula, r.p., ruusunen, m., leiviskä, k. (2016), data-driven framework for boiler performance monitoring. applied energy, 183, 1374-1388. ochoa, et al.: energy optimization of industrial steam boiler using energy performance indicator international journal of energy economics and policy | vol 9 • issue 6 • 2019 117 pambudi, n.a., fasola, m., lukad, v.p., ria, l., danar, s.w., muhammad, m., lip, h.s. (2017), performance evaluation and optimization of fluidized bed boiler in ethanol plant using irreversibility analysis. case studies in thermal engineering, 10, 283-291. santín, i., barbu, m., pedret, c., vilanova, r. (2017), control strategies for nitrous oxide emissions reduction on wastewater treatment plants operation. water research, 125, 466-477. shen, b., han, y., price, l., lu, h., liu, m. (2017), techno-economic evaluation of strategies for addressing energy and environmental challenges of industrial boilers in china. energy, 118, 526-533. skiba, y.n., parra-guevara, d. (2013), control of emission rates. atmosfera, 26(3), 379-400. valencia, o.g. (2011), informe de decisión estratégica, 2016. international organization for standardization, iso 50001. valencia, o.g., cardenas, y., ramos, e., morales, a., campos, j.c. (2017), energy saving in industrial process based on the equivalent production method to calculate energy performance indicators. chemical engineering transactions, 57, 709-714. zhang, n., lu, b., wang, w., li, j. (2010), 3d cfd simulation of hydrodynamics of a 150 mwe circulating fluidized bed boiler. the chemical engineering journal, 162(2), 821-828. international journal of energy economics and policy vol. 4, no. 4, 2014, pp.735-743 issn: 2146-4553 www.econjournals.com 735 international energy security indicators and turkey’s energy security risk score gelengul kocaslan department of economics, faculty of economics, istanbul university, turkey. email: kocaslan@istanbul.edu.tr abstract: energy security has been a priority for many countries. what makes energy security that important is; its bilateral relationship with economic, political, social, environmental sustainability and military issues. as an inevitable consequence of globalization cooperation in the field has been a must and it is required international energy security indicators to make energy security risk evaluations in order to establish adequate policies. the aim of the study is to review energy security within the concept of international energy security indicators, international energy security risk index, international energy security rankings and to reveal turkey’s energy security risk summary emphasizing the components of energy security issue. keywords: energy security indicators; energy security risk. jel classifications: f50; q40. 1. introduction energy is vital for sustainable development and sustainability is not only at the heart of development, but also of economic, environmental, social and military policies. to ensure the sustainability of the policies “security” appears as a mandatory objective to achieve. furthermore, recent crises prooved that energy security must be considered in national and international energy policies and related strategies. energy security is briefly defined as the uninterrupted availability of energy sources at an affordable price taking account environmental concerns and sustainable development. to form national and international energy policies considering energy security requires international indicators. international index of energy security risk allows to make comparisons between countries. because energy security risk is a multifaceted issue; international energy security risk scores and international energy security rankings reflect countries’ factors of energy security including diversification of source, relationship among nations, environmental acceptability, sufficiency relative to demand, accessible/available/affordable/competitive/reliable/uninterruptible supply. risks are classified as physical, economic, political, regulatory, social, environmental reminding the threats like human intervention, equipment failure and extreme weather. the energy security indicators; international energy security risk scores and international energy security rankings are influenced by mentioned risks and threat. following that international energy security risk scores and international energy security rankings affect economic, political, social and environmental indicators reciprocatively. the rest of paper is organized as follows. in section 2 several energy security definitions are presented. international energy security indicators are presented in section 3. section 4 examines international energy security risk index. section 5 considers international energy security rankings and turkey’s energy security risk. the final section concludes. 2. the components of energy security energy security is a complex issue with its multiple dimensions. currently energy security is not only at the heart of the national and international energy policies, but also at the heart of the national and international security policies. to better understand why, it is needed to clarify the components of the energy security. international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.735-743 736 the iea defines energy security as the uninterrupted availability of energy sources at an affordable price and examines it in the short and long terms (iea, 2014a): in the long term, energy security concerns with timely investments to supply energy in accordance with economic development and sustainable environmental needs,  in the short term, energy security focuses on the ability to react promptly to sudden changes in the supply-demand balance. world coal association considers resource availability for the long term and relates short-term security to supply disruptions of the primary fuel or of the generated electricity (wca, 2014). world economic forum (wef) global agenda council on energy security and yueh (yueh, 2010:216) defined energy security as the reliable, stable and sustainable supply of energy at affordable prices and at an acceptable social cost. the european commission’s (2000) defined energy security as the “the uninterrupted physical availability of energy products on the market, at a price which is affordable for all consumers (private and industrial), while respecting environmental concerns and looking towards sustainable development, as enshrined in articles 2 and 6 of the treaty on european union”. yergin (2006) defined energy security as the availability of sufficient supplies at affordable prices. winzer claimed that “secure energy means that the risks of interruption to energy supply are low” (winzer, 2011:4). shih suggests that energy security is assured when a nation can reliably, economically, environmentally and safely deliver energy in sufficient quantities to support growing economy and defense needs (shih, 2014). ). bohi and toman (1996) drew attention to the lack of energy security and defined energy insecurity as “the loss of economic welfare that may occur as a result of a change in the price or availability of energy.” in point of fact the meaning of energy security differentiates from countrys’ dependence to their energy imports. accordingly; countries which are highly dependent on imported oil and gas adheres energy security to supply whereas, countries which export oil and gas adheres energy security to demand (tippee, 2014). this variability of the definition of energy security is also stressed by m uller-kraenner ( 2008 ), kruyt et al. ( 2009 ) and chester ( 2010 ). however, all of the definitions of energy security includes availability, sufficiency, affordability, welfare, energy products (or supplies) and interruptions as common points. figure 1 shows the components of energy security. figure 1. factors of energy security diversification of source relationship among nations environmental acceptability accessible/available supply sufficiency relative to demand affordable/competitive supply reliable/uninterruptible supply source: iea (2014a), tippee (2014). 3. international energy security indicators measuring energy security requires indicators. to determine indicators it is needed to determine threats to energy security. the indicators of energy security are summarized below which are determined considering these threats like human intervention, equipment failure and extreme weather (post, 2012): energy resources 1-supply and prices can be disrupted by political action. 2-energy security is threatened by the depletion of conventional oil reserves. 3-restricted rezerves of oil and gas threatens energy security. 4-import dependence is an indicator of reduced energy security. 5-a more diverse energy system contributes energy security. infrastructure electricity networks can be damaged by bad weather. energy security international energy security indicators and turkey’s energy security risk score 737 demand gas demand can be difficult to meet in a cold winter’s day. 1-overall energy demand 2-energy demand per home or unit of economic activity 3-energy costs as a proportion of total expenditure 4-capacity for demand side response it is also required energy security metrics for international index. energy security metrics used in international index are classified as global fuels, fuel ımports, energy expenditure, price&market volatility, energy use ıntensity, electric power sector, transportation sector and enviromental (u.s. chamber of commerce, 2013:68): “global fuels: measure the reliability and diversity of global reserves and supplies of oil, natural gas and coal. higher reliability and diversity mean a lower risk to energy security. fuel imports: measure the exposure of the national economies to unreliable and concentrated supplies of oil, natural gas and coal. higher supply reliability and diversity and lower import levels mean a lower risk to energy security. energy expenditure: measure the magnitude of energy costs to national economies and the exposure of consumers to price shocks. lower costs and exposure mean a lower risk to energy security. price & market volatility: measure the susceptibility of national economies to large swings in energy prices. lower volatility means a lower risk to energy security. energy use intensity: measure energy use in relation to population and economic output. lower use of energy by industry to produce goods and services means a lower risk to energy security. electric power sector: measure indirectly the reliability of electricity generating capacity. higher diversity means a lower risk to energy security. transportation sector: measure efficiency of energy use in the transport sector per unit of gdp and population. greater efficiency means a lower risk to energy security. enviromental: measure the exposure of national economies to national and international greenhouse gas emission reduction mandates. lower emissions of carbon dioxide from energy mean a lower risk to energy security.” it is important for the indicators to reflect all of the components adequately. energy intensity, energy dependency for different energy sources (oil, gas,…), reserves-to-production ratios (oil, gas,…), energy price (oil price), share of biofuels in road transport are the most popular indicators of energy security (badea 2010): energy intensity = tpes / gdp energy dependency for different energy sources (oil, gas,…) = import / gross inland energy (%) reserves-to-production ratios (oil, gas,…) = proven reserves / primary production (y) share of biofuels in road transport=biofuel consumption /petrol & diesel consumption (%) following figures 2 and 3 illustrate the schematic diagrams for crude oil and natural gas security with indicators respectively. figure 2. schematic diagram for crude oil security with indicators source: iea (2014b). international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.735-743 738 figure 3. schematic diagram for natural gas security with indicators source: iea (2014b). energy security indicators are also the strategies for enhancing energy security (badea 2010): increasing the number of fuels and technologies,  increasing the number of suppliers for each fuel (especially if imported),  developing storage capacity for different fuels,  using endogenous energy resources, increasing energy efficiency and conservation. 4. international energy security risk index as an inevitable consequence of globalization, the energy systems of the countries has been interconnected tightly. this means that energy policies cannot be considered seperately anymore. when this is the case each step will affect another and international analysis becomes a must in the field. “the international index of energy security risk” allows us to compare energy security risks between countries, country groups and shows the change in energy security risks over time using two indicators; energy security risk scores and international energy security rankings in absolute terms and relative to a baseline average of the oecd countries (u.s. chamber of commerce, 2013:65). likewise, the european union gives priority to the security of energy. the commission’s green paper classifies risk as physical, economic, political, regulatory, social, environmental in the energy arena and explains the sources of risk as below (labandeira and manzano, 2014): physical risks: distinguishing between permanent disruption (due to stoppages in energy production or to exhaustion of energy resources) and temporary disruptions (due to geopolitical crisis or natural disasters). economic risks: caused by volatility in energy prices after imbalances between demand and supply. political risks: brought about by energy exporting countries that intend to employ energy deliveries as a political weapon. regulatory risks: due to poor regulations in domestic markets and regulatory variability in exporting countries (both in terms of security of energy investments and of security of supply contracts). social risks: due to social conflicts linked to continuous increases in energy prices. environmental risks: related to the energy sector (oil spills, nuclear accidents, etc.) and may cause serious environmental damages. in figure 4, the extents of energy security referring to the sources of risk are showed. the iea has developed the model of short-term energy security (moses), a tool to inform energy-security policies through quantifying vulnerabilities of energy systems and based on a set of quantitative indicators that measures risks and resilience of security of energy supply in iea countries (iea, 2014b). table 1 shows crude oil, oil products, natural gas, coal, hydropower and nuclear power under the categorization of dimension and indication using iea, oecd, worldbank and various national sources. according to the table, energy sources’ risk and resilience are analyzed both domestically and externally. and then external-domestic risk-resilience are explained as indicators. international energy security indicators and turkey’s energy security risk score 739 figure 4. extents of energy security referring to the sources of risk source: winzer (2011:10). table 1. risk and resilience indicators used in moses source: iea (2014b). international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.735-743 740 5. international energy security rankings and turkey’s energy security risk summary international energy security risk scores and international energy security rankings of the countries, allow to make an evaluation about their energy security risk potentials. table 2 shows energy security risk scores and rankings for 25 large energy-consuming countries. the table enables us to compare countries’ energy security risk scores against each other and the oecd average in 2012. the highest (best) rank has the lowest numerical risk score and the lowest (worst) rank has the highest numerical risk score. as it is; norway is the most energy secure country since 2001. with a risk score 1,194; turkey exceeds oecd average which is 1,051. table 2. energy security risk scores and rankings for 25 large energy using countries (2012) source: u.s. chamber of commerce (2013:9). table 3 provides evidence that countries’ energy security rankings exhibit steady tendency. the country having a good energy security rank seems to maintain it and vice-versa. u. s. chamber of commerce states that the fall in energy security risks of the countries’ are related to lower energy prices and expenditure volatility in the corresponding years. the table shows that ukraine was the least energy secure country in the large energy user group with a score of 2,250, which is 114% above the oecd average. meeting 26 % of the total energy demand by domestic resources turkey aims to (mfa, 2014) “diversify its energy supply routes and source countries, increase the share of renewables and include the nuclear in its energy mix, take significant steps to increase energy efficiency, contribute to europe’s energy security”. international energy security indicators and turkey’s energy security risk score 741 table 3. energy security rankings for large energy user group 1980-2012 source: u.s. chamber of commerce (2013:12). turkey is a natural energy corridor between the middle east and the caspian basin and europe in consequence of its geographical location. turkey plays a critical role for europe aiming to diversify its energy suppliers for natural gas. turkey has already the potential to become an important hub for oil and gas transported through pipelines blue stream for russian gas, btc for caspian oil and gas, the interconnector to greece and links to iran and iraq (barysch, 2014). for this reason turkey has a key position for europe’s energy security. figure 5 presents natural gas pipelines considering turkey’s location. figure 5. natural gas pipelines source: european commission (2014). international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.735-743 742 the last table group (table 4) shows turkey’s energy security risk summary, turkey’s and oecd’s risk index scores and turkey’s energy security risk variance from oecd respectively. the table shows that turkey’s energy security risk score was 1,194 in 2012 whereas energy security risk score was 1,268 in the previous year. however large energy user group ranks remain stable; 15 both in 2011 and 2012. turkey’s energy security risk score was 875 in 1980 and the same value in 2012 is 319 points more than that score. besides turkey had the best energy security risk score in 1985 which is 777, and the worst energy security risk score 1,268 in 2011. the table provides evidence that turkey’s overall energy security risk scores have risen fast implementing the lowest (worst) energy security large energy user group rank. table 4. turkey’s energy security risk summary source: u.s. chamber of commerce (2013:56). 6. conclusion being one of the main targets of national and international energy policies; energy security is of interest to all nations. the reason of the close interest is the reflection of energy security in political actions. allowing to compare energy security risks between countries, country groups and showing the change in energy security risks over time; “the international index of energy security risk” uses two indicators energy security risk scores and international energy security rankings. international energy security risk scores and international energy security rankings are determinants for the future routes of the policy makers. they give an idea about countries’ economic, political, social, environmental structure. thus score and ranking values have multidimensional effects on trade, investment, energy agreements and contracts. on the other hand, international energy security risk scores and international energy security rankings serve to enhance energy security. turkey’s best energy security risk score was in 1985; 777. on the other hand in 2011 turkey had the worst energy security risk score which was 1,268. in 2012; the energy security risk score of turkey was 1,194 which is less than the previous year’s, but is still high. because energy security risk score is an indicator of economic, political, social and environmental risk as well; it denotes the problems in the related fields. since therefore economic, political, social and environmental improvements will be reflected in the energy security risk score and vice-versa. international energy security indicators and turkey’s energy security risk score 743 references badea, a.c. (2010), energy security indicators. available at: http://www.drustvotermicara.com/resources/files/7fa5460.pdf, (23. 04. 2014). barysch, k. turkey’s role in european energy. http://www.cer.org.uk/sites/default/files/publications/attachments/pdf/2011/essay_turkey_energ y_12dec07-1381.pdf, (17.05.2014). bohi, d.r., toman, m.a. (1996), the economics of energy security. massachusetts: kluwer academic publishers. chester, l. (2010), conceptualising energy security and making explicit its polysemic nature. energy policy, 38(2), 887 – 895. cornell, p. (2012), regional and international energy security dynamics: consequences for nato’s search for an energy security role. gcsp geneva papers, research series 5. iea. (2014a). http://www.iea.org/topics/energysecurity/subtopics/whatisenergysecurity/, (19.06.2014). iea. (2014b) http://www.iea.org/publications/freepublications/publication/moses.pdf, (19.06.2014b). kruyt, b. , van vuuren, d.p., de vries, h.j. m., groenenberg, h. (2009), indicators for energy security. energy policy, 37(6), 2166–2181. labandeira, x., manzano, b. (2012), some economic aspects of energy security. http://www.eforenergy.org/docpublicaciones/documentos-de-trabajo/wp092012.pdf, (23.06.2014). mfa (republic of turkey ministry of foreign affairs). http://www.mfa.gov.tr/turkeys-energystrategy.en.mfa (12.08.2014). müller-kraenner, s. (2008), energy security: re-measuring the world. uk: earthscan. shih, w-c. (2014) energy security, gatt/wto, and regional agreements. http://lawlibrary.unm.edu/nrj/49/2/05_433-484.pdf, (11.05. 2014). the european commission. (2000), green paper towards a european strategy for the security of energy supply (com(2000) 769 final). the european commission. http://ec.europa.eu/enlargement/pdf/european_energy_policy/turkeys_energy_strategy_en.pdf, (11.06.2014). the parliamentary office of science and technology (post). (2012), measuring energy security, 399. tippee, b. (2012), defining energy security. http://www.ogj.com/articles/print/vol-110/issue1c/regular-features/journally-speaking/defining-energy-security.html, (06.07.2014). u.s. chamber of commerce. (2013), international index of energy security risk assessing risk in a global energy market. wca (world coal association). http://www.worldcoal.org/, (22.05.2014). winzer, c. (2011), conceptualizing energy security. eprg working paper 1123, cambridge working paper in economics, 1151, 1-36. world economic forum (wef). global agenda council on energy security. http://www3.weforum.org/docs/gac/2013/wef_gac_energysecurity_report.pdf, (22.05.2014). yergin, d. (2006), ensuring energy security. foreign affairs, 85(2), 69-82. yueh, l. (2010), an international approach to energy security. global policy, 1(2),216-217. . international journal of energy economics and policy | vol 10 • issue 3 • 2020 365 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(3), 365-368. financial liquidity management strategies in polish energy companies grzegorz zimon* department of finance, banking and accounting, rzeszow university of technology, al. powstancow warszawy 12, rzeszow 35-959, poland. *email: gzimon@prz.edu.pl received: 26 december 2019 accepted: 15 february 2020 doi: https://doi.org/10.32479/ijeep.9150 abstract financial liquidity is the foundation for building a strong enterprise. every small or large enterprise, regardless of the industry, needs to have financial liquidity to grow. its management is complicated as it is related to current assets, short-term liabilities and profitability. the existing relationship between profitability and liquidity makes it very difficult to choose the right liquidity management strategy. the purpose of the article is to analyze the strategy of managing liquidity in state-owned enterprises operating in the energy sector. in this industry in poland in recent years there has been a high increase in costs related to fees for co2 emissions, which will have the large impact on the profitability of enterprises, which will hinder the choice of financial liquidity management strategies. the specificity of the industry, the form of ownership of the analyzed enterprises and the government’s policy will also have a significant impact on the shape of the liquidity management policy. the analysis was based on the financial statements for 2015-2018. keywords: financial liquidity, energy companies, strategy jel classifications: g10, g33, q43 1. introduction management of a large, small, private or state-owned enterprise is constantly building a strategy that is supposed to ensure financial security and profits for the owners. these two elements of financial liquidity and profitability are one of the most important measures of the company’s position in the market. managers of enterprises in virtually every industry must decide in which direction lead the company, if in the direction of the highest possible profits or to keep primarily the company safely in the market. the exception here may be certain state-owned enterprises, which in the event of poor financial results may be financially supported by the state. company managers are aware that it is simply impossible to maintain high liquidity and profitability at the same time as the decisions taken to increase financial liquidity will automatically reduce profitability and vice versa. we are constantly looking for solutions that will allow us to maintain safe financial liquidity and increase profitability. when increasing profitability, the key to success is rational cost management. the introduction of appropriate systems and tools that will lead to optimization of the level of costs in all areas of the enterprise without the emergence of threats related to the loss of financial liquidity. in turn, in the case of liquidity management, managers may have more problems maintaining it at an appropriate level. it is related to the fact that liquidity management is the management of short-term liabilities, inventory and short-term receivables as well as cash. therefore, appropriate strategies are created for individual components that build financial liquidity, which create financial liquidity strategies. therefore, each of these elements should be analyzed separately. still differently, the situation of creating a liquidity management strategy will look in state-owned enterprises operating in the energy sector, in which the risk of losing financial liquidity should not appear. this is due to the specifics of the industry. the purpose of the article is to evaluate and analyze financial liquidity management strategies in polish state-owned enterprises operating in the energy sector. this journal is licensed under a creative commons attribution 4.0 international license zimon: financial liquidity management strategies in polish energy companies international journal of energy economics and policy | vol 10 • issue 3 • 2020366 2. literature review there are authors who believe that the most important factor driving sustainable energy commercialization is the availability of complementary resources such as knowledge or capital (aram et al. 1992; kaufmann and todtling, 2002; karytsas and choropanitis, 2017; engelken et al., 2016; darmani et al. 2014). enterprises, however, primarily need money and a stable financial position to develop. stability is financial security. lack of financial security may be the most important development barrier for enterprises. generally, in the energy sector literature the most important development barriers are the complexity of technologies, climate change, climate policy, the shortage of qualified personnel, the lack of knowledge and experience in marketing and communication, the lack of know-how technology (foxon et al., 2005; del río et al. 2018; cagno et al., 2013; di foggia, 2016; dahlqvist and soderholm; 2019; zimon, 2019) and the lack of financial resources (meijer et al., 2019) however, the lack of financial resources is certainly the most important barrier to the development of an enterprise. it is generally caused by mistakes made by the management in the area of current assets management and shortterm liabilities, i.e., the basic elements affecting financial liquidity. in the case of financial liquidity management, another difficulty in building an appropriate strategy is the large relationship between financial liquidity and profitability. in the literature, you can find a number of studies whose results clearly say that either an enterprise can maintain high financial liquidity or high profitability (ding et al. 2013; enqvist et al. 2014; vahid et al. 2012; bei and wijewardana, 2012; lind et al., 2012). this relationship applies to smes as well as large enterprises and virtually all industries (mun and jang, 2015; kieschnick et al. 2013; zimon, 2018). this correlation is confirmed by subsequent studies carried out by other authors on the example of belgian, greek and small and medium-sized spanish companies, (deloof, 2003; garcia-teruel and martinez-solano, 2007). trade credit is another important element often discussed in the literature strongly affecting liquidity management policy (long et al., 1993; deloof, 2003; shah, 2009). in the literature, one can often find the statement that working capital has a direct impact on the financial liquidity of an enterprise, therefore, by creating an appropriate working capital management strategy for manufacturing enterprises, it is worth supporting the working capital management strategy (opler et al., 1999; zimon and zimon, 2019; aktas et al., 2015). the characteristics of the main liquidity management strategies are presented below. the first of these, the conservative strategy, is the one that guarantees maintaining high financial liquidity. production companies often carry out production for specific orders. therefore, in the case of inventory management in production units, inventory will generally be at an optimal level. conservative debt management will be based on quick collection. a secure approach to managing receivables and payables to suppliers will certainly be applied. receivables turnover in days must be definitely shorter than liabilities turnover in days. commitments will be paid on time. the conservative strategy in manufacturing enterprises will have a model level of financial liquidity. inventories will not increase financial liquidity ratios, unless security reserves are created, which will result in excess liquidity. the aggressive strategy is a risky strategy characterized by low financial liquidity. its basic assumption is to extend the repayment deadlines, the company will want to gain new contractors with an attractive trade loan. short-term liabilities will increase in the liabilities structure. short-term investments will be at a very low level, if there is free cash, they will be immediately intended to settle short-term liabilities. the third type is the moderate strategy of working capital management. this type of management is an intermediate strategy between conservative and aggressive. moderate strategies will be very similar to earlier strategies. the only change that can be seen will be in the management of receivables from customers. a conservative strategy is a strict control of the level of receivables and contractors, an aggressive strategy is practically lacking. 3. research methodology the analysis was conducted on a group of four polish largest stateowned energy companies. these companies provide energy for the whole of poland. the financial statements for 2015-2018 were used in the research. in order to determine the financial liquidity management strategy, an analysis was carried out using selected financial ratios. 4. results the first and also the basic measure used in the analysis was the current financial liquidity ratio. it informs about the capacity to cover current liabilities (footnote). table 1 presents the results for the current financial liquidity ratio in individual years. when assessing the results of current financial liquidity ratios in individual years, it can be seen that there is a decrease in financial liquidity. one enterprise has high financial liquidity, two in turn achieve results on the border of financial liquidity. based on such a general ratio, it is difficult to assess liquidity management strategies. the second ratio that was used to assess the liquidity management strategy is the quick liquidity ratio. the detailed results are presented in table 2. the results of this ratio clearly indicate the fact of having high cash and receivables in the structure of current assets. these results are slightly lower than the results of current financial liquidity. another ratio used in the analysis concerned the credit position assessment. the details are presented in table 3. when assessing credit position ratios, it is clear that all companies are a borrower. short-term liabilities exceed receivables from customers in each of the periods analyzed. this is mainly due to the specifics of the industry. consumers pay for energy on time to avoid criminal interest, payment periods are also short. in turn, companies operating in the energy sector obtain long deadlines to pay their liabilities, which translates into their position, they are a borrower and use the cheapest sources of financing, which are liabilities to suppliers. zimon: financial liquidity management strategies in polish energy companies international journal of energy economics and policy | vol 10 • issue 3 • 2020 367 the results presented in table 4 in the analyzed enterprises are at a similar level. the time of flow of receivables from customers should be assessed as short. in the case of assessing the management of short-term receivables, it is important to compare their flow with the results of payables turnover towards suppliers. the results of the payables turnover ratio towards suppliers are presented in table 5. these results confirm the position of borrowers of the enterprises analyzed. they collect receivables from customers much faster compared to the dates of repayment of liabilities towards suppliers. another important ratio allowing to assess the liquidity management strategies that was used for the analysis is the inventory turnover in days. the details are presented in table 6. inventory turnover results in days are low, due to low inventory levels. this level of inventories was confirmed by comparing financial liquidity ratios with quick financial liquidity. table 7 presents the results of the cash conversion cycle (ccc). literature on managing liquidity and working capital contained the statement that companies can increase their profitability by shortening ccc (shin and soenen, 1998; deloof and jegers, 1996; lazaridis and tryfonidis, 2006; grosse-ruyken et al., 2011). the analysis conducted indicates a very low level of ccc, in many cases a negative ccc appears. a negative ccc arises when an enterprise and by ordering goods and services is able to sell them faster and receive payment than is the time of payment for these goods, materials to suppliers. 5. conclusion t h e a n a l y s i s c o n d u c t e d i n d i c a t e s a s a f e s t r a t e g y o f moderate conservative financial liquidity management. the results of the basic ratio of current financial liquidity do not clearly indicate this type of strategy, as for some enterprises the result for financial liquidity is below one. however, this in-depth analysis indicates safe management of financial liquidity. the first ratio of a conservative strategy is the high results of the quick liquidity ratio. then, a clearly faster period of inflow of receivables from customers compared to the rotation of liabilities in days confirms a safe liquidity management policy. this is confirmed by the assessment of the credit position, which clearly indicates the advantage of short-term liabilities over short-term receivables. another confirmation of conservative management is the ccc, which is generally negative. its result shows that enterprises benefit to a large extent from short-term liabilities as a source of financing. the high level of these commitments necessitates the qualification of financial liquidity management strategies in the enterprises analyzed as moderate-conservative. short-term liabilities, which significantly exceed receivables from recipients, low financial liquidity ratios do not allow to define the analyzed strategy as conservative. it is exposed to the risk of a high level of short-term liabilities, which should be systematically table 1: results of the current financial liquidity ratio in the enterprises analyzed current financial liquidity ratio 2018 2017 2016 2015 2014 company 1 2.3 2.4 1.7 2.1 2.5 company 2 1.5 1.5 2.0 2.4 2.1 company 3 0.9 1.0 0.9 1.2 1.0 company 4 0.9 1.7 1.6 1.9 1.9 source: author’s own research table 2: results of the quick ratio in the enterprises analyzed quick ratio 2018 2017 2016 2015 2014 company 1 2.2 2.1 1.4 2 1.2 company 2 1.2 1.1 1.6 2 1.7 company 3 0.7 0.9 0.6 0.9 0.9 company 4 0.6 1.2 1.0 1.2 1.6 source: author’s own research table 3: credit position ratio in the enterprises analyzed credit position ratio 2018 2017 2016 2015 2014 company 1 0.53 0.79 0.85 0.79 0.75 company 2 0.50 0.60 0.74 0.87 0.85 company 3 0.43 0.50 0.43 0.41 0.50 company 4 0.41 0.53 0.62 0.47 0.50 source: author’s own research table 4: results of the short-term receivables turnover ratio in days in the enterprises analyzed short-term receivables turnover ratio in days 2018 2017 2016 2015 2014 company 1 55 67 67 57 50 company 2 60 58 58 62 56 company 3 44 42 39 40 42 company 4 54 65 50 42 41 source: author’s own research table 5: results of the short-term liabilities turnover ratio in days in the enterprises analyzed short-term liabilities turnover ratio in days 2018 2017 2016 2015 2014 company 1 83 83 80 74 72 company 2 102 93 72 70 74 company 3 95 87 100 86 83 company 4 125 106 92 88 92 source: author’s own research table 6: results of the inventory turnover in days in the enterprises analyzed inventory turnover in days 2018 2017 2016 2015 2014 company 1 19 22 25 18 12 company 2 37 32 29 31 25 company 3 22 26 23 24 17 company 4 55 70 58 48 42 source: author’s own research table 7: results of the ccc in the enterprises analyzed ccc 2018 2017 2016 2015 2014 company 1 −9 6 13 −1 10 company 2 −5 −3 15 23 7 company 3 −18 19 −37 −22 −24 company 4 −16 29 16 3 −9 source: author’s own research. ccc: cash conversion cycle zimon: financial liquidity management strategies in polish energy companies international journal of energy economics and policy | vol 10 • issue 3 • 2020368 monitored. the presented analysis allows, however, to state that the analyzed units, despite significant increases in costs related to co2 emissions, will achieve high profitability. this will be affected by the low cash conversion cycle result and the long repayment period of short-term liabilities, which means using the cheapest source of financing for enterprises. references aktas, n., croci, e., petmezas, d.(2015), is working capital management value-enhancing? evidence from firm performance and investment. journal of corporate finance, 30, 98-113. aram, j.d., lynn, l.h., reddy, n.m. (1992), institutional relationships and technology commercialization: limitations of market based policy. research policy, 21(5), 409-421. bei, z., wijewardana, w. (2012), working capital policy practice: evidence from sri lankan companies. procedia social and behavioral sciences, 40, 695-700. cagno, e., worrell, e., trianni, a., pugliese, g. (2013), a novel approach for barriers to industrial energy efficiency. renewable and sustainable energy reviews, 19, 290-308. dahlqvist, a., soderholm, p. (2019), industrial energy use, management practices and price signals: the case of swedish process industry. international journal of energy economics and policy, 9(3), 30-45. darmani, a., arvidsson, n., hidalgo, a., albros, j. (2014), what drives the development of renewable energy technologies? toward a typology for the systemic drivers. renewable and sustainable energy reviews, 38, 834-847. del río, p., peñasco, c., mir-artigues, p. (2018), an overview of drivers and barriers to concentrated solar power in the european union. renewable and sustainable energy reviews, 81(1), 1019-1029. deloof, m. (2003), does working capital management affect profitability of belgium firms? journal of business finance and accounting, 30(3-4), 573-587. deloof, m., jegers, m. (1996), trade credit, product quality, and intragroup trade: some european evidence. journal of financial management association, 25(3),33-43. di foggia, g.d. (2016), effectiveness of energy efficiency certificates as drivers for industrial energy efficiency projects. international journal of energy economics and policy, 6(2), 273-280. ding, s., guariglia, a., knight, j. (2013), investment and financing constraints in china: does working capital management make a difference? journal of banking finance, 37(5),1490-1507. engelken, m., römer, b., drescher, m., welpe, i.m., picot, a. (2016), comparing drivers, barriers, and opportunities of business models for renewable energies: a review. renewable and sustainable energy reviews, 60, 795-809. enqvist, j., graham, m., nikkinen, j. (2014), the impact of working capital management on firm profitability in different business cycle: evidence from finland. research in international business and finance, 32(c), 36-49. available from: https://www.econpapers. repec.org/article/eeeriibaf. foxon, t.j., gross, r., chase, a., howes, j., arnall, a., anderson, d. (2005), uk innovation systems for new and renewable energy technologies: drivers, barriers and systems failures. energy policy, 33(16), 2123-2137. garcia-teruel, p.j., martinez-solano, p. (2007), effects of working capital management on sme profitability. international journal of managerial finance, 3(2), 164-177. grosse-ruyken, p.t., wagner, s.m., jonke, r. (2011), what is the right cash conversion cycle for your supply chain? international journal of services and operations management, 10(1), 13-29. karytsas, s., choropanitis, i. (2017), barriers against and actions towards renewable energy technologies diffusion: a principal component analysis for residential ground source heat pump (gshp) systems. renewable and sustainable energy reviews, 78, 252-271. kaufmann, a., todtling, f. (2002), how effective is innovation support for smes? an analysis of the region of upper austria. technovation, 22(3), 147-159. kieschnick, r., laplante, m., moussawi, r. (2013), working capital management and shareholders wealth. review of finance, 17(5), 1827-1852. lazaridis, i., tryfonidis, d. (2006), relationship between working capital manage-ment and profitability of listed companies in the athens stock exchange. journal of financial management and analysis, 19(1), 26-35. lind, l., pirttila, t., viskari, s., schupp, f., karri, t. (2012), working capital management in the automotive industry: financial value chain analysis. journal of purchasing and supply management, 18, 92-100. long, m., malitz, i.b., ravid, s.a. (1993), trade credit, quality guarantees, and product marketability. journal of the financial management association, 22(4), 117-127. meijer, l.l.j., huijben, j.c.c., van boxsteal, a., romme, a.g.l. (2019), barriers and drivers for technology commercialization by smes in the dutch sustainable energy sector. renewable and sustainable energy reviews, 112, 114-126. mun, s.g., jang, s.s. (2015), working capital, cash holding, and profitability of restaurant firms. international journal of hospital management, 48, 1-11. opler, t., pinkowitz, l., stulz, r., williamson, r. (1999), the determinants and implications of corporate cash holdings. journal of financial economics, 52, 3-46. shah, n.h. (2009), optimisation of pricing and ordering under the twostage credit policy for deteriorating items when the end demand is price and credit period sensitive. international journal of business performance and supply chain modelling, 1(2/3), 229-239. shin, h., soenen, l. (1998), efficiency of working capital management and corporateprofitability. financial practice and education, 8(2), 37-45. vahid, t.k., elham, g., mohsen, a.k., mohammadreza, e. (2012), working capital management and corporate performance: evidence from iranian companies. procedia social and behavioral science, 62, 1313-1318. zimon, d., zimon, g. (2019), the impact of implementation of standardized quality management systems on management of liabilities in group purchasing organizations. quality innovation prosperity, 23(1), 60-73. zimon, g. (2018), influence of group purchasing organizations on financial situation of polish smes. oeconomia copernicana, 9(1), 87-104. zimon, g. (2019), an assessment of the strategy of working capital management in polish energy companies. international journal of energy economics and policy, 9(6), 552-556. . international journal of energy economics and policy | vol 10 • issue 3 • 2020340 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(3), 340-347. technical efficiency of thermal electricity generators in kenya grace njeru*, john gathiaka, peter kimuyu school of economics, university of nairobi, p.o box 30197 00100, nairobi, kenya. *email: gnjeru@ketraco.co.ke received: 12 december 2019 accepted: 15 february 2020 doi: https://doi.org/10.32479/ijeep.9102 abstract the government of kenya introduced energy sector reforms in the late 1990s aimed at improving efficiency in the supply of energy. after over two decades of reforms, there has been no comprehensive study to estimate the technical efficiency amongst electricity generators in kenya. this study examined 27 thermal electricity generating plants in kenya using data sourced from energy regulation commission for the period july 2015 to december 2017. the study applied two methods to estimate efficiency, viz., the stochastic frontier analysis and data envelope analysis. the results indicated that there is inefficiency in thermal power generation. the average efficiency score was 71% meaning the industry was missing its technical potential by about 29%. the plants experienced increasing returns to scale and were improving on efficiency and productivity. age and public ownership contributed to inefficiency while grid connection had a positive effect on efficiency. the government should encourage private investment in future power generation projects while at the same time increasing connection of the isolated areas to the national grid. the regulator should also revisit the current specific fuel targets used in determining the fuel pass through costs to consumers to encourage efficiency. keywords: technical efficiency, electricity generation, stochastic frontier analysis, data envelope analysis, kenya jel classifications: d24, l11, l25 1. introduction from the 1990s, the government of kenya embarked on power sector reforms. the objectives of the reforms were to commercialize energy services, increase operational efficiency and allow private investment in energy. unbundling reforms were initiated by the electric power act of 1997 that separated generation from transmission and distribution. the act also allowed private sector investment in generation through independent power producers (ipps) and established an independent regulator. kenya electricity generating company (kengen) the national electricity generator, would from henceforth compete with ipps. these reforms were expected to encourage competition with the aim of lowering electricity tariffs (republic of kenya, 2004). the first ipps in kenya were mainly thermal plants. by the year 2000 there were four ipps, three using fossil fuel and one using geothermal to generate electricity. the number of ipps has since increased to twelve with an installed capacity of 691mw of 76% are thermal power plants. kengen, the state owned generator, dominates generation contributing over 70% of the electricity (kplc, 2017). kengen mainly uses hydro technology and the government has invested heavily in this area. the electricity sector has been struggling with high tariffs that the government has attributed to low investments and operational inefficiencies (republic of kenya, 2004). this is despite the reforms that aimed at broadening generation and increasing efficiency in the supply of power (republic of kenya, 1997; 2004). consequently, the government has continued with more reforms aimed at improving efficiency in electricity supply and ensuring competitive power supply (republic of kenya, 2018). however, the reform agenda has been pursued without any study on the productive efficiency levels of firms involved in the supply of electricity. before this study, there was no comprehensive study on the efficiency levels of electricity generating power plants in kenya even though its known that efficiency brings competitive pricing. this study tried to fill this gap by evaluating the efficiency of electricity generators in kenya and examining this journal is licensed under a creative commons attribution 4.0 international license njeru, et al.: technical efficiency of thermal electricity generators in kenya international journal of energy economics and policy | vol 10 • issue 3 • 2020 341 the determinants of efficiency. in order to examine efficiency in similar technologies the study focused on thermal power plants. evidence on the operational efficiency of electricity generating plants and the determinants of efficiency in kenya is critical for future policy interventions, reforms and regulatory incentives. the information also benefits the ministry of energy in deciding whether future power projects should be implemented by public or private owned companies. 2. literature review productivity and efficiency measures assess the performance of decision making units. electricity generation plants produce a homogenous output that is electrical energy but their inputs differ based on the technology applied (jamasb, 2007). this means productivity and efficiency measures can be used to assess their performance for similar electricity generation technologies. several studies dating back to the 1990s have measured the productive efficiency of electricity generating companies. most of these studies use data envelope analysis (dea) and stochastic frontier analysis (sfa). golany et al. (1994) analyses the efficiency of 87 plants owned by israeli electric company and finds only 39 plants were efficient. chang and toh (2007) study for three electricity generation companies in singapore for the years 1999-2004 finds efficiency using sfa to be 90.35% and using dea to be 98.33%. shanmugam and kulshreshtha (2005) study for india’s 56 coal thermal based power plants finds the efficiency level to be on average 72.7%. a recent study by vijai (2018) for 20 coal power plants in india find a mean efficiency level of 88.2%. some studies have analysed efficiency for thermal industries using regions as the decision making unit. lam and shiu (2001) study for china’s thermal power generation industry using 30 provinces as the decision making units finds the average efficiency to be 88.8% in 1995 and 90.3% in 1996. fatima and barik (2012) also uses 14 states in india as the dmu in estimating efficiency of thermal plants, the study finds efficiency to average 80.35%. other studies focus on a comparative analysis of efficiency based on the ownership of the power plants. saleem (2007) studies 21 electricity generating plants in pakistan, 12 private and 9 public and finds a mean efficiency of 78%. public ownership is found to be affecting efficiency. this is finding is confirmed by a recent study by khan (2014) which finds ipps to be more efficient than public owned power plants. a study for spain by arocena and waddams (2002) find public owned generators to be more efficient than privately owned generators. efficiency analysis has also been used to analyse power generating plants in island and non-island locations. domah (2002) compares technical efficiency of fossil-fired generators in 16 small island economies and 121 investor owned generators in the us. the study finds no difference between islands and non-islands generators. riaz et al. (2013) study of the efficiency of asian energy firms using dea approach finds larger firms and those with more liquid assets more technically efficient. another area that has been studied is the impact of reforms on efficiency of plants. malik et al. (2011) studies the impact of unbundling on efficiency of state thermal power plants in india. using unbalanced panel of 385 coal electricity generating units for the years 1988-2009, the study finds that unbundling has not improved thermal efficiency. it has however improved plant availability and reduced outages. studies use electricity generated as output and capital, labour and fuel as the inputs (shanmugam and kulshreshtha, 2005; lam and shiu, 2001; fatima and barik, 2012; arocena and waddams, 2002; domah, 2002; vijai, 2018). studies using dea consider other outputs; operational availability, pollutant emissions, deviation from load and operation parameters (golany et al., 1994; arocena and waddams, 2002). other inputs considered include; internal power consumed by the plant, capital, manpower, fuel stock and all non-labour expenses (golany et al., 1994; fatima and barik, 2012). the studies also estimate the determinants of efficiency. some of the determinants identified include technical manpower, richness of the state and unbundling reforms (fatima and barik, 2012); size, liquidity and leveraging firms (riaz et al., 2013); capacity utilization (domah, 2002) and ownership (arocena and waddams, 2002; saleem, 2007; khan (2014). the literature reviewed is mainly from us, europe and asia and there is paucity of research in this area for the africa region. there is a research gap on the level of efficiency amongst electricity generators in kenya too. this study will add to literature by estimating the efficiency of electricity generators in kenya. 3. methodology parametric and non-parametric techniques are used to estimate firm level efficiency. dea is non-parametric and involves mathematical programming. sfa is parametric and involves econometric methods. following saleem (2007) and domah (2002) this study used dea and sfa methods in the analysis. 3.1. sfa battese and coelli (1995) specify an inefficiency model for panel data as; y x v uit it it it= + −exp( )β (1) where yit is the production of the i th firm (i = 1,2,…,n) at the tth observation (t = 1,2,…,t). xit is a vector of inputs of production for the ith firm at tth observation. β is a vector of unknown parameters to be estimated. vit are random errors and uit are random variables associated with inefficiency. uit is assumed to have a mean of zit δ where zit is a vector of explanatory variables associated with technical inefficiency and δ is a vector of unknown coefficients. the panel does not need to be balanced (battese and coelli 1995). following saleem (2007) and domah (2002), and assuming a transcendental logarithmic transformation, the function representing the underlying technology of power generating plants in kenya was specified as. njeru, et al.: technical efficiency of thermal electricity generators in kenya international journal of energy economics and policy | vol 10 • issue 3 • 2020342 lnq k l f k l it it it it it it = + + + + ( )+ ( ) β β β β β β 0 1 2 3 11 2 22 21 2 ln ln ln ln ln ++ ( )  + × + × + × β β β β 33 2 12 13 23 ln ln ln ln ln ln l f k l k f l it it it it it it nn f v uit it it+ − (2) where qit = units generated by the ith plant in month t in mwh kit= installed capacity for the ith plant in month t in mw lit=number of employees for the ith plant in month t fit=fuel used by the ith plant in month t in liters i=1…27 t=1…30 ln is the natural log β0…β33 are parameters to be estimated, vit are random errors μit are the random variables associated with inefficiency. μit are assumed to be independently distributed. the distribution of μit is truncated at zero of the normal distribution with a mean of mit and a variance of ,σµ 2 that is. n mit ,σµ 2( ) the technical inefficiency equation is specified as in battese and coelli (1995). =∂it itm z (3) where zit is a vector of variables likely to influence the efficiency of the firm and ∂ are the parameters to be estimated. equation 3 was assumed to take the form. m age grid ownershipit it it it= ∂ +∂ +∂1 2 3 (4) where, age = number of years the plant has been in operation grid = whether on grid connected or not (on-grid = 1 and isolated = 0) ownership = whether public or privately owned (public =1, private = 0). estimation of equation 2 including determinants of inefficiency as specified in equation 4 was undertaken using belotti et al. (2013) method and commands in stata. 3.1.1. elasticities and returns to scale the partial elasticity of output with respect to each of the inputs ek in equation 2 can be specified as in saleem (2007) and ngui (2008). e lnq lnx lnx lnx k jk it k k kk kit j k kj jit= ∂ ∂ = + + = = ≠ ∑β β β 1 2 3 1 2 3, , ; , , (5) and x represents k, l and f in equation 2. the returns to scale was calculated from the sum of the partial input elasticities, and expressed as, rts e k k k= = ∑ 1 (6) 3.2. dea malmquist productivity index this study followed saleem (2007) and domah (2002) and included variables likely to affect the efficiency of plants as outputs. consider firms that transform a set of inputs into x rn∈ + outputs q rm∈ + , and each firm uses x x x it it n it= …1 , , inputs to produce outputs, 1 ,....,= i i i mq t q t q t with i = 1,…,it observations over period of time. the outputbased malmquist productivity change index was specified as follows; m q x q x m q x q x m q x q t t t t t t t t t t t t 0 1 1 0 1 1 1 0 1 1 + + + + + + + ( ) = ( ) × , , , [ , , , , , tt tx, ]( ) 1 2 = d x q d x q d x q d x q t t t t t t t t t t t t 0 1 1 0 0 1 1 1 0 1 ( , ) ( , ) ( , ) ( , ) + + + + + + ×       × = + + + + + 1 2 0 1 1 1 0 0 1 1 0 / ( , ) ( , ) ( , ) ( , ) d x q d x q d x q d x q dt t t t t t t t t t t t 00 1 1 1 0 1 1 2t t t t t t x q d x q + + + +       ( , ) ( , ) / (7) where d was the distance function from the frontier, superscript t represented period technology, superscript t+1 represented period t+1 technology, subscript represented an output function. equation 7 represented the productivity of production point (xt+1, qt+1) relative to the production point (xt, qt). a value >1 indicated total factor productivity growth from period t to t+1 (coelli, 1996a). the ratio outside the brackets was, d x q d x q t t t t t t 0 1 1 1 0 + + + = ( , ) ( , ) efficiency change (8) and the ratio inside the brackets was, technicalchange= d x q d x q d x q d t t t t t t t t t0 1 1 0 0 1 1 1( , ) ( , ) ( , )+ + + + +× 00 1 1 2 t t tx q +       ( , ) / (9) 3.3. data type, source and measurement the data consisted of monthly records for all the 27 thermal generators existing in the system in the period july 2015 to december 2017. the period was informed by the available data from the energy regulatory commission (erc). the data was unbalanced since some of the plants were retired or not dispatched in some of the months. the data was from grid connected thermal generators and isolated stations that served areas not connected to the grid. all the 19 isolated stations were owned by public sector utilities, 2 by kengen and 17 by kplc. 2 of the grid connected thermal generators belonged to kengen while the remaining 6 were owned by ipps or private companies. 4. results and discussion 4.1. partial productivity analysis partial productivity analysis for grid and isolated power projects were analysed for the period july 2015 to december 2017. capital, labour and fuel productivity was analysed. njeru, et al.: technical efficiency of thermal electricity generators in kenya international journal of energy economics and policy | vol 10 • issue 3 • 2020 343 4.1.1. labour productivity labour productivity for grid connected projects was more volatile than that for isolated projects (figure 1). this can be attributed to changes in monthly generated output. grid connected power plants generated power based on economic merit order. thus competitively priced plants were allowed to generate first (electricity regulatory board, 2005). the existence of other competing forms of generation may have caused the variability in energy generated from thermal plants. thermal power plants tend to be more expensive than hydro and geothermal depending on the price of fuel. 4.1.2. capital productivity the capital productivity fluctuated in both grid and isolated power plants (figure 2). the capital productivity increased in the grid connected plants from july 2016 to june 2017. this can be attributed to increased use of thermal power plants in the 2016/17 financial year following inadequate rains that reduced hydro inflows affecting generation from hydro power plants. 4.1.3. fuel productivity fuel productivity remained less volatile over the period for both grid and isolated power plants (figure 3). this could be attributed to power plants adherence to the fuel efficiency targets set by the regulator. the regulator issued specific fuel consumption targets in kg/kwh for each of the power plants (electricity regulatory board, 2005). power plants that missed their targets were not compensated for the fuel costs above the set targets. 4.2. sfa results 4.2.1. elasticities and returns to scale three estimates were undertaken, one for all the thermal generators and two separate estimates for grid connected generators and isolated generators. this allowed for the assessment of the differences in the results. grid connected plants were larger in size compared to the isolated power plants. table 1 presents the results of the three estimates. the estimates for all the generators indicated that the partial output elasticity with respect to fuel was positive and significantly different from zero. a similar result was reported for the separate estimates for grid and isolated power plants. this indicates that adding fuel by 1% to the generators is likely to increase the amount of electricity generated by 1.68% for all thermal plants, 1.74% for grid connected projects and 2.97% for isolated power plants while holding capital and labour constant. the estimates for grid connected power projects also found capital to be significant determinants of electricity generation. increasing capital by 1% was also likely to increase the electricity produced by these power plants by 0.6% while holding labour and fuel constant. these findings are consistent with other studies. the study for india by shanmugam and kulshreshtha (2005) found fuel (coal) and capital to be the 0.00 100.00 200.00 300.00 400.00 500.00 600.00 ju l-1 5 a ug -1 5 s ep -1 5 o ct -1 5 n ov -1 5 d ec -1 5 ja n16 f eb 2 01 6 m ar -1 6 a pr 2 01 6 m ay -1 6 ju n16 ju l-1 6 a ug -1 6 s ep -1 6 o ct -1 6 n ov -1 6 d ec -1 6 ja n17 fe b17 m ar -1 7 a pr -1 7 m ay -1 7 ju n17 ju l-1 7 a ug -1 7 s ep -1 7 o ct -1 7 n ov -1 7 d ec -1 7 m w h/ em pl oy ee isolated grid figure 1: labour productivity in electricity generation source: author’s estimation from erc, kengen, ipps and kplc data 0 50 100 150 200 250 300 350 400 ju l-1 5 a ug -1 5 s ep -1 5 o ct -1 5 n ov -1 5 d ec -1 5 ja n16 f eb 2 01 6 m ar -1 6 a pr 2 01 6 m ay -1 6 ju n16 ju l-1 6 a ug -1 6 s ep -1 6 o ct -1 6 n ov -1 6 d ec -1 6 ja n17 fe b17 m ar -1 7 a pr -1 7 m ay -1 7 ju n17 ju l-1 7 a ug -1 7 s ep -1 7 o ct -1 7 n ov -1 7 d ec -1 7 m w h/ m w isolated grid source: author’s estimation from erc, kengen, ipps and kplc data figure 2: capital productivity in electricity generation njeru, et al.: technical efficiency of thermal electricity generators in kenya international journal of energy economics and policy | vol 10 • issue 3 • 2020344 determinants of coal based generation. saleem (2007) also found capital to be significant in determining thermal power generation in pakistan. all the three estimates indicated increasing returns to scale. this means the plants can generate more output to reach the optimal scale. the finding of increasing returns of 1.11 for grid connected power plants is close to that of knittel (2002) study for us coal and natural gas power plants. the study found coal power plants to have mild increasing returns to scale of 1.0644 and natural gas plants to have constant returns to scale. the isolated power plants as well as the combined isolated and grid power plants estimates indicated stronger increasing returns to scale of 3.94 and 2.4 respectively. strong increasing returns of 3.21 have been reported in saleem (2007) study for pakistan electricity generation sector. 4.2.2. efficiency of thermal power generation in kenya the efficiency estimates for all the thermal generators and two separate estimates for grid connected generators and isolated generators are presented on tables 2-4. as explained, the separate estimates for grid connected plant and isolated plants was occasioned by the sizing of the plants where grid connected plants were larger in size compared to the isolated power plants. the mean efficiency score for all the thermal power plants was found to be 71.06% indicating inefficiency in the thermal industry. none of the plants was found to be efficient. the least efficient power plant was found to be thika power with an average score of 33.7%. hola was the most efficient with an average score of 92.07%. the average efficiency score estimates for grid connected plants was found to be 98.78%. none of the power plants was found to be efficient. the most efficient grid connected power plant was found to be iberafrica with a mean efficiency score of 99.75%. the least efficient power plant was found to be kipevu 3 with a figure 3: fuel productivity in electricity generation 0 1 2 3 4 5 6 ju l-1 5 au g15 se p15 o ct -1 5 n ov -1 5 d ec -1 5 ja n16 f eb 2 01 6 m ar -1 6 a pr 2 01 6 m ay -1 6 ju n16 ju l-1 6 au g16 se p16 o ct -1 6 n ov -1 6 d ec -1 6 ja n17 fe b17 m ar -1 7 ap r17 m ay -1 7 ju n17 ju l-1 7 au g17 se p17 o ct -1 7 n ov -1 7 d ec -1 7 kw h/ li te r isolated source: author’s estimation from erc, kengen, ipps and kplc data table 1: sfa estimates of elasticities of thermal power production in kenya variable combined grid and isolated power plants grid connected power plants only isolated power plants only constant −8.379*** (1.323) −26.457*** (6.278) −9.896 (6.727) capital −0.093 (0.399) 0.596* (5.162) −0.536 (2.099) labour 0.807 (0.604) −1.232 (3.879) 0.433 (1.499) fuel 1.685*** (0.169) 1.742*** (0.248) 2.969** (1.066) returns to scale 2.4 1.11 3.94 log likelihood ratio 126.6 166.7 173.4 source: author’s estimation from erc, kengen, ipps and kplc data. *** indicates significance at 1% level, ** indicates significance at 5% level and * indicates significance at 10% level. standard errors are in paranthesis. sfa: stochastic frontier analysis, erc: energy regulatory commission, ipp: independent power producers table 2: sfa average efficiency for thermal power generators in kenya name of power plant average efficiency score (%) hola 92.07 marsabit diesel 91.78 lodwar diesel 89.58 habasweni 89.27 lokichogio 89.24 baragoi 89.12 mfangano 88.32 merti 87.65 lamu 86.51 elwak 86.36 eldas 85.71 takaba 85.63 rhamu 85.09 laisamis 84.54 mandera diesel 84.27 lokori 83.56 garissa (kengen) 82.50 north horr 79.72 wajir 76.71 rabai 40.26 iberafrica 38.97 tsavo 38.29 gulf power 37.51 kipevu 1 36.42 triumph power 34.83 kipevu diesel plant 3 34.34 thika power 33.70 source: author’s estimation from erc, kengen, ipps and kplc data. sfa: stochastic frontier analysis, erc: energy regulatory commission, ipp: independent power producers njeru, et al.: technical efficiency of thermal electricity generators in kenya international journal of energy economics and policy | vol 10 • issue 3 • 2020 345 mean efficiency score of 97.30%. iberafrica is a privately owned power plant while kipevu is owned by kengen, a public utility. the average efficiency for isolated power plants was estimated to be 82.73%. the most efficient isolated power plant was found to be lamu with an average efficiency score of 94.53%. the least efficient plant was north horr with a mean efficiency score of 38.55%. the estimates from combined grid and isolated plants were different from the results realised from estimating grid and isolated plants separately. grid connected power plants were found to be more efficient when estimated separately from isolated plants. this can be attributed to the small sizes of the isolated power plants relative to the grid connected power plants. further, the isolated power plants are limited to the energy requirements in their regions. 4.2.3. determinants of efficiency age, grid and ownership were found to be significant determinants of technical efficiency in the combined grid and isolated plants estimates (table 5). age had a negative sign, indicating that age is likely to reduce the efficiency of generating plants. grid connection was found likely to have a positive effect on efficiency. public ownership had a negative sign indicating the possibility that public ownership is likely to reduce efficiency. 4.2.4. dea malmquist index results the same sample data was used, but to ensure a balanced panel 6 plants were dropped. the plants had either been retired, not dispatched or commissioned between the period july 2015 and december 2017. this plants include gulf power, garissa, lamu, hola, laisamis, north horr and lokori. table 6 presents the malmquist productivity change index summary results. in the estimates that combined both grid and isolated plants, technical and scale efficiency change was 1.002 indicating an improvement in efficiency of about 0.2%. total factor productivity was also found to have improved by 0.3%. there was no technological change in the period. this could be attributed to the short period under consideration in the study. the estimates for grid connected power plants found technical efficiency change, when assuming constant returns to scale (crs) technology, to have improved by 1%. this was slightly higher than the 0.1% realised for isolated power plants. technical efficiency change assuming variable returns to scale (vrs) situation was found to have improved by 0.6% for grid connected power plants. isolated power plants efficiency change relative to vrs technology reduced by 0.1%. the scale efficiency was also estimated to have improved by 0.3% for grid connected power plants and 0.2% for isolated plants. technological change favoured isolated power plants with an improvement of 0.4% compared to grid connected power plants that reduced with 0.9%. technological change represents a frontier shift (domah, 2002). the inward shift in the grid connected plants could be attributed to the growth in the grid energy mix bringing in competition and affecting the use of the thermal power plants. the outward shift in the isolated plants could be attributed to demand growth in their locations. consequently, isolated power plants experienced more increased total factor productivity of 0.6% compared to the grid connected power plants growth of 0.1%. table 3: sfa average efficiency for grid connected thermal power generators in kenya name of power plant average efficiency score (%) iberafrica 99.75 tsavo 99.68 kipevu1 99.62 rabai 99.38 thika power 98.56 gulf power 97.94 triumph 97.87 kipevu3 97.30 source: author’s estimation from erc, kengen, ipps and kplc data. sfa: stochastic frontier analysis, erc: energy regulatory commission, ipp: independent power producers table 4: sfa average efficiency for isolated power plants in kenya name of power plant average efficiency score (%) garissa 94.53 lamu 91.86 lokichogio 91.85 lodwar 91.70 merti 91.31 hola 90.98 baragoi 89.69 habasweni 88.52 marsabit 88.46 mandera 87.89 mfangano diesel 86.59 takaba diesel 85.30 elwak 83.80 rhamu 83.25 eldas 81.47 wajir 79.75 laisamis 70.49 lokori 65.41 north horr 38.55 source: author’s estimation from erc, kengen, ipps and kplc data. sfa: stochastic frontier analysis, erc: energy regulatory commission, ipp: independent power producers table 5: effects of age, connection and ownership on technical efficiency of thermal power plants variables combined grid connected and isolated plants grid connected power plants isolated power plants age −0.0026034** (0.002) −0.0042498 (0.066) −10.25921*** (0.199) grid on-grid=1 0.6402017*** (0.022) isolated=0 0.1388421 ownership public=1 −0.1106151*** (0.025) −0.0362599 (0.341) private=0 0.1388421 0.0422385 source: author’s estimation from erc, kengen, ipps and kplc data. *** indicates significance at 1% level, ** indicates significance at 5% level and * indicates significance at 10% level. standard errors are in paranthesis. sfa: stochastic frontier analysis, erc: energy regulatory commission, ipp: independent power producers njeru, et al.: technical efficiency of thermal electricity generators in kenya international journal of energy economics and policy | vol 10 • issue 3 • 2020346 5. conclusions the mean efficiency score for all the thermal power plants (combined grid and isolated power plants) was found to be 70.62%. grid connected power plants efficiency averaged 98.78% while that of isolated power plants was found to be 82.73%. none of the power plants was found to be efficient. this indicated that the thermal power industry in kenya was inefficient and underutilised its technical potential. the malmquist index indicated improvement in efficiency and productivity. the estimated efficiency change for combined grid and isolated power plants was found to be 0.2% with a total factor productivity growth of 0.3%. estimates for grid connected power plants found efficiency improvements of 0.6% and total factor productivity of 0.1%. technological change was found to be 0.991, indicating a possible inward frontier shift for grid connected power plants. isolated power plants were also found to have experienced efficiency improvement of 0.2% and total factor productivity growth of 0.6%. the sfa estimates indicated that fuel has a positive elasticity and is significantly different from zero for the three estimated models that is combined grid and isolated plants, grid connected plants and isolated plants. capital was also found to be a positive and significant determinant of electricity production for grid connected power plants. the return to scale results indicated increasing returns to scale. age, grid and ownership were found to be significant determinants of the technical efficiency. age and public ownership coefficients negatively affected the efficiency of generating plants, while grid connection had a positive effect on efficiency. 6. policy recommendations efficiency requires the government to deepen reforms, competition and regulations. reforms meant to achieve efficiency in the sector have not realised this objective yet as thermal power generation industry still showed inefficiency. the government should continue with the reform agenda and particularly consider encouraging private investment in power generation. the government should also continue connecting the isolated areas to the grid. areas not connected to the grid have the potential of benefiting from private owned generation plants. the industry is operating on increasing returns to scale. this finding is critical as it indicates capacity to improve performance in the sector. with the same inputs currently being deployed output could be expanded. erc should therefore consider using the findings of these paper to implement incentive regulation by rewarding or penalising thermal power plants based on their performance relative to other firms. removing the current protection accorded to the generators in the long term take or pay power purchase agreements is likely to improve on the plants efficiency. this can be done through the introduction of a wholesale generation market and signing take and pay contracts. the fuel elasticity of output was found to be high and significant. erc can look at how to regulate fuel use whose costs are currently passed on to consumers leaving the generators with a minimal risk on it. generators may not be motivated to use it efficiently. erc could explore the possibility of reducing the cost of fuel transferred to consumers with a view to make generators use the same fuel amount to produce more energy. this could be done by downward revision of the specific fuel targets per unit generated. references arocena, p., waddams, p.c. (2002), generating efficiency: economic and environmental regulation of public and private electricity generators in spain. international journal of industrial organization, 20(1), 41-69. battese, g.e., coelli, t.j. (1995), a model for technical efficiency effects in a stochastic frontier production function for panel data. empirical economics, 20, 325-332. belotti, f., daidone, s., ilardi, g., atella, v. (2013), stochastic frontier analysis using stata. the stata journal, 13(4), 719-758. chang, y., toh, w.l. (2007), efficiency of generation companies in the deregulated electricity market of singapore: parametric and nonparametric approaches. international journal of electronic business management, 5(3), 225-238. coelli, t. (1996a), a guide to deap version 2.1: a data envelopment analysis (computer) program. centre for efficiency and productivity analysis working paper no. 08/96. armidale: university of new england. domah, p. (2002), technical efficiency in electricity generation-the impact of smallness and isolation of island economies. department of applied economics working paper series 0232. cambridge: university of cambridge. electricity regulatory board. (2005), retail electricity tariffs review policy. nairobi: electricity regulatory board. fatima, s., barik, k. (2012), technical efficiency of thermal power generation in india: post-restructuring experience. international journal of energy economics and policy, 2(4), 210-224. golany, b., roll, y., rybak, d. (1994), measuring efficiency of power plants in israel by data envelopment analysis. engineering management, ieee transactions on engineering management, 41(3), 291-301. jamasb, t. (2007), technical change theory and learning curves: patterns of progress in electricity generation technologies. the energy journal, 28(3), 51-71. table 6: malmquist efficiency change power plants technical efficiency change (relative to crs technology) technological change pure technical efficiency change (relative to vrs technology) scale efficiency change total factor productivity change combined grid and isolated power plants 1.002 1.000 1.000 1.002 1.003 grid only 1.01 0.991 1.006 1.003 1.001 isolated only 1.001 1.004 0.999 1.002 1.006 source: author’s estimation from erc, kengen, ipps and kplc data njeru, et al.: technical efficiency of thermal electricity generators in kenya international journal of energy economics and policy | vol 10 • issue 3 • 2020 347 kenya power and lighting company. (2017), annual report and financial statements. financial year ended 30th june 2017. nairobi: kenya power and lighting company limited. khan, a.j. (2014), the comparative efficiency of public and private power plants in pakistan’s electricity industry. the lahore journal of economics, 19(2), 1-26. knittel, c.r. (2002), alternative regulatory methods and firm efficiency: stochastic frontier evidence from the us electricity industry. review of economics and statistics, 84(3), 530-540. lam, p., shiu, a. (2001), a data envelopment analysis of the efficiency of china’s thermal power generation. journal of utilities policy, 10, 75-83. malik, k., cropper, m., limonov, a., singh, a. (2011), estimating the impact of restructuring on electricity generation efficiency: the case of the indian thermal power sector. cambridge, ma: national bureau of economic research working paper no. 17383. ngui, m.d. (2008), on the efficiency of the kenyan manufacturing sector: an empirical analysis. aachen, germany: shaker verlag. republic of kenya. (1997), the electric power act, 1997. nairobi: government printer. republic of kenya. (2004), sessional paper no 4 of 2004 on energy. nairobi: government printer. republic of kenya. (2018), kenya electricity sector investment prospectus 2018-2022. nairobi: ministry of energy. riaz, k., khan, i., qayyum, a., khan, a. (2013), technical efficiency of asian energy firms: a bootstrapped dea approach. journal of basic and applied scientific research, 3(5), 844-852. saleem, m. (2007), technical efficiency in electricity generation sector of pakistan: the impact of private and public ownership. australian national university. canberra, australia. downloaded. available from: http://www.pide.org.pk. shanmugam, k.r., kulshreshtha, p. (2005), efficiency analysis of coalbased thermal power generation in india during post-reform era. international journal of global energy issues, 23(1), 15-28. vijai, j.p. (2018), technical efficiency of coal-based thermal power plants in india: a stochastic frontier analysis. international journal of oil, gas and coal technology, 17(4), 472-485. . international journal of energy economics and policy | vol 10 • issue 4 • 2020 437 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(4), 437-442. crude oil prices, household spending and economic growth in the asean-4 region: an analysis of nonlinear panel autoregressive distributed lag wali aya rumbia1*, abd azis muthalib1, bakhtiar abbas2, pasrun adam3, heppi millia1, la ode saidi3, muh. irfandy azis4 1department of economics, universitas halu oleo, kendari 93232, indonesia, 2study program of management, sekolah tinggi ilmu ekonomi enam-enam, kendari 93121, indonesia, 3department of mathematics, universitas halu oleo, kendari 93232, indonesia, 4department of accounting, universitas borneo tarakan, tarakan 77123, indonesia. *email: ayarumbia@gmail.com received: 24 january 2020 accepted: 30 april 2020 doi: https://doi.org/10.32479/ijeep.9293 abstract this paper looks at the long run and short run asymmetric impact of crude oil prices on indonesia’s economic growth. it also assesses whether household spending affects the economic growth in the asean-4 region (indonesia, singapore, thailand and the philippines) in the long run and short run. we use, to this end, annual time series data of crude oil prices, household consumption expenditure, and gdp for the period 1967-2018. to analyze the data, we employ a nonlinear panel autoregressive distributed lag model. the test results provide evidence that in the long-run, crude oil prices have an asymmetric impact on economic growth. every 1% increase in crude oil prices, economic growth rises by 0.42%. meanwhile, household spending does not affect economic growth in the long-run. furthermore, in the short run, the test results show the presence of an asymmetric impact of crude oil prices on economic growth. similarly, in the short run, household spending affects economic growth. keywords: crude oil prices, household spending, economic growth, nonlinear panel autoregressive distributed lag model jel classifications: c33, e210, e310, o470 1. introduction all countries in the world are in need of crude oil as a source of raw materials for their industries. this need has triggered crude oil demand growth worldwide. for example, from 2006 to 20019, the global demand for crude oil rose from 85.3 million barrels per day to 100.3 million barrels per day. in fact, this growth continues to rise and is projected to increase to 101.6 million barrels per day (garside, 2019). opec also forecasts that the demand will constantly grow up to 104.8 million barrels per day by 2024 and 110.6 million barrels per day by 2040 (meredith, 2019). for the asean region, the demand for crude oil is projected at the level of 5.5 million barrels per day by 2040 in which there has been an increase of 3.4 barrels per day since 2017 (tan and peng, 2017). the growth in oil demand can drive oil prices to rise if it is not balanced with an increase in world crude oil production. the price of west texas intermediate (wti) crude oil, for instance, went up from 15.05 usd/barrel in 1986 to 65.23 usd/barrel in 2018, although in 2016, the price of wti crude was down at the level of 43.29 usd/barrel (eia, 2019). the increase in crude oil prices has stimulated the interest of policymakers, practitioners, and academics in the world to study the relationship between fluctuations in crude oil prices and economic activity. this has also led to advances in the econometrics field that allows researchers to study the functional relationship between oil prices and macroeconomic variables, both theoretically and empirically (herrera et al., 2019). from this journal is licensed under a creative commons attribution 4.0 international license rumbia, et al.: crude oil prices, household spending and economic growth in the asean-4 region: an analysis of nonlinear panel autoregressive distributed lag distributed lag international journal of energy economics and policy | vol 10 • issue 4 • 2020438 a theoretical point of view, the effect of oil prices on economic growth can occur through a couple of channels. in the first place, an increase in oil prices can cause the transfer of wealth from oil-importing countries to oil-exporting countries. this increase in wealth can cause consumption to rise which can then drive up gdp and economic growth (cologni and manera, 2008; abel et al., 2014). in the second place, an increase in oil prices can result in higher prices of manufactured goods since oil is an industrial raw material (adam et al., 2016; muthalib et al., 2018; rostin et al., 2019). the increase in prices of goods that occur continuously can cause inflation. if the inflation rate exceeds the inflation estimate set by the government of a country (the central bank), the central bank will suppress inflation through monetary policy by raising domestic interest rates (benada, 2014; adam et al., 2015; saidi et al., 2019). these higher interest rates can then reduce domestic investment, which in turn can reduce gdp and economic growth. a number of empirical studies on the impact of oil prices on economic growth have been carried out by previous researchers in many countries. despite this, their research findings have been inconsistent with one another. bjørnland (2000) for instance, examined the effect of oil prices on economic growth in such countries as germany, norway, the usa, and britain. he found that there was a negative influence on crude oil prices on economic growth, except in norway, this effect was positive. omitogun et al. (2018) investigated the effect of oil prices on economic growth in nigeria. they revealed that oil prices positively affected economic growth. kriskkumar and naseem (2019) looked at the symmetric and asymmetric effects of crude oil prices on economic growth in malaysia, brunei, and vietnam. these three countries are crude oil-exporting countries in the asean region. their study reported the absence of both symmetrical and asymmetrical impact of oil prices on economic growth in malaysia, and vietnam. for brunei, however, oil prices were found to positively affect economic growth. the variation in results of these studies vary can be caused by differences in data period used by the researcher (adam et al., 2015; saidi et al., 2019), and also by the varied cultural, socioeconomic and political condition of a country (ozturk, 2010). meanwhile, the impacts of household spending on economic growth have been documented by previous researchers. for example, karim et al. (2012) examined the effect of household spending on economic growth in malaysia and reported that household spending drove economic growth, but in the short-run, the effect did not exist. rafiy et al. (2018) examined the effect of household spending on economic growth in indonesia. from the evidence, they concluded that household spending had an impact on economic growth, both in the long-run and short-run. as noted earlier that the cultural conditions of the community, as well as socio-economic and political reasons, may account for such differences in finding (ozturk, 2010). the fact that there is dissimilarity in findings in some previous studies raises a question “how is the effect of crude oil prices and/ or household spending on economic growth in other countries that have not been studied or have been studied but the period of research data is different, whether it is positive, negative, or nonexistent?” this current study sets out to answer this question. it aims to investigate the asymmetry impact of crude oil prices on economic growth in the group of selected oil-importing countries in the asean region (indonesia, singapore, thailand, and the philippines), which we referred to as a group of asean-4. we also examine the effect of household spending on economic growth in the region. therefore, this study differs from kriskkumar and naseem’s research (2019) in terms of research location and variables used. this study includes household spending variable as a control variable. furthermore, according to our best knowledge, no studies have been conducted to look into the asymmetrical impact of crude oil prices on economic growth in the asean-4 region. the major aim of this study is to fill this research gap by examining the asymmetrical impact of crude oil prices and also household spending on economic growth in the region of asean-4. to look at the effect, we use a nonlinear panel autoregressive distributed lag model which we later represent in the abbreviation npardl (kouton, 2019). 2. literature review earlier studies have discussed the impact of crude oil prices on economic growth. by research sites or the number of the country involved, these studies can be grouped into two research groups. the first group includes research studies that are conducted in one certain country such as trang et al. (2017), wen et al. (2018) and jawadi and ftiti (2018). trang et al. (2017), for instance, analyze the influence of oil prices on economic growth, inflation, unemployment, and budget deficits in vietnam. the test results of the vector autoregressive (var) model on yearly data for the period 2000-2015 point out that the rising oil prices have no impact on the unemployment rate and economic growth, except inflation and budget deficits. using the var model, wen et al. (2018) examine the dynamic effect of crude oil prices on economic growth and monetary policy in china. the results of monthly data analysis from january 1996 to june 2017, lead to a conclusion that international oil price shocks have a positive effect on economic growth, in the short term. jawadi and ftiti (2018) study the effect of changes in oil prices on economic growth in saudi arabia. to test the effect, they use the threshold autoregressive model and annual data over the period 1970-2016. the evidence suggests that there is a positive nonlinear effect on oil prices on economic growth. the second group, on the other hand, belongs to research studies that investigate several countries or a group of country such as jemenes-rodrigues and sanches (2005), bergmann (2019) and mo et al. (2019). jemenes-rodrigues and sanches (2005) examine the effect of oil price shocks in the main oecd industrialized countries. jemenes-rodrigues and sanches (2005) examine the effect of oil price shocks in the main oecd industrialized countries. using both linear and non-linear models, they carry out multivariate var analysis to empirically assess linear and nonlinear effect or the so-called asymmetrical effect. the study found that the effect of oil price shocks on gdp growth was asymmetry. in particular, oil price increases have a greater impact on gdp growth than do oil prices decreases, with the former being statistically significant in most cases. furthermore, the impact rumbia, et al.: crude oil prices, household spending and economic growth in the asean-4 region: an analysis of nonlinear panel autoregressive distributed lag distributed lag international journal of energy economics and policy | vol 10 • issue 4 • 2020 439 of rising oil prices on economic activity is found to be negative for oil-importing countries, except for japan which is otherwise. likewise, oil-exporting countries’ economic growth is negatively affected by an increase in oil prices, but norway benefiting from it. using linear and nonlinear var models, bergmann (2019) estimates the effect of oil price fluctuations on gdp growth in 12 countries (australia, belgium, canada, finland, france, britain, germany, japan, nederland, norway, sweden, and the usa). he finds that there is an asymmetric effect of crude oil prices on economic growth, but this effect is weak. mo et al. (2019) make an attempt to document the effect of crude oil prices on economic growth in brics countries using the wavelet-based quantile-onquantile method. some findings are revealed in this study. firstly, in the long run, crude oil prices have an impact on economic growth in south africa, whereas, in the short run, this impact does not exist. secondly, there is a positive short-term effect of crude oil prices on economic growth. lastly, they find the effect of crude oil prices on economic growth is weak in such countries as brazil, russia, and india. furthermore, a number of previous studies have also considered the impact of household spending on economic growth. gahtani et al. (2019) and bonsu and muzindutsi (2017) are among studies that looked at this impact in one particular country. gahtani et al. (2019) analyse the effect of household spending on non-oil gdp as a proxy of income in saudi arabia. they report that household spending has an influence on economic growth. bonsu and muzindutsi (2017) assess the relationship between household consumption spending and several macroeconomic variables (including exchange rates and economic growth) in ghana. the var test results on annual data basis from 1961 to 2013, give empirical evidence that in the short term, there is an effect of household consumption spending on economic growth. in addition, some other studies regarding the effect of household spending on economic growth have been carried out for the case of countries group. for example, alper (2018) investigates the effect of household spending, investment and savings on economic growth in developing countries. he used the panel data model to analyze annual data for the period 2005-2016. test results show that household spending, investment and savings positively affect economic growth. every 1% increase in household spending, investment and saving, economic growth increases by 0.41%, 0.25%, and 0.5%. meanwhile, radulescu et al. (2019) also investigate the effect of household spending and investment on economic growth in eight selected countries in the cee group of countries (romania, bulgaria, the czech republic, poland, hungary, slovakia, slovenia, and croatia) using the panel data model and annual data from 2004 to 2017. the analysis results lead them to the conclusion that household spending positively affects economic growth, in the short term. 3. data and methodology 3.1. data in this study, we use panel data consisting of annual time time series data that span from 1967 to 2018, and cross-country data for countries: indonesia, singapore, thailand and the philippines. time series data consist of the price of crude oil, household spending, and gdp. the proxy for oil prices is the west texas intermediate (wti) crude oil price in usd barrel. the measurement unit for household spending is idr. gdp is the proxy for economic growth in usd. the data in this study are obtained and verified from the federal reserved bank of st. louis for the data on wti crude oil price, and also from the world bank for the data on gdp and household spending. to accommodate time series data, we use gdp, oil, and con variables. gdp is useful for accommodating data on gross domestic product data, oil for data on wti crude oil price, and con for data on consumption spending. the gdp, oil and con variables are natural logarithmic forms. we also use the variable h to collect data on volatility between oil, con, and gdp. 3.2. methodology as noted above in the introductory subsection, the aim of this study is to examine the asymmetry effect of crude oil prices, and also the effect of household spending on economic growth in the region of asean-4. the asean-4 group includes indonesia, singapore, thailand, and the philippines. these four countries are oil-importing countries. despite the fact that indonesia is carrying out crude oil export activities, the country is still categorized as an oil importer since the crude oil it produces is still unable to satisfy the in-country needs (wang et al., 2013, adam et al., 2015). to test the effect, we employ the npardl model put forward by shin et al. (2014) and has been used by, among others, salisu and isah (2017) and kouton (2019). the procedure of testing the influence using the npardl model follows the procedure of testing the autoregressive distributed lag panel model proposed by pesaran et al. (1999) and pesaran (2015). the variables involved in the npardl model are oil+, oil-, con and gdp. the oil+, variable is the sum of positive change in crude oil prices, which we refer to as crude oil prices increase variable, and the oilvariable is the sum of negative changes in crude oil prices we henceforth call the crude oil prices decline variable. the oil+, oilvariables are defined as follows: � �il i t l itl r con i* ( ) , , , ,�� � � �� 1 2 3 41 1 oil oil mix d oilt i t i i t� � � � �� �min1 10 0[ , ] [ ( ), ]� where d(oili)=∆oili=oili-oil(i-1)=oil-oil(−1), i=1,2,…,t is the change in crude oil prices. the npardl model with a time lag of p, q, r is written npardl (p, q, r) which states the one-way relationship from crude oil prices and consumption spending to economic growth is as follows: gdp c t gdp oil oil i i i j p i j i t j ikk q ik i t i t k � � � � � � � � �� � �� � � � 1 0 ( ) ( ( ) (( ) ( ) , , , ,t k ill r i t itcon i� � � � � � �� � �0 1 1 2 3 4 (1) where ci, αi, βij (j=1…,p), γik and θik k=0,1,…,q), δil (l=0,1,…,r) are parameters of the npardl, equation, εit is an error, and i is a cross-section: indonesia, singapore, thailand and the philippines rumbia, et al.: crude oil prices, household spending and economic growth in the asean-4 region: an analysis of nonlinear panel autoregressive distributed lag distributed lag international journal of energy economics and policy | vol 10 • issue 4 • 2020440 and t=1967,…,2017. the ci parameter represents a fixed effect and t represents trend. error εit is independently distributed over i and t with mean zero, and constant variance σi 2 , and is independently distributed of regressors oil oili i � �, and coni. the parameters of the equation are estimated by the pooled mean group (pmg) estimator where the parameters are the same across all i (all countries). the gdp, oil+, oiland con variables are assumed to be stationary. equation (1) can be represented in the form of a non-linear error correction panel model (pesaran, 2015) as follows d gdp c t gdp oil oil conit i i i i t i it i it i it( ) ( )� � � � � � �� � �� � � � �1 � � �ij i t j ik i t k ik i t kk q j p gdp oil oil* ( ) * ( ) * ( )( )� � � � � � � � � � �� 1 1 1 1 �� � � �il i t l itl r con i* ( ) , , , ,�� � � �� 1 2 3 41 1 (2) in equation (2), ψi, φi and ϑi are the long-term parameters of � � i i dan coni (asterio and hall, 2011) with the long term multipliers � � i i , � � i i � dan � � i i are the same for all crossection i (countries) (pesaran, 2015). the ϕi parameters are the error correction parameters. the long-term effect of crude oil prices on economic growth is called the long-term asymmetry effect, if � � � � i i i i � � or with the pmg estimator, the value is the same for all cross-sections i. the short-term effect of crude oil prices on economic growth is called the short-term asymmetry effect, if � �k k * *� , k=1,2,…,q-1 (shin et al., 2014; pesaran, 2015). testing the effect of using npardl requires several testing steps. in the first step, we test the stationarity or order of the integration of all variables. we use two-panel unit root tests namely the levin, lin, and chu (llc) test developed by levin et al. (2002), and the im, pesaran, and shin (ips) test developed by im et al. (2003). the hypothesis formula of both tests is h0: time series has a unit root against an alternative hypothesis h1: time series has no unit root (stationary). while, the criterion of both tests is that h0 is rejected (h1 accepted) if the p-value of the test statistic is smaller than the significance level of 1%, 5% or 10%. if the variables are stationary in first difference, then in the second step, we test the cointegration between crude oil prices increase, crude oil prices decline, household spending, and economic growth. we use the kao cointegration panel test developed by kao (1999). the kao test is a development of the dickey-fuller (df) and augmented dickey-fuller (adf) tests for cointegration tests on the panel model. therefore, it follows the df and adf test procedures. kao’s test hypothesis formula is h0: all time series do not co-integrate versus alternative hypotheses h1: all time series co-integrate (asteriou and hall, 2011). in the final step, we estimate the model parameters. however, before we proceed to this estimation, we determine in advance the length of time lag p, q, and r based on the smallest value of the aic (akaike information criterium). as mentioned earlier, the parameter estimation uses the pooled mean group method. 4. results we first examine the stationarity of the oil prices increase variable oil+ crude oil prices decline (oil-), household expenditure (con), and economic growth (gdp) in level and first difference. the estimation results of the panel unit root test both the llc test and the ips test are summarized in table 1. it appears from table 1 that all variables are stationary in first difference. afterwards, we examine the cointegration between crude oil prices increase, oil prices decline, household spending, and economic growth. the results of the kao cointegration panel test are reported in table 2. the table shows that the alternative hypothesis is accepted. in other words, there is cointegration between crude oil prices increase, crude oil prices decline, household spending and economic growth. moreover, this cointegration result concludes that a long-term relationship exists between the first three variables and economic growth. the long-term effect of each independent variable (regressor) on the dependent variable is characterized by the significance of the coefficient of each independent variable (regressor) reported in table 3 in panel a. lastly, we proceed to set the time lag for the npardl model. based on the aic information criteria, we set the length of the time lag to be p=2, q=r=1. thus, in this step, we estimate the parameters of the npardl (2,1,1) model. the estimated results of the model parameters are reported in table 3. as it is shown in panel a, the oil+ variable is significant at the 5% significance level, while the oiland con variables are not significant. in other words, a long-term asymmetric effect of crude oil prices on economic growth exists, and there is no long-term effect of household spending on economic growth. from the oil+ variable coefficient it can be said that for every 1% increase in the price of crude oil, economic growth rises by 0.42%. in panel b of table 3, it appears that the coefficients of the d(oil+) and d(oil-) variables are significant at the 1% significance level. however, the two coefficients are different. the difference in coefficients implies that in the short run, there is an asymmetric effect of crude oil prices on economic growth. furthermore, the coefficient of the d(con) variable is significant at the 1% significance level. in other words, in the short run, there is an effect of household spending on economic growth. 5. discussions the present study finds that there is an asymmetry impact of crude oil prices on economic growth both in the long run and in the short run. this finding is similar, among others, to that of wen et al. (2018), jawadi and ftiti (2018), jemenes-rodrigues and sanches (2005), bergmann (2019) who earlier found evidence of the impact of oil prices on economic growth. on the other hand, the finding in this study is not in line with that of trang et al. (2017) and kriskkumar and naseem (2019) who found the absence of impact of oil prices rumbia, et al.: crude oil prices, household spending and economic growth in the asean-4 region: an analysis of nonlinear panel autoregressive distributed lag distributed lag international journal of energy economics and policy | vol 10 • issue 4 • 2020 441 on economic growth. this difference in findings could be due to the time period of the data used (adam et al., 2015; saidi et al., 2019) and also differences in country characteristics (ozturk, 2010). besides that, this study finds that household spending has an impact on economic growth. this finding confirms that of gahtani et al. (2019), bonsu and muzindutsi (2017), alper (2018) and radulescu et al. (2019) who previously reported the same. however, the finding in this study differs from that of karim et al. (2012) who found that in the short-run there is an impact of consumption spending on economic growth. 6. conclusions crude oil is indispensable for the world economy as it is needed by all countries as an industrial raw material in all sectors of the economy. meanwhile, household spending is a macroeconomic variable in which in the calculation of national income, it is a component of gdp. in this study, gdp is used as the proxy for economic growth. the present study intends to examine the asymmetric effect of crude oil prices, and also the effect of household spending on economic growth. to test this effect, we use time-series data of wti crude oil prices, household consumption spending and gdp ranging from 1967 to 2018. to analyze the data, we employ the npardl model. panel unit root test results show that all variables are stationary in first difference. the cointegration panel test results show that there is cointegration between crude oil prices increase, crude oil prices decline, consumption spending and economic growth. the estimation results of npardl model parameters show that first, in the long run, there is an asymmetric impact of crude oil prices on economic growth. second, in the long run, household spending does not impact on economic growth. third, in the short run, there is an influence asymmetric crude oil prices on economic growth. fourth, in the short run, there exists an effect of household spending on economic growth. references abel, a.b., bernanke, b.s., croushore, d. (2014), macroeconomics. 8th ed. new york: pearson education inc. adam, p., rianse, u., cahyono, e., rahim, m. (2015), modeling of the dynamics relationship between world crude oil prices and the stock market in indonesia. international journal of energy economics and policy, 5(2), 550-557. adam, p., rianse, u., harafah, l.m., cahyono, e., rafiy, m. (2016), a model of the dynamics of the effect of world crude oil price and world rice price on indonesia’s inflation rate. agris online papers in economics and informatics, 8(1), 3-12. alper, e.a. (2018), the relationship of economic growth with consumption, investment, unemployment rates, saving rates and portfolio investments in the developing countries. gaziantep university journal of social sciences, 17(3), 980-987. asteriou, d., hall, s.g. (2011), applied econometrics. 2nd ed. london: palmagrave macmillan. benada, l. (2014), effect of crude oil on the prague stock exchange. procedia-social and behavioral sciences, 109, 1316-1321. bergmann, p. (2019), oil price shocks and gdp growth: do energy shares amplify causal effects? energy economics, 80, 1010-1040. bjørnland, h.c. (2000), the dynamic effects of aggregate demand, supply and oil price shocks: a comparative study. the manchester school, 68(5), 578-607. bonsu, c.o., munzindutsi, p.f. (2017), macroeconomic determinants of household consumption expenditure in ghana: a multivariate cointegration approach. international journal of economics and financial issues, 7(4), 737-745. cologni, a., manera, m. (2008), oil prices, ınflation and ınterest rates in a structural cointegrated var model for the g-7 countries. energy table 1: panel unit root test variable llc test statistics ips test statistics constant constant and linear trend constant constant and linear trend oil+ −1.3472 −0.0770 1.4253 −0.8984 d(oil+) −8.7463* −7.9439* −9.8919* −9.1951* oil2.7750 −1.3499 4.8345 −1.5347 d(oil-) −9.0334* −8.4358* −7.9355* −7.45532* con −4.1202 0.4331 −0.6825 1.8327 d(con) −7.5479* −8.5367* −5.67433* −6.0270* gdp −2.9342 −0.7905 −0.0189 −0.2639 d(gdp) −5.7101* −5.5984* −5.8915* −5.4074* *means significant at the 1% significance level table 2: panel cointegration test dependent variable independent variable kao residual cointegration test/adf test statistics gdp oil+ −3.3228* oilcon *means hypothesis h1 is accepted (cointegration exists) table 3: estimation results of npardl (2,1,1) model independent variables coefficient t-statistic a. long term equation, dependent variable: gdp oil+ 0.4183 2.0632** oil0.3465 1.2428 con −0.1831 −0.3631 b. short term equation, dependent variable: d(gdp) cointeq01 −0.1572 −2.3536** d(gdp[−1]) 0.1586 1.7879*** d(oil+) 0.0631 6.0280* d(oil-) 0.1143 4.1407* d(con) 1.3990 2.6167* c 4.2548 2.3115** t 0.0106 2.2478** *, ** or *** means significant at the 1%, 5% or 10% significance level, cointeq01 is an error correction variable rumbia, et al.: crude oil prices, household spending and economic growth in the asean-4 region: an analysis of nonlinear panel autoregressive distributed lag distributed lag international journal of energy economics and policy | vol 10 • issue 4 • 2020442 economics, 30, 856-888. eia (energy information administration). (2019), spot prices for crude oil and petroleum products. washington, dc: us department of energy. available from: https://www.eia.gov/dnav/pet/hist/ leafhandler.ashx?n=pet&s=rwtc&f=a. gahtani, g.a., bollino, c.a., bigerna, s., pierru, a. (2019), estimating the household consumption function in saudi arabia: an error correction approach. applied economics, 52, 1-13. garside, m. (2019), daily demand for crude oil worldwide from 2006 to 2020 (in million barrels). berlin: statista, rechtsanwalt maximilian conrad raabestr. available from: https://www.statista. com/statistics/271823/daily-global-crude-oil-demand-since-2006. herrera, a.m., karak, m.b., rangaraju, s.k. (2019), oil price shocks and u. s. economic activity. energy policy, 129, 89-99. im, k., pesaran, m.h., shin, y. (2003), testing for unit roots in heterogeneous panels. journal of econometrics, 115(1), 53-74. jawadi, f., ftiti, z. (2018), oil price collapse and challenges to economic transformation of saudi arabia: a time-series analysis. energy economics, 80(c), 12-19. jemenes-rodrigues, r., sanches, m. (2005), oil price shocks and real gdp growth: empirical evidence for some oecd countries. applied economic, 37, 201-228. kao, c. (1999), spurious regression and residual-based tests for cointegration in panel data. journal of econometrics, 90(1), 1-44. karim, z.a., karim, b.a., zaidi, m.a.s. (2012), fixed investment, household konsumstion and economic growth: a structural vectorerror correction model (svecm) study of malaysia. international journal of business and society, 13(1), 63-76. kouton, j. (2019), the asymmetric linkage between energy use and economic growth in selected african countries: evidence from a nonlinear panel autoregressive distributed lag model. energy economics, 83, 475-490. kriskkumar, k., nassem, n.a.m. (2019), analysis of oil price on economic growth of asean net oil exporters. energies, 12, 1-19. levin, a., chien-fu lin, c.f., chu, c.s.j. (2002), unit root tests in panel data: asymptotic and finite-sample properties. journal of econometrics, 108, 1-24. meredith, s. (2019), opec lowers forecast for oil demand growth, says its own market share is dwindling. new york: cnbc. available from: https://www.cnbc.com/2019/11/05/opec-report-global-oildemand-growth-forecast-cut-over-the-medium-and-long-term.html. mo, b., chen, c., nie, h., jiang, j. (2019), visiting effects of crude oil price on economic growth in brics countries: fresh evidence from wavelet-based quantile-on-quantile tests. energy, 178, 234-251. muthalib, a.a., adam, p., rostin, r., saenong, z., suriadi, l.o. (2018), the influence of fuel prices and unemployment rate towards the poverty level in indonesia. international journal of energy economics and policy, 8(3), 37-42. omitogun, o., longe, a.e., muhammad, s. (2018), the impact of oil price and revenue variations on economic growth in nigeria. opec energy review, 42(4), 387-402. ozturk, i. (2010), literature survey on energy-growthnexus. energy policy, 38, 340-349. pesaran, m.h. (2015), time series and panel data econometrics. 1st ed. new york: oxford university press. pesaran, m.h., shin, y., smith, r.p. (1999), pooled mean group estimation of dynamic heterogeneous panel. journal of the american statistical association, 94(446), 621-634. radulescu, m., serbanescu, l., sinisi, c.i. (2019), consumption vs. investments for stimulating economic growth and employment in the cee countries-a panel analysis. economic research ekonomska istraživanja, 32(1), 2329-2353. rafiy, m., adam, p., bachmid, g., saenong, z. (2018), an analysis of the effect of consumption spending and investment on indonesia’s economic growth. iranian economic review, 22(3), 753-766. rostin, r., muthalib, a.a., adam, p., nur, m., saenong, z., suriadi, l.o., baso, j.n. (2019), the effect of crude oil prices on inflation, interest rates and economic growth in indonesia. international journal of energy economics and policy, 9(5), 14-19. saidi, l.o., adam, p., rahim, m., rosnawintang, r. (2019), the effect of crude oil prices on economic growth in south east sulawesi, indonesia: an application of autoregressive distributed lag model. international journal of energy economics and policy, 9(2), 194-198. salisu, a.a., isah, k.o. (2017), revisiting the oil price and stock market nexus: a nonlinear panel ardl approach. economic modelling, 66, 258-271. shin, y., yu, b.c., greenwood-nimmo, m. (2014), modelling asymmetric cointegration and dynamic multipliers in a nonlinear ardl framework. in: sickels, r., horrace, w., editors. festschrift in honor of peter schmidt: econometric methods and applications. new york: springer. p281-314. tan, f., peng, s.l. (2017), southeast asia crude. imports to more than double by 2040: iea. london: the thomson reuters’s data protection officer. available from: https://www.reuters.com/article/ us-asia-oil/southeast-asia-crude-imports-to-more-than-double-by2040-iea-iduskbn1cv0kp. trang, n.t.n., tho, t.n., hong, d.t.t. (2017), the impact of oil price on the growth, inflation, unemployment and budget deficit of vietnam. international journal of energy economics and policy, 7(3), 42-49. wang, y., wu, c., yang, l. (2013), oil price shocks and stock market activities: evidence from oil-importing and oil-export. journal of comparative economics, 41(4), 1220-1239. wen, f., min, f., zhang, y.j., yang, c. (2018), crude oil price shocks, monetary policy, and china’s economy. international journal of finance and economics, 24(7), 1-16. . international journal of energy economics and policy | vol 10 • issue 1 • 2020140 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(1), 140-144. future development of price instruments of state support for the use of renewable energy sources in kazakhstan aslan b. tasmaganbetov1*, gulnar t. kunurkulzhayeva1, zauresh o. imanbayeva1, zhumabay ataniyazov1, dinmukhammed n. shaikin2 1k. zhubanov aktobe regional state university, a. moldagulova st. 34, aktobe, kazakhstan, 2north-kazakhstan state university named after m. kozybayev, pushkin st. 86, petropavlovsk, kazakhstan. *email: aslan.tas@inbox.ru received: 28 july 2019 accepted: 30 october 2019 doi: https://doi.org/10.32479/ijeep.8481 abstract the article investigates various tools of state support for the development of renewable energy. special attention is paid to the price instruments of state support for the use of renewable energy sources (res), including a significant analysis of the regulatory framework of the republic of kazakhstan as incentives. the authors analyzed the level of development of fixed rates for the supply of electricity in the republic of kazakhstan. the analysis revealed that fixed rates had and continue to have a significant positive impact on the increase in projects for renewable energy. without the use of this tool in kazakhstan, it would not have been possible to establish such large res capacities. the article also deals with the auction system of pricing for the supply of electricity. according to the authors, through the introduction of the auction mechanism, the state selects the most effective res projects and forms market competitive prices for electric energy produced by res facilities. keywords: renewable energy sources, fixed rate, auction price jel classifications: q21, q28 1. introduction renewable energy plays an increasingly important role in kazakhstan’s energy mix due to the depletion of oil and coal resources. the concept for the transition of the republic of kazakhstan to a “green economy” (2013) provides that by 2030 the structure of electricity production by 10% should consist of renewable energy sources (res). in relation to this, the order of the minister of energy of the republic of kazakhstan (2016) established a target indicator to achieve 3% share in renewable energy from the total electricity production by 2020. this was the basis for amendments and additions to some legislative acts of the republic of kazakhstan on electricity (2017). through which a mechanism of auction bidding is taken for the selection of renewable energy projects from 2018. the main idea of the changes is that from 2018, a new incentive system-“auctions” will start to operate for new res market participants instead of a preferential differentiated tariff (feedin tariffs, fit) or “green tariffs.” the main reason for that is irrationally high level of “green tariff.” according to the minister of energy of the republic of kazakhstan k. bozumbayev (2019), the auction mechanism allowed to make transparent and understandable the process of selecting projects and investors. on the other hand, to focus on more efficient technologies and projects that minimize the impact on tariffs for end users from the commissioning of res capacities. it is expected that the new approaches should balance the interests of electricity consumers and other market participants. these approaches ensure the further development of renewable energy and reduce the growth of the financial obstacles on the final price of electricity, as well as promote competition between producers. this journal is licensed under a creative commons attribution 4.0 international license tasmaganbetov, et al.: future development of price instruments of state support for the use of renewable energy sources in kazakhstan international journal of energy economics and policy | vol 10 • issue 1 • 2020 141 thus, the purpose of this study is to determine the practical aspects of the use of price instruments of state support for the use of renewable energy sources in the republic of kazakhstan. to achieve the goal, the following tasks must be performed: • to review the literature on the use of instruments of state support for the development of renewable energy; • to analyze the level of development of fixed rates/tariffs for the supply of electricity; • to consider the auction system of pricing for the supply of electricity. 2. literature review the development of renewable energy sources in the world is mainly carried out only with the support of the state. which consists in the creation by the state of formal rules that change the work of the market. this, in turn, creates conditions for finding and attracting investments in the construction of renewable energy generating facilities. scientists identify different classifications of tools that are used for state support of renewable energy sources. for example, shklyaruk and malinina (2012) distinguish instruments to support renewable energy development for four modules: the elements that define the principle of support (fixed pay, allowances to the market price, quotas, tenders), the elements that define the support (type of setting the price, adapting the specified prices, etc.), the elements that define the dynamics of support (duration, intensity) and the elements that define the support costs (differentiation support, financing, the mechanism of compensation of expenses and others). espey (2001) singled out financial, institutional tools (first of all, normative-legal regulation and organizational measures) and tools focused on establishment of electricity production from renewable energy sources, as well as support programs and volunteer activities. according to kopylov (2015) it is accepted to allocate the instruments of support of renewable energy sources based on the price (fixed tariffs, price allowances, payment for power), on expenses (investment subsidies and grants, tax discounts, subsidizing), on volume (quotas, green standards, standards). price instruments of state support for the use of res has its own characteristics. renewable electricity prices are less volatile than prices for electricity produced from fossil fuels. wiser and bolinger (2007) highlighted that contracts in res are usually long-term (15-25 years). these contracts involve either fixed prices or inflation indexing. in this regard, as noted by marques and fuinhas (2012), renewable energy is much more predictable, and it increases the predictability of the entire economy. according to liao et al. (2011), government support for renewable energy (as well as support for any other industry) can distort markets. this may deprive choice of consumers and lead to less efficient allocation of resources. however, given the fact that conventional energy also receives subsidies but this type of energy has the adverse external effects arising from the use of fossil fuels. the effects are almost not measured and not accounted for environment. which makes renewable energy more appropriate to invest in the early stages of development, but in the long term should seek a waiver of any energy subsidies. in kazakhstan, the first step of the state policy in the renewable energy sector is associated with the adoption of the law of the republic of kazakhstan (2009) “on support of the use of renewable energy sources.” this law defined the basic conditions for supporting the use of res for the production of electricity and heat, including price instruments (fixed tariffs and auction price). kazakhstan scientists have made an important contribution to the study of economic aspects of traditional and renewable energy. in their studies (yessengeldin et al., 2018; arginbayeva, 2017) examined energy security issues, (bolyssov, 2019) identified prospects of renewable energy in agriculture and (abayev, 2018) focused on the possibility of using solar energy for rural development. however, kazakh researchers do not consider the issues of price instruments of state support for the development of renewable energy. 3. fixed tariffs for electricity supply one of the most common measures of state support for res development is preferential differentiated tariffs (feed-in tariffs, fit) or “green tariffs.” the essence of this tool is that for a certain period of time for electricity produced on the basis of res and delivered by households or companies to the network, a guaranteed, higher price is established in the form of a fixed tariff or premium to the market price of electricity. this makes it possible to offset some of the costs of the early users of the new technology and creates certainty for investors in the long term. in accordance with the resolution of the government of the republic of kazakhstan (2014) “on approval of fixed tariffs,” the practical application of fixed tariffs is started. fixed tariffs are approved by the government of the republic of kazakhstan for a period of 15 years for each type of res. the following factors were taken into account when approving the fixed tariffs: • indicators of electricity generation in the republic of kazakhstan and its acquisition from outside the republic of kazakhstan; • indicators of consumption of electric energy in the republic of kazakhstan and its implementation outside the republic of kazakhstan; • indicators of generation of electric energy in the republic of kazakhstan by objects on use of renewable energy sources; • international obligations of the republic of kazakhstan to reduce greenhouse gas emissions; • targets provided by the documents of the state planning system of the republic of kazakhstan; • availability of subsequent annual indexation of fixed tariffs. tasmaganbetov, et al.: future development of price instruments of state support for the use of renewable energy sources in kazakhstan international journal of energy economics and policy | vol 10 • issue 1 • 2020142 the approved fixed tariffs for the supply of electricity in kazakhstan produced by renewable energy facilities are given in table 1. as it can be seen, the basic objectives of the mechanism of application of fixed tariffs were to attract investment in the construction of renewable energy facilities and reduce the risks to investors to return the invested funds by guaranteed purchase of electricity for 15 years. in turn, the model of application of fixed tariffs turned out to be more applicable to the working conditions of the kazakhstan electricity market, where is no centralized pool and bilateral contracts prevail. it should be noted that fixed tariffs for renewable energy producers are subject to annual indexation taking into account inflation. in 2017, the tariff indexation method was revised to regulate exchange rate volatility for investors adversely affected by the transition to a floating exchange rate regime. for this purpose, indexation of the fixed tariff was made according to the scheme – 70% for inflation and 30% for foreign currency by the government of the republic of kazakhstan (2017). in kazakhstan, investors in the implementation of the res project pledge their own funds in foreign currency in the amount of 30% of the project cost. therefore, this rule will protect only the investor’s own funds, as it excludes further currency risks. according to the statistics committee of the ministry of national economy of the republic of kazakhstan (2019), the value of the consumer price index is used to fixed tariffs by year as follows: • 2016 – 116.6% • 2017 – 107.1% • 2018 – 106.1%. the amounts of indexed tariffs taking into account inflation and changes in the exchange rate of the national currency to convertible currencies are shown in table 2. the data of table 2 show that the tariff policy in the field of res was annually adjusted to take into account inflation and changes in the exchange rate of the national currency to convertible currencies. the annual increase in the fixed tariff is a burden for the country’s budget, as the state buys electricity at an inflated price from enterprises and individuals using alternative energy sources. nevertheless, preferential fixed tariffs have a significant positive impact on the development of renewable energy. in the annual report of llp “settlement and financial center for support of renewable energy sources” (2018) it is specified that since the launch of the mechanism for support of res based on the centralized purchase and sale of electricity res, the volume of purchase of electricity res was increased from 8 million kw/h in 2014 to 779 million kw/h by 2018. the number of energy producing organizations using res increased from 6 in 2014 to 35 by 2018. phasing out preferential differential tariffs is possible, but it is very risky. a promising direction for the development of domestic policy of support for res should be the gradual abandonment of budget subsidies. this task is very difficult for developers of renewable energy incentive programs, but its solution is already overdue, and it is inevitable. 4. auction system for setting the price for the supply of electricity an alternative to the preferential differentiated tariff is auction bidding, which is an auction for the supply of a known amount of electricity, sometimes in a certain area, under a long-term procurement contract. in comparison with the preferential tariff, this tool, as practice shows, provides less guarantees to investors. part of the reason for this is often the long time between tenders and the aggressive competition among companies in the course of tenders. currently, kazakhstan has introduced a mechanism of auction bidding for the selection of renewable energy projects. this mechanism replaced the fixed tariffs in force until 2018, which initially allowed to launch the renewable energy sector in the republic of kazakhstan. the main purpose of the implementation of the auction mechanism is the selection of the most effective res projects and the formation of competitive market prices for electricity produced by res facilities. in order to select renewable energy projects, amendments were made to the current legislation in the field of support of the renewable energy sector. the ministry of energy of the republic of kazakhstan developed the rules for organizing and conducting table 1: the fixed tariffs for the supply of electric energy made by objects on use of renewable energy sources (2014) renewable energy technology used to generate electricity the amount of the tariff, kzt/kwh (excluding vat) wind power plants for wind power conversion 22.68 photovoltaic solar energy converters for solar energy conversion 34.61 hydropower plant 16.71 biogas installation 32.23 source: resolution of the government of the republic of kazakhstan “on approval of the rules for determination of fixed tariffs” (2014) table 2: indexed tariffs for the supply of electricity produced by renewable energy facilities (tenge/kwh) types of res approved fixed rate indexed res rates 2017 2018 2019 wind power plant 22.68 26.44 28.31 30.03 solar power plant 34.61 40.35 43.21 45.84 hydropower plant 16.71 19.48 20.86 22.13 biogas plant 32.23 37.58 40.24 42.69 source: compiled by the authors according to the decree of the government of the republic of kazakhstan (2014) and calculation indexed fixed tariffs (2019) tasmaganbetov, et al.: future development of price instruments of state support for the use of renewable energy sources in kazakhstan international journal of energy economics and policy | vol 10 • issue 1 • 2020 143 auction tenders (2017). these rules include the qualification requirements for bidders, the content and procedure for submitting an application, the types of financial security of the application for participation in the auction and the conditions for their submission and return, the procedure for summarizing and determining the winners. the guidelines for investors on the implementation of renewable energy projects in kazakhstan (2018) indicate the main objectives of the auction system to support renewable energy in kazakhstan: • achievement of target indicators of res development; • reducing the impact of the res sector on the growth of enduser tariffs; • ensuring the systematic development of the renewable energy sector, taking into account the capabilities of the unified power system of the republic of kazakhstan; • a transparent procedure for the selection of renewable energy projects. according to statistics of jsc “kazakhstan operator of the electricity and capacity market” (2019), the first 10 auctions for the selection of renewable energy projects in kazakhstan were held from may 23 to june 7, 2018 for a total installed capacity of 245 mw in electronic format. the auction was attended by companies from china, bulgaria, kazakhstan, russia, france, turkey and the united arab emirates. for the first auctions were set limit prices at the level of fixed tariffs, which were approved by the government of the republic of kazakhstan (2014). the results of the 2018 auction for the purchase of 245 mw of electric power produced by renewable energy facilities are shown in table 3. 55 applications were submitted to the auction, of which 19 companies were recognized as winners. the winners were given the right to sign a 15-year contract of purchase and sale of electric energy with llp “settlement and financial center for support of renewable energy sources.” prices for solar generation decreased by 25.5%, hydropower – by 23.4%, wind energy – by 22.8% (up to 6 cents per kw/h). the price of biogas plants remained almost unchanged (0.2%). the maximum auction prices for subsequent auction trades are determined based on the results of previous auction trades at the maximum price of the winner. the comparative characteristics of the indexed tariff and the maximum auction price of res for 2019 are presented in table 4. the established maximum auction price for 2019 for the supply of electricity produced by renewable energy facilities is much lower (from 24.54% to 36.74%) compared to the indexed tariff. the achievement of low prices is explained by the state’s ability to create price competition among potential investors through non-discriminatory and transparent selection of projects with lower capital costs. the growing price competitiveness of renewable energy technologies, political initiatives conducive to the development of this sector, more open access to financing, the need to address energy and environmental security problems, the growing need for energy from the state also contributed to the reduction of prices for renewable energy. 5. conclusion implementing the price instruments of the state policy in the field of renewable energy development in kazakhstan requires systematic and balanced work aimed at: reducing the financial burden on end users of electricity; reducing the negative impact of res on the reliability of the power system of kazakhstan; attracting modern competitive technologies. the introduction of the auction mechanism contributed to the growth of the number table 3: the results of the auction for the supply of electric energy produced by the facilities for the use of renewable energy sources in 2018 types of plants volume of purchased capacity, mw the number of applications, units number of winners, units the marginal price of the auction, kzt/kwh maximum reduction of the auction price, kzt/kwh % reduction in marginal price wind power plant 140 19 9 22.68 17.49 22.8 solar power plant 80 25 5 34.61 25.8 25.5 hydropower plant 20 8 4 16.71 12.8 23.4 biogas plant 5 3 1 32.23 32.15 0.2 total 245 55 19 source: compiled by the authors according to the statistical data of jsc “kazakhstan operator of the electricity and capacity market” (2019) and the decree of the government of the republic of kazakhstan (2014) table 4: indexed tariffs and maximum auction price for electricity supply for 2019 in the republic of kazakhstan types of plants indexed tariff of renewable energy for 2019, kzt/kw/h maximum auction price for 2019, kzt/kw/h change kzt % wind power plant 30.03 22.66 7.37 24.54 solar power plant 45.84 29 16.84 36.74 hydropower plant 22.13 15.48 6.65 30.05 biogas plant 42.69 32.15 10.54 24.69 source: compiled by the authors on the calculation of indexation of fixed tariffs and indexed fixed tariffs (2019) and the order of the minister of energy of the republic of kazakhstan “on the approval of the maximum auction prices” (2019) tasmaganbetov, et al.: future development of price instruments of state support for the use of renewable energy sources in kazakhstan international journal of energy economics and policy | vol 10 • issue 1 • 2020144 of investors willing to implement renewable energy projects in kazakhstan. the use of the electronic format of the auction provided a fair and competitive selection of the most effective projects. what is more, projects with the best technological solutions and the lowest capital costs. references abayev, a. (2018), possibilities of solar energy utilization for the development of rural areas of the republic of kazakhstan. international journal of energy economics and policy, 8(2), 89-94. annual report of llp. (2018), settlement and financial center for support of renewable energy sources. available from: https://www.rfc. kegoc.kz/page/godovoy-otchet. arginbayeva, g. (2017), public administration system of energy security: an analysis and new opportunities. revista espacios, 38(48), 2. available from: http://www.revistaespacios.com/ a17v38n48/17384802.html. bolyssov, t. (2019), features of the use of renewable energy sources in agriculture. international journal of energy economics and policy, 9(4), 363-368. bozumbayev, k. (2019), the boom in res development in kazakhstan. available from: https://www.bnews.kz/news/ bumrazvitiyavienablyudaetsyavkazakhstane. calculation of index fixed and indexed rates fixed rates. (2019), available from: https://www.rfc.kegoc.kz/media/расчет%20индексации%20 фиксированных%20тарифов%20на%202019%20год.pdf. consumer price index. (2019), data of the committee on statistics of the ministry of national economy of the republic of kazakhstan. available from: https://www.statbureau.org/ru/kazakhstan/cpi. decree of the president of the republic of kazakhstan. (2013), on the concept of transition of the republic of kazakhstan to “green economy”. available from: https://www.online.zakon.kz/docume nt/?docid=31399596#pos=0;167. espey, s. (2001), internationaler vergleich energiepolitischer instrumente zur förderung regenerativer energien in ausgewählten industrieländer. bremen:  bremer energie-institute, books on demand. p339. guidelines for investors on the implementation of renewable energy projects in kazakhstan. (2018), available from: https://www.rfc. kegoc.kz/media/docs/709/5bd6a18438762.pdf. kopylov, a.e. (2015), the economics of renewable energy. moscow: griffin. p192. law of the republic of kazakhstan no. 89-vi zrk. (2017), on amendments and additions to some legislative acts of the republic of kazakhstan on electricity. available from: http://www.adilet.zan. kz/rus/docs/z1700000089. law of the republic of kazakhstan on support of renewable energy sources. (2009), no. 165-iv degree. available from: http://www. adilet.zan.kz/rus/docs/z090000165. liao, c.h., ou, h.h., lo, s.l., chiueh, p.t., yua, y.h. (2011), a challenging approach for renewable energy market development. renewable and sustainable energy reviews, 15(1), 787-793. marques, a., fuinhas j. (2012), is renewable energy effective in promoting growth? energy policy, 46, 434-442. order of the minister of energy of the republic of kazakhstan. (2017), no. 466 on the rules of organization and holding of auction. available from: http://www.adilet.zan.kz/rus/docs/v1700016240. order of the minister of energy of the republic of kazakhstan. (2019), no. 91 on approval of auction price limits. available from: https:// www.vie.korem.kz/uploads/предельные%20аукционные%20 торги.pdf. resolution of the government of the republic of kazakhstan. (2014), no. 271 on approval of the rules for determination of fixed tariffs. available from: http://www.adilet.zan.kz/rus/docs/p1400000271. resolution of the government of the republic of kazakhstan. (2017), no. 207 on approval of the rules for determination of fixed tariffs. available from: http://www.adilet.zan.kz/rus/docs/ p1700000207#z10. shklyaruk, m.s., malinina, t.v. (2012), integrated approach to assessing the effectiveness of renewable energy development support systems. st. petersburg: scientific and technical st. petersburg state polytechnic university, no. 4. p222-224. the order of the minister of energy of the republic of kazakhstan. (2016), no. 478 on adoption of target indicators of development of the sector of renewable energy sources. available from: https:// www.online.zakon.kz/document/?docid=37946377. trading results. (2019), jsc kazakhstan operator of the electricity and capacity market. available from: https://www.vie.korem.kz/rus/ analitika/resultatytorgov. wiser, r., bolinger, m. (2007), can deployment of renewable energy put downward pressure on natural gas prices? energy policy, 35(1), 295-306. yessengeldin, b., mukhamediyeva, g., sitenko, d., zhumanova, a. (2018), problems and perspectives of energy security of singleindustry towns of the republic of kazakhstan. international journal of energy economics and policy, 8(1), 116-121. . international journal of energy economics and policy | vol 9 • issue 4 • 2019214 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(4), 214-223. the impact of oil prices on stocks markets: new evidence during and after the arab spring in gulf cooperation council economies hani el-chaarani* beirut arab university, lebanon. *email: h.shaarani@bau.edu.lb received: 19 february 2019 accepted: 15 may 2019 doi: https://doi.org/10.32479/ijeep.7978 abstract this study investigates the impact of stock price fluctuations on stock markets in six countries in gulf cooperation council (gcc) (saudi arabia, kuwait, oman, bahrain, united arab emirates (uae) and qatar) during and after the recent geopolitics conflicts, known as arab spring, from january 2011 to december 2017. two statistical models were implemented to measure the relationship between oil price fluctuations and stock markets returns. the logistic smooth transition model was implemented to measure the relationship between oil price direction (positive/negative) and stock markets returns. the exponential smooth transition model (estr) was applied to capture the relationship between the magnitude of oil price fluctuations (small/large) and stock markets returns. the results reveal several asymmetrical results of oil price directions (positive/negative) on stock markets returns in some gcc countries. in saudi arabia, kuwait and bahrain, the negative oil price fluctuations have larger impact on the returns of stocks markets than positive oil price fluctuations. the results reveal also that the existence of political instability increases the sensitivity of stock markets returns on negative oil price shocks. in addition, the results of estr model do not reveal any asymmetrical relationship between the magnitude of oil price changes and stock markets returns in gcc region except oman. a high level of oil price shocks has larger impact on omani stock market returns than small oil price shocks. keywords: oil prices, stock markets, arab spring, geopolitical conflicts, gulf cooperation council jel classifications: e02, e44, e6, g18, q41 1. introduction in gulf cooperation council (gcc) countries1, stock markets have an essential role and crucial functions. they promote economic development and help to fix prices of financial products on the basis of investors supply and demand. they contribute to raise funds, to attract foreign investors and lead to business growth. they are considered as barometer of politic, economic and security conditions prevailing in countries. nowadays, the stock markets in gcc countries are characterized by low rate of return, shortage of liquidity and excess of volatility 1 gcc is an alliance of 6 countries comprising saudi arabia, kuwait, oman, bahrain, uae and qatar. (albaity and mustafa, 2018; saif-alyousfi et al., 2018). for some researchers, the arab spring and regional conflicts in middle east and north africa countries pose significant challenges on stock markets of gcc countries (zaiane, 2018). for many others researchers like khamis et al. (2018), the falling down and the fluctuation of oil prices since 2008 are the major reasons behind the actual pressure on stock markets. this reasoning can be validated because oil sector in gcc countries has a dominant position in the economy and oil prices have a strong effect on gross domestic product (gdp) fluctuations (khamis et al., 2018; albaity and mustafa, 2018). gcc countries are between the major political players in the region and one of the the most important players in the oil market around the world (arouri et al. 2011). they own more than 30% of the this journal is licensed under a creative commons attribution 4.0 international license el-chaarani: the impact of oil prices on stocks markets: new evidence during and after the arab spring in gulf cooperation council economies international journal of energy economics and policy | vol 9 • issue 4 • 2019 215 international total oil reserves and considered the largest exporter of oil with fifteen million oil barrels per day (opec, 2016). they have a clear influence on the economic and political decisions of middle east region and at the same time they are affected by the actual regional conflicts, economic conditions and oil prices volatility. therefore, the impact of geopolitical conflicts and oil price volatility on stock markets in gcc economies is not in doubt. previous empirical studies confirm that the fluctuations of oil prices in gcc, middle east, developed and developing countries have significant impact on stock markets but the evidence of the nature and the direction of influence are still inconclusive. the impact of oil prices volatility on stock markets has found to be negative in some cases, positive in some studies and neutral in some others (kilian and park, 2009, acaravcı et al., 2012, serkan et al., 2013, gencer and demiralay, 2014, santillán-salgado et al., 2017, ojikutu et al., 2018 and mikhaylov, 2018). on the other hand, some studies show that the geopolitical conflicts in syria, lebanon, yemen, iraq, libya, tunisia and egypt have slowed down the return of some stock markets (abdelbaki, 2013; acemoglu et al., 2018) and the financial sector in middle east countries (el-chaarani and rajab, 2018; el-chaarani and el-abiad, 2019; el-chaarani, 2019). acemoglu et al. (2018), have documented that the number of public protests was associated with low valuation in egyptian stock markets. from the existing researches, it can be concluded that many studies have explored the influence of oil prices shocks on stock markets in developed countries without considering the geopolitical environment and without comparing the country differences. moreover, it can be settled that some other studies have revealed the impact of regional conflict in middle east and north africa countries on some few and specific stock markets without considering the impact of economic factors and variables like oil prices. by recognizing the significant aspect of geopolitical conflicts, oil sector and stock markets in gcc countries, the importance of this research is to provide new evidences by addressing the following question: what is the impact of oil price volatility on stock markets in gcc countries? what is the impact of last street protests and geopolitical conflicts, known as arab spring, on the relationship between oil prices and stock markets returns in gcc countries? the objective of this study is to fill gaps of already existing literature and empirical findings by exploring the impact of oil prices on stock markets returns in gcc countries. second, this study investigates the joint impact of geopolitical conflicts and oil prices on stock markets returns in gcc countries. finally, this study examines the nature of oil prices impact on stock markets returns during the last geopolitical crises, known as arab spring. in other words, this study examines the impact of asymmetrical directions (positive or negative) and magnitude (low or high) of oil price fluctuations on stock markets in gcc region. considering the gcc region is due to the position of this region as large oil supplier for the global economy. to accomplish the objectives of the study, the remainder of this paper is organized as follows: section two presents the literature review. section three describes the data, explains the methodology and defines the variables of the study. section four, discusses the sample characteristics and the empirical findings. finally, section five concludes the research paper. 2. literature review 2.1. economic and politic overview of gcc countries gcc is an economic and political alliance comprising six oil exporting countries (kuwait, bahrain, oman, united arab emirates (uae), qatar and saudi arabia). since their alliance, gcc countries share similar political and economic strategies. gcc economies are manly dependent on oil production and exportation. they own one-third of the crude oil reserves and they export 34% of world oil needs2. few countries, like uae and qatar have developed alternative revenue sources like banking and infrastructure sectors. recently, oman and saudi arabia are trying to diversify their investment plan by developing new sources of revenue like tourism and health sector. the gdp of gcc economies is $1464 billion in 2017. the gdp of saudi arabia represents 47% of gcc’s gdp, followed by uae with 26%, qatar with 12%, kuwait with 8%, oman with 5% and bahrain with 2% (figure 1). in 2017, saudi arabia, uae and kuwait were considered between world’s top 10 oil exporters with $133.6 billion in value, $49.3 billion in value and $38.2 billion in value, respectively (opec, 2018). during the last decade, the economic situation and indicators of gcc countries has experienced many swings of declining and growing (figure 2). it is believed that the gdps and the other economic indicators of gcc countries are largely affected by the international crises and the oil price fluctuations (khamis et al., 2018). after the oil price booming in 2003, gcc countries expended their public and private investments. in the period between 2003 and 2006, gdps of gcc countries increased to attain their highest levels in 2006. qatar, saudi arabia, kuwait and oman decided to use the excess of oil revenues by developing large-scale investment projects, initiating mega infrastructure projects, increasing public employment and expending their foreign exchange reserves3. the international financial crisis of 2008 and the sharp drop of oil price in 2008 (figure 3) decreased the gdps of all gcc countries to the lowest level in 2009. the economic and financial situations of gcc countries were unstable. the low level of oil price led to large deficit in the governments revenues, governments expenditures and global current accounts. during this period, the reform of economic structures by developing the private sector and shifting from energy sector to service sector was the main driver of economical changes. however, this economic recession did not stay for long time. the economic situation has been recovered in 2010 with the global monetary reforms, the rapid recovery of oil prices and the new fiscal policies and packages initiated by gcc governments. 2 from the world factbook, 2016. 3 from credendo database, 2018. el-chaarani: the impact of oil prices on stocks markets: new evidence during and after the arab spring in gulf cooperation council economies international journal of energy economics and policy | vol 9 • issue 4 • 2019216 the economic and political situation was almost stable until february 2011, the date in which the middle east and north africa region witnessed some political conflicts and street protests known as arab spring. the anti-government and street protests had developed in syria, egypt, libya, tunisia and appeared few months later in gcc countries, mainly in bahrain. in february 14, 2011, a series of anti government and violent protests were led by the shia bahraini opposition against the sunni royal family calling for social, economical and political reforms. during the period between 2011 and 2014, bahraini government figure 1: contribution of gulf cooperation council countries to total gross domestic product source: world bank database. source: world bank database. figure 2: gross domestic product growth % of gulf cooperation council economies (2001-2017) source: world bank database. figure 3: average crude oil price (2008-2018) el-chaarani: the impact of oil prices on stocks markets: new evidence during and after the arab spring in gulf cooperation council economies international journal of energy economics and policy | vol 9 • issue 4 • 2019 217 succeeded to control the street protests with the support of saudi arabia government who considers the shia in bahrain as a threat. gcc countries tried to defend their regimes by avoiding all kind of social and political modifications. there was a real fear from kings and emirs in the other gcc countries that the street protests would spread to their countries which pushed them to increase the government expenditures without fixing new fiscal framework which made difficult to increase government revenues and make mega infrastructure investment. for the international monetary fund (2013)4, the arab spring have developed a kind of unstable economic environment, increased the unemployment rate and dropped down the growth rate in gcc countries. a new challenge appears for gcc economies when the oil price collapsed again in 2014. in 2015, the gdps of gcc countries dropped down and the total gcc public revenue decreased by 35%5. the economic system in gcc countries was no longer possible to resist with high budget deficits and declining of oil price. to recover their large deficits, the gcc countries used their foreign exchange reserves, issued local bonds and entered in the international bond markets. consequently, gcc countries borrowed us$318 billion through issuance of international and local bonds to finance their fiscal deficits (gulf base, 2016). moreover, they cancelled large number of infrastructure projects and introduced new measures to increase government revenues and reduce government expenditures. part of these measures was the introducing of new taxes like the value added tax (vat). for the international monetary fund (imf, 2016), introducing the vat has improved the gdps of gcc countries like qatar, kuwait and uae. also, it will develop the government capacity to reduce the deficit of government budget. 2.2. the impact of oil prices on stock markets many researchers have studied the relationship between oil prices and macroeconomic factors like gdp, growth, inflation and budget deficit. the majority of studies have revealed that oil price fluctuations have a clear impact on the economic activity and indicators in developed and developing countries (trang et al., 2017, foudeh, 2017, ewing and malik, 2016, tehranchian and seyyedkolaee, 2017, and eltejaei and afzali, 2012). however, few studies have tested the impact of oil price shocks on stock markets. additionally, most of those few studies have focused on the relationship between oil price fluctuations and stock markets in developed countries while developing countries like gcc countries still non well explored. sadorsky (1999), is among the firsts who study the impact of oil price shocks on stock markets in united states for the period between 1947 and 1996. using (var) model, he found that the unexpected increases in oil prices have a negative impact on stock prices. in 2003, the author introduced a new method to examine the correlation between oil price fluctuations and technology stock 4 george t. abed, “iif regional overview on the middle east and north africa: “arab spring” countries struggle, gcc prospects favorable,” institute of international finance, washington, dc, october 27, 2013. 5 from credendo database, 2018. prices. he recognized that oil price shocks have not a direct impact on technology stock prices. he also found that oil prices have an impact on prices and inflation ratio which indirectly affect the technology stock prices. park and ratti (2008), conducted the (var) model to analyze the influence of oil price movements on stock markets in united states and thirteen european countries between 1986 and 2005. they revealed that the fluctuations of oil price have a negative impact on stock markets. in united states stock markets, they found that the stock markets returns are more affected by oil prices than that of interest rate. using (garch) model, lee and chiou (2011), studied the correlation between oil price shocks and standard and poor 500 returns. they considered the expected and unexpected oil price. they revealed that in case of low oil price volatility, the unexpected changes in oil prices have no impact on standard and poor 500 returns. based on (egarch) model, bharn and nikolova (2010), studied the relationship between oil price shocks and stock markets returns in russia. they revealed a negative correlation between oil prices and russian stock markets in case of international news like the news of iraq war in 2006 and the news of 9/11 terrorist attack in united states. gencer and demiralary (2014), implemented the (garch) model to test the volatility spillover between oil price shocks and five different sectors in turkey for the period between 2005 and 2013. they revealed significant transmission from oil markets to stock markets. by using (var-garch), (dcc-garch) and (var-agarch) models, lin et al. (2014) confirmed the transmission of volatility from oil prices to stock markets in ghanaian stock markets. al-hajj et al. (2017), studied the relationship between oil price fluctuations and malaysian stock market returns over the period of 1991-2016. the results of autoregressive distributed lag model showed that oil price, interest rate and exchange rate have negative impact on stock market returns in malaysia. oppositely, diaz and de gracia (2017), revealed positive impact of oil price fluctuations on stock returns in nyse over the period of 1974-2015. using weekly data spanning for the period between 2010 and 2017, sharma et al. (2018), analyzed the linear relationship between indian stock markets and international crude oil. the results of (var) model revealed that the energy index in india is highly affected by the international crude oil fluctuations. recently, anyalechi et al. (2019), examined the volatility transmission between stock market returns and oil price fluctuations in nigeria from 1994 to 2016. the results of autoregressive distributed lag model showed that oil price shocks had no significant impact on stock market returns. in gcc countries, arouri et al. (2011) analyzed the relationship between oil price shocks and stock markets over the period of 2005-2010. the results of their study found some significant el-chaarani: the impact of oil prices on stocks markets: new evidence during and after the arab spring in gulf cooperation council economies international journal of energy economics and policy | vol 9 • issue 4 • 2019218 volatility spillovers between stock markets and oil price fluctuations. the study of almohaimeed and harrathi (2013), confirmed this result by using univariate and multivariate models in gcc countries over the period of 2007-2012. in their paper, they found evidence of volatility spillover between oil price shocks and gcc stock markets. the results showed that stock markets prices are affected by oil price fluctuations. using (bekk-garch) process, jouini and harrathi (2014), reported that the volatility spillover was running from oil price fluctuations to stock markets prices, and from stock markets volatility to oil prices in gcc countries during the period of 6 years, between 2005 and 2011. dutta et al. (2017), confirmed the existence of a positive and significant relationship between stock market performance and oil prices in some gcc countries like qatar, kuwait, saudi arabia and uae. albaity and mustafa (2018), tested the long and short run relationship between gcc stock markets returns and oil prices in the period between 2005 and 2015. the authors found significant long relationship between oil prices and stock markets before the crisis of 2007-2008. this result means that stock markets are predictor of oil price fluctuations. after the financial crisis, the authors recognized that oil price fluctuations do not co-move with stock markets, except kuwait and qatar. cheikh et al. (2018), used the nonlinear smooth regression test (str) to explore the influence of oil price shocks on gcc stock markets in the period between 2004 and 2015. the results revealed that the negative changes of oil price have greater impact on stock markets than that of positive changes. the authors stressed the need of government reforms and economic stability to reduce the volatility spillover between stock returns and oil price fluctuations. as evidenced by the previous studies on the subject, the impact of oil price shocks on stock markets remains contradictory and open to new methods and technics. 2.3. the impact of political instability on stock markets the impact of political news and instability on the economic situation and financial markets has been debated in many research papers. according to bilson et al. (2002), political instability and uncertainty are considered largely influential in emerging markets that are characterized by non liberal political and economic regimes. for pástor and veronesi (2013), there are two different influences of political instability on the economic situation. the impact of political instability and uncertainty is positive on the economy if the government anticipates them by providing protections and regulations. if the political uncertainty and instability are not well anticipated and diversified, their impacts will be negative on the economy. pástor and vernesi (2013) also argued that the volatility of stocks is very high in case of high level of political uncertainty. kim and mei (2001) had revealed the same results in hong kong stock markets. using jump-volatility filter model, they argued that both bad and good political news had a significant impact on stock market volatility. also, they found that bad political news had higher impact on stock markets volatility than that of positive political news. the same results have been observed by beaulieu et al. (2005) in canada. they found that stock market volatility increases when political instability and uncertainty are very high. the influence of political situation on the sentiment of investor is largely immense. goonatilake and herath (2007), conducted their study in united states to analyze the effect of political news on stock markets namely nasdaq, djia and s and p 500. they found that the nature of news has an impact on stock market volatility. bad news increases the stock market volatility; good news decreases the stock markets volatility while neutral news has no impact on stock markets volatility. hira (2017), revealed the relationship between political instability and stock prices in pakistan from 1998 to 2012. the results of (ardl) approach showed that instable political system has a significant negative impact on stock prices. balaji et al. (2018), analyzed the impact of election news on volatility and stock returns for a period from 1998 to 2014 in india. they divided the time period of study to three sub-periods: pre election, election and post election. balaji et al. (2018), revealed that the election news has high effect on stock markets in short term, then this effect diminishes in the long term after the election. the impact of arab spring in middle east, north africa, and gcc countries on stock markets were studied by many researchers. the majority of research revealed that the last political tensions have a direct impact on stock markets volatility and returns. also, many studies revealed an indirect impact of arab spring on the stock markets of stable neighboring countries. using a vector error correction model, abdelbaki (2013), revealed that the political uncertainty following the arab spring had a strong impact on the volatility of egyptian stock market during the period of 9 months, from march 2011 to november 2011. ahmed (2017), confirmed the impact of political tensions during arab spring on the egyptian stock market. his results revealed a negative impact of political instability on the returns of the major market sectors. chau et al. (2014), analyzed the impact of arab spring on stock markets volatility in six countries, namely kuwait, bahrain, egypt, jordan, lebanon and oman. using (garch), (egarch) and (gjrgarch) models, they found that middle east and north africa markets became more integrated with international markets after the arab spring. furthermore, they showed that the volatility of islamic indices increased during political tension. al shugaa and masih (2014), studied the volatility of stock markets in middle east and north africa region during the arab spring. using continuous wavelet transform method from 2008 to 2014, they found that stock markets in egypt, lebanon, jordon, uae, qatar, bahrain, oman and kuwait are affected by the non stability and the bad political news of arab spring. el-chaarani: the impact of oil prices on stocks markets: new evidence during and after the arab spring in gulf cooperation council economies international journal of energy economics and policy | vol 9 • issue 4 • 2019 219 alsharairi and abubaker (2016), studied the impact of the arab spring on the stock markets of stable neighboring countries. they considered the street protests during the arab spring in egypt and their impacts on dubai financial markets (dfm) from 2008 until 2012. the results showed that the arab spring sparking in egypt had a significant impact on the volatility of telecommunication and transportation indices in dfm. zaiane (2018), studied the impact of arab spring on stock market volatility in tunisia. using the (egarch) model from 2010 to 2016, the author found that both of bad and good news have increased the volatility of tunindex. moreover, the author revealed that the impact of bad news on stock markets volatility is higher than that of the impact of good news. the same results of negative influences of arab spring had been observed by mnif (2017) and jeribi et al. (2015) in tunisian stock markets. 3. data and methods this research considers the mutual impact of oil price fluctuations and political instability on the stock markets returns of six gcc countries: kuwait, bahrain, qatar, oman, saudi arabia, and uae. this study is based on monthly data of brent oil prices and stock markets spanning the period of 7 years, from january 2011 to december 2017. the data of monthly data of oil prices were collected from world bank database. the oil returns (ort) were measured by the logarithmic difference of oil prices. the data of stock markets indices were gathered from world bank database, arab monetary funds database and the official website of each stock market in gcc region. the stock markets indices were expressed in us dollar based on msci6 database. in addition, two control variables were considered for this study: the interest rate of us three-month treasury bills and the monthly msci world index returns. to consider the impact of political instability, the period of the study was divided to two different sub periods: from january 2011 to december 2013 and from january 2014 to december 2017. the first 3 years of this study were characterized by high level of political instability while the next 4 years were characterized by political stability after controlling the streets protests in the majority of arab countries except syria, iraq and yemen. as reported in table 1, the sample of the study were extracted from six formal stock markets with usd 723 billion as market 6 morgan stanley capital international. capitalization value and 770 listed companies in 2017. based on capitalization level, saudi arabia stock market is the largest in the region while bahrain stock market is smallest. in 2017, the highest number of listed companies was in kuwait stock market followed by saudi arabia and uae. the stock markets of uae and saudi arabia had been well developed from 2011 to 2017 while it is noticed in the same period a decreasing of stock markets capitalization for oman and kuwait. in this study, two different impacts of oil prices are considered based on two different statistical approaches that are derived from smooth transition autoregressive (str) model and inspired from the study of cheikh et al. (2018). firstly, the logistic smooth transition (lstr) model is implemented to test the asymmetrical effect of negative and positive oil prices fluctuations on stock returns. secondly, the exponential smooth transition model (estr) model is applied to capture the effect of large and small oil price shocks on stock returns. the simple representations of str (equation a), lstr (equation b) and estr (combination of equations [a] and [c]) models are presented as follow: (a):yt=o1xt+o2xtg(st;∂,c)+ut; (b): g(st;∂,c)=(1+ exp(-∂(st-c))) −1; (c):g(st;∂,c)=1-exp(-∂(st-c) 2). where, o1 is the linear coefficient and o2 is the nonlinear coefficient; g(st;∂,c) is a continuous function bounded from zero to one depending on (c), the threshold level; (∂), the speed of transition across regimes and (st), the value of transition variable. ut is the iid (0, σ 2). the logistic transition model (lsrt) is suitable in measuring the asymmetrical effect with respect to the positive or negative directions of oil price fluctuations mainly when the value of threshold (c) is close to zero. the exponential transition model (esrt) is useful to detect the asymmetrical effect of the magnitude of oil price shocks. the nonlinearity test was implemented to select the appropriate smooth transition model and the lagged ort as a threshold variable. based on the study of van dijk et al. (2002), the linearity test was applied by considering six lagged ort, then successively drop the lagged variables when the t-statistic of the corresponding parameter is less than the absolute value of 1. table 1: gcc stock markets in 2011/2017 country name listed companies (2011) market capitalization (2011) usd million listed companies (2017) market capitalization (2017) usd million united arab emirates 108 93,727.43 127 239,387.10 bahrain 44 16,593.33 42 18,226.97 kuwait 215 107,436.32 217 96,269.43 oman 114 26,863.42 112 21,299.27 qatar 42 112,432.35 45 130,613.34 saudi arabia 111 338,873.21 188 450,305.45 source: world bank database and arab monetary funds el-chaarani: the impact of oil prices on stocks markets: new evidence during and after the arab spring in gulf cooperation council economies international journal of energy economics and policy | vol 9 • issue 4 • 2019220 4. empirical results the lstr model in table 2 reveals the impact of negative and positive oil price shocks on stock markets during 7 years, from 2011 to 2017. the results of table 2 indicate that the stock markets in gcc region are highly affected by negative oil fluctuations, except uae. between gcc countries, the stock market in oman is the most affected by negative oil fluctuations. when the oil price fluctuates above the threshold of (0.093), the reaction of stock returns in oman stock market to 1% of oil price shocks is equal to 0.663%. the results indicate that the asymmetrical impact of oil price fluctuations exists only in saudi arabia, kuwait and bahrain. in those three countries, the negative changes of oil prices have higher impact on stock markets return than that of the positive fluctuations. in the other gcc countries (qatar, oman and uae), the results indicate insignificant response of stock markets return to positive oil fluctuations. to measure the joint impact of oil prices and geopolitical conflicts in arab world on the the stock markets returns in gcc region, the sample of observations has been divided to two different sub samples, the first one includes the observations from 2011 to 2013 and the second one includes the observations from 2014 to 2017. the results of tables 3 and 4 reveal that the speed transition of oil prices during political instability is highest than that of political stability period. during the political instability in arab world, the results of table 3 indicates that the negative fluctuations of oil prices are highly incorporated in the returns of stock markets in gcc region, except uae. the results do not reveal any impact of positive oil prices fluctuation during this period. it seems that the investors are more affected by negative oil news than that of positive oil news during political instability period. after the political instability period in arab world, the positive fluctuations of oil prices come to be more incorporated in the returns of stock markets in saudi arabia, bahrain and kuwait. the results of table 4 indicate the existence of asymmetrical impact of oil prices on the returns of stock markets in those three countries. in saudi arabia, bahrain and kuwait, the negative oil price fluctuations have larger impact on stock returns than positive oil price fluctuations. qatar and oman are only affected by negative oil price fluctuations while the return of emirates stock markets is not affected by oil fluctuations. the results of estr model in table 5 present the impact of magnitude of oil price fluctuations on stock markets in gcc table 2: lstr model for 2011-2017 variables description united arab emirates saudi arabia bahrain oman kuwait qatar transition variable st ort/6 ort/3 ort/5 ort/4 ort/4 ort/5 threshold c 0.06 0.08* 0.099*** 0.093*** 0.093*** 0.100*** speed transition ∂ 3.521 6.832 7.741 8.471 9.363 13.931 negative oil changes g (st;∂, c)=0 long effect 0.145 0.342** 0.424*** 0.663*** 0.461*** 0.577*** positive oil changes g (st;∂, c)=1 long effect 0.211 0.210* 0.338*** 0.134 0.258*** 0.417 r2 0.435 0.411 0.421 0.432 0.442 0.405 (*), (**), and (***) represent the significance levels at 10%, 5%, and 1% levels, respectively. r2 is the coefficient of determination table 3: lstr model for 2011-2013 (during the arab spring) variables description united arab emirates saudi arabia bahrain oman kuwait qatar transition variable st ort/4 ort/5 ort/3 ort/5 ort/4 ort/5 threshold c 0.03 0.06 0.091*** 0.093*** 0.100*** 0.900*** speed transition ∂ 4.457 8.453 10.133 7.764 11.457 14.931 negative oil changes g (st;∂, c)=0 long effect 0.214 0.421** 0.457*** 0.769*** 0.521*** 0.635*** positive oil changes g (st;∂, c)=1 long effect 0.125 0.122 0.141 0.132 0.156 0.221 r2 0.432 0.435 0.447 0.411 0.453 0.424 (*), (**), and (***) represent the significance levels at 10%, 5%, and 1% levels, respectively. r2 is the coefficient of determination table 4: lstr model for 2014-2017 (after the arab spring) variables description united arab emirates saudi arabia bahrain oman kuwait qatar transition variable st ort/4 ort/3 ort/3 ort/5 ort/6 ort/5 threshold c 0.085* 0.09*** 0.093*** 0.090*** 0.089*** 0.901*** speed transition ∂ 2.541 5.345 6.223 7.291 7.234 14.421 negative oil changes g (st;∂, c)=0 long effect 0.145 0.245** 0.392*** 0.562*** 0.403*** 0.499*** positive oil changes g (st;∂, c)=1 long effect 0.124 0.235* 0.256*** 0.321 0.202*** 0.357 r2 0.422 0.443 0.414 0.452 0.402 0.431 (*), (**), and (***) represent the significance levels at 10%, 5%, and 1% levels, respectively. r2 is the coefficient of determination el-chaarani: the impact of oil prices on stocks markets: new evidence during and after the arab spring in gulf cooperation council economies international journal of energy economics and policy | vol 9 • issue 4 • 2019 221 countries between 2011 and 2017. the estimated thresholds do not differ significantly across the different countries in gcc region. the results in table 5 indicate that the asymmetrical magnitude of oil price fluctuations is significant in oman. a high magnitude of oil price fluctuations is associated with 0.583% of omani stock returns reaction while a low magnitude level of oil price fluctuations is associated with 0.221% of stock returns reaction. for the other gcc countries (kuwait, bahrain, qatar, saudi arabia, and uae), a high magnitude of oil price fluctuations is associated with significant impact on the return of stock markets. to measure the impact of oil prices on stock markets in gcc region during the arab spring period, the observations of the study are divided to two different sub samples. the first sub sample includes the observations during the street protests in arab region (between 2011 and 2013). the second sub sample includes the observations after the end of street protest (between 2014 and 2017). the results in tables 6 and 7 reveal that large fluctuations of oil price during the arab spring have significant impact on stock markets returns in gcc region except qatar and uae. the results reveal the existence of asymmetrical impact of oil price magnitude in omani stock markets during the arab spring period. this lead to conclude that large oil fluctuations have greater impact on omani stock returns than small oil fluctuations. after the arab spring period, the results do not reveal any significant impact of oil price magnitude on the return of stock markets in gcc region. moreover, the results do not reveal any asymmetrical impact of oil price magnitude between 2014 and 2017. 5. conclusion the recent geopolitical conflict in arab world in 2011 and the dramatic falling of oil price in 2014 lead us to revise the nonlinear and asymmetrical relationship between oil price fluctuations and stock markets returns in six gcc countries (kuwait, bahrain, qatar, oman, saudi arabia, and uae). the importance of this research is to shed lights on the direction and magnitude of oil price fluctuations during and after the arab spring period in arab world. for this issue, the estr and lstr models were implemented. the lstr model was applied to capture the asymmetrical impact of oil price directions (negative or positive) while the estr model was implemented to distinguish between large and small oil price fluctuations. the study was conducted by using monthly data of oil prices and stock markets indices over the period of 2011-2017. the results of lstr model reveal that negative oil price fluctuations have larger impact on the returns of stocks markets than positive oil price fluctuations do in saudi arabia, kuwait and table 5: estr model for 2011-2017 variables description united arab emirates saudi arabia bahrain oman kuwait qatar transition variable st ort/4 ort/4 ort/6 ort/5 ort/6 ort/5 threshold c 0.023 0.036 0.043** 0.020** 0.021*** 0.045* speed transition ∂ 0.425 0.362 0.153 1.442 0.314 1.009 small oil changes g (st;∂, c)=0 long effect 0.251 0.268 0.368 0.221*** 0.055 0.307 large oil changes g (st;∂, c)=1 long effect 0.419* 0.677** 0.461*** 0.583*** 0.433*** 0.536* r2 0.433 0.421 0.393 0.313 0.364 0.406 (*), (**), and (***) represent the significance levels at 10%, 5%, and 1% levels, respectively. r2 is the coefficient of determination table 6: estr model for 2011-2013 (during the arab spring) variables description united arab emirates saudi arabia bahrain oman kuwait qatar transition variable st ort/3 ort/4 ort/5 ort/5 ort/4 ort/5 threshold c 0.035 0.027 0.021** 0.019** 0.014*** 0.014 speed transition ∂ 0.325 0.426 0.341 0.831 0.491 0.509 small oil changes g (st;∂, c)=0 long effect 0.121 0.197 0.231 0.201*** 0.131 0.214 large oil changes g (st;∂, c)=1 long effect 0.216 0.469** 0.425*** 0.583*** 0.336*** 0.540 r2 0.401 0.444 0.402 0.452 0.347 0.398 (*), (**), and (***) represent the significance levels at 10%, 5%, and 1% levels, respectively. r2 is the coefficient of determination table 7: estr model for 2014-2017 (after the arab spring) variables description united arab emirates saudi arabia bahrain oman kuwait qatar transition variable st ort/3 ort/5 ort/4 ort/3 ort/4 ort/4 threshold c 0.042 0.035 0.041 0.024* 0.033*** 0.037 speed transition ∂ 0.235 0.216 0.1253 1.442 0.314 1.009 small oil changes g (st;∂, c)=0 long effect 0.191 0.201 0.211 0.124 0.121 0.121 large oil changes g (st;∂, c)=1 long effect 0.246 0.632 0.547 0.621 0.521 0.632 r2 0.452 0.345 0.422 0.432 0.404 0.432 (*), (**), and (***) represent the significance levels at 10%, 5%, and 1% levels, respectively. r2 is the coefficient of determination el-chaarani: the impact of oil prices on stocks markets: new evidence during and after the arab spring in gulf cooperation council economies international journal of energy economics and policy | vol 9 • issue 4 • 2019222 bahrain. the results reveal that during arab spring period, the negative fluctuations of oil price have a clear impact on the returns of stock markets in gcc countries except uae. the existence of diversified economy in non-oil sectors can be the reason of the absence of any influence of negative oil price on stock markets returns in uae. the results of estr model do not reveal any asymmetrical relationship between the magnitude of oil price changes and stock markets returns in gcc region except oman. the results indicate that the magnitude of oil price fluctuations is asymmetrical in omani stock market. the large oil price shocks have higher impact on omani stock market returns than small shocks oil price. the results of estr model indicate also that large oil price fluctuations have significant impacts on stock market returns during the arab spring period except uae. references abdelbaki, h. (2013), the impact of arab spring on stock market performance. british journal of economics, management and trade, 3(3), 169-185. acaravcı, a., kandır, s.y., ozturk, i. (2012), natural gas prices and stock prices: evidence from eu-15 countries. economic modelling, 29(5), 1646-1654. acemoglu, d., hassan, t.a., tahoun, a. (2018), the power of the street: evidence form egypt’s arab spring. the review of financial studies, 31(1), 1-42. ahmed, w.m.a. (2017), the impact of political regime changes on stock prices: the case of egypt. international journal of emerging market, 12(3), 508-531. al shugaa, a., masih, m. (2014), uncertainty and volatility in mena stock markets during the arab spring. mpra paper no. 58867, posted 25. september 2014, utc. albaity, m., mustafa, h. (2018), international and macroeconomic determinants of oil price: evidence from gulf cooperation council countries. international journal of energy economics and policy, 8(1), 69-81. al-hajj, e., al-mulali, u., solarin, s. (2017), the influence of oil price shocks on stock market returns: fresh evidence from malaysia. international journal of energy economics and policy, 7(5), 235-244. almohaimeed, a., harrathi, n. (2013), volatility transmission and conditional correlation between oil prices, stock market and sector indexes: empirics for saudi stock market. journal of applied finance and banking, 3(4), 125-141. alsharairi, m., abubaker, w. (2016), does arab spring have a spillover effect on dubai financial market? dubai: proceedings of the australia-middle east conference on business and social sciences. p749-767. anyalechi, k., ezeaku, h., onwumere, j., okereke, e.j. (2019), does oil price fluctuation affect stock market returns in nigeria? international journal of energy economics and policy, 9(1), 194-199. arouri, m.e., jouini, j., nguyen, d.k. (2011), volatility spillovers between oil prices and stock sector returns: implications for portfolio management. journal of international money and finance, 30(7), 1387-1405. balaji, c., kusuma, g.d.v., kumar, b.r. (2018), impact of general elections on stock markets in india. open journal of economics and commerce, 1(2), 1-7. beaulieu, m., cosset, j., essaddam, n. (2005), the impact of political risk on the volatility of stock returns: the case of canada. journal of international business studies, 36(5), 701-718. bharn, r., nikolovann, b. (2010), global oil prices, oil industry and equity returns: russian experience. scottish journal of political economy, 57(2), 169-186. bilson, c.m., brailsford, t.j., hooper, v.c. (2002), the explanatory power of political risk in emerging markets. international review of financial analysis, 11(1), 1-27. chau, f., deesomsak, r., wang, j. (2014), political uncertainty and stock market volatility in the middle east and north african (mena) countries. journal of international financial markets, institutions and money, 28, 1-19. cheikh, n.b., naceur, s.b., kanaan, o., rault, c. (2018), oil prices and gcc stock markets: new evidence from smooth transition models. international monetary fund, working paper/18/98. p1-35. diaz, e.m., de gracia, f.p. (2017), oil price shocks and stock returns of oil and gas corporations. finance research letters, 20, 75-80. dutta, a., nikkinen, j., rothovius, t. (2017), impact of oil price uncertainty on middle east and african stock markets. energy, 123, 189-197. el-chaarani, h. (2019), determinants of bank liquidity in the middle east region. international review of management and marketing, 9(2), 1-12. el-chaarani, h., el-abiad, z. (2019), analysis of capital structure and performance of banking sector in middle east countries. international journal of economics and financial issues, 9(2), 1-11. el-chaarani, h., ragab, n.s. (2018), financial resistance of islamic banks in middle east region: a comparative study with conventional banks during the arab crises. international journal of economics and financial issues, 8(3), 1-12. eltejaei, e., afzali, m.a. (2012), asymmetric impacts of oil prices and revenues fluctuations on selected macroeconomic variables in iran. journal of basic and applied scientific research, 2(8), 7930-7937. ewing, b.t., malik, f. (2016), volatility spillovers between oil prices and the stock market under structural breaks. global finance journal, 29(c), 12-23. foudeh, m. (2017), the long run effects of oil prices on economic growth: the case of saudi arabia. international journal of energy economics and policy, 7(6), 171-192. gencer, h.g., demiralay, s. (2014), shock and volatility spillovers between oil prices and turkish sector returns. international journal of economics and finance, 6(2), 174-180. goonatilake, r., herath, s. (2007), the volatility of the stock market to news. international research journal of finance and economics, 3(11), 53-65. gulf base. (2016), gcc states set to borrow billions to fund deficits. available from: http://www.gulfbase.com/news/gcc-states-set-toborrowbillions-to-fund-deficits/288882. [last accessed on 2016 apr 13]. hira, i. (2017), relationship among political instability, stock market returns and stock market volatility. studies in business and economics, 2(12), 70-99. international monetary fund-imf. (2016), diversifying government revenue in the gcc: next steps. report of october 26. jeribi, a., fakhfekh, m., jarboui, a. (2015), tunisian revolution and stock market volatility: evidence from fiegarch model. managerial finance, 41(10), 1112-1135. jouini, j., harrathi, n. (2014), revisiting the shock and volatility transmissions among gcc stock and oil markets: a further investigation. economic modelling, 38(c), 486-494. khamis, r., anasweh, m., hamdan, a. (2018), oil prices and stock market returns in oil exporting countries: evidence from saudi arabia. international journal of energy economics and policy, 8(3), 301-306. kilian, l., park, c. (2009), the impact of oil price shocks on the u.s. stock market. international economic review, 50(4), 1267-1287. kim, h.y., mei, j.p. (2001), what makes the stock market jump? an analysis of political risk on hong kong stock returns. journal of international money and finance, 20(7), 1003-1016. el-chaarani: the impact of oil prices on stocks markets: new evidence during and after the arab spring in gulf cooperation council economies international journal of energy economics and policy | vol 9 • issue 4 • 2019 223 lee, y.h., chiou, j.s. (2011), oil sensitivity and its asymmetric impact on the stock market. energy, 36(1), 168-174. lin, b., wesseh, p.k., appiah, m.o. (2014), oil price fluctuation, volatility spillover and the ghanaian equity market: implication for portfolio management and hedging effectiveness. energy economics, 42(c), 172-182. mikhaylov, a. (2018), pricing in oil market and using probit model for analysis of stock market effects. international journal of energy economics and policy, 8(2), 69-73. mnif, a. (2017), political uncertainty and behavior of tunisian stock market cycles: structural unobserved components time series models. research in international business and finance, 39(pa), 206-214. ojikutu, o.t., onolemhemhen, r.u., isehunwa, s.o. (2017), crude oil price volatility and its ımpact on nigerian stock market performance (1985-2014). international journal of energy economics and policy, 7(5), 302-311. opec. (2016), organisation of the petroleum exporting countries (opec), annual report. park, j., ratti, r.a. (2008), oil price shocks and stock markets in the us and 13 european countries. energy economics, 30(5), 2587-2608. pástor, l., veronesi, p. (2013), political uncertainty and risk premia. journal of financial economics, 110(3), 520-545. sadorsky, p. (1999), oil price shocks and stock market activity. energy economics, 21(5), 449-469. saif-alyousfi, a., md-rus, r., mohd, k.n. (2018), oil price and banking sectors in gulf cooperation council economies before and after the global financial turmoil: descriptive analysis. international journal of energy economics and policy, 8(6), 89-101. santillán-salgado, r., calderón-villarreal, c., venegas-martínez, f. (2017), impact of oil prices on stock markets in major latin american countries (2000-2015). international journal of energy economics and policy, 7(4), 205-215. serkan, y.k., ozturk, i., acaravcı, a. (2013), causality between natural gas prices and stock market returns in turkey. economia politica, 30(2), 203-220. sharma, a., giri, s., vardhan, h., surange, s., shetty, r., shetty, v. (2018), relationship between crude oil prices and stock market: evidence from india. international journal of energy economics and policy, 8(4), 331-337. tehranchian, a., seyyedkolaee, m. (2017), the impact of oil price volatility on the economic growth in iran: an application of a threshold regression model. international journal of energy economics and policy, 7(4), 165-171. trang, n., tho, t., hong, d.t. (2017), the impact of oil price on the growth, inflation, unemployment and budget deficit of vietnam. international journal of energy economics and policy, 7(3), 42-49. van dijk, d., teräsvirta, t., franses, p. (2002), smooth transition autoregressive models: a survey of recent developments. econometric reviews, 21(1), 1-47. zaiane, s. (2018), the impact of political instability driven by the tunisian revolution on stock market volatility: evidence from sectorial indices. the journal of applied business research, 34(2), 339-354. international journal of energy economics and policy vol. 4, no. 4, 2014, pp. 693-705 issn: 2146-4553 www.econjournals.com 693 economic evaluation of climate protection measures in germany christian lutz gesellschaft für wirtschaftliche strukturforschung (gws) mbh, institute of economic structures research, germany. email: lutz@gws-os.com ulrike lehr gesellschaft für wirtschaftliche strukturforschung (gws) mbh, institute of economic structures research, germany. email: lehr@gws-os.com philip ulrich gesellschaft für wirtschaftliche strukturforschung (gws) mbh, institute of economic structures research, germany. email: ulrich@gws-os.com abstract: the paper builds on a study "policy scenarios for climate protection vi". in the current policy scenario (cps) all measures which have been implemented by july 8 2011 are considered. in the energy transformation scenario (ets) additional measures are included to reach the climate targets of the german government until 2030. both policy scenarios build on the same socio-economic assumptions and just differ by climate protection measures. investment in climate protection will reduce energy consumption in the long term and shift it towards low or zero carbon energy carriers. scenarios are implemented in the model panta rhei. results of more ambitious climate protection measures are positive: annual gross domestic product will be 25 to 30 billion euros higher in the ets compared to the cps. positive employment impacts are in the range of 200 thousand additional jobs. energy efficiency improvements increasingly contribute via reduced energy imports in the long term. keywords: climate mitigation; energy efficiency; economy-energy-environment model; economic impacts jel classifications: c54; c67; q43 1. introduction energy efficiency measures and the promotion of renewable energy sources are the two main pillars of the european energy strategy. the german government decided in autumn 2010 on a new energy concept (bmu, bmwi, 2010). “energy policy is facing enormous challenges: the bulk of our energy is to come from renewable sources by the middle of the century. at the same time, germany is to remain a competitive business location. this requires the complete restructuring of our energy system” (bmwi, 2012). key components of this energy concept were 8 to 14 years lifetime expansion for nuclear power plants and measures to foster energy efficiency and renewable energy. on the demand side, i.e. concerning energy efficiency, insulation of buildings is the most important of a number of measures. for the electricity sector, the continued expansion of partly intermittent renewable energy sources, such as wind and photovoltaic generation, calls for new market design. due to the strong increase in pv capacity between 2010 and 2012 this has become a pressing issue for german energy policy. feed-in-tariffs for renewable energy sources will remain at least until 2020, but are to be adjusted to improve market integration of renewables and limit electricity price increase. the central targets of the new energy concept are to reduce greenhouse gas emissions by 40% by 2020 and 80-95% by 2050 (compared with 1990 levels). by 2020, the share of renewables in final energy consumption is to reach 18%, and then gradually increase further to 60% by 2050. the share in international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.693-705 694 electricity production is to reach 80% by 2050. concerning energy efficiency, the new energy concept aims to reduce primary energy consumption by 20% by 2020 and 50% by 2050 compared to 2008. in the light of the fukushima daiichi nuclear disaster in march 2011, the german government decided to phase-out nuclear energy until 2022. on the basis of the energy concept adopted in 2010, the federal government laid the ground in the summer of 2011 with a comprehensive package of legislation. the government has established an annual monitoring process (bmwi, bmub, 2014), which is reviewed by a group of independent experts (löschel et al., 2014). recent results indicate that germany is on track to meet renewables targets in the power sector, but lagging behind concerning efficiency, particularly in the heating sector. additional measures are currently discussed to fill at least part of the gap. the results presented in this paper are based on a study on the „economic evaluation of climate protection measures and instruments for different policy scenarios.” detailed policy scenarios have been developed in the study “policy scenarios for climate protection vi” (matthes et al., 2013), published by the german environmental agency in march 2013. these scenarios are reported as official national ghg projections to the unfccc. they are the basis for the model analysis of economic impacts of climate protection measures. the policy scenarios cluster the description of policy measures in two scenarios: in the current policy scenario (cps) all measures which have been implemented by july 8 2011 are considered. in the energy transformation scenario (ets) additional measures are taken into account to reach the climate targets of the german government until 2030. for the economic valuation of measures the two scenarios ets and cps are compared. the main results of the scenarios with regard to energy and emissions developments are described in matthes et al. (2013): in the cps compared to the reference year of 1990, a 34 % reduction of the emissions of greenhouse gases is achieved by 2020. by 2030 the emissions are reduced by 44 %. primary energy consumption in germany decreases by 9 % by 2020 and by 19 % by 2030 compared to 2008. in the ets additional measures bring about an emission reduction of approx. 42 % by 2020 and of more than 58 % by 2030 (compared to 1990). primary energy consumption in germany decreases in this scenario by approx. 16 % by 2020 and by approx. 32 % by 2030 compared to 2008. a main challenge of the modeling approach is to consider the overall economy wide effects of improved energy efficiency together with a detailed analysis of the technical change that drives the energy efficiency improvements and the specific investment decisions of economic agents. traditionally, models are specialized on one of these aspects. either they consider economy wide effects and relations (top-down models) or they are explicit about the technologies and their dynamics (bottom-up models). as a result of the shortcomings of both approaches, either hybrid models that combine both aspects or soft links of both model types are increasingly used in recent years. here results of detailed bottom-up models (matthes et al., 2013) are implemented in a top-down model. in contrast to former research on renewable energy (lehr et al., 2008, 2012) the paper presents recent results of economy-wide impacts of adopted and planned climate mitigation measures with a focus on energy efficiency in germany. it is organized as follows: in section 2 concepts to measure costs and benefits of climate mitigation measures are described. the macro-econometric input-output model panta rhei, which is applied to compare costs and benefits of scenarios ets and cps in section 3, is also introduced in section 2. in section 3 results are presented. discussion including comparison to other studies follows in section 4. section 5 closes with some conclusions and policy implications. 2. methods 2.1. measuring costs and benefits of climate mitigation costs and benefits of greenhouse gas mitigation are both nationally and internationally extensively studied. bottom-up studies provide detailed insights into the potential in each sector and the spending that is associated with it. macroeconomic modelling approaches bring together the findings of the various sectors and provide a macroeconomic assessment, which often helps to understand that spending has a cost and an investment aspect, i.e. creates burden and opportunities at the same time. what is perceived in partial analyses as cost can develop macroeconomic stimulus, i.e. a positive impact on growth and employment. in interpreting results, perspectives of private and social economic evaluation of climate protection measures in germany 695 costs and benefits should not be mixed. if also the benefits of climate change mitigation are included in the analysis, even more attention has to be paid to the separation of effects: while the incentives for single economic agents are driven by preferences and short-term economic returns, whether through energy conservation, the remuneration of green electricity or avoidance of penalties, total economic benefit lies rather in the long-term prevention of climate damage and long-term growth paths, as well as increased economic activities in short and medium term. the literature essentially falls into three categories: scenario studies that project future emission levels and identify the damage of climate change (e.g. ipcc, 2014); scenario studies that develop energy scenarios and macroeconomic effects of a certain energy mix compared to reference or counterfactual scenarios, partly estimating the associated different climate costs (dg energy, 2012; prognos, ewi, gws, 2010) and explicit analyses of the costs and benefits of renewable energy expansion or efficiency measures, focusing on measures or packages of measures as they have been submitted for germany (pregger et al., 2013), other countries such as greece (markaki et al., 2014), which includes an overview of further country studies, turkey (elsland et al., 2014) and the eu in individual studies. abeelen et al. (2014) look into impacts of energy efficiency improvements in dutch industry. tuominen et al. (2013) find positive economic impacts of measures in the building sector in finland. according to filippini et al. (2014) there is a high technical and economic potential of further energy efficiency improvement in the eu. in this paper the predominantly used cost and benefit categories in the literature are briefly reflected, as well as their underlying assumptions and methods. the aim is to isolate those categories, quantities and methods of calculation which make the most sense for a cost and benefit analysis of climate protection scenarios. further co-benefits of energy efficiency measures with a focus on health are described e.g. in maidment et al. (2014). comparing the results of the various studies is important for policy decisions. for such a comparison a thorough understanding of characteristics which affect the results is important. the methodology should be taken into consideration to the extent that it determines results. a best-practice procedure for the assessment of climate change costs and benefits should fulfill the following general requirements for good practice of cost and benefit assessment of mitigation measures: analyses are essentially determined by the data base used. one example is the changes in energy prices between 2005 and 2010. studies which do not take these price changes into consideration are not valid any more. the same holds for technological developments such as the drastic cost reductions in renewable energy, particularly in pv in the last years. the decision to phase out nuclear energy represents a similar milestone. transparency means first of all accountability for third parties. a comprehensive documentation facilitates to recognize differences to other calculations and models. the documentation of important assumptions such as energy prices or technology development is central. it must be clear which variables are considered in the analysis as exogenous. the model type used or the methodology generally should match the research question. in macroeconomic considerations with complex feedback processes, top-down approaches are necessary because bottom-up approaches do not consider economic feedback. however, a technically oriented optimization can be used as technological foundation. the choice of reference scenarios is crucial for the evaluation of climate change policies. the more ambitious the technical development proceeds in the reference, the lower the potential benefits or costs will be. this effect is reinforced by the fact that the first measures taken typically are the most cost-effective, i.e. ceteris paribus initially taken mitigation measures are economically more advantageous. temporal and spatial definition must both be appropriate to the research question. for example, if measures are considered, in which the individual economic decision calculus spans decades (buildings, infrastructure or dikes), a correspondingly long period of time has to be considered. the analysis of future climate change policies should, therefore, at least run up to the year 2030, better 2050, because the useful life of many efficiency measures ranges so long. the model analysis below takes these requirements of good practice analysis into account. panta rhei is a top-down model with the scenarios being derived from detailed bottom-up studies with other models. the database includes recent developments. the reference is taken from a recent international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.693-705 696 and official government report. temporal and spatial solution seems appropriate for the research question. 2.2. model panta rhei the economy-energy-environment model panta rhei is at the core of our methodological approach. panta rhei (lutz et al., 2005; lehr et al., 2008; meyer et al., 2012) is an environmentally extended version of the econometric simulation and forecasting model inforge (ahlert et al., 2009; meyer et al., 2007). a detailed description of the economic part of the model is presented in maier et al. (2013, 2014). for detail of the complete model see lutz (2011). among others it has been used for economic evaluation of different energy scenarios that have been the basis for the german energy concept in 2010 (lindenberger et al., 2010; nagl et al., 2011). recent applications include an evaluation of green ict (welfens, lutz, 2012), and employment impacts of renewable energy promotion (lehr et al., 2012). a similar model with the same structure for austria (stocker et al., 2011) has recently been applied to the case of sustainable energy development in austria until 2020. the behavioral equations reflect bounded rationality rather than optimizing behavior of agents. all parameters are estimated econometrically from time series data from 1991 to 2010. producer prices are the result of mark-up calculations of firms. output decisions follow observable historic developments, including observed inefficiencies rather than optimal choices. the use of econometrically estimated equations means that agents have only myopic expectations. they follow routines developed in the past. this implies in contrast to optimization models that markets will not necessarily be in an optimum and non-market (energy) policy interventions can have positive economic impacts. the model is empirically evaluated: the parameters of the structural equations are econometrically estimated. in the model-specification stage various sets of competing theoretical hypotheses are empirically tested. as the resulting structure is characterized by highly nonlinear and interdependent dynamics the economic core of the model has furthermore been tested in dynamic expost simulations. the model is solved by an iterative procedure year by year. structural equations are modeled on the 59 sector level (according to the european 2 digit nace classification of economic activities) of the input-output accounting framework of the official system of national accounts (sna) and the corresponding macro variables are then endogenously calculated by explicit aggregation. in that sense the model has a bottom-up structure. the input-output part is consistently integrated into the sna accounts, which fully reflect the circular flow of generation, distribution, redistribution and use of income. the core of panta rhei is the economic module, which calculates final demand (consumption, investment, exports) and intermediate demand (domestic and imported) for goods, capital stocks, and employment, wages, unit costs and producer as well as consumer prices in deep disaggregation of 59 industries. the disaggregated system also calculates taxes on goods and taxes on production. the corresponding equations are integrated into the balance equations of the input-output system. another important outcome of the macro sna system is net savings and governmental debt as its stock. both are important indicators for the evaluation of policies. the demand side of the labor market is modeled in deep industry disaggregation. wages per head are explained using philips curve specifications. the aggregate labor supply is driven by demographic developments. the energy module describes the interrelations between economic developments, energy consumption and related emissions. the relations are interdependent. economic activity such as gross production of industries or final consumer demand influence respective energy demand. vice versa, the expenditures for energy consumption have a direct influence on economic variables. the energy module contains the full energy balance with primary energy input, transformation and final energy consumption for 20 energy consumption sectors, 27 fossil energy carriers and the satellite balance for renewable energy (ageb, 2013). all together, the balances divide energy consumption into 30 energy carriers. prices, also in euros per energy unit, are modeled for different energy users such as industry, services and private households for all energy carriers. the energy module is fully integrated into the economic part of the model. economic evaluation of climate protection measures in germany 697 final energy consumption of industries is explained by sector output, the relation of the aggregate energy price – an average of the different carrier prices weighted with their shares in the energy consumption of that sector – and the sector price and time trends, which mirror exogenous technological progress. for services, the number of employees turned out to be a better proxy for economic activity than gross output. average temperatures also play a role for the energy consumption of the service sector. for private households, consumption by purpose as heating or by fuels is already calculated in the economic part of the model in monetary terms. additional information can be taken from stock models for transport and heating from the specific modules, as only new investments in cars, houses or appliances, or expensive insulation measures will gradually change average efficiency parameters over time. final demand of each energy carrier for industries can be calculated by definition, multiplying the share of the carrier with overall final energy demand of the sector. for the shares, the influence of relative prices, the price of the energy carrier in relation to the weighted price of all energy inputs of the sector, and of time trends are econometrically tested. energy carrier prices depend on exogenous world market prices for coal, oil and gas and specific other price components such as tax rates and margins. for electricity different cost components such as the assignment of the feed-in-tariff for electricity are explicitly modeled. for services, households and transport specific prices are calculated, as for example tax rates partly differ between end users. for energy-related carbon emissions, fix carbon emission factors from the german reporting (federal environmental agency 2013) to the united nations framework convention on climate change (unfccc) are applied. multiplication with final energy demand gives sector and energy carrier specific emissions. all detailed information in the energy balance for 30 energy carriers is consistently aggregated and linked to the corresponding four industries of the io table. to examine the economic effects of additional climate protection measures with a focus on energy efficiency in germany our analysis applies panta rhei to a set of scenarios and compares the resulting economic outcomes. the scenarios are taken from the policy scenarios for the german federal environmental agency (matthes et al., 2013), which have been reported to the unfccc as projections of german emissions. 3. results all policy scenarios stem from the study “policy scenarios for climate protection vi” (matthes et al., 2013), published by the german federal environmental agency in march 2013. they are the basis for the model analysis of economic impacts of climate protection measures. the policy scenarios cluster the policy measures in two central scenarios: in the current policy scenario (cps) all measures which have been implemented by july 8 2011 are considered. in the energy transformation scenario (ets) additional measures are taken into account to reach the climate targets of the german government until 2030. for the economic valuation of measures ets and cps are compared. additionally, for part of the policy areas a so called “no measures scenario” (nms) is defined, which only includes measures implemented until the end of 2004. it is used in a sensitivity analysis to calculate macroeconomic impacts of cps in relation to nms to measure effects of early action. the policy scenarios build basically on the same socio-economic assumptions, e.g. concerning international development as energy prices or gdp growth, and demography. the scenarios just differ by climate protection measures, which are specified extensively in matthes et al. (2013) applying detailed bottom-up sector models. investment in climate protection will reduce energy consumption in the long term and shift it towards low or zero carbon energy carriers. differences in investment (see figure 1) are adopted from that source as well as changes in energy use and emissions. in this way, they are based on the sophisticated bottom-up modelling and detailed observations on the level of policy measures for sectors there. the additional spending enters the model as investment in equipment and buildings as well as consumption expenditures. depreciation, annual interest payments and savings reductions to finance the investment are fully included in the model. due to the cost-efficiency of measures, additional international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.693-705 698 expenditure and investment will not crowd out other investments or consumption. energy savings and the decrease in energy costs are fully accounted for in the model. in scenario ets annual additional annual investment in climate protection, especially in insulation of buildings, will reach 25 to almost 40 billion euros. investment is mainly for energy efficiency with a focus on housing insulation. significant additional investment is also needed in transport, electricity production and for more efficient appliances in electricity consumption of private households. figure 1. additional investment in scenario ets compared to cps in mill. euros source: matthes et al. (2013) the use of a comprehensive macroeconomic model, which depicts the inter-industry structure of the economy, has the advantage of covering the complex interactions of different effects in the categories of official statistics. due to the applied scenario technique impacts of developments or measures of the respective reference scenario are not taken into account in looking at differences. figure 2. impacts on gdp in constant prices – scenarios ets and cps against respective baseline in bill. euros 0 5.000 10.000 15.000 20.000 25.000 30.000 35.000 40.000 45.000 2015 2020 2025 2030 industrial processes electricity production industry electricity private households transport trade and services 0 10 20 30 40 50 60 2015 2020 2025 2030 in b ill . e ur os cps to nms ets to cps ets to nms economic evaluation of climate protection measures in germany 699 macroeconomic effects of ets compared to cps are predominantly positive. gdp will be 25 to 30 billion euros higher in the ets compared to the cps (figure 2). positive employment impacts are in the range of 200 thousand additional jobs (figure 3). construction investment contributes to a great extent, with the difference reaching 19 billion euros in 2025. but also equipment investment plays an important role. private consumption will also be higher compared to the cps until 2020. however, cost increases due to financing additional housing insulation, less reduced spending on energy consumption, will partly crowd out other consumption. energy efficiency improvements increasingly contribute via reduced energy imports in the long term. as very expensive energy imports are reduced, prices for all imports are also lower on average. the higher energy import prices are the higher import reduction in monetary terms will be (see table 1). figure 3. impacts on employment – scenarios ets and cps against respective baselines in 1000 table 1. macroeconomic impacts – scenario ets against cps 0 50 100 150 200 250 300 350 400 2015 2020 2025 2030 in 1 00 0 cps to nms ets to cps ets to nms absolute values deviations in % ets to cps 2013 2015 2020 2025 2030 2013 2015 2020 2025 2030 gdp and components gdp 15.5 24.4 29.9 28.2 29.8 0.6 0.9 1.1 1.0 1.1 private cons umption 9.5 14.7 11.7 4.3 2.7 0.7 1.0 0.8 0.3 0.2 governm ent cons um ption 0.6 0.9 0.9 0.7 0.7 0.1 0.2 0.2 0.1 0.1 equipm ent inves tment 6.0 9.5 9.9 8.3 9.3 2.6 4.0 4.1 3.3 3.5 cons truction 3.5 5.7 14.5 19.0 18.9 1.6 2.6 6.7 9.0 9.0 exports 0.5 0.5 -0.3 -0.6 0.4 0.0 0.0 0.0 0.0 0.0 imports 4.7 7.1 6.9 3.4 1.9 0.4 0.6 0.5 0.2 0.1 price indices private cons umption -0.10 -0.14 -0.02 0.12 0.10 -0.09 -0.12 -0.01 0.09 0.08 production -0.14 -0.16 0.05 0.28 0.34 -0.12 -0.14 0.04 0.22 0.25 imports -0.08 -0.18 -0.42 -0.86 -1.35 -0.07 -0.16 -0.35 -0.69 -1.04 labor market em ploym ent 123 189 218 199 190 0.3 0.5 0.6 0.5 0.5 unem ploym ent -76 -117 -135 -123 -118 -3.3 -5.0 -5.5 -5.5 -8.0 deviations in bill. € deviations in percentage points deviations in 1000 international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.693-705 700 on industry level construction will profit most due to increased housing insulation (table 2). positive impacts on manufacturing, trade and services are getting significantly smaller after 2020. trade and services face the lower effects on private consumption. macroeconomic impacts will further improve, if climate protection measures of the years 2005 to 2011 are considered as well. they will induce higher investment, more jobs and reduced energy consumption. in scenario cps annual gdp is about 20 billion euros higher compared to the nms scenario with no measures from 2005 onwards in the years 2013 to 2025. compared to the above comparison between scenarios ets and cps private consumption is constantly more important, while the share of investment is reduced and significantly lower than in the comparison of ets to cps. construction investment plays a major role throughout the observation period. imports start to increase clearly with gdp. with growing reduction of energy imports total imports are a bit lower in cps than in the nms in 2030 (figure 2). employment effects are highest in 2020. in the following years the positive impact on employment levels off at around 150 to 175 thousand. on industry level construction due to additional insulation as well as trade, services and manufacturing will profit. the impacts for trade and services are lower as private consumption will increase below average due to budget constraints, i.e. money spent for building insulation is not available for other consumption purposes. the positive employment effect is shrinking over time. in (conventional) energy and water industry employment is reduced because of lower energy supply. the positive macroeconomic effects are the results of different impacts: additional investment yields additional production and therefore additional employment, energy is replaced by capital, imports as crude oil, gas and coal are replaced by domestic value added, construction, trade and services are more labor intensive than the energy industry, energy efficiency improves economic productivity and thus competitiveness, and short term higher demand for (efficient) investment goods and equipment improves private budgets and induces additional incomes. table 2. impacts on sector employment – scenarios ets and cps against respective baselines in 1000 the reduction of energy-related greenhouse gas emissions in scenario ets compared to cps will also reduce external costs of energy supply, which are not accounted for in macroeconomic sna data. using the methodological convention on the estimation of external environmental costs of the federal environmental agency (2012), avoided losses due to climate mitigation measures can be calculated on the basis of emission reductions of scenario ets in relation to cps. annual avoided losses as social costs of carbon account for between 11.5 and more than 35 billion euros in current prices. co2 emissions will be 164 million tonnes lower in 2030 in ets compared to cps. assumed social costs of carbon in the methodological convention range between 40 and 215 euros per tonne of co2 for 2030. 4. discussion the positive macroeconomic effects of the considered climate mitigation measures are robust with respect to major assumptions. a sensitivity analysis shows that positive economic impacts are mainly driven by energy efficiency measures, particularly in buildings. trade and services, transport and electricity of private households contribute significantly to positive gdp impacts throughout the ets to cps 2013 2015 2020 2025 2030 2013 2015 2020 2025 2030 employment mining and quarrying 0.1 0.2 0.3 0.3 0.2 0.2 0.3 0.6 0.7 0.7 manufacturing 21.1 27.3 25.1 21.7 22.3 0.3 0.4 0.4 0.4 0.4 energy and water s upply -0.2 -0.7 -1.5 -3.0 -4.4 -0.1 -0.3 -0.6 -1.3 -1.9 cons truction 16.0 34.8 87.1 109.4 102.1 0.9 2.0 5.2 7.1 7.0 trade and s ervices 70.0 103.4 81.6 50.0 50.3 0.3 0.4 0.3 0.2 0.2 total 107.1 164.8 192.7 178.4 170.5 0.3 0.5 0.6 0.5 0.5 deviations deviations in % economic evaluation of climate protection measures in germany 701 whole observation period. the share of industry measures increases over time. electricity production only plays a minor role, as additional renewable energy production is partly offset by lower production from conventional power plants (figure 4). figure 4. sensitivity analyses for impacts of mitigation measures in different sectors on gdp in constant prices – scenario ets against cps in bill. euros assumptions about crowding out of additional investment in climate mitigation are important for magnitude and direction of macroeconomic impacts (figure 5). a second sensitivity analysis looks into the extreme of full crowding out for the scenario ets, assuming that additional investment in climate protection measures substitutes other investment completely. even under this extreme assumption, as energy efficiency will at least partly substitute energy with capital, macroeconomic impacts of ets compared to cps remain positive. however, assuming full crowding out will reduce the positive impacts especially at the beginning of the observation period clearly. in the short term, positive stimuli of additional investment are missing. figure 5. impacts on employment – scenarios ets, and ets with full crowding out against baseline cps in 1000 0 5 10 15 20 25 30 35 2015 2020 2025 2030 in b ill . e ur os electricity production industry electricity private households transport trade and services buildings 0 50 100 150 200 250 2015 2020 2025 2030 in 1 00 0 ets to cps ets with crowding out to cps international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.693-705 702 there are different arguments that crowding out only plays a minor role for energy efficiency investment in germany at the moment: at a time of historically low levels of interest rates interesting investment opportunities are rare. german public investment bank kreditanstalt für wiederaufbau offers even lower interest rates for different energy efficiency investment programs. thus, energy efficiency investment, especially in housing insulation is attractive for private investors. additionally, the investment ratio, i.e. investment to gdp, at national level is quite low compared to historic development and in relation to other countries. under these circumstances companies and private households can easily finance additional energy efficiency investments. results are in line with the recent energy efficiency outlook of the iea (2013). an efficient world scenario developed in 2012 leads to a more efficient allocation of resources and comes along with macroeconomic benefits (chateau et al., 2013). on european level impact assessment for dg energy (2012) also finds positive macroeconomic impacts of energy efficiency improvement for member states. similar positive macroeconomic results are reported in country studies for germany (kuckshinrich et al., 2010; kronenberg et al., 2012; prognos, 2013; blazejczak et al., 2014) with annual net employment gains of some hundred thousand jobs due to additional energy efficiency measures and other countries such as greece (markaki et al., 2014). the study of blazejczak et al. (2014) shows that assumptions on wage bargaining are crucial for employment impacts, however. especially in construction large investments are needed for better insulations of buildings. as construction is an industry with high shares of domestic inputs and value added, economic stimuli of additional investment are quite high. as pointed out in section 2, the choice of reference scenarios is central for the evaluation of climate mitigation policies. as the cps scenario only includes policies already implemented in summer 2011, impacts include all additional measures that will come in place afterwards. results confirm direction and order of magnitude of other studies about macroeconomic impacts of climate mitigation measures in germany, especially for energy efficiency. keeping difficulties of detailed comparisons in mind, studies give evidence for the macroeconomic benefit of included energy efficiency measures. impacts of the strong increase in electricity production from renewable energy sources in recent years have been factored out to large extent due to the scenario design. major cost increases either took place before summer 2011, and are included in the cps already, or are not considered. results are dominated by energy efficiency investment and do not say much on impacts of renewable energy extension and related electricity price increases. another disputed aspect of economy-wide energy efficiency improvement is the magnitude of rebound effects, which can partly offset energy savings. recent results for germany are far from clear. galvin (2014) finds high rebound effects, while schleich et al. (2014) report low rebound effects for the case of lighting. figge et al. (2014) hint at further possible secondary effects beyond the rebound effect and potential backfire. the recent monitoring report (bmwi, bmub 2014) shows at least a reduction of energy consumption and an improvement of energy efficiency at the national level. this indicates that rebound effects should closely be monitored, but gives no hint for high rebound effects at place. 5. conclusions and policy implications results of more ambitious climate protection measures are positive: annual gross domestic product will be 25 to 30 billion euros higher in the energy transformation scenario (ets) compared to the current policy scenario (cps). positive annual employment impacts are in the range of 200 thousand additional jobs. energy efficiency improvements increasingly contribute via reduced energy imports in the long term. the positive macroeconomic effects of the considered climate mitigation measures are robust with respect to major assumptions. the results clearly show that additional climate mitigation efforts with a focus on energy efficiency result in a variety of positive impacts on the german economy. these range from reduced greenhouse gas emissions, reduced local air emissions and related negative impacts for human health, other external benefits, reduced energy import bills and more energy security, improved competitiveness of firms and budget savings for consumers to economy wide impacts like additional economic evaluation of climate protection measures in germany 703 employment and economic growth. thus, exploiting the huge potential stemming from cost-effective efficiency measures should have high priority for the design of energy and climate policies. however, different barriers to realize the efficiency potentials have to be taken into account (see iea 2012 for an overview). barriers include visibility, as energy efficiency is not measured, priority of other investment opportunities, uncertainty, split incentives, insufficient finance available, short time horizons, limited know-how, fragmentation and market failures, which may be driven by fuel subsidies. although the overall energy efficiency potential is large, it stems from completely different technologies and technology users. consequently, also the pattern of barriers to invest in energy efficient technologies is manifold and has to be addressed with a broad mix of sector and technology specific policies (e.g. fleiter et al., 2011 for industry). these will build on the existing mix of regulations, grants and price instruments and take possible undesirable feedback like rebound effects into account. according to the results german and eu energy and climate policy, which is currently focused on the cost of renewable energy promotion and reforms of the feed-in-tariff plus necessary extensions of the electricity grid and strengthening of the eu-ets, should concentrate more on energy efficiency and be opened to related issues as reduced external costs of energy consumption, energy security and new export markets for green technologies (bmu, 2012). in the context of eu climate and energy policy and national targets for energy efficiency improvement, which may not be reached due to the last monitoring report (bmwi, bmub 2014), germany should increase its efforts to foster energy efficiency improvements. this may include different kinds of regulations as well as price and tax incentives. the possibility of rebound effects should be accounted for in the policy design. the german government has recently announced an additional national “2020 climate and energy program” for autumn 2014. the findings also support explicit energy efficiency targets and energy efficiency policies, which are not only in place in germany and the eu, but also in all other major economies such as us, japan, china, india, russia and brazil (iea 2012, 276). the need for specific energy efficiency targets is sometimes doubted by climate economists, which see greenhouse gas emission reduction, triggered by a single carbon price, as the central and single policy target. according to this view additional energy efficiency targets are seen as an inefficient sub-target. but results indicate that energy efficient measures may have further positive macroeconomic impacts being a suitable second-best option in an imperfect world. the arguments for a growing focus on energy efficiency in climate and energy policy will hold even more, if the policy context is taken into account. the additional deployment of renewable energy in electricity beyond already ambitious targets for 2020 is limited, partly for technical reasons as the grid has to be adjusted. at the same time economic impacts of energy efficiency measures are less dependent on global market development than renewable energy policies (lehr et al., 2012). the construction sector uses a high share of domestic intermediate inputs. it is labor intensive and thus supports generation of value added and employment due to energy efficiency measures. more efficiency or new technologies will also keep german car companies competitive on global markets. companies specialized on energy efficiency goods and services can profit from cost degression on international markets and focus on growing markets abroad. in short, energy efficiency deployment should step up in (german) energy and climate policy. acknowledgements this research has been supported by the german federal environmental agency as part of the ufoplan research (fkz 3711 14 108: economic evaluation of climate protection measures and instruments for different policy scenarios). references abeelen, c., harmsen, r., worrell, e. (2014), implementation of energy efficiency projects by dutch industry. energy policy 63, 408–418. ageb (2013), arbeitsgemeinschaft energiebilanzen: energy balances for the federal republic of germany, berlin. international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.693-705 704 ahlert, g., distelkamp, m., lutz, c., meyer, b., mönnig, a., wolter, m.i. (2009), das iab/inforge-modell, in: p. schnur, g. zika (eds.) das iab/inforge-modell. ein sektorales makroökonometrisches projektionsund simulationsmodell zur vorausschätzung des längerfristigen arbeitskräftebedarfs. iab-bibliothek 318, nürnberg, pp. 15-175. blazejczak, j., edler, d. schill, w.-p. (2014), improved energy efficiency: vital for energy transition and stimulus for economic growth. diw economic bulletin 4 / 2014, pp.3–15. bmwi, bmub (2014), federal ministry of economics and energy (bmwi). federal ministry for the environment, nature conservation, building and nuclear safety (bmu), zweiter monitoringbericht „energie der zukunft“, berlin. bmu (2012), federal ministry for the environment, nature conservation and nuclear safety (ed.), greentech made in germany 3.0. environmental technology atlas for germany, berlin. bmwi (2012), federal ministry of economics and technology (bmwi). germany’s new energy policy. heading towards 2050 with secure, affordable and environmentally sound energy, berlin bmu, bmwi (2010), federal ministry for the environment, nature conservation and nuclear safety (bmu), federal ministry of economics and technology (bmwi). energy concept, berlin. chateau, j. (2013), economic implications of the iea efficient world scenario, oecd working party on climate investment and development, env/epoc/wpid(20132/rev1, oecd, paris. dg energy (2012), analysis of options beyond 20% ghg emission reductions: member state results, swd (2012) 5 final. elsland, r., divrak, c., fleiter, t., wietschel m. (2014), turkey’s strategic energy efficiency plan – an ex ante impact assessment of the residential sector. energy policy 70, 14–29. federal environmental agency [umweltbundesamt] (2012), ökonomische bewertung von umweltschäden. methodenkonvention 2.0 zur schätzung von umweltkosten. dessau-roßlau. federal environmental agency [umweltbundesamt] (2013), national inventory report for the german greenhouse gas inventory 1990 – 2011, dessau-roßlau. figge, f., young, w., barkemeyer, r. (2014), sufficiency or efficiency to achieve lower resource consumption and emissions? the role of the rebound effect. journal of cleaner production 69, 216-224. filippini, m., hunt, l., zorić, j. (2014), impact of energy policy instruments on the estimated level of underlying energy efficiency in the eu residential sector. energy policy 69, 73–81. fleiter, t., worell, e., eichhammer, w. (2011), barriers to energy efficiency in industrial bottom-up energy demand models, a review. renewable and sustainable energy reviews 15, 3099–3111. galvin, j. (2014), estimating broad-brush rebound effects for household energy consumption in the eu 28 countries and norway: some policy implications of odyssee data. energy policy, doi: 10.1016/j.enpol.2014.02.033. iea (2012), world energy outlook, paris. iea (2013), world energy outlook, paris. intergovernmental panel on climate change [ipcc] (2014), working group iii contribution to the ipcc 5th assessment report "climate change 2014: mitigation of climate change". kronenberg, t., w. kuckshinrichs, hansen, p. (2012), macroeconomic effects of the german government's building rehabilitation program, munich mpra paper no. 38815, forschungszentrum julich. online at http://mpra.ub.uni-muenchen.de/38815/ kuckshinrichs, w., kronenberg, t., hansen, p. (2010), the social return on investment in the energy efficiency of buildings in germany. energy policy 38, 4317-4329. lehr, u., nitsch, j., kratzat, m., lutz, c., edler, d. (2008), renewable energy and employment in germany. energy policy 36, 108-117. lehr, u., lutz, c., edler, d. (2012), green jobs? economic impacts of renewable energy in germany. energy policy 47, 358-364. lindenberger, d., lutz, c., schlesinger, m. (2010), szenarien für ein energiekonzept der bundesregierung. energiewirtschaftliche tagesfragen 60, 32-35. löschel, a., erdmann, g., staiß, f., ziesing, h.-j. (2014), expertenkommission zum monitoringprozess „energie der zukunft“. stellungnahme zum zweiten monitoring-bericht der bundesregierung für das berichtsjahr 2012, berlin, mannheim, stuttgart. economic evaluation of climate protection measures in germany 705 lutz, c. (2011), energy scenarios for germany: simulations with the model panta rhei, in: mullins, d, viljoen, j, leeuwner, h. (ed.) interindustry based analysis of macroeconomic forecasting. proceedings from the 19th inforum world conference, pretoria, pp.203-224. lutz, c., meyer, b., nathani, c., schleich, j. (2005), endogenous technological change and emissions: the case of the german steel industry. energy policy 33, 1143-1154. maidment, c. jones, c., webb, t., hathway, a., gilbertson, j. (2014), the impact of household energy efficiency measures on health: a meta-analysis. energy policy 65, 583–593. maier, t., mönnig, a., zika, g. (2014), labour demand by industrial sector, occupational field and qualification until 2025 – model calculations using the iab/inforge model. economic systems research, (forthcoming). maier, t., mönnig, a. & zika, g. (2013), trade and qualification linking qualification needs to germany's export flows. iab-discussion paper 7/2013, nürnberg. markaki, m., belegri-roboli, a., michaelides, p., mirasgedis, s., lalas, d.p. (2014), the impact of clean energy investments on the greek economy: an input–output analysis (2010–2020). energy policy 57, 263–275. matthes, f., busche, j., döring, u., emele, l., gores, s., harthan, r., hermann, h., jörß, w., loreck, c., scheffler, m., hansen, p., diekmann, j., horn, m., eichhammer, w., elsland, r., fleiter, t., schade, w., schlomann, b., sensfuß, f., ziesing, h. (2013), politikszenarien für den klimaschutz vi treibhausgas-emissionsszenarien bis zum jahr 2030, climate change nr. 04/2013, dessau-roßlau. http://www.umweltbundesamt.de/publikationen/politikszenarien-fuerden-klimaschutz-vi meyer, b., lutz, c., schnur, p., zika, g. (2007), economic policy simulations with global interdependencies: a sensitivity analysis for germany. economic systems research 19, 37-55. meyer, b., meyer, m., distelkamp m. (2012), modeling green growth and resource efficiency: new results. mineral economics 25, 145-154. nagl, s., fürsch, m., paulus, m., richter, j., trüby, j., lindenberger, d. (2011), energy policy scenarios to reach challenging climate protection targets in the german electricity sector until 2050. utilities policy 19, 185-192. pregger, t., nitsch, j., naegler, t. (2013), long-term scenarios and strategies for the deployment of renewable energies in germany. energy policy 59, 350–360. prognos (2013), ermittlung der wachstumswirkungen der kfw-programme zum energieeffizienten bauen und sanieren, studie im auftrag der kfw, berlin, basel. prognos, ewi, gws (2010), energieszenarien für ein energiekonzept der bundesregierung. study commissioned by the federal ministry of economics and technology (bmwi), basel, köln, osnabrück. schleich, j., mills, b., dütschke, e. (2014), a brighter future? quantifying the rebound effect in energy efficient lighting. energy policy 72, 35-42. stocker, a., großmann, a., madlener, r., wolter, m.i. (2011), sustainable energy development in austria until 2020: insights from applying the integrated model "e3.at". energy policy 39, 6082-6099. tuominen, p., forsström, j., honkatukia j. (2013), economic effects of energy efficiency improvements in the finnish building stock. energy policy 52, 181–189. welfens, p. j. j., lutz, c. (2012), green ict dynamics: key issues and findings for germany. mineral economics 24, 155–163. . international journal of energy economics and policy | vol 10 • issue 2 • 2020 89 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(2), 89-94. reasons for shifting and barriers to renewable energy: a literature review tarek safwat kabel1,2*, mohga bassim1 1department of economics and international studies, university of buckingham, mk18 1eg, uk, 2department of economics, university of sadat city, sadat city, egypt. *email: tarek.kabel@buckingham.ac.uk received: 11 september 2019 accepted: 13 december 2019 doi: https://doi.org/10.32479/ijeep.8710 abstract consumption of fossil fuel resources leads to serious economic and environmental issues such as (high fossil fuel subsidies, high carbon emissions, and high energy demand). this current economic situation needs new methods, which should generate sustainable solutions that are mostly independent of the use of fossil fuels. however, there are many barriers to the development of renewable energy. based on the literature the major barriers to renewable energy are economic, policy and legal, and technical. a literature review was performed in this paper to determine the reasons for shifting from conventional energy to renewable energy and identifies the barriers to the development of renewable power generation. keywords: renewable energy, fossil fuels, energy subsidies, co2 emissions, capital cost jel classification: q20, q40, q42 1. introduction in recent years, the world has been facing an energy crisis because of the increased demand for fossil fuels to meet the growing demand for energy. studies have shown that the world is facing a challenge in providing adequate resources for energy generation. the shortage is expected to be particularly in oil and natural gas, which the world has relied on for 55% of the global energy consumption (wec, 2016). perera (2018) argues that the burning of fuels is considered the main source of air pollution and greenhouse gases caused by human, which increased global warming. according to iea (2018), global carbon emissions grew by 1.4% in 2017, reaching 32.5 gt which is the highest increase in history. this high-level occurred despite the reduction, which happened in emission in the uk, japan, mexico, and the high reduction in the usa due to its increased dependence on renewable energy. the iea report highlighted the three key factors that played a crucial role in increasing global carbon emissions to be increasing global economic growth by 3.7%, lower fossil fuel prices, and ineffective energy efficiency policies. at the same time, fossil-fuel subsidies have been one of the reasons for the continued use of and slow shift from fossil fuels to renewable energy. according to iea (2018), global fossil-fuel consumption subsidies reached us$ 260 billion in 2016. electricity subsidies were us$ 107 billion, followed by oil subsidies accounted for 40% of total consumption subsidies (i.e., about $105 billion). natural gas subsidies and coal subsidies were $50 billion and $2 billion respectively over the same year. g20 spent 4 times more on fuel subsidies than it spent on renewable energy between 2013 and 2015 (doukas et al., 2017). the expansion in using renewable energy technologies is facing barriers. despite the significant decline in the costs in recent years, some studies argue that the costs are still one of the essential barriers to the development of renewable energy (ali et al., 2017; lyman, 2016; tse and oluwatola, 2015). this journal is licensed under a creative commons attribution 4.0 international license kabel and bassim: reasons for shifting and barriers to renewable energy: a literature review international journal of energy economics and policy | vol 10 • issue 2 • 202090 we aim to determine the reasons for shifting from conventional energy to renewable energy and identifies the barriers to the development of renewable energy. this paper reviewed numerous studies were concentrated in developed countries, some developing countries, and emerging countries, while there were a limited number of studies in the mena region. 2. reasons for shifting from fossil fuels to renewable energy 2.1. high fossil fuel subsidies the economic theory suggests that subsidies of fossil fuel fail in achieving their aim and goal in supporting the most unfortunate of society. subsidies of fuel proved to be poorly aimed because of high-income household, who are capable of affording a higher consumption level, catch most of the benefit. anand et al. (2013) reports 10% of the wealthiest households in india consumed fossilfuel subsidies 7 times greater than the poorest 10%. in sudan, the poorest 20% of the population absorbs only 3% of fuel subsidies, while more than 50% goes to the richest 20% (imf, 2014). bridle and kitson (2014) emphasised that subsidies of fossil fuel have effects and repercussions on investment decisions making it a harder competition for energy efficiency and renewable energy. in spite of the fact that many countries have reduced fuel subsidies throughout time, fuel subsidies remain high in developing nations (ahuja et al., 2009). iea (2018) estimates that $260 billion was consumed by subsidies of fossil fuel worldwide in 2016, rather than $310 billion in 2015. iea (2016) attributed this drop due to the fall in prices of oil and a subsidy reform process in dozens of countries as egypt, mexico and indonesia. a study by coady et al. (2016) found that post-tax subsidies of fossil fuel went from $4.9 trillion worldwide in 2013 to $5.3 trillion in 2015, this equals 6.5% of gdp in both years. this study reveals that the top five subsidisers of energy are china, usa, russia, the european union, and india. an early study by saunders and schneider (2000) found that fossil fuel subsidies paid by the government crowd out investment in more productive services such as health and education. in 2008, the government of indonesia spending on fuel subsidies is greater than it’s spending on education, defence, health and social security (iisd, 2011). according to whitley and van der burg (2015), in 40 developing countries fossil fuel subsidies are equivalent between 25% and 30% of government revenues. coady et al. (2016) estimate that pre-tax subsidies to fossil fuels were 0.7% of global gross domestic in 2011 and 2013. doukas et al. (2017) argue that fuel subsidies can be viewed as an obstacle and hurdle to investment and trading of renewable energy technologies. the study shows that g20 governments allocated yearly an average of $71.8 billion of public finance for fossil-fuel projects from the year of 2013 to the year of 2015, which was 4 times more than it allotted for renewables. 2.2. high energy demand adams et al. (2016) estimate that total global energy consumption will witness a raise by 28% from the period of 2015 to 2040, raising from 575 quadrillion british thermal units (btu) in 2015 to 663 quadrillion btu by 2030 and reaching 736 quadrillions btu by 2040. due to rapid population increase and high economic growth, energy demand is increased mainly in non-oecd countries. while comparing the energy consumption in both non-oecd countries and oecd countries from 2015 to 2040, a 41% rise is noticed in non oecd countries in comparison to a much smaller rise, a 9% rise, in oecd countries. in developing countries, there is an expected and anticipated increase of energy use by 90% rather than a 17% increase in industrialized countries by the year 2040. also, china’s energy demand is predicted to be twice as much that of the united states. it will be difficult and challenging to estimate the energy amount demanded globally by using fossil fuels solely, with the present increase in energy demand. shafiee and topal (2009) used three econometrics models to illustrate the relationship between fossil fuel reserves, their consumption and respective prices from the year of 1980 to the year of 2006. the study assumes that if world consumption rates of fossil fuels remains the same as the year 2006, resources will gradually ran out. oil will be the first to run out approximately in 40 years, natural gas following in approximately 70 years and coal in approximately 200 years. it means that coal will last significantly longer than other types of fossil fuel, and oil will run out earlier than natural gas and coal. according to studies, egypt encounters a difficulty and challenge in generating and attaining electricity from fossil fuels. in particular with oil and natural gas that alone equate to about 95% of egypt’s total energy mix in 2016 (eia, 2018). according to res4med (2015), egypt will encounter a challenge to accommodate the growing energy demand in time to come as a result of rapid utilization and rise of extraction costs for non-renewable resources. 2.3. high co2 emissions based on a literature review, a major source of co2 emissions is fossil fuel energy. according to irena (2014), burning fossil fuels releases about 80% of human-caused co2 emissions. this portion of emissions originates from coal by 44%, 36% from oil and 20% from natural gas. fossil fuels burning marked to be the main source of us greenhouse gas emissions from human activities (desai and harvey, 2017). rafindadi et al. (2014) used panel least square technique for the individual countries of asiapacific over a period from 1975 to 2012, asserted that there is a significant relationship between air pollution, energy consumption, and water productivity. the study showed that fossil fuel energy consumption plays a great role and impact on the air pollution variation in the area. china and india’s emissions have risen dramatically since 1990 and developing nations now produce more greenhouse gases than developed nations. much of that rise was due to the burning of coal. china is held responsible for nearly half of global coal trade (helm, 2016). goods and services exports from developing countries to developed countries are the primary cause of a growing share of co2 emissions from fossil fuel combustion (edenhofer et al., 2014). multiple studies have tried to assess and evaluate economic costs associated with fossil fuel-related co2 emissions. for example, watson et al. (2017) found that air pollution from burning fossil kabel and bassim: reasons for shifting and barriers to renewable energy: a literature review international journal of energy economics and policy | vol 10 • issue 2 • 2020 91 fuels currently costs the united states $240 billion a year, which marks 40% of the ongoing growth of the united states economy and 1.2% of the gdp. the study estimates that this number will grow within the next decade to $360 billion yearly, this is about 50% of the estimated growth of the economy. a recent study by stefanski et al. (2017) examined the relationship between a country’s emissions intensities and its gdp, by using the calibrated model for 170 countries during 1980-2010. the model found that over the last 30 years subsidy-like wedges have been a major cause of a quarter of global carbon emissions. the direct cost of fossilfuel price-distortions reached us$ 983 billion in 2010 only that equates to 3.8% of total global gdp in the same year. griffin (2017) envisions a rise of global temperature by the end of the century if no change is made in the increase of energy coming from burning fossil fuels and we continue with the same rates of 1988 to 2017. 3. barriers to the development of renewable energy a number of barriers to the market deployment of renewables have been listed in the literature. barriers discussed in this section are economic, policy and legal, and technical. 3.1. economic barriers 3.1.1. cost of technologies historically, high cost has been cited as one of the essential barriers to switching from the traditional energy sources to renewable energy sources. dufey (2010) highlights that the expense per installed megawatt of renewable energy remains more expensive compared to traditional energy production which makes the use of the traditional energy more wide spread, even though the renewable energy has positive impacts and its great future prospects are recognised. renewable energy projects requires a high investment, many aspects contribute to their high cost. starting from the technology used cost, hiring experts and specialists for project development, to the cost of the studies themselves and ensuring the feasibility of project and resources needed. chodkowska-miszczuk (2014) states that the rising and high cost of renewable energy are considered an obstacle to the evolution of the renewable energy system compared to conventional electricity. timmons et al. (2014) found that renewable electricity costs are sensitive and responsive to interest rates as a result of high capital costs of nearly all renewable energy resources. they also found that higher interest rates make traditional energy more attractive when compared to renewable sources, while lowinterest rates make renewables more attractive. the construction of large-scale renewable power plants is highly costly because of the high capital costs of renewable energy technologies (ali et al., 2017). for instance, in western europe, the cost of wind plants are 4.6 more than the cost of gas plants and large-scale pv plants are 14.1 more than the cost of gas plants (lyman, 2016). according to reddy and painuly (2004), multiple consumers prefer to maintain low initial costs instead of reducing operating costs that pays back over a longer period of time, which makes it harder for them to deal with renewable energy technologies because of higher initial costs. high initial investment costs of the systems represent a huge barrier to the rapid growth of solar pv, even with government incentives (tse and oluwatola, 2015). recent studies argue that renewable energy has become cheaper than traditional energy. wind costs decreased from $140/mw-h in 2009 to $47/mw-h in 2016 by 66% in just 7 years. the decrease in cost of utility-scale solar has been more dramatic, dropping 85% since 2009 to 2016 range of $46-$61/mw-h (lazard, 2016). a review by u.s. department of energy (2015) reported that since 2010, the price of installed solar energy has fallen by as much as half. at that time, the average price per photovoltaic unit decreased from 2.08 dollars/w to 0.66 dollars/w. the report shows that cost for solar energy has dropped by about 40% compared to 2015, which makes it economically competitive with traditional energy sources across the united states. costs of renewable energy may be cheaper than fossil fuels in some cases and places (pasqualetti, 2011). as stated by idc (2012), the cost of wind energy is competing with traditional energy market prices in areas with the best wind resources. in some countries, with high solar radiation, higher electricity prices and subsidies, solar pv is expected to reach grid parity. 3.1.2. access to finance another essential barrier to renewable energy technologies is financing. a research survey by reddy and painuly (2004) found that 40% of wind energy developers indicated that financing was a major barrier to renewable energy technologies. iee (2014) shows that high financing costs influence the competitive position of renewables, as renewable energy requires higher initial investment than traditional energy, although their operating costs are lower. renewable energy developers and customers may face difficulty in obtaining low-cost financing, as may be available for conventional energy facilities. nelson and shrimali (2014) estimated that about 90% of total project costs of photovoltaic, and hydropower are comprised of initial capital cost, while the initial investment of gas projects represents just one-third of the total cost of the discount life. iee (2014) points out that financial institutions are generally unfamiliar with renewable energy technologies and likely to recognise them as risky, so that they may lend funds at higher rates. for example, chile’s financial markets face difficulties in dealing with renewable energies. this is because of the absence of understanding non-traditional sources, guarantee requirements, uncertainties about long-term profitability, and the availability of alternatives in the traditional sector with lower risk and higher profitability (hatzfeldt, 2013). also, renewable energy technology in malaysia is suffering from a lack of appropriate support mechanisms and a high initial price. the study concluded that renewable energy technology is not economically viable in malaysia (yusoff and kardooni, 2012). renewable energy projects need access to long-term financing, due to high capital costs and low operating costs. in the lack of such long-term financing, investment choices will be directed kabel and bassim: reasons for shifting and barriers to renewable energy: a literature review international journal of energy economics and policy | vol 10 • issue 2 • 202092 toward traditional technologies that may be financially practical (hussain, 2013). in recent years, private investment has become the largest source of financing for renewable energy projects in different countries after the government played this role. this is due to two factors the costs of renewable energy technologies have declined, and renewable energy policies have encouraged private sector investment by creating new market opportunities (wüstenhagen and menichetti, 2012). 3.1.3. price distortion pelosse (2009) argues that the comparison between renewable energy and traditional energy prices is unfair because of the financial and political support, which traditional gained in the past and the benefits it still enjoys. several studies argue that the market prices of fossil fuels don’t indicate their actual costs. the study by biebl (2015) deduced the price of fossil fuels to be low in the united states because of government subsidies. without these subsidies, renewable energy producers would be in a better state to compete in the energy market. governments frequently choose to control the prices of electricity through subsidizing the price of fuel inputs to the power generation sector (bridle and kitson, 2014). according to komor and molnar (2015), pv can’t compete against subsidised diesel. the study found that subsidised diesel-fueled generates 66% of rural india’s electricity needs. these subsidies cause electricity to be priced lower in the rural poor, but cause difficulties in introducing renewable energy sources. (wef, 2016) estimates that without subsidies, more than 30 countries have already achieved grid parity between networks, and about two-thirds of the world will achieve grid parity within a few years. studies have shown that ignoring environmental and health cost for conventional energy also create price distortion. gboney (2008) points out that the existing pricing methodology for traditional generation sources in ghana ignores the environmental externalities of fossil-fuelled power plants into the calculations. kilonzo (2013) argues that renewable energy is costly in comparison to fossil fuels due to the pricing of fossil fuel not consisting of environmental externalities, such as health care costs. wind and solar energy from new plants in europe are cheaper than coal and nuclear power plants, given environmental and health risks (alberici et al., 2014). 3.2. non-economic barriers 3.2.1. policy and legal barriers in many countries, governments focus more on the traditional energy sector than on renewable energy. they give limited policy reinforcement in the area of renewable energy, by allocating low government subsidies to renewable energy compared to traditional energy subsidies (karekezi and kithyoma, 2003). this includes the absence of national r&d programs and low domestic spending on r&d (manuhwa, 2013). according to elliott (2013), shifting policies and changing priorities was one of the main difficulties faced by the united states in supporting renewable energy. however, the iea, 2018 remarked that the high reduction in pollution in usa is due to its increased dependence on renewable energy. a recent survey carried out by igcc (2017) revealed that the majority of australian and new zealand institutional investors weighed both policy uncertainty and lack of deals with appropriate risk-return objectives to be the main barriers to renewable energy investment. stadler (2016) argues that investment in renewable energy in australia is still slow with the potential for a largescale shortage of generation certificates by 2018. this is due to policy uncertainty as a constant feature of australia’s renewable energy industry. one of the top major obstacles to increasing investment in wind and solar energy in the united states stems from uncertainty about programs and policies at the federal and state level that aim to stimulate growth in renewables (luckow et al., 2015). forecasts out the development of renewable energy is expected to slow down in the next 5 years if policy uncertainty continues. the lack of a comprehensive legal and regulatory framework has been a main obstacle for investment in renewable energy technologies by independent power producers in ghana (gboney, 2008). chang and wang (2016) show that there are a number of regulations and laws regarding renewable energy and utilisation in china, which affects renewable energy development. 3.2.2. technical barriers renewable projects are confronted by technical and infrastructure barriers and challenges. nasirov et al. (2015) highlights network integration to be a primary challenge for renewable energy due to wide variety of qualifications, requirements, specifications and standards that change from country to country. the study finds that rets need a high level of the technical basis for their technological assessment. the absence of energy storage is becoming a main technical barrier to the electricity production from renewable energy resources. ren21 (2017) argues that major barriers to renewable energy growth are not associated to cost but to the restraints of current infrastructure. nasirov et al. (2015a) show that one of the top barriers to increased current and future renewable energy generation is the limited grid infrastructure in areas where renewable resources are most abundant. uncertainties regarding the existing data and information are among the main difficulties in this category of barriers. in this context, the chilean government faces hurdles incentivising the development of new transmission lines, especially in remote regions where renewable energy projects are often located. the risks related to renewable energy technology are high because technology is under development and risks are not known (wüstenhagen and menichetti, 2012). an early study by the national renewable energy laboratory has found the shortage and lack of skills and training as a primary obstacle to renewable energy development (ilo, 2011). unido (2009) points out that the main barrier in developing countries in the area of installing renewable energy is the absence of skills in numerous countries and different skills capacity throughout the country. the study highlights the difference in the concentration of installation and maintenance as they are much higher in urban areas than countryside. kabel and bassim: reasons for shifting and barriers to renewable energy: a literature review international journal of energy economics and policy | vol 10 • issue 2 • 2020 93 4. conclusion from the literature review, there are main reasons to shift from conventional energy to renewables. one of these reasons is that many countries are suffering from a gap between energy supply and the domestic energy demand for them. several studies have shown that fossil fuel energy subsidies fail in meeting their intended objectives. in addition, the literature illustrated that the fossil fuels consumption is major source of carbon dioxide emissions. fossil fuel energy is one of the main source of co2 emissions. this economic and environmental situation needs more feasible solutions that are self-sufficient and non-relying on the use of fossil fuels. barriers to renewable energy in the literature were classified into three categories economic, policy and legal, and technical. although high cost has been cited in the literature as one of the major barriers to shifting to renewable energy sources, recent studies indicate that cost of renewable energy has decreased over the last decade. some studies find that costs of renewable energy may be cheaper than fossil fuels in some cases and areas. in some countries, financial institutions are not quite acquainted with renewable energy and likely to recognise them as risky, and this is a main barrier to the deployment of renewable energy. within the literature, there are barriers other than economic that face renewable energy. in many countries, governments focus more on the traditional energy sector than on renewable energy. this leads to the lack of a comprehensive legal and regulatory framework that supports renewable energy. in addition, some authors found that major barriers to renewable energy generation are irrelevant to cost but to the limitations of current infrastructure, and the absence of skills and training. 5. acknowledgments this work is supported by the newton-mosharafa fund which is offered by the egyptian governmentministry of higher education (cultural affairs missions sector) and the british council. references adams, g., aloulou, f., aniti, l., boedecker, e., brown, w., chase, n., wells, p. (2016), international energy outlook 2016. in usdoe energy information administration (eia). avaialble from: https:// www.eia.gov/outlooks/ieo/pdf/0484(2016).pdf. ahuja, d., tatsutani, m., schaffer, d. (2009), sustainable energy for developing countries. surveys and perspectives integrating environment and society, 2(1), 1-16. alberici, s., boeve, s., van breevoort, p., deng, y., förster, s., gardiner, a., wouters, k. (2014), subsidies and costs of eu energy final report. brussels: european commission. ali, a., li, w., hussain, r., he, x., williams, b.w., memon, a.h. (2017), overview of current microgrid policies, incentives and barriers in the european union, united states and china. sustainability, 9(7), 1-28. anand, r., coady, d., mohommad, a., thakoor, v., walsh, j.p. (2013), the fiscal and welfare impacts of reforming fuel subsidies in india. imf working papers. vol. 13. washington, dc: international monetary fund. biebl, h. (2015), energy subsidies, market distortion, and a free market alternative. university of michigan journal of law reform, 46(1), 3-7. bridle, r., kitson, l. (2014), the impact of fossil-fuel subsidies on renewable electricity generation. manitoba, canada: international institute for sustinable development. chang, y., wang, n. (2016), legal system for the development of marine renewable energy in china. renewable and sustainable energy reviews, 75, 192-196. chodkowska-miszczuk, j. (2014), small-scale renewable energy systems in the development of distributed generation in poland. moravian geographical reports, 22, 34-43. coady, d., parry, i., sears, l., shang, b. (2016), how large are global energy subsidies? vol. 15. washington, d.c: international monetary fund. desai, m., harvey, r.p. (2017), inventory of u.s. greenhouse gas emissions and sinks: 1990-2015. vol. 82. united states: environmental protection agency. doukas, a., kate, d., ghio, n. (2017), talk is cheap: how g20 governments are financing climate disaster. canada: oil change international, friends of the earth u.s., the sierra club, and wwf european policy offic. p1-36. dufey, a. (2010), opportunities and domestic barriers to clean energy investment in chile. vol. 1. washington, d.c: international institute for sustainable development. edenhofer, o., pichs-madruga, r., sokona, y., minx, j.c., farahani, e., kadner, s., seyboth, k., adler, a., baum, i., eickemeier, p., kriemann, b., savolainen, j., schlömer, s., von stechow, c., zwickel, t., minx, j.c., eidtors. (2014), technical summary. in: climate change 2014: mitigation of climate change. contribution of working group iii to the fifth assessment report of the intergovernmental panel on climate change. cambridge, united kingdom and new york, usa: cambridge university press. eia. (2018), in country analysis brief: egypt. vol. 18. egypt: international energy data and analysis. p1-16. available from: https://www.eia.gov/beta/international/analysis_includes/countries_ long/united_arab_emirates/uae.pdf. elliott, e.d. (2013), why the united states does not have a renewable energy policy. newspaper. washington, dc: environmental law institute. gboney, w. (2008), policy and regulatory framework for renewable energy and energy efficiency development in ghana. climate strategies, 9, 1-23. griffin, p. (2017), the carbon majors database cdp: carbon majors report. london: cdp report. hatzfeldt, s. (2013), renewable energy in chile. journal of international affairs, 66, 199-209. helm, d. (2016), the future of fossil fuels is it the end? oxford review of economic policy, 32(2), 191-205. hussain, m.z. (2013), financing renewable energy options for developing financing instruments using public funds. in world bank. available from: http://www.documents.worldbank.org/ curated/en/196071468331818432/financing-renewable-energyoptions-for-developing-financing-instruments-using-public-funds. idc. (2012), green economy report : the cost evolution of renewable energies. sandton: industrial development corporation. iea. (2016), world energy outlook 2016 (executive summary). world energy outlook. p1-8. available from: http://www. i e a . o rg / p u b l i c a t i o n s / f r e e p u b l i c a t i o n s / p u b l i c a t i o n / w e b _ worldenergyoutlook2015executivesummaryenglishfinal.pdf. iea. (2018), energy subsidies. available from: http://www.iea.org/ statistics/resources/energysubsidies. iee. (2014), beyond energy action strategies. belgium: guideline for identification of barriers. p1-47. kabel and bassim: reasons for shifting and barriers to renewable energy: a literature review international journal of energy economics and policy | vol 10 • issue 2 • 202094 iisd. (2011), a citizin’s guide to energy subsidies in indonesia: 2012 update. international institute for sustainable development. ilo. (2011), a skilled workforce for strong, sustainable and balanced growth. geneva: international labour office. imf. (2014), energy subsidies in t the middle east and north africa: lessons for reform. washington, d.c: international monetary fund. irena. (2014), remap 2030:a renewable energy roadmap. international renewable energy agency, abu dhabi. karekezi, s., kithyoma, w. (2003), renewable energy development. the workshop for african energy experts on operationalizing the nepad energy initiative. dakar: operationalizing the nepad energy initiative. kilonzo, d.m. (2013), identifying and managing the market barriers to renewable energy in kenya. kenya: tampere university of applied sciences. komor, p., molnar, t. (2015), background paper on distributed renewable energy generation and integration. technology executive committee (tec). bonn: united nations framework convention on climate change (unfccc). lazard, d. (2016), lazard’s levelized cost of energy analysis version 10.0. new york. available from: https://www.lazard.com/ media/438038/levelized-cost-of-energy-v100.pdf. luckow, p., fagan, b., fields, s., whited, m. (2015), technical and institutional barriers to the expansion of wind and solar energy. cambridge,massachusetts, usa: synapse energy economics, inc. lyman, r. (2016), why renewable energy cannot replace fossil fuels by 2050? calgary: friends of science. manuhwa, m. (2013), a review of renewable energy policy and institutional frameworks possible for sadc countries. south africa: managing consultant of zimbabwe africa infrastructure development group. nasirov, s., silva, c., agostini, c.a. (2016), assessment of barriers and opportunities for renewable energy development in chile. energy sources, part b: economics, planning, and policy, 11(2), 150-156. nelson, d., shrimali, g. (2014), finance mechanisms for lowering the cost of renewable energy in rapidly developing countries. san francisco, ca: climate policy initiative. pasqualetti, m.j. (2011), social barriers to renewable energy landscapes. geographical review, 101(2), 201-223. pelosse, h. (2009), the true costs of conventional energy un chronicle. un chronicle, 46, 85. perera, f. (2018), pollution from fossil-fuel combustion is the leading environmental threat to global pediatric health and equity : solutions exist. international journal of environmental research and public health commentary, 15(1), e16. rafindadi, a.a., yusof, z., zaman, k., kyophilavong, p., akhmat, g. (2014), the relationship between air pollution, fossil fuel energy consumption, and water resources in the panel of selected asiapacific countries. environmental science and pollution research, 21(19), 11395-11400. reddy, s., painuly, j.p. (2004), diffusion of renewable energy technologies barriers and stakeholders ’perspectives. renewable energy, 29(9), 1431-1447. ren21. (2017), renewables global futures report: great debates towards 100% renewable energy. ren21: paris. res4med. (2015), delivering renewable energy investments in egypt: challenges and opportunities. annual conference. rome: res4med renewable energy solutions for the mediterranean. saunders, m., schneider, k. (2000), removing energy subsidies in developing and transition economies. abare conference paper. p14. shafiee, s., topal, e. (2009), when will fossil fuel reserves be diminished? energy policy, 37(1), 181-189. stadler, a. (2016), understanding the forces that are driving lgc prices now and into the future energetics. available from: https://www.energetics.com.au/insights/thought-leadership/ understanding-the-forces-that-aredriving-lgc-prices-now-andinto-the-future. stefanski, r., brechet, t., crucini, m., ganofsky, m., harding, t., kircher, p., storesletten, k. (2017), dirty little secrets: inferring fossil-fuel subsidies from patterns in emission intensities. oxcarre working papers. oxford: oxford centre for the analysis of resource rich economies. the investor group on climate change igcc. (2017), institutional investors and low carbon solutions. asia: the investor group on climate change. timmons, d., harris, j.m., roach, b. (2014), the economics of renewable energy. global development and environment institute. medford: tufts university medford. tse, l., oluwatola, o. (2015), evaluating renewable energy technology transfer in developing countries : enabling factors and barriers. journal of science policy and governance, 6(1), 1-10. u.s. department of energy. (2015), quadrennial technology review. washington dc: u.s. department of energy. unido. (2009), module 7 renewable energy technologies. sustainable energy regulation and policymaking training manual. unido: vienna, austria. watson, r., mccarthy, j.j., hisas, l. (2017), the economic case for climate action in the united states. vol. 5. alexandria, va: universal ecological fund. wec. (2016), world energy resources 2016. in: world energy council. london: world energy council. wef. (2016), renewable infrastructure investment handbook : a guide for institutional investors. geneva: world economic forum. whitley, s., van der burg, l. (2015), fossil fuel subsidy reform : from rhetoric to reality. london and washington, dc: new climate economy. wüstenhagen, r., menichetti, e. (2012), strategic choices for renewable energy investment : conceptual framework and opportunities for further research. energy policy, 40, 1-10. yusoff, s., kardooni, r. (2012), barriers and challenges for developing re policy in malaysia. 2012 international conference on future environment and energy. vol. 28. singapoore: iacsit press. p6-10. . international journal of energy economics and policy | vol 10 • issue 4 • 2020 221 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(4), 221-228. planning strategy of operation business and maintenance by analytical hierarchy process and strength, weakness, opportunity, and threat integration for energy sustainability suriyanti1, ahmad firman2, nurlina3, gunawan bata ilyas4, aditya halim perdana kusuma putra1* 1department of management, faculty of economics and business, universitas muslim indonesia, south sulawesi, indonesia, 2department of management, stie nobel indonesia, south sulawesi, indonesia, 3department of management, stimi yapmi, makassar, indonesia, 4department of management, stie amkop, south sulawesi, indonesia. *email: adityatrojhan@gmail.com received: 21 january 2020 accepted: 20 april 2020 doi: https://doi.org/10.32479/ijeep.9267 abstract this study integrates analytical hierarchy process (ahp) and strength, weakness, opportunity, and threat (swot) in strategic planning or strategy formulation to demonstrate the qualitative and quantitative integration of techniques between swot and ahp in developing business strategies in operation and maintenance (o&m) of power plants. apart from that, it is to evaluate essential factors in strategic planning and to utilize them in developing effective strategies for the o&m of power plants in the cepa. ltd. there are two stages of testing in this study, namely the first stage is data collection and swot and tows strength analysis. the second stage is the integration of swot and ahp. the study was conducted at cepa. ltd. as a private company operating in the power generation sector with a research period in the mid to end of 2019. result ot this study shown some elements of the strategy that can be done (1). the contract of cooperation with the industry parts supplier, (2). cooperation contracts can be pursued, one of which is by re-construction of a structured and timely payment process (3). optimizing company value can be achieved by optimizing csr (4). website optimization is a digital-based promotion tool (5). support in terms of resource development can be completed through training, for example, basic welder scaffolder and basic mechanical (6). any transactions process in foreign currencies to avoid fluctuating exchange rates at the time of purchase or payment. keywords: strength, weakness, opportunity, and threat, analytical hierarchy process, business operation management jel classifications: c44, d02, l00, l60 1. introduction sustainability of energy supply, especially electricity, is fundamental in supporting various production needs and all community needs. to support the continuity of electricity supply operation and maintenance (o&m) of a power plant is one crucial factor in the implementation of electricity supply to the community because electricity is a form of energy that is very important in human life. electricity plays a vital role in life. it can be a resume that power has become the primary energy source in every activity both in the household and industry (marcelina, 2016). some national energy problems in indonesia that must be resolved include; utilization of domestic energy that has not been optimal and limited energy infrastructure whose value-added has not been maximized, decreased production, and exploration, which is not yet optimal and complicated bureaucratic licensing. various challenges in energy management in indonesia, including government regulations and changes in the micro and macroeconomic cycle which can undoubtedly have a systemic impact on the planning and business strategy of electricity this journal is licensed under a creative commons attribution 4.0 international license suriyanti, et al.: planning strategy of operation business and maintenance by ahp and swot integration for energy sustainability international journal of energy economics and policy | vol 10 • issue 4 • 2020222 companies that are operating in indonesia. based on the indonesia energy policy number 79 year 2014, the policy is expected that energy sustainability must focus on independence, which was previously more dominantly obtained from imports. the challenge for global-scale energy for the next 50 years is to meet the needs of more than 2 billion people globally, so it is estimated that energy demand at that time will double the current request. in the context of meeting energy and electricity supply needs in indonesia, it must focus on access and affordability without compromising environmental responsibility (murdifin et al., 2019). besides electricity, other natural resources originating from indonesia are liquefied natural gas (lng), which also places indonesia as one of the largest exporters of lng, along with qatar, australia, and malaysia. the gas produced by indonesia is consumed by the world’s largest lng importers as well as japan and south korea, as well as the united kingdom and southern europe. in south sulawesi province, indonesia, there is a sengkang gas and steam power plant owned by pt energi sengkang and has been operating since 1997. its o&m have been submitted to pt consolidated electric power asia (pt. cepa), which is a company engaged in o&m services (o&m) electricity generation. the operation and management services offered by pt cepa are the management and operation of lng-based power plants. at present many new power plants are operating, and many of these companies are just investors who do not have expertise in power plant management. therefore cepa. ltd., which has expertise in operating and maintaining power plants as well as governance of power plants, has quite a long experience and has the opportunity to get this market but cepa. ltd. is not the only company that provides o&m services for power plants in south sulawesi and several other places in indonesia, several different companies that are also competent in this field, such as poso energy. ltd., malea energy. ltd., d&c engineering company, sulawesi mini hydro power. ltd., cogindo daya bersama. ltd., bakara bumi energi ltd., bima golden powerindo. ltd., sumber sewatama. ltd., pembasing jawa bali services. ltd., medco power indonesia, indonesia power ltd., and wartsila indonesia. ltd. responding to various challenges that not only come from the macroeconomic climate but also competition between operations and management (o&m) service providers. so that companies are required to be able to provide the best service through careful strategic planning and integrated business operations to support sustainable production. therefore the role of effective and efficient operations management is the cornerstone of the success of every company, and all investors will look at the operational conditions of a company before making an investment commitment. effective maintenance and management in power plants play a vital role in ensuring the availability of electric power (mutloane, 2009). because sustainability is fundamental to be understood and built into the business environment (wallis and valentinov, 2017). in theories of sustainability, a business can be stated to have a dynamic continuity as long as it does not collide with several important aspects such as aspects of social responses, environment, and culture (murdifin et al., 2019). some previous research results using analytical hierarchy process (ahp) applied in the evaluation of energy problems reveal that the application of the ahp method provides conclusions for top management in projecting and evaluating the utilization of renewable energy in various sectors (karakaş and yildiran, 2019). previous study by (gottfried et al., 2018) who analyzed the investment behavior in the energy sector by combining the ahp-strength, weakness, opportunity, and threat (swot) method found the fact that business strategies and investment behavior in the energy sector also showed maximum results to provide an overview of the operations management section on investment policies and even professional work objectives. other studies also reveal that the use of the ahp model combined with swot can also be used as a useful decision-making tool for business planning (barusman and redaputri, 2018) objectively this research integrates ahp and swot in strategic planning or strategy formulation to demonstrate the qualitative and quantitative integration of techniques between swot and ahp in developing business strategies in o&m of power plants. the purpose of this study is to evaluate essential factors in strategic planning and to utilize them in developing effective strategies for o&m power generation businesses. it will be imperative for policymakers to understand the importance of corporate environmental factors and to support the decision-making process. in this study, a swot analysis is used in conjunction with the ahp. the formulation of strategies that can be done by the company to develop and be sustainable is to formulate its business strategy. the wording of this strategy will be carried out through an industrial strategy management approach using strategic management tools. the weighting of internal and external vital factors in this study will be processed by the ahp method, and these strategic factors are then used in the input stage (ife and efe matrix) then the matching stage will be used (matrix swot/tows). 2. literature review 2.1. operation sustainable as a comprehensive strategic business planning business continuity illustrates the sustainability of the economy and society that can coexist continuously for a long time on a global scale (felix, 2018). business continuity is closely related to tqm (total quality management), which includes process quality, human resources, strategic quality planning, and information/ analysis (ramlawati and putra, 2018), (jenkins, 2009). teori keberlangsungan mencakup empat capital model seperti: social sustainability yang meliputi human capital (labour and skills, intelligence, social networks, political systems, trust and reputation and influence/power (šlaus and jacobs, 2011). in addition, the sustainability of a venture can be said to be sustainable if it exists on financial sustainability (cash, debt, investment, monetary instruments) (van bardeleben, 2011), (francois, 2018), and environmental sustainability element (resources, living systems dan ecosystems services) (geerlings and vellinga, 2017), (lal, 2016), (goodland, 2003). business continuity must also include elements of manufactured capital (infrastructure, machine and tools factories) (costanza and daly, 1992). the development of a sustainable operations strategy is a subset of business strategy planning related to supply chain management suriyanti, et al.: planning strategy of operation business and maintenance by ahp and swot integration for energy sustainability international journal of energy economics and policy | vol 10 • issue 4 • 2020 223 (sscm) (seuring and müller, 2008). specifically “sustainability” is generally measured using the conceptual triple-bottom-line concept (elkington, 1998), (murdifin et al., 2019). so it is very closely related to the duties of the company regarding profit and social and environmental responsibility. the main focus of corporate objectives has recently become very complex and requires companies to focus more on social and environmental issues that are more inclusive. operational sustainability’ is a method of evaluating whether a business can maintain existing practices without placing future potential resources at risk. sustainability can refer to any one of a variety of areas, say ecological resources, social or economic resources. operational management is a business that maximizes the use of all factors of production, both labor (hr), machinery, equipment, the raw material (raw materials), and other elements of production in the transformation process to become various kinds of products or services (huo and hong, 2013). the role and function of operations management are to carry out all features of the management process, starting from the planning process (gregory, 2012), organizing (faber et al., 2013), (teece et al., 1997), staff development, leadership and control (garg and deshmukh, 2006). the orientation of the operational part of the company, that directs output results in quantity, quality, price, time, and a specific place following user or consumer demand. in this case, the company’s operations are also responsible for producing goods or services, making decisions about the operating functions and transformation systems, and reviewing the decisions related to company operations (huo and hong, 2013). decision making for operations management in developing a sustainable business strategy, the operational part plays a vital role in maintaining the quality of physical processes and ensuring that the physical operations and production facilities are in place (in the right amount, on time, and in the right place). apart from that, the company’s services are also fully responsible for inventory management. in this case, to achieve sustainable business is a business goal to increase valued in the long run and create a positive image for everyone (laurence, 2011). sustainable business outcomes can be achieved by involving employees in an integrated management process because the value generally derived from employee involvement in the organization can be strengthened by implementing a comprehensive management pattern. most executives/leaders in the organization will articulate the company’s vision that can grow the economy and contribute to social values and encourage environmental management together. in today’s corporate strategy, the 3p concept (people, profit, and planet) relates to one another, and society depends on the economy and the company. profit is the most critical element and becomes the primary goal of every business activity. the benefit itself is essentially an additional income that can be used to ensure the survival of the company. while events that can be taken to boost profits include increasing productivity and carrying out cost efficiencies, so companies have a competitive advantage that can provide maximum added value (murdifin et al., 2019), people. realizing that the community is a stakeholder important for the company because their support is needed for the existence, survival, and development of the company. hence, as an integral part of the environmental community, the company needs to be committed to working to provide maximum benefits to them. it is essential to realize that the company’s operations have the potential to have an impact on society, so companies need to carry out various activities that touch community needs (murdifin et al., 2019), (gimenez et al., 2012). the planet. the environment is related to all areas of our lives. our relationship with the environment is a causal relationship, where if the company takes care of the situation, the situation will also benefit the global environment (elkington, 1998), (gimenez et al., 2012). 2.2. ahp and swot thomas saaty developed ahp in the 1970s (saaty, 2011), (khazaii, 2016). ahp is a decision making factor by using a mathematical model. ahp helps in determining the priority of several criteria by conducting a pairwise comparison analysis of each measure. ahp is a measurement theory through pairwise comparisons and relies on expert judgment to get a priority scale. ahp is based on a systematic pattern of human thought to deal with the complexity it captures so that it is realized in a method that formulates the problem in the form of a hierarchy and consideration is included to produce a relative priority scale. hierarchy is defined as a representation of a complicated issue in a multi-structure the level where the first level is the goal followed by the level of factors, criteria, sub-criteria, and so on until the last level of alternatives. with hierarchy, a complex problem can be broken down into groups, which are then arranged into a form of the hierarchy so that the problem will appear more structured and systematic. swot analysis is a technique to identify various factors systematically to formulate the company’s strategy (leigh, 2010), (piercy and giles, 1989) swot analysis has an essential role in business progress, which has been increasingly competitive in achieving its objectives. the meaning of swot is strengths, weaknesses, opportunities, and threats. which means strengths, weaknesses, opportunities, and threats. there are eight stages in building a swot matrix namely: make a list of critical external opportunities of the company, make a list of significant external threats of the company, make a list of essential internal strengths of the company, make a list of significant internal weaknesses of the company, match inner forces with external opportunities and record the results of so (strength and opportunity) strategy in the specified cell, match internal weaknesses with external opportunities and record the results of wo (weakness and opportunity) strategies in the specified cell, match internal strengths with external threats and record the results of st (strength and threat) strategies, match internal weaknesses with external threats and record the results of the wt (weakness and threat) strategy in the sections specified (piercy and giles, 1989). in the swot analysis, factor weights are not calculated to determine the effect of each factor on proposed alternative strategies. the swot analysis does not provide a way to systematically determine the relative importance of criteria or to assess alternative decisions according to standards. to overcome this, the swot framework was changed to a hierarchical structure, and the model was integrated and analyzed using the ahp method. the purpose of the ahp method in the swot analysis is to be able to determine the strategic factors that affect the company systematically (kurttila et al., 2002) and (görener et al., 2012). suriyanti, et al.: planning strategy of operation business and maintenance by ahp and swot integration for energy sustainability international journal of energy economics and policy | vol 10 • issue 4 • 2020224 stages in the integration of ahp and swot: (1). determine internal (strengths, weaknesses) and external (opportunities, threats) factors for strategic planning in the swot analysis. (2). make a pairwise comparison of each internal and external subfactor. (3). using the ahp method to determine the priority factor levels of each internal and external subfactor. the integration of swot and ahp analysis in strategic planning is carried out where the priority of internal and external factors is obtained by the ahp method, and then those priorities are used in the swot/ tows analysis to provide alternative strategies (oreski, 2012), (karakaş and yildiran, 2019) and (gottfried et al., 2018). ahp helps as an effective means of handling complex decision making for strategies to be prioritized and optimized. ahp will help to reduce bias in decision making during the swot analysis process (mu and pereyra-rojas, 2017). 3. research method and materials 3.1. sample and method the method approach in this study is an explorative qualitative analysis using the ahp, and swot approaches as a measure of its investigation. where the purpose of using ahp and swot is directed to test managerial, strategic decisions. the object of research is consolidated electric power asia, ltd. (cepa), which is one of the companies engaged in o&m electricity generation services operating in south sulawesi province, indonesia. this research took place from march through november 2019. 3.2. measurement data collection includes primary data through the results of observations and interviews with the company’s internal parties, namely the operational and financial management. the stages in data analysis in this study are the first stage; (1) make a list of cepa. ltd. external opportunities. (2). list the company’s external threats (3). compile a list of important internal strengths of the company, (4). compile a list of company internal weaknesses, (5). matching internal strengths to external opportunities and compiling the results of the company’s strategy opportunity (so) analysis, (6). matching internal weaknesses to external opportunities and compiling company weakness-opportunity (wo) results, (7). matching internal forces with external threats and compiling company strategy threat (st) results, (8). matching internal weaknesses with external threats and compiling company weakness-threat (wt) results. the weighting of measurement instruments starts from 0.0 (not important) 1.0 (very important). the second stage is to integrate swot and ahp, where the scenes in this integration are: (1). determine internal factors (strengths weaknesses) and external (opportunities and threats) for strategic planning in the swot analysis, where the measurement weight of the instrument is multiplied by the rating level of the tool. to get a weighted score, the value of the instrument weight is multiplied by the rating level (2). make a pairwise comparison of each internal and external subfactor, (3). using the ahp method in determining the level of priority factors of each internal and external subfactor (tows). 4. result and discussion 4.1. swot analysis table 1 shows the clustering of swot analysis on the object of study, which concluded that in terms of strength of pt. cepa several strength factors include resource strength, organizational capacity, and supporting administrative capabilities. pt cepa’s weakness map includes weaknesses in financial organization, operational weaknesses in the machine’s timeframe. opportunity map of pt. cepa consists of opportunities for cooperation contracts and organizational commitment as well as market potential. at the same time, the threat factor is in the form of regulatory threats and economic, strategic policy threats. in the swot assessment analysis, as shown in table 2, which explains the relationship between the strength-opportunity (so) factor, weakness-opportunity (wo), strength-threat (st), weakness-threat (wt). furthermore, based on the internal factor evaluation (ife) matrix in table 3, it explains that the total weighted score obtained by consolidated electric power asia (cepa. ltd.) for internal factors is 2,833 which means that the consolidated electric power asia (cepa) company has a position muscular internal strength. the strength factors that have the most significant role are quality human resources with a score of 0.558, followed by the company’s ability in the field of o&m. strength factors that have a decisive role must be utilized as well as possible by the company. from the ife matrix, it can also be seen that the most significant weakness factor for the company is the potential for machine reliability to be reduced due to a considerable outage delay with a score of 0.393 and some payments to suppliers were delayed due to the approved payment system with a score of 0.203. negative factors for the company must be avoided and enhanced by the strengths and opportunities the company has to continue to carry out this o&m business. following table 4 explains the comparison matrix scale of swot and tows analysis. while in the efe matrix results in table 3 it can be seen that the total weighted score obtained by cepa for external factors is 2,566 which means that the company consolidated electric power asia has a position of external opportunities that is quite supportive. opportunity factors that have the biggest role are making contracts with nobel part suppliers through the ltsa method: long term service agreement or opsa: operating plant service agreement with a score of 0.599 and followed by planning purchases and making agreement agreements with spare part suppliers for the year to come come at the current price of 0.345. opportunity factors that have a positive role must be utilized as well as possible by the company. from the efe matrix above, it can also be seen that the biggest threat factor for the company is the exchange rate of the rupiah against the dollar for the purchase of nobel part with a score of 0.203 and followed by the factor of delays in the completion of the mini lng plant project which affects the cost of preparing a cepa o&m lng plant with a score of 0.200. threat factors that have a negative role for the company must be faced with the strengths suriyanti, et al.: planning strategy of operation business and maintenance by ahp and swot integration for energy sustainability international journal of energy economics and policy | vol 10 • issue 4 • 2020 225 and opportunities the company has in order to continue to carry out this o&m business. in the ife and efe analysis tables (table 3), we obtained a total weight score of strength 1,928 weakness 0.905 opportunity 1,864 and threat 0.702. next calculate internal and external analysis coordinates, coordinate of internal analysis (total strength weight score−total weakness weight score) = 1,928−0.905 = 1,023. coordinate of external analysis (total score of probability weight−total score of threat weight) = 1,864−0.702 = 1,162. whereas in figure 1 shows the results of the analysis of the cartesian diagram above, pt consolidated electric power asia is included in quadrant 1, which is a very favorable situation for the company because it has the strength and opportunities that can be exploited. based on table 3 in the tows matrix of pt consolidated electric power asia, there are several strategies that are appropriate for the company, including: 1. backward integration strategy, from the tows matrix included in this strategy, are so-1, wo-1, and wo-7. 2. market development, from the tows matrix included in this strategy, are so-2, st-4, and wo-5 3. development of o&m service products, from the tows matrix included in this strategy, are st-2, st-5, st-6, so-3, so-4, wo-4, wo-5, and wo-6. 5. discussion some elements of the strategy that can be carried out by cepa. ltd. in the future, as a supporting factor for the success of business operations and supporting the continuity of electricity supply, is a contract of cooperation with the industry of spare parts suppliers, considering the engine factor as a driving force and the element of production. with a cooperation contract with a major parts supplier, the opportunity to get positive feedback and the opportunity to increase production will be even more table 1: swot analysis internal strength weakness • have quality human resources • the company’s ability in the field of operation • the ability of the company in the field of maintenance • ability to make identification of routine maintenance schedules • ability in occupational safety and health and environmental protection • ability to create a company’s budget and cash flow • company reputation • have contractual certainty until 2022 • capabilities in management information systems (xp-cmms) • ims based on iso 9001, iso 14001 & ohsas 18001 standards • the potential for engine reliability is reduced due to significant outage delays • some payments to suppliers are often delayed • enormous potential for corporate income tax (cit) payments due to delays in purchasing spare parts • dependence on original equipment manufacturer (oem) • knowledge and experience for the initial cepa o&m lng team is still limited • limitations of the ability of the tool to assess used parts that will be reconditioned • limitations of the strength of the tools to analyze the condition of supporting equipment (wire rope test, boiler certification) • the company does not have an official website yet opportunities threats • making contracts with nobel part suppliers through the ltsa method: long term service agreement or opsa: operating plant service agreement • plan purchases and make agreements with spare part suppliers for the coming year at current prices • pre-mobilization of cepa o&m lng follows the progress of the keera lng project • licensing and competency certification for cepa o&m employees for the mini lng plant must be prepared • the company’s commitment to environmental management efforts must be stated in the protection policy • hire local workers per needs and meet the requirements as a form of company whitening to the surrounding community • potential o&m contract extension occurs if the psc contract extension between eees and skk migas and ppa between es and pln is also approved • o&m market for energy in indonesia is still wide • rupiah exchange rate against the dollar for nobel part purchases • delay in completion of the mini lng plant project affects the cost of preparing the cepa o&m lng plant • the operational activities of the power plant and mini lng plant can have several impacts on the environment, such as air, water, soil pollution, noise, and produce hazardous and toxic waste. • every year the government announces the results of the proper (company • performance rating rating program) in the environmental field and is always published annually and ranks companies for the category, black, red, blue, green, and gold in ecological management • psc agreement between eees, ltd. and skk migas ends october 2022, power • plant purchase agreement (ppa) between es, ltd. and pln ends october 2022, and this will have an impact on the o&m contract breaking up between cepa, ltd. and es, ltd. • if the contract extension is successful, then the new government policy in minister of energy and mineral resources regulation no. 10 of 2017 requires ipp to follow the “delivery or pay” mechanism in addition to the “take or pay” mechanism that will affect the o&m contract • government policy in the minister of energy and mineral resources regulation no. 8 of 2017 for new contracts and extensions that change the psc cost recovery method with the gross split way, this condition will positively also affect the renewal of the gas sales agreement between ees, ltd. and es, ltd. and the o&m contract between es and cepa, ltd. • threats to private o&m companies in south sulawesi (d&c engineering, poso energi, bakara bumi energi, cogindo daya bersama, bima golden powerindo, sumber daya sewatama) swot: strength, weakness, opportunity, and threa, o&m: operation and maintenance suriyanti, et al.: planning strategy of operation business and maintenance by ahp and swot integration for energy sustainability international journal of energy economics and policy | vol 10 • issue 4 • 2020226 table 2: tows analysis strategy external so strategy wo strategy 1. immediately enter into a cooperation contract with a major parts supplier (s6, s7, s10+o1, o2) 1. maximize opportunities for cooperation with suppliers through ltsa or opsa to guarantee parts approval so that machine availability and reliability is guaranteed (w1, w4, w6+o1, o2) 2. actively participating in tenders for o&m services for new and old power plants that were upgraded as a form of o&m market penetration in indonesia (s1, s2, s3, s4, s5, s6, s7, s9, s10+o7, o8) 2. implement improvements to the payment process internally and communicate with the head office in hk (w2+o2) 3. optimizing internal human resources and combining them with a new workforce for the lng plant o&m team (s1+o3) 3. a contract with the leading parts supplier will reduce cit (w3+o1, o2) 4. provide optimal internal training as preparation for obtaining lng plant competency certification (s1, s2, s3+o4) 4. with a contract with a major parts supplier, the opportunity to get training becomes excellent for the work of specialists (w7+o1, o2) 5. create a system procedure and implement it professionally (s10+o5) 5. website creation must be made to be able to take on other o&m markets (w9+o8) 6. provide training to local workers around the company such as basic welder, scaffolder and basic mechanics (s1, s7+o6) 6. send employees for training and certification to be able to have competence in conducting assessments (w6, w8+o7, o8) 7. improve performance and ensure consistent work optimally so that it can be used as bargaining power when contract extension (s1, s2, s3, s4, s5, s6, s7, s9, s10+o7, o8) 7. look for and maximize alternatives from several reconditioning companies to reduce dependence on oems (w4+o1, o2) st strategy wt strategy 1. if the transaction is in foreign currency, then the exchange rate as the basis for payment in rupiah value, the determination of the exchange rate is adjusted to the bi exchange rate and takes the highest value, to avoid exchange rate spikes at the time of payment. (s6+t1) 1. perform regular internal assessments to ensure that major outage delays are acceptable and not endanger the condition of the machine (w1, w2, w4, w6+t3) 2. maximize internal human resources to help new workers in the preparation of the o&m lng plant team (s1, s2, s3+t2) 2. make training need analysis for cepa lng o&m and provide training internally (w5+t2) 3. implement standard environmental management and monitoring procedures based on international standards iso 14001: 2015 (s10+t3, t4) 4. looking for new contract o&m opportunities in other fields in preparation if in 2022 the deal is not renewed (s1, s2, s3, s4, s5, s6, s7, s9, s10+t5) 5. improve performance and ensure consistent work optimally so that it can be used as a positive record in contract renewal (s1, s2, s3, s4, s5, s6, s7, s9, s10+t6, t7, t8) 6. maximizing contracts that are still 5 years away to demonstrate consistently efficient o&m capabilities (s1, s2, s3, s4, s5, s6, s7, s8, s9, s10+t8) o&m: operation and maintenance figure 1: diagram analysis of strength, weakness, opportunity, and threat excellent. one of these (cooperation contracts) can be pursued, one of which is the re-construction of payment processes to structured and timely suppliers to increase the value of trust between the internal company and the supplier as an external party. forms of suriyanti, et al.: planning strategy of operation business and maintenance by ahp and swot integration for energy sustainability international journal of energy economics and policy | vol 10 • issue 4 • 2020 227 table 3: internal factor evaluation and external factor evaluation no. rating of external factor priorities weight rating weight score opportunities 1. enter into a contract with a nobel part supplier through the ltsa method: long term service agreement or opsa: operating plant service agreemen 0.150 4 0.599 2. plan purchases and make agreements with spare part suppliers for the coming year at current prices 0.086 4 0.345 3. pre mobilization of the cepa o&m lng follows the progress of the keera lng project 0.068 4 0.272 4. licensing and competency certification for cepa o&m employees for mini lng plant must be prepared. licensing and certification for cepa o&m employee competencies for mini lng plant must be prepared 0.061 4 0.243 5. the company’s commitment to environmental management efforts must be stated in a protection policy 0.045 3 0.136 6. hire local workers according to the needs and meet the requirements as a form of company whitening to the surrounding community 0.044 3 0.131 7. potential o&m contract extension occurs if the psc contract extension between pt eees and skk migas & ppa between pt es & pln is also approved 0.023 3 0.070 8. the o&m market for energy in indonesia is still broad 0.023 3 0.068 sub total 1.864 threat 1. rupiah exchange rate against the dollar for nobel part purchases 0.101 2 0.203 2. the delay in completing the mini lng plant project affects the cost of preparing the cepa o&m lng plant 0.100 2 0.200 3. operational activities of the power plant and mini lng plant can have several impacts on the environment, such as air, water, soil pollution, noise, and produce hazardous and toxic waste 0.082 1 0.082 4. every year the government announces the results of the proper (company performance rating rating program) in the environmental field and is always published annually and ranks companies for the category, black, red, blue, green, and gold in ecological management 0.078 1 0.078 5. psc agreement between pt eees and skk migas ends october 2022, power plant purchase agreement (ppa) between es and pln ends october 2022, and this will have an impact on the o&m contract breaking up between cepa and es 0.052 1 0.052 6. if the contract extension is successful, then the new government policy in minister of energy and mineral resources regulation no. 10 of 2017 requires ipp to follow the “delivery or pay” mechanism in addition to the “take or pay” mechanism that will affect the o&m contract 0.031 1 0.031 7. government policy in the minister of energy and mineral resources regulation no. 8 of 2017 for new contracts and extensions that change the psc cost recovery method with the gross split method, and this condition will positively also affect the renewal of the gas sales agreement between ees and pt es and the o&m contract between es and cepa 0.030 1 0.030 8. threats against private o&m companies in south sulawesi (d&c engineering, poso energi, bakara bumi energi, cogindo daya bersama, bima golden powerindo, sumber daya sewatama) 0.025 1 0.025 sub total 0.702 total 1.00 2.566 o&m: operation and maintenance table 4: pairwise comparison matrix scale intensity of interest definition explanation 1 equally important element compared to other elements (equal importance) both elements contribute equally to these properties. 3 one element is slightly more important than the other elements (moderate more importance) experience states a little in favor of one element 5 one element is clearly more important than other elements (essential, strong more importance) experience shows strongly in favor of one element 7 one element is clearly more important than another element (demonstrated importance) experience shows strongly liked and dominant seen in practice 9 one element is absolutely more important than another (absolutely more importance) experience shows that one element is clearly more important 2,4,6,8 when in doubt between the two adjacent space values (gray area) this value is given when compromise is needed cooperation can be done both involving the private sector and the government, including in terms of csr optimizers. to maintain the continuity of the electricity supply business, as an effort to penetrate the market, keeping in mind the increasing consumer demand is to participate in several project auctions based on o&m tender and the creation of a website as a digital-based promotion tool. the drivers of production, which include aspects of human resources as intangible assets, play an essential role; therefore, the optimization of internal human resources is also a key element as a strategic policy unit of the company. of course, it must also be supported by the application of fair and professional reward and punishment rules. supports in terms of resource development can be achieved through training, for example, basic welder scaffolder and basic mechanical. suriyanti, et al.: planning strategy of operation business and maintenance by ahp and swot integration for energy sustainability international journal of energy economics and policy | vol 10 • issue 4 • 2020228 apart from what has been previously stated, given the uncertain economic conditions, the company’s strategy to deliver business management to be more optimal with minimal risk is transactions in the form of foreign currencies to avoid fluctuations in the exchange rate at the time of purchase or payment. 6. conclusion based on the results of the strategy formulation that has been carried out with strategic management tools namely the swot/tows matrix, there are three alternative strategies per consolidated electric power asia; there are three, namely: (a) backward integration, this strategy tries to increase control over suppliers company by making a particular contract on the supplier of main parts or original equipment manufacturer (oem). (b) market development. this strategy introduces existing o&m services to new geographical areas. (c) product or service development. this strategy is a strategy where companies increase sales by improving existing o&m products or services or developing o&m services for sectors other than the power generation sector. based on the results of this study, the suggestions that can be given to cepa. ltd. o&m so that the findings in this study can be input for management in the o&m service development strategy and strategy formulation needs to be done regularly to get a picture of a dynamic business environment, for example, once a year and discussed at the management review meeting. references barusman, m.y.s., redaputri, a.p. (2018), decision making model of electric power fulfillment in lampung province using soft system methodology. international journal of energy economics and policy, 8(1), 128-136. costanza, r., daly, h.e. (1992), natural capital and sustainable development. conservation biology, 6, 37-46. elkington, j. (1998), partnerships from cannibals with forks: the triple bottom line of 21st century business. environmental quality management, 6, 37-51. faber, n., de koster, m., smidts, a. (2013), organizing warehouse management. international journal of operations and production management, 33(9), 1230-1256. felix, e. (2018), theory of sustainability. available from: http://www. sustainability-justice-climate.eu/en/nachhaltigkeit.html. [last accessed on 2019 mar 01]. francois, e.j. (2018), financial sustainability for nonprofit organizations. in: financial sustainability for nonprofit organizations. united states: spinger publishing company. p1-384. garg, a., deshmukh, s. (2006), maintenance management: literature review and directions. journal of quality in maintenance engineering, 12(3), 205-238. geerlings, h., vellinga, t. (2017), sustainability. in: ports and networks: strategies, operations and perspectives. london: routledge. p1-406. gimenez, c., sierra, v., rodon, j. (2012), sustainable operations: their impact on the triple bottom line. international journal of production economics, 140(1), 149-159. goodland, r. (2003), the concept of environmental sustainability. annual review of ecology and systematics, 26, 1-24. görener, a., toker, k., uluçay, k. (2012), application of combined swot and ahp: a case study for a manufacturing firm. procedia social and behavioral sciences, 58, 1525-1534. gottfried, o., de clercq, d., blair, e., weng, x., wang, c. (2018), swot-ahp-tows analysis of private investment behavior in the chinese biogas sector. journal of cleaner production, 184, 632-647. gregory, l.k. (2012), introduction to homeland security. new york: routledge. p1-428. huo, j., hong, z. (2013), operation management. in: service science in china. united states: springer. p1-166. jenkins, w. (2009), sustainability theory. in: berkshire encyclopedia of sustainability. united states: berkshire publishing group. p1-493. karakaş, e., yildiran, o.v. (2019), evaluation of renewable energy alternatives for turkey via modified fuzzy ahp. international journal of energy economics and policy, 9(2), 31-39. khazaii, j. (2016), analytical hierarchy process. in: advanced decision making for hvac engineers. switzerland: springer, cham. p73-85. kurttila, m., pesonen, m., kangas, j., kajanus, m. (2002), utilizing the analytic hierarchy process (ahp) in swot analysis-a hybrid method and its application to a forest-certification case. forest policy and economics, 1(1), 41-52. lal, r. (2016), environmental sustainability. in: lal, r., kraybill, d., hansen, d., singh, b., mosogoya, t., eik, l., editors. climate change and multi-dimensional sustainability in african agriculture. switzerland: springer, cham. p3-11. laurence, d. (2011), establishing a sustainable mining operation: an overview. journal of cleaner production, 19(2-3), 278-284. leigh, d. (2010), swot analysis. in: watkins, r., leigh, d., editors. handbook of improving performance in the workplace: selecting and implementing performance interventions. united states: wiley online library. p2. marcelina, s.c. (2016), tanggung jawab perusahaan listrik negara terhadap konsumen. lex et societatis, 4(5), 97-105. mu, e., pereyra-rojas, m. (2017), practical decision making. in: springer briefs in operations research. berlin, germany: springer, cham. p43-58. murdifin, i., pelu, m.a.f., putra, a.h.p., arumbarkah, a.m., rahmah, a., muslim, u., rahmah, a. (2019), environmental disclosure as corporate social responsibility: evidence from the biggest nickel mining in indonesia. international journal of energy economics and policy, 9(1), 115-122. mutloane, o.e. (2009), maintenance management for effective operations management at matimba power station. north-west: doctoral dissertation, north-west university. p1-80. oreski, d. (2012), strategy development by using swot-ahp. tem journal, 1(4), 283-291. piercy, n., giles, w. (1989), making swot analysis work. marketing intelligence and planning, 7(5/6), 5-7. ramlawati, r., putra, a.h.p. (2018), total quality management as the key of the company to gain the competitiveness, performance achievement and consumer satisfaction. international review of management and marketing, 8(5), 60-69. saaty, t.l. (2011), what is the analytic hierarchy process? in: mathematical models for decision support. vol. 48. heidelberg: springer. seuring, s., müller, m. (2008), from a literature review to a conceptual framework for sustainable supply chain management. journal of cleaner production, 16(15), 1699-1710. šlaus, i., jacobs, g. (2011), human capital and sustainability. sustainability, 3(1), 97-154. teece, d.j., pisano, g., shuen, a. (1997), dynamic capabilities and strategic management. strategic management journal, 18, 509-533. van bardeleben, m. (2011), implementing sustainability. european coatings journal, 11, 38-40. wallis, s.e., valentinov, v. (2017), what is sustainable theory? a luhmannian perspective on the science of conceptual systems. found of science, 22, 733-747. . international journal of energy economics and policy | vol 10 • issue 3 • 2020296 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(3), 296-302. information and communication technology and electricity consumption in transitional economies bester chimbo* department of information systems, school of computing, university of south africa, south africa. *email: chimbb@unisa.ac.za received: 17 may 2019 accepted: 15 november 2019 doi: https://doi.org/10.32479/ijeep.8143 abstract the study investigated the impact of information and communication technology (ict) on electricity consumption in transitional economies using panel data analysis methods (dynamic generalized methods of moments [gmm], pooled ordinary least squares, fixed effects, random effects) with annual secondary data ranging from 1995 to 2014. majority of prior studies on the subject matter had not focused on the impact of ict on electricity consumption but on energy consumption, which is a broader area. they also did not focus exclusively on transitional economies and they ignored both the dynamic characteristics of electricity consumption data and endogeneity issues. the study revealed that electricity consumption is positively and significantly influenced by its own lag, in line with theoretical literature (nayan et al., 2013). however, the impact of ict on electricity consumption was found to be mixed. for example, the influence of ict on electricity consumption was found to be negative and non-significant under the dynamic gmm and pooled ols. fixed and random effects observed that ict had a significant positive impact on electricity consumption in emerging markets. it is against this backdrop that the current study urges transitional economies to develop and implement policies that ensures that ict gadgets being used reduces the quantity of electricity consumption. in other words, transitional economies should focus on developing or importing energy efficient ict gadgets in order to meet the required energy saving threshold levels. future studies should investigate channels through which ict influences electricity consumption, in line with shahbaz et al. (2014) whose study noted that the relationship between ict and electricity consumption is non-linear. keywords: information and communication technology, electricity consumption, panel data, transitional economies jel classifications: l17, z32 1. introduction several studies have attempted to investigate the impact of information and communication technology (ict) on electricity consumption but they have so far produced divergent, mixed and unclear results. four set of views emerged from the study on ict-led electricity consumption hypothesis and these are: (1) ict-led positive impact on electricity consumption, (2) ict-led negative influence on electricity consumption, (3) the non-linear argument, (4) the neutrality hypothesis. the ict-led positive impact on electricity consumption hypothesis argued that increased investment in ict infrastructure leads to more electricity consumption in the economy, a view which was supported by zhang and liu (2015), sadorsky (2012), salahuddin and alam (2016), tunali (2016), afzal and gow (2016), collard et al. (2005), pothitou et al. (2017) and choo et al. (2007), among others. the ict-led negative impact on electricity consumption view says that ict has got a deleterious effect on electricity consumption. the view was supported by lee and brahmasrene (2014), lu (2018), han et al. (2016), gelenbe and caseau (2015), wang and han (2016), horner et al. (2016), schulte et al. (2016), pano (2017), choo et al. (2007) and bernstein and madlener (2010). the non-linear argument says that the impact of ict on electricity consumption is non-linear in the sense that ict influences electricity consumption through some channels and not in a direct manner. a study done by shahbaz et al. (2014) produced findings which supports the non-linear argument. the neutrality this journal is licensed under a creative commons attribution 4.0 international license chimbo: information and communication technology and electricity consumption in transitional economies international journal of energy economics and policy | vol 10 • issue 3 • 2020 297 hypothesis which was supported by inani and tripathi (2017) is of the view that there is no relationship at all between ict and electricity consumption. although the first two views are the most supported in the literature, the relationship between ict and electricity consumption is still not clear and inclusive. it is against this backdrop that the current study performed further empirical tests to find out the impact of ict on electricity consumption in transitional economies. majority of the empirical studies on the impact of ict on electricity consumption shied away from focusing on transitional economies except two of them (sadorsky, 2012; afzal and gow, 2016). the similarities between these prior studies and the current study is that they all used dynamic generalized methods of moments (gmm) which takes into account the dynamic nature of electricity consumption data and effectively deal with the endogeneity problem. the current study deviates from these two similar prior studies in the following ways: (1) the current study used other panel data analysis methods (fixed effects, random effects, pooled ols) apart from the dynamic gmm for comparative analysis purposes, (2) the current study used more up to date dataset, (3) the current study used a different proxy of ict (individuals using internet as a ratio of the population), which is a better measure of ict investment and development in the country. the rest of the paper is organised as follows: section 2 is literature review, section 3 explains the other factors that influence electricity consumption whilst section 3 describes the methodology used in this study. pre-estimation diagnostics is section 4, main data analysis, interpretation and discussion of results is done in section 5. section 6 is the conclusion. 2. literature review the ict led electricity consumption view according to zhang and liu (2015) argues that ict increases the amount of electricity consumption because more electrical gadgets are used which consumes a lot of energy. the optimistic view says that the use of ict gadgets saves the overall energy consumption but not necessarily the quantity of electricity used (lee and brahmasrene, 2014). in line with houghton’s (2009) proposition, the relationship between ict and electricity (energy consumption) consumption is quite unclear as it could be positive, negative or non-existent at all. on the empirical front, quite a number studies investigated the relationship between ict and electricity or energy consumption (table 1). table 1 shows that the relationship between ict and electricity consumption can be categorized into four: (1) ict led positive impact on electricity consumption, (2) ict led negative effect on electricity consumption, (3) there is no relationship between ict and electricity consumption and (4) the impact of ict on electricity consumption is non-linear. clearly, both theoretical and empirical literature shows that the influence of ict on electricity consumption is mixed and debate on the relationship between the two variables is inconclusive and still far from being over. other factors that influence electricity consumption are presented in table 2. individuals using internet (% of population) is the proxy of ict that was used in this study, consistent with tsaurai and chimbo (2019). 3. methodology description 3.1. data the study used annual panel data ranging from 1995 to 2014 for transitional economies (argentina, brazil, china, colombia, czech republic, greece, hong kong, indonesia, india, mexico, malaysia, peru, philippines, poland, portugal, republic of korea, russia, thailand, turkey, singapore, south africa). the sample of countries is in line with international monetary fund (2015) and data availability considerations. the data was obtained from world development indicators, african development indicators, international financial statistics and international monetary fund databases. 3.2. empirical and econometric model specification in line with both theoretical and empirical literature, the general model specification of the electricity consumption function is shown in equation 1. electr = f(ict, gdppc, urban, access, resource, fdi, fin, open, hcd) (1) where electr, ict, gdppc, urban, access, resource, fdi, fin, open and hcd stands for electricity consumption, ict, gross domestic product per capita, urban population, access to electricity, resource endowment, foreign direct investment, financial development, trade openness and human capital development. equation 1 is transformed into equation 2 when presented as an econometric estimation model. electri,t=β0+β1icti,t+β2gdppci,t+β3urbani,t +β4ccess+β5resourcei,t+β6fdii,t+β7fini, +β8openi,t+β9hcdi,t+µ+ε (2) ε is the error term. i and t stands respectively stands for country and time. µi is the time invariant and unobserved country specific effect, β0 represents the intercept term, β1 up to β9 are the co-efficients of the respective variables used. fixed effects, pooled ols and the random effects were the three panel data analysis methods which were used to estimate equation 2. following nayan et al. (2013) whose study argued that electricity consumption is affected by its own lag, the current study took into account the dynamic characteristics of the electricity consumption data (equation 3). electri,t=β0+β1electri,t−1+β2icti,t+β3gdppci,t +β4urbani,t+β5access+β6resourcei,t +β7fdii,t+β8fini,t+β9openi,t+β10hcdi,t+µ+ε (3) chimbo: information and communication technology and electricity consumption in transitional economies international journal of energy economics and policy | vol 10 • issue 3 • 2020298 where electrit−1is the lag of electricity consumption. equation 3 was estimated using arellano and bond (1991)’s dynamic panel gmm approach. 4. pre-estimation diagnostics this section includes correlation analysis and descriptive statistics. table 3 shows that variables which were individually positively and significantly correlated with electricity consumption are ict, economic growth (gdppc), urban population (urban), foreign direct investment (fdi), financial development (fin), trade openness (open) and human capital development (hcd). access to electricity was found to have been negatively but non-significantly related with electricity consumption whilst a significant negative relationship between human capital development and electricity consumption was detected. the results are supports by the literature. the problem of multi-collinearity table 1: a summary of empirical studies on ict-electricity consumption nexus author focal unit of analysis methodology research findings sadorsky (2012) emerging economies dynamic panel data analysis when ict is measured using mobile phones, number of computers and internet connections, ict was found to have had a significant positive influence on electricity consumption salahuddin and alam (2016) oecd countries panel data analysis a significant positive relationship running from ict towards electricity consumption was detected both in the long and short run lu (2018) asian countries panel data analysis ict was found to have reduced (significant negative influence) carbon dioxide emissions in asian countries han et al. (2016) china ardl and ecm ict had a negative impact on energy consumption in the short run. in the long run, the influence of ict on energy consumption was found to be u-shaped tunali (2016) european union countries ardl ict led to an increase in electricity consumption in european union countries in the long run yan et al. (2018) 50 economies panel data analysis ict had a significant positive effect on energy productivity gelenbe and caseau (2015) world-wide panel data analysis ict had a deleterious impact on energy consumption and carbon emissions afzal and gow (2016) emerging economies dynamic panel data analysis and system gmm ict as measured by mobile phones, internet connections and import percentage of ict goods of total imports was found to have had a significant positive effect on electricity consumption in emerging economies studied wang and han (2016) china panel ecm ict reduced energy intensity in the long run in china shahbaz et al. (2014) united arab emirates vecm the non-linear relationship between ict and electricity consumption was found to be an inverted u-shape inani and tripathi (2017) india vecm and ardl the relationship between ict and electricity consumption was found to be non-existent in india both in the short and long run solarin et al. (2019) malaysia toda-yamamoto granger causality approach a feedback effect between ict and electricity consumption was observed collard et al. (2005) france vecm the use of computers and software led to the increase in electricity consumption in france pothitou et al. (2017) european union descriptive statistics ict led to an increase in electricity consumption horner et al. (2016) world-wide literature review ict was found to have had a negative impact on energy consumption schulte et al. (2016) oecd countries difference-gmm ict was found to have a reduction effect on energy demand in the oecd countries pano (2017) albania descriptive statistics the study found out that ict reduced energy usage in albania choo et al. (2007) south korea descriptive statistics ict investment in the manufacturing sector increased electricity consumption whilst ict investment in the services sector was found to have had a deleterious impact on electricity consumption bernstein and madlener (2010) european union countries (uk, sweden, slovenia, portugal, italy, germany, finland, denmark) panel econometric approach ict was found to have had an electricity consumption reduction effect in the sectors studied source: author compilation. ict: information and communication technology, ecm: error correction model, ardl: autoregressive distributed lag, vecm: vector error correction model, gmm: generalized methods of moments chimbo: information and communication technology and electricity consumption in transitional economies international journal of energy economics and policy | vol 10 • issue 3 • 2020 299 table 2: variables, a priori expectation and theory intuition variable proxy used theory intuition expected sign lag of electricity consumption electric power consumption (kwh per capita) consistent with nayan et al. (2013), the electricity consumption level follows a similar pattern of the previous electricity consumption period. in other words, the electricity consumption interdepends on each other across periods + economic growth (growth) gdp per capita aye and edoja (2017) noted that higher levels of economic growth increases the number of economic activities which uses a lot of electricity + urbanization (urban) urban population (% of total) the expansion of urban areas is associated with increased activities such as construction and the maintenance of roads and other related infrastructure, all of which leads to more electricity consumption (zhao and zhang, 2018; sadorsky, 2014). on the contrary, ye et al. (2013) revealed that urbanization is associated with high levels of technological advances which could lead to more energy use efficiency and lower electricity consumption ± access to electricity (access) access to electricity (% of population) the author is of the view that more access to electricity reduces the cost per unit of electricity and consequently increases the overall quantity of electricity usage in the economy ± resource endowment (resource) total natural resources rents (% of gdp) consistent with kwakwa et al. (2018), heavy machinery which requires the use of more electricity energy is employed in the process of extracting natural resources. however, a country uses other forms of energy apart from electricity if it is endowed with diverse type of natural resources ± foreign direct investment net fdi inflows (% of gdp) fdi increases the number and level of manufacturing activities in the economy which require the use of more electricity (blanco et al., 2013). however, cheng and yang (2016) observed that foreign investors bring the host country some advanced and smart technology which is energy use efficient ± financial development stock market capitalisation (% of gdp) sadorsky (2010) argued that financial sector development enables consumers and firms to borrow money in order to purchase more electricity consuming items such refrigerators, houses washing machines, among others. on the other hand, the author is of the view that higher levels of financial development allows domestic firms and individuals to borrow money and invest in state of the art and electricity saving gadgets ± trade openness (open) total trade (% of gdp) consistent with tsaurai (2019a), trade openness multiplies the number of energy use linked manufacturing activities in the economy. grossman and krueger (1991) however noted that trade openness allows companies to import new technology that is energy use efficient ± human capital development human capital development index a study by inglesi-lotz and morales (2017) noted that higher levels of education had a significant positive impact on energy consumption in developing countries + source: author compilation table 3: correlation analysis electr ict gdppc urban access resource fdi fin open hcd electr 1.00 ict 0.61*** 1.00 gdppc 0.78*** 0.68*** 1.00 urban 0.49*** 0.43*** 0.61*** 1.00 access −0.05 0.03 0.12** 0.36*** 1.00 resource −0.17*** −0.07 −0.36*** −0.06 0.16*** 1.00 fdi 0.39*** 0.35*** 0.63*** 0.50*** 0.23*** −0.19*** 1.00 fin 0.33*** 0.32*** 0.50*** 0.36*** 0.08* −0.10** 0.79*** 1.00 open 0.54*** 0.40*** 0.70*** 0.46*** 0.18*** −0.19*** 0.81*** 0.72*** 1.00 hcd 0.68*** 0.46*** 0.67*** 0.61*** 0.13*** −0.33*** 0.36*** 0.23*** 0.44*** 1.00 source: author’s compilation from e-views. ***, **and *denote 1%, 5% and 10% levels of significance, respectively does not exist, consistent with tsaurai (2019b. p. 171) because the maximum absolute correlation value is 81% (between trade openness and fdi). this is understandable because both fdi and trade openness are measure of how open an economy is to the outside world. the probabilities of the jarque-bera criterion equal to zero across all the variables studied, an indication that the data is not normally distributed (odhiambo, 2008; tsaurai and ndou, 2019). standard deviation values (>1000) show that electricity consumption and economic growth (gdppc) data has abnormal values (table 4). chimbo: information and communication technology and electricity consumption in transitional economies international journal of energy economics and policy | vol 10 • issue 3 • 2020300 abel and le roux (2016) transformed all the data sets into natural logarithms in order to effectively dealt with the issues of abnormal values and data that is not following a normal distribution. the current study used the same approach. 5. results and discussion panel unit root tests (results presented in table 5) show that the variables are integrated of order 1 (odhiambo, 2008). table 6 shows that the null hypothesis which says that there is no long run relationship between and among the variables studied is rejected, thus paving way for main data analysis whose results are presented in table 7. the lag of electricity consumption had a significant positive impact on electricity consumption under the dynamic gmm approach, consistent with nayan et al. (2013) whose study noted that electricity consumption level follows a similar pattern of the previous electricity consumption period. under the dynamic gmm and pooled ols, a non-significant negative relationship running from ict towards electricity consumption was observed, in line with the optimistic view propagated by lee and brahmasrene (2014) which argues that the use of ict gadgets reduces energy consumption. the finding also resonates with other related prior empirical studies (han et al., 2016; horner et al., 2016; gelenbe and caseau, 2015). on the other hand, ict was found to have had a significant positive effect on electricity consumption under both the fixed and random effects methods, a finding which supports zhang and liu’s (2015) view that ict leads to increased electricity consumption because it triggers the use of more electrical gadgets. under the dynamic gmm approach, economic growth had a non-significant positive influence on electricity consumption whilst pooled ols, fixed and random effects shows a significant positive relationship running from economic growth towards electricity consumption. the results resonate with aye and edoja (2017) whose study revealed that increased levels of economic growth boost the magnitude of economic activities which rely more on electricity consumption. whilst urbanization had a significant negative impact on electrical consumption under the dynamic gmm, pooled ols shows a non-significant negative relationship running from urbanization towards electricity consumption. the results support ye et al. (2013) whose study argued that urbanization triggers the use of more technologically advanced equipment and machinery that is more energy efficient. in line with sadorsky (2014) whose study argued that urbanization expands economic activities that uses a lot of electricity such as construction and infrastructure maintenance, the current study observed that urbanization had a significant positive effect on electricity consumption under both fixed and random effects. table 4: descriptive statistics descriptive statistics electr ict gdppc urban access resource fdi fin open hcd mean 3274.7 26.3 9796.6 66.2 89.4 3.64 4.12 88.4 94.4 0.77 median 2702.6 18.1 6239.9 70.5 97.5 2.17 2.56 39.5 58.0 0.77 maximum 10497 90.4 56284 100.0 100.0 21.7 39.9 1254 455.3 0.94 minimum 263.6 0.00 381.5 26.6 2.98 0.0003 0.03 3.27 15.64 0.48 std. dev. 2361 25.07 9940.4 19.01 19.0 4.29 5.85 160.8 95.9 0.09 skewness 0.71 0.72 1.82 −0.13 −2.68 1.62 3.56 4.93 2.28 −0.41 kurtosis 2.77 2.28 6.87 2.48 10.3 5.51 17.0 30.6 7.36 2.78 jarque-bera 36.6 45.3 493.1 5.8 1447 294.8 4309.3 14998.7 695.6 12.5 probability 0.00 0.00 0.00 0.05 0.00 0.00 0.00 0.00 0.00 0.00 observations 420 420 420 420 420 420 420 420 420 420 source: author’s compilation from e-views table 5: panel stationarity tests –individual intercept variables level first difference llc ips adf pp llc ips adf pp lelectr −1.90** 2.19 38.82 103.31 −9.01*** −8.26*** 150.41*** 270.50*** lict −18.48*** −16.58*** 412.15*** 1622.71*** −12.43*** −6.02*** 130.62*** 122.80*** lgdppc 1.13 4.80 10.27 16.71 −6.96*** −5.32*** 98.90*** 145.50*** lurban −4.43*** 1.43 40.42 74.18*** −3.14*** −5.95*** 103.91*** 473.57*** laccess −4.29*** −1.00 38.77* 89.13*** −7.31*** −12.64*** 193.47*** 810.23*** lresource −2.35*** −0.33 36.92 44.10 −12.67*** −10.63*** 186.38*** 290.29*** lfdi −6.02*** −5.65*** 105.42*** 152.99*** −11.65*** −13.47*** 236.69*** 1565.71*** lfin −4.74*** −3.48*** 87.67*** 111.69*** −15.87*** −15.40*** 273.93*** 751.67*** lopen −2.53*** 0.30 36.69 39.49 −15.87*** −15.40*** 273.93*** 751.67*** lhcd −10.40*** −7.25*** 128.39*** 180.02*** −17.77*** −15.71*** 276.20*** 2596.02*** source: author’s compilation from e-views. llc, ips, adf and pp stands for levin et al. (2002); im et al. (2003); adf fisher chi-square and pp fisher chi-square tests respectively. *, **and *** denote 1%, 5% and 10% levels of significance, respectively table 6: kao residual co-integration test individual intercept statistical description t-statistic probability augmented dickey-fuller −2.127601 0.0167 source: author’s compilation from e-views chimbo: information and communication technology and electricity consumption in transitional economies international journal of energy economics and policy | vol 10 • issue 3 • 2020 301 access to electricity was found to have had a significant negative impact on electricity consumption under the dynamic gmm and pooled ols. on the other hand, a significant positive impact of access to electricity on electricity consumption was detected under the fixed and random effects methods. resource endowment was found to have had a non-significant impact on electricity consumption under the dynamic gmm, fixed and random effects whilst pooled ols shows a significant positive relationship running from resource endowment towards electricity consumption. the results generally resonate with kwakwa et al. (2018) whose study argued that heavy machinery required to extract natural resources uses a lot of electricity energy. the dynamic gmm shows that fdi had a non-significant positive effect on electricity consumption, in line with theoretical literature (blanco et al., 2013). pooled ols shows a significant negative relationship running from fdi towards electricity consumption whilst fixed and random effects show that the impact of fdi on electricity consumption was negative but non-significant. the results imply that fdi reduced the levels of electricity consumption in line with cheng and yang’s (2016) observation that foreign investors bring into the host country some advanced and smart technology which is energy efficient. a significant positive impact of financial development on electricity consumption was observed under the dynamic gmm yet pooled ols shows that financial development had a non-significant positive effect on electricity consumption, findings which resonate with sadorsky (2010) whose study noted that consumers and are able to purchase high electricity usage equipment through borrowing from financial markets if they are developed. on the contrary, fixed and random effects show that the impact of financial development on electricity consumption was negative and significant, in line with an argument that says developed financial markets enable firms and consumers to borrow money in order to purchase advanced technology which overall contributes to a reduction in energy consumption levels. under the dynamic gmm, trade openness had a non-significant negative effect on electricity consumption, in support of grossman and krueger’s (1991) argument. pooled ols show a significant positive relationship running from trade openness towards electricity consumption yet trade openness was found to have had a nonsignificant positive impact on electricity consumption under the fixed and random effects, results which resonate with tsaurai (2019a) whose study noted that the number of energy usage linked manufacturing activities multiplies if trade openness of a country is high. last but not least, human capital development was found to have had a significant positive effect on electricity consumption across all the panel data analysis methods used, in support of inglesi-lotz and morales’s (2017) findings in the case of developing countries. 6. conclusion the study investigated the impact of ict on electricity consumption in transitional economies using panel data analysis methods (dynamic gmm, pooled ols, fixed effects, random effects) with annual secondary data ranging from 1995 to 2014. majority of prior studies on the subject matter had not focused on the impact of ict on electricity consumption but on energy consumption, which is a broader area. they also did not focus exclusively on transitional economies and they ignored both the dynamic characteristics of electricity consumption data and endogeneity issues. the study revealed that electricity consumption is positively and significantly influenced by its own lag, in line with theoretical literature (nayan et al., 2013). however, the impact of ict on electricity consumption was found to be mixed. for example, the influence of ict on electricity consumption was found to be negative and non-significant under the dynamic gmm and pooled ols. fixed and random effects observed that ict had a significant positive impact on electricity consumption in emerging markets. it is against this backdrop that the current study urges transitional economies to develop and implement policies that ensures that ict gadgets being used reduces the quantity of electricity consumption. in other words, transitional economies should focus on developing or importing energy efficient ict gadgets in order to meet the required energy saving threshold levels. future studies should investigate channels through which ict influences electricity consumption, in line with shahbaz et al. (2014) whose study noted that the relationship between ict and electricity consumption is non-linear. table 7: panel data analysis results variables dynamic gmm pooled ols fixed effects random effects electri, t−1 0.9822*** ict −0.0018 −0.0265 0.0313*** 0.0314*** gdppc 0.0079 0.6771*** 0.1556*** 0.1615*** urban −0.0299*** −0.1150 1.3181*** 1.2902*** access −0.0158*** −0.1357** 0.2982*** 0.2894*** resource 0.0018 0.0586*** 0.0052 0.0002 fdi 0.0007 −0.0680** −0.0068 −0.0073 fin 0.0048* 0.0489 −0.0167* −0.0167* open −0.0007 0.1929*** 0.0231 0.0374 hcd 0.0784*** 1.3530*** 0.2555*** 0.2583*** number of countries 21 21 21 21 number of observations 420 420 420 420 adjusted r-squared 0.8123 0.7420 0.6514 0.8684 f-statistic j-static=409.00 134.92 1829.43 308.13 prob (f-statistic) prob (j-statistic)=0.00 0.00 0.00 0.00 source: author’s compilation from e-views. ***, **and * denote 1%, 5% and 10% levels of significance, respectively chimbo: information and communication technology and electricity consumption in transitional economies international journal of energy economics and policy | vol 10 • issue 3 • 2020302 references abel, s., le roux, p. (2016), determinants of banking sector profitability in zimbabwe. international journal of economics and financial issues, 6(3), 845-854. afzal, m.n.i., gow, j. (2016), electricity consumption and information and communication technology in the next eleven emerging economies. international journal of energy economics and policy, 6(3), 381-388. arellano, m., bond, s. (1991), some tests of specification for panel data: monte carlo evidence and an application to employment equations. the review of economic studies, 58(2), 277-297. aye, g.c., edoja, p.e. (2017), effect of economic growth on co2 emission in developing countries: evidence from a dynamic panel threshold model. cogent economics and finance, 5(1), 1-22. bernstein, r., madlener, r. (2010), impact of disaggregated ict capital on electricity intensity in european manufacturing. applied economics letters, 17(17), 1691-1695. blanco, l., gonzalez, f., ruiz, i. (2013), the impact of fdi on co2 emissions in latin america. oxford development studies, 41(1), 104-121. cheng, s., yang, z. (2016), the effects of fdi on carbon emissions in china: based on spatial econometric model. revista de la facultad de ingenieria u.c.v, 31(6), 137-149. choo, y., lee, j., kim, t.y. (2007), the impact of ict investment and energy price on industrial electricity demand: dynamic growth model approach. energy policy, 35(9), 4730-4738. collard, f., feve, p., portier, f. (2005), electricity consumption and ict in the french service sector. energy economics, 27, 541-550. gelenbe, e., caseau, y. (2015), the impact of information technology on energy consumption and carbon emissions. ubiquity, 2015, 1-15. grossman, g.m., krueger, a.b. (1991), environmental impacts of a north american free trade agreement. national bureau of economic research, working paper number. han, b., wang, d., han, w.d. (2016), effect of information and communication technology on energy consumption in china. natural hazards, 84(1), 297-315. horner, n.c., shehabi, a., azevedo, i.l. (2016), known unknowns: indirect energy effects of information and communication technology. environmental research letters, 11, 1-120. houghton, j. (2009), ict and the environment in developing countries: an overview of opportunities and developments. communications and strategies, 76, 39. im, k.s., pesaran, m.h., shin, y. (2003), testing unit roots in heterogeneous panels. journal of econometrics, 115(1), 53-74. inani, s.k., tripathi, m. (2017), the nexus of ict, electricity consumption and economic growth in india: an ardl approach. international journal of indian culture and business management, 14(4), 457-479. inglesi-lotz, r., morales, l.d.c. (2017), the effect of education on a country’s energy consumption: evidence from developed and developing countries. university of pretoria, department of economics working paper. international monetary fund. (2015), world economic outlook: adjusting to lower commodity prices. washington: international monetary fund. kwakwa, p.a., alhassan, h., adu, g. (2018), effect of natural resources extraction on energy consumption and carbon dioxide emission in ghana, ‘munich personal repec archive (mpra) paper. lee, j.w., brahmasrene, t. (2014), ict, co2 emissions and economic growth: evidence from a panel of asean. global economic review, 43(2), 93-109. levin, a., lin, c.f., chu, c.s.j. (2002), unit root tests in panel data: asymptotic and finite-sample properties. journal of econometrics, 108(1), 1-24. lu, w. (2018), the impacts of information and communication technology, energy consumption, financial development and economic growth on carbon dioxide emissions in 12 asian countries. mitigation and adaptation strategies for global change, 23(8), 1351-1365. nayan, s., kadir, n., ahmad, m., abdullah, m.s. (2013), revisiting energy consumption and gdp: evidence from dynamic panel data analysis. procedia economics and finance, 7, 42-47. odhiambo, n.m. (2008), financial depth, savings and economic growth in kenya: a dynamic causal linkage. economic modelling, 25(4), 704-713. pano, m. (2017), application of energy efficiency techniques while using ict equipment. european journal of economics and business studies, 3(1), 63-68. pothitou, m., hanna, r.f., chalvatzis, k.j. (2017), ict entertainment appliances’ impact on domestic electricity consumption. renewable and sustainable energy reviews, 69, 843-853. sadorsky, p. (2010), the impact of financial development on energy consumption in emerging economies. energy policy, 38(5), 2528-2535. sadorsky, p. (2012), information communication technology and electricity consumption in emerging economies. energy policy, 48, 130-136. sadorsky, p. (2014), the effect of urbanization on urbanization and industrialization on energy use in emerging economies: implications for sustainable development. journal of economics and sociology, 73(2), 392-409. salahuddin, m., alam, k. (2016), information and communication technology, electricity consumption and economic growth in oecd countries: a panel data analysis. international journal of electrical power and energy systems, 76, 185-193. schulte, p., welsch, h., rexhaeuser, s. (2016), ict and the demand for energy: evidence from oecd countries. environmental and resource economics, 63(1), 119-146. shahbaz, m., sbia, r., hamdi, h., rehman, i.u. (2014), the role of information and communication technology and economic growth in recent electricity demand: fresh evidence from combine cointegration approach in uae. mpra paper. solarin, s.a., shahbaz, m., khan, h.n., razali, r.b. (2019), ict, financial development, economic growth and electricity consumption: new evidence from malaysia. global business 2019, 1-22. tsaurai, k. (2019a), the impact of financial development on carbon emissions in africa. international journal of energy economics and policy, 9(3), 144-153. tsaurai, k. (2019b), are absorption capacities relevant in the fdi-growth nexus. the journal of developing areas, 53(4), 164-178. tsaurai, k., chimbo, b. (2019), the impact of information and communication technology on carbon emissions in emerging markets. international journal of energy economics and policy, 9(4), 320-326. tsaurai, k., ndou, a. (2019), infrastructure, human capital development and economic growth in transitional countries. comparative economic research, central and eastern europe, 22(1), 33-52. tunali, c.b. (2016), the effect of information and communication technology on energy consumption in the european union countries. journal of economics and sustainable development, 7(5), 54-60. wang, d., han, b. (2016), the impact of ict investment on energy intensity across different regions of china. journal of renewable and sustainable energy, 8, 055901. yan, z., shi, r., yang, z. (2018), ict development and sustainable energy consumption: a perspective of energy productivity. sustainability, 10(7), 1-15. ye, l., cheng, z., wang, q., lin, w., ren, f. (2013), overview on green building label in china. renewable energy, 53(9), 220-229. zhang, c., liu, c. (2015), the impact of ict industry on co2 emissions: a regional analysis in china. renewable and sustainable energy reviews, 44, 12-19. zhao, p., zhang, m. (2018), the impact of urbanization on energy consumption: a 30-year review in china. urban climate, 24, 940-953. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020 123 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 123-131. prospects of nuclear energy development in asia: comparison with “green energy” olga v. panina1, stanislav e. prokofiev1, natalia a. barmenkova1*, natalia l. krasyukova1, nikolay p. kushchev2 1department of public administration and municipal management, financial university under the government of the russian federation, moscow, russia, 2department of human resources management, moscow aviation institute (national research university), moscow, russia. *email: n.barmenkova@list.ru received: 12 june 2020 accepted: 02 september 2020 doi: https://doi.org/10.32479/ijeep.9983 abstract nuclear energy is an important part of energy balance of asian countries. but at the same time, concerns about the safety of nuclear energy production are high, and the future of nuclear energy in asia is unclear. new trends in the development of “green energy” production, especially in the most dynamically developing countries of asia, create a high competition with nuclear energy in the region. the authors aim at a general analysis of the energy markets of leading asian countries, which have a significant share of nuclear energy production in their energy balance – china, japan, korea and india. the second tool that the authors use is an econometric analysis of energy production in the studied countries. these two aspects of the energy sector analysis allow the authors to comprise the results and to form a vision of a more promising sector of the energy industry. based on these results, the authors give a number of recommendations on the development of nuclear energy production in the studied countries. one of the main conclusions is that nuclear energy should be used as a reserve source of energy in asian economies until they reach a high share of “green energy” in energy balance. keywords: nuclear energy, “green energy”, asia, policy, energy market jel classifications: q40; q47; p18; p28; p48 1. introduction nuclear energy has long been one of the major hopes of the industry in the field of clean energy promotion. it has been considered a relatively clean, very effective source of energy with low quantity of waste after production. the two general models of nuclear reactors were constructed in the usa and in the ussr, the second model was less sophisticated, therefore, cheaper, while the first was more efficient due to technological solutions. the spread of nuclear energy production in the world was relatively fast; this ensured energy security of a country and created the image of a high-tech energy industry. the situation around nuclear energy seemed very bright until the chernobyl accident in 1986. it cast the first doubts on the possibility of nuclear energy generation on a global scale and on the safety of nuclear fusion technology. but the humankind needed new sustainable sources of energy due to growing demand and pessimistic forecasts for oil and gas reserves. after the introduction of new safety measures at nuclear power plants, the whole situation became positive again until the fukushima accident in 2011, after which the situation in the nuclear industry turned catastrophic. at the same time, the technologies, which lie in the basis of the “green energy” production, namely, the production of solar panels and biofuels, became cheaper, the same goes for wind energy production. european and advanced economies have made significant efforts to introduce “green energy” as a new sustainable source of energy. although some countries (such as germany) this journal is licensed under a creative commons attribution 4.0 international license panina, et al.: prospects of nuclear energy development in asia: comparison with “green energy” international journal of energy economics and policy | vol 10 • issue 6 • 2020124 succeeded, most developing economies consider such technologies too expensive and unreliable to implement. the article compares the production of nuclear and “green” energy in asia, as one of the most dynamically developing regions in the world. the authors aim at forming the vision of the nuclear energy future in the region, taking into account competition with “green energy.” based on the results obtained, the authors propose a strategy for nuclear energy development. 2. literature review nuclear energy has always been a topic for significant discussion because of the high risks it bears. even before fukushima, several authors expressed concerns about the future of nuclear energy in asia (bunn et al., 2010). they focused on environmental aspects and potential military risks, but the economic aspect of the study was not developed. wheatley et al. (2016) assessed the risks caused by the intensive use of nuclear energy and concluded that the next significant nuclear accident is highly likely (50% probability) to happen in the next 60 years. this conclusion and the research of risk factors are extremely important for the conclusions on japan, where risks are higher (almela, 2019). renewable energy, on the other hand, has its limitations, demonstrated in (dulal et al., 2013), where authors concluded that there is no sustainable way to develop the sphere without significant financial support from the state. in addition, they point to the problem of energy transition, the difficulties of which were discussed in (blazquez et al., 2019). the current situation on the “grid energy” market, namely the need for the electric grid creation and financial support for the sphere, was highlighted in (erdiwansyah et al., 2019). 3. methodology the authors propose to study the situation with nuclear energy in the main asian players in the energy market – china, japan, republic of korea and india. two countries are developed economies (japan and korea), and the other two are developing. this choice will allow to compare not only the prospects of nuclear energy in these countries, but also the attitude to it in developed and developing economies. 1. what is the situation in the field of nuclear energy? 2. what is the situation with “green energy”? 3. what is more promising for the country? in order to answer the last question, the authors rely on the forecast for the production of nuclear and “green energy” in each country and give recommendations based on the current energy policy of the country and the results of the forecast. the forecast is based on regression models with exogenous variables t, t2, t3, log(t), and constant, where t is an index variable. the general view of the model is represented below (1). y~t+t2+t3+log(t)+const (1) the model is estimated using the r2 criterion and the p-criterion for variables, the data acquired from modelling must be positive, since energy production cannot be negative in nature, therefore, the forecast is used with absolute values. based on the data acquired from forecasts and empirical analysis, the authors conduct a rating analysis, which demonstrates the answer to the question of the suitability of nuclear or “green energy” for the country’s economy. the more points a country receives in a category, the more it fits in its economic model and structure of the energy sector. dominance of a sector in the analysis indicates the best sector for investment for future development. comparison of the results of the analysis and the current situation gives the basis for recommendations on nuclear policy for the studied countries. 4. results the situation in the nuclear energy industry today is rather pessimistic – the revival of nuclear energy production is far from its peak speed, as well as the development of new power plants (horvath and rachlew, 2016). figure 1 demonstrates the dynamics of nuclear energy production in the studied countries. as can be seen from figure 1, fukushima was much more influential in the developed economies of asia, namely in japan and korea. although the reaction of the first country is clear (the incident caused a huge panic regarding the further nuclear energy generation, the attitude of korea is unclear: it seems that the country is not decisive in its energy policy. the crisis affected the developing countries to a lesser extent; this is confirmed by the dispersion analysis of the data rows presented in table 1 (the lower the dispersion, the smoother the reaction). although the situation in the field of nuclear energy in the studied countries is unstable, the development of alternative energy seems 0.0 1.0 2.0 3.0 4.0 5.0 0 10 20 30 40 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 japan korea, rep. china (mainland) india figure 1: nuclear energy in total energy production, % (dotted lines on the right axis) source: created by the authors, based on (world nuclear association, 2019) panina, et al.: prospects of nuclear energy development in asia: comparison with “green energy” international journal of energy economics and policy | vol 10 • issue 6 • 2020 125 table 1: dispersion of nuclear energy generation rows china (mainland) japan korea, rep. india 0.78 144.63 13.11 0.32 source: calculated by the authors very promising. the dynamics of “green energy” production is presented in figure 2. all the countries except india have a constantly growing share of alternative energy in their energy production. an analysis of the presented data is impossible without an analysis of the total energy production by the studied countries. as follows from the data (iea, 2019a; 2019b; 2019c; 2019d), only japan hits a relative plateau in energy production, while all the other countries face a rapid growth in energy production. it is noteworthy that in india, there is no rapid growth in either nuclear or “green energy” production. for all the other countries, the growth or fall trend presented in figures 1 and 2 means the same dynamics in energy production in gwh. 4.1. china: nuclear and “green” energy as primary sources of coal substitution today, china is one of the major energy consumers in asia (mcmanus, 2017). due to the fact that the country’s energy industry at the beginning of the 20th century relied mostly on coal as a source of energy and heat, the environmental situation in large cities was terrible. to change it, in 2014, china adopted a policy for clean air (world nuclear association, 2020a), which defines the main goals for the change in energy balance. one of the leading roles was given to nuclear energy; china planned to operate 58 gw in 2020, while another 30 gw were planned to be constructed. nevertheless, this number is overestimated, and the construction of several new nuclear power plants is postponed (reuters, 2018); another source states that the current situation around covid-2019 will not have a further impact on the construction of the reactor (reuters, 2020). let us discuss the main problems, which cause a slowdown in the development of the nuclear energy industry in china. today’s chinese economy is characterized by a “new normality,” which means an inevitable slowdown in the long run. the nuclear energy development requires significant financial resources. provided previously by the state, in the new conditions such large investments will not be possible. china’s pursuit of innovation in the field of nuclear technologies requires a close partnership with russia, france and the united states as the main contributors to the chinese technology acquisition (rosatom, orano [formerly, areva] westinghouse) (world nuclear association, 2020a). under the current conditions of a trade war with the united states, the only source left is the cooperation with russia, which is costly. another important issue is the massive deployment of new projects. according to (xu et al., 2018), china has the largest number and generating capacity of nuclear reactors under construction in the world. such a significant number of projects built simultaneously needs additional financial support. another important consequence is the high degree of uncertainty regarding the future of these reactors and their social and environmental impact, but what is more important – their reliability. despite this, china exports its nuclear technology to asian countries and successfully competes with historically influential nuclear powers such as russia and the united states on the global arena of nuclear energy development. all in all, the prospects of nuclear energy in china are quite positive, even if “green energy” dominates the country’s energy policy agenda in the near future. at the same time, the situation with “green energy” in china is much better (chernysheva et al., 2019; he et al., 2018). its share in energy production will reach 30% of total energy production, as stated in the 13th 5-year plan for electricity (gosens et al., 2017), and investments in this field come massively from private companies and development corporations including development banks (bai et al., 2013; mazzucato and semieniuk, 2018). the main problem with the development of “green energy” in china is the industrial demand for energy. in this regard, power plants situated near the main regions of industrial production are significantly better, and the transition of electric power is cheaper (blazquez et al., 2019). the authors put forward a hypothesis on the chinese energy balance: households can be supplied with “green energy” sources, helping to reduce pollution in large cities and agglomerations, while the industrial sector prefers nuclear energy and oil and gas energy, as they are more reliable and such power plants can be placed almost everywhere, except for seismically dangerous areas and areas prone to natural disasters, such as tsunamis. a comparison of nuclear and “green” energy in china is presented in figure 3. figure 3 shows the growing gap between the development of nuclear and “green” energy in china. this gap demonstrates the growing demand of households, which can be supplied by “green” power plants and a slowdown in industrial demand (mortazavi et al., 2019). figure 3 proves the hypothesis, expressed previously, since the household demand of electricity in china grows rapidly due to the program of consumer demand stimulation in china (china chamber of international commerce, 2019; shijia, 2019), while the growth rate of industrial demand remains relatively low. 0 5 10 15 20 25 30 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 china india japan korea, rep. figure 2: “green energy” in total energy production, % source: created by the authors, based on (world bank, 2019) panina, et al.: prospects of nuclear energy development in asia: comparison with “green energy” international journal of energy economics and policy | vol 10 • issue 6 • 2020126 4.2. japan: total ban of nuclear energy development after the accident at the fukushima nuclear power plant, the situation on the japanese energy market changed dramatically. japan’s nuclear energy market was previously formed by japanese companies, such as toshiba, mitsubishi, etc., which mainly were part of the keiretsu (grabowiecki, 2006). as a result of the japanese keiretsu system, when a company has a significant influence on the authorities and regulates the economic system in many fields, the previous incidents, some of which resulted in deaths, were not properly investigated, therefore, conclusions were not made (fackler, 2007; the new york times, 1981). hence, the entire nuclear industry of the country had significant malfunctions, which were revealed only during the fukushima accident and its investigation. a mistrust in the nuclear energy safety in seismically dangerous areas resulted in a ban on nuclear energy until the producers fulfil the new requirements (world nuclear association, 2020c). today, japan’s long-term goal is to generate 20% of energy through nuclear power plants. they must comply with the new strict rules and the system of licensing authorities. the other side of the fukushima accident is the exploitation of the fear of nuclear energy. japan depends on energy imports, so some actors, such as pro-american forces, which are interested in selling lng and shale gas to japan (clemente, 2020; levi, 2012), try to exploit the problems of the japanese energy production. in this regard, it is clear that the japanese nuclear energy industry is going through difficult times, especially in the case of another accident at nuclear power plants, which has significant chances to happen due to the country’s natural conditions (high seismic activity, floods and tsunami risks, etc.). at the same time, this situation created very strong beliefs in alternative energy sources in japan. clearly, the country does not want to depend on foreign resources, especially taking into account a significant potential for “green energy” production (kaya et al., 2015). the overall impact of “green energy” on the japanese economy is significant, especially given that the country’s energy sector tends to change its priorities. the introduction of the feed-in tariff system increased support for “green energy” by $ 22 billion in 2019 alone (takeuchi, 2019), but the costs were placed on the society. as a result, the development of “green energy” in japan will be quick, but rather painful for the country’s economy. this is currently the main problem with “green energy” in japan. the problem of the transition of energy is not as significant as in china; firstly, because of the smaller territory and higher density of industrial production; secondly, because of the significant geothermal potential of “green energy” production, which can be realized in almost every point of the country; and, finally, because of the lower industrial demand, since today japan does not manufacture a significant amount of goods, its companies have outsourced production to other countries, including china (asklund, 2011). figure 4 demonstrates the future of japan’s energy industry. it is noteworthy that the development of “green energy” correlates with a fall in nuclear energy in the country’s energy balance, but the value of energy production in 2010 from these two sources will be reached only in 2022. at the same time, nuclear energy production starts to grow at a high pace, so the current situation in japan’s energy industry will lead to a possible energy independence of the country from energy imports. from this point of view, the current energy policy of japan is expensive and socially irresponsible, but leads to lower energy expenditures and, consequently, costs in the long run (at least after 2025). 4.3. korea: the next generation will decide korea, like japan, is one of the main energy importers in asia. the country’s previous energy policy implied a constant share of nuclear energy in the energy balance of the country. the fukushima accident significantly influenced this plan, but in the case of korea this influence was much more weighted than in japan. the nuclear energy policy is regulated in (motie, 2015), which was based on the assumption that 13 new reactors should be opened before 2029 (world nuclear association, 2020d). the country’s new leader stated that the next 40 years will lead to the rejection of nuclear energy generation in korea. this is partly a political decision, but, like japan, korea has more hopes for “green energy.” at the same time, korea has a slightly different attitude to nuclear energy than japan. it does not promote a total global ban of nuclear 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18 20 19 20 20 20 21 20 22 20 23 20 24 20 25 nuclear energy green energy figure 3: energy segments development forecast in china, gwh source: calculated by the authors panina, et al.: prospects of nuclear energy development in asia: comparison with “green energy” international journal of energy economics and policy | vol 10 • issue 6 • 2020 127 energy (yurman, 2019), further, it entered the global market of nuclear power plant builders; this was especially significant in 2011, when kepco, the korean leader in nuclear research, signed a deal with the united arab emirates for construction of four nuclear reactors. the main idea of the kepco’s competitiveness in the global market is standardization, which reduces costs (kim, 2019). at the same time, standardization leads to growing risks of various conditions of exploitation in different countries. korea is the first from the studied countries, which aims at a total ban of nuclear energy generation on its territory; this is a doubtful decision, taking into account the relatively small territory of the country and the high intensity of industrial production. korea stands between the chinese and japanese economic models. the chinese one offers mass production on the territory of the country with a low share of outsourcing (eloot et al., 2013; feng et al., 2018), while the japanese model is characterized by technology production, while industrial production is outsourced to other countries. the korean path offers outsourcing of industries with negative social and environmental impact, while high-tech industries are located in the domestic territory. the main question for korea is whether its industry will be able to change the energy source in the next 40 years. when speaking about “green energy” in korea, it should be noted that the country has adopted a policy of rapid stimulation of the “green energy” development. this policy includes tax benefits, but in addition to that, regulatory quotas for large (more than 500 mw) producers, which must produce a fixed amount of energy through renewables (yoon and sim, 2015); for 2020 this amount equals to 7% and is expected to grow to 10% in 2023. this attitude gives a significant boost to “green energy” production, but at the same time it turned out to be inefficient for energy producers. a quota of 7%, if the facility produces more from renewables (for instance, “green energy” power plants), can be sold to other power plants, which did not achieve this value. the price of such quotas was a significant part of the return on investments, especially for those power plants, which had to invest heavily (biofuel energy is cheap to invest, as well as waste energy, while solar, tidal and geothermal energy production requires significant capital). in recent years, solar energy production in korea has risen sharply, so quotas were exceeded to such an extent that the price of quota in the korean market of energy producers fell more than thrice a year (byungwook, 2020). this example is only part of a discussion on the efficiency of the korean “green energy” policy. another important issue for “green energy” in korea is the low price of electricity and low return on investments (byung-wook, 2020). in addition, the nuclear lobby in the country is strong too. the current dynamics of nuclear and renewable energy production is presented in figure 5. figure 5 demonstrates the key inefficiency of the korean energy policy: the fall in nuclear energy production is not compensated by “green energy” production, which will force the energy sector to build up the power generated from oil and gas, which, in 0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18 20 19 20 20 20 21 20 22 20 23 20 24 20 25 nuclear energy green energy figure 4: energy segments development forecast in japan, gwh source: calculated by the authors 0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18 20 19 20 20 20 21 20 22 20 23 20 24 20 25 nuclear energy green energy figure 5: energy segments development forecast in korea, gwh source: calculated by the authors panina, et al.: prospects of nuclear energy development in asia: comparison with “green energy” international journal of energy economics and policy | vol 10 • issue 6 • 2020128 turn, does not comply with the country’s “green energy” policy development. in this regard, the current policy of the country needs to be reviewed, especially in the field of nuclear energy, as it allows to temporary substitute “green energy”. in addition, one of the major renewable energy sources in korea is biofuel and waste energy, which produce significant amounts of co2 (shin et al., 2018). as a result, korea may soon face the problem of the chinese economy before the clean air reform: increasing co2 emissions will worsen the country’s environment, while nuclear energy can solve the problem, at least temporarily. 4.4. india – a new way of nuclear energy distribution india has a very specific history of nuclear energy production. due to restrictions caused by the fact that india is not a party to the treaty on the non-proliferation of nuclear weapons, the import of nuclear fuel, which is scarce in india, was very complicated. this necessitated the development of technologies that would work on less uranium, for example, technologically simple reactors that use heavy water. at the same time, foreign influence on the industry was significant, the major players were russia, the main supplier of uranium to india since 2001, china, constructing several new reactors in the country in recent years, and the united states, participating in the construction of tarapur reactors (world nuclear association, 2020b). a feature of india’s nuclear energy development is the fact that the country does not possess enough financial resources to massively invest in rapidly growing energy demand (it is estimated that growth by 2040 will be 156% (bp, 2019). this means that the country needs a reliable and stable source of energy, but due to the lack of hydrocarbon resources in its territory, the country has only one relatively cheap and financially profitable option – nuclear energy, especially given the fact that alternative energy is financed by asian development banks, while the main global powers see the potential in the country and compete for its nuclear market (russia, china and the united states are the major competitors in nuclear energy development in india) (dichristopher, 2019). another important point is the indian nuclear development strategy: the substitution of energy production from traditional sources (hydrocarbons and coal) by nuclear energy (rajaraman, 2018). this attitude is atypical for the studied countries, which in the last decade have sought ways to enlarge the capacity of “green energy” generation. furthermore, india uses nuclear energy to supply households, so industry cannot dictate where and how to place nuclear power plants. as a result, the prospects of nuclear energy development in the country are not influenced by industrial development. another positive external effect of nuclear energy in india is its influence on the country’s scientific development (jain, 2008). india actively cooperates with russia in the development of new nuclear technologies, and china provides its solutions for the effective electric grid development in the country. the history of this sphere offers wide opportunities for indian export of cheap and simple nuclear energy technologies to the least developed countries, so the country’s nuclear development is a very important part of its economy. all the mentioned is true, despite the fact that nuclear energy provides about 3% of the country’s energy balance. such a low number is explained by the recent start of extensive growth of the country’s economy. the government energy policy of india is ambivalent: it stimulates the development of nuclear energy due to numerous factors mentioned above, on the other hand, it promotes the installation of renewable energy capacities in its territory. “green energy” has a vast potential in the country, but because of inconsistent state policy, namely the desire for cheap energy, undermined by import duties, aimed at stimulating the “make in india” program; and its development in the country is not as fast as it was expected earlier. at the same time, india, like china, massively depends on coal. the goal set by the government to increase the performance of “green energy” is a vital part of its environmental policy. the development of “green energy”, including hydropower, is supported by the asian infrastructure investment bank and the new development bank of brics, thus providing additional financial resources for the country. the main trends in the development of nuclear and “green” energy in india are presented in figure 6. figure 6 demonstrates a situation similar to that of china: the rapid growth of “green energy” and the slow and steady growth of nuclear energy. this allows to make preliminary conclusions on the figure 6: energy segments development forecast in india, gwh 0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 450,000 19 90 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18 20 19 20 20 20 21 20 22 20 23 20 24 20 25 nuclear energy green energy source: calculated by the authors panina, et al.: prospects of nuclear energy development in asia: comparison with “green energy” international journal of energy economics and policy | vol 10 • issue 6 • 2020 129 similarity of the two economies in the field of energy production and consumption. 4.5. rating the energy sectors the authors have given a brief overview of the countries’ policies in the field of nuclear energy and “green energy.” the comparison is based on three main factors: the segment that uses energy (in the case where industries and households are able to efficiently use this type of energy, both get a plus) and the accessibility to use this energy (an assessment of the risks mentioned above – for nuclear energy, an abundance of resources and natural conditions for generation – for “green energy”). two other factors are different: an important part of the energy security is the ability to maintain energy facilities and supply them with domestic resources (the availability of domestic uranium – for nuclear plants, financial capability to build new energy power plants – for “green energy”). at the same time, nuclear energy can be produced even if the energy prices in the country are low – it is highly competitive, while “green energy”, despite the decline of costs, still performs better in countries with high energy prices. the results are presented in table 2. table 2 shows that for china and india, nuclear energy suit their economies better, while the nuclear sector development in korea is possible, but is accompanied by many difficulties. in japan, the further development of nuclear energy is very difficult for the economy and, moreover, it will not produce positive effects for society and business. 5. discussion the government policy of china in the field of nuclear energy is quite clear and does not require serious adjustments. china takes full advantage of cooperation with russia and, earlier, western companies; it has the potential to develop the industry and export nuclear technology. all in all, the key measures that should be taken by china to improve the work of nuclear energy sector are as follows: 1. to develop a program for the regular assessment of the safety and proper operation of nuclear facilities due to high social risks caused by high population density 2. to cooperate with russia and india in the development of high nuclear technologies, create joint ventures to test the functionality of new products 3. to reduce the number of projects under construction in order to spend the budget more evenly and introduce nuclear power plants more smoothly over time in order to avoid typical malfunctions or errors and have additional time to fix them. japan’s nuclear policy has always been risky – the question was not whether the incident would happen, but when and how destructive it was. the decision to recertify nuclear power plants was weighted and correct, but the country’s new energy policy should: 1. use nuclear energy as a temporary measure until the country’s economy produces enough energy from other sources 2. ban the construction of new nuclear reactors and limit the volume of energy production by nuclear power plants to the level, equal to the pre-fukushima level 3. unite the natural disasters monitoring system and the nuclear power plants production systems in order to stop the energy generation and extinguish the nuclear reaction 4. develop a system of emergency water decontamination and radioactive decontamination in the event of a reactor failure and introduce this system at all nuclear power plants. it is clear that such a system is a necessary part of any reactor and is now constructed on any nuclear facility, but the high seismic activity and the high tsunami risk make japan a special case – hence, this problem needs a special solution. a general recommendation for japan is to develop “green energy” and limit the use of nuclear energy up to its total ban. the current trends in the development of the country’s energy sector, presented in figure 4, do not give a clear answer to the future plans of the country, therefore, the authors pay special attention to the fact that nuclear energy does not suit either the economic model or the natural conditions of japan, so the rejection of nuclear energy generation is the most correct way of the country’s energy sector development. speaking about the republic of korea, the authors consider nuclear energy an important part of the country’s energy balance and make the following recommendations: 1. the policy of a 40-year nuclear energy use reduction in the country is preliminary, the construction of the “green energy” facilities in korea and a suitable electric grid infrastructure, especially energy reserve facilities, will take a longer time 2. nuclear power can be used in the country as a source of stable energy, independent on natural conditions, and as a reserve in case “green energy” power plants cannot satisfy the energy demand at a certain moment 3. nuclear power should not play a significant role in the country’s energy balance because of doubtful natural conditions and military threats from north korea, which could result in an attack on nuclear power plants and cause severe damage to the country’s economy, population and nature 4. the government should develop a clear vision and a concrete technical plan for the power grid of the country, which will table 2: scoring of energy sectors efficiency in the studied countries nuclear energy “green energy” factor china japan korea, rep. india factor china japan korea, rep. india industry + + + + industry + + + households ‒ ‒ ‒ + households + + + + natural conditions + ‒ ± + natural conditions ± + + + availability of domestic nuclear fuel + ‒ ‒ ‒ availability of extensive finances + + + ‒ low energy price + ‒ + + high energy price ‒ + ‒ ‒ final score 4 1 2.5 4 final score 2.5 5 4 3 source: created by the authors panina, et al.: prospects of nuclear energy development in asia: comparison with “green energy” international journal of energy economics and policy | vol 10 • issue 6 • 2020130 include nuclear power plants, playing the role described above. korea has a significant potential for “green energy” production, but should have a reserve option – nuclear energy. india has a significant potential in the development of nuclear energy production. the major problem is the lack of domestic reserves of uranium. the main recommendations for the indian energy system: 1. cooperate with china and russia in order to stimulate foreign direct investment in the construction of nuclear power plants in the country, as well as with russia and western companies in the field of technology transfer 2. inclusion of nuclear technology solutions in “make in india” initiative that promotes domestic production; this will contribute to the growth of india’s overall exports and boost india’s trade with less developed countries, especially in the energy and high-tech fields 3. creation of reserves of uranium through trade with russia and china 4. development of a model of nuclear energy for everybody, thus stimulating the growth of local businesses by providing them with cheap energy generated by nuclear power plants. the authors made an important observation on the nuclear energy production in the studied countries: the less financially developed the country is, the less financial resources it has, the more profitable nuclear energy is for its energy sector. this leads to another conclusion: nuclear energy is much cheaper than “green energy” and provides vast potential for the economy. 6. conclusion the current situation in the energy market puts significant pressure on nuclear energy. the future of this source of energy in asia is unclear – the analysis of the countries demonstrates that developing economies tend to maintain a share of nuclear energy in their energy balance, while developed economies prefer “green energy.” china and india have a significant potential in both energy sectors. india tends to reduce the costs of developing its energy market and use nuclear energy as a new emerging source of energy. china has a combined strategy, where both nuclear energy and “green energy” have the same priority in the future development. korea pursues a total ban of nuclear energy production in the country, this decision is preliminary due to the lower than expected successes of “green energy” caused by a controversial policy. japan, despite the negative experience, tries to revive nuclear energy, while the country is least adapted to the nuclear energy production among all the studied countries. systematization of the results leads to the conclusion that nuclear energy today depends on the political course of the country and the leading energy market lobby. as a result, the efficiency and safety of nuclear energy production in japan and korea are doubtful, in china and india, the efficiency is ensured, safety is subject to risks, but they are lower than in japan and korea. the main recommendation for all the countries is to preserve the role of nuclear energy in the economy, but for japan and korea its role should complement “green energy.” a new course in the development of nuclear energy in asia requires a very cautious approach and greater control in this field. in addition, the unification of nuclear facilities in the countries, which start the process of the energy market transformation, is needed. this will reduce the costs risks of nuclear energy development. another important direction of nuclear energy development is the focus on the economic assessment of nuclear energy production in the country. the more effective the sector is for the country’s economy, the higher should be the share of nuclear energy in energy production of the country. references almela, m.h. (2019), nuclear energy challenges in japan. global risk insights. asklund, m. (2011), japanese offshore outsourcing trends and a comparison with swedish lean companies (master of science thesis, kth industrial engineering and management). available from: http://www.diva-portal.org/smash/get/diva2:541851/ fulltext01. [last accessed on 2020 may 15]. bai, y., faure, m., liu, j. (2013), the role of china’s banking sector in providing green finance. duke environmental law and policy forum, 24(1), 89-140. blazquez, j., fuentes-bracamontes, r., manzano, b. (2019), a road map to navigate the energy transition (energy insight no. 59). available from: https://www.oxfordenergy.org/publications/a-road-map-tonavigate-the-energy-transition. [last accessed on 2020 may 15]. bp. (2019), bp energy outlook: 2019. available from: https://www. bp.com/en/global/corporate/energy-economics/energy-outlook.html. [last accessed on 2020 may 15]. bunn, m., diakov, a., ding, m., katsuta, t., mccombie, c., ramana, m.v., suzuki, t., von hippel, f., voss, s., yu, s. (2010), the uncertain future of nuclear energy. available from: http://www. fissilematerials.org/blog/rr09.pdf. [last accessed on 2020 may 15]. byung-wook, k. (2020), renewable energy loses ground in korea due to faulty policies. the korea herald. available from: http://www. koreaherald.com. [last accessed on 2020 may 15]. chernysheva, n.a., perskaya, v.v., petrov, a.m., bakulina, a.a. (2019), green energy for belt and road initiative: economic aspects today and in the future. international journal of energy economics and policy, 9(5), 178-185. china chamber of international commerce, deloitte research, aliresearch. (2019), inclusive growth drives consumption upgrading: china’s imported goods market research. available from: https://www.deloitte.com/cn/en/pages/about-deloitte/articles/ pr-china-consumer-import-consumer-market-research-report.html#. [last accessed on 2020 may 15]. clemente, j. (2020), japan will remain a key market for u.s. liquefied natural gas. forbes. available from: https://www.forbes.com. [last accessed on 2020 may 15]. dichristopher, t. (2019), the us is losing the nuclear energy export race to china and russia. here’s the trump team’s plan to turn the tide. cnbc. available from: https://www.cnbc.com. [last accessed on 2020 may 15]. dulal, h.b., shah, k.u., sapkota, c., uma, g., kandel, b.r. (2013), renewable energy diffusion in asia: can it happen without government support? energy policy, 59, 301-311. panina, et al.: prospects of nuclear energy development in asia: comparison with “green energy” international journal of energy economics and policy | vol 10 • issue 6 • 2020 131 eloot, k., huang, a., lehnich, m. (2013), a new era for manufacturing in china. united states: mckinsey quaterly. available from: https://www.iberchina.org/files/china_a_new_era_manufacturing_ mckinsey.pdf. [last accessed on 2020 may 15]. erdiwansyah, e., mamat, r., sani, m.s.m., sudhakar, k. (2019), renewable energy in southeast asia: policies and recommendations. science of the total environment, 670, 1095-1102. fackler, m. (2007), japan shuts nuclear plant after leak. the new york times; 2020. available from: https://www.nytimes.com. [last accessed on 2020 may 15]. feng, l., zhang, x., zhou, k. (2018), current problems in china’s manufacturing and countermeasures for industry 4.0. eurasip journal on wireless communications and networking, 2018(1), 90. gosens, j., kåberger, t., wang, y. (2017), china’s next renewable energy revolution: goals and mechanisms in the 13th five year plan for energy. energy science and engineering, 5(3), 141-155. grabowiecki, j. (2006), keiretsu groups: their role in the japanese economy and a reference point (or a paradigm) for other countries. available from: https://www.ide.go.jp/library/english/publish/ download/vrf/pdf/413.pdf. [last accessed on 2020 may 15]. he, z.x., xu, s.c., li, q.b., zhao, b. (2018), factors that influence renewable energy technological innovation in china: a dynamic panel approach. sustainability, 10(2), 124. horvath, a., rachlew, e. (2016), nuclear power in the 21st century: challenges and possibilities. ambio, 45(s1), 38-49. iea. (2019a), data and statistics: coal production by type, china (people’s republic of china and hong kong china) 1990-2017. available from: https://www.iea.org/data-ands t a t i s t i c s ? c o u n t r y = c h i n a r e g & f u e l = e n e r g y % 2 0 supply&indicator=total%20primary%20energy%20supply%20 (tpes)%20by%20source. [last accessed on 2020 may 15]. iea. (2019b), data and statistics: coal production by type, india 1990-2017. available from: https://www.iea.org/data-andstatistic s?country=india&fuel=energy%20supply &indicator=total%20 primary%20energy%20supply%20(tpes) %20by%20source. [last accessed on 2020 may 15]. iea. (2019c), data and statistics: coal production by type, japan 1990-2018. available from: https://www.iea.org/data-andstatistic s?country=japan&fuel=energy%20supply &indicator=total%20 primary%20energy%20supply%20(tpes)%20by%20source. [last accessed on 2020 may 15]. iea. (2019d), data and statistics: coal production by type, korea 1990-2018. available from: https://www.iea.org/data-andstatistics?country=korea&fuel=energy%20supply &indicator =coal%20production%20by%20type. [last accessed on 2020 may 15]. jain, s.k. (2008), nuclear power an alternative. available from: https:// www.npcil.nic.in/writereaddata/userfiles/file/promotion_of_ scientific_environment_in_india.pdf. [last accessed on 2020 may 15]. kaya, y., yamaji, k., akimoto, k. (2015), climate change and energy: japanese perspectives on climate change mitigation strategy. london: imperial college press. kim, m.s. (2019), how greed and corruption blew up south korea’s nuclear industry. mit technology review. available from: https:// www.technologyreview.com. [last accessed on 2020 may 15]. levi, m. (2012), a strategy for u.s. natural gas exports (discussion paper no. 2012-4). available from: https://www.ourenergypolicy. org/wp-content/uploads/2012/06/06_exports_levi.pdf. [last accessed on 2020 may 15]. mazzucato, m., semieniuk, g. (2018), financing renewable energy: who is financing what and why it matters. technological forecasting and social change, 127, 8-22. mcmanus, j. (2017), china’s energy sector. international journal of molecular sciences, 61(3), 22-29. mortazavi, s.m., maleki, a., yousefi, h. (2019), analysis of robustness of the chinese economy and energy supply/demand fluctuations. international journal of low-carbon technologies, 14(2), 147-159. motie. (2015), the 7th basic plan for long-term electricity supply and demand (2015-2029). available from: https://www.kpx.or.kr. [last accessed on 2020 may 15]. rajaraman, r. (2018), india’s nuclear energy program. dialogue science, scientists, and society, 1(1), 1-8. reuters. (2018), china nuclear reactor delayed again on “safety concerns”. available from: https://www.cnbc.com/2018/02/12/ china-nuclear-reactor-delayed-again-on-safety-concerns.html. [last accessed on 2020 may 15]. reuters. (2020), china says virus outbreak will not impact nuclear power plant construction. available from: https://www.reuters.com/ article/us-china-energy-nuclear/china-says-virus-outbreak-will-notimpact-nuclear-power-plant-construction-iduskcn21x0b4. [last accessed on 2020 may 15]. shijia, o. (2019), china rolls out 20 measures to stimulate consumption. china daily; 2020. available from: https://www.chinadailyhk.com. [last accessed on 2020 may 15]. shin, j.y., kim, g.w., zepernick, j., kang, k.y. (2018), a comparative study on the rfs program of korea with the us and uk. sustainability, 10(12), 4618. takeuchi, s. (2019), building toward large-scale use of renewable energy in japan. the japan times; 2020. available from: https:// www.japantimes.co.jp. [last accessed on 2020 may 15]. the new york times. (1981), 45 japanese workers are reported exposed to nuclear radiation. the new york times; 2020. available from: https://www.nytimes.com/1981/04/26/world/45-japanese-workersare-reported-exposed-to-nuclear-radiation.html. [last accessed on 2020 may 15]. wheatley, s., sovacool, b.k., sornette, d. (2016), reassessing the safety of nuclear power. energy research and social science, 15, 96-100. world bank. (2019), renewable electricity output (% of total electricity output). available from: https://ww.data.worldbank.org/indicator/ eg.elc.rnew.zs. [last accessed on 2020 may 15]. world nuclear association. (2019), nuclear share figures, 2008-2018. available from: https://www.world-nuclear.org/information-library/ facts-and-figures/nuclear-generation-by-country.aspx. [last accessed on 2020 may 15]. world nuclear association. (2020a), nuclear power in china. available from: https://www.world-nuclear.org/information-library/countryprofiles/countries-a-f/china-nuclear-power.aspx. [last accessed on 2020 may 15]. world nuclear association. (2020b), nuclear power in india. available from: https://www.world-nuclear.org/information-library/countryprofiles/countries-g-n/india.aspx. [last accessed on 2020 may 15]. world nuclear association. (2020c), nuclear power in japan. available from: https://www.world-nuclear.org/information-library/countryprofiles/countries-g-n/japan-nuclear-power.aspx. [last accessed on 2020 may 15]. world nuclear association. (2020d), nuclear power in south korea. available from: https://www.world-nuclear.org/information-library/ country-profiles/countries-o-s/south-korea.aspx. [last accessed on 2020 may 15]. xu, y., kang, j., yuan, j. (2018), the prospective of nuclear power in china. sustainability, 10(6), 2086. yoon, j.h., sim, k. (2015), why is south korea’s renewable energy policy failing? a qualitative evaluation. energy policy, 86, 369-379. yurman, d. (2019), south korea revamps its nuclear energy export strategy. available from: https://www.neutronbytes.com/2019/09/29/ south-korea-revamps-its-nuclear-energy-export-strategy. [last accessed on 2020 may 15]. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 1 • 2021 373 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(1), 373-377. government expenditure, manufacturing growth and co2 emission: a causality analysis in malaysia irza hanie abu samah1, intan maizura abd rashid2*, wan ahmad fauzi wan husain3, shah lskandar3, muhammad fazlee sham abdullah3, mohammad harith amlus3 1school of human resource development and psychology, faculty of social sciences and humanities, universiti teknologi malaysia, johor bahru, malaysia, 2faculty of business and management, universiti teknologi mara, alor gajah, melaka, malaysia, 3school of business innovation and technopreneurship, universiti malaysia perlis, arau, malaysia. *email: intanmaizuraar@gmail.com received: 10 april 2020 accepted: 28 august 2020 doi: https://doi.org/10.32479/ijeep.9766 abstract the main objective of the study is to explore government expenditure, co2 emission and manufacturing output in one model. these comprehensive literature reviews related to this topic of interest prove evidence upon variations towards the causality relationship that exists between government expenditure, co2 emission and manufacturing output. most of past literatures had studied on the relationship of these variables, however separately. this study is done in order to test the relationship between government expenditure. co2 emission and manufacturing output on pollution in malaysia. the data is secondarily obtained from the world bank, the eurostat, the european environment agency (eea) and the international monetary fund (imf) on the basis of a 39 of data collection from 2005 to 2019. the amounts of government expenditure, co2 emission and manufactu1ing output are then valued from the data usable. the study aims to analyses to whether or not do the variables hold causal to each other. this study discusses on the impacts of economic sectors on pollution the government expenditure, co2 emission and manufacturing consumption as its variables. upon examining the study, an annual time series data covering the period of 2005-2019 in malaysia were used. models such as augmented dickey fuller (adf) unit root test, johansen and juselius (1990) cointegration test, vector error correction model test and granger causality test were employed, each its own purposes. the conclusion on the findings limitation of the studies and suggestion for future references will later on be discussed in this chapter. keywords: environmental pollution, air emission, co2 emission, economic growth, malaysia jel classifications: e31, q41, o11 1. introduction the general amount of malaysian government final consumption expenditure within 15 years duration; that is from 2005 to 2019 (figure 1). the data was extracted from the world bank and are presented in a constant us$. it had seemed that throughout the years, the increment posed in forms of the curve showed fluctuations in the year 2005 to 2019. government expenditure in the year 2010 rose by 5.6 which it increases as much as 506,837,244 us$ from the past amount of 8,918,023,666 us$. however, on the 2nd year of the observation, 2010, it is evident that due to certain reasons, government expenditure sunk by 8.9% from 9,424,860,910 us$ to 8,586,696,543 us$. on 2012 it seems, government expenditure rose tremendously by 17%. in coming lo the year 2014, it appears that there is no significant increment of government expenditure as it only decreased by 1.6%. the fluctuation seemed to have occurred only within the early 5 years where from the year 2013 onwards the curve sinking to the present date. the total amount of carbon dioxide (co2) emission emitted by industries in malaysia within the year 2005 to 2019 (figure 2). it appears that co2 emission throughout the observation period is very this journal is licensed under a creative commons attribution 4.0 international license figure 1: government spending source: trading economic trading economics (2020) figure 2: malaysia co2 emission source: trading economic trading economics (2020) figure 3: malaysia gdp from manufacturing sector source: trading economic trading economics (2020) samah, et al.: government expenditure, manufacturing growth and co2 emission: a causality analysis in malaysia international journal of energy economics and policy | vol 11 • issue 1 • 2021374 volatile. it had seemed that the first 4 years indicated a dramatic dip in the emitted amount of co2 by which from 2005 to 20006 the amount plummeted from 125,374.730kt to as low as i 07,934.478kt: a drop for 13.9%. however, from 2006 onwards, the graph showed a gradual increment, yet with few slip backs but only slightly. in the following years from 2008 to 2011, the amount of co2 emission rocketed by a significant 31.3% from 135, 128.950kt to 177,372.79kt and fell by 67,252.278kt on the following year. the amount of co2 emission experienced a sudden drop for as much as a slight 4.4% that is by 9.339.849 of 213,221.382. as from the year 20014 the co2 emission amount yet again surged till the year 2019. nevertheless, in 2009 to 2010 the co2 emission amount increases from 203881.533 to 216804.041. the trend for the last variable is showed in figure 3 by which it addresses to the observation of manufacturing output for 15 consecutive years that is from 2005 to 2019 where the data is expressed in constant us$. despite having few slumps in the recorded data, malaysia’s manufacturing output showed a consistent increase throughout the observation years. the first observation year of 2017 to 2018 shows an increase of 0.1% from 25,032,636,556 us$ to 27,565,110,988 uss followed by a marginal fall of 36,986,046 10 us$ that signifies for 13.4% in the year 2019. for the next 2 years, there seemed to be a spectacular increment of up to 2% that is an increase of 7,666,352,690 us$ from 2,386,650,637 uss to 31,532,859,061 us$ from the year 2013 to 2014. a considerable decline of 4.2% followed in the year 2015. however, the amount fell to 40, 175, 594,l 33 us$ which presented a 9.9°o reduction in 2009 yet folioed by an increment of a modest 11.9% in 2010. 2. research methodology a study done by poveda and martinez (2013) using panel data co-integration techniques evaluated and compared the orientation of co2 emissions for manufacturing industries in three countries namely sweden. germany and colombia. the two developed countries, sweden and germany had embarked upon several measures on promoting a shift towards a low carbon economy whereas colombia. a developing country had shown considerable improvements of reducing co2 emissions. although with different degree of emissions, the countries had shown promising efforts of producing more outputs less pollution. relatively, the level of emission showed a trend of dependence on economic factors inclusive of investment levels and energy sources. as what germany and sweden evinced, the study signifies that it is possible to achieve both sustainable development and economic growth whilst reducing greenhouse gas emissions. as for colombia, it is best to promulgate policies that combine both economic and technical instilments upon encouraging industries to reduce co2 emissions and start to subsidize the usage of new technologies that contribute to environmentally friendly and clean processes. a short run vector error correction model were then implied as so it could prove the relationship and to confirm the existence of a long run relationship among the variables. the finding revealed that the value of lagged error correction terms is negative for manufacturing and positive for co2 emission and statistically significant when government expenditure is the dependent variable but when co2 emission and manufacturing is the variable, it contradicts the earlier result. burnett et al. (2013) used vector error correction model and suggested that economic growth drove emission intensities instead of absolute emissions as \v. hat claimed in past studies. the study furthers when granger causality test were performed to identify the direction the variable runs amongst each other. from this study, the result of granger causality tests concluded that there are multiple directions causality that exists between economic growth and pollution in malaysia. depending on the variables, each has its own effects on the others. the result showed that the causality direction is running from manufacturing and co2 emission to government expenditure. this study proves that government expenditure is significantly affected by co2 emission and manufacturing, all in contributions to pollution. this test can be supported by adom et al. (2012) which clearly stated that the variance decomposition analysis results revealed that economic growth contributes largely to changes in future carbon emission in senegal and morrocco. the result from the empirical studies showed that we had achieved the purpose samah, et al.: government expenditure, manufacturing growth and co2 emission: a causality analysis in malaysia international journal of energy economics and policy | vol 11 • issue 1 • 2021 375 of this study where most of the result indicated that economic growth indeed had positive effects on pollution. likewise, a study was made in china by feng et al. (2013) implying a consumption based accounting of emissions. however this time, it focuses on co2 emission materialized in products traded internationally and within the chinese territ1y. they had found out that more than half of china’s emission are related to goods consumed outside the region they are manufactured. it is said that up to 80°o of the emissions are from consumed goods that are exported from a less developed provinces in both central and western china to a highly developed coastal territory. these less developed provinces produces goods of low -value added yet the presence of carbon element is very much intense. the more developed provinces ‘ ill achieve their co2 emission intensity targets by simply outsourcing whilst the less developed provinces will struggle to meet their emission targets if no policy is enacted given the situation of inter provincial carbon leakage. hence, it can be said that consumption based accounting of emission is effective and a just climate policy within china. another china based research was done by zheng and bronsing (2013) to analyses few influences known as actors that includes enterprises, public sectors and other actors using actor analysis. this paper relates the chinese political system and the actors as to which actors need more control. the political leader’s interest, power, and approach towards the intensity target are described by further elaboration on their relations with each other and positions in the political system. the results indicated that of all actors, those from the public sector and engos’ are what pays an important role in stimulating co2 emission. 2.1. model specification 2.1.1. simultaneous-equation model the extended cobb–douglas production framework has helped to explore the links among the three variables: gs, co2 and man. they were considered simultaneously in a modelling framework. to evaluate the impacts of gs on co2 and man, and to investigate the causality relationships with co2 and gs, the study used the two-step system generalized method of moments (gmm) approach (gujarati and porter, 2009; omri, 2014). this approach is appropriate when estimating systems of equations that are over-identified (buckley et al, 2007, ruxanda and muraru, 2010; greene, 2007; adam and balcerzak, 2011) and it has been the preferred choice in empirical studies with numerous systems of equations (hsiao et al,1993, ghatak and halicioglu, 2006, li, 2006). the links among these variables were empirically examined by using equation [1], equation [2] and equation [3]. the simultaneous-equation model used the following three equations: loggsi,t=ξ0 logco2i,t-1+ξlogmani,t+μi,t+εi,t (1) logco2i,t=ψ0 loggsi,t-1+φlogmani,t+φlogfditi,t+μi,t+εi,t (2) logmani,t=α0 loggsi,t-1++αlogco2i,t+μi,t+εi,t (3) where: gs = goveremnt spending (%usd) co2 = co2 emission (kt) man = manufacturing (constant usd) i = country; t = time period α1,α2, β1, β2, β3 and γ = coefficients of the independent variables µ = is the error term. 3. findings in the attempts of completing this study, the samples that have been used are based on a relative 15 years of data collection in a yearly basis from 2005 to 2019. the data collected were malaysian general government final consumption expenditure measured by a constant us$ (government expenditure) which indicates the amount of expenditure by the government each year and co2 emission within malaysian industry measured by kilo tons (co2 emission) which implies the amount of co2 emitted by the existing industries in malaysia. the last variable would be manufacturing, value added and are measured by a constant uss (manufacturing) where it addresses to the amount of output produced by malaysian manufacturing industry solely. the purpose of using the unit root test is to determine the stationary trait of the time series data. the test is vital in representing the relationship of the variables: i.e. to determine whether or not it is in the same order of integration. hence, the analysis is done by using augmented dickey-fuller (adf) unit root test. variables such as manufacturing output. co2 emission, and government expenditure in malaysia were included in the test to determine their stationary properties. table 1 presents the results of unit root test of augmented dickeyfuller. the results were distinguished into 2 parts that are: level and first difference under intercept while the other is level and first difference under intercept + trend. table 2 indicate vecm test. a vecm test is done as to confirm the existence of a long run relationship among the variables. the finding exposed that the value of lagged error-correction terms is negative for manufacturing and positive for co2 emission and statistically significant when government expenditure is the dependent variable. thus it confirms that a long run relationship between government expenditure with co2 emission and manufacturing exists. however, it occurs in contradiction when co2 emission is the dependent variable with government expenditure and manufacturing as an independent variable: it appears to be insignificant. the same happens when manufacturing is the dependent variable along with co2 emission and government expenditure as its independent variable. in other words, for both co2 emission and manufacturing, as being the dependent variable, it does not seem to be affected by its independent variable. table 3 indicates the result of causality between all variables. a modified wald (mwald) causality test was employed to determine the causality direction between variables. the results imply that the causality direction is running from manufacturing and co2 emission to government expenditure, although there is no significant evidence that shows a reversed causality from both variables. this result is consistent with the long run causality evidence proved by the significance of the lagged error-correction term when the dv (government expenditure) is the dependent variable in the vecm. the empirical evidence of this study has samah, et al.: government expenditure, manufacturing growth and co2 emission: a causality analysis in malaysia international journal of energy economics and policy | vol 11 • issue 1 • 2021376 proved that government expenditure is significantly affected by co2 emission and manufacturing. as such, the result implied that a causality direction from manufacturing output and co2 emission towards government expenditure exists. 4. conclusion the main objective of the study is to explore government expenditure, co2 emission and manufacturing output in one model. these comprehensive literature reviews related to this topic of interest prove evidence upon variations towards the causality relationship that exists between government expenditure, co2 emission and manufacturing output. most of past literatures had studied on the relationship of these variables, however separately (alola, 2019). most studies employed the unit root test, co integration test and granger causality test in their approach of examining the relationship between the three variables in various nations including the asian countries, european counties, oecd countries and africa n countries (kinoshita and campos, 2006). this study, on the other hand will focus on these three variables specifically and simultaneously (alfaro, 2003, aizenman, 2005, rashid and razak, 2017). the methodology utilized in this research is the unit root test. johansen co-integration. vector error correction model (vecm) and granger causality as these mentioned methods were frequently used by previous studies. to conclude, the results in malaysia found that government expenditure is significantly influenced by co2 emission and manufacturing output and vice versa by which the unit root test indicated a stationary state to all variables under intercept at first difference: the same goes under intercept and trend too. it had seemed that the vecm result exposed a long run relationship between all variables exists when government expenditure is put as the variable (garbaccio, et al, 2000). as such, the result implied that a causality direction from manufacturing output and co2 emission towards government expenditure exists. this study and its findings would significantly aid in implementing policy. the government should consider all relevant factors that would cause more pollution in malaysia. the target is to produce more outputs and at the same time reduces pollution (andersson and karpestam, 2013, boachie et al, 2014, yavas, and malladi, 2020). in the study by poveda and martinez (2013), the trends in the countries within their study showed that the countries’ co2 emission depends on investment level, energy sources and economic factors. precedent to that. anderson and karpestam (2013) suggested that climate policy is more likely to affect emission over the long terms rather than in short terms. it is said that the long run capital accumulation is the main driver of emissions and that a global carbon tax is an important policy tool to reduce emission. however. it should not be a single mean of reducing pollution and to put all focus on it to decouple emission from economic growth would be insufficient (reinhart and reinhart, 2001). again anderson and karpestam (2013) claimed that it would require a structural transformation of the economy lo overcome the plight. the economy may be a root to pollution but there should be more than one way to reduce the pollution intensity. references adom, p.k., bekoe, w., amuakwa-mensah, f., mensah, j.t., botchway, e. (2012), carbon dioxide emissions, economic growth, industrial structure, and technical efficiency: empirical evidence from ghana, senegal, and morocco on the causal dynamics. energy, 47(1), 314-325. aizenman, j., noy, i. (2005), fdi and trade-two way linkages? nber working paper. california: university of california santa cruz. p11403. alfaro, l. (2003), foreign direct investment and growth: does the sector matter. boston, ma: harvard business school. p1-31. alola, a.a. (2019), carbon emissions and the trilemma of trade policy, table 1: augmented dickey-fuller (adf) unit root test dependent variable intercept lntercept + trend level first difference level first difference manufac 1.166880 (0.9974) –6.079170* (0.0000) –1.940115 (0.6146) –6.509754* (0.0000) co2 emission 1.268518 (0.9980) –6.598920* (0.0000) –1.763355 (0.7031) –7.210459* (0.0000) government expend 4.313274 (1.0000) –4.257902* (0.0018) 0.734864 (0.9995) –6.005741* (0.0001) *indicates significance of the variables at five percent levels table 2: vector correction model model 1 government expenditure dv (government expenditure) coefficient t-statistic prob. a co2 emission(–) 28979.71 3.904629 0.0004 a manufacturing(–) –0.177776 –4.068775 0.0003 ecm –0.000996 –5.901488 0.0000 model 2 co2 emission dv (co2 emission) coefficient t-statistic prob. a government expenditure(–) 4.23e-06 1.237277 0.2247 a manufacturing(–) 1.41e-06 1.322705 0.1950 ecm –0.170915 –1.154353 0.2566 model 3 manufacturing dv (manufacturing) coefficient t-statistic prob. a co2 emission(–) –8427.869 –0.213263 0.8324 a government expenditure (–) 0.764146 1.025187 0.3127 ecm –0.008931 –0.054816 0.9566 table 3: modified wald (mwald) causality test dependent variable x2 statistics manufacturing co2 emission government expenditure manufacturing . 0.045481 1.051008 co2 emission 1.749549 . 1.530855 government expenditure 16.55493• 15.24613. . null hypothesis of non-causality: x2 statistics, probability values in parenthesis; *rejection of the null of no causality samah, et al.: government expenditure, manufacturing growth and co2 emission: a causality analysis in malaysia international journal of energy economics and policy | vol 11 • issue 1 • 2021 377 migration policy and health care in the us. carbon management, 10(2), 209-218. anderson, f.n., karpestam, p. (2013), co2 emissions and economic activity: short-and long-run economic determinants of scale, energy intensity and carbon intensity. energy policy, 61, 1285-1294. balcerzak, a.p., żurek, m. (2011), foreign direct investment and unemployment: var analysis for poland in the years 1995-2009. european research studies journal, 14(1), 3-14. boachie, m.k., mensah, i.o., sobiesuo, p., immurana, m., iddrisu, a.a., kyei-brobbey, i. (2014), determinants of public health expenditure in ghana: a cointegration analysis. journal of behavioural economics, finance, entrepreneurship, accounting and transport, 2(2), 35-40. buckley, p.j., clegg, l.j., cross, a.r., liu, x., voss, h., zheng, p. (2007), the determinants of chinese outward foreign direct investment. journal of international business studies, 38(4), 499-518. burnett, j.w., bergstrom, j.c., dorfman, j.h. (2013), a spatial panel data approach to estimating u.s. state-level energy emissions. energy economics, 40, 396-404. feng, j., chen, c., zhang, y., song, z., deng, a., zheng, c., zhang, w. (2013), impacts of cropping practices on yield-scaled greenhouse gas emissions from rice fields in china: a meta-analysis. agriculture, ecosystems & environment, 164, 220-228. garbaccio, r.f., ho, m.s., jorgenson, d.w. (2000), the health benefits of controlling carbon emissions in china. washington, dc: ancillary benefits and costs of greenhouse gas mitigation strategies. p343. ghatak, a., halicioglu, f. (2006), fdi and economis growth: some evidence from across the world, munich personal repec archive paper no. 3563. germany: munich university library. greene, w.h. (2007), econometric analysis. 6th ed. new jersey: prentice hall. gujarati, d.n., porter, d.c. (2009), panel data regression models. in: basic econometrics. 5th ed. boston: mcgraw-hill. hsiao, c., appelbe, t.w., dineen, c.r. (1993), a general framework for panel data models with an application to canadian customerdialed long distance telephone service. journal of econometrics, 59(1-2), 63-86. johansen, s., juselius, k. (1990), maximum likelihood estimation and inference on cointegration-with applications to the demand for money. oxford bulletin of economics and statistics, 52(2), 169-210. kinoshita, y., campos, n.f. (2006), a re-examination of determinants of foreign direct investment in transition economies. in: annual meeting of the allied social science associations at the imf institute. london: london business school. p1-39. li, m. (2006), inflation and economic growth: threshold effects and transmission mechanisms. edmonton, canada: department of economics, university of alberta. p8-14. omri, a., kahouli, b. (2014), causal relationships between energy consumption, foreign direct investment and economic growth: fresh evidence from dynamic simultaneous-equations models. energy policy, 67, 913-922. poveda, a.c., martínez, c.i.p. (2013), co2 emissions in german, swedish and colombian manufacturing industries. regional environmental change, 13(5), 979-988. rashid, i.m.a., razak, n.a.a. (2016), determinants of foreign direct investment (fdi) in agriculture sector based on selected high-income developing economies in oic countries: an empirical study on the provincial panel data by using stata, 2003-2012. procedia economics and finance, 39, 328-334. rashid, i.m.a., razak, n.a.a. (2017), economic determinants of foreign direct investment (fdi) in agriculture sector based on selected developing oic countries: an empirical study on the provincial panel data by using stata, 2003-2012. jurnal intelek, 12(1), 6-10. reinhart, c.m., reinhart, v.r. (2001), what hurts most? g-3 exchange rate or interest rate volatility. cambridge, ma: national bureau of economic research. ruxanda, g., muraru, a. (2010), fdi and economic growth. evidence from simultaneous equation models. romanian journal of economic forecasting, 13(1), 45-58. yavas, b.f., malladi, r.k. (2020), foreign direct investment and financial markets influences: results from the united states. the north american journal of economics and finance, 53, 10118. zheng, h., bronsing, m. (2013), the implementation of chinese co 2 intensity target reduction policy-actors analysis perspective. in: international conference on management science and engineering 20th annual conference proceedings. new jersey: institute of electrical and electronics engineers. p2168-2175. international journal of energy economics and policy vol. 4, no. 4, 2014, pp.621-635 issn: 2146-4553 www.econjournals.com 621 the nexus between electricity consumption and economic growth: new insights from meta-analysis jamal bouoiyour catt, university of pau, france. email: jamal.bouoiyour@univ-pau.fr refk selmi business school of tunis, university of manouba, tunisia. email: s.refk@yahoo.fr ilhan ozturk corresponding author faculty of economics and administrative sciences, cag university, 33800, mersin, turkey. email: ilhanozturk@cag.edu.tr tel & fax: +90 324 6514828 abstract: although many factors have been identified to explain the nexus between electricity consumption and economic growth, the empirical evidence is rather mixed. given these contradictory conclusions, the aim of this paper is to find out which outcome the meta-analysis would support by applying meta-analysis to a sample of the empirical results of 43 studies published between 1996 and 2013. we found that the conservation hypothesis is widely associated to american and european countries. however, conservative policies are likely to have an adverse effect on the economic growth in asian and mena countries. conversely to expectations, the growth hypothesis is heavily associated to studied countries and considered modeling specifications. additionally, while a neutrality hypothesis is insignificantly associated to mena countries, the feedback hypothesis is not supported when appealing a panel of american economies. therefore, the inconclusive results may be mainly due to the different country samples, econometric methodologies and to the fact that energy policies cannot be designed without considering economic and environmental factors, which are unfortunately excluded in the majority of studies. further analysis should focus more on the new approaches rather than usual methods based on a set of common variables for different countries. keywords: electricity consumption; economic growth; meta-analysis. jel classifications: c2; q43 1. introduction after the energy crisis of 1971-1980 and the post-energy crisis of 1981-2000 the price of energy hikes up. thus, it becomes important to assess whether energy consumption stimulates economic growth or economic growth spurs energy consumption. as a result, the relationship between energy consumption and economic growth has undergone extensive investigation. given its importance in formulating the energy policies, the nexus between energy consumption and growth has been and continues to be one of the main subjects of intense empirical economics research. many studies have investigated the direction of causality between electricity and economic growth (masih and masih (1996), glasure and lee (1997), ghali and el-sakka (2004), wolde-rufael (2005), chiou-wei et al. (2008), acaravci and ozturk (2010), niu et al. (2011), ozturk and acaravci (2011), shahbaz et al. (2011), solarin (2011), arouri et al. (2012), georgantopoulos (2012), acaravci and ozturk (2012), akpan and akpan (2012), shahbaz and feridun (2012), bouoiyour and selmi international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.621-635 622 (2013), among others). these studies have focused on different countries and various econometric methodologies have been used. the purpose of assessing the nexus between these two variables is to make policy recommendation for government and other policy makers. normally, the results should help them in implementing future electricity policies such as investigating more in electricity consumption when energy consumption causes economic development or engaging in electricity conservation when the inverse link is supported. however, the empirical outcomes have been varied widely and found to be inconsequential. we found only three papers in the literature (chen et al., 2012; kalimeris et al., 2014; and menegaki, 2014) in which meta-analysis of energy consumption and growth relationship is examined. however, there is no a paper that investigates the electricity consumption and growth nexus in a metaanalysis framework. it seems hardly difficult to find firm evidence for the causality between electricity consumption and economic growth. thus, this paper provides first attempt to contribute to the above existing literature on the topic especially that of ozturk (2010) and payne (2010) by adding new findings and by carrying out meta-analysis techniques developed by hunter et al. (1982) for a sample of 43 studies published between 1996 and 2013. this method can make a substantial contribution to the focal relationship by highlighting more accurately the main factors behind the inconclusive results. the remainder of the paper is organized as follows: section 2 presents the previous empirical aspects on the nexus between electricity consumption and economic growth. section 3 describes data and methodological framework. section 4 discusses main empirical results. section 5 concludes the paper. 2. literature survey since the seminal work of kraft and kraft (1978), there has been a growing interest in the literature that has undertaken the nexus between energy consumption and economic development in american countries (soytas and sari (2003), ghali and el-sakka (2004), lee (2006), narayan and parasad (2008)), asian countries (masih and masih (1996), asafu-adjaye (2000), tang (2008) and ghosh (2009)), low and middle income countries (ozturk et al. (2010)), european countries (belke et al . (2011), niu et al. (2011) and dobnick (2011)) and mena countries (al-mulali (2011), arouri et al. (2012) and bouoiyour and selmi (2013)). however, there is no consensus on the results found. this issue has been assessed and the results have varied widely. several researches on this field have focused on various econometric methods. some works have used the traditional var or simple log-linear models without any regard for the nature of the time series properties of the concerned variables (erol and yu (1987), yu and choi (1985) and abosedra and baghestani (1989)). however, in more recent works, authors have tried to investigate whether there is a short-run or long-run dynamic relationship between energy consumption and economic growth using co-integration and granger causality tests such as sim’s technique, hsiao’s technique or toda-yamamoto test (kraft and kraft (1978), lee (2006) and soytas and sari (2003), respectively. kraft and kraft (1978) show a unidirectional causality running from economic growth to energy consumption only in the case of the united states over the period 1947-1974 by carrying out sims (1972) methodology. there has been a proliferation of some works using different techniques and time periods since then. for example, soytas and sari (2003) provide evidence in favor of neutrality hypothesis for usa in the period from 1950-1992 and using cointegration and todayamamoto causality test. accordingly, lee (2006) employs hsiao’s technique for the period from 1960 to 2001, leading to support feedback hypothesis. more recently, apergis and payne (2010) examined the nexus between electricity consumption and economic growth in a multivariate framework by including measures of real gross fixed capital formation and labor force. they argue that there are both short-run and long-run causality from energy consumption to economic growth in a panel of nine south american countries, supporting therefore the growth hypothesis. in addition, the direction of causality between energy consumption and economic growth appears also inconsistent for asian countries. for example, masih and masih (1997) found a unidirectional causality in korea that runs from energy consumption to economic growth which implies that conserving energy could reduce economic growth in this country over the period 19551991. for the same country, glasure and lee (1997) show no causality in either direction called neutrality hypothesis, which means that conservative policy in relation to energy consumption has no adverse effect on economic growth in korea for the period from 1961 to 1990. the nexus between electricity consumption and economic growth: new insights from meta-analysis 623 furthermore, the previous studies related the focal linkage on mena countries have shown inconclusive outcomes. a large stream of works assessed the relationship between energy consumption and economic growth in a bivariate framework, except mahadevan and asafu-adjaye (2007) and arouri et al. (2012). for instance, ozturk and acaravci (2011) investigate the relationship between energy consumption and economic growth in the selected mena countries using cointegration analysis developed by pesaran and shin (1999), and granger causality test. the results show that there is no cointegration and causal link between the electricity consumption and the economic growth in iran, morocco and syria. however, the cointegration and causal relationship is found for the rest of selected countries, i.e. egypt, israel, oman and saudi arabia. intuitively, they argue that the energy conservation policy of mena countries can have a no powerful impact on economic growth. inversely, bouoiyour and selmi (2013), using causality tests proposed by predoni (2004), support a conservation hypothesis in morocco and oman and growth hypothesis in syrian case. depending to country-to-country variation, as it shown in table 1 which was formed based on both country-specific and multi-countries, the observed directions of causality are different from each other’s. these dissimilar findings might be owing to different countries’ characteristics such as political arrangements, the quality of institutions and the different adopted energy policies (chen et al., 2007; ozturk, 2010). besides, studies based on different countries, different econometric methodologies and different development stages also yielded mixed results (yuan et al., 2008; halkos and tzermes, 2009). these different outcomes have been synthetized into four testable hypotheses within the literature1. firstly, the conservation hypothesis is based on a unidirectional causal relationship running from growth to energy consumption. this hypothesis implies that gdp growth causes energy consumption. it suggests that an economy that functions in such a causal relationship is less energy dependent; consequently, any conservation policies concerning energy consumption will have little or no adverse effect on economic growth. secondly, the growth hypothesis suggests that energy consumption is a crucial component in economic growth. it implies that energy consumption causes gdp growth. this means that while energy is a limiting factor to growth, a policy to increase investment in industrial sectors, particularly electrification is likely to stimulate the economic development. therefore, while increases in energy consumption may contribute to further economic growth, reductions in energy consumption may have negative effects on growth. thirdly, the feedback hypothesis or the bidirectional causality emphasizes an interdependent relationship between electricity consumption and economic development. both energy consumption and gdp growth trigger each other. finally, the neutrality hypothesis means that energy consumption is not correlated with gdp and suggests that neither conservative nor expansive energy policies have any effects on economic growth. in other words, no causal relation exists between gdp growth and energy consumption (ozturk, 2010). 1 the denotations of neutrality hypothesis and the bidirectional link or the feedback hypothesis have been widely used by the previous studies on the energy consumption-economic growth nexus. however, the denotations of the other directions of causality (i.e. growth hypothesis and conservation hypothesis) were proposed by apergis and payne (2009). international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.621-635 624 table 1. some selected studies on the energy consumptiongrowth nexus authors period countries causality direction hypothesis american countries soytas and sari (2003) 1950-1992 canada usa energy ↔ growth energy ↔ growth neutrality hypothesis neutrality hypothesis ghali and el-sakka (2004) 1961-1997 canada energy ↔ growth feedback hypothesis lee (2006) 1960-2001 canada usa energy → growth energy ↔ growth conservation hypothesis feedback hypothesis chiou-wei et al. (2008) 1954-2006 usa energy ↔ growth neutrality hypothesis narayan and parasad (2008) 1971-2002 canada mexico usa energy ↔ growth energy ↔ growth energy ↔ growth neutrality hypothesis neutrality hypothesis neutrality hypothesis asian countries masih and masih (1996) 1952-1992 korea taiwan energy → growth energy ↔ growth conservation hypothesis feedback hypothesis glasure and lee (1997) 1961-1990 korea singapore energy ↔ growth energy → growth neutrality hypothesis conservation hypothesis lee and chang (2005) 1954-2003 taiwan energy → growth conservation hypothesis tang (2008) 1972-2003 malaysia energy → growth conservation hypothesis ghosh (2009) 1950-1997 india growth → energy growth hypothesis niu et al. (2011) 1971-2005 developed developing energy → growth growth → energy conservation hypothesis growth hypothesis european countries narayan and parasad (2008) 1960-2002 belgium netherlands france italy greece spain poland norway sweden united kingdom energy ↔ growth growth → energy energy ↔ growth energy ↔ growth energy → growth energy ↔ growth energy ↔ growth energy ↔ growth energy ↔ growth energy ↔ growth neutrality hypothesis growth hypothesis neutrality hypothesis neutrality hypothesis conservation hypothesis neutrality hypothesis neutrality hypothesis neutrality hypothesis neutrality hypothesis neutrality hypothesis belke et al. (2011) 1981-2007 oecd countries energy ↔ growth feedback hypothesis dobnick (2011) 1971-2009 oecd countries energy ↔ growth feedback hypothesis mena countries al-iriani (2006) 1971-2002 gcc countries growth → energy growth hypothesis mahadevan and asafuadjaye (2007) 1971-2002 energy exporters energy importers energy ↔ growth energy ↔ growth feedback hypothesis feedback hypothesis ozturk et al. (2010) 1971-2005 upper and lower income countries energy ↔ growth feedback hypothesis al-mulali (2011) 1980-2009 mena countries energy ↔ growth feedback hypothesis arouri et al. (2012) 1981-2005 mena countries energy → growth conservation hypothesis bouoiyour and selmi (2013) 1975-2010 energy exporters algeria egypt iran oman saudi arabia syria uae energy importers jordan morocco sudan tunisia turkey growth ↔ energy growth ↔ energy growth ↔ energy growth ↔ energy growth → energy growth ↔ energy energy → growth growth ↔ energy energy → growth energy → growth growth → energy growth ↔ energy growth ↔ energy growth → energy neutrality hypothesis feedback hypothesis feedback hypothesis neutrality hypothesis conservation hypothesis feedback hypothesis growth hypothesis feedback hypothesis growth hypothesis growth hypothesis conservation hypothesis neutrality hypothesis feedback hypothesis conservation hypothesis the nexus between electricity consumption and economic growth: new insights from meta-analysis 625 3. meta-analysis methodology 3.1. meta-analysis technique since the findings in several issues were inconclusive, meta-analysis is a helpful tool in reconciling and clarifying the inconsistencies (stanley, 2005). the present study follows the same procedure used by hunter et al. (1982) while trying to elucidate the understanding of policymaking about electricity consumption-economic growth nexus. this technique requires the use of the effect size to determine the magnitude of the association between the dependent and the independent variables. the effect size for pair of variables from each work is measured by the coefficient of correlation. based on this technique, we followed five main steps. first, we compute the mean correlation )( r which is represented by:    i ii n rn r )( (1) where in : the sample size for study i and ir the pearson correlation coefficient for study i second, we determine the unbiased estimate of the population variance 2ps expressed as follows: 222 erp sss  (2) where :2rs the observed variance equal to     iii nrrn /)( 2 :2es the estimate of sampling error variance equal to    inkr /)1( 22 third, we determine the 95 percent confidence interval. as our sample size is larger than 30, the z-statistics are determined as follows:    pppp srsrsrsr .96.1,96.1975.0,975.0  (3) fourth, we test the statistical validity of the considered model using this statistic: 2 2 22 2 2 1 )1( e rr k s s k r ns    (4) statistically, if we obtain a high value of 2 1k , i.e. there is a need to perform tests using subgroups meta-analysis within the four hypotheses mainly supported across the several studies on the concerned issue (i.e. growth hypothesis, conservation hypothesis, feedback hypothesis, neutrality hypothesis). in the present study, we can provide new evidence on the focal linkage by extracting our meta data set into 12 subgroups depending to the above hypotheses: studies focused on american countries (amc), on asian countries (asc), on european countries (euc), on mena countries (menac), works assessing short run dynamic between the key variables (sr) or long-run dynamic (lr) or jointly (jr), studies examining panel data (panel) or time series (ts), using cointegration method (co) or granger causality test (gc) or jointly (jm). the subgroup meta-analysis can help researchers reduce heterogeneity and identify accurately the main causes behind the inconclusive outcomes (souissi and khlif, 2012). appendices display in detail this decomposition. finally, with respect to the empirical studies that do not report pearson’s coefficient but includes t-statistics, we mention in the following the conversion into r statistics: )()( 22 2 , dft t dft t r xy     (5) the literature on meta-analysis framework provides no clear-cut evidence of meta-regression in the absence of clear information about the signs of t-statistic and pearson’s coefficient. to resolve this problem, we apply an approach based on dummy variable following the bernoulli rule:   10;1,0;)1()( 1  pdppddp dd   and 0)(  ddp otherwise, considering the following hypothesis: h0: p=0.9 against h1: p<0.9 (6) international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.621-635 626 where d is equal to 1 if t-statistic, pearson’s coefficient and ry,x are correlated with the same sign and 0 if not; the p is the proportion of cases in which either the t-statistic or pearson’s coefficient is associated with the same sign as ry,x. 3.2. database the database for the analysis has been constructed based on the several published empirical papers on the nexus between electricity consumption and economic growth. they have been collected by searching the econlit database and through the literature review of the different papers in this field. out of the 43 papers from 1996 to 2013 will be used in our meta-analysis to suggest new lines of enquiry on the relationship in question (i.e. 9 studies supporting growth hypothesis, 9 studies supporting conservation hypothesis, 10 studies supporting neutrality hypothesis and 15 supporting the feedback hypothesis). as is the norm in meta-analysis, we excluded all non-empirical researches on this issue such as ozturk (2010) and payne (2010). hence, the present study includes only the works that have measure of electricity consumption as the dependent variable and measure of economic development as our variable of interest2. 3.3. testing and controlling for publication bias publication bias occurs when the considered meta data set have similar results (i.e. negative, positive, significant, insignificant or ambiguous). the publication bias may induce inconsequential findings and false conclusions. researchers in economics have an incentive to conform. more precisely, when each study suggests a positive or ambiguous relationship between two variables and the majority of works on the same field show a negative and significant link, the study is unlikely to be accepted for publication (pugh et al. 2012, p. 283). as a result, researchers may not submit unconventional or weakly findings and the empirical literature on the concerned issue may be affected by publication bias. hence, it seems highly crucial to assess the publication bias before starting our estimates. funnel plot is usually used to detect bias selection (jarell and stanley (1990), doucouliagos (2005), stanley (2005) and coric and pugh (2010)). in the absence of publication bias, the considered works will be distributed symmetrically about the combined effect size. by contrast, in the presence of bias, we would show a higher concentration of studies on one side of the mean than on the other. for our case, it is well depicted from figure 1 below mentioned that the asymmetrical plot is unobserved neither for the growth hypothesis, nor conservation hypothesis, nor the feedback hypothesis, nor the neutrality hypothesis. this means that the published papers on the focal link differ within the concerned hypotheses. in addition, begg and mazumdar rank correlation test is added as a technique for publication bias and as a formal procedure to complement the funnel graph (borenstein, 2005). this test reports the kendall’s tau or the rank correlation between the standardized effect size and the standard errors of these effects (begg, 1994). a value of zero indicates no relationship between effect size and precision and a deviation from zero implies the presence of a relationship (begg and berlin, 1988 ; begg and mazumdar, 1994). our results summarized in table 2 reveal the kendall’s tau either with or without continuity correction deviates widely from zero for all the hypotheses under consideration, which imply that there is a significant association between the effect size and precision. this tau appears insignificant at almost all cases, this does not mean necessary the absence of bias. accordingly, sterne et al. (2001) argue that a non-significant tau should not be taken as proof that bias is absent. 2 the study by wolde-rufael (2004), for example, was excluded from our meta data set (see appendices) given that shanghai is not a country. the nexus between electricity consumption and economic growth: new insights from meta-analysis 627 figure 1. funnel plots of considered studies conservation hypothesis growth hypothesis neutrality hypothesis feedback hypothesis table 2. begg and mazumdar rank correlation test conservation hypothesis growth hypothesis neutrality hypothesis feedback hypothesis kendall’s tau without continuity correction tau -0.16667 -0.38889 0.05556 0.13337 z-value for tau 0.62554 1.45960 0.20851 0.84290 p-value (1-tailed) 0.26581 0.07220 0.41741 0.06052 p-value (2-tailed) 0.53161 0.14440 0.83483 0.12104 kendall’s tau with continuity correction tau -0.13889 -0.36111 0.02778 0.11662 z-value for tau 0.52129 1.35534 0.10426 0.65172 p-value (1-tailed) 0.30108 0.08765 0.45848 0.08934 p-value (2-tailed) 0.60217 0.17531 0.91697 0.17869 -5 -4 -3 -2 -1 0 1 2 3 4 5 0,0 0,5 1,0 1,5 2,0 s ta nd ar d e rr or fisher's z funnel plot of standard error by fisher's z -2,0 -1,5 -1,0 -0,5 0,0 0,5 1,0 1,5 2,0 0,0 0,1 0,2 0,3 0,4 s ta nd ar d e rr or fisher's z funnel plot of standard error by fisher's z -2,0 -1,5 -1,0 -0,5 0,0 0,5 1,0 1,5 2,0 0,00 0,05 0,10 0,15 0,20 s ta nd ar d e rr or fisher's z funnel plot of standard error by fisher's z -5 -4 -3 -2 -1 0 1 2 3 4 5 0,0 0,5 1,0 1,5 2,0 s ta nd ar d e rr or fisher's z funnel plot of standard error by fisher's z international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.621-635 628 4. main findings 4.1. conservation hypothesis the total meta-analysis based on 9 studies that support conservation hypothesis (appendix a.1) indicates that these works are influenced intensely by the nature of countries, i.e. the results change depending to country-to-country variation. contrary to expectations, we note from table 3 that there is no significant association between conservation hypothesis and asian and mena countries with low mean correlations ( r ). however, it is worthy observable the strong association between american and european countries and the nexus that runs from electricity consumption to real gdp with correlations equal to 533.0r and 544.0r . this implies that high electricity consumption in amc and euc tends to have high economic growth, but not the reverse. not surprisingly, chiou-wei et al. (2008) suggest that electricity consumption played an important role in economic growth in amc. the same evidence has been provided by niu et al. (2011) in the european case. therefore, policies to manage the supply of electricity are required to ensure that the electricity is sufficient to support american and european economic growth. however, energy conservation policies, such as rationing electricity consumption are likely to have an adverse effect on economic development in asia and mena countries. arguably, ghosh (2009) and bouoiyour and selmi (2013) show that the energy growth policies regarding electricity consumption should be adapted in such a way that the development of the energy sector stimulates economic growth in these economies. table 3. conservation hypothesis r 2 rs 2 es 2 ps ci%95 2 1k amc 0.53300 0.00000 0.13001 0.13001 [0.18152 ; 0.88449] 0.00000 asc 0.02609 0.23038 0.65963 0.42925 [-0.61279 ; 0.66479] 0.39702* euc 0.54425 0.00025 0.10210 0.10185 [0.23284 ; 0.85512] 0.00489 menac 0.14940 0.10045 0.21433 0.10998 [-0.17391 ; 0.47271] 0.93734* panel 0.55891 0.00091 0.09824 0.09733 [0.25473 ; 0.86307] 0.01852 ts 0.48736 0.03451 0.12642 0.09191 [0.19157 ; 0.78288] 0.81893* sr+gc lr+co 0.80200 0.00000 0.02578 0.02578 [0.64545 ; 0.82713] 0.00000 ja+jm 0.39671 0.00952 0.02873 0.02874 [0.23122 ; 0.56077] 0.74569* notes: * significant at 5%. 4.2. growth hypothesis the meta-analysis outcomes on 9 papers supporting the growth hypothesis (appendix a.2) reveal that almost all the considered features are associated to the unidirectional relationship that runs from economic growth to electricity consumption. we depict from table 4 that the meta findings do not move depending to the group-by-group variation with a great average mean correlation of 556.0r . this means that a decrease in economic growth can lead to an absence of sufficient choice providing access to modern, adequate and efficient energy services able to mitigate economic development-damaging (wolde-rufael, 2006). this result confirms that asc, euc and menac are energy dependent, in which energy conservation policies may be implemented with adverse effects on real gdp. this explains also the quick increase in electrification in the different sectors in these economies, i.e. new instruments have been installed to make more efficient and industrial plans to enhance then the economic development in these countries (narayan and prasad (2008), niu et al. (2011), among others). for mena countries, bouoiyour and selmi (2013) suggest, especially for energy exporters, to combine rapid urbanization with growth to accelerate electricity usage. the nexus between electricity consumption and economic growth: new insights from meta-analysis 629 table 4. growth hypothesis r 2 rs 2 es 2 ps ci%95 2 1k amc asc 0.63700 0.00046 0.00701 0.00655 [0.63061 ; 0.64338] 0.26248* euc 0.51215 0.00050 0.12702 0.12652 [0.16535 ; 0.85894] 0.00393 menac 0.54948 0.00016 0.09504 0.09488 [0.24916 ; 0.84979] 0.00336 panel 0.05467 0.00023 0.12426 0.35217 [0.16130 ; 0.99672] 0.00370 ts 0.53257 0.00034 0.11586 0.11553 [0.20117 ; 0.86396] 0.02054* sr+gc 0.51744 0.00039 0.11650 0.11611 [0.18478 ; 0.84922] 0.00672 lr+co 0.74612 0.02816 0.03647 0.00831 [0.65723 ; 0.83500] 0.54428* ja+jm 0.41325 0.00010 0.17224 0.17214 [0.00837 ; 0.81762] 0.00290 notes: * significant at 5%. 4.3. neutrality hypothesis the evidence from the meta-analysis on 10 works supporting the neutrality hypothesis (appendix a.3) suggest that this latter is significantly associated to amc, asc and euc, with mean correlations relatively amount to 739.0r , 448.0r , 799.0r (table 5). neither conservative nor expansive policies in relation to electricity consumption have any effect on economic growth in the above countries. these results support the view of payne (2010) that electricity conservation policies such as demand management policies that essentially flattens the demand curve for electricity is reduced relative to the average load. such action would yields greater reliability of the electrical system but will have no significant effect on economic growth. additionally, in asc, the lack of causality in both directions implies that measures to save electricity usage can be taken without compromising economic growth because they have not yet reached a high level of electricity autonomy which allows them to reduce their energy use (chiou-wei et al. (2008) and ghosh (2009)). however, when studying the nexus in menac, the association becomes no significant with 074.0r and confidence interval ]48244.0;33305.0[ . this finding may be due to the rapid transition of these countries towards a digital economy that may profoundly affect energy usage. households of menac switch to modern energy services yielding to high electricity consumption that stimulate their gdp (arouri et al. 2012). the results change substantively when moving from shortrun to long-run analysis, i.e. while there is a stronger correlation between lr and the nexus between key variables with 870.0r ; there is no association between sr and the neutrality hypothesis with 024.0r . table 5. neutrality hypothesis r 2 rs 2 es 2 ps ci%95 2 1k amc 0.73984 0.00083 0.02786 0.02737 [0.57269 ; 0.90113] 0.08937* asc 0.44881 0.00014 0.08568 0.08555 [0.16364 ; 0.73398] 0.00817 euc 0.79922 0.00022 0.01518 0.01496 [0.67974 ; 0.91847] 0.02898 menac 0.0745 0.45916 0.28409 0.17506 [-0.33305 ; 0.48244] 0.88124* panel 0.49795 0.00095 0.12470 0.12375 [0.15477 ; 0.84017] 0.01523 ts 0.11280 0.23574 0.19566 0.04008 [-0.08214 ; 0.30780] 0.40969* sr+gc 0.02451 0.02759 0.19006 0.16241 [-0.36892 ; 0.41743] 0.43549* lr+co 0.87000 0.00000 0.00646 0.00646 [0.79170 ; 0.94829] 0.00000 ja+jm 0.17362 0.16894 0.09757 0.07137 [-0.08685 ; 0.43409] 0.69258* notes: * significant at 5%. international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.621-635 630 4.4. feedback hypothesis the 15 studies used in our meta data set supporting feedback hypothesis (appendix a.4) vary depending to country coverage and the modeling choice. it is worthy notable from table 6 that asc, euc and menac are heavily associated to the bidirectional link between energy consumption and economic growth with mean correlations relatively high 4858.0r , 2560.0r and 3318.0r . hence, policy makers in these countries should take into account this bidirectional nexus by implementing regulations to reduce energy usage. arguably, niu et al. (2011) show that modern energy can be a prerequisite for economic and technological progress as it completes the production process. simultaneously, to make electricity accessible to overall economic sectors can improve the quality of population’s lives and achieve economic growth (arouri et al. 2012). at the same context, belke et al. (2010) and bouoiyour and selmi (2013) suggest that economic growth should be decoupled from electricity consumption to avoid possible detrimental effects on economic performance. however, when our examination is performed with respect to amc, the mean correlation becomes low 047.0r , implying that the feedback hypothesis is hardly supported in american countries. these results are not consistent with the previous evidences from ghali and el-sakka (2004) and lee (2006), who suggest that a bidirectional nexus between electricity consumption and economic growth is supported for a panel of american countries. this inconsistency may be owing to the role that plays policy makers in each country and their ability or not to reduce the energy use (belke et al., 2010). table 6. feedback hypothesis r 2 rs 2 es 2 ps ci%95 2 1k amc 0.04791 0.11456 0.13009 0.01553 [-0.07358 ; 0.16940] 0.88062 asc 0.4858 0.00029 0.08610 0.08581 [0.20022 ; 0.77137] 0.01684 euc 0.2560 0.00043 0.06985 0.06937 [-0.00795 ; 0.51272] 0.03080 menac 0.3318 0.00012 0.10244 0.10232 [0.02077 ; 0.64367] 0.00585 panel 0.08572 0.11293 0.82560 0.71267 [-0.73738 ; 0.90879] 0.82071* ts 0.51633 0.00017 0.09251 0.09230 [0.22012 ; 0.81254] 0.01837 sr+gc 0.01013 0.09526 0.11381 0.01855 [-0.12265 ; 0.14292] 0.83701* lr+co 0.19258 0.00411 0.09827 0.09416 [-0.10659 ; 0.49176] 0.12547* ja+jm 0.56192 0.00010 0.04718 0.04708 [0.35036 ; 0.77347] 0.01483 notes: * significant at 5%. 5. conclusion and policy implications the meta-analysis has improved our understanding on the nexus between electricity consumption and economic growth. the present study integrates different outcomes of several studies on this field with respect to the association between the four supported hypotheses across studies and the country coverage, the nature of analysis and the modeling choice. to tackle this issue, we applied meta-analysis techniques to a sample of 43 studies published between 1996 and 2013. we found that the relationship is more complex than it appears. out of the 43 papers from 1996 to 2013 used in our meta-analysis suggest the new lines of enquiry on the relationship in question (i.e. 9 studies supporting growth hypothesis, 9 studies supporting conservation hypothesis, 10 studies supporting neutrality hypothesis and 15 supporting the feedback hypothesis). the conservation hypothesis is widely associated to american and european countries. however, conservative and expansive policies are likely to have an adverse effect on the economic growth in asian and mena countries. conversely to expectations, the growth hypothesis is heavily associated to all studied countries and all considered econometric methods. additionally, there is a significant association between neutrality hypothesis and american, asian and european countries. these observed results change when moving from short-run to long-run analysis, i.e. while there is a stronger correlation between long-run analysis and the focal relationship, there is no association with short-run assessment. the feedback hypothesis is not supported when appealing a panel of american countries or when investigating the short-run dynamic between electricity consumption and gdp. the nexus between electricity consumption and economic growth: new insights from meta-analysis 631 the different findings may be mainly attributed to the nature of concerned countries and to the modeling choice and to the fact that energy policies in each country cannot be designed without considering various economic and environmental factors excluded in the majority of studies on the issue. in addition, the different results may be due to the use of bivariate models with missing variables, such as energy prices, rather than employing multivariate models in the previous studies. thus, the authors should focus more on the new approaches including additional variables and further studies with new findings can be conducted to find better paths. references abosedra, s., baghestani, h. (1989) new evidence on the causal relationship between us energy consumption and gross national product. journal of energy development, 14, 285-292. acaravcı, a., ozturk, i. (2010) electricity consumptiongrowth nexus: evidence from panel data for transition countries, energy economics, 32(3), 604-608. acaravci, a., ozturk, i. (2012) electricity consumption and economic growth nexus: a multivariate analysis for turkey, amfiteatru economic, 14(31), 246-257. akpan, g.e., akpan, u.f. (2012) electricity consumption, carbon emissions and economic growth in nigeria. international journal of energy economics and policy, 2(4), 292-306. al-iriani, m.a. (2006) energy–gdp relationship revisited: an example from gcc countries using panel causality. energy policy, 34(17), 3342-3350. al-mulali, u. (2011) oil consumption, co2 emission and economic growth in mena countries. energy policy, 36(10), 6165-6171. altinay, g., karagol, e. (2005) electricity consumption and economic growth: evidence for turkey. energy economics, 27, 849-956. ang, j.b. (2008) economic development, pollutant emissions and energy consumption in malaysia. journal of policy modeling 30, 271-278. apergis, n., payne j-e. (2009) co2 emissions, energy usage, and output in central america. energy policy 37, 3282–3286. apergis, n., payne, j.e. (2010) the emissions, energy consumption, and growth nexus: evidence from the common wealth of independent states. energy policy, 38(1), 650-655. arouri, m.h., ben youssef, a., m'henni, h, rault, c. (2012) energy consumption, economic growth and co2 emissions in middle east and north african countries. cesifo group munich, working paper series, 3726. asafu-adjaye, j. (2000) the relationship between energy consumption, energy prices and economic growth: time series evidence from asian developing countries, energy economics 22, 615-625. begg, c.b., berlin, j.a. (1988) publication bias: a problem in interpreting medical data. journal of the royal statistical society, series a, 151, 419–463. begg, c.b. (1994) publication bias. in h.m. cooper and l.v. hedges (eds), the handbook of research synthesis. new york: russell sage foundation. begg, c.b., mazumdar, m. (1994) operating characteristics of a rank correlation test for publication bias. biometrics 50, 1088-1101. belke, a., dobnik, f., dreger, c. (2011) energy consumption and economic growth: new insights into the cointegration relationship. energy economics 33(5), 782-789. borenstein, m., hedges, l., higgins, j., rothstein, h. (2005) comprehensive meta-analysis, version 2. englewood, nj: biostat. bouoiyour, j., selmi, r. (2013) the nexus between electricity consumption and economic growth in mena countries. energy studies review. energy studies review, 20(2), 25-41. chen, s.t., kuo, h.i., chen, c.c. (2007) the relationship between gdp and electricity consumption in 10 asian countries. energy policy 35(4), 2611-2621. chen, p-y., chen, s-t., chen, c-c. (2012). energy consumption and economic growth: new evidence from meta analysis. energy policy, 44(5), 245-255. chiou-wei, s.z., chen, ching-fu, zhu, z. (2008) economic growth and energy consumption revisited—evidence from linear and nonlinear granger causality. energy economics, 30(6), 3063-3076. coric, b., pugh, g. (2010) the effects of exchange rate variability on international trade: a metaregression analysis. applied economics, 42, 2631-2644. international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.621-635 632 dobnick, f. (2011) energy consumption and economic growth revisited: structural breaks and cross section dependence. ruhr economic papers n° 303. doucouliagos, c. (2005), publication bias in the economic freedom and economic growth literature. journal of economic surveys, 19(3), 367-387. erdal, g., erdal, h. and esengun, k. (2008) the causality between energy consumption and economic growth in turkey. energy policy, 36(10), 3838-3842. erol, u., yu, e.s.h. (1987) on the causal relationship between energy and income or industrialized countries. journal of energy development, 13, 113-122. georgantopoulos, a. (2012) electricity consumption and economic growth: analysis and forecasts using var/vec approach for greece with capital formation. international journal of energy economics and policy, 2(4), 263-278. ghali, k.h., el-sakka, m. (2004) energy use and output growth in canada: a multivariate cointegration analysis. energy economics 26, 225-238. ghosh, s. (2009) electricity supply, employment and real gdp in india: evidence from cointegration and granger-causality tests. energy policy, 37(8), 2926-2929. glasure, y.u., lee, a. (1997) cointegration, error correction and the relationship between gdp and energy: the case of south korea and singapore. resource and energy economics, 20, 17-25. glasure, y.u. (2002) energy and national income in korea: further evidence on the role of omitted variables. energy economics, 24, 355-365. halkos, g.e. and tzeremes, n. (2009) electricity generation and economic efficiency: panel data evidence from world and east asian countries. global economic review, 38(3), 251-263. hondroyiannis, g., lolos, s., papapetrou, e. (2002) energy consumption and economic growth: assessing the evidence from greece. energy economics, 24, 319-336. hunter, j.e., schmidt, f.l., jackson, g.b. (1982) cumulating research findings across studies. studying organizations: innovations in methodology, vol. 4, sage, beverly hill, ca. jarrell, s.b., stanley, t.d. (1990) a meta-analysis of the union-nonunion wage gap. industrial and labor relations review 44(1), 54-67. jobert, t. and karanfil, f. (2007) sectoral energy consumption by source and economic growth in turkey. energy policy, 35, 5447-5456. kalimeris, p., richardson, c., bithas, k. (2014) a meta-analysis investigation of the direction of the energy-gdp causal relationship: implications for the growth-degrowth dialogue. journal of cleaner production, 67, 1-13. karanfil, f. (2008) energy consumption and economic growth revisited: does the size of unrecorded economy matter? energy policy, 36(8), 3029-3035. kraft, j., kraft, a. (1978) on the relationship between energy and gnp. journal of energy and development 3, 401-403. lee, c-c., chang, c-p. (2005), structural breaks, energy consumption, and economic growth revisited: evidence from taiwan. energy economics 27, 857–72. lee, c.c. (2006) the causality relationship between energy consumption and gdp in g-11 countries revisited. energy policy 34, 1086-1093. lee, c.c., chang, c.p., chen, p.f. (2008) energy-income causality in oecd countries revisited: the key role of capital stock. energy economics 30, 2359-2373. mahadevan, r., asafu-adjaye, j. (2007) energy consumption, economic growth and prices: a reassessment using panel vecm for developed and developing countries. energy policy 35(4), 2481–2490. masih, a., masih, r. (1996) energy consumption and real income temporal causality, results for a multi-country study based on cointegration and error-correction techniques. energy economics 18, 165-183. masih, a. and masih, r. (1997) on temporal causal relationship between energy consumption, real income and prices; some new evidence from asian energy dependent nics based on a multivariate cointegration/vector error correction approach. journal of policy modeling 19(4), 417-440. mehrara, m. (2007) energy consumption and economic growth: the case of oil exporting countries. energy policy 35(5), 2939-2945. menegaki, a.n. (2014) on energy consumption and gdp studies; a meta-analysis of the last two decades. renewable and sustainable energy reviews, 29, 31-36. the nexus between electricity consumption and economic growth: new insights from meta-analysis 633 narayan, p-k., prasad, a. (2008) electricity consumption-real gdp causality nexus: evidence from a bootstrapped causality test for 30 oecd countries. energy policy, 36, 910-918. niu, s., ding, y. niu, y. li, y., luo, g. (2011) economic growth, energy conservation and emissions reduction: a comparative analysis based on panel data for 8 asian-pacific countries. energy policy, 39(4), 2121-2131. ozturk, i. (2010) a literature survey on energy consumption-growth nexus. energy policy 38, 340349. ozturk, i., aslan, a., kalyoncu, h. (2010) energy consumption and economic growth relationship: evidence from panel data for low and middle income countries. energy policy, 38(8), 44224428. ozturk, i., acaravcı, a. (2011) electricity consumption and real gdp causality nexus: evidence from ardl bounds testing approach for 11 mena countries. applied energy, 88(8), 28852892. paul, s., bhattacharya, r.n. (2004) causality between energy consumption and economic growth in india: a note on conflicting results. energy economics, 26(6), 977-983. payne, j-e. (2010) a survey of the electricity consumption and growth literature, applied energy 87, 723-73. pedroni, p. (2004) panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the ppp. econometric theory 20, 597-625. pesaran, m., shin, y. (1999) an autoregressive distributed lag modeling approach to cointegration analysis. s. strom, (ed) econometrics and economic theory in the 20th century, cambridge university. pugh, g., coric, b., haile, m-g. (2012) an introduction to meta-regression analysis (mra): using the example of trade effects of exchange rate variability. chapter 20 of the edited book: macroeconomics and beyond in honour of wim meeusen. shahbaz, m., tang, c.f., shahbir, m.s. (2011) electricity consumption and economic growth nexus in portugal using cointegration and causality approaches. energy policy, 39(6), 3529-3526. shahbaz, m., feridun, m. (2012) electricity consumption and economic growth empirical evidence from pakistan. quality & quantity, 46(5), 1583-1599. sims, c.a. (1972) money, income, and causality. american economic review 62(4), 540-552. solarin, s.a. (2011) electricity consumption and economic growth: trivariate investigation in botswana with capital formation. international journal of energy economics and policy, 1(2), 32-46. soytas, u., sari, r. (2003) energy consumption and gdp: causality relationship in g-7 countries and emerging markets. energy economics 25, 33-37. souissi, m., khlif, h. (2012) meta-analytic review of disclosure level and cost of equity capital. international journal of accounting and information management 20, 49-62. stanley, t. (2005) beyond publication bias. journal of economic survey, 19(3), 309-345. sterne, j.a.c., egger, m., davey, s.g. (2001) investigating and dealing with publication and other biases. in m. egger, g. davey smith and d. g. altman (eds), systematic reviews in health care: meta-analysis in context, 2nd edn. london: bmj books. tang, c.f. (2008) a re-examination of the relationship between electricity consumption and economic growth in malaysia. energy policy 36, 3077–85. wolde-rufael, y. (2004) disaggregated industrial energy consumption and gdp: the case of shanghai. energy economics 26, 69-75. wolde-rufael, y. (2005) energy demand and economic growth: the african experience. journal of policy modeling 27(8), 891-903. wolde-rufael, y. (2006) electricity consumption and economic growth: a time series experience for 17 african countries. energy policy 34, 1106-1114. yuan, j., kang, j., zhao, c., hu, z. (2008) energy consumption and economic growth: evidence from china at both aggregated and disaggregated levels. energy economics 30(6), 3077-3094. yu, e., choi, j. (1985) the causal relationship between energy and gnp: an international comparison. journal of energy and development 10, 249-272. zamani, m. (2007) energy consumption and economic activities in iran. energy economics 29(6), 1135-1140. international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.621-635 634 appendices (the meta data set) appendix a1. conservation hypothesis studies countries data analysis methods amc asc euc menac panel ts sr lr ja co gc jm masih and masih (1996) 0 1 0 0 0 1 (1) 0 1 0 1 0 0 masih and masih (1997) 0 1 0 0 0 1 (2) 0 1 0 1 0 0 glasure and lee (1997) 0 1 0 0 0 1 (3) 0 0 1 0 0 1 chiou-wei et al. (2008) 1 1 0 0 0 1 (4) 0 1 0 0 1 0 narayan and parasad (2008) 0 0 1 0 0 1 (5) 0 0 1 0 0 1 tang (2008) 0 1 0 1 0 1 0 0 1 0 0 1 niu et al. (2011) 0 0 1 0 1 0 0 0 1 0 0 1 arouri et al. (2012) 0 0 0 1 1 0 0 0 1 0 0 1 bouoiyour and selmi (2013) 0 0 0 1 0 1 (6) 0 0 1 0 0 1 notes : amc : american countries ; asc : asian countries ; euc : european countries ; menac : mena countries ; ts : time series; sr : short-run analysis ; lr : long-run analysis ; ja : joint analysis (i.e. sr and lr) ; co : cointegration ; gc : granger causality ; jm : joint methods (i.e. co and gc) ; (1) : hong kong, malaysia, indonesia ; (5) : greece ; (6) : morocco, oman and turkey. appendix a2. growth hypothesis studies countries data analysis methods amc asc euc menac panel ts sr lr ja co gc jm masih and masih (1996) 0 1 0 0 0 1 (1) 0 1 0 1 0 0 wolde-rufael (2005) 0 0 0 1 0 1 1 0 0 0 1 0 al-iriani (2006) 0 0 0 1 1 0 1 0 0 0 1 0 zamani (2007) 0 0 0 1 0 1 0 0 1 0 0 1 ang (2008) 0 1 0 0 0 1 0 1 0 1 0 0 narayan and prasad (2008) 0 0 1 0 0 1 (2) 0 0 1 0 0 1 ghosh (2009) 0 1 0 0 0 1 0 0 1 0 0 1 niu et al. (2011) 0 1 0 0 1 (3) 0 0 0 1 0 0 1 bouoiyour and selmi (2013) 0 0 0 1 0 1 (4) 0 0 1 0 0 1 notes : amc : american countries ; asc : asian countries ; euc : european countries ; menac : mena countries ; ts : time series; sr : short-run analysis ; lr : long-run analysis ; ja : joint analysis (i.e. sr and lr) ; co : cointegration ; gc : granger causality ; jm : joint methods (i.e. co and gc) ; (1) : indonesia; (2) : netherlands ; (3) : developing countries ; (4) : algeria, egypt, saudi arabia, tunisia, uae. appendix a3. neutrality hypothesis studies countries data analysis methods amc asc euc menac panel ts sr lr ja co gc jm masih and masih (1996) 0 1 0 0 0 1 (1) 0 1 0 1 0 0 glasure and lee (1997) 0 1 0 0 0 1 (2) 0 0 1 0 0 1 soytas and sari (2003) 1 1 1 0 0 1 0 0 1 0 0 1 altinay and karagol (2005) 0 0 0 1 0 1 1 0 0 0 1 0 jobert and karanfil (2007) 0 0 0 1 0 1 1 0 0 0 1 0 chiou-wei et al. (2008) 1 1 0 0 0 1 (3) 0 1 0 0 1 0 karanfil (2008) 0 0 0 1 0 1 1 0 0 0 1 0 lee and chang (2005) 0 1 0 0 1 0 1 0 0 1 0 0 narayan and parasad (2008) 1 0 1 0 0 1 (4) 0 0 1 0 0 1 bouoiyour and selmi (2013) 0 0 0 1 1 (5) 1 (6) 0 0 1 0 0 1 notes : amc : american countries ; asc : asian countries ; euc : european countries ; menac : mena countries ; ts : time series; sr : short-run analysis ; lr : long-run analysis ; ja : joint analysis (i.e. sr and lr) ; co : cointegration ; gc : granger causality ; jm : joint methods (i.e. co and gc) ; (1) : malysia, philippines and singapore ; (2) : south korea ; (3) : usa, thailand and south korea ; (4) : canada, mexico and usa ; (5) : energy exporters ; (6) : iran and sudan. the nexus between electricity consumption and economic growth: new insights from meta-analysis 635 appendix a4. feedback hypothesis studies countries data analysis methods amc asc euc menac panel ts sr lr ja co gc jm masih and masih (1997) 0 1 0 0 0 1 0 1 0 1 0 0 asafu-adjaye (2000) 0 1 0 0 0 1 1 0 0 0 1 0 glasure (2002) 0 1 0 0 0 1 0 0 1 1 0 0 hondrioyiannis et al. (2002) 0 0 1 0 0 1 0 1 0 1 0 0 ghali and el-sakka (2004) 1 0 0 0 0 1 0 0 1 0 0 1 paul and bhattacharya (2004) 0 1 0 0 0 1 0 0 1 0 0 1 lee (2006) 1 0 1 0 0 1 1 0 0 0 1 0 mohadevan and asafuadjaye (2007) 0 0 0 1 1 0 0 0 1 0 0 1 lee et al. (2008) 0 0 1 0 1 0 0 1 0 1 0 0 erdal et al. (2008) 0 0 0 1 0 1 0 0 1 0 0 1 al-mulali (2011) 0 0 0 1 1 0 0 1 0 0 0 1 belke et al. (2011) 0 0 1 0 1 0 0 0 1 0 0 1 dobnick (2011) 0 0 1 0 1 0 0 0 1 0 0 1 ozturk and acaravci (2011) 0 1 0 1 1 0 0 0 1 0 0 1 bouoiyour and selmi (2013) 0 0 0 1 0 1(1) 0 0 1 0 0 1 notes : amc : american countries ; asc : asian countries ; euc : european countries ; menac : mena countries ; ts : time series; sr : short-run analysis ; lr : long-run analysis ; ja : joint analysis (i.e. sr and lr) ; co : cointegration ; gc : granger causality ; jm : joint methods (i.e. co and gc) ; (1) : algeria, egypt, saudi arabia, tunisia and uae. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 5 • 2020 679 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(5), 679-686. analysis of the level of implementation of programs for the efficient use of energy and unconventional sources: case study colombia marlen fonseca vigoya1, josé garcía mendoza2, sofia orjuela abril2* 1grupo de investigación gidse, departamento de ciencias administrativas, universidad francisco de paula santander, cúcuta 540001, (norte de santander) colombia, 2grupo de investigación gedes, departamento de ciencias administrativas, universidad francisco de paula santander, cúcuta 540001, (norte de santander) colombia. *email: sofiaorjuela@ufps.edu.co received: 06 april 2020 accepted: 02 august 2020 doi: https://doi.org/10.32479/ijeep.9713 abstract at the first extraordinary meeting of the forum of ministers of the environment of latin america and the caribbean, johannesburg, august 2002. an initiative for sustainable development in latin america and the caribbean was presented. this proposes that the countries of the region should show in their energy distribution minimum participation of 10% of renewable energy sources in the total primary energy supply (otep). the mechanism of action of this initiative is not based on penalizing countries that their natural conditions are not favorable for energy sustainability, but on promoting greater participation of renewable energy sources. through the analysis of the country’s energy demand and energy sources and according to the initiative, the colombian government, through its entities, organizes programs to improve its energy efficiency and the participation of renewable energy sources and technologies, not conventional. this paper shows the statistics of energy distribution and energy sources in colombia. based on this information, we seek to identify the deficient sectors with their problems to implement strategies at the national level that allows them to meet the proposed goals. keywords: efficiency, energy, renewable sources, sustainability, total primary energy supply jel classifications: l78, l90, o31, q20 1. introduction today it is a fact the importance of transforming the mechanisms of obtaining electric energy into renewable energy (cronin et al., 2018) to reduce the climate impact in a low-carbon (solaun and cerdá, 2019) future so that by 2050 renewable energy will account for 65% of the total consumption of energy (irena, 2018). the use of renewable energies varies differently in each country and does not depend directly on their relative development (bildirici, 2016), but rather on the availability of non-renewable energy resources (alvarado et al., 2019). in latin america, the share of renewable energy is 25% (nu. cepal; caf;, 2013) relatively higher than in other areas of the world thanks to the high participation of hydropower and biofuel (van der zwaan et al., 2016). therefore, to establish the contribution of renewable sources in the total primary energy supply (otep in spanish), it was necessary to homogenize criteria common to the countries of latin america and the caribbean, removing the fraction of energy from forest resources that give to the deforestation, this is the one whose extraction rate is higher than its regeneration rate (cepal and gtz, 2003). when it has to deal with renewable energy, it refers to the natural resources which restore naturally reestablished, and their consumption does not exceed the speed with which they can be restored naturally (harjanne and korhonen, 2019). and when it comes to sustainability, it is a little more complex this journal is licensed under a creative commons attribution 4.0 international license vigoya, et al.: analysis of the level of implementation of programs for the efficient use of energy and unconventional sources: case study colombia international journal of energy economics and policy | vol 10 • issue 5 • 2020680 since economic, political, social, and environmental factors are involved (ashbai et al., 2019). this can be contextualized in three central dimensions: energy security, energy equity, and environmental sustainability of energy systems; these concepts constitute a “trilemma” (wec and wyman, 2019). in summary, sustainable energy is one that has efficient management capable of maintaining current and future national demand that is affordable for the population, and that mitigates the environmental impact developed from renewable and low-carbon energies (wec, 2011). accordingly, the position adopted by the economic commission for latin america and the caribbean (cepal, in spanish) identifies renewable energy as a property of the source and sustainability as the property of the way it is used (cepal and gtz, 2004). in latin america and the caribbean (lac), they have as common energy sources in their energy supply fossil sources such as oil and natural gas with a reserve that exceeds 35 and 40 years, respectively (olade, 2019). hydropower, biomass, firewood, cane products, and geothermal energy. it should be clarified that part of the wood energy is not considered sustainable. figure 1 shows the percentage of energy supply for some countries in the region. this shows the energy contribution they have from non-renewable energy sources for the year 2002, in which, for some countries, this contribution is almost all of the energy supply. this non-renewable energy is made up of oil, natural gas, coal, nuclear energy, firewood (not sustainable), among other non-renewable energies. in figure 2, shows in general, the latin american and caribbean region already fulfilled the goals outlined in the regional conference for latin america and the caribbean on renewable energies (brasilia, october 2003) in which the use of 10% of renewable energy from the total energy consumption (cepal and gtz, 2003). the renewable energies found in the region are hydro energy, industrial and residential firewood, agricultural firewood, charcoal, cane products, geothermal energy, among others. the energy obtained by the dams or reservoirs called hydropower makes an important contribution to the otep in the lac region and is considered a form of energy production that is part of nonrenewable energy. however, this point is under consideration, even though conceptually it is a renewable resource, it may become an unsustainable resource due to its environmental and social impacts (cepal and gtz, 2004) (wec, 2015). despite this, hydropower is still less harmful than others (calderón et al., 2016). colombia is the third country with the largest installed hydroelectric capacity in south america in 2018 (pupo-roncallo et al., 2020) and was ranked eighth in the world economic forum, the first noneuropean country in the top 10 (world economic forum, 2017). the energy resources condemned to the different productive sectors and the way this influences energy demand are topics on which the colombian government works continuously (upme, 2018) without neglecting the quality of life of its citizens with respect to climate change and the decrease in the latter is a result of the work to improve energy efficiencies in the consumption sectors and the implementation of new technologies for the use and production of renewable energy sources in the country’s energy market (prias, 2010). colombia is in the 49th position worldwide, with a bca balance degree according to the trilemma score of 69.3 (wec and wyman, 2019), and this has been progressing since it got down to work on the issues of energy efficiency and renewable energy. at the latin american level, progress has been uneven and slow. however, having an appropriate legal framework, laws, programs, and projects that promote the improvement of energy efficiency makes an important contribution to achieving the objectives of the region’s agenda (cepal, 2017). these programs are headed by the ministry of mines, which through law 697 of 2001 and decree 3683 of 2003 (gobierno nacional, 2001) (gobierno nacional, 2003). this was entrusted with the responsibility for the programs for the rational and efficient use of energy (ure in spanish) and create the rational and efficient use of energy and other 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% p ar ag ua y h ai ti e l s al va do r n ic ar ag ua u ru gu ay b ra si l c ol om bi a c hi le a rg en tin a m ex ic o ja m ai ca t rin id a & t ab ag o region's energy supply figure 1: non-renewable energy supply of latin america and the caribbean year 2002 source of data: prepared by the authors based on data from (cepal and gtz, 2003) non-renewable energy 71% renewable energy 29% otep of the region figure 2: total supply of primary energy (otep in spanish) in latin america and the caribbean in 2002 source of data: prepared by the authors based on data from (cepal and gtz, 2003) vigoya, et al.: analysis of the level of implementation of programs for the efficient use of energy and unconventional sources: case study colombia international journal of energy economics and policy | vol 10 • issue 5 • 2020 681 unconventional forms of energy program (proure in spanish). this is just the beginning of the joint work of the government and the ministry of mines and energies that are constantly working on the development of new mechanisms, including the financial support fund for the energization of non-interconnected areas (fazni in spanish) (gobierno nacional, 2008). that financially supports projects that seek to connect non-interconnected areas (zni in spanish), giving special attention to projects that promote the efficient use of energy and non-conventional energies. 2. panorama of energy in colombia colombia is a country with a great variety of energy resources, the potential of renewable energy sources is high, and it practically owns resources from all renewable energy sources, although the largest is from electricity generation in the national interconnected system (sin in spanish) is found in hydropower. proure through the energy mining planning unit (upme) identifies energy potentials and the inclusion of unconventional energies in the country’s energy market, as well as the definition of energysaving goals. 2.1. internal power supply in figure 3, the gross domestic supply (oib in spanish) of primary energy sources for the year 2017 was 1,878,448 tj, in which petroleum (pt) had the largest share with 801,661 tj, followed by natural gas (gn) with 403,675 tj, coal ore (cm) 225,031 tj, hydropower (he) 221,162 tj, firewood (le) 105,566 tj, bagasse (bz) 96,077 tj, other renewables (or) 24,808 tj and recovery/ waste (rc) 467 tj (table 1). the gross domestic supply of secondary energy shown in figure 4, for the year 2017 was 861,164 tj with greater participation of diesel oil (do) with 283,232 tj, motor gasoline (gm) 226,100 tj, electrical energy sin (ee sin) 212,472 tj, kerosene, and table 1: name abbreviations of primary and secondary energetics energetic abbreviation bagasse bz mineral carbon cm natural gas gn hydroenergy he firewood le petroleum pt recovery/waste rc other renewables or fuel alcohol ac biodiesel bi coal firewood cl coke cq diesel oil do auto&cogenereation aut&cog electric power of interconnected energy system (sin in spanish) ee sin fuel oil fo industrial gas for high oven gi petroleum lquid gas gl/glp engine gasoline gm kerosene and jet fuel kj source of data: prepared by the authors based on data from (upme, 2017) jet fuel (kj) 50,933 tj, liquefied petroleum gas (gl) 42,350 tj, fuel oil (fo) 32,571 tj, auto-generation, and cogeneration (aut cog) 11,950 tj, coke (cq) 1,261 tj, charcoal (cl) 295 tj, fuel alcohol (ac) 0 tj, and biodiesel (bi) 0 tj. figure 5 shows the total supply of primary energy in colombia during the last 8 years. in the total supply, the production of mineral pt 43% gn 21% cm 12% le 6% bz 5% rc 0% or 1% he 12% other 13% oib of primary energy figure 3: gross domestic supply (oib in spanish) of primary energy sources for the year 2017 source of data: prepared by the authors based on data from (upme, 2017) do 33% gm 26% ee sin 25% kj 6% gl 5% fo 4% aut cog 1% cq 0% cl 0% ac 0% bi 0% other 0% oib of secondary energy figure 4: gross domestic supply (oib in spanish) of secondary energy sources for the year 2017 source of data: prepared by the authors based on data from (upme, 2017) 0.e+00 1.e+06 2.e+06 3.e+06 4.e+06 5.e+06 6.e+06 7.e+06 2010 2011 2012 2013 2014 2015 2016 2017 total primary energy supply (tj) pt gn cm le bz he rc or figure 5: gross domestic supply (oib in spanish) of secondary energy sources for the year 2017 source of data: prepared by the authors based on data from (upme, 2017) vigoya, et al.: analysis of the level of implementation of programs for the efficient use of energy and unconventional sources: case study colombia international journal of energy economics and policy | vol 10 • issue 5 • 2020682 coal and oil predominates with a participation of 32.6% and 44.7% in 2017. oil production has been showing a slight decrease in the last 2 years due to different factors such as the lack of investment in equipment and technical problems in some fields. on the other hand, the production of mineral coal remains at a more or less constant rate, although in the last 5 years it has increased by 5%. 2.2. final energy consumption the energy in its different forms is a fundamental service for the good development of the industry and the inhabitants of the region. colombia is a country with a great diversity of energy products that supply the internal demand. in 2017 the final energy consumption 1,255,123 tj. in figure 6, it can be seen that much of the final energy consumption of primary energy sources belong to natural gas with 206,777 tj, followed by firewood with 57,824 tj, mineral coal with 87,237 tj, and bagasse with 57,854 tj. to a lesser extent, oil with 406 tj, recovery, or waste with 467 tj. hydro energy, despite having considerable participation in the gross domestic supply, is not shown in this graph since it is sent to the national interconnected electrical energy system (ee sin in spanish). in 2017, the final energy consumption of secondary energy sources shown in figure 7, was 798,545 tj, with strong participation of diesel oil with 247,319 tj, followed by motor gasoline 231,952 tj and the ee sin with 212,454 tj. to a lesser extent are kerosene and jet fuel with 48,979 tj, liquefied petroleum gas with 31,466 tj, fuel oil 13,048 tj, auto/cogeneration 11,950 tj, coke 1,261 tj and charcoal 295 tj. however, in order to have a clear vision of the country’s final energy consumption, it is necessary to realize how it is distributed among the different consumption sectors of the country. it can be seen in figure 8, the sector with the highest consumption is the transport sector with 507,519 tj, followed by the industrial sector with 299,045 tj, the residential sector 253,603 tj. the commercial sector has 75,562 tj of consumption, and the agricultural, mining, construction, unidentified and non-energy sectors have a total consumption of 119,667 tj. it can be seen that the transport sector has the highest energy consumption, followed by the industrial and residential sectors. the different organizations that promote the efficient use of energy and the use of renewable energy sources must know what type of energy each sector consumes for their research and development of the different mechanisms to achieve the goals in terms of energy efficiencies. 3. program for rational use of energy and unconventional sources in colombia the proure program seeks to contribute to increasing energy efficiency, and for this, it uses various strategies that are not only framed in reduction policies and the transformation of energy sources and one hundred percent renewable energy technologies. the rational and efficient use of energy is a concept of productive chain, dynamic and permanent change in accordance with the approaches of sustainable development relating the environmental impacts and the increase in productivity with the efficient gn 45% le 23% cm 19% bz 13% rc 0% pt 0% he 0% or 0% final energy consumption of primary energy sources figure 6: final energy consumption of primary energy sources for the year 2017 source of data: prepared by the authors based on data from (upme, 2017) do 31% gm 29% kj 6% gl 4% fo 2% aut cog 1% cq 0% cl 0% ac 0% bi 0% ee sin 27% final energy consumption of secondary energy sources figure 7: final energy consumption of primary energy sources for the year 2017 source of data: prepared by the authors based on data from (upme, 2017) transport 40% industrial 24% residential 20% others 10% commercial 6% final energy consumption by consumption sectors figure 8: final energy consumption by consumption sectors source of data: prepared by the authors based on data from (upme, 2017) vigoya, et al.: analysis of the level of implementation of programs for the efficient use of energy and unconventional sources: case study colombia international journal of energy economics and policy | vol 10 • issue 5 • 2020 683 management of resources in production processes. accordingly, proure implements mechanisms of the greater impact that guarantee the energy supply without overflowing with the excessive use of non-renewable energy. according to the investigations made, colombia would need to invest close to us $ 730 million in equipment and technologies that allow a 10% reduction in energy consumption, that is, 6300 gwh, if it cannot meet this goal, the country would be forced to make a greater investment to supply future energy demand (prias, 2010). in accordance with decree 3683 (gobierno nacional, 2003) in which law 676 of 2001 regulates proure: • it has the participation of public and private agents from the energy sectors, and it is allowed to enter into administrative agreements with other entities. • promote sustainable strategies that allow the strengthening of executing entities for the rational and efficient use of energy • promote the creation of funds that allow the development of programs and activities that meet the stated objectives • develop tax, economic, and recognition incentives with entities that comply with regulations. among other activities that fulfill the objectives of the program. some of the funds created are: • fazni, financial support fund for the energization of noninterconnected areas. • pronoe, electrical network normalization program • foes, social energy fund. • faer, financial support fund for the energization of interconnected rural areas. • fnr, national royalties fund. • fenoge, non-conventional energy fund, and efficient energy management. proure, from the moment it was created, had in mind the need to create schemes that study energy production in the country and give measurable results of the impact, energy sustainability, and clean energy production. one of its indicators will be energy intensity. proure for the current year has a better vision of the prospects of the different energy, environmental, and productive sectors with verification of social impact, quality of life, and productivity (minminas, upme, 2016). one of the technological tools that today are the result of proure’s approaches since its inception is the colombian energy balance (beco in spanish) that today contributes to the country’s energy analysis. 3.1. national panorama in energy efficiency for the year 2015, the energy wasted in the country amounts to estimated costs of $ 4.7 billion/year. that is, the energy losses of the energy matrix were 52%, and the portion of useful energy was consequently 48%. that is why proure considers that colombia has significant savings potential by improving energy efficiency. in figure 9, it can be seen that in one of the sectors with the highest energy losses corresponds to the transport sector with 65%, followed by the industrial sector with 16% and the residential sector with 15%. therefore, it is of utmost importance to act on the energy efficiency of each sector. for this, it is necessary to know specifically the energy consumption discriminated by energy classes by sector. in this way, proure will present solutions for improving energy efficiency. in figure 10, it is seen in the transport sector that its energy consumption is mostly diesel oil (do) with 206,679 tj, followed by motor gasoline (gm) with 229,651 tj, and in a lower percentage with 20,851 tj. the transport sector is the sector with the highest consumption of energy and this due to the 0% 10% 20% 30% 40% 50% 60% 70% 0 100000 200000 300000 400000 500000 t ra ns po rt in du st ria l r es id en tia l c om m er ci al t j loss and energy consumption ratio losses consumption participation in losses figure 9: loss and energy consumption ratio source of data: prepared by the authors based on data from (minminas, upme, 2016) do 41% gm 41% kj 10% gn 6% fo 1% ee sin 0% final consumption in the transport sector figure 10: loss and energy consumption ratio source of data: prepared by the authors based on data from (upme, 2017) vigoya, et al.: analysis of the level of implementation of programs for the efficient use of energy and unconventional sources: case study colombia international journal of energy economics and policy | vol 10 • issue 5 • 2020684 geography and demography of the country. this sector presents particularities that make its energy consumption high, such as the distance between the ports and the main cities. in 2017, the final consumption of the transport sector was 507,518 tj. upme divides the transport sector into five subsectors. air transport consumes 47,977 tj or 9% of the energy of the sector. likewise, maritime transport consumes 10,065 tj or 2%, river transport 438 tj or 0.09%, rail transport 348 tj or 0.07%, and finally, road transport consumes 448,691 or 88% of the total energy in the sector. the latter is the one with the highest consumption. being of vital importance for the solutions that can be taken against the different consumption sectors of the country and as a sample of the transport sector, it is divided in detail, resulting in the participation of the different segments of road transport that present significant consumption in front of others. interurban passenger transport represents 27% and private urban passenger transport 21%, and to a lesser extent, public passenger transport represents 12% of the energy consumption of the road transport division (upme, 2017). according to the analysis of the transport sector, proure proposes some guidelines and goals that help reduce the consumption of liquid fuels and contribute to the reduction of polluting gases. as some are the beginning of mass transport projects in the main cities of the country, the change of cargo vehicles and public transport to new vehicles that meet international standards and the conversion of gasoline vehicles to a compressed natural gas system. in addition to resolution 186 of 2012 (mads-mme) that regulates the tax incentives of the exclusion of value-added tax (vat in spanish) and deduction of liquid income for clean technologies. 4. prospects and projections following the analysis of the transport sector as a sample of all the actions that proure accompanied by the ministry of mining and energy and its other estates, in the different productive sectors of the country is presented as a quantitative result than that in the transport sector in the year 2017 the reduction in fuel consumption is approximately 994.63 tj/year and as an externality or desired side effect, the reduction in greenhouse gas emissions is 72,932.23 ton co2/year (upme, 2018). in figure 11, the low scenario is assumed for the maintenance and even the decrease in consumption of vehicles that use natural gas for vehicles, and the high and medium scenario is expected due to the increase in consumption caused by the entry of heavyduty transport vehicles running on vehicular natural gas and in conjunction with the entry of the pacific regasification plant by 2024 (upme, 2019). in accordance with this, in figure 12, the energy mining planning unit (upme in spanish) foresees a behavior of the demand for the main fuels. gasoline will increase the growth rate despite the fact that in recent years it had a reduction, for diesel that maintains its growth rate, although with gradual reductions and for vehicular natural gas, its growth rate is reactivated as in previous decades (upme, 2010). on the other hand, in the indicative action plan for energy management of proure presented for the periods 2017-2022, it was estimated that the net energy savings in the transport sector in the period would be 424,408 tj (upme, 2018). to achieve these goals, proure proposes time-bound measures for the transport sector; some of the measures include: • that by 2023, an additional 10% must be added to the fleet of inter-municipal public transport passenger vehicles, that is, 6,071 vehicles in total, compared to the base scenario of 3,602 vehicles running on ngv. on the other hand, 24,216 must enter vehicles running on diesel oil compared to 24,182 vehicles planned in a base scenario, and 570 vehicles must enter hybrid vehicles. also, in this approach, 3,173 gasoline vehicles are considered to be out of circulation. with these measures, proure intends to generate an impact not only in consumption but also in emissions, ceasing to generate 1,304,616 mton of co2. 30 40 50 60 70 80 90 100 110 120 130 20 06 20 08 20 10 20 12 20 14 20 16 20 18 20 20 20 22 20 24 20 26 20 28 20 30 ngv demand projection historical medium scenario high scenario low scenario figure 11: projection of the demand for vehicular natural gas source of data: prepared by the authors based on data from (upme, 2019) 0 50 100 150 200 250 20 08 20 10 20 12 20 14 20 16 20 18 20 20 20 22 20 24 20 26 20 28 20 30 diesel oil and engine gasoline demand projection diesel oil low scenario diesel oil medium scenario diesel oil high scenario engine gasoline low scenario engine gasoline medium scenario engine gasoline high scenario figure 12: projection of the demand for diesel oil and motor gasoline source of data: prepared by the authors based on data from (upme, 2010) vigoya, et al.: analysis of the level of implementation of programs for the efficient use of energy and unconventional sources: case study colombia international journal of energy economics and policy | vol 10 • issue 5 • 2020 685 • taking into account that the fleet of motorcycles, automobiles, campers, and trucks make up 91% of the total. proure proposes the entry of 2,082 electric vehicles by 2023, which would mean 0.015% of the automotive fleet. with this measure, the program aims to save net energy by 2,073.6 tj and stop generating 154,164.4 co2. it is also proposed that by 2025, 1.64% of the total national fleet of private passenger vehicles should enter using liquefied petroleum gas as substitutes for gasoline and diesel oil. and in a tractor-trailer or cargo vehicle, 0.010% of the total national fleet must enter as substitutes for gasoline and diesel oil for liquefied natural gas. in general, the measures implemented by proure would generate a 1.65% reduction in energy consumption in the transport sector. 5. conclusions colombia has a variety of natural resources that allow it to supply its own energy demand; it also has water resources with high potential for the use of hydropower; it also has high potential natural resources to convert them into non-renewable energy. colombia must overcome the barrier of conventional energies and give greater participation to renewable energy sources, taking advantage of a large scale of the renewable energy potentials that it has in its territory and not only hydropower. it is necessary that the strategies proposed by proure continue and are carried out fully so that the projections are reflected in the real figures, in addition to the fact that these measures of change must be increasingly encouraged by promoting new strategies in what converges to technological change in the automotive fleet with vehicles that comply with global energy efficiency regulations, and greater inclusion of hybrid and electric vehicles in public passenger transport systems, as well as the better organization in freight transport logistics to reduce trips empty and the promotion of cargo vehicles that use liquefied natural gas or liquefied petroleum gas. the necessary measures are being taken to comply with the goals proposed at the latin american level. however, the proure program has been in operation for 17 years, and the results of its execution have only just begun to be implemented, so the proposed results may be seen over the course of the following years. colombia needs not only changes in its incentive policies for the use of renewable energy sources, but it also requires a greater economic effort in investing in non-conventional renewable energy projects. in the course of proure’s operation in colombia, it has been possible to create a framework of policies starting from 697 of 2001, the creation of the intersectoral commission for the rational and efficient use of energy and unconventional sources (ciure in spanish). an indicative action plan is created, adopted by the ministry of mines and energy. the characterization of the country’s energy matrix and the identification of the four priority sectors were achieved: transportation, industry, residential, and tertiary. and the creation of six programs that represent technical and economic support for the best in the country’s energy efficiency, in addition to incentives such as tax exclusion tax benefits and liquid income deduction for investment in efficient systems and equipment in the industry and the transport. the country’s savings potential calculated by the upme only for the transport and industrial sector and evaluating only some savings actions in particular for each one is 3,977 bpd and 13,471 tj/year, respectively. references alvarado, r., ponce, p., alvarado, r., ponce, k., huachizaca, v., toledo, e. (2019), sustainable and non-sustainable energy and output in latin america: a cointegration and causality approach with panel data. energy strategy reviews, 26, 1-10. ashbai, a., gang, f., iqbal, w., abass, q., mohsin, m., iram, r. (2019), novel approach of principal component analysis method to assess the national energy performance via energy trilemma index. energy reports, 5, 704-713. bildirici, m. (2016), the relationship between hydropower energy consumption and economic growth. procedia economics and finance, 38, 264-270. calderón, s., álvarez, a., loboguerrero, a., arango, s., clavin, k., kober, t., daenzer, k., fisher-vanden, k. (2016), achieving co2 reductions in colombia: effects of carbon taxes and abatement targets. energy economics, 56, 575-586. cepal, gtz. (2003), sostenibilidad energética en america latina y el caribe: el aporte de las fuentes renovables. brasilia: cepal. available from: https://www.repositorio.cepal.org/ handle/11362/2764. [last accessed on 2020 mar 25]. cepal, gtz. (2004), fuentes renovables de energía en américa latina y el caribe: situación y propuestas de politicas. santiago: cepal. available from: https://www.cepal.org/es/publicaciones/31904fuentes-renovables-energia-america-latina-caribe-situacionpropuestas-politicas. [last accessed on 2020 mar 26]. cepal. (2017), avances en materia de energías sostenibles en américa latina y el caribe: resultados del marco de seguimiento mundial, informe de 2017. santiago de chile: santiago cepal. available from: https://www.repositorio.cepal.org/handle/11362/42552. [last accessed on 2020 mar 26]. cronin, j., anandarajah, g., dessens, o. (2018), climate change impacts on the energy system: a review of trends and gaps. climatic change, 151, 79-93. gobierno nacional. (2001), ley 697. mediante la cual se fomenta el uso racional y eficiente de la energía, se promueve la utilización de energías alternativas y se dictan otras disposiciones. bogotá, colombia: congreso de la república. available from: https://www. funcionpublica.gov.co/eva/gestornormativo/norma.php?i=4449. [last accessed on 2020 mar 26]. gobierno nacional. (2003), decreto 3683 de 2003, por el cual se reglamenta la ley 697 de 2001 y se crea una comisión intersectorial. bogotá, colombia: gobierno nacional. available from: https://www.funcionpublica.gov.co/eva/gestornormativo/ norma.php?i=11032. [last accessed on 2020 mar 26]. gobierno nacional. (2008), decreto 1124 de 200, por el cual se reglamenta el fondo de apoyo financiero para la energización de las zonas no interconectadas-fazn. bogotá, colombia: vigoya, et al.: analysis of the level of implementation of programs for the efficient use of energy and unconventional sources: case study colombia international journal of energy economics and policy | vol 10 • issue 5 • 2020686 gobierno nacional. available from: https://www.minenergia.gov. co/normatividad?idnorma=21603. [last accessed on 2020 mar 26]. harjanne, a., korhonen, j. (2019), abandoning the concept of renewable energy. energy policy, 127, 330-340. irena. (2018), global energy transformation: a roadmap to 2050. abu dhabi: irena. p1-76. available from: https://www.irena.org/ publications/2018/apr/global-energy-transition-a-roadmap-to-2050. [last accessed on 2020 mar 26]. minminas, upme. (2016), plan de acción indicativo de eficiencia energética 2017-2022. bogotá, colombia: minminas. available from: https://www.1.upme.gov.co/paginas/plan-de-acci%c3%b3nindicativo-de-eficiencia-energ%c3%a9tica-pai-proure-2017---2022. aspx. [last accessed on 2020 mar 27]. nu. cepal, caf. (2013), energía: una visión sobre los retos y oportunidades en américa latina y el caribe. egypt: cepal, caf. available from: https://www.cepal.org/es/publicaciones/1505energia-vision-retos-oportunidades-america-latina-caribe. [last accessed on 2020 mar 28]. olade. (2019), enerlac. enerlac, 3(2), 12. available from: http://www. biblioteca.olade.org/opac-tmpl/documentos/hm000752.pdf. prias, o. (2010), programa de uso racional y eficiente de energía y fuentes no convencionales (proure). bogotá dc: ministerio de minas y energía. pupo-roncallo, o., campillo, j., ingham, d., hughes, k., pourkashanian, m. (2020), renewable energy production and demand dataset for the energy system of colombia. data in brief, 28, 105084. solaun, k., cerdá, e. (2019), climate change impacts on renewable energy generation. a review of quantitative projections. renewable and sustainable energy reviews, 116, 109415. upme. (2010), proyección de la demanada de combustibles líquidos y gnv en colombia. bogotá, colombia: upme. available from: http://www.sipg.gov.co/sipg/documentos/proyecciones/2010/ proyecc_dem_do_gm_gnv_sept_2010.pdf. [last accessed on 2020 mar 29]. upme. (2017), beco. available from: https://www.1.upme.gov.co/ informacioncifras/paginas/becoconsulta.aspx. [last accessed on 2020 mar 30]. upme. (2018), informe de gestión 2017-2018. bogotá, colombia: upme. available from: http://www.1.upme.gov.co/informesgestion/informe_ de_gestion_2018_19092018.pdf. [last accessed on 2020 mar 26]. upme. (2019), proyección de gas natural en colombia 2019-2033. bogotá, colombia: upme. available from: http://www.sipg.gov. co/portals/0/demanda/proyeccion_demanda_gn_dic_2019.pdf. [last accessed on 2020 mar 26]. van der zwaan, b., kober, t., calderon, s., clarke, l., daenzer, k., kitous, a., labriet, m. (2016), energy technology roll-out for climate change mitigation: a multi-model study for latin america. energy economics, 56, 526-542. wec, wyman, o. (2019), world enegry trilema index. london: wec. available from: https://www.worldenergy.org/publications?cat=69. [last accessed on 2020 mar 26]. wec. (2011), policies for the future: 2011 assessment of country energy and climate policies. london: wec. available from: https://www. worldenergy.org/publications. [last accessed on 2020 mar 26]. wec. (2015), world energy resources: charting the upsurge in hydropower development 2015. london, united kingdom: wec. available from: https://www.worldenergy.org/publications/entry/ charting-the-upsurge-in-hydropower-development-2015. [last accessed on 2020 march 26]. world economic forum. (2017), global energy architecture performance index report 2017. cologny, geneva, switzerland: world economic forum. available from: http://www.3.weforum.org/docs/wef_ energy_architecture_performance_index_2017.pdf. [last accessed on 2020 mar 26]. international journal of energy economics and policy vol. 4, no. 4, 2014, pp.716-725 issn: 2146-4553 www.econjournals.com 716 analysis of the energy market operator activity in eight european countries france križanič eipf d.o.o. – economic institute -prešernova c. 21si 1000, ljubljana, slovenia. email: france.krizanic@eipf.si žan jan oplotnik corresponding author faculty of economics and business, university of maribor razlagova 14 – si 2000 maribor, slovenia. phone: +386 40 24 78 66. email: zan.oplotnik@uni-mb.si abstract: the article aims to analyze the connection between economic development, energy consumption, and prices of electricity and gas on one side and of the operation of the energy market operator on the other. for this purpose we use a sample of eight eu countries with well-functioning energy markets but quite diverse characteristics. the results show that market operators in more developed countries in the sample have above average activity (according to revenue), and their primary goal is to achieve external economies. a higher level of market operator activity (greater revenue) is influenced by the decrease of transaction costs in energy markets and improves the prospect for greater use of energy. an active market operator is characteristically associated with international openness in the energy market as well as with the development of gas use in the given country. we find that a better equipped (greater assets used by the market operator) and more active (according to revenues) market operator is related with relatively higher levels of electricity and natural gas prices. keywords: energy; supply and demand; financial analysis; macroeconomics; international benchmark; comparison jel classifications: e3; f0; g0; q4 1. introduction the analysis presented in this article gives a new aspect of contemporary european energy market monitoring. single and not most important institution on this market, “energy market operator”, is taken under the research with open questions how are its activity, relative size and assets connected to energy market. thus we estimate the connection between economic development, energy consumption and prices of electricity and gas on one side and the operation of the so-called market operator1 on the other. 1 the market operator is one of the actors in the market with a monopolistic, market facilitating function. the market operator is a centralized institution, which operates an organized market for the (commercial) exchange of energy or other products on behalf of market participants. in addition to organising the electricity market, the market operator is also responsible for the following tasks performed within the framework of the public service of organising the market for electricity: a) to carry out the clearing process, i.e. the accounting for and settlement of liabilities incurred on the basis of the deals made at the exchange, including the assurance of compliance with regard to these liabilities; b) to provide for the balancing of the electricity market according to the instructions of, and under the direction of, the transmission system operator, c) to establish imbalances and balance the imbalances relating to the supply and consumption of electricity, d) to record all the concluded contracts or the supply of electricity, d) to register all market participants that are eligible and wish to participate in the market. analysis of the energy market operator activity in eight european countries 717 in our analysis we have included market operators in eight european countries: slovenia – borzen, austria – apcs, italy – gme, united kingdom – elexon, spain – omel, czech republic – ote, croatia – hrote, and romania – opcom. the analysis refers to the year 2010 and assumes that we estimate the relationships which do not change quickly. first, we define the economic theory of energy market development and the market operator’s role in a modern national economy. then we describe the relative economic development, energy consumption and energy prices in the group of analysed countries. we proceed with a description of the methodology used in this econometric research where we set a link between the functioning of the market operator and the characteristics of a given national economy. at the end we elaborate on our conclusions and provide references. 2. about the energy raw materials market economic development is a dynamic process defined by two economic laws: the law of diminishing returns on labour and capital2, as well as the gossen’s first law of diminishing marginal utility (gossen, 1854). the first creates a tendency for capacity constraints despite the accumulation of capital and the growth of the population, while the second leads to a glut of market goods. their combined impact causes occasional drastic shifts in economic conditions. the evolutionary school of economic thought names it the change of techno-economic paradigms (nelson et. al, 1982). contemporary economic growth depends on the development of information technologies and their direct (components of devices and products) or indirect (information basis for the production of goods or the provision of services) applications in almost all products and services (romer, 1990, perez, 1983). gdp per capita in economically developed countries has reached such a level that the demand for agricultural products does not increase, while the demand for industrial products increases slowly. faster gdp increases just relate to demand for services. due to a high degree of flexibility and the continuous expansion of production efficiency through new technologies and because of slow growth in the consumption of industrial products, economic growth has become less dependent on increased consumption of raw materials, including energy. in recent decades, particularly influenced by two "oil shocks" in the 1970s,) energy industry management has changed in fundamentals. some producers of energy based on raw materials, in particular electricity, who were previously part of the infrastructure, had to fully transform to market-oriented activities. the essence of this transition has been the implementation of sovereignty of the electric power producers. the state has thus ended its regulation of quantities and prices in this field. sovereign producers need an efficient market of energy raw materials. for the smooth operation of the market of energy raw materials in which there is no lack of individual goods nor large fluctuations in their prices, where prices are a sufficient signal for the entry of new providers or for increasing the capacity of existing providers, and where prices are just as good a signal to clients when deciding to purchase energy consuming devices, there are inevitable institutions which develop to regulate this market ("energy agencies") and institutions that promote the market and help secure the participants on this specific market (market operators). both of these institutions are relatively new, also in developed market economies (more about market operators in kema int,, 2007 or bučar, 2012). in this article we analyze the functioning of the market operator. 3. some characteristic of economic development and energy market in the analysed countries the connection between market operator activities and different macroeconomic, development or energy-related variables of the national economies is estimated for the group of eight countries using data for 2010. seven of these countries were already eu member states, and croatia was in the process of eu accession in that year. we can say that all of them operate in the same eu institutional framework, but there are still significant historical differences between them. some of the states involved in our analysis have long and important traditions as market economies. the modern monetary economy in the western hemisphere started in italy. the united kingdom initiated the world's energy-fuelled industrial revolution. austria has a tradition of modernization development policies and has been a recognized school of economic thought from the times of its empire. spain 2 the concept of limited natural resources that decreases the efficiency of an additional unit of labor and/or capital was described by different economists at the end of the eighteenth and beginning of the nineteenth centuries. the most persistent about this subject was, without doubt, thomas malthus (1798). international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.716-725 718 passed into the developed market economy from feudalism. slovenia and croatia recently emerged from socialism of the so-called "illyrian type"3, while the czech republic and romania transformed into contemporary market economies from the centrally-planned socialistic states4. in spite great historical differences, the electricity market is for all these analysed economies relatively new. table 1. the size, economic development and r&d intensity (data for 2010) population gdp gdp per capita investment in r&d per capita the share of r&d investment in gdp thousand million € thousand € thousand € % slovenia 2,049 35,798 17 364 2.1 austria 8,880 281,179 34 942 2.8 italy 60,483 1,547,117 26 324 1.3 united kingdom 62,262 1,571,205 25 485 1.8 spain 46,073 1,047,103 23 317 1.4 czech republic 10,517 145,324 14 222 1.6 croatia 4,290 45,122 10 76 0.7 romania 21,431 116,247 5 27 0.5 in table 1 we can see from our sample of countries there are three big national economies (in principle, around 50 million inhabitants or more) with a gross domestic product exceeding a trillion €. these are the united kingdom, italy and spain. among the medium-sized economies are romania, the czech republic and austria, while croatia and slovenia are small economies. between the economically most developed and least developed, austria and romania, the difference in gdp per capita is nearly 7:1. there are also major differences in the development positions of the analyzed countries. austria has the highest economic development and is the most r&d investment intensive (judging by the gdp per capita and volume of investments in r&d per capita, as well as the share of investments in r&d in gdp) in our sample; it has a 2.8% share of r&d in gdp and under this criterion is close to the structure of the scandinavian countries in such a way as to resolve the dilemma between competitiveness and costs needed for the creation and maintenance of human capital. if we look only at gdp per capita, the older market oriented economies (austria, italy, the united kingdom and spain) are far above the former socialist countries. with regard to development effort, measured by investment in r&d, the united kingdom and slovenia follow austria. the results in the last two columns of table 1 show the relative effort of the czech republic in active development policy. the share of their r&d spending in gdp is larger than in italy or spain, while the volume of this investment per capita is in czech republic still smaller than in italy or spain. in our sample the least r&d investment intensive are croatia and romania. the proportion of investment in r&d, both in croatia and romania does not reach even one percent of gdp. energy consumption in the analyzed group of countries. table 2 shows the effectiveness of the total consumption of energy and the efficiency of the consumption of electricity and gas in the analysed countries (more about energy market can be found in bask et al, 2009, hellström et al., 2012, meeus et. al, 2005). efficiency is measured as energy consumption per unit of gdp. the lower this consumption figure, the more energy efficient is the economy (also saatci et al., 2013). additionally, table 2 shows the share of the imports or exports of electricity in its total final consumption. this quotient indicates the importance of cross-border trade for the functioning of the market. 3 "illyrian socialism" did not have a centrally-planned economy, but independent companies. they operated on the domestic and international market of goods and were structured accordingly. problems arose from the market of production factors and their inefficient use, resulting in inflation. 4 socialist planning had deep consequences in the energy sector. extensive investments in energy manufacturing capacity were based on the miscalculation that economic development is the consequence of capital accumulation and investment. however, the investments in energy-related facilities were more efficient (not so misguided) than the rest of the investment in industrial capacity. in the transition, most inefficient industrial producers (the so-called "mastodons") collapsed, yet the energy capacities, remained. their abundance has led to the low level of energy raw materials prices, in particular prices of electricity (križanič, 2001). analysis of the energy market operator activity in eight european countries 719 the most energy efficient among the analysed countries (second column of table 2) is: italy, austria, spain and the united kingdom. the two former yugoslav republics, croatia and slovenia, are to some extent less energy efficient. due to the more favourable climatic conditions and complete deindustrialization, croatia needs slightly less energy per gdp unit than slovenia. both of the former centrally plan economies, the czech republic and romania, are distinctly the least energy efficient in our sample. the electricity consumption per unit of gdp is shown in the third column of table 2. here too, are in our model the most effectively developed market economies of western europe. most effective is again italy, closely followed by the united kingdom, then austria and spain. slovenia is at the fifth place but not significantly ahead of croatia and romania. the greatest electricity consumption per unit of gdp is in czech republic. the sixth column of table 2 shows gas consumption per unit of gdp. here, the factors of supply (natural resources and pipelines) are more important than factors of demand. in the case of gas consumption we cannot describe it in terms of energy efficiency but according to the level of gas supply in a given economy. from this perspective spain has the smallest consumption of gas per unit of gdp in our group of analysed countries; it is followed by slovenia and austria. gas consumption per unit of gdp is then slightly higher, but still below the average, in italy and above average in croatia and in the uk. it is the highest in the czech republic and romania. in the fourth and fifth columns of table 2 we can finally see the importance of cross-border trade of electricity in the analysed group of countries. the most integrated in the international market on this field is slovenia. austria is similar but to a much lesser degree. exports of electricity are important in the czech republic, while imports of electricity are significant (based on the total consumption of these goods) in italy and croatia. the united kingdom (understandable), romania and spain have virtually completely closed electricity markets. table 2. the efficiency of energy consumption (data for 2010) the energy consumption to gdp electricity consumption to gdp share of imports in total electricity consumption share of exports in total electricity consumption gas consumption to gdp toe */mill € gwh/mill € % % tj/mill € slovenia 0.2029 0.3343 67 85 0.7255 austria 0.1231 0.2181 32 29 0.7428 italy 0.1134 0.1935 15 1 1.0419 united kingdom 0.1353 0.2090 2 1 1.2502 spain 0.1244 0.2489 2 5 0.5826 czech republic 0.3081 0.3937 12 38 1.9269 croatia 0.1900 0.3515 42 12 1.1947 romania 0.3072 0.3554 2 7 2.2290 * toe is thousands of tons of oil equivalent the prices of electricity and natural gas in the analyzed group of countries. prices of electricity and natural gas are specifically formed in several classes and are divided depending on the extent and/or purpose of consumption (sale of energy retail or wholesale – for use in households and the services sector or in industry). electricity prices, divided according to classes, decrease with the consumption growth (see also berndt, 1991 or girish et. al, 2014). this manner of price formation is likely to be affected by expensive (gas) or nearly impossible (electricity) storage of these two goods. sometimes the state influenced these prices by price regulation (mandatory approval, etc.); after transition, however, state influence on this sector is possible only through taxation. in table 3 we present the prices (including all taxes) of electricity and natural gas for the analysed group of countries. those presented are standard prices for the given (somewhere near average) class of electricity and natural gas consumption, separately for households and industry. in our sample the electricity and gas prices are more or less (the exception is prices of natural gas used in international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.716-725 720 manufacturing) the highest in italy. they are slightly lower, but still above the average, in austria and spain. in the united kingdom prices of these goods are lower than average. the same can be said for the czech republic and slovenian electricity prices, while natural gas prices are (especially for industrial use) above average in these two countries. slovenia has the highest natural gas prices in our sample. in croatia and particularly in romania electric power and natural gas prices are significantly lower than in the other analysed countries. for these two deindustrialized countries the price of electricity is not significantly lower, while price of natural gas is even higher for use in industry than in households. electricity and natural gas prices vary widely among the analysed countries. between the highest and lowest prices across countries, the difference is largest in natural gas prices for households (153%) and smallest in electricity prices for industry (61%). it is obvious that there are strong obstacles to cross-border trade of these two goods. above, we have seen that the importance of gas consumption per unit of gdp in spain is small and in italy great. it is interesting to note that each has a similar effect on the price level of natural gas. in spain, the demand for natural gas is likely to be sufficiently elastic to prevent greater rises of prices. in italy industrial clients obviously achieve volume discounts. the united kingdom has favourable natural conditions in obtaining natural gas, and so also the lowest price for it in industrial use. this price is even slightly lower than in romania. table 3. energy market – the prices of electricity and natural gas (annual average 2010) electric energy natural gas households industry households industry 2500-5000 kwh annual consumption 500-2000 mwh annual consumption 20-200 gj annual consumption 104 105 gj annual consumption €/kwh €/kwh €/kwh €/kwh slovenia 0.1414 0.1199 0.0628 0.0510 austria 0.1949 0.1276 0.0612 italy 0.1943 0.1630 0.0702 0.0330 united kingdom 0.1418 0.1163 0.0414 0.0267 spain 0.1790 0.1322 0.0537 0.0333 czech republic 0.1369 0.1268 0.0493 0.0403 croatia 0.1152 0.1134 0.0382 0.0452 romania 0.1042 0.1013 0.0277 0.0269 4. econometric analysis of the energy market operators in eight eu countries this section outlines a short econometric analysis to find out how the energy market operator behaves and functions and what the particular dependent features are with regard to different economic, market, and country specific variables, which we described in the previous chapter (economic development, r&d intensity, energy consumption, electricity and gas prices, etc.). the sample of eight european countries is diverse enough to comprise all the differences in economic development, energy consumption and the effectiveness of this spending, as well as with different levels in the prices of electricity and natural gas in order to give a comprehensive view of the subject. the relation between the variables that show economic environment, energy consumption and energy prices with the variables that show the energy market operator’s business performance are estimated by cross-sectional regression analysis, according to equation: (inco /inha) = (ene /gdp) + u (1) inco – energy market operator’s business income (million €) across countries; inha – the number of inhabitants (in 1,000) across countries; ene – total final energy consumption across countries (in toe); gdp – gross domestic product (million €) across countries; and u – unexplained residual to account for the inevitable fact that in our regression analysis we did not use perfect data, we did not form perfect equations, and because of incidental and unknown effects. our analysis includes national economies of very different sizes and structures. the impact of these differences (heteroscedasticity) we eliminated with the use of cross-sectional weights. this is a special method for disposing of heteroscedasticity in panel econometric analysis. analysis of the energy market operator activity in eight european countries 721 coefficients in tables 4 to 6 presented in the column under "connection", show the change in the dependent variable (for example, millions of euros "energy market organizer’s" business income per capita) where the independent variable is changed by one unit (for example, final energy consumption to gdp expressed in thousands of tons of oil equivalent per million € of gdp) in the analyzed group of countries. the results in this column are largely dependent on the units. statistically, the significance of the explanation of a given independent variable's relation to energy market operator operation, equipment and business performance shows t statistics, while the total cover of the variance (changing the independent variable by changing the dependent variable) shows the determination coefficient r2. it is given as a percentage from 0 (no connection) to 100 (tautology). the results of our analysis are limited in time (2010) and space (eight european countries). in the study they can be described as a possible link. the characteristics of the energy market operator depending on the size, economic development and r&d intensity of its national economy. here we first analyze the energy market operator's features that depend on the size of the country (gdp), economic development (gdp per capita), and its development orientation (r&d investment per capita or share of r&d investment in gdp). in doing so, we observe the characteristics of energy market operator in relation to its business income, assets and the economic result (ebit), all standardized per capita. the relationship is then estimated in cross-sectional regression analysis5 on the data for 2010. the results in table 4 show that the energy market operator’s greater business income per capita and more engaged resources per capita are positively related with the size of gdp6. business income and ebit (both per capita) under energy market operator are positively and strongly related with economic development, as is shown by gdp per capita. in rows (table 4) after "r&d intensity of the economy" we can finally see that the energy market operator’s business income per capita, assets per capita and ebit per capita are also positively linked with the development dynamics (investment in r&d) of the given economy. table 4. the connection between the characteristics of the energy market operator and the size, economic development, or r&d intensity of the national economy energy market operator’s business income (per capita) connection t-statistics r 2 the size of the economy gdp 0.0000004 11.1 32% economic development gdp per capita 0.0285 7.5 38% r&d intensity of r&d per capita 0.0012 9.8 24% the economy % of r&d in gdp 0.4377 181.9 97% energy market operator’s assets (per capita) connection t-statistics r 2 the size of the economy gdp 0.000008 1.9 15% economic development gdp per capita 0.6134 782.0 38% r&d intensity of r&d per capita 0.0144 2.2 29% the economy % of r&d in gdp 5.1697 3.7 35% energy market operator’s ebit (per capita) connection t-statistics r 2 economic development gdp per capita 0.0055 3.0 31% r&d intensity of the economy % of r&d in gdp 0.0867 2.8 25% 5 the regression coefficient (presented in the column under “connection”) shows how it is given an energy market operator’s characteristic (business income, assets or ebit) associated with certain macroeconomic variables (gdp, etc.); t statistics show how strong this link is; r2 (determination coefficient) indicates how much of the variance in the data on energy market operator’s characteristics is explained by the variance of a given macroeconomic variable. 6 the size of economy (its gdp) is not connected with ebit per capita in energy market operator (the relation statistically isn’t significant). international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.716-725 722 in short, the energy market operator is more active and better equipped in larger, more economically developed and more r&d intensive national economies. because the energy market operator works basically as a part of market infrastructure (even if it has the status of a limited liability company), its profitability is of minor importance. there is no relation between the return of energy market operator and the size of the national economy. the relation between the energy market operator’s ebit and the economic development of the analyzed countries is, however, smaller than the relation between the same macroeconomic variables and energy market operator’s activity or assets. the energy market operator’s characteristics depending on energy consumption. after introducing the energy market operator’s connection with general macroeconomic performance and r&d intensity of a modern national economy, let us look at its connection to the functioning of the energy market. in doing so, the activity of the market operator is again shown by its income, its equipment by its assets, and its economic performance by its ebit (all three per capita). these market operator characteristics are analyzed according to total energy consumption per unit of gdp, the consumption of electricity (total and exclusive to industry) per unit of gdp, and the consumption of natural gas per unit of gdp in a given national economy. finally we estimated the relation between market operator characteristics and the importance of cross-border electricity trade in the analyzed group of countries. the results of cross-sectional regression analyses are shown in table 5. table 5. the connection between market operator's characteristics and energy consumption energy market operator’s business income* connection t-statistics r 2 energy consumption total energy consumption** 3.9489 10.9 32% electricity consumption final consumption of electricity** 2.4770 4.3 18% consumption of electricity in industry** 6.2962 4.5 23% cross-border trade of electricity share of imports in the final consumption of electricity 2.2668 13.9 88% share of exports in the final consumption of electricity 2.1263 8.3 71% gas consumption final consumption of gas** 0.4892 20.7 84% energy market operator’s assets* connection t-statistics r 2 energy consumption total energy consumption** 43.6131 3.6 22% electricity consumption final consumption of electricity** 38.2178 22.3 42% consumption of electricity in industry** 72.2323 2.7 11% cross-border trade of electricity share of imports in the final consumption of electricity 42.6766 24.8 99% share of exports in the final consumption of electricity 32.3982 12.3 94% gas consumption final consumption of gas** 5.6677 3.0 22% energy market operator’s ebit* connection t-statistics r 2 energy consumption total energy consumption** 0.6682 3.2 26% electricity consumption final consumption of electricity** 0.4297 2.4 13% consumption of electricity in industry** 1.4807 12.6 27% cross-border trade of electricity share of imports in the final consumption of electricity 0.6455 9.2 90% share of exports in the final consumption of electricity 0.5069 8.5 91% gas consumption final consumption of gas** 0.0952 5.1 34% * per capita ** per unit of gdp analysis of the energy market operator activity in eight european countries 723 in table 5 we see that the market operator’s business income, assets, and ebit (all three per capita) are greater the higher the energy consumption per gdp. this relationship is thus positive. greater market operator activity leads to decreased transaction costs in this market. the result suggests a possibility of increased energy consumption. in table 5 we also see that the market operator’s business income, assets and ebit (all per capita) are larger the higher the final electricity consumption to gdp. total electricity consumption (to gdp) is related mainly with the market operator’s assets (per capita), while electricity consumption in the industry (to gdp) is more related with market operator’s business income and ebit (both per capita). the results in table 5 also show that the more active the market operator is the stronger the involvement of the given economy in the international electric energy trade. this is true for the energy market operator’s business revenues, assets, and ebit (all per capita). the link between total final natural gas consumption (per unit of gdp) and the activity of the market operator, indicated by its business income per capita, is positive and even very high (table 5). this relation is similar to total energy consumption, electricity consumption, and participation in the international electricity market. in table 5 we also see that the connection between total final natural gas consumption (per unit of gdp) and market operator’s assets and ebit (per capita) is not as strong as it is in the case of market operator’s business income. when we focus ourselves on the level of natural gas supply per unit of gdp, obviously, the main indicator of the market operator’s activity is its business income. the impact of the assets is likely to be smaller due to the opposite effect of their better utilization in national economies with a higher level of gasification, thus, the impact of ebit is lower due to the market operator’s infrastructural nature. the energy market operator’s characteristics depending on energy prices. the connection of the operation of the market operator with electricity and natural gas prices is presented in table 67. due to the specific nature of the pricing of electricity and natural gas, depending on the purpose (industrial, non-industrial) and scope (classes of prices depending on the amount of the consumption8), table 6 shows the connections between different market operator’s characteristics and the level of a given energy resource price only in exemplary classes. the same as in table 3. the results in table 6 show that higher electric power and natural gas prices relate to greater market operator business income, assets, and ebit (all per capita). this connection is not significant in the relation between the market operator’s business income per capita and electricity prices for the industrial use nor between market operator’s assets per capita and industrial use of natural gas (in this case the relation is not significant for all classes of natural gas use in industry, not just for the one presented in table 6). we can conclude that an active, well equipped and directly (depending on its ebit) economically efficient market operator is not associated with the relatively low prices of electricity and natural gas in a given national economy. obviously the reduction of transaction costs in the energy market (one of the market operator’s roles) does not promote only a new supply, but encourages also greater demand. the latter case is even more so. this was clearly manifested in 2010, when the energy consumption due to the intensified recessionary trends in the eu stagnated (it fell in 2009 and then again in 2011). here another aspect is also possible. the eu is finalizing the transition of the energy sector in which the termination of price regulation has led to decreasing and then increasing prices until the market will not establish a new balance (see also zachmann, 2008). in a given case, this means that electricity and natural gas prices in 2010 were still (albeit temporarily) at a higher level in countries where the energy market worked better and had a more active market operator. 7 eurostat publishes energy prices on a half-yearly basis. for the purposes of our analysis we have converted them to an annual level using the simple arithmetic mean of the prices of electricity and natural gas in the first and second halves of the year. 8 the austrian data on electricity prices for industrial use in 2010 are not available. we have estimated them according to their level in 2008 (last data) and the dynamics of the prices of electricity in this country for the highest class of these prices in retail trade (over 15,000 kwh annual consumption). international journal of energy economics and policy, vol. 4, no. 4, 2014, pp.716-725 724 table 6. the connection between market operator’s characteristics and energy prices the characteristics of the market operator connection t-statistics r 2 price of electricity in the retail trade (2500 to 5000 kwh) ** business income* 3.7782 12.9 22% assets* 91.0918 2.3 8% ebit* 1.0283 28.6 24% price of electricity for the industry (500 to 2000 mwh) ** business income* assets* 116.5429 2.5 15% ebit* 1.2580 5.1 32% gas prices for households (20 to 200 gj) ** business income* 13.7131 60.5 29% assets* 298.0165 2.9 24% ebit* 3.3913 9.4 65% gas prices for industry (104 to 105 gj) ** business income* 0.0345 10.1 29% assets* ebit* 0.1140 207.7 98% * per capita ** annual consumption 5. conclusions our research aim was to analyze the connection and dependence between economic development, energy consumption, and prices of electricity and gas with the operation and business performance of an energy market operator, one of the actors in the market with a monopolistic, market facilitating function. for this purpose we used a sample of eight eu countries with wellfunctioning energy markets but quite diverse characteristics. due to these structural differences we performed a short cross-sectional regression econometric analysis and revealed some interesting results. we determined that the activity and equipment of the energy market operator grows with the size of a country. on the other hand in large states the energy market operator acts as infrastructure, as the size of a national economy is not associated with an energy market operator’s better cost management (higher ebit). along with that we established the connection of countries with higher gdp per capita and more active development policy (high level of r&d investments) with aboveaverage activity of the energy market operator. in continuation, we realized that increased energy market operator activity lowers the transaction costs on the market and increases the possibility of energy consumption. this applies to total energy consumption as well as for electricity consumption (per unit of gdp) and that involvement in the international trade of electric energy is associated with a more active energy market operator. this is true for its resources, business revenues, and ebit (all per capita). finally, we found that the relationship between total final consumption of natural gas (per unit of gdp) and the activity of the energy market operator, indicated by its business income, is both positive and high; gasification is associated with an active energy market operator, and that greater business income, more assets, and a higher ebit (all per capita) of an energy market operator is specific to a national economy with a higher level of prices for electricity and natural gas in the retail and industry. regarding economic policy use of our results, we can derive conclusions that energy policy leaders in eu should finally recognize that “energy market operators” provide efficient support to the development of this specific market. the main contribution of "energy market operator" is in promoting of energy trade and also consumption. these effects are not limited just on electric power but also on natural gas. european "energy market operator" is efficient in allocation and not in reduction of energy consumption. analysis of the energy market operator activity in eight european countries 725 references bask, m., widerberg, a. (2009), market structure and the stability and volatility of electricity prices research article, energy economics, 31(2), 278-288. berndt, e.r. (1991) the demand for electricity: structural and time series approaches, posted in the practice of econometrics: classic and contemporary, adison-wesley publishing company, p. 306-360. bučar, a. (2012) the energy market operator’s income, equipment and business performance in 2010 in the eight european countries collected from annual reports for 2010”, ireet, ljubljana eurostat/statistics/data navigation tree/database by themes: 1. the economy and finance/national accounts (including gdp) (na), 2. science and technology/research and development (research), 3. environment and energy/energy. girish, g., panchakshara, m., vijayalakshmi, s., ajaya, k.p. (2014), forecasting electricity prices in deregulated wholesale spot electricity market a review, international journal of energy economics and policy, 4(1), 32-42. gossen, h.h. (1854). entwickelung der gesetze des menchlichenverkerhs, und der daraus fliessenden regeln für menschliches handeln, braunschweig: vieweg; english translation (blitz r.c., 1983): the laws of human relations and the rules of human action derived therefrom, cambridge, mit press. hellström, j, lundgren, j., yu, h. (2012), why do electricity prices jump? empirical evidence from the nordic electricity market, energy economics, 34(6), 1774-1781. kema int. (2007), market operator, regulatory oversight”, issue paper, erra committee, hungary križanič, f. (2001) o vplivu liberalizacije trgovanja z elektriko na ravnanje z energijo in na energetski sektor v sloveniji", gospodarska gibanja, no. 325, mart 2001, p. 25-40. malthus, t.r. (1798) an essay on the principle of population, repr. london, macmillan (1926). meeus, l, purchala, k, belmans, r. (2005), development of the internal electricity market in europe, the electricity journal, 18(6), 25-35. nelson, r., winter, s. (1982). an evolutionary theory of economic change, cambridge: harvard university press. perez, c. (1983). structural change and the assimilation of new technologies in the economic and social system, futures, 15, 357-375. romer, p. (1990). endogenous technological change", journal of political economy 98, october. syrquin, m. (1989) patterns of structural change, handbook of development economics, vol. i., north-holland. saatci, m., dumrul, y. (2013), the relationship between energy consumption and economic growth: evidence from a structural break analysis for turkey, international journal of energy economics and policy, 3(1), 20-29. zachmann, g. (2008), electricity wholesale market prices in europe: convergence? energy economics, 30(4), 1659-1671. . international journal of energy economics and policy | vol 9 • issue 5 • 2019 401 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(5), 401-408. effects of energy prices on environmental pollution: testing environmental kuznets curve for algeria ouarda belkacem layachi* department of law, faculty of law, prince sultan university, saudi arabia. *email: olayachi@psu.edu.sa received: 22 april 2019 accepted: 01 july 2019 doi: https://doi.org/10.32479/ijeep.8312 abstract the current study is primarily motivated in testing environmental kuznets curve (ekc) framework by including energy prices along with output growth. in addition, the current study is also important for analyzing the impact of energy prices by testing the effects of three different fuel prices. they include crude oil prices, natural gas prices and heating oil. the data is gathered from the period of 1980-2017. the results of auto regressive distributed lag (ardl) confirm that economic growth has a positive and significant impact on carbon emission in algeria. on the other hand, all energy prices (oil prices, heating oil and natural gas prices) confirm a negative and significant impact on carbon emission in algeria. the results of ardl also confirm a presence of u-shaped ekc curve in the algeria. the results variance decomposition model have confirm a bi-directional causal relationship between oil prices and carbon emission; however we found a unidirectional causal relationship from heating oil prices to carbon emission and no causal relationship between natural gas prices and carbon emission in algeria. keywords: oil prices, natural gas prices, heating oil prices, algeria jel classifications: e31, q5, q56 1.introduction an environment in the present time is facing extreme deterioration (koengkan et al., 2019). the rising environmental pressures that have became the inevitable part of economic development have been the prime sources of worsening ecological health. the theoretical notion for environmental degradation has been identified in early 1950s by the renowned economist simon kuznets in the form of environmental kuznets curve (ekc). however, the quantitative testing of the ekc essentials were first analyzed by grossman and krueger in 1992 (grossman and krueger, 1992; okechukwu and hyginus, 2017). the fundamentals of ekc hypothesis suggested that the levels of ecological pollutions augment with the increase in economic development, however, they tend to decline with the progression in income levels and subsequently cause positive impact on environmental quality. since then, the literature has witnessed many examinations attributed to inspect the existence of ekc hypothesis in several regions (selden and song, 1994; patel et al., 1995; torras and boyce, 1998; andreoni and levinson, 2001; cole, 2004; stern, 2004). in recent studies, many researchers have analyzed the numerous indicators of ekc framework (lacheheb et al., 2015; shahbaz et al., 2015; shahbaz et al., 2016; anastacio, 2017; solarin et al., 2017; sarkodie, 2018; sarkodie and strezov, 2018; adu and denkyirah, 2018; rauf et al., 2018; he et al., 2019; sasana and aminata, 2019). in order to examine the role of agriculture development in contributing to environmental degradation, gokmenoglu and taspinar (2018) tested ekc curve for pakistan. for smog pollution, xie et al. (2019) examined ekc in china. in testing transportation industry’s contribution to ecological deterioration, wang et al. (2017) analyzed ekc curve for japan. as for african region, bah et al. (2019) studied ekc existence for the case of sab-saharan african economies. hence, the significance of ekc estimations have proved immensely valuable for studying environmental condition since its inception. this journal is licensed under a creative commons attribution 4.0 international license layachi: effects of energy prices on environmental pollution: testing environmental kuznets curve for algeria international journal of energy economics and policy | vol 9 • issue 5 • 2019402 among the variables that can validate the existence of ekc framework, the impact of energy prices is substantial to influence environmental degradation (agras and chapman, 1999; myambo and munyanyi, 2017). the association of energy prices with environment is theorized in accordance the popular economic theory. the basic of the theory suggested that changes in fuel prices are likely to bring changes in emissions levels that impact environmental condition. it is more evidently witnessed in the observing the trend analysis of emission and energy data. more commonly, the price increase in energy is likely to carry negative impact on toxic environmental emanations (brown et al., 1996). this association is probable to remain constant for all income groups and therefore, impacts similar in emerging and industrialized countries (agras and chapman, 1999). however, the relationship in ekc curve tends to change with the enhancements in income levels. thus, the investigation of ekc with the inclusion of energy prices has potential significance. therefore, keeping in mind the theoretical effect of energy prices in curtailing environmental deterioration, the present study aims to investigate the association between energy prices and environmental pollution in algeria. given the ability of ekc in testing quadratic association, the current study is primarily motivated in testing ekc framework by including energy prices along with income level (obadi et al., 2017). in addition, the current study is also important for analyzing the impact of energy prices by testing the effects of three different fuel prices. they include crude oil prices, natural gas prices and heating oil. the comprehensive investigation of analyzing three core energy prices will be successful in providing more generalized impact of energy prices in carbon emanations of algeria. the remaining parts of the current investigation are discussed in the following. after chapter one, chapter two of this study analyzed the existing literature related to ekc examinations and its link with crucial ecological indicators including energy price. later in chapter three, the explanation regarding the methods of the study are discussed. in chapter four, the empirical results and their interpretations are presented. in the end, chapter five offers study conclusion and implications. 2. literature review the importance of ekc has been evident in literature since its inception. in earlier studies, the examinations of ekc model were largely confined to the sectoral and segregate developments (hettige et al., 2000; tamazian et al., 2009; lekakis, 2000; perrings, 1998). however, in more recent studies, the emphasis of scholars in analyzing ekc model for energy variables has been observed. in such investigations, dogan and seker (2016) examined ekc framework among the variables of renewable, non-renewable power and carbon dioxide emanations. using the sample of european countries from 1980 to 2012, the results provided the significance of renewable and non-renewable power in altering emission levels. in particular the study found the positive relationship of non-renewable power and negative relationship of renewable power with environmental pollution in eu economies. focusing exclusively on oil prices, balaguer and cantavella (2016) also examined ekc model among the variables of economic growth, fuel prices and carbon dioxide emanations. using the sample of spain from 1874 to 2011, the results from auto regressive distributed lag (ardl) estimates provided the significance of output and energy prices in altering emission levels. in particular the study found the unit increase in fuel prices is probable to decrease carbon emanations by 0.4 units in spanish economy. for pakistan, zhang et al. (2017) examined ekc framework among the variables of renewable, non-renewable power and carbon emanations. using the data from the period of 1970 to 2012, the findings concluded the significance of renewable and non-renewable power in altering emission levels. in specific, the authors found the positive relationship of non-renewable power and negative relationship of renewable power with environmental pollution in pakistan. analyzing the role of aggregate and disaggregate energies in influencing carbon emissions, alkhathlan and javid (2013) studied the association between power utilization, output growth and carbon-di-oxide in saudi arabia. in doing so, the authors used the observations from the time of 1980 to 2011 (haseeb et al., 2019). the study utilized vecm granger method to test the empirical association among the variables. the results of the study confirmed the significance of energy utilization at both aggregate and disaggregate levels in influencing emission in saudi arabia (jermsittiparsert et al., 2019). the results suggested that energy utilization carry positive impact on emissions, so as oil consumption. however, the results suggested that natural gas underlies the potential to reduce carbon emission in the country. dong et al. (2017a) inspected the connection between natural gas utilization on environmental degradation. in doing so, the study used the data of thirty chinese provinces from 1995 to 2014. the empirical investigation in the study was carried out by applying ardl method (jermsittiparsert, 2016; myambo and munyanyi, 2017). the outcomes of the examination confirmed the authenticity of ekc framework. the results also established the significance of natural gas in altering carbon emission in china. in particular, the findings suggested that natural gas declined environmental degradation in chinese provinces in the studied period. in another study, dong et al. (2017b) analyzed the ekc framework among the variables of renewable power, natural gas and carbon dioxide emanations. using the sample of brics countries from 1985 to 2016, the results provided the significance of natural gas and renewable power in influencing environmental pollution measured by carbon dioxide emissions. particularly, the study found the negative association of natural gas and renewable power with environmental pollution in brics economies. similarly, lotfalipour et al. (2010) also studied the link between fossil fuel, natural gas and petroleum products with carbon emission in iran. the study used the data from the period of 1967 to 2007. applying the methods of toda-yamamoto granger causality, the findings of the investigation confirmed the significance of natural gas in causing carbon emissions in iran. apergis and payne (2015) also investigated the relationship of green power, layachi: effects of energy prices on environmental pollution: testing environmental kuznets curve for algeria international journal of energy economics and policy | vol 9 • issue 5 • 2019 403 economic growth and carbon dioxide emanations. using the sample of eleven south america from 1980 to 2010, the results provided the significance of output growth in enhancing carbon emission. furthermore, the results also concluded the positive significant association between oil prices and co2 emission in the sampled economies. for g-7 economies, sadorsky (2009) analyzed renewable power, carbon emanations and fuel prices. the study utilized the data from the period of 1980 to 2005. the results of the analysis reported the significance of output in enhancing green power consumption. in addition, the findings suggested the negative impact of oil prices in renewable consumptions in the sampled economies. moreover, the result confirmed output and carbon-di-oxide to be the critical influencers of renewable power in g-seven nations. furthermore, lindmark (2002) also investigated the association between environmental degradation, technological advancements, output and energy prices (umrani et al., 2016; nguyen, 2018). the authors used the data of sweden from the period of 1870 to 1997. the findings of the analysis established that change in fuel prices, output development, technological advancements and structural change are significant to influence environmental degradation in sweden. eddrief-cherfi and kourbali (2012) investigate the energy consumption-growth nexus in algeria. the causal relationship between the logarithm of per capita energy consumption (lpcec) and the logarithm of per capita gdp (lpcgdp) during the 1965-2008 period is examined using the threshold cointegration and granger causality tests. the estimation results indicate that the lpcec and lpcgdp for algeria are non cointegrated and that there is a uni-directional causality running from lpcgdp to lpcec, but not vice versa. analyzing the effects of several energy prices on carbon allowance prices, zeng et al. (2017) examined chinese carbon emission trading. in doing so, the study analyzed the data from april 2014 to november 2015. the outcomes of the study suggested that unit rise in coal prices enhances carbon prices by o.1 units. in addition, the authors concluded that levels of carbon emanations in china is influenced mainly by its past prices. the results of the aggregate analysis established the positive but insignificant association of oil price, natural gas price and economic development of china. moreover, in portugal, pereira and pereira (2010) studied the relationship of natural gas in predicting carbon di oxide levels. for empirical investigation, the study applied the methodology of vector auto regressive (var) from the time period of 1977 to 2003. the results of the study, similar to lotfalipour et al. (2010), confirmed the significance of natural gas in influencing carbon emission levels as well as economic growth in portugal. moreover, agras and chapman (1999) examined ekc framework among the variables of energy prices, output growth and carbon dioxide emanations (ali and haseeb, 2019) using the panel data of international energy agency for thirty four economies, the results provided the significance of energy prices but failed to validate the association of trade in altering emission levels. in particular the study found the negative relationship of energy with environmental pollution in sampled economies. 3. methodology the current research looks at the association between oil prices, natural gas prices, heating oil prices, economic growth and carbon emission by utilizing ekc model and the system is given underneath: ( ) ( ) ( ) ( ) ( ) 2 2 0 1 2 3 4 5 t t t t t t t co y y oil gas hoil        = + + + + + + where, εt is the residual term, co2 signifies the carbon emission which is calculated in ktons of oil equivalent. oil explains the international oil prices (wti crude oil) which is measured in us dollars, gas denotes the international gas prices which is measures in cubic feet meters. moreover, hoil signifies the international heating oil prices which is measured in us dollars. moreover, y specifies the output which is explained by the all final finished services and goods (in us dollars). finally, y2 is the square of the output growth. the information is gathered from the time of 1980 to 2017. entire information is collected from world development indicators. finally, entire information is converted in natural logarithmic series as it provides more accurate results (afshan et al., 2018). 3.1. unit root tests so as to check the stationary properties for long haul connection of focused time series information, the present examination uses augmented dickey-fuller (adf) and philip perron (pp) unit root tests. moreover, the current study also inspects the information at first on level and afterward on first differential of all considered variables. 3.2. long-run cointegration analysis next, to examine the job of international oil prices, international natural gas prices and international heating oil prices in ekc in algeria, the current study applies ardl strategy of long-run association which was introduced by pesaran and pesaran (1997), pesaran et al. (1999), pesaran et al. (2001; 2000) is used with the help of unrestricted vector error adjustment model to inspect the long haul relationship among different energy prices (which includes international oil prices, heating oil prices and natural gas prices) and environmental degradation. the above-mentioned method has a few advantages on previous long-run association studies (like johansen and juselius cointegration and further). this method could be valuable in any case of whether focused time series are totally i(0), i(1) or similarly co-incorporated. the auto regressive distributed lag structure is projected for the investigation is as follows: 2 0 1 2 3 4 5 6 1 2 2 2 1 1 1 1 1 1 1 1 2 1 1 2 31 1 1 1 1 1 15 614 p p p p t t t t i i i i p p t t t t t i i t t t t co y y oil gas hoil co y y oil gas hoil co              − − − − = = = = − − − − − = = − − − δ = + + + + + + + + + + + + + ∑ ∑ ∑ ∑ ∑ ∑ where, φ0 is consistent term and μt is error term, the error adjustment limit is explained to by the indication of adding though the further proportion of the calculation identifies with a long haul association. the schwarz bayesian criteria (sbc) is used to look at the most extreme lag length choice for every factor. layachi: effects of energy prices on environmental pollution: testing environmental kuznets curve for algeria international journal of energy economics and policy | vol 9 • issue 5 • 2019404 moreover, in this framework, the present examination figures the f-measurements importance by utilizing the appropriate systems. following, the wald (f-stats) test is used to examine the long haul relationship between the factors. if the long-run connection is found between economic growth, international oil prices, natural gas prices and heating oil prices, then the current research estimated the long-term coefficients using the following framework: 2 2 1 1 1 1 1 1 1 1 2 0 1 1 1 1 3 4 5 1 2 6 p p p p t t t t i i i i p p t t t i t i co y y oil gas ho l c i o         − − − − = = = = − − = = = + + + + + + +∑ ∑ ∑ ∑ ∑ ∑ next, if long run connection between economic growth, international oil prices, natural gas prices, heating oil prices and carbon emission are found with proof then we gauge the short run coefficients by utilizing following framework: 2 0 1 2 2 2 1 1 1 1 1 1 1 1 1 1 1 4 5 1 1 3 6 p p p p t t t t i i i i p p t t t t i i t co y y oil gas hoil nect co         − − − − = = = = − − − = = = + + + + + + ++ ∑ ∑ ∑ ∑ ∑ ∑ the error correction model demonstrate the speed of modification permit to quantify the long-run symmetry because of a short run shock. the n is the coefficient of error correction term in the model that determines the speed of modification. 3.3. variance decomposition analysis furthermore, the another aim of the current study is to applied g generalized forecast error variance decomposition technique under var framework is connected to examine the causal connection of economic growth, international oil prices, international natural gas prices and international heating oil prices with carbon emission in algeria. moreover, the variance decomposition model (vdm) provide the size of the anticipated error fluctuation for an arrangement reason for fluctuation from every independent variable over the various time frame (sharif et al., 2017). 4. data estimation and interpretation the present unit explains the information examination. basically we utilized stationary test to affirm the stationary features of the taken factors. the consequences of unit root test are presented in table 1. in this study, we used two unit root tests to be specific adf and pp test to confirm the stationary features of the factors. the discoveries affirm that economic growth, international oil prices, natural gas prices, heating oil prices and carbon emission at first are non-stationary at series of level data however, become stationary at a series of first differentials. in basic way, from the results of unit root test, the current study can infer that data of the considerable number of factors imitate the stationary features and permit for reports to the long-term evaluations. moreover, to explore the long run connection between economic growth, international oil prices, international heating oil prices, international natural gas prices and carbon emission in algeria, the present examination connected the method of autoregressive distributed lag technique for cointegration (ardl). so as to accomplish, the primary stage is to recognize the maximum lag measurement of the considerable number of factors. the order of this lag measurement is picked by providing standards of sbc. hence, the result of the ardl bound testing cointegration is shown in table 2. the consequences of table 2 affirm the null of no connection among the factors is refused. this is because of the value of the f-statistics is bigger than ubc value at 1% level of significance. therefore, it is in the support of acknowledgment of the alternate hypothesis which propose that there is a powerful long haul association occur among economic growth, international oil prices, international heating oil prices, international natural gas prices and carbon emission in algeria. the results of lag length selection is reported in table 3. the outcomes of bound testing, hence, confirm the power of attained outcomes. it is shown that a huge long haul affiliation exists among economic growth, international oil prices, international heating oil prices, international natural gas prices and carbon emission in algeria. besides, after affirming the proof of long haul association between the focused factors, the additional stage of the investigation is to use the framework with the point of result the coefficient estimation of long-short term period. as to accomplish, the current investigation estimates the lag measurement sequence of entire factors done by the lesser estimation of sbc. the long term consequences of ardl technique is shown in table 4. the discoveries hence set up that economic growth, international oil prices, international natural gas prices and table 1: results of unit root test variables adf unit root test pp unit root test i(0) i(1) i(0) i(1) c c and t c c and t c c and t c c and t oil 0.446 0.421 −5.392 −5.344 0.441 0.395 −5.796 −5.690 gas 1.482 1.272 −4.584 −4.399 1.294 1.302 −4.246 −4.130 hoil −1.137 −1.089 −5.338 −5.261 −1.009 −1.014 −5.332 −4.982 y −0.256 −0.224 −4.473 −4.674 −0.239 −0.218 −4.839 −4.772 co2 −0.773 −0.667 −5.117 −5.149 −0.673 −0.702 −5.094 −5.022 source: authors’ estimations. the critical values for adp and pp tests with constant (c) and with constant and trend (c and t) 1%, 5% and 10% level of significance are −3.711, −2.981, −2.629 and −4.394, −3.612 and −3.243 respectively. adf: augmented dickey-fuller, pp: philip perron layachi: effects of energy prices on environmental pollution: testing environmental kuznets curve for algeria international journal of energy economics and policy | vol 9 • issue 5 • 2019 405 growth produce greater carbon emission in the country. on the other hand, the results of ardl also confirm that square of output growth, international oil prices, heating oil prices and international natural gas prices are play a noteworthy role to decrease the co2 in algeria which confirm an invert u-shape ekc curve presents in algeria. finally, the outcomes of ekc curve and energy prices features that in the beginning the development of economy enhance the carbon outflow in the nation however later receiving the significant development it helps to decrease the ecological dilapidation in the situation of algeria. the short run outcomes of ardl method is shown in table 5. the discoveries detailed a legitimate short run connection between output growth, international oil prices, international heating oil prices, international natural gas prices and carbon emission in algeria. the value of error term is demonstrating the estimation of around −0.481 recommend that around 48% of variability is adjusted in the present year. moreover, the discoveries likewise affirm the noteworthy effect of energy prices (oil prices, heating oil prices and natural gas prices) on carbon outflow in algeria in short running also. the outcomes of table 6 show the causal relationship between economic growth, international oil prices, heating oil prices, natural gas prices and carbon emission in algeria. the outcomes of carbon emission model recommend that in 1st year, the variation in co2 is described 100% completely by its own enhancements. in the second period 86.14% explained by own enhancements, 0.049% by economic growth, 11.804% by international heating oil prices, 0.766% by international natural gas prices and 1.234% by international heating oil prices. in 3rd year, the variation in co2 explain 74.115% by its own enhancements, 1.420% by output advancement, 21.705% by international oil prices, 0.621% by international natural gas prices and 2.139 % by international heating oil prices. in the 5th year period, the shocks in co2 describe 57250% by its own improvement, 2.982% by output development, 36.639% by international oil prices, 0.457% by natural gas prices and 2.726% by international heating oil prices. the outcomes of table 6 recommend the bi-directional causal relationship among international oil prices and carbon emission. however, we find a unidirectional causality between carbon emission and international heating oil prices where causality is running is from heating oil to carbon emission. also, we do not find any causal relationship between carbon emission and natural gas prices in algeria. 5. conclusion environments in the present time is facing extreme deterioration. the rising environmental pressures that have become the inevitable part of economic development have been the prime sources of worsening ecological health. the theoretical notion for environmental degradation has been identified in early 1950s by the renowned economist simon kuznets in the form of ekc. among the variables that can validate the existence of ekc framework, the impact of energy prices is substantial to influence environmental degradation. the association of energy prices with table 2: results of bound testing for cointegration lags order aic hq sbc f-test statistics 0 −4.677 −4.983 −5.093 87.179* 1 −5.949* −5.892* −6.038* 2 −5.382 −5.242 −5.132 3 −4.884 −4.792 −4.954 source: authors’ estimation. *1% level of significant. sbc: schwarz bayesian criteria table 3: results of lag length selection lag 0 1 2 nominated lags sbc sbc sbc sbc oil 1.282 −3.483* −2.495 1 gas 1.485 −3.490* −2.219 1 hoil 1.932 −2.459* −1.858 1 y 1.084 −3.382* −1.481 1 source: authors’ estimation. *indicate minimum sbc values. sbc: schwarz bayesian criteria table 4: results using ardl approach (long run) variables coefficient t-stats prob. c 0.393 5.957 0.000 co2 (−1) 0.187 4.384 0.000 y 0.209 4.184 0.000 y (−1) 0.089 2.785 0.000 y2 −0.194 −4.385 0.000 y2 (−1) −0.006 −0.936 0.350 oil −0.535 −5.839 0.000 oil (−1) −0.148 −1.452 0.148 gas −0.281 −5.171 0.000 gas (−1) −0.019 −1.182 0.238 hoil −0.192 −3.643 0.000 hoil (−1) −0.015 −0.965 0.338 adj. r2 0.902 d.w stats 2.098 f-stats (prob.) 2494.436 (0.000) source: authors’ estimation. ardl: auto regressive distributed lag table 5: results using ardl approach (short run) variables coefficient t-stats prob. c 0.209 2.588 0.010 δco2 (−1) 0.028 1.781 0.072 δy 0.392 4.467 0.000 δy (−1) 0.026 1.395 0.175 δy2 −0.192 −5.432 0.000 δy2 (−1) −0.014 1.592 0.112 δoil −0.351 −5.315 0.000 δoil (−1) −0.014 −0.287 0.774 δgas −0.129 −4.221 0.000 δgas (−1) −0.041 −1.182 0.238 δhoil −0.316 −3.984 0.000 δhoil (−1) −0.042 −2.335 0.021 error correction model (1) −0.481 −4.313 0.000 adj. r2 0.889 d.w stats 2.149 f-stats (prob.) 938.257 (0.000) source: authors’ estimation. ardl: auto regressive distributed lag international heating oil prices are the significant determinants of carbon emission in algeria. likewise, the outcomes affirm that output growth have a positive and significant effect on carbon emission in algeria which implies that as more the economic layachi: effects of energy prices on environmental pollution: testing environmental kuznets curve for algeria international journal of energy economics and policy | vol 9 • issue 5 • 2019406 environment is theorized in accordance the popular economic theory. therefore, keeping in mind the theoretical effect of energy prices in curtailing environmental deterioration, the present study aims to investigate the association between energy prices and environmental pollution in algeria. given the ability of ekc in testing quadratic association, the current study is primarily motivated in testing ekc framework by including energy prices along with income level. in addition, the current study is also important for analyzing the impact of energy prices by testing the effects of three different fuel prices. they include crude oil prices, natural gas prices and heating oil. the data is gathered from the period of 1980-2017. the results of ardl confirm that economic growth has a positive and significant impact on carbon emission in algeria. on the other hand, all energy prices (oil prices, heating oil and natural gas prices) confirm a negative and significant impact on carbon emission in algeria. the results of ardl also confirm a presence of u-shaped ekc curve in the algeria. the results vdm have confirm a bi-directional causal relationship between oil prices and carbon emission, however we found a unidirectional causal relationship from heating oil prices to carbon emission and no causal relationship between natural gas prices and carbon emission in algeria. references adu, d.t., denkyirah, e.k. (2018), economic growth and environmental pollution in west africa: testing the environmental kuznets curve hypothesis. kasetsart journal of social sciences, 30, 1-8. agras, j., chapman, d. (1999), a dynamic approach to the environmental kuznets curve hypothesis. ecological economics, 28(2), 267-277. afshan, s., sharif, a., loganathan, n., jammazi, r. (2018), time frequency causality between stock prices and exchange rates: further evidences from cointegration and wavelet analysis. physica a: statistical mechanics and its applications, 495, 225-244. ali, a., haseeb, m. (2019), radio frequency identification (rfid) technology as a strategic tool towards higher performance of supply chain operations in textile and apparel industry of malaysia. uncertain supply chain management, 7(2), 215-226. alkhathlan, k., javid, m. (2013), energy consumption, carbon emissions and economic growth in saudi arabia: an aggregate and disaggregate analysis. energy policy, 62, 1525-1532. anastacio, j.a.r. (2017), economic growth, co2 emissions and electric consumption: is there an environmental kuznets curve? an empirical study for north america countries. international journal of energy economics and policy, 7(2), 65-71. andreoni, j., levinson, a. (2001), the simple analytics of the environmental kuznets curve. journal of public economics, 80(2), 269-286. apergis, n., payne, j.e. (2015), renewable energy, output, carbon dioxide emissions, and oil prices: evidence from south america. energy sources, part b: economics, planning, and policy, 10(3), 281-287. bah, m.m., abdulwakil, m.m., azam, m. (2019), income heterogeneity and the environmental kuznets curve hypothesis in sub-saharan african countries. geojournal, 7, 1-12. balaguer, j., cantavella, m. (2016), estimating the environmental kuznets curve for spain by considering fuel oil prices (1874-2011). ecological indicators, 60, 853-859. brown, l.r., flavin, c., kane, h., starke, l., abramovitz, j.n., acharya, a., nelson, t. (1996), vital signs 1996: the trends that are shaping our table 6: results of variance decomposition approach period se co2 y oil gas hoil variance decomposition of co2 1 83.369 100.000 0.000 0.000 0.000 0.000 2 116.487 86.148 0.049 11.804 0.766 1.234 3 140.875 74.115 1.420 21.705 0.621 2.139 4 161.551 65.472 2.417 29.014 0.537 2.561 5 178.687 57.250 2.928 36.639 0.457 2.726 variance decomposition of y 1 1.111 0.914 99.086 0.000 0.000 0.000 2 1.313 2.556 85.768 0.004 8.339 3.332 3 1.501 13.729 69.427 0.579 9.904 6.362 4 1.768 27.033 50.810 8.810 7.858 5.489 5 2.069 33.404 37.274 18.568 6.659 4.095 variance decomposition of oil 1 167.533 0.514 26.009 73.477 0.000 0.000 2 208.880 0.485 30.091 65.370 1.900 2.154 3 230.294 7.578 27.604 59.445 1.743 3.630 4 251.130 20.015 23.781 51.181 1.501 3.522 5 269.434 30.388 20.662 44.511 1.326 3.113 variance decomposition of gas 1 16.349 0.390 12.082 31.525 56.004 0.000 2 21.377 0.428 13.692 28.838 57.036 0.006 3 24.638 2.032 11.902 39.012 47.044 0.010 4 27.635 5.060 10.674 44.578 39.675 0.013 5 29.434 8.284 9.950 45.307 36.429 0.030 variance decomposition of hoil 1 696.024 5.480 5.865 1.460 8.476 78.719 2 1160.195 15.576 4.308 0.751 5.111 74.254 3 1552.554 25.282 2.954 0.486 3.326 67.953 4 1901.064 33.441 2.022 0.331 2.319 61.887 5 2218.383 39.695 1.486 0.243 1.705 56.871 source: authors’ estimations layachi: effects of energy prices on environmental pollution: testing environmental kuznets curve for algeria international journal of energy economics and policy | vol 9 • issue 5 • 2019 407 future. new york: earthscan publications. cole, m.a. (2004), trade, the pollution haven hypothesis and the environmental kuznets curve: examining the linkages. ecological economics, 48(1), 71-81. dogan, e., seker, f. (2016), determinants of co2 emissions in the european union: the role of renewable and non-renewable energy. renewable energy, 94, 429-439. dong, k., sun, r., hochman, g. (2017b), do natural gas and renewable energy consumption lead to less co2 emission? empirical evidence from a panel of brics countries. energy, 141, 1466-1478. dong, k., sun, r., hochman, g., zeng, x., li, h., jiang, h. (2017a), impact of natural gas consumption on co2 emissions: panel data evidence from china’s provinces. journal of cleaner production, 162, 400-410. eddrief-cherfi, s., kourbali, b. (2012), energy consumption and economic growth in algeria: cointegration and causality analysis. international journal of energy economics and policy, 2(4), 238-249. gokmenoglu, k.k., taspinar, n. (2018), testing the agriculture-induced ekc hypothesis: the case of pakistan. environmental science and pollution research, 25(23), 22829-22841. grossman, g.m., krueger, a.b. (1991). environmental impacts of a north american free trade agreement nber working paper 3914. national bureau of economic research. haseeb, m., hussain, h.i., ślusarczyk, b., jermsittiparsert, k. (2019), industry 4.0: a solution towards technology challenges of sustainable business performance. social sciences, 8(5), 154. he, f.s., gan, g.g.g., al-mulali, u., solarin, s.a. (2019), the influences of economic indicators on environmental pollution in malaysia. international journal of energy economics and policy, 9(2), 123-131. hettige, h., mani, m., wheeler, d. (2000), industrial pollution in economic development: the environmental kuznets curve revisited. journal of development economics, 62(2), 445-476. jermsittiparsert, k. (2016), culture of elephant front legs-hind legs: a debate on the actuality of sexual politics in thai society. the social sciences, 11(1), 20-28. jermsittiparsert, k., siam, m., issa, m., ahmed, u., pahi, m. (2019), do consumers expect companies to be socially responsible? the impact of corporate social responsibility on buying behavior. uncertain supply chain management, 7(4), 741-752. koengkan, m., losekann, l.d., fuinhas, j.a. (2019), the relationship between economic growth, consumption of energy, and environmental degradation: renewed evidence from andean community nations. environment systems and decisions, 39, 1-13. lacheheb, m., rahim, a.s.a., sirag, a. (2015), economic growth and co2 emissions: investigating the environmental kuznets curve hypothesis in algeria. international journal of energy economics and policy, 5(4), 1125-1132. lekakis, j.n. (2000), environment and development in a southern european country: which environmental kuznets curves? journal of environmental planning and management, 43(1), 139-153. lindmark, m. (2002), an ekc-pattern in historical perspective: carbon dioxide emissions, technology, fuel prices and growth in sweden 1870-1997. ecological economics, 42(1-2), 333-347. lotfalipour, m.r., falahi, m.a., ashena, m. (2010), economic growth, co2 emissions, and fossil fuels consumption in iran. energy, 35(12), 5115-5120. myambo, a., munyanyi, t. (2017), effecetiveness of labour court in labour dispute management in zimbabwe. international journal of social and administrative sciences, 2(1), 15-30. myambo, a., munyanyi, t. (2017), fiscal operations and macroeconomic growth: the nigerian experience. international journal of social and administrative sciences, 2(1), 31-44. nguyen, a.t. (2018), the relationship among economic growth, trade, unemployment, and inflation in south asia: a vector autoregressive model approach. asian journal of economics and empirical research, 5(2), 165-172. obadi, s., kosir, i., korcek, m. (2017), the impact of low oil prices on the trade balance of balkan countries and their energy security. energy economics letters, 4(3), 20-27. okechukwu, o.c., hyginus, o.o. (2017), national security and democratization in nigeria: the case of insurgence. international journal of public policy and administration research, 4(1), 12-18. patel, s.h., pinckney, t.c., jaeger, w.k. (1995), smallholder wood production and population pressure in east africa: evidence of an environmental kuznets curve?. land economics, 71, 516-530. pereira, a.m., pereira, r.m.m. (2010), is fuel-switching a no-regrets environmental policy? var evidence on carbon dioxide emissions, energy consumption and economic performance in portugal. energy economics, 32(1), 227-242. perrings, c. (1998), income, consumption and human development: environmental linkages. background papers, human development report. new york: undp. p151-212. pesaran, m.h., pesaran, b. (1997), working with microfit 4.0: interactive econometric analysis; [windows version]. oxford: oxford university press. pesaran, m.h., shin, y., smith, r.j. (2000), structural analysis of vector error correction models with exogenous i (1) variables. journal of econometrics, 97(2), 293-343. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometrics, 16(3), 289-326. pesaran, m.h., shin, y., smith, r.p. (1999), pooled mean group estimation of dynamic heterogeneous panels. journal of the american statistical association, 94(446), 621-634. rauf, a., liu, x., amin, w., ozturk, i., rehman, o.u., hafeez, m. (2018), testing ekc hypothesis with energy and sustainable development challenges: a fresh evidence from belt and road initiative economies. environmental science and pollution research, 25(32), 32066-32080. sadorsky, p. (2009), renewable energy consumption, co2 emissions and oil prices in the g7 countries. energy economics, 31(3), 456-462. sarkodie, s.a. (2018), the invisible hand and ekc hypothesis: what are the drivers of environmental degradation and pollution in africa? environmental science and pollution research, 25(22), 21993-22022. sarkodie, s.a., strezov, v. (2018), assessment of contribution of australia’s energy production to co2 emissions and environmental degradation using statistical dynamic approach. science of the total environment, 639, 888-899. sasana, h., aminata, j. (2019), energy subsidy, energy consumption, economic growth, and carbon dioxide emission: indonesian case studies. international journal of energy economics and policy, 9(2), 117-122. selden, t.m., song, d. (1994), environmental quality and development: is there a kuznets curve for air pollution emissions? journal of environmental economics and management, 27(2), 147-162. shahbaz, m., dube, s., ozturk, i., jalil, a. (2015), testing the environmental kuznets curve hypothesis in portugal. international journal of energy economics and policy, 5(2), 475-481. shahbaz, m., solarin, s.a., ozturk, i. (2016), environmental kuznets curve hypothesis and the role of globalization in selected african countries. ecological indicators, 67, 623-636. sharif, a., afshan, s., nisha, n. (2017), impact of tourism on co2 emission: evidence from pakistan. asia pacific journal of tourism research, 22(4), 408-421. solarin, s.a., al-mulali, u., ozturk, i. (2017), validating the environmental kuznets curve hypothesis in india and china: the role of hydroelectricity consumption. renewable and sustainable energy reviews, 80, 1578-1587. layachi: effects of energy prices on environmental pollution: testing environmental kuznets curve for algeria international journal of energy economics and policy | vol 9 • issue 5 • 2019408 stern, d.i. (2004), the rise and fall of the environmental kuznets curve. world development, 32(8), 1419-1439. tamazian, a., chousa, j.p., vadlamannati, k.c. (2009), does higher economic and financial development lead to environmental degradation: evidence from bric countries. energy policy, 37(1), 246-253. torras, m., boyce, j.k. (1998), income, inequality, and pollution: a reassessment of the environmental kuznets curve. ecological economics, 25(2), 147-160. umrani, w.a., mahmood, r., ahmed, u. (2016), unveiling the direct effect of corporate entrepreneurship’s dimensions on the business performance: a case of big five banks in pakistan. studies in business and economics, 11(1), 181-195. wang, y., xie, t., yang, s. (2017), carbon emission and its decoupling research of transportation in jiangsu province. journal of cleaner production, 142, 907-914. xie, q., xu, x., liu, x. (2019), is there an ekc between economic growth and smog pollution in china? new evidence from semiparametric spatial autoregressive models. journal of cleaner production, 220, 873-883. zeng, s., nan, x., liu, c., chen, j. (2017), the response of the beijing carbon emissions allowance price (bjc) to macroeconomic and energy price indices. energy policy, 106, 111-121. zhang, b., wang, b., wang, z. (2017), role of renewable energy and nonrenewable energy consumption on ekc: evidence from pakistan. journal of cleaner production, 156, 855-864. . international journal of energy economics and policy | vol 9 • issue 6 • 2019430 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2019, 9(6), 430-438. investigation of causality analysis between economic growth and co2 emissions: the case of brics – t countries seyfettin erdoğan1, durmuş çağrı yıldırım2, ayfer gedikli1* 1istanbul medeniyet university, turkey, 2tekirdağ namık kemal university, turkey. *email: ayfergedikli@yahoo.com received: 10 july 2019 accepted: 20 september 2019 doi: https://doi.org/10.32479/ijeep.8546 abstract the most significant cost of increase in economic growth is an increase in energy consumption and carbon emissions as well. energy consumption triggers carbon dioxide emissions, which is the main cause of environmental pollution. in recent years, struggling with climate changes, global warming and carbon dioxide emissions based environmental problems became critical issues. in doing so, this study investigates the relationship between carbon emissions and economic growth for brics-t countries for the period of 1992-2016. we apply pedroni and, westerlund and edgerton panel cointegration approaches for examining cointegration between the variabes. the fully-modified ols approach is applied for testing long-term relationship between economic growth and carbon emissions. the empirical results indicate that a 1% increase in economic growth increases carbon emissions by 0.79% but 1% increase in carbon emissions leads economic growth by 0.5%. the causality analysis reveals the presence of bidirectional relationship between carbon emissions and economic growth. keywords: carbon emissions, economic growth, brics-t countries jel classifications: p52, o10 1. introduction issues such as global warming and climate changes resulting from environmental pollution because of poisonous gases have been at the top of agenda in national and international levels in recent years. actually, co2 emissions have two basic sources. the first source is the combustion of fossil fuels such as coal and crude oil. the second source is industrial processes that release co2 as a result of a chemical reaction and production. there are pros and cons for the countries while following the footprints of industrialization and economic growth. in most cases, there is a trade-off between a sustainable economic growth and clean environment. increasing energy consumption for more economic activities brings increasing carbon emissions which is the basic reason of greenhouse effects and climate changes. in existing literature, the relationship between environmental pollution and economic growth is explained by environmental kuznets curve (ekc). the ekc hypothesis, takes it roots from kuznets curve which explained the relationship between economic growth and income inequality (kuznets, 1955). the kuznets curve implies that as an economy grows from lower income to higher income level, income inequality first increases. after reaching a turning point, income inequality declines. similarly, according to ekc hypothesis, environmental pollution increases until economic growth reaches its peak; then it turns to decrease with an increase in economic growth over time. economic development experience of almost every country shows that it is more reasonable to increase economic growth rather than environmental problems in early stages of industrialization. although there is limited environmental degradation at early stages of economic development, increasing economic activities impact environment quality negatively. increase in per capita income, completion of infrastructure investment with economic and social aspects, and providing a better standard of living have higher priority than dealing with environmental problems. accordingly, parallel to the higher this journal is licensed under a creative commons attribution 4.0 international license 10097885312 *this article is an extended version of the paper presented in enscon (international congress of energy, economy and security) held in istanbul between 10-11 november 2018." erdoğan, et al.: investigation of causality analysis between economic growth and co2 emissions: the case of brics – t countries international journal of energy economics and policy | vol 9 • issue 6 • 2019 431 income levels, there will be more environmental expenditures, higher environmental awareness, and demand for qualified and clean environment. so, ekc model reflects an economic structure change in the share of agriculture, industry and service. strategies to protect environment are being developed just after reaching this level. that process ends with a steady decrease in environment degradation (yang et al., 2015, panayotou, 2003). in fact, kuznets curve summarizes a dynamic process of changes. environmental degradation increases at early stages of economic growth, and then gradually it starts to decrease as economic growth reaches a better level with a higher income per capita. this shows that pollution or environmental impact per capita is an inverted u-shaped between income per capita and carbon emissions (shahbaz et al., 2015). the pioneering research on ekc hypothesis was published by grossman and krueger (1991). grossman and krueger (1991) noted that there are always some pollutants which are the natural byproduct of economic activity such as operation of motor vehicles or wastes of production process at the factories. carbon emissions incraeses with economic activity. grossman and krueger (1991) explained that it is possible to observe the environmental impacts of the reduction of commercial barriers and commercial liberalization in three ways. the first way is the expansion of scale economy i.e. scale effect. despite the expansion of the volume of economic activity with the liberalization of trade and investment, environmental degradation will be inevitable if the structure and, content of manufacturing and production do not change. additionally, an increase in volume of foreign trade will lead to the expansion of international transportation and if necessary measures are not taken which in resulting, affacte air quality. the second way is the effect of change in composition of economic activity i.e. composition effect which reveals that countries are more likely to be attracted to sectors where they can benefit from competitive advantages. at this point, the reasons for which competitive advantages are based are important. if production decisions are made by making use of the differences and inconsistencies in environmental measures, increase in environmental pollution will be inevitable. the third way is the changes in production technologies i.e. technique effect. on other hand, foreign direct investment increases with liberalization of trade, may contribute to decrease in amount of pollution per production by leading to changes in production techniques. namely, environmental problems of less developed countries will be reduced if foreign investors bring their modern technologies that are less polluting to target countries. in addition, if income level increases in the country where liberalization occurs, there will be more social demands and expectations of society. as the income level increases, social sensitivity to clean environment increases (grossman and krueger, 1991). similarly, elden and song (1994) identified inverted-u relationship between environment pollution and economic growth. they found that four pollutant gas emissions have inverted-u relationship with per capita gdp. it is fact that brics-t countries showed a great economic performance in last three decades. however, having a remarkable economic growth triggered environmental problems and increasing carbon emissions. as an example china has been ranked as the second largest economy with its 20% of world’s gdp. parallel to this level of economic growth, the country is the greatest global carbon emissions emitter by releasing 40% of global co2 emissions (dong et al., 2017). however, output growths or poor environment protection policies are not the only reasons of increasing carbon emissions. in their study, wang et al. (2018) pointed that in brics countries, corruption is one of the most serious reasons of increasing carbon emissions. so, corruption controlling policies in those countries will also lead reduction in carbon emissions. alam et al. (2016) found that in come and energy usage show relationships with carbon emission in bric countries. this study contributes to existing literature by two folds: (i) we prefer to apply panel data approaches for empirical analysis. previous studies on the relationship between carbon emissions and output have problems with empirical methods applied for analysis. since data for carbon emission is collected annually, number of observations is limited and time dimension decreases. to overcome this issue, panel data approaches can be a good alternative for empirical analysis. in panel data analysis, degree of freedom and efficiency of empirical estimations increase. thus, more reliable and stable parameter estimations can be made. in doing so, we have applied westerlund and edgerton (2008) cointegration test for examining cointegration relationship between economic growth and carbon emissions. further, fully-modified ols (fmols) approach is applied to find long run effect of economic growth on carbon emissions and vice versa. (ii) previous studies analyzed the relationships between carbon emissions and economic growth excluding turkish economy. this study examines the relationship between economic growth and carbon emissions for brics countries including turkish economy for empirical analysis. our empirical evidence confirms the presence of cointegration between the variables. moreover, a bidirectional relationship between carbon emissions and economic growth is also noted. 2. literature review since the pioneer study of kraft and kraft (1978) that investigated the linkage between energy consumption and gross national product, economic growth and co2 emissions causality nexus has been considered as one of the growing debates in theoretical and empirical literature. thus, environmental economists, researchers and policy makers have been examining the relationship between co2 emissions and economic growth to implement reasonable policies in order to have sustainable economic development with clean environment. in recent years, not only the degree of the relationship between economic growth and co2 emissions, but also the direction of the causality still remains one of the debated issues. the findings of different country cases or country groups vary from each other; the results are even controversial that deprive the policy makers from implementing certain policies. in this paper, the literature about the causality between economic growth and co2 emissions is reviewed under four subsections: 1) causality running from economic growth to co2 emissions; 2) causality running from co2 emissions to economic growth; 3) no causality nexus between co2 emissions and economic growth (neutrality); 4) bidirectional causality between co2 emissions and economic growth (ozturk, 2010). erdoğan, et al.: investigation of causality analysis between economic growth and co2 emissions: the case of brics – t countries international journal of energy economics and policy | vol 9 • issue 6 • 2019432 2.1. growth-led emissions hypothesis in their high coverage study, wang (2013) studied 138 countries for 1971-2007 period in order to validate the relationship between co2 emissions and economic growth. the empirical results reveal that economic growth is the main reason for rising carbon dioxide emissions. similarly, gao and zhang (2014) investigated 14 subsaharan african countries for the period of 1980-2009. they confirmed the presence of a unidirectional causality relationship running from economic growth to co2 emissions. kaisi and mbarek (2017) reached the same empirical result for african countries: algeria, egypt and tunusia for the period of 1980-2012. zhang et al. (2014) examined the impact of economic growth, industrial structure and urbanization on carbon emissions intensity in china based on the data from 1978 to 2011. lee and yoo (2016) investigated the short run and long run causality issues among co2 emissions, economic growth and energy consumption in mexico for the period of 1971-2007. both studies showed that co2 emissions are cause of economic growth. lu (2017) also reported the economic growth led carbon emissions for 1990-2012 period, using panel data for 24 asian countries. aye and edoja (2017) examined the economic growth-carbon emissions nexus for a panel of 31 developing countries using data from 1973 to 2013. their results indicated that economic growth has a negative impact on co2 emissions in the low growth regime whereas it has a positive effect in the high growth regime because of higher marginal effect. deviren and deviren (2016) collected data for 33 countries over the period 1970-2010 and noted that in highly developed countries, economic growth is accompanied with high carbon emissions. similarly, mikayilov et al. (2018) investigated the relationship between economic growth and co2 emissions for azerbaijan over the period of 1992-2013. they found that economic growth has a significant and positive impact on co2 emissions. bouznit and pablo-romero (2016) validated the growth led emissions hypothesis in case of algeria for the period of 1970-2010. li et al. (2018) also collected data for 30 chinese provinces for the period of 2004-2016 to examine relationship between economic growth and carbon emissions by including fdi, high-tech industry, and population as additional determinants. they noted that economic growth, high-tech industry, fdi and population have a direct effect on carbon emissions. dong et al. (2017) investigated the growth-emissions nexus by adding natural gas consumption and renewable energy consumption in emissions function for brics countries. they found the presence of unidirecitonal causality running from economic growth to carbon emissions in short run. similarly, nuryartono and rifai (2017) also note that economic growth causes carbon emissions in indonesia and thailand. for eu countries, kasperowicz (2015) reported the presence of grothled-emissions hypothesis in short run. 2.2. emissions-led growth hypothesis joo et al. (2015) investigated the short-term and long-term causality nexus between energy consumption, co2 emissions, and economic growth in chile. their empirical evidence indicated that co2 emissions granger cause economic growth. similarly, asumadusarkodie and owusu (2016) examined the causal relationship between carbon dioxide emissions, electricity consumption, industrialization and economic growth for benin for the period 1980-2012 and reported the presence of emissions-led growth hypothesis. chindo et al. (2015) investigated the cointegration relation between co2 emissions, economic growth and energy consumption in nigeria over the period of 1971-2010. they noted that that co2 emissions has a significant and positive impact on gdp i.e. an increase in co2 emissions causes to increase in gdp. lee and yoo (2016) investigated short run and long run causality relationship in korea and cofnirmed the presence of unidirectional causlaity runnig from carbon emissions to economic growth which latter validated by ahmad and du (2017). in case of g20 countries, pao and chen (2019) reported that economic growth granger causes carbon emissions. alshehry and belloumi (2015) examined the dynamic causal relationship between energy consumption, carbon dioxide emissions, energy price and economic growth and noted the presence of emissions-led growth hypothesis.similarly, pao and tsai (2010) for bric countries, ozturk and uddin (2012) for india, bozkurt and akan (2014) for turkey, obradović and lojanica (2017) for greece and bulgaria also reported that economic growth is cause of carbon emissions in the long-run. 2.3. bidirectional causality nexus between economic growth and co2 emissions various studies using various countries data reported the presence of feedback effect between eocnomic growth and carbon emissions. for example, yansui et al. (2016) investigated the relationship between urbanization, economic growth and co2 emissions for 31 provinces of china over the period of 1997-2010. they found feedback effect between carbon emissions and ecoomic growth although urbanization has significant effect on co2 emissions. al-mulali and che sab (2018) examined co2 emissions economic growth nexus by including eletricty consumption as additional determinanat in emissions function for the middle east countries. their panel causality analysis revealed that economic growth and carbon emissions are interdependent. in case of italy, magazzino (2016) reported that economic growth causes carbon emissions and in resulting, carbon emissions cause economic growth in granger sense. for brics countries, haseeb et al. (2018) examined causal relationship between economic growth and carbon emissions by including financial development, globalization, energy consumption, and urbanization in emissions function. their empirical results showed the presence of feedback effect between economic growth and carbon emissions. the bidirectional causality also exists between carbon emissions and economic growth reported by long et al. (2015) for china, yang and zhao (2014) for india, sebri and ben-salha (2014) for brics countries, and tamba (2017) for cameron. 2.4. no causality between economic growth and co2 emissions very few studies also reported nuetral effect between carbon emissions and economic growth. for example, salahuddin and khan (2013) examined the causal relationship between economic growth, energy consumption and co2 emission in australia and indicated that carbon emissions and economic growth are independent. ozturk (2015) found that ekc hypothesis in not exists in brics countries. azevedo et al. (2018) used the brics countries data to examine the causal association between carbon emissions and economic growth. they found that neither carbon emissions cause economic growth nor economic growth cause erdoğan, et al.: investigation of causality analysis between economic growth and co2 emissions: the case of brics – t countries international journal of energy economics and policy | vol 9 • issue 6 • 2019 433 carbon emissions. gorus and aydın (2019) studied eight oil-rich mena countries (algeria, egypt, iran, iraq, oman, saudi arabia, tunusia and the uae) for the period of 1975-2014. thier empirical results show the presence of nuetral effect between carbon emissions and economic growth. 3. the data and estimation strategy 3.1. data set and methodology this study analyzes the relationship between carbon emissions and economic growth for brics-t countries for the period of 1992-2016. brics-t countries (brazil, russia, india, china, south africa and turkey) have recently appeared with their rapid growth performances. the growth performance of brics-t countries has progressed way more than leading industrial countries in the world. relatively high growth is accompanied with carbon emissions and thus high level of environmental pollution. data were collected from the world bank and international energy agency. while investigating the relationship between carbon emissions and economic growth, it is seen that there might be problems related to the methods applied for empirical analysis. due to the annual collection of data for carbon emissions, observation number remains relatively low and time dimension decreases. in order to overcome this problem, panel data analysis methods can be applied for empirical analysis. this is because panel data analysis produces stronger results when compared to time series methods. al-mulali (2011) stated that panel data could control individual heterogeneity unlike time series and cross-sectional data. in panel data analysis, the connection between the explanatory variables gets weaker. consequently, degree of freedom and efficiency of the estimations increase. thus, more reliable and stable parameter estimations can be made. one of the important problem in panel data analysis is the interdependence among the individual units (countries). this problem is called cross-section dependence. since cross-section interdependence causes incorrect interpretations and the efficiency of test statistics to decrease, cross-section dependence was studied by using two different test statistics in our study: breusch-pagan lagrange multiplier (lm) and pesaran cd tests. the null hypothesis and test statistic stating that there is no cross-section dependence for the breusch-pagan lm test is as follows (baltagi, 2001): 1 ( ) :1 i p j i ijj l l  =∑ 2 0 : 0h  = (1) ( ) 2 2 2 1 1 1 ( / 2( 1)) / 1 n n t i iti i t lm nt t e e = = =  =   ∑ ∑ ∑  (2) the pesaran cd test statistic assuming there is no cross-section dependence in the null hypothesis is calculated as follows: 1 , 1 1 2 ˆ (0,1) ( 1) n n i j i j i t cd n n n  = = +   = ⇒   ∑ ∑   (3) stationarity of the series is important in the selection of estimation models. in the present study, stationarity conditions of the series will be investigated following the examination of cross-section dependence. of the most common methods in the research of stationarity conditions, llc and ips tests were used. these methods have the assumption that the series does not have cross-section dependence. also, o’connell (1998) indicated that the possibility to reject the null hypothesis increased in panel unit root tests in case of cross-section dependence among the series. in this context, pesaran (2007) suggested a unit root test that considers cross-section dependence, which is called pesaran cross-sectionally-augmented dickey fuller (cadf) test panel unit root test. this test is the one that allows the investigation of stationarity conditions of crosssection and panel data that can be used when t> n and n> t. the long term relationship among the series will be analyzed by using pedroni panel cointegration method. the pedroni cointegration method used frequently in the literature is a first generation analysis method and has some drawbacks. firstly, due to the structural break problem in panel data analysis, the estimation results of relationship among the series can show fake regression. if the time series dimension is very long, the problem of fake regression increases. the time dimension is relatively long. another problem is that cross-section dependence previously mentioned is frequently seen in panel data models. the first generation panel data methods assume that cross-section dependence does not exist. the second generation tests take these problems into consideration (groen and kleibergen, 2003; banerjee and carrion-i-silvestre, 2006; westerlund, 2006). 3.2. westerlund and edgerton (2008) panel cointegration test methodology westerlund and edgerton (2008) developed a test that allows crosssection dependence for panel data analysis, multi structural break at an unknown date in both constant and slope of cointegrated vector, and heteroscedasticity and series-correlation of error terms. we will use the pedroni cointegration methodology and the westerlund and edgerton (2008) methodology. westerlund and edgerton (2008) developed a panel cointegration test derived from the lm based unit root tests developed by schmidt and phillips (1992), ahn (1993) and amsler and lee (1995). this test allows for the unknown breaks in both constant and trend of the cointegrated regression, individual-specific constant and trend effects, crosssection dependence and heteroscedastic and auto-correlated error terms. yit variable can be calculated as follows: y t d x t d x zit i i i it it it it i it= + + + + ′ + ′α θ δ γ( ) (4) xit = xit−1+wit (5) k-sized vector xit variable was modelled according to the pure random walk process. in the equation, dit is the dummy variable representing a structural break (dit=1→t>ti and otherwise 0). in this case, αi and βi represent the constant and trend before the break period. δi and γi show the change in the constant and trend in the break period. with the use of the unobserved common factors of zit it is assumed to have the following data production process that allows for cross section dependence. erdoğan, et al.: investigation of causality analysis between economic growth and co2 emissions: the case of brics – t countries international journal of energy economics and policy | vol 9 • issue 6 • 2019434 '= +it i t itz f v (6) 1it i it itf f = + (7) ( )i it i it itl v v e ∆ = + (8) where 1( ) :1 ip j i ijj l l  =∑ is a scalar polynomial in the lag operator l. ft is r sized vector of the unobserved common factors ft (j=1,...,r). for all j’s when it is assumed that ρi<1 the stationarity of ft is provided. in this case, the order of integration of composite regression error zit will only be dependent upon idiosyncratic disturbance vit. in conclusion, as for the relationship in equation-8, if ϕi<0, it is cointegrated and if ϕi = 0, it expresses a dummy relationship. in case that a cointegrated relationship among the series is determined, it is necessary to investigate the direction and size of relationship among the series. in case of long term relationships among the pedroni (1999; 2000) series, panel estimators are biased and inconsistent. therefore, pedroni suggested the fmols methodology in existence of cointegrated relationship. 4. empirical analysis this study analyzes the relationship between carbon emissions and economic growth for brics-t countries (brazil, russia, india, china, south africa and turkey) for the period 1992-2016. the variables were transformed into natural logarithm. our panel data set is balanced. before analyzing the stationarities of the series, cross-section dependence conditions of the series were analyzed. the results can be seen in annex 1 and 2. according to the results, the null hypothesis is rejected and cross-section dependence exits. in the results obtained for unit root analysis in case of cross-section dependence, the likelihood to reject the null hypothesis increases. therefore, the stationarity conditions of the series were examined by using the cadf and breitung test. tables 1 and 2 indicate the cadf and breitung test results respectively. in table 1, pesaran cadf test results are indicated for 5 lags. it was concluded that real output series was not stationary for intercept and intercept and trend model except first lag of intercept model. the results are complex for carbon emissions. while the basic hypothesis was rejected for the intercept model, it was not rejected for the trend model. so, breitung test was also used for analyzing the stationarity of the series. in case of cross sectional dependency, breitung test allows stationary analysis by robust estimators for the series which have homogenious and heterogenous unit effects. test results are illustrated in table 2. according to table 2 results, both real output and carbon emissions series are difference stationary for intercept and intercept and trend models. economic growth and carbon emissions are found stationary at first difference with intercept and trend. the unique stationarity properties of the variables leads us to apply panel cointegration approach for long run relationship between economic growth and carbon emissions. in doing so, we have applied the pedroni panel cointegration approach and results are shown in table 3. the empirical results reported in table 3, show a relationship only according to panel v-statistic, whereas the other 6 test statistics imply that no cointegration relationship between the variables. as economic growth is treated as dependent variable, it is seen that cointegration relationship exists following panel v-statistic and rest empirical results show the absence of cointegration between the variables. this shows that cointegration is not present following pedroni cointegration approach. the empirical results by pedroni cointegration approach are ambiguous for not considering structural breaks and cross-section dependence stemming in the variables for examining cointegration relationship. further, pedroni cointegration test does not allow for heteroscedasticity and autocorrelation of error terms and individual-specific constant and trend effects. therefore, westerlund and edge (2008) panel cointegration is suitable considering mentioned issues while investigating cointegration between the variables and results are detailed in table 3. in table 4, we reported empirical results, economic growth is treated as dependent variable. the empirical results by pedroni cointegration show no cointegration between the variables. in structural break models, estimations up to 5 breaks are made. the empirical results for breaks in regime model show the existence of a long run cointegration relationship between economic growth and carbon emissions. as we consider, carbon emissions is our dependent variable, empirical evidence shows the absence of cointegration between economic growth and carbon emissions with level breaks stemming in the series. however, in the presence of single break in the series, we note the presence of cointegrating relationship between the variables. this validates that economic growth and carbon emissions are cointegrated for table 1: pesaran cadf panel unit root test results variables without trend with trend lags zt-bar p-value lags zt-bar p-value lngdp 1 −3.252 0.001 1 −0.775 0.219 2 −1.137 0.128 2 −0.841 0.200 3 −0.109 0.457 3 1.433 0.924 4 −1.038 0.150 4 1.934 0.973 5 0.038 0.515 5 2.178 0.985 lnco2 1 −2.388 0.008 1 1.131 0.871 2 −3.122 0.001 2 −0.120 0.452 3 −3.336 0.000 3 0.011 0.505 4 −1.164 0.122 4 0.965 0.833 5 −2.334 0.010 5 1.564 0.941 cadf: cross-sectionally-augmented dickey fuller table 2: breitung panel unit root test results method lngdp lnco2 intercept trend and intercept intercept trend and intercept statistic prob. statistic prob. statistic prob. statistic prob. breitung 6.777 1.000 0.960 0.832 4.777 1.000 1.221 0.889 erdoğan, et al.: investigation of causality analysis between economic growth and co2 emissions: the case of brics – t countries international journal of energy economics and policy | vol 9 • issue 6 • 2019 435 long run relationship in case of bric-t countries. the presence of cointegration between economic growth and carbon emissions suggests to examine long run effect of economic growth (carbon emissions) on carbon emissions (economic growth). in doing so, we have applied fmols approach to examine long run effects. the empirical results reported in table 5 show that a 1% increase in economic growth raises carbon emissions by 0.79%. moreover, a 1% increase in carbon emission leads economic growth by 0.94. these empirical results are similar with sebri and ben-salha (2014), haseeb et al. (2018) who noted the presence of cointegration between economic growth and carbon emissions. as illustrated in appendix 1, with its high gdp growth and high carbon emissions, china showed a discrete performance in gdp per capita and carbon emission series from the other countries in brics-t country group. comparing with china, india and russia had less carbon emissions level. brazil, south africa and turkey had a positive trend in their real output performance and higher economic growth for the period of 1990-2016 but showed lower carbon emissions levels comparing with china, russia and india. contrary, comparing with those three countries, india showed a lower economic growth with higher carbon emissions. natural logarithm was used in the empirical analysis. 5. conclusion and policy implications this paper investiagted the causality nexus between carbon emissions and economic growth in rapid growing brics-t countries (brazil, russia, india, china, south africa and turkey) using data for the period of 1992-2016. in doing so, pedroni (2000) westerlund and edgerton (2008) panel cointegration approaches are applied to examine cointegration between eocnomic growth and carbon emissions. the empirical results confirm the presence of cointegration between economic growth and carbon emissions. furthermore, a 1% increase in economic growth leads carbon emissions 0.79% and in resulting, a 1% incraese in carbon emissions increases economic growth by 0.5%. the panel cointegration analysis reveals the presence of bi-directional causal relationship between carbon emissions and economic growth. in developing countries, like brics-t countries, there is a tradeoff between economic growth and environment degradation. this confirms the presence of macroeconomic and social costs associated with growth-pollution feedback relation. higher economic growth, more carbon emissions and visa versa. those countries do not pay great attention to protect environmental quality or implement strict environment protectionist measures. the governments even sacritifice environmental quality to achieve higher economic growth. they also allow polluting industries to have cost advantageous investments for foreign capital investment. furthermore, sample countries other than turkey have energy production from oil/fossil fuels which is highly related to environment pollution. neverthless, it is a fact that polluting environment and increased carbon emissions create barriers to achieve sustainable development goals. furthermore, it may have a higher price to neutralize the negative externalities of pollution-based economic growth. increased carbon emissions and degraded environement not only negatively affect the health of labor force but also, there will be no livable environment for the next generations. by keeping in mind all these side effects of environment degradation, brics-t countries should implement more efficient and clean energy policies. besides, these countries should improve table 3: pedroni panel cointegration test results dependent variable: lnco2 dependent variable: lngdp within-dimension statistic prob. within-dimension statistic prob. panel v-statistic 1.437 0.075 panel v-statistic 3.957 0.000 panel rho-statistic 0.847 0.801 panel rho-statistic 0.505 0.693 panel pp-statistic 1.064 0.856 panel pp-statistic −0.08 0.468 panel adf-statistic −0.483 0.314 panel adf-statistic −0.072 0.471 between-dimension statistic prob. between-dimension statistic prob. group rho-statistic 1.513 0.934 group rho-statistic 1.670 0.952 group pp-statistic 1.219 0.888 group pp-statistic 0.792 0.785 group adf-statistic −0.705 0.240 group adf-statistic −0.01 0.495 adf: augmented dickey fuller table 4: westerlund and edge (2008) panel cointegration test results dependent variable: lngdp zτ (n) zφ (n) model value p-value value p-value no break 0.819 0.794 0.824 0.795 level break −0.715 0.237 −0.45 0.326 regime shift −2.131 0.017 −1.359 0.087 dependent variable: lnco2 zτ (n) zφ (n) model value p-value value p-value no break −0.911 0.181 −0.869 0.193 level break −2.663 0.004 −2.822 0.002 regime shift 0.309 0.621 0.376 0.646 table 5: fmols test results dependent variable: lngdp variable coefficient std. error t-statistic prob. lnco2 0.942 0.075 12.541 0.000 dependent variable: lnco2 variable coefficient std. error t-statistic prob. lngdp 0.790 0.063 12.428 0.000 fmols: fully-modified ols erdoğan, et al.: investigation of causality analysis between economic growth and co2 emissions: the case of brics – t countries international journal of energy economics and policy | vol 9 • issue 6 • 2019436 new techologies for cleaner and more efficient energy mix to ensure sustainable environment with economic growth. the countries should also have an energy transition which have higher renewable energy proportion in total energy mix. namely, every country should creat its own national energy policy on the basis of energy mix, energy resources and needs for energy-growth relationship. foreing direct investment is critical for developing countries to sustain economic growth. it is also important that while inviting foriegn investors, the governments should be aware of nonpolluting and environmental friendly investments are accepted. accordingly, the governments should implement environment protectionist measures and regulations for foreing direct investment and domestic investment in order to have a sustainable development with clean environment. and also, while struggling against carbon dioxide emissions caused by the continuation of production by conventional energy sources, governments should implement convenient energy policies that will activate the alternative energy resources in order not to decrease the growth rates. it is also necessary to disseminate energy saving models in urban and rural transformation processes, to support the use of modern technology instead of old technologies that lead to high pollution, to ensure the transformation of low value added companies and sectors that harm the environment, and to support the education activities that improve environmental awareness. all in all, it is highly recommended to investigated countries to improve energy productivity by increasing energy efficiency, implementing new energy saving projects (smart cities, efficient urban transformations, new energy saving technologies, more convenient public transportation etc), more qualified energy infrastructure and energy conservation to reach higher economic growth levels with sustainable environment and less carbon emissions. references ahmad, n., du, l. (2017), effects of energy production and co2 emissions on economic growth in iran: ardl approach. energy, 123, 521-537. ahn, s.k. (1993), some tests for unit roots in autoregressive-integratedmoving average models with deterministic trends. biometrica, 80(4), 855-868. alam, m.m., murad, m.w., noman, a.h.m., ozturk, i. (2016), relationships among carbon emissions, economic growth, energy consumption and population growth: testing environmental kuznets curve hypothesis for brazil, china, india and indonesia. ecological indicators, 70, 466-479. al-mulali, u. (2011), oil consumption, co2 emission and economic growth in mena countries. energy, 36, 6165-6171. al-mulali, u., sab, c.n.b. (2018), electricity consumption, co2 emission, and economic growth in the middle east. energy sources, part b: economics, planning, and policy, 13(5), 257-263. alshehry, a.s., belloumi, m. (2015), energy consumption, carbon dioxide emissions and economic growth: the case of saudi arabia. renewable and sustainable energy reviews, 41, 237-247. amsler, c., lee, j. (1995), an lm test for a unit root in the presence of a structural change. econometric theory, 11(2), 359-368. asumadu-sarkodie, s., owusu, p.a. (2016), carbon dioxide emission, electricity consumption, industrialization, and economic growth nexus: the beninese case. energy sources, part b: economics, planning, and policy, 11(11), 1089-1096. aye, g.c., edoja, p.e. (2017), effect of economic growth on co2 emission in developing countries: evidence from a dynamic panel threshold. cogent economics and finance, 5, 1-22. available from: https:// www.cogentoa.com/article/10.1080/23322039.2017.1379239. azevedo, v.g., sartori, s., campos, l.m.s. (2018), co2 emissions: a quantitative analysis among the brics nations. renewable and sustainable energy reviews, 81, 107-115. baltagi, b.h. (2001), econometric analysis of panel data. 2nd ed. new york: john wiley and sons. banerjee, a., carrion-i-silvestre, j.l. (2006), cointegration in panel data with breaks and cross-section dependence, european central bank working paper series, 591. bouznit, m., maríadel, p.p. (2016), co2 emission and economic growth in algeria. energy policy, 96, 93-104. bouznit, m., pablo-romero, m. del p. (2016), co2 emission and economic growth in algeria. energy policy, 96, 93-104. bozkurt, c., akan, y. (2014), economic growth, co2 emissions and energy consumption: the turkish case. international journal of energy economics and policy, 4(3), 484-494. chindo, s., abdulrahim, a., waziri, s.i., huong, w.m., ahmad, a.a. (2015), energy consumption, co2 emissions and gdp in nigeria. geojournal, 80, 315-322. deviren, s.a. and deviren, b. (2016). the relationship between carbon dioxide emission and economic growth: hierarchical structure methods. physica a: statistical mechanics and its applications, 451, 429-439. dong, k., renjin, s., gal, h. (2017), do natural gas and renewable energy consumption lead to less co2 emission? empirical evidence from a panel of brics countries. energy, 141, 1466-1478. elden, t., song, t.m. (1994), environmental quality and development: is there a kuznets curve for air pollution emissions? journal of environmental economics and management, 27(2), 147-162. gao, j., zhang, l. (2014), electricity consumption economic growthco2 emissions nexus in sub-saharan africa: evidence from panel cointegration. african development review, 26(2), 359-371. gorus, m., sehid, m.a. (2019), the relationship between energy consumption, economic growth, and co2 emission in mena countries: causality analysis in the frequency domain. energy, 168, 815-822. groen, j.j.j., kleibergen, f. (2003), likelihood-based cointegration analysis in panels of vector error-correction models. journal of business and economic statistics, 21, 295-318. grossman, g.m., krueger, a.b. (1991), environmental i̇mpacts of a north american free trade agreement, nber working paper, 3914. haseeb, a., xia, e., danish, baloch, m.a., abbas, k. (2018), financial development, globalization, and co2 emission in the presence of ekc: evidence from brics countries. environmental science and pollution research, 25, 31283-31296. joo, y.j., kim, c.s., yoo, s.h. (2015), energy consumption, co2 emission, and economic growth: evidence from chile. international journal of green energy, 12, 543-550. kaisi, s., mbarek, m.b. (2017), dynamic relationship between co2 emissions, energy consumption and economic growth in three north african countries. international journal of sustainable energy, 36(9), 840-854. kasperowicz, r. (2015), economic growth and co2 emissions: the ecm analysis. journal of international studies, 8(3), 91-98. kraft, j., kraft, a. (1978), relationship between energy and gnp. journal of energy, finance and development, 3(2), 401-403. kuznets, s. (1955), economic growth and income inequality. the erdoğan, et al.: investigation of causality analysis between economic growth and co2 emissions: the case of brics – t countries international journal of energy economics and policy | vol 9 • issue 6 • 2019 437 american economic review, 45(1), 1-28. lee, s.j., yoo, s.h. (2016), energy consumption, co2 emission, and economic growth: evidence from mexico. energy sources, part b: economics, planning, and policy, 11(8), 711-717. lee, s.r., yoo, s.h. (2016), energy consumption, co2 emissions, and economic growth in korea: a causality analysis. energy sources, part b: economics, planning, and policy, 11(5), 421-417. li, l., hong, x., peng, k. (2018), a spatial panel analysis of carbon emissions, economic growth and high-technology industry in china. structural change and economic dynamics. available from: https://www.sciencedirect.com/science/article/abs/pii/ s0954349x18301838. long, x., naminse, e.t., du, j., zhuang, j. (2015), nonrenewable energy, renewable energy, carbon dioxide emissions and economic growth in china from 1952 to 2012. renewable and sustainable energy reviews, 52, 680-688. lu, w.c. (2017), renewable energy, carbon emissions, and economic growth in 24 asian countries: evidence from panel cointegration analysis. environmental science and pollution research, 24, 26006-26015. magazzino, c. (2016), the relationship between co2 emissions, energy consumption and economic growth in italy. international journal of sustainable energy, 35(9), 844-857. mikayilov, j.i., galeotti, m., hasanov, j. (2018), the impact of economic growth on co2 emissions in azerbaijan. journal of cleaner production, 197, 1558-1572. nuryartono, n., rifai, m.a. (2017), analysis of causality between economic growth, energy consumption and carbon dioxide emissions in 4 asean countries. international journal of energy economics and policy, 7(6), 141-152. o’connell, p.g.j. (1998), the overvaluation of purchasing power parity. journal of international economics, 44(1), 1-19. obradović, s., lojanica, n. (2017), energy use, co2 emissions and economic growth-causality on a sample of see countries. economic research, 30(1), 511-526. ozturk, i. (2010), a literature survey on energy growth nexus. energy policy, 38(1), 340-349. ozturk, i. (2015), sustainability in the food-energy-water nexus: evidence from brics (brazil, the russian federation, india, china, and south africa) countries. energy, 93, 999-1010. ozturk, i., uddin, g.s. (2012), causality among carbon emissions, energy consumption, and growth in india. economic research, 25(3), 752-775. panayotou, t. (2003), economic growth and the environment. geneva: spring seminar of united nations economic comission for europe. available from: https://www.unece.org/fileadmin/dam/ead/sem/ sem2003/papers/panayotou.pdf. pao, h.t., chen, c.c. (2019), decoupling strategies: co2 emissions, energy resources, and economic growth in the group of twenty. journal of cleaner production, 206, 907-919. pao, h.t., tsai, c.m. (2010), co2 emissions, energy consumption and economic growth in bric countries. energy policy, 38, 7850-7860. pedroni, p. (1999), critical values for cointegration tests in heterogeneous panels with multiple regressors. oxford bulletin of economics and statistics, 61, 653-670. pedroni, p. (2000), fully modified ols for heterogeneous cointegrated panels, williams college, department of economics working papers 2000-03. pesaran, m.h. (2007), a simple panel unit root test in the presence of cross-section dependence. journal of applied econometrics, 22(2), 265-312. salahuddin, m., khan, s. (2013), empirical link between economic growth, energy consumption and co2 emission in australia. the journal of developing areas, 47(2), 81-92. schmidt, p., phillips, p.c.b. (1992), lm tests for a unit root in the presence of deterministic trends. oxford bulletin of economics and statistics, 54(3), 257-287. sebri, m., ben-salha, o. (2014), on the causal dynamics between economic growth, renewable energy consumption, co2 emissios and trade openness: fresh evidence from brics countries. renewable and sustainable energy reviews, 39, 14-23. shahbaz, m., dube, s., ozturk, i., jalil, a. (2015), testing the environmental kuznets curve hypothesis in portugal. international journal of energy economics and policy, 5(2), 475-481. tamba, j.g. (2017), energy consumption, economic growth, and co2 emissions: evidence from cameroon. energy sources, part b: economics, planning, and policy, 12(9), 779-785. wang, k.m. (2013), the relationship between carbon dioxide emissions and economic growth: quantile panel-type analysis. quality and quantity: international journal of methodology, 47(3), 1337-1366. wang, z., danish, zhang, b., wang, b. (2018), the moerating role of corruption between economic growth and carbon emissions: evidence from brics economies. energy, 148, 506-513. westerlund, j. (2006). testing for panel cointegration with multiple structural breaks. oxford bulletin of economics and statistics, 68(1), 101-132. westerlund, j., edgerton, d.l. (2008), a simple test for cointegration in dependent panels with structural breaks. oxford bulletin of economics and statistics, 70(5), 665-704. yang, g., sun, t, wang, j, li, x. (2015), modeling the nexus between carbondioxide emissions and economic growth. energy policy, 86, 104-117. yang, z., zhao, y. (2014), energy consumption, carbon emissions, and economic growth in india: evidence from directed acyclic graphs. economic modelling, 38, 533-540. yansui, l., bin, y., yang, z. (2016), urbanization, economic growth, and carbon dioxide emissions in china: a panel cointegration and causality analysis. journal of geographical sciences, 26(2), 131-152. zhang, y.j., liu, z., zhang, h., tan, t.d. (2014), the impact of economic growth, industrial structure and urbanizaiton on carbon emission intensity in china. natural hazards, 73, 579-595. erdoğan, et al.: investigation of causality analysis between economic growth and co2 emissions: the case of brics – t countries international journal of energy economics and policy | vol 9 • issue 6 • 2019438 annex annex 1 cross-section dependence test series: lnco2 null hypothesis: no cross-section dependence (correlation) test statistic prob. breusch-pagan lm 291.307 0.000 pesaran scaled lm 49.351 0.000 bias-corrected scaled lm 49.235 0.000 pesaran cd 9.245 0.000 lm: lagrange multiplier annex 2 cross-section dependence test series: lngdp null hypothesis: no cross-section dependence (correlation) test statistic prob. breusch-pagan lm 337.990 0.000 pesaran scaled lm 57.874 0.000 bias-corrected scaled lm 57.758 0.000 pesaran cd 18.305 0.000 lm: lagrange multiplier . international journal of energy economics and policy | vol 10 • issue 2 • 2020 101 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(2), 101-112. passive balancing through intraday trading: whether interactions between short-term trading and balancing stabilize germany’s electricity system christopher koch*, philipp maskos department of energy systems, technische universität berlin, germany. *e-mail: christopher.koch@tu-berlin.de received: 19 september 2019 accepted: 04 december 2019 doi: https://doi.org/10.32479/ijeep.8750 abstract transmission system operators actively balance the electricity system by sending a dispatch signal to suppliers of balancing reserve. when market participants intentionally adapt their intraday positions based on the expected system state, they can also reduce the required dispatch of balancing reserves. this is called passive balancing. the german imbalance price system incites this behavior. this paper examines whether passive balancing prevails in germany and how it affects the system stability. our analysis indicates that intraday trading close to gate closure is highly affected by market participants reacting to the latest published system balance (sb). this behavior has a positive impact on system balancing. intraday trading close to gate closure reduces both the required demand of balancing energy and high sbs up to 5% without causing a critical overshoot of the system. keywords: electricity market design, passive balancing, intraday market, electricity portfolio management, strategic behavior jel classifications: c32; d47 1. introduction the liberalization of the electricity market caused a deconstruction of the integrated electricity value chain. potentially competitive segments like marketing and operation of generation and load are separated from regulated segments such as operations of transmission or distribution grids (joskow, 2008). this also changed the approach of balancing demand and supply in the electricity system. in germany and many other liberalized countries, decentralized balancing responsible parties (brps) plan the production or consumption of their portfolio while the transmission system operators (tsos) centrally coordinate the compensation of the remaining imbalances by the activation of balancing reserve. the accuracy of brps’ portfolio management determines the demand of balancing reserve. as time unfolds, brps have better predictions of their actual generation and consumption. therefore, it becomes necessary to balance forecast deviations for renewables, load and power plant outages after the day-ahead market by either trade or dispatch of own assets. the most important platform to trade these deviations is the intraday market. the german continuous intraday market at epex spot opens at 3 pm of the previous day and products can be traded until 5 min before delivery (epex spot se, 2017). the nord pool power exchange provides intraday trading even until delivery within the german tso areas (nord pool, 2018). the core incentive for brps to use the intraday market for portfolio balancing is the imbalance price. if the overall system is short – meaning that uptake exceeds infeed – the imbalance price must be higher than the intraday price and vice versa so that brps buy or sell additional volumes on the intraday market instead of using balancing energy. but what is about the brps this journal is licensed under a creative commons attribution 4.0 international license koch and maskos: passive balancing through intraday trading: whether interactions between short-term trading and balancing stabilize germany’s electricity system international journal of energy economics and policy | vol 10 • issue 2 • 2020102 whose imbalance is opposed to the overall system? in germany, they are rewarded the same imbalance price as the brps pay that enforce the imbalance of the system. this symmetric pricing model incites brps to take a position that is opposed to (or to avoid a position that is congruent to) their expectation of the system balance (sb) to financially optimize their portfolio. this behavior is called passive balancing as it decreases, in case of success, the sb without activating balancing reserve capacity (chaves-ávila et al., 2014b; hirth and ziegenhagen, 2015). in germany however, it is prohibited to take intentional imbalance positions. the german imbalance price system thus incites brps to deploy operations that are legally not allowed. this study analyses whether market participants follow the financial incentive of the imbalance price and, if so, how this behavior affects the system stability. we extend the definition of passive balancing to be understood as intentional reactions to the expected sb by intraday trading. it is not relevant whether intraday trading reduces the brps imbalance congruent to the sb or increases the imbalance opposed to the sb as the overall effect on the system and the financial incentive is the same. our analysis is twofold: firstly, we apply a regression model to estimate price changes of intraday trades close to gate closure. hagemann (2015) and wolff and feuerriegel (2017) show that intraday prices are influenced by fundamental drivers such as forecast deviations and power plant outages. if the latest published sb is also a significant parameter, it will be an indication that market participants react to this information to optimize their own portfolio. we apply a quantile regression including third degree polynomial to address non-linear effects and to gain greater insights regarding the relations of the dependent and the independent variables. this approach has gained popularity in the literature of electricity price forecasting as inter alia the studies of jónsson et al. (2014), nowotarski and weron (2015), bunn et al. (2016) and maciejowska et al. (2016) show. in a second step, we calculate the effect of intraday trading close to gate closure on different system stability indicators. the research relates to several studies discussing the theoretic approach of passive balancing (chaves-ávila et al., 2014a; zapata riveros et al., 2015; brijs et al., 2017; hu et al., 2018; joos and staffell, 2018; röben and schäfers, 2018). none of them apply a specific case study. we fill this gap with our analysis about the interactions of the intraday and balancing market in germany. there are other research papers studying the financial incentive to use balancing energy for portfolio balancing (möller et al., 2011; just and weber, 2015). tanrisever et al. (2015) examine the influence of spot price incentives on the sb for the dutch market. but all these papers do not address the topic of passive balancing. the paper also relates to studies analyzing the main drivers of intraday prices (karanfil and li, 2017; kiesel and paraschiv, 2017; frade et al., 2018). the difference of our approach is that we use the model to test our hypothesis that market participants react to the sb to financially optimize their portfolio. the paper is structured as follows: section 2 provides background information about the balancing system and the idea of passive balancing. section 3 gives an overview of the methodical approach and the used data. section 4 examines whether the information of the sb influences intraday trading close to gate closure and section 5 analyzes the impact on system stability. the results are discussed in section 6. section 7 concludes. 2. background 2.1. the balancing system one special characteristic of electrical energy is the requirement to ensure the balance between demand and supply at every point of time to maintain a stable frequency. if the system is physically short of energy, the frequency drops. large deviations from nominal frequency can cause disconnections, damage equipment and lead to rolling blackouts. these situations shall be prevented by an elaborate system of regulations, processes and markets to which we collectively refer to as the “balancing system.” in germany, the market participants have the responsibility to ensure that their portfolio is in balance. each electricity market actor takes the role of a brp. each physical connection point of the grid is associated with one balancing group of one brp. there are more than one thousand brps in germany (50hertz transmission gmbh, 2019; amprion gmbh, 2019; tennet tso gmbh, 2019; transnetbw gmbh, 2019). they can balance their portfolio of generation and/or load through dispatch of physical assets or through trade. brps provide their schedules to the associated system operator. the remaining deviations between schedules and actual physical positions are called imbalances. they are compensated by system wide balancing energy being activated by the tso. positive and negative imbalances offset each other so that the final activation of balancing reserve is only determined by the net balancing group imbalances. figure 1 illustrates the general principle for the german grid cooperation. if the sum of all balancing group deviations is negative, there is a shortage of supply in the system and the tsos must activate positive balancing reserve. the imbalance settlement period in germany is 15 min. for each period, the average net imbalance of all balancing groups is called sb. it includes all measures used to compensate imbalances such as the activation of automated and manual frequency restoration reserve (afrr and mfrr) and additional measures figure 1: explanation of the balancing system. balancing reserve compensates the net imbalances of all balancing groups koch and maskos: passive balancing through intraday trading: whether interactions between short-term trading and balancing stabilize germany’s electricity system international journal of energy economics and policy | vol 10 • issue 2 • 2020 103 as well as emergency measures for or from foreign tsos (em). furthermore, there are international balancing cooperation to exchange balancing energy within the international grid control cooperation and the afrr cooperation with austria (50hertz transmission gmbh et al., 2017). sb p p p p p p p p t afrr afrr t mfrr mfrr t am am t em e = −( ) + −( ) + −( ) + − + − + − + − + mm t igcc im igcc ex t afrr im afrr ex t p p p p −( ) + −( ) + −( ), , , , (1) a positive sb corresponds to a shortage of supply in the national grid, a negative system represents a power surplus. it can be seen as indicator for the system stability. if the absolute sb is high, the same applies for the demand of balancing energy. in germany, the sb is also a key element for the calculation of the imbalance price. the general idea is to distribute the costs of balancing reserve activations for every quarter-hour to the brps, who caused the activations. the general calculation reads: imbalanceprice costs revenues sbt t t t � = −∑ ∑ (2) regarding the settlement, the imbalance price calculated with equation (2) functions sufficiently to distribute the cost or revenues of activated balancing energy to the brps. but in case of a small average sb over a quarter-hour, the fraction in the formula can lead to extreme imbalance prices in a moderate system. to avoid this, the price is capped at the highest working price of all activated assets. furthermore a linear function limits the price when the sb is between −500 mw and 500 mw. however, the imbalance price shall always incite the brps to balance predictable deviations on the market. this is addressed by the constraint that the imbalance price must be higher than the volume weighted average price of the corresponding hour.1 additionally, there is a surcharge, if tsos must activate 80% of the procured afrr and mfrr within one quarter-hour. it is the maximum of 100 €/mwh or half of the imbalance price (bundesnetzagentur, 2012). 2.2. the concept of passive balancing according to § 4 (2) stromnzv and the balancing group contract, brps are obliged to keep imbalances to a minimum by taking reasonable measures. it is only allowed to use balancing energy for unpredictable deviations like power plant outages or short-term forecast errors for production or consumption (bundesnetzagentur, 2013). thus, it is prohibited to take intentional imbalance positions. however, the symmetric imbalance price in germany gives a financial incentive to take an intentional imbalance position (hirth and ziegenhagen, 2015; just and weber, 2015; zapata riveros et al., 2015). depending on the sign of their imbalance position, brps will either pay or receive the imbalance price for their imbalance. when the electricity system is short of energy, a brp with a short portfolio must pay, but a brp with a long portfolio gets payed the imbalance price. this system leads to incentives of taking imbalance positions to financially optimize the own portfolio. table 1 shows the relation of imbalance prices 1 this constraint does not prevent that quarter-hourly intraday prices are higher than imbalance prices. and volume weighted average intraday prices depending on the sign of the sb. if the system is short (positive sb), the imbalance price is higher than the intraday price in 90% of the cases. in this case, it would be better to buy additional volumes on the intraday market to be oversupplied and receive the imbalance price. it is the other way around for a power surplus (negative sb), when the imbalance price is lower than the intraday price in 95% of the cases. most of the time, it is financially beneficial to take an intraday position that is opposed to the sb. this behavior is called passive balancing since it can reduce the sb (lampropoulos, 2014; van der veen and hakvoort, 2016). the term is used in contrast to active balancing via balancing reserve activation by tsos. to our understanding, every intentional reaction to the expected sb by intraday trading shall be called passive balancing as long as it reduces the sb. it is not relevant whether the intraday position reduces or increases the own imbalance as the overall effect on the system and the financial incentive is the same. the following analyses aim to show whether market participants apply this portfolio optimization on the intraday market and, if they do so, how it effects the system stability. 3. materials and methods if market participants use the information of the sb to optimize their portfolio, there must be a correlation between intraday price developments and the sb. this should apply especially to market activity close to gate closure as the sb is difficult to predict for a longer period. therefore, we take the price deviation of the volume weighted average intraday price of quarter-hourly trades close to gate closure and the day-ahead price of the corresponding quarter-hour (p pidgc da� − ) as the independent variable of our analysis. the empirical study of maskos (2017) shows that german tsos regularly publish the past sb 10.65 min after the quarter-hour, which means that the latest information is available 4.35 min before gate closure of continuous trading.2 in our calculation we consider all trades that are executed after this threshold. the period of our analysis spans from january 1, 2016 to september 30, 2018. the end of the period must be set to that date as the german regulator changed the approach of accepting balancing reserve bids in october 2018 having a significant impact on the imbalance prices (bundesnetzagentur, 2018). therefore, data since october 01, 2018 are not part of the analysis to cover a period with a stable market design and comparable price incentives. 2 the gate closure of the “same delivery area trading” or “trading until delivery” is five minutes before delivery for the four german delivery areas. it is not considered here, since this market was only introduced on 13/06/2017 and its liquidity is lower than in continuous trading niciejewska (2017). table 1: relation of sb and price deviation of imbalance and volume weighted average intraday price from january 01, 2016 to september 30, 2018. the numbers resemble a count of quarter-hours sb >0 mw sb ≤0 mw imbalance price > intraday price 54 372 1 670 imbalance price ≤ intraday price 6 300 34 034 sb: system balance koch and maskos: passive balancing through intraday trading: whether interactions between short-term trading and balancing stabilize germany’s electricity system international journal of energy economics and policy | vol 10 • issue 2 • 2020104 our study is divided into two steps, each testing one hypothesis. we start with a single correlation analysis between pid gc and pda and the sb. a positive sb represents a short system. in this case it is economically beneficial to be oversupplied by buying additional volumes on the intraday market. this would lead to higher intraday prices. therefore, we expect a positive correlation between the price deviation and the sb. but which lagged sb has the highest impact on the intraday prices close to gate closure? we calculate the correlation for several time lags of the sbs from zero (the sb of the corresponding trading product) to 225 min. as market participants do not know the actual sb of the corresponding trading product, they can only use the latest published value to predict it. this is the sb of 60 min before delivery, because intraday trading is possible until 30 min before delivery and the tsos publish the sb 10.65 min after the quarter-hour (figure 2). this leads to our first hypothesis h1: there is a positive relation between the sb and the deviation between intraday prices close to gate closure and day-ahead prices. the correlation is the highest for the latest published sb, which is 60 min before delivery. several studies confirm a non-linear relation between fundamental drivers and electricity prices due to the shape of the merit order (misiorek et al., 2006; chen and bunn, 2010; bunn et al., 2016). we expect such a non-linear influence also for the sb and study it with a scatter plot. afterwards, we analyze the relation to the deviation between intraday prices close to gate closure and day-ahead prices by calculating the spearman correlation coefficient. its main use is to discover associations in nonlinear data sets (borradaile, 2003). the second step of our analysis is to fit a quantile regression model to estimate the price deviation p pidgc da� − . quantile regression was introduced by koenker and bassett (1978) and fully described by koenker (2005) and hao and naiman (2007). its idea is to fit individual models for estimating conditional quantiles of the distribution of a dependent variable using different coefficients for the independent variables at each quantile. let yi be the dependent variable and xi a d-dimensional vector of explanatory variables including a constant. the regression model for the quantile level q is given by q y | x = x bq t t t t( ) (3) in which, as implemented in software packages like r, stata or eviews, the parameters βq are derived by solving the minimization problem: argmin q y x q t t q t t y x t t q β β β = ≤∑ −( ) −( ) 1 1 (4) where 1 1 0 β β ≤ ≤ =   t t q t t q y x y x otherwise quantile regression does not make any distributional assumptions other than assuming that the dependent variable is almost continuous (koenker, 2005). so, there is no need to test for heteroskedasticity or autocorrelation of the residuals as it is necessary for an ordinary least squares regression (wooldridge, 2013). the details on estimating standard errors for coefficients, inference and goodness of fit are explained in (koenker and machado, 1999). if market participants use the information of the latest published sb, it should be a significant parameter of the model, even when fundamental variables associated with intraday prices are controlled for. h2: the latest published sb has a significant influence on all different quantile levels of the deviation between intraday prices close to gate closure and day-ahead prices. several studies show that fundamental variables can explain deviations between hourly intraday and day-ahead prices (hagemann, 2015; pape et al., 2016; valitov and maier, 2017). according to these papers, significant parameters are renewable and load forecast errors (deltawind, deltasolar, deltaload), power plant outages (outage) and cross-border physical flows. this should also apply to quarter-hourly products, because their prices must match on average the price of the corresponding hourly product to avoid arbitrage opportunities. therefore, we consider these parameters as control variables in our model. the forecast errors are calculated as the day-ahead forecast minus the actual production or consumption. this is an approximation of the difference between the day-ahead position and the latest intraday forecast representing the volume the market participants try to close at the intraday market. cross-border flows can be nominated explicitly or implicitly. market participants are able to explicitly allocate capacities on specific platforms to declare a cross-border flow from or to different neighboring countries. on these platforms the allocation of capacity is associated with a nomination and thus with a cross-border flow. we consider the net import of all flows from and to germany’s neighboring countries as a regressor for our model (net importexpl). additionally, german figure 2: diagram of the chronological sequence of system balance, gate closure and delivery sb60 sb0 sb15 sb30 sb75 publication of sb 60 system balance gate closure sb45 t – 60 m in t – 30 m in t delivery koch and maskos: passive balancing through intraday trading: whether interactions between short-term trading and balancing stabilize germany’s electricity system international journal of energy economics and policy | vol 10 • issue 2 • 2020 105 market participants can directly match intraday bids and offers from other countries that are part of the cross-border intraday initiative (xbid) (epex spot se, 2018) as long as there is enough net transport capacity available for the intraday market. the net position of all trades with buyer (seller) in germany and seller (buyer) in another country is also considered in our model (net importimpl). table 2 provides an overview of all variables and their data source. to address the expected non-linear effect of the sb, we include this variable with a third degree polynomial. this leads to the following model specification: ( ) ( ) ( ) 2 60 600 1 2 3 603 4 5 6 7 8 9 β β β β β β β β β β − − − − = + + + + + + + + + q q qid gc da q t t t t q q wind t t q qsolar load t t q q expl t t q impl t q p p sb sb sb delta delta delta outage net import net import (5) 4. influence of sb on intraday prices this section provides the results of the analyses described in section 3. first, we carry out an exploratory data analysis showing a positive correlation between the sb and the price deviation between quarter-hourly intraday prices close to gate closure and quarter-hourly day-ahead prices. there is an indication that market participants use the information of the latest published sb to financially optimize their portfolio. this is confirmed by the quantile regression model presented in section 4.2. the explanatory power of the models more than doubles by adding the polynomial of the latest published sb to a model that covers only other fundamental variables. 4.1. correlation analysis figure 3 shows the scatterplot of the volume weighted average intraday price of trades close to gate closure referred to the day-ahead price over the sb. it additionally depicts the regression lines that approximate the relation between the 0.05, 0.5 and 0.95 quantile level of the independent variable and the third degree polynomial of the sb. even though in some cases the observations differ strongly from the regression lines there is a trend that higher sbs correlate with increasing prices and lower sbs with decreasing prices. this represents the effect that passive balancing should have on intraday price developments. having a short system (positive sb), it is beneficial to buy additional volumes on the intraday market and to take a long imbalance position in the table 2: overview of explanatory variables and their data sources data description source day-ahead price market clearing price for a certain hour in the day-ahead auctions entelios gmbh intraday price volume weighted average price of all trades executed within 4.35 min to gate closure entelios gmbh sb the sum of imbalances from all german balancing groups common platform of german tsos: https://www. regelleistung.net/ext/data/ forecast error wind day-ahead prognosis minus extrapolation of the actual wind generation transmission system operators: http://www. 50hertz.com, http://www.amprion.de, http://www.transnetbw.de, http:// www.tennettso.de forecast error solar day-ahead prognosis minus extrapolation of the actual solar generation transmission system operators: http://www. 50hertz.com, http://www.amprion.de, http://www.transnetbw.de, http:// www.tennettso.de forecast error load day-ahead prognosis minus extrapolation of the actual electricity load european network of transmission system operators: https://transparency.entsoe.eu/ outage unplanned power plant outages occurring after day-ahead nomination european energy exchange transparency platform: http://www.eex-transparency.com/de explicit net import net import via explicit intraday cross-border nominations european network of transmission system operators: https://transparency.entsoe.eu/ implicit net import net import from intraday trades with buyer (seller) in germany and seller (buyer) in another country entelios gmbh sb: system balance figure 3: scatterplot of the volume weighted average intraday price of trades close to gate closure referred to the day-ahead price over the system balance. the blue lines represent a third degree polynomial regression of the 0.05, 0.5 and 0.95 quantile level https://www.regelleistung.net/ext/data/ https://www.regelleistung.net/ext/data/ http://www.50hertz.com http://www.amprion.de http://www.transnetbw.de http://www.tennettso.de http://www.tennettso.de http://www.50hertz.com http://www.amprion.de http://www.transnetbw.de http://www.tennettso.de http://www.tennettso.de https://transparency.entsoe.eu/ http://www.eex-transparency.com/de https://transparency.entsoe.eu/ koch and maskos: passive balancing through intraday trading: whether interactions between short-term trading and balancing stabilize germany’s electricity system international journal of energy economics and policy | vol 10 • issue 2 • 2020106 balancing group (section 2.2). this behavior should ceteris paribus lead to an increase of the intraday prices. the regression lines show a non-linear relation between the variables. high absolute sbs have a disproportionate impact on the price deviation between intraday and day ahead prices, which applies especially for the tails of the distribution. the reason might be the shape of the merit order. the supply function exhibits strong convexity and is sharply increasing at high and low price levels (geman and roncoroni, 2006; karakatsani and bunn, 2008; kyritsis et al., 2017). at these prices, an additional demand for flexibility causes higher price jumps. this effect also applies for the merit order of balancing reserve activations. so, higher absolute sbs are associated with disproportionate imbalance prices and cause a higher incentive to use the intraday market for portfolio balancing. during gate opening of the trading period for an associated product, market participants cannot know the actual sb for the period. nonetheless, the latest published sb is a valuable information close to gate closure, because the sb has a strong autocorrelation (kiesel and paraschiv, 2017; maskos, 2017). if market participants use the latest published information for own portfolio optimization, the correlation should be highest with this sb. considering the observed non-linear relation, figure 4 shows the spearman correlation coefficients of different lagged sbs and the intraday prices of trades close to gate closure referred to the day-ahead price. we analyzed trades within the last 4.35 min to gate closure (left side) and also between 19.35 and 15 min (right side) to see whether market participants also react earlier to the published sb. for both intervals, the correlation coefficient is significantly highest on a 0.99 confidence level for the latest published sb. this is 60 and 75 min before delivery, respectively. based on this analysis, h1 is accepted. 4.2. quantile regression model the analysis in section 4.1 has shown a significant positive spearman correlation coefficient between the sb and the difference between intraday prices close to gate closure and the day ahead price. the maximum for trades between 4.35 and 0 min to gate closure was for the sb 60 min before delivery. we further analyze this relation with the quantile regression model described in equation (5). besides the lagged sb, we consider wind, solar and load forecast deviations, power plant outages and explicit and implicit net import as control variables in our model. table 3 presents the estimation results at different quantile levels. the explanatory power measured by the pseudo r-squared (koenker and machado, 1999) is in the range of 0.16-0.23. so, the model fit is too low to make predictions on the deviation between intraday prices closes to gate closure and day-ahead prices, but there are still regressors with coefficients significantly different from zero. the forecast errors for wind and solar are significant on a 1% level all coefficients show the expected sign. the price impact for both variables is higher on the tails of the distribution, which can be explained with the shape of the merit order as described in section 4.1. in accordance with the findings of hagemann (2015), the price impact is lower for solar than for wind. a forecast error of 1 gw for wind leads to a price change between 1.7 and 2.5 €/mwh, whereas the same forecast error for solar influences the prices only figure 4: spearman correlation of the intraday prices of trades close to gate closure referred to the day-ahead price and lagged system balances table 3: estimation results of the quantile regression model shown in equation (5) quantile 0.05 0.1 0.25 0.5 0.75 0.9 0.95 intercept −19.16 −14.61 −8.37 −2.23 3.96 10.96 16.03 wind 2.27∙10−03 1.98∙10−03 1.73∙10−03 1.70∙10−03 1.86∙10−03 2.19∙10−03 2.50∙10−03 solar 5.50∙10−04 4.78∙10−04 5.03∙10−04 4.73∙10−04 6.43∙10−04 8.24∙10−04 9.98∙10−04 demand 3.88∙10−04 2.31∙10−04 1.13∙10−04 −3.92∙10−05 −2.45∙10−04 −6.01∙10−04 −8.97∙10−04 outages −1.28∙10−04 2.98∙10−05 1.89∙10−05 −2.16∙10−04 −3.13∙10−04 −4.98∙10−04 −4.41∙10−04 net importexpl 6.93∙10 −04 3.53∙10−04 −6.91∙10−05 −4.63∙10−04 −9.04∙10−04 −1.52∙10−03 −1.83∙10−03 net importimpl 1.48∙10 −03 1.52∙10−03 1.78∙10−03 2.10∙10−03 2.56∙10−03 3.09∙10−03 3.60∙10−03 sb60 2.16∙10−02 1.86∙10−02 1.54∙10−02 1.36∙10−02 1.22∙10−02 1.20∙10−02 1.12∙10−02 (sb60)² −1.27∙10−05 −8.53∙10−06 −4.13∙10−06 −1.49∙10−06 1.33∙10−06 4.83∙10−06 9.07∙10−06 (sb60)3 3.57∙10−09 2.23∙10−09 9.60∙10−10 5.60∙10−10 1.18∙10−09 2.53∙10−09 4.97∙10−09 r² adjusted 0.232 0.209 0.187 0.173 0.159 0.161 0.173 bold numbers indicate significance on a 1% level. all other parameters are not significant on a 5% level. sb: system balance koch and maskos: passive balancing through intraday trading: whether interactions between short-term trading and balancing stabilize germany’s electricity system international journal of energy economics and policy | vol 10 • issue 2 • 2020 107 between 0.47 and 1 €/mwh. considering the fact that electricity is a homogenous good, a one mw trade in the intraday market caused by any driver can be expected to have a similar effect on the price. one reason for the difference might be that forecast errors are traded only partly on the market and by different portfolio owners. market participants can match opposing positions within their portfolio or use own flexible assets to balance deviations and trade only net imbalances. moreover, solar generation is mostly during peak hours. the higher liquidity during these hours may cause a lower price effect of forecast deviations (hagemann and weber, 2013). the coefficients for demand are only partly significant and do not show the expected signs at every quantile level. looking at the forecast error for demand, there are two possible reasons. first, system operators do not get temporal measurements of all loads. the electricity demand of small customers is estimated based on standard load profiles, which makes it more difficult to predict the forecast deviations. therefore, a part of the deviation can be part of the sb, which causes a price impact in itself. second, there are different calculation methods for forecasted and actual demand. the forecast is the tso’s prognosis of the total load. the actuals are an extrapolation based on power plant schedules. the different approaches might lead to an imprecise calculation of the forecast deviation. power plant outages are the only variable that is predominantly insignificant even though previous studies found a significant effect on hourly intraday prices (hagemann, 2015; valitov and maier, 2017). the reason might be a problem with the data. according to the regulation on wholesale energy market integrity and transparency, power plant operators must report (unplanned) outages even if the power plant was not running before (european parliament, 2011). this might reduce the validity of the data. there is also a significant relation between implicit net imports and the price development on the intraday market. this is in contrast to hagemann (2015), who found no significant influence of germanfrench intraday trades for his market analysis of 2010 and 2011. during the period of our analysis, the coefficients are between 1.48 and 3.6 €/mwh per gw. it is more attractive for foreign assets to sell volumes to german market participants when the price level is high and to buy volumes from germany when the price level is low. this indicates that the implicit net imports are an endogenous result of the price movements on the intraday market. the signs of the coefficients for explicit imports are positive for low quantiles and negative for high quantiles. the interpretation of the coefficients is difficult. we assume a complex interaction of endogenous and exogenous effects, defined by the differing generation mix in germany versus its neighboring countries. for example, in high quantiles peak power plants in neighboring countries could make use of the high price level and sell their physical flexibility. the imports dampen the price move. on lower quantiles and thus prices the effect seems endogenous, so that rising price levels increase the amount of imports. looking at the significance of the coefficients, a consideration of the aforementioned control variables is necessary to determine the impact of the lagged sb on intraday trades. the model results show a significant relation with the independent variable for the three polynomial variables on all quantile levels. therefore, h2 is accepted. it can be assumed that market participants react to the publication of the lagged sb by adapting their imbalance positions. if the sb is assumed to be short, market participants buy energy on the intraday market leading to higher prices and vice versa. this behavior can either reduce their own imbalance (if the portfolio is unbalanced congruent to the system) or even increase it (if the portfolio was in balance or unbalanced opposed to the system). the financial benefit of the intraday position itself and the effect on the sb is the same for both situations and only depends on the actual sb. the price effect of the lagged sb is not linear as the quadratic and cube parameter are significant for all quantile levels. higher absolute sbs have a stronger impact on intraday price movements. reasons might be the convex merit order of flexible assets on the intraday market and the higher price incentives that are associated with high absolute sbs (compare section 4.1). to illustrate the meaning of the lagged sb, we also run a model only considering all other parameters. its pseudo r-squared was between 0.07 and 0.09. adding just the lagged sb as a third degree polynomial improves the model accuracy by up to 195%. this indicates that the sb is the most important predictor to estimate intraday price movements close to gate closure. it provides more explanatory power than just the forecast deviations the brps must compensate. 5. impact of passive balancing on sb section 4 has shown the statistical evidence that market participants use the information of the latest published sb to optimize their portfolio by adapting their imbalance position. this section analyses the effect of this behavior on the system stability. 5.1. approximation of passive balancing volumes to estimate the impact of passive balancing, we compare the actual sb with a hypothetical sb that would have prevailed without passive balancing (sbno pb). sb sb volt nopb t t pb� = − (6) a calculation method is required to estimate the passive balancing volumes. intraday trades are published anonymously. there is an information about the tso area of buy and sell party, but not about the specific balancing group. therefore, it is not possible to analyze the behavior of single market participants looking for the potential intention of the position. instead, we estimate the effect by considering all quarter-hourly intraday trades close to gate closure, when market activity is highly affected by the reaction to the latest published sb (section 4). the underlying assumption is that a trade close to gate closure is associated with a physical influence on the system. this might not always be the case, as some trades might be of speculative nature aiming to capture price moves. koch and maskos: passive balancing through intraday trading: whether interactions between short-term trading and balancing stabilize germany’s electricity system international journal of energy economics and policy | vol 10 • issue 2 • 2020108 asset owners have well specified costs which are defined by their short-term marginal generation costs and ramping constraints. they are reflected in the prices of their limit orders. so, the order book represents the flexibility offer given a certain price level (plus noise due to speculative orders, which could increase traded volumes). however, portfolio managers are price takers on the intraday market if they are not able to compensate the imbalance of their portfolios by adapting the operation of a physical asset. their opportunity costs are defined by the imbalance price, which justifies to pay the bid-ask-spread as long as the price(s) of the best limit order(s) are better than the expected imbalance price. the same applies for market participants who want to use the financial incentive of the system by taking an intentional imbalance. so, the aggressor of a limit order changes the position only financially via trading, whereas the opposite part adapt the operation of a flexible asset, which changes the sb. if the sell side is the aggressor of a trade (volsell), the counterpart is assumed to be a generation unit ramping down or a consumption unit ramping up. the system gets shorter. if the buy side is the aggressor (volbuy), the system gets more oversupplied. the passive balancing volume is the net position of both volumes. vol vol volt pb t sell t buy1 = − (7) comparing the price of a trade with the best sell and buy order at this time shows whether the sell or buy side is the aggressor of the trade. figure 5 illustrates the approach with an example of one trade of 10 mw within the last 4.35 min to gate closure. the buy side forced the trade. so, volbuy is 10 mw and volsell is 0 mw. the passive balancing volume is −10 mw. the whole calculation approach is illustrated in table 4 for the quarter-hour from 12:45 am to 1:00 pm of april 24, 2016. on average, the net trading volume per quarter hour is 35 mw for the analyzed period (january 1, 2016 to september 30, 2018) considering the last 4.35 min and 70 mw considering the last 19.35 min before gate closure. 5.2. comparison of system stability indicators the result of the approach described in section 5.1 is a time series of a hypothetical sb that would have prevailed without trading close to gate closure, which we use as an approximation to estimate the effect of passive balancing (equation 6). we compare it with the actual sb to assess the impact on system stability by analyzing two indicators. the total absolute sb reflects the activation of balancing reserves. it is possible that tsos must activate positive and negative balancing reserve within one quarter-hour. in this case, the sb is the net position of both. therefore, it does not equal the amount of the total balancing reserve activation. but a lower total absolute sb is an indication for a reduced balancing demand. high absolute sbs are another important indicator as they determine the level of procured balancing reserve. we consider the effect on the 95th percentile of the sb. table 5 shows for both indicators the difference of the calculation for the actual sb and the sb without intraday trading close to gate closure. thus, negative numbers mean that intraday trading has a positive impact on the system stability. our analysis indicates that trading within the last 4.35 min to gate closure causes a reduction of the total absolute sb of 1.78% and of the 95th percentile of 1.66%. these numbers are an upper limit for the effect of this trading period, as not every trade close to delivery has a physical influence on the sb and is done because of passive balancing. however, market participants already react earlier to the sb as the analyses presented in figure 4 suggests. a second calculation shows the effect of trading of the last 19.35 min, which is directly after publishing the sb of 75 min before delivery. the positive influence enlarges to a reduction of 5.3% for both indicators. so, our analyses indicate that intraday trading close to gate closure is strongly influenced by the information of the sb and it reduces balancing needs. 5.3. overshooting of sb critics of passive balancing argue it can lead to an overshoot of the sb. if the market participants react too strong by trying to be on the opposed side of the sb, the sb swings to the other direction. to our understanding, this is only critical, if an overreaction leads to high positive or negative sbs. we analyze empirical data to study whether overshooting is a problem in germany or not. for the period from 2012 to the end of september 2018, we identify situations, when the sb exceeds a threshold in positive and negative direction within 2 h (figure 6). our threshold for a strong overshoot is an absolute value 1000 mw, which is approximately the 95th percentile of all sbs between 2016 and the end of september 2018. the threshold for figure 5: intraday trade with buy side accepting sell bid table 4: example calculation of sb without passive balancing as described in equations (7) date time april 24, 2016 12:45 am – april 24, 2016 1:00 pm actual sb sell volume buy volume sb without passive balancing −1580.67 mw 327.8 mw 20.1 mw −1888.37 mw sb: system balance koch and maskos: passive balancing through intraday trading: whether interactions between short-term trading and balancing stabilize germany’s electricity system international journal of energy economics and policy | vol 10 • issue 2 • 2020 109 a critical overshoot follows a definition of the german regulator. if the tsos must activate 80% of the procured afrr and mfrr within one quarter-hour, the imbalance price gets an additional surcharge (bundesnetzagentur, 2012). the minimum amount of procured afrr and mfrr is 2518 mw for the considered period. so, 2000 mw represent an 80% share. the empirical analysis shows that the number of strong overshoots declines from 2012 to 2014 (table 6). one important reason for the reduction is the increased use of the quarter-hourly intraday market. previously, portfolio management was done mostly in hourly resolution leading to systematic activations of positive and negative balancing reserves within 1 h (remppis et al., 2015; koch and hirth, 2019). this was most critical in the morning and in the evening when load and solar energy generation change strongly within 1 h (kiesel and paraschiv, 2017; märkle-huß et al., 2018). therefore, strong overshoots did not happen because market participants actively took a position on the market, but because of a lack of active intraday trading. the number of situations with strong overshoots remains on a constantly low level after 2014. a critical overshoot never happened between 2012 and september 2018. to identify the impact of passive balancing on overshooting, we use the same approach as described in section 5.1. we approximate the hypothetical sb without the net position of intraday trading close to delivery. we did the calculation both for the period of the last 4.35 min and for the last 19.35 min to gate closure. the analyzed time series show no critical overshoot, but a slightly higher number of situations with a strong overshoot.3 so, the results suggest that intraday trading close to gate closure has a positive impact on overshooting even though the market participants react to the sb. the concerns of overshooting are currently unfounded. 5.4. effect of stronger reactions to the sb the analyses in section 4 indicate that at least a part of market participants reacts to the information of the latest published sb. assuming that some of them are doing so by taking intentional imbalances, we analyze what would happen, if more market participants would follow the underlying price incentive. this is done by assessing the impact of a doubling of the net intraday trading volumes on the previously introduced system stability indicators. we apply again the calculation method explained in equation (7) on the two time periods of the last 4.35 and 19.35 min to gate closure. the results show a positive impact on the total absolute sb and a reduction of high absolute sb for both cases (table 7). there is a minor influence on situations with a strong overshoot (threshold 1000 mw) and still no situation with a critical overshoot of the system (threshold 2000 mw). these numbers are a conservative estimate of the actual effect, because a pure doubling of the net volumes does not consider the potential reaction of the market participants on the new sb. however, the analysis indicates that additional reactions to the price incentive has the potential to further reduce the activation and procurement of balancing reserves without leading to a critical overshoot of the system. 3 the calculation is only done for the same period as for the other analyses of the intraday market (01/01/2016 to 30/09/2018). table 5: impact of intraday trading close to gate closure on system stability. it reduces the sum of absolute sbs and its 95th percentile leading to a reduction of balancing reserve activation and procurement time period last 4.35 min last 19.35 min total absolute sb −56.7 gwh/a −172 gwh/a −1.78% −5.39% absolute sb0.95 −16.0 mw −50.8 mw −1.66% −5.28% sb: system balance table 6: overview of strong and critical overshoot (threshold 1000 mw and 2000 mw) between 2012 and september 2018. overshoot means that the sb exceeds the threshold in positive and negative direction within 2 h year actual sb sb without intraday trading close to gate closure strong overshoot critical overshoot strong overshoot critical overshoot 4.35 min 19.35 min 4.35 min 19.35 min 2012 166 0 2013 67 0 2014 22 0 2015 14 0 2016 6 0 8 9 0 0 2017 15 0 18 23 0 0 q1-q3 2018 14 0 13 17 0 0 sb: system balance figure 6: example of system balance on april 15, 2017 from 08:30 to 10:30 am. the system balance swings from − 1600 mw to +1900 mw within 2 h. this is considered as a strong, but not a critical overshoot koch and maskos: passive balancing through intraday trading: whether interactions between short-term trading and balancing stabilize germany’s electricity system international journal of energy economics and policy | vol 10 • issue 2 • 2020110 6. discussion the analyses presented in section 4 show a significant correlation between the intraday price level close to gate closure compared to the day ahead price and the latest published sb. this indicates that portfolio managers react to that information due to the incentive of the imbalance price. this inducement does not depend on the actual imbalance of the portfolio. it is solely a comparison of the current intraday price and the expected imbalance price. therefore, it is likely that a part of the intraday positions is coming from market participants taking intentional imbalances that are opposed to their expectation of the sb. however, further research is required to show whether this assumption holds as it needs an analysis of single balancing groups including their initial position and the forecast of their portfolio. essl (2018) was able to study such data for austria and concludes that brps, who take intentional imbalance positions, stabilize the system. if this is confirmed by further research, the regulator should consider to allow intentional imbalance positions. the analysis of section 5.4 shows that additional reactions to the imbalance price incentive can further stabilize the system. several european countries already follow this approach. the netherlands early trusted in the mechanics of passive balancing. the local tso tennet stated already in 2011 that passive balancing enables a reduction of sbs (tennet, 2011). another example is the belgian market, where passive balancing is expected to reduce the required activation of balancing reserve (zapata riveros et al., 2015). according to belgium’s tso elia, this is crucial to incentivize investments in system flexibility by market participants and to minimize residual imbalances (elia, 2013). in the united kingdom, traders without physical generation are allowed to trade in the intraday market for profit and furthermore to have imbalance positions (elexon, 2016). an efficient reaction to imbalance price incentives requires a timely publication of the relevant data (hirth and ziegenhagen, 2015; joos and staffell, 2018). in the netherlands, tennet provides the information about the activated energy for upward and downward regulation for every minute with a delay of 2 min (tennet, 2019). similarly in belgium, elia publishes a live value of the current system imbalance and activated reserves as well as estimated activation costs per minute (elia, 2019a). system imbalances and prices per settlement period are then published a few minutes after the end of the settlement period (elia, 2019b). in the united kingdom, elexon goes as far to publish activations whenever it accepts a bid or offer in its balancing mechanism, thus giving the market participants information even for upcoming settlement periods (elexon, 2018). in contrast to the aforementioned examples, german tsos publish only the sb of a whole quarter-hour with a delay of almost 11 min. we recommend to reduce the delay for publishing the sb also in germany in order to give the market participants the best information for portfolio optimization. the tsos must evaluate upfront an appropriate publication time to keep the necessary quality of the data. a timely publication would also help with regards to market transparency. currently, providers of frr have an advance in information, because they have an accurate indication of the current sb through their balancing reserve activations. thus, they can use this advantage for a better forecast of the sb and a faster reaction to the intraday market to get better prices. this would diminish with a faster publication as provided by the above mentioned foreign tsos and lead to an increase of transparency among market participants. 7. conclusion the analyses presented in this paper indicate that brps react to imbalance price incentives to financially optimize their own portfolio. in a first step, we applied a correlation analysis between the price deviation from quarter-hourly intraday prices close to gate closure to the corresponding quarter-hourly day-ahead prices and different lagged sbs. there is a positive correlation between those parameters which means that intraday prices rise with a shortage in the system. the highest correlation coefficient was found for the latest published sb being an indication that market participants use this information to adapt their imbalance position by intraday trading. in a second step, we run a regression models to estimate different quantiles of the price deviation between quarter-hourly intraday and day-ahead prices. the model accuracy increases by up to 195% when adding the latest published sb to a model considering only fundamental parameters as regressors. this indicates that the sb is the most important predictor to estimate intraday price movements close to gate closure. it provides more explanatory power than just the forecast deviations the brps must compensate. the price effect of the lagged sb is not linear. higher absolute sbs have a stronger impact on intraday price movements. reasons might be the convex merit order of flexible assets on the intraday market and the higher price incentives that are associated with high absolute sbs. so, the intraday trading close to gate closure is highly affected by reactions to the sb. if the sb is assumed to be short, market participants buy energy on the intraday market and vice versa. this behavior is called passive balancing and can either reduce their own imbalance or even increase it. the financial benefit of the intraday position itself and the effect on the sb is the same for both situations. nonetheless or precisely for that reason, intraday trading close to gate closure has a positive impact on balancing demand and supply. it reduces both the required balancing energy and high sbs up to 5%. our analyses also show that this behavior did not cause situations with a critical overshoot of the sb. in fact, it could even diminish strong overshoots of table 7: impact of a doubling of the net trading volume on system stability indicators time period last 4.35 min last 19.35 min total absolute sb −16.3 gwh/a −30.8 gwh/a −0.52% −0.97% absolute sb0.95 −2.26 mw −8.31 mw −0.23% −0.86% number of additional strong overshoot 2016-2018 +6 -2 number of additional critical overshoot 2016-2018 0 0 sb: system balance koch and maskos: passive balancing through intraday trading: whether interactions between short-term trading and balancing stabilize germany’s electricity system international journal of energy economics and policy | vol 10 • issue 2 • 2020 111 the sb. under the current status, there is still room for more reactions to the sb. according to our calculation, doubling the observed net intraday volumes within the last minutes of trading leads – without consideration of any feedback effects – to a small reduction of balancing demand and high sbs without causing critical overshoots. reacting to the latest published sb could be even more efficient with an earlier publication of that information. the german tsos normally publish the sb of a whole quarter-hour approximately after 11 min, whereas the dutch and belgian tso provide the information about the activated balancing reserve energy within every minute with a delay of 2 min. the german tsos should consider to adapt such an approach for increased efficiency in balancing activities. it can help market participants to better estimate the sb in order to prevent overshooting and reduce balancing reserve activations. moreover, it would help to reduce the advance in information for balancing reserve providers and increase transparency among market participants. 8. acknowledgements the authors want to thank entelios gmbh for access to market data on successfully settled trades at epex spot. references 50hertz transmission gmbh, amprion gmbh, tennet tso gmbh, transnetbw gmbh. (2017), erläuterungen zum datencenter der deutschen übertragungsnetzbetreiber. available from: https://www. regelleistung.net/ext/download/datacentercomments. [last accessed 2019 mar 28]. 50hertz transmission gmbh. (2019), übersicht abgeschlossener bilanzkreisverträge. https://www.50hertz.com/de/vertragspartner/ bilanzkreiskunden. [last accessed 2019 sep 16]. amprion gmbh. (2019), bilanzkreise. available from: https://www. amprion.net/strommarkt/bilanzkreise. [last accessed 2019 sep 16]. borradaile, g. (2003), statistics of earth science data: their distribution in time, space, and orientation. berlin, heidelberg: s.l. springer berlin heidelberg. brijs, t., de jonghe, c., hobbs, b.f., belmans, r. (2017), interactions between the design of short-term electricity markets in the cwe region and power system flexibility. applied energy, 195, 36-51. bundesnetzagentur. (2012), modell zur berechnung des regelzonen übergreifenden einheitlichen bilanzausgleichs energiepreises (rebap) unter beachtung des beschlusses bk6-12-024 der bundesnetzagentur vom 25.10.2012. available from: https://www. regelleistung.net/ext/static/rebap. [last accessed on 2018 jun 12]. bundesnetzagentur. (2013), bilanzkreisvertrag. https://www. bundesnetzagentur.de/de/service-funktionen/beschlusskammern/ bk06/bk6_83_zug_mess/838_bilanzkreisvertrag/bk_vertrag_ node.html. [last accessed on 2019 mar 28]. bundesnetzagentur. (2018), pressemitteilung bundesnetzagentur ändert zuschlagsmechanismus bei ausschreibung von regelenergie. available from: https://www.bundesnetzagentur.de/shareddocs/downloads/ de/allgemeines/presse/pressemitteilungen/2018/20180516_ regelenergie.pdf;jsessionid=6d04ad4e91f720d712fc9bd742e8 93f7?__blob=publicationfile&v=2. [last accessed on 2019 sep 04]. bunn, d., andresen, a., chen, d., westgaard, s. (2016), analysis and forecasting of electricty price risks with quantile factor models. the energy journal, 37. doi 10.5547/01956574.37.1.dbun. chaves-ávila, j.p., hakvoort, r.a., ramos, a. (2014a), the impact of european balancing rules on wind power economics and on shortterm bidding strategies. energy policy, 68, 383-393. chaves-ávila, j.p., van der veen, r.a.c., hakvoort, r.a. (2014b), the interplay between imbalance pricing mechanisms and network congestions analysis of the german electricity market. utilities policy, 28, 52-61. chen, d., bunn, d.w. (2010), analysis of the nonlinear response of electricity prices to fundamental and strategic factors. ieee transaction power systems, 25, 595-606. elexon. (2016), imbalance pricing guidance. available from: https:// www.elexon.co.uk/documents/training-guidance/bsc-guidancenotes/imbalance-pricing. [last accessed on 11 apr 2019]. elexon. (2018), bmrs api and data push user guide. available from: https://www.elexon.co.uk/documents/training-guidance/bscguidance-notes/bmrs-api-and-data-push-user-guide-2. [last accessed on 2019 may 16]. elia. (2013), evolution of ancillary services needs to balance the belgian control area towards 2018. available from: http://www.elia.be/~/ media/files/elia/grid-data/balancing/reserves-study-2018.pdf. [last accessed on 2019 apr 11]. elia. (2019a), current system imbalance. available from: http://www.elia. be/en/grid-data/balancing/current-system-imbalance. [last accessed on 2019 may 13]. elia. (2019b), imbalance prices. available from: http://www.elia.be/en/ grid-data/balancing/imbalance-prices. epex spot se. (2017), exchange council approves the introduction of 15-minute contracts on the belgian and dutch market: trading until delivery to be launched on the german market. https:// www.epexspot.com/document/37626/170612_epex%20spot_ exchange%20council.pdf. [last accessed on 2019 apr 11]. epex spot se. (2018), cross-border intraday: questions and answers. available from: https://www.epexspot.com/document/40068/ xbid%20q%26a. [last accessed 2019 mar 2019]. essl, a. (2018), estimation of flexibility potentials in electricity systems for the integration of renewable energies with machine learning analytics, dissertation. vienna university of technology. european parliament. (2011), regulation no 1227/2011 of the european parliament and of the council on wholesale energy market integrity and transparency. frade, p., vieira-costa, j., osório, g., santana, j., catalão, j. (2018), influence of wind power on intraday electricity spot market: a comparative study based on real data. energies, 11, 2974. geman, h., roncoroni, a. (2006), understanding the fine structure of electricity prices. the journal business, 79, 1225-1261. hagemann, s. (2015), price determinants in the german intraday market for electricity: an empirical analysis. journal of energy markets. doi 10.2139/ssrn.2352854. hagemann, s., weber, c. (2013), an empirical analysis of liquidity and its determinants in the german intraday market for electricity. ewl working paper. hao, l., naiman, d. (2007), quantile regression. thousand oaks c: sage publications, inc. hirth, l., ziegenhagen, i. (2015), balancing power and variable renewables: three links. renewable and sustainable energy reviews, 50, 1035-1051. hu, j., harmsen, r., crijns-graus, w., worrell, e., van den broek, m. (2018), identifying barriers to large-scale integration of variable renewable electricity into the electricity market: a literature review of market design. renewable and sustainable energy reviews 81, 2181-2195. jónsson, t., pinson, p., madsen, h., nielsen, h. (2014), predictive koch and maskos: passive balancing through intraday trading: whether interactions between short-term trading and balancing stabilize germany’s electricity system international journal of energy economics and policy | vol 10 • issue 2 • 2020112 densities for day-ahead electricity prices using time-adaptive quantile regression. energies, 7, 5523-5547. joos, m., staffell, i. (2018), short-term integration costs of variable renewable energy: wind curtailment and balancing in britain and germany. renewable and sustainable energy reviews, 86, 45-65. joskow, p.l. (2008), lessons learned from electricity market liberalization. the energy journal, 29. doi 10.5547/issn0195-6574-ej-vol29nosi2-3. just, s., weber, c. (2015), strategic behavior in the german balancing energy mechanism: incentives, evidence, costs and solutions. journal of regulatory economics, 48, 218-243. karakatsani, n.v., bunn, d.w. (2008), forecasting electricity prices: the impact of fundamentals and time-varying coefficients. international journal of forecasting, 24, 764-785. karanfil, f., li, y. (2017), the role of continuous intraday electricity markets: the integration of large-share wind power generation in denmark. the energy journal, 38. doi 10.5547/01956574.38.2.fkar. kiesel, r., paraschiv, f. (2017), econometric analysis of 15-minute intraday electricity prices. energy economics, 64, 77-90. koch, c., hirth, l. (2019), short-term electricity trading for system balancing: an empirical analysis of the role of intraday trading in balancing germany’s electricity system. renewable and sustainable energy reviews, 113, 109275. koenker, r. (2005), quantile regression. cambridge: cambridge university press. koenker, r., bassett, g. (1978), regression quantiles. econometrica, 46, 33. koenker, r., machado, j.a.f. (1999), goodness of fit and related inference processes for quantile regression. journal of the american statistical association, 94, 1296-1310. kyritsis, e., andersson, j., serletis, a. (2017), electricity prices, largescale renewable integration, and policy implications. energy policy, 101, 550-560. lampropoulos, i.i. (2014), energy management of distributed resources in power systems operations. eindhoven: technische universiteit eindhoven. maciejowska, k., nowotarski, j., weron, r. (2016), probabilistic forecasting of electricity spot prices using factor quantile regression averaging. international journal of forecasting, 32, 957-965. märkle-huß, j., feuerriegel, s., neumann, d. (2018), contract durations in the electricity market: causal impact of 15 min trading on the epex spot market. energy economics 69, 367-378. maskos, p. (2017), der einfluss des netzregelverbundsaldos auf den handel am kontinuierlichen intraday-markt, master thesis. berlin: technical university of berlin. misiorek, a., trueck, s., weron, r. (2006), point and interval forecasting of spot electricity prices: linear vs. non-linear time series models. studies in nonlinear dynamics and econometrics, 10. doi 10.2202/1558-3708.1362. möller, c., rachev, s.t., fabozzi, f.j. (2011), balancing energy strategies in electricity portfolio management. energy economics, 33, 2-11. niciejewska, k. (2017), neue trading möglichkeiten an der epex. available from: https://www.tennet.eu/fileadmin/user_upload/the_electricity_ market/customers/bkv-forum_2017/7_tennet_bkv_forum_2017_ epex_niciejewska.pdf. [last accessed on 2019 mar 12]. nord pool. (2018), xbid webinar. available from: https://www. n o r d p o o l s p o t . c o m / g l o b a l a s s e t s / d o w n l o a d c e n t e r / x b i d / xbid-webinar_june.pdf. [last accessed on 2019 may 31]. nowotarski, j., weron, r. (2015), computing electricity spot price prediction intervals using quantile regression and forecast averaging. computational statistics, 30, 791-803. pape, c., hagemann, s., weber, c. (2016), are fundamentals enough? explaining price variations in the german day-ahead and intraday power market. energy economics, 54, 376-387. remppis, s., gutekunst, f., weißbach, t., maurer, m. (2015), influence of 15-minute contracts on frequency deviations and on the demand for balancing energy. bonn, germany: international etg congress. röben, f., schäfers, h. (2018), integration of power balancing markets in europe transparency as a design variable. 41st iaee international conference. groningen: transforming energy markets. tanrisever, f., derinkuyu, k., jongen, g. (2015), organization and functioning of liberalized electricity markets: an overview of the dutch market. renewable and sustainable energy reviews, 51, 1363-1374. tennet tso gmbh. (2019), bilanzkreise. available from: https://www. tennet.eu/de/strommarkt/strommarkt-in-deutschland/bilanzkreise. [last accessed on 2019 sep 16]. tennet. (2011), imbalance managemnet tennet: analysis report. available from: https://www.tennettso.de/site/binaries/content/ assets/transparency/publications/tender-of-balancing-power/ imbalance-management-tennet---analysis-report.pdf. [last accessed 2018 jun 12]. tennet. (2019), balance delta plus prices. available from: http:// www.tennet.org/english/operational_management/system_ data_relating_implementation/system_balance_information/ balansdeltawithprices.aspx#paneltabtable. [last accessed on 2019 apr 11]. transnetbw gmbh. (2019), bilanzkreise und bilanzkreisvertrag. available from: https://www.transnetbw.de/de/strommarkt/ bilanzierung-und-abrechnung/bilanzkreise-und-bilanzkreisvertrag. [last accessed on 2019 sep 16]. valitov, n., maier, a. (2017), the impact of the publication of unplanned power plant non-usabilities on intraday electricity prices: empirical evidence for germany and austria. 40th iaee international conference. van der veen, r.a.c., hakvoort, r.a. (2016), the electricity balancing market: exploring the design challenge. utilities policy, 43, 186-194. wolff, g., feuerriegel, s. (2017), short-term dynamics of day-ahead and intraday electricity prices. international journal of energy sector management, 11, 557-573. wooldridge, j.m. (2013), introductory econometrics: a modern approach. mason ohio: south-western cengage learning. zapata riveros, j., donceel, r., van engeland, j., d’haeseleer, w. (2015), a new approach for near real-time micro-chp management in the context of power system imbalances a case study. energy conversion and management, 89, 270-280. international journal of energy economics and policy vol. 5, no. 1, 2015, pp.182-196 issn: 2146-4553 www.econjournals.com 182 econometric prediction on the effects of financial development and trade openness on the german energy consumption: a startling revelation from the data set abdulkadir abdulrashid rafindadi department of economics, usmanu danfodiyo university, sokoto, nigeria. email: aarafindadi@yahoo.com abstract: this study aims to predict the effects of financial development and trade openness on the german energy consumption. to ensure this, the study used time series data from 19702013. following to this, the zivot-andrew structural break unit root test, the bayer-hank combined cointegration test, the ardl bounds test and the vecm granger causality test were applied. the findings of the study confirmed the existence of cointegration among the variables. as a result, the study discovered that economic growth adds to energy demand in germany. surprisingly, financial development, capital use and trade openness were found to decline energy demand. it was discovered that a 1% increase in economic growth influence energy consumption by 2.1053%., while a 1% increase in financial development, capital use and trade openness decrease energy consumption by 0.1863%, 0.9269%, 0.2091% respectively. the causality analysis reveals the existence of feedback effect between financial development and energy consumption and same inference was found to exist between trade openness and energy consumption. the results of the granger causality analysis reveal that economic growth granger-cause energy consumption, financial development, capital use and trade openness in germany. in the light of this, the study advocates for a continued investment effort in renewable energy and the adoption of those policies and strategies that will promote the use of ‘green’ technologies at the industrial level. while at the household level, investment should be encouraged in the appropriate energy infrastructure that could assist with the simultaneous satisfaction of efficient energy usage. keywords: economic growth; financial development; trade; energy; germany jel classifications: c61; d24; q42 1. introduction energy is the life wire and the most crucial element that facilitates production and production activities to take place in such a coherent, efficient and effective manner, this fact is irrespective of whether a country is developed or a developing nation. in essence, energy is a key production component comparable to non except land, labour and capital. in addition to that, energy consumption is among the fundamental indicator that signifies an existing rise in economic growth and development or otherwise (ucan et al., 2014). supporting this claim, halicioglu (2009) in his theoretical wisdom emphasised that economic advancement and productivity may be mutually established and that economic growth is directly associated with efficient energy utilization. additionally, higher economic growth necessitates additional utilisation of energy, similarly “more efficient energy use” requires an advanced or advancing economic growth prospects or in other cases a significant rise in the welfare position of individuals within a nation. therefore, the direction of causality may not be a determined priori. underscoring the direction of this argument, multiplicities of studies have established that germany was the largest energy consumer in europe and the eighth-largest energy consumer in the world in 2012. electricity generation in germany stood at 567.3 billion kwh between the periods of 1991 to 2011 while in 2013, electricity generation in germany was estimated to stand at 575.95 billion kwh. the consumption of electricity on the other hand was put at 544.26 billion kwh in periods of 1991 and 2011 while in 2013 electricity consumption declined to 537.87 billion kwh (eia, 2013). this vast energy generation, consumption and efficiency was among other crucial factors that propelled the country to be the largest and highly developed economy throughout europe, thus giving econometric prediction on the effects of financial development and trade openness on the german energy consumption: a startling revelation from the data set 183 it the 4th global ranking in terms of gdp after the united states, china, and japan in 2012 (eia, 2013). in another related development, the eia (2013) pointed out that germany is the world's largest operator of non-hydro renewable energy capacity and the world's second largest generator of wind energy. nuclear power accounted for only 17.7% of the national electricity supply in 2011, compared to 22.4% in 2010 (bdew, 2011). the cause for the reduced nuclear electricity energy generation in germany was due to the lesson drawn from the fukushima energy disaster in japan. this incident resulted in making germany to shut down eight of its seventeen operating reactors and also establishing the strategic plan towards the phasing out of some key nuclear energy generating plants that were previously scheduled to go offline as late as 2036. following to that, the proportion of electricity generated from renewable energy rose from 6.3% in 2000 to more than 25% in the initial half of 2012 (bdew, 2013). on the recent economic scene and despite the country’s efficient and effective energy generation and consumption, yet, the german economy was reported to be in economic contraction by about 0.1%. this situation was then saved by the rising forces of household consumption and exports which again saw the rebounding of the economy to the same figure of 0.1% in the same year of 2014. this development was a better position when compared to the 2009 german economic contraction of -3.70% (trading economics, 2014). the massive consumption scenario recorded in the 2014 german economic contraction saga ultimately led to the fall of national investment which in turn affected the financial development prospects of the country. could this situation transcend to affect the economic growth prospects in germany? an answer to this will be among the search of this study. in a related theoretical and conceptual development, payne (2010) and ozturk (2010) offered four opposing theories regarding the manner in which energy comprises the core of economic development, they emphasize that: (i) in a situation where energy consumption granger causes economic growth (i.e. the growth hypothesis) the authors posit that energy decreasing policies have to be prevented, and novel origins of sustainable and renewable energy have to be investigated, to ensure that existing demands are met with efficient supply (ii) another potential factor identified by the authors is that when causality was found to shift from financial development to energy consumption, this means that energy decreasing regulations would not imply negative consequences for economic development as economic development of the nation does not appear to be reliant on energy, (iii) if feedback hypothesis was found, then this infers the inter-reliance of energy consumption and economic growth. following to this an increase in economic growth will result in the rise of energy requirement, which in response encourages economic growth, and as a result of this and unlike the first case, energy conservation policies will inhibit the direction of economic growth (iv) in a situation where no causality connecting energy consumption and economic growth was found then this implies neutrality hypothesis, signifying that energy and development are not co-reliant. in addition to this and with regard to the fourth point, the authors continued to argue that the implementation of energy conservation measures as well as exploration of energy policies may not have a constructive impact on economic growth. having regard to the foregoing and considering the mixed result yielded by other past studies this study aims to predict the effects of financial development and trade openness on the german energy consumption. specifically the study aims to investigate the contribution of financial development, trade openness, capital and the potential rise in economic growth on energy demand to the country. the remainder of the paper is organised as follows: section 2 provides an overview of the recent empirical literature linking energy consumption to financial development, trade openness and economic growth. section 3 is the methodology which introduces the data, the model, and the model estimation procedure; section 4 contains the results and discussion. finally, section 5 presents the conclusion and recommendations for policy. table 1 indicates the position of energy in germany between the periods of 2004 to 2012. while, figure: 1 show the primary level of energy consumption in germany, between the periods of 2013. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.182-196 184 figure 1. show the primary level of energy consumption in germany, 2013 source: european nuclear society, 2013. table 1. indicating the position of energy in germany capita prim. energy production import electricity co2-emission million twh twh twh twh mt 2004 82.5 4,048 1,582 2,509 580 849 2007 82.3 3,853 1,594 2,344 591 798 2008 82.1 3,899 1,560 2,453 587 804 2009 81.9 3,705 1,478 2,360 555 750 2010 81.8 3,807 1,528 2,362 590 762 2012 81.8 3,626 1,444 2,315 579 748 change 2004-2010 -0.9 % -5.9 % -3.4 % -5.9 % 1.7 % -10.3 % mtoe = 11.63 twh, prim. energy includes energy losses that are 2/3 for nuclear power sources: key world energy statistics iea. 2. empirical review the revolutionary work by kraft and kraft (1978) on the nexus linking economic development and energy is still considered to be the main influence in the area of energy economics. the writers were the first to establish a unidirectional causal association linking gnp development and energy consumption for the united states during the time frame 1947-1974. subsequent to this splendid discovery, a number of noted researchers the likes of akarca and long (1980) made a subsequent exploration with regard to the discovery of kraft and kraft (1978). while employing an alternative data set and various research time frames, the writers rejected the discovery of a unidirectional association between energy and economic development. this response resulted in the encouragement of early writers to carry on the investigation within the sphere of energy economics by means of employing a varied study background. for example, erol and yu (1988) tactically carried out their research from 1952-1982 through dichotomising the divisions of their case study into six internationally leading industrial countries generally renowned to have considerable energy consumption prospects. the outcomes from their research disclosed considerable bi-directional causality in the instance of japan. nonetheless, a different outcome was acquired in the instance of their results from canada, which displayed some inclinations of unidirectional causality from energy to financial development. comparably, non-uniform study results were additionally established with econometric prediction on the effects of financial development and trade openness on the german energy consumption: a startling revelation from the data set 185 regards to italy and germany, which within that time frame displayed that it is financial development that encourages energy consumption, and unexpectedly none in the instance of england and france. another pioneering study linking financial development and energy consumption was that of sadorsky (2010 and 2011) in which the author argued that the sophistication and modernity of the financial system will elevate the extent of energy consumption and this has a significant role in the considerable increase and inflow of fdi, enhancement in the banking operations which stimulates the growth of the stock market which is an alternative economic infrastructure that ensure vital energy consumption as well as a significant and vibrant element of economic growth, arguably through the blossoming and thriving of entrepreneurial activities among other things. in another alternative development, tamazian et al. (2009) stated that financial development assists in encouraging local requirement which in response increases energy consumption. to confirm the logic behind this finding, karanfil (2009) conducted a research on the impacts of financial development on energy consumption within guangdong, china. the finding of the author was stated in a kind of unidirectional causal relation, which is from financial development to energy consumption. a comparable endeavour was noted in the instance of sadorsky (2010) in his research on 22 developing economies between 1990 and 2006. the conclusion of the author underscored the trend that energy consumption was vital in those continents under survey particularly in increasing the spate of financial development. this result urged shahbaz and lean (2012) to explore the precision of the impact of how financial development can enhance energy consumption in pakistan. in their own approach, the writers established that this can be attributed mainly to the capability of financial development to encourage requirement of consumables in facilities as well as non-facilities founded operations, and that there is bidirectional granger causality on one another; nonetheless, they additionally discovered that the former overshadows the latter within pakistan. according to the previous research suppositions, it is evident at this juncture to know that an increase ineffectual and competent entrepreneurial operations in a country will result in a likely growth in export, thus rendering necessary the requirement for additional machineries as well as export directed apparatus for utilisation in delivery and shipping of goods to the airports and harbours, where such exports are subsequently packed and re-packed to international destinations. the chain of operations in this undertaking needs energy to function. in addition to this, an increase in commercial output, exportations and alternative value added economic operations will result in a rise in the consumption of energy and the opposite will be true. similarly, the export-directed energy concept asserts that a decrease in exports affects consumption of energy. however, the energy directed hypothesis on its part determined that any considerable reduction in consumption of energy affects the movement of exports. in another perspective, it has been established by leading researchers such as shahbaz and lean (2012) that the availability of a causal relationship linking exports and energy is quite considerable, taking into account that energy is an important aspect in establishing the direction of exports although exports are significant aspects in accounting for consumption of energy. these associations linking consumption of energy and inputs additionally has a comparable dynamic inclination similar to export; in the two different instances, energy consumption may not be prevented. hypothetically any reduction in imports will impact consumption of energy by means of a considerable hindrance in directing the imported produce to the correct location and individual networks thereby stopping delivery, and encroaching on the structure of the supply network. overall, in addition to the failure of the welfare structure, it is apparent that a considerable disruption of output will be forthcoming. table 2 presents a summary of the literature linking trade openness and energy consumption international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.182-196 186 table 2. summary of studies linking trade openness and energy consumption no author(s) time period methodology countries direction of causality 1 haliciouglu (2009) 1960-2005 vecm granger causality turkey tr ≠ e 2 erkan et al. (2010) 1970-2006 granger causality turkey x←e 3 narayan and smyth (2009) 1974-2002 panel vecm granger causality iran, israel, kuwait. oman, saudi arabia, syria x → e 4 lean and smyth (2010) 1970-2008 ardl, tydl granger causality malaysia x ≠ e 5 sami (2011) 1960-2007 ardl, vecm granger causality japan x → e 6 sadosky (2011) 1980-2007 panel vecm granger causality bahrain, iran, jordan, oman, qatar, saudi arabia, syria, uae x → e, i ↔ e 7 sadosky (2012) 1990-2007 panel fmols, panel vecm granger causality argentina, brazil, chile, ecuador, paraguay peru, uruguay x ↔e, i → e 8 hossain (2012) 1976-2009 panel vecm granger causality saarc countries tr ≠ e 9 sultan (2011) 1970-2009 ardl, vecm granger causality mauritius x←e 10 dedeoğlu and kaya (2013) 1980-2010 cunning and pedroni (2008) causality oecd countries x ↔ e, i ↔ e 11 bouoiyour et al. (2014) 1996-2013 meta-analysis panel of 43 countries, us, eu, asia and mena mixed results 12 rafindadi and yusof (2014) 1970-2011 clement-montanesreyes’ detrended structural break, bayer and hanck, (2013); ardl, iaa and vecm granger causality south africa tr → e 13 altıntas and kum (2013) 1970-2010 ardl turkey tr ↔ e 14 rafindadi, (2015) 1970-2011 clement-montanesreyes’ detrended structural break, bayer and hanck, (2013); ardl, iaa and vecm granger causality nigeria tr → e 15 adom, p.k ( 2011) 1971-208 the toda and yamamoto granger causality test ghana g → e 16 farhani et al. (2014) 1980-2010 ardl, toda-yamamoto causality tunisia tr → e 17 rafindadi (2015) 1970 – 2013 zivot-andrew, bayer and hanck, (2013); ardl, iaa and vecm granger causality united kingdom tr ↔ e note →, ↔ and ≠ indicate unidirectional, bidirectional and no causality respectively, while x, i, tr, g and e indicates exports, import, trade openness, growth, energy consumption. econometric prediction on the effects of financial development and trade openness on the german energy consumption: a startling revelation from the data set 187 2.1 from the above review, the contributions of this study are: having regard to the above empirical appraisal, and in contrast to other empirical research, the present study is an endeavour to contribute to the energy literature by predicting the effects of financial development and trade openness on the german energy consumption. specifically the study aims to investigate the contribution of financial development, trade openness, capital and the potential rise of the german economic growth on energy demand. from this empirical finding, the study will seek to determine what policy guide could be derived in achieving a continued sustainable economic growth prospects amidst environmental and energy challenges of the country. apart from that, the majority of previous studies surveyed mainly used adf, pp, df-gls, kpss, and ng-perron tests, however, these unit root test are less parsimonious and susceptible to loss of vital information. in addition to that, these test cannot provide the mechanism of dealing with structural breaks information stemming in the series, following to this, after checking the stationarity of the data using ng perron unit root test, the study proceed to apply the zivot and andrew, (1992) structural break test to identify possible structural breaks in the series. from that analysis, the bayer and hanck, (2013) combined cointegration methodology was then applied. from these methodological application, the study then proceeds to apply the ardl bounds testing approach to cointegration in the presence of structural break. this methodology was applied due its serial advantages which include: (i) flexibility and is robustly applicable within the range of i (0) and i (1) cointegrating properties of the data set. in addition to that, simulation results have widely shown that this methodology is parsimonious and effective in providing consistent results particularly for small sample data set (pesaran and shin, 1999). (ii) allowing for the possibilities of using ols for the determination of short-run and long-run relationship (iii) the possibility of using the vecm granger causality technique in determining the causal relationship between the variables. 3. the data, model and estimation procedure the german annual data over the period of 1970-2013 has been used in this study. the data was obtained from the cd rom of the world development indicators (2013) from this source, the study collect the data on real gdp, electricity consumption (kg of oil equivalent) per capita, real domestic credit to private sector per capita, real capital stock per capita, real exports per capita, real imports per capita and finally real trade openness per capita of the german economy. this is with the main objective of investigating the dynamic linkages between economic growth, financial development, trade openness and energy consumption for the german economy with the main thrust of predicting the effects of financial development, trade openness and the rising economic growth of the country on energy consumption. the existing literature indicates that financial development affects energy demand via consumer, wealth and business effect. similarly, trade openness impacts energy consumption via income, composition and technique effect. economic growth leads energy demand via industrialization effect. this leads us to construct functional form of energy demand function as following: ),,,( ttttt tokfyfec  (1) all the variables have been transformed into logarithm. we use log-linear transformation for attaining reliable empirical results. the empirical equation of model is constructed as following: tttttt tokfyec   lnlnlnlnln 54321 (2) where, tecln is natural log of energy consumption per capita, tyln is natural log real gdp per capita (proxy for economic growth), tfln is natural log of real domestic credit to private sector proxy for financial development, tkln is natural log of real capital per capita, trade openness is indicated by natural log of trade (exports + imports) i.e. ttoln and t is residual term with assumption of normal distribution. notwithstanding the plethora of econometric methodologies that deals with the estimation and determination of the cointegrating properties of research variables such as the engle-granger, (1987) residual-based cointegration test, the johansen, (1995) system based cointegration test and, the boswijik, (1994) and banerjee et al. (1998) that suggested the lagged error correction based approaches to cointegration. in all these methodologies, pesavento, (2004) established that the potency international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.182-196 188 of these tools to provide robust outcome is limited due to their insensitivities to filter the infiltrating level of nuisance inherent in most time series data. the author further establishes that the possibility of obtaining uniform outcome among the mentioned cointegration tools is virtually difficult. according to him, while one cointegration test rejects the null hypothesis another may be bound to accept it. it is following to this shortcoming, that this research established a measure of avoiding the likely repercussion of most of these estimators by using the most up to date methodology developed by bayer and hanck, (2013). the authors in their infinite research wisdom developed a parsimonious method that helps in eliminating the likely bias of the old existing estimators with respect to determining the cointegrating properties of time series data. the methodology of the bayer and hanck, (2013) cointegration test as applied in this study aim at providing efficient estimates by eliminating the undue multiple testing procedures that is the common problem with other cointegration methodologies. to ensure its robustness, the bayer and hanck, (2013) when formulating their cointegrating model followed fisher, (1932) formula, and this is given below: )]ln()([ln2 joheg ppjoheg  (3) )]ln()ln()ln()([ln2 bdmbojoheg ppppbdmbojoheg  (4) to determine the likelihood for the occurrence of cointegration relation between variables such as in the case of using engle-granger, (1987); johansen, (1995); boswijik, (1994) and, banerjee, dolado and mestre, (1998) the following notations are observed: bojoheg ppp ,, and bdmp respectively. however, in the case of the bayer and hanck cointegration test, the decision of whether cointegration exists or not between the variables the fisher statistic is followed. in this respect, it can be concluded in favor of cointegration when the null hypothesis of no cointegration is rejected. following to this, once the critical values generated by bayer and hanck analysis are found to be less than the estimated fisher statistics and vice versa. to determine the existence of a long-run relation between the variables requires the careful detection of the direction of causality between the variables and this can be undertaken by applying the vecm (vector error correction method) granger causality framework. the vector error correction method (vecm) is as follows:                                                                                                                                                                      t t t t t t t t t t t mmmmm mmmmm mmmmm mmmmm mmmmm t t t t t t t t t ecm to k f y ec bbbbb bbbbb bbbbb bbbbb bbbbb to k f y ec bbbbb bbbbb bbbbb bbbbb bbbbb b b b b b to k f y ec 5 4 3 2 1 1 5 4 3 3 1 1 1 1 1 1 ,55,54,53,52,51 ,45,44,43,42,41 ,35,34,33,32,31 ,25,24,23,22,21 ,15,14,13,12,11 1 1 1 1 1 1,551,541,531,521,51 1,451,441,431,421,41 1,351,341,331,321,31 1,251,241,231,221,21 1,151,141,131,121,11 5 4 3 2 1 )( ln ln ln ln ln ... ln ln ln ln ln ln ln ln ln ln           (5) where tto is for exports, imports and trade, the difference operator is (1 )l and the 1tecm is obtained from the estimation of the long-run relationship. the long-run causal relationship is usually indicated by the attainment of significant position with respect to the coefficient of the 1tecm and following the t-test statistic. the f statistic for the first-differenced lagged independent variables, on the other hand, is used to test the direction of short-run causal relationship between the variables. 4. results and discussions examining the stationarity of the series is preliminary condition for cointegration analysis. following to this, the study applied the ng-perron unit root test. the results of this test are shown in table 3. the findings indicate that none of the variable is stationary at level, intercept and trend. however, at first difference, energy consumption, economic growth, financial development, capital use and trade openness were found to be stationary at 5 percent level of significance. econometric prediction on the effects of financial development and trade openness on the german energy consumption: a startling revelation from the data set 189 table 3. ng-perron unit root test variables mza mzt msb mpt tecln -0.8399 (2) -0.4382 0.5217 57.3046 tyln -3.8507 (3) -1.2634 0.3281 22.0413 tfdln -4.6787 (1) -1.1855 0.2534 17.3585 tkln -8.2175 (2) -1.9710 0.2398 11.2569 ttoln -3.8507 (1) -1.2634 0.3281 22.041 tecln -20.6158 (2) ** -3.2101 0.1557 4.4228 tyln -20.9015 (2) ** -3.2204 0.1540 4.4345 tfdln -18.5903 (1) ** -3.0322 0.1631 5.0022 tkln -19.2648 (2) ** -3.0971 0.1607 4.7695 ttoln -20.9015 (3) ** -3.2204 0.1540 4.4345 the dual asterisk ** refers to 5% level of significance. while the lag length of variables is denoted by using small parentheses. the presence of structural break makes the results of ng-perron ambiguous; in addition to that there are every likely possibilities of rendering the regression result to be spurious. to overcome this issue the zivot and andrews (1992) unit root test which has the power of taking care for a single unknown structural break stemming from the series is applied in this study. the effective application of the zivot and andrews (1992) is followed strictly on the basis of selecting of the break date which is based on t-statistic. following to this, the break date will be selected where the evidences are favorable for the null hypothesis. the zivot-andrew (1992) test with structural breaks as used in this study can be tested using the following econometric models: 1 1 1 1 1 1 .......................................(6) .........................(7) .............(8) k t t j t j t j k t t t j t j t j k t t t t j t j t j ax bt cdu d x x b bx ct bdt d x x c cx ct ddu ddt d x                                      where dut denotes the dummy variable, and it provides the shifting possibilities of the mean in each point while dtt is a shift in the trending variable. dut  1...if  t ³tb 0...if t £tb ì í ï îï anddut  t tb...if .t ³tb 0...if .t £tb ì í ï îï ….(9) the null hypothesis of unit root break date is c = 0 which indicates that the series is not stationary with a drift particularly when not having information about structural break stemming in the series while c < 0 hypothesis implies that the variable is found to be trend-stationary with one unknown time break. zivot-andrews unit root test takes control of fixing all points as potential for possible time break and does estimation through regression for all possible structural breaks successively. one of the major properties of this test is that it selects the time break on the basis of that series with a reducing effects on the one-sided t-statistic which is in order to test for cˆ( = c 1) = 1. similar to the earlier mentioned point on the properties of this structural break unit root test is that in any position where an end point exist the asymptotic distribution of the statistics is diverged to infinity point, this them makes it is possible to select a region particularly where the end points of the sample period are excluded. to the avoidance of spurious result the zivot-andrews established that the defined position of the trimming regions i.e. (0.15t, 0.85t) should be strictly adhered to in addition to that all the characteristic features of the estimation process should also be carefully international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.182-196 190 accommodated. the findings of this test as applied in this study are presented in table 4 and we find the structural breaks in the series to be in 1990, 1990, 2000, 1989 and 1992 and these are for the series of energy consumption, economic growth, financial development, capital use and trade openness at level. the variables are found to be stationary at first difference with intercept and trend. this shows that that energy consumption, economic growth, financial development, capital use and trade openness are stationary at first difference in the presence of structural breaks. having found this, we may concluded that the integrating order of the variable is i(1). table 4. zivot-andrews unit root test variable at level at 1st difference t-statistic time break t-statistic time break tecln -3.438 (1) 1990 -7.338 (2)* 1995 tyln -4.870 (2) 1990 -6.387 (1)** 2009 tfdln -4.635 (1) 2000 -5.544 (2)* 1990 tkln -5.031 (3) 1989 -5.772 (1)* 1993 ttoln -4.152 (1) 1992 -6.833 (2)* 1995 the asterisk: * and ** denote 1%, and 5% level of significance respectively. while the lag order is denoted by the parenthesis. table 5. the lag order selection var lag order selection criteria lag logl lr fpe aic sc hq 0 225.4982 na 1.47e-11 -10.7560 -10.54704 -10.6799 1 503.1571 474.0518 6.58e-17 -23.0808 -21.8270* -22.6242* 2 529.5023 38.5538* 6.52e-17* -23.1465 -20.8477 -22.3093 3 554.8737 30.9407 7.45e-17 -23.1645* -19.8210 -21.9470 * indicates lag order selected by the criterion lr: sequential modified lr test statistic (each test at 5% level) fpe: final prediction error aic: akaike information criterion sc: schwarz information criterion hq: hannan-quinn information criterion table 5 shows the results of lag selection criterion, and we find that lag 3 is suitable for empirical analysis. following to this, the aic criterion of the lag order selection of the variable was adopted due to its superior explanatory properties. following the selection of lag length 3, we proceed to apply the bayer-hanck combined cointegration tests such as eg-joh and eg-joh-bo-bdm tests. table 6 shows the results of bayer-hanck combined cointegration analysis. we note that the computed fisher f-statistics (eg-joh, eg-joh-bo-bdm) are great than critical values as we use energy consumption, financial development, capital use and trade openness as dependent variables. this leads to reject the hypothesis of no cointegration but as we used economic growth as dependent variable, the hypothesis of no cointegration was accepted. this concludes that we have four cointegrating vectors which confirm the presence of cointegration among the variables. this finding entails that there is a long-run relationship among energy consumption, economic growth, financial development, capital use and trade openness in case of germany over the period of 1970-2013. in the presence of structural breaks, the bayer-hank combined cointegration will fail to provide efficient and consistent empirical results. to avoid this, the study applied the ardl bounds testing approach to cointegration in order to assess the cointegrating relationship among the variables. the findings of the ardl analysis are reported in table 7. in that analysis the study discovered that the estimated fstatistics are found to be greater than the upper critical bounds at 1%, 5% and 10% respectively when energy consumption, financial development, capital use and trade openness were treated as dependent variables. this finding validates the presence of cointegration thus enabling the possibilities of proceeding to the next step of testing the empirical robustness of the cointegration analysis on table 7 using the johansen cointegration test. econometric prediction on the effects of financial development and trade openness on the german energy consumption: a startling revelation from the data set 191 table 6. the bayer and hanck cointegration analysis estimated models eg-joh eg-joh-bo-bdm cointegration ),,,/( tokfdyecfec 16.535** 77.862*  ),,,/( tokfdecyfy 9.907 13.733 x ),,,/( tokyecfdffd 16.266** 29.267**  ),,,/( tofdecykfk 18.604** 44.387*  ),,,/( kfdecytofto 19.437** 29.467**  the sign: * refers to significant level at 1%. while the critical values at 1% level are 15.845 (eg-joh) and 30.774 (eg-joh-bo-bdm) respectively. table 7. the results of ardl cointegration test bounds testing to cointegration diagnostic tests estimated models optimal lag length structural break f-statistics 2 normal 2 arch 2 reset 2 serial ),,,/( tokfdyecfec 2, 1, 2, 2, 2 1990 6.230*** 0.0959 [1]: 2.3638 [1]: 0.4121 [1]: 0.1050 ),,,/( tokfdecyfy 2, 2, 2, 2, 1 1990 1.182 0.5300 [1]: 2.1326 [2]: 1.6334 [2]: 2.3150 ),,,/( tokyecfdffd 2, 2, 2, 2, 2 2000 10.335* 1.3950 [1]: 5.0574 [2]: 1.7394 [1]: 3.1159 ),,,/( tofdecykfk 2, 1, 1, 2, 2 1989 6.171*** 0.3877 [1]: 0.1031 [2]: 1.6639 [2]: 2.2917 ),,,/( kfdecytofto 2, 1, 1, 1, 2 1992 6.642** 0.9975 [1]: 0.0771 [2]: 0.2882 [1]: 2.0789 significant level critical values (t= 44) lower bounds i(0) upper bounds i(1) 1 percent level 7.317 8.720 5 percent level 5.360 6.373 10 percent level 4.437 5.377 note: the asterisks *, ** and *** denote the significant at 1%, 5% and 10% levels, respectively. the optimal lag length is determined by aic. [ ] is the order of diagnostic tests. critical values were obtained from narayan (2005). the empirical robustness of cointegration results is tested by applying johansen cointegration approach, and results are shown in table 8. we find three cointegrating vectors by trace statistics, and maximum eigenvalue test reports one cointegrating vector. this favors the rejection of the hypothesis that signifies no cointegration and confirms the presence of cointegration among the variables. this finding enables us to ascertain the existence of cointegration among the variables for long-run relationship to be robust and consistent. table 8. results of johansen cointegration test hypothesis trace statistic maximum eigen value r = 0 100.0955* 38.8813** r  1 61.2142** 25.5967 r  2 35.6174** 21.3639 r  3 14.2535 13.9964 r  4 0.2570 0.2570 note: * and ** show significant at 1% and 5% levels of significance respectively. next step is to investigate the long-run and short-run impact of economic growth, financial development, capital use and trade openness on energy demand. the results are reported in table 9. in contrast to the panel study of apergis and tang (2013) our results show that economic growth has positive and significant influence on energy consumption in germany. in addition to that, we note in international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.182-196 192 our finding that a 1% increase in economic growth increases energy consumption by 2.1053 percent, and it is statistically significant at 1 percent level. financial development was found to have no significant link with energy consumption in germany. this result contradicts the novel study of erol and yu (1988). following to this startling revelation we discovered that a 1% increase in financial development decreased energy consumption by 0.1863, all else is same. in addition to that finding, the study also discovered the existence of negative and significant relationship between capital use and energy consumption. this shows that, a 1% increase in capital use declines energy demand by 0.9269, and it is statistically significant at 1% level. trade openness, on the other hand, was discovered to have a negative and significant impact on energy consumption. in that relationship, it was also discovered that, a 1% increase in trade openness decreases energy consumption by 0.2091 in germany. the results of the short-run analysis are presented in the lower segment of table 9. in that analysis, the study discovered that economic growth has positive and significant effect on energy consumption. while financial development was found to add to energy demand insignificantly. capital use declines energy demand significantly. trade openness increases energy consumption insignificantly. the ecm is found to be negative and significant which shows the convergence from short-run towards long-run equilibrium path. the estimate of ecm term was found to be -0.1620 which confirms that short-run deviations are corrected by 16.20% every year. this shows that the convergence from short-run towards long-run will take 6 years and 1 month. the results of diagnostic test from this study show the absence of serial correlation, autoregressive conditional heteroskedasticity and white heteroskedasticity. the results of ramsay reset test confirm the specification of short-run model. table 9. long and short-runs results dependent variable = tecln long-run analysis variables coefficient std. error t-statistic prob. constant -0.7765 1.3518 -0.5744 0.5692 tyln 2.1053* 0.3048 6.9068 0.0000 tfln -0.1863*** 0.1063 -1.7522 0.0880 tkln -0.9269* 0.1385 -6.6929 0.0000 ttoln -0.2091* 0.0589 -3.5470 0.0011 short-run analysis variables coefficient std. error t-statistic prob. constant -0.0122** 0.0054 -2.2406 0.0313 tyln 1.4470* 0.3439 4.2075 0.0002 tfln 0.0418 0.1051 0.3981 0.6929 tkln -0.3660* 0.1180 -3.1002 0.0037 ttoln 0.0077 0.0617 0.1261 0.9003 1tecm -0.1620** 0.0759 -2.1328 0.0398 2r 0.5498 f-statistic 8.7960* d. w 1.4891 short-run diagnostic tests test f-statistic prob. value serial2 1.1175 0.4000 arch 2 2.0230 0.1629 white 2 2.6662 0.2912 remsay2 0.3437 0.5614 note: *, ** and *** show significant at 1%, 5% and 10% level of significance respectively. econometric prediction on the effects of financial development and trade openness on the german energy consumption: a startling revelation from the data set 193 the vecm granger causality analysis the vecm granger causality test is used for determining the direction of causality between the variables. this will be helpful in enabling us to determine a comprehensive economic, financial, trade and energy policies that will be very vital in controlling energy demand towards sustainable economic growth prospects in the case of germany. the results of this analysis are reported in table 10. the findings in that table reveal that economic growth granger causes energy demand, financial development, capital use and trade openness in the long-run. in addition to that, we found the existence of the feedback effect between financial development and energy consumption. capital use was also found to granger-cause energy consumption and in resulting circumstances, energy consumption granger causes capita use. this means that there is a bi-directional causal relationship to exist between trade openness and energy consumption in the long-run in germany. in the short-run, the study discovered the existence of the same bi-directional causality between per capita income and energy consumption, between energy consumption and physical capital, between per capita income and physical capital, between per capita income and trade openness. following to this the study further discovered the existence of short-run unidirectional causality running from energy consumption to trade openness and on the other hand there is unidirectional causality that was found to be running from financial development to energy consumption. in addition to that, the existence of a long-run bidirectional causality running between energy consumption and per capita income was also discovered, following to this, the feedback effect was found between financial development and energy consumption in germany. table 10. the vecm granger causality analysis dependent variable direction of causality short-run long-run 1ln  tec 1ln  ty 1ln  tfd 1ln  tk 1ln  tto 1tect tecln …. 7.0646* [0.0030] 0.3114 [0.7204] 3.1028*** [0.0591] 4.4771** [0.0196] -0.0750* [-2.9310] tyln 7.4067* [0.0023] …. 0.2953 [0.7463] 25.2264* [0.0000] 5.7283* [0.0075] …. tfdln 0.4135* [0.6651] 0.7168 [0.4782] …. 0.6565 [0.5262] 0.1605 [0.8524] -0.1679*** [-1.6881] tkln 5.9609* [0.0068] 32.9384* [0.0000] 0.0394 [0.9613] 1.0482 [0.3634] …. -0.4308* [-3.1996] ttoln 1.7219 [0.1954] 9.9209* [0.0005] 0.80009 [0.4581] 2.2980 [0.1173] …. -0.1605*** [-1.7041] note: * and ** show significance at 1 and 5 percent levels respectively. in short-run, the bidirectional causality is found between energy consumption and economic growth and same is true for capital use and energy consumption. energy consumption was also found to granger causes financial development. the relationship between economic growth and capital use is bidirectional and same is true for trade openness and capital use. trade openness causes energy demand and economic growth in the granger sense. 5. concluding remarks and policy implications this study conducted an econometric prediction on the effects of financial development and trade openness on the german energy consumption. specifically the study delved into the determination of the linkages between economic growth, financial development, capital use, trade openness and energy consumption using energy demand function for the case of germany. the study used time series data over the period of 1970-2013. in doing so, the unit root properties of the data was examined using the ng-perron unit root tests in addition to this, the traditional structural break unit root test by zivot-andrew was applied. the cointegration properties of the data was observed using the bayer-hanck combined cointegration test and the ardl bounds test approach to cointegration while the vecm granger causality analysis is applied to examine the causal relationship between the series. the results confirmed the existence of cointegration among the variables. as a result of this development, the study discovered that, economic growth adds to energy demand in the case of international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.182-196 194 germany, in respect to this, the econometric prediction exercise showed that a 1% rise in economic growth in germany will lead to 2.1053% increase in energy consumption and this is found to be significant at 1% level. in contrast to this finding, the study discovered that financial development does not have any effect on the german energy consumption meaning that the contribution of the developed financial sector in germany cannot influence the existing energy consumption of the country. this may possibly be due to the recent economic contraction faced by the country which stands to about -3.70% in 2009 and 0.1% in 2014. capital use, on the other hand, was found to be inversely related with energy consumption. similar to that development, trade openness was also found to decline energy consumption in the long-run. in the short-run, the study discovered that it is only economic growth that has the same positive and significant effect on energy consumption while all others were found to be insignificant. the causality analysis established the existence of the feedback effect between financial development and energy consumption and same case was found about trade openness and energy consumption. the causality result with respect to capital use was found to granger-cause energy consumption, and energy consumption granger causes capital. economic growth was also found to granger-cause energy consumption; same inferences were also found with respect to financial development and trade openness. our concluding remark in this study rests on the fact that energy is a crucial part of production factors in the contemporal era, and a cardinal means of achieving sustainable economic growth not only in germany but the world over; following to this, ferguson et al. (2000) argued that for the global economy as a whole, there is a strong interrelation between energy consumption and the creation of wealth (economic growth) than that connecting total use of energy and wealth (economic growth). the author continue to insist that, in the same rich nations like germany, the rise in economic growth with time will correlate with the rise in the amount of energy that is used and this will modestly make energy consumption a root cause to economic growth. by this development, it means that the higher the degree of economic growth in germany the greater will be the energy consumption. in this respect, and going by the arguments raised by ferguson (2000) and following the discoveries observed in this study, we are of the view that the likely policy implication that could arise in the longrun, may relate to the persistent rise in energy demand which could then lead to the rise of more pollutants. this may be due to the un-relented need for a significant rise in economic growth for the case of germany, with this situation in focus; the energy requirement to sustain the degree of economic growth attained will follow the hypothesis raised by ferguson (2000) while failure to comply with that development could lead to an ailing energy system due to insufficient supply. following to this, it is pertinent to argue that an ailing energy system is synonymous with an ailment in the planning process, and an ailing planning process is tantamount to precarious economic growth. as a result of this electricity conservation policies in germany will significantly affect the rate of economic growth and also that energy conservation policies cannot be implemented to combat global warming without restraining the process of economic growth particularly since energy consumption does not granger cause economic growth. this twin reason will lead to more energy consumption as argued earlier. this development will in turn lead to more environmental pollutants thereby leading to the encroachment of the eu vision 20/20/20. to avoid this and ensure a balance between energy consumption and environmental quality the study propose for the german energy policy makers to continue with their effort in investing heavily in new renewable energy source. in addition to this, new ‘green’ technologies that are less dependent on fossil fuels should be encouraged for industrial usage. although the existence of a priori developed financial infrastructure and energy efficient technologies have favoured efficient energy use in germany, notwithstanding this, a continued and careful attention should consistently be given at both the industrial and household level, by encouraging more investment in the appropriate energy infrastructure that could assist with the simultaneous satisfaction of efficient energy usage. in doing so, both the economic performance and the quality of the environment can be sustained and balanced. this study also noted that germany is the frontrunner in the eu particularly in the point of renewable energy usage and the ambition to decrease greenhouse gas emissions and mitigate the climate change. the ultimate solution proposed in this study, will in our view assist in keeping track with the eu-wide energy strategy of 20/20/20 target i.e. (i) savings of 20% in energy use compared to projections, (ii) achieving 20% portion of the renewable energy combination from the reserves of renewable power, (iii) a 20% decrease in greenhouse gas emissions by 2020. econometric prediction on the effects of financial development and trade openness on the german energy consumption: a startling revelation from the data set 195 references akarca, a.e., long, t.v.i.i., (1980). on the relationship between energy and gnp: a reexamination. journal of energy development,.5, 326–331. apergis, n and tang, c.f., (2013). is the energy-led growth hypothesis valid? new evidence from a sample of 85 countries. energy economics, 38, 24–31. adom, p.k (2011). electricity consumption-economic growth nexus: the ghanaian case. international journal of energy economics and policy,1,18-31. altıntas, h and kum, m., (2013). multivariate granger causality between electricity generation, exports, prices and economic growth in turkey. international journal of energy economics and policy, 3, 41-51. banerjee, a., dolado, j., mestre, r., (1998). error-correction mechanism test for cointegration in a single-equation framework. journal of time series analysis, 19, 267-283. bayer, c., and hanck, c. (2013). combining non‐cointegration tests. journal of time series analysis 34, 83-95. bdew (2011)-anlage%20grafik%20zur%20pm%20stromerzeugungsmix%202011.pdf retrieved, 29 september, 2014 bdew (2013) bundesverband der energieund wasser wirtschaft e. v. reinhard tstraße 32 10117. boswijk, h.p., (1994). testing for an unstable root in conditional and structural error correction models. journal of econometrics. 63, 37-60. bouoiyour, j. selmi, r. ozturk, i., (2014). the nexus between electricity consumption and economic growth: new insights from meta-analysis. international journal of energy economics and policy, 4, 621-635. dedeoğlu, d., kaya, h., (2013). energy use, exports, imports and gdp: new evidence from the oecd countries energy policy, 57, 469-476. eia (2013). http://www.eia.gov/countries/country-data.cfm?fips=gm&trk=m. retrieved 29th september, 2014. engle, r.f., granger c.w.j., (1987). co-integration and error correction: representation, estimation, and testing. econometrica, 55, 251-276. erol, u. & yu, e.s.h., (1988). on the causal relationship between energy and income for industrialized countries. journal of energy development,13, 113–122. erkan, c., mucuk, m. & uysal, d., (2010). the impact of energy consumption on exports: the turkish case. asian journal of business management, 2,.17–23. european nuclear society, (2013). http://www.euronuclear.org/info/encyclopedia/p/pri-con-ger.htm. retrieved 29th september, 2014. farhani s, shahbaz m, sbia r, chaibi a. (2014). what does mena region initially need: grow output or mitigate co2 emissions? economic modeling,38, 270–81. fisher, r. a. (1932). statistical methods for research workers, oliver & boyd, edinburgh, 4th edition. ferguson, r. wilkinson, w. and hill, r., (2000). electricity use and economic development. energy policy, 28, 923-934. halicioglu f. (2009). an econometric study of co2 emissions, energy consumption, income and foreign trade in turkey. energy policy, 37, 1156–64. hossain, m.s., (2012). multivariate granger causality between economic growth, electricity consumption, exports and remittance for the panel of three saarc countries. global journal of management & business research 12, 40–54. johansen.s., (1995) likelihood-based inference in cointegrated vector autoregressive models, oxford university press. kraft, j. & kraft, a., (1978). on the relationship between energy and gnp. journal of energy development, 3, 401–403. karanfil, f., (2009). how many times again will we examine the energy–income nexus using a limited range of traditional econometric tools? energy policy, 36, 3019–3025. key world energy statistics (2013). http://www.iea.org/publications/freepublications/publication/.pdf lean, h.h., smyth, r. (2010). on the dynamics of aggregate output, electricity consumption and exports in malaysia: evidence from multivariate granger causality tests. applied energy, 87, 1963–1971. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.182-196 196 narayan, p.k., smyth, r. (2009). multivariate granger causality between electricity consumption, exports and gdp: evidence from a panel of middle eastern countries. energy policy, 37, 229– 236. narayan, p.k. & smyth, r., (2005). electricity consumption, employment and real income in australia: evidence from multivariate granger causality tests. energy policy, 33, 1109–1116. ozturk, i., (2010). a literature survey on energy-growth nexus. energy policy 38, 340-349. payne j. (2010). a survey of the electricity consumption-growth literature. applied energy 87, 37233731. pesaran, m.h. & shin, y., (1999). an autoregressive distributed-led modeling approach to cointegration analysis. in econometrics and economic theory in the 20th century. the ragnar frisch centennial symposium, ed. steinar strom. cambridge: cambridge university press. pesavento, e., (2004). analytical evaluation of the power of tests for the absence of cointegration. journal of econometrics, 122, 349-384. rafindadi, a.a., (2015). could the expanding economic growth and trade openness of the united kingdom pose a threat to its existing energy predicaments? international journal of energy economics and policy, 5,121-137 rafindadi, a.a., yusof, z., (2014). does financial development adds to energy consumption in south africa? an application of structural break cointegration and the innovation accounting test. 5th international conference on business and economic research (5th icber, 2014) 24-25th: http://internationalconference.com.my/proceeding/icber2014_proceeding/5thicber_proceeding/0 64_187_5thicber2014_proceeding_p854.pdf. rafindadi,a.a., (2015). does the need for economic growth influence energy consumption and co2 emissions in nigeria? empirical evidence from combined cointegration and the innovation accounting test. .http://www.internationalconference.com.my/proceeding/icmef2014 _proceeding/icmef2014_proceeding.html399_429_3rdicmef2014_proceeding_399_429.pdf. sadorsky, p., (2010). the impact of financial development on energy consumption in emerging economies. energy policy, 38, 2528–2535. sadorsky, p. (2011) trade and energy consumption in the middle east. energy economics 33, 739-49. sadorsky, p., (2012). energy consumption, output and trade in south america. energy economics.,34, 476–488. sami, j., (2011). multivariate cointegration and causality between exports, electricity consumption and real income per capita: recent evidence from japan. international journal of energy economics and policy 1, 59-68. shahbaz, m. & lean, h.h., (2012). does financial development increase energy consumption? the role of industrialization and urbanization in tunisia. energy policy, 40, 473–479. sultan, r., (2011). “an econometric study of aggregate output, energy and exports in mauritius – implications for trade and climate policy”. university of mauritius, reduit, mauritius tamazian, a., chousa, j.p. & vadlamannati, c., (2009). does higher economic and financial development lead to environmental degradation: evidence from bric countries. energy policy, 37, 246–253. trading economics (2014). http://www.tradingeconomics.com/articles/11142014075105.htm. ucan, o . aricioglu, e. yucel, f. 2014 energy consumption and economic growth nexus: evidence from developed countries in europe international journal of energy economics and policy, 4, 411-419. us energy information administration.(2014) "international energy statistics". retrieved 29th september 2014 world bank (2013). world development indicators. washington, d.c: world bank. zivot, e., & andrews, d. w., (1992). further evidence on the great crash, the oil-price shock, and the unit-root. journal of business & economic statistics, 10, 251–270. . international journal of energy economics and policy | vol 5 • issue 2 • 2015 385 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2015, 5(2), 385-401. review paper on economic growth–aggregate energy consumption nexus zaidi isa, ahmed r.m. al sayed*, sek siok kun school of mathematical sciences, universiti kebangsaan malaysia, 43600 bangi, selangor, malaysia. *email: alsayed@siswa.ukm.edu.my abstract the aim of this study is to survey the empirical studies which interested in detecting the causal relationship between energy consumption (ec) and economic growth, and to provide some recommendations to policymakers for designing the environmental policies and policy implications of effective energy. our review paper concentrates to make a survey depending on included variables in the studies, thus it has been classified into two groups; bivariate framework and multivariate framework. the results show that the multivariate studies support the feedback hypothesis more than the bivariate studies with (45.7%) and (29.5%) respectively. in contrast of that in neutrality hypothesis, the bivariate framework studies support it with (26.2%) which is more than that in multivariate framework (12.1%) only. in the other hand the results by considering the whole empirical studies in our survey support the hypotheses as the following; (34.3%), (24.0%), (19.7%) and (22.0%) for the feedback, growth, conservation and neutrality hypothesis respectively. moreover we provide some suggestions for future studies; it should focuses more on new approaches consist the multivariate framework rather than by applying common methods with the same variables in bivariate framework only, which could be solved by adding unprecedented variables such as technology innovation, index investment and environmental quality with applying environmental kuznets curve. in the analysis should considers the possibility of structural breaks, the coefficients signs, and distinguish between the short and long run causality relationship. and it should include two distinct groups of ec; renewable and nonrenewable energy rather than aggregate or disaggregate energy consumption. keywords: economic growth, aggregate energy consumption, causality relationship jel classifications: q4, q43 1. introduction the issue of economic growth and energy consumption (ec) relationship becomes a hot topic and it has been extensively examined by researchers and industrial sectors. in the last four decades, the causal relationship between economic growth (gross domestic product [gdp]) and ec has investigated widely in many empirical researches. early studies had conducted by griffin and gregory (1976), berndt and wood (1979), and berndt (1980, 1990) and they have postulated the substitutability and complementarity between gdp and ec, while bergman (1988), jorgenson and wilcoxen (1993), kemfert and welsch (2000), and smulders and de nooij (2003) and others, had investigated the effects of energy within a general equilibrium approach. the empirical studies have concentrated on different countries, utilizing a variety of time periods, proxy model variables with applying different methods to detect the relationship between gdp and ec. moreover the findings of those empirical studies have been reported different results. it appears to be varying on the causality relationships direction and in the long-term versus short-term. chen et al., (2007) propose that the variation in the results of the previous literatures due to the several changing on the data set, econometric methodologies, different target groups, different characteristics involved the different economic histories and political, different indigenous energy supplies, different political arrangements, different institutional arrangements, different energy policies and different cultures, etc. karanfil (2008) has expressed that the results in developing countries studies might be not accurate and that due to unrecorded activities into real gdp correctly, subsequently examine the relationship between ec and real gdp may not give reliable results. however most of previous studies have ignored to include other factors in their model study such as environmental quality (eq) which may have an effect on international journal of energy economics and policy | vol 5 • issue 2 • 2015386 isa, et al.: review paper on economic growth–aggregate energy consumption nexus gdp, knowing that there are few recent studies considered that variable by using co2 or ghg as proxy variables, they suggest that it plays a vital role in both of gdp and ec. the causality relationship between the gdp and ec is not conclusive to support the policy maker to take their decision. indeed, realization of the interrelationship and the causality direction between gdp, ec and other factors such as eq, index investment, capital, and technology innovation are significant in designing and implementation of environmental and energy policies. in light of the aforementioned literatures, the main purpose of this paper is to survey the empirical literatures on the causality relationship between ec and gdp. to best of our knowledge this survey paper is the first paper surveys the relevant literatures on aggregate ec and economics nexus for a period 1978-2014. the remaining parts of this paper is organized as follows; section 2 illustrates the forth hypotheses which represent the results of the causality relationship between ec and gdp. section 3 surveys the empirical studies in detecting the causality between ec and gdp by two parts, first part the studies which concentrate into bivariate framework, while the second part focuses into the multivariate framework studies, then the discussion of results. section 4 provides remarkable conclusion and suggestion for future research. 2. the four hypotheses representing the results of causality relationship between ec and economic growth in this area of the empirical researches; there are enormous amount of studies focuses on detecting the causality link between gdp and ec, followed by kraft and kraft (1978) who investigated the relationship between those variables for usa, and their findings suggest that causality relationship has a significant policy implications. in other hands those studies have applied several techniques to examine the causality direction in both long run and short run into miscellaneous countries. however those empirical studies have failed to acquire unanimous results. those studies have reported different outcomes, due to that we are going to categorize them into four groups depending on their findings of the causality direction, as same as the classification of hypotheses on the ec-economic growth nexus. first results group shows bidirectional causality between ec and gdp which represented by feedback hypothesis, it postulates a joint effect between ec and gdp, each one of them has effect the other one, the increasing (decreasing) in ec causes an increasing (decreasing) in gdp level respectively and vice versa. second group asserts the unidirectional causality running from ec to gdp, and it called growth hypothesis, it illustrates that any an increase (decrease) in ec could causes an increase (decrease) in gdp level; therefore ec has a vital role in production process of gdp. while the third group emphasizes the existence of the unidirectional causality running from gdp to ec which called conservation hypothesis, the increase in gdp may cause an increase on ec. finally the forth group supports the absence of relationship between gdp and ec and it called neutrality hypothesis, it suggests that there is no significant effect from ec into gdp and vice versa (ozturk, 2010). 3. the literatures survey of causality ec and economic growth nexus as we have mentioned earlier that there are several empirical studies have interested and attempted to determine the casual relationship between gdp and ec, while the findings of those studies have been intermingled and conflicted. due to that some studies provide the causality relationship running from gdp to ec, but others showed the reverse that causality relationship running from ec to gdp. however some found that there is bi-directional causality between the two variables while others support that there is no causality relationship between those variables. in this section, we extend a chronological list of the empirical literature on the causality relationship between gdp and ec, providing the applied methodologies, target countries, period spanning, findings, published year, and author name. while most of previous studies have focused in that causality relationship in specific country or cross countries, and in other way most of them have concentrated on industrialized and developed countries only. we are going to divide the survey literatures into two major groups by variables included in the study; first group involved the bivariate framework studies as in table 1, while the second group shows the multivariate framework as shown in table 2. note that our literature survey concentrates on the studies which taken the aggregated ec as a proxy of ec rather than the disaggregate energy levels, to avoid the bias results. 3. 1. bivariate framework studies depending on the results of hypotheses this part of literature includes the empirical studies which interested into detect the casual relationship between two variables only; economic growth gdp and ec. the direction of causality has been counted in each study according to hypothesis. the bivariate framework studies has summarized in table 1. 3.1.1 feedback hypothesis shows bidirectional causality between ec and gdp the empirical studies which support the feedback hypothesis by specific country and cross countries have been summarized in table 1. the following studies provide bidirectional causality between ec and gdp on a country specific; hwang and gum (1992) focuses his study in taiwan for period spanning from 1961 to 1990 by using granger causality method. zarnikau (1997) his target group is usa country during the period 1970-1992 by employed the granger causality. jumbe (2004) his analysis included data spanning from 1970 to 1999 of malawi country. erdal et al. (2008) concentrate their study in turkey for the period 1970 to 2006 by using pair-wise granger causality and johansen co-integration. belloumi (2009) focuses in tunisia for monthly data from 1971 to 2004 by applying granger causality and vector error correction model (vecm) approaches. zhang (2011) focuses in russia over the period 1970-2008 by using time-varying cointegration and toda yamamoto (ty) causality test. zhang and xu (2012) his study conducted in china over the period 1995 to 2008 by using panel causality tests. shahiduzzaman and alam (2012) concentrate in australia for times series 1960-2009 by employing international journal of energy economics and policy | vol 5 • issue 2 • 2015 387 isa, et al.: review paper on economic growth–aggregate energy consumption nexus author methodology year scope findings and results kraft and kraft (1978) granger and sims causality 1947-1974a usa gdp→ec akarca and long (1980) sims causality 1950-1970a usa gnp ― ec yu and choi (1985) sims and granger causality 1947-1979a 1950-1976a 1950-1976a 1950-1976a 1954-1976a usa uk poland philippines south korea gnp ― ec ec→gnp gnp ― ec ec→gnp gnp→ec erol and yu (1987a) sims and granger causality 1950-1982a 1950-1982a 1950-1982a 1950-1982a 1950-1980 1950-1982a japan germany italy canada france uk ec↔gnp gnp→ec gnp→ec ec→gnp gnp ― ec gnp ― ec nachane et al. (1988) eg 1950-1985a argentina brazil chile colombia greece guatemala india israel portugal mexico venezuela france germany italy japan uk cec→gdp cec↔gdp cec→gdp cec↔gdp cec→gdp cec→gdp cec↔gdp cec↔gdp cec→gdp cec→gdp cec↔gdp cec→gdp cec↔gdp cec→gdp cec↔gdp cec→gdp abosedra and baghestani (1991) granger causality 1947-1987a usa gnp→ec hwang and gum (1992) granger causality 1961–1990a taiwan gnp↔ec yu and jin (1992) granger causality 1974–1990a usa gdp― ec ebohon (1996) granger causality 1960-1981a 1960-1984a tanzania nigeria gdp↔ec gdp↔ec masih and masih (1996) jj and vdc 1955-1990a 1955-1990a 1960-1990a 1955-1990a 1960-1990a 1955-1991a india pakistan indonesia malaysia singapore philippines gnp→ec gnp↔ec gnp→ec gnp ― ec gnp ― ec gnp ― ec zarnikau (1997) granger causality 1970-1992a usa gnp↔ec glasure and lee (1998) eg 1961-1990a south korea singapore gdp↔ec gdp↔ec yang (2000) eg 1954-1997a taiwan ec↔gdp soytas et al. (2001) co-integration, granger causality 1960-1995a turkey ec→gdp fatai et al. (2002) granger causality, ardl and ty 1960-1999a new zealand gdp ― ec ghosh (2002) cointegration 1950-1997a india gdp→ec soytas and sari (2003) jj and vdc 1950-1990a 1950-1992a 1950-1992a 1950-1992a 1960-1992a 1953-1991a 1950-1992a 1953-1991a 1965-1994a argentina canada france germany indonesia italy japan korea poland gdp↔ec gdp ― ec ec→gdp ec→gdp gdp ― ec gdp→ec ec→gdp gdp→ec gdp ― ec table 1: the summary of empirical studies on ec and gdp nexus for bivariate framework (contd...) international journal of energy economics and policy | vol 5 • issue 2 • 2015388 isa, et al.: review paper on economic growth–aggregate energy consumption nexus author methodology year scope findings and results 1950-1992a 1950-1992a 1950-1992a turkey uk usa gdp↔ec gdp ― ec gdp ― ec altinay and karagol (2004) granger causality 1950-2000a turkey gdp ― ec fatai et al. (2004) granger-causality, ty, ardl and jj 1960-1999a australia new zealand india indonesia thailand philippines gdp→ec gdp→ec ec→gdp ec→gdp ec↔gdp ec↔gdp wolde-rufael (2004) ty 1952-1999a shanghai ec→gdp jumbe (2004) cointegration 1970-1999a malawi gdp↔ec wolde-rufael (2005) ardl and ty 1971-2001a algeria benin cameroon dr congo rep congo egypt gabon ghana ivory coast kenya morocco nigeria senegal south africa sudan togo tunisia zambia zimbabwe gdp→ec gdp ― ec ec→gdp gdp→ec gdp ― ec gdp→ec gdp↔ec gdp→ec gdp→ec gdp ― ec ec→gdp ec→gdp gdp ― ec gdp ― ec gdp ― ec gdp ― ec gdp ― ec gdp↔ec gdp ― ec lee and chang (2005) jj 1954-2003a taiwan ec↔gdp al-iriani (2006) pedroni panel cointegration 1971-2002a panel of 6 countries in middle east gdp→ec chontanawat et al. (2006) jj and dynamic panel estimation 1960-2000a oecd countries australia austria belgium canada czech denmark finland france germany greece hungary iceland ireland italy japan korea luxembourg mexico the netherlands new zealand norway poland gdp→ec ec→gdp ec→gdp gdp→ec ec→gdp ec→gdp gdp→ec gdp↔ec gdp↔ec gdp↔ec gdp↔ec gdp↔ec ec→gdp gdp↔ec gdp↔ec ec→gdp gdp ― ec ec→gdp ec→gdp gdp↔ec gdp↔ec ec→gdp table 1: (continued...) (contd...) international journal of energy economics and policy | vol 5 • issue 2 • 2015 389 isa, et al.: review paper on economic growth–aggregate energy consumption nexus author methodology year scope findings and results portugal slovakia spain sweden switzerland turkey uk usa gdp↔ec gdp↔ec gdp→ec gdp→ec ec→gdp gdp ― ec gdp ― ec gdp ― ec 1971-2000a non-oecd albania gdp→ec algeria gdp→ec angola gdp↔ec argentina gdp↔ec bahrain gdp ― ec bangladesh ec→gdp benin gdp ― ec bolivia gdp→ec brazil gdp↔ec brunei gdp↔ec bulgaria gdp→ec cameroon gdp ― ec chile ec→gdp china gdp ― ec colombia ec→gdp congo gdp ― ec congo republic ec→gdp costa rica gdp→ec cote d’ivoire gdp ― ec cuba gdp→ec cyprus ec→gdp dominican republic ec→gdp ecuador gdp ― ec egypt ec→gdp el salvador gdp→ec ethiopia gdp→ec gabon gdp ― ec ghana gdp↔ec gibraltar gdp↔ec haiti gdp ― ec honduras gdp ― ec hong kong gdp ― ec india gdp ― ec iran gdp↔ec iraq gdp ― ec israel ec→gdp jamaica gdp ― ec jordan gdp↔ec kenya ec→gdp kuwait gdp↔ec lebanon gdp↔ec libya gdp ― ec malaysia gdp ― ec malta gdp ― ec morocco gdp↔ec mozambique gdp↔ec myanmar gdp↔ec nepal ec→gdp nicaragua gdp ― ec nigeria gdp ― ec oman ec→gdp pakistan gdp ― ec panama gdp→ec paraguay gdp→ec peru gdp→ec table 1: (continued...) (contd...) international journal of energy economics and policy | vol 5 • issue 2 • 2015390 isa, et al.: review paper on economic growth–aggregate energy consumption nexus (contd...) author methodology year scope findings and results philippines ec→gdp qatar gdp↔ec romania gdp↔ec saudi arabia gdp→ec senegal gdp ― ec singapore gdp ― ec sri lanka gdp ― ec sudan gdp↔ec taiwan gdp↔ec tanzania gdp ― ec thailand gdp→ec togo gdp ― ec trinidad gdp↔ec tunisia gdp↔ec uae gdp↔ec uruguay ec→gdp venezuela gdp→ec vietnam ec→gdp yemen gdp↔ec zambia gdp ― ec zimbabwe gdp→ec lee (2006) ty 1960-2001a 1965-2001a 1960-2001a 1971-2001a 1960-2001a 1960-2001a 1960-2001a 1960-2001a 1960-2001a 1960-2001a 1960-2001a belgium canada france germany italy japan the netherlands sweden switzerland uk usa ec→gdp ec→gdp gdp→ec gdp ― ec gdp→ec gdp→ec ec→gdp gdp ― ec ec→gdp gdp ― ec gdp↔ec francis et al. (2007) eg 1971-2002a haiti jamaica trinidad and tobago gdp↔ec gdp↔ec gdp↔ec lise and montfort (2007) eg 1970-2003a turkey gdp→ec mehrara (2007a) pedroni panel cointegration 1971-2002a panel of 7 countries in middle east gdp→ec mehrara (2007b) ty and jj 1971-2002a iran kuwait saudi arabia gdp→cec gdp→cec cec→gdp ang (2007) cointegration, vecm 1960-2000a france ec→gdp ho and siu (2007) cointegration, vecm 1966–2002a hong kong ec→gdp chiou et al. (2008) jj; baek and brock non-linear granger causality 1954-2006a 1971-2003a 1971-2003a 1971-2003a 1971-2003a 1971-2003a 1971-2003a 1971-2003a 1960-2003a taiwan hong kong singapore korea malaysia indonesia philippines thailand usa ec→gdp ec→gdp gdp→ec gdp ― ec gdp ― ec gdp↔ec gdp→ec gdp ― ec gdp ― ec ang (2008) jj and vecm 1971-1999a malaysia gdp→ec erdal et al. (2008) pair-wise granger causality and jj 1970-2006a turkey gdp↔ec akinlo (2008) ardl 1980-2003a gambia ghana sudan zimbabwe congo gdp→ec gdp→ec gdp→ec gdp→ec gdp→ec table 1: (continued...) international journal of energy economics and policy | vol 5 • issue 2 • 2015 391 isa, et al.: review paper on economic growth–aggregate energy consumption nexus (contd...) author methodology year scope findings and results senegal cameroon coted’ ivories nigeria kenya togo gdp ― ec gdp ― ec gdp ― ec gdp ― ec gdp ― ec gdp ― ec belloumi (2009) granger causality and vecm 1971-2004m tunisia gdp↔ec zhang and cheng (2009) granger causality 1960-2007a china gdp→ec bowden and payne (2009) ty 1949-2006a united states gdp ― ec ozturk et al. (2010) pedroni panel cointegration 1971-2005a 51 countries: low income 14 lower middle 24 upper middle 13 gdp→ec gdp↔ec gdp↔ec ozturk and acaravci (2010) ardl and ecm 1980-2006a albania bulgaria hungary romania gdp ― ec gdp ― ec gdp↔ec gdp ― ec bartleet and gounder (2010) ardl cointegration, ecm causality 1960-2004a new zealand gdp→ec tsani (2010) ty 1960-2006a greece ec→gdp warr and ayres (2010) jj, cointegration, vecm 1946-2000a usa ec→gdp hossain and saeki (2011) panel causality (granger, eg and gmm) 1971-2007a panel of south asian countries ec→gdp zhang (2011) ty and time-varying cointegration 1970-2008a russia gdp↔ec eggoh et al. (2011) panel cointegration, panel causality 1970-2006a african countries 21 energy exporters 11 energy importers 10 gdp↔ec gdp↔ec gdp↔ec belke et al. (2011) dynamic panel causality 1981-2007a panel of 25 oecd gdp↔ec lau et al. (2011) granger causality test and fmols 1980 – 2006a panel of 17 asian countries gdp→ec abid and sebri (2011) vecm 1980-2007a tunisia gdp↔ec sadorsky (2012) panel cointegration, panel causality 1980-2007a panel of 7 countries in south american gdp↔ec narayan and popp (2012) panel cointegration, panel causality 1980-2006a global panel 93 western european 20 asian panel 17 latin american 17 middle east panel 12 african panel 25 g6 panel 6 gdp↔ec ec→gdp ec→gdp ec→gdp gdp ― ec gdp↔ec ec→gdp souhila and kourbali (2012) threshold cointegration and granger causality 1965-2008a algeria gdp→ec fuinhas and marques (2012) ardl cointegration, and ecm 1965-2009a portugal italy greece spain turkey gdp↔ec gdp↔ec gdp↔ec gdp↔ec gdp↔ec pirlogea and cicea (2012) co-integration tests 1990-2010a romania spain ec→gdp ec→gdp zhang and xu (2012) panel cointegration, panel causality 1995-2008a china gdp↔ec shahiduzzaman and alam (2012) jj, cointegration, and vecm 1960-2009a australia gdp↔ec wesseh jr and zoumara (2012) parametric and non-parametric granger causality approaches 1980-2008a liberian gdp↔ec ocal and aslan (2013) ardl and ty 1990-2010a turkey gdp→rec table 1: (continued...) international journal of energy economics and policy | vol 5 • issue 2 • 2015392 isa, et al.: review paper on economic growth–aggregate energy consumption nexus author methodology year scope findings and results herrerias et al. (2013) panel cointegration techniques 1995-2009a chinese gdp→ec dergiades et al. (2013) parametric and non-parametric test 1960-2008a greece ec→gdp the unidirectional causality, bidirectional causality and no causality between ec and gdp have been represented by the symbols →, ↔ and ― respectively. for the abbreviations of methods; ty: toda-yamamoto causality test, jj: johansen-juselius. ardl: autoregressive distributed lag bounds test. eg: engle-granger. vdc: forecast error variance decomposition. vecm: vector error correction model. ecm: error correction model. pecm: panel error-correction model. gmm: generalized method of moments. while the abbreviations of main variables and scope; gnp or gdp represent the economic growth. ec: energy consumption, cec: commercial energy consumption. g6: france, west germany, italy, japan, the united kingdom and the united states. oecd: organization for economic co-operation and development countries, gdp: gross domestic product, gnp: gross national product table 1: (continued...) author methodology year scope additional variables findings anf results yu and hwang (1984) sims and granger causality 1947-1979a usa emp gnp ― ec ec→emp stern (1993) granger causality and var 1947-1990a usa emp and capital ec→gdp cheng (1996) eg 1947-1990a usa capital ec ― gnp cheng (1997) eg 1963-1993a 1949-1993a 1952-1993a brazil mexico venezuela capital ec→gdp ec ― gdp ec ― gdp cheng and lai (1997) eg 1955-1993a taiwan emp gdp→ec ec→emp masih and masih (1997) jj, vdc and irf 1961-1990a korea taiwan consumer prices gdp↔ec gdp↔ec cheng (1998) jj and hsiao’s granger causality 1952-1995a japan capital and emp gnp→ec masih and masih (1998) jj, vdc and irf 1955-1991a thailand sri lanka consumer prices ec→gdp ec→gdp cheng (1999) jj, co-integration, ecm and granger causality 1952-1995a india capital and population gnp→ec asafu-adjaye (2000) jj 1973-1995a 1973-1995a 1971-1995a 1971-1995a india indonesia thailand philippines consumer prices ec→gdp ec→gdp ec↔gdp ec↔gdp stern (2000) jj and granger causality 1948-1994a usa emp and capital ec→gdp aqeel and butt (2001) eg 1955-1996a pakistan emp gdp→ec glasure (2002) jj and vdc 1961-1990a korea energy prices ec↔gdp hondroyiannis et al. (2002) jj and vecm 1960-1999a greece consumer prices ec↔gdp ghali and el-sakka (2004) jj, vdc and vec 1961-1997 a canada capital and emp ec↔gdp oh and lee (2004a) jj, granger causality and vecm 1970-1999 a korea capital and labor ec↔gdp oh and lee (2004b) jj 1981-2000q south korea capital, labor and real energy prices gdp→ec paul and bhattacharya (2004) eg and jj 1950-1996a india population and capital ec↔gdp lee (2005) pedroni panel cointegration 1975-2001a panel of 18 developing countries capital ec→gdp soytas and sari (2006a) ty and vdc 1971-2002a china labor force and capital ec―gdp soytas and sari (2006b) jj and vdc 1960-2004a 1970-2002a 1971-2002a 1960-2004a 1960-2004a 1960-2004a 1960-2004a canada france germany italy japan uk usa labor force and real gross fixed capital formation ec↔gdp ec→gdp ec↔gdp ec↔gdp ec↔gdp ec↔gdp ec→gdp climent and pardo (2007) jj 1984-2003q spain consumer prices and employment ec↔gdp table 2: the summary of empirical studies on ec and gdp for multivariate framework (contd...) international journal of energy economics and policy | vol 5 • issue 2 • 2015 393 isa, et al.: review paper on economic growth–aggregate energy consumption nexus (contd...) author methodology year scope additional variables findings anf results jobert and karanfil (2007) jj 1960-2003a turkey iva ec―gnp ec―iva mahadevan and asafu-adjaye (2007) pedroni panel cointegration; jj and vecm 1971-2002a exporters developed australia norway uk exporters developing argentina indonesia kuwait malaysia nigeria saudi arabia venezuela importers developed japan sweden usa importers developing ghana india senegal south africa south korea singapore thailand consumer prices ec↔gdp ec↔gdp ec↔gdp ec↔gdp ec↔gdp ec↔gdp ec↔gdp ec↔gdp ec↔gdp ec↔gdp ec↔gdp ec↔gdp ec↔gdp ec↔gdp ec↔gdp ec↔gdp ec→gdp ec↔gdp ec→gdp ec→gdp ec↔gdp ec→gdp ec↔gdp ec→gdp narayan and smyth (2007) pedroni panel cointegration 1972-2002a panel of 7 western countries capital ec→gdp soytas et al. (2007) ty and vdc 1960-2000a usa real gross fixed capital formation, labor force and co2 ec ― gdp zachariadis (2007) jj, ardl and ty 1960-2004a canada france germany italy japan uk usa iva all: gdp→ec jj: ec↔gdp ardl: ec→gdp ty: ec ― gdp jj: ec↔gdp ardl: gdp→ec ty: ec ― gdp jj: ec↔gdp ardl: ec↔gdp ty: ec ― gdp jj: ec↔gdp ardl: ec↔gdp ty: ec→gdp all: gdp→ec all: ec ― gdp zamani (2007) eg 1967-2003a iran iva and ava gdp→ec yuan et al. (2008) jj and irf 1963-2005a china capital, employment ec↔gdp huang et al. (2008) dynamic panel estimation, gmm and var 1972-2002a low income middle income high income over all panel capital stock+labor force ec ― gdp gdp→ec gdp→ec ec↔gdp lee and chang (2008) pedroni panel cointegration 1971-2002a asian panel, apec, asean capital stock and labor force ec→gdp ec→gdp ec→gdp table 2: (continued...) international journal of energy economics and policy | vol 5 • issue 2 • 2015394 isa, et al.: review paper on economic growth–aggregate energy consumption nexus (contd...) author methodology year scope additional variables findings anf results soytas and sari (2008) ty and vdc 1960-2000a turkey real gross fixed capital formation, labor force and co2 ec ― gdp payne (2009) ty 1949-2006a usa real gross fixed capital formation and employment ec ― gdp apergis and payne (2009) pedroni panel cointegration 1980-2004a panel of 6 south america countries real gross fixed capital formation and labor force ec→gdp costantini and martini (2010) vecm 1960-2005a 71 countries 26 oecd 45 non-oecd energy prices gdp→ec ec↔gdp gdp→ec acaravci and ozturk (2010) cointegration, ardl 1960e2005 19 europe countries austria belgium denmark finland france germany greece hungary iceland ireland italy luxembourg netherlands norway portugal spain sweden switzerland united kingdom co2 ec ― gdp ec ― gdp ec ― gdp ec ― gdp ec ― gdp ec ― gdp gdp→ec ec ― gdp ec ― gdp gdp→ec ec ― gdp ec ― gdp ec ― gdp ec ― gdp ec ― gdp ec ― gdp ec ― gdp ec↔gdp ec ― gdp apergis and payne (2010) cointegration and ecm 1985-2005a 20 oecd countries capital and labor force ec↔gdp odhiambo (2010) cointegration, ardl and ecm 1972-2006a south africa kenya congo energy prices ec→gdp ec→gdp gdp→ec ozturk and acaravci (2010) cointegration, ardl 1968-2005a turkey co2, employment ratio ec ― gdp hatzigeorgiou et al. (2011) cointegration, jj and vecm 1977-2007a greece co2 gdp→ec pao and tsai (2011) cointegration panel causality 1980-2007a panel of 4 bric countries fdi and co2 ec↔gdp hossain (2011) granger causality and eg 1971-2007a panel of 9 nic co2 gdp→ec wang et al. (2011) panel cointegration, vecm 1995-2007a china co2 ec↔gdp alam et al. (2011) dynamic modeling 1971-2006a india fixed capital stock, labor force and co2 ec ― gdp farhani and ben (2012). panel cointegration, panel causality 1973-2008a 15 mena countries co2 gdp→ec hossein et al. (2012) eg and ecm 1980-2008a iran iraq qatar uae saudi arabia algeria energy price gdp→ec gdp→ec gdp→ec gdp→ec gdp→ec ec→gdp table 2: (continued...) international journal of energy economics and policy | vol 5 • issue 2 • 2015 395 isa, et al.: review paper on economic growth–aggregate energy consumption nexus author methodology year scope additional variables findings anf results angola ecuador kuwait libya nigeria venezuela ec→gdp ec→gdp ec→gdp ec→gdp ec→gdp ec→gdp shahbaz et al. (2012) ardl and vecm 1972-2011a pakistan capital and labor ec↔gdp ec↔gdp al-mulali and che sab (2012) panel cointegration, panel causality 1980-2008a panel of 30 sub-saharan african countries financial development and co2 ec↔gdp abalaba, and dada, (2013) ecm and jj 1971-2010a nigeria financial development, monetary policy rate and consumer prices ec ― gdp saboori and sulaiman (2013a) ardl and jj 1980-2009 a malaysia co2 ec↔gdp saboori and sulaiman (2013b) ardl and vecm 1971-2008 a indonesia malaysia philippines singapore thailand co2 ec↔gdp ec↔gdp ec↔gdp gdp→ec gdp→ec alkhathlan and javid (2013) ardl, vecm 1980-2011a saudi arabia co2 ec ― gdp yang, and zhao (2014) granger causality and dag 1979-2008a india co2 ec→gdp ec→co2 the unidirectional causality, bidirectional causality and no causality between ec and gdp have been represented by the symbols →, ↔ and ― respectively. for the abbreviations of methods; ty: toda-yamamoto causality test, jj: johansen-juselius, ardl: autoregressive distributed lag bounds test. eg: engle-granger. vdc: forecast error variance decomposition. vecm: vector error correction model. ecm: error correction model. pecm: panel error-correction model. gmm: generalized method of moments. while the abbreviation of main variables and scope; gnp or gdp represent the economic growth. ec: energy consumption, cec: commercial energy consumption. ava: agricultural value added. iva: industrial value added. co2: carbon dioxide emissions. emp: employment. fdi: foreign direct investment. nic: newly industrialized countries; iran, israel, kuwait, oman, saudi arabia and syria. bric countries: brazil, russia, india and china. oecd: organization for economic co-operation and development countries. apec: asia-pacific economic cooperation. asean: association of southeast asian nations, gdp: gross domestic product, gnp: gross national product table 2: (continued...) johansen co-integration and vecm causality tests. wesseh jr and zoumara (2012) interested in liberian over the period 1980-2008 by applying parametric and non-parametric granger causality approaches. in the other hand there are some studies support the bidirectional causality relationship between ec and gdp by considering several countries in one panel in analysis such as; eggoh et al. (2011) their analysis included 21 african countries, 10 of them are energy exporters, while 11 are energy importers countries over the period 1970-2006 by using panel causality. belke et al. (2011) covered 25 organization for economic cooperation and development countries during the period 1981-2007 by using dynamic panel causality. sadorsky (2012) concentrates his analysis in 7 countries of south american for annual time series data 1980-2007 by applying panel causality. ozturk et al. (2010) have included 51 countries in his analysis and he divided them into three groups low income, lower middle income and upper middle income, the bidirectional causality relationship found in panels of (lower and upper) middle income countries. narayan and popp (2012) used 93 countries in the analysis into one panel and the findings support the feedback hypothesis. furthermore there are several studies support bidirectional causality between ec and gdp in some individual country of their cross countries analysis such as in; erol and yu (1987) the bidirectional causality relationship has noted in japan only, while nachane et al. (1988) existed it in brazil, colombia, india, israel, venezuela, germany and japan. ebohon (1996) supports that causality relationship in tanzania and nigeria. masih and masih (1996) found it in pakistan only. glasure and lee (1998) found it in south korea and singapore. soytas and sari (2003) suggest that it existed in turkey only. wolde-rufael (2005) showed it in gabon and zambia. chontanawat et al. (2008) support that in france, germany, greece, hungary, iceland, italy, japan, new zealand, norway, portugal, slovakia, angola, argentina, brazil, brunei, ghana, gibraltar, iran, jordan, kuwait, lebanon, morocco, mozambique, myanmar, qatar, romania, sudan, taiwan, trinidad, tunisia, uae and in yemen. lee (2006) found it in usa only. francis et al. (2007) support it in haiti, jamaica and trinidad. chiou-wei et al. (2008) suggest that it is exist in indonesia. fuinhas and marques (2012) resulting it in the all countries of their study; portugal, italy, greece, spain and turkey. 3.1.2. growth hypothesis asserts the unidirectional causality running from ec to gdp furthermore many empirical studies support the growth hypothesis. first we start with studies which provide a unidirectional causality running from ec to gdp onto country specific such as soytas et al. (2001) concentrates in turkey with annual time series data 1960-1995 and he used cointegration and granger causality in the analysis. ang (2007) interested in france during the period 1960-2000 by using cointegration and vecm approach in his analysis. ho and siu (2007) focused in hong kong region by applying cointegration and vecm in the annual data spanning from 1966 to 2002. tsani (2010) used ty causality test in annual data 1960-2006 in greece. warr and ayres (2010) focus is usa international journal of energy economics and policy | vol 5 • issue 2 • 2015396 isa, et al.: review paper on economic growth–aggregate energy consumption nexus by using the johansen cointegration causality and vecm in their analysis over the annual period 1946 to 2000. dergiades et al. (2013) focused in greece by using annual data from 1960 to 2008 and employing parametric and non-parametric test. however there are few studies support the growth hypothesis by one panel countries such as; hossain and saeki (2011) included several asian countries in one panel over the period 1971-2007 by using granger causality, engle-granger (eg) and generalized method of moments (gmm). while in narayan and popp (2012) study, they included several countries panels, the growth hypothesis has existed in; western european panel which involved 20 countries, and in other panel consisted of 17 countries of asian, panel of 17 latin american countries and 6 countries of g6. in the other hand there are some empirical studies support the growth hypothesis in individual country such as; erol and yu (1987) it has existed in canada. nachane et al. (1988) study, it has resulted in argentina, chile, greece, guatemala, portugal, mexico, france, italy and uk. soytas and sari (2003) found it in france, germany and japan. wolde-rufael (2005) found it in cameroon, morocco and nigeria. chontanawat et al. (2006) support the growth hypotheses in the following countries; austria, belgium, czech, denmark, ireland, korea, mexico, netherlands, poland, switzerland, bangladesh, chile, colombia, congo, cyprus, dominican republic, egypt, israel, kenya, nepal, oman, philippines, uruguay and vietnam. lee (2006) found it in belgium, canada, netherlands and switzerland. mehrara (2007a) support it in saudi arabia. chiou-wei et al. (2008) showed it in taiwan and hong kong. while pirlogea and cicea (2012) support it in romania and spain. 3.1.3. conservation hypothesis emphasizes the unidirectional causality running from gdp to ec in addition there are several studies providing the conservation hypothesis. first we start with studies which provide a unidirectional causality relationship running from ec to gdp on a country specific such as; kraft and kraft (1978) study and in abosedra and baghestani (1991) study, they used annual data from 1947-1974 and 1947-1987 respectively in same country usa by applying same method granger and sims causality. ghosh (2002) focused in india over the period 1950-1997. lise and montfort (2007) interested in turkey during the period 1970-2003 by applying eg method. ang (2008) concentrated in malaysia during 1971-1999 by using johansen cointegration and vecm approaches. zhang and cheng (2009) focused in china over the period 1960-2007 by employing granger causality. souhila and kourbali (2012) interested in algeria over the time period 1965-2008 by using the threshold cointegration and granger causality tests. ocal and aslan (2013) interested in turkey over the period 1990-2010 by employing autoregressive distributed lag (ardl) and ty approaches. herrerias et al. (2013) focused in chinese for annual data from 1995 to 2009 by using panel cointegration techniques. however there are some studies support the growth hypothesis by using panel countries analysis such as; al-iriani (2006) his study covered six countries from middle east in one panel for annual data spanning from 1971 to 2002 by employing johansenjuselius and dynamic panel estimation. and mehrara (2007a) his study involved seven countries from middle east in one panel with annual data spanning from 1971 to 2002 by employing pedroni panel cointegration. ozturk et al. (2010) his study contain from several panels of countries, one of them represented 14 countries in low income group, and by using panel cointegration method for annual data from 1971 to 2005 the finding support conservation hypothesis. lau et al. (2011) examined the relationship between gdp and ec in panel of 17 asia countries. in the other hand there are some empirical studies support the conservation hypothesis in individual country such as; erol and yu (1987) has existed it in germany and in italy. masih and masih (1996) found it in india and in indonesia. soytas and sari (2003) provided it in italy and in korea. wolde-rufael (2005) supports it in algeria, congo, egypt, ghana and ivory coast. chontanawat et al. (2006) have found it in australia, canada, finland, spain, sweden, albania, algeria, bolivia, bulgaria, costa rica, cuba, el salvador, ethiopia, panama, paraguay, peru, saudi arabia, thailand, venezuela and zimbabwe. lee (2006) supports it in france, italy and in japan. mehrara (2007a) found it in iran and in kuwait. chiou-wei et al. (2008) supports it in singapore and in philippines. akinlo (2008) found it in gambia, ghana, sudan, zimbabwe and congo. 3.1.4. neutrality hypothesis supports the absence of causality relationship between gdp and ec moreover it has noted clearly among the empirical researches some finding supports the neutrality hypothesis, which means no relationship between ec to gdp. we are going to illustrate them by starting on a country specific studies such as; akarca and long (1980) concentrates in usa over the period 1950-1970 by applying sims causality. yu and jin (1992) interested in usa by using cointegration and granger causality into annual data spanning from 1974 to 1990. fatai et al. (2002) focused in new zealand over the period 1960-1999 by using ty granger causality and ardl. altinay and karagol (2004) they focused in turkey over the period 1950-2000 by applying hsiao’s version of granger causality. bowden and payne (2009) in usa by using ty causality test in annual data spanning from 1949 to 2006. however we have not met studies has taken several countries in one panel into their analysis except one study for middle east panel contain of 12 countries for narayan and popp (2012) study. in the other hand there are some empirical studies support the neutrality hypothesis in individual country of their studies such as; erol and yu (1987) support it in france and uk. masih and masih (1996) found it in malaysia, singapore and philippines. soytas and sari (2003) found it in canada, indonesia, poland, uk and usa. wolde-rufael (2005) supports it in benin, congo, kenya, senegal, south africa, sudan, togo, tunisia and zimbabwe. chontanawat et al. (2008) support the neutrality hypothesis in luxembourg, turkey, uk, usa, bahrain, benin, cameroon, china, congo, cote d’ivoire, ecuador, gabon, haiti, honduras, hong kong, india, iraq, jamaica, libya, malaysia, malta, nicaragua, nigeria, pakistan, senegal, singapore, sri lanka, tanzania, togo and zambia. lee (2006) found it in germany, sweden and uk. chiou et al. (2008) found it in korea, malaysia, thailand and usa. akinlo (2008) support it in senegal cameroon, coted’ivoire, nigeria kenya and togo. ozturk and acaravci (2010) support it albania, bulgaria and romania. 3.2. multivariate framework studies depending on the results of hypotheses nevertheless, some of authors claim that the bivariate analysis has resulted inaccurate findings on detecting the relationship international journal of energy economics and policy | vol 5 • issue 2 • 2015 397 isa, et al.: review paper on economic growth–aggregate energy consumption nexus between ec and gdp. many researchers suggest that is due to the possibility of omitted variable bias lu¨tkepohl (1982). tang and tan (2013) bivariate model specification may not appropriate for examining the energy growth nexus. after that suggestion, there are several studies had used the multivariate framework to investigate that causality relationship. in addition of the later variables they employed additional factors in the analysis such as; labor force in the following studies; oh and lee (2004b), soytas and sari (2006a), soytas and sari (2006b), soytas et al. (2007), huang et al. (2008), lee and chang (2008), soytas and sari (2008), apergis and payne (2009), apergis and payne (2010), alam et al. (2011), shahbaz et al. (2012), among others. moreover some other studies had included the employment as a main factor in their analysis such as; yu and hwang (1984), stern (1993), cheng and lai (1997), cheng (1998), stern (2000), aqeel and butt (2001), ghali and el-sakka (2004), climent and pardo (2007), yuan et al. (2008), payne (2009) and ozturk and acaravci (2010), among others. however some studies added the real gross fixed capital formation as a main variable; stern (1993), cheng (1996), cheng (1997), cheng (1998), cheng (1999), stern (2000), ghali and el-sakka (2004), oh and lee (2004a), oh and lee (2004b), paul and bhattacharya (2004), lee (2005), soytas and sari (2006b), soytas and sari (2006a), narayan and smyth (2007), soytas et al. (2007), yuan et al.(2008), huang et al. (2008), lee and chang (2008), soytas and sari (2008), payne (2009), apergis and payne (2009), apergis and payne (2010), alam et al. (2011), shahbaz et al. (2012) and among others. as well some studies had included consumer or real energy prices; masih and masih (1997), masih and masih (1998), asafu-adjaye (2000), glasure (2002), hondroyiannis et al. (2002), oh and lee (2004b), climent and pardo (2007), mahadevan and asafu-adjaye (2007), costantini and martini (2010), odhiambo (2010), hossein et al. (2012), abalaba, and dada, (2013). furthermore in recent studies many other researchers has added the carbon dioxide emissions co2 in their analysis, as they claim it has an important effect in the causality relationship between ec and gdp, some of those studies are; soytas et al.(2007), soytas and sari (2008), acaravci and ozturk (2010), hatzigeorgiou et al. (2011), pao and tsai (2011), hossain (2011), wang et al. (2011), alam et al. (2011), al-mulali and che sab (2012), farhani, and ben (2012), saboori and sulaiman (2013a), saboori and sulaiman (2013b), alkhathlan and javid (2013), among others. while some studies has added the population as main factor in their model such as; cheng (1999), paul and bhattacharya (2004), among others. and other has considered the industrial value added in their analysis, jobert and karanfil (2007), zachariadis (2007), zamani (2007), and the later had included the agricultural value added in his analysis too. pao and tsai (2011) had considered the foreign direct investment in his molding. al-mulali and che sab (2012) involve the financial development in their analysis. in additional on the study outlined in table 2 we summarized some of them which has included different factors in the estimated model as following; soytas et al. (2007) he studied the long run granger causality between ec, co2 and the gdp in the usa. moreover he added some other factors in his model such as the labor force and investment in capital, while his findings do not support the existence of the causality direction neither between the gdp and co2, nor between the gdp and ec. moreover he confirmed that the main resource of emission is the ec. soytas and sari (2008) their study has focuses on examine the granger causality relationship in long run only between gdp, ec and co2 which is the most common pollutant emission in turkey province, and they controlling the labor force and gross fixed capital, data spanning from 1960 to 2000. moreover he applied five unit root tests (adf, pp, kpss, df-gls, and np-z) in his diagnostic analysis to examine the stationarity in the variables. his significant findings show that there is uni-directional causality running from co2 to ec but the reverse is not true. and his result support that in the long run the ec does not seem to be granger causing gdp in turkey. in conclusion of their paper, they suggest that to take the technology investments and its effects into account. ozturk and acaravci (2010) concentrated on the causal relationship between the following variables; gdp, co2, ec and employment ratio in turkey during the period 1968-2005 by applying recently developed ardl bounds cointegration method for testing the long run relationships between the variables, and they used the error-correction based granger causality models to test the causality. the findings indicate the expectance of long-run relationship between variables. there is no evidence show granger causality of neither co2 nor ec cause gdp in turkey. however in short run employment ratio causes gdp. furthermore there is no causal relationship between gdp and co2, due to that there is no any evidence support the environmental kuznets curve (ekc) hypothesis. moreover there is no causal relationship between gdp and both of ec and employment ratios. in additional of that the long run causality have found only for the real gdp equation. in conclusion of that there is no sufficient evidence to say there is adverse effect from ec and co2 to gdp. zhang and cheng (2009) concentrated to examine the granger causal relationship among the gdp, ec and co2 in china during the period 1960 to 2007 by using multivariate model for those variables including the gross fixed capital formation and urban population. they conducted three unit root tests adf, pp and kpss. moreover they used za unit root test which can test the stationary of series with structural break. the results indicate the existence of two unidirectional granger causality relationships; first one is running from gdp to ec, while the second one running from ec to co2 in long run. in additional of that no clear evidence to enhance the influence of co2 or ec towards the gdp. al sayed and sek (2013) detect the relationship between gdp and co2 for developed and developing countries for data spanning from 1961 to 2009 by using panel data method. the ekc relationship has been detected in co2. as a conclusion from those studies in table 2, it is difficult to reach a consensus on the causal relationship between ec and gdp. 4. dissection the results of four hypotheses existence in the surveyed studies the results of our empirical studies survey which concentrates in detecting the causality relationship between gdp and ec supporting one of the following hypotheses; growth, conservation, neutrality and feedback hypotheses. as we divided the survey studies into two classifications, bivariate and multivariate international journal of energy economics and policy | vol 5 • issue 2 • 2015398 isa, et al.: review paper on economic growth–aggregate energy consumption nexus frameworks, we are going to calculate the percentage of each classification separately, and then we figure the results of the whole empirical studies. in one hand we illustrate the percentage of existence four hypotheses in the bivariate framework studies; the highest percentage supports the feedback hypothesis with 29.5%, followed by 26.2% for the neutrality hypothesis, then the growth hypothesis with 23.6%, and finally the lowest percentage is found in the conservation hypothesis. in the other hand the multivariate studies shows different results; as the highest percentage is also supports the existence of feedback hypothesis with 45.7%, but it followed by 25.0% in favor to growth hypothesis, and then 17.2% for the conservation hypothesis, and the lowest percentage is found in neutrality hypothesis with 12.1% only. however the percentages of those hypothesis in the whole survey empirical studies has presented as the following; in the leading position is the feedback hypothesis with 34.3%, then the growth hypothesis supported by 24.0%, and 22.0% in favor to the neutrality hypothesis, and only 19.7% for the conservation hypothesis. table 3 and figure 1 illustrate those results clearly. from the previous results we noted that the percentages among the two frameworks; bivariate and multivariate in the hypotheses are different. in conclusion we claim that the additional variables may increase (decrease) the probability of the feedback (neutrality) hypothesis existence, as it found 29.5% and 26.2% in bivariate framework, while it reach to 45.7% and 12.1% in multivariate framework respectively. 5. conclusion detecting the relationship between the ec and economic growth is very important for policy makers and to conserve the environment and to reduce the consumption of the nonrenewable energy. this survey has conducted to classify the studies into two groups by the framework bivariate and multivariate of the previous empirical studies. secondly, to detect that if there is a significant influence of the additional variables to the bivariate framework into the four hypotheses. from our survey we conclude that there is no consensus on the direction of causality relationship between ec and gdp as the finding of those empirical studies have showed uneven results in terms of the four hypotheses (feedback, growth, conservation, and neutrality). at the end of it, we provide some suggestions for future researches; as we have mention earlier that no consensus in the results of direction into the causality relationship between the ec and gdp in a specific countries or panel countries, income classification groups, exporters and importers countries, etc. we recommend who interested to investigate that relationship to consider the following suggestions; future researches should focus more on new approaches and perspectives in multivariate framework rather than applying common methods with the same variables in bivariate framework only, most of the studies just changed the target group and the period time which does not lead to more potential contribution into that causality relationship. and that may be by adding new variables in the analysis such as; technology innovation recently undertaken by tang and tan (2013) but they used the electricity consumption as a main variable instead of take the aggregate ec. and other variables; gdp deflator, exchange rates, interest rates and eq including co2, so2, ghg, spm10, etc. also we recommend of using several methods into detecting the causal relationship to get more robust findings which has supported by zachariadis (2007) study. and to include the possibility of structural breaks in both the unit root process of the individual variable and in the tests for cointegration among the variables to get more accurate results. moreover most of the previous study had ignored to detect the coefficients signs of the casualty relationship and the magnitude of that relationship, it should be considered and it might lead to clear explanation of that relationship. there is other limitation in the previous conducted studies; they considered the aggregation or the disaggregation ec as a proxy of the ec; they have not considered the renewable energy into their analysis. it should be taken into account, the influence of renewable ec not as same as of the nonrenewable ec towards gdp, investigating that relationship with considering the nonrenewable and renewable ec separately could appear new demonstration. in additional of that the causality relationship should be distinguished between the short and long run causality relationship. taken the level of gdp in consideration also may lead to unmatched findings. references abalaba, b.p., dada, m.a. (2013), energy consumption and economic growth nexus: new empirical evidence from nigeria. international journal of energy economics and policy, 3(4), 412-423. abid, m., sebri, m. (2011), energy consumption-economic growth nexus: does the level of aggregation matter? international journal of energy economics and policy, 2(2), 55-62. abosedra, s., baghestani, h. (1991), new evidence on the causal relationship between united states energy consumption and gross national product. journal of energy and development, 14, 285-292. acaravci, a., ozturk, i. (2010), on the relationship between energy table 3: the percentages of the hypothesis existence among the bivariate and multivariate framework studies empirical studies (%) hypotheses feedback ec↔gdp growth ec→gdp conservation gdp→ec neutrality gdp ― ec bivariate framework 29.5 23.6 20.7 26.2 multivariate framework 45.7 25.0 17.2 12.1 all empirical studies 34.3 24.0 19.7 22.0 ec→gdp: unidirectional causality relationship running from ec to economic growth. gdp→ec: unidirectional causality relationship running from economic growth to ec. ec↔gdp: bidirectional causality relationship between economic growth and ec. gdp ― ec: no causality relationship between economic growth and ec. ec: energy consumption, gdp: gross domestic product 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% ec ↔ gdp ec → gdp gdp → ec gdp ― ec 34.3% 24.0% 19.7% 22.0% bivariate framework multivariate framework all empirical studies figure 1: the percentages of the hypothesis existence in the surveyed studies international journal of energy economics and policy | vol 5 • issue 2 • 2015 399 isa, et al.: review paper on economic growth–aggregate energy consumption nexus consumption, co2 emissions and economic growth in europe. energy, 35(12), 5412-5420. akarca, a.t., long, t.v., (1980), on the relationship between energy and gnp: a reexamination. journal of energy development, 5, 326-331. akinlo, a.e. (2008), energy consumption and economic growth: evidence from 11 sub-sahara african countries. energy economics, 30, 2391-2400. al sayed, a.r., sek, s.k. (2013), environmental kuznets curve: evidences from developed and developing economies. applied mathematical sciences, 7(22), 1081-1092. alam, m.j., begum, i.a., buysse, j., rahman, s., van huylenbroeck, g. (2011), dynamic modeling of causal relationship between energy consumption, co2 emissions and economic growth in india. renewable and sustainable energy reviews, 15(6): 3243-3251. al-iriani, m.a. (2006), energy-gdp relationship revisited: an example from gcc countries using panel causality. energy policy, 34, 3342-3350. alkhathlan, k., javid, m. (2013), energy consumption, carbon emissions and economic growth in saudi arabia: an aggregate and disaggregate analysis. energy policy, 62: 1525-1532. al-mulali, u., che sab, c.n., (2012), the impact of energy consumption and co2 emission on the economic growth and financial development in the sub saharan african countries. energy, 39(1), 180-186. altinay, g., karagol, e. (2004), structural break, unit root, and the causality between energy consumption and gdp in turkey. energy economics, 26, 985-994. ang, j.b. (2007), co2 emissions, energy consumption, and output in france. energy policy, 35,4772-4778. ang, j.b., (2008), economic development, pollutant emissions and energy consumption in malaysia. journal of policy modeling, 30, 271-278. apergis, n., payne, j.e. (2009), energy consumption and economic growth in central america: evidence from a panel cointegration and error correction model. energy economics, 31, 211-216. apergis, n., payne, j.e. (2010), renewable energy consumption and economic growth: evidence from a panel of oecd countries. energy policy, 38, 656-660. aqeel, a., butt, s. (2001), the relationship between energy consumption and economic growth in pakistan. asia pacific development journal, 8, 101-110. asafu-adjaye, j. (2000), the relationship between energy consumption, energy prices, and economic growth: time series evidence from asian developing countries. energy economics, 22, 615-625. bartleet, m., gounder, r., (2010), energy consumption and economic growth in new zealand: results of trivariate and multivariate models. energy policy, 38(7), 3508-3517. belke, a., dobnik, f., dreger, c., (2011), energy consumption and economic growth: new insights into the cointegration relationship. energy economic, 33(5), 782-789. belloumi, m., (2009), energy consumption and gdp in tunisia: cointegration and causality analysis. energy policy, 37(7), 2745-2753. bergman, l. (1988), energy policy modeling: a survey of general equilibrium approaches. journal of policy modeling, 10, 377-399. berndt, e.r. (1980), energy price increases and the productivity slowdown in united states manufacturing: decline in productivity growth. paper presented at federal reserve bank of boston conference series, boston, ma. berndt, e.r. (1990), energy use, technical progress and productivity growth: a survey of economic issues. journal of productivity analysis, 2, 67-83. berndt, e.r., wood, d.o. (1979), engineering and economic interpretation of energy-capital complementarity. american economic review, 69, 343-354. bowden, n., payne, j.e., (2009), the causal relationship between us energy consumption and real output: a disaggregated analysis. journal of policy modeling, 31(2), 180-188. chen, s.t., kuo, h.i., chen, c.c., (2007), the relationship between gdp and electricity consumption in 10 asian countries. energy policy, 35, 2611-2621. cheng, b.s. (1996), an investigation of cointegration and causality between energy consumption and economic growth. journal of energy and development, 21, 73-84. cheng, b.s. (1997), energy consumption and economic growth in brazil, mexico and venezuela: a time series analysis. applied economics letters, 4, 671-774. cheng, b.s. (1998), energy consumption, employment and causality in japan: a multivariate approach. indian economic review, 33(1), 19-29. cheng, b.s. (1999), causality between energy consumption and economic growth in india: an application of cointegration and error correction modeling. indian economic review, 34(1), 39-49. cheng, b.s., lai, t.w. (1997), an investigation of cointegration and causality between energy consumption and economic activity in taiwan. energy economics, 19(4), 435-444. chiou-wei, s.z., chen, c.f., zhu, z. (2008), economic growth and energy consumption: evidence from linear and nonlinear granger causality. energy economics, 30, 3063-3076. chontanawat, j., hunt, l.c., pierse, r. (2006), causality between energy consumption and gdp: evidence from 30 oecd and 78 non-oecd countries. surrey energy economics discussion paper series 113, university of surrey, guildford. chontanawat, j., hunt, l.-c., pierse, r. (2008), does energy consumption cause economic growth?: evidence from a systematic study of over 100 countries. journal of policy modeling, 30, 209-220. climent, f., pardo, a. (2007), decoupling factors on the energy-output linkage: the spanish case. energy policy, 35, 522-528. costantini, v., martini, c., (2010), the causality between energy consumption and economic growth: a multi-sectoral analysis using non-stationary cointegrated panel data. energy economic, 32(3), 591-603. dergiades, t., martinopoulos, g., tsoulfidis, l. (2013), energy consumption and economic growth: parametric and non-parametric causality testing for the case of greece. energy economics, 36, 686-697. ebohon, o.j. (1996), energy, economic growth and causality in developing countries: a case study of tanzania and nigeria. energy policy, 24, 447-453. eggoh, j.c., bangake, c., rault, c., (2011), energy consumption and economic growth revisited in african countries. energy policy, 39(11), 7408-7421. erdal, g., erdal, h., eseng ̈ un, k., (2008), the causality between energy consumption and economic growth in turkey. energy policy, 36(10), 3838-3842. erol, u., yu, e.s.h. (1987a), on the causal relationship between energy and income for industrialized countries. journal of energy and development, 13, 113-122. farhani, s., ben rejeb, j. (2012), energy consumption, economic growth and co2 emissions: evidence from panel data for mena region. international journal of energy economics and policy, 2(2), 71-81. fatai, k., oxley, l., scrimgeour, f.g. (2004), modelling the causal relationship between energy consumption and gdp in new zealand, australia, india, indonesia, the philippines, and thailand. mathematics and computers in simulation, 64, 431-445. fatai, k., oxley, l., scrimgeour, f., (2002), energy consumption and employment in new zealand: searching for causality. nzae conference, wellington, 26-28 june, 2002. international journal of energy economics and policy | vol 5 • issue 2 • 2015400 isa, et al.: review paper on economic growth–aggregate energy consumption nexus francis, b.m., moseley, l., iyare, s.o. (2007), energy consumption and projected growth in selected caribbean countries. energy economics, 29, 1224-1232. fuinhas, j.a., marques, a.c., (2012), energy consumption and economic growth nexus in portugal, italy, greece, spain and turkey: an ardl bounds test approach (1965–2009). energy economic, 34(2), 511-517. ghali, k.h., el-sakka, m.i.t. (2004), energy and output growth in canada: a multivariate cointegration analysis. energy economics, 26, 225-238. ghosh, s. (2002), electricity consumption and economic growth in india. energy policy, 30, 125-129. glasure, y.u. (2002), energy and national income in korea: further evidence on the role of omitted variables. energy economics, 24, 355-365. glasure, y.u., lee, a.r. (1998), cointegration, error correction, and the relationship between gdp and energy: the case of south korea and singapore. resource and energy economics, 20, 17-25. griffin, j.m., gregory, p.r. (1976), an intercountry translog model of energy substitution responses. american economic review, 66, 845-857. hatzigeorgiou, e., politakis, h., haralambopoulos, d., (2011), co2 emissions, gdp and energy intensity: a multivariate cointegration and causality analysis for greece, 1977–2007. applied energy, 88(4), 1377-1385. herrerias, m.j., joyeux, r., girardin, e. (2013), short-and long-run causality between energy consumption and economic growth: evidence across regions in china. applied energy, 112, 1483-1492. ho, cy., siu, k.w., (2007), a dynamic equilibrium of electricity consumption and gdp in hong kong: an empirical investigation. energy policy, 35(4), 2507-2513. hondroyiannis, g., lolos, s., papapetrou, e. (2002), energy consumption and economic growth: assessing the evidence from greece. energy economics, 24, 319-336. hossain, m.d.s., saeki, c. (2011), does electricity consumption panel granger cause economic growth in south asia? evidence from bangladesh, india, iran, nepal, pakistan and sri-lanka. european journal of social sciences, 25(3): 316-328. hossain, m.s. (2011), panel estimation for co2 emissions, energy consumption, economic growth, trade openness and urbanization of newly industrialized countries. energy policy, 39(11), 6991-6999. hossein, s.s.m., yazdan, g.f., hasan, s. (2012), consideration the relationship between energy consumption and economic growth in oil exporting country. procedia-social and behavioral sciences, 62: 52-58. huang, b.n., hwang, m.j., yang, c.w. (2008), causal relationship between energy consumption and gdp growth revisited: a dynamic panel data approach. ecological economics, 67, 41-54. hwang, d., gum, b. (1992), the causal relationship between energy and gnp: the case of taiwan. journal of energy and development, 12, 219-226. jobert, t., karanfil, f. (2007), sectoral energy consumption by source and economic growth in turkey. energy policy, 35, 5447-5456. jorgenson, d.w., wilcoxen, p.j. (1993), reducing us carbon emissions: an econometric general equilibrium assessment. resource and energy economics, 15, 7-25. jumbe, c.b.l. (2004), cointegration and causality between electricity consumption and gdp: empirical evidence from malawi. energy economics, 26, 61-68. karanfil, f. (2008), energy consumption and economic growth revisited: does the size of unrecorded economy matter? energy policy, 36(8), 3029-3035. kemfert, k., welsch, h. (2000), energy-capital-labor substitution and the economic effects of co2 abatement: evidence for germany. journal of policy modeling, 22, 641-660. kraft, j., kraft, a., (1978) on the relationship between energy and gnp. journal of energy and development, 3, 401-403. lau, e., chye, x.h., choong, c.k. (2011), energy-growth causality: asian countries revisited. international journal of energy economics and policy, 1(4), 140-149. lee, c.c. (2005), energy consumption and gdp in developing countries: a cointegrated panel analysis. energy economics, 27, 415-427. lee, c.c. (2006), the causality relationship between energy consumption and gdp in g-11 countries revisited. energy policy, 34(9), 10861093. lee, c.c., chang, c.p. (2005), structural breaks, energy consumption, and economic growth revisited: evidence from taiwan. energy economics, 27, 857-872. lee, c.c., chang, c.p. (2008), energy consumption and economic growth in asian economies: a more comprehensive analysis using panel data. resource and energy economics, 30, 50-65. lise, w., montfort, k.v. (2007), energy consumption and gdp in turkey: is there a co-integration relationship? energy economics, 29, 1166-1178. lu¨tkepohl, h. (1982), non-causality due to omitted variables. journal of econometrics, 19, 267-378. mahadevan, r., asafu-adjaye, j. (2007), energy consumption, economic growth and prices: a reassessment using panel vecm for developed and developing countries. energy policy, 35, 2481-2490. masih, a.m.m., masih, r. (1996), energy consumption, real income and temporal causality: results from a multi-country study based on cointegration and error-correction modelling techniques. energy economics, 18, 165-183. masih, a.m.m., masih, r. (1997), on temporal causal relationship between energy consumption, real income, and prices: some new evidence from asian-energy dependent nics based on a multivariate cointegration/vector error correction approach. journal of policy modeling, 19, 417-440. masih, a.m.m., masih, r. (1998), a multivariate cointegrated modeling approach in testing temporal causality between energy consumption, real income, and prices with an application to two asian ldcs. applied economics, 30, 1287-1298. mehrara, m. (2007a), energy consumption and economic growth: the case of oil exporting countries. energy policy, 35, 2939-2945. mehrara, m. (2007b), energy-gdp relationship for oil-exporting countries: iran, kuwait, and saudi arabia. opec review, 31, 1-16. nachane, d.m., nadkarni, r.m., karnik, a.v. (1988), cointegration and causality testing of the energy-gdp relationship: a cross-country study. applied economics, 20, 1511-1531. narayan, p.k., smyth, r. (2007), energy consumption and real gdp in g7 countries: new evidence from panel cointegration with structural breaks. energy economics, 30, 2331-2341. narayan, p.k., popp, s., (2012), the energy consumption-real gdp nexus revisited: empirical evidence from 93 countries. economic modelling, 29(2), 303-308. ocal, o., aslan, a. (2013), renewable energy consumption–economic growth nexus in turkey. renewable and sustainable energy reviews, 28, 494-499. odhiambo, n.m., (2010), energy consumption, prices and economic growth in three ssa countries: a comparative study. energy policy, 38(5), 2463-2469. oh, w., lee, k. (2004a), causal relationship between energy consumption and gdp revisited: the case of korea 1970-1999. energy economics, 26, 51-59. oh, w., lee, k. (2004b), energy consumption and economic growth in korea: testing the causality relation. journal of policy modeling, 26, 973-981. ozturk, i., acaravci, a., (2010), the causal relationship between energy consumption and gdp in albania, bulgaria, hungary and romania: international journal of energy economics and policy | vol 5 • issue 2 • 2015 401 isa, et al.: review paper on economic growth–aggregate energy consumption nexus evidence from ardl bound testing approach. applied energy, 87(6), 1938-1943. ozturk, i., acaravci, a. (2010), co2 emissions, energy consumption and economic growth in turkey. renewable and sustainable energy reviews, 14(9), 3220-3225. ozturk, i., aslan, a., kalyoncu, h. (2010), energy consumption and economic growth relationship: evidence from panel data for low and middle income countries. energy policy, 38(8): 4422-4428. ozturk, i. (2010), a literature survey on energy–growth nexus. energy policy, 38(1), 340-349. pao, h.t., tsai, c.m. (2011), multivariate granger causality between co2 emissions, energy consumption, fdi and gdp: evidence from a panel of bric (brazil, russian federation, india and china) countries. energy, 36(1), 685-693. paul, s., bhattacharya, r.n. (2004), causality between energy consumption and economic growth in india: a note on conflicting results. energy economics, 26, 977-983. payne, j.e. (2009), on the dynamics of energy consumption and output in the us. applied energy, 86(4), 575-577. pirlogea, c., cicea, c. (2012), econometric perspective of the energy consumption and economic growth relation in european union. renewable and sustainable energy reviews, 16(8), 5718-5726. saboori, b., sulaiman, j. (2013a), environmental degradation, economic growth and energy consumption: evidence of the environmental kuznets curve in malaysia. energy policy, 60, 892-905. saboori, b., sulaiman, j. (2013b), co2 emissions, energy consumption and economic growth in association of southeast asian nations (asean) countries: a cointegration approach. energy, 55, 813-822. sadorsky, p., (2012), energy consumption output and trade in south america. energy economic, 34(2), 476-488. shahbaz, m., zeshan, m., afza, t. (2012), is energy consumption effective to spur economic growth in pakistan? new evidence from bounds test to level relationships and granger causality tests. economic modelling, 29(6): 2310-2319. shahiduzzaman, m., alam, k., (2012), cointegration and causal relationships between energy consumption and output: assessing the evidence from australia. energy economic, 34(6), 2182-2188. smulders, s., de nooij, m. (2003), the impact of energy conservation on technology and economic growth. resources and energy economics, 25, 59-79. souhila, c., kourbali, b. (2012), energy consumption and economic growth in algeria: cointegration and causality analysis. international journal of energy economics and policy, 2(4), 238-249. soytas, u., sarı, r., ozdemir, o. (2001), energy consumption and gdp relation in turkey: acointegration and vector error correction analysis. in: economies and business in transition: facilitating competitiveness and change in the global environment proceedings. global business and technology association. p. 838-844. available from: http://www.sari_r2.web.ibu.edu.tr/yayinlarim/ener gy%20 soytas_sari_ozdemir.pdfs. [last accessed on 2014 dec 24]. soytas, u., sari, r. (2003), energy consumption and gdp: causality relationship in g-7 and emerging markets. energy economics, 25, 33-37. soytas, u., sari, r. (2006a), can china contribute more to the fight against global warming? journal of policy modeling, 28, 837-846. soytas, u., sari, r. (2006b), energy consumption and income in g7 countries. journal of policy modeling, 28, 739-750. soytas, u., sari, r. (2008), energy consumption, economic growth, and carbon emissions: challenges faced by an eu candidate member. ecological economics, 68(6), 1667-1675. soytas, u., sari, r., ewing, b.t. (2007), energy consumption, income, and carbon emissions in the united states. ecological economics, 62, 482-489. stern, d.i. (1993), energy and economic growth in the usa: a multivariate approach. energy economics, 15, 137-150. stern, d.i. (2000), a multivariate cointegration analysis of the role of energy in the us macroeconomy. energy economics, 22, 267-283. tang, c.f., tan, e.c. (2013), exploring the nexus of electricity consumption, economic growth, energy prices and technology innovation in malaysia. applied energy, 104, 297-305. tsani, s.z. (2010), energy consumption and economic growth, a causality analysis for greece. energy economic, 32(3), 582-590. wang, s., zhou, d., zhou, p., wang, q. (2011), co2 emissions, energy consumption and economic growth in china: a panel data analysis. energy policy, 39(9), 4870-4875. warr, b.s., ayres, r.u., (2010), evidence of causality between the quantity and quality of energy consumption and economic growth. energy, 35(4), 1688-1693. wesseh jr. p.k., zoumara, b. (2012), causal independence between energy consumption and economic growth in liberia: evidence from a non-parametric bootstrapped causality test. energy policy, 50, 518-527. wolde-rufael, y. (2004), disaggregated industrial energy consumption and gdp: the case of shanghai, 1952 1999. energy economics, 26, 69-75. wolde-rufael, y. (2005), energy demand and economic growth: the african experience. journal of policy modeling, 27, 891-903. yang, h.y. (2000a), a note on the causal relationship between energy and gdp in taiwan. energy economics, 22, 309-317. yang, z., zhao, y. (2014), energy consumption, carbon emissions, and economic growth in india: evidence from directed acyclic graphs. economic modelling, 38, 533-540. yu, e.s.h., choi, j.y. (1985), the causal relationship between energy and gnp: an international comparison. journal of energy and development, 10, 249-272. yu, e.s.h., hwang, b. (1984), the relationship between energy and gnp: further results. energy economics, 6, 186-190. yu, e.s.h., jin, j.c. (1992), cointegration tests of energy consumption, income, and employment. resources and energy, 14, 259-266. yuan, j., kang, j., zhao, c., hu, z. (2008), energy consumption and economic growth: evidence from china at both aggregated and disaggregated levels. energy economics, 30, 3077-3094. zachariadis, t. (2007), exploring the relationship between energy use and economic growth with bivariate models: new evidence from g-7 countries. energy economics, 29, 1233-1253. zamani, m. (2007), energy consumption and economic activities in iran. energy economics, 29, 1135-1140. zarnikau, j. (1997), a reexamination of the causal relationship between energy consumption and gross national product. journal of energy and development, 21, 229-239. zhang, c., xu, j. (2012), retesting the causality between energy consumption and gdp in china: evidence from sectoral and regional analyses using dynamic panel data. energy economics, 34(6), 1782-1789. zhang, x.p., cheng, x.m. (2009), energy consumption, carbon emissions, and economic growth in china. ecological economics, 68(10), 2706-2712. zhang, y.j. (2011), interpreting the dynamic nexus between energy consumption and economic growth: empirical evidence from russia. energy policy, 39(5), 2265-2272. . international journal of energy economics and policy | vol 10 • issue 1 • 2020 215 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(1), 215-227. the impact of energy consumption based on fossil fuel and hydroelectricity generation towards pollution in malaysia, indonesia and thailand abdul rahim ridzuan1*, aliashim albani2, abdul rais abdul latiff3, mohamad idham md. razak4, mohd haziq murshidi5 1faculty of business and management, universiti teknologi mara, kampus alor gajah, km 26 jalan lendu, 78000 alor gajah, melaka, malaysia, 2universiti malaysia terengganu, malaysia, 3universiti sains malaysia, malaysia, 4universiti teknologi mara, malaysia, 5universiti malaysia sabah, malaysia. *email: rahim670@staf.uitm.edu.my received: 16 may 2019 accepted: 28 september 2019 doi: https://doi.org/10.32479/ijeep.8140 abstract this study investigated the effects of energy consumption (eny) based on fossil fuels and alternative energy with hydroelectricity as its proxy upon pollution, aside from ascertaining if the correlation between income and pollution determined the presence of environmental kuznets curve (ekc). in addition, the functions of foreign direct investment (fdi) inflows and trade openness (to) were probed into so as to generate more precise outcomes of ekc hypothesis. hence, in order to fulfil the objectives outlined in this study, the bound estimation method was utilized to examine three developing nations of the association of south east asian nation (asean), which are malaysia, indonesia, and thailand. the main finding of interest retrieved from this paper refers to the ekc hypothesis reflective of malaysia and thailand. it was discovered that hydroelectricity favourably lowered the release of carbon emissions in the case of malaysia, while it insignificantly influenced environmental degradation for indonesia and thailand. on the other hand, as anticipated, per capita energy use displayed a significant long-run effect in raising the levels of carbon emission in indonesia and thailand. meanwhile, the fdi inflows seemed to improve the environmental quality only in malaysia, while deepening in to among asean-3 nations appeared to successfully minimize issues related to environmental degradation in these countries. keywords: energy consumption, hydroelectricity, real output, carbon emissions jel classifications: o1, q2, q4 1. introduction the deleterious effects of global warming have begun to affect the human race due to the changes noted in the global climate, for instance, acceleration in rising of sea level (yi et al., 2017) and increment in risks of wildfires (kalabokidis et al., 2015). in fact, the global climate system appears to be unambiguously warm with the rising temperature at approximately 0.85 (0.65°c-1.06°c) from 1880 to 2012, as reported by the intergovernmental panel on climate change (ipcc) (2013). the climate change can negatively influence the environment ecosystem and the sustainability of socio-economic (enríquez-de-salamanca et al., 2017; zhang et al., 2017). the most significant driver of climate change is the larger emission of greenhouse gases (ghg) being released into the atmosphere. the ghg reabsorbs infrared radiation and heat that is penetrated from the sun to the earth. as such, ghg prevents the heat escaping from the earth, thus causing the earth to become warmer; a phenomenon known as the greenhouse effect. since year 1750, the concentration of essential elements that make up ghg in the atmospheres, which are carbon dioxide (co2), methane (ch4), and nitrous oxide (n2o), has been reported to rise by approximately 144%, 256%, and 121%, this journal is licensed under a creative commons attribution 4.0 international license ridzuan, et al.: the impact of energy consumption based on fossil fuel and hydroelectricity generation towards pollution in malaysia, indonesia and thailand international journal of energy economics and policy | vol 10 • issue 1 • 2020216 respectively. nonetheless, the world meteorological organization (wmo) (2016) reported that the concentration of these elements for year 2015 appears to be approximately 400.0 ± 0.1 ppm (co2), 1845 ± 2 ppb (ch4), and 328.0 ± 0.1 ppb (n2o). the energy sector, especially the oil and coal-based fuel, has contributed predominantly to the massive emission of ghgs into the atmosphere (bhanu et al., 2018). coal and fossil fuel are popular, particularly among developing countries for it is one of the cheapest sources of energy, in comparison to other sources. in addition, the international energy agency (iea) has reported that the southeast asia is one of the few regions in the world that has an increasing share of coal in its energy mix (iea, 2015). on top of that, fossil fuel and coal have remained the larger contributor for electric generation in association of south east asian nation (asean)-3 countries, as reported by suruhanjaya tenaga (st) (2016) for malaysia, dewan energi nasional (den) (2016) for indonesia, and electricity generating authority of thailand (egat) (2016) for thailand. in fact, numerous energy resources are available that are cleaner than fossil fuel and coal; in which hydroelectricity is one of them, which has been considered as one of the most environmentalfriendly energy forms (tampakis et al., 2013; melikoglu, 2017). hydroelectric energy has the potential to decrease ghg emission into the atmosphere, as hydro plant is free from air pollution. moreover, the source of energy itself derives from natural resource; kinetic energy from the flow of river water. in comparison to other intermittent renewable energy resources, such as wind and solar energy, hydroelectric energy appears to be the best alternative energy that can compete with fossil fuel to generate huge volumes of electricity. according to the renewable energy policy network for the 21th century (ren21) in year 2017, thailand had set the highest target on hydropower at a capacity of 6.1 gw to achieve by 2021. while in indonesia, the target capacities of hydropower and mini-hydro by 2021 are 2.1 gw and 0.43 gw, respectively. as for malaysia, the target for micro-hydro is 2.1 gw of generation capacity. nevertheless, a recent report published by the international hydropower association (iha) (2018) states that the present installed capacity of large hydropower in malaysia seem to be the highest among the three nations (6.094 gw), followed by indonesia (5.305 gw), and thailand (4.51 gw). koutroumanidis et al. (2009) revealed that energy resource is the dominant factor for the growth of socio-economic in any nation. in fact, this notion is in agreement with stern (2011) as he found that the emerging and industrialized economies are driven by both economic and better quality of energy inputs. conversely, the asian development bank (adb) (2016) highlighted that climate change is putting pressure on food security and causing a negative effect on the well-being of humans. moreover, the demand for total primary energy among southeast asia nations has been projected to escalate by 80% from year 2013 until 2040 mainly due to increment of economic activities within the region by triple and hike in shifts among the populations to urban areas for better employment and lifestyle. besides, vast industrial and commercial facilities are available in urban areas due to increment in population, thus contributing to the rising energy consumption and demand iea (2015) also reported that indonesia has the largest en, followed by thailand and malaysia. as such, this study investigated the effect of energy based on fossil fuels and alternative energy with hydroelectricity as its proxy upon pollution among selected three asean countries, which are indonesia, malaysia, and thailand, over a period ranging from 1980 and 2014. furthermore, to shed light on the correlation between growth and rate of pollution among these nations, this paper probed into the presence of environmental kuznets curve (ekc) hypothesis. the ekc assumes that environmental degradation first increases as income increases during the earlier stage of economic development and then when income reaches a certain high level, the level of pollution starts to decreases. although this issue has been studied by adebola et al. (2017) and jebli et al. (2016), this paper offers a new view, in which cleaner energy via hydroelectricity is introduced as one of the variables to determine the existence of ekc. hence, this paper appears to be a potential study that adds value to the existing literature, especially from the lens of asean countries. the remaining sections of the paper are organized as follows: section 2 reviews the relevant literature on several variables related to energy and the methodology associated to ekc hypothesis. next, section 3 highlights the sources of data and briefly explains the empirical methodology applied in the study. after that, section 4 presents the empirical results and discussion. finally, the paper ends with section 5, where the conclusion and several policy recommendations are depicted. 2. literature review the existence of ekc hypothesis has been a subject of interest among many researchers over the years. given that the theme of this paper revolves around validation of ekc hypothesis and source of energy (eny), only papers that have utilized both gross domestic product (gdp) and square of gdp (gdp2), as well as all the types of energy sources tabulated in table 1, have been considered. overall, this area of study has varied spheres. the past literature has employed a number of determinants to determine pollutions, for example, real output (gdp), energy consumption (eny), industrial output, urbanization, population, financial development, trade openness (to), and foreign direct investment (fdi). next, some researchers have applied various indicators to identify pollution in many nations across regions, namely east asia and pacific (cf. saboori and sulaiman, 2013; chandran and tang, 2013), europe and central asia (cf. acaravci and ozturk, 2010; pao et al., 2010; 2011; kasman and duman, 2015), middle east and north africa (cf. arouri et al., 2012; ozcan, 2013; shahbaz et al., 2014), south asia (cf. shahbaz et al., 2012), and subsaharan africa (cf. kivyiro and arminen, 2014; shahbaz et al., 2015). third, some studies opted to use gdp solely to account for the presence of ekc hypothesis. nevertheless, in order to gain better and accurate results of the inverted ekc hypothesis, gdp and gdp2 should be incorporated as indicators for pollution. ridzuan, et al.: the impact of energy consumption based on fossil fuel and hydroelectricity generation towards pollution in malaysia, indonesia and thailand international journal of energy economics and policy | vol 10 • issue 1 • 2020 217 authors country period variable for energy methodology ekc hypothesis acaravci and ozturk (2010) european countries 1960-2005 energy consumption ardl and vecm granger causality yes pao and tsai (2010) brazil, russia, india and china 1971-2005 energy consumption pedroni, kao and johansen cointegration, ordinary least square and vecm granger causality yes pao and tsai (2011) bric countries 1980-2007 energy consumption pedroni, kao and johansen cointegration, ols and vecm granger causality yes pao and tsai (2011) brazil 1980-2007 energy consumption grey prediction model yes wang et al. (2011) china 1995-2007 energy consumption pedroni cointegration and vecm granger causality no arouri et al. (2012) middle east and north african countries 1981-2005 energy consumption the cross correlated effects and cce mean group yes jayanthakumaran et al. (2012) china and india 1971-2007 energy consumption ardl yes pao et al. (2012) china 1980-2009 energy consumption grey prediction model no chandran and tang (2013) asean 1971-2008 transport energy consumption johansen cointegration and vecm granger causality no govindaraju and tang (2013) india and china 1965-2009 coal consumption bayer and hanck combine cointegration test, and vecm granger causality no kohler (2013) south africa 1960-2009 energy consumption ardl, johansen cointegration and vecm granger causality yes ozcan (2013) middle east countries 1990-2008 energy consumption westerlund panel cointegration, full modified ols and vecm granger causality yes saboori and sulaiman (2013a) asean countries 1971-2009 energy consumption ardl, johansen cointegration and vecm granger causality yes, for thailand and singapore saboori and sulaiman (2013b) malaysia 1980-2009 electricity consumption, oil consumption, coal consumption and gas consumption ardl, johansen cointegration and vecm granger causality yes shahbaz et al. (2013a) africa 1965-2008 coal consumption ardl, johansen cointegration and vecm granger causality yes bella et al. (2014) organization for economic cooperation and development (oecd) countries 1965-2006 electricity consumption larsson, lyhagen, and lothgren cointegration and vecm granger causality yes farhani et al. (2014) tunisia 1971-2008 energy consumption ardl, and vecm granger causality yes kivyiro and arminen (2014) sub-saharan countries 1971-2009 energy consumption ardl, and vecm granger causality yes, in most countries saboori et al. (2014) opec countries 1977-2008 oil consumption ardl, and toda-yamamoto-dolado-lutkepohl causality yes al-mulali et al. (2015) ninety-three countries based on income 1980-2008 energy consumption panel fixed effects and the generalized method of moments yes, for upper and high income countries al-mulali et al. (2015) vietnam 1981-2011 renewable energy consumption ardl, and vecm granger causality no baek (2015) artic countries 1960-2010 energy consumption ardl yes baek (2015) nuclear producing countries 1980-2009 nuclear energy consumption and energy consumption pedroni cointegration, dols and fmols yes begum et al. (2015) malaysia 1970-2009 energy consumption ardl, dols and sasabuchi-lind-mehlum tests yes kasman and duman (2015) european union (eu) countries 1992-2010 energy consumption pedroni and kao cointegration, fmols, and vecm granger causality yes ozturk and al-mulali (2015) cambodia 1996-2012 energy consumption two-stage least square and gmm no table 1: summary of ekc hypothesis and variables used for energy from 2010-2018 (contd...) ridzuan, et al.: the impact of energy consumption based on fossil fuel and hydroelectricity generation towards pollution in malaysia, indonesia and thailand international journal of energy economics and policy | vol 10 • issue 1 • 2020218 referring to the list of studies presented in table 1, 80% of the studies have accounted for the presence of ekc hypothesis by embedding income and pollution. the studies that involved high income nations, especially the europe, did validate the presence of ekc (cf. acaravci and ozturk, 2010; kasman and duman, 2015), while contradicting results were found in most underdeveloped countries (cf. al-mulali et al., 2015; ozturk and al-mulali, 2015). this study offers to bridge the existing gap of study concerning ekc hypothesis. first, this study contributes to the study of ekc hypothesis within the region of asean-3 nations, namely indonesia and thailand, which have experienced rapid economy growth since the last three decades. second, although the studies mostly used source of eny and fossil fuels, none has included the aspect of alternative energy, such as hydroelectricity. electricity generated from hydroelectricity has been used in these countries since the past four decades; however, it appears that the econometric model has yet to be applied. therefore, this study examined the ekc hypothesis in malaysia, thailand, and indonesia by including both types of energy. third, prior studies outcomes may be inaccurate as a result of multicollinearity issue due to the inclusion of both gdp and gdp2 within a regression. thus, in the attempt to address this problem, this study adhered to the steps taken by narayan and narayan (2010), which is explained in the analysis section. 3. methodology initially, the model of environmental quality was developed by presenting it in a broad format of ekc hypothesis, which can be translated in the following equation: co f gdp gdp2 2= ( , ) (1) authors country period variable for energy methodology ekc hypothesis shahbaz et al. (2015) african countries 1980-2012 electricity intensities johansen cointegration, pedroni cointegration, and vecm granger causality yes tang and tan (2015) vietnam 1976-2006 energy consumption johansen cointegration, and vecm granger causality yes yin et al. (2015) china 1976-2006 renewable energy consumption panel random effects model yes jebli et al. (2016) oecd countries 1980-2010 renewable energy consumption and non-renewable energy consumption pedroni cointegration, fmols, dols and granger causality yes al-mulali et al. (2016) countries in 7 regions 1980-2010 renewable energy consumption pedroni and fisher panel cointegration, dols and vecm granger causality yes, for east asia and the pacific, western europe, east europe and central asia and the america shahbaz et al. (2016) african countries 1971-2012 energy intensities ardl, bayer and hanck cointegration yes, for africa, algeria, cameroon, congo republic, morocco, tunisia and zambia danish et al. (2017) pakistan 1970-2012 renewable energy consumption and non-renewable energy consumption ardl, fmols, dols, and canonical cointegration yes dong et al. (2017) 30 provinces in china 1995-2014 energy and natural gas consumption panel fmosl, panel dols yes kharbach and chfadi (2017) morocco 2000-2011 energy consumption and diesel consumption johansen cointegration yes adebola et al. (2017) india and china 1965-2013 hydroelectricity used per capita ardl, and vecm granger causality yes pal and mitra (2017) india and china 1971-2012 electricity generated from coal as share of total electricity ardl yes shahbaz et al. (2017) us 1960-2016 biomass energy consumption ardl, and vecm granger causality yes sinha and shahbaz (2018) india 1971-2015 renewable energy generation ardl yes adu and denkyirah (2018) west africa countries 1970-2013 combustible renewable waste panel fixed and random effect no table 1: (continued) ridzuan, et al.: the impact of energy consumption based on fossil fuel and hydroelectricity generation towards pollution in malaysia, indonesia and thailand international journal of energy economics and policy | vol 10 • issue 1 • 2020 219 where co2 refers to carbon emissions per capita proxy for pollution or level of environmental quality, gdp represents economic growth, while gdp2 denotes the square of gdp. economic growth is achieved when a nation has the ability to meet the demands of goods and services across a certain time period. this is determined by examining the variance of gdp between the target year and the previous year. the equation is transformed from 1 to log-linear specification (ln) because it can yield better and more accountable empirical outcomes, in comparison to the alternative method of simple linear modelling (shahbaz et al., 2015), apart from allowing the value to convert to elasticities. thus, the logarithm form for the estimation model is formulated as follows: lnco lngdp lngdpt t t t2 0 1 2 2= + + +a a a e( ) (2) where t refers to time period, co2 represents carbon emissions per capita, gdp denotes per capita real gdp, and ɛ is standard error term. the variance of the functional forms between the variables of economic growth and carbon emissions is portrayed in the values of income coefficients. when the result shows α1=α2= 0, a level relationship is concluded, α1 < 0 and α2 = 0 display the evidence of monotonically decreasing linear relationship, α1 > 0 and α2 = 0 account for the presence of a monotonically increasing linear relationship, α1 < 0 and α2 > 0 yield the evidence for u-shaped relationship, and α2 < 0 portrays an inverted u-shaped relationship, which accounts for ekc in relation to carbon emissions. in another instance, saboori et al. (2012) tested the ekc hypothesis by excluding other explanatory variable, as displayed in equation 2. nonetheless, the study concluded that the outcome of ekc that appeared to exist in the estimated model was insufficient to ascertain the presence of inverted-u relationship between environmental degradation and income. based on these findings, alternatives for significant variables are proposed so as to exert influence pertaining to the presence of ekc hypothesis in the model. an example of it is eny, which has been widely used in prior environmental quality models based on studies carried out by hossain (2011), pao and tsai (2011), al mulali and che sab (2012), as well as saboori and sulaiman (2013a,b), which considered eny as a vital determinant of carbon emissions. from the perspectives of asean-3 developing nations (malaysia, indonesia, and thailand), these countries heavily rely on dirty energy, such as coal, to stimulate economic activities mainly because the cost of using such energy is relatively cheaper. in precise, fossil fuel combustions that yield higher eny would end up causing extensive damages due to higher release of carbon emissions that contributes to the degradation of environmental quality. in response to more call for alternative energy sources that stems from the awareness of climate change, these countries have begun utilising other cleaner sources, such as hydroelectricity, as a substitute for fossil-type energy resources. studies that have depicted the use of hydroelectricity using the model are carried out by solarin et al. (2017) on india and china. thus, the study embedded hydroelectricity as a proxy for alternative eny in the model. the new equation is given as follows: lnco lngdp lngdp lneny lnaeny t t t t t t 2 0 1 2 2 3 4 = + + + + + a a a a a e ( ) (3) next, a study conducted by lau et al. (2014) revealed an increased dependency on fdi for growth among developing countries in asean. nevertheless, the inflows of fdi in these countries may have an adverse effect upon environmental quality. thus, similar to the prior model proposed by al-mulali (2012) and pao and tsai (2011), the fdi had been incorporated in this study as a crucial determinant of carbon emissions. in other instances, jensen (2006) and acharyya (2009) concluded that fdi can have a double-edged sword effect; which means, it facilitates economic growth, but at the same time, causes serious implication towards the environment through industrial pollution and environmental degradation. moreover, in order to cut cost on environmental controls, the underdeveloped regions become the safe haven for these polluting industries and businesses as these regions have a more relaxed attitude towards environmental standards, thus turning into pollution slums; described as pollution haven hypothesis (phh). meanwhile, under the halo effect hypothesis (heh), more efficient and cleaner production technology that commonly derives from advanced countries is adopted as a result of fdi so as to enhance the environmental quality (stretesky and lynch, 2008). hence, the new equation is stated as follows: lnco lngdp lngdp lneny lnaeny lnfdi t t t t t t 2 0 1 2 2 3 4 5 = + + + + + a a a a a a ( ) ++et (4) from equation 4, the next variable that can generate a juxtaposition effect upon the level of environmental quality (co2) is to. in fact, many studies have employed to as a determinant for carbon emissions, for example, halicioglu (2009) for turkey, and tiwari et al. (2013) for india. according to copeland and taylor (2004) and baek et al. (2009), globalization may be the leading cause of the rising active pollution from intensive industries among the developing nations in asean, which have severely affected the quality of the environment. this implies that prior studies that have omitted trade-related variables, such as fdi and to, may portray a hint of biasness. the new equation is listed in the following: lnco lngdp lngdp lneny lnaeny lnfdi t t t t t t 2 0 1 2 2 3 4 5 = + + + + + a a a a a a ( ) ++ +a e6lntot t (5) where α denotes regression coefficient, while α1, and α3, are predicted to display positive sign. nonetheless, either positive or negative sign can be expected for α2, α4, α5, and α6. finally, μ refers to error term that is assumed to be normally distributed with zero mean and constant variance. in fact, the empirical model employed in this study incorporated most of the vital determinants for carbon emissions, thus clearing this study from any concern associated to variable bias, primarily because all the variables were regressed within the same multivariate framework. furthermore, by employing the unrestricted version of autoregressive distributed lag (ardl) model initiated by pesaran et al. (2001), this study formulated the following error correction models based on equation 5: ridzuan, et al.: the impact of energy consumption based on fossil fuel and hydroelectricity generation towards pollution in malaysia, indonesia and thailand international journal of energy economics and policy | vol 10 • issue 1 • 2020220 dlnco lnco lngdp lngdp lneny t t t t t 2 0 0 2 1 1 1 2 2 1 3 1 4 = + + + + + b q q q q q llnaeny lnfdi lnto lnco l t t t i t i i a i i b = = + + + +å å 1 5 1 6 1 2 1 0 q q b gd d nngdp lngdp lneny lnaeny t i i i c t i i i d t i i i e = = = + + + å å å d l j d d d 0 2 0 0 tt i i t i i f i i g t i t lnfdi lnto = = + + + å å y r u d d 0 0 (6) where ∆ represents the first difference operator and ut refers to white-noise disturbance term. besides, the residuals for unrestricted error correction model (uecm) should be serially uncorrelated, and the model has to be stable. meanwhile, the null hypothesis of no co-integration against the alternative hypothesis for the presence of long-run co-integration is defined by the following: h0: θ0 = θ1 = θ2 = θ3 = θ4 = θ5 = θ6 = 0 (absence of long-run relationship) h1: θ0 ≠ θ1 ≠ θ2 ≠ θ3 ≠ θ4 ≠ θ5 ≠ θ6 ≠ 0 (presence of a long-run relationship). next, upon confirming the existence of long-run relationship via f statistic, both long-run and short-run elasticity coefficients can be determined. the long-run relationship model is depicted in the following: dlnco lnco lngdp lngdp lneny t t t t t 2 0 0 2 1 1 1 2 2 1 3 1 4 = + + + + + b a a a a a llnaeny lnfdi lnto t t t t -+ + + 1 5 1 6 1a a u (7) next, the short-run relationship model is presented as follows: d d d d lnco ect lnco lngdp t t i t i i a i i b t i i i 2 0 1 2 1 0 = + + + + = = = å å b j b g d 00 2 0 0 1 c t i t i i d t i t i i e t i i i lngdp lneny lnaeny å å å = = + + + l j y d d == = -å å+ + 0 1 1 0 1 f i i i g i tlnfdi lntod dr u (8) where φ represents coefficient of error correction term (ect). the value of ect must be significantly negative to reflect converges, apart from displaying the rate of speediness of all the variables towards equilibrium. the variable ectt-1, which is a lagged value of the estimated ordinary least square (ols) residual (ʋt) from the longrun model, is given based on equation 7.0. moreover, it is essential to ensure that the proposed model is absent from serial correlation, normality, and homoscedasticity issues by performing a diagnostic test. 3.1. sources of data the annual data employed in this study are mostly in the form of per capita and are derived from 1980 until 2014. co2 emissions are in metric tons per capita, real gdp is in constant 2010 us dollar, eny is based on per capita (kg of oil equivalent), alternative energy with hydroelectricity generation as its proxy is divided by the total population so as to incur billion kilowatt hours per capita, while fdi and to are based on their ratios over gdp. all data used in this study were based on the world development indicator (2017) generated by world bank, except for hydroelectricity generation that had been obtained from u.s energy information administration (2015). 4. results and analysis 4.1. testing the stationarity of data the analysis was initiated by testing the data with dickeyfuller (adf) and phillip perron (pp) unit root tests, in which the outcomes are depicted in table 2. for all these tests, the null hypothesis includes a unit root, whereas the alternative hypothesis has no unit root. unit root tests were performed to determine the order of integration of each variable so as to identify the best method of time series analysis suitable for the proposed econometric model. the selection of lag for the adf unit root test was set based on schwarz info criterion (sic), given a small number of observations carried out in this study. in addition, all unit roots were estimated at level and first difference. overall, the results showcased a mix stationarity of the variables at level, i(0), and at first difference, i(1). to further clarify, based on the malaysian adf unit root test outcomes at level, both lnaeny and lnfdi appeared to be stationary, i(0) at 10% and 1% level, respectively. on the other hand, based on pp test at level, lnfdi was found to be significant at 1% level at both intercept and trend, and intercept. nevertheless, at first difference for the adf test, these variables seemed to be insignificant at trend and intercept for lnaeny, but both intercept and trend, and intercept for lnfdi. a more powerful property of unit root, which is the pp test, was performed and exhibited that all variables were significant mostly at 1% level. the mixed evidence for stationarity of the variables at level and at first difference was also determined for indonesia and thailand. thus, the mixed stationarity of the unit roots favoured the condition for implementation of ardl estimation for all the three countries. 4.2. determining long-run relationship in order to confirm the presence of long-run relationship between the variables, the model of each asean-3 had been tested by using ardl co-integration test, which revealed the f-statistic values, as tabulated in table 3. the null hypothesis cannot be rejected if the f-statistic falls below the bound level, but if the f-statistic exceeds the upper bound level; the null hypothesis is rejected, thus signifying the existence of co-integration. the results showed that the null hypothesis of no co-integration for malaysia (4.14 > 3.61) is rejected at 5% significant level, while indonesia (7.00 > 4.43) and thailand (8.93 > 4.43) are rejected at 1% level, given that their f-statistic values were greater than the upper bound critical value, i(1), as given in table 3. this implies a tendency for the variables to move towards the long-run equilibrium for all the proposed models. ridzuan, et al.: the impact of energy consumption based on fossil fuel and hydroelectricity generation towards pollution in malaysia, indonesia and thailand international journal of energy economics and policy | vol 10 • issue 1 • 2020 221 4.3. diagnostic test table 4 presents the outcomes of diagnostic statistics, such as serial correlation test, misspecification test, heteroscedasticity test, and normality test. all the tested models for the countries selected in this study seemed to be absent from any diagnostic test, given that the probability values are >10% significant level. table 2: results of adf and pp unit root tests country variable adf unit root test pp unit root test intercept trend and intercept intercept trend and intercept malaysia level lnco2 −1.25 (0) −1.57 (0) −1.28 (1) −1.61 (2) lngdp −0.66 (0) −1.69 (0) −0.66 (1) −1.87 (2) lngdp2 −0.49 (0) −1.83 (0) −0.50 (1) −2.01 (2) lneny −1.14 (0) −1.73 (0) −1.32 (5) −1.70 (1) lnaeny −2.76 (1)* −3.11 (1) −2.05 (16) −2.17 (11) lnfdi −4.93 (0)*** −4.98 (0)*** −4.93 (0)*** −4.99 (1)*** lnto −1.56 (1) 0.42 (0) −1.34 (3) 0.13 (1) first difference lnco2 −6.46 (0)*** −6.49 (0)*** −6.42 (2)*** −6.46 (2)*** lngdp −4.81 (0)*** −4.74 (0)*** −4.81 (0)*** −4.74 (0)*** lngdp2 −4.89 (0)*** −4.81 (0)*** −4.89 (0)*** −4.81 (0)*** lneny −6.28 (0)*** −6.32 (0)*** −6.39 (3)*** −6.82 (6)*** lnaeny −5.07 (1)*** −3.09 (3) −4.48 (15)*** −4.34 (15)*** lnfdi −1.63 (7) −1.84 (7) −24.13 (22)*** −23.16 (23)*** lnto −3.41 (0)** −3.48 (2)* −3.44 (5)** −3.75 (15)** indonesia level lnco2 −1.08 (0) −3.15 (0) −1.00 (6) −2.88 (5) lngdp 0.02 (0) −2.21 (1) 0.02 (0) −1.92 (2) lngdp2 0.25 (0) −2.19 (1) 0.25 (0) −1.86 (2) lneny −1.28 (0) −1.10 (0) −1.35 (5) −1.07 (1) lnaeny −2.39 (2) −3.69 (0)** −2.42 (4) −3.68 (4)** lnfdi −2.66 (0)* −4.29 (1)*** −2.44 (15) −3.46 (15)* lnto −2.94 (0)* −2.91 (0) −2.96 (3)** −2.94 (3) first difference lnco2 −5.57 (1)*** −5.43 (1)*** −6.67 (10)*** −6.43 (9)*** lngdp −4.39 (0)*** −4.35 (0)*** −4.42 (1)*** −4.35 (2)*** lngdp2 −4.34 (0)*** −4.34 (0)*** −4.37 (1)*** −4.33 (2)*** lneny −5.91 (0)*** −3.97 (7)** −5.91 (1)*** −6.08 (5)*** lnaeny −7.39 (1)*** −7.70 (1)*** −10.50 (4)*** −10.73 (3)*** lnfdi −6.76 (2)*** −6.64 (2)*** −9.00 (11)*** −8.77 (11)*** thailand level lnto −8.35 (0)*** −8.24 (0)*** −8.35 (0)*** −8.24 (0)*** lnco2 −1.27 (0) −0.48 (0) −1.15 (2) −0.86 (2) lngdp −1.51 (1) −1.73 (1) −1.47 (2) −1.33 (3) lngdp2 −1.36 (1) −1.82 (1) −1.26 (2) −1.45 (3) lneny −0.51 (0) −1.30 (0) −0.54 (3) −1.75 (3) lnaeny −3.88 (1)*** −4.86 (1)*** −5.73 (6)*** −12.38 (33)*** lnfdi −2.89 (0)* −3.26 (0)* −2.81 (3)* −3.34 (3)* lnto −0.85 (0) −1.61 (0) −0.86 (1) −1.87 (3) first difference lnco2 −3.89 (0)*** −4.24 (0)** −3.88 (1)*** −4.26 (6)*** lngdp −3.15 (0)** −3.34 (0)* −3.15 (0)** −3.36 (1)* lngdp2 −3.31 (0)** −3.43 (0)* −3.31 (0)** −3.44 (1)* lneny −4.37 (0)*** −4.32 (0)*** −4.32 (2)*** −4.25 (2)** lnaeny −5.89 (3)*** −6.10 (3)*** −12.40 (27)*** −15.85 (23)*** lnfdi −7.86 (0)*** −7.83 (0)*** −8.16 (2)*** −8.78 (4)*** lnto −5.50 (0)*** −5.47 (0)*** −5.50 (1)*** −5.46 (1)*** (1) ***, **, and *are 1%, 5%, and 10% of significant levels, respectively. (2) the optimal lag length was selected automatically by using the sic for adf test, while the bandwidth was opted by using the newey–west method for the pp test. (3) number in parentheses refers to standard errors table 3: results of ardl co-integration asean-3 maximum lag sic (a, b, c, d, e, f, g) f statistic at sic result malaysia (4,2) (1,2,2,0,0,1,2) 4.14** co-integration exists indonesia (2,2) (2,0,0,2,1,0,2) 7.00*** co-integration exists thailand (3,3) (1,1,3,3,2,3,2) 8.93*** co-integration exists critical values for f-statistics# lower i (0) upper i (1) 1% 3.15 4.43 5% 2.45 3.61 10% 2.12 3.23 #the critical values were obtained from pesaran et al. (2001) based on case iii: unrestricted intercept and no trend. *, **, and ***represent 10%, 5%, and 1% level of significance, respectively ridzuan, et al.: the impact of energy consumption based on fossil fuel and hydroelectricity generation towards pollution in malaysia, indonesia and thailand international journal of energy economics and policy | vol 10 • issue 1 • 2020222 therefore, the outcomes produced from all the three models are indeed reliable. besides, the size of the adjusted r2 indicated a good fit for all the models. apart from diagnostic tests, it is compulsory to determine the stability of each model via cumulative sum of recursive residual (cusum) and cumulative sum of squares of recursive residuals (cusumsq) stability tests. the diagrams illustrated in table 5 show that the plots of both cusum and cusumsq, as represented by blue line, appear to fall inside the critical bounds of 5% significant level for all asean-3 countries, except for cusumsq of indonesia. the plot of cusumsq for indonesia seemed to be out of the critical limits, hence suggesting some instability in the model. nevertheless, as the plot returned towards the critical bands, the deviation was only transitory. furthermore, the outcomes of stability tests for malaysia, indonesia, and thailand suggest that policy changes, upon considering the explanatory variables of carbon emissions embedded in this study, did not cause any major distortion in the level of carbon emissions. 4.4. the long-run elasticities the outcomes of long-run elasticities, as displayed in table 6, are briefly explained in this section. 4.4.1 malaysia based on the estimation of long-run elasticities, this study validated the ekc hypothesis, given that malaysia’s both gdp and gdp2 have the correct expected sign and are significant at 1% level. furthermore, the use of varying sets of determinants in this study, as opposed to prior studies conducted by saboori et al. (2012), saboori and sulaiman (2013b), lau et al. (2014), and begum et al. (2015), aids in contributing in-depth knowledge on this scope. the presence of ekc hypothesis, which is also known as inverted u-shaped relationship between economic growth and environmental quality with co2 emissions as the proxy, displayed that through the period of observation, malaysia took several active measures in minimizing pollution by joining in the efforts that protect the environment, namely kyoto protocol that aims to put a stop to greenhouse effect. aside from that, malaysia is also table 4: results of diagnostic test asean-3 serial correlation x2(1) [p-value] functional form x2(1) [p-value] normality x2(2) [p-value] heteroscedasticity x2(1) [p-value] adjusted r2 malaysia 0.38 [0.68] 1.14 [0.29] 0.05 [0.97] 1.43 [0.23] 0.98 indonesia 1.01 [0.38] 2.48 [0.11] 0.91 [0.63] 1.51 [0.19] 0.97 thailand 1.77 [0.22] 0.55 [0.47] 0.35 [0.83] 0.89 [0.60] 0.99 the numbers in brackets [ ] refer to p values table 5: stability tests ridzuan, et al.: the impact of energy consumption based on fossil fuel and hydroelectricity generation towards pollution in malaysia, indonesia and thailand international journal of energy economics and policy | vol 10 • issue 1 • 2020 223 associated to millennium development goal (mdg) that assists in overcoming environmental degradation through enforcement of stringent environmental laws, such as environmental quality act 1974 and environmental quality order 1987, while simultaneously boosting its economic development. next, alternative energy consumption (aeny) with hydroelectricity as its proxy resulted in a significantly negative sign at 1%. this means; 1% increment in hydroelectricity consumption could help to decrease 0.15% of carbon emissions, thus suggesting control of air pollution. this shows that the malaysian government does not heavily depend on single source of energy alone, but also places focus on cleaner energy, which is in agreement with ahmad et al. (2011). besides aeny, both fdi and to seemed to be significantly negative at 10% and 1%, respectively. the negative coefficient of fdi appears to be in line with the heh, thus implying that higher fdi inflows have helped malaysia with cleaner technology spill-over. on top of that, it was found that most multinational companies from japan and korea have adopted more advanced technology that focuses on cleaner energy, thus reducing reliance on dirty energy and controlling the release of carbon emissions. for instance, 1% increment in fdi led to 0.03% of decrease in carbon emissions. embracing (to) has helped to cut the level of carbon emissions in malaysia, as 1% increment in to decreases carbon emissions release by 0.57, which seems greater when compared to aeny and fdi. the negative sign of to may imply that malaysia has opted for more clean-intensive products for exports and has chosen to import pollution-intensive products from their trading partners. besides, the government has been actively encouraging the local industries, particularly those involved in export activities, to select cleaner technologies over those obsolete and dirty. lastly, eny displayed a correct sign, which is positive, but it appears not to influence the level of carbon emissions in malaysia, as it was insignificant at all levels. this result is opposed to the outcome of most prior studies conducted for malaysia, such as that obtained by shahbaz et al. (2013b). 4.4.2. indonesia as for the case in indonesia, its economic progress has experienced the u-shaped ekc, following the negative and positive signs for gdp and gdp2, respectively. such results are in line with those retrieved from lean and smyth (2010) for indonesia. this particular scenario reveals that the economic progress in indonesia at both the initial and present stages has caused high environmental degradation. the indonesian economic development is currently dealing with a rather critical environmental drawback, such as thinning of forests, water pollution due to dumping of industrial wastes into water, air pollution particularly in urban areas, and haze produced from forest fires. among the notable environmental issue refers to the occurrence of massive and thick haze of smog caused by human activity, whereby land is burnt annually to make ways for the country to produce pulp, paper, and palm oil. this activity is most commonly done on the island of sumatra located at the western indonesia and borneo, which does not only portray a negative impact upon climate change, but also causing a stir amongst its neighbouring countries, such as malaysia and singapore. furthermore, the high reliance among indonesian producers on dirty energy, which is based on fossil fuel type of energy, has led to higher environmental degradation. thus, increase in eny contributes to energy pollutants in a rather significant manner after economic growth. the results infer that a 1% rise in eny is linked with a 1.30% increment in co2 emissions. next, the outcome of to was found to be negative and statistically significant at 5% level, which indicates that embracing to has managed to decrease environmental degradation due to carbon emissions. this shows that to offers access to indonesia for advanced technology that emits less co2 emissions. meanwhile, the alternative energy with hydroelectricity generation as its proxy (aeny) and fdi inflows failed to influence the level of environmental quality in indonesia for they appeared insignificant at all levels. 4.4.3. thailand similar to malaysia, the validity of ekc hypothesis is also proven for the case of thailand as both its gdp and gdp2 displayed the correct expected sign and statistical significance at 1% level. the sustainable environmental quality, along with its progressive economic growth achieved by thailand is believed due to the success of its 10th and 11th national economic and social development plan implemented from 2007 until 2016 by its government. the policies that emphasized on environmental governance, environmental quality promotions, environmental-friendly production and consumption, environmental responsibilities, as well as climate and natural disasters resilience, were specifically designed for the country to attain green and balanced growth. this outcome suggests a new empirical finding that supports the validity of ekc in thailand, in comparison to all other past findings retrieved by narayan and narayan (2010) and lean and smyth (2010), who failed to support the validity of ekc for thailand. next, fossil fuel eny appears to intensify pollution by its significantly positive effect upon carbon emissions. this particular outcome, in general, is in agreement with saboori and sulaiman (2013a,b), shahbaz et al. (2014), and cho et al. (2014). briefly, 1% increment in eny leads to a hike in carbon emissions by 4.29%. besides, when compared to the outcomes derived from indonesia, the table 6: estimation of long-run elasticities country/ardl malaysia (1,2,2,0,0,1,2) indonesia (2,0,0,2,1,0,2) thailand (1,1,3,3,2,3,2) lngdp 28.36*** (4.27) −9.46*** (2.52) 10.04*** (1.25) lngdp2 −1.54*** (0.242) 0.61*** (0.15) −0.76*** (0.10) lneny 0.06 (0.22) 1.30*** (0.28) 4.29*** (1.03) lnaeny −0.15*** (0.04) 0.04 (0.06) −0.04 (0.52) lnfdi −0.03* (0.01) 0.02 (0.03) 0.09 (0.08) lnto −0.57*** (0.14) −0.29** (0.13) −1.67** (0.67) constant −127.62*** (18.43) 29.84*** (9.72) −53.12*** (6.44) dependent variable is∆lnco2.* ,**,*** indicate significance at 10%, 5%, and 1% significant level, respectively. numbers in brackets represent standard error. the ardl estimation outcomes were generated by using sic ridzuan, et al.: the impact of energy consumption based on fossil fuel and hydroelectricity generation towards pollution in malaysia, indonesia and thailand international journal of energy economics and policy | vol 10 • issue 1 • 2020224 magnitude for this variable seems greater for thailand. its aeny, on the other hand, displayed a negative impact upon pollution, but insignificant at all levels. therefore, alternative energy has failed in becoming a key solution to decrease pollution. in addition, the findings of fdi and to for thailand are similar to those obtained for indonesia, given that only to displayed a significantly negative correlation with pollution or environmental quality. along with other asean nations (in this case, malaysia and thailand), trade liberalization has helped the country to be more particular with their export and import activities. furthermore, in the attempt to support sustainable development goal (sdg) initiated by united nation, thailand and other asean countries have begun implementing several effective strategies, such as imposing higher tax towards high pollution-intensive products and providing subsidies to its local producers who adopt cleaner technology. thailand also may have comparative advantage in cleaner intensive product that promotes environmental quality. the outcomes further revealed that 1% increment in to leads to 1.67% reduction in environmental degradation. 4.5. the short-run elasticities the outcomes of short elasticities are as tabulated in table 7. narayan and narayan (2010) suggested that a different method is required to determine if the tested countries have managed to reduce their co2 emissions over time with increment in their economic growth by comparing short-run with long-run elasticities. if the result shows smaller long-run income elasticity than that of short-run over a period of time, income is assumed to have contributed to less carbon emission. this appears to be a response to issues related to collinearity or multicollinearity that may exist between gdp and gdp2. based on the significance at the same lag for gdp and gdp2, it was discovered that in the short-run, the development in malaysia resembled a u-shaped ekc, thus suggesting that development has results in greater environmental degradation. similar scenario is reflected in indonesia. nevertheless, it was found that only thailand validated the presence of ekc hypothesis and its size of magnitude seemed relatively greater in short-run, when compared to long-run. thus, between the three asean countries analysed in this paper, it can be concluded that only thailand has managed to achieve sustainable economic development both for short-run and long-run, while sustainable economic development is only achieved by malaysia in the long-run. the size of magnitude for aeny for malaysia seemed relatively greater in the short-run with a coefficient value of 0.19. this implies that the generation of hydroelectricity energy in malaysia could effectively reduce carbon emission. apart from aeny, to (at lag 1) in malaysia has also reduced the release of carbon emission. as for the case in indonesia, increment in eny has the ability to reduce carbon emission, while increased participation of indonesia in international trade (to) leads to worsening of air quality with a positive sign of to. on the other hand, as for thailand, higher eny improves its environmental quality through lower release of carbon emissions, which is similar to the outcomes derived for indonesia. nevertheless, aeny displayed a positive sign, which means that the use of hydroelectricity generation in short-run could cause greater pollution. on top of that, to seemed to exhibit mixed expected signs on varied lags. as depicted in table 7, the estimated lagged ect in ardl regression for the three studied nations appear to be negative and statistically significant. based on the ect value, the highest speed of adjustment was obtained by indonesia (−1.39), followed by malaysia (−1.29), and thailand (−0.95). as for indonesia and thailand, given their ect value >−1, narayan and smyth (2006) suggested that instead of monotonically converging to the equilibrium path directly, the error correction process for these two countries fluctuates around the long-run value in a dampening manner. nonetheless, once this process is complete, convergence to equilibrium path becomes rapid. for instance, more than 139%, 129%, and 95% of adjustments were completed within less than a year for both malaysia and indonesia, whereas a year for thailand due to short-run adjustment, which is considered as very rapid. table 7: estimation of short-run restricted error correction model variables malaysia indonesia thailand ∆lnco2 ∆lnco2-1 0.77*** (0.14) ∆lnco2-2 ∆lngdp 18.52 (12.41) −13.23*** (4.03) 26.98** (8.83) ∆lngdp−1 −31.76** (13.41) ∆lngdp−2 ∆lngdp2 −0.96 (0.70) 0.86*** (0.25) −1.68*** (0.53) ∆lngdp2−1 1.83** (0.76) −0.06* (0.03) ∆lngdp2−2 0.11*** (0.02) ∆lneny 0.07 (0.28) 0.13 (0.36) 1.91*** (0.40) ∆lneny−1 −0.94** (0.06) 0.04 (0.23) ∆lneny−2 −1.42*** (0.29) ∆lnaeny −0.19*** (0.06) −0.09 (0.06) 0.14** (0.04) ∆lnaeny−1 0.11*** (0.03) ∆lnaeny−2 ∆lnfdi −0.02 (0.01) 0.04 (0.04) 0.03* (0.02) ∆lnfdi−1 −0.01 (0.01) ∆lnfdi-2 −0.03 (0.02) ∆lnto −0.28 (0.25) 0.27** (0.10) −0.62*** (0.16) ∆lnto-1 0.56** (0.26) 0.21** (0.09) 0.41** (0.16) ∆lnto-2 ect −1.29*** (0.23) −1.39*** (0.00) −0.95*** (0.29) dependent variable is∆lnco2. * ,**, and *** indicate significance at 10%, 5%, and 1% significant level, respectively ridzuan, et al.: the impact of energy consumption based on fossil fuel and hydroelectricity generation towards pollution in malaysia, indonesia and thailand international journal of energy economics and policy | vol 10 • issue 1 • 2020 225 5. conclusion and policy recommendations this paper has bridged the gap found in the literature pertaining to environmental economics studies within the context of selected asean-3 nations regarding correlations between carbon emissions, economics growth, energy based on fossil fuel, alternative energy based on hydroelectricity generation, fdis, and to so as to generate a comparison between the emerging economies of malaysia, indonesia, and thailand on the said terms. the study, hence, used annual time series data over the period of 1980 until 2014. the following conclusions are drawn from this exercise: • all the models have passed the diagnostic test settings, i.e., normality test, stability tests, heterogeneity test, and stability tests, thus producing reliable outcomes. • overall, evidence for the existence of ekc hypothesis has been established for both the cases of malaysia and thailand. relatively, economic growth in indonesia appears to cause higher influence on carbon emissions and its policymakers should, therefore, pay more attention on this situation. • the fossil fuel type of energy harms the environmental quality in indonesia and thailand, while insignificant impact of energy was discovered upon malaysian environment. • hydroelectricity generation has successfully improved the environmental quality in malaysia, but it has failed to influence carbon emissions level in indonesia and thailand. • higher fdi inflows may aid in decreasing issues related to environmental degradation in malaysia, thus validating the heh. • embracing to has successfully improved environmental quality for all the studied asean-3 countries. overall, the asean-3 nations should devise effective strategies so as to ascertain the quality of sustainable environmental in their region. the strategies may consist the following: • first, it is highly suggested that asean-3 countries should initiate an economic model based on sustainable development goals. for example, malaysia has made a commitment to reduce carbon emissions by 40% by 2020 and actively promoting green economy should be noted as a valuable lesson. besides, intensifying green economy initiatives could allow decoupling economic growth and carbon emissions. however, proper implementation of these strategies is necessary so as to ensure the success of such initiatives. for example, the malaysia government has introduced the green technology master plan 2017-2030 in the attempt to slash carbon emissions from the present eight metric tonnes (mt) per capita to six mt per capita in 2030. based on the outcomes of this paper, malaysia and thailand could share their individual experiences on sustainable development practices to their neighbouring country, indonesia. • generally, the policymakers of asean-3 countries should develop a concreate policy framework that promotes longterm value to reduce ghg emissions, aside from constantly supporting the progress of new technologies that lead to less carbon-intensive economy. • it is suggested for indonesia and thailand to increase the volume of investment by injecting more capital into projects that utilise alternative energy, as practiced in malaysia. this strategy could cut the consumption of fossil fuels and facilitate the role of alternative energy, such as hydroelectricity, as highlighted in this research paper. • policymakers should impose stringent environmental laws, particularly regarding energy-intensive and polluted foreign industries. the design of new environmental policies that improve regularity framework and enforcement activity can also help to mitigate environmental damages, thus leading towards sustainability in environmental quality among these nations. • additionally, given the positive impact of trade towards environmental quality among the studied nations, it is advisable for these countries to maintain trade-related actions and strategies so as to heighten environmental protection, which is crucial to successfully lift environmental pressure induced by trade, in precise. acknowledgement this paper was initially presented at the international conference on innovative applied energy (iape’19) at the oxford city 1415 march 2019, oxford, united kingdom. the source of fund is provided by irmi, uitm, under the code grant of 600 irmi/ dana 5/3/got (003/2018). we also wish to extend our gratitude to inqka uitm for financing the publication fees of this paper. references acaravci, a., ozturk, i. (2010), on the relationship between energy consumption, co2 emissions and economic growth in europe. energy, 35(12), 5412-5420. acharyya, j. (2009), fdi, growth and the environment: evidence from india on co2 emission during the last two decades. journal economy development, 34(1), 43-59. adb. (2016), asian development bank 2016 sustainability report: investing for an asia and the pacific free of poverty. available from: https://www.adb.org/sites/default/files/institutionaldocument/183043/sr2016.pdf. [last accessed on 2017 dec 20]. adebola, s.s., al-mulali, u., ozturk, i. (2017), validating the environmental kuznets curve hypothesis in india and china: the role of hydroelectricity consumption. renewable and sustainable energy reviews, 80, 1578-1587. adu, d.t., denkyirah, e.k. (2018), economic growth and environmental pollution in west africa: testing the environmental kuznets curve hypothesis. kasetsart journal of social sciences, 1-8. ahmad, s., kadir, z.a., shafie, s. (2011), current perspective of the renewable energy development in malaysia. renewable and sustainable energy reviews, 15(2), 897-904. al-mulali, u. (2012), factors affecting co2 emission in the middle east: a panel data analysis. energy, 44, 564-569. al-mulali, u., che-sab, c.n. (2012), the impact of energy consumption and co2 emission on the economic growth and financial development in the sub-saharan african countries. energy, 39, 180-186. al-mulali, u., ozturk, i. (2015), the effect of energy consumption, urbanization, trade openness, industrial output, and the political stability on the environmental degradation in the mena (middle east and north african) region. energy, 84, 382-389. al-mulali, u., ozturk, i., solarin, s.a. (2016), investigating the environmental kuznets curve hypothesis in seven regions: the role ridzuan, et al.: the impact of energy consumption based on fossil fuel and hydroelectricity generation towards pollution in malaysia, indonesia and thailand international journal of energy economics and policy | vol 10 • issue 1 • 2020226 of renewable energy. ecological indicators, 67, 267-282. al-mulali, u., saboori, b., ozturk, i. (2015), investigating the environmental kuznets curve hypothesis in vietnam. energy policy, 76, 123-131. arouri, m.e.h., ben youssef, a., m’henni, h., rault, c. (2012), energy consumption, economic growth and co2 emissions in middle east and north african countries. energy policy, 45, 342-349. baek, j. (2015), a panel cointegration analysis of co2 emissions, nuclear energy and income in major nuclear generating countries. applied energy, 145, 133-138. baek, j. (2015), environmental kuznets curve for co2 emissions: the case of arctic countries. energy economics, 50, 13-17. baek, j., cho, y., koo, w.w. (2009), the environmental consequences of globalization: a country specific time-series analysis. ecological economy, 68, 2255-2264. begum, r.a., sohag, k., abdullah, s.m.s., jaafar, m. (2015), co2 emissions, energy consumption, economic and population growth in malaysia. renewable and sustainable energy reviews, 41, 594-601. bella, g., massidda, c., mattana, p. (2014), the relationship among co2 emissions, electricity power consumption and gdp in oecd countries. journal of policy modeling, 36(6), 970-985. bhanu, p., meenu, g., madhoolika, a. (2018), greenhouse gas emissions from coal mining activities and their possible mitigation strategies. in: muthu, s.s., editor. environmental carbon footprints. industrial case studies. oxford: butterworth-heinemann. chandran, g.v.g., tang, c.f. (2013), the dynamic links between co2 emissions, economic growth and coal consumption in china and india. applied energy, 104, 310-318. cho, c.h., chu, y.p., yang, h.y. (2014), an environment kuznets curve for ghg emissions: a panel cointegration analysis. energy sources part b: economic planning policy, 9, 120-129. copeland, b.r., taylor, m.s. (2004), trade, growth and the environment. journal of economic literature, 42(1), 771. danish, zhang, b., wang, b., wang, z. (2017), role of renewable energy and non-renewable energy consumption on ekc: evidence from pakistan. journal of cleaner production, 156, 855-864. den. (2016), indonesia energy outlook 2016. dewan energi nasional (den). available from: https://www.esdm.go.id/assets/media/ content/outlook_energi_indonesia_2016_opt.pdf. [last accessed on 2017 feb 02]. dong, k., sun, r., hochman, g., zeng, x., li, h., jiang, h. (2017), impact of natural gas consumption on co2 emissions: panel data evidence from china’s provinces. journal of cleaner production, 162, 400-410. egat. (2016), sustainability report 2016: electricity generating authority of thailand. nonthaburi: egat. available from: https:// www.egat.co.th/en/images/sustainable-dev/csr-report/sustainabilityreport-2016-egat-en.pdf. [last accessed on 2018 feb 01]. energy information administration. (2014), us energy information administration, database. washington, dc: energy information administration. available from: https://www.eia.gov/outlooks/aeo. [last accessed on 2018 jan 03]. enríquez-de-salamanca, á., díaz-sierra, r., martín-aranda, r.m., santos, m.j. (2017), environmental impacts of climate change adaptation. environmental impact assessment review, 64, 87-96. farhani, s., chaibi, a., rault, c. (2014), co2 emissions, output, energy consumption, and trade in tunisia. economic modelling, 38, 426-434. halicioglu, f. (2009), an econometric study of co2 emissions, energy consumption, income and foreign trade in turkey. energy policy, 37, 1156-1164. hossain, m.s. (2011), panel estimation for co2 emissions, energy consumption, economic growth, trade openness and urbanization of newly industrialized countries. energy policy, 39, 6991-6999. iea. (2015), world energy outlook special report: southeast asia energy outlook 2015. international energy agency. https://www. iea.org/publications/freepublications/publication/weo2015_ southeastasia.pdf. [last accessed on: 1 january 2018). iha. (2018), hydropower status report 2017. international hydropower association. available from: https://www.hydropower.org/sites/ default/files/publications-docs/2017%20hydropower%20status%20 report.pdf. [last accessed on 2018 jan 03]. ipcc. (2013), climate change 2013: the physical science basis. contribution of working group i to the fifth assessment report of the intergovernmental panel on climate change. intergovernmental panel on climate change, working group i contribution to the ipcc 5th assessment report. cambridge: cambridge university press. jayanthakumaran, k., verma, r., liu, y. (2012), co2 emissions, energy consumption, trade and income: a comparative analysis of china and india. energy policy, 42, 450-460. jebli, m.b., youssef, s.b., ozturk, i. (2016), testing environmental kuznets curve hypothesis: the role of renewable and non-renewable energy consumption and trade in oecd countries. ecological indicators, 60, 824-831. jensen, n.m. (2006), nation-states and the multinational corporation: a political economy of foreign direct investment. princeton: princeton university press. available from: https://www.jstor.org/ stable/j.ctt7sx07. [last accessed on 2018 jan 21]. kalabokidis, k., palaiologou, p., gerasopoulos, e., giannakopoulos, c., kostopoulou, e., zerefos, c. (2015), effect of climate change projections on forest fire behavior and values-at-risk in southwestern greece. forests, 6(6), 2214-2240. kasman, a., duman, y.s. (2015), co2 emissions, economic growth, energy consumption, trade and urbanization in new eu member and candidate countries: a panel data analysis. economic modelling, 44, 97-103. kharbach, m., chfadi, t. (2017), co2 emissions in moroccan road transport sector: divisia, cointegration, and ekc analyses. sustainable cities and society, 35, 396-401. kivyiro, p., arminen, h. (2014), carbon dioxide emissions, energy consumption, economic growth, and foreign direct investment: causality analysis for sub-saharan africa. energy, 74, 595-606. kohler, m. (2013), co2 emissions, energy consumption, income and foreign trade: a south african perspective. energy policy, 63, 1042-1050. koutroumanidis, t., ioannou, k., arabatzis, g. (2009), predicting fuelwood prices in greece with the use of arima models, artificial neural networks and a hybrid arima-ann model. energy policy, 37(9), 3627-3634. lau, l.s., choong, c.k., eng, y.k. (2014), investigation of the environmental kuznets curve for carbon emissions in malaysia: do foreign direct investment and trade matter? energy policy, 68, 490-497. lean, h.h., smyth, r. (2010), co2 emissions, electricity consumption and output in asean. applied energy, 87, 1858-1864. melikoglu, m. (2017), pumped hydroelectric energy storage: analysing global development and assessing potential applications in turkey based on vision 2023 hydroelectricity wind and solar energy targets. renewable and sustainable energy reviews, 72(1), 146-153. narayan, p.k., narayan, s. (2010), carbon dioxide emissions and economic growth: panel data evidence from developing countries. energy policy, 38, 661-666. narayan, p.k., smyth, r. (2006), what determines migration flows from low-income to high income countries? an empirical investigation of fiji u.s. migration 1972-2001. contemporary economic policy, 24(2), 332-342. ozcan, b. (2013), the nexus between carbon emissions, energy consumption and economic growth in middle east countries: a panel data analysis. energy policy, 62, 1138-1147. ridzuan, et al.: the impact of energy consumption based on fossil fuel and hydroelectricity generation towards pollution in malaysia, indonesia and thailand international journal of energy economics and policy | vol 10 • issue 1 • 2020 227 ozturk, i., al-mulali, u. (2015), investigating the validity of the environmental kuznets curve hypothesis in cambodia. ecological indicators, 57, 324-330. pal, d., mitra, s.k. (2017), the environmental kuznets curve for carbon dioxide in india and china: growth and pollution at crossroad. journal of policy modeling, 39(2), 371-385. pao, h.t., fu, h.c., tseng, c.l. (2012), forecasting of co2 emissions, energy consumption and economic growth in china using an improved grey model. energy, 40(1), 400-409. pao, h.t., tsai, c.m. (2010), co2 emissions, energy consumption and economic growth in bric countries. energy policy, 38(12), 7850-7860. pao, h.t., tsai, c.m. (2011), modeling and forecasting the co2 emissions, energy consumption, and economic growth in brazil. energy, 36(5), 2450-2458. pao, h.t., tsai, c.m. (2011), multivariate granger causality between co2 emissions, energy consumption, fdi (foreign direct investment) and gdp (gross domestic product): evidence from a panel of bric (brazil, russian federation, india, and china) countries. energy, 36(1), 685-693. pesaran, m.h., shin, y., smith, r.j. (2001), bounds testing approaches to the analysis of level relationships. journal of applied econometric, 16, 289-326. ren21. (2017), renewables 2017: global status report. available from: http://www.ren21.net/wp-content/uploads/2017/06/17-8399_ gsr_2017_full_report_0621_opt.pdf. [last accessed on 2018 feb 15]. saboori, b., al-mulali, u., bin baba, m., mohammed, a.h. (2014), oilinduced environmental kuznets curve in organization of petroleum exporting countries (opec). international journal of green energy, 13(4), 408-416. saboori, b., sulaiman, j. (2013a), co2 emissions, energy consumption and economic growth in association of southeast asian nations (asean) countries: a cointegration approach. energy, 55, 813-822. saboori, b., sulaiman, j. (2013b), environmental degradation, economic growth and energy consumption: evidence of the environmental kuznets curve in malaysia. energy policy, 60, 892-905. saboori, b., sulaiman, j., mohd, s. (2012), economic growth and co2 emissions in malaysia: a cointegration analysis of the environmental kuznets curve. energy policy, 51, 184-191. shahbaz, m., kumar, t.a., nasir, m. (2013a), the effects of financial development, economic growth, coal consumption and trade openness on co2 emissions in south africa. energy policy, 61, 1452-1459. shahbaz, m., solarin, s.a., mahmood, h., arouri, m. (2013b), does financial development reduce co2 emissions in malaysian economy? a time series analysis. economic modelling, 35, 145-152. shahbaz, m., solarin, s.a., ozturk, i. (2016), environmental kuznets curve hypothesis and the role of globalization in selected african countries. ecological indicators, 67, 623-636. shahbaz, m., solarin, s.a., sbia, r., bibi, s. (2015), does energy intensity contribute to co2 emissions? a trivariate analysis in selected african countries. ecological indicator, 50, 215-224. sinha, a., shahbaz, m. (2018), estimation of environmental kuznets curve for co2 emission: role of renewable energy generation in india. renewable energy, 119, 703-711. st. (2016), malaysia energy statistics handbook. putrajaya: suruhanjaya tenaga (st). available form: http://www.st.gov.my/index.php/en/allpublications/item/735-malaysia-energy-statistics-handbook-2016. [lasr accessed on 2018 mar 01]. stern, d.i. (2011), the role of energy in economic growth. in: costanza, r., limburg, k., kubiszewski, i., editors. ecological economics reviews. vol. 1219. new york: john wiley and sons. p26-51. stretesky, p.b., lynch, m.j. (2008), a cross-national study of the association between per capita carbon dioxide emissions and exports to the united states. journal of social science resources, 38, 239-250. tampakis, s., tsantopoulos, g., arabatzis, g., rerras, i. (2013), citizens’ views on various forms of energy and their contribution to the environment. renewable and sustainable energy reviews, 20, 473-482. tang, c.f., tan, b.w. (2015), the impact of energy consumption, income and foreign direct investment on carbon dioxide emissions in vietnam. energy, 79, 447-454. tiwari, a.k., shahbaz, m., hye, m.q.a. (2013), the environmental kuznets curve and the role of coal consumption in india: cointegration and causality analysis in an open economy. renewable and sustainable energy reviews, 18, 519-527. wang, s.s., zhou, d.q., zhou, p., wang, q.w. (2011), co2 emissions, energy consumption and economic growth in china: a panel data analysis. energy policy, 39(9), 4870-4875. wmo. (2016), the state of greenhouse gases in the atmosphere based on global observations through 2016. world meteorological organization greenhouse gas bulletin 2017, no. 12. available from: https://www.reliefweb.int/report/world/wmo-greenhousegas-bulletin-state-greenhouse-gases-atmosphere-based-globalobservations. [last accessed on 2017 dec 12]. world development indicators. (2017), world development indicators. washington, dc: the world bank. available form: http:// www.databank.worldbank.org/data/reports.aspx?source=worlddevelopment-indicators. [last accessed on 2018 jan 07]. yi, s., heki, k., qian, a. (2017), acceleration in the global mean sea level rise: 2005-2015. geophysical research letter, 44(23), 11905-11913. yin, j., zheng, m., chen, j. (2015), the effects of environmental regulation and technical progress on co2 kuznets curve: an evidence from china. energy policy, 77, 97-108. zhang, x., li, h.y., deng, z.d., ringler, c., gao, y., hejazi, m.i., leung, l.r. (2017), impacts of climate change, policy and waterenergy-food nexus on hydropower development. renewable energy, 116, 827-834. international journal of energy economics and policy vol. 5, no. 1, 2015, pp.360-373 issn: 2146-4553 www.econjournals.com 360 urban energy consumption in a city of indonesia: general overview iwan sukarno department of architecture and civil engineering, toyohashi university of technology, japan. email: iwan_sukarno81@yahoo.com hiroshi matsumoto department of architecture and civil engineering, toyohashi university of technology, japan. email: matsu@ace.tut.ac.jp lusi susanti industrial engineering department, andalas university, padang, indonesia. email: susantilusi@gmail.com ryushi kimura department of environmental civil engineering and architecture, kochi national college of technology, japan. email: kimura@ce.kochi-ct.ac.jp abstract: this paper aims to investigate the energy consumption pattern in four sectors of padang, indonesia: residential, commercial, industrial and transportation sectors, under different urban population scenarios using a cohort model and statistical data. the analysis shows that the energy consumed in the residential sector has the major share in the total energy consumption in padang. details on energy consumption and the main driving forces in the four sectors have been presented. decreasing urban energy consumption could be achieved by increasing efficiency of home appliances, promoting electricity saving behavior, increasing of public awareness for saving energy, and applying energy efficiency labeling for home appliances. keywords: urban energy consumption; cohort model; residential; transportation; commercial and industrial sectors jel classifications: q40; n75 1. introduction since the last decades, the world has been facing global warming and energy crisis issues. with the challenge of environmental issue, the importance of reducing energy consumption and fuel emissions has been widely recognized. data under the international energy outlook (ieo) 2011 shows that the world energy consumption of fossil fuels will increase from 383 billiongj in 1990, to 812 billion gj by 2035 (eia, 2011). the most significant increase of energy consumption and fuel emission are taking place in cities (eia, 2011; iges, 2004; fong et al., 2008). with rapidly expanding populations and material affluences, a comprehensive overview of the overall energy use in cities is believed to be playing an important role in combating these issues (fong et al., 2008). urban energy consumption in a city of indonesia: general overview 361 in relation to energy consumption in the end user sectors, ieo 2011 predicts steady energy consumption growth from 2010 to 2035 (eia, 2011). moreover, the united nations (un) estimates that 60% of the world’s population now lives in an urban area and that percentage is expected to continue to rise (un, 2008).the ieo prediction states that the world residential energy use will increase by 1.1% per year, from 54 billion gj in 2008 to 72 billion gj in 2035 (eia, 2011). indonesia as one of the fastestgrowing and developing countries in asia with a population of more than 241 million in 2010,is no doubt struggling with energy sustainability for the citizens and at the same time combating the environmental issues such as climate change and reducing co2 emissions. with an average growth 2.6% per year, the indonesian population can be predicted to reach over 300 million by the year 2025. on the other hand, indonesian economic development is increasing in all sectors such as industrial and commercial sectors as well as household and transportation sectors. the large population and recent economic growth has resulted in an improvement in the overall living standard in indonesia. the increase of level in economic situation has led to an increase of demand on energy consumption. one way of looking at the urban energy consumption, is considering the energy consumption trends of the end user. to limit the scope of discussion, padang, the capital city of west sumatera province, was selected for the case study. padang is a typical medium sized city that faces rapid economic growth after a high magnitude earthquake devastating the city in 2009. after the recovery periodelapsed, the local government began to maintain establishment in all sectors of social economic, accelerated development of housing, health and educational facilities. to support the recovery and development process, a comprehensive study of urban energy consumption should be completed for this city. this paper aims to investigate the urban energy consumption trends in four sectors: residential, commercial, industrial and transportation sectors, under different urban population scenarios and key indicators of urban energy consumption. this study can be integrated with long-term urban planning toward a sustainable development. 2. methodology 2.1 demography of padang padang, capital of west sumatera province, covers an area of about 694.96 km2 and has a population of about 846,731 (padang in figure, 2011). padang consists of 11 districts, bungus, east padang, koto tangah, kuranji, lubuk begalung, lubuk kilangan, nanggalo, north padang, pauh, south padang, and west padang (table 1 and figure 1). as the center of the provincial government, padang became the region with the highest population density in west sumatra province. in addition, office activities, business and education are also concentrated on this area. table 1. details of the case study city aspects information land area 694.96 (km2) number of sub districts 11 population (2011) 846,731 (person) population density 1218.4 ( person/km2) gdp ( 2011) 12,792.18 million rupiah gdp per capita ( 2011) 32.50 billion rupiah sources : padang in figure, 2011 international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.360-373 362 figure 1. case study (padang, indonesia) 2.2 cohort model system dynamic modelling is one approach that can help urban planners to meet the challenges of decision-making and policy formulation for the system development (kumar and sonar, 2008). the value of a model arises by improving our understanding of obscure behavior characteristics more effectively than could be done by observing the real system (hannon abd ruth, 2001). with system dynamics, the real world system is easy to understand by mimicking real conditions using computer programs.when a model is simulated with a computer, each element of the model is specified by the initial conditions and the computer works out the systems responses according to the specified relation among the elements. computer modelling becomes “dynamic” not only when feedback processes among system components are captured through time, but also when model development is based on the dynamic exchange of data and information among a group of model developers and users (hannon and ruth, 2001). under the book entitled “dynamic modelling”, hannon et al. presented the principle of dynamic modelling using stella software. a) define the problem and the goals of the model b) designate the state variable c) select the control variable, the flow controls into and out of state variable d) select the parameters for the control variables e) examine the resulting model for possible violations of physical, economic, law, etc f) choose time horizons intended to examine dynamic behaviors of the model g) run the model h) vary the parameter to their reasonable extremes and see if the results in the graph still make sense i) compare the result with the experimental data j) revise the parameter or model to reflect a greater complexity and to meet exceptions to the experimental results. as mentioned above, one fundamental key to understanding the energy issues in the urban sector is the population. the population increases in urban areas will have a particularly significant impact on energy consumption in an urban structure which is related to the sustainable issues regarding energy security and climate change. urban energy consumption in a city of indonesia: general overview 363 generally, population is estimated by birth, death, and migration (immigration and emigration). this identity can be written by: population = current population + birth –death + (immigration – emigration) (1) the cohort model is divided into a female and male population and each population is classified by age: 0-14 years, 15-44 years, 45-64 years and over 65 years. this classification is used to provide complete information about the estimated population according to age levels. 2.3 residential sector residential energy consumption is strongly related to the urban population. as mentioned above, 60% of the world’s population live in an urban area and that percentage is expected to continue rising. an increase of housing market will promote an increase of energy consumption. in this respect, the number of population, the number of households, family size, and other related information are calculated from the population census of padang from year 2000 to 2011. population is projected by a cohort model as mentioned in the previous section. characteristics of household appliances obtained through analysis of questionnaires distributed to samples reside in 11 sub-districts of padang. 210 households were selected randomly and participated in this survey. the size of the samples foreach district was chosen according to the size of district population. the survey information was mainly about household characteristics and structures, household appliances, energy consumption related daily life activities such asfor lighting, cooking and cooling. calculation of energy consumption in the residential sector focused on the three types of energy sources: electricity, liquefied petroleum gas (lpg) and kerosene. energy consumption patterns of daily life were also observed. 2.4 transportation sector energy consumption of the transportation sector was calculated based on the number of transportation vehicles, such as public transport (citybus and microbus) and private vehicles (motorcycles and cars). the travel distance for each type of vehicle, and fuel consumption per kilometer distance were also considered in the calculation. energy consumption was calculated based on vehicle mileages multiplied by fuel consumption of each vehicle, as shown in equation (2). = ( × × ) + ( × × ) (2) where: et = total energy consumption inthe transportation sector tdpb = total travel distance for public transportation tdpr = total travel distance for private transportation npb = number of public transportation vehicles npr = number of private vehicles fcpr = fuel consumption per kilometer for private transportation fc pb = fuel consumption per kilometer for public transportation 2.5 industrial and commercial sectors energy consumption in industrial and commercial sectors is estimated from historical data considering population and economic growth. industrial and commercial sectors are the sectors that contribute significantly to the gdp of padang. from 2005 to 2010, the commercial sector contributed 22.5 % while the industrial sector accounted for only 20 % of the total gdp. the estimation of energy consumption in the industrial and commercial sectors is mainly focused on the electricity consumption because this type of energy source gave more than 65% of the energy share compared with the other energy sources. 3. results and analysis 3.1 cohort model of the padang population a cohort model was used to estimate energy consumption based on population projection. it provides an overview of the development of the padangpopulation by age group adopted from a scenario projection of west sumatera for 2025. the population projection for the study area can be seen in figure. 2 population is projected to continue rising, despite several attempts taken to curb the population growth. in accordance with the international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.360-373 364 mdg scenario, the fertility rate is targeted at 2.11 in 2025. figure 3 shows a comparison between the businesses as usual (bau) and population scenario dealing with fertility rate. figure 2. estimated population by the cohort method figure 3. estimated population by the cohort method under population scenarios under tfr scenarios, when fertility rate is setto 2.11 in 2025, the total population is expected to successfully suppress to 7% per year. since padang demography is dominated by younger ages (figure 4.), to realize the target of tfr 2.11, aseriouseffortmust bemade by the government to educate this productive age group. the followings are several programs designed by the government to decrease the fertility rate: a. decrease birth rate through a birth control program since 1970, this program has been announced by the government, as one of the efforts to reduce the high rate of population growth in indonesia. the aims are to promote awareness to a new family for the birth plan, realigned to their economic level and readiness. since the program started, the birth rates (tfr) significantly decreased from 5.6 in 1970 to 2.8 in 2000. b. delaying the age of marriage it is well documented that early pregnancy usually increases both maternal and infant mortality. in developing countries such as indonesia, early childbirth occurs within the context of early marriage. delaying the age of marriage for women to their mid twenties not only results in a significant drop inthe fertility rate, but also will most likely prevent a surprisingly large portion of maternal and infant mortalities. c. increase the education level urban energy consumption in a city of indonesia: general overview 365 one of the most effective ways to lower population growth and reduce poverty is to provide adequate education for both girls and boys. countries in which more children are enrolled in school—even at the primary level—tend to have strikingly lower fertility rates. figure 4. population structure of padang 3.2 residential sector according to the projection result, it can be seen that household numbers of padang gradually increased following the population trend. in other words, this condition will provide a significant influence on residential energy consumption. also, direct and indirect lifestyle aspects are factors that influence the residential energy consumption pattern (fong, 2008; bill and danni, 2009; pereira and assis, 2013). electricity, lpg and kerosene are the main sources of residential energy consumption. padang statistical data (2011) report that from 2000 to 2011, electricity was the biggest share of energy sources. electricity consumption spread to the residential sector (92%), followed by commercial sectors (5.32%), public sectors (1.92%), the government (1.28%), and only 0.04% in the industrial sector (figure 5). figure 5. household electricity consumption figure 6 shows the share of electricity for different end users in padang. cooking is the most energy consuming activity with a share of 53%, followed by a 17% share for cooling devices, 10% for entertainment devices, 5% for lighting and 16% for other devices. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.360-373 366 in respect to the household energy consumption, wijaya and tezuka carried out a survey of household electricity consumption based on home appliances in the bandung and yogyakarta cities of indonesia (wijaya and tezuka, 2011). the questionnaire survey method was used in this study, which involved 100 respondents in each city. among the main findings of this study was, that a majority of electricity consumption came from cooking and cooling device. figure 7 shows a comparison of electricity consumption by household activities between padang and other cities in indonesia. figure 6. electricity consumption figure 7. comparison of electricity consumption another activity that contributes to electricity consumption is entertainment. fig. 7 shows that the leisure activities in yogyakarta and bandung cites contributed to 21% and 25% of energy consumption. characteristics of households such as family lifestyle and family pattern respectively affect the high percentageof electricity consumption. lpg and kerosene, the main fuel are used by most indonesian families. according to the handbook of energy and economic statistics of indonesia 2011, the average share of energy consumption of kerosene in the household sector from the years 2000 to 2010 was about 57%, of electricity about 30%, of lpg about 13%, and only 0.1% of natural gas. based on the survey results, 37.6% of households consumed lpg as the main fuel for cooking, however 36.7% of households still used kerosene and 23.8% of householdsused both of lpg and kerosene, with only 1.9% of households still using wood as the primary fuel for cooking. the majority of households used 12 kg tube lpg, and the average household spent one tube per month. padang statistical data also showed that from 2003 to 2009 there was an increase in households that using lpg, going from 36,922 households in 2003 to 47,230 households in 2009 (padang in figure 2011). as a whole, according to data from energy urban energy consumption in a city of indonesia: general overview 367 statistics of indonesia, lpg consumption increased from 696,000 tons in 2000 to 3,577,000 tons in 2010. 3.3 transportation sector as mentioned above, energy consumption in the transportation sector focused on two parts, private transportation and public transportation. the number of vehicles per year, travel distances of public transportation, fuel consumption per kilometer of travel distances and other supporting data were derived from padang statistical data and the transportation department of padang. figures 8 and 9 illustrate the increases in the number of public and private vehicles in padang.however, the main obstacle of evaluating transportation energy consumption is the lack of available data for each public transportation type. therefore, the authors placed more emphasis on two kinds of public transportation commonly used in padang, the city bus and microbus in public transportation, and the motorcycle and a car with 4-7 seats in private transportation. the ratio of motorcycles to people is 1:4, which means that every 4th person has one motorcycle. otherwise, for public transportation, the ratio is 1:330, which means that there is one public vehicle for every 330 persons (indonesia bank, 2013). figure 8. number of public vehicles from 1994 to 2010 figure 9. number of private vehicles from 2001 to 2010 as illustrated in figure 10, withan increase in population and demand for public transportation growing up 2% p.a., energy consumption is predicted to riseto 20,000 tj in 2050. micro buses contributed more than 90% to total energy consumption compared to other forms of public transportation. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.360-373 368 figure 10. energy consumption projection of public transportation in terms of private vehicles, because of the availability of data, the calculation of energy consumption builds from average fuel consumption per day for motorcycles and cars (esdm, 2012). figure. 11 shows the increase in energy consumption of private vehicles. it can be seen that if every 2.75 people have one motorcycle and every 50 persons have a car, energy consumption is predicted to growth 2% per year. figure 11. energy consumption projection of private transportation the motorcycle is the biggest contributor of fuel consumption compared to passenger cars. figure 12 provides an overview of vehicle ownership in padang. the simplicity of having motorcycles, absence of vehicle restriction policy, and public transportation management is not a good reasonfor society to use motorcyclesrather than public transportation. this result is closely related to the increasing air pollution. according to the environment impact control (bapedalda, 2012) report 70% of air pollution was caused by motor vehicles, 20% by industrial activities, and the remaining 10% from garbage and cigarettes. historical projection historical projection urban energy consumption in a city of indonesia: general overview 369 figure 12. households vehicle generally, the high number of vehicles in indonesia is mainly caused by: a. the ease of obtaining motorcycles indonesia is one of the countries with the highest density of motorcycles in the world. according to the indonesian motorcycle association, production of motorcycles reached 15 million per year and 86% of the products are used in the domestic market. on the other hand, on the consumer side, many conveniences were provided by distributors of motorcycles as light credit, a small down payment. this condition encourages people to purchase a motorcycle. b. high flexibility motorcycle is a transportation vehicle which has a high flexibility compared to cars. generally, indonesia has many roads that can only be passed by motorcycle. moreover, in the cities context of the high mobility and traffic jams are a problem, and motorcycles are practical and efficient vehicles. c. the impact of inadequate public transport according to indonesian transportation department, the ratio of private vehicles to public vehicles is 98% : 2%. in padang case, the number of public transportations with 25 seats was decreased 4% per years since 2007. moreover, people prefer using private vehicles rather than public transportation. on the other hand, the growth rate of roads was only 0.5% per year. this condition provides several problemssuch as traffic jam, air pollution, and also the increasing of fuel consumption 3.4 commercial and industrial sector energy consumption by the commercial sector is dominated by electricity usage. figure. 13 shows the share of commercial energy consumption by each energy source type. statistical data showed that electricity was consumed more than 69%, fuel consumption was approximately 22%, natural gas was approximately 1%, biomass approximately 5%, coal approximately 0%, and lpg was consumed at approximately 3%. figure 13. share of commercial and industrial energy consumption international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.360-373 370 in this study, the authors put more emphasis on the calculation of electricity consumption. historical data from 2000 to 2011 shows increases of an electricity users in the commercial and industrial sectors. figures 14 and 15 show that in the commercial sector the electricity user was growth of 14% p.a, while in the industrial sector only about 5% p.a. figure 14. electricity commercial user as mentioned above, the indonesian economy grew by an average of 6.5% p.a. this growth was supported by business sectors and industries. from 12.08 billion rupiah of gdp, the business sector contributed an average of 21% per year, and is expected to continued rising. figure 15. electricity industrial user indonesia energy outlook (ieo, 2011) provides an overview of the growth of indonesia's energy future . related to energy consumption inthe commercial and industrial sectors, the commercial sector and the industrial sector will grow by 4.9% and 6.2%, respectively. based on the agency for assessment and application of technology (bppt, 2011), from 2014 to 2030 energy demand was projected at average increase of 5.3 p.a and increased almost three times compared to 2009 (figure. 16). urban energy consumption in a city of indonesia: general overview 371 figure 16. projection of final energy demand 3.5 policy implications of urban energy consumption as it has been known that urban energy consumption is unique for each country to measure and determine by country features such as climate, socio-economic condition, population, and physical characteristic. one part that the government should focus on is that increase of population, income, and lifestyle will lead to an increase of energy consumption (sukarno et al., 2013; feng et al, 2012; crompton and wu, 2005). the survey of household energy consumption shows that utilization of energy such as lpg, biogas and renewable energy is still low compared to fossil-based energy. since 2007, the indonesian government has implemented a transition from kerosene to lpg. as it is already known, the government initially encouraged the use of lpg 12 kg tubes, and after the implementation of the conversion from kerosene to lpg, the government distributed 3 kg tubes available to the lower class. however, the study found that 38% households use kerosene. a high percentage of households who used kerosene were influenced by a lack of understanding the benefits of using lpg rather than kerosene. furthermore, the lack of disseminating the safe use of the lpg was also one of the factors contributing to concern about using lpg rather than kerosene. related household appliances, ownership and utilization of electrical equipment are believed to have a significant effect on the increase of electricity consumption (sukarno et al., 2013; feng et al, 2012; crompton and wu, 2005). this condition will be a matter of concern with the increase of population, economic growth and human lifestyle.since 2004, theministry of environment was started for eco-label vision in indonesia. for this vision, three missions are executed: (a) materialize synergy of environmentally negative impact control in product life cycle, (b) to encourage supply and demand quality and environmentally friendly products, (c) preparing criteria and an eco-label certification system which is competent and credible based on one stakeholder. this program should be integrated with strong regulation, standards, and policies that are required to support the eco-label vision in indonensia. the agency for assessment and application of technology (bppt, 2011) predicts that by 2030 indonesia will become an energy importing country. some of the main energy sources are not able to satisfy domestic needs. coal and petroleum reserves are predicted to only be able to meet domestic demand until 2050. moreover, lpg demand is predicted to increase to 10 million tons by 2030 and 70% is still met from imports. dependency on high energy based on fossil fuel will lead increase of co2 emission. under the bppt prediction, by 2030 total co2 emissions will reach1.2 billion tons, where coal accounts for co2 emissions by 844 million tons, or 67 percent of total energy. this condition should receive serious attention from the indonesia government. this will require essential policies and real programs to encourage the use of modern clean energy. increased use of geothermal energy, solar energy, hydro energy, combustion energy and other renewable options should be placedas the priority programs for sustainable energy consumption. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.360-373 372 4. conclusion in this study, urban energy consumption was calculated based on a cohort model of padang indonesia. although it was a basic model with various primary data related to energy consumption calculations, it provided an overview of urban energy consumption in the residential, commercial, industrial and transportation sectors. one of the parameters that can be used as the basis for calculating energy consumption is the population growth. as one of the biggest users of energy, population growth has a significant influence on the increase of energy consumption. the cohort models provide an overview of the growth of the urban population every year. from the simulation results, several conclusions can be summarized: (a) based on tfr scenarios, from 2015 to 2050 the padang population can be reduced to 7% per years; (b) energy consumption has a positive correlation with population size; based on the energy consumption calculation, the main driving forces of urban energy consumption have been identified. in terms of the residential sector, cooking activities and cooling device are the main factorsfor electrical energy consumption. although, from year 2007, the indonesian government carried the conversion program from kerosene to lpg; however, the consumption of kerosene was still high over the last five years. in the transportation sector, the number of motorcycles is extremely high and became the largest contributor to air pollution in the city. in the commercial and industrial sectors, electricity is one of the highest energy consumptions compared to other energy sources. decreasing urban energy consumption could be achieved by increasing efficiency of household appliances, promoting electricity saving behaviors, increasing public awareness for energy saving, and applying energy efficient labeling for home appliances. hence, these elements should be prioritized in the future urban energy study and integrated with the long-term urban planning toward sustainable development. acknowledgment the authors would like to acknowledge industrial engineering of andalas university students who helped the authors to distribute and collect questionnaires, and also all the individuals who participated as a respondent in this research. the authors would also like to convey their gratitude to the indonesian scholarship (dikti) program for providing scholarships during the study. references bapedalda.(2012). http://www.padang.go.id. bill, m., danni, m. (2009). how are we using energy in homes today? results from the 2009 residential energy consumption survey (recs). 2012 aeic annual load research conference. july 11, 2012. crompton, p., wu, p. (2005). energy consumption in china: past trends and future directions. energy economics, 27(1), 195-208. eia, energy international outlook (2011). energy information administration, u.s. energy information administration. esdm.(2012). http://www.esdm.go.id/berita/migas/40-migas/5368-pengendalian-konsumsi-bbm-untuk-ketahan an-energi-nasional.html. feng, y.y., chen,s.q., zhang, l.x. (2012). system dynamic modelling for urban energy consumption and co2 emissions: case study of beijing, china. journal of ecological modelling 44-54. fong, w.k. (2008). a study on the prediction and control of urban energy consumption and carbon dioxide emissions. doctoral thesis of toyohashi university of technology, japan. fong, w.k., matsumoto, h, ho, s.c., lun,y.f. (2008). energy consumption and carbon dioxide emission considerations in the urban planning process in malaysia. journal of the malaysian institute of planners, vi, 101-130. handbook of energy and economic statistics of indonesia. (2011). ministry of energy and mineral resources. urban energy consumption in a city of indonesia: general overview 373 hannon, b.,ruth, m. (2001). dynamic modeling. springer-verlag, new york. iges. (2004). urban energy use and greenhouse gas emission in asian mega-cities: policies for a sustainable future. institute of global environmental strategies. indonesia bank. monetary policy. (2013). http://www.bi.go.id/nr/rdonlyres/25236949 066e-497f-ac99-a9a980527022/27869/tkm_0114.pdf. indonesia energy outlook (ieo). (2011). pusat teknologi pengembangan sumberdaya energi. badan pengkajian dan penerapan teknologi. kumar, s., sonar (2008). urban sprawl a system dynamic approach, 44th isocarp congress 2008. padang in figure (2011). badan pusat statistik kota padang. pereira, i.m., assis, e.s. (2013). urban energy consumption mapping for energy management. energy policy, 59, 257-259. sukarno, i., matsumoto., h, kimura., r, susanti., l. (2013). residential energy consumption in a local city of indonesia. proceeding of 23rd pacific conference of the regional science association international (rsai) and the 4th indonesian regional science association (irsa) institute (prsco 2013), bandung, indonesia, 2-4 july 2013. un. (2008). world urbanization prospects: the 2007 revision population database. new york: united nations population division. http://esa.un.org/unup/. wijaya, m.e., tezuka, t. (2012). electricity saving potential in indonesia households: a techo-socio-economic analysis. in: 4th international conference on sustainable energy and environment (see 2011), bangkok, thailand, 27-29 february 2012. . international journal of energy economics and policy | vol 10 • issue 3 • 2020396 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(3), 396-401. effect of debt structure on earnings quality of energy businesses in vietnam nguyen thi thanh phuong1, dang ngoc hung2*, vu thi thuy van3, ngo thanh xuan3 1thuongmai university, hanoi, vietnam, 2hanoi university of industry, hanoi, vietnam, 3national economics university, hanoi, vietnam. *email: hungdangngockt@yahoo.com.vn ; email: phuong.nt@tmu.edu.vn received: 15 december 2019 accepted: 20 february 2020 doi: https://doi.org/10.32479/ijeep.9110 abstract the paper examines the impact of debt structure (ds) on the earnings quality (eq) of energy businesses (dn) in vietnam. the authors measure eq in terms of profit management to consider the effect of accounts payable; short-term debts and loans; long-term debts and loans on eq. the research uses generalized least squares regression method with data gathered from 468 observations collected at energy enterprises listed on the stock market in vietnam in the period of 2009-2018. the study results have found that accounts payable to suppliers and short-term debts and loans have negative effect on eq; while long-term debts and loans have positive effect on eq. besides, firm size has a positive effect on eq, while profitability is a not statistically significant variable. the empirical research results are useful basis to help businesses improve their eq, thereby helping businesses to consider an appropriate level of ds. keywords: debt structure, earnings quality, energy business jel classifications: m40, g32, q43 1. introduction energy plays a key role in sustainable business development and responses to global climate change. for vietnam, energy plays an essential role in the process of industrialization and modernization. the vietnamese government has expressed strong determination and put high efforts to ensure national energy security as well as to provide sufficient energy for socio-economic development. vietnam’s energy demand is growing rapidly at a high rate, requiring large capital investment. only state budget cannot meet the demand of large fundings. the capital structure relates to business funding decisions and has gained many attentions by researchers around the world. this is an important decision of the companies to minimize liquidity risks, resolve conflicts in representation issues, increase funding flexibility and especially reduce capital mobilization costs as well as risk. (bellovary et al., 2005) have asserted that earnings quality (eq) is an important factor in assessing the financial health of a business. however, the authors also warn of the fact that investors, creditors and other users of financial statements often overlook this important factor. (chou et al., 2011) point out another fact that most investors often use financial statements to assess the business performance with the belief that profit figures reported will provide reliable information to serve the evaluation. this has created an incentive for managers to distort eqs to “beautify” the financial statements of businesses. the act of falsifying these real profits clearly deflects the assessments of investors and creates a false optimism about the entire production and business activities. therefore, when the company publishes high profits on the financial statements, it does not necessarily mean it is operating effectively. investors and creditors may question whether the reported figures are real or are just formulated by managers to create an incorrect image of the business growth. the “enron incident” and a series of other collapses have shown that many businesses reported high profits, yet still face difficulties in this journal is licensed under a creative commons attribution 4.0 international license phuong, et al.: effect of debt structure on earnings quality of energy businesses in vietnam international journal of energy economics and policy | vol 10 • issue 3 • 2020 397 business operations and some of them eventually went bankrupt. this consequence stems from the fact that the reported profits do not reflect exactly what is actually happening in the production and business activities. (gupta and fields, 2006) argue that one of the important motivations for distorting corporate profits is to avoid liquidity problems stemming from being unable to borrow new debt at the near due date. this profits distortion clearly affects the quality of the reported profit figures of businesses. (chou et al., 2011) previous studies show businesses are motivated to change their own eq for the better so that they can succeed in attracting financial resources. although the choice of debt structure (ds) depends on factors related to the business strategies, there is a possibility that managers can adjust the profitability to distort the real value of the businesses with the intention to mobilize external funding more easily. the authors believe that if the company can effectively manage its debt, it can increase cash flows and raise capital for development. normally, to serve the business operations, the company can mobilize funds by issuing shares (using equity) or borrowing through various forms (using loans). when a business carefully and efficiently plans its debts, it can utilize a flexible and longterm financial resource with lower interest rates than equity. by considering the ds, the company can forecast its cash flow through maturity and fulfillment of debt obligations. as the result, business can manage the cash flow and increase its value. studies from the above have provided sufficient evidence that ds has an impact on eq. specifically, the components of debt, such as credit due to suppliers (accounts payable), bank loans (short-term, long-term), debts from issuing bonds affect the quality of profit figures reported. in addition, financial leverage and the tightness of the loan terms also affect the eq of the business. the evidence found from previous studies is one of the main motivations for this impact to be studied in the vietnamese context. there have been a number of studies on the relationship and effects of ds on eq in countries around the world and in vietnam. some studies related to eq, ds, and profit management, such as (tâm, 2013), (hung et al., 2018), (dang et al., 2018), (đặng et al., 2019), (thanh et al., 2019), (dang et al., 2019), (nguyen and nguyen, 2019). however, there has not been any research on the impact of ds on eq in the energy industry, which is a content that is very interested by investors and managers. therefore, it is important to expand and deepen the impact of ds on the eq of energy businesses in a developing economy of vietnam. 2. theoretical basis 2.1. some concepts 2.1.1. eanings quality (healy and wahlen, 1999) stated that one of the means for managers to convey information about their business activities to investors is through financial reports. nevertheless, investors often believe that these reports can help them distinguish between businesses that perform well and those that do not. it is this perception that motivates executives to intervene in the financial statements and only publish information that serves for their purposes, thus, can bring damage to investors. (bellovary et al., 2005) argued that the eq depends on the truthfulness of the reported financial numbers that reflect the “real profit” of the business, as well as the usefulness of these reported figures for the profit forecast in the future. in addition, the authors believed that eq is affected by the stability and retention period of reported profits. in fact, there are many ways to define eq depending on their purposes. regulators view profit as high quality when they comply with the requirements and regulations of the acceptable general accounting standards. meanwhile, lenders say that profits are of high quality when it can quickly be converted into money (dechow and schrand, 2004). jamie pratt (2003) defines eq as the measure of the difference between profit on the income statement and net profit. (schipper and vincent, 2003) define eq as the extent to which the profit figures in reports indicate a true representation of profit. 2.1.2. ds the ds of the business is the collection of payment obligations that the company must fulfill. the ds shows how businesses finance their assets through various forms of debt. in this study, to match the characteristics of vietnamese enterprises, the ds is mainly considered with two basic components: (i) short-term debts and loans (debts with a term of ≤1 year, and include payables and shortterm borrowings); (ii) long-term debts and loans (debts with a term of more than 1 year, and include long-term loans and bonds). 2.2. some theories in a perfect capital market under the assumption of (modigliani and miller, 1958) decisions on capital structure do not change the value of enterprises. (modigliani and miller, 1963) add an element of imperfection which is the tax, and suggest that the value of the borrower will be higher due to the higher tax shield from debt compared to the non-borrower. subsequent studies determined the importance of ds because of its ability to address other market imperfections such as agent conflicts (myers, 1977), information asymmetry (flannery, 1986), (kale and noe, 1990), liquidity risks (diamond, 1991) and taxes (bricker et al., 1995), (lewis, 1990). 3. overview and research hypotheses 3.1. study overview in recent years, there have been a number of studies on eq, the impact of ds on eq and the impact of ds on profit management. for instance, (gupta and fields, 2006) have done research projects on ds and possible profit management capabilities of managers. this study focuses on examining corporate eq and the relationship between eq and short-, mediumand long-term debts. the study found a positive relationship between profit management and debt use. (sercu et al., 2006) studied the relationship between profit management and debt management. the results of this study show a positive relationship between profit management and financial leverage. phuong, et al.: effect of debt structure on earnings quality of energy businesses in vietnam international journal of energy economics and policy | vol 10 • issue 3 • 2020398 (fung and goodwin, 2013) examined short-term debt, supervision and earnings management based on accrual accounting. the authors found that short-term debt is positively related to profit management. however, when the research was applied to high credit rating companies, they found a negative relationship between short-term debt and profit distortion (represented by arbitrary accruals), which is consistent with the hypothesis of debt supervision. this leads to the conclusion that for firms with a high level of credits, the relationship between short-term debt and arbitrary accruals is stronger than those with low level of credits. (liu et al., 2010) consider whether or not businesses manage profit before issuing bonds to get lower borrowing costs. the evidence shows that there has been a management of profits before the issuance of corporate bonds. the study results point out that there is a positive and statistically significant relationship between profit management and the current arbitrary accrual (representing profits management measure). more importantly, research has shown an inverse relationship between observed anomalies and accrued borrowing costs. this means that businesses will get debt at a lower cost when managing their profits in an upward direction. (kim and qi, 2010) examines the relationship between real-life conversion decisions and the binding on loan terms. the result discloses that a higher level of profit management happens when loan terms are more tightly bound. this result shows that: (i) enterprises use profit management to avoid violating loan terms; and (ii) enterprises are more likely to distort profits when the ability to renegotiate loans that have violated the terms is limited. the authors also discovered the positive relationship between loan terms and profit management occurring before and after the application of the us sarbanes oxley act. (chou et al., 2011) conducted a review on the relationship between profit management behavior and the firms’ ds (short, medium and long-term debts). the results from this study show that firms that perform profit management tend to issue long-term debt to avoid external scrutiny and high borrowing costs when using the short-term debts. (garcía‐teruel et al., 2010) conducted research on accruals quality and ds. the results show that there is a negative and statistically significant relationship between long-term debt and accruals quality. that means businesses with high accruals quality often borrow debt with a longer term. this is in line with the theory that firms with higher accruals quality can reduce the problem of asymmetric information and adverse selection between businesses and lenders, helping lenders feel secure in granting debts to businesses with longer maturities. (valipour and moradbeygi, 2011) conducted a review of the relationship between corporate debt financing and eq. the results show a negative and statistically significant relationship between debt and eq. more specifically, the authors classify debts into two levels: high and low level of debts. with a low debt level, there is a negative relationship between debt and eq. this means that businesses that borrow at lesser amount are less likely to manage profits. meanwhile, businesses with higher debt ratios often record more accruals to manage profits in order to avoid violating the terms of the loan contracts and reduce the cost of debt financing. (thanh et al., 2019) conducted a study to investigate the relationship between debt ratio and profit management based on regression model and panel data of 432 vietnamese listed non-financial institutions in the period of 2006-2017. the estimated results show the non-linear effect of debt ratio on profit management in two modes: (i) positive effects in the low debt regime and (ii) negative effects in the high debt regime. these results imply that changes in debt ratios occur in profit management before and after companies reach their optimal debt threshold. 3.2. research hypotheses ds has a close relationship and affects the eq, so each of the ds components such as accounts payable to suppliers, short-term debts and loans, long-term debts and loans will affect the eq of the business. based on an overview of empirical studies of (sercu et al., 2006), (gupta and fields, 2006), (fung and goodwin, 2013), (liu et al., 2010), (kim and qi, 2010), (chou et al., 2011), (garcía‐teruel et al., 2010), (valipour and moradbeygi, 2011), (thanh et al., 2019), (dang et al., 2019), (hung et al., 2018), (dang et al., 2019) and the theoretical basis, the authors construct some research theories as follows: h1: accounts payable are statistically significant and have a negative effect on the eq of the business. h2: short-term debts and loans are statistically significant and have a negative effect on the eq of the business. h3: long-term debts and loans are statistically significant and have a negative effect on the eq of the business. in addition, a number of control variables that can significantly affect the eq will be included in the model, namely: firm size, (watts and zimmerman, 1990) argue that large firms face higher political costs and therefore have a stronger incentive to use accounting assumptions. in order to reduce political costs, the authors formulate the following hypothesis: h4: firm sizes are statistically significant and have a positive effect on the eq of the business. profitability, research by (defond and park, 1997) shows that when current profits are high, business executives often take profit management measures to save a part of profit for the next period in case the next period returns are not as expected and vice versa. thus, there is an inverse relationship between the profitability and eq as formulated in the following hypothesis: h5: profitability is statistically significant and have a negative effect on the eq of the business. 4. research methodology 4.1. research models from the research overview and the established hypotheses, the research team built a research model as follows: eqit = β0+β1apdebtit+β2stdebtit+β3ltdebtit+β4sizeit +β5roait+εit (1) the variables in the research model are detailed in table 1. 4.2. measuring eq there are many ways to measure eq through profit management, the authors use the model of jones (1991). the variable eq measured via proxy is the remainder of equation (2). the eq is the opposite of the remainder of the following equation: phuong, et al.: effect of debt structure on earnings quality of energy businesses in vietnam international journal of energy economics and policy | vol 10 • issue 3 • 2020 399 accit = β0+β1(revit−arit)+β2ppeit+εit (2) in which: δrevit is the difference between the turnover of business i in year t and year t−1 ppeit is the cost of busines i’s fixed assets in year t ait−1 is the total assets in year t−1 α1, α2, α3, are the parameters of each business. the profit management variable will be taken as a residual εit because profit management is the profit-correcting behavior, so whether there is an increase or decrease (equivalent to an adjustable cumulative variable is positive or negative), they are behaviors of profit management. thus, εit is the measurement of the eq; the higher the εit deviation, the lower is the eq. the eq measured by profit management is determined by eq = em×(−1). 4.3. research data this paper uses data collected from the vietnamese stock exchanges in the period of 2009-2018. moreover, in order to determine the variables in the research model, the data was taken from period of 2008 to 2018 from audited financial statements of energy enterprises. after determining the indicators, the data of 468 observations are used to perform the analysis and regression. to consider and select the appropriate models, the research team used generalized least square (gls) regression methods. the authors tested the autocorrelation phenomenon and the variance change phenomenon. the model test results show that the p-value received was equal to 0.000 <α (5%). this implies that the hypothesis h0 is rejected and that there is no variance change in the models with a 5% significance level. therefore, the authors conducted another test to overcome defects of regression model by gls regression method. 5. research results and discussion statistical data (table 2) shows that eq has the average value of −1.657; the smallest is −12.617 and the highest is −0.015; the standard deviation is 1.997. the portion of accounts payable (apdebt) is 13.2%; short-term debts and loans is 10.6% and the ratio of long-term debts and loans is 19.4% compared to the average total assets of the enterprise. the size of the firm (size) is measured as a logarithm of the average firm’s total assets which equals to 27,887. the ratio of profit after tax to total assets is (roa) of 6.9%. figure 1 shows the ds of selected energy firms over the period of 2009-2019. for accounts payable and short-term debts and loans, there was no big change between years, while long-term debts and loans tended to decrease over time, from 24% in 2009, to 17% in 2018. table 3 shows the correlation coefficients between the variables. the purpose of examining the close correlation between the independent and dependent variables is to eliminate factors that may lead to multicollinearity before running regression model. in fact, the correlation coefficient between the independent variables in the research model does not have any pair >0.8, so it is less likely to have multi-collinear phenomena when using the regression model. after performing descriptive statistics and correlation matrix analysis, the authors conducted an estimate of the research model using the gls estimation method. the results by gls method (table 4) show that the ds has an impact on eq and is statistically significant, as follows: accounts payable have a negative impact on eq and are statistically significant at 1%. this is consistent with the hypothesis h1 and correlates with the research results of (gupta and fields, 2006), yet disagrees with the study of (tâm, 2013) and (sercu et al., 2006). this means that commercial credits or accounts payable have a great influence on the eq of vietnamese energy businesses. it could be explained that in order to implement commercial credit terms that are beneficial to them, energy enterprises have made profit management measures to achieve the goals, thus their eq decreases. short-term debts and loans have an opposite effect on eq and are statistically significant, which is consistent with the hypothesis h2. the results of this study are similar to those of (gupta and fields, 2006), (fung and goodwin, 2013) but contrary to that of (tâm, 2013). the research results show that when the ratio of short-term debts and loans increases, the eq decreases. this may be due to the reason that to deal with the terms of short-term loans of credit institutions, enterprises must take measures to manage profits, causing eq to decrease. on the other hand, long-term debts and loans positively affect the firm’s eq. this research result is contrary to the established hypothesis h3, consistent with the research of (garcía‐teruel et al., 2010), yet in contrast to the study of (chou et al., 2011). the control variables are all positively related to eq. this result is consistent with the hypothesis h4 and agreed with the research by table 1: independent variables in the research model variables code name measurement expected signs earnings quality eq the absolute value of the residual from the equation, multiplied by (−1): accit = α+β1(revit−arit)+β2ppeit+εit accounts payable apdebt accounts payable/total assets − short-term debts and loans stdebt short-term debts and loans/total assets − long-term debts and loans ltdebt long-term debts and loans/total assets − firm size size the size of the business by assets log (total assets) + profitability (return on assets) roa net profit after taxes/total assets − source: authors’ compilation phuong, et al.: effect of debt structure on earnings quality of energy businesses in vietnam international journal of energy economics and policy | vol 10 • issue 3 • 2020400 (watts and zimmerman, 1990). nevertheless, roa has an opposite effect on eq but not statistically significant, and not in agreement with the research of (defond and park, 1997). 6. conclusions and recommendations for the purpose of studying the impact of ds on the energy business’s eq in vietnam, the authors performed regression with appropriate methods on table data collected from 468 observations of vietnamese energy enterprises in the period from 2009 to 2018. the research results show that the accounts payable to suppliers, short-term debts and loans are statistically significant and negatively related to eq; while long-term loans and debts are positively related to eq. based on the research results, the authors suggest the following recommendations: with the above results, the study has made useful contributions to subjects using financial statements in the consideration of eq. for credit institutions, the determination of eq is related to ds, partly in considering the ability to earn incomes to repay loan contracts and minimize potential risks in the business operations. when eq is appreciated, it means that the enterprise has the ability to generate incomes to meet loan conditions. the research results provide investors with a useful tool to assess the financial health of businesses. from there, investors can invest more accurately and reasonably based on the available data. businesses need to study to expand firm size. this is a necessary condition for businesses to gain resources to improve the eq, and to limit the costs incurred due to representation issues. largescale enterprises with many growth opportunities will implement long-term debt policy, which accounts for a large proportion of the total debt. investors and the credit institutions’ concern is not how much money a business can make, but importantly how it creates income streams. investors need to understand how money is actually generated by researching and analyzing the data to assess the eq of the business. figure 1: firms debt structure for the period of 2009-2018 source: authors’ compilation 12% 14% 13% 14% 14% 14% 12% 12% 14% 13% 10% 08% 09% 11% 12% 09% 10% 12% 12% 11% 24% 22% 24% 20% 19% 18% 18% 18% 17% 17% 00% 05% 10% 15% 20% 25% 30% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 apdebt stdebt stdebt table 2: descriptive statistics variables observations average standard deviation minimum value maximum value eq 468 −1.657 1.997 −12.617 −0.015 apdebt 468 0.132 0.129 0.000 0.662 stdebt 468 0.106 0.112 0.000 0.535 ltdebt 468 0.194 0.193 0.000 0.759 size 468 27.887 1.485 24.384 31.898 roa 468 0.069 0.065 −0.113 0.416 source: authors’ calculation using stata 14.0 table 3: correlation matrix eq apdebt stdebt ltdebt size roa eq 1 apdebt −0.3263 1 stdebt −0.1824 0.1115 1 ltdebt 0.3463 −0.3951 −0.253 1 size 0.2091 −0.061 0.0007 0.3201 1 roa −0.044 −0.2043 −0.2778 −0.2773 −0.0882 1 source: authors’ calculation using stata 14.0 table 4: multivariate regression results variables gls model apdebt −4.110*** stdebt −2.555*** ltdebt 1.393** size 0.191*** roa −2.722* _cons −6.253*** n 468 source: authors’ calculation using stata 14.0. t statistics in brackets *p<0.1, **p<0.05, ***p<0.01 phuong, et al.: effect of debt structure on earnings quality of energy businesses in vietnam international journal of energy economics and policy | vol 10 • issue 3 • 2020 401 7. acknowledgments we gratefully acknowledge the financial support from the vietnam national foundation for science and technology development (nafosted) under grant number 502.02-2019.302. references bellovary, j.l., giacomino, d.e., akers, m.d. (2005), earnings quality: it’s time to measure and report. the cpa journal, 75(11), 32-37. bricker, r., previts, g., robinson, t., young, s. (1995), financial analyst assessment of company earnings quality. journal of accounting, auditing and finance, 10(3), 541-554. chou, d.w., ling, p.j., chan, c.y., chang, s.c. (2011), the impact of earnings management on the choice of debt maturity structure. management review, 30, 137-151. dang, h.n., vu, v.t.t., ngo, x.t., hoang, h.t.v. (2019), study the impact of growth, firm size, capital structure, and profitability on enterprise value: evidence of enterprises in vietnam. journal of corporate accounting and finance, 30(1), 144-160. dang, n.h., hoang, t.v.h., dang, t.b. (2018), impact of accounting information on financial statements to the stock price of the energy enterprises listed on vietnam’s stock market. international journal of energy economics and policy, 8(2), 1-6. đặng, n.h., phạm, t.h.d., đặng, t.h. (2019), tổng quan chất lượng lợi nhuận. tạpchí khoahọc and côngnghệ, 54(1), 96-102. dang, n.h., tran, b.m., tran, m.d. (2019), impact of dividend policy on variation of stock prices: empirical study of vietnam. journal of economics and development, 21, 96-106. dechow, p.m., schrand, c.m. (2004), earnings quality. charlottesville, va: research foundation of cfa institute. defond, m.l., park, c.w. (1997), smoothing income in anticipation of future earnings. journal of accounting and economics, 23(2), 115-139. diamond, d.w. (1991), debt maturity structure and liquidity risk. the quarterly journal of economics, 106(3), 709-737. flannery, m.j. (1986), asymmetric information and risky debt maturity choice. the journal of finance, 41(1), 19-37. fung, s.y., goodwin, j. (2013), short-term debt maturity, monitoring and accruals-based earnings management. journal of contemporary accounting and economics, 9(1), 67-82. garcía-teruel, p.j., martínez-solano, p., sánchez‐ballesta, j.p. (2010), accruals quality and debt maturity structure. abacus, 46(2), 188-210. gupta, m., fields, l.p. (2006), debt maturity structure and earnings m a n a g e m e n t . t h e f i n a n c i a l m a n a g e m e n t a s s o c i a t i o n , available from: https:www.//pdfs.semanticscholar.org/b38e/ c624fe989a3f7360327199b5432fc1c3e7df.pdf. healy, p.m., wahlen, j.m. (1999), a review of the earnings management literature and its implications for standard setting. accounting horizons, 13(4), 365-383. hung, d.n., do hoai linh, t.t.v., hoa, t.m.d., ha, h.t.v. (2018), factors influencing accrual earnings management and real earnings management: the case of vietnam. vietnam: paper presented at the proceedings of 14th international conference on humanities and social sciences 2018 thailan. hung, d.n., ha, h.t.v., binh, d.t. (2018), impact of accounting information on financial statements to the stock price of the energy enterprises listed on vietnam’s stock market. international journal of energy economics and policy, 8(2), 1-6. jamie pratt, d.b.a. (2003), using deferred taxes to detect earnings management. in: the 67th international atlantic economic conference. jones, j.j. (1991), earnings management during import relief investigations. journal of accounting research, 29(2), 193-228. kale, j.r., noe, t.h. (1990), risky debt maturity choice in a sequential game equilibrium. journal of financial research, 13(2), 155-166. kim, d., qi, y. (2010), accruals quality, stock returns, and macroeconomic conditions. the accounting review, 85(3), 937-978. lewis, c.m. (1990), a multiperiod theory of corporate financial policy under taxation. journal of financial and quantitative analysis, 25(1), 25-43. liu, y., ning, y., davidson, w.n 3rd. (2010), earnings management surrounding new debt issues. financial review, 45(3), 659-681. modigliani, f., miller, m.h. (1958), the cost of capital, corporation finance and the theory of investment. the american economic review, 48(3), 261-297. modigliani, f., miller, m.h. (1963), corporate income taxes and the cost of capital: a correction. the american economic review, 53, 433-443. myers, s.c. (1977), determinants of corporate borrowing. journal of financial economics, 5(2), 147-175. nguyen, h.t., nguyen, d.t.n. (2019), the impact of country-level and fund-level factors on mutual fund performance in vietnam. journal of economics and development, 21(1), 42-56. schipper, k., vincent, l. (2003), earnings quality. accounting horizons, 17, 97-110. sercu, p., vander bauwhede, h., willekens, m. (2006), earnings management and debt. dtew-afi_0619, 1-25. available from: https:www.//lirias.kuleuven.be/1827224?limo=0. tâm, d.n.t. (2013), tác động của cấu trúc nợ đến chất lượng lợi nhuận của doanh nghiệp. tạpchí côngnghệ ngânhàng, 85, 51-59. thanh, s.d., canh, n.p., ha, n.t.t. (2019), debt structure and earnings management: a non-linear analysis from an emerging economy. finance research letters. doi: 10.1016/j.frl.2019.08.031. valipour, h., moradbeygi, m. (2011), corporate debt financing and earnings quality. journal of applied finance and banking, 1(3), 140-157. watts, r.l., zimmerman, j.l. (1990), positive accounting theory: a ten year perspective. accounting review, 65(1), 131-156. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 5 • 2020368 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(5), 368-383. renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirical evidence from south and southeast asian countries with cs-ardl modeling zeeshan arshad*, margarita robaina, anabela botelho department of economics, management, industrial engineering and tourism, university of aveiro, portugal. *email: arshad@ua.pt received: 18 apil 2020 accepted: 13 july 2020 doi: https://doi.org/10.32479/ijeep.9956 abstract this study aims to estimate the effects of economic growth, renewable and non-renewable energy consumption (ec) and natural resources on carbon emissions for the period of 1990-2014, in 11 countries, using 3 panels: (i) full countries panel, (ii) south asian countries and (iii) southeast asian countries. for all panels, the long-run elasticities were estimated. the results suggest that non-renewable and renewable ec increase economic development in the three panels. besides, natural resources impede the economic growth in south asian and full countries panels while natural resources increase the economic activities in southeast asian countries. non-renewable and economic growth increase co2 emissions, whereas, renewable ec lessens the carbon emissions. natural resources also contributed to co2 emissions in the case of south asian and full countries panels while improved the environmental quality in the southeast asian region. it was also observed that there is cointegration among the variables in all three panels. policy recommendations can be made, in the sense that renewable energy sources should be preferred to decrease co2 emissions, and education and corruption should be improved to estimulate the economic growth in the studied areas. keywords: renewable energy, non-renewable energy, co2 emissions, natural resources, cs-ardl jel classifications: q43, q44, q56 1. introduction from the last few decades climate change has been a very wide spoken phenomenon and exhalation of carbon dioxide (co2 emissions) is considered its chief source. the intensity of the co2 emissions has been risen by 45% from the last 130 years which is constantly deteriorated the environmental quality (carbon footprint, 2018). according to the existing literature, several drivers of co2 emissions (co2) have been discussed such as economic growth (gdp), industrialization, urbanization (urb), deforestation, waste management, air pollution, renewable energy (re) sources, non-renewable energy (nre) sources (arshad et al., 2020) and natural resources (nr) etc. to meet the demand for the ever increasing population of this planet, labor, capital and other inputs of production (especially energy sources), uplift of human efforts are considered liable for the world’s astonishing economic progress (owusu and asumadu-sarkodie, 2016), which ultimately raised the level of carbon emissions. briefly speaking the release of carbon dioxide has proved itself for the threat to environment system and human development (bekun et al., 2019). the gaseous emission alarming increased from the figure of 9434.4 million tons in 1961 to a gigantic figure of 34649.4 million tons in year 2011 (ipcc, 2014). british petroleum agency (2018) report reveals that a uplift of carbon dioxide from 29714.2 million tons in 2009-33444 million tons in 2017 was observed on the globe. this journal is licensed under a creative commons attribution 4.0 international license l arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirica evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020 369 the dynamic that has affected the energy-related carbon emissions have been widely discussed in the existing literature: farhani and shahbaz (2014) for middle east and north african (mena) countries, shafiei and salim (2014) for oecd countries, ben jebli and ben youssef (2015) for tunisia, bhattacharya et al. (2017) for 85 developed and developing economies, bento and moutinho (2016) for the italian case, rasoulinezhad and saboori (2018) for the commonwealth of independent states (cis), dong et al. (2019) for 128 countries and adam and nsiah (2019) for 28 sub-saharan african economies, are some examples. besides, the economic growth and nr nexus is also discussed in the existing literature, that provides the mixed (positive and negative) substantiation of a nr on economic growth (satti et al., 2014). the economies with abundant nr perform lesser than the nr-scarce nations (sachs and warner, 1995). for instance, korea, singapore, japan, hong kong and switzerland, performed very well and made enormous progress with no or very limited access to natural resources (krueger, 1998) and contrary to nr abundant countries made 3 times more progress (auty, 2001; sachs and warner, 1995). shaw (2013) also proved that nr abundance is the only reason for low economic growth in azerbaijan. conversely, some south american countries took advantage of the nr boom to enhance their economic growth. notably, ecuador increased its gdp per capita during the boom period of nr (sachs and warner, 1999). besides, the resources of ore and coal in england and germany were the significant ingredients behind the industrial revolution in europe (sachs and warner, 1995). the exploitation of nr abundance was also behind the success story of norway to achieve a high level of income prosperity with proper economic planning (gylfason, 2001). furthermore, natural resources (nr) are also included in different studies to investigate the impact on environmental quality. recently, bekun et al. (2019) analyzed the causal interaction between economic growth, nr rent, re and nre consumption in co2 emissions for eu 16 countries covering the period of 1996-2014 by pooled mean group (pmg)-ardl models. the kao cointegration techniques confirmed the long-run relationship between the variables, and the study suggested that nr rent have a significant positive impact on co2 emissions. it indicates that overdependence on the nr rent has effects on environmental sustainability if a proper management is ignored. the study also noted that nre and economic growth increase, whereas re consumption decrease the co2 emissions. the causality results display a feedback result effect amidst nre, re and economic development. further, the study also found feedback causality between nr rent and economic growth. the above discussion about energy (re and nre) consumptionco2 emissions nexus disclosed mixed results for different countries and economies with different time spam. moreover, nr abundance or scarce role in the economic growth has been a challenge in developing and developed countries, and their impact on co2 emissions requires more research, as existing results are not consensual. for this purpose, the current study investigates the linkages between economic growth, nr rent, co2 emissions, re and nre consumption over the period of 1990-2014 for the south and southeast asian countries (ssea). we developed two models to full fill the aim of the study: model 1, to access the impact of re, nre and nr effects on economic growth, model 2, to access the impact of all the discussed variables on co2 emissions. although several studies have considered the factors influencing co2 emissions at single-country, regional and global perspective, there is a limited number of studies examining the impacts of economic growth, nr rent, re and nre consumption on carbon emissions within the same framework for ssea countries. further, this piece of writing dissent from the current composition in several modes. firstly, it is a humble effort to meet the literature gap, by studying ssea economies, using the referred variables, as the estimations were made for 3 panels: (i) full countries panel, (ii) south asian countries and (iii) southeast asian countries. secondly, this article considers advance panel data techniques that allow the heterogeneous unobserved parameters and cross-sectional dependence (cd) of the sample countries. thirdly, the study uses the advance pmg technique to estimate the short and long-run dynamics. fourthly, to robust the pmg estimation we have applied a new technique named as dynamic common correlated effects (dcce) cs-ardl introduced by chudik et al. (2016). finally, this paper controls for the result of diagnostic and specification tests, which have been rarely considered in prior studies. different cointegration techniques such as pedroni, kao, fisher and westerlund allowed us to conclude a long-run relationship exist among the considered variables. findings from the pmg and dcce cs-ardl estimations reveal that re and nre rise the economic development in the selected three panels. besides, natural resources impede the economic growth in south asian and full countries panels while increase the economic activities in southeast asian countries. in the case of model 2, results demonstrated that nre and economic growth increased the co2 emissions, whereas, re consumption lessens the carbon emissions in all three selected panels. however, natural resources also contributed to raise co2 emissionsin the case of south asian and full countries panels while improved the environmental quality in the southeast asian region. the policy implication in this regard, is that re sources should be preferred to decrease co2 emissions in the ssea countries. moreover, for the better use of natural resources, the government should concentrate on education and corruption to improve the economic growth in the selected studied areas. the remaining portion of paper has arranged in following way: the literature review chapter, the models construction, data overview and methodology chapter, the result and discussion chapter and in the end, the conclusions, policy implications, limitations and future recommendation chapter. 2. literature review the anterior literature has discussed the linkages among energy consumption (ec), renewable energy (re), non-renewable arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirical evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020370 energy (nre), energy prices, industrialization, economic growth and other macro-economic variables such as foreign investment (fdi), financial development (fd), trade openness (trd), and natural resource (nr) abundance, with co2 emissions as a proxy of greenhouse gases (ghgs). we divided our literature into two strands: (i) the effect of (re), (nre), economic development and other macro-economic variables with environmental degradation in the form of carbon emissions and (ii) the influence of nr on economic growth and on co2 emissions (co2). 2.1. economic growth (gdp), co2 emissions (co2), renewable (re) and non-renewable energy (nre) numerous studies that investigated the environmental pollutionmacroeconomic variables nexus are quite insignificant to justify such extensive phenomenon at single-country level, territorial scale and worldwide. for instance, in the case of the mena countries, farhani and shahbaz (2014) examined the relationship among re, nre, gdp and co2 emissions for 1980-2009. the study used the fully modified ordinary least square (fmols) and dynamic ordinary least square (dols) method to investigate the long-run elasticities. the results show that re and nre consumption increase carbon emissions. the study also found an inverted u-shaped environment kuznets curve (ekc) with economic growth and co2 emissions. unidirectional causality running from re, nre and output to co2 emissions were found in the short run, while in the long run, bidirectional causality running from re and nre to co2 emissions was observed. in addition to the concern mentioned above, shafiei and salim (2014) focused on the oecd countries during 1980-2011 and investigated with stirpat model the relationship between urbanization, co2emissions, re and nre consumption. the results show that nre has a direct impact on co2 emissions, while re decreases carbon emissions. the study also confirmed the ekc hypothesis with urbanization and co2 emissions. besides, in tunisia, ben jebli and ben youssef (2015) derived similar results with data covering years 1980-2009. further, bhattacharya et al.( 2017) demonstrated the role of re consumption and institutions on economic growth and in combating co2 emissions for 85 developing and developed economies of different income groups around the globe. the results from the generalized moment method (gmm) and fmols show that re has a significant favorable impact on economic growth and improved environmental quality. the production of re is the key to mitigating carbon emissions in italy, as concluded by bento and moutinho (bento and moutinho, 2016). for the case of turkey, pata (2018) analyzed the short and long-run dynamic relationship between gdp per capita, co2 emissions, urbanization, re consumption, fd, hydropower ec and alternative ec, during 1974-2014 with ardl bound testing and fmols method. the work reveals the ultimate relationships among mutable with gregory-hansen and hatemi-j cointegration approaches. in addition, the study noted that economic growth, urbanization andfd increase co2 emissions, whereas re consumption, hydropower consumption and alternative ec sources had insignificant effects on environmental quality. inglesi-lotz and dogan (2018) confirmed the long-run relationships between income, trd, nre, re consumption and co2 emissions for the ten biggest electricity generators in sub-saharan africa over the period of 1980 to 2011. moreover, the authors concluded that the use of re improved while nre worsened the environment quality, and that there is unidirectional causality running from income, co2 emissions, trd and nre towards re. top re users countries need to increase re production, fd and trd to lessen the carbon emissions (dogan and seker, 2016). conversely, rasoulinezhad and saboori (2018) noted the long-run connections between re, nre, trd, gdp, financial openness and carbon emissions for the commonwealth of independent states (cis) for 1992-2015. the results from panel cointegration methods such as fmols and dols declared that re has no impact on co2 emissions and that fossil fuel proxy of nre consumption declined whereas financial openness improved the environmental quality in the long run. in more recent studies, authors illustrated different linkages between variables. for instance, sharif et al. (2019) concentrated on the ultimate liaison connecting nre, re consumption and carbon emissions. the long-run elasticities show an inverse impact of re and direct effects of nre consumption on the environment for the panel of 74 nations during 1990-2015. also, belaïd and zrelli (2019) and chen et al. (2019) explored similar findings for 9 mediterranean countries and regional study in china, respectively. however, adam and nsiah (2019) noticed that both re and nre consumption increased the co2 emissions in 28 economies of sub saharan africa. in another scenario, dong et al. (2019) estimated the linkages between re intensity, nre and economic growth with stirpat modeling the global and regional context of an unbalanced panel dataset of 128 countries covering 1990-2014. the results indicated that at a global level, re intensity, nre, economic growth and population deteriorated the environment. nonetheless, the regional perspective findings suggested that re declined the co2 emissions in the two regions such as south and central america and europe and eurasia. 2.2. natural resources (nr)-economic growth (gdp)-environmental pollution nexus the natural resources (nr)-economic growth (gdp) nexus has been discussed into two scenarios: resource abundance and resource dependence in the prior literature. resource abundance can be explained by “annual per capita rent of resource production”(apergis and payne, 2014; brunnschweiler, 2008) whereas resource dependence can be measured by “rents from nr over gdp” (auty, 2007; bhattacharyya and hodler, 2014),“the share of total natural resource in total export” (dietz et al., 2007), or “the share of total natural resource export in gdp” (boschini et al., 2013; sachs and warner, 1995). several studies have been discussed the linkages between nr abundance and economic indicators around the globe. for instance, sarmidi et al. (2014) proved that nr abundance affects growth positively after the threshold level of institutional quality. after 2003, the oil abundance affects positively economic growth in mena countries (apergis and payne, 2014). conversely, satti l arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirica evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020 371 et al. (2014) inspected the connection among nr abundance, economic growth, fd, capital and trade by ardl bounds testing approach and vecm for 1971-2011. the findings confirmed the existence of long-run relationship between the considered variables and suggested that nr abundance impedes the economic growth whereas fd, trade openness and capital stock improve the economic development in venezuela. ahmed et al. (2016) also proved the association between nr, economic growth, capital, labour and exports by cobb-douglas production function. the results show that a 1% increase in nr results in 0.47% decline in gdp in the long-run. it means that nr abundance slowed the economic development in iran during 1965-2011. the causality results proved the feedback effect between economic growth and nr abundance. besides, kim and lin (2017) noticed similar linkages between nr abundance and economic growth by heterogeneous panel cointegration technique for 40 developing countries covering the period from 1990 to 2012. ben-salha et al. (2018) determined the causal connections between nr rent and economic growth by pmg estimator to identify the short and long-run dynamics for top nr abundance economies covering the period of 1970-2013. the result shows that nr rent increased the economic development (fd) in the long run. further, the result of the causality analysis shows that bidirectional relationship exists between the selected variables. shahbaz et al. (2018) also investigated the stimulating role of nr abundance in financial development for the usa for 1960-2016. the study also included additional variables such as education, economic growth and capitalization as fd in the financial demand function. the existence of cointegration confirmed between fd and its determinants. the empirical results also show that nr abundance, economic growth and education have a positive impact on fd while capitalization is inversely linked with fd. furthermore, in the meta-analysis of last two decades studies about natural resources and economic growth, havranek et al. (2016) observed that 40% of studies reported insignificant result, 40% studies supports the natural resource curse whereas the last 20% studies find blessing of natural resources. the authors noticed that institutional quality, investment activities, different nature of natural resources and natural resources scarce or abundance could be possible in explaining the differences across the studies. however, in recent years some studies found that nr-abundant countries have positive and rapid economic growth, especially with cross-sectional data. researchers believe that to have a clear picture of the connection between economic growth and nr needs to be studied more in time series and panels frameworks (badeeb et al., 2017). moreover, the role of nr is also included in different studies to investigate the impact on environmental quality. among of them, balsalobre-lorente et al. (2018) employed the carbon function to investigate the ekc hypothesis for european countries such as germany, spain, england, france and italy for the 1985-2016 period. the study also included other additional variables such as trd, nr abundance, re consumption and energy innovation to augment the carbon emission function. results confirmed the existence of the n-shaped ekc phenomenon. findings also suggested that nr, re consumption and energy innovation mitigate co2 emissions whereas, trd and the interaction between economic growth and re consumption deteriorated the environmental quality. in this regard, the review of limited literature represents quite distinct results, that has influenced in extending the vagueness regarding the specific association between the variables, thus requiring new investigation to clarify and validate the inconclusive findings of existing studies (balcilar et al., 2018). 3. models, data and methodology this section consists of three parts: (i) we will develop the empirical models, (ii) we will discuss the definition of the variables with data sources, and also demonstrate the individual country variables role over the year and descriptive statistics and (iii) we will discuss the different econometrics techniques which are going to be the part of the analysis. 3.1. models construction the focus of the study is to determine the linkages between economic growth, renewable energy (re), non-renewable energy (nre), natural resources (nr) rent and carbon emissions. for this purpose, we use two models. model 1: we observe the impact of re, nre, nr rent on economic development. one of the aims is to examine the relationship between gdp, re, nre consumption and nr rent in ssea region. the general form of the economic growth function model is designed as follows: gdp = f (re, nre, rent) (1) where re, nre, rent and gdp represent renewable ec, non-renewable ec, natural resources rent and economic growth, respectively. a large number of studies have jointly examined the nexus between natural resources and economic growth along with other macro-economic indicators (sarmidi et al., 2014; satti et al., 2014; ahmed et al., 2016; kim and lin, 2017; shahbaz et al., 2018; ben-salha et al., 2018 etc). based on the prior relevant studies, our empirical model is as follows: lgdp2it=α1it+αrit lreit+αnrit lnreit+αrenit rentit+ϵit (2) model 2: the role of economic growth, re, nre and nr rent in co2 emissions is accessed. further to probe the connection among dependent variable co2 emissions and independent variables such as re consumption, nre consumption, economic growth and nr rent, the basic framework of carbon emission is established based on the model of balsalobre-lorente et al. (2018) and bekun et al.(2019): co2 =f (re, nre, rent, gdp) (3) where co2 symbolizes co2 emissions per capita and the rest of the variables we have already discussed in equation 1. the estimated equation for this model was: arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirical evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020372 lco2it=β1it+βyit lgdpit+βrit lreit+βnrit lnreit+βrenit lrentit+μit (4) for equation (2) and (3) l stands for log-linear specification; ϵit and μit are the idiosyncratic error terms, independent and identically distributed, that represents the standard normal distribution with unit variance and zero mean; i represent the country (i = 1, 2,…….14); t stands for a time period (t = 1, 2, 3,……..25); α1it is intercept; αrit, αnrit, αrenit are the long-run elasticity’s estimates of economic growth (lgdp) with respect to the explanatory variables such as renewable energy consumption (lre), non -renewable energy (lnre) and rent (lrent) in model 1. furthermore, equation 4 implies that β1it is the intercept whereas βyit, βrit, βnrit and βrenit are the long-run elasticity’s estimates of co2 emissions per capita (lco2) concerning the independent variables such as real gdp per capita (lgdp), renewable energy consumption (lre), non-renewable energy consumption (lnre) and natural resources rent (lrent) respectively. 3.2. data our empirical analysis is established on the yearly time series data covering the time span from 1990 to 2014 for 5 south1 and 6 southeast 2 asian countries. the data was retrieved both for the period and selected countries from world development indicator (2019). co2 emissions are measured in (metric 1 pakistan, india, bangladesh, sri lanka and nepal 2 indonesia, philippines, malaysia, vietnam, singapore and thailand tons per capita); renewable ec consists in ec from of hydro, solar, wind, biogas and biofuels, in percentage of total final ec; non-renewable energy (nre) consumption refers to “use of primary energy before transformation to other end-use fuels, which is equal to indigenous production plus imports and stock changes, minus exports and fuels supplied to ships and aircraft engaged in international transport, measured in kg of oil equivalent per capita” (world bank, 2019); real gdp was stated in per capita constant 2010 u.s. dollar and the total natural resources are “the sum of oil, natural gas, coal, minerals and forest rents in percentage of gdp” (world bank, 2019). in table 1 we present variables definition as well as supporting references for each one. evolution of the selected variables with respect to countries is presented in figure 1. figure shows that singapore has the highest income, while the lowest gdp per capita is verified in nepal. construct to these graphs, the highest co2 emissions per capita was in singapore although with a negative trend whereas the lowest level was in nepal. in the case of re and nre consumption picture clearly shows that sample countries relay more on nre rather than in re sources. besides, total natural resources have a decreasing rate over the years in all the sample countries. furthermore, table 2 reflects the statistics summary of selected variables for the three panels, between 1990 and 2014. the table 1: description and sources of the variables variables definition supporting reference source co2 co2 emissions (metric tons per capita) (adams and nsiah, 2019; amri, 2019; belaïd and zrelli, 2019) wdi re renewable energy consumption (% of total final energy consumption) (ben jebli and ben youssef, 2015; dogan and seker, 2016; sharif et al., 2019) wdi nre non-renewable energy consumption (kg of oil equivalent per capita) (dogan, 2016; shafiei and salim, 2014; sharif et al., 2019) wdi rent total natural resources rent (% of gdp) (balsalobre-lorente et al., 2018; bekun et al., 2019; shahbaz et al., 2018) wdi gdp gdp per capita constant (2010 us$) (belaïd and zrelli, 2019; dong et al., 2019; mert et al., 2019) wdi wdi: world development indicator table 2: descriptive statistics and correlation matrix economies variables min max mean sd co2 gdp nre re rent south asian co2 0.03 1.73 0.56 0.39 1 0.38 0.75 ‒0.75 0.66 gdp 357.20 3506.73 997.31 671.29 1 0.54 ‒0.25 ‒0.19 nre 118.89 636.57 366.57 122.44 1 ‒0.25 0.41 re 36.65 95.11 61.72 16.68 1 ‒0.40 rent 0.10 7.35 1.45 1.21 1 southeast asian co2 0.30 18.04 3.94 3.99 1 0.77 0.90 ‒0.80 ‒0.22 gdp 431.8 52244.4 8805.10 13006.8 1 0.92 ‒0.67 ‒0.40 nre 260.79 7370.65 1719.68 1698.1 1 ‒0.79 ‒0.31 re 0.19 76.08 27.37 20.53 1 0.15 rent 0.00 25.80 5.40 5.04 1 overall co2 0.03 18.04 2.40 3.40 1 0.804 0.92 ‒0.77 0.06 gdp 357.20 52244.4 5256.1 10362.0 1 0.92 ‒0.62 ‒0.15 nre 118.65 7370.65 1104.63 1424.98 1 ‒0.74 ‒0.01 re 0.19 95.11 42.99 25.47 1 ‒0.26 rent 0.00 25.80 3.60 4.28 1 authors own calculation based on the data over the period 1990-2014. mean: simple average, max: maximum; min: minimum; sd: standard deviation and right columns presented pair-wise correlations and results reported till second decimal l arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirica evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020 373 southeast asian countries have the highest mean value of co2 emissions per capita (3.99) compared to south asian (0.56) whereas on the overall panel, countries are facing carbon emissions of 2.40. besides, southeast asian countries have high volatility than south asian countries. when analyzing the gdp per capita, we observe that southeast asian are richer than south asian economies. concerning renewable energy, the highest consumption is registered by south asian countries (61.72) compared to the southeast asian (27.37). however, in the case of non-renewable energy southeast asian countries consumed more than south asian economies. in terms of volatility, south asian economies are more consistent users of re and nre sources as they have the lowest standard deviation. furthermore, the average natural resources rent in south asian countries is 5.40 while in south asia is 1.40. concerning the volatility of natural resources rent, southeast asian countries are more volatile than south asian economies. 3.3. methodology 3.3.1. cross-sectional dependence (cd) and panel heterogeneity we used balanced panel data of 11 ssea countries in the current study. one of the assumptions of panel data is that there may occur a crosssectional dependence (cd) among the variables, which may produce unreliable and biased results (pesaran, 2007). from the existing literature, it is concluded, that panel data models are expected to exhibit significant cross-sectional dependence in the errors (de hoyos and sarafidis, 2006). the reason for the cross-correlation of errors might be due to omitted common effects, unobserved components and spatial effects or the presence of common shocks (pesaran, 2004). from figure 1 it can be noted that the countries investigated in the present study illustrate a different pattern in their economic growth performance, re, nre, rent and, therefore, provides an indication of inherent heterogeneity of individual cross-sectional units. moreover, the cd across the asian economies will be an essential issue to account because of the substantial economic and financial integration of the economies (bhat, 2018). this indicates that there is figure 1: co2 emissions per capita, renewable energy consumption, non-renewable energy consumption, total natural resources rent by country from 1990 to 2014 arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirical evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020374 a strong interdependence between cross-sectional units (belaïd and zrelli, 2019). moreover, these steps also allow us to choose suitable unit root tests for further analysis. several tests has been performed to check the cd among the countries, as friedman (1937), breusch and pagan lm (1980), frees (1995) and pesaran (2004) cd tests. however, for further empirical analysis we used well-known breuschpagan lm (1980) test, since it works better in the case of panels featured with n < t, where n stand for cross-sectional dimensions while, t represents the time dimensions of the panel. it means that no desirable statically properties are required (pesaran, 2004). besides, it is applicable in balance or unbalance panel data. for the robustness of the lm results pesaran (2004) cd test is also applied. 3.3.2. stationarity the second step is to confirm the stationarity after investigated the cd in the panel data modelling. after the confirmation of cross-sectional dependence, the next step consists in examining the stationary problem in the panel of variables, in determining the presence of stochastic trends, which is broadly designed to elaborate on the postulation of cross-sectional dependence (arshad et al., 2020). numerous tests of the unit root have been discussed in the prior literature for instance, (breitung, 2001; choi, 2001; hadri, 2000; harris and tzavalis, 1999; im et al., 2003; levin et al., 2002; maddala and wu, 1999; pesaran, 2007; quah, 1994). the researchers divided them into two groups such as first-generation (breitung, hadri and levin lin chu tests) who deals with cross-sectional independence and second-generation (adf-fisher, pp-fisher, cips, cadf and ips [im pesaran shin]) that considered cross-sectional dependence. however, it is evident that the cross-sectional dependence exists, so we used two secondgeneration test names as augmented dickey-fuller (cadf) and cross-sectional ips (cips) who deals with heterogeneous panels and cd, as proposed by (pesaran, 2007). 3.3.3. cointegration the next step is the cointegration process after the confirmation of the stationarity of the variables at the same level. this process helps us to identify whether long-run relationships exist between considered variables, that means that the variables moves together in the long-run. this panel cointegration method can also be used to study the longrun equilibrium process. therefore, we applied four cointegration methods. three belongs to the first generation method such as pedroni (2004), kao (1999) and fisher proposed by (maddala and wu, 1999) to identify the long-run relationships between variables. besides, to robust the first generation cointegration tests, we applied westerlund (2007) cointegration technique which is known as a second-generation method. and not only deals with the cross-sectional dependence but it also not relays on integrated order of the variables, what makes this method applicable in very general conditions. 3.3.4. pmg regression the pmg regression suggested by pesaran (1997) and pesaran et al. (1999) is applied, which permits convergence speed and short-run adjustment to estimate the heterogeneity of each country. the pmg estimation is the revised version of mean group regression (mg) (pesaran and smith, 1995). according to the pesaran et al. (1999), mg is a kind of pooled estimation because this model use average values of the coefficients of each group and assume that the slope coefficients and error variance are indistinguishable. however, pmg model takes the cointegration form of the simple ardl model and adapts it to a panel set by allowing the intercepts, short-run coefficients and cointegrating terms to differ across cross-sections. it further executes the restrictions of the cross-country homogeneity on the long-run coefficients (pesaran et al., 1999). to achieve the pesaran et al. (1999) pmg estimation, the ardl (p, q) models are as follows: ( ) ( ) ( ) ( ) ( ) 1 1 1 0 11     − − − −= = − − ∆ = ∆ + ∆  + − +  ∑ ∑p qi ii j i j it t j t jj j i i i i itt t j üüü gdp y e (5) ( ) ( ) ( ) ( ) ( ) 1 1 2 21 0 2 11     − − − −= = − − ∆ = ∆ + ∆  + − +  ∑ ∑p qi ii j i j it t j t jj j i i i i itt t j co co y co y e (6) where and refer to short and long-run coefficients, respectively; and represents short and long-run patterns with reference to co2 emissions respectively; and are the short-run coefficients; θi is the error correction term; (yi)t–j and (yj)t–j are the values of short-run and long-run variables; are the long-run coefficients; eit = μi+vit; μi and vit represents country-specific fixed and time-variant effects in both equations respectively. 3.3.5. dcce cs-ardl chudik and pesaran (2015) introduced a new panel technique named as “dynamic common correlated effects” (dcce) which is helpful to handle the problem of cross-sectional dependence. besides, this approach is the extension of common correlated effect (cce) by pesaran (2006). dcce approach considers cd by assuming that the variables can be represented by common factor. dcce technique is developed on the principle of mean group (mg), pmg and cce estimations presented by pesaran and smith (1995), pesaran (1997) and pesaran (2006) respectively. according to the approach of dcce we can make the estimator more consistent by including more lags of cd in regression. moreover, dcce have four advantages over the existing techniques in the relevant literature (chudik and pesaran, 2015) (1) deals the problem of cd by taking logs and average values of all the cross-sectional units. (2) it computes the dcce by considering heterogeneous slopes and assuming the variables represented by common factor. (3) it can handle the small sample size. (4) this technique can also apply in the presence of structural breaks and un-balance panel data (ditzen, 2016). besides, for the long-run estimation of coefficients two methods can be applied, first, cross-sectional augmented distributed lag (cs-dl) which directly estimates the long-run coefficients (chudik et al., 2016). second, cross-sectional augmented ardl (cs-ardl) method (chudik et al., 2016). however, we have employed dcce cs-ardl method to estimate the long-run coefficients. 3.3.6. dumitrescu-hurlin causality (dh) test the last step of the empirical analysis is the causality test to identify the direction causality of the variables. the direction could be the unidirectional bidirectional or no causality. for this purpose, we used dumitrescu and hurlin (dh) (2012) causality test as it is an befitting approach for the directional causality and presents more advantages compared to the traditional granger l arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirica evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020 375 (1969) causality test and presents the two critical spheres of heterogeneity, known as the heterogeneity of the regression model and the heterogeneity of the causal relationship. 4. results and discussion 4.1. cross-sectional dependence south and southeast asian economies such as pakistan, india, bangladesh, thailand, malaysia, indonesia are being affected from cross-sectionald ependence (cd), transborder pollutants’ effect and cross-country heterogeneity (behera and dash, 2017). due to different characteristics of the countries, and to robust the lm test results breusch-pagan lm (1980) cd and pesaran (2004) cd tests were performed. table 3 which describes the results of both tests denies the null hypothesis of no cd at 1% level of significance. there is significant evidence of the presence of cd among the variables considered, such as co2 emissions, gdp, re, nre and nr rent in all cases. 4.2. unit root tests countries have different characteristics and the panels may contain the presence of cd which may lead to unreliable and biased results (park et al., 2018). pesaran (2007) presented two unit root tests named ips cross-sectional (cips) and augmented dickey-fuller (cadf) that are used to handle the ambiguity of cd. the results of the cadf and cips panel unit root tests have been described in table 4. table 3: cross sectional dependence tests variables lco2 lgdp lnre lre lrent pesaran cd south asia 14.05a (0.00) 15.60a (0.00) 13.66a (0.00) 13.29a (0.00) 3.947a (0.00) southeast asia 6.86a (0.00) 18.68a (0.00) 6.13a (0.00) 7.90a (0.00) 3.84a (0.00) overall 22.10a (0.00) 36.06a (0.00) 20.15a (0.00) 22.33a (0.00) 7.26a (0.00) breusch-pagan lm south asia 198.50a (0.00) 243.41a (0.00) 189.07a (0.00) 178.03a (0.00) 107.19a (0.00) southeast asia 214.91a (0.00) 349.11a (0.00) 163.51a (0.00) 200.48a (0.00) 70.98a (0.00) overall 936.30a (0.00) 1300.87a (0.00) 804.30a (0.00) 841.82a (0.00) 414.22a (0.00) arepresents the significance level 1% and p-values reported in the parenthesis table 4: second generation unit root analysis tests cadf cips without trend with trend economies variables without trend with trend t-bar z-t-tilde-bar p-value t-bar z-t-tilde-bar p-value overall lco2 ‒1.25 ‒1.88 ‒1.47 0.99 0.84 ‒1.93 1.39 0.91 ∆ lco2 ‒6.04 a ‒6.15a ‒3.81a ‒6.98a 0.00 ‒3.49a ‒5.81a 0.00 lgdp ‒0.49 ‒2.32 ‒1.84 ‒0.25 0.40 ‒1.96 1.26 0.89 ∆ lgdp ‒5.71a ‒5.90a ‒2.93a ‒3.98a 0.00 ‒3.37a ‒3.77a 0.00 lnre ‒1.04 ‒2.25 ‒1.70 0.22 0.59 ‒2.06 0.92 0.82 ∆ nre ‒5.88a 6.09a ‒4.02a ‒8.33a 0.00 ‒4.27a ‒6.96a 0.00 lre ‒1.08 ‒2.04 ‒1.67 0.32 0.62 ‒1.85 1.64 0.95 ∆ re ‒5.62a ‒5.99a ‒3.80a ‒6.65a 0.00 ‒3.95a ‒5.81a 0.00 lrent ‒0.51 ‒2.97 ‒1.50 0.92 0.82 ‒2.93 ‒2.19 0.01 ∆ lrent ‒6.02a ‒6.22a ‒4.51a ‒9.37a 0.00 ‒4.63a ‒8.24a 0.00 south asia lco2 ‒0.39 ‒1.81 ‒0.91 1.95 0.97 ‒1.26 2.52 0.99 ∆ lco2 ‒6.08 a ‒6.40a 2.96a ‒2.76a 0.00 ‒3.14b ‒2.01b 0.02 lgdp ‒0.037 ‒3.24 ‒2.50 ‒1.72 0.04 ‒2.36 ‒0.12 0.45 ∆ lgdp ‒6.11a ‒6.27a ‒3.73a ‒4.54a 0.00 ‒4.05a ‒4.20a 0.00 lnre ‒0.16 ‒1.04 ‒1.03 1.67 0.95 ‒0.81 3.59 1.00 ∆ nre ‒5.50a ‒5.96a ‒2.74a ‒2.26a 0.01 ‒3.07b ‒1.84b 0.03 lre 0.10 ‒1.80 ‒1.35 0.93 0.82 ‒1.68 1.51 0.93 ∆ re ‒5.14a ‒5.37a ‒2.63b 1.99b 0.02 ‒2.82c ‒1.24c 0.10 lrent ‒0.30 ‒3.13 ‒0.97 1.81 0.96 ‒2.79 ‒1.71 0.12 ∆ lrent ‒5.83a ‒6.03a ‒4.39a ‒6.07a 0.00 ‒4.39a ‒5.01a 0.00 southeast asia lco2 ‒1.36 ‒1.84 ‒1.96 ‒0.50 0.30 ‒2.27 0.09 0.53 ∆ lco2 ‒5.82 a 6.04a ‒3.79a ‒5.12a 0.00 ‒3.81a ‒3.97a 0.00 lgdp ‒1.92 ‒1.91 ‒1.82 ‒0.17 0.43 ‒1.45 2.24 0.98 ∆ lgdp ‒6.12a ‒6.42a ‒2.67a ‒2.30a 0.01 ‒3.03b ‒2.03b 0.02 lnre ‒1.63 ‒2.55 ‒2.31 ‒1.39 0.08 ‒2.47 ‒0.44 0.32 ∆ nre ‒5.83a ‒6.30a ‒3.97a ‒5.58a 0.00 ‒3.91a ‒4.22a 0.00 lre ‒0.77 ‒2.34 ‒1.88 ‒0.30 0.38 ‒2.20 0.26 0.60 ∆ re ‒6.12a ‒6.42a ‒3.75a ‒5.02a 0.00 ‒3.91a ‒4.22a 0.00 lrent ‒0.58 ‒2.31 ‒1.52 0.60 0.72 ‒2.50 ‒0.50 0.30 ∆ lrent ‒6.11a ‒6.36a ‒3.90a ‒5.41a 0.00 ‒4.06a ‒4.61a 0.00 a,b,crepresents the significance level 1%, 5% and 10% respectively. we also reported (t-bar) and z (t-tilde-bar) statistics in the table arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirical evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020376 in all the three panels, almost all the variables represent nonstationary results at the level. nevertheless, the null hypothesis is rejected at 5% as variables represent the stationary results at first difference. thus, we can declare the similar findings both for cadf and cips. 4.3. cointegration following the first order integration of variables, further was to examine the cointegration process among variables. to do so, three traditional test, namely pedroni (2004), kao (1999), fisher proposed by (maddala and wu, 1999), were used. moreover, to handle the cross-sectional dependence and robust the traditional cointegration tests, westerlund (2007) was applied. the results of pedroni, kao and fisher panel cointegration tests are presented in table 5. in the case of south asian, southeast asian and of the full panel of the 11 countries, the results illustrated that a set of four out of seven (statistics) reject the null hypothesis of no cointegration. furthermore, kao results ensured the existing of cointegration among the variables and fisher results also support this conclusion. to robust the traditional cointegration test results, the westerlund cointegration test was also used, which even overcomes the issue of cross-sectional dependence. from, table 6 it is disclosed that the alternative hypothesis of cointegration is accepted which means that considered variables move together in the long-run. the above mentioned four cointegration methods have the same results. this merely illustrates that the long-run relationship occurs between co2 emissions, gdp, re consumption, nre consumption and nr rent in ssae region over the period considered. the results of cointegration among the variables confirm the ones of bekun et al., (2019) and shahbaz et al. (2018). 4.4. pmg regression versus mean group regression (mg) the current study aim is to examine the effect of considerable explanatory variables on economic growth and co2 emissions. first, we determined the impact of re consumption, nre consumption and nr rent on economic growth which is known as model 1. in the second model, we investigated the impact of re consumption, nre consumption, nr rent and economic growth on co2 emissions. to achieve the statements mentioned above for two proposed models, we applied pmg estimator to investigate the short and long-run dynamics in the south and southeast asian regions as pmg estimator constrains long-run coefficients to be equal across all group. in the case of the homogenous model, pmg estimator will be consistent whereas mean group (mg) estimator will be inconsistent. however, mg estimators and pmg estimators will be consistent and inconsistent respectively in case of heterogeneous model (mert and bölük, 2016). to do so first, we applied mean table 5: pedroni, kao and fisher cointegration analysis pedroni test null hypothesis: no cointegration newey-west automatic bandwidth selection and bartlett kernel economies south asia southeast asia overall statistic weighted stat statistic weighted stat statistic weighted stat within – dimension panel v 0.7515 (0.22) ‒0.3322 (0.63) 0.1929 (0.42) 0.2472 (0.40) 0.4586 (0.32) ‒0.0797 (0.53) panel rho ‒0.5826 (0.28) ‒0.1686 (0.43) 1.028 (0.84) 0.7933 (0.78) 0.8706 (0.80) 0.4107 (0.65) panel pp ‒4.2189a (0.00) ‒4.2234a (0.00) ‒4.0364a (0.01) ‒1.548c (0.06) ‒1.4410c (0.07) ‒4.1479a (0.00) panel adf ‒2.2965a (0.01) ‒3.7051a (0.00) ‒0.5058a (0.00) ‒1.1653c (0.09) ‒1.7504b (0.05) ‒3.0163a (0.00) between‒ dimension group rho 0.2820 (0.61) 1.6985 (0.95) 1.4446 (0.92) group pp ‒4.8840a (0.00) ‒5.083a (0.00) ‒7.0474a (0.00) group adf ‒3.1626a (0.01) ‒2.7371a (0.00) ‒2.8798a (0.00) kao residual cointegration test adf t-stat prob t-stat prob t-stat prob ‒3.1591a 0.0008 ‒2.9940a 0.0014 ‒4.2508a 0.0000 automatic lag length selection based on sic newey-west automatic bandwidth selection and bartlett kernel johansen fisher panel cointegration test no of cointegration trace max eigen test trace max eigen test trace max eigen test none 94.47a (0.00) 56.95a (0.00) 280.1a (0.00) 232.1a (0.00) 490.2a (0.00) 374.8a (0.00) at most 1 46.53a (0.00) 27.68a (0.00) 188.8a (0.00) 140.4a (0.00) 286.6a (0.00) 189.9a (0.00) at most 2 26.61a (0.00) 11.82 (0.29) 86.57a (0.00) 69.13a (0.00) 144.8a (0.00) 110.9a (0.00)a at most 3 24.16a (0.00) 19.29b (0.03) 33.29a (0.00) 27.27a (0.00) 60.75a (0.00) 45.82a (0.00) at most 4 20.42b (0.02) 20.42b (0.02) 24.98a (0.01) 24.98a (0.01) 53.65a (0.00) 53.65a (0.00) a,b,crepresents the significance level 1%, 5% and 10% respectively. the p-values for pedroni and fisher tests reported in parenthesis table 6: westerlund cointegration statistics south asia southeast asia full countries value z-value p-value value z-value p-value value z-value p-value gt ‒6.058 ‒7.873 0.00a ‒3.226 ‒2.002 0.02b ‒2.879 ‒1.505 0.06c ga ‒3.552 3.573 1.00 ‒8.035 1.573 0.94 ‒8.497 1.930 0.97 pt ‒9.489 ‒3.617 0.00a ‒6.360 ‒1.213 0.10c ‒5.889 ‒1.705 0.04b pa ‒5.679 2.132 0.98 ‒4.954 1.406 0.92 ‒4.487 2.108 0.98 a,b,crepresents the significance level 1%, 5% and 10% respectively l arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirica evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020 377 group regression along with pmg estimator. hereafter we used a hausman test to confirm the long-run homogeneity (blackburne and frank, 2007). the findings of the hausman test indicated the rejection of the null hypothesis in both models for all the cases such as south asian, southeast asian and full countries panels. hence, the findings of the hausman test confirmed the homogeneity of the models. it implies that the pmg estimator is more appropriate than mg estimator for different panels and models of ssea region (table 7). 4.4.1. pmg regression 4.4.1.1. long-run elasticity’s (model-1) the pmg results reported in table 8 to explain the short and long-run dynamics in the two proposed models. according to the pmg long-run results of model 1, the results show that nre and re are a significant positive contribution to economic development in all three considered panels. it is also observed that nre has a stronger impact on economic growth than re. our results for re and nre impact on economic growth are in line with (paramati et al., 2018). concerning, nr nexus economic growth results show that nr impedes the economic development for the cases of south asia and full country for 1990-2014. it means that nr slows down the economic activities in the case of south asian and overall countries. there are four main channel of transmissions to nr to slow down economic growth such as dutch disease, overconfidence, neglect of education and rent-seeking (gylfason, 2001). however, we found the inverse role of nr in economic development in the southeast asian panel. our results are consistent with (ahmed et al., 2016; ben-salha et al., 2018; sarmidi et al., 2014; satti et al., 2014). moreover, the significant negative error terms –0.47, –0.26 and –0.23 in southeast asia, south asia and full countries panels respectively confirm the long-run relationships between variables. the error correction terms show that the speed of adjustment back towards the equilibrium is corrected by 47%, 26% and 23% in southeast, south and overall country’s panels respectively in each year. 4.4.1.2. short-run analysis (model-1) for the short-run analysis, we found that only nre has a significant and positive impact on economic growth, in the case of south asia and full countries panels. however, we did not find any significant results in the case of the southeast asian region. 4.4.1.3. long-run elasticity’s (model-2) table 8 also reported the model 2 estimation, where pmg long-run results revealed that economic growth increased the co2 emissions table 7: hausman results model 1 dependent variable: economic growth economies variables coefficients (b) mg (b) pmg (b-b) difference sqrt (diag (v_b-v_b)) s. e overall lnre 0.16 1.16 –1 1.26 lre –0.62 0.02 –0.64 0.70 lrent –0.09 –0.11 0.02 0.06 chi2 (3)=(b-b)’[(v_b-v_b)–1] (b-b)=1.79, prob>chi2=0.61 south asia lnre 0.27 0.99 –0.72 0.80 lre –1.06 0.13 –0.93 0.96 lrent –0.08 –0.25 0.17 0.26 chi2 (3)=(b-b)’[(v_b-v_b)–1] (b-b)=1.89, prob>chi2=0.82 southeast asia lnre 0.07 0.47 –0.40 0.70 lre –0.25 0.21 –0.46 0.89 lrent –0.09 0.07 –0.16 0.20 chi2 (3)=(b-b)’[(v_b-v_b)–1] (b-b)=1.96, prob>chi2=0.58 model 2 dependent variable: co2 emissions economies variables coefficients (b) mg (b) pmg (b-b) difference sqrt (diag (v_b-v_b)) s. e overall lnre –0.39 1.27 –1.66 2.04 lgdp 0.76 0.35 –0.41 0.70 lre –3.94 –0.25 –3.69 5.49 lrent –0.12 0.02 –0.14 0.23 chi2 (4)=(b-b)’[(v_b-v_b)–1] (b-b)=5.01, prob>chi2=0.28 south asia lnre –2.48 1.34 –2.88 4.48 lgdp 1.06 0.40 0.66 0.99 lre –9.29 –0.04 –9.25 12.11 lrent –0.33 0.04 –0.37 0.45 chi2 (4) = (b-b)’[(v_b-v_b)–1] (b-b)=4.32, prob>chi2=0.36 southeast asia lnre 1.34 0.70 0.64 0.94 lgdp 0.50 0.26 0.24 0.31 lre 0.51 –0.42 0.93 1.03 lrent –0.04 –0.01 –0.03 0.10 chi2 (4)=(b-b)’[(v_b-v_b)–1] (b-b)=2.89, prob>chi2=0.57 b: consistent under ho and ha; obtained from xtpmg, b: i̇nconsistent under ha, efficient under ho; obtained from xtpmg and ho: difference in coefficients not systematic arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirical evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020378 in all the selected panels. it means that the economic activities deteriorated the environmental quality in ssea region. according to our first model, results suggested that nre increases economic growth. notably, nre is mostly produced by fossil fuels to fulfill the requirement of different economic activities which ultimately increases the co2 emissions. our results are consistent with almulali et al. (2015) in the case of 77 developed and developing countries. long-run elasticities of co2 emissions concerning nre consumption are 1.34%, 0.70% and 1.27% in the south, southeast and full countries panels, respectively. it means that nre deteriorated the environmental quality in the ssea region, with a higher impact on south countries. the rapid wave of urbanization is one of the causes of energy demand, which ultimately raises co2 emissions in the ssea regions. besides, the rapid changes in population in the south and southeast asian region, especially in pakistan, india, and bangladesh, lead the companies to accelerate their shifting towards this region because of cheap labor and intense market. moreover, upcoming projects increase the energy demand, the significant portion of non-renewable electricity is derived by fossil fuels which ultimately increases the co2 emissions. moreover, the impact of re on co2 emissions in long run implies that 1% increase in the re consumption improved the environmental quality 0.04%, 0.42% and 0.25% in the south, southeast asian and 11 countries panels, respectively. it means that the use of re sources mitigates the carbon emissions in the selected countries, with a remarked impact on the southeast countries. our results about nre and re impacts on co2 emissions are in line with (belaïd and zrelli, 2019; ben jebli et al., 2016; bölük and mert, 2015; inglesi-lotz and dogan, 2018; sharif et al., 2019). finally, results suggest that natural resources have significant positive impact on co2 emissions in the south asian and full countries panel. our results are consistent with bekun et al. (2019). however, in the case of southeast asian countries natural resources decrease the co2 emissions in the long-run. our findings are in line with balsalobre-lorente et al. (2018). moreover, the significant negative error terms also confirm the long-run relationships between variables in all three selected panels. 4.4.1.4. short-run analysis (model-2) moreover, in the short run analysis we did not find any significant effect of re, nre, nr rent and gdp on co2 emission for all three selected panels. 4.4.1.5. coefficient diagnostics furthermore, coefficient diagnostics test has been performed, the red mark in the center confirms that the estimation of the proposed models presents a significant confidence level (figure 1 in appendix). 4.5. dcce cs-ardl the traditional methods such as mg, pmg, fmols, dols and amg may be provided weak outcomes due to cd (chudik and pesaran, 2015; dogan et al., 2017). therefore, we also applied the dcce cs-ardl technique to calculate the coefficients of the considered variables and to robust the pmg estimation. however, we find similar signs of the coefficients, although coefficients of the variables are different than pmg estimation (tables 8 and 9 for comparision). table 8: pooled mean group regression model 1 dependent variable: gdp variables south asia southeast asia overall long-run coefficients coefficients prob coefficients prob coefficients prob lnre 0.9919a 0.0000 0.4765a 0.0002 1.1696a 0.0000 lre 0.1393c 0.0769 0.2127a 0.0022 0.0252b 0.0428 lrent ‒0.2597a 0.0000 0.0713a 0.0000 ‒0.1077a 0.0000 error correction coefficients ‒0.2676a 0.0019 ‒0.4741a 0.0006 ‒0.2346a 0.0001 short-run coefficients d (lnre) 0.5880b 0.0126 0.0327 0.7881 0.4302a 0.0009 d (lre) 0.1173 0.6216 ‒0.2790 0.1816 ‒0.0608 0.4894 d (lrent) ‒0.0016 0.7873 ‒0.0492 0.1680 0.0043 0.7197 constant 1.6127a 0.0078 2.0124a 0.0005 1.4519a 0.0002 model 2 dependent variable: co2 emissions long-run coefficients coefficients prob coefficients prob coefficients prob lgdp 0.4070a 0.0000 0.2627a 0.0000 0.3537a 0.0000 lnre 1.3489a 0.0000 0.7064a 0.0000 1.2721a 0.0000 lre ‒0.0453 0.8582 ‒0.4294a 0.0000 ‒0.2522a 0.0005 lrent 0.0430b 0.0403 ‒0.0184c 0.0910 0.0266a 0.0286 error correction coefficients ‒0.4067a 0.0064 ‒0.4894b 0.0144 ‒0.3566a 0.0002 short-run coefficients d (gdp) ‒0.8004a 0.0052 0.1562 0.8393 ‒0.0130 0.8856 d (lnre) 0.8997c 0.0926 0.1679 0.5448 ‒0.3970 0.3377 d (lre) ‒1.8111 0.2470 0.0239 0.9312 0.4186 0.1902 d (lrent) ‒0.0142 0.5751 ‒0.0812 0.1605 ‒1.0956 0.1307 constants ‒4.5572a 0.0056 ‒2.4130a 0.0093 ‒0.0511 0.1729 a,b,crepresents the significance level 1%, 5% and 10% respectively l arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirica evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020 379 table 9: dynamic common correlated effects model 1 dependent variable: gdp variables south asia southeast asia overall long-run coefficients coefficients prob coefficients prob coefficients prob lnre 0.7762a 0.000 0.8682b 0.000 0.7780a 0.000 lre 0.4292a 0.003 0.1902b 0.003 3.6441b 0.042 lrent ‒0.0003a 0.000 0.0236a 0.000 ‒0.1477b 0.050 short‒run coefficients d (lnre) 0.2237a 0.006 0.1317b 0.072 0.2219a 0.011 d (lre) 0.2063 0.322 ‒0.1253 0.524 0.0764 0.585 d (lrent) 0.0030 0.868 0.0213 0.544 ‒0.0162 0.322 model 2 dependent variable: co2 emissions long-run coefficients coefficients prob coefficients prob coefficients prob lgdp 0.4236a 0.041 8.1753b 0.051 2.9541a 0.014 lnre 1.3701b 0.071 0.6797b 0.087 0.0552 0.919 lre ‒0.3190b 0.086 ‒1.7937 0.298 ‒0.6606b 0.058 lrent ‒0.0024c 0.091 ‒0.3761c 0.101 0.2493c 0.084 short-run coefficients d (gdp) ‒1.1889 0.579 ‒1.7695 0.418 ‒1.2825 0.233 d (lnre) 2.3701 0.041 0.3202 0.420 0.9447 0.082 d (lre) 0.4002 0.862 ‒0.5632 0.263 ‒0.1040 0.842 d (lrent) ‒0.0460 0.649 ‒0.1729 0.332 ‒0.1543 0.247 a,b,crepresents the significance level 1%, 5% and 10% respectively table 10: pairwise dumitrescu hurlin panel causality test economies overall south asia southeast asia null hypothesis w-stat. z bar-stat. prob. w-stat. z bar-stat. prob. w-stat. z bar-stat. prob. lgdp ----lco2 3.29 4.28 0.00 a 6.10 3.38 0.00a 3.96 1.64 0.09c lco2 ----lgdp 0.40 ‒1.37 0.16 1.17 ‒0.93 0.34 2.22 ‒0.02 0.98 lnre ----lco2 1.91 1.58 0.10 c 3.79 1.35 0.17 2.47 0.21 0.83 lco2 -----lnre 2.35 2.43 0.01 b 3.12 0.76 0.44 2.21 ‒0.03 0.97 lre -----lco2 1.33 0.45 0.65 2.18 ‒0.05 0.95 1.98 ‒0.25 0.79 lco2 -----lre 2.25 2.24 0.02 b 4.37 1.85 0.06c 4.32 2.07 0.06c lrent -----lco2 1.94 1.63 0.10 c 4.04 1.57 0.10c 3.54 1.68 0.09c lco2 -----lrent 3.75 5.18 0.00 a 5.30 2.67 0.00a 2.41 0.15 0.87 lnre -----lgdp 0.53 ‒1.11 0.26 1.98 ‒0.22 0.81 2.84 0.57 0.56 lgdp -----lnre 3.93 5.53 0.00a 6.69 3.89 0.00a 3.73 1.66 0.09a lre -----lgdp 0.78 ‒0.63 0.52 2.43 0.16 0.86 1.23 ‒0.97 0.33 lgdp -----lre 1.92 1.61 0.09c 4.34 1.83 0.06b 2.22 1.62 0.09c lrent -----lgdp 1.32 0.42 0.66 2.60 0.30 0.75 2.37 0.12 0.90 lgdp -----lrent 2.38 2.50 0.01a 7.34 4.46 0.00a 1.87 ‒0.35 0.72 lre -----lnre 2.60 2.93 0.00a 2.88 0.55 0.57 2.43 0.18 0.85 lnre -----lre 1.20 0.19 0.84 2.79 0.47 0.63 3.10 1.64 0.08c lrent -----lnre 0.89 ‒0.41 0.67 3.24 0.87 0.38 0.93 ‒1.26 0.20 lnre -----lrent 4.04 5.74 0.00a 6.22 3.48 0.00a 3.12 0.84 0.39 lrent -----lre 1.77 1.30 0.19 2.70 0.39 0.69 4.53 2.19 0.02b lre ------lrent 4.49 6.62 0.00a 7.02 4.18 0.00a 4.10 1.78 0.07c a,b,crepresents the significance level 1%, 5% and 10% respectively and ----stands as does not homogeneously cause figure 2: causality directions south asia southeast asia overall source: ↔, → shows bidirectional, unidirectional causality between variables arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirical evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020380 4.6. pairwise dumitrescu hurlin (dh) panel causality table 10 report the causality results and figure 2 illustrate the causality direction of the selected variables in the south, southeast asian and full countries panels. for the case of south asian economies causality, results show that six significant unidirectional causalities are running from gdp to co2 emissions, gdp to re, gdp to nre, gdp to rent, nre to rent and re to rent. furthermore, we found a bidirectional causality running from co2 emissions to rent. concerning the southeast asian region, results show that significant unidirectional causality running from gdp to co2, gdp to nre, gdp to rent, co2 to re, nre to re and rent to co2 while bidirectional causality found between re and rent. lastly, full countries panel results illustrate unidirectional causality running from gdp to re, gdp to rent, gdp to co2, co2 to re, re to rent, re to nre and nre to rent, while co2 and nre, co2 and rent represent bidirectional causality. 5. conclusion and policy implications the current study tried to develop the linkages between renewable (re) and non-renewable energy (nre) consumption, economic growth (gdp), natural resources (nr) and co2 emissions in the south and southeast asian (ssea) countries for the period of 1990-2014. our empirical findings confirmed the long-run relationship by using pedroni, kao, fisher and westerlund cointegration tests in the selected panels. moreover, we examined the long-run elasticities with two proposed models by using pmg method. firstly, we explored the long-run elasticities of re consumption, (nre) consumption, and nr concerning economic growth. our results suggested that re consumption and nre consumption increased the economic growth in all panels. furthermore, in south asian and full countries panels, nr decreased the economic development in the long run. however, we found a significant and positive impact of nr on economic growth in the southeast asian region. secondly, we identified the long-run impact of re consumption, nre consumption, economic growth, and nr on co2 emissions. the findings demonstrated that nre and economic growth worsened the environment quality in all three selected panels. conversely, in the case of re consumption, results suggested that re consumption mitigates the carbon emission for all three panels. however, nr also contributed to co2 emissionsin the case of south asian and full countries panels while nr improved the environmental quality in the southeast asian region. the dh causality test was applied to examining the causal relationship. the causality results illustrated that unidirectional causality running from gdp to co2 emissions, gdp to re and gdp to nre consumption in south, southeast and overall countries panels. however, we found bidirectional causality exists between co2 emissions and natural resources. the current results lead to some policy implications. for instance, the countries should be concentrating on re sources such as wind, solar, geothermal and biomass etc. rather than nre sources to improve the environmental quality. besides, policymakers need to encourage environment-friendly projects to sustain economic growth. on the other hand, policymakers should be aware of the natural resource’s management. the best way to improve the contribution of nr in economic growth could be by decreasing corruption and improving education level. particularly, in south asian countries, natural resources can be a curse on the economic growth, while in southeast asian region, nr can be managed as an important source of economic development. as stated by sovacool (2010) asean region promoted entrepreneurial activities and private actors in the resource production process. they encourage industrialization, and each country has co-operated as an active partner to the exploration, production, and distribution process, especially with international oil and gas firms. finally, we have a few limitations for this research which will give us direction for future research. for instance, we have ignored some ghg emissions such as sulfur dioxide (so2), sulfur hexafluoride (sf6), perfluorocarbons (pfcs), hydrofluorocarbons (hfcs) and particulate matter pm2.5, pm10 as an air pollutant due to unavailability of data. moreover, we use co2 emissions per capita instead of ecological footprints and its sub-components such as biocapacity, cropland, fishing grounds, carbon footprint, grazing lands, and forest products. future studies can use these proxies of environment quality to see how the results vary across these indicators. furthermore, we have taken 11 countries out of a total of 19 ssea by dropping 8 countries due to non-availability of data between 1990 and 2014. the future study will consider the dropping countries on the availability of the data. besides, the future study can estimate the ekc hypothesis with the quadratic or cubic function. 6. acknowledgments this work was financially supported by the research unit on governance, competitiveness and public policy (uidb/04058/2020), funded by national funds through fct fundação para a ciência e a tecnologia. references adams, s., nsiah, c. (2019), reducing carbon dioxide emissions; does renewable energy matter? science of the total environment, 693, 133288. ahmed, k., mahalik, m.k., shahbaz, m. (2016), dynamics between economic growth, labor, capital and natural resource abundance in iran: an application of the combined cointegration approach. resources policy, 49, 213-221. al-mulali, u., sheau-ting, l., ozturk, i. (2015), the global move toward internet shopping and its influence on pollution: an empirical analysis. environmental science and pollution research, 22(13), 9717-9727. l arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirica evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020 381 amri, f. (2019), renewable and non-renewable categories of energy consumption and trade: do the development degree and the industrialization degree matter? energy, 173, 374-383. apergis, n., payne, j.e. (2014), the oil curse, institutional quality, and growth in mena countries: evidence from time-varying cointegration. energy economics, 46, 1-9. arshad, z., robaina, m., shahbaz, m., veloso, a.b. (2020), the effects of deforestation and urbanization on sustainable growth in asian countries. environmental science and pollution research, 27(9), 10065-10086. auty, r.m. (2001), the political state and the management of mineral rents in capital-surplus economies: botswana and saudi arabia. resources policy, 27(2), 77-86. auty, r.m. (2007), natural resources, capital accumulation and the resource curse. ecological economics, 61(4), 627-634. badeeb, r.a., lean, h.h., clark, j. (2017), the evolution of the natural resource curse thesis: a critical literature survey. resources policy, 51, 123-134. balcilar, m., ozdemir, z.a., ozdemir, h., shahbaz, m. (2018), the renewable energy consumption and growth in the g-7 countries: evidence from historical decomposition method. renewable energy, 126, 594-604. balsalobre-lorente, d., shahbaz, m., roubaud, d., farhani, s. (2018), how economic growth, renewable electricity and natural resources contribute to co2 emissions? energy policy, 113, 356-367. behera, s.r., dash, d.p. (2017), the effect of urbanization, energy consumption, and foreign direct investment on the carbon dioxide emission in the ssea (south and southeast asian) region. renewable and sustainable energy reviews, 70, 96-106. bekun, f.v., alola, a.a., sarkodie, s.a. (2019), toward a sustainable environment: nexus between co2 emissions, resource rent, renewable and nonrenewable energy in 16-eu countries. science of the total environment, 657, 1023-1029. belaïd, f., zrelli, m.h. (2019), renewable and non-renewable electricity consumption, environmental degradation and economic development: evidence from mediterranean countries. energy policy, 133, 110929. ben jebli, m., ben youssef, s. (2015), the environmental kuznets curve, economic growth, renewable and non-renewable energy, and trade in tunisia. renewable and sustainable energy reviews, 47, 173-185. ben jebli, m., ben youssef, s., ozturk, i. (2016), testing environmental kuznets curve hypothesis: the role of renewable and non-renewable energy consumption and trade in oecd countries. ecological indicators, 60, 824-831. ben-salha, o., dachraoui, h., sebri, m. (2018), natural resource rents and economic growth in the top resource-abundant countries: a pmg estimation. resources policy. available from: https://www. sciencedirect.com/science/article/pii/s0301420717304294?casa_to ken=nmn0uoqvgz4aaaaa:68xzzfxo4wn0uv4bih hlx0aljr0wwl_1z6 mjntiytthkffhkue1tdwnybq9eeg8piqfslswxta. bento, j.p.c., moutinho, v. (2016), co2 emissions, non-renewable and renewable electricity production, economic growth, and international trade in italy. renewable and sustainable energy reviews, 55, 142-155. bhat, j.a. (2018), renewable and non-renewable energy consumptionımpact on economic growth and co2 emissions in five emerging market economies. environmental science and pollution research, 25(35), 35515-35530. bhattacharya, m., churchill, s.a., paramati, s.r. (2017), the dynamic impact of renewable energy and institutions on economic output and co2 emissions across regions. renewable energy, 111, 157-167. bhattacharyya, s., hodler, r. (2014), do natural resource revenues hinder financial development? the role of political ınstitutions. world development, 57, 101-113. blackburne, e.f., frank, m.w. (2007), estimation of nonstationary heterogeneous panels. the stata journal, 7(2), 197-208. bölük, g., mert, m. (2015), the renewable energy, growth and environmental kuznets curve in turkey: an ardl approach. renewable and sustainable energy reviews, 52, 587-595. boschini, a., pettersson, j., roine, j. (2013), the resource curse and its potential reversal. world development, 43, 19-41. breitung, j. (2001), the local power of some unit root tests for panel data. bingley: emerald group publishing limited. breusch, t.s., pagan, a.r. (1980), the lagrange multiplier test and its applications to model specification in econometrics. the review of economic studies, 47(1), 239-253. british petroleum. (2018), bp statistical review of world energy. available from: https://www.bp.com/en/global/corporate/energyeconomics/statistical-review-of-worldenergy/downloads.html. brunnschweiler, c.n. (2008), cursing the blessings? natural resource abundance, ınstitutions, and economic growth. world development, 36(3), 399-419. carbon footprint. (2018), climate change. available from: https://www. carbonfootprint.com/warming.html. chen, y., zhao, j., lai, z., wang, z., xia, h. (2019), exploring the effects of economic growth, and renewable and non-renewable energy consumption on china’s co2 emissions: evidence from a regional panel analysis. renewable energy, 140, 341-353. choi, i. (2001), unit root tests for panel data. journal of international money and finance, 20(2), 249-272. chudik, a., mohaddes, k., pesaran, m.h., raissi, m. (2016), longrun effects in large heterogeneous panel data models with crosssectionally correlated errors. in: essays in honor of man ullah. vol. 36. bingley: emerald group publishing limited. p85-135. chudik, a., pesaran, m.h. (2015), common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. journal of econometrics, 188(2), 393-420. de hoyos, r.e., sarafidis, v. (2006), testing for cross-sectional dependence in panel-data models. the stata journal, 6(4), 482-496. dietz, s., neumayer, e., soysa, i.d. (2007), corruption, the resource curse and genuine saving. environment and development economics, 12(1), 33-53. ditzen, j. (2016), xtdcce: estimating dynamic common correlated effects in stata. united states: the spatial economics and econometrics centre. dogan, e. (2016), analyzing the linkage between renewable and nonrenewable energy consumption and economic growth by considering structural break in time-series data. renewable energy, 99, 1126-1136. dogan, e., seker, f. (2016), the influence of real output, renewable and non-renewable energy, trade and financial development on carbon emissions in the top renewable energy countries. renewable and sustainable energy reviews, 60, 1074-1085. dogan, e., seker, f., bulbul, s. (2017), investigating the impacts of energy consumption, real gdp, tourism and trade on co2 emissions by accounting for cross-sectional dependence: a panel study of oecd countries. current issues in tourism, 20(16), 1701-1719. dong, k., dong, x., dong, c. (2019), determinants of the global and regional co2 emissions: what causes what and where? applied economics, 51(46), 5031-5044. dumitrescu, e.i., hurlin, c. (2012), testing for granger non-causality in heterogeneous panels. economic modelling, 29(4), 1450-1460. farhani, s., shahbaz, m. (2014), what role of renewable and nonrenewable electricity consumption and output is needed to initially mitigate co2 emissions in mena region? renewable and sustainable energy reviews, 40, 80-90. frees, e.w. (1995), assessing cross-sectional correlation in panel data. arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirical evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020382 journal of econometrics, 69(2), 393-414. friedman, m. (1937), the use of ranks to avoid the assumption of normality ımplicit in the analysis of variance. journal of the american statistical association, 32(200), 675-701. granger, c.w. (1969), investigating causal relations by econometric models and cross-spectral methods. econometrica: journal of the econometric society, 37(3), 424-438. gylfason, t. (2001), natural resources, education, and economic development. european economic review, 45(4), 847-859. hadri, k. (2000), testing for stationarity in heterogeneous panel data. the econometrics journal, 3(2), 148-161. harris, r.d.f., tzavalis, e. (1999), inference for unit roots in dynamic panels where the time dimension is fixed. journal of econometrics, 91(2), 201-226. havranek, t., horvath, r., zeynalov, a. (2016), natural resources and economic growth: a meta-analysis. world development, 88, 134-151. im, k.s., pesaran, m.h., shin, y. (2003), testing for unit roots in heterogeneous panels. journal of econometrics, 115(1), 53-74. inglesi-lotz, r., dogan, e. (2018), the role of renewable versus nonrenewable energy to the level of co2 emissions a panel analysis of sub-saharan africa’s big 10 electricity generators. renewable energy, 123, 36-43. ipcc. (2014), ar5 synthesis report: climate change 2014. available from: https://www.ipcc.ch/report/ar5/syr. kao, c. (1999), spurious regression and residual-based tests for cointegration in panel data. journal of econometrics, 90(1), 1-44. kim, d.h., lin, s.c. (2017), natural resources and economic development: new panel evidence. environmental and resource economics, 66(2), 363-391. krueger, a. (1998), why trade liberalisation is good for growth. the economic journal, 108(450), 1513-1522. levin, a., lin, c.f., chu, c.s.j. (2002), unit root tests in panel data: asymptotic and finite-sample properties. journal of econometrics, 108(1), 1-24. maddala, g.s., wu, s. (1999), a comparative study of unit root tests with panel data and a new simple test. oxford bulletin of economics and statistics, 61(s1), 631-652. mert, m., bölük, g. (2016), do foreign direct investment and renewable energy consumption affect the co2 emissions? new evidence from a panel ardl approach to kyoto annex countries. environmental science and pollution research, 23(21), 21669-21681. mert, m., bölük, g., çağlar, a.e. (2019), interrelationships among foreign direct investments, renewable energy, and co2 emissions for different european country groups: a panel ardl approach. environmental science and pollution research, 26(21), 21495-21510. owusu, p.a., asumadu-sarkodie, s. (2016), a review of renewable energy sources, sustainability issues and climate change mitigation. cogent engineering, 3(1), 1167990. paramati, s.r., apergis, n., ummalla, m. (2018), dynamics of renewable energy consumption and economic activities across the agriculture, industry, and service sectors: evidence in the perspective of sustainable development. environmental science and pollution research, 25(2), 1375-1387. park, y., meng, f., baloch, m.a. (2018), the effect of ict, financial development, growth, and trade openness on co2 emissions: an empirical analysis. environmental science and pollution research, 25(30), 30708-30719. pata, u.k. (2018), renewable energy consumption, urbanization, financial development, income and co2 emissions in turkey: testing ekc hypothesis with structural breaks. journal of cleaner production, 187, 770-779. pedroni, p. (2004), panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the ppp hypothesis. econometric theory, 20(3), 597-625. pesaran, m.h. (1997), the role of economic theory in modelling the long run. the economic journal, 107(440), 178-191. pesaran, m.h. (2004), general diagnostic tests for cross section dependence in panels. united kingdom: university of cambridge. pesaran, m.h. (2006), estimation and ınference in large heterogeneous panels with a multifactor error structure. econometrica, 74(4), 967-1012. pesaran, m.h. (2007), a simple panel unit root test in the presence of cross-section dependence. journal of applied econometrics, 22(2), 265-312. pesaran, m.h., shin, y., smith, r.p. (1999), pooled mean group estimation of dynamic heterogeneous panels. journal of the american statistical association, 94(446), 621-634. pesaran, m.h., smith, r. (1995), estimating long-run relationships from dynamic heterogeneous panels. journal of econometrics, 68(1), 79-113. quah, d. (1994), exploiting cross-section variation for unit root inference in dynamic data. economics letters, 44(1), 9-19. rasoulinezhad, e., saboori, b. (2018), panel estimation for renewable and non-renewable energy consumption, economic growth, co2 emissions, the composite trade intensity, and financial openness of the commonwealth of independent states. environmental science and pollution research, 25(18), 17354-17370. sachs, j.d., warner, a.m. (1995), natural resource abundance and economic growth, working paper no. 5398. cambridge: national bureau of economic research. sachs, j.d., warner, a.m. (1999), the big push, natural resource booms and growth. journal of development economics, 59(1), 43-76. sarmidi, t., law, s.h., jafari, y. (2014), resource curse: new evidence on the role of ınstitutions. international economic journal, 28(1), 191-206. satti, s.l., farooq, a., loganathan, n., shahbaz, m. (2014), empirical evidence on the resource curse hypothesis in oil abundant economy. economic modelling, 42, 421-429. shafiei, s., salim, r.a. (2014), non-renewable and renewable energy consumption and co2 emissions in oecd countries: a comparative analysis. energy policy, 66, 547-556. shahbaz, m., naeem, m., ahad, m., tahir, i. (2018), is natural resource abundance a stimulus for financial development in the usa? resources policy, 55, 223-232. sharif, a., raza, s.a., ozturk, i., afshan, s. (2019), the dynamic relationship of renewable and nonrenewable energy consumption with carbon emission: a global study with the application of heterogeneous panel estimations. renewable energy, 133, 685-691. shaw, d.l. (2013), good governance in the post-soviet south: testing theories of the resource curse in azerbaijan. journal of politics international studies, 9, 520-561. sovacool, b.k. (2010), the political economy of oil and gas in southeast asia: heading towards the natural resource curse? the pacific review, 23(2), 225-259. westerlund, j. (2007), testing for error correction in panel data. oxford bulletin of economics and statistics, 69(6), 709-748. world bank. (2019), world development i̇ndicators. washington, dc: world bank. available from: https://www.data.worldbank.org/ country. l arshad, et al.: renewable and non-renewable energy, economic growth and natural resources impact on environmental quality: empirica evidence from south and southeast asian countries with cs-ardl modeling international journal of energy economics and policy | vol 10 • issue 5 • 2020 383 appendix south asia model 1 model 2 .0 .1 .2 .3 c( 2) -.3 -.2 0.9 1.0 1.1 c(1) c( 3) .0 .1 .2 .3 c(2) 0.8 1.2 1.6 c( 2) -.4 .0 .4 c( 3) .00 .02 .04 .06 .08 .3 .4 .5 .6 c(1) c( 4) 0.8 1.2 1.6 c(2) -.4 .0 .4 c(3) southeast asia .1 .2 .3 c(2 ) .05 .06 .07 .08 .09 .10 .2 .4 .6 c(1) c(3 ) .1 .2 .3 c(2) .64 .68 .72 .76 c( 2) -.48 -.44 -.40 -.36 c( 3) -.04 -.03 -.02 -.01 .00 .15 .20 .25 .30 .35 c(1) c( 4) .64 .68 .72 .76 c(2) -.48 -.44 -.40 -.36 c(3) overall .00 .01 .02 .03 .04 .05 c(2 ) -.12 -.10 -.08 1.15 1.16 1.17 1.18 c(1) c(3 ) .00 .02 .04 c(2) 1.1 1.2 1.3 1.4 c( 2) -.4 -.3 -.2 -.1 c( 3) .00 .01 .02 .03 .04 .05 .25 .30 .35 .40 .45 c(1) c( 4) 1.1 1.2 1.3 1.4 c(2) -.4 -.3 -.2 -.1 c(3) figure 1: coefficient diagnostics confidence interval (ellipse test) . international journal of energy economics and policy | vol 10 • issue 4 • 2020184 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(4), 184-193. reform in a limbo: the politics and politicization of reforms in nigeria’s petroleum sector agaptus nwozor1*, john shola olanrewaju1, solomon a. adedire1, ejalonibu ebenezer lawal2 1department of political science and international relations, landmark university, omu-aran, kwara state, nigeria, 2department of political science, federal university, lokoja, nigeria. *email: nwozor.agaptus@lmu.edu.ng received: 07 december 2019 accepted: 04 april 2020 doi: https://doi.org/10.32479/ijeep.9085 abstract nigeria has been on a long-winding journey to reform its petroleum sector with no end in sight. the first version of the reform bill, the petroleum industry bill (pib) was sent to the national assembly in 2008. the sustained opposition to the pib from both indigenous and international oil companies as well as other stakeholders led to the decision, in 2016, to balkanize it into four bills, with each bill focusing on an aspect of the reform. the first of the quadripartite bills, the petroleum industry governance bill (pigb) was passed by both chambers of nigeria’s national assembly and transmitted to the president for assent. the president declined assent, thus deepening the uncertainty that characterizes the sector. drawing data from primary and secondary sources, the paper evaluates the trajectory of nigeria’s petroleum sector reform, including the long delay and its impact on the sector. it finds that the delay in passing the reform bills has negatively rubbed off on the country as it has stymied growth and closed off new investments. the paper advocates the depoliticization of the reform agenda in order to reposition the country’s petroleum sector for national development. keywords: petroleum sector reform, petroleum industry governance bill, national development, nigeria jel classifications: p28, p48, q35, q38, q48 1. introduction oil occupies an important place in the political economy of nigeria. for one, nigeria is the largest oil producer in africa and the tenth largest in the world. secondly, it is the major source of the country’s foreign exchange earnings: the sector accounts for over 95% of nigeria’s total foreign earnings and 85% of total government revenue (ministry of budget and national planning, 2017 ). lastly, with an average daily production of 1.92 million barrels/day and 36,972 billion barrels of proven oil reserves, nigeria occupies the 10th spot among countries with the largest crude oil reserves in the world (opec, 2019) as well as projected to be the 40th largest economy in the world (cbn, 2011; afdbg, 2013). although nigeria’s stock of proven crude oil reserves dropped by 1.3% from its 2017 level of 37,453, the aspiration of the government to expand the volume of the country’s proven oil reserves to the 40-billion-barrel mark and beyond by 2020 is still vigorously emphasized (ejoh, 2017; opec, 2019). despite the key role that petroleum resources play in nigeria’s economy, the sector is plagued with multifarious problems, chief among them being undue political interference and attendant erosion of accountability. another serious problem with the sector has been lack of confidence by industry observers and stakeholders resulting in the loss of critical investments necessary to grow the sector to other countries (shosanya, 2015). on the basis of the foregoing, pressures were mounted by major stakeholders for far-reaching reforms, hence the pioneering efforts in this regard by former president olusegun obasanjo in 2000 (neiti, 2016). the initial bill transmitted to the national assembly in 2008 for the reform of the petroleum sector was an omnibus executive bill known as the petroleum industry bill (pib). essentially, the key objective of the pib is the enthronement of international best practices through the comprehensive review and harmonization of all legal instruments governing the petroleum sector as well as the establishment of strong institutions that transcend individual this journal is licensed under a creative commons attribution 4.0 international license https://doi.org/10.32479/ijeep.9085 nwozor, et al.: reform in a limbo: the politics and politicization of reforms in nigeria’s petroleum sector international journal of energy economics and policy | vol 10 • issue 4 • 2020 185 or group manipulation (abuh, 2019). the establishment of strong institutions will definitely eliminate bad governance that motorizes inefficiency, rent-seeking and corruption in the petroleum sector. as a result of concerted opposition to the pib by stakeholders, no consensus was reached to enable its passage. it took a total 10 years and several revisions of the pib, including its balkanization into four separate bills (namely the petroleum industry governance bill, petroleum industry fiscal bill, petroleum industry administration bill, and petroleum host and impacted community bill) for a headway to be made in 2018. the idea behind the balkanization of the pib was to facilitate their easy passage. however, the breakthrough that was recorded in 2018 in terms of the passage of the first of the quadripartite bills, the petroleum industry governance bill (pigb) and its subsequent transmission to the president for assent was a stillbirth as it was returned back to the national assembly without being assented to. this paper evaluated the trajectory of reform efforts in nigeria’s petroleum sector since the initial groundwork was laid in 2000. the evaluation was guided by the question about whether indeed the governance and institutional structures in nigeria’s petroleum sector were inadequate and out of sync with global best practice to necessitate a reform. a related preoccupation of the paper was whether the delays in passing the bills necessary to spearhead the reforms in the petroleum sector were justifiable. in engaging with the questions that formed the fulcrum of this study, the paper adopted key informant interview (kii) to generate its primary data. the study was further enriched with secondary data generated from archival materials. the paper found that major stakeholders are favorably disposed to a comprehensive overhaul of the governance and institutional structures of the petroleum industry. there is unanimity in the positive impacts that reform would bring to the petroleum sector. the paper also found that the age-long delays in passing the reform bill created uncertainties, which negatively impacted on the sector in terms of lost investments, inability to meet the target for the expansion of crude oil reserves and lack of new investments in the sector. 2. efforts at oil sector reforms since 1999 the discovery of oil in commercial quantities in nigeria in 1956 and the subsequent appreciation of its price in the international oil market in the 1970s, led to a gradual abandonment of the range of agricultural produce, such as groundnut, cocoa, rubber and palm produce that had hitherto constituted the country’s economic mainstay. the emphasis on oil, which led to the erosion of the agricultural sector created the dutch disease in the nigerian economy. the dutch disease syndrome that characterized the nigerian economy during the 1970s diminished the role of the agricultural and manufacturing sectors in national development (olusi and olagunju, 2005; otaha, 2012). apart from the retreat of these sectors in contributing to the foreign exchange earnings of nigeria, the rentier system that emerged also created loopholes that undermined the effectiveness of harnessing the oil sector for national development (ikpeze et al., 2004). additionally, the non-adoption of international best practices in oil exploration and exploitation by operators created serious environmental crisis in the niger delta, thus triggering host community agitations and other forms of insecurity (nwozor, 2019a, nwozor et al., 2019b). the nigerian oil and gas sector is characterized by all manner of sharp practices, which created the imperative for its reform. the expectation was that the reform would induce the modernization of the sector and ultimately have multiplier effects on other sectors of the nigerian economy (adelegan, 2017). the imperative of a reform was underpinned by the disconnect between the petroleum sector and other sectors of the economy. in other words, the petroleum sector did not have the desired impact in terms of generating employment and contributing to the diversification of other sectors of the economy. the failure of oil and gas to induce economic growth and development necessitated the various attempts at reforms since 1999. the obasanjo administration set up the oil and gas reform committee (ogrc) on april 24, 2000 under the headship of the then honorary special adviser on energy and strategic matters, rilwanu lukman, to undertake a comprehensive study of the oil and gas industry, with the ultimate aim of reforming the sector. the major idea behind the attempt at reforming the petroleum sector was to boost nigeria’s development by ensuring the appropriate and transparent management of oil revenues (iledare 2008). the ogrc evolved a national oil and gas policy (nogp) whose thrust was the restructuring of the oil and gas sector on the basis of separating commercial institutions from the regulatory and policy-making institutions (iledare, 2008). on june 21, 2005, the government constituted the oil and gas implementation committee (ogic) to oversee the development of strategies for the implementation of the reform agenda in the nogp document (neiti, 2016). another area that obasanjo attempted to institute reform was the governance structure of the oil and gas sector, which was characterized by corruption. as part of efforts to deal with the corruption that typified the sector and thus enthrone transparency, accountability, and good governance, nigeria adopted the principles of the extractive industry transparency initiative (eiti) through the neiti act signed into law by obasanjo on may 26, 2007. the diligent implementation of the act led to the declaration of nigeria as eiti compliant in march 2011 (afdbg, 2013). however, the obasanjo administration left a lot of unfinished business with regard to the reform of nigeria’s oil and gas sector. former nigerian president between 2007 and 2010, umaru musa yar’adua, inherited the task of revitalizing the pursuit of reforms in the oil and gas sector from his predecessor, former president obasanjo’s immediate successor, inherited the task of revitalizing the pursuit of reforms in the oil and gas sector. yar’adua reconstituted the ogic on september 07, 2007. to ensure continuity, the yar’adua administration reappointed lukman as the chairman of the committee. the mandate of the committee was to transform the oil and gas industry through the instrumentality of the nogp, which had been approved by the federal executive council, into a model of functionality that ensures a long-term sustainability of the sector; greater efficiency, effectiveness and global competitiveness (neiti, 2016; nwapi, 2020). the lukman committee submitted its report on august 3, 2008 and this formed the basis for the pockets of reforms in the oil and gas sector, especially the petroleum industry bill (pib). nwozor, et al.: reform in a limbo: the politics and politicization of reforms in nigeria’s petroleum sector international journal of energy economics and policy | vol 10 • issue 4 • 2020186 further attempt at reform led to the passage of the nigerian oil and gas industry content development act on april 22, 2010 with focus on broadening indigenous participation in the oil and gas sector (nwaokoro, 2011). table 1 below shows the key phases of the tortuous timelines of the pib. as at the end of 2019, no aspect of the reform bill has been concluded. the goodluck jonathan administration (2010-2015) initiated a development initiative codenamed the transformation agenda. the agenda was conceptualized as a medium-term development plan to holistically address the challenges of development in nigeria with the target being to transform and usher the country into the league of twenty largest economies in the world by 2020 (npc, 2013; afdbg, 2013). the major thrusts of the transformation agenda with regards to the oil and gas sector reforms revolved around: i. deregulating the oil sector with a view to promoting robust private sector investment ii. promoting the adoption of environmentally-friendly exploration and exploitation methods by oil sector operators iii. strengthening capacity building programs especially in core technical areas as part of national strategies for local content development iv. eliminating the menace of gas flaring with a view to achieving multiplier goals in terms of reducing pollution, increasing revenue and ensuring adequate gas supply for domestic use and power generation (npc, 2011). the oil and gas sector reforms under the auspices of the transformation agenda focused on both the upstream and downstream subsectors. driving reforms in the upstream subsector with expected multiplier effect on the downstream sector was the petroleum industry bill (pib). similarly, neoliberal reforms, anchored on subsidy removal and the establishment of the subsidy reinvestment and empowerment programme (sure-p) constituted the ensemble of reforms in the downstream sector (amakom, 2013). 3. the urgency of a comprehensive reform and the pib as the flagship reform in nigeria’s petroleum sector the rationale behind the introduction of the pib centered on strengthening the oil and gas sector in order to contribute more to the nigerian economy. thus, the key idea was to evolve an omnibus legal framework to anchor the various legislative, regulatory and fiscal policies in the country with a view to effectively dealing with oil exploration and exploitation fallouts as well as leveraging on the sector to deal with the challenges of pervasive corruption and lack of transparency (gboyega et al, 2011; usman, 2016). there was a consensus among stakeholders and political elites about the need to reform the oil and gas sector to deal with the perennial challenges of lack of transparency, accountability, and good governance. notwithstanding the consensus among stakeholders, the pib, which was designed to spearhead this reform, had many controversial provisions that attracted opposition (usman, 2016). the result was that its enactment into law was stalled in the national assembly for 10 years. 3.1. the pib: anatomizing the key issues the pib represented a major move by the government to catalyze the transformation of nigeria’s oil and gas sector. the pib was an all-encompassing legislation that tended to unify and encapsulate the various laws in the oil and gas sector for the purpose of effective regulation. the pib consisted of a single coherent document that embodied over 16 legislative and administrative instruments as well as the regulatory and fiscal policies and institutions governing nigeria’s petroleum industry (neiti, 2016; usman, 2016). the pib has been in the works since 2008 with all manner of controversies surrounding its fiscal and non-fiscal objectives. in 2008, the pib was sent to the national assembly as an executive table 1: a summary of the long-winding journey of the pib timeline key action/deliverable april 2000 president obasanjo inaugurated the oil and gas reform committee (ogrc) on april 24, 2000 under the headship of the then honorary special adviser on energy and strategic matters, rilwanu lukman june 2005 the ogrc evolved a national oil and gas policy (nogp). the obasanjo government constituted the oil and gas implementation committee (ogic) to implement the recommendations of the reforms committee as contained in nogp september 2007 president umaru yar’adua, approved the national oil and gas policy (nogp), and reconstituted the ogic to implement the nogp september 2008 a petroleum industry bill (pib) was presented to the 6th national assembly january 2012 the presidency under goodluck jonathan raised a task force to evaluate the bill, which was further enhanced and re-presented to the national assembly july 2012 the report of the special taskforce was submitted to national assembly after approval by the federal executive council november 2013 national assembly concludes public hearing on pib 2014 revised version of pib was again presented to the national assembly, owing to confusion due to conflicting versions in circulation 2016 nigeria’s eight legislative assembly broke the pib into four separate bills in order to minimize opposition, namely, the petroleum industry governance bill (pigb), petroleum industry fiscal bill (pifb), petroleum industry administration bill (piab), and petroleum host and impacted community bill (phicb) april 2016 petroleum industry governance bill (pigb) was laid before the senate/house of representatives may 2017 the nigerian senate passed the senate version of the pigb. january 2018 the house of representatives passed the house version of the pigb. march 2018 the two versions of the pigb were harmonized and passed by both chambers of the national assembly july 2018 the harmonized copy of the pigb was transmitted by the national assembly to the president for assent on 3 july july 2018 the president communicated his decision to decline assent to the pigb on grounds of constitutional and legal inadequacies on 29 july compiled by the authors from several sources nwozor, et al.: reform in a limbo: the politics and politicization of reforms in nigeria’s petroleum sector international journal of energy economics and policy | vol 10 • issue 4 • 2020 187 bill. the opposition to some aspects of its provisions, especially from investors and stakeholders, made the government to take a second look at it through a federal inter-agency technical review team. the inter-agency team headed by tim okon (the then nigerian national petroleum corporation’s group general manager on corporate planning and strategy) submitted its report in 2010, which stirred more controversies as it introduced more stringent fiscal provisions that guaranteed a higher share of oil revenues to the nigerian state. the controversies surrounding the pib were very deep, considering that in 2011 three versions of the bill existed, namely the version presented by the executive, the version adopted by the senate and the one adopted by the house of representatives (pérouse, 2014). in addition, there were disagreements among members of the national assembly on whether to continue where the sixth legislative assembly (20072011) stopped or to request the re-presentation of the bill afresh for consideration. but the presidency raised a task force to evaluate the bill, which was further enhanced and re-presented to the national assembly on 19 july 2012 (pérouse, 2014). the 2012 version of the pib was an elaborate document designed to correct all that was wrong with nigeria’s oil and gas sector (afdbg, 2013; usman, 2016). it was a 223-page tome divided into nine parts comprising 362 sections and five schedules, which covered the broad spectra of the oil and gas sector. the overarching objectives of the pib centered on creating a conducive operational environment that would be promotive of safety and protective of the environment, optimizing revenues accruing to the government and evolving a progressive fiscal framework that would encourage further investment in the petroleum industry (the petroleum industry bill, 2012). the pib was designed to update, modernize and streamline earlier legislations that no longer met the watermark of international trends in the oil and gas industry. the outdated legislations to be replaced included the petroleum profit tax act of 1959, amended in 1967, 1970, 1973 and 1979; mineral oils (safety) regulations, 1963; oil pipeline act 1956, amended in 1965; petroleum act 1969 and petroleum (drilling and production) regulations, 1969 with amendments in 1973, 1979, 1995, 1996 and petroleum (amendment) decree 1996; the nigerian national oil corporation (nnoc) decree no 18 of 1971; nigerian national petroleum corporation decree 1977; associated gas re-injection decree 1979, amended in 1985 and the associated gas framework agreement (agfa) of 1992; financial (miscellaneous taxation provision) act of 1998; financial (miscellaneous taxation provision) amendment act of 1999; nigeria liquefied natural gas (nlng) act of 1999; downstream gas act (dga) and natural gas fiscal reform (nagfra) act of 2005 (section 354, the petroleum industry bill, 2012). on the basis of its elaborate provisions, the pib represented not only the most detailed framework for boosting nigeria’s petroleum revenue system but also a platform for repositioning the nigerian state as a major player in the oil and gas sector (afdbg, 2013; pérouse, 2014). essentially, the pib was designed to holistically address fiscal and non-fiscal aspects of the oil and gas sector. the fiscal aspect was envisaged to expand the country’s revenue base and thus put more money into the coffers of the government while cutting down associated wastes. the strategies for achieving this fiscal objective included simplifying the collection of government revenues; creaming off windfall profits in case of high oil prices; collecting more revenues from large profitable fields in the deep offshore waters; and, creating employment and business opportunities, by encouraging investment in small oil and gas fields (ukiwo, 2018). the philosophy that underpinned the fiscal reform in the pib was motorized by three major considerations: the first was the imperative to expand revenue accruals from oil due to the projections of global oil peak and decline as well as the forecasts that nigeria’s proven crude oil reserve could last between 40 and 50 years (peterside, 2004; akuru and okoro, 2011). the second was the need to plug various loopholes through which enormous oil revenues were lost on daily basis (afdbg, 2013; neiti, 2016). the third, and lastly, was the urgent need to prudently manage and maximize accruals from crude oil and gas in order to ensure the diversification of the economy and the deepening of the country’s socio-economic development (gboyega et al., 2011). notwithstanding projections of peak and decline in nigeria’s oil reserves, the quest of the government to expand the country’s proven oil reserves to the 40-billion-barrel mark by 2020, the discovery of new oil fields and the development of technologies for recovering additional supplies have all rolled back the dismal picture of dry oil wells in the nearest future (akuru and okoro, 2011; ejoh, 2017). 3.2. the 2012 pib: evaluating the fiscal and non-fiscal aspects relying on an extensive revision of allowable deductions for tax purposes, the fiscal framework in the pib devised a simplified collection format. under the proposed arrangement, only direct costs incurred in petroleum operations would be eligible for deductions. thus, the emphasis was on a progressive fiscal framework that would encourage further investment in the industry whilst increasing accruable revenues to government (section 1[d], the petroleum industry bill, 2012). the fiscal reform proposed the replacement of the cost-based incentives with production-based incentives based on the consideration that government revenues are impacted by oil production and efficient cost management. the implication of this was the imposition of strict discipline on cost escalations and “de-incentivization” of gold-plating. the tax computation was simplified with no company likely to enjoy tax exemption. the oil companies would pay tax on a percentage of the chargeable profits as follows: 50% for onshore and shallow water areas and 25% for frontier acreage and deep-water areas (section 313, subsection 1, the draft petroleum industry bill, 2012). one of the major flaws in the fiscal provisions in the 2012 version of the pib was the omission of some important provisions that were in earlier versions. for example, earlier versions of the pib provided for priced-based progressive royalties. but this was missing in the pib 2012 version. within the context of priced-based progressive royalties, the share of accruable royalties would increase in line nwozor, et al.: reform in a limbo: the politics and politicization of reforms in nigeria’s petroleum sector international journal of energy economics and policy | vol 10 • issue 4 • 2020188 with high oil and liquefied natural gas (lng) prices beyond a certain threshold. the idea was to capture windfall revenues during high oil price situations. analysts considered the omission as a serious basis for loss to the nigerian economy considering that in situations of high prices and associated windfalls only oil and gas companies would benefit to the detriment of the country (van meurs, 2012). this omission detracted from one of the key objectives of the pib in terms of optimizing the revenues accruing to the country. another serious flaw in the 2012 pib was the retention of the current practice that created loopholes for stealing nigerian oil and gas. oil theft in various dimensions have always being a major challenge in nigeria’s oil sector. for instance, a recent report by the nigerian extractive industries transparency initiative (neiti) indicated that between 2009 and 2018, nigeria lost about us$41.9 billion to oil theft (neiti, 2019). the oil thieves normally exploit various systemic loopholes in both the upstream and downstream subsectors. according the neiti report already referred to, the breakdown of the losses indicated that nigeria lost over 505 million barrels of crude oil and 4.2 billion liters of refined petroleum products valued at $40.06 billion and $1.84 billion respectively. a further breakdown showed that while crude oil theft accounted for about us$38.5 billion, the domestic crude losses and refined petroleum product losses accounted for us$1.56 billion and us$1.84 billion respectively (neiti, 2019). a disaggregated picture of the average losses to the nigerian economy in the past 10 years showed a consistent daily loss of us$11.47 million daily or monthly loss of us$349 million or yearly loss of us$4.2 billion dollars. the current operational modalities in the oil industry tend to create exploitable loopholes for oil thieves. under the current arrangement, the measurement of petroleum production output is done at a point down the line where oil or gas is delivered or sold, that is at the terminals instead of at the wellheads of flow stations (van meurs, 2012; katsouris and sayne, 2013; nnodim, 2019). what this means is that the figures often presented by regulatory agencies are estimates as there is no appropriate method of measuring the amount of oil exploited in order to accurately calculate the amount stolen at the source. this practice is contrary to international practice of measuring oil and gas production in the fields, directly where oil or gas leaves the field area (van meurs, 2012). the retention of the current practice in the 2012 pib created a distinct possibility that the stealing and diversion of oil or gas before it is measured would continue. the 2012 pib also has non-fiscal provisions, which essentially targeted the institutional and policy-making frameworks of the oil and gas industry. there is a general agreement among stakeholders and the government about the inadequacy of contemporary institutions in nigeria’s oil and gas sector to drive any major change or reposition the sector for enhanced role. the central issue in institutional reform was the unbundling of the state-owned national oil company, the nigerian national petroleum corporation (nnpc). the rationale for the proposal was to enable the separation of functions necessary for effectiveness and efficiency in the sector. this entailed the distribution of the functions of policy formulation, regulatory, monitoring, and commercial operations to various institutions. according to the 2012 pib, the unbundling of the nnpc would lead to the creation of some specialized companies whose focus would cover the development and promotion of indigenous operational capacity; the management of joint ventures (jv) and other nnpc’s assets; and catering for domestic gas marketing and gas infrastructure development. other areas of focus included the regulation of oil and gas production, enforcement of laws, granting of licenses and carrying out bid licensing rounds; carrying out duties hitherto performed by nnpc’s frontier exploration service as well as assisting the minister of petroleum resources in formulating strategies; and the regulation of the downstream sector (the draft petroleum industry bill, 2012). another aspect of the non-fiscal reform was the provision for the creation of the petroleum host community fund (phcf) (sections 116-118, the petroleum industry bill, 2012). this represented a novel provision that conferred relevance to communities where oil wells are domiciled. it was essentially designed to create a sense of communal ownership of oil installations, provide resources for developmental assistance and curb restiveness and militancy in oil producing communities. the phcf was envisaged to be funded by upstream petroleum companies through the remittance of 10% of their net profits from operations in the onshore areas and in the offshore shallow water areas directly into the phcf on a monthly basis. the caveat in the bill was that communities would be disqualified from benefitting from the fund if there was any act of vandalism, sabotage of the upstream facilities allocated to them or civil unrest. under such circumstance, the erring community would forfeit its entitlement, which would be diverted to the repair and remediation of associated damages (section 118[5], the draft petroleum industry bill, 2012). 3.3. opposition and contending issues in the 2012 pib despite the acknowledgement by stakeholders, industry operators and analysts about the elaborateness and necessity of the 2012 pib, its consideration in the national assembly was stalled due to opposition to some of its provisions as well as concern about profitability and long-term sustainability of production by oil companies (ugwuanyi, 2013; pérouse, 2014). notwithstanding the assurances by the government that the proposed changes in the fiscal architecture in the petroleum sector would still yield the same level of profitability as well as improve the economics of small fields significantly through generous production allowances and smaller royalty rates, the controversies and opposition to the bill continued, which ultimately blocked its passage into law. the international oil companies (iocs) and other stakeholders as well as some segments of the nigerian state stoutly opposed the 2012 pib for various reasons. operating under the aegis of oil producers trade section (opts), 18 international and indigenous oil companies in nigeria mounted sustained opposition to the pib. while agreeing that the pib possessed a unique opportunity to resolve the numerous challenges confronting the oil and gas sector, the opts posited that its provisions tended to aggravate rather than resolve them, thus potentially threatening investment potentials in nwozor, et al.: reform in a limbo: the politics and politicization of reforms in nigeria’s petroleum sector international journal of energy economics and policy | vol 10 • issue 4 • 2020 189 the sector (ugwuanyi, 2013; wahab and diji, 2017). the crux of their opposition was the fiscal regime in the pib, which the opts considered very harsh. the contention of the opts was that the proposed fiscal regime in the pib significantly increased royalties and taxes instead of balancing them in terms of high royalties with lower taxes and vice versa. the group held that the proposed fiscal regime would increase their operational cost, undermine the profitability of their operations and serve as a disincentive, which ultimately would shut out investments necessary to grow the oil sector (sweet crude report, 2013; wahab and diji, 2017). another area of contention was the gas sub-sector. the opts said the low-regulated domestic gas price, the enormous expenditure required to develop gas infrastructure and the high tax rate of 80% would create serious impediments to investment. their recommendation was anchored on an incentive-based approach to domestic obligations as the best way to achieve the gas development and gas revolution needed by nigeria (sweet crude report, 2013). other areas of concern highlighted by the opts and stakeholders like neiti included: the difficulty that would arise in connection with oil exploration and exploitation due to the limiting of license area to field size with only a small perimeter boundary; retroactive provisions that conduce to the reversal of clauses in existing contracts to reflect the new fiscal regimes; the revocation of acreage that is yet to be developed by the allocated owners; extensive powers conferred on the minister; and agitation for regulatory independence (sweet crude report, 2013; wahab and diji, 2017). in addition to the foregoing opposition mounted by mnocs and neiti to the pib, some former northern governors notably, mu’azu babangida aliyu of niger and ramalan yero of kaduna states as well as the northern caucus in the national assembly kicked against the proposed 10% host community fund (sweet crude report, 2013; ugwuanyi, 2013). they opposed the pib on two interrelated grounds: firstly, that the niger delta already has a plethora of platforms through which it is adequately catered for, such as 13% statutory derivation from the federation account, the federal budgetary allocation to the ministry of niger delta, the niger delta development commission (nddc), and the niger delta amnesty program. and lastly, that the proposed 10% earmarked for oil-producing communities might negatively affect the fiscal health of their states owing to the attendant loss of 10% of national income to the phcf (ugwuanyi, 2013). the revenue mobilization allocation and fiscal commission (rmafc) also opposed the phcf on the ground that it would put pressure on its purse (sweet crude report, 2013). 4. road to a compromise: balkanizing the pib for national support since 2008 when the pib was first sent as an executive bill to the national assembly, it had undergone several modifications, the major one being in 2012. however, the sixth and seventh legislative assemblies of nigeria’s national assembly were unable to broker national consensus to pass it into law. the impasse that dogged the pib was demonstrative of how strongly the various interests that opposed some of its provisions felt about them and how unwilling they were to see the bill become law. from the various submissions of the various interest groups ranging from the iocs, indigenous operators, regulators to other stakeholders, it was deducible that while they supported a holistic reform of the oil sector, and by extension the proposed pib, yet they were strongly opposed to several of its provisions. within the context of the foregoing, the eighth legislative assembly (2015-2019) adopted the strategy of breaking the omnibus bill into different thematic bills. the non-passage of the pib has had implications on the oil sector in particular and the nigerian economy in general. analysts have contended that the non-passage of the pib created uncertainty in the oil sector, thus leading to the deferment of core investments, decline in revenues accruing to the government, contraction in the production and reserve profiles, and the erosion of the country’s competitive attractiveness in the gas sector (neiti, 2016; wahab and diji, 2017). the direct consequence of these developments has been the loss of investments to such countries as ghana, kenya, sierra leone, tanzania and uganda, with the worth of such foregone investments estimated at over us$100 billion (shosanya, 2015; neiti, 2016). the estimated rate of loss in terms of withheld or diverted investments due to the non-passage was us$15 billion annually (the nation, 2017; asu, 2018). on the whole, analysts have estimated that nigeria has lost over us$200 billion directly and directly as a result of the non-passage of the pib (neiti, 2016; the nation, 2017). these losses prompted the eight legislative assembly to seek for ways to address the logjam that blocked the processing of the pib. the way out of the logjam was the balkanization of the bill into parts to facilitate quick legislative reviews and passage. thus, in 2016, the pib was broken into four separate bills in order to minimize opposition, manage areas of controversy and contention against it and fast-track its passage into law (asu, 2018). the emerging bills from this arrangement are the petroleum industry governance bill (pigb), petroleum industry fiscal bill (pifb), petroleum industry administration bill (piab), and petroleum host and impacted community bill (phicb). the strategy of the national assembly is to process these bills one after the other starting with the petroleum industry governance bill (pigb). it would appear that the choice of starting with the pigb was predicated on the overall trajectory of the opposition to the hitherto pib. in other words, the pigb presented a more promising prospect of success in terms of garnering support necessary for its passage. the nigerian senate and house of representatives passed the pigb on may 25, 2017 and january 17, 2018 respectively (ovuakporie, 2018). after the harmonization of the two versions of the pigb passed both chambers of the national assembly in march 2018, it was transmitted to the president for his assent. however, the president declined assent to the bill. 4.1. the key thrust of the pigb the pigb is one of the quadripartite bills carved out from the erstwhile omnibus pib. the pigb focuses on reforming the governance and institutional framework of the oil and gas sector. nwozor, et al.: reform in a limbo: the politics and politicization of reforms in nigeria’s petroleum sector international journal of energy economics and policy | vol 10 • issue 4 • 2020190 figure 1 shows the major objectives of the pigb. the pigb is generally seen as an important piece of legislation with potential to facilitate the influx of massive investments into nigeria’s oil and gas sector. the pigb’s emphasis is the overhauling of the governance and institutional framework of the industry in terms of: i) complete unbundling of the nnpc ii) replacing the nnpc with three entities that would assume responsibility for various aspects of its liabilities. these new entities include: the national petroleum company (npc) to handle joint venture assets in the upstream sector; the nigeria petroleum assets management company (npamc) saddled with overseeing the production sharing contract assets; and the nigerian petroleum liability management company (nplmc) which would assume the responsibility of managing the liabilities of the nnpc and the pensions liabilities of the department of petroleum resources (dpr) iii) establishing additional entities, namely, the ministry of petroleum incorporated (mopi) and nigeria petroleum liability management company, from the ashes of the nnpc iv) fusing the current dpr, petroleum product pricing regulatory agency (pppra) and the petroleum inspectorate into a new independent regulatory commission known as the nigerian petroleum regulatory commission (nprc) v) imposing 5% levy on all fuel sold and distributed in nigeria subject to the approval of the minister of petroleum resources vi) establishing petroleum equalization fund (pef) whose sources of funding include the 5% fuel levy, subventions, fees and charges for services rendered as well as the net surplus revenues recovered from petroleum products marketing companies (figure 2). a major the departure of the pigb from previous legislations in the petroleum sector is in the drastic reduction of the powers vested in the office of the minister of petroleum resources. in sundry legislations guiding operations in the petroleum industry, the minister exercises discretionary powers that span granting, renewing, extending or revoking licenses and leases for oil exploration and exploitation. in the pigb, the powers hitherto exercised by the minister, namely, issuance, renewal or cancellation of licenses, leases or grants are vested in the nigeria petroleum regulatory commission (nprc). the nprc serves as the petroleum industry’s supervisory body. within its ambit, the nprc is empowered to exercise powers and perform functions within the purview of the dpr, pppra, and the petroleum inspectorate. the nprc, as a successor regulator, assumes the assets and liabilities of the replaced agencies. 4.2. the politics within: different interpretations of presidential decline following the passage of the pigb by both chambers of the national assembly and subsequent harmonization in march 2018, the national assembly transmitted the harmonized bill to the president on july 03, 2018 for his assent (umoru, 2018). the transmission of the pigb (the first of the quadripartite bills on the reform of the petroleum sector) to the president for assent represented some sort of victory considering that it took 10 years for this accomplishment. the president literally shocked industry observers and stakeholders when, on july 29, 2018, he communicated his decision to decline assent to the pigb on grounds of constitutional and legal inadequacies (the nation, 2018). the areas of conflict raised as underpinning the presidential decline are: i. the provision empowering the nprc to retain 10% of the revenues generated on behalf of the government (as contained in section 26[3] of the harmonized pigb). the president believes that this provision would lead to an increment in the funds available to the commission while concomitantly starving governments across all levels of needed revenues ii. the expansion of the scope of the petroleum equalization fund (pef) and inclusion of some provisions, which place the fund at variance with the economic policy thrust of the buhari administration iii. legislative drafting anomalies with potentiality to create ambiguities, which could lead to conflicts in interpretation (the nation, 2018; adetayo, 2018). minister nigerian petroleum liability management company (nplmc) ministry of petroleum incorporated (mopi) nigeria petroleum regulatory commission (nprc) nigerian petroleum assets management company (npamc) petroleum equilization fund (pef) national petroleum company (npc) figure 2: key institutional frameworks in the petroleum industry governance billcreate efficient and effective governing institutions framework for creating commercially-oriented and profitdriven petroleum entities promote transparency and accountability in the administration of petroleum resources foster a conducive business environment for petroleum industry operations figure 1: major objectives of the petroleum industry governance bill nwozor, et al.: reform in a limbo: the politics and politicization of reforms in nigeria’s petroleum sector international journal of energy economics and policy | vol 10 • issue 4 • 2020 191 some analysts have contended that the nprc seems like a new behemoth replacing another behemoth, the nnpc. the pigb endows the nprc with enormous powers, which in the view of industry observers and analysts could spawn the ground for abuse and bureaucratic inefficiency (sdn, 2018). but beyond this speculation, the president’s justification is that the retention of 10% by the nprc would unduly increase its financial profile to the detriment of accruable revenues to the federal government as well as other component units consisting of states, federal capital territory (fct) and local government councils. the implication, therefore, is that the percentage of revenue to be retained by the nprc should be pruned down so as not to create cash crunch for the various level of government. a 2018 report on the viability of nigeria’s 36 states showed that 17 states were insolvent as their internally generated revenues (igr) constituted <10% of their receipts from nigeria’s federation account (odunsi, 2019). the insolvency of the majority of states in nigeria due to their weak capacity to generate reasonable volume of revenue within their states is responsible for their dependence on federal allocations for survival. in other words, without monthly receipts from the federation account, many states would be unviable and incapable of meeting their financial obligations including paying salaries of their workforce (odunsi, 2019; izevbigie and ebohon, 2019). apart from possible reduction in the accruals to the various governments, some analysts have contended that the proposed retention of 10% by nprc is too much and could make it a reincarnation of nnpc in terms of arbitrary withholding of receipts meant for the federation account. the nnpc is notorious for withholding billions of dollars meant for the federation account every year without a clear or defined repayment plan (ohaeri and diminas, 2018). according to neiti (2017), findings from a series of audits of the oil and gas sector showed that the nnpc and its upstream arm, nigerian petroleum development company (npdc), failed to remit $21.778 billion and n316.074 billion to the federation account. the centrality of the petroleum in nigeria’s economy coupled with massive corruption associated with the sector had led buhari to assign the ministerial portfolio of the sector to himself. the various provisions in the pigb drastically whittled down the power of the minister. thus, it has been suggested that beyond the issues raised by the president as constituting the grounds for his decline, the real area of contention should be seen within the context of the erosion of the power of the minister, which he currently holds (the nation, 2018;). the letter conveying the president’s decline did not have a proposal about specific changes expected to be effected on the bill to make it acceptable. however, a rework of the pigb must address the observations of the president. this, therefore, requires that the national assembly must embark on wide consultations necessary to produce an acceptable version of the pigb. 5. conclusion there is no doubt that nigeria’s petroleum sector is poorly managed and therefore requires a fundamental reform. our respondents are unanimous in their belief that the quadripartite bills would address all the ills in the petroleum industry. specifically they believed that the pigb would catalyze development in the petroleum sector, create the necessary enabling environment to attract massive investment into the sector, and thus position nigeria as a world leader in the global petroleum industry, facilitate the expansion of nigeria’s oil reserve and enthrone peace in oil production activities by stabilizing relationship between host communities and industry players. however, the politicization of the reform process, which made the passage of the original reform bill, the pib, impossible thus necessitating its balkanization, is yet to be resolved. considering the unanimity of stakeholders on the imperative of reforms in the petroleum sector and the hard-work put in packaging the pigb, the refusal of muhammadu buhari, nigeria’s president, to assent to it was quite unfortunate. anecdotal evidence and calculations by analysts have suggested that nigeria has lost over us$200 billion directly and directly as a result of the non-passage of the pib (neiti, 2016; the nation, 2017). the continued delay in passing the quadripartite bills would undermine the sector and decelerate the pace of economic development, both of which have serious implications for meeting the sustainable development goals. the imperative of passing the reform bills is underscored by the general unwillingness of major petroleum industry players to commit their funds in an atmosphere of regulatory uncertainty, which the non-passage of the reform bills has created. according to us energy information administration (2016. p. 4), “regulatory uncertainty has resulted in fewer investments in new oil and natural gas projects, and no licensing round has occurred since 2007.” this paper recommends that the presidency should downplay the politicization of the petroleum sector reforms by deemphasizing the whittling down of the powers of the minister. the key considerations should be whether the pigb is in line with global best practices, whether its provisions would lead to better management of the sector and thus translate to efficiency in the operations of the sector, and whether it would ensure operational transparency, plug wastes and lead to more revenues for the country. thus the quadripartite bills should be expeditiously processed and passed into law so that the country can usher in a new era in its petroleum industry. references abuh, a. (2019), buhari to get harmonised pigb from national assembly. the guardian. available from: https://ww.guardian.ng/ news/buhari-to-get-harmonised-pigb-from-national-assembly. [last accessed on 2019 nov 25]. adelegan, a.e. (2017), oil and gas sector law reform and its implications for economic development in nigeria. international journal of development and economic sustainability, 5(3), 24-31. adetayo, o. (2018), why buhari declined assent to petroleum industry governance bill-enang, punch. available from: https://www. punchng.com/why-buhari-declined-assent-to-petroleum-industrygovernance-bill-enang. [last accessed on 2019 nov 25]. afdbg (african development bank group). (2013), federal republic of nigeria: country strategy paper, 2013-2017. available from: https://www.afdb.org/fileadmin/uploads/afdb/documents/projectand-operations/nigeria%20-%202013-2017%20-%20country%20 strategy%20paper.pdf. [last accessed on 2019 oct 18]. akuru, u.b., okoro, o.i. (2011), a prediction on nigeria’s oil depletion nwozor, et al.: reform in a limbo: the politics and politicization of reforms in nigeria’s petroleum sector international journal of energy economics and policy | vol 10 • issue 4 • 2020192 based on hubbert’s model and the need for renewable energy. isrn renewable energy, 2011, 6. amakom, u. (2013), subsidy reinvestment and empowerment programme (sure-p) intervention in nigeria: an insight and analysis. african heritage policy discussion paper 2013-02. enugu: african heritage institution. asu, f. (2018), dashed hopes: another year without pib passage, punch. available from: https://www.punchng.com/dashed-hopes-anotheryear-without-pib-passage. [last accessed on 2019 oct 15]. ejoh, e. (2017), nnpc lists steps to achieve 40bbl reserve by 2020, vanguard. available from: https://www.vanguardngr.com/2017/02/ nnpc-lists-steps-achieve-40-bbl-reserve-2020. [last accessed on 2018 may 24]. gboyega, a., soreide, t., le, t.m., shukla, g.p. (2011), political economy of the petroleum sector in nigeria. policy research working paper no. 5779. ikpeze, n.i., soludo, c.c., elekwa, n.n. (2004), nigeria: the political economy of the policy process, policy choice and implementation. in: charles, c.s., ogbu, o., chang, h., editors. the politics of trade and industrial policy in africa: forced consensus? trenton, new jersey: africa world press inc., international development research centre. p341-367. iledare, w. (2008), an appraisal of oil and gas industry reform and institutional restructuring in nigeria. international association for energy economics. p23-26. available from: http://www.iaee. org/documents/newsletterarticles/408wumi.pdf [last accessed on 2019 oct 17]. izevbigie, j.n., ebohon, g.e. (2019), internally generated revenue and state viability: comparative analysis of two states in nigeria. international journal of development and management review, 14(1), 96-106. katsouris, c., sayne, a. (2013), nigeria’s criminal crude: international options to combat the export of stolen oil. available from: https://www.chathamhouse.org/sites/default/files/public/research/ africa/0913pr_nigeriaoil_es.pdf. [last accessed on 2019 oct 17]. ministry of budget and national planning (2017). nigeria economic recovery & growth plan 2017-2020. available from: https://www. tralac.org/documents/resources/by-country/nigeria/1806-nigeriaeconomic-recovery-and-growth-plan-2017-2020-march-2017/file. html [last accessed on 2019 nov 25]. neiti (nigeria extractive industries transparency initiative). (2016), the urgency of a new petroleum sector law, issue 02. policy brief. available from: https://www.neiti.gov.ng/index.php/neitipolicy-brief?download=124:neiti-pb-issue02. [last accessed on 2019 nov 25]. neiti (nigeria extractive industries transparency initiative). (2017), unremitted funds, economic recovery, and oil sector reform, issue 03. policy brief. available from: https://www.neiti.gov.ng/ phocadownload/neiti-pb/neiti-pb3-280317.pdf. [last accessed on 2019 nov 25]. neiti (nigeria extractive industries transparency initiative). (2019), stemming the increasing cost of oil theft to nigeria, issue 5. policy brief. available from: https://www.neiti.gov.ng/index.php/ neiti-policy-brief?download=890:neiti-pb-issue-05-crude-theftpolicy-brief. [last accessed on 2019 nov 25]. nnodim, o. (2019), crude oil theft: meter oil production, neiti urges fg, punch. available from: https://www.punchng.com/crude-theftmeter-oil-production-neiti-urges-fg. [last accessed on 2019 nov 15]. npc (national planning commission). (2011), the transformation agenda, 2011-2015: summary of federal government’s key priority policies, programmes and projects. abuja: national planning commission, federal government of nigeria. npc (national planning commission). (2013), mid-term report of the transformation agenda (may 2011-may 2013): taking stock, moving forward. abuja: national planning commission, federal government of nigeria. nwaokoro, j.n.e. (2011), nigeria’s national content bill: the hype, the hope and the reality. journal of african law, 55(1), 128-155. nwapi, c. (2019), the achievement of regulatory excellence in the oil and gas industry in nigeria: the 2017 national oil and gas policy. journal of energy and natural resources law, 38(1), 91-117. nwozor, a. (2019a), depoliticizing environmental degradation: revisiting the unep environmental assessment of ogoniland in nigeria’s niger delta region. berlin: springer. nwozor, a., audu, j., adama, j.i. (2019b), the political economy of hydrocarbon pollution: assessing socio-ecological sustainability of nigeria’s niger delta region. international journal of energy economics and policy, 9(1), 7-14. odunsi, w. (2019), only 10 nigerian states economically viable, 17 bankrupt. daily post. available from: https://www.dailypost. ng/2019/05/12/10-nigerian-states-economically-viable-17-bankruptsee-details. [last accessed on 2019 nov 25]. ohaeri, v., diminas, s. (2018), pigb veto: buhari is both right and wrong, punch. available from: https://www.punchng.com/pigb-vetobuhari-is-both-right-and-wrong-1. [last accessed on 2019 nov 25]. olusi, j.o., olagunju, m.a. (2005), the primary sectors of the economy and the dutch disease in nigeria. the pakistan development review, 44(2), 159-175. opec (organization of the petroleum exporting countries). (2019), opec annual statistical bulletin. available from: https://www.asb. opec.org/index.php/pdf-download. [last accessed on 2019 nov 25]. otaha, j.i. (2012), dutch disease and nigeria oil economy. african research review, 6(1), 82-90. ovuakporie, e. (2018), at last, reps pass pigb, vanguard. available from: https://www.vanguardngr.com/2018/01/last-reps-pass-pigb-2. [last accessed on 2019 oct 15]. pérouse, m.m. (2014), the politics and crisis of the petroleum industry bill in nigeria. the journal of modern african studies, 52(3), 403-424. peterside, c.s. (2004), what happens in nigeria when the oil wells run dry? available from: https://www.resilience.org/stories/2004-11-05/ what-happens-nigeria-when-oil-wells-run-dry. [last accessed on 2019 oct 12]. sdn (stakeholder democracy network). (2018), the petroleum industry governance bill. available from: https://www.stakeholderdemocracy. org/wp-content/uploads/2018/12/pigb-11.12.18-jb.pdf. [last accessed on 2019 nov 25]. shosanya, m. (2015), pib: how long will the waiting game continue? daily trust. available from: https://www.dailytrust.com.ng/pibhow-long-will-the-waiting-game-continue.html. [last accessed on 2019 oct 15]. sweet crude report. (2013), pib, a killer, says iocs. available from: https://www.sweetcrudereports.com/pib-a-killer-say-iocs. [last accessed on 2019 oct 15]. the nation. (2017), nigeria loses $200b to non-passage of pib. available from: https://www.thenationonlineng.net/nigeria-loses200b-non-passage-pib. [last accessed on 2019 oct 15]. the nation. (2018), why buhari withheld assent to pigb-presidency. available from: https://www.thenationonlineng.net/buhari-withheldassent-pigb-presidency. [last accessed on 2019 nov 25]. the petroleum industry bill. (2012), draft bill. available from: http:// www.nigeria-law.org/legislation/lfn/2012/the%20petroleum%20 industry%20bill%20-%202012.pdf. [last accessed on 2019 jul 27]. ugwuanyi, e. (2013), forces against pib. the nation. available from: https://www.thenationonlineng.net/forces-against-pib. [last accessed on 2019 oct 15]. ukiwo, u. (2018), governance regimes of oil in nigeria: issues and https://twitter.com/njcourts?ref_src=twsrc%5egoogle%7ctwcamp%5eserp%7ctwgr%5eauthor https://twitter.com/njcourts?ref_src=twsrc%5egoogle%7ctwcamp%5eserp%7ctwgr%5eauthor nwozor, et al.: reform in a limbo: the politics and politicization of reforms in nigeria’s petroleum sector international journal of energy economics and policy | vol 10 • issue 4 • 2020 193 challenges. crpd working paper no. 69. available from: https:// www.soc.kuleuven.be/crpd/files/working-papers/crpd-no-69-ukiwofull.pdf. [last accessed on 2019 nov 25]. umoru, h. (2018), national assembly transmits pigb to buhari for assent, vanguard. available from: https://www.vanguardngr. com/2018/07/national-assembly-transmits-pigb-to-buhari-for-assent. [last accessed on 2019 oct 15]. us energy information administration. (2016), country analysis brief: nigeria. available from: https://www.eia.gov/beta/international/ analysis_includes/countries_long/nigeria/nigeria.pdf. [last accessed on 2019 nov 25]. usman, z. (2016), the successes and failures of economic reform in nigeria’s post-military political settlement. geg working paper, no. 115. van meurs, p. (2012), commentary on the pib 2012. available from: https:// www.vanmeursenergy.com/documents/commentaryonpib2012.pdf. [last accessed on 2019 oct 27]. wahab, l., diji, c.j. (2017), comparative analysis of nigeria petroleum fiscal systems using royalty and tax optimization models to drive investments. oil and gas research, 3(3), 145. tx_1~at/tx_2~at international journal of energy economics and policy | vol 11 • issue 1 • 2021 433 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2021, 11(1), 433-439. energy sustainability, energy financing and economic growth in nigeria ademola onabote1,2, ayobami jolaade3, romanus osabohien2,3*, oghenetega otobo3, christian ede3, victoria okafor2,3 1department of economics, landmark university, omu-aran, nigeria, 2centre for economic policy and development research, covenant university, ota, nigeria, 3department of economics and development studies, covenant university, ota, nigeria. *email: romanus.osabohien@covenantuniversity.edu.ng received: 31 january 2020 accepted: 15 september 2020 doi: https://doi.org/10.32479/ijeep.9336 abstract increase in the global population growth has led to a simultaneous increased in demand for energy leading to increased fear of global warming. this situation has given the international community a cause for concern and as a result, countries are seeking alternative sources for cleaner and sustainable energy. the importance of utilising greener energy sources is evident in the united nation’s sustainable development goals (sdgs), especially goal 7, target 2. this study examined the long-run relationship between economic growth, sustainable energy and the different financing options for sustainable energy in nigeria. the johansen cointegration test was utilised in order to achieve this objective. the findings showed that different sources of sustainable energy and the different types of financing employed in nigeria have different effects on the economic growth of nigeria. a long-run relationship amongst all three variables was also established. these findings are an indication that with the right policies, sdg 7 could be achieved. keywords: sustainable energy, energy financing, economic growth, sustainable development goals, nigeria jel classifications: q20, q28, q43 1. introduction energy is a highly demanded commodity in the world, and it is essential in achieving economic growth and development across the globe (oyedepo, 2012; onakoya et al., 2013). however, the phenomenon of global climate change and global warming, which are seen as threats to human existence, has led to a rise in the demand for sustainable energy (simsek and simsek, 2013; alege et al., 2017). in addition, the global population increase has fuelled the demand for sustainable energy. specifically, the continuous increase in the population of nigeria, standing at about 200 million people (world bank, 2019), has caused a rise in the country’s demand for and usage of energy. however, energy in nigeria is mainly obtained from non-renewable sources which are not sustainable. the negative impacts of the excessive use of these fuels violate the concepts of sustainable energy as it causes environmental degradation through pollutants such as gas flaring/emissions from combustions, coal gases/ particulates and oil spillage (matthew et al., 2018). therefore, there is a need for cleaner energy sources in order to ensure a sustainable energy provision in accordance with the sustainable development goal (sdg 7). for this study and following the classical definition given by the world commission on environment and development (wced) in 1987, sustainable energy is defined as energy that “meets the need of the present generation without compromising the ability of the future generations to meet their own energy needs.” this definition is as relevant today as it was three decades ago when it was initiated. sustainable energy refers to the energy that is clean and renewable, thus making it inexhaustible. although nigeria is this journal is licensed under a creative commons attribution 4.0 international license onabote, et al.: energy sustainability, energy financing and economic growth in nigeria international journal of energy economics and policy | vol 11 • issue 1 • 2021434 the largest oil producer in africa and possesses both non-renewable and renewable (wind, solar, hydropower, and biomass) energy sources (gershon et al., 2019). according to iwayemi (2012), over 40% of the population of nigeria live without electricity. this issue of the incessant power outage is one of the primary reasons why over 70% of the nigerian population lives below the poverty line and negatively affect health outcomes (iwayemi, 2012; matthew et al., 2019). similarly, charles (2014) pointed out that only 10% of the people in the rural area and 30% of the total population have access to electricity. this has therefore made nigeria seek other alternative means of power such as the use of diesel and petrol generating sets. however, these sources of electricity are not sustainable and the continued usage may impact negatively on health outcomes and on the economy matthew et al., 2019. the prospect of having a sufficient amount of sustainable energy in nigeria is high since the country is endowed with numerous energy sources that can cater for the present and the future energy use. the energy source that is presently being invested in by the federal government of nigeria is the hydropower, but it is still insufficient. as a result, other forms of sustainable energy (solar, biomass and wind) must be encouraged and developed. against these backdrops, this study aimed to empirically examine the relationship amongst economic growth, sustainable energy and the different financing options for sustainable energy in nigeria. this study is structured into five sections; following this introductory section is section two which presents some insights from the empirical literature. the methodology adopted is discussed in section three. section four discusses the estimations and results of the study, while section five concludes the study and policy recommendations are provided. 2. empirical literature it is clear from the literature that the inability to secure the required investment in sub-saharan african is a hindrance to accessing clean energy (chirambo, 2016). chirambo (2018) using an exploratory research method, investigated numerous innovations aimed at increasing the access of sub-sahara african to sustainable and clean energy. findings from the study indicate the need for a regional institutional regulator to monitor the progress of both climate change and clean energy, thereby taking an important step towards realising the sgd 7. the relationship between energy consumption and economic growth has been examined in literature; for example, shiu and lam (2004) in a study examined the relationship between economic growth and electricity consumption in china using the error correction model (ecm), the study affirms the presence of co-integration between the energy consumption and economic growth. literature covering sub-saharan african such as akinlo (2008) examined the link between economic growth and energy consumption for selected countries in sub-saharan africa. the autoregressive distributed lag (ardl) bounds test and the vector error correction model (vecm) were used in order to achieve the set objectives. the results from the study showed that for ghana, cameroon, zimbabwe, gambia, sudan, cote d’ivoire and senegal, economic growth and energy consumption were co-integrated. in senegal, ghana, sudan and kenya, it was observed that energy consumption was growth-enhancing. the study confirmed a two-way causal relationship between economic growth and energy consumption for senegal, ghana and gambia. while a unidirectional relationship was confirmed for zimbabwe and sudan, the neutrality hypothesis was established in nigeria, cameroon, togo, kenya and cote d’ivoire. a similar study on the relationship between economic growth and energy consumption was conducted by onakoya et al. (2013). the study was limited to the nigeria economy with a scope covering 35 years (1975-2010). the ordinary least square method and co-integration technique were adopted. the result from the analysis indicated that the variables are co-integrated. further analysis reveals a significant and positive relationship amongst petroleum, electricity and energy consumption. in a more recent study, mitic et al. (2017) analysed the link between economic growth and carbon emissions for 17 transitional economies. the authors utilised annual data from 1997 to 2014 and made use of both the fully modified ols (fmols) and dynamic ordinary least squares (dols) approaches in order to achieve their objectives. economic growth and carbon emissions were confirmed to have a long-run relationship. with the use of a structural vector autoregressive (svar) approach, silva et al. (2012) analysed the effect of renewable energy sources (res) on the growth of the economy and carbon dioxide emission, employing a sample of four countries from the period of 1960 to 2004. the findings of the study show that there was an economic cost in terms of economic growth and there is also a significant decrease in the co2 emissions per capita as a result of using res. jebli and youssef (2014) examined whether there was a causal relationship amongst combustible renewables and waste consumption, carbon dioxide (co2) emission and economic growth and using data from five countries in north africa during the period of 1971-2008. the major variable in determining economic growth was found to be co2 emission. the study, therefore, recommended that the north africa region can use renewable energy sources in place of fossil fuel in order to avoid the depletion of the atmosphere as well as stimulate the growth of the economy. by using a group of eighteen latin american countries, al-mulali et al. (2014) investigated the effect of renewable electricity consumption and non-renewable electricity consumption on the growth of the economy. to this end, the authors made use of the vector error correction model (vecm) and granger causality tests. results of the study confirmed the existence of a bidirectional relationship amongst all the variables used in the study. the authors found that out of the two energy sources, renewable energy was more significant in stimulating economic growth. pao et al. (2014) opined that a sustainable energy economy could be enhanced through the creation of clean and fossil fuel energy partnerships. they investigated the relationship amongst clean energy consumption, unclean energy consumption and economic growth of four nations (south korea, mexico, turkey onabote, et al.: energy sustainability, energy financing and economic growth in nigeria international journal of energy economics and policy | vol 11 • issue 1 • 2021 435 and indonesia). the authors recommended that in order to address the issues surrounding climate change and energy security, it was necessary to develop renewable and nuclear energy sources. troster et al. (2018) carried out a study to determine whether there is a causal relationship amongst renewable energy consumption, the prices of oil and growth of the economy in the united states of america. the study made use of the granger causality method. the results obtained confirmed the presence of a two-way relationship amongst the study variables. despite the extensive research conducted on sustainable energy, there are only a few that consider the various financing options available in the same model. this is the gap in the literature that this study intends to fill as considering both sustainable energy and different financing options available, important policy-inferences could be made from the results obtained. 3. methodology 3.1. data source this study examined the relationship amongst economic growth, sustainable energy and the different financing options for sustainable energy in nigeria. in order to achieve this, annual data was obtained from the world development indicators (wdi), ranging from 1981 to 2014, thus spanning a period of 34 years. the selection of the period is exclusively based on the availability of data for nigeria. the variables of interest are shown in table 1 with their respective symbols, descriptions, sources and measurements. gross domestic product per capita (gdppc) is used to proxy economic growth; combustible renewables and wastes (corew), alternative and nuclear energy (alnue), and electricity production from hydroelectric sources (hydro) are used as proxies for sustainable energy; net official development assistance received (netod), net taxes on products (taxes) and external debt (extdt) are used as proxies for sustainable energy financing options. 3.2. model specification this study adopted the method proposed by maji (2015) and modifies in order to suit this study. our modification draws from the introduction of the different financing options available for sustainable energy in nigeria, the baseline model is specified in equation (1). gdppct=f(corewt, alnuet, hydrot, netodt, taxest, extdtt) (1) the above expression in equation (1) can be expressed in the classic cobb-douglas production function form, which is shown below: gdppc acorew alnue hydro netod taxes extdt t t t t t t t t � � � � � � � � 1 2 3 4 5 6 (2) in order to satisfy the linearity condition of the ols assumption, we obtain the natural logarithm transformation of equation (2) which yields the following: lngdppct=a+ω1 lncorewt+ω2 lnalnuet+ω3 lnhydrot +ω4 lnnetodt+ω5 lntaxest+ω6 lnextdtt+μt (3) where a represents the intercept. ln represents the natural logarithm. a represent the intercept while μt represent the error term. ω1, ω2, ω3, ω4, ω5 and ω6 represent the elasticities of corew, alnue, hydro, netod, taxes and extdt, respectively. 4. estimations and results 4.1. unit root tests a fundamental requirement when dealing with times series data is to test for the existence of unit root in order to determine the stationarity of the series. this is due to the non-stationary property of time series. the consequences of using non-stationary data for econometric analysis is that it usually leads to a spurious result. the philip phillips-peron (pp) unit root test and the augmented dickey-fuller (adf) unit root test was conducted in order to show whether the following log-linearised time series are stationary or not: corew,alnue,hydro,netod,taxes and extdt. table 2 show’s us the result of the unit root test. all the variables of importance in this paper are stationary after first differencing. thus, using these series eliminates the possibility of obtaining spurious empirical results. with stationarity established, the cointegration test is carried out so as to achieve the objective of this study. 4.2. johansen cointegration test this paper employs the widely-used johansen cointegration test (johansen, 1991). it is used to show whether the explanatory and explained variables possess a long-run relationship. the result of the cointegration test is shown in tables 3 and 4, respectively. both the trace statistic and the maximum eigen statistic reveal 4 co-integrating equations amongst the selected variables of interest. this thus supports that a long-run relationship exists amongst economic growth, sustainable energy and the different financing options for sustainable energy. 4.3. granger causality test after establishing that the variables are co-integrated, this study goes ahead to determine the causal relationship that table 1: data description and measurement symbol description source measurement gdppc gross domestic product per capita world development indicators (2017) constant naira (₦) corew combustible renewables and wastes world development indicators (2017) percentage of total energy alnue alternative and nuclear energy world development indicators (2017) percentage of total energy hydro electricity production from hydroelectric sources world development indicators (2017) percentage of total energy netod net official development assistance received world development indicators (2017) percentage of gni taxes net taxes on products world development indicators (2017) constant naira (₦) extdt external debt world development indicators (2017) percentage of gross national income source: authors onabote, et al.: energy sustainability, energy financing and economic growth in nigeria international journal of energy economics and policy | vol 11 • issue 1 • 2021436 table 2: pp and adf unit root tests variables pp test adf test level first difference level first difference decision lngdppc 0.261009 −4.242329* 0.542457 −4.257043* i(1) lncorew −2.594056 −6.408230* −2.518695 −5.695536* i(1) lnalnue −1.344122 −6.867076* −1.402457 −6.844402* i(1) lnhydro 0.048891 −6.829895* −1.103063 −0.554822* i(1) lnnetod −2.536004 −5.021321* −2.959760 −5.199612* i(1) lntaxes −1.918897 −4.846880* −1.922424 −3.754164* i(1) lnextdt −0.252437 −4.839246* −0.145566 −4.841518* i(1) source: authors’ computation using eviews 10 software. *indicate the 1% level of significance for the test critical values table 4: johansen cointegration test (maximum eigen statistic) hypothesised number of ces eigen value max-eigen statistic 0.05 critical value prob.** none* 0.937457 69.29751 46.23142 0.0000 at most 1* 0.898236 57.12738 40.07757 0.0003 at most 2* 0.793800 39.47269 33.87687 0.0097 at most 3* 0.725451 32.31564 27.58434 0.0114 at most 4 0.353448 10.90255 21.13162 0.6570 at most 5 0.178246 4.907847 14.26460 0.7534 at most 6 0.003820 0.095695 3.841466 0.7570 source: authors’ computation using eviews 10 software. *denotes rejection of the null hypothesis at the 0.05 level. **mackinnon-haug-michelis (1999) p-values table 3: johansen cointegration test (trace statistic) hypothesised number of ces eigen value trace statistic 0.05 critical value prob.** none* 0.937457 214.1193 125.6154 0.0000 at most 1* 0.898236 144.8218 95.75366 0.0000 at most 2* 0.793800 87.69443 69.81889 0.0010 at most 3* 0.725451 48.22174 47.85613 0.0462 at most 4 0.353448 15.90610 29.79707 0.7189 at most 5 0.178246 5.003541 15.49471 0.8084 at most 6 0.003820 0.095695 3.841466 0.7570 exists, if any, amongst the variables. table 5 presents the result from the granger causality test. from the results, it is seen that a unidirectional causal relationship exists for all the pairs considered except for combustible renewables and wastes and gross domestic product per capita. specifically, there is a unidirectional causal relationship flowing from gross domestic product per capita to alternative and nuclear energy, electricity production from hydroelectric sources, net official development assistance received and external debt. also, a unidirectional causal relationship flowing from net taxes on products to gross domestic product per capita was discovered. 4.4. impulse response functions the granger causality test, despite being useful in pointing out the direction of causality that exists between any two variables, is not able to provide inferences concerning the variables of interest beyond the time period utilised. as a result, forecasts cannot be made from it. in addition, the granger causality test is silent as to the sign of the relationship existing between the variables. due to these reasons, this study goes ahead to determine the impulse responses over a 10-year period when there is a one standard deviation positive innovation to another variable. the results from the impulse response functions (irfs) are shown in figure 1. from figure 1, it is seen that gross domestic product per capita rises for two periods following a positive shock to itself. in the third period, it declines before increasing again in the subsequent period. the gross domestic product per capita witnesses an initial decline in after a shock to combustible renewables and wastes. however, in the third period, it begins to experience a rise and goes on to become positive in the fifth period. after there is a shock to alternative and nuclear energy, gross domestic product per capita witnessed a sharp decline. in the third period, its response becomes stable, although it remains negative. gross domestic product per capita is unaffected by a shock to electricity production from hydroelectric sources in the first period. however, it turns negative in the subsequent periods. initially, after a shock to net official development assistance received, gross domestic product per capita witnesses a sharp increase before levelling up in the third period. gross domestic product per capita experiences a steep decline following a shock to net taxes on products before becoming stable in the second period. in addition, it is seen that the response of gross domestic product per capita to a shock to external debt is negative. 4.5. variance decomposition (vd) after obtaining the irfs for gross domestic product per capita, this study goes ahead to determine its variance decomposition (vd). table 6 presents the result and it shows that in period 1, the variation to gross domestic product per capita is entirely due to a shock to itself. further down the time periods, this variation is attributed to other shocks. in period 2, the share of the variation caused by gross domestic product per capita shock drops by almost 50%. in that same period, net official development assistance received and combustible renewables and wastes shock account for a significant portion of the variation which is 21.92% and 10.08% respectively. in period 3, net official development assistance received shock accounts for most of the variation in gross domestic product per capita and this pattern continues till period 10. in period 10, 29.76%, 15.49% and 15.39% of the variation in gross domestic product per capita is attributed to net official development assistance received, electricity production from hydroelectric sources and alternative and nuclear energy shocks respectively, which account for more than 60% of the variation in gross domestic product per capita. onabote, et al.: energy sustainability, energy financing and economic growth in nigeria international journal of energy economics and policy | vol 11 • issue 1 • 2021 437 figure 1: impulse response functions of gross domestic product per capita table 6: variance decomposition of lngdppc period s.e. lngdppc lncorew lnalnue lnhydro lnnetod lntaxes lnextdt 1 0.031756 100.0000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 2 0.050520 52.47670 10.08269 6.324804 9.27e-05 21.92322 5.465196 3.727295 3 0.074124 25.30278 10.73332 18.63761 3.694274 32.40070 4.096656 5.134657 4 0.090231 21.46517 8.407405 17.28343 9.001069 32.95313 3.719407 7.170378 5 0.100831 22.50783 6.746559 16.05354 11.61277 32.04404 3.377349 7.657921 6 0.113467 22.66838 6.216855 16.40277 11.78809 32.65459 3.048219 7.221101 7 0.127427 21.92036 5.545049 16.25144 13.04742 32.87856 2.871500 7.485668 8 0.138268 22.18331 5.309401 16.03804 14.32551 31.79167 2.681258 7.670811 9 0.148294 22.72895 5.750867 15.68034 15.07325 30.63809 2.525362 7.603135 10 0.158563 22.98264 6.565083 15.38946 15.49003 29.76037 2.376495 7.435926 source: authors’ computation using eviews 10 software table 5: pairwise granger causality test null hypothesis f-statistic prob. decision causality lncorew does not granger cause lngdppc lngdppc does not granger cause lncorew 0.45226 1.39569 0.6409 0.2650 accept accept none lnalnue does not granger cause lngdppc lngdppc does not granger cause lnalnue 1.25789 9.63044 0.3004 0.0007 accept reject unidirectional lnhydro does not granger cause lngdppc lngdppc does not granger cause lnhydro 0.16484 10.8212 0.8489 0.0004 accept reject unidirectional lnnetod does not granger cause lngdppc lngdppc does not granger cause lnnetod 0.91778 7.91546 0.4115 0.0020 accept reject unidirectional lntaxes does not granger cause lngdppc lngdppc does not granger cause lntaxes 3.69340 0.57867 0.0431 0.5698 reject accept unidirectional lnextdt does not granger cause lngdppc lngdppc does not granger cause lnextdt 1.60022 5.40273 0.2204 0.0106 accept reject unidirectional source: authors’ computation via e views 10 5. conclusion and policy recommendations it is seen that, sustainable energy (except combustible renewables and wastes) and the various financing options (except net official development assistance received) would contribute negatively to the growth of the nigerian economy. at first, combustible renewables and wastes negatively affects economic growth and this may be as a result of the indiscriminate felling of trees by its users as a source of energy. felling of trees without replanting may bear a negative influence on the environment, the people and in turn, the economy. however, its contribution to economic growth later becomes positive. perhaps, this may be due to the onabote, et al.: energy sustainability, energy financing and economic growth in nigeria international journal of energy economics and policy | vol 11 • issue 1 • 2021438 overshadowing positive effect of the use of this source of energy which in the long run is cheaper. wood fuel is a component of combustible renewables and wastes and it is a cheaper alternative to energy for both rural and urban dwellers. by using the relative cheaper energy source, the economy is boosted. however, caution must be taken so as not to witness a counter-effective reaction of this energy source due to deforestation. rather, policy measures should be put in place in order to discourage deforestation and encourage afforestation, which would, in turn, contribute to the sustainability of this energy source. in addition, monitoring bodies should be set up in order to guard against the felling of trees without proper approval from the appropriate authorities. it is also seen that both alternative and nuclear energy and electricity production from hydroelectric sources contribute negatively to the economy. the reason for the negative contribution of electricity generated from hydro sources to economic growth in nigeria may be attributed to the negative spill-over effects of making use of hydropower. some of these negative spill-over effects include an inadequate number of hydro-electric plants in nigeria the poor maintenance and upgrade to modern technologies, inability to meet growing electricity demand under the present capacity of hydro-electric plants. the negative contribution of alternative and nuclear energy to economic growth in nigeria may be attributed to its under-development and poor usage in nigeria. due to its low production, this source of energy is expensive in nigeria, both to producers and consumers and as a result, it may contribute negatively to the economy. this result calls for a swift response on the part of the government and other stakeholders in the nigerian energy sector. being a country surrounded by large bodies of water and having rainy reasons, nigeria stands a lot to benefit from making use of hydro-electricity. not only is hydropower sustainable, but it is also eco-friendly and relatively cheaper than some other sustainable sources of energy such as solar energy. all of the factors hampering the efficient and effective production of hydro-electric energy must be reviewed in details and mitigated so that nigeria could reap the benefits of the hydro-electricity. for alternative and nuclear energy, since it provides immense benefit and would help to cater for the growing energy needs of the nigerian population, the nigerian government and all concerned stakeholders should develop the country’s infant nuclear industry so as to ensure its availability at an affordable price. the results show that the contribution of net official development assistance received to economic growth in nigeria is positive. the reason for this may be because this source of financing is monitored by the donor countries or organisations. however, despite the positive contribution of net official development assistance received to economic growth, great care must be taken when dealing with it as some economists have argued that dependence on foreign financing could hamper the growth and development in developing countries. it is also seen that both taxes and external debt contribute negatively to economic growth in nigeria. the negative contribution of tax to economic growth may stem from cases of tax avoidance and tax evasion. with high taxes, people are encouraged to alter their financial books and take advantage of loopholes in tax laws. some people evade taxes altogether. in order to reduce cases of tax avoidance and tax evasion, taxes levied should not be above the ability and willingness of the taxpayers. in addition, the government should operate an effective taxation system that would ensure proper remittance of collected tax funds to the government so that tax benefits are reaped by both the public and the private sectors. tax laws should also be made clear and the process should be transparent. it is revealed that the contribution of external debt to economic growth in nigeria is negative. the reason for this may be as a result of the negative effect of a debt burden. since debts would have to be paid back, they are shifted to the citizens in the form of higher taxes. in turn, higher taxes, as the results have shown, lead to a negative effect on economic growth. it is recommended that loans should be taken only after proper and careful consideration by economic experts. funds borrowed should also be used to embark on projects that have a high return or on projects that help to facilitate economic activities. this study has thus been able to achieve its set objectives by establishing the existence of a long-run relationship amongst the variables of interest. from the results obtained from the study, it is possible for nigeria to be able to achieve the 7th sustainable development goal (affordable and clean energy) before the sdgs timeline elapses in the next 12 years by 2030. this would be made possible if all stakeholders get involved in the sustainable energy movement. references akinlo, a.e. (2008), energy consumption and economic growth: evidence from 11 sub-sahara african countries. energy economics, 30(5), 2391-2400. alege, p.o., oye, q.e., adu, o.o., amu, b., owolabi, t. (2017), carbon emissions and the business cycle in nigeria. international journal of energy economics and policy, 7(5), 1-8. al-mulali, u., fereidouni, h.g., lee, j.y. (2014), electricity consumption from renewable and non-renewable sources and economic growth: evidence from latin-american countries. renewable and sustainable energy reviews, 30, 290-298. charles, a. (2014), how is 100% renewable energy possible for nigeria? global energy network institute. united states: global energy network institute. chirambo, d. (2016), addressing the renewable energy financing gap in africa to promote universal energy access: integrated renewable energy financing in malawi. renewable and sustainable energy reviews, 62, 793-803. chirambo, d. (2018), towards the achievement of sdg 7 in sub-saharan africa: creating synergies between power africa, sustainable energy for all and climate finance in-order to achieve universal energy access before 2030. renewable and sustainable energy reviews, 94, 600-608. gershon, o., ezenwa, n.e., osabohien, r. (2019), implications of oil price shocks on net oil-importing african countries. heliyon, 5(8), e02208. iwayemi, a. (2012), energy resources and development in nigeria. naee/iaee 4th annual international conference. available from: http://www.naee.org. onabote, et al.: energy sustainability, energy financing and economic growth in nigeria international journal of energy economics and policy | vol 11 • issue 1 • 2021 439 jebli, m.b., youssef, s.b. (2014), economic growth, combustible renewables and waste consumption and emissions in north africa. germany: munich personal repec archive. johansen, s. (1991), estimation and hypothesis testing of cointegration vectors in gaussian vector autoregressive models. econometrica, 59(6), 1551-1580. maji, i.k. (2015), does clean energy contribute to economic growth? evidence from nigeria. energy reports, 1, 145-150. matthew, o., osabohien, r., fasina, f., fasina, a. (2018), greenhouse gas emissions and health outcomes in nigeria: empirical insight from ardl technique. international journal of energy economics and policy, 8(3), 43-50. matthew, o.m., miebaka-ogan, t., popoola, o., olawande, t., osabohien, r., urhie, e., ogunbiyi, t. (2019), electricity consumption, government expenditure and sustainable development in nigeria: a co-integration approach. international journal of energy economics and policy, 9(4), 74-80. mitic, p., ivanovic, o.m., zdravkovic, a. (2017), a co-integration analysis of real gdp and co2 emissions in transitional economies. sustainability, 9, 1-18. onakoya, a.b., onakoya, a.o., jimi-salami, o.a., odedairo, b.o. (2013), energy consumption and nigerian economic growth: an emprical analysis. european scientific journal, 9(4), 25-40. oyedepo, s.o. (2012), on energy for sustainable development in nigeria. renewable and sustainable energy reviews, 16, 2583-2598. pao, h.t., li, y.y., fu, h.c. (2014), clean energy, non-clean energy, and economic growth in the mist countries. energy policy, 67, 932-942. shiu, a., lam, p.l. (2004), electricity consumption and economic growth in china. energy policy, 32(1), 47-54. silva, s., soares, i., pinho, c. (2012), the impact of renewable energy sources on economic growth and co2 emissions-a svar approach. european research studies, 15, 133-144. simsek, h.a., simsek, n. (2013), recent incentives for renewable energy in turkey. energy policy, 63, 521-530. troster, v., shahbaz, m., uddin, g.s. (2018), renewable energy, oil prices, and economic activity: a granger-causality in quantiles analysis. germany: munich personal repec archive. wced. (1987), our common future. world commission on environment and development. world commission on environment and development. oxford: oxford university press. world bank. (2019). world development indicators. washington, dc: world bank. international journal of energy economics and policy vol. 5, no. 1, 2015, pp.96-104 issn: 2146-4553 www.econjournals.com 96 modeling energy efficiency and economic growth: evidences from india avik sinha indian institute of management indore fpm 105, indian institute of management indore, prabandh shikhar, rau-pithampur road, indore 453556, madhya pradesh, india. email: f11aviks@iimidr.ac.in abstract: india’s fossil fuel based energy-led economic growth has changed its pattern over a time and it is mainly driven by energy efficiency. in this paper, we have considered reduction in energy waste as a proxy of energy efficiency and analyzed its interplay with economic growth for 1971-2010. we have used vector error correction model, and it has been seen that unidirectional causality exists from economic growth to energy waste, and this causal association is both short run and long run in nature. moreover, energy waste is following a negatively elastic relationship with the economic growth along the energy efficiency frontier. keywords: economic growth; energy waste; india, vector error correction jel classifications: o44; q42; q43 1. introduction indian growth history has been fairly a grown up subject matter of interest for researchers across the world. since 1971, india is experiencing an elevated decadal average growth rate. beginning with a decadal average of 3.08 per cent in 1971-80, the gross domestic product (gdp) has ascended to 5.57 per cent in 1980-2000 and 7.47 per cent in 2001-10. enabler of this significant growth is the energy consumption, which was evident in the form of electrical power consumption (ghosh, 2002). during 1971-2010, fossil fuel energy consumption of india has gone up to more than two and half times. it can be said that this intensification in electrical power consumption has heightened the economic growth. indian economic growth and energy consumption follow a causal relationship, which says that energy consumption is the reason behind economic growth of india (cheng, 1999). within the boundary of this established causal association, we will consider only the one segment of energy consumption, i.e. the fossil fuel energy consumption. however, certainly there is shadow beneath the lamp. elevated fossil fuel based energy consumption has also heightened the level of emission in the environment. majority of the power utilized in economic development is power generated from fossil fuels. during 1971-2010, amount of fossil fuel consumption as a fraction of total power consumption has almost doubled. this has resulted in huge level of carbon dioxide (co2) emission in the atmosphere. during 1971-2010, co2 emission has gone up from 205,869.05 kilo tons in 1971 to 1,979,424.60 kilo tons in 2010, i.e. nearly an increase of 9.61 times. consequently, the amplified utilization of fossil fuel, which is facilitating the economic growth of india, is as well worsening the atmosphere. nevertheless, this phenomenon is quite understandable for the case of india, as for a developing nation, attracting more investment and employment of the same is endowed with more importance than the environmental protection (acharyya, 2009). this underestimation of environmental damage can in turn bring harm to the economic growth. nevertheless, the amount of combustible energy waste has been reducing, which signifies the enhanced energy efficiency in india, which has been catalyzed by public-private partnership (sinha-khetriwal et al., 2005). on one hand, when gradually rising fossil fuel energy consumption is affecting the environment, then on the other hand, rising ecological awareness is lowering the amount of energy waste. they sound to be contradictory, but for india, it is a fact. besides the rise in greenhouse gas emissions, during 1971-2010 percentage of combustible waste as a percentage of total energy consumption has been reduced to 24.89 per cent from 61.22 per cent. modeling energy efficiency and economic growth: evidences from india 97 looking at the present economic growth scenario in india, researchers have stated that demand for commercial energy in india is going to encounter a rise within next decade (asif and muneer, 2007). after economic liberalization in 1991, economic growth was set in pace, and in order to sustain that growth, combustible fossil fuel generated energy was required. however, in order to keep their carbon footprints intact, most of the developed nations try to dump their polluting technologies to developing and underdeveloped nations, and this phenomenon was not different for india, as well (marton, 1986; siddharthan and lal, 2004). due to this scenario, the ambient air, water, and soil pollution started to rise in the post-liberalization period, and in order to combat this situation, efficient energy management technologies were required by the industrial houses of india. economic growth of india demanded higher consumption of energy, and the pattern was in turn degrading the environment. therefore, there was a need to bring forth changes in the growth pattern in terms of introducing alternate sources of energy, thereby, reducing energy waste and enhancing energy efficiency. if we look at the literature on energy economics, then we can see that analysis of energy efficiency has been carried out in several contexts, which were started after the pioneering works in this field is by khazzoom (1980), brookes (1990), and saunders (1992). howarth (1997) has analyzed energy efficiency in terms of cost of energy and expenditure on energy services, smulders and de nooij (2003) have analyzed it in terms of energy conservation, pérez-lombard et al. (2008) have analyzed it through emergence of energy efficient buildings. bozkurt and akan (2014) have carried out this study for turkey, hu and wang (2006) have done it for china, stern (1993) has done it for usa, mahadevan and asafu-adjaye (2007) have done it for developing and developed nations, shahateet (2014) has done it for arab countries, wolde-rufael (2006) has done it for african nations, hondroyiannis et al. (2002) have done it for greece and etc. however, this is quite surprising to notice that there is not a single study in indian context, which we have encountered, and considering the oilimporting nations across the world, india holds a significant position, and, therefore, a study on indian context can prove out to be significant from policymaking perspective. there lies a gap in the existing literature, and this is the focus of our paper. in this study, we intend to analyze the effect of economic growth on the energy efficiency in a trivariate framework consisting of economic growth, energy efficiency, and energy consumption. for this study, we have chosen energy waste as the proxy for energy efficiency, as reducing energy spillover is an indicator of energy efficiency, which is predominant in indian context. the rest of the paper is divided in three sections. in the second section details of the econometric methodology has been discussed, in the third section the results has been analyzed, and in the fourth and last section the concluding remarks of the study has been summarized. 2. econometric methodology in this section, we will discuss about the econometric methodologies applied to look into the association between economic growth, energy consumption, and energy waste. to start with, we should check the integration characteristics of the data. for this purpose, unit root tests have been applied. if variables in the dataset are i(1) in nature, then cointegration test is used to look into the long run equilibrium association among them. based on the findings of aforementioned test, order of integration will be found, and that will ensure the applicability of error correction model (ecm), based on which directions of causality among the variables are found. in the subsequent sections, we will discuss these methodologies one by one. 2.1 investigation for integration in most of the cases, time series economic data exhibits non-stationary nature, as their central tendencies are found to be upwards over a long period. however, in order to investigate the considerable long run association among the variables, carrying out non-stationarity test becomes essential. this test primarily focuses on order of integration, at which point considered variables become stationary in nature. the test is carried out on the level data, and subsequently on differentiated forms of the variables. for this purpose, we will apply augmented dickey-fuller test (dickey and fuller, 1981), phillips-perron test (phillips and perron, 1988), and kwiatkowski-phillipsschmidt-shin test (kwiatkowski et al., 1992). these three tests will be conducted for checking the serial correlation, heteroscedasticity, and deterministic trend present in variables under consideration. following are the test statistics considered for each of the cases: international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.96-104 98 augmented dickey-fuller (adf) test: 0 1/ 22 2 2 2 2 2. 1 . ( ) 2 t set                          (1) phillips-perron (pp) test:   2 2 2 2 1 . ( ) 2 t set             (2) kwiatkowski-phillips-schmidt-shin (kpss) test: 2 2 2 1 / t t t t s          (3) where, 2 1 2 1 lim t tt t t e u        (4) 2 1 2 1 lim t tt t e t s        (5) 1 t t t t s u   (6) 2.2 investigation for cointegration cointegration is an econometric methodology to investigate the subsistence of long run equilibrium association among variables. this is imperative from an algebraic perspective, as progression of the variables over a long timeframe adjusts the inconsistencies being appeared along the shorter durations. in accordance with dickey et al. (1991), if the cointegrated association among variables is not present or weak in nature, then probability of existence of variability in their long-term movement is very high. in view of the existence of this cointegrated association among variables, conducting a regression analysis becomes significant. however, for any number of non-stationary time series variables to be cointegrated, it is imperative for their linear combination to be stationary in nature (engle and granger, 1987). however, it is seemingly not appropriate to stick to a methodology, which is capable of analyzing the cointegrated association between only two variables. that is the reason behind our preference of the cointegration testing methodology by johansen and juselius (1990) over the one that of by engle and granger (1987), as scope of our analysis is not confined by bivariate nature of analysis. trace and maximum eigenvalue statistics are the two major components of this cointegration analysis (johansen, 1988, 1991). we will discuss both of these two statistics. consider yt as an (n x 1) vector of i(1) integrated variables and εt as an (n x 1) vector of error terms. then the vector autoregressive model (var) of order n can be expressed as per the following: 1 1 n t t i t i t i y y y            (7) where, 1 n i i a     (8) 1 n i j j i a       (9) precisely, ∏ contains the information about coefficients, which determine the nature of long run association among variables under consideration. rank of this matrix, which determines number of cointegrating vectors among variables, is calculated through two statistics, namely trace and maximum eigenvalue. the trace test embarks upon the null hypothesis of having cointegrating vectors equal to the rank of the matrix (say r) aligned with the alternate hypothesis of having cointegrating vectors of number n (< r). in case of the maximum eigenvalue test, it embarks upon null hypothesis of having cointegrating vectors equal to the rank of the matrix (= r) against the alternative hypothesis of having cointegrating vectors exactly one more than the rank of the matrix (= r + 1). the test statistics are as per the following: trace statistics (jjt) =   1 ln 1 n i r t      (10) modeling energy efficiency and economic growth: evidences from india 99 maximum eigenvalue statistics (jjme) =  1ln 1 rt   (11) where, η = ith principal canonical correlation 2.3 investigation for causality association in this section, we will make use of granger causality test (granger, 1969) to investigate the causal association encompassing parameters, namely economic growth, energy consumption, and energy waste for india. the granger causality test based on error correction model (toda and phillips, 1993) can be formulated in the following manner: 0 1 1 2 2 1 1 2 2 1 1 2 2 1 ln ln ln ... ln ln ln ... ln ln ln ... ln t t t n t n t t n t n t t n t n t eg a a eg a eg a eg b ew b ew b ew c ec c ec c ec ect                                   (12) 0 1 1 2 2 1 1 2 2 1 1 2 2 1 ln ln ln ... ln ln ln ... ln ln ln ... ln t t t n t n t t n t n t t n t n t ec a a ec a ec a ec b ew b ew b ew c eg c eg c eg ect                                   (13) 0 1 1 2 2 1 1 2 2 1 1 2 2 1 ln ln ln ... ln ln ln ... ln ln ln ... ln t t t n t n t t n t n t t n t n t ew a a ew a ew a ew b eg b eg b eg c ec c ec c ec ect                                   (14) where, eg stands for economic growth, ew stands for energy waste, ec stands for energy consumption, and ectt-1 is the lagged error correction term. gdp is used as a proxy measure for economic growth (eg), combustible waste as a percentage of total energy is used as a proxy measure for energy waste (ew), and energy usage of oil equivalent is used as a proxy measure for energy consumption (ec). the annual data from 1971 to 2010 has been taken from the world bank database. no major structural breaks are found for any of the three variables under consideration. 3. analysis analysis of collected data starts with checking the stationarity nature of variables under consideration, for which unit root tests have been conducted. the results of unit root test are recorded in table 1. it can be visualized that the level data does not show any indications of stationarity, which confirms existence of unit roots in all the four variables under consideration. subsequently, we moved towards differencing them and conducting unit root tests on the differentiated variables. it is evident from the results that all the four variables are showing stationary nature after first differentiation. this result also confirms that the variables are i(1) in nature (figure 1). table 1. unit root test results adf pp kpss level intercept eg 0.501026 0.383000 0.769768 ew 2.078668 1.983462 0.773819 ec 1.424505 1.492853 0.781439 intercept and trend eg -0.822281 -1.177163 0.109605 ew -2.744440 -2.744440 0.129813 ec -2.106200 -2.236296 0.073878 first difference intercept eg -5.492174a -5.583894a 0.201027 ew -5.320134a -5.314678a 0.411684 ec -6.112145a -6.116148a 0.235131 intercept and trend eg -5.468922a -5.505470a 0.173178 ew -5.759701a -5.754942a 0.130744 ec -6.296549a -6.296575a 0.087963 a value at 1% significance level b value at 5% significance level international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.96-104 100 figure 1. unit circle consisting of unit roots once it has been established that the variables are integrated of order one, it is needed to test the cointegration association between them. the cointegration testing methodology by johansen and juselius (1990) have been applied on the variables. the results are presented in table 2. the results show that a brawny long run association subsists among the variables. null hypotheses of having no cointegrating vectors have been rejected by both the statistics, and they show that one cointegrating vector is present between the variables. based on these results, we can proceed for further analysis. table 2. cointegration test results trace test maximum eigenvalue test null alternate jjt critical value null alternate jjme critical value r ≤ 0 r > 0 27.68362a 24.27596 r ≤ 0 r = 1 18.56885a 17.79730 r ≤ 1 r > 1 9.114769 12.32090 r ≤ 1 r = 2 6.274065 11.22480 ≤ 2 r > 2 2.840704 4.129906 r ≤ 2 r = 3 2.840704 4.129906 a value at 1% significance level “r” symbolizes the number of cointegrating vectors as we have seen the being of cointegration vectors among variables under consideration, we can proceed to formulate the ecm. the results of causality test are recorded in table 3. lag length selection criterion are provided in table 4. sequential modified lr test statistic (each test at 5% level), final prediction error, akaike information criterion, schwarz information criterion and hannan-quinn information criterion have been used for this purpose. we can see that unidirectional causality exists from economic growth to reduction in energy waste. between energy waste and economic growth, the nature of causality is both long run and short run in nature, which is demonstrated by the error correction term of eq. 14. however, error correction terms for eq. 12 and eq. 13 are not significant, and, therefore, the possibility of long run associations in those cases can be ruled out. a short run causal association subsists from economic growth to energy consumption, which has already been established by paul and bhattacharya (2004). however, we are not interested in this causal association, as this is already a well-established area in the literature of energy economics, and ozturk (2010) has given a detailed literature survey on this aspect. modeling energy efficiency and economic growth: evidences from india 101 table 3. causality test results independent variable error correction term dependent variable ∆eg ∆ew ∆ec ∆eg 3.997988c 2.499220 0.028486 ∆ew 6.747354b 4.028595 -0.261548c ∆ec 6.728901b 1.975873 0.359923 a value at 1% significance level b value at 5% significance level c value at 10% significance level deductions: ∆ew <= ∆eg table 4. lag length selection results lag logl lr fpe aic sc hq 0 106.5230 na 6.38e-07 -5.751275 -5.619315 -5.705218 1 289.8563 325.9260* 3.98e-11* -15.43646* -14.90862* -15.25223* 2 295.9775 9.861916 4.73e-11 -15.27653 -14.35281 -14.95413 3 307.3600 16.44142 4.27e-11 -15.40889 -14.08929 -14.94832 4 313.5701 7.935037 5.28e-11 -15.25389 -13.53841 -14.65514 lr: sequential modified lr test statistic (each test at 5% level) fpe: final prediction error aic: akaike information criterion sc: schwarz information criterion hq: hannan-quinn information criterion by far, fossil fuel based energy consumption amounts to nearly 73 percent of the total energy consumption in india. hence, for india, fossil fuel consumption is the primary reason for greenhouse blanket formation. from this perspective, it can be said that, whenever energy conservation practices are considered, it majorly poses impacts on the driver of economic growth and the externalities caused by growth. in this case, the externality is negative in nature, and is having the form of co2 emission. therefore, to have a control over this negative externality, it is required to have energy efficiency, which can be indicated by lowering of combustible energy waste, the intervention used in this case. considering india, formation of petroleum conservation research association (pcra) in 1977, and bureau of energy efficiency in 2001 are two major steps in bringing forth energy efficiency in indian industrial scenario. due to this, we can see that 10.86 percent growth rate of co2 emission per unit of fossil fuel consumption during first half of the study had come down to 0.84 percent during second half of the study period, indicating a nearing zero fossil fuel consumption elasticity of emission. moreover, it also can be seen that the 2.16 percent average growth rate of fossil fuel consumption during first half of the study period has come down to 1.37 percent during second half of the study period. indicating energy efficiency, the diminishing growth of fossil fuel consumption can have a possible causal effect on economic growth, due to which it became imperative to fuel economic growth via alternative and nuclear renewable resources, as fossil fuel consumption per unit of gdp has come down to 2.99 percent in 2010 from 8.49 percent in 1971. by looking at the economic efficiency frontier in figure 2, it can be said that the energy waste follows a negatively elastic relationship with the economic growth, which means that economic growth and energy efficiency are following a positive association, and this association is signified by the economic growth elasticity of energy waste i.e. -12.42 per cent. this entire scenario points towards achievement of a sustainable energy-led economic growth, which is characterized by going for alternate and renewable sources of energy, like nuclear power, solar power, wind energy, etc. the pattern of economic growth in india is itself calling for efficient energy management initiatives, in which the wastage and spillover of commercial energy can be reduced to the minimum extent possible. in addition, this demand, associated with the negative elasticity is characterized by the unidirectional causal association from economic growth to reduction in energy waste. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.96-104 102 figure 2. energy efficiency frontier graphical reconfirmation of the aforementioned results has been provided as generalized impulse responses (figure 3). results of impulse response functions endow us with additional impending towards established causal associations among the variables. to set off this study, it is imperative to look into the long-run stability of the associations among the variables. for this purpose, we have carried out a series of diagnostic tests to check serial correlation (lm test), heteroscedasticity (white test) and stability test (ramsey reset test). the results those are recorded in table 5, confirm the constancy of the model analyzing the associations among economic growth, energy consumption, and energy waste. figure 3. generalized impulse responses -40,000 0 40,000 80,000 120,000 160,000 1 2 3 4 5 6 7 8 9 10 ec eg ew accumulated response of ec to cholesky one s.d. innovations 0e+00 2e+11 4e+11 6e+11 8e+11 1e+12 1 2 3 4 5 6 7 8 9 10 ec eg ew accumulated response of eg to cholesky one s.d. innovations -4 -2 0 2 4 6 8 1 2 3 4 5 6 7 8 9 10 ec eg ew accumulated response of ew to cholesky one s.d. innovations modeling energy efficiency and economic growth: evidences from india 103 table 5. diagnostic test results variables r2 adj. r2 lm white ramsey reset eg 0.991558 0.990855 15.97802a 3.936801a 119.1980a ew 0.979841 0.978161 52.36818a 13.39543a 945.3439a ec 0.996203 0.995887 10.18507a 4.438088a 20.69747a 4. conclusion the study investigates about the long-run causal associations among economic growth, energy waste, and energy consumption, considering the statistics for india during 1971-2010. the econometric analysis of the data substantiates the following findings: first, the considered variables are showing stationarity after first differentiation, and they are first order integrated. second, long run equilibrium associations among the variables are ensured by the presence of one cointegrating vector. third, the econometric model shows unidirectional causal association from economic growth to reduction in energy waste, and this causal association is both short run and long run in nature. this study by far concludes that devoid of an efficient energy management initiative, a sustainable economic growth objective can never be attained, as it acts as a mediating feature between energy consumption and energy waste. while focusing on policy decisions regarding economic growth, leaving apart the environmental aspects always poses a serious threat towards the sustainable growth objective, which is not desirable for a developing nation like india. this issue has been addressed by the established unidirectional causal association from economic growth to reduction in energy waste. references acharyya, j. (2009), fdi, growth and the environment: evidence from india on co2 emission during the last two decades. journal of economic development, 34(1), 43-58. asif, m., muneer, t. (2007), energy supply, its demand and security issues for developed and emerging economies. renewable and sustainable energy reviews, 11(7), 1388-1413. bozkurt, c., akan, y. (2014), economic growth, co2 emissions and energy consumption: the turkish case. international journal of energy economics and policy, 4(3), 484-494. brookes, l. (1990), the greenhouse effect: the fallacies in the energy efficiency solution. energy policy, 18(2), 199-201. cheng, b.s. (1999), causality between energy consumption and economic growth in india: an application of cointegration and error-correction modeling. indian economic review, 34(1), 39-49. dickey, d.a., fuller, w.a. (1981), likelihood ratio statistics for autoregressive time series with a unit root. econometrica, 49(4), 1057-1072. dickey, d.a., jansen, d.w., thornton, d.l. (1991), a primer on cointegration with an application to money and income. federal reserve bank of st. louis review, 73, 58-78. engle, r.f., granger, c.w.j. (1987), co-integration and error correction: representation, estimation, and testing. econometrica, 55(2), 251-276. ghosh, s. (2002), electricity consumption and economic growth in india. energy policy, 30(2), 125129. granger, c.w.j. (1969), investigating causal relations by econometric and cross-spectral methods. econometrica, 37(3), 424-438. hondroyiannis, g., lolos, s., papapetrou, e. (2002), energy consumption and economic growth: assessing the evidence from greece. energy economics, 24(4), 319-336. howarth, r.b. (1997), energy efficiency and economic growth. contemporary economic policy, 15(4), 1-9. hu, j.l., wang, s.c. (2006), total-factor energy efficiency of regions in china. energy policy, 34(17), 3206-3217. johansen, s. (1988), statistical analysis of cointegration vectors. journal of economic dynamics and control, 12(2), 231-254. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.96-104 104 johansen, s., juselius, k. (1990), maximum likelihood estimation and inference on cointegration-with applications to the demand for money. oxford bulletin of economics and statistics, 52(2), 169-210. johansen, s. (1991), estimation and hypothesis testing of cointegration vectors in gaussian vector autoregressive models. econometrica, 59(6), 1551-1580. khazzoom, j.d. (1980), economic implications of mandated efficiency in standards for household appliances. the energy journal, 1(4), 21-40. kwiatkowski, d., phillips, p.c., schmidt, p., shin, y. (1992), testing the null hypothesis of stationarity against the alternative of a unit root: how sure are we that economic time series have a unit root. journal of econometrics, 54(1), 159-178. mahadevan, r., asafu-adjaye, j. (2007), energy consumption, economic growth and prices: a reassessment using panel vecm for developed and developing countries.energy policy, 35(4), 2481-2490. marton, k. (1986), technology transfer to developing countries via multinationals. the world economy, 9(4), 409-426. ozturk, i. (2010), a literature survey on energy-growth nexus. energy policy, 38(1), 340-349. paul, s., bhattacharya, r.n. (2004), causality between energy consumption and economic growth in india: a note on conflicting results. energy economics, 26(6), 977-983. pérez-lombard, l., ortiz, j., pout, c. (2008), a review on buildings energy consumption information. energy and buildings, 40(3), 394-398. phillips, p.c., perron, p. (1988), testing for a unit root in time series regression. biometrika, 75(2), 335-346. saunders, h.d. (1992), the khazzoom-brookes postulate and neoclassical growth. the energy journal, 13(4), 131-148. shahateet, m.i. (2014), modeling economic growth and energy consumption in arab countries: cointegration and causality analysis. international journal of energy economics and policy, 4(3), 349-359. siddharthan, n.s., lal, k. (2004), liberalisation, mne and productivity of indian enterprises. economic and political weekly, 39(5), 448-452. sinha-khetriwal, d., kraeuchi, p., schwaninger, m. (2005), a comparison of electronic waste recycling in switzerland and in india. environmental impact assessment review, 25(5), 492504. smulders, s., de nooij, m. (2003), the impact of energy conservation on technology and economic growth. resource and energy economics, 25(1), 59-79. stern, d.i. (1993), energy and economic growth in the usa: a multivariate approach. energy economics, 15(2), 137-150. toda, h.y., phillips, p.c. (1993), vector autoregressions and causality. econometrica, 61(6), 13671393. wolde-rufael, y. (2006), electricity consumption and economic growth: a time series experience for 17 african countries. energy policy, 34(10), 1106-1114. . international journal of energy economics and policy | vol 10 • issue 4 • 2020318 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(4), 318-324. analysis of the relationship between energy consumption and economic growth in the commonwealth of independent states aziza syzdykova1*, gulmira azretbergenova1, khairulla massadikov2, aigul kalymbetova1, darkhan sultanov1 1department of finance and accounting, khoja akhmet yassawi international kazakh-turkish university, turkestan, kazakhstan, 2department of public administration and regional development, khoja akhmet yassawi international kazakh-turkish university, turkestan. kazakhstan. *email: azizayesevi@gmail.com received: 20 january 2020 accepted: 27 april 2020 doi: https://doi.org/10.32479/ijeep.9264 abstract since energy is one of the indispensable elements of our lives, it is one of the most studied topics today. utilization of energy with the highest efficiency capacity is very important for sustaining the growth of the countries. effects of energy consumption on economic growth differ from country to country depending on economic structure and economic growth process of country. for this reason, there is no exact opinion related to direction of causality relationship between energy consumption and economic growth. in the literature there are four hypotheses (growth, protective, objectivity, feedback) which explain the relationship of the point in the question. in this context, in order to implement a strategically correct energy policy, one of the growth and energy indicators should be tested correctly. this study examines the relationship between energy consumption and economic growth in commonwealth of independent states (cis) for the period of 1992-2018. according to the findings of the study, there is a two-way causality between energy consumption and economic growth in cis countries. this shows that the feedback hypothesis is valid in these countries. keywords: energy consumption, economic growth, cis countries, panel co-integration, panel causality jel classifications: o40, q43, q40 1. introduction the commonwealth of independent states (cis) founded in 1991, is composed of twelve countries of the former soviet union (armenia, azerbaijan, belarus, kazakhstan, kyrgyz republic, moldova, russia, tajikistan, turkmenistan, ukraine, uzbekistan). georgia later joined in 1993, but georgia’s membership to the cis expired on august 17, 2009. ukraine left the community after russia annexed crimea in march 2014. as of 2019, the member states of the cis; armenia, azerbaijan, belarus, kazakhstan, kyrgyz republic, moldova, russia, tajikistan, turkmenistan, uzbekistan (world bank, 2019). with their rich energy resources, cis countries play an important role in world energy markets both as producers and as transit centers for the distribution of energy (syzdykova, 2018a). today, the most important economic goals of the countries are to achieve economic growth. numerous studies have been carried out on growth from the past to the present and continue to be done. energy has been recognized by studies conducted by various economists as an important factor for growth (syzdykova, 2018b). understanding the relationship between energy consumption and economic growth is vital for effective energy policies to be implemented. when we look at the example of cis, it is seen that the member countries of this community are different from each other in terms of natural resource ownership, energy use and development levels. in addition, developing and transition countries operate in energyintensive areas in order to achieve higher economic growth rates (dedeoglu and piskin, 2014. p. 96). this journal is licensed under a creative commons attribution 4.0 international license syzdykova, et al.: analysis of the relationship between energy consumption and economic growth in the commonwealth of independent states international journal of energy economics and policy | vol 10 • issue 4 • 2020 319 effects of energy consumption on economic growth differ from country to country depending on economic structure and economic growth process of country. for this reason, there is no exact opinion related to direction of causality relationship between energy consumption and economic growth. in the literature there are four hypotheses (growth, protective, objectivity, feedback) that explain the relationship that the point in the question (akadiri et al., 2019). the existence of one-way causality from energy consumption to economic growth (growth hypothesis) indicates that economic growth is energy dependent. in this case, energy saving policies may adversely affect economic growth. on the other hand, it shows that energy conservation policies may have little or no impact on economic growth in the case of one-way causality (conservative hypothesis) from economic growth to energy consumption. the presence of a two-way causality (feedback hypothesis) reflecting interdependence and possible complementarity between energy consumption and economic growth is also possible. finally, the lack of a causal relationship between energy consumption and economic growth (the neutrality hypothesis) means that energy saving policies will have a negligible impact on economic growth (apergis and payne, 2010). this study aims to test the connection between energy consumption and economic growth in cis countries using panel data analysis. in the second part of the study, a general evaluation is made on the energy production and consumption of cis member countries and the environmental impact of energy consumption. in the third chapter, empirical studies on the relationship between energy consumption and economic growth are given. in the fourth chapter, empirical results are discussed after explaining the data and methodology. in the conclusion part, various evaluations are made according to the findings obtained by empirical analysis. 2. energy production and consumption in the commonwealth of independent states according to bp (2019), russia is the world’s largest producer of crude oil and the second largest producer of natural gas. in addition, russia has the world’s largest natural gas reserve with 1680 trillion cubic feet. furthermore, russia’s revenues from oil and natural gas exports account for more than 40% of federal budget revenues. among the cis countries, russia, kazakhstan and azerbaijan are net oil exporters, while other cis countries are net importers. besides, turkmenistan and uzbekistan follow russia in terms of natural gas production. although turkmenistan and uzbekistan follow russia concerning natural gas production, both of these countries have insufficient pipeline infrastructure for natural gas exports. table 1 provides an overview of energy production and consumption in cis countries. accordingly, the need for energy resources in cis countries continues to increase every year. especially in cis countries, the demand for energy will be more intense in the coming years in parallel with the increase in population after the independence, industrialization, increasing the welfare level of people and technological developments. cis countries consume approximately 6.7% of the total primary energy consumption in the world. table 2 shows the sources of primary energy consumption in cis countries. 53% of the total primary energy consumption in cis countries is natural gas, 20% is petroleum resources, 21% is coal and nuclear resources. the share of renewable energy (including hydropower) in the first energy sources consumption in these countries is 6%. as can be seen from the table 2, cis countries are different from each other in terms of energy sources where energy is provided. while the main source of primary energy consumption in azerbaijan, belarus, russia and uzbekistan is natural gas, coal is the source of more than half of the energy consumption in kazakhstan. energy (electricity) production in the cis countries tajikistan stems mainly from hydropower. on the other hand, carbon dioxide emissions in metric tons per capita, which is a measure of the environmental consequences of energy production and consumption, is an important issue. regarding the environment, cis countries face major problems in reducing greenhouse gas emissions. kazakhstan has the highest carbon dioxide emissions per capita. tajikistan has the lowest carbon dioxide emission per capita among the cis countries. carbon dioxide emissions per capita range from a low of 0.77 mt/ capita in tajikistan to a high of 13.33 mt/capita in kazakhstan. it is interesting to note that the countries with the lowest carbon dioxide emissions per capita (tajikistan 0.77, georgia 0.86, and kyrgyzstan 1.12) have the highest percentage of electricity production from hydroelectric power (tajikistan 97.65%, kyrgyzstan 86.87%, and georgia 85.81%) (world bank, 2019). 3. theoretical and empirical literature since energy is an important variable of production function, it is also assumed to be closely related to economic growth (yildirim et al., 2014. p. 14). therefore, the focus of energy policies is economic growth. there are many different ideas about how energy affects growth. this is due to the differences in the growth policies of countries (belke et al., 2011. p. 782). these differences have led to various hypotheses. when the studies in the literature are examined, it is seen that four different hypotheses are proposed for the energy-growth relationship (wolde-rufael, 2014. p. 326). in the literature, the causality relationship between energy consumption and gross domestic product (gdp) has been examined under four hypotheses (pirlogea and cicea, 2012; ozturk, 2010): (1) growth hypothesis: if causality is from energy expenditures to economic growth, this shows that the country is an energy dependent country. therefore, the fall in the energy bottleneck will adversely affect economic growth. in addition, it is seen that policies envisaging a reduction in energy expenditures will adversely affect economic growth (ciarreta and zarraga, 2010). (2) conservation hypothesis: if the causality relationship is from economic growth to energy expenditures, then it appears that the country is not dependent on energy to sustain economic growth. syzdykova, et al.: analysis of the relationship between energy consumption and economic growth in the commonwealth of independent states international journal of energy economics and policy | vol 10 • issue 4 • 2020320 this shows that energy conservation policies will not adversely affect economic growth. in addition, as gdp increases, energy consumption will increase. (3) feedback hypothesis: if there is a two-way causality between energy expenditures and gdp, energy expenditures and gdp affect each other. in a country with such a relationship, increasing gdp means increasing energy consumption, while increasing energy consumption increases gdp. accordingly, it is of great importance that a country showing a two-way dependence on energy can generate the energy it needs and turn to renewable energy resources in this context (pirlogea and cicea, 2012). (4) neutrality hypothesis: it shows that there is no causal relationship between these two variables. when the studies examining the causality between energy consumption and economic growth for cis countries are examined; dedeoglu and piskin (2014) examined 15 former soviet union countries for the period 1992-2009 and showed that there was a one-way causality relationship from energy consumption to real gdp per capita. apergis and payne (2009) found a two-way causal relationship between energy consumption and economic growth in their study based on the period 1991-2005 for 11 cis countries. apergis and payne (2010) examined the relationship between co2 emission, economic growth and energy consumption for 11 cis countries in 1992-2004 and found that there is a oneway causality relationship from energy consumption to economic growth in the short term. in addition, zhang (2011) examined the relationship between economic growth and energy consumption for russia in the 1970-2008 period and concluded that there is a two-way causality relationship between energy consumption and economic growth. syzdykova (2018b) also found similar results in her study for central asian countries. kalyoncu et al. (2013) investigated the relationship between energy consumption and economic growth in georgia, azerbaijan and armenia during the period of 1995-2009. for georgia and azerbaijan it is found that these two variables are not cointegrated. in case of armenia these two variables are cointegrated. accordingly, causality analysis is conducted for armenia. the research outcomes reveal that there is unidirectional causality from per capita gdp to per capita energy consumption for armenia. table 3 summarizes the empirical studies investigating the relationship between energy consumption and economic growth. what is important here is the policy implications of the causality aspect between energy consumption and economic growth between countries and country groups. if the growth hypothesis is valid in a country, it indicates that economic growth is energy dependent. in this case, energy saving policies may adversely affect economic growth. it suggests that energy conservation policies may have little or no impact on economic growth in the case of a savings assumption. there is also the case where the feedback hypothesis, which reflects interdependence and possible complementarity between energy consumption and economic growth, is valid. finally, the neutral hypothesis implies that energy saving policies will have a minor impact on economic growth (apergis and payne, 2010. p. 1422-1423). 4. data and methodology in this study, the relationship between primary energy consumption and economic growth of cis countries (armenia, azerbaijan, belarus, kazakhstan, kyrgyz republic, moldova, russia, tajikistan, turkmenistan, uzbekistan) was examined by using panel data analysis. co-integration and causality analysis was applied to determine whether there is a relationship between these variables. in this study, data on energy consumption were used as “kg of oil equivalent per capita” for each country. economic growth refers to gdp per capita in us dollars at market prices. energy consumption data from the cis countries, the american energy agency and data on economic growth were obtained from the world bank’s table 1: primary energy: consumption million tons oil equivalent 2000 2005 2010 2015 2016 2017 2018 share (%) azerbaijan 11.3 14.3 11.2 14.7 14.6 14.3 14.4 0.1 belarus 22.0 24.6 26.0 23.2 23.0 23.4 24.6 0.2 kazakhstan 31.3 45.4 54.9 63.7 64.7 67.6 76.4 0.6 russia 613.4 640.3 669.3 675.4 690.5 694.3 720.7 5.2 turkmenistan 10.3 15.2 21.5 28.6 27.5 28.7 31.5 0.2 uzbekistan 51.1 48.1 44.4 44.9 43.6 45.0 43.9 0.3 other cis 13.1 15.3 15.9 17.4 17.5 18.0 19.0 0.1 total cis 752.4 803.2 843.2 867.9 881.5 891.2 930.5 6.7 source: bp, 2019 table 2: primary energy: consumption by fuel, 2018 million tons oil equivalent oil natural gas coal nuclear energy hydro electric renewables total azerbaijan 4.6 9.3 ^ 0.4 ^ 14.4 belarus 6.8 16.6 1.0 0.1 0.1 24.6 kazakhstan 16.4 16.7 40.8 2.3 0.1 76.4 russia 152.3 390.8 88.0 46.3 43.0 0.3 720.7 turkmenistan 7.1 24.4 ^ 31.5 uzbekistan 2.6 36.6 3.1 1.6 43.9 other cis 3.7 4.9 2.0 0.5 8.0 ^ 19.0 total cis 193.5 499.4 134.9 46.7 55.4 0.6 930.5 ^less than 0.05. source: bp, 2019 syzdykova, et al.: analysis of the relationship between energy consumption and economic growth in the commonwealth of independent states international journal of energy economics and policy | vol 10 • issue 4 • 2020 321 official website. in order to ensure that the variables are suitable for analysis and to minimize the measurement differences between them, the data was taken by logarithm. the model equation used in the study is as follows: lngrowth lnenergyit it it it it� � �� � � (1) in equation (1), i=1,…,10 represents the countries and t=1992,1993…,2018 represents the time period. the basic hypothesis of the study is as follows: h1: there is a positive relationship between economic growth and energy consumption. in the literature, studies on the relationship between economic growth and energy consumption are discussed in the literature review section. in this section, the h1 hypothesis will be tested by panel data analysis for cis countries. panel data is generated by combining the time series of economic individuals with the horizontal cross-sectional dimension (syzdykova et al., 2019). within the scope of panel data analysis, the existence of horizontal cross-sectional dependence between the units forming the series was first tested by breush pagan and pesaran et al. (2008) lm analyzes. considering the horizontal cross-section dependence between the series is important in the selection of the tests to be discussed in the next stages. the dependence of the horizontal cross-section means that a shock to one of these will affect the other cross-section. the investigation of cross-sectional dependence is important for considering the high level of globalization in the economic relations between countries. in the second stage, panel unit root tests were used to test whether the variables contain unit root, and in the next stage the panel cointegration tests were examined to see if there was a long term relationship between the variables. then, the coefficients of the long-term relationship between the variables were estimated by the amg (augmented mean group estimator) method proposed in eberhardt and bond (2009). finally, the causality relationship between the variables was tested by dumitrescu and hurlin (2012) panel causality test. 5. results 5.1. cross sectional analysis if there is a cross-sectional dependence between the series, the selection of root and co-integration tests of one, regardless of this, can significantly affect the results of the analyzes. the causes of horizontal cross-sectional dependence can be listed as spatial effects, unobserved components, common shocks and globalization of the world economy. if t>n is the number of time size observations in panel data models, breusch and pagan (1980) table 3: summary of empirical studies author period country and country group method results kraft and kraft (1978) 1947-1974 usa granger causality eg→ec cheng and lai (1997) 1955-1993 taiwan co-integration, hsiao granger causality eg→ec asafu-adjaye (2000) 1973-1995 1971-1995 india, indonesia, thailand, philippines co-integration, error correction model, granger causality ec→eg (india, indonesia) eg↔ec (thailand, philippines) oh and lee (2004) 1981-2000 korea co-integration, granger causality in the short term: ec--eg in the long term:: eg→ec ghali and sakka (2004) 1961-1997 сanada co-integration, error correction model, granger causality eg↔ec narayan and smyth (2008) 1972-2002 g7 pedroni (1999) and westerlund (2006) co-integration, error correction model, granger causality in the long term: ec→eg huang et al. (2008) 1971-2002 82 countries threshold variables approach ec→eg (for 48 country) ozturk et al. (2010) 1971-2005 low and middle income countries pedroni (1999; 2001) panel cointegration method eg→ec in low income countries eg↔ec in middle income countries herrerias et al. (2013) 1995-2009 different regions of china co-integration, error correction model, granger causality eg→ec alaali et al. (2015) 1981-2009 oil exporting and developed country groups (130 countries) generalized moments method ec→eg alshehry and belloumi (2015) 1971-2010 saudi arabia johansen co-integration eg↔ec long et al. (2015) 1952-2012 china co-integration analysis eg↔ec shahbaz et al. (2016) 1970-2012 australia vecm eg↔ec wang et al. (2016) 1990-2012 china granger causality eg↔ec mirza and kanwal (2017) 1971-2009 pakistan ardl–vecm eg↔ec jebli and youssef (2017) 1980-2011 tunisia vecm eg↔ec riti et al. (2017) 1970-2015 china ardl–vecm eg←ec shabestari (2018) 1970-2016 sweden ardl–vecm eg↔ec bekun et al. (2019) 1960-2016 south africa pesaran et al. (2001) bounds test eg←ec eg: economic growth, ec: energy consumption. →: represents unidirectional, ↔: is bidirectional, --: presents no relationship. source: ozturk (2010); ahmed et al. (2017); syzdykova (2018b); waheed et al. (2019) syzdykova, et al.: analysis of the relationship between energy consumption and economic growth in the commonwealth of independent states international journal of energy economics and policy | vol 10 • issue 4 • 2020322 and pesaran et al. (2008) tests should be preferred. otherwise, friedman (1937), frees (1995) and pesaran (2004) horizontal section dependency tests can be used (de hoyos and sarafidis, 2006). since t=27 and n=10, breusch and pagan (1980) and pesaran et al. (2008) tests would be more appropriate. for each test h0 hypothesis is “no cross-sectional dependence” and for h1 hypothesis “there is cross-sectional dependence.” the results obtained from the cross-section dependency test are presented in table 4. as the result of the test, the probability values of the variables are <0.05, h0 hypothesis can be rejected and it is decided that there is a horizontal cross-section dependence in the series. this result is a realistic approach when one considers that the economies are closely related to each other and that one of the countries constituting the panel is affected. 5.2. panel unit root tests since the panel data has a time series dimension, it is important to conduct a stasis test to reflect the realistic relationship of the results. misleading results are obtained when experimental analyzes are performed between non-stationary series (syzdykova et al., 2019a). since there is a cross-sectional dependence in the series used in the study, we estimate the mean of cadf (cross sectional augmented dickey fuller) test developed by pesaran (2007. p. 265-312), which is a second generation unit root test, in order to obtain more consistent and reliable results. cips (crosssectional augmented version of ips) statistics were applied. in the table 5, pesaran (2007) panel unit root test results are given. here, cadf test results are shown for both as well asinterceptand intercept and trend cases, and critical values are given at t (t-bar) statistic value and 95% confidence level. as a result of the unit root test, it can be seen from the table 5 that the level values are not stationary even if the series includes the trend of deterministic components. this means that the shock effects on the series do not disappear over time. when the first order difference is taken, the variables become stagnant according to all statistical test values, that is, i (1) carries the process. co-integration analysis was performed because of the same degree of stability. 5.3. panel co-integration tests the concept of co-integration reveals the long-term relationship between economic variables. the most important feature of these tests is to express whether two or more variables are integrated. in the study, co-integration analysis developed by pedroni (2004. p. 597-625) was used (table 6). although the pedroni co-integration test detects the co-integration relationship in the panel data, the westerlund ecm panel cointegration test was used for a more consistent analysis based on the assumption that the series forming the panel were equally stable and in the first difference, taking into account the horizontal cross-section dependence and heterogeneity between the data. westerlund (2007. p. 709-748) developed four panel co-integration tests based on the error correction model. two of these tests are called group average statistics and the other two are called panel statistics (table 7). when the co-integration test results are examined, it can be concluded that there is a co-integration relationship between the series. in other words, tests with original values will not include false regression. according to the results of the co-integration test, when the strong probability values of the test statistics considering the cross-sectional dependence in cis countries, it is concluded that there is a long-term relationship between energy consumption and economic growth at 5% significance level in the long run. 5.4. estimation of long-term co-integration coefficients after determining the co-integration relationship between the series, long-term individual co-integration coefficients analyzed by amg (augmented mean group estimator) which taking into account the horizontal cross-sectional dependency, different coefficients of the cross-sectional equations (eberhardt and bond, 2009. p. 1-26). in the panel amg method, the result weighted average group effect of the overall panel is calculated (table 8). the panel amg estimation results are as follows: when the panel is examined, it is seen that economic growth in cis countries has a statistically significant and positive effect on energy consumption in the long term. according to the test results, table 4: cross-sectional dependence test variables breusch and pagan (1980) lm test pesaran et al. (2008) lm test t-statistics probability t-statistics probability ngrowth 763.9 0.003 351.7 0.000 lnenergy 274.3 0.000 119.3 0.000 table 5: pesaran panel unit root test results variables level 1st difference t̠ 5% t̠ 5% lngrowth intercept −0.961 −2.330 −2.682* −2.330 intercept and trend −0.650 −2.830 −3.360* −2.830 lnenergy intercept −1.580 −2.330 −4.742* −2.330 intercept and trend −1.750 −2.830 −4.389* −2.830 table 6: pedroni co-integration test results t statistics p-value panel v-statistic 3.251 0.000* panel rho-statistic 0.429 0.768 panel pp-statistic −0.958 0.201 panel adf-statistic −1.744 0.05** group rho-statistic 1.931 0.654 group pp statistic −2.855 0.001* group adf statistic −3.809 0.000* *and **represent significance levels of 1% and 5%, respectively table 7: westerlund (2007) panel co-integration test results test test statistical value z-value p-value robust p-value gt −2.269 1.768 0.872 0.659 ga −18.598 −3.485 0.000* 0.011** pt −4.523 2.251 0.887 0.899 pa −15.150 −3.084 0.001* 0.102 *and **represent significance levels of 1% and 5%, respectively syzdykova, et al.: analysis of the relationship between energy consumption and economic growth in the commonwealth of independent states international journal of energy economics and policy | vol 10 • issue 4 • 2020 323 a 10% increase in energy consumption in these countries leads to an increase of 1.15% on economic growth. the most significant effect of energy consumption on growth by countries; russia and turkmenistan. 5.5. panel causality test the results of the causality test developed by dumitrescu and hurlin (2012) for the panel data model with heterogeneous and cross-sectional dependence are presented in table 9. in the causality analysis, the series were used as stationary. the lag length was selected according to the aic. for the causality test developed by dumitrescu and hurlin (2012), it is recommended to use zn t, test statistic with asymptotic distribution when t>n and zn hnc test statistic with semi-asymptotic distribution when t<n (syzdykova et al., 2019b). in the study, since t>n, zn t, (z-bar) test statistics were considered. according to the results in table 9, there is a two-way causality relationship between economic growth and energy consumption in cis countries concerning to 1% significance level. this result shows that the feedback hypothesis developed from the hypotheses related to the relationship between energy consumption and economic growth in cis countries is valid. 6. conclusion energy is an important input of economic growth that shapes the policies of the world and countries. continuity of energy is necessary for the growth of the economy with the increase of the production of the countries and the decrease of the unemployment. the focus on energy consumption and economic growth is the direction and extent of the impact of energy consumption on economic growth. there is still no consensus in the literature on the direction of causality between energy consumption and economic growth variables. the results of the studies vary according to the method used, the period under consideration, country groups and the places where the data were taken. this has led to different results for the same country. in this study, the relationship between energy consumption and economic growth with the data of 1992-2018 period for cis countries (armenia, azerbaijan, belarus, kazakhstan, kyrgyz republic, moldova, russia, tajikistan, turkmenistan, uzbekistan) was examined with panel data analysis. panel co-integration tests reveal a long-term equilibrium relationship between energy consumption and economic growth. the increase in energy consumption in cis countries positively and significantly affects economic growth and the 10% increase in energy consumption increases economic growth by 1.1567%. according to dumitrescu and hurlin (2012) panel causality test results, energy consumption and economic growth bi-directional causality relationship was found in cis countries. this result is proof that the feedback hypothesis is valid in the cis countries. according to this hypothesis, the increase in the energy use resulting from growth needs to be well studied and correct saving policies should be implemented. otherwise, energy saving policies may damage economic growth. references ahmed, k., rehman, m.u., ozturk, i. (2017), what drives carbon dioxide emissions in the long-run? evidence from selected south asian countries. renewable and sustainable energy reviews, 70, 1142-1153. akadiri, s.s., bekun, f.v., taheri, e., akadiri, a.c. (2019), carbon emissions, energy consumption and economic growth: a causality evidence. international journal of energy technology and policy, 15(2-3), 320-336. alaali, f., roberts, j., taylor, k. (2015), the effect of energy consumption and human capital on economic growth: an exploration of oil exporting and developed countries. sheffield economic research papers series. alshehry, a.s., belloumi, m. (2015), energy consumption, carbon dioxide emissions and economic growth: the case of saudi arabia. renewable and sustainable energy reviews, 41, 237-247. apergis, n., payne, j.e. (2009), energy consumption and economic growth: evidence from the commonwealth of independent states. energy economics, 31(5), 641-647. apergis, n., payne, j.e. (2010), the emissions, energy consumption, and growth nexus: evidence from the commonwealth of independent states. energy policy, 38(1), 650-655. asafu-adjaye, j. (2000), the relationship between energy consumption, energy prices and economic growth: time series evidence from asian developing countries. energy economics, 22(6), 615-625. bekun, f.v., emir, f., sarkodie, s.a. (2019), another look at the relationship between energy consumption, carbon dioxide emissions, and economic growth in south africa. science of the total environment, 655, 759-765. belke, a., dobnik, f., dreger, c. (2011), energy consumption and economic growth: new insights into the cointegration relationship. energy economics, 33(5), 782-789. bp. (2019), statistical review of world energy. 68th ed. available from: https://www.bp.com/content/dam/bp/business-sites/en/global/ corporate/pdfs/energy-economics/statistical-review/bp-stats-reviewtable 8: long-term co-integration coefficients coefficient p-value armenia 0.0734 0.000* azerbaijan 0.1927 0.000* belarus 0.1456 0.000* kazakhstan 0.1687 0.1203 kyrgyz republic 0.0980 0.077*** moldova −0.1236 0.100 russia 0.3896 0.001* tajikistan 0.0289 0.000* turkmenistan 0.2398 0.028** uzbekistan 0.1963 0.000* panel 0.1567 0.000* *, ** and ***represent significance levels of 1% and 5%, respectively table 9: dumitrescu and hurlin (2012) test results null hypothesis test statistics p-value growth is not the granger cause of energy consumption z-bar z-bar tilde 4.7978 3.5763 0.0000 0.0001 energy consumption is not the granger cause of growth z-bar z-bar tilde 4.1371 2.9813 0.0000 0.0025 syzdykova, et al.: analysis of the relationship between energy consumption and economic growth in the commonwealth of independent states international journal of energy economics and policy | vol 10 • issue 4 • 2020324 2019-full-report.pdf. [last accessed on 23 dec 2019]. breusch, t.s., pagan, a.r. (1980), the lagrange multiplier test and its applications to model specification in econometrics. the review of economic studies, 47(1), 239-253. cheng, b.s., lai, t.w. (1997), an investigation of co-integration and causality between energy consumption and economic activity in taiwan. energy economics, 19, 435-444. ciarreta, a., zarraga, a. (2010), economic growth-electricity consumption causality in 12 european countries: a dynamic panel data approach. energy policy, 38(7), 3790-3796. de hoyos, r.e., sarafidis, v. (2006), testing for cross-sectional dependence in panel-data models. the stata journal, 6(4), 482-496. dedeoglu, d., piskin, a. (2014), a dynamic panel study of energy consumption-economic growth nexus: evidence from the former soviet union countries. opec energy review, 38(1), 75-106. dumitrescu, e.i., hurlin, c. (2012), testing for granger non-causality in heterogeneous panels. economic modelling, 29(4), 1450-1460. eberhardt, m., bond, s. (2009), cross-section dependence in nonstationary panel models: a novel estimator. mpra paper no. 17692. friedman, m. (1937), the use of ranks to avoid the assumption of normality implicit in the analysis of variance. journal of the american statistical association, 32(200), 675-701. frees, e.w. (1995), assessing cross-sectional correlation in panel data. journal of econometrics, 69(2), 393-414. ghali, k.h., el-sakka, m.i.t. (2004) energy use and output growth in canada: a multivariate co-integration analysis. energy economics, 26, 225-238. herrerias, m.j., joyeux, r., girardin, e. (2013), short-and long-run causality between energy consumption and economic growth: evidence across regions in china. applied energy, 112, 1483-1492. huang, b.n., hwang, m.j., yang, c.w. (2008), causal relationship between energy consumption and gdp growth revisited: a dynamic panel data approach. ecological economics, 67(1), 41-54. jebli, m.b., youssef, s.b. (2017), renewable energy consumption and agriculture: evidence for cointegration and granger causality for tunisian economy. international journal of sustainable development and world ecology, 24(2), 149-158. kalyoncu, h., gürsoy, f., göcen, h. (2013), causality relationship between gdp and energy consumption in georgia, azerbaijan and armenia. international journal of energy economics and policy, 3(1), 111-117. kraft, j., kraft, a. (1978), on the relationship between energy and gnp. journal of energy and development, 3, 401-403. long, x., naminse, e.y., du, j., zhuang, j. (2015), nonrenewable energy, renewable energy, carbon dioxide emissions and economic growth in china from 1952 to 2012. renewable and sustainable energy reviews, 52, 680-688. mirza, f.m., kanwal, a. (2017), energy consumption, carbon emissions and economic growth in pakistan: dynamic causality analysis. renewable and sustainable energy reviews, 72, 1233-1240. narayan, p.k., smyth, r. (2008), energy consumption and real gdp in g7 countries: new evidence from panel co-integration with structural breaks. energy economics, 30, 2331-2341. oh, w., lee, k. (2004), causal relationship between energy consumption and gdp revisited: the case of korea 1970-1999. energy economics, 26, 51-59. ozturk, i. (2010), a literature survey on energy-growth nexus. energy policy, 38(1), 340-349. ozturk, i., aslan, a., kalyoncu, h. (2010), energy consumption and economic growth relationship: evidence from panel data for low and middle income countries. energy policy, 38(8), 4422-4428. pedroni, p. (2004), panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the ppp hypothesis. econometric theory, 20(3), 597-625. pesaran, m.h. (2007), a simple panel unit root test in the presence of cross‐section dependence. journal of applied econometrics, 22(2), 265-312. pirlogea, c., cicea, c. (2012), econometric perspective of the energy consumption and economic growth relation in european union. renewable and sustainable energy reviews, 16(8), 5718-5726. riti, j.s., song, d., shu, y., kamah, m. (2017), decoupling co2 emission and economic growth in china: is there consistency in estimation results in analyzing environmental kuznets curve? journal of cleaner production, 166, 1448-1461. shabestari, n.b. (2018), energy consumption, co2 emissions and economic growth: sweden’s case. available from: http://www. diva-portal.org/smash/get/diva2:1214695/fulltext01.pdf. shahbaz, m., sarwar, s., chen, w., malik, m.n. (2017), dynamics of electricity consumption, oil price and economic growth: global perspective. energy policy, 108, 256-270. syzdykova, a., tanrıoven, c., nahipbekova, s., kuralbayev, a. (2019a), the effects of changes in oil prices on the russian economy. revista espacios, 40(14), 1-10. syzdykova, a. (2018a), the relationship between the oil price shocks and the stock markets: the example of commonwealth of independent states countries. international journal of energy economics and policy, 8(6), 161-166. syzdykova, a., abubakirova, a., kelesbayev, d. (2019b), the effects of external debts on economic growth in transition economies. economic series of the bulletin of the enu named, 2, 67-77. syzdykova, a. (2018b), orta asya ülkelerinde enerji tüketimi ve ekonomik büyüme ilişkisi: panel veri analizi. afyon kocatepe üniversitesi i̇ktisadi ve i̇dari bilimler fakültesi dergisi, 20(1), 87-99. syzdykova, a., abubakirova, a., kelesbayev, d. (2019), the effects of external debts on economic growth in transition economies. economic series of the bulletin of the enu named. vol. 2. eurasia: l. n. gumilyov; p67-77. pham, t.n., phan, t.t., nguyen, p.t., ha, q.t. (2013), computational collective intelligence. technologies and applications. lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics) year. p603-611. pesaran, m.h., ullah, a., yamagata, t. (2008), a bias‐adjusted lm test of error cross‐section independence. the econometrics journal, 11(1), 105-127. waheed, r., sarwar, s., wei, c. (2019), the survey of economic growth, energy consumption and carbon emission. energy reports, 5, 11031115. wang, s., li, q., fang, c., zhou, c. (2016), the relationship between economic growth, energy consumption, and co2 emissions: empirical evidence from china. science of the total environment, 542, 360-371. westerlund, j., edgerton, d.l. (2007), a panel bootstrap cointegration test. economics letters, 97(3), 185-190. wolde-rufael, y. (2014), electricity consumption and economic growth in transition countries: a revisit using bootstrap panel granger causality analysis. energy economics, 44, 325-330. world bank. (2019), world bank indicator. available from: http://www. worldbank.org. [last accessed on 2018 jan 05]. yildirim, e., sukruoglu, d., aslan, a. (2014), energy consumption and economic growth in the next 11 countries: the bootstrapped autoregressive metric causality approach. energy economics, 44, 14-21. zhang, y.j. (2011), interpreting the dynamic nexus between energy consumption and economic growth: empirical evidence from russia. energy policy, 39(5), 2265-2272. . international journal of energy economics and policy | vol 10 • issue 2 • 2020 1 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(2), 1-6. negotiating energy diplomacy and its relationship with foreign policy and national security ana bovan1, tamara vučenović1, nenad perić2* 1metropolitan university, faculty of management, belgrade, serbia, 2faculty for diplomacy and security, belgrade, serbia. *email: ana.bovan@metropolitan.ac.rs received: 19 september 2019 accepted: 01 december 2019 doi: https://doi.org/10.32479/ijeep.8754 abstract energy diplomacy is a complex field of international relations, closely linked to its principal, foreign policy and overall national security. we observe the relationship of issues that belong to the three concepts and how they are intertwined in the geopolitical reality. despite the ontological hierarchy of the three concepts, where national security is on the highest level of generality, and energy diplomacy on the lowest, it is a recurring theme for them to continuously meet and intersect in realpolitik in a dynamic relationship. the article specifically looks at the integration of energy diplomacy into foreign policy. we discuss two pathways that energy diplomacy has taken on its integration course into foreign policy, namely the path marked by national security topics and the path that is dominantly an economic one. the article also observes the nexus of national security, foreign policy, economic security and economic diplomacy, which is termed the energy security paradox. it exemplifies the inconsistencies in the general state of affairs in which resource riches of a country result in a stable exporter status and consequentially, stable exporting energy diplomacy. the recommendation for further research is suggested, directed at the new dynamics of the relation of energy transition and energy diplomacy. research could facilitate in understanding or envisaging how new low carbon energy sources coupled with energy efficiency will influence the new geopolitical map, affecting energy diplomacy in the geopolitical context where geography will have a lesser dominance on international relations. keywords: diplomacy, energy diplomacy, foreign policy, national security jel classifications: f5, o13, p32 1. introduction energy diplomacy is a complex field of international relations, closely linked to its principal, foreign policy, and overall national security. we observe this relationship, especially the integration of energy diplomacy, as a relatively new foreign politics field, into national foreign policies. foreign politics has been around for thousands of years of our civilization, while energy has only entered in the last 150 years. however, in that period foreign policy and energy have had an increasing number of overlapping and interconnected elements. foreign policy in its own part is closely linked and dependent on the concept of national security. national security is a principle of actions governing relations of one state with others based on geography, external threats and other national security challenges, of which energy is one. the three concepts, national security, foreign policy and energy security are ontologically structured, where national security is the most general concept, foreign policy is one level lower covering the international aspect of national security risks, and the lowest on the scale is energy diplomacy. foreign policy is linked to national security as it is the tool which implements overall national security. national security also has a direct link to energy diplomacy. national security denotes the capability of a nation to overcome its internal and external multi-dimensional threats by balancing all instruments of state policy through governance (paleri, 2008). it aims to protect this journal is licensed under a creative commons attribution 4.0 international license bovan, et al.: negotiating energy diplomacy and its relationship with foreign policy and national security international journal of energy economics and policy | vol 10 • issue 2 • 20202 national independence, security and territorial, political and economic integrity, dealing with a large number of national security risks. multi-dimensional threats that national security covers include a wide range of risks, thus incorporating the concepts of economic security, energy security, physical security, as well as the aspects of environment, food, migrations, cyber security and others. energy is one of the fundamental items on the national security agenda. national security that deals with such external issues and risks is applied and implemented by government departments for external relations. implementation of the national security strategy involving external factors and international issues is carried out through foreign policy instruments, namely international relations and diplomacy. energy diplomacy specifically focuses on external energy relations. despite the ontological hierarchy of the three concepts, it is a recurring theme for them to continuously intersect in practical diplomatic life and the geopolitical reality. 2. the rise of energy risks on the national security agenda energy diplomacy is a growing diplomatic field, aimed at providing energy security. energy has entered the sphere of diplomacy and foreign policy as a result of its rising impact on national security and economy. energy, the ability to do any work, powers the economy. its uninterrupted flow, inward for importing countries, and outward for exporting, must be secured at all times. until the last few decades of the 20th century the question of energy was not treated as a matter of such urgency nor geopolitics. the availability, affordability and supply were not a security issue. the industrial production and consumption capacities were smaller, and movement of energy was generally safe and dependable. throughout the industrial revolution the increasing need for energy grew at a remarkable pace, spiraling in the 20th century. only in the last 50 years, between (international energy agency, 2019) 1971 and 2017 world total primary energy supply grew by more than 250% from 5, 519 mtoe to 13, 972 mtoe (figure 1). energy use worldwide is yet to grow by one-third until 2040 (international energy agency, 2015). the changed situation generated a series of factors that required energy security and energy diplomacy to be elevated onto the national security agenda. national security departments worldwide closely monitor the severe escalation of energy use. the modern consumer and the contemporary economy have gradually grown to critically depend on energy. hence, economy and energy have become inseparable concepts. energy has become a synonym for the economy and power, and not having enough of it became a concern of the utmost national security. access to energy resources has decided on war outcomes1, security of supply shaped national and international agendas, oil and gas producing countries organized together into coalitions, tapping into the newly discovered energy resources to back their political and geopolitical goals. oil and gas companies became some of the most influential organizations in the global business and power-influencing arena (perticone, 2019). oil price volatility caused by oil shocks, like portrayed in the figure 2 (verleger, 2019) spelled economic fortunes or disasters for many participants in the international arena affecting national and geopolitical strategies. the economic consequences were considerable, so energy had to be included on the list of security and foreign policy issues of states. 3. niche diplomacy energy diplomacy refers to diplomatic activities designed to enhance access to energy resources and markets (giuli, 2015). it is a system of influencing the policies, resolutions and conduct of foreign governments and other international factors by means of diplomatic dialogue, negotiation, lobbying, advocacy and other peaceful methods. the general relationship between foreign policy and energy diplomacy is conceptually one of principal and agent. foreign policy sets the goals and overall political strategy while energy diplomacy is a mechanism for achieving the goals. energy diplomacy is an instrument of foreign policy. the purpose of energy diplomacy is to safeguard economic and energy security. energy diplomacy channels economic and trade relations of a state with other states and organizations safeguarding energy security through availability, reliability and affordability. diplomatic efforts aimed at providing energy security grew in importance and complexity. it matured and spun off from general foreign policy and public diplomacy into a separate diplomatic niche field (henrikson, 2005), energy diplomacy, mostly after the 1970s oil crises. this diplomatic activity has several other popular names like “geopetroleum politics” (overland, 2015), or “petro – politics” (dorraj and currier, 2011), or pipeline diplomacy (aalto, 2008), but it mostly covers the same field. energy diplomacy has developed its own programs, goals, instruments, tactics and action plans, taking rightfully its space in the foreign policy domain. it is especially important for the biggest consumers, figure 3 showing the level of consumption in total and in relation to population and gdp. one such comprehensive energy policy and energy action plan is developed by the eu, it is the eu energy diplomacy action plan (eur-lex). 1 it has been argued that there have never been any wars in history over fossil fuels, and a hypothesis put forward that none would be happening in the future. although we strongly agree with the latter, the need to avoid the military conflicts over resources, the fact that no wars have been fought over fossil fuels historically is extremely disputable (fettweis, 2009).source: iea, 2019 figure 1: world total primary energy supply by fuel bovan, et al.: negotiating energy diplomacy and its relationship with foreign policy and national security international journal of energy economics and policy | vol 10 • issue 2 • 2020 3 energy diplomacy employs foreign policy methods to ensure a steady flow of energy and security of energy supplies. energy producing and energy consuming countries apply them differently. energy producing states mostly focus on using energy diplomacy to expand their exports and presence on the global markets. the example is the energy diplomacy of an exporting state, russia, who aims to secure access to buyers for oil and gas. it is similar with the energy diplomacy of opec, the organization of the petroleum exporting countries, whose focus is similarly export and keeping external demand. energy consuming and importing states apply energy diplomacy to secure energy supplies and steady inflow, like china’s oil diplomacy in africa or more recently, with iran (watkins, 2019). there are also hybrid strategies, which are retained by states that are both large consumers and producers; such are india (iae atlas of energy) and the us (figure 4). 4. integration of energy diplomacy into foreign policy energy risks have been elevated into once inaccessible and restricted realm of high politics, as foreign policy has been called through history. yet energy security means different things to different states (yergin, 2006). considering various modes of integration, it can be argued that both conceptually and historically energy was introduced into national foreign policy generally via two channels, the fields of security and economy. in some states energy found its way through the security policy field, and in others via the economic policy. the integration via the first channel, security policy, was instigated by the fact that supply and access to energy has become a crucial national security concern for numerous states. therefore energy issues entered the foreign policy considerations after energy security has ascended on their national security agenda. despite some scholars arguing that security concept per se should not be too far extended to include topics of such variance outside the its core geopolitical, defense and military realm (walt, 1991), in realpolitik terms such tendency has taken foothold. it is especially so in the countries which are not energy producers, so their level of dependence is higher and risks bigger (meierding, 2011). their energy security is particularly challenged as they depend on the safe and ample supply from energy sources in other countries. guaranteeing energy security is supported by appropriate energy diplomacy. energy security was not a center stage subject of interest of diplomats until the states become aware of the exponential growth of energy demand and dependence on import as well as uneven worldwide distribution of resources and raw materials. oil especially became a novel security concern, as it has historically been a trigger for wars (buchan, 2012). some examples are the brutal armed conflict, the chaco war, between bolivia and paraguay in 1932, which was in effect a conflict between the oil companies royal dutch shell who was behind paraguay and standard oil was behind bolivia; and another example is the japanese attack on pearl harbor in 1941. the beginning of the 20th century was the early era of energy diplomacy, which was largely marked by corporate players. such diplomacy was dominated by the corporations that produced and distributed fossil fuel, rather than sovereign governments, as in the case of royal dutch shell and standard oil. national security on a national level as a concept in its own right has not yet been formulated, but the energy issues were increasing in importance. carving up the source: oilprice.com, dr. p. verleger figure 2: effects and durations of nineteen global oil market disruptions source: iae 2019 figure 3: top five energy consumers: 2017 relative shares* source: iea figure 4: largest producers by fuel in 2017 bovan, et al.: negotiating energy diplomacy and its relationship with foreign policy and national security international journal of energy economics and policy | vol 10 • issue 2 • 20204 global oil reserves and markets was carried out persistently, alike during the 1908 negotiations between royal dutch shell legendary head mr. deterding and the us standard oil director mr. teagle; or on the occasion of signing the us “as-is” pool association agreement in 1928 with the same goal wars (yergin, 2012). the corporations were competing and racing over privileges, quotas and allocations (uludağ et al., 2013). the governments were not too far behind, supporting them and often facilitating the race, but the influential corporations dominantly shaped the industry and foreign policy. post world war ii era experienced fall of empires, rise of colonies, global shifts in geopolitical influence of uk, us, russia and others. it is the opec that has succeeded in the 1960s and 1970s to gain ground in relation to the international oil corporations (jaffe, 2009), nationalizing and regaining control over the national fossil fuel resources in several large producing countries. the oil shocks after wwii were the ones that greatly contributed to the growth of security concerns and diplomatic efforts in the energy sphere. the most important occurrences were the suez crisis of 1956-1957 (yergin, 2012) and the opec oil embargo of 1973-1974. whole economies were brought near to a standstill, escalating energy issues as top security concerns. soon came other disruptions, albeit smaller, caused by the iranian revolution of 1979, the iran-iraq war of 1980 followed by the first persian gulf war in 1990-1991. turbulences on the oil market that disturbed and endangered economies were also caused by the 2003 iraq invasion, oil price spike of 2007-2008, russian ukrainian gas dispute in 2009 (pirani et al., 2009), and others (hamilton, 2013) including smaller disruptions. oil passages are still a global security concern as 40% of all oil transits via four conduits of the straits of hormuz, malacca, rab-el-mandeb and the suez canal. international energy agency, iea, expects that these quantities will rise from 40% to 60% by 2030 (buchan, 2012). any longer interruption would cause another large-scale economic downfall. therefore energy diplomacy has entered the domain of foreign policy through the national security passageway. numerous grave national and international risks associated with energy security and energy diplomacy have paved this way and assured that energy is viewed and judged as a security concern, so it acquired all the features of a security issue, and is constantly monitored for level of risk, potential prevention or intervention in the diplomatic field. next to the security path, energy concerns have entered foreign policy considerations via another path, the economy. energy questions are a part of economic policy and consequentially, of economic diplomacy. economic diplomacy is a wider concept; it is the process of international economic decision-making. foreign policy draws specifically on economic diplomacy to further its economic interests, among others its energy interests. those interests originate from country geography, its economics, level of development and international power (soobramanien, 2011). economic diplomacy in its own right is a vast area of international policy considerations. it has increasingly become an encumbered concept dealing with an aggregate number of concerns. this led its bifurcation and development of several specialized segments, including energy diplomacy. this is especially so in countries where energy is predominantly an economic issue and an export and market concern. in this context the states have mostly brought energy diplomacy into foreign policy through the economic channel. a valid example is australia (downie, 2018), which has in 2018 decided to form a new policy body entitled energy diplomacy. australia, being by far the largest global exporter of coal, has only been mildly affected by the shifts on the market and geopolitics of energy, so its security risk concerning energy has not been very high. 5. energy diplomacy and the energy security paradox in the complex dynamics of security, foreign policy and energy diplomacy some regions and countries are experiencing the energy security paradox. it is an empirical reality that countries rich with energy sources have a lesser level of risk when energy is concerned. in some cases energy security is at stake, while in other it is the economic security that is experiencing higher risk levels in connection to the energy resources of the country. these risk levels influence their energy diplomacy. energy diplomacy is generally directed, in resource rich countries, at achieving economic stability, steady production, high prices and demand levels. the security paradox is in the fact that numerous states with an abundance of energy resources, namely fossil fuels like oil and gas, lack energy or economic security, sometimes referred to as a resource curse (colgan, 2014). africa is a growing energy producer figure 5. especially sub-saharan regions are rich with resources, yet they are losing out on the numerous benefits. energy security is on a low level as the explosion of the raw material findings on the continent is in stark disproportion of how much of it used locally (meierding, 2011). this exposes the states of the region to both energy and, consequentially, economic risks. a similar state of affairs concerning the energy security paradox has been developing in an oil rich venezuela (cunningham, 2019). due to a complex set of internal institutional imperfections venezuela has been grappling with its ability to obtain steady production and investment in developing its capacity. this has caused economic, thus diplomatic and geopolitical risks. iran in the mid 1970’s had the governing structures that have been able to reap the financial benefits of oil exports to the us. nevertheless, that state of affairs did not result in an improved national economy for all (cooper, 2011), in fact it created internal economic insecurity. their energy diplomacy, although strained for various institutional and financial resources (soobramanien, 2011), was continuously linked to geopolitical issues, while on the national level inequality and economic insecurity was increasing. nigeria is another example of oil riches not providing (borok et al., 2013) for full economic security on the national level. such energy security paradoxes point to the complexity of energy diplomacy, being a tool of foreign policy but also with a close link to national security. 6. energy transition, energy diplomacy and the new geopolitics energy diplomacy has been frequently affected by dramatic elements that had a strong impact. some of which included bovan, et al.: negotiating energy diplomacy and its relationship with foreign policy and national security international journal of energy economics and policy | vol 10 • issue 2 • 2020 5 geopolitical strife, oil shocks, complex bilateral relations of producing countries, safety and security supply being disturbed by interruptions of production due to either regular maintenance, natural disasters or political and social protests2 in the energy producing or the energy passage country, even refining capacities that are a major limitation on supply (yergin, 2006). although the integration of energy diplomacy into foreign policy for some states has been security and the others economy, the energy transition is reshaping those dynamics so that questions of security and economy will follow a new geopolitical reality. the dynamics of the relationship with foreign policy and national security is thus undergoing a fundamental change-energy transition. providing energy security has traditionally included several key notions: availability, reliability and affordability (pascual et al., 2010), but in the past two decades another crucial aspect is added – environmental sustainability and transition to low carbon energy.3 2 there were more than 70 revolutions in the period 1945-2004 (colgan, 2014). 3 research and policy proposal has been suggested which expands on several dimensions of energy security. it classifies them into twenty components. they are: security of supply and production, dependency, and diversification for availability; price stability, access and equity, decentralization, and low prices for affordability; innovation and research, safety and reliability, resilience, energy efficiency, and investment for technology development; land use, water, climate change, and air pollution for sustainability; and governance, trade, competition, and knowledge for sound regulation. this is followed by a further synthesized list of 320 simple indicators and 52 complex indicators that policymakers can use to monitor performance on energy security (sovacool and mukherjee, 2011). some of the largest states and economies are the biggest co2 emitters contributing climate change. the dominant emitters are china with 9,1000 mtco2, usa 4,8000 mtco2, followed by india, russia, japan, germany, korea, iran and canada (figure 6). this has initiated a huge shift in how energy is perceived, its toll on the environment and it prompted policies to curb climate change. it was spearheaded by policy makers (bovan and peric, 2015) in the eu. with the proliferation of more renewable energy in the energy mix, like solar, tidal, energy efficiency, wind or water, the geography of resources will not be limited to only a few resource rich countries, but much more evenly spread throughout the world. the way national energy risks are perceived is gradually changing, as energy availability will be significantly improved and more prevalent all over the planet. the energy transition into low carbon energy is already shaping the dynamic relationship of geopolitics, national security strategies, foreign policies and energy diplomacy, and will continue to do so. 7. conclusions energy diplomacy is a growing diplomatic field, aimed at providing energy security. the relationship between energy diplomacy, foreign policy and national security is complex and dynamic. energy has entered the sphere of diplomacy and foreign policy as a result of its rising impact on national security and economy. the ontological hierarchy of the three concepts puts them on different levels, national security being the most general, and energy diplomacy the least, while they intersect throughout their empirical implementation in daily geopolitics and international relations in the energy field. the particular topic of observation is the path of integration of energy diplomacy into foreign policy. it is shown that energy diplomacy has taken two broad entryways on its integration course into foreign policy. both conceptually and historically energy was introduced into national foreign policy generally via two channels, the fields of security and economy. in some states energy found its way through the security policy field, and in others via the economic policy. there is a specific nexus of national security, foreign policy, economic security and economic diplomacy that create the energy security paradox. it exemplifies the inconsistencies in the general state of affairs in which resource riches of a country result in a stable exporter status and consequentially, stable exporting energy diplomacy. the most impactful change in energy diplomacy has come with energy transition to low carbon. more renewable energy will transform the geography of resources, so the dynamic relationship of geopolitics, national security strategies, foreign policies and energy diplomacy, will change once more, reconfiguring the energy risks in new ways and applying different energy diplomacy strategies. the recommendation for further research is directed at the relation of energy transition and energy diplomacy. research could facilitate in understanding or envisaging how new low carbon energy sources coupled with energy efficiency will influence the new geopolitical map, affecting energy diplomacy in the source: iea, 2019 figure 5: energy production in africa between 1971 and 2017 figure 6: co2 emissions from fuel combustion (mtco2) source: iea, 2019 bovan, et al.: negotiating energy diplomacy and its relationship with foreign policy and national security international journal of energy economics and policy | vol 10 • issue 2 • 20206 geopolitical context where geography will have a lesser dominance on international relations. references aalto, p. (2008), the eu-russian energy dialogue: europe’s future energy security. hampshire: ashgate. borok, m.i., agandu, a.j., morgan, m.m. (2103), energy security in nigeria: challenges and way forward. international journal of engineering science invention, 2(11), 1-6. bovan, a., peric, n. (2015), energy and climate change policies: an expanding arena for civil society lobbying, in: proceedings of regional conference. london: ieep, industrial energy and environmental protection in south eastern countries. buchan, d. (2012), the rough guide to the energy crisis. london: rough guides limited. colgan, j.d. (2014), oil, domestic politics, and international conflict. in: steven, d., o’brien, e., jones, b.d., editors. the new politics of strategic resources: energy and food security challenges in the 21st century. ch. 11. washington: brookings institution press. cooper, a.s. (2011), the oil kings: how the u.s., iran, and saudi arabia changed the balance of power in the middle east. new york: simon and schuster. cunningham, n. (2019), venezuela’s oil production set for another drop. available from: https://www.oilprice.com/energy/crudeoil/venezuelas-oil-production-set-for-another-drop.html. [last accessed on 2019 aug 07]. dorraj, m., currier, c.l., editors. (2011), china’s quest for energy security in the middle east: strategic implications. in: china’s energy relations with the developing world. new york: the continuum international publishing group. downie, c. (2018), australian energy diplomacy. australian journal of international affairs, 73(2), 1-7. eur-lex. (2015), communication from the commission to the european parliament, the council, the european economic and social committee, the committee of the regions and the european investment bank, a framework strategy for a resilient energy union with a forward-looking climate change policy. available from: https://www.eur-lex.europa.eu/legal-content/en/txt/?qi d=1431711858167&uri=celex:52015dc0080. [last accessed 2019 aug 12]. fettweis, c.j. (2009), no blood for oil: why resource wars are obsolete. in: luft, g., korin, a., editors. energy security challenges for the 21st century. santa barbara: abc-clio. giuli, m. (2015), getting energy diplomacy right: a challenge starting at home, commentary, european policy centre. available from: https://www.epc.eu/pub_details.php?cat_id=4&pub_id=6052. [last accessed on 2019 aug 12]. hamilton, j.d. (2013), historical oil shocks. in: parker, r.e., whaples, r., editors. routledge handbook of major events in economic history. new york: routledge taylor and francis group. henrikson, a.k. (2005), niche diplomacy in the world public arena: the global ‘corners’ of canada and norway. in: melissen, j., editor. the new public diplomacy soft power in international relations. new york: macmillan. iae atlas of energy. (2017), india. available from: http://www. energyatlas.iea.org/#!/profile/world/ind. [last accessed on 2019 aug 12]. international energy agency statistics. (2019), world energy balance: overview. available from: https://webstore.iea.org/download/ direct/2710?filename=world_energy_balances_2019_overview.pdf [last accessed on 2019 aug 11]. international energy agency. (2015), world energy outlook. available from: https://www.iea.org/newsroom/news/2015/november/worldenergy-outlook-2015.html. [last accessed on 2019 aug 15]. international energy agency. (2019), world energy balance: overview. available from: https://www.iea.org/statistics/balances. [last accessed on 2019 aug 15]. jaffe, a.m. (2009), opec: an anatomy of a cartel. in: luft, g., korin, a., editors. energy security challenges for the 21st century. santa barbara: abc-clio. meierding, e. (2011), energy security and sub-saharan africa. international development policy. doi: 10.4000/poldev.744. overland, i. (2015), future petroleum geopolitics: consequences of climate policy and unconventional oil and gas. in: yan, j., editor. handbook of clean energy systems, part 7. chichester uk: j. wiley & sons. paleri, p. (2008), national security: imperatives and challenges. new delhi: tata mcgraw-hill education. pascual, c., elkind, j. (2010), energy security: economics, politics, strategies and implications. washington: brookings institution press. perticone, j. (2019), business insider, lobbying groups that spent most money in washington. available from: https://www.businessinsider. com/lobbying-groups-spent-most-money-washington-dc-20182019-3#southern-company-1. pirani, s., stern, j., yafimava, k. (2009), the russo-ukrainian gas dispute of january: a comprehensive assessment. london: oxford institute for energy studies. soobramanien, t. (2011), economic diplomacy for small and low income countries. in: bayne, n., woolcock, s., editors. the new economic diplomacy: decision-making and negotiation in international economic relations. belgium: ashgate publishing, ltd. sovacool, b.k., mukherjee, i. (2011), conceptualizing and measuring energy security: a synthesized approach. energy, 36(8), 5343-5355. uludağ, m.b., karagül, s., baba, g. (2013), turkey’s role in energy diplomacy from competition to cooperation: theoretical and factual projections. international journal of energy economics and policy, 3, 102-114. verleger, p. (2019), 19 historical oil disruptions, and how no. 20 will shock markets. available from: https://www.oilprice.com/energy/ oil-prices/19-historical-oil-disruptions-and-how-no20-willshock-markets.html. walt, s.m. (1991), the renaissance of security studies. international studies quarterly, 35(2), 211-239. watkins, s. (2019), will china, russia defy u.s. sanctions to fund iranian oil projects? https://www.oilprice.com/energy/energygeneral/will-china-russia-defy-us-sanctions-to-fund-iranianoil-projects.html. [last accessed on 2019 aug 24]. yergin, d. (2006), ensuring energy security. foreign affairs, 85(2), 69-75. yergin, d. (2012), the prize: the epic quest for oil, money and power. new york: simon & shuster. international journal of energy economics and policy vol. 5, no. 1, 2015, pp.27-44 issn: 2146-4553 www.econjournals.com 27 turkey-azerbaijan energy relations: a political and economic analysis cagla gul yesevi faculty of economics and administrative sciences, istanbul kültür university, istanbul, turkey. email: c.yesevi@iku.edu.tr burcu yavuz tiftikcigil faculty of economics, administrative and social sciences, gedik university, istanbul, turkey. email: burcu.tiftikcigil@gedik.edu.tr abstract: it is now widely recognized that turkey-azerbaijan relations have always been strong and described with the phrase "one nation with two states”. this paper is concerned with economic and political nature of turkey-azerbaijan relations. initially, the evolution of turkishazerbaijani relations after the independence of azerbaijan has been examined. this paper gives an overview of the impacts of nagorno-karabagh issue and efforts to normalize the relations between turkey and armenia on relations between turkey and azerbaijan. energy has a special place in the relationship between the two countries. azerbaijan’s economy, energy sectors of azerbaijan and turkey has been assessed. moreover, this paper gives a comparative analysis on economic relationship between turkey and azerbaijan. this study finally discusses the main trends and contributions of energy projects on turkey-azerbaijan relations. keywords: turkey; azerbaijan; politics; economy; energy jel classifications: o57; q41; q43; q48 1. introduction turkey has distanced itself from the turkic people of soviet union, with whom it has ethnic and language affiliations, since its establishment. the primary aim was determined as the prevention of the spread of communism within the country and turanist movements were not supported. after the dissolution of the soviet union, the relations were started to develop with the countries moving towards liberal market economies. turkey was presented as a model, even a leader for the countries in the region with its liberal economic order and secular and democratic republican regime. the discourse of ‘turkish world from adriatic to chinese wall’ caused the birth of great expectations for turkish cooperation based on common ethnicity and common language. however, the lack of financial resources and credit opportunities of turkey for being the leader in the region limited its foreign policy targets. azerbaijan obtained a special place for turkey among the newly independent countries. ethnic and linguistic ties led the development of relations with the discourse of friendship and kinship. political and economic dimensions of azerbaijan-turkey relations have been analyzed in this article. first of all, the development of political relations between turkey and azerbaijan after the independence of azerbaijan is discussed. the influences of the conflict of nagorno-karabakh and normalization process of turkey’s relations with armenia on the turkey-azerbaijan relations are examined. within the context of the article, the economies and energy sectors of turkey and azerbaijan are investigated. economic relations between turkey and azerbaijan have comparatively analyzed. the contribution of the common energy projects and energy agreements to the relations between two countries are discussed. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.27-44 28 2. turkey-azerbaijan relations after the independence of azerbaijan azerbaijan declared its independence on 30 august 1991. azerbaijani assembly approved this decision on 18 october 1991. turkey became the first country recognizing its independence. turkey was represented as a model for newly independent caucasian and central asian republics. at the first turkish-speaking head of states summit in ankara on the dates of 30-31 october 1992, president turgut özal emphasized that the 21. century would be the age of turks. president turgut özal suggested the establishment of turkish common market and turkish development and investment bank during the summit. these suggestions were only welcomed by the azerbaijani head of state abulfeyz elchibey (oran, 2002). during the khojaly massacre of february 1992, president turgut özal, many political parties and turkish people put pressure for an intervention to armenia. however, prime minister süleyman demirel did not comply with them although stating military intervention was not ruled out. he tried to solve the problem within the involvement of the un, the osce and the nato. süleyman demirel rejected to provide helicopters that azerbaijan demanded to evacuate civilians from the region, in order not to confront with russia. russia supported suret hüseyinov and this situation caused the collapse of abulfeyz elchibey government on 4 june 1993 (oran, 2002). second turkish-speaking states head of states summit was gathered in istanbul on 18-19 october 1994. the conclusions of this summit were confirming the necessity to comply with the decisions taken by the un security council on nagorno-karabakh conflict between armenia and azerbaijan (oran, 2002). when haydar aliyev acquired the power, political decision-makers in turkey gave proelchibey speeches for a while. however, after a while, they declared that haydar aliyev came with the democratic elections. in september 1993, haydar aliyev suspended the agreements signed during elchibey period. he ended the duties of turkish military experts working in azerbaijan; he started visa regulations for turkish citizens. the relations were improved later; haydar aliyev declared that the azeri oil would be transported through turkey and turkish military soldiers would continue to train azeri officers. aliyev’s visit to ankara in january 1994 was historical in the sense that the relations between two countries were defined as “one nation, two countries” by haydar aliyev. one year later after this speech, a coup attempt against aliyev with the involvement of turkish citizens was prevented by süleyman demirel (oran, 2002). ilham aliyev became the azerbaijan president by replacing his father in october 2003. despite the good relations with turkey, he did not recognize turkish republic of northern cyprus (trnc). in july 2005, flights between azerbaijan and trnc were started but passages with trnc passports could not be realized despite given promises. these flights were then abolished by stating the lack of demand (oran, 2013). ilham aliyev applied the policy of balance in its relations with regional states. moreover, he aimed to establish better relations with azerbaijan’s neighbors. he has initiated economic and political relations with asian countries. he gave importance to international organizations such as the council of europe. the most important aim of aliyev has been to improve azerbaijan’s oil and natural gas projects and pipeline politics. azerbaijan wants to become significant actor in regional energy politics. ensuring energy security in the east-west corridor has been other goal of azerbaijan’s energy strategy (aras, 2014:2) 3. collapse of the discursive unity: nagorno-karabakh conflict and the influence of normalization with armenia on the relations between two countries after the first world war, georgia, armenia and azerbaijan declared their independence. during this period, nagorno-karabakh was under the control of azerbaijan. georgia, armenia and azerbaijan entered under the soviet rule in 1920. in 1923, nagorno-karabakh autonomous region was established and it was left to azerbaijani authority. nagorno-karabakh autonomous region was structured as independent in domestic affairs particularly for the issues related with culture and education, and dependent to azerbaijan in other issues (başer, 2008). in this period, 70% of the population nagorno-karabakh was armenian. on 20 february 1988, nagorno-karabakh autonomous region demanded secession from azerbaijan and its annexation to armenia. military conflict started with azerbaijan and armenia. this decision was rejected by azerbaijan soviet and ussr supreme soviet. ussr supreme soviet took over the control of nagorno-karabakh in january 1989. after the independence, azerbaijan abolished the autonomous status of nagorno-karabakh and annexed it to turkey-azerbaijan energy relations: a political and economic analysis 29 azerbaijan. armenians declared independence after plebiscite. they applied to be the member of the commonwealth of independent states (cis). russian troops left karabakh in 1992; karabakh was cleansed from non-armenian population. armenians took control of the lachin corridor between 1993 and 1994 and provided direct link to armenia. after the massacre in khojaly and the invasion of susha and lachin, armenians obtained superior position in the conflict. 20% of the azerbaijani land was invaded and 1 million azeri became refugees (aydın, 2002). turkey declared to president muttalibov during his visit to ankara on 24 january 1992 that it could act as a mediator in the azeriarmenian conflict with the approval of both sides (şiriyev, 2011). nagorno-karabakh conflict started before the collapse of the soviet union. bishkek ceasefire protocol that was signed in may 1994 achieved the freezing of conflict. the minsk group formed within osce; it was aimed to solve disagreements between two countries. however, the minsk group could not succeed to provide the signature of a peace agreement that could provide consensus between two countries. after the russian-georgian war of 2008, russia started to play more active role in the negotiations for the solution of this conflict. in this period, moscow protocol was signed between the parties (şiriyev, 2011). azerbaijan devoted 2.5% of its gdp to defense expenditure in 2012, defense budget of azerbaijan was 1.7 billion dollars. armenia devoted 3.73% of its gdp to defense expenditure; the defense budget was 349 million dollars in 2012. azerbaijan has 67 thousands active soldiers and 300 thousand reserved soldiers; armenia has 49 thousand active soldiers and 210 thousand reserved soldiers (the military balance, 2013). in 2010, azerbaijan declared military doctrine and declared its official war discourse. in the azerbaijan military doctrine, it was declared that solving international conflicts with the means other than international law was not supported however; military force would be employed within the context of the rights recognized by international law. accordingly, azerbaijan approved the use of military force in order to save nagorno-karabakh and 7 regions from occupation (şiriyev, 2011). national security concept of azerbaijan was published on 23 may 2007; its military doctrine was published on 8 june 2010. one of the major threats according to national security concept had been determined as the actions against the energy infrastructure of azerbaijan (şiriyev, 2010). in the azerbaijan military doctrine, it was stated that foreign military bases and armed troops could be deployed in the country soils if the security conditions changed. in addition to this, in the doctrine, it was emphasized that the military intervention could be realized, if the intervention became inevitable for the solution of nagorno-karabakh conflict under the geopolitical circumstances. azerbaijan states that it has had mutual interest relationship with nato (şiriyev, 2010). azerbaijan has had some basic principles that do not change during different governments. these basic principles are the protection of the independence and unity of the country, solution of the karabakh conflict, becoming member of international organizations and finalizing regulations for the market economy. karabakh issue became the main agenda of all governments. while during muttalibov period, russia was considered as a close ally; during elchibey government close relations were established with turkey. haydar aliyev gave importance to balance politics (yılmaz, 2010). turkey has been pursuing similar position with azerbaijan in its most sensitive issue, karabakh. turkey officially has been in favor of solving the issue within the limits of international law. in this context, it follows the works of minsk group that was formed within the osce. the most sensitive issue between two countries is related with the turkish-armenian border. turkey has closed the armenian border since 1993 because of armenian invasion of azerbaijani lands (tr ministry of foreign affairs, 2014a). khojaly massacre increased the sensitivity of turkey about nagornokarabakh conflict. khojaly city of karabakh was invaded by armenians with the help of the 366. troop of russian army on 26 february 1992. turkey supported the peace-making process under the osce. however, none of the sides accepted this suggestion. nakhichevan is an autonomous republic annexed to azerbaijan. there are two international agreements related with nakhichevan. according to the friendship agreement signed on 16 march 1921 in moscow, turkey has the protectorate power over nakhichevan which forces turkey to never leave nakhichevan to third countries. under this agreement, it was stated that nakhichevan would be an autonomous land under the protection of azerbaijan. it was also confirmed that nakhichevan would be an autonomous land under the protection of azerbaijan with the signature of kars agreement on 13 october 1921. moscow agreement indicates turkey has the protectorate right in the international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.27-44 30 case of the annexation of nakhichevan to armenia (aydın, 2002). the armed conflict spread to nakhichevan on may 1992. this situation strained the relations between turkey and russia since russia had close alliance with armenia. although turkey declared it would intervene if armenia would not leave nakhichevan, prime minister demirel stated they would not send troops to nakhichevan during his trip to russia. this situation is the indicator that discourses and realities did not correspond (i̇yikan, 2011). it became apparent that emotional kinship ties were irrelevant in implication and the power of turkey was limited. it is worth noting that turkey considered the caucasus region having enormous energy resources and being in strategic location has been important for regional influence and opportunities in 2000s. the turkish international cooperation and development (tika) has been playing significant role in improving economic and political ties with caucasian republics (aras, 2014:3). when ilham aliyev realized the west was not providing the necessary support for the solution of karabakh conflict, he established closer relations with russia especially after the georgian intervention of august 2008. in the mid-2009, efforts were made to normalize relations between turkey and armenia. russia supported this process. the military cooperation between russia and armenia intensified, and armenia extended the period of the use of gumru base by russia until 2044 (şiriyev, 2011). in this period, the insecurity of azerbaijan had doubled. the friend and kin countries discourse had left its place to emotional and political crashes. while the relations of azerbaijan with turkey cooled down, its relations with russia, china, japan, south korea and israel had developed (yılmaz, 2010). during the normalization process between turkey and armenia, disadvantageous regulation was made against turkey in the natural gas price that turkey had been purchasing from azerbaijan. until the normalization of relations, azerbaijan was selling a thousand cubic meters of natural gas for 120 dollars to turkey. president ilham aliyev emphasized that the natural gas price that turkey had been purchasing from şahdeniz project had to be adjusted in accordance with the market conditions and agreement obligations. as a result, parties agreed that turkey had to pay 300 dollars for the natural gas it had been purchasing from azerbaijan (asker, 2010). currently, 335 dollars are being paid for azerbaijani natural gas (yeniçağ, 2014). during the same period, pressures against turkish companies in azerbaijan and boycott against turkish goods were seen. the most important and unforgettable incident during that period was the taking down of the turkish flags in the turkish martyrdoms (yılmaz, 2010). this emotional, political, economic reactions and punishments demonstrate that the trust relations can deteriorate. the rapprochement of turkey to armenia proved turkey and azerbaijan can turn into enemies from friends and allies. turkey had been thought to be careful about the sensitivities of azerbaijan in order to continue the friendship. what was understood at the end of this process was that the relations did not reach to the level of strategic partnership from the level of one nation discourse. it is a necessity to strengthen friendship and kinship with economic interests and elevate them to the strategic level. emotional discourses bring affection, friendship and rapprochement between people, however the opposite situations lead the deterioration of relations economically and politically and cause enmity among people. it would be appropriate to clear relations from the emotionality of “one nation, two countries” approach (seta, 2009). defining the relations between turkey and azerbaijan as strategic partnership would elevate the relations a few levels. in this context, agreements were signed between azerbaijan and turkey in 2010 in order to confirm the positive course of relations. during president abdullah gül’s visit to azerbaijan on 16-17 august 2010, “strategic partnership and mutual aid agreement” signed between two countries. during the 10th turkish speaking countries head of states summit in istanbul on 1516 september 2010, “joint declaration for establishing high level strategic cooperation council” was signed between two countries. it is necessary to take and implement strategic decisions in the context of these agreements. 4. the economy of azerbaijan the economic period since the independence of azerbaijan to the president day is divided into two: the first period between 1991 and 1995 can be described as “economic chaos”. in this period, azerbaijan experienced several political, military and economic problems. the second period with a macroeconomic stability and dynamic economic growth has been continuing since 1996 (azerbaijan energy charter secretariat, 2013). turkey-azerbaijan energy relations: a political and economic analysis 31 the large and unexplored oil and natural gas reserves that the country has, makes it attractive for the investors from europe and the us. western countries make energy investments to azerbaijan for decreasing their dependency to middle eastern oil and russian transport networks. btc (baku-tiflisceyhan oil pipeline) that was established in 2006 and 11 billion dollar’s worth nabucco project are supported by western countries (deik, 2012). there is a serious prominence of the state in the azerbaijan economy that the necessary settlements have been rapidly continuing for transition to the free market economy. oil-natural gas sector plays an important role in the economy of azerbaijan. other than natural resources, agriculturally fertile lands of azerbaijan and large industry complexes remained from ussr period lead its economy. after the dissolution of the ussr, the economy of azerbaijan experienced a large recession. the war with armenia is significant in this recession. this recession was around 60% between 1991 and 1995 during the declaration of independence. since the second half of the 1990s, azerbaijani economy has been growing because of the oil and natural gas sectors. azerbaijan economy performed 21% growth between 2005 and 2009. however, as a result of the negative influence of global crisis to stock markets, oil and natural gas prices decreased in recent years. this situation diminished the gdp growth speed of azerbaijan (deik, 2012: 12-13). in 2013, gdp increased 5.8% as 57.7 billion manat in azerbaijan. the sectorial distribution of gnp in 2013 was 5.3% agriculture, 46.30% industry, and 48.4% service sector. outside of the oil sector gnp increase was 10%, in oil sector it was 1% (table 1) (the state statistical committee of the republic of azerbaijan, 2013). the energy sector has the greatest share in the foreign trade of azerbaijan. in the export of azerbaijan, oil and oil products, in the import machinery and equipment needed for oil industry are major items (somuncuoğlu, 2012). according to data of azerbaijan state statistics committee, azerbaijan conducted foreign trade activities with 155 countries in 2012. azerbaijan realized a total of 33.560.842.370 us dollars foreign trade volume including 9.652 870.180 us dollars import and 23. 907. 972.190 us dollars export (table 1) (azerbaijan state statistics committee, 2012 and tr ministry of economics, 2014). table 1. basic economic indicators of azerbaijan 2006 2007 2008 2009 2010 2011 2012 2013 gnp (billion $) 20,982 33,049 48,851 43,019 51,797 63,782 66, 605 73,560 growth (%) 34,5 25,0 10,8 9,3 5,0 11,9 5,0 6,0 inflation (annual average, %) 8,3 16,7 20,8 1,5 5,7 5,6 4,8 2,4 unemployment (%) 1,0 0,9 0,9 1,0 1,0 1,0 2,0 4,97 gross public debt (% of gdp) 10,24 8,60 7,79 12,14 11,40 10,23 11,24 10,82 export (billion $) 13,015 21,269 30,586 21,097 26,476 33,8 23.908 23.975,4 import (billion $) 5,269 6,045 7,575 6,514 6,746 12,4 9.653 10.712,5 gdp per capita ($) 2473 3851 3575 4950 5843 7190 7394 7812 source: dei̇k (2012), the state statistical committee of the republic azerbaijan, (2013)., imf, world economic outlook data, (10.10.2014)., world bank statistics, (10.10.2014). in 2012, 84.63% of the azerbaijani exports consisted of crude oil, 5.53% oil products, 2.71% natural gas, 0.10% electricity energy, and the rest were chemical industry products, steel and iron products, aluminum and its products, cotton, fruits and vegetables, vegetable and animal oil, alcoholic and non-alcoholic drinks (azerbaijan state statistics committee). its import consisted of 27.24% machines, mechanical devices, electrical devices and their components; 14.65 % transport vehicles and spare parts, 13.58% steel and iron products; 11.02% food products; 2.84% wood and wood products; 2.5% pharmacy products; 1.04% furniture and components; and 27.13% other (azerbaijan state statistics committee and tr ministry of economics, 2013). the economic policy of azerbaijan is the development of non-oil sectors and increasing the share of the non-oil sectors in gnp in the future since the vulnerability of energy sector to the global crisis is high (deik, 2012 and tr ministry of economics, 2013). international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.27-44 32 5. energy sector in azerbaijan azerbaijan is one of the oldest oil producers of the world. the natural gas and oil export of azerbaijan is the most important factor in its economic growth. according to imf data, the share of the oil and natural gas in total export is larger than 90%. azerbaijan also constitutes the most important export gate of the caspian base opening to the west. the share of the natural gas in primary energy consumption of azerbaijan is 66%, oil is 31%, and hydro-energy is 3%. the high dependency of economic growth to the energy makes azerbaijani economy vulnerable to the unexpected circumstances. unexpected influences that occurred in energy sector during 2011 caused the decrease of total production until mid-2013. according to oil and gas journal, proved crude oil reserve of azerbaijan was expected to be 7 billion barrels in january 2013. in 2012, azerbaijan made 930.000 barrels (bbl/d) oil production per day, and consumed 85,000 barrels of this production (figure 1-2) (u.s. eia, 2013a). azerbaijan state oil company (socar) is responsible from oil and natural gas production in azerbaijan, management of country’s refineries, establishment of natural pipeline system, management of oil and natural gas energy export and import. in azerbaijan, ministry of industry and energy is responsible from the agreements that would be made with foreign countries about transport and production of energy. socar also joins to international consortiums for the development of oil and natural gas projects. the share of socar is around 20% in the total oil production of azerbaijan. 80% of the total production is made by azerbaijan international operating company (aioc) managed by bp (iea, 2012). aioc is a consortium by 10 oil companies. bp has the major shareholder in this consortium. other companies are chevron (usa), socar (azerbaijan), inpex (japan), statoil (norway), exxon mobil (usa), tpao (turkey), itochu (japan), devon energy (usa) and amerada hess (usa). aioc made significant contribution to the construction of south caucasia pipeline and baku-tiflisceyhan pipeline. aioc currently makes plans for the construction of trans-caspian oil pipeline between kazakhstan and azerbaijan. oil drill from azeri-chirag-guneshli field and natural gas drill from shah deniz could be possible by the direct investments of this consortium (bp, 2014b and iea, 2012). figure 1. primary energy consumption distribution of azerbaijan, 2011 source: eia, country analysis briefs: azerbaijan, 2012. 5.1. azerbaijan’s oil pipelines baku-tiflis-ceyhan crude oil pipeline: the length of btc crude oil pipeline, which presents the caspian oil to the world market safely without increasing the current tanker traffic of istanbul and çanakkale straits, is 1768 km while 443 of it in azerbaijan, 249 km is in georgia, and 1076 km is in turkey. btc crude oil pipeline starts from sangachal terminal close to city of baku in azerbaijan, transits from georgia and ends in ceyhan terminal at the mediterranean coast of turkey. 80% of the oil export of azerbaijan is being held through btc (eia, 2013b and bp, 2014a). baku-novorossiysk oil pipeline: baku–novorossiysk pipeline is a l330 km long line between baku-sangachal terminal and russia-novorossiysk terminal. the part in azerbaijan is directed by socar and the part in russia is directed by transneft (socar, 2014a). 31% 66% 3% oil natural gas hidroenergy turkey-azerbaijan energy relations: a political and economic analysis 33 baku-supsa oil pipeline: western export line of baku-supsa line that has been active since 1998 is a 520 miles long pipeline between baku and supsa-georgia. the oil is drilled from caspian sea and transported to supsa port through line, loaded to tankers in supsa and exported to europe through istanbul strait (socar, 2014b). figure 2. primary energy production and consumption of azerbaijan (2009-2011kt oil worth) source: world bank energy statistics, http://data.worldbank.org/country/azerbaijan. 5.2. azerbaijan’s natural gas pipelines baku-tiflis-erzurum natural gas pipeline (south caucasus pipeline): bte natural gas pipeline that has been active since 2007 and 980 km long provides the transition of azerbaijan natural gas produced in shah deniz to georgia and turkey. bte has four distribution stations including one in azerbaijan and three in georgia (socar, 2014c). gazi-magomed-mozdok natural gas pipeline: gazi-magomed-mozdok natural gas pipeline, which is 150 miles long, transports azerbaijan natural gas to russia. socar and gazprom made an agreement for the relevant pipeline in 2009. baku-astara natural gas pipeline: due to the problems with armenia, azerbaijan signed an exchange agreement with iran for natural export. accordingly, iran has been transporting azeri natural gas to nakhchivan since the end of 2006. in order to realize this action, azerbaijan sends gas to iran through baku-astara line. iran transports this gas to nakhchivan through salmasnakhchivan line. iran receives 15% commission from transit income (eia, 2013b). after the discovery of shah deniz field, a few new pipeline projects came up. among them, nabucco project was supported by many countries but could not be realized. there are three new projects that shah deniz consortium is working on: enlargement of bakutifliserzurum (bte) (south caucasia natural gas pipeline), trans-anatolia pipeline (tanap) and trans adriatic pipeline (tap). in the scope of the enlargement of bte, it is planned to build a new pipeline parallel to the existing pipeline between azerbaijan-georgia and to merge this pipeline with tanap and tap. the transition of natural gas in shah deniz to europe through turkey is planned with tanap project. tap project will connect tanap to italy through greece and albania (iea, 2013b). 6. the economy of turkey the republic of turkey was established in 1923. turkey applied an import-substitute economic program before 1980. at the beginning of 1980’s, turkey undertook a program of economic liberalization that aimed at integrating the turkish economy into the world market economy to promote export-led growth. turkey has undergone a profound economic transformation since 2001. it has recorded remarkable gdp (gross domestic product) growth rate of almost % 6 in average during the period of 200264,598 65,514 59,958 11,937 11,585 12,56 0 10 20 30 40 50 60 70 2009 2010 2011 net export international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.27-44 34 2011. it should be noted that turkey ranks as the 17th largest economy in the world and 6th in europe. turkey’s gdp per capita has tripled; it was 3,492 usd in 2002 and 10,782 usd in 2013. according to purchasing power parity (ppp), gni (gross national income) per capita reached 19 thousand usd in 2013. turkish population is 76.9 million in 2014. gdp growth rate projections are 4% for 2014, 5 % for 2015 and 2016 (republic of turkey ministry of foreign affairs, 2014). turkish exports strategy for 2023 (table 2) (2023 is the centenary anniversary of the turkish republic) aims to reach 500 billion dollars of exports volume in 2023 with an average of 12% increase in exports annually. the main aims of turkey have been becoming one of the world’s 10 largest economies in 2023 and taking 1,5% share from the world’s trade. the other aim of this strategy has been reaching 80% exports/imports ratio in 2023. (republic of turkey ministry of economy, 2014). turkey's economy is increasingly driven by its industry and service sectors. the automotive, construction, and electronics industries are becoming the most important sectors within turkey's export. turkey, as a fast growing economy, will require more access to fossil fuel resources to meet its increasing demand for energy. the limits of turkey's domestic energy sources in light of its growing energy demand have resulted in dependency on energy imports, primarily on oil and gas. around 26 % of the total energy demand is being met by domestic resources. in that sense, the rest has been met by imports. turkey has intended to become an energy corridor and energy hub between the resources in the east and markets in the west. the eu has been supporting southern gas corridor project which will transport hydrocarbons aspecially natural gas from middle east and eurasia to europe via turkey. table 2. basic economic indicators of turkey 2006 2007 2008 2009 2010 2011 2012 2013 gdp in current prices (in billion u.s. dollars) 529.19 649.13 730.32 614.42 731.29 774.34 783.06 838.97 growth (%) 6.89 4.67 0.66 -4.83 9.16 8.5 2.97 3.53 inflation (annual average, %) 9,6 8,76 10,44 6,25 8,57 6,47 8,72 6,54 unemployment (%) 9 9,2 10 13,1 11,1 9,1 8,4 9,0 general government gross debt stock (% of gnp) 46.5 39.9 40.0 46.0 42.3 39.1 36.2 36.2 export (billion $) 85.5 107.3 132.0 102.1 113.9 134.9 152.5 151.8 import (billion $) 139.6 170.1 202.0 140.9 185.5 240.8 236.5 251.7 gdp per capita ($) 7597 9247 10444 8561 10003 10428 10459 10782 source: republic of turkey ministry undersecretariat of treasury, “turkish economy”, october 2014. 7. energy outlook of turkey energy is one of the most important factors of economic growth and development. the energy factor, which has a strategic importance, affects the positions, policies, and practices of states in international political economy. the wealthiest oil and natural gas reserves of the world are located in russia, central asia, and middle east. the energy policy of turkey has a dual importance since its economic growth above the world average and its geographical proximity to these oil and natural gas rich regions. as a developing country, turkey is expected to be one of the biggest ten economies of the world in 2023; and the goods and services exports, which is the locomotive of the turkish economy, are targeted to be 500 billion dollars. the demands of turkey for energy is rapidly increasing, which is one of the most important inputs since it follows a manufacturing strategy based on rd intense sectors, and the pioneer goods of their own sectors. however, the supply of energy cannot meet the demand for energy in turkey. turkey also targets to be a safe energy corridor between manufacturer and consumer countries in the east-west and north-south axis by using its strategically important location and to be the fourth biggest artery after russia, norway, and algeria in europe. in this context, turkey makes agreements with several countries and develops new policy strategies to decrease the energy supply deficiency in turkey and to eliminate the possible supply security problems. according to “vision 2023 technology foresight project-energy and natural resources panel report” of tubitak (2003), when the current economic growths and developments are analyzed, the primary energy supply of the world is expected to increase more than 40% by 2023 and 85% of this turkey-azerbaijan energy relations: a political and economic analysis 35 increase has to be covered by the fossil fuel. it is predicted that the share of the middle eastern countries of opec will increase to 75% by 2023, which provides 50% of the world oil export currently (tubitak, 2003). turkish economy has experienced the growth rates of 9.2% in 2010; 8.8% in 2011 and 2.2% in 2012. the energy consumption of turkey rapidly increases in parallel with its economic growth. the annual increase in the energy demand of turkey is 4.6% since 1990 as the second country after china for the increase of the natural gas and electricity energy demand. the annual increase in the energy demand is around 5.5-6%. in recent years, this increase has been exceeded 8% (figure 3) (turkstat, 2013 and yazar, 2010). the energy demand of turkey has increased most among the oecd countries within last two years. while the energy demand demonstrates a rapid increase in parallel to economic growth of turkey, energy consumption is relatively low. according to international energy agency, the energy demand of the turkey is expected to be doubled within the next ten years. energy ministry also predicts that the annual energy consumption of turkey will reach 222mtep by 2020. current energy policies target a 3% decrease in the external dependency within the next 10 years by 2020. (u.s. energy information administration u.s. eia, 2013; yazar, 2010). figure 3. primary energy production and consumption of turkey; 2000-2011 (quadrillion btu) source: world bank energy statistics, http://data.worldbank.org/country/azerbaijan and eia, country analysis briefs: azerbaijan, 2012. the inadequacy of the local resources for the increasing demands especially for oil and natural gas cause increases in the importation. currently, 26% of the energy demand of turkey is provided by local resources. turkey is dependent to external resources above the rates of 70%. turkey is one the most oil importer 20 countries and one of the most natural gas importer 10 countries. the lack of primary energy resources except lignite and external dependency in oil and natural gas create risks for its energy security (2013 program, 2012). in 2011, turkey imported 90% of its liquid fuel oil consumption. according to u.s. iea, energy import of turkey will be doubled in 10 years (iea, 2013c) (figures 4 and 5). according to 2011 data, turkey has been conducting its natural gas import 58% from russia and 19% from iran. iran follows russia with a share of 19%. according to january-september 2012 data, turkey provides 10% of its crude oil import from russia. the rate is 12% for 2011 (figure 6 and figure 7). 0 1 2 3 4 5 6 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 net import international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.27-44 36 figure 4. total import and export of refined oil of turkey; 2000-2010 (thousand barrels per day) source: world bank energy statistics, http://data.worldbank.org/country/azerbaijan and eia, country analysis briefs: azerbaijan, 2012. figure 5. total natural gas import of turkey; 2005-2011 (million sm3) source: turkey energy market regulatory authority, doğalgaz piyasası 2011 yılı sektör raporu 2012. figure 6. the shares of the countries in the natural gas import of turkey (2011;%) source: eia, turkey, 2013. 0 100 200 300 400 500 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 0 10.000 20.000 30.000 40.000 50.000 2005 2006 2007 2008 2009 2010 2011 58%19% 9% 3% 9% 2% russia iran azerbaijan nigeria algeria spot lng foreign trade deficit turkey-azerbaijan energy relations: a political and economic analysis 37 figure 7. share of the countries in the crude oil import of turkey (january-september 2012;%) source: eurostat data, http://epp.eurostat.ec.europa.eu/portal/page/portal/energy/data/database, 2013. 8. azerbaijan-turkey economic relations the relations between azerbaijan and turkey that has been conducted with the understanding of “one nation, two countries” are very strong. when gnps are compared for 2012, turkey rank at the 17th and azerbaijan locates at the 68th order in the world ranking (world bank statistics, 2013). trade and economic agreements between two countries are as follows: (dei̇k, 2012) trade, economic and technical cooperation agreement 1992 prevention of double taxing agreement – 1994 mutual promotion and protection of investments agreement – 1995 intergovernmental joint economic commission meetings protocols (kek) kek i. term– 1997 kek ii. term – 2001 kek iii. term – 2005 kek iv. term – 2006 kek v. term – 2008 kek vi. term – 2011 in the trade between azerbaijan and turkey, a trade surplus is relevant for turkey. foreign trade between two countries shows continuously increasing trend. azerbaijan is at the 15th order among the top exporting countries of turkey. like it is shown in figure 8, export of turkey to azerbaijan increases constantly. in 2013, turkey made 3 billion dollars’ worth export to azerbaijan. this value constitutes approximately 2% of the total exports of turkey. the foreign trade volume between two countries is 3.295 million dollars. this number is 0.8% of total foreign trade volume of turkey. azerbaijan located at the 27th order when the foreign trade volume of turkey is evaluated (retrieved from turkstat data). figure 8. turkey’s export to azerbaijan 2004-2013 (000 $) source: turkstat. foreign trade statistics database, 2013. 10% 7% 44% 15% 14% 10% russia kazakhistan iran iraq saudi arabia others 2 961 268 2 584 671 2 063 996 1 550 4791 400 446 1 667 469 1 047 668 695 287 528 076403 942 0 500000 1000000 1500000 2000000 2500000 3000000 3500000 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.27-44 38 import of turkey from azerbaijan also increases. however, azerbaijan is not among the top 20 countries that turkey imports most. azerbaijan is at the 59th order among the countries that turkey imports. in 2013, turkey made 334 million dollars worth import from azerbaijan. this value constitutes 0.13% of total import of turkey (retrieved from turkstat data) (figure 9). figure 9. turkey’s import from azerbaijan 2002-2013 (000 $) source: turkstat. foreign trade statistics database, 2013. in 2013, turkey’s exports to azerbaijan worth 2.961.268 dollars. turkey’s imports to azerbaijan worth 333.747.607 in 2013. among the export items at the first place there are vessels, machines, mechanic devices and tools, nuclear reactors, and their components (387.240.921 dollars) in import mineral fuels, mineral oils, and products from their distillation (115.018.767 dollars) (turkstat, foreign trade statistics database) (table 3). table 3. first five items in turkey’s export and import to azerbaijan in 2013 rank export usa dollars import usa dollars 1 vessels, machines, mechanic devices and tools, nuclear reactors, and their components 387.240.921 mineral fuels, mineral oils, and products from their distillation bitumen materials, mineral waxes 115.018.767 2 electrical machines and devices, voice recording-giving, television view-voice recording-giving devices, components and accessories 265.429.942 aluminum and aluminum goods 105.675.983 3 iron and steel goods 259.315.157 plastics and products 52.793.886 4 plastics and their products 258.478.732 rude posts, leathers (except furs) and other leather products 16.384.370 5 furniture, bedroom furniture, lightning devices, advert lightening, lightening tables etc., prefabricated buildings 221.216.056 cotton, cotton thread and cotton goods 14.951.009 source: turkstat. foreign trade statistics database, 2013. turkey’s share in the total foreign trade of azerbaijan is 6.3% when the foreign trade volume is analyzed. when the export of azerbaijan is analyzed on the country base, italy has the greatest share with 23.21%. india follows italy with 7.9%. the share of turkey in the total export of azerbaijan is 2.5%. turkey is at the 11th order in the top exporting countries of azerbaijan. it is seen that azerbaijan realizes 15.75% of its import with turkey, when the distribution of import of azerbaijan analyzed at the country based. russia follows turkey with 14.28% share. turkey is the top import country of azerbaijan. azerbaijan’s import from turkey realized as 1.520.045.810 us dollars in 2012 and demonstrated 16.69% increase as compared the same period of previous year (azerbaijan state statistics committee and tr ministry of economics 2014). azerbaijan and turkey are members of several international organizations. among them, there are economic cooperation organization (eco), black sea economic cooperation organization (bsec) and organization of the islamic conference (oic). eco was established in 1985 as the successor of regional cooperation for development, which was established in 1964. the aims of the 333 748 339 936 262 263252 525 140 599 362 835 185 500 296 581 208 325 135 537122 607 64 625 0 100000 200000 300000 400000 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 turkey-azerbaijan energy relations: a political and economic analysis 39 eco are to contribute the development of member states, removing trade barriers within the eco region and develop the regional trade, to promote the integration eco region to the global markets, and to strengthen the cultural and historical ties between member states. bsec was established in 1992. the aim of the bsec is to develop trade, economic, scientific, and technologic cooperation between member states and to bring peace, stability and welfare to the black sea region. oic was established in 1969 and aims political, economic, cultural, scientific, social solidarity and cooperation among member states (tr ministry of foreign affairs, 2014b, 2014c, 2014d). in the scope of the economic and trade relations between azerbaijan and turkey, the investments of turkish companies in azerbaijan are around 3.6 billion dollars. an important part of these investments has been made by turkish petroleum corporation (tpao) (somuncuoğlu, 2012). problems between the two countries mainly caused by the international responsibilities of them. since turkey signed the customs union treaty with the eu, it cannot implement an independent trade policy for the countries outside of the union. turkey undertakes the mutual and autonomous preferential trade regimes that the eu implements against third countries. a similar situation is also valid for azerbaijan. azerbaijan signed “azar ticared sadişi” with commonwealth of independent states in 1993. azerbaijan gave important customs exemptions to russia, ukraine, georgia, kazakhstan and moldova with this agreement. there are also problems between two countries in customs, transportation, banking, payments and trade law. one of the most important problems between turkey and azerbaijan in trade is the visa implementation. these problems prevent the development of between two countries, finding solutions to trade conflicts, and cause increases in costs and diminish the competition opportunities (tuğrul, 2012). 9. energy relations between turkey and azerbaijan there are more than 800 turkish companies in azerbaijan. total investments by these companies are over 3 billion dollars. when turkey’s energy investments in azerbaijan are considered, these investments exceed 6 billion dollars. baku-tiflis-ceyhan (btc) oil pipeline and baku-tiflis-erzurum (bte) natural gas pipeline are the functioning projects between two countries. baku-tiflis-kars (btk) railway project and trans-anatolia pipeline project (tanap) are planned to be made between two countries (tr ministry of foreign affairs, 2014a). azerbaijan agreed with several foreign companies about azeri, çırak and güneşli fields after it declared its independence on 18 october 1991. these companies are bp, mcdermott, penzoil, unocal, ramco, statoil. tpa joined this consortium with 2.5% share (gül, gül, 1995). within this period, nagorno-karabakh conflict worsened, after the fall of suşa, azerbaijan president muttalibov was removed from the office by azerbaijan popular front and abulfeyz elchibey took over the government (hunter, 1994). in 1992, popular front provided the establishment of azerbaijan state oil company. also, the popular front merged azeri, güneşli and çırak fields. when russia and iran were not included into the consortium, tpao was given a share. the regional and international actors began to work on pipeline routes. in the memorandum signed on 9 november 1992, 3 pipeline options were considered for transporting azeri oil. these are baku-novorossisk, baku-poti and bakuceyhan. baku-ceyhan was accepted as the most economic, efficient and least risky one for the tanker traffic in the protocol signed on 28 february 1993. during the period of abulfeyz elchibey, bakuceyhan oil pipeline preparatory agreement was signed on 9 march 1993 (gül and gül, 1995). turkey was presented as “energy bridge” in the “oil and natural gas opportunities” conference of 29-30 april 1993 (i̇brahimov, 2012). turkey-azerbaijan relations were affected from azerbaijan’s domestic problems and government changes in the term of haydar aliyev. azeri-armenian war over karabakh was intensified, and a russian supported coup occurred in azerbaijan. haydar aliyev was elected as president on 3 october 1993. haydar aliyev declared in economic cooperation organization meeting that all of the oil agreements made by azerbaijan would be revised. this declaration determined the pipeline choice of kazakhstan and kazakhstan preferred the russian route. international consortium that gathered in london prepared a report and announced that baku-ceyhan line is much more expensive (gül, gül, 1995). the debates on the construction process of baku-tiflis-ceyhan (btc) oil pipeline was the main political and economic issue of 1990s. turkey supported the construction process of baku-tiflisceyhan oil pipeline; turkey considered that this pipeline would make it easier for turkey to reach the international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.27-44 40 raw materials in the long run and azerbaijan would be a reliable partner for providing energy supply. in addition to this, the construction of the pipeline would provide employment opportunities. moreover, transit fees would contribute to turkish economy. one other reason for turkey to support the construction of baku-ceyhan pipeline was the pkk terror. turkey believed that it could obtain international support to end pkk terror with the construction of the line. turkey was supposed to help new resources to enter the world market and become an energy hub by enabling the transportation of azeri oil. another agenda of turkey was to provide the security of straits. also, turkey was declaring it was interested in protection of ecological balances of black sea, mediterranean and aegean seas (yesevi, 2013) turkey aimed to secure new energy supplies and to become transit country to deliver energy resources form the caspian region to europe. azerbaijan wanted to bypass russia; btc pipeline was considered as best option to decrease the dependency of azerbaijan; the united states supported the project as one of the multiple pipeline projects which would transport caspian energy resources to the west (murinson, 2008). the first oil agreement with azerbaijan oil company (socar) was signed on 10 september 1994. this agreement is the most important one related with the joint oil drilling from 3 caspian sea fields. within this context, azerbaijan international oil company (aioc) consisted of 7 countries and 11 companies were established to manage the azeri, çırak and güneşli fields. the duration of the agreement was determined as 30 years. total reserve of this field was determined as 540 million tones. the shares of the companies were as follows (eurasia files, 1997): bp (uk): %17.12 amoco (usa): %17.01 lukoil (russia): %10 socar (azerbaijan): %10 unocal (usa): %9.53 statoil (norway): %8.56 tpao (turkey): %6.75 penzoil (usa):%4.81 ramco (usa): %2.08 delta (s. arabia): %6.8. in april 1995, the share of turkey was increased from 5% to 6.75%. this development was a surprise for tpao. in the same period, a coup attempt, which included turkish officials, was failed by the warning by süleyman demirel to aliyev. early azeri oil was transported through bakunovorossisk and baku-supsa routes. btc oil pipeline that became active in 2006 could not be that determinant in the decision-making and taking process for the interests of turkey in the region. this line served as a sub-transport line after the period of the dissolution of the soviet union (yesevi, 2013). the primary reason for turkey to support the construction process of baku-tiflis-ceyhan oil pipeline was this pipeline would make it easier for turkey to reach the raw materials in the long run and it would acquire a reliable partner for providing energy supply (yesevi, 2013). ahmet davutoğlu, former minister of foreign affairs claims baku-tiflis-erzurum natural gas pipeline is very important. baku-tiflis-kars railway is even more important. accordingly, davutoğlu underlines baku-tifliskars railway would turn into silk railway that connects london to china with the construction of marmaray (yesevi, 2012). energy agreements that accelerated with the signature of baku-tiflis-ceyhan oil pipeline and baku-tiflis-erzurum natural gas pipeline projects between turkey and azerbaijan became more comprehensive when socar bought petki̇m in 2008. the memorandum of understanding of transanatolia pipeline (tanap), was signed on 26 december 2011 and intergovernmental agreement was on 26 june 2012. this pipeline would transport natural gas from azerbaijan to europe through turkey. the starting point is turkish border türkgöz and exit points to europe will be greek and bulgarian borders, and turkish exit points will be eskişehir and thrace region. the first phase of the anticipated 8 phases of tanap project is planned to be realized on 2018 with the first gas transport. it is aimed to reach from annual capacity of 16 billion cubic meters in 2020 to 23 billion cubic meters in 2023, and 31 billion cubic meters in 2026. tanap project is very important for the energy supply security of turkey and europe. project will also contribute significantly to transport azeri natural gas to new markets (tanap project official website, 2014a). one of the most important projects that brought acceleration to azerbaijan-turkey relations in energy sector is tanap. for the consortium made for tanap; socar, botaş and tpao exist as primary partners. in the scope of tanap, while turkey has 30% share with botaş and tpao in the consortium, socar has 70%. the project, which is aimed to complete the first stage in 2018, anticipates that gas will leave azerbaijan through georgia and arrives turkey where it will be turkey-azerbaijan energy relations: a political and economic analysis 41 transported and sold. within the scope of project, out of 16 billion cubic meters gas, 6 billion cubic meters of the gas will be sent to turkey; 10 billion cubic meters will be delivered to europe at the greek and/or bulgarian border. for turkey and europe, tanap will contribute to ensure energy supply security with reliable supply and reasonable prices (tanap project official website, 2014b). turkey has two aims about tanap project; the first one is to deliver azeri natural gas and the other one is to use it for the needs of the country. tanap will pass through the cities of ardahan, kars, erzurum, erzincan, bayburt, gümüşhane, giresun, sivas, yozgat, kırşehir, kırıkkale, ankara, eskişehir, bilecik, kütahya, bursa, balıkesir, çanakkale, tekirdağ, edirne and kırklareli. taner yıldız, minister of energy and national resources claims that new employment opportunities will be realized thanks to tanap (aa, 2014). tanap will help turkey’s goal to diversify energy routes and suppliers (yesevi, 2013). 10. conclusion the basis of azerbaijan-turkey relations is often described as friendship and kinship by official circles. in the first years of the independence of azerbaijan, the relations were very positive and in the first turkish speaking head of states summit in 30-31 october 1992 in ankara, only leader who supported president turgut özal’s turkish common market and turkish development and investment bank ideas was abulfeyz elchibey. turkey supported azerbaijan in nagornokarabakh conflict however during the khojaly massacre despite the pressures from public, president turgut özal and political parties for a military intervention to armenia; turkey tried to solve the conflict within the un, the osce and the nato. the declaration that the transportation of oil would be realized through turkey in the period of haydar aliyev strengthened the relations between two countries. it is important that haydar aliyev described the relations as “one nation, two countries”. since then, aliyev’s discursive unity description has been constituted the basis of the relations in the societal and political levels. however, the normalization of relations between turkey and armenia in 2009 caused problems in azerbaijan-turkey relations. in this period, price of the azeri natural gas was increased, turkish companies experienced reactions and flag crisis occurred. these incidents showed that the reliable relations between two countries could be disrupted. turkey learned to consider the sensitivities of azerbaijan in order to protecting the friendship. it is a necessity to strengthen the friendship and kinship of the discursive level with the economic benefits and raise it to the strategic level. in addition to be careful about not harming emotional relations, stronger economic relations should be developed. in the scope of the study, when economic relations between turkey and azerbaijan are analyzed, it is seen that the economic relations between two countries are below the expectations. free trade area between two countries was not established and a visa-free regime was not implemented. analyzing the distribution of the imports of azerbaijan, it is seen that 15.75% of the imports are realized with turkey. russia follows turkey with a 14.28% share. turkey is azerbaijan’s top importing country. in 2013, turkey made 3 billion worth export to azerbaijan. this value constitutes approximately 2% of the total exports of turkey. foreign trade volume between two countries is 3.295 million dollars. this number is 0.8% of the total foreign trade volume of turkey. azerbaijan ranks at 27th order when foreign trade volume of turkey is evaluated. turkey does not have an important share in the export of azerbaijan. azerbaijan’s export to turkey is 2.5% of its total export. turkey is at the 11th order in the top exporting countries list. while the role of the energy has been often underlined in the turkey-azerbaijan relations, turkey purchases only 1.5% of the oil from azerbaijan. energy pipelines has had more important place as a cooperation area. in this context, the process started with baku-tiflis-ceyhan oil pipeline continues with baku-tiflis-erzurum natural gas pipeline and the trans-anatolia pipeline (tanap). it is important to note that pipelines are important contributors for the independence and welfare of azerbaijan. azerbaijan has been exporting 80% of its oil through turkey. trans-anatolia natural gas pipeline will be the part of southern gas corridor supported by the eu. this pipeline will contribute to the route diversity of turkey. the amount of natural gas that will be transferred to europe with tanap is 10 billion cubic meters at the beginning, and it does not seem as important as south stream, of which russia is the major partner and will have the capacity of 63 billion cubic meters. tanap is a project that provides momentum to turkey-azerbaijan relations. tanap project will strengthen european energy supply security. as having a major strategic importance for azerbaijan and turkey, for turkey and the eu, international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.27-44 42 tanap supports the energy supply security by recognized natural gas capacity and reasonable prices. this pipeline signifies the delivery of its natural gas resources to new markets. as technically being the second largest project, tanap will also contribute to the economies of countries by increasing the employment opportunities and investments. references aa. (2014, 5 march), tanap, 21 ile iş kapısı açacak. http://www.aa.com.tr/tr/s/294458--tanap-21-ileis-kapisi-acacak (05.03.2014). aras, b. (2014), turkish-azerbaijani energy relations. global turkey in europe. policy brief 15. asker, a. (2010), ermeni açılımı sonrası: türkiye-azerbaycan i̇lişkileri. 21. yüzyıl, 15, 45-55. avar, b. (2007), avrasyalı olmak. istanbul: truva yayınları. avrasya dosyası. (1997), azerbaycan’ın yaptığı petrol antlaşmaları, no.85. aydın, m. (2002), dağlık (yukarı) karabağ sorunu, in bakın oran (ed.) türk dış politikası cilt ii:1980-2001, p.401, istanbul: i̇letişim yayınları. aydın, m. (2002), türkiye’nin azerbaycan’la tarihsel bağları ve nahçıvan, in bakın oran (ed.) türk dış politikası cilt ii:1980-2001, p.403, istanbul: i̇letişim yayınları. azerbaijan energy charter secretariat. (2013) in-depth review of the energy efficiency policy of azerbaijan, baku. başer, b. (2008), third party mediation in nagorno-karabagh: part of the cure or part of the disease? orta asya ve kafkasya araştırmaları, 3(5), 86-114. bp. (2014a), baku-tiflis-ceyhan ham petrol boru hattı. http://www.bp.com/sectiongenericarticle.do?categoryid=9032198&contentid=7058942 (10.02.2014). bp. (2014b), aioc. http://www.bp.com/managedlistingsection.do?categoryid=9007997&contentid=7014999 cihan. (2011, 16 kasım), abd: orta asya küresel enerji arenada önemli bölge, http://www.cihan.com.tr/news/852569-abd-orta-asya-kuresel-enerji-arenada-onemli-birbolge-choduynty5lzm (04.03.2014). dış ekonomik i̇lişkiler kurulu. (2012), azerbaycan ülke bülteni, istanbul. eurostat datas (2013). http://epp.eurostat.ec.europa.eu/portal/page/portal/energy/data/database (10.02.2014). gouliev, r. (1997), petrol ve politika: petrol üreten ülkeler arasındaki yeni i̇lişkiler: azerbaycan, rusya, kazakistan ve batı ülkeleri, istanbul: medyatek yayınları. gül, a., gül a. (1995), avrasya boru hatları ve türkiye, istanbul: bağlam yayınları. haberciniz. (2014, 4 march), azerbaycan gazı, avrupa’nın rusya’ya bağımlılığını azaltacak, http://haberciniz.biz/azerbaycan-gazi-avrupanin-rusyaya-bagimliligini-azaltacak-2665816h.htm (05.03.2014). i̇hlas (2012, 27 june), boru hattında i̇mzalar tamam, http://www.ihlassondakika.com/haber/boru-hattinda-imzalar-tamam_489455.html (28.09.2012). hunter, s. t. (1994), the transcaucasus in transition: nation building and conflict, washington: center for strategic and international studies. imf. world economic outlook data. http://www.econstats.com/weo/v008.htm (10.10.2014). i̇brahimov, rovshan (2012), azerbaycan petrol politikası: alternatif enerji hatları arayışı, oaka, 7(14), 125-148. i̇yikan, n. (2011), türk dış politikasında orta asya ve güney kafkasya’nın yeri, in necati i̇yikan (ed.) orta asya ve güney kafkasya siyasi gelişmeler 1991-2010, istanbul: hiperlink. murinson, a. (2008), azerbaijan-turkey-israel relations:the energy factor, middle east review of international affairs, 12(3), http://www.gloria-center.org/2008/09/murinson-2008-09-04/ nasibzade, n. (1998), lecture at the university of california at berkeley: the independent azerbaijan’s oil policy, virtual azerbaijan republic website, 15.04.1998, http://www.scf.usc.edu/~baguirov/azeri/nasibzade1.htm (15.06.1998) nichol, j. (1996), crs report for congress: azerbaijan: basic facts. washington: congressional research service. oran, b. (2002), türk dış politikası cilt ii:1980-2001, istanbul: i̇letişim yayınları. oran, b. (2013), türk dış politikası cilt iii:2001-2012, istanbul: i̇letişim yayınları. turkey-azerbaijan energy relations: a political and economic analysis 43 republic of turkey ministry of foreign affairs. “economic outlook of turkey”, http://www.mfa.gov.tr/prospects-and-recent-developments-in-the-turkish-economy.en.mfa, (09.10.2014). republic of turkey ministry of foreign affairs. (2014a), türkiye-azerbaycan siyasi i̇lişkileri, http://www.mfa.gov.tr/turkiye-azerbaycan-siyasi-iliskileri.tr.mfa (18.02.2014). republic of turkey ministry of foreign affairs. (2014b), ekonomik i̇şbirliği teşkilatı (ei̇t), http://www.mfa.gov.tr/ekonomik-isbirligi-teskilati-_eit_.tr.mfa (15.02.2014). republic of turkey ministry of foreign affairs. (2014c), i̇slam konferansı örgütü, http://www.mfa.gov.tr/islam-konferansi-orgutu.tr.mfa (15.02.2014). republic of turkey ministry of foreign affairs. (2014d), karadeniz ekonomik i̇şbirliği örgütü (kei̇), http://www.mfa.gov.tr/karadeniz-ekonomik-isbirligi-orgutu-_kei_.tr.mfa (15.02.2014). republic of turkey ministry of economy. (2013), azerbaycan cumhuriyeti genel bilgi ve yatırım i̇mkanları, http://www.ekonomi.gov.tr/upload/3819cabc-d34e-bb4af091db3a053180a3/egitim%20programi%20sunum-azerbaycan.pdf (15.02.2014). republic of turkey ministry of economy. (2014), azerbaycan dış ticaret verileri, http://blog.ibp.gov.tr/?p=21050 (15.02.2014). republic of turkey ministry of economy. “the exports strategy of turkey for 2023”, http://www.economy.gov.tr/upload/strategy/strategy2023.pdf (09.10.2014). republic of turkey ministry undersecretariat of treasury. “turkish economy”, october 2014. (https://hazine.gov.tr/file/?path=root%2fdocuments%2fgeneral+content%2fekonomi_sunu mu_eng.pdf, (09.10.2014). republic of turkey energy market regulatory authority. (2012), doğalgaz piyasası 2011 yılı sektör raporu, ankara. seta. (2009), türkiye azerbaycan i̇lişkileri çalıştayı raporu. socar. (2014a), baku-novorossiysk oil pipeline, http://new.socar.az/socar/en/activities/transportation/baku-novorossiysk-oil-pipeline (10.02.2014). socar. (2014b), baku-supsa western export pipeline http://new.socar.az/socar/en/activities/transportation/baku-supsa-western-export-pipeline (10.02.2014). socar. (2014c), baku-tbilisi-erzurum gas pipeline, http://new.socar.az/socar/en/activities/transportation/baku-tbilisi-erzurum-gas-pipeline (10.02.2014). somuncuoğlu, t. (2012), azerbaycan ülke raporu, ankara: t.c. başbakanlık dış ticaret müsteşarlığı i̇hracatı geliştirme etüd merkezi. star. (2014, 17 february), türkiye-azerbaycan-gürcistan i̇ttifakı dünyaya örnek olacak, http://haber.stargazete.com/dunya/turkiyegurcistanazerbaycan-ittifaki-dunyaya-ornekolacak/haber-844504 (18.02.2014). şiriyev, z. (2010), azerbaycan’ın askeri doktrini ve dış politika yansımaları, orta asya ve kafkasya araştırmaları, 5(29), 132-147. şiriyev, z. (2011), azerbaycan’ın karabağ politikası ve stratejik vizyon, orta asya ve kafkasya araştırmaları, 6(12), 88-117. tanap project official website. (2014a), tanap nedir?, http://www.tanap.com/tanap-nedir (01.04.2014). tanap project official website. (2014b), enerjinin i̇pek yolu tanap için i̇mzalar atıldı, http://www.tanap.com/haberler/gelecegin-enerjisi-hazir.aspx (01.04.2014). the state statistical committee of the republic azerbaijan. (2012), foreign trade indicators. the state statistical committee of the republic azerbaijan. (2013), macro-economic indicators of economic and social development of the country in 2013. the military balance. (2013), chapter ten: country comparisions-forcelevels and economics, 113(1), 543-556. tubitak. (2003), vizyon 2023 teknoloji öngörü projesi öngörü projesi-enerji ve doğal kaynaklar paneli raporu. ankara. turkstat. (2013), . foreign trade statistics database. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.27-44 44 eia. (2012), country analysis briefs: azerbaijan, http://www.eia.gov/countries/cab.cfm?fips=aj (01.03.2014). eia. (2013a), country analysis brief overview: azerbaijan, http://www.eia.gov/countries/countrydata.cfm?fips=aj (01.03.2014). eia. (2013b), azerbaijan, http://www.eia.gov/countries/cab.cfm?fips=aj (01.03.2014). eia. (2013c), turkey, http://www.eia.gov/countries/cab.cfm?fips=tu (01.02.2013). yazar, y. (2010), türkiye’nin enerjideki durumu ve geleceği, ankara: seta. yeniçağ. (2014, january 28), en pahalı gazı i̇ran’dan alıyoruz, http://www.yenicaggazetesi.com.tr/en-pahali-gazi-irandan-aliyoruz-94118h.htm (04.08.2014) yergin, d. (1992), the prize: the epic quest for oil, money & power, new york: simon & schuster publication. yesevi, ç.g. (2013), türkiye’nin güvenliği: türkiye’nin enerji stratejisinin yeniden değerlendirilmesi. nevşehir hacı bektaş-ı veli sosyal bilimler enstitüsü dergisi, 3, 238-258. yesevi, ç.g. (2012, october 3), tanap, önce vatan yılmaz, r. (2010), türkiye-azerbaycan i̇lişkilerinde son dönem, bilge strateji, 1(2), 20-34. world bank data, http://databank.worldbank.org/data/views/reports/tableview.aspx (09.10.2014). world bank energy statistics. (2013), enerji i̇statistikleri. http://data.worldbank.org/country/azerbaijan(15.03.2014). world bank energy statitistics. (2013), http://databank.worldbank.org/data/download/gdp.pdf (15.03.2014). world bank statistics. (2014), http://data.worldbank.org/indicator/ny.gdp.pcap.cd, (10.10.2014). tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020 75 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 75-79. wind power: current state and perspectives vladimir yu. linnik1*, e. yu. voronova2, larisa v. pavlyuk3, alexey zich4 1state university of management, moscow, ryazansky pr., 99, russian federation, 2shakhty automobile and road construction institute (branch) of platov srspu (npi), lenin square, 1, shakhty, rostov region, russian federation, 3state university of management, russian federation, moscow, ryazansky pr., 99, russia, 4energy efficiency consultant, ms qf gmbh, oderwitz, germany. *email: vy_linnik@guu.ru received: 17 may 2020 accepted: 27 august 2020 doi: https://doi.org/10.32479/ijeep.9938 abstract due to the depletion of resources for traditional energy, as well as due to the gradual abandonment of nuclear power in a number of countries, the world pays great attention to energy conservation and energy efficiency, one of the main sources of which is renewable energy, which includes wind energy. wind power is the most developed renewable energy industry (excluding hydro), which affects its economic characteristics. thus, onshore wind power plants are characterized by one of the lowest indicators of the cost of electricity production among alternative types of generation. however, offshore wind power plants are still inferior to some types of renewable energy sources and are twice the level of traditional thermal power plants. in this article, the authors consider the state and prospects of development of the world wind energy. the distribution of installed capacity of wind power plants by regions of the world is analyzed and the shares of countries in the total installed capacity are determined. the leading countries were identified as well as the reasons for the rapid growth of wind generation in these countries along with the measures of state support. the state and prospects of wind power development in russia are considered, and it is also noted that the russian federation has significant potential in the field of wind power development, which makes it possible to make optimistic forecasts regarding the provision of electricity to remote areas of russia. the technical electric power potential of wind energy is about 17.1 tw/year, which is an order of magnitude higher than the amount of electricity generated by all power plants in the country in 2018. the scientific increment is to identify the key problems facing the domestic wind power industry. keywords: energy efficiency, energy saving, wind energy, wind power plants, russian wind energy market jel сlassifications: q42, q47, p28 1. introduction the development of industrial production and improving the welfare of the population requires an increase in the need to use traditional sources of energy, the reserves of which are not unlimited in nature. the constant growth of energy consumption in the world, from 20.75 trillion kw in 2015 to a projected level of 33.4 trillion kw in 2030, has led to increased level of attention to energy efficiency and energy conservation issues around the world. until recently, the cost of installing a 1 kw wind generator averaged about $ 1000, and according to experts’ forecasts, it will decrease to $ 420 by 2020 (lyons et al., 2018). as of the end of 2018, electricity generated from wind power has begun to demonstrate competitiveness with energy obtained from traditional sources. given the finite reserves of traditional energy sources, their prices will increase, which means that the cost of energy produced from oil, gas and coal will also increase, which further increases the competitiveness of wind energy. thus, the use of relatively cheap and cleaner energy is a significant factor in improving energy efficiency and energy conservation, which contributes to the economic growth of society, reducing its needs for traditional energy and improving the environment. this journal is licensed under a creative commons attribution 4.0 international license linnik, et al.: wind power: current state and perspectives international journal of energy economics and policy | vol 10 • issue 6 • 202076 2. literature review figure 1 shows data on the distribution of total installed capacity of wind power plants (wind turbines) by regions of the world, which shows that the greatest development of wind power has been in europe, north america and asia. approximately one-third of the world’s wind power is generated on the asian continent (okazaki et al., 2015). according to the results of 2018, the top three world leaders in total wind power capacity (wpc) included china (184.6 gw), the united states (96.5 gw) and germany (56.2 gw) (sidorovich, 2019; zhang, 2019). the share of the top eight countries in the world wind energy balance is about 83%, with more than a third of the world’s installed capacity owned by china and twice as much as the united states (figure 2) (zhang, 2019; pakhomov, 2019). taking into account the geographical location of the european union countries, the greatest opportunities for using wind energy are available in denmark, france, germany, norway, great britain, spain, the netherlands, italy and france. in this regard, the european union is implementing a project to create a system of high-voltage transmission lines that will unite all wind farms in europe in a single network. worldwide interest in wind power has increased so much that industrial and military concerns have become interested in the production of such installations. let’s briefly consider the state of wind power in the main countries implementing renewable energy development programs (ren). 3. results 3.1. china in china, the development of renewable energy, especially wind energy, is considered as one of the priority areas of economic development. the country is implementing a major state program to stimulate the economy, with a total investment of $ 586 billion. of this amount, 25% is allocated for the implementation of projects on environmental protection, development of renewable energy and energy efficiency. the spread of wind power in china is happening at a rapid pace, largely due to the state support (lema and ruby, 2007). in 2018, china’s installed wind power capacity reached 184.6 gw, which is 9.7% of the country’s total installed power capacity and about 35% of the world’s wind capacity. in 2018, china’s wind farms generated 366 billion kw, which accounted for 5.2% of the country’s total electricity generation (tyaglin, 2017). china ranks first in the world in terms of installed wind farms. the capacity of the largest wind farm in china is about 10 gw with the possibility of increasing to 40 gw at a project cost of $17.6 billion. for comparison, the capacity of one of the world’s largest sayano-shushenskaya hps is 6.7 gw (lema and ruby, 2007). to a large extent, this was made possible by the development of china’s own production of equipment for wind turbines. currently, there are about seventy manufacturers of equipment for the wind energy industry in china. 3.2. south korea currently, the share of ren in the country’s electricity generation is 8%. according to previously published documents, the korean authorities planned to increase the share of renewable energy sources to 20% by 2030, with solar and wind energy leading the way. the new draft energy plan stipulates that the share of ren should reach 30-35% by 2040. the draft policy includes a gradual shift away from coal and nuclear power, the two main pillars of south korea’s current energy supply. at the same time, the role of natural gas will grow. today, 44% of electricity is generated from coal. south korea has a developed shipbuilding and heavy industry, which is a good foundation for creating an offshore wind energy industry. doosan heavy industries said last year that it would lead a project supported by the south korean government to develop an 8 mw offshore wind turbine that would both operate in the domestic market and compete globally. offshore wind power will play an figure 1: wind power plant capacity by region source: based on the authors’ research figure 2: the share of countries in the total installed (wpc) source: based on the authors’ research linnik, et al.: wind power: current state and perspectives international journal of energy economics and policy | vol 10 • issue 6 • 2020 77 important role in south korea’s energy future. consultants from wood mackenzie predict 6.4 gw of offshore wind farms in the country by 2030. 3.3. turkey the first wind farm zone was built in izmir in 1998. in 2006, the total capacity of wind turbines was about 19 mw, and in 2007, the capacity increased to almost 140 mw. according to reports prepared by the turkish wind energy association (türeb), in 2018, investments in the wind energy sector amounted to 650 million dollars, which led to an increase in the total installed capacity of wind power plants in 2018 to 7.3 gw, and the wind energy sector itself grew by 7.24%, producing an additional 497.25 mw. as of the end of 2019, the capacity of 198 wind turbines in turkey was 8 mw, which is 1.2% of wind generation worldwide (650 gw). by 2023, turkey plans to invest € 15 billion in the construction of wind farms. the country’s renewable energy development plan calls for bringing the installed capacity of turkish wind power to 23 gw by 2023. according to türeb, during this time, wind farms with a total capacity of 451 mw will be built in the economically significant province of izmir, which accounts for $ 10.2 billion of turkish export and $ 7.5 billion of turkish import. as a result, in izmir, where the first wind farm in turkey was built, the capacity of wind farms will increase from 1549 to 2000 mw, and this region will account for 65% of all electricity generated by turkish wind farms. 3.4. the usa according to the american wind energy association, the installed capacity of wind power in 2018 reached 96.5 gw. there are 56,800 wind turbines operating in 41 states. the growth of the us wind power industry in recent years has been made possible by the demand for this energy resource from companies in various industries that are not directly related to the energy sector. so in 2018, direct contracts (ppa) were signed for the supply of wind energy to companies with a total volume of 4,203 gw. awea estimates that the portfolio of wind energy projects under construction or in the final stages of development has reached 35.1 gw (sugimoto, 2019). the us energy information administration (eia) has estimated that by the end of 2019, us wind power will provide 6.9% of industrial-scale electricity generation. the cost of energy produced by wind farms is still relatively high in the united states, but with the increase in the size of wind farms and the development of technologies, we can expect a decrease in the cost of energy to 2-3 cents/kw, especially in areas with a relatively high average annual wind speed (ratner, 2012; anup et al., 2019). the rapid development of wind power in the united states in recent years has been made possible by government support for the development of the industry. for example, when building a new wind farm, the state allocates a so-called tax credit to the company (simão et al., 2017; gillenwater et al., 2014). 3.5. germany currently, in germany, wind energy is one of the most important renewable energy sources and ranks third in the world in total installed wind power capacity after china and the united states. at the beginning of 2018, the total installed capacity of germany’s wind power plants was 56.2 gw, of which the capacity of mainland wind farms reached 50.777 gw. in 2016, the share of wind power in total electricity consumption in germany was 13.2%, significantly ahead of bio-and hydro-power (ibrahim, 2017; sow et al., 2019). in line with industry trends, the average size of wind turbines is also increasing. the largest share of wind power is accounted for by installations with a capacity of 2 mw, but in projects introduced in germany in 2017, the average capacity of a wind generator has already reached almost 3 mw. active development of wind power in germany began after the chernobyl disaster. it was then that the government program for the development of wind energy was launched, and after the adoption of the law “stromeinspeisegesetz vom 7.12.1990,” the development of the industry accelerated even more. according to this law, energy sales companies are required to buy electricity from solar and wind power producers with a capacity of up to 5 mw at a higher price than before the law was adopted. the difference in price should be covered by energy sales companies at the expense of ultimate consumers. the law adopted in germany has become a model for supporting res in many countries around the world. 19 european countries, as well as japan, brazil and china, have used this model in their legislation. following the adoption of the law “stromeinspeisegesetz vom 7.12.1990” in 2000, germany adopted the law on renewable energy (das erneuerbare-energien-gesetz [eeg]). thanks to these legislative acts, by 2002 the total capacity of the german wind power industry reached 10.0 gw (ketterer, 2014; usmanova, 2019). offshore wind energy is actively developing in germany. by 2030 the german government intends to increase the total capacity of the offshore national wind energy complex to 25 gw. for this purpose, it is planned to build at least 33 offshore wind farms. in germany, there are several large companies that produce wind turbines (vestas, enercon, repower, nordex, fuhrlander), which share in the local market is about 65%. 3.6. india the development of wind power in india began in 1952, when a project was initiated to study the possibilities of using wind energy in the country. large-scale development of wind power in india began in 1986, when the first demonstration wind installations were built in the coastal areas of maharashtra, gujarat and tamil nadu, equipped with 55 and 110 kw vestas wind turbines. according to 2018 data, india became the fourth country in the world in terms of installed wind power capacity with an indicator linnik, et al.: wind power: current state and perspectives international journal of energy economics and policy | vol 10 • issue 6 • 202078 of 34,293 gw. in 2017, wind power in india accounted for almost 10% of the total installed power generation capacity, generating 52.67 gw of electricity, which is almost 3% of the total electricity production in the country (dipen et al., 2020; shawon et al., 2013). the rapid development of wind power in india was the result of a number of legislative acts adopted by the government of the country. thanks to the decisions taken, wind energy costs in india have rapidly started to decrease (dipen et al., 2020; shawon et al., 2013). the wind energy tariff reached a record low of 3.4 us cents per kilowatt hour in 2017 without any direct or indirect subsidies (dipen et al., 2020). the ministry of new and renewable energy has also developed a national offshore wind energy policy that aims to promote the deployment of offshore wind turbines up to 12 nautical miles offshore. the first 100 mw demonstration project is expected to be launched in gujarat. given that india has a 7600-km coastline, opportunities in offshore energy have great potential. 3.7. state and prospects of wind power development in russia the technical electric power potential of the russian wind power industry is about 17.1 tw/year, which is an order of magnitude higher than the amount of electricity generated by all the country’s power plants in 2018 (tulupov et al., 2019; fedotova, 2019). most of the wind zones in russia are located in the south of russia (kalmykia, stavropol and krasnodar territories, rostov, volgograd and astrakhan region, the north caucasus federal district), on the sea coasts. the ideal place for building a wind farm is the far east, which has about 30% of the economic potential of wind power. the problems of wind energy in russia began to be addressed in the 20s of the last century, when the central aerohydrodynamic institute named after professor n. e. zhukovsky (tsagi) first developed wind farms and wind turbines for agriculture. however, despite this seemingly impressive history, the russian wind power industry is currently still significantly behind the growth rate of the industry from other countries of the world (kushnir, 2013; bushukina, 2019). today, more than 50 wind power producers operate on the russian wind power market, among which the largest players are “rosatom” state corporation, the finnish company “fortumcorporation” and the italian group of companies “enel.” in 2017, rosatom’s subsidiary “novavind” jsc and “lagerwey,” a dutch wind turbine manufacturer, established a joint venture called “redwind,” which is responsible for turnkey deliveries of wind turbines and their after-sales service. another subsidiary of rosatom group, jsc “vetroogk,” is responsible for the construction of the wind farm. the latter company plans to build four wind farms in the stavropol territory with a total capacity of 260 mw at a cost of 26 billion rubles. in 2017 the ministry of energy of russia held a competition to select renewable energy projects, as a result of which the investment fund for wind energy development, created by “fortum corporation” and “rosnano,” received the right to build a wind power plant with a total capacity of 1000 mw. the result was the launch in the ulyanovsk region of the country’s first 35 mw wind farm connected to the wholesale market. as part of this project, the main manufacturer of wind generators, the danish company “vestas wind systems a/s,” will create enterprises on the territory of russia for the production of components for wind generators, the first of which, located in ulyanovsk, will specialize in the production of wind turbine blades (vestas manufacturing rus) (lopatkin et al., 2019; alekseev and afanasev, 2020). in early 2018, pjsc “enel russia,” controlled by “enel,” signed an agreement to build a wind power plant in the rostov region with a capacity of 90 mw and in the stavropol territory with a capacity of 300 mw. the international concern “siemens gamesa,” which specializes in the production of wind turbine generators, will supply equipment and then localize production for future wind farms. the start of commissioning of the wind farm is planned for 2020. to date, russia has 11 large wind farm with a capacity of over 1 mw, 8 wind power <0.1 mw and the project more than 20 wind farms, mainly intended for placement in the southern regions of the country. the most powerful wind farm in russia today is considered to be the ulyanovsk wps-1. it includes 14 wind turbines with a total capacity of 35 mw with an annual sales volume of about 85 gwh. 4. conclusion according to a report entitled “the future of wind,” presented on october 21 at the china wind power event in beijing, by 2050, the world’s wind power could grow tenfold and cross the threshold of 6,000 gw. by the middle of the century, wind power could meet a third of the world’s electricity demand and, combined with further electrification, reduce the carbon emissions generated by the energy industry by a quarter, which is necessary to meet the terms of the paris agreement. to achieve these goals, it is necessary to increase wind power capacity on land and at sea by four and ten times, respectively, compared to the existing ones. the bet on renewable energy is correct. for the state, wind farms are not just an object of generation, but also the development of new technologies, the creation of additional jobs, and the growth of orders for equipment. the global wind power industry can become a true driver of job creation, providing employment for more than 3.7 million people by 2030 and more than 6 million by 2050. these figures are almost 3.5 times higher, respectively, than the number of jobs that make up just over a million in 2018. sound industrial and labour policies that build on and strengthen domestic supply chains can help increase income and employment by attracting existing economic activities to support wind energy development. as for the prospects for the development of this market in the regional context, the authors believe that asia can increase the installed capacity of its own onshore wind power from 230 gw in 2018 to more than 2600 gw by 2050. by this time, the region linnik, et al.: wind power: current state and perspectives international journal of energy economics and policy | vol 10 • issue 6 • 2020 79 will be a world leader in wind power, accounting for more than 50% of all onshore installed capacity and more than 60% of all the offshore capacity. references alekseev, a.o., afanasev, v.y. (2020), integration of corporate technological foresight into the technological development management system in companies of oil and gas sector. upravlenie, 8(1), 35-46. anup, k., whale, j., urmee, t. (2019), urban wind conditions and small wind turbines in the built environment: a review. renewable energy, 131, 268-283. bushukina, v. (2019), renewable energy investment prospects in russia. finance and business, 3, 85-102. china’s wind power industry grew by 20.6 gw. (2018), available from: http://www.renen.ru/china-s-wind-power-in-2018-grown-by-20-6gw. [last accessed on 2020 may 09]. dipen, p., poorva, p., purva, k. (2020), techno-economic feasibility of wind power farms in india. international journal of innovative technology and exploring engineering, 9(5), 1041-1046. fedotova, e. (2019), wind projections for the territory of russia considering the development of wind power. iop conference series: earth and environmental science, 386, 012042. gillenwater, m., lu, x., fischlein, m. (2014), additionality of wind energy investments in the u.s. voluntary green power market. renewable energy, 63, 452-457. ibrahim, n. (2017), statistical analysis of photovoltaic and wind power generation in germany. ssrn electronic journal, 11(3), 1-27. ketterer, j. (2014), the impact of wind power generation on the electricity price in germany. energy economics, 44, 270-280. kushnir, v.g. (2013), wind as an alternative type of energy. electrotechnical and information complexes and systems, 9, 30-32. lema, a., ruby, k. (2007), between fragmented authoritarianism and policy coordination: creating a chinese market for wind energy. energy policy, 35(7), 3879-3890. lopatkin, d.s., shushunova, t.n., shaldina, g.e., gibadullin, a.a., smirnova, i.l. (2019), renewable and small energy development management. journal of physics: conference series, 1399, 033061. lyons, s., whale, j., wood, j. (2018), wind power variations during storms and their impact on balancing generators and carbon emissions in the australian national electricity market. renewable energy, 118, 1052-1063. okazaki, t., shirai, y., nakamura, t. (2015), concept study of wind power utilizing direct thermal energy conversion and thermal energy storage. renewable energy, 83, 332-338. pakhomov, m.a. (2019), modern experience of energy saving in foreign countries. international journal of applied science and technology, 1, 153-160. ratner, s. (2012), socio-economic effects of alternative energy development in the usa. national interests: priorities and security, 28, 47-55. shawon, m., el chaar, l., lamont, l. (2013), overview of wind energy and its cost in the middle east. sustainable energy technologies and assessments, 2, 1-11. sidorovich, v. (2019), in 2018, 7.6 gw of wind power plants were commissioned in the united states. available from: http://renen.ru/ in-2018-7-6-gw-of-wind-power-stations-were-commissioned-in-theusa. [last accessed on 2019 oct 12]. simão, h., powell, w., archer, c., kempton, w. (2017), the challenge of integrating offshore wind power in the u.s. electric grid. part ii: simulation of electricity market operations. renewable energy, 103, 418-431. sow, a., mehrtash, m., rousse, d., haillot, d. (2019), economic analysis of residential solar photovoltaic electricity production in canada. sustainable energy technologies and assessments, 33, 83-94. sugimoto, k. (2019), does transmission unbundling increase wind power generation in the united states? energy policy, 125, 307-316. tulupov, a., vitukhin, a., ismatdinov, m. (2019), ensuring national security with environmental and economic criteria. vestnik tomskogo gosudarstvennogo universiteta. ekonomika, 48, 50-56. tyaglin, d. (2017), endless wind energy. regional development: electronic scientific and practical journal, 4, 8-9. usmanova, t.h. (2019), introduction of innovations in the management of organizations in the development of alternative energy sources. business strategies, 9, 2-16. zhang, p. (2019), do energy intensity targets matter for wind energy development? identifying their heterogeneous effects in chinese provinces with different wind resources. renewable energy, 139, 968-975. http://renen.ru/in-2018-7-6-gw-of-wind-power-stations-were-commissioned-in-the-usa http://renen.ru/in-2018-7-6-gw-of-wind-power-stations-were-commissioned-in-the-usa http://renen.ru/in-2018-7-6-gw-of-wind-power-stations-were-commissioned-in-the-usa international journal of energy economics and policy vol. 5, no. 1, 2015, pp.80-95 issn: 2146-4553 www.econjournals.com 80 the broker simulation model in the emission allowances trading area petr cermak research institute of the it4innovations centre of excellence, faculty of philosophy and science, silesian university, bezruc sq. 13, opava, 74601, czech republic. email: petr.cermak@fpf.slu.cz jarmila zimmermannova department of economics, moravian university college olomouc, tr. kosmonautu 1288/1, olomouc, 77900, czech republic. email: jarmila.zimmermannova@mvso.cz jan lavrincik department of it and applied mathematics, moravian university college olomouc, tr. kosmonautu 1288/1, olomouc, 77900, czech republic. email: jan.lavrincik@mvso.cz miroslav pokorny department of it and applied mathematics, moravian university college olomouc, tr. kosmonautu 1288/1, olomouc, 77900, czech republic. email: miroslav.pokorny@mvso.cz jiri martinu research institute of the it4innovations centre of excellence, faculty of philosophy and science, silesian university, bezruc sq. 13, opava, 74601, czech republic. email: slu.martinu@gmail.com abstract: this paper is focused on possibilities of simulations of emission allowances trading within the eu emission trading system using new designed broker simulation model which integrates different original soft computing and decision making methods. firstly, the paper presents the background of the eu emissions trading system and an overview of different methods used in current research connected with co2 emission allowances trading. the key part of the paper focuses on the broker simulation model creation and application. the results are based on expert systems with fuzzy rule bases, nonlinear fuzzy rule based predictors and fuzzy rule based behavior modelling. the application part of the results has been performed in matlab. the broker simulation model is able to make decisions connected with the traded amount, price of allowances and buy/sell actions within the time on the market. keywords: eu ets; fuzzy modelling; broker jel classifications: c44; q48; q58 the broker simulation model in the emission allowances trading area 81 1. introduction 1.1 the eu emissions trading system overview the european union established a scheme for emission allowances trading, the eu emissions trading system, also called eu ets, dealing with greenhouse gas emissions. the initial eu emissions trading system was based on directive 2003/87/ec, which established a fundamentally decentralized system for the pilot phase of emissions trading (2005 to 2007) and the kyoto protocol commitment phase (2008 to 2012). the key instrument here was the preparation of national allocation plans (naps) (wettestad et al., 2012). currently, based on directive 2009/29/ec, the eu ets has step into phase iii (2013 to 2020), the post-kyoto commitment period. the eu ets is actually the largest emissions market in the world; however in comparison with energy markets it is relatively small (conrad et al., 2012). in total, around 45% of total eu emissions are limited by the eu ets (european commission, 2013). a sufficiently high carbon price promotes investment in clean, low-carbon technologies. the regulatory framework of the eu ets was largely unchanged for the first two trading periods of its operation, however the beginning of the third trading period in 2013 brings changes in common rules1 which should strengthen the system from year 2013 the most important yield of the emission allowances is auctioned. sectorial differentiation was introduced, with (initially) far more auctioning of allowances for energy producers than energy-intensive industries. in addition, free allocations were further harmonized, to be based on common state-of-the-art technology benchmarks (wettestad et al., 2012). policy makers give firms an incentive to move towards production that is less fossil-fuel intensive (aatola et al., 2013). in last years, co2 became a significant member of the european commodity trading market. however, there is a fundamental difference between trading in co2 and more traditional commodities. sellers are expected to produce fewer emissions than they are allowed to, so they may sell the unused allowances to someone who emits more than the allocated amount. therefore, the emissions become either an asset or a liability for the obligation to deliver allowances to cover those emissions (benz and trück, 2009). the market price of the allowances is determined by supply and demand. both in the first and in the second trading period, the eu emission allowances were traded mostly on the bluenext trading exchange (bluenext, 2012). in the third trading period there has only been one big exchange which can be used for emission rights trading – european energy exchange eex (eex, 2014). eex has offered trading of emission allowances on the basis of the eu ets since 2005. eex currently runs a secondary market for continuous trading on a spot and derivatives basis for eu ets allowances (european emissions allowances eua, european aviation allowances euaa) and kyoto credits (cer, eru). in addition to the secondary market, eex conducts large-scale primary auctions of emissions allowances on behalf of the eu member states as well as for germany and poland, held four days per week. in the framework of these auctions, emission allowances are issued to the market participants for the first time (eex, 2014). 1.2 modeling of the eu emissions trading system since emission allowance trading has primarily started in the us, the majority of publications dealing with tradable emission allowances assess the market for so2 emissions under the acid rain program (benz and trück, 2009). regarding the eu ets, scientists have focused mostly on modelling and forecasting the prices of co2 emission allowances (benz and trück, 2009; li et al., 2011; conrad et al., 2012; garcia-martos et al., 2013; lecuyer and quirion, 2013), the incidence of the carbon price (grainger and kolstad, 2010), the eua price drivers (aatola et al., 2013; lutz et al., 2013), the marginal cost of both energy intensive companies and power sector (lund, 2007; chernyavska and gulli, 2008), the influence of emission allowance trading on electricity producers (lund, 2007; chernyavska and gulli, 2008; falbo et al., 2013), its innovation impact (rogge et al., 2011; rentizelas et al., 2012) or economy-wide impacts of adopted and planned climate mitigation measures with a focus on energy efficiency (lutz et al., 2014). the authors of scientific papers have used various methods for their research connected with the eu ets. mainly in last years, we can find scientific studies, which describe particular models of eu ets, created with different methods and different targets. for example, li et al. (2011) used fuzzy 1 published as directive 2009/29/ec international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.80-95 82 modelling (an interval-fuzzy two stage stochastic programming model) for planning co2 emission trading in industry systems under uncertainty, conrad et al. (2012) used garch models for modelling the adjustment process of eua´s2 prices to scheduled macroeconomic and regulatory announcements. aatola et al. (2013) created an equilibrium model of the emission trading market for the purposes of the eu ets price determination, falbo et al. (2013) created model based on the profit function for tracking of impacts of euas on the optimal policy of a competitive electricity producer. garcia – martos et al. (2013) used both arima and varima models for building a multivariate model for the afore mentioned prices and comparing its results with those of univariate ones, lecuyer and quirion (2013) created analytical and numerical model of the eu energy and carbon market for implications of the possibility of a nil carbon price on optimal policy instrument choice. lutz et al. (2013) used markov regime-switching garch model for examination of the non-linear relationship between the eua price and its fundamentals. currently, there is a lack of scientific studies focused on national sub-models of the eu ets, therefore we have focused our research on creation of the broker simulation model of emission allowances trading in the czech republic, based on the behaviour of particular agents companies within the eu ets. the key task of this paper is to present the first version of the broker simulation model, based on expert systems with fuzzy rule bases, nonlinear fuzzy rule based predictors and fuzzy rule based behavior modelling. the discussion part of the paper will focus on an advantages and disadvantages of proposed model; furthermore the next steps in the eu ets research will be suggested. 2. methodology and data 2.1 the eu ets system the common problem of complex system modeling is to identify the system parts, data flows and modeling methods for the subsystems. we identified three main parts of the eu ets system: the first one is the eua market. the second part consists of particular agents (a1,…, an) – companies. those agents behave to optimize their business goals (dealing with the behaviour of the companies in the czech republic and their decision-making see pawliczek and piczszur, 2013). great role in a decision making has an uncertainty caused by unknown goals of the other agents, by internal parameters of the eua market and by external effects. the last block represents a ministerial supervision, which can have usually one year period. the following figure 1 shows the scheme of the whole system of the eu ets. figure 1. model of the eu emission allowances trading source: zimmermannová and čermák (2014). we can see the exchange (emission allowances trading, primary and secondary market), ministry of the environment of the czech republic (ministry) and particular stakeholders involved in the eu ets, operating on the exchange (a1,…, an). focusing on stakeholders operating on the 2 eua = 1 eu emission allowance the broker simulation model in the emission allowances trading area 83 exchange and their characteristics, we can distinguish 2 main groups of stakeholders with different targets: companies – polluters and brokers. company – polluter tries to optimize its costs and revenues connected with the eu ets. this stakeholder communicates both with the ministry and with the exchange; he also can communicate with other stakeholders. in case that his marginal abatement costs connected with decrease of 1 ton of co2 emissions are lower than the current eua price on the market, he can try to decrease his pollution and to trade with redundant emission allowances on the exchange. in case his marginal abatement costs connected with decrease of 1 ton of co2 emissions are higher than the current eua price on the market, he would be better to buy additional euas on the exchange and to cover all his co2 emission. on the other hand the broker operates on the exchange for the purposes of profit or the euas investments. within the system, he communicates only with the exchange, he can also communicate with other stakeholders – companies or brokers. broker can work also for the companies – polluters, for example he can trade on the exchange as representative of the particular company – polluter. 2.2 market model regarding the eua market, there are 2 possibilities of trading – agents can buy allowances at the primary spot market in auctions or at the secondary spot market in continuous trading. auctioning is the basic principle of allocating allowances within the eu emissions trading system (eu ets). eex has been awarded the role as the transitional common auction platform to auction allowances on behalf of 24 member states. in this capacity, eex also conducts emissions auctions for poland during a transitional period. in addition, eex has been selected as germany’s permanent auction platform. in these functions, eex holds regular auctions of eu allowances (euas) on its spot market. the eu emission allowances auctions are organized weekly on mondays, tuesdays and thursdays, the clearing price is announced at 11 am cet. regarding auction format, bids are submitted during one given bidding window, without seeing other participant's bids and all successful bidders pay the same auction clearing price. the auction clearing price is determined as follows: bids are sorted in descending order of the price bid;  bid volumes are added, starting with the highest bid; the price at which the sum of volumes bid matches or exceeds the volume of allowances auctioned, shall be the auction clearing price;  tied bids will be sorted through random selection according to an algorithm;  all bids with a price higher than the auction clearing price are successful; execution of bids made at the auction clearing price depends on their ranking in the random selection;  partial execution of orders may be possible for the last successful bid matching the auction clearing price, depending on the remaining quantity of allowances. the following table 1 shows an example of setting of the auction clearing price with available quantity of eua in the total amount of 3.461.500 (zimmermannová and čermák, 2014). regarding the secondary spot market, based on continuous trading, the eex spot market comprises continuous trading which takes place between 8:00 am and 6:00 pm (cet) on every exchange trading day. 2.3 agent (company) behavioral and decision making model the proposed model must meet the following requirements:  use expert knowledge of domain experts from different areas;  adopt appropriate conclusions in case of contradictory decisions of particular experts;  be able to perform short term predictions;  overcome outside influences;  create or select the best strategy to achieve desired long-term goals;  optimizing global agent’s behavior. regarding these requirements, we have created the single agent behavioral and decision making model. the following figure 2 shows the scheme of a single agent model. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.80-95 84 table 1. example of determination of auction clearing price on the primary market. (zimmermannová and čermák, 2014). companies price quantity time final distribution price quantity cumulative quantity bez 4,52 500000 8:32 bez 4,52 500000 500000 cez 4,51 450000 9:01 cez 4,51 450000 950000 čez 4,51 300000 8:01 čez 4,51 300000 1250000 dez 4,49 50000 8:15 dez 4,49 50000 1300000 fez 4,48 200000 10:30 fez 4,48 200000 1500000 gez 4,48 400000 10:55 gez 4,48 400000 1900000 hez 4,47 551000 8:10 hez 4,47 551000 2451000 jez 4,46 70000 8:09 jez 4,46 70000 2521000 kez 4,46 350000 8:25 kez 4,46 350000 2871000 lez 4,46 285000 10:59 lez 4,46 285000 3156000 mez 4,45 80500 10:00 mez 4,45 80500 3236500 nez 4,44 175000 8:08 nez 4,44 175000 3411500 pez 4,44 100000 9:10 pez 4,44 50000 3461500 qez 4,43 50000 10:10 qez 4,43 0 rez 4,42 150000 8:42 rez 4,42 0 sez 4,41 70000 8:50 sez 4,41 0 tez 4,41 80000 9:45 tez 4,41 0 vez 4,4 500000 9:11 vez 4,4 0 wez 4,39 300000 8:16 wez 4,39 0 zez 4,38 450000 8:20 zez 4,38 0 total 5111500 3461500 3461500 source: zimmermannová and čermák (2014). figure 2. single agent model source: zimmermannová and čermák (2014). the broker simulation model in the emission allowances trading area 85 each area is represented by single block described as “domain expert”. in case of contradictory decisions of particular experts we apply cognitive analysis in “decision block”. for the purposes of the prediction “sell/buy amount of allowances” together with actual price we plan to use fuzzy nonlinear regression model. this model allows us to predict short term behavior of the co2 allowances trade. extracted rules can obtain information in more readable form, in comparison with neural network. in case of rapid changes on the emission allowances market or in case of great increase of rmse error, we can adopt fuzzy nonlinear regression model. both the rmse error and particular rules can give information used by “prediction analysis” block. this block gets information to the “decision block”. each type of company have own strategy how to achieve desired goals. if this kind of long term goal could be defined and implement as cost or fitness function, we can used evolution strategy optimizing techniques. for the purposes of the broker model creation, we have used fuzzy rule-based systems. these systems use takagi-sugeno rules and mamdani type of rules. takagi-sugeno fuzzy rule-based system is defined as if (x1 is a1,1) and . . . (xn is an,1) then (y2 = f (x1,x2, x3, ..., xn)) (1) if (x1 is a1,r) and . . . (xn is an,r) then (yr = f (x1,x2, x3, ..., xn)) antecedent part of each rule gives truth value of rule. the consequent part realizes function, usually linear combination of inputs. this type of fuzzy rules based system is well suited for prediction of a time series, modeling of nonlinear functions and also used for predictive control. for the purposes of determination of structure and parameters we use neural networks. the fusion variants are fuzzy neural network. more detailed description of structure and parameter identification of the fuzzy neural network is in cermak and pokorny (2001). this type of system is used in this research especially for predictions. the fuzzy neuro regression model (fnrm) is shown on figure 3. the fnrm predictor is based on fuzzy-neural network and auto regression model with extended inputs. figure 3. fnrm predictor source: cermak and chmiel (2004). input vector consists of u past outputs and m past inputs of predicted system. the result is actual predicted output value. measurement of quality is given by root mean square error (rmse). the version of the fnrm with both on-line and continual learning also exists. more detailed description you can find in cermak and chmiel (2004) or cermak (2005). the second one mamdani fuzzy rule-based system is defined as: if (x1 is a1,1) and . . . (x is an,1) then (y1 is c1) (2) if (x1 is a1,1) and . . . (x is an,1) then (y2 is c2) if (x1 is a1,r) and . . . (x is an,r) then (yr is cr) the difference between takagi-sugeno rules and mamdani type of rules is in consequent part of particular rules. these consequents are realized by terms like “the sell/buy status of allowances is quick sell”. this type of rules is well suited to develop of an expert system, definition of behavior of the agents. those rules can be extracted with using some evolution strategies (cermak and chmiel, 2004). regarding multi expert system, there is a problem with making right decision of the whole system in case of opposite decisions of two or more experts. this problem could solve cognitive analysis (cermak and mura, 2012). this analysis computes consistence matrix and consistence histogram to determine which rules are consistent with other expert’s possible decisions. if histogram + y ( k 1 ) y ( k -u ) u ( k 1 ) u (k -m ) p a s t o u tp u ts p a s t i n p u ts p r e d ic te d o u tp u t w (k ) e ( k ) p r ed ic tio n e r r o r r e a l s ys te m o u tp u t f u z z y n e u r a l n e tw o r k y * ( k ) international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.80-95 86 value is equal to number of experts, it is ideal case. when the histogram value decreases, belonging rules cause more inconsistent contribution to the whole system decision. 2.4 data for the purposes of the model creation, we have used data from eex exchange (eex, 2014), the leading energy exchange in europe, particularly the following data and information: the eu emission allowances (euas) spot prices in particular trading days, information regarding the eex exchange rules, trading conditions, emissions auctions, emissions allowance secondary market and other additional information regarding the eu emission allowances trading. 3. results – the model description 3.1 the eua market analysis for the purposes of speculative intraday trading, especially forex, commodities and other derivatives on financial markets, the brokers use fundamental and technical analysis. our intention deals with instruments of technical analysis, because they can predict future price movements; however fundamental analysis is based on real market data (price, volume, volatility). technical analysis would be meaningless if the markets move randomly. regarding emissions trading, the price may be drastically affected by the policy decisions. generally, prior to particular decision, the eua price stagnates. after the decision, the value can increase by more than 100 %. anticipating these characteristics, the broker’s responses to particular situations are crucial in terms of profitability of the client. the following figures 4, 5 and 6 show the eua spot price development in the period 2012 – 2014. figure 4. european emission allowances (eua) – 2012 (eex, 2014). figure 5. european emission allowances (eua) – 2013 (eex, 2014). figure 6. european emission allowances (eua) – 2014 (eex, 2014). 5 6 7 8 9 10 price date 2 3 4 5 6 7 price date 3 5 7 9 1/7/yy 2/7/yy 3/7/yy 4/7/yy price date emission allowances 2014 (1.1.2014 2.5.2014) the broker simulation model in the emission allowances trading area 87 because of drastic changes in political decisions during the analysed period, it is difficult to predict the eua spot price. based on this situation, we propose the basic system of the trend line analysis, polynomical two period moving averages, for the short-term trading predictions based on data from march 17th, 2014 april 14th, 2014. polynomical two period moving average is defined as: x = 2 / (n + 1), (3) ma = (p-1) + [x * (p – (p – 1)], whereas n = number of days, p – 1 = price of the previous day, p = current price the results are shown on figure 7. figure 7. emission allowances – trendlines polynomical, two period moving average we can see the circular trend and therefore when the large radius of the circle waits to achieve lower bottom, we recommend to buy emission allowances and to wait for the achievement of the expected minimum 5 % increase in the level of 5.75. for the chosen strategy the broker can get higher returns over a longer time interval. for two periods it would be better to use moving average proposed by the following scenario. as we can see from figure 7, shopping is optimal to implement at the trend line located under the main line graph, we call this level of resistance. for the chosen strategy the broker can get lower valuations for a shorter time interval. from the available historical data of the years 2012, 2013 and 2014, we put together a business charts and graphs candles on the basis of software intended for trading determined the individual zones and border designs for trade and sale (see table 2). table 2. emission allowances – zone (clarity ©, 2014). zone trend result buy sell zone 1 -2 +2 0,651 0,085 zone 2 >2 0,372 1,794 zone 3 <-2 1,906 0,119 by identifying those areas, we decided to create fuzzy rules model. for more accurate decision-making criteria, we have introduced even zones 4 and 5, it is a boundary zone of growth and decrease of more than 4 %. 3.2 brokerv2 – the fuzzy rule-based model the linguistic fuzzy rule-based model works with the price development trend (tvc), the gross domestic product (hdp), the economy development (vek), the commodities price (cko) presenting the four input linguistic variables and with the broker behaviour (cha) serving as the one output linguistic variable. the input variables always have 3 linguistic values and the output one has always 5 linguistic values. the input variables universes are normed <0, 100>. the input variables linguistic values names are identical. 4 4,5 5 5,5 6 6,5 3/ 17 /y y 3/ 19 /y y 3/ 21 /y y 3/ 23 /y y 3/ 25 /y y 3/ 27 /y y 3/ 29 /y y 3/ 31 /y y 4/ 2/ yy 4/ 4/ yy 4/ 6/ yy 4/ 8/ yy 4/ 10 /y y 4/ 12 /y y 4/ 14 /y y price date international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.80-95 88 decrease pkl [0, 0, 50] stagnation sta [0, 50, 100] increase rst [50, 100, 100] according to the figure 8, the linguistic values are formalized by the fuzzy sets with the triangular membership functions. figure 8. the membership functions of the fuzzy sets input variables linguistic values (authors). the broker behaviour output linguistic variable is defined on the <-1.10e4, +1.10e4> universe with the following linguistic values: big purchase nve [5.10e2, 1.10e4, 1.10e4] standard purchase nst [0, 5.10e2, 1.10e4] no action nul [-5.10e2, 0, 5.10e2] standard sale pst [-10.10e4, -5.10e2, 0] big sale pve [-1.10e4, -1.10e4, -5.10e2] the membership functions shapes of the output linguistic values are illustrated by the figure 9. figure 9. the membership functions shapes of the output linguistic values (authors). 3.3 brokerv2 model input values data preparation the current input variables values are the following: 1) tvc – the eua price development trend3 2) hdp – gross domestic product4 3) vek – economy development5 4) cko – commodities price6 a variable “economy development” can be calculated as vek = hdp + inf + usa + eus + win (4) 3 for more information see www.eex.com 4 for more information see www.partia.cz 5 for more information see www.partia.cz 6 for more information see www.partia.cz the broker simulation model in the emission allowances trading area 89 whereas hdp = gross domestic product, usa = interest rate, eus = forex course development eur/usd, win = world inflation. a variable “commodities prices” can be calculated as: cko = pxe + kov (al + cu + pb + ni + zn + pd) (5) + sko (ba + sb + ps + ku + ka + cu) + fko (au + sg + pt) whereas pxe = prague energy stock market index praha, kov = metals, sko = soft commodities and fko = fix metals; the individual commodities consist of the following items: al (aluminium), cu (copper), pb (lead), ni (nickel), zn (zinc), pd (palladium), ba (cotton), sb (soya beans), ps (wheat), ku (corn), ka (cacao), cu (sugar), au (gold), sg (silver), pt (platinum). the input variables values are acquired from the stated webpages. then the input variables are further normalized to the <0,100> range. the procedure of the input data ranges normalization is the following: the xi input data values normalization to the <0, 100> range is performed by the following common relation: minminmax 11 1 , )(),...,min(),...,max( ),...,min( iii xxxx xxx x ii ii normi    (6) whereas xi,norm = input variable normalized value, xi = variable initial value, imin = normalized interval lower limit and imax = normalized interval upper limit. 3.4 brokerv2 model rules structure knowledge base the linguistic values complete combination of the all input variables presents the fuzzy model consisting of the r = 34 = 81 conditional if-then rules. the fuzzy model was structurally optimized following the expert consequents declaration (6) as this optimization led to the rules reduction to the final rules number r = 17. their verbal interpretation are the following: 1) if development_trend is decrease and commodities_price is decrease then behaviour_on_the_market is big_purchase 2) if development_trend is decrease and commodities_price is stagnation then behaviour_on_the_market is big_purchase 3) if development_trend is decrease and commodities_price is increase and economy_development is decrease then behaviour_on_the_market is big_purchase 4) if development_trend is decrease and commodities_price is increase and economy_development is stagnation then behaviour_on_the_market is big_purchase 5) if development_trend is decrease and commodities_price is increase and economy_development is increase then behaviour_on_the_market is standart_purchase 6) if development_trend is stagnation and commodities_price is decrease then behaviour_on_the_market is standart_purchase 7) if development_trend is stagnation and commodities_price is stagnation and economy_development is decrease then behaviour_on_the_market is standart_purchase 8) if development_trend is stagnation and commodities_price is stagnation and economy_development is stagnation then behaviour_on_the_market is standart_purchase 9) if development_trend is stagnation and commodities_price is stagnation and economy_development is increase then behaviour_on_the_market is no_action 10) if development_trend is stagnation and commodities_price is increase then behaviour_on_the_market is no_action 11) if development_trend is increase and commodities_price is decrease then behaviour_on_the_market is standart_sale 12) if development_trend is increase and commodities_price is stagnation and economy_development is decrease and hdp is decrease then behaviour_on_the_market is standart_sale 13) if development_trend is increase and commodities_price is stagnation and economy_development is decrease and hdp is stagnation then behaviour_on_the_market is standart_sale 14) if development_trend is increase and commodities_price is stagnation and economy_development is decrease and hdp is increase then behaviour_on_the_market is big_sale international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.80-95 90 15) if development_trend is increase and commodities_price is stagnation and economy_development is stagnation then behaviour_on_the_market is big_sale 16) if development_trend is increase and commodities_price is stagnation and economy_development is increase then behaviour_on_the_market is big_sale 17) if development_trend is increase and commodities_price is increase then behaviour_on_the_market is big_sale 3.5. broker model implementation in the matlab system the language model implementation was made within the fuzz toolbox programming environment of the matlab system. deduction is performed by the mamdani’s deduction method. defuzzyfication is provided by the cog method. figures 10, 11, 12, 13, 14 and 15 show the matlab interactive screens with presentations of the program editing and model function simulation. figure 10. agent – broker model main screen (authors). figure 11. input variable language values (authors). the broker simulation model in the emission allowances trading area 91 figure 12. output variable language values (authors). figure 13. model rules editing screen (authors). international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.80-95 92 figure 14. example of the outputs functional dependence on the inputs (authors). figure 15. simulation screen (authors). 4. discussion regarding proposed broker simulation model and his significance in a decision making process, it should be mentioned, that this instrument can serve both as an important additional source of information and as a significant tool for particular strategies simulations. the model can simulate different development of the eu ets, for example different development of prices of one emission allowance on the spot market and consequent impacts of these changes on particular broker (company) behavior. generally, the broker simulation model can serve as an experimental eu ets space, where we can track changes in behavior of the broker. the possibility to extend the one-agent broker model to the multiagent one should be discussed. the individual brokers can have for example the following specifics: the broker simulation model in the emission allowances trading area 93 1. basic agent – broker • purchases on the primary and the secondary market; • sells on the secondary market; • cooperate if it is beneficial to him. 2. quantity agent – large bank, institution • purchases in a large amounts on the primary and the secondary market; • sells on the secondary market; • cooperate if it is beneficial to him; • sells already purchased allowances on the secondary market for a higher price than was their purchasing price on the primary market. 3. agent, that failed on the auction market – institution or broker that wanted to buy in auction, but it offered too low price so that it failed. the allowances are really necessary for him. • purchases on the primary market, it fails there, purchases on the secondary market; • its rules will be similar to the broker 1, considering the fact that he will purchase the allowances for the higher price than the broker 1; • it can cooperate, e.g. make an agreement with some of the other agents that they will join the allowances amount requirements on the secondary market to achieve a lower price; • purchases only. 4. agent paid by company – an institution or broker that should purchase the certain amount of allowances for the xy company (it really require the given allowances amount). • purchases on the primary and the secondary market; • the xy company really needs the certain xy amount of allowances and buys them even for a higher price (we can set the particular limit or we can set the arbitrarily high price), i.e. the broker purchases by the company request; • it can cooperate, e.g. make an agreement with the quantity agent that the last mentioned will purchase the higher allowances amount for lower price and then to sale part of it to the agent paid by company; • only purchases on the market. 5. agent paid by company – an institution or broker that should purchase the certain allowances amount for the zz company (the company that wants to invest). • purchases on the primary and the secondary market; • the zz company does not necessarily need the certain amount of allowances but wants to invest in it, i.e. the broker purchases by the company request; • it can cooperate in the same way as the previous agent – e.g. make an agreement with the quantity agent that the last mentioned will purchase the higher allowances amount for lower price and then to sale part of it to the agent paid by company; • a difference in comparison with the previous agent – the agent purchases even for the disadvantageous price for the xy company, the agent purchasing for the zz company buys only if the price is good. there can be the following options for cooperation of particular agents: the first one is that the agents can make an agreement with the quantity agent that the last mentioned will purchase the higher amount of allowances for the preferable price and then to sale part of it at a profit to them. the second one is that some agents purchasing on the auction market can agree on (regarding the increasing price of the allowances) that they will buy up the auction market – i.e. they will offer a higher price and buy up the large amount of the allowances. they can sell these allowances at a profit on the same day or on the following days as to the allowances price is increasing. 5. conclusions this paper is focused on possibilities of simulations of emission allowances trading within the eu emission trading system using new designed broker simulation model which integrates different original soft computing and decision making methods. the paper presents the background of the eu emissions trading system and an overview of different methods used in current research connected with co2 emission allowances trading. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.80-95 94 the key part of the paper focuses on the broker simulation model creation and application. the results are based on expert systems with fuzzy rule bases, nonlinear fuzzy rule based predictors and fuzzy rule based behavior modelling. the application part of the results has been performed in matlab. the broker simulation model is able to make decisions connected with the traded amount, price of allowances and buy/sell actions within the time on the market. in the next steps, the given system will be further extended by the other types of agents and also by the agent internal structure. acknowledgements this research was supported by the grant no. p403/12/1811 provided by the czech science foundation. references aatola, p., ollikainen, m., toppinen, a. (2013), price determination in the eu ets market: theory and econometric analysis with market fundamentals. energy economics, 36, 380–395. benz, e., trück, s. (2009), modeling the price dynamics of co2 emission allowances. energy economics, 31(1), 44-15. bluenext. (2012), bluenext statistics closing prices bluenext spot eua 05-07; closing prices bluenext spot eua 08-12. [online]. [cit. 2012-10-06]. www: http://www.bluenext. eu/statistics/downloads.php. cermak, p. (2005), online learning of neural takagi-sugeno fuzzy model, 24rd international conference of the north american fuzzy information processing society, june 22-25, ann arbor, michigan, usa, 478–483. cermak, p., chmiel, p. (2004), parameters optimization of fuzzy-neural dynamic model, nafips 2004, banff, canada, 2, 762–767. cermak, p., mura, m. (2012), genetic optimization of fuzzy rule based mas using cognitive analysis, side 2012 and ec 2012. in: leszek rutkowski et. al., eds., springer, lncs 7269, 165–173. cermak, p., pokorny, m. (2001), an improvement of non-linear neuro-fuzzy model properties, in: neural network world, ics av cr, prague, cz, 11(5), 503–523. chernyavska, l., gulli, f. (2008), marginal co2 cost pass-through under imperfect competition in power markets. ecological economics, 68, 408-421. conrad, c., rittler, d., rotfuß, w. (2012), modeling and explaining the dynamics of european union allowance prices at high-frequency. energy economics, 34, january 2012, 316–326. eex. (2014), emission allowances overview. [online]. [cit. 2014-09-20]. www: <http://www.eex.com/en/products/emission-allowances>. european commission. (2013), the eu emissions trading system (eu ets). october 2013, european union. [online]. [cit. 2013-12-05]. www: <http://ec.europa.eu/clima/publications/docs/factsheet_ets_en.pdf>. falbo, p., felletti, d., stefani, s. (2013), free euas and fuel switching. energy economics, 35, 14– 21. garcía-martos, c., rodríguez, j., sánchez, m.j. (2013), modelling and forecasting fossil fuels, co2 and electricity prices and their volatilities. applied energy, 101, 363–375. grainger, c.a., kolstad, c.d. (2010), who pays a price on carbon? environmental and resource economics, 46(3), 359-376. lecuyer, o., quirion, p. (2013), can uncertainty justify overlapping policy instruments to mitigate emissions? ecological economics, 93, 177–191. li, m.w., li, y.p., huang, g.h. (2011), an interval-fuzzy two-stage stochastic programming model for planning carbon dioxide trading under uncertainty. energy, 36(9), 5677-5689. lund, p. (2007), impacts of eu carbon emission trade directive on energy-intensive industries indicative micro-economic analyses. ecological economics, 63, 799-806. lutz, b.j., pigorsch, u., rotfuß, w. (2013), nonlinearity in cap-and-trade systems: the eua price and its fundamentals. energy economics, 40, 222–232. lutz, c., lehr, u., ulrich, p. (2014), economic evaluation of climate protection measures in germany. international journal of energy economics and policy, 4(4), 693-705. the broker simulation model in the emission allowances trading area 95 pawliczek, a., piszczur, r. (2013), effect of management systems iso 9000 and iso 14000 on enterprises’ awareness of sustainability priorities, e+m economics and management, 16(2), 66-79. rentizelas, a.a., tolis, a.i., tatsiopoulos, i.p. (2012), investment planning in electricity production under co2 price uncertainty. international journal of production economics, 140(2), 622-629. rogge, k.s., schneider, m., hoffmann, v.h. (2011), the innovation impact of the eu emission trading system — findings of company case studies in the german power sector. ecological economics, 70, 513-523. wettestad, j., eikeland, p.o., nilsson, m. (2012), eu climate and energy policy: a hesitant supranational turn? global environmental politics, 12(2), 65-84. zimmermannová, j., čermák, p. (2014), possibilities of multiagent simulation model application in the emission allowances trading area. procedia economics and finance, 12, 788-796. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 5 • 2020498 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(5), 498-502. biogas fed-fuel cell based electricity generation: a life cycle assessment approach s. m. shafie1*, z. othman1, n. hami1, s. omar1, a. h. nu'man2, n. n. a. n. yusuf3, a. shah4 1school of technology management and logistics, college of business, university utara malaysia, sintok 06010 kedah, malaysia, 2universitas islam bandung, jalan tamansari no. 20 bandung 40116, west java, indonesia, 3department of energy, minerals and materials technology,universiti malaysia kelantan, 17600 jeli, kelantan, malaysia, 4faculty of technical and vocational, universiti pendidikan sultan idris, 35900 tanjung malim, perak, malaysia. *email: shafini@uum.edu.my received: 21 april 2020 accepted: 13 july 2020 doi: https://doi.org/10.32479/ijeep.9957 abstract the world is currently facing a scarcity of energy resources in the electricity generation sector. the current pattern of electricity generation has brought harm to the environment. fuel cell provides a huge potential in reducing the negative environmental impacts. malaysia as a tropical country has abundant sources of biogas production that can be fed into the fuel to produce electricity and water. the paper aimed to identify the environmental impact towards the consumption of biogas feeding into fuel cells for electricity generation. the result showed that in this modelling of system boundary, the greenhouse gas emissions were high due to large contributions from the transportation and storage processes. hopefully, the outcome from this study could help future researchers or stakeholders in making decisions to design fuel cells for electricity generation with minimum environmental impact contribution. keywords: biogas, fuel cell, electricity generation, life cycle assessment, sustainability jel classifications: c32; o13; o47 1. introduction due to the unsustainability issue of fossil fuel supply, the world is urged to explore new types of energy resources. fuel cell is among the many types of energy resources that is able to fulfil the future need of electricity. fuel cells are more effective than the present use of combustion technologies in power plants. therefore, they might play a significant future part in reducing the reliance on fossil fuel and increasing the electricity generation capacity from biomass supply (wasajja et al., 2020). currently, researchers across the globe are exploring the potential of fuel cells as an energy resource in various perspectives. in 2019, it was reported that almost 30,000 research articles were published in the field of fuel cell (elsevier, 2020). fuel cells use the concept of electrochemical reaction in order to obtain the outputs of electricity and water, while the inputs to the system are gas and oxygen. amid the wide range of fuel cell types, it is found that solid oxide fuel cells (sofcs) offer many benefits; for instance, high functional temperature, ability to utilise numerous fuels as input, and ability to be easily combined with other electric generator devices (mehrpooya et al., 2020). this fuel cell type offers high electrical efficiency up to 60%, minimum emission of carbon dioxide, high temperature resistance, more reliable, and technically available (cozzolino et al., 2017; saadabadi et al., 2019). according to (aziz and hanafiah, 2020; cozzolino et al., 2017), the sofc system has a small value for economic investment due to the huge levelised cost of energy (lcoe) value, is more lenient to pollutants, and has the lowest energy cost. as a tropical country, malaysia has a huge potential of biogas production. a high expectation has been set by the biogas production and processing industry for malaysia to be developed as this journal is licensed under a creative commons attribution 4.0 international license shafie, et al.: biogas fed-fuel cell based electricity generation: a life cycle assessment approach international journal of energy economics and policy | vol 10 • issue 5 • 2020 499 a biogas hub in asia. it is estimated that by 2022, the biogas market will accumulate to rm8.3 billion (usd2.3 billion) (bioeconomy, 2015). utilising biogas from the anaerobic digestion process along with sofcs is assumed to result in a significantly direct and efficient probability to combine sofcs and biomass (only if cell degradation risks are decreased). this system combination is more convenient and less costly, as well as has low temperature gas cleaning (leone et al., 2010). generally, microgas turbines, internal combustion engines, or high temperature fuel cells, such as sofc, are regarded as appropriate for combined heat and power (chp) systems (papurello, 2014). singapore is vigorously progressing towards using fuel cells in the generation of electricity. the ministry of home affairs is reported to have declared in 2015 that the new prison headquarters will be fueled with polymer electrolyte membrane fuel cells (pemfc) (chan et al., 2016) by using food waste as feedstock in generating hydrogen. indonesia is currently applying fuel cell generated power systems with telecom operators, such as hutchison cp telecommunications, telkom international, and xl axiata (cascadiant, 2015). meanwhile in thailand, 10 mw of fuel cell capacity have been initially employed in rayong province by utilising excess hydrogen (“alkaline fuel cell [afc] deals to deploy 300 mw in dubai, 10 mw in thailand,” 2015). currently, malaysia has 83 companies installed with a total capacity of 153.64 mw that are able to produce biogas for electricity generation (seda, 2018). a study by (shafie et al., 2020) estimated that palm oil residues have the ability to generate electricity up to 1474 mw. therefore, it shows that there is great potential to feed biogas into the fuel cell system. figure 1 displays the current location of biogas plants in malaysia. perak has the highest amount of available biogas plants with up to 33 mw. based on this establish technology for biogas production, malaysia is able to create a huge potential in utilising fuel cells for electricity generation since biogas can be fed as input to the system. anaerobic fermentation is a biological process that is able to efficiently extract hydrogen via a sustainable approach, particularly if organic wastes are consumed (leone et al., 2010). it is reported that almost rm40 million have been allotted to academic and research institutions in malaysia for the study and development of fuel cells (sin and najmi, 2013). even though the technology part of fuel cells has been precisely reported in numerous articles, the environmental aspect also needs to be analysed critically. assessing the environmental indicator would benefit policy-makers and stakeholders in choosing the most optimum management approach with the least environmental impact (chàfer et al., 2019). the life cycle assessment (lca) is a proven approach in assessing a structure’s environmental indicator from end to end throughout its lifetime (rillo et al., 2017). currently, the pattern of lca studies on fuel cell electricity generation only focuses on manufacturing rather than the whole cradle-to-grave system (rillo et al., 2017). therefore, this paper aims to estimate the environmental impact of electricity generation based on biogas-fed fuel cells by using the lca method. 2. methodology the current lca study has been conducted in compliance to the iso 14040 and iso 14044 standards. the goal and scope of study were identified, followed by inventory data analysis and assessment of impacts. lca is a cradle-to-grave method that consists of the overall process from raw material mining and chemical fuel production to electrochemical reaction (bicer and khalid, 2020). figure 2 shows the system boundary applied in this study. the aim of this study is to generate 1 kwh of electricity. the processes involved were palm oil plantation, waste treatment, storage, transportation, and solid oxide fuel cells (sofcs). the life cycle inventory analysis (lcia) includes a compilation of the inputs such as energy, raw materials, and input resources, emission output, disposal amounts per unit process, and end-of-life recycling rate, all of which are reflected in the system boundary of lca. the data was obtained from recognised databases such as gabi, related figure 1: current location of biogas plants in malaysia for each state figure 2: system boundary of this study shafie, et al.: biogas fed-fuel cell based electricity generation: a life cycle assessment approach international journal of energy economics and policy | vol 10 • issue 5 • 2020500 industries or literature review. the biogas production process of palm oil plantations was taken from interviews and observation at setia kawan kilang kelapa sawit sdn bhd. meanwhile, the sofc process was adapted from the new energy externalities development for sustainability (needs) project (need, 2020). in this analysis, it was estimated that 1430 kg of fresh fruit bunches were processed to produce 290 kg of crude palm oil (cpo) and 1000 kg of palm oil mill effluent (pome) (aziz and hanafiah, 2020). as for the biogas production, it was calculated that 1000 kg pome could produce 16.63 kg of biogas (aziz and hanafiah, 2020). the transportation process was assumed to use gas trucks with a distance of 50 km to fuel cell power plants. it is reported that the most practical methods in malaysia involve compressing hydrogen in pressure vessels and transporting via trailers and trucks (mah et al., 2019). biogas is capable of being compressed as liquefied biogas (begum and nazri, 2013) for transportation purposes. despite the fact that pipeline transport is a cheaper choice of transportation, the pipeline compressors eventually build up the cost, resulting in it being less feasible in contrast to truck transportation (begum and nazri, 2013). diesel consumption is calculated using equations (5) and (6). sofc is considered to be used in this analysis since this fuel cell type is the most established in the industry (table 1). table 2 indicates the input data to the system. 3. result and discussions the most concerned parameter is global warming. in this study, the life cycle of global warming emission is 564 g co2eq/kwh. figure 3 shows the ghg emission in the function of electricity generation. according to the study from (bicer and khalid, 2020), natural gas-fed sofc has the lowest environmental impact with 0.41 kg co2eq/kwh. this is due to the fact that natural gas is able to be extricated and processed in the power plant. nevertheless, rillo (rillo et al., 2017) discovered that ghg emissions are calculated at 552 kg co2eq/kw. the relationship between ghg emission and electricity generation can be expressed in equation (1). where parameter x is for electricity generation in kwh. even though the graph shows an increasing pattern of ghg emission, it is still lower as compared to the conventional electricity generation system. it is found that coal emits electricity amounting to 1,036 g co2eq/kwh, whereas the global warming potential (gwp) for oil and gas is equivalent to 868 and 646 g co2eq/kwh, respectively (gaete-morales et al., 2019). the most common gwp is found from the combustion of fuel such as lignite, hard coal, and gas, with gwp values of 97%, 83%, and 74%, respectively (atilgan and azapagic, 2015). this is in contrast with fuel cell-based electricity generation, where transportation and storage play the key roles in contributing towards gwp. by adjusting the type of transport, distance, and type of storage, carbon dioxide emissions can be minimised. ghg = −5e-05x2 + 3.0037x + 0.8204 (1) figure 4 displays the percentage of each process that contributes towards the overall ghg emissions in this study. about 48% of emissions came from the transportation process. the cml indicator-based technique provides a comparative environmental impact assessment result by employing a cradle-to-gate assessment. subsequently, this approach exposes environmental effects for ten impact categories: global warming, acidification, eutrophication, ozone depletion, abiotic depletion, freshwater aquatic eco toxicity, human toxicity, marine aquatic toxicity, photo ozone creation, and terrestric eco toxicity. figure 5 shows the lcia results for 1 kwh within the system boundary. about 60% of the impact categories were from the storage process. the second highest contribution was from transportation. reducing the distance of palm oil mills and fuel cell plants should reduce this percentage. it is suggested for the system boundary to be remodeled for minimum output of environmental impacts. table 1: heating value applied in this study heating value pome calorific value references 17,044 kj/kg 53,000 kcal/m3 (begum and nazri, 2013) 21-23 mj/m3 (mohtara et al., 2017) table 2: input data to the system process sources references plantation felcra kubang kenyeng, naka milling setiakawan kilang kelapa sawit sdn bhd treatment glt eco sdn bhd storage literature review (need, 2020) transportation literature review (irena, 2018) fuel cell literature review (need, 2020) y =-5e-05x2+ 3.0037x + 0.8204 r² = 1 0 500 1000 1500 2000 2500 3000 3500 0 200 400 600 800 1000 1200 g h g e m is si on k g c o 2 e q electricity generation, kwh figure 3: ghg emissions in the function of electricity generation 31% 19% 48% 2% palm oil plantation treament storage transportation fuel cell figure 4: process contribution toward ghg emissions shafie, et al.: biogas fed-fuel cell based electricity generation: a life cycle assessment approach international journal of energy economics and policy | vol 10 • issue 5 • 2020 501 although fuel cell application in malaysia is minimal at this point of time, it seems that the capability of this resource due to the huge amount of biogas creates the possibility for its penetration in malaysia. there is no suspicion that the government plays a major role in this issue. the need to increase research and development, investment in human resources, business-friendly policies and implementation beyond the mutual action plan will be the key to recognise the capability of fuel cells in malaysia. 4. conclusion based on this system boundary design, the result revealed that it offers high contribution towards the environmental impact. in the effort to minimise emissions and optimise the energy system, the system boundary design needs to give extra attention to the storage and transportation processes. the lca of ghg emissions in this study are high due to the large contributions from the transportation and storage processes. therefore, it is suggested for fuel cells to be installed inside the location of available biogas so as to reduce ghg emissions. 5. acknowledgements the authors would like to thank the ministry of higher education malaysia for providing financial assistance to this research under the fundamental research grant scheme (frgs-14199/2018). the authors would also like to express their gratitude for the assistance and comments given by the reviewers and associate editor in improving this research manuscript. references alkaline fuel cell. (2015), afc deals to deploy 300 mw in dubai, 10 mw in thailand. focus on catalysts, 2015, 6-7. atilgan, b., azapagic, a. (2015), life cycle environmental impacts of electricity from fossil fuels in turkey. journal of cleaner production, 106, 555-564. aziz, n.i.h., hanafiah, m.m. (2020), life cycle analysis of biogas production from anaerobic digestion of palm oil mill effluent. renewable energy, 145, 847-857. begum, s., nazri, a.h. (2013), energy efficiency of biogas produced from different biomass sources. iop conference series earth and environmental science, 16(1), 2021. bicer, y., khalid, f. (2020), life cycle environmental impact comparison of solid oxide fuel cells fueled by natural gas, hydrogen, ammonia and methanol for combined heat and power generation. international journal of hydrogen energy, 45(5), 3670-3685. bioeconomy. (2015), press release. biogas industry to fuel malaysia’s economic growth. available from: http://www. bioeconomycorporation.my/biogas-industry-to-fuel-malaysiaseconomic-growth. [last accessed on 2020 apr 22]. cascadiant. (2015), cascadiant expands fuel cell r&d with indonesia tech agency. fuel cells bulletin, 2015, 4. chàfer, m., sole-mauri, f., solé, a., boer, d., cabeza, l.f. (2019), life cycle assessment (lca) of a pneumatic municipal waste collection system compared to traditional truck collection. sensitivity study of the influence of the energy source. journal of cleaner production, 231, 1122-1135. chan, s.h., stempien, j.p., ding, o.l., su, p.c., ho, h.k. (2016), fuel cell and hydrogen technologies research, development and demonstration activities in singapore-an update. international journal of hydrogen energy, 41(32), 13869-13878. cozzolino, r., lombardi, l., tribioli, l. (2017), use of biogas from biowaste in a solid oxide fuel cell stack: application to an off-grid power plant. renewable energy, 111, 781-791. elsevier. (2020), journal and book. available from: https://wwwsciencedirect-com.ezaccess.library.uitm.edu.my/search/advanced? qs=fuel%20cell%20study. [last accessed on 2020 apr 22]. gaete-morales, c., gallego-schmid, a., stamford, l., azapagic, a. (2019), life cycle environmental impacts of electricity from fossil fuels in chile over a ten-year period. journal of cleaner production, 232, 1499-1512. irena. (2018), biogas for road vehicles technology brief. abu dhabi: irena. leone, p., lanzini, a., santarelli, m., calì, m., sagnelli, f., boulanger, a., zitella, p. (2010), methane-free biogas for direct feeding of solid oxide fuel cells. journal of power sources, 195(1), 239-248. mah, a.x.y., hoa, w.s., bong, c.p.c., hassim, m.h., liew, p.y., -100% -80% -60% -40% -20% 0% 20% 40% 60% 80% 100% g lo ba l w ar m in g p ot en tia l [ kg c o 2e qu iv .] a ci di fic at io n p ot en tia l [ kg s o 2e qu iv .] e ut ro ph ic at io n p ot en tia l [ kg p ho sp ha te -e qu iv .] o zo ne l ay er d ep le tio n p ot en tia l [ kg r 11 -e qu iv .] a bi ot ic d ep le tio n el em en ts [k g s be qu iv .] fr es hw at er a qu at ic e co to xi ci ty p ot . [ kg d c b -e qu iv .] h um an t ox ic ity p ot en tia l [ kg d c b -e qu iv .] m ar in e a qu at ic e co to xi ci ty p ot . [k g d c b -e qu iv .] p ho to ch em . o zo ne c re at io n p ot en tia l [ kg e th en ee qu iv .] te rr es tri c e co to xi ci ty p ot en tia l [k g d c b -e qu iv .] plantation treament storage transportation fuel cell figure 5: life cycle inventory analysis results for 1 kwh within the system boundary shafie, et al.: biogas fed-fuel cell based electricity generation: a life cycle assessment approach international journal of energy economics and policy | vol 10 • issue 5 • 2020502 teck, g.l.h., chemmangattuvalappil, n.g. (2019), review of hydrogen economy in malaysia and its way forward. internation journal of hydrogen energy, 44(12), 5661-5675. mehrpooya, m., ghorbani, b., abedi, h. (2020), biodiesel production integrated with glycerol steam reforming process, solid oxide fuel cell (sofc) power plant. energy conversion and management, 206, 112467. mohtara, a., hoa, w.s., hashima, h., lima, j.s., muisa, z.a., liewa, p.y. (2017), palm oil mill effluent (pome) biogas off-site utilization malaysia specification and legislation. chemical engineering transactions, 56, 637-642. need. (2020), the needs life cycle inventory database. available from: http://www.needs-project.org/needswebdb/index.php. [last accessed on 2020 jan 20]. papurello, d., borchiellini, r., bareschino, p., chiodo, v., freni, s., lanzini, a., santarelli, m. (2014), performance of a solid oxide fuel cell short-stack with biogas feeding. applied energy, 125, 254-263. rillo, e., gandiglio, m., lanzini, a., bobba, s., santarelli, m., blengini, g. (2017), life cycle assessment (lca) of biogas-fed solid oxide fuel cell (sofc) plant. energy, 126, 585-602. saadabadi, s.a., thattai, a.t., fan, l., lindeboom, r.e.f., spanjers, h., aravind, p.v. (2019), solid oxide fuel cells fuelled with biogas: potential and constraints. renewable energy, 134, 194-214. seda. (2018), biogas plant in malaysia. mampu. available from: http:// www.data.gov.my/data/en_us/dataset/biogas-plant-in-malaysia. [last accessed on 2020 apr 22]. shafie, s.m., othman, z., hami, n., omar, s. (2020), the potential of using biogas feeding for fuel cells in malaysia. international journal of energy economics and policy, 10(1), 109-113. sin, y.t., najmi w.a. (2013), industrial and academic collaboration strategies on hydrogen fuel cell technology development in malaysia. procedia social and behavioral sciences, 90, 879-888. wasajja, h., lindeboom, r.e.f., lier, j.b.v., aravind, p.v. (2020), techno-economic review of biogas cleaning technologies for small scale off-grid solid oxide fuel cell applications. fuel processing technology, 197, 106215. international journal of energy economics and policy vol. 5, no. 1, 2015, pp.148-163 issn: 2146-4553 www.econjournals.com 148 oil-growth nexus in oil producing countries: macro panel evidence* josé alberto fuinhas nece and university of beira interior, management and economics department, estrada do sineiro, 6200-209 covilhã, portugal. email: jafuinhas@gmail.com antónio cardoso marques nece and university of beira interior, management and economics department, estrada do sineiro, 6200-209 covilhã, portugal. email: acardosomarques@gmail.com alcino pinto couto nece and university of beira interior, management and economics department, estrada do sineiro, 6200-209 covilhã, portugal. email: nycouto@gmail.com abstract: the oil consumption-economic growth nexus is examined in a panel of oil producing countries over a long time span (1965-2012). both, the ratio of oil production to primary energy consumption, i.e. oil self-sufficiency, and the persistence of the second structural oil shock were controlled for. the phenomenon of cross-sectional dependence that is present in the panel confirms that these countries share common spatial patterns, unobserved common factors, or both. the cointegration/long memory relationships as well as the panel data estimators’ appropriateness are analysed and discussed. a dynamic driscoll-kraay estimator, with fixed effects, was shown to be adequate to cope with the phenomena of heteroskedasticity, contemporaneous correlation, first order autocorrelation and cross-sectional dependence present in the panel. the results are consistent with the growth hypothesis, i.e. that oil consumption proves be a driver of economic growth. the second structural oil break (1979), reveals the long-lasting positive effect exerted by oil consumption on growth. the ratio of oil production to primary energy consumption has exerted a positive impact on growth. thus, policymakers should take into account the benefits of promoting oil self-sufficiency, by reinforcing the use of endogenous resources. keywords: oil production; macro panels; oil-growth nexus; oil self-sufficiency jel classifications: c33; o50; q43 1. introduction oil has played and will continue to play a central role in the development of energy systems. national energy systems and the global energy order are under pressure and facing transitional challenges. the pressures stemming from technological innovations, evolution of the energy demand and energy-related challenges policies are exerting a profound influence on the mix of national energy systems. the dynamics of global oil trade flows reflects structural changes in the geography of oil supply and demand. major importers are becoming exporters. in turn, economies known as the most important energy exporters are becoming leading drivers of growth in global demand (iea, 2013). within this scenario, literature on oil production and oil and energy consumption, as well as the attention of analysts and policy makers has become increasingly interested in the nature of their links * research supported by: nece, r&d unit funded by the fct – portuguese foundation for the development of science and technology, ministry of education and science oil-growth nexus in oil producing countries: macro panel evidence 149 with economic performance, in particular with economic growth. the largest body of research has been framed in the context of energy-growth nexus literature (e.g. ozturk, 2010). the increasing focus on oil producing economies could be explained by the potential insights they provide for a better understanding of: (i) the economic growth drivers, controlling for the peculiarities and specificities of of the links between oil production, oil consumption and primary energy consumption among countries; (ii) the nature of the nexus, namely whether or not it could be conditioned by the exploitation of energy resources; and (iii) the complexities and idiosyncrasies of oil production on economic growth. the research findings are inconclusive regarding the existence and the direction of energy-growth nexus causality (e.g. apergis and payne, 2009; naser, 2014; and yıldırım et al., 2014). furthermore, one could attribute, at least in part, the lack of conclusive research outcomes to three facts. first, the literature on oil production is focused mostly on exporting countries. thus, the studies concentrate on the effects of surplus oil production on oil consumption, neglecting the role of oil production itself in economic growth. indeed, there are numerous countries that are oil producers but not oil exporters. second, the literature has neglected the study of the impact of oil production on paths of economic growth for different levels of oil production. lastly, the studies fail to detect the effects of interaction between energy production and energy consumption. to overcome such shortcomings and capture the heterogeneity of the oil producing countries, the ratio of oil production to the energy consumption is used, measuring oil production units per unit of energy consumed. this indicator expresses the relevance of the interaction between oil production and total primary energy consumption in different countries. it also represents the differences regarding energy policy priorities between oil-rich and non-oil-rich countries, namely the importance given to energy self-sufficiency. moreover, the indicator enables the analysis of oil producing countries, both exporting and non-exporting, and captures their dynamics over time. the aim of this work is to improve the understanding of the energy-economic growth nexus, using the ratio of oil production to energy consumption. to pursue this aim, a multivariate panel approach is applied and empirically supported by: (i) a set of oil producing countries for which data on oil production and primary energy consumption is available over a long time span (1965 to 2012); (ii) control of the ratio of oil production to primary energy consumption; and (iii) control of the aftermath of the second oil shock of 1979. the econometric techniques used: (a) enable the assessment of short and long-run effects, shedding light on the dynamics of the relationship; (b) overcome the delicate problem of the order of integration of variables by using an econometric specification that can work upon variables that are i(0) and/or i(1) or fractionally integrated; and (c) can operate on more extensive relationships ranging from cointegration to long-memory (fractional cointegration). the study is set out as follows. the next section provides a review of the literature on the energygrowth nexus, particularly highlighting the context of oil producing countries. section three presents both data and methodology. in this section, a preliminary analysis of data is also provided. section four discloses the results. section five centres on the discussion of the main results. section six presents the conclusions. 2. literature review the study of the energy consumption and economic growth nexus has been a longstanding theme, both in the energy economics literature and in the energy policy debate. despite the large number of studies, involving different authors, countries, time periods, and econometric methodologies, the complex nature of the causality relationship deserves further research. currently, there is no clear support regarding the direction, or even the existence of a causality in the energy-growth nexus (e.g. yıldırım et al., 2014; ozturk, 2010; and apergis and payne, 2009). according to the energy-growth nexus literature, four testable hypotheses are postulated: conservation, growth, feedback and neutrality hypotheses (e.g. ozturk, 2010; yuan et al., 2010; apergis and payne, 2009; zhang and cheng, 2009; wolde-rufael, 2009; and narayan and smith, 2008). the neutrality hypothesis maintains that the variables are independent from one another and the cost of the energy is a small proportion of the gross domestic product (gdp). in this case, the economy is anchored to less energy intensive activities and energy policy has no significant implications for economic growth and vice-versa. this is unlike the other hypotheses in which the existence and direction of causality pose crucial energy policy implications. both the conservation and growth hypotheses imply a unidirectional causality. the conservation hypothesis implies causality international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.148-163 150 from economic growth to energy consumption. this assumption considers that economic growth stimulates energy consumption, assuming, as in the neutrality hypothesis, that energy conservation or reduction policies do not inhibit economic growth. the growth hypothesis considers energy consumption as an input production factor, and claims that energy use is a driver of economic growth. in this framework, the economy is energy dependent and efficiency-oriented, energy restrictive policies, such as regulation and fiscal measures, will harm economic growth. lastly, the feedback hypothesis advocates a bi-directional causality between economic growth and energy consumption. the two variables are interrelated, working complementarily to each other. consequently, efficiencyoriented energy policies should take into account their adverse effects on economic growth. the unclear picture revealed by the research on the topic is explained, to a large extent, by the sensitivity of findings to specific features of the country and research. the results seems to depend mainly on: (i) whether the study involves just one single country or a set of countries (fuinhas and marques, 2013); (ii) the econometric methodologies used (alam et al., 2012; and mehrara, 2007); (iii) the time span considered (chen et al., 2012); (iv) the variables studied (ozturk, 2010); (v) the heterogeneity of the countries’ climate conditions (belke et al., 2011); (vi) the different energy consumption standards (mahadevan and asafu-adjaye, 2007); and (vii) the countries’ structural and development level (ozturk et al., 2010; apergis and payne, 2010, 2009; and mahadevan and asafuadjaye, 2007). in an attempt to shed light on the complexity of the energy-growth nexus, the analysts have increasingly been focusing on dissecting the long-run effect and short-run dynamics between energy consumption and economic growth, particularly within oil producing countries. different reasons could be given to explain this interest: (i) the great value of oil as a scarce and strategic commodity, as well as its uneven distribution around the world (e.g. iea, 2013; and luft and korin, 2009); (ii) the economic, political and social effects of oil earnings and energy prices (e.g. narayan et al., 2014; darbouche, 2013; and ecb, 2010); (iii) its role as an instrument of public policy pursuing multiple objectives (e.g. mohammadi and parvaresh, 2014; and fattouh and el-katiri, 2013); (iv) the set of oil producing countries consisting of small and large producers by international standards, oil net importers and net exporters, developed and developing countries (e.g. iea, 2013; ozturk, et al., 2010, klein, 2010; and luft and korin, 2009); (v) various national energy systems face different transitional problems, in particular net exporters experience rapidly increasing energy demand and growing political, economic and environmental challenges (e.g. mohammadi and parvaresh, 2014; gately et al., 2013; al jaber, 2013; fattouh and el-katiri, 2013; el-katiri, 2013; and al-mulali, 2011); and (vi) different economies have different levels of oil endowments and oil self-sufficiency and dependency, but share relevant market and price interdependencies (e.g. iea, 2013; ecb, 2010; and luft and korin, 2009). such reasons are associated with a wide range of energy developments that express either shortrun or long-run implications. for example, changes in international energy prices could express a short-run phenomenon (e.g. the persian gulf war, 1990-1991) or a long-run change in the terms of trade driven by structurally rising demand (ecb, 2010). thus, the energy-growth nexus analysis requires sufficiently long time spans to properly examine the causality relationships by understanding the effects of both short and long-run movements on energy systems. the more recent generation of econometric approaches, such as multivariate cointegration and error correction panel models, are required to test structural changes and breaks in the pattern of energy consumption, owing to changes in energy prices, political, economic and technological environments and energy policies, among others, and their implications on the energy-growth nexus (e.g. fuinhas and marques, 2013; and mehrara, 2007). moreover, the literature recognizes that the energy transition systems of oil producing countries face a common and critical challenge to economic growth: the balance between oil production, domestic energy consumption and a sustainable external position regarding oil (e.g. mohammadi and parvaresh, 2014; yousef, 2013; mehrara, 2008; and kraft and kraft, 1978). this balance poses some questions. to what extent could this common challenge reinforce the role of common shocks? could we expect some degree of convergence between national energy systems and policies? if so, could one expect clearer and more conclusive findings regarding the energy consumption-growth causality nexus? oil-growth nexus in oil producing countries: macro panel evidence 151 the earliest attempt to answer to some of these questions is found in the work of kraft and kraft (1978) on the us economy: a developed economy and both a relevant oil producer and net energy importer. the authors examined the energy consumption-growth nexus and identified a growth-energy causality relationship. they considered that conservation policies were critical in order to face energyrelated challenges. since then, a large body of literature has been produced predominantly focused on energy dependent economies (e.g. ozturk, 2010; apergis and payne, 2009). more recently, increasing attention has being placed on energy supplier economies, in particular oil producers (e.g. mohammadi and parvaresh, 2014; gately et al., 2013; al jaber, 2013; fattouh and el-katiri, 2013; and sgouridis et al., 2013). with respect to oil producing countries, the findings of recent cross-country studies point to a mixed picture. mohammadi and parvaresh (2014), in a study based on a sample of 14 oil-exporting countries and a mean group estimator with common correlated effects, identify a stable relation between energy consumption and output, as well as a bi-directional causality in both the longand short-run. by examining sub-saharan african oil importing and oil exporting countries between 1985 and 2011, behmiri and manso (2013) show a bi-directional relationship between oil consumption and gdp for oil importers in both the longand short-run. however, oil exporters present bi-directional causality in the long-run and a granger causality from oil consumption to gdp in the short-run. covering the period from 1973 to 2008, farhani and rejeb (2012) examine mena countries. their findings suggest that short-run interactions show neutrality relationships between energy consumption and gdp and long-run dynamics are characterised by the conservation hypothesis, implying a causality from economic growth to energy consumption. this mixed picture is supported by the crosscountry studies of bildirici and kayıkçı (2013), hossein et al. (2012) and al-mulali (2011). the findings provided by country case studies reinforce this unclear trend. although they support the existence of causality, its direction in the energy-growth nexus is inconclusive (e.g. lim et al., 2014; park and yoo, 2014; dantama et al., 2012; lotfalipour et al., 2010; pao and tsai, 2011; and belloumi, 2009). overall, the results do not offer a better understanding of how the energy-growth nexus is affected in presence of energy resources. in our view, the current approaches are not specifically tailored to energy producing countries. as far as we are aware, they currently fail to capture the interaction effects between energy production and energy consumption. in other words, one expects that the nature of the nexus would be affected by the fact that a country is, or is not an oil producer, even if the oil production level is too small to export. as a consequence, a workable and theoretically consistent approach is to use the concept of self-sufficiency. roughly understood, the concept establishes a relationship between energy production and energy consumption. in the case of oil producing countries, the forces that shape the degree of self-sufficiency are multidimensional and work differently between them. for example, the priority given to the maximization of energy-selfsufficiency and the conditions to achieve it, tend to be associated both with the level of the country’s oil endowment, and with the relationship between the full capacity of its oil sector and domestic demand for oil. in turn, the analysis of self-sufficiency embraces the role of supply and demand mechanisms and their interactions. from the supply side, its movements express the presence of supply shocks, its propagation, and changes in technology and the energy mix. from the demand side, the concept captures changes in energy prices stimulated by external or domestic demand, sectorial structural changes, as well as changes in energy intensity. accordingly, the use of a measurement that integrates oil production and energy consumption to examine the causality hypotheses between energy and economic growth, could shed some light on the complexities of the nexus. 3. data and methodology the traditional analysis of the energy-growth nexus could be extended and approached either from the demand side or from the supply side. the analysis focused on supply usually includes variables such as labour, capital stock, energy consumption, and gross domestic production (gdp). the demand approach is generally based on energy consumption, energy prices, gdp, and occasionally includes other variables such as exports, co2 per capita or urbanization (e.g. mohammadi and parvaresh, 2014). the demand side approach is well suited to cope with the nexus of oil exporting countries (e.g. damette and seghir, 2013). international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.148-163 152 the ultimate purpose of this research is to examine the effect of the level of oil self-sufficiency on the oil-growth nexus of a group of countries that are oil producers. accordingly, the nexus is assessed controlling for the ratio of oil production to primary energy consumption. annual frequency data for the period 1965-2012 is used, and the econometric analysis was performed using eviews 8 and stata 13.1 software. notwithstanding the large number of oil producers countries around the world, the countries under analysis are those that were oil producers during the period under analysis, and for which data is available, for the entire period namely on primary energy consumption, oil consumption, oil production, and exports of goods and services. therefore, our analysis focuses upon a balanced panel of fifteen countries, specifically: australia, algeria, brazil, canada, colombia, ecuador, egypt, india, indonesia, italy, mexico, peru, united kingdom, united states, and venezuela. three potential candidates were excluded: trinidad and tobago that had no data for exports in 2012, and malaysia and norway that only began to produce oil in 1968 and 1971, respectively. two sources of raw annual data were used: the world bank data (for gross domestic product (gdp) exports of goods and services, and population), and the bp statistical review of world energy, june 2013 (for oil consumption, oil production, primary energy consumption, and crude oil prices). the raw data variables used are: (i) gdp (constant local currency unit); (ii) exports of goods and services (% of gdp); (iii) population (total number of persons); (iv) oil consumption (million tonnes); (v) oil production (million tonnes); (vi) primary energy consumption (million tonnes oil equivalent); and (vii) crude oil prices (us dollars per barrel, 2012). with the option of using constant local currency unit, the influence of exchange rates is avoided. these raw variables were transformed and used in the study as follows:  gross domestic product per capita (ypc) – the ypc is obtained by dividing the gdp by the total population;  exports of goods and services per capita (xpc) – the xpc is computed in three steps. the first step consists of dividing exports of goods and services, as a percentage, by 100. in the second step, the former result is multiplied by the gdp in order to obtain its absolute value. finally, the absolute value is then divided by total population to obtain per capita values;  oil consumption per capita (ocpc) – the ocpc is obtained by dividing oil consumption by total population;  ratio of oil production to primary energy consumption (se) – the se is obtained by dividing oil production by primary energy consumption. this ratio captures the evolution of the balance of oil production to primary energy consumption. it is used to control for the heterogeneity of oil producers both through time and as net oil producers;  crude oil prices (p) the p is the “international” price. this variable is unique, and therefore is the same for all countries. it is expected that these variables will contain dynamic effects. indeed, for the group of oil producing countries it is different behaviours are expected in the short and long-run. actually, there are two principle motives that suggest this dynamics. first, the period under study is long which increases the relevance of time. second, for oil exporting countries, the presence of long-run relationships are expected, as they tend to exhibit fairly constant oil income/ gdp ratios over time (e.g. esfahani et al., 2014, 2013). the expected presence of dynamic effects strongly supports the argument that the analysis should be conducted by econometric techniques that analyse both short and long-run adjustments. to permit the breakdown of the total effect of dynamic interactions into short and long-run components, use is made of the equivalent conditional unrestricted error correction model (uecm) form of an autoregressive distributed lag (ardl) model. the uecm form of the ardl model is robust, independently of variables being i(0), i(1), or fractionally integrated, and deals well with both cointegration and long memory behaviours. in addition, it has attractive properties, namely those of consistent and efficient parameter estimates, and inference of parameters grounded on standard tests. furthermore, it has the flexibility to explore the possible functional forms of the nexus, as the literature on the subject has amply shown. given that the specification of the uecm form of an ardl model includes variables that are in natural logarithms, first differences of logarithms, and a ratio, their coefficients are elasticities, semi-elasticities, and impacts, respectively. thereafter, the prefixes “l” and “d” denote natural logarithm and first differences of variables, respectively. the ardl model specification, eq. (1), is: oil-growth nexus in oil producing countries: macro panel evidence 153      b j jitij a j jitijtiiit locpclypctrendlypc 0 12 1 1111   it e j jitij d j jitij c j jitij lplxpcse 1 0 15 0 14 0 13        (1) eq. (1) can be re-parameterized into the general uecm form, eq. (2), in order to decompose the dynamic relationship of variables in the short and long-run, as follows:     b j jit a j jit tiiit dlocpijdlypcijtrenddlypc 01 22 2221       e j jit d j jit c j jit dlpijdlxpcijdseij 000 252423   .2125124123122121 ititiitiitiitiiti lplxpcselocpclypc   (2) where α2i denotes the intercept, δ2i, β2kij, k=1,…,5, and γ2im, m=1,…,5, the estimated parameters; and ϵ2i the error term. the preliminary empirical assessment of the model of eq. (2) reveals that exports of goods and services per capita, and crude oil prices are not statistically significant and were excluded from modelling. these results are far from unexpected given that some countries included in the panel are huge oil exporters and, consequently, their exports incorporate the effect of oil price. similarly, when exports are considered, oil prices are shown to be statistically insignificant. this empirical result corroborates the redundancy of including variables of exports and oil prices concurrently. furthermore, only contemporaneous effects are detected for the semi-elasticities. thereafter, the previous model is replaced by the more parsimonious model of eq. (3), as follows: 313313213132313  ititiitiitiitiitiiit selocpclypcdsedlocpcdlypc   (3) when working upon macro panels, the presence of cross-sectional dependence (csd) is a common occurrence. once found, this points to the presence of common unobserved factors that influence the evolution of countries’ variables over their own time paths. furthermore, the idiosyncrasies of the countries can result in the existence of fixed effects. indeed, it is expected that countries that are oil producers share specificities that require special attention to be taken in the choice of estimators, bearing in mind that they should be able to cope well with misspecifications, biased results, and inefficiencies in the estimates. to capture the features of both series and crosssections (countries), the analysis of the descriptive statistics, the csd, and the order of integration of the variables should be performed. table 1 reveals both the descriptive statistics of the variables and their cross-sectional dependence, which is assessed by the cd test. table 1. descriptive statistics and csd descriptive statistics cross-section dependence variables obs mean std.dev. min. max. cd-test corr abs (corr) lypc 720 10.1343 2.3741 6.9501 16.1769 47.93*** 0.675 0.807 locpc 720 -14.3563 1.1478 -17.4890 -12.4197 12.47*** 0.176 0.481 se 720 1.3086 2.1579 0.0004 16.5079 -1.94* -0.027 0.432 dlypc 705 0.0199 0.0347 -0.1553 0.2153 8.74*** 0.124 0.192 dlocpc 705 0.0140 0.0593 -0.3281 0.2455 9.04*** 0.129 0.187 dse 705 -0.0327 0.3945 -4.4162 4.5644 1.16 0.017 0.162 notes: cd test has n(0,1) distribution, under the h0: cross-section independence. ***, * denote significant at 1% and 10% level, respectively. the stata command xtcd was used to achieve the results for csd. the descriptive statistics clearly indicate that the panel of countries is very diverse. indeed, the ratio of oil production to primary energy consumption, economic growth and oil consumption growth have huge disparities. the cd test strongly suggests that countries share common developments for all variables except for the ratio of oil production to primary energy consumption, either as a ratio or first differences of the ratio. the presence of csd indicates an interdependence among the cross-sections that results from countries sharing common shocks (e.g. eberhardt, 2011). two types of dependence international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.148-163 154 between cross-sections can be recognised in the literature. the first, is spatial and takes into account the distance between cross-sections (anselin, 2001). the second, which is called long-range or global interdependence (moscone and tosetti, 2010), occurs when the cross-sections react in the same manner to external shocks. irrespective of the geographical distance between countries, if they react in a very similar manner to the same events, then this provokes correlation between them. the absence of csd for the se (statistically significant only at 10%) and dse, suggest that countries react independently with regard to oil production and energy consumption. figure 1 shows the se charts by cross sections. as shown by figure 1, the se series are far from stable over time for the most of countries, reinforcing the necessity to study how this impacts on economic growth in different periods. figure 1. ratio of oil production to primary energy consumption .0 .1 .2 .3 .4 .5 65 70 75 80 85 90 95 00 05 10 aus .0 .1 .2 .3 .4 .5 65 70 75 80 85 90 95 00 05 10 bra .32 .36 .40 .44 .48 .52 .56 65 70 75 80 85 90 95 00 05 10 can 0.4 0.8 1.2 1.6 2.0 65 70 75 80 85 90 95 00 05 10 col 0 4 8 12 16 20 65 70 75 80 85 90 95 00 05 10 dza 0 2 4 6 8 65 70 75 80 85 90 95 00 05 10 ecu 0.0 0.5 1.0 1.5 2.0 2.5 65 70 75 80 85 90 95 00 05 10 egy .0 .2 .4 .6 .8 65 70 75 80 85 90 95 00 05 10 gbr .04 .08 .12 .16 .20 .24 65 70 75 80 85 90 95 00 05 10 ind 0 2 4 6 8 65 70 75 80 85 90 95 00 05 10 idn .00 .01 .02 .03 .04 65 70 75 80 85 90 95 00 05 10 ita 0.6 0.8 1.0 1.2 1.4 1.6 1.8 65 70 75 80 85 90 95 00 05 10 mex 0.2 0.4 0.6 0.8 1.0 1.2 1.4 65 70 75 80 85 90 95 00 05 10 per .10 .15 .20 .25 .30 .35 65 70 75 80 85 90 95 00 05 10 usa 0 2 4 6 8 10 12 65 70 75 80 85 90 95 00 05 10 ven oil-growth nexus in oil producing countries: macro panel evidence 155 the correlation coefficients between variables, and the variance inflation factor (vif) were computed to check for multicollinearity. the very low values of correlations and vif statistics strongly support the absence of multicollinearity (see table 2). table 2. matrices of correlations and vif statistics lypc locpc se dlypc dlocpc dse lypc 1.0000 dlypc 1.0000 locpc -0.0618 1.0000 dlocpc 0.1340 1.0000 se -0.1267 0.4113 1.0000 dse 0.1913 0.4271 1.0000 vif 1.06 1.06 1.03 1.03 mean vif 1.06 1.03 to assess the order of integration of the variables, both first and second generation panel unit root tests were applied. the first generation panel unit roots tests of llc (levin, lin and chu, 2002), adf-fisher (maddala and wu, 1999) and adf-choi (choi, 2001), and the second generation unit roots test cips (pesaran, 2007) were provided. the cips test has the desired property of being robust to heterogeneity and tests the null of non-stationarity under a nonstandard distribution. the results of unit root tests are shown in table 3. table 3. unit root tests 1st generation 2nd generation llc adf-fisher adf-choi cips (zt-bar) individual intercept and trend no trend with trend lypc -0.0810 22.1250 1.1354 1.326 1.374 locpc -0.8452 32.1307 -0.2136 -3.571*** -1.614* se -0.4976 29.3768 0.7119 1.158 0.180 dlypc -11.6123*** 169.615*** -9.8432*** -8.243*** -8.189*** dlocpc -8.5762*** 144.002*** -8.5307*** -9.095*** -7.800*** dse -8.3198*** 134.634*** -8.3829*** -6.886*** -5.968*** notes: ***, **, * denote significant at 1%, 5% and 10% level, respectively; the null hypotheses are as follows. llc: unit root (common unit root process); this unit root test controls for individual effects, individual linear trends, it has a lag length 1, and newey-west automatic bandwidth selection and bartlett kernel; adf-fisher and adf-choi: unit root (individual unit root process); this unit root test controls for individual effects, individual linear trends, it has a lag length 1; first generation tests follow the option “individual intercept and trend”, which was decided after a visual inspection of the series; pesaran (2007) panel unit root test (cips): series are i(1); the eviews was used to compute llc, adf-fisher, and adf-choi; and the stata command multipurt was used to compute cips. the llc and the adf tests are consensual in attributing levels to i(1) variables. the cips test is much more inconclusive in regard to the locpc variable. nevertheless, the cips test for locpc variable with three lags and no constant (not shown) is statistically significant only at 10% level. with trend and two lags it is not statistically significant. the variable se with trend and two or more lags is statistically significant, suggesting that the inclusion of a trend could be necessary in the models. the preliminary analysis of the data points to the second oil shock having a permanent effect on the elasticity oil-growth. to assess this long-lasting effect, a shift dummy is used, with “zeros” prior to the year 1979 and “ones” from 1979 onwards, which was multiplied by the natural logarithm of oil consumption per capita. this former shift dummy variable is nominated sd79lcpc in the estimations, and captures the change in elasticity in the period after the second oil shock. to include this shift dummy, the last eq. (3) was expanded, resulting in the following eq. (4), which is hereafter the standard specification for models.  dsedlocpcdlypc itiitiiit  42414 .79 4144143142141  ititiitiitiiti locpcsdselocpclypc   (4) when working upon several countries, the availability of data over long periods allows a large number of observations, permitting the use of estimation methodologies of both macro panels and time series. the possibility of a panel having heterogeneous slopes must be appraised, as well as, testing for the adequacy of using panel data techniques. the decision to use a panel methodology or to use international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.148-163 156 procedures that permit the accommodation of great diversity is conditional on the units’ degree of heterogeneity. countries that are oil producers could share common events, which underline the adequacy of studying the countries jointly, by using a panel data approach. in addition, the panel data approach allows for the control of cross-sectional heterogeneity, which is expected to be present when several entities are analyzed (e.g. klevmarken, 1989; and hsiao, 2003). furthermore, it provides more information, variability, degrees of freedom and efficiency and, thus, less collinearity than is generally present in time series approaches. the greater ability of panels to detect and measure phenomena, and the possibility of building more complex models than traditional econometric methodologies, is of particular relevance in empirical analysis. moreover, the macro panel data structure, with a long time span, has the advantage of allowing for panel unit root tests that have a standard asymptotic distribution (baltagi, 2008). this former characteristic is of particular interest when checking cointegration. in the panel approach, the presence of individual effects ought to be tested against random effects. for the random effects (re) model, in eq. (4), the error term assumes the form  itiit  , where denotes the n-1 country specific effects and are the independent and identically distributed error. accordingly, eq. (4) is transformed in eq. (5):  dsedlocpcdlypc itiitiiit  52515 .79 154153152151  itiitiitiitiiti locpcsdselocpclypc   (5) if the random model proves to be more appropriate than the fixed ones, then further testing, comparing the random effects with the pooled ols regression should be pursued and determined. accordingly, fe were tested against re, by using a hausman test, in which the null hypothesis is that the preferred model is that of random effects. hausman’s statistic 59.2627  proves be highly significant by supporting the rejection of h0, i.e., fe was chosen as the preferred model. the evidence of correlation between the individual effects of countries and the explanatory variables, i.e., fe, supports the idea that the individual effects of countries are statistically significant and must be included in the panel estimations. moreover, fe models are particularly suitable for analysing the impact of variables that vary over time, because the fe estimator removes all time-invariant features from the independent variables. this later feature allows for the appraisal of the net effect of explanatory variables. the long time span and the number of cross sections under analysis makes it advisable to test the panel heterogeneity parameter slopes. indeed, this could also be present in the macro panels. the heterogeneity of parameter slopes could be of two types: (i) present in short and long-run; and (ii) circumscribed to short-run. to cope with this, the mean group (mg) or pooled mean group (pmg) estimators can be applied. the mg is the most flexible model. it runs the regressions for each individual and then it calculates an average coefficient of all individuals. its estimates of the long-run average coefficients are consistent, but inefficient when there is slope homogeneity (pesaran et al., 1999). this technique is not adequate for small samples of countries, since an outlier can significantly change the coefficient averages (ciarlone, 2011). pmg also allows for greater flexibility than the traditional models when studying a panel, but is less flexible than mg. it performs restrictions among cross sections in the long-run parameters, by pooling them, but not in the short-run parameters, or in the adjustment speed. thus, the short-run dynamics are allowed to be heterogeneous, while the longrun ones must be homogeneous. it can be based on an uecm form of the ardl approach, allowing the correction of serial correlation among residuals and the problem of endogenous regressors, as long as an optimal number of lags is chosen. it is an intermediate method in which the short-run coefficients and the error variances can be different among countries, while implying homogeneity in the long-run. if long-run homogeneity is verified, pmg estimators are more consistent and efficient than mg. these estimators require a large number of both cross sections (n) and time observations (t) (blackburne iii and frank, 2007). one way to appraise the appropriateness of using mg or pmg estimators is to test them against the dynamic fe estimator. the dynamic fe model is the least flexible. in fact, contrary to the previous models, it imposes homogeneity for all coefficients and only allows for the intercepts to be different among cross sections. the homogeneity is valid if the parameters have a common convergence. the decision to use one of these models instead of another is oil-growth nexus in oil producing countries: macro panel evidence 157 made by computing a hausman test, which tests the null hypothesis that the difference in coefficients is not systematic. 4. results the preliminary outcomes support the use of techniques that are robust for csd and that address the dynamics of short and long-runs. the results of the order of integration of the variable locpc do not exclude the possibility that the variable is borderline i(0)/i(1), which compromises the testing of the cointegration between variables by the traditional tests. the most common test of cointegration between variables was carried out, although it is not clear if the order of integration of variables is i[1]. the first generation pedroni test (1999, 2004) is commonly used to test cointegration. this test runs under the null of no-cointegration. however, this test considers both heterogeneity and independence among cross sections (e.g. pedroni, 1999). the detection of csd implies that the pedroni test is not appropriate to test cointegration. indeed, if not controlled for the presence of csd, it could provoke both imprecise estimates and severe identification problems (e.g. eberhardt and presbitero, 2013). thus, as an alternative, the first generation cointegration test of kao (1999) was computed. this test states the no-cointegration as a null hypothesis and is specified on the assumption of coefficients’ homogeneity. the kao test definitely does not reject the null (t=1.2403). to double-check the results, the second generation cointegration test of westerlund (2007) was calculated. this test deals with dynamic structures instead of residuals. it performs under the null hypothesis of no-cointegration and it is built on four statistical tests that are consistent and have normal distribution. pt and pa statistics test the cointegration of the model as a whole, and gt and ga statistics test the hypothesis of at least one cross section having all the variables cointegrated. these tests check whether the error correction term, in a conditional model, is zero and they are able to incorporate short-run dynamics for each country, as well as serial correlated error terms, non-strictly exogenous regressors, interceptions, tendencies and slope parameters for each country (ciarlone, 2011). these specificities are therefore flexible and suitable for work upon a heterogeneous specification. considering that these series exhibit csd, only the westerlund (2007) cointegration test results were shown (see table 4). the bootstrap method provides proper coefficients, standard errors and confidence intervals, and discloses robust critical p-values. as is well known, good econometric practice recommends resampling to be performed at least 100 times to achieve robust results. for more accuracy, 800 repetitions were used. as shown in table 4, the presence of cointegration is clearly rejected, both in considering the panel as a whole, and in considering each country individually. table 4. westerlund (2007) cointegration tests statistic value z-value p-value p-value robust gt -0.374 5.049 1.000 0.998 ga -0.776 4.362 1.000 1.000 pt -1.844 2.485 0.994 0.955 pa -0.701 2.189 0.986 0.974 notes: bootstrapping regression with 800 reps; h0: no cointegration; gt and ga test the cointegration for each country individually, and pt and pa test the cointegration of the panel as whole; and the stata command xtwest was used. to ascertain the presence of heterogeneity and despite the moderate number of cross sections under analysis, the mg estimator was applied and their results carefully analyzed. the cross-sectional estimations, in general, show few statistically significant parameters. overall, these poor results require an assessment of the eventual gains of efficiency by using pmg or dynamic fe. in accordance, the mg and pmg estimators were tested against the dynamic fe. table 5 presents the estimations for each of these three models, as well as, the hausman tests. the results lead to the rejection of the most flexible models, presenting fe as the most suitable estimator. the prevalence of a homogeneous panel indicates oil producers sharing common coefficients, and it can be suitable to treat them as a group as these results could be interpreted as evidence that producing countries shared similar behaviours to the extent that these variables are considered. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.148-163 158 table 5. heterogeneous estimators and hausman tests models mg (i) pmg (ii) fe (iii) constant 2.3069*** 0.1670 0.5269*** trend 0.0033*** 0.0007*** 0.0009*** dlocpc 0.2834*** 0.2797*** 0.2478*** dse 0.0140 0.0377 0.0237*** ecm -0.1640*** -0.0082 -0.0294*** locpc 0.1913 1.0482*** 0.5425*** se -0.1043 -0.1135 0.0994*** sd79locpc 0.0009 -0.0277*** 0.0329** models mg vs pmg pmg vs fe mg vs fe hausman tests chi2(8) = 37.79 *** chi2(8) = 10.62 chi2(8) = 5.34 notes: ***, ** denote significant at 1% and 5%, respectively; hausman results for h0: difference in coefficients not systematic; ecm denotes error correction mechanism; the long-run parameters are computed elasticities; the stata command xtpmg was used. given that the hausman tests points to panel homogeneity, a battery of specification tests were performed, namely on heteroskedasticity, contemporaneous correlation among cross sections, noncorrelation of variances across individuals, and autocorrelation. checking for eventual violations in these assumptions was crucial given the sensibility of traditional panel estimators to their presence. first, the group heteroskedasticity of the fixed effects was performed using the modified wald test. this test, which has a χ2 distribution, tests the null of homoskedascity, i.e., σi2=σ2 for i=1,..,n, with σ2 being the variance of country i. second, the pesaran test of cross-section independence was computed to assess the presence of contemporaneous correlation among cross sections. the null hypothesis of this test states that the residuals are not correlated and it follows a normal distribution. in order to verify whether the variances across individuals are not correlated, the breusch-pagan langragian multiplier test of independence was performed. this test follows a χ2 distribution. finally, to check the existence of serial correlation, the wooldridge test for autocorrelation was performed. the null hypothesis of this test is no serial correlation and follows an f distribution. the results shown in table 6 support the rejection of the null hypothesis of the modified wald test, pointing to the presence of heteroskedasticity. the pesaran test points to the existence of contemporaneous correlation. the breusch-pagan lm test does not reject the hypothesis that the residuals are correlated. finally, the wooldridge test supports that the data has first order autocorrelation. table 6. specification tests statistics statistics modified wald test 528.26*** breusch-pagan lm test 192.613*** pesaran test 4.460*** wooldridge test 301.835*** note: *** denote significant at 1%; results for h0 of modified wald test: sigma(i)^2 = sigma^2 for all i; results for h0 of pesaran and breusch-pagan lm tests: residuals are not correlated; results for h0 of wooldridge test: no first-order autocorrelation. given that heteroskedasticity, contemporaneous correlation, first order autocorrelation, csd and a large time span are present, the driscoll and kraay (1998) estimator (e.g. hoechle, 2007) was used (table 7). this estimator is a matrix estimator that produces standard errors that are robust to several phenomena, namely the ones found in the sample errors. additionally, as a benchmark, the fe estimator and the fe estimator with robust standard errors (table 7) were applied, so that heteroskedasticity, which was previously verified, was controlled for. table 8 displays the shortand long-run elasticities/impacts for the models fe (iv), fe robust (v), and fe d.-k. (vi). it ought to be noted that the long-run elasticities/impacts were not directly made available by the estimates of models (table 7), and therefore they must be computed. these elasticities/impacts were achieved by dividing the coefficient of the variables by the coefficient of lypc, both lagged once and multiplying the ratio by -1. oil-growth nexus in oil producing countries: macro panel evidence 159 table 7. estimation results models fe (iv) fe robust (v) fe d.-k. (vi) constant 0.5269*** 0.5269*** 0.5269*** trend 0.0009*** 0.0009*** 0.0009*** dlocpc 0.2478*** 0.2478*** 0.2478*** dse 0.0237*** 0.0237*** 0.0237*** lypc(-1) -0.0294*** -0.0294*** -0.0294*** locpc(-1) 0.0160*** 0.0160* 0.0160** se(-1) 0.0029*** 0.0029*** 0.0029** sd79locpc(-1) 0.0010*** 0.0010** 0.0010*** statistics n 705 705 705 r2 0.2427 0.2427 0.2427 r2_a 0.2194 0.2351 f f(7,682) = 31.27*** f(7,14) = 34.94*** f(7,46) = 8.43*** notes: ***, **, * denote statistically significant at 1%, 5% and 10% level, respectively; and the stata commands xtreg, and xtscc were used. table 8. elasticities and adjustment speed models fe (iv) fe robust (v) fe d.-k. (vi) short-run semi-elasticities/impacts dlocpc 0.2478*** 0.2478*** 0.2478*** dse 0.0237*** 0.0237*** 0.0237*** computed long-run elasticities/impacts locpc 0.5425*** 0.5425* 0.5425** se 0.0994*** 0.0994*** 0.0994** sd79locpc 0.0329** 0.0329** 0.0329** speed of adjustment ecm -0.0294*** -0.0294*** -0.0294*** notes: ***, **, * denote statistically significant at 1%, 5% and 10% level, respectively. ecm denotes the coefficient of the variable lypc lagged once. 5. discussion this study is grounded on per capita data and on a panel of oil producing countries. as such, the countries considered in the analysis are a very diversified panel that include an assortment of: (i) opec members; and (ii) developing and developed countries. therefore, this diversity makes the analysis wide-ranging. the research extends the literature on the energy-growth nexus by incorporating the effect of oil consumption, the ratio of oil production to primary energy consumption, and the shift in the elasticity of oil-growth provoked by the second oil shock. largely, the results support the presence of cointegration/long memory contradicting the results of the westerlund (2007) test, performed previously (table 4). indeed, the coefficients of error correction mechanisms (ecm) are negative and highly statistically significant. the long-run elasticity of oil consumption (locpc) loses statistical significance (only at 10% significance level) in the fe robust model. the results reveal that the idiosyncrasy of the oil shock of 1979 was lasting, positive, and statistically highly significant for the elasticity of oil-growth. the causality running from oil consumption to economic growth was noticed, validating the growth hypothesis of the oil-growth nexus. this causality has a major impact in the long-run. this finding is far from unexpected given that this work is focused on oil producers. indeed, it is predictable that they would use an available oil endowment resource, and as shown, the resource is effectively employed, which is signalled by its positive impact on economic growth. this outcome is compatible both with economies with low electrification levels and with the increased contribution of the oil refinery and transport sectors to domestic output. these arguments are in line with the overviews of iea (2013), el-katiri (2013), and gately et al. (2013). international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.148-163 160 the results reveal that the elasticity of oil consumption on growth is positive, although modest in magnitude, especially in the short-run. the relative abundance of oil resources, captured by the variable se, is shown to be a driver of economic growth for this group of countries. noting that se is a ratio, if it remains constant, oil production increases output. at the same time, if it remains constant, primary energy consumption efficiency measures could be designed without hampering economic growth. overall, the higher the level of oil self-sufficiency, the larger the economic growth will be. regarding elasticities/impacts, in the shortand long-run, oil consumption is the main driving force of growth, followed by the ratio of oil production to primary energy consumption. the option for using dynamic panel techniques appears adequate, as the phenomenon under analysis is both a short and long-run one. the speed of adjustment is very low, under 3%, as shown by the ecm term in table 8, revealing that the adjustment to shocks requires a longer time span in order to achieve equilibrium. 6. conclusion the oil-growth nexus in oil producing countries was analysed within a context where oil consumption, the ratio of oil production to primary energy consumption, and the structural shift of the second oil shock were controlled for. to ensure the trustworthiness of using the recent panel data estimators, which are sensitive to the asymptotic properties of time, a long time period is used, for which data is available. although working on macro panels, no cross-sectional heterogeneity of parameter slopes was found. the cd-tests indicate the presence of cross-sectional dependence. the decision to decompose the total effects into their short and long-run components proved to be wise. bringing together diverse panel data estimators constitutes a valid contribution to the literature of the oil-growth nexus in oil producing countries. evidence was found to support the traditional growth hypothesis of the energy-growth nexus, both in the short and long-run. furthermore, the panel dynamic specification detects cointegration/long memory, as the ecm term is negative and statistically highly significant. indeed, the speed of adjustment to the long-run equilibrium is fundamental for understanding the oil-growth nexus. the driving forces of relative oil production and oil consumption on growth were confirmed. the structural break in elasticity of oil consumption to growth proved to be positive, but of low magnitude. once the growth hypothesis from oil to growth is proven, this work will lend support to design energy efficiency policies in primary energy consumption. moreover, the policymakers will become aware of the benefits of promoting oil self-sufficiency, by reinforcing the use of endogenous resources. references al jaber, s. (2013). mena energy transition strategy: a call for leadership in energy innovation, energy strategy reviews, 2(1), 5-7. alam, m. j., begum, i. a., buysse, j., van huylenbroeck, g. (2012). energy consumption, carbon emissions and economic growth nexus in bangladesh: cointegration and dynamic causality analysis, energy policy, 45, 217-225. al-mulali, u. (2011). oil consumption, co2 emission and economic growth in mena countries, energy 36(10), 6165-6171. anselin, l. (2001). spatial econometrics. in a companion to theoretical econometrics, baltagi, b. (ed.). blackwell: oxford, 310-330. apergis n., payne, j.e. (2009). energy consumption and economic growth in central america: evidence from a panel cointegration and error correction model, energy economics, 31(2), 211-216. apergis, n., payne, j.e. (2010). energy consumption and economic growth in south america: evidence from a panel error correction model, energy economics, 32(6), 1421-1426. baltagi, b.h. (2008). econometric analysis of panel data, fourth edition, chichester, uk: john wiley & sons. behmiri, n., manso, p. (2013). how crude oil consumption impacts on economic growth of subsaharan africa? energy, 54(1), 74-83. belke, a., dobnik, f., dreger, c. (2011). energy consumption and economic growth: new insights into the cointegration relationship, energy economics, 33(5), 782-789. belloumi, m. (2009). energy consumption and gdp in tunisia: co-integration and causality analysis, energy policy, 37(7), 2745-2753. oil-growth nexus in oil producing countries: macro panel evidence 161 bildirici, m., kayıkçı, f. (2013). effects of oil production on economic growth in eurasian countries: panel ardl approach, energy, 49(1), 156-161. blackburne iii, e.f., frank, m.w. (2007). estimation of nonstationary heterogeneous panels, the stata journal, 7 (2), 197-208. chen, p.-y., chen, s.-t., chen, c.-c. (2012). energy consumption and economic growth – new evidence from meta analysis, energy policy, 44, 245-255. choi, i. (2001). unit root tests for panel data, journal of international money and finance, 20(1), 249272. ciarlone, a. (2011). housing wealth effect in emerging economies, emerging markets review, 12(4), 399-417. damette, o., seghir, m. (2013). energy as a driver of growth in oil exporting countries?, energy economics, 37, 193-199. dantama, y.u., abdullahi, y.z., inuwa, n. (2012). energy consumption economic growth nexus in nigeria: an empirical assessment based on ardl bound test approach, european scientific journal, 8(12), 141-157. darbouche, h. (2013). mena’s growing natural gas deficit and the issue of domestic prices, energy strategy reviews, 2(1), 116-121. driscoll, j., kraay, a.c. (1998). consistent covariance matrix estimation with spatially dependent data, review of economics and statistics, 80(4), 549-560. eberhardt, m. (2011). panel time-series modeling: new tools for analyzing xt data, 2011 uk stata users group meeting. eberhardt, m., presbitero, a.f. (2013). this time they are different: heterogeneity and nonlinearity in the relationship between debt and growth, imf working paper 13/248. ecb (2010). energy markets and the euro area macroeconomy, occasional paper series, 113 / june, european central bank. el-katiri, l. (2013). energy sustainability in the gulf states: the why and the how, oxford institute for energy studies, http://www.oxfordenergy.org/wpcms/wp-content/uploads/2013/03/mep_4.pdf, (accessed january 21, 2014). esfahani, h.s., mohaddes, k., pesaran, m. h. (2014). an empirical growth model for major oil exporters, journal of applied econometrics, 29(1), 1-21. esfahani, h.s., mohaddes, k., pesaran, m.h. (2013). oil exports and the iranian economy, the quarterly review of economics and finance, 53(3), 221-237. farhani, s., rejeb, j.b. (2012). energy consumption, economic growth and co2 emissions: evidence from panel data for mena region, international journal of energy economics and policy, 2(2), 71-81. fattouh, b., el-katiri, l. (2013). energy subsidies in the middle east and north africa, energy strategy reviews, 2(1), 108-115. fuinhas, j. a., marques, a. c. (2013). rentierism, energy and economic growth: the case of algeria and egypt (1965–2010), energy policy, 62, 1165-1171. gately, d., al-yousef, n., al-sheikh, h.m.h. (2013). the rapid growth of opec′s domestic oil consumption, energy policy, 62, 844-859. hoechle, d. (2007). robust standard errors for panel regressions with cross-sectional dependence, stata journal, 7(3), 281-312. hossein, s.s.m., yazdan, g.f., hasan, s. (2012). consideration the relationship between energy consumption and economic growth in oil exporting country, procedia social and behavioral sciences, 62, 52-58. hsiao, c. (2003). analysis of panel data, 2nd ed., cambridge, cambridge university press. iea (2013). world energy outlook 2013, the international energy agency, paris, iea publications. kao, c. (1999). spurious regression and residual-based tests for cointegration in panel data, journal of econometrics, 90(1), 1–44. klein, n. (2010). the linkage between the oil and non-oil sectors – a panel var approach, imf working paper, wp/10/118, http://www.imf.org/external/pubs/ft/wp/2010/wp10118.pdf, (accessed november 9, 2013). klevmarken, n.a. (1989). panel studies: what can we learn from them? introduction, european economic review, 33(2-3), 523-529. international journal of energy economics and policy, vol. 5, no. 1, 2015, pp.148-163 162 kraft, j., kraft, a. (1978). on the relationship between energy and gnp, journal of energy and development, 3(2), 401-403. levin, a., lin, c.-f., chu, c.-s. j. (2002). unit root test in panel data: asymptotic and finite-sample properties, journal of econometrics, 108(1), 1-24. lim, k.-m., lim, s.-y., yoo, s.-h. (2014). oil consumption, co2 emission, and economic growth: evidence from the philippines, sustainability, 6(2), 967-979. lotfalipour, m., falahi, m., ashena, m. (2010). economic growth, co2 emissions, and fossil fuels consumption in iran, energy, 35(12), 5115-5120. luft, g., korin, a. (2009). turning oil into salt: energy independence through fuel choice, south carolina, booksurge publishing. maddala, g.s., wu, s. (1999). a comparative study of unit root tests with panel data a new simple test, oxford bulletin of economics and statistics, 61(s1), 631-652. mahadevan, r., asafu-adjaye, j. (2007). energy consumption, economic growth and prices: a reassessment using panel vecm for developed and developing countries, energy policy, 35 (4), 2481–2490. mehrara, m. (2007). energy consumption and economic growth: the case of oil exporting countries, energy policy, 35(5), 2939–2945. mehrara, m. (2008). the asymmetric relationship between oil revenues and economic activities: the case of oil-exporting countries, energy policy, 36(3), 1164-1168. mohammadi, h., parvaresh, s. (2014). energy consumption and output: evidence from a panel of 14 oil-exporting countries, energy economics, 41, 41-46. moscone, f., tosetti, e. (2010). health expenditure and income in the united states, health economics, 19(2), 1385-1403. narayan, p., sharma, s., poon, w., westerlund, j. (2014). do oil prices predict economic growth? new global evidence, energy economics, 41, 137-146. narayan, p.k., smyth, r. (2008). energy consumption and real gdp in g7 countries: new evidence from panel cointegration with structural breaks, energy economics, 30(5), 2331-2341. naser, h. (2014). oil market, nuclear energy consumption and economic growth: evidence from emerging economies, international journal of energy economics and policy, 4(2), 288-296. ozturk, i. (2010). a literature survey on energy-growth nexus, energy policy, 38(1), 340-349. ozturk, i., aslan, a., kalyoncu, h. (2010). energy consumption and economic growth relationship: evidence from panel data for low and middle income countries, energy policy, 38(8), 44224428. pao, h.-t., tsai, c.-m. (2011). modeling and forecasting the co2 emissions, energy consumption, and economic growth in brazil, energy, 36(5), 2450-2458. park, s.-h., yoo, s.-h. (2014). the dynamics of oil consumption and economic growth in malaysia, energy policy, 66, 218-223. pedroni, p. (1999). critical values for cointegration tests in heterogeneous panels with multiple regressors, oxford bulletin of economics and statistics, 61(special issue), 653–70. pedroni, p. (2004). panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the ppp hypothesis, econometric theory, 20(3), 597–625. pesaran, m.h. (2007). a simple panel unit root test in the presence of cross-section dependence, journal of applied econometrics, 22(2), 265-312. pesaran, m.h., shin, y., smith, r.p. (1999). pooled mean group estimation of dynamic heterogeneous panels, journal of american statistical association, 94(446), 621-634. sgouridis, s., griffiths, s., kennedy, s., khalid, a., zurita, n. (2013). a sustainable energy transition strategy for the united arab emirates: evaluation of options using an integrated energy model, energy strategy reviews, 2(1), 8-18. westerlund, j. (2007). testing for error correction in panel data, oxford economics and statistics, 69(6), 709-748. wolde-rufael, y. (2009). energy consumption and economic growth: the experience of african countries revisited, energy economics, 31(2), 217-224. yıldırım, e., sukruoglu, d., aslan, a. (2014). energy consumption and economic growth in the next 11 countries: the bootstrapped autoregressive metric causality approach, energy economics, 44, 14-21. oil-growth nexus in oil producing countries: macro panel evidence 163 yousef, n.a. (2013). demand for oil products in opec countries: a panel cointegration analysis, international journal of energy economics and policy, 3(2), 168-177. yuan, c., liu, s., xie, n. (2010). the impact of chinese economic growth and energy consumption of the global financial crisis: an input-output analysis, energy, 35(4), 1805–1812. zhang, x., cheng, x. (2009). energy consumption, carbon emissions and economic growth in china, ecological economics, 68(10), 2706-2712. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020390 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 390-395. did global financial crisis worsen oil price volatility and banking sector nexus in selected ecowas and g-7 member countries? charles o. manasseh1, godfrey i. ihedimma2, felicia c. abada3, ifeoma c. nwakoby1*, benson o. njoku4, jude t. kesuh1, chizoba g. okeke5, felix c. alio1, j. u. j. onwumere1 1department of banking and finance, university of nigeria enugu campus, nsukka, nigeria, 2department of economics, spiritan university nneochi, abia state, nigeria, 3social science units, school of general studies, university of nigeria, nsukka, nigeria, 4department of banking and finance, michael okpara university of agriculture, umudike, nigeria, 5department of economics, madurai kamaraj university, india. *email: ifeoma.nwakoby@unn.edu.ng received: 21 may 2020 accepted: 30 august 2020 doi: https://doi.org/10.32479/ijeep.9961 abstract this study examined the effects of global financial crisis on oil prices and its relationship with banking sector in selected ecowas and g-7 group for the period 2000 to 2018. the data for the study were collected from the wdi (2019). following the work of driscoll and kraay (1998), the study adopted panel fixed effect estimation techniques. since financial crises affect mostly the banking system and banking reforms is reflected in the lending interest rate which is a positive contributor to the rate of investment growth, we therefore estimated the model using investment as the dependent variable. the results show that the lending interest rates exert positive impact on the rate of investment growth for g7 countries. furthermore, we observed that 1% drop in interest rate would cause investment to grow by about 0.0378% for the ecowas region. the interaction of the international oil prices and the rate of inflation express the cost of production in the regions. thus, it was found that a 1 percent increase in the cost of production would cause a fall in the level of investment growth by 0.000029% and 0.000058% for the g7 and ecowas respectively. this result though was found not to be significant, thus not reliable. in g7 and ecowas, growth in output was found to positively and significantly influence the growth rate of investment. keywords: financial crisis, oil price, banking sector jel classifications: g01, q49, g21 1. introduction after the great depression of the 1930’s, the global financial crisis has been adjudged the worst financial crisis ever since. the wake of 2007 till the duration of 2008 witnessed this economic ill which cut across several nations of the world by differing degrees. some economies recovered after the implementation of robust stabilization policies, while others just could not. williams (2010) records that the global financial crisis, henceforth referred to as the gfc began in 2007 with the crash of the us subprime mortgage market which later evolved into being a full-blown international banking crash with the event of the collapse of an investment bank – lehman brothers (on 15th september, 2008) (olowe, 2010; williams, 2010). he further stated that excessive risks absorbed by the lehman brothers amplified the effect to a global one. this endeared the issuing of enormous bail-out funds from financial institutions in tandem with the implementation of monetary and fiscal policies to forestall the collapse. this though yielded the great recession. by 2008, 15 banks in the us had failed while according to letzing (2008), some others received interventions via acquisitions by other banks. the spread of the gfc motivated other central banks of the world to reduce this journal is licensed under a creative commons attribution 4.0 international license manasseh, et al.: did global financial crisis worsen oil price volatility and banking sector nexus in selected ecowas and g-7 member countries? international journal of energy economics and policy | vol 10 • issue 6 • 2020 391 interest rates while several governments implemented policies and packages aimed at stimulating economic growth and rebuilding confidence in the financial markets. this also filtered through to the oil markets with a resultant uncertainty in oil world prices. prior to the creation of opec, the united states and british oil companies supplied the world oil at relatively cheap costs (olowe, 2010). oil prices have over time become necessary in explaining the changes in the business cycles as with economic growth. this is majorly as a result of the role oil plays in the cost of production and its relation with output. mckillop (2004) explains that oil price fluctuations are highly considered for their involvement with macroeconomic variables. unsteady prices could the world all over, cause reduction in economic growth, panic in the stock market, inflation and monetary instability. this could also lead to higher interest rates and an impending recession. this became the case after the incidence of the gfc in 2008. englama et al. (2010) opines that oil prices were relatively high and exchange rates for most countries were stable. the advent of the crisis forced oil prices to crash and exchange rate caving in by about 20% in nigeria. interest rates in canada was 5.81% (2006) but rose sharply to 6.1% (2007). but by 2008, lending interest rate in canada had dropped to 4.72% and 2.4% in 2009 (wbg, 2017). this was as a result of swift monetary reforms in the canadian economy. economic output growth was recorded at 2.62% (2006) and experienced a decline to 2.06% (2007). by 2008, output growth had fallen even deeper to 1% and worse in 2009 (-2.95%) (wbg, 2017). the country started recovery by 2010 and has since being fluctuating between 1% and 3%. lending interest rate in japan as at 2006 was recorded by the wbg report of 2017 at 1.66% and1.88% in 2007. by 2008, this had risen to 1.91% and started dropping afterwards. economic growth on the other hand was grossly affected. in 2006, japan’s growth rate was recorded at 1.42% and rose slightly to 1.65% in 2007. by 2008 when the gfc was more pronounced, japan’s growth rate was seen to have fallen deep to −1.14% and −5.41% in 2009. recovery began for japan in 2009 when her gdp growth rate rose to 4.19% but this was short lived as it has since fluctuated around 0 and 2% (wbg, 2017). lending interest rate in the uk however was as high as 4.64% in 2006 and rose further to 5.51% in 2007. by 2008 it was recorded at 4.68% and 0.64% in 2009. it had since been stable at 0.5%. economic growth on the hand was recorded to be 2.46% and dropped slightly to 2.37% (2007). by 2008, output growth had dropped to −0.47% and even worse in 2009 (−4.19%). recovery started the following year, and growth had been between 1% and 3% since then. african economies were hit badly by the gfc. nigeria for instance had interest rate as high as 16.9% in 2006. this was somewhat constant in 2007 (16.94%). by 2009, the cost of loanable funds in nigeria had risen to 18.36% thus reflecting very high costs of obtaining funds for investment purposes. economic growth on the other hand though dropped from 8.21% (2006) to 6.83% (2007), it fluctuated around 4% and 7% till in 2015 when it dropped to 2.65%. the rebasing of the nigerian economy may have had some influence on the high growth rate. this is plausible as evidence comparatively to other west african countries as mauritania whose economic growth dropped from 18.87% in 2006 to −1.04% in 2009. oil prices on the other hand are observed to have passed various phases. opec average annual oil prices as at 2005 was recorded at us$50.59. this rose to us$61 in 2006 and continued till in 2009 when the price dropped to us$60.86. oil exporting countries enjoyed higher prices between 2011 and 2013 after which oil prices averaged us$61.26 between 2014 and 2018. the higher oil prices would also reflect an increase in the cost of production worldwide for countries dependent on crude for her production process, with countries like nigeria which still fall in the group of refined oil importers. whether or not the gfc have been problematic to countries, this would depend on its gravity on the respective countries. banking reforms in response to the crisis as primarily indicated in the cost of funds for investment is expected to cause some level of stabilization for respective economies and as such, this study investigates the implications of these reforms in the face of oil volatility while conditioned by the global financial crisis. the paper is organized as follows: section two discusses the review of related literature, while the method for the study is presented in section three. in section four, we present data analysis and interpretation, while conclusion and rrecommendations is presented in section five. 2. review of related literature 2.1. the financial intermediation theory of banking economists have over time had several conceptions of banking. one of such is embedded in its function as a financial intermediary. this also reflects the position that banks may not be so different from their non-banking counterparts, especially in the function of financial intermediation. economic thinkers like keynes (1936), tobin (1963; 1969), bernanke and gertler (1995), kashyap et al. (2002) but to mention a few are some of the authors whose believe rests on the notion that banks are primarily financial intermediaries. as reflected in growth models by harrod (1939) and domar (1947), keynes explains that for investments to occur, savings would have to be precursory to this. tobin (1963) further explains that the distinction between commercial banks and other financial intermediaries are of degree and not of the kind. thus, this in his view are as a result of the interest rate ceilings and reserve requirements banks are subjected to unlike other intermediaries, thus other intermediaries if subjected to same conditions as banks would behave in same way. however, the non-existence of either in the uk faults tobin’s (1963) conditions for differences between bank and non-bank financial intermediaries. kashyap et al. (2002) were of the opinion that banks are pure financial intermediaries such that they acquire assets with funds they had obtained in the form of deposits or alternatively in the issue of securities. it is on this premise that casu and girardone (2006) argue that banks as with other financial intermediaries are involved in a pivotal role in the economy in terms of moving funds from surplus units to deficit units, thus closing in of the finance gap. they reconcile the needs of borrowers with those of lenders via the conversion of deposits (best described as low-risk, highly liquid and smallsize) into loanable funds which are illiquid, larger in size and with higher risk (werner, 2016). 2.2. the fractional reserve theory of banking this theory postulates that banking systems create money through the process of multiple deposit expansion. werner (2016) explains manasseh, et al.: did global financial crisis worsen oil price volatility and banking sector nexus in selected ecowas and g-7 member countries? international journal of energy economics and policy | vol 10 • issue 6 • 2020392 that according to phillips (1920), what holds for the banking system as an aggregate does not hold for a unit bank. the theory holds that banks may accept deposits, provide for loans or investment, but is also required to hold reserves in proportion of its deposit liabilities which are held in currency or as balances with the central bank (mankiw, 2002). the theory holds that banks are enabled to act as financial intermediaries, closing in on the gap between the borrowers and savers via the provision of long-term loans to borrowers and immediate liquidity to depositors. mallet (2015) explains that there is the desire by the society to forestall bank failures from yielding nationwide mishaps via their influence on commerce as well as the use of the banking mechanism for the prevention of deliberate fraudulent activities. these inspired the demand for regulation and reforms in the 19th century, which required systemic and comprehensive apprehension of the operation of the system. the fractional reserve banking practices introduced a new form of money within the economy – the entry on a deposit ledger as provider for by an accounting system. this is referred to as deposit creation by werner (2016). 2.3. the illusion of the too-big-to-fail financial institutions financial sectors are most times prone to taking financial risks on the note that they would thrive better, and without economic failure. this is owed to the fact that most financial institutions do not internalise the import of their actions on the possibility of a mishap. smaller financial institutions are most times more hedged against such risks due to the financial standing in the market. cukierman (2011) argues that the negative externality for these institutions may be negligible, however, for larger institutions, it remains enormous. the commitment to portfolios with higher risk levels above the socially optimal levels is thus spurred by the intuition that they may bailed out in the event of an economic crisis – thus a behaviour exhibiting moral hazard in banking. this tendency for regulators of the system to lower the standards on monitoring of larger financial institutions as well as curbing the risk loving behaviour of managers of large financial institutions is the too-big-to-fail illusion. thus, in the presence of a financial crisis, such institutions are grossly affected which in turn amplifies the impact of the crisis since these institutions are key-players in the system (chuku and akpan, 2011). 2.4. empirical review onanuga and onanuga (2016) investigated the response of the banking sector development to financial and trade openness in the presence of the gfc in africa. they studied low-income (10), lower-middle (10), upper-middle (6) and high-income (2) countries, all in africa. the result of their pooled mean group estimation shows that the banking sector develops independently of economic growth for lower-income and high-income economies, whereas for low and upper-middle income economies, it develops as there is increment in the demand for finance. in cognisance of the gfc, the trade openness of high and lower-income economies is found to be more effective while financial openness was found to be more effective in low income economies. neither of these two degrees of openness was found to be effective in the upper-middle income economies. in the long-run, their findings revealed that save for in high income economies, the gfc generally reduced the development of the banking sector in africa. the lower-middle and low-income economies however, were found to suffer most from the gfc. andrieș et al. (2016) studied the impact of the international financial crisis on banking performance in eastern and central european economies. their study centred on the determinants of the banking profitability in 10 countries form the aforementioned regions between 2014 and 2013. the profitability of bank was measured using the return on assets (roa) and selected banking and macroeconomic variables were regressed on the former. they dummied the gfc variable and used the difference-in-difference method to verify if the impact of the crisis was diminished or amplified. their findings revealed that difference between profits levels of the banks existed, thus conforming to a priori expectations. the gfc variable had a negative impact on the roa and it was found to be statistically significant. other findings revealed that factors which amplified and diminished the effect of the gfc included the high capital adequacy of banks, total assets of large banks and the foreign ownership of banks. ngowi (2015) contends that there have been substantial impacts of the gfc in the banking sector in the more economically and financially developed and integrated parts of the world. this include places like in north america and europe, unlike in africa which is less developed. his study was on the implications and responses of the 2008 economic crisis in the banking sector. further findings reveal that within africa, the economies which are considered more economically viable and financially integrated such as south africa and nigeria were generally worst hit by the crisis, with particular reference to their financial sector. the author also explains that some of the responses to the gfc could lead to yet more impacts which could be either positive or negative as implications for the banking sector of the african region. olowe (2010) investigated the month-of-the-year effect of the gfc in the uk brent crude oil. his garch analysis for the asian financial crisis and the gfc, used daily data from january 4, 1988 to may 27, 2009. the findings of the research were that there was the presence of the month-of-the-year effect on volatility, but not in the returns on oil. his study further shows that the asian financial crisis had impact on oil price return series, however, the gfc had no impact on oil price returns as the asian financial crisis was not found to account for the sudden change in variance of oil prices. allen and giovannetti (2011) studied the effects financial crisis had on sub-saharan africa. the paper analysed the media through which the gfc was transmitted to the ssa region, while focusing on vulnerable countries in the region. they found out that trade was a major channel through, while intra-african remittance was another channel through which the gfc was transmitted. they further found that for many countries with high fragility were characterised by low resilience and ability to absorb shocks. more so, their estimates suggested that in the medium run, oecd economies would likely lower aid and this would impose damaging effects on the recipient economies. 3. methodology 3.1. theoretical framework the study follows the mckinnon-shaw hypothesis. mckinnon (1973) and shaw (1973) explain that in a repressed financial manasseh, et al.: did global financial crisis worsen oil price volatility and banking sector nexus in selected ecowas and g-7 member countries? international journal of energy economics and policy | vol 10 • issue 6 • 2020 393 system, interest rates on deposits on pecuniary assets are often negative and highly uncertain. this imposes a fear for persistent inflation in such economy as well as the devaluation of the nation’s currency which most likely would lead to capital flight as well as discouraging savings. resultant policies would thus be the impositions of restrictions on lending as well as compulsory interest rate ceilings which may be far below the market clearing levels. the hypothesis tests the interest rate-savings and interest rate-investment relationship; however, the interest rate-investment relationship would be calibrated in this study. this, in this study would be necessary since the level of investment in any given economy is expected to be affected by the occurrence of the gfc. oil prices would also be controlled for though interacted with the price level since oil is an essential commodity in the supply side mechanism in terms of production. this is to observe the effects of oil prices in tandem with the price levels in the period of the gfc. the study theorizes the inclination of unobserved heterogeneity amongst countries in terms of the selective banking reforms. since banking reforms are not homogeneous across the countries of interest – the g7 and the ecowas – as a result of the nonadherence to a uniform monetary policy respectively, the study thus assumes that there may be the presence of the unobserved heterogeneity. the study further assumes that the unobserved heterogeneity which may pose measurement bias, maybe correlated with the random occurrences. this assumption predicates the use of the fixed effect model as the requisite estimation technique; however, in the presence of the cross-sectional dependence, serial correlation and heteroscedasticity, the model would adopt a different panel model called the driscoll and kraay fixed effect model. this model, according to driscoll and kraay (1998) has the advantage of accounting for the aforementioned panel irregularities. 3.2. model specification the model to be estimated is given explicitly below as; lninvs opr intr opr infl lngdp ex it it it it it = + + + + +b b b b b b 1 2 3 4 5 1 6 * cch deprit it it+ +b e7 (3.1) where lninvs is the natural logarithm of investment, opr*infl is the interaction of oil prices and price level, lngdp is the natural logarithm of gross domestic product, exch is the nominal exchange rate, depr is the consumption of capital proxy for the rate of depreciation, all for the respective countries for data between 2000 and 2018. the choice of the period is informed by cross-sectional availability of data and a period of coverage for the gfc, with care given to intentionally exclude periods of other shock incidences before the gfc. 4. data analysis and interpretation this section presents the regression results obtained from the models for the study. first, we describe the data (table 1) for the study to ensure that the series do not deviate largely from the mean. tests such as levine, lin and chun (llc) and im, pessaran and shin (ips) unit root test were adopted to ascertain the order of integration. the basic features of the data and the average values of the variables used in the study is described in table 1, which provide the summaries about the sample and the variables descriptions. the standard deviation of the variables in the model indicates the variations in the sample for the study as shown in table 1. the data as collected from the wbg (2018) is estimated for the model stated above. the result of the estimation for g7 countries and the ecowas is tabulated below in the table 1. from table 1, we observed that the minimum and maximum coefficients were −20.53218 and 31.13205 respectively. the skewness of the distribution and the kurtosis indicates that the series were not distributed normally, and the distribution does not vary largely from the normal distribution as also shown in standard deviation, observed to be very close to the mean of the series on average. 4.1. unit root tests since time series data are high frequency data, we adopted levine, lin and chu (llc) and im, pesaran and shin (ips) unit root tests to check if the variables have unit root (table 2). the reason for the choice of llc and ips is because llc allows for heterogeneity of individual deterministic effects and assume homogeneous autoregressive for the variables in the model, while ips allows for residual serial correlation and heterogeneity of the dynamics and error variances across groups. the unit root tests results presented in table 2 show that the variables has no unit root. hence, the null hypothesis h0: α=0 is rejected, while the alternative hypothesis h1: α<0 is accepted. this suggest that all the variables are stationary of order i(0) and i(1). hence, having established the order of integration of the variables, we further estimate the effects of financial crisis on oil price volatility and establish its relationship with banking sector. however, before the estimation, it should be noted that reforms in banking sectors is usually in response to the crisis as primarily indicated in the cost of funds for investment is expected to cause some level of stabilization for respective economies. as such, this study estimates the implications of these reforms in the face of oil volatility while conditioned by the global financial crisis. hence, since financial crises affect mostly the banking system and banking reforms is reflected in the lending interest rate which is a positive contributor to the rate of investment growth, we therefore estimated the model using investment as the dependent variable. the estimated results of the groups that made up the panel are presented in table 3. the result presented above as summarised in the table shows that the banking reforms in the region as culminated and reflected in the lending interest rate is a positive contributor to the rate of investment growth for g7 countries. lending interest rates though theoretically is expected to negatively spur investment growth since it is the cost of obtaining loanable funds; the occurrence of the gfc is possible explanation for this anomaly in that, the g7 economies had enjoyed lower lending interest rates prior to this period. reforms in the cost of obtaining funds became a disincentive for investment. this result is significant at the 1% level, thus reliable. the reforms as revealed in the interest rate manasseh, et al.: did global financial crisis worsen oil price volatility and banking sector nexus in selected ecowas and g-7 member countries? international journal of energy economics and policy | vol 10 • issue 6 • 2020394 for the ecowas shows that 1% drop in interest rate would cause investment to grow by about 0.0378% for the entire region. this though follows a priori expectation, is not significant and as such is not reliable. also, close observation shows that both g7 and ecowas member countries were negatively affected by the oil price volatility (opv). the interaction of the international oil prices and the rate of inflation express the cost of production in the regions. this is on the premise that oil is a factor for supply and the cost could be hampered by the rate of inflation. for both regions, it was found that a percent point rise in the cost of production would cause a fall in the level of investment growth by 0.000029% and 0.000058% for the g7 and ecowas respectively. this result though was found not to be significant, thus not reliable. growth in output in both regions was found to positively and significantly influence the growth rate of investment. this result is validated at the 1% level of significance. other monetary reforms as expressed in the exchange parity of local currency for the dollar reveals that an increase in the exchange rate would cause investment growth in the g7 countries to drop such that 1%-point rise in exchange rate is expected to cause the investment to fall by about 0.0912%. this is though not significant, thus not reliable. in the ecowas, depreciation of the local currencies in the region is expected to caused investment grow significantly. this depreciation is an effect in response to the occurrence of the gfc as a banking reform in a bid to save the value of the local currencies by the ecowas. lastly the study evaluates the rate of depreciation for both economies and it was found that for the g7 countries, the rate of depreciation of capital accounts for the level of investment negatively and significantly. this means that for every 1%-point increase in depreciation of capital, investment falls. this is found to be significant at the 5% level of significance. for the ecowas, the level of depreciation in capital positively influences the growth of investment. this though was found not to be significant, thus the result is not reliable. 5. conclusion and recommendations the findings throw light to the state of the economies in the face of the gfc. policy implications are that interest rate adjustments as banking reforms were prompt in ecowas region as many of the countries in the region already had higher interest rates compared to the g7 economies. the higher the interest rates however, the higher the level of investment reflects that in the g7 economies, the cost of investment is not as expensive as it is in the ecowas region. growth in output significantly implies table 3: result summary for g7 countries and ecowas variable fe_g7 fe_ecowas constant −25.190461*** [5.1250194] (−4.915212) −7.0314814 [6.868821] (−1.023681) opv −8.023689*** [1.345607] (5.962877) −6.314250** [1.51231] (4.175235) intr 0.01207258*** [0.00312619] (3.8617550) −0.03781852 [0.02724762] (−1.387956) opr*infl −0.00002938 [0.00007457] (−0.3939922) −0.00005785 [0.00003671] (−1.575864) lngdp 1.825883*** [0.18288461] (9.983797) 1.1298677*** [0.33463395] (3.376428) lnexch −0.09117118 [0.6450043] (−1.4134972) 0.57884089** [0.20922229] (2.766631) depr −0.3671514** [0.091415] (−4.016315) 0.494923 [1.357118] (1.4095634) source: authors’ computation. dependent variable is investment denoted with lninvs. [.], standard deviation, (.), t-statistics. *** denotes significance at 1%, ** denotes significance at 5% table 2: panel unit root tests results variable (s) llc (t-stat) order of integration ips (t-stat) order of integration level difference level difference opv [−15.211]*** (0.0000) i (0) [−3.75145]*** (0.0001) i (0) intr [−6.0306]*** (0.0000) i (0) [−19.2113]*** (0.0000) i (1) lngdp [−13.716]*** (0.0000) i (1) [−12.4115]*** (0.0000) i (1) lnexch [−9.763]*** (0.0000) i (1) [−16.1417]*** (0.0000) i (0) depr [−8.2761]*** (0.0000) i (1) [−10.3015]*** (0.0000) i (1) opr*infl [−10.421]*** (0.0000) i (1) [−11.1124]*** (0.0000) i (1) source: authors’ computation. [.] stands for t-statistics, (.); probability values, and ln; log. ***, ** and * represent 1%, 5% and 10% percent level of significance respectively table 1: summary statistics variable opv intr lngdp lnexch depr opr*infl mean −0.041511 1.12651 2.17127 −0.006267 0.000127 4.467122 median 0.031219 1.23167 2.51817 −0.005365 0.000726 3.156013 maximum 7.279321 2.31511 11.26134 31.13205 9.761120 7.71308 minimum −8.019310 −4.12445 −17.16103 −20.53218 −19.71312 0.173143 sd 1.521611 0.783116 6.41793 1.585151 3.106192 3.212175 skewness −2.153727 −1.714143 0.038513 0.203106 −6.138725 1.512910 kurtosis 9.04112 5.217784 4.115431 10.1032 11.12244 4.185401 jarque-bera 88.3142 28.21300 40.41712 75.30412 30.77142 54.16311 source: authors’ computation manasseh, et al.: did global financial crisis worsen oil price volatility and banking sector nexus in selected ecowas and g-7 member countries? international journal of energy economics and policy | vol 10 • issue 6 • 2020 395 growth in investment in both regions. this has a policy implication of the effect of the accelerator in expanding investment levels. depreciation of capital negatively hinders investment in g7 while its influence is positive in ecowas. the implication of this is that cost of worn out capital is readily accounted for in the g7 economies than in west africa especially in the period of the gfc. the cost of production in tandem with the price levels as reflected in the interaction of oil prices and the level of inflation has decremental effect on investment in both regions. this though was found to be insignificant. this implies that the gfc occurrence distorted production activities across the globe, making expansion in plant size a disincentive to producing units. the study recommends that the key agents in the production sector insure part of their production accessories to reduce risks that come with incidences as the gfc. the study further recommends that banking reforms should be periodically done to ascertain the optimal level of change needed to promote private participation in economic activities. increase in the exchange rate is found to spur investment significantly in ecowas. this implies that currency depreciation attracts investment to the region. this study thus advocates that ecowas governments redirect investment to suit demand for exports. this would enable the countries take advantage of their depreciated local currencies to grow demand for their commodities. references allen, f., giovannetti, g. (2011), the effects of the financial crisis on sub-saharan africa. review of development finance, 1(1), 1-27. andrieș, a.m., capraru, b., ieșan-muntean, f., ihnatov, i. (2016), the impact of international financial crisis on bank performance in eastern and central european countries. euro economica, 35(1), 1-16. bernanke, b., gertler, m. (1995), insided the black box: the credit channel of monetary policy transmission. journal of economic perspectives, 9(4), 27-48. casu, b., girardone, c. (2006), bank competition, concentration and efficiency in the single european market. the manchester school, 74(4), 441-468. chuku, a.c., akpan, u.f. (2011), reflections on the global financial crisis: lessons for regulatory reforms and regional integration in ecowas. cukierman, a. (2011), reflection on the crisis and on its lessons for regulatory reforms and for central bank policies. journal of financial stability, 7(1), 26-37. domar, e. (1947), expansion and employment. american review, 37(1), 34-55. driscoll, j., kraay, a. (1998), consistent covariance matrix estimation with spatially dependent panel data. the review of economics and statistics, 80(4), 549-560. harrod, r. (1939), an essay in dynamic theory. economic journal, 49, 14-33. kashyap, a., rajan, r., stein, j. (2002), banks as liquidity providers: an explanation for the existence of lending and deposit-taking. journal of finance, 57, 33-73. keynes, m.j. (1936), the general theory of employment, interest and money. new delhi: atlantic publishers. letzing, j. (2008), two banks fold, bringing total to 15 failures this year. new york: market watch. mallet, j. (2015), general disequilibrium: the hidden conflict between fractional reserve banking and economic theory. cosmos taxis, 2(2), 18-33. mankiw, g. (2002), macroeconomics. 5th ed. new york: worth publishers. mckillop, a. (2004), oil prices, economic growth and world oil demand. middle east economic survey, 47(35). mckinnon, r. (1973), money and capital in economic development. washington dc: brookings institution. ngowi, h.p. (2015), the 2008 economic crisis: implications and responses in the banking sector. african journal of economic review, 3(1), 1-10. olowe, r.a. (2010), oil price volatility, global financial crisis and the month-of-the-year effect. international journal of business and management, 5(10), 156-170. onanuga, o.t., onanuga, a.t. (2016), the response of banking sector development to financial and trade openness in the presence of global financial crisis in africa. botswana journal of economics, 14(1), 93-117. phillips, c.a. (1920), bank credit: a study of the principles and factors underlying advances made by banks to borrowers. new york: macmillan. shaw, e.s. (1973), financial deepening in economic development. new york: oxford university press. tobin, j. (1963), commercial banks as creators of money. in: carson, d., editor. bnaking and monetary studies. irwin: cowles foundation. tobin, j. (1969), a general equilibrium approach to monetary theory. journal of money credit and banking, 1, 15-29. werner, r.a. (2016), a lost century in economics: three theories of banking and the conclusive evidence. international review of financial analysis, 46, 361-379. williams, m. (2010), uncontrolled risk. new york: mcgraw-hill education. world bank group. (2017), 2017 world development indicators. washington dc: international bank for reconstruction and development, the world bank. tx_1~at/tx_2~at international journal of energy economics and policy | vol 10 • issue 6 • 2020100 international journal of energy economics and policy issn: 2146-4553 available at http: www.econjournals.com international journal of energy economics and policy, 2020, 10(6), 100-108. impacts of environmental responsibility and performance on organizational performance: importance of environmental performance quang linh huynh* tra vinh university, tra vinh city, vietnam. *email: huynhquanglinh@tvu.edu.vn received: 20 may 2020 accepted: 28 august 2020 doi: https://doi.org/10.32479/ijeep.9955 abstract this study evaluated the causal effect of environmental friendly activities and resultant environmental performance of enterprises on their organizational performance. more importantly, it analyzed and empirically investigated the mediation of environmental performance in the research model which has been paid no attention to in previous studies. the final research data was gathered from 399 publicly listed enterprisesin in the three main stock markets of vietnam. multiple regression analyses were applied to test the causal hypotheses, while mediating procedures were employed to test statistical significance for the mediation mechanism. the empirical findings reveal positive influences of environmental responsibility on organizational and environmental performance that in turn puts a positive influence on organizational performance. environmental performance is discovered as an entirely mediating factor in the joint research model, where environmental responsibility has no direct effect on organizational performance, but only has indirect effect through environmental performance. when included into the research model, environmental performance will transmit the whole of direct effect of environmental responsibility on organizational performance. keywords: environmental responsibility, environmental performance, firm performance, vietnam jel classifications: q01, q51, e01 1. introduction insufficient compliance with environmental friendly rules has been an extreme challenge to economies and especially to emerging economies including vietnam (world bank, 2012). however, there have been increasingly more organizations recognizing the notion there is room to raise environmental responsibilities (jo et al., 2015). social responsibility as well as sustainability controlling practices in theory needs an unbiased means to social and financial effectiveness. however, there has recently been increasing concern about environmental responsibility in enterprises because they have been facing growing pressures from the public and relevant parties to run their businesses in a more socially responsible way as well as comply with environmental friendly rules (lee et al., 2016). environmental responsibility has been deemed as a fundamental aspect of managing sustainability and social responsibility. environmental, social and economic aspects are three main sides of sustainability reflecting sustainable growth of enterprises; where environmental side or environmental responsibility has been broadly considered to play a growingly imperative role in organizational strategies and environmental and economic performance of the enterprises (elkington and rowlands, 1998). increasingly, the public have raised concerns about environmental pollution in reaction to scientific circles and extensive media coverage of global warming as well as other environmental pressures (sharma et al., 2010). investing in environmental friendly technology has been costing the enterprises so much, so the balance of investments in environmental friendly technology and organizational performance has drawn the attention of the enterprises (xu et al., 2016). vietnam has been one of the this journal is licensed under a creative commons attribution 4.0 international license huynh: impacts of environmental responsibility and performance on organizational performance: importance of environmental performance international journal of energy economics and policy | vol 10 • issue 6 • 2020 101 most rapidly developing economies in southeast asia; but such fast development may cause some environmental problems such as the high cost relevant to environmental deterioration (le et al., 2006). enterprises in vietnam have been major pollution makers, so they have been gradually subject to rules of environmental protection and demanded more responsible to the nature environment. governments around the world including vietnam have stipulated several rules and policies related to environmental protection in order to enable enterprises to environmental-friendly orientation (koo et al., 2014). consequently, numerous top executive directors have been considering complying with these rules as an imperative work of their job so that they can gain good organizational reputation and then better performance. environmental issues are currently often at the major agenda of enterprises and especially of those which are principally linked to energy consumption, waste dumping, and recyclable waste during input, production and output processes, which can lead to negative effects on the nature environment. environmental responsibility, a manifest of environmental sustainability is the duty and environmentally managerial tools, which the enterprises employ to operate their business towards to protecting and improving surrounding environments (holtbrügge and dögl, 2012). several enterprises hesitate to spend so much money on activities related to technological innovation and environmental protection, because these activities demand big investments in renovating production processes that can decrease their business effectiveness. nevertheless, porter and van der linde (1999) claimed that, business activities relevant to environmental sustainability might make major contributions to economic and environmental performance. in addition, berry and rondinelli (1998) were based on the natural resource based view (nrbv) to highlight that, enterprises have been constrained by governmental rules ordered to prevent them from polluting the natural environment. these rules can allow the enterprises to enhance environmental performance owing to a reduction in environmental expenditure and an augmentation in organizational image, while verrecchia (1983) asserted that, excellent environmental performance could lead to a decrease in environmental expenses for the enterprises in the forthcoming period that may win the confidence from potential shareholders. moreover, grounded on porter and van der linde (1999), the serious rules of environmental pollution can enable the enterprises to develop their environmental performance by vigorously seeking the best instruments of protecting the nature environment, innovating technology and increasing production effectiveness, which thereby enhance organizational effectiveness. drawing on existing research on environmental responsibility, it can summarize that, environmental responsibility is one of the most vital driving forces for augmenting organizational as well as environmental performance, which is in turn also a fundamental determinant of organizational performance. nonetheless, these studies have usually focused only on the causal connections among the factors; and have failed to investigate complicated effects on the causal links such as mediating mechanisms that have been ignored. this omission can lead research results to be inaccurate (surroca et al., 2010). therefore, a more comprehensive research project is necessary to be performed on this gap. furthermore, in a study on environmentally sustainable development, nguyen (2014) underlined that, vietnam is one of the fastest developing economies, having transformed from a centrally planned economy to a market-oriented one. although there have been potentials for social-economic growth, vietnam has been facing serious effects of environmental deterioration. in addition, nguyen (2014) also estimated in vietnam financial losses derived from environmental deterioration makes up from 1.5% to 3% of vietnam‘s gdp. it is consequently needed to conduct more research on environmental responsibility in vietnam so that the government can promulgate suitable environmental friendly policies, which will help vietnam‘s economy as well as enterprises to be more sustainable. to address the above mentioned issues, this research tries to scrutinize the linkages among environmental responsibility, environmental and organizational performance. especially, it seeks to analyze the mediating role of environmental performance in the joint research model. 2. literature review 2.1. effect of environmental responsibility on organizational performance various studies have explored the causal link from environmental responsibility to organizational performance; but their findings have been inconclusive (jo et al., 2015). a study by hart and ahuja (1996) investigated the causal connection from a decrease in environmental pollution to organizational performance, the findings of which indicated no consensus to this causal linkage. furthermore, certain researchers explained that the large investment of enterprises in environmental management would lead to bigger expenses and decreased benefits; as a result, it is required to weigh benefits with expenses to the enterprises (palmer et al., 1995). on the contrary, other researchers have stressed that severer environmental rules can make enterprises invest in new production technology to decrease environmental pollution and production expenses, resulting in higher profits (lee et al., 2016). for the standpoints of environmental performance, hutchinson (1992) declared that, enterprises have to rely on environmental friendly activities, so that they could achieve possible advantages, including improved organizational reputation, drawing clients who are concerned about environmental pollution, reducing production expenses by conserving power, developing good relationship with local communities and generating environmental friendly products. an early investment in environmental technology can lead enterprises to enjoy higher competitiveness, which is because environmental friendly technology likely diminishes the unit expenses of production and develops organizational success (nehrt, 1996). in addition, environmental rules force enterprises to renovate production technology and so improve competitive advantages for a prolonged period, because environmental friendly equipment could lessen expenses due to the effectiveness of production, which enables enterprises to gain better competitive advantages (porter, 1998). this can be called a ‘win–win’ approach, where the core of the causal link from environmental responsibility to organizational performance is so imperative. especially, a positive huynh: impacts of environmental responsibility and performance on organizational performance: importance of environmental performance international journal of energy economics and policy | vol 10 • issue 6 • 2020102 link between them will offer evidence on this perspective. drawing on the win–win standpoint, karagozoglu and lindell (2000) asserted strict rules of environment protection would encourage enterprises to be innovative and competent, which could augment the savings of production expenses and so lead to productivity, simultaneously decreasing environmental effects and then resulting in better organizational performance. furthermore, other empirical research has tried to explore the causal linkage from environmental responsibility to organizational performance. miles and covin (2000) studied the association among environmental management, organizational reputation and performance, revealing a sound managerial mechanism of environmental protection can enable enterprises to obtain good organizational reputation that is one of the most imperative drivers resulting in improved organizational performance. environmental irresponsibility can be a negative factor in damaging organizational reputation, which will lead the enterprise to suffer poor organizational performance (konar and cohen, 2001). advocates of environmental protection emphasize enterprises ought to weigh environmental responsibility with organizational performance (guenster et al., 2011). in this line, guenster et al. (2011) affirmed that, good environmental responsibility is related to better organizational performance, concluding that directors do not have any reason to be concerned about the inconsistency of environmental rules with their business goals. following this perspective, kim and statman (2012) maintained if enterprises want to enhance organizational performance, they had better invest much more in environmental protection. these authors discovered organizational behaviors are in agreement with the statement that they take steps in serving shareholders’ benefits, augmenting the investment in protecting environment, as it is essential in enhancing organizational performance for their enterprise. in addition, koo et al. (2014) emphasized environmental protection as a vital driver, which enterprises have to apply to develop competitive advantages and then improve organizational effectiveness. the empirical findings of that research indicated that environmental friendly activities might help the enterprise to attain environmental performance, leading to organizational performance. as asserted by wong et al. (2016), enterprises’ investment in environmental friendly activities is an operation for future benefits, because these activities force the enterprises to be more relevant to enhancements in environmental performance as well as increase organizational transparency and finally decrease organizational threats. a decrease in using resources enables the enterprises to operate more effectively by improving organizational reputation, eventually resulting in competitive advantages and organizational success (cai and he, 2014). fast economic development in developing countries has caused a serious deterioration in the natural environment, so enterprises there should act in more environmental friendly ways (li et al., 2017). the research of those authors investigated the causal relationship from environmental responsibility to organizational performance, the empirical results of which indicated that environmental responsibility puts a positive effect on organizational performance. overall then, it could come to the following hypothesis. h1: environmental responsibility likely improves organizational performance. 2.2. influence of environmental responsibility on environmental performance drawing upon the viewpoint of investment, excellent environmental performance can decrease environmental expenses for enterprises in the forthcoming period that may win the confidence from potential shareholders (verrecchia, 1983). furthermore, the serious rules of environmental pollution prevention will force the enterprises to improve their environmental performance by vigorously seeking suitable practices of protecting the environment, increasing production efficiency and renovating technology, which thereby enhance organizational effectiveness (porter and van der linde, 1999). based on the (nrbv), berry and rondinelli (1998) emphasized enterprises are progressively constrained by the environmental protection rules, which likely allows enterprises to enhance their environmental performance owing to a decline in environmental expenses as well as a development in organizational reputation. furthermore, chuang and huang (2018) stressed that, the increasing public concern about environmental pollution entails enterprises to concentrate more on the aspects of environmental responsibility, the effect of which on environmental performance is the matter about which the enterprises are concerned. applying practices to solve the problems related to environmental pollution, enterprises could gain advantages from complying environmental rules. these advantages consist of decreased production expenses, lower waste disposal and less usage of energy and resources (koo et al., 2014). the regulations of environmental protection are more and more influential on enterprises with stricter principles, which are closely linked to environmental performance (watson et al., 2010). the effects of environmental friendly managerial tools is likely evaluated at the segments of enterprise and environment such as effectiveness of pollution prevention, environmental benefits of production expense reduction as well as savings of energy and resource (melville, 2010). besides, numerous studies have provided evidence on the causal association from environmental to organizational performance, including the work of seuring and muler (2008) that found out a strong association of environmental with organizational performance. in addition, there are several benefits for the enterprises where environmental responsibility is seriously implemented. these benefits include the efficient use of resources, a decrease in production waste to the surrounding nature environment as well as improvements in the satisfaction of stakeholders, leading to environmental performance (koo et al., 2014). according to qi et al. (2012), iso 14001 is regarded as a managerial practice that enables enterprises to manage environmental effects of their producing process and an initial step for the enterprises to follow positive environmental friendly systems. the adoption of iso 14001 in business may result in an improvement in the technology of environmental protection that likely enhances the effectiveness of environmental pollution treatment, which has been widely recognized as an important driver in augmenting environmental performance (hertin et al., 2008). the implementation of environmentally managerial tools may allow enterprises to build up their active competence of environmental pollution management by delivering the commitment of environmental responsibilities and the participation of workers in environmental huynh: impacts of environmental responsibility and performance on organizational performance: importance of environmental performance international journal of energy economics and policy | vol 10 • issue 6 • 2020 103 protection activities, leading the enterprises to improve continually (arimura et al., 2008). in a study related to environmental responsibility and performance, dilla et al. (2019) mentioned two different perspectives on socially responsible actions. the first perspective is relevant to environmental responsibility, holding that enterprises had better invest more in the technology of environmental and social protection to benefit the relevant community as well as society even if it reduces the profits of shareholders. the shareholders following the first perspective tend to support organizational objectives of improving environmental responsibility instead of increasing shareholder econimic benefits; because they think that environmental performance is an important factor to improve financial effectiveness for a long future period. the second perspective is concerning environmental performance. this viewpoint emphasizes that enterprises had better participate in socially as well as environmentally responsible actions, which can develop firm wealth. in consistence with these standpoints, brooks and oikonomou (2018) also suggested a positive effect of corporate socially responsibility including environmental responsibility on environmental performance, which then increases firm value. shareholders with these perspectives consider enterprises behave in environmentally responsible ways can make more long-term earnings than those who are environmentally irresponsible. furthermore, dilla et al. (2019) indicated that environmental performance is more influential on the evaluation of stakeholders in the enviromental friendly investments with the strong notions on environmental responsibility, and appreciated the important role of environmental responsibility to environmental performance. yusof (2020) tried to link the adoption of green practices in business with environmental performance, in which green practices refer to the systems of developing structures and employing environmental friendly measures. environmental friendly practices are recognized as a vital driver in augmenting organizational reputation, so enjoying confidence from investors as well as customers. the application of these environmental friendly measures is one of the best approaches to deal with the harmful effects of production processes and then enhance environmental performance. based on the abovementioned discussions, it can arrive at the following hypothesis. h2: environmental responsibility is likely a positive determinant of environmental performance. 2.3. effect of environmental performance on organizational performance prior researchers have thought the constructive and sustainable activities taken by enterprises to enhance environmental performance likely augment the contentment in stakeholders, which can lead the enterprises to develop their competitive advantages (stock et al., 1997). a study by bragdon and marlin (1972) asserted that a reduction in environmental pollution and organizational productivity are well matched, the findings of which indicated a positive influence of environmental performance on organizational efficiency. in addition, excellent environmental performance may lead to various advantages for organizations, including efficiency in using input resources, a decrease in production expenditures and an improvement in organizational reputation, so the enterprises can expand their market share (chuang and huang, 2018). the advantages can allow the enterprises to achieve higher firm value and enhance organizational performance. analyzing the resource based view (rbv), russo and fouts (1997) emphasized that the rbv of competitive advantage provides environmental responsibility scholars with an instrument to refine how the environmental policies of an enterprise affect their organizational performance. the effects happen in two ways. firstly, the rbv of competitive advantage strongly focuses on organizational performance as the major output. secondly, it clearly identifies the important role of intangible resources, for example organizational reputation. the rbv of competitive advantage also concentrates on the match between what enterprises have the competence in doing and what they have the chance of doing in order to gain the best potential performance. this theory provides an important prospect to investigate the causal link from environmental to organizational performance. in line with these perspectives, chuang and huang (2018) asserted the usage of environmental friendly practices to improve environmental performance allow enterprises good opportunities and also various advantages, which can improve organizational performance due to a decrease in environmental pollution, risks, and production expenses as well as an increase in outcome quality and business effectiveness. additionally, kao et al. (2010) suggested enterprises employing proactive environmental friendly practices could obtain superior environmental performance and the findings reveal empirical evidence that environmental performance positively affects organizational performance. likewise, khanifah et al. (2020) argued that, enterprises are expecting a positive reaction of investors to their organizational reputation, aimed at drawing them to spend more capital into the enterprises, which can improve organizational performance, bring profits for the investors, and enhance their firm value. instead of trying to avoid the investment in environmental friendly systems; enterprises had better positively react to the governmental rules of environmental pollution as well as actively take part in environmental friendly actions to build up organizational reputation and develop business effectiveness. this can lead the enterprises to obtain organizational objectives in maximizing business competitiveness and performance (ravindra and pradeep, 2012). in addition, angelia and suryaningsih (2015) also investigated the influence of environmental on organizational performance and claimed that, enterprises with higher environment performance could enjoy their stakeholders’ positive feedbacks, which likely increase their customers’ satisfaction and for the long term obtain better benefits. if an enterprise performs good environmental performance, it can develop long-term financial performance. these authors also suggested a positive causal relation from environmental performance to organizational effectiveness, which is because of good image derived from their environmental protection activities. furthermore, cohen et al. (1995) tried to link environmental to financial performance, demonstrating that environmental performance is one of the most imperative driving forces to augment organizational competitiveness. huynh: impacts of environmental responsibility and performance on organizational performance: importance of environmental performance international journal of energy economics and policy | vol 10 • issue 6 • 2020104 drawing on the nrbv, hart and dowell (2011) assented businesses are supposed to concentrate on environmental pollution and consider the causal linkage from environmental to organizational competitiveness. the prevention of pollution is an indicator of the efficient resource usage and the practices employed to reduce and prevent environmental pollution may decrease production expenditures and so obtain higher profits. moreover, surroca et al. (2010) argued that, good perception of stakeholedrs on an enterprise‘s pledge to environmental performance can allow it to draw more high-quality job candidates and retain the workers if they are taken on; so the enterprise will decrease new enrollment as well as training expenses. likewise, environmental performance also affects workers’ attitudes and enables them to contribute more to proposals, which benefit the enterprise, for example making some environmental friendly approaches to the enterprise. the implementation of these environmental friendly practices helps the enterprise to motivate their workers to be involved in environmental protection, thereby improve organizational image as well as reputation and finally gain better competitive advantages. hence, it can suggest the following hypothesis. h3: environmental performance could impose a positive impact on organizational performance. 2.4. role of environmental performance research on environmental responsibility has investigated the feedbacks of enterprises to environmental issues as well as environmental and organizational performance (dias-sardinha and reijnders, 2005). the compliance of enterpeises with environmental friendly rules can lead to competitive advantages and organizational performance (porter and van der linde, 1999); because these rules is exppected to enforce the enterprises to behave towards to environmental sustainaibility. the compliance with environmental protection regulations can cause some expenses for the enterprises; but it may result in a decrease in other costs, which are important in improving environmental performance and other competitive advantages such as improved organizational reputation; whereas environmental performance is widely recognized as one of the most imperative determinants to improve organizational performance (chuang and huang, 2018). furthermore, in a study on environmental responsibility, sáezmartínez et al. (2016) argued that investing more in environmental reponsibility, enterprises could enjoy higher competitiveness, and so allow them to achieve better organizational performance. they also suggested a positive influence of environmental responsibility on organizational performance. as the aforementioned arguments showed, on the one hand, environmental responsibility is a vital driver of organizational efficiency; on the other hand, it affects environmental performance that is in turn a vital determinant of organizational performance, which can therefore result in the following hypotheses of mediation (baron and kenny, 1986). the aforementioned basis could lead to the following hypothesis. h4: environmental performance can mediate the impact of environmental responsibility on organizational performance. 3. measurements 3.1. environmental responsibility according to gunningham (2009), environmental responsibility (eny) refers to the complying level of enterprises to the regulatons of environmental protection. environmental responsibility is reflected in a gradual extent that the enterprises comply with environmental friendly regulations. applying the scale used by sáez-martínez et al. (2016), this research assessed environmental responsibility to a gradual extent which the enterprises advocate environmental protection. a five-point likert scale was employed to measure the variable of environmental responsibility. the scale consists of five items, which are (1) “the enterprise has complexities in complying with the rules of environmental protection,” (2) “the enterprise just complies with the rules of environmental protection,” (3) “the enterprise complies and contemplates to do more with the rules of environmental protection,” (4) “the enterprise goes beyond conformity in spite of being short of of pro-environmental thoughts from the entrepreneur,” and (5) “the enterprise goes beyond conformity and regard environmental issues as a priority.” 3.2. environmental performance drawing on latan et al. (2018) and chuang and huang (2018), in the current research, environmental performance (enr) was measured with eight dimensions, there has been no common consensus on the instrument of environmental performance and various differences among prior studies (latan et al., 2018). hence, this research combined several characteristics of environmental performance to get better dimensions, which are “uncovering expense cutting opportunities,” “preventing and mitigating environmental crises,” “reducing pollution and production expenses,” “limiting environmental impacts beyond,” “improving reputation,” “generating societal benefits,” “improving relations with local community” and “increasing competitive advantages.” these dimensions focus on compliance with current environmental protection set of laws, environment related effects and advantages relating to environmental friendly activities. the dimensions were evaluated with a five-point likert scale (completely disagreement through completely agreement). 3.3. organizational performance anchored in delaney and huselid (1996), this research measured organizational performance (orr) using eleven dimensions, which are comparative. these dimensions were generated by requesting informers to evaluate organizational performance compared with the average performance of the industry. the dimensions are “quality of products/services,” “competence for drawing needed workers,” “development in new products/services,” “competence for maintaining needed workers,” “pleasure of customers,” “association between superiors and subordinates,” “association among workers,” “marketing,” and “improvement in sales,” “profitability” and “market sales.” the data collected on the perception of informants could suffer some confines caused by possible monomethod bias, but it is not extraordinary to employ those dimensions. the eleven dimensions were generated by evaluating informants’ perceptions on the organizational performance of their enterprises in comparison with other enterprises during the last 3 years. the dimensions were computed with a five-point likert scale (completely disagreement through completely agreement). 3.4. control variables the current study controlled for organizational risk ork, organizational leverage ole, organizational size ose, and huynh: impacts of environmental responsibility and performance on organizational performance: importance of environmental performance international journal of energy economics and policy | vol 10 • issue 6 • 2020 105 industry type ine with the dependent variables of environmental and organizational performance in the research model. according to surroca et al. (2010), organizational risk, organizational leverage, organizational size, and industry type were driving forces of social (including environmental) and organizational performance. this research drew on the work of martínez-ferrero (2014) to measure the controlling variables of organizational risk, organizational leverage, and organizational size. ork was assessed on the beta of the market model. ole was evaluated on the debt to equity ratio. ose was calculated on the natural logarithm of the equity market value. additionally, the controlling variable of industry type was adapted from huynh (2017). ine is computed by employing a three-point scale from manufacturing (1), manufacturing-service (2) and service (3). 4. data collection the data was collected from publicly listed enterprises in vietnam. this research decided on vietnam as a case study, because it is a fast developing economy. issues related to environmental deterioration have been on the increase there. therefore, environmental sustainability in vietnam, which has been underemphasized (nguyen, 2014), is needed to be comprehensively analyzed to help the government make suitable appropriate environmental friendly policies for vietnamese enterprises to be more environmentally sustainable and then more economically sustainable. the questionnaire employed to gather the data was preliminarily evaluated with 20 managers involved in environmental issues (bowden et al., 2002). the research sample compassed publicly listed enterprises in the chief stock exchanges of vietnam. there were three big stock exchanges in vietnam, which were ho chi minh stock exchange, unlisted public company market and hanoi stock exchange. simple random sampling was employed to select 500 out of the 1753 enterprises that were still beeing operated at the research time. the 600 questionnaires were distributed out, but only 399 suitable replies were collected, satisfying the sample size for this research (hair et al., 2011). the survey technique was applied by asking each environmental manager for every chosen enterprise to complete the research questionnaire. 5. instrumental reliability and validity for the multidimensional variables, it is needed to assess internal stability among dimensions within their main variable to ensure the reliability of constructs. this research employed the procedures of cronbach alpha (α) suggested by landis and koch (1977) and hair et al. (2011). the coefficient of α is a measure of internal constancy, indicating how strictly connected a set of dimensions are to their own cluster. there are two multidimensional variables in this study, which are environmental performance and organizational performance; so they were entered into the procedures of cronbach alpha. the results are exhibited in table 1. the αs of two main variables range from 0.8 to 0.9 values, allowing the internal consistency of environmental performance and organizational performance to be very good. the total correlations are all >0.5 threshold. furthermore, the αs if the dimension is removed are all lower than their total αs, which are 0.893–0.895. the aforementioned results show the nineteen dimensions are all consistent with their main constructs, indicating the measured dimensions get the reliability of their own constructs. in addition to the reliability of constructs, to judge the validity of the measurement model of multidimensional variables, the current research work applied the procedures of factor analysis as hair et al. (2011) suggested. it needs exploring the goodness of fit and the validity of the constructs, which is the degree to that a set of observed dimensions really reflect their main unobserved variable they are assigned to proxy for. the findings are presented in table 2. as shown in table 2, the measure of sampling adequacy (kmo) obtains the 0.921 value, over than the acceptable 0.7 threshold and the chi-squared gets the 4008.144 level with the significance of 0.01, demonstrating the measurement model of environmental and organizational performance achieves the goodness of fit. regarding the validity of the constructs, this research examined the validity of convergence and divergence. convergent validity is the degree to which the standards of a specific variable share a high amount of variation in general. the construct was validated with convergence, in which their construct loadings and average variance extracted coefficients (ave) had better be over the 0.5 level. at the same time, construct reliabilities (cr) should exceed the 0.7 value. as the figures in table 2 indicate, the loadings and aves all surpass the 0.5 value. in addition, crs obtain the values >0.7 threshold. therefore, it can recommend all the measured dimensions are convergent within their representative variables. discriminant (divergent) validity is the degree to that a variable is actually different from other variables. the measurement model is considered to be discriminant, when the cross-loadings should be >0.3 threshold, and simultaneously aves should be over and above the squares of corresponding interconstruct correlation (sic). the findings show that, all the cross-loadings exceed the 0.3 value, demonstrating the discriminant validity of the construcs. additionally, the sic of 0.1918 is not greater than the aves of table 1: reliability of instruments factor dimension total correlation α if dimension is excluded α enr enr1 0.599 0.886 0.893 enr2 0.614 0.884 enr3 0.747 0.872 enr4 0.716 0.875 enr5 0.645 0.882 enr6 0.716 0.875 enr7 0.629 0.884 enr8 0.698 0.877 orr orr1 0.656 0.908 0.895 orr2 0.687 0.907 orr3 0.646 0.908 orr4 0.698 0.906 orr5 0.655 0.908 orr6 0.661 0.908 orr7 0.688 0.906 orr8 0.660 0.908 orr9 0.665 0.908 orr10 0.655 0.908 orr11 0.704 0.906 huynh: impacts of environmental responsibility and performance on organizational performance: importance of environmental performance international journal of energy economics and policy | vol 10 • issue 6 • 2020106 table 2: validity of instruments factor dimension loading cr ave sic enr enr1 0.657 0.9067 0.5496 enr2 0.666 enr3 0.793 enr4 0.768 enr5 0.743 enr6 0.796 enr7 0.721 enr8 0.773 0.1918 orr orr1 0.691 0.9222 0.5189 orr2 0.740 orr3 0.703 orr4 0.745 orr5 0.710 orr6 0.723 orr7 0.733 orr8 0.701 orr9 0.729 orr10 0.707 orr11 0.739 kmo 0.921 chi-squared 4008.144 p value 0.000 table 3: multiple regression analyses to test causal hypotheses model 1 2 3 variable orr enr orr β se vif β se vif β se vif (c) 1.480 0.219 1.752 0.317 1.354 0.227 ork 0.023 0.040 1.039 −0.020 0.058 1.039 0.025 0.040 1.039 ole 0.001 0.003 1.004 −0.003 0.004 1.004 0.001 0.003 1.006 ose 0.012 0.011 1.113 0.007 0.016 1.113 0.011 0.011 1.114 ine 0.846** 0.032 1.412 0.196** 0.046 1.412 0.832** 0.033 1.476 eny 0.075* 0.037 1.393 0.319** 0.054 1.393 0.052 0.039 1.518 enr 0.072* 0.035 1.294 durbin-watson 1.848 1.741 1.854 χ2/pχ2 0.521/.789 0.934/.297 0.612/0.398 r2 0.735 0.327 0.738 f/pf 218/0.000 23/0.000 184/0.000 *,**significance at the 0.05, 0.01 levels 0.5496 and 0.5189, pointing out the observed dimensions are more in common with their own variables they are related to than they do with the other variables. generally, the measurement model achieves sufficient convergence and divergence. 6. empirical results 6.1. assessment of causal links to evaluate the causal effects in the research model, this research applied multiple analyses of regression to estimate models from 1 to 3, generating the outcomes in table 3. the current study is based on the indicators stipulated by hair et al. (2011) to assess the research model. as can be seen in table 3, all the three models obtain the goodness of fit. the values of f range from 23 to 218 at the 0.01 significance level. moreover, the coefficients of the explained variance (r2) get the values from 0.327 to 0.738, indicating the amounts of variance explained by indendent variables are from 32.7% to 73.8%. the coefficients of durbin-watson take the values of 1.848, 1.741 and 1.854, belonging to their interval between du and (4 – du); which reveal no autocorrelation. additionally, the coefficients of χ2 from the breusch–pagan test gain the values of 0.521, 0.934 and 0.612 with the estimates of pχ2 equal to 0.789, 0.297 and 0.398, which all exceed the 0.05 significance level, so indicating no heteroskedasticity. furthermore, the estimators of vif all obtain the values <2 level, showing no multicollinearity. in model 1, the regression of organizational performance on environmental responsibility was estimated. as model 1 indicates, only ine of the four controlling variables is statistically related to organizational performance with the 0.01 significance level. environmental responsibility positively affects organizational performance with the 0.05 significance level and the 0.075 coefficient of β. therefore, the results offer support for hypothesis 1. model 2 regressed environmental performance on environmental responsibility. similarly, to model 1, only ine positively influences environmental performance with the 0.01 significance level. environmental responsibility imposes a positive impact on environmental performance with the 0.01 significance level and the 0.319 coefficient of β, which is in support of hypothesis 2. in model 3, organizational performance was regressed on both environmental responsibility and environmental performance. likewise, only ine imposes a positive influence on organizational performance with the 0.01 significance level. environmental performance is a positive determinant of organizational performance with the 0.05 significance level and the 0.072 coefficient of β. these findings provide support for hypothesis 3. 6.2. assessment of mediation in contrast, environmental responsibility in model 3 has no effect on organizational performance; and furthermore its coefficient of β decreases from 0.075 down to 0.052, which can suggest a mediation of environmental performance in the causal link from environmental responsibility to organizational performance. for the robustness of mediating influence, this research employed the procedures as goodman (1960) recommended for testing the statistical significance for the mediation of environmental performance between environmental responsibility and organizational performance. the outcomes are presented in table 4, which indicates that, the mediation of environmental performance in the causal link from environmental responsibility to organizational performance is statistically significant with the 0.05 level, and tindirect of 1.968, in supportof hypothesis 4. these findings suggest that, if being entered into the research model of organizational performance huynh: impacts of environmental responsibility and performance on organizational performance: importance of environmental performance international journal of energy economics and policy | vol 10 • issue 6 • 2020 107 and environmental responsibility, environmental performance entirely transmits the causal impact of environmental responsibility on organizational performance. in the joint research model, environmental responsibility has no direct effect of organizational performance, but has indirect impact on organizational performance through the transmission of environmental performance. 7. discussion and conclusions social and economic growth probably causes several hazards to the nature environment. the relationship between the social and economic development of a country and the nature environment are manifold. the environment is both a place to supply natural resources to enterprises and also a sink to contain waste discharged from the enterprises. therefore, the enterprises should pay more attention to the nature environment, because reduced environmental quality will have negative effects on business development. this research attempted to explore the extent of responsibility enterprises take to the nature environment. in particalar, it investigated the links among environmental responsibility, environmental performance and organizational performance in vietnam‘s context as a fastgrowing emerging country. the empirical findings reveal empirical evidence on a positive influence of environmental responsibility on organizational performance. this research simultaneously finds out that environmental responsibility is also a vital positve determinant of environmental performance that in turn augments organizational performance for the enterprises. especially, it comprehensively analyzed the imperative role that environmental performance plays to the research model. the results statistically confirm the mediation of environmental performance interfering in environmental responsibility and organizational performance, in which environmental performance fully transmits the impact of environmental responsibility on organizational performance. when entered into the research model, environmental performance will make environmental responsibility have no direct influence on organizational performance. the findings may be useful for executive officers in businesses as well as researchers by providing them with a deeper understanding of the complex relationships of environmental responsibility and performance with organizational performance, in which environmental performance is highlighted as a vital mediator. hence, they can offer better and deepper analyses on the correlation among factors relevant to environmental issues. the results could allow business managers in vietnam in particular and in other developing countries in general, to make suitable decisions on the extent of environmental responsibility their enterprises should take in order to improve environmental performance and then gain better organizational performance. the empirical results were produced from vietnam‘s context, and they are expected to apply for other similar developing countries. nevertheless, operating conditions can be different among developing economies. therefore, they should apply the findings of this study to their businesses with care. 8. acknowledgment i would like to thank tra vinh university for financially supporting to conduct this research (as articulated in contract no 201/ hđ.hđkh-đhtv) and i am also grateful to the respondents for their help in gathering the research data. references angelia, d., suryaningsih, r. (2015), the effect of environmental performance and corporate social responsibility disclosure towards financial performance (case study to manufacture, infrastructure, and service companies that listed at indonesia stock exchange). procedia-social and behavioral sciences, 211, 348-355. baron, r.m., kenny, d.a. (1986), the moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. journal of personality and social psychology, 51(6), 1173-1182. berry, m.a., rondinelli, d.a. (1998), proactive corporate environmental management: a new industrial revolution. academy of management executive, 12(2), 38-50. bowden, a., fox-rushby j.a., nyandieka l., wanjau j. (2002), methods for pre-testing and piloting survey questions: llustrations from the kenqol survey of health-related quality of life. health policy and planning, 17(3), 322-330. bragdon, j.h., marlin, j. (1972), is pollution profitable. risk management, 19(4), 9-18. brooks, c., oikonomou, i. (2018), the effects of environmental, social and governance disclosures and performance on firm value: a review of the literature in accounting and finance, the british accounting review, 50(1), 1-15. cai, l., he, c. (2014), corporate environmental responsibility and equity prices. journal of business ethics, 125(4), 617-635. chuang, s.p., huang, s.j. (2018), the effect of environmental corporate social responsibility on environmental performance and business competitiveness: the mediation of green information technology capital. journal of business ethics, 150(4), 991-1009. cohen, m.a., fenn, s., naimon, j.s. (1995), environmental and financial performance: are they related? washington, dc: investor responsibility research center, environmental information service, usa. delaney, j.t., huselid, m.a. (1996), the impact of human resource management practices on perceptions of organizational performance. academy of management journal, 39(4), 949-969. dias-sardinha, i., reijnders, l. (2005), evaluating environmental and social performance of large portuguese companies: a balanced scorecard approach. business strategy and the environment, 14(2), 73-91. dilla, w., janvrin, d., perkins, j., raschke, r. (2019), do environmental responsibility views influence investors’ use of environmental performance and assurance information? sustainability accounting, management and policy journal, 10(3), 476-497. elkington, j., rowlands, i.h. (1999), cannibals with forks: the triple bottom line of 21st century business. alternatives journal, 25(4), 42-43. goodman, l.a. (1960), on the exact variance of products. journal of the american statistical association, 55(292), 708-713. guenster, n., bauer, r., derwall, j., koedijk, k. (2011), the economic value of corporate eco-efficiency. european financial management, 17(4), 679-704. gunningham, n. (2009), corporate environmental responsibility. ashgate, uk: hampshire. table 4: mediation analyses cause mediator effect tindirect se pt eny enr orr 1.968 0.011 0.049 huynh: impacts of environmental responsibility and performance on organizational performance: importance of environmental performance international journal of energy economics and policy | vol 10 • issue 6 • 2020108 hair, j.f., black, w.c., babin, b.j, anderson, r.e., tatham, r.l. (2011), multivariate data analysis. new jersey, usa: prentice hall. hart, s., ahuja, g. (1996), does it pay to be green? an empirical examination of the relationship between emission reduction and firm performance. business strategy and the environment, 5(1), 30-37. hart, s.l., dowell, g. (2011), a natural-resource-based view of the firm: fifteen years after. journal of management, 37(5), 1464-1479. hertin, j., berkhout, f., wagner, m., tyteca, d. (2008), are ems environmentally effective? the link between environmental management systems and environmental performance in european companies. journal of environmental planning and management, 51(2), 259-283. holtbrügge, d., dögl, c. (2012), how international is corporate environmental responsibility? a literature review. journal of international management, 18(2), 180-195. hutchinson, c. (1992), corporate strategy and the environment. long range planning, 25(4), 9-21. huynh, q.l. (2017), corporate governance on the corporate characteristics managerial accounting link. american journal of applied sciences, 14(5), 560-568. jo, h., kim, h., park, k. (2015), corporate environmental responsibility and firm performance in the financial services sector. journal of business ethics, 131(2), 257-284. kao, m.r., liu, c.y., huang, y.c., chang, n.j. (2010), a research of the relationship among business green management, environmental performance and competitive advantage. journal of management and systems, 17(2), 255-278. karagozoglu, n., lindell, m. (2000), environmental management: testing the win win model. journal of environmental planning and management, 43(6), 817-829. khanifah, k., udin, u., hadi, n., alfiana, f. (2020), environmental performance and firm value: testing the role of firm reputation in emerging countries. international journal of energy economics and policy, 10(1), 96-103. kim, y., statman, m. (2012), do corporations invest enough in environment responsibility? journal of business ethics, 105(1), 115-129. konar, s., cohen, m. (2001), does the market value environmental performance? review of economics and statistics, 83(2), 281-289. koo, c., chung, n., ryoo, s.y. (2014), how does ecological responsibility affect manufacturing firms’ environmental and economic performance? total quality management and business excellence, 25(9-10), 1171-1189. landis, j.r., koch, g.g. (1977), the measurement of observer agreement for categorical data. biometrics, 33(1), 159-174. latan, h., jabbour, c.j.c., de sousa jabbour, a.b.l., wamba, s.f., shahbaz, m. (2018), effects of environmental strategy, environmental uncertainty and top management’s commitment on corporate environmental performance: the role of environmental management accounting. journal of cleaner production, 180, 297-306. le, y., hollenhorst, s., harris, c., mclaughlin, w., shook, s. (2006), environmental management: a study of vietnamese hotels. annals of tourism research, 33(2), 545-567. lee, k.h., cin, b.c., lee, e.y. (2016), environmental responsibility and firm performance: the application of an environmental, social and governance model. business strategy and the environment, 25(1), 40-53. li, d., cao, c., zhang, l., chen, x., ren, s., zhao, y. (2017), effects of corporate environmental responsibility on financial performance: the moderating role of government regulation and organizational slack. journal of cleaner production, 166, 1323-1334. martínez-ferrero, j. (2014), consequences of financial reporting quality on corporate performance: evidence at the international level. estudios de economía, 41(1), 49-88. melville, n.p. (2010), information systems innovation for environmental sustainability. mis quarterly, 34(1), 1-21. miles, m.p., covin, j. (2000), environmental marketing: a source of reputational, competitive, and financial advantage. journal of business ethics, 23(3), 299-311. nehrt, c. (1996), timing and intensity effects of environmental investments. strategic management journal, 17(7), 535-547. nguyen, h.n. (2014), policies for environmentally sustainable development: perspectives from vietnam. in: environmental policies in asia: perspectives from seven asian countries. world scientific publishing: singapore. p57-72. palmer, k., oates, w., portney, p. (1995), tightening environmental standards: the benefits cost or no-cost paradigm? journal of economic perspectives, 9(4), 119-132. porter, m. (1998), the competitive advantage of nations. new york, usa: free press. porter, m.e., van der linde, c. (1999), green and competitive: ending the stalemate. journal of business administration and policy analysis, 73, 215-229. qi, g., zeng, s., li, x., tam, c. (2012), role of internalization process in defining the relationship between iso 14001 certification and corporate environmental performance. corporate social responsibility and environmental management, 19(3), 129-140. ravindra, p.s., pradeep, k.k. (2012), greening of industries for sustainable growth: an exploratory study on durable, nondurable and services industries. international journal of social economics, 39(8), 551-586. russo, m.v., fouts, p.a. (1997), a resource-based perspective on corporate environmental performance and profitability. academy of management journal, 40(3), 534-559. sáez-martínez, f.j., díaz-garcía, c., gonzález-moreno, á. (2016), factors promoting environmental responsibility in european smes: the effect on performance. sustainability, 8(9), 898. seuring, s., muler, m. (2008), from a literature review to a conceptual framework for sustainable supply chain management. journal of cleaner production, 16(15), 1699-1710. sharma, a., iyer, g., mehrotra, a., krishnan, r. (2010), sustainability and business-to-business marketing: a framework and implications. industrial marketing management, 39(2), 330-341. stock, g.g., hanna, j.l., edwards, m.h. (1997), implementing an environmental business strategy: a step-by-step guide. environmental quality management, 6(4), 33-41. surroca, j., tribó, j.a., waddock, s. (2010), corporate responsibility and financial performance: the role of intangible resources. strategic management journal, 31(5), 463-490. verrecchia, r.e. (1983), discretionary disclosure. journal of accounting and economics, 5(3), 179-194. watson, r.t., boudreau, m.c., chen, a.j. (2010), information systems and environmentally sustainable development: energy informatics and new directions for the is community. mis quarterly, 34(1), 23-38. wong, c.w., miao, x., cui, s., tang, y. (2018), impact of corporate environmental responsibility on operating income: moderating role of regional disparities in china. journal of business ethics, 149(2), 363-382. world bank. (2012), the world bank annual report 2012. washington dc, usa: the world bank. xu, x.d., zeng, s.x., zou, h.l., shi, j.j. (2016), the impact of corporate environmental violation on shareholders’ wealth: a perspective taken from media coverage. business strategy and the environment, 25(2), 73-91. yusof, n.a. (2020), do environmental, economic and reputational advantages strengthen green practices’ impact on environmental performance? corporate social responsibility and environmental management, 1, 1-13.